diff --git "a/CVCliniDB/logs/EAT_CVCliniDB_log.txt" "b/CVCliniDB/logs/EAT_CVCliniDB_log.txt" new file mode 100644--- /dev/null +++ "b/CVCliniDB/logs/EAT_CVCliniDB_log.txt" @@ -0,0 +1,96214 @@ +, + 'EDD_seg': , + 'Kvasir_SEG': + >, + 'finetune': , + 'models': , + 'branch5': + >, + 'cfp_net': , + 'branch5': + >, + 'cvc_unetr': , + 'branch5': + >, + 'EAT': , + 'branch5': + >, + 'duat': , + 'branch5': + >, + 'swin_unetr': , + 'branch5': + >, + 'trans_unet': , + 'branch5': + >, + 'u_netr': , + 'branch5': + >, + 'unet': , + 'branch5': + > + >, + 'shared path': '/root/.cache/huggingface/forget/model_stores/', + 'trainer': , + 'visualization': +> +Load Model... +Load Dataloader... +Error(s) in loading state_dict for EAT: + Missing key(s) in state_dict: "block2.gobel_attention.conv.offset_mask_dw.weight", "block2.gobel_attention.conv.offset_mask_dw.bias", "block2.gobel_attention.conv.offset_mask.weight", "block2.gobel_attention.conv.offset_mask.bias", "block2.gobel_attention.conv.value_proj.weight", "block2.gobel_attention.conv.value_proj.bias", "block2.gobel_attention.conv.output_proj.weight", "block2.gobel_attention.conv.output_proj.bias", "block3.gobel_attention.conv.offset_mask_dw.weight", "block3.gobel_attention.conv.offset_mask_dw.bias", "block3.gobel_attention.conv.offset_mask.weight", "block3.gobel_attention.conv.offset_mask.bias", "block3.gobel_attention.conv.value_proj.weight", "block3.gobel_attention.conv.value_proj.bias", "block3.gobel_attention.conv.output_proj.weight", "block3.gobel_attention.conv.output_proj.bias", "block4.gobel_attention.conv.offset_mask_dw.weight", "block4.gobel_attention.conv.offset_mask_dw.bias", "block4.gobel_attention.conv.offset_mask.weight", "block4.gobel_attention.conv.offset_mask.bias", "block4.gobel_attention.conv.value_proj.weight", "block4.gobel_attention.conv.value_proj.bias", "block4.gobel_attention.conv.output_proj.weight", "block4.gobel_attention.conv.output_proj.bias". + Unexpected key(s) in state_dict: "block2.gobel_attention.conv.weight", "block2.gobel_attention.conv.bias", "block3.gobel_attention.conv.weight", "block3.gobel_attention.conv.bias", "block4.gobel_attention.conv.weight", "block4.gobel_attention.conv.bias". +Failed to load the training model！ +loaded state dict contains a parameter group that doesn't match the size of optimizer's group +Failed to load training state！ +Start Training！ +Epoch [1/4000] Training [1/16] Loss: 5.60037 +Epoch [1/4000] Training [2/16] Loss: 4.07847 +Epoch [1/4000] Training [3/16] Loss: 5.50653 +Epoch [1/4000] Training [4/16] Loss: 6.28106 +Epoch [1/4000] Training [5/16] Loss: 4.68223 +Epoch [1/4000] Training [6/16] Loss: 3.71170 +Epoch [1/4000] Training [7/16] Loss: 7.19312 +Epoch [1/4000] Training [8/16] Loss: 6.01628 +Epoch [1/4000] Training [9/16] Loss: 4.26157 +Epoch [1/4000] Training [10/16] Loss: 5.52722 +Epoch [1/4000] Training [11/16] Loss: 4.47334 +Epoch [1/4000] Training [12/16] Loss: 4.91074 +Epoch [1/4000] Training [13/16] Loss: 4.76564 +Epoch [1/4000] Training [14/16] Loss: 4.68250 +Epoch [1/4000] Training [15/16] Loss: 4.73443 +Epoch [1/4000] Training [16/16] Loss: 5.26372 +Epoch [1/4000] Training metric {'Train/mean dice_metric': 0.12540987133979797, 'Train/mean miou_metric': 0.06860561668872833, 'Train/mean f1': 0.10864735394716263, 'Train/mean precision': 0.2119446098804474, 'Train/mean recall': 0.07304619997739792, 'Train/mean hd95_metric': 215.78343200683594} +Epoch [1/4000] Validation [1/4] Loss: 5.34658 focal_loss 4.40999 dice_loss 0.93659 +Epoch [1/4000] Validation [2/4] Loss: 3.54831 focal_loss 2.61384 dice_loss 0.93447 +Epoch [1/4000] Validation [3/4] Loss: 4.47640 focal_loss 3.52092 dice_loss 0.95548 +Epoch [1/4000] Validation [4/4] Loss: 4.00609 focal_loss 3.08703 dice_loss 0.91906 +Epoch [1/4000] Validation metric {'Val/mean dice_metric': 0.11447805166244507, 'Val/mean miou_metric': 0.06265262514352798, 'Val/mean f1': 0.09946098178625107, 'Val/mean precision': 0.21222181618213654, 'Val/mean recall': 0.06495051831007004, 'Val/mean hd95_metric': 216.77944946289062} +Cheakpoint... +Epoch [1/4000] best acc:tensor([0.1145], device='cuda:0'), Now : mean acc: tensor([0.1145], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.11447805166244507, 'Val/mean miou_metric': 0.06265262514352798, 'Val/mean f1': 0.09946098178625107, 'Val/mean precision': 0.21222181618213654, 'Val/mean recall': 0.06495051831007004, 'Val/mean hd95_metric': 216.77944946289062} +Epoch [2/4000] Training [1/16] Loss: 6.24032 +Epoch [2/4000] Training [2/16] Loss: 3.66516 +Epoch [2/4000] Training [3/16] Loss: 3.27508 +Epoch [2/4000] Training [4/16] Loss: 5.00918 +Epoch [2/4000] Training [5/16] Loss: 4.65941 +Epoch [2/4000] Training [6/16] Loss: 4.77338 +Epoch [2/4000] Training [7/16] Loss: 6.46762 +Epoch [2/4000] Training [8/16] Loss: 6.81259 +Epoch [2/4000] Training [9/16] Loss: 4.95989 +Epoch [2/4000] Training [10/16] Loss: 4.45028 +Epoch [2/4000] Training [11/16] Loss: 4.56167 +Epoch [2/4000] Training [12/16] Loss: 6.95026 +Epoch [2/4000] Training [13/16] Loss: 5.47030 +Epoch [2/4000] Training [14/16] Loss: 4.20463 +Epoch [2/4000] Training [15/16] Loss: 8.14413 +Epoch [2/4000] Training [16/16] Loss: 5.58693 +Epoch [2/4000] Training metric {'Train/mean dice_metric': 0.1294306218624115, 'Train/mean miou_metric': 0.07094092667102814, 'Train/mean f1': 0.1122884601354599, 'Train/mean precision': 0.22049754858016968, 'Train/mean recall': 0.07532349228858948, 'Train/mean hd95_metric': 216.53976440429688} +Epoch [2/4000] Validation [1/4] Loss: 6.15790 focal_loss 5.23292 dice_loss 0.92497 +Epoch [2/4000] Validation [2/4] Loss: 3.99992 focal_loss 3.07456 dice_loss 0.92537 +Epoch [2/4000] Validation [3/4] Loss: 5.06593 focal_loss 4.11012 dice_loss 0.95581 +Epoch [2/4000] Validation [4/4] Loss: 4.77577 focal_loss 3.86500 dice_loss 0.91077 +Epoch [2/4000] Validation metric {'Val/mean dice_metric': 0.11832375824451447, 'Val/mean miou_metric': 0.06471320241689682, 'Val/mean f1': 0.10356968641281128, 'Val/mean precision': 0.20722389221191406, 'Val/mean recall': 0.0690370723605156, 'Val/mean hd95_metric': 217.2207794189453} +Cheakpoint... +Epoch [2/4000] best acc:tensor([0.1183], device='cuda:0'), Now : mean acc: tensor([0.1183], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.11832375824451447, 'Val/mean miou_metric': 0.06471320241689682, 'Val/mean f1': 0.10356968641281128, 'Val/mean precision': 0.20722389221191406, 'Val/mean recall': 0.0690370723605156, 'Val/mean hd95_metric': 217.2207794189453} +Epoch [3/4000] Training [1/16] Loss: 5.48932 +Epoch [3/4000] Training [2/16] Loss: 1.48673 +Epoch [3/4000] Training [3/16] Loss: 1.01090 +Epoch [3/4000] Training [4/16] Loss: 0.91053 +Epoch [3/4000] Training [5/16] Loss: 0.82725 +Epoch [3/4000] Training [6/16] Loss: 1.31688 +Epoch [3/4000] Training [7/16] Loss: 0.46296 +Epoch [3/4000] Training [8/16] Loss: 0.56277 +Epoch [3/4000] Training [9/16] Loss: 0.51244 +Epoch [3/4000] Training [10/16] Loss: 0.44292 +Epoch [3/4000] Training [11/16] Loss: 0.38368 +Epoch [3/4000] Training [12/16] Loss: 0.32926 +Epoch [3/4000] Training [13/16] Loss: 0.20975 +Epoch [3/4000] Training [14/16] Loss: 0.24532 +Epoch [3/4000] Training [15/16] Loss: 0.25416 +Epoch [3/4000] Training [16/16] Loss: 0.13585 +Epoch [3/4000] Training metric {'Train/mean dice_metric': 0.7106027603149414, 'Train/mean miou_metric': 0.593795895576477, 'Train/mean f1': 0.7356796860694885, 'Train/mean precision': 0.7511997222900391, 'Train/mean recall': 0.7207880020141602, 'Train/mean hd95_metric': 137.33738708496094} +Epoch [3/4000] Validation [1/4] Loss: 1.11163 focal_loss 0.90069 dice_loss 0.21093 +Epoch [3/4000] Validation [2/4] Loss: 0.40806 focal_loss 0.22887 dice_loss 0.17919 +Epoch [3/4000] Validation [3/4] Loss: 0.68692 focal_loss 0.49395 dice_loss 0.19297 +Epoch [3/4000] Validation [4/4] Loss: 0.42946 focal_loss 0.28751 dice_loss 0.14195 +Epoch [3/4000] Validation metric {'Val/mean dice_metric': 0.727217435836792, 'Val/mean miou_metric': 0.6152305006980896, 'Val/mean f1': 0.749343752861023, 'Val/mean precision': 0.7746066451072693, 'Val/mean recall': 0.7256766557693481, 'Val/mean hd95_metric': 128.62950134277344} +Cheakpoint... +Epoch [3/4000] best acc:tensor([0.7272], device='cuda:0'), Now : mean acc: tensor([0.7272], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.727217435836792, 'Val/mean miou_metric': 0.6152305006980896, 'Val/mean f1': 0.749343752861023, 'Val/mean precision': 0.7746066451072693, 'Val/mean recall': 0.7256766557693481, 'Val/mean hd95_metric': 128.62950134277344} +Epoch [4/4000] Training [1/16] Loss: 0.19832 +Epoch [4/4000] Training [2/16] Loss: 0.20403 +Epoch [4/4000] Training [3/16] Loss: 0.11370 +Epoch [4/4000] Training [4/16] Loss: 0.10032 +Epoch [4/4000] Training [5/16] Loss: 0.10407 +Epoch [4/4000] Training [6/16] Loss: 0.23225 +Epoch [4/4000] Training [7/16] Loss: 0.17504 +Epoch [4/4000] Training [8/16] Loss: 0.10554 +Epoch [4/4000] Training [9/16] Loss: 0.12104 +Epoch [4/4000] Training [10/16] Loss: 0.08426 +Epoch [4/4000] Training [11/16] Loss: 0.14271 +Epoch [4/4000] Training [12/16] Loss: 0.25529 +Epoch [4/4000] Training [13/16] Loss: 0.10628 +Epoch [4/4000] Training [14/16] Loss: 0.08275 +Epoch [4/4000] Training [15/16] Loss: 0.10196 +Epoch [4/4000] Training [16/16] Loss: 0.08044 +Epoch [4/4000] Training metric {'Train/mean dice_metric': 0.9207900166511536, 'Train/mean miou_metric': 0.8613883852958679, 'Train/mean f1': 0.9142983555793762, 'Train/mean precision': 0.9043478965759277, 'Train/mean recall': 0.9244701266288757, 'Train/mean hd95_metric': 54.60027313232422} +Epoch [4/4000] Validation [1/4] Loss: 0.77657 focal_loss 0.55068 dice_loss 0.22590 +Epoch [4/4000] Validation [2/4] Loss: 0.54457 focal_loss 0.31463 dice_loss 0.22994 +Epoch [4/4000] Validation [3/4] Loss: 0.43539 focal_loss 0.27353 dice_loss 0.16186 +Epoch [4/4000] Validation [4/4] Loss: 0.62942 focal_loss 0.42443 dice_loss 0.20499 +Epoch [4/4000] Validation metric {'Val/mean dice_metric': 0.8949548602104187, 'Val/mean miou_metric': 0.8283882141113281, 'Val/mean f1': 0.8932330012321472, 'Val/mean precision': 0.9049943089485168, 'Val/mean recall': 0.8817734122276306, 'Val/mean hd95_metric': 53.518951416015625} +Cheakpoint... +Epoch [4/4000] best acc:tensor([0.8950], device='cuda:0'), Now : mean acc: tensor([0.8950], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.8949548602104187, 'Val/mean miou_metric': 0.8283882141113281, 'Val/mean f1': 0.8932330012321472, 'Val/mean precision': 0.9049943089485168, 'Val/mean recall': 0.8817734122276306, 'Val/mean hd95_metric': 53.518951416015625} +Epoch [5/4000] Training [1/16] Loss: 0.07309 +Epoch [5/4000] Training [2/16] Loss: 0.15782 +Epoch [5/4000] Training [3/16] Loss: 0.25410 +Epoch [5/4000] Training [4/16] Loss: 0.09123 +Epoch [5/4000] Training [5/16] Loss: 0.12284 +Epoch [5/4000] Training [6/16] Loss: 0.09129 +Epoch [5/4000] Training [7/16] Loss: 0.23012 +Epoch [5/4000] Training [8/16] Loss: 0.05308 +Epoch [5/4000] Training [9/16] Loss: 0.07348 +Epoch [5/4000] Training [10/16] Loss: 0.11852 +Epoch [5/4000] Training [11/16] Loss: 0.08661 +Epoch [5/4000] Training [12/16] Loss: 0.23616 +Epoch [5/4000] Training [13/16] Loss: 0.05354 +Epoch [5/4000] Training [14/16] Loss: 0.06737 +Epoch [5/4000] Training [15/16] Loss: 0.10652 +Epoch [5/4000] Training [16/16] Loss: 0.07373 +Epoch [5/4000] Training metric {'Train/mean dice_metric': 0.9392322301864624, 'Train/mean miou_metric': 0.8916541337966919, 'Train/mean f1': 0.9340856075286865, 'Train/mean precision': 0.9332165122032166, 'Train/mean recall': 0.9349562525749207, 'Train/mean hd95_metric': 23.89736557006836} +Epoch [5/4000] Validation [1/4] Loss: 0.26945 focal_loss 0.16348 dice_loss 0.10598 +Epoch [5/4000] Validation [2/4] Loss: 0.43383 focal_loss 0.18762 dice_loss 0.24621 +Epoch [5/4000] Validation [3/4] Loss: 0.27823 focal_loss 0.14436 dice_loss 0.13387 +Epoch [5/4000] Validation [4/4] Loss: 0.28861 focal_loss 0.14341 dice_loss 0.14520 +Epoch [5/4000] Validation metric {'Val/mean dice_metric': 0.9178253412246704, 'Val/mean miou_metric': 0.8629156351089478, 'Val/mean f1': 0.9170584082603455, 'Val/mean precision': 0.921817421913147, 'Val/mean recall': 0.9123481512069702, 'Val/mean hd95_metric': 28.5170955657959} +Cheakpoint... +Epoch [5/4000] best acc:tensor([0.9178], device='cuda:0'), Now : mean acc: tensor([0.9178], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9178253412246704, 'Val/mean miou_metric': 0.8629156351089478, 'Val/mean f1': 0.9170584082603455, 'Val/mean precision': 0.921817421913147, 'Val/mean recall': 0.9123481512069702, 'Val/mean hd95_metric': 28.5170955657959} +Epoch [6/4000] Training [1/16] Loss: 0.14334 +Epoch [6/4000] Training [2/16] Loss: 0.07262 +Epoch [6/4000] Training [3/16] Loss: 0.06385 +Epoch [6/4000] Training [4/16] Loss: 0.05524 +Epoch [6/4000] Training [5/16] Loss: 0.05452 +Epoch [6/4000] Training [6/16] Loss: 0.05176 +Epoch [6/4000] Training [7/16] Loss: 0.12072 +Epoch [6/4000] Training [8/16] Loss: 0.05718 +Epoch [6/4000] Training [9/16] Loss: 0.07517 +Epoch [6/4000] Training [10/16] Loss: 0.09536 +Epoch [6/4000] Training [11/16] Loss: 0.06779 +Epoch [6/4000] Training [12/16] Loss: 0.05781 +Epoch [6/4000] Training [13/16] Loss: 0.06276 +Epoch [6/4000] Training [14/16] Loss: 0.06240 +Epoch [6/4000] Training [15/16] Loss: 0.05610 +Epoch [6/4000] Training [16/16] Loss: 0.04546 +Epoch [6/4000] Training metric {'Train/mean dice_metric': 0.9584558010101318, 'Train/mean miou_metric': 0.9218130111694336, 'Train/mean f1': 0.9577339887619019, 'Train/mean precision': 0.9551073908805847, 'Train/mean recall': 0.9603752493858337, 'Train/mean hd95_metric': 14.579055786132812} +Epoch [6/4000] Validation [1/4] Loss: 0.42944 focal_loss 0.28675 dice_loss 0.14269 +Epoch [6/4000] Validation [2/4] Loss: 0.33510 focal_loss 0.14469 dice_loss 0.19041 +Epoch [6/4000] Validation [3/4] Loss: 0.35978 focal_loss 0.21780 dice_loss 0.14198 +Epoch [6/4000] Validation [4/4] Loss: 0.31875 focal_loss 0.17503 dice_loss 0.14372 +Epoch [6/4000] Validation metric {'Val/mean dice_metric': 0.9357711672782898, 'Val/mean miou_metric': 0.8906472325325012, 'Val/mean f1': 0.9391252398490906, 'Val/mean precision': 0.9414951205253601, 'Val/mean recall': 0.9367672204971313, 'Val/mean hd95_metric': 18.98341178894043} +Cheakpoint... +Epoch [6/4000] best acc:tensor([0.9358], device='cuda:0'), Now : mean acc: tensor([0.9358], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9357711672782898, 'Val/mean miou_metric': 0.8906472325325012, 'Val/mean f1': 0.9391252398490906, 'Val/mean precision': 0.9414951205253601, 'Val/mean recall': 0.9367672204971313, 'Val/mean hd95_metric': 18.98341178894043} +Epoch [7/4000] Training [1/16] Loss: 0.07559 +Epoch [7/4000] Training [2/16] Loss: 0.06223 +Epoch [7/4000] Training [3/16] Loss: 0.05170 +Epoch [7/4000] Training [4/16] Loss: 0.04644 +Epoch [7/4000] Training [5/16] Loss: 0.04554 +Epoch [7/4000] Training [6/16] Loss: 0.04772 +Epoch [7/4000] Training [7/16] Loss: 0.03763 +Epoch [7/4000] Training [8/16] Loss: 0.04525 +Epoch [7/4000] Training [9/16] Loss: 0.04243 +Epoch [7/4000] Training [10/16] Loss: 0.03494 +Epoch [7/4000] Training [11/16] Loss: 0.03717 +Epoch [7/4000] Training [12/16] Loss: 0.04277 +Epoch [7/4000] Training [13/16] Loss: 0.03764 +Epoch [7/4000] Training [14/16] Loss: 0.04585 +Epoch [7/4000] Training [15/16] Loss: 0.04529 +Epoch [7/4000] Training [16/16] Loss: 0.03942 +Epoch [7/4000] Training metric {'Train/mean dice_metric': 0.9710979461669922, 'Train/mean miou_metric': 0.944263756275177, 'Train/mean f1': 0.9711447358131409, 'Train/mean precision': 0.9675107002258301, 'Train/mean recall': 0.9748061895370483, 'Train/mean hd95_metric': 7.77609395980835} +Epoch [7/4000] Validation [1/4] Loss: 0.38935 focal_loss 0.25162 dice_loss 0.13773 +Epoch [7/4000] Validation [2/4] Loss: 0.19596 focal_loss 0.07103 dice_loss 0.12493 +Epoch [7/4000] Validation [3/4] Loss: 0.22937 focal_loss 0.11991 dice_loss 0.10946 +Epoch [7/4000] Validation [4/4] Loss: 0.28426 focal_loss 0.15238 dice_loss 0.13188 +Epoch [7/4000] Validation metric {'Val/mean dice_metric': 0.9493095278739929, 'Val/mean miou_metric': 0.9130398035049438, 'Val/mean f1': 0.9540133476257324, 'Val/mean precision': 0.9570507407188416, 'Val/mean recall': 0.9509952664375305, 'Val/mean hd95_metric': 11.357441902160645} +Cheakpoint... +Epoch [7/4000] best acc:tensor([0.9493], device='cuda:0'), Now : mean acc: tensor([0.9493], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9493095278739929, 'Val/mean miou_metric': 0.9130398035049438, 'Val/mean f1': 0.9540133476257324, 'Val/mean precision': 0.9570507407188416, 'Val/mean recall': 0.9509952664375305, 'Val/mean hd95_metric': 11.357441902160645} +Epoch [8/4000] Training [1/16] Loss: 0.03498 +Epoch [8/4000] Training [2/16] Loss: 0.04015 +Epoch [8/4000] Training [3/16] Loss: 0.02675 +Epoch [8/4000] Training [4/16] Loss: 0.03601 +Epoch [8/4000] Training [5/16] Loss: 0.04437 +Epoch [8/4000] Training [6/16] Loss: 0.03661 +Epoch [8/4000] Training [7/16] Loss: 0.03798 +Epoch [8/4000] Training [8/16] Loss: 0.02851 +Epoch [8/4000] Training [9/16] Loss: 0.03823 +Epoch [8/4000] Training [10/16] Loss: 0.02529 +Epoch [8/4000] Training [11/16] Loss: 0.03259 +Epoch [8/4000] Training [12/16] Loss: 0.03925 +Epoch [8/4000] Training [13/16] Loss: 0.04193 +Epoch [8/4000] Training [14/16] Loss: 0.04119 +Epoch [8/4000] Training [15/16] Loss: 0.03300 +Epoch [8/4000] Training [16/16] Loss: 0.03191 +Epoch [8/4000] Training metric {'Train/mean dice_metric': 0.97687828540802, 'Train/mean miou_metric': 0.9548717141151428, 'Train/mean f1': 0.9756706953048706, 'Train/mean precision': 0.9717420339584351, 'Train/mean recall': 0.979631245136261, 'Train/mean hd95_metric': 4.959643363952637} +Epoch [8/4000] Validation [1/4] Loss: 0.23178 focal_loss 0.14056 dice_loss 0.09121 +Epoch [8/4000] Validation [2/4] Loss: 0.23692 focal_loss 0.10381 dice_loss 0.13310 +Epoch [8/4000] Validation [3/4] Loss: 0.17218 focal_loss 0.08486 dice_loss 0.08731 +Epoch [8/4000] Validation [4/4] Loss: 0.21828 focal_loss 0.09337 dice_loss 0.12492 +Epoch [8/4000] Validation metric {'Val/mean dice_metric': 0.9539788961410522, 'Val/mean miou_metric': 0.9221905469894409, 'Val/mean f1': 0.9573638439178467, 'Val/mean precision': 0.9563117623329163, 'Val/mean recall': 0.9584183096885681, 'Val/mean hd95_metric': 9.873106956481934} +Cheakpoint... +Epoch [8/4000] best acc:tensor([0.9540], device='cuda:0'), Now : mean acc: tensor([0.9540], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9539788961410522, 'Val/mean miou_metric': 0.9221905469894409, 'Val/mean f1': 0.9573638439178467, 'Val/mean precision': 0.9563117623329163, 'Val/mean recall': 0.9584183096885681, 'Val/mean hd95_metric': 9.873106956481934} +Epoch [9/4000] Training [1/16] Loss: 0.03841 +Epoch [9/4000] Training [2/16] Loss: 0.02294 +Epoch [9/4000] Training [3/16] Loss: 0.03156 +Epoch [9/4000] Training [4/16] Loss: 0.02446 +Epoch [9/4000] Training [5/16] Loss: 0.02895 +Epoch [9/4000] Training [6/16] Loss: 0.03712 +Epoch [9/4000] Training [7/16] Loss: 0.02841 +Epoch [9/4000] Training [8/16] Loss: 0.01898 +Epoch [9/4000] Training [9/16] Loss: 0.02989 +Epoch [9/4000] Training [10/16] Loss: 0.02763 +Epoch [9/4000] Training [11/16] Loss: 0.02793 +Epoch [9/4000] Training [12/16] Loss: 0.03013 +Epoch [9/4000] Training [13/16] Loss: 0.02662 +Epoch [9/4000] Training [14/16] Loss: 0.02941 +Epoch [9/4000] Training [15/16] Loss: 0.02977 +Epoch [9/4000] Training [16/16] Loss: 0.02518 +Epoch [9/4000] Training metric {'Train/mean dice_metric': 0.979455828666687, 'Train/mean miou_metric': 0.9598027467727661, 'Train/mean f1': 0.9786030054092407, 'Train/mean precision': 0.9736246466636658, 'Train/mean recall': 0.9836324453353882, 'Train/mean hd95_metric': 3.3658390045166016} +Epoch [9/4000] Validation [1/4] Loss: 0.29181 focal_loss 0.17389 dice_loss 0.11792 +Epoch [9/4000] Validation [2/4] Loss: 0.31806 focal_loss 0.14601 dice_loss 0.17205 +Epoch [9/4000] Validation [3/4] Loss: 0.13523 focal_loss 0.06052 dice_loss 0.07471 +Epoch [9/4000] Validation [4/4] Loss: 0.30299 focal_loss 0.16073 dice_loss 0.14226 +Epoch [9/4000] Validation metric {'Val/mean dice_metric': 0.9571460485458374, 'Val/mean miou_metric': 0.9265705347061157, 'Val/mean f1': 0.9598866105079651, 'Val/mean precision': 0.9633708596229553, 'Val/mean recall': 0.9564274549484253, 'Val/mean hd95_metric': 8.546867370605469} +Cheakpoint... +Epoch [9/4000] best acc:tensor([0.9571], device='cuda:0'), Now : mean acc: tensor([0.9571], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9571460485458374, 'Val/mean miou_metric': 0.9265705347061157, 'Val/mean f1': 0.9598866105079651, 'Val/mean precision': 0.9633708596229553, 'Val/mean recall': 0.9564274549484253, 'Val/mean hd95_metric': 8.546867370605469} +Epoch [10/4000] Training [1/16] Loss: 0.03456 +Epoch [10/4000] Training [2/16] Loss: 0.02859 +Epoch [10/4000] Training [3/16] Loss: 0.04432 +Epoch [10/4000] Training [4/16] Loss: 0.03243 +Epoch [10/4000] Training [5/16] Loss: 0.03332 +Epoch [10/4000] Training [6/16] Loss: 0.02323 +Epoch [10/4000] Training [7/16] Loss: 0.02600 +Epoch [10/4000] Training [8/16] Loss: 0.02713 +Epoch [10/4000] Training [9/16] Loss: 0.02239 +Epoch [10/4000] Training [10/16] Loss: 0.02388 +Epoch [10/4000] Training [11/16] Loss: 0.02929 +Epoch [10/4000] Training [12/16] Loss: 0.02204 +Epoch [10/4000] Training [13/16] Loss: 0.04546 +Epoch [10/4000] Training [14/16] Loss: 0.03524 +Epoch [10/4000] Training [15/16] Loss: 0.01962 +Epoch [10/4000] Training [16/16] Loss: 0.03052 +Epoch [10/4000] Training metric {'Train/mean dice_metric': 0.9813061356544495, 'Train/mean miou_metric': 0.9633769392967224, 'Train/mean f1': 0.980148434638977, 'Train/mean precision': 0.9757426977157593, 'Train/mean recall': 0.9845941066741943, 'Train/mean hd95_metric': 3.472114086151123} +Epoch [10/4000] Validation [1/4] Loss: 0.26368 focal_loss 0.16359 dice_loss 0.10009 +Epoch [10/4000] Validation [2/4] Loss: 0.47538 focal_loss 0.27189 dice_loss 0.20349 +Epoch [10/4000] Validation [3/4] Loss: 0.20689 focal_loss 0.10800 dice_loss 0.09890 +Epoch [10/4000] Validation [4/4] Loss: 0.25023 focal_loss 0.12903 dice_loss 0.12120 +Epoch [10/4000] Validation metric {'Val/mean dice_metric': 0.9583942294120789, 'Val/mean miou_metric': 0.9301484823226929, 'Val/mean f1': 0.9626317620277405, 'Val/mean precision': 0.959168553352356, 'Val/mean recall': 0.9661201238632202, 'Val/mean hd95_metric': 8.583719253540039} +Cheakpoint... +Epoch [10/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9584], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9583942294120789, 'Val/mean miou_metric': 0.9301484823226929, 'Val/mean f1': 0.9626317620277405, 'Val/mean precision': 0.959168553352356, 'Val/mean recall': 0.9661201238632202, 'Val/mean hd95_metric': 8.583719253540039} +Epoch [11/4000] Training [1/16] Loss: 0.01882 +Epoch [11/4000] Training [2/16] Loss: 0.04071 +Epoch [11/4000] Training [3/16] Loss: 0.02709 +Epoch [11/4000] Training [4/16] Loss: 0.10774 +Epoch [11/4000] Training [5/16] Loss: 0.02553 +Epoch [11/4000] Training [6/16] Loss: 0.02544 +Epoch [11/4000] Training [7/16] Loss: 0.04770 +Epoch [11/4000] Training [8/16] Loss: 0.02742 +Epoch [11/4000] Training [9/16] Loss: 0.02956 +Epoch [11/4000] Training [10/16] Loss: 0.02692 +Epoch [11/4000] Training [11/16] Loss: 0.02758 +Epoch [11/4000] Training [12/16] Loss: 0.02392 +Epoch [11/4000] Training [13/16] Loss: 0.02840 +Epoch [11/4000] Training [14/16] Loss: 0.02956 +Epoch [11/4000] Training [15/16] Loss: 0.02968 +Epoch [11/4000] Training [16/16] Loss: 0.04617 +Epoch [11/4000] Training metric {'Train/mean dice_metric': 0.9769786596298218, 'Train/mean miou_metric': 0.9562103748321533, 'Train/mean f1': 0.9767469167709351, 'Train/mean precision': 0.9725930690765381, 'Train/mean recall': 0.9809363484382629, 'Train/mean hd95_metric': 5.982967376708984} +Epoch [11/4000] Validation [1/4] Loss: 0.12856 focal_loss 0.06336 dice_loss 0.06520 +Epoch [11/4000] Validation [2/4] Loss: 0.34388 focal_loss 0.15073 dice_loss 0.19315 +Epoch [11/4000] Validation [3/4] Loss: 0.28961 focal_loss 0.15069 dice_loss 0.13891 +Epoch [11/4000] Validation [4/4] Loss: 0.39142 focal_loss 0.20950 dice_loss 0.18192 +Epoch [11/4000] Validation metric {'Val/mean dice_metric': 0.9513231515884399, 'Val/mean miou_metric': 0.919532299041748, 'Val/mean f1': 0.9560726284980774, 'Val/mean precision': 0.9502114653587341, 'Val/mean recall': 0.9620065093040466, 'Val/mean hd95_metric': 13.178889274597168} +Cheakpoint... +Epoch [11/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9513], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9513231515884399, 'Val/mean miou_metric': 0.919532299041748, 'Val/mean f1': 0.9560726284980774, 'Val/mean precision': 0.9502114653587341, 'Val/mean recall': 0.9620065093040466, 'Val/mean hd95_metric': 13.178889274597168} +Epoch [12/4000] Training [1/16] Loss: 0.02749 +Epoch [12/4000] Training [2/16] Loss: 0.02779 +Epoch [12/4000] Training [3/16] Loss: 0.03039 +Epoch [12/4000] Training [4/16] Loss: 0.05712 +Epoch [12/4000] Training [5/16] Loss: 0.03897 +Epoch [12/4000] Training [6/16] Loss: 0.02694 +Epoch [12/4000] Training [7/16] Loss: 0.03119 +Epoch [12/4000] Training [8/16] Loss: 0.02980 +Epoch [12/4000] Training [9/16] Loss: 0.03284 +Epoch [12/4000] Training [10/16] Loss: 0.02943 +Epoch [12/4000] Training [11/16] Loss: 0.07037 +Epoch [12/4000] Training [12/16] Loss: 0.02722 +Epoch [12/4000] Training [13/16] Loss: 0.04863 +Epoch [12/4000] Training [14/16] Loss: 0.03493 +Epoch [12/4000] Training [15/16] Loss: 0.07771 +Epoch [12/4000] Training [16/16] Loss: 0.03078 +Epoch [12/4000] Training metric {'Train/mean dice_metric': 0.9758475422859192, 'Train/mean miou_metric': 0.9533326625823975, 'Train/mean f1': 0.972673237323761, 'Train/mean precision': 0.9677928686141968, 'Train/mean recall': 0.9776030778884888, 'Train/mean hd95_metric': 7.989863872528076} +Epoch [12/4000] Validation [1/4] Loss: 0.32422 focal_loss 0.21372 dice_loss 0.11050 +Epoch [12/4000] Validation [2/4] Loss: 0.37747 focal_loss 0.16861 dice_loss 0.20886 +Epoch [12/4000] Validation [3/4] Loss: 0.17907 focal_loss 0.07762 dice_loss 0.10145 +Epoch [12/4000] Validation [4/4] Loss: 0.29213 focal_loss 0.15643 dice_loss 0.13569 +Epoch [12/4000] Validation metric {'Val/mean dice_metric': 0.9483743906021118, 'Val/mean miou_metric': 0.9145166277885437, 'Val/mean f1': 0.9495460391044617, 'Val/mean precision': 0.9511794447898865, 'Val/mean recall': 0.9479182958602905, 'Val/mean hd95_metric': 13.568536758422852} +Cheakpoint... +Epoch [12/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9484], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9483743906021118, 'Val/mean miou_metric': 0.9145166277885437, 'Val/mean f1': 0.9495460391044617, 'Val/mean precision': 0.9511794447898865, 'Val/mean recall': 0.9479182958602905, 'Val/mean hd95_metric': 13.568536758422852} +Epoch [13/4000] Training [1/16] Loss: 0.04133 +Epoch [13/4000] Training [2/16] Loss: 0.03064 +Epoch [13/4000] Training [3/16] Loss: 0.03837 +Epoch [13/4000] Training [4/16] Loss: 0.09055 +Epoch [13/4000] Training [5/16] Loss: 0.02970 +Epoch [13/4000] Training [6/16] Loss: 0.03415 +Epoch [13/4000] Training [7/16] Loss: 0.05048 +Epoch [13/4000] Training [8/16] Loss: 0.04104 +Epoch [13/4000] Training [9/16] Loss: 0.03815 +Epoch [13/4000] Training [10/16] Loss: 0.03249 +Epoch [13/4000] Training [11/16] Loss: 0.03881 +Epoch [13/4000] Training [12/16] Loss: 0.08064 +Epoch [13/4000] Training [13/16] Loss: 0.06543 +Epoch [13/4000] Training [14/16] Loss: 0.05214 +Epoch [13/4000] Training [15/16] Loss: 0.08279 +Epoch [13/4000] Training [16/16] Loss: 0.05399 +Epoch [13/4000] Training metric {'Train/mean dice_metric': 0.9662168025970459, 'Train/mean miou_metric': 0.9370790719985962, 'Train/mean f1': 0.9612041711807251, 'Train/mean precision': 0.9550016522407532, 'Train/mean recall': 0.9674877524375916, 'Train/mean hd95_metric': 14.713606834411621} +Epoch [13/4000] Validation [1/4] Loss: 0.14958 focal_loss 0.07154 dice_loss 0.07804 +Epoch [13/4000] Validation [2/4] Loss: 0.33546 focal_loss 0.13478 dice_loss 0.20068 +Epoch [13/4000] Validation [3/4] Loss: 0.19615 focal_loss 0.07891 dice_loss 0.11724 +Epoch [13/4000] Validation [4/4] Loss: 0.66174 focal_loss 0.37649 dice_loss 0.28525 +Epoch [13/4000] Validation metric {'Val/mean dice_metric': 0.9374032020568848, 'Val/mean miou_metric': 0.8969589471817017, 'Val/mean f1': 0.9354200959205627, 'Val/mean precision': 0.9170932173728943, 'Val/mean recall': 0.9544943571090698, 'Val/mean hd95_metric': 23.37352752685547} +Cheakpoint... +Epoch [13/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9374], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9374032020568848, 'Val/mean miou_metric': 0.8969589471817017, 'Val/mean f1': 0.9354200959205627, 'Val/mean precision': 0.9170932173728943, 'Val/mean recall': 0.9544943571090698, 'Val/mean hd95_metric': 23.37352752685547} +Epoch [14/4000] Training [1/16] Loss: 0.05965 +Epoch [14/4000] Training [2/16] Loss: 0.04619 +Epoch [14/4000] Training [3/16] Loss: 0.03716 +Epoch [14/4000] Training [4/16] Loss: 0.06503 +Epoch [14/4000] Training [5/16] Loss: 0.05734 +Epoch [14/4000] Training [6/16] Loss: 0.04035 +Epoch [14/4000] Training [7/16] Loss: 0.07767 +Epoch [14/4000] Training [8/16] Loss: 0.05425 +Epoch [14/4000] Training [9/16] Loss: 0.06039 +Epoch [14/4000] Training [10/16] Loss: 0.06510 +Epoch [14/4000] Training [11/16] Loss: 0.03310 +Epoch [14/4000] Training [12/16] Loss: 0.03869 +Epoch [14/4000] Training [13/16] Loss: 0.03365 +Epoch [14/4000] Training [14/16] Loss: 0.06910 +Epoch [14/4000] Training [15/16] Loss: 0.04447 +Epoch [14/4000] Training [16/16] Loss: 0.04795 +Epoch [14/4000] Training metric {'Train/mean dice_metric': 0.9658674001693726, 'Train/mean miou_metric': 0.9353506565093994, 'Train/mean f1': 0.9632879495620728, 'Train/mean precision': 0.9600162506103516, 'Train/mean recall': 0.9665820002555847, 'Train/mean hd95_metric': 10.39291000366211} +Epoch [14/4000] Validation [1/4] Loss: 0.23736 focal_loss 0.14296 dice_loss 0.09439 +Epoch [14/4000] Validation [2/4] Loss: 0.26702 focal_loss 0.09694 dice_loss 0.17008 +Epoch [14/4000] Validation [3/4] Loss: 0.27867 focal_loss 0.15092 dice_loss 0.12775 +Epoch [14/4000] Validation [4/4] Loss: 0.41164 focal_loss 0.23827 dice_loss 0.17337 +Epoch [14/4000] Validation metric {'Val/mean dice_metric': 0.94048011302948, 'Val/mean miou_metric': 0.8995679616928101, 'Val/mean f1': 0.9436843991279602, 'Val/mean precision': 0.946022629737854, 'Val/mean recall': 0.9413577318191528, 'Val/mean hd95_metric': 15.294438362121582} +Cheakpoint... +Epoch [14/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9405], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.94048011302948, 'Val/mean miou_metric': 0.8995679616928101, 'Val/mean f1': 0.9436843991279602, 'Val/mean precision': 0.946022629737854, 'Val/mean recall': 0.9413577318191528, 'Val/mean hd95_metric': 15.294438362121582} +Epoch [15/4000] Training [1/16] Loss: 0.06125 +Epoch [15/4000] Training [2/16] Loss: 0.02660 +Epoch [15/4000] Training [3/16] Loss: 0.06743 +Epoch [15/4000] Training [4/16] Loss: 0.07458 +Epoch [15/4000] Training [5/16] Loss: 0.05203 +Epoch [15/4000] Training [6/16] Loss: 0.07258 +Epoch [15/4000] Training [7/16] Loss: 0.02743 +Epoch [15/4000] Training [8/16] Loss: 0.04630 +Epoch [15/4000] Training [9/16] Loss: 0.02815 +Epoch [15/4000] Training [10/16] Loss: 0.05084 +Epoch [15/4000] Training [11/16] Loss: 0.03401 +Epoch [15/4000] Training [12/16] Loss: 0.03801 +Epoch [15/4000] Training [13/16] Loss: 0.03549 +Epoch [15/4000] Training [14/16] Loss: 0.02546 +Epoch [15/4000] Training [15/16] Loss: 0.03335 +Epoch [15/4000] Training [16/16] Loss: 0.02853 +Epoch [15/4000] Training metric {'Train/mean dice_metric': 0.971426784992218, 'Train/mean miou_metric': 0.9459786415100098, 'Train/mean f1': 0.9705487489700317, 'Train/mean precision': 0.9653767347335815, 'Train/mean recall': 0.9757764935493469, 'Train/mean hd95_metric': 7.679671764373779} +Epoch [15/4000] Validation [1/4] Loss: 1.30469 focal_loss 1.11486 dice_loss 0.18983 +Epoch [15/4000] Validation [2/4] Loss: 0.22770 focal_loss 0.06581 dice_loss 0.16189 +Epoch [15/4000] Validation [3/4] Loss: 0.23806 focal_loss 0.11760 dice_loss 0.12046 +Epoch [15/4000] Validation [4/4] Loss: 0.20707 focal_loss 0.08812 dice_loss 0.11895 +Epoch [15/4000] Validation metric {'Val/mean dice_metric': 0.9474245309829712, 'Val/mean miou_metric': 0.9126226305961609, 'Val/mean f1': 0.9522148370742798, 'Val/mean precision': 0.9523537158966064, 'Val/mean recall': 0.9520758986473083, 'Val/mean hd95_metric': 11.816121101379395} +Cheakpoint... +Epoch [15/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9474], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9474245309829712, 'Val/mean miou_metric': 0.9126226305961609, 'Val/mean f1': 0.9522148370742798, 'Val/mean precision': 0.9523537158966064, 'Val/mean recall': 0.9520758986473083, 'Val/mean hd95_metric': 11.816121101379395} +Epoch [16/4000] Training [1/16] Loss: 0.02335 +Epoch [16/4000] Training [2/16] Loss: 0.04902 +Epoch [16/4000] Training [3/16] Loss: 0.02495 +Epoch [16/4000] Training [4/16] Loss: 0.02954 +Epoch [16/4000] Training [5/16] Loss: 0.05587 +Epoch [16/4000] Training [6/16] Loss: 0.02844 +Epoch [16/4000] Training [7/16] Loss: 0.04075 +Epoch [16/4000] Training [8/16] Loss: 0.02155 +Epoch [16/4000] Training [9/16] Loss: 0.02369 +Epoch [16/4000] Training [10/16] Loss: 0.07370 +Epoch [16/4000] Training [11/16] Loss: 0.05042 +Epoch [16/4000] Training [12/16] Loss: 0.02588 +Epoch [16/4000] Training [13/16] Loss: 0.02404 +Epoch [16/4000] Training [14/16] Loss: 0.02688 +Epoch [16/4000] Training [15/16] Loss: 0.03166 +Epoch [16/4000] Training [16/16] Loss: 0.02959 +Epoch [16/4000] Training metric {'Train/mean dice_metric': 0.9727140665054321, 'Train/mean miou_metric': 0.9492895603179932, 'Train/mean f1': 0.9740314483642578, 'Train/mean precision': 0.9694768786430359, 'Train/mean recall': 0.9786289930343628, 'Train/mean hd95_metric': 5.97601842880249} +Epoch [16/4000] Validation [1/4] Loss: 0.50929 focal_loss 0.38023 dice_loss 0.12906 +Epoch [16/4000] Validation [2/4] Loss: 0.24764 focal_loss 0.08696 dice_loss 0.16068 +Epoch [16/4000] Validation [3/4] Loss: 0.23811 focal_loss 0.14679 dice_loss 0.09132 +Epoch [16/4000] Validation [4/4] Loss: 0.21493 focal_loss 0.07876 dice_loss 0.13617 +Epoch [16/4000] Validation metric {'Val/mean dice_metric': 0.9500888586044312, 'Val/mean miou_metric': 0.9163593053817749, 'Val/mean f1': 0.953782320022583, 'Val/mean precision': 0.9505465626716614, 'Val/mean recall': 0.9570401310920715, 'Val/mean hd95_metric': 10.8765287399292} +Cheakpoint... +Epoch [16/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9501], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9500888586044312, 'Val/mean miou_metric': 0.9163593053817749, 'Val/mean f1': 0.953782320022583, 'Val/mean precision': 0.9505465626716614, 'Val/mean recall': 0.9570401310920715, 'Val/mean hd95_metric': 10.8765287399292} +Epoch [17/4000] Training [1/16] Loss: 0.04754 +Epoch [17/4000] Training [2/16] Loss: 0.02643 +Epoch [17/4000] Training [3/16] Loss: 0.02282 +Epoch [17/4000] Training [4/16] Loss: 0.03588 +Epoch [17/4000] Training [5/16] Loss: 0.03031 +Epoch [17/4000] Training [6/16] Loss: 0.02393 +Epoch [17/4000] Training [7/16] Loss: 0.04268 +Epoch [17/4000] Training [8/16] Loss: 0.02598 +Epoch [17/4000] Training [9/16] Loss: 0.05362 +Epoch [17/4000] Training [10/16] Loss: 0.03549 +Epoch [17/4000] Training [11/16] Loss: 0.02770 +Epoch [17/4000] Training [12/16] Loss: 0.02233 +Epoch [17/4000] Training [13/16] Loss: 0.04061 +Epoch [17/4000] Training [14/16] Loss: 0.02338 +Epoch [17/4000] Training [15/16] Loss: 0.02525 +Epoch [17/4000] Training [16/16] Loss: 0.02985 +Epoch [17/4000] Training metric {'Train/mean dice_metric': 0.9768866896629333, 'Train/mean miou_metric': 0.9554600715637207, 'Train/mean f1': 0.975482702255249, 'Train/mean precision': 0.970863938331604, 'Train/mean recall': 0.9801456928253174, 'Train/mean hd95_metric': 5.566588401794434} +Epoch [17/4000] Validation [1/4] Loss: 0.65330 focal_loss 0.47657 dice_loss 0.17673 +Epoch [17/4000] Validation [2/4] Loss: 0.33563 focal_loss 0.14911 dice_loss 0.18653 +Epoch [17/4000] Validation [3/4] Loss: 0.34644 focal_loss 0.18703 dice_loss 0.15941 +Epoch [17/4000] Validation [4/4] Loss: 0.23954 focal_loss 0.09219 dice_loss 0.14735 +Epoch [17/4000] Validation metric {'Val/mean dice_metric': 0.9500175714492798, 'Val/mean miou_metric': 0.9177769422531128, 'Val/mean f1': 0.950660228729248, 'Val/mean precision': 0.9460133910179138, 'Val/mean recall': 0.9553530216217041, 'Val/mean hd95_metric': 11.299273490905762} +Cheakpoint... +Epoch [17/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9500], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9500175714492798, 'Val/mean miou_metric': 0.9177769422531128, 'Val/mean f1': 0.950660228729248, 'Val/mean precision': 0.9460133910179138, 'Val/mean recall': 0.9553530216217041, 'Val/mean hd95_metric': 11.299273490905762} +Epoch [18/4000] Training [1/16] Loss: 0.02355 +Epoch [18/4000] Training [2/16] Loss: 0.02505 +Epoch [18/4000] Training [3/16] Loss: 0.02422 +Epoch [18/4000] Training [4/16] Loss: 0.04113 +Epoch [18/4000] Training [5/16] Loss: 0.04776 +Epoch [18/4000] Training [6/16] Loss: 0.02556 +Epoch [18/4000] Training [7/16] Loss: 0.03066 +Epoch [18/4000] Training [8/16] Loss: 0.03115 +Epoch [18/4000] Training [9/16] Loss: 0.03655 +Epoch [18/4000] Training [10/16] Loss: 0.07195 +Epoch [18/4000] Training [11/16] Loss: 0.03076 +Epoch [18/4000] Training [12/16] Loss: 0.03579 +Epoch [18/4000] Training [13/16] Loss: 0.03077 +Epoch [18/4000] Training [14/16] Loss: 0.05506 +Epoch [18/4000] Training [15/16] Loss: 0.05678 +Epoch [18/4000] Training [16/16] Loss: 0.02904 +Epoch [18/4000] Training metric {'Train/mean dice_metric': 0.9760658144950867, 'Train/mean miou_metric': 0.9543320536613464, 'Train/mean f1': 0.9714335799217224, 'Train/mean precision': 0.9652708172798157, 'Train/mean recall': 0.9776755571365356, 'Train/mean hd95_metric': 7.663496971130371} +Epoch [18/4000] Validation [1/4] Loss: 0.89698 focal_loss 0.69863 dice_loss 0.19835 +Epoch [18/4000] Validation [2/4] Loss: 0.24051 focal_loss 0.09067 dice_loss 0.14984 +Epoch [18/4000] Validation [3/4] Loss: 0.50832 focal_loss 0.26289 dice_loss 0.24544 +Epoch [18/4000] Validation [4/4] Loss: 0.25918 focal_loss 0.11297 dice_loss 0.14621 +Epoch [18/4000] Validation metric {'Val/mean dice_metric': 0.9457736015319824, 'Val/mean miou_metric': 0.913413405418396, 'Val/mean f1': 0.9477906823158264, 'Val/mean precision': 0.9475684762001038, 'Val/mean recall': 0.9480130672454834, 'Val/mean hd95_metric': 12.082630157470703} +Cheakpoint... +Epoch [18/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9458], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9457736015319824, 'Val/mean miou_metric': 0.913413405418396, 'Val/mean f1': 0.9477906823158264, 'Val/mean precision': 0.9475684762001038, 'Val/mean recall': 0.9480130672454834, 'Val/mean hd95_metric': 12.082630157470703} +Epoch [19/4000] Training [1/16] Loss: 0.02523 +Epoch [19/4000] Training [2/16] Loss: 0.03316 +Epoch [19/4000] Training [3/16] Loss: 0.03259 +Epoch [19/4000] Training [4/16] Loss: 0.03027 +Epoch [19/4000] Training [5/16] Loss: 0.01926 +Epoch [19/4000] Training [6/16] Loss: 0.03427 +Epoch [19/4000] Training [7/16] Loss: 0.02113 +Epoch [19/4000] Training [8/16] Loss: 0.02576 +Epoch [19/4000] Training [9/16] Loss: 0.02297 +Epoch [19/4000] Training [10/16] Loss: 0.03361 +Epoch [19/4000] Training [11/16] Loss: 0.03603 +Epoch [19/4000] Training [12/16] Loss: 0.02027 +Epoch [19/4000] Training [13/16] Loss: 0.02550 +Epoch [19/4000] Training [14/16] Loss: 0.04045 +Epoch [19/4000] Training [15/16] Loss: 0.03985 +Epoch [19/4000] Training [16/16] Loss: 0.02836 +Epoch [19/4000] Training metric {'Train/mean dice_metric': 0.9754347205162048, 'Train/mean miou_metric': 0.9539186954498291, 'Train/mean f1': 0.973650336265564, 'Train/mean precision': 0.9717919230461121, 'Train/mean recall': 0.9755158424377441, 'Train/mean hd95_metric': 5.654230117797852} +Epoch [19/4000] Validation [1/4] Loss: 0.49988 focal_loss 0.31289 dice_loss 0.18699 +Epoch [19/4000] Validation [2/4] Loss: 0.39262 focal_loss 0.13680 dice_loss 0.25582 +Epoch [19/4000] Validation [3/4] Loss: 0.12612 focal_loss 0.05205 dice_loss 0.07406 +Epoch [19/4000] Validation [4/4] Loss: 0.34875 focal_loss 0.17694 dice_loss 0.17181 +Epoch [19/4000] Validation metric {'Val/mean dice_metric': 0.9468491673469543, 'Val/mean miou_metric': 0.9142991304397583, 'Val/mean f1': 0.9499626159667969, 'Val/mean precision': 0.9528919458389282, 'Val/mean recall': 0.9470512270927429, 'Val/mean hd95_metric': 11.498493194580078} +Cheakpoint... +Epoch [19/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9468], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9468491673469543, 'Val/mean miou_metric': 0.9142991304397583, 'Val/mean f1': 0.9499626159667969, 'Val/mean precision': 0.9528919458389282, 'Val/mean recall': 0.9470512270927429, 'Val/mean hd95_metric': 11.498493194580078} +Epoch [20/4000] Training [1/16] Loss: 0.02614 +Epoch [20/4000] Training [2/16] Loss: 0.02509 +Epoch [20/4000] Training [3/16] Loss: 0.07847 +Epoch [20/4000] Training [4/16] Loss: 0.02249 +Epoch [20/4000] Training [5/16] Loss: 0.02898 +Epoch [20/4000] Training [6/16] Loss: 0.04696 +Epoch [20/4000] Training [7/16] Loss: 0.04795 +Epoch [20/4000] Training [8/16] Loss: 0.03684 +Epoch [20/4000] Training [9/16] Loss: 0.05046 +Epoch [20/4000] Training [10/16] Loss: 0.04530 +Epoch [20/4000] Training [11/16] Loss: 0.02994 +Epoch [20/4000] Training [12/16] Loss: 0.03015 +Epoch [20/4000] Training [13/16] Loss: 0.02515 +Epoch [20/4000] Training [14/16] Loss: 0.07764 +Epoch [20/4000] Training [15/16] Loss: 0.08665 +Epoch [20/4000] Training [16/16] Loss: 0.04218 +Epoch [20/4000] Training metric {'Train/mean dice_metric': 0.9739217758178711, 'Train/mean miou_metric': 0.9514575600624084, 'Train/mean f1': 0.9719777703285217, 'Train/mean precision': 0.9675358533859253, 'Train/mean recall': 0.9764606952667236, 'Train/mean hd95_metric': 7.4281744956970215} +Epoch [20/4000] Validation [1/4] Loss: 0.22084 focal_loss 0.13073 dice_loss 0.09011 +Epoch [20/4000] Validation [2/4] Loss: 0.48755 focal_loss 0.23827 dice_loss 0.24927 +Epoch [20/4000] Validation [3/4] Loss: 0.20779 focal_loss 0.11226 dice_loss 0.09553 +Epoch [20/4000] Validation [4/4] Loss: 0.35471 focal_loss 0.15730 dice_loss 0.19742 +Epoch [20/4000] Validation metric {'Val/mean dice_metric': 0.9471340179443359, 'Val/mean miou_metric': 0.9145949482917786, 'Val/mean f1': 0.9519830942153931, 'Val/mean precision': 0.9393718242645264, 'Val/mean recall': 0.9649376273155212, 'Val/mean hd95_metric': 12.256470680236816} +Cheakpoint... +Epoch [20/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9471], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9471340179443359, 'Val/mean miou_metric': 0.9145949482917786, 'Val/mean f1': 0.9519830942153931, 'Val/mean precision': 0.9393718242645264, 'Val/mean recall': 0.9649376273155212, 'Val/mean hd95_metric': 12.256470680236816} +Epoch [21/4000] Training [1/16] Loss: 0.02821 +Epoch [21/4000] Training [2/16] Loss: 0.03762 +Epoch [21/4000] Training [3/16] Loss: 0.03403 +Epoch [21/4000] Training [4/16] Loss: 0.04814 +Epoch [21/4000] Training [5/16] Loss: 0.06720 +Epoch [21/4000] Training [6/16] Loss: 0.05192 +Epoch [21/4000] Training [7/16] Loss: 0.03553 +Epoch [21/4000] Training [8/16] Loss: 0.03014 +Epoch [21/4000] Training [9/16] Loss: 0.02343 +Epoch [21/4000] Training [10/16] Loss: 0.03416 +Epoch [21/4000] Training [11/16] Loss: 0.04086 +Epoch [21/4000] Training [12/16] Loss: 0.05700 +Epoch [21/4000] Training [13/16] Loss: 0.03488 +Epoch [21/4000] Training [14/16] Loss: 0.03376 +Epoch [21/4000] Training [15/16] Loss: 0.03790 +Epoch [21/4000] Training [16/16] Loss: 0.04195 +Epoch [21/4000] Training metric {'Train/mean dice_metric': 0.9699743986129761, 'Train/mean miou_metric': 0.9443165063858032, 'Train/mean f1': 0.9699947237968445, 'Train/mean precision': 0.9648804068565369, 'Train/mean recall': 0.9751635789871216, 'Train/mean hd95_metric': 8.419570922851562} +Epoch [21/4000] Validation [1/4] Loss: 0.94190 focal_loss 0.77152 dice_loss 0.17038 +Epoch [21/4000] Validation [2/4] Loss: 0.36996 focal_loss 0.15645 dice_loss 0.21351 +Epoch [21/4000] Validation [3/4] Loss: 0.30154 focal_loss 0.19313 dice_loss 0.10841 +Epoch [21/4000] Validation [4/4] Loss: 0.24080 focal_loss 0.12131 dice_loss 0.11949 +Epoch [21/4000] Validation metric {'Val/mean dice_metric': 0.9438787698745728, 'Val/mean miou_metric': 0.9089717864990234, 'Val/mean f1': 0.9472159743309021, 'Val/mean precision': 0.9498682022094727, 'Val/mean recall': 0.9445784091949463, 'Val/mean hd95_metric': 13.427984237670898} +Cheakpoint... +Epoch [21/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9439], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9438787698745728, 'Val/mean miou_metric': 0.9089717864990234, 'Val/mean f1': 0.9472159743309021, 'Val/mean precision': 0.9498682022094727, 'Val/mean recall': 0.9445784091949463, 'Val/mean hd95_metric': 13.427984237670898} +Epoch [22/4000] Training [1/16] Loss: 0.09735 +Epoch [22/4000] Training [2/16] Loss: 0.02487 +Epoch [22/4000] Training [3/16] Loss: 0.03775 +Epoch [22/4000] Training [4/16] Loss: 0.06599 +Epoch [22/4000] Training [5/16] Loss: 0.02905 +Epoch [22/4000] Training [6/16] Loss: 0.02668 +Epoch [22/4000] Training [7/16] Loss: 0.03391 +Epoch [22/4000] Training [8/16] Loss: 0.02577 +Epoch [22/4000] Training [9/16] Loss: 0.02022 +Epoch [22/4000] Training [10/16] Loss: 0.02673 +Epoch [22/4000] Training [11/16] Loss: 0.02321 +Epoch [22/4000] Training [12/16] Loss: 0.03786 +Epoch [22/4000] Training [13/16] Loss: 0.02943 +Epoch [22/4000] Training [14/16] Loss: 0.02451 +Epoch [22/4000] Training [15/16] Loss: 0.03353 +Epoch [22/4000] Training [16/16] Loss: 0.07551 +Epoch [22/4000] Training metric {'Train/mean dice_metric': 0.9764310121536255, 'Train/mean miou_metric': 0.9552340507507324, 'Train/mean f1': 0.974631130695343, 'Train/mean precision': 0.969476044178009, 'Train/mean recall': 0.9798412919044495, 'Train/mean hd95_metric': 5.458662509918213} +Epoch [22/4000] Validation [1/4] Loss: 0.32260 focal_loss 0.19786 dice_loss 0.12475 +Epoch [22/4000] Validation [2/4] Loss: 0.30463 focal_loss 0.10833 dice_loss 0.19631 +Epoch [22/4000] Validation [3/4] Loss: 0.22993 focal_loss 0.09184 dice_loss 0.13810 +Epoch [22/4000] Validation [4/4] Loss: 0.23707 focal_loss 0.07347 dice_loss 0.16360 +Epoch [22/4000] Validation metric {'Val/mean dice_metric': 0.9496333003044128, 'Val/mean miou_metric': 0.9176473617553711, 'Val/mean f1': 0.9517439007759094, 'Val/mean precision': 0.9406335353851318, 'Val/mean recall': 0.9631198048591614, 'Val/mean hd95_metric': 12.420673370361328} +Cheakpoint... +Epoch [22/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9496], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9496333003044128, 'Val/mean miou_metric': 0.9176473617553711, 'Val/mean f1': 0.9517439007759094, 'Val/mean precision': 0.9406335353851318, 'Val/mean recall': 0.9631198048591614, 'Val/mean hd95_metric': 12.420673370361328} +Epoch [23/4000] Training [1/16] Loss: 0.02811 +Epoch [23/4000] Training [2/16] Loss: 0.03636 +Epoch [23/4000] Training [3/16] Loss: 0.03046 +Epoch [23/4000] Training [4/16] Loss: 0.02421 +Epoch [23/4000] Training [5/16] Loss: 0.03699 +Epoch [23/4000] Training [6/16] Loss: 0.02844 +Epoch [23/4000] Training [7/16] Loss: 0.03005 +Epoch [23/4000] Training [8/16] Loss: 0.02237 +Epoch [23/4000] Training [9/16] Loss: 0.02814 +Epoch [23/4000] Training [10/16] Loss: 0.02475 +Epoch [23/4000] Training [11/16] Loss: 0.03435 +Epoch [23/4000] Training [12/16] Loss: 0.04898 +Epoch [23/4000] Training [13/16] Loss: 0.02815 +Epoch [23/4000] Training [14/16] Loss: 0.03256 +Epoch [23/4000] Training [15/16] Loss: 0.02011 +Epoch [23/4000] Training [16/16] Loss: 0.02751 +Epoch [23/4000] Training metric {'Train/mean dice_metric': 0.9752117395401001, 'Train/mean miou_metric': 0.9528277516365051, 'Train/mean f1': 0.972870409488678, 'Train/mean precision': 0.9672523140907288, 'Train/mean recall': 0.9785541296005249, 'Train/mean hd95_metric': 7.875122547149658} +Epoch [23/4000] Validation [1/4] Loss: 0.86198 focal_loss 0.66284 dice_loss 0.19914 +Epoch [23/4000] Validation [2/4] Loss: 0.29336 focal_loss 0.08031 dice_loss 0.21305 +Epoch [23/4000] Validation [3/4] Loss: 0.14652 focal_loss 0.06215 dice_loss 0.08437 +Epoch [23/4000] Validation [4/4] Loss: 0.48280 focal_loss 0.29030 dice_loss 0.19250 +Epoch [23/4000] Validation metric {'Val/mean dice_metric': 0.9476696848869324, 'Val/mean miou_metric': 0.9137913584709167, 'Val/mean f1': 0.9485708475112915, 'Val/mean precision': 0.9540640115737915, 'Val/mean recall': 0.9431406259536743, 'Val/mean hd95_metric': 13.238016128540039} +Cheakpoint... +Epoch [23/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9477], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9476696848869324, 'Val/mean miou_metric': 0.9137913584709167, 'Val/mean f1': 0.9485708475112915, 'Val/mean precision': 0.9540640115737915, 'Val/mean recall': 0.9431406259536743, 'Val/mean hd95_metric': 13.238016128540039} +Epoch [24/4000] Training [1/16] Loss: 0.04407 +Epoch [24/4000] Training [2/16] Loss: 0.04678 +Epoch [24/4000] Training [3/16] Loss: 0.02567 +Epoch [24/4000] Training [4/16] Loss: 0.02591 +Epoch [24/4000] Training [5/16] Loss: 0.02312 +Epoch [24/4000] Training [6/16] Loss: 0.04327 +Epoch [24/4000] Training [7/16] Loss: 0.02670 +Epoch [24/4000] Training [8/16] Loss: 0.02314 +Epoch [24/4000] Training [9/16] Loss: 0.02551 +Epoch [24/4000] Training [10/16] Loss: 0.02890 +Epoch [24/4000] Training [11/16] Loss: 0.02400 +Epoch [24/4000] Training [12/16] Loss: 0.03465 +Epoch [24/4000] Training [13/16] Loss: 0.02507 +Epoch [24/4000] Training [14/16] Loss: 0.02552 +Epoch [24/4000] Training [15/16] Loss: 0.04504 +Epoch [24/4000] Training [16/16] Loss: 0.02346 +Epoch [24/4000] Training metric {'Train/mean dice_metric': 0.9765949845314026, 'Train/mean miou_metric': 0.9563696384429932, 'Train/mean f1': 0.9742615222930908, 'Train/mean precision': 0.9681734442710876, 'Train/mean recall': 0.9804267287254333, 'Train/mean hd95_metric': 6.458620548248291} +Epoch [24/4000] Validation [1/4] Loss: 0.40508 focal_loss 0.26576 dice_loss 0.13932 +Epoch [24/4000] Validation [2/4] Loss: 0.37295 focal_loss 0.16325 dice_loss 0.20970 +Epoch [24/4000] Validation [3/4] Loss: 0.40168 focal_loss 0.28206 dice_loss 0.11962 +Epoch [24/4000] Validation [4/4] Loss: 0.31897 focal_loss 0.14556 dice_loss 0.17342 +Epoch [24/4000] Validation metric {'Val/mean dice_metric': 0.9501094818115234, 'Val/mean miou_metric': 0.9188440442085266, 'Val/mean f1': 0.9523025155067444, 'Val/mean precision': 0.9556028246879578, 'Val/mean recall': 0.9490249156951904, 'Val/mean hd95_metric': 11.482572555541992} +Cheakpoint... +Epoch [24/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9501], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9501094818115234, 'Val/mean miou_metric': 0.9188440442085266, 'Val/mean f1': 0.9523025155067444, 'Val/mean precision': 0.9556028246879578, 'Val/mean recall': 0.9490249156951904, 'Val/mean hd95_metric': 11.482572555541992} +Epoch [25/4000] Training [1/16] Loss: 0.07751 +Epoch [25/4000] Training [2/16] Loss: 0.02470 +Epoch [25/4000] Training [3/16] Loss: 0.02565 +Epoch [25/4000] Training [4/16] Loss: 0.02357 +Epoch [25/4000] Training [5/16] Loss: 0.03273 +Epoch [25/4000] Training [6/16] Loss: 0.03537 +Epoch [25/4000] Training [7/16] Loss: 0.03264 +Epoch [25/4000] Training [8/16] Loss: 0.02863 +Epoch [25/4000] Training [9/16] Loss: 0.02572 +Epoch [25/4000] Training [10/16] Loss: 0.03561 +Epoch [25/4000] Training [11/16] Loss: 0.02241 +Epoch [25/4000] Training [12/16] Loss: 0.02268 +Epoch [25/4000] Training [13/16] Loss: 0.01969 +Epoch [25/4000] Training [14/16] Loss: 0.03338 +Epoch [25/4000] Training [15/16] Loss: 0.02617 +Epoch [25/4000] Training [16/16] Loss: 0.03178 +Epoch [25/4000] Training metric {'Train/mean dice_metric': 0.9789936542510986, 'Train/mean miou_metric': 0.95937579870224, 'Train/mean f1': 0.9762647747993469, 'Train/mean precision': 0.9707630276679993, 'Train/mean recall': 0.9818292856216431, 'Train/mean hd95_metric': 5.0715131759643555} +Epoch [25/4000] Validation [1/4] Loss: 0.72563 focal_loss 0.57493 dice_loss 0.15070 +Epoch [25/4000] Validation [2/4] Loss: 0.51357 focal_loss 0.30172 dice_loss 0.21184 +Epoch [25/4000] Validation [3/4] Loss: 0.20197 focal_loss 0.11191 dice_loss 0.09006 +Epoch [25/4000] Validation [4/4] Loss: 0.23844 focal_loss 0.10029 dice_loss 0.13815 +Epoch [25/4000] Validation metric {'Val/mean dice_metric': 0.9559105038642883, 'Val/mean miou_metric': 0.9260663986206055, 'Val/mean f1': 0.9567317366600037, 'Val/mean precision': 0.9570745825767517, 'Val/mean recall': 0.9563890695571899, 'Val/mean hd95_metric': 9.378629684448242} +Cheakpoint... +Epoch [25/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9559], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9559105038642883, 'Val/mean miou_metric': 0.9260663986206055, 'Val/mean f1': 0.9567317366600037, 'Val/mean precision': 0.9570745825767517, 'Val/mean recall': 0.9563890695571899, 'Val/mean hd95_metric': 9.378629684448242} +Epoch [26/4000] Training [1/16] Loss: 0.02335 +Epoch [26/4000] Training [2/16] Loss: 0.02243 +Epoch [26/4000] Training [3/16] Loss: 0.02689 +Epoch [26/4000] Training [4/16] Loss: 0.02787 +Epoch [26/4000] Training [5/16] Loss: 0.07067 +Epoch [26/4000] Training [6/16] Loss: 0.02834 +Epoch [26/4000] Training [7/16] Loss: 0.02183 +Epoch [26/4000] Training [8/16] Loss: 0.02604 +Epoch [26/4000] Training [9/16] Loss: 0.02360 +Epoch [26/4000] Training [10/16] Loss: 0.02646 +Epoch [26/4000] Training [11/16] Loss: 0.02440 +Epoch [26/4000] Training [12/16] Loss: 0.03540 +Epoch [26/4000] Training [13/16] Loss: 0.02406 +Epoch [26/4000] Training [14/16] Loss: 0.05067 +Epoch [26/4000] Training [15/16] Loss: 0.03146 +Epoch [26/4000] Training [16/16] Loss: 0.02477 +Epoch [26/4000] Training metric {'Train/mean dice_metric': 0.9787858724594116, 'Train/mean miou_metric': 0.9589748382568359, 'Train/mean f1': 0.9772036075592041, 'Train/mean precision': 0.973682165145874, 'Train/mean recall': 0.980750560760498, 'Train/mean hd95_metric': 5.33878231048584} +Epoch [26/4000] Validation [1/4] Loss: 0.41014 focal_loss 0.28080 dice_loss 0.12934 +Epoch [26/4000] Validation [2/4] Loss: 0.27390 focal_loss 0.10103 dice_loss 0.17287 +Epoch [26/4000] Validation [3/4] Loss: 0.19087 focal_loss 0.11274 dice_loss 0.07813 +Epoch [26/4000] Validation [4/4] Loss: 0.25193 focal_loss 0.11172 dice_loss 0.14021 +Epoch [26/4000] Validation metric {'Val/mean dice_metric': 0.9545785188674927, 'Val/mean miou_metric': 0.9229331016540527, 'Val/mean f1': 0.9567573666572571, 'Val/mean precision': 0.9604169726371765, 'Val/mean recall': 0.9531255960464478, 'Val/mean hd95_metric': 11.053849220275879} +Cheakpoint... +Epoch [26/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9546], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9545785188674927, 'Val/mean miou_metric': 0.9229331016540527, 'Val/mean f1': 0.9567573666572571, 'Val/mean precision': 0.9604169726371765, 'Val/mean recall': 0.9531255960464478, 'Val/mean hd95_metric': 11.053849220275879} +Epoch [27/4000] Training [1/16] Loss: 0.02789 +Epoch [27/4000] Training [2/16] Loss: 0.04651 +Epoch [27/4000] Training [3/16] Loss: 0.02414 +Epoch [27/4000] Training [4/16] Loss: 0.02983 +Epoch [27/4000] Training [5/16] Loss: 0.08849 +Epoch [27/4000] Training [6/16] Loss: 0.02291 +Epoch [27/4000] Training [7/16] Loss: 0.03469 +Epoch [27/4000] Training [8/16] Loss: 0.11893 +Epoch [27/4000] Training [9/16] Loss: 0.02540 +Epoch [27/4000] Training [10/16] Loss: 0.02187 +Epoch [27/4000] Training [11/16] Loss: 0.09236 +Epoch [27/4000] Training [12/16] Loss: 0.02855 +Epoch [27/4000] Training [13/16] Loss: 0.02896 +Epoch [27/4000] Training [14/16] Loss: 0.02496 +Epoch [27/4000] Training [15/16] Loss: 0.02349 +Epoch [27/4000] Training [16/16] Loss: 0.03761 +Epoch [27/4000] Training metric {'Train/mean dice_metric': 0.9776109457015991, 'Train/mean miou_metric': 0.9574592113494873, 'Train/mean f1': 0.9748077988624573, 'Train/mean precision': 0.9709547162055969, 'Train/mean recall': 0.978691577911377, 'Train/mean hd95_metric': 4.786105632781982} +Epoch [27/4000] Validation [1/4] Loss: 0.17636 focal_loss 0.08134 dice_loss 0.09502 +Epoch [27/4000] Validation [2/4] Loss: 0.27839 focal_loss 0.12823 dice_loss 0.15016 +Epoch [27/4000] Validation [3/4] Loss: 0.12821 focal_loss 0.06055 dice_loss 0.06766 +Epoch [27/4000] Validation [4/4] Loss: 0.20912 focal_loss 0.07920 dice_loss 0.12992 +Epoch [27/4000] Validation metric {'Val/mean dice_metric': 0.9525405764579773, 'Val/mean miou_metric': 0.9214990735054016, 'Val/mean f1': 0.9541121125221252, 'Val/mean precision': 0.9561451077461243, 'Val/mean recall': 0.9520877003669739, 'Val/mean hd95_metric': 9.685937881469727} +Cheakpoint... +Epoch [27/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9525], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9525405764579773, 'Val/mean miou_metric': 0.9214990735054016, 'Val/mean f1': 0.9541121125221252, 'Val/mean precision': 0.9561451077461243, 'Val/mean recall': 0.9520877003669739, 'Val/mean hd95_metric': 9.685937881469727} +Epoch [28/4000] Training [1/16] Loss: 0.07572 +Epoch [28/4000] Training [2/16] Loss: 0.04539 +Epoch [28/4000] Training [3/16] Loss: 0.03808 +Epoch [28/4000] Training [4/16] Loss: 0.02152 +Epoch [28/4000] Training [5/16] Loss: 0.02653 +Epoch [28/4000] Training [6/16] Loss: 0.04348 +Epoch [28/4000] Training [7/16] Loss: 0.02643 +Epoch [28/4000] Training [8/16] Loss: 0.03447 +Epoch [28/4000] Training [9/16] Loss: 0.01887 +Epoch [28/4000] Training [10/16] Loss: 0.02602 +Epoch [28/4000] Training [11/16] Loss: 0.02208 +Epoch [28/4000] Training [12/16] Loss: 0.05003 +Epoch [28/4000] Training [13/16] Loss: 0.04344 +Epoch [28/4000] Training [14/16] Loss: 0.02980 +Epoch [28/4000] Training [15/16] Loss: 0.02671 +Epoch [28/4000] Training [16/16] Loss: 0.09562 +Epoch [28/4000] Training metric {'Train/mean dice_metric': 0.9733784198760986, 'Train/mean miou_metric': 0.9505591988563538, 'Train/mean f1': 0.9722558856010437, 'Train/mean precision': 0.9694074392318726, 'Train/mean recall': 0.9751211404800415, 'Train/mean hd95_metric': 6.63995361328125} +Epoch [28/4000] Validation [1/4] Loss: 0.17838 focal_loss 0.09506 dice_loss 0.08332 +Epoch [28/4000] Validation [2/4] Loss: 0.22654 focal_loss 0.07033 dice_loss 0.15621 +Epoch [28/4000] Validation [3/4] Loss: 0.16143 focal_loss 0.08700 dice_loss 0.07443 +Epoch [28/4000] Validation [4/4] Loss: 0.33566 focal_loss 0.14004 dice_loss 0.19563 +Epoch [28/4000] Validation metric {'Val/mean dice_metric': 0.9492114186286926, 'Val/mean miou_metric': 0.9158967733383179, 'Val/mean f1': 0.9512699842453003, 'Val/mean precision': 0.9413503408432007, 'Val/mean recall': 0.9614009261131287, 'Val/mean hd95_metric': 12.818285942077637} +Cheakpoint... +Epoch [28/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9492], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9492114186286926, 'Val/mean miou_metric': 0.9158967733383179, 'Val/mean f1': 0.9512699842453003, 'Val/mean precision': 0.9413503408432007, 'Val/mean recall': 0.9614009261131287, 'Val/mean hd95_metric': 12.818285942077637} +Epoch [29/4000] Training [1/16] Loss: 0.02838 +Epoch [29/4000] Training [2/16] Loss: 0.07910 +Epoch [29/4000] Training [3/16] Loss: 0.02947 +Epoch [29/4000] Training [4/16] Loss: 0.02473 +Epoch [29/4000] Training [5/16] Loss: 0.02853 +Epoch [29/4000] Training [6/16] Loss: 0.04609 +Epoch [29/4000] Training [7/16] Loss: 0.02755 +Epoch [29/4000] Training [8/16] Loss: 0.02715 +Epoch [29/4000] Training [9/16] Loss: 0.04911 +Epoch [29/4000] Training [10/16] Loss: 0.02822 +Epoch [29/4000] Training [11/16] Loss: 0.03181 +Epoch [29/4000] Training [12/16] Loss: 0.02990 +Epoch [29/4000] Training [13/16] Loss: 0.03773 +Epoch [29/4000] Training [14/16] Loss: 0.03492 +Epoch [29/4000] Training [15/16] Loss: 0.02857 +Epoch [29/4000] Training [16/16] Loss: 0.02649 +Epoch [29/4000] Training metric {'Train/mean dice_metric': 0.9744912385940552, 'Train/mean miou_metric': 0.9527367353439331, 'Train/mean f1': 0.9739664196968079, 'Train/mean precision': 0.9685004949569702, 'Train/mean recall': 0.9794944524765015, 'Train/mean hd95_metric': 7.640984535217285} +Epoch [29/4000] Validation [1/4] Loss: 0.16492 focal_loss 0.07944 dice_loss 0.08548 +Epoch [29/4000] Validation [2/4] Loss: 0.33527 focal_loss 0.12756 dice_loss 0.20771 +Epoch [29/4000] Validation [3/4] Loss: 0.18351 focal_loss 0.09303 dice_loss 0.09048 +Epoch [29/4000] Validation [4/4] Loss: 0.24181 focal_loss 0.09212 dice_loss 0.14970 +Epoch [29/4000] Validation metric {'Val/mean dice_metric': 0.9477561116218567, 'Val/mean miou_metric': 0.9148533940315247, 'Val/mean f1': 0.9489457607269287, 'Val/mean precision': 0.942046046257019, 'Val/mean recall': 0.95594722032547, 'Val/mean hd95_metric': 13.175811767578125} +Cheakpoint... +Epoch [29/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9478], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9477561116218567, 'Val/mean miou_metric': 0.9148533940315247, 'Val/mean f1': 0.9489457607269287, 'Val/mean precision': 0.942046046257019, 'Val/mean recall': 0.95594722032547, 'Val/mean hd95_metric': 13.175811767578125} +Epoch [30/4000] Training [1/16] Loss: 0.05466 +Epoch [30/4000] Training [2/16] Loss: 0.02418 +Epoch [30/4000] Training [3/16] Loss: 0.03295 +Epoch [30/4000] Training [4/16] Loss: 0.04900 +Epoch [30/4000] Training [5/16] Loss: 0.03288 +Epoch [30/4000] Training [6/16] Loss: 0.02564 +Epoch [30/4000] Training [7/16] Loss: 0.03050 +Epoch [30/4000] Training [8/16] Loss: 0.15997 +Epoch [30/4000] Training [9/16] Loss: 0.04829 +Epoch [30/4000] Training [10/16] Loss: 0.02255 +Epoch [30/4000] Training [11/16] Loss: 0.02566 +Epoch [30/4000] Training [12/16] Loss: 0.03165 +Epoch [30/4000] Training [13/16] Loss: 0.03409 +Epoch [30/4000] Training [14/16] Loss: 0.02477 +Epoch [30/4000] Training [15/16] Loss: 0.02964 +Epoch [30/4000] Training [16/16] Loss: 0.02426 +Epoch [30/4000] Training metric {'Train/mean dice_metric': 0.9762910604476929, 'Train/mean miou_metric': 0.9558631777763367, 'Train/mean f1': 0.9744267463684082, 'Train/mean precision': 0.9692336916923523, 'Train/mean recall': 0.9796757698059082, 'Train/mean hd95_metric': 5.199574947357178} +Epoch [30/4000] Validation [1/4] Loss: 0.88987 focal_loss 0.70261 dice_loss 0.18726 +Epoch [30/4000] Validation [2/4] Loss: 0.28800 focal_loss 0.10085 dice_loss 0.18715 +Epoch [30/4000] Validation [3/4] Loss: 0.13640 focal_loss 0.04938 dice_loss 0.08702 +Epoch [30/4000] Validation [4/4] Loss: 0.18354 focal_loss 0.07719 dice_loss 0.10635 +Epoch [30/4000] Validation metric {'Val/mean dice_metric': 0.9499334096908569, 'Val/mean miou_metric': 0.9187577962875366, 'Val/mean f1': 0.9510494470596313, 'Val/mean precision': 0.9497385025024414, 'Val/mean recall': 0.952363908290863, 'Val/mean hd95_metric': 10.180027961730957} +Cheakpoint... +Epoch [30/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9499], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9499334096908569, 'Val/mean miou_metric': 0.9187577962875366, 'Val/mean f1': 0.9510494470596313, 'Val/mean precision': 0.9497385025024414, 'Val/mean recall': 0.952363908290863, 'Val/mean hd95_metric': 10.180027961730957} +Epoch [31/4000] Training [1/16] Loss: 0.03608 +Epoch [31/4000] Training [2/16] Loss: 0.02263 +Epoch [31/4000] Training [3/16] Loss: 0.02727 +Epoch [31/4000] Training [4/16] Loss: 0.03187 +Epoch [31/4000] Training [5/16] Loss: 0.09914 +Epoch [31/4000] Training [6/16] Loss: 0.02506 +Epoch [31/4000] Training [7/16] Loss: 0.02480 +Epoch [31/4000] Training [8/16] Loss: 0.02266 +Epoch [31/4000] Training [9/16] Loss: 0.03497 +Epoch [31/4000] Training [10/16] Loss: 0.03259 +Epoch [31/4000] Training [11/16] Loss: 0.02694 +Epoch [31/4000] Training [12/16] Loss: 0.02356 +Epoch [31/4000] Training [13/16] Loss: 0.03305 +Epoch [31/4000] Training [14/16] Loss: 0.04094 +Epoch [31/4000] Training [15/16] Loss: 0.02524 +Epoch [31/4000] Training [16/16] Loss: 0.02251 +Epoch [31/4000] Training metric {'Train/mean dice_metric': 0.9762523174285889, 'Train/mean miou_metric': 0.9551586508750916, 'Train/mean f1': 0.9764552712440491, 'Train/mean precision': 0.9718834161758423, 'Train/mean recall': 0.9810703992843628, 'Train/mean hd95_metric': 5.015908718109131} +Epoch [31/4000] Validation [1/4] Loss: 0.16814 focal_loss 0.09244 dice_loss 0.07571 +Epoch [31/4000] Validation [2/4] Loss: 0.24777 focal_loss 0.09361 dice_loss 0.15416 +Epoch [31/4000] Validation [3/4] Loss: 0.15788 focal_loss 0.07974 dice_loss 0.07814 +Epoch [31/4000] Validation [4/4] Loss: 0.29072 focal_loss 0.12738 dice_loss 0.16334 +Epoch [31/4000] Validation metric {'Val/mean dice_metric': 0.953578770160675, 'Val/mean miou_metric': 0.9223411679267883, 'Val/mean f1': 0.9579307436943054, 'Val/mean precision': 0.956539511680603, 'Val/mean recall': 0.9593259692192078, 'Val/mean hd95_metric': 9.70036792755127} +Cheakpoint... +Epoch [31/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9536], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.953578770160675, 'Val/mean miou_metric': 0.9223411679267883, 'Val/mean f1': 0.9579307436943054, 'Val/mean precision': 0.956539511680603, 'Val/mean recall': 0.9593259692192078, 'Val/mean hd95_metric': 9.70036792755127} +Epoch [32/4000] Training [1/16] Loss: 0.03578 +Epoch [32/4000] Training [2/16] Loss: 0.03198 +Epoch [32/4000] Training [3/16] Loss: 0.03309 +Epoch [32/4000] Training [4/16] Loss: 0.02646 +Epoch [32/4000] Training [5/16] Loss: 0.02683 +Epoch [32/4000] Training [6/16] Loss: 0.02903 +Epoch [32/4000] Training [7/16] Loss: 0.02748 +Epoch [32/4000] Training [8/16] Loss: 0.02497 +Epoch [32/4000] Training [9/16] Loss: 0.02765 +Epoch [32/4000] Training [10/16] Loss: 0.03594 +Epoch [32/4000] Training [11/16] Loss: 0.14279 +Epoch [32/4000] Training [12/16] Loss: 0.02347 +Epoch [32/4000] Training [13/16] Loss: 0.02605 +Epoch [32/4000] Training [14/16] Loss: 0.02662 +Epoch [32/4000] Training [15/16] Loss: 0.02629 +Epoch [32/4000] Training [16/16] Loss: 0.02936 +Epoch [32/4000] Training metric {'Train/mean dice_metric': 0.9745047092437744, 'Train/mean miou_metric': 0.9532595872879028, 'Train/mean f1': 0.9748377799987793, 'Train/mean precision': 0.9713528156280518, 'Train/mean recall': 0.978347897529602, 'Train/mean hd95_metric': 6.2812981605529785} +Epoch [32/4000] Validation [1/4] Loss: 0.50296 focal_loss 0.36994 dice_loss 0.13302 +Epoch [32/4000] Validation [2/4] Loss: 0.30661 focal_loss 0.11608 dice_loss 0.19052 +Epoch [32/4000] Validation [3/4] Loss: 0.18258 focal_loss 0.08427 dice_loss 0.09831 +Epoch [32/4000] Validation [4/4] Loss: 0.25469 focal_loss 0.09697 dice_loss 0.15772 +Epoch [32/4000] Validation metric {'Val/mean dice_metric': 0.9502309560775757, 'Val/mean miou_metric': 0.9186688661575317, 'Val/mean f1': 0.9523299932479858, 'Val/mean precision': 0.9455893635749817, 'Val/mean recall': 0.9591673612594604, 'Val/mean hd95_metric': 11.355173110961914} +Cheakpoint... +Epoch [32/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9502], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9502309560775757, 'Val/mean miou_metric': 0.9186688661575317, 'Val/mean f1': 0.9523299932479858, 'Val/mean precision': 0.9455893635749817, 'Val/mean recall': 0.9591673612594604, 'Val/mean hd95_metric': 11.355173110961914} +Epoch [33/4000] Training [1/16] Loss: 0.02694 +Epoch [33/4000] Training [2/16] Loss: 0.03291 +Epoch [33/4000] Training [3/16] Loss: 0.02971 +Epoch [33/4000] Training [4/16] Loss: 0.01875 +Epoch [33/4000] Training [5/16] Loss: 0.02579 +Epoch [33/4000] Training [6/16] Loss: 0.02898 +Epoch [33/4000] Training [7/16] Loss: 0.03005 +Epoch [33/4000] Training [8/16] Loss: 0.03322 +Epoch [33/4000] Training [9/16] Loss: 0.08095 +Epoch [33/4000] Training [10/16] Loss: 0.03325 +Epoch [33/4000] Training [11/16] Loss: 0.03706 +Epoch [33/4000] Training [12/16] Loss: 0.02534 +Epoch [33/4000] Training [13/16] Loss: 0.03286 +Epoch [33/4000] Training [14/16] Loss: 0.02605 +Epoch [33/4000] Training [15/16] Loss: 0.02794 +Epoch [33/4000] Training [16/16] Loss: 0.02450 +Epoch [33/4000] Training metric {'Train/mean dice_metric': 0.9791830778121948, 'Train/mean miou_metric': 0.9596556425094604, 'Train/mean f1': 0.9769150614738464, 'Train/mean precision': 0.9721584916114807, 'Train/mean recall': 0.9817183613777161, 'Train/mean hd95_metric': 4.6781721115112305} +Epoch [33/4000] Validation [1/4] Loss: 0.39258 focal_loss 0.26899 dice_loss 0.12359 +Epoch [33/4000] Validation [2/4] Loss: 0.20310 focal_loss 0.06861 dice_loss 0.13449 +Epoch [33/4000] Validation [3/4] Loss: 0.19270 focal_loss 0.09218 dice_loss 0.10052 +Epoch [33/4000] Validation [4/4] Loss: 0.26470 focal_loss 0.09756 dice_loss 0.16713 +Epoch [33/4000] Validation metric {'Val/mean dice_metric': 0.9517322778701782, 'Val/mean miou_metric': 0.9211549758911133, 'Val/mean f1': 0.9509913325309753, 'Val/mean precision': 0.9402858018875122, 'Val/mean recall': 0.9619434475898743, 'Val/mean hd95_metric': 11.838174819946289} +Cheakpoint... +Epoch [33/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9517], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9517322778701782, 'Val/mean miou_metric': 0.9211549758911133, 'Val/mean f1': 0.9509913325309753, 'Val/mean precision': 0.9402858018875122, 'Val/mean recall': 0.9619434475898743, 'Val/mean hd95_metric': 11.838174819946289} +Epoch [34/4000] Training [1/16] Loss: 0.02191 +Epoch [34/4000] Training [2/16] Loss: 0.02429 +Epoch [34/4000] Training [3/16] Loss: 0.02233 +Epoch [34/4000] Training [4/16] Loss: 0.02106 +Epoch [34/4000] Training [5/16] Loss: 0.02797 +Epoch [34/4000] Training [6/16] Loss: 0.02315 +Epoch [34/4000] Training [7/16] Loss: 0.02326 +Epoch [34/4000] Training [8/16] Loss: 0.02081 +Epoch [34/4000] Training [9/16] Loss: 0.03186 +Epoch [34/4000] Training [10/16] Loss: 0.03025 +Epoch [34/4000] Training [11/16] Loss: 0.02613 +Epoch [34/4000] Training [12/16] Loss: 0.02887 +Epoch [34/4000] Training [13/16] Loss: 0.02284 +Epoch [34/4000] Training [14/16] Loss: 0.02064 +Epoch [34/4000] Training [15/16] Loss: 0.03328 +Epoch [34/4000] Training [16/16] Loss: 0.02910 +Epoch [34/4000] Training metric {'Train/mean dice_metric': 0.9805324673652649, 'Train/mean miou_metric': 0.9619755744934082, 'Train/mean f1': 0.9788878560066223, 'Train/mean precision': 0.9750937223434448, 'Train/mean recall': 0.982711672782898, 'Train/mean hd95_metric': 4.404014587402344} +Epoch [34/4000] Validation [1/4] Loss: 0.77566 focal_loss 0.61764 dice_loss 0.15802 +Epoch [34/4000] Validation [2/4] Loss: 0.19724 focal_loss 0.07782 dice_loss 0.11941 +Epoch [34/4000] Validation [3/4] Loss: 0.24171 focal_loss 0.14360 dice_loss 0.09811 +Epoch [34/4000] Validation [4/4] Loss: 0.30233 focal_loss 0.14325 dice_loss 0.15908 +Epoch [34/4000] Validation metric {'Val/mean dice_metric': 0.9531791806221008, 'Val/mean miou_metric': 0.9233667254447937, 'Val/mean f1': 0.954689085483551, 'Val/mean precision': 0.9580227136611938, 'Val/mean recall': 0.9513786435127258, 'Val/mean hd95_metric': 10.212788581848145} +Cheakpoint... +Epoch [34/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9532], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9531791806221008, 'Val/mean miou_metric': 0.9233667254447937, 'Val/mean f1': 0.954689085483551, 'Val/mean precision': 0.9580227136611938, 'Val/mean recall': 0.9513786435127258, 'Val/mean hd95_metric': 10.212788581848145} +Epoch [35/4000] Training [1/16] Loss: 0.02711 +Epoch [35/4000] Training [2/16] Loss: 0.02191 +Epoch [35/4000] Training [3/16] Loss: 0.02347 +Epoch [35/4000] Training [4/16] Loss: 0.02714 +Epoch [35/4000] Training [5/16] Loss: 0.02494 +Epoch [35/4000] Training [6/16] Loss: 0.03236 +Epoch [35/4000] Training [7/16] Loss: 0.02229 +Epoch [35/4000] Training [8/16] Loss: 0.02267 +Epoch [35/4000] Training [9/16] Loss: 0.03032 +Epoch [35/4000] Training [10/16] Loss: 0.02946 +Epoch [35/4000] Training [11/16] Loss: 0.02355 +Epoch [35/4000] Training [12/16] Loss: 0.03165 +Epoch [35/4000] Training [13/16] Loss: 0.01993 +Epoch [35/4000] Training [14/16] Loss: 0.02527 +Epoch [35/4000] Training [15/16] Loss: 0.02556 +Epoch [35/4000] Training [16/16] Loss: 0.02364 +Epoch [35/4000] Training metric {'Train/mean dice_metric': 0.9805638194084167, 'Train/mean miou_metric': 0.9624898433685303, 'Train/mean f1': 0.9785363674163818, 'Train/mean precision': 0.9735422730445862, 'Train/mean recall': 0.9835819602012634, 'Train/mean hd95_metric': 4.042524337768555} +Epoch [35/4000] Validation [1/4] Loss: 0.22571 focal_loss 0.13086 dice_loss 0.09485 +Epoch [35/4000] Validation [2/4] Loss: 0.21307 focal_loss 0.07636 dice_loss 0.13671 +Epoch [35/4000] Validation [3/4] Loss: 0.21029 focal_loss 0.12941 dice_loss 0.08088 +Epoch [35/4000] Validation [4/4] Loss: 0.33934 focal_loss 0.17642 dice_loss 0.16292 +Epoch [35/4000] Validation metric {'Val/mean dice_metric': 0.9567182660102844, 'Val/mean miou_metric': 0.9279653429985046, 'Val/mean f1': 0.9591010212898254, 'Val/mean precision': 0.9554442763328552, 'Val/mean recall': 0.9627857804298401, 'Val/mean hd95_metric': 8.682950019836426} +Cheakpoint... +Epoch [35/4000] best acc:tensor([0.9584], device='cuda:0'), Now : mean acc: tensor([0.9567], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9567182660102844, 'Val/mean miou_metric': 0.9279653429985046, 'Val/mean f1': 0.9591010212898254, 'Val/mean precision': 0.9554442763328552, 'Val/mean recall': 0.9627857804298401, 'Val/mean hd95_metric': 8.682950019836426} +Epoch [36/4000] Training [1/16] Loss: 0.03309 +Epoch [36/4000] Training [2/16] Loss: 0.03484 +Epoch [36/4000] Training [3/16] Loss: 0.02350 +Epoch [36/4000] Training [4/16] Loss: 0.02384 +Epoch [36/4000] Training [5/16] Loss: 0.02565 +Epoch [36/4000] Training [6/16] Loss: 0.02863 +Epoch [36/4000] Training [7/16] Loss: 0.02702 +Epoch [36/4000] Training [8/16] Loss: 0.02180 +Epoch [36/4000] Training [9/16] Loss: 0.02339 +Epoch [36/4000] Training [10/16] Loss: 0.01679 +Epoch [36/4000] Training [11/16] Loss: 0.03277 +Epoch [36/4000] Training [12/16] Loss: 0.02157 +Epoch [36/4000] Training [13/16] Loss: 0.02499 +Epoch [36/4000] Training [14/16] Loss: 0.01855 +Epoch [36/4000] Training [15/16] Loss: 0.02447 +Epoch [36/4000] Training [16/16] Loss: 0.02472 +Epoch [36/4000] Training metric {'Train/mean dice_metric': 0.9834631681442261, 'Train/mean miou_metric': 0.9673894047737122, 'Train/mean f1': 0.9815346598625183, 'Train/mean precision': 0.9771010875701904, 'Train/mean recall': 0.9860087037086487, 'Train/mean hd95_metric': 2.614680290222168} +Epoch [36/4000] Validation [1/4] Loss: 0.14551 focal_loss 0.07990 dice_loss 0.06561 +Epoch [36/4000] Validation [2/4] Loss: 0.35228 focal_loss 0.14805 dice_loss 0.20423 +Epoch [36/4000] Validation [3/4] Loss: 0.25367 focal_loss 0.14235 dice_loss 0.11133 +Epoch [36/4000] Validation [4/4] Loss: 0.33587 focal_loss 0.15413 dice_loss 0.18174 +Epoch [36/4000] Validation metric {'Val/mean dice_metric': 0.9593662023544312, 'Val/mean miou_metric': 0.9323837161064148, 'Val/mean f1': 0.9638748168945312, 'Val/mean precision': 0.9562011957168579, 'Val/mean recall': 0.9716726541519165, 'Val/mean hd95_metric': 8.673887252807617} +Cheakpoint... +Epoch [36/4000] best acc:tensor([0.9594], device='cuda:0'), Now : mean acc: tensor([0.9594], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9593662023544312, 'Val/mean miou_metric': 0.9323837161064148, 'Val/mean f1': 0.9638748168945312, 'Val/mean precision': 0.9562011957168579, 'Val/mean recall': 0.9716726541519165, 'Val/mean hd95_metric': 8.673887252807617} +Epoch [37/4000] Training [1/16] Loss: 0.02007 +Epoch [37/4000] Training [2/16] Loss: 0.01701 +Epoch [37/4000] Training [3/16] Loss: 0.03391 +Epoch [37/4000] Training [4/16] Loss: 0.02229 +Epoch [37/4000] Training [5/16] Loss: 0.02175 +Epoch [37/4000] Training [6/16] Loss: 0.01947 +Epoch [37/4000] Training [7/16] Loss: 0.02175 +Epoch [37/4000] Training [8/16] Loss: 0.02540 +Epoch [37/4000] Training [9/16] Loss: 0.02303 +Epoch [37/4000] Training [10/16] Loss: 0.02980 +Epoch [37/4000] Training [11/16] Loss: 0.02446 +Epoch [37/4000] Training [12/16] Loss: 0.02882 +Epoch [37/4000] Training [13/16] Loss: 0.02688 +Epoch [37/4000] Training [14/16] Loss: 0.02647 +Epoch [37/4000] Training [15/16] Loss: 0.02293 +Epoch [37/4000] Training [16/16] Loss: 0.01686 +Epoch [37/4000] Training metric {'Train/mean dice_metric': 0.9837640523910522, 'Train/mean miou_metric': 0.9680107831954956, 'Train/mean f1': 0.9817938208580017, 'Train/mean precision': 0.9772647023200989, 'Train/mean recall': 0.9863650798797607, 'Train/mean hd95_metric': 2.4339499473571777} +Epoch [37/4000] Validation [1/4] Loss: 0.19124 focal_loss 0.10450 dice_loss 0.08674 +Epoch [37/4000] Validation [2/4] Loss: 0.23487 focal_loss 0.09112 dice_loss 0.14375 +Epoch [37/4000] Validation [3/4] Loss: 0.14875 focal_loss 0.06845 dice_loss 0.08029 +Epoch [37/4000] Validation [4/4] Loss: 0.21793 focal_loss 0.09135 dice_loss 0.12657 +Epoch [37/4000] Validation metric {'Val/mean dice_metric': 0.9602206945419312, 'Val/mean miou_metric': 0.933097243309021, 'Val/mean f1': 0.9611157774925232, 'Val/mean precision': 0.9601598978042603, 'Val/mean recall': 0.9620736837387085, 'Val/mean hd95_metric': 7.748386383056641} +Cheakpoint... +Epoch [37/4000] best acc:tensor([0.9602], device='cuda:0'), Now : mean acc: tensor([0.9602], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9602206945419312, 'Val/mean miou_metric': 0.933097243309021, 'Val/mean f1': 0.9611157774925232, 'Val/mean precision': 0.9601598978042603, 'Val/mean recall': 0.9620736837387085, 'Val/mean hd95_metric': 7.748386383056641} +Epoch [38/4000] Training [1/16] Loss: 0.01806 +Epoch [38/4000] Training [2/16] Loss: 0.01910 +Epoch [38/4000] Training [3/16] Loss: 0.01986 +Epoch [38/4000] Training [4/16] Loss: 0.02977 +Epoch [38/4000] Training [5/16] Loss: 0.04070 +Epoch [38/4000] Training [6/16] Loss: 0.01743 +Epoch [38/4000] Training [7/16] Loss: 0.03340 +Epoch [38/4000] Training [8/16] Loss: 0.01948 +Epoch [38/4000] Training [9/16] Loss: 0.01683 +Epoch [38/4000] Training [10/16] Loss: 0.02291 +Epoch [38/4000] Training [11/16] Loss: 0.01817 +Epoch [38/4000] Training [12/16] Loss: 0.02862 +Epoch [38/4000] Training [13/16] Loss: 0.02530 +Epoch [38/4000] Training [14/16] Loss: 0.02081 +Epoch [38/4000] Training [15/16] Loss: 0.02285 +Epoch [38/4000] Training [16/16] Loss: 0.01664 +Epoch [38/4000] Training metric {'Train/mean dice_metric': 0.9846597909927368, 'Train/mean miou_metric': 0.969717264175415, 'Train/mean f1': 0.9819028973579407, 'Train/mean precision': 0.977445662021637, 'Train/mean recall': 0.9864010214805603, 'Train/mean hd95_metric': 2.423445224761963} +Epoch [38/4000] Validation [1/4] Loss: 0.13296 focal_loss 0.06835 dice_loss 0.06461 +Epoch [38/4000] Validation [2/4] Loss: 0.45144 focal_loss 0.21895 dice_loss 0.23249 +Epoch [38/4000] Validation [3/4] Loss: 0.17253 focal_loss 0.09560 dice_loss 0.07693 +Epoch [38/4000] Validation [4/4] Loss: 0.25213 focal_loss 0.12115 dice_loss 0.13097 +Epoch [38/4000] Validation metric {'Val/mean dice_metric': 0.9610006213188171, 'Val/mean miou_metric': 0.9356487393379211, 'Val/mean f1': 0.9631943106651306, 'Val/mean precision': 0.9574529528617859, 'Val/mean recall': 0.9690050482749939, 'Val/mean hd95_metric': 6.9348907470703125} +Cheakpoint... +Epoch [38/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9610], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610006213188171, 'Val/mean miou_metric': 0.9356487393379211, 'Val/mean f1': 0.9631943106651306, 'Val/mean precision': 0.9574529528617859, 'Val/mean recall': 0.9690050482749939, 'Val/mean hd95_metric': 6.9348907470703125} +Epoch [39/4000] Training [1/16] Loss: 0.02420 +Epoch [39/4000] Training [2/16] Loss: 0.02019 +Epoch [39/4000] Training [3/16] Loss: 0.01697 +Epoch [39/4000] Training [4/16] Loss: 0.02420 +Epoch [39/4000] Training [5/16] Loss: 0.01787 +Epoch [39/4000] Training [6/16] Loss: 0.03829 +Epoch [39/4000] Training [7/16] Loss: 0.03714 +Epoch [39/4000] Training [8/16] Loss: 0.02041 +Epoch [39/4000] Training [9/16] Loss: 0.02544 +Epoch [39/4000] Training [10/16] Loss: 0.02082 +Epoch [39/4000] Training [11/16] Loss: 0.01813 +Epoch [39/4000] Training [12/16] Loss: 0.02292 +Epoch [39/4000] Training [13/16] Loss: 0.02010 +Epoch [39/4000] Training [14/16] Loss: 0.02589 +Epoch [39/4000] Training [15/16] Loss: 0.02787 +Epoch [39/4000] Training [16/16] Loss: 0.02465 +Epoch [39/4000] Training metric {'Train/mean dice_metric': 0.9834027290344238, 'Train/mean miou_metric': 0.9673820734024048, 'Train/mean f1': 0.9801567792892456, 'Train/mean precision': 0.9757961630821228, 'Train/mean recall': 0.9845564961433411, 'Train/mean hd95_metric': 3.056154727935791} +Epoch [39/4000] Validation [1/4] Loss: 0.22777 focal_loss 0.12180 dice_loss 0.10597 +Epoch [39/4000] Validation [2/4] Loss: 0.38492 focal_loss 0.17311 dice_loss 0.21180 +Epoch [39/4000] Validation [3/4] Loss: 0.18580 focal_loss 0.09080 dice_loss 0.09500 +Epoch [39/4000] Validation [4/4] Loss: 0.19499 focal_loss 0.07768 dice_loss 0.11732 +Epoch [39/4000] Validation metric {'Val/mean dice_metric': 0.9582322835922241, 'Val/mean miou_metric': 0.9313774108886719, 'Val/mean f1': 0.9593586921691895, 'Val/mean precision': 0.9580625891685486, 'Val/mean recall': 0.9606582522392273, 'Val/mean hd95_metric': 7.8468828201293945} +Cheakpoint... +Epoch [39/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9582], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9582322835922241, 'Val/mean miou_metric': 0.9313774108886719, 'Val/mean f1': 0.9593586921691895, 'Val/mean precision': 0.9580625891685486, 'Val/mean recall': 0.9606582522392273, 'Val/mean hd95_metric': 7.8468828201293945} +Epoch [40/4000] Training [1/16] Loss: 0.01897 +Epoch [40/4000] Training [2/16] Loss: 0.02464 +Epoch [40/4000] Training [3/16] Loss: 0.02365 +Epoch [40/4000] Training [4/16] Loss: 0.02193 +Epoch [40/4000] Training [5/16] Loss: 0.02902 +Epoch [40/4000] Training [6/16] Loss: 0.01973 +Epoch [40/4000] Training [7/16] Loss: 0.03282 +Epoch [40/4000] Training [8/16] Loss: 0.02969 +Epoch [40/4000] Training [9/16] Loss: 0.03927 +Epoch [40/4000] Training [10/16] Loss: 0.02418 +Epoch [40/4000] Training [11/16] Loss: 0.04027 +Epoch [40/4000] Training [12/16] Loss: 0.02571 +Epoch [40/4000] Training [13/16] Loss: 0.02994 +Epoch [40/4000] Training [14/16] Loss: 0.05587 +Epoch [40/4000] Training [15/16] Loss: 0.02935 +Epoch [40/4000] Training [16/16] Loss: 0.03010 +Epoch [40/4000] Training metric {'Train/mean dice_metric': 0.979894757270813, 'Train/mean miou_metric': 0.9609674215316772, 'Train/mean f1': 0.9780338406562805, 'Train/mean precision': 0.9744903445243835, 'Train/mean recall': 0.9816031455993652, 'Train/mean hd95_metric': 5.399357795715332} +Epoch [40/4000] Validation [1/4] Loss: 0.14665 focal_loss 0.07771 dice_loss 0.06894 +Epoch [40/4000] Validation [2/4] Loss: 0.32258 focal_loss 0.10628 dice_loss 0.21630 +Epoch [40/4000] Validation [3/4] Loss: 0.17648 focal_loss 0.09018 dice_loss 0.08629 +Epoch [40/4000] Validation [4/4] Loss: 0.24189 focal_loss 0.09780 dice_loss 0.14410 +Epoch [40/4000] Validation metric {'Val/mean dice_metric': 0.9564393758773804, 'Val/mean miou_metric': 0.9281167984008789, 'Val/mean f1': 0.9581695199012756, 'Val/mean precision': 0.9503470063209534, 'Val/mean recall': 0.9661219120025635, 'Val/mean hd95_metric': 10.27471923828125} +Cheakpoint... +Epoch [40/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9564], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9564393758773804, 'Val/mean miou_metric': 0.9281167984008789, 'Val/mean f1': 0.9581695199012756, 'Val/mean precision': 0.9503470063209534, 'Val/mean recall': 0.9661219120025635, 'Val/mean hd95_metric': 10.27471923828125} +Epoch [41/4000] Training [1/16] Loss: 0.02816 +Epoch [41/4000] Training [2/16] Loss: 0.02139 +Epoch [41/4000] Training [3/16] Loss: 0.02487 +Epoch [41/4000] Training [4/16] Loss: 0.03641 +Epoch [41/4000] Training [5/16] Loss: 0.03845 +Epoch [41/4000] Training [6/16] Loss: 0.02702 +Epoch [41/4000] Training [7/16] Loss: 0.02377 +Epoch [41/4000] Training [8/16] Loss: 0.02704 +Epoch [41/4000] Training [9/16] Loss: 0.02806 +Epoch [41/4000] Training [10/16] Loss: 0.02827 +Epoch [41/4000] Training [11/16] Loss: 0.01902 +Epoch [41/4000] Training [12/16] Loss: 0.02932 +Epoch [41/4000] Training [13/16] Loss: 0.01883 +Epoch [41/4000] Training [14/16] Loss: 0.02507 +Epoch [41/4000] Training [15/16] Loss: 0.02629 +Epoch [41/4000] Training [16/16] Loss: 0.01878 +Epoch [41/4000] Training metric {'Train/mean dice_metric': 0.9809916019439697, 'Train/mean miou_metric': 0.9630115032196045, 'Train/mean f1': 0.9793183207511902, 'Train/mean precision': 0.9751498103141785, 'Train/mean recall': 0.9835226535797119, 'Train/mean hd95_metric': 5.383827209472656} +Epoch [41/4000] Validation [1/4] Loss: 0.51309 focal_loss 0.38324 dice_loss 0.12985 +Epoch [41/4000] Validation [2/4] Loss: 0.30570 focal_loss 0.09924 dice_loss 0.20646 +Epoch [41/4000] Validation [3/4] Loss: 0.13049 focal_loss 0.05902 dice_loss 0.07147 +Epoch [41/4000] Validation [4/4] Loss: 0.14283 focal_loss 0.05050 dice_loss 0.09234 +Epoch [41/4000] Validation metric {'Val/mean dice_metric': 0.9595519304275513, 'Val/mean miou_metric': 0.9306637644767761, 'Val/mean f1': 0.9599381685256958, 'Val/mean precision': 0.9612908959388733, 'Val/mean recall': 0.9585893154144287, 'Val/mean hd95_metric': 9.15031623840332} +Cheakpoint... +Epoch [41/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9596], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9595519304275513, 'Val/mean miou_metric': 0.9306637644767761, 'Val/mean f1': 0.9599381685256958, 'Val/mean precision': 0.9612908959388733, 'Val/mean recall': 0.9585893154144287, 'Val/mean hd95_metric': 9.15031623840332} +Epoch [42/4000] Training [1/16] Loss: 0.02225 +Epoch [42/4000] Training [2/16] Loss: 0.02448 +Epoch [42/4000] Training [3/16] Loss: 0.02098 +Epoch [42/4000] Training [4/16] Loss: 0.02251 +Epoch [42/4000] Training [5/16] Loss: 0.01971 +Epoch [42/4000] Training [6/16] Loss: 0.02189 +Epoch [42/4000] Training [7/16] Loss: 0.02104 +Epoch [42/4000] Training [8/16] Loss: 0.20695 +Epoch [42/4000] Training [9/16] Loss: 0.02221 +Epoch [42/4000] Training [10/16] Loss: 0.02491 +Epoch [42/4000] Training [11/16] Loss: 0.02788 +Epoch [42/4000] Training [12/16] Loss: 0.02919 +Epoch [42/4000] Training [13/16] Loss: 0.02824 +Epoch [42/4000] Training [14/16] Loss: 0.02365 +Epoch [42/4000] Training [15/16] Loss: 0.02633 +Epoch [42/4000] Training [16/16] Loss: 0.03077 +Epoch [42/4000] Training metric {'Train/mean dice_metric': 0.9771274924278259, 'Train/mean miou_metric': 0.9583451747894287, 'Train/mean f1': 0.9770364165306091, 'Train/mean precision': 0.9714303016662598, 'Train/mean recall': 0.982707679271698, 'Train/mean hd95_metric': 4.776137828826904} +Epoch [42/4000] Validation [1/4] Loss: 0.37395 focal_loss 0.21791 dice_loss 0.15603 +Epoch [42/4000] Validation [2/4] Loss: 0.50214 focal_loss 0.20829 dice_loss 0.29385 +Epoch [42/4000] Validation [3/4] Loss: 0.24146 focal_loss 0.11335 dice_loss 0.12811 +Epoch [42/4000] Validation [4/4] Loss: 0.42453 focal_loss 0.20983 dice_loss 0.21471 +Epoch [42/4000] Validation metric {'Val/mean dice_metric': 0.9446550607681274, 'Val/mean miou_metric': 0.9133847951889038, 'Val/mean f1': 0.9410114884376526, 'Val/mean precision': 0.9222115874290466, 'Val/mean recall': 0.9605938792228699, 'Val/mean hd95_metric': 13.806289672851562} +Cheakpoint... +Epoch [42/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9447], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9446550607681274, 'Val/mean miou_metric': 0.9133847951889038, 'Val/mean f1': 0.9410114884376526, 'Val/mean precision': 0.9222115874290466, 'Val/mean recall': 0.9605938792228699, 'Val/mean hd95_metric': 13.806289672851562} +Epoch [43/4000] Training [1/16] Loss: 0.03672 +Epoch [43/4000] Training [2/16] Loss: 0.06383 +Epoch [43/4000] Training [3/16] Loss: 0.03551 +Epoch [43/4000] Training [4/16] Loss: 0.02793 +Epoch [43/4000] Training [5/16] Loss: 0.03745 +Epoch [43/4000] Training [6/16] Loss: 0.02887 +Epoch [43/4000] Training [7/16] Loss: 0.02634 +Epoch [43/4000] Training [8/16] Loss: 0.03193 +Epoch [43/4000] Training [9/16] Loss: 0.02826 +Epoch [43/4000] Training [10/16] Loss: 0.02904 +Epoch [43/4000] Training [11/16] Loss: 0.02341 +Epoch [43/4000] Training [12/16] Loss: 0.02422 +Epoch [43/4000] Training [13/16] Loss: 0.02983 +Epoch [43/4000] Training [14/16] Loss: 0.03523 +Epoch [43/4000] Training [15/16] Loss: 0.03349 +Epoch [43/4000] Training [16/16] Loss: 0.03698 +Epoch [43/4000] Training metric {'Train/mean dice_metric': 0.9766730070114136, 'Train/mean miou_metric': 0.9554466605186462, 'Train/mean f1': 0.9728453159332275, 'Train/mean precision': 0.9670610427856445, 'Train/mean recall': 0.9786992073059082, 'Train/mean hd95_metric': 7.19862174987793} +Epoch [43/4000] Validation [1/4] Loss: 0.21042 focal_loss 0.11637 dice_loss 0.09405 +Epoch [43/4000] Validation [2/4] Loss: 0.46825 focal_loss 0.17698 dice_loss 0.29127 +Epoch [43/4000] Validation [3/4] Loss: 0.11825 focal_loss 0.04925 dice_loss 0.06899 +Epoch [43/4000] Validation [4/4] Loss: 0.24626 focal_loss 0.09207 dice_loss 0.15419 +Epoch [43/4000] Validation metric {'Val/mean dice_metric': 0.9535828828811646, 'Val/mean miou_metric': 0.923082709312439, 'Val/mean f1': 0.9549083113670349, 'Val/mean precision': 0.9524630308151245, 'Val/mean recall': 0.9573663473129272, 'Val/mean hd95_metric': 11.360363006591797} +Cheakpoint... +Epoch [43/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9536], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9535828828811646, 'Val/mean miou_metric': 0.923082709312439, 'Val/mean f1': 0.9549083113670349, 'Val/mean precision': 0.9524630308151245, 'Val/mean recall': 0.9573663473129272, 'Val/mean hd95_metric': 11.360363006591797} +Epoch [44/4000] Training [1/16] Loss: 0.02834 +Epoch [44/4000] Training [2/16] Loss: 0.02856 +Epoch [44/4000] Training [3/16] Loss: 0.02625 +Epoch [44/4000] Training [4/16] Loss: 0.02117 +Epoch [44/4000] Training [5/16] Loss: 0.02868 +Epoch [44/4000] Training [6/16] Loss: 0.03445 +Epoch [44/4000] Training [7/16] Loss: 0.02536 +Epoch [44/4000] Training [8/16] Loss: 0.02358 +Epoch [44/4000] Training [9/16] Loss: 0.35407 +Epoch [44/4000] Training [10/16] Loss: 0.02541 +Epoch [44/4000] Training [11/16] Loss: 0.07253 +Epoch [44/4000] Training [12/16] Loss: 0.02981 +Epoch [44/4000] Training [13/16] Loss: 0.13047 +Epoch [44/4000] Training [14/16] Loss: 0.03267 +Epoch [44/4000] Training [15/16] Loss: 0.03958 +Epoch [44/4000] Training [16/16] Loss: 0.21931 +Epoch [44/4000] Training metric {'Train/mean dice_metric': 0.9743858575820923, 'Train/mean miou_metric': 0.9528546333312988, 'Train/mean f1': 0.9685032367706299, 'Train/mean precision': 0.9622299671173096, 'Train/mean recall': 0.974858820438385, 'Train/mean hd95_metric': 6.206517696380615} +Epoch [44/4000] Validation [1/4] Loss: 0.20107 focal_loss 0.11726 dice_loss 0.08381 +Epoch [44/4000] Validation [2/4] Loss: 0.42875 focal_loss 0.15645 dice_loss 0.27231 +Epoch [44/4000] Validation [3/4] Loss: 0.25537 focal_loss 0.10843 dice_loss 0.14694 +Epoch [44/4000] Validation [4/4] Loss: 0.38484 focal_loss 0.15487 dice_loss 0.22997 +Epoch [44/4000] Validation metric {'Val/mean dice_metric': 0.9458880424499512, 'Val/mean miou_metric': 0.9139364361763, 'Val/mean f1': 0.9466472268104553, 'Val/mean precision': 0.9350148439407349, 'Val/mean recall': 0.9585726261138916, 'Val/mean hd95_metric': 13.073748588562012} +Cheakpoint... +Epoch [44/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9459], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9458880424499512, 'Val/mean miou_metric': 0.9139364361763, 'Val/mean f1': 0.9466472268104553, 'Val/mean precision': 0.9350148439407349, 'Val/mean recall': 0.9585726261138916, 'Val/mean hd95_metric': 13.073748588562012} +Epoch [45/4000] Training [1/16] Loss: 0.05043 +Epoch [45/4000] Training [2/16] Loss: 0.02779 +Epoch [45/4000] Training [3/16] Loss: 0.02913 +Epoch [45/4000] Training [4/16] Loss: 0.04256 +Epoch [45/4000] Training [5/16] Loss: 0.06782 +Epoch [45/4000] Training [6/16] Loss: 0.05700 +Epoch [45/4000] Training [7/16] Loss: 0.03418 +Epoch [45/4000] Training [8/16] Loss: 0.03316 +Epoch [45/4000] Training [9/16] Loss: 0.16446 +Epoch [45/4000] Training [10/16] Loss: 0.03056 +Epoch [45/4000] Training [11/16] Loss: 0.04047 +Epoch [45/4000] Training [12/16] Loss: 0.03749 +Epoch [45/4000] Training [13/16] Loss: 0.04275 +Epoch [45/4000] Training [14/16] Loss: 0.03109 +Epoch [45/4000] Training [15/16] Loss: 0.03166 +Epoch [45/4000] Training [16/16] Loss: 0.07034 +Epoch [45/4000] Training metric {'Train/mean dice_metric': 0.971576452255249, 'Train/mean miou_metric': 0.947077214717865, 'Train/mean f1': 0.9680727124214172, 'Train/mean precision': 0.9661776423454285, 'Train/mean recall': 0.9699752330780029, 'Train/mean hd95_metric': 8.700387954711914} +Epoch [45/4000] Validation [1/4] Loss: 0.17477 focal_loss 0.08973 dice_loss 0.08504 +Epoch [45/4000] Validation [2/4] Loss: 0.48623 focal_loss 0.20797 dice_loss 0.27825 +Epoch [45/4000] Validation [3/4] Loss: 0.15374 focal_loss 0.06775 dice_loss 0.08599 +Epoch [45/4000] Validation [4/4] Loss: 0.24539 focal_loss 0.08083 dice_loss 0.16455 +Epoch [45/4000] Validation metric {'Val/mean dice_metric': 0.9454137086868286, 'Val/mean miou_metric': 0.9112230539321899, 'Val/mean f1': 0.9433430433273315, 'Val/mean precision': 0.9287844896316528, 'Val/mean recall': 0.9583650827407837, 'Val/mean hd95_metric': 14.679826736450195} +Cheakpoint... +Epoch [45/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9454], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9454137086868286, 'Val/mean miou_metric': 0.9112230539321899, 'Val/mean f1': 0.9433430433273315, 'Val/mean precision': 0.9287844896316528, 'Val/mean recall': 0.9583650827407837, 'Val/mean hd95_metric': 14.679826736450195} +Epoch [46/4000] Training [1/16] Loss: 0.03066 +Epoch [46/4000] Training [2/16] Loss: 0.02322 +Epoch [46/4000] Training [3/16] Loss: 0.03757 +Epoch [46/4000] Training [4/16] Loss: 0.01901 +Epoch [46/4000] Training [5/16] Loss: 0.02914 +Epoch [46/4000] Training [6/16] Loss: 0.02669 +Epoch [46/4000] Training [7/16] Loss: 0.02692 +Epoch [46/4000] Training [8/16] Loss: 0.02717 +Epoch [46/4000] Training [9/16] Loss: 0.02172 +Epoch [46/4000] Training [10/16] Loss: 0.02228 +Epoch [46/4000] Training [11/16] Loss: 0.02810 +Epoch [46/4000] Training [12/16] Loss: 0.06469 +Epoch [46/4000] Training [13/16] Loss: 0.02340 +Epoch [46/4000] Training [14/16] Loss: 0.03114 +Epoch [46/4000] Training [15/16] Loss: 0.03542 +Epoch [46/4000] Training [16/16] Loss: 0.02787 +Epoch [46/4000] Training metric {'Train/mean dice_metric': 0.9795347452163696, 'Train/mean miou_metric': 0.9601182341575623, 'Train/mean f1': 0.977266252040863, 'Train/mean precision': 0.9712846279144287, 'Train/mean recall': 0.983322024345398, 'Train/mean hd95_metric': 4.420291900634766} +Epoch [46/4000] Validation [1/4] Loss: 0.39442 focal_loss 0.26715 dice_loss 0.12727 +Epoch [46/4000] Validation [2/4] Loss: 0.46107 focal_loss 0.25508 dice_loss 0.20599 +Epoch [46/4000] Validation [3/4] Loss: 0.22078 focal_loss 0.11962 dice_loss 0.10116 +Epoch [46/4000] Validation [4/4] Loss: 0.24746 focal_loss 0.10887 dice_loss 0.13859 +Epoch [46/4000] Validation metric {'Val/mean dice_metric': 0.9565423130989075, 'Val/mean miou_metric': 0.9266821146011353, 'Val/mean f1': 0.9569278359413147, 'Val/mean precision': 0.9550793170928955, 'Val/mean recall': 0.9587836861610413, 'Val/mean hd95_metric': 9.398416519165039} +Cheakpoint... +Epoch [46/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9565], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9565423130989075, 'Val/mean miou_metric': 0.9266821146011353, 'Val/mean f1': 0.9569278359413147, 'Val/mean precision': 0.9550793170928955, 'Val/mean recall': 0.9587836861610413, 'Val/mean hd95_metric': 9.398416519165039} +Epoch [47/4000] Training [1/16] Loss: 0.03292 +Epoch [47/4000] Training [2/16] Loss: 0.03197 +Epoch [47/4000] Training [3/16] Loss: 0.02552 +Epoch [47/4000] Training [4/16] Loss: 0.02915 +Epoch [47/4000] Training [5/16] Loss: 0.03241 +Epoch [47/4000] Training [6/16] Loss: 0.02014 +Epoch [47/4000] Training [7/16] Loss: 0.03560 +Epoch [47/4000] Training [8/16] Loss: 0.02377 +Epoch [47/4000] Training [9/16] Loss: 0.02653 +Epoch [47/4000] Training [10/16] Loss: 0.08601 +Epoch [47/4000] Training [11/16] Loss: 0.02388 +Epoch [47/4000] Training [12/16] Loss: 0.02916 +Epoch [47/4000] Training [13/16] Loss: 0.02171 +Epoch [47/4000] Training [14/16] Loss: 0.02432 +Epoch [47/4000] Training [15/16] Loss: 0.03422 +Epoch [47/4000] Training [16/16] Loss: 0.03431 +Epoch [47/4000] Training metric {'Train/mean dice_metric': 0.9790241718292236, 'Train/mean miou_metric': 0.9595351219177246, 'Train/mean f1': 0.9781656265258789, 'Train/mean precision': 0.9721654057502747, 'Train/mean recall': 0.9842404127120972, 'Train/mean hd95_metric': 4.01828145980835} +Epoch [47/4000] Validation [1/4] Loss: 0.45156 focal_loss 0.32306 dice_loss 0.12850 +Epoch [47/4000] Validation [2/4] Loss: 0.46107 focal_loss 0.25865 dice_loss 0.20242 +Epoch [47/4000] Validation [3/4] Loss: 0.17627 focal_loss 0.07029 dice_loss 0.10597 +Epoch [47/4000] Validation [4/4] Loss: 0.35749 focal_loss 0.16837 dice_loss 0.18912 +Epoch [47/4000] Validation metric {'Val/mean dice_metric': 0.9536131024360657, 'Val/mean miou_metric': 0.9229593276977539, 'Val/mean f1': 0.9548865556716919, 'Val/mean precision': 0.9482313990592957, 'Val/mean recall': 0.9616357088088989, 'Val/mean hd95_metric': 10.280405044555664} +Cheakpoint... +Epoch [47/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9536], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9536131024360657, 'Val/mean miou_metric': 0.9229593276977539, 'Val/mean f1': 0.9548865556716919, 'Val/mean precision': 0.9482313990592957, 'Val/mean recall': 0.9616357088088989, 'Val/mean hd95_metric': 10.280405044555664} +Epoch [48/4000] Training [1/16] Loss: 0.02208 +Epoch [48/4000] Training [2/16] Loss: 0.02949 +Epoch [48/4000] Training [3/16] Loss: 0.02377 +Epoch [48/4000] Training [4/16] Loss: 0.02477 +Epoch [48/4000] Training [5/16] Loss: 0.02874 +Epoch [48/4000] Training [6/16] Loss: 0.02472 +Epoch [48/4000] Training [7/16] Loss: 0.02270 +Epoch [48/4000] Training [8/16] Loss: 0.02181 +Epoch [48/4000] Training [9/16] Loss: 0.02251 +Epoch [48/4000] Training [10/16] Loss: 0.02686 +Epoch [48/4000] Training [11/16] Loss: 0.01965 +Epoch [48/4000] Training [12/16] Loss: 0.02357 +Epoch [48/4000] Training [13/16] Loss: 0.02445 +Epoch [48/4000] Training [14/16] Loss: 0.01994 +Epoch [48/4000] Training [15/16] Loss: 0.02247 +Epoch [48/4000] Training [16/16] Loss: 0.01971 +Epoch [48/4000] Training metric {'Train/mean dice_metric': 0.9813405275344849, 'Train/mean miou_metric': 0.9641115665435791, 'Train/mean f1': 0.9798557162284851, 'Train/mean precision': 0.9762188196182251, 'Train/mean recall': 0.9835197925567627, 'Train/mean hd95_metric': 3.0691871643066406} +Epoch [48/4000] Validation [1/4] Loss: 0.13699 focal_loss 0.07414 dice_loss 0.06285 +Epoch [48/4000] Validation [2/4] Loss: 0.21681 focal_loss 0.06592 dice_loss 0.15089 +Epoch [48/4000] Validation [3/4] Loss: 0.12826 focal_loss 0.05708 dice_loss 0.07117 +Epoch [48/4000] Validation [4/4] Loss: 0.24413 focal_loss 0.09913 dice_loss 0.14500 +Epoch [48/4000] Validation metric {'Val/mean dice_metric': 0.9599447250366211, 'Val/mean miou_metric': 0.9323955774307251, 'Val/mean f1': 0.9628055691719055, 'Val/mean precision': 0.9579311013221741, 'Val/mean recall': 0.967729926109314, 'Val/mean hd95_metric': 7.790093898773193} +Cheakpoint... +Epoch [48/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599447250366211, 'Val/mean miou_metric': 0.9323955774307251, 'Val/mean f1': 0.9628055691719055, 'Val/mean precision': 0.9579311013221741, 'Val/mean recall': 0.967729926109314, 'Val/mean hd95_metric': 7.790093898773193} +Epoch [49/4000] Training [1/16] Loss: 0.03275 +Epoch [49/4000] Training [2/16] Loss: 0.02045 +Epoch [49/4000] Training [3/16] Loss: 0.02452 +Epoch [49/4000] Training [4/16] Loss: 0.02170 +Epoch [49/4000] Training [5/16] Loss: 0.01964 +Epoch [49/4000] Training [6/16] Loss: 0.01931 +Epoch [49/4000] Training [7/16] Loss: 0.02415 +Epoch [49/4000] Training [8/16] Loss: 0.02048 +Epoch [49/4000] Training [9/16] Loss: 0.02423 +Epoch [49/4000] Training [10/16] Loss: 0.02044 +Epoch [49/4000] Training [11/16] Loss: 0.01360 +Epoch [49/4000] Training [12/16] Loss: 0.01846 +Epoch [49/4000] Training [13/16] Loss: 0.04136 +Epoch [49/4000] Training [14/16] Loss: 0.04782 +Epoch [49/4000] Training [15/16] Loss: 0.02644 +Epoch [49/4000] Training [16/16] Loss: 0.02213 +Epoch [49/4000] Training metric {'Train/mean dice_metric': 0.9837550520896912, 'Train/mean miou_metric': 0.9680492877960205, 'Train/mean f1': 0.9820743799209595, 'Train/mean precision': 0.9773545265197754, 'Train/mean recall': 0.9868400692939758, 'Train/mean hd95_metric': 3.0866458415985107} +Epoch [49/4000] Validation [1/4] Loss: 0.13903 focal_loss 0.07615 dice_loss 0.06288 +Epoch [49/4000] Validation [2/4] Loss: 0.16615 focal_loss 0.05652 dice_loss 0.10963 +Epoch [49/4000] Validation [3/4] Loss: 0.15905 focal_loss 0.07562 dice_loss 0.08343 +Epoch [49/4000] Validation [4/4] Loss: 0.37863 focal_loss 0.17937 dice_loss 0.19926 +Epoch [49/4000] Validation metric {'Val/mean dice_metric': 0.9602198600769043, 'Val/mean miou_metric': 0.9336128234863281, 'Val/mean f1': 0.9635868072509766, 'Val/mean precision': 0.9543687701225281, 'Val/mean recall': 0.9729846119880676, 'Val/mean hd95_metric': 9.853362083435059} +Cheakpoint... +Epoch [49/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9602], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9602198600769043, 'Val/mean miou_metric': 0.9336128234863281, 'Val/mean f1': 0.9635868072509766, 'Val/mean precision': 0.9543687701225281, 'Val/mean recall': 0.9729846119880676, 'Val/mean hd95_metric': 9.853362083435059} +Epoch [50/4000] Training [1/16] Loss: 0.02272 +Epoch [50/4000] Training [2/16] Loss: 0.02268 +Epoch [50/4000] Training [3/16] Loss: 0.03868 +Epoch [50/4000] Training [4/16] Loss: 0.02882 +Epoch [50/4000] Training [5/16] Loss: 0.01858 +Epoch [50/4000] Training [6/16] Loss: 0.03440 +Epoch [50/4000] Training [7/16] Loss: 0.02021 +Epoch [50/4000] Training [8/16] Loss: 0.01898 +Epoch [50/4000] Training [9/16] Loss: 0.01879 +Epoch [50/4000] Training [10/16] Loss: 0.03449 +Epoch [50/4000] Training [11/16] Loss: 0.01740 +Epoch [50/4000] Training [12/16] Loss: 0.02680 +Epoch [50/4000] Training [13/16] Loss: 0.03976 +Epoch [50/4000] Training [14/16] Loss: 0.04569 +Epoch [50/4000] Training [15/16] Loss: 0.02360 +Epoch [50/4000] Training [16/16] Loss: 0.01731 +Epoch [50/4000] Training metric {'Train/mean dice_metric': 0.9822553396224976, 'Train/mean miou_metric': 0.9654785394668579, 'Train/mean f1': 0.9806804656982422, 'Train/mean precision': 0.976898193359375, 'Train/mean recall': 0.9844921231269836, 'Train/mean hd95_metric': 3.898189067840576} +Epoch [50/4000] Validation [1/4] Loss: 0.19061 focal_loss 0.10811 dice_loss 0.08251 +Epoch [50/4000] Validation [2/4] Loss: 0.20610 focal_loss 0.06488 dice_loss 0.14122 +Epoch [50/4000] Validation [3/4] Loss: 0.14583 focal_loss 0.06535 dice_loss 0.08049 +Epoch [50/4000] Validation [4/4] Loss: 0.19339 focal_loss 0.05944 dice_loss 0.13394 +Epoch [50/4000] Validation metric {'Val/mean dice_metric': 0.9555803537368774, 'Val/mean miou_metric': 0.9278785586357117, 'Val/mean f1': 0.9597816467285156, 'Val/mean precision': 0.9573005437850952, 'Val/mean recall': 0.9622756242752075, 'Val/mean hd95_metric': 9.00847053527832} +Cheakpoint... +Epoch [50/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9556], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9555803537368774, 'Val/mean miou_metric': 0.9278785586357117, 'Val/mean f1': 0.9597816467285156, 'Val/mean precision': 0.9573005437850952, 'Val/mean recall': 0.9622756242752075, 'Val/mean hd95_metric': 9.00847053527832} +Epoch [51/4000] Training [1/16] Loss: 0.01816 +Epoch [51/4000] Training [2/16] Loss: 0.02737 +Epoch [51/4000] Training [3/16] Loss: 0.01928 +Epoch [51/4000] Training [4/16] Loss: 0.03117 +Epoch [51/4000] Training [5/16] Loss: 0.02402 +Epoch [51/4000] Training [6/16] Loss: 0.01727 +Epoch [51/4000] Training [7/16] Loss: 0.05016 +Epoch [51/4000] Training [8/16] Loss: 0.01994 +Epoch [51/4000] Training [9/16] Loss: 0.02359 +Epoch [51/4000] Training [10/16] Loss: 0.02328 +Epoch [51/4000] Training [11/16] Loss: 0.03331 +Epoch [51/4000] Training [12/16] Loss: 0.02490 +Epoch [51/4000] Training [13/16] Loss: 0.06389 +Epoch [51/4000] Training [14/16] Loss: 0.01911 +Epoch [51/4000] Training [15/16] Loss: 0.02080 +Epoch [51/4000] Training [16/16] Loss: 0.02580 +Epoch [51/4000] Training metric {'Train/mean dice_metric': 0.9817407131195068, 'Train/mean miou_metric': 0.9647022485733032, 'Train/mean f1': 0.9800078868865967, 'Train/mean precision': 0.9755431413650513, 'Train/mean recall': 0.9845136404037476, 'Train/mean hd95_metric': 3.3591058254241943} +Epoch [51/4000] Validation [1/4] Loss: 0.19909 focal_loss 0.12410 dice_loss 0.07499 +Epoch [51/4000] Validation [2/4] Loss: 0.39853 focal_loss 0.19540 dice_loss 0.20313 +Epoch [51/4000] Validation [3/4] Loss: 0.22867 focal_loss 0.12219 dice_loss 0.10648 +Epoch [51/4000] Validation [4/4] Loss: 0.30705 focal_loss 0.14293 dice_loss 0.16412 +Epoch [51/4000] Validation metric {'Val/mean dice_metric': 0.9584514498710632, 'Val/mean miou_metric': 0.9295334815979004, 'Val/mean f1': 0.9602752923965454, 'Val/mean precision': 0.9548864960670471, 'Val/mean recall': 0.965725302696228, 'Val/mean hd95_metric': 9.002585411071777} +Cheakpoint... +Epoch [51/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9585], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9584514498710632, 'Val/mean miou_metric': 0.9295334815979004, 'Val/mean f1': 0.9602752923965454, 'Val/mean precision': 0.9548864960670471, 'Val/mean recall': 0.965725302696228, 'Val/mean hd95_metric': 9.002585411071777} +Epoch [52/4000] Training [1/16] Loss: 0.01700 +Epoch [52/4000] Training [2/16] Loss: 0.02866 +Epoch [52/4000] Training [3/16] Loss: 0.02315 +Epoch [52/4000] Training [4/16] Loss: 0.02375 +Epoch [52/4000] Training [5/16] Loss: 0.02248 +Epoch [52/4000] Training [6/16] Loss: 0.03525 +Epoch [52/4000] Training [7/16] Loss: 0.01835 +Epoch [52/4000] Training [8/16] Loss: 0.02240 +Epoch [52/4000] Training [9/16] Loss: 0.02381 +Epoch [52/4000] Training [10/16] Loss: 0.02177 +Epoch [52/4000] Training [11/16] Loss: 0.01766 +Epoch [52/4000] Training [12/16] Loss: 0.03189 +Epoch [52/4000] Training [13/16] Loss: 0.02971 +Epoch [52/4000] Training [14/16] Loss: 0.02532 +Epoch [52/4000] Training [15/16] Loss: 0.03251 +Epoch [52/4000] Training [16/16] Loss: 0.06970 +Epoch [52/4000] Training metric {'Train/mean dice_metric': 0.9807103872299194, 'Train/mean miou_metric': 0.962756335735321, 'Train/mean f1': 0.9777832627296448, 'Train/mean precision': 0.9729855060577393, 'Train/mean recall': 0.9826285243034363, 'Train/mean hd95_metric': 4.854238986968994} +Epoch [52/4000] Validation [1/4] Loss: 0.42541 focal_loss 0.29800 dice_loss 0.12741 +Epoch [52/4000] Validation [2/4] Loss: 0.21324 focal_loss 0.08141 dice_loss 0.13183 +Epoch [52/4000] Validation [3/4] Loss: 0.19166 focal_loss 0.09402 dice_loss 0.09764 +Epoch [52/4000] Validation [4/4] Loss: 0.21295 focal_loss 0.08814 dice_loss 0.12482 +Epoch [52/4000] Validation metric {'Val/mean dice_metric': 0.9536784887313843, 'Val/mean miou_metric': 0.9238866567611694, 'Val/mean f1': 0.9540278315544128, 'Val/mean precision': 0.9535019993782043, 'Val/mean recall': 0.9545542597770691, 'Val/mean hd95_metric': 10.43079662322998} +Cheakpoint... +Epoch [52/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9537], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9536784887313843, 'Val/mean miou_metric': 0.9238866567611694, 'Val/mean f1': 0.9540278315544128, 'Val/mean precision': 0.9535019993782043, 'Val/mean recall': 0.9545542597770691, 'Val/mean hd95_metric': 10.43079662322998} +Epoch [53/4000] Training [1/16] Loss: 0.02652 +Epoch [53/4000] Training [2/16] Loss: 0.02250 +Epoch [53/4000] Training [3/16] Loss: 0.02857 +Epoch [53/4000] Training [4/16] Loss: 0.02145 +Epoch [53/4000] Training [5/16] Loss: 0.05201 +Epoch [53/4000] Training [6/16] Loss: 0.01900 +Epoch [53/4000] Training [7/16] Loss: 0.02022 +Epoch [53/4000] Training [8/16] Loss: 0.03081 +Epoch [53/4000] Training [9/16] Loss: 0.03408 +Epoch [53/4000] Training [10/16] Loss: 0.05103 +Epoch [53/4000] Training [11/16] Loss: 0.03367 +Epoch [53/4000] Training [12/16] Loss: 0.02643 +Epoch [53/4000] Training [13/16] Loss: 0.01935 +Epoch [53/4000] Training [14/16] Loss: 0.02101 +Epoch [53/4000] Training [15/16] Loss: 0.02527 +Epoch [53/4000] Training [16/16] Loss: 0.03325 +Epoch [53/4000] Training metric {'Train/mean dice_metric': 0.9812314510345459, 'Train/mean miou_metric': 0.96346515417099, 'Train/mean f1': 0.9791480898857117, 'Train/mean precision': 0.9747803807258606, 'Train/mean recall': 0.9835550785064697, 'Train/mean hd95_metric': 4.831901550292969} +Epoch [53/4000] Validation [1/4] Loss: 0.18190 focal_loss 0.09806 dice_loss 0.08385 +Epoch [53/4000] Validation [2/4] Loss: 0.53688 focal_loss 0.29083 dice_loss 0.24605 +Epoch [53/4000] Validation [3/4] Loss: 0.14047 focal_loss 0.05358 dice_loss 0.08688 +Epoch [53/4000] Validation [4/4] Loss: 0.25227 focal_loss 0.11272 dice_loss 0.13955 +Epoch [53/4000] Validation metric {'Val/mean dice_metric': 0.953277587890625, 'Val/mean miou_metric': 0.9237937927246094, 'Val/mean f1': 0.9583245515823364, 'Val/mean precision': 0.9569457173347473, 'Val/mean recall': 0.9597074389457703, 'Val/mean hd95_metric': 10.444390296936035} +Cheakpoint... +Epoch [53/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9533], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.953277587890625, 'Val/mean miou_metric': 0.9237937927246094, 'Val/mean f1': 0.9583245515823364, 'Val/mean precision': 0.9569457173347473, 'Val/mean recall': 0.9597074389457703, 'Val/mean hd95_metric': 10.444390296936035} +Epoch [54/4000] Training [1/16] Loss: 0.02705 +Epoch [54/4000] Training [2/16] Loss: 0.03354 +Epoch [54/4000] Training [3/16] Loss: 0.01824 +Epoch [54/4000] Training [4/16] Loss: 0.20064 +Epoch [54/4000] Training [5/16] Loss: 0.01768 +Epoch [54/4000] Training [6/16] Loss: 0.02231 +Epoch [54/4000] Training [7/16] Loss: 0.02578 +Epoch [54/4000] Training [8/16] Loss: 0.02666 +Epoch [54/4000] Training [9/16] Loss: 0.02222 +Epoch [54/4000] Training [10/16] Loss: 0.02780 +Epoch [54/4000] Training [11/16] Loss: 0.02488 +Epoch [54/4000] Training [12/16] Loss: 0.02632 +Epoch [54/4000] Training [13/16] Loss: 0.02307 +Epoch [54/4000] Training [14/16] Loss: 0.04139 +Epoch [54/4000] Training [15/16] Loss: 0.03524 +Epoch [54/4000] Training [16/16] Loss: 0.03099 +Epoch [54/4000] Training metric {'Train/mean dice_metric': 0.9778860211372375, 'Train/mean miou_metric': 0.9575703144073486, 'Train/mean f1': 0.9762333035469055, 'Train/mean precision': 0.9721075296401978, 'Train/mean recall': 0.9803943037986755, 'Train/mean hd95_metric': 5.416258335113525} +Epoch [54/4000] Validation [1/4] Loss: 0.13198 focal_loss 0.06724 dice_loss 0.06474 +Epoch [54/4000] Validation [2/4] Loss: 0.30981 focal_loss 0.10248 dice_loss 0.20733 +Epoch [54/4000] Validation [3/4] Loss: 0.17848 focal_loss 0.07676 dice_loss 0.10172 +Epoch [54/4000] Validation [4/4] Loss: 0.21319 focal_loss 0.08189 dice_loss 0.13130 +Epoch [54/4000] Validation metric {'Val/mean dice_metric': 0.9539110064506531, 'Val/mean miou_metric': 0.9232221841812134, 'Val/mean f1': 0.9592956304550171, 'Val/mean precision': 0.9531261920928955, 'Val/mean recall': 0.9655454158782959, 'Val/mean hd95_metric': 10.699708938598633} +Cheakpoint... +Epoch [54/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9539], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9539110064506531, 'Val/mean miou_metric': 0.9232221841812134, 'Val/mean f1': 0.9592956304550171, 'Val/mean precision': 0.9531261920928955, 'Val/mean recall': 0.9655454158782959, 'Val/mean hd95_metric': 10.699708938598633} +Epoch [55/4000] Training [1/16] Loss: 0.04668 +Epoch [55/4000] Training [2/16] Loss: 0.02581 +Epoch [55/4000] Training [3/16] Loss: 0.02710 +Epoch [55/4000] Training [4/16] Loss: 0.04049 +Epoch [55/4000] Training [5/16] Loss: 0.02351 +Epoch [55/4000] Training [6/16] Loss: 0.03820 +Epoch [55/4000] Training [7/16] Loss: 0.02311 +Epoch [55/4000] Training [8/16] Loss: 0.02385 +Epoch [55/4000] Training [9/16] Loss: 0.02202 +Epoch [55/4000] Training [10/16] Loss: 0.02795 +Epoch [55/4000] Training [11/16] Loss: 0.02405 +Epoch [55/4000] Training [12/16] Loss: 0.02313 +Epoch [55/4000] Training [13/16] Loss: 0.02432 +Epoch [55/4000] Training [14/16] Loss: 0.02578 +Epoch [55/4000] Training [15/16] Loss: 0.03012 +Epoch [55/4000] Training [16/16] Loss: 0.02133 +Epoch [55/4000] Training metric {'Train/mean dice_metric': 0.9792530536651611, 'Train/mean miou_metric': 0.9600343704223633, 'Train/mean f1': 0.9775192141532898, 'Train/mean precision': 0.9726588726043701, 'Train/mean recall': 0.9824284315109253, 'Train/mean hd95_metric': 3.962468147277832} +Epoch [55/4000] Validation [1/4] Loss: 0.13199 focal_loss 0.07107 dice_loss 0.06092 +Epoch [55/4000] Validation [2/4] Loss: 0.34807 focal_loss 0.17250 dice_loss 0.17557 +Epoch [55/4000] Validation [3/4] Loss: 0.19563 focal_loss 0.08414 dice_loss 0.11149 +Epoch [55/4000] Validation [4/4] Loss: 0.29206 focal_loss 0.13657 dice_loss 0.15550 +Epoch [55/4000] Validation metric {'Val/mean dice_metric': 0.9548184275627136, 'Val/mean miou_metric': 0.9239503741264343, 'Val/mean f1': 0.9560479521751404, 'Val/mean precision': 0.9469026923179626, 'Val/mean recall': 0.9653715491294861, 'Val/mean hd95_metric': 9.439275741577148} +Cheakpoint... +Epoch [55/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9548], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9548184275627136, 'Val/mean miou_metric': 0.9239503741264343, 'Val/mean f1': 0.9560479521751404, 'Val/mean precision': 0.9469026923179626, 'Val/mean recall': 0.9653715491294861, 'Val/mean hd95_metric': 9.439275741577148} +Epoch [56/4000] Training [1/16] Loss: 0.02490 +Epoch [56/4000] Training [2/16] Loss: 0.02335 +Epoch [56/4000] Training [3/16] Loss: 0.03008 +Epoch [56/4000] Training [4/16] Loss: 0.02405 +Epoch [56/4000] Training [5/16] Loss: 0.04233 +Epoch [56/4000] Training [6/16] Loss: 0.02983 +Epoch [56/4000] Training [7/16] Loss: 0.02026 +Epoch [56/4000] Training [8/16] Loss: 0.02546 +Epoch [56/4000] Training [9/16] Loss: 0.02205 +Epoch [56/4000] Training [10/16] Loss: 0.02097 +Epoch [56/4000] Training [11/16] Loss: 0.02862 +Epoch [56/4000] Training [12/16] Loss: 0.02994 +Epoch [56/4000] Training [13/16] Loss: 0.04909 +Epoch [56/4000] Training [14/16] Loss: 0.01929 +Epoch [56/4000] Training [15/16] Loss: 0.05356 +Epoch [56/4000] Training [16/16] Loss: 0.02947 +Epoch [56/4000] Training metric {'Train/mean dice_metric': 0.979120671749115, 'Train/mean miou_metric': 0.9602179527282715, 'Train/mean f1': 0.9792265295982361, 'Train/mean precision': 0.9741573333740234, 'Train/mean recall': 0.9843487739562988, 'Train/mean hd95_metric': 4.387283802032471} +Epoch [56/4000] Validation [1/4] Loss: 0.21605 focal_loss 0.12674 dice_loss 0.08931 +Epoch [56/4000] Validation [2/4] Loss: 0.42728 focal_loss 0.23405 dice_loss 0.19323 +Epoch [56/4000] Validation [3/4] Loss: 0.13674 focal_loss 0.05843 dice_loss 0.07830 +Epoch [56/4000] Validation [4/4] Loss: 0.26318 focal_loss 0.13580 dice_loss 0.12738 +Epoch [56/4000] Validation metric {'Val/mean dice_metric': 0.9524677395820618, 'Val/mean miou_metric': 0.9221410751342773, 'Val/mean f1': 0.9556536078453064, 'Val/mean precision': 0.9494031667709351, 'Val/mean recall': 0.9619868993759155, 'Val/mean hd95_metric': 10.399368286132812} +Cheakpoint... +Epoch [56/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9525], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9524677395820618, 'Val/mean miou_metric': 0.9221410751342773, 'Val/mean f1': 0.9556536078453064, 'Val/mean precision': 0.9494031667709351, 'Val/mean recall': 0.9619868993759155, 'Val/mean hd95_metric': 10.399368286132812} +Epoch [57/4000] Training [1/16] Loss: 0.04010 +Epoch [57/4000] Training [2/16] Loss: 0.01921 +Epoch [57/4000] Training [3/16] Loss: 0.02674 +Epoch [57/4000] Training [4/16] Loss: 0.02416 +Epoch [57/4000] Training [5/16] Loss: 0.03582 +Epoch [57/4000] Training [6/16] Loss: 0.02139 +Epoch [57/4000] Training [7/16] Loss: 0.03582 +Epoch [57/4000] Training [8/16] Loss: 0.08051 +Epoch [57/4000] Training [9/16] Loss: 0.02086 +Epoch [57/4000] Training [10/16] Loss: 0.02856 +Epoch [57/4000] Training [11/16] Loss: 0.02519 +Epoch [57/4000] Training [12/16] Loss: 0.13111 +Epoch [57/4000] Training [13/16] Loss: 0.02742 +Epoch [57/4000] Training [14/16] Loss: 0.17847 +Epoch [57/4000] Training [15/16] Loss: 0.02587 +Epoch [57/4000] Training [16/16] Loss: 0.03115 +Epoch [57/4000] Training metric {'Train/mean dice_metric': 0.9734290838241577, 'Train/mean miou_metric': 0.9536965489387512, 'Train/mean f1': 0.9765410423278809, 'Train/mean precision': 0.9725428223609924, 'Train/mean recall': 0.9805723428726196, 'Train/mean hd95_metric': 6.2332024574279785} +Epoch [57/4000] Validation [1/4] Loss: 0.17621 focal_loss 0.06909 dice_loss 0.10712 +Epoch [57/4000] Validation [2/4] Loss: 0.49748 focal_loss 0.17628 dice_loss 0.32120 +Epoch [57/4000] Validation [3/4] Loss: 0.14852 focal_loss 0.06479 dice_loss 0.08373 +Epoch [57/4000] Validation [4/4] Loss: 0.21674 focal_loss 0.06847 dice_loss 0.14827 +Epoch [57/4000] Validation metric {'Val/mean dice_metric': 0.9402718544006348, 'Val/mean miou_metric': 0.9098308682441711, 'Val/mean f1': 0.953550398349762, 'Val/mean precision': 0.9564480185508728, 'Val/mean recall': 0.9506701827049255, 'Val/mean hd95_metric': 11.492883682250977} +Cheakpoint... +Epoch [57/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9403], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9402718544006348, 'Val/mean miou_metric': 0.9098308682441711, 'Val/mean f1': 0.953550398349762, 'Val/mean precision': 0.9564480185508728, 'Val/mean recall': 0.9506701827049255, 'Val/mean hd95_metric': 11.492883682250977} +Epoch [58/4000] Training [1/16] Loss: 0.04890 +Epoch [58/4000] Training [2/16] Loss: 0.03635 +Epoch [58/4000] Training [3/16] Loss: 0.05889 +Epoch [58/4000] Training [4/16] Loss: 0.02751 +Epoch [58/4000] Training [5/16] Loss: 0.02166 +Epoch [58/4000] Training [6/16] Loss: 0.02399 +Epoch [58/4000] Training [7/16] Loss: 0.03916 +Epoch [58/4000] Training [8/16] Loss: 0.03510 +Epoch [58/4000] Training [9/16] Loss: 0.02478 +Epoch [58/4000] Training [10/16] Loss: 0.03213 +Epoch [58/4000] Training [11/16] Loss: 0.02000 +Epoch [58/4000] Training [12/16] Loss: 0.04116 +Epoch [58/4000] Training [13/16] Loss: 0.02620 +Epoch [58/4000] Training [14/16] Loss: 0.04005 +Epoch [58/4000] Training [15/16] Loss: 0.02769 +Epoch [58/4000] Training [16/16] Loss: 0.02338 +Epoch [58/4000] Training metric {'Train/mean dice_metric': 0.9774781465530396, 'Train/mean miou_metric': 0.9564493894577026, 'Train/mean f1': 0.9776914715766907, 'Train/mean precision': 0.9740716218948364, 'Train/mean recall': 0.9813382625579834, 'Train/mean hd95_metric': 4.4251813888549805} +Epoch [58/4000] Validation [1/4] Loss: 0.16429 focal_loss 0.09199 dice_loss 0.07230 +Epoch [58/4000] Validation [2/4] Loss: 0.41682 focal_loss 0.21581 dice_loss 0.20101 +Epoch [58/4000] Validation [3/4] Loss: 0.27686 focal_loss 0.15499 dice_loss 0.12187 +Epoch [58/4000] Validation [4/4] Loss: 0.20605 focal_loss 0.08341 dice_loss 0.12264 +Epoch [58/4000] Validation metric {'Val/mean dice_metric': 0.9540899991989136, 'Val/mean miou_metric': 0.9236749410629272, 'Val/mean f1': 0.9577348828315735, 'Val/mean precision': 0.9542826414108276, 'Val/mean recall': 0.961212158203125, 'Val/mean hd95_metric': 9.160757064819336} +Cheakpoint... +Epoch [58/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9541], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9540899991989136, 'Val/mean miou_metric': 0.9236749410629272, 'Val/mean f1': 0.9577348828315735, 'Val/mean precision': 0.9542826414108276, 'Val/mean recall': 0.961212158203125, 'Val/mean hd95_metric': 9.160757064819336} +Epoch [59/4000] Training [1/16] Loss: 0.02537 +Epoch [59/4000] Training [2/16] Loss: 0.02237 +Epoch [59/4000] Training [3/16] Loss: 0.02575 +Epoch [59/4000] Training [4/16] Loss: 0.03083 +Epoch [59/4000] Training [5/16] Loss: 0.02565 +Epoch [59/4000] Training [6/16] Loss: 0.02411 +Epoch [59/4000] Training [7/16] Loss: 0.04433 +Epoch [59/4000] Training [8/16] Loss: 0.02513 +Epoch [59/4000] Training [9/16] Loss: 0.02067 +Epoch [59/4000] Training [10/16] Loss: 0.01974 +Epoch [59/4000] Training [11/16] Loss: 0.02809 +Epoch [59/4000] Training [12/16] Loss: 0.10316 +Epoch [59/4000] Training [13/16] Loss: 0.02501 +Epoch [59/4000] Training [14/16] Loss: 0.05834 +Epoch [59/4000] Training [15/16] Loss: 0.02980 +Epoch [59/4000] Training [16/16] Loss: 0.02137 +Epoch [59/4000] Training metric {'Train/mean dice_metric': 0.9791898727416992, 'Train/mean miou_metric': 0.9604611396789551, 'Train/mean f1': 0.978898286819458, 'Train/mean precision': 0.9738009572029114, 'Train/mean recall': 0.9840493202209473, 'Train/mean hd95_metric': 3.714707851409912} +Epoch [59/4000] Validation [1/4] Loss: 0.49089 focal_loss 0.33619 dice_loss 0.15470 +Epoch [59/4000] Validation [2/4] Loss: 0.22543 focal_loss 0.08573 dice_loss 0.13971 +Epoch [59/4000] Validation [3/4] Loss: 0.15721 focal_loss 0.07023 dice_loss 0.08698 +Epoch [59/4000] Validation [4/4] Loss: 0.19451 focal_loss 0.06625 dice_loss 0.12826 +Epoch [59/4000] Validation metric {'Val/mean dice_metric': 0.9499877095222473, 'Val/mean miou_metric': 0.9206954836845398, 'Val/mean f1': 0.9546024799346924, 'Val/mean precision': 0.9530994892120361, 'Val/mean recall': 0.9561102390289307, 'Val/mean hd95_metric': 9.681416511535645} +Cheakpoint... +Epoch [59/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9500], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9499877095222473, 'Val/mean miou_metric': 0.9206954836845398, 'Val/mean f1': 0.9546024799346924, 'Val/mean precision': 0.9530994892120361, 'Val/mean recall': 0.9561102390289307, 'Val/mean hd95_metric': 9.681416511535645} +Epoch [60/4000] Training [1/16] Loss: 0.01990 +Epoch [60/4000] Training [2/16] Loss: 0.02643 +Epoch [60/4000] Training [3/16] Loss: 0.02317 +Epoch [60/4000] Training [4/16] Loss: 0.03185 +Epoch [60/4000] Training [5/16] Loss: 0.03244 +Epoch [60/4000] Training [6/16] Loss: 0.02716 +Epoch [60/4000] Training [7/16] Loss: 0.02423 +Epoch [60/4000] Training [8/16] Loss: 0.01732 +Epoch [60/4000] Training [9/16] Loss: 0.02407 +Epoch [60/4000] Training [10/16] Loss: 0.01819 +Epoch [60/4000] Training [11/16] Loss: 0.02763 +Epoch [60/4000] Training [12/16] Loss: 0.02750 +Epoch [60/4000] Training [13/16] Loss: 0.01617 +Epoch [60/4000] Training [14/16] Loss: 0.01986 +Epoch [60/4000] Training [15/16] Loss: 0.02826 +Epoch [60/4000] Training [16/16] Loss: 0.01747 +Epoch [60/4000] Training metric {'Train/mean dice_metric': 0.9827209711074829, 'Train/mean miou_metric': 0.9662338495254517, 'Train/mean f1': 0.9807727932929993, 'Train/mean precision': 0.9761626720428467, 'Train/mean recall': 0.9854267239570618, 'Train/mean hd95_metric': 2.766602039337158} +Epoch [60/4000] Validation [1/4] Loss: 0.12205 focal_loss 0.06242 dice_loss 0.05962 +Epoch [60/4000] Validation [2/4] Loss: 0.17885 focal_loss 0.06771 dice_loss 0.11115 +Epoch [60/4000] Validation [3/4] Loss: 0.16477 focal_loss 0.07497 dice_loss 0.08980 +Epoch [60/4000] Validation [4/4] Loss: 0.22987 focal_loss 0.10061 dice_loss 0.12926 +Epoch [60/4000] Validation metric {'Val/mean dice_metric': 0.9570237994194031, 'Val/mean miou_metric': 0.929984450340271, 'Val/mean f1': 0.9584068059921265, 'Val/mean precision': 0.9540238380432129, 'Val/mean recall': 0.9628302454948425, 'Val/mean hd95_metric': 7.953726768493652} +Cheakpoint... +Epoch [60/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9570], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9570237994194031, 'Val/mean miou_metric': 0.929984450340271, 'Val/mean f1': 0.9584068059921265, 'Val/mean precision': 0.9540238380432129, 'Val/mean recall': 0.9628302454948425, 'Val/mean hd95_metric': 7.953726768493652} +Epoch [61/4000] Training [1/16] Loss: 0.02612 +Epoch [61/4000] Training [2/16] Loss: 0.02506 +Epoch [61/4000] Training [3/16] Loss: 0.01711 +Epoch [61/4000] Training [4/16] Loss: 0.02608 +Epoch [61/4000] Training [5/16] Loss: 0.02224 +Epoch [61/4000] Training [6/16] Loss: 0.02211 +Epoch [61/4000] Training [7/16] Loss: 0.02876 +Epoch [61/4000] Training [8/16] Loss: 0.07786 +Epoch [61/4000] Training [9/16] Loss: 0.02249 +Epoch [61/4000] Training [10/16] Loss: 0.02216 +Epoch [61/4000] Training [11/16] Loss: 0.05025 +Epoch [61/4000] Training [12/16] Loss: 0.03818 +Epoch [61/4000] Training [13/16] Loss: 0.02208 +Epoch [61/4000] Training [14/16] Loss: 0.02034 +Epoch [61/4000] Training [15/16] Loss: 0.01833 +Epoch [61/4000] Training [16/16] Loss: 0.02926 +Epoch [61/4000] Training metric {'Train/mean dice_metric': 0.9810246229171753, 'Train/mean miou_metric': 0.9640005826950073, 'Train/mean f1': 0.9795618057250977, 'Train/mean precision': 0.974584698677063, 'Train/mean recall': 0.9845900535583496, 'Train/mean hd95_metric': 3.7910032272338867} +Epoch [61/4000] Validation [1/4] Loss: 0.63703 focal_loss 0.47035 dice_loss 0.16668 +Epoch [61/4000] Validation [2/4] Loss: 0.31718 focal_loss 0.14354 dice_loss 0.17364 +Epoch [61/4000] Validation [3/4] Loss: 0.22196 focal_loss 0.11054 dice_loss 0.11142 +Epoch [61/4000] Validation [4/4] Loss: 0.20838 focal_loss 0.09064 dice_loss 0.11774 +Epoch [61/4000] Validation metric {'Val/mean dice_metric': 0.9503018260002136, 'Val/mean miou_metric': 0.9219862222671509, 'Val/mean f1': 0.9541483521461487, 'Val/mean precision': 0.9633652567863464, 'Val/mean recall': 0.9451061487197876, 'Val/mean hd95_metric': 9.11081314086914} +Cheakpoint... +Epoch [61/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9503], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9503018260002136, 'Val/mean miou_metric': 0.9219862222671509, 'Val/mean f1': 0.9541483521461487, 'Val/mean precision': 0.9633652567863464, 'Val/mean recall': 0.9451061487197876, 'Val/mean hd95_metric': 9.11081314086914} +Epoch [62/4000] Training [1/16] Loss: 0.02784 +Epoch [62/4000] Training [2/16] Loss: 0.02490 +Epoch [62/4000] Training [3/16] Loss: 0.02001 +Epoch [62/4000] Training [4/16] Loss: 0.06754 +Epoch [62/4000] Training [5/16] Loss: 0.02076 +Epoch [62/4000] Training [6/16] Loss: 0.02316 +Epoch [62/4000] Training [7/16] Loss: 0.02578 +Epoch [62/4000] Training [8/16] Loss: 0.02432 +Epoch [62/4000] Training [9/16] Loss: 0.02574 +Epoch [62/4000] Training [10/16] Loss: 0.01905 +Epoch [62/4000] Training [11/16] Loss: 0.03225 +Epoch [62/4000] Training [12/16] Loss: 0.15051 +Epoch [62/4000] Training [13/16] Loss: 0.02668 +Epoch [62/4000] Training [14/16] Loss: 0.03341 +Epoch [62/4000] Training [15/16] Loss: 0.02386 +Epoch [62/4000] Training [16/16] Loss: 0.02665 +Epoch [62/4000] Training metric {'Train/mean dice_metric': 0.9770408868789673, 'Train/mean miou_metric': 0.9579783082008362, 'Train/mean f1': 0.9747900366783142, 'Train/mean precision': 0.9685320854187012, 'Train/mean recall': 0.9811294078826904, 'Train/mean hd95_metric': 4.163488864898682} +Epoch [62/4000] Validation [1/4] Loss: 0.68566 focal_loss 0.49173 dice_loss 0.19393 +Epoch [62/4000] Validation [2/4] Loss: 0.22939 focal_loss 0.07889 dice_loss 0.15050 +Epoch [62/4000] Validation [3/4] Loss: 0.16397 focal_loss 0.08473 dice_loss 0.07925 +Epoch [62/4000] Validation [4/4] Loss: 0.38122 focal_loss 0.21128 dice_loss 0.16994 +Epoch [62/4000] Validation metric {'Val/mean dice_metric': 0.9447916150093079, 'Val/mean miou_metric': 0.9129543304443359, 'Val/mean f1': 0.9454185962677002, 'Val/mean precision': 0.9542194604873657, 'Val/mean recall': 0.9367786645889282, 'Val/mean hd95_metric': 11.601577758789062} +Cheakpoint... +Epoch [62/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9448], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9447916150093079, 'Val/mean miou_metric': 0.9129543304443359, 'Val/mean f1': 0.9454185962677002, 'Val/mean precision': 0.9542194604873657, 'Val/mean recall': 0.9367786645889282, 'Val/mean hd95_metric': 11.601577758789062} +Epoch [63/4000] Training [1/16] Loss: 0.03457 +Epoch [63/4000] Training [2/16] Loss: 0.05551 +Epoch [63/4000] Training [3/16] Loss: 0.06093 +Epoch [63/4000] Training [4/16] Loss: 0.02269 +Epoch [63/4000] Training [5/16] Loss: 0.04951 +Epoch [63/4000] Training [6/16] Loss: 0.09203 +Epoch [63/4000] Training [7/16] Loss: 0.02173 +Epoch [63/4000] Training [8/16] Loss: 0.02956 +Epoch [63/4000] Training [9/16] Loss: 0.02144 +Epoch [63/4000] Training [10/16] Loss: 0.01937 +Epoch [63/4000] Training [11/16] Loss: 0.04567 +Epoch [63/4000] Training [12/16] Loss: 0.13836 +Epoch [63/4000] Training [13/16] Loss: 0.02019 +Epoch [63/4000] Training [14/16] Loss: 0.04342 +Epoch [63/4000] Training [15/16] Loss: 0.02768 +Epoch [63/4000] Training [16/16] Loss: 0.02638 +Epoch [63/4000] Training metric {'Train/mean dice_metric': 0.97383713722229, 'Train/mean miou_metric': 0.9514656066894531, 'Train/mean f1': 0.9720429182052612, 'Train/mean precision': 0.9665055871009827, 'Train/mean recall': 0.977644145488739, 'Train/mean hd95_metric': 8.033719062805176} +Epoch [63/4000] Validation [1/4] Loss: 0.18282 focal_loss 0.09927 dice_loss 0.08355 +Epoch [63/4000] Validation [2/4] Loss: 0.45686 focal_loss 0.22051 dice_loss 0.23635 +Epoch [63/4000] Validation [3/4] Loss: 0.25376 focal_loss 0.12437 dice_loss 0.12939 +Epoch [63/4000] Validation [4/4] Loss: 0.23100 focal_loss 0.11201 dice_loss 0.11899 +Epoch [63/4000] Validation metric {'Val/mean dice_metric': 0.9512888193130493, 'Val/mean miou_metric': 0.9181785583496094, 'Val/mean f1': 0.9528663754463196, 'Val/mean precision': 0.946087121963501, 'Val/mean recall': 0.9597434401512146, 'Val/mean hd95_metric': 12.768427848815918} +Cheakpoint... +Epoch [63/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9513], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9512888193130493, 'Val/mean miou_metric': 0.9181785583496094, 'Val/mean f1': 0.9528663754463196, 'Val/mean precision': 0.946087121963501, 'Val/mean recall': 0.9597434401512146, 'Val/mean hd95_metric': 12.768427848815918} +Epoch [64/4000] Training [1/16] Loss: 0.03672 +Epoch [64/4000] Training [2/16] Loss: 0.03982 +Epoch [64/4000] Training [3/16] Loss: 0.03040 +Epoch [64/4000] Training [4/16] Loss: 0.02763 +Epoch [64/4000] Training [5/16] Loss: 0.02388 +Epoch [64/4000] Training [6/16] Loss: 0.02969 +Epoch [64/4000] Training [7/16] Loss: 0.04948 +Epoch [64/4000] Training [8/16] Loss: 0.02845 +Epoch [64/4000] Training [9/16] Loss: 0.03249 +Epoch [64/4000] Training [10/16] Loss: 0.02269 +Epoch [64/4000] Training [11/16] Loss: 0.02689 +Epoch [64/4000] Training [12/16] Loss: 0.02836 +Epoch [64/4000] Training [13/16] Loss: 0.02678 +Epoch [64/4000] Training [14/16] Loss: 0.02550 +Epoch [64/4000] Training [15/16] Loss: 0.03191 +Epoch [64/4000] Training [16/16] Loss: 0.02290 +Epoch [64/4000] Training metric {'Train/mean dice_metric': 0.9796674251556396, 'Train/mean miou_metric': 0.9606147408485413, 'Train/mean f1': 0.9785884618759155, 'Train/mean precision': 0.9751042127609253, 'Train/mean recall': 0.9820976853370667, 'Train/mean hd95_metric': 3.7536561489105225} +Epoch [64/4000] Validation [1/4] Loss: 0.15733 focal_loss 0.07108 dice_loss 0.08625 +Epoch [64/4000] Validation [2/4] Loss: 0.23591 focal_loss 0.08286 dice_loss 0.15305 +Epoch [64/4000] Validation [3/4] Loss: 0.19246 focal_loss 0.08882 dice_loss 0.10365 +Epoch [64/4000] Validation [4/4] Loss: 0.23676 focal_loss 0.10051 dice_loss 0.13626 +Epoch [64/4000] Validation metric {'Val/mean dice_metric': 0.9555209875106812, 'Val/mean miou_metric': 0.9258956909179688, 'Val/mean f1': 0.9599833488464355, 'Val/mean precision': 0.9570896029472351, 'Val/mean recall': 0.9628945589065552, 'Val/mean hd95_metric': 9.462641716003418} +Cheakpoint... +Epoch [64/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9555], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9555209875106812, 'Val/mean miou_metric': 0.9258956909179688, 'Val/mean f1': 0.9599833488464355, 'Val/mean precision': 0.9570896029472351, 'Val/mean recall': 0.9628945589065552, 'Val/mean hd95_metric': 9.462641716003418} +Epoch [65/4000] Training [1/16] Loss: 0.02965 +Epoch [65/4000] Training [2/16] Loss: 0.02467 +Epoch [65/4000] Training [3/16] Loss: 0.03470 +Epoch [65/4000] Training [4/16] Loss: 0.02401 +Epoch [65/4000] Training [5/16] Loss: 0.02882 +Epoch [65/4000] Training [6/16] Loss: 0.03768 +Epoch [65/4000] Training [7/16] Loss: 0.02456 +Epoch [65/4000] Training [8/16] Loss: 0.02907 +Epoch [65/4000] Training [9/16] Loss: 0.01963 +Epoch [65/4000] Training [10/16] Loss: 0.02841 +Epoch [65/4000] Training [11/16] Loss: 0.01893 +Epoch [65/4000] Training [12/16] Loss: 0.05585 +Epoch [65/4000] Training [13/16] Loss: 0.03025 +Epoch [65/4000] Training [14/16] Loss: 0.02267 +Epoch [65/4000] Training [15/16] Loss: 0.01994 +Epoch [65/4000] Training [16/16] Loss: 0.03286 +Epoch [65/4000] Training metric {'Train/mean dice_metric': 0.9796081781387329, 'Train/mean miou_metric': 0.9607344269752502, 'Train/mean f1': 0.9776015281677246, 'Train/mean precision': 0.9722058176994324, 'Train/mean recall': 0.98305743932724, 'Train/mean hd95_metric': 3.809504985809326} +Epoch [65/4000] Validation [1/4] Loss: 0.32374 focal_loss 0.18643 dice_loss 0.13731 +Epoch [65/4000] Validation [2/4] Loss: 0.49858 focal_loss 0.18161 dice_loss 0.31697 +Epoch [65/4000] Validation [3/4] Loss: 0.18346 focal_loss 0.08431 dice_loss 0.09915 +Epoch [65/4000] Validation [4/4] Loss: 0.22102 focal_loss 0.08549 dice_loss 0.13554 +Epoch [65/4000] Validation metric {'Val/mean dice_metric': 0.9531466364860535, 'Val/mean miou_metric': 0.9241126775741577, 'Val/mean f1': 0.9580981731414795, 'Val/mean precision': 0.9560623168945312, 'Val/mean recall': 0.9601427316665649, 'Val/mean hd95_metric': 9.142062187194824} +Cheakpoint... +Epoch [65/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9531], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9531466364860535, 'Val/mean miou_metric': 0.9241126775741577, 'Val/mean f1': 0.9580981731414795, 'Val/mean precision': 0.9560623168945312, 'Val/mean recall': 0.9601427316665649, 'Val/mean hd95_metric': 9.142062187194824} +Epoch [66/4000] Training [1/16] Loss: 0.02437 +Epoch [66/4000] Training [2/16] Loss: 0.01959 +Epoch [66/4000] Training [3/16] Loss: 0.02531 +Epoch [66/4000] Training [4/16] Loss: 0.02060 +Epoch [66/4000] Training [5/16] Loss: 0.01812 +Epoch [66/4000] Training [6/16] Loss: 0.03767 +Epoch [66/4000] Training [7/16] Loss: 0.01806 +Epoch [66/4000] Training [8/16] Loss: 0.10022 +Epoch [66/4000] Training [9/16] Loss: 0.02854 +Epoch [66/4000] Training [10/16] Loss: 0.02502 +Epoch [66/4000] Training [11/16] Loss: 0.01625 +Epoch [66/4000] Training [12/16] Loss: 0.02327 +Epoch [66/4000] Training [13/16] Loss: 0.04238 +Epoch [66/4000] Training [14/16] Loss: 0.02249 +Epoch [66/4000] Training [15/16] Loss: 0.02821 +Epoch [66/4000] Training [16/16] Loss: 0.02751 +Epoch [66/4000] Training metric {'Train/mean dice_metric': 0.9817762970924377, 'Train/mean miou_metric': 0.9646711349487305, 'Train/mean f1': 0.9802368879318237, 'Train/mean precision': 0.9752529859542847, 'Train/mean recall': 0.9852719902992249, 'Train/mean hd95_metric': 3.6572425365448} +Epoch [66/4000] Validation [1/4] Loss: 0.13504 focal_loss 0.07436 dice_loss 0.06068 +Epoch [66/4000] Validation [2/4] Loss: 0.33846 focal_loss 0.13585 dice_loss 0.20261 +Epoch [66/4000] Validation [3/4] Loss: 0.28938 focal_loss 0.13420 dice_loss 0.15518 +Epoch [66/4000] Validation [4/4] Loss: 0.18803 focal_loss 0.06957 dice_loss 0.11846 +Epoch [66/4000] Validation metric {'Val/mean dice_metric': 0.9595268964767456, 'Val/mean miou_metric': 0.9319452047348022, 'Val/mean f1': 0.963042140007019, 'Val/mean precision': 0.954803466796875, 'Val/mean recall': 0.9714241027832031, 'Val/mean hd95_metric': 8.687253952026367} +Cheakpoint... +Epoch [66/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9595], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9595268964767456, 'Val/mean miou_metric': 0.9319452047348022, 'Val/mean f1': 0.963042140007019, 'Val/mean precision': 0.954803466796875, 'Val/mean recall': 0.9714241027832031, 'Val/mean hd95_metric': 8.687253952026367} +Epoch [67/4000] Training [1/16] Loss: 0.01967 +Epoch [67/4000] Training [2/16] Loss: 0.02674 +Epoch [67/4000] Training [3/16] Loss: 0.01777 +Epoch [67/4000] Training [4/16] Loss: 0.01905 +Epoch [67/4000] Training [5/16] Loss: 0.02535 +Epoch [67/4000] Training [6/16] Loss: 0.02130 +Epoch [67/4000] Training [7/16] Loss: 0.02241 +Epoch [67/4000] Training [8/16] Loss: 0.07463 +Epoch [67/4000] Training [9/16] Loss: 0.02195 +Epoch [67/4000] Training [10/16] Loss: 0.02308 +Epoch [67/4000] Training [11/16] Loss: 0.01805 +Epoch [67/4000] Training [12/16] Loss: 0.02036 +Epoch [67/4000] Training [13/16] Loss: 0.02171 +Epoch [67/4000] Training [14/16] Loss: 0.02967 +Epoch [67/4000] Training [15/16] Loss: 0.02330 +Epoch [67/4000] Training [16/16] Loss: 0.02034 +Epoch [67/4000] Training metric {'Train/mean dice_metric': 0.982014536857605, 'Train/mean miou_metric': 0.9654684066772461, 'Train/mean f1': 0.9804646968841553, 'Train/mean precision': 0.9768480658531189, 'Train/mean recall': 0.9841082692146301, 'Train/mean hd95_metric': 2.6117191314697266} +Epoch [67/4000] Validation [1/4] Loss: 0.99231 focal_loss 0.78556 dice_loss 0.20675 +Epoch [67/4000] Validation [2/4] Loss: 0.29884 focal_loss 0.11158 dice_loss 0.18726 +Epoch [67/4000] Validation [3/4] Loss: 0.23297 focal_loss 0.11454 dice_loss 0.11843 +Epoch [67/4000] Validation [4/4] Loss: 0.35523 focal_loss 0.21236 dice_loss 0.14287 +Epoch [67/4000] Validation metric {'Val/mean dice_metric': 0.9532537460327148, 'Val/mean miou_metric': 0.9249876737594604, 'Val/mean f1': 0.9557041525840759, 'Val/mean precision': 0.9626319408416748, 'Val/mean recall': 0.9488754868507385, 'Val/mean hd95_metric': 8.734029769897461} +Cheakpoint... +Epoch [67/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9533], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9532537460327148, 'Val/mean miou_metric': 0.9249876737594604, 'Val/mean f1': 0.9557041525840759, 'Val/mean precision': 0.9626319408416748, 'Val/mean recall': 0.9488754868507385, 'Val/mean hd95_metric': 8.734029769897461} +Epoch [68/4000] Training [1/16] Loss: 0.02158 +Epoch [68/4000] Training [2/16] Loss: 0.03708 +Epoch [68/4000] Training [3/16] Loss: 0.02414 +Epoch [68/4000] Training [4/16] Loss: 0.02988 +Epoch [68/4000] Training [5/16] Loss: 0.02176 +Epoch [68/4000] Training [6/16] Loss: 0.07546 +Epoch [68/4000] Training [7/16] Loss: 0.02383 +Epoch [68/4000] Training [8/16] Loss: 0.02053 +Epoch [68/4000] Training [9/16] Loss: 0.02100 +Epoch [68/4000] Training [10/16] Loss: 0.02235 +Epoch [68/4000] Training [11/16] Loss: 0.02938 +Epoch [68/4000] Training [12/16] Loss: 0.04143 +Epoch [68/4000] Training [13/16] Loss: 0.03606 +Epoch [68/4000] Training [14/16] Loss: 0.02197 +Epoch [68/4000] Training [15/16] Loss: 0.02044 +Epoch [68/4000] Training [16/16] Loss: 0.02926 +Epoch [68/4000] Training metric {'Train/mean dice_metric': 0.9801980257034302, 'Train/mean miou_metric': 0.963098406791687, 'Train/mean f1': 0.9789686799049377, 'Train/mean precision': 0.9737218618392944, 'Train/mean recall': 0.9842723608016968, 'Train/mean hd95_metric': 3.6645030975341797} +Epoch [68/4000] Validation [1/4] Loss: 1.21920 focal_loss 0.94844 dice_loss 0.27076 +Epoch [68/4000] Validation [2/4] Loss: 0.35801 focal_loss 0.13785 dice_loss 0.22016 +Epoch [68/4000] Validation [3/4] Loss: 0.15643 focal_loss 0.07811 dice_loss 0.07833 +Epoch [68/4000] Validation [4/4] Loss: 0.18260 focal_loss 0.07338 dice_loss 0.10923 +Epoch [68/4000] Validation metric {'Val/mean dice_metric': 0.9484668970108032, 'Val/mean miou_metric': 0.9207844734191895, 'Val/mean f1': 0.9539744257926941, 'Val/mean precision': 0.9608038663864136, 'Val/mean recall': 0.9472414255142212, 'Val/mean hd95_metric': 9.007014274597168} +Cheakpoint... +Epoch [68/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9485], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9484668970108032, 'Val/mean miou_metric': 0.9207844734191895, 'Val/mean f1': 0.9539744257926941, 'Val/mean precision': 0.9608038663864136, 'Val/mean recall': 0.9472414255142212, 'Val/mean hd95_metric': 9.007014274597168} +Epoch [69/4000] Training [1/16] Loss: 0.02866 +Epoch [69/4000] Training [2/16] Loss: 0.05415 +Epoch [69/4000] Training [3/16] Loss: 0.01947 +Epoch [69/4000] Training [4/16] Loss: 0.02682 +Epoch [69/4000] Training [5/16] Loss: 0.01787 +Epoch [69/4000] Training [6/16] Loss: 0.02271 +Epoch [69/4000] Training [7/16] Loss: 0.02423 +Epoch [69/4000] Training [8/16] Loss: 0.02741 +Epoch [69/4000] Training [9/16] Loss: 0.03310 +Epoch [69/4000] Training [10/16] Loss: 0.02750 +Epoch [69/4000] Training [11/16] Loss: 0.03174 +Epoch [69/4000] Training [12/16] Loss: 0.02672 +Epoch [69/4000] Training [13/16] Loss: 0.05136 +Epoch [69/4000] Training [14/16] Loss: 0.04222 +Epoch [69/4000] Training [15/16] Loss: 0.02755 +Epoch [69/4000] Training [16/16] Loss: 0.02674 +Epoch [69/4000] Training metric {'Train/mean dice_metric': 0.9793979525566101, 'Train/mean miou_metric': 0.9601328372955322, 'Train/mean f1': 0.9771718978881836, 'Train/mean precision': 0.9738967418670654, 'Train/mean recall': 0.9804691672325134, 'Train/mean hd95_metric': 4.958600997924805} +Epoch [69/4000] Validation [1/4] Loss: 0.24887 focal_loss 0.13496 dice_loss 0.11391 +Epoch [69/4000] Validation [2/4] Loss: 0.33309 focal_loss 0.11416 dice_loss 0.21893 +Epoch [69/4000] Validation [3/4] Loss: 0.11939 focal_loss 0.05763 dice_loss 0.06176 +Epoch [69/4000] Validation [4/4] Loss: 0.19812 focal_loss 0.08697 dice_loss 0.11114 +Epoch [69/4000] Validation metric {'Val/mean dice_metric': 0.9530375599861145, 'Val/mean miou_metric': 0.9229087829589844, 'Val/mean f1': 0.9557512998580933, 'Val/mean precision': 0.9536837339401245, 'Val/mean recall': 0.9578278660774231, 'Val/mean hd95_metric': 9.501263618469238} +Cheakpoint... +Epoch [69/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9530], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9530375599861145, 'Val/mean miou_metric': 0.9229087829589844, 'Val/mean f1': 0.9557512998580933, 'Val/mean precision': 0.9536837339401245, 'Val/mean recall': 0.9578278660774231, 'Val/mean hd95_metric': 9.501263618469238} +Epoch [70/4000] Training [1/16] Loss: 0.02469 +Epoch [70/4000] Training [2/16] Loss: 0.02626 +Epoch [70/4000] Training [3/16] Loss: 0.03445 +Epoch [70/4000] Training [4/16] Loss: 0.02790 +Epoch [70/4000] Training [5/16] Loss: 0.02450 +Epoch [70/4000] Training [6/16] Loss: 0.07274 +Epoch [70/4000] Training [7/16] Loss: 0.02527 +Epoch [70/4000] Training [8/16] Loss: 0.02574 +Epoch [70/4000] Training [9/16] Loss: 0.03198 +Epoch [70/4000] Training [10/16] Loss: 0.02460 +Epoch [70/4000] Training [11/16] Loss: 0.03330 +Epoch [70/4000] Training [12/16] Loss: 0.02225 +Epoch [70/4000] Training [13/16] Loss: 0.04013 +Epoch [70/4000] Training [14/16] Loss: 0.02803 +Epoch [70/4000] Training [15/16] Loss: 0.03625 +Epoch [70/4000] Training [16/16] Loss: 0.03543 +Epoch [70/4000] Training metric {'Train/mean dice_metric': 0.9749650955200195, 'Train/mean miou_metric': 0.9537431001663208, 'Train/mean f1': 0.9730989933013916, 'Train/mean precision': 0.9687805771827698, 'Train/mean recall': 0.9774560332298279, 'Train/mean hd95_metric': 5.123283386230469} +Epoch [70/4000] Validation [1/4] Loss: 0.57758 focal_loss 0.43940 dice_loss 0.13818 +Epoch [70/4000] Validation [2/4] Loss: 0.42112 focal_loss 0.19254 dice_loss 0.22858 +Epoch [70/4000] Validation [3/4] Loss: 0.12779 focal_loss 0.06002 dice_loss 0.06777 +Epoch [70/4000] Validation [4/4] Loss: 0.33214 focal_loss 0.18575 dice_loss 0.14639 +Epoch [70/4000] Validation metric {'Val/mean dice_metric': 0.9484630823135376, 'Val/mean miou_metric': 0.9167105555534363, 'Val/mean f1': 0.951687753200531, 'Val/mean precision': 0.9518517851829529, 'Val/mean recall': 0.9515238404273987, 'Val/mean hd95_metric': 10.16393756866455} +Cheakpoint... +Epoch [70/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9485], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9484630823135376, 'Val/mean miou_metric': 0.9167105555534363, 'Val/mean f1': 0.951687753200531, 'Val/mean precision': 0.9518517851829529, 'Val/mean recall': 0.9515238404273987, 'Val/mean hd95_metric': 10.16393756866455} +Epoch [71/4000] Training [1/16] Loss: 0.06231 +Epoch [71/4000] Training [2/16] Loss: 0.32700 +Epoch [71/4000] Training [3/16] Loss: 0.02585 +Epoch [71/4000] Training [4/16] Loss: 0.02956 +Epoch [71/4000] Training [5/16] Loss: 0.04661 +Epoch [71/4000] Training [6/16] Loss: 0.03795 +Epoch [71/4000] Training [7/16] Loss: 0.02742 +Epoch [71/4000] Training [8/16] Loss: 0.03314 +Epoch [71/4000] Training [9/16] Loss: 0.04095 +Epoch [71/4000] Training [10/16] Loss: 0.04447 +Epoch [71/4000] Training [11/16] Loss: 0.09457 +Epoch [71/4000] Training [12/16] Loss: 0.02487 +Epoch [71/4000] Training [13/16] Loss: 0.03256 +Epoch [71/4000] Training [14/16] Loss: 0.02505 +Epoch [71/4000] Training [15/16] Loss: 0.02800 +Epoch [71/4000] Training [16/16] Loss: 0.05193 +Epoch [71/4000] Training metric {'Train/mean dice_metric': 0.9671265482902527, 'Train/mean miou_metric': 0.9407699704170227, 'Train/mean f1': 0.9652199745178223, 'Train/mean precision': 0.9603152871131897, 'Train/mean recall': 0.9701749682426453, 'Train/mean hd95_metric': 9.604421615600586} +Epoch [71/4000] Validation [1/4] Loss: 0.25476 focal_loss 0.15487 dice_loss 0.09990 +Epoch [71/4000] Validation [2/4] Loss: 0.27188 focal_loss 0.11166 dice_loss 0.16022 +Epoch [71/4000] Validation [3/4] Loss: 0.20593 focal_loss 0.10969 dice_loss 0.09624 +Epoch [71/4000] Validation [4/4] Loss: 0.21659 focal_loss 0.09122 dice_loss 0.12537 +Epoch [71/4000] Validation metric {'Val/mean dice_metric': 0.9413841366767883, 'Val/mean miou_metric': 0.9045448303222656, 'Val/mean f1': 0.9441429972648621, 'Val/mean precision': 0.9411433339118958, 'Val/mean recall': 0.9471617341041565, 'Val/mean hd95_metric': 14.608782768249512} +Cheakpoint... +Epoch [71/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9414], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9413841366767883, 'Val/mean miou_metric': 0.9045448303222656, 'Val/mean f1': 0.9441429972648621, 'Val/mean precision': 0.9411433339118958, 'Val/mean recall': 0.9471617341041565, 'Val/mean hd95_metric': 14.608782768249512} +Epoch [72/4000] Training [1/16] Loss: 0.11479 +Epoch [72/4000] Training [2/16] Loss: 0.06553 +Epoch [72/4000] Training [3/16] Loss: 0.02745 +Epoch [72/4000] Training [4/16] Loss: 0.02692 +Epoch [72/4000] Training [5/16] Loss: 0.03886 +Epoch [72/4000] Training [6/16] Loss: 0.02540 +Epoch [72/4000] Training [7/16] Loss: 0.02199 +Epoch [72/4000] Training [8/16] Loss: 0.02374 +Epoch [72/4000] Training [9/16] Loss: 0.02293 +Epoch [72/4000] Training [10/16] Loss: 0.02600 +Epoch [72/4000] Training [11/16] Loss: 0.05665 +Epoch [72/4000] Training [12/16] Loss: 0.03889 +Epoch [72/4000] Training [13/16] Loss: 0.02282 +Epoch [72/4000] Training [14/16] Loss: 0.05970 +Epoch [72/4000] Training [15/16] Loss: 0.03263 +Epoch [72/4000] Training [16/16] Loss: 0.05589 +Epoch [72/4000] Training metric {'Train/mean dice_metric': 0.9729019403457642, 'Train/mean miou_metric': 0.9492455720901489, 'Train/mean f1': 0.9728493690490723, 'Train/mean precision': 0.9697186946868896, 'Train/mean recall': 0.9760003089904785, 'Train/mean hd95_metric': 6.391911506652832} +Epoch [72/4000] Validation [1/4] Loss: 0.40351 focal_loss 0.26243 dice_loss 0.14108 +Epoch [72/4000] Validation [2/4] Loss: 0.41634 focal_loss 0.18321 dice_loss 0.23312 +Epoch [72/4000] Validation [3/4] Loss: 0.16630 focal_loss 0.07198 dice_loss 0.09432 +Epoch [72/4000] Validation [4/4] Loss: 0.25119 focal_loss 0.10130 dice_loss 0.14989 +Epoch [72/4000] Validation metric {'Val/mean dice_metric': 0.9482337832450867, 'Val/mean miou_metric': 0.9149731397628784, 'Val/mean f1': 0.9541404843330383, 'Val/mean precision': 0.9516628980636597, 'Val/mean recall': 0.9566310048103333, 'Val/mean hd95_metric': 10.32928466796875} +Cheakpoint... +Epoch [72/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9482], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9482337832450867, 'Val/mean miou_metric': 0.9149731397628784, 'Val/mean f1': 0.9541404843330383, 'Val/mean precision': 0.9516628980636597, 'Val/mean recall': 0.9566310048103333, 'Val/mean hd95_metric': 10.32928466796875} +Epoch [73/4000] Training [1/16] Loss: 0.02397 +Epoch [73/4000] Training [2/16] Loss: 0.02956 +Epoch [73/4000] Training [3/16] Loss: 0.02784 +Epoch [73/4000] Training [4/16] Loss: 0.02588 +Epoch [73/4000] Training [5/16] Loss: 0.02105 +Epoch [73/4000] Training [6/16] Loss: 0.03171 +Epoch [73/4000] Training [7/16] Loss: 0.09089 +Epoch [73/4000] Training [8/16] Loss: 0.03680 +Epoch [73/4000] Training [9/16] Loss: 0.02953 +Epoch [73/4000] Training [10/16] Loss: 0.04150 +Epoch [73/4000] Training [11/16] Loss: 0.02482 +Epoch [73/4000] Training [12/16] Loss: 0.02469 +Epoch [73/4000] Training [13/16] Loss: 0.09366 +Epoch [73/4000] Training [14/16] Loss: 0.04443 +Epoch [73/4000] Training [15/16] Loss: 0.02866 +Epoch [73/4000] Training [16/16] Loss: 0.02396 +Epoch [73/4000] Training metric {'Train/mean dice_metric': 0.9771013855934143, 'Train/mean miou_metric': 0.9563500881195068, 'Train/mean f1': 0.9760505557060242, 'Train/mean precision': 0.9731417894363403, 'Train/mean recall': 0.9789767265319824, 'Train/mean hd95_metric': 4.143362045288086} +Epoch [73/4000] Validation [1/4] Loss: 0.25090 focal_loss 0.15214 dice_loss 0.09875 +Epoch [73/4000] Validation [2/4] Loss: 0.24413 focal_loss 0.08698 dice_loss 0.15715 +Epoch [73/4000] Validation [3/4] Loss: 0.16944 focal_loss 0.06215 dice_loss 0.10728 +Epoch [73/4000] Validation [4/4] Loss: 0.15310 focal_loss 0.05146 dice_loss 0.10164 +Epoch [73/4000] Validation metric {'Val/mean dice_metric': 0.9507262110710144, 'Val/mean miou_metric': 0.9194742441177368, 'Val/mean f1': 0.9556517601013184, 'Val/mean precision': 0.957051694393158, 'Val/mean recall': 0.9542558789253235, 'Val/mean hd95_metric': 8.958416938781738} +Cheakpoint... +Epoch [73/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9507], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9507262110710144, 'Val/mean miou_metric': 0.9194742441177368, 'Val/mean f1': 0.9556517601013184, 'Val/mean precision': 0.957051694393158, 'Val/mean recall': 0.9542558789253235, 'Val/mean hd95_metric': 8.958416938781738} +Epoch [74/4000] Training [1/16] Loss: 0.02212 +Epoch [74/4000] Training [2/16] Loss: 0.02263 +Epoch [74/4000] Training [3/16] Loss: 0.02195 +Epoch [74/4000] Training [4/16] Loss: 0.02414 +Epoch [74/4000] Training [5/16] Loss: 0.02453 +Epoch [74/4000] Training [6/16] Loss: 0.02997 +Epoch [74/4000] Training [7/16] Loss: 0.12797 +Epoch [74/4000] Training [8/16] Loss: 0.03184 +Epoch [74/4000] Training [9/16] Loss: 0.02491 +Epoch [74/4000] Training [10/16] Loss: 0.19485 +Epoch [74/4000] Training [11/16] Loss: 0.02851 +Epoch [74/4000] Training [12/16] Loss: 0.05405 +Epoch [74/4000] Training [13/16] Loss: 0.03309 +Epoch [74/4000] Training [14/16] Loss: 0.04528 +Epoch [74/4000] Training [15/16] Loss: 0.02793 +Epoch [74/4000] Training [16/16] Loss: 0.03193 +Epoch [74/4000] Training metric {'Train/mean dice_metric': 0.9764716625213623, 'Train/mean miou_metric': 0.9553736448287964, 'Train/mean f1': 0.9733806848526001, 'Train/mean precision': 0.9653246998786926, 'Train/mean recall': 0.9815722107887268, 'Train/mean hd95_metric': 6.224403381347656} +Epoch [74/4000] Validation [1/4] Loss: 0.28100 focal_loss 0.17735 dice_loss 0.10365 +Epoch [74/4000] Validation [2/4] Loss: 0.31386 focal_loss 0.08294 dice_loss 0.23092 +Epoch [74/4000] Validation [3/4] Loss: 0.20893 focal_loss 0.08867 dice_loss 0.12026 +Epoch [74/4000] Validation [4/4] Loss: 0.30823 focal_loss 0.14611 dice_loss 0.16212 +Epoch [74/4000] Validation metric {'Val/mean dice_metric': 0.9502754211425781, 'Val/mean miou_metric': 0.9198883175849915, 'Val/mean f1': 0.9550364017486572, 'Val/mean precision': 0.9466651678085327, 'Val/mean recall': 0.9635569453239441, 'Val/mean hd95_metric': 11.887406349182129} +Cheakpoint... +Epoch [74/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9503], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9502754211425781, 'Val/mean miou_metric': 0.9198883175849915, 'Val/mean f1': 0.9550364017486572, 'Val/mean precision': 0.9466651678085327, 'Val/mean recall': 0.9635569453239441, 'Val/mean hd95_metric': 11.887406349182129} +Epoch [75/4000] Training [1/16] Loss: 0.02491 +Epoch [75/4000] Training [2/16] Loss: 0.05402 +Epoch [75/4000] Training [3/16] Loss: 0.02625 +Epoch [75/4000] Training [4/16] Loss: 0.02685 +Epoch [75/4000] Training [5/16] Loss: 0.04109 +Epoch [75/4000] Training [6/16] Loss: 0.04949 +Epoch [75/4000] Training [7/16] Loss: 0.02342 +Epoch [75/4000] Training [8/16] Loss: 0.01945 +Epoch [75/4000] Training [9/16] Loss: 0.03133 +Epoch [75/4000] Training [10/16] Loss: 0.02333 +Epoch [75/4000] Training [11/16] Loss: 0.02816 +Epoch [75/4000] Training [12/16] Loss: 0.02920 +Epoch [75/4000] Training [13/16] Loss: 0.02257 +Epoch [75/4000] Training [14/16] Loss: 0.02331 +Epoch [75/4000] Training [15/16] Loss: 0.02855 +Epoch [75/4000] Training [16/16] Loss: 0.02320 +Epoch [75/4000] Training metric {'Train/mean dice_metric': 0.9775951504707336, 'Train/mean miou_metric': 0.9580087661743164, 'Train/mean f1': 0.9722597599029541, 'Train/mean precision': 0.9725666046142578, 'Train/mean recall': 0.9719530940055847, 'Train/mean hd95_metric': 5.1493635177612305} +Epoch [75/4000] Validation [1/4] Loss: 0.33265 focal_loss 0.21267 dice_loss 0.11998 +Epoch [75/4000] Validation [2/4] Loss: 0.64694 focal_loss 0.31404 dice_loss 0.33289 +Epoch [75/4000] Validation [3/4] Loss: 0.15035 focal_loss 0.07827 dice_loss 0.07208 +Epoch [75/4000] Validation [4/4] Loss: 0.21772 focal_loss 0.10816 dice_loss 0.10956 +Epoch [75/4000] Validation metric {'Val/mean dice_metric': 0.9518097043037415, 'Val/mean miou_metric': 0.9227550625801086, 'Val/mean f1': 0.9542666077613831, 'Val/mean precision': 0.9624412655830383, 'Val/mean recall': 0.9462296962738037, 'Val/mean hd95_metric': 9.077990531921387} +Cheakpoint... +Epoch [75/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9518], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9518097043037415, 'Val/mean miou_metric': 0.9227550625801086, 'Val/mean f1': 0.9542666077613831, 'Val/mean precision': 0.9624412655830383, 'Val/mean recall': 0.9462296962738037, 'Val/mean hd95_metric': 9.077990531921387} +Epoch [76/4000] Training [1/16] Loss: 0.03010 +Epoch [76/4000] Training [2/16] Loss: 0.03446 +Epoch [76/4000] Training [3/16] Loss: 0.02498 +Epoch [76/4000] Training [4/16] Loss: 0.02283 +Epoch [76/4000] Training [5/16] Loss: 0.02179 +Epoch [76/4000] Training [6/16] Loss: 0.02543 +Epoch [76/4000] Training [7/16] Loss: 0.02322 +Epoch [76/4000] Training [8/16] Loss: 0.02838 +Epoch [76/4000] Training [9/16] Loss: 0.03814 +Epoch [76/4000] Training [10/16] Loss: 0.02280 +Epoch [76/4000] Training [11/16] Loss: 0.02372 +Epoch [76/4000] Training [12/16] Loss: 0.05196 +Epoch [76/4000] Training [13/16] Loss: 0.03614 +Epoch [76/4000] Training [14/16] Loss: 0.02683 +Epoch [76/4000] Training [15/16] Loss: 0.02215 +Epoch [76/4000] Training [16/16] Loss: 0.01903 +Epoch [76/4000] Training metric {'Train/mean dice_metric': 0.9791476726531982, 'Train/mean miou_metric': 0.9598021507263184, 'Train/mean f1': 0.9771578311920166, 'Train/mean precision': 0.9734774231910706, 'Train/mean recall': 0.9808662533760071, 'Train/mean hd95_metric': 4.729578971862793} +Epoch [76/4000] Validation [1/4] Loss: 0.25498 focal_loss 0.15622 dice_loss 0.09876 +Epoch [76/4000] Validation [2/4] Loss: 0.23386 focal_loss 0.08255 dice_loss 0.15130 +Epoch [76/4000] Validation [3/4] Loss: 0.13510 focal_loss 0.06544 dice_loss 0.06966 +Epoch [76/4000] Validation [4/4] Loss: 0.27199 focal_loss 0.13574 dice_loss 0.13624 +Epoch [76/4000] Validation metric {'Val/mean dice_metric': 0.9522102475166321, 'Val/mean miou_metric': 0.9221866726875305, 'Val/mean f1': 0.9556719660758972, 'Val/mean precision': 0.9495766162872314, 'Val/mean recall': 0.961846113204956, 'Val/mean hd95_metric': 10.977269172668457} +Cheakpoint... +Epoch [76/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9522], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9522102475166321, 'Val/mean miou_metric': 0.9221866726875305, 'Val/mean f1': 0.9556719660758972, 'Val/mean precision': 0.9495766162872314, 'Val/mean recall': 0.961846113204956, 'Val/mean hd95_metric': 10.977269172668457} +Epoch [77/4000] Training [1/16] Loss: 0.02482 +Epoch [77/4000] Training [2/16] Loss: 0.02085 +Epoch [77/4000] Training [3/16] Loss: 0.02452 +Epoch [77/4000] Training [4/16] Loss: 0.02845 +Epoch [77/4000] Training [5/16] Loss: 0.02892 +Epoch [77/4000] Training [6/16] Loss: 0.02015 +Epoch [77/4000] Training [7/16] Loss: 0.02143 +Epoch [77/4000] Training [8/16] Loss: 0.02978 +Epoch [77/4000] Training [9/16] Loss: 0.04980 +Epoch [77/4000] Training [10/16] Loss: 0.07366 +Epoch [77/4000] Training [11/16] Loss: 0.03812 +Epoch [77/4000] Training [12/16] Loss: 0.02371 +Epoch [77/4000] Training [13/16] Loss: 0.02601 +Epoch [77/4000] Training [14/16] Loss: 0.03486 +Epoch [77/4000] Training [15/16] Loss: 0.03217 +Epoch [77/4000] Training [16/16] Loss: 0.02967 +Epoch [77/4000] Training metric {'Train/mean dice_metric': 0.9776109457015991, 'Train/mean miou_metric': 0.957981526851654, 'Train/mean f1': 0.9780367612838745, 'Train/mean precision': 0.9744023680686951, 'Train/mean recall': 0.9816983938217163, 'Train/mean hd95_metric': 5.021391868591309} +Epoch [77/4000] Validation [1/4] Loss: 0.14490 focal_loss 0.07862 dice_loss 0.06628 +Epoch [77/4000] Validation [2/4] Loss: 0.54590 focal_loss 0.23028 dice_loss 0.31561 +Epoch [77/4000] Validation [3/4] Loss: 0.15357 focal_loss 0.06857 dice_loss 0.08500 +Epoch [77/4000] Validation [4/4] Loss: 0.19718 focal_loss 0.07734 dice_loss 0.11984 +Epoch [77/4000] Validation metric {'Val/mean dice_metric': 0.9521452188491821, 'Val/mean miou_metric': 0.9227821230888367, 'Val/mean f1': 0.9594314694404602, 'Val/mean precision': 0.9575387239456177, 'Val/mean recall': 0.9613315463066101, 'Val/mean hd95_metric': 9.647160530090332} +Cheakpoint... +Epoch [77/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9521], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9521452188491821, 'Val/mean miou_metric': 0.9227821230888367, 'Val/mean f1': 0.9594314694404602, 'Val/mean precision': 0.9575387239456177, 'Val/mean recall': 0.9613315463066101, 'Val/mean hd95_metric': 9.647160530090332} +Epoch [78/4000] Training [1/16] Loss: 0.03358 +Epoch [78/4000] Training [2/16] Loss: 0.02553 +Epoch [78/4000] Training [3/16] Loss: 0.02118 +Epoch [78/4000] Training [4/16] Loss: 0.02890 +Epoch [78/4000] Training [5/16] Loss: 0.02481 +Epoch [78/4000] Training [6/16] Loss: 0.02997 +Epoch [78/4000] Training [7/16] Loss: 0.02176 +Epoch [78/4000] Training [8/16] Loss: 0.02061 +Epoch [78/4000] Training [9/16] Loss: 0.02907 +Epoch [78/4000] Training [10/16] Loss: 0.02303 +Epoch [78/4000] Training [11/16] Loss: 0.02313 +Epoch [78/4000] Training [12/16] Loss: 0.02444 +Epoch [78/4000] Training [13/16] Loss: 0.01782 +Epoch [78/4000] Training [14/16] Loss: 0.10643 +Epoch [78/4000] Training [15/16] Loss: 0.02400 +Epoch [78/4000] Training [16/16] Loss: 0.04033 +Epoch [78/4000] Training metric {'Train/mean dice_metric': 0.9796172976493835, 'Train/mean miou_metric': 0.961586058139801, 'Train/mean f1': 0.978249192237854, 'Train/mean precision': 0.9744062423706055, 'Train/mean recall': 0.9821226000785828, 'Train/mean hd95_metric': 3.240983486175537} +Epoch [78/4000] Validation [1/4] Loss: 0.17320 focal_loss 0.09215 dice_loss 0.08105 +Epoch [78/4000] Validation [2/4] Loss: 0.42719 focal_loss 0.13183 dice_loss 0.29537 +Epoch [78/4000] Validation [3/4] Loss: 0.22269 focal_loss 0.08645 dice_loss 0.13624 +Epoch [78/4000] Validation [4/4] Loss: 0.15519 focal_loss 0.06167 dice_loss 0.09352 +Epoch [78/4000] Validation metric {'Val/mean dice_metric': 0.9524440765380859, 'Val/mean miou_metric': 0.9249870181083679, 'Val/mean f1': 0.9582734107971191, 'Val/mean precision': 0.9494363069534302, 'Val/mean recall': 0.9672765135765076, 'Val/mean hd95_metric': 7.936860084533691} +Cheakpoint... +Epoch [78/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9524], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9524440765380859, 'Val/mean miou_metric': 0.9249870181083679, 'Val/mean f1': 0.9582734107971191, 'Val/mean precision': 0.9494363069534302, 'Val/mean recall': 0.9672765135765076, 'Val/mean hd95_metric': 7.936860084533691} +Epoch [79/4000] Training [1/16] Loss: 0.04357 +Epoch [79/4000] Training [2/16] Loss: 0.02319 +Epoch [79/4000] Training [3/16] Loss: 0.03397 +Epoch [79/4000] Training [4/16] Loss: 0.02085 +Epoch [79/4000] Training [5/16] Loss: 0.02173 +Epoch [79/4000] Training [6/16] Loss: 0.02128 +Epoch [79/4000] Training [7/16] Loss: 0.02063 +Epoch [79/4000] Training [8/16] Loss: 0.02929 +Epoch [79/4000] Training [9/16] Loss: 0.02871 +Epoch [79/4000] Training [10/16] Loss: 0.05159 +Epoch [79/4000] Training [11/16] Loss: 0.01824 +Epoch [79/4000] Training [12/16] Loss: 0.04223 +Epoch [79/4000] Training [13/16] Loss: 0.03297 +Epoch [79/4000] Training [14/16] Loss: 0.02668 +Epoch [79/4000] Training [15/16] Loss: 0.02874 +Epoch [79/4000] Training [16/16] Loss: 0.15485 +Epoch [79/4000] Training metric {'Train/mean dice_metric': 0.9771935939788818, 'Train/mean miou_metric': 0.9585250616073608, 'Train/mean f1': 0.9788541793823242, 'Train/mean precision': 0.9754935503005981, 'Train/mean recall': 0.9822379350662231, 'Train/mean hd95_metric': 4.006333351135254} +Epoch [79/4000] Validation [1/4] Loss: 0.61664 focal_loss 0.39377 dice_loss 0.22287 +Epoch [79/4000] Validation [2/4] Loss: 0.31175 focal_loss 0.09115 dice_loss 0.22060 +Epoch [79/4000] Validation [3/4] Loss: 0.20739 focal_loss 0.11998 dice_loss 0.08741 +Epoch [79/4000] Validation [4/4] Loss: 0.26137 focal_loss 0.15462 dice_loss 0.10675 +Epoch [79/4000] Validation metric {'Val/mean dice_metric': 0.9468165636062622, 'Val/mean miou_metric': 0.9182044863700867, 'Val/mean f1': 0.9544374942779541, 'Val/mean precision': 0.9597904682159424, 'Val/mean recall': 0.9491439461708069, 'Val/mean hd95_metric': 8.82149600982666} +Cheakpoint... +Epoch [79/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9468], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9468165636062622, 'Val/mean miou_metric': 0.9182044863700867, 'Val/mean f1': 0.9544374942779541, 'Val/mean precision': 0.9597904682159424, 'Val/mean recall': 0.9491439461708069, 'Val/mean hd95_metric': 8.82149600982666} +Epoch [80/4000] Training [1/16] Loss: 0.03464 +Epoch [80/4000] Training [2/16] Loss: 0.02283 +Epoch [80/4000] Training [3/16] Loss: 0.02644 +Epoch [80/4000] Training [4/16] Loss: 0.02919 +Epoch [80/4000] Training [5/16] Loss: 0.02506 +Epoch [80/4000] Training [6/16] Loss: 0.02220 +Epoch [80/4000] Training [7/16] Loss: 0.02152 +Epoch [80/4000] Training [8/16] Loss: 0.04258 +Epoch [80/4000] Training [9/16] Loss: 0.02501 +Epoch [80/4000] Training [10/16] Loss: 0.02905 +Epoch [80/4000] Training [11/16] Loss: 0.02139 +Epoch [80/4000] Training [12/16] Loss: 0.03363 +Epoch [80/4000] Training [13/16] Loss: 0.12425 +Epoch [80/4000] Training [14/16] Loss: 0.03052 +Epoch [80/4000] Training [15/16] Loss: 0.03502 +Epoch [80/4000] Training [16/16] Loss: 0.03483 +Epoch [80/4000] Training metric {'Train/mean dice_metric': 0.9787861108779907, 'Train/mean miou_metric': 0.9591740965843201, 'Train/mean f1': 0.9779607653617859, 'Train/mean precision': 0.9735830426216125, 'Train/mean recall': 0.9823780059814453, 'Train/mean hd95_metric': 4.819513320922852} +Epoch [80/4000] Validation [1/4] Loss: 0.17331 focal_loss 0.09806 dice_loss 0.07525 +Epoch [80/4000] Validation [2/4] Loss: 0.40449 focal_loss 0.17071 dice_loss 0.23378 +Epoch [80/4000] Validation [3/4] Loss: 0.30394 focal_loss 0.17245 dice_loss 0.13148 +Epoch [80/4000] Validation [4/4] Loss: 0.21256 focal_loss 0.10621 dice_loss 0.10635 +Epoch [80/4000] Validation metric {'Val/mean dice_metric': 0.9515395164489746, 'Val/mean miou_metric': 0.9216650128364563, 'Val/mean f1': 0.9540762901306152, 'Val/mean precision': 0.9487214088439941, 'Val/mean recall': 0.9594919085502625, 'Val/mean hd95_metric': 10.4168701171875} +Cheakpoint... +Epoch [80/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9515], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9515395164489746, 'Val/mean miou_metric': 0.9216650128364563, 'Val/mean f1': 0.9540762901306152, 'Val/mean precision': 0.9487214088439941, 'Val/mean recall': 0.9594919085502625, 'Val/mean hd95_metric': 10.4168701171875} +Epoch [81/4000] Training [1/16] Loss: 0.03831 +Epoch [81/4000] Training [2/16] Loss: 0.02813 +Epoch [81/4000] Training [3/16] Loss: 0.03347 +Epoch [81/4000] Training [4/16] Loss: 0.02846 +Epoch [81/4000] Training [5/16] Loss: 0.03198 +Epoch [81/4000] Training [6/16] Loss: 0.03906 +Epoch [81/4000] Training [7/16] Loss: 0.02784 +Epoch [81/4000] Training [8/16] Loss: 0.04060 +Epoch [81/4000] Training [9/16] Loss: 0.02017 +Epoch [81/4000] Training [10/16] Loss: 0.03093 +Epoch [81/4000] Training [11/16] Loss: 0.02688 +Epoch [81/4000] Training [12/16] Loss: 0.02875 +Epoch [81/4000] Training [13/16] Loss: 0.02302 +Epoch [81/4000] Training [14/16] Loss: 0.01964 +Epoch [81/4000] Training [15/16] Loss: 0.02441 +Epoch [81/4000] Training [16/16] Loss: 0.03710 +Epoch [81/4000] Training metric {'Train/mean dice_metric': 0.9808181524276733, 'Train/mean miou_metric': 0.962439775466919, 'Train/mean f1': 0.9796091914176941, 'Train/mean precision': 0.9751261472702026, 'Train/mean recall': 0.9841336607933044, 'Train/mean hd95_metric': 2.913252115249634} +Epoch [81/4000] Validation [1/4] Loss: 0.44207 focal_loss 0.31548 dice_loss 0.12659 +Epoch [81/4000] Validation [2/4] Loss: 0.24785 focal_loss 0.09214 dice_loss 0.15572 +Epoch [81/4000] Validation [3/4] Loss: 0.27262 focal_loss 0.14306 dice_loss 0.12957 +Epoch [81/4000] Validation [4/4] Loss: 0.25576 focal_loss 0.12210 dice_loss 0.13366 +Epoch [81/4000] Validation metric {'Val/mean dice_metric': 0.9535146951675415, 'Val/mean miou_metric': 0.9240735769271851, 'Val/mean f1': 0.9557590484619141, 'Val/mean precision': 0.9510253071784973, 'Val/mean recall': 0.9605401158332825, 'Val/mean hd95_metric': 9.616308212280273} +Cheakpoint... +Epoch [81/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9535], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9535146951675415, 'Val/mean miou_metric': 0.9240735769271851, 'Val/mean f1': 0.9557590484619141, 'Val/mean precision': 0.9510253071784973, 'Val/mean recall': 0.9605401158332825, 'Val/mean hd95_metric': 9.616308212280273} +Epoch [82/4000] Training [1/16] Loss: 0.02387 +Epoch [82/4000] Training [2/16] Loss: 0.02069 +Epoch [82/4000] Training [3/16] Loss: 0.02300 +Epoch [82/4000] Training [4/16] Loss: 0.04538 +Epoch [82/4000] Training [5/16] Loss: 0.02187 +Epoch [82/4000] Training [6/16] Loss: 0.02665 +Epoch [82/4000] Training [7/16] Loss: 0.02543 +Epoch [82/4000] Training [8/16] Loss: 0.02545 +Epoch [82/4000] Training [9/16] Loss: 0.02148 +Epoch [82/4000] Training [10/16] Loss: 0.02396 +Epoch [82/4000] Training [11/16] Loss: 0.04015 +Epoch [82/4000] Training [12/16] Loss: 0.02531 +Epoch [82/4000] Training [13/16] Loss: 0.06926 +Epoch [82/4000] Training [14/16] Loss: 0.03405 +Epoch [82/4000] Training [15/16] Loss: 0.02184 +Epoch [82/4000] Training [16/16] Loss: 0.01947 +Epoch [82/4000] Training metric {'Train/mean dice_metric': 0.9767286777496338, 'Train/mean miou_metric': 0.9579663276672363, 'Train/mean f1': 0.9762263298034668, 'Train/mean precision': 0.971126139163971, 'Train/mean recall': 0.9813804030418396, 'Train/mean hd95_metric': 5.827303886413574} +Epoch [82/4000] Validation [1/4] Loss: 0.72828 focal_loss 0.55400 dice_loss 0.17428 +Epoch [82/4000] Validation [2/4] Loss: 0.21457 focal_loss 0.07156 dice_loss 0.14301 +Epoch [82/4000] Validation [3/4] Loss: 0.15307 focal_loss 0.08008 dice_loss 0.07299 +Epoch [82/4000] Validation [4/4] Loss: 0.25266 focal_loss 0.12008 dice_loss 0.13258 +Epoch [82/4000] Validation metric {'Val/mean dice_metric': 0.9500066637992859, 'Val/mean miou_metric': 0.9210659265518188, 'Val/mean f1': 0.9545918703079224, 'Val/mean precision': 0.9541876912117004, 'Val/mean recall': 0.9549963474273682, 'Val/mean hd95_metric': 10.76224422454834} +Cheakpoint... +Epoch [82/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9500], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9500066637992859, 'Val/mean miou_metric': 0.9210659265518188, 'Val/mean f1': 0.9545918703079224, 'Val/mean precision': 0.9541876912117004, 'Val/mean recall': 0.9549963474273682, 'Val/mean hd95_metric': 10.76224422454834} +Epoch [83/4000] Training [1/16] Loss: 0.02463 +Epoch [83/4000] Training [2/16] Loss: 0.02100 +Epoch [83/4000] Training [3/16] Loss: 0.01938 +Epoch [83/4000] Training [4/16] Loss: 0.01828 +Epoch [83/4000] Training [5/16] Loss: 0.02401 +Epoch [83/4000] Training [6/16] Loss: 0.03188 +Epoch [83/4000] Training [7/16] Loss: 0.02836 +Epoch [83/4000] Training [8/16] Loss: 0.03207 +Epoch [83/4000] Training [9/16] Loss: 0.03702 +Epoch [83/4000] Training [10/16] Loss: 0.07759 +Epoch [83/4000] Training [11/16] Loss: 0.02296 +Epoch [83/4000] Training [12/16] Loss: 0.02124 +Epoch [83/4000] Training [13/16] Loss: 0.02534 +Epoch [83/4000] Training [14/16] Loss: 0.02860 +Epoch [83/4000] Training [15/16] Loss: 0.04609 +Epoch [83/4000] Training [16/16] Loss: 0.02948 +Epoch [83/4000] Training metric {'Train/mean dice_metric': 0.9808849096298218, 'Train/mean miou_metric': 0.9629946947097778, 'Train/mean f1': 0.9798663258552551, 'Train/mean precision': 0.9736800193786621, 'Train/mean recall': 0.9861318469047546, 'Train/mean hd95_metric': 3.2081456184387207} +Epoch [83/4000] Validation [1/4] Loss: 0.43219 focal_loss 0.31665 dice_loss 0.11554 +Epoch [83/4000] Validation [2/4] Loss: 0.45110 focal_loss 0.19707 dice_loss 0.25402 +Epoch [83/4000] Validation [3/4] Loss: 0.24174 focal_loss 0.12471 dice_loss 0.11703 +Epoch [83/4000] Validation [4/4] Loss: 0.21607 focal_loss 0.09659 dice_loss 0.11948 +Epoch [83/4000] Validation metric {'Val/mean dice_metric': 0.9535297155380249, 'Val/mean miou_metric': 0.9255462884902954, 'Val/mean f1': 0.9588950276374817, 'Val/mean precision': 0.9559605121612549, 'Val/mean recall': 0.9618475437164307, 'Val/mean hd95_metric': 8.46953010559082} +Cheakpoint... +Epoch [83/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9535], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9535297155380249, 'Val/mean miou_metric': 0.9255462884902954, 'Val/mean f1': 0.9588950276374817, 'Val/mean precision': 0.9559605121612549, 'Val/mean recall': 0.9618475437164307, 'Val/mean hd95_metric': 8.46953010559082} +Epoch [84/4000] Training [1/16] Loss: 0.03833 +Epoch [84/4000] Training [2/16] Loss: 0.01969 +Epoch [84/4000] Training [3/16] Loss: 0.03413 +Epoch [84/4000] Training [4/16] Loss: 0.02622 +Epoch [84/4000] Training [5/16] Loss: 0.03131 +Epoch [84/4000] Training [6/16] Loss: 0.03073 +Epoch [84/4000] Training [7/16] Loss: 0.02539 +Epoch [84/4000] Training [8/16] Loss: 0.02501 +Epoch [84/4000] Training [9/16] Loss: 0.02360 +Epoch [84/4000] Training [10/16] Loss: 0.04773 +Epoch [84/4000] Training [11/16] Loss: 0.02509 +Epoch [84/4000] Training [12/16] Loss: 0.02004 +Epoch [84/4000] Training [13/16] Loss: 0.02012 +Epoch [84/4000] Training [14/16] Loss: 0.02283 +Epoch [84/4000] Training [15/16] Loss: 0.01904 +Epoch [84/4000] Training [16/16] Loss: 0.03570 +Epoch [84/4000] Training metric {'Train/mean dice_metric': 0.9819199442863464, 'Train/mean miou_metric': 0.9647411704063416, 'Train/mean f1': 0.9804623126983643, 'Train/mean precision': 0.9756579995155334, 'Train/mean recall': 0.9853141903877258, 'Train/mean hd95_metric': 2.80446720123291} +Epoch [84/4000] Validation [1/4] Loss: 0.22344 focal_loss 0.12398 dice_loss 0.09946 +Epoch [84/4000] Validation [2/4] Loss: 0.19554 focal_loss 0.06912 dice_loss 0.12642 +Epoch [84/4000] Validation [3/4] Loss: 0.25231 focal_loss 0.11908 dice_loss 0.13322 +Epoch [84/4000] Validation [4/4] Loss: 0.33296 focal_loss 0.17487 dice_loss 0.15809 +Epoch [84/4000] Validation metric {'Val/mean dice_metric': 0.9567685127258301, 'Val/mean miou_metric': 0.9290391802787781, 'Val/mean f1': 0.9622347950935364, 'Val/mean precision': 0.9622798562049866, 'Val/mean recall': 0.9621897339820862, 'Val/mean hd95_metric': 7.370654106140137} +Cheakpoint... +Epoch [84/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9568], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9567685127258301, 'Val/mean miou_metric': 0.9290391802787781, 'Val/mean f1': 0.9622347950935364, 'Val/mean precision': 0.9622798562049866, 'Val/mean recall': 0.9621897339820862, 'Val/mean hd95_metric': 7.370654106140137} +Epoch [85/4000] Training [1/16] Loss: 0.01584 +Epoch [85/4000] Training [2/16] Loss: 0.02178 +Epoch [85/4000] Training [3/16] Loss: 0.03037 +Epoch [85/4000] Training [4/16] Loss: 0.01807 +Epoch [85/4000] Training [5/16] Loss: 0.01981 +Epoch [85/4000] Training [6/16] Loss: 0.03284 +Epoch [85/4000] Training [7/16] Loss: 0.02266 +Epoch [85/4000] Training [8/16] Loss: 0.02754 +Epoch [85/4000] Training [9/16] Loss: 0.02330 +Epoch [85/4000] Training [10/16] Loss: 0.01978 +Epoch [85/4000] Training [11/16] Loss: 0.02052 +Epoch [85/4000] Training [12/16] Loss: 0.02932 +Epoch [85/4000] Training [13/16] Loss: 0.02461 +Epoch [85/4000] Training [14/16] Loss: 0.02197 +Epoch [85/4000] Training [15/16] Loss: 0.04557 +Epoch [85/4000] Training [16/16] Loss: 0.01997 +Epoch [85/4000] Training metric {'Train/mean dice_metric': 0.9845132827758789, 'Train/mean miou_metric': 0.9694389700889587, 'Train/mean f1': 0.9813001155853271, 'Train/mean precision': 0.9770273566246033, 'Train/mean recall': 0.9856104850769043, 'Train/mean hd95_metric': 2.2202043533325195} +Epoch [85/4000] Validation [1/4] Loss: 0.23806 focal_loss 0.12590 dice_loss 0.11216 +Epoch [85/4000] Validation [2/4] Loss: 0.40263 focal_loss 0.16571 dice_loss 0.23691 +Epoch [85/4000] Validation [3/4] Loss: 0.19871 focal_loss 0.08467 dice_loss 0.11404 +Epoch [85/4000] Validation [4/4] Loss: 0.23502 focal_loss 0.10890 dice_loss 0.12612 +Epoch [85/4000] Validation metric {'Val/mean dice_metric': 0.9542704820632935, 'Val/mean miou_metric': 0.9281021356582642, 'Val/mean f1': 0.9588080644607544, 'Val/mean precision': 0.9543038606643677, 'Val/mean recall': 0.9633548855781555, 'Val/mean hd95_metric': 8.78856086730957} +Cheakpoint... +Epoch [85/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9543], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9542704820632935, 'Val/mean miou_metric': 0.9281021356582642, 'Val/mean f1': 0.9588080644607544, 'Val/mean precision': 0.9543038606643677, 'Val/mean recall': 0.9633548855781555, 'Val/mean hd95_metric': 8.78856086730957} +Epoch [86/4000] Training [1/16] Loss: 0.01756 +Epoch [86/4000] Training [2/16] Loss: 0.01761 +Epoch [86/4000] Training [3/16] Loss: 0.01987 +Epoch [86/4000] Training [4/16] Loss: 0.01950 +Epoch [86/4000] Training [5/16] Loss: 0.02245 +Epoch [86/4000] Training [6/16] Loss: 0.01687 +Epoch [86/4000] Training [7/16] Loss: 0.02924 +Epoch [86/4000] Training [8/16] Loss: 0.06519 +Epoch [86/4000] Training [9/16] Loss: 0.02891 +Epoch [86/4000] Training [10/16] Loss: 0.01918 +Epoch [86/4000] Training [11/16] Loss: 0.03735 +Epoch [86/4000] Training [12/16] Loss: 0.02528 +Epoch [86/4000] Training [13/16] Loss: 0.02597 +Epoch [86/4000] Training [14/16] Loss: 0.01904 +Epoch [86/4000] Training [15/16] Loss: 0.02887 +Epoch [86/4000] Training [16/16] Loss: 0.01838 +Epoch [86/4000] Training metric {'Train/mean dice_metric': 0.9807710647583008, 'Train/mean miou_metric': 0.9642981290817261, 'Train/mean f1': 0.9808340668678284, 'Train/mean precision': 0.977519154548645, 'Train/mean recall': 0.9841715097427368, 'Train/mean hd95_metric': 4.148019790649414} +Epoch [86/4000] Validation [1/4] Loss: 0.94391 focal_loss 0.76153 dice_loss 0.18237 +Epoch [86/4000] Validation [2/4] Loss: 0.70482 focal_loss 0.38464 dice_loss 0.32018 +Epoch [86/4000] Validation [3/4] Loss: 0.26888 focal_loss 0.15884 dice_loss 0.11004 +Epoch [86/4000] Validation [4/4] Loss: 0.23478 focal_loss 0.11794 dice_loss 0.11684 +Epoch [86/4000] Validation metric {'Val/mean dice_metric': 0.9494508504867554, 'Val/mean miou_metric': 0.9218384027481079, 'Val/mean f1': 0.9542088508605957, 'Val/mean precision': 0.9609036445617676, 'Val/mean recall': 0.9476068019866943, 'Val/mean hd95_metric': 9.61917781829834} +Cheakpoint... +Epoch [86/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9495], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9494508504867554, 'Val/mean miou_metric': 0.9218384027481079, 'Val/mean f1': 0.9542088508605957, 'Val/mean precision': 0.9609036445617676, 'Val/mean recall': 0.9476068019866943, 'Val/mean hd95_metric': 9.61917781829834} +Epoch [87/4000] Training [1/16] Loss: 0.02353 +Epoch [87/4000] Training [2/16] Loss: 0.02733 +Epoch [87/4000] Training [3/16] Loss: 0.02894 +Epoch [87/4000] Training [4/16] Loss: 0.02807 +Epoch [87/4000] Training [5/16] Loss: 0.29263 +Epoch [87/4000] Training [6/16] Loss: 0.06622 +Epoch [87/4000] Training [7/16] Loss: 0.03095 +Epoch [87/4000] Training [8/16] Loss: 0.04050 +Epoch [87/4000] Training [9/16] Loss: 0.02059 +Epoch [87/4000] Training [10/16] Loss: 0.02091 +Epoch [87/4000] Training [11/16] Loss: 0.03207 +Epoch [87/4000] Training [12/16] Loss: 0.02925 +Epoch [87/4000] Training [13/16] Loss: 0.02448 +Epoch [87/4000] Training [14/16] Loss: 0.03658 +Epoch [87/4000] Training [15/16] Loss: 0.02561 +Epoch [87/4000] Training [16/16] Loss: 0.03584 +Epoch [87/4000] Training metric {'Train/mean dice_metric': 0.9719586372375488, 'Train/mean miou_metric': 0.9488580822944641, 'Train/mean f1': 0.9674647450447083, 'Train/mean precision': 0.9619101881980896, 'Train/mean recall': 0.9730837345123291, 'Train/mean hd95_metric': 7.026099681854248} +Epoch [87/4000] Validation [1/4] Loss: 0.14026 focal_loss 0.07213 dice_loss 0.06813 +Epoch [87/4000] Validation [2/4] Loss: 0.33325 focal_loss 0.12771 dice_loss 0.20554 +Epoch [87/4000] Validation [3/4] Loss: 0.16796 focal_loss 0.08102 dice_loss 0.08694 +Epoch [87/4000] Validation [4/4] Loss: 0.20673 focal_loss 0.09655 dice_loss 0.11019 +Epoch [87/4000] Validation metric {'Val/mean dice_metric': 0.9440733790397644, 'Val/mean miou_metric': 0.9107492566108704, 'Val/mean f1': 0.9450898170471191, 'Val/mean precision': 0.941998302936554, 'Val/mean recall': 0.948201596736908, 'Val/mean hd95_metric': 12.58050537109375} +Cheakpoint... +Epoch [87/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9441], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9440733790397644, 'Val/mean miou_metric': 0.9107492566108704, 'Val/mean f1': 0.9450898170471191, 'Val/mean precision': 0.941998302936554, 'Val/mean recall': 0.948201596736908, 'Val/mean hd95_metric': 12.58050537109375} +Epoch [88/4000] Training [1/16] Loss: 0.04012 +Epoch [88/4000] Training [2/16] Loss: 0.02466 +Epoch [88/4000] Training [3/16] Loss: 0.04304 +Epoch [88/4000] Training [4/16] Loss: 0.03584 +Epoch [88/4000] Training [5/16] Loss: 0.03731 +Epoch [88/4000] Training [6/16] Loss: 0.04498 +Epoch [88/4000] Training [7/16] Loss: 0.02857 +Epoch [88/4000] Training [8/16] Loss: 0.04713 +Epoch [88/4000] Training [9/16] Loss: 0.05308 +Epoch [88/4000] Training [10/16] Loss: 0.02794 +Epoch [88/4000] Training [11/16] Loss: 0.03145 +Epoch [88/4000] Training [12/16] Loss: 0.02846 +Epoch [88/4000] Training [13/16] Loss: 0.02666 +Epoch [88/4000] Training [14/16] Loss: 0.02565 +Epoch [88/4000] Training [15/16] Loss: 0.02212 +Epoch [88/4000] Training [16/16] Loss: 0.04825 +Epoch [88/4000] Training metric {'Train/mean dice_metric': 0.9762049317359924, 'Train/mean miou_metric': 0.9543114900588989, 'Train/mean f1': 0.9734845161437988, 'Train/mean precision': 0.9682709574699402, 'Train/mean recall': 0.9787545204162598, 'Train/mean hd95_metric': 5.707960605621338} +Epoch [88/4000] Validation [1/4] Loss: 0.20985 focal_loss 0.10713 dice_loss 0.10271 +Epoch [88/4000] Validation [2/4] Loss: 0.41428 focal_loss 0.17938 dice_loss 0.23490 +Epoch [88/4000] Validation [3/4] Loss: 0.14210 focal_loss 0.05566 dice_loss 0.08644 +Epoch [88/4000] Validation [4/4] Loss: 0.14694 focal_loss 0.06632 dice_loss 0.08062 +Epoch [88/4000] Validation metric {'Val/mean dice_metric': 0.9485479593276978, 'Val/mean miou_metric': 0.9163920283317566, 'Val/mean f1': 0.9524883031845093, 'Val/mean precision': 0.9501572847366333, 'Val/mean recall': 0.9548308849334717, 'Val/mean hd95_metric': 11.24659538269043} +Cheakpoint... +Epoch [88/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9485], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9485479593276978, 'Val/mean miou_metric': 0.9163920283317566, 'Val/mean f1': 0.9524883031845093, 'Val/mean precision': 0.9501572847366333, 'Val/mean recall': 0.9548308849334717, 'Val/mean hd95_metric': 11.24659538269043} +Epoch [89/4000] Training [1/16] Loss: 0.02234 +Epoch [89/4000] Training [2/16] Loss: 0.04205 +Epoch [89/4000] Training [3/16] Loss: 0.03599 +Epoch [89/4000] Training [4/16] Loss: 0.03269 +Epoch [89/4000] Training [5/16] Loss: 0.02515 +Epoch [89/4000] Training [6/16] Loss: 0.03296 +Epoch [89/4000] Training [7/16] Loss: 0.02344 +Epoch [89/4000] Training [8/16] Loss: 0.02602 +Epoch [89/4000] Training [9/16] Loss: 0.03095 +Epoch [89/4000] Training [10/16] Loss: 0.02404 +Epoch [89/4000] Training [11/16] Loss: 0.02821 +Epoch [89/4000] Training [12/16] Loss: 0.05241 +Epoch [89/4000] Training [13/16] Loss: 0.01913 +Epoch [89/4000] Training [14/16] Loss: 0.02915 +Epoch [89/4000] Training [15/16] Loss: 0.03498 +Epoch [89/4000] Training [16/16] Loss: 0.03853 +Epoch [89/4000] Training metric {'Train/mean dice_metric': 0.9780922532081604, 'Train/mean miou_metric': 0.9590956568717957, 'Train/mean f1': 0.976708173751831, 'Train/mean precision': 0.9727546572685242, 'Train/mean recall': 0.9806938767433167, 'Train/mean hd95_metric': 3.7901711463928223} +Epoch [89/4000] Validation [1/4] Loss: 0.16316 focal_loss 0.08992 dice_loss 0.07324 +Epoch [89/4000] Validation [2/4] Loss: 0.41231 focal_loss 0.16749 dice_loss 0.24482 +Epoch [89/4000] Validation [3/4] Loss: 0.14939 focal_loss 0.06541 dice_loss 0.08398 +Epoch [89/4000] Validation [4/4] Loss: 0.17802 focal_loss 0.06440 dice_loss 0.11362 +Epoch [89/4000] Validation metric {'Val/mean dice_metric': 0.9529476165771484, 'Val/mean miou_metric': 0.9237228631973267, 'Val/mean f1': 0.9553399682044983, 'Val/mean precision': 0.9425442218780518, 'Val/mean recall': 0.9684878587722778, 'Val/mean hd95_metric': 9.669439315795898} +Cheakpoint... +Epoch [89/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9529], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9529476165771484, 'Val/mean miou_metric': 0.9237228631973267, 'Val/mean f1': 0.9553399682044983, 'Val/mean precision': 0.9425442218780518, 'Val/mean recall': 0.9684878587722778, 'Val/mean hd95_metric': 9.669439315795898} +Epoch [90/4000] Training [1/16] Loss: 0.02833 +Epoch [90/4000] Training [2/16] Loss: 0.02439 +Epoch [90/4000] Training [3/16] Loss: 0.02516 +Epoch [90/4000] Training [4/16] Loss: 0.02196 +Epoch [90/4000] Training [5/16] Loss: 0.01854 +Epoch [90/4000] Training [6/16] Loss: 0.02212 +Epoch [90/4000] Training [7/16] Loss: 0.02421 +Epoch [90/4000] Training [8/16] Loss: 0.02550 +Epoch [90/4000] Training [9/16] Loss: 0.02122 +Epoch [90/4000] Training [10/16] Loss: 0.02390 +Epoch [90/4000] Training [11/16] Loss: 0.02047 +Epoch [90/4000] Training [12/16] Loss: 0.04004 +Epoch [90/4000] Training [13/16] Loss: 0.02807 +Epoch [90/4000] Training [14/16] Loss: 0.05229 +Epoch [90/4000] Training [15/16] Loss: 0.02464 +Epoch [90/4000] Training [16/16] Loss: 0.02738 +Epoch [90/4000] Training metric {'Train/mean dice_metric': 0.981503963470459, 'Train/mean miou_metric': 0.9641745686531067, 'Train/mean f1': 0.9797874689102173, 'Train/mean precision': 0.9748803973197937, 'Train/mean recall': 0.9847443103790283, 'Train/mean hd95_metric': 3.805753707885742} +Epoch [90/4000] Validation [1/4] Loss: 0.17002 focal_loss 0.08778 dice_loss 0.08224 +Epoch [90/4000] Validation [2/4] Loss: 0.43702 focal_loss 0.17313 dice_loss 0.26389 +Epoch [90/4000] Validation [3/4] Loss: 0.24959 focal_loss 0.12626 dice_loss 0.12333 +Epoch [90/4000] Validation [4/4] Loss: 0.10710 focal_loss 0.03698 dice_loss 0.07012 +Epoch [90/4000] Validation metric {'Val/mean dice_metric': 0.9564691781997681, 'Val/mean miou_metric': 0.9292479753494263, 'Val/mean f1': 0.9590689539909363, 'Val/mean precision': 0.9501001834869385, 'Val/mean recall': 0.9682087302207947, 'Val/mean hd95_metric': 8.980108261108398} +Cheakpoint... +Epoch [90/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9565], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9564691781997681, 'Val/mean miou_metric': 0.9292479753494263, 'Val/mean f1': 0.9590689539909363, 'Val/mean precision': 0.9501001834869385, 'Val/mean recall': 0.9682087302207947, 'Val/mean hd95_metric': 8.980108261108398} +Epoch [91/4000] Training [1/16] Loss: 0.02210 +Epoch [91/4000] Training [2/16] Loss: 0.02990 +Epoch [91/4000] Training [3/16] Loss: 0.02497 +Epoch [91/4000] Training [4/16] Loss: 0.03267 +Epoch [91/4000] Training [5/16] Loss: 0.02389 +Epoch [91/4000] Training [6/16] Loss: 0.02773 +Epoch [91/4000] Training [7/16] Loss: 0.01698 +Epoch [91/4000] Training [8/16] Loss: 0.02421 +Epoch [91/4000] Training [9/16] Loss: 0.02217 +Epoch [91/4000] Training [10/16] Loss: 0.02586 +Epoch [91/4000] Training [11/16] Loss: 0.02136 +Epoch [91/4000] Training [12/16] Loss: 0.01951 +Epoch [91/4000] Training [13/16] Loss: 0.03007 +Epoch [91/4000] Training [14/16] Loss: 0.01660 +Epoch [91/4000] Training [15/16] Loss: 0.03686 +Epoch [91/4000] Training [16/16] Loss: 0.01447 +Epoch [91/4000] Training metric {'Train/mean dice_metric': 0.9826563596725464, 'Train/mean miou_metric': 0.9659872055053711, 'Train/mean f1': 0.9805309772491455, 'Train/mean precision': 0.9759266972541809, 'Train/mean recall': 0.9851789474487305, 'Train/mean hd95_metric': 2.8037378787994385} +Epoch [91/4000] Validation [1/4] Loss: 0.23225 focal_loss 0.13327 dice_loss 0.09897 +Epoch [91/4000] Validation [2/4] Loss: 0.30666 focal_loss 0.11353 dice_loss 0.19313 +Epoch [91/4000] Validation [3/4] Loss: 0.25601 focal_loss 0.13577 dice_loss 0.12024 +Epoch [91/4000] Validation [4/4] Loss: 0.18104 focal_loss 0.06703 dice_loss 0.11401 +Epoch [91/4000] Validation metric {'Val/mean dice_metric': 0.9584657549858093, 'Val/mean miou_metric': 0.9321610331535339, 'Val/mean f1': 0.961854100227356, 'Val/mean precision': 0.9563626646995544, 'Val/mean recall': 0.9674089550971985, 'Val/mean hd95_metric': 7.556601047515869} +Cheakpoint... +Epoch [91/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9585], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9584657549858093, 'Val/mean miou_metric': 0.9321610331535339, 'Val/mean f1': 0.961854100227356, 'Val/mean precision': 0.9563626646995544, 'Val/mean recall': 0.9674089550971985, 'Val/mean hd95_metric': 7.556601047515869} +Epoch [92/4000] Training [1/16] Loss: 0.02980 +Epoch [92/4000] Training [2/16] Loss: 0.02624 +Epoch [92/4000] Training [3/16] Loss: 0.01987 +Epoch [92/4000] Training [4/16] Loss: 0.02221 +Epoch [92/4000] Training [5/16] Loss: 0.01839 +Epoch [92/4000] Training [6/16] Loss: 0.02271 +Epoch [92/4000] Training [7/16] Loss: 0.02505 +Epoch [92/4000] Training [8/16] Loss: 0.02408 +Epoch [92/4000] Training [9/16] Loss: 0.01935 +Epoch [92/4000] Training [10/16] Loss: 0.01595 +Epoch [92/4000] Training [11/16] Loss: 0.02282 +Epoch [92/4000] Training [12/16] Loss: 0.01625 +Epoch [92/4000] Training [13/16] Loss: 0.01995 +Epoch [92/4000] Training [14/16] Loss: 0.01957 +Epoch [92/4000] Training [15/16] Loss: 0.02061 +Epoch [92/4000] Training [16/16] Loss: 0.02020 +Epoch [92/4000] Training metric {'Train/mean dice_metric': 0.9838094115257263, 'Train/mean miou_metric': 0.9698408842086792, 'Train/mean f1': 0.9830920696258545, 'Train/mean precision': 0.9783445596694946, 'Train/mean recall': 0.9878858923912048, 'Train/mean hd95_metric': 1.9520374536514282} +Epoch [92/4000] Validation [1/4] Loss: 0.23131 focal_loss 0.13301 dice_loss 0.09830 +Epoch [92/4000] Validation [2/4] Loss: 0.41679 focal_loss 0.17316 dice_loss 0.24363 +Epoch [92/4000] Validation [3/4] Loss: 0.14943 focal_loss 0.05430 dice_loss 0.09513 +Epoch [92/4000] Validation [4/4] Loss: 0.15485 focal_loss 0.06120 dice_loss 0.09365 +Epoch [92/4000] Validation metric {'Val/mean dice_metric': 0.9602686762809753, 'Val/mean miou_metric': 0.9358718991279602, 'Val/mean f1': 0.9647480249404907, 'Val/mean precision': 0.9614170789718628, 'Val/mean recall': 0.9681021571159363, 'Val/mean hd95_metric': 6.624011039733887} +Cheakpoint... +Epoch [92/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9603], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9602686762809753, 'Val/mean miou_metric': 0.9358718991279602, 'Val/mean f1': 0.9647480249404907, 'Val/mean precision': 0.9614170789718628, 'Val/mean recall': 0.9681021571159363, 'Val/mean hd95_metric': 6.624011039733887} +Epoch [93/4000] Training [1/16] Loss: 0.02020 +Epoch [93/4000] Training [2/16] Loss: 0.01751 +Epoch [93/4000] Training [3/16] Loss: 0.01737 +Epoch [93/4000] Training [4/16] Loss: 0.02081 +Epoch [93/4000] Training [5/16] Loss: 0.01878 +Epoch [93/4000] Training [6/16] Loss: 0.01864 +Epoch [93/4000] Training [7/16] Loss: 0.01565 +Epoch [93/4000] Training [8/16] Loss: 0.01963 +Epoch [93/4000] Training [9/16] Loss: 0.01802 +Epoch [93/4000] Training [10/16] Loss: 0.01656 +Epoch [93/4000] Training [11/16] Loss: 0.02156 +Epoch [93/4000] Training [12/16] Loss: 0.01535 +Epoch [93/4000] Training [13/16] Loss: 0.02941 +Epoch [93/4000] Training [14/16] Loss: 0.02052 +Epoch [93/4000] Training [15/16] Loss: 0.02647 +Epoch [93/4000] Training [16/16] Loss: 0.01938 +Epoch [93/4000] Training metric {'Train/mean dice_metric': 0.9836209416389465, 'Train/mean miou_metric': 0.9693406820297241, 'Train/mean f1': 0.9799527525901794, 'Train/mean precision': 0.9732249975204468, 'Train/mean recall': 0.986774206161499, 'Train/mean hd95_metric': 4.336586952209473} +Epoch [93/4000] Validation [1/4] Loss: 0.51146 focal_loss 0.31351 dice_loss 0.19795 +Epoch [93/4000] Validation [2/4] Loss: 0.55908 focal_loss 0.24816 dice_loss 0.31092 +Epoch [93/4000] Validation [3/4] Loss: 0.27542 focal_loss 0.14534 dice_loss 0.13008 +Epoch [93/4000] Validation [4/4] Loss: 0.22861 focal_loss 0.12431 dice_loss 0.10430 +Epoch [93/4000] Validation metric {'Val/mean dice_metric': 0.9566633105278015, 'Val/mean miou_metric': 0.9308931231498718, 'Val/mean f1': 0.958375871181488, 'Val/mean precision': 0.9602641463279724, 'Val/mean recall': 0.9564951062202454, 'Val/mean hd95_metric': 9.452674865722656} +Cheakpoint... +Epoch [93/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9567], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9566633105278015, 'Val/mean miou_metric': 0.9308931231498718, 'Val/mean f1': 0.958375871181488, 'Val/mean precision': 0.9602641463279724, 'Val/mean recall': 0.9564951062202454, 'Val/mean hd95_metric': 9.452674865722656} +Epoch [94/4000] Training [1/16] Loss: 0.01936 +Epoch [94/4000] Training [2/16] Loss: 0.02047 +Epoch [94/4000] Training [3/16] Loss: 0.03483 +Epoch [94/4000] Training [4/16] Loss: 0.02987 +Epoch [94/4000] Training [5/16] Loss: 0.02665 +Epoch [94/4000] Training [6/16] Loss: 0.03304 +Epoch [94/4000] Training [7/16] Loss: 0.02466 +Epoch [94/4000] Training [8/16] Loss: 0.03815 +Epoch [94/4000] Training [9/16] Loss: 0.02942 +Epoch [94/4000] Training [10/16] Loss: 0.02051 +Epoch [94/4000] Training [11/16] Loss: 0.02601 +Epoch [94/4000] Training [12/16] Loss: 0.03670 +Epoch [94/4000] Training [13/16] Loss: 0.02645 +Epoch [94/4000] Training [14/16] Loss: 0.02258 +Epoch [94/4000] Training [15/16] Loss: 0.03137 +Epoch [94/4000] Training [16/16] Loss: 0.02266 +Epoch [94/4000] Training metric {'Train/mean dice_metric': 0.9795677661895752, 'Train/mean miou_metric': 0.961094319820404, 'Train/mean f1': 0.9754171371459961, 'Train/mean precision': 0.9719958305358887, 'Train/mean recall': 0.9788625240325928, 'Train/mean hd95_metric': 4.237557411193848} +Epoch [94/4000] Validation [1/4] Loss: 0.19856 focal_loss 0.10956 dice_loss 0.08901 +Epoch [94/4000] Validation [2/4] Loss: 0.24865 focal_loss 0.07039 dice_loss 0.17826 +Epoch [94/4000] Validation [3/4] Loss: 0.14346 focal_loss 0.05538 dice_loss 0.08807 +Epoch [94/4000] Validation [4/4] Loss: 0.21810 focal_loss 0.10168 dice_loss 0.11641 +Epoch [94/4000] Validation metric {'Val/mean dice_metric': 0.9562536478042603, 'Val/mean miou_metric': 0.927569568157196, 'Val/mean f1': 0.9573420286178589, 'Val/mean precision': 0.9507557153701782, 'Val/mean recall': 0.9640201926231384, 'Val/mean hd95_metric': 9.524946212768555} +Cheakpoint... +Epoch [94/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9563], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9562536478042603, 'Val/mean miou_metric': 0.927569568157196, 'Val/mean f1': 0.9573420286178589, 'Val/mean precision': 0.9507557153701782, 'Val/mean recall': 0.9640201926231384, 'Val/mean hd95_metric': 9.524946212768555} +Epoch [95/4000] Training [1/16] Loss: 0.01793 +Epoch [95/4000] Training [2/16] Loss: 0.02528 +Epoch [95/4000] Training [3/16] Loss: 0.01885 +Epoch [95/4000] Training [4/16] Loss: 0.02809 +Epoch [95/4000] Training [5/16] Loss: 0.02214 +Epoch [95/4000] Training [6/16] Loss: 0.02027 +Epoch [95/4000] Training [7/16] Loss: 0.03676 +Epoch [95/4000] Training [8/16] Loss: 0.02138 +Epoch [95/4000] Training [9/16] Loss: 0.05284 +Epoch [95/4000] Training [10/16] Loss: 0.02185 +Epoch [95/4000] Training [11/16] Loss: 0.02677 +Epoch [95/4000] Training [12/16] Loss: 0.02221 +Epoch [95/4000] Training [13/16] Loss: 0.02659 +Epoch [95/4000] Training [14/16] Loss: 0.03004 +Epoch [95/4000] Training [15/16] Loss: 0.03143 +Epoch [95/4000] Training [16/16] Loss: 0.02648 +Epoch [95/4000] Training metric {'Train/mean dice_metric': 0.9828307628631592, 'Train/mean miou_metric': 0.9664047360420227, 'Train/mean f1': 0.9788348078727722, 'Train/mean precision': 0.9773547649383545, 'Train/mean recall': 0.9803192615509033, 'Train/mean hd95_metric': 3.524526596069336} +Epoch [95/4000] Validation [1/4] Loss: 0.14628 focal_loss 0.07519 dice_loss 0.07109 +Epoch [95/4000] Validation [2/4] Loss: 0.35877 focal_loss 0.12842 dice_loss 0.23035 +Epoch [95/4000] Validation [3/4] Loss: 0.14194 focal_loss 0.06192 dice_loss 0.08001 +Epoch [95/4000] Validation [4/4] Loss: 0.19780 focal_loss 0.09314 dice_loss 0.10466 +Epoch [95/4000] Validation metric {'Val/mean dice_metric': 0.9590193033218384, 'Val/mean miou_metric': 0.9319131970405579, 'Val/mean f1': 0.9601448774337769, 'Val/mean precision': 0.9507956504821777, 'Val/mean recall': 0.9696797132492065, 'Val/mean hd95_metric': 9.626213073730469} +Cheakpoint... +Epoch [95/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9590], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9590193033218384, 'Val/mean miou_metric': 0.9319131970405579, 'Val/mean f1': 0.9601448774337769, 'Val/mean precision': 0.9507956504821777, 'Val/mean recall': 0.9696797132492065, 'Val/mean hd95_metric': 9.626213073730469} +Epoch [96/4000] Training [1/16] Loss: 0.02256 +Epoch [96/4000] Training [2/16] Loss: 0.02326 +Epoch [96/4000] Training [3/16] Loss: 0.04199 +Epoch [96/4000] Training [4/16] Loss: 0.02121 +Epoch [96/4000] Training [5/16] Loss: 0.01935 +Epoch [96/4000] Training [6/16] Loss: 0.03049 +Epoch [96/4000] Training [7/16] Loss: 0.02208 +Epoch [96/4000] Training [8/16] Loss: 0.02298 +Epoch [96/4000] Training [9/16] Loss: 0.03023 +Epoch [96/4000] Training [10/16] Loss: 0.02107 +Epoch [96/4000] Training [11/16] Loss: 0.02139 +Epoch [96/4000] Training [12/16] Loss: 0.02051 +Epoch [96/4000] Training [13/16] Loss: 0.02755 +Epoch [96/4000] Training [14/16] Loss: 0.03772 +Epoch [96/4000] Training [15/16] Loss: 0.02164 +Epoch [96/4000] Training [16/16] Loss: 0.02395 +Epoch [96/4000] Training metric {'Train/mean dice_metric': 0.981095552444458, 'Train/mean miou_metric': 0.9631800651550293, 'Train/mean f1': 0.9791849851608276, 'Train/mean precision': 0.9748260974884033, 'Train/mean recall': 0.9835830926895142, 'Train/mean hd95_metric': 4.231605529785156} +Epoch [96/4000] Validation [1/4] Loss: 0.22320 focal_loss 0.12155 dice_loss 0.10166 +Epoch [96/4000] Validation [2/4] Loss: 0.47768 focal_loss 0.24787 dice_loss 0.22981 +Epoch [96/4000] Validation [3/4] Loss: 0.11563 focal_loss 0.04890 dice_loss 0.06674 +Epoch [96/4000] Validation [4/4] Loss: 0.22686 focal_loss 0.08662 dice_loss 0.14024 +Epoch [96/4000] Validation metric {'Val/mean dice_metric': 0.9579361081123352, 'Val/mean miou_metric': 0.9287809133529663, 'Val/mean f1': 0.9604073166847229, 'Val/mean precision': 0.9514952898025513, 'Val/mean recall': 0.9694879651069641, 'Val/mean hd95_metric': 9.820520401000977} +Cheakpoint... +Epoch [96/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9579], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9579361081123352, 'Val/mean miou_metric': 0.9287809133529663, 'Val/mean f1': 0.9604073166847229, 'Val/mean precision': 0.9514952898025513, 'Val/mean recall': 0.9694879651069641, 'Val/mean hd95_metric': 9.820520401000977} +Epoch [97/4000] Training [1/16] Loss: 0.02350 +Epoch [97/4000] Training [2/16] Loss: 0.02651 +Epoch [97/4000] Training [3/16] Loss: 0.02947 +Epoch [97/4000] Training [4/16] Loss: 0.02200 +Epoch [97/4000] Training [5/16] Loss: 0.02013 +Epoch [97/4000] Training [6/16] Loss: 0.02365 +Epoch [97/4000] Training [7/16] Loss: 0.02695 +Epoch [97/4000] Training [8/16] Loss: 0.02738 +Epoch [97/4000] Training [9/16] Loss: 0.02113 +Epoch [97/4000] Training [10/16] Loss: 0.02707 +Epoch [97/4000] Training [11/16] Loss: 0.02186 +Epoch [97/4000] Training [12/16] Loss: 0.02211 +Epoch [97/4000] Training [13/16] Loss: 0.02163 +Epoch [97/4000] Training [14/16] Loss: 0.02770 +Epoch [97/4000] Training [15/16] Loss: 0.06976 +Epoch [97/4000] Training [16/16] Loss: 0.02234 +Epoch [97/4000] Training metric {'Train/mean dice_metric': 0.9820402264595032, 'Train/mean miou_metric': 0.9649808406829834, 'Train/mean f1': 0.9795048236846924, 'Train/mean precision': 0.9746641516685486, 'Train/mean recall': 0.984393835067749, 'Train/mean hd95_metric': 3.313431739807129} +Epoch [97/4000] Validation [1/4] Loss: 0.55728 focal_loss 0.41332 dice_loss 0.14395 +Epoch [97/4000] Validation [2/4] Loss: 0.21852 focal_loss 0.06682 dice_loss 0.15171 +Epoch [97/4000] Validation [3/4] Loss: 0.14405 focal_loss 0.05713 dice_loss 0.08692 +Epoch [97/4000] Validation [4/4] Loss: 0.14652 focal_loss 0.06120 dice_loss 0.08532 +Epoch [97/4000] Validation metric {'Val/mean dice_metric': 0.9587821960449219, 'Val/mean miou_metric': 0.9313150644302368, 'Val/mean f1': 0.9598086476325989, 'Val/mean precision': 0.9596458077430725, 'Val/mean recall': 0.9599713683128357, 'Val/mean hd95_metric': 7.504495143890381} +Cheakpoint... +Epoch [97/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9588], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9587821960449219, 'Val/mean miou_metric': 0.9313150644302368, 'Val/mean f1': 0.9598086476325989, 'Val/mean precision': 0.9596458077430725, 'Val/mean recall': 0.9599713683128357, 'Val/mean hd95_metric': 7.504495143890381} +Epoch [98/4000] Training [1/16] Loss: 0.04275 +Epoch [98/4000] Training [2/16] Loss: 0.02162 +Epoch [98/4000] Training [3/16] Loss: 0.02330 +Epoch [98/4000] Training [4/16] Loss: 0.02469 +Epoch [98/4000] Training [5/16] Loss: 0.02368 +Epoch [98/4000] Training [6/16] Loss: 0.02069 +Epoch [98/4000] Training [7/16] Loss: 0.02248 +Epoch [98/4000] Training [8/16] Loss: 0.02128 +Epoch [98/4000] Training [9/16] Loss: 0.04175 +Epoch [98/4000] Training [10/16] Loss: 0.06313 +Epoch [98/4000] Training [11/16] Loss: 0.02071 +Epoch [98/4000] Training [12/16] Loss: 0.03257 +Epoch [98/4000] Training [13/16] Loss: 0.02736 +Epoch [98/4000] Training [14/16] Loss: 0.04261 +Epoch [98/4000] Training [15/16] Loss: 0.04794 +Epoch [98/4000] Training [16/16] Loss: 0.03374 +Epoch [98/4000] Training metric {'Train/mean dice_metric': 0.9769402742385864, 'Train/mean miou_metric': 0.9567834734916687, 'Train/mean f1': 0.9756034016609192, 'Train/mean precision': 0.9710861444473267, 'Train/mean recall': 0.9801627993583679, 'Train/mean hd95_metric': 5.788812637329102} +Epoch [98/4000] Validation [1/4] Loss: 0.31861 focal_loss 0.19142 dice_loss 0.12719 +Epoch [98/4000] Validation [2/4] Loss: 0.47541 focal_loss 0.24660 dice_loss 0.22882 +Epoch [98/4000] Validation [3/4] Loss: 0.24439 focal_loss 0.09368 dice_loss 0.15071 +Epoch [98/4000] Validation [4/4] Loss: 0.18672 focal_loss 0.06540 dice_loss 0.12131 +Epoch [98/4000] Validation metric {'Val/mean dice_metric': 0.9505974054336548, 'Val/mean miou_metric': 0.9203577041625977, 'Val/mean f1': 0.9537566304206848, 'Val/mean precision': 0.9468534588813782, 'Val/mean recall': 0.9607611298561096, 'Val/mean hd95_metric': 11.276209831237793} +Cheakpoint... +Epoch [98/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9506], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9505974054336548, 'Val/mean miou_metric': 0.9203577041625977, 'Val/mean f1': 0.9537566304206848, 'Val/mean precision': 0.9468534588813782, 'Val/mean recall': 0.9607611298561096, 'Val/mean hd95_metric': 11.276209831237793} +Epoch [99/4000] Training [1/16] Loss: 0.01841 +Epoch [99/4000] Training [2/16] Loss: 0.03644 +Epoch [99/4000] Training [3/16] Loss: 0.04011 +Epoch [99/4000] Training [4/16] Loss: 0.02796 +Epoch [99/4000] Training [5/16] Loss: 0.02195 +Epoch [99/4000] Training [6/16] Loss: 0.02225 +Epoch [99/4000] Training [7/16] Loss: 0.02315 +Epoch [99/4000] Training [8/16] Loss: 0.02365 +Epoch [99/4000] Training [9/16] Loss: 0.01991 +Epoch [99/4000] Training [10/16] Loss: 0.01945 +Epoch [99/4000] Training [11/16] Loss: 0.02933 +Epoch [99/4000] Training [12/16] Loss: 0.02329 +Epoch [99/4000] Training [13/16] Loss: 0.02107 +Epoch [99/4000] Training [14/16] Loss: 0.02074 +Epoch [99/4000] Training [15/16] Loss: 0.02579 +Epoch [99/4000] Training [16/16] Loss: 0.02649 +Epoch [99/4000] Training metric {'Train/mean dice_metric': 0.9795752763748169, 'Train/mean miou_metric': 0.9610331058502197, 'Train/mean f1': 0.9779080748558044, 'Train/mean precision': 0.9764812588691711, 'Train/mean recall': 0.9793391227722168, 'Train/mean hd95_metric': 3.436431407928467} +Epoch [99/4000] Validation [1/4] Loss: 0.28447 focal_loss 0.17301 dice_loss 0.11146 +Epoch [99/4000] Validation [2/4] Loss: 0.25938 focal_loss 0.09581 dice_loss 0.16357 +Epoch [99/4000] Validation [3/4] Loss: 0.15489 focal_loss 0.07316 dice_loss 0.08173 +Epoch [99/4000] Validation [4/4] Loss: 0.18965 focal_loss 0.07528 dice_loss 0.11437 +Epoch [99/4000] Validation metric {'Val/mean dice_metric': 0.9539557695388794, 'Val/mean miou_metric': 0.924945056438446, 'Val/mean f1': 0.9591674208641052, 'Val/mean precision': 0.9550148248672485, 'Val/mean recall': 0.9633561968803406, 'Val/mean hd95_metric': 8.459375381469727} +Cheakpoint... +Epoch [99/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9540], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9539557695388794, 'Val/mean miou_metric': 0.924945056438446, 'Val/mean f1': 0.9591674208641052, 'Val/mean precision': 0.9550148248672485, 'Val/mean recall': 0.9633561968803406, 'Val/mean hd95_metric': 8.459375381469727} +Epoch [100/4000] Training [1/16] Loss: 0.02949 +Epoch [100/4000] Training [2/16] Loss: 0.02534 +Epoch [100/4000] Training [3/16] Loss: 0.02000 +Epoch [100/4000] Training [4/16] Loss: 0.04713 +Epoch [100/4000] Training [5/16] Loss: 0.11244 +Epoch [100/4000] Training [6/16] Loss: 0.02214 +Epoch [100/4000] Training [7/16] Loss: 0.25416 +Epoch [100/4000] Training [8/16] Loss: 0.06087 +Epoch [100/4000] Training [9/16] Loss: 0.02567 +Epoch [100/4000] Training [10/16] Loss: 0.02689 +Epoch [100/4000] Training [11/16] Loss: 0.04441 +Epoch [100/4000] Training [12/16] Loss: 0.03661 +Epoch [100/4000] Training [13/16] Loss: 0.03463 +Epoch [100/4000] Training [14/16] Loss: 0.03346 +Epoch [100/4000] Training [15/16] Loss: 0.02581 +Epoch [100/4000] Training [16/16] Loss: 0.08194 +Epoch [100/4000] Training metric {'Train/mean dice_metric': 0.9730786085128784, 'Train/mean miou_metric': 0.9508042335510254, 'Train/mean f1': 0.9708210229873657, 'Train/mean precision': 0.965151846408844, 'Train/mean recall': 0.9765572547912598, 'Train/mean hd95_metric': 6.679657936096191} +Epoch [100/4000] Validation [1/4] Loss: 0.50501 focal_loss 0.37214 dice_loss 0.13287 +Epoch [100/4000] Validation [2/4] Loss: 0.20092 focal_loss 0.06240 dice_loss 0.13852 +Epoch [100/4000] Validation [3/4] Loss: 0.16708 focal_loss 0.06766 dice_loss 0.09942 +Epoch [100/4000] Validation [4/4] Loss: 0.22884 focal_loss 0.08857 dice_loss 0.14027 +Epoch [100/4000] Validation metric {'Val/mean dice_metric': 0.9445177316665649, 'Val/mean miou_metric': 0.9117401242256165, 'Val/mean f1': 0.9472097158432007, 'Val/mean precision': 0.9486600160598755, 'Val/mean recall': 0.9457638263702393, 'Val/mean hd95_metric': 12.274080276489258} +Cheakpoint... +Epoch [100/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9445], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9445177316665649, 'Val/mean miou_metric': 0.9117401242256165, 'Val/mean f1': 0.9472097158432007, 'Val/mean precision': 0.9486600160598755, 'Val/mean recall': 0.9457638263702393, 'Val/mean hd95_metric': 12.274080276489258} +Epoch [101/4000] Training [1/16] Loss: 0.02632 +Epoch [101/4000] Training [2/16] Loss: 0.02535 +Epoch [101/4000] Training [3/16] Loss: 0.03084 +Epoch [101/4000] Training [4/16] Loss: 0.03247 +Epoch [101/4000] Training [5/16] Loss: 0.02996 +Epoch [101/4000] Training [6/16] Loss: 0.02321 +Epoch [101/4000] Training [7/16] Loss: 0.03462 +Epoch [101/4000] Training [8/16] Loss: 0.02742 +Epoch [101/4000] Training [9/16] Loss: 0.03412 +Epoch [101/4000] Training [10/16] Loss: 0.03457 +Epoch [101/4000] Training [11/16] Loss: 0.05016 +Epoch [101/4000] Training [12/16] Loss: 0.03718 +Epoch [101/4000] Training [13/16] Loss: 0.02765 +Epoch [101/4000] Training [14/16] Loss: 0.02398 +Epoch [101/4000] Training [15/16] Loss: 0.03019 +Epoch [101/4000] Training [16/16] Loss: 0.02379 +Epoch [101/4000] Training metric {'Train/mean dice_metric': 0.9780832529067993, 'Train/mean miou_metric': 0.9576267004013062, 'Train/mean f1': 0.9766297340393066, 'Train/mean precision': 0.9697434306144714, 'Train/mean recall': 0.9836145639419556, 'Train/mean hd95_metric': 4.277814865112305} +Epoch [101/4000] Validation [1/4] Loss: 0.16079 focal_loss 0.08910 dice_loss 0.07169 +Epoch [101/4000] Validation [2/4] Loss: 0.25860 focal_loss 0.10148 dice_loss 0.15712 +Epoch [101/4000] Validation [3/4] Loss: 0.13942 focal_loss 0.06107 dice_loss 0.07835 +Epoch [101/4000] Validation [4/4] Loss: 0.19621 focal_loss 0.08951 dice_loss 0.10670 +Epoch [101/4000] Validation metric {'Val/mean dice_metric': 0.9574893712997437, 'Val/mean miou_metric': 0.9275015592575073, 'Val/mean f1': 0.9592797160148621, 'Val/mean precision': 0.950967013835907, 'Val/mean recall': 0.9677389860153198, 'Val/mean hd95_metric': 9.053312301635742} +Cheakpoint... +Epoch [101/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9575], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9574893712997437, 'Val/mean miou_metric': 0.9275015592575073, 'Val/mean f1': 0.9592797160148621, 'Val/mean precision': 0.950967013835907, 'Val/mean recall': 0.9677389860153198, 'Val/mean hd95_metric': 9.053312301635742} +Epoch [102/4000] Training [1/16] Loss: 0.01719 +Epoch [102/4000] Training [2/16] Loss: 0.02082 +Epoch [102/4000] Training [3/16] Loss: 0.02846 +Epoch [102/4000] Training [4/16] Loss: 0.02570 +Epoch [102/4000] Training [5/16] Loss: 0.01958 +Epoch [102/4000] Training [6/16] Loss: 0.02399 +Epoch [102/4000] Training [7/16] Loss: 0.02037 +Epoch [102/4000] Training [8/16] Loss: 0.03016 +Epoch [102/4000] Training [9/16] Loss: 0.03615 +Epoch [102/4000] Training [10/16] Loss: 0.02549 +Epoch [102/4000] Training [11/16] Loss: 0.02014 +Epoch [102/4000] Training [12/16] Loss: 0.02892 +Epoch [102/4000] Training [13/16] Loss: 0.02281 +Epoch [102/4000] Training [14/16] Loss: 0.01915 +Epoch [102/4000] Training [15/16] Loss: 0.02493 +Epoch [102/4000] Training [16/16] Loss: 0.02047 +Epoch [102/4000] Training metric {'Train/mean dice_metric': 0.9830071926116943, 'Train/mean miou_metric': 0.9665836095809937, 'Train/mean f1': 0.9807419180870056, 'Train/mean precision': 0.9768981337547302, 'Train/mean recall': 0.9846162796020508, 'Train/mean hd95_metric': 2.8585643768310547} +Epoch [102/4000] Validation [1/4] Loss: 0.14003 focal_loss 0.06692 dice_loss 0.07311 +Epoch [102/4000] Validation [2/4] Loss: 0.19021 focal_loss 0.04635 dice_loss 0.14386 +Epoch [102/4000] Validation [3/4] Loss: 0.17098 focal_loss 0.06455 dice_loss 0.10643 +Epoch [102/4000] Validation [4/4] Loss: 0.18540 focal_loss 0.06585 dice_loss 0.11955 +Epoch [102/4000] Validation metric {'Val/mean dice_metric': 0.9601427316665649, 'Val/mean miou_metric': 0.9333852529525757, 'Val/mean f1': 0.9626541137695312, 'Val/mean precision': 0.9573198556900024, 'Val/mean recall': 0.968048095703125, 'Val/mean hd95_metric': 7.307570457458496} +Cheakpoint... +Epoch [102/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9601], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9601427316665649, 'Val/mean miou_metric': 0.9333852529525757, 'Val/mean f1': 0.9626541137695312, 'Val/mean precision': 0.9573198556900024, 'Val/mean recall': 0.968048095703125, 'Val/mean hd95_metric': 7.307570457458496} +Epoch [103/4000] Training [1/16] Loss: 0.02849 +Epoch [103/4000] Training [2/16] Loss: 0.01726 +Epoch [103/4000] Training [3/16] Loss: 0.02458 +Epoch [103/4000] Training [4/16] Loss: 0.02608 +Epoch [103/4000] Training [5/16] Loss: 0.02031 +Epoch [103/4000] Training [6/16] Loss: 0.03164 +Epoch [103/4000] Training [7/16] Loss: 0.04066 +Epoch [103/4000] Training [8/16] Loss: 0.01619 +Epoch [103/4000] Training [9/16] Loss: 0.02326 +Epoch [103/4000] Training [10/16] Loss: 0.02964 +Epoch [103/4000] Training [11/16] Loss: 0.03744 +Epoch [103/4000] Training [12/16] Loss: 0.02227 +Epoch [103/4000] Training [13/16] Loss: 0.02181 +Epoch [103/4000] Training [14/16] Loss: 0.01675 +Epoch [103/4000] Training [15/16] Loss: 0.02266 +Epoch [103/4000] Training [16/16] Loss: 0.01905 +Epoch [103/4000] Training metric {'Train/mean dice_metric': 0.9824556112289429, 'Train/mean miou_metric': 0.9660815000534058, 'Train/mean f1': 0.9801669120788574, 'Train/mean precision': 0.9747918844223022, 'Train/mean recall': 0.9856016039848328, 'Train/mean hd95_metric': 3.0017900466918945} +Epoch [103/4000] Validation [1/4] Loss: 0.20172 focal_loss 0.11105 dice_loss 0.09067 +Epoch [103/4000] Validation [2/4] Loss: 0.28044 focal_loss 0.11511 dice_loss 0.16534 +Epoch [103/4000] Validation [3/4] Loss: 0.12920 focal_loss 0.05589 dice_loss 0.07331 +Epoch [103/4000] Validation [4/4] Loss: 0.21318 focal_loss 0.10068 dice_loss 0.11251 +Epoch [103/4000] Validation metric {'Val/mean dice_metric': 0.9576738476753235, 'Val/mean miou_metric': 0.9307311773300171, 'Val/mean f1': 0.961527943611145, 'Val/mean precision': 0.9573538303375244, 'Val/mean recall': 0.9657385349273682, 'Val/mean hd95_metric': 7.7966461181640625} +Cheakpoint... +Epoch [103/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9577], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576738476753235, 'Val/mean miou_metric': 0.9307311773300171, 'Val/mean f1': 0.961527943611145, 'Val/mean precision': 0.9573538303375244, 'Val/mean recall': 0.9657385349273682, 'Val/mean hd95_metric': 7.7966461181640625} +Epoch [104/4000] Training [1/16] Loss: 0.02376 +Epoch [104/4000] Training [2/16] Loss: 0.02404 +Epoch [104/4000] Training [3/16] Loss: 0.02471 +Epoch [104/4000] Training [4/16] Loss: 0.02279 +Epoch [104/4000] Training [5/16] Loss: 0.02294 +Epoch [104/4000] Training [6/16] Loss: 0.02553 +Epoch [104/4000] Training [7/16] Loss: 0.02708 +Epoch [104/4000] Training [8/16] Loss: 0.02677 +Epoch [104/4000] Training [9/16] Loss: 0.02973 +Epoch [104/4000] Training [10/16] Loss: 0.02968 +Epoch [104/4000] Training [11/16] Loss: 0.02916 +Epoch [104/4000] Training [12/16] Loss: 0.05254 +Epoch [104/4000] Training [13/16] Loss: 0.02194 +Epoch [104/4000] Training [14/16] Loss: 0.02450 +Epoch [104/4000] Training [15/16] Loss: 0.02343 +Epoch [104/4000] Training [16/16] Loss: 0.08267 +Epoch [104/4000] Training metric {'Train/mean dice_metric': 0.9808975458145142, 'Train/mean miou_metric': 0.964047908782959, 'Train/mean f1': 0.9791930317878723, 'Train/mean precision': 0.9743935465812683, 'Train/mean recall': 0.9840400815010071, 'Train/mean hd95_metric': 3.574308156967163} +Epoch [104/4000] Validation [1/4] Loss: 0.15757 focal_loss 0.08366 dice_loss 0.07391 +Epoch [104/4000] Validation [2/4] Loss: 0.26241 focal_loss 0.09181 dice_loss 0.17061 +Epoch [104/4000] Validation [3/4] Loss: 0.12958 focal_loss 0.05929 dice_loss 0.07029 +Epoch [104/4000] Validation [4/4] Loss: 0.24647 focal_loss 0.12428 dice_loss 0.12219 +Epoch [104/4000] Validation metric {'Val/mean dice_metric': 0.9561483263969421, 'Val/mean miou_metric': 0.928685188293457, 'Val/mean f1': 0.9600316286087036, 'Val/mean precision': 0.9572857022285461, 'Val/mean recall': 0.962793231010437, 'Val/mean hd95_metric': 7.7137451171875} +Cheakpoint... +Epoch [104/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9561], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9561483263969421, 'Val/mean miou_metric': 0.928685188293457, 'Val/mean f1': 0.9600316286087036, 'Val/mean precision': 0.9572857022285461, 'Val/mean recall': 0.962793231010437, 'Val/mean hd95_metric': 7.7137451171875} +Epoch [105/4000] Training [1/16] Loss: 0.01987 +Epoch [105/4000] Training [2/16] Loss: 0.02805 +Epoch [105/4000] Training [3/16] Loss: 0.02701 +Epoch [105/4000] Training [4/16] Loss: 0.03318 +Epoch [105/4000] Training [5/16] Loss: 0.02137 +Epoch [105/4000] Training [6/16] Loss: 0.02406 +Epoch [105/4000] Training [7/16] Loss: 0.02013 +Epoch [105/4000] Training [8/16] Loss: 0.02315 +Epoch [105/4000] Training [9/16] Loss: 0.02382 +Epoch [105/4000] Training [10/16] Loss: 0.02213 +Epoch [105/4000] Training [11/16] Loss: 0.02150 +Epoch [105/4000] Training [12/16] Loss: 0.04564 +Epoch [105/4000] Training [13/16] Loss: 0.02641 +Epoch [105/4000] Training [14/16] Loss: 0.03412 +Epoch [105/4000] Training [15/16] Loss: 0.04430 +Epoch [105/4000] Training [16/16] Loss: 0.02617 +Epoch [105/4000] Training metric {'Train/mean dice_metric': 0.9779249429702759, 'Train/mean miou_metric': 0.9587353467941284, 'Train/mean f1': 0.9780794382095337, 'Train/mean precision': 0.973731279373169, 'Train/mean recall': 0.9824666380882263, 'Train/mean hd95_metric': 4.1095781326293945} +Epoch [105/4000] Validation [1/4] Loss: 0.29840 focal_loss 0.19611 dice_loss 0.10230 +Epoch [105/4000] Validation [2/4] Loss: 0.31930 focal_loss 0.11955 dice_loss 0.19975 +Epoch [105/4000] Validation [3/4] Loss: 0.15848 focal_loss 0.06145 dice_loss 0.09703 +Epoch [105/4000] Validation [4/4] Loss: 0.16541 focal_loss 0.06941 dice_loss 0.09600 +Epoch [105/4000] Validation metric {'Val/mean dice_metric': 0.9542174339294434, 'Val/mean miou_metric': 0.9250704050064087, 'Val/mean f1': 0.9573944211006165, 'Val/mean precision': 0.9485479593276978, 'Val/mean recall': 0.9664074778556824, 'Val/mean hd95_metric': 9.118297576904297} +Cheakpoint... +Epoch [105/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9542], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9542174339294434, 'Val/mean miou_metric': 0.9250704050064087, 'Val/mean f1': 0.9573944211006165, 'Val/mean precision': 0.9485479593276978, 'Val/mean recall': 0.9664074778556824, 'Val/mean hd95_metric': 9.118297576904297} +Epoch [106/4000] Training [1/16] Loss: 0.03330 +Epoch [106/4000] Training [2/16] Loss: 0.02119 +Epoch [106/4000] Training [3/16] Loss: 0.02766 +Epoch [106/4000] Training [4/16] Loss: 0.02615 +Epoch [106/4000] Training [5/16] Loss: 0.02238 +Epoch [106/4000] Training [6/16] Loss: 0.03218 +Epoch [106/4000] Training [7/16] Loss: 0.01916 +Epoch [106/4000] Training [8/16] Loss: 0.02019 +Epoch [106/4000] Training [9/16] Loss: 0.04214 +Epoch [106/4000] Training [10/16] Loss: 0.02426 +Epoch [106/4000] Training [11/16] Loss: 0.02697 +Epoch [106/4000] Training [12/16] Loss: 0.06215 +Epoch [106/4000] Training [13/16] Loss: 0.02602 +Epoch [106/4000] Training [14/16] Loss: 0.02649 +Epoch [106/4000] Training [15/16] Loss: 0.01970 +Epoch [106/4000] Training [16/16] Loss: 0.03517 +Epoch [106/4000] Training metric {'Train/mean dice_metric': 0.9813843369483948, 'Train/mean miou_metric': 0.9638264179229736, 'Train/mean f1': 0.9799466133117676, 'Train/mean precision': 0.976631760597229, 'Train/mean recall': 0.983284056186676, 'Train/mean hd95_metric': 4.139096260070801} +Epoch [106/4000] Validation [1/4] Loss: 0.13850 focal_loss 0.07215 dice_loss 0.06635 +Epoch [106/4000] Validation [2/4] Loss: 0.22242 focal_loss 0.06412 dice_loss 0.15831 +Epoch [106/4000] Validation [3/4] Loss: 0.26657 focal_loss 0.15315 dice_loss 0.11342 +Epoch [106/4000] Validation [4/4] Loss: 0.28131 focal_loss 0.14058 dice_loss 0.14072 +Epoch [106/4000] Validation metric {'Val/mean dice_metric': 0.9586019515991211, 'Val/mean miou_metric': 0.9304569959640503, 'Val/mean f1': 0.9596660137176514, 'Val/mean precision': 0.949137806892395, 'Val/mean recall': 0.9704304337501526, 'Val/mean hd95_metric': 8.828874588012695} +Cheakpoint... +Epoch [106/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9586], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9586019515991211, 'Val/mean miou_metric': 0.9304569959640503, 'Val/mean f1': 0.9596660137176514, 'Val/mean precision': 0.949137806892395, 'Val/mean recall': 0.9704304337501526, 'Val/mean hd95_metric': 8.828874588012695} +Epoch [107/4000] Training [1/16] Loss: 0.02009 +Epoch [107/4000] Training [2/16] Loss: 0.02365 +Epoch [107/4000] Training [3/16] Loss: 0.02634 +Epoch [107/4000] Training [4/16] Loss: 0.03032 +Epoch [107/4000] Training [5/16] Loss: 0.02385 +Epoch [107/4000] Training [6/16] Loss: 0.02521 +Epoch [107/4000] Training [7/16] Loss: 0.02556 +Epoch [107/4000] Training [8/16] Loss: 0.02184 +Epoch [107/4000] Training [9/16] Loss: 0.02706 +Epoch [107/4000] Training [10/16] Loss: 0.03506 +Epoch [107/4000] Training [11/16] Loss: 0.03017 +Epoch [107/4000] Training [12/16] Loss: 0.06171 +Epoch [107/4000] Training [13/16] Loss: 0.02982 +Epoch [107/4000] Training [14/16] Loss: 0.02912 +Epoch [107/4000] Training [15/16] Loss: 0.02554 +Epoch [107/4000] Training [16/16] Loss: 0.03536 +Epoch [107/4000] Training metric {'Train/mean dice_metric': 0.9796074628829956, 'Train/mean miou_metric': 0.9605166912078857, 'Train/mean f1': 0.9770642518997192, 'Train/mean precision': 0.9730778932571411, 'Train/mean recall': 0.9810833930969238, 'Train/mean hd95_metric': 4.398693084716797} +Epoch [107/4000] Validation [1/4] Loss: 0.92486 focal_loss 0.74848 dice_loss 0.17638 +Epoch [107/4000] Validation [2/4] Loss: 0.29527 focal_loss 0.10195 dice_loss 0.19332 +Epoch [107/4000] Validation [3/4] Loss: 0.13817 focal_loss 0.05828 dice_loss 0.07989 +Epoch [107/4000] Validation [4/4] Loss: 0.17611 focal_loss 0.06688 dice_loss 0.10923 +Epoch [107/4000] Validation metric {'Val/mean dice_metric': 0.9539729356765747, 'Val/mean miou_metric': 0.9245031476020813, 'Val/mean f1': 0.9554506540298462, 'Val/mean precision': 0.957700788974762, 'Val/mean recall': 0.9532110691070557, 'Val/mean hd95_metric': 8.592873573303223} +Cheakpoint... +Epoch [107/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9540], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9539729356765747, 'Val/mean miou_metric': 0.9245031476020813, 'Val/mean f1': 0.9554506540298462, 'Val/mean precision': 0.957700788974762, 'Val/mean recall': 0.9532110691070557, 'Val/mean hd95_metric': 8.592873573303223} +Epoch [108/4000] Training [1/16] Loss: 0.03689 +Epoch [108/4000] Training [2/16] Loss: 0.01947 +Epoch [108/4000] Training [3/16] Loss: 0.01978 +Epoch [108/4000] Training [4/16] Loss: 0.02574 +Epoch [108/4000] Training [5/16] Loss: 0.03602 +Epoch [108/4000] Training [6/16] Loss: 0.02120 +Epoch [108/4000] Training [7/16] Loss: 0.02350 +Epoch [108/4000] Training [8/16] Loss: 0.02442 +Epoch [108/4000] Training [9/16] Loss: 0.02601 +Epoch [108/4000] Training [10/16] Loss: 0.01964 +Epoch [108/4000] Training [11/16] Loss: 0.03027 +Epoch [108/4000] Training [12/16] Loss: 0.10035 +Epoch [108/4000] Training [13/16] Loss: 0.01842 +Epoch [108/4000] Training [14/16] Loss: 0.03382 +Epoch [108/4000] Training [15/16] Loss: 0.02369 +Epoch [108/4000] Training [16/16] Loss: 0.02414 +Epoch [108/4000] Training metric {'Train/mean dice_metric': 0.9793623685836792, 'Train/mean miou_metric': 0.9613876938819885, 'Train/mean f1': 0.9788583517074585, 'Train/mean precision': 0.9743691682815552, 'Train/mean recall': 0.9833890795707703, 'Train/mean hd95_metric': 3.0827646255493164} +Epoch [108/4000] Validation [1/4] Loss: 0.27612 focal_loss 0.16456 dice_loss 0.11155 +Epoch [108/4000] Validation [2/4] Loss: 0.20565 focal_loss 0.06661 dice_loss 0.13903 +Epoch [108/4000] Validation [3/4] Loss: 0.16396 focal_loss 0.07066 dice_loss 0.09330 +Epoch [108/4000] Validation [4/4] Loss: 0.18593 focal_loss 0.07711 dice_loss 0.10882 +Epoch [108/4000] Validation metric {'Val/mean dice_metric': 0.9571256637573242, 'Val/mean miou_metric': 0.9285383224487305, 'Val/mean f1': 0.9587275385856628, 'Val/mean precision': 0.9488654732704163, 'Val/mean recall': 0.9687968492507935, 'Val/mean hd95_metric': 9.206089973449707} +Cheakpoint... +Epoch [108/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9571], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9571256637573242, 'Val/mean miou_metric': 0.9285383224487305, 'Val/mean f1': 0.9587275385856628, 'Val/mean precision': 0.9488654732704163, 'Val/mean recall': 0.9687968492507935, 'Val/mean hd95_metric': 9.206089973449707} +Epoch [109/4000] Training [1/16] Loss: 0.02447 +Epoch [109/4000] Training [2/16] Loss: 0.03542 +Epoch [109/4000] Training [3/16] Loss: 0.02383 +Epoch [109/4000] Training [4/16] Loss: 0.02120 +Epoch [109/4000] Training [5/16] Loss: 0.02128 +Epoch [109/4000] Training [6/16] Loss: 0.02505 +Epoch [109/4000] Training [7/16] Loss: 0.02299 +Epoch [109/4000] Training [8/16] Loss: 0.02067 +Epoch [109/4000] Training [9/16] Loss: 0.02031 +Epoch [109/4000] Training [10/16] Loss: 0.07065 +Epoch [109/4000] Training [11/16] Loss: 0.02756 +Epoch [109/4000] Training [12/16] Loss: 0.02768 +Epoch [109/4000] Training [13/16] Loss: 0.01907 +Epoch [109/4000] Training [14/16] Loss: 0.02918 +Epoch [109/4000] Training [15/16] Loss: 0.02080 +Epoch [109/4000] Training [16/16] Loss: 0.02111 +Epoch [109/4000] Training metric {'Train/mean dice_metric': 0.9811731576919556, 'Train/mean miou_metric': 0.9634370803833008, 'Train/mean f1': 0.9791713356971741, 'Train/mean precision': 0.9755052924156189, 'Train/mean recall': 0.982865035533905, 'Train/mean hd95_metric': 3.967517375946045} +Epoch [109/4000] Validation [1/4] Loss: 0.21802 focal_loss 0.13205 dice_loss 0.08598 +Epoch [109/4000] Validation [2/4] Loss: 0.40237 focal_loss 0.18618 dice_loss 0.21620 +Epoch [109/4000] Validation [3/4] Loss: 0.29767 focal_loss 0.13590 dice_loss 0.16176 +Epoch [109/4000] Validation [4/4] Loss: 0.30421 focal_loss 0.13188 dice_loss 0.17233 +Epoch [109/4000] Validation metric {'Val/mean dice_metric': 0.950919508934021, 'Val/mean miou_metric': 0.9220453500747681, 'Val/mean f1': 0.9523899555206299, 'Val/mean precision': 0.9394373297691345, 'Val/mean recall': 0.9657048583030701, 'Val/mean hd95_metric': 11.208518981933594} +Cheakpoint... +Epoch [109/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9509], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.950919508934021, 'Val/mean miou_metric': 0.9220453500747681, 'Val/mean f1': 0.9523899555206299, 'Val/mean precision': 0.9394373297691345, 'Val/mean recall': 0.9657048583030701, 'Val/mean hd95_metric': 11.208518981933594} +Epoch [110/4000] Training [1/16] Loss: 0.01798 +Epoch [110/4000] Training [2/16] Loss: 0.03856 +Epoch [110/4000] Training [3/16] Loss: 0.03286 +Epoch [110/4000] Training [4/16] Loss: 0.02267 +Epoch [110/4000] Training [5/16] Loss: 0.02377 +Epoch [110/4000] Training [6/16] Loss: 0.03929 +Epoch [110/4000] Training [7/16] Loss: 0.01918 +Epoch [110/4000] Training [8/16] Loss: 0.02046 +Epoch [110/4000] Training [9/16] Loss: 0.03644 +Epoch [110/4000] Training [10/16] Loss: 0.02023 +Epoch [110/4000] Training [11/16] Loss: 0.02424 +Epoch [110/4000] Training [12/16] Loss: 0.04879 +Epoch [110/4000] Training [13/16] Loss: 0.02987 +Epoch [110/4000] Training [14/16] Loss: 0.02091 +Epoch [110/4000] Training [15/16] Loss: 0.03625 +Epoch [110/4000] Training [16/16] Loss: 0.02083 +Epoch [110/4000] Training metric {'Train/mean dice_metric': 0.9799551963806152, 'Train/mean miou_metric': 0.9612221717834473, 'Train/mean f1': 0.9785148501396179, 'Train/mean precision': 0.9737069010734558, 'Train/mean recall': 0.9833706021308899, 'Train/mean hd95_metric': 4.466049671173096} +Epoch [110/4000] Validation [1/4] Loss: 0.57285 focal_loss 0.39350 dice_loss 0.17935 +Epoch [110/4000] Validation [2/4] Loss: 0.32534 focal_loss 0.09993 dice_loss 0.22541 +Epoch [110/4000] Validation [3/4] Loss: 0.13097 focal_loss 0.04804 dice_loss 0.08293 +Epoch [110/4000] Validation [4/4] Loss: 0.19480 focal_loss 0.09460 dice_loss 0.10020 +Epoch [110/4000] Validation metric {'Val/mean dice_metric': 0.953626275062561, 'Val/mean miou_metric': 0.9254058599472046, 'Val/mean f1': 0.9571166634559631, 'Val/mean precision': 0.9540387392044067, 'Val/mean recall': 0.9602146148681641, 'Val/mean hd95_metric': 9.908014297485352} +Cheakpoint... +Epoch [110/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9536], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.953626275062561, 'Val/mean miou_metric': 0.9254058599472046, 'Val/mean f1': 0.9571166634559631, 'Val/mean precision': 0.9540387392044067, 'Val/mean recall': 0.9602146148681641, 'Val/mean hd95_metric': 9.908014297485352} +Epoch [111/4000] Training [1/16] Loss: 0.05757 +Epoch [111/4000] Training [2/16] Loss: 0.01886 +Epoch [111/4000] Training [3/16] Loss: 0.03142 +Epoch [111/4000] Training [4/16] Loss: 0.02693 +Epoch [111/4000] Training [5/16] Loss: 0.01770 +Epoch [111/4000] Training [6/16] Loss: 0.03743 +Epoch [111/4000] Training [7/16] Loss: 0.04710 +Epoch [111/4000] Training [8/16] Loss: 0.05819 +Epoch [111/4000] Training [9/16] Loss: 0.03150 +Epoch [111/4000] Training [10/16] Loss: 0.02061 +Epoch [111/4000] Training [11/16] Loss: 0.02737 +Epoch [111/4000] Training [12/16] Loss: 0.01841 +Epoch [111/4000] Training [13/16] Loss: 0.03456 +Epoch [111/4000] Training [14/16] Loss: 0.02201 +Epoch [111/4000] Training [15/16] Loss: 0.02479 +Epoch [111/4000] Training [16/16] Loss: 0.02564 +Epoch [111/4000] Training metric {'Train/mean dice_metric': 0.9788879156112671, 'Train/mean miou_metric': 0.9598184823989868, 'Train/mean f1': 0.9759975075721741, 'Train/mean precision': 0.9728357791900635, 'Train/mean recall': 0.9791797399520874, 'Train/mean hd95_metric': 4.551435470581055} +Epoch [111/4000] Validation [1/4] Loss: 0.19844 focal_loss 0.10934 dice_loss 0.08910 +Epoch [111/4000] Validation [2/4] Loss: 0.35625 focal_loss 0.12895 dice_loss 0.22730 +Epoch [111/4000] Validation [3/4] Loss: 0.10664 focal_loss 0.04488 dice_loss 0.06176 +Epoch [111/4000] Validation [4/4] Loss: 0.14635 focal_loss 0.05815 dice_loss 0.08820 +Epoch [111/4000] Validation metric {'Val/mean dice_metric': 0.9520204663276672, 'Val/mean miou_metric': 0.9232619404792786, 'Val/mean f1': 0.9559891223907471, 'Val/mean precision': 0.9511918425559998, 'Val/mean recall': 0.9608350992202759, 'Val/mean hd95_metric': 10.069916725158691} +Cheakpoint... +Epoch [111/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9520], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9520204663276672, 'Val/mean miou_metric': 0.9232619404792786, 'Val/mean f1': 0.9559891223907471, 'Val/mean precision': 0.9511918425559998, 'Val/mean recall': 0.9608350992202759, 'Val/mean hd95_metric': 10.069916725158691} +Epoch [112/4000] Training [1/16] Loss: 0.02316 +Epoch [112/4000] Training [2/16] Loss: 0.02188 +Epoch [112/4000] Training [3/16] Loss: 0.02646 +Epoch [112/4000] Training [4/16] Loss: 0.02145 +Epoch [112/4000] Training [5/16] Loss: 0.02264 +Epoch [112/4000] Training [6/16] Loss: 0.02636 +Epoch [112/4000] Training [7/16] Loss: 0.01876 +Epoch [112/4000] Training [8/16] Loss: 0.03398 +Epoch [112/4000] Training [9/16] Loss: 0.02840 +Epoch [112/4000] Training [10/16] Loss: 0.02469 +Epoch [112/4000] Training [11/16] Loss: 0.03001 +Epoch [112/4000] Training [12/16] Loss: 0.02205 +Epoch [112/4000] Training [13/16] Loss: 0.03122 +Epoch [112/4000] Training [14/16] Loss: 0.02307 +Epoch [112/4000] Training [15/16] Loss: 0.03503 +Epoch [112/4000] Training [16/16] Loss: 0.01808 +Epoch [112/4000] Training metric {'Train/mean dice_metric': 0.9777201414108276, 'Train/mean miou_metric': 0.9584415555000305, 'Train/mean f1': 0.9765880107879639, 'Train/mean precision': 0.9721072316169739, 'Train/mean recall': 0.9811103343963623, 'Train/mean hd95_metric': 4.686221122741699} +Epoch [112/4000] Validation [1/4] Loss: 0.99251 focal_loss 0.80141 dice_loss 0.19110 +Epoch [112/4000] Validation [2/4] Loss: 0.20256 focal_loss 0.06256 dice_loss 0.14000 +Epoch [112/4000] Validation [3/4] Loss: 0.13915 focal_loss 0.05209 dice_loss 0.08705 +Epoch [112/4000] Validation [4/4] Loss: 0.33021 focal_loss 0.17287 dice_loss 0.15734 +Epoch [112/4000] Validation metric {'Val/mean dice_metric': 0.9483949542045593, 'Val/mean miou_metric': 0.9182079434394836, 'Val/mean f1': 0.954296350479126, 'Val/mean precision': 0.9566391110420227, 'Val/mean recall': 0.9519649744033813, 'Val/mean hd95_metric': 9.879083633422852} +Cheakpoint... +Epoch [112/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9484], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9483949542045593, 'Val/mean miou_metric': 0.9182079434394836, 'Val/mean f1': 0.954296350479126, 'Val/mean precision': 0.9566391110420227, 'Val/mean recall': 0.9519649744033813, 'Val/mean hd95_metric': 9.879083633422852} +Epoch [113/4000] Training [1/16] Loss: 0.01980 +Epoch [113/4000] Training [2/16] Loss: 0.03778 +Epoch [113/4000] Training [3/16] Loss: 0.04425 +Epoch [113/4000] Training [4/16] Loss: 0.02428 +Epoch [113/4000] Training [5/16] Loss: 0.02375 +Epoch [113/4000] Training [6/16] Loss: 0.03833 +Epoch [113/4000] Training [7/16] Loss: 0.02361 +Epoch [113/4000] Training [8/16] Loss: 0.02807 +Epoch [113/4000] Training [9/16] Loss: 0.02732 +Epoch [113/4000] Training [10/16] Loss: 0.03124 +Epoch [113/4000] Training [11/16] Loss: 0.01554 +Epoch [113/4000] Training [12/16] Loss: 0.02326 +Epoch [113/4000] Training [13/16] Loss: 0.02965 +Epoch [113/4000] Training [14/16] Loss: 0.01862 +Epoch [113/4000] Training [15/16] Loss: 0.02086 +Epoch [113/4000] Training [16/16] Loss: 0.01964 +Epoch [113/4000] Training metric {'Train/mean dice_metric': 0.9827389717102051, 'Train/mean miou_metric': 0.9660347104072571, 'Train/mean f1': 0.9809392690658569, 'Train/mean precision': 0.9761993885040283, 'Train/mean recall': 0.9857254028320312, 'Train/mean hd95_metric': 2.6190853118896484} +Epoch [113/4000] Validation [1/4] Loss: 0.81702 focal_loss 0.66128 dice_loss 0.15574 +Epoch [113/4000] Validation [2/4] Loss: 0.25000 focal_loss 0.09182 dice_loss 0.15818 +Epoch [113/4000] Validation [3/4] Loss: 0.14695 focal_loss 0.06904 dice_loss 0.07790 +Epoch [113/4000] Validation [4/4] Loss: 0.21464 focal_loss 0.09804 dice_loss 0.11661 +Epoch [113/4000] Validation metric {'Val/mean dice_metric': 0.9572259187698364, 'Val/mean miou_metric': 0.9300506711006165, 'Val/mean f1': 0.9589370489120483, 'Val/mean precision': 0.9523810148239136, 'Val/mean recall': 0.9655839800834656, 'Val/mean hd95_metric': 8.078737258911133} +Cheakpoint... +Epoch [113/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9572], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9572259187698364, 'Val/mean miou_metric': 0.9300506711006165, 'Val/mean f1': 0.9589370489120483, 'Val/mean precision': 0.9523810148239136, 'Val/mean recall': 0.9655839800834656, 'Val/mean hd95_metric': 8.078737258911133} +Epoch [114/4000] Training [1/16] Loss: 0.02630 +Epoch [114/4000] Training [2/16] Loss: 0.02845 +Epoch [114/4000] Training [3/16] Loss: 0.02731 +Epoch [114/4000] Training [4/16] Loss: 0.02373 +Epoch [114/4000] Training [5/16] Loss: 0.02079 +Epoch [114/4000] Training [6/16] Loss: 0.02517 +Epoch [114/4000] Training [7/16] Loss: 0.01981 +Epoch [114/4000] Training [8/16] Loss: 0.01922 +Epoch [114/4000] Training [9/16] Loss: 0.02433 +Epoch [114/4000] Training [10/16] Loss: 0.02252 +Epoch [114/4000] Training [11/16] Loss: 0.01801 +Epoch [114/4000] Training [12/16] Loss: 0.01989 +Epoch [114/4000] Training [13/16] Loss: 0.01929 +Epoch [114/4000] Training [14/16] Loss: 0.01805 +Epoch [114/4000] Training [15/16] Loss: 0.02070 +Epoch [114/4000] Training [16/16] Loss: 0.01959 +Epoch [114/4000] Training metric {'Train/mean dice_metric': 0.9838842153549194, 'Train/mean miou_metric': 0.9682941436767578, 'Train/mean f1': 0.9818450212478638, 'Train/mean precision': 0.9770137071609497, 'Train/mean recall': 0.9867243766784668, 'Train/mean hd95_metric': 2.785414218902588} +Epoch [114/4000] Validation [1/4] Loss: 0.14195 focal_loss 0.07116 dice_loss 0.07079 +Epoch [114/4000] Validation [2/4] Loss: 0.41162 focal_loss 0.14812 dice_loss 0.26350 +Epoch [114/4000] Validation [3/4] Loss: 0.10615 focal_loss 0.04154 dice_loss 0.06461 +Epoch [114/4000] Validation [4/4] Loss: 0.17142 focal_loss 0.07058 dice_loss 0.10084 +Epoch [114/4000] Validation metric {'Val/mean dice_metric': 0.9585426449775696, 'Val/mean miou_metric': 0.9334625005722046, 'Val/mean f1': 0.9637291431427002, 'Val/mean precision': 0.9604170322418213, 'Val/mean recall': 0.9670640230178833, 'Val/mean hd95_metric': 7.716778755187988} +Cheakpoint... +Epoch [114/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9585], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9585426449775696, 'Val/mean miou_metric': 0.9334625005722046, 'Val/mean f1': 0.9637291431427002, 'Val/mean precision': 0.9604170322418213, 'Val/mean recall': 0.9670640230178833, 'Val/mean hd95_metric': 7.716778755187988} +Epoch [115/4000] Training [1/16] Loss: 0.01606 +Epoch [115/4000] Training [2/16] Loss: 0.01827 +Epoch [115/4000] Training [3/16] Loss: 0.02137 +Epoch [115/4000] Training [4/16] Loss: 0.01699 +Epoch [115/4000] Training [5/16] Loss: 0.03878 +Epoch [115/4000] Training [6/16] Loss: 0.01685 +Epoch [115/4000] Training [7/16] Loss: 0.01777 +Epoch [115/4000] Training [8/16] Loss: 0.02049 +Epoch [115/4000] Training [9/16] Loss: 0.02644 +Epoch [115/4000] Training [10/16] Loss: 0.01472 +Epoch [115/4000] Training [11/16] Loss: 0.05757 +Epoch [115/4000] Training [12/16] Loss: 0.01975 +Epoch [115/4000] Training [13/16] Loss: 0.03071 +Epoch [115/4000] Training [14/16] Loss: 0.01902 +Epoch [115/4000] Training [15/16] Loss: 0.02041 +Epoch [115/4000] Training [16/16] Loss: 0.02421 +Epoch [115/4000] Training metric {'Train/mean dice_metric': 0.9825725555419922, 'Train/mean miou_metric': 0.9678210616111755, 'Train/mean f1': 0.9831691384315491, 'Train/mean precision': 0.979196310043335, 'Train/mean recall': 0.987174391746521, 'Train/mean hd95_metric': 2.148148536682129} +Epoch [115/4000] Validation [1/4] Loss: 0.18322 focal_loss 0.10843 dice_loss 0.07479 +Epoch [115/4000] Validation [2/4] Loss: 0.20466 focal_loss 0.07286 dice_loss 0.13181 +Epoch [115/4000] Validation [3/4] Loss: 0.20177 focal_loss 0.09593 dice_loss 0.10584 +Epoch [115/4000] Validation [4/4] Loss: 0.26427 focal_loss 0.13552 dice_loss 0.12875 +Epoch [115/4000] Validation metric {'Val/mean dice_metric': 0.9575058221817017, 'Val/mean miou_metric': 0.9317005276679993, 'Val/mean f1': 0.9622817039489746, 'Val/mean precision': 0.9536705613136292, 'Val/mean recall': 0.9710497856140137, 'Val/mean hd95_metric': 8.263914108276367} +Cheakpoint... +Epoch [115/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9575], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9575058221817017, 'Val/mean miou_metric': 0.9317005276679993, 'Val/mean f1': 0.9622817039489746, 'Val/mean precision': 0.9536705613136292, 'Val/mean recall': 0.9710497856140137, 'Val/mean hd95_metric': 8.263914108276367} +Epoch [116/4000] Training [1/16] Loss: 0.02320 +Epoch [116/4000] Training [2/16] Loss: 0.13283 +Epoch [116/4000] Training [3/16] Loss: 0.01937 +Epoch [116/4000] Training [4/16] Loss: 0.02957 +Epoch [116/4000] Training [5/16] Loss: 0.01947 +Epoch [116/4000] Training [6/16] Loss: 0.02961 +Epoch [116/4000] Training [7/16] Loss: 0.02484 +Epoch [116/4000] Training [8/16] Loss: 0.03483 +Epoch [116/4000] Training [9/16] Loss: 0.02549 +Epoch [116/4000] Training [10/16] Loss: 0.02541 +Epoch [116/4000] Training [11/16] Loss: 0.02335 +Epoch [116/4000] Training [12/16] Loss: 0.02180 +Epoch [116/4000] Training [13/16] Loss: 0.04691 +Epoch [116/4000] Training [14/16] Loss: 0.02157 +Epoch [116/4000] Training [15/16] Loss: 0.02102 +Epoch [116/4000] Training [16/16] Loss: 0.06133 +Epoch [116/4000] Training metric {'Train/mean dice_metric': 0.9760560989379883, 'Train/mean miou_metric': 0.9576486945152283, 'Train/mean f1': 0.974616527557373, 'Train/mean precision': 0.9689362049102783, 'Train/mean recall': 0.9803639054298401, 'Train/mean hd95_metric': 3.9983937740325928} +Epoch [116/4000] Validation [1/4] Loss: 0.25427 focal_loss 0.12905 dice_loss 0.12522 +Epoch [116/4000] Validation [2/4] Loss: 0.28229 focal_loss 0.11642 dice_loss 0.16587 +Epoch [116/4000] Validation [3/4] Loss: 0.32596 focal_loss 0.14167 dice_loss 0.18429 +Epoch [116/4000] Validation [4/4] Loss: 0.18348 focal_loss 0.05638 dice_loss 0.12709 +Epoch [116/4000] Validation metric {'Val/mean dice_metric': 0.9488841891288757, 'Val/mean miou_metric': 0.9190820455551147, 'Val/mean f1': 0.9539424180984497, 'Val/mean precision': 0.949496865272522, 'Val/mean recall': 0.958429753780365, 'Val/mean hd95_metric': 9.346427917480469} +Cheakpoint... +Epoch [116/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9489], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9488841891288757, 'Val/mean miou_metric': 0.9190820455551147, 'Val/mean f1': 0.9539424180984497, 'Val/mean precision': 0.949496865272522, 'Val/mean recall': 0.958429753780365, 'Val/mean hd95_metric': 9.346427917480469} +Epoch [117/4000] Training [1/16] Loss: 0.02177 +Epoch [117/4000] Training [2/16] Loss: 0.01871 +Epoch [117/4000] Training [3/16] Loss: 0.02399 +Epoch [117/4000] Training [4/16] Loss: 0.03311 +Epoch [117/4000] Training [5/16] Loss: 0.02271 +Epoch [117/4000] Training [6/16] Loss: 0.03541 +Epoch [117/4000] Training [7/16] Loss: 0.03020 +Epoch [117/4000] Training [8/16] Loss: 0.02821 +Epoch [117/4000] Training [9/16] Loss: 0.02514 +Epoch [117/4000] Training [10/16] Loss: 0.02358 +Epoch [117/4000] Training [11/16] Loss: 0.03389 +Epoch [117/4000] Training [12/16] Loss: 0.02183 +Epoch [117/4000] Training [13/16] Loss: 0.01878 +Epoch [117/4000] Training [14/16] Loss: 0.02042 +Epoch [117/4000] Training [15/16] Loss: 0.03337 +Epoch [117/4000] Training [16/16] Loss: 0.02741 +Epoch [117/4000] Training metric {'Train/mean dice_metric': 0.9809198379516602, 'Train/mean miou_metric': 0.9630081653594971, 'Train/mean f1': 0.9806497097015381, 'Train/mean precision': 0.9752828478813171, 'Train/mean recall': 0.9860759377479553, 'Train/mean hd95_metric': 3.8848860263824463} +Epoch [117/4000] Validation [1/4] Loss: 0.13220 focal_loss 0.06879 dice_loss 0.06341 +Epoch [117/4000] Validation [2/4] Loss: 0.34001 focal_loss 0.15832 dice_loss 0.18169 +Epoch [117/4000] Validation [3/4] Loss: 0.16357 focal_loss 0.07081 dice_loss 0.09277 +Epoch [117/4000] Validation [4/4] Loss: 0.21336 focal_loss 0.08539 dice_loss 0.12797 +Epoch [117/4000] Validation metric {'Val/mean dice_metric': 0.957638144493103, 'Val/mean miou_metric': 0.9292243123054504, 'Val/mean f1': 0.9613983631134033, 'Val/mean precision': 0.959426760673523, 'Val/mean recall': 0.9633781313896179, 'Val/mean hd95_metric': 8.25694465637207} +Cheakpoint... +Epoch [117/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.957638144493103, 'Val/mean miou_metric': 0.9292243123054504, 'Val/mean f1': 0.9613983631134033, 'Val/mean precision': 0.959426760673523, 'Val/mean recall': 0.9633781313896179, 'Val/mean hd95_metric': 8.25694465637207} +Epoch [118/4000] Training [1/16] Loss: 0.02492 +Epoch [118/4000] Training [2/16] Loss: 0.01707 +Epoch [118/4000] Training [3/16] Loss: 0.02440 +Epoch [118/4000] Training [4/16] Loss: 0.02174 +Epoch [118/4000] Training [5/16] Loss: 0.02730 +Epoch [118/4000] Training [6/16] Loss: 0.01927 +Epoch [118/4000] Training [7/16] Loss: 0.03168 +Epoch [118/4000] Training [8/16] Loss: 0.02181 +Epoch [118/4000] Training [9/16] Loss: 0.06847 +Epoch [118/4000] Training [10/16] Loss: 0.02102 +Epoch [118/4000] Training [11/16] Loss: 0.02491 +Epoch [118/4000] Training [12/16] Loss: 0.03225 +Epoch [118/4000] Training [13/16] Loss: 0.03261 +Epoch [118/4000] Training [14/16] Loss: 0.02658 +Epoch [118/4000] Training [15/16] Loss: 0.02864 +Epoch [118/4000] Training [16/16] Loss: 0.02800 +Epoch [118/4000] Training metric {'Train/mean dice_metric': 0.9766297340393066, 'Train/mean miou_metric': 0.9571402668952942, 'Train/mean f1': 0.9758008718490601, 'Train/mean precision': 0.9724479913711548, 'Train/mean recall': 0.979176938533783, 'Train/mean hd95_metric': 4.398050308227539} +Epoch [118/4000] Validation [1/4] Loss: 0.16435 focal_loss 0.08570 dice_loss 0.07866 +Epoch [118/4000] Validation [2/4] Loss: 0.34770 focal_loss 0.15082 dice_loss 0.19688 +Epoch [118/4000] Validation [3/4] Loss: 0.22671 focal_loss 0.11898 dice_loss 0.10773 +Epoch [118/4000] Validation [4/4] Loss: 0.18522 focal_loss 0.05853 dice_loss 0.12669 +Epoch [118/4000] Validation metric {'Val/mean dice_metric': 0.9523693323135376, 'Val/mean miou_metric': 0.9226778149604797, 'Val/mean f1': 0.9576525092124939, 'Val/mean precision': 0.9573433995246887, 'Val/mean recall': 0.957961916923523, 'Val/mean hd95_metric': 8.364853858947754} +Cheakpoint... +Epoch [118/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9524], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9523693323135376, 'Val/mean miou_metric': 0.9226778149604797, 'Val/mean f1': 0.9576525092124939, 'Val/mean precision': 0.9573433995246887, 'Val/mean recall': 0.957961916923523, 'Val/mean hd95_metric': 8.364853858947754} +Epoch [119/4000] Training [1/16] Loss: 0.02247 +Epoch [119/4000] Training [2/16] Loss: 0.02214 +Epoch [119/4000] Training [3/16] Loss: 0.05063 +Epoch [119/4000] Training [4/16] Loss: 0.06962 +Epoch [119/4000] Training [5/16] Loss: 0.10716 +Epoch [119/4000] Training [6/16] Loss: 0.02189 +Epoch [119/4000] Training [7/16] Loss: 0.03324 +Epoch [119/4000] Training [8/16] Loss: 0.02446 +Epoch [119/4000] Training [9/16] Loss: 0.02021 +Epoch [119/4000] Training [10/16] Loss: 0.01725 +Epoch [119/4000] Training [11/16] Loss: 0.02332 +Epoch [119/4000] Training [12/16] Loss: 0.01938 +Epoch [119/4000] Training [13/16] Loss: 0.02200 +Epoch [119/4000] Training [14/16] Loss: 0.02594 +Epoch [119/4000] Training [15/16] Loss: 0.04238 +Epoch [119/4000] Training [16/16] Loss: 0.02861 +Epoch [119/4000] Training metric {'Train/mean dice_metric': 0.978926420211792, 'Train/mean miou_metric': 0.9601567983627319, 'Train/mean f1': 0.9785687327384949, 'Train/mean precision': 0.973048746585846, 'Train/mean recall': 0.9841517210006714, 'Train/mean hd95_metric': 3.604745388031006} +Epoch [119/4000] Validation [1/4] Loss: 0.49407 focal_loss 0.35765 dice_loss 0.13642 +Epoch [119/4000] Validation [2/4] Loss: 0.33035 focal_loss 0.13522 dice_loss 0.19512 +Epoch [119/4000] Validation [3/4] Loss: 0.16921 focal_loss 0.07875 dice_loss 0.09046 +Epoch [119/4000] Validation [4/4] Loss: 0.14577 focal_loss 0.05731 dice_loss 0.08847 +Epoch [119/4000] Validation metric {'Val/mean dice_metric': 0.9562921524047852, 'Val/mean miou_metric': 0.9274110794067383, 'Val/mean f1': 0.9583519101142883, 'Val/mean precision': 0.9488947987556458, 'Val/mean recall': 0.9679993987083435, 'Val/mean hd95_metric': 8.612195014953613} +Cheakpoint... +Epoch [119/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9563], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9562921524047852, 'Val/mean miou_metric': 0.9274110794067383, 'Val/mean f1': 0.9583519101142883, 'Val/mean precision': 0.9488947987556458, 'Val/mean recall': 0.9679993987083435, 'Val/mean hd95_metric': 8.612195014953613} +Epoch [120/4000] Training [1/16] Loss: 0.01868 +Epoch [120/4000] Training [2/16] Loss: 0.03805 +Epoch [120/4000] Training [3/16] Loss: 0.02180 +Epoch [120/4000] Training [4/16] Loss: 0.02961 +Epoch [120/4000] Training [5/16] Loss: 0.02287 +Epoch [120/4000] Training [6/16] Loss: 0.02649 +Epoch [120/4000] Training [7/16] Loss: 0.02082 +Epoch [120/4000] Training [8/16] Loss: 0.03780 +Epoch [120/4000] Training [9/16] Loss: 0.02331 +Epoch [120/4000] Training [10/16] Loss: 0.03422 +Epoch [120/4000] Training [11/16] Loss: 0.01872 +Epoch [120/4000] Training [12/16] Loss: 0.02130 +Epoch [120/4000] Training [13/16] Loss: 0.03335 +Epoch [120/4000] Training [14/16] Loss: 0.02372 +Epoch [120/4000] Training [15/16] Loss: 0.02768 +Epoch [120/4000] Training [16/16] Loss: 0.02573 +Epoch [120/4000] Training metric {'Train/mean dice_metric': 0.981487512588501, 'Train/mean miou_metric': 0.9641163349151611, 'Train/mean f1': 0.9803183078765869, 'Train/mean precision': 0.9761912226676941, 'Train/mean recall': 0.9844804406166077, 'Train/mean hd95_metric': 2.9432601928710938} +Epoch [120/4000] Validation [1/4] Loss: 0.13894 focal_loss 0.07464 dice_loss 0.06431 +Epoch [120/4000] Validation [2/4] Loss: 0.28707 focal_loss 0.09456 dice_loss 0.19251 +Epoch [120/4000] Validation [3/4] Loss: 0.13266 focal_loss 0.05527 dice_loss 0.07739 +Epoch [120/4000] Validation [4/4] Loss: 0.24712 focal_loss 0.13224 dice_loss 0.11488 +Epoch [120/4000] Validation metric {'Val/mean dice_metric': 0.9573864936828613, 'Val/mean miou_metric': 0.930130124092102, 'Val/mean f1': 0.9608558416366577, 'Val/mean precision': 0.9558374285697937, 'Val/mean recall': 0.9659273624420166, 'Val/mean hd95_metric': 7.463710784912109} +Cheakpoint... +Epoch [120/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9574], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573864936828613, 'Val/mean miou_metric': 0.930130124092102, 'Val/mean f1': 0.9608558416366577, 'Val/mean precision': 0.9558374285697937, 'Val/mean recall': 0.9659273624420166, 'Val/mean hd95_metric': 7.463710784912109} +Epoch [121/4000] Training [1/16] Loss: 0.01590 +Epoch [121/4000] Training [2/16] Loss: 0.05173 +Epoch [121/4000] Training [3/16] Loss: 0.02023 +Epoch [121/4000] Training [4/16] Loss: 0.02295 +Epoch [121/4000] Training [5/16] Loss: 0.02556 +Epoch [121/4000] Training [6/16] Loss: 0.02185 +Epoch [121/4000] Training [7/16] Loss: 0.02765 +Epoch [121/4000] Training [8/16] Loss: 0.02134 +Epoch [121/4000] Training [9/16] Loss: 0.04634 +Epoch [121/4000] Training [10/16] Loss: 0.02135 +Epoch [121/4000] Training [11/16] Loss: 0.01670 +Epoch [121/4000] Training [12/16] Loss: 0.01660 +Epoch [121/4000] Training [13/16] Loss: 0.02151 +Epoch [121/4000] Training [14/16] Loss: 0.02261 +Epoch [121/4000] Training [15/16] Loss: 0.01919 +Epoch [121/4000] Training [16/16] Loss: 0.02970 +Epoch [121/4000] Training metric {'Train/mean dice_metric': 0.9833148717880249, 'Train/mean miou_metric': 0.9675623178482056, 'Train/mean f1': 0.9819949865341187, 'Train/mean precision': 0.9766356348991394, 'Train/mean recall': 0.9874135255813599, 'Train/mean hd95_metric': 2.7947773933410645} +Epoch [121/4000] Validation [1/4] Loss: 0.67882 focal_loss 0.49887 dice_loss 0.17996 +Epoch [121/4000] Validation [2/4] Loss: 0.24588 focal_loss 0.08759 dice_loss 0.15829 +Epoch [121/4000] Validation [3/4] Loss: 0.19723 focal_loss 0.10053 dice_loss 0.09670 +Epoch [121/4000] Validation [4/4] Loss: 0.39915 focal_loss 0.22261 dice_loss 0.17654 +Epoch [121/4000] Validation metric {'Val/mean dice_metric': 0.9553813934326172, 'Val/mean miou_metric': 0.9286664724349976, 'Val/mean f1': 0.9567750692367554, 'Val/mean precision': 0.9561021327972412, 'Val/mean recall': 0.9574490785598755, 'Val/mean hd95_metric': 7.494978904724121} +Cheakpoint... +Epoch [121/4000] best acc:tensor([0.9610], device='cuda:0'), Now : mean acc: tensor([0.9554], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9553813934326172, 'Val/mean miou_metric': 0.9286664724349976, 'Val/mean f1': 0.9567750692367554, 'Val/mean precision': 0.9561021327972412, 'Val/mean recall': 0.9574490785598755, 'Val/mean hd95_metric': 7.494978904724121} +Epoch [122/4000] Training [1/16] Loss: 0.02758 +Epoch [122/4000] Training [2/16] Loss: 0.02646 +Epoch [122/4000] Training [3/16] Loss: 0.01840 +Epoch [122/4000] Training [4/16] Loss: 0.01982 +Epoch [122/4000] Training [5/16] Loss: 0.01652 +Epoch [122/4000] Training [6/16] Loss: 0.03027 +Epoch [122/4000] Training [7/16] Loss: 0.02168 +Epoch [122/4000] Training [8/16] Loss: 0.02863 +Epoch [122/4000] Training [9/16] Loss: 0.01862 +Epoch [122/4000] Training [10/16] Loss: 0.02623 +Epoch [122/4000] Training [11/16] Loss: 0.02017 +Epoch [122/4000] Training [12/16] Loss: 0.02680 +Epoch [122/4000] Training [13/16] Loss: 0.02313 +Epoch [122/4000] Training [14/16] Loss: 0.02540 +Epoch [122/4000] Training [15/16] Loss: 0.01930 +Epoch [122/4000] Training [16/16] Loss: 0.02697 +Epoch [122/4000] Training metric {'Train/mean dice_metric': 0.9831066131591797, 'Train/mean miou_metric': 0.9668681025505066, 'Train/mean f1': 0.9813367128372192, 'Train/mean precision': 0.9769731163978577, 'Train/mean recall': 0.9857394695281982, 'Train/mean hd95_metric': 2.6922335624694824} +Epoch [122/4000] Validation [1/4] Loss: 0.18423 focal_loss 0.10972 dice_loss 0.07451 +Epoch [122/4000] Validation [2/4] Loss: 0.28693 focal_loss 0.11065 dice_loss 0.17628 +Epoch [122/4000] Validation [3/4] Loss: 0.10971 focal_loss 0.04683 dice_loss 0.06288 +Epoch [122/4000] Validation [4/4] Loss: 0.20573 focal_loss 0.10130 dice_loss 0.10443 +Epoch [122/4000] Validation metric {'Val/mean dice_metric': 0.9611902236938477, 'Val/mean miou_metric': 0.9344648122787476, 'Val/mean f1': 0.9638262391090393, 'Val/mean precision': 0.960837185382843, 'Val/mean recall': 0.9668341279029846, 'Val/mean hd95_metric': 7.643864631652832} +Cheakpoint... +Epoch [122/4000] best acc:tensor([0.9612], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9611902236938477, 'Val/mean miou_metric': 0.9344648122787476, 'Val/mean f1': 0.9638262391090393, 'Val/mean precision': 0.960837185382843, 'Val/mean recall': 0.9668341279029846, 'Val/mean hd95_metric': 7.643864631652832} +Epoch [123/4000] Training [1/16] Loss: 0.02104 +Epoch [123/4000] Training [2/16] Loss: 0.01851 +Epoch [123/4000] Training [3/16] Loss: 0.01753 +Epoch [123/4000] Training [4/16] Loss: 0.02884 +Epoch [123/4000] Training [5/16] Loss: 0.16755 +Epoch [123/4000] Training [6/16] Loss: 0.01795 +Epoch [123/4000] Training [7/16] Loss: 0.01924 +Epoch [123/4000] Training [8/16] Loss: 0.01860 +Epoch [123/4000] Training [9/16] Loss: 0.01955 +Epoch [123/4000] Training [10/16] Loss: 0.02296 +Epoch [123/4000] Training [11/16] Loss: 0.01841 +Epoch [123/4000] Training [12/16] Loss: 0.02340 +Epoch [123/4000] Training [13/16] Loss: 0.02189 +Epoch [123/4000] Training [14/16] Loss: 0.01883 +Epoch [123/4000] Training [15/16] Loss: 0.01721 +Epoch [123/4000] Training [16/16] Loss: 0.01895 +Epoch [123/4000] Training metric {'Train/mean dice_metric': 0.9829878211021423, 'Train/mean miou_metric': 0.9683266878128052, 'Train/mean f1': 0.9811807870864868, 'Train/mean precision': 0.976176917552948, 'Train/mean recall': 0.9862362146377563, 'Train/mean hd95_metric': 3.319201946258545} +Epoch [123/4000] Validation [1/4] Loss: 0.29603 focal_loss 0.17880 dice_loss 0.11723 +Epoch [123/4000] Validation [2/4] Loss: 0.32433 focal_loss 0.13327 dice_loss 0.19106 +Epoch [123/4000] Validation [3/4] Loss: 0.18727 focal_loss 0.08328 dice_loss 0.10399 +Epoch [123/4000] Validation [4/4] Loss: 0.25148 focal_loss 0.13300 dice_loss 0.11848 +Epoch [123/4000] Validation metric {'Val/mean dice_metric': 0.9580706357955933, 'Val/mean miou_metric': 0.9320780634880066, 'Val/mean f1': 0.959786057472229, 'Val/mean precision': 0.9558690190315247, 'Val/mean recall': 0.9637351632118225, 'Val/mean hd95_metric': 8.29253101348877} +Cheakpoint... +Epoch [123/4000] best acc:tensor([0.9612], device='cuda:0'), Now : mean acc: tensor([0.9581], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9580706357955933, 'Val/mean miou_metric': 0.9320780634880066, 'Val/mean f1': 0.959786057472229, 'Val/mean precision': 0.9558690190315247, 'Val/mean recall': 0.9637351632118225, 'Val/mean hd95_metric': 8.29253101348877} +Epoch [124/4000] Training [1/16] Loss: 0.02381 +Epoch [124/4000] Training [2/16] Loss: 0.02502 +Epoch [124/4000] Training [3/16] Loss: 0.02307 +Epoch [124/4000] Training [4/16] Loss: 0.02010 +Epoch [124/4000] Training [5/16] Loss: 0.03302 +Epoch [124/4000] Training [6/16] Loss: 0.02516 +Epoch [124/4000] Training [7/16] Loss: 0.01943 +Epoch [124/4000] Training [8/16] Loss: 0.02394 +Epoch [124/4000] Training [9/16] Loss: 0.01814 +Epoch [124/4000] Training [10/16] Loss: 0.03173 +Epoch [124/4000] Training [11/16] Loss: 0.02593 +Epoch [124/4000] Training [12/16] Loss: 0.02400 +Epoch [124/4000] Training [13/16] Loss: 0.02014 +Epoch [124/4000] Training [14/16] Loss: 0.01680 +Epoch [124/4000] Training [15/16] Loss: 0.01917 +Epoch [124/4000] Training [16/16] Loss: 0.05643 +Epoch [124/4000] Training metric {'Train/mean dice_metric': 0.9847005009651184, 'Train/mean miou_metric': 0.9698415994644165, 'Train/mean f1': 0.9821159839630127, 'Train/mean precision': 0.9772825241088867, 'Train/mean recall': 0.9869975447654724, 'Train/mean hd95_metric': 2.5612127780914307} +Epoch [124/4000] Validation [1/4] Loss: 0.28992 focal_loss 0.17901 dice_loss 0.11092 +Epoch [124/4000] Validation [2/4] Loss: 0.34721 focal_loss 0.16837 dice_loss 0.17885 +Epoch [124/4000] Validation [3/4] Loss: 0.12155 focal_loss 0.05790 dice_loss 0.06364 +Epoch [124/4000] Validation [4/4] Loss: 0.18270 focal_loss 0.07585 dice_loss 0.10686 +Epoch [124/4000] Validation metric {'Val/mean dice_metric': 0.9622397422790527, 'Val/mean miou_metric': 0.9366071820259094, 'Val/mean f1': 0.965264618396759, 'Val/mean precision': 0.9637478590011597, 'Val/mean recall': 0.96678626537323, 'Val/mean hd95_metric': 6.49793004989624} +Cheakpoint... +Epoch [124/4000] best acc:tensor([0.9622], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622397422790527, 'Val/mean miou_metric': 0.9366071820259094, 'Val/mean f1': 0.965264618396759, 'Val/mean precision': 0.9637478590011597, 'Val/mean recall': 0.96678626537323, 'Val/mean hd95_metric': 6.49793004989624} +Epoch [125/4000] Training [1/16] Loss: 0.01605 +Epoch [125/4000] Training [2/16] Loss: 0.01542 +Epoch [125/4000] Training [3/16] Loss: 0.02120 +Epoch [125/4000] Training [4/16] Loss: 0.01853 +Epoch [125/4000] Training [5/16] Loss: 0.02005 +Epoch [125/4000] Training [6/16] Loss: 0.01712 +Epoch [125/4000] Training [7/16] Loss: 0.01774 +Epoch [125/4000] Training [8/16] Loss: 0.02791 +Epoch [125/4000] Training [9/16] Loss: 0.01919 +Epoch [125/4000] Training [10/16] Loss: 0.01653 +Epoch [125/4000] Training [11/16] Loss: 0.02527 +Epoch [125/4000] Training [12/16] Loss: 0.02697 +Epoch [125/4000] Training [13/16] Loss: 0.01994 +Epoch [125/4000] Training [14/16] Loss: 0.01909 +Epoch [125/4000] Training [15/16] Loss: 0.02368 +Epoch [125/4000] Training [16/16] Loss: 0.01682 +Epoch [125/4000] Training metric {'Train/mean dice_metric': 0.9858886003494263, 'Train/mean miou_metric': 0.9720731377601624, 'Train/mean f1': 0.9838022589683533, 'Train/mean precision': 0.9795231223106384, 'Train/mean recall': 0.9881191253662109, 'Train/mean hd95_metric': 2.14039945602417} +Epoch [125/4000] Validation [1/4] Loss: 0.13890 focal_loss 0.07887 dice_loss 0.06003 +Epoch [125/4000] Validation [2/4] Loss: 0.20784 focal_loss 0.07161 dice_loss 0.13623 +Epoch [125/4000] Validation [3/4] Loss: 0.17647 focal_loss 0.09174 dice_loss 0.08473 +Epoch [125/4000] Validation [4/4] Loss: 0.18350 focal_loss 0.07649 dice_loss 0.10702 +Epoch [125/4000] Validation metric {'Val/mean dice_metric': 0.9642342329025269, 'Val/mean miou_metric': 0.93995600938797, 'Val/mean f1': 0.9684122800827026, 'Val/mean precision': 0.9628668427467346, 'Val/mean recall': 0.9740219712257385, 'Val/mean hd95_metric': 6.560096740722656} +Cheakpoint... +Epoch [125/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9642], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9642342329025269, 'Val/mean miou_metric': 0.93995600938797, 'Val/mean f1': 0.9684122800827026, 'Val/mean precision': 0.9628668427467346, 'Val/mean recall': 0.9740219712257385, 'Val/mean hd95_metric': 6.560096740722656} +Epoch [126/4000] Training [1/16] Loss: 0.02744 +Epoch [126/4000] Training [2/16] Loss: 0.01572 +Epoch [126/4000] Training [3/16] Loss: 0.01871 +Epoch [126/4000] Training [4/16] Loss: 0.01756 +Epoch [126/4000] Training [5/16] Loss: 0.01855 +Epoch [126/4000] Training [6/16] Loss: 0.01734 +Epoch [126/4000] Training [7/16] Loss: 0.04015 +Epoch [126/4000] Training [8/16] Loss: 0.02707 +Epoch [126/4000] Training [9/16] Loss: 0.05364 +Epoch [126/4000] Training [10/16] Loss: 0.02044 +Epoch [126/4000] Training [11/16] Loss: 0.01922 +Epoch [126/4000] Training [12/16] Loss: 0.01898 +Epoch [126/4000] Training [13/16] Loss: 0.01871 +Epoch [126/4000] Training [14/16] Loss: 0.01914 +Epoch [126/4000] Training [15/16] Loss: 0.01914 +Epoch [126/4000] Training [16/16] Loss: 0.01915 +Epoch [126/4000] Training metric {'Train/mean dice_metric': 0.9841657876968384, 'Train/mean miou_metric': 0.9689279794692993, 'Train/mean f1': 0.9819144606590271, 'Train/mean precision': 0.9771483540534973, 'Train/mean recall': 0.9867272973060608, 'Train/mean hd95_metric': 2.0368247032165527} +Epoch [126/4000] Validation [1/4] Loss: 0.12922 focal_loss 0.07277 dice_loss 0.05646 +Epoch [126/4000] Validation [2/4] Loss: 0.24721 focal_loss 0.08348 dice_loss 0.16374 +Epoch [126/4000] Validation [3/4] Loss: 0.13529 focal_loss 0.06507 dice_loss 0.07022 +Epoch [126/4000] Validation [4/4] Loss: 0.17843 focal_loss 0.06908 dice_loss 0.10935 +Epoch [126/4000] Validation metric {'Val/mean dice_metric': 0.9612905383110046, 'Val/mean miou_metric': 0.935826301574707, 'Val/mean f1': 0.9631494283676147, 'Val/mean precision': 0.9547215700149536, 'Val/mean recall': 0.9717275500297546, 'Val/mean hd95_metric': 7.289569854736328} +Cheakpoint... +Epoch [126/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612905383110046, 'Val/mean miou_metric': 0.935826301574707, 'Val/mean f1': 0.9631494283676147, 'Val/mean precision': 0.9547215700149536, 'Val/mean recall': 0.9717275500297546, 'Val/mean hd95_metric': 7.289569854736328} +Epoch [127/4000] Training [1/16] Loss: 0.02019 +Epoch [127/4000] Training [2/16] Loss: 0.02251 +Epoch [127/4000] Training [3/16] Loss: 0.01895 +Epoch [127/4000] Training [4/16] Loss: 0.02409 +Epoch [127/4000] Training [5/16] Loss: 0.03019 +Epoch [127/4000] Training [6/16] Loss: 0.02320 +Epoch [127/4000] Training [7/16] Loss: 0.12329 +Epoch [127/4000] Training [8/16] Loss: 0.03142 +Epoch [127/4000] Training [9/16] Loss: 0.02871 +Epoch [127/4000] Training [10/16] Loss: 0.01805 +Epoch [127/4000] Training [11/16] Loss: 0.01937 +Epoch [127/4000] Training [12/16] Loss: 0.02026 +Epoch [127/4000] Training [13/16] Loss: 0.03088 +Epoch [127/4000] Training [14/16] Loss: 0.01898 +Epoch [127/4000] Training [15/16] Loss: 0.04176 +Epoch [127/4000] Training [16/16] Loss: 0.03253 +Epoch [127/4000] Training metric {'Train/mean dice_metric': 0.9808695912361145, 'Train/mean miou_metric': 0.9638018608093262, 'Train/mean f1': 0.9796242713928223, 'Train/mean precision': 0.9755859375, 'Train/mean recall': 0.9836961627006531, 'Train/mean hd95_metric': 2.988910675048828} +Epoch [127/4000] Validation [1/4] Loss: 0.74291 focal_loss 0.52293 dice_loss 0.21999 +Epoch [127/4000] Validation [2/4] Loss: 0.15393 focal_loss 0.05056 dice_loss 0.10337 +Epoch [127/4000] Validation [3/4] Loss: 0.18534 focal_loss 0.09077 dice_loss 0.09457 +Epoch [127/4000] Validation [4/4] Loss: 0.12988 focal_loss 0.04301 dice_loss 0.08687 +Epoch [127/4000] Validation metric {'Val/mean dice_metric': 0.9594318270683289, 'Val/mean miou_metric': 0.9319164156913757, 'Val/mean f1': 0.9597311019897461, 'Val/mean precision': 0.9617541432380676, 'Val/mean recall': 0.9577164649963379, 'Val/mean hd95_metric': 7.765345096588135} +Cheakpoint... +Epoch [127/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9594], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9594318270683289, 'Val/mean miou_metric': 0.9319164156913757, 'Val/mean f1': 0.9597311019897461, 'Val/mean precision': 0.9617541432380676, 'Val/mean recall': 0.9577164649963379, 'Val/mean hd95_metric': 7.765345096588135} +Epoch [128/4000] Training [1/16] Loss: 0.01946 +Epoch [128/4000] Training [2/16] Loss: 0.02261 +Epoch [128/4000] Training [3/16] Loss: 0.02117 +Epoch [128/4000] Training [4/16] Loss: 0.03040 +Epoch [128/4000] Training [5/16] Loss: 0.02527 +Epoch [128/4000] Training [6/16] Loss: 0.02897 +Epoch [128/4000] Training [7/16] Loss: 0.02969 +Epoch [128/4000] Training [8/16] Loss: 0.01891 +Epoch [128/4000] Training [9/16] Loss: 0.02408 +Epoch [128/4000] Training [10/16] Loss: 0.02282 +Epoch [128/4000] Training [11/16] Loss: 0.01987 +Epoch [128/4000] Training [12/16] Loss: 0.02480 +Epoch [128/4000] Training [13/16] Loss: 0.02359 +Epoch [128/4000] Training [14/16] Loss: 0.02055 +Epoch [128/4000] Training [15/16] Loss: 0.02379 +Epoch [128/4000] Training [16/16] Loss: 0.02765 +Epoch [128/4000] Training metric {'Train/mean dice_metric': 0.9810805320739746, 'Train/mean miou_metric': 0.9632373452186584, 'Train/mean f1': 0.979350745677948, 'Train/mean precision': 0.9732345342636108, 'Train/mean recall': 0.9855443835258484, 'Train/mean hd95_metric': 5.267934799194336} +Epoch [128/4000] Validation [1/4] Loss: 0.12547 focal_loss 0.06871 dice_loss 0.05676 +Epoch [128/4000] Validation [2/4] Loss: 0.24465 focal_loss 0.08927 dice_loss 0.15538 +Epoch [128/4000] Validation [3/4] Loss: 0.14773 focal_loss 0.07183 dice_loss 0.07590 +Epoch [128/4000] Validation [4/4] Loss: 0.23992 focal_loss 0.10970 dice_loss 0.13021 +Epoch [128/4000] Validation metric {'Val/mean dice_metric': 0.9580103158950806, 'Val/mean miou_metric': 0.9297407269477844, 'Val/mean f1': 0.9607868790626526, 'Val/mean precision': 0.9496956467628479, 'Val/mean recall': 0.9721401929855347, 'Val/mean hd95_metric': 10.90577507019043} +Cheakpoint... +Epoch [128/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9580], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9580103158950806, 'Val/mean miou_metric': 0.9297407269477844, 'Val/mean f1': 0.9607868790626526, 'Val/mean precision': 0.9496956467628479, 'Val/mean recall': 0.9721401929855347, 'Val/mean hd95_metric': 10.90577507019043} +Epoch [129/4000] Training [1/16] Loss: 0.02664 +Epoch [129/4000] Training [2/16] Loss: 0.02134 +Epoch [129/4000] Training [3/16] Loss: 0.04985 +Epoch [129/4000] Training [4/16] Loss: 0.02126 +Epoch [129/4000] Training [5/16] Loss: 0.02267 +Epoch [129/4000] Training [6/16] Loss: 0.03409 +Epoch [129/4000] Training [7/16] Loss: 0.03188 +Epoch [129/4000] Training [8/16] Loss: 0.02231 +Epoch [129/4000] Training [9/16] Loss: 0.02979 +Epoch [129/4000] Training [10/16] Loss: 0.02428 +Epoch [129/4000] Training [11/16] Loss: 0.03180 +Epoch [129/4000] Training [12/16] Loss: 0.02124 +Epoch [129/4000] Training [13/16] Loss: 0.04368 +Epoch [129/4000] Training [14/16] Loss: 0.03089 +Epoch [129/4000] Training [15/16] Loss: 0.02723 +Epoch [129/4000] Training [16/16] Loss: 0.02579 +Epoch [129/4000] Training metric {'Train/mean dice_metric': 0.9795126914978027, 'Train/mean miou_metric': 0.9610602855682373, 'Train/mean f1': 0.9790294170379639, 'Train/mean precision': 0.9757170677185059, 'Train/mean recall': 0.982364296913147, 'Train/mean hd95_metric': 4.013131141662598} +Epoch [129/4000] Validation [1/4] Loss: 0.88018 focal_loss 0.72268 dice_loss 0.15751 +Epoch [129/4000] Validation [2/4] Loss: 0.21187 focal_loss 0.07534 dice_loss 0.13653 +Epoch [129/4000] Validation [3/4] Loss: 0.19719 focal_loss 0.09819 dice_loss 0.09900 +Epoch [129/4000] Validation [4/4] Loss: 0.25697 focal_loss 0.12269 dice_loss 0.13427 +Epoch [129/4000] Validation metric {'Val/mean dice_metric': 0.9553869962692261, 'Val/mean miou_metric': 0.9264634847640991, 'Val/mean f1': 0.9589253664016724, 'Val/mean precision': 0.9583530426025391, 'Val/mean recall': 0.9594982862472534, 'Val/mean hd95_metric': 8.204168319702148} +Cheakpoint... +Epoch [129/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9554], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9553869962692261, 'Val/mean miou_metric': 0.9264634847640991, 'Val/mean f1': 0.9589253664016724, 'Val/mean precision': 0.9583530426025391, 'Val/mean recall': 0.9594982862472534, 'Val/mean hd95_metric': 8.204168319702148} +Epoch [130/4000] Training [1/16] Loss: 0.01971 +Epoch [130/4000] Training [2/16] Loss: 0.01918 +Epoch [130/4000] Training [3/16] Loss: 0.03097 +Epoch [130/4000] Training [4/16] Loss: 0.02024 +Epoch [130/4000] Training [5/16] Loss: 0.03210 +Epoch [130/4000] Training [6/16] Loss: 0.01852 +Epoch [130/4000] Training [7/16] Loss: 0.02242 +Epoch [130/4000] Training [8/16] Loss: 0.02479 +Epoch [130/4000] Training [9/16] Loss: 0.02672 +Epoch [130/4000] Training [10/16] Loss: 0.03337 +Epoch [130/4000] Training [11/16] Loss: 0.02603 +Epoch [130/4000] Training [12/16] Loss: 0.01851 +Epoch [130/4000] Training [13/16] Loss: 0.01870 +Epoch [130/4000] Training [14/16] Loss: 0.02228 +Epoch [130/4000] Training [15/16] Loss: 0.02145 +Epoch [130/4000] Training [16/16] Loss: 0.03110 +Epoch [130/4000] Training metric {'Train/mean dice_metric': 0.9819594621658325, 'Train/mean miou_metric': 0.9651298522949219, 'Train/mean f1': 0.9808247089385986, 'Train/mean precision': 0.9761736989021301, 'Train/mean recall': 0.9855201840400696, 'Train/mean hd95_metric': 2.8447518348693848} +Epoch [130/4000] Validation [1/4] Loss: 0.48752 focal_loss 0.35536 dice_loss 0.13216 +Epoch [130/4000] Validation [2/4] Loss: 0.26188 focal_loss 0.11058 dice_loss 0.15130 +Epoch [130/4000] Validation [3/4] Loss: 0.15077 focal_loss 0.06452 dice_loss 0.08625 +Epoch [130/4000] Validation [4/4] Loss: 0.16777 focal_loss 0.07145 dice_loss 0.09632 +Epoch [130/4000] Validation metric {'Val/mean dice_metric': 0.9610904455184937, 'Val/mean miou_metric': 0.9337501525878906, 'Val/mean f1': 0.9630099534988403, 'Val/mean precision': 0.9634004831314087, 'Val/mean recall': 0.9626197814941406, 'Val/mean hd95_metric': 6.915952205657959} +Cheakpoint... +Epoch [130/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610904455184937, 'Val/mean miou_metric': 0.9337501525878906, 'Val/mean f1': 0.9630099534988403, 'Val/mean precision': 0.9634004831314087, 'Val/mean recall': 0.9626197814941406, 'Val/mean hd95_metric': 6.915952205657959} +Epoch [131/4000] Training [1/16] Loss: 0.01844 +Epoch [131/4000] Training [2/16] Loss: 0.01924 +Epoch [131/4000] Training [3/16] Loss: 0.03008 +Epoch [131/4000] Training [4/16] Loss: 0.01595 +Epoch [131/4000] Training [5/16] Loss: 0.02390 +Epoch [131/4000] Training [6/16] Loss: 0.01725 +Epoch [131/4000] Training [7/16] Loss: 0.03014 +Epoch [131/4000] Training [8/16] Loss: 0.01759 +Epoch [131/4000] Training [9/16] Loss: 0.02459 +Epoch [131/4000] Training [10/16] Loss: 0.02032 +Epoch [131/4000] Training [11/16] Loss: 0.01682 +Epoch [131/4000] Training [12/16] Loss: 0.01929 +Epoch [131/4000] Training [13/16] Loss: 0.02284 +Epoch [131/4000] Training [14/16] Loss: 0.02176 +Epoch [131/4000] Training [15/16] Loss: 0.02563 +Epoch [131/4000] Training [16/16] Loss: 0.02072 +Epoch [131/4000] Training metric {'Train/mean dice_metric': 0.9849354028701782, 'Train/mean miou_metric': 0.9705230593681335, 'Train/mean f1': 0.9831685423851013, 'Train/mean precision': 0.9786443114280701, 'Train/mean recall': 0.9877347350120544, 'Train/mean hd95_metric': 2.342987060546875} +Epoch [131/4000] Validation [1/4] Loss: 0.23330 focal_loss 0.12282 dice_loss 0.11048 +Epoch [131/4000] Validation [2/4] Loss: 0.27090 focal_loss 0.10499 dice_loss 0.16591 +Epoch [131/4000] Validation [3/4] Loss: 0.18297 focal_loss 0.08339 dice_loss 0.09958 +Epoch [131/4000] Validation [4/4] Loss: 0.28513 focal_loss 0.15953 dice_loss 0.12560 +Epoch [131/4000] Validation metric {'Val/mean dice_metric': 0.9616538882255554, 'Val/mean miou_metric': 0.9355109333992004, 'Val/mean f1': 0.9641465544700623, 'Val/mean precision': 0.9615464210510254, 'Val/mean recall': 0.9667606949806213, 'Val/mean hd95_metric': 7.0225982666015625} +Cheakpoint... +Epoch [131/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616538882255554, 'Val/mean miou_metric': 0.9355109333992004, 'Val/mean f1': 0.9641465544700623, 'Val/mean precision': 0.9615464210510254, 'Val/mean recall': 0.9667606949806213, 'Val/mean hd95_metric': 7.0225982666015625} +Epoch [132/4000] Training [1/16] Loss: 0.02445 +Epoch [132/4000] Training [2/16] Loss: 0.01715 +Epoch [132/4000] Training [3/16] Loss: 0.02895 +Epoch [132/4000] Training [4/16] Loss: 0.01607 +Epoch [132/4000] Training [5/16] Loss: 0.01854 +Epoch [132/4000] Training [6/16] Loss: 0.02390 +Epoch [132/4000] Training [7/16] Loss: 0.02045 +Epoch [132/4000] Training [8/16] Loss: 0.03097 +Epoch [132/4000] Training [9/16] Loss: 0.01571 +Epoch [132/4000] Training [10/16] Loss: 0.02009 +Epoch [132/4000] Training [11/16] Loss: 0.02902 +Epoch [132/4000] Training [12/16] Loss: 0.02334 +Epoch [132/4000] Training [13/16] Loss: 0.01827 +Epoch [132/4000] Training [14/16] Loss: 0.02509 +Epoch [132/4000] Training [15/16] Loss: 0.02290 +Epoch [132/4000] Training [16/16] Loss: 0.02912 +Epoch [132/4000] Training metric {'Train/mean dice_metric': 0.9841986894607544, 'Train/mean miou_metric': 0.9689211249351501, 'Train/mean f1': 0.9820787906646729, 'Train/mean precision': 0.9779205918312073, 'Train/mean recall': 0.9862725138664246, 'Train/mean hd95_metric': 3.181279420852661} +Epoch [132/4000] Validation [1/4] Loss: 0.38135 focal_loss 0.22626 dice_loss 0.15509 +Epoch [132/4000] Validation [2/4] Loss: 0.56476 focal_loss 0.24993 dice_loss 0.31483 +Epoch [132/4000] Validation [3/4] Loss: 0.22575 focal_loss 0.11066 dice_loss 0.11510 +Epoch [132/4000] Validation [4/4] Loss: 0.14960 focal_loss 0.06355 dice_loss 0.08605 +Epoch [132/4000] Validation metric {'Val/mean dice_metric': 0.9513524770736694, 'Val/mean miou_metric': 0.923426628112793, 'Val/mean f1': 0.9559959769248962, 'Val/mean precision': 0.9643159508705139, 'Val/mean recall': 0.9478182792663574, 'Val/mean hd95_metric': 8.73447322845459} +Cheakpoint... +Epoch [132/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9514], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9513524770736694, 'Val/mean miou_metric': 0.923426628112793, 'Val/mean f1': 0.9559959769248962, 'Val/mean precision': 0.9643159508705139, 'Val/mean recall': 0.9478182792663574, 'Val/mean hd95_metric': 8.73447322845459} +Epoch [133/4000] Training [1/16] Loss: 0.07199 +Epoch [133/4000] Training [2/16] Loss: 0.02028 +Epoch [133/4000] Training [3/16] Loss: 0.02307 +Epoch [133/4000] Training [4/16] Loss: 0.01963 +Epoch [133/4000] Training [5/16] Loss: 0.01607 +Epoch [133/4000] Training [6/16] Loss: 0.01679 +Epoch [133/4000] Training [7/16] Loss: 0.03196 +Epoch [133/4000] Training [8/16] Loss: 0.02729 +Epoch [133/4000] Training [9/16] Loss: 0.01778 +Epoch [133/4000] Training [10/16] Loss: 0.02245 +Epoch [133/4000] Training [11/16] Loss: 0.01767 +Epoch [133/4000] Training [12/16] Loss: 0.01894 +Epoch [133/4000] Training [13/16] Loss: 0.03432 +Epoch [133/4000] Training [14/16] Loss: 0.04888 +Epoch [133/4000] Training [15/16] Loss: 0.02163 +Epoch [133/4000] Training [16/16] Loss: 0.03359 +Epoch [133/4000] Training metric {'Train/mean dice_metric': 0.9820783138275146, 'Train/mean miou_metric': 0.9659773707389832, 'Train/mean f1': 0.9794315099716187, 'Train/mean precision': 0.9726200103759766, 'Train/mean recall': 0.9863391518592834, 'Train/mean hd95_metric': 3.2810401916503906} +Epoch [133/4000] Validation [1/4] Loss: 0.30549 focal_loss 0.20010 dice_loss 0.10539 +Epoch [133/4000] Validation [2/4] Loss: 0.33307 focal_loss 0.14452 dice_loss 0.18856 +Epoch [133/4000] Validation [3/4] Loss: 0.19405 focal_loss 0.09276 dice_loss 0.10129 +Epoch [133/4000] Validation [4/4] Loss: 0.18103 focal_loss 0.08218 dice_loss 0.09886 +Epoch [133/4000] Validation metric {'Val/mean dice_metric': 0.9591304063796997, 'Val/mean miou_metric': 0.9322648048400879, 'Val/mean f1': 0.9594977498054504, 'Val/mean precision': 0.9527984261512756, 'Val/mean recall': 0.9662920236587524, 'Val/mean hd95_metric': 8.3907470703125} +Cheakpoint... +Epoch [133/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9591], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9591304063796997, 'Val/mean miou_metric': 0.9322648048400879, 'Val/mean f1': 0.9594977498054504, 'Val/mean precision': 0.9527984261512756, 'Val/mean recall': 0.9662920236587524, 'Val/mean hd95_metric': 8.3907470703125} +Epoch [134/4000] Training [1/16] Loss: 0.01524 +Epoch [134/4000] Training [2/16] Loss: 0.01837 +Epoch [134/4000] Training [3/16] Loss: 0.02444 +Epoch [134/4000] Training [4/16] Loss: 0.02336 +Epoch [134/4000] Training [5/16] Loss: 0.01959 +Epoch [134/4000] Training [6/16] Loss: 0.02693 +Epoch [134/4000] Training [7/16] Loss: 0.01691 +Epoch [134/4000] Training [8/16] Loss: 0.01941 +Epoch [134/4000] Training [9/16] Loss: 0.02233 +Epoch [134/4000] Training [10/16] Loss: 0.03083 +Epoch [134/4000] Training [11/16] Loss: 0.02432 +Epoch [134/4000] Training [12/16] Loss: 0.01711 +Epoch [134/4000] Training [13/16] Loss: 0.01737 +Epoch [134/4000] Training [14/16] Loss: 0.02892 +Epoch [134/4000] Training [15/16] Loss: 0.03344 +Epoch [134/4000] Training [16/16] Loss: 0.02347 +Epoch [134/4000] Training metric {'Train/mean dice_metric': 0.9844940304756165, 'Train/mean miou_metric': 0.9694482088088989, 'Train/mean f1': 0.98241126537323, 'Train/mean precision': 0.9786457419395447, 'Train/mean recall': 0.9862058758735657, 'Train/mean hd95_metric': 2.3943796157836914} +Epoch [134/4000] Validation [1/4] Loss: 0.24873 focal_loss 0.15820 dice_loss 0.09053 +Epoch [134/4000] Validation [2/4] Loss: 0.22664 focal_loss 0.08381 dice_loss 0.14284 +Epoch [134/4000] Validation [3/4] Loss: 0.10957 focal_loss 0.04301 dice_loss 0.06657 +Epoch [134/4000] Validation [4/4] Loss: 0.16078 focal_loss 0.05759 dice_loss 0.10318 +Epoch [134/4000] Validation metric {'Val/mean dice_metric': 0.9607040286064148, 'Val/mean miou_metric': 0.935559868812561, 'Val/mean f1': 0.9627615809440613, 'Val/mean precision': 0.9545221328735352, 'Val/mean recall': 0.9711446166038513, 'Val/mean hd95_metric': 7.1526994705200195} +Cheakpoint... +Epoch [134/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9607], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9607040286064148, 'Val/mean miou_metric': 0.935559868812561, 'Val/mean f1': 0.9627615809440613, 'Val/mean precision': 0.9545221328735352, 'Val/mean recall': 0.9711446166038513, 'Val/mean hd95_metric': 7.1526994705200195} +Epoch [135/4000] Training [1/16] Loss: 0.02043 +Epoch [135/4000] Training [2/16] Loss: 0.03050 +Epoch [135/4000] Training [3/16] Loss: 0.01694 +Epoch [135/4000] Training [4/16] Loss: 0.01724 +Epoch [135/4000] Training [5/16] Loss: 0.02022 +Epoch [135/4000] Training [6/16] Loss: 0.01889 +Epoch [135/4000] Training [7/16] Loss: 0.03416 +Epoch [135/4000] Training [8/16] Loss: 0.01607 +Epoch [135/4000] Training [9/16] Loss: 0.01937 +Epoch [135/4000] Training [10/16] Loss: 0.02331 +Epoch [135/4000] Training [11/16] Loss: 0.02501 +Epoch [135/4000] Training [12/16] Loss: 0.02389 +Epoch [135/4000] Training [13/16] Loss: 0.02204 +Epoch [135/4000] Training [14/16] Loss: 0.01789 +Epoch [135/4000] Training [15/16] Loss: 0.01914 +Epoch [135/4000] Training [16/16] Loss: 0.02197 +Epoch [135/4000] Training metric {'Train/mean dice_metric': 0.9850793480873108, 'Train/mean miou_metric': 0.9705133438110352, 'Train/mean f1': 0.9829564094543457, 'Train/mean precision': 0.978766918182373, 'Train/mean recall': 0.9871819615364075, 'Train/mean hd95_metric': 1.8817766904830933} +Epoch [135/4000] Validation [1/4] Loss: 0.10747 focal_loss 0.05421 dice_loss 0.05326 +Epoch [135/4000] Validation [2/4] Loss: 0.20519 focal_loss 0.07760 dice_loss 0.12759 +Epoch [135/4000] Validation [3/4] Loss: 0.14374 focal_loss 0.07092 dice_loss 0.07282 +Epoch [135/4000] Validation [4/4] Loss: 0.21414 focal_loss 0.10844 dice_loss 0.10569 +Epoch [135/4000] Validation metric {'Val/mean dice_metric': 0.9610645174980164, 'Val/mean miou_metric': 0.93610018491745, 'Val/mean f1': 0.9651434421539307, 'Val/mean precision': 0.959987998008728, 'Val/mean recall': 0.970354437828064, 'Val/mean hd95_metric': 6.570803642272949} +Cheakpoint... +Epoch [135/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610645174980164, 'Val/mean miou_metric': 0.93610018491745, 'Val/mean f1': 0.9651434421539307, 'Val/mean precision': 0.959987998008728, 'Val/mean recall': 0.970354437828064, 'Val/mean hd95_metric': 6.570803642272949} +Epoch [136/4000] Training [1/16] Loss: 0.02477 +Epoch [136/4000] Training [2/16] Loss: 0.02165 +Epoch [136/4000] Training [3/16] Loss: 0.02895 +Epoch [136/4000] Training [4/16] Loss: 0.02329 +Epoch [136/4000] Training [5/16] Loss: 0.01792 +Epoch [136/4000] Training [6/16] Loss: 0.01889 +Epoch [136/4000] Training [7/16] Loss: 0.01907 +Epoch [136/4000] Training [8/16] Loss: 0.01946 +Epoch [136/4000] Training [9/16] Loss: 0.01783 +Epoch [136/4000] Training [10/16] Loss: 0.02437 +Epoch [136/4000] Training [11/16] Loss: 0.02240 +Epoch [136/4000] Training [12/16] Loss: 0.01939 +Epoch [136/4000] Training [13/16] Loss: 0.02026 +Epoch [136/4000] Training [14/16] Loss: 0.02566 +Epoch [136/4000] Training [15/16] Loss: 0.02744 +Epoch [136/4000] Training [16/16] Loss: 0.02392 +Epoch [136/4000] Training metric {'Train/mean dice_metric': 0.9805944561958313, 'Train/mean miou_metric': 0.964625358581543, 'Train/mean f1': 0.980584442615509, 'Train/mean precision': 0.9750218391418457, 'Train/mean recall': 0.986210823059082, 'Train/mean hd95_metric': 3.002963066101074} +Epoch [136/4000] Validation [1/4] Loss: 0.16255 focal_loss 0.10305 dice_loss 0.05950 +Epoch [136/4000] Validation [2/4] Loss: 0.24813 focal_loss 0.09090 dice_loss 0.15723 +Epoch [136/4000] Validation [3/4] Loss: 0.24095 focal_loss 0.13350 dice_loss 0.10745 +Epoch [136/4000] Validation [4/4] Loss: 0.27041 focal_loss 0.13891 dice_loss 0.13151 +Epoch [136/4000] Validation metric {'Val/mean dice_metric': 0.9573535919189453, 'Val/mean miou_metric': 0.9302564859390259, 'Val/mean f1': 0.9614373445510864, 'Val/mean precision': 0.9518136382102966, 'Val/mean recall': 0.9712576866149902, 'Val/mean hd95_metric': 8.363325119018555} +Cheakpoint... +Epoch [136/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9574], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573535919189453, 'Val/mean miou_metric': 0.9302564859390259, 'Val/mean f1': 0.9614373445510864, 'Val/mean precision': 0.9518136382102966, 'Val/mean recall': 0.9712576866149902, 'Val/mean hd95_metric': 8.363325119018555} +Epoch [137/4000] Training [1/16] Loss: 0.01957 +Epoch [137/4000] Training [2/16] Loss: 0.02556 +Epoch [137/4000] Training [3/16] Loss: 0.01638 +Epoch [137/4000] Training [4/16] Loss: 0.02342 +Epoch [137/4000] Training [5/16] Loss: 0.02067 +Epoch [137/4000] Training [6/16] Loss: 0.04290 +Epoch [137/4000] Training [7/16] Loss: 0.03653 +Epoch [137/4000] Training [8/16] Loss: 0.01698 +Epoch [137/4000] Training [9/16] Loss: 0.03051 +Epoch [137/4000] Training [10/16] Loss: 0.03473 +Epoch [137/4000] Training [11/16] Loss: 0.02396 +Epoch [137/4000] Training [12/16] Loss: 0.02452 +Epoch [137/4000] Training [13/16] Loss: 0.02424 +Epoch [137/4000] Training [14/16] Loss: 0.02727 +Epoch [137/4000] Training [15/16] Loss: 0.02906 +Epoch [137/4000] Training [16/16] Loss: 0.04788 +Epoch [137/4000] Training metric {'Train/mean dice_metric': 0.9794753789901733, 'Train/mean miou_metric': 0.961083173751831, 'Train/mean f1': 0.977728009223938, 'Train/mean precision': 0.9714319705963135, 'Train/mean recall': 0.9841061234474182, 'Train/mean hd95_metric': 5.287175178527832} +Epoch [137/4000] Validation [1/4] Loss: 0.13346 focal_loss 0.06871 dice_loss 0.06475 +Epoch [137/4000] Validation [2/4] Loss: 0.26428 focal_loss 0.07461 dice_loss 0.18967 +Epoch [137/4000] Validation [3/4] Loss: 0.23156 focal_loss 0.11792 dice_loss 0.11364 +Epoch [137/4000] Validation [4/4] Loss: 0.31640 focal_loss 0.14248 dice_loss 0.17391 +Epoch [137/4000] Validation metric {'Val/mean dice_metric': 0.9532167315483093, 'Val/mean miou_metric': 0.9233258962631226, 'Val/mean f1': 0.9547299742698669, 'Val/mean precision': 0.9478580951690674, 'Val/mean recall': 0.9617021679878235, 'Val/mean hd95_metric': 11.417284965515137} +Cheakpoint... +Epoch [137/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9532], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9532167315483093, 'Val/mean miou_metric': 0.9233258962631226, 'Val/mean f1': 0.9547299742698669, 'Val/mean precision': 0.9478580951690674, 'Val/mean recall': 0.9617021679878235, 'Val/mean hd95_metric': 11.417284965515137} +Epoch [138/4000] Training [1/16] Loss: 0.02229 +Epoch [138/4000] Training [2/16] Loss: 0.07630 +Epoch [138/4000] Training [3/16] Loss: 0.02167 +Epoch [138/4000] Training [4/16] Loss: 0.03386 +Epoch [138/4000] Training [5/16] Loss: 0.03711 +Epoch [138/4000] Training [6/16] Loss: 0.01968 +Epoch [138/4000] Training [7/16] Loss: 0.02042 +Epoch [138/4000] Training [8/16] Loss: 0.02524 +Epoch [138/4000] Training [9/16] Loss: 0.01847 +Epoch [138/4000] Training [10/16] Loss: 0.03117 +Epoch [138/4000] Training [11/16] Loss: 0.04021 +Epoch [138/4000] Training [12/16] Loss: 0.02656 +Epoch [138/4000] Training [13/16] Loss: 0.02229 +Epoch [138/4000] Training [14/16] Loss: 0.02180 +Epoch [138/4000] Training [15/16] Loss: 0.02928 +Epoch [138/4000] Training [16/16] Loss: 0.04363 +Epoch [138/4000] Training metric {'Train/mean dice_metric': 0.9790784120559692, 'Train/mean miou_metric': 0.9604372978210449, 'Train/mean f1': 0.9757409691810608, 'Train/mean precision': 0.9717314839363098, 'Train/mean recall': 0.9797837138175964, 'Train/mean hd95_metric': 3.972355604171753} +Epoch [138/4000] Validation [1/4] Loss: 0.16361 focal_loss 0.09829 dice_loss 0.06532 +Epoch [138/4000] Validation [2/4] Loss: 0.19327 focal_loss 0.06175 dice_loss 0.13153 +Epoch [138/4000] Validation [3/4] Loss: 0.12791 focal_loss 0.05954 dice_loss 0.06837 +Epoch [138/4000] Validation [4/4] Loss: 0.30203 focal_loss 0.15784 dice_loss 0.14418 +Epoch [138/4000] Validation metric {'Val/mean dice_metric': 0.9544111490249634, 'Val/mean miou_metric': 0.9257510900497437, 'Val/mean f1': 0.9562222361564636, 'Val/mean precision': 0.9458327293395996, 'Val/mean recall': 0.966842532157898, 'Val/mean hd95_metric': 9.18153190612793} +Cheakpoint... +Epoch [138/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9544], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9544111490249634, 'Val/mean miou_metric': 0.9257510900497437, 'Val/mean f1': 0.9562222361564636, 'Val/mean precision': 0.9458327293395996, 'Val/mean recall': 0.966842532157898, 'Val/mean hd95_metric': 9.18153190612793} +Epoch [139/4000] Training [1/16] Loss: 0.03618 +Epoch [139/4000] Training [2/16] Loss: 0.02888 +Epoch [139/4000] Training [3/16] Loss: 0.02070 +Epoch [139/4000] Training [4/16] Loss: 0.02157 +Epoch [139/4000] Training [5/16] Loss: 0.01875 +Epoch [139/4000] Training [6/16] Loss: 0.05826 +Epoch [139/4000] Training [7/16] Loss: 0.03465 +Epoch [139/4000] Training [8/16] Loss: 0.02611 +Epoch [139/4000] Training [9/16] Loss: 0.02453 +Epoch [139/4000] Training [10/16] Loss: 0.02543 +Epoch [139/4000] Training [11/16] Loss: 0.02326 +Epoch [139/4000] Training [12/16] Loss: 0.01834 +Epoch [139/4000] Training [13/16] Loss: 0.03859 +Epoch [139/4000] Training [14/16] Loss: 0.01877 +Epoch [139/4000] Training [15/16] Loss: 0.03703 +Epoch [139/4000] Training [16/16] Loss: 0.03386 +Epoch [139/4000] Training metric {'Train/mean dice_metric': 0.9782099723815918, 'Train/mean miou_metric': 0.9583891034126282, 'Train/mean f1': 0.977230429649353, 'Train/mean precision': 0.9726914763450623, 'Train/mean recall': 0.9818120002746582, 'Train/mean hd95_metric': 5.802719593048096} +Epoch [139/4000] Validation [1/4] Loss: 0.36364 focal_loss 0.23999 dice_loss 0.12365 +Epoch [139/4000] Validation [2/4] Loss: 0.18821 focal_loss 0.06106 dice_loss 0.12715 +Epoch [139/4000] Validation [3/4] Loss: 0.19946 focal_loss 0.10478 dice_loss 0.09468 +Epoch [139/4000] Validation [4/4] Loss: 0.24528 focal_loss 0.11440 dice_loss 0.13088 +Epoch [139/4000] Validation metric {'Val/mean dice_metric': 0.9523828625679016, 'Val/mean miou_metric': 0.9215503931045532, 'Val/mean f1': 0.9557480812072754, 'Val/mean precision': 0.9597923159599304, 'Val/mean recall': 0.9517379403114319, 'Val/mean hd95_metric': 10.896087646484375} +Cheakpoint... +Epoch [139/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9524], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9523828625679016, 'Val/mean miou_metric': 0.9215503931045532, 'Val/mean f1': 0.9557480812072754, 'Val/mean precision': 0.9597923159599304, 'Val/mean recall': 0.9517379403114319, 'Val/mean hd95_metric': 10.896087646484375} +Epoch [140/4000] Training [1/16] Loss: 0.02878 +Epoch [140/4000] Training [2/16] Loss: 0.02518 +Epoch [140/4000] Training [3/16] Loss: 0.04901 +Epoch [140/4000] Training [4/16] Loss: 0.04653 +Epoch [140/4000] Training [5/16] Loss: 0.02618 +Epoch [140/4000] Training [6/16] Loss: 0.02415 +Epoch [140/4000] Training [7/16] Loss: 0.02847 +Epoch [140/4000] Training [8/16] Loss: 0.02426 +Epoch [140/4000] Training [9/16] Loss: 0.02492 +Epoch [140/4000] Training [10/16] Loss: 0.02069 +Epoch [140/4000] Training [11/16] Loss: 0.03732 +Epoch [140/4000] Training [12/16] Loss: 0.04398 +Epoch [140/4000] Training [13/16] Loss: 0.02555 +Epoch [140/4000] Training [14/16] Loss: 0.02317 +Epoch [140/4000] Training [15/16] Loss: 0.02765 +Epoch [140/4000] Training [16/16] Loss: 0.03123 +Epoch [140/4000] Training metric {'Train/mean dice_metric': 0.9773997068405151, 'Train/mean miou_metric': 0.957526445388794, 'Train/mean f1': 0.9762701392173767, 'Train/mean precision': 0.970499575138092, 'Train/mean recall': 0.982109785079956, 'Train/mean hd95_metric': 4.362349510192871} +Epoch [140/4000] Validation [1/4] Loss: 0.31835 focal_loss 0.21453 dice_loss 0.10382 +Epoch [140/4000] Validation [2/4] Loss: 0.14334 focal_loss 0.03823 dice_loss 0.10511 +Epoch [140/4000] Validation [3/4] Loss: 0.12422 focal_loss 0.04403 dice_loss 0.08019 +Epoch [140/4000] Validation [4/4] Loss: 0.27004 focal_loss 0.13533 dice_loss 0.13471 +Epoch [140/4000] Validation metric {'Val/mean dice_metric': 0.9557201266288757, 'Val/mean miou_metric': 0.9259958267211914, 'Val/mean f1': 0.9576781392097473, 'Val/mean precision': 0.9503321647644043, 'Val/mean recall': 0.9651384949684143, 'Val/mean hd95_metric': 9.52247142791748} +Cheakpoint... +Epoch [140/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9557], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9557201266288757, 'Val/mean miou_metric': 0.9259958267211914, 'Val/mean f1': 0.9576781392097473, 'Val/mean precision': 0.9503321647644043, 'Val/mean recall': 0.9651384949684143, 'Val/mean hd95_metric': 9.52247142791748} +Epoch [141/4000] Training [1/16] Loss: 0.02532 +Epoch [141/4000] Training [2/16] Loss: 0.02066 +Epoch [141/4000] Training [3/16] Loss: 0.02530 +Epoch [141/4000] Training [4/16] Loss: 0.02068 +Epoch [141/4000] Training [5/16] Loss: 0.02750 +Epoch [141/4000] Training [6/16] Loss: 0.02262 +Epoch [141/4000] Training [7/16] Loss: 0.07851 +Epoch [141/4000] Training [8/16] Loss: 0.02253 +Epoch [141/4000] Training [9/16] Loss: 0.02524 +Epoch [141/4000] Training [10/16] Loss: 0.02035 +Epoch [141/4000] Training [11/16] Loss: 0.02954 +Epoch [141/4000] Training [12/16] Loss: 0.06982 +Epoch [141/4000] Training [13/16] Loss: 0.01796 +Epoch [141/4000] Training [14/16] Loss: 0.03527 +Epoch [141/4000] Training [15/16] Loss: 0.02860 +Epoch [141/4000] Training [16/16] Loss: 0.02763 +Epoch [141/4000] Training metric {'Train/mean dice_metric': 0.9783139824867249, 'Train/mean miou_metric': 0.959101676940918, 'Train/mean f1': 0.9761395454406738, 'Train/mean precision': 0.9714114665985107, 'Train/mean recall': 0.9809138774871826, 'Train/mean hd95_metric': 4.995144367218018} +Epoch [141/4000] Validation [1/4] Loss: 0.52389 focal_loss 0.38855 dice_loss 0.13533 +Epoch [141/4000] Validation [2/4] Loss: 0.20070 focal_loss 0.07462 dice_loss 0.12608 +Epoch [141/4000] Validation [3/4] Loss: 0.27717 focal_loss 0.15636 dice_loss 0.12081 +Epoch [141/4000] Validation [4/4] Loss: 0.21470 focal_loss 0.07769 dice_loss 0.13700 +Epoch [141/4000] Validation metric {'Val/mean dice_metric': 0.9500858187675476, 'Val/mean miou_metric': 0.9202133417129517, 'Val/mean f1': 0.953389048576355, 'Val/mean precision': 0.9526560306549072, 'Val/mean recall': 0.9541232585906982, 'Val/mean hd95_metric': 11.27869701385498} +Cheakpoint... +Epoch [141/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9501], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9500858187675476, 'Val/mean miou_metric': 0.9202133417129517, 'Val/mean f1': 0.953389048576355, 'Val/mean precision': 0.9526560306549072, 'Val/mean recall': 0.9541232585906982, 'Val/mean hd95_metric': 11.27869701385498} +Epoch [142/4000] Training [1/16] Loss: 0.02781 +Epoch [142/4000] Training [2/16] Loss: 0.07503 +Epoch [142/4000] Training [3/16] Loss: 0.02629 +Epoch [142/4000] Training [4/16] Loss: 0.02302 +Epoch [142/4000] Training [5/16] Loss: 0.02463 +Epoch [142/4000] Training [6/16] Loss: 0.06387 +Epoch [142/4000] Training [7/16] Loss: 0.02619 +Epoch [142/4000] Training [8/16] Loss: 0.02810 +Epoch [142/4000] Training [9/16] Loss: 0.02516 +Epoch [142/4000] Training [10/16] Loss: 0.02795 +Epoch [142/4000] Training [11/16] Loss: 0.05905 +Epoch [142/4000] Training [12/16] Loss: 0.02140 +Epoch [142/4000] Training [13/16] Loss: 0.03489 +Epoch [142/4000] Training [14/16] Loss: 0.02415 +Epoch [142/4000] Training [15/16] Loss: 0.02696 +Epoch [142/4000] Training [16/16] Loss: 0.05688 +Epoch [142/4000] Training metric {'Train/mean dice_metric': 0.9743517637252808, 'Train/mean miou_metric': 0.9525347352027893, 'Train/mean f1': 0.9729161858558655, 'Train/mean precision': 0.9688262343406677, 'Train/mean recall': 0.9770408272743225, 'Train/mean hd95_metric': 6.434340476989746} +Epoch [142/4000] Validation [1/4] Loss: 0.17128 focal_loss 0.07835 dice_loss 0.09292 +Epoch [142/4000] Validation [2/4] Loss: 0.30445 focal_loss 0.07660 dice_loss 0.22785 +Epoch [142/4000] Validation [3/4] Loss: 0.31998 focal_loss 0.18462 dice_loss 0.13536 +Epoch [142/4000] Validation [4/4] Loss: 0.17209 focal_loss 0.07826 dice_loss 0.09384 +Epoch [142/4000] Validation metric {'Val/mean dice_metric': 0.9447851181030273, 'Val/mean miou_metric': 0.9127610921859741, 'Val/mean f1': 0.9514011144638062, 'Val/mean precision': 0.949020504951477, 'Val/mean recall': 0.9537936449050903, 'Val/mean hd95_metric': 12.080351829528809} +Cheakpoint... +Epoch [142/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9448], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9447851181030273, 'Val/mean miou_metric': 0.9127610921859741, 'Val/mean f1': 0.9514011144638062, 'Val/mean precision': 0.949020504951477, 'Val/mean recall': 0.9537936449050903, 'Val/mean hd95_metric': 12.080351829528809} +Epoch [143/4000] Training [1/16] Loss: 0.06357 +Epoch [143/4000] Training [2/16] Loss: 0.05237 +Epoch [143/4000] Training [3/16] Loss: 0.03073 +Epoch [143/4000] Training [4/16] Loss: 0.02953 +Epoch [143/4000] Training [5/16] Loss: 0.03438 +Epoch [143/4000] Training [6/16] Loss: 0.02347 +Epoch [143/4000] Training [7/16] Loss: 0.03214 +Epoch [143/4000] Training [8/16] Loss: 0.04553 +Epoch [143/4000] Training [9/16] Loss: 0.03111 +Epoch [143/4000] Training [10/16] Loss: 0.02499 +Epoch [143/4000] Training [11/16] Loss: 0.02277 +Epoch [143/4000] Training [12/16] Loss: 0.02059 +Epoch [143/4000] Training [13/16] Loss: 0.02387 +Epoch [143/4000] Training [14/16] Loss: 0.02886 +Epoch [143/4000] Training [15/16] Loss: 0.02794 +Epoch [143/4000] Training [16/16] Loss: 0.03644 +Epoch [143/4000] Training metric {'Train/mean dice_metric': 0.9762193560600281, 'Train/mean miou_metric': 0.9552410840988159, 'Train/mean f1': 0.9746979475021362, 'Train/mean precision': 0.971242368221283, 'Train/mean recall': 0.9781781435012817, 'Train/mean hd95_metric': 5.056026458740234} +Epoch [143/4000] Validation [1/4] Loss: 0.13401 focal_loss 0.08030 dice_loss 0.05370 +Epoch [143/4000] Validation [2/4] Loss: 0.20486 focal_loss 0.06617 dice_loss 0.13869 +Epoch [143/4000] Validation [3/4] Loss: 0.22223 focal_loss 0.10384 dice_loss 0.11838 +Epoch [143/4000] Validation [4/4] Loss: 0.30446 focal_loss 0.15482 dice_loss 0.14964 +Epoch [143/4000] Validation metric {'Val/mean dice_metric': 0.9524528384208679, 'Val/mean miou_metric': 0.9210073351860046, 'Val/mean f1': 0.9559807777404785, 'Val/mean precision': 0.9552928805351257, 'Val/mean recall': 0.9566694498062134, 'Val/mean hd95_metric': 9.475091934204102} +Cheakpoint... +Epoch [143/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9525], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9524528384208679, 'Val/mean miou_metric': 0.9210073351860046, 'Val/mean f1': 0.9559807777404785, 'Val/mean precision': 0.9552928805351257, 'Val/mean recall': 0.9566694498062134, 'Val/mean hd95_metric': 9.475091934204102} +Epoch [144/4000] Training [1/16] Loss: 0.02186 +Epoch [144/4000] Training [2/16] Loss: 0.03008 +Epoch [144/4000] Training [3/16] Loss: 0.03077 +Epoch [144/4000] Training [4/16] Loss: 0.02655 +Epoch [144/4000] Training [5/16] Loss: 0.03601 +Epoch [144/4000] Training [6/16] Loss: 0.02534 +Epoch [144/4000] Training [7/16] Loss: 0.02270 +Epoch [144/4000] Training [8/16] Loss: 0.02712 +Epoch [144/4000] Training [9/16] Loss: 0.03728 +Epoch [144/4000] Training [10/16] Loss: 0.02092 +Epoch [144/4000] Training [11/16] Loss: 0.02379 +Epoch [144/4000] Training [12/16] Loss: 0.02941 +Epoch [144/4000] Training [13/16] Loss: 0.02899 +Epoch [144/4000] Training [14/16] Loss: 0.02172 +Epoch [144/4000] Training [15/16] Loss: 0.03696 +Epoch [144/4000] Training [16/16] Loss: 0.06710 +Epoch [144/4000] Training metric {'Train/mean dice_metric': 0.9794214367866516, 'Train/mean miou_metric': 0.9600366353988647, 'Train/mean f1': 0.9770004749298096, 'Train/mean precision': 0.9729581475257874, 'Train/mean recall': 0.9810765385627747, 'Train/mean hd95_metric': 4.382894515991211} +Epoch [144/4000] Validation [1/4] Loss: 0.23256 focal_loss 0.14526 dice_loss 0.08730 +Epoch [144/4000] Validation [2/4] Loss: 0.23822 focal_loss 0.07489 dice_loss 0.16333 +Epoch [144/4000] Validation [3/4] Loss: 0.22530 focal_loss 0.11443 dice_loss 0.11087 +Epoch [144/4000] Validation [4/4] Loss: 0.14522 focal_loss 0.06154 dice_loss 0.08368 +Epoch [144/4000] Validation metric {'Val/mean dice_metric': 0.9562274813652039, 'Val/mean miou_metric': 0.9266525506973267, 'Val/mean f1': 0.9578224420547485, 'Val/mean precision': 0.9548316597938538, 'Val/mean recall': 0.9608321189880371, 'Val/mean hd95_metric': 9.744314193725586} +Cheakpoint... +Epoch [144/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9562], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9562274813652039, 'Val/mean miou_metric': 0.9266525506973267, 'Val/mean f1': 0.9578224420547485, 'Val/mean precision': 0.9548316597938538, 'Val/mean recall': 0.9608321189880371, 'Val/mean hd95_metric': 9.744314193725586} +Epoch [145/4000] Training [1/16] Loss: 0.03191 +Epoch [145/4000] Training [2/16] Loss: 0.02125 +Epoch [145/4000] Training [3/16] Loss: 0.02442 +Epoch [145/4000] Training [4/16] Loss: 0.02689 +Epoch [145/4000] Training [5/16] Loss: 0.06609 +Epoch [145/4000] Training [6/16] Loss: 0.02680 +Epoch [145/4000] Training [7/16] Loss: 0.01973 +Epoch [145/4000] Training [8/16] Loss: 0.05110 +Epoch [145/4000] Training [9/16] Loss: 0.02616 +Epoch [145/4000] Training [10/16] Loss: 0.03069 +Epoch [145/4000] Training [11/16] Loss: 0.03281 +Epoch [145/4000] Training [12/16] Loss: 0.02776 +Epoch [145/4000] Training [13/16] Loss: 0.02316 +Epoch [145/4000] Training [14/16] Loss: 0.02555 +Epoch [145/4000] Training [15/16] Loss: 0.02779 +Epoch [145/4000] Training [16/16] Loss: 0.02758 +Epoch [145/4000] Training metric {'Train/mean dice_metric': 0.9810901880264282, 'Train/mean miou_metric': 0.9631972312927246, 'Train/mean f1': 0.9792596101760864, 'Train/mean precision': 0.9753628373146057, 'Train/mean recall': 0.9831876754760742, 'Train/mean hd95_metric': 3.3710339069366455} +Epoch [145/4000] Validation [1/4] Loss: 0.35681 focal_loss 0.22895 dice_loss 0.12786 +Epoch [145/4000] Validation [2/4] Loss: 0.22589 focal_loss 0.07662 dice_loss 0.14927 +Epoch [145/4000] Validation [3/4] Loss: 0.12251 focal_loss 0.04482 dice_loss 0.07769 +Epoch [145/4000] Validation [4/4] Loss: 0.29821 focal_loss 0.15609 dice_loss 0.14212 +Epoch [145/4000] Validation metric {'Val/mean dice_metric': 0.9584842920303345, 'Val/mean miou_metric': 0.9303245544433594, 'Val/mean f1': 0.9594516754150391, 'Val/mean precision': 0.9590731859207153, 'Val/mean recall': 0.9598305225372314, 'Val/mean hd95_metric': 7.895157814025879} +Cheakpoint... +Epoch [145/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9585], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9584842920303345, 'Val/mean miou_metric': 0.9303245544433594, 'Val/mean f1': 0.9594516754150391, 'Val/mean precision': 0.9590731859207153, 'Val/mean recall': 0.9598305225372314, 'Val/mean hd95_metric': 7.895157814025879} +Epoch [146/4000] Training [1/16] Loss: 0.04193 +Epoch [146/4000] Training [2/16] Loss: 0.02981 +Epoch [146/4000] Training [3/16] Loss: 0.02479 +Epoch [146/4000] Training [4/16] Loss: 0.02555 +Epoch [146/4000] Training [5/16] Loss: 0.02466 +Epoch [146/4000] Training [6/16] Loss: 0.02137 +Epoch [146/4000] Training [7/16] Loss: 0.01958 +Epoch [146/4000] Training [8/16] Loss: 0.03540 +Epoch [146/4000] Training [9/16] Loss: 0.02363 +Epoch [146/4000] Training [10/16] Loss: 0.01905 +Epoch [146/4000] Training [11/16] Loss: 0.02475 +Epoch [146/4000] Training [12/16] Loss: 0.02560 +Epoch [146/4000] Training [13/16] Loss: 0.05359 +Epoch [146/4000] Training [14/16] Loss: 0.01591 +Epoch [146/4000] Training [15/16] Loss: 0.02386 +Epoch [146/4000] Training [16/16] Loss: 0.01650 +Epoch [146/4000] Training metric {'Train/mean dice_metric': 0.9816547632217407, 'Train/mean miou_metric': 0.9646483659744263, 'Train/mean f1': 0.980222761631012, 'Train/mean precision': 0.9744150638580322, 'Train/mean recall': 0.9861000776290894, 'Train/mean hd95_metric': 3.5441319942474365} +Epoch [146/4000] Validation [1/4] Loss: 0.15762 focal_loss 0.08346 dice_loss 0.07415 +Epoch [146/4000] Validation [2/4] Loss: 0.15698 focal_loss 0.05123 dice_loss 0.10575 +Epoch [146/4000] Validation [3/4] Loss: 0.10416 focal_loss 0.04053 dice_loss 0.06363 +Epoch [146/4000] Validation [4/4] Loss: 0.25087 focal_loss 0.11071 dice_loss 0.14016 +Epoch [146/4000] Validation metric {'Val/mean dice_metric': 0.9596338272094727, 'Val/mean miou_metric': 0.9321132898330688, 'Val/mean f1': 0.9620630741119385, 'Val/mean precision': 0.9559749364852905, 'Val/mean recall': 0.9682292938232422, 'Val/mean hd95_metric': 7.950979709625244} +Cheakpoint... +Epoch [146/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9596], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9596338272094727, 'Val/mean miou_metric': 0.9321132898330688, 'Val/mean f1': 0.9620630741119385, 'Val/mean precision': 0.9559749364852905, 'Val/mean recall': 0.9682292938232422, 'Val/mean hd95_metric': 7.950979709625244} +Epoch [147/4000] Training [1/16] Loss: 0.02435 +Epoch [147/4000] Training [2/16] Loss: 0.01980 +Epoch [147/4000] Training [3/16] Loss: 0.03676 +Epoch [147/4000] Training [4/16] Loss: 0.02106 +Epoch [147/4000] Training [5/16] Loss: 0.02074 +Epoch [147/4000] Training [6/16] Loss: 0.01816 +Epoch [147/4000] Training [7/16] Loss: 0.15910 +Epoch [147/4000] Training [8/16] Loss: 0.02514 +Epoch [147/4000] Training [9/16] Loss: 0.02195 +Epoch [147/4000] Training [10/16] Loss: 0.02020 +Epoch [147/4000] Training [11/16] Loss: 0.02110 +Epoch [147/4000] Training [12/16] Loss: 0.01702 +Epoch [147/4000] Training [13/16] Loss: 0.02735 +Epoch [147/4000] Training [14/16] Loss: 0.02407 +Epoch [147/4000] Training [15/16] Loss: 0.02202 +Epoch [147/4000] Training [16/16] Loss: 0.02755 +Epoch [147/4000] Training metric {'Train/mean dice_metric': 0.9793567061424255, 'Train/mean miou_metric': 0.9622451066970825, 'Train/mean f1': 0.9798687696456909, 'Train/mean precision': 0.975174069404602, 'Train/mean recall': 0.9846088886260986, 'Train/mean hd95_metric': 2.984635353088379} +Epoch [147/4000] Validation [1/4] Loss: 0.39158 focal_loss 0.25048 dice_loss 0.14111 +Epoch [147/4000] Validation [2/4] Loss: 0.43135 focal_loss 0.22427 dice_loss 0.20708 +Epoch [147/4000] Validation [3/4] Loss: 0.23001 focal_loss 0.12490 dice_loss 0.10510 +Epoch [147/4000] Validation [4/4] Loss: 0.26082 focal_loss 0.12287 dice_loss 0.13795 +Epoch [147/4000] Validation metric {'Val/mean dice_metric': 0.9520052075386047, 'Val/mean miou_metric': 0.9226815104484558, 'Val/mean f1': 0.9554781317710876, 'Val/mean precision': 0.9608737230300903, 'Val/mean recall': 0.9501428008079529, 'Val/mean hd95_metric': 7.977496147155762} +Cheakpoint... +Epoch [147/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9520], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9520052075386047, 'Val/mean miou_metric': 0.9226815104484558, 'Val/mean f1': 0.9554781317710876, 'Val/mean precision': 0.9608737230300903, 'Val/mean recall': 0.9501428008079529, 'Val/mean hd95_metric': 7.977496147155762} +Epoch [148/4000] Training [1/16] Loss: 0.02415 +Epoch [148/4000] Training [2/16] Loss: 0.02013 +Epoch [148/4000] Training [3/16] Loss: 0.02312 +Epoch [148/4000] Training [4/16] Loss: 0.02383 +Epoch [148/4000] Training [5/16] Loss: 0.02798 +Epoch [148/4000] Training [6/16] Loss: 0.04242 +Epoch [148/4000] Training [7/16] Loss: 0.05547 +Epoch [148/4000] Training [8/16] Loss: 0.05915 +Epoch [148/4000] Training [9/16] Loss: 0.02065 +Epoch [148/4000] Training [10/16] Loss: 0.03117 +Epoch [148/4000] Training [11/16] Loss: 0.02321 +Epoch [148/4000] Training [12/16] Loss: 0.01581 +Epoch [148/4000] Training [13/16] Loss: 0.02509 +Epoch [148/4000] Training [14/16] Loss: 0.02362 +Epoch [148/4000] Training [15/16] Loss: 0.01977 +Epoch [148/4000] Training [16/16] Loss: 0.06786 +Epoch [148/4000] Training metric {'Train/mean dice_metric': 0.9818498492240906, 'Train/mean miou_metric': 0.9646010994911194, 'Train/mean f1': 0.9802260398864746, 'Train/mean precision': 0.9761433005332947, 'Train/mean recall': 0.9843430519104004, 'Train/mean hd95_metric': 2.957089900970459} +Epoch [148/4000] Validation [1/4] Loss: 0.16871 focal_loss 0.09892 dice_loss 0.06979 +Epoch [148/4000] Validation [2/4] Loss: 0.14529 focal_loss 0.04963 dice_loss 0.09566 +Epoch [148/4000] Validation [3/4] Loss: 0.23525 focal_loss 0.13961 dice_loss 0.09564 +Epoch [148/4000] Validation [4/4] Loss: 0.20364 focal_loss 0.08561 dice_loss 0.11802 +Epoch [148/4000] Validation metric {'Val/mean dice_metric': 0.9614771604537964, 'Val/mean miou_metric': 0.9343312978744507, 'Val/mean f1': 0.9654525518417358, 'Val/mean precision': 0.9622522592544556, 'Val/mean recall': 0.9686743021011353, 'Val/mean hd95_metric': 7.004712104797363} +Cheakpoint... +Epoch [148/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9615], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614771604537964, 'Val/mean miou_metric': 0.9343312978744507, 'Val/mean f1': 0.9654525518417358, 'Val/mean precision': 0.9622522592544556, 'Val/mean recall': 0.9686743021011353, 'Val/mean hd95_metric': 7.004712104797363} +Epoch [149/4000] Training [1/16] Loss: 0.02451 +Epoch [149/4000] Training [2/16] Loss: 0.02441 +Epoch [149/4000] Training [3/16] Loss: 0.01740 +Epoch [149/4000] Training [4/16] Loss: 0.04431 +Epoch [149/4000] Training [5/16] Loss: 0.02483 +Epoch [149/4000] Training [6/16] Loss: 0.02373 +Epoch [149/4000] Training [7/16] Loss: 0.02710 +Epoch [149/4000] Training [8/16] Loss: 0.02601 +Epoch [149/4000] Training [9/16] Loss: 0.02313 +Epoch [149/4000] Training [10/16] Loss: 0.02101 +Epoch [149/4000] Training [11/16] Loss: 0.02587 +Epoch [149/4000] Training [12/16] Loss: 0.02267 +Epoch [149/4000] Training [13/16] Loss: 0.03157 +Epoch [149/4000] Training [14/16] Loss: 0.01935 +Epoch [149/4000] Training [15/16] Loss: 0.01919 +Epoch [149/4000] Training [16/16] Loss: 0.05780 +Epoch [149/4000] Training metric {'Train/mean dice_metric': 0.9815760850906372, 'Train/mean miou_metric': 0.9643514752388, 'Train/mean f1': 0.9800577759742737, 'Train/mean precision': 0.9755520224571228, 'Train/mean recall': 0.9846053123474121, 'Train/mean hd95_metric': 3.698878765106201} +Epoch [149/4000] Validation [1/4] Loss: 0.62683 focal_loss 0.48608 dice_loss 0.14075 +Epoch [149/4000] Validation [2/4] Loss: 0.14763 focal_loss 0.04739 dice_loss 0.10024 +Epoch [149/4000] Validation [3/4] Loss: 0.11230 focal_loss 0.04890 dice_loss 0.06341 +Epoch [149/4000] Validation [4/4] Loss: 0.27356 focal_loss 0.13993 dice_loss 0.13363 +Epoch [149/4000] Validation metric {'Val/mean dice_metric': 0.9602462649345398, 'Val/mean miou_metric': 0.9329751133918762, 'Val/mean f1': 0.9636667370796204, 'Val/mean precision': 0.9644966721534729, 'Val/mean recall': 0.962838351726532, 'Val/mean hd95_metric': 7.559104919433594} +Cheakpoint... +Epoch [149/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9602], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9602462649345398, 'Val/mean miou_metric': 0.9329751133918762, 'Val/mean f1': 0.9636667370796204, 'Val/mean precision': 0.9644966721534729, 'Val/mean recall': 0.962838351726532, 'Val/mean hd95_metric': 7.559104919433594} +Epoch [150/4000] Training [1/16] Loss: 0.02061 +Epoch [150/4000] Training [2/16] Loss: 0.02829 +Epoch [150/4000] Training [3/16] Loss: 0.01618 +Epoch [150/4000] Training [4/16] Loss: 0.02271 +Epoch [150/4000] Training [5/16] Loss: 0.01952 +Epoch [150/4000] Training [6/16] Loss: 0.02379 +Epoch [150/4000] Training [7/16] Loss: 0.07056 +Epoch [150/4000] Training [8/16] Loss: 0.02003 +Epoch [150/4000] Training [9/16] Loss: 0.01750 +Epoch [150/4000] Training [10/16] Loss: 0.01693 +Epoch [150/4000] Training [11/16] Loss: 0.02060 +Epoch [150/4000] Training [12/16] Loss: 0.02107 +Epoch [150/4000] Training [13/16] Loss: 0.01901 +Epoch [150/4000] Training [14/16] Loss: 0.04120 +Epoch [150/4000] Training [15/16] Loss: 0.04338 +Epoch [150/4000] Training [16/16] Loss: 0.02675 +Epoch [150/4000] Training metric {'Train/mean dice_metric': 0.9822307229042053, 'Train/mean miou_metric': 0.9661580920219421, 'Train/mean f1': 0.9808902740478516, 'Train/mean precision': 0.97699373960495, 'Train/mean recall': 0.9848179817199707, 'Train/mean hd95_metric': 2.6903553009033203} +Epoch [150/4000] Validation [1/4] Loss: 0.29220 focal_loss 0.19031 dice_loss 0.10189 +Epoch [150/4000] Validation [2/4] Loss: 0.18379 focal_loss 0.08797 dice_loss 0.09582 +Epoch [150/4000] Validation [3/4] Loss: 0.15137 focal_loss 0.06652 dice_loss 0.08485 +Epoch [150/4000] Validation [4/4] Loss: 0.22543 focal_loss 0.09925 dice_loss 0.12618 +Epoch [150/4000] Validation metric {'Val/mean dice_metric': 0.9629852175712585, 'Val/mean miou_metric': 0.9363285303115845, 'Val/mean f1': 0.9638767838478088, 'Val/mean precision': 0.9593091011047363, 'Val/mean recall': 0.9684880375862122, 'Val/mean hd95_metric': 7.957123756408691} +Cheakpoint... +Epoch [150/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629852175712585, 'Val/mean miou_metric': 0.9363285303115845, 'Val/mean f1': 0.9638767838478088, 'Val/mean precision': 0.9593091011047363, 'Val/mean recall': 0.9684880375862122, 'Val/mean hd95_metric': 7.957123756408691} +Epoch [151/4000] Training [1/16] Loss: 0.02572 +Epoch [151/4000] Training [2/16] Loss: 0.02152 +Epoch [151/4000] Training [3/16] Loss: 0.02031 +Epoch [151/4000] Training [4/16] Loss: 0.02044 +Epoch [151/4000] Training [5/16] Loss: 0.02019 +Epoch [151/4000] Training [6/16] Loss: 0.02586 +Epoch [151/4000] Training [7/16] Loss: 0.02185 +Epoch [151/4000] Training [8/16] Loss: 0.02695 +Epoch [151/4000] Training [9/16] Loss: 0.02211 +Epoch [151/4000] Training [10/16] Loss: 0.02953 +Epoch [151/4000] Training [11/16] Loss: 0.03391 +Epoch [151/4000] Training [12/16] Loss: 0.02446 +Epoch [151/4000] Training [13/16] Loss: 0.04790 +Epoch [151/4000] Training [14/16] Loss: 0.02370 +Epoch [151/4000] Training [15/16] Loss: 0.02298 +Epoch [151/4000] Training [16/16] Loss: 0.02356 +Epoch [151/4000] Training metric {'Train/mean dice_metric': 0.9822921752929688, 'Train/mean miou_metric': 0.9652975797653198, 'Train/mean f1': 0.9795607924461365, 'Train/mean precision': 0.9753482937812805, 'Train/mean recall': 0.9838098287582397, 'Train/mean hd95_metric': 4.426031112670898} +Epoch [151/4000] Validation [1/4] Loss: 0.48386 focal_loss 0.33946 dice_loss 0.14440 +Epoch [151/4000] Validation [2/4] Loss: 0.15559 focal_loss 0.05225 dice_loss 0.10335 +Epoch [151/4000] Validation [3/4] Loss: 0.27061 focal_loss 0.16319 dice_loss 0.10742 +Epoch [151/4000] Validation [4/4] Loss: 0.18068 focal_loss 0.07405 dice_loss 0.10663 +Epoch [151/4000] Validation metric {'Val/mean dice_metric': 0.9592727422714233, 'Val/mean miou_metric': 0.9318659901618958, 'Val/mean f1': 0.9595747590065002, 'Val/mean precision': 0.9575494527816772, 'Val/mean recall': 0.9616085886955261, 'Val/mean hd95_metric': 8.859346389770508} +Cheakpoint... +Epoch [151/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9592727422714233, 'Val/mean miou_metric': 0.9318659901618958, 'Val/mean f1': 0.9595747590065002, 'Val/mean precision': 0.9575494527816772, 'Val/mean recall': 0.9616085886955261, 'Val/mean hd95_metric': 8.859346389770508} +Epoch [152/4000] Training [1/16] Loss: 0.03145 +Epoch [152/4000] Training [2/16] Loss: 0.02958 +Epoch [152/4000] Training [3/16] Loss: 0.03957 +Epoch [152/4000] Training [4/16] Loss: 0.02410 +Epoch [152/4000] Training [5/16] Loss: 0.02526 +Epoch [152/4000] Training [6/16] Loss: 0.02383 +Epoch [152/4000] Training [7/16] Loss: 0.01759 +Epoch [152/4000] Training [8/16] Loss: 0.02258 +Epoch [152/4000] Training [9/16] Loss: 0.02374 +Epoch [152/4000] Training [10/16] Loss: 0.03212 +Epoch [152/4000] Training [11/16] Loss: 0.02045 +Epoch [152/4000] Training [12/16] Loss: 0.02666 +Epoch [152/4000] Training [13/16] Loss: 0.01814 +Epoch [152/4000] Training [14/16] Loss: 0.02380 +Epoch [152/4000] Training [15/16] Loss: 0.05334 +Epoch [152/4000] Training [16/16] Loss: 0.02515 +Epoch [152/4000] Training metric {'Train/mean dice_metric': 0.9819416403770447, 'Train/mean miou_metric': 0.9648076891899109, 'Train/mean f1': 0.9802258014678955, 'Train/mean precision': 0.9758498072624207, 'Train/mean recall': 0.9846412539482117, 'Train/mean hd95_metric': 3.080467939376831} +Epoch [152/4000] Validation [1/4] Loss: 0.43139 focal_loss 0.28119 dice_loss 0.15020 +Epoch [152/4000] Validation [2/4] Loss: 0.19312 focal_loss 0.07044 dice_loss 0.12268 +Epoch [152/4000] Validation [3/4] Loss: 0.14066 focal_loss 0.05100 dice_loss 0.08965 +Epoch [152/4000] Validation [4/4] Loss: 0.24589 focal_loss 0.10478 dice_loss 0.14111 +Epoch [152/4000] Validation metric {'Val/mean dice_metric': 0.9573076963424683, 'Val/mean miou_metric': 0.9296701550483704, 'Val/mean f1': 0.9611960053443909, 'Val/mean precision': 0.9572005271911621, 'Val/mean recall': 0.9652249217033386, 'Val/mean hd95_metric': 8.093111038208008} +Cheakpoint... +Epoch [152/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9573], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573076963424683, 'Val/mean miou_metric': 0.9296701550483704, 'Val/mean f1': 0.9611960053443909, 'Val/mean precision': 0.9572005271911621, 'Val/mean recall': 0.9652249217033386, 'Val/mean hd95_metric': 8.093111038208008} +Epoch [153/4000] Training [1/16] Loss: 0.04819 +Epoch [153/4000] Training [2/16] Loss: 0.02455 +Epoch [153/4000] Training [3/16] Loss: 0.02788 +Epoch [153/4000] Training [4/16] Loss: 0.03598 +Epoch [153/4000] Training [5/16] Loss: 0.01904 +Epoch [153/4000] Training [6/16] Loss: 0.02967 +Epoch [153/4000] Training [7/16] Loss: 0.02642 +Epoch [153/4000] Training [8/16] Loss: 0.04672 +Epoch [153/4000] Training [9/16] Loss: 0.04890 +Epoch [153/4000] Training [10/16] Loss: 0.01922 +Epoch [153/4000] Training [11/16] Loss: 0.02641 +Epoch [153/4000] Training [12/16] Loss: 0.03821 +Epoch [153/4000] Training [13/16] Loss: 0.02034 +Epoch [153/4000] Training [14/16] Loss: 0.02185 +Epoch [153/4000] Training [15/16] Loss: 0.02079 +Epoch [153/4000] Training [16/16] Loss: 0.02488 +Epoch [153/4000] Training metric {'Train/mean dice_metric': 0.9814881086349487, 'Train/mean miou_metric': 0.9639427661895752, 'Train/mean f1': 0.9798488020896912, 'Train/mean precision': 0.9760319590568542, 'Train/mean recall': 0.9836956858634949, 'Train/mean hd95_metric': 3.1472513675689697} +Epoch [153/4000] Validation [1/4] Loss: 0.20773 focal_loss 0.12612 dice_loss 0.08161 +Epoch [153/4000] Validation [2/4] Loss: 0.30168 focal_loss 0.13506 dice_loss 0.16662 +Epoch [153/4000] Validation [3/4] Loss: 0.29580 focal_loss 0.17151 dice_loss 0.12429 +Epoch [153/4000] Validation [4/4] Loss: 0.22825 focal_loss 0.10098 dice_loss 0.12727 +Epoch [153/4000] Validation metric {'Val/mean dice_metric': 0.9570951461791992, 'Val/mean miou_metric': 0.9289901852607727, 'Val/mean f1': 0.9595723152160645, 'Val/mean precision': 0.9584699273109436, 'Val/mean recall': 0.9606772661209106, 'Val/mean hd95_metric': 8.146467208862305} +Cheakpoint... +Epoch [153/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9571], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9570951461791992, 'Val/mean miou_metric': 0.9289901852607727, 'Val/mean f1': 0.9595723152160645, 'Val/mean precision': 0.9584699273109436, 'Val/mean recall': 0.9606772661209106, 'Val/mean hd95_metric': 8.146467208862305} +Epoch [154/4000] Training [1/16] Loss: 0.02048 +Epoch [154/4000] Training [2/16] Loss: 0.02188 +Epoch [154/4000] Training [3/16] Loss: 0.01629 +Epoch [154/4000] Training [4/16] Loss: 0.02117 +Epoch [154/4000] Training [5/16] Loss: 0.02602 +Epoch [154/4000] Training [6/16] Loss: 0.03941 +Epoch [154/4000] Training [7/16] Loss: 0.02255 +Epoch [154/4000] Training [8/16] Loss: 0.02306 +Epoch [154/4000] Training [9/16] Loss: 0.02771 +Epoch [154/4000] Training [10/16] Loss: 0.01761 +Epoch [154/4000] Training [11/16] Loss: 0.02926 +Epoch [154/4000] Training [12/16] Loss: 0.02937 +Epoch [154/4000] Training [13/16] Loss: 0.03053 +Epoch [154/4000] Training [14/16] Loss: 0.02958 +Epoch [154/4000] Training [15/16] Loss: 0.02298 +Epoch [154/4000] Training [16/16] Loss: 0.02374 +Epoch [154/4000] Training metric {'Train/mean dice_metric': 0.982900857925415, 'Train/mean miou_metric': 0.9665273427963257, 'Train/mean f1': 0.9811162948608398, 'Train/mean precision': 0.9771580100059509, 'Train/mean recall': 0.9851067662239075, 'Train/mean hd95_metric': 3.028081178665161} +Epoch [154/4000] Validation [1/4] Loss: 0.14816 focal_loss 0.08089 dice_loss 0.06727 +Epoch [154/4000] Validation [2/4] Loss: 0.29360 focal_loss 0.09602 dice_loss 0.19758 +Epoch [154/4000] Validation [3/4] Loss: 0.30692 focal_loss 0.17776 dice_loss 0.12916 +Epoch [154/4000] Validation [4/4] Loss: 0.29916 focal_loss 0.15089 dice_loss 0.14827 +Epoch [154/4000] Validation metric {'Val/mean dice_metric': 0.9598568081855774, 'Val/mean miou_metric': 0.9330509305000305, 'Val/mean f1': 0.9614832401275635, 'Val/mean precision': 0.9495323896408081, 'Val/mean recall': 0.9737387895584106, 'Val/mean hd95_metric': 8.087137222290039} +Cheakpoint... +Epoch [154/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9598568081855774, 'Val/mean miou_metric': 0.9330509305000305, 'Val/mean f1': 0.9614832401275635, 'Val/mean precision': 0.9495323896408081, 'Val/mean recall': 0.9737387895584106, 'Val/mean hd95_metric': 8.087137222290039} +Epoch [155/4000] Training [1/16] Loss: 0.01683 +Epoch [155/4000] Training [2/16] Loss: 0.03022 +Epoch [155/4000] Training [3/16] Loss: 0.01981 +Epoch [155/4000] Training [4/16] Loss: 0.01938 +Epoch [155/4000] Training [5/16] Loss: 0.03058 +Epoch [155/4000] Training [6/16] Loss: 0.01842 +Epoch [155/4000] Training [7/16] Loss: 0.01855 +Epoch [155/4000] Training [8/16] Loss: 0.03311 +Epoch [155/4000] Training [9/16] Loss: 0.02771 +Epoch [155/4000] Training [10/16] Loss: 0.02140 +Epoch [155/4000] Training [11/16] Loss: 0.02214 +Epoch [155/4000] Training [12/16] Loss: 0.03073 +Epoch [155/4000] Training [13/16] Loss: 0.01595 +Epoch [155/4000] Training [14/16] Loss: 0.02820 +Epoch [155/4000] Training [15/16] Loss: 0.02656 +Epoch [155/4000] Training [16/16] Loss: 0.01791 +Epoch [155/4000] Training metric {'Train/mean dice_metric': 0.9847848415374756, 'Train/mean miou_metric': 0.9698963165283203, 'Train/mean f1': 0.9815139770507812, 'Train/mean precision': 0.9762916564941406, 'Train/mean recall': 0.9867924451828003, 'Train/mean hd95_metric': 2.3264238834381104} +Epoch [155/4000] Validation [1/4] Loss: 0.12892 focal_loss 0.06561 dice_loss 0.06331 +Epoch [155/4000] Validation [2/4] Loss: 0.21426 focal_loss 0.07358 dice_loss 0.14068 +Epoch [155/4000] Validation [3/4] Loss: 0.33506 focal_loss 0.19589 dice_loss 0.13917 +Epoch [155/4000] Validation [4/4] Loss: 0.25145 focal_loss 0.13379 dice_loss 0.11766 +Epoch [155/4000] Validation metric {'Val/mean dice_metric': 0.9585941433906555, 'Val/mean miou_metric': 0.9327122569084167, 'Val/mean f1': 0.9597938060760498, 'Val/mean precision': 0.9488689303398132, 'Val/mean recall': 0.9709731936454773, 'Val/mean hd95_metric': 8.890329360961914} +Cheakpoint... +Epoch [155/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9586], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9585941433906555, 'Val/mean miou_metric': 0.9327122569084167, 'Val/mean f1': 0.9597938060760498, 'Val/mean precision': 0.9488689303398132, 'Val/mean recall': 0.9709731936454773, 'Val/mean hd95_metric': 8.890329360961914} +Epoch [156/4000] Training [1/16] Loss: 0.01751 +Epoch [156/4000] Training [2/16] Loss: 0.01957 +Epoch [156/4000] Training [3/16] Loss: 0.02104 +Epoch [156/4000] Training [4/16] Loss: 0.02135 +Epoch [156/4000] Training [5/16] Loss: 0.02175 +Epoch [156/4000] Training [6/16] Loss: 0.01972 +Epoch [156/4000] Training [7/16] Loss: 0.02309 +Epoch [156/4000] Training [8/16] Loss: 0.02389 +Epoch [156/4000] Training [9/16] Loss: 0.02194 +Epoch [156/4000] Training [10/16] Loss: 0.01801 +Epoch [156/4000] Training [11/16] Loss: 0.03201 +Epoch [156/4000] Training [12/16] Loss: 0.02363 +Epoch [156/4000] Training [13/16] Loss: 0.02376 +Epoch [156/4000] Training [14/16] Loss: 0.02457 +Epoch [156/4000] Training [15/16] Loss: 0.02626 +Epoch [156/4000] Training [16/16] Loss: 0.07729 +Epoch [156/4000] Training metric {'Train/mean dice_metric': 0.9805525541305542, 'Train/mean miou_metric': 0.9631929397583008, 'Train/mean f1': 0.9792818427085876, 'Train/mean precision': 0.9744253158569336, 'Train/mean recall': 0.9841870665550232, 'Train/mean hd95_metric': 4.160192966461182} +Epoch [156/4000] Validation [1/4] Loss: 0.10686 focal_loss 0.04950 dice_loss 0.05736 +Epoch [156/4000] Validation [2/4] Loss: 0.29052 focal_loss 0.09013 dice_loss 0.20039 +Epoch [156/4000] Validation [3/4] Loss: 0.41154 focal_loss 0.20902 dice_loss 0.20252 +Epoch [156/4000] Validation [4/4] Loss: 0.25259 focal_loss 0.09586 dice_loss 0.15673 +Epoch [156/4000] Validation metric {'Val/mean dice_metric': 0.9572461843490601, 'Val/mean miou_metric': 0.9296815991401672, 'Val/mean f1': 0.9620190858840942, 'Val/mean precision': 0.9575974345207214, 'Val/mean recall': 0.9664816856384277, 'Val/mean hd95_metric': 8.526182174682617} +Cheakpoint... +Epoch [156/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9572], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9572461843490601, 'Val/mean miou_metric': 0.9296815991401672, 'Val/mean f1': 0.9620190858840942, 'Val/mean precision': 0.9575974345207214, 'Val/mean recall': 0.9664816856384277, 'Val/mean hd95_metric': 8.526182174682617} +Epoch [157/4000] Training [1/16] Loss: 0.02093 +Epoch [157/4000] Training [2/16] Loss: 0.02368 +Epoch [157/4000] Training [3/16] Loss: 0.07741 +Epoch [157/4000] Training [4/16] Loss: 0.03617 +Epoch [157/4000] Training [5/16] Loss: 0.02341 +Epoch [157/4000] Training [6/16] Loss: 0.02395 +Epoch [157/4000] Training [7/16] Loss: 0.03020 +Epoch [157/4000] Training [8/16] Loss: 0.02529 +Epoch [157/4000] Training [9/16] Loss: 0.02615 +Epoch [157/4000] Training [10/16] Loss: 0.02637 +Epoch [157/4000] Training [11/16] Loss: 0.02159 +Epoch [157/4000] Training [12/16] Loss: 0.02777 +Epoch [157/4000] Training [13/16] Loss: 0.02580 +Epoch [157/4000] Training [14/16] Loss: 0.04768 +Epoch [157/4000] Training [15/16] Loss: 0.02763 +Epoch [157/4000] Training [16/16] Loss: 0.03195 +Epoch [157/4000] Training metric {'Train/mean dice_metric': 0.9775158762931824, 'Train/mean miou_metric': 0.9585009217262268, 'Train/mean f1': 0.9776701331138611, 'Train/mean precision': 0.9743170142173767, 'Train/mean recall': 0.9810462594032288, 'Train/mean hd95_metric': 4.647855758666992} +Epoch [157/4000] Validation [1/4] Loss: 0.15280 focal_loss 0.08175 dice_loss 0.07105 +Epoch [157/4000] Validation [2/4] Loss: 0.23041 focal_loss 0.07427 dice_loss 0.15614 +Epoch [157/4000] Validation [3/4] Loss: 0.44293 focal_loss 0.28114 dice_loss 0.16179 +Epoch [157/4000] Validation [4/4] Loss: 0.26992 focal_loss 0.14175 dice_loss 0.12817 +Epoch [157/4000] Validation metric {'Val/mean dice_metric': 0.9499592781066895, 'Val/mean miou_metric': 0.9207962155342102, 'Val/mean f1': 0.9563984870910645, 'Val/mean precision': 0.9513726830482483, 'Val/mean recall': 0.9614775776863098, 'Val/mean hd95_metric': 10.877301216125488} +Cheakpoint... +Epoch [157/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9500], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9499592781066895, 'Val/mean miou_metric': 0.9207962155342102, 'Val/mean f1': 0.9563984870910645, 'Val/mean precision': 0.9513726830482483, 'Val/mean recall': 0.9614775776863098, 'Val/mean hd95_metric': 10.877301216125488} +Epoch [158/4000] Training [1/16] Loss: 0.04990 +Epoch [158/4000] Training [2/16] Loss: 0.01922 +Epoch [158/4000] Training [3/16] Loss: 0.02764 +Epoch [158/4000] Training [4/16] Loss: 0.02899 +Epoch [158/4000] Training [5/16] Loss: 0.02085 +Epoch [158/4000] Training [6/16] Loss: 0.02478 +Epoch [158/4000] Training [7/16] Loss: 0.02451 +Epoch [158/4000] Training [8/16] Loss: 0.06501 +Epoch [158/4000] Training [9/16] Loss: 0.03115 +Epoch [158/4000] Training [10/16] Loss: 0.06072 +Epoch [158/4000] Training [11/16] Loss: 0.02782 +Epoch [158/4000] Training [12/16] Loss: 0.12264 +Epoch [158/4000] Training [13/16] Loss: 0.06239 +Epoch [158/4000] Training [14/16] Loss: 0.03533 +Epoch [158/4000] Training [15/16] Loss: 0.03367 +Epoch [158/4000] Training [16/16] Loss: 0.03620 +Epoch [158/4000] Training metric {'Train/mean dice_metric': 0.9730595350265503, 'Train/mean miou_metric': 0.9502879977226257, 'Train/mean f1': 0.9714183211326599, 'Train/mean precision': 0.9673734903335571, 'Train/mean recall': 0.9754971861839294, 'Train/mean hd95_metric': 7.523748397827148} +Epoch [158/4000] Validation [1/4] Loss: 0.23776 focal_loss 0.12791 dice_loss 0.10985 +Epoch [158/4000] Validation [2/4] Loss: 0.32096 focal_loss 0.12476 dice_loss 0.19619 +Epoch [158/4000] Validation [3/4] Loss: 0.15417 focal_loss 0.05664 dice_loss 0.09753 +Epoch [158/4000] Validation [4/4] Loss: 0.51107 focal_loss 0.27131 dice_loss 0.23976 +Epoch [158/4000] Validation metric {'Val/mean dice_metric': 0.9455822110176086, 'Val/mean miou_metric': 0.9112556576728821, 'Val/mean f1': 0.9483732581138611, 'Val/mean precision': 0.9435568451881409, 'Val/mean recall': 0.9532391428947449, 'Val/mean hd95_metric': 13.578969955444336} +Cheakpoint... +Epoch [158/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9456], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9455822110176086, 'Val/mean miou_metric': 0.9112556576728821, 'Val/mean f1': 0.9483732581138611, 'Val/mean precision': 0.9435568451881409, 'Val/mean recall': 0.9532391428947449, 'Val/mean hd95_metric': 13.578969955444336} +Epoch [159/4000] Training [1/16] Loss: 0.02412 +Epoch [159/4000] Training [2/16] Loss: 0.03195 +Epoch [159/4000] Training [3/16] Loss: 0.07335 +Epoch [159/4000] Training [4/16] Loss: 0.03340 +Epoch [159/4000] Training [5/16] Loss: 0.03532 +Epoch [159/4000] Training [6/16] Loss: 0.02937 +Epoch [159/4000] Training [7/16] Loss: 0.03377 +Epoch [159/4000] Training [8/16] Loss: 0.03491 +Epoch [159/4000] Training [9/16] Loss: 0.03017 +Epoch [159/4000] Training [10/16] Loss: 0.03995 +Epoch [159/4000] Training [11/16] Loss: 0.02421 +Epoch [159/4000] Training [12/16] Loss: 0.03711 +Epoch [159/4000] Training [13/16] Loss: 0.08109 +Epoch [159/4000] Training [14/16] Loss: 0.02815 +Epoch [159/4000] Training [15/16] Loss: 0.02773 +Epoch [159/4000] Training [16/16] Loss: 0.03000 +Epoch [159/4000] Training metric {'Train/mean dice_metric': 0.9768209457397461, 'Train/mean miou_metric': 0.9556300640106201, 'Train/mean f1': 0.9741410613059998, 'Train/mean precision': 0.9701778888702393, 'Train/mean recall': 0.9781367778778076, 'Train/mean hd95_metric': 5.879663467407227} +Epoch [159/4000] Validation [1/4] Loss: 0.22378 focal_loss 0.12442 dice_loss 0.09936 +Epoch [159/4000] Validation [2/4] Loss: 0.35879 focal_loss 0.11144 dice_loss 0.24735 +Epoch [159/4000] Validation [3/4] Loss: 0.24149 focal_loss 0.12172 dice_loss 0.11977 +Epoch [159/4000] Validation [4/4] Loss: 0.35456 focal_loss 0.15751 dice_loss 0.19705 +Epoch [159/4000] Validation metric {'Val/mean dice_metric': 0.9504691958427429, 'Val/mean miou_metric': 0.9187847375869751, 'Val/mean f1': 0.9522159695625305, 'Val/mean precision': 0.9435195922851562, 'Val/mean recall': 0.9610740542411804, 'Val/mean hd95_metric': 11.518400192260742} +Cheakpoint... +Epoch [159/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9505], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9504691958427429, 'Val/mean miou_metric': 0.9187847375869751, 'Val/mean f1': 0.9522159695625305, 'Val/mean precision': 0.9435195922851562, 'Val/mean recall': 0.9610740542411804, 'Val/mean hd95_metric': 11.518400192260742} +Epoch [160/4000] Training [1/16] Loss: 0.02794 +Epoch [160/4000] Training [2/16] Loss: 0.02661 +Epoch [160/4000] Training [3/16] Loss: 0.02677 +Epoch [160/4000] Training [4/16] Loss: 0.03367 +Epoch [160/4000] Training [5/16] Loss: 0.05272 +Epoch [160/4000] Training [6/16] Loss: 0.04793 +Epoch [160/4000] Training [7/16] Loss: 0.02024 +Epoch [160/4000] Training [8/16] Loss: 0.02716 +Epoch [160/4000] Training [9/16] Loss: 0.02825 +Epoch [160/4000] Training [10/16] Loss: 0.02333 +Epoch [160/4000] Training [11/16] Loss: 0.03139 +Epoch [160/4000] Training [12/16] Loss: 0.03122 +Epoch [160/4000] Training [13/16] Loss: 0.03551 +Epoch [160/4000] Training [14/16] Loss: 0.12739 +Epoch [160/4000] Training [15/16] Loss: 0.02632 +Epoch [160/4000] Training [16/16] Loss: 0.02897 +Epoch [160/4000] Training metric {'Train/mean dice_metric': 0.9764536023139954, 'Train/mean miou_metric': 0.9558917284011841, 'Train/mean f1': 0.9729810953140259, 'Train/mean precision': 0.9715830683708191, 'Train/mean recall': 0.9743831753730774, 'Train/mean hd95_metric': 5.548036575317383} +Epoch [160/4000] Validation [1/4] Loss: 0.14507 focal_loss 0.07665 dice_loss 0.06841 +Epoch [160/4000] Validation [2/4] Loss: 0.17899 focal_loss 0.06326 dice_loss 0.11573 +Epoch [160/4000] Validation [3/4] Loss: 0.20742 focal_loss 0.08927 dice_loss 0.11815 +Epoch [160/4000] Validation [4/4] Loss: 0.36274 focal_loss 0.15974 dice_loss 0.20300 +Epoch [160/4000] Validation metric {'Val/mean dice_metric': 0.9474814534187317, 'Val/mean miou_metric': 0.9164624214172363, 'Val/mean f1': 0.9468179941177368, 'Val/mean precision': 0.9340891242027283, 'Val/mean recall': 0.9598985910415649, 'Val/mean hd95_metric': 12.309102058410645} +Cheakpoint... +Epoch [160/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9475], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9474814534187317, 'Val/mean miou_metric': 0.9164624214172363, 'Val/mean f1': 0.9468179941177368, 'Val/mean precision': 0.9340891242027283, 'Val/mean recall': 0.9598985910415649, 'Val/mean hd95_metric': 12.309102058410645} +Epoch [161/4000] Training [1/16] Loss: 0.02219 +Epoch [161/4000] Training [2/16] Loss: 0.04040 +Epoch [161/4000] Training [3/16] Loss: 0.02687 +Epoch [161/4000] Training [4/16] Loss: 0.02324 +Epoch [161/4000] Training [5/16] Loss: 0.02225 +Epoch [161/4000] Training [6/16] Loss: 0.03258 +Epoch [161/4000] Training [7/16] Loss: 0.02248 +Epoch [161/4000] Training [8/16] Loss: 0.02984 +Epoch [161/4000] Training [9/16] Loss: 0.04904 +Epoch [161/4000] Training [10/16] Loss: 0.02558 +Epoch [161/4000] Training [11/16] Loss: 0.02687 +Epoch [161/4000] Training [12/16] Loss: 0.02819 +Epoch [161/4000] Training [13/16] Loss: 0.03682 +Epoch [161/4000] Training [14/16] Loss: 0.02091 +Epoch [161/4000] Training [15/16] Loss: 0.02209 +Epoch [161/4000] Training [16/16] Loss: 0.02336 +Epoch [161/4000] Training metric {'Train/mean dice_metric': 0.9784287810325623, 'Train/mean miou_metric': 0.9583531618118286, 'Train/mean f1': 0.9750382900238037, 'Train/mean precision': 0.9713123440742493, 'Train/mean recall': 0.9787929654121399, 'Train/mean hd95_metric': 5.8761467933654785} +Epoch [161/4000] Validation [1/4] Loss: 0.15195 focal_loss 0.07363 dice_loss 0.07832 +Epoch [161/4000] Validation [2/4] Loss: 0.21278 focal_loss 0.06769 dice_loss 0.14509 +Epoch [161/4000] Validation [3/4] Loss: 0.21518 focal_loss 0.08531 dice_loss 0.12987 +Epoch [161/4000] Validation [4/4] Loss: 0.25045 focal_loss 0.09993 dice_loss 0.15052 +Epoch [161/4000] Validation metric {'Val/mean dice_metric': 0.9546558260917664, 'Val/mean miou_metric': 0.9245691299438477, 'Val/mean f1': 0.955647349357605, 'Val/mean precision': 0.9473395943641663, 'Val/mean recall': 0.964102029800415, 'Val/mean hd95_metric': 10.911824226379395} +Cheakpoint... +Epoch [161/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9547], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9546558260917664, 'Val/mean miou_metric': 0.9245691299438477, 'Val/mean f1': 0.955647349357605, 'Val/mean precision': 0.9473395943641663, 'Val/mean recall': 0.964102029800415, 'Val/mean hd95_metric': 10.911824226379395} +Epoch [162/4000] Training [1/16] Loss: 0.02937 +Epoch [162/4000] Training [2/16] Loss: 0.02749 +Epoch [162/4000] Training [3/16] Loss: 0.02143 +Epoch [162/4000] Training [4/16] Loss: 0.02414 +Epoch [162/4000] Training [5/16] Loss: 0.02632 +Epoch [162/4000] Training [6/16] Loss: 0.01999 +Epoch [162/4000] Training [7/16] Loss: 0.03517 +Epoch [162/4000] Training [8/16] Loss: 0.02362 +Epoch [162/4000] Training [9/16] Loss: 0.02035 +Epoch [162/4000] Training [10/16] Loss: 0.02419 +Epoch [162/4000] Training [11/16] Loss: 0.02617 +Epoch [162/4000] Training [12/16] Loss: 0.02705 +Epoch [162/4000] Training [13/16] Loss: 0.02498 +Epoch [162/4000] Training [14/16] Loss: 0.04252 +Epoch [162/4000] Training [15/16] Loss: 0.01782 +Epoch [162/4000] Training [16/16] Loss: 0.02792 +Epoch [162/4000] Training metric {'Train/mean dice_metric': 0.9821615219116211, 'Train/mean miou_metric': 0.9649636745452881, 'Train/mean f1': 0.9800329208374023, 'Train/mean precision': 0.9758496284484863, 'Train/mean recall': 0.9842522144317627, 'Train/mean hd95_metric': 3.295827865600586} +Epoch [162/4000] Validation [1/4] Loss: 0.16665 focal_loss 0.07586 dice_loss 0.09079 +Epoch [162/4000] Validation [2/4] Loss: 0.31364 focal_loss 0.12372 dice_loss 0.18991 +Epoch [162/4000] Validation [3/4] Loss: 0.16420 focal_loss 0.07716 dice_loss 0.08703 +Epoch [162/4000] Validation [4/4] Loss: 0.21255 focal_loss 0.10170 dice_loss 0.11085 +Epoch [162/4000] Validation metric {'Val/mean dice_metric': 0.9623392224311829, 'Val/mean miou_metric': 0.9349370002746582, 'Val/mean f1': 0.9637312889099121, 'Val/mean precision': 0.961974024772644, 'Val/mean recall': 0.9654949903488159, 'Val/mean hd95_metric': 7.883258819580078} +Cheakpoint... +Epoch [162/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9623], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9623392224311829, 'Val/mean miou_metric': 0.9349370002746582, 'Val/mean f1': 0.9637312889099121, 'Val/mean precision': 0.961974024772644, 'Val/mean recall': 0.9654949903488159, 'Val/mean hd95_metric': 7.883258819580078} +Epoch [163/4000] Training [1/16] Loss: 0.01763 +Epoch [163/4000] Training [2/16] Loss: 0.01454 +Epoch [163/4000] Training [3/16] Loss: 0.02200 +Epoch [163/4000] Training [4/16] Loss: 0.01992 +Epoch [163/4000] Training [5/16] Loss: 0.01823 +Epoch [163/4000] Training [6/16] Loss: 0.01893 +Epoch [163/4000] Training [7/16] Loss: 0.02211 +Epoch [163/4000] Training [8/16] Loss: 0.02272 +Epoch [163/4000] Training [9/16] Loss: 0.01641 +Epoch [163/4000] Training [10/16] Loss: 0.01903 +Epoch [163/4000] Training [11/16] Loss: 0.01923 +Epoch [163/4000] Training [12/16] Loss: 0.01913 +Epoch [163/4000] Training [13/16] Loss: 0.02247 +Epoch [163/4000] Training [14/16] Loss: 0.02598 +Epoch [163/4000] Training [15/16] Loss: 0.01755 +Epoch [163/4000] Training [16/16] Loss: 0.03279 +Epoch [163/4000] Training metric {'Train/mean dice_metric': 0.984789252281189, 'Train/mean miou_metric': 0.9702242612838745, 'Train/mean f1': 0.9824101328849792, 'Train/mean precision': 0.977687656879425, 'Train/mean recall': 0.9871784448623657, 'Train/mean hd95_metric': 2.1814589500427246} +Epoch [163/4000] Validation [1/4] Loss: 0.15254 focal_loss 0.08607 dice_loss 0.06647 +Epoch [163/4000] Validation [2/4] Loss: 0.15483 focal_loss 0.05379 dice_loss 0.10105 +Epoch [163/4000] Validation [3/4] Loss: 0.19809 focal_loss 0.08557 dice_loss 0.11251 +Epoch [163/4000] Validation [4/4] Loss: 0.27650 focal_loss 0.10338 dice_loss 0.17311 +Epoch [163/4000] Validation metric {'Val/mean dice_metric': 0.9607685804367065, 'Val/mean miou_metric': 0.9360138177871704, 'Val/mean f1': 0.963726282119751, 'Val/mean precision': 0.9559285640716553, 'Val/mean recall': 0.9716522097587585, 'Val/mean hd95_metric': 7.056334018707275} +Cheakpoint... +Epoch [163/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9607685804367065, 'Val/mean miou_metric': 0.9360138177871704, 'Val/mean f1': 0.963726282119751, 'Val/mean precision': 0.9559285640716553, 'Val/mean recall': 0.9716522097587585, 'Val/mean hd95_metric': 7.056334018707275} +Epoch [164/4000] Training [1/16] Loss: 0.03086 +Epoch [164/4000] Training [2/16] Loss: 0.02127 +Epoch [164/4000] Training [3/16] Loss: 0.02229 +Epoch [164/4000] Training [4/16] Loss: 0.02419 +Epoch [164/4000] Training [5/16] Loss: 0.02112 +Epoch [164/4000] Training [6/16] Loss: 0.33147 +Epoch [164/4000] Training [7/16] Loss: 0.02563 +Epoch [164/4000] Training [8/16] Loss: 0.01876 +Epoch [164/4000] Training [9/16] Loss: 0.02432 +Epoch [164/4000] Training [10/16] Loss: 0.01767 +Epoch [164/4000] Training [11/16] Loss: 0.01916 +Epoch [164/4000] Training [12/16] Loss: 0.04113 +Epoch [164/4000] Training [13/16] Loss: 0.02021 +Epoch [164/4000] Training [14/16] Loss: 0.02646 +Epoch [164/4000] Training [15/16] Loss: 0.01952 +Epoch [164/4000] Training [16/16] Loss: 0.02396 +Epoch [164/4000] Training metric {'Train/mean dice_metric': 0.980394721031189, 'Train/mean miou_metric': 0.9638611078262329, 'Train/mean f1': 0.9749201536178589, 'Train/mean precision': 0.9670175909996033, 'Train/mean recall': 0.9829529523849487, 'Train/mean hd95_metric': 4.019467353820801} +Epoch [164/4000] Validation [1/4] Loss: 0.27797 focal_loss 0.17026 dice_loss 0.10771 +Epoch [164/4000] Validation [2/4] Loss: 0.25347 focal_loss 0.10122 dice_loss 0.15225 +Epoch [164/4000] Validation [3/4] Loss: 0.22916 focal_loss 0.11785 dice_loss 0.11131 +Epoch [164/4000] Validation [4/4] Loss: 0.25367 focal_loss 0.10354 dice_loss 0.15013 +Epoch [164/4000] Validation metric {'Val/mean dice_metric': 0.953429102897644, 'Val/mean miou_metric': 0.9260574579238892, 'Val/mean f1': 0.9528328776359558, 'Val/mean precision': 0.9495648145675659, 'Val/mean recall': 0.9561235308647156, 'Val/mean hd95_metric': 9.469179153442383} +Cheakpoint... +Epoch [164/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9534], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.953429102897644, 'Val/mean miou_metric': 0.9260574579238892, 'Val/mean f1': 0.9528328776359558, 'Val/mean precision': 0.9495648145675659, 'Val/mean recall': 0.9561235308647156, 'Val/mean hd95_metric': 9.469179153442383} +Epoch [165/4000] Training [1/16] Loss: 0.02140 +Epoch [165/4000] Training [2/16] Loss: 0.02984 +Epoch [165/4000] Training [3/16] Loss: 0.02139 +Epoch [165/4000] Training [4/16] Loss: 0.02585 +Epoch [165/4000] Training [5/16] Loss: 0.01858 +Epoch [165/4000] Training [6/16] Loss: 0.02036 +Epoch [165/4000] Training [7/16] Loss: 0.03496 +Epoch [165/4000] Training [8/16] Loss: 0.02393 +Epoch [165/4000] Training [9/16] Loss: 0.02308 +Epoch [165/4000] Training [10/16] Loss: 0.02934 +Epoch [165/4000] Training [11/16] Loss: 0.06377 +Epoch [165/4000] Training [12/16] Loss: 0.02825 +Epoch [165/4000] Training [13/16] Loss: 0.01801 +Epoch [165/4000] Training [14/16] Loss: 0.01753 +Epoch [165/4000] Training [15/16] Loss: 0.02057 +Epoch [165/4000] Training [16/16] Loss: 0.02837 +Epoch [165/4000] Training metric {'Train/mean dice_metric': 0.9824821352958679, 'Train/mean miou_metric': 0.9658332467079163, 'Train/mean f1': 0.9791557788848877, 'Train/mean precision': 0.9737863540649414, 'Train/mean recall': 0.9845846891403198, 'Train/mean hd95_metric': 4.086414337158203} +Epoch [165/4000] Validation [1/4] Loss: 0.16989 focal_loss 0.07065 dice_loss 0.09923 +Epoch [165/4000] Validation [2/4] Loss: 0.22542 focal_loss 0.06419 dice_loss 0.16123 +Epoch [165/4000] Validation [3/4] Loss: 0.12110 focal_loss 0.04609 dice_loss 0.07501 +Epoch [165/4000] Validation [4/4] Loss: 0.30044 focal_loss 0.11728 dice_loss 0.18316 +Epoch [165/4000] Validation metric {'Val/mean dice_metric': 0.9567009210586548, 'Val/mean miou_metric': 0.9293218851089478, 'Val/mean f1': 0.961350679397583, 'Val/mean precision': 0.9600078463554382, 'Val/mean recall': 0.9626972079277039, 'Val/mean hd95_metric': 9.01287841796875} +Cheakpoint... +Epoch [165/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9567], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9567009210586548, 'Val/mean miou_metric': 0.9293218851089478, 'Val/mean f1': 0.961350679397583, 'Val/mean precision': 0.9600078463554382, 'Val/mean recall': 0.9626972079277039, 'Val/mean hd95_metric': 9.01287841796875} +Epoch [166/4000] Training [1/16] Loss: 0.02238 +Epoch [166/4000] Training [2/16] Loss: 0.03389 +Epoch [166/4000] Training [3/16] Loss: 0.02506 +Epoch [166/4000] Training [4/16] Loss: 0.02155 +Epoch [166/4000] Training [5/16] Loss: 0.02699 +Epoch [166/4000] Training [6/16] Loss: 0.04697 +Epoch [166/4000] Training [7/16] Loss: 0.02175 +Epoch [166/4000] Training [8/16] Loss: 0.09023 +Epoch [166/4000] Training [9/16] Loss: 0.03219 +Epoch [166/4000] Training [10/16] Loss: 0.02939 +Epoch [166/4000] Training [11/16] Loss: 0.01949 +Epoch [166/4000] Training [12/16] Loss: 0.02308 +Epoch [166/4000] Training [13/16] Loss: 0.02741 +Epoch [166/4000] Training [14/16] Loss: 0.22778 +Epoch [166/4000] Training [15/16] Loss: 0.02483 +Epoch [166/4000] Training [16/16] Loss: 0.02677 +Epoch [166/4000] Training metric {'Train/mean dice_metric': 0.9798755645751953, 'Train/mean miou_metric': 0.9616168737411499, 'Train/mean f1': 0.9760186672210693, 'Train/mean precision': 0.9742938876152039, 'Train/mean recall': 0.9777495265007019, 'Train/mean hd95_metric': 3.123197317123413} +Epoch [166/4000] Validation [1/4] Loss: 0.11898 focal_loss 0.05606 dice_loss 0.06292 +Epoch [166/4000] Validation [2/4] Loss: 0.48639 focal_loss 0.26132 dice_loss 0.22507 +Epoch [166/4000] Validation [3/4] Loss: 0.10386 focal_loss 0.04556 dice_loss 0.05830 +Epoch [166/4000] Validation [4/4] Loss: 0.26561 focal_loss 0.12017 dice_loss 0.14544 +Epoch [166/4000] Validation metric {'Val/mean dice_metric': 0.9548660516738892, 'Val/mean miou_metric': 0.9260009527206421, 'Val/mean f1': 0.9535952806472778, 'Val/mean precision': 0.9401836395263672, 'Val/mean recall': 0.967395007610321, 'Val/mean hd95_metric': 9.72753620147705} +Cheakpoint... +Epoch [166/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9549], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9548660516738892, 'Val/mean miou_metric': 0.9260009527206421, 'Val/mean f1': 0.9535952806472778, 'Val/mean precision': 0.9401836395263672, 'Val/mean recall': 0.967395007610321, 'Val/mean hd95_metric': 9.72753620147705} +Epoch [167/4000] Training [1/16] Loss: 0.03692 +Epoch [167/4000] Training [2/16] Loss: 0.03412 +Epoch [167/4000] Training [3/16] Loss: 0.01988 +Epoch [167/4000] Training [4/16] Loss: 0.02195 +Epoch [167/4000] Training [5/16] Loss: 0.02477 +Epoch [167/4000] Training [6/16] Loss: 0.02234 +Epoch [167/4000] Training [7/16] Loss: 0.02244 +Epoch [167/4000] Training [8/16] Loss: 0.03774 +Epoch [167/4000] Training [9/16] Loss: 0.02283 +Epoch [167/4000] Training [10/16] Loss: 0.02894 +Epoch [167/4000] Training [11/16] Loss: 0.03026 +Epoch [167/4000] Training [12/16] Loss: 0.04174 +Epoch [167/4000] Training [13/16] Loss: 0.03769 +Epoch [167/4000] Training [14/16] Loss: 0.02856 +Epoch [167/4000] Training [15/16] Loss: 0.04029 +Epoch [167/4000] Training [16/16] Loss: 0.05940 +Epoch [167/4000] Training metric {'Train/mean dice_metric': 0.9794518947601318, 'Train/mean miou_metric': 0.9601162672042847, 'Train/mean f1': 0.9771645665168762, 'Train/mean precision': 0.9734901189804077, 'Train/mean recall': 0.9808668494224548, 'Train/mean hd95_metric': 4.714789390563965} +Epoch [167/4000] Validation [1/4] Loss: 0.15059 focal_loss 0.08360 dice_loss 0.06699 +Epoch [167/4000] Validation [2/4] Loss: 0.29755 focal_loss 0.12957 dice_loss 0.16799 +Epoch [167/4000] Validation [3/4] Loss: 0.21989 focal_loss 0.11361 dice_loss 0.10628 +Epoch [167/4000] Validation [4/4] Loss: 0.27069 focal_loss 0.13358 dice_loss 0.13711 +Epoch [167/4000] Validation metric {'Val/mean dice_metric': 0.9546800851821899, 'Val/mean miou_metric': 0.9252212643623352, 'Val/mean f1': 0.9598056674003601, 'Val/mean precision': 0.9549096822738647, 'Val/mean recall': 0.9647522568702698, 'Val/mean hd95_metric': 8.922636985778809} +Cheakpoint... +Epoch [167/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9547], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9546800851821899, 'Val/mean miou_metric': 0.9252212643623352, 'Val/mean f1': 0.9598056674003601, 'Val/mean precision': 0.9549096822738647, 'Val/mean recall': 0.9647522568702698, 'Val/mean hd95_metric': 8.922636985778809} +Epoch [168/4000] Training [1/16] Loss: 0.02276 +Epoch [168/4000] Training [2/16] Loss: 0.02395 +Epoch [168/4000] Training [3/16] Loss: 0.02868 +Epoch [168/4000] Training [4/16] Loss: 0.02411 +Epoch [168/4000] Training [5/16] Loss: 0.04824 +Epoch [168/4000] Training [6/16] Loss: 0.02436 +Epoch [168/4000] Training [7/16] Loss: 0.02340 +Epoch [168/4000] Training [8/16] Loss: 0.02332 +Epoch [168/4000] Training [9/16] Loss: 0.02426 +Epoch [168/4000] Training [10/16] Loss: 0.02852 +Epoch [168/4000] Training [11/16] Loss: 0.02620 +Epoch [168/4000] Training [12/16] Loss: 0.02883 +Epoch [168/4000] Training [13/16] Loss: 0.01991 +Epoch [168/4000] Training [14/16] Loss: 0.02282 +Epoch [168/4000] Training [15/16] Loss: 0.03634 +Epoch [168/4000] Training [16/16] Loss: 0.04720 +Epoch [168/4000] Training metric {'Train/mean dice_metric': 0.9810275435447693, 'Train/mean miou_metric': 0.9630099534988403, 'Train/mean f1': 0.9786084890365601, 'Train/mean precision': 0.9731116890907288, 'Train/mean recall': 0.9841676950454712, 'Train/mean hd95_metric': 3.3738350868225098} +Epoch [168/4000] Validation [1/4] Loss: 0.44344 focal_loss 0.29280 dice_loss 0.15064 +Epoch [168/4000] Validation [2/4] Loss: 0.18977 focal_loss 0.05806 dice_loss 0.13171 +Epoch [168/4000] Validation [3/4] Loss: 0.19891 focal_loss 0.08610 dice_loss 0.11281 +Epoch [168/4000] Validation [4/4] Loss: 0.27276 focal_loss 0.13142 dice_loss 0.14133 +Epoch [168/4000] Validation metric {'Val/mean dice_metric': 0.9528050422668457, 'Val/mean miou_metric': 0.9241611361503601, 'Val/mean f1': 0.954888641834259, 'Val/mean precision': 0.9494990110397339, 'Val/mean recall': 0.9603397846221924, 'Val/mean hd95_metric': 9.145886421203613} +Cheakpoint... +Epoch [168/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9528], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9528050422668457, 'Val/mean miou_metric': 0.9241611361503601, 'Val/mean f1': 0.954888641834259, 'Val/mean precision': 0.9494990110397339, 'Val/mean recall': 0.9603397846221924, 'Val/mean hd95_metric': 9.145886421203613} +Epoch [169/4000] Training [1/16] Loss: 0.01811 +Epoch [169/4000] Training [2/16] Loss: 0.03196 +Epoch [169/4000] Training [3/16] Loss: 0.02314 +Epoch [169/4000] Training [4/16] Loss: 0.02766 +Epoch [169/4000] Training [5/16] Loss: 0.02714 +Epoch [169/4000] Training [6/16] Loss: 0.01952 +Epoch [169/4000] Training [7/16] Loss: 0.03878 +Epoch [169/4000] Training [8/16] Loss: 0.03523 +Epoch [169/4000] Training [9/16] Loss: 0.02398 +Epoch [169/4000] Training [10/16] Loss: 0.02013 +Epoch [169/4000] Training [11/16] Loss: 0.04104 +Epoch [169/4000] Training [12/16] Loss: 0.03265 +Epoch [169/4000] Training [13/16] Loss: 0.04785 +Epoch [169/4000] Training [14/16] Loss: 0.07542 +Epoch [169/4000] Training [15/16] Loss: 0.03321 +Epoch [169/4000] Training [16/16] Loss: 0.03430 +Epoch [169/4000] Training metric {'Train/mean dice_metric': 0.9760507345199585, 'Train/mean miou_metric': 0.9549344778060913, 'Train/mean f1': 0.9718723893165588, 'Train/mean precision': 0.9670414328575134, 'Train/mean recall': 0.9767518043518066, 'Train/mean hd95_metric': 5.546344757080078} +Epoch [169/4000] Validation [1/4] Loss: 0.17009 focal_loss 0.08959 dice_loss 0.08050 +Epoch [169/4000] Validation [2/4] Loss: 0.42497 focal_loss 0.21439 dice_loss 0.21058 +Epoch [169/4000] Validation [3/4] Loss: 0.31569 focal_loss 0.16680 dice_loss 0.14889 +Epoch [169/4000] Validation [4/4] Loss: 0.30111 focal_loss 0.12484 dice_loss 0.17627 +Epoch [169/4000] Validation metric {'Val/mean dice_metric': 0.9515383839607239, 'Val/mean miou_metric': 0.9195703268051147, 'Val/mean f1': 0.9528970122337341, 'Val/mean precision': 0.9444801807403564, 'Val/mean recall': 0.961465060710907, 'Val/mean hd95_metric': 10.860686302185059} +Cheakpoint... +Epoch [169/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9515], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9515383839607239, 'Val/mean miou_metric': 0.9195703268051147, 'Val/mean f1': 0.9528970122337341, 'Val/mean precision': 0.9444801807403564, 'Val/mean recall': 0.961465060710907, 'Val/mean hd95_metric': 10.860686302185059} +Epoch [170/4000] Training [1/16] Loss: 0.04174 +Epoch [170/4000] Training [2/16] Loss: 0.02801 +Epoch [170/4000] Training [3/16] Loss: 0.03429 +Epoch [170/4000] Training [4/16] Loss: 0.04507 +Epoch [170/4000] Training [5/16] Loss: 0.04810 +Epoch [170/4000] Training [6/16] Loss: 0.02305 +Epoch [170/4000] Training [7/16] Loss: 0.03318 +Epoch [170/4000] Training [8/16] Loss: 0.30922 +Epoch [170/4000] Training [9/16] Loss: 0.02591 +Epoch [170/4000] Training [10/16] Loss: 0.02361 +Epoch [170/4000] Training [11/16] Loss: 0.02121 +Epoch [170/4000] Training [12/16] Loss: 0.02922 +Epoch [170/4000] Training [13/16] Loss: 0.02314 +Epoch [170/4000] Training [14/16] Loss: 0.02633 +Epoch [170/4000] Training [15/16] Loss: 0.03395 +Epoch [170/4000] Training [16/16] Loss: 0.02622 +Epoch [170/4000] Training metric {'Train/mean dice_metric': 0.9770810604095459, 'Train/mean miou_metric': 0.956010103225708, 'Train/mean f1': 0.9733030796051025, 'Train/mean precision': 0.9716825485229492, 'Train/mean recall': 0.9749290347099304, 'Train/mean hd95_metric': 4.981141567230225} +Epoch [170/4000] Validation [1/4] Loss: 0.17629 focal_loss 0.06753 dice_loss 0.10877 +Epoch [170/4000] Validation [2/4] Loss: 0.39146 focal_loss 0.15509 dice_loss 0.23637 +Epoch [170/4000] Validation [3/4] Loss: 0.12629 focal_loss 0.05849 dice_loss 0.06780 +Epoch [170/4000] Validation [4/4] Loss: 0.16969 focal_loss 0.05929 dice_loss 0.11040 +Epoch [170/4000] Validation metric {'Val/mean dice_metric': 0.9522964358329773, 'Val/mean miou_metric': 0.9218674898147583, 'Val/mean f1': 0.9552300572395325, 'Val/mean precision': 0.9538031816482544, 'Val/mean recall': 0.9566612839698792, 'Val/mean hd95_metric': 9.660782814025879} +Cheakpoint... +Epoch [170/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9523], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9522964358329773, 'Val/mean miou_metric': 0.9218674898147583, 'Val/mean f1': 0.9552300572395325, 'Val/mean precision': 0.9538031816482544, 'Val/mean recall': 0.9566612839698792, 'Val/mean hd95_metric': 9.660782814025879} +Epoch [171/4000] Training [1/16] Loss: 0.02882 +Epoch [171/4000] Training [2/16] Loss: 0.01963 +Epoch [171/4000] Training [3/16] Loss: 0.02247 +Epoch [171/4000] Training [4/16] Loss: 0.03475 +Epoch [171/4000] Training [5/16] Loss: 0.02509 +Epoch [171/4000] Training [6/16] Loss: 0.02489 +Epoch [171/4000] Training [7/16] Loss: 0.02277 +Epoch [171/4000] Training [8/16] Loss: 0.03534 +Epoch [171/4000] Training [9/16] Loss: 0.02440 +Epoch [171/4000] Training [10/16] Loss: 0.02283 +Epoch [171/4000] Training [11/16] Loss: 0.02711 +Epoch [171/4000] Training [12/16] Loss: 0.02641 +Epoch [171/4000] Training [13/16] Loss: 0.02819 +Epoch [171/4000] Training [14/16] Loss: 0.02256 +Epoch [171/4000] Training [15/16] Loss: 0.08931 +Epoch [171/4000] Training [16/16] Loss: 0.02682 +Epoch [171/4000] Training metric {'Train/mean dice_metric': 0.9803560972213745, 'Train/mean miou_metric': 0.9619463682174683, 'Train/mean f1': 0.9775934219360352, 'Train/mean precision': 0.9737880229949951, 'Train/mean recall': 0.9814286231994629, 'Train/mean hd95_metric': 3.6745753288269043} +Epoch [171/4000] Validation [1/4] Loss: 0.19365 focal_loss 0.09924 dice_loss 0.09441 +Epoch [171/4000] Validation [2/4] Loss: 0.36501 focal_loss 0.13391 dice_loss 0.23110 +Epoch [171/4000] Validation [3/4] Loss: 0.13241 focal_loss 0.04784 dice_loss 0.08458 +Epoch [171/4000] Validation [4/4] Loss: 0.17942 focal_loss 0.06540 dice_loss 0.11402 +Epoch [171/4000] Validation metric {'Val/mean dice_metric': 0.9567157030105591, 'Val/mean miou_metric': 0.927625834941864, 'Val/mean f1': 0.9589840769767761, 'Val/mean precision': 0.9542683362960815, 'Val/mean recall': 0.9637466073036194, 'Val/mean hd95_metric': 9.447049140930176} +Cheakpoint... +Epoch [171/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9567], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9567157030105591, 'Val/mean miou_metric': 0.927625834941864, 'Val/mean f1': 0.9589840769767761, 'Val/mean precision': 0.9542683362960815, 'Val/mean recall': 0.9637466073036194, 'Val/mean hd95_metric': 9.447049140930176} +Epoch [172/4000] Training [1/16] Loss: 0.03333 +Epoch [172/4000] Training [2/16] Loss: 0.02330 +Epoch [172/4000] Training [3/16] Loss: 0.02708 +Epoch [172/4000] Training [4/16] Loss: 0.02467 +Epoch [172/4000] Training [5/16] Loss: 0.01991 +Epoch [172/4000] Training [6/16] Loss: 0.02014 +Epoch [172/4000] Training [7/16] Loss: 0.02577 +Epoch [172/4000] Training [8/16] Loss: 0.02719 +Epoch [172/4000] Training [9/16] Loss: 0.01762 +Epoch [172/4000] Training [10/16] Loss: 0.01762 +Epoch [172/4000] Training [11/16] Loss: 0.02273 +Epoch [172/4000] Training [12/16] Loss: 0.02105 +Epoch [172/4000] Training [13/16] Loss: 0.02025 +Epoch [172/4000] Training [14/16] Loss: 0.02669 +Epoch [172/4000] Training [15/16] Loss: 0.02408 +Epoch [172/4000] Training [16/16] Loss: 0.03487 +Epoch [172/4000] Training metric {'Train/mean dice_metric': 0.9826961755752563, 'Train/mean miou_metric': 0.9660120010375977, 'Train/mean f1': 0.9810045957565308, 'Train/mean precision': 0.9762234687805176, 'Train/mean recall': 0.9858327507972717, 'Train/mean hd95_metric': 2.368755578994751} +Epoch [172/4000] Validation [1/4] Loss: 0.32941 focal_loss 0.21266 dice_loss 0.11676 +Epoch [172/4000] Validation [2/4] Loss: 0.44947 focal_loss 0.22519 dice_loss 0.22428 +Epoch [172/4000] Validation [3/4] Loss: 0.28102 focal_loss 0.14739 dice_loss 0.13363 +Epoch [172/4000] Validation [4/4] Loss: 0.21174 focal_loss 0.10638 dice_loss 0.10536 +Epoch [172/4000] Validation metric {'Val/mean dice_metric': 0.957179069519043, 'Val/mean miou_metric': 0.9297126531600952, 'Val/mean f1': 0.9618099927902222, 'Val/mean precision': 0.9594005346298218, 'Val/mean recall': 0.9642314910888672, 'Val/mean hd95_metric': 8.25910472869873} +Cheakpoint... +Epoch [172/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9572], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.957179069519043, 'Val/mean miou_metric': 0.9297126531600952, 'Val/mean f1': 0.9618099927902222, 'Val/mean precision': 0.9594005346298218, 'Val/mean recall': 0.9642314910888672, 'Val/mean hd95_metric': 8.25910472869873} +Epoch [173/4000] Training [1/16] Loss: 0.02255 +Epoch [173/4000] Training [2/16] Loss: 0.01919 +Epoch [173/4000] Training [3/16] Loss: 0.02108 +Epoch [173/4000] Training [4/16] Loss: 0.01771 +Epoch [173/4000] Training [5/16] Loss: 0.02855 +Epoch [173/4000] Training [6/16] Loss: 0.01747 +Epoch [173/4000] Training [7/16] Loss: 0.02421 +Epoch [173/4000] Training [8/16] Loss: 0.01755 +Epoch [173/4000] Training [9/16] Loss: 0.02940 +Epoch [173/4000] Training [10/16] Loss: 0.01800 +Epoch [173/4000] Training [11/16] Loss: 0.01891 +Epoch [173/4000] Training [12/16] Loss: 0.02325 +Epoch [173/4000] Training [13/16] Loss: 0.01792 +Epoch [173/4000] Training [14/16] Loss: 0.02242 +Epoch [173/4000] Training [15/16] Loss: 0.02271 +Epoch [173/4000] Training [16/16] Loss: 0.02742 +Epoch [173/4000] Training metric {'Train/mean dice_metric': 0.9853765368461609, 'Train/mean miou_metric': 0.9710647463798523, 'Train/mean f1': 0.9827565550804138, 'Train/mean precision': 0.9785292744636536, 'Train/mean recall': 0.9870204925537109, 'Train/mean hd95_metric': 2.232583999633789} +Epoch [173/4000] Validation [1/4] Loss: 0.46570 focal_loss 0.32629 dice_loss 0.13941 +Epoch [173/4000] Validation [2/4] Loss: 0.50649 focal_loss 0.20472 dice_loss 0.30177 +Epoch [173/4000] Validation [3/4] Loss: 0.18231 focal_loss 0.08187 dice_loss 0.10044 +Epoch [173/4000] Validation [4/4] Loss: 0.21636 focal_loss 0.08828 dice_loss 0.12808 +Epoch [173/4000] Validation metric {'Val/mean dice_metric': 0.9613921046257019, 'Val/mean miou_metric': 0.9369238615036011, 'Val/mean f1': 0.9639794230461121, 'Val/mean precision': 0.9595999121665955, 'Val/mean recall': 0.9683991074562073, 'Val/mean hd95_metric': 7.324089050292969} +Cheakpoint... +Epoch [173/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9613921046257019, 'Val/mean miou_metric': 0.9369238615036011, 'Val/mean f1': 0.9639794230461121, 'Val/mean precision': 0.9595999121665955, 'Val/mean recall': 0.9683991074562073, 'Val/mean hd95_metric': 7.324089050292969} +Epoch [174/4000] Training [1/16] Loss: 0.02591 +Epoch [174/4000] Training [2/16] Loss: 0.03117 +Epoch [174/4000] Training [3/16] Loss: 0.01727 +Epoch [174/4000] Training [4/16] Loss: 0.01805 +Epoch [174/4000] Training [5/16] Loss: 0.04155 +Epoch [174/4000] Training [6/16] Loss: 0.01867 +Epoch [174/4000] Training [7/16] Loss: 0.02034 +Epoch [174/4000] Training [8/16] Loss: 0.01368 +Epoch [174/4000] Training [9/16] Loss: 0.02469 +Epoch [174/4000] Training [10/16] Loss: 0.02077 +Epoch [174/4000] Training [11/16] Loss: 0.04811 +Epoch [174/4000] Training [12/16] Loss: 0.02424 +Epoch [174/4000] Training [13/16] Loss: 0.01593 +Epoch [174/4000] Training [14/16] Loss: 0.02370 +Epoch [174/4000] Training [15/16] Loss: 0.02065 +Epoch [174/4000] Training [16/16] Loss: 0.01997 +Epoch [174/4000] Training metric {'Train/mean dice_metric': 0.9844182729721069, 'Train/mean miou_metric': 0.9693925380706787, 'Train/mean f1': 0.9828109741210938, 'Train/mean precision': 0.9781960844993591, 'Train/mean recall': 0.9874696135520935, 'Train/mean hd95_metric': 2.2142794132232666} +Epoch [174/4000] Validation [1/4] Loss: 0.13513 focal_loss 0.06961 dice_loss 0.06552 +Epoch [174/4000] Validation [2/4] Loss: 0.17994 focal_loss 0.06219 dice_loss 0.11775 +Epoch [174/4000] Validation [3/4] Loss: 0.19317 focal_loss 0.10361 dice_loss 0.08956 +Epoch [174/4000] Validation [4/4] Loss: 0.20856 focal_loss 0.10401 dice_loss 0.10455 +Epoch [174/4000] Validation metric {'Val/mean dice_metric': 0.960218608379364, 'Val/mean miou_metric': 0.9349223971366882, 'Val/mean f1': 0.9663732647895813, 'Val/mean precision': 0.9607470035552979, 'Val/mean recall': 0.9720657467842102, 'Val/mean hd95_metric': 7.872860908508301} +Cheakpoint... +Epoch [174/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9602], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.960218608379364, 'Val/mean miou_metric': 0.9349223971366882, 'Val/mean f1': 0.9663732647895813, 'Val/mean precision': 0.9607470035552979, 'Val/mean recall': 0.9720657467842102, 'Val/mean hd95_metric': 7.872860908508301} +Epoch [175/4000] Training [1/16] Loss: 0.01581 +Epoch [175/4000] Training [2/16] Loss: 0.04076 +Epoch [175/4000] Training [3/16] Loss: 0.01763 +Epoch [175/4000] Training [4/16] Loss: 0.02134 +Epoch [175/4000] Training [5/16] Loss: 0.03750 +Epoch [175/4000] Training [6/16] Loss: 0.01662 +Epoch [175/4000] Training [7/16] Loss: 0.02189 +Epoch [175/4000] Training [8/16] Loss: 0.02520 +Epoch [175/4000] Training [9/16] Loss: 0.01978 +Epoch [175/4000] Training [10/16] Loss: 0.03078 +Epoch [175/4000] Training [11/16] Loss: 0.01750 +Epoch [175/4000] Training [12/16] Loss: 0.02624 +Epoch [175/4000] Training [13/16] Loss: 0.01957 +Epoch [175/4000] Training [14/16] Loss: 0.02264 +Epoch [175/4000] Training [15/16] Loss: 0.02386 +Epoch [175/4000] Training [16/16] Loss: 0.02446 +Epoch [175/4000] Training metric {'Train/mean dice_metric': 0.9831847548484802, 'Train/mean miou_metric': 0.9679266810417175, 'Train/mean f1': 0.981438934803009, 'Train/mean precision': 0.9776026010513306, 'Train/mean recall': 0.9853055477142334, 'Train/mean hd95_metric': 2.523577928543091} +Epoch [175/4000] Validation [1/4] Loss: 0.28643 focal_loss 0.16883 dice_loss 0.11760 +Epoch [175/4000] Validation [2/4] Loss: 0.40355 focal_loss 0.20195 dice_loss 0.20160 +Epoch [175/4000] Validation [3/4] Loss: 0.27357 focal_loss 0.13692 dice_loss 0.13665 +Epoch [175/4000] Validation [4/4] Loss: 0.18994 focal_loss 0.08287 dice_loss 0.10707 +Epoch [175/4000] Validation metric {'Val/mean dice_metric': 0.9567809104919434, 'Val/mean miou_metric': 0.930371105670929, 'Val/mean f1': 0.9615687727928162, 'Val/mean precision': 0.9627949595451355, 'Val/mean recall': 0.9603457450866699, 'Val/mean hd95_metric': 7.339367866516113} +Cheakpoint... +Epoch [175/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9568], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9567809104919434, 'Val/mean miou_metric': 0.930371105670929, 'Val/mean f1': 0.9615687727928162, 'Val/mean precision': 0.9627949595451355, 'Val/mean recall': 0.9603457450866699, 'Val/mean hd95_metric': 7.339367866516113} +Epoch [176/4000] Training [1/16] Loss: 0.02162 +Epoch [176/4000] Training [2/16] Loss: 0.01424 +Epoch [176/4000] Training [3/16] Loss: 0.15527 +Epoch [176/4000] Training [4/16] Loss: 0.02892 +Epoch [176/4000] Training [5/16] Loss: 0.01680 +Epoch [176/4000] Training [6/16] Loss: 0.02446 +Epoch [176/4000] Training [7/16] Loss: 0.02221 +Epoch [176/4000] Training [8/16] Loss: 0.02362 +Epoch [176/4000] Training [9/16] Loss: 0.01876 +Epoch [176/4000] Training [10/16] Loss: 0.02847 +Epoch [176/4000] Training [11/16] Loss: 0.02308 +Epoch [176/4000] Training [12/16] Loss: 0.02094 +Epoch [176/4000] Training [13/16] Loss: 0.02466 +Epoch [176/4000] Training [14/16] Loss: 0.02555 +Epoch [176/4000] Training [15/16] Loss: 0.02736 +Epoch [176/4000] Training [16/16] Loss: 0.02052 +Epoch [176/4000] Training metric {'Train/mean dice_metric': 0.9793175458908081, 'Train/mean miou_metric': 0.963139533996582, 'Train/mean f1': 0.9786742925643921, 'Train/mean precision': 0.9723055362701416, 'Train/mean recall': 0.9851270318031311, 'Train/mean hd95_metric': 3.5090954303741455} +Epoch [176/4000] Validation [1/4] Loss: 0.13951 focal_loss 0.07473 dice_loss 0.06477 +Epoch [176/4000] Validation [2/4] Loss: 0.34208 focal_loss 0.14332 dice_loss 0.19876 +Epoch [176/4000] Validation [3/4] Loss: 0.21335 focal_loss 0.11924 dice_loss 0.09411 +Epoch [176/4000] Validation [4/4] Loss: 0.35138 focal_loss 0.18373 dice_loss 0.16764 +Epoch [176/4000] Validation metric {'Val/mean dice_metric': 0.9549720883369446, 'Val/mean miou_metric': 0.9276039004325867, 'Val/mean f1': 0.9606439471244812, 'Val/mean precision': 0.9625633955001831, 'Val/mean recall': 0.9587322473526001, 'Val/mean hd95_metric': 7.809198379516602} +Cheakpoint... +Epoch [176/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9550], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9549720883369446, 'Val/mean miou_metric': 0.9276039004325867, 'Val/mean f1': 0.9606439471244812, 'Val/mean precision': 0.9625633955001831, 'Val/mean recall': 0.9587322473526001, 'Val/mean hd95_metric': 7.809198379516602} +Epoch [177/4000] Training [1/16] Loss: 0.02276 +Epoch [177/4000] Training [2/16] Loss: 0.02244 +Epoch [177/4000] Training [3/16] Loss: 0.01799 +Epoch [177/4000] Training [4/16] Loss: 0.03127 +Epoch [177/4000] Training [5/16] Loss: 0.02443 +Epoch [177/4000] Training [6/16] Loss: 0.01713 +Epoch [177/4000] Training [7/16] Loss: 0.01958 +Epoch [177/4000] Training [8/16] Loss: 0.04264 +Epoch [177/4000] Training [9/16] Loss: 0.02308 +Epoch [177/4000] Training [10/16] Loss: 0.02787 +Epoch [177/4000] Training [11/16] Loss: 0.01943 +Epoch [177/4000] Training [12/16] Loss: 0.02199 +Epoch [177/4000] Training [13/16] Loss: 0.02463 +Epoch [177/4000] Training [14/16] Loss: 0.01962 +Epoch [177/4000] Training [15/16] Loss: 0.02364 +Epoch [177/4000] Training [16/16] Loss: 0.02831 +Epoch [177/4000] Training metric {'Train/mean dice_metric': 0.9829895496368408, 'Train/mean miou_metric': 0.9665153622627258, 'Train/mean f1': 0.9809558987617493, 'Train/mean precision': 0.9763314127922058, 'Train/mean recall': 0.985624372959137, 'Train/mean hd95_metric': 3.0962982177734375} +Epoch [177/4000] Validation [1/4] Loss: 0.16201 focal_loss 0.09588 dice_loss 0.06613 +Epoch [177/4000] Validation [2/4] Loss: 0.59815 focal_loss 0.29169 dice_loss 0.30645 +Epoch [177/4000] Validation [3/4] Loss: 0.23227 focal_loss 0.12703 dice_loss 0.10523 +Epoch [177/4000] Validation [4/4] Loss: 0.22966 focal_loss 0.10654 dice_loss 0.12312 +Epoch [177/4000] Validation metric {'Val/mean dice_metric': 0.9576826095581055, 'Val/mean miou_metric': 0.9311923980712891, 'Val/mean f1': 0.9617850184440613, 'Val/mean precision': 0.9525076746940613, 'Val/mean recall': 0.9712450504302979, 'Val/mean hd95_metric': 8.18138313293457} +Cheakpoint... +Epoch [177/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9577], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576826095581055, 'Val/mean miou_metric': 0.9311923980712891, 'Val/mean f1': 0.9617850184440613, 'Val/mean precision': 0.9525076746940613, 'Val/mean recall': 0.9712450504302979, 'Val/mean hd95_metric': 8.18138313293457} +Epoch [178/4000] Training [1/16] Loss: 0.02066 +Epoch [178/4000] Training [2/16] Loss: 0.01775 +Epoch [178/4000] Training [3/16] Loss: 0.03019 +Epoch [178/4000] Training [4/16] Loss: 0.03293 +Epoch [178/4000] Training [5/16] Loss: 0.02589 +Epoch [178/4000] Training [6/16] Loss: 0.04344 +Epoch [178/4000] Training [7/16] Loss: 0.02729 +Epoch [178/4000] Training [8/16] Loss: 0.01753 +Epoch [178/4000] Training [9/16] Loss: 0.02354 +Epoch [178/4000] Training [10/16] Loss: 0.02253 +Epoch [178/4000] Training [11/16] Loss: 0.02678 +Epoch [178/4000] Training [12/16] Loss: 0.01959 +Epoch [178/4000] Training [13/16] Loss: 0.01941 +Epoch [178/4000] Training [14/16] Loss: 0.01941 +Epoch [178/4000] Training [15/16] Loss: 0.02223 +Epoch [178/4000] Training [16/16] Loss: 0.01921 +Epoch [178/4000] Training metric {'Train/mean dice_metric': 0.9841409921646118, 'Train/mean miou_metric': 0.9687806367874146, 'Train/mean f1': 0.9812918901443481, 'Train/mean precision': 0.9760230779647827, 'Train/mean recall': 0.9866178631782532, 'Train/mean hd95_metric': 2.6038994789123535} +Epoch [178/4000] Validation [1/4] Loss: 0.17638 focal_loss 0.08875 dice_loss 0.08764 +Epoch [178/4000] Validation [2/4] Loss: 0.52026 focal_loss 0.22716 dice_loss 0.29310 +Epoch [178/4000] Validation [3/4] Loss: 0.09861 focal_loss 0.04119 dice_loss 0.05742 +Epoch [178/4000] Validation [4/4] Loss: 0.23443 focal_loss 0.12332 dice_loss 0.11111 +Epoch [178/4000] Validation metric {'Val/mean dice_metric': 0.958990216255188, 'Val/mean miou_metric': 0.9332486391067505, 'Val/mean f1': 0.9632604122161865, 'Val/mean precision': 0.9608308672904968, 'Val/mean recall': 0.9657022356987, 'Val/mean hd95_metric': 6.9569993019104} +Cheakpoint... +Epoch [178/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9590], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.958990216255188, 'Val/mean miou_metric': 0.9332486391067505, 'Val/mean f1': 0.9632604122161865, 'Val/mean precision': 0.9608308672904968, 'Val/mean recall': 0.9657022356987, 'Val/mean hd95_metric': 6.9569993019104} +Epoch [179/4000] Training [1/16] Loss: 0.05822 +Epoch [179/4000] Training [2/16] Loss: 0.02411 +Epoch [179/4000] Training [3/16] Loss: 0.01776 +Epoch [179/4000] Training [4/16] Loss: 0.01604 +Epoch [179/4000] Training [5/16] Loss: 0.02352 +Epoch [179/4000] Training [6/16] Loss: 0.01650 +Epoch [179/4000] Training [7/16] Loss: 0.02213 +Epoch [179/4000] Training [8/16] Loss: 0.02149 +Epoch [179/4000] Training [9/16] Loss: 0.02151 +Epoch [179/4000] Training [10/16] Loss: 0.02174 +Epoch [179/4000] Training [11/16] Loss: 0.01921 +Epoch [179/4000] Training [12/16] Loss: 0.02985 +Epoch [179/4000] Training [13/16] Loss: 0.02208 +Epoch [179/4000] Training [14/16] Loss: 0.02035 +Epoch [179/4000] Training [15/16] Loss: 0.02424 +Epoch [179/4000] Training [16/16] Loss: 0.03605 +Epoch [179/4000] Training metric {'Train/mean dice_metric': 0.9848052263259888, 'Train/mean miou_metric': 0.9700183272361755, 'Train/mean f1': 0.982171356678009, 'Train/mean precision': 0.9779305458068848, 'Train/mean recall': 0.9864491820335388, 'Train/mean hd95_metric': 2.252836227416992} +Epoch [179/4000] Validation [1/4] Loss: 0.09685 focal_loss 0.04151 dice_loss 0.05534 +Epoch [179/4000] Validation [2/4] Loss: 0.43362 focal_loss 0.19099 dice_loss 0.24263 +Epoch [179/4000] Validation [3/4] Loss: 0.12093 focal_loss 0.04840 dice_loss 0.07254 +Epoch [179/4000] Validation [4/4] Loss: 0.20240 focal_loss 0.09037 dice_loss 0.11203 +Epoch [179/4000] Validation metric {'Val/mean dice_metric': 0.9601802825927734, 'Val/mean miou_metric': 0.9353917241096497, 'Val/mean f1': 0.9639438986778259, 'Val/mean precision': 0.9576529860496521, 'Val/mean recall': 0.970318078994751, 'Val/mean hd95_metric': 7.542756080627441} +Cheakpoint... +Epoch [179/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9602], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9601802825927734, 'Val/mean miou_metric': 0.9353917241096497, 'Val/mean f1': 0.9639438986778259, 'Val/mean precision': 0.9576529860496521, 'Val/mean recall': 0.970318078994751, 'Val/mean hd95_metric': 7.542756080627441} +Epoch [180/4000] Training [1/16] Loss: 0.03052 +Epoch [180/4000] Training [2/16] Loss: 0.01659 +Epoch [180/4000] Training [3/16] Loss: 0.01445 +Epoch [180/4000] Training [4/16] Loss: 0.01849 +Epoch [180/4000] Training [5/16] Loss: 0.03094 +Epoch [180/4000] Training [6/16] Loss: 0.02134 +Epoch [180/4000] Training [7/16] Loss: 0.01759 +Epoch [180/4000] Training [8/16] Loss: 0.01777 +Epoch [180/4000] Training [9/16] Loss: 0.01977 +Epoch [180/4000] Training [10/16] Loss: 0.03259 +Epoch [180/4000] Training [11/16] Loss: 0.02858 +Epoch [180/4000] Training [12/16] Loss: 0.01620 +Epoch [180/4000] Training [13/16] Loss: 0.01951 +Epoch [180/4000] Training [14/16] Loss: 0.02022 +Epoch [180/4000] Training [15/16] Loss: 0.02323 +Epoch [180/4000] Training [16/16] Loss: 0.02161 +Epoch [180/4000] Training metric {'Train/mean dice_metric': 0.9840438365936279, 'Train/mean miou_metric': 0.9687457084655762, 'Train/mean f1': 0.9814767241477966, 'Train/mean precision': 0.9775474667549133, 'Train/mean recall': 0.9854376912117004, 'Train/mean hd95_metric': 2.7904436588287354} +Epoch [180/4000] Validation [1/4] Loss: 0.55032 focal_loss 0.38694 dice_loss 0.16338 +Epoch [180/4000] Validation [2/4] Loss: 0.54252 focal_loss 0.25896 dice_loss 0.28355 +Epoch [180/4000] Validation [3/4] Loss: 0.11247 focal_loss 0.04365 dice_loss 0.06882 +Epoch [180/4000] Validation [4/4] Loss: 0.26946 focal_loss 0.13487 dice_loss 0.13458 +Epoch [180/4000] Validation metric {'Val/mean dice_metric': 0.9562009572982788, 'Val/mean miou_metric': 0.930268406867981, 'Val/mean f1': 0.9591383934020996, 'Val/mean precision': 0.9631761908531189, 'Val/mean recall': 0.9551345109939575, 'Val/mean hd95_metric': 7.914973258972168} +Cheakpoint... +Epoch [180/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9562], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9562009572982788, 'Val/mean miou_metric': 0.930268406867981, 'Val/mean f1': 0.9591383934020996, 'Val/mean precision': 0.9631761908531189, 'Val/mean recall': 0.9551345109939575, 'Val/mean hd95_metric': 7.914973258972168} +Epoch [181/4000] Training [1/16] Loss: 0.01860 +Epoch [181/4000] Training [2/16] Loss: 0.02082 +Epoch [181/4000] Training [3/16] Loss: 0.02190 +Epoch [181/4000] Training [4/16] Loss: 0.02798 +Epoch [181/4000] Training [5/16] Loss: 0.03050 +Epoch [181/4000] Training [6/16] Loss: 0.02441 +Epoch [181/4000] Training [7/16] Loss: 0.01694 +Epoch [181/4000] Training [8/16] Loss: 0.02326 +Epoch [181/4000] Training [9/16] Loss: 0.03119 +Epoch [181/4000] Training [10/16] Loss: 0.01874 +Epoch [181/4000] Training [11/16] Loss: 0.01473 +Epoch [181/4000] Training [12/16] Loss: 0.04463 +Epoch [181/4000] Training [13/16] Loss: 0.05195 +Epoch [181/4000] Training [14/16] Loss: 0.06131 +Epoch [181/4000] Training [15/16] Loss: 0.02034 +Epoch [181/4000] Training [16/16] Loss: 0.02050 +Epoch [181/4000] Training metric {'Train/mean dice_metric': 0.9812233448028564, 'Train/mean miou_metric': 0.9639755487442017, 'Train/mean f1': 0.9797421097755432, 'Train/mean precision': 0.9753406047821045, 'Train/mean recall': 0.9841834902763367, 'Train/mean hd95_metric': 4.984206676483154} +Epoch [181/4000] Validation [1/4] Loss: 0.18556 focal_loss 0.09861 dice_loss 0.08696 +Epoch [181/4000] Validation [2/4] Loss: 0.35833 focal_loss 0.14708 dice_loss 0.21125 +Epoch [181/4000] Validation [3/4] Loss: 0.20095 focal_loss 0.09649 dice_loss 0.10446 +Epoch [181/4000] Validation [4/4] Loss: 0.29468 focal_loss 0.15278 dice_loss 0.14191 +Epoch [181/4000] Validation metric {'Val/mean dice_metric': 0.9541905522346497, 'Val/mean miou_metric': 0.9254773855209351, 'Val/mean f1': 0.9604018330574036, 'Val/mean precision': 0.9579372406005859, 'Val/mean recall': 0.9628790616989136, 'Val/mean hd95_metric': 10.749956130981445} +Cheakpoint... +Epoch [181/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9542], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9541905522346497, 'Val/mean miou_metric': 0.9254773855209351, 'Val/mean f1': 0.9604018330574036, 'Val/mean precision': 0.9579372406005859, 'Val/mean recall': 0.9628790616989136, 'Val/mean hd95_metric': 10.749956130981445} +Epoch [182/4000] Training [1/16] Loss: 0.02362 +Epoch [182/4000] Training [2/16] Loss: 0.01647 +Epoch [182/4000] Training [3/16] Loss: 0.03490 +Epoch [182/4000] Training [4/16] Loss: 0.02175 +Epoch [182/4000] Training [5/16] Loss: 0.02303 +Epoch [182/4000] Training [6/16] Loss: 0.02262 +Epoch [182/4000] Training [7/16] Loss: 0.02169 +Epoch [182/4000] Training [8/16] Loss: 0.02751 +Epoch [182/4000] Training [9/16] Loss: 0.02144 +Epoch [182/4000] Training [10/16] Loss: 0.02653 +Epoch [182/4000] Training [11/16] Loss: 0.01825 +Epoch [182/4000] Training [12/16] Loss: 0.01795 +Epoch [182/4000] Training [13/16] Loss: 0.03063 +Epoch [182/4000] Training [14/16] Loss: 0.02353 +Epoch [182/4000] Training [15/16] Loss: 0.01992 +Epoch [182/4000] Training [16/16] Loss: 0.01720 +Epoch [182/4000] Training metric {'Train/mean dice_metric': 0.9831534624099731, 'Train/mean miou_metric': 0.9673196077346802, 'Train/mean f1': 0.9807754158973694, 'Train/mean precision': 0.9753745794296265, 'Train/mean recall': 0.9862363338470459, 'Train/mean hd95_metric': 3.20078182220459} +Epoch [182/4000] Validation [1/4] Loss: 0.14896 focal_loss 0.07580 dice_loss 0.07316 +Epoch [182/4000] Validation [2/4] Loss: 0.18734 focal_loss 0.06041 dice_loss 0.12693 +Epoch [182/4000] Validation [3/4] Loss: 0.26206 focal_loss 0.13525 dice_loss 0.12681 +Epoch [182/4000] Validation [4/4] Loss: 0.26533 focal_loss 0.12155 dice_loss 0.14378 +Epoch [182/4000] Validation metric {'Val/mean dice_metric': 0.957869827747345, 'Val/mean miou_metric': 0.9315641522407532, 'Val/mean f1': 0.9624363780021667, 'Val/mean precision': 0.9587516188621521, 'Val/mean recall': 0.9661494493484497, 'Val/mean hd95_metric': 8.481670379638672} +Cheakpoint... +Epoch [182/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9579], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.957869827747345, 'Val/mean miou_metric': 0.9315641522407532, 'Val/mean f1': 0.9624363780021667, 'Val/mean precision': 0.9587516188621521, 'Val/mean recall': 0.9661494493484497, 'Val/mean hd95_metric': 8.481670379638672} +Epoch [183/4000] Training [1/16] Loss: 0.02474 +Epoch [183/4000] Training [2/16] Loss: 0.01615 +Epoch [183/4000] Training [3/16] Loss: 0.01874 +Epoch [183/4000] Training [4/16] Loss: 0.02280 +Epoch [183/4000] Training [5/16] Loss: 0.02775 +Epoch [183/4000] Training [6/16] Loss: 0.04020 +Epoch [183/4000] Training [7/16] Loss: 0.02235 +Epoch [183/4000] Training [8/16] Loss: 0.02153 +Epoch [183/4000] Training [9/16] Loss: 0.02243 +Epoch [183/4000] Training [10/16] Loss: 0.02074 +Epoch [183/4000] Training [11/16] Loss: 0.02068 +Epoch [183/4000] Training [12/16] Loss: 0.03698 +Epoch [183/4000] Training [13/16] Loss: 0.01999 +Epoch [183/4000] Training [14/16] Loss: 0.02285 +Epoch [183/4000] Training [15/16] Loss: 0.02284 +Epoch [183/4000] Training [16/16] Loss: 0.01861 +Epoch [183/4000] Training metric {'Train/mean dice_metric': 0.9832164645195007, 'Train/mean miou_metric': 0.9674637317657471, 'Train/mean f1': 0.9817876815795898, 'Train/mean precision': 0.9776197075843811, 'Train/mean recall': 0.9859912991523743, 'Train/mean hd95_metric': 2.560704231262207} +Epoch [183/4000] Validation [1/4] Loss: 0.14687 focal_loss 0.06977 dice_loss 0.07710 +Epoch [183/4000] Validation [2/4] Loss: 0.29749 focal_loss 0.11940 dice_loss 0.17809 +Epoch [183/4000] Validation [3/4] Loss: 0.21114 focal_loss 0.13368 dice_loss 0.07746 +Epoch [183/4000] Validation [4/4] Loss: 0.30286 focal_loss 0.16195 dice_loss 0.14092 +Epoch [183/4000] Validation metric {'Val/mean dice_metric': 0.9573427438735962, 'Val/mean miou_metric': 0.9317812919616699, 'Val/mean f1': 0.9627513289451599, 'Val/mean precision': 0.9617162942886353, 'Val/mean recall': 0.963788628578186, 'Val/mean hd95_metric': 7.4908552169799805} +Cheakpoint... +Epoch [183/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9573], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573427438735962, 'Val/mean miou_metric': 0.9317812919616699, 'Val/mean f1': 0.9627513289451599, 'Val/mean precision': 0.9617162942886353, 'Val/mean recall': 0.963788628578186, 'Val/mean hd95_metric': 7.4908552169799805} +Epoch [184/4000] Training [1/16] Loss: 0.01876 +Epoch [184/4000] Training [2/16] Loss: 0.02224 +Epoch [184/4000] Training [3/16] Loss: 0.01960 +Epoch [184/4000] Training [4/16] Loss: 0.02503 +Epoch [184/4000] Training [5/16] Loss: 0.02644 +Epoch [184/4000] Training [6/16] Loss: 0.02221 +Epoch [184/4000] Training [7/16] Loss: 0.02703 +Epoch [184/4000] Training [8/16] Loss: 0.02481 +Epoch [184/4000] Training [9/16] Loss: 0.02156 +Epoch [184/4000] Training [10/16] Loss: 0.01507 +Epoch [184/4000] Training [11/16] Loss: 0.04006 +Epoch [184/4000] Training [12/16] Loss: 0.02205 +Epoch [184/4000] Training [13/16] Loss: 0.01507 +Epoch [184/4000] Training [14/16] Loss: 0.02220 +Epoch [184/4000] Training [15/16] Loss: 0.05973 +Epoch [184/4000] Training [16/16] Loss: 0.01917 +Epoch [184/4000] Training metric {'Train/mean dice_metric': 0.9827430248260498, 'Train/mean miou_metric': 0.9665675163269043, 'Train/mean f1': 0.9817821383476257, 'Train/mean precision': 0.9770433902740479, 'Train/mean recall': 0.9865670800209045, 'Train/mean hd95_metric': 2.8481340408325195} +Epoch [184/4000] Validation [1/4] Loss: 0.43263 focal_loss 0.27218 dice_loss 0.16045 +Epoch [184/4000] Validation [2/4] Loss: 0.36807 focal_loss 0.16290 dice_loss 0.20516 +Epoch [184/4000] Validation [3/4] Loss: 0.16871 focal_loss 0.07396 dice_loss 0.09476 +Epoch [184/4000] Validation [4/4] Loss: 0.23858 focal_loss 0.12075 dice_loss 0.11783 +Epoch [184/4000] Validation metric {'Val/mean dice_metric': 0.9579712152481079, 'Val/mean miou_metric': 0.9306168556213379, 'Val/mean f1': 0.9630143642425537, 'Val/mean precision': 0.9643362760543823, 'Val/mean recall': 0.961696207523346, 'Val/mean hd95_metric': 8.54106616973877} +Cheakpoint... +Epoch [184/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9580], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9579712152481079, 'Val/mean miou_metric': 0.9306168556213379, 'Val/mean f1': 0.9630143642425537, 'Val/mean precision': 0.9643362760543823, 'Val/mean recall': 0.961696207523346, 'Val/mean hd95_metric': 8.54106616973877} +Epoch [185/4000] Training [1/16] Loss: 0.03594 +Epoch [185/4000] Training [2/16] Loss: 0.01792 +Epoch [185/4000] Training [3/16] Loss: 0.03016 +Epoch [185/4000] Training [4/16] Loss: 0.04032 +Epoch [185/4000] Training [5/16] Loss: 0.02253 +Epoch [185/4000] Training [6/16] Loss: 0.02470 +Epoch [185/4000] Training [7/16] Loss: 0.02703 +Epoch [185/4000] Training [8/16] Loss: 0.09646 +Epoch [185/4000] Training [9/16] Loss: 0.02331 +Epoch [185/4000] Training [10/16] Loss: 0.02341 +Epoch [185/4000] Training [11/16] Loss: 0.01654 +Epoch [185/4000] Training [12/16] Loss: 0.04633 +Epoch [185/4000] Training [13/16] Loss: 0.02541 +Epoch [185/4000] Training [14/16] Loss: 0.03078 +Epoch [185/4000] Training [15/16] Loss: 0.05258 +Epoch [185/4000] Training [16/16] Loss: 0.02892 +Epoch [185/4000] Training metric {'Train/mean dice_metric': 0.9791607856750488, 'Train/mean miou_metric': 0.9598507881164551, 'Train/mean f1': 0.9780184626579285, 'Train/mean precision': 0.9749082922935486, 'Train/mean recall': 0.9811485409736633, 'Train/mean hd95_metric': 3.9705018997192383} +Epoch [185/4000] Validation [1/4] Loss: 0.34159 focal_loss 0.21927 dice_loss 0.12233 +Epoch [185/4000] Validation [2/4] Loss: 0.21076 focal_loss 0.08166 dice_loss 0.12911 +Epoch [185/4000] Validation [3/4] Loss: 0.19182 focal_loss 0.09551 dice_loss 0.09631 +Epoch [185/4000] Validation [4/4] Loss: 0.29688 focal_loss 0.14840 dice_loss 0.14847 +Epoch [185/4000] Validation metric {'Val/mean dice_metric': 0.951982319355011, 'Val/mean miou_metric': 0.9227851629257202, 'Val/mean f1': 0.956804633140564, 'Val/mean precision': 0.959314227104187, 'Val/mean recall': 0.9543080925941467, 'Val/mean hd95_metric': 9.129096984863281} +Cheakpoint... +Epoch [185/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9520], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.951982319355011, 'Val/mean miou_metric': 0.9227851629257202, 'Val/mean f1': 0.956804633140564, 'Val/mean precision': 0.959314227104187, 'Val/mean recall': 0.9543080925941467, 'Val/mean hd95_metric': 9.129096984863281} +Epoch [186/4000] Training [1/16] Loss: 0.02202 +Epoch [186/4000] Training [2/16] Loss: 0.02326 +Epoch [186/4000] Training [3/16] Loss: 0.01724 +Epoch [186/4000] Training [4/16] Loss: 0.01990 +Epoch [186/4000] Training [5/16] Loss: 0.02606 +Epoch [186/4000] Training [6/16] Loss: 0.04506 +Epoch [186/4000] Training [7/16] Loss: 0.02022 +Epoch [186/4000] Training [8/16] Loss: 0.02307 +Epoch [186/4000] Training [9/16] Loss: 0.01841 +Epoch [186/4000] Training [10/16] Loss: 0.02488 +Epoch [186/4000] Training [11/16] Loss: 0.03314 +Epoch [186/4000] Training [12/16] Loss: 0.02313 +Epoch [186/4000] Training [13/16] Loss: 0.03050 +Epoch [186/4000] Training [14/16] Loss: 0.02373 +Epoch [186/4000] Training [15/16] Loss: 0.02554 +Epoch [186/4000] Training [16/16] Loss: 0.02487 +Epoch [186/4000] Training metric {'Train/mean dice_metric': 0.9790818095207214, 'Train/mean miou_metric': 0.9613631963729858, 'Train/mean f1': 0.9795742034912109, 'Train/mean precision': 0.974739134311676, 'Train/mean recall': 0.9844574332237244, 'Train/mean hd95_metric': 4.2101054191589355} +Epoch [186/4000] Validation [1/4] Loss: 0.15411 focal_loss 0.07643 dice_loss 0.07768 +Epoch [186/4000] Validation [2/4] Loss: 0.32524 focal_loss 0.11031 dice_loss 0.21492 +Epoch [186/4000] Validation [3/4] Loss: 0.24677 focal_loss 0.13189 dice_loss 0.11488 +Epoch [186/4000] Validation [4/4] Loss: 0.25903 focal_loss 0.11345 dice_loss 0.14558 +Epoch [186/4000] Validation metric {'Val/mean dice_metric': 0.9526904821395874, 'Val/mean miou_metric': 0.9240821599960327, 'Val/mean f1': 0.9582124948501587, 'Val/mean precision': 0.9558719992637634, 'Val/mean recall': 0.9605643153190613, 'Val/mean hd95_metric': 9.606611251831055} +Cheakpoint... +Epoch [186/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9527], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9526904821395874, 'Val/mean miou_metric': 0.9240821599960327, 'Val/mean f1': 0.9582124948501587, 'Val/mean precision': 0.9558719992637634, 'Val/mean recall': 0.9605643153190613, 'Val/mean hd95_metric': 9.606611251831055} +Epoch [187/4000] Training [1/16] Loss: 0.01975 +Epoch [187/4000] Training [2/16] Loss: 0.01948 +Epoch [187/4000] Training [3/16] Loss: 0.01884 +Epoch [187/4000] Training [4/16] Loss: 0.03150 +Epoch [187/4000] Training [5/16] Loss: 0.02886 +Epoch [187/4000] Training [6/16] Loss: 0.01887 +Epoch [187/4000] Training [7/16] Loss: 0.03176 +Epoch [187/4000] Training [8/16] Loss: 0.02619 +Epoch [187/4000] Training [9/16] Loss: 0.02348 +Epoch [187/4000] Training [10/16] Loss: 0.01926 +Epoch [187/4000] Training [11/16] Loss: 0.02282 +Epoch [187/4000] Training [12/16] Loss: 0.01832 +Epoch [187/4000] Training [13/16] Loss: 0.01910 +Epoch [187/4000] Training [14/16] Loss: 0.02959 +Epoch [187/4000] Training [15/16] Loss: 0.02147 +Epoch [187/4000] Training [16/16] Loss: 0.02181 +Epoch [187/4000] Training metric {'Train/mean dice_metric': 0.9822266101837158, 'Train/mean miou_metric': 0.9653412103652954, 'Train/mean f1': 0.9805670380592346, 'Train/mean precision': 0.9761770963668823, 'Train/mean recall': 0.9849966168403625, 'Train/mean hd95_metric': 3.183518886566162} +Epoch [187/4000] Validation [1/4] Loss: 0.52660 focal_loss 0.40760 dice_loss 0.11899 +Epoch [187/4000] Validation [2/4] Loss: 0.37577 focal_loss 0.13947 dice_loss 0.23629 +Epoch [187/4000] Validation [3/4] Loss: 0.24502 focal_loss 0.12291 dice_loss 0.12212 +Epoch [187/4000] Validation [4/4] Loss: 0.33415 focal_loss 0.18216 dice_loss 0.15199 +Epoch [187/4000] Validation metric {'Val/mean dice_metric': 0.9543453454971313, 'Val/mean miou_metric': 0.9260486364364624, 'Val/mean f1': 0.9584826231002808, 'Val/mean precision': 0.9616767764091492, 'Val/mean recall': 0.9553097486495972, 'Val/mean hd95_metric': 8.12274169921875} +Cheakpoint... +Epoch [187/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9543], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9543453454971313, 'Val/mean miou_metric': 0.9260486364364624, 'Val/mean f1': 0.9584826231002808, 'Val/mean precision': 0.9616767764091492, 'Val/mean recall': 0.9553097486495972, 'Val/mean hd95_metric': 8.12274169921875} +Epoch [188/4000] Training [1/16] Loss: 0.02441 +Epoch [188/4000] Training [2/16] Loss: 0.02131 +Epoch [188/4000] Training [3/16] Loss: 0.01962 +Epoch [188/4000] Training [4/16] Loss: 0.02551 +Epoch [188/4000] Training [5/16] Loss: 0.01681 +Epoch [188/4000] Training [6/16] Loss: 0.02923 +Epoch [188/4000] Training [7/16] Loss: 0.01746 +Epoch [188/4000] Training [8/16] Loss: 0.02140 +Epoch [188/4000] Training [9/16] Loss: 0.02934 +Epoch [188/4000] Training [10/16] Loss: 0.02258 +Epoch [188/4000] Training [11/16] Loss: 0.02369 +Epoch [188/4000] Training [12/16] Loss: 0.01834 +Epoch [188/4000] Training [13/16] Loss: 0.02141 +Epoch [188/4000] Training [14/16] Loss: 0.02369 +Epoch [188/4000] Training [15/16] Loss: 0.02182 +Epoch [188/4000] Training [16/16] Loss: 0.02906 +Epoch [188/4000] Training metric {'Train/mean dice_metric': 0.983606219291687, 'Train/mean miou_metric': 0.967806339263916, 'Train/mean f1': 0.9812516570091248, 'Train/mean precision': 0.9764646887779236, 'Train/mean recall': 0.986085832118988, 'Train/mean hd95_metric': 2.7494351863861084} +Epoch [188/4000] Validation [1/4] Loss: 0.56197 focal_loss 0.43981 dice_loss 0.12216 +Epoch [188/4000] Validation [2/4] Loss: 0.25513 focal_loss 0.09322 dice_loss 0.16191 +Epoch [188/4000] Validation [3/4] Loss: 0.24043 focal_loss 0.11825 dice_loss 0.12218 +Epoch [188/4000] Validation [4/4] Loss: 0.31617 focal_loss 0.15911 dice_loss 0.15706 +Epoch [188/4000] Validation metric {'Val/mean dice_metric': 0.9561843872070312, 'Val/mean miou_metric': 0.9284704327583313, 'Val/mean f1': 0.9587861895561218, 'Val/mean precision': 0.9612874388694763, 'Val/mean recall': 0.9562981128692627, 'Val/mean hd95_metric': 8.940115928649902} +Cheakpoint... +Epoch [188/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9562], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9561843872070312, 'Val/mean miou_metric': 0.9284704327583313, 'Val/mean f1': 0.9587861895561218, 'Val/mean precision': 0.9612874388694763, 'Val/mean recall': 0.9562981128692627, 'Val/mean hd95_metric': 8.940115928649902} +Epoch [189/4000] Training [1/16] Loss: 0.01877 +Epoch [189/4000] Training [2/16] Loss: 0.02135 +Epoch [189/4000] Training [3/16] Loss: 0.01874 +Epoch [189/4000] Training [4/16] Loss: 0.01998 +Epoch [189/4000] Training [5/16] Loss: 0.01806 +Epoch [189/4000] Training [6/16] Loss: 0.02366 +Epoch [189/4000] Training [7/16] Loss: 0.01863 +Epoch [189/4000] Training [8/16] Loss: 0.01964 +Epoch [189/4000] Training [9/16] Loss: 0.03007 +Epoch [189/4000] Training [10/16] Loss: 0.02440 +Epoch [189/4000] Training [11/16] Loss: 0.01738 +Epoch [189/4000] Training [12/16] Loss: 0.01983 +Epoch [189/4000] Training [13/16] Loss: 0.02129 +Epoch [189/4000] Training [14/16] Loss: 0.07710 +Epoch [189/4000] Training [15/16] Loss: 0.02748 +Epoch [189/4000] Training [16/16] Loss: 0.02171 +Epoch [189/4000] Training metric {'Train/mean dice_metric': 0.9829986095428467, 'Train/mean miou_metric': 0.9669106602668762, 'Train/mean f1': 0.9803586602210999, 'Train/mean precision': 0.9751782417297363, 'Train/mean recall': 0.9855943918228149, 'Train/mean hd95_metric': 2.7714169025421143} +Epoch [189/4000] Validation [1/4] Loss: 0.38114 focal_loss 0.26604 dice_loss 0.11510 +Epoch [189/4000] Validation [2/4] Loss: 0.34746 focal_loss 0.14650 dice_loss 0.20095 +Epoch [189/4000] Validation [3/4] Loss: 0.32047 focal_loss 0.17981 dice_loss 0.14066 +Epoch [189/4000] Validation [4/4] Loss: 0.23613 focal_loss 0.12438 dice_loss 0.11175 +Epoch [189/4000] Validation metric {'Val/mean dice_metric': 0.9579164385795593, 'Val/mean miou_metric': 0.9318793416023254, 'Val/mean f1': 0.96124267578125, 'Val/mean precision': 0.9580870270729065, 'Val/mean recall': 0.9644191265106201, 'Val/mean hd95_metric': 8.069364547729492} +Cheakpoint... +Epoch [189/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9579], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9579164385795593, 'Val/mean miou_metric': 0.9318793416023254, 'Val/mean f1': 0.96124267578125, 'Val/mean precision': 0.9580870270729065, 'Val/mean recall': 0.9644191265106201, 'Val/mean hd95_metric': 8.069364547729492} +Epoch [190/4000] Training [1/16] Loss: 0.01810 +Epoch [190/4000] Training [2/16] Loss: 0.02041 +Epoch [190/4000] Training [3/16] Loss: 0.02040 +Epoch [190/4000] Training [4/16] Loss: 0.02033 +Epoch [190/4000] Training [5/16] Loss: 0.02515 +Epoch [190/4000] Training [6/16] Loss: 0.01819 +Epoch [190/4000] Training [7/16] Loss: 0.04904 +Epoch [190/4000] Training [8/16] Loss: 0.02788 +Epoch [190/4000] Training [9/16] Loss: 0.01883 +Epoch [190/4000] Training [10/16] Loss: 0.07446 +Epoch [190/4000] Training [11/16] Loss: 0.03198 +Epoch [190/4000] Training [12/16] Loss: 0.02271 +Epoch [190/4000] Training [13/16] Loss: 0.02076 +Epoch [190/4000] Training [14/16] Loss: 0.02600 +Epoch [190/4000] Training [15/16] Loss: 0.02232 +Epoch [190/4000] Training [16/16] Loss: 0.02045 +Epoch [190/4000] Training metric {'Train/mean dice_metric': 0.9820601940155029, 'Train/mean miou_metric': 0.9656687378883362, 'Train/mean f1': 0.9802114963531494, 'Train/mean precision': 0.9772464036941528, 'Train/mean recall': 0.9831946492195129, 'Train/mean hd95_metric': 2.918097496032715} +Epoch [190/4000] Validation [1/4] Loss: 0.45796 focal_loss 0.32889 dice_loss 0.12907 +Epoch [190/4000] Validation [2/4] Loss: 0.16487 focal_loss 0.05152 dice_loss 0.11336 +Epoch [190/4000] Validation [3/4] Loss: 0.33006 focal_loss 0.18194 dice_loss 0.14812 +Epoch [190/4000] Validation [4/4] Loss: 0.18416 focal_loss 0.07638 dice_loss 0.10778 +Epoch [190/4000] Validation metric {'Val/mean dice_metric': 0.955522894859314, 'Val/mean miou_metric': 0.9284575581550598, 'Val/mean f1': 0.9579392075538635, 'Val/mean precision': 0.9532864689826965, 'Val/mean recall': 0.9626374244689941, 'Val/mean hd95_metric': 9.504800796508789} +Cheakpoint... +Epoch [190/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9555], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.955522894859314, 'Val/mean miou_metric': 0.9284575581550598, 'Val/mean f1': 0.9579392075538635, 'Val/mean precision': 0.9532864689826965, 'Val/mean recall': 0.9626374244689941, 'Val/mean hd95_metric': 9.504800796508789} +Epoch [191/4000] Training [1/16] Loss: 0.02224 +Epoch [191/4000] Training [2/16] Loss: 0.01665 +Epoch [191/4000] Training [3/16] Loss: 0.04470 +Epoch [191/4000] Training [4/16] Loss: 0.02909 +Epoch [191/4000] Training [5/16] Loss: 0.05120 +Epoch [191/4000] Training [6/16] Loss: 0.01857 +Epoch [191/4000] Training [7/16] Loss: 0.01910 +Epoch [191/4000] Training [8/16] Loss: 0.02398 +Epoch [191/4000] Training [9/16] Loss: 0.02931 +Epoch [191/4000] Training [10/16] Loss: 0.03229 +Epoch [191/4000] Training [11/16] Loss: 0.02644 +Epoch [191/4000] Training [12/16] Loss: 0.03681 +Epoch [191/4000] Training [13/16] Loss: 0.02169 +Epoch [191/4000] Training [14/16] Loss: 0.02537 +Epoch [191/4000] Training [15/16] Loss: 0.11951 +Epoch [191/4000] Training [16/16] Loss: 0.02629 +Epoch [191/4000] Training metric {'Train/mean dice_metric': 0.9796968698501587, 'Train/mean miou_metric': 0.9613434076309204, 'Train/mean f1': 0.9773197174072266, 'Train/mean precision': 0.9743750095367432, 'Train/mean recall': 0.9802822470664978, 'Train/mean hd95_metric': 4.434041976928711} +Epoch [191/4000] Validation [1/4] Loss: 0.09031 focal_loss 0.04231 dice_loss 0.04800 +Epoch [191/4000] Validation [2/4] Loss: 0.32747 focal_loss 0.14462 dice_loss 0.18284 +Epoch [191/4000] Validation [3/4] Loss: 0.22127 focal_loss 0.10051 dice_loss 0.12077 +Epoch [191/4000] Validation [4/4] Loss: 0.20974 focal_loss 0.09219 dice_loss 0.11755 +Epoch [191/4000] Validation metric {'Val/mean dice_metric': 0.9554357528686523, 'Val/mean miou_metric': 0.9258148074150085, 'Val/mean f1': 0.9568032026290894, 'Val/mean precision': 0.9445975422859192, 'Val/mean recall': 0.9693284034729004, 'Val/mean hd95_metric': 11.944119453430176} +Cheakpoint... +Epoch [191/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9554], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9554357528686523, 'Val/mean miou_metric': 0.9258148074150085, 'Val/mean f1': 0.9568032026290894, 'Val/mean precision': 0.9445975422859192, 'Val/mean recall': 0.9693284034729004, 'Val/mean hd95_metric': 11.944119453430176} +Epoch [192/4000] Training [1/16] Loss: 0.02792 +Epoch [192/4000] Training [2/16] Loss: 0.02197 +Epoch [192/4000] Training [3/16] Loss: 0.01808 +Epoch [192/4000] Training [4/16] Loss: 0.07154 +Epoch [192/4000] Training [5/16] Loss: 0.02185 +Epoch [192/4000] Training [6/16] Loss: 0.02031 +Epoch [192/4000] Training [7/16] Loss: 0.02036 +Epoch [192/4000] Training [8/16] Loss: 0.04142 +Epoch [192/4000] Training [9/16] Loss: 0.02185 +Epoch [192/4000] Training [10/16] Loss: 0.02289 +Epoch [192/4000] Training [11/16] Loss: 0.02133 +Epoch [192/4000] Training [12/16] Loss: 0.02871 +Epoch [192/4000] Training [13/16] Loss: 0.02774 +Epoch [192/4000] Training [14/16] Loss: 0.03572 +Epoch [192/4000] Training [15/16] Loss: 0.03771 +Epoch [192/4000] Training [16/16] Loss: 0.04262 +Epoch [192/4000] Training metric {'Train/mean dice_metric': 0.9805388450622559, 'Train/mean miou_metric': 0.9623526930809021, 'Train/mean f1': 0.9785913825035095, 'Train/mean precision': 0.9730089902877808, 'Train/mean recall': 0.9842381477355957, 'Train/mean hd95_metric': 4.312722206115723} +Epoch [192/4000] Validation [1/4] Loss: 0.25341 focal_loss 0.13020 dice_loss 0.12321 +Epoch [192/4000] Validation [2/4] Loss: 0.29299 focal_loss 0.07652 dice_loss 0.21647 +Epoch [192/4000] Validation [3/4] Loss: 0.15772 focal_loss 0.07446 dice_loss 0.08325 +Epoch [192/4000] Validation [4/4] Loss: 0.27364 focal_loss 0.13491 dice_loss 0.13873 +Epoch [192/4000] Validation metric {'Val/mean dice_metric': 0.9532042741775513, 'Val/mean miou_metric': 0.9243288040161133, 'Val/mean f1': 0.9560893774032593, 'Val/mean precision': 0.9533991813659668, 'Val/mean recall': 0.9587948322296143, 'Val/mean hd95_metric': 9.797004699707031} +Cheakpoint... +Epoch [192/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9532], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9532042741775513, 'Val/mean miou_metric': 0.9243288040161133, 'Val/mean f1': 0.9560893774032593, 'Val/mean precision': 0.9533991813659668, 'Val/mean recall': 0.9587948322296143, 'Val/mean hd95_metric': 9.797004699707031} +Epoch [193/4000] Training [1/16] Loss: 0.02111 +Epoch [193/4000] Training [2/16] Loss: 0.02955 +Epoch [193/4000] Training [3/16] Loss: 0.01704 +Epoch [193/4000] Training [4/16] Loss: 0.02575 +Epoch [193/4000] Training [5/16] Loss: 0.02257 +Epoch [193/4000] Training [6/16] Loss: 0.02069 +Epoch [193/4000] Training [7/16] Loss: 0.02255 +Epoch [193/4000] Training [8/16] Loss: 0.02672 +Epoch [193/4000] Training [9/16] Loss: 0.02236 +Epoch [193/4000] Training [10/16] Loss: 0.02357 +Epoch [193/4000] Training [11/16] Loss: 0.01758 +Epoch [193/4000] Training [12/16] Loss: 0.02177 +Epoch [193/4000] Training [13/16] Loss: 0.02524 +Epoch [193/4000] Training [14/16] Loss: 0.08078 +Epoch [193/4000] Training [15/16] Loss: 0.02143 +Epoch [193/4000] Training [16/16] Loss: 0.01968 +Epoch [193/4000] Training metric {'Train/mean dice_metric': 0.9822602272033691, 'Train/mean miou_metric': 0.9653472900390625, 'Train/mean f1': 0.9800184369087219, 'Train/mean precision': 0.9767205119132996, 'Train/mean recall': 0.9833387136459351, 'Train/mean hd95_metric': 3.237898349761963} +Epoch [193/4000] Validation [1/4] Loss: 0.11572 focal_loss 0.05819 dice_loss 0.05753 +Epoch [193/4000] Validation [2/4] Loss: 0.24756 focal_loss 0.09240 dice_loss 0.15516 +Epoch [193/4000] Validation [3/4] Loss: 0.30457 focal_loss 0.16462 dice_loss 0.13995 +Epoch [193/4000] Validation [4/4] Loss: 0.21523 focal_loss 0.09023 dice_loss 0.12500 +Epoch [193/4000] Validation metric {'Val/mean dice_metric': 0.9545243978500366, 'Val/mean miou_metric': 0.9256622195243835, 'Val/mean f1': 0.9582486152648926, 'Val/mean precision': 0.9512937068939209, 'Val/mean recall': 0.9653059244155884, 'Val/mean hd95_metric': 9.377151489257812} +Cheakpoint... +Epoch [193/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9545], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9545243978500366, 'Val/mean miou_metric': 0.9256622195243835, 'Val/mean f1': 0.9582486152648926, 'Val/mean precision': 0.9512937068939209, 'Val/mean recall': 0.9653059244155884, 'Val/mean hd95_metric': 9.377151489257812} +Epoch [194/4000] Training [1/16] Loss: 0.02703 +Epoch [194/4000] Training [2/16] Loss: 0.02290 +Epoch [194/4000] Training [3/16] Loss: 0.02554 +Epoch [194/4000] Training [4/16] Loss: 0.01723 +Epoch [194/4000] Training [5/16] Loss: 0.01870 +Epoch [194/4000] Training [6/16] Loss: 0.02144 +Epoch [194/4000] Training [7/16] Loss: 0.02530 +Epoch [194/4000] Training [8/16] Loss: 0.01835 +Epoch [194/4000] Training [9/16] Loss: 0.03206 +Epoch [194/4000] Training [10/16] Loss: 0.02181 +Epoch [194/4000] Training [11/16] Loss: 0.01907 +Epoch [194/4000] Training [12/16] Loss: 0.02723 +Epoch [194/4000] Training [13/16] Loss: 0.02381 +Epoch [194/4000] Training [14/16] Loss: 0.01750 +Epoch [194/4000] Training [15/16] Loss: 0.01931 +Epoch [194/4000] Training [16/16] Loss: 0.01970 +Epoch [194/4000] Training metric {'Train/mean dice_metric': 0.9840167760848999, 'Train/mean miou_metric': 0.9684985876083374, 'Train/mean f1': 0.9808065295219421, 'Train/mean precision': 0.9755749702453613, 'Train/mean recall': 0.9860944747924805, 'Train/mean hd95_metric': 2.532712936401367} +Epoch [194/4000] Validation [1/4] Loss: 0.10840 focal_loss 0.05442 dice_loss 0.05398 +Epoch [194/4000] Validation [2/4] Loss: 0.31587 focal_loss 0.10615 dice_loss 0.20972 +Epoch [194/4000] Validation [3/4] Loss: 0.18793 focal_loss 0.08705 dice_loss 0.10088 +Epoch [194/4000] Validation [4/4] Loss: 0.18751 focal_loss 0.08016 dice_loss 0.10736 +Epoch [194/4000] Validation metric {'Val/mean dice_metric': 0.9592965841293335, 'Val/mean miou_metric': 0.9333483576774597, 'Val/mean f1': 0.9611091613769531, 'Val/mean precision': 0.9536091685295105, 'Val/mean recall': 0.9687281250953674, 'Val/mean hd95_metric': 7.960122585296631} +Cheakpoint... +Epoch [194/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9592965841293335, 'Val/mean miou_metric': 0.9333483576774597, 'Val/mean f1': 0.9611091613769531, 'Val/mean precision': 0.9536091685295105, 'Val/mean recall': 0.9687281250953674, 'Val/mean hd95_metric': 7.960122585296631} +Epoch [195/4000] Training [1/16] Loss: 0.01539 +Epoch [195/4000] Training [2/16] Loss: 0.01504 +Epoch [195/4000] Training [3/16] Loss: 0.02304 +Epoch [195/4000] Training [4/16] Loss: 0.02205 +Epoch [195/4000] Training [5/16] Loss: 0.01663 +Epoch [195/4000] Training [6/16] Loss: 0.02519 +Epoch [195/4000] Training [7/16] Loss: 0.01859 +Epoch [195/4000] Training [8/16] Loss: 0.01696 +Epoch [195/4000] Training [9/16] Loss: 0.02018 +Epoch [195/4000] Training [10/16] Loss: 0.07984 +Epoch [195/4000] Training [11/16] Loss: 0.01809 +Epoch [195/4000] Training [12/16] Loss: 0.01521 +Epoch [195/4000] Training [13/16] Loss: 0.02111 +Epoch [195/4000] Training [14/16] Loss: 0.01726 +Epoch [195/4000] Training [15/16] Loss: 0.02194 +Epoch [195/4000] Training [16/16] Loss: 0.01561 +Epoch [195/4000] Training metric {'Train/mean dice_metric': 0.9860928058624268, 'Train/mean miou_metric': 0.9724808931350708, 'Train/mean f1': 0.9826512932777405, 'Train/mean precision': 0.9786344170570374, 'Train/mean recall': 0.9867013692855835, 'Train/mean hd95_metric': 2.144317150115967} +Epoch [195/4000] Validation [1/4] Loss: 0.11787 focal_loss 0.06162 dice_loss 0.05626 +Epoch [195/4000] Validation [2/4] Loss: 0.27640 focal_loss 0.09203 dice_loss 0.18437 +Epoch [195/4000] Validation [3/4] Loss: 0.11717 focal_loss 0.04507 dice_loss 0.07210 +Epoch [195/4000] Validation [4/4] Loss: 0.22304 focal_loss 0.10782 dice_loss 0.11522 +Epoch [195/4000] Validation metric {'Val/mean dice_metric': 0.9608041644096375, 'Val/mean miou_metric': 0.9361766576766968, 'Val/mean f1': 0.9628964066505432, 'Val/mean precision': 0.955227255821228, 'Val/mean recall': 0.9706897139549255, 'Val/mean hd95_metric': 7.994515895843506} +Cheakpoint... +Epoch [195/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608041644096375, 'Val/mean miou_metric': 0.9361766576766968, 'Val/mean f1': 0.9628964066505432, 'Val/mean precision': 0.955227255821228, 'Val/mean recall': 0.9706897139549255, 'Val/mean hd95_metric': 7.994515895843506} +Epoch [196/4000] Training [1/16] Loss: 0.01571 +Epoch [196/4000] Training [2/16] Loss: 0.01405 +Epoch [196/4000] Training [3/16] Loss: 0.01615 +Epoch [196/4000] Training [4/16] Loss: 0.02087 +Epoch [196/4000] Training [5/16] Loss: 0.02062 +Epoch [196/4000] Training [6/16] Loss: 0.06184 +Epoch [196/4000] Training [7/16] Loss: 0.02101 +Epoch [196/4000] Training [8/16] Loss: 0.02171 +Epoch [196/4000] Training [9/16] Loss: 0.02074 +Epoch [196/4000] Training [10/16] Loss: 0.01873 +Epoch [196/4000] Training [11/16] Loss: 0.01752 +Epoch [196/4000] Training [12/16] Loss: 0.02119 +Epoch [196/4000] Training [13/16] Loss: 0.02412 +Epoch [196/4000] Training [14/16] Loss: 0.01363 +Epoch [196/4000] Training [15/16] Loss: 0.02561 +Epoch [196/4000] Training [16/16] Loss: 0.02608 +Epoch [196/4000] Training metric {'Train/mean dice_metric': 0.9854509830474854, 'Train/mean miou_metric': 0.9712839126586914, 'Train/mean f1': 0.9826477766036987, 'Train/mean precision': 0.9783307909965515, 'Train/mean recall': 0.9870030879974365, 'Train/mean hd95_metric': 2.3519511222839355} +Epoch [196/4000] Validation [1/4] Loss: 0.12507 focal_loss 0.06522 dice_loss 0.05986 +Epoch [196/4000] Validation [2/4] Loss: 0.31571 focal_loss 0.14282 dice_loss 0.17289 +Epoch [196/4000] Validation [3/4] Loss: 0.20210 focal_loss 0.09841 dice_loss 0.10369 +Epoch [196/4000] Validation [4/4] Loss: 0.33501 focal_loss 0.17796 dice_loss 0.15705 +Epoch [196/4000] Validation metric {'Val/mean dice_metric': 0.9609186053276062, 'Val/mean miou_metric': 0.9359208941459656, 'Val/mean f1': 0.9654457569122314, 'Val/mean precision': 0.962532103061676, 'Val/mean recall': 0.9683772325515747, 'Val/mean hd95_metric': 7.374873161315918} +Cheakpoint... +Epoch [196/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9609], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9609186053276062, 'Val/mean miou_metric': 0.9359208941459656, 'Val/mean f1': 0.9654457569122314, 'Val/mean precision': 0.962532103061676, 'Val/mean recall': 0.9683772325515747, 'Val/mean hd95_metric': 7.374873161315918} +Epoch [197/4000] Training [1/16] Loss: 0.01728 +Epoch [197/4000] Training [2/16] Loss: 0.01922 +Epoch [197/4000] Training [3/16] Loss: 0.01793 +Epoch [197/4000] Training [4/16] Loss: 0.02130 +Epoch [197/4000] Training [5/16] Loss: 0.01727 +Epoch [197/4000] Training [6/16] Loss: 0.02218 +Epoch [197/4000] Training [7/16] Loss: 0.01987 +Epoch [197/4000] Training [8/16] Loss: 0.02155 +Epoch [197/4000] Training [9/16] Loss: 0.01733 +Epoch [197/4000] Training [10/16] Loss: 0.01543 +Epoch [197/4000] Training [11/16] Loss: 0.01877 +Epoch [197/4000] Training [12/16] Loss: 0.02102 +Epoch [197/4000] Training [13/16] Loss: 0.02176 +Epoch [197/4000] Training [14/16] Loss: 0.02162 +Epoch [197/4000] Training [15/16] Loss: 0.02585 +Epoch [197/4000] Training [16/16] Loss: 0.02044 +Epoch [197/4000] Training metric {'Train/mean dice_metric': 0.9856376647949219, 'Train/mean miou_metric': 0.9717473387718201, 'Train/mean f1': 0.9829086661338806, 'Train/mean precision': 0.9784260988235474, 'Train/mean recall': 0.9874325394630432, 'Train/mean hd95_metric': 2.145162582397461} +Epoch [197/4000] Validation [1/4] Loss: 0.15380 focal_loss 0.08398 dice_loss 0.06982 +Epoch [197/4000] Validation [2/4] Loss: 0.46443 focal_loss 0.16105 dice_loss 0.30337 +Epoch [197/4000] Validation [3/4] Loss: 0.33427 focal_loss 0.17641 dice_loss 0.15786 +Epoch [197/4000] Validation [4/4] Loss: 0.32102 focal_loss 0.14851 dice_loss 0.17251 +Epoch [197/4000] Validation metric {'Val/mean dice_metric': 0.9551330804824829, 'Val/mean miou_metric': 0.9293569326400757, 'Val/mean f1': 0.9570596218109131, 'Val/mean precision': 0.9396247863769531, 'Val/mean recall': 0.9751536846160889, 'Val/mean hd95_metric': 9.644432067871094} +Cheakpoint... +Epoch [197/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9551], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9551330804824829, 'Val/mean miou_metric': 0.9293569326400757, 'Val/mean f1': 0.9570596218109131, 'Val/mean precision': 0.9396247863769531, 'Val/mean recall': 0.9751536846160889, 'Val/mean hd95_metric': 9.644432067871094} +Epoch [198/4000] Training [1/16] Loss: 0.01710 +Epoch [198/4000] Training [2/16] Loss: 0.02550 +Epoch [198/4000] Training [3/16] Loss: 0.01718 +Epoch [198/4000] Training [4/16] Loss: 0.02541 +Epoch [198/4000] Training [5/16] Loss: 0.02956 +Epoch [198/4000] Training [6/16] Loss: 0.01692 +Epoch [198/4000] Training [7/16] Loss: 0.02448 +Epoch [198/4000] Training [8/16] Loss: 0.02141 +Epoch [198/4000] Training [9/16] Loss: 0.02206 +Epoch [198/4000] Training [10/16] Loss: 0.03157 +Epoch [198/4000] Training [11/16] Loss: 0.02226 +Epoch [198/4000] Training [12/16] Loss: 0.02130 +Epoch [198/4000] Training [13/16] Loss: 0.02192 +Epoch [198/4000] Training [14/16] Loss: 0.01965 +Epoch [198/4000] Training [15/16] Loss: 0.01798 +Epoch [198/4000] Training [16/16] Loss: 0.01859 +Epoch [198/4000] Training metric {'Train/mean dice_metric': 0.9820592403411865, 'Train/mean miou_metric': 0.9657737016677856, 'Train/mean f1': 0.9788514375686646, 'Train/mean precision': 0.9734070301055908, 'Train/mean recall': 0.9843571186065674, 'Train/mean hd95_metric': 3.3205678462982178} +Epoch [198/4000] Validation [1/4] Loss: 0.73996 focal_loss 0.50810 dice_loss 0.23186 +Epoch [198/4000] Validation [2/4] Loss: 0.35396 focal_loss 0.16729 dice_loss 0.18668 +Epoch [198/4000] Validation [3/4] Loss: 0.15812 focal_loss 0.07438 dice_loss 0.08375 +Epoch [198/4000] Validation [4/4] Loss: 0.28701 focal_loss 0.13581 dice_loss 0.15120 +Epoch [198/4000] Validation metric {'Val/mean dice_metric': 0.9540210962295532, 'Val/mean miou_metric': 0.9266878366470337, 'Val/mean f1': 0.9567851424217224, 'Val/mean precision': 0.9626597166061401, 'Val/mean recall': 0.950981855392456, 'Val/mean hd95_metric': 7.911492347717285} +Cheakpoint... +Epoch [198/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9540], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9540210962295532, 'Val/mean miou_metric': 0.9266878366470337, 'Val/mean f1': 0.9567851424217224, 'Val/mean precision': 0.9626597166061401, 'Val/mean recall': 0.950981855392456, 'Val/mean hd95_metric': 7.911492347717285} +Epoch [199/4000] Training [1/16] Loss: 0.02723 +Epoch [199/4000] Training [2/16] Loss: 0.02565 +Epoch [199/4000] Training [3/16] Loss: 0.01711 +Epoch [199/4000] Training [4/16] Loss: 0.02283 +Epoch [199/4000] Training [5/16] Loss: 0.03216 +Epoch [199/4000] Training [6/16] Loss: 0.02403 +Epoch [199/4000] Training [7/16] Loss: 0.03019 +Epoch [199/4000] Training [8/16] Loss: 0.02911 +Epoch [199/4000] Training [9/16] Loss: 0.01527 +Epoch [199/4000] Training [10/16] Loss: 0.01986 +Epoch [199/4000] Training [11/16] Loss: 0.02061 +Epoch [199/4000] Training [12/16] Loss: 0.02026 +Epoch [199/4000] Training [13/16] Loss: 0.02525 +Epoch [199/4000] Training [14/16] Loss: 0.02187 +Epoch [199/4000] Training [15/16] Loss: 0.03113 +Epoch [199/4000] Training [16/16] Loss: 0.02239 +Epoch [199/4000] Training metric {'Train/mean dice_metric': 0.9817919135093689, 'Train/mean miou_metric': 0.9649747610092163, 'Train/mean f1': 0.9801589250564575, 'Train/mean precision': 0.9745508432388306, 'Train/mean recall': 0.9858319163322449, 'Train/mean hd95_metric': 3.2251358032226562} +Epoch [199/4000] Validation [1/4] Loss: 0.12789 focal_loss 0.05708 dice_loss 0.07081 +Epoch [199/4000] Validation [2/4] Loss: 0.14331 focal_loss 0.05218 dice_loss 0.09113 +Epoch [199/4000] Validation [3/4] Loss: 0.13395 focal_loss 0.05321 dice_loss 0.08073 +Epoch [199/4000] Validation [4/4] Loss: 0.16242 focal_loss 0.06299 dice_loss 0.09943 +Epoch [199/4000] Validation metric {'Val/mean dice_metric': 0.955878734588623, 'Val/mean miou_metric': 0.9296671152114868, 'Val/mean f1': 0.9639769196510315, 'Val/mean precision': 0.9615384936332703, 'Val/mean recall': 0.9664278030395508, 'Val/mean hd95_metric': 7.931936264038086} +Cheakpoint... +Epoch [199/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9559], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.955878734588623, 'Val/mean miou_metric': 0.9296671152114868, 'Val/mean f1': 0.9639769196510315, 'Val/mean precision': 0.9615384936332703, 'Val/mean recall': 0.9664278030395508, 'Val/mean hd95_metric': 7.931936264038086} +Epoch [200/4000] Training [1/16] Loss: 0.02055 +Epoch [200/4000] Training [2/16] Loss: 0.03533 +Epoch [200/4000] Training [3/16] Loss: 0.02187 +Epoch [200/4000] Training [4/16] Loss: 0.01862 +Epoch [200/4000] Training [5/16] Loss: 0.02714 +Epoch [200/4000] Training [6/16] Loss: 0.01941 +Epoch [200/4000] Training [7/16] Loss: 0.02022 +Epoch [200/4000] Training [8/16] Loss: 0.01838 +Epoch [200/4000] Training [9/16] Loss: 0.02644 +Epoch [200/4000] Training [10/16] Loss: 0.01808 +Epoch [200/4000] Training [11/16] Loss: 0.02187 +Epoch [200/4000] Training [12/16] Loss: 0.01912 +Epoch [200/4000] Training [13/16] Loss: 0.02069 +Epoch [200/4000] Training [14/16] Loss: 0.02298 +Epoch [200/4000] Training [15/16] Loss: 0.02044 +Epoch [200/4000] Training [16/16] Loss: 0.02481 +Epoch [200/4000] Training metric {'Train/mean dice_metric': 0.9819685220718384, 'Train/mean miou_metric': 0.9653638601303101, 'Train/mean f1': 0.9813017845153809, 'Train/mean precision': 0.9768784642219543, 'Train/mean recall': 0.985765278339386, 'Train/mean hd95_metric': 4.722002029418945} +Epoch [200/4000] Validation [1/4] Loss: 0.14256 focal_loss 0.07405 dice_loss 0.06852 +Epoch [200/4000] Validation [2/4] Loss: 0.18308 focal_loss 0.06765 dice_loss 0.11544 +Epoch [200/4000] Validation [3/4] Loss: 0.14912 focal_loss 0.06088 dice_loss 0.08824 +Epoch [200/4000] Validation [4/4] Loss: 0.25035 focal_loss 0.12730 dice_loss 0.12304 +Epoch [200/4000] Validation metric {'Val/mean dice_metric': 0.9580885171890259, 'Val/mean miou_metric': 0.9303188323974609, 'Val/mean f1': 0.9618423581123352, 'Val/mean precision': 0.9617459774017334, 'Val/mean recall': 0.961938738822937, 'Val/mean hd95_metric': 8.977913856506348} +Cheakpoint... +Epoch [200/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9581], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9580885171890259, 'Val/mean miou_metric': 0.9303188323974609, 'Val/mean f1': 0.9618423581123352, 'Val/mean precision': 0.9617459774017334, 'Val/mean recall': 0.961938738822937, 'Val/mean hd95_metric': 8.977913856506348} +Epoch [201/4000] Training [1/16] Loss: 0.02010 +Epoch [201/4000] Training [2/16] Loss: 0.07387 +Epoch [201/4000] Training [3/16] Loss: 0.01972 +Epoch [201/4000] Training [4/16] Loss: 0.02888 +Epoch [201/4000] Training [5/16] Loss: 0.05447 +Epoch [201/4000] Training [6/16] Loss: 0.02190 +Epoch [201/4000] Training [7/16] Loss: 0.02764 +Epoch [201/4000] Training [8/16] Loss: 0.02471 +Epoch [201/4000] Training [9/16] Loss: 0.03339 +Epoch [201/4000] Training [10/16] Loss: 0.03072 +Epoch [201/4000] Training [11/16] Loss: 0.02080 +Epoch [201/4000] Training [12/16] Loss: 0.02795 +Epoch [201/4000] Training [13/16] Loss: 0.03455 +Epoch [201/4000] Training [14/16] Loss: 0.02619 +Epoch [201/4000] Training [15/16] Loss: 0.04706 +Epoch [201/4000] Training [16/16] Loss: 0.02080 +Epoch [201/4000] Training metric {'Train/mean dice_metric': 0.9797682166099548, 'Train/mean miou_metric': 0.9608500003814697, 'Train/mean f1': 0.9776905179023743, 'Train/mean precision': 0.9721701741218567, 'Train/mean recall': 0.983273983001709, 'Train/mean hd95_metric': 3.7410707473754883} +Epoch [201/4000] Validation [1/4] Loss: 0.55124 focal_loss 0.37836 dice_loss 0.17288 +Epoch [201/4000] Validation [2/4] Loss: 0.20446 focal_loss 0.05931 dice_loss 0.14516 +Epoch [201/4000] Validation [3/4] Loss: 0.10940 focal_loss 0.04107 dice_loss 0.06833 +Epoch [201/4000] Validation [4/4] Loss: 0.20112 focal_loss 0.08091 dice_loss 0.12021 +Epoch [201/4000] Validation metric {'Val/mean dice_metric': 0.95708167552948, 'Val/mean miou_metric': 0.9274832010269165, 'Val/mean f1': 0.9591155052185059, 'Val/mean precision': 0.9557473063468933, 'Val/mean recall': 0.9625075459480286, 'Val/mean hd95_metric': 9.40290641784668} +Cheakpoint... +Epoch [201/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9571], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.95708167552948, 'Val/mean miou_metric': 0.9274832010269165, 'Val/mean f1': 0.9591155052185059, 'Val/mean precision': 0.9557473063468933, 'Val/mean recall': 0.9625075459480286, 'Val/mean hd95_metric': 9.40290641784668} +Epoch [202/4000] Training [1/16] Loss: 0.02068 +Epoch [202/4000] Training [2/16] Loss: 0.02049 +Epoch [202/4000] Training [3/16] Loss: 0.02081 +Epoch [202/4000] Training [4/16] Loss: 0.02419 +Epoch [202/4000] Training [5/16] Loss: 0.01883 +Epoch [202/4000] Training [6/16] Loss: 0.02542 +Epoch [202/4000] Training [7/16] Loss: 0.02609 +Epoch [202/4000] Training [8/16] Loss: 0.02570 +Epoch [202/4000] Training [9/16] Loss: 0.02199 +Epoch [202/4000] Training [10/16] Loss: 0.03052 +Epoch [202/4000] Training [11/16] Loss: 0.02552 +Epoch [202/4000] Training [12/16] Loss: 0.02398 +Epoch [202/4000] Training [13/16] Loss: 0.02406 +Epoch [202/4000] Training [14/16] Loss: 0.02971 +Epoch [202/4000] Training [15/16] Loss: 0.02703 +Epoch [202/4000] Training [16/16] Loss: 0.01750 +Epoch [202/4000] Training metric {'Train/mean dice_metric': 0.9824018478393555, 'Train/mean miou_metric': 0.9654945135116577, 'Train/mean f1': 0.9805059432983398, 'Train/mean precision': 0.9771798253059387, 'Train/mean recall': 0.9838547706604004, 'Train/mean hd95_metric': 3.16251802444458} +Epoch [202/4000] Validation [1/4] Loss: 0.29011 focal_loss 0.17373 dice_loss 0.11638 +Epoch [202/4000] Validation [2/4] Loss: 0.25254 focal_loss 0.08390 dice_loss 0.16864 +Epoch [202/4000] Validation [3/4] Loss: 0.11411 focal_loss 0.04680 dice_loss 0.06731 +Epoch [202/4000] Validation [4/4] Loss: 0.23707 focal_loss 0.11375 dice_loss 0.12333 +Epoch [202/4000] Validation metric {'Val/mean dice_metric': 0.9573225975036621, 'Val/mean miou_metric': 0.9303759336471558, 'Val/mean f1': 0.9606569409370422, 'Val/mean precision': 0.9643821120262146, 'Val/mean recall': 0.9569604396820068, 'Val/mean hd95_metric': 7.629626274108887} +Cheakpoint... +Epoch [202/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9573], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573225975036621, 'Val/mean miou_metric': 0.9303759336471558, 'Val/mean f1': 0.9606569409370422, 'Val/mean precision': 0.9643821120262146, 'Val/mean recall': 0.9569604396820068, 'Val/mean hd95_metric': 7.629626274108887} +Epoch [203/4000] Training [1/16] Loss: 0.02100 +Epoch [203/4000] Training [2/16] Loss: 0.01874 +Epoch [203/4000] Training [3/16] Loss: 0.01940 +Epoch [203/4000] Training [4/16] Loss: 0.02300 +Epoch [203/4000] Training [5/16] Loss: 0.02711 +Epoch [203/4000] Training [6/16] Loss: 0.02067 +Epoch [203/4000] Training [7/16] Loss: 0.02046 +Epoch [203/4000] Training [8/16] Loss: 0.01886 +Epoch [203/4000] Training [9/16] Loss: 0.02130 +Epoch [203/4000] Training [10/16] Loss: 0.02239 +Epoch [203/4000] Training [11/16] Loss: 0.01896 +Epoch [203/4000] Training [12/16] Loss: 0.01672 +Epoch [203/4000] Training [13/16] Loss: 0.01511 +Epoch [203/4000] Training [14/16] Loss: 0.02516 +Epoch [203/4000] Training [15/16] Loss: 0.02925 +Epoch [203/4000] Training [16/16] Loss: 0.02290 +Epoch [203/4000] Training metric {'Train/mean dice_metric': 0.9848361015319824, 'Train/mean miou_metric': 0.9700837135314941, 'Train/mean f1': 0.9819256663322449, 'Train/mean precision': 0.9773731827735901, 'Train/mean recall': 0.9865207672119141, 'Train/mean hd95_metric': 2.261263847351074} +Epoch [203/4000] Validation [1/4] Loss: 0.13370 focal_loss 0.07553 dice_loss 0.05817 +Epoch [203/4000] Validation [2/4] Loss: 0.12926 focal_loss 0.04728 dice_loss 0.08198 +Epoch [203/4000] Validation [3/4] Loss: 0.14646 focal_loss 0.07084 dice_loss 0.07561 +Epoch [203/4000] Validation [4/4] Loss: 0.28445 focal_loss 0.10936 dice_loss 0.17509 +Epoch [203/4000] Validation metric {'Val/mean dice_metric': 0.9626213908195496, 'Val/mean miou_metric': 0.9375244379043579, 'Val/mean f1': 0.9647403955459595, 'Val/mean precision': 0.9576733112335205, 'Val/mean recall': 0.9719125628471375, 'Val/mean hd95_metric': 6.91324520111084} +Cheakpoint... +Epoch [203/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9626], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9626213908195496, 'Val/mean miou_metric': 0.9375244379043579, 'Val/mean f1': 0.9647403955459595, 'Val/mean precision': 0.9576733112335205, 'Val/mean recall': 0.9719125628471375, 'Val/mean hd95_metric': 6.91324520111084} +Epoch [204/4000] Training [1/16] Loss: 0.02503 +Epoch [204/4000] Training [2/16] Loss: 0.02046 +Epoch [204/4000] Training [3/16] Loss: 0.13557 +Epoch [204/4000] Training [4/16] Loss: 0.01575 +Epoch [204/4000] Training [5/16] Loss: 0.02449 +Epoch [204/4000] Training [6/16] Loss: 0.01916 +Epoch [204/4000] Training [7/16] Loss: 0.02463 +Epoch [204/4000] Training [8/16] Loss: 0.02068 +Epoch [204/4000] Training [9/16] Loss: 0.02811 +Epoch [204/4000] Training [10/16] Loss: 0.01941 +Epoch [204/4000] Training [11/16] Loss: 0.02412 +Epoch [204/4000] Training [12/16] Loss: 0.02514 +Epoch [204/4000] Training [13/16] Loss: 0.02964 +Epoch [204/4000] Training [14/16] Loss: 0.03227 +Epoch [204/4000] Training [15/16] Loss: 0.01908 +Epoch [204/4000] Training [16/16] Loss: 0.22508 +Epoch [204/4000] Training metric {'Train/mean dice_metric': 0.9813541173934937, 'Train/mean miou_metric': 0.9641906023025513, 'Train/mean f1': 0.9760600328445435, 'Train/mean precision': 0.973299503326416, 'Train/mean recall': 0.9788362383842468, 'Train/mean hd95_metric': 4.086318016052246} +Epoch [204/4000] Validation [1/4] Loss: 0.35962 focal_loss 0.20670 dice_loss 0.15292 +Epoch [204/4000] Validation [2/4] Loss: 0.18211 focal_loss 0.05073 dice_loss 0.13138 +Epoch [204/4000] Validation [3/4] Loss: 0.11736 focal_loss 0.05265 dice_loss 0.06471 +Epoch [204/4000] Validation [4/4] Loss: 0.30983 focal_loss 0.15250 dice_loss 0.15733 +Epoch [204/4000] Validation metric {'Val/mean dice_metric': 0.9563808441162109, 'Val/mean miou_metric': 0.9278379678726196, 'Val/mean f1': 0.9569622278213501, 'Val/mean precision': 0.9598787426948547, 'Val/mean recall': 0.9540634751319885, 'Val/mean hd95_metric': 8.715757369995117} +Cheakpoint... +Epoch [204/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9564], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9563808441162109, 'Val/mean miou_metric': 0.9278379678726196, 'Val/mean f1': 0.9569622278213501, 'Val/mean precision': 0.9598787426948547, 'Val/mean recall': 0.9540634751319885, 'Val/mean hd95_metric': 8.715757369995117} +Epoch [205/4000] Training [1/16] Loss: 0.01716 +Epoch [205/4000] Training [2/16] Loss: 0.02048 +Epoch [205/4000] Training [3/16] Loss: 0.02731 +Epoch [205/4000] Training [4/16] Loss: 0.09696 +Epoch [205/4000] Training [5/16] Loss: 0.11269 +Epoch [205/4000] Training [6/16] Loss: 0.03380 +Epoch [205/4000] Training [7/16] Loss: 0.02335 +Epoch [205/4000] Training [8/16] Loss: 0.02362 +Epoch [205/4000] Training [9/16] Loss: 0.02442 +Epoch [205/4000] Training [10/16] Loss: 0.02209 +Epoch [205/4000] Training [11/16] Loss: 0.03099 +Epoch [205/4000] Training [12/16] Loss: 0.03560 +Epoch [205/4000] Training [13/16] Loss: 0.02986 +Epoch [205/4000] Training [14/16] Loss: 0.04095 +Epoch [205/4000] Training [15/16] Loss: 0.02498 +Epoch [205/4000] Training [16/16] Loss: 0.03155 +Epoch [205/4000] Training metric {'Train/mean dice_metric': 0.980492115020752, 'Train/mean miou_metric': 0.962030291557312, 'Train/mean f1': 0.9778771996498108, 'Train/mean precision': 0.972952663898468, 'Train/mean recall': 0.9828517436981201, 'Train/mean hd95_metric': 4.7315216064453125} +Epoch [205/4000] Validation [1/4] Loss: 0.47753 focal_loss 0.27752 dice_loss 0.20001 +Epoch [205/4000] Validation [2/4] Loss: 0.31820 focal_loss 0.09395 dice_loss 0.22425 +Epoch [205/4000] Validation [3/4] Loss: 0.17466 focal_loss 0.07852 dice_loss 0.09615 +Epoch [205/4000] Validation [4/4] Loss: 0.24588 focal_loss 0.09746 dice_loss 0.14843 +Epoch [205/4000] Validation metric {'Val/mean dice_metric': 0.9522244334220886, 'Val/mean miou_metric': 0.9226469993591309, 'Val/mean f1': 0.9565966725349426, 'Val/mean precision': 0.9575259685516357, 'Val/mean recall': 0.9556691646575928, 'Val/mean hd95_metric': 10.46554946899414} +Cheakpoint... +Epoch [205/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9522], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9522244334220886, 'Val/mean miou_metric': 0.9226469993591309, 'Val/mean f1': 0.9565966725349426, 'Val/mean precision': 0.9575259685516357, 'Val/mean recall': 0.9556691646575928, 'Val/mean hd95_metric': 10.46554946899414} +Epoch [206/4000] Training [1/16] Loss: 0.01879 +Epoch [206/4000] Training [2/16] Loss: 0.04092 +Epoch [206/4000] Training [3/16] Loss: 0.04165 +Epoch [206/4000] Training [4/16] Loss: 0.02361 +Epoch [206/4000] Training [5/16] Loss: 0.06365 +Epoch [206/4000] Training [6/16] Loss: 0.02558 +Epoch [206/4000] Training [7/16] Loss: 0.02205 +Epoch [206/4000] Training [8/16] Loss: 0.02469 +Epoch [206/4000] Training [9/16] Loss: 0.02316 +Epoch [206/4000] Training [10/16] Loss: 0.02160 +Epoch [206/4000] Training [11/16] Loss: 0.09417 +Epoch [206/4000] Training [12/16] Loss: 0.02299 +Epoch [206/4000] Training [13/16] Loss: 0.03532 +Epoch [206/4000] Training [14/16] Loss: 0.04671 +Epoch [206/4000] Training [15/16] Loss: 0.03362 +Epoch [206/4000] Training [16/16] Loss: 0.03230 +Epoch [206/4000] Training metric {'Train/mean dice_metric': 0.9799594879150391, 'Train/mean miou_metric': 0.9614301919937134, 'Train/mean f1': 0.9771497845649719, 'Train/mean precision': 0.9714983701705933, 'Train/mean recall': 0.9828673005104065, 'Train/mean hd95_metric': 4.159122467041016} +Epoch [206/4000] Validation [1/4] Loss: 0.19009 focal_loss 0.10059 dice_loss 0.08950 +Epoch [206/4000] Validation [2/4] Loss: 0.26383 focal_loss 0.08042 dice_loss 0.18341 +Epoch [206/4000] Validation [3/4] Loss: 0.13898 focal_loss 0.06013 dice_loss 0.07885 +Epoch [206/4000] Validation [4/4] Loss: 0.25761 focal_loss 0.09965 dice_loss 0.15796 +Epoch [206/4000] Validation metric {'Val/mean dice_metric': 0.9527460336685181, 'Val/mean miou_metric': 0.9231586456298828, 'Val/mean f1': 0.9574642777442932, 'Val/mean precision': 0.9559627175331116, 'Val/mean recall': 0.9589705467224121, 'Val/mean hd95_metric': 9.459915161132812} +Cheakpoint... +Epoch [206/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9527], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9527460336685181, 'Val/mean miou_metric': 0.9231586456298828, 'Val/mean f1': 0.9574642777442932, 'Val/mean precision': 0.9559627175331116, 'Val/mean recall': 0.9589705467224121, 'Val/mean hd95_metric': 9.459915161132812} +Epoch [207/4000] Training [1/16] Loss: 0.01966 +Epoch [207/4000] Training [2/16] Loss: 0.02300 +Epoch [207/4000] Training [3/16] Loss: 0.02536 +Epoch [207/4000] Training [4/16] Loss: 0.02184 +Epoch [207/4000] Training [5/16] Loss: 0.03022 +Epoch [207/4000] Training [6/16] Loss: 0.02192 +Epoch [207/4000] Training [7/16] Loss: 0.02696 +Epoch [207/4000] Training [8/16] Loss: 0.01981 +Epoch [207/4000] Training [9/16] Loss: 0.25860 +Epoch [207/4000] Training [10/16] Loss: 0.02305 +Epoch [207/4000] Training [11/16] Loss: 0.03777 +Epoch [207/4000] Training [12/16] Loss: 0.03251 +Epoch [207/4000] Training [13/16] Loss: 0.02144 +Epoch [207/4000] Training [14/16] Loss: 0.02537 +Epoch [207/4000] Training [15/16] Loss: 0.01539 +Epoch [207/4000] Training [16/16] Loss: 0.02715 +Epoch [207/4000] Training metric {'Train/mean dice_metric': 0.9800682663917542, 'Train/mean miou_metric': 0.962981104850769, 'Train/mean f1': 0.9787800312042236, 'Train/mean precision': 0.976179301738739, 'Train/mean recall': 0.9813946485519409, 'Train/mean hd95_metric': 3.3830976486206055} +Epoch [207/4000] Validation [1/4] Loss: 0.13997 focal_loss 0.07565 dice_loss 0.06432 +Epoch [207/4000] Validation [2/4] Loss: 0.32497 focal_loss 0.15514 dice_loss 0.16983 +Epoch [207/4000] Validation [3/4] Loss: 0.28843 focal_loss 0.14064 dice_loss 0.14778 +Epoch [207/4000] Validation [4/4] Loss: 0.20017 focal_loss 0.07805 dice_loss 0.12212 +Epoch [207/4000] Validation metric {'Val/mean dice_metric': 0.9554784893989563, 'Val/mean miou_metric': 0.9270356893539429, 'Val/mean f1': 0.9573970437049866, 'Val/mean precision': 0.9483949542045593, 'Val/mean recall': 0.9665716290473938, 'Val/mean hd95_metric': 9.70742416381836} +Cheakpoint... +Epoch [207/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9555], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9554784893989563, 'Val/mean miou_metric': 0.9270356893539429, 'Val/mean f1': 0.9573970437049866, 'Val/mean precision': 0.9483949542045593, 'Val/mean recall': 0.9665716290473938, 'Val/mean hd95_metric': 9.70742416381836} +Epoch [208/4000] Training [1/16] Loss: 0.02831 +Epoch [208/4000] Training [2/16] Loss: 0.02452 +Epoch [208/4000] Training [3/16] Loss: 0.02009 +Epoch [208/4000] Training [4/16] Loss: 0.03509 +Epoch [208/4000] Training [5/16] Loss: 0.02187 +Epoch [208/4000] Training [6/16] Loss: 0.01984 +Epoch [208/4000] Training [7/16] Loss: 0.02213 +Epoch [208/4000] Training [8/16] Loss: 0.01985 +Epoch [208/4000] Training [9/16] Loss: 0.07205 +Epoch [208/4000] Training [10/16] Loss: 0.02152 +Epoch [208/4000] Training [11/16] Loss: 0.02099 +Epoch [208/4000] Training [12/16] Loss: 0.02632 +Epoch [208/4000] Training [13/16] Loss: 0.01730 +Epoch [208/4000] Training [14/16] Loss: 0.02461 +Epoch [208/4000] Training [15/16] Loss: 0.03199 +Epoch [208/4000] Training [16/16] Loss: 0.03016 +Epoch [208/4000] Training metric {'Train/mean dice_metric': 0.9828248023986816, 'Train/mean miou_metric': 0.9662749767303467, 'Train/mean f1': 0.9805759191513062, 'Train/mean precision': 0.9753896594047546, 'Train/mean recall': 0.9858176708221436, 'Train/mean hd95_metric': 3.589719295501709} +Epoch [208/4000] Validation [1/4] Loss: 0.54604 focal_loss 0.39240 dice_loss 0.15365 +Epoch [208/4000] Validation [2/4] Loss: 0.57373 focal_loss 0.30931 dice_loss 0.26441 +Epoch [208/4000] Validation [3/4] Loss: 0.16787 focal_loss 0.05924 dice_loss 0.10863 +Epoch [208/4000] Validation [4/4] Loss: 0.25837 focal_loss 0.13153 dice_loss 0.12685 +Epoch [208/4000] Validation metric {'Val/mean dice_metric': 0.9578243494033813, 'Val/mean miou_metric': 0.9306739568710327, 'Val/mean f1': 0.9578060507774353, 'Val/mean precision': 0.9568124413490295, 'Val/mean recall': 0.9588016867637634, 'Val/mean hd95_metric': 8.241165161132812} +Cheakpoint... +Epoch [208/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9578], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9578243494033813, 'Val/mean miou_metric': 0.9306739568710327, 'Val/mean f1': 0.9578060507774353, 'Val/mean precision': 0.9568124413490295, 'Val/mean recall': 0.9588016867637634, 'Val/mean hd95_metric': 8.241165161132812} +Epoch [209/4000] Training [1/16] Loss: 0.02042 +Epoch [209/4000] Training [2/16] Loss: 0.02688 +Epoch [209/4000] Training [3/16] Loss: 0.01661 +Epoch [209/4000] Training [4/16] Loss: 0.01920 +Epoch [209/4000] Training [5/16] Loss: 0.01570 +Epoch [209/4000] Training [6/16] Loss: 0.02124 +Epoch [209/4000] Training [7/16] Loss: 0.02594 +Epoch [209/4000] Training [8/16] Loss: 0.02403 +Epoch [209/4000] Training [9/16] Loss: 0.02069 +Epoch [209/4000] Training [10/16] Loss: 0.02113 +Epoch [209/4000] Training [11/16] Loss: 0.03301 +Epoch [209/4000] Training [12/16] Loss: 0.04584 +Epoch [209/4000] Training [13/16] Loss: 0.02364 +Epoch [209/4000] Training [14/16] Loss: 0.04378 +Epoch [209/4000] Training [15/16] Loss: 0.02213 +Epoch [209/4000] Training [16/16] Loss: 0.03323 +Epoch [209/4000] Training metric {'Train/mean dice_metric': 0.9790301322937012, 'Train/mean miou_metric': 0.9608312845230103, 'Train/mean f1': 0.9788035154342651, 'Train/mean precision': 0.9738616347312927, 'Train/mean recall': 0.9837958216667175, 'Train/mean hd95_metric': 3.5521013736724854} +Epoch [209/4000] Validation [1/4] Loss: 0.14246 focal_loss 0.06629 dice_loss 0.07617 +Epoch [209/4000] Validation [2/4] Loss: 0.40314 focal_loss 0.15453 dice_loss 0.24860 +Epoch [209/4000] Validation [3/4] Loss: 0.11379 focal_loss 0.04428 dice_loss 0.06951 +Epoch [209/4000] Validation [4/4] Loss: 0.12620 focal_loss 0.04856 dice_loss 0.07764 +Epoch [209/4000] Validation metric {'Val/mean dice_metric': 0.9574552774429321, 'Val/mean miou_metric': 0.929338812828064, 'Val/mean f1': 0.9622514843940735, 'Val/mean precision': 0.9565222859382629, 'Val/mean recall': 0.9680497646331787, 'Val/mean hd95_metric': 8.118505477905273} +Cheakpoint... +Epoch [209/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9575], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9574552774429321, 'Val/mean miou_metric': 0.929338812828064, 'Val/mean f1': 0.9622514843940735, 'Val/mean precision': 0.9565222859382629, 'Val/mean recall': 0.9680497646331787, 'Val/mean hd95_metric': 8.118505477905273} +Epoch [210/4000] Training [1/16] Loss: 0.02105 +Epoch [210/4000] Training [2/16] Loss: 0.01882 +Epoch [210/4000] Training [3/16] Loss: 0.02259 +Epoch [210/4000] Training [4/16] Loss: 0.02078 +Epoch [210/4000] Training [5/16] Loss: 0.02291 +Epoch [210/4000] Training [6/16] Loss: 0.05565 +Epoch [210/4000] Training [7/16] Loss: 0.02492 +Epoch [210/4000] Training [8/16] Loss: 0.02310 +Epoch [210/4000] Training [9/16] Loss: 0.02092 +Epoch [210/4000] Training [10/16] Loss: 0.03128 +Epoch [210/4000] Training [11/16] Loss: 0.01786 +Epoch [210/4000] Training [12/16] Loss: 0.02300 +Epoch [210/4000] Training [13/16] Loss: 0.01952 +Epoch [210/4000] Training [14/16] Loss: 0.02513 +Epoch [210/4000] Training [15/16] Loss: 0.01795 +Epoch [210/4000] Training [16/16] Loss: 0.02792 +Epoch [210/4000] Training metric {'Train/mean dice_metric': 0.9825730323791504, 'Train/mean miou_metric': 0.9658867716789246, 'Train/mean f1': 0.9806192517280579, 'Train/mean precision': 0.976364016532898, 'Train/mean recall': 0.9849116802215576, 'Train/mean hd95_metric': 3.0330796241760254} +Epoch [210/4000] Validation [1/4] Loss: 0.12446 focal_loss 0.06882 dice_loss 0.05564 +Epoch [210/4000] Validation [2/4] Loss: 0.47256 focal_loss 0.26239 dice_loss 0.21017 +Epoch [210/4000] Validation [3/4] Loss: 0.16181 focal_loss 0.07734 dice_loss 0.08447 +Epoch [210/4000] Validation [4/4] Loss: 0.16716 focal_loss 0.06995 dice_loss 0.09722 +Epoch [210/4000] Validation metric {'Val/mean dice_metric': 0.9623347520828247, 'Val/mean miou_metric': 0.9361268281936646, 'Val/mean f1': 0.9652788043022156, 'Val/mean precision': 0.9611232876777649, 'Val/mean recall': 0.9694703817367554, 'Val/mean hd95_metric': 7.147737979888916} +Cheakpoint... +Epoch [210/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9623], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9623347520828247, 'Val/mean miou_metric': 0.9361268281936646, 'Val/mean f1': 0.9652788043022156, 'Val/mean precision': 0.9611232876777649, 'Val/mean recall': 0.9694703817367554, 'Val/mean hd95_metric': 7.147737979888916} +Epoch [211/4000] Training [1/16] Loss: 0.02935 +Epoch [211/4000] Training [2/16] Loss: 0.01788 +Epoch [211/4000] Training [3/16] Loss: 0.01777 +Epoch [211/4000] Training [4/16] Loss: 0.02462 +Epoch [211/4000] Training [5/16] Loss: 0.02445 +Epoch [211/4000] Training [6/16] Loss: 0.01600 +Epoch [211/4000] Training [7/16] Loss: 0.01794 +Epoch [211/4000] Training [8/16] Loss: 0.02265 +Epoch [211/4000] Training [9/16] Loss: 0.01862 +Epoch [211/4000] Training [10/16] Loss: 0.02254 +Epoch [211/4000] Training [11/16] Loss: 0.01765 +Epoch [211/4000] Training [12/16] Loss: 0.01625 +Epoch [211/4000] Training [13/16] Loss: 0.02086 +Epoch [211/4000] Training [14/16] Loss: 0.01831 +Epoch [211/4000] Training [15/16] Loss: 0.03512 +Epoch [211/4000] Training [16/16] Loss: 0.02118 +Epoch [211/4000] Training metric {'Train/mean dice_metric': 0.98475182056427, 'Train/mean miou_metric': 0.969902753829956, 'Train/mean f1': 0.9827630519866943, 'Train/mean precision': 0.9785894751548767, 'Train/mean recall': 0.9869723320007324, 'Train/mean hd95_metric': 2.022043228149414} +Epoch [211/4000] Validation [1/4] Loss: 0.36208 focal_loss 0.24311 dice_loss 0.11898 +Epoch [211/4000] Validation [2/4] Loss: 0.28076 focal_loss 0.13232 dice_loss 0.14844 +Epoch [211/4000] Validation [3/4] Loss: 0.10391 focal_loss 0.04800 dice_loss 0.05591 +Epoch [211/4000] Validation [4/4] Loss: 0.22441 focal_loss 0.11273 dice_loss 0.11168 +Epoch [211/4000] Validation metric {'Val/mean dice_metric': 0.9624164700508118, 'Val/mean miou_metric': 0.9371174573898315, 'Val/mean f1': 0.9642786383628845, 'Val/mean precision': 0.9604487419128418, 'Val/mean recall': 0.9681392312049866, 'Val/mean hd95_metric': 7.96877908706665} +Cheakpoint... +Epoch [211/4000] best acc:tensor([0.9642], device='cuda:0'), Now : mean acc: tensor([0.9624], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9624164700508118, 'Val/mean miou_metric': 0.9371174573898315, 'Val/mean f1': 0.9642786383628845, 'Val/mean precision': 0.9604487419128418, 'Val/mean recall': 0.9681392312049866, 'Val/mean hd95_metric': 7.96877908706665} +Epoch [212/4000] Training [1/16] Loss: 0.02052 +Epoch [212/4000] Training [2/16] Loss: 0.01421 +Epoch [212/4000] Training [3/16] Loss: 0.02252 +Epoch [212/4000] Training [4/16] Loss: 0.03166 +Epoch [212/4000] Training [5/16] Loss: 0.01910 +Epoch [212/4000] Training [6/16] Loss: 0.01616 +Epoch [212/4000] Training [7/16] Loss: 0.02481 +Epoch [212/4000] Training [8/16] Loss: 0.01698 +Epoch [212/4000] Training [9/16] Loss: 0.01587 +Epoch [212/4000] Training [10/16] Loss: 0.01914 +Epoch [212/4000] Training [11/16] Loss: 0.01787 +Epoch [212/4000] Training [12/16] Loss: 0.02039 +Epoch [212/4000] Training [13/16] Loss: 0.01406 +Epoch [212/4000] Training [14/16] Loss: 0.01591 +Epoch [212/4000] Training [15/16] Loss: 0.01663 +Epoch [212/4000] Training [16/16] Loss: 0.03278 +Epoch [212/4000] Training metric {'Train/mean dice_metric': 0.9860939979553223, 'Train/mean miou_metric': 0.9724299311637878, 'Train/mean f1': 0.9834887981414795, 'Train/mean precision': 0.9785462617874146, 'Train/mean recall': 0.9884815812110901, 'Train/mean hd95_metric': 1.7125811576843262} +Epoch [212/4000] Validation [1/4] Loss: 0.41577 focal_loss 0.29161 dice_loss 0.12416 +Epoch [212/4000] Validation [2/4] Loss: 0.23867 focal_loss 0.09832 dice_loss 0.14035 +Epoch [212/4000] Validation [3/4] Loss: 0.10569 focal_loss 0.04483 dice_loss 0.06085 +Epoch [212/4000] Validation [4/4] Loss: 0.30437 focal_loss 0.16447 dice_loss 0.13989 +Epoch [212/4000] Validation metric {'Val/mean dice_metric': 0.9645763635635376, 'Val/mean miou_metric': 0.9399601221084595, 'Val/mean f1': 0.9665059447288513, 'Val/mean precision': 0.965014636516571, 'Val/mean recall': 0.9680018424987793, 'Val/mean hd95_metric': 6.662762641906738} +Cheakpoint... +Epoch [212/4000] best acc:tensor([0.9646], device='cuda:0'), Now : mean acc: tensor([0.9646], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645763635635376, 'Val/mean miou_metric': 0.9399601221084595, 'Val/mean f1': 0.9665059447288513, 'Val/mean precision': 0.965014636516571, 'Val/mean recall': 0.9680018424987793, 'Val/mean hd95_metric': 6.662762641906738} +Epoch [213/4000] Training [1/16] Loss: 0.01637 +Epoch [213/4000] Training [2/16] Loss: 0.01682 +Epoch [213/4000] Training [3/16] Loss: 0.03053 +Epoch [213/4000] Training [4/16] Loss: 0.01530 +Epoch [213/4000] Training [5/16] Loss: 0.02393 +Epoch [213/4000] Training [6/16] Loss: 0.02080 +Epoch [213/4000] Training [7/16] Loss: 0.02268 +Epoch [213/4000] Training [8/16] Loss: 0.02560 +Epoch [213/4000] Training [9/16] Loss: 0.01660 +Epoch [213/4000] Training [10/16] Loss: 0.02557 +Epoch [213/4000] Training [11/16] Loss: 0.02344 +Epoch [213/4000] Training [12/16] Loss: 0.02000 +Epoch [213/4000] Training [13/16] Loss: 0.01718 +Epoch [213/4000] Training [14/16] Loss: 0.02323 +Epoch [213/4000] Training [15/16] Loss: 0.01846 +Epoch [213/4000] Training [16/16] Loss: 0.02046 +Epoch [213/4000] Training metric {'Train/mean dice_metric': 0.9857125878334045, 'Train/mean miou_metric': 0.971734344959259, 'Train/mean f1': 0.9838396906852722, 'Train/mean precision': 0.9789616465568542, 'Train/mean recall': 0.988766610622406, 'Train/mean hd95_metric': 2.1837615966796875} +Epoch [213/4000] Validation [1/4] Loss: 0.37359 focal_loss 0.24626 dice_loss 0.12734 +Epoch [213/4000] Validation [2/4] Loss: 0.22330 focal_loss 0.07730 dice_loss 0.14600 +Epoch [213/4000] Validation [3/4] Loss: 0.18925 focal_loss 0.09391 dice_loss 0.09534 +Epoch [213/4000] Validation [4/4] Loss: 0.31857 focal_loss 0.17427 dice_loss 0.14430 +Epoch [213/4000] Validation metric {'Val/mean dice_metric': 0.9634959101676941, 'Val/mean miou_metric': 0.938119113445282, 'Val/mean f1': 0.9645049571990967, 'Val/mean precision': 0.9630525708198547, 'Val/mean recall': 0.9659618139266968, 'Val/mean hd95_metric': 6.621197700500488} +Cheakpoint... +Epoch [213/4000] best acc:tensor([0.9646], device='cuda:0'), Now : mean acc: tensor([0.9635], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9634959101676941, 'Val/mean miou_metric': 0.938119113445282, 'Val/mean f1': 0.9645049571990967, 'Val/mean precision': 0.9630525708198547, 'Val/mean recall': 0.9659618139266968, 'Val/mean hd95_metric': 6.621197700500488} +Epoch [214/4000] Training [1/16] Loss: 0.01687 +Epoch [214/4000] Training [2/16] Loss: 0.01593 +Epoch [214/4000] Training [3/16] Loss: 0.01626 +Epoch [214/4000] Training [4/16] Loss: 0.01358 +Epoch [214/4000] Training [5/16] Loss: 0.01759 +Epoch [214/4000] Training [6/16] Loss: 0.02031 +Epoch [214/4000] Training [7/16] Loss: 0.01546 +Epoch [214/4000] Training [8/16] Loss: 0.01821 +Epoch [214/4000] Training [9/16] Loss: 0.02853 +Epoch [214/4000] Training [10/16] Loss: 0.03043 +Epoch [214/4000] Training [11/16] Loss: 0.01601 +Epoch [214/4000] Training [12/16] Loss: 0.01517 +Epoch [214/4000] Training [13/16] Loss: 0.01614 +Epoch [214/4000] Training [14/16] Loss: 0.08341 +Epoch [214/4000] Training [15/16] Loss: 0.02044 +Epoch [214/4000] Training [16/16] Loss: 0.02524 +Epoch [214/4000] Training metric {'Train/mean dice_metric': 0.9864405393600464, 'Train/mean miou_metric': 0.9734025001525879, 'Train/mean f1': 0.9844358563423157, 'Train/mean precision': 0.980175793170929, 'Train/mean recall': 0.9887331128120422, 'Train/mean hd95_metric': 1.6050119400024414} +Epoch [214/4000] Validation [1/4] Loss: 0.21819 focal_loss 0.12512 dice_loss 0.09307 +Epoch [214/4000] Validation [2/4] Loss: 0.17947 focal_loss 0.05029 dice_loss 0.12918 +Epoch [214/4000] Validation [3/4] Loss: 0.15167 focal_loss 0.07317 dice_loss 0.07850 +Epoch [214/4000] Validation [4/4] Loss: 0.19156 focal_loss 0.08559 dice_loss 0.10597 +Epoch [214/4000] Validation metric {'Val/mean dice_metric': 0.9658107757568359, 'Val/mean miou_metric': 0.9420315027236938, 'Val/mean f1': 0.9680437445640564, 'Val/mean precision': 0.964209794998169, 'Val/mean recall': 0.9719082713127136, 'Val/mean hd95_metric': 6.902567386627197} +Cheakpoint... +Epoch [214/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658107757568359, 'Val/mean miou_metric': 0.9420315027236938, 'Val/mean f1': 0.9680437445640564, 'Val/mean precision': 0.964209794998169, 'Val/mean recall': 0.9719082713127136, 'Val/mean hd95_metric': 6.902567386627197} +Epoch [215/4000] Training [1/16] Loss: 0.02203 +Epoch [215/4000] Training [2/16] Loss: 0.01928 +Epoch [215/4000] Training [3/16] Loss: 0.01694 +Epoch [215/4000] Training [4/16] Loss: 0.02990 +Epoch [215/4000] Training [5/16] Loss: 0.02199 +Epoch [215/4000] Training [6/16] Loss: 0.01786 +Epoch [215/4000] Training [7/16] Loss: 0.01685 +Epoch [215/4000] Training [8/16] Loss: 0.02072 +Epoch [215/4000] Training [9/16] Loss: 0.03078 +Epoch [215/4000] Training [10/16] Loss: 0.02853 +Epoch [215/4000] Training [11/16] Loss: 0.02108 +Epoch [215/4000] Training [12/16] Loss: 0.01730 +Epoch [215/4000] Training [13/16] Loss: 0.02363 +Epoch [215/4000] Training [14/16] Loss: 0.02229 +Epoch [215/4000] Training [15/16] Loss: 0.02105 +Epoch [215/4000] Training [16/16] Loss: 0.01856 +Epoch [215/4000] Training metric {'Train/mean dice_metric': 0.9853568077087402, 'Train/mean miou_metric': 0.9710884690284729, 'Train/mean f1': 0.9822940230369568, 'Train/mean precision': 0.9781408905982971, 'Train/mean recall': 0.9864826202392578, 'Train/mean hd95_metric': 2.5330328941345215} +Epoch [215/4000] Validation [1/4] Loss: 0.17823 focal_loss 0.08844 dice_loss 0.08979 +Epoch [215/4000] Validation [2/4] Loss: 0.15481 focal_loss 0.04999 dice_loss 0.10482 +Epoch [215/4000] Validation [3/4] Loss: 0.10191 focal_loss 0.04042 dice_loss 0.06148 +Epoch [215/4000] Validation [4/4] Loss: 0.20191 focal_loss 0.10163 dice_loss 0.10029 +Epoch [215/4000] Validation metric {'Val/mean dice_metric': 0.9653497934341431, 'Val/mean miou_metric': 0.9405657052993774, 'Val/mean f1': 0.9670878052711487, 'Val/mean precision': 0.9664402604103088, 'Val/mean recall': 0.9677362442016602, 'Val/mean hd95_metric': 6.662786960601807} +Cheakpoint... +Epoch [215/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653497934341431, 'Val/mean miou_metric': 0.9405657052993774, 'Val/mean f1': 0.9670878052711487, 'Val/mean precision': 0.9664402604103088, 'Val/mean recall': 0.9677362442016602, 'Val/mean hd95_metric': 6.662786960601807} +Epoch [216/4000] Training [1/16] Loss: 0.02052 +Epoch [216/4000] Training [2/16] Loss: 0.02086 +Epoch [216/4000] Training [3/16] Loss: 0.02177 +Epoch [216/4000] Training [4/16] Loss: 0.01816 +Epoch [216/4000] Training [5/16] Loss: 0.01483 +Epoch [216/4000] Training [6/16] Loss: 0.01777 +Epoch [216/4000] Training [7/16] Loss: 0.01887 +Epoch [216/4000] Training [8/16] Loss: 0.01658 +Epoch [216/4000] Training [9/16] Loss: 0.01920 +Epoch [216/4000] Training [10/16] Loss: 0.02923 +Epoch [216/4000] Training [11/16] Loss: 0.06794 +Epoch [216/4000] Training [12/16] Loss: 0.01977 +Epoch [216/4000] Training [13/16] Loss: 0.02019 +Epoch [216/4000] Training [14/16] Loss: 0.02129 +Epoch [216/4000] Training [15/16] Loss: 0.01595 +Epoch [216/4000] Training [16/16] Loss: 0.01769 +Epoch [216/4000] Training metric {'Train/mean dice_metric': 0.9848822355270386, 'Train/mean miou_metric': 0.9703977704048157, 'Train/mean f1': 0.9823352098464966, 'Train/mean precision': 0.9769362807273865, 'Train/mean recall': 0.9877941012382507, 'Train/mean hd95_metric': 2.0870866775512695} +Epoch [216/4000] Validation [1/4] Loss: 0.16818 focal_loss 0.09119 dice_loss 0.07698 +Epoch [216/4000] Validation [2/4] Loss: 0.45955 focal_loss 0.26411 dice_loss 0.19544 +Epoch [216/4000] Validation [3/4] Loss: 0.14015 focal_loss 0.05771 dice_loss 0.08243 +Epoch [216/4000] Validation [4/4] Loss: 0.23463 focal_loss 0.11727 dice_loss 0.11736 +Epoch [216/4000] Validation metric {'Val/mean dice_metric': 0.9625481367111206, 'Val/mean miou_metric': 0.9373337626457214, 'Val/mean f1': 0.9631139039993286, 'Val/mean precision': 0.9638001322746277, 'Val/mean recall': 0.962428629398346, 'Val/mean hd95_metric': 6.556449890136719} +Cheakpoint... +Epoch [216/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625481367111206, 'Val/mean miou_metric': 0.9373337626457214, 'Val/mean f1': 0.9631139039993286, 'Val/mean precision': 0.9638001322746277, 'Val/mean recall': 0.962428629398346, 'Val/mean hd95_metric': 6.556449890136719} +Epoch [217/4000] Training [1/16] Loss: 0.02240 +Epoch [217/4000] Training [2/16] Loss: 0.02011 +Epoch [217/4000] Training [3/16] Loss: 0.05731 +Epoch [217/4000] Training [4/16] Loss: 0.03162 +Epoch [217/4000] Training [5/16] Loss: 0.01749 +Epoch [217/4000] Training [6/16] Loss: 0.01730 +Epoch [217/4000] Training [7/16] Loss: 0.02145 +Epoch [217/4000] Training [8/16] Loss: 0.02004 +Epoch [217/4000] Training [9/16] Loss: 0.03415 +Epoch [217/4000] Training [10/16] Loss: 0.03626 +Epoch [217/4000] Training [11/16] Loss: 0.01705 +Epoch [217/4000] Training [12/16] Loss: 0.02711 +Epoch [217/4000] Training [13/16] Loss: 0.01632 +Epoch [217/4000] Training [14/16] Loss: 0.02957 +Epoch [217/4000] Training [15/16] Loss: 0.02990 +Epoch [217/4000] Training [16/16] Loss: 0.02054 +Epoch [217/4000] Training metric {'Train/mean dice_metric': 0.9827082753181458, 'Train/mean miou_metric': 0.9665816426277161, 'Train/mean f1': 0.9796859622001648, 'Train/mean precision': 0.9743996858596802, 'Train/mean recall': 0.9850299954414368, 'Train/mean hd95_metric': 3.8531246185302734} +Epoch [217/4000] Validation [1/4] Loss: 0.47266 focal_loss 0.33093 dice_loss 0.14174 +Epoch [217/4000] Validation [2/4] Loss: 0.53746 focal_loss 0.24146 dice_loss 0.29600 +Epoch [217/4000] Validation [3/4] Loss: 0.11753 focal_loss 0.05452 dice_loss 0.06302 +Epoch [217/4000] Validation [4/4] Loss: 0.23131 focal_loss 0.10563 dice_loss 0.12568 +Epoch [217/4000] Validation metric {'Val/mean dice_metric': 0.9547107815742493, 'Val/mean miou_metric': 0.9260810613632202, 'Val/mean f1': 0.953631579875946, 'Val/mean precision': 0.954786479473114, 'Val/mean recall': 0.9524795413017273, 'Val/mean hd95_metric': 10.422178268432617} +Cheakpoint... +Epoch [217/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9547], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9547107815742493, 'Val/mean miou_metric': 0.9260810613632202, 'Val/mean f1': 0.953631579875946, 'Val/mean precision': 0.954786479473114, 'Val/mean recall': 0.9524795413017273, 'Val/mean hd95_metric': 10.422178268432617} +Epoch [218/4000] Training [1/16] Loss: 0.02663 +Epoch [218/4000] Training [2/16] Loss: 0.02987 +Epoch [218/4000] Training [3/16] Loss: 0.02184 +Epoch [218/4000] Training [4/16] Loss: 0.01875 +Epoch [218/4000] Training [5/16] Loss: 0.02365 +Epoch [218/4000] Training [6/16] Loss: 0.02445 +Epoch [218/4000] Training [7/16] Loss: 0.02833 +Epoch [218/4000] Training [8/16] Loss: 0.02865 +Epoch [218/4000] Training [9/16] Loss: 0.02941 +Epoch [218/4000] Training [10/16] Loss: 0.02404 +Epoch [218/4000] Training [11/16] Loss: 0.02863 +Epoch [218/4000] Training [12/16] Loss: 0.01965 +Epoch [218/4000] Training [13/16] Loss: 0.02923 +Epoch [218/4000] Training [14/16] Loss: 0.02830 +Epoch [218/4000] Training [15/16] Loss: 0.01986 +Epoch [218/4000] Training [16/16] Loss: 0.02531 +Epoch [218/4000] Training metric {'Train/mean dice_metric': 0.980332612991333, 'Train/mean miou_metric': 0.9623476266860962, 'Train/mean f1': 0.976831316947937, 'Train/mean precision': 0.9746126532554626, 'Train/mean recall': 0.9790601134300232, 'Train/mean hd95_metric': 5.198259353637695} +Epoch [218/4000] Validation [1/4] Loss: 0.11612 focal_loss 0.05321 dice_loss 0.06291 +Epoch [218/4000] Validation [2/4] Loss: 0.45102 focal_loss 0.21984 dice_loss 0.23118 +Epoch [218/4000] Validation [3/4] Loss: 0.16869 focal_loss 0.06925 dice_loss 0.09944 +Epoch [218/4000] Validation [4/4] Loss: 0.23286 focal_loss 0.08832 dice_loss 0.14454 +Epoch [218/4000] Validation metric {'Val/mean dice_metric': 0.9529033899307251, 'Val/mean miou_metric': 0.9251901507377625, 'Val/mean f1': 0.9553501605987549, 'Val/mean precision': 0.9464674592018127, 'Val/mean recall': 0.9644010663032532, 'Val/mean hd95_metric': 10.992609024047852} +Cheakpoint... +Epoch [218/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9529], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9529033899307251, 'Val/mean miou_metric': 0.9251901507377625, 'Val/mean f1': 0.9553501605987549, 'Val/mean precision': 0.9464674592018127, 'Val/mean recall': 0.9644010663032532, 'Val/mean hd95_metric': 10.992609024047852} +Epoch [219/4000] Training [1/16] Loss: 0.03536 +Epoch [219/4000] Training [2/16] Loss: 0.01844 +Epoch [219/4000] Training [3/16] Loss: 0.08784 +Epoch [219/4000] Training [4/16] Loss: 0.01732 +Epoch [219/4000] Training [5/16] Loss: 0.02909 +Epoch [219/4000] Training [6/16] Loss: 0.02164 +Epoch [219/4000] Training [7/16] Loss: 0.02074 +Epoch [219/4000] Training [8/16] Loss: 0.02207 +Epoch [219/4000] Training [9/16] Loss: 0.02890 +Epoch [219/4000] Training [10/16] Loss: 0.11073 +Epoch [219/4000] Training [11/16] Loss: 0.01626 +Epoch [219/4000] Training [12/16] Loss: 0.03135 +Epoch [219/4000] Training [13/16] Loss: 0.02115 +Epoch [219/4000] Training [14/16] Loss: 0.03493 +Epoch [219/4000] Training [15/16] Loss: 0.03751 +Epoch [219/4000] Training [16/16] Loss: 0.02660 +Epoch [219/4000] Training metric {'Train/mean dice_metric': 0.9768983125686646, 'Train/mean miou_metric': 0.9583455324172974, 'Train/mean f1': 0.9784857034683228, 'Train/mean precision': 0.9744802117347717, 'Train/mean recall': 0.9825242161750793, 'Train/mean hd95_metric': 4.75009822845459} +Epoch [219/4000] Validation [1/4] Loss: 0.48543 focal_loss 0.35336 dice_loss 0.13207 +Epoch [219/4000] Validation [2/4] Loss: 0.56372 focal_loss 0.19949 dice_loss 0.36423 +Epoch [219/4000] Validation [3/4] Loss: 0.21198 focal_loss 0.10951 dice_loss 0.10247 +Epoch [219/4000] Validation [4/4] Loss: 0.32764 focal_loss 0.12445 dice_loss 0.20319 +Epoch [219/4000] Validation metric {'Val/mean dice_metric': 0.9439411163330078, 'Val/mean miou_metric': 0.9147768020629883, 'Val/mean f1': 0.9484089612960815, 'Val/mean precision': 0.9340314865112305, 'Val/mean recall': 0.9632357358932495, 'Val/mean hd95_metric': 12.007149696350098} +Cheakpoint... +Epoch [219/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9439], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9439411163330078, 'Val/mean miou_metric': 0.9147768020629883, 'Val/mean f1': 0.9484089612960815, 'Val/mean precision': 0.9340314865112305, 'Val/mean recall': 0.9632357358932495, 'Val/mean hd95_metric': 12.007149696350098} +Epoch [220/4000] Training [1/16] Loss: 0.09790 +Epoch [220/4000] Training [2/16] Loss: 0.01931 +Epoch [220/4000] Training [3/16] Loss: 0.04709 +Epoch [220/4000] Training [4/16] Loss: 0.02235 +Epoch [220/4000] Training [5/16] Loss: 0.03160 +Epoch [220/4000] Training [6/16] Loss: 0.02279 +Epoch [220/4000] Training [7/16] Loss: 0.02174 +Epoch [220/4000] Training [8/16] Loss: 0.09429 +Epoch [220/4000] Training [9/16] Loss: 0.05438 +Epoch [220/4000] Training [10/16] Loss: 0.02806 +Epoch [220/4000] Training [11/16] Loss: 0.03643 +Epoch [220/4000] Training [12/16] Loss: 0.03288 +Epoch [220/4000] Training [13/16] Loss: 0.03092 +Epoch [220/4000] Training [14/16] Loss: 0.02286 +Epoch [220/4000] Training [15/16] Loss: 0.01942 +Epoch [220/4000] Training [16/16] Loss: 0.02109 +Epoch [220/4000] Training metric {'Train/mean dice_metric': 0.9791092872619629, 'Train/mean miou_metric': 0.9601038694381714, 'Train/mean f1': 0.9766784906387329, 'Train/mean precision': 0.9718040227890015, 'Train/mean recall': 0.981602132320404, 'Train/mean hd95_metric': 5.917878150939941} +Epoch [220/4000] Validation [1/4] Loss: 0.42647 focal_loss 0.27699 dice_loss 0.14949 +Epoch [220/4000] Validation [2/4] Loss: 0.35929 focal_loss 0.13417 dice_loss 0.22512 +Epoch [220/4000] Validation [3/4] Loss: 0.21815 focal_loss 0.11227 dice_loss 0.10588 +Epoch [220/4000] Validation [4/4] Loss: 0.18574 focal_loss 0.06885 dice_loss 0.11689 +Epoch [220/4000] Validation metric {'Val/mean dice_metric': 0.9529412388801575, 'Val/mean miou_metric': 0.9236885905265808, 'Val/mean f1': 0.9548233151435852, 'Val/mean precision': 0.9539746642112732, 'Val/mean recall': 0.9556733965873718, 'Val/mean hd95_metric': 10.72001838684082} +Cheakpoint... +Epoch [220/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9529], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9529412388801575, 'Val/mean miou_metric': 0.9236885905265808, 'Val/mean f1': 0.9548233151435852, 'Val/mean precision': 0.9539746642112732, 'Val/mean recall': 0.9556733965873718, 'Val/mean hd95_metric': 10.72001838684082} +Epoch [221/4000] Training [1/16] Loss: 0.02327 +Epoch [221/4000] Training [2/16] Loss: 0.02446 +Epoch [221/4000] Training [3/16] Loss: 0.02612 +Epoch [221/4000] Training [4/16] Loss: 0.03081 +Epoch [221/4000] Training [5/16] Loss: 0.03301 +Epoch [221/4000] Training [6/16] Loss: 0.03276 +Epoch [221/4000] Training [7/16] Loss: 0.02249 +Epoch [221/4000] Training [8/16] Loss: 0.03137 +Epoch [221/4000] Training [9/16] Loss: 0.02007 +Epoch [221/4000] Training [10/16] Loss: 0.02144 +Epoch [221/4000] Training [11/16] Loss: 0.02632 +Epoch [221/4000] Training [12/16] Loss: 0.02167 +Epoch [221/4000] Training [13/16] Loss: 0.02957 +Epoch [221/4000] Training [14/16] Loss: 0.02244 +Epoch [221/4000] Training [15/16] Loss: 0.02248 +Epoch [221/4000] Training [16/16] Loss: 0.02590 +Epoch [221/4000] Training metric {'Train/mean dice_metric': 0.9793936610221863, 'Train/mean miou_metric': 0.9608014822006226, 'Train/mean f1': 0.979712724685669, 'Train/mean precision': 0.9745614528656006, 'Train/mean recall': 0.9849187731742859, 'Train/mean hd95_metric': 3.38411808013916} +Epoch [221/4000] Validation [1/4] Loss: 0.11245 focal_loss 0.05812 dice_loss 0.05433 +Epoch [221/4000] Validation [2/4] Loss: 0.14913 focal_loss 0.04971 dice_loss 0.09942 +Epoch [221/4000] Validation [3/4] Loss: 0.15080 focal_loss 0.07479 dice_loss 0.07601 +Epoch [221/4000] Validation [4/4] Loss: 0.18306 focal_loss 0.06650 dice_loss 0.11656 +Epoch [221/4000] Validation metric {'Val/mean dice_metric': 0.9600960612297058, 'Val/mean miou_metric': 0.9318763613700867, 'Val/mean f1': 0.9642019867897034, 'Val/mean precision': 0.9599382281303406, 'Val/mean recall': 0.9685037732124329, 'Val/mean hd95_metric': 7.682415962219238} +Cheakpoint... +Epoch [221/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9601], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9600960612297058, 'Val/mean miou_metric': 0.9318763613700867, 'Val/mean f1': 0.9642019867897034, 'Val/mean precision': 0.9599382281303406, 'Val/mean recall': 0.9685037732124329, 'Val/mean hd95_metric': 7.682415962219238} +Epoch [222/4000] Training [1/16] Loss: 0.02570 +Epoch [222/4000] Training [2/16] Loss: 0.01609 +Epoch [222/4000] Training [3/16] Loss: 0.03211 +Epoch [222/4000] Training [4/16] Loss: 0.01782 +Epoch [222/4000] Training [5/16] Loss: 0.02084 +Epoch [222/4000] Training [6/16] Loss: 0.02011 +Epoch [222/4000] Training [7/16] Loss: 0.01853 +Epoch [222/4000] Training [8/16] Loss: 0.02007 +Epoch [222/4000] Training [9/16] Loss: 0.02881 +Epoch [222/4000] Training [10/16] Loss: 0.02758 +Epoch [222/4000] Training [11/16] Loss: 0.01841 +Epoch [222/4000] Training [12/16] Loss: 0.02965 +Epoch [222/4000] Training [13/16] Loss: 0.05873 +Epoch [222/4000] Training [14/16] Loss: 0.02750 +Epoch [222/4000] Training [15/16] Loss: 0.01672 +Epoch [222/4000] Training [16/16] Loss: 0.02158 +Epoch [222/4000] Training metric {'Train/mean dice_metric': 0.9820722937583923, 'Train/mean miou_metric': 0.9659931063652039, 'Train/mean f1': 0.9811761975288391, 'Train/mean precision': 0.9781157970428467, 'Train/mean recall': 0.984255850315094, 'Train/mean hd95_metric': 3.0557079315185547} +Epoch [222/4000] Validation [1/4] Loss: 0.12660 focal_loss 0.06597 dice_loss 0.06063 +Epoch [222/4000] Validation [2/4] Loss: 0.33053 focal_loss 0.15139 dice_loss 0.17914 +Epoch [222/4000] Validation [3/4] Loss: 0.11786 focal_loss 0.05271 dice_loss 0.06516 +Epoch [222/4000] Validation [4/4] Loss: 0.18177 focal_loss 0.07293 dice_loss 0.10883 +Epoch [222/4000] Validation metric {'Val/mean dice_metric': 0.9591054916381836, 'Val/mean miou_metric': 0.9329172968864441, 'Val/mean f1': 0.9631121754646301, 'Val/mean precision': 0.9561691284179688, 'Val/mean recall': 0.9701567888259888, 'Val/mean hd95_metric': 8.09193229675293} +Cheakpoint... +Epoch [222/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9591], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9591054916381836, 'Val/mean miou_metric': 0.9329172968864441, 'Val/mean f1': 0.9631121754646301, 'Val/mean precision': 0.9561691284179688, 'Val/mean recall': 0.9701567888259888, 'Val/mean hd95_metric': 8.09193229675293} +Epoch [223/4000] Training [1/16] Loss: 0.01333 +Epoch [223/4000] Training [2/16] Loss: 0.02450 +Epoch [223/4000] Training [3/16] Loss: 0.02553 +Epoch [223/4000] Training [4/16] Loss: 0.02279 +Epoch [223/4000] Training [5/16] Loss: 0.03205 +Epoch [223/4000] Training [6/16] Loss: 0.02572 +Epoch [223/4000] Training [7/16] Loss: 0.01737 +Epoch [223/4000] Training [8/16] Loss: 0.01975 +Epoch [223/4000] Training [9/16] Loss: 0.02181 +Epoch [223/4000] Training [10/16] Loss: 0.01880 +Epoch [223/4000] Training [11/16] Loss: 0.02073 +Epoch [223/4000] Training [12/16] Loss: 0.01901 +Epoch [223/4000] Training [13/16] Loss: 0.02090 +Epoch [223/4000] Training [14/16] Loss: 0.02225 +Epoch [223/4000] Training [15/16] Loss: 0.02916 +Epoch [223/4000] Training [16/16] Loss: 0.02326 +Epoch [223/4000] Training metric {'Train/mean dice_metric': 0.9828529357910156, 'Train/mean miou_metric': 0.9667734503746033, 'Train/mean f1': 0.9807851314544678, 'Train/mean precision': 0.9754379987716675, 'Train/mean recall': 0.9861911535263062, 'Train/mean hd95_metric': 3.3844187259674072} +Epoch [223/4000] Validation [1/4] Loss: 0.49120 focal_loss 0.34387 dice_loss 0.14732 +Epoch [223/4000] Validation [2/4] Loss: 0.29111 focal_loss 0.13426 dice_loss 0.15685 +Epoch [223/4000] Validation [3/4] Loss: 0.18796 focal_loss 0.09304 dice_loss 0.09492 +Epoch [223/4000] Validation [4/4] Loss: 0.17535 focal_loss 0.06464 dice_loss 0.11071 +Epoch [223/4000] Validation metric {'Val/mean dice_metric': 0.9579013586044312, 'Val/mean miou_metric': 0.9315641522407532, 'Val/mean f1': 0.9597898125648499, 'Val/mean precision': 0.9589747786521912, 'Val/mean recall': 0.9606062769889832, 'Val/mean hd95_metric': 8.567692756652832} +Cheakpoint... +Epoch [223/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9579], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9579013586044312, 'Val/mean miou_metric': 0.9315641522407532, 'Val/mean f1': 0.9597898125648499, 'Val/mean precision': 0.9589747786521912, 'Val/mean recall': 0.9606062769889832, 'Val/mean hd95_metric': 8.567692756652832} +Epoch [224/4000] Training [1/16] Loss: 0.02155 +Epoch [224/4000] Training [2/16] Loss: 0.04182 +Epoch [224/4000] Training [3/16] Loss: 0.02785 +Epoch [224/4000] Training [4/16] Loss: 0.03074 +Epoch [224/4000] Training [5/16] Loss: 0.02285 +Epoch [224/4000] Training [6/16] Loss: 0.01674 +Epoch [224/4000] Training [7/16] Loss: 0.02231 +Epoch [224/4000] Training [8/16] Loss: 0.02105 +Epoch [224/4000] Training [9/16] Loss: 0.02089 +Epoch [224/4000] Training [10/16] Loss: 0.02101 +Epoch [224/4000] Training [11/16] Loss: 0.02658 +Epoch [224/4000] Training [12/16] Loss: 0.02406 +Epoch [224/4000] Training [13/16] Loss: 0.02388 +Epoch [224/4000] Training [14/16] Loss: 0.02906 +Epoch [224/4000] Training [15/16] Loss: 0.02512 +Epoch [224/4000] Training [16/16] Loss: 0.07830 +Epoch [224/4000] Training metric {'Train/mean dice_metric': 0.9817772507667542, 'Train/mean miou_metric': 0.9651056528091431, 'Train/mean f1': 0.9805071353912354, 'Train/mean precision': 0.9759244918823242, 'Train/mean recall': 0.9851329326629639, 'Train/mean hd95_metric': 3.519341468811035} +Epoch [224/4000] Validation [1/4] Loss: 0.12984 focal_loss 0.05953 dice_loss 0.07032 +Epoch [224/4000] Validation [2/4] Loss: 0.27096 focal_loss 0.12871 dice_loss 0.14225 +Epoch [224/4000] Validation [3/4] Loss: 0.14098 focal_loss 0.05371 dice_loss 0.08727 +Epoch [224/4000] Validation [4/4] Loss: 0.25016 focal_loss 0.10208 dice_loss 0.14808 +Epoch [224/4000] Validation metric {'Val/mean dice_metric': 0.9589883685112, 'Val/mean miou_metric': 0.9309369325637817, 'Val/mean f1': 0.9613259434700012, 'Val/mean precision': 0.9545332193374634, 'Val/mean recall': 0.968216061592102, 'Val/mean hd95_metric': 8.949101448059082} +Cheakpoint... +Epoch [224/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9590], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9589883685112, 'Val/mean miou_metric': 0.9309369325637817, 'Val/mean f1': 0.9613259434700012, 'Val/mean precision': 0.9545332193374634, 'Val/mean recall': 0.968216061592102, 'Val/mean hd95_metric': 8.949101448059082} +Epoch [225/4000] Training [1/16] Loss: 0.02385 +Epoch [225/4000] Training [2/16] Loss: 0.02123 +Epoch [225/4000] Training [3/16] Loss: 0.01945 +Epoch [225/4000] Training [4/16] Loss: 0.04090 +Epoch [225/4000] Training [5/16] Loss: 0.02008 +Epoch [225/4000] Training [6/16] Loss: 0.05161 +Epoch [225/4000] Training [7/16] Loss: 0.02010 +Epoch [225/4000] Training [8/16] Loss: 0.07526 +Epoch [225/4000] Training [9/16] Loss: 0.01669 +Epoch [225/4000] Training [10/16] Loss: 0.02282 +Epoch [225/4000] Training [11/16] Loss: 0.02060 +Epoch [225/4000] Training [12/16] Loss: 0.02021 +Epoch [225/4000] Training [13/16] Loss: 0.02400 +Epoch [225/4000] Training [14/16] Loss: 0.03127 +Epoch [225/4000] Training [15/16] Loss: 0.02457 +Epoch [225/4000] Training [16/16] Loss: 0.01965 +Epoch [225/4000] Training metric {'Train/mean dice_metric': 0.9831929206848145, 'Train/mean miou_metric': 0.9671956300735474, 'Train/mean f1': 0.9817467927932739, 'Train/mean precision': 0.9780415892601013, 'Train/mean recall': 0.9854801297187805, 'Train/mean hd95_metric': 3.418766975402832} +Epoch [225/4000] Validation [1/4] Loss: 0.15170 focal_loss 0.08006 dice_loss 0.07163 +Epoch [225/4000] Validation [2/4] Loss: 0.17603 focal_loss 0.05446 dice_loss 0.12157 +Epoch [225/4000] Validation [3/4] Loss: 0.11938 focal_loss 0.05303 dice_loss 0.06635 +Epoch [225/4000] Validation [4/4] Loss: 0.37680 focal_loss 0.18446 dice_loss 0.19234 +Epoch [225/4000] Validation metric {'Val/mean dice_metric': 0.9598833322525024, 'Val/mean miou_metric': 0.9324377179145813, 'Val/mean f1': 0.9623428583145142, 'Val/mean precision': 0.9580388069152832, 'Val/mean recall': 0.966685950756073, 'Val/mean hd95_metric': 7.917485237121582} +Cheakpoint... +Epoch [225/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9598833322525024, 'Val/mean miou_metric': 0.9324377179145813, 'Val/mean f1': 0.9623428583145142, 'Val/mean precision': 0.9580388069152832, 'Val/mean recall': 0.966685950756073, 'Val/mean hd95_metric': 7.917485237121582} +Epoch [226/4000] Training [1/16] Loss: 0.03718 +Epoch [226/4000] Training [2/16] Loss: 0.02652 +Epoch [226/4000] Training [3/16] Loss: 0.03150 +Epoch [226/4000] Training [4/16] Loss: 0.02434 +Epoch [226/4000] Training [5/16] Loss: 0.03053 +Epoch [226/4000] Training [6/16] Loss: 0.02096 +Epoch [226/4000] Training [7/16] Loss: 0.02050 +Epoch [226/4000] Training [8/16] Loss: 0.03749 +Epoch [226/4000] Training [9/16] Loss: 0.01891 +Epoch [226/4000] Training [10/16] Loss: 0.02392 +Epoch [226/4000] Training [11/16] Loss: 0.02109 +Epoch [226/4000] Training [12/16] Loss: 0.05565 +Epoch [226/4000] Training [13/16] Loss: 0.01720 +Epoch [226/4000] Training [14/16] Loss: 0.01745 +Epoch [226/4000] Training [15/16] Loss: 0.02469 +Epoch [226/4000] Training [16/16] Loss: 0.03580 +Epoch [226/4000] Training metric {'Train/mean dice_metric': 0.9828668832778931, 'Train/mean miou_metric': 0.9664773941040039, 'Train/mean f1': 0.981290340423584, 'Train/mean precision': 0.9774991869926453, 'Train/mean recall': 0.9851111173629761, 'Train/mean hd95_metric': 4.02758264541626} +Epoch [226/4000] Validation [1/4] Loss: 0.19039 focal_loss 0.10674 dice_loss 0.08365 +Epoch [226/4000] Validation [2/4] Loss: 0.25915 focal_loss 0.12477 dice_loss 0.13438 +Epoch [226/4000] Validation [3/4] Loss: 0.11871 focal_loss 0.04881 dice_loss 0.06990 +Epoch [226/4000] Validation [4/4] Loss: 0.38629 focal_loss 0.20155 dice_loss 0.18474 +Epoch [226/4000] Validation metric {'Val/mean dice_metric': 0.9551643133163452, 'Val/mean miou_metric': 0.9270585179328918, 'Val/mean f1': 0.9607133865356445, 'Val/mean precision': 0.9663389921188354, 'Val/mean recall': 0.9551529288291931, 'Val/mean hd95_metric': 8.951863288879395} +Cheakpoint... +Epoch [226/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9552], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9551643133163452, 'Val/mean miou_metric': 0.9270585179328918, 'Val/mean f1': 0.9607133865356445, 'Val/mean precision': 0.9663389921188354, 'Val/mean recall': 0.9551529288291931, 'Val/mean hd95_metric': 8.951863288879395} +Epoch [227/4000] Training [1/16] Loss: 0.02163 +Epoch [227/4000] Training [2/16] Loss: 0.02171 +Epoch [227/4000] Training [3/16] Loss: 0.03371 +Epoch [227/4000] Training [4/16] Loss: 0.03187 +Epoch [227/4000] Training [5/16] Loss: 0.03104 +Epoch [227/4000] Training [6/16] Loss: 0.02066 +Epoch [227/4000] Training [7/16] Loss: 0.03662 +Epoch [227/4000] Training [8/16] Loss: 0.03399 +Epoch [227/4000] Training [9/16] Loss: 0.02241 +Epoch [227/4000] Training [10/16] Loss: 0.02452 +Epoch [227/4000] Training [11/16] Loss: 0.02765 +Epoch [227/4000] Training [12/16] Loss: 0.02285 +Epoch [227/4000] Training [13/16] Loss: 0.02542 +Epoch [227/4000] Training [14/16] Loss: 0.02433 +Epoch [227/4000] Training [15/16] Loss: 0.04911 +Epoch [227/4000] Training [16/16] Loss: 0.04282 +Epoch [227/4000] Training metric {'Train/mean dice_metric': 0.9772680401802063, 'Train/mean miou_metric': 0.9577744007110596, 'Train/mean f1': 0.9761432409286499, 'Train/mean precision': 0.9719737768173218, 'Train/mean recall': 0.9803485870361328, 'Train/mean hd95_metric': 5.24435567855835} +Epoch [227/4000] Validation [1/4] Loss: 0.12918 focal_loss 0.06636 dice_loss 0.06283 +Epoch [227/4000] Validation [2/4] Loss: 0.49239 focal_loss 0.19062 dice_loss 0.30177 +Epoch [227/4000] Validation [3/4] Loss: 0.19051 focal_loss 0.07282 dice_loss 0.11769 +Epoch [227/4000] Validation [4/4] Loss: 0.27712 focal_loss 0.12168 dice_loss 0.15544 +Epoch [227/4000] Validation metric {'Val/mean dice_metric': 0.9503877758979797, 'Val/mean miou_metric': 0.920894980430603, 'Val/mean f1': 0.9574224352836609, 'Val/mean precision': 0.9514151215553284, 'Val/mean recall': 0.9635061025619507, 'Val/mean hd95_metric': 11.67249870300293} +Cheakpoint... +Epoch [227/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9504], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9503877758979797, 'Val/mean miou_metric': 0.920894980430603, 'Val/mean f1': 0.9574224352836609, 'Val/mean precision': 0.9514151215553284, 'Val/mean recall': 0.9635061025619507, 'Val/mean hd95_metric': 11.67249870300293} +Epoch [228/4000] Training [1/16] Loss: 0.02037 +Epoch [228/4000] Training [2/16] Loss: 0.02379 +Epoch [228/4000] Training [3/16] Loss: 0.01659 +Epoch [228/4000] Training [4/16] Loss: 0.01868 +Epoch [228/4000] Training [5/16] Loss: 0.02783 +Epoch [228/4000] Training [6/16] Loss: 0.02997 +Epoch [228/4000] Training [7/16] Loss: 0.02033 +Epoch [228/4000] Training [8/16] Loss: 0.03350 +Epoch [228/4000] Training [9/16] Loss: 0.02500 +Epoch [228/4000] Training [10/16] Loss: 0.01973 +Epoch [228/4000] Training [11/16] Loss: 0.03178 +Epoch [228/4000] Training [12/16] Loss: 0.02031 +Epoch [228/4000] Training [13/16] Loss: 0.03452 +Epoch [228/4000] Training [14/16] Loss: 0.02242 +Epoch [228/4000] Training [15/16] Loss: 0.02418 +Epoch [228/4000] Training [16/16] Loss: 0.01831 +Epoch [228/4000] Training metric {'Train/mean dice_metric': 0.980303168296814, 'Train/mean miou_metric': 0.9622381329536438, 'Train/mean f1': 0.9788512587547302, 'Train/mean precision': 0.9747399091720581, 'Train/mean recall': 0.9829974174499512, 'Train/mean hd95_metric': 3.269219160079956} +Epoch [228/4000] Validation [1/4] Loss: 0.46000 focal_loss 0.32168 dice_loss 0.13832 +Epoch [228/4000] Validation [2/4] Loss: 0.52984 focal_loss 0.29998 dice_loss 0.22987 +Epoch [228/4000] Validation [3/4] Loss: 0.14011 focal_loss 0.06858 dice_loss 0.07153 +Epoch [228/4000] Validation [4/4] Loss: 0.25769 focal_loss 0.11343 dice_loss 0.14425 +Epoch [228/4000] Validation metric {'Val/mean dice_metric': 0.9558494687080383, 'Val/mean miou_metric': 0.9270197749137878, 'Val/mean f1': 0.9600668549537659, 'Val/mean precision': 0.960281252861023, 'Val/mean recall': 0.9598527550697327, 'Val/mean hd95_metric': 7.941728115081787} +Cheakpoint... +Epoch [228/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9558], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9558494687080383, 'Val/mean miou_metric': 0.9270197749137878, 'Val/mean f1': 0.9600668549537659, 'Val/mean precision': 0.960281252861023, 'Val/mean recall': 0.9598527550697327, 'Val/mean hd95_metric': 7.941728115081787} +Epoch [229/4000] Training [1/16] Loss: 0.04171 +Epoch [229/4000] Training [2/16] Loss: 0.03256 +Epoch [229/4000] Training [3/16] Loss: 0.02167 +Epoch [229/4000] Training [4/16] Loss: 0.04035 +Epoch [229/4000] Training [5/16] Loss: 0.05934 +Epoch [229/4000] Training [6/16] Loss: 0.02279 +Epoch [229/4000] Training [7/16] Loss: 0.07555 +Epoch [229/4000] Training [8/16] Loss: 0.02450 +Epoch [229/4000] Training [9/16] Loss: 0.02035 +Epoch [229/4000] Training [10/16] Loss: 0.02870 +Epoch [229/4000] Training [11/16] Loss: 0.15283 +Epoch [229/4000] Training [12/16] Loss: 0.02133 +Epoch [229/4000] Training [13/16] Loss: 0.02345 +Epoch [229/4000] Training [14/16] Loss: 0.01942 +Epoch [229/4000] Training [15/16] Loss: 0.02495 +Epoch [229/4000] Training [16/16] Loss: 0.02311 +Epoch [229/4000] Training metric {'Train/mean dice_metric': 0.9786538481712341, 'Train/mean miou_metric': 0.959655225276947, 'Train/mean f1': 0.976722002029419, 'Train/mean precision': 0.9725794792175293, 'Train/mean recall': 0.9808999300003052, 'Train/mean hd95_metric': 3.857943534851074} +Epoch [229/4000] Validation [1/4] Loss: 0.12076 focal_loss 0.06044 dice_loss 0.06033 +Epoch [229/4000] Validation [2/4] Loss: 0.34297 focal_loss 0.12215 dice_loss 0.22081 +Epoch [229/4000] Validation [3/4] Loss: 0.12165 focal_loss 0.05228 dice_loss 0.06936 +Epoch [229/4000] Validation [4/4] Loss: 0.17083 focal_loss 0.07167 dice_loss 0.09916 +Epoch [229/4000] Validation metric {'Val/mean dice_metric': 0.9543657302856445, 'Val/mean miou_metric': 0.9259366989135742, 'Val/mean f1': 0.9578161835670471, 'Val/mean precision': 0.9471070170402527, 'Val/mean recall': 0.9687703251838684, 'Val/mean hd95_metric': 9.119185447692871} +Cheakpoint... +Epoch [229/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9544], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9543657302856445, 'Val/mean miou_metric': 0.9259366989135742, 'Val/mean f1': 0.9578161835670471, 'Val/mean precision': 0.9471070170402527, 'Val/mean recall': 0.9687703251838684, 'Val/mean hd95_metric': 9.119185447692871} +Epoch [230/4000] Training [1/16] Loss: 0.02683 +Epoch [230/4000] Training [2/16] Loss: 0.04384 +Epoch [230/4000] Training [3/16] Loss: 0.04059 +Epoch [230/4000] Training [4/16] Loss: 0.02611 +Epoch [230/4000] Training [5/16] Loss: 0.03128 +Epoch [230/4000] Training [6/16] Loss: 0.02816 +Epoch [230/4000] Training [7/16] Loss: 0.04317 +Epoch [230/4000] Training [8/16] Loss: 0.03583 +Epoch [230/4000] Training [9/16] Loss: 0.02846 +Epoch [230/4000] Training [10/16] Loss: 0.02033 +Epoch [230/4000] Training [11/16] Loss: 0.03696 +Epoch [230/4000] Training [12/16] Loss: 0.02143 +Epoch [230/4000] Training [13/16] Loss: 0.02615 +Epoch [230/4000] Training [14/16] Loss: 0.02322 +Epoch [230/4000] Training [15/16] Loss: 0.02264 +Epoch [230/4000] Training [16/16] Loss: 0.02053 +Epoch [230/4000] Training metric {'Train/mean dice_metric': 0.9814471006393433, 'Train/mean miou_metric': 0.9637588858604431, 'Train/mean f1': 0.9785872101783752, 'Train/mean precision': 0.9740843772888184, 'Train/mean recall': 0.9831318855285645, 'Train/mean hd95_metric': 3.9374523162841797} +Epoch [230/4000] Validation [1/4] Loss: 0.20408 focal_loss 0.11415 dice_loss 0.08993 +Epoch [230/4000] Validation [2/4] Loss: 0.35116 focal_loss 0.14292 dice_loss 0.20824 +Epoch [230/4000] Validation [3/4] Loss: 0.11791 focal_loss 0.05363 dice_loss 0.06428 +Epoch [230/4000] Validation [4/4] Loss: 0.22082 focal_loss 0.10875 dice_loss 0.11207 +Epoch [230/4000] Validation metric {'Val/mean dice_metric': 0.9576520919799805, 'Val/mean miou_metric': 0.9302999377250671, 'Val/mean f1': 0.9604670405387878, 'Val/mean precision': 0.9577166438102722, 'Val/mean recall': 0.963233232498169, 'Val/mean hd95_metric': 8.530645370483398} +Cheakpoint... +Epoch [230/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9577], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576520919799805, 'Val/mean miou_metric': 0.9302999377250671, 'Val/mean f1': 0.9604670405387878, 'Val/mean precision': 0.9577166438102722, 'Val/mean recall': 0.963233232498169, 'Val/mean hd95_metric': 8.530645370483398} +Epoch [231/4000] Training [1/16] Loss: 0.02499 +Epoch [231/4000] Training [2/16] Loss: 0.08549 +Epoch [231/4000] Training [3/16] Loss: 0.01914 +Epoch [231/4000] Training [4/16] Loss: 0.02159 +Epoch [231/4000] Training [5/16] Loss: 0.01697 +Epoch [231/4000] Training [6/16] Loss: 0.02391 +Epoch [231/4000] Training [7/16] Loss: 0.01976 +Epoch [231/4000] Training [8/16] Loss: 0.02128 +Epoch [231/4000] Training [9/16] Loss: 0.02045 +Epoch [231/4000] Training [10/16] Loss: 0.02020 +Epoch [231/4000] Training [11/16] Loss: 0.03082 +Epoch [231/4000] Training [12/16] Loss: 0.02225 +Epoch [231/4000] Training [13/16] Loss: 0.09566 +Epoch [231/4000] Training [14/16] Loss: 0.03005 +Epoch [231/4000] Training [15/16] Loss: 0.02376 +Epoch [231/4000] Training [16/16] Loss: 0.02601 +Epoch [231/4000] Training metric {'Train/mean dice_metric': 0.9803170561790466, 'Train/mean miou_metric': 0.9636644124984741, 'Train/mean f1': 0.9785842895507812, 'Train/mean precision': 0.9725093245506287, 'Train/mean recall': 0.9847356677055359, 'Train/mean hd95_metric': 2.755462408065796} +Epoch [231/4000] Validation [1/4] Loss: 0.11690 focal_loss 0.06156 dice_loss 0.05534 +Epoch [231/4000] Validation [2/4] Loss: 0.29889 focal_loss 0.14455 dice_loss 0.15434 +Epoch [231/4000] Validation [3/4] Loss: 0.08817 focal_loss 0.03364 dice_loss 0.05453 +Epoch [231/4000] Validation [4/4] Loss: 0.18154 focal_loss 0.06399 dice_loss 0.11755 +Epoch [231/4000] Validation metric {'Val/mean dice_metric': 0.959911048412323, 'Val/mean miou_metric': 0.9327467083930969, 'Val/mean f1': 0.9621766209602356, 'Val/mean precision': 0.9599985480308533, 'Val/mean recall': 0.9643646478652954, 'Val/mean hd95_metric': 6.979666233062744} +Cheakpoint... +Epoch [231/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959911048412323, 'Val/mean miou_metric': 0.9327467083930969, 'Val/mean f1': 0.9621766209602356, 'Val/mean precision': 0.9599985480308533, 'Val/mean recall': 0.9643646478652954, 'Val/mean hd95_metric': 6.979666233062744} +Epoch [232/4000] Training [1/16] Loss: 0.01767 +Epoch [232/4000] Training [2/16] Loss: 0.02306 +Epoch [232/4000] Training [3/16] Loss: 0.02802 +Epoch [232/4000] Training [4/16] Loss: 0.01905 +Epoch [232/4000] Training [5/16] Loss: 0.01801 +Epoch [232/4000] Training [6/16] Loss: 0.01818 +Epoch [232/4000] Training [7/16] Loss: 0.02223 +Epoch [232/4000] Training [8/16] Loss: 0.01913 +Epoch [232/4000] Training [9/16] Loss: 0.02056 +Epoch [232/4000] Training [10/16] Loss: 0.02231 +Epoch [232/4000] Training [11/16] Loss: 0.02591 +Epoch [232/4000] Training [12/16] Loss: 0.02398 +Epoch [232/4000] Training [13/16] Loss: 0.01878 +Epoch [232/4000] Training [14/16] Loss: 0.02188 +Epoch [232/4000] Training [15/16] Loss: 0.02572 +Epoch [232/4000] Training [16/16] Loss: 0.02246 +Epoch [232/4000] Training metric {'Train/mean dice_metric': 0.9843893051147461, 'Train/mean miou_metric': 0.9693527221679688, 'Train/mean f1': 0.9821116924285889, 'Train/mean precision': 0.9783946871757507, 'Train/mean recall': 0.9858570098876953, 'Train/mean hd95_metric': 2.709949493408203} +Epoch [232/4000] Validation [1/4] Loss: 0.12039 focal_loss 0.06697 dice_loss 0.05341 +Epoch [232/4000] Validation [2/4] Loss: 0.58649 focal_loss 0.33878 dice_loss 0.24771 +Epoch [232/4000] Validation [3/4] Loss: 0.14039 focal_loss 0.06148 dice_loss 0.07890 +Epoch [232/4000] Validation [4/4] Loss: 0.16263 focal_loss 0.06222 dice_loss 0.10041 +Epoch [232/4000] Validation metric {'Val/mean dice_metric': 0.9599723815917969, 'Val/mean miou_metric': 0.9346756935119629, 'Val/mean f1': 0.9642841815948486, 'Val/mean precision': 0.9613456130027771, 'Val/mean recall': 0.9672407507896423, 'Val/mean hd95_metric': 7.3593878746032715} +Cheakpoint... +Epoch [232/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9600], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599723815917969, 'Val/mean miou_metric': 0.9346756935119629, 'Val/mean f1': 0.9642841815948486, 'Val/mean precision': 0.9613456130027771, 'Val/mean recall': 0.9672407507896423, 'Val/mean hd95_metric': 7.3593878746032715} +Epoch [233/4000] Training [1/16] Loss: 0.02512 +Epoch [233/4000] Training [2/16] Loss: 0.04216 +Epoch [233/4000] Training [3/16] Loss: 0.01667 +Epoch [233/4000] Training [4/16] Loss: 0.02290 +Epoch [233/4000] Training [5/16] Loss: 0.03177 +Epoch [233/4000] Training [6/16] Loss: 0.01903 +Epoch [233/4000] Training [7/16] Loss: 0.01934 +Epoch [233/4000] Training [8/16] Loss: 0.02293 +Epoch [233/4000] Training [9/16] Loss: 0.01625 +Epoch [233/4000] Training [10/16] Loss: 0.02448 +Epoch [233/4000] Training [11/16] Loss: 0.02256 +Epoch [233/4000] Training [12/16] Loss: 0.01855 +Epoch [233/4000] Training [13/16] Loss: 0.01797 +Epoch [233/4000] Training [14/16] Loss: 0.02931 +Epoch [233/4000] Training [15/16] Loss: 0.02115 +Epoch [233/4000] Training [16/16] Loss: 0.02318 +Epoch [233/4000] Training metric {'Train/mean dice_metric': 0.9829790592193604, 'Train/mean miou_metric': 0.9667654037475586, 'Train/mean f1': 0.9795703887939453, 'Train/mean precision': 0.9753400683403015, 'Train/mean recall': 0.9838376045227051, 'Train/mean hd95_metric': 3.143965005874634} +Epoch [233/4000] Validation [1/4] Loss: 0.27234 focal_loss 0.13717 dice_loss 0.13516 +Epoch [233/4000] Validation [2/4] Loss: 0.20503 focal_loss 0.07177 dice_loss 0.13326 +Epoch [233/4000] Validation [3/4] Loss: 0.11513 focal_loss 0.05071 dice_loss 0.06442 +Epoch [233/4000] Validation [4/4] Loss: 0.25414 focal_loss 0.13504 dice_loss 0.11910 +Epoch [233/4000] Validation metric {'Val/mean dice_metric': 0.9616697430610657, 'Val/mean miou_metric': 0.9346920251846313, 'Val/mean f1': 0.9616360664367676, 'Val/mean precision': 0.9596158266067505, 'Val/mean recall': 0.9636648297309875, 'Val/mean hd95_metric': 7.931021213531494} +Cheakpoint... +Epoch [233/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616697430610657, 'Val/mean miou_metric': 0.9346920251846313, 'Val/mean f1': 0.9616360664367676, 'Val/mean precision': 0.9596158266067505, 'Val/mean recall': 0.9636648297309875, 'Val/mean hd95_metric': 7.931021213531494} +Epoch [234/4000] Training [1/16] Loss: 0.02363 +Epoch [234/4000] Training [2/16] Loss: 0.02269 +Epoch [234/4000] Training [3/16] Loss: 0.03054 +Epoch [234/4000] Training [4/16] Loss: 0.03453 +Epoch [234/4000] Training [5/16] Loss: 0.01575 +Epoch [234/4000] Training [6/16] Loss: 0.02138 +Epoch [234/4000] Training [7/16] Loss: 0.01492 +Epoch [234/4000] Training [8/16] Loss: 0.01960 +Epoch [234/4000] Training [9/16] Loss: 0.01747 +Epoch [234/4000] Training [10/16] Loss: 0.01620 +Epoch [234/4000] Training [11/16] Loss: 0.01576 +Epoch [234/4000] Training [12/16] Loss: 0.01676 +Epoch [234/4000] Training [13/16] Loss: 0.12209 +Epoch [234/4000] Training [14/16] Loss: 0.01695 +Epoch [234/4000] Training [15/16] Loss: 0.02844 +Epoch [234/4000] Training [16/16] Loss: 0.01617 +Epoch [234/4000] Training metric {'Train/mean dice_metric': 0.9842842817306519, 'Train/mean miou_metric': 0.9694526195526123, 'Train/mean f1': 0.9823917746543884, 'Train/mean precision': 0.9782458543777466, 'Train/mean recall': 0.9865731000900269, 'Train/mean hd95_metric': 2.3460991382598877} +Epoch [234/4000] Validation [1/4] Loss: 0.51757 focal_loss 0.37033 dice_loss 0.14724 +Epoch [234/4000] Validation [2/4] Loss: 0.16882 focal_loss 0.06598 dice_loss 0.10284 +Epoch [234/4000] Validation [3/4] Loss: 0.12976 focal_loss 0.05131 dice_loss 0.07845 +Epoch [234/4000] Validation [4/4] Loss: 0.18844 focal_loss 0.10051 dice_loss 0.08794 +Epoch [234/4000] Validation metric {'Val/mean dice_metric': 0.9591150283813477, 'Val/mean miou_metric': 0.9331650733947754, 'Val/mean f1': 0.9617672562599182, 'Val/mean precision': 0.9590572118759155, 'Val/mean recall': 0.9644926190376282, 'Val/mean hd95_metric': 8.038471221923828} +Cheakpoint... +Epoch [234/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9591], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9591150283813477, 'Val/mean miou_metric': 0.9331650733947754, 'Val/mean f1': 0.9617672562599182, 'Val/mean precision': 0.9590572118759155, 'Val/mean recall': 0.9644926190376282, 'Val/mean hd95_metric': 8.038471221923828} +Epoch [235/4000] Training [1/16] Loss: 0.02571 +Epoch [235/4000] Training [2/16] Loss: 0.02336 +Epoch [235/4000] Training [3/16] Loss: 0.03419 +Epoch [235/4000] Training [4/16] Loss: 0.01899 +Epoch [235/4000] Training [5/16] Loss: 0.01494 +Epoch [235/4000] Training [6/16] Loss: 0.01897 +Epoch [235/4000] Training [7/16] Loss: 0.02788 +Epoch [235/4000] Training [8/16] Loss: 0.04570 +Epoch [235/4000] Training [9/16] Loss: 0.01848 +Epoch [235/4000] Training [10/16] Loss: 0.01988 +Epoch [235/4000] Training [11/16] Loss: 0.02104 +Epoch [235/4000] Training [12/16] Loss: 0.03754 +Epoch [235/4000] Training [13/16] Loss: 0.02369 +Epoch [235/4000] Training [14/16] Loss: 0.02153 +Epoch [235/4000] Training [15/16] Loss: 0.02029 +Epoch [235/4000] Training [16/16] Loss: 0.02751 +Epoch [235/4000] Training metric {'Train/mean dice_metric': 0.9842011332511902, 'Train/mean miou_metric': 0.9690989255905151, 'Train/mean f1': 0.9818853139877319, 'Train/mean precision': 0.9772125482559204, 'Train/mean recall': 0.9866029024124146, 'Train/mean hd95_metric': 3.0036628246307373} +Epoch [235/4000] Validation [1/4] Loss: 0.31964 focal_loss 0.19414 dice_loss 0.12550 +Epoch [235/4000] Validation [2/4] Loss: 0.36127 focal_loss 0.15153 dice_loss 0.20974 +Epoch [235/4000] Validation [3/4] Loss: 0.12373 focal_loss 0.06004 dice_loss 0.06369 +Epoch [235/4000] Validation [4/4] Loss: 0.20282 focal_loss 0.09399 dice_loss 0.10883 +Epoch [235/4000] Validation metric {'Val/mean dice_metric': 0.961439311504364, 'Val/mean miou_metric': 0.9359506368637085, 'Val/mean f1': 0.9640190601348877, 'Val/mean precision': 0.9638832807540894, 'Val/mean recall': 0.9641548991203308, 'Val/mean hd95_metric': 7.140266418457031} +Cheakpoint... +Epoch [235/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961439311504364, 'Val/mean miou_metric': 0.9359506368637085, 'Val/mean f1': 0.9640190601348877, 'Val/mean precision': 0.9638832807540894, 'Val/mean recall': 0.9641548991203308, 'Val/mean hd95_metric': 7.140266418457031} +Epoch [236/4000] Training [1/16] Loss: 0.01848 +Epoch [236/4000] Training [2/16] Loss: 0.01509 +Epoch [236/4000] Training [3/16] Loss: 0.01860 +Epoch [236/4000] Training [4/16] Loss: 0.01780 +Epoch [236/4000] Training [5/16] Loss: 0.02593 +Epoch [236/4000] Training [6/16] Loss: 0.02104 +Epoch [236/4000] Training [7/16] Loss: 0.03202 +Epoch [236/4000] Training [8/16] Loss: 0.02901 +Epoch [236/4000] Training [9/16] Loss: 0.02048 +Epoch [236/4000] Training [10/16] Loss: 0.02110 +Epoch [236/4000] Training [11/16] Loss: 0.02302 +Epoch [236/4000] Training [12/16] Loss: 0.03125 +Epoch [236/4000] Training [13/16] Loss: 0.02235 +Epoch [236/4000] Training [14/16] Loss: 0.02155 +Epoch [236/4000] Training [15/16] Loss: 0.04073 +Epoch [236/4000] Training [16/16] Loss: 0.02117 +Epoch [236/4000] Training metric {'Train/mean dice_metric': 0.9822885990142822, 'Train/mean miou_metric': 0.9669579863548279, 'Train/mean f1': 0.9816344976425171, 'Train/mean precision': 0.9765221476554871, 'Train/mean recall': 0.9868006706237793, 'Train/mean hd95_metric': 2.2394747734069824} +Epoch [236/4000] Validation [1/4] Loss: 0.21707 focal_loss 0.11709 dice_loss 0.09998 +Epoch [236/4000] Validation [2/4] Loss: 0.29069 focal_loss 0.12904 dice_loss 0.16165 +Epoch [236/4000] Validation [3/4] Loss: 0.09934 focal_loss 0.03655 dice_loss 0.06279 +Epoch [236/4000] Validation [4/4] Loss: 0.21274 focal_loss 0.08641 dice_loss 0.12633 +Epoch [236/4000] Validation metric {'Val/mean dice_metric': 0.9608010053634644, 'Val/mean miou_metric': 0.9348870515823364, 'Val/mean f1': 0.9644935727119446, 'Val/mean precision': 0.9618440866470337, 'Val/mean recall': 0.9671578407287598, 'Val/mean hd95_metric': 6.530116081237793} +Cheakpoint... +Epoch [236/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608010053634644, 'Val/mean miou_metric': 0.9348870515823364, 'Val/mean f1': 0.9644935727119446, 'Val/mean precision': 0.9618440866470337, 'Val/mean recall': 0.9671578407287598, 'Val/mean hd95_metric': 6.530116081237793} +Epoch [237/4000] Training [1/16] Loss: 0.01704 +Epoch [237/4000] Training [2/16] Loss: 0.01692 +Epoch [237/4000] Training [3/16] Loss: 0.01617 +Epoch [237/4000] Training [4/16] Loss: 0.01663 +Epoch [237/4000] Training [5/16] Loss: 0.02528 +Epoch [237/4000] Training [6/16] Loss: 0.02054 +Epoch [237/4000] Training [7/16] Loss: 0.02098 +Epoch [237/4000] Training [8/16] Loss: 0.01758 +Epoch [237/4000] Training [9/16] Loss: 0.01918 +Epoch [237/4000] Training [10/16] Loss: 0.01915 +Epoch [237/4000] Training [11/16] Loss: 0.02019 +Epoch [237/4000] Training [12/16] Loss: 0.02868 +Epoch [237/4000] Training [13/16] Loss: 0.07578 +Epoch [237/4000] Training [14/16] Loss: 0.01794 +Epoch [237/4000] Training [15/16] Loss: 0.02023 +Epoch [237/4000] Training [16/16] Loss: 0.01896 +Epoch [237/4000] Training metric {'Train/mean dice_metric': 0.9841450452804565, 'Train/mean miou_metric': 0.9693584442138672, 'Train/mean f1': 0.981394350528717, 'Train/mean precision': 0.9767020344734192, 'Train/mean recall': 0.9861319065093994, 'Train/mean hd95_metric': 2.6767044067382812} +Epoch [237/4000] Validation [1/4] Loss: 0.22205 focal_loss 0.11750 dice_loss 0.10455 +Epoch [237/4000] Validation [2/4] Loss: 0.56672 focal_loss 0.28584 dice_loss 0.28088 +Epoch [237/4000] Validation [3/4] Loss: 0.08625 focal_loss 0.03197 dice_loss 0.05429 +Epoch [237/4000] Validation [4/4] Loss: 0.23697 focal_loss 0.10907 dice_loss 0.12790 +Epoch [237/4000] Validation metric {'Val/mean dice_metric': 0.9587364196777344, 'Val/mean miou_metric': 0.9318426847457886, 'Val/mean f1': 0.9609152674674988, 'Val/mean precision': 0.9633097648620605, 'Val/mean recall': 0.9585326910018921, 'Val/mean hd95_metric': 7.6631317138671875} +Cheakpoint... +Epoch [237/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9587], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9587364196777344, 'Val/mean miou_metric': 0.9318426847457886, 'Val/mean f1': 0.9609152674674988, 'Val/mean precision': 0.9633097648620605, 'Val/mean recall': 0.9585326910018921, 'Val/mean hd95_metric': 7.6631317138671875} +Epoch [238/4000] Training [1/16] Loss: 0.07260 +Epoch [238/4000] Training [2/16] Loss: 0.02015 +Epoch [238/4000] Training [3/16] Loss: 0.03629 +Epoch [238/4000] Training [4/16] Loss: 0.02155 +Epoch [238/4000] Training [5/16] Loss: 0.02457 +Epoch [238/4000] Training [6/16] Loss: 0.01743 +Epoch [238/4000] Training [7/16] Loss: 0.02752 +Epoch [238/4000] Training [8/16] Loss: 0.05054 +Epoch [238/4000] Training [9/16] Loss: 0.05504 +Epoch [238/4000] Training [10/16] Loss: 0.02518 +Epoch [238/4000] Training [11/16] Loss: 0.01775 +Epoch [238/4000] Training [12/16] Loss: 0.05621 +Epoch [238/4000] Training [13/16] Loss: 0.02781 +Epoch [238/4000] Training [14/16] Loss: 0.02105 +Epoch [238/4000] Training [15/16] Loss: 0.02165 +Epoch [238/4000] Training [16/16] Loss: 0.02137 +Epoch [238/4000] Training metric {'Train/mean dice_metric': 0.9794753789901733, 'Train/mean miou_metric': 0.9609909653663635, 'Train/mean f1': 0.9782748222351074, 'Train/mean precision': 0.9743303656578064, 'Train/mean recall': 0.9822514057159424, 'Train/mean hd95_metric': 3.76405668258667} +Epoch [238/4000] Validation [1/4] Loss: 0.13760 focal_loss 0.07248 dice_loss 0.06512 +Epoch [238/4000] Validation [2/4] Loss: 0.45837 focal_loss 0.24240 dice_loss 0.21597 +Epoch [238/4000] Validation [3/4] Loss: 0.13415 focal_loss 0.05894 dice_loss 0.07522 +Epoch [238/4000] Validation [4/4] Loss: 0.29968 focal_loss 0.14955 dice_loss 0.15013 +Epoch [238/4000] Validation metric {'Val/mean dice_metric': 0.9573609232902527, 'Val/mean miou_metric': 0.9292945861816406, 'Val/mean f1': 0.9616223573684692, 'Val/mean precision': 0.9567543864250183, 'Val/mean recall': 0.9665399789810181, 'Val/mean hd95_metric': 8.098756790161133} +Cheakpoint... +Epoch [238/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9574], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573609232902527, 'Val/mean miou_metric': 0.9292945861816406, 'Val/mean f1': 0.9616223573684692, 'Val/mean precision': 0.9567543864250183, 'Val/mean recall': 0.9665399789810181, 'Val/mean hd95_metric': 8.098756790161133} +Epoch [239/4000] Training [1/16] Loss: 0.01842 +Epoch [239/4000] Training [2/16] Loss: 0.02265 +Epoch [239/4000] Training [3/16] Loss: 0.02256 +Epoch [239/4000] Training [4/16] Loss: 0.02377 +Epoch [239/4000] Training [5/16] Loss: 0.02244 +Epoch [239/4000] Training [6/16] Loss: 0.02464 +Epoch [239/4000] Training [7/16] Loss: 0.01635 +Epoch [239/4000] Training [8/16] Loss: 0.02071 +Epoch [239/4000] Training [9/16] Loss: 0.01689 +Epoch [239/4000] Training [10/16] Loss: 0.02372 +Epoch [239/4000] Training [11/16] Loss: 0.02615 +Epoch [239/4000] Training [12/16] Loss: 0.01882 +Epoch [239/4000] Training [13/16] Loss: 0.02676 +Epoch [239/4000] Training [14/16] Loss: 0.02458 +Epoch [239/4000] Training [15/16] Loss: 0.03020 +Epoch [239/4000] Training [16/16] Loss: 0.02949 +Epoch [239/4000] Training metric {'Train/mean dice_metric': 0.9812880754470825, 'Train/mean miou_metric': 0.9643304944038391, 'Train/mean f1': 0.9804697632789612, 'Train/mean precision': 0.9757736921310425, 'Train/mean recall': 0.9852113127708435, 'Train/mean hd95_metric': 3.6467392444610596} +Epoch [239/4000] Validation [1/4] Loss: 0.38768 focal_loss 0.24323 dice_loss 0.14445 +Epoch [239/4000] Validation [2/4] Loss: 0.34930 focal_loss 0.15507 dice_loss 0.19423 +Epoch [239/4000] Validation [3/4] Loss: 0.15797 focal_loss 0.07213 dice_loss 0.08584 +Epoch [239/4000] Validation [4/4] Loss: 0.26848 focal_loss 0.09866 dice_loss 0.16982 +Epoch [239/4000] Validation metric {'Val/mean dice_metric': 0.9563595056533813, 'Val/mean miou_metric': 0.9286746978759766, 'Val/mean f1': 0.959393322467804, 'Val/mean precision': 0.9586615562438965, 'Val/mean recall': 0.9601262807846069, 'Val/mean hd95_metric': 8.518142700195312} +Cheakpoint... +Epoch [239/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9564], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9563595056533813, 'Val/mean miou_metric': 0.9286746978759766, 'Val/mean f1': 0.959393322467804, 'Val/mean precision': 0.9586615562438965, 'Val/mean recall': 0.9601262807846069, 'Val/mean hd95_metric': 8.518142700195312} +Epoch [240/4000] Training [1/16] Loss: 0.02344 +Epoch [240/4000] Training [2/16] Loss: 0.01878 +Epoch [240/4000] Training [3/16] Loss: 0.03250 +Epoch [240/4000] Training [4/16] Loss: 0.02409 +Epoch [240/4000] Training [5/16] Loss: 0.02491 +Epoch [240/4000] Training [6/16] Loss: 0.02366 +Epoch [240/4000] Training [7/16] Loss: 0.02516 +Epoch [240/4000] Training [8/16] Loss: 0.01756 +Epoch [240/4000] Training [9/16] Loss: 0.02774 +Epoch [240/4000] Training [10/16] Loss: 0.01800 +Epoch [240/4000] Training [11/16] Loss: 0.01960 +Epoch [240/4000] Training [12/16] Loss: 0.02353 +Epoch [240/4000] Training [13/16] Loss: 0.06810 +Epoch [240/4000] Training [14/16] Loss: 0.01626 +Epoch [240/4000] Training [15/16] Loss: 0.01986 +Epoch [240/4000] Training [16/16] Loss: 0.02143 +Epoch [240/4000] Training metric {'Train/mean dice_metric': 0.9827358722686768, 'Train/mean miou_metric': 0.9664535522460938, 'Train/mean f1': 0.9804434180259705, 'Train/mean precision': 0.9764115214347839, 'Train/mean recall': 0.984508752822876, 'Train/mean hd95_metric': 3.634803295135498} +Epoch [240/4000] Validation [1/4] Loss: 0.17901 focal_loss 0.10000 dice_loss 0.07901 +Epoch [240/4000] Validation [2/4] Loss: 0.17381 focal_loss 0.06719 dice_loss 0.10662 +Epoch [240/4000] Validation [3/4] Loss: 0.15097 focal_loss 0.06270 dice_loss 0.08828 +Epoch [240/4000] Validation [4/4] Loss: 0.29711 focal_loss 0.15697 dice_loss 0.14013 +Epoch [240/4000] Validation metric {'Val/mean dice_metric': 0.9575166702270508, 'Val/mean miou_metric': 0.9308252334594727, 'Val/mean f1': 0.9612154960632324, 'Val/mean precision': 0.9584574103355408, 'Val/mean recall': 0.9639895558357239, 'Val/mean hd95_metric': 8.480744361877441} +Cheakpoint... +Epoch [240/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9575], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9575166702270508, 'Val/mean miou_metric': 0.9308252334594727, 'Val/mean f1': 0.9612154960632324, 'Val/mean precision': 0.9584574103355408, 'Val/mean recall': 0.9639895558357239, 'Val/mean hd95_metric': 8.480744361877441} +Epoch [241/4000] Training [1/16] Loss: 0.02527 +Epoch [241/4000] Training [2/16] Loss: 0.14939 +Epoch [241/4000] Training [3/16] Loss: 0.02516 +Epoch [241/4000] Training [4/16] Loss: 0.02149 +Epoch [241/4000] Training [5/16] Loss: 0.02682 +Epoch [241/4000] Training [6/16] Loss: 0.01916 +Epoch [241/4000] Training [7/16] Loss: 0.02530 +Epoch [241/4000] Training [8/16] Loss: 0.02071 +Epoch [241/4000] Training [9/16] Loss: 0.02232 +Epoch [241/4000] Training [10/16] Loss: 0.08137 +Epoch [241/4000] Training [11/16] Loss: 0.02295 +Epoch [241/4000] Training [12/16] Loss: 0.03929 +Epoch [241/4000] Training [13/16] Loss: 0.02462 +Epoch [241/4000] Training [14/16] Loss: 0.02339 +Epoch [241/4000] Training [15/16] Loss: 0.02639 +Epoch [241/4000] Training [16/16] Loss: 0.01646 +Epoch [241/4000] Training metric {'Train/mean dice_metric': 0.9788548350334167, 'Train/mean miou_metric': 0.9614123106002808, 'Train/mean f1': 0.9789784550666809, 'Train/mean precision': 0.9737168550491333, 'Train/mean recall': 0.9842971563339233, 'Train/mean hd95_metric': 3.5492286682128906} +Epoch [241/4000] Validation [1/4] Loss: 0.14233 focal_loss 0.08011 dice_loss 0.06222 +Epoch [241/4000] Validation [2/4] Loss: 0.21622 focal_loss 0.07890 dice_loss 0.13732 +Epoch [241/4000] Validation [3/4] Loss: 0.18079 focal_loss 0.07529 dice_loss 0.10550 +Epoch [241/4000] Validation [4/4] Loss: 0.27174 focal_loss 0.14127 dice_loss 0.13047 +Epoch [241/4000] Validation metric {'Val/mean dice_metric': 0.9564269781112671, 'Val/mean miou_metric': 0.929295539855957, 'Val/mean f1': 0.9634134769439697, 'Val/mean precision': 0.9616684913635254, 'Val/mean recall': 0.9651647210121155, 'Val/mean hd95_metric': 7.813420295715332} +Cheakpoint... +Epoch [241/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9564], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9564269781112671, 'Val/mean miou_metric': 0.929295539855957, 'Val/mean f1': 0.9634134769439697, 'Val/mean precision': 0.9616684913635254, 'Val/mean recall': 0.9651647210121155, 'Val/mean hd95_metric': 7.813420295715332} +Epoch [242/4000] Training [1/16] Loss: 0.02372 +Epoch [242/4000] Training [2/16] Loss: 0.01897 +Epoch [242/4000] Training [3/16] Loss: 0.01660 +Epoch [242/4000] Training [4/16] Loss: 0.02213 +Epoch [242/4000] Training [5/16] Loss: 0.02336 +Epoch [242/4000] Training [6/16] Loss: 0.02478 +Epoch [242/4000] Training [7/16] Loss: 0.02429 +Epoch [242/4000] Training [8/16] Loss: 0.01874 +Epoch [242/4000] Training [9/16] Loss: 0.01987 +Epoch [242/4000] Training [10/16] Loss: 0.02698 +Epoch [242/4000] Training [11/16] Loss: 0.04840 +Epoch [242/4000] Training [12/16] Loss: 0.01886 +Epoch [242/4000] Training [13/16] Loss: 0.02337 +Epoch [242/4000] Training [14/16] Loss: 0.02155 +Epoch [242/4000] Training [15/16] Loss: 0.02168 +Epoch [242/4000] Training [16/16] Loss: 0.01549 +Epoch [242/4000] Training metric {'Train/mean dice_metric': 0.9850009679794312, 'Train/mean miou_metric': 0.9705030918121338, 'Train/mean f1': 0.9829733371734619, 'Train/mean precision': 0.9782130718231201, 'Train/mean recall': 0.9877801537513733, 'Train/mean hd95_metric': 2.595217227935791} +Epoch [242/4000] Validation [1/4] Loss: 0.15236 focal_loss 0.08393 dice_loss 0.06843 +Epoch [242/4000] Validation [2/4] Loss: 0.22114 focal_loss 0.07275 dice_loss 0.14839 +Epoch [242/4000] Validation [3/4] Loss: 0.11816 focal_loss 0.04170 dice_loss 0.07646 +Epoch [242/4000] Validation [4/4] Loss: 0.21672 focal_loss 0.07152 dice_loss 0.14520 +Epoch [242/4000] Validation metric {'Val/mean dice_metric': 0.9627361297607422, 'Val/mean miou_metric': 0.9371147155761719, 'Val/mean f1': 0.9665906429290771, 'Val/mean precision': 0.9615694880485535, 'Val/mean recall': 0.9716643691062927, 'Val/mean hd95_metric': 8.235859870910645} +Cheakpoint... +Epoch [242/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9627], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9627361297607422, 'Val/mean miou_metric': 0.9371147155761719, 'Val/mean f1': 0.9665906429290771, 'Val/mean precision': 0.9615694880485535, 'Val/mean recall': 0.9716643691062927, 'Val/mean hd95_metric': 8.235859870910645} +Epoch [243/4000] Training [1/16] Loss: 0.02150 +Epoch [243/4000] Training [2/16] Loss: 0.01783 +Epoch [243/4000] Training [3/16] Loss: 0.01308 +Epoch [243/4000] Training [4/16] Loss: 0.01880 +Epoch [243/4000] Training [5/16] Loss: 0.02152 +Epoch [243/4000] Training [6/16] Loss: 0.05580 +Epoch [243/4000] Training [7/16] Loss: 0.01799 +Epoch [243/4000] Training [8/16] Loss: 0.01871 +Epoch [243/4000] Training [9/16] Loss: 0.01767 +Epoch [243/4000] Training [10/16] Loss: 0.02045 +Epoch [243/4000] Training [11/16] Loss: 0.03010 +Epoch [243/4000] Training [12/16] Loss: 0.01523 +Epoch [243/4000] Training [13/16] Loss: 0.02055 +Epoch [243/4000] Training [14/16] Loss: 0.01871 +Epoch [243/4000] Training [15/16] Loss: 0.01828 +Epoch [243/4000] Training [16/16] Loss: 0.03033 +Epoch [243/4000] Training metric {'Train/mean dice_metric': 0.9846088290214539, 'Train/mean miou_metric': 0.9706451892852783, 'Train/mean f1': 0.9831674695014954, 'Train/mean precision': 0.9785300493240356, 'Train/mean recall': 0.9878490567207336, 'Train/mean hd95_metric': 3.035797119140625} +Epoch [243/4000] Validation [1/4] Loss: 0.13756 focal_loss 0.06897 dice_loss 0.06859 +Epoch [243/4000] Validation [2/4] Loss: 0.18038 focal_loss 0.06409 dice_loss 0.11629 +Epoch [243/4000] Validation [3/4] Loss: 0.15385 focal_loss 0.06460 dice_loss 0.08925 +Epoch [243/4000] Validation [4/4] Loss: 0.21214 focal_loss 0.08990 dice_loss 0.12223 +Epoch [243/4000] Validation metric {'Val/mean dice_metric': 0.9639337658882141, 'Val/mean miou_metric': 0.9396318197250366, 'Val/mean f1': 0.967966616153717, 'Val/mean precision': 0.9650619029998779, 'Val/mean recall': 0.9708887934684753, 'Val/mean hd95_metric': 7.658350467681885} +Cheakpoint... +Epoch [243/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639337658882141, 'Val/mean miou_metric': 0.9396318197250366, 'Val/mean f1': 0.967966616153717, 'Val/mean precision': 0.9650619029998779, 'Val/mean recall': 0.9708887934684753, 'Val/mean hd95_metric': 7.658350467681885} +Epoch [244/4000] Training [1/16] Loss: 0.02441 +Epoch [244/4000] Training [2/16] Loss: 0.01916 +Epoch [244/4000] Training [3/16] Loss: 0.01514 +Epoch [244/4000] Training [4/16] Loss: 0.01672 +Epoch [244/4000] Training [5/16] Loss: 0.02532 +Epoch [244/4000] Training [6/16] Loss: 0.03076 +Epoch [244/4000] Training [7/16] Loss: 0.03511 +Epoch [244/4000] Training [8/16] Loss: 0.01839 +Epoch [244/4000] Training [9/16] Loss: 0.01687 +Epoch [244/4000] Training [10/16] Loss: 0.01879 +Epoch [244/4000] Training [11/16] Loss: 0.03008 +Epoch [244/4000] Training [12/16] Loss: 0.01746 +Epoch [244/4000] Training [13/16] Loss: 0.01530 +Epoch [244/4000] Training [14/16] Loss: 0.01874 +Epoch [244/4000] Training [15/16] Loss: 0.02372 +Epoch [244/4000] Training [16/16] Loss: 0.02195 +Epoch [244/4000] Training metric {'Train/mean dice_metric': 0.9842962026596069, 'Train/mean miou_metric': 0.9693204760551453, 'Train/mean f1': 0.9825503826141357, 'Train/mean precision': 0.9783453345298767, 'Train/mean recall': 0.9867917895317078, 'Train/mean hd95_metric': 2.3851139545440674} +Epoch [244/4000] Validation [1/4] Loss: 0.12147 focal_loss 0.06379 dice_loss 0.05768 +Epoch [244/4000] Validation [2/4] Loss: 0.33702 focal_loss 0.14732 dice_loss 0.18970 +Epoch [244/4000] Validation [3/4] Loss: 0.15657 focal_loss 0.06937 dice_loss 0.08720 +Epoch [244/4000] Validation [4/4] Loss: 0.24777 focal_loss 0.12025 dice_loss 0.12752 +Epoch [244/4000] Validation metric {'Val/mean dice_metric': 0.9603222608566284, 'Val/mean miou_metric': 0.9343310594558716, 'Val/mean f1': 0.963966965675354, 'Val/mean precision': 0.9565935730934143, 'Val/mean recall': 0.9714549779891968, 'Val/mean hd95_metric': 8.750874519348145} +Cheakpoint... +Epoch [244/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9603], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9603222608566284, 'Val/mean miou_metric': 0.9343310594558716, 'Val/mean f1': 0.963966965675354, 'Val/mean precision': 0.9565935730934143, 'Val/mean recall': 0.9714549779891968, 'Val/mean hd95_metric': 8.750874519348145} +Epoch [245/4000] Training [1/16] Loss: 0.02379 +Epoch [245/4000] Training [2/16] Loss: 0.01913 +Epoch [245/4000] Training [3/16] Loss: 0.01871 +Epoch [245/4000] Training [4/16] Loss: 0.02124 +Epoch [245/4000] Training [5/16] Loss: 0.01323 +Epoch [245/4000] Training [6/16] Loss: 0.02566 +Epoch [245/4000] Training [7/16] Loss: 0.01876 +Epoch [245/4000] Training [8/16] Loss: 0.04159 +Epoch [245/4000] Training [9/16] Loss: 0.01685 +Epoch [245/4000] Training [10/16] Loss: 0.01660 +Epoch [245/4000] Training [11/16] Loss: 0.02032 +Epoch [245/4000] Training [12/16] Loss: 0.02127 +Epoch [245/4000] Training [13/16] Loss: 0.02062 +Epoch [245/4000] Training [14/16] Loss: 0.03186 +Epoch [245/4000] Training [15/16] Loss: 0.01625 +Epoch [245/4000] Training [16/16] Loss: 0.02326 +Epoch [245/4000] Training metric {'Train/mean dice_metric': 0.9846687912940979, 'Train/mean miou_metric': 0.9701688289642334, 'Train/mean f1': 0.9815636277198792, 'Train/mean precision': 0.9756208658218384, 'Train/mean recall': 0.9875791668891907, 'Train/mean hd95_metric': 2.9963808059692383} +Epoch [245/4000] Validation [1/4] Loss: 0.09839 focal_loss 0.04430 dice_loss 0.05409 +Epoch [245/4000] Validation [2/4] Loss: 0.24685 focal_loss 0.08882 dice_loss 0.15803 +Epoch [245/4000] Validation [3/4] Loss: 0.13582 focal_loss 0.06328 dice_loss 0.07254 +Epoch [245/4000] Validation [4/4] Loss: 0.22840 focal_loss 0.09110 dice_loss 0.13731 +Epoch [245/4000] Validation metric {'Val/mean dice_metric': 0.9599801301956177, 'Val/mean miou_metric': 0.9346572756767273, 'Val/mean f1': 0.9622805714607239, 'Val/mean precision': 0.9552162289619446, 'Val/mean recall': 0.9694502353668213, 'Val/mean hd95_metric': 8.159568786621094} +Cheakpoint... +Epoch [245/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9600], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599801301956177, 'Val/mean miou_metric': 0.9346572756767273, 'Val/mean f1': 0.9622805714607239, 'Val/mean precision': 0.9552162289619446, 'Val/mean recall': 0.9694502353668213, 'Val/mean hd95_metric': 8.159568786621094} +Epoch [246/4000] Training [1/16] Loss: 0.03276 +Epoch [246/4000] Training [2/16] Loss: 0.01988 +Epoch [246/4000] Training [3/16] Loss: 0.02990 +Epoch [246/4000] Training [4/16] Loss: 0.02767 +Epoch [246/4000] Training [5/16] Loss: 0.02252 +Epoch [246/4000] Training [6/16] Loss: 0.02781 +Epoch [246/4000] Training [7/16] Loss: 0.02337 +Epoch [246/4000] Training [8/16] Loss: 0.03847 +Epoch [246/4000] Training [9/16] Loss: 0.02564 +Epoch [246/4000] Training [10/16] Loss: 0.02751 +Epoch [246/4000] Training [11/16] Loss: 0.02435 +Epoch [246/4000] Training [12/16] Loss: 0.02290 +Epoch [246/4000] Training [13/16] Loss: 0.06312 +Epoch [246/4000] Training [14/16] Loss: 0.02750 +Epoch [246/4000] Training [15/16] Loss: 0.02822 +Epoch [246/4000] Training [16/16] Loss: 0.02999 +Epoch [246/4000] Training metric {'Train/mean dice_metric': 0.9807895421981812, 'Train/mean miou_metric': 0.9631104469299316, 'Train/mean f1': 0.979043185710907, 'Train/mean precision': 0.9757670164108276, 'Train/mean recall': 0.9823414087295532, 'Train/mean hd95_metric': 4.4152421951293945} +Epoch [246/4000] Validation [1/4] Loss: 0.53907 focal_loss 0.40472 dice_loss 0.13435 +Epoch [246/4000] Validation [2/4] Loss: 0.31812 focal_loss 0.12509 dice_loss 0.19303 +Epoch [246/4000] Validation [3/4] Loss: 0.11455 focal_loss 0.05068 dice_loss 0.06386 +Epoch [246/4000] Validation [4/4] Loss: 0.16846 focal_loss 0.07190 dice_loss 0.09655 +Epoch [246/4000] Validation metric {'Val/mean dice_metric': 0.9533136487007141, 'Val/mean miou_metric': 0.9245582818984985, 'Val/mean f1': 0.95618736743927, 'Val/mean precision': 0.9557027220726013, 'Val/mean recall': 0.9566723704338074, 'Val/mean hd95_metric': 10.7333984375} +Cheakpoint... +Epoch [246/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9533], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9533136487007141, 'Val/mean miou_metric': 0.9245582818984985, 'Val/mean f1': 0.95618736743927, 'Val/mean precision': 0.9557027220726013, 'Val/mean recall': 0.9566723704338074, 'Val/mean hd95_metric': 10.7333984375} +Epoch [247/4000] Training [1/16] Loss: 0.02976 +Epoch [247/4000] Training [2/16] Loss: 0.06192 +Epoch [247/4000] Training [3/16] Loss: 0.02611 +Epoch [247/4000] Training [4/16] Loss: 0.02449 +Epoch [247/4000] Training [5/16] Loss: 0.02417 +Epoch [247/4000] Training [6/16] Loss: 0.02842 +Epoch [247/4000] Training [7/16] Loss: 0.02063 +Epoch [247/4000] Training [8/16] Loss: 0.02428 +Epoch [247/4000] Training [9/16] Loss: 0.02358 +Epoch [247/4000] Training [10/16] Loss: 0.02297 +Epoch [247/4000] Training [11/16] Loss: 0.01943 +Epoch [247/4000] Training [12/16] Loss: 0.02217 +Epoch [247/4000] Training [13/16] Loss: 0.02466 +Epoch [247/4000] Training [14/16] Loss: 0.09476 +Epoch [247/4000] Training [15/16] Loss: 0.02001 +Epoch [247/4000] Training [16/16] Loss: 0.02003 +Epoch [247/4000] Training metric {'Train/mean dice_metric': 0.9830788373947144, 'Train/mean miou_metric': 0.9670170545578003, 'Train/mean f1': 0.9789366722106934, 'Train/mean precision': 0.9748578071594238, 'Train/mean recall': 0.9830498099327087, 'Train/mean hd95_metric': 4.033224105834961} +Epoch [247/4000] Validation [1/4] Loss: 0.12836 focal_loss 0.06187 dice_loss 0.06649 +Epoch [247/4000] Validation [2/4] Loss: 0.25042 focal_loss 0.08868 dice_loss 0.16174 +Epoch [247/4000] Validation [3/4] Loss: 0.23101 focal_loss 0.11874 dice_loss 0.11227 +Epoch [247/4000] Validation [4/4] Loss: 0.27644 focal_loss 0.15112 dice_loss 0.12532 +Epoch [247/4000] Validation metric {'Val/mean dice_metric': 0.9561587572097778, 'Val/mean miou_metric': 0.9288443326950073, 'Val/mean f1': 0.9582288265228271, 'Val/mean precision': 0.951580286026001, 'Val/mean recall': 0.9649710655212402, 'Val/mean hd95_metric': 9.963598251342773} +Cheakpoint... +Epoch [247/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9562], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9561587572097778, 'Val/mean miou_metric': 0.9288443326950073, 'Val/mean f1': 0.9582288265228271, 'Val/mean precision': 0.951580286026001, 'Val/mean recall': 0.9649710655212402, 'Val/mean hd95_metric': 9.963598251342773} +Epoch [248/4000] Training [1/16] Loss: 0.02383 +Epoch [248/4000] Training [2/16] Loss: 0.02539 +Epoch [248/4000] Training [3/16] Loss: 0.01871 +Epoch [248/4000] Training [4/16] Loss: 0.03555 +Epoch [248/4000] Training [5/16] Loss: 0.02268 +Epoch [248/4000] Training [6/16] Loss: 0.03051 +Epoch [248/4000] Training [7/16] Loss: 0.05129 +Epoch [248/4000] Training [8/16] Loss: 0.02345 +Epoch [248/4000] Training [9/16] Loss: 0.02252 +Epoch [248/4000] Training [10/16] Loss: 0.01863 +Epoch [248/4000] Training [11/16] Loss: 0.02253 +Epoch [248/4000] Training [12/16] Loss: 0.02519 +Epoch [248/4000] Training [13/16] Loss: 0.01885 +Epoch [248/4000] Training [14/16] Loss: 0.02783 +Epoch [248/4000] Training [15/16] Loss: 0.01799 +Epoch [248/4000] Training [16/16] Loss: 0.04053 +Epoch [248/4000] Training metric {'Train/mean dice_metric': 0.981864333152771, 'Train/mean miou_metric': 0.9652649164199829, 'Train/mean f1': 0.9797804951667786, 'Train/mean precision': 0.9754729866981506, 'Train/mean recall': 0.9841262698173523, 'Train/mean hd95_metric': 4.124770164489746} +Epoch [248/4000] Validation [1/4] Loss: 0.14191 focal_loss 0.08196 dice_loss 0.05995 +Epoch [248/4000] Validation [2/4] Loss: 0.24584 focal_loss 0.07217 dice_loss 0.17366 +Epoch [248/4000] Validation [3/4] Loss: 0.17726 focal_loss 0.08134 dice_loss 0.09592 +Epoch [248/4000] Validation [4/4] Loss: 0.22152 focal_loss 0.09813 dice_loss 0.12339 +Epoch [248/4000] Validation metric {'Val/mean dice_metric': 0.9573723077774048, 'Val/mean miou_metric': 0.9304972887039185, 'Val/mean f1': 0.9632275700569153, 'Val/mean precision': 0.9609551429748535, 'Val/mean recall': 0.9655107855796814, 'Val/mean hd95_metric': 7.938398838043213} +Cheakpoint... +Epoch [248/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9574], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573723077774048, 'Val/mean miou_metric': 0.9304972887039185, 'Val/mean f1': 0.9632275700569153, 'Val/mean precision': 0.9609551429748535, 'Val/mean recall': 0.9655107855796814, 'Val/mean hd95_metric': 7.938398838043213} +Epoch [249/4000] Training [1/16] Loss: 0.02551 +Epoch [249/4000] Training [2/16] Loss: 0.02588 +Epoch [249/4000] Training [3/16] Loss: 0.01843 +Epoch [249/4000] Training [4/16] Loss: 0.02529 +Epoch [249/4000] Training [5/16] Loss: 0.01816 +Epoch [249/4000] Training [6/16] Loss: 0.02711 +Epoch [249/4000] Training [7/16] Loss: 0.02213 +Epoch [249/4000] Training [8/16] Loss: 0.02065 +Epoch [249/4000] Training [9/16] Loss: 0.02057 +Epoch [249/4000] Training [10/16] Loss: 0.02545 +Epoch [249/4000] Training [11/16] Loss: 0.02375 +Epoch [249/4000] Training [12/16] Loss: 0.02632 +Epoch [249/4000] Training [13/16] Loss: 0.02590 +Epoch [249/4000] Training [14/16] Loss: 0.02780 +Epoch [249/4000] Training [15/16] Loss: 0.03226 +Epoch [249/4000] Training [16/16] Loss: 0.02301 +Epoch [249/4000] Training metric {'Train/mean dice_metric': 0.9844540357589722, 'Train/mean miou_metric': 0.9693207740783691, 'Train/mean f1': 0.9812347888946533, 'Train/mean precision': 0.9761085510253906, 'Train/mean recall': 0.9864152073860168, 'Train/mean hd95_metric': 2.455625057220459} +Epoch [249/4000] Validation [1/4] Loss: 0.23478 focal_loss 0.12710 dice_loss 0.10768 +Epoch [249/4000] Validation [2/4] Loss: 0.15031 focal_loss 0.05064 dice_loss 0.09967 +Epoch [249/4000] Validation [3/4] Loss: 0.10554 focal_loss 0.04490 dice_loss 0.06064 +Epoch [249/4000] Validation [4/4] Loss: 0.24580 focal_loss 0.11481 dice_loss 0.13100 +Epoch [249/4000] Validation metric {'Val/mean dice_metric': 0.9631597399711609, 'Val/mean miou_metric': 0.9379886388778687, 'Val/mean f1': 0.9657056331634521, 'Val/mean precision': 0.9616815447807312, 'Val/mean recall': 0.9697636961936951, 'Val/mean hd95_metric': 6.479498863220215} +Cheakpoint... +Epoch [249/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631597399711609, 'Val/mean miou_metric': 0.9379886388778687, 'Val/mean f1': 0.9657056331634521, 'Val/mean precision': 0.9616815447807312, 'Val/mean recall': 0.9697636961936951, 'Val/mean hd95_metric': 6.479498863220215} +Epoch [250/4000] Training [1/16] Loss: 0.02041 +Epoch [250/4000] Training [2/16] Loss: 0.02018 +Epoch [250/4000] Training [3/16] Loss: 0.02561 +Epoch [250/4000] Training [4/16] Loss: 0.01805 +Epoch [250/4000] Training [5/16] Loss: 0.02428 +Epoch [250/4000] Training [6/16] Loss: 0.02008 +Epoch [250/4000] Training [7/16] Loss: 0.01789 +Epoch [250/4000] Training [8/16] Loss: 0.01654 +Epoch [250/4000] Training [9/16] Loss: 0.01780 +Epoch [250/4000] Training [10/16] Loss: 0.02273 +Epoch [250/4000] Training [11/16] Loss: 0.02502 +Epoch [250/4000] Training [12/16] Loss: 0.01972 +Epoch [250/4000] Training [13/16] Loss: 0.02030 +Epoch [250/4000] Training [14/16] Loss: 0.01460 +Epoch [250/4000] Training [15/16] Loss: 0.02684 +Epoch [250/4000] Training [16/16] Loss: 0.01336 +Epoch [250/4000] Training metric {'Train/mean dice_metric': 0.9858742356300354, 'Train/mean miou_metric': 0.971981942653656, 'Train/mean f1': 0.9826183319091797, 'Train/mean precision': 0.9782570004463196, 'Train/mean recall': 0.9870185852050781, 'Train/mean hd95_metric': 2.0009989738464355} +Epoch [250/4000] Validation [1/4] Loss: 0.13853 focal_loss 0.07654 dice_loss 0.06199 +Epoch [250/4000] Validation [2/4] Loss: 0.14529 focal_loss 0.04688 dice_loss 0.09840 +Epoch [250/4000] Validation [3/4] Loss: 0.11718 focal_loss 0.05208 dice_loss 0.06510 +Epoch [250/4000] Validation [4/4] Loss: 0.19961 focal_loss 0.09112 dice_loss 0.10848 +Epoch [250/4000] Validation metric {'Val/mean dice_metric': 0.9651800990104675, 'Val/mean miou_metric': 0.9411693811416626, 'Val/mean f1': 0.9677425622940063, 'Val/mean precision': 0.9628143310546875, 'Val/mean recall': 0.972721517086029, 'Val/mean hd95_metric': 5.922821998596191} +Cheakpoint... +Epoch [250/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651800990104675, 'Val/mean miou_metric': 0.9411693811416626, 'Val/mean f1': 0.9677425622940063, 'Val/mean precision': 0.9628143310546875, 'Val/mean recall': 0.972721517086029, 'Val/mean hd95_metric': 5.922821998596191} +Epoch [251/4000] Training [1/16] Loss: 0.01723 +Epoch [251/4000] Training [2/16] Loss: 0.02204 +Epoch [251/4000] Training [3/16] Loss: 0.01850 +Epoch [251/4000] Training [4/16] Loss: 0.01449 +Epoch [251/4000] Training [5/16] Loss: 0.01558 +Epoch [251/4000] Training [6/16] Loss: 0.01326 +Epoch [251/4000] Training [7/16] Loss: 0.01887 +Epoch [251/4000] Training [8/16] Loss: 0.01636 +Epoch [251/4000] Training [9/16] Loss: 0.01345 +Epoch [251/4000] Training [10/16] Loss: 0.01810 +Epoch [251/4000] Training [11/16] Loss: 0.01812 +Epoch [251/4000] Training [12/16] Loss: 0.01731 +Epoch [251/4000] Training [13/16] Loss: 0.01716 +Epoch [251/4000] Training [14/16] Loss: 0.01737 +Epoch [251/4000] Training [15/16] Loss: 0.01638 +Epoch [251/4000] Training [16/16] Loss: 0.03032 +Epoch [251/4000] Training metric {'Train/mean dice_metric': 0.9873553514480591, 'Train/mean miou_metric': 0.9749478101730347, 'Train/mean f1': 0.9853900074958801, 'Train/mean precision': 0.9809995293617249, 'Train/mean recall': 0.9898200035095215, 'Train/mean hd95_metric': 1.6998001337051392} +Epoch [251/4000] Validation [1/4] Loss: 0.16868 focal_loss 0.09438 dice_loss 0.07430 +Epoch [251/4000] Validation [2/4] Loss: 0.32378 focal_loss 0.13404 dice_loss 0.18974 +Epoch [251/4000] Validation [3/4] Loss: 0.11854 focal_loss 0.05910 dice_loss 0.05944 +Epoch [251/4000] Validation [4/4] Loss: 0.20643 focal_loss 0.09387 dice_loss 0.11256 +Epoch [251/4000] Validation metric {'Val/mean dice_metric': 0.9643470644950867, 'Val/mean miou_metric': 0.9420830011367798, 'Val/mean f1': 0.9688796997070312, 'Val/mean precision': 0.9634160995483398, 'Val/mean recall': 0.9744056463241577, 'Val/mean hd95_metric': 6.270163059234619} +Cheakpoint... +Epoch [251/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9643], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9643470644950867, 'Val/mean miou_metric': 0.9420830011367798, 'Val/mean f1': 0.9688796997070312, 'Val/mean precision': 0.9634160995483398, 'Val/mean recall': 0.9744056463241577, 'Val/mean hd95_metric': 6.270163059234619} +Epoch [252/4000] Training [1/16] Loss: 0.03473 +Epoch [252/4000] Training [2/16] Loss: 0.01744 +Epoch [252/4000] Training [3/16] Loss: 0.01716 +Epoch [252/4000] Training [4/16] Loss: 0.02254 +Epoch [252/4000] Training [5/16] Loss: 0.01947 +Epoch [252/4000] Training [6/16] Loss: 0.01812 +Epoch [252/4000] Training [7/16] Loss: 0.01788 +Epoch [252/4000] Training [8/16] Loss: 0.01563 +Epoch [252/4000] Training [9/16] Loss: 0.01906 +Epoch [252/4000] Training [10/16] Loss: 0.01919 +Epoch [252/4000] Training [11/16] Loss: 0.02024 +Epoch [252/4000] Training [12/16] Loss: 0.01555 +Epoch [252/4000] Training [13/16] Loss: 0.01793 +Epoch [252/4000] Training [14/16] Loss: 0.01557 +Epoch [252/4000] Training [15/16] Loss: 0.02284 +Epoch [252/4000] Training [16/16] Loss: 0.01507 +Epoch [252/4000] Training metric {'Train/mean dice_metric': 0.9865496158599854, 'Train/mean miou_metric': 0.9733353853225708, 'Train/mean f1': 0.9846848249435425, 'Train/mean precision': 0.9804162979125977, 'Train/mean recall': 0.9889905452728271, 'Train/mean hd95_metric': 1.5876652002334595} +Epoch [252/4000] Validation [1/4] Loss: 0.15200 focal_loss 0.08986 dice_loss 0.06214 +Epoch [252/4000] Validation [2/4] Loss: 0.19058 focal_loss 0.05793 dice_loss 0.13265 +Epoch [252/4000] Validation [3/4] Loss: 0.17237 focal_loss 0.09232 dice_loss 0.08005 +Epoch [252/4000] Validation [4/4] Loss: 0.18866 focal_loss 0.08165 dice_loss 0.10701 +Epoch [252/4000] Validation metric {'Val/mean dice_metric': 0.9650434255599976, 'Val/mean miou_metric': 0.941362738609314, 'Val/mean f1': 0.9696401953697205, 'Val/mean precision': 0.9643983244895935, 'Val/mean recall': 0.9749393463134766, 'Val/mean hd95_metric': 6.348791599273682} +Cheakpoint... +Epoch [252/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650434255599976, 'Val/mean miou_metric': 0.941362738609314, 'Val/mean f1': 0.9696401953697205, 'Val/mean precision': 0.9643983244895935, 'Val/mean recall': 0.9749393463134766, 'Val/mean hd95_metric': 6.348791599273682} +Epoch [253/4000] Training [1/16] Loss: 0.01328 +Epoch [253/4000] Training [2/16] Loss: 0.01938 +Epoch [253/4000] Training [3/16] Loss: 0.03222 +Epoch [253/4000] Training [4/16] Loss: 0.01558 +Epoch [253/4000] Training [5/16] Loss: 0.01501 +Epoch [253/4000] Training [6/16] Loss: 0.01656 +Epoch [253/4000] Training [7/16] Loss: 0.01373 +Epoch [253/4000] Training [8/16] Loss: 0.01892 +Epoch [253/4000] Training [9/16] Loss: 0.01547 +Epoch [253/4000] Training [10/16] Loss: 0.01493 +Epoch [253/4000] Training [11/16] Loss: 0.01853 +Epoch [253/4000] Training [12/16] Loss: 0.01869 +Epoch [253/4000] Training [13/16] Loss: 0.01964 +Epoch [253/4000] Training [14/16] Loss: 0.01603 +Epoch [253/4000] Training [15/16] Loss: 0.02075 +Epoch [253/4000] Training [16/16] Loss: 0.02287 +Epoch [253/4000] Training metric {'Train/mean dice_metric': 0.9865086078643799, 'Train/mean miou_metric': 0.9733714461326599, 'Train/mean f1': 0.9843829274177551, 'Train/mean precision': 0.9793479442596436, 'Train/mean recall': 0.9894698858261108, 'Train/mean hd95_metric': 1.997126579284668} +Epoch [253/4000] Validation [1/4] Loss: 0.13590 focal_loss 0.07936 dice_loss 0.05654 +Epoch [253/4000] Validation [2/4] Loss: 0.53335 focal_loss 0.26904 dice_loss 0.26431 +Epoch [253/4000] Validation [3/4] Loss: 0.12215 focal_loss 0.05974 dice_loss 0.06241 +Epoch [253/4000] Validation [4/4] Loss: 0.17613 focal_loss 0.07257 dice_loss 0.10356 +Epoch [253/4000] Validation metric {'Val/mean dice_metric': 0.9632388949394226, 'Val/mean miou_metric': 0.9399822354316711, 'Val/mean f1': 0.9672176837921143, 'Val/mean precision': 0.9585041403770447, 'Val/mean recall': 0.9760910272598267, 'Val/mean hd95_metric': 6.3595781326293945} +Cheakpoint... +Epoch [253/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632388949394226, 'Val/mean miou_metric': 0.9399822354316711, 'Val/mean f1': 0.9672176837921143, 'Val/mean precision': 0.9585041403770447, 'Val/mean recall': 0.9760910272598267, 'Val/mean hd95_metric': 6.3595781326293945} +Epoch [254/4000] Training [1/16] Loss: 0.01596 +Epoch [254/4000] Training [2/16] Loss: 0.01738 +Epoch [254/4000] Training [3/16] Loss: 0.02029 +Epoch [254/4000] Training [4/16] Loss: 0.02071 +Epoch [254/4000] Training [5/16] Loss: 0.02170 +Epoch [254/4000] Training [6/16] Loss: 0.01756 +Epoch [254/4000] Training [7/16] Loss: 0.01760 +Epoch [254/4000] Training [8/16] Loss: 0.02031 +Epoch [254/4000] Training [9/16] Loss: 0.02211 +Epoch [254/4000] Training [10/16] Loss: 0.01522 +Epoch [254/4000] Training [11/16] Loss: 0.01534 +Epoch [254/4000] Training [12/16] Loss: 0.01773 +Epoch [254/4000] Training [13/16] Loss: 0.02819 +Epoch [254/4000] Training [14/16] Loss: 0.03091 +Epoch [254/4000] Training [15/16] Loss: 0.01778 +Epoch [254/4000] Training [16/16] Loss: 0.01482 +Epoch [254/4000] Training metric {'Train/mean dice_metric': 0.9864624738693237, 'Train/mean miou_metric': 0.9732243418693542, 'Train/mean f1': 0.9843268394470215, 'Train/mean precision': 0.9796305894851685, 'Train/mean recall': 0.989068329334259, 'Train/mean hd95_metric': 1.8770184516906738} +Epoch [254/4000] Validation [1/4] Loss: 0.25764 focal_loss 0.14061 dice_loss 0.11702 +Epoch [254/4000] Validation [2/4] Loss: 0.20681 focal_loss 0.08464 dice_loss 0.12217 +Epoch [254/4000] Validation [3/4] Loss: 0.13571 focal_loss 0.06612 dice_loss 0.06958 +Epoch [254/4000] Validation [4/4] Loss: 0.25113 focal_loss 0.12463 dice_loss 0.12650 +Epoch [254/4000] Validation metric {'Val/mean dice_metric': 0.9635119438171387, 'Val/mean miou_metric': 0.9388920068740845, 'Val/mean f1': 0.9667814373970032, 'Val/mean precision': 0.9653769135475159, 'Val/mean recall': 0.9681899547576904, 'Val/mean hd95_metric': 6.536295413970947} +Cheakpoint... +Epoch [254/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9635], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9635119438171387, 'Val/mean miou_metric': 0.9388920068740845, 'Val/mean f1': 0.9667814373970032, 'Val/mean precision': 0.9653769135475159, 'Val/mean recall': 0.9681899547576904, 'Val/mean hd95_metric': 6.536295413970947} +Epoch [255/4000] Training [1/16] Loss: 0.01724 +Epoch [255/4000] Training [2/16] Loss: 0.02387 +Epoch [255/4000] Training [3/16] Loss: 0.01693 +Epoch [255/4000] Training [4/16] Loss: 0.02016 +Epoch [255/4000] Training [5/16] Loss: 0.01787 +Epoch [255/4000] Training [6/16] Loss: 0.02651 +Epoch [255/4000] Training [7/16] Loss: 0.01651 +Epoch [255/4000] Training [8/16] Loss: 0.01872 +Epoch [255/4000] Training [9/16] Loss: 0.02128 +Epoch [255/4000] Training [10/16] Loss: 0.03277 +Epoch [255/4000] Training [11/16] Loss: 0.01744 +Epoch [255/4000] Training [12/16] Loss: 0.01763 +Epoch [255/4000] Training [13/16] Loss: 0.01861 +Epoch [255/4000] Training [14/16] Loss: 0.02165 +Epoch [255/4000] Training [15/16] Loss: 0.02030 +Epoch [255/4000] Training [16/16] Loss: 0.01593 +Epoch [255/4000] Training metric {'Train/mean dice_metric': 0.9858949184417725, 'Train/mean miou_metric': 0.9721408486366272, 'Train/mean f1': 0.9836776256561279, 'Train/mean precision': 0.9797192215919495, 'Train/mean recall': 0.9876680970191956, 'Train/mean hd95_metric': 2.1052956581115723} +Epoch [255/4000] Validation [1/4] Loss: 0.27083 focal_loss 0.14811 dice_loss 0.12272 +Epoch [255/4000] Validation [2/4] Loss: 0.20322 focal_loss 0.07367 dice_loss 0.12955 +Epoch [255/4000] Validation [3/4] Loss: 0.25259 focal_loss 0.13536 dice_loss 0.11723 +Epoch [255/4000] Validation [4/4] Loss: 0.22980 focal_loss 0.09383 dice_loss 0.13596 +Epoch [255/4000] Validation metric {'Val/mean dice_metric': 0.9622436761856079, 'Val/mean miou_metric': 0.937718391418457, 'Val/mean f1': 0.9665339589118958, 'Val/mean precision': 0.9625213742256165, 'Val/mean recall': 0.9705801606178284, 'Val/mean hd95_metric': 7.289495944976807} +Cheakpoint... +Epoch [255/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622436761856079, 'Val/mean miou_metric': 0.937718391418457, 'Val/mean f1': 0.9665339589118958, 'Val/mean precision': 0.9625213742256165, 'Val/mean recall': 0.9705801606178284, 'Val/mean hd95_metric': 7.289495944976807} +Epoch [256/4000] Training [1/16] Loss: 0.02058 +Epoch [256/4000] Training [2/16] Loss: 0.01780 +Epoch [256/4000] Training [3/16] Loss: 0.01856 +Epoch [256/4000] Training [4/16] Loss: 0.01599 +Epoch [256/4000] Training [5/16] Loss: 0.09017 +Epoch [256/4000] Training [6/16] Loss: 0.01816 +Epoch [256/4000] Training [7/16] Loss: 0.02634 +Epoch [256/4000] Training [8/16] Loss: 0.01931 +Epoch [256/4000] Training [9/16] Loss: 0.01566 +Epoch [256/4000] Training [10/16] Loss: 0.02336 +Epoch [256/4000] Training [11/16] Loss: 0.02049 +Epoch [256/4000] Training [12/16] Loss: 0.01695 +Epoch [256/4000] Training [13/16] Loss: 0.02903 +Epoch [256/4000] Training [14/16] Loss: 0.01839 +Epoch [256/4000] Training [15/16] Loss: 0.02115 +Epoch [256/4000] Training [16/16] Loss: 0.02652 +Epoch [256/4000] Training metric {'Train/mean dice_metric': 0.984527587890625, 'Train/mean miou_metric': 0.9702283143997192, 'Train/mean f1': 0.9823510646820068, 'Train/mean precision': 0.9771105051040649, 'Train/mean recall': 0.9876481890678406, 'Train/mean hd95_metric': 2.2655766010284424} +Epoch [256/4000] Validation [1/4] Loss: 0.87508 focal_loss 0.66978 dice_loss 0.20530 +Epoch [256/4000] Validation [2/4] Loss: 0.34709 focal_loss 0.15283 dice_loss 0.19426 +Epoch [256/4000] Validation [3/4] Loss: 0.12520 focal_loss 0.05958 dice_loss 0.06562 +Epoch [256/4000] Validation [4/4] Loss: 0.58960 focal_loss 0.33860 dice_loss 0.25100 +Epoch [256/4000] Validation metric {'Val/mean dice_metric': 0.9556381106376648, 'Val/mean miou_metric': 0.9289315342903137, 'Val/mean f1': 0.9583617448806763, 'Val/mean precision': 0.9648048877716064, 'Val/mean recall': 0.9520040154457092, 'Val/mean hd95_metric': 7.770971775054932} +Cheakpoint... +Epoch [256/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9556], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9556381106376648, 'Val/mean miou_metric': 0.9289315342903137, 'Val/mean f1': 0.9583617448806763, 'Val/mean precision': 0.9648048877716064, 'Val/mean recall': 0.9520040154457092, 'Val/mean hd95_metric': 7.770971775054932} +Epoch [257/4000] Training [1/16] Loss: 0.01591 +Epoch [257/4000] Training [2/16] Loss: 0.02577 +Epoch [257/4000] Training [3/16] Loss: 0.01641 +Epoch [257/4000] Training [4/16] Loss: 0.02057 +Epoch [257/4000] Training [5/16] Loss: 0.01558 +Epoch [257/4000] Training [6/16] Loss: 0.01926 +Epoch [257/4000] Training [7/16] Loss: 0.02508 +Epoch [257/4000] Training [8/16] Loss: 0.02210 +Epoch [257/4000] Training [9/16] Loss: 0.01861 +Epoch [257/4000] Training [10/16] Loss: 0.01860 +Epoch [257/4000] Training [11/16] Loss: 0.03037 +Epoch [257/4000] Training [12/16] Loss: 0.01763 +Epoch [257/4000] Training [13/16] Loss: 0.02260 +Epoch [257/4000] Training [14/16] Loss: 0.01493 +Epoch [257/4000] Training [15/16] Loss: 0.01926 +Epoch [257/4000] Training [16/16] Loss: 0.02001 +Epoch [257/4000] Training metric {'Train/mean dice_metric': 0.9850709438323975, 'Train/mean miou_metric': 0.9705114364624023, 'Train/mean f1': 0.9830194711685181, 'Train/mean precision': 0.978383481502533, 'Train/mean recall': 0.9876996874809265, 'Train/mean hd95_metric': 2.151895523071289} +Epoch [257/4000] Validation [1/4] Loss: 0.16915 focal_loss 0.09214 dice_loss 0.07701 +Epoch [257/4000] Validation [2/4] Loss: 0.16837 focal_loss 0.06300 dice_loss 0.10536 +Epoch [257/4000] Validation [3/4] Loss: 0.10485 focal_loss 0.04848 dice_loss 0.05637 +Epoch [257/4000] Validation [4/4] Loss: 0.28684 focal_loss 0.15234 dice_loss 0.13450 +Epoch [257/4000] Validation metric {'Val/mean dice_metric': 0.9622270464897156, 'Val/mean miou_metric': 0.9374141693115234, 'Val/mean f1': 0.965567409992218, 'Val/mean precision': 0.9606665968894958, 'Val/mean recall': 0.9705183506011963, 'Val/mean hd95_metric': 6.377781867980957} +Cheakpoint... +Epoch [257/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622270464897156, 'Val/mean miou_metric': 0.9374141693115234, 'Val/mean f1': 0.965567409992218, 'Val/mean precision': 0.9606665968894958, 'Val/mean recall': 0.9705183506011963, 'Val/mean hd95_metric': 6.377781867980957} +Epoch [258/4000] Training [1/16] Loss: 0.01952 +Epoch [258/4000] Training [2/16] Loss: 0.01575 +Epoch [258/4000] Training [3/16] Loss: 0.02312 +Epoch [258/4000] Training [4/16] Loss: 0.01928 +Epoch [258/4000] Training [5/16] Loss: 0.01877 +Epoch [258/4000] Training [6/16] Loss: 0.01943 +Epoch [258/4000] Training [7/16] Loss: 0.02043 +Epoch [258/4000] Training [8/16] Loss: 0.02472 +Epoch [258/4000] Training [9/16] Loss: 0.14068 +Epoch [258/4000] Training [10/16] Loss: 0.01841 +Epoch [258/4000] Training [11/16] Loss: 0.02230 +Epoch [258/4000] Training [12/16] Loss: 0.01770 +Epoch [258/4000] Training [13/16] Loss: 0.01772 +Epoch [258/4000] Training [14/16] Loss: 0.02345 +Epoch [258/4000] Training [15/16] Loss: 0.05637 +Epoch [258/4000] Training [16/16] Loss: 0.01582 +Epoch [258/4000] Training metric {'Train/mean dice_metric': 0.9837595224380493, 'Train/mean miou_metric': 0.9691417813301086, 'Train/mean f1': 0.9822262525558472, 'Train/mean precision': 0.9777491688728333, 'Train/mean recall': 0.9867445826530457, 'Train/mean hd95_metric': 2.413360357284546} +Epoch [258/4000] Validation [1/4] Loss: 0.17758 focal_loss 0.09057 dice_loss 0.08701 +Epoch [258/4000] Validation [2/4] Loss: 0.38453 focal_loss 0.16979 dice_loss 0.21474 +Epoch [258/4000] Validation [3/4] Loss: 0.17918 focal_loss 0.08976 dice_loss 0.08942 +Epoch [258/4000] Validation [4/4] Loss: 0.36325 focal_loss 0.17747 dice_loss 0.18578 +Epoch [258/4000] Validation metric {'Val/mean dice_metric': 0.9577930569648743, 'Val/mean miou_metric': 0.9313654899597168, 'Val/mean f1': 0.9618433117866516, 'Val/mean precision': 0.9644332528114319, 'Val/mean recall': 0.959267258644104, 'Val/mean hd95_metric': 7.075407981872559} +Cheakpoint... +Epoch [258/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9578], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9577930569648743, 'Val/mean miou_metric': 0.9313654899597168, 'Val/mean f1': 0.9618433117866516, 'Val/mean precision': 0.9644332528114319, 'Val/mean recall': 0.959267258644104, 'Val/mean hd95_metric': 7.075407981872559} +Epoch [259/4000] Training [1/16] Loss: 0.01431 +Epoch [259/4000] Training [2/16] Loss: 0.01719 +Epoch [259/4000] Training [3/16] Loss: 0.02391 +Epoch [259/4000] Training [4/16] Loss: 0.01931 +Epoch [259/4000] Training [5/16] Loss: 0.01602 +Epoch [259/4000] Training [6/16] Loss: 0.03843 +Epoch [259/4000] Training [7/16] Loss: 0.01676 +Epoch [259/4000] Training [8/16] Loss: 0.03224 +Epoch [259/4000] Training [9/16] Loss: 0.03944 +Epoch [259/4000] Training [10/16] Loss: 0.03159 +Epoch [259/4000] Training [11/16] Loss: 0.02678 +Epoch [259/4000] Training [12/16] Loss: 0.03092 +Epoch [259/4000] Training [13/16] Loss: 0.02376 +Epoch [259/4000] Training [14/16] Loss: 0.03826 +Epoch [259/4000] Training [15/16] Loss: 0.01692 +Epoch [259/4000] Training [16/16] Loss: 0.01781 +Epoch [259/4000] Training metric {'Train/mean dice_metric': 0.9837568998336792, 'Train/mean miou_metric': 0.9681462049484253, 'Train/mean f1': 0.9816218614578247, 'Train/mean precision': 0.9763709306716919, 'Train/mean recall': 0.9869295954704285, 'Train/mean hd95_metric': 3.0730791091918945} +Epoch [259/4000] Validation [1/4] Loss: 0.15207 focal_loss 0.07945 dice_loss 0.07262 +Epoch [259/4000] Validation [2/4] Loss: 0.46407 focal_loss 0.17532 dice_loss 0.28875 +Epoch [259/4000] Validation [3/4] Loss: 0.13543 focal_loss 0.06035 dice_loss 0.07508 +Epoch [259/4000] Validation [4/4] Loss: 0.22230 focal_loss 0.10327 dice_loss 0.11903 +Epoch [259/4000] Validation metric {'Val/mean dice_metric': 0.9580005407333374, 'Val/mean miou_metric': 0.9309228658676147, 'Val/mean f1': 0.9586931467056274, 'Val/mean precision': 0.9539299011230469, 'Val/mean recall': 0.9635041952133179, 'Val/mean hd95_metric': 8.386449813842773} +Cheakpoint... +Epoch [259/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9580], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9580005407333374, 'Val/mean miou_metric': 0.9309228658676147, 'Val/mean f1': 0.9586931467056274, 'Val/mean precision': 0.9539299011230469, 'Val/mean recall': 0.9635041952133179, 'Val/mean hd95_metric': 8.386449813842773} +Epoch [260/4000] Training [1/16] Loss: 0.02226 +Epoch [260/4000] Training [2/16] Loss: 0.02147 +Epoch [260/4000] Training [3/16] Loss: 0.02777 +Epoch [260/4000] Training [4/16] Loss: 0.02686 +Epoch [260/4000] Training [5/16] Loss: 0.02236 +Epoch [260/4000] Training [6/16] Loss: 0.02036 +Epoch [260/4000] Training [7/16] Loss: 0.01762 +Epoch [260/4000] Training [8/16] Loss: 0.07353 +Epoch [260/4000] Training [9/16] Loss: 0.02201 +Epoch [260/4000] Training [10/16] Loss: 0.02363 +Epoch [260/4000] Training [11/16] Loss: 0.02458 +Epoch [260/4000] Training [12/16] Loss: 0.02808 +Epoch [260/4000] Training [13/16] Loss: 0.01887 +Epoch [260/4000] Training [14/16] Loss: 0.01483 +Epoch [260/4000] Training [15/16] Loss: 0.02173 +Epoch [260/4000] Training [16/16] Loss: 0.02818 +Epoch [260/4000] Training metric {'Train/mean dice_metric': 0.9823720455169678, 'Train/mean miou_metric': 0.9658255577087402, 'Train/mean f1': 0.9804872274398804, 'Train/mean precision': 0.9762030243873596, 'Train/mean recall': 0.9848092198371887, 'Train/mean hd95_metric': 3.10892391204834} +Epoch [260/4000] Validation [1/4] Loss: 0.16581 focal_loss 0.08057 dice_loss 0.08524 +Epoch [260/4000] Validation [2/4] Loss: 0.46456 focal_loss 0.22199 dice_loss 0.24257 +Epoch [260/4000] Validation [3/4] Loss: 0.13000 focal_loss 0.06070 dice_loss 0.06930 +Epoch [260/4000] Validation [4/4] Loss: 0.20092 focal_loss 0.08409 dice_loss 0.11683 +Epoch [260/4000] Validation metric {'Val/mean dice_metric': 0.959668755531311, 'Val/mean miou_metric': 0.932377815246582, 'Val/mean f1': 0.9622981548309326, 'Val/mean precision': 0.9606273174285889, 'Val/mean recall': 0.9639748334884644, 'Val/mean hd95_metric': 7.206027030944824} +Cheakpoint... +Epoch [260/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9597], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959668755531311, 'Val/mean miou_metric': 0.932377815246582, 'Val/mean f1': 0.9622981548309326, 'Val/mean precision': 0.9606273174285889, 'Val/mean recall': 0.9639748334884644, 'Val/mean hd95_metric': 7.206027030944824} +Epoch [261/4000] Training [1/16] Loss: 0.02160 +Epoch [261/4000] Training [2/16] Loss: 0.01753 +Epoch [261/4000] Training [3/16] Loss: 0.02111 +Epoch [261/4000] Training [4/16] Loss: 0.02477 +Epoch [261/4000] Training [5/16] Loss: 0.02017 +Epoch [261/4000] Training [6/16] Loss: 0.02379 +Epoch [261/4000] Training [7/16] Loss: 0.02025 +Epoch [261/4000] Training [8/16] Loss: 0.01673 +Epoch [261/4000] Training [9/16] Loss: 0.02343 +Epoch [261/4000] Training [10/16] Loss: 0.02234 +Epoch [261/4000] Training [11/16] Loss: 0.01869 +Epoch [261/4000] Training [12/16] Loss: 0.01584 +Epoch [261/4000] Training [13/16] Loss: 0.01533 +Epoch [261/4000] Training [14/16] Loss: 0.01653 +Epoch [261/4000] Training [15/16] Loss: 0.01632 +Epoch [261/4000] Training [16/16] Loss: 0.02211 +Epoch [261/4000] Training metric {'Train/mean dice_metric': 0.9858847856521606, 'Train/mean miou_metric': 0.9721224904060364, 'Train/mean f1': 0.9832783341407776, 'Train/mean precision': 0.9787418246269226, 'Train/mean recall': 0.9878570437431335, 'Train/mean hd95_metric': 2.5506467819213867} +Epoch [261/4000] Validation [1/4] Loss: 0.16476 focal_loss 0.08588 dice_loss 0.07887 +Epoch [261/4000] Validation [2/4] Loss: 0.40357 focal_loss 0.16849 dice_loss 0.23508 +Epoch [261/4000] Validation [3/4] Loss: 0.19156 focal_loss 0.08393 dice_loss 0.10762 +Epoch [261/4000] Validation [4/4] Loss: 0.19461 focal_loss 0.07199 dice_loss 0.12262 +Epoch [261/4000] Validation metric {'Val/mean dice_metric': 0.9619072675704956, 'Val/mean miou_metric': 0.9373432993888855, 'Val/mean f1': 0.966762125492096, 'Val/mean precision': 0.9656510353088379, 'Val/mean recall': 0.9678757786750793, 'Val/mean hd95_metric': 6.7521257400512695} +Cheakpoint... +Epoch [261/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9619], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9619072675704956, 'Val/mean miou_metric': 0.9373432993888855, 'Val/mean f1': 0.966762125492096, 'Val/mean precision': 0.9656510353088379, 'Val/mean recall': 0.9678757786750793, 'Val/mean hd95_metric': 6.7521257400512695} +Epoch [262/4000] Training [1/16] Loss: 0.02141 +Epoch [262/4000] Training [2/16] Loss: 0.01462 +Epoch [262/4000] Training [3/16] Loss: 0.02151 +Epoch [262/4000] Training [4/16] Loss: 0.02211 +Epoch [262/4000] Training [5/16] Loss: 0.01617 +Epoch [262/4000] Training [6/16] Loss: 0.02445 +Epoch [262/4000] Training [7/16] Loss: 0.03179 +Epoch [262/4000] Training [8/16] Loss: 0.01603 +Epoch [262/4000] Training [9/16] Loss: 0.01992 +Epoch [262/4000] Training [10/16] Loss: 0.01893 +Epoch [262/4000] Training [11/16] Loss: 0.01604 +Epoch [262/4000] Training [12/16] Loss: 0.01467 +Epoch [262/4000] Training [13/16] Loss: 0.01668 +Epoch [262/4000] Training [14/16] Loss: 0.01797 +Epoch [262/4000] Training [15/16] Loss: 0.01521 +Epoch [262/4000] Training [16/16] Loss: 0.02147 +Epoch [262/4000] Training metric {'Train/mean dice_metric': 0.9860028028488159, 'Train/mean miou_metric': 0.9723626971244812, 'Train/mean f1': 0.9828978776931763, 'Train/mean precision': 0.9779584407806396, 'Train/mean recall': 0.9878875017166138, 'Train/mean hd95_metric': 2.2122015953063965} +Epoch [262/4000] Validation [1/4] Loss: 0.18965 focal_loss 0.10630 dice_loss 0.08335 +Epoch [262/4000] Validation [2/4] Loss: 0.42229 focal_loss 0.17548 dice_loss 0.24681 +Epoch [262/4000] Validation [3/4] Loss: 0.12807 focal_loss 0.05759 dice_loss 0.07048 +Epoch [262/4000] Validation [4/4] Loss: 0.17598 focal_loss 0.06106 dice_loss 0.11492 +Epoch [262/4000] Validation metric {'Val/mean dice_metric': 0.9637987017631531, 'Val/mean miou_metric': 0.9395759701728821, 'Val/mean f1': 0.9661444425582886, 'Val/mean precision': 0.9622774720191956, 'Val/mean recall': 0.9700425863265991, 'Val/mean hd95_metric': 6.852295875549316} +Cheakpoint... +Epoch [262/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9638], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637987017631531, 'Val/mean miou_metric': 0.9395759701728821, 'Val/mean f1': 0.9661444425582886, 'Val/mean precision': 0.9622774720191956, 'Val/mean recall': 0.9700425863265991, 'Val/mean hd95_metric': 6.852295875549316} +Epoch [263/4000] Training [1/16] Loss: 0.01682 +Epoch [263/4000] Training [2/16] Loss: 0.01819 +Epoch [263/4000] Training [3/16] Loss: 0.01971 +Epoch [263/4000] Training [4/16] Loss: 0.04007 +Epoch [263/4000] Training [5/16] Loss: 0.01604 +Epoch [263/4000] Training [6/16] Loss: 0.01965 +Epoch [263/4000] Training [7/16] Loss: 0.01681 +Epoch [263/4000] Training [8/16] Loss: 0.01748 +Epoch [263/4000] Training [9/16] Loss: 0.01788 +Epoch [263/4000] Training [10/16] Loss: 0.01638 +Epoch [263/4000] Training [11/16] Loss: 0.03154 +Epoch [263/4000] Training [12/16] Loss: 0.01620 +Epoch [263/4000] Training [13/16] Loss: 0.01925 +Epoch [263/4000] Training [14/16] Loss: 0.01788 +Epoch [263/4000] Training [15/16] Loss: 0.01385 +Epoch [263/4000] Training [16/16] Loss: 0.02201 +Epoch [263/4000] Training metric {'Train/mean dice_metric': 0.9859541654586792, 'Train/mean miou_metric': 0.972285270690918, 'Train/mean f1': 0.9839192628860474, 'Train/mean precision': 0.9793577194213867, 'Train/mean recall': 0.9885234832763672, 'Train/mean hd95_metric': 2.348543167114258} +Epoch [263/4000] Validation [1/4] Loss: 0.37963 focal_loss 0.22510 dice_loss 0.15453 +Epoch [263/4000] Validation [2/4] Loss: 0.23499 focal_loss 0.09634 dice_loss 0.13865 +Epoch [263/4000] Validation [3/4] Loss: 0.24687 focal_loss 0.13502 dice_loss 0.11185 +Epoch [263/4000] Validation [4/4] Loss: 0.23330 focal_loss 0.10610 dice_loss 0.12720 +Epoch [263/4000] Validation metric {'Val/mean dice_metric': 0.9610862731933594, 'Val/mean miou_metric': 0.9356886148452759, 'Val/mean f1': 0.9643375873565674, 'Val/mean precision': 0.9662853479385376, 'Val/mean recall': 0.9623978137969971, 'Val/mean hd95_metric': 7.608090400695801} +Cheakpoint... +Epoch [263/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610862731933594, 'Val/mean miou_metric': 0.9356886148452759, 'Val/mean f1': 0.9643375873565674, 'Val/mean precision': 0.9662853479385376, 'Val/mean recall': 0.9623978137969971, 'Val/mean hd95_metric': 7.608090400695801} +Epoch [264/4000] Training [1/16] Loss: 0.01379 +Epoch [264/4000] Training [2/16] Loss: 0.02930 +Epoch [264/4000] Training [3/16] Loss: 0.01871 +Epoch [264/4000] Training [4/16] Loss: 0.01410 +Epoch [264/4000] Training [5/16] Loss: 0.03256 +Epoch [264/4000] Training [6/16] Loss: 0.01418 +Epoch [264/4000] Training [7/16] Loss: 0.01468 +Epoch [264/4000] Training [8/16] Loss: 0.01617 +Epoch [264/4000] Training [9/16] Loss: 0.01397 +Epoch [264/4000] Training [10/16] Loss: 0.01919 +Epoch [264/4000] Training [11/16] Loss: 0.01665 +Epoch [264/4000] Training [12/16] Loss: 0.02983 +Epoch [264/4000] Training [13/16] Loss: 0.01857 +Epoch [264/4000] Training [14/16] Loss: 0.01487 +Epoch [264/4000] Training [15/16] Loss: 0.01761 +Epoch [264/4000] Training [16/16] Loss: 0.01729 +Epoch [264/4000] Training metric {'Train/mean dice_metric': 0.986838698387146, 'Train/mean miou_metric': 0.9740308523178101, 'Train/mean f1': 0.9845567345619202, 'Train/mean precision': 0.9796360731124878, 'Train/mean recall': 0.9895271062850952, 'Train/mean hd95_metric': 1.8504140377044678} +Epoch [264/4000] Validation [1/4] Loss: 0.15128 focal_loss 0.08596 dice_loss 0.06532 +Epoch [264/4000] Validation [2/4] Loss: 0.38315 focal_loss 0.14165 dice_loss 0.24150 +Epoch [264/4000] Validation [3/4] Loss: 0.13440 focal_loss 0.06689 dice_loss 0.06751 +Epoch [264/4000] Validation [4/4] Loss: 0.17793 focal_loss 0.07595 dice_loss 0.10198 +Epoch [264/4000] Validation metric {'Val/mean dice_metric': 0.9629337191581726, 'Val/mean miou_metric': 0.9394871592521667, 'Val/mean f1': 0.9679976105690002, 'Val/mean precision': 0.9675092101097107, 'Val/mean recall': 0.9684866070747375, 'Val/mean hd95_metric': 6.133680820465088} +Cheakpoint... +Epoch [264/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9629], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629337191581726, 'Val/mean miou_metric': 0.9394871592521667, 'Val/mean f1': 0.9679976105690002, 'Val/mean precision': 0.9675092101097107, 'Val/mean recall': 0.9684866070747375, 'Val/mean hd95_metric': 6.133680820465088} +Epoch [265/4000] Training [1/16] Loss: 0.02159 +Epoch [265/4000] Training [2/16] Loss: 0.01748 +Epoch [265/4000] Training [3/16] Loss: 0.01730 +Epoch [265/4000] Training [4/16] Loss: 0.01695 +Epoch [265/4000] Training [5/16] Loss: 0.02772 +Epoch [265/4000] Training [6/16] Loss: 0.01668 +Epoch [265/4000] Training [7/16] Loss: 0.01759 +Epoch [265/4000] Training [8/16] Loss: 0.01652 +Epoch [265/4000] Training [9/16] Loss: 0.01459 +Epoch [265/4000] Training [10/16] Loss: 0.01709 +Epoch [265/4000] Training [11/16] Loss: 0.02703 +Epoch [265/4000] Training [12/16] Loss: 0.02278 +Epoch [265/4000] Training [13/16] Loss: 0.01663 +Epoch [265/4000] Training [14/16] Loss: 0.01728 +Epoch [265/4000] Training [15/16] Loss: 0.01381 +Epoch [265/4000] Training [16/16] Loss: 0.03081 +Epoch [265/4000] Training metric {'Train/mean dice_metric': 0.9867256879806519, 'Train/mean miou_metric': 0.973706841468811, 'Train/mean f1': 0.9843432903289795, 'Train/mean precision': 0.9801521301269531, 'Train/mean recall': 0.9885704517364502, 'Train/mean hd95_metric': 1.7237073183059692} +Epoch [265/4000] Validation [1/4] Loss: 0.40674 focal_loss 0.29283 dice_loss 0.11391 +Epoch [265/4000] Validation [2/4] Loss: 0.35751 focal_loss 0.12297 dice_loss 0.23454 +Epoch [265/4000] Validation [3/4] Loss: 0.21835 focal_loss 0.12263 dice_loss 0.09572 +Epoch [265/4000] Validation [4/4] Loss: 0.23422 focal_loss 0.10856 dice_loss 0.12566 +Epoch [265/4000] Validation metric {'Val/mean dice_metric': 0.9619867205619812, 'Val/mean miou_metric': 0.9384084939956665, 'Val/mean f1': 0.9661610126495361, 'Val/mean precision': 0.9643032550811768, 'Val/mean recall': 0.9680259227752686, 'Val/mean hd95_metric': 6.5740509033203125} +Cheakpoint... +Epoch [265/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9620], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9619867205619812, 'Val/mean miou_metric': 0.9384084939956665, 'Val/mean f1': 0.9661610126495361, 'Val/mean precision': 0.9643032550811768, 'Val/mean recall': 0.9680259227752686, 'Val/mean hd95_metric': 6.5740509033203125} +Epoch [266/4000] Training [1/16] Loss: 0.01618 +Epoch [266/4000] Training [2/16] Loss: 0.02295 +Epoch [266/4000] Training [3/16] Loss: 0.02112 +Epoch [266/4000] Training [4/16] Loss: 0.02713 +Epoch [266/4000] Training [5/16] Loss: 0.02070 +Epoch [266/4000] Training [6/16] Loss: 0.02426 +Epoch [266/4000] Training [7/16] Loss: 0.01441 +Epoch [266/4000] Training [8/16] Loss: 0.01542 +Epoch [266/4000] Training [9/16] Loss: 0.02003 +Epoch [266/4000] Training [10/16] Loss: 0.02462 +Epoch [266/4000] Training [11/16] Loss: 0.01580 +Epoch [266/4000] Training [12/16] Loss: 0.02099 +Epoch [266/4000] Training [13/16] Loss: 0.02792 +Epoch [266/4000] Training [14/16] Loss: 0.01980 +Epoch [266/4000] Training [15/16] Loss: 0.01718 +Epoch [266/4000] Training [16/16] Loss: 0.02450 +Epoch [266/4000] Training metric {'Train/mean dice_metric': 0.9858636856079102, 'Train/mean miou_metric': 0.9722439050674438, 'Train/mean f1': 0.9841482639312744, 'Train/mean precision': 0.979395866394043, 'Train/mean recall': 0.9889470338821411, 'Train/mean hd95_metric': 2.4600536823272705} +Epoch [266/4000] Validation [1/4] Loss: 0.15900 focal_loss 0.09904 dice_loss 0.05996 +Epoch [266/4000] Validation [2/4] Loss: 0.23773 focal_loss 0.08644 dice_loss 0.15130 +Epoch [266/4000] Validation [3/4] Loss: 0.12514 focal_loss 0.06643 dice_loss 0.05871 +Epoch [266/4000] Validation [4/4] Loss: 0.22161 focal_loss 0.10824 dice_loss 0.11337 +Epoch [266/4000] Validation metric {'Val/mean dice_metric': 0.9622337222099304, 'Val/mean miou_metric': 0.9374154210090637, 'Val/mean f1': 0.9667502641677856, 'Val/mean precision': 0.9585515260696411, 'Val/mean recall': 0.9750903844833374, 'Val/mean hd95_metric': 8.005510330200195} +Cheakpoint... +Epoch [266/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622337222099304, 'Val/mean miou_metric': 0.9374154210090637, 'Val/mean f1': 0.9667502641677856, 'Val/mean precision': 0.9585515260696411, 'Val/mean recall': 0.9750903844833374, 'Val/mean hd95_metric': 8.005510330200195} +Epoch [267/4000] Training [1/16] Loss: 0.02024 +Epoch [267/4000] Training [2/16] Loss: 0.01995 +Epoch [267/4000] Training [3/16] Loss: 0.01738 +Epoch [267/4000] Training [4/16] Loss: 0.02046 +Epoch [267/4000] Training [5/16] Loss: 0.02592 +Epoch [267/4000] Training [6/16] Loss: 0.02158 +Epoch [267/4000] Training [7/16] Loss: 0.02065 +Epoch [267/4000] Training [8/16] Loss: 0.01674 +Epoch [267/4000] Training [9/16] Loss: 0.01790 +Epoch [267/4000] Training [10/16] Loss: 0.01854 +Epoch [267/4000] Training [11/16] Loss: 0.01846 +Epoch [267/4000] Training [12/16] Loss: 0.01786 +Epoch [267/4000] Training [13/16] Loss: 0.02174 +Epoch [267/4000] Training [14/16] Loss: 0.01663 +Epoch [267/4000] Training [15/16] Loss: 0.01914 +Epoch [267/4000] Training [16/16] Loss: 0.02116 +Epoch [267/4000] Training metric {'Train/mean dice_metric': 0.9850504398345947, 'Train/mean miou_metric': 0.9708983898162842, 'Train/mean f1': 0.9836153388023376, 'Train/mean precision': 0.9792864918708801, 'Train/mean recall': 0.9879826307296753, 'Train/mean hd95_metric': 2.2217888832092285} +Epoch [267/4000] Validation [1/4] Loss: 0.14394 focal_loss 0.08127 dice_loss 0.06266 +Epoch [267/4000] Validation [2/4] Loss: 0.47407 focal_loss 0.19076 dice_loss 0.28331 +Epoch [267/4000] Validation [3/4] Loss: 0.16381 focal_loss 0.07459 dice_loss 0.08922 +Epoch [267/4000] Validation [4/4] Loss: 0.40422 focal_loss 0.17823 dice_loss 0.22599 +Epoch [267/4000] Validation metric {'Val/mean dice_metric': 0.955523669719696, 'Val/mean miou_metric': 0.9305611848831177, 'Val/mean f1': 0.9596145749092102, 'Val/mean precision': 0.9449560046195984, 'Val/mean recall': 0.9747352004051208, 'Val/mean hd95_metric': 7.876305103302002} +Cheakpoint... +Epoch [267/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9555], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.955523669719696, 'Val/mean miou_metric': 0.9305611848831177, 'Val/mean f1': 0.9596145749092102, 'Val/mean precision': 0.9449560046195984, 'Val/mean recall': 0.9747352004051208, 'Val/mean hd95_metric': 7.876305103302002} +Epoch [268/4000] Training [1/16] Loss: 0.04104 +Epoch [268/4000] Training [2/16] Loss: 0.02399 +Epoch [268/4000] Training [3/16] Loss: 0.01993 +Epoch [268/4000] Training [4/16] Loss: 0.02508 +Epoch [268/4000] Training [5/16] Loss: 0.01796 +Epoch [268/4000] Training [6/16] Loss: 0.01488 +Epoch [268/4000] Training [7/16] Loss: 0.02352 +Epoch [268/4000] Training [8/16] Loss: 0.01443 +Epoch [268/4000] Training [9/16] Loss: 0.01524 +Epoch [268/4000] Training [10/16] Loss: 0.02286 +Epoch [268/4000] Training [11/16] Loss: 0.02440 +Epoch [268/4000] Training [12/16] Loss: 0.01875 +Epoch [268/4000] Training [13/16] Loss: 0.02213 +Epoch [268/4000] Training [14/16] Loss: 0.02327 +Epoch [268/4000] Training [15/16] Loss: 0.01378 +Epoch [268/4000] Training [16/16] Loss: 0.01832 +Epoch [268/4000] Training metric {'Train/mean dice_metric': 0.9843360185623169, 'Train/mean miou_metric': 0.9693220853805542, 'Train/mean f1': 0.9828336834907532, 'Train/mean precision': 0.9786279797554016, 'Train/mean recall': 0.987075686454773, 'Train/mean hd95_metric': 2.1995484828948975} +Epoch [268/4000] Validation [1/4] Loss: 0.18266 focal_loss 0.10625 dice_loss 0.07642 +Epoch [268/4000] Validation [2/4] Loss: 0.68689 focal_loss 0.36705 dice_loss 0.31984 +Epoch [268/4000] Validation [3/4] Loss: 0.26201 focal_loss 0.16079 dice_loss 0.10122 +Epoch [268/4000] Validation [4/4] Loss: 0.30065 focal_loss 0.15863 dice_loss 0.14202 +Epoch [268/4000] Validation metric {'Val/mean dice_metric': 0.95818030834198, 'Val/mean miou_metric': 0.9320381283760071, 'Val/mean f1': 0.9629443287849426, 'Val/mean precision': 0.9584968686103821, 'Val/mean recall': 0.9674332141876221, 'Val/mean hd95_metric': 8.103001594543457} +Cheakpoint... +Epoch [268/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9582], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.95818030834198, 'Val/mean miou_metric': 0.9320381283760071, 'Val/mean f1': 0.9629443287849426, 'Val/mean precision': 0.9584968686103821, 'Val/mean recall': 0.9674332141876221, 'Val/mean hd95_metric': 8.103001594543457} +Epoch [269/4000] Training [1/16] Loss: 0.01591 +Epoch [269/4000] Training [2/16] Loss: 0.01952 +Epoch [269/4000] Training [3/16] Loss: 0.02165 +Epoch [269/4000] Training [4/16] Loss: 0.02070 +Epoch [269/4000] Training [5/16] Loss: 0.01767 +Epoch [269/4000] Training [6/16] Loss: 0.01689 +Epoch [269/4000] Training [7/16] Loss: 0.01857 +Epoch [269/4000] Training [8/16] Loss: 0.01815 +Epoch [269/4000] Training [9/16] Loss: 0.02185 +Epoch [269/4000] Training [10/16] Loss: 0.02057 +Epoch [269/4000] Training [11/16] Loss: 0.04089 +Epoch [269/4000] Training [12/16] Loss: 0.02094 +Epoch [269/4000] Training [13/16] Loss: 0.02203 +Epoch [269/4000] Training [14/16] Loss: 0.02212 +Epoch [269/4000] Training [15/16] Loss: 0.02085 +Epoch [269/4000] Training [16/16] Loss: 0.02123 +Epoch [269/4000] Training metric {'Train/mean dice_metric': 0.9839224815368652, 'Train/mean miou_metric': 0.9687079191207886, 'Train/mean f1': 0.9815253019332886, 'Train/mean precision': 0.9772278070449829, 'Train/mean recall': 0.9858607053756714, 'Train/mean hd95_metric': 2.7439637184143066} +Epoch [269/4000] Validation [1/4] Loss: 0.42542 focal_loss 0.30377 dice_loss 0.12165 +Epoch [269/4000] Validation [2/4] Loss: 0.56933 focal_loss 0.24180 dice_loss 0.32753 +Epoch [269/4000] Validation [3/4] Loss: 0.13627 focal_loss 0.06638 dice_loss 0.06989 +Epoch [269/4000] Validation [4/4] Loss: 0.16499 focal_loss 0.07609 dice_loss 0.08890 +Epoch [269/4000] Validation metric {'Val/mean dice_metric': 0.9571481943130493, 'Val/mean miou_metric': 0.9311432838439941, 'Val/mean f1': 0.9580539464950562, 'Val/mean precision': 0.9505503177642822, 'Val/mean recall': 0.96567702293396, 'Val/mean hd95_metric': 8.849352836608887} +Cheakpoint... +Epoch [269/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9571], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9571481943130493, 'Val/mean miou_metric': 0.9311432838439941, 'Val/mean f1': 0.9580539464950562, 'Val/mean precision': 0.9505503177642822, 'Val/mean recall': 0.96567702293396, 'Val/mean hd95_metric': 8.849352836608887} +Epoch [270/4000] Training [1/16] Loss: 0.01930 +Epoch [270/4000] Training [2/16] Loss: 0.01813 +Epoch [270/4000] Training [3/16] Loss: 0.01999 +Epoch [270/4000] Training [4/16] Loss: 0.01880 +Epoch [270/4000] Training [5/16] Loss: 0.02041 +Epoch [270/4000] Training [6/16] Loss: 0.02992 +Epoch [270/4000] Training [7/16] Loss: 0.02171 +Epoch [270/4000] Training [8/16] Loss: 0.04537 +Epoch [270/4000] Training [9/16] Loss: 0.02168 +Epoch [270/4000] Training [10/16] Loss: 0.02530 +Epoch [270/4000] Training [11/16] Loss: 0.01923 +Epoch [270/4000] Training [12/16] Loss: 0.02052 +Epoch [270/4000] Training [13/16] Loss: 0.02416 +Epoch [270/4000] Training [14/16] Loss: 0.02462 +Epoch [270/4000] Training [15/16] Loss: 0.02240 +Epoch [270/4000] Training [16/16] Loss: 0.02101 +Epoch [270/4000] Training metric {'Train/mean dice_metric': 0.9841489195823669, 'Train/mean miou_metric': 0.9689053297042847, 'Train/mean f1': 0.9817513823509216, 'Train/mean precision': 0.9769443273544312, 'Train/mean recall': 0.9866059422492981, 'Train/mean hd95_metric': 3.8983583450317383} +Epoch [270/4000] Validation [1/4] Loss: 1.07490 focal_loss 0.86682 dice_loss 0.20808 +Epoch [270/4000] Validation [2/4] Loss: 0.80021 focal_loss 0.46213 dice_loss 0.33809 +Epoch [270/4000] Validation [3/4] Loss: 0.12860 focal_loss 0.06166 dice_loss 0.06694 +Epoch [270/4000] Validation [4/4] Loss: 0.20851 focal_loss 0.08941 dice_loss 0.11909 +Epoch [270/4000] Validation metric {'Val/mean dice_metric': 0.956299901008606, 'Val/mean miou_metric': 0.9304240942001343, 'Val/mean f1': 0.9588780403137207, 'Val/mean precision': 0.9574074745178223, 'Val/mean recall': 0.9603530764579773, 'Val/mean hd95_metric': 9.345991134643555} +Cheakpoint... +Epoch [270/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9563], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.956299901008606, 'Val/mean miou_metric': 0.9304240942001343, 'Val/mean f1': 0.9588780403137207, 'Val/mean precision': 0.9574074745178223, 'Val/mean recall': 0.9603530764579773, 'Val/mean hd95_metric': 9.345991134643555} +Epoch [271/4000] Training [1/16] Loss: 0.02080 +Epoch [271/4000] Training [2/16] Loss: 0.02225 +Epoch [271/4000] Training [3/16] Loss: 0.02126 +Epoch [271/4000] Training [4/16] Loss: 0.01644 +Epoch [271/4000] Training [5/16] Loss: 0.02373 +Epoch [271/4000] Training [6/16] Loss: 0.05206 +Epoch [271/4000] Training [7/16] Loss: 0.04133 +Epoch [271/4000] Training [8/16] Loss: 0.03051 +Epoch [271/4000] Training [9/16] Loss: 0.02702 +Epoch [271/4000] Training [10/16] Loss: 0.02400 +Epoch [271/4000] Training [11/16] Loss: 0.01963 +Epoch [271/4000] Training [12/16] Loss: 0.02008 +Epoch [271/4000] Training [13/16] Loss: 0.02077 +Epoch [271/4000] Training [14/16] Loss: 0.02701 +Epoch [271/4000] Training [15/16] Loss: 0.02921 +Epoch [271/4000] Training [16/16] Loss: 0.02041 +Epoch [271/4000] Training metric {'Train/mean dice_metric': 0.9817466139793396, 'Train/mean miou_metric': 0.9648340940475464, 'Train/mean f1': 0.9792053699493408, 'Train/mean precision': 0.9739276170730591, 'Train/mean recall': 0.984540581703186, 'Train/mean hd95_metric': 3.481168508529663} +Epoch [271/4000] Validation [1/4] Loss: 0.20021 focal_loss 0.10067 dice_loss 0.09954 +Epoch [271/4000] Validation [2/4] Loss: 0.39267 focal_loss 0.16789 dice_loss 0.22478 +Epoch [271/4000] Validation [3/4] Loss: 0.20510 focal_loss 0.09572 dice_loss 0.10938 +Epoch [271/4000] Validation [4/4] Loss: 0.26133 focal_loss 0.09705 dice_loss 0.16429 +Epoch [271/4000] Validation metric {'Val/mean dice_metric': 0.9533416628837585, 'Val/mean miou_metric': 0.9252622723579407, 'Val/mean f1': 0.9550827145576477, 'Val/mean precision': 0.9510592818260193, 'Val/mean recall': 0.9591403603553772, 'Val/mean hd95_metric': 8.558759689331055} +Cheakpoint... +Epoch [271/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9533], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9533416628837585, 'Val/mean miou_metric': 0.9252622723579407, 'Val/mean f1': 0.9550827145576477, 'Val/mean precision': 0.9510592818260193, 'Val/mean recall': 0.9591403603553772, 'Val/mean hd95_metric': 8.558759689331055} +Epoch [272/4000] Training [1/16] Loss: 0.02271 +Epoch [272/4000] Training [2/16] Loss: 0.02074 +Epoch [272/4000] Training [3/16] Loss: 0.02209 +Epoch [272/4000] Training [4/16] Loss: 0.01935 +Epoch [272/4000] Training [5/16] Loss: 0.03232 +Epoch [272/4000] Training [6/16] Loss: 0.02268 +Epoch [272/4000] Training [7/16] Loss: 0.02368 +Epoch [272/4000] Training [8/16] Loss: 0.01991 +Epoch [272/4000] Training [9/16] Loss: 0.03032 +Epoch [272/4000] Training [10/16] Loss: 0.01643 +Epoch [272/4000] Training [11/16] Loss: 0.02984 +Epoch [272/4000] Training [12/16] Loss: 0.02464 +Epoch [272/4000] Training [13/16] Loss: 0.01848 +Epoch [272/4000] Training [14/16] Loss: 0.02938 +Epoch [272/4000] Training [15/16] Loss: 0.03589 +Epoch [272/4000] Training [16/16] Loss: 0.03837 +Epoch [272/4000] Training metric {'Train/mean dice_metric': 0.9804955720901489, 'Train/mean miou_metric': 0.9626127481460571, 'Train/mean f1': 0.9787514209747314, 'Train/mean precision': 0.9739542007446289, 'Train/mean recall': 0.9835960865020752, 'Train/mean hd95_metric': 3.6014134883880615} +Epoch [272/4000] Validation [1/4] Loss: 0.22098 focal_loss 0.13611 dice_loss 0.08487 +Epoch [272/4000] Validation [2/4] Loss: 0.60538 focal_loss 0.31085 dice_loss 0.29454 +Epoch [272/4000] Validation [3/4] Loss: 0.18700 focal_loss 0.08165 dice_loss 0.10535 +Epoch [272/4000] Validation [4/4] Loss: 0.29253 focal_loss 0.14258 dice_loss 0.14995 +Epoch [272/4000] Validation metric {'Val/mean dice_metric': 0.9522703289985657, 'Val/mean miou_metric': 0.9235385656356812, 'Val/mean f1': 0.9558724164962769, 'Val/mean precision': 0.948945164680481, 'Val/mean recall': 0.9629013538360596, 'Val/mean hd95_metric': 9.389768600463867} +Cheakpoint... +Epoch [272/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9523], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9522703289985657, 'Val/mean miou_metric': 0.9235385656356812, 'Val/mean f1': 0.9558724164962769, 'Val/mean precision': 0.948945164680481, 'Val/mean recall': 0.9629013538360596, 'Val/mean hd95_metric': 9.389768600463867} +Epoch [273/4000] Training [1/16] Loss: 0.03064 +Epoch [273/4000] Training [2/16] Loss: 0.03372 +Epoch [273/4000] Training [3/16] Loss: 0.06933 +Epoch [273/4000] Training [4/16] Loss: 0.02207 +Epoch [273/4000] Training [5/16] Loss: 0.03037 +Epoch [273/4000] Training [6/16] Loss: 0.01819 +Epoch [273/4000] Training [7/16] Loss: 0.02800 +Epoch [273/4000] Training [8/16] Loss: 0.01558 +Epoch [273/4000] Training [9/16] Loss: 0.02011 +Epoch [273/4000] Training [10/16] Loss: 0.02042 +Epoch [273/4000] Training [11/16] Loss: 0.07270 +Epoch [273/4000] Training [12/16] Loss: 0.02073 +Epoch [273/4000] Training [13/16] Loss: 0.02672 +Epoch [273/4000] Training [14/16] Loss: 0.03265 +Epoch [273/4000] Training [15/16] Loss: 0.02021 +Epoch [273/4000] Training [16/16] Loss: 0.04993 +Epoch [273/4000] Training metric {'Train/mean dice_metric': 0.9800448417663574, 'Train/mean miou_metric': 0.9617565274238586, 'Train/mean f1': 0.9760631322860718, 'Train/mean precision': 0.9733844995498657, 'Train/mean recall': 0.9787566065788269, 'Train/mean hd95_metric': 5.530688285827637} +Epoch [273/4000] Validation [1/4] Loss: 0.14286 focal_loss 0.07243 dice_loss 0.07043 +Epoch [273/4000] Validation [2/4] Loss: 0.42659 focal_loss 0.17524 dice_loss 0.25135 +Epoch [273/4000] Validation [3/4] Loss: 0.16360 focal_loss 0.06523 dice_loss 0.09837 +Epoch [273/4000] Validation [4/4] Loss: 0.46914 focal_loss 0.23213 dice_loss 0.23702 +Epoch [273/4000] Validation metric {'Val/mean dice_metric': 0.9485212564468384, 'Val/mean miou_metric': 0.9189962148666382, 'Val/mean f1': 0.9455745220184326, 'Val/mean precision': 0.9251137971878052, 'Val/mean recall': 0.9669607281684875, 'Val/mean hd95_metric': 12.645784378051758} +Cheakpoint... +Epoch [273/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9485], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9485212564468384, 'Val/mean miou_metric': 0.9189962148666382, 'Val/mean f1': 0.9455745220184326, 'Val/mean precision': 0.9251137971878052, 'Val/mean recall': 0.9669607281684875, 'Val/mean hd95_metric': 12.645784378051758} +Epoch [274/4000] Training [1/16] Loss: 0.01872 +Epoch [274/4000] Training [2/16] Loss: 0.02822 +Epoch [274/4000] Training [3/16] Loss: 0.02042 +Epoch [274/4000] Training [4/16] Loss: 0.03101 +Epoch [274/4000] Training [5/16] Loss: 0.01919 +Epoch [274/4000] Training [6/16] Loss: 0.01863 +Epoch [274/4000] Training [7/16] Loss: 0.02084 +Epoch [274/4000] Training [8/16] Loss: 0.02069 +Epoch [274/4000] Training [9/16] Loss: 0.02602 +Epoch [274/4000] Training [10/16] Loss: 0.10715 +Epoch [274/4000] Training [11/16] Loss: 0.02068 +Epoch [274/4000] Training [12/16] Loss: 0.02101 +Epoch [274/4000] Training [13/16] Loss: 0.02746 +Epoch [274/4000] Training [14/16] Loss: 0.01713 +Epoch [274/4000] Training [15/16] Loss: 0.02026 +Epoch [274/4000] Training [16/16] Loss: 0.02494 +Epoch [274/4000] Training metric {'Train/mean dice_metric': 0.9828932285308838, 'Train/mean miou_metric': 0.9672327041625977, 'Train/mean f1': 0.9787442684173584, 'Train/mean precision': 0.9756554961204529, 'Train/mean recall': 0.981852650642395, 'Train/mean hd95_metric': 4.441706657409668} +Epoch [274/4000] Validation [1/4] Loss: 0.90373 focal_loss 0.69609 dice_loss 0.20765 +Epoch [274/4000] Validation [2/4] Loss: 0.15353 focal_loss 0.03994 dice_loss 0.11359 +Epoch [274/4000] Validation [3/4] Loss: 0.12032 focal_loss 0.05358 dice_loss 0.06674 +Epoch [274/4000] Validation [4/4] Loss: 0.39468 focal_loss 0.23235 dice_loss 0.16233 +Epoch [274/4000] Validation metric {'Val/mean dice_metric': 0.9521496891975403, 'Val/mean miou_metric': 0.9249688386917114, 'Val/mean f1': 0.9511340856552124, 'Val/mean precision': 0.9602892398834229, 'Val/mean recall': 0.9421519637107849, 'Val/mean hd95_metric': 10.23863410949707} +Cheakpoint... +Epoch [274/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9521], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9521496891975403, 'Val/mean miou_metric': 0.9249688386917114, 'Val/mean f1': 0.9511340856552124, 'Val/mean precision': 0.9602892398834229, 'Val/mean recall': 0.9421519637107849, 'Val/mean hd95_metric': 10.23863410949707} +Epoch [275/4000] Training [1/16] Loss: 0.02443 +Epoch [275/4000] Training [2/16] Loss: 0.05225 +Epoch [275/4000] Training [3/16] Loss: 0.01586 +Epoch [275/4000] Training [4/16] Loss: 0.02008 +Epoch [275/4000] Training [5/16] Loss: 0.02175 +Epoch [275/4000] Training [6/16] Loss: 0.02143 +Epoch [275/4000] Training [7/16] Loss: 0.02490 +Epoch [275/4000] Training [8/16] Loss: 0.02925 +Epoch [275/4000] Training [9/16] Loss: 0.04797 +Epoch [275/4000] Training [10/16] Loss: 0.02149 +Epoch [275/4000] Training [11/16] Loss: 0.02240 +Epoch [275/4000] Training [12/16] Loss: 0.02658 +Epoch [275/4000] Training [13/16] Loss: 0.02247 +Epoch [275/4000] Training [14/16] Loss: 0.02416 +Epoch [275/4000] Training [15/16] Loss: 0.02238 +Epoch [275/4000] Training [16/16] Loss: 0.04581 +Epoch [275/4000] Training metric {'Train/mean dice_metric': 0.9793016910552979, 'Train/mean miou_metric': 0.9609835147857666, 'Train/mean f1': 0.9765258431434631, 'Train/mean precision': 0.9725561738014221, 'Train/mean recall': 0.9805279970169067, 'Train/mean hd95_metric': 5.285248756408691} +Epoch [275/4000] Validation [1/4] Loss: 0.47196 focal_loss 0.33387 dice_loss 0.13809 +Epoch [275/4000] Validation [2/4] Loss: 0.45548 focal_loss 0.17283 dice_loss 0.28265 +Epoch [275/4000] Validation [3/4] Loss: 0.23381 focal_loss 0.10656 dice_loss 0.12725 +Epoch [275/4000] Validation [4/4] Loss: 0.17822 focal_loss 0.06740 dice_loss 0.11082 +Epoch [275/4000] Validation metric {'Val/mean dice_metric': 0.9542005658149719, 'Val/mean miou_metric': 0.9241913557052612, 'Val/mean f1': 0.9552603960037231, 'Val/mean precision': 0.949284553527832, 'Val/mean recall': 0.9613119959831238, 'Val/mean hd95_metric': 11.376461029052734} +Cheakpoint... +Epoch [275/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9542], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9542005658149719, 'Val/mean miou_metric': 0.9241913557052612, 'Val/mean f1': 0.9552603960037231, 'Val/mean precision': 0.949284553527832, 'Val/mean recall': 0.9613119959831238, 'Val/mean hd95_metric': 11.376461029052734} +Epoch [276/4000] Training [1/16] Loss: 0.01924 +Epoch [276/4000] Training [2/16] Loss: 0.02575 +Epoch [276/4000] Training [3/16] Loss: 0.02506 +Epoch [276/4000] Training [4/16] Loss: 0.02601 +Epoch [276/4000] Training [5/16] Loss: 0.01825 +Epoch [276/4000] Training [6/16] Loss: 0.02297 +Epoch [276/4000] Training [7/16] Loss: 0.01989 +Epoch [276/4000] Training [8/16] Loss: 0.01697 +Epoch [276/4000] Training [9/16] Loss: 0.02199 +Epoch [276/4000] Training [10/16] Loss: 0.02490 +Epoch [276/4000] Training [11/16] Loss: 0.01561 +Epoch [276/4000] Training [12/16] Loss: 0.03365 +Epoch [276/4000] Training [13/16] Loss: 0.02310 +Epoch [276/4000] Training [14/16] Loss: 0.03300 +Epoch [276/4000] Training [15/16] Loss: 0.04071 +Epoch [276/4000] Training [16/16] Loss: 0.02366 +Epoch [276/4000] Training metric {'Train/mean dice_metric': 0.9821705222129822, 'Train/mean miou_metric': 0.9655163288116455, 'Train/mean f1': 0.9803476333618164, 'Train/mean precision': 0.9760636687278748, 'Train/mean recall': 0.9846693873405457, 'Train/mean hd95_metric': 3.9841060638427734} +Epoch [276/4000] Validation [1/4] Loss: 0.29516 focal_loss 0.17096 dice_loss 0.12420 +Epoch [276/4000] Validation [2/4] Loss: 0.27459 focal_loss 0.09351 dice_loss 0.18108 +Epoch [276/4000] Validation [3/4] Loss: 0.13203 focal_loss 0.06054 dice_loss 0.07149 +Epoch [276/4000] Validation [4/4] Loss: 0.21117 focal_loss 0.07308 dice_loss 0.13809 +Epoch [276/4000] Validation metric {'Val/mean dice_metric': 0.9578456878662109, 'Val/mean miou_metric': 0.9303380846977234, 'Val/mean f1': 0.9599390625953674, 'Val/mean precision': 0.9596832394599915, 'Val/mean recall': 0.960195004940033, 'Val/mean hd95_metric': 8.708513259887695} +Cheakpoint... +Epoch [276/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9578], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9578456878662109, 'Val/mean miou_metric': 0.9303380846977234, 'Val/mean f1': 0.9599390625953674, 'Val/mean precision': 0.9596832394599915, 'Val/mean recall': 0.960195004940033, 'Val/mean hd95_metric': 8.708513259887695} +Epoch [277/4000] Training [1/16] Loss: 0.01805 +Epoch [277/4000] Training [2/16] Loss: 0.02614 +Epoch [277/4000] Training [3/16] Loss: 0.02230 +Epoch [277/4000] Training [4/16] Loss: 0.02983 +Epoch [277/4000] Training [5/16] Loss: 0.02577 +Epoch [277/4000] Training [6/16] Loss: 0.02959 +Epoch [277/4000] Training [7/16] Loss: 0.02214 +Epoch [277/4000] Training [8/16] Loss: 0.02135 +Epoch [277/4000] Training [9/16] Loss: 0.02572 +Epoch [277/4000] Training [10/16] Loss: 0.03274 +Epoch [277/4000] Training [11/16] Loss: 0.04876 +Epoch [277/4000] Training [12/16] Loss: 0.02551 +Epoch [277/4000] Training [13/16] Loss: 0.02061 +Epoch [277/4000] Training [14/16] Loss: 0.02711 +Epoch [277/4000] Training [15/16] Loss: 0.01652 +Epoch [277/4000] Training [16/16] Loss: 0.02714 +Epoch [277/4000] Training metric {'Train/mean dice_metric': 0.9819503426551819, 'Train/mean miou_metric': 0.965305745601654, 'Train/mean f1': 0.9796174764633179, 'Train/mean precision': 0.9754698872566223, 'Train/mean recall': 0.9838007092475891, 'Train/mean hd95_metric': 3.030442714691162} +Epoch [277/4000] Validation [1/4] Loss: 0.26316 focal_loss 0.16381 dice_loss 0.09935 +Epoch [277/4000] Validation [2/4] Loss: 0.37880 focal_loss 0.14832 dice_loss 0.23048 +Epoch [277/4000] Validation [3/4] Loss: 0.17898 focal_loss 0.08633 dice_loss 0.09266 +Epoch [277/4000] Validation [4/4] Loss: 0.17632 focal_loss 0.06535 dice_loss 0.11097 +Epoch [277/4000] Validation metric {'Val/mean dice_metric': 0.9578418731689453, 'Val/mean miou_metric': 0.9298222661018372, 'Val/mean f1': 0.9598492980003357, 'Val/mean precision': 0.9548366069793701, 'Val/mean recall': 0.9649150371551514, 'Val/mean hd95_metric': 8.11005687713623} +Cheakpoint... +Epoch [277/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9578], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9578418731689453, 'Val/mean miou_metric': 0.9298222661018372, 'Val/mean f1': 0.9598492980003357, 'Val/mean precision': 0.9548366069793701, 'Val/mean recall': 0.9649150371551514, 'Val/mean hd95_metric': 8.11005687713623} +Epoch [278/4000] Training [1/16] Loss: 0.01761 +Epoch [278/4000] Training [2/16] Loss: 0.01978 +Epoch [278/4000] Training [3/16] Loss: 0.02139 +Epoch [278/4000] Training [4/16] Loss: 0.02070 +Epoch [278/4000] Training [5/16] Loss: 0.01978 +Epoch [278/4000] Training [6/16] Loss: 0.02023 +Epoch [278/4000] Training [7/16] Loss: 0.02613 +Epoch [278/4000] Training [8/16] Loss: 0.01584 +Epoch [278/4000] Training [9/16] Loss: 0.02055 +Epoch [278/4000] Training [10/16] Loss: 0.01874 +Epoch [278/4000] Training [11/16] Loss: 0.01465 +Epoch [278/4000] Training [12/16] Loss: 0.02120 +Epoch [278/4000] Training [13/16] Loss: 0.01568 +Epoch [278/4000] Training [14/16] Loss: 0.01849 +Epoch [278/4000] Training [15/16] Loss: 0.04013 +Epoch [278/4000] Training [16/16] Loss: 0.01974 +Epoch [278/4000] Training metric {'Train/mean dice_metric': 0.9860739707946777, 'Train/mean miou_metric': 0.9724587202072144, 'Train/mean f1': 0.983673095703125, 'Train/mean precision': 0.9789080619812012, 'Train/mean recall': 0.9884846806526184, 'Train/mean hd95_metric': 2.007462501525879} +Epoch [278/4000] Validation [1/4] Loss: 0.27260 focal_loss 0.17561 dice_loss 0.09700 +Epoch [278/4000] Validation [2/4] Loss: 0.40790 focal_loss 0.16529 dice_loss 0.24260 +Epoch [278/4000] Validation [3/4] Loss: 0.12076 focal_loss 0.05742 dice_loss 0.06334 +Epoch [278/4000] Validation [4/4] Loss: 0.16997 focal_loss 0.06912 dice_loss 0.10084 +Epoch [278/4000] Validation metric {'Val/mean dice_metric': 0.9629669189453125, 'Val/mean miou_metric': 0.9388046264648438, 'Val/mean f1': 0.9633333683013916, 'Val/mean precision': 0.958672046661377, 'Val/mean recall': 0.9680404663085938, 'Val/mean hd95_metric': 6.739274024963379} +Cheakpoint... +Epoch [278/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629669189453125, 'Val/mean miou_metric': 0.9388046264648438, 'Val/mean f1': 0.9633333683013916, 'Val/mean precision': 0.958672046661377, 'Val/mean recall': 0.9680404663085938, 'Val/mean hd95_metric': 6.739274024963379} +Epoch [279/4000] Training [1/16] Loss: 0.01643 +Epoch [279/4000] Training [2/16] Loss: 0.01852 +Epoch [279/4000] Training [3/16] Loss: 0.02401 +Epoch [279/4000] Training [4/16] Loss: 0.02245 +Epoch [279/4000] Training [5/16] Loss: 0.03002 +Epoch [279/4000] Training [6/16] Loss: 0.01814 +Epoch [279/4000] Training [7/16] Loss: 0.01770 +Epoch [279/4000] Training [8/16] Loss: 0.02602 +Epoch [279/4000] Training [9/16] Loss: 0.02017 +Epoch [279/4000] Training [10/16] Loss: 0.02033 +Epoch [279/4000] Training [11/16] Loss: 0.01741 +Epoch [279/4000] Training [12/16] Loss: 0.02065 +Epoch [279/4000] Training [13/16] Loss: 0.01818 +Epoch [279/4000] Training [14/16] Loss: 0.04902 +Epoch [279/4000] Training [15/16] Loss: 0.01666 +Epoch [279/4000] Training [16/16] Loss: 0.02348 +Epoch [279/4000] Training metric {'Train/mean dice_metric': 0.9852048754692078, 'Train/mean miou_metric': 0.9709005355834961, 'Train/mean f1': 0.9820234775543213, 'Train/mean precision': 0.9775198101997375, 'Train/mean recall': 0.9865688681602478, 'Train/mean hd95_metric': 2.6083908081054688} +Epoch [279/4000] Validation [1/4] Loss: 0.11825 focal_loss 0.06131 dice_loss 0.05694 +Epoch [279/4000] Validation [2/4] Loss: 0.71618 focal_loss 0.38078 dice_loss 0.33540 +Epoch [279/4000] Validation [3/4] Loss: 0.13275 focal_loss 0.06266 dice_loss 0.07009 +Epoch [279/4000] Validation [4/4] Loss: 0.13156 focal_loss 0.04615 dice_loss 0.08540 +Epoch [279/4000] Validation metric {'Val/mean dice_metric': 0.9639843702316284, 'Val/mean miou_metric': 0.9397251009941101, 'Val/mean f1': 0.9658140540122986, 'Val/mean precision': 0.9589756727218628, 'Val/mean recall': 0.9727506637573242, 'Val/mean hd95_metric': 6.7460036277771} +Cheakpoint... +Epoch [279/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639843702316284, 'Val/mean miou_metric': 0.9397251009941101, 'Val/mean f1': 0.9658140540122986, 'Val/mean precision': 0.9589756727218628, 'Val/mean recall': 0.9727506637573242, 'Val/mean hd95_metric': 6.7460036277771} +Epoch [280/4000] Training [1/16] Loss: 0.02032 +Epoch [280/4000] Training [2/16] Loss: 0.02675 +Epoch [280/4000] Training [3/16] Loss: 0.02499 +Epoch [280/4000] Training [4/16] Loss: 0.01995 +Epoch [280/4000] Training [5/16] Loss: 0.02290 +Epoch [280/4000] Training [6/16] Loss: 0.01520 +Epoch [280/4000] Training [7/16] Loss: 0.02656 +Epoch [280/4000] Training [8/16] Loss: 0.01911 +Epoch [280/4000] Training [9/16] Loss: 0.01390 +Epoch [280/4000] Training [10/16] Loss: 0.01722 +Epoch [280/4000] Training [11/16] Loss: 0.05475 +Epoch [280/4000] Training [12/16] Loss: 0.02284 +Epoch [280/4000] Training [13/16] Loss: 0.02105 +Epoch [280/4000] Training [14/16] Loss: 0.01666 +Epoch [280/4000] Training [15/16] Loss: 0.01910 +Epoch [280/4000] Training [16/16] Loss: 0.02555 +Epoch [280/4000] Training metric {'Train/mean dice_metric': 0.9849086999893188, 'Train/mean miou_metric': 0.9703249931335449, 'Train/mean f1': 0.9817037582397461, 'Train/mean precision': 0.976255476474762, 'Train/mean recall': 0.9872131943702698, 'Train/mean hd95_metric': 2.2532031536102295} +Epoch [280/4000] Validation [1/4] Loss: 0.90807 focal_loss 0.72715 dice_loss 0.18092 +Epoch [280/4000] Validation [2/4] Loss: 0.43512 focal_loss 0.22989 dice_loss 0.20523 +Epoch [280/4000] Validation [3/4] Loss: 0.14850 focal_loss 0.07332 dice_loss 0.07517 +Epoch [280/4000] Validation [4/4] Loss: 0.24169 focal_loss 0.11445 dice_loss 0.12724 +Epoch [280/4000] Validation metric {'Val/mean dice_metric': 0.9572548866271973, 'Val/mean miou_metric': 0.9316362142562866, 'Val/mean f1': 0.9582576155662537, 'Val/mean precision': 0.9619802236557007, 'Val/mean recall': 0.9545636773109436, 'Val/mean hd95_metric': 7.806815147399902} +Cheakpoint... +Epoch [280/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9573], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9572548866271973, 'Val/mean miou_metric': 0.9316362142562866, 'Val/mean f1': 0.9582576155662537, 'Val/mean precision': 0.9619802236557007, 'Val/mean recall': 0.9545636773109436, 'Val/mean hd95_metric': 7.806815147399902} +Epoch [281/4000] Training [1/16] Loss: 0.01902 +Epoch [281/4000] Training [2/16] Loss: 0.04554 +Epoch [281/4000] Training [3/16] Loss: 0.04622 +Epoch [281/4000] Training [4/16] Loss: 0.02846 +Epoch [281/4000] Training [5/16] Loss: 0.02106 +Epoch [281/4000] Training [6/16] Loss: 0.02204 +Epoch [281/4000] Training [7/16] Loss: 0.03602 +Epoch [281/4000] Training [8/16] Loss: 0.02237 +Epoch [281/4000] Training [9/16] Loss: 0.01554 +Epoch [281/4000] Training [10/16] Loss: 0.02281 +Epoch [281/4000] Training [11/16] Loss: 0.02529 +Epoch [281/4000] Training [12/16] Loss: 0.02514 +Epoch [281/4000] Training [13/16] Loss: 0.02236 +Epoch [281/4000] Training [14/16] Loss: 0.01807 +Epoch [281/4000] Training [15/16] Loss: 0.02390 +Epoch [281/4000] Training [16/16] Loss: 0.02037 +Epoch [281/4000] Training metric {'Train/mean dice_metric': 0.9826138615608215, 'Train/mean miou_metric': 0.9659559726715088, 'Train/mean f1': 0.9798685908317566, 'Train/mean precision': 0.9760423302650452, 'Train/mean recall': 0.9837248921394348, 'Train/mean hd95_metric': 3.758596897125244} +Epoch [281/4000] Validation [1/4] Loss: 0.13225 focal_loss 0.07171 dice_loss 0.06054 +Epoch [281/4000] Validation [2/4] Loss: 0.43281 focal_loss 0.18972 dice_loss 0.24309 +Epoch [281/4000] Validation [3/4] Loss: 0.13606 focal_loss 0.06139 dice_loss 0.07467 +Epoch [281/4000] Validation [4/4] Loss: 0.24044 focal_loss 0.10307 dice_loss 0.13737 +Epoch [281/4000] Validation metric {'Val/mean dice_metric': 0.9591838717460632, 'Val/mean miou_metric': 0.932168185710907, 'Val/mean f1': 0.9628101587295532, 'Val/mean precision': 0.960006058216095, 'Val/mean recall': 0.9656305313110352, 'Val/mean hd95_metric': 8.048100471496582} +Cheakpoint... +Epoch [281/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9592], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9591838717460632, 'Val/mean miou_metric': 0.932168185710907, 'Val/mean f1': 0.9628101587295532, 'Val/mean precision': 0.960006058216095, 'Val/mean recall': 0.9656305313110352, 'Val/mean hd95_metric': 8.048100471496582} +Epoch [282/4000] Training [1/16] Loss: 0.03059 +Epoch [282/4000] Training [2/16] Loss: 0.01992 +Epoch [282/4000] Training [3/16] Loss: 0.02107 +Epoch [282/4000] Training [4/16] Loss: 0.03140 +Epoch [282/4000] Training [5/16] Loss: 0.02207 +Epoch [282/4000] Training [6/16] Loss: 0.06535 +Epoch [282/4000] Training [7/16] Loss: 0.01872 +Epoch [282/4000] Training [8/16] Loss: 0.02794 +Epoch [282/4000] Training [9/16] Loss: 0.01865 +Epoch [282/4000] Training [10/16] Loss: 0.02239 +Epoch [282/4000] Training [11/16] Loss: 0.02377 +Epoch [282/4000] Training [12/16] Loss: 0.02286 +Epoch [282/4000] Training [13/16] Loss: 0.02667 +Epoch [282/4000] Training [14/16] Loss: 0.01670 +Epoch [282/4000] Training [15/16] Loss: 0.02114 +Epoch [282/4000] Training [16/16] Loss: 0.02307 +Epoch [282/4000] Training metric {'Train/mean dice_metric': 0.9829622507095337, 'Train/mean miou_metric': 0.9666906595230103, 'Train/mean f1': 0.9797413945198059, 'Train/mean precision': 0.9759297370910645, 'Train/mean recall': 0.9835830330848694, 'Train/mean hd95_metric': 2.659475326538086} +Epoch [282/4000] Validation [1/4] Loss: 0.14579 focal_loss 0.08426 dice_loss 0.06154 +Epoch [282/4000] Validation [2/4] Loss: 0.53963 focal_loss 0.25427 dice_loss 0.28536 +Epoch [282/4000] Validation [3/4] Loss: 0.19555 focal_loss 0.08783 dice_loss 0.10772 +Epoch [282/4000] Validation [4/4] Loss: 0.18523 focal_loss 0.07474 dice_loss 0.11049 +Epoch [282/4000] Validation metric {'Val/mean dice_metric': 0.9583263397216797, 'Val/mean miou_metric': 0.9311798810958862, 'Val/mean f1': 0.9603148102760315, 'Val/mean precision': 0.9499746561050415, 'Val/mean recall': 0.9708824753761292, 'Val/mean hd95_metric': 9.525464057922363} +Cheakpoint... +Epoch [282/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9583], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9583263397216797, 'Val/mean miou_metric': 0.9311798810958862, 'Val/mean f1': 0.9603148102760315, 'Val/mean precision': 0.9499746561050415, 'Val/mean recall': 0.9708824753761292, 'Val/mean hd95_metric': 9.525464057922363} +Epoch [283/4000] Training [1/16] Loss: 0.02759 +Epoch [283/4000] Training [2/16] Loss: 0.04518 +Epoch [283/4000] Training [3/16] Loss: 0.02444 +Epoch [283/4000] Training [4/16] Loss: 0.03349 +Epoch [283/4000] Training [5/16] Loss: 0.01683 +Epoch [283/4000] Training [6/16] Loss: 0.02520 +Epoch [283/4000] Training [7/16] Loss: 0.02215 +Epoch [283/4000] Training [8/16] Loss: 0.02377 +Epoch [283/4000] Training [9/16] Loss: 0.02250 +Epoch [283/4000] Training [10/16] Loss: 0.01873 +Epoch [283/4000] Training [11/16] Loss: 0.02228 +Epoch [283/4000] Training [12/16] Loss: 0.02580 +Epoch [283/4000] Training [13/16] Loss: 0.01843 +Epoch [283/4000] Training [14/16] Loss: 0.02237 +Epoch [283/4000] Training [15/16] Loss: 0.02915 +Epoch [283/4000] Training [16/16] Loss: 0.02085 +Epoch [283/4000] Training metric {'Train/mean dice_metric': 0.9832329750061035, 'Train/mean miou_metric': 0.9671008586883545, 'Train/mean f1': 0.9813036322593689, 'Train/mean precision': 0.9764465689659119, 'Train/mean recall': 0.9862092733383179, 'Train/mean hd95_metric': 3.0996713638305664} +Epoch [283/4000] Validation [1/4] Loss: 0.16335 focal_loss 0.08096 dice_loss 0.08239 +Epoch [283/4000] Validation [2/4] Loss: 0.31105 focal_loss 0.12268 dice_loss 0.18837 +Epoch [283/4000] Validation [3/4] Loss: 0.15377 focal_loss 0.07613 dice_loss 0.07764 +Epoch [283/4000] Validation [4/4] Loss: 0.31235 focal_loss 0.16258 dice_loss 0.14977 +Epoch [283/4000] Validation metric {'Val/mean dice_metric': 0.9594658017158508, 'Val/mean miou_metric': 0.9328378438949585, 'Val/mean f1': 0.9617989659309387, 'Val/mean precision': 0.9558001160621643, 'Val/mean recall': 0.9678736925125122, 'Val/mean hd95_metric': 8.110723495483398} +Cheakpoint... +Epoch [283/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9595], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9594658017158508, 'Val/mean miou_metric': 0.9328378438949585, 'Val/mean f1': 0.9617989659309387, 'Val/mean precision': 0.9558001160621643, 'Val/mean recall': 0.9678736925125122, 'Val/mean hd95_metric': 8.110723495483398} +Epoch [284/4000] Training [1/16] Loss: 0.02270 +Epoch [284/4000] Training [2/16] Loss: 0.02470 +Epoch [284/4000] Training [3/16] Loss: 0.02110 +Epoch [284/4000] Training [4/16] Loss: 0.01748 +Epoch [284/4000] Training [5/16] Loss: 0.02026 +Epoch [284/4000] Training [6/16] Loss: 0.01878 +Epoch [284/4000] Training [7/16] Loss: 0.01627 +Epoch [284/4000] Training [8/16] Loss: 0.01764 +Epoch [284/4000] Training [9/16] Loss: 0.02120 +Epoch [284/4000] Training [10/16] Loss: 0.02277 +Epoch [284/4000] Training [11/16] Loss: 0.02977 +Epoch [284/4000] Training [12/16] Loss: 0.01713 +Epoch [284/4000] Training [13/16] Loss: 0.02135 +Epoch [284/4000] Training [14/16] Loss: 0.01931 +Epoch [284/4000] Training [15/16] Loss: 0.01774 +Epoch [284/4000] Training [16/16] Loss: 0.03771 +Epoch [284/4000] Training metric {'Train/mean dice_metric': 0.9852627515792847, 'Train/mean miou_metric': 0.970975399017334, 'Train/mean f1': 0.9828513860702515, 'Train/mean precision': 0.9790202379226685, 'Train/mean recall': 0.986712634563446, 'Train/mean hd95_metric': 2.307739019393921} +Epoch [284/4000] Validation [1/4] Loss: 0.42454 focal_loss 0.26987 dice_loss 0.15467 +Epoch [284/4000] Validation [2/4] Loss: 0.44964 focal_loss 0.20927 dice_loss 0.24037 +Epoch [284/4000] Validation [3/4] Loss: 0.15787 focal_loss 0.08065 dice_loss 0.07722 +Epoch [284/4000] Validation [4/4] Loss: 0.28791 focal_loss 0.16350 dice_loss 0.12441 +Epoch [284/4000] Validation metric {'Val/mean dice_metric': 0.961205005645752, 'Val/mean miou_metric': 0.935347855091095, 'Val/mean f1': 0.9627140760421753, 'Val/mean precision': 0.9636800289154053, 'Val/mean recall': 0.9617498517036438, 'Val/mean hd95_metric': 6.673300266265869} +Cheakpoint... +Epoch [284/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961205005645752, 'Val/mean miou_metric': 0.935347855091095, 'Val/mean f1': 0.9627140760421753, 'Val/mean precision': 0.9636800289154053, 'Val/mean recall': 0.9617498517036438, 'Val/mean hd95_metric': 6.673300266265869} +Epoch [285/4000] Training [1/16] Loss: 0.02393 +Epoch [285/4000] Training [2/16] Loss: 0.02284 +Epoch [285/4000] Training [3/16] Loss: 0.01852 +Epoch [285/4000] Training [4/16] Loss: 0.01884 +Epoch [285/4000] Training [5/16] Loss: 0.02425 +Epoch [285/4000] Training [6/16] Loss: 0.02117 +Epoch [285/4000] Training [7/16] Loss: 0.01609 +Epoch [285/4000] Training [8/16] Loss: 0.02146 +Epoch [285/4000] Training [9/16] Loss: 0.01920 +Epoch [285/4000] Training [10/16] Loss: 0.02375 +Epoch [285/4000] Training [11/16] Loss: 0.02971 +Epoch [285/4000] Training [12/16] Loss: 0.02066 +Epoch [285/4000] Training [13/16] Loss: 0.02079 +Epoch [285/4000] Training [14/16] Loss: 0.02320 +Epoch [285/4000] Training [15/16] Loss: 0.01595 +Epoch [285/4000] Training [16/16] Loss: 0.02259 +Epoch [285/4000] Training metric {'Train/mean dice_metric': 0.9834095239639282, 'Train/mean miou_metric': 0.9681216478347778, 'Train/mean f1': 0.9818235039710999, 'Train/mean precision': 0.9767378568649292, 'Train/mean recall': 0.9869623780250549, 'Train/mean hd95_metric': 3.744014263153076} +Epoch [285/4000] Validation [1/4] Loss: 0.16472 focal_loss 0.09808 dice_loss 0.06664 +Epoch [285/4000] Validation [2/4] Loss: 0.42074 focal_loss 0.17881 dice_loss 0.24193 +Epoch [285/4000] Validation [3/4] Loss: 0.12931 focal_loss 0.06161 dice_loss 0.06771 +Epoch [285/4000] Validation [4/4] Loss: 0.18044 focal_loss 0.07977 dice_loss 0.10067 +Epoch [285/4000] Validation metric {'Val/mean dice_metric': 0.9588519930839539, 'Val/mean miou_metric': 0.9324480295181274, 'Val/mean f1': 0.9624452590942383, 'Val/mean precision': 0.9514169096946716, 'Val/mean recall': 0.9737323522567749, 'Val/mean hd95_metric': 9.29167652130127} +Cheakpoint... +Epoch [285/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9589], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9588519930839539, 'Val/mean miou_metric': 0.9324480295181274, 'Val/mean f1': 0.9624452590942383, 'Val/mean precision': 0.9514169096946716, 'Val/mean recall': 0.9737323522567749, 'Val/mean hd95_metric': 9.29167652130127} +Epoch [286/4000] Training [1/16] Loss: 0.02655 +Epoch [286/4000] Training [2/16] Loss: 0.02159 +Epoch [286/4000] Training [3/16] Loss: 0.02419 +Epoch [286/4000] Training [4/16] Loss: 0.03997 +Epoch [286/4000] Training [5/16] Loss: 0.02109 +Epoch [286/4000] Training [6/16] Loss: 0.01899 +Epoch [286/4000] Training [7/16] Loss: 0.02193 +Epoch [286/4000] Training [8/16] Loss: 0.01970 +Epoch [286/4000] Training [9/16] Loss: 0.01883 +Epoch [286/4000] Training [10/16] Loss: 0.03163 +Epoch [286/4000] Training [11/16] Loss: 0.03111 +Epoch [286/4000] Training [12/16] Loss: 0.02757 +Epoch [286/4000] Training [13/16] Loss: 0.20971 +Epoch [286/4000] Training [14/16] Loss: 0.01987 +Epoch [286/4000] Training [15/16] Loss: 0.02152 +Epoch [286/4000] Training [16/16] Loss: 0.02646 +Epoch [286/4000] Training metric {'Train/mean dice_metric': 0.9804948568344116, 'Train/mean miou_metric': 0.9629297256469727, 'Train/mean f1': 0.9771395921707153, 'Train/mean precision': 0.9745746850967407, 'Train/mean recall': 0.979718029499054, 'Train/mean hd95_metric': 3.640620708465576} +Epoch [286/4000] Validation [1/4] Loss: 0.11214 focal_loss 0.05727 dice_loss 0.05487 +Epoch [286/4000] Validation [2/4] Loss: 0.23651 focal_loss 0.08429 dice_loss 0.15222 +Epoch [286/4000] Validation [3/4] Loss: 0.12181 focal_loss 0.05324 dice_loss 0.06857 +Epoch [286/4000] Validation [4/4] Loss: 0.14142 focal_loss 0.04650 dice_loss 0.09492 +Epoch [286/4000] Validation metric {'Val/mean dice_metric': 0.9585262537002563, 'Val/mean miou_metric': 0.9317730069160461, 'Val/mean f1': 0.9612141251564026, 'Val/mean precision': 0.9564639329910278, 'Val/mean recall': 0.9660115838050842, 'Val/mean hd95_metric': 7.840648651123047} +Cheakpoint... +Epoch [286/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9585], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9585262537002563, 'Val/mean miou_metric': 0.9317730069160461, 'Val/mean f1': 0.9612141251564026, 'Val/mean precision': 0.9564639329910278, 'Val/mean recall': 0.9660115838050842, 'Val/mean hd95_metric': 7.840648651123047} +Epoch [287/4000] Training [1/16] Loss: 0.03159 +Epoch [287/4000] Training [2/16] Loss: 0.02304 +Epoch [287/4000] Training [3/16] Loss: 0.03555 +Epoch [287/4000] Training [4/16] Loss: 0.05555 +Epoch [287/4000] Training [5/16] Loss: 0.02039 +Epoch [287/4000] Training [6/16] Loss: 0.02566 +Epoch [287/4000] Training [7/16] Loss: 0.02535 +Epoch [287/4000] Training [8/16] Loss: 0.02051 +Epoch [287/4000] Training [9/16] Loss: 0.02961 +Epoch [287/4000] Training [10/16] Loss: 0.02113 +Epoch [287/4000] Training [11/16] Loss: 0.02791 +Epoch [287/4000] Training [12/16] Loss: 0.02464 +Epoch [287/4000] Training [13/16] Loss: 0.03014 +Epoch [287/4000] Training [14/16] Loss: 0.02528 +Epoch [287/4000] Training [15/16] Loss: 0.01946 +Epoch [287/4000] Training [16/16] Loss: 0.03005 +Epoch [287/4000] Training metric {'Train/mean dice_metric': 0.979088544845581, 'Train/mean miou_metric': 0.9611022472381592, 'Train/mean f1': 0.9791309237480164, 'Train/mean precision': 0.9734508991241455, 'Train/mean recall': 0.9848775863647461, 'Train/mean hd95_metric': 4.101367473602295} +Epoch [287/4000] Validation [1/4] Loss: 0.55554 focal_loss 0.40310 dice_loss 0.15244 +Epoch [287/4000] Validation [2/4] Loss: 0.39173 focal_loss 0.11485 dice_loss 0.27687 +Epoch [287/4000] Validation [3/4] Loss: 0.11969 focal_loss 0.04746 dice_loss 0.07224 +Epoch [287/4000] Validation [4/4] Loss: 0.29165 focal_loss 0.12753 dice_loss 0.16412 +Epoch [287/4000] Validation metric {'Val/mean dice_metric': 0.9541835784912109, 'Val/mean miou_metric': 0.9254692196846008, 'Val/mean f1': 0.958818256855011, 'Val/mean precision': 0.9561187028884888, 'Val/mean recall': 0.9615331292152405, 'Val/mean hd95_metric': 9.611180305480957} +Cheakpoint... +Epoch [287/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9542], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9541835784912109, 'Val/mean miou_metric': 0.9254692196846008, 'Val/mean f1': 0.958818256855011, 'Val/mean precision': 0.9561187028884888, 'Val/mean recall': 0.9615331292152405, 'Val/mean hd95_metric': 9.611180305480957} +Epoch [288/4000] Training [1/16] Loss: 0.03030 +Epoch [288/4000] Training [2/16] Loss: 0.02111 +Epoch [288/4000] Training [3/16] Loss: 0.03065 +Epoch [288/4000] Training [4/16] Loss: 0.04474 +Epoch [288/4000] Training [5/16] Loss: 0.02033 +Epoch [288/4000] Training [6/16] Loss: 0.01880 +Epoch [288/4000] Training [7/16] Loss: 0.07486 +Epoch [288/4000] Training [8/16] Loss: 0.02209 +Epoch [288/4000] Training [9/16] Loss: 0.02222 +Epoch [288/4000] Training [10/16] Loss: 0.02056 +Epoch [288/4000] Training [11/16] Loss: 0.02800 +Epoch [288/4000] Training [12/16] Loss: 0.02742 +Epoch [288/4000] Training [13/16] Loss: 0.01980 +Epoch [288/4000] Training [14/16] Loss: 0.02204 +Epoch [288/4000] Training [15/16] Loss: 0.01952 +Epoch [288/4000] Training [16/16] Loss: 0.01860 +Epoch [288/4000] Training metric {'Train/mean dice_metric': 0.9816234111785889, 'Train/mean miou_metric': 0.9643489122390747, 'Train/mean f1': 0.9795106649398804, 'Train/mean precision': 0.9747948050498962, 'Train/mean recall': 0.9842723608016968, 'Train/mean hd95_metric': 4.9166059494018555} +Epoch [288/4000] Validation [1/4] Loss: 0.18421 focal_loss 0.09718 dice_loss 0.08703 +Epoch [288/4000] Validation [2/4] Loss: 0.26917 focal_loss 0.10035 dice_loss 0.16882 +Epoch [288/4000] Validation [3/4] Loss: 0.12268 focal_loss 0.05694 dice_loss 0.06574 +Epoch [288/4000] Validation [4/4] Loss: 0.18707 focal_loss 0.07224 dice_loss 0.11483 +Epoch [288/4000] Validation metric {'Val/mean dice_metric': 0.9606329202651978, 'Val/mean miou_metric': 0.9325813055038452, 'Val/mean f1': 0.9622334241867065, 'Val/mean precision': 0.9562437534332275, 'Val/mean recall': 0.9682985544204712, 'Val/mean hd95_metric': 9.428255081176758} +Cheakpoint... +Epoch [288/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9606], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9606329202651978, 'Val/mean miou_metric': 0.9325813055038452, 'Val/mean f1': 0.9622334241867065, 'Val/mean precision': 0.9562437534332275, 'Val/mean recall': 0.9682985544204712, 'Val/mean hd95_metric': 9.428255081176758} +Epoch [289/4000] Training [1/16] Loss: 0.02392 +Epoch [289/4000] Training [2/16] Loss: 0.02783 +Epoch [289/4000] Training [3/16] Loss: 0.02115 +Epoch [289/4000] Training [4/16] Loss: 0.03092 +Epoch [289/4000] Training [5/16] Loss: 0.02642 +Epoch [289/4000] Training [6/16] Loss: 0.03599 +Epoch [289/4000] Training [7/16] Loss: 0.01768 +Epoch [289/4000] Training [8/16] Loss: 0.01935 +Epoch [289/4000] Training [9/16] Loss: 0.02132 +Epoch [289/4000] Training [10/16] Loss: 0.02841 +Epoch [289/4000] Training [11/16] Loss: 0.01919 +Epoch [289/4000] Training [12/16] Loss: 0.01834 +Epoch [289/4000] Training [13/16] Loss: 0.03085 +Epoch [289/4000] Training [14/16] Loss: 0.02330 +Epoch [289/4000] Training [15/16] Loss: 0.01905 +Epoch [289/4000] Training [16/16] Loss: 0.01582 +Epoch [289/4000] Training metric {'Train/mean dice_metric': 0.9828927516937256, 'Train/mean miou_metric': 0.9667917490005493, 'Train/mean f1': 0.9810112118721008, 'Train/mean precision': 0.9766839742660522, 'Train/mean recall': 0.9853770136833191, 'Train/mean hd95_metric': 3.0301008224487305} +Epoch [289/4000] Validation [1/4] Loss: 0.17388 focal_loss 0.09715 dice_loss 0.07674 +Epoch [289/4000] Validation [2/4] Loss: 0.20901 focal_loss 0.07276 dice_loss 0.13624 +Epoch [289/4000] Validation [3/4] Loss: 0.21405 focal_loss 0.10863 dice_loss 0.10542 +Epoch [289/4000] Validation [4/4] Loss: 0.18111 focal_loss 0.06936 dice_loss 0.11175 +Epoch [289/4000] Validation metric {'Val/mean dice_metric': 0.9616689682006836, 'Val/mean miou_metric': 0.9349247217178345, 'Val/mean f1': 0.964945375919342, 'Val/mean precision': 0.9593298435211182, 'Val/mean recall': 0.9706271886825562, 'Val/mean hd95_metric': 8.556901931762695} +Cheakpoint... +Epoch [289/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616689682006836, 'Val/mean miou_metric': 0.9349247217178345, 'Val/mean f1': 0.964945375919342, 'Val/mean precision': 0.9593298435211182, 'Val/mean recall': 0.9706271886825562, 'Val/mean hd95_metric': 8.556901931762695} +Epoch [290/4000] Training [1/16] Loss: 0.01843 +Epoch [290/4000] Training [2/16] Loss: 0.02109 +Epoch [290/4000] Training [3/16] Loss: 0.03369 +Epoch [290/4000] Training [4/16] Loss: 0.04329 +Epoch [290/4000] Training [5/16] Loss: 0.01908 +Epoch [290/4000] Training [6/16] Loss: 0.01713 +Epoch [290/4000] Training [7/16] Loss: 0.06071 +Epoch [290/4000] Training [8/16] Loss: 0.02235 +Epoch [290/4000] Training [9/16] Loss: 0.01571 +Epoch [290/4000] Training [10/16] Loss: 0.01958 +Epoch [290/4000] Training [11/16] Loss: 0.02957 +Epoch [290/4000] Training [12/16] Loss: 0.02332 +Epoch [290/4000] Training [13/16] Loss: 0.02074 +Epoch [290/4000] Training [14/16] Loss: 0.02026 +Epoch [290/4000] Training [15/16] Loss: 0.01765 +Epoch [290/4000] Training [16/16] Loss: 0.01981 +Epoch [290/4000] Training metric {'Train/mean dice_metric': 0.9824875593185425, 'Train/mean miou_metric': 0.9665518403053284, 'Train/mean f1': 0.9812628030776978, 'Train/mean precision': 0.9755657315254211, 'Train/mean recall': 0.9870268702507019, 'Train/mean hd95_metric': 2.771589517593384} +Epoch [290/4000] Validation [1/4] Loss: 0.13414 focal_loss 0.07112 dice_loss 0.06302 +Epoch [290/4000] Validation [2/4] Loss: 0.34213 focal_loss 0.11117 dice_loss 0.23095 +Epoch [290/4000] Validation [3/4] Loss: 0.15115 focal_loss 0.07126 dice_loss 0.07989 +Epoch [290/4000] Validation [4/4] Loss: 0.21681 focal_loss 0.10662 dice_loss 0.11019 +Epoch [290/4000] Validation metric {'Val/mean dice_metric': 0.9587596654891968, 'Val/mean miou_metric': 0.9323728680610657, 'Val/mean f1': 0.9648436903953552, 'Val/mean precision': 0.9597738981246948, 'Val/mean recall': 0.9699673056602478, 'Val/mean hd95_metric': 7.906920433044434} +Cheakpoint... +Epoch [290/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9588], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9587596654891968, 'Val/mean miou_metric': 0.9323728680610657, 'Val/mean f1': 0.9648436903953552, 'Val/mean precision': 0.9597738981246948, 'Val/mean recall': 0.9699673056602478, 'Val/mean hd95_metric': 7.906920433044434} +Epoch [291/4000] Training [1/16] Loss: 0.02944 +Epoch [291/4000] Training [2/16] Loss: 0.02676 +Epoch [291/4000] Training [3/16] Loss: 0.03103 +Epoch [291/4000] Training [4/16] Loss: 0.01887 +Epoch [291/4000] Training [5/16] Loss: 0.02433 +Epoch [291/4000] Training [6/16] Loss: 0.01873 +Epoch [291/4000] Training [7/16] Loss: 0.02144 +Epoch [291/4000] Training [8/16] Loss: 0.02402 +Epoch [291/4000] Training [9/16] Loss: 0.02290 +Epoch [291/4000] Training [10/16] Loss: 0.01887 +Epoch [291/4000] Training [11/16] Loss: 0.02164 +Epoch [291/4000] Training [12/16] Loss: 0.02142 +Epoch [291/4000] Training [13/16] Loss: 0.03284 +Epoch [291/4000] Training [14/16] Loss: 0.02645 +Epoch [291/4000] Training [15/16] Loss: 0.02166 +Epoch [291/4000] Training [16/16] Loss: 0.02231 +Epoch [291/4000] Training metric {'Train/mean dice_metric': 0.9824703931808472, 'Train/mean miou_metric': 0.9658405780792236, 'Train/mean f1': 0.9806052446365356, 'Train/mean precision': 0.9772129654884338, 'Train/mean recall': 0.9840211272239685, 'Train/mean hd95_metric': 3.2881031036376953} +Epoch [291/4000] Validation [1/4] Loss: 0.36936 focal_loss 0.24085 dice_loss 0.12851 +Epoch [291/4000] Validation [2/4] Loss: 0.27736 focal_loss 0.10205 dice_loss 0.17531 +Epoch [291/4000] Validation [3/4] Loss: 0.14567 focal_loss 0.06991 dice_loss 0.07576 +Epoch [291/4000] Validation [4/4] Loss: 0.19787 focal_loss 0.08448 dice_loss 0.11339 +Epoch [291/4000] Validation metric {'Val/mean dice_metric': 0.9576553106307983, 'Val/mean miou_metric': 0.9308765530586243, 'Val/mean f1': 0.9576241970062256, 'Val/mean precision': 0.9516261219978333, 'Val/mean recall': 0.9636984467506409, 'Val/mean hd95_metric': 7.970162868499756} +Cheakpoint... +Epoch [291/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9577], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576553106307983, 'Val/mean miou_metric': 0.9308765530586243, 'Val/mean f1': 0.9576241970062256, 'Val/mean precision': 0.9516261219978333, 'Val/mean recall': 0.9636984467506409, 'Val/mean hd95_metric': 7.970162868499756} +Epoch [292/4000] Training [1/16] Loss: 0.02582 +Epoch [292/4000] Training [2/16] Loss: 0.14791 +Epoch [292/4000] Training [3/16] Loss: 0.02286 +Epoch [292/4000] Training [4/16] Loss: 0.01790 +Epoch [292/4000] Training [5/16] Loss: 0.02007 +Epoch [292/4000] Training [6/16] Loss: 0.01833 +Epoch [292/4000] Training [7/16] Loss: 0.01915 +Epoch [292/4000] Training [8/16] Loss: 0.01723 +Epoch [292/4000] Training [9/16] Loss: 0.02515 +Epoch [292/4000] Training [10/16] Loss: 0.02225 +Epoch [292/4000] Training [11/16] Loss: 0.01628 +Epoch [292/4000] Training [12/16] Loss: 0.02698 +Epoch [292/4000] Training [13/16] Loss: 0.03176 +Epoch [292/4000] Training [14/16] Loss: 0.02154 +Epoch [292/4000] Training [15/16] Loss: 0.03291 +Epoch [292/4000] Training [16/16] Loss: 0.01937 +Epoch [292/4000] Training metric {'Train/mean dice_metric': 0.9813396334648132, 'Train/mean miou_metric': 0.9655264616012573, 'Train/mean f1': 0.9798774719238281, 'Train/mean precision': 0.9747836589813232, 'Train/mean recall': 0.9850248098373413, 'Train/mean hd95_metric': 3.015101432800293} +Epoch [292/4000] Validation [1/4] Loss: 0.11433 focal_loss 0.05546 dice_loss 0.05887 +Epoch [292/4000] Validation [2/4] Loss: 0.42080 focal_loss 0.18339 dice_loss 0.23741 +Epoch [292/4000] Validation [3/4] Loss: 0.11129 focal_loss 0.04618 dice_loss 0.06512 +Epoch [292/4000] Validation [4/4] Loss: 0.16368 focal_loss 0.06891 dice_loss 0.09477 +Epoch [292/4000] Validation metric {'Val/mean dice_metric': 0.9597116708755493, 'Val/mean miou_metric': 0.9340101480484009, 'Val/mean f1': 0.9622620344161987, 'Val/mean precision': 0.9559821486473083, 'Val/mean recall': 0.9686249494552612, 'Val/mean hd95_metric': 7.6267900466918945} +Cheakpoint... +Epoch [292/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9597], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9597116708755493, 'Val/mean miou_metric': 0.9340101480484009, 'Val/mean f1': 0.9622620344161987, 'Val/mean precision': 0.9559821486473083, 'Val/mean recall': 0.9686249494552612, 'Val/mean hd95_metric': 7.6267900466918945} +Epoch [293/4000] Training [1/16] Loss: 0.02927 +Epoch [293/4000] Training [2/16] Loss: 0.01924 +Epoch [293/4000] Training [3/16] Loss: 0.02048 +Epoch [293/4000] Training [4/16] Loss: 0.03152 +Epoch [293/4000] Training [5/16] Loss: 0.02580 +Epoch [293/4000] Training [6/16] Loss: 0.02102 +Epoch [293/4000] Training [7/16] Loss: 0.01870 +Epoch [293/4000] Training [8/16] Loss: 0.02104 +Epoch [293/4000] Training [9/16] Loss: 0.02140 +Epoch [293/4000] Training [10/16] Loss: 0.02258 +Epoch [293/4000] Training [11/16] Loss: 0.03311 +Epoch [293/4000] Training [12/16] Loss: 0.02312 +Epoch [293/4000] Training [13/16] Loss: 0.02404 +Epoch [293/4000] Training [14/16] Loss: 0.02210 +Epoch [293/4000] Training [15/16] Loss: 0.03464 +Epoch [293/4000] Training [16/16] Loss: 0.02414 +Epoch [293/4000] Training metric {'Train/mean dice_metric': 0.9837816953659058, 'Train/mean miou_metric': 0.9682765603065491, 'Train/mean f1': 0.9816322922706604, 'Train/mean precision': 0.9776976704597473, 'Train/mean recall': 0.9855986833572388, 'Train/mean hd95_metric': 2.520747661590576} +Epoch [293/4000] Validation [1/4] Loss: 0.14726 focal_loss 0.08068 dice_loss 0.06658 +Epoch [293/4000] Validation [2/4] Loss: 0.47158 focal_loss 0.21032 dice_loss 0.26125 +Epoch [293/4000] Validation [3/4] Loss: 0.15984 focal_loss 0.07308 dice_loss 0.08676 +Epoch [293/4000] Validation [4/4] Loss: 0.21433 focal_loss 0.08377 dice_loss 0.13056 +Epoch [293/4000] Validation metric {'Val/mean dice_metric': 0.9610466957092285, 'Val/mean miou_metric': 0.9357620477676392, 'Val/mean f1': 0.9645403027534485, 'Val/mean precision': 0.9582207202911377, 'Val/mean recall': 0.9709439277648926, 'Val/mean hd95_metric': 7.677838325500488} +Cheakpoint... +Epoch [293/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9610], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610466957092285, 'Val/mean miou_metric': 0.9357620477676392, 'Val/mean f1': 0.9645403027534485, 'Val/mean precision': 0.9582207202911377, 'Val/mean recall': 0.9709439277648926, 'Val/mean hd95_metric': 7.677838325500488} +Epoch [294/4000] Training [1/16] Loss: 0.02425 +Epoch [294/4000] Training [2/16] Loss: 0.01418 +Epoch [294/4000] Training [3/16] Loss: 0.02105 +Epoch [294/4000] Training [4/16] Loss: 0.05952 +Epoch [294/4000] Training [5/16] Loss: 0.02323 +Epoch [294/4000] Training [6/16] Loss: 0.01733 +Epoch [294/4000] Training [7/16] Loss: 0.01713 +Epoch [294/4000] Training [8/16] Loss: 0.01836 +Epoch [294/4000] Training [9/16] Loss: 0.01729 +Epoch [294/4000] Training [10/16] Loss: 0.01951 +Epoch [294/4000] Training [11/16] Loss: 0.03285 +Epoch [294/4000] Training [12/16] Loss: 0.01795 +Epoch [294/4000] Training [13/16] Loss: 0.01817 +Epoch [294/4000] Training [14/16] Loss: 0.01995 +Epoch [294/4000] Training [15/16] Loss: 0.03005 +Epoch [294/4000] Training [16/16] Loss: 0.01706 +Epoch [294/4000] Training metric {'Train/mean dice_metric': 0.984686017036438, 'Train/mean miou_metric': 0.9701197147369385, 'Train/mean f1': 0.9829584360122681, 'Train/mean precision': 0.978742241859436, 'Train/mean recall': 0.9872111082077026, 'Train/mean hd95_metric': 2.847468614578247} +Epoch [294/4000] Validation [1/4] Loss: 0.18020 focal_loss 0.09603 dice_loss 0.08418 +Epoch [294/4000] Validation [2/4] Loss: 0.67930 focal_loss 0.36466 dice_loss 0.31464 +Epoch [294/4000] Validation [3/4] Loss: 0.12258 focal_loss 0.05079 dice_loss 0.07179 +Epoch [294/4000] Validation [4/4] Loss: 0.21680 focal_loss 0.09450 dice_loss 0.12230 +Epoch [294/4000] Validation metric {'Val/mean dice_metric': 0.959384560585022, 'Val/mean miou_metric': 0.9348104596138, 'Val/mean f1': 0.9651941061019897, 'Val/mean precision': 0.96682208776474, 'Val/mean recall': 0.9635715484619141, 'Val/mean hd95_metric': 7.056402206420898} +Cheakpoint... +Epoch [294/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9594], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959384560585022, 'Val/mean miou_metric': 0.9348104596138, 'Val/mean f1': 0.9651941061019897, 'Val/mean precision': 0.96682208776474, 'Val/mean recall': 0.9635715484619141, 'Val/mean hd95_metric': 7.056402206420898} +Epoch [295/4000] Training [1/16] Loss: 0.01962 +Epoch [295/4000] Training [2/16] Loss: 0.01951 +Epoch [295/4000] Training [3/16] Loss: 0.02329 +Epoch [295/4000] Training [4/16] Loss: 0.01949 +Epoch [295/4000] Training [5/16] Loss: 0.01669 +Epoch [295/4000] Training [6/16] Loss: 0.02071 +Epoch [295/4000] Training [7/16] Loss: 0.02148 +Epoch [295/4000] Training [8/16] Loss: 0.03715 +Epoch [295/4000] Training [9/16] Loss: 0.01321 +Epoch [295/4000] Training [10/16] Loss: 0.01622 +Epoch [295/4000] Training [11/16] Loss: 0.01898 +Epoch [295/4000] Training [12/16] Loss: 0.01804 +Epoch [295/4000] Training [13/16] Loss: 0.02087 +Epoch [295/4000] Training [14/16] Loss: 0.02464 +Epoch [295/4000] Training [15/16] Loss: 0.02811 +Epoch [295/4000] Training [16/16] Loss: 0.01542 +Epoch [295/4000] Training metric {'Train/mean dice_metric': 0.9848805665969849, 'Train/mean miou_metric': 0.970576286315918, 'Train/mean f1': 0.9824991822242737, 'Train/mean precision': 0.9782224297523499, 'Train/mean recall': 0.9868134260177612, 'Train/mean hd95_metric': 2.351252317428589} +Epoch [295/4000] Validation [1/4] Loss: 0.38904 focal_loss 0.26865 dice_loss 0.12040 +Epoch [295/4000] Validation [2/4] Loss: 0.60572 focal_loss 0.27298 dice_loss 0.33274 +Epoch [295/4000] Validation [3/4] Loss: 0.21120 focal_loss 0.10218 dice_loss 0.10902 +Epoch [295/4000] Validation [4/4] Loss: 0.40390 focal_loss 0.18659 dice_loss 0.21731 +Epoch [295/4000] Validation metric {'Val/mean dice_metric': 0.9579242467880249, 'Val/mean miou_metric': 0.9325540661811829, 'Val/mean f1': 0.9608525037765503, 'Val/mean precision': 0.9588191509246826, 'Val/mean recall': 0.9628944993019104, 'Val/mean hd95_metric': 7.666041374206543} +Cheakpoint... +Epoch [295/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9579], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9579242467880249, 'Val/mean miou_metric': 0.9325540661811829, 'Val/mean f1': 0.9608525037765503, 'Val/mean precision': 0.9588191509246826, 'Val/mean recall': 0.9628944993019104, 'Val/mean hd95_metric': 7.666041374206543} +Epoch [296/4000] Training [1/16] Loss: 0.01863 +Epoch [296/4000] Training [2/16] Loss: 0.02258 +Epoch [296/4000] Training [3/16] Loss: 0.02104 +Epoch [296/4000] Training [4/16] Loss: 0.01596 +Epoch [296/4000] Training [5/16] Loss: 0.02237 +Epoch [296/4000] Training [6/16] Loss: 0.01569 +Epoch [296/4000] Training [7/16] Loss: 0.01876 +Epoch [296/4000] Training [8/16] Loss: 0.04551 +Epoch [296/4000] Training [9/16] Loss: 0.01862 +Epoch [296/4000] Training [10/16] Loss: 0.01920 +Epoch [296/4000] Training [11/16] Loss: 0.02591 +Epoch [296/4000] Training [12/16] Loss: 0.01784 +Epoch [296/4000] Training [13/16] Loss: 0.01548 +Epoch [296/4000] Training [14/16] Loss: 0.03749 +Epoch [296/4000] Training [15/16] Loss: 0.02975 +Epoch [296/4000] Training [16/16] Loss: 0.01961 +Epoch [296/4000] Training metric {'Train/mean dice_metric': 0.9842720031738281, 'Train/mean miou_metric': 0.9694068431854248, 'Train/mean f1': 0.9817215800285339, 'Train/mean precision': 0.9769189357757568, 'Train/mean recall': 0.9865716695785522, 'Train/mean hd95_metric': 2.623406410217285} +Epoch [296/4000] Validation [1/4] Loss: 1.02393 focal_loss 0.80157 dice_loss 0.22237 +Epoch [296/4000] Validation [2/4] Loss: 0.43234 focal_loss 0.19471 dice_loss 0.23763 +Epoch [296/4000] Validation [3/4] Loss: 0.21546 focal_loss 0.08728 dice_loss 0.12818 +Epoch [296/4000] Validation [4/4] Loss: 0.32005 focal_loss 0.16173 dice_loss 0.15833 +Epoch [296/4000] Validation metric {'Val/mean dice_metric': 0.9515430331230164, 'Val/mean miou_metric': 0.925892174243927, 'Val/mean f1': 0.9579290151596069, 'Val/mean precision': 0.9672139286994934, 'Val/mean recall': 0.9488205909729004, 'Val/mean hd95_metric': 7.184138298034668} +Cheakpoint... +Epoch [296/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9515], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9515430331230164, 'Val/mean miou_metric': 0.925892174243927, 'Val/mean f1': 0.9579290151596069, 'Val/mean precision': 0.9672139286994934, 'Val/mean recall': 0.9488205909729004, 'Val/mean hd95_metric': 7.184138298034668} +Epoch [297/4000] Training [1/16] Loss: 0.03708 +Epoch [297/4000] Training [2/16] Loss: 0.02094 +Epoch [297/4000] Training [3/16] Loss: 0.02424 +Epoch [297/4000] Training [4/16] Loss: 0.01895 +Epoch [297/4000] Training [5/16] Loss: 0.03305 +Epoch [297/4000] Training [6/16] Loss: 0.01865 +Epoch [297/4000] Training [7/16] Loss: 0.02185 +Epoch [297/4000] Training [8/16] Loss: 0.01755 +Epoch [297/4000] Training [9/16] Loss: 0.02614 +Epoch [297/4000] Training [10/16] Loss: 0.02119 +Epoch [297/4000] Training [11/16] Loss: 0.02394 +Epoch [297/4000] Training [12/16] Loss: 0.04589 +Epoch [297/4000] Training [13/16] Loss: 0.04599 +Epoch [297/4000] Training [14/16] Loss: 0.02615 +Epoch [297/4000] Training [15/16] Loss: 0.02217 +Epoch [297/4000] Training [16/16] Loss: 0.02204 +Epoch [297/4000] Training metric {'Train/mean dice_metric': 0.9792250990867615, 'Train/mean miou_metric': 0.9610300064086914, 'Train/mean f1': 0.9775684475898743, 'Train/mean precision': 0.9733572602272034, 'Train/mean recall': 0.981816291809082, 'Train/mean hd95_metric': 4.44614315032959} +Epoch [297/4000] Validation [1/4] Loss: 0.11753 focal_loss 0.06149 dice_loss 0.05604 +Epoch [297/4000] Validation [2/4] Loss: 0.26905 focal_loss 0.10958 dice_loss 0.15947 +Epoch [297/4000] Validation [3/4] Loss: 0.21244 focal_loss 0.08020 dice_loss 0.13224 +Epoch [297/4000] Validation [4/4] Loss: 0.29412 focal_loss 0.14274 dice_loss 0.15138 +Epoch [297/4000] Validation metric {'Val/mean dice_metric': 0.9523258209228516, 'Val/mean miou_metric': 0.9232471585273743, 'Val/mean f1': 0.9484689831733704, 'Val/mean precision': 0.9311805963516235, 'Val/mean recall': 0.9664114713668823, 'Val/mean hd95_metric': 10.763627052307129} +Cheakpoint... +Epoch [297/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9523], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9523258209228516, 'Val/mean miou_metric': 0.9232471585273743, 'Val/mean f1': 0.9484689831733704, 'Val/mean precision': 0.9311805963516235, 'Val/mean recall': 0.9664114713668823, 'Val/mean hd95_metric': 10.763627052307129} +Epoch [298/4000] Training [1/16] Loss: 0.02590 +Epoch [298/4000] Training [2/16] Loss: 0.02505 +Epoch [298/4000] Training [3/16] Loss: 0.02677 +Epoch [298/4000] Training [4/16] Loss: 0.01828 +Epoch [298/4000] Training [5/16] Loss: 0.02882 +Epoch [298/4000] Training [6/16] Loss: 0.01945 +Epoch [298/4000] Training [7/16] Loss: 0.02206 +Epoch [298/4000] Training [8/16] Loss: 0.02389 +Epoch [298/4000] Training [9/16] Loss: 0.03244 +Epoch [298/4000] Training [10/16] Loss: 0.02166 +Epoch [298/4000] Training [11/16] Loss: 0.02132 +Epoch [298/4000] Training [12/16] Loss: 0.01814 +Epoch [298/4000] Training [13/16] Loss: 0.05039 +Epoch [298/4000] Training [14/16] Loss: 0.02191 +Epoch [298/4000] Training [15/16] Loss: 0.03594 +Epoch [298/4000] Training [16/16] Loss: 0.02703 +Epoch [298/4000] Training metric {'Train/mean dice_metric': 0.9782103300094604, 'Train/mean miou_metric': 0.959534764289856, 'Train/mean f1': 0.9774244427680969, 'Train/mean precision': 0.9752364158630371, 'Train/mean recall': 0.9796223640441895, 'Train/mean hd95_metric': 4.595479965209961} +Epoch [298/4000] Validation [1/4] Loss: 0.14019 focal_loss 0.07297 dice_loss 0.06721 +Epoch [298/4000] Validation [2/4] Loss: 0.32490 focal_loss 0.14290 dice_loss 0.18199 +Epoch [298/4000] Validation [3/4] Loss: 0.23029 focal_loss 0.12235 dice_loss 0.10794 +Epoch [298/4000] Validation [4/4] Loss: 0.33980 focal_loss 0.19418 dice_loss 0.14561 +Epoch [298/4000] Validation metric {'Val/mean dice_metric': 0.9519222974777222, 'Val/mean miou_metric': 0.9225597381591797, 'Val/mean f1': 0.9520571827888489, 'Val/mean precision': 0.9444270133972168, 'Val/mean recall': 0.9598117470741272, 'Val/mean hd95_metric': 10.619237899780273} +Cheakpoint... +Epoch [298/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9519], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9519222974777222, 'Val/mean miou_metric': 0.9225597381591797, 'Val/mean f1': 0.9520571827888489, 'Val/mean precision': 0.9444270133972168, 'Val/mean recall': 0.9598117470741272, 'Val/mean hd95_metric': 10.619237899780273} +Epoch [299/4000] Training [1/16] Loss: 0.03697 +Epoch [299/4000] Training [2/16] Loss: 0.02332 +Epoch [299/4000] Training [3/16] Loss: 0.01992 +Epoch [299/4000] Training [4/16] Loss: 0.02575 +Epoch [299/4000] Training [5/16] Loss: 0.02285 +Epoch [299/4000] Training [6/16] Loss: 0.02668 +Epoch [299/4000] Training [7/16] Loss: 0.02740 +Epoch [299/4000] Training [8/16] Loss: 0.02592 +Epoch [299/4000] Training [9/16] Loss: 0.02195 +Epoch [299/4000] Training [10/16] Loss: 0.01881 +Epoch [299/4000] Training [11/16] Loss: 0.05194 +Epoch [299/4000] Training [12/16] Loss: 0.02372 +Epoch [299/4000] Training [13/16] Loss: 0.02296 +Epoch [299/4000] Training [14/16] Loss: 0.02502 +Epoch [299/4000] Training [15/16] Loss: 0.02428 +Epoch [299/4000] Training [16/16] Loss: 0.01842 +Epoch [299/4000] Training metric {'Train/mean dice_metric': 0.9809656739234924, 'Train/mean miou_metric': 0.9635030627250671, 'Train/mean f1': 0.978805422782898, 'Train/mean precision': 0.9725838899612427, 'Train/mean recall': 0.9851071238517761, 'Train/mean hd95_metric': 5.1931610107421875} +Epoch [299/4000] Validation [1/4] Loss: 0.14595 focal_loss 0.07677 dice_loss 0.06918 +Epoch [299/4000] Validation [2/4] Loss: 0.71932 focal_loss 0.45942 dice_loss 0.25990 +Epoch [299/4000] Validation [3/4] Loss: 0.15771 focal_loss 0.07449 dice_loss 0.08322 +Epoch [299/4000] Validation [4/4] Loss: 0.29798 focal_loss 0.15455 dice_loss 0.14343 +Epoch [299/4000] Validation metric {'Val/mean dice_metric': 0.9561425447463989, 'Val/mean miou_metric': 0.9280301928520203, 'Val/mean f1': 0.9579461812973022, 'Val/mean precision': 0.9552916884422302, 'Val/mean recall': 0.9606154561042786, 'Val/mean hd95_metric': 9.485015869140625} +Cheakpoint... +Epoch [299/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9561], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9561425447463989, 'Val/mean miou_metric': 0.9280301928520203, 'Val/mean f1': 0.9579461812973022, 'Val/mean precision': 0.9552916884422302, 'Val/mean recall': 0.9606154561042786, 'Val/mean hd95_metric': 9.485015869140625} +Epoch [300/4000] Training [1/16] Loss: 0.01748 +Epoch [300/4000] Training [2/16] Loss: 0.02192 +Epoch [300/4000] Training [3/16] Loss: 0.09249 +Epoch [300/4000] Training [4/16] Loss: 0.01911 +Epoch [300/4000] Training [5/16] Loss: 0.02245 +Epoch [300/4000] Training [6/16] Loss: 0.02751 +Epoch [300/4000] Training [7/16] Loss: 0.03359 +Epoch [300/4000] Training [8/16] Loss: 0.01786 +Epoch [300/4000] Training [9/16] Loss: 0.04065 +Epoch [300/4000] Training [10/16] Loss: 0.03490 +Epoch [300/4000] Training [11/16] Loss: 0.02118 +Epoch [300/4000] Training [12/16] Loss: 0.02828 +Epoch [300/4000] Training [13/16] Loss: 0.02167 +Epoch [300/4000] Training [14/16] Loss: 0.03628 +Epoch [300/4000] Training [15/16] Loss: 0.02854 +Epoch [300/4000] Training [16/16] Loss: 0.03998 +Epoch [300/4000] Training metric {'Train/mean dice_metric': 0.9781199097633362, 'Train/mean miou_metric': 0.9594480395317078, 'Train/mean f1': 0.9783344864845276, 'Train/mean precision': 0.9739851355552673, 'Train/mean recall': 0.9827229380607605, 'Train/mean hd95_metric': 4.248064994812012} +Epoch [300/4000] Validation [1/4] Loss: 0.52466 focal_loss 0.37062 dice_loss 0.15404 +Epoch [300/4000] Validation [2/4] Loss: 0.48797 focal_loss 0.26076 dice_loss 0.22720 +Epoch [300/4000] Validation [3/4] Loss: 0.17689 focal_loss 0.07870 dice_loss 0.09820 +Epoch [300/4000] Validation [4/4] Loss: 0.30188 focal_loss 0.13971 dice_loss 0.16217 +Epoch [300/4000] Validation metric {'Val/mean dice_metric': 0.9527098536491394, 'Val/mean miou_metric': 0.9229491353034973, 'Val/mean f1': 0.9541950225830078, 'Val/mean precision': 0.952938973903656, 'Val/mean recall': 0.9554542899131775, 'Val/mean hd95_metric': 9.058755874633789} +Cheakpoint... +Epoch [300/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9527], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9527098536491394, 'Val/mean miou_metric': 0.9229491353034973, 'Val/mean f1': 0.9541950225830078, 'Val/mean precision': 0.952938973903656, 'Val/mean recall': 0.9554542899131775, 'Val/mean hd95_metric': 9.058755874633789} +Epoch [301/4000] Training [1/16] Loss: 0.01840 +Epoch [301/4000] Training [2/16] Loss: 0.02377 +Epoch [301/4000] Training [3/16] Loss: 0.07262 +Epoch [301/4000] Training [4/16] Loss: 0.02726 +Epoch [301/4000] Training [5/16] Loss: 0.02863 +Epoch [301/4000] Training [6/16] Loss: 0.02556 +Epoch [301/4000] Training [7/16] Loss: 0.01866 +Epoch [301/4000] Training [8/16] Loss: 0.01983 +Epoch [301/4000] Training [9/16] Loss: 0.01779 +Epoch [301/4000] Training [10/16] Loss: 0.03364 +Epoch [301/4000] Training [11/16] Loss: 0.02649 +Epoch [301/4000] Training [12/16] Loss: 0.02519 +Epoch [301/4000] Training [13/16] Loss: 0.03140 +Epoch [301/4000] Training [14/16] Loss: 0.02138 +Epoch [301/4000] Training [15/16] Loss: 0.02351 +Epoch [301/4000] Training [16/16] Loss: 0.02551 +Epoch [301/4000] Training metric {'Train/mean dice_metric': 0.9782916307449341, 'Train/mean miou_metric': 0.9593195915222168, 'Train/mean f1': 0.9783638715744019, 'Train/mean precision': 0.9730792045593262, 'Train/mean recall': 0.9837062358856201, 'Train/mean hd95_metric': 3.5533618927001953} +Epoch [301/4000] Validation [1/4] Loss: 0.13792 focal_loss 0.06799 dice_loss 0.06993 +Epoch [301/4000] Validation [2/4] Loss: 0.41655 focal_loss 0.19183 dice_loss 0.22471 +Epoch [301/4000] Validation [3/4] Loss: 0.30930 focal_loss 0.16377 dice_loss 0.14553 +Epoch [301/4000] Validation [4/4] Loss: 0.27192 focal_loss 0.12163 dice_loss 0.15029 +Epoch [301/4000] Validation metric {'Val/mean dice_metric': 0.9544433355331421, 'Val/mean miou_metric': 0.9248363375663757, 'Val/mean f1': 0.9583100080490112, 'Val/mean precision': 0.9480671286582947, 'Val/mean recall': 0.9687765836715698, 'Val/mean hd95_metric': 8.933996200561523} +Cheakpoint... +Epoch [301/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9544], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9544433355331421, 'Val/mean miou_metric': 0.9248363375663757, 'Val/mean f1': 0.9583100080490112, 'Val/mean precision': 0.9480671286582947, 'Val/mean recall': 0.9687765836715698, 'Val/mean hd95_metric': 8.933996200561523} +Epoch [302/4000] Training [1/16] Loss: 0.01810 +Epoch [302/4000] Training [2/16] Loss: 0.02284 +Epoch [302/4000] Training [3/16] Loss: 0.02265 +Epoch [302/4000] Training [4/16] Loss: 0.02094 +Epoch [302/4000] Training [5/16] Loss: 0.07876 +Epoch [302/4000] Training [6/16] Loss: 0.01922 +Epoch [302/4000] Training [7/16] Loss: 0.07563 +Epoch [302/4000] Training [8/16] Loss: 0.02247 +Epoch [302/4000] Training [9/16] Loss: 0.01976 +Epoch [302/4000] Training [10/16] Loss: 0.01928 +Epoch [302/4000] Training [11/16] Loss: 0.01673 +Epoch [302/4000] Training [12/16] Loss: 0.03394 +Epoch [302/4000] Training [13/16] Loss: 0.02531 +Epoch [302/4000] Training [14/16] Loss: 0.03195 +Epoch [302/4000] Training [15/16] Loss: 0.02283 +Epoch [302/4000] Training [16/16] Loss: 0.02087 +Epoch [302/4000] Training metric {'Train/mean dice_metric': 0.9815033674240112, 'Train/mean miou_metric': 0.9641828536987305, 'Train/mean f1': 0.9784987568855286, 'Train/mean precision': 0.973527193069458, 'Train/mean recall': 0.9835214018821716, 'Train/mean hd95_metric': 3.3626646995544434} +Epoch [302/4000] Validation [1/4] Loss: 0.11865 focal_loss 0.05629 dice_loss 0.06236 +Epoch [302/4000] Validation [2/4] Loss: 0.25701 focal_loss 0.09220 dice_loss 0.16481 +Epoch [302/4000] Validation [3/4] Loss: 0.19747 focal_loss 0.09146 dice_loss 0.10601 +Epoch [302/4000] Validation [4/4] Loss: 0.22554 focal_loss 0.10036 dice_loss 0.12518 +Epoch [302/4000] Validation metric {'Val/mean dice_metric': 0.9584857225418091, 'Val/mean miou_metric': 0.9309295415878296, 'Val/mean f1': 0.9617080092430115, 'Val/mean precision': 0.9573795199394226, 'Val/mean recall': 0.9660757184028625, 'Val/mean hd95_metric': 7.557795524597168} +Cheakpoint... +Epoch [302/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9585], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9584857225418091, 'Val/mean miou_metric': 0.9309295415878296, 'Val/mean f1': 0.9617080092430115, 'Val/mean precision': 0.9573795199394226, 'Val/mean recall': 0.9660757184028625, 'Val/mean hd95_metric': 7.557795524597168} +Epoch [303/4000] Training [1/16] Loss: 0.02212 +Epoch [303/4000] Training [2/16] Loss: 0.02318 +Epoch [303/4000] Training [3/16] Loss: 0.04279 +Epoch [303/4000] Training [4/16] Loss: 0.01991 +Epoch [303/4000] Training [5/16] Loss: 0.01691 +Epoch [303/4000] Training [6/16] Loss: 0.01825 +Epoch [303/4000] Training [7/16] Loss: 0.02464 +Epoch [303/4000] Training [8/16] Loss: 0.02165 +Epoch [303/4000] Training [9/16] Loss: 0.02713 +Epoch [303/4000] Training [10/16] Loss: 0.02001 +Epoch [303/4000] Training [11/16] Loss: 0.02180 +Epoch [303/4000] Training [12/16] Loss: 0.02242 +Epoch [303/4000] Training [13/16] Loss: 0.02548 +Epoch [303/4000] Training [14/16] Loss: 0.02517 +Epoch [303/4000] Training [15/16] Loss: 0.01768 +Epoch [303/4000] Training [16/16] Loss: 0.03447 +Epoch [303/4000] Training metric {'Train/mean dice_metric': 0.9824029207229614, 'Train/mean miou_metric': 0.9662571549415588, 'Train/mean f1': 0.978095531463623, 'Train/mean precision': 0.9765058755874634, 'Train/mean recall': 0.9796903729438782, 'Train/mean hd95_metric': 2.5079855918884277} +Epoch [303/4000] Validation [1/4] Loss: 0.13186 focal_loss 0.07116 dice_loss 0.06069 +Epoch [303/4000] Validation [2/4] Loss: 0.42309 focal_loss 0.22179 dice_loss 0.20130 +Epoch [303/4000] Validation [3/4] Loss: 0.12202 focal_loss 0.05003 dice_loss 0.07199 +Epoch [303/4000] Validation [4/4] Loss: 0.23140 focal_loss 0.10332 dice_loss 0.12808 +Epoch [303/4000] Validation metric {'Val/mean dice_metric': 0.9589422345161438, 'Val/mean miou_metric': 0.9326785802841187, 'Val/mean f1': 0.9601736068725586, 'Val/mean precision': 0.9577491283416748, 'Val/mean recall': 0.9626104235649109, 'Val/mean hd95_metric': 6.971151828765869} +Cheakpoint... +Epoch [303/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9589], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9589422345161438, 'Val/mean miou_metric': 0.9326785802841187, 'Val/mean f1': 0.9601736068725586, 'Val/mean precision': 0.9577491283416748, 'Val/mean recall': 0.9626104235649109, 'Val/mean hd95_metric': 6.971151828765869} +Epoch [304/4000] Training [1/16] Loss: 0.02512 +Epoch [304/4000] Training [2/16] Loss: 0.01870 +Epoch [304/4000] Training [3/16] Loss: 0.03686 +Epoch [304/4000] Training [4/16] Loss: 0.01778 +Epoch [304/4000] Training [5/16] Loss: 0.01527 +Epoch [304/4000] Training [6/16] Loss: 0.01901 +Epoch [304/4000] Training [7/16] Loss: 0.01809 +Epoch [304/4000] Training [8/16] Loss: 0.02063 +Epoch [304/4000] Training [9/16] Loss: 0.02093 +Epoch [304/4000] Training [10/16] Loss: 0.04847 +Epoch [304/4000] Training [11/16] Loss: 0.02270 +Epoch [304/4000] Training [12/16] Loss: 0.02411 +Epoch [304/4000] Training [13/16] Loss: 0.02390 +Epoch [304/4000] Training [14/16] Loss: 0.03065 +Epoch [304/4000] Training [15/16] Loss: 0.02018 +Epoch [304/4000] Training [16/16] Loss: 0.02144 +Epoch [304/4000] Training metric {'Train/mean dice_metric': 0.9823029637336731, 'Train/mean miou_metric': 0.965862512588501, 'Train/mean f1': 0.9799428582191467, 'Train/mean precision': 0.9751235842704773, 'Train/mean recall': 0.984809935092926, 'Train/mean hd95_metric': 3.4210543632507324} +Epoch [304/4000] Validation [1/4] Loss: 0.14507 focal_loss 0.07212 dice_loss 0.07296 +Epoch [304/4000] Validation [2/4] Loss: 0.25160 focal_loss 0.08966 dice_loss 0.16194 +Epoch [304/4000] Validation [3/4] Loss: 0.22485 focal_loss 0.13025 dice_loss 0.09461 +Epoch [304/4000] Validation [4/4] Loss: 0.36785 focal_loss 0.21386 dice_loss 0.15399 +Epoch [304/4000] Validation metric {'Val/mean dice_metric': 0.9566610455513, 'Val/mean miou_metric': 0.9284747838973999, 'Val/mean f1': 0.958772599697113, 'Val/mean precision': 0.9611997008323669, 'Val/mean recall': 0.9563577175140381, 'Val/mean hd95_metric': 7.8753252029418945} +Cheakpoint... +Epoch [304/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9567], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9566610455513, 'Val/mean miou_metric': 0.9284747838973999, 'Val/mean f1': 0.958772599697113, 'Val/mean precision': 0.9611997008323669, 'Val/mean recall': 0.9563577175140381, 'Val/mean hd95_metric': 7.8753252029418945} +Epoch [305/4000] Training [1/16] Loss: 0.03231 +Epoch [305/4000] Training [2/16] Loss: 0.02105 +Epoch [305/4000] Training [3/16] Loss: 0.02244 +Epoch [305/4000] Training [4/16] Loss: 0.02009 +Epoch [305/4000] Training [5/16] Loss: 0.02067 +Epoch [305/4000] Training [6/16] Loss: 0.03312 +Epoch [305/4000] Training [7/16] Loss: 0.02228 +Epoch [305/4000] Training [8/16] Loss: 0.02394 +Epoch [305/4000] Training [9/16] Loss: 0.02373 +Epoch [305/4000] Training [10/16] Loss: 0.02070 +Epoch [305/4000] Training [11/16] Loss: 0.02241 +Epoch [305/4000] Training [12/16] Loss: 0.03126 +Epoch [305/4000] Training [13/16] Loss: 0.02392 +Epoch [305/4000] Training [14/16] Loss: 0.01897 +Epoch [305/4000] Training [15/16] Loss: 0.02571 +Epoch [305/4000] Training [16/16] Loss: 0.07084 +Epoch [305/4000] Training metric {'Train/mean dice_metric': 0.9777387380599976, 'Train/mean miou_metric': 0.9598663449287415, 'Train/mean f1': 0.9736840128898621, 'Train/mean precision': 0.969303548336029, 'Train/mean recall': 0.978104293346405, 'Train/mean hd95_metric': 4.350889205932617} +Epoch [305/4000] Validation [1/4] Loss: 0.15088 focal_loss 0.08621 dice_loss 0.06466 +Epoch [305/4000] Validation [2/4] Loss: 0.34919 focal_loss 0.11146 dice_loss 0.23774 +Epoch [305/4000] Validation [3/4] Loss: 0.16010 focal_loss 0.07690 dice_loss 0.08320 +Epoch [305/4000] Validation [4/4] Loss: 0.25418 focal_loss 0.12592 dice_loss 0.12826 +Epoch [305/4000] Validation metric {'Val/mean dice_metric': 0.9543026089668274, 'Val/mean miou_metric': 0.9255280494689941, 'Val/mean f1': 0.9548991918563843, 'Val/mean precision': 0.9484876990318298, 'Val/mean recall': 0.9613980054855347, 'Val/mean hd95_metric': 10.92657470703125} +Cheakpoint... +Epoch [305/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9543], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9543026089668274, 'Val/mean miou_metric': 0.9255280494689941, 'Val/mean f1': 0.9548991918563843, 'Val/mean precision': 0.9484876990318298, 'Val/mean recall': 0.9613980054855347, 'Val/mean hd95_metric': 10.92657470703125} +Epoch [306/4000] Training [1/16] Loss: 0.01691 +Epoch [306/4000] Training [2/16] Loss: 0.02732 +Epoch [306/4000] Training [3/16] Loss: 0.02102 +Epoch [306/4000] Training [4/16] Loss: 0.01643 +Epoch [306/4000] Training [5/16] Loss: 0.03008 +Epoch [306/4000] Training [6/16] Loss: 0.02300 +Epoch [306/4000] Training [7/16] Loss: 0.02808 +Epoch [306/4000] Training [8/16] Loss: 0.02486 +Epoch [306/4000] Training [9/16] Loss: 0.02722 +Epoch [306/4000] Training [10/16] Loss: 0.02646 +Epoch [306/4000] Training [11/16] Loss: 0.02999 +Epoch [306/4000] Training [12/16] Loss: 0.02304 +Epoch [306/4000] Training [13/16] Loss: 0.02059 +Epoch [306/4000] Training [14/16] Loss: 0.02522 +Epoch [306/4000] Training [15/16] Loss: 0.02332 +Epoch [306/4000] Training [16/16] Loss: 0.02114 +Epoch [306/4000] Training metric {'Train/mean dice_metric': 0.9834007024765015, 'Train/mean miou_metric': 0.9673730134963989, 'Train/mean f1': 0.9811559319496155, 'Train/mean precision': 0.9762859344482422, 'Train/mean recall': 0.9860747456550598, 'Train/mean hd95_metric': 3.8557164669036865} +Epoch [306/4000] Validation [1/4] Loss: 0.30600 focal_loss 0.17396 dice_loss 0.13204 +Epoch [306/4000] Validation [2/4] Loss: 0.25596 focal_loss 0.08242 dice_loss 0.17353 +Epoch [306/4000] Validation [3/4] Loss: 0.18969 focal_loss 0.07953 dice_loss 0.11016 +Epoch [306/4000] Validation [4/4] Loss: 0.32023 focal_loss 0.16485 dice_loss 0.15538 +Epoch [306/4000] Validation metric {'Val/mean dice_metric': 0.9587581753730774, 'Val/mean miou_metric': 0.930921196937561, 'Val/mean f1': 0.9604399800300598, 'Val/mean precision': 0.95683753490448, 'Val/mean recall': 0.9640696048736572, 'Val/mean hd95_metric': 9.237306594848633} +Cheakpoint... +Epoch [306/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9588], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9587581753730774, 'Val/mean miou_metric': 0.930921196937561, 'Val/mean f1': 0.9604399800300598, 'Val/mean precision': 0.95683753490448, 'Val/mean recall': 0.9640696048736572, 'Val/mean hd95_metric': 9.237306594848633} +Epoch [307/4000] Training [1/16] Loss: 0.03179 +Epoch [307/4000] Training [2/16] Loss: 0.02450 +Epoch [307/4000] Training [3/16] Loss: 0.01969 +Epoch [307/4000] Training [4/16] Loss: 0.02370 +Epoch [307/4000] Training [5/16] Loss: 0.01752 +Epoch [307/4000] Training [6/16] Loss: 0.02665 +Epoch [307/4000] Training [7/16] Loss: 0.04111 +Epoch [307/4000] Training [8/16] Loss: 0.02149 +Epoch [307/4000] Training [9/16] Loss: 0.02058 +Epoch [307/4000] Training [10/16] Loss: 0.02163 +Epoch [307/4000] Training [11/16] Loss: 0.02010 +Epoch [307/4000] Training [12/16] Loss: 0.01745 +Epoch [307/4000] Training [13/16] Loss: 0.01856 +Epoch [307/4000] Training [14/16] Loss: 0.02080 +Epoch [307/4000] Training [15/16] Loss: 0.02869 +Epoch [307/4000] Training [16/16] Loss: 0.02537 +Epoch [307/4000] Training metric {'Train/mean dice_metric': 0.9843465685844421, 'Train/mean miou_metric': 0.9691365957260132, 'Train/mean f1': 0.9809455275535583, 'Train/mean precision': 0.9771906137466431, 'Train/mean recall': 0.9847294688224792, 'Train/mean hd95_metric': 2.6513185501098633} +Epoch [307/4000] Validation [1/4] Loss: 0.13935 focal_loss 0.08062 dice_loss 0.05874 +Epoch [307/4000] Validation [2/4] Loss: 0.20210 focal_loss 0.06903 dice_loss 0.13307 +Epoch [307/4000] Validation [3/4] Loss: 0.12100 focal_loss 0.05688 dice_loss 0.06412 +Epoch [307/4000] Validation [4/4] Loss: 0.21951 focal_loss 0.11203 dice_loss 0.10748 +Epoch [307/4000] Validation metric {'Val/mean dice_metric': 0.9629022479057312, 'Val/mean miou_metric': 0.9372360110282898, 'Val/mean f1': 0.9651510119438171, 'Val/mean precision': 0.9605981707572937, 'Val/mean recall': 0.9697473645210266, 'Val/mean hd95_metric': 7.714159965515137} +Cheakpoint... +Epoch [307/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9629], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629022479057312, 'Val/mean miou_metric': 0.9372360110282898, 'Val/mean f1': 0.9651510119438171, 'Val/mean precision': 0.9605981707572937, 'Val/mean recall': 0.9697473645210266, 'Val/mean hd95_metric': 7.714159965515137} +Epoch [308/4000] Training [1/16] Loss: 0.02283 +Epoch [308/4000] Training [2/16] Loss: 0.01889 +Epoch [308/4000] Training [3/16] Loss: 0.01638 +Epoch [308/4000] Training [4/16] Loss: 0.02356 +Epoch [308/4000] Training [5/16] Loss: 0.01899 +Epoch [308/4000] Training [6/16] Loss: 0.01417 +Epoch [308/4000] Training [7/16] Loss: 0.01789 +Epoch [308/4000] Training [8/16] Loss: 0.02269 +Epoch [308/4000] Training [9/16] Loss: 0.01845 +Epoch [308/4000] Training [10/16] Loss: 0.01535 +Epoch [308/4000] Training [11/16] Loss: 0.01688 +Epoch [308/4000] Training [12/16] Loss: 0.01754 +Epoch [308/4000] Training [13/16] Loss: 0.01983 +Epoch [308/4000] Training [14/16] Loss: 0.01682 +Epoch [308/4000] Training [15/16] Loss: 0.01769 +Epoch [308/4000] Training [16/16] Loss: 0.01898 +Epoch [308/4000] Training metric {'Train/mean dice_metric': 0.9867756366729736, 'Train/mean miou_metric': 0.9737571477890015, 'Train/mean f1': 0.9835800528526306, 'Train/mean precision': 0.9789578318595886, 'Train/mean recall': 0.9882461428642273, 'Train/mean hd95_metric': 2.162899971008301} +Epoch [308/4000] Validation [1/4] Loss: 0.61236 focal_loss 0.45664 dice_loss 0.15572 +Epoch [308/4000] Validation [2/4] Loss: 0.33768 focal_loss 0.13639 dice_loss 0.20128 +Epoch [308/4000] Validation [3/4] Loss: 0.18167 focal_loss 0.10179 dice_loss 0.07988 +Epoch [308/4000] Validation [4/4] Loss: 0.31899 focal_loss 0.15490 dice_loss 0.16408 +Epoch [308/4000] Validation metric {'Val/mean dice_metric': 0.9617906808853149, 'Val/mean miou_metric': 0.9369970560073853, 'Val/mean f1': 0.9628588557243347, 'Val/mean precision': 0.9645217657089233, 'Val/mean recall': 0.9612017869949341, 'Val/mean hd95_metric': 7.580172538757324} +Cheakpoint... +Epoch [308/4000] best acc:tensor([0.9658], device='cuda:0'), Now : mean acc: tensor([0.9618], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9617906808853149, 'Val/mean miou_metric': 0.9369970560073853, 'Val/mean f1': 0.9628588557243347, 'Val/mean precision': 0.9645217657089233, 'Val/mean recall': 0.9612017869949341, 'Val/mean hd95_metric': 7.580172538757324} +Epoch [309/4000] Training [1/16] Loss: 0.01783 +Epoch [309/4000] Training [2/16] Loss: 0.01723 +Epoch [309/4000] Training [3/16] Loss: 0.02217 +Epoch [309/4000] Training [4/16] Loss: 0.01835 +Epoch [309/4000] Training [5/16] Loss: 0.01846 +Epoch [309/4000] Training [6/16] Loss: 0.01725 +Epoch [309/4000] Training [7/16] Loss: 0.01799 +Epoch [309/4000] Training [8/16] Loss: 0.02056 +Epoch [309/4000] Training [9/16] Loss: 0.01758 +Epoch [309/4000] Training [10/16] Loss: 0.02016 +Epoch [309/4000] Training [11/16] Loss: 0.01668 +Epoch [309/4000] Training [12/16] Loss: 0.01895 +Epoch [309/4000] Training [13/16] Loss: 0.01641 +Epoch [309/4000] Training [14/16] Loss: 0.01545 +Epoch [309/4000] Training [15/16] Loss: 0.02274 +Epoch [309/4000] Training [16/16] Loss: 0.01820 +Epoch [309/4000] Training metric {'Train/mean dice_metric': 0.9872784614562988, 'Train/mean miou_metric': 0.974725604057312, 'Train/mean f1': 0.98451167345047, 'Train/mean precision': 0.9799904823303223, 'Train/mean recall': 0.98907470703125, 'Train/mean hd95_metric': 1.6714107990264893} +Epoch [309/4000] Validation [1/4] Loss: 0.11521 focal_loss 0.05884 dice_loss 0.05637 +Epoch [309/4000] Validation [2/4] Loss: 0.28824 focal_loss 0.11072 dice_loss 0.17752 +Epoch [309/4000] Validation [3/4] Loss: 0.15339 focal_loss 0.07023 dice_loss 0.08316 +Epoch [309/4000] Validation [4/4] Loss: 0.23045 focal_loss 0.12237 dice_loss 0.10808 +Epoch [309/4000] Validation metric {'Val/mean dice_metric': 0.9664093852043152, 'Val/mean miou_metric': 0.9427284002304077, 'Val/mean f1': 0.9682034850120544, 'Val/mean precision': 0.9662596583366394, 'Val/mean recall': 0.9701553583145142, 'Val/mean hd95_metric': 6.067215919494629} +Cheakpoint... +Epoch [309/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664093852043152, 'Val/mean miou_metric': 0.9427284002304077, 'Val/mean f1': 0.9682034850120544, 'Val/mean precision': 0.9662596583366394, 'Val/mean recall': 0.9701553583145142, 'Val/mean hd95_metric': 6.067215919494629} +Epoch [310/4000] Training [1/16] Loss: 0.01971 +Epoch [310/4000] Training [2/16] Loss: 0.01642 +Epoch [310/4000] Training [3/16] Loss: 0.01635 +Epoch [310/4000] Training [4/16] Loss: 0.01910 +Epoch [310/4000] Training [5/16] Loss: 0.01661 +Epoch [310/4000] Training [6/16] Loss: 0.01949 +Epoch [310/4000] Training [7/16] Loss: 0.01600 +Epoch [310/4000] Training [8/16] Loss: 0.01688 +Epoch [310/4000] Training [9/16] Loss: 0.02221 +Epoch [310/4000] Training [10/16] Loss: 0.01744 +Epoch [310/4000] Training [11/16] Loss: 0.01578 +Epoch [310/4000] Training [12/16] Loss: 0.02139 +Epoch [310/4000] Training [13/16] Loss: 0.02129 +Epoch [310/4000] Training [14/16] Loss: 0.02482 +Epoch [310/4000] Training [15/16] Loss: 0.01467 +Epoch [310/4000] Training [16/16] Loss: 0.01908 +Epoch [310/4000] Training metric {'Train/mean dice_metric': 0.9868733286857605, 'Train/mean miou_metric': 0.9739498496055603, 'Train/mean f1': 0.983920693397522, 'Train/mean precision': 0.9794935584068298, 'Train/mean recall': 0.988388180732727, 'Train/mean hd95_metric': 1.8101260662078857} +Epoch [310/4000] Validation [1/4] Loss: 0.18515 focal_loss 0.09574 dice_loss 0.08941 +Epoch [310/4000] Validation [2/4] Loss: 0.33621 focal_loss 0.11288 dice_loss 0.22333 +Epoch [310/4000] Validation [3/4] Loss: 0.12027 focal_loss 0.05712 dice_loss 0.06315 +Epoch [310/4000] Validation [4/4] Loss: 0.32236 focal_loss 0.18798 dice_loss 0.13438 +Epoch [310/4000] Validation metric {'Val/mean dice_metric': 0.9599353075027466, 'Val/mean miou_metric': 0.9351005554199219, 'Val/mean f1': 0.9618160724639893, 'Val/mean precision': 0.9653521776199341, 'Val/mean recall': 0.9583056569099426, 'Val/mean hd95_metric': 6.605915069580078} +Cheakpoint... +Epoch [310/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599353075027466, 'Val/mean miou_metric': 0.9351005554199219, 'Val/mean f1': 0.9618160724639893, 'Val/mean precision': 0.9653521776199341, 'Val/mean recall': 0.9583056569099426, 'Val/mean hd95_metric': 6.605915069580078} +Epoch [311/4000] Training [1/16] Loss: 0.01515 +Epoch [311/4000] Training [2/16] Loss: 0.02831 +Epoch [311/4000] Training [3/16] Loss: 0.01945 +Epoch [311/4000] Training [4/16] Loss: 0.02690 +Epoch [311/4000] Training [5/16] Loss: 0.01381 +Epoch [311/4000] Training [6/16] Loss: 0.01866 +Epoch [311/4000] Training [7/16] Loss: 0.02195 +Epoch [311/4000] Training [8/16] Loss: 0.01935 +Epoch [311/4000] Training [9/16] Loss: 0.01488 +Epoch [311/4000] Training [10/16] Loss: 0.01329 +Epoch [311/4000] Training [11/16] Loss: 0.01961 +Epoch [311/4000] Training [12/16] Loss: 0.01693 +Epoch [311/4000] Training [13/16] Loss: 0.02111 +Epoch [311/4000] Training [14/16] Loss: 0.02819 +Epoch [311/4000] Training [15/16] Loss: 0.02035 +Epoch [311/4000] Training [16/16] Loss: 0.01992 +Epoch [311/4000] Training metric {'Train/mean dice_metric': 0.9864411354064941, 'Train/mean miou_metric': 0.9731559157371521, 'Train/mean f1': 0.9841644763946533, 'Train/mean precision': 0.9795503616333008, 'Train/mean recall': 0.9888222813606262, 'Train/mean hd95_metric': 1.9364070892333984} +Epoch [311/4000] Validation [1/4] Loss: 0.12337 focal_loss 0.07197 dice_loss 0.05139 +Epoch [311/4000] Validation [2/4] Loss: 0.23690 focal_loss 0.08949 dice_loss 0.14742 +Epoch [311/4000] Validation [3/4] Loss: 0.14026 focal_loss 0.05819 dice_loss 0.08207 +Epoch [311/4000] Validation [4/4] Loss: 0.26235 focal_loss 0.13721 dice_loss 0.12514 +Epoch [311/4000] Validation metric {'Val/mean dice_metric': 0.9655122756958008, 'Val/mean miou_metric': 0.9421688318252563, 'Val/mean f1': 0.9689101576805115, 'Val/mean precision': 0.9660911560058594, 'Val/mean recall': 0.9717455506324768, 'Val/mean hd95_metric': 5.863633632659912} +Cheakpoint... +Epoch [311/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655122756958008, 'Val/mean miou_metric': 0.9421688318252563, 'Val/mean f1': 0.9689101576805115, 'Val/mean precision': 0.9660911560058594, 'Val/mean recall': 0.9717455506324768, 'Val/mean hd95_metric': 5.863633632659912} +Epoch [312/4000] Training [1/16] Loss: 0.01653 +Epoch [312/4000] Training [2/16] Loss: 0.01744 +Epoch [312/4000] Training [3/16] Loss: 0.01844 +Epoch [312/4000] Training [4/16] Loss: 0.02689 +Epoch [312/4000] Training [5/16] Loss: 0.02025 +Epoch [312/4000] Training [6/16] Loss: 0.02824 +Epoch [312/4000] Training [7/16] Loss: 0.01591 +Epoch [312/4000] Training [8/16] Loss: 0.02240 +Epoch [312/4000] Training [9/16] Loss: 0.01355 +Epoch [312/4000] Training [10/16] Loss: 0.02189 +Epoch [312/4000] Training [11/16] Loss: 0.01386 +Epoch [312/4000] Training [12/16] Loss: 0.01856 +Epoch [312/4000] Training [13/16] Loss: 0.01742 +Epoch [312/4000] Training [14/16] Loss: 0.03031 +Epoch [312/4000] Training [15/16] Loss: 0.02065 +Epoch [312/4000] Training [16/16] Loss: 0.02134 +Epoch [312/4000] Training metric {'Train/mean dice_metric': 0.9860892295837402, 'Train/mean miou_metric': 0.9724918603897095, 'Train/mean f1': 0.9839601516723633, 'Train/mean precision': 0.9795371890068054, 'Train/mean recall': 0.9884231686592102, 'Train/mean hd95_metric': 2.174595832824707} +Epoch [312/4000] Validation [1/4] Loss: 0.11571 focal_loss 0.06259 dice_loss 0.05312 +Epoch [312/4000] Validation [2/4] Loss: 0.29532 focal_loss 0.12170 dice_loss 0.17363 +Epoch [312/4000] Validation [3/4] Loss: 0.11893 focal_loss 0.05731 dice_loss 0.06162 +Epoch [312/4000] Validation [4/4] Loss: 0.22743 focal_loss 0.10544 dice_loss 0.12200 +Epoch [312/4000] Validation metric {'Val/mean dice_metric': 0.9640700221061707, 'Val/mean miou_metric': 0.9400666952133179, 'Val/mean f1': 0.9680773019790649, 'Val/mean precision': 0.962165117263794, 'Val/mean recall': 0.974062442779541, 'Val/mean hd95_metric': 6.575725555419922} +Cheakpoint... +Epoch [312/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640700221061707, 'Val/mean miou_metric': 0.9400666952133179, 'Val/mean f1': 0.9680773019790649, 'Val/mean precision': 0.962165117263794, 'Val/mean recall': 0.974062442779541, 'Val/mean hd95_metric': 6.575725555419922} +Epoch [313/4000] Training [1/16] Loss: 0.07426 +Epoch [313/4000] Training [2/16] Loss: 0.01579 +Epoch [313/4000] Training [3/16] Loss: 0.02508 +Epoch [313/4000] Training [4/16] Loss: 0.01708 +Epoch [313/4000] Training [5/16] Loss: 0.01978 +Epoch [313/4000] Training [6/16] Loss: 0.02040 +Epoch [313/4000] Training [7/16] Loss: 0.02255 +Epoch [313/4000] Training [8/16] Loss: 0.01616 +Epoch [313/4000] Training [9/16] Loss: 0.01669 +Epoch [313/4000] Training [10/16] Loss: 0.02521 +Epoch [313/4000] Training [11/16] Loss: 0.03162 +Epoch [313/4000] Training [12/16] Loss: 0.01681 +Epoch [313/4000] Training [13/16] Loss: 0.01999 +Epoch [313/4000] Training [14/16] Loss: 0.02153 +Epoch [313/4000] Training [15/16] Loss: 0.01976 +Epoch [313/4000] Training [16/16] Loss: 0.02332 +Epoch [313/4000] Training metric {'Train/mean dice_metric': 0.9847025275230408, 'Train/mean miou_metric': 0.9702410101890564, 'Train/mean f1': 0.9828086495399475, 'Train/mean precision': 0.9778770208358765, 'Train/mean recall': 0.9877902865409851, 'Train/mean hd95_metric': 2.6590347290039062} +Epoch [313/4000] Validation [1/4] Loss: 0.18808 focal_loss 0.09971 dice_loss 0.08837 +Epoch [313/4000] Validation [2/4] Loss: 0.22355 focal_loss 0.07095 dice_loss 0.15260 +Epoch [313/4000] Validation [3/4] Loss: 0.14029 focal_loss 0.06133 dice_loss 0.07895 +Epoch [313/4000] Validation [4/4] Loss: 0.28802 focal_loss 0.15389 dice_loss 0.13413 +Epoch [313/4000] Validation metric {'Val/mean dice_metric': 0.9621607065200806, 'Val/mean miou_metric': 0.9368613362312317, 'Val/mean f1': 0.9662528038024902, 'Val/mean precision': 0.965366780757904, 'Val/mean recall': 0.9671406149864197, 'Val/mean hd95_metric': 7.13485050201416} +Cheakpoint... +Epoch [313/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9621607065200806, 'Val/mean miou_metric': 0.9368613362312317, 'Val/mean f1': 0.9662528038024902, 'Val/mean precision': 0.965366780757904, 'Val/mean recall': 0.9671406149864197, 'Val/mean hd95_metric': 7.13485050201416} +Epoch [314/4000] Training [1/16] Loss: 0.01911 +Epoch [314/4000] Training [2/16] Loss: 0.02052 +Epoch [314/4000] Training [3/16] Loss: 0.01723 +Epoch [314/4000] Training [4/16] Loss: 0.02538 +Epoch [314/4000] Training [5/16] Loss: 0.01905 +Epoch [314/4000] Training [6/16] Loss: 0.03681 +Epoch [314/4000] Training [7/16] Loss: 0.02372 +Epoch [314/4000] Training [8/16] Loss: 0.02116 +Epoch [314/4000] Training [9/16] Loss: 0.01941 +Epoch [314/4000] Training [10/16] Loss: 0.01665 +Epoch [314/4000] Training [11/16] Loss: 0.02017 +Epoch [314/4000] Training [12/16] Loss: 0.02160 +Epoch [314/4000] Training [13/16] Loss: 0.01642 +Epoch [314/4000] Training [14/16] Loss: 0.01969 +Epoch [314/4000] Training [15/16] Loss: 0.01906 +Epoch [314/4000] Training [16/16] Loss: 0.02507 +Epoch [314/4000] Training metric {'Train/mean dice_metric': 0.9850083589553833, 'Train/mean miou_metric': 0.970553994178772, 'Train/mean f1': 0.983544111251831, 'Train/mean precision': 0.9788920879364014, 'Train/mean recall': 0.9882405996322632, 'Train/mean hd95_metric': 2.0926170349121094} +Epoch [314/4000] Validation [1/4] Loss: 0.11035 focal_loss 0.05458 dice_loss 0.05577 +Epoch [314/4000] Validation [2/4] Loss: 0.16478 focal_loss 0.05408 dice_loss 0.11070 +Epoch [314/4000] Validation [3/4] Loss: 0.11257 focal_loss 0.05082 dice_loss 0.06175 +Epoch [314/4000] Validation [4/4] Loss: 0.27137 focal_loss 0.12917 dice_loss 0.14220 +Epoch [314/4000] Validation metric {'Val/mean dice_metric': 0.9641059637069702, 'Val/mean miou_metric': 0.9397805333137512, 'Val/mean f1': 0.9683230519294739, 'Val/mean precision': 0.9653984904289246, 'Val/mean recall': 0.9712654948234558, 'Val/mean hd95_metric': 5.921013832092285} +Cheakpoint... +Epoch [314/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9641059637069702, 'Val/mean miou_metric': 0.9397805333137512, 'Val/mean f1': 0.9683230519294739, 'Val/mean precision': 0.9653984904289246, 'Val/mean recall': 0.9712654948234558, 'Val/mean hd95_metric': 5.921013832092285} +Epoch [315/4000] Training [1/16] Loss: 0.01829 +Epoch [315/4000] Training [2/16] Loss: 0.01928 +Epoch [315/4000] Training [3/16] Loss: 0.01389 +Epoch [315/4000] Training [4/16] Loss: 0.01712 +Epoch [315/4000] Training [5/16] Loss: 0.02464 +Epoch [315/4000] Training [6/16] Loss: 0.02814 +Epoch [315/4000] Training [7/16] Loss: 0.02248 +Epoch [315/4000] Training [8/16] Loss: 0.01410 +Epoch [315/4000] Training [9/16] Loss: 0.01933 +Epoch [315/4000] Training [10/16] Loss: 0.01697 +Epoch [315/4000] Training [11/16] Loss: 0.01891 +Epoch [315/4000] Training [12/16] Loss: 0.01589 +Epoch [315/4000] Training [13/16] Loss: 0.02078 +Epoch [315/4000] Training [14/16] Loss: 0.01502 +Epoch [315/4000] Training [15/16] Loss: 0.01992 +Epoch [315/4000] Training [16/16] Loss: 0.01794 +Epoch [315/4000] Training metric {'Train/mean dice_metric': 0.986491322517395, 'Train/mean miou_metric': 0.9732463955879211, 'Train/mean f1': 0.9841206669807434, 'Train/mean precision': 0.9798069596290588, 'Train/mean recall': 0.9884724617004395, 'Train/mean hd95_metric': 2.085467576980591} +Epoch [315/4000] Validation [1/4] Loss: 0.11908 focal_loss 0.06282 dice_loss 0.05627 +Epoch [315/4000] Validation [2/4] Loss: 0.22473 focal_loss 0.08113 dice_loss 0.14361 +Epoch [315/4000] Validation [3/4] Loss: 0.13285 focal_loss 0.06538 dice_loss 0.06747 +Epoch [315/4000] Validation [4/4] Loss: 0.25553 focal_loss 0.12836 dice_loss 0.12717 +Epoch [315/4000] Validation metric {'Val/mean dice_metric': 0.9632726907730103, 'Val/mean miou_metric': 0.9392706155776978, 'Val/mean f1': 0.9669923782348633, 'Val/mean precision': 0.9619964361190796, 'Val/mean recall': 0.9720404744148254, 'Val/mean hd95_metric': 6.970310211181641} +Cheakpoint... +Epoch [315/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632726907730103, 'Val/mean miou_metric': 0.9392706155776978, 'Val/mean f1': 0.9669923782348633, 'Val/mean precision': 0.9619964361190796, 'Val/mean recall': 0.9720404744148254, 'Val/mean hd95_metric': 6.970310211181641} +Epoch [316/4000] Training [1/16] Loss: 0.02554 +Epoch [316/4000] Training [2/16] Loss: 0.02028 +Epoch [316/4000] Training [3/16] Loss: 0.02735 +Epoch [316/4000] Training [4/16] Loss: 0.01703 +Epoch [316/4000] Training [5/16] Loss: 0.01365 +Epoch [316/4000] Training [6/16] Loss: 0.02380 +Epoch [316/4000] Training [7/16] Loss: 0.02286 +Epoch [316/4000] Training [8/16] Loss: 0.02048 +Epoch [316/4000] Training [9/16] Loss: 0.02752 +Epoch [316/4000] Training [10/16] Loss: 0.02308 +Epoch [316/4000] Training [11/16] Loss: 0.01950 +Epoch [316/4000] Training [12/16] Loss: 0.01930 +Epoch [316/4000] Training [13/16] Loss: 0.02232 +Epoch [316/4000] Training [14/16] Loss: 0.02836 +Epoch [316/4000] Training [15/16] Loss: 0.01841 +Epoch [316/4000] Training [16/16] Loss: 0.01823 +Epoch [316/4000] Training metric {'Train/mean dice_metric': 0.9852608442306519, 'Train/mean miou_metric': 0.9709380865097046, 'Train/mean f1': 0.983265221118927, 'Train/mean precision': 0.9788777828216553, 'Train/mean recall': 0.98769211769104, 'Train/mean hd95_metric': 2.388782501220703} +Epoch [316/4000] Validation [1/4] Loss: 0.11539 focal_loss 0.06279 dice_loss 0.05260 +Epoch [316/4000] Validation [2/4] Loss: 0.25209 focal_loss 0.10212 dice_loss 0.14997 +Epoch [316/4000] Validation [3/4] Loss: 0.12297 focal_loss 0.06263 dice_loss 0.06034 +Epoch [316/4000] Validation [4/4] Loss: 0.28875 focal_loss 0.14347 dice_loss 0.14528 +Epoch [316/4000] Validation metric {'Val/mean dice_metric': 0.9654262661933899, 'Val/mean miou_metric': 0.9407742619514465, 'Val/mean f1': 0.9684877395629883, 'Val/mean precision': 0.9611750841140747, 'Val/mean recall': 0.9759125113487244, 'Val/mean hd95_metric': 6.491725921630859} +Cheakpoint... +Epoch [316/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654262661933899, 'Val/mean miou_metric': 0.9407742619514465, 'Val/mean f1': 0.9684877395629883, 'Val/mean precision': 0.9611750841140747, 'Val/mean recall': 0.9759125113487244, 'Val/mean hd95_metric': 6.491725921630859} +Epoch [317/4000] Training [1/16] Loss: 0.01710 +Epoch [317/4000] Training [2/16] Loss: 0.01567 +Epoch [317/4000] Training [3/16] Loss: 0.03009 +Epoch [317/4000] Training [4/16] Loss: 0.01840 +Epoch [317/4000] Training [5/16] Loss: 0.02009 +Epoch [317/4000] Training [6/16] Loss: 0.02391 +Epoch [317/4000] Training [7/16] Loss: 0.01721 +Epoch [317/4000] Training [8/16] Loss: 0.01857 +Epoch [317/4000] Training [9/16] Loss: 0.01990 +Epoch [317/4000] Training [10/16] Loss: 0.03216 +Epoch [317/4000] Training [11/16] Loss: 0.02131 +Epoch [317/4000] Training [12/16] Loss: 0.01710 +Epoch [317/4000] Training [13/16] Loss: 0.01531 +Epoch [317/4000] Training [14/16] Loss: 0.02225 +Epoch [317/4000] Training [15/16] Loss: 0.01761 +Epoch [317/4000] Training [16/16] Loss: 0.01515 +Epoch [317/4000] Training metric {'Train/mean dice_metric': 0.9854167103767395, 'Train/mean miou_metric': 0.9712915420532227, 'Train/mean f1': 0.9834533333778381, 'Train/mean precision': 0.9785287380218506, 'Train/mean recall': 0.9884277582168579, 'Train/mean hd95_metric': 1.9088828563690186} +Epoch [317/4000] Validation [1/4] Loss: 0.16007 focal_loss 0.09147 dice_loss 0.06860 +Epoch [317/4000] Validation [2/4] Loss: 0.48972 focal_loss 0.23604 dice_loss 0.25368 +Epoch [317/4000] Validation [3/4] Loss: 0.13828 focal_loss 0.06747 dice_loss 0.07081 +Epoch [317/4000] Validation [4/4] Loss: 0.16617 focal_loss 0.07596 dice_loss 0.09021 +Epoch [317/4000] Validation metric {'Val/mean dice_metric': 0.9634149670600891, 'Val/mean miou_metric': 0.9384428262710571, 'Val/mean f1': 0.9660515189170837, 'Val/mean precision': 0.962043821811676, 'Val/mean recall': 0.9700927734375, 'Val/mean hd95_metric': 6.612793922424316} +Cheakpoint... +Epoch [317/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9634149670600891, 'Val/mean miou_metric': 0.9384428262710571, 'Val/mean f1': 0.9660515189170837, 'Val/mean precision': 0.962043821811676, 'Val/mean recall': 0.9700927734375, 'Val/mean hd95_metric': 6.612793922424316} +Epoch [318/4000] Training [1/16] Loss: 0.03442 +Epoch [318/4000] Training [2/16] Loss: 0.01766 +Epoch [318/4000] Training [3/16] Loss: 0.01667 +Epoch [318/4000] Training [4/16] Loss: 0.01973 +Epoch [318/4000] Training [5/16] Loss: 0.01929 +Epoch [318/4000] Training [6/16] Loss: 0.02261 +Epoch [318/4000] Training [7/16] Loss: 0.01966 +Epoch [318/4000] Training [8/16] Loss: 0.01705 +Epoch [318/4000] Training [9/16] Loss: 0.01758 +Epoch [318/4000] Training [10/16] Loss: 0.01874 +Epoch [318/4000] Training [11/16] Loss: 0.02261 +Epoch [318/4000] Training [12/16] Loss: 0.02497 +Epoch [318/4000] Training [13/16] Loss: 0.02237 +Epoch [318/4000] Training [14/16] Loss: 0.01333 +Epoch [318/4000] Training [15/16] Loss: 0.02157 +Epoch [318/4000] Training [16/16] Loss: 0.01591 +Epoch [318/4000] Training metric {'Train/mean dice_metric': 0.9860076904296875, 'Train/mean miou_metric': 0.9723390340805054, 'Train/mean f1': 0.9841434359550476, 'Train/mean precision': 0.9798214435577393, 'Train/mean recall': 0.9885037541389465, 'Train/mean hd95_metric': 1.968104600906372} +Epoch [318/4000] Validation [1/4] Loss: 0.13268 focal_loss 0.07554 dice_loss 0.05713 +Epoch [318/4000] Validation [2/4] Loss: 0.38134 focal_loss 0.16759 dice_loss 0.21375 +Epoch [318/4000] Validation [3/4] Loss: 0.10693 focal_loss 0.05205 dice_loss 0.05488 +Epoch [318/4000] Validation [4/4] Loss: 0.22124 focal_loss 0.09753 dice_loss 0.12371 +Epoch [318/4000] Validation metric {'Val/mean dice_metric': 0.9650079607963562, 'Val/mean miou_metric': 0.940619945526123, 'Val/mean f1': 0.9683104157447815, 'Val/mean precision': 0.9622223377227783, 'Val/mean recall': 0.9744759202003479, 'Val/mean hd95_metric': 6.76462459564209} +Cheakpoint... +Epoch [318/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650079607963562, 'Val/mean miou_metric': 0.940619945526123, 'Val/mean f1': 0.9683104157447815, 'Val/mean precision': 0.9622223377227783, 'Val/mean recall': 0.9744759202003479, 'Val/mean hd95_metric': 6.76462459564209} +Epoch [319/4000] Training [1/16] Loss: 0.01873 +Epoch [319/4000] Training [2/16] Loss: 0.02098 +Epoch [319/4000] Training [3/16] Loss: 0.03310 +Epoch [319/4000] Training [4/16] Loss: 0.01597 +Epoch [319/4000] Training [5/16] Loss: 0.01397 +Epoch [319/4000] Training [6/16] Loss: 0.03211 +Epoch [319/4000] Training [7/16] Loss: 0.01814 +Epoch [319/4000] Training [8/16] Loss: 0.01574 +Epoch [319/4000] Training [9/16] Loss: 0.01895 +Epoch [319/4000] Training [10/16] Loss: 0.01778 +Epoch [319/4000] Training [11/16] Loss: 0.01467 +Epoch [319/4000] Training [12/16] Loss: 0.03296 +Epoch [319/4000] Training [13/16] Loss: 0.01911 +Epoch [319/4000] Training [14/16] Loss: 0.01283 +Epoch [319/4000] Training [15/16] Loss: 0.04553 +Epoch [319/4000] Training [16/16] Loss: 0.01674 +Epoch [319/4000] Training metric {'Train/mean dice_metric': 0.9866471290588379, 'Train/mean miou_metric': 0.9736403226852417, 'Train/mean f1': 0.9840449094772339, 'Train/mean precision': 0.9798267483711243, 'Train/mean recall': 0.9882994890213013, 'Train/mean hd95_metric': 1.8702423572540283} +Epoch [319/4000] Validation [1/4] Loss: 0.15374 focal_loss 0.09038 dice_loss 0.06336 +Epoch [319/4000] Validation [2/4] Loss: 0.20649 focal_loss 0.07331 dice_loss 0.13318 +Epoch [319/4000] Validation [3/4] Loss: 0.10724 focal_loss 0.05156 dice_loss 0.05568 +Epoch [319/4000] Validation [4/4] Loss: 0.28585 focal_loss 0.14499 dice_loss 0.14086 +Epoch [319/4000] Validation metric {'Val/mean dice_metric': 0.9646772146224976, 'Val/mean miou_metric': 0.9412997961044312, 'Val/mean f1': 0.9685492515563965, 'Val/mean precision': 0.9624051451683044, 'Val/mean recall': 0.9747722744941711, 'Val/mean hd95_metric': 6.309586524963379} +Cheakpoint... +Epoch [319/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646772146224976, 'Val/mean miou_metric': 0.9412997961044312, 'Val/mean f1': 0.9685492515563965, 'Val/mean precision': 0.9624051451683044, 'Val/mean recall': 0.9747722744941711, 'Val/mean hd95_metric': 6.309586524963379} +Epoch [320/4000] Training [1/16] Loss: 0.02337 +Epoch [320/4000] Training [2/16] Loss: 0.02090 +Epoch [320/4000] Training [3/16] Loss: 0.02076 +Epoch [320/4000] Training [4/16] Loss: 0.01761 +Epoch [320/4000] Training [5/16] Loss: 0.01902 +Epoch [320/4000] Training [6/16] Loss: 0.01538 +Epoch [320/4000] Training [7/16] Loss: 0.02015 +Epoch [320/4000] Training [8/16] Loss: 0.01711 +Epoch [320/4000] Training [9/16] Loss: 0.01847 +Epoch [320/4000] Training [10/16] Loss: 0.02114 +Epoch [320/4000] Training [11/16] Loss: 0.01975 +Epoch [320/4000] Training [12/16] Loss: 0.02776 +Epoch [320/4000] Training [13/16] Loss: 0.02233 +Epoch [320/4000] Training [14/16] Loss: 0.02222 +Epoch [320/4000] Training [15/16] Loss: 0.02216 +Epoch [320/4000] Training [16/16] Loss: 0.02163 +Epoch [320/4000] Training metric {'Train/mean dice_metric': 0.984927237033844, 'Train/mean miou_metric': 0.9704416990280151, 'Train/mean f1': 0.9820672273635864, 'Train/mean precision': 0.9773090481758118, 'Train/mean recall': 0.9868719577789307, 'Train/mean hd95_metric': 2.530132293701172} +Epoch [320/4000] Validation [1/4] Loss: 0.22383 focal_loss 0.13060 dice_loss 0.09323 +Epoch [320/4000] Validation [2/4] Loss: 0.36508 focal_loss 0.15502 dice_loss 0.21006 +Epoch [320/4000] Validation [3/4] Loss: 0.15955 focal_loss 0.08513 dice_loss 0.07442 +Epoch [320/4000] Validation [4/4] Loss: 0.46309 focal_loss 0.27209 dice_loss 0.19100 +Epoch [320/4000] Validation metric {'Val/mean dice_metric': 0.9621655344963074, 'Val/mean miou_metric': 0.9355699419975281, 'Val/mean f1': 0.9642969369888306, 'Val/mean precision': 0.9639104604721069, 'Val/mean recall': 0.9646836519241333, 'Val/mean hd95_metric': 7.2429399490356445} +Cheakpoint... +Epoch [320/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9621655344963074, 'Val/mean miou_metric': 0.9355699419975281, 'Val/mean f1': 0.9642969369888306, 'Val/mean precision': 0.9639104604721069, 'Val/mean recall': 0.9646836519241333, 'Val/mean hd95_metric': 7.2429399490356445} +Epoch [321/4000] Training [1/16] Loss: 0.02204 +Epoch [321/4000] Training [2/16] Loss: 0.02445 +Epoch [321/4000] Training [3/16] Loss: 0.01553 +Epoch [321/4000] Training [4/16] Loss: 0.02864 +Epoch [321/4000] Training [5/16] Loss: 0.02163 +Epoch [321/4000] Training [6/16] Loss: 0.02082 +Epoch [321/4000] Training [7/16] Loss: 0.02392 +Epoch [321/4000] Training [8/16] Loss: 0.02484 +Epoch [321/4000] Training [9/16] Loss: 0.02114 +Epoch [321/4000] Training [10/16] Loss: 0.02391 +Epoch [321/4000] Training [11/16] Loss: 0.02026 +Epoch [321/4000] Training [12/16] Loss: 0.02147 +Epoch [321/4000] Training [13/16] Loss: 0.01800 +Epoch [321/4000] Training [14/16] Loss: 0.01511 +Epoch [321/4000] Training [15/16] Loss: 0.01629 +Epoch [321/4000] Training [16/16] Loss: 0.02374 +Epoch [321/4000] Training metric {'Train/mean dice_metric': 0.985507607460022, 'Train/mean miou_metric': 0.9714315533638, 'Train/mean f1': 0.9832590818405151, 'Train/mean precision': 0.9790404438972473, 'Train/mean recall': 0.9875142574310303, 'Train/mean hd95_metric': 1.989446759223938} +Epoch [321/4000] Validation [1/4] Loss: 0.12891 focal_loss 0.06663 dice_loss 0.06229 +Epoch [321/4000] Validation [2/4] Loss: 0.19092 focal_loss 0.06514 dice_loss 0.12578 +Epoch [321/4000] Validation [3/4] Loss: 0.17010 focal_loss 0.07263 dice_loss 0.09747 +Epoch [321/4000] Validation [4/4] Loss: 0.22725 focal_loss 0.10198 dice_loss 0.12527 +Epoch [321/4000] Validation metric {'Val/mean dice_metric': 0.9641107320785522, 'Val/mean miou_metric': 0.938667893409729, 'Val/mean f1': 0.9660829305648804, 'Val/mean precision': 0.9569418430328369, 'Val/mean recall': 0.9754003882408142, 'Val/mean hd95_metric': 7.917547702789307} +Cheakpoint... +Epoch [321/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9641107320785522, 'Val/mean miou_metric': 0.938667893409729, 'Val/mean f1': 0.9660829305648804, 'Val/mean precision': 0.9569418430328369, 'Val/mean recall': 0.9754003882408142, 'Val/mean hd95_metric': 7.917547702789307} +Epoch [322/4000] Training [1/16] Loss: 0.01991 +Epoch [322/4000] Training [2/16] Loss: 0.01447 +Epoch [322/4000] Training [3/16] Loss: 0.02833 +Epoch [322/4000] Training [4/16] Loss: 0.01498 +Epoch [322/4000] Training [5/16] Loss: 0.01686 +Epoch [322/4000] Training [6/16] Loss: 0.01748 +Epoch [322/4000] Training [7/16] Loss: 0.01609 +Epoch [322/4000] Training [8/16] Loss: 0.01751 +Epoch [322/4000] Training [9/16] Loss: 0.02127 +Epoch [322/4000] Training [10/16] Loss: 0.02640 +Epoch [322/4000] Training [11/16] Loss: 0.01606 +Epoch [322/4000] Training [12/16] Loss: 0.01355 +Epoch [322/4000] Training [13/16] Loss: 0.01543 +Epoch [322/4000] Training [14/16] Loss: 0.04776 +Epoch [322/4000] Training [15/16] Loss: 0.03016 +Epoch [322/4000] Training [16/16] Loss: 0.01707 +Epoch [322/4000] Training metric {'Train/mean dice_metric': 0.9860880374908447, 'Train/mean miou_metric': 0.973194420337677, 'Train/mean f1': 0.9823563098907471, 'Train/mean precision': 0.9799533486366272, 'Train/mean recall': 0.9847710132598877, 'Train/mean hd95_metric': 2.296510696411133} +Epoch [322/4000] Validation [1/4] Loss: 0.13992 focal_loss 0.08118 dice_loss 0.05874 +Epoch [322/4000] Validation [2/4] Loss: 0.40440 focal_loss 0.20193 dice_loss 0.20247 +Epoch [322/4000] Validation [3/4] Loss: 0.12510 focal_loss 0.05795 dice_loss 0.06715 +Epoch [322/4000] Validation [4/4] Loss: 0.29113 focal_loss 0.15281 dice_loss 0.13832 +Epoch [322/4000] Validation metric {'Val/mean dice_metric': 0.9636791944503784, 'Val/mean miou_metric': 0.9402726292610168, 'Val/mean f1': 0.9662302136421204, 'Val/mean precision': 0.9599504470825195, 'Val/mean recall': 0.972592830657959, 'Val/mean hd95_metric': 7.321785926818848} +Cheakpoint... +Epoch [322/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636791944503784, 'Val/mean miou_metric': 0.9402726292610168, 'Val/mean f1': 0.9662302136421204, 'Val/mean precision': 0.9599504470825195, 'Val/mean recall': 0.972592830657959, 'Val/mean hd95_metric': 7.321785926818848} +Epoch [323/4000] Training [1/16] Loss: 0.01625 +Epoch [323/4000] Training [2/16] Loss: 0.02871 +Epoch [323/4000] Training [3/16] Loss: 0.01725 +Epoch [323/4000] Training [4/16] Loss: 0.18429 +Epoch [323/4000] Training [5/16] Loss: 0.04030 +Epoch [323/4000] Training [6/16] Loss: 0.03842 +Epoch [323/4000] Training [7/16] Loss: 0.01616 +Epoch [323/4000] Training [8/16] Loss: 0.02043 +Epoch [323/4000] Training [9/16] Loss: 0.03342 +Epoch [323/4000] Training [10/16] Loss: 0.02459 +Epoch [323/4000] Training [11/16] Loss: 0.01409 +Epoch [323/4000] Training [12/16] Loss: 0.02182 +Epoch [323/4000] Training [13/16] Loss: 0.01764 +Epoch [323/4000] Training [14/16] Loss: 0.01990 +Epoch [323/4000] Training [15/16] Loss: 0.02486 +Epoch [323/4000] Training [16/16] Loss: 0.02046 +Epoch [323/4000] Training metric {'Train/mean dice_metric': 0.9839193224906921, 'Train/mean miou_metric': 0.9687699675559998, 'Train/mean f1': 0.981656014919281, 'Train/mean precision': 0.9764499068260193, 'Train/mean recall': 0.9869179725646973, 'Train/mean hd95_metric': 4.424299240112305} +Epoch [323/4000] Validation [1/4] Loss: 0.15759 focal_loss 0.07134 dice_loss 0.08625 +Epoch [323/4000] Validation [2/4] Loss: 0.23620 focal_loss 0.05551 dice_loss 0.18069 +Epoch [323/4000] Validation [3/4] Loss: 0.14865 focal_loss 0.06341 dice_loss 0.08524 +Epoch [323/4000] Validation [4/4] Loss: 0.32093 focal_loss 0.16155 dice_loss 0.15938 +Epoch [323/4000] Validation metric {'Val/mean dice_metric': 0.9566823840141296, 'Val/mean miou_metric': 0.9296051263809204, 'Val/mean f1': 0.9588414430618286, 'Val/mean precision': 0.9547566771507263, 'Val/mean recall': 0.9629612565040588, 'Val/mean hd95_metric': 9.735737800598145} +Cheakpoint... +Epoch [323/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9567], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9566823840141296, 'Val/mean miou_metric': 0.9296051263809204, 'Val/mean f1': 0.9588414430618286, 'Val/mean precision': 0.9547566771507263, 'Val/mean recall': 0.9629612565040588, 'Val/mean hd95_metric': 9.735737800598145} +Epoch [324/4000] Training [1/16] Loss: 0.01635 +Epoch [324/4000] Training [2/16] Loss: 0.02363 +Epoch [324/4000] Training [3/16] Loss: 0.03804 +Epoch [324/4000] Training [4/16] Loss: 0.02009 +Epoch [324/4000] Training [5/16] Loss: 0.01977 +Epoch [324/4000] Training [6/16] Loss: 0.02382 +Epoch [324/4000] Training [7/16] Loss: 0.03167 +Epoch [324/4000] Training [8/16] Loss: 0.02702 +Epoch [324/4000] Training [9/16] Loss: 0.01670 +Epoch [324/4000] Training [10/16] Loss: 0.02038 +Epoch [324/4000] Training [11/16] Loss: 0.02083 +Epoch [324/4000] Training [12/16] Loss: 0.02256 +Epoch [324/4000] Training [13/16] Loss: 0.01659 +Epoch [324/4000] Training [14/16] Loss: 0.01794 +Epoch [324/4000] Training [15/16] Loss: 0.01811 +Epoch [324/4000] Training [16/16] Loss: 0.01808 +Epoch [324/4000] Training metric {'Train/mean dice_metric': 0.9827626347541809, 'Train/mean miou_metric': 0.9675962924957275, 'Train/mean f1': 0.9804648756980896, 'Train/mean precision': 0.9747995734214783, 'Train/mean recall': 0.9861964583396912, 'Train/mean hd95_metric': 3.1342663764953613} +Epoch [324/4000] Validation [1/4] Loss: 0.57140 focal_loss 0.38064 dice_loss 0.19076 +Epoch [324/4000] Validation [2/4] Loss: 0.41717 focal_loss 0.18792 dice_loss 0.22924 +Epoch [324/4000] Validation [3/4] Loss: 0.13749 focal_loss 0.06269 dice_loss 0.07480 +Epoch [324/4000] Validation [4/4] Loss: 0.27118 focal_loss 0.14284 dice_loss 0.12833 +Epoch [324/4000] Validation metric {'Val/mean dice_metric': 0.9575274586677551, 'Val/mean miou_metric': 0.9305194616317749, 'Val/mean f1': 0.9598267674446106, 'Val/mean precision': 0.9572246074676514, 'Val/mean recall': 0.9624431729316711, 'Val/mean hd95_metric': 8.461457252502441} +Cheakpoint... +Epoch [324/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9575], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9575274586677551, 'Val/mean miou_metric': 0.9305194616317749, 'Val/mean f1': 0.9598267674446106, 'Val/mean precision': 0.9572246074676514, 'Val/mean recall': 0.9624431729316711, 'Val/mean hd95_metric': 8.461457252502441} +Epoch [325/4000] Training [1/16] Loss: 0.05683 +Epoch [325/4000] Training [2/16] Loss: 0.02171 +Epoch [325/4000] Training [3/16] Loss: 0.01625 +Epoch [325/4000] Training [4/16] Loss: 0.01678 +Epoch [325/4000] Training [5/16] Loss: 0.04070 +Epoch [325/4000] Training [6/16] Loss: 0.02048 +Epoch [325/4000] Training [7/16] Loss: 0.01682 +Epoch [325/4000] Training [8/16] Loss: 0.02108 +Epoch [325/4000] Training [9/16] Loss: 0.01598 +Epoch [325/4000] Training [10/16] Loss: 0.01495 +Epoch [325/4000] Training [11/16] Loss: 0.01486 +Epoch [325/4000] Training [12/16] Loss: 0.02344 +Epoch [325/4000] Training [13/16] Loss: 0.02048 +Epoch [325/4000] Training [14/16] Loss: 0.05840 +Epoch [325/4000] Training [15/16] Loss: 0.03505 +Epoch [325/4000] Training [16/16] Loss: 0.01696 +Epoch [325/4000] Training metric {'Train/mean dice_metric': 0.9847666025161743, 'Train/mean miou_metric': 0.9703733325004578, 'Train/mean f1': 0.9831958413124084, 'Train/mean precision': 0.9792504906654358, 'Train/mean recall': 0.9871731400489807, 'Train/mean hd95_metric': 2.559185028076172} +Epoch [325/4000] Validation [1/4] Loss: 0.26292 focal_loss 0.14235 dice_loss 0.12058 +Epoch [325/4000] Validation [2/4] Loss: 0.31905 focal_loss 0.13936 dice_loss 0.17969 +Epoch [325/4000] Validation [3/4] Loss: 0.16278 focal_loss 0.08207 dice_loss 0.08071 +Epoch [325/4000] Validation [4/4] Loss: 0.23242 focal_loss 0.11603 dice_loss 0.11639 +Epoch [325/4000] Validation metric {'Val/mean dice_metric': 0.9591797590255737, 'Val/mean miou_metric': 0.9340835809707642, 'Val/mean f1': 0.9627875685691833, 'Val/mean precision': 0.962418258190155, 'Val/mean recall': 0.9631569981575012, 'Val/mean hd95_metric': 6.8650336265563965} +Cheakpoint... +Epoch [325/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9592], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9591797590255737, 'Val/mean miou_metric': 0.9340835809707642, 'Val/mean f1': 0.9627875685691833, 'Val/mean precision': 0.962418258190155, 'Val/mean recall': 0.9631569981575012, 'Val/mean hd95_metric': 6.8650336265563965} +Epoch [326/4000] Training [1/16] Loss: 0.01665 +Epoch [326/4000] Training [2/16] Loss: 0.01982 +Epoch [326/4000] Training [3/16] Loss: 0.05452 +Epoch [326/4000] Training [4/16] Loss: 0.01422 +Epoch [326/4000] Training [5/16] Loss: 0.02441 +Epoch [326/4000] Training [6/16] Loss: 0.02000 +Epoch [326/4000] Training [7/16] Loss: 0.02036 +Epoch [326/4000] Training [8/16] Loss: 0.02147 +Epoch [326/4000] Training [9/16] Loss: 0.02126 +Epoch [326/4000] Training [10/16] Loss: 0.02178 +Epoch [326/4000] Training [11/16] Loss: 0.02158 +Epoch [326/4000] Training [12/16] Loss: 0.02025 +Epoch [326/4000] Training [13/16] Loss: 0.02552 +Epoch [326/4000] Training [14/16] Loss: 0.02467 +Epoch [326/4000] Training [15/16] Loss: 0.01967 +Epoch [326/4000] Training [16/16] Loss: 0.02026 +Epoch [326/4000] Training metric {'Train/mean dice_metric': 0.9843556880950928, 'Train/mean miou_metric': 0.9693859815597534, 'Train/mean f1': 0.981420636177063, 'Train/mean precision': 0.9767717719078064, 'Train/mean recall': 0.9861140251159668, 'Train/mean hd95_metric': 3.778141975402832} +Epoch [326/4000] Validation [1/4] Loss: 0.53423 focal_loss 0.35556 dice_loss 0.17867 +Epoch [326/4000] Validation [2/4] Loss: 0.30146 focal_loss 0.10558 dice_loss 0.19588 +Epoch [326/4000] Validation [3/4] Loss: 0.13927 focal_loss 0.06476 dice_loss 0.07451 +Epoch [326/4000] Validation [4/4] Loss: 0.25301 focal_loss 0.11438 dice_loss 0.13863 +Epoch [326/4000] Validation metric {'Val/mean dice_metric': 0.9576074481010437, 'Val/mean miou_metric': 0.931169867515564, 'Val/mean f1': 0.9592624306678772, 'Val/mean precision': 0.9640904068946838, 'Val/mean recall': 0.9544826149940491, 'Val/mean hd95_metric': 8.354293823242188} +Cheakpoint... +Epoch [326/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576074481010437, 'Val/mean miou_metric': 0.931169867515564, 'Val/mean f1': 0.9592624306678772, 'Val/mean precision': 0.9640904068946838, 'Val/mean recall': 0.9544826149940491, 'Val/mean hd95_metric': 8.354293823242188} +Epoch [327/4000] Training [1/16] Loss: 0.02950 +Epoch [327/4000] Training [2/16] Loss: 0.03395 +Epoch [327/4000] Training [3/16] Loss: 0.01924 +Epoch [327/4000] Training [4/16] Loss: 0.01974 +Epoch [327/4000] Training [5/16] Loss: 0.03476 +Epoch [327/4000] Training [6/16] Loss: 0.01919 +Epoch [327/4000] Training [7/16] Loss: 0.02174 +Epoch [327/4000] Training [8/16] Loss: 0.01878 +Epoch [327/4000] Training [9/16] Loss: 0.01919 +Epoch [327/4000] Training [10/16] Loss: 0.01728 +Epoch [327/4000] Training [11/16] Loss: 0.02653 +Epoch [327/4000] Training [12/16] Loss: 0.02889 +Epoch [327/4000] Training [13/16] Loss: 0.01792 +Epoch [327/4000] Training [14/16] Loss: 0.02219 +Epoch [327/4000] Training [15/16] Loss: 0.01637 +Epoch [327/4000] Training [16/16] Loss: 0.01615 +Epoch [327/4000] Training metric {'Train/mean dice_metric': 0.9844378232955933, 'Train/mean miou_metric': 0.9695464372634888, 'Train/mean f1': 0.9823776483535767, 'Train/mean precision': 0.9778342843055725, 'Train/mean recall': 0.9869635105133057, 'Train/mean hd95_metric': 2.713257312774658} +Epoch [327/4000] Validation [1/4] Loss: 0.17898 focal_loss 0.09973 dice_loss 0.07925 +Epoch [327/4000] Validation [2/4] Loss: 0.33115 focal_loss 0.11251 dice_loss 0.21864 +Epoch [327/4000] Validation [3/4] Loss: 0.14991 focal_loss 0.07345 dice_loss 0.07646 +Epoch [327/4000] Validation [4/4] Loss: 0.45592 focal_loss 0.25773 dice_loss 0.19819 +Epoch [327/4000] Validation metric {'Val/mean dice_metric': 0.9602785110473633, 'Val/mean miou_metric': 0.9333209991455078, 'Val/mean f1': 0.9627963304519653, 'Val/mean precision': 0.9535552263259888, 'Val/mean recall': 0.9722183346748352, 'Val/mean hd95_metric': 8.425992965698242} +Cheakpoint... +Epoch [327/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9603], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9602785110473633, 'Val/mean miou_metric': 0.9333209991455078, 'Val/mean f1': 0.9627963304519653, 'Val/mean precision': 0.9535552263259888, 'Val/mean recall': 0.9722183346748352, 'Val/mean hd95_metric': 8.425992965698242} +Epoch [328/4000] Training [1/16] Loss: 0.01676 +Epoch [328/4000] Training [2/16] Loss: 0.01787 +Epoch [328/4000] Training [3/16] Loss: 0.01775 +Epoch [328/4000] Training [4/16] Loss: 0.01910 +Epoch [328/4000] Training [5/16] Loss: 0.01899 +Epoch [328/4000] Training [6/16] Loss: 0.01843 +Epoch [328/4000] Training [7/16] Loss: 0.02090 +Epoch [328/4000] Training [8/16] Loss: 0.01945 +Epoch [328/4000] Training [9/16] Loss: 0.02068 +Epoch [328/4000] Training [10/16] Loss: 0.02377 +Epoch [328/4000] Training [11/16] Loss: 0.01943 +Epoch [328/4000] Training [12/16] Loss: 0.02504 +Epoch [328/4000] Training [13/16] Loss: 0.10484 +Epoch [328/4000] Training [14/16] Loss: 0.01871 +Epoch [328/4000] Training [15/16] Loss: 0.02583 +Epoch [328/4000] Training [16/16] Loss: 0.03700 +Epoch [328/4000] Training metric {'Train/mean dice_metric': 0.984963059425354, 'Train/mean miou_metric': 0.9706466794013977, 'Train/mean f1': 0.9807454943656921, 'Train/mean precision': 0.9746854901313782, 'Train/mean recall': 0.9868813157081604, 'Train/mean hd95_metric': 2.322704553604126} +Epoch [328/4000] Validation [1/4] Loss: 0.20170 focal_loss 0.11388 dice_loss 0.08783 +Epoch [328/4000] Validation [2/4] Loss: 0.37118 focal_loss 0.17543 dice_loss 0.19575 +Epoch [328/4000] Validation [3/4] Loss: 0.28591 focal_loss 0.16044 dice_loss 0.12546 +Epoch [328/4000] Validation [4/4] Loss: 0.40630 focal_loss 0.25059 dice_loss 0.15571 +Epoch [328/4000] Validation metric {'Val/mean dice_metric': 0.9592227935791016, 'Val/mean miou_metric': 0.9321655035018921, 'Val/mean f1': 0.9598844647407532, 'Val/mean precision': 0.9575142860412598, 'Val/mean recall': 0.9622665047645569, 'Val/mean hd95_metric': 8.641563415527344} +Cheakpoint... +Epoch [328/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9592], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9592227935791016, 'Val/mean miou_metric': 0.9321655035018921, 'Val/mean f1': 0.9598844647407532, 'Val/mean precision': 0.9575142860412598, 'Val/mean recall': 0.9622665047645569, 'Val/mean hd95_metric': 8.641563415527344} +Epoch [329/4000] Training [1/16] Loss: 0.02843 +Epoch [329/4000] Training [2/16] Loss: 0.02184 +Epoch [329/4000] Training [3/16] Loss: 0.05318 +Epoch [329/4000] Training [4/16] Loss: 0.02753 +Epoch [329/4000] Training [5/16] Loss: 0.02215 +Epoch [329/4000] Training [6/16] Loss: 0.01516 +Epoch [329/4000] Training [7/16] Loss: 0.02084 +Epoch [329/4000] Training [8/16] Loss: 0.01854 +Epoch [329/4000] Training [9/16] Loss: 0.02058 +Epoch [329/4000] Training [10/16] Loss: 0.02145 +Epoch [329/4000] Training [11/16] Loss: 0.02154 +Epoch [329/4000] Training [12/16] Loss: 0.02802 +Epoch [329/4000] Training [13/16] Loss: 0.02145 +Epoch [329/4000] Training [14/16] Loss: 0.02178 +Epoch [329/4000] Training [15/16] Loss: 0.02424 +Epoch [329/4000] Training [16/16] Loss: 0.01782 +Epoch [329/4000] Training metric {'Train/mean dice_metric': 0.9816322922706604, 'Train/mean miou_metric': 0.9646682739257812, 'Train/mean f1': 0.9793885946273804, 'Train/mean precision': 0.9753483533859253, 'Train/mean recall': 0.9834624528884888, 'Train/mean hd95_metric': 4.048519134521484} +Epoch [329/4000] Validation [1/4] Loss: 0.31330 focal_loss 0.20631 dice_loss 0.10699 +Epoch [329/4000] Validation [2/4] Loss: 0.41829 focal_loss 0.14249 dice_loss 0.27581 +Epoch [329/4000] Validation [3/4] Loss: 0.10806 focal_loss 0.04721 dice_loss 0.06085 +Epoch [329/4000] Validation [4/4] Loss: 0.15870 focal_loss 0.05934 dice_loss 0.09936 +Epoch [329/4000] Validation metric {'Val/mean dice_metric': 0.9560370445251465, 'Val/mean miou_metric': 0.9291283488273621, 'Val/mean f1': 0.9583714604377747, 'Val/mean precision': 0.9549373984336853, 'Val/mean recall': 0.9618303179740906, 'Val/mean hd95_metric': 9.16846752166748} +Cheakpoint... +Epoch [329/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9560], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9560370445251465, 'Val/mean miou_metric': 0.9291283488273621, 'Val/mean f1': 0.9583714604377747, 'Val/mean precision': 0.9549373984336853, 'Val/mean recall': 0.9618303179740906, 'Val/mean hd95_metric': 9.16846752166748} +Epoch [330/4000] Training [1/16] Loss: 0.01816 +Epoch [330/4000] Training [2/16] Loss: 0.02052 +Epoch [330/4000] Training [3/16] Loss: 0.01753 +Epoch [330/4000] Training [4/16] Loss: 0.03279 +Epoch [330/4000] Training [5/16] Loss: 0.03056 +Epoch [330/4000] Training [6/16] Loss: 0.06671 +Epoch [330/4000] Training [7/16] Loss: 0.02193 +Epoch [330/4000] Training [8/16] Loss: 0.01869 +Epoch [330/4000] Training [9/16] Loss: 0.02043 +Epoch [330/4000] Training [10/16] Loss: 0.03500 +Epoch [330/4000] Training [11/16] Loss: 0.03593 +Epoch [330/4000] Training [12/16] Loss: 0.02170 +Epoch [330/4000] Training [13/16] Loss: 0.02317 +Epoch [330/4000] Training [14/16] Loss: 0.15010 +Epoch [330/4000] Training [15/16] Loss: 0.02771 +Epoch [330/4000] Training [16/16] Loss: 0.01895 +Epoch [330/4000] Training metric {'Train/mean dice_metric': 0.9831962585449219, 'Train/mean miou_metric': 0.967373788356781, 'Train/mean f1': 0.9792866110801697, 'Train/mean precision': 0.9738870859146118, 'Train/mean recall': 0.9847463369369507, 'Train/mean hd95_metric': 2.9876115322113037} +Epoch [330/4000] Validation [1/4] Loss: 0.16204 focal_loss 0.09399 dice_loss 0.06805 +Epoch [330/4000] Validation [2/4] Loss: 0.22398 focal_loss 0.08515 dice_loss 0.13883 +Epoch [330/4000] Validation [3/4] Loss: 0.14863 focal_loss 0.07786 dice_loss 0.07077 +Epoch [330/4000] Validation [4/4] Loss: 0.24060 focal_loss 0.11472 dice_loss 0.12589 +Epoch [330/4000] Validation metric {'Val/mean dice_metric': 0.9613708257675171, 'Val/mean miou_metric': 0.9346364140510559, 'Val/mean f1': 0.9635854363441467, 'Val/mean precision': 0.9608932137489319, 'Val/mean recall': 0.966292679309845, 'Val/mean hd95_metric': 7.899090766906738} +Cheakpoint... +Epoch [330/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9613708257675171, 'Val/mean miou_metric': 0.9346364140510559, 'Val/mean f1': 0.9635854363441467, 'Val/mean precision': 0.9608932137489319, 'Val/mean recall': 0.966292679309845, 'Val/mean hd95_metric': 7.899090766906738} +Epoch [331/4000] Training [1/16] Loss: 0.03615 +Epoch [331/4000] Training [2/16] Loss: 0.01780 +Epoch [331/4000] Training [3/16] Loss: 0.02203 +Epoch [331/4000] Training [4/16] Loss: 0.01794 +Epoch [331/4000] Training [5/16] Loss: 0.02862 +Epoch [331/4000] Training [6/16] Loss: 0.02175 +Epoch [331/4000] Training [7/16] Loss: 0.02304 +Epoch [331/4000] Training [8/16] Loss: 0.04462 +Epoch [331/4000] Training [9/16] Loss: 0.23902 +Epoch [331/4000] Training [10/16] Loss: 0.01900 +Epoch [331/4000] Training [11/16] Loss: 0.02197 +Epoch [331/4000] Training [12/16] Loss: 0.02801 +Epoch [331/4000] Training [13/16] Loss: 0.01772 +Epoch [331/4000] Training [14/16] Loss: 0.02263 +Epoch [331/4000] Training [15/16] Loss: 0.02353 +Epoch [331/4000] Training [16/16] Loss: 0.02543 +Epoch [331/4000] Training metric {'Train/mean dice_metric': 0.9793168306350708, 'Train/mean miou_metric': 0.9623175263404846, 'Train/mean f1': 0.9759754538536072, 'Train/mean precision': 0.9747827649116516, 'Train/mean recall': 0.9771711230278015, 'Train/mean hd95_metric': 4.751482963562012} +Epoch [331/4000] Validation [1/4] Loss: 0.16007 focal_loss 0.08469 dice_loss 0.07538 +Epoch [331/4000] Validation [2/4] Loss: 0.40729 focal_loss 0.16489 dice_loss 0.24240 +Epoch [331/4000] Validation [3/4] Loss: 0.24135 focal_loss 0.13413 dice_loss 0.10722 +Epoch [331/4000] Validation [4/4] Loss: 0.40880 focal_loss 0.21446 dice_loss 0.19434 +Epoch [331/4000] Validation metric {'Val/mean dice_metric': 0.9545100331306458, 'Val/mean miou_metric': 0.926770806312561, 'Val/mean f1': 0.9566026926040649, 'Val/mean precision': 0.9512147903442383, 'Val/mean recall': 0.962052047252655, 'Val/mean hd95_metric': 10.771319389343262} +Cheakpoint... +Epoch [331/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9545], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9545100331306458, 'Val/mean miou_metric': 0.926770806312561, 'Val/mean f1': 0.9566026926040649, 'Val/mean precision': 0.9512147903442383, 'Val/mean recall': 0.962052047252655, 'Val/mean hd95_metric': 10.771319389343262} +Epoch [332/4000] Training [1/16] Loss: 0.02163 +Epoch [332/4000] Training [2/16] Loss: 0.05383 +Epoch [332/4000] Training [3/16] Loss: 0.07167 +Epoch [332/4000] Training [4/16] Loss: 0.02699 +Epoch [332/4000] Training [5/16] Loss: 0.03577 +Epoch [332/4000] Training [6/16] Loss: 0.01906 +Epoch [332/4000] Training [7/16] Loss: 0.02123 +Epoch [332/4000] Training [8/16] Loss: 0.01770 +Epoch [332/4000] Training [9/16] Loss: 0.01781 +Epoch [332/4000] Training [10/16] Loss: 0.05081 +Epoch [332/4000] Training [11/16] Loss: 0.02199 +Epoch [332/4000] Training [12/16] Loss: 0.04785 +Epoch [332/4000] Training [13/16] Loss: 0.02845 +Epoch [332/4000] Training [14/16] Loss: 0.02439 +Epoch [332/4000] Training [15/16] Loss: 0.01939 +Epoch [332/4000] Training [16/16] Loss: 0.03835 +Epoch [332/4000] Training metric {'Train/mean dice_metric': 0.9783775806427002, 'Train/mean miou_metric': 0.9593748450279236, 'Train/mean f1': 0.9756656885147095, 'Train/mean precision': 0.9716925621032715, 'Train/mean recall': 0.9796713590621948, 'Train/mean hd95_metric': 5.419099807739258} +Epoch [332/4000] Validation [1/4] Loss: 0.37680 focal_loss 0.23047 dice_loss 0.14633 +Epoch [332/4000] Validation [2/4] Loss: 0.33661 focal_loss 0.11410 dice_loss 0.22251 +Epoch [332/4000] Validation [3/4] Loss: 0.13532 focal_loss 0.04460 dice_loss 0.09072 +Epoch [332/4000] Validation [4/4] Loss: 0.23286 focal_loss 0.09665 dice_loss 0.13621 +Epoch [332/4000] Validation metric {'Val/mean dice_metric': 0.9495899081230164, 'Val/mean miou_metric': 0.9198545217514038, 'Val/mean f1': 0.9535573124885559, 'Val/mean precision': 0.9557104110717773, 'Val/mean recall': 0.9514139294624329, 'Val/mean hd95_metric': 10.36628532409668} +Cheakpoint... +Epoch [332/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9496], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9495899081230164, 'Val/mean miou_metric': 0.9198545217514038, 'Val/mean f1': 0.9535573124885559, 'Val/mean precision': 0.9557104110717773, 'Val/mean recall': 0.9514139294624329, 'Val/mean hd95_metric': 10.36628532409668} +Epoch [333/4000] Training [1/16] Loss: 0.01963 +Epoch [333/4000] Training [2/16] Loss: 0.02088 +Epoch [333/4000] Training [3/16] Loss: 0.02247 +Epoch [333/4000] Training [4/16] Loss: 0.01822 +Epoch [333/4000] Training [5/16] Loss: 0.05093 +Epoch [333/4000] Training [6/16] Loss: 0.02254 +Epoch [333/4000] Training [7/16] Loss: 0.03027 +Epoch [333/4000] Training [8/16] Loss: 0.02522 +Epoch [333/4000] Training [9/16] Loss: 0.02341 +Epoch [333/4000] Training [10/16] Loss: 0.02336 +Epoch [333/4000] Training [11/16] Loss: 0.02844 +Epoch [333/4000] Training [12/16] Loss: 0.03136 +Epoch [333/4000] Training [13/16] Loss: 0.02194 +Epoch [333/4000] Training [14/16] Loss: 0.02599 +Epoch [333/4000] Training [15/16] Loss: 0.02150 +Epoch [333/4000] Training [16/16] Loss: 0.01782 +Epoch [333/4000] Training metric {'Train/mean dice_metric': 0.9826632738113403, 'Train/mean miou_metric': 0.9659976959228516, 'Train/mean f1': 0.9800084233283997, 'Train/mean precision': 0.9736923575401306, 'Train/mean recall': 0.9864069223403931, 'Train/mean hd95_metric': 2.9842751026153564} +Epoch [333/4000] Validation [1/4] Loss: 0.19650 focal_loss 0.10978 dice_loss 0.08672 +Epoch [333/4000] Validation [2/4] Loss: 0.49276 focal_loss 0.21555 dice_loss 0.27721 +Epoch [333/4000] Validation [3/4] Loss: 0.18524 focal_loss 0.07498 dice_loss 0.11026 +Epoch [333/4000] Validation [4/4] Loss: 0.35510 focal_loss 0.18811 dice_loss 0.16698 +Epoch [333/4000] Validation metric {'Val/mean dice_metric': 0.9575985670089722, 'Val/mean miou_metric': 0.9293802976608276, 'Val/mean f1': 0.9583784341812134, 'Val/mean precision': 0.9536697268486023, 'Val/mean recall': 0.9631338715553284, 'Val/mean hd95_metric': 8.400039672851562} +Cheakpoint... +Epoch [333/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9575985670089722, 'Val/mean miou_metric': 0.9293802976608276, 'Val/mean f1': 0.9583784341812134, 'Val/mean precision': 0.9536697268486023, 'Val/mean recall': 0.9631338715553284, 'Val/mean hd95_metric': 8.400039672851562} +Epoch [334/4000] Training [1/16] Loss: 0.02534 +Epoch [334/4000] Training [2/16] Loss: 0.01993 +Epoch [334/4000] Training [3/16] Loss: 0.02215 +Epoch [334/4000] Training [4/16] Loss: 0.01842 +Epoch [334/4000] Training [5/16] Loss: 0.02317 +Epoch [334/4000] Training [6/16] Loss: 0.02032 +Epoch [334/4000] Training [7/16] Loss: 0.02420 +Epoch [334/4000] Training [8/16] Loss: 0.01930 +Epoch [334/4000] Training [9/16] Loss: 0.02312 +Epoch [334/4000] Training [10/16] Loss: 0.01719 +Epoch [334/4000] Training [11/16] Loss: 0.01535 +Epoch [334/4000] Training [12/16] Loss: 0.02570 +Epoch [334/4000] Training [13/16] Loss: 0.02924 +Epoch [334/4000] Training [14/16] Loss: 0.01838 +Epoch [334/4000] Training [15/16] Loss: 0.01786 +Epoch [334/4000] Training [16/16] Loss: 0.01564 +Epoch [334/4000] Training metric {'Train/mean dice_metric': 0.9856578707695007, 'Train/mean miou_metric': 0.9716545343399048, 'Train/mean f1': 0.9822252988815308, 'Train/mean precision': 0.9782085418701172, 'Train/mean recall': 0.9862751960754395, 'Train/mean hd95_metric': 2.7185072898864746} +Epoch [334/4000] Validation [1/4] Loss: 0.14530 focal_loss 0.07461 dice_loss 0.07070 +Epoch [334/4000] Validation [2/4] Loss: 0.31563 focal_loss 0.13023 dice_loss 0.18540 +Epoch [334/4000] Validation [3/4] Loss: 0.13621 focal_loss 0.05194 dice_loss 0.08426 +Epoch [334/4000] Validation [4/4] Loss: 0.25740 focal_loss 0.09570 dice_loss 0.16169 +Epoch [334/4000] Validation metric {'Val/mean dice_metric': 0.9622365832328796, 'Val/mean miou_metric': 0.937333881855011, 'Val/mean f1': 0.9616963267326355, 'Val/mean precision': 0.9492546319961548, 'Val/mean recall': 0.9744685292243958, 'Val/mean hd95_metric': 8.295347213745117} +Cheakpoint... +Epoch [334/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622365832328796, 'Val/mean miou_metric': 0.937333881855011, 'Val/mean f1': 0.9616963267326355, 'Val/mean precision': 0.9492546319961548, 'Val/mean recall': 0.9744685292243958, 'Val/mean hd95_metric': 8.295347213745117} +Epoch [335/4000] Training [1/16] Loss: 0.02579 +Epoch [335/4000] Training [2/16] Loss: 0.02521 +Epoch [335/4000] Training [3/16] Loss: 0.02065 +Epoch [335/4000] Training [4/16] Loss: 0.02003 +Epoch [335/4000] Training [5/16] Loss: 0.01950 +Epoch [335/4000] Training [6/16] Loss: 0.02653 +Epoch [335/4000] Training [7/16] Loss: 0.02142 +Epoch [335/4000] Training [8/16] Loss: 0.01604 +Epoch [335/4000] Training [9/16] Loss: 0.01569 +Epoch [335/4000] Training [10/16] Loss: 0.02781 +Epoch [335/4000] Training [11/16] Loss: 0.02161 +Epoch [335/4000] Training [12/16] Loss: 0.02388 +Epoch [335/4000] Training [13/16] Loss: 0.02181 +Epoch [335/4000] Training [14/16] Loss: 0.02300 +Epoch [335/4000] Training [15/16] Loss: 0.01517 +Epoch [335/4000] Training [16/16] Loss: 0.02080 +Epoch [335/4000] Training metric {'Train/mean dice_metric': 0.98626708984375, 'Train/mean miou_metric': 0.9727991223335266, 'Train/mean f1': 0.9840589165687561, 'Train/mean precision': 0.9797977209091187, 'Train/mean recall': 0.9883573055267334, 'Train/mean hd95_metric': 1.7240514755249023} +Epoch [335/4000] Validation [1/4] Loss: 0.17679 focal_loss 0.10606 dice_loss 0.07073 +Epoch [335/4000] Validation [2/4] Loss: 0.39369 focal_loss 0.17747 dice_loss 0.21622 +Epoch [335/4000] Validation [3/4] Loss: 0.15266 focal_loss 0.06678 dice_loss 0.08587 +Epoch [335/4000] Validation [4/4] Loss: 0.17743 focal_loss 0.06730 dice_loss 0.11013 +Epoch [335/4000] Validation metric {'Val/mean dice_metric': 0.962958037853241, 'Val/mean miou_metric': 0.9382907748222351, 'Val/mean f1': 0.9632835388183594, 'Val/mean precision': 0.9521950483322144, 'Val/mean recall': 0.9746332764625549, 'Val/mean hd95_metric': 7.729730129241943} +Cheakpoint... +Epoch [335/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.962958037853241, 'Val/mean miou_metric': 0.9382907748222351, 'Val/mean f1': 0.9632835388183594, 'Val/mean precision': 0.9521950483322144, 'Val/mean recall': 0.9746332764625549, 'Val/mean hd95_metric': 7.729730129241943} +Epoch [336/4000] Training [1/16] Loss: 0.01542 +Epoch [336/4000] Training [2/16] Loss: 0.02397 +Epoch [336/4000] Training [3/16] Loss: 0.01679 +Epoch [336/4000] Training [4/16] Loss: 0.01658 +Epoch [336/4000] Training [5/16] Loss: 0.01579 +Epoch [336/4000] Training [6/16] Loss: 0.02371 +Epoch [336/4000] Training [7/16] Loss: 0.01688 +Epoch [336/4000] Training [8/16] Loss: 0.01559 +Epoch [336/4000] Training [9/16] Loss: 0.01573 +Epoch [336/4000] Training [10/16] Loss: 0.02152 +Epoch [336/4000] Training [11/16] Loss: 0.01531 +Epoch [336/4000] Training [12/16] Loss: 0.02006 +Epoch [336/4000] Training [13/16] Loss: 0.01894 +Epoch [336/4000] Training [14/16] Loss: 0.01888 +Epoch [336/4000] Training [15/16] Loss: 0.01595 +Epoch [336/4000] Training [16/16] Loss: 0.02776 +Epoch [336/4000] Training metric {'Train/mean dice_metric': 0.9875103235244751, 'Train/mean miou_metric': 0.9751648902893066, 'Train/mean f1': 0.9846237301826477, 'Train/mean precision': 0.9798519611358643, 'Train/mean recall': 0.9894422292709351, 'Train/mean hd95_metric': 1.5698833465576172} +Epoch [336/4000] Validation [1/4] Loss: 0.19605 focal_loss 0.11860 dice_loss 0.07745 +Epoch [336/4000] Validation [2/4] Loss: 0.36443 focal_loss 0.15756 dice_loss 0.20686 +Epoch [336/4000] Validation [3/4] Loss: 0.11940 focal_loss 0.05653 dice_loss 0.06287 +Epoch [336/4000] Validation [4/4] Loss: 0.19834 focal_loss 0.07805 dice_loss 0.12029 +Epoch [336/4000] Validation metric {'Val/mean dice_metric': 0.9662357568740845, 'Val/mean miou_metric': 0.9434100985527039, 'Val/mean f1': 0.9668258428573608, 'Val/mean precision': 0.9580335021018982, 'Val/mean recall': 0.9757810235023499, 'Val/mean hd95_metric': 6.262587547302246} +Cheakpoint... +Epoch [336/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662357568740845, 'Val/mean miou_metric': 0.9434100985527039, 'Val/mean f1': 0.9668258428573608, 'Val/mean precision': 0.9580335021018982, 'Val/mean recall': 0.9757810235023499, 'Val/mean hd95_metric': 6.262587547302246} +Epoch [337/4000] Training [1/16] Loss: 0.01450 +Epoch [337/4000] Training [2/16] Loss: 0.01716 +Epoch [337/4000] Training [3/16] Loss: 0.01345 +Epoch [337/4000] Training [4/16] Loss: 0.02185 +Epoch [337/4000] Training [5/16] Loss: 0.01829 +Epoch [337/4000] Training [6/16] Loss: 0.01305 +Epoch [337/4000] Training [7/16] Loss: 0.01528 +Epoch [337/4000] Training [8/16] Loss: 0.01372 +Epoch [337/4000] Training [9/16] Loss: 0.01420 +Epoch [337/4000] Training [10/16] Loss: 0.02055 +Epoch [337/4000] Training [11/16] Loss: 0.01305 +Epoch [337/4000] Training [12/16] Loss: 0.01394 +Epoch [337/4000] Training [13/16] Loss: 0.01854 +Epoch [337/4000] Training [14/16] Loss: 0.01666 +Epoch [337/4000] Training [15/16] Loss: 0.01153 +Epoch [337/4000] Training [16/16] Loss: 0.02368 +Epoch [337/4000] Training metric {'Train/mean dice_metric': 0.9884892702102661, 'Train/mean miou_metric': 0.9771137237548828, 'Train/mean f1': 0.9854877591133118, 'Train/mean precision': 0.9811056852340698, 'Train/mean recall': 0.9899091124534607, 'Train/mean hd95_metric': 1.6511809825897217} +Epoch [337/4000] Validation [1/4] Loss: 0.23650 focal_loss 0.15073 dice_loss 0.08578 +Epoch [337/4000] Validation [2/4] Loss: 0.28226 focal_loss 0.11079 dice_loss 0.17147 +Epoch [337/4000] Validation [3/4] Loss: 0.13912 focal_loss 0.06591 dice_loss 0.07321 +Epoch [337/4000] Validation [4/4] Loss: 0.17950 focal_loss 0.07449 dice_loss 0.10501 +Epoch [337/4000] Validation metric {'Val/mean dice_metric': 0.9648653268814087, 'Val/mean miou_metric': 0.9419918060302734, 'Val/mean f1': 0.9672889113426208, 'Val/mean precision': 0.960075318813324, 'Val/mean recall': 0.9746115803718567, 'Val/mean hd95_metric': 7.266482353210449} +Cheakpoint... +Epoch [337/4000] best acc:tensor([0.9664], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648653268814087, 'Val/mean miou_metric': 0.9419918060302734, 'Val/mean f1': 0.9672889113426208, 'Val/mean precision': 0.960075318813324, 'Val/mean recall': 0.9746115803718567, 'Val/mean hd95_metric': 7.266482353210449} +Epoch [338/4000] Training [1/16] Loss: 0.01733 +Epoch [338/4000] Training [2/16] Loss: 0.01955 +Epoch [338/4000] Training [3/16] Loss: 0.01619 +Epoch [338/4000] Training [4/16] Loss: 0.01517 +Epoch [338/4000] Training [5/16] Loss: 0.01385 +Epoch [338/4000] Training [6/16] Loss: 0.01518 +Epoch [338/4000] Training [7/16] Loss: 0.01427 +Epoch [338/4000] Training [8/16] Loss: 0.01993 +Epoch [338/4000] Training [9/16] Loss: 0.01456 +Epoch [338/4000] Training [10/16] Loss: 0.01972 +Epoch [338/4000] Training [11/16] Loss: 0.01629 +Epoch [338/4000] Training [12/16] Loss: 0.01575 +Epoch [338/4000] Training [13/16] Loss: 0.01696 +Epoch [338/4000] Training [14/16] Loss: 0.01435 +Epoch [338/4000] Training [15/16] Loss: 0.02596 +Epoch [338/4000] Training [16/16] Loss: 0.01880 +Epoch [338/4000] Training metric {'Train/mean dice_metric': 0.9879011511802673, 'Train/mean miou_metric': 0.9760800004005432, 'Train/mean f1': 0.9853417873382568, 'Train/mean precision': 0.9805487394332886, 'Train/mean recall': 0.9901819825172424, 'Train/mean hd95_metric': 1.4917349815368652} +Epoch [338/4000] Validation [1/4] Loss: 0.16095 focal_loss 0.09476 dice_loss 0.06620 +Epoch [338/4000] Validation [2/4] Loss: 0.20818 focal_loss 0.07454 dice_loss 0.13365 +Epoch [338/4000] Validation [3/4] Loss: 0.15101 focal_loss 0.07802 dice_loss 0.07299 +Epoch [338/4000] Validation [4/4] Loss: 0.24706 focal_loss 0.11838 dice_loss 0.12868 +Epoch [338/4000] Validation metric {'Val/mean dice_metric': 0.9667317271232605, 'Val/mean miou_metric': 0.9440592527389526, 'Val/mean f1': 0.9677727818489075, 'Val/mean precision': 0.9620271921157837, 'Val/mean recall': 0.9735875129699707, 'Val/mean hd95_metric': 5.890839576721191} +Cheakpoint... +Epoch [338/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667317271232605, 'Val/mean miou_metric': 0.9440592527389526, 'Val/mean f1': 0.9677727818489075, 'Val/mean precision': 0.9620271921157837, 'Val/mean recall': 0.9735875129699707, 'Val/mean hd95_metric': 5.890839576721191} +Epoch [339/4000] Training [1/16] Loss: 0.01787 +Epoch [339/4000] Training [2/16] Loss: 0.01404 +Epoch [339/4000] Training [3/16] Loss: 0.01699 +Epoch [339/4000] Training [4/16] Loss: 0.01908 +Epoch [339/4000] Training [5/16] Loss: 0.01564 +Epoch [339/4000] Training [6/16] Loss: 0.01341 +Epoch [339/4000] Training [7/16] Loss: 0.03007 +Epoch [339/4000] Training [8/16] Loss: 0.01882 +Epoch [339/4000] Training [9/16] Loss: 0.01818 +Epoch [339/4000] Training [10/16] Loss: 0.01721 +Epoch [339/4000] Training [11/16] Loss: 0.02561 +Epoch [339/4000] Training [12/16] Loss: 0.02510 +Epoch [339/4000] Training [13/16] Loss: 0.03300 +Epoch [339/4000] Training [14/16] Loss: 0.02149 +Epoch [339/4000] Training [15/16] Loss: 0.01775 +Epoch [339/4000] Training [16/16] Loss: 0.01528 +Epoch [339/4000] Training metric {'Train/mean dice_metric': 0.9867979288101196, 'Train/mean miou_metric': 0.9738917350769043, 'Train/mean f1': 0.984624445438385, 'Train/mean precision': 0.9801852703094482, 'Train/mean recall': 0.9891040325164795, 'Train/mean hd95_metric': 1.662237524986267} +Epoch [339/4000] Validation [1/4] Loss: 0.14200 focal_loss 0.08589 dice_loss 0.05611 +Epoch [339/4000] Validation [2/4] Loss: 0.29500 focal_loss 0.11952 dice_loss 0.17548 +Epoch [339/4000] Validation [3/4] Loss: 0.15885 focal_loss 0.07379 dice_loss 0.08506 +Epoch [339/4000] Validation [4/4] Loss: 0.17581 focal_loss 0.06569 dice_loss 0.11011 +Epoch [339/4000] Validation metric {'Val/mean dice_metric': 0.9646747708320618, 'Val/mean miou_metric': 0.9411211013793945, 'Val/mean f1': 0.9669456481933594, 'Val/mean precision': 0.9604206085205078, 'Val/mean recall': 0.9735597372055054, 'Val/mean hd95_metric': 6.994026184082031} +Cheakpoint... +Epoch [339/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646747708320618, 'Val/mean miou_metric': 0.9411211013793945, 'Val/mean f1': 0.9669456481933594, 'Val/mean precision': 0.9604206085205078, 'Val/mean recall': 0.9735597372055054, 'Val/mean hd95_metric': 6.994026184082031} +Epoch [340/4000] Training [1/16] Loss: 0.02327 +Epoch [340/4000] Training [2/16] Loss: 0.01698 +Epoch [340/4000] Training [3/16] Loss: 0.01743 +Epoch [340/4000] Training [4/16] Loss: 0.02528 +Epoch [340/4000] Training [5/16] Loss: 0.01745 +Epoch [340/4000] Training [6/16] Loss: 0.01475 +Epoch [340/4000] Training [7/16] Loss: 0.01576 +Epoch [340/4000] Training [8/16] Loss: 0.01860 +Epoch [340/4000] Training [9/16] Loss: 0.01266 +Epoch [340/4000] Training [10/16] Loss: 0.01739 +Epoch [340/4000] Training [11/16] Loss: 0.01608 +Epoch [340/4000] Training [12/16] Loss: 0.01708 +Epoch [340/4000] Training [13/16] Loss: 0.02014 +Epoch [340/4000] Training [14/16] Loss: 0.01644 +Epoch [340/4000] Training [15/16] Loss: 0.01502 +Epoch [340/4000] Training [16/16] Loss: 0.01711 +Epoch [340/4000] Training metric {'Train/mean dice_metric': 0.9875774383544922, 'Train/mean miou_metric': 0.9752998352050781, 'Train/mean f1': 0.9850291609764099, 'Train/mean precision': 0.9803285002708435, 'Train/mean recall': 0.9897751212120056, 'Train/mean hd95_metric': 1.4981467723846436} +Epoch [340/4000] Validation [1/4] Loss: 0.13641 focal_loss 0.08068 dice_loss 0.05573 +Epoch [340/4000] Validation [2/4] Loss: 0.43904 focal_loss 0.20989 dice_loss 0.22916 +Epoch [340/4000] Validation [3/4] Loss: 0.17090 focal_loss 0.08003 dice_loss 0.09087 +Epoch [340/4000] Validation [4/4] Loss: 0.17402 focal_loss 0.06903 dice_loss 0.10500 +Epoch [340/4000] Validation metric {'Val/mean dice_metric': 0.9645347595214844, 'Val/mean miou_metric': 0.9417324066162109, 'Val/mean f1': 0.9659403562545776, 'Val/mean precision': 0.957276463508606, 'Val/mean recall': 0.974762499332428, 'Val/mean hd95_metric': 6.2556962966918945} +Cheakpoint... +Epoch [340/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645347595214844, 'Val/mean miou_metric': 0.9417324066162109, 'Val/mean f1': 0.9659403562545776, 'Val/mean precision': 0.957276463508606, 'Val/mean recall': 0.974762499332428, 'Val/mean hd95_metric': 6.2556962966918945} +Epoch [341/4000] Training [1/16] Loss: 0.02733 +Epoch [341/4000] Training [2/16] Loss: 0.01560 +Epoch [341/4000] Training [3/16] Loss: 0.02115 +Epoch [341/4000] Training [4/16] Loss: 0.01299 +Epoch [341/4000] Training [5/16] Loss: 0.01869 +Epoch [341/4000] Training [6/16] Loss: 0.01676 +Epoch [341/4000] Training [7/16] Loss: 0.01625 +Epoch [341/4000] Training [8/16] Loss: 0.01295 +Epoch [341/4000] Training [9/16] Loss: 0.01305 +Epoch [341/4000] Training [10/16] Loss: 0.02075 +Epoch [341/4000] Training [11/16] Loss: 0.01779 +Epoch [341/4000] Training [12/16] Loss: 0.02005 +Epoch [341/4000] Training [13/16] Loss: 0.02332 +Epoch [341/4000] Training [14/16] Loss: 0.02947 +Epoch [341/4000] Training [15/16] Loss: 0.01919 +Epoch [341/4000] Training [16/16] Loss: 0.03177 +Epoch [341/4000] Training metric {'Train/mean dice_metric': 0.9874604940414429, 'Train/mean miou_metric': 0.9751523733139038, 'Train/mean f1': 0.9856951236724854, 'Train/mean precision': 0.981490969657898, 'Train/mean recall': 0.9899353384971619, 'Train/mean hd95_metric': 1.8047053813934326} +Epoch [341/4000] Validation [1/4] Loss: 0.12298 focal_loss 0.06088 dice_loss 0.06210 +Epoch [341/4000] Validation [2/4] Loss: 0.33428 focal_loss 0.13242 dice_loss 0.20185 +Epoch [341/4000] Validation [3/4] Loss: 0.13213 focal_loss 0.06552 dice_loss 0.06661 +Epoch [341/4000] Validation [4/4] Loss: 0.20253 focal_loss 0.09268 dice_loss 0.10986 +Epoch [341/4000] Validation metric {'Val/mean dice_metric': 0.9629985690116882, 'Val/mean miou_metric': 0.9408512115478516, 'Val/mean f1': 0.9665164351463318, 'Val/mean precision': 0.9596825838088989, 'Val/mean recall': 0.9734482169151306, 'Val/mean hd95_metric': 6.726579189300537} +Cheakpoint... +Epoch [341/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629985690116882, 'Val/mean miou_metric': 0.9408512115478516, 'Val/mean f1': 0.9665164351463318, 'Val/mean precision': 0.9596825838088989, 'Val/mean recall': 0.9734482169151306, 'Val/mean hd95_metric': 6.726579189300537} +Epoch [342/4000] Training [1/16] Loss: 0.01909 +Epoch [342/4000] Training [2/16] Loss: 0.01981 +Epoch [342/4000] Training [3/16] Loss: 0.01335 +Epoch [342/4000] Training [4/16] Loss: 0.03339 +Epoch [342/4000] Training [5/16] Loss: 0.01423 +Epoch [342/4000] Training [6/16] Loss: 0.01736 +Epoch [342/4000] Training [7/16] Loss: 0.01565 +Epoch [342/4000] Training [8/16] Loss: 0.01665 +Epoch [342/4000] Training [9/16] Loss: 0.02702 +Epoch [342/4000] Training [10/16] Loss: 0.01387 +Epoch [342/4000] Training [11/16] Loss: 0.02041 +Epoch [342/4000] Training [12/16] Loss: 0.03155 +Epoch [342/4000] Training [13/16] Loss: 0.02324 +Epoch [342/4000] Training [14/16] Loss: 0.01654 +Epoch [342/4000] Training [15/16] Loss: 0.01679 +Epoch [342/4000] Training [16/16] Loss: 0.02345 +Epoch [342/4000] Training metric {'Train/mean dice_metric': 0.9813505411148071, 'Train/mean miou_metric': 0.9668489694595337, 'Train/mean f1': 0.9818009734153748, 'Train/mean precision': 0.9761866927146912, 'Train/mean recall': 0.9874802231788635, 'Train/mean hd95_metric': 2.956319570541382} +Epoch [342/4000] Validation [1/4] Loss: 0.19756 focal_loss 0.11907 dice_loss 0.07849 +Epoch [342/4000] Validation [2/4] Loss: 0.16630 focal_loss 0.05854 dice_loss 0.10776 +Epoch [342/4000] Validation [3/4] Loss: 0.19421 focal_loss 0.10338 dice_loss 0.09084 +Epoch [342/4000] Validation [4/4] Loss: 0.19837 focal_loss 0.08473 dice_loss 0.11364 +Epoch [342/4000] Validation metric {'Val/mean dice_metric': 0.9586530923843384, 'Val/mean miou_metric': 0.9337689280509949, 'Val/mean f1': 0.964450478553772, 'Val/mean precision': 0.9614472389221191, 'Val/mean recall': 0.9674724340438843, 'Val/mean hd95_metric': 7.863288879394531} +Cheakpoint... +Epoch [342/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9587], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9586530923843384, 'Val/mean miou_metric': 0.9337689280509949, 'Val/mean f1': 0.964450478553772, 'Val/mean precision': 0.9614472389221191, 'Val/mean recall': 0.9674724340438843, 'Val/mean hd95_metric': 7.863288879394531} +Epoch [343/4000] Training [1/16] Loss: 0.01837 +Epoch [343/4000] Training [2/16] Loss: 0.01402 +Epoch [343/4000] Training [3/16] Loss: 0.01994 +Epoch [343/4000] Training [4/16] Loss: 0.01857 +Epoch [343/4000] Training [5/16] Loss: 0.02311 +Epoch [343/4000] Training [6/16] Loss: 0.02048 +Epoch [343/4000] Training [7/16] Loss: 0.02017 +Epoch [343/4000] Training [8/16] Loss: 0.03289 +Epoch [343/4000] Training [9/16] Loss: 0.13088 +Epoch [343/4000] Training [10/16] Loss: 0.02618 +Epoch [343/4000] Training [11/16] Loss: 0.02971 +Epoch [343/4000] Training [12/16] Loss: 0.02424 +Epoch [343/4000] Training [13/16] Loss: 0.01705 +Epoch [343/4000] Training [14/16] Loss: 0.02063 +Epoch [343/4000] Training [15/16] Loss: 0.01607 +Epoch [343/4000] Training [16/16] Loss: 0.02195 +Epoch [343/4000] Training metric {'Train/mean dice_metric': 0.9843530654907227, 'Train/mean miou_metric': 0.9698134660720825, 'Train/mean f1': 0.9825067520141602, 'Train/mean precision': 0.9786916375160217, 'Train/mean recall': 0.986351728439331, 'Train/mean hd95_metric': 2.2641987800598145} +Epoch [343/4000] Validation [1/4] Loss: 0.13798 focal_loss 0.07769 dice_loss 0.06030 +Epoch [343/4000] Validation [2/4] Loss: 0.29067 focal_loss 0.11005 dice_loss 0.18062 +Epoch [343/4000] Validation [3/4] Loss: 0.35734 focal_loss 0.24642 dice_loss 0.11091 +Epoch [343/4000] Validation [4/4] Loss: 0.22309 focal_loss 0.09641 dice_loss 0.12668 +Epoch [343/4000] Validation metric {'Val/mean dice_metric': 0.9585663080215454, 'Val/mean miou_metric': 0.9334611892700195, 'Val/mean f1': 0.9630613327026367, 'Val/mean precision': 0.9546321034431458, 'Val/mean recall': 0.9716408848762512, 'Val/mean hd95_metric': 8.04981517791748} +Cheakpoint... +Epoch [343/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9586], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9585663080215454, 'Val/mean miou_metric': 0.9334611892700195, 'Val/mean f1': 0.9630613327026367, 'Val/mean precision': 0.9546321034431458, 'Val/mean recall': 0.9716408848762512, 'Val/mean hd95_metric': 8.04981517791748} +Epoch [344/4000] Training [1/16] Loss: 0.03027 +Epoch [344/4000] Training [2/16] Loss: 0.02062 +Epoch [344/4000] Training [3/16] Loss: 0.01818 +Epoch [344/4000] Training [4/16] Loss: 0.01604 +Epoch [344/4000] Training [5/16] Loss: 0.01750 +Epoch [344/4000] Training [6/16] Loss: 0.01569 +Epoch [344/4000] Training [7/16] Loss: 0.02373 +Epoch [344/4000] Training [8/16] Loss: 0.01885 +Epoch [344/4000] Training [9/16] Loss: 0.01583 +Epoch [344/4000] Training [10/16] Loss: 0.02798 +Epoch [344/4000] Training [11/16] Loss: 0.01836 +Epoch [344/4000] Training [12/16] Loss: 0.02052 +Epoch [344/4000] Training [13/16] Loss: 0.01865 +Epoch [344/4000] Training [14/16] Loss: 0.01630 +Epoch [344/4000] Training [15/16] Loss: 0.02224 +Epoch [344/4000] Training [16/16] Loss: 0.02204 +Epoch [344/4000] Training metric {'Train/mean dice_metric': 0.9835183620452881, 'Train/mean miou_metric': 0.9689874649047852, 'Train/mean f1': 0.9824814200401306, 'Train/mean precision': 0.9784151911735535, 'Train/mean recall': 0.986581563949585, 'Train/mean hd95_metric': 2.474229097366333} +Epoch [344/4000] Validation [1/4] Loss: 0.13542 focal_loss 0.07361 dice_loss 0.06182 +Epoch [344/4000] Validation [2/4] Loss: 0.30763 focal_loss 0.15129 dice_loss 0.15633 +Epoch [344/4000] Validation [3/4] Loss: 0.15786 focal_loss 0.06630 dice_loss 0.09156 +Epoch [344/4000] Validation [4/4] Loss: 0.24192 focal_loss 0.10923 dice_loss 0.13270 +Epoch [344/4000] Validation metric {'Val/mean dice_metric': 0.9597198367118835, 'Val/mean miou_metric': 0.934086799621582, 'Val/mean f1': 0.963466465473175, 'Val/mean precision': 0.957690954208374, 'Val/mean recall': 0.9693120718002319, 'Val/mean hd95_metric': 7.890007019042969} +Cheakpoint... +Epoch [344/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9597], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9597198367118835, 'Val/mean miou_metric': 0.934086799621582, 'Val/mean f1': 0.963466465473175, 'Val/mean precision': 0.957690954208374, 'Val/mean recall': 0.9693120718002319, 'Val/mean hd95_metric': 7.890007019042969} +Epoch [345/4000] Training [1/16] Loss: 0.01949 +Epoch [345/4000] Training [2/16] Loss: 0.01562 +Epoch [345/4000] Training [3/16] Loss: 0.02326 +Epoch [345/4000] Training [4/16] Loss: 0.02193 +Epoch [345/4000] Training [5/16] Loss: 0.01668 +Epoch [345/4000] Training [6/16] Loss: 0.02080 +Epoch [345/4000] Training [7/16] Loss: 0.02048 +Epoch [345/4000] Training [8/16] Loss: 0.01859 +Epoch [345/4000] Training [9/16] Loss: 0.04093 +Epoch [345/4000] Training [10/16] Loss: 0.01985 +Epoch [345/4000] Training [11/16] Loss: 0.02064 +Epoch [345/4000] Training [12/16] Loss: 0.02512 +Epoch [345/4000] Training [13/16] Loss: 0.02421 +Epoch [345/4000] Training [14/16] Loss: 0.03119 +Epoch [345/4000] Training [15/16] Loss: 0.02237 +Epoch [345/4000] Training [16/16] Loss: 0.03022 +Epoch [345/4000] Training metric {'Train/mean dice_metric': 0.9825074076652527, 'Train/mean miou_metric': 0.9673093557357788, 'Train/mean f1': 0.9821081161499023, 'Train/mean precision': 0.9784854650497437, 'Train/mean recall': 0.9857577085494995, 'Train/mean hd95_metric': 3.9183993339538574} +Epoch [345/4000] Validation [1/4] Loss: 0.14052 focal_loss 0.08147 dice_loss 0.05906 +Epoch [345/4000] Validation [2/4] Loss: 0.45853 focal_loss 0.20124 dice_loss 0.25729 +Epoch [345/4000] Validation [3/4] Loss: 0.11451 focal_loss 0.04746 dice_loss 0.06705 +Epoch [345/4000] Validation [4/4] Loss: 0.17365 focal_loss 0.07853 dice_loss 0.09512 +Epoch [345/4000] Validation metric {'Val/mean dice_metric': 0.9568325281143188, 'Val/mean miou_metric': 0.9311870336532593, 'Val/mean f1': 0.9643005728721619, 'Val/mean precision': 0.9633169770240784, 'Val/mean recall': 0.965286135673523, 'Val/mean hd95_metric': 7.972235202789307} +Cheakpoint... +Epoch [345/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9568], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9568325281143188, 'Val/mean miou_metric': 0.9311870336532593, 'Val/mean f1': 0.9643005728721619, 'Val/mean precision': 0.9633169770240784, 'Val/mean recall': 0.965286135673523, 'Val/mean hd95_metric': 7.972235202789307} +Epoch [346/4000] Training [1/16] Loss: 0.02224 +Epoch [346/4000] Training [2/16] Loss: 0.01958 +Epoch [346/4000] Training [3/16] Loss: 0.01901 +Epoch [346/4000] Training [4/16] Loss: 0.01746 +Epoch [346/4000] Training [5/16] Loss: 0.01766 +Epoch [346/4000] Training [6/16] Loss: 0.01934 +Epoch [346/4000] Training [7/16] Loss: 0.07453 +Epoch [346/4000] Training [8/16] Loss: 0.02070 +Epoch [346/4000] Training [9/16] Loss: 0.02144 +Epoch [346/4000] Training [10/16] Loss: 0.02210 +Epoch [346/4000] Training [11/16] Loss: 0.01999 +Epoch [346/4000] Training [12/16] Loss: 0.02031 +Epoch [346/4000] Training [13/16] Loss: 0.03148 +Epoch [346/4000] Training [14/16] Loss: 0.02691 +Epoch [346/4000] Training [15/16] Loss: 0.01825 +Epoch [346/4000] Training [16/16] Loss: 0.01647 +Epoch [346/4000] Training metric {'Train/mean dice_metric': 0.9845626950263977, 'Train/mean miou_metric': 0.9698761701583862, 'Train/mean f1': 0.9820345044136047, 'Train/mean precision': 0.9772681593894958, 'Train/mean recall': 0.9868476390838623, 'Train/mean hd95_metric': 3.0844669342041016} +Epoch [346/4000] Validation [1/4] Loss: 0.17663 focal_loss 0.09599 dice_loss 0.08064 +Epoch [346/4000] Validation [2/4] Loss: 0.50914 focal_loss 0.20293 dice_loss 0.30621 +Epoch [346/4000] Validation [3/4] Loss: 0.16698 focal_loss 0.07808 dice_loss 0.08889 +Epoch [346/4000] Validation [4/4] Loss: 0.25206 focal_loss 0.12056 dice_loss 0.13150 +Epoch [346/4000] Validation metric {'Val/mean dice_metric': 0.959377646446228, 'Val/mean miou_metric': 0.9335128664970398, 'Val/mean f1': 0.9628968834877014, 'Val/mean precision': 0.9597041606903076, 'Val/mean recall': 0.9661109447479248, 'Val/mean hd95_metric': 8.836496353149414} +Cheakpoint... +Epoch [346/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9594], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959377646446228, 'Val/mean miou_metric': 0.9335128664970398, 'Val/mean f1': 0.9628968834877014, 'Val/mean precision': 0.9597041606903076, 'Val/mean recall': 0.9661109447479248, 'Val/mean hd95_metric': 8.836496353149414} +Epoch [347/4000] Training [1/16] Loss: 0.01969 +Epoch [347/4000] Training [2/16] Loss: 0.01739 +Epoch [347/4000] Training [3/16] Loss: 0.02389 +Epoch [347/4000] Training [4/16] Loss: 0.02091 +Epoch [347/4000] Training [5/16] Loss: 0.05228 +Epoch [347/4000] Training [6/16] Loss: 0.01550 +Epoch [347/4000] Training [7/16] Loss: 0.01556 +Epoch [347/4000] Training [8/16] Loss: 0.03161 +Epoch [347/4000] Training [9/16] Loss: 0.02012 +Epoch [347/4000] Training [10/16] Loss: 0.03196 +Epoch [347/4000] Training [11/16] Loss: 0.02651 +Epoch [347/4000] Training [12/16] Loss: 0.01647 +Epoch [347/4000] Training [13/16] Loss: 0.01882 +Epoch [347/4000] Training [14/16] Loss: 0.03009 +Epoch [347/4000] Training [15/16] Loss: 0.01975 +Epoch [347/4000] Training [16/16] Loss: 0.03010 +Epoch [347/4000] Training metric {'Train/mean dice_metric': 0.9828735589981079, 'Train/mean miou_metric': 0.9680923223495483, 'Train/mean f1': 0.9811778664588928, 'Train/mean precision': 0.9748410582542419, 'Train/mean recall': 0.9875975847244263, 'Train/mean hd95_metric': 3.1443848609924316} +Epoch [347/4000] Validation [1/4] Loss: 0.21645 focal_loss 0.12821 dice_loss 0.08825 +Epoch [347/4000] Validation [2/4] Loss: 0.28817 focal_loss 0.09042 dice_loss 0.19775 +Epoch [347/4000] Validation [3/4] Loss: 0.13355 focal_loss 0.05018 dice_loss 0.08337 +Epoch [347/4000] Validation [4/4] Loss: 0.23915 focal_loss 0.10682 dice_loss 0.13233 +Epoch [347/4000] Validation metric {'Val/mean dice_metric': 0.9581357836723328, 'Val/mean miou_metric': 0.933200478553772, 'Val/mean f1': 0.9627581834793091, 'Val/mean precision': 0.9571183323860168, 'Val/mean recall': 0.9684649705886841, 'Val/mean hd95_metric': 8.128138542175293} +Cheakpoint... +Epoch [347/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9581], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9581357836723328, 'Val/mean miou_metric': 0.933200478553772, 'Val/mean f1': 0.9627581834793091, 'Val/mean precision': 0.9571183323860168, 'Val/mean recall': 0.9684649705886841, 'Val/mean hd95_metric': 8.128138542175293} +Epoch [348/4000] Training [1/16] Loss: 0.02002 +Epoch [348/4000] Training [2/16] Loss: 0.02918 +Epoch [348/4000] Training [3/16] Loss: 0.01935 +Epoch [348/4000] Training [4/16] Loss: 0.02055 +Epoch [348/4000] Training [5/16] Loss: 0.02938 +Epoch [348/4000] Training [6/16] Loss: 0.01691 +Epoch [348/4000] Training [7/16] Loss: 0.01534 +Epoch [348/4000] Training [8/16] Loss: 0.02511 +Epoch [348/4000] Training [9/16] Loss: 0.02358 +Epoch [348/4000] Training [10/16] Loss: 0.02145 +Epoch [348/4000] Training [11/16] Loss: 0.01435 +Epoch [348/4000] Training [12/16] Loss: 0.01896 +Epoch [348/4000] Training [13/16] Loss: 0.02183 +Epoch [348/4000] Training [14/16] Loss: 0.01905 +Epoch [348/4000] Training [15/16] Loss: 0.01667 +Epoch [348/4000] Training [16/16] Loss: 0.02576 +Epoch [348/4000] Training metric {'Train/mean dice_metric': 0.9849714040756226, 'Train/mean miou_metric': 0.9704565405845642, 'Train/mean f1': 0.9828693270683289, 'Train/mean precision': 0.9786452054977417, 'Train/mean recall': 0.9871300458908081, 'Train/mean hd95_metric': 2.431433916091919} +Epoch [348/4000] Validation [1/4] Loss: 0.15375 focal_loss 0.08962 dice_loss 0.06413 +Epoch [348/4000] Validation [2/4] Loss: 0.24688 focal_loss 0.09277 dice_loss 0.15411 +Epoch [348/4000] Validation [3/4] Loss: 0.08766 focal_loss 0.03689 dice_loss 0.05077 +Epoch [348/4000] Validation [4/4] Loss: 0.36081 focal_loss 0.20010 dice_loss 0.16071 +Epoch [348/4000] Validation metric {'Val/mean dice_metric': 0.962898850440979, 'Val/mean miou_metric': 0.9384007453918457, 'Val/mean f1': 0.9662061333656311, 'Val/mean precision': 0.9608538150787354, 'Val/mean recall': 0.9716184139251709, 'Val/mean hd95_metric': 6.630251884460449} +Cheakpoint... +Epoch [348/4000] best acc:tensor([0.9667], device='cuda:0'), Now : mean acc: tensor([0.9629], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.962898850440979, 'Val/mean miou_metric': 0.9384007453918457, 'Val/mean f1': 0.9662061333656311, 'Val/mean precision': 0.9608538150787354, 'Val/mean recall': 0.9716184139251709, 'Val/mean hd95_metric': 6.630251884460449} +Epoch [349/4000] Training [1/16] Loss: 0.01998 +Epoch [349/4000] Training [2/16] Loss: 0.01892 +Epoch [349/4000] Training [3/16] Loss: 0.01772 +Epoch [349/4000] Training [4/16] Loss: 0.01541 +Epoch [349/4000] Training [5/16] Loss: 0.01552 +Epoch [349/4000] Training [6/16] Loss: 0.01596 +Epoch [349/4000] Training [7/16] Loss: 0.01719 +Epoch [349/4000] Training [8/16] Loss: 0.01688 +Epoch [349/4000] Training [9/16] Loss: 0.01968 +Epoch [349/4000] Training [10/16] Loss: 0.01810 +Epoch [349/4000] Training [11/16] Loss: 0.01788 +Epoch [349/4000] Training [12/16] Loss: 0.01755 +Epoch [349/4000] Training [13/16] Loss: 0.01654 +Epoch [349/4000] Training [14/16] Loss: 0.01424 +Epoch [349/4000] Training [15/16] Loss: 0.01918 +Epoch [349/4000] Training [16/16] Loss: 0.02226 +Epoch [349/4000] Training metric {'Train/mean dice_metric': 0.9875759482383728, 'Train/mean miou_metric': 0.9752991199493408, 'Train/mean f1': 0.9852213859558105, 'Train/mean precision': 0.9806371927261353, 'Train/mean recall': 0.9898486733436584, 'Train/mean hd95_metric': 1.9739553928375244} +Epoch [349/4000] Validation [1/4] Loss: 0.13666 focal_loss 0.07565 dice_loss 0.06101 +Epoch [349/4000] Validation [2/4] Loss: 0.19685 focal_loss 0.07327 dice_loss 0.12358 +Epoch [349/4000] Validation [3/4] Loss: 0.17035 focal_loss 0.09292 dice_loss 0.07744 +Epoch [349/4000] Validation [4/4] Loss: 0.20531 focal_loss 0.09291 dice_loss 0.11239 +Epoch [349/4000] Validation metric {'Val/mean dice_metric': 0.9676544070243835, 'Val/mean miou_metric': 0.9448426961898804, 'Val/mean f1': 0.9693459272384644, 'Val/mean precision': 0.964228093624115, 'Val/mean recall': 0.9745184183120728, 'Val/mean hd95_metric': 6.173360347747803} +Cheakpoint... +Epoch [349/4000] best acc:tensor([0.9677], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676544070243835, 'Val/mean miou_metric': 0.9448426961898804, 'Val/mean f1': 0.9693459272384644, 'Val/mean precision': 0.964228093624115, 'Val/mean recall': 0.9745184183120728, 'Val/mean hd95_metric': 6.173360347747803} +Epoch [350/4000] Training [1/16] Loss: 0.01772 +Epoch [350/4000] Training [2/16] Loss: 0.01561 +Epoch [350/4000] Training [3/16] Loss: 0.01484 +Epoch [350/4000] Training [4/16] Loss: 0.01689 +Epoch [350/4000] Training [5/16] Loss: 0.01827 +Epoch [350/4000] Training [6/16] Loss: 0.01462 +Epoch [350/4000] Training [7/16] Loss: 0.01693 +Epoch [350/4000] Training [8/16] Loss: 0.02580 +Epoch [350/4000] Training [9/16] Loss: 0.01485 +Epoch [350/4000] Training [10/16] Loss: 0.01754 +Epoch [350/4000] Training [11/16] Loss: 0.01800 +Epoch [350/4000] Training [12/16] Loss: 0.01944 +Epoch [350/4000] Training [13/16] Loss: 0.01522 +Epoch [350/4000] Training [14/16] Loss: 0.01328 +Epoch [350/4000] Training [15/16] Loss: 0.01947 +Epoch [350/4000] Training [16/16] Loss: 0.01428 +Epoch [350/4000] Training metric {'Train/mean dice_metric': 0.987891674041748, 'Train/mean miou_metric': 0.9759845733642578, 'Train/mean f1': 0.9856022000312805, 'Train/mean precision': 0.9811671376228333, 'Train/mean recall': 0.9900774955749512, 'Train/mean hd95_metric': 1.6150896549224854} +Epoch [350/4000] Validation [1/4] Loss: 0.16090 focal_loss 0.09759 dice_loss 0.06331 +Epoch [350/4000] Validation [2/4] Loss: 0.19148 focal_loss 0.07942 dice_loss 0.11206 +Epoch [350/4000] Validation [3/4] Loss: 0.17398 focal_loss 0.10152 dice_loss 0.07246 +Epoch [350/4000] Validation [4/4] Loss: 0.18532 focal_loss 0.09898 dice_loss 0.08635 +Epoch [350/4000] Validation metric {'Val/mean dice_metric': 0.9681329727172852, 'Val/mean miou_metric': 0.9459183812141418, 'Val/mean f1': 0.9704068899154663, 'Val/mean precision': 0.966781735420227, 'Val/mean recall': 0.9740593433380127, 'Val/mean hd95_metric': 5.496726036071777} +Cheakpoint... +Epoch [350/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681329727172852, 'Val/mean miou_metric': 0.9459183812141418, 'Val/mean f1': 0.9704068899154663, 'Val/mean precision': 0.966781735420227, 'Val/mean recall': 0.9740593433380127, 'Val/mean hd95_metric': 5.496726036071777} +Epoch [351/4000] Training [1/16] Loss: 0.01272 +Epoch [351/4000] Training [2/16] Loss: 0.01344 +Epoch [351/4000] Training [3/16] Loss: 0.01661 +Epoch [351/4000] Training [4/16] Loss: 0.01535 +Epoch [351/4000] Training [5/16] Loss: 0.01651 +Epoch [351/4000] Training [6/16] Loss: 0.01776 +Epoch [351/4000] Training [7/16] Loss: 0.01459 +Epoch [351/4000] Training [8/16] Loss: 0.01695 +Epoch [351/4000] Training [9/16] Loss: 0.01599 +Epoch [351/4000] Training [10/16] Loss: 0.01456 +Epoch [351/4000] Training [11/16] Loss: 0.01958 +Epoch [351/4000] Training [12/16] Loss: 0.01463 +Epoch [351/4000] Training [13/16] Loss: 0.02446 +Epoch [351/4000] Training [14/16] Loss: 0.01352 +Epoch [351/4000] Training [15/16] Loss: 0.01372 +Epoch [351/4000] Training [16/16] Loss: 0.06480 +Epoch [351/4000] Training metric {'Train/mean dice_metric': 0.9877039194107056, 'Train/mean miou_metric': 0.975753128528595, 'Train/mean f1': 0.9853453636169434, 'Train/mean precision': 0.9806352257728577, 'Train/mean recall': 0.9901009202003479, 'Train/mean hd95_metric': 1.5223053693771362} +Epoch [351/4000] Validation [1/4] Loss: 0.18574 focal_loss 0.11490 dice_loss 0.07084 +Epoch [351/4000] Validation [2/4] Loss: 0.22155 focal_loss 0.10194 dice_loss 0.11961 +Epoch [351/4000] Validation [3/4] Loss: 0.11429 focal_loss 0.05658 dice_loss 0.05771 +Epoch [351/4000] Validation [4/4] Loss: 0.24824 focal_loss 0.11695 dice_loss 0.13130 +Epoch [351/4000] Validation metric {'Val/mean dice_metric': 0.9659503102302551, 'Val/mean miou_metric': 0.9432156682014465, 'Val/mean f1': 0.9689384698867798, 'Val/mean precision': 0.9648138880729675, 'Val/mean recall': 0.9730983972549438, 'Val/mean hd95_metric': 5.825826168060303} +Cheakpoint... +Epoch [351/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659503102302551, 'Val/mean miou_metric': 0.9432156682014465, 'Val/mean f1': 0.9689384698867798, 'Val/mean precision': 0.9648138880729675, 'Val/mean recall': 0.9730983972549438, 'Val/mean hd95_metric': 5.825826168060303} +Epoch [352/4000] Training [1/16] Loss: 0.01321 +Epoch [352/4000] Training [2/16] Loss: 0.01619 +Epoch [352/4000] Training [3/16] Loss: 0.03218 +Epoch [352/4000] Training [4/16] Loss: 0.01474 +Epoch [352/4000] Training [5/16] Loss: 0.01140 +Epoch [352/4000] Training [6/16] Loss: 0.01335 +Epoch [352/4000] Training [7/16] Loss: 0.01429 +Epoch [352/4000] Training [8/16] Loss: 0.01710 +Epoch [352/4000] Training [9/16] Loss: 0.01925 +Epoch [352/4000] Training [10/16] Loss: 0.01896 +Epoch [352/4000] Training [11/16] Loss: 0.02133 +Epoch [352/4000] Training [12/16] Loss: 0.01946 +Epoch [352/4000] Training [13/16] Loss: 0.01536 +Epoch [352/4000] Training [14/16] Loss: 0.01519 +Epoch [352/4000] Training [15/16] Loss: 0.02646 +Epoch [352/4000] Training [16/16] Loss: 0.01593 +Epoch [352/4000] Training metric {'Train/mean dice_metric': 0.9883484244346619, 'Train/mean miou_metric': 0.9768152832984924, 'Train/mean f1': 0.9857829809188843, 'Train/mean precision': 0.9815219044685364, 'Train/mean recall': 0.9900811910629272, 'Train/mean hd95_metric': 1.4625240564346313} +Epoch [352/4000] Validation [1/4] Loss: 0.26270 focal_loss 0.16436 dice_loss 0.09835 +Epoch [352/4000] Validation [2/4] Loss: 0.23552 focal_loss 0.08957 dice_loss 0.14595 +Epoch [352/4000] Validation [3/4] Loss: 0.16524 focal_loss 0.07533 dice_loss 0.08990 +Epoch [352/4000] Validation [4/4] Loss: 0.30951 focal_loss 0.16634 dice_loss 0.14317 +Epoch [352/4000] Validation metric {'Val/mean dice_metric': 0.965854287147522, 'Val/mean miou_metric': 0.943320095539093, 'Val/mean f1': 0.9686635732650757, 'Val/mean precision': 0.9667267799377441, 'Val/mean recall': 0.9706080555915833, 'Val/mean hd95_metric': 5.783731937408447} +Cheakpoint... +Epoch [352/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965854287147522, 'Val/mean miou_metric': 0.943320095539093, 'Val/mean f1': 0.9686635732650757, 'Val/mean precision': 0.9667267799377441, 'Val/mean recall': 0.9706080555915833, 'Val/mean hd95_metric': 5.783731937408447} +Epoch [353/4000] Training [1/16] Loss: 0.01309 +Epoch [353/4000] Training [2/16] Loss: 0.01627 +Epoch [353/4000] Training [3/16] Loss: 0.01982 +Epoch [353/4000] Training [4/16] Loss: 0.01462 +Epoch [353/4000] Training [5/16] Loss: 0.01647 +Epoch [353/4000] Training [6/16] Loss: 0.01520 +Epoch [353/4000] Training [7/16] Loss: 0.02416 +Epoch [353/4000] Training [8/16] Loss: 0.01485 +Epoch [353/4000] Training [9/16] Loss: 0.01193 +Epoch [353/4000] Training [10/16] Loss: 0.01593 +Epoch [353/4000] Training [11/16] Loss: 0.01435 +Epoch [353/4000] Training [12/16] Loss: 0.01313 +Epoch [353/4000] Training [13/16] Loss: 0.01584 +Epoch [353/4000] Training [14/16] Loss: 0.01664 +Epoch [353/4000] Training [15/16] Loss: 0.01661 +Epoch [353/4000] Training [16/16] Loss: 0.02097 +Epoch [353/4000] Training metric {'Train/mean dice_metric': 0.9874758720397949, 'Train/mean miou_metric': 0.9752168655395508, 'Train/mean f1': 0.9852608442306519, 'Train/mean precision': 0.9807614684104919, 'Train/mean recall': 0.9898017048835754, 'Train/mean hd95_metric': 2.063713788986206} +Epoch [353/4000] Validation [1/4] Loss: 0.22638 focal_loss 0.13699 dice_loss 0.08940 +Epoch [353/4000] Validation [2/4] Loss: 0.46071 focal_loss 0.18711 dice_loss 0.27360 +Epoch [353/4000] Validation [3/4] Loss: 0.10650 focal_loss 0.05047 dice_loss 0.05603 +Epoch [353/4000] Validation [4/4] Loss: 0.24993 focal_loss 0.13174 dice_loss 0.11818 +Epoch [353/4000] Validation metric {'Val/mean dice_metric': 0.9635385274887085, 'Val/mean miou_metric': 0.9405926465988159, 'Val/mean f1': 0.967685341835022, 'Val/mean precision': 0.9649671912193298, 'Val/mean recall': 0.9704188704490662, 'Val/mean hd95_metric': 6.363794326782227} +Cheakpoint... +Epoch [353/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9635], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9635385274887085, 'Val/mean miou_metric': 0.9405926465988159, 'Val/mean f1': 0.967685341835022, 'Val/mean precision': 0.9649671912193298, 'Val/mean recall': 0.9704188704490662, 'Val/mean hd95_metric': 6.363794326782227} +Epoch [354/4000] Training [1/16] Loss: 0.02234 +Epoch [354/4000] Training [2/16] Loss: 0.01315 +Epoch [354/4000] Training [3/16] Loss: 0.01479 +Epoch [354/4000] Training [4/16] Loss: 0.01615 +Epoch [354/4000] Training [5/16] Loss: 0.02174 +Epoch [354/4000] Training [6/16] Loss: 0.02071 +Epoch [354/4000] Training [7/16] Loss: 0.01904 +Epoch [354/4000] Training [8/16] Loss: 0.02198 +Epoch [354/4000] Training [9/16] Loss: 0.01965 +Epoch [354/4000] Training [10/16] Loss: 0.01884 +Epoch [354/4000] Training [11/16] Loss: 0.01239 +Epoch [354/4000] Training [12/16] Loss: 0.01871 +Epoch [354/4000] Training [13/16] Loss: 0.01803 +Epoch [354/4000] Training [14/16] Loss: 0.02458 +Epoch [354/4000] Training [15/16] Loss: 0.01970 +Epoch [354/4000] Training [16/16] Loss: 0.01868 +Epoch [354/4000] Training metric {'Train/mean dice_metric': 0.9861061573028564, 'Train/mean miou_metric': 0.9725996851921082, 'Train/mean f1': 0.9836068153381348, 'Train/mean precision': 0.9790084362030029, 'Train/mean recall': 0.9882486462593079, 'Train/mean hd95_metric': 2.0191311836242676} +Epoch [354/4000] Validation [1/4] Loss: 0.12594 focal_loss 0.06861 dice_loss 0.05733 +Epoch [354/4000] Validation [2/4] Loss: 0.32597 focal_loss 0.14372 dice_loss 0.18225 +Epoch [354/4000] Validation [3/4] Loss: 0.13715 focal_loss 0.07113 dice_loss 0.06602 +Epoch [354/4000] Validation [4/4] Loss: 0.23880 focal_loss 0.11666 dice_loss 0.12214 +Epoch [354/4000] Validation metric {'Val/mean dice_metric': 0.9633867144584656, 'Val/mean miou_metric': 0.9398676753044128, 'Val/mean f1': 0.9663170576095581, 'Val/mean precision': 0.9563897848129272, 'Val/mean recall': 0.976452648639679, 'Val/mean hd95_metric': 6.863646507263184} +Cheakpoint... +Epoch [354/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633867144584656, 'Val/mean miou_metric': 0.9398676753044128, 'Val/mean f1': 0.9663170576095581, 'Val/mean precision': 0.9563897848129272, 'Val/mean recall': 0.976452648639679, 'Val/mean hd95_metric': 6.863646507263184} +Epoch [355/4000] Training [1/16] Loss: 0.01793 +Epoch [355/4000] Training [2/16] Loss: 0.02272 +Epoch [355/4000] Training [3/16] Loss: 0.02735 +Epoch [355/4000] Training [4/16] Loss: 0.01520 +Epoch [355/4000] Training [5/16] Loss: 0.01360 +Epoch [355/4000] Training [6/16] Loss: 0.01836 +Epoch [355/4000] Training [7/16] Loss: 0.01896 +Epoch [355/4000] Training [8/16] Loss: 0.01735 +Epoch [355/4000] Training [9/16] Loss: 0.01838 +Epoch [355/4000] Training [10/16] Loss: 0.01765 +Epoch [355/4000] Training [11/16] Loss: 0.01839 +Epoch [355/4000] Training [12/16] Loss: 0.01621 +Epoch [355/4000] Training [13/16] Loss: 0.01638 +Epoch [355/4000] Training [14/16] Loss: 0.01669 +Epoch [355/4000] Training [15/16] Loss: 0.01529 +Epoch [355/4000] Training [16/16] Loss: 0.03225 +Epoch [355/4000] Training metric {'Train/mean dice_metric': 0.9872342348098755, 'Train/mean miou_metric': 0.9747096300125122, 'Train/mean f1': 0.9848096966743469, 'Train/mean precision': 0.9801908135414124, 'Train/mean recall': 0.9894722700119019, 'Train/mean hd95_metric': 1.7990115880966187} +Epoch [355/4000] Validation [1/4] Loss: 0.15434 focal_loss 0.08575 dice_loss 0.06859 +Epoch [355/4000] Validation [2/4] Loss: 0.35788 focal_loss 0.15547 dice_loss 0.20241 +Epoch [355/4000] Validation [3/4] Loss: 0.11212 focal_loss 0.04984 dice_loss 0.06228 +Epoch [355/4000] Validation [4/4] Loss: 0.27568 focal_loss 0.14819 dice_loss 0.12748 +Epoch [355/4000] Validation metric {'Val/mean dice_metric': 0.9633167386054993, 'Val/mean miou_metric': 0.9403444528579712, 'Val/mean f1': 0.9681790471076965, 'Val/mean precision': 0.9639053344726562, 'Val/mean recall': 0.9724907875061035, 'Val/mean hd95_metric': 6.172646522521973} +Cheakpoint... +Epoch [355/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633167386054993, 'Val/mean miou_metric': 0.9403444528579712, 'Val/mean f1': 0.9681790471076965, 'Val/mean precision': 0.9639053344726562, 'Val/mean recall': 0.9724907875061035, 'Val/mean hd95_metric': 6.172646522521973} +Epoch [356/4000] Training [1/16] Loss: 0.01756 +Epoch [356/4000] Training [2/16] Loss: 0.02098 +Epoch [356/4000] Training [3/16] Loss: 0.01151 +Epoch [356/4000] Training [4/16] Loss: 0.01227 +Epoch [356/4000] Training [5/16] Loss: 0.01831 +Epoch [356/4000] Training [6/16] Loss: 0.01855 +Epoch [356/4000] Training [7/16] Loss: 0.01937 +Epoch [356/4000] Training [8/16] Loss: 0.01725 +Epoch [356/4000] Training [9/16] Loss: 0.01621 +Epoch [356/4000] Training [10/16] Loss: 0.02236 +Epoch [356/4000] Training [11/16] Loss: 0.01934 +Epoch [356/4000] Training [12/16] Loss: 0.02017 +Epoch [356/4000] Training [13/16] Loss: 0.01599 +Epoch [356/4000] Training [14/16] Loss: 0.01679 +Epoch [356/4000] Training [15/16] Loss: 0.01956 +Epoch [356/4000] Training [16/16] Loss: 0.01636 +Epoch [356/4000] Training metric {'Train/mean dice_metric': 0.9871410727500916, 'Train/mean miou_metric': 0.9744961261749268, 'Train/mean f1': 0.9844823479652405, 'Train/mean precision': 0.9797759652137756, 'Train/mean recall': 0.989234209060669, 'Train/mean hd95_metric': 1.7452061176300049} +Epoch [356/4000] Validation [1/4] Loss: 0.13215 focal_loss 0.07388 dice_loss 0.05827 +Epoch [356/4000] Validation [2/4] Loss: 0.31107 focal_loss 0.11495 dice_loss 0.19612 +Epoch [356/4000] Validation [3/4] Loss: 0.12561 focal_loss 0.05502 dice_loss 0.07059 +Epoch [356/4000] Validation [4/4] Loss: 0.50016 focal_loss 0.29655 dice_loss 0.20361 +Epoch [356/4000] Validation metric {'Val/mean dice_metric': 0.9646976590156555, 'Val/mean miou_metric': 0.9410964846611023, 'Val/mean f1': 0.9663863778114319, 'Val/mean precision': 0.9603186845779419, 'Val/mean recall': 0.9725311994552612, 'Val/mean hd95_metric': 6.534864902496338} +Cheakpoint... +Epoch [356/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646976590156555, 'Val/mean miou_metric': 0.9410964846611023, 'Val/mean f1': 0.9663863778114319, 'Val/mean precision': 0.9603186845779419, 'Val/mean recall': 0.9725311994552612, 'Val/mean hd95_metric': 6.534864902496338} +Epoch [357/4000] Training [1/16] Loss: 0.01839 +Epoch [357/4000] Training [2/16] Loss: 0.01798 +Epoch [357/4000] Training [3/16] Loss: 0.01720 +Epoch [357/4000] Training [4/16] Loss: 0.01479 +Epoch [357/4000] Training [5/16] Loss: 0.01341 +Epoch [357/4000] Training [6/16] Loss: 0.01776 +Epoch [357/4000] Training [7/16] Loss: 0.01741 +Epoch [357/4000] Training [8/16] Loss: 0.01995 +Epoch [357/4000] Training [9/16] Loss: 0.01763 +Epoch [357/4000] Training [10/16] Loss: 0.01493 +Epoch [357/4000] Training [11/16] Loss: 0.01850 +Epoch [357/4000] Training [12/16] Loss: 0.01705 +Epoch [357/4000] Training [13/16] Loss: 0.01922 +Epoch [357/4000] Training [14/16] Loss: 0.02370 +Epoch [357/4000] Training [15/16] Loss: 0.02032 +Epoch [357/4000] Training [16/16] Loss: 0.02512 +Epoch [357/4000] Training metric {'Train/mean dice_metric': 0.9868065714836121, 'Train/mean miou_metric': 0.974024772644043, 'Train/mean f1': 0.9850362539291382, 'Train/mean precision': 0.980904757976532, 'Train/mean recall': 0.9892026782035828, 'Train/mean hd95_metric': 2.85026216506958} +Epoch [357/4000] Validation [1/4] Loss: 0.14073 focal_loss 0.07557 dice_loss 0.06516 +Epoch [357/4000] Validation [2/4] Loss: 0.21769 focal_loss 0.07722 dice_loss 0.14048 +Epoch [357/4000] Validation [3/4] Loss: 0.11067 focal_loss 0.05100 dice_loss 0.05967 +Epoch [357/4000] Validation [4/4] Loss: 0.26871 focal_loss 0.14960 dice_loss 0.11911 +Epoch [357/4000] Validation metric {'Val/mean dice_metric': 0.9599359631538391, 'Val/mean miou_metric': 0.9366214871406555, 'Val/mean f1': 0.9648557305335999, 'Val/mean precision': 0.9607836008071899, 'Val/mean recall': 0.968962550163269, 'Val/mean hd95_metric': 8.016952514648438} +Cheakpoint... +Epoch [357/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599359631538391, 'Val/mean miou_metric': 0.9366214871406555, 'Val/mean f1': 0.9648557305335999, 'Val/mean precision': 0.9607836008071899, 'Val/mean recall': 0.968962550163269, 'Val/mean hd95_metric': 8.016952514648438} +Epoch [358/4000] Training [1/16] Loss: 0.01900 +Epoch [358/4000] Training [2/16] Loss: 0.01652 +Epoch [358/4000] Training [3/16] Loss: 0.01546 +Epoch [358/4000] Training [4/16] Loss: 0.01726 +Epoch [358/4000] Training [5/16] Loss: 0.02798 +Epoch [358/4000] Training [6/16] Loss: 0.02398 +Epoch [358/4000] Training [7/16] Loss: 0.02452 +Epoch [358/4000] Training [8/16] Loss: 0.02261 +Epoch [358/4000] Training [9/16] Loss: 0.02213 +Epoch [358/4000] Training [10/16] Loss: 0.01651 +Epoch [358/4000] Training [11/16] Loss: 0.01828 +Epoch [358/4000] Training [12/16] Loss: 0.02006 +Epoch [358/4000] Training [13/16] Loss: 0.01965 +Epoch [358/4000] Training [14/16] Loss: 0.01532 +Epoch [358/4000] Training [15/16] Loss: 0.02756 +Epoch [358/4000] Training [16/16] Loss: 0.04337 +Epoch [358/4000] Training metric {'Train/mean dice_metric': 0.9851645231246948, 'Train/mean miou_metric': 0.970833420753479, 'Train/mean f1': 0.9828840494155884, 'Train/mean precision': 0.9786166548728943, 'Train/mean recall': 0.9871888756752014, 'Train/mean hd95_metric': 2.8621745109558105} +Epoch [358/4000] Validation [1/4] Loss: 0.22685 focal_loss 0.13116 dice_loss 0.09569 +Epoch [358/4000] Validation [2/4] Loss: 0.37143 focal_loss 0.15713 dice_loss 0.21430 +Epoch [358/4000] Validation [3/4] Loss: 0.13284 focal_loss 0.06436 dice_loss 0.06848 +Epoch [358/4000] Validation [4/4] Loss: 0.48433 focal_loss 0.28348 dice_loss 0.20085 +Epoch [358/4000] Validation metric {'Val/mean dice_metric': 0.9616767764091492, 'Val/mean miou_metric': 0.9371930956840515, 'Val/mean f1': 0.9635785818099976, 'Val/mean precision': 0.9581805467605591, 'Val/mean recall': 0.9690378308296204, 'Val/mean hd95_metric': 7.972486972808838} +Cheakpoint... +Epoch [358/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616767764091492, 'Val/mean miou_metric': 0.9371930956840515, 'Val/mean f1': 0.9635785818099976, 'Val/mean precision': 0.9581805467605591, 'Val/mean recall': 0.9690378308296204, 'Val/mean hd95_metric': 7.972486972808838} +Epoch [359/4000] Training [1/16] Loss: 0.01807 +Epoch [359/4000] Training [2/16] Loss: 0.02002 +Epoch [359/4000] Training [3/16] Loss: 0.02049 +Epoch [359/4000] Training [4/16] Loss: 0.01735 +Epoch [359/4000] Training [5/16] Loss: 0.01733 +Epoch [359/4000] Training [6/16] Loss: 0.01922 +Epoch [359/4000] Training [7/16] Loss: 0.01956 +Epoch [359/4000] Training [8/16] Loss: 0.01863 +Epoch [359/4000] Training [9/16] Loss: 0.02258 +Epoch [359/4000] Training [10/16] Loss: 0.02219 +Epoch [359/4000] Training [11/16] Loss: 0.01717 +Epoch [359/4000] Training [12/16] Loss: 0.02105 +Epoch [359/4000] Training [13/16] Loss: 0.01271 +Epoch [359/4000] Training [14/16] Loss: 0.01668 +Epoch [359/4000] Training [15/16] Loss: 0.02193 +Epoch [359/4000] Training [16/16] Loss: 0.01345 +Epoch [359/4000] Training metric {'Train/mean dice_metric': 0.9854879379272461, 'Train/mean miou_metric': 0.9717123508453369, 'Train/mean f1': 0.9829232692718506, 'Train/mean precision': 0.9782627820968628, 'Train/mean recall': 0.9876283407211304, 'Train/mean hd95_metric': 2.506312608718872} +Epoch [359/4000] Validation [1/4] Loss: 0.14475 focal_loss 0.08283 dice_loss 0.06192 +Epoch [359/4000] Validation [2/4] Loss: 0.47622 focal_loss 0.22213 dice_loss 0.25409 +Epoch [359/4000] Validation [3/4] Loss: 0.13026 focal_loss 0.05874 dice_loss 0.07152 +Epoch [359/4000] Validation [4/4] Loss: 0.25986 focal_loss 0.14172 dice_loss 0.11814 +Epoch [359/4000] Validation metric {'Val/mean dice_metric': 0.9608262181282043, 'Val/mean miou_metric': 0.9371698498725891, 'Val/mean f1': 0.9655129313468933, 'Val/mean precision': 0.9627140164375305, 'Val/mean recall': 0.9683282375335693, 'Val/mean hd95_metric': 7.288321018218994} +Cheakpoint... +Epoch [359/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608262181282043, 'Val/mean miou_metric': 0.9371698498725891, 'Val/mean f1': 0.9655129313468933, 'Val/mean precision': 0.9627140164375305, 'Val/mean recall': 0.9683282375335693, 'Val/mean hd95_metric': 7.288321018218994} +Epoch [360/4000] Training [1/16] Loss: 0.02187 +Epoch [360/4000] Training [2/16] Loss: 0.01702 +Epoch [360/4000] Training [3/16] Loss: 0.02339 +Epoch [360/4000] Training [4/16] Loss: 0.01659 +Epoch [360/4000] Training [5/16] Loss: 0.02428 +Epoch [360/4000] Training [6/16] Loss: 0.02013 +Epoch [360/4000] Training [7/16] Loss: 0.04247 +Epoch [360/4000] Training [8/16] Loss: 0.02211 +Epoch [360/4000] Training [9/16] Loss: 0.03992 +Epoch [360/4000] Training [10/16] Loss: 0.01626 +Epoch [360/4000] Training [11/16] Loss: 0.01789 +Epoch [360/4000] Training [12/16] Loss: 0.02195 +Epoch [360/4000] Training [13/16] Loss: 0.02180 +Epoch [360/4000] Training [14/16] Loss: 0.02909 +Epoch [360/4000] Training [15/16] Loss: 0.02329 +Epoch [360/4000] Training [16/16] Loss: 0.03283 +Epoch [360/4000] Training metric {'Train/mean dice_metric': 0.9840753078460693, 'Train/mean miou_metric': 0.9688774347305298, 'Train/mean f1': 0.9810732007026672, 'Train/mean precision': 0.9772330522537231, 'Train/mean recall': 0.9849435687065125, 'Train/mean hd95_metric': 3.0064995288848877} +Epoch [360/4000] Validation [1/4] Loss: 0.35027 focal_loss 0.22424 dice_loss 0.12603 +Epoch [360/4000] Validation [2/4] Loss: 0.46196 focal_loss 0.19844 dice_loss 0.26352 +Epoch [360/4000] Validation [3/4] Loss: 0.12320 focal_loss 0.05494 dice_loss 0.06826 +Epoch [360/4000] Validation [4/4] Loss: 0.18873 focal_loss 0.08335 dice_loss 0.10539 +Epoch [360/4000] Validation metric {'Val/mean dice_metric': 0.9561057090759277, 'Val/mean miou_metric': 0.9307743310928345, 'Val/mean f1': 0.9603757858276367, 'Val/mean precision': 0.9556217193603516, 'Val/mean recall': 0.9651774168014526, 'Val/mean hd95_metric': 8.868703842163086} +Cheakpoint... +Epoch [360/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9561], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9561057090759277, 'Val/mean miou_metric': 0.9307743310928345, 'Val/mean f1': 0.9603757858276367, 'Val/mean precision': 0.9556217193603516, 'Val/mean recall': 0.9651774168014526, 'Val/mean hd95_metric': 8.868703842163086} +Epoch [361/4000] Training [1/16] Loss: 0.02573 +Epoch [361/4000] Training [2/16] Loss: 0.02020 +Epoch [361/4000] Training [3/16] Loss: 0.02242 +Epoch [361/4000] Training [4/16] Loss: 0.01903 +Epoch [361/4000] Training [5/16] Loss: 0.02689 +Epoch [361/4000] Training [6/16] Loss: 0.01940 +Epoch [361/4000] Training [7/16] Loss: 0.02156 +Epoch [361/4000] Training [8/16] Loss: 0.02589 +Epoch [361/4000] Training [9/16] Loss: 0.01966 +Epoch [361/4000] Training [10/16] Loss: 0.01699 +Epoch [361/4000] Training [11/16] Loss: 0.01926 +Epoch [361/4000] Training [12/16] Loss: 0.01818 +Epoch [361/4000] Training [13/16] Loss: 0.01693 +Epoch [361/4000] Training [14/16] Loss: 0.02280 +Epoch [361/4000] Training [15/16] Loss: 0.02156 +Epoch [361/4000] Training [16/16] Loss: 0.01676 +Epoch [361/4000] Training metric {'Train/mean dice_metric': 0.9838483333587646, 'Train/mean miou_metric': 0.9684836864471436, 'Train/mean f1': 0.9816086292266846, 'Train/mean precision': 0.9768567681312561, 'Train/mean recall': 0.9864069819450378, 'Train/mean hd95_metric': 2.5548319816589355} +Epoch [361/4000] Validation [1/4] Loss: 0.49911 focal_loss 0.38789 dice_loss 0.11122 +Epoch [361/4000] Validation [2/4] Loss: 0.37074 focal_loss 0.15774 dice_loss 0.21300 +Epoch [361/4000] Validation [3/4] Loss: 0.15572 focal_loss 0.06557 dice_loss 0.09015 +Epoch [361/4000] Validation [4/4] Loss: 0.23984 focal_loss 0.12589 dice_loss 0.11395 +Epoch [361/4000] Validation metric {'Val/mean dice_metric': 0.9595986604690552, 'Val/mean miou_metric': 0.9325596690177917, 'Val/mean f1': 0.9604283571243286, 'Val/mean precision': 0.954717218875885, 'Val/mean recall': 0.9662082195281982, 'Val/mean hd95_metric': 8.410290718078613} +Cheakpoint... +Epoch [361/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9596], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9595986604690552, 'Val/mean miou_metric': 0.9325596690177917, 'Val/mean f1': 0.9604283571243286, 'Val/mean precision': 0.954717218875885, 'Val/mean recall': 0.9662082195281982, 'Val/mean hd95_metric': 8.410290718078613} +Epoch [362/4000] Training [1/16] Loss: 0.03091 +Epoch [362/4000] Training [2/16] Loss: 0.02127 +Epoch [362/4000] Training [3/16] Loss: 0.02301 +Epoch [362/4000] Training [4/16] Loss: 0.02201 +Epoch [362/4000] Training [5/16] Loss: 0.02020 +Epoch [362/4000] Training [6/16] Loss: 0.02065 +Epoch [362/4000] Training [7/16] Loss: 0.03113 +Epoch [362/4000] Training [8/16] Loss: 0.01406 +Epoch [362/4000] Training [9/16] Loss: 0.01767 +Epoch [362/4000] Training [10/16] Loss: 0.01654 +Epoch [362/4000] Training [11/16] Loss: 0.04796 +Epoch [362/4000] Training [12/16] Loss: 0.01922 +Epoch [362/4000] Training [13/16] Loss: 0.02742 +Epoch [362/4000] Training [14/16] Loss: 0.01763 +Epoch [362/4000] Training [15/16] Loss: 0.01928 +Epoch [362/4000] Training [16/16] Loss: 0.01903 +Epoch [362/4000] Training metric {'Train/mean dice_metric': 0.9839015007019043, 'Train/mean miou_metric': 0.9690586924552917, 'Train/mean f1': 0.9804189801216125, 'Train/mean precision': 0.9740318059921265, 'Train/mean recall': 0.9868905544281006, 'Train/mean hd95_metric': 2.7325804233551025} +Epoch [362/4000] Validation [1/4] Loss: 0.14730 focal_loss 0.07918 dice_loss 0.06812 +Epoch [362/4000] Validation [2/4] Loss: 0.44491 focal_loss 0.22023 dice_loss 0.22468 +Epoch [362/4000] Validation [3/4] Loss: 0.14307 focal_loss 0.06674 dice_loss 0.07633 +Epoch [362/4000] Validation [4/4] Loss: 0.28625 focal_loss 0.12784 dice_loss 0.15841 +Epoch [362/4000] Validation metric {'Val/mean dice_metric': 0.9568411111831665, 'Val/mean miou_metric': 0.931317925453186, 'Val/mean f1': 0.9598942995071411, 'Val/mean precision': 0.9488270282745361, 'Val/mean recall': 0.9712227582931519, 'Val/mean hd95_metric': 8.730262756347656} +Cheakpoint... +Epoch [362/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9568], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9568411111831665, 'Val/mean miou_metric': 0.931317925453186, 'Val/mean f1': 0.9598942995071411, 'Val/mean precision': 0.9488270282745361, 'Val/mean recall': 0.9712227582931519, 'Val/mean hd95_metric': 8.730262756347656} +Epoch [363/4000] Training [1/16] Loss: 0.01769 +Epoch [363/4000] Training [2/16] Loss: 0.01888 +Epoch [363/4000] Training [3/16] Loss: 0.01901 +Epoch [363/4000] Training [4/16] Loss: 0.01734 +Epoch [363/4000] Training [5/16] Loss: 0.01537 +Epoch [363/4000] Training [6/16] Loss: 0.02011 +Epoch [363/4000] Training [7/16] Loss: 0.02472 +Epoch [363/4000] Training [8/16] Loss: 0.02399 +Epoch [363/4000] Training [9/16] Loss: 0.01806 +Epoch [363/4000] Training [10/16] Loss: 0.02439 +Epoch [363/4000] Training [11/16] Loss: 0.01988 +Epoch [363/4000] Training [12/16] Loss: 0.01747 +Epoch [363/4000] Training [13/16] Loss: 0.02380 +Epoch [363/4000] Training [14/16] Loss: 0.01830 +Epoch [363/4000] Training [15/16] Loss: 0.01361 +Epoch [363/4000] Training [16/16] Loss: 0.02496 +Epoch [363/4000] Training metric {'Train/mean dice_metric': 0.9848877191543579, 'Train/mean miou_metric': 0.9706723093986511, 'Train/mean f1': 0.983267068862915, 'Train/mean precision': 0.9788890480995178, 'Train/mean recall': 0.987684428691864, 'Train/mean hd95_metric': 2.311941146850586} +Epoch [363/4000] Validation [1/4] Loss: 0.47959 focal_loss 0.35215 dice_loss 0.12744 +Epoch [363/4000] Validation [2/4] Loss: 0.43286 focal_loss 0.21045 dice_loss 0.22241 +Epoch [363/4000] Validation [3/4] Loss: 0.26878 focal_loss 0.14743 dice_loss 0.12135 +Epoch [363/4000] Validation [4/4] Loss: 0.30322 focal_loss 0.14161 dice_loss 0.16161 +Epoch [363/4000] Validation metric {'Val/mean dice_metric': 0.9606293439865112, 'Val/mean miou_metric': 0.9349139332771301, 'Val/mean f1': 0.96377032995224, 'Val/mean precision': 0.9613510966300964, 'Val/mean recall': 0.9662017226219177, 'Val/mean hd95_metric': 7.1668243408203125} +Cheakpoint... +Epoch [363/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9606], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9606293439865112, 'Val/mean miou_metric': 0.9349139332771301, 'Val/mean f1': 0.96377032995224, 'Val/mean precision': 0.9613510966300964, 'Val/mean recall': 0.9662017226219177, 'Val/mean hd95_metric': 7.1668243408203125} +Epoch [364/4000] Training [1/16] Loss: 0.01899 +Epoch [364/4000] Training [2/16] Loss: 0.01910 +Epoch [364/4000] Training [3/16] Loss: 0.01970 +Epoch [364/4000] Training [4/16] Loss: 0.02490 +Epoch [364/4000] Training [5/16] Loss: 0.01969 +Epoch [364/4000] Training [6/16] Loss: 0.02045 +Epoch [364/4000] Training [7/16] Loss: 0.02130 +Epoch [364/4000] Training [8/16] Loss: 0.01645 +Epoch [364/4000] Training [9/16] Loss: 0.02703 +Epoch [364/4000] Training [10/16] Loss: 0.02396 +Epoch [364/4000] Training [11/16] Loss: 0.01711 +Epoch [364/4000] Training [12/16] Loss: 0.01943 +Epoch [364/4000] Training [13/16] Loss: 0.02375 +Epoch [364/4000] Training [14/16] Loss: 0.03481 +Epoch [364/4000] Training [15/16] Loss: 0.03696 +Epoch [364/4000] Training [16/16] Loss: 0.02486 +Epoch [364/4000] Training metric {'Train/mean dice_metric': 0.9846012592315674, 'Train/mean miou_metric': 0.9698082804679871, 'Train/mean f1': 0.9817236065864563, 'Train/mean precision': 0.9777005314826965, 'Train/mean recall': 0.9857798218727112, 'Train/mean hd95_metric': 2.473893880844116} +Epoch [364/4000] Validation [1/4] Loss: 0.28575 focal_loss 0.16218 dice_loss 0.12357 +Epoch [364/4000] Validation [2/4] Loss: 0.32966 focal_loss 0.14395 dice_loss 0.18571 +Epoch [364/4000] Validation [3/4] Loss: 0.36415 focal_loss 0.21104 dice_loss 0.15311 +Epoch [364/4000] Validation [4/4] Loss: 0.39048 focal_loss 0.20693 dice_loss 0.18354 +Epoch [364/4000] Validation metric {'Val/mean dice_metric': 0.9592727422714233, 'Val/mean miou_metric': 0.9329465627670288, 'Val/mean f1': 0.9617282152175903, 'Val/mean precision': 0.9534765481948853, 'Val/mean recall': 0.9701240658760071, 'Val/mean hd95_metric': 8.665014266967773} +Cheakpoint... +Epoch [364/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9592727422714233, 'Val/mean miou_metric': 0.9329465627670288, 'Val/mean f1': 0.9617282152175903, 'Val/mean precision': 0.9534765481948853, 'Val/mean recall': 0.9701240658760071, 'Val/mean hd95_metric': 8.665014266967773} +Epoch [365/4000] Training [1/16] Loss: 0.02126 +Epoch [365/4000] Training [2/16] Loss: 0.02493 +Epoch [365/4000] Training [3/16] Loss: 0.01997 +Epoch [365/4000] Training [4/16] Loss: 0.02134 +Epoch [365/4000] Training [5/16] Loss: 0.01523 +Epoch [365/4000] Training [6/16] Loss: 0.02565 +Epoch [365/4000] Training [7/16] Loss: 0.01718 +Epoch [365/4000] Training [8/16] Loss: 0.02101 +Epoch [365/4000] Training [9/16] Loss: 0.01915 +Epoch [365/4000] Training [10/16] Loss: 0.02286 +Epoch [365/4000] Training [11/16] Loss: 0.02373 +Epoch [365/4000] Training [12/16] Loss: 0.02219 +Epoch [365/4000] Training [13/16] Loss: 0.01924 +Epoch [365/4000] Training [14/16] Loss: 0.02086 +Epoch [365/4000] Training [15/16] Loss: 0.03543 +Epoch [365/4000] Training [16/16] Loss: 0.01964 +Epoch [365/4000] Training metric {'Train/mean dice_metric': 0.9852138757705688, 'Train/mean miou_metric': 0.9707738757133484, 'Train/mean f1': 0.9818975329399109, 'Train/mean precision': 0.9772021770477295, 'Train/mean recall': 0.9866381883621216, 'Train/mean hd95_metric': 4.085665702819824} +Epoch [365/4000] Validation [1/4] Loss: 0.21698 focal_loss 0.13866 dice_loss 0.07832 +Epoch [365/4000] Validation [2/4] Loss: 0.18480 focal_loss 0.07557 dice_loss 0.10923 +Epoch [365/4000] Validation [3/4] Loss: 0.13908 focal_loss 0.06995 dice_loss 0.06912 +Epoch [365/4000] Validation [4/4] Loss: 0.49143 focal_loss 0.27364 dice_loss 0.21778 +Epoch [365/4000] Validation metric {'Val/mean dice_metric': 0.9604763984680176, 'Val/mean miou_metric': 0.9343149065971375, 'Val/mean f1': 0.9611707925796509, 'Val/mean precision': 0.9515830278396606, 'Val/mean recall': 0.9709535837173462, 'Val/mean hd95_metric': 8.769633293151855} +Cheakpoint... +Epoch [365/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9605], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9604763984680176, 'Val/mean miou_metric': 0.9343149065971375, 'Val/mean f1': 0.9611707925796509, 'Val/mean precision': 0.9515830278396606, 'Val/mean recall': 0.9709535837173462, 'Val/mean hd95_metric': 8.769633293151855} +Epoch [366/4000] Training [1/16] Loss: 0.01740 +Epoch [366/4000] Training [2/16] Loss: 0.01698 +Epoch [366/4000] Training [3/16] Loss: 0.03456 +Epoch [366/4000] Training [4/16] Loss: 0.02904 +Epoch [366/4000] Training [5/16] Loss: 0.14895 +Epoch [366/4000] Training [6/16] Loss: 0.02758 +Epoch [366/4000] Training [7/16] Loss: 0.02577 +Epoch [366/4000] Training [8/16] Loss: 0.01801 +Epoch [366/4000] Training [9/16] Loss: 0.01610 +Epoch [366/4000] Training [10/16] Loss: 0.01961 +Epoch [366/4000] Training [11/16] Loss: 0.01775 +Epoch [366/4000] Training [12/16] Loss: 0.02016 +Epoch [366/4000] Training [13/16] Loss: 0.01761 +Epoch [366/4000] Training [14/16] Loss: 0.01651 +Epoch [366/4000] Training [15/16] Loss: 0.01599 +Epoch [366/4000] Training [16/16] Loss: 0.01738 +Epoch [366/4000] Training metric {'Train/mean dice_metric': 0.9846718311309814, 'Train/mean miou_metric': 0.971320390701294, 'Train/mean f1': 0.9832176566123962, 'Train/mean precision': 0.9782403111457825, 'Train/mean recall': 0.9882459044456482, 'Train/mean hd95_metric': 2.5264739990234375} +Epoch [366/4000] Validation [1/4] Loss: 0.37703 focal_loss 0.22276 dice_loss 0.15427 +Epoch [366/4000] Validation [2/4] Loss: 0.28998 focal_loss 0.13735 dice_loss 0.15262 +Epoch [366/4000] Validation [3/4] Loss: 0.16236 focal_loss 0.07429 dice_loss 0.08806 +Epoch [366/4000] Validation [4/4] Loss: 0.43466 focal_loss 0.22226 dice_loss 0.21240 +Epoch [366/4000] Validation metric {'Val/mean dice_metric': 0.9577210545539856, 'Val/mean miou_metric': 0.9330641627311707, 'Val/mean f1': 0.9614119529724121, 'Val/mean precision': 0.9496588110923767, 'Val/mean recall': 0.9734595417976379, 'Val/mean hd95_metric': 8.610180854797363} +Cheakpoint... +Epoch [366/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9577], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9577210545539856, 'Val/mean miou_metric': 0.9330641627311707, 'Val/mean f1': 0.9614119529724121, 'Val/mean precision': 0.9496588110923767, 'Val/mean recall': 0.9734595417976379, 'Val/mean hd95_metric': 8.610180854797363} +Epoch [367/4000] Training [1/16] Loss: 0.09199 +Epoch [367/4000] Training [2/16] Loss: 0.02244 +Epoch [367/4000] Training [3/16] Loss: 0.02176 +Epoch [367/4000] Training [4/16] Loss: 0.02205 +Epoch [367/4000] Training [5/16] Loss: 0.01818 +Epoch [367/4000] Training [6/16] Loss: 0.01597 +Epoch [367/4000] Training [7/16] Loss: 0.01609 +Epoch [367/4000] Training [8/16] Loss: 0.01896 +Epoch [367/4000] Training [9/16] Loss: 0.01552 +Epoch [367/4000] Training [10/16] Loss: 0.01611 +Epoch [367/4000] Training [11/16] Loss: 0.01465 +Epoch [367/4000] Training [12/16] Loss: 0.01620 +Epoch [367/4000] Training [13/16] Loss: 0.01986 +Epoch [367/4000] Training [14/16] Loss: 0.02146 +Epoch [367/4000] Training [15/16] Loss: 0.02397 +Epoch [367/4000] Training [16/16] Loss: 0.02241 +Epoch [367/4000] Training metric {'Train/mean dice_metric': 0.9859577417373657, 'Train/mean miou_metric': 0.972476601600647, 'Train/mean f1': 0.9835547804832458, 'Train/mean precision': 0.978949248790741, 'Train/mean recall': 0.9882038235664368, 'Train/mean hd95_metric': 2.099454402923584} +Epoch [367/4000] Validation [1/4] Loss: 0.34696 focal_loss 0.20094 dice_loss 0.14602 +Epoch [367/4000] Validation [2/4] Loss: 0.24006 focal_loss 0.10354 dice_loss 0.13653 +Epoch [367/4000] Validation [3/4] Loss: 0.15435 focal_loss 0.07296 dice_loss 0.08139 +Epoch [367/4000] Validation [4/4] Loss: 0.26521 focal_loss 0.12161 dice_loss 0.14360 +Epoch [367/4000] Validation metric {'Val/mean dice_metric': 0.96124666929245, 'Val/mean miou_metric': 0.9367486834526062, 'Val/mean f1': 0.9659321308135986, 'Val/mean precision': 0.9646892547607422, 'Val/mean recall': 0.9671782851219177, 'Val/mean hd95_metric': 6.961886405944824} +Cheakpoint... +Epoch [367/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96124666929245, 'Val/mean miou_metric': 0.9367486834526062, 'Val/mean f1': 0.9659321308135986, 'Val/mean precision': 0.9646892547607422, 'Val/mean recall': 0.9671782851219177, 'Val/mean hd95_metric': 6.961886405944824} +Epoch [368/4000] Training [1/16] Loss: 0.01558 +Epoch [368/4000] Training [2/16] Loss: 0.01983 +Epoch [368/4000] Training [3/16] Loss: 0.03761 +Epoch [368/4000] Training [4/16] Loss: 0.01769 +Epoch [368/4000] Training [5/16] Loss: 0.01956 +Epoch [368/4000] Training [6/16] Loss: 0.01617 +Epoch [368/4000] Training [7/16] Loss: 0.01984 +Epoch [368/4000] Training [8/16] Loss: 0.02112 +Epoch [368/4000] Training [9/16] Loss: 0.01775 +Epoch [368/4000] Training [10/16] Loss: 0.01725 +Epoch [368/4000] Training [11/16] Loss: 0.02152 +Epoch [368/4000] Training [12/16] Loss: 0.02159 +Epoch [368/4000] Training [13/16] Loss: 0.01525 +Epoch [368/4000] Training [14/16] Loss: 0.02643 +Epoch [368/4000] Training [15/16] Loss: 0.01582 +Epoch [368/4000] Training [16/16] Loss: 0.02463 +Epoch [368/4000] Training metric {'Train/mean dice_metric': 0.9858005046844482, 'Train/mean miou_metric': 0.9721337556838989, 'Train/mean f1': 0.9836591482162476, 'Train/mean precision': 0.9798542261123657, 'Train/mean recall': 0.987493634223938, 'Train/mean hd95_metric': 2.1583974361419678} +Epoch [368/4000] Validation [1/4] Loss: 0.24126 focal_loss 0.15051 dice_loss 0.09074 +Epoch [368/4000] Validation [2/4] Loss: 0.28599 focal_loss 0.13037 dice_loss 0.15562 +Epoch [368/4000] Validation [3/4] Loss: 0.11747 focal_loss 0.05638 dice_loss 0.06109 +Epoch [368/4000] Validation [4/4] Loss: 0.29119 focal_loss 0.11536 dice_loss 0.17583 +Epoch [368/4000] Validation metric {'Val/mean dice_metric': 0.9641879796981812, 'Val/mean miou_metric': 0.9393079876899719, 'Val/mean f1': 0.9665212035179138, 'Val/mean precision': 0.9617584347724915, 'Val/mean recall': 0.9713312983512878, 'Val/mean hd95_metric': 7.0889787673950195} +Cheakpoint... +Epoch [368/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9642], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9641879796981812, 'Val/mean miou_metric': 0.9393079876899719, 'Val/mean f1': 0.9665212035179138, 'Val/mean precision': 0.9617584347724915, 'Val/mean recall': 0.9713312983512878, 'Val/mean hd95_metric': 7.0889787673950195} +Epoch [369/4000] Training [1/16] Loss: 0.01815 +Epoch [369/4000] Training [2/16] Loss: 0.01822 +Epoch [369/4000] Training [3/16] Loss: 0.01406 +Epoch [369/4000] Training [4/16] Loss: 0.01328 +Epoch [369/4000] Training [5/16] Loss: 0.01343 +Epoch [369/4000] Training [6/16] Loss: 0.01598 +Epoch [369/4000] Training [7/16] Loss: 0.01726 +Epoch [369/4000] Training [8/16] Loss: 0.01182 +Epoch [369/4000] Training [9/16] Loss: 0.02142 +Epoch [369/4000] Training [10/16] Loss: 0.01441 +Epoch [369/4000] Training [11/16] Loss: 0.01942 +Epoch [369/4000] Training [12/16] Loss: 0.01351 +Epoch [369/4000] Training [13/16] Loss: 0.01829 +Epoch [369/4000] Training [14/16] Loss: 0.01790 +Epoch [369/4000] Training [15/16] Loss: 0.01920 +Epoch [369/4000] Training [16/16] Loss: 0.02126 +Epoch [369/4000] Training metric {'Train/mean dice_metric': 0.9881654977798462, 'Train/mean miou_metric': 0.976451575756073, 'Train/mean f1': 0.985323429107666, 'Train/mean precision': 0.9806662201881409, 'Train/mean recall': 0.9900251030921936, 'Train/mean hd95_metric': 1.5050981044769287} +Epoch [369/4000] Validation [1/4] Loss: 0.16472 focal_loss 0.09759 dice_loss 0.06714 +Epoch [369/4000] Validation [2/4] Loss: 0.28542 focal_loss 0.13546 dice_loss 0.14996 +Epoch [369/4000] Validation [3/4] Loss: 0.11315 focal_loss 0.05195 dice_loss 0.06120 +Epoch [369/4000] Validation [4/4] Loss: 0.31067 focal_loss 0.13139 dice_loss 0.17928 +Epoch [369/4000] Validation metric {'Val/mean dice_metric': 0.9655691385269165, 'Val/mean miou_metric': 0.9420474171638489, 'Val/mean f1': 0.9669429659843445, 'Val/mean precision': 0.9611597061157227, 'Val/mean recall': 0.9727963209152222, 'Val/mean hd95_metric': 6.4871110916137695} +Cheakpoint... +Epoch [369/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655691385269165, 'Val/mean miou_metric': 0.9420474171638489, 'Val/mean f1': 0.9669429659843445, 'Val/mean precision': 0.9611597061157227, 'Val/mean recall': 0.9727963209152222, 'Val/mean hd95_metric': 6.4871110916137695} +Epoch [370/4000] Training [1/16] Loss: 0.01483 +Epoch [370/4000] Training [2/16] Loss: 0.01550 +Epoch [370/4000] Training [3/16] Loss: 0.01804 +Epoch [370/4000] Training [4/16] Loss: 0.01466 +Epoch [370/4000] Training [5/16] Loss: 0.01610 +Epoch [370/4000] Training [6/16] Loss: 0.01439 +Epoch [370/4000] Training [7/16] Loss: 0.01432 +Epoch [370/4000] Training [8/16] Loss: 0.01368 +Epoch [370/4000] Training [9/16] Loss: 0.01399 +Epoch [370/4000] Training [10/16] Loss: 0.01729 +Epoch [370/4000] Training [11/16] Loss: 0.01719 +Epoch [370/4000] Training [12/16] Loss: 0.03738 +Epoch [370/4000] Training [13/16] Loss: 0.01405 +Epoch [370/4000] Training [14/16] Loss: 0.01772 +Epoch [370/4000] Training [15/16] Loss: 0.01185 +Epoch [370/4000] Training [16/16] Loss: 0.01182 +Epoch [370/4000] Training metric {'Train/mean dice_metric': 0.9883705377578735, 'Train/mean miou_metric': 0.9770969152450562, 'Train/mean f1': 0.9854366183280945, 'Train/mean precision': 0.9808120727539062, 'Train/mean recall': 0.9901049733161926, 'Train/mean hd95_metric': 1.693213939666748} +Epoch [370/4000] Validation [1/4] Loss: 0.15789 focal_loss 0.09356 dice_loss 0.06433 +Epoch [370/4000] Validation [2/4] Loss: 0.22168 focal_loss 0.09511 dice_loss 0.12657 +Epoch [370/4000] Validation [3/4] Loss: 0.18134 focal_loss 0.07767 dice_loss 0.10368 +Epoch [370/4000] Validation [4/4] Loss: 0.33233 focal_loss 0.15868 dice_loss 0.17364 +Epoch [370/4000] Validation metric {'Val/mean dice_metric': 0.9640630483627319, 'Val/mean miou_metric': 0.9410347938537598, 'Val/mean f1': 0.9656761884689331, 'Val/mean precision': 0.9584022760391235, 'Val/mean recall': 0.9730615019798279, 'Val/mean hd95_metric': 7.345442295074463} +Cheakpoint... +Epoch [370/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640630483627319, 'Val/mean miou_metric': 0.9410347938537598, 'Val/mean f1': 0.9656761884689331, 'Val/mean precision': 0.9584022760391235, 'Val/mean recall': 0.9730615019798279, 'Val/mean hd95_metric': 7.345442295074463} +Epoch [371/4000] Training [1/16] Loss: 0.01897 +Epoch [371/4000] Training [2/16] Loss: 0.01440 +Epoch [371/4000] Training [3/16] Loss: 0.02156 +Epoch [371/4000] Training [4/16] Loss: 0.02128 +Epoch [371/4000] Training [5/16] Loss: 0.01845 +Epoch [371/4000] Training [6/16] Loss: 0.01315 +Epoch [371/4000] Training [7/16] Loss: 0.02631 +Epoch [371/4000] Training [8/16] Loss: 0.03302 +Epoch [371/4000] Training [9/16] Loss: 0.01818 +Epoch [371/4000] Training [10/16] Loss: 0.01504 +Epoch [371/4000] Training [11/16] Loss: 0.01410 +Epoch [371/4000] Training [12/16] Loss: 0.02423 +Epoch [371/4000] Training [13/16] Loss: 0.01999 +Epoch [371/4000] Training [14/16] Loss: 0.01657 +Epoch [371/4000] Training [15/16] Loss: 0.02954 +Epoch [371/4000] Training [16/16] Loss: 0.02597 +Epoch [371/4000] Training metric {'Train/mean dice_metric': 0.9850248098373413, 'Train/mean miou_metric': 0.9707337021827698, 'Train/mean f1': 0.9813429713249207, 'Train/mean precision': 0.9768436551094055, 'Train/mean recall': 0.9858839511871338, 'Train/mean hd95_metric': 2.814643383026123} +Epoch [371/4000] Validation [1/4] Loss: 0.62104 focal_loss 0.42810 dice_loss 0.19295 +Epoch [371/4000] Validation [2/4] Loss: 0.25023 focal_loss 0.09228 dice_loss 0.15794 +Epoch [371/4000] Validation [3/4] Loss: 0.13492 focal_loss 0.06221 dice_loss 0.07271 +Epoch [371/4000] Validation [4/4] Loss: 0.50230 focal_loss 0.27722 dice_loss 0.22508 +Epoch [371/4000] Validation metric {'Val/mean dice_metric': 0.9586498141288757, 'Val/mean miou_metric': 0.9328492879867554, 'Val/mean f1': 0.9592493176460266, 'Val/mean precision': 0.9553364515304565, 'Val/mean recall': 0.9631942510604858, 'Val/mean hd95_metric': 8.338676452636719} +Cheakpoint... +Epoch [371/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9586], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9586498141288757, 'Val/mean miou_metric': 0.9328492879867554, 'Val/mean f1': 0.9592493176460266, 'Val/mean precision': 0.9553364515304565, 'Val/mean recall': 0.9631942510604858, 'Val/mean hd95_metric': 8.338676452636719} +Epoch [372/4000] Training [1/16] Loss: 0.03559 +Epoch [372/4000] Training [2/16] Loss: 0.02546 +Epoch [372/4000] Training [3/16] Loss: 0.02482 +Epoch [372/4000] Training [4/16] Loss: 0.02185 +Epoch [372/4000] Training [5/16] Loss: 0.02401 +Epoch [372/4000] Training [6/16] Loss: 0.01865 +Epoch [372/4000] Training [7/16] Loss: 0.01934 +Epoch [372/4000] Training [8/16] Loss: 0.01662 +Epoch [372/4000] Training [9/16] Loss: 0.02867 +Epoch [372/4000] Training [10/16] Loss: 0.01909 +Epoch [372/4000] Training [11/16] Loss: 0.01875 +Epoch [372/4000] Training [12/16] Loss: 0.02218 +Epoch [372/4000] Training [13/16] Loss: 0.03121 +Epoch [372/4000] Training [14/16] Loss: 0.02407 +Epoch [372/4000] Training [15/16] Loss: 0.02005 +Epoch [372/4000] Training [16/16] Loss: 0.02249 +Epoch [372/4000] Training metric {'Train/mean dice_metric': 0.9820507168769836, 'Train/mean miou_metric': 0.9658581018447876, 'Train/mean f1': 0.9788710474967957, 'Train/mean precision': 0.9734385013580322, 'Train/mean recall': 0.9843645691871643, 'Train/mean hd95_metric': 2.9640913009643555} +Epoch [372/4000] Validation [1/4] Loss: 0.98300 focal_loss 0.77310 dice_loss 0.20990 +Epoch [372/4000] Validation [2/4] Loss: 0.36468 focal_loss 0.16836 dice_loss 0.19633 +Epoch [372/4000] Validation [3/4] Loss: 0.11183 focal_loss 0.04879 dice_loss 0.06304 +Epoch [372/4000] Validation [4/4] Loss: 0.27327 focal_loss 0.14725 dice_loss 0.12602 +Epoch [372/4000] Validation metric {'Val/mean dice_metric': 0.9539216756820679, 'Val/mean miou_metric': 0.9265262484550476, 'Val/mean f1': 0.955132007598877, 'Val/mean precision': 0.9577676057815552, 'Val/mean recall': 0.9525108933448792, 'Val/mean hd95_metric': 8.61168098449707} +Cheakpoint... +Epoch [372/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9539], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9539216756820679, 'Val/mean miou_metric': 0.9265262484550476, 'Val/mean f1': 0.955132007598877, 'Val/mean precision': 0.9577676057815552, 'Val/mean recall': 0.9525108933448792, 'Val/mean hd95_metric': 8.61168098449707} +Epoch [373/4000] Training [1/16] Loss: 0.02351 +Epoch [373/4000] Training [2/16] Loss: 0.02016 +Epoch [373/4000] Training [3/16] Loss: 0.03264 +Epoch [373/4000] Training [4/16] Loss: 0.02076 +Epoch [373/4000] Training [5/16] Loss: 0.01707 +Epoch [373/4000] Training [6/16] Loss: 0.01786 +Epoch [373/4000] Training [7/16] Loss: 0.02448 +Epoch [373/4000] Training [8/16] Loss: 0.02199 +Epoch [373/4000] Training [9/16] Loss: 0.01995 +Epoch [373/4000] Training [10/16] Loss: 0.01843 +Epoch [373/4000] Training [11/16] Loss: 0.03367 +Epoch [373/4000] Training [12/16] Loss: 0.02079 +Epoch [373/4000] Training [13/16] Loss: 0.01961 +Epoch [373/4000] Training [14/16] Loss: 0.01895 +Epoch [373/4000] Training [15/16] Loss: 0.02317 +Epoch [373/4000] Training [16/16] Loss: 0.02916 +Epoch [373/4000] Training metric {'Train/mean dice_metric': 0.985379159450531, 'Train/mean miou_metric': 0.9711384773254395, 'Train/mean f1': 0.9829758405685425, 'Train/mean precision': 0.9781221747398376, 'Train/mean recall': 0.9878779053688049, 'Train/mean hd95_metric': 2.579592704772949} +Epoch [373/4000] Validation [1/4] Loss: 0.26447 focal_loss 0.15392 dice_loss 0.11055 +Epoch [373/4000] Validation [2/4] Loss: 0.42259 focal_loss 0.21681 dice_loss 0.20578 +Epoch [373/4000] Validation [3/4] Loss: 0.16919 focal_loss 0.08160 dice_loss 0.08760 +Epoch [373/4000] Validation [4/4] Loss: 0.18300 focal_loss 0.08899 dice_loss 0.09400 +Epoch [373/4000] Validation metric {'Val/mean dice_metric': 0.9597499966621399, 'Val/mean miou_metric': 0.9342830777168274, 'Val/mean f1': 0.9631093740463257, 'Val/mean precision': 0.9592617750167847, 'Val/mean recall': 0.9669879078865051, 'Val/mean hd95_metric': 7.680319309234619} +Cheakpoint... +Epoch [373/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9597], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9597499966621399, 'Val/mean miou_metric': 0.9342830777168274, 'Val/mean f1': 0.9631093740463257, 'Val/mean precision': 0.9592617750167847, 'Val/mean recall': 0.9669879078865051, 'Val/mean hd95_metric': 7.680319309234619} +Epoch [374/4000] Training [1/16] Loss: 0.01872 +Epoch [374/4000] Training [2/16] Loss: 0.01625 +Epoch [374/4000] Training [3/16] Loss: 0.02017 +Epoch [374/4000] Training [4/16] Loss: 0.01689 +Epoch [374/4000] Training [5/16] Loss: 0.01472 +Epoch [374/4000] Training [6/16] Loss: 0.01751 +Epoch [374/4000] Training [7/16] Loss: 0.01417 +Epoch [374/4000] Training [8/16] Loss: 0.01591 +Epoch [374/4000] Training [9/16] Loss: 0.01838 +Epoch [374/4000] Training [10/16] Loss: 0.02738 +Epoch [374/4000] Training [11/16] Loss: 0.01514 +Epoch [374/4000] Training [12/16] Loss: 0.01748 +Epoch [374/4000] Training [13/16] Loss: 0.01638 +Epoch [374/4000] Training [14/16] Loss: 0.02571 +Epoch [374/4000] Training [15/16] Loss: 0.01861 +Epoch [374/4000] Training [16/16] Loss: 0.01840 +Epoch [374/4000] Training metric {'Train/mean dice_metric': 0.9851468801498413, 'Train/mean miou_metric': 0.9714456796646118, 'Train/mean f1': 0.9833599925041199, 'Train/mean precision': 0.9790338277816772, 'Train/mean recall': 0.9877244830131531, 'Train/mean hd95_metric': 3.0664680004119873} +Epoch [374/4000] Validation [1/4] Loss: 0.77769 focal_loss 0.61056 dice_loss 0.16713 +Epoch [374/4000] Validation [2/4] Loss: 0.30692 focal_loss 0.10853 dice_loss 0.19839 +Epoch [374/4000] Validation [3/4] Loss: 0.25325 focal_loss 0.13640 dice_loss 0.11684 +Epoch [374/4000] Validation [4/4] Loss: 0.21407 focal_loss 0.11266 dice_loss 0.10140 +Epoch [374/4000] Validation metric {'Val/mean dice_metric': 0.9585647583007812, 'Val/mean miou_metric': 0.9338115453720093, 'Val/mean f1': 0.9625118970870972, 'Val/mean precision': 0.961597740650177, 'Val/mean recall': 0.9634276032447815, 'Val/mean hd95_metric': 7.9938554763793945} +Cheakpoint... +Epoch [374/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9586], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9585647583007812, 'Val/mean miou_metric': 0.9338115453720093, 'Val/mean f1': 0.9625118970870972, 'Val/mean precision': 0.961597740650177, 'Val/mean recall': 0.9634276032447815, 'Val/mean hd95_metric': 7.9938554763793945} +Epoch [375/4000] Training [1/16] Loss: 0.01766 +Epoch [375/4000] Training [2/16] Loss: 0.01795 +Epoch [375/4000] Training [3/16] Loss: 0.02001 +Epoch [375/4000] Training [4/16] Loss: 0.01819 +Epoch [375/4000] Training [5/16] Loss: 0.01784 +Epoch [375/4000] Training [6/16] Loss: 0.01614 +Epoch [375/4000] Training [7/16] Loss: 0.02330 +Epoch [375/4000] Training [8/16] Loss: 0.01647 +Epoch [375/4000] Training [9/16] Loss: 0.04213 +Epoch [375/4000] Training [10/16] Loss: 0.02133 +Epoch [375/4000] Training [11/16] Loss: 0.01872 +Epoch [375/4000] Training [12/16] Loss: 0.01992 +Epoch [375/4000] Training [13/16] Loss: 0.02342 +Epoch [375/4000] Training [14/16] Loss: 0.01931 +Epoch [375/4000] Training [15/16] Loss: 0.01635 +Epoch [375/4000] Training [16/16] Loss: 0.01812 +Epoch [375/4000] Training metric {'Train/mean dice_metric': 0.9859613180160522, 'Train/mean miou_metric': 0.9722366333007812, 'Train/mean f1': 0.9833155274391174, 'Train/mean precision': 0.9787865877151489, 'Train/mean recall': 0.9878865480422974, 'Train/mean hd95_metric': 2.464336633682251} +Epoch [375/4000] Validation [1/4] Loss: 0.60038 focal_loss 0.46778 dice_loss 0.13260 +Epoch [375/4000] Validation [2/4] Loss: 0.45578 focal_loss 0.19219 dice_loss 0.26359 +Epoch [375/4000] Validation [3/4] Loss: 0.15184 focal_loss 0.06519 dice_loss 0.08665 +Epoch [375/4000] Validation [4/4] Loss: 0.42720 focal_loss 0.24392 dice_loss 0.18328 +Epoch [375/4000] Validation metric {'Val/mean dice_metric': 0.958311915397644, 'Val/mean miou_metric': 0.9328606724739075, 'Val/mean f1': 0.9607625007629395, 'Val/mean precision': 0.9575342535972595, 'Val/mean recall': 0.9640124440193176, 'Val/mean hd95_metric': 8.074934005737305} +Cheakpoint... +Epoch [375/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9583], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.958311915397644, 'Val/mean miou_metric': 0.9328606724739075, 'Val/mean f1': 0.9607625007629395, 'Val/mean precision': 0.9575342535972595, 'Val/mean recall': 0.9640124440193176, 'Val/mean hd95_metric': 8.074934005737305} +Epoch [376/4000] Training [1/16] Loss: 0.01850 +Epoch [376/4000] Training [2/16] Loss: 0.03288 +Epoch [376/4000] Training [3/16] Loss: 0.04031 +Epoch [376/4000] Training [4/16] Loss: 0.02658 +Epoch [376/4000] Training [5/16] Loss: 0.01410 +Epoch [376/4000] Training [6/16] Loss: 0.01487 +Epoch [376/4000] Training [7/16] Loss: 0.01563 +Epoch [376/4000] Training [8/16] Loss: 0.02160 +Epoch [376/4000] Training [9/16] Loss: 0.02328 +Epoch [376/4000] Training [10/16] Loss: 0.02669 +Epoch [376/4000] Training [11/16] Loss: 0.02191 +Epoch [376/4000] Training [12/16] Loss: 0.02476 +Epoch [376/4000] Training [13/16] Loss: 0.01420 +Epoch [376/4000] Training [14/16] Loss: 0.02622 +Epoch [376/4000] Training [15/16] Loss: 0.02162 +Epoch [376/4000] Training [16/16] Loss: 0.01928 +Epoch [376/4000] Training metric {'Train/mean dice_metric': 0.9845069050788879, 'Train/mean miou_metric': 0.9698013067245483, 'Train/mean f1': 0.9824532270431519, 'Train/mean precision': 0.9777612686157227, 'Train/mean recall': 0.9871904850006104, 'Train/mean hd95_metric': 2.5639796257019043} +Epoch [376/4000] Validation [1/4] Loss: 0.70236 focal_loss 0.55434 dice_loss 0.14802 +Epoch [376/4000] Validation [2/4] Loss: 0.58731 focal_loss 0.28658 dice_loss 0.30073 +Epoch [376/4000] Validation [3/4] Loss: 0.16077 focal_loss 0.07373 dice_loss 0.08704 +Epoch [376/4000] Validation [4/4] Loss: 0.31012 focal_loss 0.15866 dice_loss 0.15146 +Epoch [376/4000] Validation metric {'Val/mean dice_metric': 0.9579184651374817, 'Val/mean miou_metric': 0.9323499798774719, 'Val/mean f1': 0.9600808024406433, 'Val/mean precision': 0.9588123559951782, 'Val/mean recall': 0.9613526463508606, 'Val/mean hd95_metric': 7.953187465667725} +Cheakpoint... +Epoch [376/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9579], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9579184651374817, 'Val/mean miou_metric': 0.9323499798774719, 'Val/mean f1': 0.9600808024406433, 'Val/mean precision': 0.9588123559951782, 'Val/mean recall': 0.9613526463508606, 'Val/mean hd95_metric': 7.953187465667725} +Epoch [377/4000] Training [1/16] Loss: 0.01832 +Epoch [377/4000] Training [2/16] Loss: 0.01792 +Epoch [377/4000] Training [3/16] Loss: 0.02348 +Epoch [377/4000] Training [4/16] Loss: 0.01740 +Epoch [377/4000] Training [5/16] Loss: 0.01815 +Epoch [377/4000] Training [6/16] Loss: 0.17643 +Epoch [377/4000] Training [7/16] Loss: 0.01516 +Epoch [377/4000] Training [8/16] Loss: 0.01859 +Epoch [377/4000] Training [9/16] Loss: 0.01825 +Epoch [377/4000] Training [10/16] Loss: 0.01637 +Epoch [377/4000] Training [11/16] Loss: 0.01480 +Epoch [377/4000] Training [12/16] Loss: 0.01816 +Epoch [377/4000] Training [13/16] Loss: 0.01833 +Epoch [377/4000] Training [14/16] Loss: 0.01541 +Epoch [377/4000] Training [15/16] Loss: 0.01618 +Epoch [377/4000] Training [16/16] Loss: 0.01954 +Epoch [377/4000] Training metric {'Train/mean dice_metric': 0.9847396612167358, 'Train/mean miou_metric': 0.9713895320892334, 'Train/mean f1': 0.9832701683044434, 'Train/mean precision': 0.9783862233161926, 'Train/mean recall': 0.9882031083106995, 'Train/mean hd95_metric': 2.445208787918091} +Epoch [377/4000] Validation [1/4] Loss: 0.20309 focal_loss 0.11638 dice_loss 0.08671 +Epoch [377/4000] Validation [2/4] Loss: 0.45931 focal_loss 0.22270 dice_loss 0.23661 +Epoch [377/4000] Validation [3/4] Loss: 0.13517 focal_loss 0.05667 dice_loss 0.07850 +Epoch [377/4000] Validation [4/4] Loss: 0.30301 focal_loss 0.15192 dice_loss 0.15109 +Epoch [377/4000] Validation metric {'Val/mean dice_metric': 0.9607648849487305, 'Val/mean miou_metric': 0.9357349276542664, 'Val/mean f1': 0.963456928730011, 'Val/mean precision': 0.9560893774032593, 'Val/mean recall': 0.9709388613700867, 'Val/mean hd95_metric': 7.8828864097595215} +Cheakpoint... +Epoch [377/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9607648849487305, 'Val/mean miou_metric': 0.9357349276542664, 'Val/mean f1': 0.963456928730011, 'Val/mean precision': 0.9560893774032593, 'Val/mean recall': 0.9709388613700867, 'Val/mean hd95_metric': 7.8828864097595215} +Epoch [378/4000] Training [1/16] Loss: 0.01911 +Epoch [378/4000] Training [2/16] Loss: 0.01619 +Epoch [378/4000] Training [3/16] Loss: 0.01655 +Epoch [378/4000] Training [4/16] Loss: 0.01434 +Epoch [378/4000] Training [5/16] Loss: 0.02239 +Epoch [378/4000] Training [6/16] Loss: 0.01270 +Epoch [378/4000] Training [7/16] Loss: 0.02379 +Epoch [378/4000] Training [8/16] Loss: 0.01761 +Epoch [378/4000] Training [9/16] Loss: 0.01773 +Epoch [378/4000] Training [10/16] Loss: 0.02090 +Epoch [378/4000] Training [11/16] Loss: 0.02234 +Epoch [378/4000] Training [12/16] Loss: 0.02649 +Epoch [378/4000] Training [13/16] Loss: 0.01767 +Epoch [378/4000] Training [14/16] Loss: 0.01969 +Epoch [378/4000] Training [15/16] Loss: 0.01272 +Epoch [378/4000] Training [16/16] Loss: 0.05432 +Epoch [378/4000] Training metric {'Train/mean dice_metric': 0.9866241812705994, 'Train/mean miou_metric': 0.9739038944244385, 'Train/mean f1': 0.9844257235527039, 'Train/mean precision': 0.9796992540359497, 'Train/mean recall': 0.9891980886459351, 'Train/mean hd95_metric': 2.01739501953125} +Epoch [378/4000] Validation [1/4] Loss: 0.40087 focal_loss 0.28314 dice_loss 0.11774 +Epoch [378/4000] Validation [2/4] Loss: 0.49616 focal_loss 0.23241 dice_loss 0.26375 +Epoch [378/4000] Validation [3/4] Loss: 0.10003 focal_loss 0.04903 dice_loss 0.05100 +Epoch [378/4000] Validation [4/4] Loss: 0.23052 focal_loss 0.11888 dice_loss 0.11163 +Epoch [378/4000] Validation metric {'Val/mean dice_metric': 0.961879551410675, 'Val/mean miou_metric': 0.9387788772583008, 'Val/mean f1': 0.9647592306137085, 'Val/mean precision': 0.9618605971336365, 'Val/mean recall': 0.967675507068634, 'Val/mean hd95_metric': 6.521166801452637} +Cheakpoint... +Epoch [378/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9619], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961879551410675, 'Val/mean miou_metric': 0.9387788772583008, 'Val/mean f1': 0.9647592306137085, 'Val/mean precision': 0.9618605971336365, 'Val/mean recall': 0.967675507068634, 'Val/mean hd95_metric': 6.521166801452637} +Epoch [379/4000] Training [1/16] Loss: 0.01843 +Epoch [379/4000] Training [2/16] Loss: 0.01635 +Epoch [379/4000] Training [3/16] Loss: 0.01591 +Epoch [379/4000] Training [4/16] Loss: 0.01953 +Epoch [379/4000] Training [5/16] Loss: 0.02055 +Epoch [379/4000] Training [6/16] Loss: 0.02042 +Epoch [379/4000] Training [7/16] Loss: 0.01840 +Epoch [379/4000] Training [8/16] Loss: 0.01372 +Epoch [379/4000] Training [9/16] Loss: 0.02038 +Epoch [379/4000] Training [10/16] Loss: 0.01646 +Epoch [379/4000] Training [11/16] Loss: 0.01360 +Epoch [379/4000] Training [12/16] Loss: 0.02352 +Epoch [379/4000] Training [13/16] Loss: 0.01316 +Epoch [379/4000] Training [14/16] Loss: 0.01706 +Epoch [379/4000] Training [15/16] Loss: 0.01779 +Epoch [379/4000] Training [16/16] Loss: 0.02340 +Epoch [379/4000] Training metric {'Train/mean dice_metric': 0.9871789216995239, 'Train/mean miou_metric': 0.9745533466339111, 'Train/mean f1': 0.984390914440155, 'Train/mean precision': 0.9799453616142273, 'Train/mean recall': 0.98887699842453, 'Train/mean hd95_metric': 2.1988348960876465} +Epoch [379/4000] Validation [1/4] Loss: 0.21579 focal_loss 0.12467 dice_loss 0.09112 +Epoch [379/4000] Validation [2/4] Loss: 0.26073 focal_loss 0.12166 dice_loss 0.13908 +Epoch [379/4000] Validation [3/4] Loss: 0.10692 focal_loss 0.05173 dice_loss 0.05519 +Epoch [379/4000] Validation [4/4] Loss: 0.23560 focal_loss 0.11284 dice_loss 0.12276 +Epoch [379/4000] Validation metric {'Val/mean dice_metric': 0.9636789560317993, 'Val/mean miou_metric': 0.9400704503059387, 'Val/mean f1': 0.9656239748001099, 'Val/mean precision': 0.9625275731086731, 'Val/mean recall': 0.9687404036521912, 'Val/mean hd95_metric': 6.839591026306152} +Cheakpoint... +Epoch [379/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636789560317993, 'Val/mean miou_metric': 0.9400704503059387, 'Val/mean f1': 0.9656239748001099, 'Val/mean precision': 0.9625275731086731, 'Val/mean recall': 0.9687404036521912, 'Val/mean hd95_metric': 6.839591026306152} +Epoch [380/4000] Training [1/16] Loss: 0.01548 +Epoch [380/4000] Training [2/16] Loss: 0.01761 +Epoch [380/4000] Training [3/16] Loss: 0.01324 +Epoch [380/4000] Training [4/16] Loss: 0.01809 +Epoch [380/4000] Training [5/16] Loss: 0.01294 +Epoch [380/4000] Training [6/16] Loss: 0.01843 +Epoch [380/4000] Training [7/16] Loss: 0.01600 +Epoch [380/4000] Training [8/16] Loss: 0.01565 +Epoch [380/4000] Training [9/16] Loss: 0.01396 +Epoch [380/4000] Training [10/16] Loss: 0.01827 +Epoch [380/4000] Training [11/16] Loss: 0.01831 +Epoch [380/4000] Training [12/16] Loss: 0.01660 +Epoch [380/4000] Training [13/16] Loss: 0.01590 +Epoch [380/4000] Training [14/16] Loss: 0.01638 +Epoch [380/4000] Training [15/16] Loss: 0.01869 +Epoch [380/4000] Training [16/16] Loss: 0.01356 +Epoch [380/4000] Training metric {'Train/mean dice_metric': 0.9885127544403076, 'Train/mean miou_metric': 0.9771245121955872, 'Train/mean f1': 0.9858044385910034, 'Train/mean precision': 0.9813129901885986, 'Train/mean recall': 0.9903371930122375, 'Train/mean hd95_metric': 1.4715094566345215} +Epoch [380/4000] Validation [1/4] Loss: 0.40758 focal_loss 0.24191 dice_loss 0.16567 +Epoch [380/4000] Validation [2/4] Loss: 0.22443 focal_loss 0.10231 dice_loss 0.12212 +Epoch [380/4000] Validation [3/4] Loss: 0.12778 focal_loss 0.06020 dice_loss 0.06758 +Epoch [380/4000] Validation [4/4] Loss: 0.16346 focal_loss 0.06191 dice_loss 0.10155 +Epoch [380/4000] Validation metric {'Val/mean dice_metric': 0.9660602807998657, 'Val/mean miou_metric': 0.9438973665237427, 'Val/mean f1': 0.966658353805542, 'Val/mean precision': 0.9652644395828247, 'Val/mean recall': 0.968056321144104, 'Val/mean hd95_metric': 5.899788856506348} +Cheakpoint... +Epoch [380/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660602807998657, 'Val/mean miou_metric': 0.9438973665237427, 'Val/mean f1': 0.966658353805542, 'Val/mean precision': 0.9652644395828247, 'Val/mean recall': 0.968056321144104, 'Val/mean hd95_metric': 5.899788856506348} +Epoch [381/4000] Training [1/16] Loss: 0.01975 +Epoch [381/4000] Training [2/16] Loss: 0.01598 +Epoch [381/4000] Training [3/16] Loss: 0.01235 +Epoch [381/4000] Training [4/16] Loss: 0.01748 +Epoch [381/4000] Training [5/16] Loss: 0.01431 +Epoch [381/4000] Training [6/16] Loss: 0.01630 +Epoch [381/4000] Training [7/16] Loss: 0.01526 +Epoch [381/4000] Training [8/16] Loss: 0.02537 +Epoch [381/4000] Training [9/16] Loss: 0.01375 +Epoch [381/4000] Training [10/16] Loss: 0.01820 +Epoch [381/4000] Training [11/16] Loss: 0.01800 +Epoch [381/4000] Training [12/16] Loss: 0.01307 +Epoch [381/4000] Training [13/16] Loss: 0.01573 +Epoch [381/4000] Training [14/16] Loss: 0.01523 +Epoch [381/4000] Training [15/16] Loss: 0.01776 +Epoch [381/4000] Training [16/16] Loss: 0.02104 +Epoch [381/4000] Training metric {'Train/mean dice_metric': 0.9880927801132202, 'Train/mean miou_metric': 0.9763117432594299, 'Train/mean f1': 0.9852438569068909, 'Train/mean precision': 0.9804487824440002, 'Train/mean recall': 0.9900861382484436, 'Train/mean hd95_metric': 1.509714961051941} +Epoch [381/4000] Validation [1/4] Loss: 0.41110 focal_loss 0.29391 dice_loss 0.11719 +Epoch [381/4000] Validation [2/4] Loss: 0.38206 focal_loss 0.17795 dice_loss 0.20411 +Epoch [381/4000] Validation [3/4] Loss: 0.17068 focal_loss 0.08840 dice_loss 0.08228 +Epoch [381/4000] Validation [4/4] Loss: 0.19299 focal_loss 0.10129 dice_loss 0.09171 +Epoch [381/4000] Validation metric {'Val/mean dice_metric': 0.9652286767959595, 'Val/mean miou_metric': 0.9413784146308899, 'Val/mean f1': 0.965837836265564, 'Val/mean precision': 0.9620218276977539, 'Val/mean recall': 0.9696843028068542, 'Val/mean hd95_metric': 7.569891452789307} +Cheakpoint... +Epoch [381/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652286767959595, 'Val/mean miou_metric': 0.9413784146308899, 'Val/mean f1': 0.965837836265564, 'Val/mean precision': 0.9620218276977539, 'Val/mean recall': 0.9696843028068542, 'Val/mean hd95_metric': 7.569891452789307} +Epoch [382/4000] Training [1/16] Loss: 0.01411 +Epoch [382/4000] Training [2/16] Loss: 0.01704 +Epoch [382/4000] Training [3/16] Loss: 0.02086 +Epoch [382/4000] Training [4/16] Loss: 0.01460 +Epoch [382/4000] Training [5/16] Loss: 0.01638 +Epoch [382/4000] Training [6/16] Loss: 0.01332 +Epoch [382/4000] Training [7/16] Loss: 0.01898 +Epoch [382/4000] Training [8/16] Loss: 0.01563 +Epoch [382/4000] Training [9/16] Loss: 0.01545 +Epoch [382/4000] Training [10/16] Loss: 0.01472 +Epoch [382/4000] Training [11/16] Loss: 0.01782 +Epoch [382/4000] Training [12/16] Loss: 0.02464 +Epoch [382/4000] Training [13/16] Loss: 0.01615 +Epoch [382/4000] Training [14/16] Loss: 0.01325 +Epoch [382/4000] Training [15/16] Loss: 0.02069 +Epoch [382/4000] Training [16/16] Loss: 0.01656 +Epoch [382/4000] Training metric {'Train/mean dice_metric': 0.9863138198852539, 'Train/mean miou_metric': 0.973663330078125, 'Train/mean f1': 0.98517245054245, 'Train/mean precision': 0.9811214804649353, 'Train/mean recall': 0.9892569780349731, 'Train/mean hd95_metric': 2.102417469024658} +Epoch [382/4000] Validation [1/4] Loss: 0.35875 focal_loss 0.25111 dice_loss 0.10764 +Epoch [382/4000] Validation [2/4] Loss: 0.30885 focal_loss 0.12685 dice_loss 0.18200 +Epoch [382/4000] Validation [3/4] Loss: 0.10659 focal_loss 0.05034 dice_loss 0.05625 +Epoch [382/4000] Validation [4/4] Loss: 0.19260 focal_loss 0.07580 dice_loss 0.11680 +Epoch [382/4000] Validation metric {'Val/mean dice_metric': 0.9649429321289062, 'Val/mean miou_metric': 0.9411476254463196, 'Val/mean f1': 0.9668120741844177, 'Val/mean precision': 0.963617205619812, 'Val/mean recall': 0.9700281023979187, 'Val/mean hd95_metric': 6.832843780517578} +Cheakpoint... +Epoch [382/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649429321289062, 'Val/mean miou_metric': 0.9411476254463196, 'Val/mean f1': 0.9668120741844177, 'Val/mean precision': 0.963617205619812, 'Val/mean recall': 0.9700281023979187, 'Val/mean hd95_metric': 6.832843780517578} +Epoch [383/4000] Training [1/16] Loss: 0.01487 +Epoch [383/4000] Training [2/16] Loss: 0.01308 +Epoch [383/4000] Training [3/16] Loss: 0.01797 +Epoch [383/4000] Training [4/16] Loss: 0.01272 +Epoch [383/4000] Training [5/16] Loss: 0.01557 +Epoch [383/4000] Training [6/16] Loss: 0.02196 +Epoch [383/4000] Training [7/16] Loss: 0.02233 +Epoch [383/4000] Training [8/16] Loss: 0.01630 +Epoch [383/4000] Training [9/16] Loss: 0.01392 +Epoch [383/4000] Training [10/16] Loss: 0.01577 +Epoch [383/4000] Training [11/16] Loss: 0.01665 +Epoch [383/4000] Training [12/16] Loss: 0.01372 +Epoch [383/4000] Training [13/16] Loss: 0.01570 +Epoch [383/4000] Training [14/16] Loss: 0.02381 +Epoch [383/4000] Training [15/16] Loss: 0.01595 +Epoch [383/4000] Training [16/16] Loss: 0.01841 +Epoch [383/4000] Training metric {'Train/mean dice_metric': 0.9875378608703613, 'Train/mean miou_metric': 0.9752370715141296, 'Train/mean f1': 0.9851300120353699, 'Train/mean precision': 0.9803044199943542, 'Train/mean recall': 0.9900033473968506, 'Train/mean hd95_metric': 1.5740745067596436} +Epoch [383/4000] Validation [1/4] Loss: 0.35280 focal_loss 0.24584 dice_loss 0.10696 +Epoch [383/4000] Validation [2/4] Loss: 0.37313 focal_loss 0.15865 dice_loss 0.21448 +Epoch [383/4000] Validation [3/4] Loss: 0.11391 focal_loss 0.05285 dice_loss 0.06106 +Epoch [383/4000] Validation [4/4] Loss: 0.18027 focal_loss 0.07276 dice_loss 0.10750 +Epoch [383/4000] Validation metric {'Val/mean dice_metric': 0.966697096824646, 'Val/mean miou_metric': 0.9435569643974304, 'Val/mean f1': 0.9683511257171631, 'Val/mean precision': 0.9642504453659058, 'Val/mean recall': 0.9724869132041931, 'Val/mean hd95_metric': 5.636462211608887} +Cheakpoint... +Epoch [383/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966697096824646, 'Val/mean miou_metric': 0.9435569643974304, 'Val/mean f1': 0.9683511257171631, 'Val/mean precision': 0.9642504453659058, 'Val/mean recall': 0.9724869132041931, 'Val/mean hd95_metric': 5.636462211608887} +Epoch [384/4000] Training [1/16] Loss: 0.02482 +Epoch [384/4000] Training [2/16] Loss: 0.01334 +Epoch [384/4000] Training [3/16] Loss: 0.01518 +Epoch [384/4000] Training [4/16] Loss: 0.01693 +Epoch [384/4000] Training [5/16] Loss: 0.01545 +Epoch [384/4000] Training [6/16] Loss: 0.02208 +Epoch [384/4000] Training [7/16] Loss: 0.01834 +Epoch [384/4000] Training [8/16] Loss: 0.02086 +Epoch [384/4000] Training [9/16] Loss: 0.02040 +Epoch [384/4000] Training [10/16] Loss: 0.01647 +Epoch [384/4000] Training [11/16] Loss: 0.02333 +Epoch [384/4000] Training [12/16] Loss: 0.01505 +Epoch [384/4000] Training [13/16] Loss: 0.02142 +Epoch [384/4000] Training [14/16] Loss: 0.01775 +Epoch [384/4000] Training [15/16] Loss: 0.01412 +Epoch [384/4000] Training [16/16] Loss: 0.01651 +Epoch [384/4000] Training metric {'Train/mean dice_metric': 0.9870885610580444, 'Train/mean miou_metric': 0.9744812250137329, 'Train/mean f1': 0.9849181771278381, 'Train/mean precision': 0.9802538156509399, 'Train/mean recall': 0.9896271228790283, 'Train/mean hd95_metric': 1.5524373054504395} +Epoch [384/4000] Validation [1/4] Loss: 0.20289 focal_loss 0.12963 dice_loss 0.07326 +Epoch [384/4000] Validation [2/4] Loss: 0.50449 focal_loss 0.23624 dice_loss 0.26825 +Epoch [384/4000] Validation [3/4] Loss: 0.10831 focal_loss 0.05367 dice_loss 0.05464 +Epoch [384/4000] Validation [4/4] Loss: 0.22005 focal_loss 0.11889 dice_loss 0.10116 +Epoch [384/4000] Validation metric {'Val/mean dice_metric': 0.9644563794136047, 'Val/mean miou_metric': 0.9415839910507202, 'Val/mean f1': 0.9670090675354004, 'Val/mean precision': 0.9650405645370483, 'Val/mean recall': 0.9689856767654419, 'Val/mean hd95_metric': 5.975669860839844} +Cheakpoint... +Epoch [384/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644563794136047, 'Val/mean miou_metric': 0.9415839910507202, 'Val/mean f1': 0.9670090675354004, 'Val/mean precision': 0.9650405645370483, 'Val/mean recall': 0.9689856767654419, 'Val/mean hd95_metric': 5.975669860839844} +Epoch [385/4000] Training [1/16] Loss: 0.01285 +Epoch [385/4000] Training [2/16] Loss: 0.02071 +Epoch [385/4000] Training [3/16] Loss: 0.01383 +Epoch [385/4000] Training [4/16] Loss: 0.01340 +Epoch [385/4000] Training [5/16] Loss: 0.02090 +Epoch [385/4000] Training [6/16] Loss: 0.02124 +Epoch [385/4000] Training [7/16] Loss: 0.01321 +Epoch [385/4000] Training [8/16] Loss: 0.01912 +Epoch [385/4000] Training [9/16] Loss: 0.01572 +Epoch [385/4000] Training [10/16] Loss: 0.01520 +Epoch [385/4000] Training [11/16] Loss: 0.01681 +Epoch [385/4000] Training [12/16] Loss: 0.02077 +Epoch [385/4000] Training [13/16] Loss: 0.01325 +Epoch [385/4000] Training [14/16] Loss: 0.01577 +Epoch [385/4000] Training [15/16] Loss: 0.01360 +Epoch [385/4000] Training [16/16] Loss: 0.02128 +Epoch [385/4000] Training metric {'Train/mean dice_metric': 0.987966775894165, 'Train/mean miou_metric': 0.9761353731155396, 'Train/mean f1': 0.9857043027877808, 'Train/mean precision': 0.9812111258506775, 'Train/mean recall': 0.9902389049530029, 'Train/mean hd95_metric': 1.4907041788101196} +Epoch [385/4000] Validation [1/4] Loss: 0.36477 focal_loss 0.25336 dice_loss 0.11141 +Epoch [385/4000] Validation [2/4] Loss: 0.37485 focal_loss 0.15937 dice_loss 0.21549 +Epoch [385/4000] Validation [3/4] Loss: 0.10962 focal_loss 0.05250 dice_loss 0.05712 +Epoch [385/4000] Validation [4/4] Loss: 0.23861 focal_loss 0.11720 dice_loss 0.12141 +Epoch [385/4000] Validation metric {'Val/mean dice_metric': 0.9653741121292114, 'Val/mean miou_metric': 0.9429484605789185, 'Val/mean f1': 0.9677523374557495, 'Val/mean precision': 0.965204119682312, 'Val/mean recall': 0.9703139662742615, 'Val/mean hd95_metric': 6.164680480957031} +Cheakpoint... +Epoch [385/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653741121292114, 'Val/mean miou_metric': 0.9429484605789185, 'Val/mean f1': 0.9677523374557495, 'Val/mean precision': 0.965204119682312, 'Val/mean recall': 0.9703139662742615, 'Val/mean hd95_metric': 6.164680480957031} +Epoch [386/4000] Training [1/16] Loss: 0.01278 +Epoch [386/4000] Training [2/16] Loss: 0.01492 +Epoch [386/4000] Training [3/16] Loss: 0.01557 +Epoch [386/4000] Training [4/16] Loss: 0.02514 +Epoch [386/4000] Training [5/16] Loss: 0.01793 +Epoch [386/4000] Training [6/16] Loss: 0.01751 +Epoch [386/4000] Training [7/16] Loss: 0.01561 +Epoch [386/4000] Training [8/16] Loss: 0.01997 +Epoch [386/4000] Training [9/16] Loss: 0.01698 +Epoch [386/4000] Training [10/16] Loss: 0.01950 +Epoch [386/4000] Training [11/16] Loss: 0.01601 +Epoch [386/4000] Training [12/16] Loss: 0.03035 +Epoch [386/4000] Training [13/16] Loss: 0.01192 +Epoch [386/4000] Training [14/16] Loss: 0.01579 +Epoch [386/4000] Training [15/16] Loss: 0.01389 +Epoch [386/4000] Training [16/16] Loss: 0.01637 +Epoch [386/4000] Training metric {'Train/mean dice_metric': 0.9878418445587158, 'Train/mean miou_metric': 0.9758422374725342, 'Train/mean f1': 0.9854418039321899, 'Train/mean precision': 0.9813294410705566, 'Train/mean recall': 0.9895887970924377, 'Train/mean hd95_metric': 1.5036076307296753} +Epoch [386/4000] Validation [1/4] Loss: 0.23268 focal_loss 0.14481 dice_loss 0.08787 +Epoch [386/4000] Validation [2/4] Loss: 0.35527 focal_loss 0.14064 dice_loss 0.21463 +Epoch [386/4000] Validation [3/4] Loss: 0.09370 focal_loss 0.04265 dice_loss 0.05105 +Epoch [386/4000] Validation [4/4] Loss: 0.21550 focal_loss 0.09763 dice_loss 0.11788 +Epoch [386/4000] Validation metric {'Val/mean dice_metric': 0.965287983417511, 'Val/mean miou_metric': 0.9427450299263, 'Val/mean f1': 0.9673863649368286, 'Val/mean precision': 0.9610661864280701, 'Val/mean recall': 0.9737903475761414, 'Val/mean hd95_metric': 5.997596740722656} +Cheakpoint... +Epoch [386/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965287983417511, 'Val/mean miou_metric': 0.9427450299263, 'Val/mean f1': 0.9673863649368286, 'Val/mean precision': 0.9610661864280701, 'Val/mean recall': 0.9737903475761414, 'Val/mean hd95_metric': 5.997596740722656} +Epoch [387/4000] Training [1/16] Loss: 0.01388 +Epoch [387/4000] Training [2/16] Loss: 0.01573 +Epoch [387/4000] Training [3/16] Loss: 0.01341 +Epoch [387/4000] Training [4/16] Loss: 0.02048 +Epoch [387/4000] Training [5/16] Loss: 0.01718 +Epoch [387/4000] Training [6/16] Loss: 0.01698 +Epoch [387/4000] Training [7/16] Loss: 0.01418 +Epoch [387/4000] Training [8/16] Loss: 0.02187 +Epoch [387/4000] Training [9/16] Loss: 0.02311 +Epoch [387/4000] Training [10/16] Loss: 0.02147 +Epoch [387/4000] Training [11/16] Loss: 0.01571 +Epoch [387/4000] Training [12/16] Loss: 0.03092 +Epoch [387/4000] Training [13/16] Loss: 0.02136 +Epoch [387/4000] Training [14/16] Loss: 0.02023 +Epoch [387/4000] Training [15/16] Loss: 0.01481 +Epoch [387/4000] Training [16/16] Loss: 0.02027 +Epoch [387/4000] Training metric {'Train/mean dice_metric': 0.9866040349006653, 'Train/mean miou_metric': 0.9739036560058594, 'Train/mean f1': 0.98452228307724, 'Train/mean precision': 0.9796781539916992, 'Train/mean recall': 0.989414632320404, 'Train/mean hd95_metric': 2.1660754680633545} +Epoch [387/4000] Validation [1/4] Loss: 0.34527 focal_loss 0.23383 dice_loss 0.11144 +Epoch [387/4000] Validation [2/4] Loss: 0.52214 focal_loss 0.23145 dice_loss 0.29069 +Epoch [387/4000] Validation [3/4] Loss: 0.18051 focal_loss 0.08693 dice_loss 0.09358 +Epoch [387/4000] Validation [4/4] Loss: 0.27980 focal_loss 0.16543 dice_loss 0.11437 +Epoch [387/4000] Validation metric {'Val/mean dice_metric': 0.9613134264945984, 'Val/mean miou_metric': 0.9379631280899048, 'Val/mean f1': 0.9653410911560059, 'Val/mean precision': 0.9646071791648865, 'Val/mean recall': 0.966076135635376, 'Val/mean hd95_metric': 6.832465171813965} +Cheakpoint... +Epoch [387/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9613134264945984, 'Val/mean miou_metric': 0.9379631280899048, 'Val/mean f1': 0.9653410911560059, 'Val/mean precision': 0.9646071791648865, 'Val/mean recall': 0.966076135635376, 'Val/mean hd95_metric': 6.832465171813965} +Epoch [388/4000] Training [1/16] Loss: 0.01595 +Epoch [388/4000] Training [2/16] Loss: 0.01553 +Epoch [388/4000] Training [3/16] Loss: 0.02115 +Epoch [388/4000] Training [4/16] Loss: 0.01502 +Epoch [388/4000] Training [5/16] Loss: 0.02174 +Epoch [388/4000] Training [6/16] Loss: 0.02195 +Epoch [388/4000] Training [7/16] Loss: 0.01781 +Epoch [388/4000] Training [8/16] Loss: 0.01789 +Epoch [388/4000] Training [9/16] Loss: 0.01884 +Epoch [388/4000] Training [10/16] Loss: 0.01686 +Epoch [388/4000] Training [11/16] Loss: 0.01728 +Epoch [388/4000] Training [12/16] Loss: 0.03283 +Epoch [388/4000] Training [13/16] Loss: 0.01275 +Epoch [388/4000] Training [14/16] Loss: 0.01863 +Epoch [388/4000] Training [15/16] Loss: 0.01749 +Epoch [388/4000] Training [16/16] Loss: 0.01830 +Epoch [388/4000] Training metric {'Train/mean dice_metric': 0.9859910011291504, 'Train/mean miou_metric': 0.9725139141082764, 'Train/mean f1': 0.9841533303260803, 'Train/mean precision': 0.9790512323379517, 'Train/mean recall': 0.9893088340759277, 'Train/mean hd95_metric': 2.368015766143799} +Epoch [388/4000] Validation [1/4] Loss: 0.39470 focal_loss 0.27629 dice_loss 0.11840 +Epoch [388/4000] Validation [2/4] Loss: 0.38522 focal_loss 0.14812 dice_loss 0.23710 +Epoch [388/4000] Validation [3/4] Loss: 0.10282 focal_loss 0.05070 dice_loss 0.05211 +Epoch [388/4000] Validation [4/4] Loss: 0.23230 focal_loss 0.13025 dice_loss 0.10205 +Epoch [388/4000] Validation metric {'Val/mean dice_metric': 0.9624830484390259, 'Val/mean miou_metric': 0.9386827349662781, 'Val/mean f1': 0.9650189280509949, 'Val/mean precision': 0.9647316336631775, 'Val/mean recall': 0.9653063416481018, 'Val/mean hd95_metric': 6.519529819488525} +Cheakpoint... +Epoch [388/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9624830484390259, 'Val/mean miou_metric': 0.9386827349662781, 'Val/mean f1': 0.9650189280509949, 'Val/mean precision': 0.9647316336631775, 'Val/mean recall': 0.9653063416481018, 'Val/mean hd95_metric': 6.519529819488525} +Epoch [389/4000] Training [1/16] Loss: 0.01603 +Epoch [389/4000] Training [2/16] Loss: 0.01411 +Epoch [389/4000] Training [3/16] Loss: 0.06825 +Epoch [389/4000] Training [4/16] Loss: 0.01880 +Epoch [389/4000] Training [5/16] Loss: 0.02506 +Epoch [389/4000] Training [6/16] Loss: 0.01549 +Epoch [389/4000] Training [7/16] Loss: 0.01908 +Epoch [389/4000] Training [8/16] Loss: 0.02541 +Epoch [389/4000] Training [9/16] Loss: 0.01714 +Epoch [389/4000] Training [10/16] Loss: 0.01312 +Epoch [389/4000] Training [11/16] Loss: 0.02497 +Epoch [389/4000] Training [12/16] Loss: 0.01629 +Epoch [389/4000] Training [13/16] Loss: 0.02066 +Epoch [389/4000] Training [14/16] Loss: 0.26725 +Epoch [389/4000] Training [15/16] Loss: 0.02249 +Epoch [389/4000] Training [16/16] Loss: 0.01622 +Epoch [389/4000] Training metric {'Train/mean dice_metric': 0.9842939376831055, 'Train/mean miou_metric': 0.9699805974960327, 'Train/mean f1': 0.9804254770278931, 'Train/mean precision': 0.974379301071167, 'Train/mean recall': 0.9865471720695496, 'Train/mean hd95_metric': 2.505840539932251} +Epoch [389/4000] Validation [1/4] Loss: 0.51643 focal_loss 0.35161 dice_loss 0.16482 +Epoch [389/4000] Validation [2/4] Loss: 0.45815 focal_loss 0.20932 dice_loss 0.24883 +Epoch [389/4000] Validation [3/4] Loss: 0.14968 focal_loss 0.07727 dice_loss 0.07241 +Epoch [389/4000] Validation [4/4] Loss: 0.16838 focal_loss 0.07920 dice_loss 0.08917 +Epoch [389/4000] Validation metric {'Val/mean dice_metric': 0.9594999551773071, 'Val/mean miou_metric': 0.9336465001106262, 'Val/mean f1': 0.9602339863777161, 'Val/mean precision': 0.9597631692886353, 'Val/mean recall': 0.9607052206993103, 'Val/mean hd95_metric': 7.475527763366699} +Cheakpoint... +Epoch [389/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9595], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9594999551773071, 'Val/mean miou_metric': 0.9336465001106262, 'Val/mean f1': 0.9602339863777161, 'Val/mean precision': 0.9597631692886353, 'Val/mean recall': 0.9607052206993103, 'Val/mean hd95_metric': 7.475527763366699} +Epoch [390/4000] Training [1/16] Loss: 0.02178 +Epoch [390/4000] Training [2/16] Loss: 0.02206 +Epoch [390/4000] Training [3/16] Loss: 0.02110 +Epoch [390/4000] Training [4/16] Loss: 0.01867 +Epoch [390/4000] Training [5/16] Loss: 0.02657 +Epoch [390/4000] Training [6/16] Loss: 0.02007 +Epoch [390/4000] Training [7/16] Loss: 0.01630 +Epoch [390/4000] Training [8/16] Loss: 0.02068 +Epoch [390/4000] Training [9/16] Loss: 0.05688 +Epoch [390/4000] Training [10/16] Loss: 0.02879 +Epoch [390/4000] Training [11/16] Loss: 0.02077 +Epoch [390/4000] Training [12/16] Loss: 0.01880 +Epoch [390/4000] Training [13/16] Loss: 0.02058 +Epoch [390/4000] Training [14/16] Loss: 0.02410 +Epoch [390/4000] Training [15/16] Loss: 0.02251 +Epoch [390/4000] Training [16/16] Loss: 0.02824 +Epoch [390/4000] Training metric {'Train/mean dice_metric': 0.9837071299552917, 'Train/mean miou_metric': 0.9685525298118591, 'Train/mean f1': 0.9816960096359253, 'Train/mean precision': 0.9782903790473938, 'Train/mean recall': 0.9851254224777222, 'Train/mean hd95_metric': 3.329620599746704} +Epoch [390/4000] Validation [1/4] Loss: 0.17909 focal_loss 0.11177 dice_loss 0.06732 +Epoch [390/4000] Validation [2/4] Loss: 0.35858 focal_loss 0.15673 dice_loss 0.20185 +Epoch [390/4000] Validation [3/4] Loss: 0.13923 focal_loss 0.07185 dice_loss 0.06738 +Epoch [390/4000] Validation [4/4] Loss: 0.34305 focal_loss 0.20455 dice_loss 0.13850 +Epoch [390/4000] Validation metric {'Val/mean dice_metric': 0.9592048525810242, 'Val/mean miou_metric': 0.9338771104812622, 'Val/mean f1': 0.9642186164855957, 'Val/mean precision': 0.9582844972610474, 'Val/mean recall': 0.970226526260376, 'Val/mean hd95_metric': 8.857156753540039} +Cheakpoint... +Epoch [390/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9592], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9592048525810242, 'Val/mean miou_metric': 0.9338771104812622, 'Val/mean f1': 0.9642186164855957, 'Val/mean precision': 0.9582844972610474, 'Val/mean recall': 0.970226526260376, 'Val/mean hd95_metric': 8.857156753540039} +Epoch [391/4000] Training [1/16] Loss: 0.02380 +Epoch [391/4000] Training [2/16] Loss: 0.01737 +Epoch [391/4000] Training [3/16] Loss: 0.01730 +Epoch [391/4000] Training [4/16] Loss: 0.01421 +Epoch [391/4000] Training [5/16] Loss: 0.01981 +Epoch [391/4000] Training [6/16] Loss: 0.02851 +Epoch [391/4000] Training [7/16] Loss: 0.07314 +Epoch [391/4000] Training [8/16] Loss: 0.01546 +Epoch [391/4000] Training [9/16] Loss: 0.01904 +Epoch [391/4000] Training [10/16] Loss: 0.02335 +Epoch [391/4000] Training [11/16] Loss: 0.01680 +Epoch [391/4000] Training [12/16] Loss: 0.02323 +Epoch [391/4000] Training [13/16] Loss: 0.01581 +Epoch [391/4000] Training [14/16] Loss: 0.02060 +Epoch [391/4000] Training [15/16] Loss: 0.02206 +Epoch [391/4000] Training [16/16] Loss: 0.05243 +Epoch [391/4000] Training metric {'Train/mean dice_metric': 0.9853968024253845, 'Train/mean miou_metric': 0.9715384244918823, 'Train/mean f1': 0.98332279920578, 'Train/mean precision': 0.9790071845054626, 'Train/mean recall': 0.9876766800880432, 'Train/mean hd95_metric': 2.4937472343444824} +Epoch [391/4000] Validation [1/4] Loss: 0.15074 focal_loss 0.08549 dice_loss 0.06525 +Epoch [391/4000] Validation [2/4] Loss: 0.22586 focal_loss 0.07769 dice_loss 0.14817 +Epoch [391/4000] Validation [3/4] Loss: 0.18423 focal_loss 0.08046 dice_loss 0.10376 +Epoch [391/4000] Validation [4/4] Loss: 0.18522 focal_loss 0.09595 dice_loss 0.08927 +Epoch [391/4000] Validation metric {'Val/mean dice_metric': 0.963456928730011, 'Val/mean miou_metric': 0.9391195178031921, 'Val/mean f1': 0.9665128588676453, 'Val/mean precision': 0.9582867622375488, 'Val/mean recall': 0.9748813509941101, 'Val/mean hd95_metric': 7.419353485107422} +Cheakpoint... +Epoch [391/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9635], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963456928730011, 'Val/mean miou_metric': 0.9391195178031921, 'Val/mean f1': 0.9665128588676453, 'Val/mean precision': 0.9582867622375488, 'Val/mean recall': 0.9748813509941101, 'Val/mean hd95_metric': 7.419353485107422} +Epoch [392/4000] Training [1/16] Loss: 0.01714 +Epoch [392/4000] Training [2/16] Loss: 0.01792 +Epoch [392/4000] Training [3/16] Loss: 0.01634 +Epoch [392/4000] Training [4/16] Loss: 0.02049 +Epoch [392/4000] Training [5/16] Loss: 0.01556 +Epoch [392/4000] Training [6/16] Loss: 0.01629 +Epoch [392/4000] Training [7/16] Loss: 0.02093 +Epoch [392/4000] Training [8/16] Loss: 0.01939 +Epoch [392/4000] Training [9/16] Loss: 0.01500 +Epoch [392/4000] Training [10/16] Loss: 0.02308 +Epoch [392/4000] Training [11/16] Loss: 0.03301 +Epoch [392/4000] Training [12/16] Loss: 0.01717 +Epoch [392/4000] Training [13/16] Loss: 0.02132 +Epoch [392/4000] Training [14/16] Loss: 0.01748 +Epoch [392/4000] Training [15/16] Loss: 0.01225 +Epoch [392/4000] Training [16/16] Loss: 0.01248 +Epoch [392/4000] Training metric {'Train/mean dice_metric': 0.9865219593048096, 'Train/mean miou_metric': 0.9734790325164795, 'Train/mean f1': 0.9845579266548157, 'Train/mean precision': 0.980278730392456, 'Train/mean recall': 0.9888745546340942, 'Train/mean hd95_metric': 2.012418270111084} +Epoch [392/4000] Validation [1/4] Loss: 0.18263 focal_loss 0.11365 dice_loss 0.06898 +Epoch [392/4000] Validation [2/4] Loss: 0.38931 focal_loss 0.16730 dice_loss 0.22201 +Epoch [392/4000] Validation [3/4] Loss: 0.16360 focal_loss 0.07361 dice_loss 0.08999 +Epoch [392/4000] Validation [4/4] Loss: 0.23203 focal_loss 0.12234 dice_loss 0.10969 +Epoch [392/4000] Validation metric {'Val/mean dice_metric': 0.9639240503311157, 'Val/mean miou_metric': 0.9400884509086609, 'Val/mean f1': 0.9678760170936584, 'Val/mean precision': 0.9638267159461975, 'Val/mean recall': 0.9719594717025757, 'Val/mean hd95_metric': 6.765474796295166} +Cheakpoint... +Epoch [392/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639240503311157, 'Val/mean miou_metric': 0.9400884509086609, 'Val/mean f1': 0.9678760170936584, 'Val/mean precision': 0.9638267159461975, 'Val/mean recall': 0.9719594717025757, 'Val/mean hd95_metric': 6.765474796295166} +Epoch [393/4000] Training [1/16] Loss: 0.01549 +Epoch [393/4000] Training [2/16] Loss: 0.01597 +Epoch [393/4000] Training [3/16] Loss: 0.01903 +Epoch [393/4000] Training [4/16] Loss: 0.01426 +Epoch [393/4000] Training [5/16] Loss: 0.01407 +Epoch [393/4000] Training [6/16] Loss: 0.01916 +Epoch [393/4000] Training [7/16] Loss: 0.01452 +Epoch [393/4000] Training [8/16] Loss: 0.01664 +Epoch [393/4000] Training [9/16] Loss: 0.01703 +Epoch [393/4000] Training [10/16] Loss: 0.01879 +Epoch [393/4000] Training [11/16] Loss: 0.02198 +Epoch [393/4000] Training [12/16] Loss: 0.01418 +Epoch [393/4000] Training [13/16] Loss: 0.01846 +Epoch [393/4000] Training [14/16] Loss: 0.01485 +Epoch [393/4000] Training [15/16] Loss: 0.03037 +Epoch [393/4000] Training [16/16] Loss: 0.01709 +Epoch [393/4000] Training metric {'Train/mean dice_metric': 0.9872859716415405, 'Train/mean miou_metric': 0.9747933149337769, 'Train/mean f1': 0.9849582314491272, 'Train/mean precision': 0.980719804763794, 'Train/mean recall': 0.9892334938049316, 'Train/mean hd95_metric': 1.5838392972946167} +Epoch [393/4000] Validation [1/4] Loss: 0.20983 focal_loss 0.13927 dice_loss 0.07057 +Epoch [393/4000] Validation [2/4] Loss: 0.40690 focal_loss 0.14920 dice_loss 0.25770 +Epoch [393/4000] Validation [3/4] Loss: 0.16179 focal_loss 0.07420 dice_loss 0.08760 +Epoch [393/4000] Validation [4/4] Loss: 0.27875 focal_loss 0.14870 dice_loss 0.13005 +Epoch [393/4000] Validation metric {'Val/mean dice_metric': 0.9616314768791199, 'Val/mean miou_metric': 0.9374394416809082, 'Val/mean f1': 0.9634476900100708, 'Val/mean precision': 0.9525379538536072, 'Val/mean recall': 0.9746102094650269, 'Val/mean hd95_metric': 8.496342658996582} +Cheakpoint... +Epoch [393/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9616], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616314768791199, 'Val/mean miou_metric': 0.9374394416809082, 'Val/mean f1': 0.9634476900100708, 'Val/mean precision': 0.9525379538536072, 'Val/mean recall': 0.9746102094650269, 'Val/mean hd95_metric': 8.496342658996582} +Epoch [394/4000] Training [1/16] Loss: 0.01802 +Epoch [394/4000] Training [2/16] Loss: 0.02788 +Epoch [394/4000] Training [3/16] Loss: 0.01865 +Epoch [394/4000] Training [4/16] Loss: 0.02083 +Epoch [394/4000] Training [5/16] Loss: 0.01459 +Epoch [394/4000] Training [6/16] Loss: 0.02404 +Epoch [394/4000] Training [7/16] Loss: 0.01506 +Epoch [394/4000] Training [8/16] Loss: 0.01402 +Epoch [394/4000] Training [9/16] Loss: 0.01320 +Epoch [394/4000] Training [10/16] Loss: 0.01260 +Epoch [394/4000] Training [11/16] Loss: 0.02117 +Epoch [394/4000] Training [12/16] Loss: 0.01644 +Epoch [394/4000] Training [13/16] Loss: 0.01824 +Epoch [394/4000] Training [14/16] Loss: 0.01615 +Epoch [394/4000] Training [15/16] Loss: 0.02578 +Epoch [394/4000] Training [16/16] Loss: 0.01866 +Epoch [394/4000] Training metric {'Train/mean dice_metric': 0.9877495765686035, 'Train/mean miou_metric': 0.9756694436073303, 'Train/mean f1': 0.9849310517311096, 'Train/mean precision': 0.9805797934532166, 'Train/mean recall': 0.9893211126327515, 'Train/mean hd95_metric': 2.3449249267578125} +Epoch [394/4000] Validation [1/4] Loss: 0.14097 focal_loss 0.08129 dice_loss 0.05968 +Epoch [394/4000] Validation [2/4] Loss: 0.32454 focal_loss 0.10508 dice_loss 0.21946 +Epoch [394/4000] Validation [3/4] Loss: 0.18612 focal_loss 0.09456 dice_loss 0.09156 +Epoch [394/4000] Validation [4/4] Loss: 0.21483 focal_loss 0.11618 dice_loss 0.09864 +Epoch [394/4000] Validation metric {'Val/mean dice_metric': 0.9627214670181274, 'Val/mean miou_metric': 0.9392784237861633, 'Val/mean f1': 0.9658122062683105, 'Val/mean precision': 0.9609240889549255, 'Val/mean recall': 0.9707501530647278, 'Val/mean hd95_metric': 7.409123420715332} +Cheakpoint... +Epoch [394/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9627], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9627214670181274, 'Val/mean miou_metric': 0.9392784237861633, 'Val/mean f1': 0.9658122062683105, 'Val/mean precision': 0.9609240889549255, 'Val/mean recall': 0.9707501530647278, 'Val/mean hd95_metric': 7.409123420715332} +Epoch [395/4000] Training [1/16] Loss: 0.01557 +Epoch [395/4000] Training [2/16] Loss: 0.01907 +Epoch [395/4000] Training [3/16] Loss: 0.01492 +Epoch [395/4000] Training [4/16] Loss: 0.01355 +Epoch [395/4000] Training [5/16] Loss: 0.01343 +Epoch [395/4000] Training [6/16] Loss: 0.02251 +Epoch [395/4000] Training [7/16] Loss: 0.01294 +Epoch [395/4000] Training [8/16] Loss: 0.01344 +Epoch [395/4000] Training [9/16] Loss: 0.01544 +Epoch [395/4000] Training [10/16] Loss: 0.02053 +Epoch [395/4000] Training [11/16] Loss: 0.01397 +Epoch [395/4000] Training [12/16] Loss: 0.01681 +Epoch [395/4000] Training [13/16] Loss: 0.02315 +Epoch [395/4000] Training [14/16] Loss: 0.01987 +Epoch [395/4000] Training [15/16] Loss: 0.01590 +Epoch [395/4000] Training [16/16] Loss: 0.01656 +Epoch [395/4000] Training metric {'Train/mean dice_metric': 0.9883965253829956, 'Train/mean miou_metric': 0.9769386053085327, 'Train/mean f1': 0.985715925693512, 'Train/mean precision': 0.9809517860412598, 'Train/mean recall': 0.990526556968689, 'Train/mean hd95_metric': 1.5055198669433594} +Epoch [395/4000] Validation [1/4] Loss: 0.17766 focal_loss 0.10998 dice_loss 0.06769 +Epoch [395/4000] Validation [2/4] Loss: 0.31362 focal_loss 0.14075 dice_loss 0.17287 +Epoch [395/4000] Validation [3/4] Loss: 0.22297 focal_loss 0.11984 dice_loss 0.10313 +Epoch [395/4000] Validation [4/4] Loss: 0.22885 focal_loss 0.11593 dice_loss 0.11292 +Epoch [395/4000] Validation metric {'Val/mean dice_metric': 0.9626821279525757, 'Val/mean miou_metric': 0.9399688839912415, 'Val/mean f1': 0.9641076326370239, 'Val/mean precision': 0.9515781998634338, 'Val/mean recall': 0.976971447467804, 'Val/mean hd95_metric': 8.087885856628418} +Cheakpoint... +Epoch [395/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9627], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9626821279525757, 'Val/mean miou_metric': 0.9399688839912415, 'Val/mean f1': 0.9641076326370239, 'Val/mean precision': 0.9515781998634338, 'Val/mean recall': 0.976971447467804, 'Val/mean hd95_metric': 8.087885856628418} +Epoch [396/4000] Training [1/16] Loss: 0.01525 +Epoch [396/4000] Training [2/16] Loss: 0.01265 +Epoch [396/4000] Training [3/16] Loss: 0.02147 +Epoch [396/4000] Training [4/16] Loss: 0.01499 +Epoch [396/4000] Training [5/16] Loss: 0.02283 +Epoch [396/4000] Training [6/16] Loss: 0.01328 +Epoch [396/4000] Training [7/16] Loss: 0.02283 +Epoch [396/4000] Training [8/16] Loss: 0.02005 +Epoch [396/4000] Training [9/16] Loss: 0.03251 +Epoch [396/4000] Training [10/16] Loss: 0.02433 +Epoch [396/4000] Training [11/16] Loss: 0.01466 +Epoch [396/4000] Training [12/16] Loss: 0.02320 +Epoch [396/4000] Training [13/16] Loss: 0.01558 +Epoch [396/4000] Training [14/16] Loss: 0.01658 +Epoch [396/4000] Training [15/16] Loss: 0.01759 +Epoch [396/4000] Training [16/16] Loss: 0.01946 +Epoch [396/4000] Training metric {'Train/mean dice_metric': 0.9865522384643555, 'Train/mean miou_metric': 0.9734642505645752, 'Train/mean f1': 0.9843757748603821, 'Train/mean precision': 0.9800813794136047, 'Train/mean recall': 0.9887079000473022, 'Train/mean hd95_metric': 2.037139415740967} +Epoch [396/4000] Validation [1/4] Loss: 0.24043 focal_loss 0.14774 dice_loss 0.09268 +Epoch [396/4000] Validation [2/4] Loss: 0.28804 focal_loss 0.11772 dice_loss 0.17032 +Epoch [396/4000] Validation [3/4] Loss: 0.12481 focal_loss 0.06249 dice_loss 0.06232 +Epoch [396/4000] Validation [4/4] Loss: 0.26592 focal_loss 0.13971 dice_loss 0.12621 +Epoch [396/4000] Validation metric {'Val/mean dice_metric': 0.9635719060897827, 'Val/mean miou_metric': 0.9392238855361938, 'Val/mean f1': 0.965473473072052, 'Val/mean precision': 0.9626758694648743, 'Val/mean recall': 0.9682873487472534, 'Val/mean hd95_metric': 6.826568603515625} +Cheakpoint... +Epoch [396/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9635719060897827, 'Val/mean miou_metric': 0.9392238855361938, 'Val/mean f1': 0.965473473072052, 'Val/mean precision': 0.9626758694648743, 'Val/mean recall': 0.9682873487472534, 'Val/mean hd95_metric': 6.826568603515625} +Epoch [397/4000] Training [1/16] Loss: 0.01828 +Epoch [397/4000] Training [2/16] Loss: 0.01335 +Epoch [397/4000] Training [3/16] Loss: 0.02479 +Epoch [397/4000] Training [4/16] Loss: 0.01516 +Epoch [397/4000] Training [5/16] Loss: 0.01746 +Epoch [397/4000] Training [6/16] Loss: 0.01754 +Epoch [397/4000] Training [7/16] Loss: 0.01457 +Epoch [397/4000] Training [8/16] Loss: 0.02207 +Epoch [397/4000] Training [9/16] Loss: 0.01649 +Epoch [397/4000] Training [10/16] Loss: 0.01646 +Epoch [397/4000] Training [11/16] Loss: 0.01783 +Epoch [397/4000] Training [12/16] Loss: 0.04140 +Epoch [397/4000] Training [13/16] Loss: 0.01647 +Epoch [397/4000] Training [14/16] Loss: 0.02059 +Epoch [397/4000] Training [15/16] Loss: 0.01515 +Epoch [397/4000] Training [16/16] Loss: 0.01472 +Epoch [397/4000] Training metric {'Train/mean dice_metric': 0.987122654914856, 'Train/mean miou_metric': 0.9745583534240723, 'Train/mean f1': 0.9843241572380066, 'Train/mean precision': 0.9793591499328613, 'Train/mean recall': 0.9893397092819214, 'Train/mean hd95_metric': 1.6861683130264282} +Epoch [397/4000] Validation [1/4] Loss: 0.29275 focal_loss 0.17855 dice_loss 0.11420 +Epoch [397/4000] Validation [2/4] Loss: 0.28129 focal_loss 0.13184 dice_loss 0.14945 +Epoch [397/4000] Validation [3/4] Loss: 0.18172 focal_loss 0.08380 dice_loss 0.09792 +Epoch [397/4000] Validation [4/4] Loss: 0.24398 focal_loss 0.12999 dice_loss 0.11400 +Epoch [397/4000] Validation metric {'Val/mean dice_metric': 0.9636330604553223, 'Val/mean miou_metric': 0.9392833709716797, 'Val/mean f1': 0.9656140804290771, 'Val/mean precision': 0.9654368758201599, 'Val/mean recall': 0.9657914638519287, 'Val/mean hd95_metric': 6.396181583404541} +Cheakpoint... +Epoch [397/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636330604553223, 'Val/mean miou_metric': 0.9392833709716797, 'Val/mean f1': 0.9656140804290771, 'Val/mean precision': 0.9654368758201599, 'Val/mean recall': 0.9657914638519287, 'Val/mean hd95_metric': 6.396181583404541} +Epoch [398/4000] Training [1/16] Loss: 0.01695 +Epoch [398/4000] Training [2/16] Loss: 0.02170 +Epoch [398/4000] Training [3/16] Loss: 0.01727 +Epoch [398/4000] Training [4/16] Loss: 0.02377 +Epoch [398/4000] Training [5/16] Loss: 0.02031 +Epoch [398/4000] Training [6/16] Loss: 0.01598 +Epoch [398/4000] Training [7/16] Loss: 0.01506 +Epoch [398/4000] Training [8/16] Loss: 0.10720 +Epoch [398/4000] Training [9/16] Loss: 0.01210 +Epoch [398/4000] Training [10/16] Loss: 0.02145 +Epoch [398/4000] Training [11/16] Loss: 0.01273 +Epoch [398/4000] Training [12/16] Loss: 0.01520 +Epoch [398/4000] Training [13/16] Loss: 0.01375 +Epoch [398/4000] Training [14/16] Loss: 0.01703 +Epoch [398/4000] Training [15/16] Loss: 0.01945 +Epoch [398/4000] Training [16/16] Loss: 0.02155 +Epoch [398/4000] Training metric {'Train/mean dice_metric': 0.9874236583709717, 'Train/mean miou_metric': 0.9753100872039795, 'Train/mean f1': 0.9848192930221558, 'Train/mean precision': 0.9798198342323303, 'Train/mean recall': 0.9898701310157776, 'Train/mean hd95_metric': 1.797258734703064} +Epoch [398/4000] Validation [1/4] Loss: 0.14717 focal_loss 0.08518 dice_loss 0.06200 +Epoch [398/4000] Validation [2/4] Loss: 0.36759 focal_loss 0.13727 dice_loss 0.23033 +Epoch [398/4000] Validation [3/4] Loss: 0.13504 focal_loss 0.05618 dice_loss 0.07886 +Epoch [398/4000] Validation [4/4] Loss: 0.22579 focal_loss 0.12427 dice_loss 0.10152 +Epoch [398/4000] Validation metric {'Val/mean dice_metric': 0.9639976620674133, 'Val/mean miou_metric': 0.941653847694397, 'Val/mean f1': 0.9673322439193726, 'Val/mean precision': 0.9637466669082642, 'Val/mean recall': 0.9709444642066956, 'Val/mean hd95_metric': 6.336501121520996} +Cheakpoint... +Epoch [398/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639976620674133, 'Val/mean miou_metric': 0.941653847694397, 'Val/mean f1': 0.9673322439193726, 'Val/mean precision': 0.9637466669082642, 'Val/mean recall': 0.9709444642066956, 'Val/mean hd95_metric': 6.336501121520996} +Epoch [399/4000] Training [1/16] Loss: 0.01728 +Epoch [399/4000] Training [2/16] Loss: 0.01590 +Epoch [399/4000] Training [3/16] Loss: 0.01839 +Epoch [399/4000] Training [4/16] Loss: 0.02492 +Epoch [399/4000] Training [5/16] Loss: 0.01620 +Epoch [399/4000] Training [6/16] Loss: 0.01896 +Epoch [399/4000] Training [7/16] Loss: 0.05854 +Epoch [399/4000] Training [8/16] Loss: 0.01662 +Epoch [399/4000] Training [9/16] Loss: 0.01707 +Epoch [399/4000] Training [10/16] Loss: 0.01673 +Epoch [399/4000] Training [11/16] Loss: 0.01754 +Epoch [399/4000] Training [12/16] Loss: 0.01842 +Epoch [399/4000] Training [13/16] Loss: 0.02539 +Epoch [399/4000] Training [14/16] Loss: 0.02087 +Epoch [399/4000] Training [15/16] Loss: 0.01602 +Epoch [399/4000] Training [16/16] Loss: 0.01718 +Epoch [399/4000] Training metric {'Train/mean dice_metric': 0.9873030781745911, 'Train/mean miou_metric': 0.9748039841651917, 'Train/mean f1': 0.9847391843795776, 'Train/mean precision': 0.9807257056236267, 'Train/mean recall': 0.9887856841087341, 'Train/mean hd95_metric': 1.723158359527588} +Epoch [399/4000] Validation [1/4] Loss: 0.28644 focal_loss 0.17988 dice_loss 0.10656 +Epoch [399/4000] Validation [2/4] Loss: 0.29689 focal_loss 0.11541 dice_loss 0.18148 +Epoch [399/4000] Validation [3/4] Loss: 0.18475 focal_loss 0.09191 dice_loss 0.09283 +Epoch [399/4000] Validation [4/4] Loss: 0.21051 focal_loss 0.09868 dice_loss 0.11184 +Epoch [399/4000] Validation metric {'Val/mean dice_metric': 0.9646102786064148, 'Val/mean miou_metric': 0.9407164454460144, 'Val/mean f1': 0.9632391929626465, 'Val/mean precision': 0.9538527131080627, 'Val/mean recall': 0.9728123545646667, 'Val/mean hd95_metric': 7.260819435119629} +Cheakpoint... +Epoch [399/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9646], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646102786064148, 'Val/mean miou_metric': 0.9407164454460144, 'Val/mean f1': 0.9632391929626465, 'Val/mean precision': 0.9538527131080627, 'Val/mean recall': 0.9728123545646667, 'Val/mean hd95_metric': 7.260819435119629} +Epoch [400/4000] Training [1/16] Loss: 0.01442 +Epoch [400/4000] Training [2/16] Loss: 0.01382 +Epoch [400/4000] Training [3/16] Loss: 0.01452 +Epoch [400/4000] Training [4/16] Loss: 0.01487 +Epoch [400/4000] Training [5/16] Loss: 0.01725 +Epoch [400/4000] Training [6/16] Loss: 0.01258 +Epoch [400/4000] Training [7/16] Loss: 0.01773 +Epoch [400/4000] Training [8/16] Loss: 0.01622 +Epoch [400/4000] Training [9/16] Loss: 0.01933 +Epoch [400/4000] Training [10/16] Loss: 0.02046 +Epoch [400/4000] Training [11/16] Loss: 0.02063 +Epoch [400/4000] Training [12/16] Loss: 0.01974 +Epoch [400/4000] Training [13/16] Loss: 0.01565 +Epoch [400/4000] Training [14/16] Loss: 0.01230 +Epoch [400/4000] Training [15/16] Loss: 0.01947 +Epoch [400/4000] Training [16/16] Loss: 0.01989 +Epoch [400/4000] Training metric {'Train/mean dice_metric': 0.9885320663452148, 'Train/mean miou_metric': 0.977142333984375, 'Train/mean f1': 0.9855958223342896, 'Train/mean precision': 0.9811549782752991, 'Train/mean recall': 0.990077018737793, 'Train/mean hd95_metric': 1.4945485591888428} +Epoch [400/4000] Validation [1/4] Loss: 0.11422 focal_loss 0.05498 dice_loss 0.05924 +Epoch [400/4000] Validation [2/4] Loss: 0.27447 focal_loss 0.11486 dice_loss 0.15961 +Epoch [400/4000] Validation [3/4] Loss: 0.13531 focal_loss 0.06317 dice_loss 0.07213 +Epoch [400/4000] Validation [4/4] Loss: 0.21788 focal_loss 0.10017 dice_loss 0.11771 +Epoch [400/4000] Validation metric {'Val/mean dice_metric': 0.9665634036064148, 'Val/mean miou_metric': 0.9441372752189636, 'Val/mean f1': 0.9661359786987305, 'Val/mean precision': 0.9581904411315918, 'Val/mean recall': 0.9742145538330078, 'Val/mean hd95_metric': 6.454281806945801} +Cheakpoint... +Epoch [400/4000] best acc:tensor([0.9681], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665634036064148, 'Val/mean miou_metric': 0.9441372752189636, 'Val/mean f1': 0.9661359786987305, 'Val/mean precision': 0.9581904411315918, 'Val/mean recall': 0.9742145538330078, 'Val/mean hd95_metric': 6.454281806945801} +Epoch [401/4000] Training [1/16] Loss: 0.01453 +Epoch [401/4000] Training [2/16] Loss: 0.01558 +Epoch [401/4000] Training [3/16] Loss: 0.01908 +Epoch [401/4000] Training [4/16] Loss: 0.01633 +Epoch [401/4000] Training [5/16] Loss: 0.01732 +Epoch [401/4000] Training [6/16] Loss: 0.01270 +Epoch [401/4000] Training [7/16] Loss: 0.01193 +Epoch [401/4000] Training [8/16] Loss: 0.01413 +Epoch [401/4000] Training [9/16] Loss: 0.01640 +Epoch [401/4000] Training [10/16] Loss: 0.01952 +Epoch [401/4000] Training [11/16] Loss: 0.01608 +Epoch [401/4000] Training [12/16] Loss: 0.01423 +Epoch [401/4000] Training [13/16] Loss: 0.01756 +Epoch [401/4000] Training [14/16] Loss: 0.01361 +Epoch [401/4000] Training [15/16] Loss: 0.01936 +Epoch [401/4000] Training [16/16] Loss: 0.01566 +Epoch [401/4000] Training metric {'Train/mean dice_metric': 0.9881927967071533, 'Train/mean miou_metric': 0.9765876531600952, 'Train/mean f1': 0.9860286712646484, 'Train/mean precision': 0.9814401865005493, 'Train/mean recall': 0.9906602501869202, 'Train/mean hd95_metric': 1.4100857973098755} +Epoch [401/4000] Validation [1/4] Loss: 0.44989 focal_loss 0.32689 dice_loss 0.12300 +Epoch [401/4000] Validation [2/4] Loss: 0.19858 focal_loss 0.07608 dice_loss 0.12250 +Epoch [401/4000] Validation [3/4] Loss: 0.12834 focal_loss 0.05543 dice_loss 0.07291 +Epoch [401/4000] Validation [4/4] Loss: 0.20108 focal_loss 0.10487 dice_loss 0.09621 +Epoch [401/4000] Validation metric {'Val/mean dice_metric': 0.9686072468757629, 'Val/mean miou_metric': 0.9462603330612183, 'Val/mean f1': 0.9685649275779724, 'Val/mean precision': 0.9626407027244568, 'Val/mean recall': 0.9745625257492065, 'Val/mean hd95_metric': 6.2158613204956055} +Cheakpoint... +Epoch [401/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686072468757629, 'Val/mean miou_metric': 0.9462603330612183, 'Val/mean f1': 0.9685649275779724, 'Val/mean precision': 0.9626407027244568, 'Val/mean recall': 0.9745625257492065, 'Val/mean hd95_metric': 6.2158613204956055} +Epoch [402/4000] Training [1/16] Loss: 0.01583 +Epoch [402/4000] Training [2/16] Loss: 0.01738 +Epoch [402/4000] Training [3/16] Loss: 0.01601 +Epoch [402/4000] Training [4/16] Loss: 0.01607 +Epoch [402/4000] Training [5/16] Loss: 0.01844 +Epoch [402/4000] Training [6/16] Loss: 0.02180 +Epoch [402/4000] Training [7/16] Loss: 0.02036 +Epoch [402/4000] Training [8/16] Loss: 0.01100 +Epoch [402/4000] Training [9/16] Loss: 0.01296 +Epoch [402/4000] Training [10/16] Loss: 0.01317 +Epoch [402/4000] Training [11/16] Loss: 0.01065 +Epoch [402/4000] Training [12/16] Loss: 0.01445 +Epoch [402/4000] Training [13/16] Loss: 0.01552 +Epoch [402/4000] Training [14/16] Loss: 0.01963 +Epoch [402/4000] Training [15/16] Loss: 0.02700 +Epoch [402/4000] Training [16/16] Loss: 0.02177 +Epoch [402/4000] Training metric {'Train/mean dice_metric': 0.9888991713523865, 'Train/mean miou_metric': 0.977873682975769, 'Train/mean f1': 0.9861341118812561, 'Train/mean precision': 0.981460452079773, 'Train/mean recall': 0.990852415561676, 'Train/mean hd95_metric': 1.3376325368881226} +Epoch [402/4000] Validation [1/4] Loss: 0.39208 focal_loss 0.27454 dice_loss 0.11754 +Epoch [402/4000] Validation [2/4] Loss: 0.33660 focal_loss 0.13017 dice_loss 0.20642 +Epoch [402/4000] Validation [3/4] Loss: 0.11452 focal_loss 0.05549 dice_loss 0.05903 +Epoch [402/4000] Validation [4/4] Loss: 0.18456 focal_loss 0.09451 dice_loss 0.09005 +Epoch [402/4000] Validation metric {'Val/mean dice_metric': 0.9655143618583679, 'Val/mean miou_metric': 0.9432918429374695, 'Val/mean f1': 0.9672721028327942, 'Val/mean precision': 0.9658235907554626, 'Val/mean recall': 0.9687249660491943, 'Val/mean hd95_metric': 5.79410982131958} +Cheakpoint... +Epoch [402/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655143618583679, 'Val/mean miou_metric': 0.9432918429374695, 'Val/mean f1': 0.9672721028327942, 'Val/mean precision': 0.9658235907554626, 'Val/mean recall': 0.9687249660491943, 'Val/mean hd95_metric': 5.79410982131958} +Epoch [403/4000] Training [1/16] Loss: 0.01593 +Epoch [403/4000] Training [2/16] Loss: 0.01488 +Epoch [403/4000] Training [3/16] Loss: 0.01694 +Epoch [403/4000] Training [4/16] Loss: 0.01522 +Epoch [403/4000] Training [5/16] Loss: 0.01808 +Epoch [403/4000] Training [6/16] Loss: 0.01299 +Epoch [403/4000] Training [7/16] Loss: 0.01322 +Epoch [403/4000] Training [8/16] Loss: 0.01676 +Epoch [403/4000] Training [9/16] Loss: 0.01393 +Epoch [403/4000] Training [10/16] Loss: 0.01678 +Epoch [403/4000] Training [11/16] Loss: 0.01666 +Epoch [403/4000] Training [12/16] Loss: 0.01301 +Epoch [403/4000] Training [13/16] Loss: 0.01698 +Epoch [403/4000] Training [14/16] Loss: 0.01719 +Epoch [403/4000] Training [15/16] Loss: 0.01679 +Epoch [403/4000] Training [16/16] Loss: 0.01535 +Epoch [403/4000] Training metric {'Train/mean dice_metric': 0.9868534803390503, 'Train/mean miou_metric': 0.9750211238861084, 'Train/mean f1': 0.9858978986740112, 'Train/mean precision': 0.9811739921569824, 'Train/mean recall': 0.990667462348938, 'Train/mean hd95_metric': 2.0463805198669434} +Epoch [403/4000] Validation [1/4] Loss: 0.14086 focal_loss 0.08337 dice_loss 0.05750 +Epoch [403/4000] Validation [2/4] Loss: 0.25148 focal_loss 0.11778 dice_loss 0.13370 +Epoch [403/4000] Validation [3/4] Loss: 0.14961 focal_loss 0.07553 dice_loss 0.07408 +Epoch [403/4000] Validation [4/4] Loss: 0.15768 focal_loss 0.06914 dice_loss 0.08853 +Epoch [403/4000] Validation metric {'Val/mean dice_metric': 0.965650737285614, 'Val/mean miou_metric': 0.9436806440353394, 'Val/mean f1': 0.9687736630439758, 'Val/mean precision': 0.9618371725082397, 'Val/mean recall': 0.9758108854293823, 'Val/mean hd95_metric': 6.664334774017334} +Cheakpoint... +Epoch [403/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9657], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965650737285614, 'Val/mean miou_metric': 0.9436806440353394, 'Val/mean f1': 0.9687736630439758, 'Val/mean precision': 0.9618371725082397, 'Val/mean recall': 0.9758108854293823, 'Val/mean hd95_metric': 6.664334774017334} +Epoch [404/4000] Training [1/16] Loss: 0.01709 +Epoch [404/4000] Training [2/16] Loss: 0.01749 +Epoch [404/4000] Training [3/16] Loss: 0.01734 +Epoch [404/4000] Training [4/16] Loss: 0.01993 +Epoch [404/4000] Training [5/16] Loss: 0.01208 +Epoch [404/4000] Training [6/16] Loss: 0.01898 +Epoch [404/4000] Training [7/16] Loss: 0.02384 +Epoch [404/4000] Training [8/16] Loss: 0.02112 +Epoch [404/4000] Training [9/16] Loss: 0.02347 +Epoch [404/4000] Training [10/16] Loss: 0.01428 +Epoch [404/4000] Training [11/16] Loss: 0.01426 +Epoch [404/4000] Training [12/16] Loss: 0.01841 +Epoch [404/4000] Training [13/16] Loss: 0.01551 +Epoch [404/4000] Training [14/16] Loss: 0.01377 +Epoch [404/4000] Training [15/16] Loss: 0.01534 +Epoch [404/4000] Training [16/16] Loss: 0.01656 +Epoch [404/4000] Training metric {'Train/mean dice_metric': 0.9875018000602722, 'Train/mean miou_metric': 0.9751720428466797, 'Train/mean f1': 0.9840404987335205, 'Train/mean precision': 0.9781742691993713, 'Train/mean recall': 0.9899774789810181, 'Train/mean hd95_metric': 1.6685101985931396} +Epoch [404/4000] Validation [1/4] Loss: 0.39179 focal_loss 0.27713 dice_loss 0.11466 +Epoch [404/4000] Validation [2/4] Loss: 0.44343 focal_loss 0.20551 dice_loss 0.23792 +Epoch [404/4000] Validation [3/4] Loss: 0.14028 focal_loss 0.06917 dice_loss 0.07111 +Epoch [404/4000] Validation [4/4] Loss: 0.34006 focal_loss 0.17469 dice_loss 0.16538 +Epoch [404/4000] Validation metric {'Val/mean dice_metric': 0.9614715576171875, 'Val/mean miou_metric': 0.9375156164169312, 'Val/mean f1': 0.963699460029602, 'Val/mean precision': 0.9634200930595398, 'Val/mean recall': 0.9639790058135986, 'Val/mean hd95_metric': 6.567655086517334} +Cheakpoint... +Epoch [404/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9615], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614715576171875, 'Val/mean miou_metric': 0.9375156164169312, 'Val/mean f1': 0.963699460029602, 'Val/mean precision': 0.9634200930595398, 'Val/mean recall': 0.9639790058135986, 'Val/mean hd95_metric': 6.567655086517334} +Epoch [405/4000] Training [1/16] Loss: 0.01586 +Epoch [405/4000] Training [2/16] Loss: 0.01172 +Epoch [405/4000] Training [3/16] Loss: 0.01885 +Epoch [405/4000] Training [4/16] Loss: 0.02395 +Epoch [405/4000] Training [5/16] Loss: 0.01638 +Epoch [405/4000] Training [6/16] Loss: 0.01767 +Epoch [405/4000] Training [7/16] Loss: 0.01425 +Epoch [405/4000] Training [8/16] Loss: 0.01501 +Epoch [405/4000] Training [9/16] Loss: 0.01713 +Epoch [405/4000] Training [10/16] Loss: 0.08231 +Epoch [405/4000] Training [11/16] Loss: 0.01754 +Epoch [405/4000] Training [12/16] Loss: 0.01267 +Epoch [405/4000] Training [13/16] Loss: 0.01584 +Epoch [405/4000] Training [14/16] Loss: 0.01456 +Epoch [405/4000] Training [15/16] Loss: 0.01732 +Epoch [405/4000] Training [16/16] Loss: 0.01635 +Epoch [405/4000] Training metric {'Train/mean dice_metric': 0.9853391647338867, 'Train/mean miou_metric': 0.972065806388855, 'Train/mean f1': 0.9834669828414917, 'Train/mean precision': 0.9803105592727661, 'Train/mean recall': 0.9866437911987305, 'Train/mean hd95_metric': 2.1836090087890625} +Epoch [405/4000] Validation [1/4] Loss: 0.14094 focal_loss 0.08403 dice_loss 0.05691 +Epoch [405/4000] Validation [2/4] Loss: 0.28299 focal_loss 0.13572 dice_loss 0.14727 +Epoch [405/4000] Validation [3/4] Loss: 0.18700 focal_loss 0.09540 dice_loss 0.09161 +Epoch [405/4000] Validation [4/4] Loss: 0.21486 focal_loss 0.10620 dice_loss 0.10866 +Epoch [405/4000] Validation metric {'Val/mean dice_metric': 0.9637402296066284, 'Val/mean miou_metric': 0.9398304224014282, 'Val/mean f1': 0.965912401676178, 'Val/mean precision': 0.9595958590507507, 'Val/mean recall': 0.9723128080368042, 'Val/mean hd95_metric': 7.203060150146484} +Cheakpoint... +Epoch [405/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637402296066284, 'Val/mean miou_metric': 0.9398304224014282, 'Val/mean f1': 0.965912401676178, 'Val/mean precision': 0.9595958590507507, 'Val/mean recall': 0.9723128080368042, 'Val/mean hd95_metric': 7.203060150146484} +Epoch [406/4000] Training [1/16] Loss: 0.01360 +Epoch [406/4000] Training [2/16] Loss: 0.01710 +Epoch [406/4000] Training [3/16] Loss: 0.01929 +Epoch [406/4000] Training [4/16] Loss: 0.01589 +Epoch [406/4000] Training [5/16] Loss: 0.02186 +Epoch [406/4000] Training [6/16] Loss: 0.02203 +Epoch [406/4000] Training [7/16] Loss: 0.01445 +Epoch [406/4000] Training [8/16] Loss: 0.01935 +Epoch [406/4000] Training [9/16] Loss: 0.01575 +Epoch [406/4000] Training [10/16] Loss: 0.01810 +Epoch [406/4000] Training [11/16] Loss: 0.02347 +Epoch [406/4000] Training [12/16] Loss: 0.01683 +Epoch [406/4000] Training [13/16] Loss: 0.02625 +Epoch [406/4000] Training [14/16] Loss: 0.01790 +Epoch [406/4000] Training [15/16] Loss: 0.01421 +Epoch [406/4000] Training [16/16] Loss: 0.02705 +Epoch [406/4000] Training metric {'Train/mean dice_metric': 0.9844588041305542, 'Train/mean miou_metric': 0.971077561378479, 'Train/mean f1': 0.9821764230728149, 'Train/mean precision': 0.9771891832351685, 'Train/mean recall': 0.9872147440910339, 'Train/mean hd95_metric': 3.025615692138672} +Epoch [406/4000] Validation [1/4] Loss: 0.14995 focal_loss 0.08957 dice_loss 0.06039 +Epoch [406/4000] Validation [2/4] Loss: 0.25898 focal_loss 0.08849 dice_loss 0.17049 +Epoch [406/4000] Validation [3/4] Loss: 0.12282 focal_loss 0.05582 dice_loss 0.06700 +Epoch [406/4000] Validation [4/4] Loss: 0.23004 focal_loss 0.10695 dice_loss 0.12309 +Epoch [406/4000] Validation metric {'Val/mean dice_metric': 0.9608262181282043, 'Val/mean miou_metric': 0.9370096325874329, 'Val/mean f1': 0.9640678763389587, 'Val/mean precision': 0.9594888091087341, 'Val/mean recall': 0.9686907529830933, 'Val/mean hd95_metric': 7.983799457550049} +Cheakpoint... +Epoch [406/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608262181282043, 'Val/mean miou_metric': 0.9370096325874329, 'Val/mean f1': 0.9640678763389587, 'Val/mean precision': 0.9594888091087341, 'Val/mean recall': 0.9686907529830933, 'Val/mean hd95_metric': 7.983799457550049} +Epoch [407/4000] Training [1/16] Loss: 0.02786 +Epoch [407/4000] Training [2/16] Loss: 0.02827 +Epoch [407/4000] Training [3/16] Loss: 0.01623 +Epoch [407/4000] Training [4/16] Loss: 0.01960 +Epoch [407/4000] Training [5/16] Loss: 0.01990 +Epoch [407/4000] Training [6/16] Loss: 0.01640 +Epoch [407/4000] Training [7/16] Loss: 0.01781 +Epoch [407/4000] Training [8/16] Loss: 0.01598 +Epoch [407/4000] Training [9/16] Loss: 0.01547 +Epoch [407/4000] Training [10/16] Loss: 0.01852 +Epoch [407/4000] Training [11/16] Loss: 0.01681 +Epoch [407/4000] Training [12/16] Loss: 0.01603 +Epoch [407/4000] Training [13/16] Loss: 0.01397 +Epoch [407/4000] Training [14/16] Loss: 0.02098 +Epoch [407/4000] Training [15/16] Loss: 0.01594 +Epoch [407/4000] Training [16/16] Loss: 0.01959 +Epoch [407/4000] Training metric {'Train/mean dice_metric': 0.9863993525505066, 'Train/mean miou_metric': 0.9731012582778931, 'Train/mean f1': 0.9841914772987366, 'Train/mean precision': 0.9792580008506775, 'Train/mean recall': 0.9891749620437622, 'Train/mean hd95_metric': 1.9354089498519897} +Epoch [407/4000] Validation [1/4] Loss: 0.15017 focal_loss 0.09068 dice_loss 0.05949 +Epoch [407/4000] Validation [2/4] Loss: 0.29829 focal_loss 0.12387 dice_loss 0.17442 +Epoch [407/4000] Validation [3/4] Loss: 0.13483 focal_loss 0.05778 dice_loss 0.07705 +Epoch [407/4000] Validation [4/4] Loss: 0.25177 focal_loss 0.13335 dice_loss 0.11842 +Epoch [407/4000] Validation metric {'Val/mean dice_metric': 0.9619210958480835, 'Val/mean miou_metric': 0.9376544952392578, 'Val/mean f1': 0.9609805941581726, 'Val/mean precision': 0.9473011493682861, 'Val/mean recall': 0.9750608801841736, 'Val/mean hd95_metric': 8.64918041229248} +Cheakpoint... +Epoch [407/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9619], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9619210958480835, 'Val/mean miou_metric': 0.9376544952392578, 'Val/mean f1': 0.9609805941581726, 'Val/mean precision': 0.9473011493682861, 'Val/mean recall': 0.9750608801841736, 'Val/mean hd95_metric': 8.64918041229248} +Epoch [408/4000] Training [1/16] Loss: 0.02336 +Epoch [408/4000] Training [2/16] Loss: 0.01706 +Epoch [408/4000] Training [3/16] Loss: 0.01711 +Epoch [408/4000] Training [4/16] Loss: 0.01254 +Epoch [408/4000] Training [5/16] Loss: 0.02419 +Epoch [408/4000] Training [6/16] Loss: 0.01625 +Epoch [408/4000] Training [7/16] Loss: 0.01541 +Epoch [408/4000] Training [8/16] Loss: 0.02336 +Epoch [408/4000] Training [9/16] Loss: 0.02080 +Epoch [408/4000] Training [10/16] Loss: 0.02250 +Epoch [408/4000] Training [11/16] Loss: 0.01713 +Epoch [408/4000] Training [12/16] Loss: 0.02747 +Epoch [408/4000] Training [13/16] Loss: 0.01547 +Epoch [408/4000] Training [14/16] Loss: 0.01661 +Epoch [408/4000] Training [15/16] Loss: 0.03291 +Epoch [408/4000] Training [16/16] Loss: 0.01911 +Epoch [408/4000] Training metric {'Train/mean dice_metric': 0.9864648580551147, 'Train/mean miou_metric': 0.9732540845870972, 'Train/mean f1': 0.9837321639060974, 'Train/mean precision': 0.9790703654289246, 'Train/mean recall': 0.9884385466575623, 'Train/mean hd95_metric': 3.041940212249756} +Epoch [408/4000] Validation [1/4] Loss: 0.39216 focal_loss 0.25485 dice_loss 0.13732 +Epoch [408/4000] Validation [2/4] Loss: 0.36872 focal_loss 0.14832 dice_loss 0.22040 +Epoch [408/4000] Validation [3/4] Loss: 0.12200 focal_loss 0.05372 dice_loss 0.06827 +Epoch [408/4000] Validation [4/4] Loss: 0.27210 focal_loss 0.13962 dice_loss 0.13248 +Epoch [408/4000] Validation metric {'Val/mean dice_metric': 0.9611524343490601, 'Val/mean miou_metric': 0.9366116523742676, 'Val/mean f1': 0.9624010324478149, 'Val/mean precision': 0.9629116058349609, 'Val/mean recall': 0.9618909955024719, 'Val/mean hd95_metric': 7.416956901550293} +Cheakpoint... +Epoch [408/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9611524343490601, 'Val/mean miou_metric': 0.9366116523742676, 'Val/mean f1': 0.9624010324478149, 'Val/mean precision': 0.9629116058349609, 'Val/mean recall': 0.9618909955024719, 'Val/mean hd95_metric': 7.416956901550293} +Epoch [409/4000] Training [1/16] Loss: 0.01654 +Epoch [409/4000] Training [2/16] Loss: 0.01621 +Epoch [409/4000] Training [3/16] Loss: 0.01639 +Epoch [409/4000] Training [4/16] Loss: 0.01886 +Epoch [409/4000] Training [5/16] Loss: 0.01921 +Epoch [409/4000] Training [6/16] Loss: 0.01997 +Epoch [409/4000] Training [7/16] Loss: 0.01510 +Epoch [409/4000] Training [8/16] Loss: 0.02137 +Epoch [409/4000] Training [9/16] Loss: 0.01477 +Epoch [409/4000] Training [10/16] Loss: 0.01323 +Epoch [409/4000] Training [11/16] Loss: 0.01572 +Epoch [409/4000] Training [12/16] Loss: 0.01702 +Epoch [409/4000] Training [13/16] Loss: 0.01451 +Epoch [409/4000] Training [14/16] Loss: 0.03173 +Epoch [409/4000] Training [15/16] Loss: 0.01659 +Epoch [409/4000] Training [16/16] Loss: 0.01189 +Epoch [409/4000] Training metric {'Train/mean dice_metric': 0.9877879619598389, 'Train/mean miou_metric': 0.9757280945777893, 'Train/mean f1': 0.9851161241531372, 'Train/mean precision': 0.9808803796768188, 'Train/mean recall': 0.9893885850906372, 'Train/mean hd95_metric': 1.583634376525879} +Epoch [409/4000] Validation [1/4] Loss: 0.24230 focal_loss 0.13702 dice_loss 0.10528 +Epoch [409/4000] Validation [2/4] Loss: 0.35436 focal_loss 0.14715 dice_loss 0.20721 +Epoch [409/4000] Validation [3/4] Loss: 0.10941 focal_loss 0.04821 dice_loss 0.06120 +Epoch [409/4000] Validation [4/4] Loss: 0.20493 focal_loss 0.09533 dice_loss 0.10960 +Epoch [409/4000] Validation metric {'Val/mean dice_metric': 0.964655876159668, 'Val/mean miou_metric': 0.9410349726676941, 'Val/mean f1': 0.9664658904075623, 'Val/mean precision': 0.9653429985046387, 'Val/mean recall': 0.967591404914856, 'Val/mean hd95_metric': 5.775577545166016} +Cheakpoint... +Epoch [409/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964655876159668, 'Val/mean miou_metric': 0.9410349726676941, 'Val/mean f1': 0.9664658904075623, 'Val/mean precision': 0.9653429985046387, 'Val/mean recall': 0.967591404914856, 'Val/mean hd95_metric': 5.775577545166016} +Epoch [410/4000] Training [1/16] Loss: 0.01371 +Epoch [410/4000] Training [2/16] Loss: 0.01404 +Epoch [410/4000] Training [3/16] Loss: 0.01705 +Epoch [410/4000] Training [4/16] Loss: 0.01037 +Epoch [410/4000] Training [5/16] Loss: 0.01705 +Epoch [410/4000] Training [6/16] Loss: 0.01525 +Epoch [410/4000] Training [7/16] Loss: 0.01499 +Epoch [410/4000] Training [8/16] Loss: 0.01399 +Epoch [410/4000] Training [9/16] Loss: 0.02092 +Epoch [410/4000] Training [10/16] Loss: 0.01395 +Epoch [410/4000] Training [11/16] Loss: 0.01438 +Epoch [410/4000] Training [12/16] Loss: 0.01327 +Epoch [410/4000] Training [13/16] Loss: 0.01501 +Epoch [410/4000] Training [14/16] Loss: 0.02697 +Epoch [410/4000] Training [15/16] Loss: 0.03986 +Epoch [410/4000] Training [16/16] Loss: 0.01671 +Epoch [410/4000] Training metric {'Train/mean dice_metric': 0.987656831741333, 'Train/mean miou_metric': 0.9758574962615967, 'Train/mean f1': 0.9844262599945068, 'Train/mean precision': 0.9813581109046936, 'Train/mean recall': 0.9875136613845825, 'Train/mean hd95_metric': 2.1226377487182617} +Epoch [410/4000] Validation [1/4] Loss: 0.29618 focal_loss 0.19694 dice_loss 0.09924 +Epoch [410/4000] Validation [2/4] Loss: 0.55351 focal_loss 0.24041 dice_loss 0.31310 +Epoch [410/4000] Validation [3/4] Loss: 0.09910 focal_loss 0.04398 dice_loss 0.05512 +Epoch [410/4000] Validation [4/4] Loss: 0.39515 focal_loss 0.23060 dice_loss 0.16456 +Epoch [410/4000] Validation metric {'Val/mean dice_metric': 0.9575872421264648, 'Val/mean miou_metric': 0.9346727132797241, 'Val/mean f1': 0.9619064331054688, 'Val/mean precision': 0.9679673314094543, 'Val/mean recall': 0.9559209942817688, 'Val/mean hd95_metric': 7.067352294921875} +Cheakpoint... +Epoch [410/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9575872421264648, 'Val/mean miou_metric': 0.9346727132797241, 'Val/mean f1': 0.9619064331054688, 'Val/mean precision': 0.9679673314094543, 'Val/mean recall': 0.9559209942817688, 'Val/mean hd95_metric': 7.067352294921875} +Epoch [411/4000] Training [1/16] Loss: 0.01794 +Epoch [411/4000] Training [2/16] Loss: 0.01621 +Epoch [411/4000] Training [3/16] Loss: 0.01049 +Epoch [411/4000] Training [4/16] Loss: 0.18399 +Epoch [411/4000] Training [5/16] Loss: 0.01949 +Epoch [411/4000] Training [6/16] Loss: 0.01823 +Epoch [411/4000] Training [7/16] Loss: 0.01639 +Epoch [411/4000] Training [8/16] Loss: 0.01855 +Epoch [411/4000] Training [9/16] Loss: 0.07412 +Epoch [411/4000] Training [10/16] Loss: 0.01449 +Epoch [411/4000] Training [11/16] Loss: 0.01805 +Epoch [411/4000] Training [12/16] Loss: 0.02840 +Epoch [411/4000] Training [13/16] Loss: 0.03019 +Epoch [411/4000] Training [14/16] Loss: 0.02675 +Epoch [411/4000] Training [15/16] Loss: 0.02590 +Epoch [411/4000] Training [16/16] Loss: 0.02185 +Epoch [411/4000] Training metric {'Train/mean dice_metric': 0.9809356331825256, 'Train/mean miou_metric': 0.965817391872406, 'Train/mean f1': 0.9788703322410583, 'Train/mean precision': 0.9721176624298096, 'Train/mean recall': 0.9857174158096313, 'Train/mean hd95_metric': 4.684362888336182} +Epoch [411/4000] Validation [1/4] Loss: 0.22739 focal_loss 0.13735 dice_loss 0.09004 +Epoch [411/4000] Validation [2/4] Loss: 0.57304 focal_loss 0.28564 dice_loss 0.28740 +Epoch [411/4000] Validation [3/4] Loss: 0.10373 focal_loss 0.04631 dice_loss 0.05741 +Epoch [411/4000] Validation [4/4] Loss: 0.27465 focal_loss 0.15031 dice_loss 0.12434 +Epoch [411/4000] Validation metric {'Val/mean dice_metric': 0.9547742605209351, 'Val/mean miou_metric': 0.9279981851577759, 'Val/mean f1': 0.9587291479110718, 'Val/mean precision': 0.9556120038032532, 'Val/mean recall': 0.9618666768074036, 'Val/mean hd95_metric': 10.676252365112305} +Cheakpoint... +Epoch [411/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9548], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9547742605209351, 'Val/mean miou_metric': 0.9279981851577759, 'Val/mean f1': 0.9587291479110718, 'Val/mean precision': 0.9556120038032532, 'Val/mean recall': 0.9618666768074036, 'Val/mean hd95_metric': 10.676252365112305} +Epoch [412/4000] Training [1/16] Loss: 0.02072 +Epoch [412/4000] Training [2/16] Loss: 0.01527 +Epoch [412/4000] Training [3/16] Loss: 0.02500 +Epoch [412/4000] Training [4/16] Loss: 0.01434 +Epoch [412/4000] Training [5/16] Loss: 0.01753 +Epoch [412/4000] Training [6/16] Loss: 0.02058 +Epoch [412/4000] Training [7/16] Loss: 0.02064 +Epoch [412/4000] Training [8/16] Loss: 0.02281 +Epoch [412/4000] Training [9/16] Loss: 0.02490 +Epoch [412/4000] Training [10/16] Loss: 0.01645 +Epoch [412/4000] Training [11/16] Loss: 0.10832 +Epoch [412/4000] Training [12/16] Loss: 0.03261 +Epoch [412/4000] Training [13/16] Loss: 0.01564 +Epoch [412/4000] Training [14/16] Loss: 0.02050 +Epoch [412/4000] Training [15/16] Loss: 0.01552 +Epoch [412/4000] Training [16/16] Loss: 0.02101 +Epoch [412/4000] Training metric {'Train/mean dice_metric': 0.9835973978042603, 'Train/mean miou_metric': 0.9687884449958801, 'Train/mean f1': 0.9814797639846802, 'Train/mean precision': 0.9767746329307556, 'Train/mean recall': 0.9862304925918579, 'Train/mean hd95_metric': 3.314821243286133} +Epoch [412/4000] Validation [1/4] Loss: 0.12116 focal_loss 0.06417 dice_loss 0.05699 +Epoch [412/4000] Validation [2/4] Loss: 0.51026 focal_loss 0.22670 dice_loss 0.28356 +Epoch [412/4000] Validation [3/4] Loss: 0.11817 focal_loss 0.05637 dice_loss 0.06180 +Epoch [412/4000] Validation [4/4] Loss: 0.21440 focal_loss 0.10189 dice_loss 0.11251 +Epoch [412/4000] Validation metric {'Val/mean dice_metric': 0.9575711488723755, 'Val/mean miou_metric': 0.9325512051582336, 'Val/mean f1': 0.9599603414535522, 'Val/mean precision': 0.9541836380958557, 'Val/mean recall': 0.9658075571060181, 'Val/mean hd95_metric': 8.510823249816895} +Cheakpoint... +Epoch [412/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9575711488723755, 'Val/mean miou_metric': 0.9325512051582336, 'Val/mean f1': 0.9599603414535522, 'Val/mean precision': 0.9541836380958557, 'Val/mean recall': 0.9658075571060181, 'Val/mean hd95_metric': 8.510823249816895} +Epoch [413/4000] Training [1/16] Loss: 0.01382 +Epoch [413/4000] Training [2/16] Loss: 0.02170 +Epoch [413/4000] Training [3/16] Loss: 0.02024 +Epoch [413/4000] Training [4/16] Loss: 0.01483 +Epoch [413/4000] Training [5/16] Loss: 0.03623 +Epoch [413/4000] Training [6/16] Loss: 0.03737 +Epoch [413/4000] Training [7/16] Loss: 0.01656 +Epoch [413/4000] Training [8/16] Loss: 0.02110 +Epoch [413/4000] Training [9/16] Loss: 0.01505 +Epoch [413/4000] Training [10/16] Loss: 0.01770 +Epoch [413/4000] Training [11/16] Loss: 0.02180 +Epoch [413/4000] Training [12/16] Loss: 0.01762 +Epoch [413/4000] Training [13/16] Loss: 0.01526 +Epoch [413/4000] Training [14/16] Loss: 0.01887 +Epoch [413/4000] Training [15/16] Loss: 0.02934 +Epoch [413/4000] Training [16/16] Loss: 0.01625 +Epoch [413/4000] Training metric {'Train/mean dice_metric': 0.9866085052490234, 'Train/mean miou_metric': 0.973486065864563, 'Train/mean f1': 0.9828746914863586, 'Train/mean precision': 0.9783158898353577, 'Train/mean recall': 0.9874763488769531, 'Train/mean hd95_metric': 2.3016319274902344} +Epoch [413/4000] Validation [1/4] Loss: 0.36039 focal_loss 0.24239 dice_loss 0.11800 +Epoch [413/4000] Validation [2/4] Loss: 0.36389 focal_loss 0.12788 dice_loss 0.23601 +Epoch [413/4000] Validation [3/4] Loss: 0.15057 focal_loss 0.06236 dice_loss 0.08822 +Epoch [413/4000] Validation [4/4] Loss: 0.23790 focal_loss 0.11402 dice_loss 0.12388 +Epoch [413/4000] Validation metric {'Val/mean dice_metric': 0.9610279202461243, 'Val/mean miou_metric': 0.9369789958000183, 'Val/mean f1': 0.9632891416549683, 'Val/mean precision': 0.9592472910881042, 'Val/mean recall': 0.9673652052879333, 'Val/mean hd95_metric': 7.525601387023926} +Cheakpoint... +Epoch [413/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9610], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610279202461243, 'Val/mean miou_metric': 0.9369789958000183, 'Val/mean f1': 0.9632891416549683, 'Val/mean precision': 0.9592472910881042, 'Val/mean recall': 0.9673652052879333, 'Val/mean hd95_metric': 7.525601387023926} +Epoch [414/4000] Training [1/16] Loss: 0.01479 +Epoch [414/4000] Training [2/16] Loss: 0.01643 +Epoch [414/4000] Training [3/16] Loss: 0.01492 +Epoch [414/4000] Training [4/16] Loss: 0.01477 +Epoch [414/4000] Training [5/16] Loss: 0.01669 +Epoch [414/4000] Training [6/16] Loss: 0.01331 +Epoch [414/4000] Training [7/16] Loss: 0.03275 +Epoch [414/4000] Training [8/16] Loss: 0.01753 +Epoch [414/4000] Training [9/16] Loss: 0.01937 +Epoch [414/4000] Training [10/16] Loss: 0.01259 +Epoch [414/4000] Training [11/16] Loss: 0.02001 +Epoch [414/4000] Training [12/16] Loss: 0.02575 +Epoch [414/4000] Training [13/16] Loss: 0.01714 +Epoch [414/4000] Training [14/16] Loss: 0.01359 +Epoch [414/4000] Training [15/16] Loss: 0.01930 +Epoch [414/4000] Training [16/16] Loss: 0.01255 +Epoch [414/4000] Training metric {'Train/mean dice_metric': 0.988262414932251, 'Train/mean miou_metric': 0.9766604900360107, 'Train/mean f1': 0.9850977063179016, 'Train/mean precision': 0.9804984927177429, 'Train/mean recall': 0.989740252494812, 'Train/mean hd95_metric': 1.6522867679595947} +Epoch [414/4000] Validation [1/4] Loss: 0.14720 focal_loss 0.08275 dice_loss 0.06445 +Epoch [414/4000] Validation [2/4] Loss: 0.25194 focal_loss 0.09591 dice_loss 0.15603 +Epoch [414/4000] Validation [3/4] Loss: 0.24039 focal_loss 0.13310 dice_loss 0.10729 +Epoch [414/4000] Validation [4/4] Loss: 0.23031 focal_loss 0.12481 dice_loss 0.10550 +Epoch [414/4000] Validation metric {'Val/mean dice_metric': 0.9636338949203491, 'Val/mean miou_metric': 0.9404823184013367, 'Val/mean f1': 0.9669515490531921, 'Val/mean precision': 0.963550329208374, 'Val/mean recall': 0.9703768491744995, 'Val/mean hd95_metric': 7.066084384918213} +Cheakpoint... +Epoch [414/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636338949203491, 'Val/mean miou_metric': 0.9404823184013367, 'Val/mean f1': 0.9669515490531921, 'Val/mean precision': 0.963550329208374, 'Val/mean recall': 0.9703768491744995, 'Val/mean hd95_metric': 7.066084384918213} +Epoch [415/4000] Training [1/16] Loss: 0.01661 +Epoch [415/4000] Training [2/16] Loss: 0.01265 +Epoch [415/4000] Training [3/16] Loss: 0.01380 +Epoch [415/4000] Training [4/16] Loss: 0.01627 +Epoch [415/4000] Training [5/16] Loss: 0.01291 +Epoch [415/4000] Training [6/16] Loss: 0.01482 +Epoch [415/4000] Training [7/16] Loss: 0.01297 +Epoch [415/4000] Training [8/16] Loss: 0.01394 +Epoch [415/4000] Training [9/16] Loss: 0.01276 +Epoch [415/4000] Training [10/16] Loss: 0.01469 +Epoch [415/4000] Training [11/16] Loss: 0.01350 +Epoch [415/4000] Training [12/16] Loss: 0.01575 +Epoch [415/4000] Training [13/16] Loss: 0.01633 +Epoch [415/4000] Training [14/16] Loss: 0.01547 +Epoch [415/4000] Training [15/16] Loss: 0.01656 +Epoch [415/4000] Training [16/16] Loss: 0.01403 +Epoch [415/4000] Training metric {'Train/mean dice_metric': 0.989962100982666, 'Train/mean miou_metric': 0.9798973798751831, 'Train/mean f1': 0.9864218831062317, 'Train/mean precision': 0.9818607568740845, 'Train/mean recall': 0.9910255074501038, 'Train/mean hd95_metric': 1.28622305393219} +Epoch [415/4000] Validation [1/4] Loss: 0.22270 focal_loss 0.13551 dice_loss 0.08719 +Epoch [415/4000] Validation [2/4] Loss: 0.41659 focal_loss 0.18348 dice_loss 0.23312 +Epoch [415/4000] Validation [3/4] Loss: 0.14304 focal_loss 0.07290 dice_loss 0.07014 +Epoch [415/4000] Validation [4/4] Loss: 0.21721 focal_loss 0.11828 dice_loss 0.09893 +Epoch [415/4000] Validation metric {'Val/mean dice_metric': 0.9651601910591125, 'Val/mean miou_metric': 0.9438030123710632, 'Val/mean f1': 0.9660804867744446, 'Val/mean precision': 0.9653471112251282, 'Val/mean recall': 0.9668149948120117, 'Val/mean hd95_metric': 5.725564002990723} +Cheakpoint... +Epoch [415/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651601910591125, 'Val/mean miou_metric': 0.9438030123710632, 'Val/mean f1': 0.9660804867744446, 'Val/mean precision': 0.9653471112251282, 'Val/mean recall': 0.9668149948120117, 'Val/mean hd95_metric': 5.725564002990723} +Epoch [416/4000] Training [1/16] Loss: 0.01772 +Epoch [416/4000] Training [2/16] Loss: 0.02110 +Epoch [416/4000] Training [3/16] Loss: 0.01671 +Epoch [416/4000] Training [4/16] Loss: 0.01473 +Epoch [416/4000] Training [5/16] Loss: 0.01034 +Epoch [416/4000] Training [6/16] Loss: 0.01280 +Epoch [416/4000] Training [7/16] Loss: 0.01372 +Epoch [416/4000] Training [8/16] Loss: 0.01399 +Epoch [416/4000] Training [9/16] Loss: 0.02185 +Epoch [416/4000] Training [10/16] Loss: 0.01061 +Epoch [416/4000] Training [11/16] Loss: 0.01281 +Epoch [416/4000] Training [12/16] Loss: 0.01433 +Epoch [416/4000] Training [13/16] Loss: 0.01586 +Epoch [416/4000] Training [14/16] Loss: 0.01664 +Epoch [416/4000] Training [15/16] Loss: 0.01760 +Epoch [416/4000] Training [16/16] Loss: 0.01279 +Epoch [416/4000] Training metric {'Train/mean dice_metric': 0.9894630908966064, 'Train/mean miou_metric': 0.9789599776268005, 'Train/mean f1': 0.9861549735069275, 'Train/mean precision': 0.981576681137085, 'Train/mean recall': 0.9907762408256531, 'Train/mean hd95_metric': 1.5126153230667114} +Epoch [416/4000] Validation [1/4] Loss: 0.45808 focal_loss 0.33527 dice_loss 0.12281 +Epoch [416/4000] Validation [2/4] Loss: 0.48158 focal_loss 0.22336 dice_loss 0.25822 +Epoch [416/4000] Validation [3/4] Loss: 0.11849 focal_loss 0.04460 dice_loss 0.07389 +Epoch [416/4000] Validation [4/4] Loss: 0.30724 focal_loss 0.18871 dice_loss 0.11853 +Epoch [416/4000] Validation metric {'Val/mean dice_metric': 0.9615241289138794, 'Val/mean miou_metric': 0.9395266771316528, 'Val/mean f1': 0.9639891982078552, 'Val/mean precision': 0.9675540328025818, 'Val/mean recall': 0.9604504704475403, 'Val/mean hd95_metric': 6.917765140533447} +Cheakpoint... +Epoch [416/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9615], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9615241289138794, 'Val/mean miou_metric': 0.9395266771316528, 'Val/mean f1': 0.9639891982078552, 'Val/mean precision': 0.9675540328025818, 'Val/mean recall': 0.9604504704475403, 'Val/mean hd95_metric': 6.917765140533447} +Epoch [417/4000] Training [1/16] Loss: 0.01457 +Epoch [417/4000] Training [2/16] Loss: 0.01299 +Epoch [417/4000] Training [3/16] Loss: 0.01257 +Epoch [417/4000] Training [4/16] Loss: 0.01516 +Epoch [417/4000] Training [5/16] Loss: 0.01378 +Epoch [417/4000] Training [6/16] Loss: 0.01707 +Epoch [417/4000] Training [7/16] Loss: 0.01441 +Epoch [417/4000] Training [8/16] Loss: 0.01350 +Epoch [417/4000] Training [9/16] Loss: 0.01483 +Epoch [417/4000] Training [10/16] Loss: 0.01484 +Epoch [417/4000] Training [11/16] Loss: 0.01246 +Epoch [417/4000] Training [12/16] Loss: 0.01401 +Epoch [417/4000] Training [13/16] Loss: 0.01812 +Epoch [417/4000] Training [14/16] Loss: 0.01229 +Epoch [417/4000] Training [15/16] Loss: 0.01293 +Epoch [417/4000] Training [16/16] Loss: 0.01528 +Epoch [417/4000] Training metric {'Train/mean dice_metric': 0.9899040460586548, 'Train/mean miou_metric': 0.9797987341880798, 'Train/mean f1': 0.9867719411849976, 'Train/mean precision': 0.982282280921936, 'Train/mean recall': 0.9913028478622437, 'Train/mean hd95_metric': 1.5662480592727661} +Epoch [417/4000] Validation [1/4] Loss: 0.14191 focal_loss 0.08561 dice_loss 0.05629 +Epoch [417/4000] Validation [2/4] Loss: 0.30303 focal_loss 0.13017 dice_loss 0.17286 +Epoch [417/4000] Validation [3/4] Loss: 0.15805 focal_loss 0.07347 dice_loss 0.08458 +Epoch [417/4000] Validation [4/4] Loss: 0.39145 focal_loss 0.22047 dice_loss 0.17098 +Epoch [417/4000] Validation metric {'Val/mean dice_metric': 0.9677189588546753, 'Val/mean miou_metric': 0.9460211992263794, 'Val/mean f1': 0.9697228074073792, 'Val/mean precision': 0.9630156755447388, 'Val/mean recall': 0.9765241146087646, 'Val/mean hd95_metric': 6.5812578201293945} +Cheakpoint... +Epoch [417/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677189588546753, 'Val/mean miou_metric': 0.9460211992263794, 'Val/mean f1': 0.9697228074073792, 'Val/mean precision': 0.9630156755447388, 'Val/mean recall': 0.9765241146087646, 'Val/mean hd95_metric': 6.5812578201293945} +Epoch [418/4000] Training [1/16] Loss: 0.01535 +Epoch [418/4000] Training [2/16] Loss: 0.01389 +Epoch [418/4000] Training [3/16] Loss: 0.01031 +Epoch [418/4000] Training [4/16] Loss: 0.01455 +Epoch [418/4000] Training [5/16] Loss: 0.01631 +Epoch [418/4000] Training [6/16] Loss: 0.01432 +Epoch [418/4000] Training [7/16] Loss: 0.01321 +Epoch [418/4000] Training [8/16] Loss: 0.04917 +Epoch [418/4000] Training [9/16] Loss: 0.01305 +Epoch [418/4000] Training [10/16] Loss: 0.01767 +Epoch [418/4000] Training [11/16] Loss: 0.01214 +Epoch [418/4000] Training [12/16] Loss: 0.01408 +Epoch [418/4000] Training [13/16] Loss: 0.01735 +Epoch [418/4000] Training [14/16] Loss: 0.01376 +Epoch [418/4000] Training [15/16] Loss: 0.01816 +Epoch [418/4000] Training [16/16] Loss: 0.01271 +Epoch [418/4000] Training metric {'Train/mean dice_metric': 0.9881096482276917, 'Train/mean miou_metric': 0.9767425656318665, 'Train/mean f1': 0.9856792688369751, 'Train/mean precision': 0.9812588095664978, 'Train/mean recall': 0.9901397228240967, 'Train/mean hd95_metric': 1.971771001815796} +Epoch [418/4000] Validation [1/4] Loss: 0.17088 focal_loss 0.10074 dice_loss 0.07014 +Epoch [418/4000] Validation [2/4] Loss: 0.18261 focal_loss 0.07708 dice_loss 0.10553 +Epoch [418/4000] Validation [3/4] Loss: 0.13109 focal_loss 0.07004 dice_loss 0.06106 +Epoch [418/4000] Validation [4/4] Loss: 0.26097 focal_loss 0.13855 dice_loss 0.12242 +Epoch [418/4000] Validation metric {'Val/mean dice_metric': 0.9650298953056335, 'Val/mean miou_metric': 0.9423791766166687, 'Val/mean f1': 0.9687050580978394, 'Val/mean precision': 0.9662140011787415, 'Val/mean recall': 0.9712091088294983, 'Val/mean hd95_metric': 6.557005882263184} +Cheakpoint... +Epoch [418/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650298953056335, 'Val/mean miou_metric': 0.9423791766166687, 'Val/mean f1': 0.9687050580978394, 'Val/mean precision': 0.9662140011787415, 'Val/mean recall': 0.9712091088294983, 'Val/mean hd95_metric': 6.557005882263184} +Epoch [419/4000] Training [1/16] Loss: 0.01576 +Epoch [419/4000] Training [2/16] Loss: 0.01552 +Epoch [419/4000] Training [3/16] Loss: 0.01737 +Epoch [419/4000] Training [4/16] Loss: 0.01286 +Epoch [419/4000] Training [5/16] Loss: 0.01524 +Epoch [419/4000] Training [6/16] Loss: 0.03931 +Epoch [419/4000] Training [7/16] Loss: 0.01906 +Epoch [419/4000] Training [8/16] Loss: 0.01536 +Epoch [419/4000] Training [9/16] Loss: 0.01463 +Epoch [419/4000] Training [10/16] Loss: 0.01431 +Epoch [419/4000] Training [11/16] Loss: 0.02660 +Epoch [419/4000] Training [12/16] Loss: 0.01462 +Epoch [419/4000] Training [13/16] Loss: 0.01669 +Epoch [419/4000] Training [14/16] Loss: 0.01368 +Epoch [419/4000] Training [15/16] Loss: 0.01521 +Epoch [419/4000] Training [16/16] Loss: 0.01546 +Epoch [419/4000] Training metric {'Train/mean dice_metric': 0.9883390665054321, 'Train/mean miou_metric': 0.976837158203125, 'Train/mean f1': 0.9859903454780579, 'Train/mean precision': 0.9816429615020752, 'Train/mean recall': 0.990376353263855, 'Train/mean hd95_metric': 1.994568109512329} +Epoch [419/4000] Validation [1/4] Loss: 0.22960 focal_loss 0.13667 dice_loss 0.09293 +Epoch [419/4000] Validation [2/4] Loss: 0.32092 focal_loss 0.12949 dice_loss 0.19143 +Epoch [419/4000] Validation [3/4] Loss: 0.11282 focal_loss 0.05695 dice_loss 0.05586 +Epoch [419/4000] Validation [4/4] Loss: 0.14652 focal_loss 0.06562 dice_loss 0.08089 +Epoch [419/4000] Validation metric {'Val/mean dice_metric': 0.9637895822525024, 'Val/mean miou_metric': 0.9407541155815125, 'Val/mean f1': 0.9668630361557007, 'Val/mean precision': 0.966213047504425, 'Val/mean recall': 0.9675137996673584, 'Val/mean hd95_metric': 6.522867679595947} +Cheakpoint... +Epoch [419/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9638], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637895822525024, 'Val/mean miou_metric': 0.9407541155815125, 'Val/mean f1': 0.9668630361557007, 'Val/mean precision': 0.966213047504425, 'Val/mean recall': 0.9675137996673584, 'Val/mean hd95_metric': 6.522867679595947} +Epoch [420/4000] Training [1/16] Loss: 0.01717 +Epoch [420/4000] Training [2/16] Loss: 0.01238 +Epoch [420/4000] Training [3/16] Loss: 0.01283 +Epoch [420/4000] Training [4/16] Loss: 0.01494 +Epoch [420/4000] Training [5/16] Loss: 0.01338 +Epoch [420/4000] Training [6/16] Loss: 0.01226 +Epoch [420/4000] Training [7/16] Loss: 0.01360 +Epoch [420/4000] Training [8/16] Loss: 0.04398 +Epoch [420/4000] Training [9/16] Loss: 0.02158 +Epoch [420/4000] Training [10/16] Loss: 0.01577 +Epoch [420/4000] Training [11/16] Loss: 0.01833 +Epoch [420/4000] Training [12/16] Loss: 0.01670 +Epoch [420/4000] Training [13/16] Loss: 0.01374 +Epoch [420/4000] Training [14/16] Loss: 0.01520 +Epoch [420/4000] Training [15/16] Loss: 0.01875 +Epoch [420/4000] Training [16/16] Loss: 0.01473 +Epoch [420/4000] Training metric {'Train/mean dice_metric': 0.9878270626068115, 'Train/mean miou_metric': 0.975914716720581, 'Train/mean f1': 0.9846059679985046, 'Train/mean precision': 0.979161262512207, 'Train/mean recall': 0.9901115298271179, 'Train/mean hd95_metric': 1.7992291450500488} +Epoch [420/4000] Validation [1/4] Loss: 0.21408 focal_loss 0.12124 dice_loss 0.09285 +Epoch [420/4000] Validation [2/4] Loss: 0.32861 focal_loss 0.16079 dice_loss 0.16782 +Epoch [420/4000] Validation [3/4] Loss: 0.11878 focal_loss 0.06037 dice_loss 0.05841 +Epoch [420/4000] Validation [4/4] Loss: 0.18808 focal_loss 0.10972 dice_loss 0.07836 +Epoch [420/4000] Validation metric {'Val/mean dice_metric': 0.9648761749267578, 'Val/mean miou_metric': 0.9412651062011719, 'Val/mean f1': 0.9670116901397705, 'Val/mean precision': 0.9636030793190002, 'Val/mean recall': 0.97044438123703, 'Val/mean hd95_metric': 6.7482757568359375} +Cheakpoint... +Epoch [420/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648761749267578, 'Val/mean miou_metric': 0.9412651062011719, 'Val/mean f1': 0.9670116901397705, 'Val/mean precision': 0.9636030793190002, 'Val/mean recall': 0.97044438123703, 'Val/mean hd95_metric': 6.7482757568359375} +Epoch [421/4000] Training [1/16] Loss: 0.01324 +Epoch [421/4000] Training [2/16] Loss: 0.01592 +Epoch [421/4000] Training [3/16] Loss: 0.01743 +Epoch [421/4000] Training [4/16] Loss: 0.06930 +Epoch [421/4000] Training [5/16] Loss: 0.01811 +Epoch [421/4000] Training [6/16] Loss: 0.01448 +Epoch [421/4000] Training [7/16] Loss: 0.01717 +Epoch [421/4000] Training [8/16] Loss: 0.01993 +Epoch [421/4000] Training [9/16] Loss: 0.01812 +Epoch [421/4000] Training [10/16] Loss: 0.01596 +Epoch [421/4000] Training [11/16] Loss: 0.01902 +Epoch [421/4000] Training [12/16] Loss: 0.01392 +Epoch [421/4000] Training [13/16] Loss: 0.01890 +Epoch [421/4000] Training [14/16] Loss: 0.01295 +Epoch [421/4000] Training [15/16] Loss: 0.02039 +Epoch [421/4000] Training [16/16] Loss: 0.01116 +Epoch [421/4000] Training metric {'Train/mean dice_metric': 0.9873236417770386, 'Train/mean miou_metric': 0.9751458168029785, 'Train/mean f1': 0.9850548505783081, 'Train/mean precision': 0.9804040193557739, 'Train/mean recall': 0.9897499680519104, 'Train/mean hd95_metric': 2.190969705581665} +Epoch [421/4000] Validation [1/4] Loss: 0.11983 focal_loss 0.06012 dice_loss 0.05971 +Epoch [421/4000] Validation [2/4] Loss: 0.29687 focal_loss 0.11261 dice_loss 0.18426 +Epoch [421/4000] Validation [3/4] Loss: 0.13194 focal_loss 0.05797 dice_loss 0.07397 +Epoch [421/4000] Validation [4/4] Loss: 0.15470 focal_loss 0.06283 dice_loss 0.09187 +Epoch [421/4000] Validation metric {'Val/mean dice_metric': 0.9612873792648315, 'Val/mean miou_metric': 0.9382365942001343, 'Val/mean f1': 0.9668710231781006, 'Val/mean precision': 0.9616380333900452, 'Val/mean recall': 0.9721612334251404, 'Val/mean hd95_metric': 7.595699310302734} +Cheakpoint... +Epoch [421/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612873792648315, 'Val/mean miou_metric': 0.9382365942001343, 'Val/mean f1': 0.9668710231781006, 'Val/mean precision': 0.9616380333900452, 'Val/mean recall': 0.9721612334251404, 'Val/mean hd95_metric': 7.595699310302734} +Epoch [422/4000] Training [1/16] Loss: 0.01532 +Epoch [422/4000] Training [2/16] Loss: 0.01410 +Epoch [422/4000] Training [3/16] Loss: 0.01290 +Epoch [422/4000] Training [4/16] Loss: 0.01661 +Epoch [422/4000] Training [5/16] Loss: 0.01554 +Epoch [422/4000] Training [6/16] Loss: 0.01711 +Epoch [422/4000] Training [7/16] Loss: 0.02050 +Epoch [422/4000] Training [8/16] Loss: 0.01649 +Epoch [422/4000] Training [9/16] Loss: 0.01692 +Epoch [422/4000] Training [10/16] Loss: 0.01694 +Epoch [422/4000] Training [11/16] Loss: 0.01506 +Epoch [422/4000] Training [12/16] Loss: 0.02109 +Epoch [422/4000] Training [13/16] Loss: 0.01230 +Epoch [422/4000] Training [14/16] Loss: 0.02355 +Epoch [422/4000] Training [15/16] Loss: 0.01656 +Epoch [422/4000] Training [16/16] Loss: 0.01467 +Epoch [422/4000] Training metric {'Train/mean dice_metric': 0.9875953197479248, 'Train/mean miou_metric': 0.9755569100379944, 'Train/mean f1': 0.9836398363113403, 'Train/mean precision': 0.9787378311157227, 'Train/mean recall': 0.9885911345481873, 'Train/mean hd95_metric': 2.309558629989624} +Epoch [422/4000] Validation [1/4] Loss: 0.22930 focal_loss 0.13518 dice_loss 0.09412 +Epoch [422/4000] Validation [2/4] Loss: 0.20163 focal_loss 0.07474 dice_loss 0.12690 +Epoch [422/4000] Validation [3/4] Loss: 0.14054 focal_loss 0.06925 dice_loss 0.07129 +Epoch [422/4000] Validation [4/4] Loss: 0.19381 focal_loss 0.08267 dice_loss 0.11114 +Epoch [422/4000] Validation metric {'Val/mean dice_metric': 0.9642386436462402, 'Val/mean miou_metric': 0.9410362243652344, 'Val/mean f1': 0.965252161026001, 'Val/mean precision': 0.9662795662879944, 'Val/mean recall': 0.9642269015312195, 'Val/mean hd95_metric': 6.843195915222168} +Cheakpoint... +Epoch [422/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9642], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9642386436462402, 'Val/mean miou_metric': 0.9410362243652344, 'Val/mean f1': 0.965252161026001, 'Val/mean precision': 0.9662795662879944, 'Val/mean recall': 0.9642269015312195, 'Val/mean hd95_metric': 6.843195915222168} +Epoch [423/4000] Training [1/16] Loss: 0.02661 +Epoch [423/4000] Training [2/16] Loss: 0.02560 +Epoch [423/4000] Training [3/16] Loss: 0.01465 +Epoch [423/4000] Training [4/16] Loss: 0.01497 +Epoch [423/4000] Training [5/16] Loss: 0.02118 +Epoch [423/4000] Training [6/16] Loss: 0.01484 +Epoch [423/4000] Training [7/16] Loss: 0.01618 +Epoch [423/4000] Training [8/16] Loss: 0.02088 +Epoch [423/4000] Training [9/16] Loss: 0.01678 +Epoch [423/4000] Training [10/16] Loss: 0.01431 +Epoch [423/4000] Training [11/16] Loss: 0.01729 +Epoch [423/4000] Training [12/16] Loss: 0.02234 +Epoch [423/4000] Training [13/16] Loss: 0.01736 +Epoch [423/4000] Training [14/16] Loss: 0.02123 +Epoch [423/4000] Training [15/16] Loss: 0.02045 +Epoch [423/4000] Training [16/16] Loss: 0.01350 +Epoch [423/4000] Training metric {'Train/mean dice_metric': 0.9874246120452881, 'Train/mean miou_metric': 0.9750147461891174, 'Train/mean f1': 0.9840410947799683, 'Train/mean precision': 0.9797375202178955, 'Train/mean recall': 0.9883826375007629, 'Train/mean hd95_metric': 2.658163547515869} +Epoch [423/4000] Validation [1/4] Loss: 0.58078 focal_loss 0.38932 dice_loss 0.19146 +Epoch [423/4000] Validation [2/4] Loss: 0.35742 focal_loss 0.14261 dice_loss 0.21482 +Epoch [423/4000] Validation [3/4] Loss: 0.15885 focal_loss 0.07970 dice_loss 0.07915 +Epoch [423/4000] Validation [4/4] Loss: 0.29409 focal_loss 0.17541 dice_loss 0.11868 +Epoch [423/4000] Validation metric {'Val/mean dice_metric': 0.9598973393440247, 'Val/mean miou_metric': 0.9362854957580566, 'Val/mean f1': 0.9632089734077454, 'Val/mean precision': 0.9651544094085693, 'Val/mean recall': 0.9612712860107422, 'Val/mean hd95_metric': 6.567070007324219} +Cheakpoint... +Epoch [423/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9598973393440247, 'Val/mean miou_metric': 0.9362854957580566, 'Val/mean f1': 0.9632089734077454, 'Val/mean precision': 0.9651544094085693, 'Val/mean recall': 0.9612712860107422, 'Val/mean hd95_metric': 6.567070007324219} +Epoch [424/4000] Training [1/16] Loss: 0.01336 +Epoch [424/4000] Training [2/16] Loss: 0.01504 +Epoch [424/4000] Training [3/16] Loss: 0.01584 +Epoch [424/4000] Training [4/16] Loss: 0.02205 +Epoch [424/4000] Training [5/16] Loss: 0.01371 +Epoch [424/4000] Training [6/16] Loss: 0.02410 +Epoch [424/4000] Training [7/16] Loss: 0.01383 +Epoch [424/4000] Training [8/16] Loss: 0.01595 +Epoch [424/4000] Training [9/16] Loss: 0.02004 +Epoch [424/4000] Training [10/16] Loss: 0.01461 +Epoch [424/4000] Training [11/16] Loss: 0.01250 +Epoch [424/4000] Training [12/16] Loss: 0.01849 +Epoch [424/4000] Training [13/16] Loss: 0.01596 +Epoch [424/4000] Training [14/16] Loss: 0.02013 +Epoch [424/4000] Training [15/16] Loss: 0.01247 +Epoch [424/4000] Training [16/16] Loss: 0.02676 +Epoch [424/4000] Training metric {'Train/mean dice_metric': 0.9887316226959229, 'Train/mean miou_metric': 0.9775491952896118, 'Train/mean f1': 0.9851882457733154, 'Train/mean precision': 0.9806267619132996, 'Train/mean recall': 0.9897924065589905, 'Train/mean hd95_metric': 1.572153091430664} +Epoch [424/4000] Validation [1/4] Loss: 0.31768 focal_loss 0.19935 dice_loss 0.11833 +Epoch [424/4000] Validation [2/4] Loss: 0.19412 focal_loss 0.07706 dice_loss 0.11707 +Epoch [424/4000] Validation [3/4] Loss: 0.12456 focal_loss 0.06119 dice_loss 0.06337 +Epoch [424/4000] Validation [4/4] Loss: 0.22239 focal_loss 0.11889 dice_loss 0.10350 +Epoch [424/4000] Validation metric {'Val/mean dice_metric': 0.9645795822143555, 'Val/mean miou_metric': 0.9417751431465149, 'Val/mean f1': 0.9652836322784424, 'Val/mean precision': 0.9652345776557922, 'Val/mean recall': 0.9653327465057373, 'Val/mean hd95_metric': 5.747588157653809} +Cheakpoint... +Epoch [424/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9646], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645795822143555, 'Val/mean miou_metric': 0.9417751431465149, 'Val/mean f1': 0.9652836322784424, 'Val/mean precision': 0.9652345776557922, 'Val/mean recall': 0.9653327465057373, 'Val/mean hd95_metric': 5.747588157653809} +Epoch [425/4000] Training [1/16] Loss: 0.01448 +Epoch [425/4000] Training [2/16] Loss: 0.01026 +Epoch [425/4000] Training [3/16] Loss: 0.01079 +Epoch [425/4000] Training [4/16] Loss: 0.01593 +Epoch [425/4000] Training [5/16] Loss: 0.01471 +Epoch [425/4000] Training [6/16] Loss: 0.01744 +Epoch [425/4000] Training [7/16] Loss: 0.01418 +Epoch [425/4000] Training [8/16] Loss: 0.01478 +Epoch [425/4000] Training [9/16] Loss: 0.01794 +Epoch [425/4000] Training [10/16] Loss: 0.01819 +Epoch [425/4000] Training [11/16] Loss: 0.01667 +Epoch [425/4000] Training [12/16] Loss: 0.01238 +Epoch [425/4000] Training [13/16] Loss: 0.02120 +Epoch [425/4000] Training [14/16] Loss: 0.01208 +Epoch [425/4000] Training [15/16] Loss: 0.01392 +Epoch [425/4000] Training [16/16] Loss: 0.01567 +Epoch [425/4000] Training metric {'Train/mean dice_metric': 0.9893304705619812, 'Train/mean miou_metric': 0.9786983728408813, 'Train/mean f1': 0.986505389213562, 'Train/mean precision': 0.9819859266281128, 'Train/mean recall': 0.991066575050354, 'Train/mean hd95_metric': 1.3838095664978027} +Epoch [425/4000] Validation [1/4] Loss: 0.21319 focal_loss 0.12262 dice_loss 0.09058 +Epoch [425/4000] Validation [2/4] Loss: 0.27336 focal_loss 0.12453 dice_loss 0.14884 +Epoch [425/4000] Validation [3/4] Loss: 0.10363 focal_loss 0.04795 dice_loss 0.05568 +Epoch [425/4000] Validation [4/4] Loss: 0.21769 focal_loss 0.11707 dice_loss 0.10062 +Epoch [425/4000] Validation metric {'Val/mean dice_metric': 0.9658744931221008, 'Val/mean miou_metric': 0.9442710876464844, 'Val/mean f1': 0.9688634276390076, 'Val/mean precision': 0.9644765257835388, 'Val/mean recall': 0.9732906222343445, 'Val/mean hd95_metric': 6.10575008392334} +Cheakpoint... +Epoch [425/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658744931221008, 'Val/mean miou_metric': 0.9442710876464844, 'Val/mean f1': 0.9688634276390076, 'Val/mean precision': 0.9644765257835388, 'Val/mean recall': 0.9732906222343445, 'Val/mean hd95_metric': 6.10575008392334} +Epoch [426/4000] Training [1/16] Loss: 0.01553 +Epoch [426/4000] Training [2/16] Loss: 0.01599 +Epoch [426/4000] Training [3/16] Loss: 0.01254 +Epoch [426/4000] Training [4/16] Loss: 0.01420 +Epoch [426/4000] Training [5/16] Loss: 0.01649 +Epoch [426/4000] Training [6/16] Loss: 0.01853 +Epoch [426/4000] Training [7/16] Loss: 0.01710 +Epoch [426/4000] Training [8/16] Loss: 0.01288 +Epoch [426/4000] Training [9/16] Loss: 0.01853 +Epoch [426/4000] Training [10/16] Loss: 0.01228 +Epoch [426/4000] Training [11/16] Loss: 0.01677 +Epoch [426/4000] Training [12/16] Loss: 0.01768 +Epoch [426/4000] Training [13/16] Loss: 0.01482 +Epoch [426/4000] Training [14/16] Loss: 0.01447 +Epoch [426/4000] Training [15/16] Loss: 0.01454 +Epoch [426/4000] Training [16/16] Loss: 0.01973 +Epoch [426/4000] Training metric {'Train/mean dice_metric': 0.9887690544128418, 'Train/mean miou_metric': 0.9776394367218018, 'Train/mean f1': 0.9863142371177673, 'Train/mean precision': 0.9821303486824036, 'Train/mean recall': 0.9905338287353516, 'Train/mean hd95_metric': 1.4416407346725464} +Epoch [426/4000] Validation [1/4] Loss: 0.34814 focal_loss 0.22687 dice_loss 0.12127 +Epoch [426/4000] Validation [2/4] Loss: 0.23098 focal_loss 0.07759 dice_loss 0.15339 +Epoch [426/4000] Validation [3/4] Loss: 0.10710 focal_loss 0.05507 dice_loss 0.05203 +Epoch [426/4000] Validation [4/4] Loss: 0.20524 focal_loss 0.09993 dice_loss 0.10531 +Epoch [426/4000] Validation metric {'Val/mean dice_metric': 0.9643203020095825, 'Val/mean miou_metric': 0.9414661526679993, 'Val/mean f1': 0.9665024876594543, 'Val/mean precision': 0.9632238149642944, 'Val/mean recall': 0.9698038101196289, 'Val/mean hd95_metric': 6.285522937774658} +Cheakpoint... +Epoch [426/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9643], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9643203020095825, 'Val/mean miou_metric': 0.9414661526679993, 'Val/mean f1': 0.9665024876594543, 'Val/mean precision': 0.9632238149642944, 'Val/mean recall': 0.9698038101196289, 'Val/mean hd95_metric': 6.285522937774658} +Epoch [427/4000] Training [1/16] Loss: 0.01477 +Epoch [427/4000] Training [2/16] Loss: 0.01419 +Epoch [427/4000] Training [3/16] Loss: 0.01267 +Epoch [427/4000] Training [4/16] Loss: 0.02470 +Epoch [427/4000] Training [5/16] Loss: 0.01473 +Epoch [427/4000] Training [6/16] Loss: 0.01653 +Epoch [427/4000] Training [7/16] Loss: 0.01570 +Epoch [427/4000] Training [8/16] Loss: 0.01521 +Epoch [427/4000] Training [9/16] Loss: 0.02149 +Epoch [427/4000] Training [10/16] Loss: 0.01465 +Epoch [427/4000] Training [11/16] Loss: 0.01255 +Epoch [427/4000] Training [12/16] Loss: 0.02270 +Epoch [427/4000] Training [13/16] Loss: 0.01573 +Epoch [427/4000] Training [14/16] Loss: 0.01692 +Epoch [427/4000] Training [15/16] Loss: 0.01531 +Epoch [427/4000] Training [16/16] Loss: 0.01823 +Epoch [427/4000] Training metric {'Train/mean dice_metric': 0.9887739419937134, 'Train/mean miou_metric': 0.9776263236999512, 'Train/mean f1': 0.9859651923179626, 'Train/mean precision': 0.98145991563797, 'Train/mean recall': 0.9905120134353638, 'Train/mean hd95_metric': 1.7321302890777588} +Epoch [427/4000] Validation [1/4] Loss: 0.64615 focal_loss 0.47778 dice_loss 0.16838 +Epoch [427/4000] Validation [2/4] Loss: 0.22448 focal_loss 0.10304 dice_loss 0.12145 +Epoch [427/4000] Validation [3/4] Loss: 0.11922 focal_loss 0.06418 dice_loss 0.05504 +Epoch [427/4000] Validation [4/4] Loss: 0.28923 focal_loss 0.15285 dice_loss 0.13638 +Epoch [427/4000] Validation metric {'Val/mean dice_metric': 0.9664978981018066, 'Val/mean miou_metric': 0.9437652826309204, 'Val/mean f1': 0.96715247631073, 'Val/mean precision': 0.9687681794166565, 'Val/mean recall': 0.9655423164367676, 'Val/mean hd95_metric': 6.072779178619385} +Cheakpoint... +Epoch [427/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664978981018066, 'Val/mean miou_metric': 0.9437652826309204, 'Val/mean f1': 0.96715247631073, 'Val/mean precision': 0.9687681794166565, 'Val/mean recall': 0.9655423164367676, 'Val/mean hd95_metric': 6.072779178619385} +Epoch [428/4000] Training [1/16] Loss: 0.01540 +Epoch [428/4000] Training [2/16] Loss: 0.01383 +Epoch [428/4000] Training [3/16] Loss: 0.01682 +Epoch [428/4000] Training [4/16] Loss: 0.01747 +Epoch [428/4000] Training [5/16] Loss: 0.01407 +Epoch [428/4000] Training [6/16] Loss: 0.01448 +Epoch [428/4000] Training [7/16] Loss: 0.01927 +Epoch [428/4000] Training [8/16] Loss: 0.03567 +Epoch [428/4000] Training [9/16] Loss: 0.01027 +Epoch [428/4000] Training [10/16] Loss: 0.01362 +Epoch [428/4000] Training [11/16] Loss: 0.01773 +Epoch [428/4000] Training [12/16] Loss: 0.02287 +Epoch [428/4000] Training [13/16] Loss: 0.01741 +Epoch [428/4000] Training [14/16] Loss: 0.02059 +Epoch [428/4000] Training [15/16] Loss: 0.01467 +Epoch [428/4000] Training [16/16] Loss: 0.01889 +Epoch [428/4000] Training metric {'Train/mean dice_metric': 0.9886902570724487, 'Train/mean miou_metric': 0.9775038957595825, 'Train/mean f1': 0.9863525629043579, 'Train/mean precision': 0.9818664789199829, 'Train/mean recall': 0.9908797740936279, 'Train/mean hd95_metric': 1.559368371963501} +Epoch [428/4000] Validation [1/4] Loss: 0.46685 focal_loss 0.34043 dice_loss 0.12642 +Epoch [428/4000] Validation [2/4] Loss: 0.23547 focal_loss 0.09224 dice_loss 0.14324 +Epoch [428/4000] Validation [3/4] Loss: 0.12032 focal_loss 0.05755 dice_loss 0.06278 +Epoch [428/4000] Validation [4/4] Loss: 0.21566 focal_loss 0.09850 dice_loss 0.11716 +Epoch [428/4000] Validation metric {'Val/mean dice_metric': 0.964316725730896, 'Val/mean miou_metric': 0.9420192837715149, 'Val/mean f1': 0.9669263958930969, 'Val/mean precision': 0.9680493474006653, 'Val/mean recall': 0.9658060669898987, 'Val/mean hd95_metric': 5.621787071228027} +Cheakpoint... +Epoch [428/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9643], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964316725730896, 'Val/mean miou_metric': 0.9420192837715149, 'Val/mean f1': 0.9669263958930969, 'Val/mean precision': 0.9680493474006653, 'Val/mean recall': 0.9658060669898987, 'Val/mean hd95_metric': 5.621787071228027} +Epoch [429/4000] Training [1/16] Loss: 0.01920 +Epoch [429/4000] Training [2/16] Loss: 0.01190 +Epoch [429/4000] Training [3/16] Loss: 0.01616 +Epoch [429/4000] Training [4/16] Loss: 0.01149 +Epoch [429/4000] Training [5/16] Loss: 0.01183 +Epoch [429/4000] Training [6/16] Loss: 0.01355 +Epoch [429/4000] Training [7/16] Loss: 0.01272 +Epoch [429/4000] Training [8/16] Loss: 0.01567 +Epoch [429/4000] Training [9/16] Loss: 0.01637 +Epoch [429/4000] Training [10/16] Loss: 0.01425 +Epoch [429/4000] Training [11/16] Loss: 0.01148 +Epoch [429/4000] Training [12/16] Loss: 0.01489 +Epoch [429/4000] Training [13/16] Loss: 0.01193 +Epoch [429/4000] Training [14/16] Loss: 0.02153 +Epoch [429/4000] Training [15/16] Loss: 0.01740 +Epoch [429/4000] Training [16/16] Loss: 0.01796 +Epoch [429/4000] Training metric {'Train/mean dice_metric': 0.9892820119857788, 'Train/mean miou_metric': 0.978694498538971, 'Train/mean f1': 0.9868248105049133, 'Train/mean precision': 0.9822999835014343, 'Train/mean recall': 0.9913914799690247, 'Train/mean hd95_metric': 1.3552829027175903} +Epoch [429/4000] Validation [1/4] Loss: 0.56688 focal_loss 0.41875 dice_loss 0.14813 +Epoch [429/4000] Validation [2/4] Loss: 0.17527 focal_loss 0.07072 dice_loss 0.10455 +Epoch [429/4000] Validation [3/4] Loss: 0.09956 focal_loss 0.04705 dice_loss 0.05251 +Epoch [429/4000] Validation [4/4] Loss: 0.29468 focal_loss 0.14670 dice_loss 0.14798 +Epoch [429/4000] Validation metric {'Val/mean dice_metric': 0.9651992917060852, 'Val/mean miou_metric': 0.9432318806648254, 'Val/mean f1': 0.9683243036270142, 'Val/mean precision': 0.9715225100517273, 'Val/mean recall': 0.9651471972465515, 'Val/mean hd95_metric': 4.845639705657959} +Cheakpoint... +Epoch [429/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651992917060852, 'Val/mean miou_metric': 0.9432318806648254, 'Val/mean f1': 0.9683243036270142, 'Val/mean precision': 0.9715225100517273, 'Val/mean recall': 0.9651471972465515, 'Val/mean hd95_metric': 4.845639705657959} +Epoch [430/4000] Training [1/16] Loss: 0.01110 +Epoch [430/4000] Training [2/16] Loss: 0.01696 +Epoch [430/4000] Training [3/16] Loss: 0.01918 +Epoch [430/4000] Training [4/16] Loss: 0.01504 +Epoch [430/4000] Training [5/16] Loss: 0.01273 +Epoch [430/4000] Training [6/16] Loss: 0.01737 +Epoch [430/4000] Training [7/16] Loss: 0.01469 +Epoch [430/4000] Training [8/16] Loss: 0.02048 +Epoch [430/4000] Training [9/16] Loss: 0.01805 +Epoch [430/4000] Training [10/16] Loss: 0.01386 +Epoch [430/4000] Training [11/16] Loss: 0.01798 +Epoch [430/4000] Training [12/16] Loss: 0.01050 +Epoch [430/4000] Training [13/16] Loss: 0.01886 +Epoch [430/4000] Training [14/16] Loss: 0.01964 +Epoch [430/4000] Training [15/16] Loss: 0.07655 +Epoch [430/4000] Training [16/16] Loss: 0.01331 +Epoch [430/4000] Training metric {'Train/mean dice_metric': 0.988082766532898, 'Train/mean miou_metric': 0.9765247106552124, 'Train/mean f1': 0.9850846529006958, 'Train/mean precision': 0.9805814623832703, 'Train/mean recall': 0.9896293878555298, 'Train/mean hd95_metric': 1.5979247093200684} +Epoch [430/4000] Validation [1/4] Loss: 0.47714 focal_loss 0.35651 dice_loss 0.12063 +Epoch [430/4000] Validation [2/4] Loss: 0.25986 focal_loss 0.11130 dice_loss 0.14856 +Epoch [430/4000] Validation [3/4] Loss: 0.17374 focal_loss 0.08122 dice_loss 0.09252 +Epoch [430/4000] Validation [4/4] Loss: 0.21881 focal_loss 0.11146 dice_loss 0.10735 +Epoch [430/4000] Validation metric {'Val/mean dice_metric': 0.9639180898666382, 'Val/mean miou_metric': 0.9414804577827454, 'Val/mean f1': 0.9671589732170105, 'Val/mean precision': 0.963830292224884, 'Val/mean recall': 0.9705104827880859, 'Val/mean hd95_metric': 6.200532913208008} +Cheakpoint... +Epoch [430/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639180898666382, 'Val/mean miou_metric': 0.9414804577827454, 'Val/mean f1': 0.9671589732170105, 'Val/mean precision': 0.963830292224884, 'Val/mean recall': 0.9705104827880859, 'Val/mean hd95_metric': 6.200532913208008} +Epoch [431/4000] Training [1/16] Loss: 0.02321 +Epoch [431/4000] Training [2/16] Loss: 0.01678 +Epoch [431/4000] Training [3/16] Loss: 0.02159 +Epoch [431/4000] Training [4/16] Loss: 0.01220 +Epoch [431/4000] Training [5/16] Loss: 0.01921 +Epoch [431/4000] Training [6/16] Loss: 0.01451 +Epoch [431/4000] Training [7/16] Loss: 0.01460 +Epoch [431/4000] Training [8/16] Loss: 0.06251 +Epoch [431/4000] Training [9/16] Loss: 0.01744 +Epoch [431/4000] Training [10/16] Loss: 0.01429 +Epoch [431/4000] Training [11/16] Loss: 0.02041 +Epoch [431/4000] Training [12/16] Loss: 0.01490 +Epoch [431/4000] Training [13/16] Loss: 0.02184 +Epoch [431/4000] Training [14/16] Loss: 0.01376 +Epoch [431/4000] Training [15/16] Loss: 0.01669 +Epoch [431/4000] Training [16/16] Loss: 0.01589 +Epoch [431/4000] Training metric {'Train/mean dice_metric': 0.987207293510437, 'Train/mean miou_metric': 0.97491455078125, 'Train/mean f1': 0.9847491979598999, 'Train/mean precision': 0.980627715587616, 'Train/mean recall': 0.9889054298400879, 'Train/mean hd95_metric': 2.098611831665039} +Epoch [431/4000] Validation [1/4] Loss: 0.15748 focal_loss 0.08918 dice_loss 0.06831 +Epoch [431/4000] Validation [2/4] Loss: 0.21787 focal_loss 0.07985 dice_loss 0.13802 +Epoch [431/4000] Validation [3/4] Loss: 0.11712 focal_loss 0.05913 dice_loss 0.05799 +Epoch [431/4000] Validation [4/4] Loss: 0.20923 focal_loss 0.10340 dice_loss 0.10584 +Epoch [431/4000] Validation metric {'Val/mean dice_metric': 0.963923454284668, 'Val/mean miou_metric': 0.9409062266349792, 'Val/mean f1': 0.9667555093765259, 'Val/mean precision': 0.9572650790214539, 'Val/mean recall': 0.9764359593391418, 'Val/mean hd95_metric': 7.400097846984863} +Cheakpoint... +Epoch [431/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963923454284668, 'Val/mean miou_metric': 0.9409062266349792, 'Val/mean f1': 0.9667555093765259, 'Val/mean precision': 0.9572650790214539, 'Val/mean recall': 0.9764359593391418, 'Val/mean hd95_metric': 7.400097846984863} +Epoch [432/4000] Training [1/16] Loss: 0.02185 +Epoch [432/4000] Training [2/16] Loss: 0.02369 +Epoch [432/4000] Training [3/16] Loss: 0.01489 +Epoch [432/4000] Training [4/16] Loss: 0.01472 +Epoch [432/4000] Training [5/16] Loss: 0.01900 +Epoch [432/4000] Training [6/16] Loss: 0.01610 +Epoch [432/4000] Training [7/16] Loss: 0.02144 +Epoch [432/4000] Training [8/16] Loss: 0.01990 +Epoch [432/4000] Training [9/16] Loss: 0.01796 +Epoch [432/4000] Training [10/16] Loss: 0.02594 +Epoch [432/4000] Training [11/16] Loss: 0.01411 +Epoch [432/4000] Training [12/16] Loss: 0.02309 +Epoch [432/4000] Training [13/16] Loss: 0.01596 +Epoch [432/4000] Training [14/16] Loss: 0.02112 +Epoch [432/4000] Training [15/16] Loss: 0.01664 +Epoch [432/4000] Training [16/16] Loss: 0.01323 +Epoch [432/4000] Training metric {'Train/mean dice_metric': 0.9856895208358765, 'Train/mean miou_metric': 0.9720324277877808, 'Train/mean f1': 0.9826635122299194, 'Train/mean precision': 0.9780373573303223, 'Train/mean recall': 0.9873336553573608, 'Train/mean hd95_metric': 2.3566253185272217} +Epoch [432/4000] Validation [1/4] Loss: 0.58275 focal_loss 0.44383 dice_loss 0.13893 +Epoch [432/4000] Validation [2/4] Loss: 0.34503 focal_loss 0.11795 dice_loss 0.22708 +Epoch [432/4000] Validation [3/4] Loss: 0.11833 focal_loss 0.04806 dice_loss 0.07027 +Epoch [432/4000] Validation [4/4] Loss: 0.20160 focal_loss 0.08538 dice_loss 0.11622 +Epoch [432/4000] Validation metric {'Val/mean dice_metric': 0.9583898782730103, 'Val/mean miou_metric': 0.9339170455932617, 'Val/mean f1': 0.9610467553138733, 'Val/mean precision': 0.9571039080619812, 'Val/mean recall': 0.9650222659111023, 'Val/mean hd95_metric': 7.91840124130249} +Cheakpoint... +Epoch [432/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9584], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9583898782730103, 'Val/mean miou_metric': 0.9339170455932617, 'Val/mean f1': 0.9610467553138733, 'Val/mean precision': 0.9571039080619812, 'Val/mean recall': 0.9650222659111023, 'Val/mean hd95_metric': 7.91840124130249} +Epoch [433/4000] Training [1/16] Loss: 0.01863 +Epoch [433/4000] Training [2/16] Loss: 0.02309 +Epoch [433/4000] Training [3/16] Loss: 0.03382 +Epoch [433/4000] Training [4/16] Loss: 0.01392 +Epoch [433/4000] Training [5/16] Loss: 0.01723 +Epoch [433/4000] Training [6/16] Loss: 0.01685 +Epoch [433/4000] Training [7/16] Loss: 0.01568 +Epoch [433/4000] Training [8/16] Loss: 0.01793 +Epoch [433/4000] Training [9/16] Loss: 0.02350 +Epoch [433/4000] Training [10/16] Loss: 0.01456 +Epoch [433/4000] Training [11/16] Loss: 0.01528 +Epoch [433/4000] Training [12/16] Loss: 0.01185 +Epoch [433/4000] Training [13/16] Loss: 0.01677 +Epoch [433/4000] Training [14/16] Loss: 0.01582 +Epoch [433/4000] Training [15/16] Loss: 0.01584 +Epoch [433/4000] Training [16/16] Loss: 0.05204 +Epoch [433/4000] Training metric {'Train/mean dice_metric': 0.9868998527526855, 'Train/mean miou_metric': 0.9741847515106201, 'Train/mean f1': 0.9838993549346924, 'Train/mean precision': 0.9786933660507202, 'Train/mean recall': 0.9891610145568848, 'Train/mean hd95_metric': 2.459761142730713} +Epoch [433/4000] Validation [1/4] Loss: 0.79963 focal_loss 0.57860 dice_loss 0.22104 +Epoch [433/4000] Validation [2/4] Loss: 0.19652 focal_loss 0.06649 dice_loss 0.13003 +Epoch [433/4000] Validation [3/4] Loss: 0.12756 focal_loss 0.05162 dice_loss 0.07594 +Epoch [433/4000] Validation [4/4] Loss: 0.24219 focal_loss 0.11115 dice_loss 0.13104 +Epoch [433/4000] Validation metric {'Val/mean dice_metric': 0.9599153399467468, 'Val/mean miou_metric': 0.9353914260864258, 'Val/mean f1': 0.9616760611534119, 'Val/mean precision': 0.9647417664527893, 'Val/mean recall': 0.958629846572876, 'Val/mean hd95_metric': 7.618159294128418} +Cheakpoint... +Epoch [433/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599153399467468, 'Val/mean miou_metric': 0.9353914260864258, 'Val/mean f1': 0.9616760611534119, 'Val/mean precision': 0.9647417664527893, 'Val/mean recall': 0.958629846572876, 'Val/mean hd95_metric': 7.618159294128418} +Epoch [434/4000] Training [1/16] Loss: 0.01637 +Epoch [434/4000] Training [2/16] Loss: 0.01273 +Epoch [434/4000] Training [3/16] Loss: 0.02110 +Epoch [434/4000] Training [4/16] Loss: 0.01679 +Epoch [434/4000] Training [5/16] Loss: 0.01561 +Epoch [434/4000] Training [6/16] Loss: 0.01611 +Epoch [434/4000] Training [7/16] Loss: 0.02206 +Epoch [434/4000] Training [8/16] Loss: 0.01435 +Epoch [434/4000] Training [9/16] Loss: 0.01914 +Epoch [434/4000] Training [10/16] Loss: 0.01424 +Epoch [434/4000] Training [11/16] Loss: 0.01359 +Epoch [434/4000] Training [12/16] Loss: 0.01401 +Epoch [434/4000] Training [13/16] Loss: 0.02041 +Epoch [434/4000] Training [14/16] Loss: 0.01190 +Epoch [434/4000] Training [15/16] Loss: 0.02609 +Epoch [434/4000] Training [16/16] Loss: 0.01964 +Epoch [434/4000] Training metric {'Train/mean dice_metric': 0.9889047145843506, 'Train/mean miou_metric': 0.9779437184333801, 'Train/mean f1': 0.9856618642807007, 'Train/mean precision': 0.9817633032798767, 'Train/mean recall': 0.9895914793014526, 'Train/mean hd95_metric': 1.6441508531570435} +Epoch [434/4000] Validation [1/4] Loss: 0.59218 focal_loss 0.42191 dice_loss 0.17027 +Epoch [434/4000] Validation [2/4] Loss: 0.26019 focal_loss 0.09879 dice_loss 0.16140 +Epoch [434/4000] Validation [3/4] Loss: 0.10722 focal_loss 0.05379 dice_loss 0.05342 +Epoch [434/4000] Validation [4/4] Loss: 0.18155 focal_loss 0.07820 dice_loss 0.10335 +Epoch [434/4000] Validation metric {'Val/mean dice_metric': 0.9639589190483093, 'Val/mean miou_metric': 0.942501425743103, 'Val/mean f1': 0.9657412767410278, 'Val/mean precision': 0.9655275940895081, 'Val/mean recall': 0.9659548997879028, 'Val/mean hd95_metric': 6.023885250091553} +Cheakpoint... +Epoch [434/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639589190483093, 'Val/mean miou_metric': 0.942501425743103, 'Val/mean f1': 0.9657412767410278, 'Val/mean precision': 0.9655275940895081, 'Val/mean recall': 0.9659548997879028, 'Val/mean hd95_metric': 6.023885250091553} +Epoch [435/4000] Training [1/16] Loss: 0.01565 +Epoch [435/4000] Training [2/16] Loss: 0.01533 +Epoch [435/4000] Training [3/16] Loss: 0.02006 +Epoch [435/4000] Training [4/16] Loss: 0.01503 +Epoch [435/4000] Training [5/16] Loss: 0.02570 +Epoch [435/4000] Training [6/16] Loss: 0.01858 +Epoch [435/4000] Training [7/16] Loss: 0.01653 +Epoch [435/4000] Training [8/16] Loss: 0.01466 +Epoch [435/4000] Training [9/16] Loss: 0.01546 +Epoch [435/4000] Training [10/16] Loss: 0.02022 +Epoch [435/4000] Training [11/16] Loss: 0.01380 +Epoch [435/4000] Training [12/16] Loss: 0.01186 +Epoch [435/4000] Training [13/16] Loss: 0.01447 +Epoch [435/4000] Training [14/16] Loss: 0.01374 +Epoch [435/4000] Training [15/16] Loss: 0.01556 +Epoch [435/4000] Training [16/16] Loss: 0.01843 +Epoch [435/4000] Training metric {'Train/mean dice_metric': 0.9889261722564697, 'Train/mean miou_metric': 0.9779070615768433, 'Train/mean f1': 0.985299825668335, 'Train/mean precision': 0.9799864292144775, 'Train/mean recall': 0.9906710982322693, 'Train/mean hd95_metric': 1.4620355367660522} +Epoch [435/4000] Validation [1/4] Loss: 0.35897 focal_loss 0.24783 dice_loss 0.11115 +Epoch [435/4000] Validation [2/4] Loss: 0.19994 focal_loss 0.08253 dice_loss 0.11741 +Epoch [435/4000] Validation [3/4] Loss: 0.09750 focal_loss 0.04739 dice_loss 0.05011 +Epoch [435/4000] Validation [4/4] Loss: 0.19167 focal_loss 0.08097 dice_loss 0.11070 +Epoch [435/4000] Validation metric {'Val/mean dice_metric': 0.9642866849899292, 'Val/mean miou_metric': 0.9422000646591187, 'Val/mean f1': 0.9669235944747925, 'Val/mean precision': 0.9636090993881226, 'Val/mean recall': 0.9702609181404114, 'Val/mean hd95_metric': 6.423981666564941} +Cheakpoint... +Epoch [435/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9643], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9642866849899292, 'Val/mean miou_metric': 0.9422000646591187, 'Val/mean f1': 0.9669235944747925, 'Val/mean precision': 0.9636090993881226, 'Val/mean recall': 0.9702609181404114, 'Val/mean hd95_metric': 6.423981666564941} +Epoch [436/4000] Training [1/16] Loss: 0.01518 +Epoch [436/4000] Training [2/16] Loss: 0.01944 +Epoch [436/4000] Training [3/16] Loss: 0.01610 +Epoch [436/4000] Training [4/16] Loss: 0.01525 +Epoch [436/4000] Training [5/16] Loss: 0.01275 +Epoch [436/4000] Training [6/16] Loss: 0.01139 +Epoch [436/4000] Training [7/16] Loss: 0.01465 +Epoch [436/4000] Training [8/16] Loss: 0.01416 +Epoch [436/4000] Training [9/16] Loss: 0.01943 +Epoch [436/4000] Training [10/16] Loss: 0.01851 +Epoch [436/4000] Training [11/16] Loss: 0.02802 +Epoch [436/4000] Training [12/16] Loss: 0.01712 +Epoch [436/4000] Training [13/16] Loss: 0.01691 +Epoch [436/4000] Training [14/16] Loss: 0.01660 +Epoch [436/4000] Training [15/16] Loss: 0.01693 +Epoch [436/4000] Training [16/16] Loss: 0.01498 +Epoch [436/4000] Training metric {'Train/mean dice_metric': 0.9883418679237366, 'Train/mean miou_metric': 0.9768696427345276, 'Train/mean f1': 0.9855571389198303, 'Train/mean precision': 0.9810688495635986, 'Train/mean recall': 0.9900866746902466, 'Train/mean hd95_metric': 1.8414242267608643} +Epoch [436/4000] Validation [1/4] Loss: 0.24943 focal_loss 0.15175 dice_loss 0.09768 +Epoch [436/4000] Validation [2/4] Loss: 0.23778 focal_loss 0.09847 dice_loss 0.13931 +Epoch [436/4000] Validation [3/4] Loss: 0.15790 focal_loss 0.07192 dice_loss 0.08598 +Epoch [436/4000] Validation [4/4] Loss: 0.21326 focal_loss 0.10664 dice_loss 0.10662 +Epoch [436/4000] Validation metric {'Val/mean dice_metric': 0.9653761982917786, 'Val/mean miou_metric': 0.9429234266281128, 'Val/mean f1': 0.9682762622833252, 'Val/mean precision': 0.9649979472160339, 'Val/mean recall': 0.9715770483016968, 'Val/mean hd95_metric': 6.783799648284912} +Cheakpoint... +Epoch [436/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653761982917786, 'Val/mean miou_metric': 0.9429234266281128, 'Val/mean f1': 0.9682762622833252, 'Val/mean precision': 0.9649979472160339, 'Val/mean recall': 0.9715770483016968, 'Val/mean hd95_metric': 6.783799648284912} +Epoch [437/4000] Training [1/16] Loss: 0.02344 +Epoch [437/4000] Training [2/16] Loss: 0.01190 +Epoch [437/4000] Training [3/16] Loss: 0.01618 +Epoch [437/4000] Training [4/16] Loss: 0.01379 +Epoch [437/4000] Training [5/16] Loss: 0.01863 +Epoch [437/4000] Training [6/16] Loss: 0.01405 +Epoch [437/4000] Training [7/16] Loss: 0.01399 +Epoch [437/4000] Training [8/16] Loss: 0.01269 +Epoch [437/4000] Training [9/16] Loss: 0.01728 +Epoch [437/4000] Training [10/16] Loss: 0.01497 +Epoch [437/4000] Training [11/16] Loss: 0.01175 +Epoch [437/4000] Training [12/16] Loss: 0.01505 +Epoch [437/4000] Training [13/16] Loss: 0.02099 +Epoch [437/4000] Training [14/16] Loss: 0.01405 +Epoch [437/4000] Training [15/16] Loss: 0.07672 +Epoch [437/4000] Training [16/16] Loss: 0.01485 +Epoch [437/4000] Training metric {'Train/mean dice_metric': 0.9885365962982178, 'Train/mean miou_metric': 0.9773160219192505, 'Train/mean f1': 0.9851425886154175, 'Train/mean precision': 0.9814452528953552, 'Train/mean recall': 0.9888679385185242, 'Train/mean hd95_metric': 1.5692602396011353} +Epoch [437/4000] Validation [1/4] Loss: 0.16075 focal_loss 0.09350 dice_loss 0.06725 +Epoch [437/4000] Validation [2/4] Loss: 0.30812 focal_loss 0.11921 dice_loss 0.18892 +Epoch [437/4000] Validation [3/4] Loss: 0.27410 focal_loss 0.15102 dice_loss 0.12308 +Epoch [437/4000] Validation [4/4] Loss: 0.34834 focal_loss 0.16785 dice_loss 0.18049 +Epoch [437/4000] Validation metric {'Val/mean dice_metric': 0.9613486528396606, 'Val/mean miou_metric': 0.9384264945983887, 'Val/mean f1': 0.9611778259277344, 'Val/mean precision': 0.9469134211540222, 'Val/mean recall': 0.9758786559104919, 'Val/mean hd95_metric': 8.245954513549805} +Cheakpoint... +Epoch [437/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9613486528396606, 'Val/mean miou_metric': 0.9384264945983887, 'Val/mean f1': 0.9611778259277344, 'Val/mean precision': 0.9469134211540222, 'Val/mean recall': 0.9758786559104919, 'Val/mean hd95_metric': 8.245954513549805} +Epoch [438/4000] Training [1/16] Loss: 0.03387 +Epoch [438/4000] Training [2/16] Loss: 0.02346 +Epoch [438/4000] Training [3/16] Loss: 0.01847 +Epoch [438/4000] Training [4/16] Loss: 0.01554 +Epoch [438/4000] Training [5/16] Loss: 0.01887 +Epoch [438/4000] Training [6/16] Loss: 0.02418 +Epoch [438/4000] Training [7/16] Loss: 0.01976 +Epoch [438/4000] Training [8/16] Loss: 0.01880 +Epoch [438/4000] Training [9/16] Loss: 0.02038 +Epoch [438/4000] Training [10/16] Loss: 0.01529 +Epoch [438/4000] Training [11/16] Loss: 0.04996 +Epoch [438/4000] Training [12/16] Loss: 0.02502 +Epoch [438/4000] Training [13/16] Loss: 0.01949 +Epoch [438/4000] Training [14/16] Loss: 0.02091 +Epoch [438/4000] Training [15/16] Loss: 0.01677 +Epoch [438/4000] Training [16/16] Loss: 0.01934 +Epoch [438/4000] Training metric {'Train/mean dice_metric': 0.9798980951309204, 'Train/mean miou_metric': 0.964101254940033, 'Train/mean f1': 0.9760535955429077, 'Train/mean precision': 0.9695364832878113, 'Train/mean recall': 0.982658863067627, 'Train/mean hd95_metric': 5.1418609619140625} +Epoch [438/4000] Validation [1/4] Loss: 0.22174 focal_loss 0.13100 dice_loss 0.09074 +Epoch [438/4000] Validation [2/4] Loss: 0.30036 focal_loss 0.12559 dice_loss 0.17477 +Epoch [438/4000] Validation [3/4] Loss: 0.21534 focal_loss 0.09980 dice_loss 0.11554 +Epoch [438/4000] Validation [4/4] Loss: 0.29122 focal_loss 0.13376 dice_loss 0.15745 +Epoch [438/4000] Validation metric {'Val/mean dice_metric': 0.9541170001029968, 'Val/mean miou_metric': 0.9272066950798035, 'Val/mean f1': 0.9569324254989624, 'Val/mean precision': 0.9490787386894226, 'Val/mean recall': 0.9649171233177185, 'Val/mean hd95_metric': 11.327108383178711} +Cheakpoint... +Epoch [438/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9541], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9541170001029968, 'Val/mean miou_metric': 0.9272066950798035, 'Val/mean f1': 0.9569324254989624, 'Val/mean precision': 0.9490787386894226, 'Val/mean recall': 0.9649171233177185, 'Val/mean hd95_metric': 11.327108383178711} +Epoch [439/4000] Training [1/16] Loss: 0.01988 +Epoch [439/4000] Training [2/16] Loss: 0.02771 +Epoch [439/4000] Training [3/16] Loss: 0.01751 +Epoch [439/4000] Training [4/16] Loss: 0.02061 +Epoch [439/4000] Training [5/16] Loss: 0.01789 +Epoch [439/4000] Training [6/16] Loss: 0.04173 +Epoch [439/4000] Training [7/16] Loss: 0.02191 +Epoch [439/4000] Training [8/16] Loss: 0.02438 +Epoch [439/4000] Training [9/16] Loss: 0.02460 +Epoch [439/4000] Training [10/16] Loss: 0.01608 +Epoch [439/4000] Training [11/16] Loss: 0.02196 +Epoch [439/4000] Training [12/16] Loss: 0.02557 +Epoch [439/4000] Training [13/16] Loss: 0.02109 +Epoch [439/4000] Training [14/16] Loss: 0.02206 +Epoch [439/4000] Training [15/16] Loss: 0.02176 +Epoch [439/4000] Training [16/16] Loss: 0.01397 +Epoch [439/4000] Training metric {'Train/mean dice_metric': 0.9855995178222656, 'Train/mean miou_metric': 0.9715491533279419, 'Train/mean f1': 0.9823211431503296, 'Train/mean precision': 0.9766537547111511, 'Train/mean recall': 0.9880546927452087, 'Train/mean hd95_metric': 3.2251923084259033} +Epoch [439/4000] Validation [1/4] Loss: 0.21670 focal_loss 0.11901 dice_loss 0.09769 +Epoch [439/4000] Validation [2/4] Loss: 0.20122 focal_loss 0.04914 dice_loss 0.15208 +Epoch [439/4000] Validation [3/4] Loss: 0.14253 focal_loss 0.05783 dice_loss 0.08470 +Epoch [439/4000] Validation [4/4] Loss: 0.25926 focal_loss 0.10922 dice_loss 0.15004 +Epoch [439/4000] Validation metric {'Val/mean dice_metric': 0.958773136138916, 'Val/mean miou_metric': 0.9339057803153992, 'Val/mean f1': 0.9612659215927124, 'Val/mean precision': 0.9523085355758667, 'Val/mean recall': 0.9703932404518127, 'Val/mean hd95_metric': 8.903529167175293} +Cheakpoint... +Epoch [439/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9588], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.958773136138916, 'Val/mean miou_metric': 0.9339057803153992, 'Val/mean f1': 0.9612659215927124, 'Val/mean precision': 0.9523085355758667, 'Val/mean recall': 0.9703932404518127, 'Val/mean hd95_metric': 8.903529167175293} +Epoch [440/4000] Training [1/16] Loss: 0.02046 +Epoch [440/4000] Training [2/16] Loss: 0.01374 +Epoch [440/4000] Training [3/16] Loss: 0.01763 +Epoch [440/4000] Training [4/16] Loss: 0.01641 +Epoch [440/4000] Training [5/16] Loss: 0.01526 +Epoch [440/4000] Training [6/16] Loss: 0.01670 +Epoch [440/4000] Training [7/16] Loss: 0.02039 +Epoch [440/4000] Training [8/16] Loss: 0.01724 +Epoch [440/4000] Training [9/16] Loss: 0.01327 +Epoch [440/4000] Training [10/16] Loss: 0.01659 +Epoch [440/4000] Training [11/16] Loss: 0.01714 +Epoch [440/4000] Training [12/16] Loss: 0.02339 +Epoch [440/4000] Training [13/16] Loss: 0.01702 +Epoch [440/4000] Training [14/16] Loss: 0.01522 +Epoch [440/4000] Training [15/16] Loss: 0.01607 +Epoch [440/4000] Training [16/16] Loss: 0.01688 +Epoch [440/4000] Training metric {'Train/mean dice_metric': 0.9876080751419067, 'Train/mean miou_metric': 0.9753735065460205, 'Train/mean f1': 0.9839205145835876, 'Train/mean precision': 0.9787708520889282, 'Train/mean recall': 0.989124596118927, 'Train/mean hd95_metric': 1.7010611295700073} +Epoch [440/4000] Validation [1/4] Loss: 0.46062 focal_loss 0.33096 dice_loss 0.12966 +Epoch [440/4000] Validation [2/4] Loss: 0.22988 focal_loss 0.07191 dice_loss 0.15797 +Epoch [440/4000] Validation [3/4] Loss: 0.15054 focal_loss 0.06570 dice_loss 0.08484 +Epoch [440/4000] Validation [4/4] Loss: 0.21667 focal_loss 0.08048 dice_loss 0.13619 +Epoch [440/4000] Validation metric {'Val/mean dice_metric': 0.9612419009208679, 'Val/mean miou_metric': 0.9367092847824097, 'Val/mean f1': 0.9628520011901855, 'Val/mean precision': 0.9601048827171326, 'Val/mean recall': 0.9656148552894592, 'Val/mean hd95_metric': 6.985653877258301} +Cheakpoint... +Epoch [440/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612419009208679, 'Val/mean miou_metric': 0.9367092847824097, 'Val/mean f1': 0.9628520011901855, 'Val/mean precision': 0.9601048827171326, 'Val/mean recall': 0.9656148552894592, 'Val/mean hd95_metric': 6.985653877258301} +Epoch [441/4000] Training [1/16] Loss: 0.02301 +Epoch [441/4000] Training [2/16] Loss: 0.01810 +Epoch [441/4000] Training [3/16] Loss: 0.02002 +Epoch [441/4000] Training [4/16] Loss: 0.01461 +Epoch [441/4000] Training [5/16] Loss: 0.01338 +Epoch [441/4000] Training [6/16] Loss: 0.01345 +Epoch [441/4000] Training [7/16] Loss: 0.01351 +Epoch [441/4000] Training [8/16] Loss: 0.02023 +Epoch [441/4000] Training [9/16] Loss: 0.03531 +Epoch [441/4000] Training [10/16] Loss: 0.01324 +Epoch [441/4000] Training [11/16] Loss: 0.01447 +Epoch [441/4000] Training [12/16] Loss: 0.01477 +Epoch [441/4000] Training [13/16] Loss: 0.01811 +Epoch [441/4000] Training [14/16] Loss: 0.01463 +Epoch [441/4000] Training [15/16] Loss: 0.01335 +Epoch [441/4000] Training [16/16] Loss: 0.01404 +Epoch [441/4000] Training metric {'Train/mean dice_metric': 0.9887112379074097, 'Train/mean miou_metric': 0.9775034785270691, 'Train/mean f1': 0.9854188561439514, 'Train/mean precision': 0.9808237552642822, 'Train/mean recall': 0.9900572299957275, 'Train/mean hd95_metric': 1.5054746866226196} +Epoch [441/4000] Validation [1/4] Loss: 0.19992 focal_loss 0.12121 dice_loss 0.07871 +Epoch [441/4000] Validation [2/4] Loss: 0.13912 focal_loss 0.04624 dice_loss 0.09288 +Epoch [441/4000] Validation [3/4] Loss: 0.21756 focal_loss 0.11761 dice_loss 0.09995 +Epoch [441/4000] Validation [4/4] Loss: 0.22052 focal_loss 0.08561 dice_loss 0.13491 +Epoch [441/4000] Validation metric {'Val/mean dice_metric': 0.9625231623649597, 'Val/mean miou_metric': 0.939043402671814, 'Val/mean f1': 0.9652428030967712, 'Val/mean precision': 0.9573986530303955, 'Val/mean recall': 0.9732165932655334, 'Val/mean hd95_metric': 7.243199348449707} +Cheakpoint... +Epoch [441/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625231623649597, 'Val/mean miou_metric': 0.939043402671814, 'Val/mean f1': 0.9652428030967712, 'Val/mean precision': 0.9573986530303955, 'Val/mean recall': 0.9732165932655334, 'Val/mean hd95_metric': 7.243199348449707} +Epoch [442/4000] Training [1/16] Loss: 0.01714 +Epoch [442/4000] Training [2/16] Loss: 0.01567 +Epoch [442/4000] Training [3/16] Loss: 0.01457 +Epoch [442/4000] Training [4/16] Loss: 0.01534 +Epoch [442/4000] Training [5/16] Loss: 0.01841 +Epoch [442/4000] Training [6/16] Loss: 0.01318 +Epoch [442/4000] Training [7/16] Loss: 0.01464 +Epoch [442/4000] Training [8/16] Loss: 0.01518 +Epoch [442/4000] Training [9/16] Loss: 0.01477 +Epoch [442/4000] Training [10/16] Loss: 0.01343 +Epoch [442/4000] Training [11/16] Loss: 0.01398 +Epoch [442/4000] Training [12/16] Loss: 0.01654 +Epoch [442/4000] Training [13/16] Loss: 0.01556 +Epoch [442/4000] Training [14/16] Loss: 0.01701 +Epoch [442/4000] Training [15/16] Loss: 0.01666 +Epoch [442/4000] Training [16/16] Loss: 0.01437 +Epoch [442/4000] Training metric {'Train/mean dice_metric': 0.9896687269210815, 'Train/mean miou_metric': 0.979353666305542, 'Train/mean f1': 0.9862073659896851, 'Train/mean precision': 0.9813082218170166, 'Train/mean recall': 0.9911556839942932, 'Train/mean hd95_metric': 1.8851121664047241} +Epoch [442/4000] Validation [1/4] Loss: 0.28932 focal_loss 0.19080 dice_loss 0.09852 +Epoch [442/4000] Validation [2/4] Loss: 0.39563 focal_loss 0.16088 dice_loss 0.23475 +Epoch [442/4000] Validation [3/4] Loss: 0.22965 focal_loss 0.12587 dice_loss 0.10378 +Epoch [442/4000] Validation [4/4] Loss: 0.19343 focal_loss 0.06318 dice_loss 0.13025 +Epoch [442/4000] Validation metric {'Val/mean dice_metric': 0.9637495279312134, 'Val/mean miou_metric': 0.9417179226875305, 'Val/mean f1': 0.9670438766479492, 'Val/mean precision': 0.9619554877281189, 'Val/mean recall': 0.9721863269805908, 'Val/mean hd95_metric': 7.376860618591309} +Cheakpoint... +Epoch [442/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637495279312134, 'Val/mean miou_metric': 0.9417179226875305, 'Val/mean f1': 0.9670438766479492, 'Val/mean precision': 0.9619554877281189, 'Val/mean recall': 0.9721863269805908, 'Val/mean hd95_metric': 7.376860618591309} +Epoch [443/4000] Training [1/16] Loss: 0.01588 +Epoch [443/4000] Training [2/16] Loss: 0.01503 +Epoch [443/4000] Training [3/16] Loss: 0.00985 +Epoch [443/4000] Training [4/16] Loss: 0.01215 +Epoch [443/4000] Training [5/16] Loss: 0.01645 +Epoch [443/4000] Training [6/16] Loss: 0.01243 +Epoch [443/4000] Training [7/16] Loss: 0.01012 +Epoch [443/4000] Training [8/16] Loss: 0.01220 +Epoch [443/4000] Training [9/16] Loss: 0.01294 +Epoch [443/4000] Training [10/16] Loss: 0.02527 +Epoch [443/4000] Training [11/16] Loss: 0.01456 +Epoch [443/4000] Training [12/16] Loss: 0.01368 +Epoch [443/4000] Training [13/16] Loss: 0.01031 +Epoch [443/4000] Training [14/16] Loss: 0.01454 +Epoch [443/4000] Training [15/16] Loss: 0.01291 +Epoch [443/4000] Training [16/16] Loss: 0.01066 +Epoch [443/4000] Training metric {'Train/mean dice_metric': 0.9902520775794983, 'Train/mean miou_metric': 0.9805107712745667, 'Train/mean f1': 0.9868554472923279, 'Train/mean precision': 0.982026219367981, 'Train/mean recall': 0.9917323589324951, 'Train/mean hd95_metric': 1.2822884321212769} +Epoch [443/4000] Validation [1/4] Loss: 0.19939 focal_loss 0.12339 dice_loss 0.07600 +Epoch [443/4000] Validation [2/4] Loss: 0.15417 focal_loss 0.05656 dice_loss 0.09762 +Epoch [443/4000] Validation [3/4] Loss: 0.18502 focal_loss 0.09290 dice_loss 0.09211 +Epoch [443/4000] Validation [4/4] Loss: 0.23995 focal_loss 0.11270 dice_loss 0.12724 +Epoch [443/4000] Validation metric {'Val/mean dice_metric': 0.9653892517089844, 'Val/mean miou_metric': 0.9439741373062134, 'Val/mean f1': 0.9682931900024414, 'Val/mean precision': 0.9634953737258911, 'Val/mean recall': 0.9731389284133911, 'Val/mean hd95_metric': 6.412911891937256} +Cheakpoint... +Epoch [443/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653892517089844, 'Val/mean miou_metric': 0.9439741373062134, 'Val/mean f1': 0.9682931900024414, 'Val/mean precision': 0.9634953737258911, 'Val/mean recall': 0.9731389284133911, 'Val/mean hd95_metric': 6.412911891937256} +Epoch [444/4000] Training [1/16] Loss: 0.01244 +Epoch [444/4000] Training [2/16] Loss: 0.01117 +Epoch [444/4000] Training [3/16] Loss: 0.01571 +Epoch [444/4000] Training [4/16] Loss: 0.01138 +Epoch [444/4000] Training [5/16] Loss: 0.01563 +Epoch [444/4000] Training [6/16] Loss: 0.01512 +Epoch [444/4000] Training [7/16] Loss: 0.01579 +Epoch [444/4000] Training [8/16] Loss: 0.01734 +Epoch [444/4000] Training [9/16] Loss: 0.01518 +Epoch [444/4000] Training [10/16] Loss: 0.01462 +Epoch [444/4000] Training [11/16] Loss: 0.02314 +Epoch [444/4000] Training [12/16] Loss: 0.01289 +Epoch [444/4000] Training [13/16] Loss: 0.01351 +Epoch [444/4000] Training [14/16] Loss: 0.01410 +Epoch [444/4000] Training [15/16] Loss: 0.01429 +Epoch [444/4000] Training [16/16] Loss: 0.01327 +Epoch [444/4000] Training metric {'Train/mean dice_metric': 0.9894876480102539, 'Train/mean miou_metric': 0.9790382385253906, 'Train/mean f1': 0.9866448044776917, 'Train/mean precision': 0.9820002317428589, 'Train/mean recall': 0.991333544254303, 'Train/mean hd95_metric': 1.34114670753479} +Epoch [444/4000] Validation [1/4] Loss: 0.14706 focal_loss 0.08792 dice_loss 0.05914 +Epoch [444/4000] Validation [2/4] Loss: 0.14647 focal_loss 0.06048 dice_loss 0.08600 +Epoch [444/4000] Validation [3/4] Loss: 0.18969 focal_loss 0.09727 dice_loss 0.09243 +Epoch [444/4000] Validation [4/4] Loss: 0.20745 focal_loss 0.08747 dice_loss 0.11998 +Epoch [444/4000] Validation metric {'Val/mean dice_metric': 0.9652964472770691, 'Val/mean miou_metric': 0.9434531331062317, 'Val/mean f1': 0.9678993225097656, 'Val/mean precision': 0.9637086987495422, 'Val/mean recall': 0.9721264839172363, 'Val/mean hd95_metric': 6.233147621154785} +Cheakpoint... +Epoch [444/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652964472770691, 'Val/mean miou_metric': 0.9434531331062317, 'Val/mean f1': 0.9678993225097656, 'Val/mean precision': 0.9637086987495422, 'Val/mean recall': 0.9721264839172363, 'Val/mean hd95_metric': 6.233147621154785} +Epoch [445/4000] Training [1/16] Loss: 0.01318 +Epoch [445/4000] Training [2/16] Loss: 0.01154 +Epoch [445/4000] Training [3/16] Loss: 0.01152 +Epoch [445/4000] Training [4/16] Loss: 0.01163 +Epoch [445/4000] Training [5/16] Loss: 0.01389 +Epoch [445/4000] Training [6/16] Loss: 0.01382 +Epoch [445/4000] Training [7/16] Loss: 0.01293 +Epoch [445/4000] Training [8/16] Loss: 0.01519 +Epoch [445/4000] Training [9/16] Loss: 0.01573 +Epoch [445/4000] Training [10/16] Loss: 0.01232 +Epoch [445/4000] Training [11/16] Loss: 0.01483 +Epoch [445/4000] Training [12/16] Loss: 0.01266 +Epoch [445/4000] Training [13/16] Loss: 0.01056 +Epoch [445/4000] Training [14/16] Loss: 0.01608 +Epoch [445/4000] Training [15/16] Loss: 0.01300 +Epoch [445/4000] Training [16/16] Loss: 0.02331 +Epoch [445/4000] Training metric {'Train/mean dice_metric': 0.9899283647537231, 'Train/mean miou_metric': 0.9798701405525208, 'Train/mean f1': 0.9870211482048035, 'Train/mean precision': 0.9824520945549011, 'Train/mean recall': 0.991632878780365, 'Train/mean hd95_metric': 1.2409576177597046} +Epoch [445/4000] Validation [1/4] Loss: 0.33597 focal_loss 0.23143 dice_loss 0.10454 +Epoch [445/4000] Validation [2/4] Loss: 0.16460 focal_loss 0.05620 dice_loss 0.10840 +Epoch [445/4000] Validation [3/4] Loss: 0.23492 focal_loss 0.13797 dice_loss 0.09695 +Epoch [445/4000] Validation [4/4] Loss: 0.18611 focal_loss 0.09396 dice_loss 0.09215 +Epoch [445/4000] Validation metric {'Val/mean dice_metric': 0.9659727215766907, 'Val/mean miou_metric': 0.9444698095321655, 'Val/mean f1': 0.9679984450340271, 'Val/mean precision': 0.9628697633743286, 'Val/mean recall': 0.973181962966919, 'Val/mean hd95_metric': 6.4645490646362305} +Cheakpoint... +Epoch [445/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659727215766907, 'Val/mean miou_metric': 0.9444698095321655, 'Val/mean f1': 0.9679984450340271, 'Val/mean precision': 0.9628697633743286, 'Val/mean recall': 0.973181962966919, 'Val/mean hd95_metric': 6.4645490646362305} +Epoch [446/4000] Training [1/16] Loss: 0.01199 +Epoch [446/4000] Training [2/16] Loss: 0.01226 +Epoch [446/4000] Training [3/16] Loss: 0.01712 +Epoch [446/4000] Training [4/16] Loss: 0.01702 +Epoch [446/4000] Training [5/16] Loss: 0.01654 +Epoch [446/4000] Training [6/16] Loss: 0.01419 +Epoch [446/4000] Training [7/16] Loss: 0.01415 +Epoch [446/4000] Training [8/16] Loss: 0.01170 +Epoch [446/4000] Training [9/16] Loss: 0.01039 +Epoch [446/4000] Training [10/16] Loss: 0.01433 +Epoch [446/4000] Training [11/16] Loss: 0.01490 +Epoch [446/4000] Training [12/16] Loss: 0.01438 +Epoch [446/4000] Training [13/16] Loss: 0.01779 +Epoch [446/4000] Training [14/16] Loss: 0.01418 +Epoch [446/4000] Training [15/16] Loss: 0.01415 +Epoch [446/4000] Training [16/16] Loss: 0.01980 +Epoch [446/4000] Training metric {'Train/mean dice_metric': 0.9896422624588013, 'Train/mean miou_metric': 0.9793154001235962, 'Train/mean f1': 0.9868821501731873, 'Train/mean precision': 0.9824858903884888, 'Train/mean recall': 0.9913180470466614, 'Train/mean hd95_metric': 1.4179576635360718} +Epoch [446/4000] Validation [1/4] Loss: 0.46112 focal_loss 0.34703 dice_loss 0.11409 +Epoch [446/4000] Validation [2/4] Loss: 0.35116 focal_loss 0.14295 dice_loss 0.20822 +Epoch [446/4000] Validation [3/4] Loss: 0.16033 focal_loss 0.07052 dice_loss 0.08981 +Epoch [446/4000] Validation [4/4] Loss: 0.15764 focal_loss 0.06681 dice_loss 0.09083 +Epoch [446/4000] Validation metric {'Val/mean dice_metric': 0.9659515619277954, 'Val/mean miou_metric': 0.9444110989570618, 'Val/mean f1': 0.967054545879364, 'Val/mean precision': 0.9670782685279846, 'Val/mean recall': 0.9670307636260986, 'Val/mean hd95_metric': 6.1844987869262695} +Cheakpoint... +Epoch [446/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659515619277954, 'Val/mean miou_metric': 0.9444110989570618, 'Val/mean f1': 0.967054545879364, 'Val/mean precision': 0.9670782685279846, 'Val/mean recall': 0.9670307636260986, 'Val/mean hd95_metric': 6.1844987869262695} +Epoch [447/4000] Training [1/16] Loss: 0.01795 +Epoch [447/4000] Training [2/16] Loss: 0.01532 +Epoch [447/4000] Training [3/16] Loss: 0.01586 +Epoch [447/4000] Training [4/16] Loss: 0.01567 +Epoch [447/4000] Training [5/16] Loss: 0.01431 +Epoch [447/4000] Training [6/16] Loss: 0.01901 +Epoch [447/4000] Training [7/16] Loss: 0.01305 +Epoch [447/4000] Training [8/16] Loss: 0.01935 +Epoch [447/4000] Training [9/16] Loss: 0.02081 +Epoch [447/4000] Training [10/16] Loss: 0.01674 +Epoch [447/4000] Training [11/16] Loss: 0.01922 +Epoch [447/4000] Training [12/16] Loss: 0.01297 +Epoch [447/4000] Training [13/16] Loss: 0.01455 +Epoch [447/4000] Training [14/16] Loss: 0.01510 +Epoch [447/4000] Training [15/16] Loss: 0.01152 +Epoch [447/4000] Training [16/16] Loss: 0.01585 +Epoch [447/4000] Training metric {'Train/mean dice_metric': 0.9887654185295105, 'Train/mean miou_metric': 0.9776700735092163, 'Train/mean f1': 0.9865681529045105, 'Train/mean precision': 0.9820566773414612, 'Train/mean recall': 0.991121232509613, 'Train/mean hd95_metric': 1.3862230777740479} +Epoch [447/4000] Validation [1/4] Loss: 0.39100 focal_loss 0.27962 dice_loss 0.11138 +Epoch [447/4000] Validation [2/4] Loss: 0.22054 focal_loss 0.09211 dice_loss 0.12842 +Epoch [447/4000] Validation [3/4] Loss: 0.13043 focal_loss 0.06421 dice_loss 0.06622 +Epoch [447/4000] Validation [4/4] Loss: 0.22375 focal_loss 0.10504 dice_loss 0.11871 +Epoch [447/4000] Validation metric {'Val/mean dice_metric': 0.9653293490409851, 'Val/mean miou_metric': 0.9434980154037476, 'Val/mean f1': 0.9678730368614197, 'Val/mean precision': 0.9627522230148315, 'Val/mean recall': 0.973048746585846, 'Val/mean hd95_metric': 6.470736026763916} +Cheakpoint... +Epoch [447/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653293490409851, 'Val/mean miou_metric': 0.9434980154037476, 'Val/mean f1': 0.9678730368614197, 'Val/mean precision': 0.9627522230148315, 'Val/mean recall': 0.973048746585846, 'Val/mean hd95_metric': 6.470736026763916} +Epoch [448/4000] Training [1/16] Loss: 0.01348 +Epoch [448/4000] Training [2/16] Loss: 0.01432 +Epoch [448/4000] Training [3/16] Loss: 0.01379 +Epoch [448/4000] Training [4/16] Loss: 0.01954 +Epoch [448/4000] Training [5/16] Loss: 0.02152 +Epoch [448/4000] Training [6/16] Loss: 0.01510 +Epoch [448/4000] Training [7/16] Loss: 0.01463 +Epoch [448/4000] Training [8/16] Loss: 0.01503 +Epoch [448/4000] Training [9/16] Loss: 0.01798 +Epoch [448/4000] Training [10/16] Loss: 0.01563 +Epoch [448/4000] Training [11/16] Loss: 0.01269 +Epoch [448/4000] Training [12/16] Loss: 0.01563 +Epoch [448/4000] Training [13/16] Loss: 0.01453 +Epoch [448/4000] Training [14/16] Loss: 0.01179 +Epoch [448/4000] Training [15/16] Loss: 0.01489 +Epoch [448/4000] Training [16/16] Loss: 0.01396 +Epoch [448/4000] Training metric {'Train/mean dice_metric': 0.9886150360107422, 'Train/mean miou_metric': 0.9773772954940796, 'Train/mean f1': 0.9854333996772766, 'Train/mean precision': 0.9800733923912048, 'Train/mean recall': 0.9908523559570312, 'Train/mean hd95_metric': 1.5393296480178833} +Epoch [448/4000] Validation [1/4] Loss: 0.43599 focal_loss 0.31230 dice_loss 0.12369 +Epoch [448/4000] Validation [2/4] Loss: 0.21052 focal_loss 0.08295 dice_loss 0.12757 +Epoch [448/4000] Validation [3/4] Loss: 0.10874 focal_loss 0.05323 dice_loss 0.05551 +Epoch [448/4000] Validation [4/4] Loss: 0.26327 focal_loss 0.13317 dice_loss 0.13011 +Epoch [448/4000] Validation metric {'Val/mean dice_metric': 0.9664360880851746, 'Val/mean miou_metric': 0.943462073802948, 'Val/mean f1': 0.9676202535629272, 'Val/mean precision': 0.967237651348114, 'Val/mean recall': 0.9680030941963196, 'Val/mean hd95_metric': 5.79217529296875} +Cheakpoint... +Epoch [448/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664360880851746, 'Val/mean miou_metric': 0.943462073802948, 'Val/mean f1': 0.9676202535629272, 'Val/mean precision': 0.967237651348114, 'Val/mean recall': 0.9680030941963196, 'Val/mean hd95_metric': 5.79217529296875} +Epoch [449/4000] Training [1/16] Loss: 0.01602 +Epoch [449/4000] Training [2/16] Loss: 0.01226 +Epoch [449/4000] Training [3/16] Loss: 0.01661 +Epoch [449/4000] Training [4/16] Loss: 0.01381 +Epoch [449/4000] Training [5/16] Loss: 0.01235 +Epoch [449/4000] Training [6/16] Loss: 0.01407 +Epoch [449/4000] Training [7/16] Loss: 0.01431 +Epoch [449/4000] Training [8/16] Loss: 0.01607 +Epoch [449/4000] Training [9/16] Loss: 0.01748 +Epoch [449/4000] Training [10/16] Loss: 0.01547 +Epoch [449/4000] Training [11/16] Loss: 0.01256 +Epoch [449/4000] Training [12/16] Loss: 0.01460 +Epoch [449/4000] Training [13/16] Loss: 0.01163 +Epoch [449/4000] Training [14/16] Loss: 0.01789 +Epoch [449/4000] Training [15/16] Loss: 0.01270 +Epoch [449/4000] Training [16/16] Loss: 0.01227 +Epoch [449/4000] Training metric {'Train/mean dice_metric': 0.9889539480209351, 'Train/mean miou_metric': 0.9780594110488892, 'Train/mean f1': 0.986345112323761, 'Train/mean precision': 0.9816793203353882, 'Train/mean recall': 0.9910555481910706, 'Train/mean hd95_metric': 1.364113688468933} +Epoch [449/4000] Validation [1/4] Loss: 0.39490 focal_loss 0.25398 dice_loss 0.14092 +Epoch [449/4000] Validation [2/4] Loss: 0.17557 focal_loss 0.06507 dice_loss 0.11050 +Epoch [449/4000] Validation [3/4] Loss: 0.13783 focal_loss 0.07101 dice_loss 0.06682 +Epoch [449/4000] Validation [4/4] Loss: 0.28840 focal_loss 0.14736 dice_loss 0.14105 +Epoch [449/4000] Validation metric {'Val/mean dice_metric': 0.962384045124054, 'Val/mean miou_metric': 0.9398962259292603, 'Val/mean f1': 0.9658647775650024, 'Val/mean precision': 0.9641798734664917, 'Val/mean recall': 0.9675555229187012, 'Val/mean hd95_metric': 6.1764373779296875} +Cheakpoint... +Epoch [449/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9624], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.962384045124054, 'Val/mean miou_metric': 0.9398962259292603, 'Val/mean f1': 0.9658647775650024, 'Val/mean precision': 0.9641798734664917, 'Val/mean recall': 0.9675555229187012, 'Val/mean hd95_metric': 6.1764373779296875} +Epoch [450/4000] Training [1/16] Loss: 0.01480 +Epoch [450/4000] Training [2/16] Loss: 0.01558 +Epoch [450/4000] Training [3/16] Loss: 0.01729 +Epoch [450/4000] Training [4/16] Loss: 0.01558 +Epoch [450/4000] Training [5/16] Loss: 0.01250 +Epoch [450/4000] Training [6/16] Loss: 0.01386 +Epoch [450/4000] Training [7/16] Loss: 0.01371 +Epoch [450/4000] Training [8/16] Loss: 0.01876 +Epoch [450/4000] Training [9/16] Loss: 0.01203 +Epoch [450/4000] Training [10/16] Loss: 0.01264 +Epoch [450/4000] Training [11/16] Loss: 0.01023 +Epoch [450/4000] Training [12/16] Loss: 0.01694 +Epoch [450/4000] Training [13/16] Loss: 0.01777 +Epoch [450/4000] Training [14/16] Loss: 0.01864 +Epoch [450/4000] Training [15/16] Loss: 0.01903 +Epoch [450/4000] Training [16/16] Loss: 0.01662 +Epoch [450/4000] Training metric {'Train/mean dice_metric': 0.9885848760604858, 'Train/mean miou_metric': 0.9773485660552979, 'Train/mean f1': 0.986278772354126, 'Train/mean precision': 0.9813529849052429, 'Train/mean recall': 0.9912542700767517, 'Train/mean hd95_metric': 1.3984063863754272} +Epoch [450/4000] Validation [1/4] Loss: 0.16203 focal_loss 0.10068 dice_loss 0.06135 +Epoch [450/4000] Validation [2/4] Loss: 0.20981 focal_loss 0.08900 dice_loss 0.12082 +Epoch [450/4000] Validation [3/4] Loss: 0.11137 focal_loss 0.05282 dice_loss 0.05855 +Epoch [450/4000] Validation [4/4] Loss: 0.21159 focal_loss 0.11470 dice_loss 0.09689 +Epoch [450/4000] Validation metric {'Val/mean dice_metric': 0.9668213129043579, 'Val/mean miou_metric': 0.9445360898971558, 'Val/mean f1': 0.9694347381591797, 'Val/mean precision': 0.9659570455551147, 'Val/mean recall': 0.9729375839233398, 'Val/mean hd95_metric': 5.664370536804199} +Cheakpoint... +Epoch [450/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668213129043579, 'Val/mean miou_metric': 0.9445360898971558, 'Val/mean f1': 0.9694347381591797, 'Val/mean precision': 0.9659570455551147, 'Val/mean recall': 0.9729375839233398, 'Val/mean hd95_metric': 5.664370536804199} +Epoch [451/4000] Training [1/16] Loss: 0.01747 +Epoch [451/4000] Training [2/16] Loss: 0.01296 +Epoch [451/4000] Training [3/16] Loss: 0.01809 +Epoch [451/4000] Training [4/16] Loss: 0.01314 +Epoch [451/4000] Training [5/16] Loss: 0.01898 +Epoch [451/4000] Training [6/16] Loss: 0.01383 +Epoch [451/4000] Training [7/16] Loss: 0.01540 +Epoch [451/4000] Training [8/16] Loss: 0.01289 +Epoch [451/4000] Training [9/16] Loss: 0.01606 +Epoch [451/4000] Training [10/16] Loss: 0.01927 +Epoch [451/4000] Training [11/16] Loss: 0.01747 +Epoch [451/4000] Training [12/16] Loss: 0.01768 +Epoch [451/4000] Training [13/16] Loss: 0.01553 +Epoch [451/4000] Training [14/16] Loss: 0.01506 +Epoch [451/4000] Training [15/16] Loss: 0.03966 +Epoch [451/4000] Training [16/16] Loss: 0.01261 +Epoch [451/4000] Training metric {'Train/mean dice_metric': 0.9889097213745117, 'Train/mean miou_metric': 0.9779934883117676, 'Train/mean f1': 0.986675500869751, 'Train/mean precision': 0.9825468063354492, 'Train/mean recall': 0.9908390641212463, 'Train/mean hd95_metric': 1.4089813232421875} +Epoch [451/4000] Validation [1/4] Loss: 0.29697 focal_loss 0.19387 dice_loss 0.10310 +Epoch [451/4000] Validation [2/4] Loss: 0.22718 focal_loss 0.08947 dice_loss 0.13772 +Epoch [451/4000] Validation [3/4] Loss: 0.11519 focal_loss 0.04750 dice_loss 0.06768 +Epoch [451/4000] Validation [4/4] Loss: 0.19815 focal_loss 0.09962 dice_loss 0.09853 +Epoch [451/4000] Validation metric {'Val/mean dice_metric': 0.9661960601806641, 'Val/mean miou_metric': 0.9435922503471375, 'Val/mean f1': 0.968207836151123, 'Val/mean precision': 0.9654302597045898, 'Val/mean recall': 0.971001386642456, 'Val/mean hd95_metric': 6.013807773590088} +Cheakpoint... +Epoch [451/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661960601806641, 'Val/mean miou_metric': 0.9435922503471375, 'Val/mean f1': 0.968207836151123, 'Val/mean precision': 0.9654302597045898, 'Val/mean recall': 0.971001386642456, 'Val/mean hd95_metric': 6.013807773590088} +Epoch [452/4000] Training [1/16] Loss: 0.02164 +Epoch [452/4000] Training [2/16] Loss: 0.01406 +Epoch [452/4000] Training [3/16] Loss: 0.01936 +Epoch [452/4000] Training [4/16] Loss: 0.01181 +Epoch [452/4000] Training [5/16] Loss: 0.01211 +Epoch [452/4000] Training [6/16] Loss: 0.01558 +Epoch [452/4000] Training [7/16] Loss: 0.02958 +Epoch [452/4000] Training [8/16] Loss: 0.01599 +Epoch [452/4000] Training [9/16] Loss: 0.01396 +Epoch [452/4000] Training [10/16] Loss: 0.01112 +Epoch [452/4000] Training [11/16] Loss: 0.01587 +Epoch [452/4000] Training [12/16] Loss: 0.01651 +Epoch [452/4000] Training [13/16] Loss: 0.01479 +Epoch [452/4000] Training [14/16] Loss: 0.01528 +Epoch [452/4000] Training [15/16] Loss: 0.01660 +Epoch [452/4000] Training [16/16] Loss: 0.01887 +Epoch [452/4000] Training metric {'Train/mean dice_metric': 0.9864897131919861, 'Train/mean miou_metric': 0.9750409722328186, 'Train/mean f1': 0.9855673909187317, 'Train/mean precision': 0.9811923503875732, 'Train/mean recall': 0.9899816513061523, 'Train/mean hd95_metric': 2.0377163887023926} +Epoch [452/4000] Validation [1/4] Loss: 0.45423 focal_loss 0.32059 dice_loss 0.13365 +Epoch [452/4000] Validation [2/4] Loss: 0.17036 focal_loss 0.06985 dice_loss 0.10051 +Epoch [452/4000] Validation [3/4] Loss: 0.09920 focal_loss 0.04595 dice_loss 0.05325 +Epoch [452/4000] Validation [4/4] Loss: 0.21682 focal_loss 0.10381 dice_loss 0.11300 +Epoch [452/4000] Validation metric {'Val/mean dice_metric': 0.9619119763374329, 'Val/mean miou_metric': 0.938873291015625, 'Val/mean f1': 0.9649698734283447, 'Val/mean precision': 0.9688755869865417, 'Val/mean recall': 0.9610957503318787, 'Val/mean hd95_metric': 7.087828636169434} +Cheakpoint... +Epoch [452/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9619], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9619119763374329, 'Val/mean miou_metric': 0.938873291015625, 'Val/mean f1': 0.9649698734283447, 'Val/mean precision': 0.9688755869865417, 'Val/mean recall': 0.9610957503318787, 'Val/mean hd95_metric': 7.087828636169434} +Epoch [453/4000] Training [1/16] Loss: 0.01684 +Epoch [453/4000] Training [2/16] Loss: 0.01595 +Epoch [453/4000] Training [3/16] Loss: 0.02025 +Epoch [453/4000] Training [4/16] Loss: 0.01838 +Epoch [453/4000] Training [5/16] Loss: 0.00976 +Epoch [453/4000] Training [6/16] Loss: 0.01238 +Epoch [453/4000] Training [7/16] Loss: 0.01442 +Epoch [453/4000] Training [8/16] Loss: 0.01821 +Epoch [453/4000] Training [9/16] Loss: 0.01536 +Epoch [453/4000] Training [10/16] Loss: 0.01599 +Epoch [453/4000] Training [11/16] Loss: 0.01415 +Epoch [453/4000] Training [12/16] Loss: 0.01431 +Epoch [453/4000] Training [13/16] Loss: 0.01543 +Epoch [453/4000] Training [14/16] Loss: 0.01485 +Epoch [453/4000] Training [15/16] Loss: 0.02340 +Epoch [453/4000] Training [16/16] Loss: 0.01553 +Epoch [453/4000] Training metric {'Train/mean dice_metric': 0.9871643781661987, 'Train/mean miou_metric': 0.9752593636512756, 'Train/mean f1': 0.9850110411643982, 'Train/mean precision': 0.9800631403923035, 'Train/mean recall': 0.9900091886520386, 'Train/mean hd95_metric': 2.3072314262390137} +Epoch [453/4000] Validation [1/4] Loss: 0.18242 focal_loss 0.10233 dice_loss 0.08009 +Epoch [453/4000] Validation [2/4] Loss: 0.21940 focal_loss 0.08006 dice_loss 0.13934 +Epoch [453/4000] Validation [3/4] Loss: 0.13342 focal_loss 0.06808 dice_loss 0.06534 +Epoch [453/4000] Validation [4/4] Loss: 0.23576 focal_loss 0.10837 dice_loss 0.12739 +Epoch [453/4000] Validation metric {'Val/mean dice_metric': 0.9636517763137817, 'Val/mean miou_metric': 0.9404848217964172, 'Val/mean f1': 0.9676413536071777, 'Val/mean precision': 0.9628796577453613, 'Val/mean recall': 0.9724502563476562, 'Val/mean hd95_metric': 6.999987602233887} +Cheakpoint... +Epoch [453/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636517763137817, 'Val/mean miou_metric': 0.9404848217964172, 'Val/mean f1': 0.9676413536071777, 'Val/mean precision': 0.9628796577453613, 'Val/mean recall': 0.9724502563476562, 'Val/mean hd95_metric': 6.999987602233887} +Epoch [454/4000] Training [1/16] Loss: 0.01587 +Epoch [454/4000] Training [2/16] Loss: 0.02217 +Epoch [454/4000] Training [3/16] Loss: 0.01256 +Epoch [454/4000] Training [4/16] Loss: 0.01847 +Epoch [454/4000] Training [5/16] Loss: 0.01781 +Epoch [454/4000] Training [6/16] Loss: 0.01600 +Epoch [454/4000] Training [7/16] Loss: 0.01775 +Epoch [454/4000] Training [8/16] Loss: 0.01669 +Epoch [454/4000] Training [9/16] Loss: 0.01829 +Epoch [454/4000] Training [10/16] Loss: 0.01496 +Epoch [454/4000] Training [11/16] Loss: 0.01684 +Epoch [454/4000] Training [12/16] Loss: 0.01551 +Epoch [454/4000] Training [13/16] Loss: 0.01520 +Epoch [454/4000] Training [14/16] Loss: 0.01639 +Epoch [454/4000] Training [15/16] Loss: 0.01387 +Epoch [454/4000] Training [16/16] Loss: 0.01606 +Epoch [454/4000] Training metric {'Train/mean dice_metric': 0.987152099609375, 'Train/mean miou_metric': 0.9751259088516235, 'Train/mean f1': 0.9854311347007751, 'Train/mean precision': 0.9809382557868958, 'Train/mean recall': 0.9899653196334839, 'Train/mean hd95_metric': 1.9446086883544922} +Epoch [454/4000] Validation [1/4] Loss: 0.24813 focal_loss 0.16581 dice_loss 0.08231 +Epoch [454/4000] Validation [2/4] Loss: 0.26787 focal_loss 0.12806 dice_loss 0.13981 +Epoch [454/4000] Validation [3/4] Loss: 0.21282 focal_loss 0.11594 dice_loss 0.09688 +Epoch [454/4000] Validation [4/4] Loss: 0.24388 focal_loss 0.12415 dice_loss 0.11973 +Epoch [454/4000] Validation metric {'Val/mean dice_metric': 0.9642259478569031, 'Val/mean miou_metric': 0.9409756660461426, 'Val/mean f1': 0.9672880172729492, 'Val/mean precision': 0.962570309638977, 'Val/mean recall': 0.9720520973205566, 'Val/mean hd95_metric': 7.219206809997559} +Cheakpoint... +Epoch [454/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9642], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9642259478569031, 'Val/mean miou_metric': 0.9409756660461426, 'Val/mean f1': 0.9672880172729492, 'Val/mean precision': 0.962570309638977, 'Val/mean recall': 0.9720520973205566, 'Val/mean hd95_metric': 7.219206809997559} +Epoch [455/4000] Training [1/16] Loss: 0.01904 +Epoch [455/4000] Training [2/16] Loss: 0.01752 +Epoch [455/4000] Training [3/16] Loss: 0.01406 +Epoch [455/4000] Training [4/16] Loss: 0.01866 +Epoch [455/4000] Training [5/16] Loss: 0.01664 +Epoch [455/4000] Training [6/16] Loss: 0.01335 +Epoch [455/4000] Training [7/16] Loss: 0.02530 +Epoch [455/4000] Training [8/16] Loss: 0.01610 +Epoch [455/4000] Training [9/16] Loss: 0.01210 +Epoch [455/4000] Training [10/16] Loss: 0.01736 +Epoch [455/4000] Training [11/16] Loss: 0.01608 +Epoch [455/4000] Training [12/16] Loss: 0.01373 +Epoch [455/4000] Training [13/16] Loss: 0.01310 +Epoch [455/4000] Training [14/16] Loss: 0.01601 +Epoch [455/4000] Training [15/16] Loss: 0.01492 +Epoch [455/4000] Training [16/16] Loss: 0.01223 +Epoch [455/4000] Training metric {'Train/mean dice_metric': 0.9885472059249878, 'Train/mean miou_metric': 0.9772680997848511, 'Train/mean f1': 0.9861263632774353, 'Train/mean precision': 0.9818025231361389, 'Train/mean recall': 0.9904884696006775, 'Train/mean hd95_metric': 2.250342607498169} +Epoch [455/4000] Validation [1/4] Loss: 0.34514 focal_loss 0.22214 dice_loss 0.12300 +Epoch [455/4000] Validation [2/4] Loss: 0.23721 focal_loss 0.10045 dice_loss 0.13676 +Epoch [455/4000] Validation [3/4] Loss: 0.15376 focal_loss 0.07566 dice_loss 0.07810 +Epoch [455/4000] Validation [4/4] Loss: 0.18705 focal_loss 0.08391 dice_loss 0.10314 +Epoch [455/4000] Validation metric {'Val/mean dice_metric': 0.9650998115539551, 'Val/mean miou_metric': 0.9419258236885071, 'Val/mean f1': 0.9661654233932495, 'Val/mean precision': 0.9677147269248962, 'Val/mean recall': 0.9646210670471191, 'Val/mean hd95_metric': 6.459643363952637} +Cheakpoint... +Epoch [455/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650998115539551, 'Val/mean miou_metric': 0.9419258236885071, 'Val/mean f1': 0.9661654233932495, 'Val/mean precision': 0.9677147269248962, 'Val/mean recall': 0.9646210670471191, 'Val/mean hd95_metric': 6.459643363952637} +Epoch [456/4000] Training [1/16] Loss: 0.01639 +Epoch [456/4000] Training [2/16] Loss: 0.01586 +Epoch [456/4000] Training [3/16] Loss: 0.01404 +Epoch [456/4000] Training [4/16] Loss: 0.02652 +Epoch [456/4000] Training [5/16] Loss: 0.01762 +Epoch [456/4000] Training [6/16] Loss: 0.02321 +Epoch [456/4000] Training [7/16] Loss: 0.01888 +Epoch [456/4000] Training [8/16] Loss: 0.01435 +Epoch [456/4000] Training [9/16] Loss: 0.01172 +Epoch [456/4000] Training [10/16] Loss: 0.01529 +Epoch [456/4000] Training [11/16] Loss: 0.01565 +Epoch [456/4000] Training [12/16] Loss: 0.01439 +Epoch [456/4000] Training [13/16] Loss: 0.01695 +Epoch [456/4000] Training [14/16] Loss: 0.01075 +Epoch [456/4000] Training [15/16] Loss: 0.01191 +Epoch [456/4000] Training [16/16] Loss: 0.01542 +Epoch [456/4000] Training metric {'Train/mean dice_metric': 0.9890549778938293, 'Train/mean miou_metric': 0.9782012701034546, 'Train/mean f1': 0.9866649508476257, 'Train/mean precision': 0.9823192954063416, 'Train/mean recall': 0.9910491704940796, 'Train/mean hd95_metric': 1.3808962106704712} +Epoch [456/4000] Validation [1/4] Loss: 0.26294 focal_loss 0.16984 dice_loss 0.09310 +Epoch [456/4000] Validation [2/4] Loss: 0.18189 focal_loss 0.07159 dice_loss 0.11030 +Epoch [456/4000] Validation [3/4] Loss: 0.12538 focal_loss 0.06491 dice_loss 0.06047 +Epoch [456/4000] Validation [4/4] Loss: 0.22510 focal_loss 0.10760 dice_loss 0.11751 +Epoch [456/4000] Validation metric {'Val/mean dice_metric': 0.9666740298271179, 'Val/mean miou_metric': 0.9440361261367798, 'Val/mean f1': 0.9681633710861206, 'Val/mean precision': 0.9646688103675842, 'Val/mean recall': 0.9716833829879761, 'Val/mean hd95_metric': 6.460182189941406} +Cheakpoint... +Epoch [456/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666740298271179, 'Val/mean miou_metric': 0.9440361261367798, 'Val/mean f1': 0.9681633710861206, 'Val/mean precision': 0.9646688103675842, 'Val/mean recall': 0.9716833829879761, 'Val/mean hd95_metric': 6.460182189941406} +Epoch [457/4000] Training [1/16] Loss: 0.01000 +Epoch [457/4000] Training [2/16] Loss: 0.01637 +Epoch [457/4000] Training [3/16] Loss: 0.01668 +Epoch [457/4000] Training [4/16] Loss: 0.02122 +Epoch [457/4000] Training [5/16] Loss: 0.01740 +Epoch [457/4000] Training [6/16] Loss: 0.01382 +Epoch [457/4000] Training [7/16] Loss: 0.02023 +Epoch [457/4000] Training [8/16] Loss: 0.01157 +Epoch [457/4000] Training [9/16] Loss: 0.02136 +Epoch [457/4000] Training [10/16] Loss: 0.01500 +Epoch [457/4000] Training [11/16] Loss: 0.01570 +Epoch [457/4000] Training [12/16] Loss: 0.01516 +Epoch [457/4000] Training [13/16] Loss: 0.01323 +Epoch [457/4000] Training [14/16] Loss: 0.01957 +Epoch [457/4000] Training [15/16] Loss: 0.01521 +Epoch [457/4000] Training [16/16] Loss: 0.01979 +Epoch [457/4000] Training metric {'Train/mean dice_metric': 0.9894879460334778, 'Train/mean miou_metric': 0.9790160059928894, 'Train/mean f1': 0.9866878390312195, 'Train/mean precision': 0.9822399616241455, 'Train/mean recall': 0.9911761283874512, 'Train/mean hd95_metric': 1.7688195705413818} +Epoch [457/4000] Validation [1/4] Loss: 0.48906 focal_loss 0.34455 dice_loss 0.14452 +Epoch [457/4000] Validation [2/4] Loss: 0.27350 focal_loss 0.10465 dice_loss 0.16885 +Epoch [457/4000] Validation [3/4] Loss: 0.11434 focal_loss 0.05689 dice_loss 0.05745 +Epoch [457/4000] Validation [4/4] Loss: 0.22117 focal_loss 0.10315 dice_loss 0.11801 +Epoch [457/4000] Validation metric {'Val/mean dice_metric': 0.9647983312606812, 'Val/mean miou_metric': 0.9428116083145142, 'Val/mean f1': 0.967048704624176, 'Val/mean precision': 0.9674980044364929, 'Val/mean recall': 0.9665998816490173, 'Val/mean hd95_metric': 6.78133487701416} +Cheakpoint... +Epoch [457/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647983312606812, 'Val/mean miou_metric': 0.9428116083145142, 'Val/mean f1': 0.967048704624176, 'Val/mean precision': 0.9674980044364929, 'Val/mean recall': 0.9665998816490173, 'Val/mean hd95_metric': 6.78133487701416} +Epoch [458/4000] Training [1/16] Loss: 0.01454 +Epoch [458/4000] Training [2/16] Loss: 0.01365 +Epoch [458/4000] Training [3/16] Loss: 0.01250 +Epoch [458/4000] Training [4/16] Loss: 0.01977 +Epoch [458/4000] Training [5/16] Loss: 0.01279 +Epoch [458/4000] Training [6/16] Loss: 0.02012 +Epoch [458/4000] Training [7/16] Loss: 0.01552 +Epoch [458/4000] Training [8/16] Loss: 0.02037 +Epoch [458/4000] Training [9/16] Loss: 0.01521 +Epoch [458/4000] Training [10/16] Loss: 0.03467 +Epoch [458/4000] Training [11/16] Loss: 0.01734 +Epoch [458/4000] Training [12/16] Loss: 0.01416 +Epoch [458/4000] Training [13/16] Loss: 0.01422 +Epoch [458/4000] Training [14/16] Loss: 0.02320 +Epoch [458/4000] Training [15/16] Loss: 0.01640 +Epoch [458/4000] Training [16/16] Loss: 0.00994 +Epoch [458/4000] Training metric {'Train/mean dice_metric': 0.9889397621154785, 'Train/mean miou_metric': 0.9780218005180359, 'Train/mean f1': 0.9861479997634888, 'Train/mean precision': 0.9812157154083252, 'Train/mean recall': 0.9911301136016846, 'Train/mean hd95_metric': 1.4744359254837036} +Epoch [458/4000] Validation [1/4] Loss: 0.28958 focal_loss 0.18806 dice_loss 0.10152 +Epoch [458/4000] Validation [2/4] Loss: 0.26315 focal_loss 0.11136 dice_loss 0.15179 +Epoch [458/4000] Validation [3/4] Loss: 0.16589 focal_loss 0.08068 dice_loss 0.08521 +Epoch [458/4000] Validation [4/4] Loss: 0.24777 focal_loss 0.13092 dice_loss 0.11685 +Epoch [458/4000] Validation metric {'Val/mean dice_metric': 0.9638856649398804, 'Val/mean miou_metric': 0.9410645365715027, 'Val/mean f1': 0.9670900702476501, 'Val/mean precision': 0.965804934501648, 'Val/mean recall': 0.9683787822723389, 'Val/mean hd95_metric': 6.940733909606934} +Cheakpoint... +Epoch [458/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9638856649398804, 'Val/mean miou_metric': 0.9410645365715027, 'Val/mean f1': 0.9670900702476501, 'Val/mean precision': 0.965804934501648, 'Val/mean recall': 0.9683787822723389, 'Val/mean hd95_metric': 6.940733909606934} +Epoch [459/4000] Training [1/16] Loss: 0.01382 +Epoch [459/4000] Training [2/16] Loss: 0.01560 +Epoch [459/4000] Training [3/16] Loss: 0.01115 +Epoch [459/4000] Training [4/16] Loss: 0.01065 +Epoch [459/4000] Training [5/16] Loss: 0.01328 +Epoch [459/4000] Training [6/16] Loss: 0.01346 +Epoch [459/4000] Training [7/16] Loss: 0.01187 +Epoch [459/4000] Training [8/16] Loss: 0.02486 +Epoch [459/4000] Training [9/16] Loss: 0.01471 +Epoch [459/4000] Training [10/16] Loss: 0.01345 +Epoch [459/4000] Training [11/16] Loss: 0.01452 +Epoch [459/4000] Training [12/16] Loss: 0.01858 +Epoch [459/4000] Training [13/16] Loss: 0.01263 +Epoch [459/4000] Training [14/16] Loss: 0.01473 +Epoch [459/4000] Training [15/16] Loss: 0.01287 +Epoch [459/4000] Training [16/16] Loss: 0.01883 +Epoch [459/4000] Training metric {'Train/mean dice_metric': 0.9894859790802002, 'Train/mean miou_metric': 0.9790275692939758, 'Train/mean f1': 0.9866806864738464, 'Train/mean precision': 0.9822636246681213, 'Train/mean recall': 0.9911376237869263, 'Train/mean hd95_metric': 1.3350231647491455} +Epoch [459/4000] Validation [1/4] Loss: 0.25966 focal_loss 0.17476 dice_loss 0.08490 +Epoch [459/4000] Validation [2/4] Loss: 0.30653 focal_loss 0.14749 dice_loss 0.15905 +Epoch [459/4000] Validation [3/4] Loss: 0.14970 focal_loss 0.06545 dice_loss 0.08425 +Epoch [459/4000] Validation [4/4] Loss: 0.26761 focal_loss 0.14507 dice_loss 0.12254 +Epoch [459/4000] Validation metric {'Val/mean dice_metric': 0.9660198092460632, 'Val/mean miou_metric': 0.944235622882843, 'Val/mean f1': 0.9696924090385437, 'Val/mean precision': 0.9656457304954529, 'Val/mean recall': 0.9737730622291565, 'Val/mean hd95_metric': 6.709639072418213} +Cheakpoint... +Epoch [459/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660198092460632, 'Val/mean miou_metric': 0.944235622882843, 'Val/mean f1': 0.9696924090385437, 'Val/mean precision': 0.9656457304954529, 'Val/mean recall': 0.9737730622291565, 'Val/mean hd95_metric': 6.709639072418213} +Epoch [460/4000] Training [1/16] Loss: 0.01609 +Epoch [460/4000] Training [2/16] Loss: 0.01991 +Epoch [460/4000] Training [3/16] Loss: 0.01272 +Epoch [460/4000] Training [4/16] Loss: 0.01385 +Epoch [460/4000] Training [5/16] Loss: 0.01415 +Epoch [460/4000] Training [6/16] Loss: 0.01655 +Epoch [460/4000] Training [7/16] Loss: 0.02314 +Epoch [460/4000] Training [8/16] Loss: 0.02259 +Epoch [460/4000] Training [9/16] Loss: 0.01414 +Epoch [460/4000] Training [10/16] Loss: 0.01566 +Epoch [460/4000] Training [11/16] Loss: 0.02032 +Epoch [460/4000] Training [12/16] Loss: 0.01227 +Epoch [460/4000] Training [13/16] Loss: 0.01581 +Epoch [460/4000] Training [14/16] Loss: 0.02183 +Epoch [460/4000] Training [15/16] Loss: 0.01223 +Epoch [460/4000] Training [16/16] Loss: 0.01581 +Epoch [460/4000] Training metric {'Train/mean dice_metric': 0.9864157438278198, 'Train/mean miou_metric': 0.9750072360038757, 'Train/mean f1': 0.984999418258667, 'Train/mean precision': 0.9798815250396729, 'Train/mean recall': 0.9901710152626038, 'Train/mean hd95_metric': 1.9126522541046143} +Epoch [460/4000] Validation [1/4] Loss: 0.58364 focal_loss 0.43061 dice_loss 0.15303 +Epoch [460/4000] Validation [2/4] Loss: 0.18657 focal_loss 0.08432 dice_loss 0.10225 +Epoch [460/4000] Validation [3/4] Loss: 0.14863 focal_loss 0.07665 dice_loss 0.07199 +Epoch [460/4000] Validation [4/4] Loss: 0.34708 focal_loss 0.19531 dice_loss 0.15176 +Epoch [460/4000] Validation metric {'Val/mean dice_metric': 0.9603933095932007, 'Val/mean miou_metric': 0.9370070695877075, 'Val/mean f1': 0.9637601375579834, 'Val/mean precision': 0.9665796160697937, 'Val/mean recall': 0.960956871509552, 'Val/mean hd95_metric': 6.8824143409729} +Cheakpoint... +Epoch [460/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9604], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9603933095932007, 'Val/mean miou_metric': 0.9370070695877075, 'Val/mean f1': 0.9637601375579834, 'Val/mean precision': 0.9665796160697937, 'Val/mean recall': 0.960956871509552, 'Val/mean hd95_metric': 6.8824143409729} +Epoch [461/4000] Training [1/16] Loss: 0.01336 +Epoch [461/4000] Training [2/16] Loss: 0.01194 +Epoch [461/4000] Training [3/16] Loss: 0.01470 +Epoch [461/4000] Training [4/16] Loss: 0.01676 +Epoch [461/4000] Training [5/16] Loss: 0.01229 +Epoch [461/4000] Training [6/16] Loss: 0.01302 +Epoch [461/4000] Training [7/16] Loss: 0.01454 +Epoch [461/4000] Training [8/16] Loss: 0.01634 +Epoch [461/4000] Training [9/16] Loss: 0.01306 +Epoch [461/4000] Training [10/16] Loss: 0.02162 +Epoch [461/4000] Training [11/16] Loss: 0.02480 +Epoch [461/4000] Training [12/16] Loss: 0.01330 +Epoch [461/4000] Training [13/16] Loss: 0.02019 +Epoch [461/4000] Training [14/16] Loss: 0.02620 +Epoch [461/4000] Training [15/16] Loss: 0.01396 +Epoch [461/4000] Training [16/16] Loss: 0.01795 +Epoch [461/4000] Training metric {'Train/mean dice_metric': 0.9882041215896606, 'Train/mean miou_metric': 0.9765818119049072, 'Train/mean f1': 0.985460638999939, 'Train/mean precision': 0.9812228679656982, 'Train/mean recall': 0.9897352457046509, 'Train/mean hd95_metric': 1.9569997787475586} +Epoch [461/4000] Validation [1/4] Loss: 0.47679 focal_loss 0.35250 dice_loss 0.12428 +Epoch [461/4000] Validation [2/4] Loss: 0.27875 focal_loss 0.11138 dice_loss 0.16736 +Epoch [461/4000] Validation [3/4] Loss: 0.11163 focal_loss 0.05781 dice_loss 0.05382 +Epoch [461/4000] Validation [4/4] Loss: 0.20530 focal_loss 0.09960 dice_loss 0.10570 +Epoch [461/4000] Validation metric {'Val/mean dice_metric': 0.9636180996894836, 'Val/mean miou_metric': 0.9413241147994995, 'Val/mean f1': 0.9681345820426941, 'Val/mean precision': 0.9666461944580078, 'Val/mean recall': 0.9696276187896729, 'Val/mean hd95_metric': 6.4203925132751465} +Cheakpoint... +Epoch [461/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636180996894836, 'Val/mean miou_metric': 0.9413241147994995, 'Val/mean f1': 0.9681345820426941, 'Val/mean precision': 0.9666461944580078, 'Val/mean recall': 0.9696276187896729, 'Val/mean hd95_metric': 6.4203925132751465} +Epoch [462/4000] Training [1/16] Loss: 0.01641 +Epoch [462/4000] Training [2/16] Loss: 0.01479 +Epoch [462/4000] Training [3/16] Loss: 0.01694 +Epoch [462/4000] Training [4/16] Loss: 0.01961 +Epoch [462/4000] Training [5/16] Loss: 0.01259 +Epoch [462/4000] Training [6/16] Loss: 0.01675 +Epoch [462/4000] Training [7/16] Loss: 0.01505 +Epoch [462/4000] Training [8/16] Loss: 0.01252 +Epoch [462/4000] Training [9/16] Loss: 0.01380 +Epoch [462/4000] Training [10/16] Loss: 0.01574 +Epoch [462/4000] Training [11/16] Loss: 0.02026 +Epoch [462/4000] Training [12/16] Loss: 0.01272 +Epoch [462/4000] Training [13/16] Loss: 0.01895 +Epoch [462/4000] Training [14/16] Loss: 0.01908 +Epoch [462/4000] Training [15/16] Loss: 0.01393 +Epoch [462/4000] Training [16/16] Loss: 0.01445 +Epoch [462/4000] Training metric {'Train/mean dice_metric': 0.9886279702186584, 'Train/mean miou_metric': 0.9774793386459351, 'Train/mean f1': 0.9864230751991272, 'Train/mean precision': 0.9818986058235168, 'Train/mean recall': 0.9909894466400146, 'Train/mean hd95_metric': 1.6777664422988892} +Epoch [462/4000] Validation [1/4] Loss: 0.13091 focal_loss 0.07728 dice_loss 0.05362 +Epoch [462/4000] Validation [2/4] Loss: 0.23348 focal_loss 0.07747 dice_loss 0.15601 +Epoch [462/4000] Validation [3/4] Loss: 0.12782 focal_loss 0.06108 dice_loss 0.06674 +Epoch [462/4000] Validation [4/4] Loss: 0.27999 focal_loss 0.15267 dice_loss 0.12732 +Epoch [462/4000] Validation metric {'Val/mean dice_metric': 0.964398205280304, 'Val/mean miou_metric': 0.941675066947937, 'Val/mean f1': 0.9683040976524353, 'Val/mean precision': 0.9691282510757446, 'Val/mean recall': 0.9674814939498901, 'Val/mean hd95_metric': 5.982141017913818} +Cheakpoint... +Epoch [462/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964398205280304, 'Val/mean miou_metric': 0.941675066947937, 'Val/mean f1': 0.9683040976524353, 'Val/mean precision': 0.9691282510757446, 'Val/mean recall': 0.9674814939498901, 'Val/mean hd95_metric': 5.982141017913818} +Epoch [463/4000] Training [1/16] Loss: 0.01839 +Epoch [463/4000] Training [2/16] Loss: 0.01492 +Epoch [463/4000] Training [3/16] Loss: 0.01159 +Epoch [463/4000] Training [4/16] Loss: 0.01533 +Epoch [463/4000] Training [5/16] Loss: 0.01590 +Epoch [463/4000] Training [6/16] Loss: 0.01416 +Epoch [463/4000] Training [7/16] Loss: 0.01364 +Epoch [463/4000] Training [8/16] Loss: 0.01264 +Epoch [463/4000] Training [9/16] Loss: 0.01866 +Epoch [463/4000] Training [10/16] Loss: 0.01872 +Epoch [463/4000] Training [11/16] Loss: 0.01199 +Epoch [463/4000] Training [12/16] Loss: 0.01840 +Epoch [463/4000] Training [13/16] Loss: 0.01530 +Epoch [463/4000] Training [14/16] Loss: 0.01252 +Epoch [463/4000] Training [15/16] Loss: 0.01444 +Epoch [463/4000] Training [16/16] Loss: 0.01486 +Epoch [463/4000] Training metric {'Train/mean dice_metric': 0.9890087842941284, 'Train/mean miou_metric': 0.9781743288040161, 'Train/mean f1': 0.986629843711853, 'Train/mean precision': 0.9820630550384521, 'Train/mean recall': 0.9912393093109131, 'Train/mean hd95_metric': 1.404657006263733} +Epoch [463/4000] Validation [1/4] Loss: 0.84238 focal_loss 0.68960 dice_loss 0.15278 +Epoch [463/4000] Validation [2/4] Loss: 0.27871 focal_loss 0.12991 dice_loss 0.14880 +Epoch [463/4000] Validation [3/4] Loss: 0.11942 focal_loss 0.05526 dice_loss 0.06416 +Epoch [463/4000] Validation [4/4] Loss: 0.26424 focal_loss 0.14083 dice_loss 0.12342 +Epoch [463/4000] Validation metric {'Val/mean dice_metric': 0.9643640518188477, 'Val/mean miou_metric': 0.9420997500419617, 'Val/mean f1': 0.9665389657020569, 'Val/mean precision': 0.9658429622650146, 'Val/mean recall': 0.9672359824180603, 'Val/mean hd95_metric': 6.704493522644043} +Cheakpoint... +Epoch [463/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9643640518188477, 'Val/mean miou_metric': 0.9420997500419617, 'Val/mean f1': 0.9665389657020569, 'Val/mean precision': 0.9658429622650146, 'Val/mean recall': 0.9672359824180603, 'Val/mean hd95_metric': 6.704493522644043} +Epoch [464/4000] Training [1/16] Loss: 0.01622 +Epoch [464/4000] Training [2/16] Loss: 0.01745 +Epoch [464/4000] Training [3/16] Loss: 0.01395 +Epoch [464/4000] Training [4/16] Loss: 0.01583 +Epoch [464/4000] Training [5/16] Loss: 0.01381 +Epoch [464/4000] Training [6/16] Loss: 0.01595 +Epoch [464/4000] Training [7/16] Loss: 0.01362 +Epoch [464/4000] Training [8/16] Loss: 0.01905 +Epoch [464/4000] Training [9/16] Loss: 0.01991 +Epoch [464/4000] Training [10/16] Loss: 0.01553 +Epoch [464/4000] Training [11/16] Loss: 0.02296 +Epoch [464/4000] Training [12/16] Loss: 0.01504 +Epoch [464/4000] Training [13/16] Loss: 0.01236 +Epoch [464/4000] Training [14/16] Loss: 0.01365 +Epoch [464/4000] Training [15/16] Loss: 0.01603 +Epoch [464/4000] Training [16/16] Loss: 0.01423 +Epoch [464/4000] Training metric {'Train/mean dice_metric': 0.9888837933540344, 'Train/mean miou_metric': 0.9778329133987427, 'Train/mean f1': 0.9863191843032837, 'Train/mean precision': 0.9816041588783264, 'Train/mean recall': 0.9910797476768494, 'Train/mean hd95_metric': 1.3492584228515625} +Epoch [464/4000] Validation [1/4] Loss: 0.50635 focal_loss 0.37784 dice_loss 0.12851 +Epoch [464/4000] Validation [2/4] Loss: 0.17518 focal_loss 0.05659 dice_loss 0.11859 +Epoch [464/4000] Validation [3/4] Loss: 0.11687 focal_loss 0.05635 dice_loss 0.06053 +Epoch [464/4000] Validation [4/4] Loss: 0.21341 focal_loss 0.10210 dice_loss 0.11131 +Epoch [464/4000] Validation metric {'Val/mean dice_metric': 0.9657164812088013, 'Val/mean miou_metric': 0.9435172080993652, 'Val/mean f1': 0.9692779779434204, 'Val/mean precision': 0.9664327502250671, 'Val/mean recall': 0.972139835357666, 'Val/mean hd95_metric': 6.56341552734375} +Cheakpoint... +Epoch [464/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9657], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9657164812088013, 'Val/mean miou_metric': 0.9435172080993652, 'Val/mean f1': 0.9692779779434204, 'Val/mean precision': 0.9664327502250671, 'Val/mean recall': 0.972139835357666, 'Val/mean hd95_metric': 6.56341552734375} +Epoch [465/4000] Training [1/16] Loss: 0.02721 +Epoch [465/4000] Training [2/16] Loss: 0.01278 +Epoch [465/4000] Training [3/16] Loss: 0.01470 +Epoch [465/4000] Training [4/16] Loss: 0.01455 +Epoch [465/4000] Training [5/16] Loss: 0.01714 +Epoch [465/4000] Training [6/16] Loss: 0.01188 +Epoch [465/4000] Training [7/16] Loss: 0.01061 +Epoch [465/4000] Training [8/16] Loss: 0.02285 +Epoch [465/4000] Training [9/16] Loss: 0.02704 +Epoch [465/4000] Training [10/16] Loss: 0.02286 +Epoch [465/4000] Training [11/16] Loss: 0.01452 +Epoch [465/4000] Training [12/16] Loss: 0.01809 +Epoch [465/4000] Training [13/16] Loss: 0.01952 +Epoch [465/4000] Training [14/16] Loss: 0.01574 +Epoch [465/4000] Training [15/16] Loss: 0.01338 +Epoch [465/4000] Training [16/16] Loss: 0.01495 +Epoch [465/4000] Training metric {'Train/mean dice_metric': 0.9866800308227539, 'Train/mean miou_metric': 0.974674642086029, 'Train/mean f1': 0.9847762584686279, 'Train/mean precision': 0.9792963266372681, 'Train/mean recall': 0.9903178215026855, 'Train/mean hd95_metric': 1.7258944511413574} +Epoch [465/4000] Validation [1/4] Loss: 0.15618 focal_loss 0.09468 dice_loss 0.06150 +Epoch [465/4000] Validation [2/4] Loss: 0.15626 focal_loss 0.06212 dice_loss 0.09414 +Epoch [465/4000] Validation [3/4] Loss: 0.16014 focal_loss 0.08331 dice_loss 0.07683 +Epoch [465/4000] Validation [4/4] Loss: 0.28722 focal_loss 0.15072 dice_loss 0.13650 +Epoch [465/4000] Validation metric {'Val/mean dice_metric': 0.9612325429916382, 'Val/mean miou_metric': 0.9381622076034546, 'Val/mean f1': 0.9665752053260803, 'Val/mean precision': 0.960114061832428, 'Val/mean recall': 0.9731239080429077, 'Val/mean hd95_metric': 7.441288948059082} +Cheakpoint... +Epoch [465/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612325429916382, 'Val/mean miou_metric': 0.9381622076034546, 'Val/mean f1': 0.9665752053260803, 'Val/mean precision': 0.960114061832428, 'Val/mean recall': 0.9731239080429077, 'Val/mean hd95_metric': 7.441288948059082} +Epoch [466/4000] Training [1/16] Loss: 0.01497 +Epoch [466/4000] Training [2/16] Loss: 0.01700 +Epoch [466/4000] Training [3/16] Loss: 0.01269 +Epoch [466/4000] Training [4/16] Loss: 0.02230 +Epoch [466/4000] Training [5/16] Loss: 0.02703 +Epoch [466/4000] Training [6/16] Loss: 0.01997 +Epoch [466/4000] Training [7/16] Loss: 0.01408 +Epoch [466/4000] Training [8/16] Loss: 0.01608 +Epoch [466/4000] Training [9/16] Loss: 0.01598 +Epoch [466/4000] Training [10/16] Loss: 0.01727 +Epoch [466/4000] Training [11/16] Loss: 0.04661 +Epoch [466/4000] Training [12/16] Loss: 0.01642 +Epoch [466/4000] Training [13/16] Loss: 0.01348 +Epoch [466/4000] Training [14/16] Loss: 0.01699 +Epoch [466/4000] Training [15/16] Loss: 0.01579 +Epoch [466/4000] Training [16/16] Loss: 0.02180 +Epoch [466/4000] Training metric {'Train/mean dice_metric': 0.98750901222229, 'Train/mean miou_metric': 0.9753777980804443, 'Train/mean f1': 0.9850369691848755, 'Train/mean precision': 0.9799792766571045, 'Train/mean recall': 0.9901471734046936, 'Train/mean hd95_metric': 1.8535709381103516} +Epoch [466/4000] Validation [1/4] Loss: 0.18379 focal_loss 0.11219 dice_loss 0.07159 +Epoch [466/4000] Validation [2/4] Loss: 0.53876 focal_loss 0.23153 dice_loss 0.30723 +Epoch [466/4000] Validation [3/4] Loss: 0.16613 focal_loss 0.07371 dice_loss 0.09242 +Epoch [466/4000] Validation [4/4] Loss: 0.26067 focal_loss 0.13185 dice_loss 0.12882 +Epoch [466/4000] Validation metric {'Val/mean dice_metric': 0.96210116147995, 'Val/mean miou_metric': 0.9393825531005859, 'Val/mean f1': 0.9661826491355896, 'Val/mean precision': 0.9638146162033081, 'Val/mean recall': 0.9685623049736023, 'Val/mean hd95_metric': 7.011346340179443} +Cheakpoint... +Epoch [466/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9621], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96210116147995, 'Val/mean miou_metric': 0.9393825531005859, 'Val/mean f1': 0.9661826491355896, 'Val/mean precision': 0.9638146162033081, 'Val/mean recall': 0.9685623049736023, 'Val/mean hd95_metric': 7.011346340179443} +Epoch [467/4000] Training [1/16] Loss: 0.01389 +Epoch [467/4000] Training [2/16] Loss: 0.01782 +Epoch [467/4000] Training [3/16] Loss: 0.01884 +Epoch [467/4000] Training [4/16] Loss: 0.02082 +Epoch [467/4000] Training [5/16] Loss: 0.01546 +Epoch [467/4000] Training [6/16] Loss: 0.01371 +Epoch [467/4000] Training [7/16] Loss: 0.01356 +Epoch [467/4000] Training [8/16] Loss: 0.01650 +Epoch [467/4000] Training [9/16] Loss: 0.01328 +Epoch [467/4000] Training [10/16] Loss: 0.02024 +Epoch [467/4000] Training [11/16] Loss: 0.01302 +Epoch [467/4000] Training [12/16] Loss: 0.01399 +Epoch [467/4000] Training [13/16] Loss: 0.01397 +Epoch [467/4000] Training [14/16] Loss: 0.01762 +Epoch [467/4000] Training [15/16] Loss: 0.01436 +Epoch [467/4000] Training [16/16] Loss: 0.01326 +Epoch [467/4000] Training metric {'Train/mean dice_metric': 0.9885257482528687, 'Train/mean miou_metric': 0.9776943325996399, 'Train/mean f1': 0.9862149953842163, 'Train/mean precision': 0.981209933757782, 'Train/mean recall': 0.9912713766098022, 'Train/mean hd95_metric': 1.7690201997756958} +Epoch [467/4000] Validation [1/4] Loss: 0.23721 focal_loss 0.14350 dice_loss 0.09371 +Epoch [467/4000] Validation [2/4] Loss: 0.22725 focal_loss 0.08585 dice_loss 0.14140 +Epoch [467/4000] Validation [3/4] Loss: 0.10427 focal_loss 0.04590 dice_loss 0.05837 +Epoch [467/4000] Validation [4/4] Loss: 0.26047 focal_loss 0.13185 dice_loss 0.12862 +Epoch [467/4000] Validation metric {'Val/mean dice_metric': 0.9669777154922485, 'Val/mean miou_metric': 0.9444721937179565, 'Val/mean f1': 0.967682421207428, 'Val/mean precision': 0.962920069694519, 'Val/mean recall': 0.9724920392036438, 'Val/mean hd95_metric': 6.820652961730957} +Cheakpoint... +Epoch [467/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669777154922485, 'Val/mean miou_metric': 0.9444721937179565, 'Val/mean f1': 0.967682421207428, 'Val/mean precision': 0.962920069694519, 'Val/mean recall': 0.9724920392036438, 'Val/mean hd95_metric': 6.820652961730957} +Epoch [468/4000] Training [1/16] Loss: 0.02457 +Epoch [468/4000] Training [2/16] Loss: 0.01274 +Epoch [468/4000] Training [3/16] Loss: 0.01413 +Epoch [468/4000] Training [4/16] Loss: 0.01309 +Epoch [468/4000] Training [5/16] Loss: 0.01362 +Epoch [468/4000] Training [6/16] Loss: 0.01264 +Epoch [468/4000] Training [7/16] Loss: 0.01166 +Epoch [468/4000] Training [8/16] Loss: 0.01882 +Epoch [468/4000] Training [9/16] Loss: 0.01254 +Epoch [468/4000] Training [10/16] Loss: 0.01453 +Epoch [468/4000] Training [11/16] Loss: 0.01338 +Epoch [468/4000] Training [12/16] Loss: 0.01423 +Epoch [468/4000] Training [13/16] Loss: 0.01506 +Epoch [468/4000] Training [14/16] Loss: 0.01572 +Epoch [468/4000] Training [15/16] Loss: 0.01508 +Epoch [468/4000] Training [16/16] Loss: 0.01658 +Epoch [468/4000] Training metric {'Train/mean dice_metric': 0.9890987873077393, 'Train/mean miou_metric': 0.9783749580383301, 'Train/mean f1': 0.9865275025367737, 'Train/mean precision': 0.982171893119812, 'Train/mean recall': 0.9909219145774841, 'Train/mean hd95_metric': 1.5191761255264282} +Epoch [468/4000] Validation [1/4] Loss: 0.16052 focal_loss 0.09847 dice_loss 0.06205 +Epoch [468/4000] Validation [2/4] Loss: 0.31522 focal_loss 0.13239 dice_loss 0.18284 +Epoch [468/4000] Validation [3/4] Loss: 0.11006 focal_loss 0.05308 dice_loss 0.05698 +Epoch [468/4000] Validation [4/4] Loss: 0.19502 focal_loss 0.09411 dice_loss 0.10091 +Epoch [468/4000] Validation metric {'Val/mean dice_metric': 0.964451014995575, 'Val/mean miou_metric': 0.9429807662963867, 'Val/mean f1': 0.9690635204315186, 'Val/mean precision': 0.9689025282859802, 'Val/mean recall': 0.9692245125770569, 'Val/mean hd95_metric': 5.919523239135742} +Cheakpoint... +Epoch [468/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964451014995575, 'Val/mean miou_metric': 0.9429807662963867, 'Val/mean f1': 0.9690635204315186, 'Val/mean precision': 0.9689025282859802, 'Val/mean recall': 0.9692245125770569, 'Val/mean hd95_metric': 5.919523239135742} +Epoch [469/4000] Training [1/16] Loss: 0.02023 +Epoch [469/4000] Training [2/16] Loss: 0.01161 +Epoch [469/4000] Training [3/16] Loss: 0.01000 +Epoch [469/4000] Training [4/16] Loss: 0.01150 +Epoch [469/4000] Training [5/16] Loss: 0.01166 +Epoch [469/4000] Training [6/16] Loss: 0.02031 +Epoch [469/4000] Training [7/16] Loss: 0.01687 +Epoch [469/4000] Training [8/16] Loss: 0.01243 +Epoch [469/4000] Training [9/16] Loss: 0.01265 +Epoch [469/4000] Training [10/16] Loss: 0.01104 +Epoch [469/4000] Training [11/16] Loss: 0.01482 +Epoch [469/4000] Training [12/16] Loss: 0.01265 +Epoch [469/4000] Training [13/16] Loss: 0.01441 +Epoch [469/4000] Training [14/16] Loss: 0.01912 +Epoch [469/4000] Training [15/16] Loss: 0.01560 +Epoch [469/4000] Training [16/16] Loss: 0.01347 +Epoch [469/4000] Training metric {'Train/mean dice_metric': 0.9896421432495117, 'Train/mean miou_metric': 0.9793797135353088, 'Train/mean f1': 0.9870734214782715, 'Train/mean precision': 0.982262372970581, 'Train/mean recall': 0.9919318556785583, 'Train/mean hd95_metric': 1.3303802013397217} +Epoch [469/4000] Validation [1/4] Loss: 0.38322 focal_loss 0.26352 dice_loss 0.11971 +Epoch [469/4000] Validation [2/4] Loss: 0.45630 focal_loss 0.22065 dice_loss 0.23565 +Epoch [469/4000] Validation [3/4] Loss: 0.10926 focal_loss 0.05274 dice_loss 0.05653 +Epoch [469/4000] Validation [4/4] Loss: 0.34120 focal_loss 0.17830 dice_loss 0.16290 +Epoch [469/4000] Validation metric {'Val/mean dice_metric': 0.9646471738815308, 'Val/mean miou_metric': 0.9430091977119446, 'Val/mean f1': 0.9674848318099976, 'Val/mean precision': 0.9685986638069153, 'Val/mean recall': 0.9663735628128052, 'Val/mean hd95_metric': 5.6024627685546875} +Cheakpoint... +Epoch [469/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9646], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646471738815308, 'Val/mean miou_metric': 0.9430091977119446, 'Val/mean f1': 0.9674848318099976, 'Val/mean precision': 0.9685986638069153, 'Val/mean recall': 0.9663735628128052, 'Val/mean hd95_metric': 5.6024627685546875} +Epoch [470/4000] Training [1/16] Loss: 0.01642 +Epoch [470/4000] Training [2/16] Loss: 0.01790 +Epoch [470/4000] Training [3/16] Loss: 0.01370 +Epoch [470/4000] Training [4/16] Loss: 0.01222 +Epoch [470/4000] Training [5/16] Loss: 0.01729 +Epoch [470/4000] Training [6/16] Loss: 0.02569 +Epoch [470/4000] Training [7/16] Loss: 0.01432 +Epoch [470/4000] Training [8/16] Loss: 0.01452 +Epoch [470/4000] Training [9/16] Loss: 0.01337 +Epoch [470/4000] Training [10/16] Loss: 0.02752 +Epoch [470/4000] Training [11/16] Loss: 0.01430 +Epoch [470/4000] Training [12/16] Loss: 0.01869 +Epoch [470/4000] Training [13/16] Loss: 0.01818 +Epoch [470/4000] Training [14/16] Loss: 0.01954 +Epoch [470/4000] Training [15/16] Loss: 0.02031 +Epoch [470/4000] Training [16/16] Loss: 0.01229 +Epoch [470/4000] Training metric {'Train/mean dice_metric': 0.9879583120346069, 'Train/mean miou_metric': 0.9762486815452576, 'Train/mean f1': 0.9855555891990662, 'Train/mean precision': 0.9811562299728394, 'Train/mean recall': 0.9899945259094238, 'Train/mean hd95_metric': 1.5890085697174072} +Epoch [470/4000] Validation [1/4] Loss: 0.16113 focal_loss 0.10168 dice_loss 0.05945 +Epoch [470/4000] Validation [2/4] Loss: 0.26746 focal_loss 0.10729 dice_loss 0.16017 +Epoch [470/4000] Validation [3/4] Loss: 0.11771 focal_loss 0.05238 dice_loss 0.06534 +Epoch [470/4000] Validation [4/4] Loss: 0.25968 focal_loss 0.12639 dice_loss 0.13329 +Epoch [470/4000] Validation metric {'Val/mean dice_metric': 0.962657630443573, 'Val/mean miou_metric': 0.9401533007621765, 'Val/mean f1': 0.9670209288597107, 'Val/mean precision': 0.9601219296455383, 'Val/mean recall': 0.9740198254585266, 'Val/mean hd95_metric': 6.988597393035889} +Cheakpoint... +Epoch [470/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9627], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.962657630443573, 'Val/mean miou_metric': 0.9401533007621765, 'Val/mean f1': 0.9670209288597107, 'Val/mean precision': 0.9601219296455383, 'Val/mean recall': 0.9740198254585266, 'Val/mean hd95_metric': 6.988597393035889} +Epoch [471/4000] Training [1/16] Loss: 0.01587 +Epoch [471/4000] Training [2/16] Loss: 0.01550 +Epoch [471/4000] Training [3/16] Loss: 0.01860 +Epoch [471/4000] Training [4/16] Loss: 0.01882 +Epoch [471/4000] Training [5/16] Loss: 0.01483 +Epoch [471/4000] Training [6/16] Loss: 0.01836 +Epoch [471/4000] Training [7/16] Loss: 0.01453 +Epoch [471/4000] Training [8/16] Loss: 0.02137 +Epoch [471/4000] Training [9/16] Loss: 0.01420 +Epoch [471/4000] Training [10/16] Loss: 0.01275 +Epoch [471/4000] Training [11/16] Loss: 0.01906 +Epoch [471/4000] Training [12/16] Loss: 0.01437 +Epoch [471/4000] Training [13/16] Loss: 0.01772 +Epoch [471/4000] Training [14/16] Loss: 0.01516 +Epoch [471/4000] Training [15/16] Loss: 0.01421 +Epoch [471/4000] Training [16/16] Loss: 0.01374 +Epoch [471/4000] Training metric {'Train/mean dice_metric': 0.988884449005127, 'Train/mean miou_metric': 0.9778549671173096, 'Train/mean f1': 0.9862115979194641, 'Train/mean precision': 0.9815863370895386, 'Train/mean recall': 0.9908806085586548, 'Train/mean hd95_metric': 1.4066283702850342} +Epoch [471/4000] Validation [1/4] Loss: 0.15262 focal_loss 0.09390 dice_loss 0.05872 +Epoch [471/4000] Validation [2/4] Loss: 0.37723 focal_loss 0.18616 dice_loss 0.19107 +Epoch [471/4000] Validation [3/4] Loss: 0.12291 focal_loss 0.05684 dice_loss 0.06607 +Epoch [471/4000] Validation [4/4] Loss: 0.22163 focal_loss 0.11008 dice_loss 0.11155 +Epoch [471/4000] Validation metric {'Val/mean dice_metric': 0.963215708732605, 'Val/mean miou_metric': 0.9413010478019714, 'Val/mean f1': 0.9685029983520508, 'Val/mean precision': 0.9631040692329407, 'Val/mean recall': 0.9739627838134766, 'Val/mean hd95_metric': 6.835237979888916} +Cheakpoint... +Epoch [471/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963215708732605, 'Val/mean miou_metric': 0.9413010478019714, 'Val/mean f1': 0.9685029983520508, 'Val/mean precision': 0.9631040692329407, 'Val/mean recall': 0.9739627838134766, 'Val/mean hd95_metric': 6.835237979888916} +Epoch [472/4000] Training [1/16] Loss: 0.01232 +Epoch [472/4000] Training [2/16] Loss: 0.01344 +Epoch [472/4000] Training [3/16] Loss: 0.01548 +Epoch [472/4000] Training [4/16] Loss: 0.01384 +Epoch [472/4000] Training [5/16] Loss: 0.02125 +Epoch [472/4000] Training [6/16] Loss: 0.04253 +Epoch [472/4000] Training [7/16] Loss: 0.01237 +Epoch [472/4000] Training [8/16] Loss: 0.01699 +Epoch [472/4000] Training [9/16] Loss: 0.01218 +Epoch [472/4000] Training [10/16] Loss: 0.01596 +Epoch [472/4000] Training [11/16] Loss: 0.01549 +Epoch [472/4000] Training [12/16] Loss: 0.01426 +Epoch [472/4000] Training [13/16] Loss: 0.01390 +Epoch [472/4000] Training [14/16] Loss: 0.01474 +Epoch [472/4000] Training [15/16] Loss: 0.01553 +Epoch [472/4000] Training [16/16] Loss: 0.01836 +Epoch [472/4000] Training metric {'Train/mean dice_metric': 0.9890931844711304, 'Train/mean miou_metric': 0.9783360958099365, 'Train/mean f1': 0.9862068295478821, 'Train/mean precision': 0.9816318154335022, 'Train/mean recall': 0.9908246994018555, 'Train/mean hd95_metric': 1.5735242366790771} +Epoch [472/4000] Validation [1/4] Loss: 0.48320 focal_loss 0.35527 dice_loss 0.12793 +Epoch [472/4000] Validation [2/4] Loss: 0.58994 focal_loss 0.34401 dice_loss 0.24593 +Epoch [472/4000] Validation [3/4] Loss: 0.10603 focal_loss 0.04783 dice_loss 0.05820 +Epoch [472/4000] Validation [4/4] Loss: 0.27825 focal_loss 0.14682 dice_loss 0.13143 +Epoch [472/4000] Validation metric {'Val/mean dice_metric': 0.9608190655708313, 'Val/mean miou_metric': 0.9394539594650269, 'Val/mean f1': 0.9660872220993042, 'Val/mean precision': 0.9668827652931213, 'Val/mean recall': 0.9652930498123169, 'Val/mean hd95_metric': 6.178836345672607} +Cheakpoint... +Epoch [472/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608190655708313, 'Val/mean miou_metric': 0.9394539594650269, 'Val/mean f1': 0.9660872220993042, 'Val/mean precision': 0.9668827652931213, 'Val/mean recall': 0.9652930498123169, 'Val/mean hd95_metric': 6.178836345672607} +Epoch [473/4000] Training [1/16] Loss: 0.01298 +Epoch [473/4000] Training [2/16] Loss: 0.01102 +Epoch [473/4000] Training [3/16] Loss: 0.01779 +Epoch [473/4000] Training [4/16] Loss: 0.01572 +Epoch [473/4000] Training [5/16] Loss: 0.02390 +Epoch [473/4000] Training [6/16] Loss: 0.01577 +Epoch [473/4000] Training [7/16] Loss: 0.01518 +Epoch [473/4000] Training [8/16] Loss: 0.02846 +Epoch [473/4000] Training [9/16] Loss: 0.02122 +Epoch [473/4000] Training [10/16] Loss: 0.01826 +Epoch [473/4000] Training [11/16] Loss: 0.03793 +Epoch [473/4000] Training [12/16] Loss: 0.04076 +Epoch [473/4000] Training [13/16] Loss: 0.01382 +Epoch [473/4000] Training [14/16] Loss: 0.01588 +Epoch [473/4000] Training [15/16] Loss: 0.03111 +Epoch [473/4000] Training [16/16] Loss: 0.04905 +Epoch [473/4000] Training metric {'Train/mean dice_metric': 0.9819945096969604, 'Train/mean miou_metric': 0.9667774438858032, 'Train/mean f1': 0.977440595626831, 'Train/mean precision': 0.9720924496650696, 'Train/mean recall': 0.9828479290008545, 'Train/mean hd95_metric': 4.345574855804443} +Epoch [473/4000] Validation [1/4] Loss: 0.18955 focal_loss 0.11534 dice_loss 0.07421 +Epoch [473/4000] Validation [2/4] Loss: 0.26992 focal_loss 0.12373 dice_loss 0.14620 +Epoch [473/4000] Validation [3/4] Loss: 0.17773 focal_loss 0.09159 dice_loss 0.08614 +Epoch [473/4000] Validation [4/4] Loss: 0.37144 focal_loss 0.21784 dice_loss 0.15360 +Epoch [473/4000] Validation metric {'Val/mean dice_metric': 0.9558638334274292, 'Val/mean miou_metric': 0.9282442331314087, 'Val/mean f1': 0.9566118121147156, 'Val/mean precision': 0.9546676874160767, 'Val/mean recall': 0.958564043045044, 'Val/mean hd95_metric': 9.771059036254883} +Cheakpoint... +Epoch [473/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9559], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9558638334274292, 'Val/mean miou_metric': 0.9282442331314087, 'Val/mean f1': 0.9566118121147156, 'Val/mean precision': 0.9546676874160767, 'Val/mean recall': 0.958564043045044, 'Val/mean hd95_metric': 9.771059036254883} +Epoch [474/4000] Training [1/16] Loss: 0.02047 +Epoch [474/4000] Training [2/16] Loss: 0.02983 +Epoch [474/4000] Training [3/16] Loss: 0.02272 +Epoch [474/4000] Training [4/16] Loss: 0.02178 +Epoch [474/4000] Training [5/16] Loss: 0.01777 +Epoch [474/4000] Training [6/16] Loss: 0.05425 +Epoch [474/4000] Training [7/16] Loss: 0.01645 +Epoch [474/4000] Training [8/16] Loss: 0.03520 +Epoch [474/4000] Training [9/16] Loss: 0.02749 +Epoch [474/4000] Training [10/16] Loss: 0.01613 +Epoch [474/4000] Training [11/16] Loss: 0.02060 +Epoch [474/4000] Training [12/16] Loss: 0.01753 +Epoch [474/4000] Training [13/16] Loss: 0.01725 +Epoch [474/4000] Training [14/16] Loss: 0.02380 +Epoch [474/4000] Training [15/16] Loss: 0.01965 +Epoch [474/4000] Training [16/16] Loss: 0.02683 +Epoch [474/4000] Training metric {'Train/mean dice_metric': 0.9829928874969482, 'Train/mean miou_metric': 0.9669769406318665, 'Train/mean f1': 0.9798603057861328, 'Train/mean precision': 0.9761133193969727, 'Train/mean recall': 0.983636200428009, 'Train/mean hd95_metric': 4.7689666748046875} +Epoch [474/4000] Validation [1/4] Loss: 0.82197 focal_loss 0.64536 dice_loss 0.17661 +Epoch [474/4000] Validation [2/4] Loss: 0.30634 focal_loss 0.15134 dice_loss 0.15501 +Epoch [474/4000] Validation [3/4] Loss: 0.14199 focal_loss 0.05600 dice_loss 0.08599 +Epoch [474/4000] Validation [4/4] Loss: 0.42187 focal_loss 0.26463 dice_loss 0.15724 +Epoch [474/4000] Validation metric {'Val/mean dice_metric': 0.9523018002510071, 'Val/mean miou_metric': 0.9258024096488953, 'Val/mean f1': 0.9554652571678162, 'Val/mean precision': 0.9579207897186279, 'Val/mean recall': 0.953022301197052, 'Val/mean hd95_metric': 10.019556999206543} +Cheakpoint... +Epoch [474/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9523], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9523018002510071, 'Val/mean miou_metric': 0.9258024096488953, 'Val/mean f1': 0.9554652571678162, 'Val/mean precision': 0.9579207897186279, 'Val/mean recall': 0.953022301197052, 'Val/mean hd95_metric': 10.019556999206543} +Epoch [475/4000] Training [1/16] Loss: 0.01493 +Epoch [475/4000] Training [2/16] Loss: 0.02090 +Epoch [475/4000] Training [3/16] Loss: 0.02853 +Epoch [475/4000] Training [4/16] Loss: 0.02212 +Epoch [475/4000] Training [5/16] Loss: 0.02391 +Epoch [475/4000] Training [6/16] Loss: 0.02066 +Epoch [475/4000] Training [7/16] Loss: 0.02061 +Epoch [475/4000] Training [8/16] Loss: 0.01968 +Epoch [475/4000] Training [9/16] Loss: 0.01660 +Epoch [475/4000] Training [10/16] Loss: 0.01624 +Epoch [475/4000] Training [11/16] Loss: 0.01988 +Epoch [475/4000] Training [12/16] Loss: 0.01370 +Epoch [475/4000] Training [13/16] Loss: 0.02288 +Epoch [475/4000] Training [14/16] Loss: 0.01928 +Epoch [475/4000] Training [15/16] Loss: 0.02128 +Epoch [475/4000] Training [16/16] Loss: 0.02419 +Epoch [475/4000] Training metric {'Train/mean dice_metric': 0.9857310056686401, 'Train/mean miou_metric': 0.9719254970550537, 'Train/mean f1': 0.9830338358879089, 'Train/mean precision': 0.9772717356681824, 'Train/mean recall': 0.9888641834259033, 'Train/mean hd95_metric': 3.6204495429992676} +Epoch [475/4000] Validation [1/4] Loss: 0.37490 focal_loss 0.24211 dice_loss 0.13279 +Epoch [475/4000] Validation [2/4] Loss: 0.17670 focal_loss 0.06995 dice_loss 0.10675 +Epoch [475/4000] Validation [3/4] Loss: 0.15843 focal_loss 0.07870 dice_loss 0.07973 +Epoch [475/4000] Validation [4/4] Loss: 0.18499 focal_loss 0.08673 dice_loss 0.09825 +Epoch [475/4000] Validation metric {'Val/mean dice_metric': 0.9613901376724243, 'Val/mean miou_metric': 0.9366474151611328, 'Val/mean f1': 0.9602961540222168, 'Val/mean precision': 0.9562482833862305, 'Val/mean recall': 0.9643783569335938, 'Val/mean hd95_metric': 8.833133697509766} +Cheakpoint... +Epoch [475/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9613901376724243, 'Val/mean miou_metric': 0.9366474151611328, 'Val/mean f1': 0.9602961540222168, 'Val/mean precision': 0.9562482833862305, 'Val/mean recall': 0.9643783569335938, 'Val/mean hd95_metric': 8.833133697509766} +Epoch [476/4000] Training [1/16] Loss: 0.01675 +Epoch [476/4000] Training [2/16] Loss: 0.02110 +Epoch [476/4000] Training [3/16] Loss: 0.02053 +Epoch [476/4000] Training [4/16] Loss: 0.02013 +Epoch [476/4000] Training [5/16] Loss: 0.03411 +Epoch [476/4000] Training [6/16] Loss: 0.01789 +Epoch [476/4000] Training [7/16] Loss: 0.01573 +Epoch [476/4000] Training [8/16] Loss: 0.01918 +Epoch [476/4000] Training [9/16] Loss: 0.02091 +Epoch [476/4000] Training [10/16] Loss: 0.01274 +Epoch [476/4000] Training [11/16] Loss: 0.01571 +Epoch [476/4000] Training [12/16] Loss: 0.01552 +Epoch [476/4000] Training [13/16] Loss: 0.01740 +Epoch [476/4000] Training [14/16] Loss: 0.01313 +Epoch [476/4000] Training [15/16] Loss: 0.01759 +Epoch [476/4000] Training [16/16] Loss: 0.01431 +Epoch [476/4000] Training metric {'Train/mean dice_metric': 0.9880740642547607, 'Train/mean miou_metric': 0.9762875437736511, 'Train/mean f1': 0.984748125076294, 'Train/mean precision': 0.9799391627311707, 'Train/mean recall': 0.9896045923233032, 'Train/mean hd95_metric': 1.590813159942627} +Epoch [476/4000] Validation [1/4] Loss: 0.11476 focal_loss 0.05975 dice_loss 0.05501 +Epoch [476/4000] Validation [2/4] Loss: 0.26764 focal_loss 0.11510 dice_loss 0.15254 +Epoch [476/4000] Validation [3/4] Loss: 0.23982 focal_loss 0.12097 dice_loss 0.11885 +Epoch [476/4000] Validation [4/4] Loss: 0.21214 focal_loss 0.10393 dice_loss 0.10820 +Epoch [476/4000] Validation metric {'Val/mean dice_metric': 0.9641935229301453, 'Val/mean miou_metric': 0.9420850872993469, 'Val/mean f1': 0.9665194153785706, 'Val/mean precision': 0.9598639011383057, 'Val/mean recall': 0.9732679724693298, 'Val/mean hd95_metric': 6.959011077880859} +Cheakpoint... +Epoch [476/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9642], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9641935229301453, 'Val/mean miou_metric': 0.9420850872993469, 'Val/mean f1': 0.9665194153785706, 'Val/mean precision': 0.9598639011383057, 'Val/mean recall': 0.9732679724693298, 'Val/mean hd95_metric': 6.959011077880859} +Epoch [477/4000] Training [1/16] Loss: 0.01290 +Epoch [477/4000] Training [2/16] Loss: 0.01985 +Epoch [477/4000] Training [3/16] Loss: 0.01419 +Epoch [477/4000] Training [4/16] Loss: 0.03063 +Epoch [477/4000] Training [5/16] Loss: 0.01528 +Epoch [477/4000] Training [6/16] Loss: 0.00917 +Epoch [477/4000] Training [7/16] Loss: 0.01587 +Epoch [477/4000] Training [8/16] Loss: 0.02023 +Epoch [477/4000] Training [9/16] Loss: 0.01555 +Epoch [477/4000] Training [10/16] Loss: 0.01354 +Epoch [477/4000] Training [11/16] Loss: 0.01855 +Epoch [477/4000] Training [12/16] Loss: 0.02065 +Epoch [477/4000] Training [13/16] Loss: 0.01054 +Epoch [477/4000] Training [14/16] Loss: 0.01222 +Epoch [477/4000] Training [15/16] Loss: 0.00974 +Epoch [477/4000] Training [16/16] Loss: 0.01602 +Epoch [477/4000] Training metric {'Train/mean dice_metric': 0.9893438220024109, 'Train/mean miou_metric': 0.9787875413894653, 'Train/mean f1': 0.9860853552818298, 'Train/mean precision': 0.9815581440925598, 'Train/mean recall': 0.9906545281410217, 'Train/mean hd95_metric': 1.5014586448669434} +Epoch [477/4000] Validation [1/4] Loss: 0.30917 focal_loss 0.19846 dice_loss 0.11070 +Epoch [477/4000] Validation [2/4] Loss: 0.34783 focal_loss 0.15249 dice_loss 0.19534 +Epoch [477/4000] Validation [3/4] Loss: 0.12671 focal_loss 0.06131 dice_loss 0.06540 +Epoch [477/4000] Validation [4/4] Loss: 0.15882 focal_loss 0.07693 dice_loss 0.08190 +Epoch [477/4000] Validation metric {'Val/mean dice_metric': 0.9658035039901733, 'Val/mean miou_metric': 0.9440253973007202, 'Val/mean f1': 0.9669488668441772, 'Val/mean precision': 0.9669347405433655, 'Val/mean recall': 0.9669629335403442, 'Val/mean hd95_metric': 6.1121697425842285} +Cheakpoint... +Epoch [477/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658035039901733, 'Val/mean miou_metric': 0.9440253973007202, 'Val/mean f1': 0.9669488668441772, 'Val/mean precision': 0.9669347405433655, 'Val/mean recall': 0.9669629335403442, 'Val/mean hd95_metric': 6.1121697425842285} +Epoch [478/4000] Training [1/16] Loss: 0.01131 +Epoch [478/4000] Training [2/16] Loss: 0.01316 +Epoch [478/4000] Training [3/16] Loss: 0.02183 +Epoch [478/4000] Training [4/16] Loss: 0.01171 +Epoch [478/4000] Training [5/16] Loss: 0.01606 +Epoch [478/4000] Training [6/16] Loss: 0.01265 +Epoch [478/4000] Training [7/16] Loss: 0.02248 +Epoch [478/4000] Training [8/16] Loss: 0.01332 +Epoch [478/4000] Training [9/16] Loss: 0.01247 +Epoch [478/4000] Training [10/16] Loss: 0.01289 +Epoch [478/4000] Training [11/16] Loss: 0.01383 +Epoch [478/4000] Training [12/16] Loss: 0.01362 +Epoch [478/4000] Training [13/16] Loss: 0.01420 +Epoch [478/4000] Training [14/16] Loss: 0.01298 +Epoch [478/4000] Training [15/16] Loss: 0.01451 +Epoch [478/4000] Training [16/16] Loss: 0.01223 +Epoch [478/4000] Training metric {'Train/mean dice_metric': 0.9888353943824768, 'Train/mean miou_metric': 0.9788535833358765, 'Train/mean f1': 0.986182451248169, 'Train/mean precision': 0.9822981357574463, 'Train/mean recall': 0.9900976419448853, 'Train/mean hd95_metric': 2.032580852508545} +Epoch [478/4000] Validation [1/4] Loss: 0.21545 focal_loss 0.13057 dice_loss 0.08488 +Epoch [478/4000] Validation [2/4] Loss: 0.45360 focal_loss 0.22653 dice_loss 0.22707 +Epoch [478/4000] Validation [3/4] Loss: 0.29087 focal_loss 0.18728 dice_loss 0.10360 +Epoch [478/4000] Validation [4/4] Loss: 0.31297 focal_loss 0.15537 dice_loss 0.15761 +Epoch [478/4000] Validation metric {'Val/mean dice_metric': 0.9627760052680969, 'Val/mean miou_metric': 0.9403988718986511, 'Val/mean f1': 0.9649155735969543, 'Val/mean precision': 0.9581811428070068, 'Val/mean recall': 0.9717453122138977, 'Val/mean hd95_metric': 8.883646965026855} +Cheakpoint... +Epoch [478/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9628], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9627760052680969, 'Val/mean miou_metric': 0.9403988718986511, 'Val/mean f1': 0.9649155735969543, 'Val/mean precision': 0.9581811428070068, 'Val/mean recall': 0.9717453122138977, 'Val/mean hd95_metric': 8.883646965026855} +Epoch [479/4000] Training [1/16] Loss: 0.01664 +Epoch [479/4000] Training [2/16] Loss: 0.01632 +Epoch [479/4000] Training [3/16] Loss: 0.01835 +Epoch [479/4000] Training [4/16] Loss: 0.01761 +Epoch [479/4000] Training [5/16] Loss: 0.01395 +Epoch [479/4000] Training [6/16] Loss: 0.01796 +Epoch [479/4000] Training [7/16] Loss: 0.02091 +Epoch [479/4000] Training [8/16] Loss: 0.01627 +Epoch [479/4000] Training [9/16] Loss: 0.01605 +Epoch [479/4000] Training [10/16] Loss: 0.01944 +Epoch [479/4000] Training [11/16] Loss: 0.02332 +Epoch [479/4000] Training [12/16] Loss: 0.01726 +Epoch [479/4000] Training [13/16] Loss: 0.02426 +Epoch [479/4000] Training [14/16] Loss: 0.02092 +Epoch [479/4000] Training [15/16] Loss: 0.01413 +Epoch [479/4000] Training [16/16] Loss: 0.03090 +Epoch [479/4000] Training metric {'Train/mean dice_metric': 0.9860441088676453, 'Train/mean miou_metric': 0.9725490808486938, 'Train/mean f1': 0.9835084080696106, 'Train/mean precision': 0.9790686964988708, 'Train/mean recall': 0.9879885315895081, 'Train/mean hd95_metric': 3.686739444732666} +Epoch [479/4000] Validation [1/4] Loss: 0.50484 focal_loss 0.36880 dice_loss 0.13604 +Epoch [479/4000] Validation [2/4] Loss: 0.63987 focal_loss 0.39849 dice_loss 0.24138 +Epoch [479/4000] Validation [3/4] Loss: 0.21167 focal_loss 0.11305 dice_loss 0.09862 +Epoch [479/4000] Validation [4/4] Loss: 0.39613 focal_loss 0.22237 dice_loss 0.17376 +Epoch [479/4000] Validation metric {'Val/mean dice_metric': 0.959228515625, 'Val/mean miou_metric': 0.9336258172988892, 'Val/mean f1': 0.9615014791488647, 'Val/mean precision': 0.9651453495025635, 'Val/mean recall': 0.9578849673271179, 'Val/mean hd95_metric': 8.54058837890625} +Cheakpoint... +Epoch [479/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9592], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959228515625, 'Val/mean miou_metric': 0.9336258172988892, 'Val/mean f1': 0.9615014791488647, 'Val/mean precision': 0.9651453495025635, 'Val/mean recall': 0.9578849673271179, 'Val/mean hd95_metric': 8.54058837890625} +Epoch [480/4000] Training [1/16] Loss: 0.01358 +Epoch [480/4000] Training [2/16] Loss: 0.01266 +Epoch [480/4000] Training [3/16] Loss: 0.01589 +Epoch [480/4000] Training [4/16] Loss: 0.01443 +Epoch [480/4000] Training [5/16] Loss: 0.01343 +Epoch [480/4000] Training [6/16] Loss: 0.01506 +Epoch [480/4000] Training [7/16] Loss: 0.01736 +Epoch [480/4000] Training [8/16] Loss: 0.01939 +Epoch [480/4000] Training [9/16] Loss: 0.01775 +Epoch [480/4000] Training [10/16] Loss: 0.01628 +Epoch [480/4000] Training [11/16] Loss: 0.01402 +Epoch [480/4000] Training [12/16] Loss: 0.02255 +Epoch [480/4000] Training [13/16] Loss: 0.01571 +Epoch [480/4000] Training [14/16] Loss: 0.01524 +Epoch [480/4000] Training [15/16] Loss: 0.01765 +Epoch [480/4000] Training [16/16] Loss: 0.01732 +Epoch [480/4000] Training metric {'Train/mean dice_metric': 0.9888089895248413, 'Train/mean miou_metric': 0.9777213335037231, 'Train/mean f1': 0.9856175780296326, 'Train/mean precision': 0.9808664321899414, 'Train/mean recall': 0.9904150366783142, 'Train/mean hd95_metric': 1.5716214179992676} +Epoch [480/4000] Validation [1/4] Loss: 0.33191 focal_loss 0.22681 dice_loss 0.10510 +Epoch [480/4000] Validation [2/4] Loss: 0.29140 focal_loss 0.12941 dice_loss 0.16199 +Epoch [480/4000] Validation [3/4] Loss: 0.11688 focal_loss 0.04792 dice_loss 0.06896 +Epoch [480/4000] Validation [4/4] Loss: 0.23409 focal_loss 0.10723 dice_loss 0.12686 +Epoch [480/4000] Validation metric {'Val/mean dice_metric': 0.965911865234375, 'Val/mean miou_metric': 0.9428808093070984, 'Val/mean f1': 0.967254638671875, 'Val/mean precision': 0.9619734883308411, 'Val/mean recall': 0.972594141960144, 'Val/mean hd95_metric': 6.714636325836182} +Cheakpoint... +Epoch [480/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965911865234375, 'Val/mean miou_metric': 0.9428808093070984, 'Val/mean f1': 0.967254638671875, 'Val/mean precision': 0.9619734883308411, 'Val/mean recall': 0.972594141960144, 'Val/mean hd95_metric': 6.714636325836182} +Epoch [481/4000] Training [1/16] Loss: 0.01490 +Epoch [481/4000] Training [2/16] Loss: 0.01468 +Epoch [481/4000] Training [3/16] Loss: 0.01508 +Epoch [481/4000] Training [4/16] Loss: 0.04361 +Epoch [481/4000] Training [5/16] Loss: 0.01662 +Epoch [481/4000] Training [6/16] Loss: 0.01569 +Epoch [481/4000] Training [7/16] Loss: 0.01907 +Epoch [481/4000] Training [8/16] Loss: 0.03944 +Epoch [481/4000] Training [9/16] Loss: 0.01526 +Epoch [481/4000] Training [10/16] Loss: 0.01554 +Epoch [481/4000] Training [11/16] Loss: 0.01932 +Epoch [481/4000] Training [12/16] Loss: 0.01406 +Epoch [481/4000] Training [13/16] Loss: 0.01436 +Epoch [481/4000] Training [14/16] Loss: 0.02822 +Epoch [481/4000] Training [15/16] Loss: 0.02801 +Epoch [481/4000] Training [16/16] Loss: 0.02048 +Epoch [481/4000] Training metric {'Train/mean dice_metric': 0.9863438010215759, 'Train/mean miou_metric': 0.9733738303184509, 'Train/mean f1': 0.9839980006217957, 'Train/mean precision': 0.9799027442932129, 'Train/mean recall': 0.9881276488304138, 'Train/mean hd95_metric': 2.7435545921325684} +Epoch [481/4000] Validation [1/4] Loss: 0.27147 focal_loss 0.16857 dice_loss 0.10290 +Epoch [481/4000] Validation [2/4] Loss: 0.38291 focal_loss 0.16492 dice_loss 0.21799 +Epoch [481/4000] Validation [3/4] Loss: 0.11266 focal_loss 0.05689 dice_loss 0.05576 +Epoch [481/4000] Validation [4/4] Loss: 0.48805 focal_loss 0.28738 dice_loss 0.20068 +Epoch [481/4000] Validation metric {'Val/mean dice_metric': 0.9606478810310364, 'Val/mean miou_metric': 0.935620903968811, 'Val/mean f1': 0.9643518328666687, 'Val/mean precision': 0.9612067937850952, 'Val/mean recall': 0.9675175547599792, 'Val/mean hd95_metric': 8.154809951782227} +Cheakpoint... +Epoch [481/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9606], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9606478810310364, 'Val/mean miou_metric': 0.935620903968811, 'Val/mean f1': 0.9643518328666687, 'Val/mean precision': 0.9612067937850952, 'Val/mean recall': 0.9675175547599792, 'Val/mean hd95_metric': 8.154809951782227} +Epoch [482/4000] Training [1/16] Loss: 0.01633 +Epoch [482/4000] Training [2/16] Loss: 0.01761 +Epoch [482/4000] Training [3/16] Loss: 0.01957 +Epoch [482/4000] Training [4/16] Loss: 0.02213 +Epoch [482/4000] Training [5/16] Loss: 0.02059 +Epoch [482/4000] Training [6/16] Loss: 0.01423 +Epoch [482/4000] Training [7/16] Loss: 0.01844 +Epoch [482/4000] Training [8/16] Loss: 0.02320 +Epoch [482/4000] Training [9/16] Loss: 0.12371 +Epoch [482/4000] Training [10/16] Loss: 0.02352 +Epoch [482/4000] Training [11/16] Loss: 0.01737 +Epoch [482/4000] Training [12/16] Loss: 0.02617 +Epoch [482/4000] Training [13/16] Loss: 0.01329 +Epoch [482/4000] Training [14/16] Loss: 0.02385 +Epoch [482/4000] Training [15/16] Loss: 0.02067 +Epoch [482/4000] Training [16/16] Loss: 0.02134 +Epoch [482/4000] Training metric {'Train/mean dice_metric': 0.9843976497650146, 'Train/mean miou_metric': 0.9706035256385803, 'Train/mean f1': 0.9825572371482849, 'Train/mean precision': 0.9778764843940735, 'Train/mean recall': 0.9872829914093018, 'Train/mean hd95_metric': 3.3130991458892822} +Epoch [482/4000] Validation [1/4] Loss: 0.29440 focal_loss 0.18708 dice_loss 0.10732 +Epoch [482/4000] Validation [2/4] Loss: 0.24890 focal_loss 0.11462 dice_loss 0.13427 +Epoch [482/4000] Validation [3/4] Loss: 0.15438 focal_loss 0.08542 dice_loss 0.06895 +Epoch [482/4000] Validation [4/4] Loss: 0.37111 focal_loss 0.22046 dice_loss 0.15065 +Epoch [482/4000] Validation metric {'Val/mean dice_metric': 0.9596790075302124, 'Val/mean miou_metric': 0.933713436126709, 'Val/mean f1': 0.9599693417549133, 'Val/mean precision': 0.9505197405815125, 'Val/mean recall': 0.9696085453033447, 'Val/mean hd95_metric': 10.371877670288086} +Cheakpoint... +Epoch [482/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9597], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9596790075302124, 'Val/mean miou_metric': 0.933713436126709, 'Val/mean f1': 0.9599693417549133, 'Val/mean precision': 0.9505197405815125, 'Val/mean recall': 0.9696085453033447, 'Val/mean hd95_metric': 10.371877670288086} +Epoch [483/4000] Training [1/16] Loss: 0.01781 +Epoch [483/4000] Training [2/16] Loss: 0.02324 +Epoch [483/4000] Training [3/16] Loss: 0.01819 +Epoch [483/4000] Training [4/16] Loss: 0.01643 +Epoch [483/4000] Training [5/16] Loss: 0.01461 +Epoch [483/4000] Training [6/16] Loss: 0.01524 +Epoch [483/4000] Training [7/16] Loss: 0.01264 +Epoch [483/4000] Training [8/16] Loss: 0.02068 +Epoch [483/4000] Training [9/16] Loss: 0.01774 +Epoch [483/4000] Training [10/16] Loss: 0.01721 +Epoch [483/4000] Training [11/16] Loss: 0.07261 +Epoch [483/4000] Training [12/16] Loss: 0.02548 +Epoch [483/4000] Training [13/16] Loss: 0.01726 +Epoch [483/4000] Training [14/16] Loss: 0.01809 +Epoch [483/4000] Training [15/16] Loss: 0.01798 +Epoch [483/4000] Training [16/16] Loss: 0.02507 +Epoch [483/4000] Training metric {'Train/mean dice_metric': 0.9868192076683044, 'Train/mean miou_metric': 0.9740752577781677, 'Train/mean f1': 0.9840706586837769, 'Train/mean precision': 0.9805595278739929, 'Train/mean recall': 0.9876070618629456, 'Train/mean hd95_metric': 2.576026439666748} +Epoch [483/4000] Validation [1/4] Loss: 0.77680 focal_loss 0.60675 dice_loss 0.17005 +Epoch [483/4000] Validation [2/4] Loss: 0.26839 focal_loss 0.11593 dice_loss 0.15246 +Epoch [483/4000] Validation [3/4] Loss: 0.22473 focal_loss 0.11828 dice_loss 0.10645 +Epoch [483/4000] Validation [4/4] Loss: 0.21915 focal_loss 0.10242 dice_loss 0.11673 +Epoch [483/4000] Validation metric {'Val/mean dice_metric': 0.9633150100708008, 'Val/mean miou_metric': 0.9382403492927551, 'Val/mean f1': 0.963585615158081, 'Val/mean precision': 0.9629771709442139, 'Val/mean recall': 0.9641949534416199, 'Val/mean hd95_metric': 7.7715911865234375} +Cheakpoint... +Epoch [483/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633150100708008, 'Val/mean miou_metric': 0.9382403492927551, 'Val/mean f1': 0.963585615158081, 'Val/mean precision': 0.9629771709442139, 'Val/mean recall': 0.9641949534416199, 'Val/mean hd95_metric': 7.7715911865234375} +Epoch [484/4000] Training [1/16] Loss: 0.01370 +Epoch [484/4000] Training [2/16] Loss: 0.01456 +Epoch [484/4000] Training [3/16] Loss: 0.01411 +Epoch [484/4000] Training [4/16] Loss: 0.02609 +Epoch [484/4000] Training [5/16] Loss: 0.01764 +Epoch [484/4000] Training [6/16] Loss: 0.02225 +Epoch [484/4000] Training [7/16] Loss: 0.01486 +Epoch [484/4000] Training [8/16] Loss: 0.01229 +Epoch [484/4000] Training [9/16] Loss: 0.04724 +Epoch [484/4000] Training [10/16] Loss: 0.02973 +Epoch [484/4000] Training [11/16] Loss: 0.01835 +Epoch [484/4000] Training [12/16] Loss: 0.01866 +Epoch [484/4000] Training [13/16] Loss: 0.01560 +Epoch [484/4000] Training [14/16] Loss: 0.01830 +Epoch [484/4000] Training [15/16] Loss: 0.04651 +Epoch [484/4000] Training [16/16] Loss: 0.01730 +Epoch [484/4000] Training metric {'Train/mean dice_metric': 0.9844038486480713, 'Train/mean miou_metric': 0.9704180955886841, 'Train/mean f1': 0.9815722107887268, 'Train/mean precision': 0.9768697619438171, 'Train/mean recall': 0.9863201379776001, 'Train/mean hd95_metric': 3.235448122024536} +Epoch [484/4000] Validation [1/4] Loss: 0.76208 focal_loss 0.59544 dice_loss 0.16664 +Epoch [484/4000] Validation [2/4] Loss: 0.31780 focal_loss 0.14687 dice_loss 0.17093 +Epoch [484/4000] Validation [3/4] Loss: 0.16110 focal_loss 0.08628 dice_loss 0.07481 +Epoch [484/4000] Validation [4/4] Loss: 0.37468 focal_loss 0.22424 dice_loss 0.15044 +Epoch [484/4000] Validation metric {'Val/mean dice_metric': 0.954642653465271, 'Val/mean miou_metric': 0.928156852722168, 'Val/mean f1': 0.9568002820014954, 'Val/mean precision': 0.9601756930351257, 'Val/mean recall': 0.9534485340118408, 'Val/mean hd95_metric': 9.537652969360352} +Cheakpoint... +Epoch [484/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9546], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.954642653465271, 'Val/mean miou_metric': 0.928156852722168, 'Val/mean f1': 0.9568002820014954, 'Val/mean precision': 0.9601756930351257, 'Val/mean recall': 0.9534485340118408, 'Val/mean hd95_metric': 9.537652969360352} +Epoch [485/4000] Training [1/16] Loss: 0.01581 +Epoch [485/4000] Training [2/16] Loss: 0.02025 +Epoch [485/4000] Training [3/16] Loss: 0.03175 +Epoch [485/4000] Training [4/16] Loss: 0.02299 +Epoch [485/4000] Training [5/16] Loss: 0.03995 +Epoch [485/4000] Training [6/16] Loss: 0.01436 +Epoch [485/4000] Training [7/16] Loss: 0.04412 +Epoch [485/4000] Training [8/16] Loss: 0.01784 +Epoch [485/4000] Training [9/16] Loss: 0.01720 +Epoch [485/4000] Training [10/16] Loss: 0.03230 +Epoch [485/4000] Training [11/16] Loss: 0.02336 +Epoch [485/4000] Training [12/16] Loss: 0.02048 +Epoch [485/4000] Training [13/16] Loss: 0.09942 +Epoch [485/4000] Training [14/16] Loss: 0.02265 +Epoch [485/4000] Training [15/16] Loss: 0.02770 +Epoch [485/4000] Training [16/16] Loss: 0.03051 +Epoch [485/4000] Training metric {'Train/mean dice_metric': 0.9805377721786499, 'Train/mean miou_metric': 0.9634271860122681, 'Train/mean f1': 0.9759455919265747, 'Train/mean precision': 0.970897912979126, 'Train/mean recall': 0.9810460209846497, 'Train/mean hd95_metric': 5.1710638999938965} +Epoch [485/4000] Validation [1/4] Loss: 0.13131 focal_loss 0.06443 dice_loss 0.06688 +Epoch [485/4000] Validation [2/4] Loss: 0.34270 focal_loss 0.11839 dice_loss 0.22432 +Epoch [485/4000] Validation [3/4] Loss: 0.16211 focal_loss 0.06927 dice_loss 0.09283 +Epoch [485/4000] Validation [4/4] Loss: 0.37163 focal_loss 0.18020 dice_loss 0.19144 +Epoch [485/4000] Validation metric {'Val/mean dice_metric': 0.9537350535392761, 'Val/mean miou_metric': 0.9255510568618774, 'Val/mean f1': 0.9567890763282776, 'Val/mean precision': 0.9466186165809631, 'Val/mean recall': 0.9671804308891296, 'Val/mean hd95_metric': 11.169360160827637} +Cheakpoint... +Epoch [485/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9537], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9537350535392761, 'Val/mean miou_metric': 0.9255510568618774, 'Val/mean f1': 0.9567890763282776, 'Val/mean precision': 0.9466186165809631, 'Val/mean recall': 0.9671804308891296, 'Val/mean hd95_metric': 11.169360160827637} +Epoch [486/4000] Training [1/16] Loss: 0.01862 +Epoch [486/4000] Training [2/16] Loss: 0.02270 +Epoch [486/4000] Training [3/16] Loss: 0.03605 +Epoch [486/4000] Training [4/16] Loss: 0.02507 +Epoch [486/4000] Training [5/16] Loss: 0.01764 +Epoch [486/4000] Training [6/16] Loss: 0.01463 +Epoch [486/4000] Training [7/16] Loss: 0.01977 +Epoch [486/4000] Training [8/16] Loss: 0.03172 +Epoch [486/4000] Training [9/16] Loss: 0.01604 +Epoch [486/4000] Training [10/16] Loss: 0.02316 +Epoch [486/4000] Training [11/16] Loss: 0.02005 +Epoch [486/4000] Training [12/16] Loss: 0.01704 +Epoch [486/4000] Training [13/16] Loss: 0.02648 +Epoch [486/4000] Training [14/16] Loss: 0.01456 +Epoch [486/4000] Training [15/16] Loss: 0.01718 +Epoch [486/4000] Training [16/16] Loss: 0.02885 +Epoch [486/4000] Training metric {'Train/mean dice_metric': 0.98521888256073, 'Train/mean miou_metric': 0.9708127975463867, 'Train/mean f1': 0.9817618131637573, 'Train/mean precision': 0.9776492714881897, 'Train/mean recall': 0.985909104347229, 'Train/mean hd95_metric': 3.201735496520996} +Epoch [486/4000] Validation [1/4] Loss: 0.30153 focal_loss 0.18999 dice_loss 0.11154 +Epoch [486/4000] Validation [2/4] Loss: 0.37323 focal_loss 0.18962 dice_loss 0.18361 +Epoch [486/4000] Validation [3/4] Loss: 0.11249 focal_loss 0.04988 dice_loss 0.06261 +Epoch [486/4000] Validation [4/4] Loss: 0.26046 focal_loss 0.14292 dice_loss 0.11755 +Epoch [486/4000] Validation metric {'Val/mean dice_metric': 0.9625810384750366, 'Val/mean miou_metric': 0.9370786547660828, 'Val/mean f1': 0.9637036919593811, 'Val/mean precision': 0.9642196893692017, 'Val/mean recall': 0.9631883502006531, 'Val/mean hd95_metric': 7.390887260437012} +Cheakpoint... +Epoch [486/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9626], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625810384750366, 'Val/mean miou_metric': 0.9370786547660828, 'Val/mean f1': 0.9637036919593811, 'Val/mean precision': 0.9642196893692017, 'Val/mean recall': 0.9631883502006531, 'Val/mean hd95_metric': 7.390887260437012} +Epoch [487/4000] Training [1/16] Loss: 0.01470 +Epoch [487/4000] Training [2/16] Loss: 0.03140 +Epoch [487/4000] Training [3/16] Loss: 0.01400 +Epoch [487/4000] Training [4/16] Loss: 0.01557 +Epoch [487/4000] Training [5/16] Loss: 0.01664 +Epoch [487/4000] Training [6/16] Loss: 0.01560 +Epoch [487/4000] Training [7/16] Loss: 0.01827 +Epoch [487/4000] Training [8/16] Loss: 0.01255 +Epoch [487/4000] Training [9/16] Loss: 0.01788 +Epoch [487/4000] Training [10/16] Loss: 0.01682 +Epoch [487/4000] Training [11/16] Loss: 0.01619 +Epoch [487/4000] Training [12/16] Loss: 0.01639 +Epoch [487/4000] Training [13/16] Loss: 0.01563 +Epoch [487/4000] Training [14/16] Loss: 0.01871 +Epoch [487/4000] Training [15/16] Loss: 0.01896 +Epoch [487/4000] Training [16/16] Loss: 0.02137 +Epoch [487/4000] Training metric {'Train/mean dice_metric': 0.9876384735107422, 'Train/mean miou_metric': 0.9754692316055298, 'Train/mean f1': 0.9847460985183716, 'Train/mean precision': 0.9799911975860596, 'Train/mean recall': 0.9895473718643188, 'Train/mean hd95_metric': 1.7636244297027588} +Epoch [487/4000] Validation [1/4] Loss: 0.14733 focal_loss 0.07709 dice_loss 0.07024 +Epoch [487/4000] Validation [2/4] Loss: 0.26664 focal_loss 0.11921 dice_loss 0.14743 +Epoch [487/4000] Validation [3/4] Loss: 0.32144 focal_loss 0.17753 dice_loss 0.14391 +Epoch [487/4000] Validation [4/4] Loss: 0.16894 focal_loss 0.07743 dice_loss 0.09151 +Epoch [487/4000] Validation metric {'Val/mean dice_metric': 0.9647286534309387, 'Val/mean miou_metric': 0.9409269094467163, 'Val/mean f1': 0.9653126001358032, 'Val/mean precision': 0.9571841955184937, 'Val/mean recall': 0.9735801219940186, 'Val/mean hd95_metric': 7.017055511474609} +Cheakpoint... +Epoch [487/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647286534309387, 'Val/mean miou_metric': 0.9409269094467163, 'Val/mean f1': 0.9653126001358032, 'Val/mean precision': 0.9571841955184937, 'Val/mean recall': 0.9735801219940186, 'Val/mean hd95_metric': 7.017055511474609} +Epoch [488/4000] Training [1/16] Loss: 0.03128 +Epoch [488/4000] Training [2/16] Loss: 0.01721 +Epoch [488/4000] Training [3/16] Loss: 0.01791 +Epoch [488/4000] Training [4/16] Loss: 0.02064 +Epoch [488/4000] Training [5/16] Loss: 0.02060 +Epoch [488/4000] Training [6/16] Loss: 0.02075 +Epoch [488/4000] Training [7/16] Loss: 0.01470 +Epoch [488/4000] Training [8/16] Loss: 0.01515 +Epoch [488/4000] Training [9/16] Loss: 0.01213 +Epoch [488/4000] Training [10/16] Loss: 0.01581 +Epoch [488/4000] Training [11/16] Loss: 0.01613 +Epoch [488/4000] Training [12/16] Loss: 0.02607 +Epoch [488/4000] Training [13/16] Loss: 0.01671 +Epoch [488/4000] Training [14/16] Loss: 0.01446 +Epoch [488/4000] Training [15/16] Loss: 0.01464 +Epoch [488/4000] Training [16/16] Loss: 0.01465 +Epoch [488/4000] Training metric {'Train/mean dice_metric': 0.9882677793502808, 'Train/mean miou_metric': 0.9766484498977661, 'Train/mean f1': 0.9850231409072876, 'Train/mean precision': 0.9803137183189392, 'Train/mean recall': 0.9897781014442444, 'Train/mean hd95_metric': 1.758880853652954} +Epoch [488/4000] Validation [1/4] Loss: 0.23004 focal_loss 0.14358 dice_loss 0.08646 +Epoch [488/4000] Validation [2/4] Loss: 0.48459 focal_loss 0.21994 dice_loss 0.26465 +Epoch [488/4000] Validation [3/4] Loss: 0.17066 focal_loss 0.08703 dice_loss 0.08363 +Epoch [488/4000] Validation [4/4] Loss: 0.20336 focal_loss 0.10263 dice_loss 0.10073 +Epoch [488/4000] Validation metric {'Val/mean dice_metric': 0.9640447497367859, 'Val/mean miou_metric': 0.9408747553825378, 'Val/mean f1': 0.9661126136779785, 'Val/mean precision': 0.9605499505996704, 'Val/mean recall': 0.9717400670051575, 'Val/mean hd95_metric': 6.755228519439697} +Cheakpoint... +Epoch [488/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640447497367859, 'Val/mean miou_metric': 0.9408747553825378, 'Val/mean f1': 0.9661126136779785, 'Val/mean precision': 0.9605499505996704, 'Val/mean recall': 0.9717400670051575, 'Val/mean hd95_metric': 6.755228519439697} +Epoch [489/4000] Training [1/16] Loss: 0.03883 +Epoch [489/4000] Training [2/16] Loss: 0.01499 +Epoch [489/4000] Training [3/16] Loss: 0.01309 +Epoch [489/4000] Training [4/16] Loss: 0.01623 +Epoch [489/4000] Training [5/16] Loss: 0.01691 +Epoch [489/4000] Training [6/16] Loss: 0.01357 +Epoch [489/4000] Training [7/16] Loss: 0.01907 +Epoch [489/4000] Training [8/16] Loss: 0.01387 +Epoch [489/4000] Training [9/16] Loss: 0.01414 +Epoch [489/4000] Training [10/16] Loss: 0.01721 +Epoch [489/4000] Training [11/16] Loss: 0.01231 +Epoch [489/4000] Training [12/16] Loss: 0.01375 +Epoch [489/4000] Training [13/16] Loss: 0.01684 +Epoch [489/4000] Training [14/16] Loss: 0.02359 +Epoch [489/4000] Training [15/16] Loss: 0.02051 +Epoch [489/4000] Training [16/16] Loss: 0.01234 +Epoch [489/4000] Training metric {'Train/mean dice_metric': 0.9876902103424072, 'Train/mean miou_metric': 0.9761909246444702, 'Train/mean f1': 0.9855119585990906, 'Train/mean precision': 0.9814162850379944, 'Train/mean recall': 0.9896419644355774, 'Train/mean hd95_metric': 1.9949666261672974} +Epoch [489/4000] Validation [1/4] Loss: 0.39394 focal_loss 0.28186 dice_loss 0.11208 +Epoch [489/4000] Validation [2/4] Loss: 0.29205 focal_loss 0.11503 dice_loss 0.17702 +Epoch [489/4000] Validation [3/4] Loss: 0.12871 focal_loss 0.06609 dice_loss 0.06262 +Epoch [489/4000] Validation [4/4] Loss: 0.19891 focal_loss 0.09552 dice_loss 0.10338 +Epoch [489/4000] Validation metric {'Val/mean dice_metric': 0.9667894244194031, 'Val/mean miou_metric': 0.9442178606987, 'Val/mean f1': 0.9677537679672241, 'Val/mean precision': 0.96502685546875, 'Val/mean recall': 0.9704961776733398, 'Val/mean hd95_metric': 6.010656833648682} +Cheakpoint... +Epoch [489/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667894244194031, 'Val/mean miou_metric': 0.9442178606987, 'Val/mean f1': 0.9677537679672241, 'Val/mean precision': 0.96502685546875, 'Val/mean recall': 0.9704961776733398, 'Val/mean hd95_metric': 6.010656833648682} +Epoch [490/4000] Training [1/16] Loss: 0.01798 +Epoch [490/4000] Training [2/16] Loss: 0.02215 +Epoch [490/4000] Training [3/16] Loss: 0.01932 +Epoch [490/4000] Training [4/16] Loss: 0.01748 +Epoch [490/4000] Training [5/16] Loss: 0.02183 +Epoch [490/4000] Training [6/16] Loss: 0.02200 +Epoch [490/4000] Training [7/16] Loss: 0.01769 +Epoch [490/4000] Training [8/16] Loss: 0.01454 +Epoch [490/4000] Training [9/16] Loss: 0.01781 +Epoch [490/4000] Training [10/16] Loss: 0.01439 +Epoch [490/4000] Training [11/16] Loss: 0.01353 +Epoch [490/4000] Training [12/16] Loss: 0.01404 +Epoch [490/4000] Training [13/16] Loss: 0.01464 +Epoch [490/4000] Training [14/16] Loss: 0.01356 +Epoch [490/4000] Training [15/16] Loss: 0.01448 +Epoch [490/4000] Training [16/16] Loss: 0.01586 +Epoch [490/4000] Training metric {'Train/mean dice_metric': 0.9885808229446411, 'Train/mean miou_metric': 0.9772601127624512, 'Train/mean f1': 0.9860548377037048, 'Train/mean precision': 0.981329619884491, 'Train/mean recall': 0.9908257722854614, 'Train/mean hd95_metric': 1.7121232748031616} +Epoch [490/4000] Validation [1/4] Loss: 0.44684 focal_loss 0.34166 dice_loss 0.10518 +Epoch [490/4000] Validation [2/4] Loss: 0.23168 focal_loss 0.08780 dice_loss 0.14387 +Epoch [490/4000] Validation [3/4] Loss: 0.15542 focal_loss 0.06705 dice_loss 0.08837 +Epoch [490/4000] Validation [4/4] Loss: 0.17227 focal_loss 0.08159 dice_loss 0.09067 +Epoch [490/4000] Validation metric {'Val/mean dice_metric': 0.9654766321182251, 'Val/mean miou_metric': 0.9430512189865112, 'Val/mean f1': 0.9664221405982971, 'Val/mean precision': 0.9626324772834778, 'Val/mean recall': 0.9702417254447937, 'Val/mean hd95_metric': 6.540982246398926} +Cheakpoint... +Epoch [490/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654766321182251, 'Val/mean miou_metric': 0.9430512189865112, 'Val/mean f1': 0.9664221405982971, 'Val/mean precision': 0.9626324772834778, 'Val/mean recall': 0.9702417254447937, 'Val/mean hd95_metric': 6.540982246398926} +Epoch [491/4000] Training [1/16] Loss: 0.01302 +Epoch [491/4000] Training [2/16] Loss: 0.01153 +Epoch [491/4000] Training [3/16] Loss: 0.01429 +Epoch [491/4000] Training [4/16] Loss: 0.01473 +Epoch [491/4000] Training [5/16] Loss: 0.01234 +Epoch [491/4000] Training [6/16] Loss: 0.01454 +Epoch [491/4000] Training [7/16] Loss: 0.01686 +Epoch [491/4000] Training [8/16] Loss: 0.01916 +Epoch [491/4000] Training [9/16] Loss: 0.01903 +Epoch [491/4000] Training [10/16] Loss: 0.01173 +Epoch [491/4000] Training [11/16] Loss: 0.02378 +Epoch [491/4000] Training [12/16] Loss: 0.01633 +Epoch [491/4000] Training [13/16] Loss: 0.02038 +Epoch [491/4000] Training [14/16] Loss: 0.01216 +Epoch [491/4000] Training [15/16] Loss: 0.01106 +Epoch [491/4000] Training [16/16] Loss: 0.01788 +Epoch [491/4000] Training metric {'Train/mean dice_metric': 0.9897468686103821, 'Train/mean miou_metric': 0.9795201420783997, 'Train/mean f1': 0.9866796135902405, 'Train/mean precision': 0.9821341633796692, 'Train/mean recall': 0.9912673234939575, 'Train/mean hd95_metric': 1.3556544780731201} +Epoch [491/4000] Validation [1/4] Loss: 0.26371 focal_loss 0.16862 dice_loss 0.09509 +Epoch [491/4000] Validation [2/4] Loss: 0.23192 focal_loss 0.09104 dice_loss 0.14088 +Epoch [491/4000] Validation [3/4] Loss: 0.19099 focal_loss 0.09081 dice_loss 0.10019 +Epoch [491/4000] Validation [4/4] Loss: 0.23123 focal_loss 0.11248 dice_loss 0.11875 +Epoch [491/4000] Validation metric {'Val/mean dice_metric': 0.966683030128479, 'Val/mean miou_metric': 0.9449340105056763, 'Val/mean f1': 0.9681196212768555, 'Val/mean precision': 0.9634364247322083, 'Val/mean recall': 0.972848653793335, 'Val/mean hd95_metric': 6.0117387771606445} +Cheakpoint... +Epoch [491/4000] best acc:tensor([0.9686], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966683030128479, 'Val/mean miou_metric': 0.9449340105056763, 'Val/mean f1': 0.9681196212768555, 'Val/mean precision': 0.9634364247322083, 'Val/mean recall': 0.972848653793335, 'Val/mean hd95_metric': 6.0117387771606445} +Epoch [492/4000] Training [1/16] Loss: 0.01215 +Epoch [492/4000] Training [2/16] Loss: 0.01325 +Epoch [492/4000] Training [3/16] Loss: 0.01542 +Epoch [492/4000] Training [4/16] Loss: 0.01531 +Epoch [492/4000] Training [5/16] Loss: 0.01297 +Epoch [492/4000] Training [6/16] Loss: 0.02454 +Epoch [492/4000] Training [7/16] Loss: 0.02414 +Epoch [492/4000] Training [8/16] Loss: 0.01331 +Epoch [492/4000] Training [9/16] Loss: 0.01332 +Epoch [492/4000] Training [10/16] Loss: 0.01803 +Epoch [492/4000] Training [11/16] Loss: 0.01421 +Epoch [492/4000] Training [12/16] Loss: 0.01214 +Epoch [492/4000] Training [13/16] Loss: 0.01258 +Epoch [492/4000] Training [14/16] Loss: 0.01621 +Epoch [492/4000] Training [15/16] Loss: 0.01312 +Epoch [492/4000] Training [16/16] Loss: 0.01617 +Epoch [492/4000] Training metric {'Train/mean dice_metric': 0.9894481897354126, 'Train/mean miou_metric': 0.9789484143257141, 'Train/mean f1': 0.9864583611488342, 'Train/mean precision': 0.9820008277893066, 'Train/mean recall': 0.9909565448760986, 'Train/mean hd95_metric': 1.406317949295044} +Epoch [492/4000] Validation [1/4] Loss: 0.26677 focal_loss 0.18260 dice_loss 0.08417 +Epoch [492/4000] Validation [2/4] Loss: 0.24845 focal_loss 0.10165 dice_loss 0.14681 +Epoch [492/4000] Validation [3/4] Loss: 0.13514 focal_loss 0.06302 dice_loss 0.07213 +Epoch [492/4000] Validation [4/4] Loss: 0.23205 focal_loss 0.11617 dice_loss 0.11588 +Epoch [492/4000] Validation metric {'Val/mean dice_metric': 0.9686886072158813, 'Val/mean miou_metric': 0.9466506838798523, 'Val/mean f1': 0.9697107076644897, 'Val/mean precision': 0.9628194570541382, 'Val/mean recall': 0.9767013788223267, 'Val/mean hd95_metric': 6.4672651290893555} +Cheakpoint... +Epoch [492/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686886072158813, 'Val/mean miou_metric': 0.9466506838798523, 'Val/mean f1': 0.9697107076644897, 'Val/mean precision': 0.9628194570541382, 'Val/mean recall': 0.9767013788223267, 'Val/mean hd95_metric': 6.4672651290893555} +Epoch [493/4000] Training [1/16] Loss: 0.01504 +Epoch [493/4000] Training [2/16] Loss: 0.01862 +Epoch [493/4000] Training [3/16] Loss: 0.01119 +Epoch [493/4000] Training [4/16] Loss: 0.01548 +Epoch [493/4000] Training [5/16] Loss: 0.01276 +Epoch [493/4000] Training [6/16] Loss: 0.01538 +Epoch [493/4000] Training [7/16] Loss: 0.01233 +Epoch [493/4000] Training [8/16] Loss: 0.01341 +Epoch [493/4000] Training [9/16] Loss: 0.01797 +Epoch [493/4000] Training [10/16] Loss: 0.01675 +Epoch [493/4000] Training [11/16] Loss: 0.01087 +Epoch [493/4000] Training [12/16] Loss: 0.01500 +Epoch [493/4000] Training [13/16] Loss: 0.01361 +Epoch [493/4000] Training [14/16] Loss: 0.01703 +Epoch [493/4000] Training [15/16] Loss: 0.01451 +Epoch [493/4000] Training [16/16] Loss: 0.01588 +Epoch [493/4000] Training metric {'Train/mean dice_metric': 0.9892811179161072, 'Train/mean miou_metric': 0.9786118865013123, 'Train/mean f1': 0.9861811399459839, 'Train/mean precision': 0.9816023111343384, 'Train/mean recall': 0.9908028244972229, 'Train/mean hd95_metric': 1.4130910634994507} +Epoch [493/4000] Validation [1/4] Loss: 0.21765 focal_loss 0.13980 dice_loss 0.07785 +Epoch [493/4000] Validation [2/4] Loss: 0.19022 focal_loss 0.07661 dice_loss 0.11361 +Epoch [493/4000] Validation [3/4] Loss: 0.14600 focal_loss 0.07137 dice_loss 0.07463 +Epoch [493/4000] Validation [4/4] Loss: 0.21404 focal_loss 0.09842 dice_loss 0.11561 +Epoch [493/4000] Validation metric {'Val/mean dice_metric': 0.9680198431015015, 'Val/mean miou_metric': 0.9462941884994507, 'Val/mean f1': 0.9700048565864563, 'Val/mean precision': 0.9650492072105408, 'Val/mean recall': 0.9750115871429443, 'Val/mean hd95_metric': 6.262118339538574} +Cheakpoint... +Epoch [493/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680198431015015, 'Val/mean miou_metric': 0.9462941884994507, 'Val/mean f1': 0.9700048565864563, 'Val/mean precision': 0.9650492072105408, 'Val/mean recall': 0.9750115871429443, 'Val/mean hd95_metric': 6.262118339538574} +Epoch [494/4000] Training [1/16] Loss: 0.01474 +Epoch [494/4000] Training [2/16] Loss: 0.01754 +Epoch [494/4000] Training [3/16] Loss: 0.01209 +Epoch [494/4000] Training [4/16] Loss: 0.01029 +Epoch [494/4000] Training [5/16] Loss: 0.01503 +Epoch [494/4000] Training [6/16] Loss: 0.01339 +Epoch [494/4000] Training [7/16] Loss: 0.01112 +Epoch [494/4000] Training [8/16] Loss: 0.01540 +Epoch [494/4000] Training [9/16] Loss: 0.01774 +Epoch [494/4000] Training [10/16] Loss: 0.01735 +Epoch [494/4000] Training [11/16] Loss: 0.01657 +Epoch [494/4000] Training [12/16] Loss: 0.01504 +Epoch [494/4000] Training [13/16] Loss: 0.01535 +Epoch [494/4000] Training [14/16] Loss: 0.01496 +Epoch [494/4000] Training [15/16] Loss: 0.02422 +Epoch [494/4000] Training [16/16] Loss: 0.01671 +Epoch [494/4000] Training metric {'Train/mean dice_metric': 0.9887170791625977, 'Train/mean miou_metric': 0.9775853753089905, 'Train/mean f1': 0.9861859083175659, 'Train/mean precision': 0.9814236760139465, 'Train/mean recall': 0.9909946322441101, 'Train/mean hd95_metric': 1.4564614295959473} +Epoch [494/4000] Validation [1/4] Loss: 0.16017 focal_loss 0.09274 dice_loss 0.06743 +Epoch [494/4000] Validation [2/4] Loss: 0.25839 focal_loss 0.10735 dice_loss 0.15104 +Epoch [494/4000] Validation [3/4] Loss: 0.10960 focal_loss 0.05052 dice_loss 0.05908 +Epoch [494/4000] Validation [4/4] Loss: 0.23302 focal_loss 0.12485 dice_loss 0.10817 +Epoch [494/4000] Validation metric {'Val/mean dice_metric': 0.9669691920280457, 'Val/mean miou_metric': 0.9450114965438843, 'Val/mean f1': 0.9701889157295227, 'Val/mean precision': 0.9664726853370667, 'Val/mean recall': 0.9739338755607605, 'Val/mean hd95_metric': 5.913478851318359} +Cheakpoint... +Epoch [494/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669691920280457, 'Val/mean miou_metric': 0.9450114965438843, 'Val/mean f1': 0.9701889157295227, 'Val/mean precision': 0.9664726853370667, 'Val/mean recall': 0.9739338755607605, 'Val/mean hd95_metric': 5.913478851318359} +Epoch [495/4000] Training [1/16] Loss: 0.01517 +Epoch [495/4000] Training [2/16] Loss: 0.02045 +Epoch [495/4000] Training [3/16] Loss: 0.01442 +Epoch [495/4000] Training [4/16] Loss: 0.02223 +Epoch [495/4000] Training [5/16] Loss: 0.01692 +Epoch [495/4000] Training [6/16] Loss: 0.01088 +Epoch [495/4000] Training [7/16] Loss: 0.01223 +Epoch [495/4000] Training [8/16] Loss: 0.01450 +Epoch [495/4000] Training [9/16] Loss: 0.01370 +Epoch [495/4000] Training [10/16] Loss: 0.01667 +Epoch [495/4000] Training [11/16] Loss: 0.01341 +Epoch [495/4000] Training [12/16] Loss: 0.01429 +Epoch [495/4000] Training [13/16] Loss: 0.01121 +Epoch [495/4000] Training [14/16] Loss: 0.01514 +Epoch [495/4000] Training [15/16] Loss: 0.01301 +Epoch [495/4000] Training [16/16] Loss: 0.01359 +Epoch [495/4000] Training metric {'Train/mean dice_metric': 0.9893860816955566, 'Train/mean miou_metric': 0.9788091778755188, 'Train/mean f1': 0.9865871071815491, 'Train/mean precision': 0.9819478988647461, 'Train/mean recall': 0.9912703633308411, 'Train/mean hd95_metric': 1.3400928974151611} +Epoch [495/4000] Validation [1/4] Loss: 0.21526 focal_loss 0.13906 dice_loss 0.07620 +Epoch [495/4000] Validation [2/4] Loss: 0.15788 focal_loss 0.05944 dice_loss 0.09844 +Epoch [495/4000] Validation [3/4] Loss: 0.15030 focal_loss 0.07454 dice_loss 0.07576 +Epoch [495/4000] Validation [4/4] Loss: 0.20504 focal_loss 0.09985 dice_loss 0.10519 +Epoch [495/4000] Validation metric {'Val/mean dice_metric': 0.9681499600410461, 'Val/mean miou_metric': 0.9465200304985046, 'Val/mean f1': 0.9700459241867065, 'Val/mean precision': 0.965785562992096, 'Val/mean recall': 0.9743438959121704, 'Val/mean hd95_metric': 6.137206077575684} +Cheakpoint... +Epoch [495/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681499600410461, 'Val/mean miou_metric': 0.9465200304985046, 'Val/mean f1': 0.9700459241867065, 'Val/mean precision': 0.965785562992096, 'Val/mean recall': 0.9743438959121704, 'Val/mean hd95_metric': 6.137206077575684} +Epoch [496/4000] Training [1/16] Loss: 0.01283 +Epoch [496/4000] Training [2/16] Loss: 0.01877 +Epoch [496/4000] Training [3/16] Loss: 0.01458 +Epoch [496/4000] Training [4/16] Loss: 0.05975 +Epoch [496/4000] Training [5/16] Loss: 0.01572 +Epoch [496/4000] Training [6/16] Loss: 0.01443 +Epoch [496/4000] Training [7/16] Loss: 0.01727 +Epoch [496/4000] Training [8/16] Loss: 0.01625 +Epoch [496/4000] Training [9/16] Loss: 0.01444 +Epoch [496/4000] Training [10/16] Loss: 0.01772 +Epoch [496/4000] Training [11/16] Loss: 0.01642 +Epoch [496/4000] Training [12/16] Loss: 0.01279 +Epoch [496/4000] Training [13/16] Loss: 0.01552 +Epoch [496/4000] Training [14/16] Loss: 0.01522 +Epoch [496/4000] Training [15/16] Loss: 0.01671 +Epoch [496/4000] Training [16/16] Loss: 0.01636 +Epoch [496/4000] Training metric {'Train/mean dice_metric': 0.9883617162704468, 'Train/mean miou_metric': 0.9770315289497375, 'Train/mean f1': 0.9859187602996826, 'Train/mean precision': 0.9813736081123352, 'Train/mean recall': 0.9905061721801758, 'Train/mean hd95_metric': 1.620408296585083} +Epoch [496/4000] Validation [1/4] Loss: 0.20666 focal_loss 0.12710 dice_loss 0.07956 +Epoch [496/4000] Validation [2/4] Loss: 0.26138 focal_loss 0.10937 dice_loss 0.15201 +Epoch [496/4000] Validation [3/4] Loss: 0.13661 focal_loss 0.06814 dice_loss 0.06847 +Epoch [496/4000] Validation [4/4] Loss: 0.19728 focal_loss 0.08726 dice_loss 0.11001 +Epoch [496/4000] Validation metric {'Val/mean dice_metric': 0.9659246206283569, 'Val/mean miou_metric': 0.9437534213066101, 'Val/mean f1': 0.9684991836547852, 'Val/mean precision': 0.9624947905540466, 'Val/mean recall': 0.9745789170265198, 'Val/mean hd95_metric': 6.4841413497924805} +Cheakpoint... +Epoch [496/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659246206283569, 'Val/mean miou_metric': 0.9437534213066101, 'Val/mean f1': 0.9684991836547852, 'Val/mean precision': 0.9624947905540466, 'Val/mean recall': 0.9745789170265198, 'Val/mean hd95_metric': 6.4841413497924805} +Epoch [497/4000] Training [1/16] Loss: 0.01314 +Epoch [497/4000] Training [2/16] Loss: 0.02292 +Epoch [497/4000] Training [3/16] Loss: 0.01715 +Epoch [497/4000] Training [4/16] Loss: 0.01671 +Epoch [497/4000] Training [5/16] Loss: 0.01754 +Epoch [497/4000] Training [6/16] Loss: 0.01291 +Epoch [497/4000] Training [7/16] Loss: 0.01677 +Epoch [497/4000] Training [8/16] Loss: 0.01350 +Epoch [497/4000] Training [9/16] Loss: 0.01749 +Epoch [497/4000] Training [10/16] Loss: 0.01650 +Epoch [497/4000] Training [11/16] Loss: 0.01800 +Epoch [497/4000] Training [12/16] Loss: 0.01383 +Epoch [497/4000] Training [13/16] Loss: 0.08534 +Epoch [497/4000] Training [14/16] Loss: 0.01639 +Epoch [497/4000] Training [15/16] Loss: 0.02187 +Epoch [497/4000] Training [16/16] Loss: 0.01954 +Epoch [497/4000] Training metric {'Train/mean dice_metric': 0.9866930246353149, 'Train/mean miou_metric': 0.9742072224617004, 'Train/mean f1': 0.9849720597267151, 'Train/mean precision': 0.9799525141716003, 'Train/mean recall': 0.9900432229042053, 'Train/mean hd95_metric': 1.9434326887130737} +Epoch [497/4000] Validation [1/4] Loss: 0.47449 focal_loss 0.36656 dice_loss 0.10792 +Epoch [497/4000] Validation [2/4] Loss: 0.23496 focal_loss 0.10174 dice_loss 0.13322 +Epoch [497/4000] Validation [3/4] Loss: 0.27841 focal_loss 0.15150 dice_loss 0.12691 +Epoch [497/4000] Validation [4/4] Loss: 0.20507 focal_loss 0.10071 dice_loss 0.10436 +Epoch [497/4000] Validation metric {'Val/mean dice_metric': 0.9632645845413208, 'Val/mean miou_metric': 0.9404674768447876, 'Val/mean f1': 0.9673110842704773, 'Val/mean precision': 0.9623394012451172, 'Val/mean recall': 0.9723344445228577, 'Val/mean hd95_metric': 6.802903652191162} +Cheakpoint... +Epoch [497/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632645845413208, 'Val/mean miou_metric': 0.9404674768447876, 'Val/mean f1': 0.9673110842704773, 'Val/mean precision': 0.9623394012451172, 'Val/mean recall': 0.9723344445228577, 'Val/mean hd95_metric': 6.802903652191162} +Epoch [498/4000] Training [1/16] Loss: 0.01170 +Epoch [498/4000] Training [2/16] Loss: 0.02080 +Epoch [498/4000] Training [3/16] Loss: 0.01656 +Epoch [498/4000] Training [4/16] Loss: 0.01605 +Epoch [498/4000] Training [5/16] Loss: 0.01260 +Epoch [498/4000] Training [6/16] Loss: 0.01997 +Epoch [498/4000] Training [7/16] Loss: 0.01366 +Epoch [498/4000] Training [8/16] Loss: 0.01654 +Epoch [498/4000] Training [9/16] Loss: 0.01956 +Epoch [498/4000] Training [10/16] Loss: 0.01381 +Epoch [498/4000] Training [11/16] Loss: 0.03324 +Epoch [498/4000] Training [12/16] Loss: 0.01375 +Epoch [498/4000] Training [13/16] Loss: 0.01739 +Epoch [498/4000] Training [14/16] Loss: 0.01998 +Epoch [498/4000] Training [15/16] Loss: 0.01591 +Epoch [498/4000] Training [16/16] Loss: 0.01767 +Epoch [498/4000] Training metric {'Train/mean dice_metric': 0.9886662364006042, 'Train/mean miou_metric': 0.977493166923523, 'Train/mean f1': 0.986179530620575, 'Train/mean precision': 0.981853187084198, 'Train/mean recall': 0.9905441403388977, 'Train/mean hd95_metric': 1.5521305799484253} +Epoch [498/4000] Validation [1/4] Loss: 0.39071 focal_loss 0.28825 dice_loss 0.10246 +Epoch [498/4000] Validation [2/4] Loss: 0.22095 focal_loss 0.07899 dice_loss 0.14196 +Epoch [498/4000] Validation [3/4] Loss: 0.13338 focal_loss 0.05944 dice_loss 0.07395 +Epoch [498/4000] Validation [4/4] Loss: 0.20328 focal_loss 0.10635 dice_loss 0.09693 +Epoch [498/4000] Validation metric {'Val/mean dice_metric': 0.9660872220993042, 'Val/mean miou_metric': 0.9439183473587036, 'Val/mean f1': 0.9685975909233093, 'Val/mean precision': 0.9658467173576355, 'Val/mean recall': 0.9713642001152039, 'Val/mean hd95_metric': 6.359894752502441} +Cheakpoint... +Epoch [498/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660872220993042, 'Val/mean miou_metric': 0.9439183473587036, 'Val/mean f1': 0.9685975909233093, 'Val/mean precision': 0.9658467173576355, 'Val/mean recall': 0.9713642001152039, 'Val/mean hd95_metric': 6.359894752502441} +Epoch [499/4000] Training [1/16] Loss: 0.01931 +Epoch [499/4000] Training [2/16] Loss: 0.01620 +Epoch [499/4000] Training [3/16] Loss: 0.01339 +Epoch [499/4000] Training [4/16] Loss: 0.01123 +Epoch [499/4000] Training [5/16] Loss: 0.01475 +Epoch [499/4000] Training [6/16] Loss: 0.03386 +Epoch [499/4000] Training [7/16] Loss: 0.01798 +Epoch [499/4000] Training [8/16] Loss: 0.01434 +Epoch [499/4000] Training [9/16] Loss: 0.01706 +Epoch [499/4000] Training [10/16] Loss: 0.01382 +Epoch [499/4000] Training [11/16] Loss: 0.02967 +Epoch [499/4000] Training [12/16] Loss: 0.01746 +Epoch [499/4000] Training [13/16] Loss: 0.01476 +Epoch [499/4000] Training [14/16] Loss: 0.02665 +Epoch [499/4000] Training [15/16] Loss: 0.01959 +Epoch [499/4000] Training [16/16] Loss: 0.01358 +Epoch [499/4000] Training metric {'Train/mean dice_metric': 0.9867573976516724, 'Train/mean miou_metric': 0.974808931350708, 'Train/mean f1': 0.9854505658149719, 'Train/mean precision': 0.9806013703346252, 'Train/mean recall': 0.9903479218482971, 'Train/mean hd95_metric': 1.830635666847229} +Epoch [499/4000] Validation [1/4] Loss: 0.47760 focal_loss 0.36266 dice_loss 0.11493 +Epoch [499/4000] Validation [2/4] Loss: 0.42229 focal_loss 0.19765 dice_loss 0.22464 +Epoch [499/4000] Validation [3/4] Loss: 0.19228 focal_loss 0.09173 dice_loss 0.10056 +Epoch [499/4000] Validation [4/4] Loss: 0.14523 focal_loss 0.06272 dice_loss 0.08250 +Epoch [499/4000] Validation metric {'Val/mean dice_metric': 0.9623268246650696, 'Val/mean miou_metric': 0.9395910501480103, 'Val/mean f1': 0.9669467210769653, 'Val/mean precision': 0.9636133909225464, 'Val/mean recall': 0.9703029990196228, 'Val/mean hd95_metric': 6.7683539390563965} +Cheakpoint... +Epoch [499/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9623], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9623268246650696, 'Val/mean miou_metric': 0.9395910501480103, 'Val/mean f1': 0.9669467210769653, 'Val/mean precision': 0.9636133909225464, 'Val/mean recall': 0.9703029990196228, 'Val/mean hd95_metric': 6.7683539390563965} +Epoch [500/4000] Training [1/16] Loss: 0.01543 +Epoch [500/4000] Training [2/16] Loss: 0.01482 +Epoch [500/4000] Training [3/16] Loss: 0.01094 +Epoch [500/4000] Training [4/16] Loss: 0.01656 +Epoch [500/4000] Training [5/16] Loss: 0.01118 +Epoch [500/4000] Training [6/16] Loss: 0.01648 +Epoch [500/4000] Training [7/16] Loss: 0.01177 +Epoch [500/4000] Training [8/16] Loss: 0.01269 +Epoch [500/4000] Training [9/16] Loss: 0.01665 +Epoch [500/4000] Training [10/16] Loss: 0.01498 +Epoch [500/4000] Training [11/16] Loss: 0.01411 +Epoch [500/4000] Training [12/16] Loss: 0.01379 +Epoch [500/4000] Training [13/16] Loss: 0.01521 +Epoch [500/4000] Training [14/16] Loss: 0.01469 +Epoch [500/4000] Training [15/16] Loss: 0.01598 +Epoch [500/4000] Training [16/16] Loss: 0.01708 +Epoch [500/4000] Training metric {'Train/mean dice_metric': 0.9889955520629883, 'Train/mean miou_metric': 0.9781694412231445, 'Train/mean f1': 0.9860120415687561, 'Train/mean precision': 0.9817901253700256, 'Train/mean recall': 0.9902703762054443, 'Train/mean hd95_metric': 1.729508876800537} +Epoch [500/4000] Validation [1/4] Loss: 0.39864 focal_loss 0.28369 dice_loss 0.11495 +Epoch [500/4000] Validation [2/4] Loss: 0.12770 focal_loss 0.04028 dice_loss 0.08742 +Epoch [500/4000] Validation [3/4] Loss: 0.13368 focal_loss 0.05892 dice_loss 0.07476 +Epoch [500/4000] Validation [4/4] Loss: 0.20097 focal_loss 0.09226 dice_loss 0.10870 +Epoch [500/4000] Validation metric {'Val/mean dice_metric': 0.9640130996704102, 'Val/mean miou_metric': 0.9411934018135071, 'Val/mean f1': 0.965065598487854, 'Val/mean precision': 0.9602470993995667, 'Val/mean recall': 0.9699326753616333, 'Val/mean hd95_metric': 7.311953544616699} +Cheakpoint... +Epoch [500/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640130996704102, 'Val/mean miou_metric': 0.9411934018135071, 'Val/mean f1': 0.965065598487854, 'Val/mean precision': 0.9602470993995667, 'Val/mean recall': 0.9699326753616333, 'Val/mean hd95_metric': 7.311953544616699} +Epoch [501/4000] Training [1/16] Loss: 0.01330 +Epoch [501/4000] Training [2/16] Loss: 0.01407 +Epoch [501/4000] Training [3/16] Loss: 0.01917 +Epoch [501/4000] Training [4/16] Loss: 0.01328 +Epoch [501/4000] Training [5/16] Loss: 0.01537 +Epoch [501/4000] Training [6/16] Loss: 0.01251 +Epoch [501/4000] Training [7/16] Loss: 0.01473 +Epoch [501/4000] Training [8/16] Loss: 0.04223 +Epoch [501/4000] Training [9/16] Loss: 0.01630 +Epoch [501/4000] Training [10/16] Loss: 0.01776 +Epoch [501/4000] Training [11/16] Loss: 0.01013 +Epoch [501/4000] Training [12/16] Loss: 0.01536 +Epoch [501/4000] Training [13/16] Loss: 0.01443 +Epoch [501/4000] Training [14/16] Loss: 0.01362 +Epoch [501/4000] Training [15/16] Loss: 0.01959 +Epoch [501/4000] Training [16/16] Loss: 0.01365 +Epoch [501/4000] Training metric {'Train/mean dice_metric': 0.9896557331085205, 'Train/mean miou_metric': 0.9794221520423889, 'Train/mean f1': 0.9868445992469788, 'Train/mean precision': 0.9820927381515503, 'Train/mean recall': 0.9916427135467529, 'Train/mean hd95_metric': 1.325779676437378} +Epoch [501/4000] Validation [1/4] Loss: 0.30104 focal_loss 0.21047 dice_loss 0.09057 +Epoch [501/4000] Validation [2/4] Loss: 0.31802 focal_loss 0.15716 dice_loss 0.16087 +Epoch [501/4000] Validation [3/4] Loss: 0.21696 focal_loss 0.12447 dice_loss 0.09249 +Epoch [501/4000] Validation [4/4] Loss: 0.17154 focal_loss 0.07062 dice_loss 0.10092 +Epoch [501/4000] Validation metric {'Val/mean dice_metric': 0.9650963544845581, 'Val/mean miou_metric': 0.9428442716598511, 'Val/mean f1': 0.9663282036781311, 'Val/mean precision': 0.9569127559661865, 'Val/mean recall': 0.9759306907653809, 'Val/mean hd95_metric': 7.170691013336182} +Cheakpoint... +Epoch [501/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650963544845581, 'Val/mean miou_metric': 0.9428442716598511, 'Val/mean f1': 0.9663282036781311, 'Val/mean precision': 0.9569127559661865, 'Val/mean recall': 0.9759306907653809, 'Val/mean hd95_metric': 7.170691013336182} +Epoch [502/4000] Training [1/16] Loss: 0.01112 +Epoch [502/4000] Training [2/16] Loss: 0.01838 +Epoch [502/4000] Training [3/16] Loss: 0.01254 +Epoch [502/4000] Training [4/16] Loss: 0.01045 +Epoch [502/4000] Training [5/16] Loss: 0.01304 +Epoch [502/4000] Training [6/16] Loss: 0.01822 +Epoch [502/4000] Training [7/16] Loss: 0.01716 +Epoch [502/4000] Training [8/16] Loss: 0.01588 +Epoch [502/4000] Training [9/16] Loss: 0.01466 +Epoch [502/4000] Training [10/16] Loss: 0.02520 +Epoch [502/4000] Training [11/16] Loss: 0.02196 +Epoch [502/4000] Training [12/16] Loss: 0.01373 +Epoch [502/4000] Training [13/16] Loss: 0.01777 +Epoch [502/4000] Training [14/16] Loss: 0.04121 +Epoch [502/4000] Training [15/16] Loss: 0.03949 +Epoch [502/4000] Training [16/16] Loss: 0.01163 +Epoch [502/4000] Training metric {'Train/mean dice_metric': 0.9873983860015869, 'Train/mean miou_metric': 0.9752449989318848, 'Train/mean f1': 0.9851254224777222, 'Train/mean precision': 0.9801560640335083, 'Train/mean recall': 0.9901454448699951, 'Train/mean hd95_metric': 2.014986991882324} +Epoch [502/4000] Validation [1/4] Loss: 0.39328 focal_loss 0.27962 dice_loss 0.11366 +Epoch [502/4000] Validation [2/4] Loss: 0.46141 focal_loss 0.24488 dice_loss 0.21653 +Epoch [502/4000] Validation [3/4] Loss: 0.14685 focal_loss 0.06499 dice_loss 0.08186 +Epoch [502/4000] Validation [4/4] Loss: 0.28132 focal_loss 0.15478 dice_loss 0.12654 +Epoch [502/4000] Validation metric {'Val/mean dice_metric': 0.9622284770011902, 'Val/mean miou_metric': 0.9385223388671875, 'Val/mean f1': 0.9647281169891357, 'Val/mean precision': 0.9639583230018616, 'Val/mean recall': 0.9654991626739502, 'Val/mean hd95_metric': 7.754705429077148} +Cheakpoint... +Epoch [502/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622284770011902, 'Val/mean miou_metric': 0.9385223388671875, 'Val/mean f1': 0.9647281169891357, 'Val/mean precision': 0.9639583230018616, 'Val/mean recall': 0.9654991626739502, 'Val/mean hd95_metric': 7.754705429077148} +Epoch [503/4000] Training [1/16] Loss: 0.01627 +Epoch [503/4000] Training [2/16] Loss: 0.02542 +Epoch [503/4000] Training [3/16] Loss: 0.01524 +Epoch [503/4000] Training [4/16] Loss: 0.01428 +Epoch [503/4000] Training [5/16] Loss: 0.01264 +Epoch [503/4000] Training [6/16] Loss: 0.04073 +Epoch [503/4000] Training [7/16] Loss: 0.01712 +Epoch [503/4000] Training [8/16] Loss: 0.01969 +Epoch [503/4000] Training [9/16] Loss: 0.01144 +Epoch [503/4000] Training [10/16] Loss: 0.01735 +Epoch [503/4000] Training [11/16] Loss: 0.02107 +Epoch [503/4000] Training [12/16] Loss: 0.01498 +Epoch [503/4000] Training [13/16] Loss: 0.01179 +Epoch [503/4000] Training [14/16] Loss: 0.01354 +Epoch [503/4000] Training [15/16] Loss: 0.01445 +Epoch [503/4000] Training [16/16] Loss: 0.01505 +Epoch [503/4000] Training metric {'Train/mean dice_metric': 0.9885962009429932, 'Train/mean miou_metric': 0.977321207523346, 'Train/mean f1': 0.9847593307495117, 'Train/mean precision': 0.9798584580421448, 'Train/mean recall': 0.9897094368934631, 'Train/mean hd95_metric': 1.824765682220459} +Epoch [503/4000] Validation [1/4] Loss: 0.14031 focal_loss 0.07933 dice_loss 0.06099 +Epoch [503/4000] Validation [2/4] Loss: 0.36478 focal_loss 0.17860 dice_loss 0.18618 +Epoch [503/4000] Validation [3/4] Loss: 0.23831 focal_loss 0.11966 dice_loss 0.11864 +Epoch [503/4000] Validation [4/4] Loss: 0.27347 focal_loss 0.13337 dice_loss 0.14011 +Epoch [503/4000] Validation metric {'Val/mean dice_metric': 0.9640275835990906, 'Val/mean miou_metric': 0.9413649439811707, 'Val/mean f1': 0.9669216871261597, 'Val/mean precision': 0.9581135511398315, 'Val/mean recall': 0.9758931994438171, 'Val/mean hd95_metric': 7.178694725036621} +Cheakpoint... +Epoch [503/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640275835990906, 'Val/mean miou_metric': 0.9413649439811707, 'Val/mean f1': 0.9669216871261597, 'Val/mean precision': 0.9581135511398315, 'Val/mean recall': 0.9758931994438171, 'Val/mean hd95_metric': 7.178694725036621} +Epoch [504/4000] Training [1/16] Loss: 0.01866 +Epoch [504/4000] Training [2/16] Loss: 0.01366 +Epoch [504/4000] Training [3/16] Loss: 0.01224 +Epoch [504/4000] Training [4/16] Loss: 0.01541 +Epoch [504/4000] Training [5/16] Loss: 0.01311 +Epoch [504/4000] Training [6/16] Loss: 0.01529 +Epoch [504/4000] Training [7/16] Loss: 0.01242 +Epoch [504/4000] Training [8/16] Loss: 0.01613 +Epoch [504/4000] Training [9/16] Loss: 0.01387 +Epoch [504/4000] Training [10/16] Loss: 0.01718 +Epoch [504/4000] Training [11/16] Loss: 0.01609 +Epoch [504/4000] Training [12/16] Loss: 0.02177 +Epoch [504/4000] Training [13/16] Loss: 0.01330 +Epoch [504/4000] Training [14/16] Loss: 0.02351 +Epoch [504/4000] Training [15/16] Loss: 0.02662 +Epoch [504/4000] Training [16/16] Loss: 0.01248 +Epoch [504/4000] Training metric {'Train/mean dice_metric': 0.9852167367935181, 'Train/mean miou_metric': 0.9727963209152222, 'Train/mean f1': 0.9847075939178467, 'Train/mean precision': 0.9805200099945068, 'Train/mean recall': 0.9889310598373413, 'Train/mean hd95_metric': 2.428812265396118} +Epoch [504/4000] Validation [1/4] Loss: 0.31863 focal_loss 0.21019 dice_loss 0.10844 +Epoch [504/4000] Validation [2/4] Loss: 0.26555 focal_loss 0.10136 dice_loss 0.16419 +Epoch [504/4000] Validation [3/4] Loss: 0.15334 focal_loss 0.06677 dice_loss 0.08657 +Epoch [504/4000] Validation [4/4] Loss: 0.24193 focal_loss 0.14063 dice_loss 0.10130 +Epoch [504/4000] Validation metric {'Val/mean dice_metric': 0.9612614512443542, 'Val/mean miou_metric': 0.9384322166442871, 'Val/mean f1': 0.9666836857795715, 'Val/mean precision': 0.9641172289848328, 'Val/mean recall': 0.9692639708518982, 'Val/mean hd95_metric': 7.609343528747559} +Cheakpoint... +Epoch [504/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612614512443542, 'Val/mean miou_metric': 0.9384322166442871, 'Val/mean f1': 0.9666836857795715, 'Val/mean precision': 0.9641172289848328, 'Val/mean recall': 0.9692639708518982, 'Val/mean hd95_metric': 7.609343528747559} +Epoch [505/4000] Training [1/16] Loss: 0.01517 +Epoch [505/4000] Training [2/16] Loss: 0.01541 +Epoch [505/4000] Training [3/16] Loss: 0.01913 +Epoch [505/4000] Training [4/16] Loss: 0.02421 +Epoch [505/4000] Training [5/16] Loss: 0.01743 +Epoch [505/4000] Training [6/16] Loss: 0.01477 +Epoch [505/4000] Training [7/16] Loss: 0.01298 +Epoch [505/4000] Training [8/16] Loss: 0.01703 +Epoch [505/4000] Training [9/16] Loss: 0.02668 +Epoch [505/4000] Training [10/16] Loss: 0.01404 +Epoch [505/4000] Training [11/16] Loss: 0.01693 +Epoch [505/4000] Training [12/16] Loss: 0.02609 +Epoch [505/4000] Training [13/16] Loss: 0.01563 +Epoch [505/4000] Training [14/16] Loss: 0.02701 +Epoch [505/4000] Training [15/16] Loss: 0.01920 +Epoch [505/4000] Training [16/16] Loss: 0.01905 +Epoch [505/4000] Training metric {'Train/mean dice_metric': 0.9872685670852661, 'Train/mean miou_metric': 0.9748451709747314, 'Train/mean f1': 0.9846577048301697, 'Train/mean precision': 0.9797182083129883, 'Train/mean recall': 0.9896472692489624, 'Train/mean hd95_metric': 1.9341418743133545} +Epoch [505/4000] Validation [1/4] Loss: 0.46862 focal_loss 0.34839 dice_loss 0.12023 +Epoch [505/4000] Validation [2/4] Loss: 0.36227 focal_loss 0.18594 dice_loss 0.17633 +Epoch [505/4000] Validation [3/4] Loss: 0.12048 focal_loss 0.06010 dice_loss 0.06038 +Epoch [505/4000] Validation [4/4] Loss: 0.21138 focal_loss 0.10989 dice_loss 0.10149 +Epoch [505/4000] Validation metric {'Val/mean dice_metric': 0.9625616073608398, 'Val/mean miou_metric': 0.9387710690498352, 'Val/mean f1': 0.96304851770401, 'Val/mean precision': 0.9586617946624756, 'Val/mean recall': 0.9674757122993469, 'Val/mean hd95_metric': 7.150689601898193} +Cheakpoint... +Epoch [505/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9626], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625616073608398, 'Val/mean miou_metric': 0.9387710690498352, 'Val/mean f1': 0.96304851770401, 'Val/mean precision': 0.9586617946624756, 'Val/mean recall': 0.9674757122993469, 'Val/mean hd95_metric': 7.150689601898193} +Epoch [506/4000] Training [1/16] Loss: 0.01226 +Epoch [506/4000] Training [2/16] Loss: 0.01647 +Epoch [506/4000] Training [3/16] Loss: 0.01955 +Epoch [506/4000] Training [4/16] Loss: 0.01754 +Epoch [506/4000] Training [5/16] Loss: 0.01247 +Epoch [506/4000] Training [6/16] Loss: 0.01122 +Epoch [506/4000] Training [7/16] Loss: 0.01832 +Epoch [506/4000] Training [8/16] Loss: 0.01504 +Epoch [506/4000] Training [9/16] Loss: 0.01363 +Epoch [506/4000] Training [10/16] Loss: 0.01609 +Epoch [506/4000] Training [11/16] Loss: 0.02252 +Epoch [506/4000] Training [12/16] Loss: 0.01543 +Epoch [506/4000] Training [13/16] Loss: 0.01701 +Epoch [506/4000] Training [14/16] Loss: 0.01250 +Epoch [506/4000] Training [15/16] Loss: 0.01711 +Epoch [506/4000] Training [16/16] Loss: 0.01658 +Epoch [506/4000] Training metric {'Train/mean dice_metric': 0.98888099193573, 'Train/mean miou_metric': 0.9778990745544434, 'Train/mean f1': 0.9863100647926331, 'Train/mean precision': 0.9818208813667297, 'Train/mean recall': 0.9908404350280762, 'Train/mean hd95_metric': 1.7806220054626465} +Epoch [506/4000] Validation [1/4] Loss: 0.24465 focal_loss 0.15267 dice_loss 0.09198 +Epoch [506/4000] Validation [2/4] Loss: 0.58580 focal_loss 0.30870 dice_loss 0.27710 +Epoch [506/4000] Validation [3/4] Loss: 0.12351 focal_loss 0.06100 dice_loss 0.06251 +Epoch [506/4000] Validation [4/4] Loss: 0.21520 focal_loss 0.11170 dice_loss 0.10350 +Epoch [506/4000] Validation metric {'Val/mean dice_metric': 0.9661199450492859, 'Val/mean miou_metric': 0.9435332417488098, 'Val/mean f1': 0.9679449200630188, 'Val/mean precision': 0.9632366299629211, 'Val/mean recall': 0.9726994633674622, 'Val/mean hd95_metric': 6.519415855407715} +Cheakpoint... +Epoch [506/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661199450492859, 'Val/mean miou_metric': 0.9435332417488098, 'Val/mean f1': 0.9679449200630188, 'Val/mean precision': 0.9632366299629211, 'Val/mean recall': 0.9726994633674622, 'Val/mean hd95_metric': 6.519415855407715} +Epoch [507/4000] Training [1/16] Loss: 0.01304 +Epoch [507/4000] Training [2/16] Loss: 0.01642 +Epoch [507/4000] Training [3/16] Loss: 0.01222 +Epoch [507/4000] Training [4/16] Loss: 0.01712 +Epoch [507/4000] Training [5/16] Loss: 0.01242 +Epoch [507/4000] Training [6/16] Loss: 0.01089 +Epoch [507/4000] Training [7/16] Loss: 0.01147 +Epoch [507/4000] Training [8/16] Loss: 0.01520 +Epoch [507/4000] Training [9/16] Loss: 0.02131 +Epoch [507/4000] Training [10/16] Loss: 0.02424 +Epoch [507/4000] Training [11/16] Loss: 0.01126 +Epoch [507/4000] Training [12/16] Loss: 0.01370 +Epoch [507/4000] Training [13/16] Loss: 0.01271 +Epoch [507/4000] Training [14/16] Loss: 0.01298 +Epoch [507/4000] Training [15/16] Loss: 0.01436 +Epoch [507/4000] Training [16/16] Loss: 0.02530 +Epoch [507/4000] Training metric {'Train/mean dice_metric': 0.9895153641700745, 'Train/mean miou_metric': 0.9791145324707031, 'Train/mean f1': 0.9867038726806641, 'Train/mean precision': 0.9820468425750732, 'Train/mean recall': 0.991405189037323, 'Train/mean hd95_metric': 1.743335485458374} +Epoch [507/4000] Validation [1/4] Loss: 0.14714 focal_loss 0.08736 dice_loss 0.05978 +Epoch [507/4000] Validation [2/4] Loss: 0.25305 focal_loss 0.11524 dice_loss 0.13781 +Epoch [507/4000] Validation [3/4] Loss: 0.13222 focal_loss 0.06466 dice_loss 0.06757 +Epoch [507/4000] Validation [4/4] Loss: 0.21509 focal_loss 0.12384 dice_loss 0.09125 +Epoch [507/4000] Validation metric {'Val/mean dice_metric': 0.9648793935775757, 'Val/mean miou_metric': 0.9433048963546753, 'Val/mean f1': 0.967288613319397, 'Val/mean precision': 0.9658929705619812, 'Val/mean recall': 0.9686883687973022, 'Val/mean hd95_metric': 6.730433464050293} +Cheakpoint... +Epoch [507/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648793935775757, 'Val/mean miou_metric': 0.9433048963546753, 'Val/mean f1': 0.967288613319397, 'Val/mean precision': 0.9658929705619812, 'Val/mean recall': 0.9686883687973022, 'Val/mean hd95_metric': 6.730433464050293} +Epoch [508/4000] Training [1/16] Loss: 0.01561 +Epoch [508/4000] Training [2/16] Loss: 0.02180 +Epoch [508/4000] Training [3/16] Loss: 0.01312 +Epoch [508/4000] Training [4/16] Loss: 0.01447 +Epoch [508/4000] Training [5/16] Loss: 0.01685 +Epoch [508/4000] Training [6/16] Loss: 0.01089 +Epoch [508/4000] Training [7/16] Loss: 0.01566 +Epoch [508/4000] Training [8/16] Loss: 0.01171 +Epoch [508/4000] Training [9/16] Loss: 0.01693 +Epoch [508/4000] Training [10/16] Loss: 0.01544 +Epoch [508/4000] Training [11/16] Loss: 0.01371 +Epoch [508/4000] Training [12/16] Loss: 0.01183 +Epoch [508/4000] Training [13/16] Loss: 0.01242 +Epoch [508/4000] Training [14/16] Loss: 0.01084 +Epoch [508/4000] Training [15/16] Loss: 0.01363 +Epoch [508/4000] Training [16/16] Loss: 0.01327 +Epoch [508/4000] Training metric {'Train/mean dice_metric': 0.990114688873291, 'Train/mean miou_metric': 0.9802417755126953, 'Train/mean f1': 0.9871473908424377, 'Train/mean precision': 0.9826864004135132, 'Train/mean recall': 0.9916490316390991, 'Train/mean hd95_metric': 1.3108851909637451} +Epoch [508/4000] Validation [1/4] Loss: 0.26242 focal_loss 0.16807 dice_loss 0.09434 +Epoch [508/4000] Validation [2/4] Loss: 0.24621 focal_loss 0.11155 dice_loss 0.13466 +Epoch [508/4000] Validation [3/4] Loss: 0.13074 focal_loss 0.06602 dice_loss 0.06472 +Epoch [508/4000] Validation [4/4] Loss: 0.19758 focal_loss 0.10730 dice_loss 0.09028 +Epoch [508/4000] Validation metric {'Val/mean dice_metric': 0.9665396809577942, 'Val/mean miou_metric': 0.9456623792648315, 'Val/mean f1': 0.9698867201805115, 'Val/mean precision': 0.9684075117111206, 'Val/mean recall': 0.9713704586029053, 'Val/mean hd95_metric': 5.927656173706055} +Cheakpoint... +Epoch [508/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665396809577942, 'Val/mean miou_metric': 0.9456623792648315, 'Val/mean f1': 0.9698867201805115, 'Val/mean precision': 0.9684075117111206, 'Val/mean recall': 0.9713704586029053, 'Val/mean hd95_metric': 5.927656173706055} +Epoch [509/4000] Training [1/16] Loss: 0.01196 +Epoch [509/4000] Training [2/16] Loss: 0.01332 +Epoch [509/4000] Training [3/16] Loss: 0.01023 +Epoch [509/4000] Training [4/16] Loss: 0.01347 +Epoch [509/4000] Training [5/16] Loss: 0.01170 +Epoch [509/4000] Training [6/16] Loss: 0.01050 +Epoch [509/4000] Training [7/16] Loss: 0.01884 +Epoch [509/4000] Training [8/16] Loss: 0.01233 +Epoch [509/4000] Training [9/16] Loss: 0.02772 +Epoch [509/4000] Training [10/16] Loss: 0.01607 +Epoch [509/4000] Training [11/16] Loss: 0.01502 +Epoch [509/4000] Training [12/16] Loss: 0.01460 +Epoch [509/4000] Training [13/16] Loss: 0.01524 +Epoch [509/4000] Training [14/16] Loss: 0.01809 +Epoch [509/4000] Training [15/16] Loss: 0.01472 +Epoch [509/4000] Training [16/16] Loss: 0.01245 +Epoch [509/4000] Training metric {'Train/mean dice_metric': 0.9898877143859863, 'Train/mean miou_metric': 0.979838490486145, 'Train/mean f1': 0.9870693683624268, 'Train/mean precision': 0.982724666595459, 'Train/mean recall': 0.9914526343345642, 'Train/mean hd95_metric': 1.7647254467010498} +Epoch [509/4000] Validation [1/4] Loss: 0.47830 focal_loss 0.35457 dice_loss 0.12373 +Epoch [509/4000] Validation [2/4] Loss: 0.27265 focal_loss 0.12116 dice_loss 0.15149 +Epoch [509/4000] Validation [3/4] Loss: 0.14680 focal_loss 0.06775 dice_loss 0.07906 +Epoch [509/4000] Validation [4/4] Loss: 0.20460 focal_loss 0.09902 dice_loss 0.10558 +Epoch [509/4000] Validation metric {'Val/mean dice_metric': 0.9655787348747253, 'Val/mean miou_metric': 0.9433878064155579, 'Val/mean f1': 0.9679825305938721, 'Val/mean precision': 0.9652695655822754, 'Val/mean recall': 0.970710813999176, 'Val/mean hd95_metric': 6.046473979949951} +Cheakpoint... +Epoch [509/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655787348747253, 'Val/mean miou_metric': 0.9433878064155579, 'Val/mean f1': 0.9679825305938721, 'Val/mean precision': 0.9652695655822754, 'Val/mean recall': 0.970710813999176, 'Val/mean hd95_metric': 6.046473979949951} +Epoch [510/4000] Training [1/16] Loss: 0.01671 +Epoch [510/4000] Training [2/16] Loss: 0.01296 +Epoch [510/4000] Training [3/16] Loss: 0.01477 +Epoch [510/4000] Training [4/16] Loss: 0.01228 +Epoch [510/4000] Training [5/16] Loss: 0.01379 +Epoch [510/4000] Training [6/16] Loss: 0.01430 +Epoch [510/4000] Training [7/16] Loss: 0.01326 +Epoch [510/4000] Training [8/16] Loss: 0.01232 +Epoch [510/4000] Training [9/16] Loss: 0.01552 +Epoch [510/4000] Training [10/16] Loss: 0.01484 +Epoch [510/4000] Training [11/16] Loss: 0.01383 +Epoch [510/4000] Training [12/16] Loss: 0.01799 +Epoch [510/4000] Training [13/16] Loss: 0.01425 +Epoch [510/4000] Training [14/16] Loss: 0.01191 +Epoch [510/4000] Training [15/16] Loss: 0.01958 +Epoch [510/4000] Training [16/16] Loss: 0.01147 +Epoch [510/4000] Training metric {'Train/mean dice_metric': 0.9897652268409729, 'Train/mean miou_metric': 0.9795762300491333, 'Train/mean f1': 0.986625611782074, 'Train/mean precision': 0.9821282029151917, 'Train/mean recall': 0.9911644458770752, 'Train/mean hd95_metric': 1.8837400674819946} +Epoch [510/4000] Validation [1/4] Loss: 0.17758 focal_loss 0.11384 dice_loss 0.06374 +Epoch [510/4000] Validation [2/4] Loss: 0.39390 focal_loss 0.21493 dice_loss 0.17898 +Epoch [510/4000] Validation [3/4] Loss: 0.18355 focal_loss 0.09069 dice_loss 0.09286 +Epoch [510/4000] Validation [4/4] Loss: 0.26153 focal_loss 0.15197 dice_loss 0.10956 +Epoch [510/4000] Validation metric {'Val/mean dice_metric': 0.9658492207527161, 'Val/mean miou_metric': 0.9436963796615601, 'Val/mean f1': 0.9671265482902527, 'Val/mean precision': 0.9630353450775146, 'Val/mean recall': 0.9712525606155396, 'Val/mean hd95_metric': 6.891931056976318} +Cheakpoint... +Epoch [510/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658492207527161, 'Val/mean miou_metric': 0.9436963796615601, 'Val/mean f1': 0.9671265482902527, 'Val/mean precision': 0.9630353450775146, 'Val/mean recall': 0.9712525606155396, 'Val/mean hd95_metric': 6.891931056976318} +Epoch [511/4000] Training [1/16] Loss: 0.01204 +Epoch [511/4000] Training [2/16] Loss: 0.01559 +Epoch [511/4000] Training [3/16] Loss: 0.01631 +Epoch [511/4000] Training [4/16] Loss: 0.01458 +Epoch [511/4000] Training [5/16] Loss: 0.15893 +Epoch [511/4000] Training [6/16] Loss: 0.01475 +Epoch [511/4000] Training [7/16] Loss: 0.01480 +Epoch [511/4000] Training [8/16] Loss: 0.01156 +Epoch [511/4000] Training [9/16] Loss: 0.01397 +Epoch [511/4000] Training [10/16] Loss: 0.02442 +Epoch [511/4000] Training [11/16] Loss: 0.03456 +Epoch [511/4000] Training [12/16] Loss: 0.01976 +Epoch [511/4000] Training [13/16] Loss: 0.01907 +Epoch [511/4000] Training [14/16] Loss: 0.01410 +Epoch [511/4000] Training [15/16] Loss: 0.01230 +Epoch [511/4000] Training [16/16] Loss: 0.01706 +Epoch [511/4000] Training metric {'Train/mean dice_metric': 0.9857667088508606, 'Train/mean miou_metric': 0.9731349945068359, 'Train/mean f1': 0.982546329498291, 'Train/mean precision': 0.9770610928535461, 'Train/mean recall': 0.9880934953689575, 'Train/mean hd95_metric': 2.4803996086120605} +Epoch [511/4000] Validation [1/4] Loss: 0.25062 focal_loss 0.15664 dice_loss 0.09398 +Epoch [511/4000] Validation [2/4] Loss: 0.50701 focal_loss 0.24299 dice_loss 0.26402 +Epoch [511/4000] Validation [3/4] Loss: 0.12736 focal_loss 0.05593 dice_loss 0.07142 +Epoch [511/4000] Validation [4/4] Loss: 0.29880 focal_loss 0.14316 dice_loss 0.15564 +Epoch [511/4000] Validation metric {'Val/mean dice_metric': 0.9581201672554016, 'Val/mean miou_metric': 0.9333018064498901, 'Val/mean f1': 0.9601131677627563, 'Val/mean precision': 0.9519588947296143, 'Val/mean recall': 0.9684084057807922, 'Val/mean hd95_metric': 8.920920372009277} +Cheakpoint... +Epoch [511/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9581], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9581201672554016, 'Val/mean miou_metric': 0.9333018064498901, 'Val/mean f1': 0.9601131677627563, 'Val/mean precision': 0.9519588947296143, 'Val/mean recall': 0.9684084057807922, 'Val/mean hd95_metric': 8.920920372009277} +Epoch [512/4000] Training [1/16] Loss: 0.02873 +Epoch [512/4000] Training [2/16] Loss: 0.02503 +Epoch [512/4000] Training [3/16] Loss: 0.01507 +Epoch [512/4000] Training [4/16] Loss: 0.01391 +Epoch [512/4000] Training [5/16] Loss: 0.02584 +Epoch [512/4000] Training [6/16] Loss: 0.02362 +Epoch [512/4000] Training [7/16] Loss: 0.01120 +Epoch [512/4000] Training [8/16] Loss: 0.01881 +Epoch [512/4000] Training [9/16] Loss: 0.01609 +Epoch [512/4000] Training [10/16] Loss: 0.01537 +Epoch [512/4000] Training [11/16] Loss: 0.01770 +Epoch [512/4000] Training [12/16] Loss: 0.01735 +Epoch [512/4000] Training [13/16] Loss: 0.07328 +Epoch [512/4000] Training [14/16] Loss: 0.01677 +Epoch [512/4000] Training [15/16] Loss: 0.01941 +Epoch [512/4000] Training [16/16] Loss: 0.01668 +Epoch [512/4000] Training metric {'Train/mean dice_metric': 0.9858506917953491, 'Train/mean miou_metric': 0.9725383520126343, 'Train/mean f1': 0.9806267023086548, 'Train/mean precision': 0.9779000878334045, 'Train/mean recall': 0.9833685755729675, 'Train/mean hd95_metric': 2.723003387451172} +Epoch [512/4000] Validation [1/4] Loss: 0.15589 focal_loss 0.06869 dice_loss 0.08720 +Epoch [512/4000] Validation [2/4] Loss: 0.37602 focal_loss 0.16491 dice_loss 0.21112 +Epoch [512/4000] Validation [3/4] Loss: 0.17968 focal_loss 0.07597 dice_loss 0.10371 +Epoch [512/4000] Validation [4/4] Loss: 0.21867 focal_loss 0.08339 dice_loss 0.13528 +Epoch [512/4000] Validation metric {'Val/mean dice_metric': 0.9601430892944336, 'Val/mean miou_metric': 0.935028076171875, 'Val/mean f1': 0.959287703037262, 'Val/mean precision': 0.9560943245887756, 'Val/mean recall': 0.9625025391578674, 'Val/mean hd95_metric': 7.985160827636719} +Cheakpoint... +Epoch [512/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9601], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9601430892944336, 'Val/mean miou_metric': 0.935028076171875, 'Val/mean f1': 0.959287703037262, 'Val/mean precision': 0.9560943245887756, 'Val/mean recall': 0.9625025391578674, 'Val/mean hd95_metric': 7.985160827636719} +Epoch [513/4000] Training [1/16] Loss: 0.02421 +Epoch [513/4000] Training [2/16] Loss: 0.01868 +Epoch [513/4000] Training [3/16] Loss: 0.01426 +Epoch [513/4000] Training [4/16] Loss: 0.01721 +Epoch [513/4000] Training [5/16] Loss: 0.01493 +Epoch [513/4000] Training [6/16] Loss: 0.01570 +Epoch [513/4000] Training [7/16] Loss: 0.02084 +Epoch [513/4000] Training [8/16] Loss: 0.02119 +Epoch [513/4000] Training [9/16] Loss: 0.01399 +Epoch [513/4000] Training [10/16] Loss: 0.01716 +Epoch [513/4000] Training [11/16] Loss: 0.02709 +Epoch [513/4000] Training [12/16] Loss: 0.01735 +Epoch [513/4000] Training [13/16] Loss: 0.01568 +Epoch [513/4000] Training [14/16] Loss: 0.01591 +Epoch [513/4000] Training [15/16] Loss: 0.01775 +Epoch [513/4000] Training [16/16] Loss: 0.02051 +Epoch [513/4000] Training metric {'Train/mean dice_metric': 0.9860628247261047, 'Train/mean miou_metric': 0.972920298576355, 'Train/mean f1': 0.9830146431922913, 'Train/mean precision': 0.9779613614082336, 'Train/mean recall': 0.988120436668396, 'Train/mean hd95_metric': 3.024015188217163} +Epoch [513/4000] Validation [1/4] Loss: 0.13035 focal_loss 0.05970 dice_loss 0.07065 +Epoch [513/4000] Validation [2/4] Loss: 0.52203 focal_loss 0.24311 dice_loss 0.27892 +Epoch [513/4000] Validation [3/4] Loss: 0.31973 focal_loss 0.19295 dice_loss 0.12677 +Epoch [513/4000] Validation [4/4] Loss: 0.31252 focal_loss 0.15618 dice_loss 0.15634 +Epoch [513/4000] Validation metric {'Val/mean dice_metric': 0.961788535118103, 'Val/mean miou_metric': 0.9366366267204285, 'Val/mean f1': 0.9630063772201538, 'Val/mean precision': 0.9551354050636292, 'Val/mean recall': 0.9710081815719604, 'Val/mean hd95_metric': 8.700150489807129} +Cheakpoint... +Epoch [513/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9618], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961788535118103, 'Val/mean miou_metric': 0.9366366267204285, 'Val/mean f1': 0.9630063772201538, 'Val/mean precision': 0.9551354050636292, 'Val/mean recall': 0.9710081815719604, 'Val/mean hd95_metric': 8.700150489807129} +Epoch [514/4000] Training [1/16] Loss: 0.01845 +Epoch [514/4000] Training [2/16] Loss: 0.01236 +Epoch [514/4000] Training [3/16] Loss: 0.01483 +Epoch [514/4000] Training [4/16] Loss: 0.02348 +Epoch [514/4000] Training [5/16] Loss: 0.01648 +Epoch [514/4000] Training [6/16] Loss: 0.02045 +Epoch [514/4000] Training [7/16] Loss: 0.02730 +Epoch [514/4000] Training [8/16] Loss: 0.01691 +Epoch [514/4000] Training [9/16] Loss: 0.01529 +Epoch [514/4000] Training [10/16] Loss: 0.01853 +Epoch [514/4000] Training [11/16] Loss: 0.01558 +Epoch [514/4000] Training [12/16] Loss: 0.02726 +Epoch [514/4000] Training [13/16] Loss: 0.02171 +Epoch [514/4000] Training [14/16] Loss: 0.01217 +Epoch [514/4000] Training [15/16] Loss: 0.02010 +Epoch [514/4000] Training [16/16] Loss: 0.01671 +Epoch [514/4000] Training metric {'Train/mean dice_metric': 0.9880708456039429, 'Train/mean miou_metric': 0.9763025641441345, 'Train/mean f1': 0.9855476021766663, 'Train/mean precision': 0.9813936948776245, 'Train/mean recall': 0.9897368550300598, 'Train/mean hd95_metric': 1.9404829740524292} +Epoch [514/4000] Validation [1/4] Loss: 0.13321 focal_loss 0.07678 dice_loss 0.05643 +Epoch [514/4000] Validation [2/4] Loss: 0.32668 focal_loss 0.14660 dice_loss 0.18007 +Epoch [514/4000] Validation [3/4] Loss: 0.16227 focal_loss 0.07749 dice_loss 0.08478 +Epoch [514/4000] Validation [4/4] Loss: 0.25139 focal_loss 0.12348 dice_loss 0.12791 +Epoch [514/4000] Validation metric {'Val/mean dice_metric': 0.9644935727119446, 'Val/mean miou_metric': 0.9407367706298828, 'Val/mean f1': 0.9680467844009399, 'Val/mean precision': 0.9613642692565918, 'Val/mean recall': 0.9748228788375854, 'Val/mean hd95_metric': 7.331148624420166} +Cheakpoint... +Epoch [514/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644935727119446, 'Val/mean miou_metric': 0.9407367706298828, 'Val/mean f1': 0.9680467844009399, 'Val/mean precision': 0.9613642692565918, 'Val/mean recall': 0.9748228788375854, 'Val/mean hd95_metric': 7.331148624420166} +Epoch [515/4000] Training [1/16] Loss: 0.01633 +Epoch [515/4000] Training [2/16] Loss: 0.01916 +Epoch [515/4000] Training [3/16] Loss: 0.01143 +Epoch [515/4000] Training [4/16] Loss: 0.01787 +Epoch [515/4000] Training [5/16] Loss: 0.01987 +Epoch [515/4000] Training [6/16] Loss: 0.01868 +Epoch [515/4000] Training [7/16] Loss: 0.01313 +Epoch [515/4000] Training [8/16] Loss: 0.01737 +Epoch [515/4000] Training [9/16] Loss: 0.01511 +Epoch [515/4000] Training [10/16] Loss: 0.01416 +Epoch [515/4000] Training [11/16] Loss: 0.01284 +Epoch [515/4000] Training [12/16] Loss: 0.01568 +Epoch [515/4000] Training [13/16] Loss: 0.01705 +Epoch [515/4000] Training [14/16] Loss: 0.01348 +Epoch [515/4000] Training [15/16] Loss: 0.01230 +Epoch [515/4000] Training [16/16] Loss: 0.02159 +Epoch [515/4000] Training metric {'Train/mean dice_metric': 0.9891594052314758, 'Train/mean miou_metric': 0.978376567363739, 'Train/mean f1': 0.9858982563018799, 'Train/mean precision': 0.9813340306282043, 'Train/mean recall': 0.9905050992965698, 'Train/mean hd95_metric': 1.497187852859497} +Epoch [515/4000] Validation [1/4] Loss: 0.14763 focal_loss 0.08230 dice_loss 0.06533 +Epoch [515/4000] Validation [2/4] Loss: 0.33379 focal_loss 0.16842 dice_loss 0.16537 +Epoch [515/4000] Validation [3/4] Loss: 0.13368 focal_loss 0.07280 dice_loss 0.06089 +Epoch [515/4000] Validation [4/4] Loss: 0.25573 focal_loss 0.11548 dice_loss 0.14025 +Epoch [515/4000] Validation metric {'Val/mean dice_metric': 0.9659277200698853, 'Val/mean miou_metric': 0.9430254101753235, 'Val/mean f1': 0.9668518900871277, 'Val/mean precision': 0.9571238160133362, 'Val/mean recall': 0.9767798185348511, 'Val/mean hd95_metric': 6.849671840667725} +Cheakpoint... +Epoch [515/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659277200698853, 'Val/mean miou_metric': 0.9430254101753235, 'Val/mean f1': 0.9668518900871277, 'Val/mean precision': 0.9571238160133362, 'Val/mean recall': 0.9767798185348511, 'Val/mean hd95_metric': 6.849671840667725} +Epoch [516/4000] Training [1/16] Loss: 0.01123 +Epoch [516/4000] Training [2/16] Loss: 0.03670 +Epoch [516/4000] Training [3/16] Loss: 0.01182 +Epoch [516/4000] Training [4/16] Loss: 0.01747 +Epoch [516/4000] Training [5/16] Loss: 0.01773 +Epoch [516/4000] Training [6/16] Loss: 0.01270 +Epoch [516/4000] Training [7/16] Loss: 0.01281 +Epoch [516/4000] Training [8/16] Loss: 0.01280 +Epoch [516/4000] Training [9/16] Loss: 0.01302 +Epoch [516/4000] Training [10/16] Loss: 0.02836 +Epoch [516/4000] Training [11/16] Loss: 0.01291 +Epoch [516/4000] Training [12/16] Loss: 0.01321 +Epoch [516/4000] Training [13/16] Loss: 0.01651 +Epoch [516/4000] Training [14/16] Loss: 0.01785 +Epoch [516/4000] Training [15/16] Loss: 0.01827 +Epoch [516/4000] Training [16/16] Loss: 0.01072 +Epoch [516/4000] Training metric {'Train/mean dice_metric': 0.9891180992126465, 'Train/mean miou_metric': 0.9785534143447876, 'Train/mean f1': 0.9859633445739746, 'Train/mean precision': 0.9809378385543823, 'Train/mean recall': 0.9910406470298767, 'Train/mean hd95_metric': 1.780534267425537} +Epoch [516/4000] Validation [1/4] Loss: 0.55782 focal_loss 0.40925 dice_loss 0.14857 +Epoch [516/4000] Validation [2/4] Loss: 0.55426 focal_loss 0.23577 dice_loss 0.31848 +Epoch [516/4000] Validation [3/4] Loss: 0.12147 focal_loss 0.05362 dice_loss 0.06785 +Epoch [516/4000] Validation [4/4] Loss: 0.27057 focal_loss 0.12756 dice_loss 0.14301 +Epoch [516/4000] Validation metric {'Val/mean dice_metric': 0.9608422517776489, 'Val/mean miou_metric': 0.9384492635726929, 'Val/mean f1': 0.9646787643432617, 'Val/mean precision': 0.9637486338615417, 'Val/mean recall': 0.9656107425689697, 'Val/mean hd95_metric': 6.743231296539307} +Cheakpoint... +Epoch [516/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608422517776489, 'Val/mean miou_metric': 0.9384492635726929, 'Val/mean f1': 0.9646787643432617, 'Val/mean precision': 0.9637486338615417, 'Val/mean recall': 0.9656107425689697, 'Val/mean hd95_metric': 6.743231296539307} +Epoch [517/4000] Training [1/16] Loss: 0.02162 +Epoch [517/4000] Training [2/16] Loss: 0.01668 +Epoch [517/4000] Training [3/16] Loss: 0.01956 +Epoch [517/4000] Training [4/16] Loss: 0.02174 +Epoch [517/4000] Training [5/16] Loss: 0.01526 +Epoch [517/4000] Training [6/16] Loss: 0.02289 +Epoch [517/4000] Training [7/16] Loss: 0.01639 +Epoch [517/4000] Training [8/16] Loss: 0.01438 +Epoch [517/4000] Training [9/16] Loss: 0.01689 +Epoch [517/4000] Training [10/16] Loss: 0.01332 +Epoch [517/4000] Training [11/16] Loss: 0.01252 +Epoch [517/4000] Training [12/16] Loss: 0.01513 +Epoch [517/4000] Training [13/16] Loss: 0.02332 +Epoch [517/4000] Training [14/16] Loss: 0.05486 +Epoch [517/4000] Training [15/16] Loss: 0.01802 +Epoch [517/4000] Training [16/16] Loss: 0.01778 +Epoch [517/4000] Training metric {'Train/mean dice_metric': 0.9845119714736938, 'Train/mean miou_metric': 0.9704834222793579, 'Train/mean f1': 0.9813700914382935, 'Train/mean precision': 0.9761734008789062, 'Train/mean recall': 0.9866223931312561, 'Train/mean hd95_metric': 3.4143764972686768} +Epoch [517/4000] Validation [1/4] Loss: 0.17192 focal_loss 0.10194 dice_loss 0.06998 +Epoch [517/4000] Validation [2/4] Loss: 0.40010 focal_loss 0.19599 dice_loss 0.20411 +Epoch [517/4000] Validation [3/4] Loss: 0.12644 focal_loss 0.05753 dice_loss 0.06891 +Epoch [517/4000] Validation [4/4] Loss: 0.28336 focal_loss 0.14724 dice_loss 0.13612 +Epoch [517/4000] Validation metric {'Val/mean dice_metric': 0.9608379602432251, 'Val/mean miou_metric': 0.9345749020576477, 'Val/mean f1': 0.9610897898674011, 'Val/mean precision': 0.9495689272880554, 'Val/mean recall': 0.9728936553001404, 'Val/mean hd95_metric': 9.49046802520752} +Cheakpoint... +Epoch [517/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608379602432251, 'Val/mean miou_metric': 0.9345749020576477, 'Val/mean f1': 0.9610897898674011, 'Val/mean precision': 0.9495689272880554, 'Val/mean recall': 0.9728936553001404, 'Val/mean hd95_metric': 9.49046802520752} +Epoch [518/4000] Training [1/16] Loss: 0.01525 +Epoch [518/4000] Training [2/16] Loss: 0.01309 +Epoch [518/4000] Training [3/16] Loss: 0.01432 +Epoch [518/4000] Training [4/16] Loss: 0.01701 +Epoch [518/4000] Training [5/16] Loss: 0.01402 +Epoch [518/4000] Training [6/16] Loss: 0.01889 +Epoch [518/4000] Training [7/16] Loss: 0.01484 +Epoch [518/4000] Training [8/16] Loss: 0.02314 +Epoch [518/4000] Training [9/16] Loss: 0.02321 +Epoch [518/4000] Training [10/16] Loss: 0.02069 +Epoch [518/4000] Training [11/16] Loss: 0.01700 +Epoch [518/4000] Training [12/16] Loss: 0.01181 +Epoch [518/4000] Training [13/16] Loss: 0.01636 +Epoch [518/4000] Training [14/16] Loss: 0.01415 +Epoch [518/4000] Training [15/16] Loss: 0.01452 +Epoch [518/4000] Training [16/16] Loss: 0.01585 +Epoch [518/4000] Training metric {'Train/mean dice_metric': 0.9884997606277466, 'Train/mean miou_metric': 0.977099597454071, 'Train/mean f1': 0.9855051636695862, 'Train/mean precision': 0.9819643497467041, 'Train/mean recall': 0.9890716671943665, 'Train/mean hd95_metric': 1.665045142173767} +Epoch [518/4000] Validation [1/4] Loss: 0.17119 focal_loss 0.10313 dice_loss 0.06806 +Epoch [518/4000] Validation [2/4] Loss: 0.50098 focal_loss 0.27153 dice_loss 0.22945 +Epoch [518/4000] Validation [3/4] Loss: 0.21227 focal_loss 0.11550 dice_loss 0.09677 +Epoch [518/4000] Validation [4/4] Loss: 0.17287 focal_loss 0.07480 dice_loss 0.09808 +Epoch [518/4000] Validation metric {'Val/mean dice_metric': 0.965399444103241, 'Val/mean miou_metric': 0.9428796768188477, 'Val/mean f1': 0.9669502377510071, 'Val/mean precision': 0.9620553851127625, 'Val/mean recall': 0.971895158290863, 'Val/mean hd95_metric': 6.942091464996338} +Cheakpoint... +Epoch [518/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965399444103241, 'Val/mean miou_metric': 0.9428796768188477, 'Val/mean f1': 0.9669502377510071, 'Val/mean precision': 0.9620553851127625, 'Val/mean recall': 0.971895158290863, 'Val/mean hd95_metric': 6.942091464996338} +Epoch [519/4000] Training [1/16] Loss: 0.01440 +Epoch [519/4000] Training [2/16] Loss: 0.01387 +Epoch [519/4000] Training [3/16] Loss: 0.03718 +Epoch [519/4000] Training [4/16] Loss: 0.01025 +Epoch [519/4000] Training [5/16] Loss: 0.01655 +Epoch [519/4000] Training [6/16] Loss: 0.01388 +Epoch [519/4000] Training [7/16] Loss: 0.01592 +Epoch [519/4000] Training [8/16] Loss: 0.01283 +Epoch [519/4000] Training [9/16] Loss: 0.01493 +Epoch [519/4000] Training [10/16] Loss: 0.01310 +Epoch [519/4000] Training [11/16] Loss: 0.01718 +Epoch [519/4000] Training [12/16] Loss: 0.01504 +Epoch [519/4000] Training [13/16] Loss: 0.01140 +Epoch [519/4000] Training [14/16] Loss: 0.03402 +Epoch [519/4000] Training [15/16] Loss: 0.01541 +Epoch [519/4000] Training [16/16] Loss: 0.01738 +Epoch [519/4000] Training metric {'Train/mean dice_metric': 0.9898976683616638, 'Train/mean miou_metric': 0.979806125164032, 'Train/mean f1': 0.9857181906700134, 'Train/mean precision': 0.9803078174591064, 'Train/mean recall': 0.9911885857582092, 'Train/mean hd95_metric': 1.4434256553649902} +Epoch [519/4000] Validation [1/4] Loss: 0.37657 focal_loss 0.25613 dice_loss 0.12044 +Epoch [519/4000] Validation [2/4] Loss: 0.36686 focal_loss 0.18995 dice_loss 0.17691 +Epoch [519/4000] Validation [3/4] Loss: 0.14581 focal_loss 0.06718 dice_loss 0.07864 +Epoch [519/4000] Validation [4/4] Loss: 0.27519 focal_loss 0.15246 dice_loss 0.12273 +Epoch [519/4000] Validation metric {'Val/mean dice_metric': 0.9652139544487, 'Val/mean miou_metric': 0.9431027173995972, 'Val/mean f1': 0.9648216962814331, 'Val/mean precision': 0.9645516872406006, 'Val/mean recall': 0.9650918841362, 'Val/mean hd95_metric': 6.7121758460998535} +Cheakpoint... +Epoch [519/4000] best acc:tensor([0.9687], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652139544487, 'Val/mean miou_metric': 0.9431027173995972, 'Val/mean f1': 0.9648216962814331, 'Val/mean precision': 0.9645516872406006, 'Val/mean recall': 0.9650918841362, 'Val/mean hd95_metric': 6.7121758460998535} +Epoch [520/4000] Training [1/16] Loss: 0.01032 +Epoch [520/4000] Training [2/16] Loss: 0.01277 +Epoch [520/4000] Training [3/16] Loss: 0.01302 +Epoch [520/4000] Training [4/16] Loss: 0.01066 +Epoch [520/4000] Training [5/16] Loss: 0.01567 +Epoch [520/4000] Training [6/16] Loss: 0.01539 +Epoch [520/4000] Training [7/16] Loss: 0.00861 +Epoch [520/4000] Training [8/16] Loss: 0.01307 +Epoch [520/4000] Training [9/16] Loss: 0.01154 +Epoch [520/4000] Training [10/16] Loss: 0.02287 +Epoch [520/4000] Training [11/16] Loss: 0.01685 +Epoch [520/4000] Training [12/16] Loss: 0.01282 +Epoch [520/4000] Training [13/16] Loss: 0.01345 +Epoch [520/4000] Training [14/16] Loss: 0.01274 +Epoch [520/4000] Training [15/16] Loss: 0.01211 +Epoch [520/4000] Training [16/16] Loss: 0.01168 +Epoch [520/4000] Training metric {'Train/mean dice_metric': 0.9905635714530945, 'Train/mean miou_metric': 0.9811004400253296, 'Train/mean f1': 0.9873715043067932, 'Train/mean precision': 0.9826899170875549, 'Train/mean recall': 0.9920979738235474, 'Train/mean hd95_metric': 1.3234421014785767} +Epoch [520/4000] Validation [1/4] Loss: 0.12945 focal_loss 0.07326 dice_loss 0.05620 +Epoch [520/4000] Validation [2/4] Loss: 0.35105 focal_loss 0.16060 dice_loss 0.19045 +Epoch [520/4000] Validation [3/4] Loss: 0.16263 focal_loss 0.07131 dice_loss 0.09131 +Epoch [520/4000] Validation [4/4] Loss: 0.22233 focal_loss 0.10154 dice_loss 0.12079 +Epoch [520/4000] Validation metric {'Val/mean dice_metric': 0.9691497683525085, 'Val/mean miou_metric': 0.9482070207595825, 'Val/mean f1': 0.9706388115882874, 'Val/mean precision': 0.9638521671295166, 'Val/mean recall': 0.9775216579437256, 'Val/mean hd95_metric': 6.14989709854126} +Cheakpoint... +Epoch [520/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691497683525085, 'Val/mean miou_metric': 0.9482070207595825, 'Val/mean f1': 0.9706388115882874, 'Val/mean precision': 0.9638521671295166, 'Val/mean recall': 0.9775216579437256, 'Val/mean hd95_metric': 6.14989709854126} +Epoch [521/4000] Training [1/16] Loss: 0.01385 +Epoch [521/4000] Training [2/16] Loss: 0.01277 +Epoch [521/4000] Training [3/16] Loss: 0.00979 +Epoch [521/4000] Training [4/16] Loss: 0.01219 +Epoch [521/4000] Training [5/16] Loss: 0.01615 +Epoch [521/4000] Training [6/16] Loss: 0.01263 +Epoch [521/4000] Training [7/16] Loss: 0.01602 +Epoch [521/4000] Training [8/16] Loss: 0.01593 +Epoch [521/4000] Training [9/16] Loss: 0.01358 +Epoch [521/4000] Training [10/16] Loss: 0.01503 +Epoch [521/4000] Training [11/16] Loss: 0.01524 +Epoch [521/4000] Training [12/16] Loss: 0.01545 +Epoch [521/4000] Training [13/16] Loss: 0.01447 +Epoch [521/4000] Training [14/16] Loss: 0.01478 +Epoch [521/4000] Training [15/16] Loss: 0.01776 +Epoch [521/4000] Training [16/16] Loss: 0.01504 +Epoch [521/4000] Training metric {'Train/mean dice_metric': 0.9899560213088989, 'Train/mean miou_metric': 0.9799447655677795, 'Train/mean f1': 0.9864760637283325, 'Train/mean precision': 0.9817101359367371, 'Train/mean recall': 0.9912885427474976, 'Train/mean hd95_metric': 1.861218810081482} +Epoch [521/4000] Validation [1/4] Loss: 0.21011 focal_loss 0.12859 dice_loss 0.08152 +Epoch [521/4000] Validation [2/4] Loss: 0.42421 focal_loss 0.20553 dice_loss 0.21868 +Epoch [521/4000] Validation [3/4] Loss: 0.19245 focal_loss 0.09455 dice_loss 0.09789 +Epoch [521/4000] Validation [4/4] Loss: 0.25354 focal_loss 0.12574 dice_loss 0.12780 +Epoch [521/4000] Validation metric {'Val/mean dice_metric': 0.9669010043144226, 'Val/mean miou_metric': 0.9444343447685242, 'Val/mean f1': 0.9668729901313782, 'Val/mean precision': 0.9615519046783447, 'Val/mean recall': 0.9722533226013184, 'Val/mean hd95_metric': 6.906756401062012} +Cheakpoint... +Epoch [521/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669010043144226, 'Val/mean miou_metric': 0.9444343447685242, 'Val/mean f1': 0.9668729901313782, 'Val/mean precision': 0.9615519046783447, 'Val/mean recall': 0.9722533226013184, 'Val/mean hd95_metric': 6.906756401062012} +Epoch [522/4000] Training [1/16] Loss: 0.01326 +Epoch [522/4000] Training [2/16] Loss: 0.01388 +Epoch [522/4000] Training [3/16] Loss: 0.01480 +Epoch [522/4000] Training [4/16] Loss: 0.01500 +Epoch [522/4000] Training [5/16] Loss: 0.02549 +Epoch [522/4000] Training [6/16] Loss: 0.01429 +Epoch [522/4000] Training [7/16] Loss: 0.01021 +Epoch [522/4000] Training [8/16] Loss: 0.05771 +Epoch [522/4000] Training [9/16] Loss: 0.01565 +Epoch [522/4000] Training [10/16] Loss: 0.02107 +Epoch [522/4000] Training [11/16] Loss: 0.01384 +Epoch [522/4000] Training [12/16] Loss: 0.01255 +Epoch [522/4000] Training [13/16] Loss: 0.01799 +Epoch [522/4000] Training [14/16] Loss: 0.01395 +Epoch [522/4000] Training [15/16] Loss: 0.02426 +Epoch [522/4000] Training [16/16] Loss: 0.01562 +Epoch [522/4000] Training metric {'Train/mean dice_metric': 0.9878807067871094, 'Train/mean miou_metric': 0.9761621356010437, 'Train/mean f1': 0.9842979311943054, 'Train/mean precision': 0.9795295596122742, 'Train/mean recall': 0.9891128540039062, 'Train/mean hd95_metric': 1.997959852218628} +Epoch [522/4000] Validation [1/4] Loss: 0.25682 focal_loss 0.16488 dice_loss 0.09194 +Epoch [522/4000] Validation [2/4] Loss: 0.70872 focal_loss 0.39711 dice_loss 0.31161 +Epoch [522/4000] Validation [3/4] Loss: 0.13648 focal_loss 0.05719 dice_loss 0.07930 +Epoch [522/4000] Validation [4/4] Loss: 0.39464 focal_loss 0.21374 dice_loss 0.18090 +Epoch [522/4000] Validation metric {'Val/mean dice_metric': 0.9576323628425598, 'Val/mean miou_metric': 0.9331396818161011, 'Val/mean f1': 0.9576554298400879, 'Val/mean precision': 0.9432409405708313, 'Val/mean recall': 0.9725173115730286, 'Val/mean hd95_metric': 9.918479919433594} +Cheakpoint... +Epoch [522/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576323628425598, 'Val/mean miou_metric': 0.9331396818161011, 'Val/mean f1': 0.9576554298400879, 'Val/mean precision': 0.9432409405708313, 'Val/mean recall': 0.9725173115730286, 'Val/mean hd95_metric': 9.918479919433594} +Epoch [523/4000] Training [1/16] Loss: 0.01436 +Epoch [523/4000] Training [2/16] Loss: 0.01533 +Epoch [523/4000] Training [3/16] Loss: 0.01690 +Epoch [523/4000] Training [4/16] Loss: 0.01721 +Epoch [523/4000] Training [5/16] Loss: 0.01537 +Epoch [523/4000] Training [6/16] Loss: 0.01218 +Epoch [523/4000] Training [7/16] Loss: 0.01519 +Epoch [523/4000] Training [8/16] Loss: 0.01894 +Epoch [523/4000] Training [9/16] Loss: 0.02432 +Epoch [523/4000] Training [10/16] Loss: 0.01811 +Epoch [523/4000] Training [11/16] Loss: 0.01556 +Epoch [523/4000] Training [12/16] Loss: 0.01761 +Epoch [523/4000] Training [13/16] Loss: 0.01755 +Epoch [523/4000] Training [14/16] Loss: 0.01169 +Epoch [523/4000] Training [15/16] Loss: 0.02812 +Epoch [523/4000] Training [16/16] Loss: 0.01357 +Epoch [523/4000] Training metric {'Train/mean dice_metric': 0.9868662357330322, 'Train/mean miou_metric': 0.9744622111320496, 'Train/mean f1': 0.984775722026825, 'Train/mean precision': 0.9804409146308899, 'Train/mean recall': 0.9891490936279297, 'Train/mean hd95_metric': 2.9527885913848877} +Epoch [523/4000] Validation [1/4] Loss: 0.15199 focal_loss 0.08262 dice_loss 0.06937 +Epoch [523/4000] Validation [2/4] Loss: 0.69378 focal_loss 0.37564 dice_loss 0.31815 +Epoch [523/4000] Validation [3/4] Loss: 0.15141 focal_loss 0.06981 dice_loss 0.08160 +Epoch [523/4000] Validation [4/4] Loss: 0.37817 focal_loss 0.21221 dice_loss 0.16596 +Epoch [523/4000] Validation metric {'Val/mean dice_metric': 0.9631948471069336, 'Val/mean miou_metric': 0.9396661520004272, 'Val/mean f1': 0.9657289385795593, 'Val/mean precision': 0.9587693214416504, 'Val/mean recall': 0.9727903008460999, 'Val/mean hd95_metric': 8.303276062011719} +Cheakpoint... +Epoch [523/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631948471069336, 'Val/mean miou_metric': 0.9396661520004272, 'Val/mean f1': 0.9657289385795593, 'Val/mean precision': 0.9587693214416504, 'Val/mean recall': 0.9727903008460999, 'Val/mean hd95_metric': 8.303276062011719} +Epoch [524/4000] Training [1/16] Loss: 0.01425 +Epoch [524/4000] Training [2/16] Loss: 0.01729 +Epoch [524/4000] Training [3/16] Loss: 0.01209 +Epoch [524/4000] Training [4/16] Loss: 0.01928 +Epoch [524/4000] Training [5/16] Loss: 0.01731 +Epoch [524/4000] Training [6/16] Loss: 0.01338 +Epoch [524/4000] Training [7/16] Loss: 0.01377 +Epoch [524/4000] Training [8/16] Loss: 0.01388 +Epoch [524/4000] Training [9/16] Loss: 0.01268 +Epoch [524/4000] Training [10/16] Loss: 0.01623 +Epoch [524/4000] Training [11/16] Loss: 0.01296 +Epoch [524/4000] Training [12/16] Loss: 0.03206 +Epoch [524/4000] Training [13/16] Loss: 0.01738 +Epoch [524/4000] Training [14/16] Loss: 0.02006 +Epoch [524/4000] Training [15/16] Loss: 0.01795 +Epoch [524/4000] Training [16/16] Loss: 0.01348 +Epoch [524/4000] Training metric {'Train/mean dice_metric': 0.9888412952423096, 'Train/mean miou_metric': 0.9777612686157227, 'Train/mean f1': 0.985922634601593, 'Train/mean precision': 0.9815194606781006, 'Train/mean recall': 0.9903654456138611, 'Train/mean hd95_metric': 1.7990138530731201} +Epoch [524/4000] Validation [1/4] Loss: 0.26455 focal_loss 0.15798 dice_loss 0.10657 +Epoch [524/4000] Validation [2/4] Loss: 0.23980 focal_loss 0.10867 dice_loss 0.13114 +Epoch [524/4000] Validation [3/4] Loss: 0.13140 focal_loss 0.06093 dice_loss 0.07046 +Epoch [524/4000] Validation [4/4] Loss: 0.20150 focal_loss 0.09178 dice_loss 0.10972 +Epoch [524/4000] Validation metric {'Val/mean dice_metric': 0.9671949148178101, 'Val/mean miou_metric': 0.9441738128662109, 'Val/mean f1': 0.9663196206092834, 'Val/mean precision': 0.9600377678871155, 'Val/mean recall': 0.9726840853691101, 'Val/mean hd95_metric': 6.510825157165527} +Cheakpoint... +Epoch [524/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671949148178101, 'Val/mean miou_metric': 0.9441738128662109, 'Val/mean f1': 0.9663196206092834, 'Val/mean precision': 0.9600377678871155, 'Val/mean recall': 0.9726840853691101, 'Val/mean hd95_metric': 6.510825157165527} +Epoch [525/4000] Training [1/16] Loss: 0.01993 +Epoch [525/4000] Training [2/16] Loss: 0.01616 +Epoch [525/4000] Training [3/16] Loss: 0.02052 +Epoch [525/4000] Training [4/16] Loss: 0.01370 +Epoch [525/4000] Training [5/16] Loss: 0.01500 +Epoch [525/4000] Training [6/16] Loss: 0.01765 +Epoch [525/4000] Training [7/16] Loss: 0.01324 +Epoch [525/4000] Training [8/16] Loss: 0.01659 +Epoch [525/4000] Training [9/16] Loss: 0.01624 +Epoch [525/4000] Training [10/16] Loss: 0.01507 +Epoch [525/4000] Training [11/16] Loss: 0.01367 +Epoch [525/4000] Training [12/16] Loss: 0.01599 +Epoch [525/4000] Training [13/16] Loss: 0.01487 +Epoch [525/4000] Training [14/16] Loss: 0.01316 +Epoch [525/4000] Training [15/16] Loss: 0.01591 +Epoch [525/4000] Training [16/16] Loss: 0.02188 +Epoch [525/4000] Training metric {'Train/mean dice_metric': 0.9887539148330688, 'Train/mean miou_metric': 0.9776354432106018, 'Train/mean f1': 0.9857906699180603, 'Train/mean precision': 0.9809756875038147, 'Train/mean recall': 0.9906531572341919, 'Train/mean hd95_metric': 1.6050353050231934} +Epoch [525/4000] Validation [1/4] Loss: 0.34749 focal_loss 0.23467 dice_loss 0.11282 +Epoch [525/4000] Validation [2/4] Loss: 0.25029 focal_loss 0.10840 dice_loss 0.14188 +Epoch [525/4000] Validation [3/4] Loss: 0.11544 focal_loss 0.05589 dice_loss 0.05955 +Epoch [525/4000] Validation [4/4] Loss: 0.19233 focal_loss 0.08593 dice_loss 0.10640 +Epoch [525/4000] Validation metric {'Val/mean dice_metric': 0.9671350717544556, 'Val/mean miou_metric': 0.9446876645088196, 'Val/mean f1': 0.9654734134674072, 'Val/mean precision': 0.9614823460578918, 'Val/mean recall': 0.9694977402687073, 'Val/mean hd95_metric': 6.205869197845459} +Cheakpoint... +Epoch [525/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671350717544556, 'Val/mean miou_metric': 0.9446876645088196, 'Val/mean f1': 0.9654734134674072, 'Val/mean precision': 0.9614823460578918, 'Val/mean recall': 0.9694977402687073, 'Val/mean hd95_metric': 6.205869197845459} +Epoch [526/4000] Training [1/16] Loss: 0.01335 +Epoch [526/4000] Training [2/16] Loss: 0.01621 +Epoch [526/4000] Training [3/16] Loss: 0.01750 +Epoch [526/4000] Training [4/16] Loss: 0.01907 +Epoch [526/4000] Training [5/16] Loss: 0.01472 +Epoch [526/4000] Training [6/16] Loss: 0.02123 +Epoch [526/4000] Training [7/16] Loss: 0.01711 +Epoch [526/4000] Training [8/16] Loss: 0.01979 +Epoch [526/4000] Training [9/16] Loss: 0.01457 +Epoch [526/4000] Training [10/16] Loss: 0.01517 +Epoch [526/4000] Training [11/16] Loss: 0.01699 +Epoch [526/4000] Training [12/16] Loss: 0.01495 +Epoch [526/4000] Training [13/16] Loss: 0.01466 +Epoch [526/4000] Training [14/16] Loss: 0.01574 +Epoch [526/4000] Training [15/16] Loss: 0.01085 +Epoch [526/4000] Training [16/16] Loss: 0.01407 +Epoch [526/4000] Training metric {'Train/mean dice_metric': 0.9878004193305969, 'Train/mean miou_metric': 0.9761133790016174, 'Train/mean f1': 0.9842239022254944, 'Train/mean precision': 0.9803882241249084, 'Train/mean recall': 0.9880897998809814, 'Train/mean hd95_metric': 2.463167905807495} +Epoch [526/4000] Validation [1/4] Loss: 0.12291 focal_loss 0.06585 dice_loss 0.05707 +Epoch [526/4000] Validation [2/4] Loss: 0.77597 focal_loss 0.46674 dice_loss 0.30923 +Epoch [526/4000] Validation [3/4] Loss: 0.36368 focal_loss 0.22402 dice_loss 0.13966 +Epoch [526/4000] Validation [4/4] Loss: 0.26586 focal_loss 0.09883 dice_loss 0.16703 +Epoch [526/4000] Validation metric {'Val/mean dice_metric': 0.9533640742301941, 'Val/mean miou_metric': 0.9288837313652039, 'Val/mean f1': 0.9504913091659546, 'Val/mean precision': 0.9291622042655945, 'Val/mean recall': 0.9728226065635681, 'Val/mean hd95_metric': 11.509236335754395} +Cheakpoint... +Epoch [526/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9534], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9533640742301941, 'Val/mean miou_metric': 0.9288837313652039, 'Val/mean f1': 0.9504913091659546, 'Val/mean precision': 0.9291622042655945, 'Val/mean recall': 0.9728226065635681, 'Val/mean hd95_metric': 11.509236335754395} +Epoch [527/4000] Training [1/16] Loss: 0.01420 +Epoch [527/4000] Training [2/16] Loss: 0.02267 +Epoch [527/4000] Training [3/16] Loss: 0.10403 +Epoch [527/4000] Training [4/16] Loss: 0.01401 +Epoch [527/4000] Training [5/16] Loss: 0.01493 +Epoch [527/4000] Training [6/16] Loss: 0.01593 +Epoch [527/4000] Training [7/16] Loss: 0.01459 +Epoch [527/4000] Training [8/16] Loss: 0.01432 +Epoch [527/4000] Training [9/16] Loss: 0.02580 +Epoch [527/4000] Training [10/16] Loss: 0.01829 +Epoch [527/4000] Training [11/16] Loss: 0.02288 +Epoch [527/4000] Training [12/16] Loss: 0.02594 +Epoch [527/4000] Training [13/16] Loss: 0.02705 +Epoch [527/4000] Training [14/16] Loss: 0.01997 +Epoch [527/4000] Training [15/16] Loss: 0.01847 +Epoch [527/4000] Training [16/16] Loss: 0.09128 +Epoch [527/4000] Training metric {'Train/mean dice_metric': 0.9827616214752197, 'Train/mean miou_metric': 0.9675517082214355, 'Train/mean f1': 0.9801808595657349, 'Train/mean precision': 0.9767266511917114, 'Train/mean recall': 0.9836596250534058, 'Train/mean hd95_metric': 5.046140670776367} +Epoch [527/4000] Validation [1/4] Loss: 0.43987 focal_loss 0.29228 dice_loss 0.14759 +Epoch [527/4000] Validation [2/4] Loss: 0.50549 focal_loss 0.24922 dice_loss 0.25627 +Epoch [527/4000] Validation [3/4] Loss: 0.12322 focal_loss 0.05389 dice_loss 0.06934 +Epoch [527/4000] Validation [4/4] Loss: 0.20749 focal_loss 0.10302 dice_loss 0.10447 +Epoch [527/4000] Validation metric {'Val/mean dice_metric': 0.9568694233894348, 'Val/mean miou_metric': 0.9304399490356445, 'Val/mean f1': 0.9586015939712524, 'Val/mean precision': 0.9634371399879456, 'Val/mean recall': 0.9538144469261169, 'Val/mean hd95_metric': 9.455160140991211} +Cheakpoint... +Epoch [527/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9569], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9568694233894348, 'Val/mean miou_metric': 0.9304399490356445, 'Val/mean f1': 0.9586015939712524, 'Val/mean precision': 0.9634371399879456, 'Val/mean recall': 0.9538144469261169, 'Val/mean hd95_metric': 9.455160140991211} +Epoch [528/4000] Training [1/16] Loss: 0.01708 +Epoch [528/4000] Training [2/16] Loss: 0.02712 +Epoch [528/4000] Training [3/16] Loss: 0.01716 +Epoch [528/4000] Training [4/16] Loss: 0.01600 +Epoch [528/4000] Training [5/16] Loss: 0.02083 +Epoch [528/4000] Training [6/16] Loss: 0.02849 +Epoch [528/4000] Training [7/16] Loss: 0.02238 +Epoch [528/4000] Training [8/16] Loss: 0.02056 +Epoch [528/4000] Training [9/16] Loss: 0.01826 +Epoch [528/4000] Training [10/16] Loss: 0.01817 +Epoch [528/4000] Training [11/16] Loss: 0.02436 +Epoch [528/4000] Training [12/16] Loss: 0.01754 +Epoch [528/4000] Training [13/16] Loss: 0.01579 +Epoch [528/4000] Training [14/16] Loss: 0.02100 +Epoch [528/4000] Training [15/16] Loss: 0.01581 +Epoch [528/4000] Training [16/16] Loss: 0.01547 +Epoch [528/4000] Training metric {'Train/mean dice_metric': 0.9857603907585144, 'Train/mean miou_metric': 0.9719327688217163, 'Train/mean f1': 0.9822598099708557, 'Train/mean precision': 0.9776749610900879, 'Train/mean recall': 0.9868878722190857, 'Train/mean hd95_metric': 3.244899272918701} +Epoch [528/4000] Validation [1/4] Loss: 0.34644 focal_loss 0.22205 dice_loss 0.12439 +Epoch [528/4000] Validation [2/4] Loss: 0.36254 focal_loss 0.11299 dice_loss 0.24955 +Epoch [528/4000] Validation [3/4] Loss: 0.37700 focal_loss 0.19566 dice_loss 0.18134 +Epoch [528/4000] Validation [4/4] Loss: 0.19998 focal_loss 0.10241 dice_loss 0.09757 +Epoch [528/4000] Validation metric {'Val/mean dice_metric': 0.9564172625541687, 'Val/mean miou_metric': 0.9308425188064575, 'Val/mean f1': 0.9595625996589661, 'Val/mean precision': 0.9608704447746277, 'Val/mean recall': 0.958258330821991, 'Val/mean hd95_metric': 9.532343864440918} +Cheakpoint... +Epoch [528/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9564], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9564172625541687, 'Val/mean miou_metric': 0.9308425188064575, 'Val/mean f1': 0.9595625996589661, 'Val/mean precision': 0.9608704447746277, 'Val/mean recall': 0.958258330821991, 'Val/mean hd95_metric': 9.532343864440918} +Epoch [529/4000] Training [1/16] Loss: 0.01943 +Epoch [529/4000] Training [2/16] Loss: 0.01884 +Epoch [529/4000] Training [3/16] Loss: 0.02233 +Epoch [529/4000] Training [4/16] Loss: 0.01440 +Epoch [529/4000] Training [5/16] Loss: 0.01475 +Epoch [529/4000] Training [6/16] Loss: 0.01490 +Epoch [529/4000] Training [7/16] Loss: 0.01832 +Epoch [529/4000] Training [8/16] Loss: 0.01876 +Epoch [529/4000] Training [9/16] Loss: 0.01783 +Epoch [529/4000] Training [10/16] Loss: 0.01852 +Epoch [529/4000] Training [11/16] Loss: 0.01439 +Epoch [529/4000] Training [12/16] Loss: 0.01513 +Epoch [529/4000] Training [13/16] Loss: 0.02079 +Epoch [529/4000] Training [14/16] Loss: 0.01537 +Epoch [529/4000] Training [15/16] Loss: 0.01777 +Epoch [529/4000] Training [16/16] Loss: 0.02684 +Epoch [529/4000] Training metric {'Train/mean dice_metric': 0.9880179166793823, 'Train/mean miou_metric': 0.9762684106826782, 'Train/mean f1': 0.9849551320075989, 'Train/mean precision': 0.9803129434585571, 'Train/mean recall': 0.9896414875984192, 'Train/mean hd95_metric': 1.9396060705184937} +Epoch [529/4000] Validation [1/4] Loss: 0.19116 focal_loss 0.12033 dice_loss 0.07083 +Epoch [529/4000] Validation [2/4] Loss: 0.25484 focal_loss 0.10403 dice_loss 0.15081 +Epoch [529/4000] Validation [3/4] Loss: 0.21885 focal_loss 0.11790 dice_loss 0.10096 +Epoch [529/4000] Validation [4/4] Loss: 0.23069 focal_loss 0.11710 dice_loss 0.11359 +Epoch [529/4000] Validation metric {'Val/mean dice_metric': 0.9667094945907593, 'Val/mean miou_metric': 0.94328373670578, 'Val/mean f1': 0.9667984843254089, 'Val/mean precision': 0.9605475068092346, 'Val/mean recall': 0.9731313586235046, 'Val/mean hd95_metric': 7.094902038574219} +Cheakpoint... +Epoch [529/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667094945907593, 'Val/mean miou_metric': 0.94328373670578, 'Val/mean f1': 0.9667984843254089, 'Val/mean precision': 0.9605475068092346, 'Val/mean recall': 0.9731313586235046, 'Val/mean hd95_metric': 7.094902038574219} +Epoch [530/4000] Training [1/16] Loss: 0.01243 +Epoch [530/4000] Training [2/16] Loss: 0.01629 +Epoch [530/4000] Training [3/16] Loss: 0.00991 +Epoch [530/4000] Training [4/16] Loss: 0.01318 +Epoch [530/4000] Training [5/16] Loss: 0.01438 +Epoch [530/4000] Training [6/16] Loss: 0.01876 +Epoch [530/4000] Training [7/16] Loss: 0.01402 +Epoch [530/4000] Training [8/16] Loss: 0.01634 +Epoch [530/4000] Training [9/16] Loss: 0.01429 +Epoch [530/4000] Training [10/16] Loss: 0.01623 +Epoch [530/4000] Training [11/16] Loss: 0.01281 +Epoch [530/4000] Training [12/16] Loss: 0.01510 +Epoch [530/4000] Training [13/16] Loss: 0.01599 +Epoch [530/4000] Training [14/16] Loss: 0.01952 +Epoch [530/4000] Training [15/16] Loss: 0.01940 +Epoch [530/4000] Training [16/16] Loss: 0.01381 +Epoch [530/4000] Training metric {'Train/mean dice_metric': 0.9886656999588013, 'Train/mean miou_metric': 0.9779441356658936, 'Train/mean f1': 0.9861765503883362, 'Train/mean precision': 0.9817612171173096, 'Train/mean recall': 0.9906316995620728, 'Train/mean hd95_metric': 1.6288552284240723} +Epoch [530/4000] Validation [1/4] Loss: 0.15316 focal_loss 0.09205 dice_loss 0.06110 +Epoch [530/4000] Validation [2/4] Loss: 0.23763 focal_loss 0.09489 dice_loss 0.14274 +Epoch [530/4000] Validation [3/4] Loss: 0.13475 focal_loss 0.06948 dice_loss 0.06527 +Epoch [530/4000] Validation [4/4] Loss: 0.28345 focal_loss 0.14587 dice_loss 0.13758 +Epoch [530/4000] Validation metric {'Val/mean dice_metric': 0.9675877690315247, 'Val/mean miou_metric': 0.945121169090271, 'Val/mean f1': 0.9693013429641724, 'Val/mean precision': 0.9677878618240356, 'Val/mean recall': 0.9708196520805359, 'Val/mean hd95_metric': 6.096461296081543} +Cheakpoint... +Epoch [530/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675877690315247, 'Val/mean miou_metric': 0.945121169090271, 'Val/mean f1': 0.9693013429641724, 'Val/mean precision': 0.9677878618240356, 'Val/mean recall': 0.9708196520805359, 'Val/mean hd95_metric': 6.096461296081543} +Epoch [531/4000] Training [1/16] Loss: 0.01300 +Epoch [531/4000] Training [2/16] Loss: 0.01307 +Epoch [531/4000] Training [3/16] Loss: 0.01284 +Epoch [531/4000] Training [4/16] Loss: 0.01632 +Epoch [531/4000] Training [5/16] Loss: 0.01237 +Epoch [531/4000] Training [6/16] Loss: 0.01563 +Epoch [531/4000] Training [7/16] Loss: 0.01602 +Epoch [531/4000] Training [8/16] Loss: 0.01049 +Epoch [531/4000] Training [9/16] Loss: 0.01476 +Epoch [531/4000] Training [10/16] Loss: 0.01005 +Epoch [531/4000] Training [11/16] Loss: 0.01222 +Epoch [531/4000] Training [12/16] Loss: 0.01507 +Epoch [531/4000] Training [13/16] Loss: 0.01486 +Epoch [531/4000] Training [14/16] Loss: 0.01447 +Epoch [531/4000] Training [15/16] Loss: 0.01790 +Epoch [531/4000] Training [16/16] Loss: 0.01380 +Epoch [531/4000] Training metric {'Train/mean dice_metric': 0.9903464317321777, 'Train/mean miou_metric': 0.9806773066520691, 'Train/mean f1': 0.9872040748596191, 'Train/mean precision': 0.9825710654258728, 'Train/mean recall': 0.9918809533119202, 'Train/mean hd95_metric': 1.2764978408813477} +Epoch [531/4000] Validation [1/4] Loss: 0.14234 focal_loss 0.08409 dice_loss 0.05825 +Epoch [531/4000] Validation [2/4] Loss: 0.46274 focal_loss 0.25345 dice_loss 0.20929 +Epoch [531/4000] Validation [3/4] Loss: 0.15549 focal_loss 0.06825 dice_loss 0.08724 +Epoch [531/4000] Validation [4/4] Loss: 0.20715 focal_loss 0.10155 dice_loss 0.10559 +Epoch [531/4000] Validation metric {'Val/mean dice_metric': 0.966181755065918, 'Val/mean miou_metric': 0.9454218149185181, 'Val/mean f1': 0.9680399894714355, 'Val/mean precision': 0.9635469317436218, 'Val/mean recall': 0.9725750684738159, 'Val/mean hd95_metric': 6.185672760009766} +Cheakpoint... +Epoch [531/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966181755065918, 'Val/mean miou_metric': 0.9454218149185181, 'Val/mean f1': 0.9680399894714355, 'Val/mean precision': 0.9635469317436218, 'Val/mean recall': 0.9725750684738159, 'Val/mean hd95_metric': 6.185672760009766} +Epoch [532/4000] Training [1/16] Loss: 0.01294 +Epoch [532/4000] Training [2/16] Loss: 0.01926 +Epoch [532/4000] Training [3/16] Loss: 0.01223 +Epoch [532/4000] Training [4/16] Loss: 0.01247 +Epoch [532/4000] Training [5/16] Loss: 0.01229 +Epoch [532/4000] Training [6/16] Loss: 0.01509 +Epoch [532/4000] Training [7/16] Loss: 0.01346 +Epoch [532/4000] Training [8/16] Loss: 0.01521 +Epoch [532/4000] Training [9/16] Loss: 0.01074 +Epoch [532/4000] Training [10/16] Loss: 0.01381 +Epoch [532/4000] Training [11/16] Loss: 0.01156 +Epoch [532/4000] Training [12/16] Loss: 0.01080 +Epoch [532/4000] Training [13/16] Loss: 0.01524 +Epoch [532/4000] Training [14/16] Loss: 0.01118 +Epoch [532/4000] Training [15/16] Loss: 0.01719 +Epoch [532/4000] Training [16/16] Loss: 0.01691 +Epoch [532/4000] Training metric {'Train/mean dice_metric': 0.9903231859207153, 'Train/mean miou_metric': 0.9806227684020996, 'Train/mean f1': 0.9871124625205994, 'Train/mean precision': 0.9825321435928345, 'Train/mean recall': 0.9917356967926025, 'Train/mean hd95_metric': 1.2693495750427246} +Epoch [532/4000] Validation [1/4] Loss: 0.19434 focal_loss 0.11866 dice_loss 0.07568 +Epoch [532/4000] Validation [2/4] Loss: 0.70498 focal_loss 0.40082 dice_loss 0.30415 +Epoch [532/4000] Validation [3/4] Loss: 0.20888 focal_loss 0.11001 dice_loss 0.09887 +Epoch [532/4000] Validation [4/4] Loss: 0.23409 focal_loss 0.11121 dice_loss 0.12288 +Epoch [532/4000] Validation metric {'Val/mean dice_metric': 0.9664214849472046, 'Val/mean miou_metric': 0.9451917409896851, 'Val/mean f1': 0.9669656753540039, 'Val/mean precision': 0.9638033509254456, 'Val/mean recall': 0.9701488018035889, 'Val/mean hd95_metric': 5.959303855895996} +Cheakpoint... +Epoch [532/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664214849472046, 'Val/mean miou_metric': 0.9451917409896851, 'Val/mean f1': 0.9669656753540039, 'Val/mean precision': 0.9638033509254456, 'Val/mean recall': 0.9701488018035889, 'Val/mean hd95_metric': 5.959303855895996} +Epoch [533/4000] Training [1/16] Loss: 0.02177 +Epoch [533/4000] Training [2/16] Loss: 0.01378 +Epoch [533/4000] Training [3/16] Loss: 0.01555 +Epoch [533/4000] Training [4/16] Loss: 0.02607 +Epoch [533/4000] Training [5/16] Loss: 0.01460 +Epoch [533/4000] Training [6/16] Loss: 0.01465 +Epoch [533/4000] Training [7/16] Loss: 0.01225 +Epoch [533/4000] Training [8/16] Loss: 0.01340 +Epoch [533/4000] Training [9/16] Loss: 0.01475 +Epoch [533/4000] Training [10/16] Loss: 0.02655 +Epoch [533/4000] Training [11/16] Loss: 0.01517 +Epoch [533/4000] Training [12/16] Loss: 0.01378 +Epoch [533/4000] Training [13/16] Loss: 0.01552 +Epoch [533/4000] Training [14/16] Loss: 0.01259 +Epoch [533/4000] Training [15/16] Loss: 0.01470 +Epoch [533/4000] Training [16/16] Loss: 0.01142 +Epoch [533/4000] Training metric {'Train/mean dice_metric': 0.9873607754707336, 'Train/mean miou_metric': 0.9761602878570557, 'Train/mean f1': 0.985582709312439, 'Train/mean precision': 0.9802892804145813, 'Train/mean recall': 0.9909335374832153, 'Train/mean hd95_metric': 2.411226272583008} +Epoch [533/4000] Validation [1/4] Loss: 0.18944 focal_loss 0.10711 dice_loss 0.08234 +Epoch [533/4000] Validation [2/4] Loss: 0.35805 focal_loss 0.15857 dice_loss 0.19947 +Epoch [533/4000] Validation [3/4] Loss: 0.16192 focal_loss 0.07226 dice_loss 0.08965 +Epoch [533/4000] Validation [4/4] Loss: 0.29464 focal_loss 0.16153 dice_loss 0.13310 +Epoch [533/4000] Validation metric {'Val/mean dice_metric': 0.9612913131713867, 'Val/mean miou_metric': 0.938552975654602, 'Val/mean f1': 0.9638890027999878, 'Val/mean precision': 0.9622838497161865, 'Val/mean recall': 0.9654995203018188, 'Val/mean hd95_metric': 7.241457939147949} +Cheakpoint... +Epoch [533/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612913131713867, 'Val/mean miou_metric': 0.938552975654602, 'Val/mean f1': 0.9638890027999878, 'Val/mean precision': 0.9622838497161865, 'Val/mean recall': 0.9654995203018188, 'Val/mean hd95_metric': 7.241457939147949} +Epoch [534/4000] Training [1/16] Loss: 0.01133 +Epoch [534/4000] Training [2/16] Loss: 0.01694 +Epoch [534/4000] Training [3/16] Loss: 0.01458 +Epoch [534/4000] Training [4/16] Loss: 0.01546 +Epoch [534/4000] Training [5/16] Loss: 0.01355 +Epoch [534/4000] Training [6/16] Loss: 0.01724 +Epoch [534/4000] Training [7/16] Loss: 0.01352 +Epoch [534/4000] Training [8/16] Loss: 0.01890 +Epoch [534/4000] Training [9/16] Loss: 0.01626 +Epoch [534/4000] Training [10/16] Loss: 0.01543 +Epoch [534/4000] Training [11/16] Loss: 0.01369 +Epoch [534/4000] Training [12/16] Loss: 0.01631 +Epoch [534/4000] Training [13/16] Loss: 0.01342 +Epoch [534/4000] Training [14/16] Loss: 0.01515 +Epoch [534/4000] Training [15/16] Loss: 0.02173 +Epoch [534/4000] Training [16/16] Loss: 0.02165 +Epoch [534/4000] Training metric {'Train/mean dice_metric': 0.9891716241836548, 'Train/mean miou_metric': 0.9783966541290283, 'Train/mean f1': 0.9858625531196594, 'Train/mean precision': 0.9813807606697083, 'Train/mean recall': 0.9903855323791504, 'Train/mean hd95_metric': 2.4733994007110596} +Epoch [534/4000] Validation [1/4] Loss: 0.15391 focal_loss 0.09046 dice_loss 0.06345 +Epoch [534/4000] Validation [2/4] Loss: 0.39810 focal_loss 0.16834 dice_loss 0.22976 +Epoch [534/4000] Validation [3/4] Loss: 0.13630 focal_loss 0.06776 dice_loss 0.06854 +Epoch [534/4000] Validation [4/4] Loss: 0.21809 focal_loss 0.10419 dice_loss 0.11391 +Epoch [534/4000] Validation metric {'Val/mean dice_metric': 0.963382363319397, 'Val/mean miou_metric': 0.9423003196716309, 'Val/mean f1': 0.9657068252563477, 'Val/mean precision': 0.9570713043212891, 'Val/mean recall': 0.9744997024536133, 'Val/mean hd95_metric': 7.638722896575928} +Cheakpoint... +Epoch [534/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963382363319397, 'Val/mean miou_metric': 0.9423003196716309, 'Val/mean f1': 0.9657068252563477, 'Val/mean precision': 0.9570713043212891, 'Val/mean recall': 0.9744997024536133, 'Val/mean hd95_metric': 7.638722896575928} +Epoch [535/4000] Training [1/16] Loss: 0.01787 +Epoch [535/4000] Training [2/16] Loss: 0.01229 +Epoch [535/4000] Training [3/16] Loss: 0.01769 +Epoch [535/4000] Training [4/16] Loss: 0.01871 +Epoch [535/4000] Training [5/16] Loss: 0.01723 +Epoch [535/4000] Training [6/16] Loss: 0.01590 +Epoch [535/4000] Training [7/16] Loss: 0.02059 +Epoch [535/4000] Training [8/16] Loss: 0.01129 +Epoch [535/4000] Training [9/16] Loss: 0.01564 +Epoch [535/4000] Training [10/16] Loss: 0.01460 +Epoch [535/4000] Training [11/16] Loss: 0.01566 +Epoch [535/4000] Training [12/16] Loss: 0.03001 +Epoch [535/4000] Training [13/16] Loss: 0.01640 +Epoch [535/4000] Training [14/16] Loss: 0.01206 +Epoch [535/4000] Training [15/16] Loss: 0.03253 +Epoch [535/4000] Training [16/16] Loss: 0.01578 +Epoch [535/4000] Training metric {'Train/mean dice_metric': 0.9865090847015381, 'Train/mean miou_metric': 0.973791241645813, 'Train/mean f1': 0.9844729900360107, 'Train/mean precision': 0.9807475805282593, 'Train/mean recall': 0.9882268309593201, 'Train/mean hd95_metric': 2.3792502880096436} +Epoch [535/4000] Validation [1/4] Loss: 0.47783 focal_loss 0.35461 dice_loss 0.12322 +Epoch [535/4000] Validation [2/4] Loss: 0.15195 focal_loss 0.06157 dice_loss 0.09038 +Epoch [535/4000] Validation [3/4] Loss: 0.15572 focal_loss 0.08410 dice_loss 0.07162 +Epoch [535/4000] Validation [4/4] Loss: 0.25751 focal_loss 0.12020 dice_loss 0.13731 +Epoch [535/4000] Validation metric {'Val/mean dice_metric': 0.963479220867157, 'Val/mean miou_metric': 0.9397131204605103, 'Val/mean f1': 0.9647347927093506, 'Val/mean precision': 0.9600013494491577, 'Val/mean recall': 0.9695151448249817, 'Val/mean hd95_metric': 6.880915641784668} +Cheakpoint... +Epoch [535/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9635], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963479220867157, 'Val/mean miou_metric': 0.9397131204605103, 'Val/mean f1': 0.9647347927093506, 'Val/mean precision': 0.9600013494491577, 'Val/mean recall': 0.9695151448249817, 'Val/mean hd95_metric': 6.880915641784668} +Epoch [536/4000] Training [1/16] Loss: 0.01681 +Epoch [536/4000] Training [2/16] Loss: 0.01203 +Epoch [536/4000] Training [3/16] Loss: 0.02183 +Epoch [536/4000] Training [4/16] Loss: 0.01266 +Epoch [536/4000] Training [5/16] Loss: 0.01560 +Epoch [536/4000] Training [6/16] Loss: 0.01663 +Epoch [536/4000] Training [7/16] Loss: 0.03329 +Epoch [536/4000] Training [8/16] Loss: 0.01507 +Epoch [536/4000] Training [9/16] Loss: 0.01627 +Epoch [536/4000] Training [10/16] Loss: 0.01785 +Epoch [536/4000] Training [11/16] Loss: 0.01226 +Epoch [536/4000] Training [12/16] Loss: 0.01694 +Epoch [536/4000] Training [13/16] Loss: 0.01916 +Epoch [536/4000] Training [14/16] Loss: 0.01913 +Epoch [536/4000] Training [15/16] Loss: 0.07261 +Epoch [536/4000] Training [16/16] Loss: 0.01882 +Epoch [536/4000] Training metric {'Train/mean dice_metric': 0.985234797000885, 'Train/mean miou_metric': 0.9719465374946594, 'Train/mean f1': 0.9818844199180603, 'Train/mean precision': 0.9778922200202942, 'Train/mean recall': 0.9859094023704529, 'Train/mean hd95_metric': 3.6244454383850098} +Epoch [536/4000] Validation [1/4] Loss: 0.45312 focal_loss 0.26168 dice_loss 0.19144 +Epoch [536/4000] Validation [2/4] Loss: 0.44064 focal_loss 0.21153 dice_loss 0.22911 +Epoch [536/4000] Validation [3/4] Loss: 0.29091 focal_loss 0.13343 dice_loss 0.15748 +Epoch [536/4000] Validation [4/4] Loss: 0.47321 focal_loss 0.29357 dice_loss 0.17964 +Epoch [536/4000] Validation metric {'Val/mean dice_metric': 0.9552000164985657, 'Val/mean miou_metric': 0.9274972081184387, 'Val/mean f1': 0.955653190612793, 'Val/mean precision': 0.9626909494400024, 'Val/mean recall': 0.9487173557281494, 'Val/mean hd95_metric': 10.12334156036377} +Cheakpoint... +Epoch [536/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9552], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9552000164985657, 'Val/mean miou_metric': 0.9274972081184387, 'Val/mean f1': 0.955653190612793, 'Val/mean precision': 0.9626909494400024, 'Val/mean recall': 0.9487173557281494, 'Val/mean hd95_metric': 10.12334156036377} +Epoch [537/4000] Training [1/16] Loss: 0.08919 +Epoch [537/4000] Training [2/16] Loss: 0.03321 +Epoch [537/4000] Training [3/16] Loss: 0.03277 +Epoch [537/4000] Training [4/16] Loss: 0.02135 +Epoch [537/4000] Training [5/16] Loss: 0.03449 +Epoch [537/4000] Training [6/16] Loss: 0.06647 +Epoch [537/4000] Training [7/16] Loss: 0.02472 +Epoch [537/4000] Training [8/16] Loss: 0.02161 +Epoch [537/4000] Training [9/16] Loss: 0.01962 +Epoch [537/4000] Training [10/16] Loss: 0.01596 +Epoch [537/4000] Training [11/16] Loss: 0.02058 +Epoch [537/4000] Training [12/16] Loss: 0.01840 +Epoch [537/4000] Training [13/16] Loss: 0.01926 +Epoch [537/4000] Training [14/16] Loss: 0.02659 +Epoch [537/4000] Training [15/16] Loss: 0.01292 +Epoch [537/4000] Training [16/16] Loss: 0.02498 +Epoch [537/4000] Training metric {'Train/mean dice_metric': 0.9819725155830383, 'Train/mean miou_metric': 0.965265691280365, 'Train/mean f1': 0.9780168533325195, 'Train/mean precision': 0.9742478132247925, 'Train/mean recall': 0.9818150997161865, 'Train/mean hd95_metric': 6.220847129821777} +Epoch [537/4000] Validation [1/4] Loss: 0.13126 focal_loss 0.07514 dice_loss 0.05611 +Epoch [537/4000] Validation [2/4] Loss: 0.39598 focal_loss 0.22067 dice_loss 0.17532 +Epoch [537/4000] Validation [3/4] Loss: 0.23344 focal_loss 0.12191 dice_loss 0.11153 +Epoch [537/4000] Validation [4/4] Loss: 0.27941 focal_loss 0.14400 dice_loss 0.13542 +Epoch [537/4000] Validation metric {'Val/mean dice_metric': 0.9593775868415833, 'Val/mean miou_metric': 0.9312772750854492, 'Val/mean f1': 0.9590426087379456, 'Val/mean precision': 0.953698992729187, 'Val/mean recall': 0.9644461870193481, 'Val/mean hd95_metric': 11.724729537963867} +Cheakpoint... +Epoch [537/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9594], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9593775868415833, 'Val/mean miou_metric': 0.9312772750854492, 'Val/mean f1': 0.9590426087379456, 'Val/mean precision': 0.953698992729187, 'Val/mean recall': 0.9644461870193481, 'Val/mean hd95_metric': 11.724729537963867} +Epoch [538/4000] Training [1/16] Loss: 0.02101 +Epoch [538/4000] Training [2/16] Loss: 0.01762 +Epoch [538/4000] Training [3/16] Loss: 0.01995 +Epoch [538/4000] Training [4/16] Loss: 0.01661 +Epoch [538/4000] Training [5/16] Loss: 0.02015 +Epoch [538/4000] Training [6/16] Loss: 0.01878 +Epoch [538/4000] Training [7/16] Loss: 0.02097 +Epoch [538/4000] Training [8/16] Loss: 0.01762 +Epoch [538/4000] Training [9/16] Loss: 0.03645 +Epoch [538/4000] Training [10/16] Loss: 0.01880 +Epoch [538/4000] Training [11/16] Loss: 0.01653 +Epoch [538/4000] Training [12/16] Loss: 0.01721 +Epoch [538/4000] Training [13/16] Loss: 0.01859 +Epoch [538/4000] Training [14/16] Loss: 0.01983 +Epoch [538/4000] Training [15/16] Loss: 0.02065 +Epoch [538/4000] Training [16/16] Loss: 0.01596 +Epoch [538/4000] Training metric {'Train/mean dice_metric': 0.9841979742050171, 'Train/mean miou_metric': 0.9695373773574829, 'Train/mean f1': 0.9817327857017517, 'Train/mean precision': 0.9778823256492615, 'Train/mean recall': 0.9856136441230774, 'Train/mean hd95_metric': 3.757099151611328} +Epoch [538/4000] Validation [1/4] Loss: 0.14182 focal_loss 0.07414 dice_loss 0.06768 +Epoch [538/4000] Validation [2/4] Loss: 0.28968 focal_loss 0.12878 dice_loss 0.16090 +Epoch [538/4000] Validation [3/4] Loss: 0.16341 focal_loss 0.06393 dice_loss 0.09948 +Epoch [538/4000] Validation [4/4] Loss: 0.35999 focal_loss 0.19207 dice_loss 0.16792 +Epoch [538/4000] Validation metric {'Val/mean dice_metric': 0.957484245300293, 'Val/mean miou_metric': 0.9308886528015137, 'Val/mean f1': 0.961685836315155, 'Val/mean precision': 0.9608142971992493, 'Val/mean recall': 0.962558925151825, 'Val/mean hd95_metric': 8.767727851867676} +Cheakpoint... +Epoch [538/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9575], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.957484245300293, 'Val/mean miou_metric': 0.9308886528015137, 'Val/mean f1': 0.961685836315155, 'Val/mean precision': 0.9608142971992493, 'Val/mean recall': 0.962558925151825, 'Val/mean hd95_metric': 8.767727851867676} +Epoch [539/4000] Training [1/16] Loss: 0.01704 +Epoch [539/4000] Training [2/16] Loss: 0.02327 +Epoch [539/4000] Training [3/16] Loss: 0.02152 +Epoch [539/4000] Training [4/16] Loss: 0.01659 +Epoch [539/4000] Training [5/16] Loss: 0.02075 +Epoch [539/4000] Training [6/16] Loss: 0.02086 +Epoch [539/4000] Training [7/16] Loss: 0.16158 +Epoch [539/4000] Training [8/16] Loss: 0.01972 +Epoch [539/4000] Training [9/16] Loss: 0.01492 +Epoch [539/4000] Training [10/16] Loss: 0.02197 +Epoch [539/4000] Training [11/16] Loss: 0.01982 +Epoch [539/4000] Training [12/16] Loss: 0.01525 +Epoch [539/4000] Training [13/16] Loss: 0.01470 +Epoch [539/4000] Training [14/16] Loss: 0.01606 +Epoch [539/4000] Training [15/16] Loss: 0.02885 +Epoch [539/4000] Training [16/16] Loss: 0.04137 +Epoch [539/4000] Training metric {'Train/mean dice_metric': 0.9820642471313477, 'Train/mean miou_metric': 0.9670103788375854, 'Train/mean f1': 0.9802390933036804, 'Train/mean precision': 0.9775722026824951, 'Train/mean recall': 0.9829205870628357, 'Train/mean hd95_metric': 4.146039962768555} +Epoch [539/4000] Validation [1/4] Loss: 0.20422 focal_loss 0.11751 dice_loss 0.08670 +Epoch [539/4000] Validation [2/4] Loss: 0.33952 focal_loss 0.15441 dice_loss 0.18511 +Epoch [539/4000] Validation [3/4] Loss: 0.21922 focal_loss 0.09490 dice_loss 0.12432 +Epoch [539/4000] Validation [4/4] Loss: 0.52583 focal_loss 0.27553 dice_loss 0.25030 +Epoch [539/4000] Validation metric {'Val/mean dice_metric': 0.9462709426879883, 'Val/mean miou_metric': 0.9184495210647583, 'Val/mean f1': 0.9463785886764526, 'Val/mean precision': 0.9273912906646729, 'Val/mean recall': 0.9661595821380615, 'Val/mean hd95_metric': 14.384724617004395} +Cheakpoint... +Epoch [539/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9463], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9462709426879883, 'Val/mean miou_metric': 0.9184495210647583, 'Val/mean f1': 0.9463785886764526, 'Val/mean precision': 0.9273912906646729, 'Val/mean recall': 0.9661595821380615, 'Val/mean hd95_metric': 14.384724617004395} +Epoch [540/4000] Training [1/16] Loss: 0.04384 +Epoch [540/4000] Training [2/16] Loss: 0.02139 +Epoch [540/4000] Training [3/16] Loss: 0.04545 +Epoch [540/4000] Training [4/16] Loss: 0.02595 +Epoch [540/4000] Training [5/16] Loss: 0.02009 +Epoch [540/4000] Training [6/16] Loss: 0.02006 +Epoch [540/4000] Training [7/16] Loss: 0.02541 +Epoch [540/4000] Training [8/16] Loss: 0.02034 +Epoch [540/4000] Training [9/16] Loss: 0.02205 +Epoch [540/4000] Training [10/16] Loss: 0.03897 +Epoch [540/4000] Training [11/16] Loss: 0.01780 +Epoch [540/4000] Training [12/16] Loss: 0.01846 +Epoch [540/4000] Training [13/16] Loss: 0.01628 +Epoch [540/4000] Training [14/16] Loss: 0.01446 +Epoch [540/4000] Training [15/16] Loss: 0.01567 +Epoch [540/4000] Training [16/16] Loss: 0.01797 +Epoch [540/4000] Training metric {'Train/mean dice_metric': 0.9843682050704956, 'Train/mean miou_metric': 0.9693379998207092, 'Train/mean f1': 0.9822755455970764, 'Train/mean precision': 0.9775940775871277, 'Train/mean recall': 0.9870020747184753, 'Train/mean hd95_metric': 3.437548875808716} +Epoch [540/4000] Validation [1/4] Loss: 0.17531 focal_loss 0.09465 dice_loss 0.08066 +Epoch [540/4000] Validation [2/4] Loss: 0.66251 focal_loss 0.36275 dice_loss 0.29976 +Epoch [540/4000] Validation [3/4] Loss: 0.34556 focal_loss 0.19006 dice_loss 0.15550 +Epoch [540/4000] Validation [4/4] Loss: 0.43365 focal_loss 0.25072 dice_loss 0.18292 +Epoch [540/4000] Validation metric {'Val/mean dice_metric': 0.9569002389907837, 'Val/mean miou_metric': 0.9298270344734192, 'Val/mean f1': 0.9611504673957825, 'Val/mean precision': 0.9634168148040771, 'Val/mean recall': 0.958894670009613, 'Val/mean hd95_metric': 8.805880546569824} +Cheakpoint... +Epoch [540/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9569], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9569002389907837, 'Val/mean miou_metric': 0.9298270344734192, 'Val/mean f1': 0.9611504673957825, 'Val/mean precision': 0.9634168148040771, 'Val/mean recall': 0.958894670009613, 'Val/mean hd95_metric': 8.805880546569824} +Epoch [541/4000] Training [1/16] Loss: 0.01420 +Epoch [541/4000] Training [2/16] Loss: 0.01992 +Epoch [541/4000] Training [3/16] Loss: 0.02299 +Epoch [541/4000] Training [4/16] Loss: 0.01418 +Epoch [541/4000] Training [5/16] Loss: 0.01610 +Epoch [541/4000] Training [6/16] Loss: 0.01338 +Epoch [541/4000] Training [7/16] Loss: 0.02098 +Epoch [541/4000] Training [8/16] Loss: 0.02441 +Epoch [541/4000] Training [9/16] Loss: 0.02239 +Epoch [541/4000] Training [10/16] Loss: 0.01649 +Epoch [541/4000] Training [11/16] Loss: 0.01339 +Epoch [541/4000] Training [12/16] Loss: 0.01881 +Epoch [541/4000] Training [13/16] Loss: 0.01809 +Epoch [541/4000] Training [14/16] Loss: 0.01640 +Epoch [541/4000] Training [15/16] Loss: 0.01662 +Epoch [541/4000] Training [16/16] Loss: 0.01857 +Epoch [541/4000] Training metric {'Train/mean dice_metric': 0.9872268438339233, 'Train/mean miou_metric': 0.9746699929237366, 'Train/mean f1': 0.984252393245697, 'Train/mean precision': 0.9799788594245911, 'Train/mean recall': 0.9885632991790771, 'Train/mean hd95_metric': 1.8910928964614868} +Epoch [541/4000] Validation [1/4] Loss: 0.11916 focal_loss 0.06017 dice_loss 0.05898 +Epoch [541/4000] Validation [2/4] Loss: 0.46601 focal_loss 0.22808 dice_loss 0.23793 +Epoch [541/4000] Validation [3/4] Loss: 0.31685 focal_loss 0.14883 dice_loss 0.16802 +Epoch [541/4000] Validation [4/4] Loss: 0.19973 focal_loss 0.07883 dice_loss 0.12089 +Epoch [541/4000] Validation metric {'Val/mean dice_metric': 0.9610663652420044, 'Val/mean miou_metric': 0.937907874584198, 'Val/mean f1': 0.9665723443031311, 'Val/mean precision': 0.9621083736419678, 'Val/mean recall': 0.9710777997970581, 'Val/mean hd95_metric': 7.023324489593506} +Cheakpoint... +Epoch [541/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610663652420044, 'Val/mean miou_metric': 0.937907874584198, 'Val/mean f1': 0.9665723443031311, 'Val/mean precision': 0.9621083736419678, 'Val/mean recall': 0.9710777997970581, 'Val/mean hd95_metric': 7.023324489593506} +Epoch [542/4000] Training [1/16] Loss: 0.01620 +Epoch [542/4000] Training [2/16] Loss: 0.01407 +Epoch [542/4000] Training [3/16] Loss: 0.01665 +Epoch [542/4000] Training [4/16] Loss: 0.01296 +Epoch [542/4000] Training [5/16] Loss: 0.01784 +Epoch [542/4000] Training [6/16] Loss: 0.01489 +Epoch [542/4000] Training [7/16] Loss: 0.01730 +Epoch [542/4000] Training [8/16] Loss: 0.01678 +Epoch [542/4000] Training [9/16] Loss: 0.01434 +Epoch [542/4000] Training [10/16] Loss: 0.01225 +Epoch [542/4000] Training [11/16] Loss: 0.01540 +Epoch [542/4000] Training [12/16] Loss: 0.01741 +Epoch [542/4000] Training [13/16] Loss: 0.01239 +Epoch [542/4000] Training [14/16] Loss: 0.01082 +Epoch [542/4000] Training [15/16] Loss: 0.01261 +Epoch [542/4000] Training [16/16] Loss: 0.01766 +Epoch [542/4000] Training metric {'Train/mean dice_metric': 0.9888722896575928, 'Train/mean miou_metric': 0.9779157042503357, 'Train/mean f1': 0.9858840107917786, 'Train/mean precision': 0.9814644455909729, 'Train/mean recall': 0.9903435111045837, 'Train/mean hd95_metric': 2.002974510192871} +Epoch [542/4000] Validation [1/4] Loss: 0.15950 focal_loss 0.09158 dice_loss 0.06792 +Epoch [542/4000] Validation [2/4] Loss: 0.34286 focal_loss 0.15876 dice_loss 0.18410 +Epoch [542/4000] Validation [3/4] Loss: 0.26447 focal_loss 0.15860 dice_loss 0.10587 +Epoch [542/4000] Validation [4/4] Loss: 0.22318 focal_loss 0.11207 dice_loss 0.11111 +Epoch [542/4000] Validation metric {'Val/mean dice_metric': 0.9662405848503113, 'Val/mean miou_metric': 0.9433088302612305, 'Val/mean f1': 0.9667367935180664, 'Val/mean precision': 0.9564847350120544, 'Val/mean recall': 0.977211058139801, 'Val/mean hd95_metric': 7.550763130187988} +Cheakpoint... +Epoch [542/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662405848503113, 'Val/mean miou_metric': 0.9433088302612305, 'Val/mean f1': 0.9667367935180664, 'Val/mean precision': 0.9564847350120544, 'Val/mean recall': 0.977211058139801, 'Val/mean hd95_metric': 7.550763130187988} +Epoch [543/4000] Training [1/16] Loss: 0.01471 +Epoch [543/4000] Training [2/16] Loss: 0.01513 +Epoch [543/4000] Training [3/16] Loss: 0.01476 +Epoch [543/4000] Training [4/16] Loss: 0.01727 +Epoch [543/4000] Training [5/16] Loss: 0.01890 +Epoch [543/4000] Training [6/16] Loss: 0.01796 +Epoch [543/4000] Training [7/16] Loss: 0.01273 +Epoch [543/4000] Training [8/16] Loss: 0.01401 +Epoch [543/4000] Training [9/16] Loss: 0.01857 +Epoch [543/4000] Training [10/16] Loss: 0.01709 +Epoch [543/4000] Training [11/16] Loss: 0.02051 +Epoch [543/4000] Training [12/16] Loss: 0.01245 +Epoch [543/4000] Training [13/16] Loss: 0.01656 +Epoch [543/4000] Training [14/16] Loss: 0.01729 +Epoch [543/4000] Training [15/16] Loss: 0.01904 +Epoch [543/4000] Training [16/16] Loss: 0.01234 +Epoch [543/4000] Training metric {'Train/mean dice_metric': 0.988366425037384, 'Train/mean miou_metric': 0.9770249128341675, 'Train/mean f1': 0.9853107333183289, 'Train/mean precision': 0.9808555841445923, 'Train/mean recall': 0.9898065328598022, 'Train/mean hd95_metric': 1.771456241607666} +Epoch [543/4000] Validation [1/4] Loss: 0.10563 focal_loss 0.05548 dice_loss 0.05015 +Epoch [543/4000] Validation [2/4] Loss: 0.19644 focal_loss 0.06506 dice_loss 0.13138 +Epoch [543/4000] Validation [3/4] Loss: 0.21122 focal_loss 0.11604 dice_loss 0.09518 +Epoch [543/4000] Validation [4/4] Loss: 0.19785 focal_loss 0.09112 dice_loss 0.10674 +Epoch [543/4000] Validation metric {'Val/mean dice_metric': 0.9639312028884888, 'Val/mean miou_metric': 0.9418575167655945, 'Val/mean f1': 0.9672790169715881, 'Val/mean precision': 0.9588838219642639, 'Val/mean recall': 0.9758224487304688, 'Val/mean hd95_metric': 7.074632167816162} +Cheakpoint... +Epoch [543/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639312028884888, 'Val/mean miou_metric': 0.9418575167655945, 'Val/mean f1': 0.9672790169715881, 'Val/mean precision': 0.9588838219642639, 'Val/mean recall': 0.9758224487304688, 'Val/mean hd95_metric': 7.074632167816162} +Epoch [544/4000] Training [1/16] Loss: 0.00996 +Epoch [544/4000] Training [2/16] Loss: 0.01114 +Epoch [544/4000] Training [3/16] Loss: 0.01715 +Epoch [544/4000] Training [4/16] Loss: 0.02337 +Epoch [544/4000] Training [5/16] Loss: 0.01498 +Epoch [544/4000] Training [6/16] Loss: 0.01103 +Epoch [544/4000] Training [7/16] Loss: 0.01410 +Epoch [544/4000] Training [8/16] Loss: 0.01087 +Epoch [544/4000] Training [9/16] Loss: 0.01435 +Epoch [544/4000] Training [10/16] Loss: 0.01446 +Epoch [544/4000] Training [11/16] Loss: 0.01401 +Epoch [544/4000] Training [12/16] Loss: 0.01148 +Epoch [544/4000] Training [13/16] Loss: 0.01560 +Epoch [544/4000] Training [14/16] Loss: 0.02160 +Epoch [544/4000] Training [15/16] Loss: 0.02359 +Epoch [544/4000] Training [16/16] Loss: 0.01927 +Epoch [544/4000] Training metric {'Train/mean dice_metric': 0.9888057708740234, 'Train/mean miou_metric': 0.9779919385910034, 'Train/mean f1': 0.9863721132278442, 'Train/mean precision': 0.9815617203712463, 'Train/mean recall': 0.9912298917770386, 'Train/mean hd95_metric': 1.5500245094299316} +Epoch [544/4000] Validation [1/4] Loss: 0.13995 focal_loss 0.08005 dice_loss 0.05990 +Epoch [544/4000] Validation [2/4] Loss: 0.51108 focal_loss 0.22448 dice_loss 0.28661 +Epoch [544/4000] Validation [3/4] Loss: 0.24769 focal_loss 0.15012 dice_loss 0.09757 +Epoch [544/4000] Validation [4/4] Loss: 0.28710 focal_loss 0.11957 dice_loss 0.16752 +Epoch [544/4000] Validation metric {'Val/mean dice_metric': 0.9653501510620117, 'Val/mean miou_metric': 0.9429374933242798, 'Val/mean f1': 0.9685915112495422, 'Val/mean precision': 0.9629513025283813, 'Val/mean recall': 0.974298357963562, 'Val/mean hd95_metric': 6.693845272064209} +Cheakpoint... +Epoch [544/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653501510620117, 'Val/mean miou_metric': 0.9429374933242798, 'Val/mean f1': 0.9685915112495422, 'Val/mean precision': 0.9629513025283813, 'Val/mean recall': 0.974298357963562, 'Val/mean hd95_metric': 6.693845272064209} +Epoch [545/4000] Training [1/16] Loss: 0.01434 +Epoch [545/4000] Training [2/16] Loss: 0.01252 +Epoch [545/4000] Training [3/16] Loss: 0.01413 +Epoch [545/4000] Training [4/16] Loss: 0.01560 +Epoch [545/4000] Training [5/16] Loss: 0.01864 +Epoch [545/4000] Training [6/16] Loss: 0.01248 +Epoch [545/4000] Training [7/16] Loss: 0.01583 +Epoch [545/4000] Training [8/16] Loss: 0.01334 +Epoch [545/4000] Training [9/16] Loss: 0.01073 +Epoch [545/4000] Training [10/16] Loss: 0.01429 +Epoch [545/4000] Training [11/16] Loss: 0.01492 +Epoch [545/4000] Training [12/16] Loss: 0.01691 +Epoch [545/4000] Training [13/16] Loss: 0.01914 +Epoch [545/4000] Training [14/16] Loss: 0.01608 +Epoch [545/4000] Training [15/16] Loss: 0.01411 +Epoch [545/4000] Training [16/16] Loss: 0.01518 +Epoch [545/4000] Training metric {'Train/mean dice_metric': 0.9893536567687988, 'Train/mean miou_metric': 0.9787590503692627, 'Train/mean f1': 0.9855899214744568, 'Train/mean precision': 0.9809006452560425, 'Train/mean recall': 0.9903242588043213, 'Train/mean hd95_metric': 1.7282915115356445} +Epoch [545/4000] Validation [1/4] Loss: 0.14068 focal_loss 0.08288 dice_loss 0.05779 +Epoch [545/4000] Validation [2/4] Loss: 0.28020 focal_loss 0.10661 dice_loss 0.17359 +Epoch [545/4000] Validation [3/4] Loss: 0.27906 focal_loss 0.17482 dice_loss 0.10425 +Epoch [545/4000] Validation [4/4] Loss: 0.15820 focal_loss 0.06161 dice_loss 0.09659 +Epoch [545/4000] Validation metric {'Val/mean dice_metric': 0.9688525199890137, 'Val/mean miou_metric': 0.9474515914916992, 'Val/mean f1': 0.9699900150299072, 'Val/mean precision': 0.9637322425842285, 'Val/mean recall': 0.9763296842575073, 'Val/mean hd95_metric': 6.2051801681518555} +Cheakpoint... +Epoch [545/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688525199890137, 'Val/mean miou_metric': 0.9474515914916992, 'Val/mean f1': 0.9699900150299072, 'Val/mean precision': 0.9637322425842285, 'Val/mean recall': 0.9763296842575073, 'Val/mean hd95_metric': 6.2051801681518555} +Epoch [546/4000] Training [1/16] Loss: 0.01154 +Epoch [546/4000] Training [2/16] Loss: 0.01567 +Epoch [546/4000] Training [3/16] Loss: 0.01535 +Epoch [546/4000] Training [4/16] Loss: 0.01348 +Epoch [546/4000] Training [5/16] Loss: 0.01707 +Epoch [546/4000] Training [6/16] Loss: 0.01377 +Epoch [546/4000] Training [7/16] Loss: 0.01319 +Epoch [546/4000] Training [8/16] Loss: 0.01720 +Epoch [546/4000] Training [9/16] Loss: 0.01995 +Epoch [546/4000] Training [10/16] Loss: 0.03105 +Epoch [546/4000] Training [11/16] Loss: 0.01192 +Epoch [546/4000] Training [12/16] Loss: 0.01168 +Epoch [546/4000] Training [13/16] Loss: 0.01436 +Epoch [546/4000] Training [14/16] Loss: 0.01413 +Epoch [546/4000] Training [15/16] Loss: 0.01724 +Epoch [546/4000] Training [16/16] Loss: 0.01540 +Epoch [546/4000] Training metric {'Train/mean dice_metric': 0.9892188310623169, 'Train/mean miou_metric': 0.9785782098770142, 'Train/mean f1': 0.98647540807724, 'Train/mean precision': 0.981669008731842, 'Train/mean recall': 0.9913290739059448, 'Train/mean hd95_metric': 1.683298110961914} +Epoch [546/4000] Validation [1/4] Loss: 0.14781 focal_loss 0.08828 dice_loss 0.05953 +Epoch [546/4000] Validation [2/4] Loss: 0.36271 focal_loss 0.16998 dice_loss 0.19273 +Epoch [546/4000] Validation [3/4] Loss: 0.25718 focal_loss 0.15710 dice_loss 0.10008 +Epoch [546/4000] Validation [4/4] Loss: 0.24345 focal_loss 0.11702 dice_loss 0.12643 +Epoch [546/4000] Validation metric {'Val/mean dice_metric': 0.9649284482002258, 'Val/mean miou_metric': 0.9424343109130859, 'Val/mean f1': 0.9680542945861816, 'Val/mean precision': 0.9656379222869873, 'Val/mean recall': 0.9704826474189758, 'Val/mean hd95_metric': 6.360306739807129} +Cheakpoint... +Epoch [546/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649284482002258, 'Val/mean miou_metric': 0.9424343109130859, 'Val/mean f1': 0.9680542945861816, 'Val/mean precision': 0.9656379222869873, 'Val/mean recall': 0.9704826474189758, 'Val/mean hd95_metric': 6.360306739807129} +Epoch [547/4000] Training [1/16] Loss: 0.01869 +Epoch [547/4000] Training [2/16] Loss: 0.01487 +Epoch [547/4000] Training [3/16] Loss: 0.01378 +Epoch [547/4000] Training [4/16] Loss: 0.01237 +Epoch [547/4000] Training [5/16] Loss: 0.03439 +Epoch [547/4000] Training [6/16] Loss: 0.01441 +Epoch [547/4000] Training [7/16] Loss: 0.01698 +Epoch [547/4000] Training [8/16] Loss: 0.01740 +Epoch [547/4000] Training [9/16] Loss: 0.01615 +Epoch [547/4000] Training [10/16] Loss: 0.01605 +Epoch [547/4000] Training [11/16] Loss: 0.01864 +Epoch [547/4000] Training [12/16] Loss: 0.01781 +Epoch [547/4000] Training [13/16] Loss: 0.01381 +Epoch [547/4000] Training [14/16] Loss: 0.01470 +Epoch [547/4000] Training [15/16] Loss: 0.01920 +Epoch [547/4000] Training [16/16] Loss: 0.01835 +Epoch [547/4000] Training metric {'Train/mean dice_metric': 0.9879661798477173, 'Train/mean miou_metric': 0.9761282205581665, 'Train/mean f1': 0.9847628474235535, 'Train/mean precision': 0.9801740646362305, 'Train/mean recall': 0.9893947839736938, 'Train/mean hd95_metric': 1.985114336013794} +Epoch [547/4000] Validation [1/4] Loss: 0.11778 focal_loss 0.05766 dice_loss 0.06012 +Epoch [547/4000] Validation [2/4] Loss: 0.27853 focal_loss 0.14301 dice_loss 0.13552 +Epoch [547/4000] Validation [3/4] Loss: 0.26707 focal_loss 0.16069 dice_loss 0.10639 +Epoch [547/4000] Validation [4/4] Loss: 0.24343 focal_loss 0.12003 dice_loss 0.12341 +Epoch [547/4000] Validation metric {'Val/mean dice_metric': 0.9653644561767578, 'Val/mean miou_metric': 0.9422626495361328, 'Val/mean f1': 0.9654210805892944, 'Val/mean precision': 0.9611158967018127, 'Val/mean recall': 0.9697650074958801, 'Val/mean hd95_metric': 6.9126434326171875} +Cheakpoint... +Epoch [547/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653644561767578, 'Val/mean miou_metric': 0.9422626495361328, 'Val/mean f1': 0.9654210805892944, 'Val/mean precision': 0.9611158967018127, 'Val/mean recall': 0.9697650074958801, 'Val/mean hd95_metric': 6.9126434326171875} +Epoch [548/4000] Training [1/16] Loss: 0.01564 +Epoch [548/4000] Training [2/16] Loss: 0.01446 +Epoch [548/4000] Training [3/16] Loss: 0.01437 +Epoch [548/4000] Training [4/16] Loss: 0.01315 +Epoch [548/4000] Training [5/16] Loss: 0.01475 +Epoch [548/4000] Training [6/16] Loss: 0.01807 +Epoch [548/4000] Training [7/16] Loss: 0.01353 +Epoch [548/4000] Training [8/16] Loss: 0.01341 +Epoch [548/4000] Training [9/16] Loss: 0.01456 +Epoch [548/4000] Training [10/16] Loss: 0.01309 +Epoch [548/4000] Training [11/16] Loss: 0.01309 +Epoch [548/4000] Training [12/16] Loss: 0.02291 +Epoch [548/4000] Training [13/16] Loss: 0.01757 +Epoch [548/4000] Training [14/16] Loss: 0.04041 +Epoch [548/4000] Training [15/16] Loss: 0.01267 +Epoch [548/4000] Training [16/16] Loss: 0.02199 +Epoch [548/4000] Training metric {'Train/mean dice_metric': 0.9874874353408813, 'Train/mean miou_metric': 0.9759364724159241, 'Train/mean f1': 0.9850850105285645, 'Train/mean precision': 0.9803777933120728, 'Train/mean recall': 0.989837646484375, 'Train/mean hd95_metric': 2.2268893718719482} +Epoch [548/4000] Validation [1/4] Loss: 0.15441 focal_loss 0.09026 dice_loss 0.06415 +Epoch [548/4000] Validation [2/4] Loss: 0.56157 focal_loss 0.25699 dice_loss 0.30458 +Epoch [548/4000] Validation [3/4] Loss: 0.20916 focal_loss 0.10540 dice_loss 0.10375 +Epoch [548/4000] Validation [4/4] Loss: 0.21076 focal_loss 0.09691 dice_loss 0.11384 +Epoch [548/4000] Validation metric {'Val/mean dice_metric': 0.9614957571029663, 'Val/mean miou_metric': 0.9390726089477539, 'Val/mean f1': 0.9661951065063477, 'Val/mean precision': 0.9668635725975037, 'Val/mean recall': 0.9655275940895081, 'Val/mean hd95_metric': 7.35452127456665} +Cheakpoint... +Epoch [548/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9615], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614957571029663, 'Val/mean miou_metric': 0.9390726089477539, 'Val/mean f1': 0.9661951065063477, 'Val/mean precision': 0.9668635725975037, 'Val/mean recall': 0.9655275940895081, 'Val/mean hd95_metric': 7.35452127456665} +Epoch [549/4000] Training [1/16] Loss: 0.01558 +Epoch [549/4000] Training [2/16] Loss: 0.01622 +Epoch [549/4000] Training [3/16] Loss: 0.02069 +Epoch [549/4000] Training [4/16] Loss: 0.01920 +Epoch [549/4000] Training [5/16] Loss: 0.01280 +Epoch [549/4000] Training [6/16] Loss: 0.01732 +Epoch [549/4000] Training [7/16] Loss: 0.02137 +Epoch [549/4000] Training [8/16] Loss: 0.01613 +Epoch [549/4000] Training [9/16] Loss: 0.02225 +Epoch [549/4000] Training [10/16] Loss: 0.01573 +Epoch [549/4000] Training [11/16] Loss: 0.01866 +Epoch [549/4000] Training [12/16] Loss: 0.02788 +Epoch [549/4000] Training [13/16] Loss: 0.01494 +Epoch [549/4000] Training [14/16] Loss: 0.01979 +Epoch [549/4000] Training [15/16] Loss: 0.05664 +Epoch [549/4000] Training [16/16] Loss: 0.01383 +Epoch [549/4000] Training metric {'Train/mean dice_metric': 0.9877404570579529, 'Train/mean miou_metric': 0.9758319854736328, 'Train/mean f1': 0.9846815466880798, 'Train/mean precision': 0.9795393943786621, 'Train/mean recall': 0.9898779988288879, 'Train/mean hd95_metric': 2.3341920375823975} +Epoch [549/4000] Validation [1/4] Loss: 0.19746 focal_loss 0.12627 dice_loss 0.07119 +Epoch [549/4000] Validation [2/4] Loss: 0.51134 focal_loss 0.21633 dice_loss 0.29501 +Epoch [549/4000] Validation [3/4] Loss: 0.27393 focal_loss 0.15332 dice_loss 0.12061 +Epoch [549/4000] Validation [4/4] Loss: 0.47147 focal_loss 0.27154 dice_loss 0.19993 +Epoch [549/4000] Validation metric {'Val/mean dice_metric': 0.9580211639404297, 'Val/mean miou_metric': 0.9346540570259094, 'Val/mean f1': 0.9601157903671265, 'Val/mean precision': 0.9457876086235046, 'Val/mean recall': 0.9748847484588623, 'Val/mean hd95_metric': 10.844346046447754} +Cheakpoint... +Epoch [549/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9580], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9580211639404297, 'Val/mean miou_metric': 0.9346540570259094, 'Val/mean f1': 0.9601157903671265, 'Val/mean precision': 0.9457876086235046, 'Val/mean recall': 0.9748847484588623, 'Val/mean hd95_metric': 10.844346046447754} +Epoch [550/4000] Training [1/16] Loss: 0.01483 +Epoch [550/4000] Training [2/16] Loss: 0.01413 +Epoch [550/4000] Training [3/16] Loss: 0.01711 +Epoch [550/4000] Training [4/16] Loss: 0.01927 +Epoch [550/4000] Training [5/16] Loss: 0.01388 +Epoch [550/4000] Training [6/16] Loss: 0.01352 +Epoch [550/4000] Training [7/16] Loss: 0.01883 +Epoch [550/4000] Training [8/16] Loss: 0.01718 +Epoch [550/4000] Training [9/16] Loss: 0.01490 +Epoch [550/4000] Training [10/16] Loss: 0.04337 +Epoch [550/4000] Training [11/16] Loss: 0.02363 +Epoch [550/4000] Training [12/16] Loss: 0.02205 +Epoch [550/4000] Training [13/16] Loss: 0.02113 +Epoch [550/4000] Training [14/16] Loss: 0.01343 +Epoch [550/4000] Training [15/16] Loss: 0.01246 +Epoch [550/4000] Training [16/16] Loss: 0.01832 +Epoch [550/4000] Training metric {'Train/mean dice_metric': 0.9869901537895203, 'Train/mean miou_metric': 0.9744418859481812, 'Train/mean f1': 0.9840717315673828, 'Train/mean precision': 0.9800337553024292, 'Train/mean recall': 0.9881430864334106, 'Train/mean hd95_metric': 3.423452377319336} +Epoch [550/4000] Validation [1/4] Loss: 0.21442 focal_loss 0.13124 dice_loss 0.08319 +Epoch [550/4000] Validation [2/4] Loss: 0.21735 focal_loss 0.08034 dice_loss 0.13701 +Epoch [550/4000] Validation [3/4] Loss: 0.29030 focal_loss 0.16645 dice_loss 0.12385 +Epoch [550/4000] Validation [4/4] Loss: 0.28116 focal_loss 0.14351 dice_loss 0.13766 +Epoch [550/4000] Validation metric {'Val/mean dice_metric': 0.9610780477523804, 'Val/mean miou_metric': 0.9370540380477905, 'Val/mean f1': 0.9630253911018372, 'Val/mean precision': 0.9553110599517822, 'Val/mean recall': 0.9708653092384338, 'Val/mean hd95_metric': 9.620699882507324} +Cheakpoint... +Epoch [550/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610780477523804, 'Val/mean miou_metric': 0.9370540380477905, 'Val/mean f1': 0.9630253911018372, 'Val/mean precision': 0.9553110599517822, 'Val/mean recall': 0.9708653092384338, 'Val/mean hd95_metric': 9.620699882507324} +Epoch [551/4000] Training [1/16] Loss: 0.01654 +Epoch [551/4000] Training [2/16] Loss: 0.01225 +Epoch [551/4000] Training [3/16] Loss: 0.01448 +Epoch [551/4000] Training [4/16] Loss: 0.01541 +Epoch [551/4000] Training [5/16] Loss: 0.01971 +Epoch [551/4000] Training [6/16] Loss: 0.01893 +Epoch [551/4000] Training [7/16] Loss: 0.01465 +Epoch [551/4000] Training [8/16] Loss: 0.01586 +Epoch [551/4000] Training [9/16] Loss: 0.01409 +Epoch [551/4000] Training [10/16] Loss: 0.01314 +Epoch [551/4000] Training [11/16] Loss: 0.01374 +Epoch [551/4000] Training [12/16] Loss: 0.02022 +Epoch [551/4000] Training [13/16] Loss: 0.02332 +Epoch [551/4000] Training [14/16] Loss: 0.01681 +Epoch [551/4000] Training [15/16] Loss: 0.01546 +Epoch [551/4000] Training [16/16] Loss: 0.01431 +Epoch [551/4000] Training metric {'Train/mean dice_metric': 0.9885190725326538, 'Train/mean miou_metric': 0.9771659970283508, 'Train/mean f1': 0.985784113407135, 'Train/mean precision': 0.9813314080238342, 'Train/mean recall': 0.9902773499488831, 'Train/mean hd95_metric': 2.3046813011169434} +Epoch [551/4000] Validation [1/4] Loss: 0.22656 focal_loss 0.14427 dice_loss 0.08229 +Epoch [551/4000] Validation [2/4] Loss: 0.48535 focal_loss 0.18372 dice_loss 0.30163 +Epoch [551/4000] Validation [3/4] Loss: 0.24947 focal_loss 0.12638 dice_loss 0.12309 +Epoch [551/4000] Validation [4/4] Loss: 0.33906 focal_loss 0.15993 dice_loss 0.17914 +Epoch [551/4000] Validation metric {'Val/mean dice_metric': 0.9576610326766968, 'Val/mean miou_metric': 0.9351264834403992, 'Val/mean f1': 0.9640375375747681, 'Val/mean precision': 0.9636608362197876, 'Val/mean recall': 0.9644145369529724, 'Val/mean hd95_metric': 8.347396850585938} +Cheakpoint... +Epoch [551/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9577], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576610326766968, 'Val/mean miou_metric': 0.9351264834403992, 'Val/mean f1': 0.9640375375747681, 'Val/mean precision': 0.9636608362197876, 'Val/mean recall': 0.9644145369529724, 'Val/mean hd95_metric': 8.347396850585938} +Epoch [552/4000] Training [1/16] Loss: 0.02158 +Epoch [552/4000] Training [2/16] Loss: 0.03054 +Epoch [552/4000] Training [3/16] Loss: 0.01459 +Epoch [552/4000] Training [4/16] Loss: 0.01970 +Epoch [552/4000] Training [5/16] Loss: 0.03467 +Epoch [552/4000] Training [6/16] Loss: 0.01647 +Epoch [552/4000] Training [7/16] Loss: 0.02003 +Epoch [552/4000] Training [8/16] Loss: 0.01850 +Epoch [552/4000] Training [9/16] Loss: 0.01417 +Epoch [552/4000] Training [10/16] Loss: 0.01818 +Epoch [552/4000] Training [11/16] Loss: 0.02572 +Epoch [552/4000] Training [12/16] Loss: 0.01770 +Epoch [552/4000] Training [13/16] Loss: 0.02045 +Epoch [552/4000] Training [14/16] Loss: 0.01804 +Epoch [552/4000] Training [15/16] Loss: 0.01504 +Epoch [552/4000] Training [16/16] Loss: 0.01281 +Epoch [552/4000] Training metric {'Train/mean dice_metric': 0.9859076738357544, 'Train/mean miou_metric': 0.9727702140808105, 'Train/mean f1': 0.9838125705718994, 'Train/mean precision': 0.9795591235160828, 'Train/mean recall': 0.9881031513214111, 'Train/mean hd95_metric': 2.884498357772827} +Epoch [552/4000] Validation [1/4] Loss: 0.13292 focal_loss 0.07764 dice_loss 0.05528 +Epoch [552/4000] Validation [2/4] Loss: 0.28416 focal_loss 0.11349 dice_loss 0.17067 +Epoch [552/4000] Validation [3/4] Loss: 0.18536 focal_loss 0.09180 dice_loss 0.09355 +Epoch [552/4000] Validation [4/4] Loss: 0.19533 focal_loss 0.09103 dice_loss 0.10431 +Epoch [552/4000] Validation metric {'Val/mean dice_metric': 0.9619026184082031, 'Val/mean miou_metric': 0.9377975463867188, 'Val/mean f1': 0.9645940065383911, 'Val/mean precision': 0.9550568461418152, 'Val/mean recall': 0.9743236899375916, 'Val/mean hd95_metric': 8.623601913452148} +Cheakpoint... +Epoch [552/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9619], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9619026184082031, 'Val/mean miou_metric': 0.9377975463867188, 'Val/mean f1': 0.9645940065383911, 'Val/mean precision': 0.9550568461418152, 'Val/mean recall': 0.9743236899375916, 'Val/mean hd95_metric': 8.623601913452148} +Epoch [553/4000] Training [1/16] Loss: 0.01407 +Epoch [553/4000] Training [2/16] Loss: 0.01842 +Epoch [553/4000] Training [3/16] Loss: 0.01345 +Epoch [553/4000] Training [4/16] Loss: 0.01635 +Epoch [553/4000] Training [5/16] Loss: 0.01650 +Epoch [553/4000] Training [6/16] Loss: 0.02488 +Epoch [553/4000] Training [7/16] Loss: 0.01579 +Epoch [553/4000] Training [8/16] Loss: 0.03613 +Epoch [553/4000] Training [9/16] Loss: 0.01914 +Epoch [553/4000] Training [10/16] Loss: 0.04083 +Epoch [553/4000] Training [11/16] Loss: 0.13813 +Epoch [553/4000] Training [12/16] Loss: 0.02073 +Epoch [553/4000] Training [13/16] Loss: 0.06308 +Epoch [553/4000] Training [14/16] Loss: 0.01770 +Epoch [553/4000] Training [15/16] Loss: 0.02261 +Epoch [553/4000] Training [16/16] Loss: 0.04073 +Epoch [553/4000] Training metric {'Train/mean dice_metric': 0.9807881116867065, 'Train/mean miou_metric': 0.9647343158721924, 'Train/mean f1': 0.9778441786766052, 'Train/mean precision': 0.9728624224662781, 'Train/mean recall': 0.9828771948814392, 'Train/mean hd95_metric': 3.9185612201690674} +Epoch [553/4000] Validation [1/4] Loss: 0.14531 focal_loss 0.08077 dice_loss 0.06454 +Epoch [553/4000] Validation [2/4] Loss: 0.23499 focal_loss 0.10116 dice_loss 0.13383 +Epoch [553/4000] Validation [3/4] Loss: 0.18203 focal_loss 0.06678 dice_loss 0.11526 +Epoch [553/4000] Validation [4/4] Loss: 0.27218 focal_loss 0.10860 dice_loss 0.16357 +Epoch [553/4000] Validation metric {'Val/mean dice_metric': 0.9512243270874023, 'Val/mean miou_metric': 0.9250463247299194, 'Val/mean f1': 0.9527401328086853, 'Val/mean precision': 0.9432754516601562, 'Val/mean recall': 0.9623966217041016, 'Val/mean hd95_metric': 10.520112991333008} +Cheakpoint... +Epoch [553/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9512], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9512243270874023, 'Val/mean miou_metric': 0.9250463247299194, 'Val/mean f1': 0.9527401328086853, 'Val/mean precision': 0.9432754516601562, 'Val/mean recall': 0.9623966217041016, 'Val/mean hd95_metric': 10.520112991333008} +Epoch [554/4000] Training [1/16] Loss: 0.04603 +Epoch [554/4000] Training [2/16] Loss: 0.01584 +Epoch [554/4000] Training [3/16] Loss: 0.01662 +Epoch [554/4000] Training [4/16] Loss: 0.02306 +Epoch [554/4000] Training [5/16] Loss: 0.02054 +Epoch [554/4000] Training [6/16] Loss: 0.01771 +Epoch [554/4000] Training [7/16] Loss: 0.02005 +Epoch [554/4000] Training [8/16] Loss: 0.01917 +Epoch [554/4000] Training [9/16] Loss: 0.01699 +Epoch [554/4000] Training [10/16] Loss: 0.01731 +Epoch [554/4000] Training [11/16] Loss: 0.02542 +Epoch [554/4000] Training [12/16] Loss: 0.02115 +Epoch [554/4000] Training [13/16] Loss: 0.04622 +Epoch [554/4000] Training [14/16] Loss: 0.02505 +Epoch [554/4000] Training [15/16] Loss: 0.02179 +Epoch [554/4000] Training [16/16] Loss: 0.01764 +Epoch [554/4000] Training metric {'Train/mean dice_metric': 0.9856555461883545, 'Train/mean miou_metric': 0.9717308878898621, 'Train/mean f1': 0.9831072688102722, 'Train/mean precision': 0.9788880348205566, 'Train/mean recall': 0.9873629212379456, 'Train/mean hd95_metric': 3.1453070640563965} +Epoch [554/4000] Validation [1/4] Loss: 0.21552 focal_loss 0.13144 dice_loss 0.08408 +Epoch [554/4000] Validation [2/4] Loss: 0.42784 focal_loss 0.19440 dice_loss 0.23345 +Epoch [554/4000] Validation [3/4] Loss: 0.26607 focal_loss 0.14344 dice_loss 0.12263 +Epoch [554/4000] Validation [4/4] Loss: 0.31774 focal_loss 0.14906 dice_loss 0.16868 +Epoch [554/4000] Validation metric {'Val/mean dice_metric': 0.9569899439811707, 'Val/mean miou_metric': 0.9320268630981445, 'Val/mean f1': 0.9627977609634399, 'Val/mean precision': 0.9567782878875732, 'Val/mean recall': 0.9688934683799744, 'Val/mean hd95_metric': 10.29041862487793} +Cheakpoint... +Epoch [554/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9570], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9569899439811707, 'Val/mean miou_metric': 0.9320268630981445, 'Val/mean f1': 0.9627977609634399, 'Val/mean precision': 0.9567782878875732, 'Val/mean recall': 0.9688934683799744, 'Val/mean hd95_metric': 10.29041862487793} +Epoch [555/4000] Training [1/16] Loss: 0.02126 +Epoch [555/4000] Training [2/16] Loss: 0.01710 +Epoch [555/4000] Training [3/16] Loss: 0.01837 +Epoch [555/4000] Training [4/16] Loss: 0.01682 +Epoch [555/4000] Training [5/16] Loss: 0.02978 +Epoch [555/4000] Training [6/16] Loss: 0.01608 +Epoch [555/4000] Training [7/16] Loss: 0.02310 +Epoch [555/4000] Training [8/16] Loss: 0.01649 +Epoch [555/4000] Training [9/16] Loss: 0.01619 +Epoch [555/4000] Training [10/16] Loss: 0.01173 +Epoch [555/4000] Training [11/16] Loss: 0.02002 +Epoch [555/4000] Training [12/16] Loss: 0.01633 +Epoch [555/4000] Training [13/16] Loss: 0.02297 +Epoch [555/4000] Training [14/16] Loss: 0.01646 +Epoch [555/4000] Training [15/16] Loss: 0.01731 +Epoch [555/4000] Training [16/16] Loss: 0.01392 +Epoch [555/4000] Training metric {'Train/mean dice_metric': 0.9876676797866821, 'Train/mean miou_metric': 0.9755231142044067, 'Train/mean f1': 0.9844244718551636, 'Train/mean precision': 0.9794137477874756, 'Train/mean recall': 0.9894867539405823, 'Train/mean hd95_metric': 1.667171597480774} +Epoch [555/4000] Validation [1/4] Loss: 0.15696 focal_loss 0.08600 dice_loss 0.07096 +Epoch [555/4000] Validation [2/4] Loss: 0.24421 focal_loss 0.09473 dice_loss 0.14948 +Epoch [555/4000] Validation [3/4] Loss: 0.23709 focal_loss 0.14155 dice_loss 0.09554 +Epoch [555/4000] Validation [4/4] Loss: 0.34190 focal_loss 0.15312 dice_loss 0.18878 +Epoch [555/4000] Validation metric {'Val/mean dice_metric': 0.9613239169120789, 'Val/mean miou_metric': 0.9381231069564819, 'Val/mean f1': 0.9656242728233337, 'Val/mean precision': 0.9590347409248352, 'Val/mean recall': 0.9723049998283386, 'Val/mean hd95_metric': 8.53761100769043} +Cheakpoint... +Epoch [555/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9613239169120789, 'Val/mean miou_metric': 0.9381231069564819, 'Val/mean f1': 0.9656242728233337, 'Val/mean precision': 0.9590347409248352, 'Val/mean recall': 0.9723049998283386, 'Val/mean hd95_metric': 8.53761100769043} +Epoch [556/4000] Training [1/16] Loss: 0.01450 +Epoch [556/4000] Training [2/16] Loss: 0.01977 +Epoch [556/4000] Training [3/16] Loss: 0.01503 +Epoch [556/4000] Training [4/16] Loss: 0.01456 +Epoch [556/4000] Training [5/16] Loss: 0.01521 +Epoch [556/4000] Training [6/16] Loss: 0.01557 +Epoch [556/4000] Training [7/16] Loss: 0.01080 +Epoch [556/4000] Training [8/16] Loss: 0.02536 +Epoch [556/4000] Training [9/16] Loss: 0.06995 +Epoch [556/4000] Training [10/16] Loss: 0.01491 +Epoch [556/4000] Training [11/16] Loss: 0.02312 +Epoch [556/4000] Training [12/16] Loss: 0.01234 +Epoch [556/4000] Training [13/16] Loss: 0.01393 +Epoch [556/4000] Training [14/16] Loss: 0.01177 +Epoch [556/4000] Training [15/16] Loss: 0.01666 +Epoch [556/4000] Training [16/16] Loss: 0.01657 +Epoch [556/4000] Training metric {'Train/mean dice_metric': 0.986941397190094, 'Train/mean miou_metric': 0.9748363494873047, 'Train/mean f1': 0.9838604927062988, 'Train/mean precision': 0.978617787361145, 'Train/mean recall': 0.9891597032546997, 'Train/mean hd95_metric': 1.9475921392440796} +Epoch [556/4000] Validation [1/4] Loss: 0.20221 focal_loss 0.12238 dice_loss 0.07983 +Epoch [556/4000] Validation [2/4] Loss: 0.37963 focal_loss 0.16823 dice_loss 0.21140 +Epoch [556/4000] Validation [3/4] Loss: 0.21836 focal_loss 0.10389 dice_loss 0.11448 +Epoch [556/4000] Validation [4/4] Loss: 0.34892 focal_loss 0.16851 dice_loss 0.18041 +Epoch [556/4000] Validation metric {'Val/mean dice_metric': 0.9593488574028015, 'Val/mean miou_metric': 0.9352716207504272, 'Val/mean f1': 0.960417628288269, 'Val/mean precision': 0.947999894618988, 'Val/mean recall': 0.9731650352478027, 'Val/mean hd95_metric': 8.735918045043945} +Cheakpoint... +Epoch [556/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9593488574028015, 'Val/mean miou_metric': 0.9352716207504272, 'Val/mean f1': 0.960417628288269, 'Val/mean precision': 0.947999894618988, 'Val/mean recall': 0.9731650352478027, 'Val/mean hd95_metric': 8.735918045043945} +Epoch [557/4000] Training [1/16] Loss: 0.01636 +Epoch [557/4000] Training [2/16] Loss: 0.01494 +Epoch [557/4000] Training [3/16] Loss: 0.02000 +Epoch [557/4000] Training [4/16] Loss: 0.01776 +Epoch [557/4000] Training [5/16] Loss: 0.01364 +Epoch [557/4000] Training [6/16] Loss: 0.01756 +Epoch [557/4000] Training [7/16] Loss: 0.01360 +Epoch [557/4000] Training [8/16] Loss: 0.01839 +Epoch [557/4000] Training [9/16] Loss: 0.01736 +Epoch [557/4000] Training [10/16] Loss: 0.01625 +Epoch [557/4000] Training [11/16] Loss: 0.01423 +Epoch [557/4000] Training [12/16] Loss: 0.01477 +Epoch [557/4000] Training [13/16] Loss: 0.01331 +Epoch [557/4000] Training [14/16] Loss: 0.01718 +Epoch [557/4000] Training [15/16] Loss: 0.01918 +Epoch [557/4000] Training [16/16] Loss: 0.02010 +Epoch [557/4000] Training metric {'Train/mean dice_metric': 0.9884375333786011, 'Train/mean miou_metric': 0.9770024418830872, 'Train/mean f1': 0.9854739904403687, 'Train/mean precision': 0.9809659719467163, 'Train/mean recall': 0.990023672580719, 'Train/mean hd95_metric': 1.5655325651168823} +Epoch [557/4000] Validation [1/4] Loss: 0.15602 focal_loss 0.08533 dice_loss 0.07069 +Epoch [557/4000] Validation [2/4] Loss: 0.31236 focal_loss 0.13128 dice_loss 0.18108 +Epoch [557/4000] Validation [3/4] Loss: 0.27155 focal_loss 0.16098 dice_loss 0.11058 +Epoch [557/4000] Validation [4/4] Loss: 0.28292 focal_loss 0.14893 dice_loss 0.13399 +Epoch [557/4000] Validation metric {'Val/mean dice_metric': 0.9633272886276245, 'Val/mean miou_metric': 0.9399691820144653, 'Val/mean f1': 0.9648235440254211, 'Val/mean precision': 0.9594697952270508, 'Val/mean recall': 0.9702374339103699, 'Val/mean hd95_metric': 7.445623874664307} +Cheakpoint... +Epoch [557/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633272886276245, 'Val/mean miou_metric': 0.9399691820144653, 'Val/mean f1': 0.9648235440254211, 'Val/mean precision': 0.9594697952270508, 'Val/mean recall': 0.9702374339103699, 'Val/mean hd95_metric': 7.445623874664307} +Epoch [558/4000] Training [1/16] Loss: 0.01320 +Epoch [558/4000] Training [2/16] Loss: 0.01346 +Epoch [558/4000] Training [3/16] Loss: 0.10375 +Epoch [558/4000] Training [4/16] Loss: 0.01392 +Epoch [558/4000] Training [5/16] Loss: 0.01566 +Epoch [558/4000] Training [6/16] Loss: 0.01554 +Epoch [558/4000] Training [7/16] Loss: 0.01483 +Epoch [558/4000] Training [8/16] Loss: 0.01402 +Epoch [558/4000] Training [9/16] Loss: 0.01324 +Epoch [558/4000] Training [10/16] Loss: 0.01724 +Epoch [558/4000] Training [11/16] Loss: 0.01493 +Epoch [558/4000] Training [12/16] Loss: 0.01639 +Epoch [558/4000] Training [13/16] Loss: 0.01360 +Epoch [558/4000] Training [14/16] Loss: 0.01959 +Epoch [558/4000] Training [15/16] Loss: 0.01864 +Epoch [558/4000] Training [16/16] Loss: 0.01151 +Epoch [558/4000] Training metric {'Train/mean dice_metric': 0.9867497682571411, 'Train/mean miou_metric': 0.9751558303833008, 'Train/mean f1': 0.9856418371200562, 'Train/mean precision': 0.9810535907745361, 'Train/mean recall': 0.9902731776237488, 'Train/mean hd95_metric': 1.8013741970062256} +Epoch [558/4000] Validation [1/4] Loss: 0.18772 focal_loss 0.11076 dice_loss 0.07696 +Epoch [558/4000] Validation [2/4] Loss: 0.28328 focal_loss 0.12638 dice_loss 0.15690 +Epoch [558/4000] Validation [3/4] Loss: 0.25998 focal_loss 0.15442 dice_loss 0.10557 +Epoch [558/4000] Validation [4/4] Loss: 0.25300 focal_loss 0.12170 dice_loss 0.13130 +Epoch [558/4000] Validation metric {'Val/mean dice_metric': 0.9625482559204102, 'Val/mean miou_metric': 0.9392054677009583, 'Val/mean f1': 0.9660723209381104, 'Val/mean precision': 0.9598047733306885, 'Val/mean recall': 0.9724223017692566, 'Val/mean hd95_metric': 6.8217973709106445} +Cheakpoint... +Epoch [558/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625482559204102, 'Val/mean miou_metric': 0.9392054677009583, 'Val/mean f1': 0.9660723209381104, 'Val/mean precision': 0.9598047733306885, 'Val/mean recall': 0.9724223017692566, 'Val/mean hd95_metric': 6.8217973709106445} +Epoch [559/4000] Training [1/16] Loss: 0.01589 +Epoch [559/4000] Training [2/16] Loss: 0.01955 +Epoch [559/4000] Training [3/16] Loss: 0.01258 +Epoch [559/4000] Training [4/16] Loss: 0.01798 +Epoch [559/4000] Training [5/16] Loss: 0.01603 +Epoch [559/4000] Training [6/16] Loss: 0.02704 +Epoch [559/4000] Training [7/16] Loss: 0.01833 +Epoch [559/4000] Training [8/16] Loss: 0.02908 +Epoch [559/4000] Training [9/16] Loss: 0.01577 +Epoch [559/4000] Training [10/16] Loss: 0.02036 +Epoch [559/4000] Training [11/16] Loss: 0.01406 +Epoch [559/4000] Training [12/16] Loss: 0.01293 +Epoch [559/4000] Training [13/16] Loss: 0.01096 +Epoch [559/4000] Training [14/16] Loss: 0.01924 +Epoch [559/4000] Training [15/16] Loss: 0.01926 +Epoch [559/4000] Training [16/16] Loss: 0.02746 +Epoch [559/4000] Training metric {'Train/mean dice_metric': 0.985812783241272, 'Train/mean miou_metric': 0.9732574224472046, 'Train/mean f1': 0.9827221035957336, 'Train/mean precision': 0.9768559336662292, 'Train/mean recall': 0.9886590838432312, 'Train/mean hd95_metric': 2.4293506145477295} +Epoch [559/4000] Validation [1/4] Loss: 0.40633 focal_loss 0.27623 dice_loss 0.13010 +Epoch [559/4000] Validation [2/4] Loss: 0.35340 focal_loss 0.12704 dice_loss 0.22636 +Epoch [559/4000] Validation [3/4] Loss: 0.16745 focal_loss 0.08335 dice_loss 0.08410 +Epoch [559/4000] Validation [4/4] Loss: 0.20907 focal_loss 0.08869 dice_loss 0.12038 +Epoch [559/4000] Validation metric {'Val/mean dice_metric': 0.9589368104934692, 'Val/mean miou_metric': 0.9357150793075562, 'Val/mean f1': 0.9634801149368286, 'Val/mean precision': 0.9627756476402283, 'Val/mean recall': 0.9641855955123901, 'Val/mean hd95_metric': 7.279857158660889} +Cheakpoint... +Epoch [559/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9589], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9589368104934692, 'Val/mean miou_metric': 0.9357150793075562, 'Val/mean f1': 0.9634801149368286, 'Val/mean precision': 0.9627756476402283, 'Val/mean recall': 0.9641855955123901, 'Val/mean hd95_metric': 7.279857158660889} +Epoch [560/4000] Training [1/16] Loss: 0.01583 +Epoch [560/4000] Training [2/16] Loss: 0.01514 +Epoch [560/4000] Training [3/16] Loss: 0.01422 +Epoch [560/4000] Training [4/16] Loss: 0.01346 +Epoch [560/4000] Training [5/16] Loss: 0.01648 +Epoch [560/4000] Training [6/16] Loss: 0.01555 +Epoch [560/4000] Training [7/16] Loss: 0.01473 +Epoch [560/4000] Training [8/16] Loss: 0.01585 +Epoch [560/4000] Training [9/16] Loss: 0.01578 +Epoch [560/4000] Training [10/16] Loss: 0.01572 +Epoch [560/4000] Training [11/16] Loss: 0.01401 +Epoch [560/4000] Training [12/16] Loss: 0.02303 +Epoch [560/4000] Training [13/16] Loss: 0.01330 +Epoch [560/4000] Training [14/16] Loss: 0.01866 +Epoch [560/4000] Training [15/16] Loss: 0.02004 +Epoch [560/4000] Training [16/16] Loss: 0.01385 +Epoch [560/4000] Training metric {'Train/mean dice_metric': 0.9887539148330688, 'Train/mean miou_metric': 0.9775745868682861, 'Train/mean f1': 0.9852344989776611, 'Train/mean precision': 0.9807071089744568, 'Train/mean recall': 0.9898038506507874, 'Train/mean hd95_metric': 1.67281174659729} +Epoch [560/4000] Validation [1/4] Loss: 0.25040 focal_loss 0.15886 dice_loss 0.09154 +Epoch [560/4000] Validation [2/4] Loss: 0.56104 focal_loss 0.30462 dice_loss 0.25642 +Epoch [560/4000] Validation [3/4] Loss: 0.14946 focal_loss 0.07403 dice_loss 0.07543 +Epoch [560/4000] Validation [4/4] Loss: 0.24631 focal_loss 0.10888 dice_loss 0.13743 +Epoch [560/4000] Validation metric {'Val/mean dice_metric': 0.959223747253418, 'Val/mean miou_metric': 0.9364193081855774, 'Val/mean f1': 0.9567009806632996, 'Val/mean precision': 0.9408057332038879, 'Val/mean recall': 0.9731425046920776, 'Val/mean hd95_metric': 9.173513412475586} +Cheakpoint... +Epoch [560/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9592], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959223747253418, 'Val/mean miou_metric': 0.9364193081855774, 'Val/mean f1': 0.9567009806632996, 'Val/mean precision': 0.9408057332038879, 'Val/mean recall': 0.9731425046920776, 'Val/mean hd95_metric': 9.173513412475586} +Epoch [561/4000] Training [1/16] Loss: 0.01813 +Epoch [561/4000] Training [2/16] Loss: 0.01316 +Epoch [561/4000] Training [3/16] Loss: 0.01261 +Epoch [561/4000] Training [4/16] Loss: 0.01066 +Epoch [561/4000] Training [5/16] Loss: 0.01484 +Epoch [561/4000] Training [6/16] Loss: 0.01257 +Epoch [561/4000] Training [7/16] Loss: 0.01245 +Epoch [561/4000] Training [8/16] Loss: 0.01671 +Epoch [561/4000] Training [9/16] Loss: 0.01744 +Epoch [561/4000] Training [10/16] Loss: 0.01372 +Epoch [561/4000] Training [11/16] Loss: 0.01324 +Epoch [561/4000] Training [12/16] Loss: 0.01462 +Epoch [561/4000] Training [13/16] Loss: 0.02157 +Epoch [561/4000] Training [14/16] Loss: 0.01607 +Epoch [561/4000] Training [15/16] Loss: 0.01609 +Epoch [561/4000] Training [16/16] Loss: 0.01474 +Epoch [561/4000] Training metric {'Train/mean dice_metric': 0.9881182909011841, 'Train/mean miou_metric': 0.9768060445785522, 'Train/mean f1': 0.9853355288505554, 'Train/mean precision': 0.9802712202072144, 'Train/mean recall': 0.9904524683952332, 'Train/mean hd95_metric': 1.792602300643921} +Epoch [561/4000] Validation [1/4] Loss: 0.13598 focal_loss 0.07313 dice_loss 0.06285 +Epoch [561/4000] Validation [2/4] Loss: 0.23479 focal_loss 0.08498 dice_loss 0.14980 +Epoch [561/4000] Validation [3/4] Loss: 0.21144 focal_loss 0.11661 dice_loss 0.09483 +Epoch [561/4000] Validation [4/4] Loss: 0.19738 focal_loss 0.10022 dice_loss 0.09716 +Epoch [561/4000] Validation metric {'Val/mean dice_metric': 0.9648052453994751, 'Val/mean miou_metric': 0.9419113397598267, 'Val/mean f1': 0.9643157720565796, 'Val/mean precision': 0.9560436010360718, 'Val/mean recall': 0.9727323651313782, 'Val/mean hd95_metric': 6.998293399810791} +Cheakpoint... +Epoch [561/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648052453994751, 'Val/mean miou_metric': 0.9419113397598267, 'Val/mean f1': 0.9643157720565796, 'Val/mean precision': 0.9560436010360718, 'Val/mean recall': 0.9727323651313782, 'Val/mean hd95_metric': 6.998293399810791} +Epoch [562/4000] Training [1/16] Loss: 0.01559 +Epoch [562/4000] Training [2/16] Loss: 0.01514 +Epoch [562/4000] Training [3/16] Loss: 0.02320 +Epoch [562/4000] Training [4/16] Loss: 0.01499 +Epoch [562/4000] Training [5/16] Loss: 0.01390 +Epoch [562/4000] Training [6/16] Loss: 0.01428 +Epoch [562/4000] Training [7/16] Loss: 0.01774 +Epoch [562/4000] Training [8/16] Loss: 0.01115 +Epoch [562/4000] Training [9/16] Loss: 0.01881 +Epoch [562/4000] Training [10/16] Loss: 0.01409 +Epoch [562/4000] Training [11/16] Loss: 0.02488 +Epoch [562/4000] Training [12/16] Loss: 0.01767 +Epoch [562/4000] Training [13/16] Loss: 0.01441 +Epoch [562/4000] Training [14/16] Loss: 0.01198 +Epoch [562/4000] Training [15/16] Loss: 0.01369 +Epoch [562/4000] Training [16/16] Loss: 0.01575 +Epoch [562/4000] Training metric {'Train/mean dice_metric': 0.9885707497596741, 'Train/mean miou_metric': 0.9772641658782959, 'Train/mean f1': 0.9854394197463989, 'Train/mean precision': 0.9810113906860352, 'Train/mean recall': 0.9899076223373413, 'Train/mean hd95_metric': 1.7433063983917236} +Epoch [562/4000] Validation [1/4] Loss: 0.23253 focal_loss 0.14409 dice_loss 0.08844 +Epoch [562/4000] Validation [2/4] Loss: 0.21600 focal_loss 0.08589 dice_loss 0.13012 +Epoch [562/4000] Validation [3/4] Loss: 0.13766 focal_loss 0.07097 dice_loss 0.06669 +Epoch [562/4000] Validation [4/4] Loss: 0.28596 focal_loss 0.14907 dice_loss 0.13689 +Epoch [562/4000] Validation metric {'Val/mean dice_metric': 0.9657243490219116, 'Val/mean miou_metric': 0.942864716053009, 'Val/mean f1': 0.9676851630210876, 'Val/mean precision': 0.9656608700752258, 'Val/mean recall': 0.9697179794311523, 'Val/mean hd95_metric': 5.971426486968994} +Cheakpoint... +Epoch [562/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9657], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9657243490219116, 'Val/mean miou_metric': 0.942864716053009, 'Val/mean f1': 0.9676851630210876, 'Val/mean precision': 0.9656608700752258, 'Val/mean recall': 0.9697179794311523, 'Val/mean hd95_metric': 5.971426486968994} +Epoch [563/4000] Training [1/16] Loss: 0.01545 +Epoch [563/4000] Training [2/16] Loss: 0.01207 +Epoch [563/4000] Training [3/16] Loss: 0.01452 +Epoch [563/4000] Training [4/16] Loss: 0.01758 +Epoch [563/4000] Training [5/16] Loss: 0.01316 +Epoch [563/4000] Training [6/16] Loss: 0.02013 +Epoch [563/4000] Training [7/16] Loss: 0.02235 +Epoch [563/4000] Training [8/16] Loss: 0.01887 +Epoch [563/4000] Training [9/16] Loss: 0.01744 +Epoch [563/4000] Training [10/16] Loss: 0.01792 +Epoch [563/4000] Training [11/16] Loss: 0.01468 +Epoch [563/4000] Training [12/16] Loss: 0.01331 +Epoch [563/4000] Training [13/16] Loss: 0.01472 +Epoch [563/4000] Training [14/16] Loss: 0.01844 +Epoch [563/4000] Training [15/16] Loss: 0.01601 +Epoch [563/4000] Training [16/16] Loss: 0.01390 +Epoch [563/4000] Training metric {'Train/mean dice_metric': 0.9892244935035706, 'Train/mean miou_metric': 0.9785144329071045, 'Train/mean f1': 0.9864814877510071, 'Train/mean precision': 0.9817919731140137, 'Train/mean recall': 0.9912159442901611, 'Train/mean hd95_metric': 2.2003655433654785} +Epoch [563/4000] Validation [1/4] Loss: 0.37676 focal_loss 0.25573 dice_loss 0.12104 +Epoch [563/4000] Validation [2/4] Loss: 0.24265 focal_loss 0.10931 dice_loss 0.13335 +Epoch [563/4000] Validation [3/4] Loss: 0.16542 focal_loss 0.07251 dice_loss 0.09291 +Epoch [563/4000] Validation [4/4] Loss: 0.18406 focal_loss 0.07597 dice_loss 0.10809 +Epoch [563/4000] Validation metric {'Val/mean dice_metric': 0.963930606842041, 'Val/mean miou_metric': 0.9410476684570312, 'Val/mean f1': 0.967212438583374, 'Val/mean precision': 0.9668837189674377, 'Val/mean recall': 0.9675413966178894, 'Val/mean hd95_metric': 6.839413642883301} +Cheakpoint... +Epoch [563/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963930606842041, 'Val/mean miou_metric': 0.9410476684570312, 'Val/mean f1': 0.967212438583374, 'Val/mean precision': 0.9668837189674377, 'Val/mean recall': 0.9675413966178894, 'Val/mean hd95_metric': 6.839413642883301} +Epoch [564/4000] Training [1/16] Loss: 0.01435 +Epoch [564/4000] Training [2/16] Loss: 0.00981 +Epoch [564/4000] Training [3/16] Loss: 0.01278 +Epoch [564/4000] Training [4/16] Loss: 0.01465 +Epoch [564/4000] Training [5/16] Loss: 0.01976 +Epoch [564/4000] Training [6/16] Loss: 0.01393 +Epoch [564/4000] Training [7/16] Loss: 0.01552 +Epoch [564/4000] Training [8/16] Loss: 0.01362 +Epoch [564/4000] Training [9/16] Loss: 0.01752 +Epoch [564/4000] Training [10/16] Loss: 0.01296 +Epoch [564/4000] Training [11/16] Loss: 0.01124 +Epoch [564/4000] Training [12/16] Loss: 0.01643 +Epoch [564/4000] Training [13/16] Loss: 0.01632 +Epoch [564/4000] Training [14/16] Loss: 0.01433 +Epoch [564/4000] Training [15/16] Loss: 0.01907 +Epoch [564/4000] Training [16/16] Loss: 0.01675 +Epoch [564/4000] Training metric {'Train/mean dice_metric': 0.9896949529647827, 'Train/mean miou_metric': 0.9794113039970398, 'Train/mean f1': 0.9865691065788269, 'Train/mean precision': 0.9822450280189514, 'Train/mean recall': 0.9909313917160034, 'Train/mean hd95_metric': 1.3807176351547241} +Epoch [564/4000] Validation [1/4] Loss: 0.23124 focal_loss 0.15099 dice_loss 0.08026 +Epoch [564/4000] Validation [2/4] Loss: 0.25016 focal_loss 0.11848 dice_loss 0.13168 +Epoch [564/4000] Validation [3/4] Loss: 0.13462 focal_loss 0.06604 dice_loss 0.06858 +Epoch [564/4000] Validation [4/4] Loss: 0.16643 focal_loss 0.06560 dice_loss 0.10083 +Epoch [564/4000] Validation metric {'Val/mean dice_metric': 0.9651697874069214, 'Val/mean miou_metric': 0.9436002969741821, 'Val/mean f1': 0.9688836336135864, 'Val/mean precision': 0.9670329689979553, 'Val/mean recall': 0.9707413911819458, 'Val/mean hd95_metric': 5.903570652008057} +Cheakpoint... +Epoch [564/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651697874069214, 'Val/mean miou_metric': 0.9436002969741821, 'Val/mean f1': 0.9688836336135864, 'Val/mean precision': 0.9670329689979553, 'Val/mean recall': 0.9707413911819458, 'Val/mean hd95_metric': 5.903570652008057} +Epoch [565/4000] Training [1/16] Loss: 0.01448 +Epoch [565/4000] Training [2/16] Loss: 0.01734 +Epoch [565/4000] Training [3/16] Loss: 0.01482 +Epoch [565/4000] Training [4/16] Loss: 0.02654 +Epoch [565/4000] Training [5/16] Loss: 0.01787 +Epoch [565/4000] Training [6/16] Loss: 0.01383 +Epoch [565/4000] Training [7/16] Loss: 0.01139 +Epoch [565/4000] Training [8/16] Loss: 0.01891 +Epoch [565/4000] Training [9/16] Loss: 0.01755 +Epoch [565/4000] Training [10/16] Loss: 0.01164 +Epoch [565/4000] Training [11/16] Loss: 0.01455 +Epoch [565/4000] Training [12/16] Loss: 0.01732 +Epoch [565/4000] Training [13/16] Loss: 0.01784 +Epoch [565/4000] Training [14/16] Loss: 0.01333 +Epoch [565/4000] Training [15/16] Loss: 0.01437 +Epoch [565/4000] Training [16/16] Loss: 0.02760 +Epoch [565/4000] Training metric {'Train/mean dice_metric': 0.987923264503479, 'Train/mean miou_metric': 0.976253867149353, 'Train/mean f1': 0.9857800006866455, 'Train/mean precision': 0.9810143113136292, 'Train/mean recall': 0.9905922412872314, 'Train/mean hd95_metric': 1.823407769203186} +Epoch [565/4000] Validation [1/4] Loss: 0.14647 focal_loss 0.08398 dice_loss 0.06248 +Epoch [565/4000] Validation [2/4] Loss: 0.22971 focal_loss 0.09816 dice_loss 0.13155 +Epoch [565/4000] Validation [3/4] Loss: 0.15443 focal_loss 0.07263 dice_loss 0.08180 +Epoch [565/4000] Validation [4/4] Loss: 0.27843 focal_loss 0.12144 dice_loss 0.15699 +Epoch [565/4000] Validation metric {'Val/mean dice_metric': 0.9646997451782227, 'Val/mean miou_metric': 0.9422730207443237, 'Val/mean f1': 0.968613862991333, 'Val/mean precision': 0.9634833335876465, 'Val/mean recall': 0.9737991690635681, 'Val/mean hd95_metric': 6.412166118621826} +Cheakpoint... +Epoch [565/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646997451782227, 'Val/mean miou_metric': 0.9422730207443237, 'Val/mean f1': 0.968613862991333, 'Val/mean precision': 0.9634833335876465, 'Val/mean recall': 0.9737991690635681, 'Val/mean hd95_metric': 6.412166118621826} +Epoch [566/4000] Training [1/16] Loss: 0.01570 +Epoch [566/4000] Training [2/16] Loss: 0.01250 +Epoch [566/4000] Training [3/16] Loss: 0.01604 +Epoch [566/4000] Training [4/16] Loss: 0.01437 +Epoch [566/4000] Training [5/16] Loss: 0.02389 +Epoch [566/4000] Training [6/16] Loss: 0.01596 +Epoch [566/4000] Training [7/16] Loss: 0.01851 +Epoch [566/4000] Training [8/16] Loss: 0.01466 +Epoch [566/4000] Training [9/16] Loss: 0.01755 +Epoch [566/4000] Training [10/16] Loss: 0.01423 +Epoch [566/4000] Training [11/16] Loss: 0.01227 +Epoch [566/4000] Training [12/16] Loss: 0.01430 +Epoch [566/4000] Training [13/16] Loss: 0.01659 +Epoch [566/4000] Training [14/16] Loss: 0.01326 +Epoch [566/4000] Training [15/16] Loss: 0.01415 +Epoch [566/4000] Training [16/16] Loss: 0.01268 +Epoch [566/4000] Training metric {'Train/mean dice_metric': 0.9890526533126831, 'Train/mean miou_metric': 0.9781799912452698, 'Train/mean f1': 0.9856639504432678, 'Train/mean precision': 0.980257511138916, 'Train/mean recall': 0.9911302924156189, 'Train/mean hd95_metric': 1.386110782623291} +Epoch [566/4000] Validation [1/4] Loss: 0.18325 focal_loss 0.11257 dice_loss 0.07068 +Epoch [566/4000] Validation [2/4] Loss: 0.23069 focal_loss 0.07940 dice_loss 0.15129 +Epoch [566/4000] Validation [3/4] Loss: 0.28072 focal_loss 0.13544 dice_loss 0.14528 +Epoch [566/4000] Validation [4/4] Loss: 0.24898 focal_loss 0.12324 dice_loss 0.12574 +Epoch [566/4000] Validation metric {'Val/mean dice_metric': 0.9651899337768555, 'Val/mean miou_metric': 0.9434221386909485, 'Val/mean f1': 0.9687145948410034, 'Val/mean precision': 0.963710367679596, 'Val/mean recall': 0.9737710952758789, 'Val/mean hd95_metric': 6.078404426574707} +Cheakpoint... +Epoch [566/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651899337768555, 'Val/mean miou_metric': 0.9434221386909485, 'Val/mean f1': 0.9687145948410034, 'Val/mean precision': 0.963710367679596, 'Val/mean recall': 0.9737710952758789, 'Val/mean hd95_metric': 6.078404426574707} +Epoch [567/4000] Training [1/16] Loss: 0.01471 +Epoch [567/4000] Training [2/16] Loss: 0.01548 +Epoch [567/4000] Training [3/16] Loss: 0.01275 +Epoch [567/4000] Training [4/16] Loss: 0.01241 +Epoch [567/4000] Training [5/16] Loss: 0.01609 +Epoch [567/4000] Training [6/16] Loss: 0.02181 +Epoch [567/4000] Training [7/16] Loss: 0.01258 +Epoch [567/4000] Training [8/16] Loss: 0.01526 +Epoch [567/4000] Training [9/16] Loss: 0.01234 +Epoch [567/4000] Training [10/16] Loss: 0.01338 +Epoch [567/4000] Training [11/16] Loss: 0.00933 +Epoch [567/4000] Training [12/16] Loss: 0.01351 +Epoch [567/4000] Training [13/16] Loss: 0.01251 +Epoch [567/4000] Training [14/16] Loss: 0.01142 +Epoch [567/4000] Training [15/16] Loss: 0.01311 +Epoch [567/4000] Training [16/16] Loss: 0.01734 +Epoch [567/4000] Training metric {'Train/mean dice_metric': 0.989208459854126, 'Train/mean miou_metric': 0.9784538149833679, 'Train/mean f1': 0.986105740070343, 'Train/mean precision': 0.9810936450958252, 'Train/mean recall': 0.9911693334579468, 'Train/mean hd95_metric': 1.3149056434631348} +Epoch [567/4000] Validation [1/4] Loss: 0.29884 focal_loss 0.19671 dice_loss 0.10213 +Epoch [567/4000] Validation [2/4] Loss: 0.39028 focal_loss 0.18406 dice_loss 0.20622 +Epoch [567/4000] Validation [3/4] Loss: 0.18091 focal_loss 0.08095 dice_loss 0.09996 +Epoch [567/4000] Validation [4/4] Loss: 0.23861 focal_loss 0.12502 dice_loss 0.11358 +Epoch [567/4000] Validation metric {'Val/mean dice_metric': 0.9639908671379089, 'Val/mean miou_metric': 0.9418808221817017, 'Val/mean f1': 0.9668381810188293, 'Val/mean precision': 0.965033233165741, 'Val/mean recall': 0.9686498641967773, 'Val/mean hd95_metric': 6.401740550994873} +Cheakpoint... +Epoch [567/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639908671379089, 'Val/mean miou_metric': 0.9418808221817017, 'Val/mean f1': 0.9668381810188293, 'Val/mean precision': 0.965033233165741, 'Val/mean recall': 0.9686498641967773, 'Val/mean hd95_metric': 6.401740550994873} +Epoch [568/4000] Training [1/16] Loss: 0.01681 +Epoch [568/4000] Training [2/16] Loss: 0.01436 +Epoch [568/4000] Training [3/16] Loss: 0.01537 +Epoch [568/4000] Training [4/16] Loss: 0.01434 +Epoch [568/4000] Training [5/16] Loss: 0.01447 +Epoch [568/4000] Training [6/16] Loss: 0.01297 +Epoch [568/4000] Training [7/16] Loss: 0.01656 +Epoch [568/4000] Training [8/16] Loss: 0.02302 +Epoch [568/4000] Training [9/16] Loss: 0.01439 +Epoch [568/4000] Training [10/16] Loss: 0.01843 +Epoch [568/4000] Training [11/16] Loss: 0.01682 +Epoch [568/4000] Training [12/16] Loss: 0.01374 +Epoch [568/4000] Training [13/16] Loss: 0.01714 +Epoch [568/4000] Training [14/16] Loss: 0.01404 +Epoch [568/4000] Training [15/16] Loss: 0.01237 +Epoch [568/4000] Training [16/16] Loss: 0.01499 +Epoch [568/4000] Training metric {'Train/mean dice_metric': 0.9892486333847046, 'Train/mean miou_metric': 0.9787455797195435, 'Train/mean f1': 0.9869587421417236, 'Train/mean precision': 0.9823641777038574, 'Train/mean recall': 0.9915964603424072, 'Train/mean hd95_metric': 1.3928277492523193} +Epoch [568/4000] Validation [1/4] Loss: 0.16895 focal_loss 0.10080 dice_loss 0.06815 +Epoch [568/4000] Validation [2/4] Loss: 0.37585 focal_loss 0.18638 dice_loss 0.18947 +Epoch [568/4000] Validation [3/4] Loss: 0.16868 focal_loss 0.08126 dice_loss 0.08742 +Epoch [568/4000] Validation [4/4] Loss: 0.17890 focal_loss 0.08012 dice_loss 0.09878 +Epoch [568/4000] Validation metric {'Val/mean dice_metric': 0.9649798274040222, 'Val/mean miou_metric': 0.9435572624206543, 'Val/mean f1': 0.9692506194114685, 'Val/mean precision': 0.9650915861129761, 'Val/mean recall': 0.9734456539154053, 'Val/mean hd95_metric': 6.411854267120361} +Cheakpoint... +Epoch [568/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649798274040222, 'Val/mean miou_metric': 0.9435572624206543, 'Val/mean f1': 0.9692506194114685, 'Val/mean precision': 0.9650915861129761, 'Val/mean recall': 0.9734456539154053, 'Val/mean hd95_metric': 6.411854267120361} +Epoch [569/4000] Training [1/16] Loss: 0.01323 +Epoch [569/4000] Training [2/16] Loss: 0.01251 +Epoch [569/4000] Training [3/16] Loss: 0.02134 +Epoch [569/4000] Training [4/16] Loss: 0.01393 +Epoch [569/4000] Training [5/16] Loss: 0.01863 +Epoch [569/4000] Training [6/16] Loss: 0.02955 +Epoch [569/4000] Training [7/16] Loss: 0.01291 +Epoch [569/4000] Training [8/16] Loss: 0.01312 +Epoch [569/4000] Training [9/16] Loss: 0.01308 +Epoch [569/4000] Training [10/16] Loss: 0.01261 +Epoch [569/4000] Training [11/16] Loss: 0.02074 +Epoch [569/4000] Training [12/16] Loss: 0.01515 +Epoch [569/4000] Training [13/16] Loss: 0.01771 +Epoch [569/4000] Training [14/16] Loss: 0.01612 +Epoch [569/4000] Training [15/16] Loss: 0.01411 +Epoch [569/4000] Training [16/16] Loss: 0.01538 +Epoch [569/4000] Training metric {'Train/mean dice_metric': 0.9880713224411011, 'Train/mean miou_metric': 0.976649284362793, 'Train/mean f1': 0.9862309098243713, 'Train/mean precision': 0.9816725850105286, 'Train/mean recall': 0.9908317923545837, 'Train/mean hd95_metric': 1.9503016471862793} +Epoch [569/4000] Validation [1/4] Loss: 0.12394 focal_loss 0.06906 dice_loss 0.05488 +Epoch [569/4000] Validation [2/4] Loss: 0.56589 focal_loss 0.25873 dice_loss 0.30716 +Epoch [569/4000] Validation [3/4] Loss: 0.25864 focal_loss 0.15767 dice_loss 0.10097 +Epoch [569/4000] Validation [4/4] Loss: 0.32355 focal_loss 0.19680 dice_loss 0.12675 +Epoch [569/4000] Validation metric {'Val/mean dice_metric': 0.9607008099555969, 'Val/mean miou_metric': 0.9379199743270874, 'Val/mean f1': 0.9670562744140625, 'Val/mean precision': 0.9611532092094421, 'Val/mean recall': 0.973032534122467, 'Val/mean hd95_metric': 8.243274688720703} +Cheakpoint... +Epoch [569/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9607], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9607008099555969, 'Val/mean miou_metric': 0.9379199743270874, 'Val/mean f1': 0.9670562744140625, 'Val/mean precision': 0.9611532092094421, 'Val/mean recall': 0.973032534122467, 'Val/mean hd95_metric': 8.243274688720703} +Epoch [570/4000] Training [1/16] Loss: 0.01642 +Epoch [570/4000] Training [2/16] Loss: 0.01753 +Epoch [570/4000] Training [3/16] Loss: 0.01874 +Epoch [570/4000] Training [4/16] Loss: 0.01306 +Epoch [570/4000] Training [5/16] Loss: 0.01424 +Epoch [570/4000] Training [6/16] Loss: 0.01949 +Epoch [570/4000] Training [7/16] Loss: 0.01219 +Epoch [570/4000] Training [8/16] Loss: 0.01438 +Epoch [570/4000] Training [9/16] Loss: 0.01464 +Epoch [570/4000] Training [10/16] Loss: 0.01706 +Epoch [570/4000] Training [11/16] Loss: 0.01059 +Epoch [570/4000] Training [12/16] Loss: 0.01574 +Epoch [570/4000] Training [13/16] Loss: 0.01759 +Epoch [570/4000] Training [14/16] Loss: 0.01620 +Epoch [570/4000] Training [15/16] Loss: 0.01914 +Epoch [570/4000] Training [16/16] Loss: 0.02222 +Epoch [570/4000] Training metric {'Train/mean dice_metric': 0.988120973110199, 'Train/mean miou_metric': 0.9769953489303589, 'Train/mean f1': 0.9858354926109314, 'Train/mean precision': 0.9808639287948608, 'Train/mean recall': 0.9908577799797058, 'Train/mean hd95_metric': 2.277711868286133} +Epoch [570/4000] Validation [1/4] Loss: 0.16141 focal_loss 0.09868 dice_loss 0.06273 +Epoch [570/4000] Validation [2/4] Loss: 0.25277 focal_loss 0.11107 dice_loss 0.14170 +Epoch [570/4000] Validation [3/4] Loss: 0.23776 focal_loss 0.12218 dice_loss 0.11558 +Epoch [570/4000] Validation [4/4] Loss: 0.20198 focal_loss 0.10273 dice_loss 0.09926 +Epoch [570/4000] Validation metric {'Val/mean dice_metric': 0.9641111493110657, 'Val/mean miou_metric': 0.9412638545036316, 'Val/mean f1': 0.9663969874382019, 'Val/mean precision': 0.9591377973556519, 'Val/mean recall': 0.9737669825553894, 'Val/mean hd95_metric': 7.374800682067871} +Cheakpoint... +Epoch [570/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9641111493110657, 'Val/mean miou_metric': 0.9412638545036316, 'Val/mean f1': 0.9663969874382019, 'Val/mean precision': 0.9591377973556519, 'Val/mean recall': 0.9737669825553894, 'Val/mean hd95_metric': 7.374800682067871} +Epoch [571/4000] Training [1/16] Loss: 0.01334 +Epoch [571/4000] Training [2/16] Loss: 0.01350 +Epoch [571/4000] Training [3/16] Loss: 0.01895 +Epoch [571/4000] Training [4/16] Loss: 0.01487 +Epoch [571/4000] Training [5/16] Loss: 0.01700 +Epoch [571/4000] Training [6/16] Loss: 0.01286 +Epoch [571/4000] Training [7/16] Loss: 0.01188 +Epoch [571/4000] Training [8/16] Loss: 0.01252 +Epoch [571/4000] Training [9/16] Loss: 0.01704 +Epoch [571/4000] Training [10/16] Loss: 0.02464 +Epoch [571/4000] Training [11/16] Loss: 0.01939 +Epoch [571/4000] Training [12/16] Loss: 0.01996 +Epoch [571/4000] Training [13/16] Loss: 0.01281 +Epoch [571/4000] Training [14/16] Loss: 0.01153 +Epoch [571/4000] Training [15/16] Loss: 0.02027 +Epoch [571/4000] Training [16/16] Loss: 0.01630 +Epoch [571/4000] Training metric {'Train/mean dice_metric': 0.9878582954406738, 'Train/mean miou_metric': 0.9759141802787781, 'Train/mean f1': 0.9852117896080017, 'Train/mean precision': 0.9804518222808838, 'Train/mean recall': 0.9900182485580444, 'Train/mean hd95_metric': 2.272636651992798} +Epoch [571/4000] Validation [1/4] Loss: 0.22336 focal_loss 0.12708 dice_loss 0.09627 +Epoch [571/4000] Validation [2/4] Loss: 0.40071 focal_loss 0.17991 dice_loss 0.22080 +Epoch [571/4000] Validation [3/4] Loss: 0.18065 focal_loss 0.09493 dice_loss 0.08572 +Epoch [571/4000] Validation [4/4] Loss: 0.20660 focal_loss 0.09734 dice_loss 0.10926 +Epoch [571/4000] Validation metric {'Val/mean dice_metric': 0.9608378410339355, 'Val/mean miou_metric': 0.9379909634590149, 'Val/mean f1': 0.9640424251556396, 'Val/mean precision': 0.9633901715278625, 'Val/mean recall': 0.9646956324577332, 'Val/mean hd95_metric': 7.213718414306641} +Cheakpoint... +Epoch [571/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608378410339355, 'Val/mean miou_metric': 0.9379909634590149, 'Val/mean f1': 0.9640424251556396, 'Val/mean precision': 0.9633901715278625, 'Val/mean recall': 0.9646956324577332, 'Val/mean hd95_metric': 7.213718414306641} +Epoch [572/4000] Training [1/16] Loss: 0.01391 +Epoch [572/4000] Training [2/16] Loss: 0.01238 +Epoch [572/4000] Training [3/16] Loss: 0.01284 +Epoch [572/4000] Training [4/16] Loss: 0.02162 +Epoch [572/4000] Training [5/16] Loss: 0.02742 +Epoch [572/4000] Training [6/16] Loss: 0.01639 +Epoch [572/4000] Training [7/16] Loss: 0.01406 +Epoch [572/4000] Training [8/16] Loss: 0.01538 +Epoch [572/4000] Training [9/16] Loss: 0.01682 +Epoch [572/4000] Training [10/16] Loss: 0.01929 +Epoch [572/4000] Training [11/16] Loss: 0.01440 +Epoch [572/4000] Training [12/16] Loss: 0.01643 +Epoch [572/4000] Training [13/16] Loss: 0.02047 +Epoch [572/4000] Training [14/16] Loss: 0.01845 +Epoch [572/4000] Training [15/16] Loss: 0.01709 +Epoch [572/4000] Training [16/16] Loss: 0.01800 +Epoch [572/4000] Training metric {'Train/mean dice_metric': 0.9890069365501404, 'Train/mean miou_metric': 0.9780081510543823, 'Train/mean f1': 0.9844133257865906, 'Train/mean precision': 0.9788275957107544, 'Train/mean recall': 0.9900631904602051, 'Train/mean hd95_metric': 1.7050862312316895} +Epoch [572/4000] Validation [1/4] Loss: 0.18957 focal_loss 0.11115 dice_loss 0.07843 +Epoch [572/4000] Validation [2/4] Loss: 0.30107 focal_loss 0.13279 dice_loss 0.16828 +Epoch [572/4000] Validation [3/4] Loss: 0.22851 focal_loss 0.11380 dice_loss 0.11471 +Epoch [572/4000] Validation [4/4] Loss: 0.25662 focal_loss 0.13601 dice_loss 0.12062 +Epoch [572/4000] Validation metric {'Val/mean dice_metric': 0.9656082391738892, 'Val/mean miou_metric': 0.9429028630256653, 'Val/mean f1': 0.9666845798492432, 'Val/mean precision': 0.9591324329376221, 'Val/mean recall': 0.9743565320968628, 'Val/mean hd95_metric': 6.72329044342041} +Cheakpoint... +Epoch [572/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656082391738892, 'Val/mean miou_metric': 0.9429028630256653, 'Val/mean f1': 0.9666845798492432, 'Val/mean precision': 0.9591324329376221, 'Val/mean recall': 0.9743565320968628, 'Val/mean hd95_metric': 6.72329044342041} +Epoch [573/4000] Training [1/16] Loss: 0.01287 +Epoch [573/4000] Training [2/16] Loss: 0.01291 +Epoch [573/4000] Training [3/16] Loss: 0.01522 +Epoch [573/4000] Training [4/16] Loss: 0.01295 +Epoch [573/4000] Training [5/16] Loss: 0.01731 +Epoch [573/4000] Training [6/16] Loss: 0.01665 +Epoch [573/4000] Training [7/16] Loss: 0.01442 +Epoch [573/4000] Training [8/16] Loss: 0.01398 +Epoch [573/4000] Training [9/16] Loss: 0.01698 +Epoch [573/4000] Training [10/16] Loss: 0.01638 +Epoch [573/4000] Training [11/16] Loss: 0.01644 +Epoch [573/4000] Training [12/16] Loss: 0.01257 +Epoch [573/4000] Training [13/16] Loss: 0.01225 +Epoch [573/4000] Training [14/16] Loss: 0.01433 +Epoch [573/4000] Training [15/16] Loss: 0.01309 +Epoch [573/4000] Training [16/16] Loss: 0.01338 +Epoch [573/4000] Training metric {'Train/mean dice_metric': 0.989313006401062, 'Train/mean miou_metric': 0.9788770079612732, 'Train/mean f1': 0.9864915013313293, 'Train/mean precision': 0.9816117882728577, 'Train/mean recall': 0.9914199113845825, 'Train/mean hd95_metric': 1.60722017288208} +Epoch [573/4000] Validation [1/4] Loss: 0.18878 focal_loss 0.10949 dice_loss 0.07928 +Epoch [573/4000] Validation [2/4] Loss: 0.33505 focal_loss 0.15319 dice_loss 0.18186 +Epoch [573/4000] Validation [3/4] Loss: 0.28470 focal_loss 0.17782 dice_loss 0.10688 +Epoch [573/4000] Validation [4/4] Loss: 0.19968 focal_loss 0.09763 dice_loss 0.10205 +Epoch [573/4000] Validation metric {'Val/mean dice_metric': 0.9648690223693848, 'Val/mean miou_metric': 0.9431718587875366, 'Val/mean f1': 0.9670579433441162, 'Val/mean precision': 0.961748480796814, 'Val/mean recall': 0.9724264144897461, 'Val/mean hd95_metric': 6.686026096343994} +Cheakpoint... +Epoch [573/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648690223693848, 'Val/mean miou_metric': 0.9431718587875366, 'Val/mean f1': 0.9670579433441162, 'Val/mean precision': 0.961748480796814, 'Val/mean recall': 0.9724264144897461, 'Val/mean hd95_metric': 6.686026096343994} +Epoch [574/4000] Training [1/16] Loss: 0.01246 +Epoch [574/4000] Training [2/16] Loss: 0.02068 +Epoch [574/4000] Training [3/16] Loss: 0.01352 +Epoch [574/4000] Training [4/16] Loss: 0.01764 +Epoch [574/4000] Training [5/16] Loss: 0.01531 +Epoch [574/4000] Training [6/16] Loss: 0.01459 +Epoch [574/4000] Training [7/16] Loss: 0.01475 +Epoch [574/4000] Training [8/16] Loss: 0.02907 +Epoch [574/4000] Training [9/16] Loss: 0.01288 +Epoch [574/4000] Training [10/16] Loss: 0.01886 +Epoch [574/4000] Training [11/16] Loss: 0.10027 +Epoch [574/4000] Training [12/16] Loss: 0.01268 +Epoch [574/4000] Training [13/16] Loss: 0.01494 +Epoch [574/4000] Training [14/16] Loss: 0.03711 +Epoch [574/4000] Training [15/16] Loss: 0.01715 +Epoch [574/4000] Training [16/16] Loss: 0.02106 +Epoch [574/4000] Training metric {'Train/mean dice_metric': 0.9866153001785278, 'Train/mean miou_metric': 0.9749112129211426, 'Train/mean f1': 0.9842406511306763, 'Train/mean precision': 0.9796559810638428, 'Train/mean recall': 0.9888684153556824, 'Train/mean hd95_metric': 2.5582940578460693} +Epoch [574/4000] Validation [1/4] Loss: 0.16421 focal_loss 0.09540 dice_loss 0.06881 +Epoch [574/4000] Validation [2/4] Loss: 0.31352 focal_loss 0.12320 dice_loss 0.19032 +Epoch [574/4000] Validation [3/4] Loss: 0.27172 focal_loss 0.16241 dice_loss 0.10931 +Epoch [574/4000] Validation [4/4] Loss: 0.55791 focal_loss 0.34760 dice_loss 0.21031 +Epoch [574/4000] Validation metric {'Val/mean dice_metric': 0.9545592069625854, 'Val/mean miou_metric': 0.9300329089164734, 'Val/mean f1': 0.9509364366531372, 'Val/mean precision': 0.9266063570976257, 'Val/mean recall': 0.9765787124633789, 'Val/mean hd95_metric': 11.344003677368164} +Cheakpoint... +Epoch [574/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9546], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9545592069625854, 'Val/mean miou_metric': 0.9300329089164734, 'Val/mean f1': 0.9509364366531372, 'Val/mean precision': 0.9266063570976257, 'Val/mean recall': 0.9765787124633789, 'Val/mean hd95_metric': 11.344003677368164} +Epoch [575/4000] Training [1/16] Loss: 0.01892 +Epoch [575/4000] Training [2/16] Loss: 0.01835 +Epoch [575/4000] Training [3/16] Loss: 0.01858 +Epoch [575/4000] Training [4/16] Loss: 0.01551 +Epoch [575/4000] Training [5/16] Loss: 0.07607 +Epoch [575/4000] Training [6/16] Loss: 0.04121 +Epoch [575/4000] Training [7/16] Loss: 0.01450 +Epoch [575/4000] Training [8/16] Loss: 0.02613 +Epoch [575/4000] Training [9/16] Loss: 0.01620 +Epoch [575/4000] Training [10/16] Loss: 0.02512 +Epoch [575/4000] Training [11/16] Loss: 0.01852 +Epoch [575/4000] Training [12/16] Loss: 0.01924 +Epoch [575/4000] Training [13/16] Loss: 0.06082 +Epoch [575/4000] Training [14/16] Loss: 0.01659 +Epoch [575/4000] Training [15/16] Loss: 0.15549 +Epoch [575/4000] Training [16/16] Loss: 0.02021 +Epoch [575/4000] Training metric {'Train/mean dice_metric': 0.9776080846786499, 'Train/mean miou_metric': 0.961345911026001, 'Train/mean f1': 0.970970094203949, 'Train/mean precision': 0.9697926640510559, 'Train/mean recall': 0.9721503257751465, 'Train/mean hd95_metric': 4.299130916595459} +Epoch [575/4000] Validation [1/4] Loss: 0.16733 focal_loss 0.09839 dice_loss 0.06893 +Epoch [575/4000] Validation [2/4] Loss: 0.40127 focal_loss 0.14016 dice_loss 0.26111 +Epoch [575/4000] Validation [3/4] Loss: 0.39152 focal_loss 0.25141 dice_loss 0.14010 +Epoch [575/4000] Validation [4/4] Loss: 0.57743 focal_loss 0.31769 dice_loss 0.25975 +Epoch [575/4000] Validation metric {'Val/mean dice_metric': 0.9426460266113281, 'Val/mean miou_metric': 0.9152789115905762, 'Val/mean f1': 0.9418721795082092, 'Val/mean precision': 0.9263852834701538, 'Val/mean recall': 0.9578856825828552, 'Val/mean hd95_metric': 12.738638877868652} +Cheakpoint... +Epoch [575/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9426], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9426460266113281, 'Val/mean miou_metric': 0.9152789115905762, 'Val/mean f1': 0.9418721795082092, 'Val/mean precision': 0.9263852834701538, 'Val/mean recall': 0.9578856825828552, 'Val/mean hd95_metric': 12.738638877868652} +Epoch [576/4000] Training [1/16] Loss: 0.02156 +Epoch [576/4000] Training [2/16] Loss: 0.03009 +Epoch [576/4000] Training [3/16] Loss: 0.13544 +Epoch [576/4000] Training [4/16] Loss: 0.01647 +Epoch [576/4000] Training [5/16] Loss: 0.01735 +Epoch [576/4000] Training [6/16] Loss: 0.02231 +Epoch [576/4000] Training [7/16] Loss: 0.03571 +Epoch [576/4000] Training [8/16] Loss: 0.02361 +Epoch [576/4000] Training [9/16] Loss: 0.02643 +Epoch [576/4000] Training [10/16] Loss: 0.02659 +Epoch [576/4000] Training [11/16] Loss: 0.03706 +Epoch [576/4000] Training [12/16] Loss: 0.34854 +Epoch [576/4000] Training [13/16] Loss: 0.02092 +Epoch [576/4000] Training [14/16] Loss: 0.02690 +Epoch [576/4000] Training [15/16] Loss: 0.02388 +Epoch [576/4000] Training [16/16] Loss: 0.04198 +Epoch [576/4000] Training metric {'Train/mean dice_metric': 0.978355884552002, 'Train/mean miou_metric': 0.9612617492675781, 'Train/mean f1': 0.975523829460144, 'Train/mean precision': 0.9703081846237183, 'Train/mean recall': 0.9807958602905273, 'Train/mean hd95_metric': 6.995081901550293} +Epoch [576/4000] Validation [1/4] Loss: 0.12195 focal_loss 0.06035 dice_loss 0.06160 +Epoch [576/4000] Validation [2/4] Loss: 0.32958 focal_loss 0.14227 dice_loss 0.18731 +Epoch [576/4000] Validation [3/4] Loss: 0.16371 focal_loss 0.07677 dice_loss 0.08694 +Epoch [576/4000] Validation [4/4] Loss: 0.47945 focal_loss 0.26882 dice_loss 0.21063 +Epoch [576/4000] Validation metric {'Val/mean dice_metric': 0.9508268237113953, 'Val/mean miou_metric': 0.9221717715263367, 'Val/mean f1': 0.9557431936264038, 'Val/mean precision': 0.9512917399406433, 'Val/mean recall': 0.9602366089820862, 'Val/mean hd95_metric': 12.630928039550781} +Cheakpoint... +Epoch [576/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9508], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9508268237113953, 'Val/mean miou_metric': 0.9221717715263367, 'Val/mean f1': 0.9557431936264038, 'Val/mean precision': 0.9512917399406433, 'Val/mean recall': 0.9602366089820862, 'Val/mean hd95_metric': 12.630928039550781} +Epoch [577/4000] Training [1/16] Loss: 0.03110 +Epoch [577/4000] Training [2/16] Loss: 0.02153 +Epoch [577/4000] Training [3/16] Loss: 0.01980 +Epoch [577/4000] Training [4/16] Loss: 0.01970 +Epoch [577/4000] Training [5/16] Loss: 0.02784 +Epoch [577/4000] Training [6/16] Loss: 0.01713 +Epoch [577/4000] Training [7/16] Loss: 0.02358 +Epoch [577/4000] Training [8/16] Loss: 0.02455 +Epoch [577/4000] Training [9/16] Loss: 0.03049 +Epoch [577/4000] Training [10/16] Loss: 0.03100 +Epoch [577/4000] Training [11/16] Loss: 0.02399 +Epoch [577/4000] Training [12/16] Loss: 0.01823 +Epoch [577/4000] Training [13/16] Loss: 0.02027 +Epoch [577/4000] Training [14/16] Loss: 0.06368 +Epoch [577/4000] Training [15/16] Loss: 0.03229 +Epoch [577/4000] Training [16/16] Loss: 0.01532 +Epoch [577/4000] Training metric {'Train/mean dice_metric': 0.9821099042892456, 'Train/mean miou_metric': 0.9653855562210083, 'Train/mean f1': 0.9780815243721008, 'Train/mean precision': 0.9748256802558899, 'Train/mean recall': 0.9813592433929443, 'Train/mean hd95_metric': 4.606501579284668} +Epoch [577/4000] Validation [1/4] Loss: 0.13292 focal_loss 0.06006 dice_loss 0.07286 +Epoch [577/4000] Validation [2/4] Loss: 0.29504 focal_loss 0.11346 dice_loss 0.18158 +Epoch [577/4000] Validation [3/4] Loss: 0.25973 focal_loss 0.14541 dice_loss 0.11432 +Epoch [577/4000] Validation [4/4] Loss: 0.29527 focal_loss 0.14270 dice_loss 0.15257 +Epoch [577/4000] Validation metric {'Val/mean dice_metric': 0.9590199589729309, 'Val/mean miou_metric': 0.9303172826766968, 'Val/mean f1': 0.9595056772232056, 'Val/mean precision': 0.9565111398696899, 'Val/mean recall': 0.962519109249115, 'Val/mean hd95_metric': 9.478246688842773} +Cheakpoint... +Epoch [577/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9590], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9590199589729309, 'Val/mean miou_metric': 0.9303172826766968, 'Val/mean f1': 0.9595056772232056, 'Val/mean precision': 0.9565111398696899, 'Val/mean recall': 0.962519109249115, 'Val/mean hd95_metric': 9.478246688842773} +Epoch [578/4000] Training [1/16] Loss: 0.04200 +Epoch [578/4000] Training [2/16] Loss: 0.02201 +Epoch [578/4000] Training [3/16] Loss: 0.02869 +Epoch [578/4000] Training [4/16] Loss: 0.01950 +Epoch [578/4000] Training [5/16] Loss: 0.03125 +Epoch [578/4000] Training [6/16] Loss: 0.01758 +Epoch [578/4000] Training [7/16] Loss: 0.02223 +Epoch [578/4000] Training [8/16] Loss: 0.02043 +Epoch [578/4000] Training [9/16] Loss: 0.01653 +Epoch [578/4000] Training [10/16] Loss: 0.02486 +Epoch [578/4000] Training [11/16] Loss: 0.02223 +Epoch [578/4000] Training [12/16] Loss: 0.01858 +Epoch [578/4000] Training [13/16] Loss: 0.02691 +Epoch [578/4000] Training [14/16] Loss: 0.01952 +Epoch [578/4000] Training [15/16] Loss: 0.01604 +Epoch [578/4000] Training [16/16] Loss: 0.01767 +Epoch [578/4000] Training metric {'Train/mean dice_metric': 0.9848219156265259, 'Train/mean miou_metric': 0.9702173471450806, 'Train/mean f1': 0.9812510013580322, 'Train/mean precision': 0.9760748744010925, 'Train/mean recall': 0.9864822626113892, 'Train/mean hd95_metric': 3.4859423637390137} +Epoch [578/4000] Validation [1/4] Loss: 0.13129 focal_loss 0.06613 dice_loss 0.06516 +Epoch [578/4000] Validation [2/4] Loss: 0.22642 focal_loss 0.09555 dice_loss 0.13087 +Epoch [578/4000] Validation [3/4] Loss: 0.18013 focal_loss 0.07713 dice_loss 0.10301 +Epoch [578/4000] Validation [4/4] Loss: 0.22127 focal_loss 0.10022 dice_loss 0.12105 +Epoch [578/4000] Validation metric {'Val/mean dice_metric': 0.961544394493103, 'Val/mean miou_metric': 0.9355093836784363, 'Val/mean f1': 0.9631344676017761, 'Val/mean precision': 0.9552998542785645, 'Val/mean recall': 0.9710986018180847, 'Val/mean hd95_metric': 8.974886894226074} +Cheakpoint... +Epoch [578/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9615], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961544394493103, 'Val/mean miou_metric': 0.9355093836784363, 'Val/mean f1': 0.9631344676017761, 'Val/mean precision': 0.9552998542785645, 'Val/mean recall': 0.9710986018180847, 'Val/mean hd95_metric': 8.974886894226074} +Epoch [579/4000] Training [1/16] Loss: 0.02393 +Epoch [579/4000] Training [2/16] Loss: 0.01713 +Epoch [579/4000] Training [3/16] Loss: 0.02480 +Epoch [579/4000] Training [4/16] Loss: 0.02667 +Epoch [579/4000] Training [5/16] Loss: 0.01555 +Epoch [579/4000] Training [6/16] Loss: 0.01708 +Epoch [579/4000] Training [7/16] Loss: 0.02545 +Epoch [579/4000] Training [8/16] Loss: 0.01617 +Epoch [579/4000] Training [9/16] Loss: 0.04007 +Epoch [579/4000] Training [10/16] Loss: 0.01389 +Epoch [579/4000] Training [11/16] Loss: 0.01851 +Epoch [579/4000] Training [12/16] Loss: 0.01536 +Epoch [579/4000] Training [13/16] Loss: 0.04379 +Epoch [579/4000] Training [14/16] Loss: 0.01665 +Epoch [579/4000] Training [15/16] Loss: 0.01690 +Epoch [579/4000] Training [16/16] Loss: 0.01639 +Epoch [579/4000] Training metric {'Train/mean dice_metric': 0.9870502352714539, 'Train/mean miou_metric': 0.9745277166366577, 'Train/mean f1': 0.9842259287834167, 'Train/mean precision': 0.9802863597869873, 'Train/mean recall': 0.9881972670555115, 'Train/mean hd95_metric': 2.468777656555176} +Epoch [579/4000] Validation [1/4] Loss: 0.19397 focal_loss 0.11656 dice_loss 0.07741 +Epoch [579/4000] Validation [2/4] Loss: 0.39171 focal_loss 0.16631 dice_loss 0.22540 +Epoch [579/4000] Validation [3/4] Loss: 0.26135 focal_loss 0.14425 dice_loss 0.11710 +Epoch [579/4000] Validation [4/4] Loss: 0.20325 focal_loss 0.09760 dice_loss 0.10565 +Epoch [579/4000] Validation metric {'Val/mean dice_metric': 0.9650812149047852, 'Val/mean miou_metric': 0.9411743879318237, 'Val/mean f1': 0.9679660797119141, 'Val/mean precision': 0.9615309238433838, 'Val/mean recall': 0.9744880199432373, 'Val/mean hd95_metric': 7.4376702308654785} +Cheakpoint... +Epoch [579/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650812149047852, 'Val/mean miou_metric': 0.9411743879318237, 'Val/mean f1': 0.9679660797119141, 'Val/mean precision': 0.9615309238433838, 'Val/mean recall': 0.9744880199432373, 'Val/mean hd95_metric': 7.4376702308654785} +Epoch [580/4000] Training [1/16] Loss: 0.01456 +Epoch [580/4000] Training [2/16] Loss: 0.01365 +Epoch [580/4000] Training [3/16] Loss: 0.02109 +Epoch [580/4000] Training [4/16] Loss: 0.01527 +Epoch [580/4000] Training [5/16] Loss: 0.01545 +Epoch [580/4000] Training [6/16] Loss: 0.02112 +Epoch [580/4000] Training [7/16] Loss: 0.01412 +Epoch [580/4000] Training [8/16] Loss: 0.01981 +Epoch [580/4000] Training [9/16] Loss: 0.01552 +Epoch [580/4000] Training [10/16] Loss: 0.01511 +Epoch [580/4000] Training [11/16] Loss: 0.02433 +Epoch [580/4000] Training [12/16] Loss: 0.01224 +Epoch [580/4000] Training [13/16] Loss: 0.02670 +Epoch [580/4000] Training [14/16] Loss: 0.01524 +Epoch [580/4000] Training [15/16] Loss: 0.01251 +Epoch [580/4000] Training [16/16] Loss: 0.01463 +Epoch [580/4000] Training metric {'Train/mean dice_metric': 0.9886249303817749, 'Train/mean miou_metric': 0.977369487285614, 'Train/mean f1': 0.9856098890304565, 'Train/mean precision': 0.9812504053115845, 'Train/mean recall': 0.9900082349777222, 'Train/mean hd95_metric': 1.672273874282837} +Epoch [580/4000] Validation [1/4] Loss: 0.13015 focal_loss 0.06978 dice_loss 0.06038 +Epoch [580/4000] Validation [2/4] Loss: 0.20254 focal_loss 0.07355 dice_loss 0.12899 +Epoch [580/4000] Validation [3/4] Loss: 0.12515 focal_loss 0.05940 dice_loss 0.06575 +Epoch [580/4000] Validation [4/4] Loss: 0.17387 focal_loss 0.06112 dice_loss 0.11276 +Epoch [580/4000] Validation metric {'Val/mean dice_metric': 0.9690849184989929, 'Val/mean miou_metric': 0.9466446042060852, 'Val/mean f1': 0.969416081905365, 'Val/mean precision': 0.9616557359695435, 'Val/mean recall': 0.9773026704788208, 'Val/mean hd95_metric': 6.213131904602051} +Cheakpoint... +Epoch [580/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690849184989929, 'Val/mean miou_metric': 0.9466446042060852, 'Val/mean f1': 0.969416081905365, 'Val/mean precision': 0.9616557359695435, 'Val/mean recall': 0.9773026704788208, 'Val/mean hd95_metric': 6.213131904602051} +Epoch [581/4000] Training [1/16] Loss: 0.01576 +Epoch [581/4000] Training [2/16] Loss: 0.01308 +Epoch [581/4000] Training [3/16] Loss: 0.01646 +Epoch [581/4000] Training [4/16] Loss: 0.01197 +Epoch [581/4000] Training [5/16] Loss: 0.01943 +Epoch [581/4000] Training [6/16] Loss: 0.01512 +Epoch [581/4000] Training [7/16] Loss: 0.01500 +Epoch [581/4000] Training [8/16] Loss: 0.01659 +Epoch [581/4000] Training [9/16] Loss: 0.01424 +Epoch [581/4000] Training [10/16] Loss: 0.01669 +Epoch [581/4000] Training [11/16] Loss: 0.01766 +Epoch [581/4000] Training [12/16] Loss: 0.01543 +Epoch [581/4000] Training [13/16] Loss: 0.01183 +Epoch [581/4000] Training [14/16] Loss: 0.01651 +Epoch [581/4000] Training [15/16] Loss: 0.01245 +Epoch [581/4000] Training [16/16] Loss: 0.01424 +Epoch [581/4000] Training metric {'Train/mean dice_metric': 0.9891613721847534, 'Train/mean miou_metric': 0.9783700108528137, 'Train/mean f1': 0.9860494136810303, 'Train/mean precision': 0.9814168214797974, 'Train/mean recall': 0.9907259345054626, 'Train/mean hd95_metric': 1.467941403388977} +Epoch [581/4000] Validation [1/4] Loss: 0.10817 focal_loss 0.05182 dice_loss 0.05635 +Epoch [581/4000] Validation [2/4] Loss: 0.33011 focal_loss 0.14081 dice_loss 0.18931 +Epoch [581/4000] Validation [3/4] Loss: 0.18209 focal_loss 0.08510 dice_loss 0.09699 +Epoch [581/4000] Validation [4/4] Loss: 0.23795 focal_loss 0.10103 dice_loss 0.13692 +Epoch [581/4000] Validation metric {'Val/mean dice_metric': 0.9657881855964661, 'Val/mean miou_metric': 0.9437379837036133, 'Val/mean f1': 0.9689502120018005, 'Val/mean precision': 0.9630292057991028, 'Val/mean recall': 0.9749443531036377, 'Val/mean hd95_metric': 5.989047050476074} +Cheakpoint... +Epoch [581/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9657881855964661, 'Val/mean miou_metric': 0.9437379837036133, 'Val/mean f1': 0.9689502120018005, 'Val/mean precision': 0.9630292057991028, 'Val/mean recall': 0.9749443531036377, 'Val/mean hd95_metric': 5.989047050476074} +Epoch [582/4000] Training [1/16] Loss: 0.01350 +Epoch [582/4000] Training [2/16] Loss: 0.01724 +Epoch [582/4000] Training [3/16] Loss: 0.01734 +Epoch [582/4000] Training [4/16] Loss: 0.01109 +Epoch [582/4000] Training [5/16] Loss: 0.01061 +Epoch [582/4000] Training [6/16] Loss: 0.01523 +Epoch [582/4000] Training [7/16] Loss: 0.01131 +Epoch [582/4000] Training [8/16] Loss: 0.01113 +Epoch [582/4000] Training [9/16] Loss: 0.01397 +Epoch [582/4000] Training [10/16] Loss: 0.01490 +Epoch [582/4000] Training [11/16] Loss: 0.01113 +Epoch [582/4000] Training [12/16] Loss: 0.01308 +Epoch [582/4000] Training [13/16] Loss: 0.01867 +Epoch [582/4000] Training [14/16] Loss: 0.01359 +Epoch [582/4000] Training [15/16] Loss: 0.01300 +Epoch [582/4000] Training [16/16] Loss: 0.01923 +Epoch [582/4000] Training metric {'Train/mean dice_metric': 0.9902399182319641, 'Train/mean miou_metric': 0.9804511070251465, 'Train/mean f1': 0.9864103198051453, 'Train/mean precision': 0.9810048937797546, 'Train/mean recall': 0.9918756484985352, 'Train/mean hd95_metric': 1.6705918312072754} +Epoch [582/4000] Validation [1/4] Loss: 0.14454 focal_loss 0.08405 dice_loss 0.06050 +Epoch [582/4000] Validation [2/4] Loss: 0.23349 focal_loss 0.10523 dice_loss 0.12825 +Epoch [582/4000] Validation [3/4] Loss: 0.14560 focal_loss 0.06751 dice_loss 0.07809 +Epoch [582/4000] Validation [4/4] Loss: 0.32318 focal_loss 0.15422 dice_loss 0.16896 +Epoch [582/4000] Validation metric {'Val/mean dice_metric': 0.967921257019043, 'Val/mean miou_metric': 0.946210503578186, 'Val/mean f1': 0.9693657755851746, 'Val/mean precision': 0.9619234800338745, 'Val/mean recall': 0.9769241213798523, 'Val/mean hd95_metric': 5.987948417663574} +Cheakpoint... +Epoch [582/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967921257019043, 'Val/mean miou_metric': 0.946210503578186, 'Val/mean f1': 0.9693657755851746, 'Val/mean precision': 0.9619234800338745, 'Val/mean recall': 0.9769241213798523, 'Val/mean hd95_metric': 5.987948417663574} +Epoch [583/4000] Training [1/16] Loss: 0.01429 +Epoch [583/4000] Training [2/16] Loss: 0.01501 +Epoch [583/4000] Training [3/16] Loss: 0.01089 +Epoch [583/4000] Training [4/16] Loss: 0.01479 +Epoch [583/4000] Training [5/16] Loss: 0.01372 +Epoch [583/4000] Training [6/16] Loss: 0.01017 +Epoch [583/4000] Training [7/16] Loss: 0.01635 +Epoch [583/4000] Training [8/16] Loss: 0.01083 +Epoch [583/4000] Training [9/16] Loss: 0.01152 +Epoch [583/4000] Training [10/16] Loss: 0.01184 +Epoch [583/4000] Training [11/16] Loss: 0.01579 +Epoch [583/4000] Training [12/16] Loss: 0.01768 +Epoch [583/4000] Training [13/16] Loss: 0.01524 +Epoch [583/4000] Training [14/16] Loss: 0.01234 +Epoch [583/4000] Training [15/16] Loss: 0.01557 +Epoch [583/4000] Training [16/16] Loss: 0.02230 +Epoch [583/4000] Training metric {'Train/mean dice_metric': 0.989868700504303, 'Train/mean miou_metric': 0.9798085689544678, 'Train/mean f1': 0.9867252111434937, 'Train/mean precision': 0.982348620891571, 'Train/mean recall': 0.9911409616470337, 'Train/mean hd95_metric': 1.403688907623291} +Epoch [583/4000] Validation [1/4] Loss: 0.14328 focal_loss 0.08527 dice_loss 0.05801 +Epoch [583/4000] Validation [2/4] Loss: 0.21198 focal_loss 0.07623 dice_loss 0.13574 +Epoch [583/4000] Validation [3/4] Loss: 0.17309 focal_loss 0.06658 dice_loss 0.10651 +Epoch [583/4000] Validation [4/4] Loss: 0.15403 focal_loss 0.06375 dice_loss 0.09028 +Epoch [583/4000] Validation metric {'Val/mean dice_metric': 0.9680566787719727, 'Val/mean miou_metric': 0.946694016456604, 'Val/mean f1': 0.9685026407241821, 'Val/mean precision': 0.9598274230957031, 'Val/mean recall': 0.9773362278938293, 'Val/mean hd95_metric': 6.455603122711182} +Cheakpoint... +Epoch [583/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680566787719727, 'Val/mean miou_metric': 0.946694016456604, 'Val/mean f1': 0.9685026407241821, 'Val/mean precision': 0.9598274230957031, 'Val/mean recall': 0.9773362278938293, 'Val/mean hd95_metric': 6.455603122711182} +Epoch [584/4000] Training [1/16] Loss: 0.01643 +Epoch [584/4000] Training [2/16] Loss: 0.01831 +Epoch [584/4000] Training [3/16] Loss: 0.01788 +Epoch [584/4000] Training [4/16] Loss: 0.01178 +Epoch [584/4000] Training [5/16] Loss: 0.01414 +Epoch [584/4000] Training [6/16] Loss: 0.01273 +Epoch [584/4000] Training [7/16] Loss: 0.01709 +Epoch [584/4000] Training [8/16] Loss: 0.01112 +Epoch [584/4000] Training [9/16] Loss: 0.01146 +Epoch [584/4000] Training [10/16] Loss: 0.01494 +Epoch [584/4000] Training [11/16] Loss: 0.01637 +Epoch [584/4000] Training [12/16] Loss: 0.01803 +Epoch [584/4000] Training [13/16] Loss: 0.01192 +Epoch [584/4000] Training [14/16] Loss: 0.01193 +Epoch [584/4000] Training [15/16] Loss: 0.01308 +Epoch [584/4000] Training [16/16] Loss: 0.01218 +Epoch [584/4000] Training metric {'Train/mean dice_metric': 0.9903087615966797, 'Train/mean miou_metric': 0.9805866479873657, 'Train/mean f1': 0.9868412613868713, 'Train/mean precision': 0.9823290705680847, 'Train/mean recall': 0.991395115852356, 'Train/mean hd95_metric': 1.2398123741149902} +Epoch [584/4000] Validation [1/4] Loss: 0.12650 focal_loss 0.06666 dice_loss 0.05984 +Epoch [584/4000] Validation [2/4] Loss: 0.20720 focal_loss 0.08927 dice_loss 0.11793 +Epoch [584/4000] Validation [3/4] Loss: 0.20208 focal_loss 0.11054 dice_loss 0.09154 +Epoch [584/4000] Validation [4/4] Loss: 0.24087 focal_loss 0.12745 dice_loss 0.11342 +Epoch [584/4000] Validation metric {'Val/mean dice_metric': 0.9683228731155396, 'Val/mean miou_metric': 0.9473038911819458, 'Val/mean f1': 0.9684923887252808, 'Val/mean precision': 0.9599871635437012, 'Val/mean recall': 0.977149486541748, 'Val/mean hd95_metric': 6.268726825714111} +Cheakpoint... +Epoch [584/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683228731155396, 'Val/mean miou_metric': 0.9473038911819458, 'Val/mean f1': 0.9684923887252808, 'Val/mean precision': 0.9599871635437012, 'Val/mean recall': 0.977149486541748, 'Val/mean hd95_metric': 6.268726825714111} +Epoch [585/4000] Training [1/16] Loss: 0.01180 +Epoch [585/4000] Training [2/16] Loss: 0.01388 +Epoch [585/4000] Training [3/16] Loss: 0.01057 +Epoch [585/4000] Training [4/16] Loss: 0.01532 +Epoch [585/4000] Training [5/16] Loss: 0.01275 +Epoch [585/4000] Training [6/16] Loss: 0.01551 +Epoch [585/4000] Training [7/16] Loss: 0.01780 +Epoch [585/4000] Training [8/16] Loss: 0.01184 +Epoch [585/4000] Training [9/16] Loss: 0.01614 +Epoch [585/4000] Training [10/16] Loss: 0.01270 +Epoch [585/4000] Training [11/16] Loss: 0.01858 +Epoch [585/4000] Training [12/16] Loss: 0.01379 +Epoch [585/4000] Training [13/16] Loss: 0.01057 +Epoch [585/4000] Training [14/16] Loss: 0.01478 +Epoch [585/4000] Training [15/16] Loss: 0.02442 +Epoch [585/4000] Training [16/16] Loss: 0.01236 +Epoch [585/4000] Training metric {'Train/mean dice_metric': 0.9899075031280518, 'Train/mean miou_metric': 0.979819118976593, 'Train/mean f1': 0.9866981506347656, 'Train/mean precision': 0.9818209409713745, 'Train/mean recall': 0.9916240572929382, 'Train/mean hd95_metric': 1.8199101686477661} +Epoch [585/4000] Validation [1/4] Loss: 0.16315 focal_loss 0.09744 dice_loss 0.06570 +Epoch [585/4000] Validation [2/4] Loss: 0.21678 focal_loss 0.08503 dice_loss 0.13175 +Epoch [585/4000] Validation [3/4] Loss: 0.25308 focal_loss 0.14866 dice_loss 0.10442 +Epoch [585/4000] Validation [4/4] Loss: 0.23261 focal_loss 0.11683 dice_loss 0.11578 +Epoch [585/4000] Validation metric {'Val/mean dice_metric': 0.9680188894271851, 'Val/mean miou_metric': 0.9468612670898438, 'Val/mean f1': 0.970818281173706, 'Val/mean precision': 0.9651995301246643, 'Val/mean recall': 0.9765028357505798, 'Val/mean hd95_metric': 6.3003387451171875} +Cheakpoint... +Epoch [585/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680188894271851, 'Val/mean miou_metric': 0.9468612670898438, 'Val/mean f1': 0.970818281173706, 'Val/mean precision': 0.9651995301246643, 'Val/mean recall': 0.9765028357505798, 'Val/mean hd95_metric': 6.3003387451171875} +Epoch [586/4000] Training [1/16] Loss: 0.01707 +Epoch [586/4000] Training [2/16] Loss: 0.01438 +Epoch [586/4000] Training [3/16] Loss: 0.01439 +Epoch [586/4000] Training [4/16] Loss: 0.01549 +Epoch [586/4000] Training [5/16] Loss: 0.01421 +Epoch [586/4000] Training [6/16] Loss: 0.02056 +Epoch [586/4000] Training [7/16] Loss: 0.02085 +Epoch [586/4000] Training [8/16] Loss: 0.01203 +Epoch [586/4000] Training [9/16] Loss: 0.01162 +Epoch [586/4000] Training [10/16] Loss: 0.01343 +Epoch [586/4000] Training [11/16] Loss: 0.01413 +Epoch [586/4000] Training [12/16] Loss: 0.01307 +Epoch [586/4000] Training [13/16] Loss: 0.01447 +Epoch [586/4000] Training [14/16] Loss: 0.01402 +Epoch [586/4000] Training [15/16] Loss: 0.01679 +Epoch [586/4000] Training [16/16] Loss: 0.01300 +Epoch [586/4000] Training metric {'Train/mean dice_metric': 0.989933967590332, 'Train/mean miou_metric': 0.9798790216445923, 'Train/mean f1': 0.9871737360954285, 'Train/mean precision': 0.9828665256500244, 'Train/mean recall': 0.9915188550949097, 'Train/mean hd95_metric': 1.297153115272522} +Epoch [586/4000] Validation [1/4] Loss: 0.16818 focal_loss 0.10302 dice_loss 0.06516 +Epoch [586/4000] Validation [2/4] Loss: 0.26071 focal_loss 0.11524 dice_loss 0.14546 +Epoch [586/4000] Validation [3/4] Loss: 0.24307 focal_loss 0.14724 dice_loss 0.09584 +Epoch [586/4000] Validation [4/4] Loss: 0.25401 focal_loss 0.12330 dice_loss 0.13071 +Epoch [586/4000] Validation metric {'Val/mean dice_metric': 0.966325581073761, 'Val/mean miou_metric': 0.9451753497123718, 'Val/mean f1': 0.9695043563842773, 'Val/mean precision': 0.962539553642273, 'Val/mean recall': 0.9765704870223999, 'Val/mean hd95_metric': 5.952856540679932} +Cheakpoint... +Epoch [586/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966325581073761, 'Val/mean miou_metric': 0.9451753497123718, 'Val/mean f1': 0.9695043563842773, 'Val/mean precision': 0.962539553642273, 'Val/mean recall': 0.9765704870223999, 'Val/mean hd95_metric': 5.952856540679932} +Epoch [587/4000] Training [1/16] Loss: 0.01813 +Epoch [587/4000] Training [2/16] Loss: 0.01240 +Epoch [587/4000] Training [3/16] Loss: 0.01818 +Epoch [587/4000] Training [4/16] Loss: 0.01486 +Epoch [587/4000] Training [5/16] Loss: 0.02250 +Epoch [587/4000] Training [6/16] Loss: 0.01968 +Epoch [587/4000] Training [7/16] Loss: 0.01710 +Epoch [587/4000] Training [8/16] Loss: 0.01341 +Epoch [587/4000] Training [9/16] Loss: 0.01489 +Epoch [587/4000] Training [10/16] Loss: 0.01485 +Epoch [587/4000] Training [11/16] Loss: 0.02274 +Epoch [587/4000] Training [12/16] Loss: 0.01394 +Epoch [587/4000] Training [13/16] Loss: 0.01424 +Epoch [587/4000] Training [14/16] Loss: 0.00988 +Epoch [587/4000] Training [15/16] Loss: 0.01743 +Epoch [587/4000] Training [16/16] Loss: 0.01280 +Epoch [587/4000] Training metric {'Train/mean dice_metric': 0.9887428283691406, 'Train/mean miou_metric': 0.9775513410568237, 'Train/mean f1': 0.9855151176452637, 'Train/mean precision': 0.9802565574645996, 'Train/mean recall': 0.9908303618431091, 'Train/mean hd95_metric': 1.670851230621338} +Epoch [587/4000] Validation [1/4] Loss: 0.15661 focal_loss 0.09679 dice_loss 0.05982 +Epoch [587/4000] Validation [2/4] Loss: 0.18129 focal_loss 0.07417 dice_loss 0.10712 +Epoch [587/4000] Validation [3/4] Loss: 0.19151 focal_loss 0.09397 dice_loss 0.09753 +Epoch [587/4000] Validation [4/4] Loss: 0.24049 focal_loss 0.13247 dice_loss 0.10802 +Epoch [587/4000] Validation metric {'Val/mean dice_metric': 0.9651849865913391, 'Val/mean miou_metric': 0.9431165456771851, 'Val/mean f1': 0.9683967232704163, 'Val/mean precision': 0.9629052877426147, 'Val/mean recall': 0.9739512205123901, 'Val/mean hd95_metric': 6.345005989074707} +Cheakpoint... +Epoch [587/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651849865913391, 'Val/mean miou_metric': 0.9431165456771851, 'Val/mean f1': 0.9683967232704163, 'Val/mean precision': 0.9629052877426147, 'Val/mean recall': 0.9739512205123901, 'Val/mean hd95_metric': 6.345005989074707} +Epoch [588/4000] Training [1/16] Loss: 0.01963 +Epoch [588/4000] Training [2/16] Loss: 0.01178 +Epoch [588/4000] Training [3/16] Loss: 0.01295 +Epoch [588/4000] Training [4/16] Loss: 0.01199 +Epoch [588/4000] Training [5/16] Loss: 0.01620 +Epoch [588/4000] Training [6/16] Loss: 0.01225 +Epoch [588/4000] Training [7/16] Loss: 0.02931 +Epoch [588/4000] Training [8/16] Loss: 0.01429 +Epoch [588/4000] Training [9/16] Loss: 0.00962 +Epoch [588/4000] Training [10/16] Loss: 0.01368 +Epoch [588/4000] Training [11/16] Loss: 0.01304 +Epoch [588/4000] Training [12/16] Loss: 0.01815 +Epoch [588/4000] Training [13/16] Loss: 0.01364 +Epoch [588/4000] Training [14/16] Loss: 0.01416 +Epoch [588/4000] Training [15/16] Loss: 0.01597 +Epoch [588/4000] Training [16/16] Loss: 0.03767 +Epoch [588/4000] Training metric {'Train/mean dice_metric': 0.9897165298461914, 'Train/mean miou_metric': 0.9794728755950928, 'Train/mean f1': 0.9865632057189941, 'Train/mean precision': 0.9822222590446472, 'Train/mean recall': 0.990942656993866, 'Train/mean hd95_metric': 1.4369542598724365} +Epoch [588/4000] Validation [1/4] Loss: 0.22942 focal_loss 0.15108 dice_loss 0.07834 +Epoch [588/4000] Validation [2/4] Loss: 0.28431 focal_loss 0.14591 dice_loss 0.13840 +Epoch [588/4000] Validation [3/4] Loss: 0.23874 focal_loss 0.13781 dice_loss 0.10093 +Epoch [588/4000] Validation [4/4] Loss: 0.21167 focal_loss 0.10642 dice_loss 0.10525 +Epoch [588/4000] Validation metric {'Val/mean dice_metric': 0.9669266939163208, 'Val/mean miou_metric': 0.9456815719604492, 'Val/mean f1': 0.9695886373519897, 'Val/mean precision': 0.9640488624572754, 'Val/mean recall': 0.9751925468444824, 'Val/mean hd95_metric': 6.381160736083984} +Cheakpoint... +Epoch [588/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669266939163208, 'Val/mean miou_metric': 0.9456815719604492, 'Val/mean f1': 0.9695886373519897, 'Val/mean precision': 0.9640488624572754, 'Val/mean recall': 0.9751925468444824, 'Val/mean hd95_metric': 6.381160736083984} +Epoch [589/4000] Training [1/16] Loss: 0.04509 +Epoch [589/4000] Training [2/16] Loss: 0.01372 +Epoch [589/4000] Training [3/16] Loss: 0.01437 +Epoch [589/4000] Training [4/16] Loss: 0.01955 +Epoch [589/4000] Training [5/16] Loss: 0.01477 +Epoch [589/4000] Training [6/16] Loss: 0.01532 +Epoch [589/4000] Training [7/16] Loss: 0.01763 +Epoch [589/4000] Training [8/16] Loss: 0.01431 +Epoch [589/4000] Training [9/16] Loss: 0.01591 +Epoch [589/4000] Training [10/16] Loss: 0.01285 +Epoch [589/4000] Training [11/16] Loss: 0.17119 +Epoch [589/4000] Training [12/16] Loss: 0.01629 +Epoch [589/4000] Training [13/16] Loss: 0.01551 +Epoch [589/4000] Training [14/16] Loss: 0.01896 +Epoch [589/4000] Training [15/16] Loss: 0.01660 +Epoch [589/4000] Training [16/16] Loss: 0.01416 +Epoch [589/4000] Training metric {'Train/mean dice_metric': 0.987766683101654, 'Train/mean miou_metric': 0.9762232303619385, 'Train/mean f1': 0.9839454293251038, 'Train/mean precision': 0.9776807427406311, 'Train/mean recall': 0.9902908802032471, 'Train/mean hd95_metric': 1.8578310012817383} +Epoch [589/4000] Validation [1/4] Loss: 0.30784 focal_loss 0.20406 dice_loss 0.10378 +Epoch [589/4000] Validation [2/4] Loss: 0.54012 focal_loss 0.25644 dice_loss 0.28369 +Epoch [589/4000] Validation [3/4] Loss: 0.19986 focal_loss 0.10903 dice_loss 0.09083 +Epoch [589/4000] Validation [4/4] Loss: 0.19941 focal_loss 0.09452 dice_loss 0.10489 +Epoch [589/4000] Validation metric {'Val/mean dice_metric': 0.959276020526886, 'Val/mean miou_metric': 0.9368585348129272, 'Val/mean f1': 0.9633861184120178, 'Val/mean precision': 0.9608430862426758, 'Val/mean recall': 0.9659426212310791, 'Val/mean hd95_metric': 7.955132961273193} +Cheakpoint... +Epoch [589/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959276020526886, 'Val/mean miou_metric': 0.9368585348129272, 'Val/mean f1': 0.9633861184120178, 'Val/mean precision': 0.9608430862426758, 'Val/mean recall': 0.9659426212310791, 'Val/mean hd95_metric': 7.955132961273193} +Epoch [590/4000] Training [1/16] Loss: 0.01784 +Epoch [590/4000] Training [2/16] Loss: 0.01515 +Epoch [590/4000] Training [3/16] Loss: 0.00964 +Epoch [590/4000] Training [4/16] Loss: 0.01486 +Epoch [590/4000] Training [5/16] Loss: 0.01589 +Epoch [590/4000] Training [6/16] Loss: 0.01344 +Epoch [590/4000] Training [7/16] Loss: 0.02075 +Epoch [590/4000] Training [8/16] Loss: 0.01579 +Epoch [590/4000] Training [9/16] Loss: 0.01262 +Epoch [590/4000] Training [10/16] Loss: 0.01256 +Epoch [590/4000] Training [11/16] Loss: 0.01197 +Epoch [590/4000] Training [12/16] Loss: 0.01848 +Epoch [590/4000] Training [13/16] Loss: 0.01095 +Epoch [590/4000] Training [14/16] Loss: 0.01189 +Epoch [590/4000] Training [15/16] Loss: 0.01543 +Epoch [590/4000] Training [16/16] Loss: 0.01701 +Epoch [590/4000] Training metric {'Train/mean dice_metric': 0.9895554184913635, 'Train/mean miou_metric': 0.9791560173034668, 'Train/mean f1': 0.9865883588790894, 'Train/mean precision': 0.9819000959396362, 'Train/mean recall': 0.9913216233253479, 'Train/mean hd95_metric': 1.430464744567871} +Epoch [590/4000] Validation [1/4] Loss: 0.23991 focal_loss 0.14610 dice_loss 0.09381 +Epoch [590/4000] Validation [2/4] Loss: 0.46074 focal_loss 0.26264 dice_loss 0.19810 +Epoch [590/4000] Validation [3/4] Loss: 0.24842 focal_loss 0.13773 dice_loss 0.11069 +Epoch [590/4000] Validation [4/4] Loss: 0.33394 focal_loss 0.17619 dice_loss 0.15775 +Epoch [590/4000] Validation metric {'Val/mean dice_metric': 0.9647091031074524, 'Val/mean miou_metric': 0.9419944882392883, 'Val/mean f1': 0.9660539031028748, 'Val/mean precision': 0.9666327238082886, 'Val/mean recall': 0.9654759168624878, 'Val/mean hd95_metric': 6.386991024017334} +Cheakpoint... +Epoch [590/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647091031074524, 'Val/mean miou_metric': 0.9419944882392883, 'Val/mean f1': 0.9660539031028748, 'Val/mean precision': 0.9666327238082886, 'Val/mean recall': 0.9654759168624878, 'Val/mean hd95_metric': 6.386991024017334} +Epoch [591/4000] Training [1/16] Loss: 0.02301 +Epoch [591/4000] Training [2/16] Loss: 0.01221 +Epoch [591/4000] Training [3/16] Loss: 0.01912 +Epoch [591/4000] Training [4/16] Loss: 0.11316 +Epoch [591/4000] Training [5/16] Loss: 0.01451 +Epoch [591/4000] Training [6/16] Loss: 0.01335 +Epoch [591/4000] Training [7/16] Loss: 0.01166 +Epoch [591/4000] Training [8/16] Loss: 0.01437 +Epoch [591/4000] Training [9/16] Loss: 0.01599 +Epoch [591/4000] Training [10/16] Loss: 0.01136 +Epoch [591/4000] Training [11/16] Loss: 0.01285 +Epoch [591/4000] Training [12/16] Loss: 0.01198 +Epoch [591/4000] Training [13/16] Loss: 0.01431 +Epoch [591/4000] Training [14/16] Loss: 0.01533 +Epoch [591/4000] Training [15/16] Loss: 0.01533 +Epoch [591/4000] Training [16/16] Loss: 0.01244 +Epoch [591/4000] Training metric {'Train/mean dice_metric': 0.9895453453063965, 'Train/mean miou_metric': 0.97925865650177, 'Train/mean f1': 0.9846200942993164, 'Train/mean precision': 0.9795507192611694, 'Train/mean recall': 0.9897422194480896, 'Train/mean hd95_metric': 1.6465682983398438} +Epoch [591/4000] Validation [1/4] Loss: 0.17522 focal_loss 0.10447 dice_loss 0.07076 +Epoch [591/4000] Validation [2/4] Loss: 0.31685 focal_loss 0.16052 dice_loss 0.15634 +Epoch [591/4000] Validation [3/4] Loss: 0.29085 focal_loss 0.14882 dice_loss 0.14203 +Epoch [591/4000] Validation [4/4] Loss: 0.36262 focal_loss 0.19192 dice_loss 0.17070 +Epoch [591/4000] Validation metric {'Val/mean dice_metric': 0.9651397466659546, 'Val/mean miou_metric': 0.9425384402275085, 'Val/mean f1': 0.9617339372634888, 'Val/mean precision': 0.948323130607605, 'Val/mean recall': 0.9755296111106873, 'Val/mean hd95_metric': 8.134428024291992} +Cheakpoint... +Epoch [591/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651397466659546, 'Val/mean miou_metric': 0.9425384402275085, 'Val/mean f1': 0.9617339372634888, 'Val/mean precision': 0.948323130607605, 'Val/mean recall': 0.9755296111106873, 'Val/mean hd95_metric': 8.134428024291992} +Epoch [592/4000] Training [1/16] Loss: 0.01121 +Epoch [592/4000] Training [2/16] Loss: 0.01212 +Epoch [592/4000] Training [3/16] Loss: 0.01270 +Epoch [592/4000] Training [4/16] Loss: 0.01134 +Epoch [592/4000] Training [5/16] Loss: 0.01580 +Epoch [592/4000] Training [6/16] Loss: 0.01331 +Epoch [592/4000] Training [7/16] Loss: 0.01171 +Epoch [592/4000] Training [8/16] Loss: 0.01052 +Epoch [592/4000] Training [9/16] Loss: 0.01373 +Epoch [592/4000] Training [10/16] Loss: 0.01248 +Epoch [592/4000] Training [11/16] Loss: 0.02746 +Epoch [592/4000] Training [12/16] Loss: 0.01351 +Epoch [592/4000] Training [13/16] Loss: 0.01554 +Epoch [592/4000] Training [14/16] Loss: 0.01242 +Epoch [592/4000] Training [15/16] Loss: 0.01443 +Epoch [592/4000] Training [16/16] Loss: 0.01488 +Epoch [592/4000] Training metric {'Train/mean dice_metric': 0.9903716444969177, 'Train/mean miou_metric': 0.9807308912277222, 'Train/mean f1': 0.9871044754981995, 'Train/mean precision': 0.9824700355529785, 'Train/mean recall': 0.9917827844619751, 'Train/mean hd95_metric': 1.3780503273010254} +Epoch [592/4000] Validation [1/4] Loss: 0.19822 focal_loss 0.11869 dice_loss 0.07953 +Epoch [592/4000] Validation [2/4] Loss: 0.27550 focal_loss 0.13625 dice_loss 0.13924 +Epoch [592/4000] Validation [3/4] Loss: 0.10665 focal_loss 0.05481 dice_loss 0.05185 +Epoch [592/4000] Validation [4/4] Loss: 0.32223 focal_loss 0.17084 dice_loss 0.15140 +Epoch [592/4000] Validation metric {'Val/mean dice_metric': 0.9668617248535156, 'Val/mean miou_metric': 0.9451369047164917, 'Val/mean f1': 0.9657402634620667, 'Val/mean precision': 0.9552989602088928, 'Val/mean recall': 0.9764123558998108, 'Val/mean hd95_metric': 7.033795356750488} +Cheakpoint... +Epoch [592/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668617248535156, 'Val/mean miou_metric': 0.9451369047164917, 'Val/mean f1': 0.9657402634620667, 'Val/mean precision': 0.9552989602088928, 'Val/mean recall': 0.9764123558998108, 'Val/mean hd95_metric': 7.033795356750488} +Epoch [593/4000] Training [1/16] Loss: 0.01100 +Epoch [593/4000] Training [2/16] Loss: 0.02382 +Epoch [593/4000] Training [3/16] Loss: 0.01300 +Epoch [593/4000] Training [4/16] Loss: 0.01024 +Epoch [593/4000] Training [5/16] Loss: 0.01620 +Epoch [593/4000] Training [6/16] Loss: 0.01846 +Epoch [593/4000] Training [7/16] Loss: 0.01282 +Epoch [593/4000] Training [8/16] Loss: 0.00997 +Epoch [593/4000] Training [9/16] Loss: 0.01113 +Epoch [593/4000] Training [10/16] Loss: 0.01796 +Epoch [593/4000] Training [11/16] Loss: 0.01388 +Epoch [593/4000] Training [12/16] Loss: 0.01170 +Epoch [593/4000] Training [13/16] Loss: 0.01752 +Epoch [593/4000] Training [14/16] Loss: 0.01295 +Epoch [593/4000] Training [15/16] Loss: 0.01067 +Epoch [593/4000] Training [16/16] Loss: 0.01097 +Epoch [593/4000] Training metric {'Train/mean dice_metric': 0.9903260469436646, 'Train/mean miou_metric': 0.9806647300720215, 'Train/mean f1': 0.9873722791671753, 'Train/mean precision': 0.982465386390686, 'Train/mean recall': 0.992328405380249, 'Train/mean hd95_metric': 1.2818751335144043} +Epoch [593/4000] Validation [1/4] Loss: 0.16407 focal_loss 0.09868 dice_loss 0.06539 +Epoch [593/4000] Validation [2/4] Loss: 0.21784 focal_loss 0.10056 dice_loss 0.11728 +Epoch [593/4000] Validation [3/4] Loss: 0.17947 focal_loss 0.08180 dice_loss 0.09767 +Epoch [593/4000] Validation [4/4] Loss: 0.33172 focal_loss 0.17245 dice_loss 0.15927 +Epoch [593/4000] Validation metric {'Val/mean dice_metric': 0.9679080843925476, 'Val/mean miou_metric': 0.9465214014053345, 'Val/mean f1': 0.9685056209564209, 'Val/mean precision': 0.9611367583274841, 'Val/mean recall': 0.975988507270813, 'Val/mean hd95_metric': 6.362133026123047} +Cheakpoint... +Epoch [593/4000] best acc:tensor([0.9691], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679080843925476, 'Val/mean miou_metric': 0.9465214014053345, 'Val/mean f1': 0.9685056209564209, 'Val/mean precision': 0.9611367583274841, 'Val/mean recall': 0.975988507270813, 'Val/mean hd95_metric': 6.362133026123047} +Epoch [594/4000] Training [1/16] Loss: 0.01134 +Epoch [594/4000] Training [2/16] Loss: 0.01543 +Epoch [594/4000] Training [3/16] Loss: 0.01280 +Epoch [594/4000] Training [4/16] Loss: 0.01247 +Epoch [594/4000] Training [5/16] Loss: 0.01216 +Epoch [594/4000] Training [6/16] Loss: 0.01817 +Epoch [594/4000] Training [7/16] Loss: 0.01130 +Epoch [594/4000] Training [8/16] Loss: 0.01241 +Epoch [594/4000] Training [9/16] Loss: 0.01836 +Epoch [594/4000] Training [10/16] Loss: 0.01346 +Epoch [594/4000] Training [11/16] Loss: 0.01222 +Epoch [594/4000] Training [12/16] Loss: 0.01246 +Epoch [594/4000] Training [13/16] Loss: 0.01466 +Epoch [594/4000] Training [14/16] Loss: 0.02032 +Epoch [594/4000] Training [15/16] Loss: 0.01873 +Epoch [594/4000] Training [16/16] Loss: 0.01267 +Epoch [594/4000] Training metric {'Train/mean dice_metric': 0.990251898765564, 'Train/mean miou_metric': 0.9805058240890503, 'Train/mean f1': 0.9872594475746155, 'Train/mean precision': 0.9827823042869568, 'Train/mean recall': 0.9917775392532349, 'Train/mean hd95_metric': 1.3203439712524414} +Epoch [594/4000] Validation [1/4] Loss: 0.17354 focal_loss 0.09932 dice_loss 0.07422 +Epoch [594/4000] Validation [2/4] Loss: 0.19337 focal_loss 0.07943 dice_loss 0.11394 +Epoch [594/4000] Validation [3/4] Loss: 0.10505 focal_loss 0.05038 dice_loss 0.05467 +Epoch [594/4000] Validation [4/4] Loss: 0.28485 focal_loss 0.15333 dice_loss 0.13152 +Epoch [594/4000] Validation metric {'Val/mean dice_metric': 0.9691654443740845, 'Val/mean miou_metric': 0.9482923746109009, 'Val/mean f1': 0.9675017595291138, 'Val/mean precision': 0.9587383270263672, 'Val/mean recall': 0.9764268398284912, 'Val/mean hd95_metric': 6.145073890686035} +Cheakpoint... +Epoch [594/4000] best acc:tensor([0.9692], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691654443740845, 'Val/mean miou_metric': 0.9482923746109009, 'Val/mean f1': 0.9675017595291138, 'Val/mean precision': 0.9587383270263672, 'Val/mean recall': 0.9764268398284912, 'Val/mean hd95_metric': 6.145073890686035} +Epoch [595/4000] Training [1/16] Loss: 0.01697 +Epoch [595/4000] Training [2/16] Loss: 0.01974 +Epoch [595/4000] Training [3/16] Loss: 0.01424 +Epoch [595/4000] Training [4/16] Loss: 0.01552 +Epoch [595/4000] Training [5/16] Loss: 0.01391 +Epoch [595/4000] Training [6/16] Loss: 0.01108 +Epoch [595/4000] Training [7/16] Loss: 0.01129 +Epoch [595/4000] Training [8/16] Loss: 0.01620 +Epoch [595/4000] Training [9/16] Loss: 0.01577 +Epoch [595/4000] Training [10/16] Loss: 0.01324 +Epoch [595/4000] Training [11/16] Loss: 0.01864 +Epoch [595/4000] Training [12/16] Loss: 0.01131 +Epoch [595/4000] Training [13/16] Loss: 0.01273 +Epoch [595/4000] Training [14/16] Loss: 0.01223 +Epoch [595/4000] Training [15/16] Loss: 0.01744 +Epoch [595/4000] Training [16/16] Loss: 0.01582 +Epoch [595/4000] Training metric {'Train/mean dice_metric': 0.9895234704017639, 'Train/mean miou_metric': 0.9791054725646973, 'Train/mean f1': 0.9867812395095825, 'Train/mean precision': 0.9820891618728638, 'Train/mean recall': 0.9915183186531067, 'Train/mean hd95_metric': 1.6187267303466797} +Epoch [595/4000] Validation [1/4] Loss: 0.19912 focal_loss 0.12534 dice_loss 0.07379 +Epoch [595/4000] Validation [2/4] Loss: 0.21339 focal_loss 0.09661 dice_loss 0.11678 +Epoch [595/4000] Validation [3/4] Loss: 0.10359 focal_loss 0.04617 dice_loss 0.05742 +Epoch [595/4000] Validation [4/4] Loss: 0.25098 focal_loss 0.11234 dice_loss 0.13864 +Epoch [595/4000] Validation metric {'Val/mean dice_metric': 0.9640694856643677, 'Val/mean miou_metric': 0.9425989985466003, 'Val/mean f1': 0.967264711856842, 'Val/mean precision': 0.9605571031570435, 'Val/mean recall': 0.974066436290741, 'Val/mean hd95_metric': 7.26366662979126} +Cheakpoint... +Epoch [595/4000] best acc:tensor([0.9692], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640694856643677, 'Val/mean miou_metric': 0.9425989985466003, 'Val/mean f1': 0.967264711856842, 'Val/mean precision': 0.9605571031570435, 'Val/mean recall': 0.974066436290741, 'Val/mean hd95_metric': 7.26366662979126} +Epoch [596/4000] Training [1/16] Loss: 0.01531 +Epoch [596/4000] Training [2/16] Loss: 0.00933 +Epoch [596/4000] Training [3/16] Loss: 0.01383 +Epoch [596/4000] Training [4/16] Loss: 0.01316 +Epoch [596/4000] Training [5/16] Loss: 0.01370 +Epoch [596/4000] Training [6/16] Loss: 0.02219 +Epoch [596/4000] Training [7/16] Loss: 0.01655 +Epoch [596/4000] Training [8/16] Loss: 0.01082 +Epoch [596/4000] Training [9/16] Loss: 0.01549 +Epoch [596/4000] Training [10/16] Loss: 0.01593 +Epoch [596/4000] Training [11/16] Loss: 0.01924 +Epoch [596/4000] Training [12/16] Loss: 0.01802 +Epoch [596/4000] Training [13/16] Loss: 0.02322 +Epoch [596/4000] Training [14/16] Loss: 0.01746 +Epoch [596/4000] Training [15/16] Loss: 0.01657 +Epoch [596/4000] Training [16/16] Loss: 0.01586 +Epoch [596/4000] Training metric {'Train/mean dice_metric': 0.9892441034317017, 'Train/mean miou_metric': 0.9785400032997131, 'Train/mean f1': 0.9863151907920837, 'Train/mean precision': 0.9814435839653015, 'Train/mean recall': 0.9912353754043579, 'Train/mean hd95_metric': 1.4976229667663574} +Epoch [596/4000] Validation [1/4] Loss: 0.15077 focal_loss 0.09053 dice_loss 0.06024 +Epoch [596/4000] Validation [2/4] Loss: 0.30624 focal_loss 0.11456 dice_loss 0.19168 +Epoch [596/4000] Validation [3/4] Loss: 0.12110 focal_loss 0.06384 dice_loss 0.05726 +Epoch [596/4000] Validation [4/4] Loss: 0.43794 focal_loss 0.24630 dice_loss 0.19164 +Epoch [596/4000] Validation metric {'Val/mean dice_metric': 0.9645273089408875, 'Val/mean miou_metric': 0.9424238204956055, 'Val/mean f1': 0.9617300033569336, 'Val/mean precision': 0.9472875595092773, 'Val/mean recall': 0.9766196012496948, 'Val/mean hd95_metric': 7.918046474456787} +Cheakpoint... +Epoch [596/4000] best acc:tensor([0.9692], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645273089408875, 'Val/mean miou_metric': 0.9424238204956055, 'Val/mean f1': 0.9617300033569336, 'Val/mean precision': 0.9472875595092773, 'Val/mean recall': 0.9766196012496948, 'Val/mean hd95_metric': 7.918046474456787} +Epoch [597/4000] Training [1/16] Loss: 0.02263 +Epoch [597/4000] Training [2/16] Loss: 0.01730 +Epoch [597/4000] Training [3/16] Loss: 0.02052 +Epoch [597/4000] Training [4/16] Loss: 0.01331 +Epoch [597/4000] Training [5/16] Loss: 0.01528 +Epoch [597/4000] Training [6/16] Loss: 0.01726 +Epoch [597/4000] Training [7/16] Loss: 0.01142 +Epoch [597/4000] Training [8/16] Loss: 0.01444 +Epoch [597/4000] Training [9/16] Loss: 0.01955 +Epoch [597/4000] Training [10/16] Loss: 0.01493 +Epoch [597/4000] Training [11/16] Loss: 0.01745 +Epoch [597/4000] Training [12/16] Loss: 0.01420 +Epoch [597/4000] Training [13/16] Loss: 0.01589 +Epoch [597/4000] Training [14/16] Loss: 0.01287 +Epoch [597/4000] Training [15/16] Loss: 0.01529 +Epoch [597/4000] Training [16/16] Loss: 0.01533 +Epoch [597/4000] Training metric {'Train/mean dice_metric': 0.9889224171638489, 'Train/mean miou_metric': 0.9778870344161987, 'Train/mean f1': 0.9858459830284119, 'Train/mean precision': 0.9810827970504761, 'Train/mean recall': 0.9906556606292725, 'Train/mean hd95_metric': 1.8233534097671509} +Epoch [597/4000] Validation [1/4] Loss: 0.16410 focal_loss 0.10088 dice_loss 0.06322 +Epoch [597/4000] Validation [2/4] Loss: 0.27292 focal_loss 0.13427 dice_loss 0.13865 +Epoch [597/4000] Validation [3/4] Loss: 0.12021 focal_loss 0.06517 dice_loss 0.05504 +Epoch [597/4000] Validation [4/4] Loss: 0.26458 focal_loss 0.15348 dice_loss 0.11110 +Epoch [597/4000] Validation metric {'Val/mean dice_metric': 0.966286838054657, 'Val/mean miou_metric': 0.9440302848815918, 'Val/mean f1': 0.9667874574661255, 'Val/mean precision': 0.9618685245513916, 'Val/mean recall': 0.9717569351196289, 'Val/mean hd95_metric': 7.072020053863525} +Cheakpoint... +Epoch [597/4000] best acc:tensor([0.9692], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966286838054657, 'Val/mean miou_metric': 0.9440302848815918, 'Val/mean f1': 0.9667874574661255, 'Val/mean precision': 0.9618685245513916, 'Val/mean recall': 0.9717569351196289, 'Val/mean hd95_metric': 7.072020053863525} +Epoch [598/4000] Training [1/16] Loss: 0.01428 +Epoch [598/4000] Training [2/16] Loss: 0.01447 +Epoch [598/4000] Training [3/16] Loss: 0.01422 +Epoch [598/4000] Training [4/16] Loss: 0.02319 +Epoch [598/4000] Training [5/16] Loss: 0.02130 +Epoch [598/4000] Training [6/16] Loss: 0.01207 +Epoch [598/4000] Training [7/16] Loss: 0.01461 +Epoch [598/4000] Training [8/16] Loss: 0.01562 +Epoch [598/4000] Training [9/16] Loss: 0.01398 +Epoch [598/4000] Training [10/16] Loss: 0.01744 +Epoch [598/4000] Training [11/16] Loss: 0.01672 +Epoch [598/4000] Training [12/16] Loss: 0.01406 +Epoch [598/4000] Training [13/16] Loss: 0.01412 +Epoch [598/4000] Training [14/16] Loss: 0.01345 +Epoch [598/4000] Training [15/16] Loss: 0.01339 +Epoch [598/4000] Training [16/16] Loss: 0.01400 +Epoch [598/4000] Training metric {'Train/mean dice_metric': 0.9892591238021851, 'Train/mean miou_metric': 0.9785768985748291, 'Train/mean f1': 0.9863616228103638, 'Train/mean precision': 0.9816559553146362, 'Train/mean recall': 0.9911125898361206, 'Train/mean hd95_metric': 1.4259908199310303} +Epoch [598/4000] Validation [1/4] Loss: 0.15807 focal_loss 0.09629 dice_loss 0.06178 +Epoch [598/4000] Validation [2/4] Loss: 0.36523 focal_loss 0.17794 dice_loss 0.18729 +Epoch [598/4000] Validation [3/4] Loss: 0.12178 focal_loss 0.06118 dice_loss 0.06060 +Epoch [598/4000] Validation [4/4] Loss: 0.24453 focal_loss 0.12985 dice_loss 0.11467 +Epoch [598/4000] Validation metric {'Val/mean dice_metric': 0.9654712677001953, 'Val/mean miou_metric': 0.9441148638725281, 'Val/mean f1': 0.963378369808197, 'Val/mean precision': 0.9504458904266357, 'Val/mean recall': 0.9766678214073181, 'Val/mean hd95_metric': 7.038498878479004} +Cheakpoint... +Epoch [598/4000] best acc:tensor([0.9692], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654712677001953, 'Val/mean miou_metric': 0.9441148638725281, 'Val/mean f1': 0.963378369808197, 'Val/mean precision': 0.9504458904266357, 'Val/mean recall': 0.9766678214073181, 'Val/mean hd95_metric': 7.038498878479004} +Epoch [599/4000] Training [1/16] Loss: 0.01264 +Epoch [599/4000] Training [2/16] Loss: 0.01249 +Epoch [599/4000] Training [3/16] Loss: 0.01985 +Epoch [599/4000] Training [4/16] Loss: 0.01147 +Epoch [599/4000] Training [5/16] Loss: 0.01391 +Epoch [599/4000] Training [6/16] Loss: 0.01342 +Epoch [599/4000] Training [7/16] Loss: 0.01150 +Epoch [599/4000] Training [8/16] Loss: 0.01581 +Epoch [599/4000] Training [9/16] Loss: 0.01628 +Epoch [599/4000] Training [10/16] Loss: 0.01144 +Epoch [599/4000] Training [11/16] Loss: 0.01392 +Epoch [599/4000] Training [12/16] Loss: 0.01246 +Epoch [599/4000] Training [13/16] Loss: 0.01164 +Epoch [599/4000] Training [14/16] Loss: 0.01448 +Epoch [599/4000] Training [15/16] Loss: 0.01651 +Epoch [599/4000] Training [16/16] Loss: 0.02022 +Epoch [599/4000] Training metric {'Train/mean dice_metric': 0.9898608326911926, 'Train/mean miou_metric': 0.979708194732666, 'Train/mean f1': 0.9862021207809448, 'Train/mean precision': 0.981648862361908, 'Train/mean recall': 0.9907978177070618, 'Train/mean hd95_metric': 1.2835997343063354} +Epoch [599/4000] Validation [1/4] Loss: 0.15234 focal_loss 0.08743 dice_loss 0.06491 +Epoch [599/4000] Validation [2/4] Loss: 0.23951 focal_loss 0.11144 dice_loss 0.12807 +Epoch [599/4000] Validation [3/4] Loss: 0.17029 focal_loss 0.09534 dice_loss 0.07495 +Epoch [599/4000] Validation [4/4] Loss: 0.23722 focal_loss 0.11884 dice_loss 0.11838 +Epoch [599/4000] Validation metric {'Val/mean dice_metric': 0.969465434551239, 'Val/mean miou_metric': 0.9479557871818542, 'Val/mean f1': 0.9684039354324341, 'Val/mean precision': 0.9625353217124939, 'Val/mean recall': 0.9743446111679077, 'Val/mean hd95_metric': 5.710379123687744} +Cheakpoint... +Epoch [599/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969465434551239, 'Val/mean miou_metric': 0.9479557871818542, 'Val/mean f1': 0.9684039354324341, 'Val/mean precision': 0.9625353217124939, 'Val/mean recall': 0.9743446111679077, 'Val/mean hd95_metric': 5.710379123687744} +Epoch [600/4000] Training [1/16] Loss: 0.01332 +Epoch [600/4000] Training [2/16] Loss: 0.01251 +Epoch [600/4000] Training [3/16] Loss: 0.01362 +Epoch [600/4000] Training [4/16] Loss: 0.01138 +Epoch [600/4000] Training [5/16] Loss: 0.01334 +Epoch [600/4000] Training [6/16] Loss: 0.01275 +Epoch [600/4000] Training [7/16] Loss: 0.01425 +Epoch [600/4000] Training [8/16] Loss: 0.01656 +Epoch [600/4000] Training [9/16] Loss: 0.01390 +Epoch [600/4000] Training [10/16] Loss: 0.01334 +Epoch [600/4000] Training [11/16] Loss: 0.01316 +Epoch [600/4000] Training [12/16] Loss: 0.01237 +Epoch [600/4000] Training [13/16] Loss: 0.02327 +Epoch [600/4000] Training [14/16] Loss: 0.01231 +Epoch [600/4000] Training [15/16] Loss: 0.01450 +Epoch [600/4000] Training [16/16] Loss: 0.01165 +Epoch [600/4000] Training metric {'Train/mean dice_metric': 0.9899469614028931, 'Train/mean miou_metric': 0.9799867868423462, 'Train/mean f1': 0.9862495064735413, 'Train/mean precision': 0.9812470078468323, 'Train/mean recall': 0.9913032650947571, 'Train/mean hd95_metric': 1.8627796173095703} +Epoch [600/4000] Validation [1/4] Loss: 0.29674 focal_loss 0.20116 dice_loss 0.09558 +Epoch [600/4000] Validation [2/4] Loss: 0.31554 focal_loss 0.12774 dice_loss 0.18780 +Epoch [600/4000] Validation [3/4] Loss: 0.24884 focal_loss 0.12107 dice_loss 0.12777 +Epoch [600/4000] Validation [4/4] Loss: 0.54974 focal_loss 0.35972 dice_loss 0.19003 +Epoch [600/4000] Validation metric {'Val/mean dice_metric': 0.9623271822929382, 'Val/mean miou_metric': 0.9396233558654785, 'Val/mean f1': 0.9640242457389832, 'Val/mean precision': 0.9665212035179138, 'Val/mean recall': 0.9615401029586792, 'Val/mean hd95_metric': 8.089826583862305} +Cheakpoint... +Epoch [600/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9623], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9623271822929382, 'Val/mean miou_metric': 0.9396233558654785, 'Val/mean f1': 0.9640242457389832, 'Val/mean precision': 0.9665212035179138, 'Val/mean recall': 0.9615401029586792, 'Val/mean hd95_metric': 8.089826583862305} +Epoch [601/4000] Training [1/16] Loss: 0.01319 +Epoch [601/4000] Training [2/16] Loss: 0.01161 +Epoch [601/4000] Training [3/16] Loss: 0.01441 +Epoch [601/4000] Training [4/16] Loss: 0.01498 +Epoch [601/4000] Training [5/16] Loss: 0.01480 +Epoch [601/4000] Training [6/16] Loss: 0.01112 +Epoch [601/4000] Training [7/16] Loss: 0.01467 +Epoch [601/4000] Training [8/16] Loss: 0.01453 +Epoch [601/4000] Training [9/16] Loss: 0.01632 +Epoch [601/4000] Training [10/16] Loss: 0.01723 +Epoch [601/4000] Training [11/16] Loss: 0.02091 +Epoch [601/4000] Training [12/16] Loss: 0.01380 +Epoch [601/4000] Training [13/16] Loss: 0.01779 +Epoch [601/4000] Training [14/16] Loss: 0.02663 +Epoch [601/4000] Training [15/16] Loss: 0.01577 +Epoch [601/4000] Training [16/16] Loss: 0.01419 +Epoch [601/4000] Training metric {'Train/mean dice_metric': 0.9884188175201416, 'Train/mean miou_metric': 0.9770196676254272, 'Train/mean f1': 0.9848222732543945, 'Train/mean precision': 0.9792953133583069, 'Train/mean recall': 0.9904119372367859, 'Train/mean hd95_metric': 2.379689931869507} +Epoch [601/4000] Validation [1/4] Loss: 0.38001 focal_loss 0.26573 dice_loss 0.11427 +Epoch [601/4000] Validation [2/4] Loss: 0.26396 focal_loss 0.11730 dice_loss 0.14666 +Epoch [601/4000] Validation [3/4] Loss: 0.14805 focal_loss 0.07771 dice_loss 0.07033 +Epoch [601/4000] Validation [4/4] Loss: 0.20664 focal_loss 0.09947 dice_loss 0.10717 +Epoch [601/4000] Validation metric {'Val/mean dice_metric': 0.9650731086730957, 'Val/mean miou_metric': 0.9420148134231567, 'Val/mean f1': 0.9660892486572266, 'Val/mean precision': 0.9643453359603882, 'Val/mean recall': 0.9678394198417664, 'Val/mean hd95_metric': 7.011773586273193} +Cheakpoint... +Epoch [601/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650731086730957, 'Val/mean miou_metric': 0.9420148134231567, 'Val/mean f1': 0.9660892486572266, 'Val/mean precision': 0.9643453359603882, 'Val/mean recall': 0.9678394198417664, 'Val/mean hd95_metric': 7.011773586273193} +Epoch [602/4000] Training [1/16] Loss: 0.01248 +Epoch [602/4000] Training [2/16] Loss: 0.01210 +Epoch [602/4000] Training [3/16] Loss: 0.03066 +Epoch [602/4000] Training [4/16] Loss: 0.01318 +Epoch [602/4000] Training [5/16] Loss: 0.01144 +Epoch [602/4000] Training [6/16] Loss: 0.01480 +Epoch [602/4000] Training [7/16] Loss: 0.01450 +Epoch [602/4000] Training [8/16] Loss: 0.03226 +Epoch [602/4000] Training [9/16] Loss: 0.01312 +Epoch [602/4000] Training [10/16] Loss: 0.02357 +Epoch [602/4000] Training [11/16] Loss: 0.01388 +Epoch [602/4000] Training [12/16] Loss: 0.01360 +Epoch [602/4000] Training [13/16] Loss: 0.01661 +Epoch [602/4000] Training [14/16] Loss: 0.02109 +Epoch [602/4000] Training [15/16] Loss: 0.01542 +Epoch [602/4000] Training [16/16] Loss: 0.01496 +Epoch [602/4000] Training metric {'Train/mean dice_metric': 0.9880777597427368, 'Train/mean miou_metric': 0.9767957925796509, 'Train/mean f1': 0.9856975674629211, 'Train/mean precision': 0.9814358353614807, 'Train/mean recall': 0.9899964928627014, 'Train/mean hd95_metric': 1.7865875959396362} +Epoch [602/4000] Validation [1/4] Loss: 0.47170 focal_loss 0.32681 dice_loss 0.14489 +Epoch [602/4000] Validation [2/4] Loss: 0.21351 focal_loss 0.09571 dice_loss 0.11780 +Epoch [602/4000] Validation [3/4] Loss: 0.16200 focal_loss 0.08789 dice_loss 0.07412 +Epoch [602/4000] Validation [4/4] Loss: 0.20986 focal_loss 0.08465 dice_loss 0.12521 +Epoch [602/4000] Validation metric {'Val/mean dice_metric': 0.9614043235778809, 'Val/mean miou_metric': 0.9391590356826782, 'Val/mean f1': 0.9661129713058472, 'Val/mean precision': 0.9653142690658569, 'Val/mean recall': 0.966913104057312, 'Val/mean hd95_metric': 6.788806915283203} +Cheakpoint... +Epoch [602/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614043235778809, 'Val/mean miou_metric': 0.9391590356826782, 'Val/mean f1': 0.9661129713058472, 'Val/mean precision': 0.9653142690658569, 'Val/mean recall': 0.966913104057312, 'Val/mean hd95_metric': 6.788806915283203} +Epoch [603/4000] Training [1/16] Loss: 0.01791 +Epoch [603/4000] Training [2/16] Loss: 0.01289 +Epoch [603/4000] Training [3/16] Loss: 0.01531 +Epoch [603/4000] Training [4/16] Loss: 0.01909 +Epoch [603/4000] Training [5/16] Loss: 0.01803 +Epoch [603/4000] Training [6/16] Loss: 0.01326 +Epoch [603/4000] Training [7/16] Loss: 0.01994 +Epoch [603/4000] Training [8/16] Loss: 0.01458 +Epoch [603/4000] Training [9/16] Loss: 0.01595 +Epoch [603/4000] Training [10/16] Loss: 0.01090 +Epoch [603/4000] Training [11/16] Loss: 0.01592 +Epoch [603/4000] Training [12/16] Loss: 0.01737 +Epoch [603/4000] Training [13/16] Loss: 0.01311 +Epoch [603/4000] Training [14/16] Loss: 0.01420 +Epoch [603/4000] Training [15/16] Loss: 0.01167 +Epoch [603/4000] Training [16/16] Loss: 0.01869 +Epoch [603/4000] Training metric {'Train/mean dice_metric': 0.98722904920578, 'Train/mean miou_metric': 0.9750286340713501, 'Train/mean f1': 0.9846413731575012, 'Train/mean precision': 0.9804444909095764, 'Train/mean recall': 0.9888743758201599, 'Train/mean hd95_metric': 2.3817951679229736} +Epoch [603/4000] Validation [1/4] Loss: 0.27280 focal_loss 0.16738 dice_loss 0.10542 +Epoch [603/4000] Validation [2/4] Loss: 0.22310 focal_loss 0.09700 dice_loss 0.12610 +Epoch [603/4000] Validation [3/4] Loss: 0.15311 focal_loss 0.06231 dice_loss 0.09079 +Epoch [603/4000] Validation [4/4] Loss: 0.20754 focal_loss 0.09655 dice_loss 0.11100 +Epoch [603/4000] Validation metric {'Val/mean dice_metric': 0.9633709788322449, 'Val/mean miou_metric': 0.9402408599853516, 'Val/mean f1': 0.9668409824371338, 'Val/mean precision': 0.9645607471466064, 'Val/mean recall': 0.9691320657730103, 'Val/mean hd95_metric': 6.779483795166016} +Cheakpoint... +Epoch [603/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633709788322449, 'Val/mean miou_metric': 0.9402408599853516, 'Val/mean f1': 0.9668409824371338, 'Val/mean precision': 0.9645607471466064, 'Val/mean recall': 0.9691320657730103, 'Val/mean hd95_metric': 6.779483795166016} +Epoch [604/4000] Training [1/16] Loss: 0.01510 +Epoch [604/4000] Training [2/16] Loss: 0.01275 +Epoch [604/4000] Training [3/16] Loss: 0.01752 +Epoch [604/4000] Training [4/16] Loss: 0.01594 +Epoch [604/4000] Training [5/16] Loss: 0.02432 +Epoch [604/4000] Training [6/16] Loss: 0.01264 +Epoch [604/4000] Training [7/16] Loss: 0.01368 +Epoch [604/4000] Training [8/16] Loss: 0.01655 +Epoch [604/4000] Training [9/16] Loss: 0.01335 +Epoch [604/4000] Training [10/16] Loss: 0.01345 +Epoch [604/4000] Training [11/16] Loss: 0.01379 +Epoch [604/4000] Training [12/16] Loss: 0.01707 +Epoch [604/4000] Training [13/16] Loss: 0.01248 +Epoch [604/4000] Training [14/16] Loss: 0.05252 +Epoch [604/4000] Training [15/16] Loss: 0.01290 +Epoch [604/4000] Training [16/16] Loss: 0.01614 +Epoch [604/4000] Training metric {'Train/mean dice_metric': 0.989039957523346, 'Train/mean miou_metric': 0.9781724214553833, 'Train/mean f1': 0.9854726791381836, 'Train/mean precision': 0.9808409214019775, 'Train/mean recall': 0.9901483654975891, 'Train/mean hd95_metric': 2.00270938873291} +Epoch [604/4000] Validation [1/4] Loss: 0.63810 focal_loss 0.48426 dice_loss 0.15384 +Epoch [604/4000] Validation [2/4] Loss: 0.17566 focal_loss 0.07714 dice_loss 0.09851 +Epoch [604/4000] Validation [3/4] Loss: 0.17729 focal_loss 0.08635 dice_loss 0.09094 +Epoch [604/4000] Validation [4/4] Loss: 0.27778 focal_loss 0.13320 dice_loss 0.14458 +Epoch [604/4000] Validation metric {'Val/mean dice_metric': 0.9625740051269531, 'Val/mean miou_metric': 0.9412687420845032, 'Val/mean f1': 0.9666502475738525, 'Val/mean precision': 0.9668554663658142, 'Val/mean recall': 0.9664451479911804, 'Val/mean hd95_metric': 6.168660640716553} +Cheakpoint... +Epoch [604/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9626], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625740051269531, 'Val/mean miou_metric': 0.9412687420845032, 'Val/mean f1': 0.9666502475738525, 'Val/mean precision': 0.9668554663658142, 'Val/mean recall': 0.9664451479911804, 'Val/mean hd95_metric': 6.168660640716553} +Epoch [605/4000] Training [1/16] Loss: 0.02091 +Epoch [605/4000] Training [2/16] Loss: 0.01348 +Epoch [605/4000] Training [3/16] Loss: 0.01096 +Epoch [605/4000] Training [4/16] Loss: 0.01482 +Epoch [605/4000] Training [5/16] Loss: 0.01820 +Epoch [605/4000] Training [6/16] Loss: 0.01887 +Epoch [605/4000] Training [7/16] Loss: 0.01161 +Epoch [605/4000] Training [8/16] Loss: 0.01107 +Epoch [605/4000] Training [9/16] Loss: 0.02370 +Epoch [605/4000] Training [10/16] Loss: 0.01370 +Epoch [605/4000] Training [11/16] Loss: 0.01789 +Epoch [605/4000] Training [12/16] Loss: 0.01368 +Epoch [605/4000] Training [13/16] Loss: 0.01744 +Epoch [605/4000] Training [14/16] Loss: 0.03487 +Epoch [605/4000] Training [15/16] Loss: 0.01376 +Epoch [605/4000] Training [16/16] Loss: 0.07369 +Epoch [605/4000] Training metric {'Train/mean dice_metric': 0.9860191345214844, 'Train/mean miou_metric': 0.9736591577529907, 'Train/mean f1': 0.9832572340965271, 'Train/mean precision': 0.9775376915931702, 'Train/mean recall': 0.9890441298484802, 'Train/mean hd95_metric': 2.527646541595459} +Epoch [605/4000] Validation [1/4] Loss: 0.28789 focal_loss 0.18225 dice_loss 0.10564 +Epoch [605/4000] Validation [2/4] Loss: 0.41681 focal_loss 0.18963 dice_loss 0.22718 +Epoch [605/4000] Validation [3/4] Loss: 0.16253 focal_loss 0.08193 dice_loss 0.08060 +Epoch [605/4000] Validation [4/4] Loss: 0.24902 focal_loss 0.11890 dice_loss 0.13011 +Epoch [605/4000] Validation metric {'Val/mean dice_metric': 0.957593560218811, 'Val/mean miou_metric': 0.9337566494941711, 'Val/mean f1': 0.9616497755050659, 'Val/mean precision': 0.9594146013259888, 'Val/mean recall': 0.963895320892334, 'Val/mean hd95_metric': 8.491403579711914} +Cheakpoint... +Epoch [605/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.957593560218811, 'Val/mean miou_metric': 0.9337566494941711, 'Val/mean f1': 0.9616497755050659, 'Val/mean precision': 0.9594146013259888, 'Val/mean recall': 0.963895320892334, 'Val/mean hd95_metric': 8.491403579711914} +Epoch [606/4000] Training [1/16] Loss: 0.01676 +Epoch [606/4000] Training [2/16] Loss: 0.01610 +Epoch [606/4000] Training [3/16] Loss: 0.01781 +Epoch [606/4000] Training [4/16] Loss: 0.04313 +Epoch [606/4000] Training [5/16] Loss: 0.01851 +Epoch [606/4000] Training [6/16] Loss: 0.01732 +Epoch [606/4000] Training [7/16] Loss: 0.02901 +Epoch [606/4000] Training [8/16] Loss: 0.02255 +Epoch [606/4000] Training [9/16] Loss: 0.01839 +Epoch [606/4000] Training [10/16] Loss: 0.01862 +Epoch [606/4000] Training [11/16] Loss: 0.02128 +Epoch [606/4000] Training [12/16] Loss: 0.01831 +Epoch [606/4000] Training [13/16] Loss: 0.02008 +Epoch [606/4000] Training [14/16] Loss: 0.11357 +Epoch [606/4000] Training [15/16] Loss: 0.01800 +Epoch [606/4000] Training [16/16] Loss: 0.01547 +Epoch [606/4000] Training metric {'Train/mean dice_metric': 0.9814212322235107, 'Train/mean miou_metric': 0.966945469379425, 'Train/mean f1': 0.9809480905532837, 'Train/mean precision': 0.977456271648407, 'Train/mean recall': 0.9844649434089661, 'Train/mean hd95_metric': 3.8821489810943604} +Epoch [606/4000] Validation [1/4] Loss: 0.14955 focal_loss 0.08069 dice_loss 0.06885 +Epoch [606/4000] Validation [2/4] Loss: 0.48981 focal_loss 0.21202 dice_loss 0.27778 +Epoch [606/4000] Validation [3/4] Loss: 0.15408 focal_loss 0.07237 dice_loss 0.08171 +Epoch [606/4000] Validation [4/4] Loss: 0.33326 focal_loss 0.17321 dice_loss 0.16005 +Epoch [606/4000] Validation metric {'Val/mean dice_metric': 0.9535813331604004, 'Val/mean miou_metric': 0.9281870126724243, 'Val/mean f1': 0.9590453505516052, 'Val/mean precision': 0.9513270854949951, 'Val/mean recall': 0.9668900370597839, 'Val/mean hd95_metric': 9.852930068969727} +Cheakpoint... +Epoch [606/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9536], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9535813331604004, 'Val/mean miou_metric': 0.9281870126724243, 'Val/mean f1': 0.9590453505516052, 'Val/mean precision': 0.9513270854949951, 'Val/mean recall': 0.9668900370597839, 'Val/mean hd95_metric': 9.852930068969727} +Epoch [607/4000] Training [1/16] Loss: 0.01830 +Epoch [607/4000] Training [2/16] Loss: 0.01460 +Epoch [607/4000] Training [3/16] Loss: 0.01426 +Epoch [607/4000] Training [4/16] Loss: 0.01209 +Epoch [607/4000] Training [5/16] Loss: 0.01837 +Epoch [607/4000] Training [6/16] Loss: 0.02329 +Epoch [607/4000] Training [7/16] Loss: 0.01712 +Epoch [607/4000] Training [8/16] Loss: 0.01969 +Epoch [607/4000] Training [9/16] Loss: 0.01775 +Epoch [607/4000] Training [10/16] Loss: 0.02604 +Epoch [607/4000] Training [11/16] Loss: 0.14400 +Epoch [607/4000] Training [12/16] Loss: 0.02093 +Epoch [607/4000] Training [13/16] Loss: 0.01541 +Epoch [607/4000] Training [14/16] Loss: 0.01665 +Epoch [607/4000] Training [15/16] Loss: 0.01565 +Epoch [607/4000] Training [16/16] Loss: 0.01350 +Epoch [607/4000] Training metric {'Train/mean dice_metric': 0.9849282503128052, 'Train/mean miou_metric': 0.9711184501647949, 'Train/mean f1': 0.9809178113937378, 'Train/mean precision': 0.9768638014793396, 'Train/mean recall': 0.9850056171417236, 'Train/mean hd95_metric': 3.3735642433166504} +Epoch [607/4000] Validation [1/4] Loss: 0.35728 focal_loss 0.20915 dice_loss 0.14812 +Epoch [607/4000] Validation [2/4] Loss: 0.33928 focal_loss 0.14576 dice_loss 0.19351 +Epoch [607/4000] Validation [3/4] Loss: 0.21744 focal_loss 0.11454 dice_loss 0.10290 +Epoch [607/4000] Validation [4/4] Loss: 0.19878 focal_loss 0.07237 dice_loss 0.12641 +Epoch [607/4000] Validation metric {'Val/mean dice_metric': 0.9576287269592285, 'Val/mean miou_metric': 0.9312645792961121, 'Val/mean f1': 0.9571801424026489, 'Val/mean precision': 0.951359748840332, 'Val/mean recall': 0.9630720019340515, 'Val/mean hd95_metric': 9.457025527954102} +Cheakpoint... +Epoch [607/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576287269592285, 'Val/mean miou_metric': 0.9312645792961121, 'Val/mean f1': 0.9571801424026489, 'Val/mean precision': 0.951359748840332, 'Val/mean recall': 0.9630720019340515, 'Val/mean hd95_metric': 9.457025527954102} +Epoch [608/4000] Training [1/16] Loss: 0.02176 +Epoch [608/4000] Training [2/16] Loss: 0.02620 +Epoch [608/4000] Training [3/16] Loss: 0.01835 +Epoch [608/4000] Training [4/16] Loss: 0.01739 +Epoch [608/4000] Training [5/16] Loss: 0.02726 +Epoch [608/4000] Training [6/16] Loss: 0.01428 +Epoch [608/4000] Training [7/16] Loss: 0.02083 +Epoch [608/4000] Training [8/16] Loss: 0.02388 +Epoch [608/4000] Training [9/16] Loss: 0.02049 +Epoch [608/4000] Training [10/16] Loss: 0.01321 +Epoch [608/4000] Training [11/16] Loss: 0.02519 +Epoch [608/4000] Training [12/16] Loss: 0.01586 +Epoch [608/4000] Training [13/16] Loss: 0.01380 +Epoch [608/4000] Training [14/16] Loss: 0.01863 +Epoch [608/4000] Training [15/16] Loss: 0.01900 +Epoch [608/4000] Training [16/16] Loss: 0.01904 +Epoch [608/4000] Training metric {'Train/mean dice_metric': 0.9838807582855225, 'Train/mean miou_metric': 0.9696509838104248, 'Train/mean f1': 0.9826148748397827, 'Train/mean precision': 0.9784971475601196, 'Train/mean recall': 0.9867674112319946, 'Train/mean hd95_metric': 3.853151321411133} +Epoch [608/4000] Validation [1/4] Loss: 0.23034 focal_loss 0.14280 dice_loss 0.08754 +Epoch [608/4000] Validation [2/4] Loss: 0.30963 focal_loss 0.11336 dice_loss 0.19627 +Epoch [608/4000] Validation [3/4] Loss: 0.22794 focal_loss 0.14173 dice_loss 0.08621 +Epoch [608/4000] Validation [4/4] Loss: 0.32425 focal_loss 0.13013 dice_loss 0.19412 +Epoch [608/4000] Validation metric {'Val/mean dice_metric': 0.9584001302719116, 'Val/mean miou_metric': 0.9326364398002625, 'Val/mean f1': 0.9609028697013855, 'Val/mean precision': 0.953132152557373, 'Val/mean recall': 0.9688013792037964, 'Val/mean hd95_metric': 10.329679489135742} +Cheakpoint... +Epoch [608/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9584], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9584001302719116, 'Val/mean miou_metric': 0.9326364398002625, 'Val/mean f1': 0.9609028697013855, 'Val/mean precision': 0.953132152557373, 'Val/mean recall': 0.9688013792037964, 'Val/mean hd95_metric': 10.329679489135742} +Epoch [609/4000] Training [1/16] Loss: 0.01541 +Epoch [609/4000] Training [2/16] Loss: 0.01351 +Epoch [609/4000] Training [3/16] Loss: 0.01687 +Epoch [609/4000] Training [4/16] Loss: 0.01143 +Epoch [609/4000] Training [5/16] Loss: 0.01307 +Epoch [609/4000] Training [6/16] Loss: 0.01443 +Epoch [609/4000] Training [7/16] Loss: 0.01452 +Epoch [609/4000] Training [8/16] Loss: 0.04329 +Epoch [609/4000] Training [9/16] Loss: 0.01404 +Epoch [609/4000] Training [10/16] Loss: 0.01367 +Epoch [609/4000] Training [11/16] Loss: 0.01436 +Epoch [609/4000] Training [12/16] Loss: 0.01551 +Epoch [609/4000] Training [13/16] Loss: 0.01578 +Epoch [609/4000] Training [14/16] Loss: 0.01806 +Epoch [609/4000] Training [15/16] Loss: 0.01262 +Epoch [609/4000] Training [16/16] Loss: 0.02396 +Epoch [609/4000] Training metric {'Train/mean dice_metric': 0.9887128472328186, 'Train/mean miou_metric': 0.9775702953338623, 'Train/mean f1': 0.9856603741645813, 'Train/mean precision': 0.9814877510070801, 'Train/mean recall': 0.9898685812950134, 'Train/mean hd95_metric': 2.03006911277771} +Epoch [609/4000] Validation [1/4] Loss: 0.13571 focal_loss 0.07818 dice_loss 0.05752 +Epoch [609/4000] Validation [2/4] Loss: 0.24486 focal_loss 0.10437 dice_loss 0.14049 +Epoch [609/4000] Validation [3/4] Loss: 0.20813 focal_loss 0.11252 dice_loss 0.09561 +Epoch [609/4000] Validation [4/4] Loss: 0.33509 focal_loss 0.15573 dice_loss 0.17936 +Epoch [609/4000] Validation metric {'Val/mean dice_metric': 0.961264431476593, 'Val/mean miou_metric': 0.9384815096855164, 'Val/mean f1': 0.9643141031265259, 'Val/mean precision': 0.9583413004875183, 'Val/mean recall': 0.9703617095947266, 'Val/mean hd95_metric': 8.394508361816406} +Cheakpoint... +Epoch [609/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961264431476593, 'Val/mean miou_metric': 0.9384815096855164, 'Val/mean f1': 0.9643141031265259, 'Val/mean precision': 0.9583413004875183, 'Val/mean recall': 0.9703617095947266, 'Val/mean hd95_metric': 8.394508361816406} +Epoch [610/4000] Training [1/16] Loss: 0.01525 +Epoch [610/4000] Training [2/16] Loss: 0.01903 +Epoch [610/4000] Training [3/16] Loss: 0.02854 +Epoch [610/4000] Training [4/16] Loss: 0.01245 +Epoch [610/4000] Training [5/16] Loss: 0.01836 +Epoch [610/4000] Training [6/16] Loss: 0.01462 +Epoch [610/4000] Training [7/16] Loss: 0.01238 +Epoch [610/4000] Training [8/16] Loss: 0.01584 +Epoch [610/4000] Training [9/16] Loss: 0.01552 +Epoch [610/4000] Training [10/16] Loss: 0.01389 +Epoch [610/4000] Training [11/16] Loss: 0.01388 +Epoch [610/4000] Training [12/16] Loss: 0.01689 +Epoch [610/4000] Training [13/16] Loss: 0.02035 +Epoch [610/4000] Training [14/16] Loss: 0.01586 +Epoch [610/4000] Training [15/16] Loss: 0.01586 +Epoch [610/4000] Training [16/16] Loss: 0.01717 +Epoch [610/4000] Training metric {'Train/mean dice_metric': 0.988722562789917, 'Train/mean miou_metric': 0.977582573890686, 'Train/mean f1': 0.9853225946426392, 'Train/mean precision': 0.9806615710258484, 'Train/mean recall': 0.9900281429290771, 'Train/mean hd95_metric': 1.9011849164962769} +Epoch [610/4000] Validation [1/4] Loss: 0.35235 focal_loss 0.22816 dice_loss 0.12419 +Epoch [610/4000] Validation [2/4] Loss: 0.16583 focal_loss 0.06879 dice_loss 0.09705 +Epoch [610/4000] Validation [3/4] Loss: 0.26646 focal_loss 0.14308 dice_loss 0.12338 +Epoch [610/4000] Validation [4/4] Loss: 0.32407 focal_loss 0.17046 dice_loss 0.15361 +Epoch [610/4000] Validation metric {'Val/mean dice_metric': 0.9627429842948914, 'Val/mean miou_metric': 0.9402424097061157, 'Val/mean f1': 0.9639642834663391, 'Val/mean precision': 0.96297287940979, 'Val/mean recall': 0.9649577736854553, 'Val/mean hd95_metric': 6.993508815765381} +Cheakpoint... +Epoch [610/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9627], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9627429842948914, 'Val/mean miou_metric': 0.9402424097061157, 'Val/mean f1': 0.9639642834663391, 'Val/mean precision': 0.96297287940979, 'Val/mean recall': 0.9649577736854553, 'Val/mean hd95_metric': 6.993508815765381} +Epoch [611/4000] Training [1/16] Loss: 0.01615 +Epoch [611/4000] Training [2/16] Loss: 0.02068 +Epoch [611/4000] Training [3/16] Loss: 0.01413 +Epoch [611/4000] Training [4/16] Loss: 0.01632 +Epoch [611/4000] Training [5/16] Loss: 0.01699 +Epoch [611/4000] Training [6/16] Loss: 0.01442 +Epoch [611/4000] Training [7/16] Loss: 0.01458 +Epoch [611/4000] Training [8/16] Loss: 0.01557 +Epoch [611/4000] Training [9/16] Loss: 0.01748 +Epoch [611/4000] Training [10/16] Loss: 0.01151 +Epoch [611/4000] Training [11/16] Loss: 0.01376 +Epoch [611/4000] Training [12/16] Loss: 0.01757 +Epoch [611/4000] Training [13/16] Loss: 0.01279 +Epoch [611/4000] Training [14/16] Loss: 0.01531 +Epoch [611/4000] Training [15/16] Loss: 0.01662 +Epoch [611/4000] Training [16/16] Loss: 0.01907 +Epoch [611/4000] Training metric {'Train/mean dice_metric': 0.9893988370895386, 'Train/mean miou_metric': 0.9788342118263245, 'Train/mean f1': 0.9862684607505798, 'Train/mean precision': 0.9814311861991882, 'Train/mean recall': 0.9911535978317261, 'Train/mean hd95_metric': 1.7163876295089722} +Epoch [611/4000] Validation [1/4] Loss: 0.48776 focal_loss 0.33955 dice_loss 0.14821 +Epoch [611/4000] Validation [2/4] Loss: 0.20770 focal_loss 0.08662 dice_loss 0.12108 +Epoch [611/4000] Validation [3/4] Loss: 0.16048 focal_loss 0.07306 dice_loss 0.08742 +Epoch [611/4000] Validation [4/4] Loss: 0.18714 focal_loss 0.08256 dice_loss 0.10458 +Epoch [611/4000] Validation metric {'Val/mean dice_metric': 0.9621240496635437, 'Val/mean miou_metric': 0.9409021139144897, 'Val/mean f1': 0.9641590714454651, 'Val/mean precision': 0.9639847278594971, 'Val/mean recall': 0.9643332958221436, 'Val/mean hd95_metric': 6.482792854309082} +Cheakpoint... +Epoch [611/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9621], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9621240496635437, 'Val/mean miou_metric': 0.9409021139144897, 'Val/mean f1': 0.9641590714454651, 'Val/mean precision': 0.9639847278594971, 'Val/mean recall': 0.9643332958221436, 'Val/mean hd95_metric': 6.482792854309082} +Epoch [612/4000] Training [1/16] Loss: 0.01811 +Epoch [612/4000] Training [2/16] Loss: 0.01462 +Epoch [612/4000] Training [3/16] Loss: 0.01850 +Epoch [612/4000] Training [4/16] Loss: 0.02774 +Epoch [612/4000] Training [5/16] Loss: 0.01663 +Epoch [612/4000] Training [6/16] Loss: 0.01689 +Epoch [612/4000] Training [7/16] Loss: 0.02093 +Epoch [612/4000] Training [8/16] Loss: 0.01369 +Epoch [612/4000] Training [9/16] Loss: 0.02902 +Epoch [612/4000] Training [10/16] Loss: 0.01363 +Epoch [612/4000] Training [11/16] Loss: 0.01583 +Epoch [612/4000] Training [12/16] Loss: 0.01584 +Epoch [612/4000] Training [13/16] Loss: 0.01662 +Epoch [612/4000] Training [14/16] Loss: 0.01568 +Epoch [612/4000] Training [15/16] Loss: 0.01390 +Epoch [612/4000] Training [16/16] Loss: 0.01838 +Epoch [612/4000] Training metric {'Train/mean dice_metric': 0.9888280630111694, 'Train/mean miou_metric': 0.9777601957321167, 'Train/mean f1': 0.9853087067604065, 'Train/mean precision': 0.981168806552887, 'Train/mean recall': 0.989483654499054, 'Train/mean hd95_metric': 1.8829829692840576} +Epoch [612/4000] Validation [1/4] Loss: 0.21674 focal_loss 0.13919 dice_loss 0.07754 +Epoch [612/4000] Validation [2/4] Loss: 0.34483 focal_loss 0.14524 dice_loss 0.19959 +Epoch [612/4000] Validation [3/4] Loss: 0.10884 focal_loss 0.05179 dice_loss 0.05705 +Epoch [612/4000] Validation [4/4] Loss: 0.26539 focal_loss 0.13527 dice_loss 0.13012 +Epoch [612/4000] Validation metric {'Val/mean dice_metric': 0.9656244516372681, 'Val/mean miou_metric': 0.9432888031005859, 'Val/mean f1': 0.9654236435890198, 'Val/mean precision': 0.9586651921272278, 'Val/mean recall': 0.9722778797149658, 'Val/mean hd95_metric': 6.650533199310303} +Cheakpoint... +Epoch [612/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656244516372681, 'Val/mean miou_metric': 0.9432888031005859, 'Val/mean f1': 0.9654236435890198, 'Val/mean precision': 0.9586651921272278, 'Val/mean recall': 0.9722778797149658, 'Val/mean hd95_metric': 6.650533199310303} +Epoch [613/4000] Training [1/16] Loss: 0.01293 +Epoch [613/4000] Training [2/16] Loss: 0.01085 +Epoch [613/4000] Training [3/16] Loss: 0.02105 +Epoch [613/4000] Training [4/16] Loss: 0.01280 +Epoch [613/4000] Training [5/16] Loss: 0.01617 +Epoch [613/4000] Training [6/16] Loss: 0.02415 +Epoch [613/4000] Training [7/16] Loss: 0.01230 +Epoch [613/4000] Training [8/16] Loss: 0.01588 +Epoch [613/4000] Training [9/16] Loss: 0.01707 +Epoch [613/4000] Training [10/16] Loss: 0.01299 +Epoch [613/4000] Training [11/16] Loss: 0.01953 +Epoch [613/4000] Training [12/16] Loss: 0.01124 +Epoch [613/4000] Training [13/16] Loss: 0.01671 +Epoch [613/4000] Training [14/16] Loss: 0.01334 +Epoch [613/4000] Training [15/16] Loss: 0.01519 +Epoch [613/4000] Training [16/16] Loss: 0.01443 +Epoch [613/4000] Training metric {'Train/mean dice_metric': 0.9898722171783447, 'Train/mean miou_metric': 0.9798101782798767, 'Train/mean f1': 0.9869111180305481, 'Train/mean precision': 0.9824690818786621, 'Train/mean recall': 0.9913935661315918, 'Train/mean hd95_metric': 1.3948636054992676} +Epoch [613/4000] Validation [1/4] Loss: 0.21435 focal_loss 0.13404 dice_loss 0.08032 +Epoch [613/4000] Validation [2/4] Loss: 0.27716 focal_loss 0.14266 dice_loss 0.13450 +Epoch [613/4000] Validation [3/4] Loss: 0.11691 focal_loss 0.05817 dice_loss 0.05874 +Epoch [613/4000] Validation [4/4] Loss: 0.24795 focal_loss 0.14232 dice_loss 0.10563 +Epoch [613/4000] Validation metric {'Val/mean dice_metric': 0.9647830128669739, 'Val/mean miou_metric': 0.9433013796806335, 'Val/mean f1': 0.9669399261474609, 'Val/mean precision': 0.9631697535514832, 'Val/mean recall': 0.9707397222518921, 'Val/mean hd95_metric': 7.475602626800537} +Cheakpoint... +Epoch [613/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647830128669739, 'Val/mean miou_metric': 0.9433013796806335, 'Val/mean f1': 0.9669399261474609, 'Val/mean precision': 0.9631697535514832, 'Val/mean recall': 0.9707397222518921, 'Val/mean hd95_metric': 7.475602626800537} +Epoch [614/4000] Training [1/16] Loss: 0.01820 +Epoch [614/4000] Training [2/16] Loss: 0.01316 +Epoch [614/4000] Training [3/16] Loss: 0.01155 +Epoch [614/4000] Training [4/16] Loss: 0.01447 +Epoch [614/4000] Training [5/16] Loss: 0.01643 +Epoch [614/4000] Training [6/16] Loss: 0.01381 +Epoch [614/4000] Training [7/16] Loss: 0.01227 +Epoch [614/4000] Training [8/16] Loss: 0.01589 +Epoch [614/4000] Training [9/16] Loss: 0.01418 +Epoch [614/4000] Training [10/16] Loss: 0.02750 +Epoch [614/4000] Training [11/16] Loss: 0.01370 +Epoch [614/4000] Training [12/16] Loss: 0.01015 +Epoch [614/4000] Training [13/16] Loss: 0.01426 +Epoch [614/4000] Training [14/16] Loss: 0.01334 +Epoch [614/4000] Training [15/16] Loss: 0.01324 +Epoch [614/4000] Training [16/16] Loss: 0.02954 +Epoch [614/4000] Training metric {'Train/mean dice_metric': 0.9894817471504211, 'Train/mean miou_metric': 0.9790578484535217, 'Train/mean f1': 0.9862905144691467, 'Train/mean precision': 0.9819117784500122, 'Train/mean recall': 0.9907085299491882, 'Train/mean hd95_metric': 1.5121108293533325} +Epoch [614/4000] Validation [1/4] Loss: 0.58273 focal_loss 0.45979 dice_loss 0.12295 +Epoch [614/4000] Validation [2/4] Loss: 0.36070 focal_loss 0.15527 dice_loss 0.20543 +Epoch [614/4000] Validation [3/4] Loss: 0.11980 focal_loss 0.06115 dice_loss 0.05865 +Epoch [614/4000] Validation [4/4] Loss: 0.20279 focal_loss 0.10067 dice_loss 0.10213 +Epoch [614/4000] Validation metric {'Val/mean dice_metric': 0.9654790759086609, 'Val/mean miou_metric': 0.9433428049087524, 'Val/mean f1': 0.9650066494941711, 'Val/mean precision': 0.9624419212341309, 'Val/mean recall': 0.9675851464271545, 'Val/mean hd95_metric': 6.520371913909912} +Cheakpoint... +Epoch [614/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654790759086609, 'Val/mean miou_metric': 0.9433428049087524, 'Val/mean f1': 0.9650066494941711, 'Val/mean precision': 0.9624419212341309, 'Val/mean recall': 0.9675851464271545, 'Val/mean hd95_metric': 6.520371913909912} +Epoch [615/4000] Training [1/16] Loss: 0.01066 +Epoch [615/4000] Training [2/16] Loss: 0.01718 +Epoch [615/4000] Training [3/16] Loss: 0.01195 +Epoch [615/4000] Training [4/16] Loss: 0.01094 +Epoch [615/4000] Training [5/16] Loss: 0.01492 +Epoch [615/4000] Training [6/16] Loss: 0.01011 +Epoch [615/4000] Training [7/16] Loss: 0.01362 +Epoch [615/4000] Training [8/16] Loss: 0.01207 +Epoch [615/4000] Training [9/16] Loss: 0.02156 +Epoch [615/4000] Training [10/16] Loss: 0.01357 +Epoch [615/4000] Training [11/16] Loss: 0.02828 +Epoch [615/4000] Training [12/16] Loss: 0.01107 +Epoch [615/4000] Training [13/16] Loss: 0.02427 +Epoch [615/4000] Training [14/16] Loss: 0.01287 +Epoch [615/4000] Training [15/16] Loss: 0.01578 +Epoch [615/4000] Training [16/16] Loss: 0.01507 +Epoch [615/4000] Training metric {'Train/mean dice_metric': 0.989787757396698, 'Train/mean miou_metric': 0.9798157215118408, 'Train/mean f1': 0.9870586395263672, 'Train/mean precision': 0.9824162125587463, 'Train/mean recall': 0.9917450547218323, 'Train/mean hd95_metric': 1.3425812721252441} +Epoch [615/4000] Validation [1/4] Loss: 0.43264 focal_loss 0.32103 dice_loss 0.11162 +Epoch [615/4000] Validation [2/4] Loss: 0.17185 focal_loss 0.07325 dice_loss 0.09859 +Epoch [615/4000] Validation [3/4] Loss: 0.18246 focal_loss 0.10180 dice_loss 0.08065 +Epoch [615/4000] Validation [4/4] Loss: 0.23888 focal_loss 0.13194 dice_loss 0.10693 +Epoch [615/4000] Validation metric {'Val/mean dice_metric': 0.9638764262199402, 'Val/mean miou_metric': 0.9428669810295105, 'Val/mean f1': 0.9654325246810913, 'Val/mean precision': 0.9598745107650757, 'Val/mean recall': 0.9710553288459778, 'Val/mean hd95_metric': 6.484403133392334} +Cheakpoint... +Epoch [615/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9638764262199402, 'Val/mean miou_metric': 0.9428669810295105, 'Val/mean f1': 0.9654325246810913, 'Val/mean precision': 0.9598745107650757, 'Val/mean recall': 0.9710553288459778, 'Val/mean hd95_metric': 6.484403133392334} +Epoch [616/4000] Training [1/16] Loss: 0.01253 +Epoch [616/4000] Training [2/16] Loss: 0.01826 +Epoch [616/4000] Training [3/16] Loss: 0.01754 +Epoch [616/4000] Training [4/16] Loss: 0.01487 +Epoch [616/4000] Training [5/16] Loss: 0.01724 +Epoch [616/4000] Training [6/16] Loss: 0.01391 +Epoch [616/4000] Training [7/16] Loss: 0.01499 +Epoch [616/4000] Training [8/16] Loss: 0.01634 +Epoch [616/4000] Training [9/16] Loss: 0.02260 +Epoch [616/4000] Training [10/16] Loss: 0.01295 +Epoch [616/4000] Training [11/16] Loss: 0.01567 +Epoch [616/4000] Training [12/16] Loss: 0.01395 +Epoch [616/4000] Training [13/16] Loss: 0.02214 +Epoch [616/4000] Training [14/16] Loss: 0.01737 +Epoch [616/4000] Training [15/16] Loss: 0.01348 +Epoch [616/4000] Training [16/16] Loss: 0.01383 +Epoch [616/4000] Training metric {'Train/mean dice_metric': 0.9891258478164673, 'Train/mean miou_metric': 0.9784318804740906, 'Train/mean f1': 0.986486554145813, 'Train/mean precision': 0.9816502332687378, 'Train/mean recall': 0.9913707375526428, 'Train/mean hd95_metric': 1.5038046836853027} +Epoch [616/4000] Validation [1/4] Loss: 0.40363 focal_loss 0.29666 dice_loss 0.10697 +Epoch [616/4000] Validation [2/4] Loss: 0.40879 focal_loss 0.18270 dice_loss 0.22609 +Epoch [616/4000] Validation [3/4] Loss: 0.11131 focal_loss 0.05695 dice_loss 0.05436 +Epoch [616/4000] Validation [4/4] Loss: 0.21665 focal_loss 0.09731 dice_loss 0.11934 +Epoch [616/4000] Validation metric {'Val/mean dice_metric': 0.9645960927009583, 'Val/mean miou_metric': 0.9427553415298462, 'Val/mean f1': 0.9663466215133667, 'Val/mean precision': 0.9631549715995789, 'Val/mean recall': 0.969559371471405, 'Val/mean hd95_metric': 6.5440993309021} +Cheakpoint... +Epoch [616/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9646], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645960927009583, 'Val/mean miou_metric': 0.9427553415298462, 'Val/mean f1': 0.9663466215133667, 'Val/mean precision': 0.9631549715995789, 'Val/mean recall': 0.969559371471405, 'Val/mean hd95_metric': 6.5440993309021} +Epoch [617/4000] Training [1/16] Loss: 0.03032 +Epoch [617/4000] Training [2/16] Loss: 0.01120 +Epoch [617/4000] Training [3/16] Loss: 0.01481 +Epoch [617/4000] Training [4/16] Loss: 0.01155 +Epoch [617/4000] Training [5/16] Loss: 0.01075 +Epoch [617/4000] Training [6/16] Loss: 0.01381 +Epoch [617/4000] Training [7/16] Loss: 0.01316 +Epoch [617/4000] Training [8/16] Loss: 0.01659 +Epoch [617/4000] Training [9/16] Loss: 0.01723 +Epoch [617/4000] Training [10/16] Loss: 0.01567 +Epoch [617/4000] Training [11/16] Loss: 0.01287 +Epoch [617/4000] Training [12/16] Loss: 0.01244 +Epoch [617/4000] Training [13/16] Loss: 0.01242 +Epoch [617/4000] Training [14/16] Loss: 0.01265 +Epoch [617/4000] Training [15/16] Loss: 0.01288 +Epoch [617/4000] Training [16/16] Loss: 0.03755 +Epoch [617/4000] Training metric {'Train/mean dice_metric': 0.9891927242279053, 'Train/mean miou_metric': 0.9785866737365723, 'Train/mean f1': 0.9863296151161194, 'Train/mean precision': 0.9817681312561035, 'Train/mean recall': 0.9909337759017944, 'Train/mean hd95_metric': 1.4479963779449463} +Epoch [617/4000] Validation [1/4] Loss: 0.39789 focal_loss 0.28717 dice_loss 0.11072 +Epoch [617/4000] Validation [2/4] Loss: 0.23753 focal_loss 0.10259 dice_loss 0.13494 +Epoch [617/4000] Validation [3/4] Loss: 0.13105 focal_loss 0.06384 dice_loss 0.06721 +Epoch [617/4000] Validation [4/4] Loss: 0.17105 focal_loss 0.07191 dice_loss 0.09914 +Epoch [617/4000] Validation metric {'Val/mean dice_metric': 0.9669540524482727, 'Val/mean miou_metric': 0.9450909495353699, 'Val/mean f1': 0.9676004648208618, 'Val/mean precision': 0.9631454944610596, 'Val/mean recall': 0.9720969796180725, 'Val/mean hd95_metric': 6.293105125427246} +Cheakpoint... +Epoch [617/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669540524482727, 'Val/mean miou_metric': 0.9450909495353699, 'Val/mean f1': 0.9676004648208618, 'Val/mean precision': 0.9631454944610596, 'Val/mean recall': 0.9720969796180725, 'Val/mean hd95_metric': 6.293105125427246} +Epoch [618/4000] Training [1/16] Loss: 0.01307 +Epoch [618/4000] Training [2/16] Loss: 0.01228 +Epoch [618/4000] Training [3/16] Loss: 0.01320 +Epoch [618/4000] Training [4/16] Loss: 0.02388 +Epoch [618/4000] Training [5/16] Loss: 0.01581 +Epoch [618/4000] Training [6/16] Loss: 0.01227 +Epoch [618/4000] Training [7/16] Loss: 0.01353 +Epoch [618/4000] Training [8/16] Loss: 0.03419 +Epoch [618/4000] Training [9/16] Loss: 0.01311 +Epoch [618/4000] Training [10/16] Loss: 0.01039 +Epoch [618/4000] Training [11/16] Loss: 0.02637 +Epoch [618/4000] Training [12/16] Loss: 0.01211 +Epoch [618/4000] Training [13/16] Loss: 0.01169 +Epoch [618/4000] Training [14/16] Loss: 0.01496 +Epoch [618/4000] Training [15/16] Loss: 0.01344 +Epoch [618/4000] Training [16/16] Loss: 0.01935 +Epoch [618/4000] Training metric {'Train/mean dice_metric': 0.9901566505432129, 'Train/mean miou_metric': 0.9803220629692078, 'Train/mean f1': 0.9858925938606262, 'Train/mean precision': 0.9799888730049133, 'Train/mean recall': 0.9918678402900696, 'Train/mean hd95_metric': 1.3329464197158813} +Epoch [618/4000] Validation [1/4] Loss: 0.36367 focal_loss 0.26144 dice_loss 0.10222 +Epoch [618/4000] Validation [2/4] Loss: 0.18818 focal_loss 0.07655 dice_loss 0.11163 +Epoch [618/4000] Validation [3/4] Loss: 0.12322 focal_loss 0.05891 dice_loss 0.06431 +Epoch [618/4000] Validation [4/4] Loss: 0.23970 focal_loss 0.11400 dice_loss 0.12570 +Epoch [618/4000] Validation metric {'Val/mean dice_metric': 0.968031108379364, 'Val/mean miou_metric': 0.9467014074325562, 'Val/mean f1': 0.9678319096565247, 'Val/mean precision': 0.9619148373603821, 'Val/mean recall': 0.9738221168518066, 'Val/mean hd95_metric': 6.056490421295166} +Cheakpoint... +Epoch [618/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968031108379364, 'Val/mean miou_metric': 0.9467014074325562, 'Val/mean f1': 0.9678319096565247, 'Val/mean precision': 0.9619148373603821, 'Val/mean recall': 0.9738221168518066, 'Val/mean hd95_metric': 6.056490421295166} +Epoch [619/4000] Training [1/16] Loss: 0.01073 +Epoch [619/4000] Training [2/16] Loss: 0.01358 +Epoch [619/4000] Training [3/16] Loss: 0.01700 +Epoch [619/4000] Training [4/16] Loss: 0.01680 +Epoch [619/4000] Training [5/16] Loss: 0.01374 +Epoch [619/4000] Training [6/16] Loss: 0.01478 +Epoch [619/4000] Training [7/16] Loss: 0.01064 +Epoch [619/4000] Training [8/16] Loss: 0.01324 +Epoch [619/4000] Training [9/16] Loss: 0.02428 +Epoch [619/4000] Training [10/16] Loss: 0.01377 +Epoch [619/4000] Training [11/16] Loss: 0.01110 +Epoch [619/4000] Training [12/16] Loss: 0.01366 +Epoch [619/4000] Training [13/16] Loss: 0.01207 +Epoch [619/4000] Training [14/16] Loss: 0.01404 +Epoch [619/4000] Training [15/16] Loss: 0.01709 +Epoch [619/4000] Training [16/16] Loss: 0.01317 +Epoch [619/4000] Training metric {'Train/mean dice_metric': 0.9898711442947388, 'Train/mean miou_metric': 0.9797829985618591, 'Train/mean f1': 0.9870532155036926, 'Train/mean precision': 0.9825435280799866, 'Train/mean recall': 0.9916045665740967, 'Train/mean hd95_metric': 1.3075916767120361} +Epoch [619/4000] Validation [1/4] Loss: 0.22920 focal_loss 0.14870 dice_loss 0.08050 +Epoch [619/4000] Validation [2/4] Loss: 0.19631 focal_loss 0.08567 dice_loss 0.11064 +Epoch [619/4000] Validation [3/4] Loss: 0.16143 focal_loss 0.07584 dice_loss 0.08559 +Epoch [619/4000] Validation [4/4] Loss: 0.30234 focal_loss 0.15203 dice_loss 0.15030 +Epoch [619/4000] Validation metric {'Val/mean dice_metric': 0.9668232202529907, 'Val/mean miou_metric': 0.9451925158500671, 'Val/mean f1': 0.9684135913848877, 'Val/mean precision': 0.961407482624054, 'Val/mean recall': 0.9755225777626038, 'Val/mean hd95_metric': 6.412428855895996} +Cheakpoint... +Epoch [619/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668232202529907, 'Val/mean miou_metric': 0.9451925158500671, 'Val/mean f1': 0.9684135913848877, 'Val/mean precision': 0.961407482624054, 'Val/mean recall': 0.9755225777626038, 'Val/mean hd95_metric': 6.412428855895996} +Epoch [620/4000] Training [1/16] Loss: 0.01412 +Epoch [620/4000] Training [2/16] Loss: 0.01483 +Epoch [620/4000] Training [3/16] Loss: 0.01481 +Epoch [620/4000] Training [4/16] Loss: 0.01462 +Epoch [620/4000] Training [5/16] Loss: 0.01047 +Epoch [620/4000] Training [6/16] Loss: 0.01233 +Epoch [620/4000] Training [7/16] Loss: 0.01401 +Epoch [620/4000] Training [8/16] Loss: 0.01454 +Epoch [620/4000] Training [9/16] Loss: 0.01056 +Epoch [620/4000] Training [10/16] Loss: 0.02377 +Epoch [620/4000] Training [11/16] Loss: 0.01661 +Epoch [620/4000] Training [12/16] Loss: 0.01614 +Epoch [620/4000] Training [13/16] Loss: 0.01327 +Epoch [620/4000] Training [14/16] Loss: 0.01374 +Epoch [620/4000] Training [15/16] Loss: 0.01082 +Epoch [620/4000] Training [16/16] Loss: 0.01275 +Epoch [620/4000] Training metric {'Train/mean dice_metric': 0.9897767305374146, 'Train/mean miou_metric': 0.9795852899551392, 'Train/mean f1': 0.987001359462738, 'Train/mean precision': 0.9825747609138489, 'Train/mean recall': 0.9914680123329163, 'Train/mean hd95_metric': 1.3810875415802002} +Epoch [620/4000] Validation [1/4] Loss: 0.42627 focal_loss 0.31437 dice_loss 0.11190 +Epoch [620/4000] Validation [2/4] Loss: 0.20521 focal_loss 0.09249 dice_loss 0.11271 +Epoch [620/4000] Validation [3/4] Loss: 0.24597 focal_loss 0.14685 dice_loss 0.09913 +Epoch [620/4000] Validation [4/4] Loss: 0.21357 focal_loss 0.10816 dice_loss 0.10540 +Epoch [620/4000] Validation metric {'Val/mean dice_metric': 0.9662522077560425, 'Val/mean miou_metric': 0.9443586468696594, 'Val/mean f1': 0.966621994972229, 'Val/mean precision': 0.9618138670921326, 'Val/mean recall': 0.9714784026145935, 'Val/mean hd95_metric': 6.464454650878906} +Cheakpoint... +Epoch [620/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662522077560425, 'Val/mean miou_metric': 0.9443586468696594, 'Val/mean f1': 0.966621994972229, 'Val/mean precision': 0.9618138670921326, 'Val/mean recall': 0.9714784026145935, 'Val/mean hd95_metric': 6.464454650878906} +Epoch [621/4000] Training [1/16] Loss: 0.04081 +Epoch [621/4000] Training [2/16] Loss: 0.01290 +Epoch [621/4000] Training [3/16] Loss: 0.01396 +Epoch [621/4000] Training [4/16] Loss: 0.02256 +Epoch [621/4000] Training [5/16] Loss: 0.01385 +Epoch [621/4000] Training [6/16] Loss: 0.01325 +Epoch [621/4000] Training [7/16] Loss: 0.01501 +Epoch [621/4000] Training [8/16] Loss: 0.01401 +Epoch [621/4000] Training [9/16] Loss: 0.01229 +Epoch [621/4000] Training [10/16] Loss: 0.01255 +Epoch [621/4000] Training [11/16] Loss: 0.01585 +Epoch [621/4000] Training [12/16] Loss: 0.01560 +Epoch [621/4000] Training [13/16] Loss: 0.01872 +Epoch [621/4000] Training [14/16] Loss: 0.01223 +Epoch [621/4000] Training [15/16] Loss: 0.04187 +Epoch [621/4000] Training [16/16] Loss: 0.01759 +Epoch [621/4000] Training metric {'Train/mean dice_metric': 0.9873560070991516, 'Train/mean miou_metric': 0.9756157398223877, 'Train/mean f1': 0.9858937859535217, 'Train/mean precision': 0.9809836149215698, 'Train/mean recall': 0.9908533692359924, 'Train/mean hd95_metric': 1.9219708442687988} +Epoch [621/4000] Validation [1/4] Loss: 0.43709 focal_loss 0.31272 dice_loss 0.12436 +Epoch [621/4000] Validation [2/4] Loss: 0.18460 focal_loss 0.08051 dice_loss 0.10409 +Epoch [621/4000] Validation [3/4] Loss: 0.12412 focal_loss 0.06315 dice_loss 0.06097 +Epoch [621/4000] Validation [4/4] Loss: 0.29279 focal_loss 0.15764 dice_loss 0.13514 +Epoch [621/4000] Validation metric {'Val/mean dice_metric': 0.9634708166122437, 'Val/mean miou_metric': 0.9403076171875, 'Val/mean f1': 0.9648142457008362, 'Val/mean precision': 0.9589020013809204, 'Val/mean recall': 0.97079998254776, 'Val/mean hd95_metric': 7.025057792663574} +Cheakpoint... +Epoch [621/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9635], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9634708166122437, 'Val/mean miou_metric': 0.9403076171875, 'Val/mean f1': 0.9648142457008362, 'Val/mean precision': 0.9589020013809204, 'Val/mean recall': 0.97079998254776, 'Val/mean hd95_metric': 7.025057792663574} +Epoch [622/4000] Training [1/16] Loss: 0.01253 +Epoch [622/4000] Training [2/16] Loss: 0.01800 +Epoch [622/4000] Training [3/16] Loss: 0.01287 +Epoch [622/4000] Training [4/16] Loss: 0.01420 +Epoch [622/4000] Training [5/16] Loss: 0.01564 +Epoch [622/4000] Training [6/16] Loss: 0.01337 +Epoch [622/4000] Training [7/16] Loss: 0.01709 +Epoch [622/4000] Training [8/16] Loss: 0.01656 +Epoch [622/4000] Training [9/16] Loss: 0.01707 +Epoch [622/4000] Training [10/16] Loss: 0.01839 +Epoch [622/4000] Training [11/16] Loss: 0.01684 +Epoch [622/4000] Training [12/16] Loss: 0.01468 +Epoch [622/4000] Training [13/16] Loss: 0.01378 +Epoch [622/4000] Training [14/16] Loss: 0.01276 +Epoch [622/4000] Training [15/16] Loss: 0.01440 +Epoch [622/4000] Training [16/16] Loss: 0.01358 +Epoch [622/4000] Training metric {'Train/mean dice_metric': 0.9890438318252563, 'Train/mean miou_metric': 0.9782000780105591, 'Train/mean f1': 0.9864618182182312, 'Train/mean precision': 0.9824300408363342, 'Train/mean recall': 0.9905267357826233, 'Train/mean hd95_metric': 1.3889611959457397} +Epoch [622/4000] Validation [1/4] Loss: 0.27511 focal_loss 0.17683 dice_loss 0.09828 +Epoch [622/4000] Validation [2/4] Loss: 0.16647 focal_loss 0.06801 dice_loss 0.09846 +Epoch [622/4000] Validation [3/4] Loss: 0.12277 focal_loss 0.06023 dice_loss 0.06254 +Epoch [622/4000] Validation [4/4] Loss: 0.27234 focal_loss 0.13739 dice_loss 0.13496 +Epoch [622/4000] Validation metric {'Val/mean dice_metric': 0.9652406573295593, 'Val/mean miou_metric': 0.9437718391418457, 'Val/mean f1': 0.967543363571167, 'Val/mean precision': 0.9616312980651855, 'Val/mean recall': 0.9735284447669983, 'Val/mean hd95_metric': 7.007241725921631} +Cheakpoint... +Epoch [622/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652406573295593, 'Val/mean miou_metric': 0.9437718391418457, 'Val/mean f1': 0.967543363571167, 'Val/mean precision': 0.9616312980651855, 'Val/mean recall': 0.9735284447669983, 'Val/mean hd95_metric': 7.007241725921631} +Epoch [623/4000] Training [1/16] Loss: 0.01440 +Epoch [623/4000] Training [2/16] Loss: 0.03667 +Epoch [623/4000] Training [3/16] Loss: 0.01706 +Epoch [623/4000] Training [4/16] Loss: 0.01140 +Epoch [623/4000] Training [5/16] Loss: 0.01278 +Epoch [623/4000] Training [6/16] Loss: 0.00984 +Epoch [623/4000] Training [7/16] Loss: 0.02023 +Epoch [623/4000] Training [8/16] Loss: 0.01489 +Epoch [623/4000] Training [9/16] Loss: 0.01083 +Epoch [623/4000] Training [10/16] Loss: 0.01530 +Epoch [623/4000] Training [11/16] Loss: 0.01783 +Epoch [623/4000] Training [12/16] Loss: 0.01220 +Epoch [623/4000] Training [13/16] Loss: 0.01262 +Epoch [623/4000] Training [14/16] Loss: 0.01474 +Epoch [623/4000] Training [15/16] Loss: 0.02030 +Epoch [623/4000] Training [16/16] Loss: 0.01181 +Epoch [623/4000] Training metric {'Train/mean dice_metric': 0.989730715751648, 'Train/mean miou_metric': 0.9795015454292297, 'Train/mean f1': 0.986630916595459, 'Train/mean precision': 0.9822750091552734, 'Train/mean recall': 0.9910256266593933, 'Train/mean hd95_metric': 1.3648326396942139} +Epoch [623/4000] Validation [1/4] Loss: 0.26770 focal_loss 0.17609 dice_loss 0.09161 +Epoch [623/4000] Validation [2/4] Loss: 0.36821 focal_loss 0.19923 dice_loss 0.16897 +Epoch [623/4000] Validation [3/4] Loss: 0.13984 focal_loss 0.06632 dice_loss 0.07352 +Epoch [623/4000] Validation [4/4] Loss: 0.28807 focal_loss 0.16213 dice_loss 0.12594 +Epoch [623/4000] Validation metric {'Val/mean dice_metric': 0.965732216835022, 'Val/mean miou_metric': 0.9442340135574341, 'Val/mean f1': 0.9676007032394409, 'Val/mean precision': 0.9619770646095276, 'Val/mean recall': 0.9732903242111206, 'Val/mean hd95_metric': 6.713696002960205} +Cheakpoint... +Epoch [623/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9657], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965732216835022, 'Val/mean miou_metric': 0.9442340135574341, 'Val/mean f1': 0.9676007032394409, 'Val/mean precision': 0.9619770646095276, 'Val/mean recall': 0.9732903242111206, 'Val/mean hd95_metric': 6.713696002960205} +Epoch [624/4000] Training [1/16] Loss: 0.01458 +Epoch [624/4000] Training [2/16] Loss: 0.01315 +Epoch [624/4000] Training [3/16] Loss: 0.01215 +Epoch [624/4000] Training [4/16] Loss: 0.01284 +Epoch [624/4000] Training [5/16] Loss: 0.02067 +Epoch [624/4000] Training [6/16] Loss: 0.01204 +Epoch [624/4000] Training [7/16] Loss: 0.00993 +Epoch [624/4000] Training [8/16] Loss: 0.01434 +Epoch [624/4000] Training [9/16] Loss: 0.02012 +Epoch [624/4000] Training [10/16] Loss: 0.01053 +Epoch [624/4000] Training [11/16] Loss: 0.01379 +Epoch [624/4000] Training [12/16] Loss: 0.02083 +Epoch [624/4000] Training [13/16] Loss: 0.01090 +Epoch [624/4000] Training [14/16] Loss: 0.01157 +Epoch [624/4000] Training [15/16] Loss: 0.01155 +Epoch [624/4000] Training [16/16] Loss: 0.01351 +Epoch [624/4000] Training metric {'Train/mean dice_metric': 0.9896283745765686, 'Train/mean miou_metric': 0.979634165763855, 'Train/mean f1': 0.9874877333641052, 'Train/mean precision': 0.9830353856086731, 'Train/mean recall': 0.9919805526733398, 'Train/mean hd95_metric': 1.3184643983840942} +Epoch [624/4000] Validation [1/4] Loss: 0.30737 focal_loss 0.21170 dice_loss 0.09566 +Epoch [624/4000] Validation [2/4] Loss: 0.18031 focal_loss 0.08458 dice_loss 0.09573 +Epoch [624/4000] Validation [3/4] Loss: 0.14417 focal_loss 0.06609 dice_loss 0.07808 +Epoch [624/4000] Validation [4/4] Loss: 0.24240 focal_loss 0.12255 dice_loss 0.11985 +Epoch [624/4000] Validation metric {'Val/mean dice_metric': 0.9661065936088562, 'Val/mean miou_metric': 0.9449920654296875, 'Val/mean f1': 0.9695054292678833, 'Val/mean precision': 0.965609073638916, 'Val/mean recall': 0.9734334349632263, 'Val/mean hd95_metric': 6.468005180358887} +Cheakpoint... +Epoch [624/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661065936088562, 'Val/mean miou_metric': 0.9449920654296875, 'Val/mean f1': 0.9695054292678833, 'Val/mean precision': 0.965609073638916, 'Val/mean recall': 0.9734334349632263, 'Val/mean hd95_metric': 6.468005180358887} +Epoch [625/4000] Training [1/16] Loss: 0.01268 +Epoch [625/4000] Training [2/16] Loss: 0.01572 +Epoch [625/4000] Training [3/16] Loss: 0.02301 +Epoch [625/4000] Training [4/16] Loss: 0.01261 +Epoch [625/4000] Training [5/16] Loss: 0.01085 +Epoch [625/4000] Training [6/16] Loss: 0.01464 +Epoch [625/4000] Training [7/16] Loss: 0.01396 +Epoch [625/4000] Training [8/16] Loss: 0.01626 +Epoch [625/4000] Training [9/16] Loss: 0.01410 +Epoch [625/4000] Training [10/16] Loss: 0.01403 +Epoch [625/4000] Training [11/16] Loss: 0.01394 +Epoch [625/4000] Training [12/16] Loss: 0.03140 +Epoch [625/4000] Training [13/16] Loss: 0.02810 +Epoch [625/4000] Training [14/16] Loss: 0.01391 +Epoch [625/4000] Training [15/16] Loss: 0.01969 +Epoch [625/4000] Training [16/16] Loss: 0.01817 +Epoch [625/4000] Training metric {'Train/mean dice_metric': 0.9889126420021057, 'Train/mean miou_metric': 0.9780969619750977, 'Train/mean f1': 0.9867250323295593, 'Train/mean precision': 0.9824317097663879, 'Train/mean recall': 0.9910560846328735, 'Train/mean hd95_metric': 2.033064842224121} +Epoch [625/4000] Validation [1/4] Loss: 0.40156 focal_loss 0.29883 dice_loss 0.10272 +Epoch [625/4000] Validation [2/4] Loss: 0.15130 focal_loss 0.05756 dice_loss 0.09373 +Epoch [625/4000] Validation [3/4] Loss: 0.10959 focal_loss 0.05649 dice_loss 0.05310 +Epoch [625/4000] Validation [4/4] Loss: 0.39825 focal_loss 0.22061 dice_loss 0.17764 +Epoch [625/4000] Validation metric {'Val/mean dice_metric': 0.9661970138549805, 'Val/mean miou_metric': 0.9439128637313843, 'Val/mean f1': 0.9693527817726135, 'Val/mean precision': 0.9659706354141235, 'Val/mean recall': 0.9727587699890137, 'Val/mean hd95_metric': 6.251756191253662} +Cheakpoint... +Epoch [625/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661970138549805, 'Val/mean miou_metric': 0.9439128637313843, 'Val/mean f1': 0.9693527817726135, 'Val/mean precision': 0.9659706354141235, 'Val/mean recall': 0.9727587699890137, 'Val/mean hd95_metric': 6.251756191253662} +Epoch [626/4000] Training [1/16] Loss: 0.01438 +Epoch [626/4000] Training [2/16] Loss: 0.01556 +Epoch [626/4000] Training [3/16] Loss: 0.01288 +Epoch [626/4000] Training [4/16] Loss: 0.01180 +Epoch [626/4000] Training [5/16] Loss: 0.01449 +Epoch [626/4000] Training [6/16] Loss: 0.01379 +Epoch [626/4000] Training [7/16] Loss: 0.01282 +Epoch [626/4000] Training [8/16] Loss: 0.01813 +Epoch [626/4000] Training [9/16] Loss: 0.01299 +Epoch [626/4000] Training [10/16] Loss: 0.01684 +Epoch [626/4000] Training [11/16] Loss: 0.01122 +Epoch [626/4000] Training [12/16] Loss: 0.01348 +Epoch [626/4000] Training [13/16] Loss: 0.01349 +Epoch [626/4000] Training [14/16] Loss: 0.01583 +Epoch [626/4000] Training [15/16] Loss: 0.01382 +Epoch [626/4000] Training [16/16] Loss: 0.01199 +Epoch [626/4000] Training metric {'Train/mean dice_metric': 0.9886461496353149, 'Train/mean miou_metric': 0.9779067039489746, 'Train/mean f1': 0.9864737391471863, 'Train/mean precision': 0.981885552406311, 'Train/mean recall': 0.9911050200462341, 'Train/mean hd95_metric': 2.2830538749694824} +Epoch [626/4000] Validation [1/4] Loss: 0.43130 focal_loss 0.32693 dice_loss 0.10438 +Epoch [626/4000] Validation [2/4] Loss: 0.22361 focal_loss 0.11004 dice_loss 0.11357 +Epoch [626/4000] Validation [3/4] Loss: 0.13531 focal_loss 0.07152 dice_loss 0.06378 +Epoch [626/4000] Validation [4/4] Loss: 0.32292 focal_loss 0.18021 dice_loss 0.14270 +Epoch [626/4000] Validation metric {'Val/mean dice_metric': 0.9659660458564758, 'Val/mean miou_metric': 0.9446040987968445, 'Val/mean f1': 0.9680463671684265, 'Val/mean precision': 0.9626328349113464, 'Val/mean recall': 0.9735211730003357, 'Val/mean hd95_metric': 6.95193338394165} +Cheakpoint... +Epoch [626/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659660458564758, 'Val/mean miou_metric': 0.9446040987968445, 'Val/mean f1': 0.9680463671684265, 'Val/mean precision': 0.9626328349113464, 'Val/mean recall': 0.9735211730003357, 'Val/mean hd95_metric': 6.95193338394165} +Epoch [627/4000] Training [1/16] Loss: 0.01274 +Epoch [627/4000] Training [2/16] Loss: 0.01342 +Epoch [627/4000] Training [3/16] Loss: 0.01941 +Epoch [627/4000] Training [4/16] Loss: 0.01589 +Epoch [627/4000] Training [5/16] Loss: 0.01014 +Epoch [627/4000] Training [6/16] Loss: 0.01753 +Epoch [627/4000] Training [7/16] Loss: 0.01574 +Epoch [627/4000] Training [8/16] Loss: 0.01080 +Epoch [627/4000] Training [9/16] Loss: 0.01636 +Epoch [627/4000] Training [10/16] Loss: 0.01219 +Epoch [627/4000] Training [11/16] Loss: 0.01235 +Epoch [627/4000] Training [12/16] Loss: 0.10561 +Epoch [627/4000] Training [13/16] Loss: 0.10991 +Epoch [627/4000] Training [14/16] Loss: 0.01557 +Epoch [627/4000] Training [15/16] Loss: 0.01052 +Epoch [627/4000] Training [16/16] Loss: 0.01300 +Epoch [627/4000] Training metric {'Train/mean dice_metric': 0.986854076385498, 'Train/mean miou_metric': 0.976110577583313, 'Train/mean f1': 0.9863263964653015, 'Train/mean precision': 0.98211669921875, 'Train/mean recall': 0.9905723333358765, 'Train/mean hd95_metric': 2.290254592895508} +Epoch [627/4000] Validation [1/4] Loss: 0.66205 focal_loss 0.50789 dice_loss 0.15416 +Epoch [627/4000] Validation [2/4] Loss: 0.31665 focal_loss 0.15601 dice_loss 0.16064 +Epoch [627/4000] Validation [3/4] Loss: 0.15617 focal_loss 0.07211 dice_loss 0.08406 +Epoch [627/4000] Validation [4/4] Loss: 0.40803 focal_loss 0.23196 dice_loss 0.17607 +Epoch [627/4000] Validation metric {'Val/mean dice_metric': 0.9593351483345032, 'Val/mean miou_metric': 0.936855673789978, 'Val/mean f1': 0.9632646441459656, 'Val/mean precision': 0.9656988382339478, 'Val/mean recall': 0.9608427286148071, 'Val/mean hd95_metric': 7.2597479820251465} +Cheakpoint... +Epoch [627/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9593351483345032, 'Val/mean miou_metric': 0.936855673789978, 'Val/mean f1': 0.9632646441459656, 'Val/mean precision': 0.9656988382339478, 'Val/mean recall': 0.9608427286148071, 'Val/mean hd95_metric': 7.2597479820251465} +Epoch [628/4000] Training [1/16] Loss: 0.01619 +Epoch [628/4000] Training [2/16] Loss: 0.01431 +Epoch [628/4000] Training [3/16] Loss: 0.01672 +Epoch [628/4000] Training [4/16] Loss: 0.01651 +Epoch [628/4000] Training [5/16] Loss: 0.01530 +Epoch [628/4000] Training [6/16] Loss: 0.01732 +Epoch [628/4000] Training [7/16] Loss: 0.01763 +Epoch [628/4000] Training [8/16] Loss: 0.01565 +Epoch [628/4000] Training [9/16] Loss: 0.01576 +Epoch [628/4000] Training [10/16] Loss: 0.01546 +Epoch [628/4000] Training [11/16] Loss: 0.02314 +Epoch [628/4000] Training [12/16] Loss: 0.01710 +Epoch [628/4000] Training [13/16] Loss: 0.01592 +Epoch [628/4000] Training [14/16] Loss: 0.01523 +Epoch [628/4000] Training [15/16] Loss: 0.01332 +Epoch [628/4000] Training [16/16] Loss: 0.01478 +Epoch [628/4000] Training metric {'Train/mean dice_metric': 0.9879981279373169, 'Train/mean miou_metric': 0.9764031171798706, 'Train/mean f1': 0.9855083227157593, 'Train/mean precision': 0.9809669852256775, 'Train/mean recall': 0.990091860294342, 'Train/mean hd95_metric': 2.3598740100860596} +Epoch [628/4000] Validation [1/4] Loss: 0.22223 focal_loss 0.13798 dice_loss 0.08425 +Epoch [628/4000] Validation [2/4] Loss: 0.32027 focal_loss 0.15775 dice_loss 0.16252 +Epoch [628/4000] Validation [3/4] Loss: 0.10023 focal_loss 0.04647 dice_loss 0.05376 +Epoch [628/4000] Validation [4/4] Loss: 0.19836 focal_loss 0.08907 dice_loss 0.10929 +Epoch [628/4000] Validation metric {'Val/mean dice_metric': 0.9640619158744812, 'Val/mean miou_metric': 0.9420528411865234, 'Val/mean f1': 0.9689382910728455, 'Val/mean precision': 0.9677529335021973, 'Val/mean recall': 0.9701265692710876, 'Val/mean hd95_metric': 6.3858323097229} +Cheakpoint... +Epoch [628/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640619158744812, 'Val/mean miou_metric': 0.9420528411865234, 'Val/mean f1': 0.9689382910728455, 'Val/mean precision': 0.9677529335021973, 'Val/mean recall': 0.9701265692710876, 'Val/mean hd95_metric': 6.3858323097229} +Epoch [629/4000] Training [1/16] Loss: 0.01416 +Epoch [629/4000] Training [2/16] Loss: 0.01173 +Epoch [629/4000] Training [3/16] Loss: 0.02235 +Epoch [629/4000] Training [4/16] Loss: 0.01430 +Epoch [629/4000] Training [5/16] Loss: 0.01316 +Epoch [629/4000] Training [6/16] Loss: 0.01424 +Epoch [629/4000] Training [7/16] Loss: 0.01586 +Epoch [629/4000] Training [8/16] Loss: 0.01959 +Epoch [629/4000] Training [9/16] Loss: 0.01708 +Epoch [629/4000] Training [10/16] Loss: 0.01672 +Epoch [629/4000] Training [11/16] Loss: 0.02080 +Epoch [629/4000] Training [12/16] Loss: 0.12807 +Epoch [629/4000] Training [13/16] Loss: 0.01962 +Epoch [629/4000] Training [14/16] Loss: 0.01278 +Epoch [629/4000] Training [15/16] Loss: 0.01363 +Epoch [629/4000] Training [16/16] Loss: 0.01543 +Epoch [629/4000] Training metric {'Train/mean dice_metric': 0.9868165254592896, 'Train/mean miou_metric': 0.9749326705932617, 'Train/mean f1': 0.9845297336578369, 'Train/mean precision': 0.9791707992553711, 'Train/mean recall': 0.9899475574493408, 'Train/mean hd95_metric': 1.8962303400039673} +Epoch [629/4000] Validation [1/4] Loss: 0.38459 focal_loss 0.27870 dice_loss 0.10589 +Epoch [629/4000] Validation [2/4] Loss: 0.42274 focal_loss 0.24067 dice_loss 0.18207 +Epoch [629/4000] Validation [3/4] Loss: 0.15424 focal_loss 0.08655 dice_loss 0.06770 +Epoch [629/4000] Validation [4/4] Loss: 0.22610 focal_loss 0.12059 dice_loss 0.10551 +Epoch [629/4000] Validation metric {'Val/mean dice_metric': 0.9581369161605835, 'Val/mean miou_metric': 0.9351055026054382, 'Val/mean f1': 0.9615540504455566, 'Val/mean precision': 0.9582859873771667, 'Val/mean recall': 0.9648444056510925, 'Val/mean hd95_metric': 6.758880615234375} +Cheakpoint... +Epoch [629/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9581], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9581369161605835, 'Val/mean miou_metric': 0.9351055026054382, 'Val/mean f1': 0.9615540504455566, 'Val/mean precision': 0.9582859873771667, 'Val/mean recall': 0.9648444056510925, 'Val/mean hd95_metric': 6.758880615234375} +Epoch [630/4000] Training [1/16] Loss: 0.01786 +Epoch [630/4000] Training [2/16] Loss: 0.01467 +Epoch [630/4000] Training [3/16] Loss: 0.01513 +Epoch [630/4000] Training [4/16] Loss: 0.01413 +Epoch [630/4000] Training [5/16] Loss: 0.01711 +Epoch [630/4000] Training [6/16] Loss: 0.01569 +Epoch [630/4000] Training [7/16] Loss: 0.01412 +Epoch [630/4000] Training [8/16] Loss: 0.01256 +Epoch [630/4000] Training [9/16] Loss: 0.01567 +Epoch [630/4000] Training [10/16] Loss: 0.01561 +Epoch [630/4000] Training [11/16] Loss: 0.02072 +Epoch [630/4000] Training [12/16] Loss: 0.02525 +Epoch [630/4000] Training [13/16] Loss: 0.02295 +Epoch [630/4000] Training [14/16] Loss: 0.04823 +Epoch [630/4000] Training [15/16] Loss: 0.02362 +Epoch [630/4000] Training [16/16] Loss: 0.02177 +Epoch [630/4000] Training metric {'Train/mean dice_metric': 0.9845144152641296, 'Train/mean miou_metric': 0.9707826375961304, 'Train/mean f1': 0.982148289680481, 'Train/mean precision': 0.9776402711868286, 'Train/mean recall': 0.9866980910301208, 'Train/mean hd95_metric': 3.102128505706787} +Epoch [630/4000] Validation [1/4] Loss: 0.15283 focal_loss 0.08793 dice_loss 0.06490 +Epoch [630/4000] Validation [2/4] Loss: 0.26585 focal_loss 0.11939 dice_loss 0.14646 +Epoch [630/4000] Validation [3/4] Loss: 0.27577 focal_loss 0.14591 dice_loss 0.12986 +Epoch [630/4000] Validation [4/4] Loss: 0.23808 focal_loss 0.13752 dice_loss 0.10056 +Epoch [630/4000] Validation metric {'Val/mean dice_metric': 0.9578069448471069, 'Val/mean miou_metric': 0.9328843951225281, 'Val/mean f1': 0.9611359238624573, 'Val/mean precision': 0.9545225501060486, 'Val/mean recall': 0.9678414463996887, 'Val/mean hd95_metric': 8.575838088989258} +Cheakpoint... +Epoch [630/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9578], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9578069448471069, 'Val/mean miou_metric': 0.9328843951225281, 'Val/mean f1': 0.9611359238624573, 'Val/mean precision': 0.9545225501060486, 'Val/mean recall': 0.9678414463996887, 'Val/mean hd95_metric': 8.575838088989258} +Epoch [631/4000] Training [1/16] Loss: 0.01401 +Epoch [631/4000] Training [2/16] Loss: 0.01523 +Epoch [631/4000] Training [3/16] Loss: 0.01395 +Epoch [631/4000] Training [4/16] Loss: 0.01949 +Epoch [631/4000] Training [5/16] Loss: 0.01471 +Epoch [631/4000] Training [6/16] Loss: 0.01743 +Epoch [631/4000] Training [7/16] Loss: 0.01442 +Epoch [631/4000] Training [8/16] Loss: 0.01325 +Epoch [631/4000] Training [9/16] Loss: 0.02248 +Epoch [631/4000] Training [10/16] Loss: 0.01915 +Epoch [631/4000] Training [11/16] Loss: 0.01733 +Epoch [631/4000] Training [12/16] Loss: 0.01621 +Epoch [631/4000] Training [13/16] Loss: 0.01213 +Epoch [631/4000] Training [14/16] Loss: 0.01519 +Epoch [631/4000] Training [15/16] Loss: 0.02692 +Epoch [631/4000] Training [16/16] Loss: 0.02459 +Epoch [631/4000] Training metric {'Train/mean dice_metric': 0.9859476089477539, 'Train/mean miou_metric': 0.9730758666992188, 'Train/mean f1': 0.9831842184066772, 'Train/mean precision': 0.9802829027175903, 'Train/mean recall': 0.9861027002334595, 'Train/mean hd95_metric': 2.9415347576141357} +Epoch [631/4000] Validation [1/4] Loss: 0.17970 focal_loss 0.11144 dice_loss 0.06826 +Epoch [631/4000] Validation [2/4] Loss: 0.20996 focal_loss 0.09332 dice_loss 0.11664 +Epoch [631/4000] Validation [3/4] Loss: 0.16314 focal_loss 0.07617 dice_loss 0.08697 +Epoch [631/4000] Validation [4/4] Loss: 0.31565 focal_loss 0.19141 dice_loss 0.12424 +Epoch [631/4000] Validation metric {'Val/mean dice_metric': 0.9590997695922852, 'Val/mean miou_metric': 0.9353746175765991, 'Val/mean f1': 0.9642014503479004, 'Val/mean precision': 0.9617370963096619, 'Val/mean recall': 0.9666784405708313, 'Val/mean hd95_metric': 8.401250839233398} +Cheakpoint... +Epoch [631/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9591], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9590997695922852, 'Val/mean miou_metric': 0.9353746175765991, 'Val/mean f1': 0.9642014503479004, 'Val/mean precision': 0.9617370963096619, 'Val/mean recall': 0.9666784405708313, 'Val/mean hd95_metric': 8.401250839233398} +Epoch [632/4000] Training [1/16] Loss: 0.02931 +Epoch [632/4000] Training [2/16] Loss: 0.01461 +Epoch [632/4000] Training [3/16] Loss: 0.01819 +Epoch [632/4000] Training [4/16] Loss: 0.02246 +Epoch [632/4000] Training [5/16] Loss: 0.01114 +Epoch [632/4000] Training [6/16] Loss: 0.01270 +Epoch [632/4000] Training [7/16] Loss: 0.01453 +Epoch [632/4000] Training [8/16] Loss: 0.01174 +Epoch [632/4000] Training [9/16] Loss: 0.01137 +Epoch [632/4000] Training [10/16] Loss: 0.01698 +Epoch [632/4000] Training [11/16] Loss: 0.01432 +Epoch [632/4000] Training [12/16] Loss: 0.01445 +Epoch [632/4000] Training [13/16] Loss: 0.02280 +Epoch [632/4000] Training [14/16] Loss: 0.01357 +Epoch [632/4000] Training [15/16] Loss: 0.01334 +Epoch [632/4000] Training [16/16] Loss: 0.01849 +Epoch [632/4000] Training metric {'Train/mean dice_metric': 0.988672137260437, 'Train/mean miou_metric': 0.9775339961051941, 'Train/mean f1': 0.9853190779685974, 'Train/mean precision': 0.9806912541389465, 'Train/mean recall': 0.989990770816803, 'Train/mean hd95_metric': 1.7780389785766602} +Epoch [632/4000] Validation [1/4] Loss: 0.31202 focal_loss 0.21037 dice_loss 0.10165 +Epoch [632/4000] Validation [2/4] Loss: 0.43661 focal_loss 0.22258 dice_loss 0.21403 +Epoch [632/4000] Validation [3/4] Loss: 0.10940 focal_loss 0.04666 dice_loss 0.06274 +Epoch [632/4000] Validation [4/4] Loss: 0.47517 focal_loss 0.24511 dice_loss 0.23006 +Epoch [632/4000] Validation metric {'Val/mean dice_metric': 0.9632457494735718, 'Val/mean miou_metric': 0.93970787525177, 'Val/mean f1': 0.9647502899169922, 'Val/mean precision': 0.9588199257850647, 'Val/mean recall': 0.9707544445991516, 'Val/mean hd95_metric': 7.688141822814941} +Cheakpoint... +Epoch [632/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632457494735718, 'Val/mean miou_metric': 0.93970787525177, 'Val/mean f1': 0.9647502899169922, 'Val/mean precision': 0.9588199257850647, 'Val/mean recall': 0.9707544445991516, 'Val/mean hd95_metric': 7.688141822814941} +Epoch [633/4000] Training [1/16] Loss: 0.01432 +Epoch [633/4000] Training [2/16] Loss: 0.01229 +Epoch [633/4000] Training [3/16] Loss: 0.01840 +Epoch [633/4000] Training [4/16] Loss: 0.06807 +Epoch [633/4000] Training [5/16] Loss: 0.01286 +Epoch [633/4000] Training [6/16] Loss: 0.01297 +Epoch [633/4000] Training [7/16] Loss: 0.02253 +Epoch [633/4000] Training [8/16] Loss: 0.02935 +Epoch [633/4000] Training [9/16] Loss: 0.02103 +Epoch [633/4000] Training [10/16] Loss: 0.01790 +Epoch [633/4000] Training [11/16] Loss: 0.01520 +Epoch [633/4000] Training [12/16] Loss: 0.02362 +Epoch [633/4000] Training [13/16] Loss: 0.01666 +Epoch [633/4000] Training [14/16] Loss: 0.01764 +Epoch [633/4000] Training [15/16] Loss: 0.02894 +Epoch [633/4000] Training [16/16] Loss: 0.01758 +Epoch [633/4000] Training metric {'Train/mean dice_metric': 0.9863743782043457, 'Train/mean miou_metric': 0.9735572338104248, 'Train/mean f1': 0.983029842376709, 'Train/mean precision': 0.9787784218788147, 'Train/mean recall': 0.9873183965682983, 'Train/mean hd95_metric': 2.948439598083496} +Epoch [633/4000] Validation [1/4] Loss: 0.20103 focal_loss 0.10157 dice_loss 0.09946 +Epoch [633/4000] Validation [2/4] Loss: 0.41555 focal_loss 0.17652 dice_loss 0.23903 +Epoch [633/4000] Validation [3/4] Loss: 0.22274 focal_loss 0.10542 dice_loss 0.11732 +Epoch [633/4000] Validation [4/4] Loss: 0.20742 focal_loss 0.09563 dice_loss 0.11178 +Epoch [633/4000] Validation metric {'Val/mean dice_metric': 0.9592863917350769, 'Val/mean miou_metric': 0.9344472885131836, 'Val/mean f1': 0.9585339426994324, 'Val/mean precision': 0.9476063251495361, 'Val/mean recall': 0.9697163701057434, 'Val/mean hd95_metric': 9.576597213745117} +Cheakpoint... +Epoch [633/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9592863917350769, 'Val/mean miou_metric': 0.9344472885131836, 'Val/mean f1': 0.9585339426994324, 'Val/mean precision': 0.9476063251495361, 'Val/mean recall': 0.9697163701057434, 'Val/mean hd95_metric': 9.576597213745117} +Epoch [634/4000] Training [1/16] Loss: 0.02000 +Epoch [634/4000] Training [2/16] Loss: 0.01566 +Epoch [634/4000] Training [3/16] Loss: 0.01752 +Epoch [634/4000] Training [4/16] Loss: 0.01580 +Epoch [634/4000] Training [5/16] Loss: 0.01942 +Epoch [634/4000] Training [6/16] Loss: 0.01649 +Epoch [634/4000] Training [7/16] Loss: 0.02046 +Epoch [634/4000] Training [8/16] Loss: 0.01571 +Epoch [634/4000] Training [9/16] Loss: 0.01854 +Epoch [634/4000] Training [10/16] Loss: 0.01892 +Epoch [634/4000] Training [11/16] Loss: 0.02149 +Epoch [634/4000] Training [12/16] Loss: 0.02153 +Epoch [634/4000] Training [13/16] Loss: 0.01407 +Epoch [634/4000] Training [14/16] Loss: 0.01655 +Epoch [634/4000] Training [15/16] Loss: 0.02436 +Epoch [634/4000] Training [16/16] Loss: 0.05272 +Epoch [634/4000] Training metric {'Train/mean dice_metric': 0.9868252873420715, 'Train/mean miou_metric': 0.973971426486969, 'Train/mean f1': 0.9834086298942566, 'Train/mean precision': 0.9784387946128845, 'Train/mean recall': 0.9884292483329773, 'Train/mean hd95_metric': 2.2503163814544678} +Epoch [634/4000] Validation [1/4] Loss: 0.12653 focal_loss 0.06810 dice_loss 0.05844 +Epoch [634/4000] Validation [2/4] Loss: 0.49088 focal_loss 0.27010 dice_loss 0.22078 +Epoch [634/4000] Validation [3/4] Loss: 0.21186 focal_loss 0.10035 dice_loss 0.11151 +Epoch [634/4000] Validation [4/4] Loss: 0.47313 focal_loss 0.26362 dice_loss 0.20951 +Epoch [634/4000] Validation metric {'Val/mean dice_metric': 0.9616166949272156, 'Val/mean miou_metric': 0.936840832233429, 'Val/mean f1': 0.9623671174049377, 'Val/mean precision': 0.9511670470237732, 'Val/mean recall': 0.9738339781761169, 'Val/mean hd95_metric': 8.87031078338623} +Cheakpoint... +Epoch [634/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9616], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616166949272156, 'Val/mean miou_metric': 0.936840832233429, 'Val/mean f1': 0.9623671174049377, 'Val/mean precision': 0.9511670470237732, 'Val/mean recall': 0.9738339781761169, 'Val/mean hd95_metric': 8.87031078338623} +Epoch [635/4000] Training [1/16] Loss: 0.02122 +Epoch [635/4000] Training [2/16] Loss: 0.01261 +Epoch [635/4000] Training [3/16] Loss: 0.01561 +Epoch [635/4000] Training [4/16] Loss: 0.01427 +Epoch [635/4000] Training [5/16] Loss: 0.01409 +Epoch [635/4000] Training [6/16] Loss: 0.02511 +Epoch [635/4000] Training [7/16] Loss: 0.01871 +Epoch [635/4000] Training [8/16] Loss: 0.02104 +Epoch [635/4000] Training [9/16] Loss: 0.01759 +Epoch [635/4000] Training [10/16] Loss: 0.02592 +Epoch [635/4000] Training [11/16] Loss: 0.01486 +Epoch [635/4000] Training [12/16] Loss: 0.01648 +Epoch [635/4000] Training [13/16] Loss: 0.01642 +Epoch [635/4000] Training [14/16] Loss: 0.01572 +Epoch [635/4000] Training [15/16] Loss: 0.01861 +Epoch [635/4000] Training [16/16] Loss: 0.01922 +Epoch [635/4000] Training metric {'Train/mean dice_metric': 0.9879201650619507, 'Train/mean miou_metric': 0.975985050201416, 'Train/mean f1': 0.9846305847167969, 'Train/mean precision': 0.9800698757171631, 'Train/mean recall': 0.9892339706420898, 'Train/mean hd95_metric': 2.283919334411621} +Epoch [635/4000] Validation [1/4] Loss: 0.61566 focal_loss 0.44503 dice_loss 0.17063 +Epoch [635/4000] Validation [2/4] Loss: 0.35777 focal_loss 0.19649 dice_loss 0.16128 +Epoch [635/4000] Validation [3/4] Loss: 0.28559 focal_loss 0.17788 dice_loss 0.10771 +Epoch [635/4000] Validation [4/4] Loss: 0.25156 focal_loss 0.14216 dice_loss 0.10940 +Epoch [635/4000] Validation metric {'Val/mean dice_metric': 0.9616235494613647, 'Val/mean miou_metric': 0.9380123019218445, 'Val/mean f1': 0.9628125429153442, 'Val/mean precision': 0.9635964632034302, 'Val/mean recall': 0.9620299935340881, 'Val/mean hd95_metric': 7.511900424957275} +Cheakpoint... +Epoch [635/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9616], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616235494613647, 'Val/mean miou_metric': 0.9380123019218445, 'Val/mean f1': 0.9628125429153442, 'Val/mean precision': 0.9635964632034302, 'Val/mean recall': 0.9620299935340881, 'Val/mean hd95_metric': 7.511900424957275} +Epoch [636/4000] Training [1/16] Loss: 0.01518 +Epoch [636/4000] Training [2/16] Loss: 0.05478 +Epoch [636/4000] Training [3/16] Loss: 0.02141 +Epoch [636/4000] Training [4/16] Loss: 0.01450 +Epoch [636/4000] Training [5/16] Loss: 0.02284 +Epoch [636/4000] Training [6/16] Loss: 0.01671 +Epoch [636/4000] Training [7/16] Loss: 0.01645 +Epoch [636/4000] Training [8/16] Loss: 0.01441 +Epoch [636/4000] Training [9/16] Loss: 0.01837 +Epoch [636/4000] Training [10/16] Loss: 0.01393 +Epoch [636/4000] Training [11/16] Loss: 0.01511 +Epoch [636/4000] Training [12/16] Loss: 0.01799 +Epoch [636/4000] Training [13/16] Loss: 0.01958 +Epoch [636/4000] Training [14/16] Loss: 0.02042 +Epoch [636/4000] Training [15/16] Loss: 0.01253 +Epoch [636/4000] Training [16/16] Loss: 0.01526 +Epoch [636/4000] Training metric {'Train/mean dice_metric': 0.9880954623222351, 'Train/mean miou_metric': 0.9764108657836914, 'Train/mean f1': 0.9849503040313721, 'Train/mean precision': 0.9806644320487976, 'Train/mean recall': 0.989273726940155, 'Train/mean hd95_metric': 1.9739351272583008} +Epoch [636/4000] Validation [1/4] Loss: 0.18942 focal_loss 0.10997 dice_loss 0.07946 +Epoch [636/4000] Validation [2/4] Loss: 0.36290 focal_loss 0.16260 dice_loss 0.20031 +Epoch [636/4000] Validation [3/4] Loss: 0.31283 focal_loss 0.19275 dice_loss 0.12008 +Epoch [636/4000] Validation [4/4] Loss: 0.39668 focal_loss 0.20887 dice_loss 0.18780 +Epoch [636/4000] Validation metric {'Val/mean dice_metric': 0.9633150100708008, 'Val/mean miou_metric': 0.9392464756965637, 'Val/mean f1': 0.9647293090820312, 'Val/mean precision': 0.9538203477859497, 'Val/mean recall': 0.9758906364440918, 'Val/mean hd95_metric': 8.535247802734375} +Cheakpoint... +Epoch [636/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633150100708008, 'Val/mean miou_metric': 0.9392464756965637, 'Val/mean f1': 0.9647293090820312, 'Val/mean precision': 0.9538203477859497, 'Val/mean recall': 0.9758906364440918, 'Val/mean hd95_metric': 8.535247802734375} +Epoch [637/4000] Training [1/16] Loss: 0.01388 +Epoch [637/4000] Training [2/16] Loss: 0.03048 +Epoch [637/4000] Training [3/16] Loss: 0.01053 +Epoch [637/4000] Training [4/16] Loss: 0.01806 +Epoch [637/4000] Training [5/16] Loss: 0.01768 +Epoch [637/4000] Training [6/16] Loss: 0.01156 +Epoch [637/4000] Training [7/16] Loss: 0.01822 +Epoch [637/4000] Training [8/16] Loss: 0.01398 +Epoch [637/4000] Training [9/16] Loss: 0.01757 +Epoch [637/4000] Training [10/16] Loss: 0.01758 +Epoch [637/4000] Training [11/16] Loss: 0.01825 +Epoch [637/4000] Training [12/16] Loss: 0.01520 +Epoch [637/4000] Training [13/16] Loss: 0.10300 +Epoch [637/4000] Training [14/16] Loss: 0.01378 +Epoch [637/4000] Training [15/16] Loss: 0.01689 +Epoch [637/4000] Training [16/16] Loss: 0.01535 +Epoch [637/4000] Training metric {'Train/mean dice_metric': 0.9881733655929565, 'Train/mean miou_metric': 0.9766911268234253, 'Train/mean f1': 0.9851633906364441, 'Train/mean precision': 0.9799563884735107, 'Train/mean recall': 0.9904260039329529, 'Train/mean hd95_metric': 2.2278056144714355} +Epoch [637/4000] Validation [1/4] Loss: 0.14360 focal_loss 0.07742 dice_loss 0.06618 +Epoch [637/4000] Validation [2/4] Loss: 0.23995 focal_loss 0.09686 dice_loss 0.14309 +Epoch [637/4000] Validation [3/4] Loss: 0.25286 focal_loss 0.15186 dice_loss 0.10100 +Epoch [637/4000] Validation [4/4] Loss: 0.25838 focal_loss 0.13484 dice_loss 0.12353 +Epoch [637/4000] Validation metric {'Val/mean dice_metric': 0.96515953540802, 'Val/mean miou_metric': 0.9421054124832153, 'Val/mean f1': 0.9679271578788757, 'Val/mean precision': 0.9628345966339111, 'Val/mean recall': 0.9730738997459412, 'Val/mean hd95_metric': 7.4363579750061035} +Cheakpoint... +Epoch [637/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96515953540802, 'Val/mean miou_metric': 0.9421054124832153, 'Val/mean f1': 0.9679271578788757, 'Val/mean precision': 0.9628345966339111, 'Val/mean recall': 0.9730738997459412, 'Val/mean hd95_metric': 7.4363579750061035} +Epoch [638/4000] Training [1/16] Loss: 0.01940 +Epoch [638/4000] Training [2/16] Loss: 0.02089 +Epoch [638/4000] Training [3/16] Loss: 0.01392 +Epoch [638/4000] Training [4/16] Loss: 0.01911 +Epoch [638/4000] Training [5/16] Loss: 0.01434 +Epoch [638/4000] Training [6/16] Loss: 0.02143 +Epoch [638/4000] Training [7/16] Loss: 0.01081 +Epoch [638/4000] Training [8/16] Loss: 0.01457 +Epoch [638/4000] Training [9/16] Loss: 0.01902 +Epoch [638/4000] Training [10/16] Loss: 0.01198 +Epoch [638/4000] Training [11/16] Loss: 0.01290 +Epoch [638/4000] Training [12/16] Loss: 0.01269 +Epoch [638/4000] Training [13/16] Loss: 0.01314 +Epoch [638/4000] Training [14/16] Loss: 0.01131 +Epoch [638/4000] Training [15/16] Loss: 0.01496 +Epoch [638/4000] Training [16/16] Loss: 0.01338 +Epoch [638/4000] Training metric {'Train/mean dice_metric': 0.9896570444107056, 'Train/mean miou_metric': 0.9793280959129333, 'Train/mean f1': 0.9862555265426636, 'Train/mean precision': 0.9813690185546875, 'Train/mean recall': 0.991191029548645, 'Train/mean hd95_metric': 1.571699619293213} +Epoch [638/4000] Validation [1/4] Loss: 0.15691 focal_loss 0.08929 dice_loss 0.06762 +Epoch [638/4000] Validation [2/4] Loss: 0.31730 focal_loss 0.14247 dice_loss 0.17484 +Epoch [638/4000] Validation [3/4] Loss: 0.31324 focal_loss 0.20063 dice_loss 0.11261 +Epoch [638/4000] Validation [4/4] Loss: 0.30566 focal_loss 0.13982 dice_loss 0.16583 +Epoch [638/4000] Validation metric {'Val/mean dice_metric': 0.9630244374275208, 'Val/mean miou_metric': 0.9407711029052734, 'Val/mean f1': 0.9651570916175842, 'Val/mean precision': 0.9564977884292603, 'Val/mean recall': 0.9739747643470764, 'Val/mean hd95_metric': 7.844152927398682} +Cheakpoint... +Epoch [638/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9630244374275208, 'Val/mean miou_metric': 0.9407711029052734, 'Val/mean f1': 0.9651570916175842, 'Val/mean precision': 0.9564977884292603, 'Val/mean recall': 0.9739747643470764, 'Val/mean hd95_metric': 7.844152927398682} +Epoch [639/4000] Training [1/16] Loss: 0.01379 +Epoch [639/4000] Training [2/16] Loss: 0.01541 +Epoch [639/4000] Training [3/16] Loss: 0.01049 +Epoch [639/4000] Training [4/16] Loss: 0.01460 +Epoch [639/4000] Training [5/16] Loss: 0.01428 +Epoch [639/4000] Training [6/16] Loss: 0.01518 +Epoch [639/4000] Training [7/16] Loss: 0.01675 +Epoch [639/4000] Training [8/16] Loss: 0.01448 +Epoch [639/4000] Training [9/16] Loss: 0.01675 +Epoch [639/4000] Training [10/16] Loss: 0.01570 +Epoch [639/4000] Training [11/16] Loss: 0.01388 +Epoch [639/4000] Training [12/16] Loss: 0.01113 +Epoch [639/4000] Training [13/16] Loss: 0.02231 +Epoch [639/4000] Training [14/16] Loss: 0.01580 +Epoch [639/4000] Training [15/16] Loss: 0.01253 +Epoch [639/4000] Training [16/16] Loss: 0.01625 +Epoch [639/4000] Training metric {'Train/mean dice_metric': 0.9890508651733398, 'Train/mean miou_metric': 0.9783953428268433, 'Train/mean f1': 0.9859790802001953, 'Train/mean precision': 0.9817673563957214, 'Train/mean recall': 0.9902271032333374, 'Train/mean hd95_metric': 1.6472358703613281} +Epoch [639/4000] Validation [1/4] Loss: 0.23527 focal_loss 0.14862 dice_loss 0.08665 +Epoch [639/4000] Validation [2/4] Loss: 0.43396 focal_loss 0.23590 dice_loss 0.19805 +Epoch [639/4000] Validation [3/4] Loss: 0.26306 focal_loss 0.16051 dice_loss 0.10255 +Epoch [639/4000] Validation [4/4] Loss: 0.21493 focal_loss 0.10806 dice_loss 0.10687 +Epoch [639/4000] Validation metric {'Val/mean dice_metric': 0.9639402627944946, 'Val/mean miou_metric': 0.941441535949707, 'Val/mean f1': 0.965506374835968, 'Val/mean precision': 0.9603713750839233, 'Val/mean recall': 0.9706966876983643, 'Val/mean hd95_metric': 7.506805419921875} +Cheakpoint... +Epoch [639/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639402627944946, 'Val/mean miou_metric': 0.941441535949707, 'Val/mean f1': 0.965506374835968, 'Val/mean precision': 0.9603713750839233, 'Val/mean recall': 0.9706966876983643, 'Val/mean hd95_metric': 7.506805419921875} +Epoch [640/4000] Training [1/16] Loss: 0.01438 +Epoch [640/4000] Training [2/16] Loss: 0.01924 +Epoch [640/4000] Training [3/16] Loss: 0.01619 +Epoch [640/4000] Training [4/16] Loss: 0.01526 +Epoch [640/4000] Training [5/16] Loss: 0.01620 +Epoch [640/4000] Training [6/16] Loss: 0.01256 +Epoch [640/4000] Training [7/16] Loss: 0.01166 +Epoch [640/4000] Training [8/16] Loss: 0.01250 +Epoch [640/4000] Training [9/16] Loss: 0.01478 +Epoch [640/4000] Training [10/16] Loss: 0.01235 +Epoch [640/4000] Training [11/16] Loss: 0.01669 +Epoch [640/4000] Training [12/16] Loss: 0.01671 +Epoch [640/4000] Training [13/16] Loss: 0.01072 +Epoch [640/4000] Training [14/16] Loss: 0.01170 +Epoch [640/4000] Training [15/16] Loss: 0.01026 +Epoch [640/4000] Training [16/16] Loss: 0.01108 +Epoch [640/4000] Training metric {'Train/mean dice_metric': 0.9907059669494629, 'Train/mean miou_metric': 0.9813699722290039, 'Train/mean f1': 0.9873731732368469, 'Train/mean precision': 0.9824823141098022, 'Train/mean recall': 0.9923129081726074, 'Train/mean hd95_metric': 1.2695828676223755} +Epoch [640/4000] Validation [1/4] Loss: 0.23652 focal_loss 0.15170 dice_loss 0.08483 +Epoch [640/4000] Validation [2/4] Loss: 0.24530 focal_loss 0.11015 dice_loss 0.13515 +Epoch [640/4000] Validation [3/4] Loss: 0.25161 focal_loss 0.13254 dice_loss 0.11906 +Epoch [640/4000] Validation [4/4] Loss: 0.27764 focal_loss 0.15638 dice_loss 0.12126 +Epoch [640/4000] Validation metric {'Val/mean dice_metric': 0.9665098190307617, 'Val/mean miou_metric': 0.9453161954879761, 'Val/mean f1': 0.9679874181747437, 'Val/mean precision': 0.9618625044822693, 'Val/mean recall': 0.9741908311843872, 'Val/mean hd95_metric': 7.33539342880249} +Cheakpoint... +Epoch [640/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665098190307617, 'Val/mean miou_metric': 0.9453161954879761, 'Val/mean f1': 0.9679874181747437, 'Val/mean precision': 0.9618625044822693, 'Val/mean recall': 0.9741908311843872, 'Val/mean hd95_metric': 7.33539342880249} +Epoch [641/4000] Training [1/16] Loss: 0.01413 +Epoch [641/4000] Training [2/16] Loss: 0.01330 +Epoch [641/4000] Training [3/16] Loss: 0.01638 +Epoch [641/4000] Training [4/16] Loss: 0.01497 +Epoch [641/4000] Training [5/16] Loss: 0.01446 +Epoch [641/4000] Training [6/16] Loss: 0.01944 +Epoch [641/4000] Training [7/16] Loss: 0.01360 +Epoch [641/4000] Training [8/16] Loss: 0.01235 +Epoch [641/4000] Training [9/16] Loss: 0.01084 +Epoch [641/4000] Training [10/16] Loss: 0.01872 +Epoch [641/4000] Training [11/16] Loss: 0.02623 +Epoch [641/4000] Training [12/16] Loss: 0.01791 +Epoch [641/4000] Training [13/16] Loss: 0.02097 +Epoch [641/4000] Training [14/16] Loss: 0.01117 +Epoch [641/4000] Training [15/16] Loss: 0.01559 +Epoch [641/4000] Training [16/16] Loss: 0.01494 +Epoch [641/4000] Training metric {'Train/mean dice_metric': 0.9892066717147827, 'Train/mean miou_metric': 0.9786970615386963, 'Train/mean f1': 0.9860313534736633, 'Train/mean precision': 0.98131263256073, 'Train/mean recall': 0.9907956719398499, 'Train/mean hd95_metric': 1.557241439819336} +Epoch [641/4000] Validation [1/4] Loss: 0.51746 focal_loss 0.37553 dice_loss 0.14193 +Epoch [641/4000] Validation [2/4] Loss: 0.24447 focal_loss 0.11586 dice_loss 0.12861 +Epoch [641/4000] Validation [3/4] Loss: 0.24289 focal_loss 0.13958 dice_loss 0.10332 +Epoch [641/4000] Validation [4/4] Loss: 0.24258 focal_loss 0.11262 dice_loss 0.12996 +Epoch [641/4000] Validation metric {'Val/mean dice_metric': 0.9635990262031555, 'Val/mean miou_metric': 0.9410995244979858, 'Val/mean f1': 0.9651102423667908, 'Val/mean precision': 0.9619130492210388, 'Val/mean recall': 0.9683288335800171, 'Val/mean hd95_metric': 7.415065765380859} +Cheakpoint... +Epoch [641/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9635990262031555, 'Val/mean miou_metric': 0.9410995244979858, 'Val/mean f1': 0.9651102423667908, 'Val/mean precision': 0.9619130492210388, 'Val/mean recall': 0.9683288335800171, 'Val/mean hd95_metric': 7.415065765380859} +Epoch [642/4000] Training [1/16] Loss: 0.00891 +Epoch [642/4000] Training [2/16] Loss: 0.01352 +Epoch [642/4000] Training [3/16] Loss: 0.00986 +Epoch [642/4000] Training [4/16] Loss: 0.01699 +Epoch [642/4000] Training [5/16] Loss: 0.01185 +Epoch [642/4000] Training [6/16] Loss: 0.01407 +Epoch [642/4000] Training [7/16] Loss: 0.01294 +Epoch [642/4000] Training [8/16] Loss: 0.01353 +Epoch [642/4000] Training [9/16] Loss: 0.01809 +Epoch [642/4000] Training [10/16] Loss: 0.02035 +Epoch [642/4000] Training [11/16] Loss: 0.01446 +Epoch [642/4000] Training [12/16] Loss: 0.02128 +Epoch [642/4000] Training [13/16] Loss: 0.01050 +Epoch [642/4000] Training [14/16] Loss: 0.01482 +Epoch [642/4000] Training [15/16] Loss: 0.01282 +Epoch [642/4000] Training [16/16] Loss: 0.01380 +Epoch [642/4000] Training metric {'Train/mean dice_metric': 0.9903864860534668, 'Train/mean miou_metric': 0.9807490110397339, 'Train/mean f1': 0.9875020384788513, 'Train/mean precision': 0.9831990599632263, 'Train/mean recall': 0.9918428659439087, 'Train/mean hd95_metric': 1.2921836376190186} +Epoch [642/4000] Validation [1/4] Loss: 0.15262 focal_loss 0.09034 dice_loss 0.06228 +Epoch [642/4000] Validation [2/4] Loss: 0.22682 focal_loss 0.10299 dice_loss 0.12384 +Epoch [642/4000] Validation [3/4] Loss: 0.19653 focal_loss 0.10174 dice_loss 0.09479 +Epoch [642/4000] Validation [4/4] Loss: 0.23195 focal_loss 0.09474 dice_loss 0.13722 +Epoch [642/4000] Validation metric {'Val/mean dice_metric': 0.9671639204025269, 'Val/mean miou_metric': 0.9460102915763855, 'Val/mean f1': 0.9697791337966919, 'Val/mean precision': 0.9641469717025757, 'Val/mean recall': 0.9754775166511536, 'Val/mean hd95_metric': 6.475730895996094} +Cheakpoint... +Epoch [642/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671639204025269, 'Val/mean miou_metric': 0.9460102915763855, 'Val/mean f1': 0.9697791337966919, 'Val/mean precision': 0.9641469717025757, 'Val/mean recall': 0.9754775166511536, 'Val/mean hd95_metric': 6.475730895996094} +Epoch [643/4000] Training [1/16] Loss: 0.01129 +Epoch [643/4000] Training [2/16] Loss: 0.01135 +Epoch [643/4000] Training [3/16] Loss: 0.01453 +Epoch [643/4000] Training [4/16] Loss: 0.01201 +Epoch [643/4000] Training [5/16] Loss: 0.01033 +Epoch [643/4000] Training [6/16] Loss: 0.01421 +Epoch [643/4000] Training [7/16] Loss: 0.01740 +Epoch [643/4000] Training [8/16] Loss: 0.01269 +Epoch [643/4000] Training [9/16] Loss: 0.01207 +Epoch [643/4000] Training [10/16] Loss: 0.01336 +Epoch [643/4000] Training [11/16] Loss: 0.01157 +Epoch [643/4000] Training [12/16] Loss: 0.01234 +Epoch [643/4000] Training [13/16] Loss: 0.01780 +Epoch [643/4000] Training [14/16] Loss: 0.01307 +Epoch [643/4000] Training [15/16] Loss: 0.01253 +Epoch [643/4000] Training [16/16] Loss: 0.01365 +Epoch [643/4000] Training metric {'Train/mean dice_metric': 0.9896858930587769, 'Train/mean miou_metric': 0.9797807931900024, 'Train/mean f1': 0.9872833490371704, 'Train/mean precision': 0.9823827147483826, 'Train/mean recall': 0.9922330975532532, 'Train/mean hd95_metric': 1.349433183670044} +Epoch [643/4000] Validation [1/4] Loss: 0.29974 focal_loss 0.19701 dice_loss 0.10273 +Epoch [643/4000] Validation [2/4] Loss: 0.52599 focal_loss 0.27858 dice_loss 0.24741 +Epoch [643/4000] Validation [3/4] Loss: 0.13042 focal_loss 0.06028 dice_loss 0.07014 +Epoch [643/4000] Validation [4/4] Loss: 0.20107 focal_loss 0.07974 dice_loss 0.12133 +Epoch [643/4000] Validation metric {'Val/mean dice_metric': 0.9651151895523071, 'Val/mean miou_metric': 0.9437627792358398, 'Val/mean f1': 0.9680563807487488, 'Val/mean precision': 0.9643574357032776, 'Val/mean recall': 0.9717839360237122, 'Val/mean hd95_metric': 6.704721450805664} +Cheakpoint... +Epoch [643/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651151895523071, 'Val/mean miou_metric': 0.9437627792358398, 'Val/mean f1': 0.9680563807487488, 'Val/mean precision': 0.9643574357032776, 'Val/mean recall': 0.9717839360237122, 'Val/mean hd95_metric': 6.704721450805664} +Epoch [644/4000] Training [1/16] Loss: 0.01248 +Epoch [644/4000] Training [2/16] Loss: 0.01212 +Epoch [644/4000] Training [3/16] Loss: 0.01713 +Epoch [644/4000] Training [4/16] Loss: 0.01730 +Epoch [644/4000] Training [5/16] Loss: 0.01236 +Epoch [644/4000] Training [6/16] Loss: 0.01158 +Epoch [644/4000] Training [7/16] Loss: 0.01215 +Epoch [644/4000] Training [8/16] Loss: 0.01604 +Epoch [644/4000] Training [9/16] Loss: 0.01558 +Epoch [644/4000] Training [10/16] Loss: 0.01152 +Epoch [644/4000] Training [11/16] Loss: 0.02032 +Epoch [644/4000] Training [12/16] Loss: 0.01601 +Epoch [644/4000] Training [13/16] Loss: 0.02228 +Epoch [644/4000] Training [14/16] Loss: 0.01223 +Epoch [644/4000] Training [15/16] Loss: 0.01061 +Epoch [644/4000] Training [16/16] Loss: 0.01242 +Epoch [644/4000] Training metric {'Train/mean dice_metric': 0.989946186542511, 'Train/mean miou_metric': 0.9800035357475281, 'Train/mean f1': 0.987466037273407, 'Train/mean precision': 0.9827993512153625, 'Train/mean recall': 0.9921773076057434, 'Train/mean hd95_metric': 1.3245184421539307} +Epoch [644/4000] Validation [1/4] Loss: 0.19719 focal_loss 0.12503 dice_loss 0.07216 +Epoch [644/4000] Validation [2/4] Loss: 0.34246 focal_loss 0.16705 dice_loss 0.17541 +Epoch [644/4000] Validation [3/4] Loss: 0.17450 focal_loss 0.08890 dice_loss 0.08560 +Epoch [644/4000] Validation [4/4] Loss: 0.26754 focal_loss 0.15248 dice_loss 0.11507 +Epoch [644/4000] Validation metric {'Val/mean dice_metric': 0.9665945768356323, 'Val/mean miou_metric': 0.9447392225265503, 'Val/mean f1': 0.9696741104125977, 'Val/mean precision': 0.9639210104942322, 'Val/mean recall': 0.9754962921142578, 'Val/mean hd95_metric': 6.967620849609375} +Cheakpoint... +Epoch [644/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665945768356323, 'Val/mean miou_metric': 0.9447392225265503, 'Val/mean f1': 0.9696741104125977, 'Val/mean precision': 0.9639210104942322, 'Val/mean recall': 0.9754962921142578, 'Val/mean hd95_metric': 6.967620849609375} +Epoch [645/4000] Training [1/16] Loss: 0.01602 +Epoch [645/4000] Training [2/16] Loss: 0.01192 +Epoch [645/4000] Training [3/16] Loss: 0.01588 +Epoch [645/4000] Training [4/16] Loss: 0.01559 +Epoch [645/4000] Training [5/16] Loss: 0.01954 +Epoch [645/4000] Training [6/16] Loss: 0.01306 +Epoch [645/4000] Training [7/16] Loss: 0.01132 +Epoch [645/4000] Training [8/16] Loss: 0.01403 +Epoch [645/4000] Training [9/16] Loss: 0.01913 +Epoch [645/4000] Training [10/16] Loss: 0.01726 +Epoch [645/4000] Training [11/16] Loss: 0.01128 +Epoch [645/4000] Training [12/16] Loss: 0.01510 +Epoch [645/4000] Training [13/16] Loss: 0.01470 +Epoch [645/4000] Training [14/16] Loss: 0.01581 +Epoch [645/4000] Training [15/16] Loss: 0.01564 +Epoch [645/4000] Training [16/16] Loss: 0.02304 +Epoch [645/4000] Training metric {'Train/mean dice_metric': 0.9893254041671753, 'Train/mean miou_metric': 0.9787191152572632, 'Train/mean f1': 0.986812949180603, 'Train/mean precision': 0.9824304580688477, 'Train/mean recall': 0.9912347197532654, 'Train/mean hd95_metric': 1.600855827331543} +Epoch [645/4000] Validation [1/4] Loss: 0.48664 focal_loss 0.36252 dice_loss 0.12411 +Epoch [645/4000] Validation [2/4] Loss: 0.23154 focal_loss 0.10551 dice_loss 0.12603 +Epoch [645/4000] Validation [3/4] Loss: 0.12230 focal_loss 0.05888 dice_loss 0.06341 +Epoch [645/4000] Validation [4/4] Loss: 0.21596 focal_loss 0.11480 dice_loss 0.10116 +Epoch [645/4000] Validation metric {'Val/mean dice_metric': 0.9652034640312195, 'Val/mean miou_metric': 0.9431413412094116, 'Val/mean f1': 0.9671823382377625, 'Val/mean precision': 0.967145562171936, 'Val/mean recall': 0.9672191739082336, 'Val/mean hd95_metric': 6.630792140960693} +Cheakpoint... +Epoch [645/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652034640312195, 'Val/mean miou_metric': 0.9431413412094116, 'Val/mean f1': 0.9671823382377625, 'Val/mean precision': 0.967145562171936, 'Val/mean recall': 0.9672191739082336, 'Val/mean hd95_metric': 6.630792140960693} +Epoch [646/4000] Training [1/16] Loss: 0.01729 +Epoch [646/4000] Training [2/16] Loss: 0.01298 +Epoch [646/4000] Training [3/16] Loss: 0.01214 +Epoch [646/4000] Training [4/16] Loss: 0.01355 +Epoch [646/4000] Training [5/16] Loss: 0.01058 +Epoch [646/4000] Training [6/16] Loss: 0.01415 +Epoch [646/4000] Training [7/16] Loss: 0.01961 +Epoch [646/4000] Training [8/16] Loss: 0.01720 +Epoch [646/4000] Training [9/16] Loss: 0.01327 +Epoch [646/4000] Training [10/16] Loss: 0.01072 +Epoch [646/4000] Training [11/16] Loss: 0.01511 +Epoch [646/4000] Training [12/16] Loss: 0.02224 +Epoch [646/4000] Training [13/16] Loss: 0.02698 +Epoch [646/4000] Training [14/16] Loss: 0.01436 +Epoch [646/4000] Training [15/16] Loss: 0.01509 +Epoch [646/4000] Training [16/16] Loss: 0.01721 +Epoch [646/4000] Training metric {'Train/mean dice_metric': 0.9896663427352905, 'Train/mean miou_metric': 0.9793686866760254, 'Train/mean f1': 0.9868292808532715, 'Train/mean precision': 0.9821433424949646, 'Train/mean recall': 0.9915602207183838, 'Train/mean hd95_metric': 1.2935771942138672} +Epoch [646/4000] Validation [1/4] Loss: 0.26191 focal_loss 0.16617 dice_loss 0.09575 +Epoch [646/4000] Validation [2/4] Loss: 0.32243 focal_loss 0.11686 dice_loss 0.20557 +Epoch [646/4000] Validation [3/4] Loss: 0.18196 focal_loss 0.09144 dice_loss 0.09052 +Epoch [646/4000] Validation [4/4] Loss: 0.29960 focal_loss 0.17348 dice_loss 0.12612 +Epoch [646/4000] Validation metric {'Val/mean dice_metric': 0.9644647836685181, 'Val/mean miou_metric': 0.9426689147949219, 'Val/mean f1': 0.9685052633285522, 'Val/mean precision': 0.966832160949707, 'Val/mean recall': 0.9701842665672302, 'Val/mean hd95_metric': 6.329010009765625} +Cheakpoint... +Epoch [646/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644647836685181, 'Val/mean miou_metric': 0.9426689147949219, 'Val/mean f1': 0.9685052633285522, 'Val/mean precision': 0.966832160949707, 'Val/mean recall': 0.9701842665672302, 'Val/mean hd95_metric': 6.329010009765625} +Epoch [647/4000] Training [1/16] Loss: 0.01233 +Epoch [647/4000] Training [2/16] Loss: 0.01301 +Epoch [647/4000] Training [3/16] Loss: 0.01043 +Epoch [647/4000] Training [4/16] Loss: 0.01343 +Epoch [647/4000] Training [5/16] Loss: 0.01404 +Epoch [647/4000] Training [6/16] Loss: 0.01334 +Epoch [647/4000] Training [7/16] Loss: 0.01967 +Epoch [647/4000] Training [8/16] Loss: 0.01351 +Epoch [647/4000] Training [9/16] Loss: 0.01591 +Epoch [647/4000] Training [10/16] Loss: 0.01418 +Epoch [647/4000] Training [11/16] Loss: 0.01565 +Epoch [647/4000] Training [12/16] Loss: 0.01651 +Epoch [647/4000] Training [13/16] Loss: 0.02913 +Epoch [647/4000] Training [14/16] Loss: 0.01072 +Epoch [647/4000] Training [15/16] Loss: 0.01260 +Epoch [647/4000] Training [16/16] Loss: 0.02025 +Epoch [647/4000] Training metric {'Train/mean dice_metric': 0.9900290966033936, 'Train/mean miou_metric': 0.9800876379013062, 'Train/mean f1': 0.9869415163993835, 'Train/mean precision': 0.9825595021247864, 'Train/mean recall': 0.9913628101348877, 'Train/mean hd95_metric': 1.5523266792297363} +Epoch [647/4000] Validation [1/4] Loss: 0.28050 focal_loss 0.18725 dice_loss 0.09325 +Epoch [647/4000] Validation [2/4] Loss: 0.25233 focal_loss 0.12731 dice_loss 0.12502 +Epoch [647/4000] Validation [3/4] Loss: 0.13012 focal_loss 0.06793 dice_loss 0.06219 +Epoch [647/4000] Validation [4/4] Loss: 0.34081 focal_loss 0.18301 dice_loss 0.15780 +Epoch [647/4000] Validation metric {'Val/mean dice_metric': 0.965014636516571, 'Val/mean miou_metric': 0.9441295862197876, 'Val/mean f1': 0.9691044092178345, 'Val/mean precision': 0.966045081615448, 'Val/mean recall': 0.9721832275390625, 'Val/mean hd95_metric': 6.599325180053711} +Cheakpoint... +Epoch [647/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965014636516571, 'Val/mean miou_metric': 0.9441295862197876, 'Val/mean f1': 0.9691044092178345, 'Val/mean precision': 0.966045081615448, 'Val/mean recall': 0.9721832275390625, 'Val/mean hd95_metric': 6.599325180053711} +Epoch [648/4000] Training [1/16] Loss: 0.02470 +Epoch [648/4000] Training [2/16] Loss: 0.01337 +Epoch [648/4000] Training [3/16] Loss: 0.01348 +Epoch [648/4000] Training [4/16] Loss: 0.01436 +Epoch [648/4000] Training [5/16] Loss: 0.01220 +Epoch [648/4000] Training [6/16] Loss: 0.01331 +Epoch [648/4000] Training [7/16] Loss: 0.01536 +Epoch [648/4000] Training [8/16] Loss: 0.01419 +Epoch [648/4000] Training [9/16] Loss: 0.01619 +Epoch [648/4000] Training [10/16] Loss: 0.01841 +Epoch [648/4000] Training [11/16] Loss: 0.01265 +Epoch [648/4000] Training [12/16] Loss: 0.01339 +Epoch [648/4000] Training [13/16] Loss: 0.01031 +Epoch [648/4000] Training [14/16] Loss: 0.01550 +Epoch [648/4000] Training [15/16] Loss: 0.01361 +Epoch [648/4000] Training [16/16] Loss: 0.01276 +Epoch [648/4000] Training metric {'Train/mean dice_metric': 0.9896945953369141, 'Train/mean miou_metric': 0.9794229865074158, 'Train/mean f1': 0.9859170317649841, 'Train/mean precision': 0.9807523488998413, 'Train/mean recall': 0.9911364912986755, 'Train/mean hd95_metric': 1.396459937095642} +Epoch [648/4000] Validation [1/4] Loss: 0.19065 focal_loss 0.12773 dice_loss 0.06292 +Epoch [648/4000] Validation [2/4] Loss: 0.25724 focal_loss 0.12440 dice_loss 0.13284 +Epoch [648/4000] Validation [3/4] Loss: 0.18398 focal_loss 0.08875 dice_loss 0.09524 +Epoch [648/4000] Validation [4/4] Loss: 0.39941 focal_loss 0.24238 dice_loss 0.15704 +Epoch [648/4000] Validation metric {'Val/mean dice_metric': 0.9666654467582703, 'Val/mean miou_metric': 0.9443023800849915, 'Val/mean f1': 0.9682604670524597, 'Val/mean precision': 0.964451014995575, 'Val/mean recall': 0.9721002578735352, 'Val/mean hd95_metric': 6.340041637420654} +Cheakpoint... +Epoch [648/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666654467582703, 'Val/mean miou_metric': 0.9443023800849915, 'Val/mean f1': 0.9682604670524597, 'Val/mean precision': 0.964451014995575, 'Val/mean recall': 0.9721002578735352, 'Val/mean hd95_metric': 6.340041637420654} +Epoch [649/4000] Training [1/16] Loss: 0.01272 +Epoch [649/4000] Training [2/16] Loss: 0.01582 +Epoch [649/4000] Training [3/16] Loss: 0.01331 +Epoch [649/4000] Training [4/16] Loss: 0.01358 +Epoch [649/4000] Training [5/16] Loss: 0.01061 +Epoch [649/4000] Training [6/16] Loss: 0.02470 +Epoch [649/4000] Training [7/16] Loss: 0.01058 +Epoch [649/4000] Training [8/16] Loss: 0.01482 +Epoch [649/4000] Training [9/16] Loss: 0.01419 +Epoch [649/4000] Training [10/16] Loss: 0.01111 +Epoch [649/4000] Training [11/16] Loss: 0.02144 +Epoch [649/4000] Training [12/16] Loss: 0.01448 +Epoch [649/4000] Training [13/16] Loss: 0.01461 +Epoch [649/4000] Training [14/16] Loss: 0.01617 +Epoch [649/4000] Training [15/16] Loss: 0.02114 +Epoch [649/4000] Training [16/16] Loss: 0.01394 +Epoch [649/4000] Training metric {'Train/mean dice_metric': 0.9901271462440491, 'Train/mean miou_metric': 0.9802327156066895, 'Train/mean f1': 0.986472487449646, 'Train/mean precision': 0.9811444878578186, 'Train/mean recall': 0.9918586611747742, 'Train/mean hd95_metric': 1.2839150428771973} +Epoch [649/4000] Validation [1/4] Loss: 0.16383 focal_loss 0.10038 dice_loss 0.06344 +Epoch [649/4000] Validation [2/4] Loss: 0.24805 focal_loss 0.12180 dice_loss 0.12625 +Epoch [649/4000] Validation [3/4] Loss: 0.15660 focal_loss 0.07465 dice_loss 0.08195 +Epoch [649/4000] Validation [4/4] Loss: 0.27552 focal_loss 0.12770 dice_loss 0.14782 +Epoch [649/4000] Validation metric {'Val/mean dice_metric': 0.9659271240234375, 'Val/mean miou_metric': 0.9447148442268372, 'Val/mean f1': 0.9695018529891968, 'Val/mean precision': 0.9621934294700623, 'Val/mean recall': 0.9769221544265747, 'Val/mean hd95_metric': 6.995678901672363} +Cheakpoint... +Epoch [649/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659271240234375, 'Val/mean miou_metric': 0.9447148442268372, 'Val/mean f1': 0.9695018529891968, 'Val/mean precision': 0.9621934294700623, 'Val/mean recall': 0.9769221544265747, 'Val/mean hd95_metric': 6.995678901672363} +Epoch [650/4000] Training [1/16] Loss: 0.01309 +Epoch [650/4000] Training [2/16] Loss: 0.01734 +Epoch [650/4000] Training [3/16] Loss: 0.01969 +Epoch [650/4000] Training [4/16] Loss: 0.01422 +Epoch [650/4000] Training [5/16] Loss: 0.01095 +Epoch [650/4000] Training [6/16] Loss: 0.01731 +Epoch [650/4000] Training [7/16] Loss: 0.01444 +Epoch [650/4000] Training [8/16] Loss: 0.01205 +Epoch [650/4000] Training [9/16] Loss: 0.01319 +Epoch [650/4000] Training [10/16] Loss: 0.01762 +Epoch [650/4000] Training [11/16] Loss: 0.01568 +Epoch [650/4000] Training [12/16] Loss: 0.01485 +Epoch [650/4000] Training [13/16] Loss: 0.01240 +Epoch [650/4000] Training [14/16] Loss: 0.01901 +Epoch [650/4000] Training [15/16] Loss: 0.01529 +Epoch [650/4000] Training [16/16] Loss: 0.01577 +Epoch [650/4000] Training metric {'Train/mean dice_metric': 0.9894387125968933, 'Train/mean miou_metric': 0.9789376854896545, 'Train/mean f1': 0.9861053824424744, 'Train/mean precision': 0.9810299277305603, 'Train/mean recall': 0.9912336468696594, 'Train/mean hd95_metric': 1.3610308170318604} +Epoch [650/4000] Validation [1/4] Loss: 0.14048 focal_loss 0.08612 dice_loss 0.05436 +Epoch [650/4000] Validation [2/4] Loss: 0.25615 focal_loss 0.12857 dice_loss 0.12758 +Epoch [650/4000] Validation [3/4] Loss: 0.12697 focal_loss 0.06149 dice_loss 0.06548 +Epoch [650/4000] Validation [4/4] Loss: 0.26505 focal_loss 0.12628 dice_loss 0.13877 +Epoch [650/4000] Validation metric {'Val/mean dice_metric': 0.9652596712112427, 'Val/mean miou_metric': 0.9436155557632446, 'Val/mean f1': 0.9688212871551514, 'Val/mean precision': 0.963757336139679, 'Val/mean recall': 0.9739386439323425, 'Val/mean hd95_metric': 6.663496494293213} +Cheakpoint... +Epoch [650/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652596712112427, 'Val/mean miou_metric': 0.9436155557632446, 'Val/mean f1': 0.9688212871551514, 'Val/mean precision': 0.963757336139679, 'Val/mean recall': 0.9739386439323425, 'Val/mean hd95_metric': 6.663496494293213} +Epoch [651/4000] Training [1/16] Loss: 0.01365 +Epoch [651/4000] Training [2/16] Loss: 0.01226 +Epoch [651/4000] Training [3/16] Loss: 0.01400 +Epoch [651/4000] Training [4/16] Loss: 0.01377 +Epoch [651/4000] Training [5/16] Loss: 0.01275 +Epoch [651/4000] Training [6/16] Loss: 0.01396 +Epoch [651/4000] Training [7/16] Loss: 0.01333 +Epoch [651/4000] Training [8/16] Loss: 0.01155 +Epoch [651/4000] Training [9/16] Loss: 0.01405 +Epoch [651/4000] Training [10/16] Loss: 0.01291 +Epoch [651/4000] Training [11/16] Loss: 0.01336 +Epoch [651/4000] Training [12/16] Loss: 0.01366 +Epoch [651/4000] Training [13/16] Loss: 0.01228 +Epoch [651/4000] Training [14/16] Loss: 0.01166 +Epoch [651/4000] Training [15/16] Loss: 0.01382 +Epoch [651/4000] Training [16/16] Loss: 0.01284 +Epoch [651/4000] Training metric {'Train/mean dice_metric': 0.9908954501152039, 'Train/mean miou_metric': 0.9817368984222412, 'Train/mean f1': 0.9876789450645447, 'Train/mean precision': 0.9834265112876892, 'Train/mean recall': 0.9919682741165161, 'Train/mean hd95_metric': 1.179826021194458} +Epoch [651/4000] Validation [1/4] Loss: 0.17709 focal_loss 0.11131 dice_loss 0.06578 +Epoch [651/4000] Validation [2/4] Loss: 0.22751 focal_loss 0.10516 dice_loss 0.12234 +Epoch [651/4000] Validation [3/4] Loss: 0.14717 focal_loss 0.07078 dice_loss 0.07639 +Epoch [651/4000] Validation [4/4] Loss: 0.33972 focal_loss 0.17938 dice_loss 0.16035 +Epoch [651/4000] Validation metric {'Val/mean dice_metric': 0.9681495428085327, 'Val/mean miou_metric': 0.9474231600761414, 'Val/mean f1': 0.971010148525238, 'Val/mean precision': 0.963852047920227, 'Val/mean recall': 0.9782752990722656, 'Val/mean hd95_metric': 6.774658203125} +Cheakpoint... +Epoch [651/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681495428085327, 'Val/mean miou_metric': 0.9474231600761414, 'Val/mean f1': 0.971010148525238, 'Val/mean precision': 0.963852047920227, 'Val/mean recall': 0.9782752990722656, 'Val/mean hd95_metric': 6.774658203125} +Epoch [652/4000] Training [1/16] Loss: 0.01024 +Epoch [652/4000] Training [2/16] Loss: 0.01505 +Epoch [652/4000] Training [3/16] Loss: 0.01021 +Epoch [652/4000] Training [4/16] Loss: 0.01706 +Epoch [652/4000] Training [5/16] Loss: 0.01286 +Epoch [652/4000] Training [6/16] Loss: 0.01417 +Epoch [652/4000] Training [7/16] Loss: 0.01861 +Epoch [652/4000] Training [8/16] Loss: 0.03699 +Epoch [652/4000] Training [9/16] Loss: 0.01308 +Epoch [652/4000] Training [10/16] Loss: 0.01259 +Epoch [652/4000] Training [11/16] Loss: 0.01396 +Epoch [652/4000] Training [12/16] Loss: 0.01263 +Epoch [652/4000] Training [13/16] Loss: 0.01775 +Epoch [652/4000] Training [14/16] Loss: 0.01902 +Epoch [652/4000] Training [15/16] Loss: 0.01832 +Epoch [652/4000] Training [16/16] Loss: 0.01181 +Epoch [652/4000] Training metric {'Train/mean dice_metric': 0.9895097017288208, 'Train/mean miou_metric': 0.9791688919067383, 'Train/mean f1': 0.9867706298828125, 'Train/mean precision': 0.9824299812316895, 'Train/mean recall': 0.9911498427391052, 'Train/mean hd95_metric': 1.472103238105774} +Epoch [652/4000] Validation [1/4] Loss: 0.58297 focal_loss 0.44485 dice_loss 0.13812 +Epoch [652/4000] Validation [2/4] Loss: 0.19176 focal_loss 0.08643 dice_loss 0.10532 +Epoch [652/4000] Validation [3/4] Loss: 0.19138 focal_loss 0.09304 dice_loss 0.09834 +Epoch [652/4000] Validation [4/4] Loss: 0.32207 focal_loss 0.17252 dice_loss 0.14956 +Epoch [652/4000] Validation metric {'Val/mean dice_metric': 0.9657639265060425, 'Val/mean miou_metric': 0.9438735246658325, 'Val/mean f1': 0.9682268500328064, 'Val/mean precision': 0.9656495451927185, 'Val/mean recall': 0.9708181023597717, 'Val/mean hd95_metric': 6.273253440856934} +Cheakpoint... +Epoch [652/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9657639265060425, 'Val/mean miou_metric': 0.9438735246658325, 'Val/mean f1': 0.9682268500328064, 'Val/mean precision': 0.9656495451927185, 'Val/mean recall': 0.9708181023597717, 'Val/mean hd95_metric': 6.273253440856934} +Epoch [653/4000] Training [1/16] Loss: 0.01158 +Epoch [653/4000] Training [2/16] Loss: 0.01280 +Epoch [653/4000] Training [3/16] Loss: 0.01294 +Epoch [653/4000] Training [4/16] Loss: 0.01356 +Epoch [653/4000] Training [5/16] Loss: 0.01871 +Epoch [653/4000] Training [6/16] Loss: 0.01412 +Epoch [653/4000] Training [7/16] Loss: 0.01634 +Epoch [653/4000] Training [8/16] Loss: 0.01630 +Epoch [653/4000] Training [9/16] Loss: 0.01156 +Epoch [653/4000] Training [10/16] Loss: 0.00951 +Epoch [653/4000] Training [11/16] Loss: 0.01302 +Epoch [653/4000] Training [12/16] Loss: 0.01125 +Epoch [653/4000] Training [13/16] Loss: 0.01689 +Epoch [653/4000] Training [14/16] Loss: 0.01471 +Epoch [653/4000] Training [15/16] Loss: 0.01425 +Epoch [653/4000] Training [16/16] Loss: 0.01716 +Epoch [653/4000] Training metric {'Train/mean dice_metric': 0.9901953935623169, 'Train/mean miou_metric': 0.980414628982544, 'Train/mean f1': 0.987028956413269, 'Train/mean precision': 0.9822950959205627, 'Train/mean recall': 0.9918085932731628, 'Train/mean hd95_metric': 1.3417272567749023} +Epoch [653/4000] Validation [1/4] Loss: 0.53758 focal_loss 0.40837 dice_loss 0.12922 +Epoch [653/4000] Validation [2/4] Loss: 0.48719 focal_loss 0.24697 dice_loss 0.24022 +Epoch [653/4000] Validation [3/4] Loss: 0.14092 focal_loss 0.06630 dice_loss 0.07462 +Epoch [653/4000] Validation [4/4] Loss: 0.35881 focal_loss 0.19653 dice_loss 0.16228 +Epoch [653/4000] Validation metric {'Val/mean dice_metric': 0.9608948826789856, 'Val/mean miou_metric': 0.938456654548645, 'Val/mean f1': 0.9655458927154541, 'Val/mean precision': 0.9685565233230591, 'Val/mean recall': 0.9625539779663086, 'Val/mean hd95_metric': 6.813866138458252} +Cheakpoint... +Epoch [653/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9609], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608948826789856, 'Val/mean miou_metric': 0.938456654548645, 'Val/mean f1': 0.9655458927154541, 'Val/mean precision': 0.9685565233230591, 'Val/mean recall': 0.9625539779663086, 'Val/mean hd95_metric': 6.813866138458252} +Epoch [654/4000] Training [1/16] Loss: 0.01252 +Epoch [654/4000] Training [2/16] Loss: 0.01194 +Epoch [654/4000] Training [3/16] Loss: 0.01198 +Epoch [654/4000] Training [4/16] Loss: 0.01216 +Epoch [654/4000] Training [5/16] Loss: 0.02147 +Epoch [654/4000] Training [6/16] Loss: 0.01586 +Epoch [654/4000] Training [7/16] Loss: 0.01952 +Epoch [654/4000] Training [8/16] Loss: 0.01327 +Epoch [654/4000] Training [9/16] Loss: 0.01234 +Epoch [654/4000] Training [10/16] Loss: 0.01811 +Epoch [654/4000] Training [11/16] Loss: 0.01531 +Epoch [654/4000] Training [12/16] Loss: 0.04840 +Epoch [654/4000] Training [13/16] Loss: 0.01486 +Epoch [654/4000] Training [14/16] Loss: 0.01572 +Epoch [654/4000] Training [15/16] Loss: 0.01932 +Epoch [654/4000] Training [16/16] Loss: 0.01320 +Epoch [654/4000] Training metric {'Train/mean dice_metric': 0.986971378326416, 'Train/mean miou_metric': 0.9765181541442871, 'Train/mean f1': 0.9864117503166199, 'Train/mean precision': 0.9819758534431458, 'Train/mean recall': 0.9908878803253174, 'Train/mean hd95_metric': 1.721605896949768} +Epoch [654/4000] Validation [1/4] Loss: 0.16619 focal_loss 0.10340 dice_loss 0.06279 +Epoch [654/4000] Validation [2/4] Loss: 0.40472 focal_loss 0.20512 dice_loss 0.19960 +Epoch [654/4000] Validation [3/4] Loss: 0.21142 focal_loss 0.12098 dice_loss 0.09044 +Epoch [654/4000] Validation [4/4] Loss: 0.29704 focal_loss 0.14075 dice_loss 0.15629 +Epoch [654/4000] Validation metric {'Val/mean dice_metric': 0.963707447052002, 'Val/mean miou_metric': 0.9418390393257141, 'Val/mean f1': 0.9686779975891113, 'Val/mean precision': 0.9640993475914001, 'Val/mean recall': 0.9733002185821533, 'Val/mean hd95_metric': 6.995614051818848} +Cheakpoint... +Epoch [654/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963707447052002, 'Val/mean miou_metric': 0.9418390393257141, 'Val/mean f1': 0.9686779975891113, 'Val/mean precision': 0.9640993475914001, 'Val/mean recall': 0.9733002185821533, 'Val/mean hd95_metric': 6.995614051818848} +Epoch [655/4000] Training [1/16] Loss: 0.01582 +Epoch [655/4000] Training [2/16] Loss: 0.01234 +Epoch [655/4000] Training [3/16] Loss: 0.01758 +Epoch [655/4000] Training [4/16] Loss: 0.01610 +Epoch [655/4000] Training [5/16] Loss: 0.01427 +Epoch [655/4000] Training [6/16] Loss: 0.01536 +Epoch [655/4000] Training [7/16] Loss: 0.01382 +Epoch [655/4000] Training [8/16] Loss: 0.01744 +Epoch [655/4000] Training [9/16] Loss: 0.01217 +Epoch [655/4000] Training [10/16] Loss: 0.01335 +Epoch [655/4000] Training [11/16] Loss: 0.01828 +Epoch [655/4000] Training [12/16] Loss: 0.01717 +Epoch [655/4000] Training [13/16] Loss: 0.01502 +Epoch [655/4000] Training [14/16] Loss: 0.01439 +Epoch [655/4000] Training [15/16] Loss: 0.01326 +Epoch [655/4000] Training [16/16] Loss: 0.01409 +Epoch [655/4000] Training metric {'Train/mean dice_metric': 0.9881658554077148, 'Train/mean miou_metric': 0.9766252040863037, 'Train/mean f1': 0.9858880043029785, 'Train/mean precision': 0.9809679388999939, 'Train/mean recall': 0.9908576011657715, 'Train/mean hd95_metric': 2.697237253189087} +Epoch [655/4000] Validation [1/4] Loss: 0.42219 focal_loss 0.29197 dice_loss 0.13022 +Epoch [655/4000] Validation [2/4] Loss: 0.29884 focal_loss 0.14390 dice_loss 0.15494 +Epoch [655/4000] Validation [3/4] Loss: 0.18904 focal_loss 0.09140 dice_loss 0.09763 +Epoch [655/4000] Validation [4/4] Loss: 0.29046 focal_loss 0.16459 dice_loss 0.12586 +Epoch [655/4000] Validation metric {'Val/mean dice_metric': 0.961175799369812, 'Val/mean miou_metric': 0.9369128346443176, 'Val/mean f1': 0.9615557193756104, 'Val/mean precision': 0.9646986722946167, 'Val/mean recall': 0.9584330916404724, 'Val/mean hd95_metric': 7.810650825500488} +Cheakpoint... +Epoch [655/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961175799369812, 'Val/mean miou_metric': 0.9369128346443176, 'Val/mean f1': 0.9615557193756104, 'Val/mean precision': 0.9646986722946167, 'Val/mean recall': 0.9584330916404724, 'Val/mean hd95_metric': 7.810650825500488} +Epoch [656/4000] Training [1/16] Loss: 0.01649 +Epoch [656/4000] Training [2/16] Loss: 0.01149 +Epoch [656/4000] Training [3/16] Loss: 0.02011 +Epoch [656/4000] Training [4/16] Loss: 0.01293 +Epoch [656/4000] Training [5/16] Loss: 0.01396 +Epoch [656/4000] Training [6/16] Loss: 0.01656 +Epoch [656/4000] Training [7/16] Loss: 0.02114 +Epoch [656/4000] Training [8/16] Loss: 0.01562 +Epoch [656/4000] Training [9/16] Loss: 0.01618 +Epoch [656/4000] Training [10/16] Loss: 0.02007 +Epoch [656/4000] Training [11/16] Loss: 0.01986 +Epoch [656/4000] Training [12/16] Loss: 0.01480 +Epoch [656/4000] Training [13/16] Loss: 0.02203 +Epoch [656/4000] Training [14/16] Loss: 0.04078 +Epoch [656/4000] Training [15/16] Loss: 0.02032 +Epoch [656/4000] Training [16/16] Loss: 0.01666 +Epoch [656/4000] Training metric {'Train/mean dice_metric': 0.9865400791168213, 'Train/mean miou_metric': 0.9737138152122498, 'Train/mean f1': 0.9815982580184937, 'Train/mean precision': 0.9755066633224487, 'Train/mean recall': 0.987766444683075, 'Train/mean hd95_metric': 3.8723020553588867} +Epoch [656/4000] Validation [1/4] Loss: 0.14975 focal_loss 0.09066 dice_loss 0.05909 +Epoch [656/4000] Validation [2/4] Loss: 0.31541 focal_loss 0.13872 dice_loss 0.17669 +Epoch [656/4000] Validation [3/4] Loss: 0.23896 focal_loss 0.11540 dice_loss 0.12356 +Epoch [656/4000] Validation [4/4] Loss: 0.32952 focal_loss 0.17806 dice_loss 0.15146 +Epoch [656/4000] Validation metric {'Val/mean dice_metric': 0.9590330123901367, 'Val/mean miou_metric': 0.9348058700561523, 'Val/mean f1': 0.95987468957901, 'Val/mean precision': 0.9505251049995422, 'Val/mean recall': 0.969410240650177, 'Val/mean hd95_metric': 9.447239875793457} +Cheakpoint... +Epoch [656/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9590], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9590330123901367, 'Val/mean miou_metric': 0.9348058700561523, 'Val/mean f1': 0.95987468957901, 'Val/mean precision': 0.9505251049995422, 'Val/mean recall': 0.969410240650177, 'Val/mean hd95_metric': 9.447239875793457} +Epoch [657/4000] Training [1/16] Loss: 0.01431 +Epoch [657/4000] Training [2/16] Loss: 0.01742 +Epoch [657/4000] Training [3/16] Loss: 0.02771 +Epoch [657/4000] Training [4/16] Loss: 0.01633 +Epoch [657/4000] Training [5/16] Loss: 0.05540 +Epoch [657/4000] Training [6/16] Loss: 0.01471 +Epoch [657/4000] Training [7/16] Loss: 0.01891 +Epoch [657/4000] Training [8/16] Loss: 0.02438 +Epoch [657/4000] Training [9/16] Loss: 0.02023 +Epoch [657/4000] Training [10/16] Loss: 0.31394 +Epoch [657/4000] Training [11/16] Loss: 0.02960 +Epoch [657/4000] Training [12/16] Loss: 0.02071 +Epoch [657/4000] Training [13/16] Loss: 0.02264 +Epoch [657/4000] Training [14/16] Loss: 0.05970 +Epoch [657/4000] Training [15/16] Loss: 0.02140 +Epoch [657/4000] Training [16/16] Loss: 0.02035 +Epoch [657/4000] Training metric {'Train/mean dice_metric': 0.9822974801063538, 'Train/mean miou_metric': 0.9672961235046387, 'Train/mean f1': 0.9794102311134338, 'Train/mean precision': 0.9780351519584656, 'Train/mean recall': 0.9807892441749573, 'Train/mean hd95_metric': 3.6743664741516113} +Epoch [657/4000] Validation [1/4] Loss: 0.28689 focal_loss 0.18328 dice_loss 0.10361 +Epoch [657/4000] Validation [2/4] Loss: 0.43593 focal_loss 0.23009 dice_loss 0.20584 +Epoch [657/4000] Validation [3/4] Loss: 0.43280 focal_loss 0.27992 dice_loss 0.15289 +Epoch [657/4000] Validation [4/4] Loss: 0.56512 focal_loss 0.34037 dice_loss 0.22474 +Epoch [657/4000] Validation metric {'Val/mean dice_metric': 0.9517616033554077, 'Val/mean miou_metric': 0.9239429235458374, 'Val/mean f1': 0.9526201486587524, 'Val/mean precision': 0.9438946843147278, 'Val/mean recall': 0.961508572101593, 'Val/mean hd95_metric': 10.657130241394043} +Cheakpoint... +Epoch [657/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9518], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9517616033554077, 'Val/mean miou_metric': 0.9239429235458374, 'Val/mean f1': 0.9526201486587524, 'Val/mean precision': 0.9438946843147278, 'Val/mean recall': 0.961508572101593, 'Val/mean hd95_metric': 10.657130241394043} +Epoch [658/4000] Training [1/16] Loss: 0.01698 +Epoch [658/4000] Training [2/16] Loss: 0.02099 +Epoch [658/4000] Training [3/16] Loss: 0.02309 +Epoch [658/4000] Training [4/16] Loss: 0.01753 +Epoch [658/4000] Training [5/16] Loss: 0.01538 +Epoch [658/4000] Training [6/16] Loss: 0.01759 +Epoch [658/4000] Training [7/16] Loss: 0.03109 +Epoch [658/4000] Training [8/16] Loss: 0.01999 +Epoch [658/4000] Training [9/16] Loss: 0.01554 +Epoch [658/4000] Training [10/16] Loss: 0.01756 +Epoch [658/4000] Training [11/16] Loss: 0.02293 +Epoch [658/4000] Training [12/16] Loss: 0.08925 +Epoch [658/4000] Training [13/16] Loss: 0.02261 +Epoch [658/4000] Training [14/16] Loss: 0.02323 +Epoch [658/4000] Training [15/16] Loss: 0.02266 +Epoch [658/4000] Training [16/16] Loss: 0.01864 +Epoch [658/4000] Training metric {'Train/mean dice_metric': 0.984472393989563, 'Train/mean miou_metric': 0.9700686931610107, 'Train/mean f1': 0.9822037220001221, 'Train/mean precision': 0.9779769778251648, 'Train/mean recall': 0.9864671230316162, 'Train/mean hd95_metric': 3.3809242248535156} +Epoch [658/4000] Validation [1/4] Loss: 0.15692 focal_loss 0.09172 dice_loss 0.06520 +Epoch [658/4000] Validation [2/4] Loss: 0.52061 focal_loss 0.26118 dice_loss 0.25943 +Epoch [658/4000] Validation [3/4] Loss: 0.28585 focal_loss 0.14929 dice_loss 0.13656 +Epoch [658/4000] Validation [4/4] Loss: 0.32216 focal_loss 0.17191 dice_loss 0.15025 +Epoch [658/4000] Validation metric {'Val/mean dice_metric': 0.9537971615791321, 'Val/mean miou_metric': 0.926437258720398, 'Val/mean f1': 0.9555813074111938, 'Val/mean precision': 0.948279619216919, 'Val/mean recall': 0.9629963636398315, 'Val/mean hd95_metric': 9.722420692443848} +Cheakpoint... +Epoch [658/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9538], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9537971615791321, 'Val/mean miou_metric': 0.926437258720398, 'Val/mean f1': 0.9555813074111938, 'Val/mean precision': 0.948279619216919, 'Val/mean recall': 0.9629963636398315, 'Val/mean hd95_metric': 9.722420692443848} +Epoch [659/4000] Training [1/16] Loss: 0.01917 +Epoch [659/4000] Training [2/16] Loss: 0.02489 +Epoch [659/4000] Training [3/16] Loss: 0.03580 +Epoch [659/4000] Training [4/16] Loss: 0.01654 +Epoch [659/4000] Training [5/16] Loss: 0.02543 +Epoch [659/4000] Training [6/16] Loss: 0.01662 +Epoch [659/4000] Training [7/16] Loss: 0.01627 +Epoch [659/4000] Training [8/16] Loss: 0.02185 +Epoch [659/4000] Training [9/16] Loss: 0.07084 +Epoch [659/4000] Training [10/16] Loss: 0.01783 +Epoch [659/4000] Training [11/16] Loss: 0.01805 +Epoch [659/4000] Training [12/16] Loss: 0.01389 +Epoch [659/4000] Training [13/16] Loss: 0.01577 +Epoch [659/4000] Training [14/16] Loss: 0.01745 +Epoch [659/4000] Training [15/16] Loss: 0.01495 +Epoch [659/4000] Training [16/16] Loss: 0.02113 +Epoch [659/4000] Training metric {'Train/mean dice_metric': 0.9848477244377136, 'Train/mean miou_metric': 0.9706896543502808, 'Train/mean f1': 0.9816498756408691, 'Train/mean precision': 0.9774556756019592, 'Train/mean recall': 0.9858802556991577, 'Train/mean hd95_metric': 2.438157558441162} +Epoch [659/4000] Validation [1/4] Loss: 0.39299 focal_loss 0.25212 dice_loss 0.14087 +Epoch [659/4000] Validation [2/4] Loss: 0.49839 focal_loss 0.26092 dice_loss 0.23747 +Epoch [659/4000] Validation [3/4] Loss: 0.18962 focal_loss 0.09769 dice_loss 0.09193 +Epoch [659/4000] Validation [4/4] Loss: 0.24727 focal_loss 0.10232 dice_loss 0.14495 +Epoch [659/4000] Validation metric {'Val/mean dice_metric': 0.9577256441116333, 'Val/mean miou_metric': 0.9316068887710571, 'Val/mean f1': 0.9590534567832947, 'Val/mean precision': 0.9556881785392761, 'Val/mean recall': 0.9624426960945129, 'Val/mean hd95_metric': 8.201558113098145} +Cheakpoint... +Epoch [659/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9577], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9577256441116333, 'Val/mean miou_metric': 0.9316068887710571, 'Val/mean f1': 0.9590534567832947, 'Val/mean precision': 0.9556881785392761, 'Val/mean recall': 0.9624426960945129, 'Val/mean hd95_metric': 8.201558113098145} +Epoch [660/4000] Training [1/16] Loss: 0.03253 +Epoch [660/4000] Training [2/16] Loss: 0.01994 +Epoch [660/4000] Training [3/16] Loss: 0.01405 +Epoch [660/4000] Training [4/16] Loss: 0.02348 +Epoch [660/4000] Training [5/16] Loss: 0.01783 +Epoch [660/4000] Training [6/16] Loss: 0.01735 +Epoch [660/4000] Training [7/16] Loss: 0.02457 +Epoch [660/4000] Training [8/16] Loss: 0.01468 +Epoch [660/4000] Training [9/16] Loss: 0.01354 +Epoch [660/4000] Training [10/16] Loss: 0.02060 +Epoch [660/4000] Training [11/16] Loss: 0.01571 +Epoch [660/4000] Training [12/16] Loss: 0.01838 +Epoch [660/4000] Training [13/16] Loss: 0.01534 +Epoch [660/4000] Training [14/16] Loss: 0.01798 +Epoch [660/4000] Training [15/16] Loss: 0.01507 +Epoch [660/4000] Training [16/16] Loss: 0.02227 +Epoch [660/4000] Training metric {'Train/mean dice_metric': 0.987120509147644, 'Train/mean miou_metric': 0.9744864702224731, 'Train/mean f1': 0.9840559959411621, 'Train/mean precision': 0.9790837168693542, 'Train/mean recall': 0.9890789985656738, 'Train/mean hd95_metric': 2.002803087234497} +Epoch [660/4000] Validation [1/4] Loss: 0.24156 focal_loss 0.14437 dice_loss 0.09720 +Epoch [660/4000] Validation [2/4] Loss: 0.22423 focal_loss 0.09437 dice_loss 0.12986 +Epoch [660/4000] Validation [3/4] Loss: 0.21029 focal_loss 0.10911 dice_loss 0.10118 +Epoch [660/4000] Validation [4/4] Loss: 0.23295 focal_loss 0.12772 dice_loss 0.10522 +Epoch [660/4000] Validation metric {'Val/mean dice_metric': 0.9645225405693054, 'Val/mean miou_metric': 0.9400985836982727, 'Val/mean f1': 0.9638901352882385, 'Val/mean precision': 0.9574688076972961, 'Val/mean recall': 0.9703981876373291, 'Val/mean hd95_metric': 7.594553470611572} +Cheakpoint... +Epoch [660/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645225405693054, 'Val/mean miou_metric': 0.9400985836982727, 'Val/mean f1': 0.9638901352882385, 'Val/mean precision': 0.9574688076972961, 'Val/mean recall': 0.9703981876373291, 'Val/mean hd95_metric': 7.594553470611572} +Epoch [661/4000] Training [1/16] Loss: 0.01827 +Epoch [661/4000] Training [2/16] Loss: 0.01551 +Epoch [661/4000] Training [3/16] Loss: 0.01294 +Epoch [661/4000] Training [4/16] Loss: 0.03517 +Epoch [661/4000] Training [5/16] Loss: 0.01311 +Epoch [661/4000] Training [6/16] Loss: 0.01242 +Epoch [661/4000] Training [7/16] Loss: 0.01105 +Epoch [661/4000] Training [8/16] Loss: 0.01390 +Epoch [661/4000] Training [9/16] Loss: 0.01348 +Epoch [661/4000] Training [10/16] Loss: 0.01688 +Epoch [661/4000] Training [11/16] Loss: 0.01183 +Epoch [661/4000] Training [12/16] Loss: 0.01291 +Epoch [661/4000] Training [13/16] Loss: 0.02251 +Epoch [661/4000] Training [14/16] Loss: 0.02274 +Epoch [661/4000] Training [15/16] Loss: 0.01607 +Epoch [661/4000] Training [16/16] Loss: 0.01325 +Epoch [661/4000] Training metric {'Train/mean dice_metric': 0.988906979560852, 'Train/mean miou_metric': 0.9785386919975281, 'Train/mean f1': 0.986234724521637, 'Train/mean precision': 0.9819023609161377, 'Train/mean recall': 0.9906054735183716, 'Train/mean hd95_metric': 1.639556646347046} +Epoch [661/4000] Validation [1/4] Loss: 0.49861 focal_loss 0.37505 dice_loss 0.12356 +Epoch [661/4000] Validation [2/4] Loss: 0.43292 focal_loss 0.21152 dice_loss 0.22140 +Epoch [661/4000] Validation [3/4] Loss: 0.18605 focal_loss 0.09515 dice_loss 0.09090 +Epoch [661/4000] Validation [4/4] Loss: 0.26048 focal_loss 0.12693 dice_loss 0.13354 +Epoch [661/4000] Validation metric {'Val/mean dice_metric': 0.9639221429824829, 'Val/mean miou_metric': 0.9417510032653809, 'Val/mean f1': 0.9654272794723511, 'Val/mean precision': 0.9604470133781433, 'Val/mean recall': 0.9704594612121582, 'Val/mean hd95_metric': 7.270872592926025} +Cheakpoint... +Epoch [661/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639221429824829, 'Val/mean miou_metric': 0.9417510032653809, 'Val/mean f1': 0.9654272794723511, 'Val/mean precision': 0.9604470133781433, 'Val/mean recall': 0.9704594612121582, 'Val/mean hd95_metric': 7.270872592926025} +Epoch [662/4000] Training [1/16] Loss: 0.01540 +Epoch [662/4000] Training [2/16] Loss: 0.01220 +Epoch [662/4000] Training [3/16] Loss: 0.01502 +Epoch [662/4000] Training [4/16] Loss: 0.01339 +Epoch [662/4000] Training [5/16] Loss: 0.01208 +Epoch [662/4000] Training [6/16] Loss: 0.01550 +Epoch [662/4000] Training [7/16] Loss: 0.01393 +Epoch [662/4000] Training [8/16] Loss: 0.01217 +Epoch [662/4000] Training [9/16] Loss: 0.01335 +Epoch [662/4000] Training [10/16] Loss: 0.01304 +Epoch [662/4000] Training [11/16] Loss: 0.01631 +Epoch [662/4000] Training [12/16] Loss: 0.02487 +Epoch [662/4000] Training [13/16] Loss: 0.01741 +Epoch [662/4000] Training [14/16] Loss: 0.01394 +Epoch [662/4000] Training [15/16] Loss: 0.03068 +Epoch [662/4000] Training [16/16] Loss: 0.01590 +Epoch [662/4000] Training metric {'Train/mean dice_metric': 0.9883265495300293, 'Train/mean miou_metric': 0.9773974418640137, 'Train/mean f1': 0.9851803779602051, 'Train/mean precision': 0.9797272682189941, 'Train/mean recall': 0.9906944632530212, 'Train/mean hd95_metric': 1.7501676082611084} +Epoch [662/4000] Validation [1/4] Loss: 0.53060 focal_loss 0.39362 dice_loss 0.13698 +Epoch [662/4000] Validation [2/4] Loss: 0.20703 focal_loss 0.08093 dice_loss 0.12610 +Epoch [662/4000] Validation [3/4] Loss: 0.13891 focal_loss 0.06033 dice_loss 0.07858 +Epoch [662/4000] Validation [4/4] Loss: 0.33944 focal_loss 0.18185 dice_loss 0.15759 +Epoch [662/4000] Validation metric {'Val/mean dice_metric': 0.9626861810684204, 'Val/mean miou_metric': 0.9397827982902527, 'Val/mean f1': 0.9636425375938416, 'Val/mean precision': 0.9597161412239075, 'Val/mean recall': 0.9676012396812439, 'Val/mean hd95_metric': 7.541823387145996} +Cheakpoint... +Epoch [662/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9627], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9626861810684204, 'Val/mean miou_metric': 0.9397827982902527, 'Val/mean f1': 0.9636425375938416, 'Val/mean precision': 0.9597161412239075, 'Val/mean recall': 0.9676012396812439, 'Val/mean hd95_metric': 7.541823387145996} +Epoch [663/4000] Training [1/16] Loss: 0.02309 +Epoch [663/4000] Training [2/16] Loss: 0.01070 +Epoch [663/4000] Training [3/16] Loss: 0.01369 +Epoch [663/4000] Training [4/16] Loss: 0.01182 +Epoch [663/4000] Training [5/16] Loss: 0.01270 +Epoch [663/4000] Training [6/16] Loss: 0.01313 +Epoch [663/4000] Training [7/16] Loss: 0.01322 +Epoch [663/4000] Training [8/16] Loss: 0.02839 +Epoch [663/4000] Training [9/16] Loss: 0.02109 +Epoch [663/4000] Training [10/16] Loss: 0.02488 +Epoch [663/4000] Training [11/16] Loss: 0.01593 +Epoch [663/4000] Training [12/16] Loss: 0.01336 +Epoch [663/4000] Training [13/16] Loss: 0.01506 +Epoch [663/4000] Training [14/16] Loss: 0.01641 +Epoch [663/4000] Training [15/16] Loss: 0.01084 +Epoch [663/4000] Training [16/16] Loss: 0.01232 +Epoch [663/4000] Training metric {'Train/mean dice_metric': 0.9890421628952026, 'Train/mean miou_metric': 0.9783883094787598, 'Train/mean f1': 0.9862281084060669, 'Train/mean precision': 0.9819188117980957, 'Train/mean recall': 0.9905754327774048, 'Train/mean hd95_metric': 1.9966790676116943} +Epoch [663/4000] Validation [1/4] Loss: 0.45215 focal_loss 0.32691 dice_loss 0.12524 +Epoch [663/4000] Validation [2/4] Loss: 0.48233 focal_loss 0.23850 dice_loss 0.24383 +Epoch [663/4000] Validation [3/4] Loss: 0.16950 focal_loss 0.07211 dice_loss 0.09739 +Epoch [663/4000] Validation [4/4] Loss: 0.23113 focal_loss 0.10043 dice_loss 0.13070 +Epoch [663/4000] Validation metric {'Val/mean dice_metric': 0.9628473520278931, 'Val/mean miou_metric': 0.9401030540466309, 'Val/mean f1': 0.9645875692367554, 'Val/mean precision': 0.9620670676231384, 'Val/mean recall': 0.967121422290802, 'Val/mean hd95_metric': 7.353836536407471} +Cheakpoint... +Epoch [663/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9628], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9628473520278931, 'Val/mean miou_metric': 0.9401030540466309, 'Val/mean f1': 0.9645875692367554, 'Val/mean precision': 0.9620670676231384, 'Val/mean recall': 0.967121422290802, 'Val/mean hd95_metric': 7.353836536407471} +Epoch [664/4000] Training [1/16] Loss: 0.01520 +Epoch [664/4000] Training [2/16] Loss: 0.01328 +Epoch [664/4000] Training [3/16] Loss: 0.01081 +Epoch [664/4000] Training [4/16] Loss: 0.01700 +Epoch [664/4000] Training [5/16] Loss: 0.01548 +Epoch [664/4000] Training [6/16] Loss: 0.01687 +Epoch [664/4000] Training [7/16] Loss: 0.01025 +Epoch [664/4000] Training [8/16] Loss: 0.01233 +Epoch [664/4000] Training [9/16] Loss: 0.01372 +Epoch [664/4000] Training [10/16] Loss: 0.00902 +Epoch [664/4000] Training [11/16] Loss: 0.01439 +Epoch [664/4000] Training [12/16] Loss: 0.01292 +Epoch [664/4000] Training [13/16] Loss: 0.01146 +Epoch [664/4000] Training [14/16] Loss: 0.01199 +Epoch [664/4000] Training [15/16] Loss: 0.01744 +Epoch [664/4000] Training [16/16] Loss: 0.01197 +Epoch [664/4000] Training metric {'Train/mean dice_metric': 0.9903949499130249, 'Train/mean miou_metric': 0.981002926826477, 'Train/mean f1': 0.9870774149894714, 'Train/mean precision': 0.9819367527961731, 'Train/mean recall': 0.992272138595581, 'Train/mean hd95_metric': 1.7535645961761475} +Epoch [664/4000] Validation [1/4] Loss: 0.30036 focal_loss 0.18468 dice_loss 0.11568 +Epoch [664/4000] Validation [2/4] Loss: 0.22036 focal_loss 0.09574 dice_loss 0.12461 +Epoch [664/4000] Validation [3/4] Loss: 0.18855 focal_loss 0.07814 dice_loss 0.11041 +Epoch [664/4000] Validation [4/4] Loss: 0.30048 focal_loss 0.14102 dice_loss 0.15946 +Epoch [664/4000] Validation metric {'Val/mean dice_metric': 0.9654265642166138, 'Val/mean miou_metric': 0.9437580108642578, 'Val/mean f1': 0.9672238826751709, 'Val/mean precision': 0.9649918079376221, 'Val/mean recall': 0.9694661498069763, 'Val/mean hd95_metric': 6.664494514465332} +Cheakpoint... +Epoch [664/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654265642166138, 'Val/mean miou_metric': 0.9437580108642578, 'Val/mean f1': 0.9672238826751709, 'Val/mean precision': 0.9649918079376221, 'Val/mean recall': 0.9694661498069763, 'Val/mean hd95_metric': 6.664494514465332} +Epoch [665/4000] Training [1/16] Loss: 0.01952 +Epoch [665/4000] Training [2/16] Loss: 0.01122 +Epoch [665/4000] Training [3/16] Loss: 0.01144 +Epoch [665/4000] Training [4/16] Loss: 0.01067 +Epoch [665/4000] Training [5/16] Loss: 0.01556 +Epoch [665/4000] Training [6/16] Loss: 0.01358 +Epoch [665/4000] Training [7/16] Loss: 0.01349 +Epoch [665/4000] Training [8/16] Loss: 0.01296 +Epoch [665/4000] Training [9/16] Loss: 0.02858 +Epoch [665/4000] Training [10/16] Loss: 0.01455 +Epoch [665/4000] Training [11/16] Loss: 0.01205 +Epoch [665/4000] Training [12/16] Loss: 0.01089 +Epoch [665/4000] Training [13/16] Loss: 0.01120 +Epoch [665/4000] Training [14/16] Loss: 0.01349 +Epoch [665/4000] Training [15/16] Loss: 0.02382 +Epoch [665/4000] Training [16/16] Loss: 0.01669 +Epoch [665/4000] Training metric {'Train/mean dice_metric': 0.9888584017753601, 'Train/mean miou_metric': 0.9780730605125427, 'Train/mean f1': 0.9862606525421143, 'Train/mean precision': 0.9822772741317749, 'Train/mean recall': 0.9902765154838562, 'Train/mean hd95_metric': 1.773913860321045} +Epoch [665/4000] Validation [1/4] Loss: 0.16703 focal_loss 0.10271 dice_loss 0.06432 +Epoch [665/4000] Validation [2/4] Loss: 0.20660 focal_loss 0.09080 dice_loss 0.11580 +Epoch [665/4000] Validation [3/4] Loss: 0.23088 focal_loss 0.12763 dice_loss 0.10325 +Epoch [665/4000] Validation [4/4] Loss: 0.23247 focal_loss 0.09006 dice_loss 0.14241 +Epoch [665/4000] Validation metric {'Val/mean dice_metric': 0.967084527015686, 'Val/mean miou_metric': 0.9446414709091187, 'Val/mean f1': 0.9690486788749695, 'Val/mean precision': 0.9626643657684326, 'Val/mean recall': 0.9755182862281799, 'Val/mean hd95_metric': 7.3193254470825195} +Cheakpoint... +Epoch [665/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967084527015686, 'Val/mean miou_metric': 0.9446414709091187, 'Val/mean f1': 0.9690486788749695, 'Val/mean precision': 0.9626643657684326, 'Val/mean recall': 0.9755182862281799, 'Val/mean hd95_metric': 7.3193254470825195} +Epoch [666/4000] Training [1/16] Loss: 0.01745 +Epoch [666/4000] Training [2/16] Loss: 0.01217 +Epoch [666/4000] Training [3/16] Loss: 0.01315 +Epoch [666/4000] Training [4/16] Loss: 0.01030 +Epoch [666/4000] Training [5/16] Loss: 0.01277 +Epoch [666/4000] Training [6/16] Loss: 0.01318 +Epoch [666/4000] Training [7/16] Loss: 0.01445 +Epoch [666/4000] Training [8/16] Loss: 0.01126 +Epoch [666/4000] Training [9/16] Loss: 0.01119 +Epoch [666/4000] Training [10/16] Loss: 0.01255 +Epoch [666/4000] Training [11/16] Loss: 0.01617 +Epoch [666/4000] Training [12/16] Loss: 0.01528 +Epoch [666/4000] Training [13/16] Loss: 0.01574 +Epoch [666/4000] Training [14/16] Loss: 0.01333 +Epoch [666/4000] Training [15/16] Loss: 0.01364 +Epoch [666/4000] Training [16/16] Loss: 0.02131 +Epoch [666/4000] Training metric {'Train/mean dice_metric': 0.9904067516326904, 'Train/mean miou_metric': 0.9807645082473755, 'Train/mean f1': 0.9866079092025757, 'Train/mean precision': 0.9816597700119019, 'Train/mean recall': 0.9916061758995056, 'Train/mean hd95_metric': 1.3053689002990723} +Epoch [666/4000] Validation [1/4] Loss: 0.13969 focal_loss 0.08363 dice_loss 0.05605 +Epoch [666/4000] Validation [2/4] Loss: 0.33659 focal_loss 0.14877 dice_loss 0.18782 +Epoch [666/4000] Validation [3/4] Loss: 0.25142 focal_loss 0.14600 dice_loss 0.10542 +Epoch [666/4000] Validation [4/4] Loss: 0.30022 focal_loss 0.15204 dice_loss 0.14819 +Epoch [666/4000] Validation metric {'Val/mean dice_metric': 0.9675521850585938, 'Val/mean miou_metric': 0.946180522441864, 'Val/mean f1': 0.9682368636131287, 'Val/mean precision': 0.961228609085083, 'Val/mean recall': 0.9753481149673462, 'Val/mean hd95_metric': 6.7960205078125} +Cheakpoint... +Epoch [666/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675521850585938, 'Val/mean miou_metric': 0.946180522441864, 'Val/mean f1': 0.9682368636131287, 'Val/mean precision': 0.961228609085083, 'Val/mean recall': 0.9753481149673462, 'Val/mean hd95_metric': 6.7960205078125} +Epoch [667/4000] Training [1/16] Loss: 0.01306 +Epoch [667/4000] Training [2/16] Loss: 0.01333 +Epoch [667/4000] Training [3/16] Loss: 0.01569 +Epoch [667/4000] Training [4/16] Loss: 0.01085 +Epoch [667/4000] Training [5/16] Loss: 0.01349 +Epoch [667/4000] Training [6/16] Loss: 0.01289 +Epoch [667/4000] Training [7/16] Loss: 0.01286 +Epoch [667/4000] Training [8/16] Loss: 0.01485 +Epoch [667/4000] Training [9/16] Loss: 0.01265 +Epoch [667/4000] Training [10/16] Loss: 0.02140 +Epoch [667/4000] Training [11/16] Loss: 0.01011 +Epoch [667/4000] Training [12/16] Loss: 0.01480 +Epoch [667/4000] Training [13/16] Loss: 0.02016 +Epoch [667/4000] Training [14/16] Loss: 0.01274 +Epoch [667/4000] Training [15/16] Loss: 0.01289 +Epoch [667/4000] Training [16/16] Loss: 0.01521 +Epoch [667/4000] Training metric {'Train/mean dice_metric': 0.9906808137893677, 'Train/mean miou_metric': 0.9813303351402283, 'Train/mean f1': 0.9873921871185303, 'Train/mean precision': 0.9829628467559814, 'Train/mean recall': 0.9918614625930786, 'Train/mean hd95_metric': 1.261605143547058} +Epoch [667/4000] Validation [1/4] Loss: 0.21069 focal_loss 0.13369 dice_loss 0.07700 +Epoch [667/4000] Validation [2/4] Loss: 0.29076 focal_loss 0.12349 dice_loss 0.16726 +Epoch [667/4000] Validation [3/4] Loss: 0.21064 focal_loss 0.12289 dice_loss 0.08775 +Epoch [667/4000] Validation [4/4] Loss: 0.21139 focal_loss 0.10182 dice_loss 0.10957 +Epoch [667/4000] Validation metric {'Val/mean dice_metric': 0.9672091603279114, 'Val/mean miou_metric': 0.9465022087097168, 'Val/mean f1': 0.9694008827209473, 'Val/mean precision': 0.9630041718482971, 'Val/mean recall': 0.9758830070495605, 'Val/mean hd95_metric': 6.308897495269775} +Cheakpoint... +Epoch [667/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672091603279114, 'Val/mean miou_metric': 0.9465022087097168, 'Val/mean f1': 0.9694008827209473, 'Val/mean precision': 0.9630041718482971, 'Val/mean recall': 0.9758830070495605, 'Val/mean hd95_metric': 6.308897495269775} +Epoch [668/4000] Training [1/16] Loss: 0.01269 +Epoch [668/4000] Training [2/16] Loss: 0.01156 +Epoch [668/4000] Training [3/16] Loss: 0.01162 +Epoch [668/4000] Training [4/16] Loss: 0.02014 +Epoch [668/4000] Training [5/16] Loss: 0.01305 +Epoch [668/4000] Training [6/16] Loss: 0.01702 +Epoch [668/4000] Training [7/16] Loss: 0.01257 +Epoch [668/4000] Training [8/16] Loss: 0.01497 +Epoch [668/4000] Training [9/16] Loss: 0.01496 +Epoch [668/4000] Training [10/16] Loss: 0.01127 +Epoch [668/4000] Training [11/16] Loss: 0.01364 +Epoch [668/4000] Training [12/16] Loss: 0.01283 +Epoch [668/4000] Training [13/16] Loss: 0.01027 +Epoch [668/4000] Training [14/16] Loss: 0.01160 +Epoch [668/4000] Training [15/16] Loss: 0.01369 +Epoch [668/4000] Training [16/16] Loss: 0.01060 +Epoch [668/4000] Training metric {'Train/mean dice_metric': 0.9904868602752686, 'Train/mean miou_metric': 0.9809914231300354, 'Train/mean f1': 0.9873793125152588, 'Train/mean precision': 0.9826619029045105, 'Train/mean recall': 0.9921422600746155, 'Train/mean hd95_metric': 1.3687336444854736} +Epoch [668/4000] Validation [1/4] Loss: 0.24770 focal_loss 0.16443 dice_loss 0.08327 +Epoch [668/4000] Validation [2/4] Loss: 0.23823 focal_loss 0.11917 dice_loss 0.11906 +Epoch [668/4000] Validation [3/4] Loss: 0.20173 focal_loss 0.11497 dice_loss 0.08676 +Epoch [668/4000] Validation [4/4] Loss: 0.29071 focal_loss 0.15191 dice_loss 0.13880 +Epoch [668/4000] Validation metric {'Val/mean dice_metric': 0.9680309295654297, 'Val/mean miou_metric': 0.9472675323486328, 'Val/mean f1': 0.9697805047035217, 'Val/mean precision': 0.9657236933708191, 'Val/mean recall': 0.9738715291023254, 'Val/mean hd95_metric': 5.972543239593506} +Cheakpoint... +Epoch [668/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680309295654297, 'Val/mean miou_metric': 0.9472675323486328, 'Val/mean f1': 0.9697805047035217, 'Val/mean precision': 0.9657236933708191, 'Val/mean recall': 0.9738715291023254, 'Val/mean hd95_metric': 5.972543239593506} +Epoch [669/4000] Training [1/16] Loss: 0.01135 +Epoch [669/4000] Training [2/16] Loss: 0.01262 +Epoch [669/4000] Training [3/16] Loss: 0.01395 +Epoch [669/4000] Training [4/16] Loss: 0.01081 +Epoch [669/4000] Training [5/16] Loss: 0.01094 +Epoch [669/4000] Training [6/16] Loss: 0.01424 +Epoch [669/4000] Training [7/16] Loss: 0.01196 +Epoch [669/4000] Training [8/16] Loss: 0.01276 +Epoch [669/4000] Training [9/16] Loss: 0.01243 +Epoch [669/4000] Training [10/16] Loss: 0.01277 +Epoch [669/4000] Training [11/16] Loss: 0.01481 +Epoch [669/4000] Training [12/16] Loss: 0.01393 +Epoch [669/4000] Training [13/16] Loss: 0.01530 +Epoch [669/4000] Training [14/16] Loss: 0.01387 +Epoch [669/4000] Training [15/16] Loss: 0.00961 +Epoch [669/4000] Training [16/16] Loss: 0.01176 +Epoch [669/4000] Training metric {'Train/mean dice_metric': 0.9913543462753296, 'Train/mean miou_metric': 0.9826154708862305, 'Train/mean f1': 0.9871984124183655, 'Train/mean precision': 0.9821979999542236, 'Train/mean recall': 0.9922499656677246, 'Train/mean hd95_metric': 1.2392072677612305} +Epoch [669/4000] Validation [1/4] Loss: 0.18989 focal_loss 0.11691 dice_loss 0.07298 +Epoch [669/4000] Validation [2/4] Loss: 0.47451 focal_loss 0.26361 dice_loss 0.21090 +Epoch [669/4000] Validation [3/4] Loss: 0.10856 focal_loss 0.05339 dice_loss 0.05517 +Epoch [669/4000] Validation [4/4] Loss: 0.28638 focal_loss 0.15315 dice_loss 0.13324 +Epoch [669/4000] Validation metric {'Val/mean dice_metric': 0.9684937596321106, 'Val/mean miou_metric': 0.9486058950424194, 'Val/mean f1': 0.9698292016983032, 'Val/mean precision': 0.9654784202575684, 'Val/mean recall': 0.9742193222045898, 'Val/mean hd95_metric': 5.86870813369751} +Cheakpoint... +Epoch [669/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684937596321106, 'Val/mean miou_metric': 0.9486058950424194, 'Val/mean f1': 0.9698292016983032, 'Val/mean precision': 0.9654784202575684, 'Val/mean recall': 0.9742193222045898, 'Val/mean hd95_metric': 5.86870813369751} +Epoch [670/4000] Training [1/16] Loss: 0.01326 +Epoch [670/4000] Training [2/16] Loss: 0.02008 +Epoch [670/4000] Training [3/16] Loss: 0.01025 +Epoch [670/4000] Training [4/16] Loss: 0.01718 +Epoch [670/4000] Training [5/16] Loss: 0.01348 +Epoch [670/4000] Training [6/16] Loss: 0.01272 +Epoch [670/4000] Training [7/16] Loss: 0.01286 +Epoch [670/4000] Training [8/16] Loss: 0.03193 +Epoch [670/4000] Training [9/16] Loss: 0.01404 +Epoch [670/4000] Training [10/16] Loss: 0.01760 +Epoch [670/4000] Training [11/16] Loss: 0.01236 +Epoch [670/4000] Training [12/16] Loss: 0.01352 +Epoch [670/4000] Training [13/16] Loss: 0.01260 +Epoch [670/4000] Training [14/16] Loss: 0.01195 +Epoch [670/4000] Training [15/16] Loss: 0.01438 +Epoch [670/4000] Training [16/16] Loss: 0.01461 +Epoch [670/4000] Training metric {'Train/mean dice_metric': 0.9897364377975464, 'Train/mean miou_metric': 0.9796344637870789, 'Train/mean f1': 0.986954391002655, 'Train/mean precision': 0.982168436050415, 'Train/mean recall': 0.9917871952056885, 'Train/mean hd95_metric': 1.5625181198120117} +Epoch [670/4000] Validation [1/4] Loss: 0.23943 focal_loss 0.15165 dice_loss 0.08778 +Epoch [670/4000] Validation [2/4] Loss: 0.21944 focal_loss 0.09724 dice_loss 0.12221 +Epoch [670/4000] Validation [3/4] Loss: 0.10912 focal_loss 0.05501 dice_loss 0.05411 +Epoch [670/4000] Validation [4/4] Loss: 0.31031 focal_loss 0.16206 dice_loss 0.14825 +Epoch [670/4000] Validation metric {'Val/mean dice_metric': 0.9667461514472961, 'Val/mean miou_metric': 0.9447747468948364, 'Val/mean f1': 0.9680948853492737, 'Val/mean precision': 0.9636247158050537, 'Val/mean recall': 0.9726067185401917, 'Val/mean hd95_metric': 6.2946600914001465} +Cheakpoint... +Epoch [670/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667461514472961, 'Val/mean miou_metric': 0.9447747468948364, 'Val/mean f1': 0.9680948853492737, 'Val/mean precision': 0.9636247158050537, 'Val/mean recall': 0.9726067185401917, 'Val/mean hd95_metric': 6.2946600914001465} +Epoch [671/4000] Training [1/16] Loss: 0.01669 +Epoch [671/4000] Training [2/16] Loss: 0.01243 +Epoch [671/4000] Training [3/16] Loss: 0.01542 +Epoch [671/4000] Training [4/16] Loss: 0.01240 +Epoch [671/4000] Training [5/16] Loss: 0.01251 +Epoch [671/4000] Training [6/16] Loss: 0.01240 +Epoch [671/4000] Training [7/16] Loss: 0.01457 +Epoch [671/4000] Training [8/16] Loss: 0.01772 +Epoch [671/4000] Training [9/16] Loss: 0.01182 +Epoch [671/4000] Training [10/16] Loss: 0.01428 +Epoch [671/4000] Training [11/16] Loss: 0.01739 +Epoch [671/4000] Training [12/16] Loss: 0.01084 +Epoch [671/4000] Training [13/16] Loss: 0.01548 +Epoch [671/4000] Training [14/16] Loss: 0.01497 +Epoch [671/4000] Training [15/16] Loss: 0.00879 +Epoch [671/4000] Training [16/16] Loss: 0.01797 +Epoch [671/4000] Training metric {'Train/mean dice_metric': 0.9902923107147217, 'Train/mean miou_metric': 0.9805691242218018, 'Train/mean f1': 0.9875370264053345, 'Train/mean precision': 0.9829210042953491, 'Train/mean recall': 0.9921965599060059, 'Train/mean hd95_metric': 1.2632567882537842} +Epoch [671/4000] Validation [1/4] Loss: 0.24133 focal_loss 0.15872 dice_loss 0.08261 +Epoch [671/4000] Validation [2/4] Loss: 0.37894 focal_loss 0.18540 dice_loss 0.19354 +Epoch [671/4000] Validation [3/4] Loss: 0.12573 focal_loss 0.06975 dice_loss 0.05597 +Epoch [671/4000] Validation [4/4] Loss: 0.35788 focal_loss 0.18349 dice_loss 0.17439 +Epoch [671/4000] Validation metric {'Val/mean dice_metric': 0.9661878347396851, 'Val/mean miou_metric': 0.944973349571228, 'Val/mean f1': 0.9686235189437866, 'Val/mean precision': 0.962908148765564, 'Val/mean recall': 0.9744070768356323, 'Val/mean hd95_metric': 7.065797328948975} +Cheakpoint... +Epoch [671/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661878347396851, 'Val/mean miou_metric': 0.944973349571228, 'Val/mean f1': 0.9686235189437866, 'Val/mean precision': 0.962908148765564, 'Val/mean recall': 0.9744070768356323, 'Val/mean hd95_metric': 7.065797328948975} +Epoch [672/4000] Training [1/16] Loss: 0.01644 +Epoch [672/4000] Training [2/16] Loss: 0.01366 +Epoch [672/4000] Training [3/16] Loss: 0.01609 +Epoch [672/4000] Training [4/16] Loss: 0.01421 +Epoch [672/4000] Training [5/16] Loss: 0.01093 +Epoch [672/4000] Training [6/16] Loss: 0.01498 +Epoch [672/4000] Training [7/16] Loss: 0.01238 +Epoch [672/4000] Training [8/16] Loss: 0.01560 +Epoch [672/4000] Training [9/16] Loss: 0.01340 +Epoch [672/4000] Training [10/16] Loss: 0.01380 +Epoch [672/4000] Training [11/16] Loss: 0.01430 +Epoch [672/4000] Training [12/16] Loss: 0.01215 +Epoch [672/4000] Training [13/16] Loss: 0.01819 +Epoch [672/4000] Training [14/16] Loss: 0.01042 +Epoch [672/4000] Training [15/16] Loss: 0.02116 +Epoch [672/4000] Training [16/16] Loss: 0.01747 +Epoch [672/4000] Training metric {'Train/mean dice_metric': 0.9886367321014404, 'Train/mean miou_metric': 0.9778558015823364, 'Train/mean f1': 0.9867917895317078, 'Train/mean precision': 0.9823331832885742, 'Train/mean recall': 0.9912909865379333, 'Train/mean hd95_metric': 1.5593855381011963} +Epoch [672/4000] Validation [1/4] Loss: 0.14226 focal_loss 0.08084 dice_loss 0.06143 +Epoch [672/4000] Validation [2/4] Loss: 0.19860 focal_loss 0.09358 dice_loss 0.10502 +Epoch [672/4000] Validation [3/4] Loss: 0.13776 focal_loss 0.07797 dice_loss 0.05979 +Epoch [672/4000] Validation [4/4] Loss: 0.32274 focal_loss 0.17580 dice_loss 0.14694 +Epoch [672/4000] Validation metric {'Val/mean dice_metric': 0.9669944643974304, 'Val/mean miou_metric': 0.9449707269668579, 'Val/mean f1': 0.9688581228256226, 'Val/mean precision': 0.9619450569152832, 'Val/mean recall': 0.9758712649345398, 'Val/mean hd95_metric': 6.045567989349365} +Cheakpoint... +Epoch [672/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669944643974304, 'Val/mean miou_metric': 0.9449707269668579, 'Val/mean f1': 0.9688581228256226, 'Val/mean precision': 0.9619450569152832, 'Val/mean recall': 0.9758712649345398, 'Val/mean hd95_metric': 6.045567989349365} +Epoch [673/4000] Training [1/16] Loss: 0.01606 +Epoch [673/4000] Training [2/16] Loss: 0.02459 +Epoch [673/4000] Training [3/16] Loss: 0.01575 +Epoch [673/4000] Training [4/16] Loss: 0.01279 +Epoch [673/4000] Training [5/16] Loss: 0.01242 +Epoch [673/4000] Training [6/16] Loss: 0.02164 +Epoch [673/4000] Training [7/16] Loss: 0.01309 +Epoch [673/4000] Training [8/16] Loss: 0.01411 +Epoch [673/4000] Training [9/16] Loss: 0.01480 +Epoch [673/4000] Training [10/16] Loss: 0.01327 +Epoch [673/4000] Training [11/16] Loss: 0.01667 +Epoch [673/4000] Training [12/16] Loss: 0.01551 +Epoch [673/4000] Training [13/16] Loss: 0.01513 +Epoch [673/4000] Training [14/16] Loss: 0.01503 +Epoch [673/4000] Training [15/16] Loss: 0.01522 +Epoch [673/4000] Training [16/16] Loss: 0.02061 +Epoch [673/4000] Training metric {'Train/mean dice_metric': 0.9884228706359863, 'Train/mean miou_metric': 0.9773778915405273, 'Train/mean f1': 0.9860350489616394, 'Train/mean precision': 0.9819566607475281, 'Train/mean recall': 0.9901475310325623, 'Train/mean hd95_metric': 1.820664405822754} +Epoch [673/4000] Validation [1/4] Loss: 0.38355 focal_loss 0.26828 dice_loss 0.11527 +Epoch [673/4000] Validation [2/4] Loss: 0.22504 focal_loss 0.10155 dice_loss 0.12349 +Epoch [673/4000] Validation [3/4] Loss: 0.12215 focal_loss 0.06035 dice_loss 0.06180 +Epoch [673/4000] Validation [4/4] Loss: 0.29337 focal_loss 0.16806 dice_loss 0.12531 +Epoch [673/4000] Validation metric {'Val/mean dice_metric': 0.9645596742630005, 'Val/mean miou_metric': 0.9415748715400696, 'Val/mean f1': 0.9653587937355042, 'Val/mean precision': 0.96628338098526, 'Val/mean recall': 0.964435875415802, 'Val/mean hd95_metric': 6.409071922302246} +Cheakpoint... +Epoch [673/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9646], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645596742630005, 'Val/mean miou_metric': 0.9415748715400696, 'Val/mean f1': 0.9653587937355042, 'Val/mean precision': 0.96628338098526, 'Val/mean recall': 0.964435875415802, 'Val/mean hd95_metric': 6.409071922302246} +Epoch [674/4000] Training [1/16] Loss: 0.02907 +Epoch [674/4000] Training [2/16] Loss: 0.01377 +Epoch [674/4000] Training [3/16] Loss: 0.02192 +Epoch [674/4000] Training [4/16] Loss: 0.01221 +Epoch [674/4000] Training [5/16] Loss: 0.01664 +Epoch [674/4000] Training [6/16] Loss: 0.01697 +Epoch [674/4000] Training [7/16] Loss: 0.01664 +Epoch [674/4000] Training [8/16] Loss: 0.01841 +Epoch [674/4000] Training [9/16] Loss: 0.02008 +Epoch [674/4000] Training [10/16] Loss: 0.01451 +Epoch [674/4000] Training [11/16] Loss: 0.01412 +Epoch [674/4000] Training [12/16] Loss: 0.01620 +Epoch [674/4000] Training [13/16] Loss: 0.01309 +Epoch [674/4000] Training [14/16] Loss: 0.01476 +Epoch [674/4000] Training [15/16] Loss: 0.01423 +Epoch [674/4000] Training [16/16] Loss: 0.01294 +Epoch [674/4000] Training metric {'Train/mean dice_metric': 0.9891613721847534, 'Train/mean miou_metric': 0.9783824682235718, 'Train/mean f1': 0.9858883619308472, 'Train/mean precision': 0.9813185930252075, 'Train/mean recall': 0.9905009269714355, 'Train/mean hd95_metric': 2.1770591735839844} +Epoch [674/4000] Validation [1/4] Loss: 0.43667 focal_loss 0.32036 dice_loss 0.11631 +Epoch [674/4000] Validation [2/4] Loss: 0.16707 focal_loss 0.06748 dice_loss 0.09959 +Epoch [674/4000] Validation [3/4] Loss: 0.16483 focal_loss 0.08747 dice_loss 0.07736 +Epoch [674/4000] Validation [4/4] Loss: 0.27172 focal_loss 0.14378 dice_loss 0.12794 +Epoch [674/4000] Validation metric {'Val/mean dice_metric': 0.9653114080429077, 'Val/mean miou_metric': 0.9427629709243774, 'Val/mean f1': 0.9658874869346619, 'Val/mean precision': 0.9609379768371582, 'Val/mean recall': 0.9708882570266724, 'Val/mean hd95_metric': 7.293404579162598} +Cheakpoint... +Epoch [674/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653114080429077, 'Val/mean miou_metric': 0.9427629709243774, 'Val/mean f1': 0.9658874869346619, 'Val/mean precision': 0.9609379768371582, 'Val/mean recall': 0.9708882570266724, 'Val/mean hd95_metric': 7.293404579162598} +Epoch [675/4000] Training [1/16] Loss: 0.01595 +Epoch [675/4000] Training [2/16] Loss: 0.01365 +Epoch [675/4000] Training [3/16] Loss: 0.01093 +Epoch [675/4000] Training [4/16] Loss: 0.01389 +Epoch [675/4000] Training [5/16] Loss: 0.01024 +Epoch [675/4000] Training [6/16] Loss: 0.01435 +Epoch [675/4000] Training [7/16] Loss: 0.01404 +Epoch [675/4000] Training [8/16] Loss: 0.01484 +Epoch [675/4000] Training [9/16] Loss: 0.01871 +Epoch [675/4000] Training [10/16] Loss: 0.03017 +Epoch [675/4000] Training [11/16] Loss: 0.01472 +Epoch [675/4000] Training [12/16] Loss: 0.01270 +Epoch [675/4000] Training [13/16] Loss: 0.01111 +Epoch [675/4000] Training [14/16] Loss: 0.01299 +Epoch [675/4000] Training [15/16] Loss: 0.01726 +Epoch [675/4000] Training [16/16] Loss: 0.01150 +Epoch [675/4000] Training metric {'Train/mean dice_metric': 0.9902468919754028, 'Train/mean miou_metric': 0.9805123805999756, 'Train/mean f1': 0.986678957939148, 'Train/mean precision': 0.981663167476654, 'Train/mean recall': 0.9917462468147278, 'Train/mean hd95_metric': 1.5310194492340088} +Epoch [675/4000] Validation [1/4] Loss: 0.15382 focal_loss 0.08986 dice_loss 0.06396 +Epoch [675/4000] Validation [2/4] Loss: 0.29774 focal_loss 0.14395 dice_loss 0.15379 +Epoch [675/4000] Validation [3/4] Loss: 0.23812 focal_loss 0.13456 dice_loss 0.10356 +Epoch [675/4000] Validation [4/4] Loss: 0.32114 focal_loss 0.15884 dice_loss 0.16229 +Epoch [675/4000] Validation metric {'Val/mean dice_metric': 0.9656219482421875, 'Val/mean miou_metric': 0.9431082606315613, 'Val/mean f1': 0.9659571647644043, 'Val/mean precision': 0.9551136493682861, 'Val/mean recall': 0.977049708366394, 'Val/mean hd95_metric': 7.396570682525635} +Cheakpoint... +Epoch [675/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656219482421875, 'Val/mean miou_metric': 0.9431082606315613, 'Val/mean f1': 0.9659571647644043, 'Val/mean precision': 0.9551136493682861, 'Val/mean recall': 0.977049708366394, 'Val/mean hd95_metric': 7.396570682525635} +Epoch [676/4000] Training [1/16] Loss: 0.01547 +Epoch [676/4000] Training [2/16] Loss: 0.02484 +Epoch [676/4000] Training [3/16] Loss: 0.01399 +Epoch [676/4000] Training [4/16] Loss: 0.01119 +Epoch [676/4000] Training [5/16] Loss: 0.01500 +Epoch [676/4000] Training [6/16] Loss: 0.01461 +Epoch [676/4000] Training [7/16] Loss: 0.01423 +Epoch [676/4000] Training [8/16] Loss: 0.01969 +Epoch [676/4000] Training [9/16] Loss: 0.01515 +Epoch [676/4000] Training [10/16] Loss: 0.01219 +Epoch [676/4000] Training [11/16] Loss: 0.01150 +Epoch [676/4000] Training [12/16] Loss: 0.01438 +Epoch [676/4000] Training [13/16] Loss: 0.01101 +Epoch [676/4000] Training [14/16] Loss: 0.02002 +Epoch [676/4000] Training [15/16] Loss: 0.01289 +Epoch [676/4000] Training [16/16] Loss: 0.01261 +Epoch [676/4000] Training metric {'Train/mean dice_metric': 0.9897254109382629, 'Train/mean miou_metric': 0.9795212745666504, 'Train/mean f1': 0.9871065020561218, 'Train/mean precision': 0.9828258752822876, 'Train/mean recall': 0.9914245009422302, 'Train/mean hd95_metric': 2.1076714992523193} +Epoch [676/4000] Validation [1/4] Loss: 0.22231 focal_loss 0.13289 dice_loss 0.08942 +Epoch [676/4000] Validation [2/4] Loss: 0.58232 focal_loss 0.31348 dice_loss 0.26884 +Epoch [676/4000] Validation [3/4] Loss: 0.17894 focal_loss 0.10191 dice_loss 0.07703 +Epoch [676/4000] Validation [4/4] Loss: 0.34069 focal_loss 0.18833 dice_loss 0.15236 +Epoch [676/4000] Validation metric {'Val/mean dice_metric': 0.9639118909835815, 'Val/mean miou_metric': 0.9415801167488098, 'Val/mean f1': 0.966076135635376, 'Val/mean precision': 0.9616732001304626, 'Val/mean recall': 0.9705196022987366, 'Val/mean hd95_metric': 7.164088249206543} +Cheakpoint... +Epoch [676/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639118909835815, 'Val/mean miou_metric': 0.9415801167488098, 'Val/mean f1': 0.966076135635376, 'Val/mean precision': 0.9616732001304626, 'Val/mean recall': 0.9705196022987366, 'Val/mean hd95_metric': 7.164088249206543} +Epoch [677/4000] Training [1/16] Loss: 0.01633 +Epoch [677/4000] Training [2/16] Loss: 0.01606 +Epoch [677/4000] Training [3/16] Loss: 0.01434 +Epoch [677/4000] Training [4/16] Loss: 0.01058 +Epoch [677/4000] Training [5/16] Loss: 0.01694 +Epoch [677/4000] Training [6/16] Loss: 0.01592 +Epoch [677/4000] Training [7/16] Loss: 0.02631 +Epoch [677/4000] Training [8/16] Loss: 0.01175 +Epoch [677/4000] Training [9/16] Loss: 0.01692 +Epoch [677/4000] Training [10/16] Loss: 0.01697 +Epoch [677/4000] Training [11/16] Loss: 0.01342 +Epoch [677/4000] Training [12/16] Loss: 0.01432 +Epoch [677/4000] Training [13/16] Loss: 0.01217 +Epoch [677/4000] Training [14/16] Loss: 0.01483 +Epoch [677/4000] Training [15/16] Loss: 0.01478 +Epoch [677/4000] Training [16/16] Loss: 0.01381 +Epoch [677/4000] Training metric {'Train/mean dice_metric': 0.9894334077835083, 'Train/mean miou_metric': 0.9789724349975586, 'Train/mean f1': 0.9864736795425415, 'Train/mean precision': 0.9818485975265503, 'Train/mean recall': 0.9911425113677979, 'Train/mean hd95_metric': 1.4992656707763672} +Epoch [677/4000] Validation [1/4] Loss: 0.21705 focal_loss 0.14564 dice_loss 0.07140 +Epoch [677/4000] Validation [2/4] Loss: 0.24781 focal_loss 0.12427 dice_loss 0.12354 +Epoch [677/4000] Validation [3/4] Loss: 0.23445 focal_loss 0.14000 dice_loss 0.09444 +Epoch [677/4000] Validation [4/4] Loss: 0.28303 focal_loss 0.15732 dice_loss 0.12571 +Epoch [677/4000] Validation metric {'Val/mean dice_metric': 0.9665803909301758, 'Val/mean miou_metric': 0.9448511004447937, 'Val/mean f1': 0.9687410593032837, 'Val/mean precision': 0.9622336626052856, 'Val/mean recall': 0.975337028503418, 'Val/mean hd95_metric': 6.775129795074463} +Cheakpoint... +Epoch [677/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665803909301758, 'Val/mean miou_metric': 0.9448511004447937, 'Val/mean f1': 0.9687410593032837, 'Val/mean precision': 0.9622336626052856, 'Val/mean recall': 0.975337028503418, 'Val/mean hd95_metric': 6.775129795074463} +Epoch [678/4000] Training [1/16] Loss: 0.01555 +Epoch [678/4000] Training [2/16] Loss: 0.01173 +Epoch [678/4000] Training [3/16] Loss: 0.02288 +Epoch [678/4000] Training [4/16] Loss: 0.01057 +Epoch [678/4000] Training [5/16] Loss: 0.01233 +Epoch [678/4000] Training [6/16] Loss: 0.01424 +Epoch [678/4000] Training [7/16] Loss: 0.01535 +Epoch [678/4000] Training [8/16] Loss: 0.01177 +Epoch [678/4000] Training [9/16] Loss: 0.01029 +Epoch [678/4000] Training [10/16] Loss: 0.01397 +Epoch [678/4000] Training [11/16] Loss: 0.01825 +Epoch [678/4000] Training [12/16] Loss: 0.01530 +Epoch [678/4000] Training [13/16] Loss: 0.01658 +Epoch [678/4000] Training [14/16] Loss: 0.01510 +Epoch [678/4000] Training [15/16] Loss: 0.01121 +Epoch [678/4000] Training [16/16] Loss: 0.00948 +Epoch [678/4000] Training metric {'Train/mean dice_metric': 0.9896901249885559, 'Train/mean miou_metric': 0.9795821905136108, 'Train/mean f1': 0.9861327409744263, 'Train/mean precision': 0.9808388352394104, 'Train/mean recall': 0.9914842844009399, 'Train/mean hd95_metric': 1.5405025482177734} +Epoch [678/4000] Validation [1/4] Loss: 0.14648 focal_loss 0.08849 dice_loss 0.05798 +Epoch [678/4000] Validation [2/4] Loss: 0.23541 focal_loss 0.11243 dice_loss 0.12298 +Epoch [678/4000] Validation [3/4] Loss: 0.12483 focal_loss 0.06218 dice_loss 0.06265 +Epoch [678/4000] Validation [4/4] Loss: 0.30662 focal_loss 0.19147 dice_loss 0.11515 +Epoch [678/4000] Validation metric {'Val/mean dice_metric': 0.9681730270385742, 'Val/mean miou_metric': 0.9469574093818665, 'Val/mean f1': 0.9701096415519714, 'Val/mean precision': 0.9679102301597595, 'Val/mean recall': 0.9723190665245056, 'Val/mean hd95_metric': 5.869095325469971} +Cheakpoint... +Epoch [678/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681730270385742, 'Val/mean miou_metric': 0.9469574093818665, 'Val/mean f1': 0.9701096415519714, 'Val/mean precision': 0.9679102301597595, 'Val/mean recall': 0.9723190665245056, 'Val/mean hd95_metric': 5.869095325469971} +Epoch [679/4000] Training [1/16] Loss: 0.01237 +Epoch [679/4000] Training [2/16] Loss: 0.01310 +Epoch [679/4000] Training [3/16] Loss: 0.01884 +Epoch [679/4000] Training [4/16] Loss: 0.01519 +Epoch [679/4000] Training [5/16] Loss: 0.01588 +Epoch [679/4000] Training [6/16] Loss: 0.01586 +Epoch [679/4000] Training [7/16] Loss: 0.01717 +Epoch [679/4000] Training [8/16] Loss: 0.01202 +Epoch [679/4000] Training [9/16] Loss: 0.06921 +Epoch [679/4000] Training [10/16] Loss: 0.01400 +Epoch [679/4000] Training [11/16] Loss: 0.01298 +Epoch [679/4000] Training [12/16] Loss: 0.01380 +Epoch [679/4000] Training [13/16] Loss: 0.01869 +Epoch [679/4000] Training [14/16] Loss: 0.02412 +Epoch [679/4000] Training [15/16] Loss: 0.01375 +Epoch [679/4000] Training [16/16] Loss: 0.01598 +Epoch [679/4000] Training metric {'Train/mean dice_metric': 0.9883518218994141, 'Train/mean miou_metric': 0.977239727973938, 'Train/mean f1': 0.9853339791297913, 'Train/mean precision': 0.9803125262260437, 'Train/mean recall': 0.9904072284698486, 'Train/mean hd95_metric': 1.7956318855285645} +Epoch [679/4000] Validation [1/4] Loss: 0.55918 focal_loss 0.41666 dice_loss 0.14252 +Epoch [679/4000] Validation [2/4] Loss: 0.51829 focal_loss 0.30972 dice_loss 0.20857 +Epoch [679/4000] Validation [3/4] Loss: 0.13916 focal_loss 0.07207 dice_loss 0.06709 +Epoch [679/4000] Validation [4/4] Loss: 0.31226 focal_loss 0.18771 dice_loss 0.12454 +Epoch [679/4000] Validation metric {'Val/mean dice_metric': 0.9621780514717102, 'Val/mean miou_metric': 0.9393659830093384, 'Val/mean f1': 0.9637759327888489, 'Val/mean precision': 0.9663176536560059, 'Val/mean recall': 0.9612475037574768, 'Val/mean hd95_metric': 6.989756107330322} +Cheakpoint... +Epoch [679/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9621780514717102, 'Val/mean miou_metric': 0.9393659830093384, 'Val/mean f1': 0.9637759327888489, 'Val/mean precision': 0.9663176536560059, 'Val/mean recall': 0.9612475037574768, 'Val/mean hd95_metric': 6.989756107330322} +Epoch [680/4000] Training [1/16] Loss: 0.01837 +Epoch [680/4000] Training [2/16] Loss: 0.01260 +Epoch [680/4000] Training [3/16] Loss: 0.02193 +Epoch [680/4000] Training [4/16] Loss: 0.01542 +Epoch [680/4000] Training [5/16] Loss: 0.02440 +Epoch [680/4000] Training [6/16] Loss: 0.04383 +Epoch [680/4000] Training [7/16] Loss: 0.01715 +Epoch [680/4000] Training [8/16] Loss: 0.01414 +Epoch [680/4000] Training [9/16] Loss: 0.01310 +Epoch [680/4000] Training [10/16] Loss: 0.01582 +Epoch [680/4000] Training [11/16] Loss: 0.01360 +Epoch [680/4000] Training [12/16] Loss: 0.01738 +Epoch [680/4000] Training [13/16] Loss: 0.01725 +Epoch [680/4000] Training [14/16] Loss: 0.02642 +Epoch [680/4000] Training [15/16] Loss: 0.02116 +Epoch [680/4000] Training [16/16] Loss: 0.02119 +Epoch [680/4000] Training metric {'Train/mean dice_metric': 0.9861298203468323, 'Train/mean miou_metric': 0.9730793237686157, 'Train/mean f1': 0.9847160577774048, 'Train/mean precision': 0.9801262617111206, 'Train/mean recall': 0.9893490672111511, 'Train/mean hd95_metric': 2.463724136352539} +Epoch [680/4000] Validation [1/4] Loss: 0.14723 focal_loss 0.08836 dice_loss 0.05886 +Epoch [680/4000] Validation [2/4] Loss: 0.62678 focal_loss 0.32742 dice_loss 0.29936 +Epoch [680/4000] Validation [3/4] Loss: 0.22871 focal_loss 0.12194 dice_loss 0.10677 +Epoch [680/4000] Validation [4/4] Loss: 0.33011 focal_loss 0.18331 dice_loss 0.14680 +Epoch [680/4000] Validation metric {'Val/mean dice_metric': 0.9600822329521179, 'Val/mean miou_metric': 0.93519526720047, 'Val/mean f1': 0.9628294706344604, 'Val/mean precision': 0.9586666822433472, 'Val/mean recall': 0.9670285582542419, 'Val/mean hd95_metric': 8.185869216918945} +Cheakpoint... +Epoch [680/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9601], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9600822329521179, 'Val/mean miou_metric': 0.93519526720047, 'Val/mean f1': 0.9628294706344604, 'Val/mean precision': 0.9586666822433472, 'Val/mean recall': 0.9670285582542419, 'Val/mean hd95_metric': 8.185869216918945} +Epoch [681/4000] Training [1/16] Loss: 0.01167 +Epoch [681/4000] Training [2/16] Loss: 0.02194 +Epoch [681/4000] Training [3/16] Loss: 0.03178 +Epoch [681/4000] Training [4/16] Loss: 0.01803 +Epoch [681/4000] Training [5/16] Loss: 0.02015 +Epoch [681/4000] Training [6/16] Loss: 0.01294 +Epoch [681/4000] Training [7/16] Loss: 0.01417 +Epoch [681/4000] Training [8/16] Loss: 0.02857 +Epoch [681/4000] Training [9/16] Loss: 0.01572 +Epoch [681/4000] Training [10/16] Loss: 0.01744 +Epoch [681/4000] Training [11/16] Loss: 0.01956 +Epoch [681/4000] Training [12/16] Loss: 0.01467 +Epoch [681/4000] Training [13/16] Loss: 0.02324 +Epoch [681/4000] Training [14/16] Loss: 0.04553 +Epoch [681/4000] Training [15/16] Loss: 0.01515 +Epoch [681/4000] Training [16/16] Loss: 0.02924 +Epoch [681/4000] Training metric {'Train/mean dice_metric': 0.985345184803009, 'Train/mean miou_metric': 0.971874475479126, 'Train/mean f1': 0.9821205735206604, 'Train/mean precision': 0.977064311504364, 'Train/mean recall': 0.9872294664382935, 'Train/mean hd95_metric': 4.002317428588867} +Epoch [681/4000] Validation [1/4] Loss: 0.12807 focal_loss 0.06769 dice_loss 0.06038 +Epoch [681/4000] Validation [2/4] Loss: 0.32521 focal_loss 0.15705 dice_loss 0.16816 +Epoch [681/4000] Validation [3/4] Loss: 0.28946 focal_loss 0.14256 dice_loss 0.14689 +Epoch [681/4000] Validation [4/4] Loss: 0.26855 focal_loss 0.15294 dice_loss 0.11562 +Epoch [681/4000] Validation metric {'Val/mean dice_metric': 0.9590692520141602, 'Val/mean miou_metric': 0.9331811666488647, 'Val/mean f1': 0.9616744518280029, 'Val/mean precision': 0.9613388776779175, 'Val/mean recall': 0.9620102643966675, 'Val/mean hd95_metric': 9.396037101745605} +Cheakpoint... +Epoch [681/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9591], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9590692520141602, 'Val/mean miou_metric': 0.9331811666488647, 'Val/mean f1': 0.9616744518280029, 'Val/mean precision': 0.9613388776779175, 'Val/mean recall': 0.9620102643966675, 'Val/mean hd95_metric': 9.396037101745605} +Epoch [682/4000] Training [1/16] Loss: 0.01550 +Epoch [682/4000] Training [2/16] Loss: 0.01954 +Epoch [682/4000] Training [3/16] Loss: 0.01618 +Epoch [682/4000] Training [4/16] Loss: 0.02044 +Epoch [682/4000] Training [5/16] Loss: 0.01673 +Epoch [682/4000] Training [6/16] Loss: 0.01588 +Epoch [682/4000] Training [7/16] Loss: 0.01877 +Epoch [682/4000] Training [8/16] Loss: 0.01558 +Epoch [682/4000] Training [9/16] Loss: 0.02290 +Epoch [682/4000] Training [10/16] Loss: 0.01611 +Epoch [682/4000] Training [11/16] Loss: 0.01429 +Epoch [682/4000] Training [12/16] Loss: 0.01298 +Epoch [682/4000] Training [13/16] Loss: 0.01431 +Epoch [682/4000] Training [14/16] Loss: 0.01853 +Epoch [682/4000] Training [15/16] Loss: 0.01967 +Epoch [682/4000] Training [16/16] Loss: 0.01395 +Epoch [682/4000] Training metric {'Train/mean dice_metric': 0.9877423048019409, 'Train/mean miou_metric': 0.9758911728858948, 'Train/mean f1': 0.984739363193512, 'Train/mean precision': 0.9805689454078674, 'Train/mean recall': 0.9889453649520874, 'Train/mean hd95_metric': 2.5205698013305664} +Epoch [682/4000] Validation [1/4] Loss: 0.15682 focal_loss 0.09585 dice_loss 0.06097 +Epoch [682/4000] Validation [2/4] Loss: 0.40167 focal_loss 0.20429 dice_loss 0.19738 +Epoch [682/4000] Validation [3/4] Loss: 0.22036 focal_loss 0.12381 dice_loss 0.09655 +Epoch [682/4000] Validation [4/4] Loss: 0.51152 focal_loss 0.31980 dice_loss 0.19172 +Epoch [682/4000] Validation metric {'Val/mean dice_metric': 0.959255039691925, 'Val/mean miou_metric': 0.9350389242172241, 'Val/mean f1': 0.9631094932556152, 'Val/mean precision': 0.9666833877563477, 'Val/mean recall': 0.9595620036125183, 'Val/mean hd95_metric': 7.222458362579346} +Cheakpoint... +Epoch [682/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959255039691925, 'Val/mean miou_metric': 0.9350389242172241, 'Val/mean f1': 0.9631094932556152, 'Val/mean precision': 0.9666833877563477, 'Val/mean recall': 0.9595620036125183, 'Val/mean hd95_metric': 7.222458362579346} +Epoch [683/4000] Training [1/16] Loss: 0.01299 +Epoch [683/4000] Training [2/16] Loss: 0.01590 +Epoch [683/4000] Training [3/16] Loss: 0.01579 +Epoch [683/4000] Training [4/16] Loss: 0.01419 +Epoch [683/4000] Training [5/16] Loss: 0.01461 +Epoch [683/4000] Training [6/16] Loss: 0.01239 +Epoch [683/4000] Training [7/16] Loss: 0.01466 +Epoch [683/4000] Training [8/16] Loss: 0.02004 +Epoch [683/4000] Training [9/16] Loss: 0.01738 +Epoch [683/4000] Training [10/16] Loss: 0.01304 +Epoch [683/4000] Training [11/16] Loss: 0.01550 +Epoch [683/4000] Training [12/16] Loss: 0.02255 +Epoch [683/4000] Training [13/16] Loss: 0.01882 +Epoch [683/4000] Training [14/16] Loss: 0.01356 +Epoch [683/4000] Training [15/16] Loss: 0.02309 +Epoch [683/4000] Training [16/16] Loss: 0.01895 +Epoch [683/4000] Training metric {'Train/mean dice_metric': 0.9873307943344116, 'Train/mean miou_metric': 0.9755070805549622, 'Train/mean f1': 0.9850120544433594, 'Train/mean precision': 0.979554295539856, 'Train/mean recall': 0.9905309677124023, 'Train/mean hd95_metric': 2.134756088256836} +Epoch [683/4000] Validation [1/4] Loss: 0.26162 focal_loss 0.16814 dice_loss 0.09348 +Epoch [683/4000] Validation [2/4] Loss: 0.48916 focal_loss 0.25367 dice_loss 0.23550 +Epoch [683/4000] Validation [3/4] Loss: 0.12226 focal_loss 0.05064 dice_loss 0.07162 +Epoch [683/4000] Validation [4/4] Loss: 0.27408 focal_loss 0.11784 dice_loss 0.15623 +Epoch [683/4000] Validation metric {'Val/mean dice_metric': 0.9621904492378235, 'Val/mean miou_metric': 0.9376358985900879, 'Val/mean f1': 0.9631543159484863, 'Val/mean precision': 0.9561235308647156, 'Val/mean recall': 0.9702893495559692, 'Val/mean hd95_metric': 8.026664733886719} +Cheakpoint... +Epoch [683/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9621904492378235, 'Val/mean miou_metric': 0.9376358985900879, 'Val/mean f1': 0.9631543159484863, 'Val/mean precision': 0.9561235308647156, 'Val/mean recall': 0.9702893495559692, 'Val/mean hd95_metric': 8.026664733886719} +Epoch [684/4000] Training [1/16] Loss: 0.01248 +Epoch [684/4000] Training [2/16] Loss: 0.01389 +Epoch [684/4000] Training [3/16] Loss: 0.02055 +Epoch [684/4000] Training [4/16] Loss: 0.01941 +Epoch [684/4000] Training [5/16] Loss: 0.02241 +Epoch [684/4000] Training [6/16] Loss: 0.01331 +Epoch [684/4000] Training [7/16] Loss: 0.01168 +Epoch [684/4000] Training [8/16] Loss: 0.01562 +Epoch [684/4000] Training [9/16] Loss: 0.01073 +Epoch [684/4000] Training [10/16] Loss: 0.01288 +Epoch [684/4000] Training [11/16] Loss: 0.01644 +Epoch [684/4000] Training [12/16] Loss: 0.01287 +Epoch [684/4000] Training [13/16] Loss: 0.09905 +Epoch [684/4000] Training [14/16] Loss: 0.01424 +Epoch [684/4000] Training [15/16] Loss: 0.01709 +Epoch [684/4000] Training [16/16] Loss: 0.01120 +Epoch [684/4000] Training metric {'Train/mean dice_metric': 0.9886811375617981, 'Train/mean miou_metric': 0.9781891107559204, 'Train/mean f1': 0.9862806797027588, 'Train/mean precision': 0.9824182391166687, 'Train/mean recall': 0.9901736378669739, 'Train/mean hd95_metric': 1.5150612592697144} +Epoch [684/4000] Validation [1/4] Loss: 0.51403 focal_loss 0.40020 dice_loss 0.11383 +Epoch [684/4000] Validation [2/4] Loss: 0.37954 focal_loss 0.19643 dice_loss 0.18311 +Epoch [684/4000] Validation [3/4] Loss: 0.17334 focal_loss 0.07596 dice_loss 0.09739 +Epoch [684/4000] Validation [4/4] Loss: 0.26177 focal_loss 0.14307 dice_loss 0.11870 +Epoch [684/4000] Validation metric {'Val/mean dice_metric': 0.9631593823432922, 'Val/mean miou_metric': 0.9406534433364868, 'Val/mean f1': 0.9644590020179749, 'Val/mean precision': 0.9605469107627869, 'Val/mean recall': 0.9684030413627625, 'Val/mean hd95_metric': 7.210925102233887} +Cheakpoint... +Epoch [684/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631593823432922, 'Val/mean miou_metric': 0.9406534433364868, 'Val/mean f1': 0.9644590020179749, 'Val/mean precision': 0.9605469107627869, 'Val/mean recall': 0.9684030413627625, 'Val/mean hd95_metric': 7.210925102233887} +Epoch [685/4000] Training [1/16] Loss: 0.01242 +Epoch [685/4000] Training [2/16] Loss: 0.01463 +Epoch [685/4000] Training [3/16] Loss: 0.01293 +Epoch [685/4000] Training [4/16] Loss: 0.01344 +Epoch [685/4000] Training [5/16] Loss: 0.01527 +Epoch [685/4000] Training [6/16] Loss: 0.02718 +Epoch [685/4000] Training [7/16] Loss: 0.01270 +Epoch [685/4000] Training [8/16] Loss: 0.01157 +Epoch [685/4000] Training [9/16] Loss: 0.02385 +Epoch [685/4000] Training [10/16] Loss: 0.02789 +Epoch [685/4000] Training [11/16] Loss: 0.01110 +Epoch [685/4000] Training [12/16] Loss: 0.01613 +Epoch [685/4000] Training [13/16] Loss: 0.01603 +Epoch [685/4000] Training [14/16] Loss: 0.01710 +Epoch [685/4000] Training [15/16] Loss: 0.02447 +Epoch [685/4000] Training [16/16] Loss: 0.01280 +Epoch [685/4000] Training metric {'Train/mean dice_metric': 0.9888744950294495, 'Train/mean miou_metric': 0.9778913855552673, 'Train/mean f1': 0.9855709671974182, 'Train/mean precision': 0.9811538457870483, 'Train/mean recall': 0.9900280833244324, 'Train/mean hd95_metric': 2.229663848876953} +Epoch [685/4000] Validation [1/4] Loss: 0.65969 focal_loss 0.53200 dice_loss 0.12769 +Epoch [685/4000] Validation [2/4] Loss: 0.22954 focal_loss 0.11617 dice_loss 0.11337 +Epoch [685/4000] Validation [3/4] Loss: 0.26007 focal_loss 0.15535 dice_loss 0.10472 +Epoch [685/4000] Validation [4/4] Loss: 0.29477 focal_loss 0.18163 dice_loss 0.11314 +Epoch [685/4000] Validation metric {'Val/mean dice_metric': 0.9636432528495789, 'Val/mean miou_metric': 0.939682126045227, 'Val/mean f1': 0.962384045124054, 'Val/mean precision': 0.9638092517852783, 'Val/mean recall': 0.9609628915786743, 'Val/mean hd95_metric': 8.033933639526367} +Cheakpoint... +Epoch [685/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636432528495789, 'Val/mean miou_metric': 0.939682126045227, 'Val/mean f1': 0.962384045124054, 'Val/mean precision': 0.9638092517852783, 'Val/mean recall': 0.9609628915786743, 'Val/mean hd95_metric': 8.033933639526367} +Epoch [686/4000] Training [1/16] Loss: 0.01507 +Epoch [686/4000] Training [2/16] Loss: 0.01816 +Epoch [686/4000] Training [3/16] Loss: 0.01757 +Epoch [686/4000] Training [4/16] Loss: 0.02195 +Epoch [686/4000] Training [5/16] Loss: 0.01659 +Epoch [686/4000] Training [6/16] Loss: 0.02230 +Epoch [686/4000] Training [7/16] Loss: 0.01364 +Epoch [686/4000] Training [8/16] Loss: 0.15138 +Epoch [686/4000] Training [9/16] Loss: 0.01916 +Epoch [686/4000] Training [10/16] Loss: 0.01271 +Epoch [686/4000] Training [11/16] Loss: 0.01625 +Epoch [686/4000] Training [12/16] Loss: 0.02091 +Epoch [686/4000] Training [13/16] Loss: 0.02230 +Epoch [686/4000] Training [14/16] Loss: 0.02928 +Epoch [686/4000] Training [15/16] Loss: 0.01472 +Epoch [686/4000] Training [16/16] Loss: 0.01814 +Epoch [686/4000] Training metric {'Train/mean dice_metric': 0.983984112739563, 'Train/mean miou_metric': 0.9696617722511292, 'Train/mean f1': 0.9738643765449524, 'Train/mean precision': 0.9668704271316528, 'Train/mean recall': 0.9809602499008179, 'Train/mean hd95_metric': 5.589881896972656} +Epoch [686/4000] Validation [1/4] Loss: 0.31214 focal_loss 0.16849 dice_loss 0.14365 +Epoch [686/4000] Validation [2/4] Loss: 0.43174 focal_loss 0.20167 dice_loss 0.23006 +Epoch [686/4000] Validation [3/4] Loss: 0.20894 focal_loss 0.10629 dice_loss 0.10265 +Epoch [686/4000] Validation [4/4] Loss: 0.39220 focal_loss 0.20546 dice_loss 0.18674 +Epoch [686/4000] Validation metric {'Val/mean dice_metric': 0.9530774354934692, 'Val/mean miou_metric': 0.9266874194145203, 'Val/mean f1': 0.9502193927764893, 'Val/mean precision': 0.9499130845069885, 'Val/mean recall': 0.9505258798599243, 'Val/mean hd95_metric': 11.178019523620605} +Cheakpoint... +Epoch [686/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9531], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9530774354934692, 'Val/mean miou_metric': 0.9266874194145203, 'Val/mean f1': 0.9502193927764893, 'Val/mean precision': 0.9499130845069885, 'Val/mean recall': 0.9505258798599243, 'Val/mean hd95_metric': 11.178019523620605} +Epoch [687/4000] Training [1/16] Loss: 0.02556 +Epoch [687/4000] Training [2/16] Loss: 0.01641 +Epoch [687/4000] Training [3/16] Loss: 0.01842 +Epoch [687/4000] Training [4/16] Loss: 0.02926 +Epoch [687/4000] Training [5/16] Loss: 0.02048 +Epoch [687/4000] Training [6/16] Loss: 0.02587 +Epoch [687/4000] Training [7/16] Loss: 0.02204 +Epoch [687/4000] Training [8/16] Loss: 0.01619 +Epoch [687/4000] Training [9/16] Loss: 0.01698 +Epoch [687/4000] Training [10/16] Loss: 0.01775 +Epoch [687/4000] Training [11/16] Loss: 0.01526 +Epoch [687/4000] Training [12/16] Loss: 0.02650 +Epoch [687/4000] Training [13/16] Loss: 0.01618 +Epoch [687/4000] Training [14/16] Loss: 0.02022 +Epoch [687/4000] Training [15/16] Loss: 0.02203 +Epoch [687/4000] Training [16/16] Loss: 0.01964 +Epoch [687/4000] Training metric {'Train/mean dice_metric': 0.9862410426139832, 'Train/mean miou_metric': 0.9728075265884399, 'Train/mean f1': 0.9834778308868408, 'Train/mean precision': 0.9789356589317322, 'Train/mean recall': 0.98806232213974, 'Train/mean hd95_metric': 2.194463014602661} +Epoch [687/4000] Validation [1/4] Loss: 0.16826 focal_loss 0.09809 dice_loss 0.07017 +Epoch [687/4000] Validation [2/4] Loss: 0.59628 focal_loss 0.29407 dice_loss 0.30221 +Epoch [687/4000] Validation [3/4] Loss: 0.24516 focal_loss 0.14364 dice_loss 0.10152 +Epoch [687/4000] Validation [4/4] Loss: 0.37125 focal_loss 0.22609 dice_loss 0.14516 +Epoch [687/4000] Validation metric {'Val/mean dice_metric': 0.9574283361434937, 'Val/mean miou_metric': 0.9324072003364563, 'Val/mean f1': 0.9603152871131897, 'Val/mean precision': 0.9549356698989868, 'Val/mean recall': 0.9657559990882874, 'Val/mean hd95_metric': 8.464627265930176} +Cheakpoint... +Epoch [687/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9574], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9574283361434937, 'Val/mean miou_metric': 0.9324072003364563, 'Val/mean f1': 0.9603152871131897, 'Val/mean precision': 0.9549356698989868, 'Val/mean recall': 0.9657559990882874, 'Val/mean hd95_metric': 8.464627265930176} +Epoch [688/4000] Training [1/16] Loss: 0.01686 +Epoch [688/4000] Training [2/16] Loss: 0.01428 +Epoch [688/4000] Training [3/16] Loss: 0.01641 +Epoch [688/4000] Training [4/16] Loss: 0.02170 +Epoch [688/4000] Training [5/16] Loss: 0.01526 +Epoch [688/4000] Training [6/16] Loss: 0.01474 +Epoch [688/4000] Training [7/16] Loss: 0.01790 +Epoch [688/4000] Training [8/16] Loss: 0.02053 +Epoch [688/4000] Training [9/16] Loss: 0.02367 +Epoch [688/4000] Training [10/16] Loss: 0.01782 +Epoch [688/4000] Training [11/16] Loss: 0.02033 +Epoch [688/4000] Training [12/16] Loss: 0.02359 +Epoch [688/4000] Training [13/16] Loss: 0.03543 +Epoch [688/4000] Training [14/16] Loss: 0.01558 +Epoch [688/4000] Training [15/16] Loss: 0.01724 +Epoch [688/4000] Training [16/16] Loss: 0.01825 +Epoch [688/4000] Training metric {'Train/mean dice_metric': 0.9848415851593018, 'Train/mean miou_metric': 0.9713999629020691, 'Train/mean f1': 0.9804799556732178, 'Train/mean precision': 0.9759891033172607, 'Train/mean recall': 0.985012412071228, 'Train/mean hd95_metric': 3.058272361755371} +Epoch [688/4000] Validation [1/4] Loss: 0.34362 focal_loss 0.21395 dice_loss 0.12967 +Epoch [688/4000] Validation [2/4] Loss: 0.40931 focal_loss 0.20024 dice_loss 0.20907 +Epoch [688/4000] Validation [3/4] Loss: 0.18548 focal_loss 0.08167 dice_loss 0.10381 +Epoch [688/4000] Validation [4/4] Loss: 0.31043 focal_loss 0.16308 dice_loss 0.14736 +Epoch [688/4000] Validation metric {'Val/mean dice_metric': 0.9572900533676147, 'Val/mean miou_metric': 0.9316293597221375, 'Val/mean f1': 0.9575410485267639, 'Val/mean precision': 0.9567613005638123, 'Val/mean recall': 0.9583220481872559, 'Val/mean hd95_metric': 9.088361740112305} +Cheakpoint... +Epoch [688/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9573], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9572900533676147, 'Val/mean miou_metric': 0.9316293597221375, 'Val/mean f1': 0.9575410485267639, 'Val/mean precision': 0.9567613005638123, 'Val/mean recall': 0.9583220481872559, 'Val/mean hd95_metric': 9.088361740112305} +Epoch [689/4000] Training [1/16] Loss: 0.01806 +Epoch [689/4000] Training [2/16] Loss: 0.01505 +Epoch [689/4000] Training [3/16] Loss: 0.01572 +Epoch [689/4000] Training [4/16] Loss: 0.01775 +Epoch [689/4000] Training [5/16] Loss: 0.01932 +Epoch [689/4000] Training [6/16] Loss: 0.01517 +Epoch [689/4000] Training [7/16] Loss: 0.01772 +Epoch [689/4000] Training [8/16] Loss: 0.01588 +Epoch [689/4000] Training [9/16] Loss: 0.01805 +Epoch [689/4000] Training [10/16] Loss: 0.01849 +Epoch [689/4000] Training [11/16] Loss: 0.01752 +Epoch [689/4000] Training [12/16] Loss: 0.01833 +Epoch [689/4000] Training [13/16] Loss: 0.01379 +Epoch [689/4000] Training [14/16] Loss: 0.02020 +Epoch [689/4000] Training [15/16] Loss: 0.01449 +Epoch [689/4000] Training [16/16] Loss: 0.02426 +Epoch [689/4000] Training metric {'Train/mean dice_metric': 0.9879491329193115, 'Train/mean miou_metric': 0.9760294556617737, 'Train/mean f1': 0.9846835136413574, 'Train/mean precision': 0.9799813628196716, 'Train/mean recall': 0.9894310235977173, 'Train/mean hd95_metric': 1.9348561763763428} +Epoch [689/4000] Validation [1/4] Loss: 0.15491 focal_loss 0.08518 dice_loss 0.06972 +Epoch [689/4000] Validation [2/4] Loss: 0.51459 focal_loss 0.28564 dice_loss 0.22895 +Epoch [689/4000] Validation [3/4] Loss: 0.20576 focal_loss 0.10842 dice_loss 0.09735 +Epoch [689/4000] Validation [4/4] Loss: 0.26766 focal_loss 0.12800 dice_loss 0.13966 +Epoch [689/4000] Validation metric {'Val/mean dice_metric': 0.9598159790039062, 'Val/mean miou_metric': 0.9357413053512573, 'Val/mean f1': 0.9606204628944397, 'Val/mean precision': 0.9517781138420105, 'Val/mean recall': 0.9696285724639893, 'Val/mean hd95_metric': 8.448545455932617} +Cheakpoint... +Epoch [689/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9598], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9598159790039062, 'Val/mean miou_metric': 0.9357413053512573, 'Val/mean f1': 0.9606204628944397, 'Val/mean precision': 0.9517781138420105, 'Val/mean recall': 0.9696285724639893, 'Val/mean hd95_metric': 8.448545455932617} +Epoch [690/4000] Training [1/16] Loss: 0.01259 +Epoch [690/4000] Training [2/16] Loss: 0.01433 +Epoch [690/4000] Training [3/16] Loss: 0.01942 +Epoch [690/4000] Training [4/16] Loss: 0.01690 +Epoch [690/4000] Training [5/16] Loss: 0.01356 +Epoch [690/4000] Training [6/16] Loss: 0.01948 +Epoch [690/4000] Training [7/16] Loss: 0.02167 +Epoch [690/4000] Training [8/16] Loss: 0.01301 +Epoch [690/4000] Training [9/16] Loss: 0.01182 +Epoch [690/4000] Training [10/16] Loss: 0.01199 +Epoch [690/4000] Training [11/16] Loss: 0.01244 +Epoch [690/4000] Training [12/16] Loss: 0.01378 +Epoch [690/4000] Training [13/16] Loss: 0.01511 +Epoch [690/4000] Training [14/16] Loss: 0.01561 +Epoch [690/4000] Training [15/16] Loss: 0.01049 +Epoch [690/4000] Training [16/16] Loss: 0.01875 +Epoch [690/4000] Training metric {'Train/mean dice_metric': 0.9901059865951538, 'Train/mean miou_metric': 0.9801890254020691, 'Train/mean f1': 0.9869590401649475, 'Train/mean precision': 0.9823665618896484, 'Train/mean recall': 0.9915947318077087, 'Train/mean hd95_metric': 1.907514214515686} +Epoch [690/4000] Validation [1/4] Loss: 0.12489 focal_loss 0.07079 dice_loss 0.05410 +Epoch [690/4000] Validation [2/4] Loss: 0.56574 focal_loss 0.31801 dice_loss 0.24773 +Epoch [690/4000] Validation [3/4] Loss: 0.23083 focal_loss 0.13853 dice_loss 0.09231 +Epoch [690/4000] Validation [4/4] Loss: 0.16367 focal_loss 0.06970 dice_loss 0.09397 +Epoch [690/4000] Validation metric {'Val/mean dice_metric': 0.9612334966659546, 'Val/mean miou_metric': 0.9397362470626831, 'Val/mean f1': 0.96399986743927, 'Val/mean precision': 0.9589575529098511, 'Val/mean recall': 0.9690954685211182, 'Val/mean hd95_metric': 7.224656105041504} +Cheakpoint... +Epoch [690/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9612], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612334966659546, 'Val/mean miou_metric': 0.9397362470626831, 'Val/mean f1': 0.96399986743927, 'Val/mean precision': 0.9589575529098511, 'Val/mean recall': 0.9690954685211182, 'Val/mean hd95_metric': 7.224656105041504} +Epoch [691/4000] Training [1/16] Loss: 0.01434 +Epoch [691/4000] Training [2/16] Loss: 0.01250 +Epoch [691/4000] Training [3/16] Loss: 0.01358 +Epoch [691/4000] Training [4/16] Loss: 0.01458 +Epoch [691/4000] Training [5/16] Loss: 0.01286 +Epoch [691/4000] Training [6/16] Loss: 0.03050 +Epoch [691/4000] Training [7/16] Loss: 0.01309 +Epoch [691/4000] Training [8/16] Loss: 0.01284 +Epoch [691/4000] Training [9/16] Loss: 0.08973 +Epoch [691/4000] Training [10/16] Loss: 0.01370 +Epoch [691/4000] Training [11/16] Loss: 0.01454 +Epoch [691/4000] Training [12/16] Loss: 0.01850 +Epoch [691/4000] Training [13/16] Loss: 0.01663 +Epoch [691/4000] Training [14/16] Loss: 0.01713 +Epoch [691/4000] Training [15/16] Loss: 0.01350 +Epoch [691/4000] Training [16/16] Loss: 0.01364 +Epoch [691/4000] Training metric {'Train/mean dice_metric': 0.9885464906692505, 'Train/mean miou_metric': 0.9776207208633423, 'Train/mean f1': 0.98447585105896, 'Train/mean precision': 0.9802446365356445, 'Train/mean recall': 0.988743782043457, 'Train/mean hd95_metric': 2.1308369636535645} +Epoch [691/4000] Validation [1/4] Loss: 0.33232 focal_loss 0.22763 dice_loss 0.10469 +Epoch [691/4000] Validation [2/4] Loss: 0.25758 focal_loss 0.11469 dice_loss 0.14288 +Epoch [691/4000] Validation [3/4] Loss: 0.15903 focal_loss 0.06791 dice_loss 0.09112 +Epoch [691/4000] Validation [4/4] Loss: 0.17379 focal_loss 0.08574 dice_loss 0.08805 +Epoch [691/4000] Validation metric {'Val/mean dice_metric': 0.9644008874893188, 'Val/mean miou_metric': 0.9420145750045776, 'Val/mean f1': 0.9640197157859802, 'Val/mean precision': 0.9603067636489868, 'Val/mean recall': 0.9677614569664001, 'Val/mean hd95_metric': 7.079911708831787} +Cheakpoint... +Epoch [691/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644008874893188, 'Val/mean miou_metric': 0.9420145750045776, 'Val/mean f1': 0.9640197157859802, 'Val/mean precision': 0.9603067636489868, 'Val/mean recall': 0.9677614569664001, 'Val/mean hd95_metric': 7.079911708831787} +Epoch [692/4000] Training [1/16] Loss: 0.01200 +Epoch [692/4000] Training [2/16] Loss: 0.01129 +Epoch [692/4000] Training [3/16] Loss: 0.01178 +Epoch [692/4000] Training [4/16] Loss: 0.01445 +Epoch [692/4000] Training [5/16] Loss: 0.02029 +Epoch [692/4000] Training [6/16] Loss: 0.01129 +Epoch [692/4000] Training [7/16] Loss: 0.01631 +Epoch [692/4000] Training [8/16] Loss: 0.02251 +Epoch [692/4000] Training [9/16] Loss: 0.01907 +Epoch [692/4000] Training [10/16] Loss: 0.01256 +Epoch [692/4000] Training [11/16] Loss: 0.01377 +Epoch [692/4000] Training [12/16] Loss: 0.01511 +Epoch [692/4000] Training [13/16] Loss: 0.02129 +Epoch [692/4000] Training [14/16] Loss: 0.01447 +Epoch [692/4000] Training [15/16] Loss: 0.01405 +Epoch [692/4000] Training [16/16] Loss: 0.01979 +Epoch [692/4000] Training metric {'Train/mean dice_metric': 0.9894825220108032, 'Train/mean miou_metric': 0.9790217876434326, 'Train/mean f1': 0.9855949878692627, 'Train/mean precision': 0.9807465076446533, 'Train/mean recall': 0.9904915690422058, 'Train/mean hd95_metric': 2.4181432723999023} +Epoch [692/4000] Validation [1/4] Loss: 0.83252 focal_loss 0.65957 dice_loss 0.17295 +Epoch [692/4000] Validation [2/4] Loss: 0.33877 focal_loss 0.15098 dice_loss 0.18779 +Epoch [692/4000] Validation [3/4] Loss: 0.28528 focal_loss 0.17948 dice_loss 0.10581 +Epoch [692/4000] Validation [4/4] Loss: 0.80823 focal_loss 0.50768 dice_loss 0.30054 +Epoch [692/4000] Validation metric {'Val/mean dice_metric': 0.9601581692695618, 'Val/mean miou_metric': 0.9366966485977173, 'Val/mean f1': 0.9606720805168152, 'Val/mean precision': 0.9645513296127319, 'Val/mean recall': 0.9568238854408264, 'Val/mean hd95_metric': 8.484749794006348} +Cheakpoint... +Epoch [692/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9602], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9601581692695618, 'Val/mean miou_metric': 0.9366966485977173, 'Val/mean f1': 0.9606720805168152, 'Val/mean precision': 0.9645513296127319, 'Val/mean recall': 0.9568238854408264, 'Val/mean hd95_metric': 8.484749794006348} +Epoch [693/4000] Training [1/16] Loss: 0.01607 +Epoch [693/4000] Training [2/16] Loss: 0.02461 +Epoch [693/4000] Training [3/16] Loss: 0.01777 +Epoch [693/4000] Training [4/16] Loss: 0.01100 +Epoch [693/4000] Training [5/16] Loss: 0.01308 +Epoch [693/4000] Training [6/16] Loss: 0.01627 +Epoch [693/4000] Training [7/16] Loss: 0.01644 +Epoch [693/4000] Training [8/16] Loss: 0.01330 +Epoch [693/4000] Training [9/16] Loss: 0.01493 +Epoch [693/4000] Training [10/16] Loss: 0.01520 +Epoch [693/4000] Training [11/16] Loss: 0.01329 +Epoch [693/4000] Training [12/16] Loss: 0.01694 +Epoch [693/4000] Training [13/16] Loss: 0.02881 +Epoch [693/4000] Training [14/16] Loss: 0.01434 +Epoch [693/4000] Training [15/16] Loss: 0.01684 +Epoch [693/4000] Training [16/16] Loss: 0.01500 +Epoch [693/4000] Training metric {'Train/mean dice_metric': 0.9879549741744995, 'Train/mean miou_metric': 0.9762258529663086, 'Train/mean f1': 0.9839645624160767, 'Train/mean precision': 0.9797458052635193, 'Train/mean recall': 0.9882198572158813, 'Train/mean hd95_metric': 2.2254459857940674} +Epoch [693/4000] Validation [1/4] Loss: 0.21365 focal_loss 0.11599 dice_loss 0.09766 +Epoch [693/4000] Validation [2/4] Loss: 0.33051 focal_loss 0.14764 dice_loss 0.18287 +Epoch [693/4000] Validation [3/4] Loss: 0.18647 focal_loss 0.08960 dice_loss 0.09687 +Epoch [693/4000] Validation [4/4] Loss: 0.18478 focal_loss 0.07835 dice_loss 0.10644 +Epoch [693/4000] Validation metric {'Val/mean dice_metric': 0.9620214700698853, 'Val/mean miou_metric': 0.9378930926322937, 'Val/mean f1': 0.9631773233413696, 'Val/mean precision': 0.9603446125984192, 'Val/mean recall': 0.9660267233848572, 'Val/mean hd95_metric': 8.394895553588867} +Cheakpoint... +Epoch [693/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9620], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9620214700698853, 'Val/mean miou_metric': 0.9378930926322937, 'Val/mean f1': 0.9631773233413696, 'Val/mean precision': 0.9603446125984192, 'Val/mean recall': 0.9660267233848572, 'Val/mean hd95_metric': 8.394895553588867} +Epoch [694/4000] Training [1/16] Loss: 0.01223 +Epoch [694/4000] Training [2/16] Loss: 0.01180 +Epoch [694/4000] Training [3/16] Loss: 0.01295 +Epoch [694/4000] Training [4/16] Loss: 0.01449 +Epoch [694/4000] Training [5/16] Loss: 0.01936 +Epoch [694/4000] Training [6/16] Loss: 0.01665 +Epoch [694/4000] Training [7/16] Loss: 0.01704 +Epoch [694/4000] Training [8/16] Loss: 0.01784 +Epoch [694/4000] Training [9/16] Loss: 0.01283 +Epoch [694/4000] Training [10/16] Loss: 0.01194 +Epoch [694/4000] Training [11/16] Loss: 0.01417 +Epoch [694/4000] Training [12/16] Loss: 0.04269 +Epoch [694/4000] Training [13/16] Loss: 0.01399 +Epoch [694/4000] Training [14/16] Loss: 0.02689 +Epoch [694/4000] Training [15/16] Loss: 0.01302 +Epoch [694/4000] Training [16/16] Loss: 0.01829 +Epoch [694/4000] Training metric {'Train/mean dice_metric': 0.9889366030693054, 'Train/mean miou_metric': 0.9779831767082214, 'Train/mean f1': 0.9852755665779114, 'Train/mean precision': 0.9804498553276062, 'Train/mean recall': 0.9901490807533264, 'Train/mean hd95_metric': 1.8157747983932495} +Epoch [694/4000] Validation [1/4] Loss: 0.14203 focal_loss 0.07575 dice_loss 0.06628 +Epoch [694/4000] Validation [2/4] Loss: 0.37644 focal_loss 0.18964 dice_loss 0.18680 +Epoch [694/4000] Validation [3/4] Loss: 0.23989 focal_loss 0.12817 dice_loss 0.11172 +Epoch [694/4000] Validation [4/4] Loss: 0.34702 focal_loss 0.18705 dice_loss 0.15997 +Epoch [694/4000] Validation metric {'Val/mean dice_metric': 0.9601016044616699, 'Val/mean miou_metric': 0.9356911778450012, 'Val/mean f1': 0.9582016468048096, 'Val/mean precision': 0.943891167640686, 'Val/mean recall': 0.972952663898468, 'Val/mean hd95_metric': 10.067845344543457} +Cheakpoint... +Epoch [694/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9601], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9601016044616699, 'Val/mean miou_metric': 0.9356911778450012, 'Val/mean f1': 0.9582016468048096, 'Val/mean precision': 0.943891167640686, 'Val/mean recall': 0.972952663898468, 'Val/mean hd95_metric': 10.067845344543457} +Epoch [695/4000] Training [1/16] Loss: 0.01453 +Epoch [695/4000] Training [2/16] Loss: 0.01713 +Epoch [695/4000] Training [3/16] Loss: 0.01643 +Epoch [695/4000] Training [4/16] Loss: 0.01323 +Epoch [695/4000] Training [5/16] Loss: 0.01504 +Epoch [695/4000] Training [6/16] Loss: 0.01396 +Epoch [695/4000] Training [7/16] Loss: 0.01945 +Epoch [695/4000] Training [8/16] Loss: 0.01278 +Epoch [695/4000] Training [9/16] Loss: 0.02345 +Epoch [695/4000] Training [10/16] Loss: 0.01600 +Epoch [695/4000] Training [11/16] Loss: 0.01796 +Epoch [695/4000] Training [12/16] Loss: 0.04081 +Epoch [695/4000] Training [13/16] Loss: 0.01288 +Epoch [695/4000] Training [14/16] Loss: 0.02559 +Epoch [695/4000] Training [15/16] Loss: 0.01351 +Epoch [695/4000] Training [16/16] Loss: 0.03038 +Epoch [695/4000] Training metric {'Train/mean dice_metric': 0.9870835542678833, 'Train/mean miou_metric': 0.9746741652488708, 'Train/mean f1': 0.9832302927970886, 'Train/mean precision': 0.9792028069496155, 'Train/mean recall': 0.9872910380363464, 'Train/mean hd95_metric': 2.133810043334961} +Epoch [695/4000] Validation [1/4] Loss: 0.14784 focal_loss 0.07708 dice_loss 0.07076 +Epoch [695/4000] Validation [2/4] Loss: 0.32975 focal_loss 0.14865 dice_loss 0.18110 +Epoch [695/4000] Validation [3/4] Loss: 0.19403 focal_loss 0.09459 dice_loss 0.09944 +Epoch [695/4000] Validation [4/4] Loss: 0.20288 focal_loss 0.09637 dice_loss 0.10650 +Epoch [695/4000] Validation metric {'Val/mean dice_metric': 0.9594724774360657, 'Val/mean miou_metric': 0.9348546862602234, 'Val/mean f1': 0.9586145281791687, 'Val/mean precision': 0.9461891055107117, 'Val/mean recall': 0.9713706374168396, 'Val/mean hd95_metric': 9.326499938964844} +Cheakpoint... +Epoch [695/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9595], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9594724774360657, 'Val/mean miou_metric': 0.9348546862602234, 'Val/mean f1': 0.9586145281791687, 'Val/mean precision': 0.9461891055107117, 'Val/mean recall': 0.9713706374168396, 'Val/mean hd95_metric': 9.326499938964844} +Epoch [696/4000] Training [1/16] Loss: 0.01675 +Epoch [696/4000] Training [2/16] Loss: 0.01618 +Epoch [696/4000] Training [3/16] Loss: 0.01300 +Epoch [696/4000] Training [4/16] Loss: 0.01401 +Epoch [696/4000] Training [5/16] Loss: 0.02176 +Epoch [696/4000] Training [6/16] Loss: 0.01341 +Epoch [696/4000] Training [7/16] Loss: 0.01746 +Epoch [696/4000] Training [8/16] Loss: 0.01662 +Epoch [696/4000] Training [9/16] Loss: 0.02417 +Epoch [696/4000] Training [10/16] Loss: 0.02154 +Epoch [696/4000] Training [11/16] Loss: 0.01806 +Epoch [696/4000] Training [12/16] Loss: 0.01233 +Epoch [696/4000] Training [13/16] Loss: 0.01638 +Epoch [696/4000] Training [14/16] Loss: 0.01854 +Epoch [696/4000] Training [15/16] Loss: 0.01546 +Epoch [696/4000] Training [16/16] Loss: 0.01910 +Epoch [696/4000] Training metric {'Train/mean dice_metric': 0.9877402782440186, 'Train/mean miou_metric': 0.9759763479232788, 'Train/mean f1': 0.9838857054710388, 'Train/mean precision': 0.9784564971923828, 'Train/mean recall': 0.9893754720687866, 'Train/mean hd95_metric': 3.2577929496765137} +Epoch [696/4000] Validation [1/4] Loss: 0.17326 focal_loss 0.09717 dice_loss 0.07609 +Epoch [696/4000] Validation [2/4] Loss: 0.33605 focal_loss 0.17082 dice_loss 0.16523 +Epoch [696/4000] Validation [3/4] Loss: 0.14386 focal_loss 0.07481 dice_loss 0.06905 +Epoch [696/4000] Validation [4/4] Loss: 0.31691 focal_loss 0.16116 dice_loss 0.15575 +Epoch [696/4000] Validation metric {'Val/mean dice_metric': 0.960837185382843, 'Val/mean miou_metric': 0.9370883107185364, 'Val/mean f1': 0.9625794887542725, 'Val/mean precision': 0.9591755867004395, 'Val/mean recall': 0.9660075902938843, 'Val/mean hd95_metric': 8.502676010131836} +Cheakpoint... +Epoch [696/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.960837185382843, 'Val/mean miou_metric': 0.9370883107185364, 'Val/mean f1': 0.9625794887542725, 'Val/mean precision': 0.9591755867004395, 'Val/mean recall': 0.9660075902938843, 'Val/mean hd95_metric': 8.502676010131836} +Epoch [697/4000] Training [1/16] Loss: 0.02633 +Epoch [697/4000] Training [2/16] Loss: 0.01223 +Epoch [697/4000] Training [3/16] Loss: 0.01240 +Epoch [697/4000] Training [4/16] Loss: 0.01892 +Epoch [697/4000] Training [5/16] Loss: 0.01587 +Epoch [697/4000] Training [6/16] Loss: 0.01850 +Epoch [697/4000] Training [7/16] Loss: 0.01411 +Epoch [697/4000] Training [8/16] Loss: 0.04388 +Epoch [697/4000] Training [9/16] Loss: 0.01348 +Epoch [697/4000] Training [10/16] Loss: 0.01596 +Epoch [697/4000] Training [11/16] Loss: 0.01345 +Epoch [697/4000] Training [12/16] Loss: 0.01577 +Epoch [697/4000] Training [13/16] Loss: 0.01718 +Epoch [697/4000] Training [14/16] Loss: 0.01541 +Epoch [697/4000] Training [15/16] Loss: 0.02099 +Epoch [697/4000] Training [16/16] Loss: 0.03616 +Epoch [697/4000] Training metric {'Train/mean dice_metric': 0.9887994527816772, 'Train/mean miou_metric': 0.9776962995529175, 'Train/mean f1': 0.9848030805587769, 'Train/mean precision': 0.9794044494628906, 'Train/mean recall': 0.9902615547180176, 'Train/mean hd95_metric': 2.0328941345214844} +Epoch [697/4000] Validation [1/4] Loss: 0.27340 focal_loss 0.14728 dice_loss 0.12611 +Epoch [697/4000] Validation [2/4] Loss: 0.33798 focal_loss 0.13731 dice_loss 0.20067 +Epoch [697/4000] Validation [3/4] Loss: 0.19972 focal_loss 0.10218 dice_loss 0.09753 +Epoch [697/4000] Validation [4/4] Loss: 0.16518 focal_loss 0.06732 dice_loss 0.09786 +Epoch [697/4000] Validation metric {'Val/mean dice_metric': 0.9571738243103027, 'Val/mean miou_metric': 0.9334247708320618, 'Val/mean f1': 0.9595047831535339, 'Val/mean precision': 0.9493170976638794, 'Val/mean recall': 0.9699134826660156, 'Val/mean hd95_metric': 8.932368278503418} +Cheakpoint... +Epoch [697/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9572], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9571738243103027, 'Val/mean miou_metric': 0.9334247708320618, 'Val/mean f1': 0.9595047831535339, 'Val/mean precision': 0.9493170976638794, 'Val/mean recall': 0.9699134826660156, 'Val/mean hd95_metric': 8.932368278503418} +Epoch [698/4000] Training [1/16] Loss: 0.01750 +Epoch [698/4000] Training [2/16] Loss: 0.01265 +Epoch [698/4000] Training [3/16] Loss: 0.01530 +Epoch [698/4000] Training [4/16] Loss: 0.01272 +Epoch [698/4000] Training [5/16] Loss: 0.02059 +Epoch [698/4000] Training [6/16] Loss: 0.01758 +Epoch [698/4000] Training [7/16] Loss: 0.01761 +Epoch [698/4000] Training [8/16] Loss: 0.01489 +Epoch [698/4000] Training [9/16] Loss: 0.01195 +Epoch [698/4000] Training [10/16] Loss: 0.01610 +Epoch [698/4000] Training [11/16] Loss: 0.02013 +Epoch [698/4000] Training [12/16] Loss: 0.01427 +Epoch [698/4000] Training [13/16] Loss: 0.01160 +Epoch [698/4000] Training [14/16] Loss: 0.01962 +Epoch [698/4000] Training [15/16] Loss: 0.01336 +Epoch [698/4000] Training [16/16] Loss: 0.01622 +Epoch [698/4000] Training metric {'Train/mean dice_metric': 0.9892956018447876, 'Train/mean miou_metric': 0.9786357879638672, 'Train/mean f1': 0.9858570098876953, 'Train/mean precision': 0.9811795949935913, 'Train/mean recall': 0.9905791878700256, 'Train/mean hd95_metric': 1.629502534866333} +Epoch [698/4000] Validation [1/4] Loss: 0.19545 focal_loss 0.12430 dice_loss 0.07115 +Epoch [698/4000] Validation [2/4] Loss: 0.23321 focal_loss 0.10942 dice_loss 0.12379 +Epoch [698/4000] Validation [3/4] Loss: 0.19302 focal_loss 0.10165 dice_loss 0.09137 +Epoch [698/4000] Validation [4/4] Loss: 0.32033 focal_loss 0.16863 dice_loss 0.15170 +Epoch [698/4000] Validation metric {'Val/mean dice_metric': 0.9641040563583374, 'Val/mean miou_metric': 0.9414466619491577, 'Val/mean f1': 0.9654244184494019, 'Val/mean precision': 0.9584951400756836, 'Val/mean recall': 0.9724545478820801, 'Val/mean hd95_metric': 6.882533073425293} +Cheakpoint... +Epoch [698/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9641040563583374, 'Val/mean miou_metric': 0.9414466619491577, 'Val/mean f1': 0.9654244184494019, 'Val/mean precision': 0.9584951400756836, 'Val/mean recall': 0.9724545478820801, 'Val/mean hd95_metric': 6.882533073425293} +Epoch [699/4000] Training [1/16] Loss: 0.01275 +Epoch [699/4000] Training [2/16] Loss: 0.01918 +Epoch [699/4000] Training [3/16] Loss: 0.01380 +Epoch [699/4000] Training [4/16] Loss: 0.01707 +Epoch [699/4000] Training [5/16] Loss: 0.01498 +Epoch [699/4000] Training [6/16] Loss: 0.01447 +Epoch [699/4000] Training [7/16] Loss: 0.01465 +Epoch [699/4000] Training [8/16] Loss: 0.01830 +Epoch [699/4000] Training [9/16] Loss: 0.01419 +Epoch [699/4000] Training [10/16] Loss: 0.02221 +Epoch [699/4000] Training [11/16] Loss: 0.01290 +Epoch [699/4000] Training [12/16] Loss: 0.02000 +Epoch [699/4000] Training [13/16] Loss: 0.02035 +Epoch [699/4000] Training [14/16] Loss: 0.01751 +Epoch [699/4000] Training [15/16] Loss: 0.01886 +Epoch [699/4000] Training [16/16] Loss: 0.01571 +Epoch [699/4000] Training metric {'Train/mean dice_metric': 0.9873830080032349, 'Train/mean miou_metric': 0.9752842783927917, 'Train/mean f1': 0.9835578203201294, 'Train/mean precision': 0.9791284799575806, 'Train/mean recall': 0.9880273342132568, 'Train/mean hd95_metric': 2.6752500534057617} +Epoch [699/4000] Validation [1/4] Loss: 0.71945 focal_loss 0.51834 dice_loss 0.20111 +Epoch [699/4000] Validation [2/4] Loss: 0.35141 focal_loss 0.18956 dice_loss 0.16185 +Epoch [699/4000] Validation [3/4] Loss: 0.16702 focal_loss 0.07755 dice_loss 0.08947 +Epoch [699/4000] Validation [4/4] Loss: 0.65054 focal_loss 0.39908 dice_loss 0.25146 +Epoch [699/4000] Validation metric {'Val/mean dice_metric': 0.9573062658309937, 'Val/mean miou_metric': 0.932002067565918, 'Val/mean f1': 0.9584444165229797, 'Val/mean precision': 0.9600651860237122, 'Val/mean recall': 0.9568291306495667, 'Val/mean hd95_metric': 8.765932083129883} +Cheakpoint... +Epoch [699/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9573], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9573062658309937, 'Val/mean miou_metric': 0.932002067565918, 'Val/mean f1': 0.9584444165229797, 'Val/mean precision': 0.9600651860237122, 'Val/mean recall': 0.9568291306495667, 'Val/mean hd95_metric': 8.765932083129883} +Epoch [700/4000] Training [1/16] Loss: 0.01434 +Epoch [700/4000] Training [2/16] Loss: 0.01449 +Epoch [700/4000] Training [3/16] Loss: 0.01591 +Epoch [700/4000] Training [4/16] Loss: 0.02136 +Epoch [700/4000] Training [5/16] Loss: 0.01347 +Epoch [700/4000] Training [6/16] Loss: 0.02491 +Epoch [700/4000] Training [7/16] Loss: 0.02038 +Epoch [700/4000] Training [8/16] Loss: 0.01300 +Epoch [700/4000] Training [9/16] Loss: 0.01592 +Epoch [700/4000] Training [10/16] Loss: 0.01403 +Epoch [700/4000] Training [11/16] Loss: 0.01531 +Epoch [700/4000] Training [12/16] Loss: 0.02471 +Epoch [700/4000] Training [13/16] Loss: 0.01828 +Epoch [700/4000] Training [14/16] Loss: 0.01360 +Epoch [700/4000] Training [15/16] Loss: 0.01768 +Epoch [700/4000] Training [16/16] Loss: 0.01583 +Epoch [700/4000] Training metric {'Train/mean dice_metric': 0.9874728322029114, 'Train/mean miou_metric': 0.9752644300460815, 'Train/mean f1': 0.9832068085670471, 'Train/mean precision': 0.9795351624488831, 'Train/mean recall': 0.9869059920310974, 'Train/mean hd95_metric': 2.2851200103759766} +Epoch [700/4000] Validation [1/4] Loss: 0.58711 focal_loss 0.44798 dice_loss 0.13913 +Epoch [700/4000] Validation [2/4] Loss: 0.32916 focal_loss 0.15627 dice_loss 0.17288 +Epoch [700/4000] Validation [3/4] Loss: 0.26396 focal_loss 0.15496 dice_loss 0.10900 +Epoch [700/4000] Validation [4/4] Loss: 0.17782 focal_loss 0.07141 dice_loss 0.10641 +Epoch [700/4000] Validation metric {'Val/mean dice_metric': 0.9630964398384094, 'Val/mean miou_metric': 0.9393518567085266, 'Val/mean f1': 0.9604518413543701, 'Val/mean precision': 0.9543053507804871, 'Val/mean recall': 0.9666779637336731, 'Val/mean hd95_metric': 7.292661190032959} +Cheakpoint... +Epoch [700/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9631], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9630964398384094, 'Val/mean miou_metric': 0.9393518567085266, 'Val/mean f1': 0.9604518413543701, 'Val/mean precision': 0.9543053507804871, 'Val/mean recall': 0.9666779637336731, 'Val/mean hd95_metric': 7.292661190032959} +Epoch [701/4000] Training [1/16] Loss: 0.01567 +Epoch [701/4000] Training [2/16] Loss: 0.01648 +Epoch [701/4000] Training [3/16] Loss: 0.01766 +Epoch [701/4000] Training [4/16] Loss: 0.02374 +Epoch [701/4000] Training [5/16] Loss: 0.01913 +Epoch [701/4000] Training [6/16] Loss: 0.02145 +Epoch [701/4000] Training [7/16] Loss: 0.02001 +Epoch [701/4000] Training [8/16] Loss: 0.01495 +Epoch [701/4000] Training [9/16] Loss: 0.01316 +Epoch [701/4000] Training [10/16] Loss: 0.01431 +Epoch [701/4000] Training [11/16] Loss: 0.01517 +Epoch [701/4000] Training [12/16] Loss: 0.01425 +Epoch [701/4000] Training [13/16] Loss: 0.01616 +Epoch [701/4000] Training [14/16] Loss: 0.01384 +Epoch [701/4000] Training [15/16] Loss: 0.01782 +Epoch [701/4000] Training [16/16] Loss: 0.01618 +Epoch [701/4000] Training metric {'Train/mean dice_metric': 0.9887157678604126, 'Train/mean miou_metric': 0.9774941802024841, 'Train/mean f1': 0.9851177334785461, 'Train/mean precision': 0.981112539768219, 'Train/mean recall': 0.9891557693481445, 'Train/mean hd95_metric': 2.8868021965026855} +Epoch [701/4000] Validation [1/4] Loss: 0.63097 focal_loss 0.47348 dice_loss 0.15749 +Epoch [701/4000] Validation [2/4] Loss: 0.25109 focal_loss 0.10998 dice_loss 0.14111 +Epoch [701/4000] Validation [3/4] Loss: 0.20483 focal_loss 0.10528 dice_loss 0.09955 +Epoch [701/4000] Validation [4/4] Loss: 0.28436 focal_loss 0.15802 dice_loss 0.12633 +Epoch [701/4000] Validation metric {'Val/mean dice_metric': 0.9621986150741577, 'Val/mean miou_metric': 0.9394245147705078, 'Val/mean f1': 0.9603261351585388, 'Val/mean precision': 0.9545429348945618, 'Val/mean recall': 0.9661799073219299, 'Val/mean hd95_metric': 7.832781791687012} +Cheakpoint... +Epoch [701/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9621986150741577, 'Val/mean miou_metric': 0.9394245147705078, 'Val/mean f1': 0.9603261351585388, 'Val/mean precision': 0.9545429348945618, 'Val/mean recall': 0.9661799073219299, 'Val/mean hd95_metric': 7.832781791687012} +Epoch [702/4000] Training [1/16] Loss: 0.01398 +Epoch [702/4000] Training [2/16] Loss: 0.01615 +Epoch [702/4000] Training [3/16] Loss: 0.01798 +Epoch [702/4000] Training [4/16] Loss: 0.02080 +Epoch [702/4000] Training [5/16] Loss: 0.01988 +Epoch [702/4000] Training [6/16] Loss: 0.01403 +Epoch [702/4000] Training [7/16] Loss: 0.01405 +Epoch [702/4000] Training [8/16] Loss: 0.01455 +Epoch [702/4000] Training [9/16] Loss: 0.02022 +Epoch [702/4000] Training [10/16] Loss: 0.01994 +Epoch [702/4000] Training [11/16] Loss: 0.01420 +Epoch [702/4000] Training [12/16] Loss: 0.01314 +Epoch [702/4000] Training [13/16] Loss: 0.01541 +Epoch [702/4000] Training [14/16] Loss: 0.01428 +Epoch [702/4000] Training [15/16] Loss: 0.01711 +Epoch [702/4000] Training [16/16] Loss: 0.02653 +Epoch [702/4000] Training metric {'Train/mean dice_metric': 0.9891573786735535, 'Train/mean miou_metric': 0.9783769845962524, 'Train/mean f1': 0.9861957430839539, 'Train/mean precision': 0.9816470742225647, 'Train/mean recall': 0.9907866716384888, 'Train/mean hd95_metric': 1.708790898323059} +Epoch [702/4000] Validation [1/4] Loss: 0.14891 focal_loss 0.07785 dice_loss 0.07106 +Epoch [702/4000] Validation [2/4] Loss: 0.32022 focal_loss 0.15942 dice_loss 0.16080 +Epoch [702/4000] Validation [3/4] Loss: 0.24368 focal_loss 0.14597 dice_loss 0.09772 +Epoch [702/4000] Validation [4/4] Loss: 0.24885 focal_loss 0.12973 dice_loss 0.11912 +Epoch [702/4000] Validation metric {'Val/mean dice_metric': 0.963916003704071, 'Val/mean miou_metric': 0.9410102963447571, 'Val/mean f1': 0.9656208753585815, 'Val/mean precision': 0.9622030854225159, 'Val/mean recall': 0.9690631031990051, 'Val/mean hd95_metric': 7.174471855163574} +Cheakpoint... +Epoch [702/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963916003704071, 'Val/mean miou_metric': 0.9410102963447571, 'Val/mean f1': 0.9656208753585815, 'Val/mean precision': 0.9622030854225159, 'Val/mean recall': 0.9690631031990051, 'Val/mean hd95_metric': 7.174471855163574} +Epoch [703/4000] Training [1/16] Loss: 0.01734 +Epoch [703/4000] Training [2/16] Loss: 0.02042 +Epoch [703/4000] Training [3/16] Loss: 0.01342 +Epoch [703/4000] Training [4/16] Loss: 0.01451 +Epoch [703/4000] Training [5/16] Loss: 0.01639 +Epoch [703/4000] Training [6/16] Loss: 0.01103 +Epoch [703/4000] Training [7/16] Loss: 0.01591 +Epoch [703/4000] Training [8/16] Loss: 0.01726 +Epoch [703/4000] Training [9/16] Loss: 0.01287 +Epoch [703/4000] Training [10/16] Loss: 0.02216 +Epoch [703/4000] Training [11/16] Loss: 0.01619 +Epoch [703/4000] Training [12/16] Loss: 0.01995 +Epoch [703/4000] Training [13/16] Loss: 0.01385 +Epoch [703/4000] Training [14/16] Loss: 0.01683 +Epoch [703/4000] Training [15/16] Loss: 0.01293 +Epoch [703/4000] Training [16/16] Loss: 0.01562 +Epoch [703/4000] Training metric {'Train/mean dice_metric': 0.9887521266937256, 'Train/mean miou_metric': 0.9775991439819336, 'Train/mean f1': 0.9858703017234802, 'Train/mean precision': 0.9815829396247864, 'Train/mean recall': 0.9901952743530273, 'Train/mean hd95_metric': 1.5966479778289795} +Epoch [703/4000] Validation [1/4] Loss: 0.49451 focal_loss 0.36459 dice_loss 0.12992 +Epoch [703/4000] Validation [2/4] Loss: 0.28440 focal_loss 0.13744 dice_loss 0.14696 +Epoch [703/4000] Validation [3/4] Loss: 0.23866 focal_loss 0.12574 dice_loss 0.11291 +Epoch [703/4000] Validation [4/4] Loss: 0.20853 focal_loss 0.09501 dice_loss 0.11352 +Epoch [703/4000] Validation metric {'Val/mean dice_metric': 0.9626283645629883, 'Val/mean miou_metric': 0.9392839670181274, 'Val/mean f1': 0.9649137854576111, 'Val/mean precision': 0.9654000997543335, 'Val/mean recall': 0.9644278883934021, 'Val/mean hd95_metric': 6.895949363708496} +Cheakpoint... +Epoch [703/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9626], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9626283645629883, 'Val/mean miou_metric': 0.9392839670181274, 'Val/mean f1': 0.9649137854576111, 'Val/mean precision': 0.9654000997543335, 'Val/mean recall': 0.9644278883934021, 'Val/mean hd95_metric': 6.895949363708496} +Epoch [704/4000] Training [1/16] Loss: 0.01415 +Epoch [704/4000] Training [2/16] Loss: 0.02139 +Epoch [704/4000] Training [3/16] Loss: 0.01827 +Epoch [704/4000] Training [4/16] Loss: 0.01131 +Epoch [704/4000] Training [5/16] Loss: 0.01467 +Epoch [704/4000] Training [6/16] Loss: 0.01888 +Epoch [704/4000] Training [7/16] Loss: 0.01229 +Epoch [704/4000] Training [8/16] Loss: 0.01436 +Epoch [704/4000] Training [9/16] Loss: 0.03777 +Epoch [704/4000] Training [10/16] Loss: 0.01261 +Epoch [704/4000] Training [11/16] Loss: 0.01327 +Epoch [704/4000] Training [12/16] Loss: 0.01662 +Epoch [704/4000] Training [13/16] Loss: 0.01158 +Epoch [704/4000] Training [14/16] Loss: 0.01384 +Epoch [704/4000] Training [15/16] Loss: 0.01831 +Epoch [704/4000] Training [16/16] Loss: 0.01305 +Epoch [704/4000] Training metric {'Train/mean dice_metric': 0.9897345900535583, 'Train/mean miou_metric': 0.9795658588409424, 'Train/mean f1': 0.9866196513175964, 'Train/mean precision': 0.9820270538330078, 'Train/mean recall': 0.9912554025650024, 'Train/mean hd95_metric': 1.5231707096099854} +Epoch [704/4000] Validation [1/4] Loss: 0.37544 focal_loss 0.27015 dice_loss 0.10529 +Epoch [704/4000] Validation [2/4] Loss: 0.22023 focal_loss 0.08580 dice_loss 0.13443 +Epoch [704/4000] Validation [3/4] Loss: 0.13788 focal_loss 0.07337 dice_loss 0.06451 +Epoch [704/4000] Validation [4/4] Loss: 0.18135 focal_loss 0.08743 dice_loss 0.09393 +Epoch [704/4000] Validation metric {'Val/mean dice_metric': 0.9660199880599976, 'Val/mean miou_metric': 0.944959819316864, 'Val/mean f1': 0.967260479927063, 'Val/mean precision': 0.9624731540679932, 'Val/mean recall': 0.972095787525177, 'Val/mean hd95_metric': 5.778517246246338} +Cheakpoint... +Epoch [704/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660199880599976, 'Val/mean miou_metric': 0.944959819316864, 'Val/mean f1': 0.967260479927063, 'Val/mean precision': 0.9624731540679932, 'Val/mean recall': 0.972095787525177, 'Val/mean hd95_metric': 5.778517246246338} +Epoch [705/4000] Training [1/16] Loss: 0.01301 +Epoch [705/4000] Training [2/16] Loss: 0.01149 +Epoch [705/4000] Training [3/16] Loss: 0.01538 +Epoch [705/4000] Training [4/16] Loss: 0.01302 +Epoch [705/4000] Training [5/16] Loss: 0.01712 +Epoch [705/4000] Training [6/16] Loss: 0.01472 +Epoch [705/4000] Training [7/16] Loss: 0.01700 +Epoch [705/4000] Training [8/16] Loss: 0.01261 +Epoch [705/4000] Training [9/16] Loss: 0.01338 +Epoch [705/4000] Training [10/16] Loss: 0.01241 +Epoch [705/4000] Training [11/16] Loss: 0.01432 +Epoch [705/4000] Training [12/16] Loss: 0.01675 +Epoch [705/4000] Training [13/16] Loss: 0.01376 +Epoch [705/4000] Training [14/16] Loss: 0.01620 +Epoch [705/4000] Training [15/16] Loss: 0.08643 +Epoch [705/4000] Training [16/16] Loss: 0.01170 +Epoch [705/4000] Training metric {'Train/mean dice_metric': 0.9873917102813721, 'Train/mean miou_metric': 0.9761378169059753, 'Train/mean f1': 0.9860497117042542, 'Train/mean precision': 0.9824907779693604, 'Train/mean recall': 0.9896344542503357, 'Train/mean hd95_metric': 1.9480831623077393} +Epoch [705/4000] Validation [1/4] Loss: 0.30763 focal_loss 0.20279 dice_loss 0.10484 +Epoch [705/4000] Validation [2/4] Loss: 0.31566 focal_loss 0.15791 dice_loss 0.15775 +Epoch [705/4000] Validation [3/4] Loss: 0.27873 focal_loss 0.17958 dice_loss 0.09916 +Epoch [705/4000] Validation [4/4] Loss: 0.19532 focal_loss 0.09212 dice_loss 0.10320 +Epoch [705/4000] Validation metric {'Val/mean dice_metric': 0.9634283185005188, 'Val/mean miou_metric': 0.9407269358634949, 'Val/mean f1': 0.9643463492393494, 'Val/mean precision': 0.9564670920372009, 'Val/mean recall': 0.9723566174507141, 'Val/mean hd95_metric': 7.927693843841553} +Cheakpoint... +Epoch [705/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9634283185005188, 'Val/mean miou_metric': 0.9407269358634949, 'Val/mean f1': 0.9643463492393494, 'Val/mean precision': 0.9564670920372009, 'Val/mean recall': 0.9723566174507141, 'Val/mean hd95_metric': 7.927693843841553} +Epoch [706/4000] Training [1/16] Loss: 0.01368 +Epoch [706/4000] Training [2/16] Loss: 0.01927 +Epoch [706/4000] Training [3/16] Loss: 0.01337 +Epoch [706/4000] Training [4/16] Loss: 0.01833 +Epoch [706/4000] Training [5/16] Loss: 0.01499 +Epoch [706/4000] Training [6/16] Loss: 0.01617 +Epoch [706/4000] Training [7/16] Loss: 0.01091 +Epoch [706/4000] Training [8/16] Loss: 0.01315 +Epoch [706/4000] Training [9/16] Loss: 0.01638 +Epoch [706/4000] Training [10/16] Loss: 0.01793 +Epoch [706/4000] Training [11/16] Loss: 0.01323 +Epoch [706/4000] Training [12/16] Loss: 0.01830 +Epoch [706/4000] Training [13/16] Loss: 0.01596 +Epoch [706/4000] Training [14/16] Loss: 0.01867 +Epoch [706/4000] Training [15/16] Loss: 0.03436 +Epoch [706/4000] Training [16/16] Loss: 0.01663 +Epoch [706/4000] Training metric {'Train/mean dice_metric': 0.9891365170478821, 'Train/mean miou_metric': 0.9783545732498169, 'Train/mean f1': 0.9860891103744507, 'Train/mean precision': 0.981153130531311, 'Train/mean recall': 0.9910750389099121, 'Train/mean hd95_metric': 2.2837460041046143} +Epoch [706/4000] Validation [1/4] Loss: 0.34411 focal_loss 0.22794 dice_loss 0.11617 +Epoch [706/4000] Validation [2/4] Loss: 0.19739 focal_loss 0.08276 dice_loss 0.11462 +Epoch [706/4000] Validation [3/4] Loss: 0.16268 focal_loss 0.08373 dice_loss 0.07895 +Epoch [706/4000] Validation [4/4] Loss: 0.27512 focal_loss 0.11763 dice_loss 0.15749 +Epoch [706/4000] Validation metric {'Val/mean dice_metric': 0.9649792909622192, 'Val/mean miou_metric': 0.9428680539131165, 'Val/mean f1': 0.9654117226600647, 'Val/mean precision': 0.957088053226471, 'Val/mean recall': 0.9738815426826477, 'Val/mean hd95_metric': 6.823376655578613} +Cheakpoint... +Epoch [706/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649792909622192, 'Val/mean miou_metric': 0.9428680539131165, 'Val/mean f1': 0.9654117226600647, 'Val/mean precision': 0.957088053226471, 'Val/mean recall': 0.9738815426826477, 'Val/mean hd95_metric': 6.823376655578613} +Epoch [707/4000] Training [1/16] Loss: 0.01656 +Epoch [707/4000] Training [2/16] Loss: 0.01504 +Epoch [707/4000] Training [3/16] Loss: 0.01649 +Epoch [707/4000] Training [4/16] Loss: 0.01458 +Epoch [707/4000] Training [5/16] Loss: 0.01487 +Epoch [707/4000] Training [6/16] Loss: 0.01316 +Epoch [707/4000] Training [7/16] Loss: 0.01358 +Epoch [707/4000] Training [8/16] Loss: 0.01286 +Epoch [707/4000] Training [9/16] Loss: 0.01611 +Epoch [707/4000] Training [10/16] Loss: 0.01624 +Epoch [707/4000] Training [11/16] Loss: 0.01633 +Epoch [707/4000] Training [12/16] Loss: 0.01022 +Epoch [707/4000] Training [13/16] Loss: 0.03781 +Epoch [707/4000] Training [14/16] Loss: 0.01677 +Epoch [707/4000] Training [15/16] Loss: 0.01583 +Epoch [707/4000] Training [16/16] Loss: 0.01566 +Epoch [707/4000] Training metric {'Train/mean dice_metric': 0.9899275302886963, 'Train/mean miou_metric': 0.9798939228057861, 'Train/mean f1': 0.986247718334198, 'Train/mean precision': 0.9814258813858032, 'Train/mean recall': 0.9911172389984131, 'Train/mean hd95_metric': 1.7813825607299805} +Epoch [707/4000] Validation [1/4] Loss: 0.20445 focal_loss 0.12760 dice_loss 0.07685 +Epoch [707/4000] Validation [2/4] Loss: 0.46325 focal_loss 0.25993 dice_loss 0.20332 +Epoch [707/4000] Validation [3/4] Loss: 0.15489 focal_loss 0.08470 dice_loss 0.07019 +Epoch [707/4000] Validation [4/4] Loss: 0.31706 focal_loss 0.15940 dice_loss 0.15766 +Epoch [707/4000] Validation metric {'Val/mean dice_metric': 0.9654759168624878, 'Val/mean miou_metric': 0.944591224193573, 'Val/mean f1': 0.9674155712127686, 'Val/mean precision': 0.9605425596237183, 'Val/mean recall': 0.9743877649307251, 'Val/mean hd95_metric': 6.997218132019043} +Cheakpoint... +Epoch [707/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654759168624878, 'Val/mean miou_metric': 0.944591224193573, 'Val/mean f1': 0.9674155712127686, 'Val/mean precision': 0.9605425596237183, 'Val/mean recall': 0.9743877649307251, 'Val/mean hd95_metric': 6.997218132019043} +Epoch [708/4000] Training [1/16] Loss: 0.01376 +Epoch [708/4000] Training [2/16] Loss: 0.01101 +Epoch [708/4000] Training [3/16] Loss: 0.01597 +Epoch [708/4000] Training [4/16] Loss: 0.01457 +Epoch [708/4000] Training [5/16] Loss: 0.01423 +Epoch [708/4000] Training [6/16] Loss: 0.01591 +Epoch [708/4000] Training [7/16] Loss: 0.01281 +Epoch [708/4000] Training [8/16] Loss: 0.01224 +Epoch [708/4000] Training [9/16] Loss: 0.01314 +Epoch [708/4000] Training [10/16] Loss: 0.01269 +Epoch [708/4000] Training [11/16] Loss: 0.01237 +Epoch [708/4000] Training [12/16] Loss: 0.02258 +Epoch [708/4000] Training [13/16] Loss: 0.01509 +Epoch [708/4000] Training [14/16] Loss: 0.01417 +Epoch [708/4000] Training [15/16] Loss: 0.01745 +Epoch [708/4000] Training [16/16] Loss: 0.01299 +Epoch [708/4000] Training metric {'Train/mean dice_metric': 0.9889333248138428, 'Train/mean miou_metric': 0.9790791273117065, 'Train/mean f1': 0.9866337180137634, 'Train/mean precision': 0.9820316433906555, 'Train/mean recall': 0.9912791848182678, 'Train/mean hd95_metric': 1.437635064125061} +Epoch [708/4000] Validation [1/4] Loss: 0.19995 focal_loss 0.12707 dice_loss 0.07288 +Epoch [708/4000] Validation [2/4] Loss: 0.33544 focal_loss 0.16040 dice_loss 0.17504 +Epoch [708/4000] Validation [3/4] Loss: 0.13557 focal_loss 0.06977 dice_loss 0.06581 +Epoch [708/4000] Validation [4/4] Loss: 0.28200 focal_loss 0.12469 dice_loss 0.15731 +Epoch [708/4000] Validation metric {'Val/mean dice_metric': 0.961300253868103, 'Val/mean miou_metric': 0.9401315450668335, 'Val/mean f1': 0.9643933176994324, 'Val/mean precision': 0.959437906742096, 'Val/mean recall': 0.96940016746521, 'Val/mean hd95_metric': 6.931309700012207} +Cheakpoint... +Epoch [708/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961300253868103, 'Val/mean miou_metric': 0.9401315450668335, 'Val/mean f1': 0.9643933176994324, 'Val/mean precision': 0.959437906742096, 'Val/mean recall': 0.96940016746521, 'Val/mean hd95_metric': 6.931309700012207} +Epoch [709/4000] Training [1/16] Loss: 0.01337 +Epoch [709/4000] Training [2/16] Loss: 0.01674 +Epoch [709/4000] Training [3/16] Loss: 0.01496 +Epoch [709/4000] Training [4/16] Loss: 0.01222 +Epoch [709/4000] Training [5/16] Loss: 0.02278 +Epoch [709/4000] Training [6/16] Loss: 0.02113 +Epoch [709/4000] Training [7/16] Loss: 0.03006 +Epoch [709/4000] Training [8/16] Loss: 0.01433 +Epoch [709/4000] Training [9/16] Loss: 0.06589 +Epoch [709/4000] Training [10/16] Loss: 0.01604 +Epoch [709/4000] Training [11/16] Loss: 0.01832 +Epoch [709/4000] Training [12/16] Loss: 0.01376 +Epoch [709/4000] Training [13/16] Loss: 0.01548 +Epoch [709/4000] Training [14/16] Loss: 0.01328 +Epoch [709/4000] Training [15/16] Loss: 0.01698 +Epoch [709/4000] Training [16/16] Loss: 0.01654 +Epoch [709/4000] Training metric {'Train/mean dice_metric': 0.9870036244392395, 'Train/mean miou_metric': 0.9750003218650818, 'Train/mean f1': 0.9840483069419861, 'Train/mean precision': 0.9792072772979736, 'Train/mean recall': 0.9889373779296875, 'Train/mean hd95_metric': 2.6223154067993164} +Epoch [709/4000] Validation [1/4] Loss: 0.30447 focal_loss 0.20456 dice_loss 0.09992 +Epoch [709/4000] Validation [2/4] Loss: 0.58247 focal_loss 0.34386 dice_loss 0.23861 +Epoch [709/4000] Validation [3/4] Loss: 0.33310 focal_loss 0.19842 dice_loss 0.13467 +Epoch [709/4000] Validation [4/4] Loss: 0.27527 focal_loss 0.11633 dice_loss 0.15894 +Epoch [709/4000] Validation metric {'Val/mean dice_metric': 0.9591849446296692, 'Val/mean miou_metric': 0.9349716901779175, 'Val/mean f1': 0.9598285555839539, 'Val/mean precision': 0.9516589641571045, 'Val/mean recall': 0.9681394100189209, 'Val/mean hd95_metric': 9.857351303100586} +Cheakpoint... +Epoch [709/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9592], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9591849446296692, 'Val/mean miou_metric': 0.9349716901779175, 'Val/mean f1': 0.9598285555839539, 'Val/mean precision': 0.9516589641571045, 'Val/mean recall': 0.9681394100189209, 'Val/mean hd95_metric': 9.857351303100586} +Epoch [710/4000] Training [1/16] Loss: 0.01454 +Epoch [710/4000] Training [2/16] Loss: 0.01605 +Epoch [710/4000] Training [3/16] Loss: 0.01238 +Epoch [710/4000] Training [4/16] Loss: 0.01552 +Epoch [710/4000] Training [5/16] Loss: 0.03466 +Epoch [710/4000] Training [6/16] Loss: 0.01779 +Epoch [710/4000] Training [7/16] Loss: 0.01132 +Epoch [710/4000] Training [8/16] Loss: 0.03371 +Epoch [710/4000] Training [9/16] Loss: 0.01574 +Epoch [710/4000] Training [10/16] Loss: 0.01481 +Epoch [710/4000] Training [11/16] Loss: 0.01674 +Epoch [710/4000] Training [12/16] Loss: 0.02261 +Epoch [710/4000] Training [13/16] Loss: 0.01179 +Epoch [710/4000] Training [14/16] Loss: 0.01410 +Epoch [710/4000] Training [15/16] Loss: 0.01181 +Epoch [710/4000] Training [16/16] Loss: 0.01449 +Epoch [710/4000] Training metric {'Train/mean dice_metric': 0.987835168838501, 'Train/mean miou_metric': 0.9759032130241394, 'Train/mean f1': 0.9848953485488892, 'Train/mean precision': 0.9796125292778015, 'Train/mean recall': 0.990235447883606, 'Train/mean hd95_metric': 2.349666118621826} +Epoch [710/4000] Validation [1/4] Loss: 0.18511 focal_loss 0.11657 dice_loss 0.06854 +Epoch [710/4000] Validation [2/4] Loss: 0.26143 focal_loss 0.12058 dice_loss 0.14085 +Epoch [710/4000] Validation [3/4] Loss: 0.19658 focal_loss 0.11520 dice_loss 0.08138 +Epoch [710/4000] Validation [4/4] Loss: 0.31591 focal_loss 0.16395 dice_loss 0.15196 +Epoch [710/4000] Validation metric {'Val/mean dice_metric': 0.9615674018859863, 'Val/mean miou_metric': 0.9374176859855652, 'Val/mean f1': 0.9628309607505798, 'Val/mean precision': 0.9526707530021667, 'Val/mean recall': 0.9732101559638977, 'Val/mean hd95_metric': 8.581169128417969} +Cheakpoint... +Epoch [710/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9616], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9615674018859863, 'Val/mean miou_metric': 0.9374176859855652, 'Val/mean f1': 0.9628309607505798, 'Val/mean precision': 0.9526707530021667, 'Val/mean recall': 0.9732101559638977, 'Val/mean hd95_metric': 8.581169128417969} +Epoch [711/4000] Training [1/16] Loss: 0.01864 +Epoch [711/4000] Training [2/16] Loss: 0.01476 +Epoch [711/4000] Training [3/16] Loss: 0.01661 +Epoch [711/4000] Training [4/16] Loss: 0.02048 +Epoch [711/4000] Training [5/16] Loss: 0.01288 +Epoch [711/4000] Training [6/16] Loss: 0.01433 +Epoch [711/4000] Training [7/16] Loss: 0.01486 +Epoch [711/4000] Training [8/16] Loss: 0.01983 +Epoch [711/4000] Training [9/16] Loss: 0.01479 +Epoch [711/4000] Training [10/16] Loss: 0.01392 +Epoch [711/4000] Training [11/16] Loss: 0.01678 +Epoch [711/4000] Training [12/16] Loss: 0.01529 +Epoch [711/4000] Training [13/16] Loss: 0.01485 +Epoch [711/4000] Training [14/16] Loss: 0.01188 +Epoch [711/4000] Training [15/16] Loss: 0.02052 +Epoch [711/4000] Training [16/16] Loss: 0.01415 +Epoch [711/4000] Training metric {'Train/mean dice_metric': 0.9891772270202637, 'Train/mean miou_metric': 0.9784372448921204, 'Train/mean f1': 0.986318051815033, 'Train/mean precision': 0.9821076989173889, 'Train/mean recall': 0.9905646443367004, 'Train/mean hd95_metric': 1.5695314407348633} +Epoch [711/4000] Validation [1/4] Loss: 0.53723 focal_loss 0.41379 dice_loss 0.12344 +Epoch [711/4000] Validation [2/4] Loss: 0.42046 focal_loss 0.19436 dice_loss 0.22611 +Epoch [711/4000] Validation [3/4] Loss: 0.15544 focal_loss 0.08266 dice_loss 0.07278 +Epoch [711/4000] Validation [4/4] Loss: 0.25148 focal_loss 0.11268 dice_loss 0.13880 +Epoch [711/4000] Validation metric {'Val/mean dice_metric': 0.9637476205825806, 'Val/mean miou_metric': 0.9417923092842102, 'Val/mean f1': 0.9671828150749207, 'Val/mean precision': 0.9646710157394409, 'Val/mean recall': 0.9697078466415405, 'Val/mean hd95_metric': 6.5232367515563965} +Cheakpoint... +Epoch [711/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637476205825806, 'Val/mean miou_metric': 0.9417923092842102, 'Val/mean f1': 0.9671828150749207, 'Val/mean precision': 0.9646710157394409, 'Val/mean recall': 0.9697078466415405, 'Val/mean hd95_metric': 6.5232367515563965} +Epoch [712/4000] Training [1/16] Loss: 0.01198 +Epoch [712/4000] Training [2/16] Loss: 0.01621 +Epoch [712/4000] Training [3/16] Loss: 0.01722 +Epoch [712/4000] Training [4/16] Loss: 0.01450 +Epoch [712/4000] Training [5/16] Loss: 0.01304 +Epoch [712/4000] Training [6/16] Loss: 0.01729 +Epoch [712/4000] Training [7/16] Loss: 0.01118 +Epoch [712/4000] Training [8/16] Loss: 0.01771 +Epoch [712/4000] Training [9/16] Loss: 0.01468 +Epoch [712/4000] Training [10/16] Loss: 0.01125 +Epoch [712/4000] Training [11/16] Loss: 0.01688 +Epoch [712/4000] Training [12/16] Loss: 0.01235 +Epoch [712/4000] Training [13/16] Loss: 0.01212 +Epoch [712/4000] Training [14/16] Loss: 0.01403 +Epoch [712/4000] Training [15/16] Loss: 0.00967 +Epoch [712/4000] Training [16/16] Loss: 0.02665 +Epoch [712/4000] Training metric {'Train/mean dice_metric': 0.9898573160171509, 'Train/mean miou_metric': 0.9797858595848083, 'Train/mean f1': 0.987088143825531, 'Train/mean precision': 0.9828159213066101, 'Train/mean recall': 0.9913976788520813, 'Train/mean hd95_metric': 1.575418472290039} +Epoch [712/4000] Validation [1/4] Loss: 0.17740 focal_loss 0.11134 dice_loss 0.06606 +Epoch [712/4000] Validation [2/4] Loss: 0.52158 focal_loss 0.22254 dice_loss 0.29904 +Epoch [712/4000] Validation [3/4] Loss: 0.18716 focal_loss 0.10055 dice_loss 0.08661 +Epoch [712/4000] Validation [4/4] Loss: 0.26720 focal_loss 0.12134 dice_loss 0.14586 +Epoch [712/4000] Validation metric {'Val/mean dice_metric': 0.9642534255981445, 'Val/mean miou_metric': 0.9431989789009094, 'Val/mean f1': 0.9690052270889282, 'Val/mean precision': 0.9644907712936401, 'Val/mean recall': 0.9735622406005859, 'Val/mean hd95_metric': 7.090234279632568} +Cheakpoint... +Epoch [712/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9643], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9642534255981445, 'Val/mean miou_metric': 0.9431989789009094, 'Val/mean f1': 0.9690052270889282, 'Val/mean precision': 0.9644907712936401, 'Val/mean recall': 0.9735622406005859, 'Val/mean hd95_metric': 7.090234279632568} +Epoch [713/4000] Training [1/16] Loss: 0.01310 +Epoch [713/4000] Training [2/16] Loss: 0.01616 +Epoch [713/4000] Training [3/16] Loss: 0.01373 +Epoch [713/4000] Training [4/16] Loss: 0.01141 +Epoch [713/4000] Training [5/16] Loss: 0.01412 +Epoch [713/4000] Training [6/16] Loss: 0.01124 +Epoch [713/4000] Training [7/16] Loss: 0.01235 +Epoch [713/4000] Training [8/16] Loss: 0.01782 +Epoch [713/4000] Training [9/16] Loss: 0.01210 +Epoch [713/4000] Training [10/16] Loss: 0.01424 +Epoch [713/4000] Training [11/16] Loss: 0.02094 +Epoch [713/4000] Training [12/16] Loss: 0.01127 +Epoch [713/4000] Training [13/16] Loss: 0.01508 +Epoch [713/4000] Training [14/16] Loss: 0.01944 +Epoch [713/4000] Training [15/16] Loss: 0.01201 +Epoch [713/4000] Training [16/16] Loss: 0.01918 +Epoch [713/4000] Training metric {'Train/mean dice_metric': 0.9897974133491516, 'Train/mean miou_metric': 0.9796924591064453, 'Train/mean f1': 0.9860799312591553, 'Train/mean precision': 0.9808909296989441, 'Train/mean recall': 0.9913240671157837, 'Train/mean hd95_metric': 1.6564974784851074} +Epoch [713/4000] Validation [1/4] Loss: 0.37143 focal_loss 0.25065 dice_loss 0.12078 +Epoch [713/4000] Validation [2/4] Loss: 0.26553 focal_loss 0.13298 dice_loss 0.13254 +Epoch [713/4000] Validation [3/4] Loss: 0.12865 focal_loss 0.05817 dice_loss 0.07048 +Epoch [713/4000] Validation [4/4] Loss: 0.29299 focal_loss 0.15626 dice_loss 0.13673 +Epoch [713/4000] Validation metric {'Val/mean dice_metric': 0.9651899337768555, 'Val/mean miou_metric': 0.9434003829956055, 'Val/mean f1': 0.9657407402992249, 'Val/mean precision': 0.9612157344818115, 'Val/mean recall': 0.9703083038330078, 'Val/mean hd95_metric': 6.639368534088135} +Cheakpoint... +Epoch [713/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651899337768555, 'Val/mean miou_metric': 0.9434003829956055, 'Val/mean f1': 0.9657407402992249, 'Val/mean precision': 0.9612157344818115, 'Val/mean recall': 0.9703083038330078, 'Val/mean hd95_metric': 6.639368534088135} +Epoch [714/4000] Training [1/16] Loss: 0.01284 +Epoch [714/4000] Training [2/16] Loss: 0.01166 +Epoch [714/4000] Training [3/16] Loss: 0.01445 +Epoch [714/4000] Training [4/16] Loss: 0.01359 +Epoch [714/4000] Training [5/16] Loss: 0.01378 +Epoch [714/4000] Training [6/16] Loss: 0.01743 +Epoch [714/4000] Training [7/16] Loss: 0.01144 +Epoch [714/4000] Training [8/16] Loss: 0.01692 +Epoch [714/4000] Training [9/16] Loss: 0.01091 +Epoch [714/4000] Training [10/16] Loss: 0.03049 +Epoch [714/4000] Training [11/16] Loss: 0.01685 +Epoch [714/4000] Training [12/16] Loss: 0.01256 +Epoch [714/4000] Training [13/16] Loss: 0.01288 +Epoch [714/4000] Training [14/16] Loss: 0.01261 +Epoch [714/4000] Training [15/16] Loss: 0.01362 +Epoch [714/4000] Training [16/16] Loss: 0.01455 +Epoch [714/4000] Training metric {'Train/mean dice_metric': 0.9900765419006348, 'Train/mean miou_metric': 0.9801884293556213, 'Train/mean f1': 0.9868637919425964, 'Train/mean precision': 0.9824165105819702, 'Train/mean recall': 0.9913514852523804, 'Train/mean hd95_metric': 1.4496828317642212} +Epoch [714/4000] Validation [1/4] Loss: 0.58507 focal_loss 0.42959 dice_loss 0.15549 +Epoch [714/4000] Validation [2/4] Loss: 0.22115 focal_loss 0.09757 dice_loss 0.12358 +Epoch [714/4000] Validation [3/4] Loss: 0.12187 focal_loss 0.06019 dice_loss 0.06168 +Epoch [714/4000] Validation [4/4] Loss: 0.26909 focal_loss 0.15814 dice_loss 0.11095 +Epoch [714/4000] Validation metric {'Val/mean dice_metric': 0.9651400446891785, 'Val/mean miou_metric': 0.9436437487602234, 'Val/mean f1': 0.9655015468597412, 'Val/mean precision': 0.9662518501281738, 'Val/mean recall': 0.9647523164749146, 'Val/mean hd95_metric': 6.131402969360352} +Cheakpoint... +Epoch [714/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651400446891785, 'Val/mean miou_metric': 0.9436437487602234, 'Val/mean f1': 0.9655015468597412, 'Val/mean precision': 0.9662518501281738, 'Val/mean recall': 0.9647523164749146, 'Val/mean hd95_metric': 6.131402969360352} +Epoch [715/4000] Training [1/16] Loss: 0.01065 +Epoch [715/4000] Training [2/16] Loss: 0.01210 +Epoch [715/4000] Training [3/16] Loss: 0.01264 +Epoch [715/4000] Training [4/16] Loss: 0.01223 +Epoch [715/4000] Training [5/16] Loss: 0.01408 +Epoch [715/4000] Training [6/16] Loss: 0.01573 +Epoch [715/4000] Training [7/16] Loss: 0.01179 +Epoch [715/4000] Training [8/16] Loss: 0.01482 +Epoch [715/4000] Training [9/16] Loss: 0.01550 +Epoch [715/4000] Training [10/16] Loss: 0.01290 +Epoch [715/4000] Training [11/16] Loss: 0.01436 +Epoch [715/4000] Training [12/16] Loss: 0.01335 +Epoch [715/4000] Training [13/16] Loss: 0.01077 +Epoch [715/4000] Training [14/16] Loss: 0.01579 +Epoch [715/4000] Training [15/16] Loss: 0.01197 +Epoch [715/4000] Training [16/16] Loss: 0.01554 +Epoch [715/4000] Training metric {'Train/mean dice_metric': 0.9899129867553711, 'Train/mean miou_metric': 0.9799278974533081, 'Train/mean f1': 0.9871028065681458, 'Train/mean precision': 0.982928454875946, 'Train/mean recall': 0.9913128018379211, 'Train/mean hd95_metric': 1.3109673261642456} +Epoch [715/4000] Validation [1/4] Loss: 0.51276 focal_loss 0.38681 dice_loss 0.12595 +Epoch [715/4000] Validation [2/4] Loss: 0.21311 focal_loss 0.10730 dice_loss 0.10581 +Epoch [715/4000] Validation [3/4] Loss: 0.17193 focal_loss 0.08101 dice_loss 0.09092 +Epoch [715/4000] Validation [4/4] Loss: 0.40478 focal_loss 0.21416 dice_loss 0.19062 +Epoch [715/4000] Validation metric {'Val/mean dice_metric': 0.9643104672431946, 'Val/mean miou_metric': 0.9421703219413757, 'Val/mean f1': 0.9662238955497742, 'Val/mean precision': 0.9633806347846985, 'Val/mean recall': 0.9690840244293213, 'Val/mean hd95_metric': 6.700384616851807} +Cheakpoint... +Epoch [715/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9643], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9643104672431946, 'Val/mean miou_metric': 0.9421703219413757, 'Val/mean f1': 0.9662238955497742, 'Val/mean precision': 0.9633806347846985, 'Val/mean recall': 0.9690840244293213, 'Val/mean hd95_metric': 6.700384616851807} +Epoch [716/4000] Training [1/16] Loss: 0.01118 +Epoch [716/4000] Training [2/16] Loss: 0.02132 +Epoch [716/4000] Training [3/16] Loss: 0.01214 +Epoch [716/4000] Training [4/16] Loss: 0.01592 +Epoch [716/4000] Training [5/16] Loss: 0.01342 +Epoch [716/4000] Training [6/16] Loss: 0.02847 +Epoch [716/4000] Training [7/16] Loss: 0.01229 +Epoch [716/4000] Training [8/16] Loss: 0.02594 +Epoch [716/4000] Training [9/16] Loss: 0.01584 +Epoch [716/4000] Training [10/16] Loss: 0.01117 +Epoch [716/4000] Training [11/16] Loss: 0.01393 +Epoch [716/4000] Training [12/16] Loss: 0.01223 +Epoch [716/4000] Training [13/16] Loss: 0.01467 +Epoch [716/4000] Training [14/16] Loss: 0.01519 +Epoch [716/4000] Training [15/16] Loss: 0.01674 +Epoch [716/4000] Training [16/16] Loss: 0.01646 +Epoch [716/4000] Training metric {'Train/mean dice_metric': 0.9891701936721802, 'Train/mean miou_metric': 0.9785796999931335, 'Train/mean f1': 0.9866176247596741, 'Train/mean precision': 0.9823208451271057, 'Train/mean recall': 0.9909521341323853, 'Train/mean hd95_metric': 1.6452510356903076} +Epoch [716/4000] Validation [1/4] Loss: 0.56389 focal_loss 0.43155 dice_loss 0.13234 +Epoch [716/4000] Validation [2/4] Loss: 0.28051 focal_loss 0.14027 dice_loss 0.14024 +Epoch [716/4000] Validation [3/4] Loss: 0.34916 focal_loss 0.22830 dice_loss 0.12086 +Epoch [716/4000] Validation [4/4] Loss: 0.31589 focal_loss 0.19354 dice_loss 0.12235 +Epoch [716/4000] Validation metric {'Val/mean dice_metric': 0.9655271768569946, 'Val/mean miou_metric': 0.9431018829345703, 'Val/mean f1': 0.9662554264068604, 'Val/mean precision': 0.9648057222366333, 'Val/mean recall': 0.9677095413208008, 'Val/mean hd95_metric': 7.015988349914551} +Cheakpoint... +Epoch [716/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655271768569946, 'Val/mean miou_metric': 0.9431018829345703, 'Val/mean f1': 0.9662554264068604, 'Val/mean precision': 0.9648057222366333, 'Val/mean recall': 0.9677095413208008, 'Val/mean hd95_metric': 7.015988349914551} +Epoch [717/4000] Training [1/16] Loss: 0.01055 +Epoch [717/4000] Training [2/16] Loss: 0.01253 +Epoch [717/4000] Training [3/16] Loss: 0.01467 +Epoch [717/4000] Training [4/16] Loss: 0.01675 +Epoch [717/4000] Training [5/16] Loss: 0.01348 +Epoch [717/4000] Training [6/16] Loss: 0.01369 +Epoch [717/4000] Training [7/16] Loss: 0.01876 +Epoch [717/4000] Training [8/16] Loss: 0.01284 +Epoch [717/4000] Training [9/16] Loss: 0.01222 +Epoch [717/4000] Training [10/16] Loss: 0.01628 +Epoch [717/4000] Training [11/16] Loss: 0.02048 +Epoch [717/4000] Training [12/16] Loss: 0.01425 +Epoch [717/4000] Training [13/16] Loss: 0.01155 +Epoch [717/4000] Training [14/16] Loss: 0.01429 +Epoch [717/4000] Training [15/16] Loss: 0.01346 +Epoch [717/4000] Training [16/16] Loss: 0.01827 +Epoch [717/4000] Training metric {'Train/mean dice_metric': 0.9895974397659302, 'Train/mean miou_metric': 0.9792802333831787, 'Train/mean f1': 0.9864745736122131, 'Train/mean precision': 0.9815635681152344, 'Train/mean recall': 0.9914349913597107, 'Train/mean hd95_metric': 1.6223511695861816} +Epoch [717/4000] Validation [1/4] Loss: 0.60821 focal_loss 0.48336 dice_loss 0.12485 +Epoch [717/4000] Validation [2/4] Loss: 0.22492 focal_loss 0.11428 dice_loss 0.11064 +Epoch [717/4000] Validation [3/4] Loss: 0.11689 focal_loss 0.05959 dice_loss 0.05730 +Epoch [717/4000] Validation [4/4] Loss: 0.24494 focal_loss 0.12845 dice_loss 0.11649 +Epoch [717/4000] Validation metric {'Val/mean dice_metric': 0.9649613499641418, 'Val/mean miou_metric': 0.9438144564628601, 'Val/mean f1': 0.9653144478797913, 'Val/mean precision': 0.9630147814750671, 'Val/mean recall': 0.9676251411437988, 'Val/mean hd95_metric': 6.2998151779174805} +Cheakpoint... +Epoch [717/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649613499641418, 'Val/mean miou_metric': 0.9438144564628601, 'Val/mean f1': 0.9653144478797913, 'Val/mean precision': 0.9630147814750671, 'Val/mean recall': 0.9676251411437988, 'Val/mean hd95_metric': 6.2998151779174805} +Epoch [718/4000] Training [1/16] Loss: 0.01210 +Epoch [718/4000] Training [2/16] Loss: 0.01403 +Epoch [718/4000] Training [3/16] Loss: 0.01754 +Epoch [718/4000] Training [4/16] Loss: 0.01435 +Epoch [718/4000] Training [5/16] Loss: 0.01454 +Epoch [718/4000] Training [6/16] Loss: 0.01331 +Epoch [718/4000] Training [7/16] Loss: 0.01734 +Epoch [718/4000] Training [8/16] Loss: 0.02417 +Epoch [718/4000] Training [9/16] Loss: 0.01620 +Epoch [718/4000] Training [10/16] Loss: 0.01647 +Epoch [718/4000] Training [11/16] Loss: 0.01527 +Epoch [718/4000] Training [12/16] Loss: 0.01528 +Epoch [718/4000] Training [13/16] Loss: 0.01544 +Epoch [718/4000] Training [14/16] Loss: 0.01283 +Epoch [718/4000] Training [15/16] Loss: 0.01449 +Epoch [718/4000] Training [16/16] Loss: 0.01267 +Epoch [718/4000] Training metric {'Train/mean dice_metric': 0.9895503520965576, 'Train/mean miou_metric': 0.9791445136070251, 'Train/mean f1': 0.9865669012069702, 'Train/mean precision': 0.982071578502655, 'Train/mean recall': 0.9911035299301147, 'Train/mean hd95_metric': 1.4168092012405396} +Epoch [718/4000] Validation [1/4] Loss: 0.43816 focal_loss 0.31842 dice_loss 0.11974 +Epoch [718/4000] Validation [2/4] Loss: 0.24459 focal_loss 0.12346 dice_loss 0.12113 +Epoch [718/4000] Validation [3/4] Loss: 0.14029 focal_loss 0.07657 dice_loss 0.06372 +Epoch [718/4000] Validation [4/4] Loss: 0.30093 focal_loss 0.18284 dice_loss 0.11809 +Epoch [718/4000] Validation metric {'Val/mean dice_metric': 0.9655641317367554, 'Val/mean miou_metric': 0.944078266620636, 'Val/mean f1': 0.9677274823188782, 'Val/mean precision': 0.9679742455482483, 'Val/mean recall': 0.9674807786941528, 'Val/mean hd95_metric': 5.4577836990356445} +Cheakpoint... +Epoch [718/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655641317367554, 'Val/mean miou_metric': 0.944078266620636, 'Val/mean f1': 0.9677274823188782, 'Val/mean precision': 0.9679742455482483, 'Val/mean recall': 0.9674807786941528, 'Val/mean hd95_metric': 5.4577836990356445} +Epoch [719/4000] Training [1/16] Loss: 0.01305 +Epoch [719/4000] Training [2/16] Loss: 0.01326 +Epoch [719/4000] Training [3/16] Loss: 0.01299 +Epoch [719/4000] Training [4/16] Loss: 0.01557 +Epoch [719/4000] Training [5/16] Loss: 0.01763 +Epoch [719/4000] Training [6/16] Loss: 0.01800 +Epoch [719/4000] Training [7/16] Loss: 0.01314 +Epoch [719/4000] Training [8/16] Loss: 0.01372 +Epoch [719/4000] Training [9/16] Loss: 0.01440 +Epoch [719/4000] Training [10/16] Loss: 0.01213 +Epoch [719/4000] Training [11/16] Loss: 0.01526 +Epoch [719/4000] Training [12/16] Loss: 0.01423 +Epoch [719/4000] Training [13/16] Loss: 0.01242 +Epoch [719/4000] Training [14/16] Loss: 0.01338 +Epoch [719/4000] Training [15/16] Loss: 0.02138 +Epoch [719/4000] Training [16/16] Loss: 0.01045 +Epoch [719/4000] Training metric {'Train/mean dice_metric': 0.9896687865257263, 'Train/mean miou_metric': 0.9793583154678345, 'Train/mean f1': 0.9852148294448853, 'Train/mean precision': 0.9804843664169312, 'Train/mean recall': 0.9899911880493164, 'Train/mean hd95_metric': 1.631900668144226} +Epoch [719/4000] Validation [1/4] Loss: 0.54482 focal_loss 0.41600 dice_loss 0.12882 +Epoch [719/4000] Validation [2/4] Loss: 0.25907 focal_loss 0.13784 dice_loss 0.12124 +Epoch [719/4000] Validation [3/4] Loss: 0.12829 focal_loss 0.07008 dice_loss 0.05821 +Epoch [719/4000] Validation [4/4] Loss: 0.30305 focal_loss 0.17309 dice_loss 0.12996 +Epoch [719/4000] Validation metric {'Val/mean dice_metric': 0.9676162600517273, 'Val/mean miou_metric': 0.9464744329452515, 'Val/mean f1': 0.9673047661781311, 'Val/mean precision': 0.9626273512840271, 'Val/mean recall': 0.9720277786254883, 'Val/mean hd95_metric': 6.125148773193359} +Cheakpoint... +Epoch [719/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676162600517273, 'Val/mean miou_metric': 0.9464744329452515, 'Val/mean f1': 0.9673047661781311, 'Val/mean precision': 0.9626273512840271, 'Val/mean recall': 0.9720277786254883, 'Val/mean hd95_metric': 6.125148773193359} +Epoch [720/4000] Training [1/16] Loss: 0.05574 +Epoch [720/4000] Training [2/16] Loss: 0.01470 +Epoch [720/4000] Training [3/16] Loss: 0.01729 +Epoch [720/4000] Training [4/16] Loss: 0.01345 +Epoch [720/4000] Training [5/16] Loss: 0.01392 +Epoch [720/4000] Training [6/16] Loss: 0.01396 +Epoch [720/4000] Training [7/16] Loss: 0.01573 +Epoch [720/4000] Training [8/16] Loss: 0.01176 +Epoch [720/4000] Training [9/16] Loss: 0.01437 +Epoch [720/4000] Training [10/16] Loss: 0.12700 +Epoch [720/4000] Training [11/16] Loss: 0.02039 +Epoch [720/4000] Training [12/16] Loss: 0.01801 +Epoch [720/4000] Training [13/16] Loss: 0.01735 +Epoch [720/4000] Training [14/16] Loss: 0.01197 +Epoch [720/4000] Training [15/16] Loss: 0.01901 +Epoch [720/4000] Training [16/16] Loss: 0.01637 +Epoch [720/4000] Training metric {'Train/mean dice_metric': 0.9886918663978577, 'Train/mean miou_metric': 0.9778831601142883, 'Train/mean f1': 0.9850960969924927, 'Train/mean precision': 0.9793983101844788, 'Train/mean recall': 0.9908605217933655, 'Train/mean hd95_metric': 1.8950366973876953} +Epoch [720/4000] Validation [1/4] Loss: 0.29124 focal_loss 0.20256 dice_loss 0.08868 +Epoch [720/4000] Validation [2/4] Loss: 0.21526 focal_loss 0.10732 dice_loss 0.10794 +Epoch [720/4000] Validation [3/4] Loss: 0.17012 focal_loss 0.09037 dice_loss 0.07975 +Epoch [720/4000] Validation [4/4] Loss: 0.23840 focal_loss 0.11860 dice_loss 0.11980 +Epoch [720/4000] Validation metric {'Val/mean dice_metric': 0.9615222811698914, 'Val/mean miou_metric': 0.9386189579963684, 'Val/mean f1': 0.9622752666473389, 'Val/mean precision': 0.9596385955810547, 'Val/mean recall': 0.9649264812469482, 'Val/mean hd95_metric': 7.6985273361206055} +Cheakpoint... +Epoch [720/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9615], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9615222811698914, 'Val/mean miou_metric': 0.9386189579963684, 'Val/mean f1': 0.9622752666473389, 'Val/mean precision': 0.9596385955810547, 'Val/mean recall': 0.9649264812469482, 'Val/mean hd95_metric': 7.6985273361206055} +Epoch [721/4000] Training [1/16] Loss: 0.01505 +Epoch [721/4000] Training [2/16] Loss: 0.01462 +Epoch [721/4000] Training [3/16] Loss: 0.01371 +Epoch [721/4000] Training [4/16] Loss: 0.01230 +Epoch [721/4000] Training [5/16] Loss: 0.02031 +Epoch [721/4000] Training [6/16] Loss: 0.01348 +Epoch [721/4000] Training [7/16] Loss: 0.01603 +Epoch [721/4000] Training [8/16] Loss: 0.01349 +Epoch [721/4000] Training [9/16] Loss: 0.01421 +Epoch [721/4000] Training [10/16] Loss: 0.04749 +Epoch [721/4000] Training [11/16] Loss: 0.01422 +Epoch [721/4000] Training [12/16] Loss: 0.01812 +Epoch [721/4000] Training [13/16] Loss: 0.01916 +Epoch [721/4000] Training [14/16] Loss: 0.01563 +Epoch [721/4000] Training [15/16] Loss: 0.02002 +Epoch [721/4000] Training [16/16] Loss: 0.01437 +Epoch [721/4000] Training metric {'Train/mean dice_metric': 0.9883570075035095, 'Train/mean miou_metric': 0.9769194722175598, 'Train/mean f1': 0.984867513179779, 'Train/mean precision': 0.980531632900238, 'Train/mean recall': 0.9892419576644897, 'Train/mean hd95_metric': 2.145113229751587} +Epoch [721/4000] Validation [1/4] Loss: 0.53237 focal_loss 0.41338 dice_loss 0.11899 +Epoch [721/4000] Validation [2/4] Loss: 0.18663 focal_loss 0.08248 dice_loss 0.10415 +Epoch [721/4000] Validation [3/4] Loss: 0.12088 focal_loss 0.06389 dice_loss 0.05699 +Epoch [721/4000] Validation [4/4] Loss: 0.26382 focal_loss 0.14639 dice_loss 0.11743 +Epoch [721/4000] Validation metric {'Val/mean dice_metric': 0.9651080965995789, 'Val/mean miou_metric': 0.9426370859146118, 'Val/mean f1': 0.9657979011535645, 'Val/mean precision': 0.9648432731628418, 'Val/mean recall': 0.9667544364929199, 'Val/mean hd95_metric': 6.903631687164307} +Cheakpoint... +Epoch [721/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651080965995789, 'Val/mean miou_metric': 0.9426370859146118, 'Val/mean f1': 0.9657979011535645, 'Val/mean precision': 0.9648432731628418, 'Val/mean recall': 0.9667544364929199, 'Val/mean hd95_metric': 6.903631687164307} +Epoch [722/4000] Training [1/16] Loss: 0.01690 +Epoch [722/4000] Training [2/16] Loss: 0.02465 +Epoch [722/4000] Training [3/16] Loss: 0.01559 +Epoch [722/4000] Training [4/16] Loss: 0.02035 +Epoch [722/4000] Training [5/16] Loss: 0.02056 +Epoch [722/4000] Training [6/16] Loss: 0.01556 +Epoch [722/4000] Training [7/16] Loss: 0.01586 +Epoch [722/4000] Training [8/16] Loss: 0.01295 +Epoch [722/4000] Training [9/16] Loss: 0.02122 +Epoch [722/4000] Training [10/16] Loss: 0.01333 +Epoch [722/4000] Training [11/16] Loss: 0.01463 +Epoch [722/4000] Training [12/16] Loss: 0.01733 +Epoch [722/4000] Training [13/16] Loss: 0.01225 +Epoch [722/4000] Training [14/16] Loss: 0.01539 +Epoch [722/4000] Training [15/16] Loss: 0.02120 +Epoch [722/4000] Training [16/16] Loss: 0.01411 +Epoch [722/4000] Training metric {'Train/mean dice_metric': 0.987722635269165, 'Train/mean miou_metric': 0.9759141206741333, 'Train/mean f1': 0.9836686849594116, 'Train/mean precision': 0.9799966812133789, 'Train/mean recall': 0.9873683452606201, 'Train/mean hd95_metric': 2.502088785171509} +Epoch [722/4000] Validation [1/4] Loss: 0.23191 focal_loss 0.16344 dice_loss 0.06848 +Epoch [722/4000] Validation [2/4] Loss: 0.25909 focal_loss 0.09745 dice_loss 0.16164 +Epoch [722/4000] Validation [3/4] Loss: 0.11802 focal_loss 0.05800 dice_loss 0.06001 +Epoch [722/4000] Validation [4/4] Loss: 0.30070 focal_loss 0.15354 dice_loss 0.14716 +Epoch [722/4000] Validation metric {'Val/mean dice_metric': 0.9649562835693359, 'Val/mean miou_metric': 0.9409855008125305, 'Val/mean f1': 0.9661620855331421, 'Val/mean precision': 0.9614139795303345, 'Val/mean recall': 0.9709571599960327, 'Val/mean hd95_metric': 7.185877799987793} +Cheakpoint... +Epoch [722/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649562835693359, 'Val/mean miou_metric': 0.9409855008125305, 'Val/mean f1': 0.9661620855331421, 'Val/mean precision': 0.9614139795303345, 'Val/mean recall': 0.9709571599960327, 'Val/mean hd95_metric': 7.185877799987793} +Epoch [723/4000] Training [1/16] Loss: 0.01783 +Epoch [723/4000] Training [2/16] Loss: 0.01564 +Epoch [723/4000] Training [3/16] Loss: 0.01270 +Epoch [723/4000] Training [4/16] Loss: 0.01863 +Epoch [723/4000] Training [5/16] Loss: 0.01779 +Epoch [723/4000] Training [6/16] Loss: 0.01832 +Epoch [723/4000] Training [7/16] Loss: 0.01456 +Epoch [723/4000] Training [8/16] Loss: 0.02745 +Epoch [723/4000] Training [9/16] Loss: 0.01418 +Epoch [723/4000] Training [10/16] Loss: 0.01880 +Epoch [723/4000] Training [11/16] Loss: 0.01585 +Epoch [723/4000] Training [12/16] Loss: 0.01870 +Epoch [723/4000] Training [13/16] Loss: 0.01787 +Epoch [723/4000] Training [14/16] Loss: 0.01284 +Epoch [723/4000] Training [15/16] Loss: 0.02108 +Epoch [723/4000] Training [16/16] Loss: 0.01481 +Epoch [723/4000] Training metric {'Train/mean dice_metric': 0.9881194829940796, 'Train/mean miou_metric': 0.9764589667320251, 'Train/mean f1': 0.9853168725967407, 'Train/mean precision': 0.9815167784690857, 'Train/mean recall': 0.9891464710235596, 'Train/mean hd95_metric': 1.9651108980178833} +Epoch [723/4000] Validation [1/4] Loss: 0.17728 focal_loss 0.11022 dice_loss 0.06706 +Epoch [723/4000] Validation [2/4] Loss: 0.21842 focal_loss 0.09699 dice_loss 0.12142 +Epoch [723/4000] Validation [3/4] Loss: 0.13228 focal_loss 0.07161 dice_loss 0.06067 +Epoch [723/4000] Validation [4/4] Loss: 0.27756 focal_loss 0.12756 dice_loss 0.15000 +Epoch [723/4000] Validation metric {'Val/mean dice_metric': 0.963652491569519, 'Val/mean miou_metric': 0.9410301446914673, 'Val/mean f1': 0.9653781056404114, 'Val/mean precision': 0.9600075483322144, 'Val/mean recall': 0.9708092212677002, 'Val/mean hd95_metric': 7.0039849281311035} +Cheakpoint... +Epoch [723/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963652491569519, 'Val/mean miou_metric': 0.9410301446914673, 'Val/mean f1': 0.9653781056404114, 'Val/mean precision': 0.9600075483322144, 'Val/mean recall': 0.9708092212677002, 'Val/mean hd95_metric': 7.0039849281311035} +Epoch [724/4000] Training [1/16] Loss: 0.01595 +Epoch [724/4000] Training [2/16] Loss: 0.02546 +Epoch [724/4000] Training [3/16] Loss: 0.01440 +Epoch [724/4000] Training [4/16] Loss: 0.01447 +Epoch [724/4000] Training [5/16] Loss: 0.01237 +Epoch [724/4000] Training [6/16] Loss: 0.01171 +Epoch [724/4000] Training [7/16] Loss: 0.01593 +Epoch [724/4000] Training [8/16] Loss: 0.01717 +Epoch [724/4000] Training [9/16] Loss: 0.01630 +Epoch [724/4000] Training [10/16] Loss: 0.01185 +Epoch [724/4000] Training [11/16] Loss: 0.01767 +Epoch [724/4000] Training [12/16] Loss: 0.00988 +Epoch [724/4000] Training [13/16] Loss: 0.01630 +Epoch [724/4000] Training [14/16] Loss: 0.01455 +Epoch [724/4000] Training [15/16] Loss: 0.01257 +Epoch [724/4000] Training [16/16] Loss: 0.01658 +Epoch [724/4000] Training metric {'Train/mean dice_metric': 0.988946259021759, 'Train/mean miou_metric': 0.9780253171920776, 'Train/mean f1': 0.9855238795280457, 'Train/mean precision': 0.981049120426178, 'Train/mean recall': 0.9900395274162292, 'Train/mean hd95_metric': 2.19102144241333} +Epoch [724/4000] Validation [1/4] Loss: 0.20881 focal_loss 0.13589 dice_loss 0.07292 +Epoch [724/4000] Validation [2/4] Loss: 0.26055 focal_loss 0.12260 dice_loss 0.13796 +Epoch [724/4000] Validation [3/4] Loss: 0.16160 focal_loss 0.08568 dice_loss 0.07593 +Epoch [724/4000] Validation [4/4] Loss: 0.30438 focal_loss 0.15270 dice_loss 0.15168 +Epoch [724/4000] Validation metric {'Val/mean dice_metric': 0.9669160842895508, 'Val/mean miou_metric': 0.9437782168388367, 'Val/mean f1': 0.964763343334198, 'Val/mean precision': 0.9541382193565369, 'Val/mean recall': 0.9756278991699219, 'Val/mean hd95_metric': 8.01483154296875} +Cheakpoint... +Epoch [724/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669160842895508, 'Val/mean miou_metric': 0.9437782168388367, 'Val/mean f1': 0.964763343334198, 'Val/mean precision': 0.9541382193565369, 'Val/mean recall': 0.9756278991699219, 'Val/mean hd95_metric': 8.01483154296875} +Epoch [725/4000] Training [1/16] Loss: 0.01580 +Epoch [725/4000] Training [2/16] Loss: 0.01374 +Epoch [725/4000] Training [3/16] Loss: 0.01361 +Epoch [725/4000] Training [4/16] Loss: 0.01444 +Epoch [725/4000] Training [5/16] Loss: 0.01293 +Epoch [725/4000] Training [6/16] Loss: 0.01429 +Epoch [725/4000] Training [7/16] Loss: 0.01276 +Epoch [725/4000] Training [8/16] Loss: 0.01517 +Epoch [725/4000] Training [9/16] Loss: 0.01359 +Epoch [725/4000] Training [10/16] Loss: 0.01436 +Epoch [725/4000] Training [11/16] Loss: 0.01479 +Epoch [725/4000] Training [12/16] Loss: 0.01319 +Epoch [725/4000] Training [13/16] Loss: 0.01643 +Epoch [725/4000] Training [14/16] Loss: 0.01460 +Epoch [725/4000] Training [15/16] Loss: 0.01407 +Epoch [725/4000] Training [16/16] Loss: 0.04939 +Epoch [725/4000] Training metric {'Train/mean dice_metric': 0.9889554977416992, 'Train/mean miou_metric': 0.9785411357879639, 'Train/mean f1': 0.9830818176269531, 'Train/mean precision': 0.9777101278305054, 'Train/mean recall': 0.9885129332542419, 'Train/mean hd95_metric': 2.299146890640259} +Epoch [725/4000] Validation [1/4] Loss: 0.72183 focal_loss 0.48940 dice_loss 0.23243 +Epoch [725/4000] Validation [2/4] Loss: 0.18833 focal_loss 0.07015 dice_loss 0.11817 +Epoch [725/4000] Validation [3/4] Loss: 0.13383 focal_loss 0.06857 dice_loss 0.06526 +Epoch [725/4000] Validation [4/4] Loss: 0.26446 focal_loss 0.11310 dice_loss 0.15136 +Epoch [725/4000] Validation metric {'Val/mean dice_metric': 0.9607365727424622, 'Val/mean miou_metric': 0.9379044771194458, 'Val/mean f1': 0.9588848948478699, 'Val/mean precision': 0.9579315781593323, 'Val/mean recall': 0.9598400592803955, 'Val/mean hd95_metric': 7.399036407470703} +Cheakpoint... +Epoch [725/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9607], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9607365727424622, 'Val/mean miou_metric': 0.9379044771194458, 'Val/mean f1': 0.9588848948478699, 'Val/mean precision': 0.9579315781593323, 'Val/mean recall': 0.9598400592803955, 'Val/mean hd95_metric': 7.399036407470703} +Epoch [726/4000] Training [1/16] Loss: 0.03158 +Epoch [726/4000] Training [2/16] Loss: 0.01624 +Epoch [726/4000] Training [3/16] Loss: 0.01593 +Epoch [726/4000] Training [4/16] Loss: 0.01272 +Epoch [726/4000] Training [5/16] Loss: 0.01320 +Epoch [726/4000] Training [6/16] Loss: 0.01460 +Epoch [726/4000] Training [7/16] Loss: 0.01826 +Epoch [726/4000] Training [8/16] Loss: 0.01447 +Epoch [726/4000] Training [9/16] Loss: 0.07940 +Epoch [726/4000] Training [10/16] Loss: 0.01422 +Epoch [726/4000] Training [11/16] Loss: 0.01611 +Epoch [726/4000] Training [12/16] Loss: 0.01401 +Epoch [726/4000] Training [13/16] Loss: 0.01286 +Epoch [726/4000] Training [14/16] Loss: 0.03224 +Epoch [726/4000] Training [15/16] Loss: 0.02551 +Epoch [726/4000] Training [16/16] Loss: 0.02993 +Epoch [726/4000] Training metric {'Train/mean dice_metric': 0.987331748008728, 'Train/mean miou_metric': 0.9751957058906555, 'Train/mean f1': 0.9844664335250854, 'Train/mean precision': 0.9790982007980347, 'Train/mean recall': 0.9898938536643982, 'Train/mean hd95_metric': 3.011873245239258} +Epoch [726/4000] Validation [1/4] Loss: 0.16697 focal_loss 0.08945 dice_loss 0.07752 +Epoch [726/4000] Validation [2/4] Loss: 0.21067 focal_loss 0.07047 dice_loss 0.14020 +Epoch [726/4000] Validation [3/4] Loss: 0.13651 focal_loss 0.06773 dice_loss 0.06879 +Epoch [726/4000] Validation [4/4] Loss: 0.22142 focal_loss 0.06543 dice_loss 0.15599 +Epoch [726/4000] Validation metric {'Val/mean dice_metric': 0.9614713788032532, 'Val/mean miou_metric': 0.9372545480728149, 'Val/mean f1': 0.9661950469017029, 'Val/mean precision': 0.9590796232223511, 'Val/mean recall': 0.9734170436859131, 'Val/mean hd95_metric': 8.674112319946289} +Cheakpoint... +Epoch [726/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9615], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614713788032532, 'Val/mean miou_metric': 0.9372545480728149, 'Val/mean f1': 0.9661950469017029, 'Val/mean precision': 0.9590796232223511, 'Val/mean recall': 0.9734170436859131, 'Val/mean hd95_metric': 8.674112319946289} +Epoch [727/4000] Training [1/16] Loss: 0.01637 +Epoch [727/4000] Training [2/16] Loss: 0.05509 +Epoch [727/4000] Training [3/16] Loss: 0.02059 +Epoch [727/4000] Training [4/16] Loss: 0.01595 +Epoch [727/4000] Training [5/16] Loss: 0.01778 +Epoch [727/4000] Training [6/16] Loss: 0.07541 +Epoch [727/4000] Training [7/16] Loss: 0.01898 +Epoch [727/4000] Training [8/16] Loss: 0.01717 +Epoch [727/4000] Training [9/16] Loss: 0.01776 +Epoch [727/4000] Training [10/16] Loss: 0.01756 +Epoch [727/4000] Training [11/16] Loss: 0.01528 +Epoch [727/4000] Training [12/16] Loss: 0.01773 +Epoch [727/4000] Training [13/16] Loss: 0.02026 +Epoch [727/4000] Training [14/16] Loss: 0.01545 +Epoch [727/4000] Training [15/16] Loss: 0.02187 +Epoch [727/4000] Training [16/16] Loss: 0.01752 +Epoch [727/4000] Training metric {'Train/mean dice_metric': 0.9847603440284729, 'Train/mean miou_metric': 0.9713304042816162, 'Train/mean f1': 0.9823697805404663, 'Train/mean precision': 0.9780239462852478, 'Train/mean recall': 0.9867544174194336, 'Train/mean hd95_metric': 2.8854663372039795} +Epoch [727/4000] Validation [1/4] Loss: 0.68028 focal_loss 0.51710 dice_loss 0.16318 +Epoch [727/4000] Validation [2/4] Loss: 0.23127 focal_loss 0.11428 dice_loss 0.11699 +Epoch [727/4000] Validation [3/4] Loss: 0.19010 focal_loss 0.10605 dice_loss 0.08405 +Epoch [727/4000] Validation [4/4] Loss: 0.63833 focal_loss 0.39817 dice_loss 0.24016 +Epoch [727/4000] Validation metric {'Val/mean dice_metric': 0.9561243057250977, 'Val/mean miou_metric': 0.9299644231796265, 'Val/mean f1': 0.9557986855506897, 'Val/mean precision': 0.954983651638031, 'Val/mean recall': 0.9566152691841125, 'Val/mean hd95_metric': 10.038684844970703} +Cheakpoint... +Epoch [727/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9561], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9561243057250977, 'Val/mean miou_metric': 0.9299644231796265, 'Val/mean f1': 0.9557986855506897, 'Val/mean precision': 0.954983651638031, 'Val/mean recall': 0.9566152691841125, 'Val/mean hd95_metric': 10.038684844970703} +Epoch [728/4000] Training [1/16] Loss: 0.13492 +Epoch [728/4000] Training [2/16] Loss: 0.01938 +Epoch [728/4000] Training [3/16] Loss: 0.01676 +Epoch [728/4000] Training [4/16] Loss: 0.01784 +Epoch [728/4000] Training [5/16] Loss: 0.02126 +Epoch [728/4000] Training [6/16] Loss: 0.01834 +Epoch [728/4000] Training [7/16] Loss: 0.01574 +Epoch [728/4000] Training [8/16] Loss: 0.06075 +Epoch [728/4000] Training [9/16] Loss: 0.02109 +Epoch [728/4000] Training [10/16] Loss: 0.01800 +Epoch [728/4000] Training [11/16] Loss: 0.03245 +Epoch [728/4000] Training [12/16] Loss: 0.02261 +Epoch [728/4000] Training [13/16] Loss: 0.01647 +Epoch [728/4000] Training [14/16] Loss: 0.01752 +Epoch [728/4000] Training [15/16] Loss: 0.01680 +Epoch [728/4000] Training [16/16] Loss: 0.02381 +Epoch [728/4000] Training metric {'Train/mean dice_metric': 0.9849463701248169, 'Train/mean miou_metric': 0.9714500308036804, 'Train/mean f1': 0.9826325178146362, 'Train/mean precision': 0.9783720374107361, 'Train/mean recall': 0.9869303107261658, 'Train/mean hd95_metric': 3.558541774749756} +Epoch [728/4000] Validation [1/4] Loss: 0.37204 focal_loss 0.21703 dice_loss 0.15501 +Epoch [728/4000] Validation [2/4] Loss: 0.21752 focal_loss 0.10452 dice_loss 0.11300 +Epoch [728/4000] Validation [3/4] Loss: 0.18212 focal_loss 0.08610 dice_loss 0.09602 +Epoch [728/4000] Validation [4/4] Loss: 0.42158 focal_loss 0.21474 dice_loss 0.20684 +Epoch [728/4000] Validation metric {'Val/mean dice_metric': 0.9597026705741882, 'Val/mean miou_metric': 0.9344329833984375, 'Val/mean f1': 0.9611484408378601, 'Val/mean precision': 0.9587783813476562, 'Val/mean recall': 0.963530421257019, 'Val/mean hd95_metric': 8.77575969696045} +Cheakpoint... +Epoch [728/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9597], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9597026705741882, 'Val/mean miou_metric': 0.9344329833984375, 'Val/mean f1': 0.9611484408378601, 'Val/mean precision': 0.9587783813476562, 'Val/mean recall': 0.963530421257019, 'Val/mean hd95_metric': 8.77575969696045} +Epoch [729/4000] Training [1/16] Loss: 0.03131 +Epoch [729/4000] Training [2/16] Loss: 0.01683 +Epoch [729/4000] Training [3/16] Loss: 0.01219 +Epoch [729/4000] Training [4/16] Loss: 0.01424 +Epoch [729/4000] Training [5/16] Loss: 0.01404 +Epoch [729/4000] Training [6/16] Loss: 0.01897 +Epoch [729/4000] Training [7/16] Loss: 0.05880 +Epoch [729/4000] Training [8/16] Loss: 0.01361 +Epoch [729/4000] Training [9/16] Loss: 0.03686 +Epoch [729/4000] Training [10/16] Loss: 0.01648 +Epoch [729/4000] Training [11/16] Loss: 0.01905 +Epoch [729/4000] Training [12/16] Loss: 0.01444 +Epoch [729/4000] Training [13/16] Loss: 0.03650 +Epoch [729/4000] Training [14/16] Loss: 0.01749 +Epoch [729/4000] Training [15/16] Loss: 0.01555 +Epoch [729/4000] Training [16/16] Loss: 0.01334 +Epoch [729/4000] Training metric {'Train/mean dice_metric': 0.9868574142456055, 'Train/mean miou_metric': 0.9741700887680054, 'Train/mean f1': 0.9844198822975159, 'Train/mean precision': 0.9806550145149231, 'Train/mean recall': 0.9882137775421143, 'Train/mean hd95_metric': 3.1662349700927734} +Epoch [729/4000] Validation [1/4] Loss: 0.19812 focal_loss 0.11586 dice_loss 0.08227 +Epoch [729/4000] Validation [2/4] Loss: 0.26318 focal_loss 0.09976 dice_loss 0.16342 +Epoch [729/4000] Validation [3/4] Loss: 0.14902 focal_loss 0.08099 dice_loss 0.06803 +Epoch [729/4000] Validation [4/4] Loss: 0.45299 focal_loss 0.25806 dice_loss 0.19493 +Epoch [729/4000] Validation metric {'Val/mean dice_metric': 0.9598153233528137, 'Val/mean miou_metric': 0.9353702664375305, 'Val/mean f1': 0.9637378454208374, 'Val/mean precision': 0.9606851935386658, 'Val/mean recall': 0.9668099880218506, 'Val/mean hd95_metric': 9.364665031433105} +Cheakpoint... +Epoch [729/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9598], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9598153233528137, 'Val/mean miou_metric': 0.9353702664375305, 'Val/mean f1': 0.9637378454208374, 'Val/mean precision': 0.9606851935386658, 'Val/mean recall': 0.9668099880218506, 'Val/mean hd95_metric': 9.364665031433105} +Epoch [730/4000] Training [1/16] Loss: 0.02246 +Epoch [730/4000] Training [2/16] Loss: 0.02210 +Epoch [730/4000] Training [3/16] Loss: 0.01594 +Epoch [730/4000] Training [4/16] Loss: 0.01451 +Epoch [730/4000] Training [5/16] Loss: 0.01384 +Epoch [730/4000] Training [6/16] Loss: 0.01617 +Epoch [730/4000] Training [7/16] Loss: 0.01694 +Epoch [730/4000] Training [8/16] Loss: 0.09080 +Epoch [730/4000] Training [9/16] Loss: 0.01717 +Epoch [730/4000] Training [10/16] Loss: 0.01525 +Epoch [730/4000] Training [11/16] Loss: 0.01854 +Epoch [730/4000] Training [12/16] Loss: 0.02409 +Epoch [730/4000] Training [13/16] Loss: 0.01262 +Epoch [730/4000] Training [14/16] Loss: 0.02030 +Epoch [730/4000] Training [15/16] Loss: 0.02147 +Epoch [730/4000] Training [16/16] Loss: 0.02139 +Epoch [730/4000] Training metric {'Train/mean dice_metric': 0.9877501130104065, 'Train/mean miou_metric': 0.9756982326507568, 'Train/mean f1': 0.984171450138092, 'Train/mean precision': 0.9798347353935242, 'Train/mean recall': 0.9885469079017639, 'Train/mean hd95_metric': 3.1750597953796387} +Epoch [730/4000] Validation [1/4] Loss: 0.13214 focal_loss 0.07409 dice_loss 0.05805 +Epoch [730/4000] Validation [2/4] Loss: 0.21183 focal_loss 0.08125 dice_loss 0.13059 +Epoch [730/4000] Validation [3/4] Loss: 0.15771 focal_loss 0.08600 dice_loss 0.07171 +Epoch [730/4000] Validation [4/4] Loss: 0.19299 focal_loss 0.07850 dice_loss 0.11449 +Epoch [730/4000] Validation metric {'Val/mean dice_metric': 0.9633458852767944, 'Val/mean miou_metric': 0.9399968981742859, 'Val/mean f1': 0.9657144546508789, 'Val/mean precision': 0.9602388739585876, 'Val/mean recall': 0.9712527394294739, 'Val/mean hd95_metric': 8.234740257263184} +Cheakpoint... +Epoch [730/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633458852767944, 'Val/mean miou_metric': 0.9399968981742859, 'Val/mean f1': 0.9657144546508789, 'Val/mean precision': 0.9602388739585876, 'Val/mean recall': 0.9712527394294739, 'Val/mean hd95_metric': 8.234740257263184} +Epoch [731/4000] Training [1/16] Loss: 0.01582 +Epoch [731/4000] Training [2/16] Loss: 0.01848 +Epoch [731/4000] Training [3/16] Loss: 0.01934 +Epoch [731/4000] Training [4/16] Loss: 0.01495 +Epoch [731/4000] Training [5/16] Loss: 0.01607 +Epoch [731/4000] Training [6/16] Loss: 0.01337 +Epoch [731/4000] Training [7/16] Loss: 0.01436 +Epoch [731/4000] Training [8/16] Loss: 0.01512 +Epoch [731/4000] Training [9/16] Loss: 0.03594 +Epoch [731/4000] Training [10/16] Loss: 0.01801 +Epoch [731/4000] Training [11/16] Loss: 0.01056 +Epoch [731/4000] Training [12/16] Loss: 0.01180 +Epoch [731/4000] Training [13/16] Loss: 0.01753 +Epoch [731/4000] Training [14/16] Loss: 0.01185 +Epoch [731/4000] Training [15/16] Loss: 0.01377 +Epoch [731/4000] Training [16/16] Loss: 0.01688 +Epoch [731/4000] Training metric {'Train/mean dice_metric': 0.9883446097373962, 'Train/mean miou_metric': 0.9775062799453735, 'Train/mean f1': 0.984929621219635, 'Train/mean precision': 0.9813094735145569, 'Train/mean recall': 0.9885765314102173, 'Train/mean hd95_metric': 2.671043634414673} +Epoch [731/4000] Validation [1/4] Loss: 0.12934 focal_loss 0.06735 dice_loss 0.06199 +Epoch [731/4000] Validation [2/4] Loss: 0.20789 focal_loss 0.09269 dice_loss 0.11520 +Epoch [731/4000] Validation [3/4] Loss: 0.15362 focal_loss 0.08332 dice_loss 0.07029 +Epoch [731/4000] Validation [4/4] Loss: 0.27230 focal_loss 0.14278 dice_loss 0.12952 +Epoch [731/4000] Validation metric {'Val/mean dice_metric': 0.9638551473617554, 'Val/mean miou_metric': 0.9419263601303101, 'Val/mean f1': 0.9654102325439453, 'Val/mean precision': 0.9607762098312378, 'Val/mean recall': 0.9700891375541687, 'Val/mean hd95_metric': 7.9485979080200195} +Cheakpoint... +Epoch [731/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9638551473617554, 'Val/mean miou_metric': 0.9419263601303101, 'Val/mean f1': 0.9654102325439453, 'Val/mean precision': 0.9607762098312378, 'Val/mean recall': 0.9700891375541687, 'Val/mean hd95_metric': 7.9485979080200195} +Epoch [732/4000] Training [1/16] Loss: 0.01680 +Epoch [732/4000] Training [2/16] Loss: 0.01421 +Epoch [732/4000] Training [3/16] Loss: 0.04137 +Epoch [732/4000] Training [4/16] Loss: 0.01409 +Epoch [732/4000] Training [5/16] Loss: 0.02295 +Epoch [732/4000] Training [6/16] Loss: 0.07594 +Epoch [732/4000] Training [7/16] Loss: 0.02206 +Epoch [732/4000] Training [8/16] Loss: 0.01422 +Epoch [732/4000] Training [9/16] Loss: 0.01363 +Epoch [732/4000] Training [10/16] Loss: 0.02498 +Epoch [732/4000] Training [11/16] Loss: 0.01671 +Epoch [732/4000] Training [12/16] Loss: 0.01446 +Epoch [732/4000] Training [13/16] Loss: 0.02178 +Epoch [732/4000] Training [14/16] Loss: 0.01524 +Epoch [732/4000] Training [15/16] Loss: 0.02009 +Epoch [732/4000] Training [16/16] Loss: 0.01566 +Epoch [732/4000] Training metric {'Train/mean dice_metric': 0.9870080351829529, 'Train/mean miou_metric': 0.9747241139411926, 'Train/mean f1': 0.9843811988830566, 'Train/mean precision': 0.9796910881996155, 'Train/mean recall': 0.989116370677948, 'Train/mean hd95_metric': 3.0322728157043457} +Epoch [732/4000] Validation [1/4] Loss: 0.25548 focal_loss 0.17041 dice_loss 0.08507 +Epoch [732/4000] Validation [2/4] Loss: 0.21353 focal_loss 0.10912 dice_loss 0.10442 +Epoch [732/4000] Validation [3/4] Loss: 0.20609 focal_loss 0.12552 dice_loss 0.08057 +Epoch [732/4000] Validation [4/4] Loss: 0.32196 focal_loss 0.18208 dice_loss 0.13988 +Epoch [732/4000] Validation metric {'Val/mean dice_metric': 0.9619770050048828, 'Val/mean miou_metric': 0.9371585845947266, 'Val/mean f1': 0.9633703827857971, 'Val/mean precision': 0.9612642526626587, 'Val/mean recall': 0.9654858112335205, 'Val/mean hd95_metric': 8.526127815246582} +Cheakpoint... +Epoch [732/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9620], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9619770050048828, 'Val/mean miou_metric': 0.9371585845947266, 'Val/mean f1': 0.9633703827857971, 'Val/mean precision': 0.9612642526626587, 'Val/mean recall': 0.9654858112335205, 'Val/mean hd95_metric': 8.526127815246582} +Epoch [733/4000] Training [1/16] Loss: 0.01838 +Epoch [733/4000] Training [2/16] Loss: 0.02145 +Epoch [733/4000] Training [3/16] Loss: 0.01353 +Epoch [733/4000] Training [4/16] Loss: 0.01223 +Epoch [733/4000] Training [5/16] Loss: 0.01366 +Epoch [733/4000] Training [6/16] Loss: 0.02530 +Epoch [733/4000] Training [7/16] Loss: 0.01335 +Epoch [733/4000] Training [8/16] Loss: 0.01661 +Epoch [733/4000] Training [9/16] Loss: 0.01344 +Epoch [733/4000] Training [10/16] Loss: 0.02064 +Epoch [733/4000] Training [11/16] Loss: 0.01688 +Epoch [733/4000] Training [12/16] Loss: 0.01698 +Epoch [733/4000] Training [13/16] Loss: 0.01283 +Epoch [733/4000] Training [14/16] Loss: 0.02207 +Epoch [733/4000] Training [15/16] Loss: 0.01811 +Epoch [733/4000] Training [16/16] Loss: 0.02284 +Epoch [733/4000] Training metric {'Train/mean dice_metric': 0.9873924255371094, 'Train/mean miou_metric': 0.9750904440879822, 'Train/mean f1': 0.9851663708686829, 'Train/mean precision': 0.9810388088226318, 'Train/mean recall': 0.9893288016319275, 'Train/mean hd95_metric': 2.36008358001709} +Epoch [733/4000] Validation [1/4] Loss: 0.13234 focal_loss 0.07079 dice_loss 0.06155 +Epoch [733/4000] Validation [2/4] Loss: 0.27863 focal_loss 0.12097 dice_loss 0.15767 +Epoch [733/4000] Validation [3/4] Loss: 0.13481 focal_loss 0.06507 dice_loss 0.06973 +Epoch [733/4000] Validation [4/4] Loss: 0.26896 focal_loss 0.11578 dice_loss 0.15319 +Epoch [733/4000] Validation metric {'Val/mean dice_metric': 0.9620317220687866, 'Val/mean miou_metric': 0.9378431439399719, 'Val/mean f1': 0.9660884737968445, 'Val/mean precision': 0.9631364345550537, 'Val/mean recall': 0.9690586924552917, 'Val/mean hd95_metric': 6.859642505645752} +Cheakpoint... +Epoch [733/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9620], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9620317220687866, 'Val/mean miou_metric': 0.9378431439399719, 'Val/mean f1': 0.9660884737968445, 'Val/mean precision': 0.9631364345550537, 'Val/mean recall': 0.9690586924552917, 'Val/mean hd95_metric': 6.859642505645752} +Epoch [734/4000] Training [1/16] Loss: 0.01111 +Epoch [734/4000] Training [2/16] Loss: 0.01795 +Epoch [734/4000] Training [3/16] Loss: 0.01489 +Epoch [734/4000] Training [4/16] Loss: 0.01663 +Epoch [734/4000] Training [5/16] Loss: 0.01534 +Epoch [734/4000] Training [6/16] Loss: 0.01518 +Epoch [734/4000] Training [7/16] Loss: 0.01366 +Epoch [734/4000] Training [8/16] Loss: 0.01376 +Epoch [734/4000] Training [9/16] Loss: 0.01510 +Epoch [734/4000] Training [10/16] Loss: 0.01221 +Epoch [734/4000] Training [11/16] Loss: 0.01616 +Epoch [734/4000] Training [12/16] Loss: 0.01514 +Epoch [734/4000] Training [13/16] Loss: 0.01637 +Epoch [734/4000] Training [14/16] Loss: 0.01274 +Epoch [734/4000] Training [15/16] Loss: 0.01141 +Epoch [734/4000] Training [16/16] Loss: 0.01371 +Epoch [734/4000] Training metric {'Train/mean dice_metric': 0.9895957708358765, 'Train/mean miou_metric': 0.9792081713676453, 'Train/mean f1': 0.9862760901451111, 'Train/mean precision': 0.9813187718391418, 'Train/mean recall': 0.9912837147712708, 'Train/mean hd95_metric': 1.4251880645751953} +Epoch [734/4000] Validation [1/4] Loss: 0.15113 focal_loss 0.08808 dice_loss 0.06305 +Epoch [734/4000] Validation [2/4] Loss: 0.28473 focal_loss 0.14632 dice_loss 0.13841 +Epoch [734/4000] Validation [3/4] Loss: 0.13886 focal_loss 0.07451 dice_loss 0.06435 +Epoch [734/4000] Validation [4/4] Loss: 0.29005 focal_loss 0.15511 dice_loss 0.13494 +Epoch [734/4000] Validation metric {'Val/mean dice_metric': 0.9670696258544922, 'Val/mean miou_metric': 0.9451478719711304, 'Val/mean f1': 0.9687259197235107, 'Val/mean precision': 0.9616435170173645, 'Val/mean recall': 0.975913405418396, 'Val/mean hd95_metric': 6.422508239746094} +Cheakpoint... +Epoch [734/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670696258544922, 'Val/mean miou_metric': 0.9451478719711304, 'Val/mean f1': 0.9687259197235107, 'Val/mean precision': 0.9616435170173645, 'Val/mean recall': 0.975913405418396, 'Val/mean hd95_metric': 6.422508239746094} +Epoch [735/4000] Training [1/16] Loss: 0.01272 +Epoch [735/4000] Training [2/16] Loss: 0.01382 +Epoch [735/4000] Training [3/16] Loss: 0.01096 +Epoch [735/4000] Training [4/16] Loss: 0.02321 +Epoch [735/4000] Training [5/16] Loss: 0.01267 +Epoch [735/4000] Training [6/16] Loss: 0.01564 +Epoch [735/4000] Training [7/16] Loss: 0.01590 +Epoch [735/4000] Training [8/16] Loss: 0.01348 +Epoch [735/4000] Training [9/16] Loss: 0.01900 +Epoch [735/4000] Training [10/16] Loss: 0.02697 +Epoch [735/4000] Training [11/16] Loss: 0.01030 +Epoch [735/4000] Training [12/16] Loss: 0.01538 +Epoch [735/4000] Training [13/16] Loss: 0.01922 +Epoch [735/4000] Training [14/16] Loss: 0.01886 +Epoch [735/4000] Training [15/16] Loss: 0.01464 +Epoch [735/4000] Training [16/16] Loss: 0.01560 +Epoch [735/4000] Training metric {'Train/mean dice_metric': 0.9879148006439209, 'Train/mean miou_metric': 0.9766078591346741, 'Train/mean f1': 0.9854915738105774, 'Train/mean precision': 0.9811143279075623, 'Train/mean recall': 0.9899080395698547, 'Train/mean hd95_metric': 1.9597792625427246} +Epoch [735/4000] Validation [1/4] Loss: 0.48366 focal_loss 0.35376 dice_loss 0.12991 +Epoch [735/4000] Validation [2/4] Loss: 0.22044 focal_loss 0.11645 dice_loss 0.10399 +Epoch [735/4000] Validation [3/4] Loss: 0.12269 focal_loss 0.06278 dice_loss 0.05991 +Epoch [735/4000] Validation [4/4] Loss: 0.30734 focal_loss 0.17415 dice_loss 0.13320 +Epoch [735/4000] Validation metric {'Val/mean dice_metric': 0.9657211303710938, 'Val/mean miou_metric': 0.9425680041313171, 'Val/mean f1': 0.9663495421409607, 'Val/mean precision': 0.9665876030921936, 'Val/mean recall': 0.9661117196083069, 'Val/mean hd95_metric': 6.172182559967041} +Cheakpoint... +Epoch [735/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9657], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9657211303710938, 'Val/mean miou_metric': 0.9425680041313171, 'Val/mean f1': 0.9663495421409607, 'Val/mean precision': 0.9665876030921936, 'Val/mean recall': 0.9661117196083069, 'Val/mean hd95_metric': 6.172182559967041} +Epoch [736/4000] Training [1/16] Loss: 0.01424 +Epoch [736/4000] Training [2/16] Loss: 0.01190 +Epoch [736/4000] Training [3/16] Loss: 0.01608 +Epoch [736/4000] Training [4/16] Loss: 0.01384 +Epoch [736/4000] Training [5/16] Loss: 0.02041 +Epoch [736/4000] Training [6/16] Loss: 0.02014 +Epoch [736/4000] Training [7/16] Loss: 0.01467 +Epoch [736/4000] Training [8/16] Loss: 0.01253 +Epoch [736/4000] Training [9/16] Loss: 0.02914 +Epoch [736/4000] Training [10/16] Loss: 0.01573 +Epoch [736/4000] Training [11/16] Loss: 0.01488 +Epoch [736/4000] Training [12/16] Loss: 0.01366 +Epoch [736/4000] Training [13/16] Loss: 0.01464 +Epoch [736/4000] Training [14/16] Loss: 0.01271 +Epoch [736/4000] Training [15/16] Loss: 0.02131 +Epoch [736/4000] Training [16/16] Loss: 0.01654 +Epoch [736/4000] Training metric {'Train/mean dice_metric': 0.9897778034210205, 'Train/mean miou_metric': 0.9795812964439392, 'Train/mean f1': 0.9864452481269836, 'Train/mean precision': 0.981783926486969, 'Train/mean recall': 0.9911510944366455, 'Train/mean hd95_metric': 1.5270628929138184} +Epoch [736/4000] Validation [1/4] Loss: 0.21988 focal_loss 0.11896 dice_loss 0.10092 +Epoch [736/4000] Validation [2/4] Loss: 0.24632 focal_loss 0.12624 dice_loss 0.12008 +Epoch [736/4000] Validation [3/4] Loss: 0.14504 focal_loss 0.07575 dice_loss 0.06929 +Epoch [736/4000] Validation [4/4] Loss: 0.19572 focal_loss 0.08360 dice_loss 0.11212 +Epoch [736/4000] Validation metric {'Val/mean dice_metric': 0.9670432806015015, 'Val/mean miou_metric': 0.9453462362289429, 'Val/mean f1': 0.9696279764175415, 'Val/mean precision': 0.9655625820159912, 'Val/mean recall': 0.973727822303772, 'Val/mean hd95_metric': 5.773695945739746} +Cheakpoint... +Epoch [736/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670432806015015, 'Val/mean miou_metric': 0.9453462362289429, 'Val/mean f1': 0.9696279764175415, 'Val/mean precision': 0.9655625820159912, 'Val/mean recall': 0.973727822303772, 'Val/mean hd95_metric': 5.773695945739746} +Epoch [737/4000] Training [1/16] Loss: 0.01232 +Epoch [737/4000] Training [2/16] Loss: 0.01207 +Epoch [737/4000] Training [3/16] Loss: 0.01612 +Epoch [737/4000] Training [4/16] Loss: 0.01290 +Epoch [737/4000] Training [5/16] Loss: 0.01760 +Epoch [737/4000] Training [6/16] Loss: 0.01782 +Epoch [737/4000] Training [7/16] Loss: 0.01556 +Epoch [737/4000] Training [8/16] Loss: 0.01002 +Epoch [737/4000] Training [9/16] Loss: 0.01326 +Epoch [737/4000] Training [10/16] Loss: 0.01270 +Epoch [737/4000] Training [11/16] Loss: 0.01555 +Epoch [737/4000] Training [12/16] Loss: 0.01404 +Epoch [737/4000] Training [13/16] Loss: 0.01049 +Epoch [737/4000] Training [14/16] Loss: 0.01096 +Epoch [737/4000] Training [15/16] Loss: 0.01187 +Epoch [737/4000] Training [16/16] Loss: 0.01201 +Epoch [737/4000] Training metric {'Train/mean dice_metric': 0.9906828999519348, 'Train/mean miou_metric': 0.9813249111175537, 'Train/mean f1': 0.9874196648597717, 'Train/mean precision': 0.9830675721168518, 'Train/mean recall': 0.9918104410171509, 'Train/mean hd95_metric': 1.2305779457092285} +Epoch [737/4000] Validation [1/4] Loss: 0.37415 focal_loss 0.26544 dice_loss 0.10870 +Epoch [737/4000] Validation [2/4] Loss: 0.21909 focal_loss 0.11713 dice_loss 0.10196 +Epoch [737/4000] Validation [3/4] Loss: 0.12992 focal_loss 0.06530 dice_loss 0.06462 +Epoch [737/4000] Validation [4/4] Loss: 0.25772 focal_loss 0.12053 dice_loss 0.13720 +Epoch [737/4000] Validation metric {'Val/mean dice_metric': 0.9681106805801392, 'Val/mean miou_metric': 0.9462159872055054, 'Val/mean f1': 0.9680829048156738, 'Val/mean precision': 0.9680306911468506, 'Val/mean recall': 0.9681351780891418, 'Val/mean hd95_metric': 5.3870134353637695} +Cheakpoint... +Epoch [737/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681106805801392, 'Val/mean miou_metric': 0.9462159872055054, 'Val/mean f1': 0.9680829048156738, 'Val/mean precision': 0.9680306911468506, 'Val/mean recall': 0.9681351780891418, 'Val/mean hd95_metric': 5.3870134353637695} +Epoch [738/4000] Training [1/16] Loss: 0.01713 +Epoch [738/4000] Training [2/16] Loss: 0.01601 +Epoch [738/4000] Training [3/16] Loss: 0.01218 +Epoch [738/4000] Training [4/16] Loss: 0.01621 +Epoch [738/4000] Training [5/16] Loss: 0.00959 +Epoch [738/4000] Training [6/16] Loss: 0.01775 +Epoch [738/4000] Training [7/16] Loss: 0.01424 +Epoch [738/4000] Training [8/16] Loss: 0.01192 +Epoch [738/4000] Training [9/16] Loss: 0.01182 +Epoch [738/4000] Training [10/16] Loss: 0.01618 +Epoch [738/4000] Training [11/16] Loss: 0.01210 +Epoch [738/4000] Training [12/16] Loss: 0.01406 +Epoch [738/4000] Training [13/16] Loss: 0.01106 +Epoch [738/4000] Training [14/16] Loss: 0.01175 +Epoch [738/4000] Training [15/16] Loss: 0.01058 +Epoch [738/4000] Training [16/16] Loss: 0.01578 +Epoch [738/4000] Training metric {'Train/mean dice_metric': 0.9905259609222412, 'Train/mean miou_metric': 0.9810298681259155, 'Train/mean f1': 0.986913800239563, 'Train/mean precision': 0.981694221496582, 'Train/mean recall': 0.9921891689300537, 'Train/mean hd95_metric': 1.2482478618621826} +Epoch [738/4000] Validation [1/4] Loss: 0.17660 focal_loss 0.10509 dice_loss 0.07152 +Epoch [738/4000] Validation [2/4] Loss: 0.17984 focal_loss 0.07921 dice_loss 0.10063 +Epoch [738/4000] Validation [3/4] Loss: 0.15302 focal_loss 0.08180 dice_loss 0.07123 +Epoch [738/4000] Validation [4/4] Loss: 0.20737 focal_loss 0.07909 dice_loss 0.12828 +Epoch [738/4000] Validation metric {'Val/mean dice_metric': 0.9680134057998657, 'Val/mean miou_metric': 0.9473102688789368, 'Val/mean f1': 0.9688766598701477, 'Val/mean precision': 0.960822343826294, 'Val/mean recall': 0.9770670533180237, 'Val/mean hd95_metric': 5.6748151779174805} +Cheakpoint... +Epoch [738/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680134057998657, 'Val/mean miou_metric': 0.9473102688789368, 'Val/mean f1': 0.9688766598701477, 'Val/mean precision': 0.960822343826294, 'Val/mean recall': 0.9770670533180237, 'Val/mean hd95_metric': 5.6748151779174805} +Epoch [739/4000] Training [1/16] Loss: 0.01954 +Epoch [739/4000] Training [2/16] Loss: 0.01295 +Epoch [739/4000] Training [3/16] Loss: 0.01511 +Epoch [739/4000] Training [4/16] Loss: 0.01341 +Epoch [739/4000] Training [5/16] Loss: 0.01519 +Epoch [739/4000] Training [6/16] Loss: 0.01498 +Epoch [739/4000] Training [7/16] Loss: 0.01706 +Epoch [739/4000] Training [8/16] Loss: 0.01345 +Epoch [739/4000] Training [9/16] Loss: 0.01289 +Epoch [739/4000] Training [10/16] Loss: 0.01163 +Epoch [739/4000] Training [11/16] Loss: 0.01207 +Epoch [739/4000] Training [12/16] Loss: 0.01260 +Epoch [739/4000] Training [13/16] Loss: 0.01490 +Epoch [739/4000] Training [14/16] Loss: 0.01426 +Epoch [739/4000] Training [15/16] Loss: 0.01754 +Epoch [739/4000] Training [16/16] Loss: 0.01186 +Epoch [739/4000] Training metric {'Train/mean dice_metric': 0.9906959533691406, 'Train/mean miou_metric': 0.9813347458839417, 'Train/mean f1': 0.9870476722717285, 'Train/mean precision': 0.982130229473114, 'Train/mean recall': 0.9920146465301514, 'Train/mean hd95_metric': 1.2407852411270142} +Epoch [739/4000] Validation [1/4] Loss: 0.21611 focal_loss 0.13390 dice_loss 0.08220 +Epoch [739/4000] Validation [2/4] Loss: 0.21188 focal_loss 0.09496 dice_loss 0.11692 +Epoch [739/4000] Validation [3/4] Loss: 0.13082 focal_loss 0.06693 dice_loss 0.06389 +Epoch [739/4000] Validation [4/4] Loss: 0.22634 focal_loss 0.12122 dice_loss 0.10512 +Epoch [739/4000] Validation metric {'Val/mean dice_metric': 0.966717541217804, 'Val/mean miou_metric': 0.9455599784851074, 'Val/mean f1': 0.9689779281616211, 'Val/mean precision': 0.9670398831367493, 'Val/mean recall': 0.9709236025810242, 'Val/mean hd95_metric': 6.085813522338867} +Cheakpoint... +Epoch [739/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966717541217804, 'Val/mean miou_metric': 0.9455599784851074, 'Val/mean f1': 0.9689779281616211, 'Val/mean precision': 0.9670398831367493, 'Val/mean recall': 0.9709236025810242, 'Val/mean hd95_metric': 6.085813522338867} +Epoch [740/4000] Training [1/16] Loss: 0.01399 +Epoch [740/4000] Training [2/16] Loss: 0.00993 +Epoch [740/4000] Training [3/16] Loss: 0.01057 +Epoch [740/4000] Training [4/16] Loss: 0.01167 +Epoch [740/4000] Training [5/16] Loss: 0.01357 +Epoch [740/4000] Training [6/16] Loss: 0.01560 +Epoch [740/4000] Training [7/16] Loss: 0.01466 +Epoch [740/4000] Training [8/16] Loss: 0.01267 +Epoch [740/4000] Training [9/16] Loss: 0.01569 +Epoch [740/4000] Training [10/16] Loss: 0.01353 +Epoch [740/4000] Training [11/16] Loss: 0.01669 +Epoch [740/4000] Training [12/16] Loss: 0.01782 +Epoch [740/4000] Training [13/16] Loss: 0.01446 +Epoch [740/4000] Training [14/16] Loss: 0.01611 +Epoch [740/4000] Training [15/16] Loss: 0.01130 +Epoch [740/4000] Training [16/16] Loss: 0.01459 +Epoch [740/4000] Training metric {'Train/mean dice_metric': 0.9904113411903381, 'Train/mean miou_metric': 0.9808119535446167, 'Train/mean f1': 0.9870771169662476, 'Train/mean precision': 0.9823567271232605, 'Train/mean recall': 0.9918431043624878, 'Train/mean hd95_metric': 1.4720650911331177} +Epoch [740/4000] Validation [1/4] Loss: 0.41447 focal_loss 0.29533 dice_loss 0.11914 +Epoch [740/4000] Validation [2/4] Loss: 0.19652 focal_loss 0.08285 dice_loss 0.11367 +Epoch [740/4000] Validation [3/4] Loss: 0.12291 focal_loss 0.06466 dice_loss 0.05826 +Epoch [740/4000] Validation [4/4] Loss: 0.20323 focal_loss 0.09011 dice_loss 0.11312 +Epoch [740/4000] Validation metric {'Val/mean dice_metric': 0.9654359817504883, 'Val/mean miou_metric': 0.9442432522773743, 'Val/mean f1': 0.9678909182548523, 'Val/mean precision': 0.9669830799102783, 'Val/mean recall': 0.9688003063201904, 'Val/mean hd95_metric': 5.666452884674072} +Cheakpoint... +Epoch [740/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654359817504883, 'Val/mean miou_metric': 0.9442432522773743, 'Val/mean f1': 0.9678909182548523, 'Val/mean precision': 0.9669830799102783, 'Val/mean recall': 0.9688003063201904, 'Val/mean hd95_metric': 5.666452884674072} +Epoch [741/4000] Training [1/16] Loss: 0.01182 +Epoch [741/4000] Training [2/16] Loss: 0.01403 +Epoch [741/4000] Training [3/16] Loss: 0.01683 +Epoch [741/4000] Training [4/16] Loss: 0.01398 +Epoch [741/4000] Training [5/16] Loss: 0.01177 +Epoch [741/4000] Training [6/16] Loss: 0.01886 +Epoch [741/4000] Training [7/16] Loss: 0.01531 +Epoch [741/4000] Training [8/16] Loss: 0.02231 +Epoch [741/4000] Training [9/16] Loss: 0.01198 +Epoch [741/4000] Training [10/16] Loss: 0.01222 +Epoch [741/4000] Training [11/16] Loss: 0.01991 +Epoch [741/4000] Training [12/16] Loss: 0.01434 +Epoch [741/4000] Training [13/16] Loss: 0.01263 +Epoch [741/4000] Training [14/16] Loss: 0.01676 +Epoch [741/4000] Training [15/16] Loss: 0.01615 +Epoch [741/4000] Training [16/16] Loss: 0.01272 +Epoch [741/4000] Training metric {'Train/mean dice_metric': 0.989537239074707, 'Train/mean miou_metric': 0.9791615009307861, 'Train/mean f1': 0.9866780638694763, 'Train/mean precision': 0.9825927019119263, 'Train/mean recall': 0.9907975196838379, 'Train/mean hd95_metric': 1.3542976379394531} +Epoch [741/4000] Validation [1/4] Loss: 0.28520 focal_loss 0.18428 dice_loss 0.10092 +Epoch [741/4000] Validation [2/4] Loss: 0.23266 focal_loss 0.10229 dice_loss 0.13037 +Epoch [741/4000] Validation [3/4] Loss: 0.11903 focal_loss 0.05958 dice_loss 0.05945 +Epoch [741/4000] Validation [4/4] Loss: 0.26083 focal_loss 0.13949 dice_loss 0.12134 +Epoch [741/4000] Validation metric {'Val/mean dice_metric': 0.9632782936096191, 'Val/mean miou_metric': 0.941371738910675, 'Val/mean f1': 0.9684019088745117, 'Val/mean precision': 0.9686540961265564, 'Val/mean recall': 0.9681499004364014, 'Val/mean hd95_metric': 6.005012512207031} +Cheakpoint... +Epoch [741/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632782936096191, 'Val/mean miou_metric': 0.941371738910675, 'Val/mean f1': 0.9684019088745117, 'Val/mean precision': 0.9686540961265564, 'Val/mean recall': 0.9681499004364014, 'Val/mean hd95_metric': 6.005012512207031} +Epoch [742/4000] Training [1/16] Loss: 0.01344 +Epoch [742/4000] Training [2/16] Loss: 0.01280 +Epoch [742/4000] Training [3/16] Loss: 0.01278 +Epoch [742/4000] Training [4/16] Loss: 0.01481 +Epoch [742/4000] Training [5/16] Loss: 0.01396 +Epoch [742/4000] Training [6/16] Loss: 0.01334 +Epoch [742/4000] Training [7/16] Loss: 0.01208 +Epoch [742/4000] Training [8/16] Loss: 0.01289 +Epoch [742/4000] Training [9/16] Loss: 0.01628 +Epoch [742/4000] Training [10/16] Loss: 0.01207 +Epoch [742/4000] Training [11/16] Loss: 0.01459 +Epoch [742/4000] Training [12/16] Loss: 0.01369 +Epoch [742/4000] Training [13/16] Loss: 0.01272 +Epoch [742/4000] Training [14/16] Loss: 0.01588 +Epoch [742/4000] Training [15/16] Loss: 0.01005 +Epoch [742/4000] Training [16/16] Loss: 0.01910 +Epoch [742/4000] Training metric {'Train/mean dice_metric': 0.9903937578201294, 'Train/mean miou_metric': 0.9807945489883423, 'Train/mean f1': 0.9868783354759216, 'Train/mean precision': 0.9825077056884766, 'Train/mean recall': 0.9912880063056946, 'Train/mean hd95_metric': 1.3687593936920166} +Epoch [742/4000] Validation [1/4] Loss: 0.19521 focal_loss 0.12058 dice_loss 0.07463 +Epoch [742/4000] Validation [2/4] Loss: 0.22009 focal_loss 0.10917 dice_loss 0.11092 +Epoch [742/4000] Validation [3/4] Loss: 0.10711 focal_loss 0.05270 dice_loss 0.05441 +Epoch [742/4000] Validation [4/4] Loss: 0.23159 focal_loss 0.09680 dice_loss 0.13480 +Epoch [742/4000] Validation metric {'Val/mean dice_metric': 0.9674867391586304, 'Val/mean miou_metric': 0.9460517168045044, 'Val/mean f1': 0.9695258140563965, 'Val/mean precision': 0.9645302295684814, 'Val/mean recall': 0.9745734930038452, 'Val/mean hd95_metric': 5.7585320472717285} +Cheakpoint... +Epoch [742/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674867391586304, 'Val/mean miou_metric': 0.9460517168045044, 'Val/mean f1': 0.9695258140563965, 'Val/mean precision': 0.9645302295684814, 'Val/mean recall': 0.9745734930038452, 'Val/mean hd95_metric': 5.7585320472717285} +Epoch [743/4000] Training [1/16] Loss: 0.01380 +Epoch [743/4000] Training [2/16] Loss: 0.01217 +Epoch [743/4000] Training [3/16] Loss: 0.01991 +Epoch [743/4000] Training [4/16] Loss: 0.01313 +Epoch [743/4000] Training [5/16] Loss: 0.01485 +Epoch [743/4000] Training [6/16] Loss: 0.02077 +Epoch [743/4000] Training [7/16] Loss: 0.01662 +Epoch [743/4000] Training [8/16] Loss: 0.01345 +Epoch [743/4000] Training [9/16] Loss: 0.01281 +Epoch [743/4000] Training [10/16] Loss: 0.01713 +Epoch [743/4000] Training [11/16] Loss: 0.01667 +Epoch [743/4000] Training [12/16] Loss: 0.01357 +Epoch [743/4000] Training [13/16] Loss: 0.01306 +Epoch [743/4000] Training [14/16] Loss: 0.01321 +Epoch [743/4000] Training [15/16] Loss: 0.01358 +Epoch [743/4000] Training [16/16] Loss: 0.01283 +Epoch [743/4000] Training metric {'Train/mean dice_metric': 0.9898781180381775, 'Train/mean miou_metric': 0.9797651767730713, 'Train/mean f1': 0.98653244972229, 'Train/mean precision': 0.9818010926246643, 'Train/mean recall': 0.9913097023963928, 'Train/mean hd95_metric': 1.8387653827667236} +Epoch [743/4000] Validation [1/4] Loss: 0.17160 focal_loss 0.10304 dice_loss 0.06856 +Epoch [743/4000] Validation [2/4] Loss: 0.32005 focal_loss 0.16522 dice_loss 0.15483 +Epoch [743/4000] Validation [3/4] Loss: 0.15523 focal_loss 0.07961 dice_loss 0.07562 +Epoch [743/4000] Validation [4/4] Loss: 0.25687 focal_loss 0.13064 dice_loss 0.12623 +Epoch [743/4000] Validation metric {'Val/mean dice_metric': 0.9670480489730835, 'Val/mean miou_metric': 0.9452419281005859, 'Val/mean f1': 0.9689540863037109, 'Val/mean precision': 0.9654109477996826, 'Val/mean recall': 0.9725233316421509, 'Val/mean hd95_metric': 6.764701843261719} +Cheakpoint... +Epoch [743/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670480489730835, 'Val/mean miou_metric': 0.9452419281005859, 'Val/mean f1': 0.9689540863037109, 'Val/mean precision': 0.9654109477996826, 'Val/mean recall': 0.9725233316421509, 'Val/mean hd95_metric': 6.764701843261719} +Epoch [744/4000] Training [1/16] Loss: 0.00932 +Epoch [744/4000] Training [2/16] Loss: 0.01295 +Epoch [744/4000] Training [3/16] Loss: 0.01612 +Epoch [744/4000] Training [4/16] Loss: 0.01236 +Epoch [744/4000] Training [5/16] Loss: 0.01335 +Epoch [744/4000] Training [6/16] Loss: 0.01299 +Epoch [744/4000] Training [7/16] Loss: 0.01274 +Epoch [744/4000] Training [8/16] Loss: 0.01417 +Epoch [744/4000] Training [9/16] Loss: 0.01157 +Epoch [744/4000] Training [10/16] Loss: 0.02587 +Epoch [744/4000] Training [11/16] Loss: 0.01480 +Epoch [744/4000] Training [12/16] Loss: 0.01307 +Epoch [744/4000] Training [13/16] Loss: 0.01447 +Epoch [744/4000] Training [14/16] Loss: 0.01553 +Epoch [744/4000] Training [15/16] Loss: 0.06483 +Epoch [744/4000] Training [16/16] Loss: 0.01539 +Epoch [744/4000] Training metric {'Train/mean dice_metric': 0.9892653822898865, 'Train/mean miou_metric': 0.9791607856750488, 'Train/mean f1': 0.9849523305892944, 'Train/mean precision': 0.9794444441795349, 'Train/mean recall': 0.9905225038528442, 'Train/mean hd95_metric': 2.3590521812438965} +Epoch [744/4000] Validation [1/4] Loss: 0.49276 focal_loss 0.31923 dice_loss 0.17353 +Epoch [744/4000] Validation [2/4] Loss: 0.38039 focal_loss 0.18910 dice_loss 0.19129 +Epoch [744/4000] Validation [3/4] Loss: 0.17570 focal_loss 0.09786 dice_loss 0.07785 +Epoch [744/4000] Validation [4/4] Loss: 0.44518 focal_loss 0.26625 dice_loss 0.17893 +Epoch [744/4000] Validation metric {'Val/mean dice_metric': 0.959365725517273, 'Val/mean miou_metric': 0.9362476468086243, 'Val/mean f1': 0.9602930545806885, 'Val/mean precision': 0.966905951499939, 'Val/mean recall': 0.9537698030471802, 'Val/mean hd95_metric': 7.839206695556641} +Cheakpoint... +Epoch [744/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9594], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.959365725517273, 'Val/mean miou_metric': 0.9362476468086243, 'Val/mean f1': 0.9602930545806885, 'Val/mean precision': 0.966905951499939, 'Val/mean recall': 0.9537698030471802, 'Val/mean hd95_metric': 7.839206695556641} +Epoch [745/4000] Training [1/16] Loss: 0.01602 +Epoch [745/4000] Training [2/16] Loss: 0.01676 +Epoch [745/4000] Training [3/16] Loss: 0.01531 +Epoch [745/4000] Training [4/16] Loss: 0.01607 +Epoch [745/4000] Training [5/16] Loss: 0.01571 +Epoch [745/4000] Training [6/16] Loss: 0.01232 +Epoch [745/4000] Training [7/16] Loss: 0.01746 +Epoch [745/4000] Training [8/16] Loss: 0.03831 +Epoch [745/4000] Training [9/16] Loss: 0.04464 +Epoch [745/4000] Training [10/16] Loss: 0.01607 +Epoch [745/4000] Training [11/16] Loss: 0.01723 +Epoch [745/4000] Training [12/16] Loss: 0.01685 +Epoch [745/4000] Training [13/16] Loss: 0.01672 +Epoch [745/4000] Training [14/16] Loss: 0.01498 +Epoch [745/4000] Training [15/16] Loss: 0.02382 +Epoch [745/4000] Training [16/16] Loss: 0.01794 +Epoch [745/4000] Training metric {'Train/mean dice_metric': 0.9878308773040771, 'Train/mean miou_metric': 0.975899338722229, 'Train/mean f1': 0.9850338101387024, 'Train/mean precision': 0.9799476265907288, 'Train/mean recall': 0.9901729822158813, 'Train/mean hd95_metric': 2.203665256500244} +Epoch [745/4000] Validation [1/4] Loss: 0.23418 focal_loss 0.14994 dice_loss 0.08423 +Epoch [745/4000] Validation [2/4] Loss: 0.26129 focal_loss 0.12691 dice_loss 0.13439 +Epoch [745/4000] Validation [3/4] Loss: 0.11511 focal_loss 0.05997 dice_loss 0.05514 +Epoch [745/4000] Validation [4/4] Loss: 0.16685 focal_loss 0.07677 dice_loss 0.09008 +Epoch [745/4000] Validation metric {'Val/mean dice_metric': 0.9632198214530945, 'Val/mean miou_metric': 0.9405025243759155, 'Val/mean f1': 0.9673979878425598, 'Val/mean precision': 0.9675669074058533, 'Val/mean recall': 0.9672292470932007, 'Val/mean hd95_metric': 6.876126289367676} +Cheakpoint... +Epoch [745/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632198214530945, 'Val/mean miou_metric': 0.9405025243759155, 'Val/mean f1': 0.9673979878425598, 'Val/mean precision': 0.9675669074058533, 'Val/mean recall': 0.9672292470932007, 'Val/mean hd95_metric': 6.876126289367676} +Epoch [746/4000] Training [1/16] Loss: 0.01537 +Epoch [746/4000] Training [2/16] Loss: 0.01619 +Epoch [746/4000] Training [3/16] Loss: 0.01343 +Epoch [746/4000] Training [4/16] Loss: 0.01815 +Epoch [746/4000] Training [5/16] Loss: 0.01274 +Epoch [746/4000] Training [6/16] Loss: 0.01179 +Epoch [746/4000] Training [7/16] Loss: 0.01654 +Epoch [746/4000] Training [8/16] Loss: 0.01369 +Epoch [746/4000] Training [9/16] Loss: 0.01111 +Epoch [746/4000] Training [10/16] Loss: 0.02156 +Epoch [746/4000] Training [11/16] Loss: 0.01470 +Epoch [746/4000] Training [12/16] Loss: 0.01476 +Epoch [746/4000] Training [13/16] Loss: 0.01315 +Epoch [746/4000] Training [14/16] Loss: 0.02909 +Epoch [746/4000] Training [15/16] Loss: 0.02181 +Epoch [746/4000] Training [16/16] Loss: 0.01783 +Epoch [746/4000] Training metric {'Train/mean dice_metric': 0.9888493418693542, 'Train/mean miou_metric': 0.9777967929840088, 'Train/mean f1': 0.9855430126190186, 'Train/mean precision': 0.9810212850570679, 'Train/mean recall': 0.9901065230369568, 'Train/mean hd95_metric': 2.106595516204834} +Epoch [746/4000] Validation [1/4] Loss: 0.18895 focal_loss 0.10004 dice_loss 0.08891 +Epoch [746/4000] Validation [2/4] Loss: 0.30456 focal_loss 0.13597 dice_loss 0.16858 +Epoch [746/4000] Validation [3/4] Loss: 0.17335 focal_loss 0.09821 dice_loss 0.07513 +Epoch [746/4000] Validation [4/4] Loss: 0.24728 focal_loss 0.11186 dice_loss 0.13542 +Epoch [746/4000] Validation metric {'Val/mean dice_metric': 0.957809329032898, 'Val/mean miou_metric': 0.9349117279052734, 'Val/mean f1': 0.9635937213897705, 'Val/mean precision': 0.9670769572257996, 'Val/mean recall': 0.9601355195045471, 'Val/mean hd95_metric': 6.69097900390625} +Cheakpoint... +Epoch [746/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9578], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.957809329032898, 'Val/mean miou_metric': 0.9349117279052734, 'Val/mean f1': 0.9635937213897705, 'Val/mean precision': 0.9670769572257996, 'Val/mean recall': 0.9601355195045471, 'Val/mean hd95_metric': 6.69097900390625} +Epoch [747/4000] Training [1/16] Loss: 0.01145 +Epoch [747/4000] Training [2/16] Loss: 0.01842 +Epoch [747/4000] Training [3/16] Loss: 0.01241 +Epoch [747/4000] Training [4/16] Loss: 0.01916 +Epoch [747/4000] Training [5/16] Loss: 0.01072 +Epoch [747/4000] Training [6/16] Loss: 0.01375 +Epoch [747/4000] Training [7/16] Loss: 0.01581 +Epoch [747/4000] Training [8/16] Loss: 0.01429 +Epoch [747/4000] Training [9/16] Loss: 0.01759 +Epoch [747/4000] Training [10/16] Loss: 0.01424 +Epoch [747/4000] Training [11/16] Loss: 0.01446 +Epoch [747/4000] Training [12/16] Loss: 0.01505 +Epoch [747/4000] Training [13/16] Loss: 0.01586 +Epoch [747/4000] Training [14/16] Loss: 0.01174 +Epoch [747/4000] Training [15/16] Loss: 0.01193 +Epoch [747/4000] Training [16/16] Loss: 0.01445 +Epoch [747/4000] Training metric {'Train/mean dice_metric': 0.9901220798492432, 'Train/mean miou_metric': 0.9802474975585938, 'Train/mean f1': 0.9867006540298462, 'Train/mean precision': 0.9821663498878479, 'Train/mean recall': 0.9912769794464111, 'Train/mean hd95_metric': 1.2886383533477783} +Epoch [747/4000] Validation [1/4] Loss: 0.72251 focal_loss 0.51649 dice_loss 0.20602 +Epoch [747/4000] Validation [2/4] Loss: 0.24738 focal_loss 0.11854 dice_loss 0.12885 +Epoch [747/4000] Validation [3/4] Loss: 0.11388 focal_loss 0.05175 dice_loss 0.06213 +Epoch [747/4000] Validation [4/4] Loss: 0.22879 focal_loss 0.09644 dice_loss 0.13235 +Epoch [747/4000] Validation metric {'Val/mean dice_metric': 0.9631458520889282, 'Val/mean miou_metric': 0.9418286085128784, 'Val/mean f1': 0.9658076763153076, 'Val/mean precision': 0.967928946018219, 'Val/mean recall': 0.963695764541626, 'Val/mean hd95_metric': 6.834017753601074} +Cheakpoint... +Epoch [747/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9631], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631458520889282, 'Val/mean miou_metric': 0.9418286085128784, 'Val/mean f1': 0.9658076763153076, 'Val/mean precision': 0.967928946018219, 'Val/mean recall': 0.963695764541626, 'Val/mean hd95_metric': 6.834017753601074} +Epoch [748/4000] Training [1/16] Loss: 0.01584 +Epoch [748/4000] Training [2/16] Loss: 0.01419 +Epoch [748/4000] Training [3/16] Loss: 0.01313 +Epoch [748/4000] Training [4/16] Loss: 0.01228 +Epoch [748/4000] Training [5/16] Loss: 0.02059 +Epoch [748/4000] Training [6/16] Loss: 0.01647 +Epoch [748/4000] Training [7/16] Loss: 0.01131 +Epoch [748/4000] Training [8/16] Loss: 0.01692 +Epoch [748/4000] Training [9/16] Loss: 0.01131 +Epoch [748/4000] Training [10/16] Loss: 0.01285 +Epoch [748/4000] Training [11/16] Loss: 0.01519 +Epoch [748/4000] Training [12/16] Loss: 0.01742 +Epoch [748/4000] Training [13/16] Loss: 0.01166 +Epoch [748/4000] Training [14/16] Loss: 0.01679 +Epoch [748/4000] Training [15/16] Loss: 0.01527 +Epoch [748/4000] Training [16/16] Loss: 0.01385 +Epoch [748/4000] Training metric {'Train/mean dice_metric': 0.9896558523178101, 'Train/mean miou_metric': 0.9793521761894226, 'Train/mean f1': 0.9868285059928894, 'Train/mean precision': 0.9821463227272034, 'Train/mean recall': 0.9915555715560913, 'Train/mean hd95_metric': 1.5860247611999512} +Epoch [748/4000] Validation [1/4] Loss: 0.49365 focal_loss 0.37175 dice_loss 0.12190 +Epoch [748/4000] Validation [2/4] Loss: 0.23619 focal_loss 0.11352 dice_loss 0.12267 +Epoch [748/4000] Validation [3/4] Loss: 0.12246 focal_loss 0.06182 dice_loss 0.06064 +Epoch [748/4000] Validation [4/4] Loss: 0.21125 focal_loss 0.10141 dice_loss 0.10984 +Epoch [748/4000] Validation metric {'Val/mean dice_metric': 0.9660859107971191, 'Val/mean miou_metric': 0.9441245794296265, 'Val/mean f1': 0.967313289642334, 'Val/mean precision': 0.9640378952026367, 'Val/mean recall': 0.970611035823822, 'Val/mean hd95_metric': 6.807858467102051} +Cheakpoint... +Epoch [748/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660859107971191, 'Val/mean miou_metric': 0.9441245794296265, 'Val/mean f1': 0.967313289642334, 'Val/mean precision': 0.9640378952026367, 'Val/mean recall': 0.970611035823822, 'Val/mean hd95_metric': 6.807858467102051} +Epoch [749/4000] Training [1/16] Loss: 0.01430 +Epoch [749/4000] Training [2/16] Loss: 0.01106 +Epoch [749/4000] Training [3/16] Loss: 0.01349 +Epoch [749/4000] Training [4/16] Loss: 0.02732 +Epoch [749/4000] Training [5/16] Loss: 0.01797 +Epoch [749/4000] Training [6/16] Loss: 0.01208 +Epoch [749/4000] Training [7/16] Loss: 0.01095 +Epoch [749/4000] Training [8/16] Loss: 0.01936 +Epoch [749/4000] Training [9/16] Loss: 0.01447 +Epoch [749/4000] Training [10/16] Loss: 0.01504 +Epoch [749/4000] Training [11/16] Loss: 0.00936 +Epoch [749/4000] Training [12/16] Loss: 0.01370 +Epoch [749/4000] Training [13/16] Loss: 0.01431 +Epoch [749/4000] Training [14/16] Loss: 0.01724 +Epoch [749/4000] Training [15/16] Loss: 0.01382 +Epoch [749/4000] Training [16/16] Loss: 0.01516 +Epoch [749/4000] Training metric {'Train/mean dice_metric': 0.9899686574935913, 'Train/mean miou_metric': 0.9800288677215576, 'Train/mean f1': 0.9871876239776611, 'Train/mean precision': 0.9826487302780151, 'Train/mean recall': 0.9917687177658081, 'Train/mean hd95_metric': 1.3906593322753906} +Epoch [749/4000] Validation [1/4] Loss: 0.27412 focal_loss 0.17358 dice_loss 0.10054 +Epoch [749/4000] Validation [2/4] Loss: 0.20084 focal_loss 0.08443 dice_loss 0.11641 +Epoch [749/4000] Validation [3/4] Loss: 0.14699 focal_loss 0.07906 dice_loss 0.06792 +Epoch [749/4000] Validation [4/4] Loss: 0.28001 focal_loss 0.13009 dice_loss 0.14993 +Epoch [749/4000] Validation metric {'Val/mean dice_metric': 0.966517448425293, 'Val/mean miou_metric': 0.9445047378540039, 'Val/mean f1': 0.968072772026062, 'Val/mean precision': 0.9653729796409607, 'Val/mean recall': 0.9707876443862915, 'Val/mean hd95_metric': 6.312336444854736} +Cheakpoint... +Epoch [749/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966517448425293, 'Val/mean miou_metric': 0.9445047378540039, 'Val/mean f1': 0.968072772026062, 'Val/mean precision': 0.9653729796409607, 'Val/mean recall': 0.9707876443862915, 'Val/mean hd95_metric': 6.312336444854736} +Epoch [750/4000] Training [1/16] Loss: 0.01146 +Epoch [750/4000] Training [2/16] Loss: 0.01501 +Epoch [750/4000] Training [3/16] Loss: 0.01157 +Epoch [750/4000] Training [4/16] Loss: 0.01155 +Epoch [750/4000] Training [5/16] Loss: 0.01197 +Epoch [750/4000] Training [6/16] Loss: 0.01098 +Epoch [750/4000] Training [7/16] Loss: 0.01140 +Epoch [750/4000] Training [8/16] Loss: 0.01133 +Epoch [750/4000] Training [9/16] Loss: 0.01100 +Epoch [750/4000] Training [10/16] Loss: 0.01256 +Epoch [750/4000] Training [11/16] Loss: 0.01739 +Epoch [750/4000] Training [12/16] Loss: 0.01756 +Epoch [750/4000] Training [13/16] Loss: 0.00984 +Epoch [750/4000] Training [14/16] Loss: 0.01781 +Epoch [750/4000] Training [15/16] Loss: 0.00900 +Epoch [750/4000] Training [16/16] Loss: 0.01386 +Epoch [750/4000] Training metric {'Train/mean dice_metric': 0.9911595582962036, 'Train/mean miou_metric': 0.982271671295166, 'Train/mean f1': 0.9879283308982849, 'Train/mean precision': 0.9833617210388184, 'Train/mean recall': 0.9925376176834106, 'Train/mean hd95_metric': 1.1889100074768066} +Epoch [750/4000] Validation [1/4] Loss: 0.42306 focal_loss 0.30946 dice_loss 0.11360 +Epoch [750/4000] Validation [2/4] Loss: 0.14733 focal_loss 0.06341 dice_loss 0.08392 +Epoch [750/4000] Validation [3/4] Loss: 0.13870 focal_loss 0.07629 dice_loss 0.06241 +Epoch [750/4000] Validation [4/4] Loss: 0.26748 focal_loss 0.15627 dice_loss 0.11120 +Epoch [750/4000] Validation metric {'Val/mean dice_metric': 0.9688620567321777, 'Val/mean miou_metric': 0.9484230279922485, 'Val/mean f1': 0.9693359732627869, 'Val/mean precision': 0.9677761197090149, 'Val/mean recall': 0.97090083360672, 'Val/mean hd95_metric': 5.592277526855469} +Cheakpoint... +Epoch [750/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688620567321777, 'Val/mean miou_metric': 0.9484230279922485, 'Val/mean f1': 0.9693359732627869, 'Val/mean precision': 0.9677761197090149, 'Val/mean recall': 0.97090083360672, 'Val/mean hd95_metric': 5.592277526855469} +Epoch [751/4000] Training [1/16] Loss: 0.01167 +Epoch [751/4000] Training [2/16] Loss: 0.01283 +Epoch [751/4000] Training [3/16] Loss: 0.01492 +Epoch [751/4000] Training [4/16] Loss: 0.00914 +Epoch [751/4000] Training [5/16] Loss: 0.01460 +Epoch [751/4000] Training [6/16] Loss: 0.01386 +Epoch [751/4000] Training [7/16] Loss: 0.01403 +Epoch [751/4000] Training [8/16] Loss: 0.01383 +Epoch [751/4000] Training [9/16] Loss: 0.01496 +Epoch [751/4000] Training [10/16] Loss: 0.01258 +Epoch [751/4000] Training [11/16] Loss: 0.01507 +Epoch [751/4000] Training [12/16] Loss: 0.01597 +Epoch [751/4000] Training [13/16] Loss: 0.01498 +Epoch [751/4000] Training [14/16] Loss: 0.01120 +Epoch [751/4000] Training [15/16] Loss: 0.01219 +Epoch [751/4000] Training [16/16] Loss: 0.01383 +Epoch [751/4000] Training metric {'Train/mean dice_metric': 0.99034583568573, 'Train/mean miou_metric': 0.9806381464004517, 'Train/mean f1': 0.9862942695617676, 'Train/mean precision': 0.9809748530387878, 'Train/mean recall': 0.9916716814041138, 'Train/mean hd95_metric': 1.3022953271865845} +Epoch [751/4000] Validation [1/4] Loss: 0.18686 focal_loss 0.11376 dice_loss 0.07310 +Epoch [751/4000] Validation [2/4] Loss: 0.18804 focal_loss 0.09022 dice_loss 0.09782 +Epoch [751/4000] Validation [3/4] Loss: 0.10498 focal_loss 0.05541 dice_loss 0.04957 +Epoch [751/4000] Validation [4/4] Loss: 0.24967 focal_loss 0.12327 dice_loss 0.12640 +Epoch [751/4000] Validation metric {'Val/mean dice_metric': 0.9681142568588257, 'Val/mean miou_metric': 0.9470040202140808, 'Val/mean f1': 0.9685078859329224, 'Val/mean precision': 0.9677103161811829, 'Val/mean recall': 0.9693068265914917, 'Val/mean hd95_metric': 5.481663227081299} +Cheakpoint... +Epoch [751/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681142568588257, 'Val/mean miou_metric': 0.9470040202140808, 'Val/mean f1': 0.9685078859329224, 'Val/mean precision': 0.9677103161811829, 'Val/mean recall': 0.9693068265914917, 'Val/mean hd95_metric': 5.481663227081299} +Epoch [752/4000] Training [1/16] Loss: 0.02703 +Epoch [752/4000] Training [2/16] Loss: 0.01234 +Epoch [752/4000] Training [3/16] Loss: 0.01190 +Epoch [752/4000] Training [4/16] Loss: 0.01532 +Epoch [752/4000] Training [5/16] Loss: 0.01410 +Epoch [752/4000] Training [6/16] Loss: 0.01304 +Epoch [752/4000] Training [7/16] Loss: 0.01312 +Epoch [752/4000] Training [8/16] Loss: 0.01466 +Epoch [752/4000] Training [9/16] Loss: 0.01271 +Epoch [752/4000] Training [10/16] Loss: 0.05141 +Epoch [752/4000] Training [11/16] Loss: 0.01770 +Epoch [752/4000] Training [12/16] Loss: 0.01472 +Epoch [752/4000] Training [13/16] Loss: 0.01680 +Epoch [752/4000] Training [14/16] Loss: 0.01467 +Epoch [752/4000] Training [15/16] Loss: 0.01584 +Epoch [752/4000] Training [16/16] Loss: 0.01529 +Epoch [752/4000] Training metric {'Train/mean dice_metric': 0.9887805581092834, 'Train/mean miou_metric': 0.9779002666473389, 'Train/mean f1': 0.9860450625419617, 'Train/mean precision': 0.9815459251403809, 'Train/mean recall': 0.9905856847763062, 'Train/mean hd95_metric': 2.0095293521881104} +Epoch [752/4000] Validation [1/4] Loss: 0.51034 focal_loss 0.38513 dice_loss 0.12521 +Epoch [752/4000] Validation [2/4] Loss: 0.19006 focal_loss 0.07268 dice_loss 0.11738 +Epoch [752/4000] Validation [3/4] Loss: 0.15443 focal_loss 0.08636 dice_loss 0.06807 +Epoch [752/4000] Validation [4/4] Loss: 0.23276 focal_loss 0.11599 dice_loss 0.11677 +Epoch [752/4000] Validation metric {'Val/mean dice_metric': 0.9653726816177368, 'Val/mean miou_metric': 0.9423502087593079, 'Val/mean f1': 0.9657132625579834, 'Val/mean precision': 0.9642398953437805, 'Val/mean recall': 0.967191219329834, 'Val/mean hd95_metric': 7.470872402191162} +Cheakpoint... +Epoch [752/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653726816177368, 'Val/mean miou_metric': 0.9423502087593079, 'Val/mean f1': 0.9657132625579834, 'Val/mean precision': 0.9642398953437805, 'Val/mean recall': 0.967191219329834, 'Val/mean hd95_metric': 7.470872402191162} +Epoch [753/4000] Training [1/16] Loss: 0.00998 +Epoch [753/4000] Training [2/16] Loss: 0.01727 +Epoch [753/4000] Training [3/16] Loss: 0.01716 +Epoch [753/4000] Training [4/16] Loss: 0.01718 +Epoch [753/4000] Training [5/16] Loss: 0.04951 +Epoch [753/4000] Training [6/16] Loss: 0.01503 +Epoch [753/4000] Training [7/16] Loss: 0.01383 +Epoch [753/4000] Training [8/16] Loss: 0.01682 +Epoch [753/4000] Training [9/16] Loss: 0.02047 +Epoch [753/4000] Training [10/16] Loss: 0.01435 +Epoch [753/4000] Training [11/16] Loss: 0.01581 +Epoch [753/4000] Training [12/16] Loss: 0.01510 +Epoch [753/4000] Training [13/16] Loss: 0.02293 +Epoch [753/4000] Training [14/16] Loss: 0.01842 +Epoch [753/4000] Training [15/16] Loss: 0.01529 +Epoch [753/4000] Training [16/16] Loss: 0.01480 +Epoch [753/4000] Training metric {'Train/mean dice_metric': 0.9868036508560181, 'Train/mean miou_metric': 0.9749276638031006, 'Train/mean f1': 0.984812319278717, 'Train/mean precision': 0.9808049201965332, 'Train/mean recall': 0.9888525605201721, 'Train/mean hd95_metric': 2.8735108375549316} +Epoch [753/4000] Validation [1/4] Loss: 0.81740 focal_loss 0.63528 dice_loss 0.18212 +Epoch [753/4000] Validation [2/4] Loss: 0.22546 focal_loss 0.10287 dice_loss 0.12259 +Epoch [753/4000] Validation [3/4] Loss: 0.11422 focal_loss 0.04922 dice_loss 0.06500 +Epoch [753/4000] Validation [4/4] Loss: 0.32527 focal_loss 0.18889 dice_loss 0.13638 +Epoch [753/4000] Validation metric {'Val/mean dice_metric': 0.9548295736312866, 'Val/mean miou_metric': 0.9308039546012878, 'Val/mean f1': 0.9598029851913452, 'Val/mean precision': 0.9687515497207642, 'Val/mean recall': 0.9510182738304138, 'Val/mean hd95_metric': 7.399296283721924} +Cheakpoint... +Epoch [753/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9548], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9548295736312866, 'Val/mean miou_metric': 0.9308039546012878, 'Val/mean f1': 0.9598029851913452, 'Val/mean precision': 0.9687515497207642, 'Val/mean recall': 0.9510182738304138, 'Val/mean hd95_metric': 7.399296283721924} +Epoch [754/4000] Training [1/16] Loss: 0.01738 +Epoch [754/4000] Training [2/16] Loss: 0.01641 +Epoch [754/4000] Training [3/16] Loss: 0.01195 +Epoch [754/4000] Training [4/16] Loss: 0.01631 +Epoch [754/4000] Training [5/16] Loss: 0.01956 +Epoch [754/4000] Training [6/16] Loss: 0.01951 +Epoch [754/4000] Training [7/16] Loss: 0.02007 +Epoch [754/4000] Training [8/16] Loss: 0.01375 +Epoch [754/4000] Training [9/16] Loss: 0.01401 +Epoch [754/4000] Training [10/16] Loss: 0.03084 +Epoch [754/4000] Training [11/16] Loss: 0.01581 +Epoch [754/4000] Training [12/16] Loss: 0.01869 +Epoch [754/4000] Training [13/16] Loss: 0.01383 +Epoch [754/4000] Training [14/16] Loss: 0.01281 +Epoch [754/4000] Training [15/16] Loss: 0.02196 +Epoch [754/4000] Training [16/16] Loss: 0.02742 +Epoch [754/4000] Training metric {'Train/mean dice_metric': 0.9861675500869751, 'Train/mean miou_metric': 0.97327721118927, 'Train/mean f1': 0.9834340810775757, 'Train/mean precision': 0.9784632325172424, 'Train/mean recall': 0.9884556531906128, 'Train/mean hd95_metric': 2.593733310699463} +Epoch [754/4000] Validation [1/4] Loss: 0.26664 focal_loss 0.17611 dice_loss 0.09053 +Epoch [754/4000] Validation [2/4] Loss: 0.42191 focal_loss 0.22222 dice_loss 0.19969 +Epoch [754/4000] Validation [3/4] Loss: 0.14411 focal_loss 0.07693 dice_loss 0.06718 +Epoch [754/4000] Validation [4/4] Loss: 0.26562 focal_loss 0.12842 dice_loss 0.13721 +Epoch [754/4000] Validation metric {'Val/mean dice_metric': 0.9569805860519409, 'Val/mean miou_metric': 0.9315996170043945, 'Val/mean f1': 0.9565664529800415, 'Val/mean precision': 0.9409345388412476, 'Val/mean recall': 0.9727265238761902, 'Val/mean hd95_metric': 10.774083137512207} +Cheakpoint... +Epoch [754/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9570], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9569805860519409, 'Val/mean miou_metric': 0.9315996170043945, 'Val/mean f1': 0.9565664529800415, 'Val/mean precision': 0.9409345388412476, 'Val/mean recall': 0.9727265238761902, 'Val/mean hd95_metric': 10.774083137512207} +Epoch [755/4000] Training [1/16] Loss: 0.01852 +Epoch [755/4000] Training [2/16] Loss: 0.02405 +Epoch [755/4000] Training [3/16] Loss: 0.01477 +Epoch [755/4000] Training [4/16] Loss: 0.01359 +Epoch [755/4000] Training [5/16] Loss: 0.01236 +Epoch [755/4000] Training [6/16] Loss: 0.02098 +Epoch [755/4000] Training [7/16] Loss: 0.01362 +Epoch [755/4000] Training [8/16] Loss: 0.01491 +Epoch [755/4000] Training [9/16] Loss: 0.01980 +Epoch [755/4000] Training [10/16] Loss: 0.01933 +Epoch [755/4000] Training [11/16] Loss: 0.01670 +Epoch [755/4000] Training [12/16] Loss: 0.02494 +Epoch [755/4000] Training [13/16] Loss: 0.01646 +Epoch [755/4000] Training [14/16] Loss: 0.01456 +Epoch [755/4000] Training [15/16] Loss: 0.01290 +Epoch [755/4000] Training [16/16] Loss: 0.01622 +Epoch [755/4000] Training metric {'Train/mean dice_metric': 0.9882882833480835, 'Train/mean miou_metric': 0.9766918420791626, 'Train/mean f1': 0.9851322174072266, 'Train/mean precision': 0.9808003306388855, 'Train/mean recall': 0.9895026087760925, 'Train/mean hd95_metric': 2.8963143825531006} +Epoch [755/4000] Validation [1/4] Loss: 0.26146 focal_loss 0.15552 dice_loss 0.10594 +Epoch [755/4000] Validation [2/4] Loss: 0.18977 focal_loss 0.08298 dice_loss 0.10679 +Epoch [755/4000] Validation [3/4] Loss: 0.16011 focal_loss 0.08202 dice_loss 0.07809 +Epoch [755/4000] Validation [4/4] Loss: 0.19404 focal_loss 0.09208 dice_loss 0.10196 +Epoch [755/4000] Validation metric {'Val/mean dice_metric': 0.9635663032531738, 'Val/mean miou_metric': 0.9402841329574585, 'Val/mean f1': 0.9652397632598877, 'Val/mean precision': 0.9600446224212646, 'Val/mean recall': 0.9704915285110474, 'Val/mean hd95_metric': 8.20057487487793} +Cheakpoint... +Epoch [755/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9635663032531738, 'Val/mean miou_metric': 0.9402841329574585, 'Val/mean f1': 0.9652397632598877, 'Val/mean precision': 0.9600446224212646, 'Val/mean recall': 0.9704915285110474, 'Val/mean hd95_metric': 8.20057487487793} +Epoch [756/4000] Training [1/16] Loss: 0.01539 +Epoch [756/4000] Training [2/16] Loss: 0.01418 +Epoch [756/4000] Training [3/16] Loss: 0.01530 +Epoch [756/4000] Training [4/16] Loss: 0.01182 +Epoch [756/4000] Training [5/16] Loss: 0.01561 +Epoch [756/4000] Training [6/16] Loss: 0.01051 +Epoch [756/4000] Training [7/16] Loss: 0.01655 +Epoch [756/4000] Training [8/16] Loss: 0.01518 +Epoch [756/4000] Training [9/16] Loss: 0.01532 +Epoch [756/4000] Training [10/16] Loss: 0.01772 +Epoch [756/4000] Training [11/16] Loss: 0.01491 +Epoch [756/4000] Training [12/16] Loss: 0.01273 +Epoch [756/4000] Training [13/16] Loss: 0.01665 +Epoch [756/4000] Training [14/16] Loss: 0.02089 +Epoch [756/4000] Training [15/16] Loss: 0.01836 +Epoch [756/4000] Training [16/16] Loss: 0.01970 +Epoch [756/4000] Training metric {'Train/mean dice_metric': 0.9888788461685181, 'Train/mean miou_metric': 0.9780517220497131, 'Train/mean f1': 0.9858102202415466, 'Train/mean precision': 0.9814624786376953, 'Train/mean recall': 0.9901966452598572, 'Train/mean hd95_metric': 1.9421873092651367} +Epoch [756/4000] Validation [1/4] Loss: 0.14859 focal_loss 0.08136 dice_loss 0.06723 +Epoch [756/4000] Validation [2/4] Loss: 0.26791 focal_loss 0.11843 dice_loss 0.14948 +Epoch [756/4000] Validation [3/4] Loss: 0.30418 focal_loss 0.19014 dice_loss 0.11404 +Epoch [756/4000] Validation [4/4] Loss: 0.34769 focal_loss 0.18605 dice_loss 0.16164 +Epoch [756/4000] Validation metric {'Val/mean dice_metric': 0.9633744359016418, 'Val/mean miou_metric': 0.9401972889900208, 'Val/mean f1': 0.9627115726470947, 'Val/mean precision': 0.9494785666465759, 'Val/mean recall': 0.9763185977935791, 'Val/mean hd95_metric': 8.298561096191406} +Cheakpoint... +Epoch [756/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633744359016418, 'Val/mean miou_metric': 0.9401972889900208, 'Val/mean f1': 0.9627115726470947, 'Val/mean precision': 0.9494785666465759, 'Val/mean recall': 0.9763185977935791, 'Val/mean hd95_metric': 8.298561096191406} +Epoch [757/4000] Training [1/16] Loss: 0.01826 +Epoch [757/4000] Training [2/16] Loss: 0.01248 +Epoch [757/4000] Training [3/16] Loss: 0.01259 +Epoch [757/4000] Training [4/16] Loss: 0.00996 +Epoch [757/4000] Training [5/16] Loss: 0.01603 +Epoch [757/4000] Training [6/16] Loss: 0.01618 +Epoch [757/4000] Training [7/16] Loss: 0.01862 +Epoch [757/4000] Training [8/16] Loss: 0.01411 +Epoch [757/4000] Training [9/16] Loss: 0.01294 +Epoch [757/4000] Training [10/16] Loss: 0.01189 +Epoch [757/4000] Training [11/16] Loss: 0.01368 +Epoch [757/4000] Training [12/16] Loss: 0.01400 +Epoch [757/4000] Training [13/16] Loss: 0.01654 +Epoch [757/4000] Training [14/16] Loss: 0.01696 +Epoch [757/4000] Training [15/16] Loss: 0.01770 +Epoch [757/4000] Training [16/16] Loss: 0.01563 +Epoch [757/4000] Training metric {'Train/mean dice_metric': 0.9899083375930786, 'Train/mean miou_metric': 0.9798352122306824, 'Train/mean f1': 0.986655056476593, 'Train/mean precision': 0.9823433756828308, 'Train/mean recall': 0.9910047650337219, 'Train/mean hd95_metric': 2.067347288131714} +Epoch [757/4000] Validation [1/4] Loss: 0.57899 focal_loss 0.41531 dice_loss 0.16367 +Epoch [757/4000] Validation [2/4] Loss: 0.25355 focal_loss 0.12110 dice_loss 0.13245 +Epoch [757/4000] Validation [3/4] Loss: 0.11361 focal_loss 0.05554 dice_loss 0.05807 +Epoch [757/4000] Validation [4/4] Loss: 0.29759 focal_loss 0.16003 dice_loss 0.13757 +Epoch [757/4000] Validation metric {'Val/mean dice_metric': 0.9654214978218079, 'Val/mean miou_metric': 0.9434536099433899, 'Val/mean f1': 0.964931070804596, 'Val/mean precision': 0.9633763432502747, 'Val/mean recall': 0.9664909243583679, 'Val/mean hd95_metric': 6.8388261795043945} +Cheakpoint... +Epoch [757/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654214978218079, 'Val/mean miou_metric': 0.9434536099433899, 'Val/mean f1': 0.964931070804596, 'Val/mean precision': 0.9633763432502747, 'Val/mean recall': 0.9664909243583679, 'Val/mean hd95_metric': 6.8388261795043945} +Epoch [758/4000] Training [1/16] Loss: 0.01248 +Epoch [758/4000] Training [2/16] Loss: 0.01461 +Epoch [758/4000] Training [3/16] Loss: 0.01478 +Epoch [758/4000] Training [4/16] Loss: 0.01566 +Epoch [758/4000] Training [5/16] Loss: 0.01278 +Epoch [758/4000] Training [6/16] Loss: 0.01534 +Epoch [758/4000] Training [7/16] Loss: 0.01272 +Epoch [758/4000] Training [8/16] Loss: 0.01259 +Epoch [758/4000] Training [9/16] Loss: 0.01568 +Epoch [758/4000] Training [10/16] Loss: 0.01241 +Epoch [758/4000] Training [11/16] Loss: 0.01130 +Epoch [758/4000] Training [12/16] Loss: 0.01038 +Epoch [758/4000] Training [13/16] Loss: 0.01030 +Epoch [758/4000] Training [14/16] Loss: 0.01170 +Epoch [758/4000] Training [15/16] Loss: 0.01469 +Epoch [758/4000] Training [16/16] Loss: 0.01567 +Epoch [758/4000] Training metric {'Train/mean dice_metric': 0.9910567998886108, 'Train/mean miou_metric': 0.9820550680160522, 'Train/mean f1': 0.9874957203865051, 'Train/mean precision': 0.9831662178039551, 'Train/mean recall': 0.9918636679649353, 'Train/mean hd95_metric': 1.2391552925109863} +Epoch [758/4000] Validation [1/4] Loss: 0.47535 focal_loss 0.35019 dice_loss 0.12515 +Epoch [758/4000] Validation [2/4] Loss: 0.23719 focal_loss 0.10710 dice_loss 0.13009 +Epoch [758/4000] Validation [3/4] Loss: 0.19439 focal_loss 0.10732 dice_loss 0.08706 +Epoch [758/4000] Validation [4/4] Loss: 0.25771 focal_loss 0.12800 dice_loss 0.12971 +Epoch [758/4000] Validation metric {'Val/mean dice_metric': 0.966341495513916, 'Val/mean miou_metric': 0.9453401565551758, 'Val/mean f1': 0.9664077162742615, 'Val/mean precision': 0.9635576009750366, 'Val/mean recall': 0.9692746996879578, 'Val/mean hd95_metric': 5.839846611022949} +Cheakpoint... +Epoch [758/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966341495513916, 'Val/mean miou_metric': 0.9453401565551758, 'Val/mean f1': 0.9664077162742615, 'Val/mean precision': 0.9635576009750366, 'Val/mean recall': 0.9692746996879578, 'Val/mean hd95_metric': 5.839846611022949} +Epoch [759/4000] Training [1/16] Loss: 0.01027 +Epoch [759/4000] Training [2/16] Loss: 0.01206 +Epoch [759/4000] Training [3/16] Loss: 0.01474 +Epoch [759/4000] Training [4/16] Loss: 0.01036 +Epoch [759/4000] Training [5/16] Loss: 0.01503 +Epoch [759/4000] Training [6/16] Loss: 0.00883 +Epoch [759/4000] Training [7/16] Loss: 0.01065 +Epoch [759/4000] Training [8/16] Loss: 0.01135 +Epoch [759/4000] Training [9/16] Loss: 0.01256 +Epoch [759/4000] Training [10/16] Loss: 0.01236 +Epoch [759/4000] Training [11/16] Loss: 0.01205 +Epoch [759/4000] Training [12/16] Loss: 0.01026 +Epoch [759/4000] Training [13/16] Loss: 0.01284 +Epoch [759/4000] Training [14/16] Loss: 0.01450 +Epoch [759/4000] Training [15/16] Loss: 0.02102 +Epoch [759/4000] Training [16/16] Loss: 0.01082 +Epoch [759/4000] Training metric {'Train/mean dice_metric': 0.9912718534469604, 'Train/mean miou_metric': 0.9826365113258362, 'Train/mean f1': 0.9883317947387695, 'Train/mean precision': 0.9837632179260254, 'Train/mean recall': 0.9929430484771729, 'Train/mean hd95_metric': 1.2555149793624878} +Epoch [759/4000] Validation [1/4] Loss: 0.30396 focal_loss 0.20144 dice_loss 0.10252 +Epoch [759/4000] Validation [2/4] Loss: 0.24057 focal_loss 0.11906 dice_loss 0.12152 +Epoch [759/4000] Validation [3/4] Loss: 0.18441 focal_loss 0.09053 dice_loss 0.09388 +Epoch [759/4000] Validation [4/4] Loss: 0.23083 focal_loss 0.12831 dice_loss 0.10252 +Epoch [759/4000] Validation metric {'Val/mean dice_metric': 0.9667884707450867, 'Val/mean miou_metric': 0.9465212821960449, 'Val/mean f1': 0.9685837626457214, 'Val/mean precision': 0.9653035402297974, 'Val/mean recall': 0.9718863368034363, 'Val/mean hd95_metric': 6.892027378082275} +Cheakpoint... +Epoch [759/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667884707450867, 'Val/mean miou_metric': 0.9465212821960449, 'Val/mean f1': 0.9685837626457214, 'Val/mean precision': 0.9653035402297974, 'Val/mean recall': 0.9718863368034363, 'Val/mean hd95_metric': 6.892027378082275} +Epoch [760/4000] Training [1/16] Loss: 0.01035 +Epoch [760/4000] Training [2/16] Loss: 0.01275 +Epoch [760/4000] Training [3/16] Loss: 0.01061 +Epoch [760/4000] Training [4/16] Loss: 0.01648 +Epoch [760/4000] Training [5/16] Loss: 0.01281 +Epoch [760/4000] Training [6/16] Loss: 0.01509 +Epoch [760/4000] Training [7/16] Loss: 0.01437 +Epoch [760/4000] Training [8/16] Loss: 0.01111 +Epoch [760/4000] Training [9/16] Loss: 0.01256 +Epoch [760/4000] Training [10/16] Loss: 0.01652 +Epoch [760/4000] Training [11/16] Loss: 0.01166 +Epoch [760/4000] Training [12/16] Loss: 0.01246 +Epoch [760/4000] Training [13/16] Loss: 0.01069 +Epoch [760/4000] Training [14/16] Loss: 0.01384 +Epoch [760/4000] Training [15/16] Loss: 0.00998 +Epoch [760/4000] Training [16/16] Loss: 0.01462 +Epoch [760/4000] Training metric {'Train/mean dice_metric': 0.991096019744873, 'Train/mean miou_metric': 0.9821187853813171, 'Train/mean f1': 0.9870965480804443, 'Train/mean precision': 0.9822119474411011, 'Train/mean recall': 0.9920300245285034, 'Train/mean hd95_metric': 1.379238486289978} +Epoch [760/4000] Validation [1/4] Loss: 0.14378 focal_loss 0.08273 dice_loss 0.06104 +Epoch [760/4000] Validation [2/4] Loss: 0.18978 focal_loss 0.07915 dice_loss 0.11062 +Epoch [760/4000] Validation [3/4] Loss: 0.15200 focal_loss 0.08444 dice_loss 0.06756 +Epoch [760/4000] Validation [4/4] Loss: 0.24910 focal_loss 0.10876 dice_loss 0.14034 +Epoch [760/4000] Validation metric {'Val/mean dice_metric': 0.9675396680831909, 'Val/mean miou_metric': 0.947517991065979, 'Val/mean f1': 0.9696998596191406, 'Val/mean precision': 0.9617602825164795, 'Val/mean recall': 0.9777714610099792, 'Val/mean hd95_metric': 6.681427001953125} +Cheakpoint... +Epoch [760/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675396680831909, 'Val/mean miou_metric': 0.947517991065979, 'Val/mean f1': 0.9696998596191406, 'Val/mean precision': 0.9617602825164795, 'Val/mean recall': 0.9777714610099792, 'Val/mean hd95_metric': 6.681427001953125} +Epoch [761/4000] Training [1/16] Loss: 0.01393 +Epoch [761/4000] Training [2/16] Loss: 0.01658 +Epoch [761/4000] Training [3/16] Loss: 0.01607 +Epoch [761/4000] Training [4/16] Loss: 0.01164 +Epoch [761/4000] Training [5/16] Loss: 0.01466 +Epoch [761/4000] Training [6/16] Loss: 0.01132 +Epoch [761/4000] Training [7/16] Loss: 0.01216 +Epoch [761/4000] Training [8/16] Loss: 0.01202 +Epoch [761/4000] Training [9/16] Loss: 0.01196 +Epoch [761/4000] Training [10/16] Loss: 0.01146 +Epoch [761/4000] Training [11/16] Loss: 0.01221 +Epoch [761/4000] Training [12/16] Loss: 0.01268 +Epoch [761/4000] Training [13/16] Loss: 0.01469 +Epoch [761/4000] Training [14/16] Loss: 0.00897 +Epoch [761/4000] Training [15/16] Loss: 0.15718 +Epoch [761/4000] Training [16/16] Loss: 0.01722 +Epoch [761/4000] Training metric {'Train/mean dice_metric': 0.9893350601196289, 'Train/mean miou_metric': 0.9799772500991821, 'Train/mean f1': 0.9868226051330566, 'Train/mean precision': 0.9816076755523682, 'Train/mean recall': 0.9920932650566101, 'Train/mean hd95_metric': 1.8316117525100708} +Epoch [761/4000] Validation [1/4] Loss: 0.45049 focal_loss 0.33055 dice_loss 0.11994 +Epoch [761/4000] Validation [2/4] Loss: 0.32374 focal_loss 0.13865 dice_loss 0.18509 +Epoch [761/4000] Validation [3/4] Loss: 0.14111 focal_loss 0.07115 dice_loss 0.06996 +Epoch [761/4000] Validation [4/4] Loss: 0.27507 focal_loss 0.12357 dice_loss 0.15150 +Epoch [761/4000] Validation metric {'Val/mean dice_metric': 0.9639374613761902, 'Val/mean miou_metric': 0.9433431625366211, 'Val/mean f1': 0.9678041934967041, 'Val/mean precision': 0.96429443359375, 'Val/mean recall': 0.9713395833969116, 'Val/mean hd95_metric': 6.349733352661133} +Cheakpoint... +Epoch [761/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639374613761902, 'Val/mean miou_metric': 0.9433431625366211, 'Val/mean f1': 0.9678041934967041, 'Val/mean precision': 0.96429443359375, 'Val/mean recall': 0.9713395833969116, 'Val/mean hd95_metric': 6.349733352661133} +Epoch [762/4000] Training [1/16] Loss: 0.02917 +Epoch [762/4000] Training [2/16] Loss: 0.01245 +Epoch [762/4000] Training [3/16] Loss: 0.01238 +Epoch [762/4000] Training [4/16] Loss: 0.00976 +Epoch [762/4000] Training [5/16] Loss: 0.01121 +Epoch [762/4000] Training [6/16] Loss: 0.01264 +Epoch [762/4000] Training [7/16] Loss: 0.01978 +Epoch [762/4000] Training [8/16] Loss: 0.01432 +Epoch [762/4000] Training [9/16] Loss: 0.01290 +Epoch [762/4000] Training [10/16] Loss: 0.01180 +Epoch [762/4000] Training [11/16] Loss: 0.01058 +Epoch [762/4000] Training [12/16] Loss: 0.01293 +Epoch [762/4000] Training [13/16] Loss: 0.01308 +Epoch [762/4000] Training [14/16] Loss: 0.01531 +Epoch [762/4000] Training [15/16] Loss: 0.02026 +Epoch [762/4000] Training [16/16] Loss: 0.02167 +Epoch [762/4000] Training metric {'Train/mean dice_metric': 0.989834189414978, 'Train/mean miou_metric': 0.979763388633728, 'Train/mean f1': 0.9861038327217102, 'Train/mean precision': 0.9809049963951111, 'Train/mean recall': 0.9913581609725952, 'Train/mean hd95_metric': 1.4636247158050537} +Epoch [762/4000] Validation [1/4] Loss: 0.65554 focal_loss 0.48804 dice_loss 0.16750 +Epoch [762/4000] Validation [2/4] Loss: 0.42887 focal_loss 0.21680 dice_loss 0.21207 +Epoch [762/4000] Validation [3/4] Loss: 0.11861 focal_loss 0.06361 dice_loss 0.05500 +Epoch [762/4000] Validation [4/4] Loss: 0.22770 focal_loss 0.10396 dice_loss 0.12374 +Epoch [762/4000] Validation metric {'Val/mean dice_metric': 0.9623958468437195, 'Val/mean miou_metric': 0.9416939616203308, 'Val/mean f1': 0.9656522870063782, 'Val/mean precision': 0.9691991209983826, 'Val/mean recall': 0.9621313810348511, 'Val/mean hd95_metric': 6.103490352630615} +Cheakpoint... +Epoch [762/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9624], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9623958468437195, 'Val/mean miou_metric': 0.9416939616203308, 'Val/mean f1': 0.9656522870063782, 'Val/mean precision': 0.9691991209983826, 'Val/mean recall': 0.9621313810348511, 'Val/mean hd95_metric': 6.103490352630615} +Epoch [763/4000] Training [1/16] Loss: 0.01395 +Epoch [763/4000] Training [2/16] Loss: 0.01662 +Epoch [763/4000] Training [3/16] Loss: 0.02947 +Epoch [763/4000] Training [4/16] Loss: 0.01682 +Epoch [763/4000] Training [5/16] Loss: 0.01005 +Epoch [763/4000] Training [6/16] Loss: 0.01493 +Epoch [763/4000] Training [7/16] Loss: 0.01501 +Epoch [763/4000] Training [8/16] Loss: 0.01555 +Epoch [763/4000] Training [9/16] Loss: 0.02196 +Epoch [763/4000] Training [10/16] Loss: 0.01542 +Epoch [763/4000] Training [11/16] Loss: 0.01351 +Epoch [763/4000] Training [12/16] Loss: 0.02695 +Epoch [763/4000] Training [13/16] Loss: 0.01389 +Epoch [763/4000] Training [14/16] Loss: 0.02047 +Epoch [763/4000] Training [15/16] Loss: 0.01388 +Epoch [763/4000] Training [16/16] Loss: 0.01192 +Epoch [763/4000] Training metric {'Train/mean dice_metric': 0.9880839586257935, 'Train/mean miou_metric': 0.9766270518302917, 'Train/mean f1': 0.9855291247367859, 'Train/mean precision': 0.9812362194061279, 'Train/mean recall': 0.9898597598075867, 'Train/mean hd95_metric': 1.6678285598754883} +Epoch [763/4000] Validation [1/4] Loss: 0.22008 focal_loss 0.14351 dice_loss 0.07658 +Epoch [763/4000] Validation [2/4] Loss: 0.29408 focal_loss 0.13496 dice_loss 0.15913 +Epoch [763/4000] Validation [3/4] Loss: 0.16436 focal_loss 0.08044 dice_loss 0.08392 +Epoch [763/4000] Validation [4/4] Loss: 0.24722 focal_loss 0.12239 dice_loss 0.12484 +Epoch [763/4000] Validation metric {'Val/mean dice_metric': 0.9634414911270142, 'Val/mean miou_metric': 0.9405773282051086, 'Val/mean f1': 0.9673639535903931, 'Val/mean precision': 0.9602296352386475, 'Val/mean recall': 0.974605143070221, 'Val/mean hd95_metric': 7.8342671394348145} +Cheakpoint... +Epoch [763/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9634414911270142, 'Val/mean miou_metric': 0.9405773282051086, 'Val/mean f1': 0.9673639535903931, 'Val/mean precision': 0.9602296352386475, 'Val/mean recall': 0.974605143070221, 'Val/mean hd95_metric': 7.8342671394348145} +Epoch [764/4000] Training [1/16] Loss: 0.01353 +Epoch [764/4000] Training [2/16] Loss: 0.01196 +Epoch [764/4000] Training [3/16] Loss: 0.05618 +Epoch [764/4000] Training [4/16] Loss: 0.01511 +Epoch [764/4000] Training [5/16] Loss: 0.01516 +Epoch [764/4000] Training [6/16] Loss: 0.02204 +Epoch [764/4000] Training [7/16] Loss: 0.01454 +Epoch [764/4000] Training [8/16] Loss: 0.01796 +Epoch [764/4000] Training [9/16] Loss: 0.01785 +Epoch [764/4000] Training [10/16] Loss: 0.02342 +Epoch [764/4000] Training [11/16] Loss: 0.02174 +Epoch [764/4000] Training [12/16] Loss: 0.01560 +Epoch [764/4000] Training [13/16] Loss: 0.02075 +Epoch [764/4000] Training [14/16] Loss: 0.01207 +Epoch [764/4000] Training [15/16] Loss: 0.01659 +Epoch [764/4000] Training [16/16] Loss: 0.01414 +Epoch [764/4000] Training metric {'Train/mean dice_metric': 0.9879489541053772, 'Train/mean miou_metric': 0.9763051271438599, 'Train/mean f1': 0.9854487776756287, 'Train/mean precision': 0.9807899594306946, 'Train/mean recall': 0.9901520609855652, 'Train/mean hd95_metric': 2.408785820007324} +Epoch [764/4000] Validation [1/4] Loss: 0.42255 focal_loss 0.27469 dice_loss 0.14785 +Epoch [764/4000] Validation [2/4] Loss: 0.26250 focal_loss 0.10954 dice_loss 0.15296 +Epoch [764/4000] Validation [3/4] Loss: 0.15704 focal_loss 0.07880 dice_loss 0.07824 +Epoch [764/4000] Validation [4/4] Loss: 0.31525 focal_loss 0.17352 dice_loss 0.14173 +Epoch [764/4000] Validation metric {'Val/mean dice_metric': 0.9609676599502563, 'Val/mean miou_metric': 0.9377022981643677, 'Val/mean f1': 0.9654284715652466, 'Val/mean precision': 0.9667717814445496, 'Val/mean recall': 0.9640889167785645, 'Val/mean hd95_metric': 7.277975082397461} +Cheakpoint... +Epoch [764/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9610], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9609676599502563, 'Val/mean miou_metric': 0.9377022981643677, 'Val/mean f1': 0.9654284715652466, 'Val/mean precision': 0.9667717814445496, 'Val/mean recall': 0.9640889167785645, 'Val/mean hd95_metric': 7.277975082397461} +Epoch [765/4000] Training [1/16] Loss: 0.01245 +Epoch [765/4000] Training [2/16] Loss: 0.01337 +Epoch [765/4000] Training [3/16] Loss: 0.01361 +Epoch [765/4000] Training [4/16] Loss: 0.01130 +Epoch [765/4000] Training [5/16] Loss: 0.01107 +Epoch [765/4000] Training [6/16] Loss: 0.01180 +Epoch [765/4000] Training [7/16] Loss: 0.01347 +Epoch [765/4000] Training [8/16] Loss: 0.01652 +Epoch [765/4000] Training [9/16] Loss: 0.01315 +Epoch [765/4000] Training [10/16] Loss: 0.01138 +Epoch [765/4000] Training [11/16] Loss: 0.01119 +Epoch [765/4000] Training [12/16] Loss: 0.01231 +Epoch [765/4000] Training [13/16] Loss: 0.01236 +Epoch [765/4000] Training [14/16] Loss: 0.01535 +Epoch [765/4000] Training [15/16] Loss: 0.01500 +Epoch [765/4000] Training [16/16] Loss: 0.01786 +Epoch [765/4000] Training metric {'Train/mean dice_metric': 0.9900764226913452, 'Train/mean miou_metric': 0.9803018569946289, 'Train/mean f1': 0.9866907596588135, 'Train/mean precision': 0.9822331070899963, 'Train/mean recall': 0.9911891222000122, 'Train/mean hd95_metric': 1.8953169584274292} +Epoch [765/4000] Validation [1/4] Loss: 0.15079 focal_loss 0.08788 dice_loss 0.06291 +Epoch [765/4000] Validation [2/4] Loss: 0.35753 focal_loss 0.19293 dice_loss 0.16461 +Epoch [765/4000] Validation [3/4] Loss: 0.24742 focal_loss 0.14284 dice_loss 0.10459 +Epoch [765/4000] Validation [4/4] Loss: 0.33685 focal_loss 0.19833 dice_loss 0.13852 +Epoch [765/4000] Validation metric {'Val/mean dice_metric': 0.9653817415237427, 'Val/mean miou_metric': 0.9435924291610718, 'Val/mean f1': 0.9670459032058716, 'Val/mean precision': 0.9653041362762451, 'Val/mean recall': 0.9687938690185547, 'Val/mean hd95_metric': 6.3369646072387695} +Cheakpoint... +Epoch [765/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653817415237427, 'Val/mean miou_metric': 0.9435924291610718, 'Val/mean f1': 0.9670459032058716, 'Val/mean precision': 0.9653041362762451, 'Val/mean recall': 0.9687938690185547, 'Val/mean hd95_metric': 6.3369646072387695} +Epoch [766/4000] Training [1/16] Loss: 0.01500 +Epoch [766/4000] Training [2/16] Loss: 0.00987 +Epoch [766/4000] Training [3/16] Loss: 0.00960 +Epoch [766/4000] Training [4/16] Loss: 0.01447 +Epoch [766/4000] Training [5/16] Loss: 0.01207 +Epoch [766/4000] Training [6/16] Loss: 0.01650 +Epoch [766/4000] Training [7/16] Loss: 0.01082 +Epoch [766/4000] Training [8/16] Loss: 0.01032 +Epoch [766/4000] Training [9/16] Loss: 0.01355 +Epoch [766/4000] Training [10/16] Loss: 0.01119 +Epoch [766/4000] Training [11/16] Loss: 0.01352 +Epoch [766/4000] Training [12/16] Loss: 0.01926 +Epoch [766/4000] Training [13/16] Loss: 0.02173 +Epoch [766/4000] Training [14/16] Loss: 0.01296 +Epoch [766/4000] Training [15/16] Loss: 0.01325 +Epoch [766/4000] Training [16/16] Loss: 0.01188 +Epoch [766/4000] Training metric {'Train/mean dice_metric': 0.9902373552322388, 'Train/mean miou_metric': 0.9804550409317017, 'Train/mean f1': 0.9867520928382874, 'Train/mean precision': 0.982268214225769, 'Train/mean recall': 0.9912770390510559, 'Train/mean hd95_metric': 1.3301671743392944} +Epoch [766/4000] Validation [1/4] Loss: 0.46368 focal_loss 0.32663 dice_loss 0.13705 +Epoch [766/4000] Validation [2/4] Loss: 0.39034 focal_loss 0.20241 dice_loss 0.18793 +Epoch [766/4000] Validation [3/4] Loss: 0.11051 focal_loss 0.05422 dice_loss 0.05629 +Epoch [766/4000] Validation [4/4] Loss: 0.23757 focal_loss 0.11789 dice_loss 0.11967 +Epoch [766/4000] Validation metric {'Val/mean dice_metric': 0.964691162109375, 'Val/mean miou_metric': 0.9437295794487, 'Val/mean f1': 0.9671075940132141, 'Val/mean precision': 0.9698948264122009, 'Val/mean recall': 0.9643363356590271, 'Val/mean hd95_metric': 5.425232887268066} +Cheakpoint... +Epoch [766/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964691162109375, 'Val/mean miou_metric': 0.9437295794487, 'Val/mean f1': 0.9671075940132141, 'Val/mean precision': 0.9698948264122009, 'Val/mean recall': 0.9643363356590271, 'Val/mean hd95_metric': 5.425232887268066} +Epoch [767/4000] Training [1/16] Loss: 0.01173 +Epoch [767/4000] Training [2/16] Loss: 0.01051 +Epoch [767/4000] Training [3/16] Loss: 0.01215 +Epoch [767/4000] Training [4/16] Loss: 0.01281 +Epoch [767/4000] Training [5/16] Loss: 0.01042 +Epoch [767/4000] Training [6/16] Loss: 0.01320 +Epoch [767/4000] Training [7/16] Loss: 0.01384 +Epoch [767/4000] Training [8/16] Loss: 0.00985 +Epoch [767/4000] Training [9/16] Loss: 0.01379 +Epoch [767/4000] Training [10/16] Loss: 0.01443 +Epoch [767/4000] Training [11/16] Loss: 0.01519 +Epoch [767/4000] Training [12/16] Loss: 0.01104 +Epoch [767/4000] Training [13/16] Loss: 0.00959 +Epoch [767/4000] Training [14/16] Loss: 0.01089 +Epoch [767/4000] Training [15/16] Loss: 0.01339 +Epoch [767/4000] Training [16/16] Loss: 0.00921 +Epoch [767/4000] Training metric {'Train/mean dice_metric': 0.9909064769744873, 'Train/mean miou_metric': 0.9817889332771301, 'Train/mean f1': 0.987595796585083, 'Train/mean precision': 0.98280268907547, 'Train/mean recall': 0.992435872554779, 'Train/mean hd95_metric': 1.496131420135498} +Epoch [767/4000] Validation [1/4] Loss: 0.55642 focal_loss 0.42894 dice_loss 0.12748 +Epoch [767/4000] Validation [2/4] Loss: 0.24254 focal_loss 0.11595 dice_loss 0.12659 +Epoch [767/4000] Validation [3/4] Loss: 0.09975 focal_loss 0.05018 dice_loss 0.04957 +Epoch [767/4000] Validation [4/4] Loss: 0.20871 focal_loss 0.08662 dice_loss 0.12209 +Epoch [767/4000] Validation metric {'Val/mean dice_metric': 0.9674173593521118, 'Val/mean miou_metric': 0.9465460777282715, 'Val/mean f1': 0.9678098559379578, 'Val/mean precision': 0.9696938395500183, 'Val/mean recall': 0.965933084487915, 'Val/mean hd95_metric': 5.541621685028076} +Cheakpoint... +Epoch [767/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674173593521118, 'Val/mean miou_metric': 0.9465460777282715, 'Val/mean f1': 0.9678098559379578, 'Val/mean precision': 0.9696938395500183, 'Val/mean recall': 0.965933084487915, 'Val/mean hd95_metric': 5.541621685028076} +Epoch [768/4000] Training [1/16] Loss: 0.00963 +Epoch [768/4000] Training [2/16] Loss: 0.01277 +Epoch [768/4000] Training [3/16] Loss: 0.01366 +Epoch [768/4000] Training [4/16] Loss: 0.01517 +Epoch [768/4000] Training [5/16] Loss: 0.01401 +Epoch [768/4000] Training [6/16] Loss: 0.01392 +Epoch [768/4000] Training [7/16] Loss: 0.01162 +Epoch [768/4000] Training [8/16] Loss: 0.01561 +Epoch [768/4000] Training [9/16] Loss: 0.01229 +Epoch [768/4000] Training [10/16] Loss: 0.01283 +Epoch [768/4000] Training [11/16] Loss: 0.01215 +Epoch [768/4000] Training [12/16] Loss: 0.01283 +Epoch [768/4000] Training [13/16] Loss: 0.01016 +Epoch [768/4000] Training [14/16] Loss: 0.01428 +Epoch [768/4000] Training [15/16] Loss: 0.01169 +Epoch [768/4000] Training [16/16] Loss: 0.01030 +Epoch [768/4000] Training metric {'Train/mean dice_metric': 0.9908478260040283, 'Train/mean miou_metric': 0.981656014919281, 'Train/mean f1': 0.9873776435852051, 'Train/mean precision': 0.9825432300567627, 'Train/mean recall': 0.9922598600387573, 'Train/mean hd95_metric': 1.2886366844177246} +Epoch [768/4000] Validation [1/4] Loss: 0.53803 focal_loss 0.41689 dice_loss 0.12114 +Epoch [768/4000] Validation [2/4] Loss: 0.17947 focal_loss 0.07686 dice_loss 0.10261 +Epoch [768/4000] Validation [3/4] Loss: 0.10291 focal_loss 0.05376 dice_loss 0.04916 +Epoch [768/4000] Validation [4/4] Loss: 0.22984 focal_loss 0.11952 dice_loss 0.11032 +Epoch [768/4000] Validation metric {'Val/mean dice_metric': 0.9687032699584961, 'Val/mean miou_metric': 0.9481587409973145, 'Val/mean f1': 0.9689692258834839, 'Val/mean precision': 0.9685695767402649, 'Val/mean recall': 0.9693691730499268, 'Val/mean hd95_metric': 5.073433876037598} +Cheakpoint... +Epoch [768/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687032699584961, 'Val/mean miou_metric': 0.9481587409973145, 'Val/mean f1': 0.9689692258834839, 'Val/mean precision': 0.9685695767402649, 'Val/mean recall': 0.9693691730499268, 'Val/mean hd95_metric': 5.073433876037598} +Epoch [769/4000] Training [1/16] Loss: 0.01932 +Epoch [769/4000] Training [2/16] Loss: 0.01013 +Epoch [769/4000] Training [3/16] Loss: 0.02065 +Epoch [769/4000] Training [4/16] Loss: 0.01110 +Epoch [769/4000] Training [5/16] Loss: 0.00975 +Epoch [769/4000] Training [6/16] Loss: 0.01168 +Epoch [769/4000] Training [7/16] Loss: 0.01211 +Epoch [769/4000] Training [8/16] Loss: 0.01791 +Epoch [769/4000] Training [9/16] Loss: 0.01223 +Epoch [769/4000] Training [10/16] Loss: 0.01394 +Epoch [769/4000] Training [11/16] Loss: 0.01347 +Epoch [769/4000] Training [12/16] Loss: 0.01179 +Epoch [769/4000] Training [13/16] Loss: 0.01699 +Epoch [769/4000] Training [14/16] Loss: 0.01302 +Epoch [769/4000] Training [15/16] Loss: 0.01322 +Epoch [769/4000] Training [16/16] Loss: 0.01034 +Epoch [769/4000] Training metric {'Train/mean dice_metric': 0.9894152879714966, 'Train/mean miou_metric': 0.9795511364936829, 'Train/mean f1': 0.9876947402954102, 'Train/mean precision': 0.9829968214035034, 'Train/mean recall': 0.9924377202987671, 'Train/mean hd95_metric': 1.451215147972107} +Epoch [769/4000] Validation [1/4] Loss: 0.43116 focal_loss 0.30988 dice_loss 0.12128 +Epoch [769/4000] Validation [2/4] Loss: 0.42380 focal_loss 0.22698 dice_loss 0.19682 +Epoch [769/4000] Validation [3/4] Loss: 0.11820 focal_loss 0.05843 dice_loss 0.05976 +Epoch [769/4000] Validation [4/4] Loss: 0.17058 focal_loss 0.07317 dice_loss 0.09741 +Epoch [769/4000] Validation metric {'Val/mean dice_metric': 0.963771641254425, 'Val/mean miou_metric': 0.9433625936508179, 'Val/mean f1': 0.9682711362838745, 'Val/mean precision': 0.9683682918548584, 'Val/mean recall': 0.9681740999221802, 'Val/mean hd95_metric': 6.578097343444824} +Cheakpoint... +Epoch [769/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9638], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963771641254425, 'Val/mean miou_metric': 0.9433625936508179, 'Val/mean f1': 0.9682711362838745, 'Val/mean precision': 0.9683682918548584, 'Val/mean recall': 0.9681740999221802, 'Val/mean hd95_metric': 6.578097343444824} +Epoch [770/4000] Training [1/16] Loss: 0.01995 +Epoch [770/4000] Training [2/16] Loss: 0.01362 +Epoch [770/4000] Training [3/16] Loss: 0.04060 +Epoch [770/4000] Training [4/16] Loss: 0.01432 +Epoch [770/4000] Training [5/16] Loss: 0.01044 +Epoch [770/4000] Training [6/16] Loss: 0.01029 +Epoch [770/4000] Training [7/16] Loss: 0.01615 +Epoch [770/4000] Training [8/16] Loss: 0.01143 +Epoch [770/4000] Training [9/16] Loss: 0.01343 +Epoch [770/4000] Training [10/16] Loss: 0.01415 +Epoch [770/4000] Training [11/16] Loss: 0.01363 +Epoch [770/4000] Training [12/16] Loss: 0.01681 +Epoch [770/4000] Training [13/16] Loss: 0.01174 +Epoch [770/4000] Training [14/16] Loss: 0.01184 +Epoch [770/4000] Training [15/16] Loss: 0.01663 +Epoch [770/4000] Training [16/16] Loss: 0.01391 +Epoch [770/4000] Training metric {'Train/mean dice_metric': 0.990318775177002, 'Train/mean miou_metric': 0.9806588292121887, 'Train/mean f1': 0.9874340891838074, 'Train/mean precision': 0.982911229133606, 'Train/mean recall': 0.9919987916946411, 'Train/mean hd95_metric': 1.6299216747283936} +Epoch [770/4000] Validation [1/4] Loss: 0.35685 focal_loss 0.22521 dice_loss 0.13164 +Epoch [770/4000] Validation [2/4] Loss: 0.56872 focal_loss 0.28519 dice_loss 0.28353 +Epoch [770/4000] Validation [3/4] Loss: 0.13545 focal_loss 0.07362 dice_loss 0.06184 +Epoch [770/4000] Validation [4/4] Loss: 0.28442 focal_loss 0.16709 dice_loss 0.11733 +Epoch [770/4000] Validation metric {'Val/mean dice_metric': 0.9625529050827026, 'Val/mean miou_metric': 0.9415903091430664, 'Val/mean f1': 0.9658430814743042, 'Val/mean precision': 0.96840900182724, 'Val/mean recall': 0.9632907509803772, 'Val/mean hd95_metric': 6.420904636383057} +Cheakpoint... +Epoch [770/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9626], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625529050827026, 'Val/mean miou_metric': 0.9415903091430664, 'Val/mean f1': 0.9658430814743042, 'Val/mean precision': 0.96840900182724, 'Val/mean recall': 0.9632907509803772, 'Val/mean hd95_metric': 6.420904636383057} +Epoch [771/4000] Training [1/16] Loss: 0.01266 +Epoch [771/4000] Training [2/16] Loss: 0.01723 +Epoch [771/4000] Training [3/16] Loss: 0.01161 +Epoch [771/4000] Training [4/16] Loss: 0.01093 +Epoch [771/4000] Training [5/16] Loss: 0.01126 +Epoch [771/4000] Training [6/16] Loss: 0.01594 +Epoch [771/4000] Training [7/16] Loss: 0.01455 +Epoch [771/4000] Training [8/16] Loss: 0.01482 +Epoch [771/4000] Training [9/16] Loss: 0.01096 +Epoch [771/4000] Training [10/16] Loss: 0.01560 +Epoch [771/4000] Training [11/16] Loss: 0.01236 +Epoch [771/4000] Training [12/16] Loss: 0.01834 +Epoch [771/4000] Training [13/16] Loss: 0.01188 +Epoch [771/4000] Training [14/16] Loss: 0.01614 +Epoch [771/4000] Training [15/16] Loss: 0.03353 +Epoch [771/4000] Training [16/16] Loss: 0.01343 +Epoch [771/4000] Training metric {'Train/mean dice_metric': 0.99019855260849, 'Train/mean miou_metric': 0.9804073572158813, 'Train/mean f1': 0.9862609505653381, 'Train/mean precision': 0.9808579683303833, 'Train/mean recall': 0.9917237162590027, 'Train/mean hd95_metric': 1.3206555843353271} +Epoch [771/4000] Validation [1/4] Loss: 0.17725 focal_loss 0.10611 dice_loss 0.07114 +Epoch [771/4000] Validation [2/4] Loss: 0.26341 focal_loss 0.11534 dice_loss 0.14807 +Epoch [771/4000] Validation [3/4] Loss: 0.11297 focal_loss 0.06050 dice_loss 0.05247 +Epoch [771/4000] Validation [4/4] Loss: 0.35883 focal_loss 0.17076 dice_loss 0.18807 +Epoch [771/4000] Validation metric {'Val/mean dice_metric': 0.9676521420478821, 'Val/mean miou_metric': 0.9461606740951538, 'Val/mean f1': 0.9691168665885925, 'Val/mean precision': 0.9616573452949524, 'Val/mean recall': 0.9766930937767029, 'Val/mean hd95_metric': 6.9605913162231445} +Cheakpoint... +Epoch [771/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676521420478821, 'Val/mean miou_metric': 0.9461606740951538, 'Val/mean f1': 0.9691168665885925, 'Val/mean precision': 0.9616573452949524, 'Val/mean recall': 0.9766930937767029, 'Val/mean hd95_metric': 6.9605913162231445} +Epoch [772/4000] Training [1/16] Loss: 0.01287 +Epoch [772/4000] Training [2/16] Loss: 0.01350 +Epoch [772/4000] Training [3/16] Loss: 0.01595 +Epoch [772/4000] Training [4/16] Loss: 0.01348 +Epoch [772/4000] Training [5/16] Loss: 0.01230 +Epoch [772/4000] Training [6/16] Loss: 0.01437 +Epoch [772/4000] Training [7/16] Loss: 0.01180 +Epoch [772/4000] Training [8/16] Loss: 0.02913 +Epoch [772/4000] Training [9/16] Loss: 0.01277 +Epoch [772/4000] Training [10/16] Loss: 0.01644 +Epoch [772/4000] Training [11/16] Loss: 0.01110 +Epoch [772/4000] Training [12/16] Loss: 0.01903 +Epoch [772/4000] Training [13/16] Loss: 0.01284 +Epoch [772/4000] Training [14/16] Loss: 0.01162 +Epoch [772/4000] Training [15/16] Loss: 0.02128 +Epoch [772/4000] Training [16/16] Loss: 0.01159 +Epoch [772/4000] Training metric {'Train/mean dice_metric': 0.9902706146240234, 'Train/mean miou_metric': 0.9806022644042969, 'Train/mean f1': 0.9875187873840332, 'Train/mean precision': 0.9832455515861511, 'Train/mean recall': 0.9918294548988342, 'Train/mean hd95_metric': 1.7109055519104004} +Epoch [772/4000] Validation [1/4] Loss: 0.19043 focal_loss 0.11565 dice_loss 0.07478 +Epoch [772/4000] Validation [2/4] Loss: 0.19681 focal_loss 0.08301 dice_loss 0.11380 +Epoch [772/4000] Validation [3/4] Loss: 0.13939 focal_loss 0.07142 dice_loss 0.06797 +Epoch [772/4000] Validation [4/4] Loss: 0.27388 focal_loss 0.15300 dice_loss 0.12088 +Epoch [772/4000] Validation metric {'Val/mean dice_metric': 0.9692503809928894, 'Val/mean miou_metric': 0.9481328129768372, 'Val/mean f1': 0.9711368680000305, 'Val/mean precision': 0.9696751236915588, 'Val/mean recall': 0.9726029634475708, 'Val/mean hd95_metric': 5.687676429748535} +Cheakpoint... +Epoch [772/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692503809928894, 'Val/mean miou_metric': 0.9481328129768372, 'Val/mean f1': 0.9711368680000305, 'Val/mean precision': 0.9696751236915588, 'Val/mean recall': 0.9726029634475708, 'Val/mean hd95_metric': 5.687676429748535} +Epoch [773/4000] Training [1/16] Loss: 0.01009 +Epoch [773/4000] Training [2/16] Loss: 0.01591 +Epoch [773/4000] Training [3/16] Loss: 0.01458 +Epoch [773/4000] Training [4/16] Loss: 0.01439 +Epoch [773/4000] Training [5/16] Loss: 0.01054 +Epoch [773/4000] Training [6/16] Loss: 0.01483 +Epoch [773/4000] Training [7/16] Loss: 0.01237 +Epoch [773/4000] Training [8/16] Loss: 0.01089 +Epoch [773/4000] Training [9/16] Loss: 0.01485 +Epoch [773/4000] Training [10/16] Loss: 0.01086 +Epoch [773/4000] Training [11/16] Loss: 0.01431 +Epoch [773/4000] Training [12/16] Loss: 0.01923 +Epoch [773/4000] Training [13/16] Loss: 0.01430 +Epoch [773/4000] Training [14/16] Loss: 0.00985 +Epoch [773/4000] Training [15/16] Loss: 0.01175 +Epoch [773/4000] Training [16/16] Loss: 0.01098 +Epoch [773/4000] Training metric {'Train/mean dice_metric': 0.9908022880554199, 'Train/mean miou_metric': 0.9815645217895508, 'Train/mean f1': 0.9877665042877197, 'Train/mean precision': 0.9830925464630127, 'Train/mean recall': 0.9924850463867188, 'Train/mean hd95_metric': 1.3116271495819092} +Epoch [773/4000] Validation [1/4] Loss: 0.16955 focal_loss 0.10362 dice_loss 0.06592 +Epoch [773/4000] Validation [2/4] Loss: 0.33704 focal_loss 0.18119 dice_loss 0.15585 +Epoch [773/4000] Validation [3/4] Loss: 0.09880 focal_loss 0.05092 dice_loss 0.04788 +Epoch [773/4000] Validation [4/4] Loss: 0.24749 focal_loss 0.12763 dice_loss 0.11986 +Epoch [773/4000] Validation metric {'Val/mean dice_metric': 0.9686411023139954, 'Val/mean miou_metric': 0.9478940963745117, 'Val/mean f1': 0.9707126021385193, 'Val/mean precision': 0.9684805274009705, 'Val/mean recall': 0.9729551076889038, 'Val/mean hd95_metric': 5.792996883392334} +Cheakpoint... +Epoch [773/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686411023139954, 'Val/mean miou_metric': 0.9478940963745117, 'Val/mean f1': 0.9707126021385193, 'Val/mean precision': 0.9684805274009705, 'Val/mean recall': 0.9729551076889038, 'Val/mean hd95_metric': 5.792996883392334} +Epoch [774/4000] Training [1/16] Loss: 0.01434 +Epoch [774/4000] Training [2/16] Loss: 0.01084 +Epoch [774/4000] Training [3/16] Loss: 0.01142 +Epoch [774/4000] Training [4/16] Loss: 0.01114 +Epoch [774/4000] Training [5/16] Loss: 0.01363 +Epoch [774/4000] Training [6/16] Loss: 0.00942 +Epoch [774/4000] Training [7/16] Loss: 0.01488 +Epoch [774/4000] Training [8/16] Loss: 0.01149 +Epoch [774/4000] Training [9/16] Loss: 0.01437 +Epoch [774/4000] Training [10/16] Loss: 0.01532 +Epoch [774/4000] Training [11/16] Loss: 0.01192 +Epoch [774/4000] Training [12/16] Loss: 0.01168 +Epoch [774/4000] Training [13/16] Loss: 0.01321 +Epoch [774/4000] Training [14/16] Loss: 0.01302 +Epoch [774/4000] Training [15/16] Loss: 0.01935 +Epoch [774/4000] Training [16/16] Loss: 0.01210 +Epoch [774/4000] Training metric {'Train/mean dice_metric': 0.9908099174499512, 'Train/mean miou_metric': 0.9815791249275208, 'Train/mean f1': 0.9871842861175537, 'Train/mean precision': 0.9821748733520508, 'Train/mean recall': 0.992245078086853, 'Train/mean hd95_metric': 1.2867709398269653} +Epoch [774/4000] Validation [1/4] Loss: 0.46262 focal_loss 0.35221 dice_loss 0.11041 +Epoch [774/4000] Validation [2/4] Loss: 0.18066 focal_loss 0.07645 dice_loss 0.10421 +Epoch [774/4000] Validation [3/4] Loss: 0.14510 focal_loss 0.07738 dice_loss 0.06772 +Epoch [774/4000] Validation [4/4] Loss: 0.28689 focal_loss 0.15597 dice_loss 0.13092 +Epoch [774/4000] Validation metric {'Val/mean dice_metric': 0.9672296643257141, 'Val/mean miou_metric': 0.9464067220687866, 'Val/mean f1': 0.9684581160545349, 'Val/mean precision': 0.9652713537216187, 'Val/mean recall': 0.9716658592224121, 'Val/mean hd95_metric': 6.006468296051025} +Cheakpoint... +Epoch [774/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672296643257141, 'Val/mean miou_metric': 0.9464067220687866, 'Val/mean f1': 0.9684581160545349, 'Val/mean precision': 0.9652713537216187, 'Val/mean recall': 0.9716658592224121, 'Val/mean hd95_metric': 6.006468296051025} +Epoch [775/4000] Training [1/16] Loss: 0.01164 +Epoch [775/4000] Training [2/16] Loss: 0.01018 +Epoch [775/4000] Training [3/16] Loss: 0.01316 +Epoch [775/4000] Training [4/16] Loss: 0.01430 +Epoch [775/4000] Training [5/16] Loss: 0.01375 +Epoch [775/4000] Training [6/16] Loss: 0.01323 +Epoch [775/4000] Training [7/16] Loss: 0.01169 +Epoch [775/4000] Training [8/16] Loss: 0.01391 +Epoch [775/4000] Training [9/16] Loss: 0.01890 +Epoch [775/4000] Training [10/16] Loss: 0.01026 +Epoch [775/4000] Training [11/16] Loss: 0.01219 +Epoch [775/4000] Training [12/16] Loss: 0.01385 +Epoch [775/4000] Training [13/16] Loss: 0.01954 +Epoch [775/4000] Training [14/16] Loss: 0.01975 +Epoch [775/4000] Training [15/16] Loss: 0.01284 +Epoch [775/4000] Training [16/16] Loss: 0.02261 +Epoch [775/4000] Training metric {'Train/mean dice_metric': 0.9884402751922607, 'Train/mean miou_metric': 0.9775668382644653, 'Train/mean f1': 0.9861470460891724, 'Train/mean precision': 0.9813244342803955, 'Train/mean recall': 0.99101722240448, 'Train/mean hd95_metric': 1.6220507621765137} +Epoch [775/4000] Validation [1/4] Loss: 0.46329 focal_loss 0.34952 dice_loss 0.11377 +Epoch [775/4000] Validation [2/4] Loss: 0.20800 focal_loss 0.10298 dice_loss 0.10502 +Epoch [775/4000] Validation [3/4] Loss: 0.16232 focal_loss 0.09710 dice_loss 0.06522 +Epoch [775/4000] Validation [4/4] Loss: 0.40004 focal_loss 0.24862 dice_loss 0.15142 +Epoch [775/4000] Validation metric {'Val/mean dice_metric': 0.9652820825576782, 'Val/mean miou_metric': 0.9427902102470398, 'Val/mean f1': 0.9666340351104736, 'Val/mean precision': 0.967074990272522, 'Val/mean recall': 0.9661933779716492, 'Val/mean hd95_metric': 6.685347080230713} +Cheakpoint... +Epoch [775/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652820825576782, 'Val/mean miou_metric': 0.9427902102470398, 'Val/mean f1': 0.9666340351104736, 'Val/mean precision': 0.967074990272522, 'Val/mean recall': 0.9661933779716492, 'Val/mean hd95_metric': 6.685347080230713} +Epoch [776/4000] Training [1/16] Loss: 0.01263 +Epoch [776/4000] Training [2/16] Loss: 0.01609 +Epoch [776/4000] Training [3/16] Loss: 0.01162 +Epoch [776/4000] Training [4/16] Loss: 0.01466 +Epoch [776/4000] Training [5/16] Loss: 0.01174 +Epoch [776/4000] Training [6/16] Loss: 0.01372 +Epoch [776/4000] Training [7/16] Loss: 0.01366 +Epoch [776/4000] Training [8/16] Loss: 0.01309 +Epoch [776/4000] Training [9/16] Loss: 0.01182 +Epoch [776/4000] Training [10/16] Loss: 0.01229 +Epoch [776/4000] Training [11/16] Loss: 0.01462 +Epoch [776/4000] Training [12/16] Loss: 0.01285 +Epoch [776/4000] Training [13/16] Loss: 0.01384 +Epoch [776/4000] Training [14/16] Loss: 0.01657 +Epoch [776/4000] Training [15/16] Loss: 0.01340 +Epoch [776/4000] Training [16/16] Loss: 0.02529 +Epoch [776/4000] Training metric {'Train/mean dice_metric': 0.9900619387626648, 'Train/mean miou_metric': 0.9801558256149292, 'Train/mean f1': 0.9872579574584961, 'Train/mean precision': 0.9828577041625977, 'Train/mean recall': 0.9916977882385254, 'Train/mean hd95_metric': 1.2682058811187744} +Epoch [776/4000] Validation [1/4] Loss: 0.43605 focal_loss 0.32465 dice_loss 0.11141 +Epoch [776/4000] Validation [2/4] Loss: 0.20944 focal_loss 0.08854 dice_loss 0.12090 +Epoch [776/4000] Validation [3/4] Loss: 0.16552 focal_loss 0.09869 dice_loss 0.06683 +Epoch [776/4000] Validation [4/4] Loss: 0.27851 focal_loss 0.13792 dice_loss 0.14060 +Epoch [776/4000] Validation metric {'Val/mean dice_metric': 0.9662917852401733, 'Val/mean miou_metric': 0.944815993309021, 'Val/mean f1': 0.966690719127655, 'Val/mean precision': 0.9637261033058167, 'Val/mean recall': 0.9696735739707947, 'Val/mean hd95_metric': 6.080423355102539} +Cheakpoint... +Epoch [776/4000] best acc:tensor([0.9695], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662917852401733, 'Val/mean miou_metric': 0.944815993309021, 'Val/mean f1': 0.966690719127655, 'Val/mean precision': 0.9637261033058167, 'Val/mean recall': 0.9696735739707947, 'Val/mean hd95_metric': 6.080423355102539} +Epoch [777/4000] Training [1/16] Loss: 0.01572 +Epoch [777/4000] Training [2/16] Loss: 0.00899 +Epoch [777/4000] Training [3/16] Loss: 0.01229 +Epoch [777/4000] Training [4/16] Loss: 0.01552 +Epoch [777/4000] Training [5/16] Loss: 0.01216 +Epoch [777/4000] Training [6/16] Loss: 0.01951 +Epoch [777/4000] Training [7/16] Loss: 0.01117 +Epoch [777/4000] Training [8/16] Loss: 0.01039 +Epoch [777/4000] Training [9/16] Loss: 0.01104 +Epoch [777/4000] Training [10/16] Loss: 0.01223 +Epoch [777/4000] Training [11/16] Loss: 0.01218 +Epoch [777/4000] Training [12/16] Loss: 0.01378 +Epoch [777/4000] Training [13/16] Loss: 0.01150 +Epoch [777/4000] Training [14/16] Loss: 0.01074 +Epoch [777/4000] Training [15/16] Loss: 0.01195 +Epoch [777/4000] Training [16/16] Loss: 0.02429 +Epoch [777/4000] Training metric {'Train/mean dice_metric': 0.9913146495819092, 'Train/mean miou_metric': 0.9825973510742188, 'Train/mean f1': 0.9879006743431091, 'Train/mean precision': 0.9833906888961792, 'Train/mean recall': 0.9924522042274475, 'Train/mean hd95_metric': 1.3579177856445312} +Epoch [777/4000] Validation [1/4] Loss: 0.16278 focal_loss 0.09309 dice_loss 0.06968 +Epoch [777/4000] Validation [2/4] Loss: 0.30993 focal_loss 0.16233 dice_loss 0.14760 +Epoch [777/4000] Validation [3/4] Loss: 0.10910 focal_loss 0.05340 dice_loss 0.05570 +Epoch [777/4000] Validation [4/4] Loss: 0.28169 focal_loss 0.14861 dice_loss 0.13308 +Epoch [777/4000] Validation metric {'Val/mean dice_metric': 0.9702857732772827, 'Val/mean miou_metric': 0.949735164642334, 'Val/mean f1': 0.9714943170547485, 'Val/mean precision': 0.9667809009552002, 'Val/mean recall': 0.976253867149353, 'Val/mean hd95_metric': 5.986682891845703} +Cheakpoint... +Epoch [777/4000] best acc:tensor([0.9703], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702857732772827, 'Val/mean miou_metric': 0.949735164642334, 'Val/mean f1': 0.9714943170547485, 'Val/mean precision': 0.9667809009552002, 'Val/mean recall': 0.976253867149353, 'Val/mean hd95_metric': 5.986682891845703} +Epoch [778/4000] Training [1/16] Loss: 0.01620 +Epoch [778/4000] Training [2/16] Loss: 0.01369 +Epoch [778/4000] Training [3/16] Loss: 0.01091 +Epoch [778/4000] Training [4/16] Loss: 0.01614 +Epoch [778/4000] Training [5/16] Loss: 0.01152 +Epoch [778/4000] Training [6/16] Loss: 0.01759 +Epoch [778/4000] Training [7/16] Loss: 0.01170 +Epoch [778/4000] Training [8/16] Loss: 0.01236 +Epoch [778/4000] Training [9/16] Loss: 0.01098 +Epoch [778/4000] Training [10/16] Loss: 0.06223 +Epoch [778/4000] Training [11/16] Loss: 0.01728 +Epoch [778/4000] Training [12/16] Loss: 0.01198 +Epoch [778/4000] Training [13/16] Loss: 0.01827 +Epoch [778/4000] Training [14/16] Loss: 0.01045 +Epoch [778/4000] Training [15/16] Loss: 0.01324 +Epoch [778/4000] Training [16/16] Loss: 0.01489 +Epoch [778/4000] Training metric {'Train/mean dice_metric': 0.9905353784561157, 'Train/mean miou_metric': 0.9811513423919678, 'Train/mean f1': 0.9871901273727417, 'Train/mean precision': 0.9822901487350464, 'Train/mean recall': 0.9921392202377319, 'Train/mean hd95_metric': 1.775985598564148} +Epoch [778/4000] Validation [1/4] Loss: 0.63194 focal_loss 0.45354 dice_loss 0.17840 +Epoch [778/4000] Validation [2/4] Loss: 0.48225 focal_loss 0.17563 dice_loss 0.30661 +Epoch [778/4000] Validation [3/4] Loss: 0.11446 focal_loss 0.05400 dice_loss 0.06047 +Epoch [778/4000] Validation [4/4] Loss: 0.20456 focal_loss 0.06613 dice_loss 0.13843 +Epoch [778/4000] Validation metric {'Val/mean dice_metric': 0.9576148986816406, 'Val/mean miou_metric': 0.9375015497207642, 'Val/mean f1': 0.9659609794616699, 'Val/mean precision': 0.9670880436897278, 'Val/mean recall': 0.9648365378379822, 'Val/mean hd95_metric': 6.322318077087402} +Cheakpoint... +Epoch [778/4000] best acc:tensor([0.9703], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9576148986816406, 'Val/mean miou_metric': 0.9375015497207642, 'Val/mean f1': 0.9659609794616699, 'Val/mean precision': 0.9670880436897278, 'Val/mean recall': 0.9648365378379822, 'Val/mean hd95_metric': 6.322318077087402} +Epoch [779/4000] Training [1/16] Loss: 0.01427 +Epoch [779/4000] Training [2/16] Loss: 0.01264 +Epoch [779/4000] Training [3/16] Loss: 0.01035 +Epoch [779/4000] Training [4/16] Loss: 0.01820 +Epoch [779/4000] Training [5/16] Loss: 0.01282 +Epoch [779/4000] Training [6/16] Loss: 0.01363 +Epoch [779/4000] Training [7/16] Loss: 0.01714 +Epoch [779/4000] Training [8/16] Loss: 0.01299 +Epoch [779/4000] Training [9/16] Loss: 0.01507 +Epoch [779/4000] Training [10/16] Loss: 0.02009 +Epoch [779/4000] Training [11/16] Loss: 0.01375 +Epoch [779/4000] Training [12/16] Loss: 0.01569 +Epoch [779/4000] Training [13/16] Loss: 0.01546 +Epoch [779/4000] Training [14/16] Loss: 0.01649 +Epoch [779/4000] Training [15/16] Loss: 0.01954 +Epoch [779/4000] Training [16/16] Loss: 0.01387 +Epoch [779/4000] Training metric {'Train/mean dice_metric': 0.9889720678329468, 'Train/mean miou_metric': 0.978230893611908, 'Train/mean f1': 0.9866217970848083, 'Train/mean precision': 0.9822136759757996, 'Train/mean recall': 0.9910696744918823, 'Train/mean hd95_metric': 1.6681766510009766} +Epoch [779/4000] Validation [1/4] Loss: 0.20240 focal_loss 0.13289 dice_loss 0.06951 +Epoch [779/4000] Validation [2/4] Loss: 0.22144 focal_loss 0.10595 dice_loss 0.11549 +Epoch [779/4000] Validation [3/4] Loss: 0.13527 focal_loss 0.06261 dice_loss 0.07266 +Epoch [779/4000] Validation [4/4] Loss: 0.31350 focal_loss 0.17435 dice_loss 0.13914 +Epoch [779/4000] Validation metric {'Val/mean dice_metric': 0.9680209159851074, 'Val/mean miou_metric': 0.9456275701522827, 'Val/mean f1': 0.9681368470191956, 'Val/mean precision': 0.9638298153877258, 'Val/mean recall': 0.972482442855835, 'Val/mean hd95_metric': 6.777262210845947} +Cheakpoint... +Epoch [779/4000] best acc:tensor([0.9703], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680209159851074, 'Val/mean miou_metric': 0.9456275701522827, 'Val/mean f1': 0.9681368470191956, 'Val/mean precision': 0.9638298153877258, 'Val/mean recall': 0.972482442855835, 'Val/mean hd95_metric': 6.777262210845947} +Epoch [780/4000] Training [1/16] Loss: 0.02040 +Epoch [780/4000] Training [2/16] Loss: 0.00836 +Epoch [780/4000] Training [3/16] Loss: 0.01124 +Epoch [780/4000] Training [4/16] Loss: 0.03415 +Epoch [780/4000] Training [5/16] Loss: 0.01817 +Epoch [780/4000] Training [6/16] Loss: 0.01077 +Epoch [780/4000] Training [7/16] Loss: 0.01461 +Epoch [780/4000] Training [8/16] Loss: 0.01574 +Epoch [780/4000] Training [9/16] Loss: 0.01359 +Epoch [780/4000] Training [10/16] Loss: 0.01676 +Epoch [780/4000] Training [11/16] Loss: 0.01192 +Epoch [780/4000] Training [12/16] Loss: 0.01508 +Epoch [780/4000] Training [13/16] Loss: 0.01300 +Epoch [780/4000] Training [14/16] Loss: 0.01404 +Epoch [780/4000] Training [15/16] Loss: 0.01382 +Epoch [780/4000] Training [16/16] Loss: 0.01573 +Epoch [780/4000] Training metric {'Train/mean dice_metric': 0.989300012588501, 'Train/mean miou_metric': 0.9787036180496216, 'Train/mean f1': 0.9862431883811951, 'Train/mean precision': 0.9819645285606384, 'Train/mean recall': 0.9905592799186707, 'Train/mean hd95_metric': 1.9811978340148926} +Epoch [780/4000] Validation [1/4] Loss: 0.13764 focal_loss 0.07751 dice_loss 0.06013 +Epoch [780/4000] Validation [2/4] Loss: 0.19940 focal_loss 0.09477 dice_loss 0.10463 +Epoch [780/4000] Validation [3/4] Loss: 0.14477 focal_loss 0.07492 dice_loss 0.06985 +Epoch [780/4000] Validation [4/4] Loss: 0.24824 focal_loss 0.12957 dice_loss 0.11867 +Epoch [780/4000] Validation metric {'Val/mean dice_metric': 0.9674053192138672, 'Val/mean miou_metric': 0.9452328681945801, 'Val/mean f1': 0.9683942198753357, 'Val/mean precision': 0.9639279842376709, 'Val/mean recall': 0.9729018807411194, 'Val/mean hd95_metric': 7.214465141296387} +Cheakpoint... +Epoch [780/4000] best acc:tensor([0.9703], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674053192138672, 'Val/mean miou_metric': 0.9452328681945801, 'Val/mean f1': 0.9683942198753357, 'Val/mean precision': 0.9639279842376709, 'Val/mean recall': 0.9729018807411194, 'Val/mean hd95_metric': 7.214465141296387} +Epoch [781/4000] Training [1/16] Loss: 0.01147 +Epoch [781/4000] Training [2/16] Loss: 0.01227 +Epoch [781/4000] Training [3/16] Loss: 0.01186 +Epoch [781/4000] Training [4/16] Loss: 0.01372 +Epoch [781/4000] Training [5/16] Loss: 0.02502 +Epoch [781/4000] Training [6/16] Loss: 0.01364 +Epoch [781/4000] Training [7/16] Loss: 0.01335 +Epoch [781/4000] Training [8/16] Loss: 0.01722 +Epoch [781/4000] Training [9/16] Loss: 0.01461 +Epoch [781/4000] Training [10/16] Loss: 0.01229 +Epoch [781/4000] Training [11/16] Loss: 0.01224 +Epoch [781/4000] Training [12/16] Loss: 0.01114 +Epoch [781/4000] Training [13/16] Loss: 0.01266 +Epoch [781/4000] Training [14/16] Loss: 0.01227 +Epoch [781/4000] Training [15/16] Loss: 0.01662 +Epoch [781/4000] Training [16/16] Loss: 0.01179 +Epoch [781/4000] Training metric {'Train/mean dice_metric': 0.9903665781021118, 'Train/mean miou_metric': 0.9807408452033997, 'Train/mean f1': 0.9872106313705444, 'Train/mean precision': 0.982127845287323, 'Train/mean recall': 0.9923462271690369, 'Train/mean hd95_metric': 1.2722680568695068} +Epoch [781/4000] Validation [1/4] Loss: 0.15569 focal_loss 0.08958 dice_loss 0.06611 +Epoch [781/4000] Validation [2/4] Loss: 0.17024 focal_loss 0.07872 dice_loss 0.09152 +Epoch [781/4000] Validation [3/4] Loss: 0.10624 focal_loss 0.05648 dice_loss 0.04976 +Epoch [781/4000] Validation [4/4] Loss: 0.33738 focal_loss 0.20950 dice_loss 0.12788 +Epoch [781/4000] Validation metric {'Val/mean dice_metric': 0.9686368703842163, 'Val/mean miou_metric': 0.9475356936454773, 'Val/mean f1': 0.9686933755874634, 'Val/mean precision': 0.9618558883666992, 'Val/mean recall': 0.9756289124488831, 'Val/mean hd95_metric': 6.290084362030029} +Cheakpoint... +Epoch [781/4000] best acc:tensor([0.9703], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686368703842163, 'Val/mean miou_metric': 0.9475356936454773, 'Val/mean f1': 0.9686933755874634, 'Val/mean precision': 0.9618558883666992, 'Val/mean recall': 0.9756289124488831, 'Val/mean hd95_metric': 6.290084362030029} +Epoch [782/4000] Training [1/16] Loss: 0.00970 +Epoch [782/4000] Training [2/16] Loss: 0.01300 +Epoch [782/4000] Training [3/16] Loss: 0.01931 +Epoch [782/4000] Training [4/16] Loss: 0.01219 +Epoch [782/4000] Training [5/16] Loss: 0.01252 +Epoch [782/4000] Training [6/16] Loss: 0.01103 +Epoch [782/4000] Training [7/16] Loss: 0.01231 +Epoch [782/4000] Training [8/16] Loss: 0.01351 +Epoch [782/4000] Training [9/16] Loss: 0.00966 +Epoch [782/4000] Training [10/16] Loss: 0.01244 +Epoch [782/4000] Training [11/16] Loss: 0.02837 +Epoch [782/4000] Training [12/16] Loss: 0.01729 +Epoch [782/4000] Training [13/16] Loss: 0.01085 +Epoch [782/4000] Training [14/16] Loss: 0.01290 +Epoch [782/4000] Training [15/16] Loss: 0.01212 +Epoch [782/4000] Training [16/16] Loss: 0.01819 +Epoch [782/4000] Training metric {'Train/mean dice_metric': 0.9909364581108093, 'Train/mean miou_metric': 0.9818676710128784, 'Train/mean f1': 0.9879469275474548, 'Train/mean precision': 0.9834328293800354, 'Train/mean recall': 0.9925026893615723, 'Train/mean hd95_metric': 1.2557189464569092} +Epoch [782/4000] Validation [1/4] Loss: 0.19186 focal_loss 0.12170 dice_loss 0.07016 +Epoch [782/4000] Validation [2/4] Loss: 0.18565 focal_loss 0.09444 dice_loss 0.09121 +Epoch [782/4000] Validation [3/4] Loss: 0.12244 focal_loss 0.06225 dice_loss 0.06018 +Epoch [782/4000] Validation [4/4] Loss: 0.27177 focal_loss 0.14656 dice_loss 0.12521 +Epoch [782/4000] Validation metric {'Val/mean dice_metric': 0.9687374234199524, 'Val/mean miou_metric': 0.9481500387191772, 'Val/mean f1': 0.970329761505127, 'Val/mean precision': 0.9631809592247009, 'Val/mean recall': 0.9775854349136353, 'Val/mean hd95_metric': 6.1592912673950195} +Cheakpoint... +Epoch [782/4000] best acc:tensor([0.9703], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687374234199524, 'Val/mean miou_metric': 0.9481500387191772, 'Val/mean f1': 0.970329761505127, 'Val/mean precision': 0.9631809592247009, 'Val/mean recall': 0.9775854349136353, 'Val/mean hd95_metric': 6.1592912673950195} +Epoch [783/4000] Training [1/16] Loss: 0.01004 +Epoch [783/4000] Training [2/16] Loss: 0.01131 +Epoch [783/4000] Training [3/16] Loss: 0.01279 +Epoch [783/4000] Training [4/16] Loss: 0.01426 +Epoch [783/4000] Training [5/16] Loss: 0.01689 +Epoch [783/4000] Training [6/16] Loss: 0.01291 +Epoch [783/4000] Training [7/16] Loss: 0.00924 +Epoch [783/4000] Training [8/16] Loss: 0.01553 +Epoch [783/4000] Training [9/16] Loss: 0.01523 +Epoch [783/4000] Training [10/16] Loss: 0.01252 +Epoch [783/4000] Training [11/16] Loss: 0.00852 +Epoch [783/4000] Training [12/16] Loss: 0.00997 +Epoch [783/4000] Training [13/16] Loss: 0.00949 +Epoch [783/4000] Training [14/16] Loss: 0.01373 +Epoch [783/4000] Training [15/16] Loss: 0.01211 +Epoch [783/4000] Training [16/16] Loss: 0.01107 +Epoch [783/4000] Training metric {'Train/mean dice_metric': 0.9914519786834717, 'Train/mean miou_metric': 0.9828516840934753, 'Train/mean f1': 0.988012969493866, 'Train/mean precision': 0.9835702180862427, 'Train/mean recall': 0.9924960732460022, 'Train/mean hd95_metric': 1.2279636859893799} +Epoch [783/4000] Validation [1/4] Loss: 0.19721 focal_loss 0.12774 dice_loss 0.06947 +Epoch [783/4000] Validation [2/4] Loss: 0.19047 focal_loss 0.09290 dice_loss 0.09757 +Epoch [783/4000] Validation [3/4] Loss: 0.12124 focal_loss 0.06337 dice_loss 0.05787 +Epoch [783/4000] Validation [4/4] Loss: 0.26252 focal_loss 0.14226 dice_loss 0.12026 +Epoch [783/4000] Validation metric {'Val/mean dice_metric': 0.9705508947372437, 'Val/mean miou_metric': 0.9508745074272156, 'Val/mean f1': 0.9707456231117249, 'Val/mean precision': 0.9648646712303162, 'Val/mean recall': 0.9766988754272461, 'Val/mean hd95_metric': 5.793848991394043} +Cheakpoint... +Epoch [783/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705508947372437, 'Val/mean miou_metric': 0.9508745074272156, 'Val/mean f1': 0.9707456231117249, 'Val/mean precision': 0.9648646712303162, 'Val/mean recall': 0.9766988754272461, 'Val/mean hd95_metric': 5.793848991394043} +Epoch [784/4000] Training [1/16] Loss: 0.00919 +Epoch [784/4000] Training [2/16] Loss: 0.01000 +Epoch [784/4000] Training [3/16] Loss: 0.01064 +Epoch [784/4000] Training [4/16] Loss: 0.01911 +Epoch [784/4000] Training [5/16] Loss: 0.00886 +Epoch [784/4000] Training [6/16] Loss: 0.01069 +Epoch [784/4000] Training [7/16] Loss: 0.01517 +Epoch [784/4000] Training [8/16] Loss: 0.01460 +Epoch [784/4000] Training [9/16] Loss: 0.01101 +Epoch [784/4000] Training [10/16] Loss: 0.01558 +Epoch [784/4000] Training [11/16] Loss: 0.01418 +Epoch [784/4000] Training [12/16] Loss: 0.01425 +Epoch [784/4000] Training [13/16] Loss: 0.01627 +Epoch [784/4000] Training [14/16] Loss: 0.01099 +Epoch [784/4000] Training [15/16] Loss: 0.01199 +Epoch [784/4000] Training [16/16] Loss: 0.01825 +Epoch [784/4000] Training metric {'Train/mean dice_metric': 0.9898163080215454, 'Train/mean miou_metric': 0.9807149171829224, 'Train/mean f1': 0.9857317805290222, 'Train/mean precision': 0.9818540215492249, 'Train/mean recall': 0.9896403551101685, 'Train/mean hd95_metric': 1.5985546112060547} +Epoch [784/4000] Validation [1/4] Loss: 0.17733 focal_loss 0.10821 dice_loss 0.06912 +Epoch [784/4000] Validation [2/4] Loss: 0.19273 focal_loss 0.09357 dice_loss 0.09916 +Epoch [784/4000] Validation [3/4] Loss: 0.13523 focal_loss 0.07945 dice_loss 0.05579 +Epoch [784/4000] Validation [4/4] Loss: 0.24230 focal_loss 0.11801 dice_loss 0.12429 +Epoch [784/4000] Validation metric {'Val/mean dice_metric': 0.9669401049613953, 'Val/mean miou_metric': 0.9462520480155945, 'Val/mean f1': 0.9673503041267395, 'Val/mean precision': 0.9626333117485046, 'Val/mean recall': 0.9721137881278992, 'Val/mean hd95_metric': 6.7003679275512695} +Cheakpoint... +Epoch [784/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669401049613953, 'Val/mean miou_metric': 0.9462520480155945, 'Val/mean f1': 0.9673503041267395, 'Val/mean precision': 0.9626333117485046, 'Val/mean recall': 0.9721137881278992, 'Val/mean hd95_metric': 6.7003679275512695} +Epoch [785/4000] Training [1/16] Loss: 0.01007 +Epoch [785/4000] Training [2/16] Loss: 0.01294 +Epoch [785/4000] Training [3/16] Loss: 0.01229 +Epoch [785/4000] Training [4/16] Loss: 0.01140 +Epoch [785/4000] Training [5/16] Loss: 0.01487 +Epoch [785/4000] Training [6/16] Loss: 0.01590 +Epoch [785/4000] Training [7/16] Loss: 0.01360 +Epoch [785/4000] Training [8/16] Loss: 0.01420 +Epoch [785/4000] Training [9/16] Loss: 0.01474 +Epoch [785/4000] Training [10/16] Loss: 0.01365 +Epoch [785/4000] Training [11/16] Loss: 0.01698 +Epoch [785/4000] Training [12/16] Loss: 0.01175 +Epoch [785/4000] Training [13/16] Loss: 0.01018 +Epoch [785/4000] Training [14/16] Loss: 0.01569 +Epoch [785/4000] Training [15/16] Loss: 0.01905 +Epoch [785/4000] Training [16/16] Loss: 0.01787 +Epoch [785/4000] Training metric {'Train/mean dice_metric': 0.9886747598648071, 'Train/mean miou_metric': 0.9785070419311523, 'Train/mean f1': 0.9854061007499695, 'Train/mean precision': 0.9796874523162842, 'Train/mean recall': 0.9911919236183167, 'Train/mean hd95_metric': 1.8117619752883911} +Epoch [785/4000] Validation [1/4] Loss: 0.16742 focal_loss 0.09777 dice_loss 0.06965 +Epoch [785/4000] Validation [2/4] Loss: 0.30587 focal_loss 0.13673 dice_loss 0.16913 +Epoch [785/4000] Validation [3/4] Loss: 0.15780 focal_loss 0.08887 dice_loss 0.06893 +Epoch [785/4000] Validation [4/4] Loss: 0.18535 focal_loss 0.07503 dice_loss 0.11032 +Epoch [785/4000] Validation metric {'Val/mean dice_metric': 0.9641435742378235, 'Val/mean miou_metric': 0.9417961239814758, 'Val/mean f1': 0.9658398032188416, 'Val/mean precision': 0.9624411463737488, 'Val/mean recall': 0.9692624807357788, 'Val/mean hd95_metric': 7.4398345947265625} +Cheakpoint... +Epoch [785/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9641435742378235, 'Val/mean miou_metric': 0.9417961239814758, 'Val/mean f1': 0.9658398032188416, 'Val/mean precision': 0.9624411463737488, 'Val/mean recall': 0.9692624807357788, 'Val/mean hd95_metric': 7.4398345947265625} +Epoch [786/4000] Training [1/16] Loss: 0.01301 +Epoch [786/4000] Training [2/16] Loss: 0.01295 +Epoch [786/4000] Training [3/16] Loss: 0.01169 +Epoch [786/4000] Training [4/16] Loss: 0.01268 +Epoch [786/4000] Training [5/16] Loss: 0.01241 +Epoch [786/4000] Training [6/16] Loss: 0.01384 +Epoch [786/4000] Training [7/16] Loss: 0.01221 +Epoch [786/4000] Training [8/16] Loss: 0.01213 +Epoch [786/4000] Training [9/16] Loss: 0.01286 +Epoch [786/4000] Training [10/16] Loss: 0.01324 +Epoch [786/4000] Training [11/16] Loss: 0.01156 +Epoch [786/4000] Training [12/16] Loss: 0.01734 +Epoch [786/4000] Training [13/16] Loss: 0.02293 +Epoch [786/4000] Training [14/16] Loss: 0.01107 +Epoch [786/4000] Training [15/16] Loss: 0.00974 +Epoch [786/4000] Training [16/16] Loss: 0.01218 +Epoch [786/4000] Training metric {'Train/mean dice_metric': 0.9908888339996338, 'Train/mean miou_metric': 0.9817089438438416, 'Train/mean f1': 0.9868082404136658, 'Train/mean precision': 0.9821143746376038, 'Train/mean recall': 0.991547167301178, 'Train/mean hd95_metric': 1.4650235176086426} +Epoch [786/4000] Validation [1/4] Loss: 0.15009 focal_loss 0.09475 dice_loss 0.05534 +Epoch [786/4000] Validation [2/4] Loss: 0.33903 focal_loss 0.17042 dice_loss 0.16862 +Epoch [786/4000] Validation [3/4] Loss: 0.15072 focal_loss 0.06602 dice_loss 0.08471 +Epoch [786/4000] Validation [4/4] Loss: 0.24877 focal_loss 0.11090 dice_loss 0.13787 +Epoch [786/4000] Validation metric {'Val/mean dice_metric': 0.9661611318588257, 'Val/mean miou_metric': 0.9457648992538452, 'Val/mean f1': 0.9669312238693237, 'Val/mean precision': 0.9580696821212769, 'Val/mean recall': 0.9759582281112671, 'Val/mean hd95_metric': 6.933631896972656} +Cheakpoint... +Epoch [786/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661611318588257, 'Val/mean miou_metric': 0.9457648992538452, 'Val/mean f1': 0.9669312238693237, 'Val/mean precision': 0.9580696821212769, 'Val/mean recall': 0.9759582281112671, 'Val/mean hd95_metric': 6.933631896972656} +Epoch [787/4000] Training [1/16] Loss: 0.01270 +Epoch [787/4000] Training [2/16] Loss: 0.01192 +Epoch [787/4000] Training [3/16] Loss: 0.01741 +Epoch [787/4000] Training [4/16] Loss: 0.00881 +Epoch [787/4000] Training [5/16] Loss: 0.01333 +Epoch [787/4000] Training [6/16] Loss: 0.01330 +Epoch [787/4000] Training [7/16] Loss: 0.01708 +Epoch [787/4000] Training [8/16] Loss: 0.01491 +Epoch [787/4000] Training [9/16] Loss: 0.01778 +Epoch [787/4000] Training [10/16] Loss: 0.01236 +Epoch [787/4000] Training [11/16] Loss: 0.01434 +Epoch [787/4000] Training [12/16] Loss: 0.01151 +Epoch [787/4000] Training [13/16] Loss: 0.01130 +Epoch [787/4000] Training [14/16] Loss: 0.01088 +Epoch [787/4000] Training [15/16] Loss: 0.01492 +Epoch [787/4000] Training [16/16] Loss: 0.01390 +Epoch [787/4000] Training metric {'Train/mean dice_metric': 0.9899618625640869, 'Train/mean miou_metric': 0.9801231026649475, 'Train/mean f1': 0.9873834848403931, 'Train/mean precision': 0.9829195141792297, 'Train/mean recall': 0.9918882250785828, 'Train/mean hd95_metric': 1.802796483039856} +Epoch [787/4000] Validation [1/4] Loss: 0.36888 focal_loss 0.26058 dice_loss 0.10830 +Epoch [787/4000] Validation [2/4] Loss: 0.40818 focal_loss 0.20657 dice_loss 0.20161 +Epoch [787/4000] Validation [3/4] Loss: 0.10959 focal_loss 0.05710 dice_loss 0.05249 +Epoch [787/4000] Validation [4/4] Loss: 0.21612 focal_loss 0.10275 dice_loss 0.11337 +Epoch [787/4000] Validation metric {'Val/mean dice_metric': 0.9657684564590454, 'Val/mean miou_metric': 0.943023681640625, 'Val/mean f1': 0.9652104377746582, 'Val/mean precision': 0.9673947095870972, 'Val/mean recall': 0.9630359411239624, 'Val/mean hd95_metric': 6.55224609375} +Cheakpoint... +Epoch [787/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9657684564590454, 'Val/mean miou_metric': 0.943023681640625, 'Val/mean f1': 0.9652104377746582, 'Val/mean precision': 0.9673947095870972, 'Val/mean recall': 0.9630359411239624, 'Val/mean hd95_metric': 6.55224609375} +Epoch [788/4000] Training [1/16] Loss: 0.01050 +Epoch [788/4000] Training [2/16] Loss: 0.01182 +Epoch [788/4000] Training [3/16] Loss: 0.01321 +Epoch [788/4000] Training [4/16] Loss: 0.01211 +Epoch [788/4000] Training [5/16] Loss: 0.02838 +Epoch [788/4000] Training [6/16] Loss: 0.01261 +Epoch [788/4000] Training [7/16] Loss: 0.01695 +Epoch [788/4000] Training [8/16] Loss: 0.02951 +Epoch [788/4000] Training [9/16] Loss: 0.01361 +Epoch [788/4000] Training [10/16] Loss: 0.01256 +Epoch [788/4000] Training [11/16] Loss: 0.01662 +Epoch [788/4000] Training [12/16] Loss: 0.01247 +Epoch [788/4000] Training [13/16] Loss: 0.01339 +Epoch [788/4000] Training [14/16] Loss: 0.01268 +Epoch [788/4000] Training [15/16] Loss: 0.01238 +Epoch [788/4000] Training [16/16] Loss: 0.01413 +Epoch [788/4000] Training metric {'Train/mean dice_metric': 0.9899777173995972, 'Train/mean miou_metric': 0.9800056219100952, 'Train/mean f1': 0.9860110282897949, 'Train/mean precision': 0.9809209704399109, 'Train/mean recall': 0.9911541938781738, 'Train/mean hd95_metric': 1.8857202529907227} +Epoch [788/4000] Validation [1/4] Loss: 0.14322 focal_loss 0.08320 dice_loss 0.06002 +Epoch [788/4000] Validation [2/4] Loss: 0.40299 focal_loss 0.21417 dice_loss 0.18882 +Epoch [788/4000] Validation [3/4] Loss: 0.21015 focal_loss 0.13358 dice_loss 0.07657 +Epoch [788/4000] Validation [4/4] Loss: 0.34614 focal_loss 0.19759 dice_loss 0.14855 +Epoch [788/4000] Validation metric {'Val/mean dice_metric': 0.9622007608413696, 'Val/mean miou_metric': 0.9402116537094116, 'Val/mean f1': 0.9632977843284607, 'Val/mean precision': 0.9552979469299316, 'Val/mean recall': 0.9714326858520508, 'Val/mean hd95_metric': 7.846957206726074} +Cheakpoint... +Epoch [788/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622007608413696, 'Val/mean miou_metric': 0.9402116537094116, 'Val/mean f1': 0.9632977843284607, 'Val/mean precision': 0.9552979469299316, 'Val/mean recall': 0.9714326858520508, 'Val/mean hd95_metric': 7.846957206726074} +Epoch [789/4000] Training [1/16] Loss: 0.01677 +Epoch [789/4000] Training [2/16] Loss: 0.01405 +Epoch [789/4000] Training [3/16] Loss: 0.01582 +Epoch [789/4000] Training [4/16] Loss: 0.01591 +Epoch [789/4000] Training [5/16] Loss: 0.01759 +Epoch [789/4000] Training [6/16] Loss: 0.02101 +Epoch [789/4000] Training [7/16] Loss: 0.01843 +Epoch [789/4000] Training [8/16] Loss: 0.01447 +Epoch [789/4000] Training [9/16] Loss: 0.01457 +Epoch [789/4000] Training [10/16] Loss: 0.01215 +Epoch [789/4000] Training [11/16] Loss: 0.01022 +Epoch [789/4000] Training [12/16] Loss: 0.01886 +Epoch [789/4000] Training [13/16] Loss: 0.01564 +Epoch [789/4000] Training [14/16] Loss: 0.01259 +Epoch [789/4000] Training [15/16] Loss: 0.01901 +Epoch [789/4000] Training [16/16] Loss: 0.01480 +Epoch [789/4000] Training metric {'Train/mean dice_metric': 0.9872398376464844, 'Train/mean miou_metric': 0.9752199053764343, 'Train/mean f1': 0.9837002158164978, 'Train/mean precision': 0.9789001941680908, 'Train/mean recall': 0.9885475039482117, 'Train/mean hd95_metric': 2.267819881439209} +Epoch [789/4000] Validation [1/4] Loss: 0.16203 focal_loss 0.09691 dice_loss 0.06512 +Epoch [789/4000] Validation [2/4] Loss: 0.31267 focal_loss 0.14745 dice_loss 0.16522 +Epoch [789/4000] Validation [3/4] Loss: 0.25801 focal_loss 0.16573 dice_loss 0.09228 +Epoch [789/4000] Validation [4/4] Loss: 0.23966 focal_loss 0.10231 dice_loss 0.13735 +Epoch [789/4000] Validation metric {'Val/mean dice_metric': 0.9614116549491882, 'Val/mean miou_metric': 0.9382619857788086, 'Val/mean f1': 0.9636236429214478, 'Val/mean precision': 0.9570164084434509, 'Val/mean recall': 0.9703227281570435, 'Val/mean hd95_metric': 7.47910213470459} +Cheakpoint... +Epoch [789/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614116549491882, 'Val/mean miou_metric': 0.9382619857788086, 'Val/mean f1': 0.9636236429214478, 'Val/mean precision': 0.9570164084434509, 'Val/mean recall': 0.9703227281570435, 'Val/mean hd95_metric': 7.47910213470459} +Epoch [790/4000] Training [1/16] Loss: 0.01651 +Epoch [790/4000] Training [2/16] Loss: 0.01747 +Epoch [790/4000] Training [3/16] Loss: 0.01792 +Epoch [790/4000] Training [4/16] Loss: 0.01302 +Epoch [790/4000] Training [5/16] Loss: 0.01868 +Epoch [790/4000] Training [6/16] Loss: 0.01422 +Epoch [790/4000] Training [7/16] Loss: 0.01223 +Epoch [790/4000] Training [8/16] Loss: 0.04269 +Epoch [790/4000] Training [9/16] Loss: 0.01094 +Epoch [790/4000] Training [10/16] Loss: 0.01803 +Epoch [790/4000] Training [11/16] Loss: 0.01869 +Epoch [790/4000] Training [12/16] Loss: 0.01647 +Epoch [790/4000] Training [13/16] Loss: 0.01363 +Epoch [790/4000] Training [14/16] Loss: 0.01153 +Epoch [790/4000] Training [15/16] Loss: 0.01141 +Epoch [790/4000] Training [16/16] Loss: 0.01124 +Epoch [790/4000] Training metric {'Train/mean dice_metric': 0.9894706010818481, 'Train/mean miou_metric': 0.979010820388794, 'Train/mean f1': 0.9853758811950684, 'Train/mean precision': 0.9803645610809326, 'Train/mean recall': 0.9904386401176453, 'Train/mean hd95_metric': 2.0241661071777344} +Epoch [790/4000] Validation [1/4] Loss: 0.15073 focal_loss 0.09141 dice_loss 0.05932 +Epoch [790/4000] Validation [2/4] Loss: 0.20690 focal_loss 0.09289 dice_loss 0.11400 +Epoch [790/4000] Validation [3/4] Loss: 0.16068 focal_loss 0.09668 dice_loss 0.06400 +Epoch [790/4000] Validation [4/4] Loss: 0.32208 focal_loss 0.17377 dice_loss 0.14832 +Epoch [790/4000] Validation metric {'Val/mean dice_metric': 0.9647622108459473, 'Val/mean miou_metric': 0.9419586062431335, 'Val/mean f1': 0.9653634428977966, 'Val/mean precision': 0.9580003619194031, 'Val/mean recall': 0.972840428352356, 'Val/mean hd95_metric': 7.223140716552734} +Cheakpoint... +Epoch [790/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647622108459473, 'Val/mean miou_metric': 0.9419586062431335, 'Val/mean f1': 0.9653634428977966, 'Val/mean precision': 0.9580003619194031, 'Val/mean recall': 0.972840428352356, 'Val/mean hd95_metric': 7.223140716552734} +Epoch [791/4000] Training [1/16] Loss: 0.01091 +Epoch [791/4000] Training [2/16] Loss: 0.01561 +Epoch [791/4000] Training [3/16] Loss: 0.01369 +Epoch [791/4000] Training [4/16] Loss: 0.01090 +Epoch [791/4000] Training [5/16] Loss: 0.01874 +Epoch [791/4000] Training [6/16] Loss: 0.01537 +Epoch [791/4000] Training [7/16] Loss: 0.01484 +Epoch [791/4000] Training [8/16] Loss: 0.01324 +Epoch [791/4000] Training [9/16] Loss: 0.02301 +Epoch [791/4000] Training [10/16] Loss: 0.01100 +Epoch [791/4000] Training [11/16] Loss: 0.01639 +Epoch [791/4000] Training [12/16] Loss: 0.01758 +Epoch [791/4000] Training [13/16] Loss: 0.01290 +Epoch [791/4000] Training [14/16] Loss: 0.02425 +Epoch [791/4000] Training [15/16] Loss: 0.01561 +Epoch [791/4000] Training [16/16] Loss: 0.01227 +Epoch [791/4000] Training metric {'Train/mean dice_metric': 0.988591194152832, 'Train/mean miou_metric': 0.9775859117507935, 'Train/mean f1': 0.9859670400619507, 'Train/mean precision': 0.9815720915794373, 'Train/mean recall': 0.9904014468193054, 'Train/mean hd95_metric': 1.6551976203918457} +Epoch [791/4000] Validation [1/4] Loss: 0.16293 focal_loss 0.10436 dice_loss 0.05857 +Epoch [791/4000] Validation [2/4] Loss: 0.17430 focal_loss 0.07260 dice_loss 0.10170 +Epoch [791/4000] Validation [3/4] Loss: 0.12586 focal_loss 0.07149 dice_loss 0.05437 +Epoch [791/4000] Validation [4/4] Loss: 0.16342 focal_loss 0.06517 dice_loss 0.09826 +Epoch [791/4000] Validation metric {'Val/mean dice_metric': 0.9666999578475952, 'Val/mean miou_metric': 0.9446462392807007, 'Val/mean f1': 0.9685308933258057, 'Val/mean precision': 0.9598991274833679, 'Val/mean recall': 0.9773192405700684, 'Val/mean hd95_metric': 7.1265435218811035} +Cheakpoint... +Epoch [791/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666999578475952, 'Val/mean miou_metric': 0.9446462392807007, 'Val/mean f1': 0.9685308933258057, 'Val/mean precision': 0.9598991274833679, 'Val/mean recall': 0.9773192405700684, 'Val/mean hd95_metric': 7.1265435218811035} +Epoch [792/4000] Training [1/16] Loss: 0.01388 +Epoch [792/4000] Training [2/16] Loss: 0.01307 +Epoch [792/4000] Training [3/16] Loss: 0.01560 +Epoch [792/4000] Training [4/16] Loss: 0.01167 +Epoch [792/4000] Training [5/16] Loss: 0.01410 +Epoch [792/4000] Training [6/16] Loss: 0.01443 +Epoch [792/4000] Training [7/16] Loss: 0.01339 +Epoch [792/4000] Training [8/16] Loss: 0.01168 +Epoch [792/4000] Training [9/16] Loss: 0.01345 +Epoch [792/4000] Training [10/16] Loss: 0.01457 +Epoch [792/4000] Training [11/16] Loss: 0.01016 +Epoch [792/4000] Training [12/16] Loss: 0.00941 +Epoch [792/4000] Training [13/16] Loss: 0.01263 +Epoch [792/4000] Training [14/16] Loss: 0.01232 +Epoch [792/4000] Training [15/16] Loss: 0.02436 +Epoch [792/4000] Training [16/16] Loss: 0.01607 +Epoch [792/4000] Training metric {'Train/mean dice_metric': 0.9905271530151367, 'Train/mean miou_metric': 0.9810431003570557, 'Train/mean f1': 0.9870017170906067, 'Train/mean precision': 0.9827010035514832, 'Train/mean recall': 0.9913402795791626, 'Train/mean hd95_metric': 1.503488540649414} +Epoch [792/4000] Validation [1/4] Loss: 0.23659 focal_loss 0.16091 dice_loss 0.07568 +Epoch [792/4000] Validation [2/4] Loss: 0.20152 focal_loss 0.08171 dice_loss 0.11980 +Epoch [792/4000] Validation [3/4] Loss: 0.10679 focal_loss 0.05681 dice_loss 0.04998 +Epoch [792/4000] Validation [4/4] Loss: 0.22616 focal_loss 0.10938 dice_loss 0.11677 +Epoch [792/4000] Validation metric {'Val/mean dice_metric': 0.9682650566101074, 'Val/mean miou_metric': 0.9473124742507935, 'Val/mean f1': 0.9690748453140259, 'Val/mean precision': 0.9648145437240601, 'Val/mean recall': 0.9733728766441345, 'Val/mean hd95_metric': 5.911695957183838} +Cheakpoint... +Epoch [792/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9682650566101074, 'Val/mean miou_metric': 0.9473124742507935, 'Val/mean f1': 0.9690748453140259, 'Val/mean precision': 0.9648145437240601, 'Val/mean recall': 0.9733728766441345, 'Val/mean hd95_metric': 5.911695957183838} +Epoch [793/4000] Training [1/16] Loss: 0.01204 +Epoch [793/4000] Training [2/16] Loss: 0.01162 +Epoch [793/4000] Training [3/16] Loss: 0.01436 +Epoch [793/4000] Training [4/16] Loss: 0.01699 +Epoch [793/4000] Training [5/16] Loss: 0.01517 +Epoch [793/4000] Training [6/16] Loss: 0.01476 +Epoch [793/4000] Training [7/16] Loss: 0.03422 +Epoch [793/4000] Training [8/16] Loss: 0.01242 +Epoch [793/4000] Training [9/16] Loss: 0.02487 +Epoch [793/4000] Training [10/16] Loss: 0.01465 +Epoch [793/4000] Training [11/16] Loss: 0.01285 +Epoch [793/4000] Training [12/16] Loss: 0.01649 +Epoch [793/4000] Training [13/16] Loss: 0.01989 +Epoch [793/4000] Training [14/16] Loss: 0.01279 +Epoch [793/4000] Training [15/16] Loss: 0.01355 +Epoch [793/4000] Training [16/16] Loss: 0.01242 +Epoch [793/4000] Training metric {'Train/mean dice_metric': 0.9892323017120361, 'Train/mean miou_metric': 0.9786533713340759, 'Train/mean f1': 0.9867870211601257, 'Train/mean precision': 0.9818840622901917, 'Train/mean recall': 0.9917392134666443, 'Train/mean hd95_metric': 2.2101893424987793} +Epoch [793/4000] Validation [1/4] Loss: 0.17720 focal_loss 0.11289 dice_loss 0.06431 +Epoch [793/4000] Validation [2/4] Loss: 0.34442 focal_loss 0.16817 dice_loss 0.17626 +Epoch [793/4000] Validation [3/4] Loss: 0.13930 focal_loss 0.07413 dice_loss 0.06517 +Epoch [793/4000] Validation [4/4] Loss: 0.28731 focal_loss 0.13710 dice_loss 0.15021 +Epoch [793/4000] Validation metric {'Val/mean dice_metric': 0.9655545353889465, 'Val/mean miou_metric': 0.943240761756897, 'Val/mean f1': 0.9692785143852234, 'Val/mean precision': 0.9643933176994324, 'Val/mean recall': 0.9742134809494019, 'Val/mean hd95_metric': 8.29079818725586} +Cheakpoint... +Epoch [793/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655545353889465, 'Val/mean miou_metric': 0.943240761756897, 'Val/mean f1': 0.9692785143852234, 'Val/mean precision': 0.9643933176994324, 'Val/mean recall': 0.9742134809494019, 'Val/mean hd95_metric': 8.29079818725586} +Epoch [794/4000] Training [1/16] Loss: 0.01653 +Epoch [794/4000] Training [2/16] Loss: 0.01093 +Epoch [794/4000] Training [3/16] Loss: 0.02470 +Epoch [794/4000] Training [4/16] Loss: 0.01091 +Epoch [794/4000] Training [5/16] Loss: 0.01840 +Epoch [794/4000] Training [6/16] Loss: 0.01295 +Epoch [794/4000] Training [7/16] Loss: 0.01355 +Epoch [794/4000] Training [8/16] Loss: 0.01360 +Epoch [794/4000] Training [9/16] Loss: 0.01398 +Epoch [794/4000] Training [10/16] Loss: 0.01393 +Epoch [794/4000] Training [11/16] Loss: 0.01324 +Epoch [794/4000] Training [12/16] Loss: 0.01385 +Epoch [794/4000] Training [13/16] Loss: 0.01153 +Epoch [794/4000] Training [14/16] Loss: 0.01407 +Epoch [794/4000] Training [15/16] Loss: 0.01077 +Epoch [794/4000] Training [16/16] Loss: 0.00917 +Epoch [794/4000] Training metric {'Train/mean dice_metric': 0.9906005859375, 'Train/mean miou_metric': 0.9812671542167664, 'Train/mean f1': 0.986989438533783, 'Train/mean precision': 0.9824438691139221, 'Train/mean recall': 0.9915772676467896, 'Train/mean hd95_metric': 1.4264806509017944} +Epoch [794/4000] Validation [1/4] Loss: 0.17777 focal_loss 0.11427 dice_loss 0.06351 +Epoch [794/4000] Validation [2/4] Loss: 0.18235 focal_loss 0.08595 dice_loss 0.09641 +Epoch [794/4000] Validation [3/4] Loss: 0.14019 focal_loss 0.06733 dice_loss 0.07286 +Epoch [794/4000] Validation [4/4] Loss: 0.40978 focal_loss 0.22736 dice_loss 0.18242 +Epoch [794/4000] Validation metric {'Val/mean dice_metric': 0.9676090478897095, 'Val/mean miou_metric': 0.9466384649276733, 'Val/mean f1': 0.9690452814102173, 'Val/mean precision': 0.9618315100669861, 'Val/mean recall': 0.9763680696487427, 'Val/mean hd95_metric': 6.386750221252441} +Cheakpoint... +Epoch [794/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676090478897095, 'Val/mean miou_metric': 0.9466384649276733, 'Val/mean f1': 0.9690452814102173, 'Val/mean precision': 0.9618315100669861, 'Val/mean recall': 0.9763680696487427, 'Val/mean hd95_metric': 6.386750221252441} +Epoch [795/4000] Training [1/16] Loss: 0.01267 +Epoch [795/4000] Training [2/16] Loss: 0.01249 +Epoch [795/4000] Training [3/16] Loss: 0.01399 +Epoch [795/4000] Training [4/16] Loss: 0.01471 +Epoch [795/4000] Training [5/16] Loss: 0.01340 +Epoch [795/4000] Training [6/16] Loss: 0.01021 +Epoch [795/4000] Training [7/16] Loss: 0.01291 +Epoch [795/4000] Training [8/16] Loss: 0.01252 +Epoch [795/4000] Training [9/16] Loss: 0.01254 +Epoch [795/4000] Training [10/16] Loss: 0.01419 +Epoch [795/4000] Training [11/16] Loss: 0.01344 +Epoch [795/4000] Training [12/16] Loss: 0.07097 +Epoch [795/4000] Training [13/16] Loss: 0.01865 +Epoch [795/4000] Training [14/16] Loss: 0.01467 +Epoch [795/4000] Training [15/16] Loss: 0.01184 +Epoch [795/4000] Training [16/16] Loss: 0.01585 +Epoch [795/4000] Training metric {'Train/mean dice_metric': 0.9890286326408386, 'Train/mean miou_metric': 0.9788730144500732, 'Train/mean f1': 0.9837481379508972, 'Train/mean precision': 0.9766367673873901, 'Train/mean recall': 0.9909637570381165, 'Train/mean hd95_metric': 2.017761707305908} +Epoch [795/4000] Validation [1/4] Loss: 0.21401 focal_loss 0.13637 dice_loss 0.07764 +Epoch [795/4000] Validation [2/4] Loss: 0.19983 focal_loss 0.08972 dice_loss 0.11011 +Epoch [795/4000] Validation [3/4] Loss: 0.13235 focal_loss 0.07238 dice_loss 0.05996 +Epoch [795/4000] Validation [4/4] Loss: 0.33377 focal_loss 0.19914 dice_loss 0.13464 +Epoch [795/4000] Validation metric {'Val/mean dice_metric': 0.9674339294433594, 'Val/mean miou_metric': 0.9456021189689636, 'Val/mean f1': 0.9660468101501465, 'Val/mean precision': 0.9618325233459473, 'Val/mean recall': 0.970298171043396, 'Val/mean hd95_metric': 6.800971984863281} +Cheakpoint... +Epoch [795/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674339294433594, 'Val/mean miou_metric': 0.9456021189689636, 'Val/mean f1': 0.9660468101501465, 'Val/mean precision': 0.9618325233459473, 'Val/mean recall': 0.970298171043396, 'Val/mean hd95_metric': 6.800971984863281} +Epoch [796/4000] Training [1/16] Loss: 0.01425 +Epoch [796/4000] Training [2/16] Loss: 0.02057 +Epoch [796/4000] Training [3/16] Loss: 0.01530 +Epoch [796/4000] Training [4/16] Loss: 0.01261 +Epoch [796/4000] Training [5/16] Loss: 0.01112 +Epoch [796/4000] Training [6/16] Loss: 0.01193 +Epoch [796/4000] Training [7/16] Loss: 0.01513 +Epoch [796/4000] Training [8/16] Loss: 0.01577 +Epoch [796/4000] Training [9/16] Loss: 0.01564 +Epoch [796/4000] Training [10/16] Loss: 0.01669 +Epoch [796/4000] Training [11/16] Loss: 0.01537 +Epoch [796/4000] Training [12/16] Loss: 0.04279 +Epoch [796/4000] Training [13/16] Loss: 0.01667 +Epoch [796/4000] Training [14/16] Loss: 0.04137 +Epoch [796/4000] Training [15/16] Loss: 0.01788 +Epoch [796/4000] Training [16/16] Loss: 0.04342 +Epoch [796/4000] Training metric {'Train/mean dice_metric': 0.986318051815033, 'Train/mean miou_metric': 0.9738061428070068, 'Train/mean f1': 0.9834352135658264, 'Train/mean precision': 0.979121208190918, 'Train/mean recall': 0.9877873659133911, 'Train/mean hd95_metric': 2.8180837631225586} +Epoch [796/4000] Validation [1/4] Loss: 0.19982 focal_loss 0.12425 dice_loss 0.07557 +Epoch [796/4000] Validation [2/4] Loss: 0.22066 focal_loss 0.08738 dice_loss 0.13329 +Epoch [796/4000] Validation [3/4] Loss: 0.14354 focal_loss 0.06985 dice_loss 0.07369 +Epoch [796/4000] Validation [4/4] Loss: 0.27366 focal_loss 0.13845 dice_loss 0.13520 +Epoch [796/4000] Validation metric {'Val/mean dice_metric': 0.9625104069709778, 'Val/mean miou_metric': 0.9384084939956665, 'Val/mean f1': 0.9645988941192627, 'Val/mean precision': 0.955887496471405, 'Val/mean recall': 0.9734704494476318, 'Val/mean hd95_metric': 8.738222122192383} +Cheakpoint... +Epoch [796/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625104069709778, 'Val/mean miou_metric': 0.9384084939956665, 'Val/mean f1': 0.9645988941192627, 'Val/mean precision': 0.955887496471405, 'Val/mean recall': 0.9734704494476318, 'Val/mean hd95_metric': 8.738222122192383} +Epoch [797/4000] Training [1/16] Loss: 0.01138 +Epoch [797/4000] Training [2/16] Loss: 0.02913 +Epoch [797/4000] Training [3/16] Loss: 0.01772 +Epoch [797/4000] Training [4/16] Loss: 0.01475 +Epoch [797/4000] Training [5/16] Loss: 0.01559 +Epoch [797/4000] Training [6/16] Loss: 0.01663 +Epoch [797/4000] Training [7/16] Loss: 0.01471 +Epoch [797/4000] Training [8/16] Loss: 0.02441 +Epoch [797/4000] Training [9/16] Loss: 0.01561 +Epoch [797/4000] Training [10/16] Loss: 0.01398 +Epoch [797/4000] Training [11/16] Loss: 0.01873 +Epoch [797/4000] Training [12/16] Loss: 0.01755 +Epoch [797/4000] Training [13/16] Loss: 0.01327 +Epoch [797/4000] Training [14/16] Loss: 0.01576 +Epoch [797/4000] Training [15/16] Loss: 0.01848 +Epoch [797/4000] Training [16/16] Loss: 0.02896 +Epoch [797/4000] Training metric {'Train/mean dice_metric': 0.9881162643432617, 'Train/mean miou_metric': 0.9764378070831299, 'Train/mean f1': 0.9849115014076233, 'Train/mean precision': 0.9803532361984253, 'Train/mean recall': 0.9895123839378357, 'Train/mean hd95_metric': 2.9190621376037598} +Epoch [797/4000] Validation [1/4] Loss: 0.32392 focal_loss 0.19944 dice_loss 0.12449 +Epoch [797/4000] Validation [2/4] Loss: 0.19911 focal_loss 0.08510 dice_loss 0.11401 +Epoch [797/4000] Validation [3/4] Loss: 0.16627 focal_loss 0.07660 dice_loss 0.08967 +Epoch [797/4000] Validation [4/4] Loss: 0.33110 focal_loss 0.18173 dice_loss 0.14937 +Epoch [797/4000] Validation metric {'Val/mean dice_metric': 0.9607968330383301, 'Val/mean miou_metric': 0.9357738494873047, 'Val/mean f1': 0.9619140028953552, 'Val/mean precision': 0.9648149013519287, 'Val/mean recall': 0.9590304493904114, 'Val/mean hd95_metric': 8.608983993530273} +Cheakpoint... +Epoch [797/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9608], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9607968330383301, 'Val/mean miou_metric': 0.9357738494873047, 'Val/mean f1': 0.9619140028953552, 'Val/mean precision': 0.9648149013519287, 'Val/mean recall': 0.9590304493904114, 'Val/mean hd95_metric': 8.608983993530273} +Epoch [798/4000] Training [1/16] Loss: 0.01964 +Epoch [798/4000] Training [2/16] Loss: 0.02007 +Epoch [798/4000] Training [3/16] Loss: 0.01425 +Epoch [798/4000] Training [4/16] Loss: 0.01554 +Epoch [798/4000] Training [5/16] Loss: 0.01684 +Epoch [798/4000] Training [6/16] Loss: 0.01434 +Epoch [798/4000] Training [7/16] Loss: 0.02431 +Epoch [798/4000] Training [8/16] Loss: 0.01530 +Epoch [798/4000] Training [9/16] Loss: 0.01579 +Epoch [798/4000] Training [10/16] Loss: 0.01665 +Epoch [798/4000] Training [11/16] Loss: 0.01013 +Epoch [798/4000] Training [12/16] Loss: 0.01334 +Epoch [798/4000] Training [13/16] Loss: 0.01316 +Epoch [798/4000] Training [14/16] Loss: 0.01683 +Epoch [798/4000] Training [15/16] Loss: 0.02212 +Epoch [798/4000] Training [16/16] Loss: 0.02126 +Epoch [798/4000] Training metric {'Train/mean dice_metric': 0.9870716333389282, 'Train/mean miou_metric': 0.9753177762031555, 'Train/mean f1': 0.9828411340713501, 'Train/mean precision': 0.9797291159629822, 'Train/mean recall': 0.9859730005264282, 'Train/mean hd95_metric': 3.1359026432037354} +Epoch [798/4000] Validation [1/4] Loss: 0.15047 focal_loss 0.07251 dice_loss 0.07796 +Epoch [798/4000] Validation [2/4] Loss: 0.45687 focal_loss 0.22933 dice_loss 0.22754 +Epoch [798/4000] Validation [3/4] Loss: 0.12666 focal_loss 0.06571 dice_loss 0.06095 +Epoch [798/4000] Validation [4/4] Loss: 0.22661 focal_loss 0.11288 dice_loss 0.11373 +Epoch [798/4000] Validation metric {'Val/mean dice_metric': 0.9625318646430969, 'Val/mean miou_metric': 0.9395231008529663, 'Val/mean f1': 0.9647990465164185, 'Val/mean precision': 0.9625597596168518, 'Val/mean recall': 0.9670488238334656, 'Val/mean hd95_metric': 7.567981719970703} +Cheakpoint... +Epoch [798/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9625318646430969, 'Val/mean miou_metric': 0.9395231008529663, 'Val/mean f1': 0.9647990465164185, 'Val/mean precision': 0.9625597596168518, 'Val/mean recall': 0.9670488238334656, 'Val/mean hd95_metric': 7.567981719970703} +Epoch [799/4000] Training [1/16] Loss: 0.02416 +Epoch [799/4000] Training [2/16] Loss: 0.01453 +Epoch [799/4000] Training [3/16] Loss: 0.01785 +Epoch [799/4000] Training [4/16] Loss: 0.01705 +Epoch [799/4000] Training [5/16] Loss: 0.01337 +Epoch [799/4000] Training [6/16] Loss: 0.01891 +Epoch [799/4000] Training [7/16] Loss: 0.01245 +Epoch [799/4000] Training [8/16] Loss: 0.01439 +Epoch [799/4000] Training [9/16] Loss: 0.01333 +Epoch [799/4000] Training [10/16] Loss: 0.01391 +Epoch [799/4000] Training [11/16] Loss: 0.01945 +Epoch [799/4000] Training [12/16] Loss: 0.01927 +Epoch [799/4000] Training [13/16] Loss: 0.01651 +Epoch [799/4000] Training [14/16] Loss: 0.01354 +Epoch [799/4000] Training [15/16] Loss: 0.01809 +Epoch [799/4000] Training [16/16] Loss: 0.01689 +Epoch [799/4000] Training metric {'Train/mean dice_metric': 0.9881078600883484, 'Train/mean miou_metric': 0.9765779376029968, 'Train/mean f1': 0.9853143095970154, 'Train/mean precision': 0.9813446402549744, 'Train/mean recall': 0.9893162846565247, 'Train/mean hd95_metric': 2.3402016162872314} +Epoch [799/4000] Validation [1/4] Loss: 0.36610 focal_loss 0.23904 dice_loss 0.12706 +Epoch [799/4000] Validation [2/4] Loss: 0.35255 focal_loss 0.16531 dice_loss 0.18724 +Epoch [799/4000] Validation [3/4] Loss: 0.11208 focal_loss 0.05295 dice_loss 0.05913 +Epoch [799/4000] Validation [4/4] Loss: 0.30159 focal_loss 0.16208 dice_loss 0.13951 +Epoch [799/4000] Validation metric {'Val/mean dice_metric': 0.9572731256484985, 'Val/mean miou_metric': 0.9333942532539368, 'Val/mean f1': 0.9621601104736328, 'Val/mean precision': 0.9674827456474304, 'Val/mean recall': 0.9568955898284912, 'Val/mean hd95_metric': 7.824800968170166} +Cheakpoint... +Epoch [799/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9573], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9572731256484985, 'Val/mean miou_metric': 0.9333942532539368, 'Val/mean f1': 0.9621601104736328, 'Val/mean precision': 0.9674827456474304, 'Val/mean recall': 0.9568955898284912, 'Val/mean hd95_metric': 7.824800968170166} +Epoch [800/4000] Training [1/16] Loss: 0.01373 +Epoch [800/4000] Training [2/16] Loss: 0.01361 +Epoch [800/4000] Training [3/16] Loss: 0.01756 +Epoch [800/4000] Training [4/16] Loss: 0.01296 +Epoch [800/4000] Training [5/16] Loss: 0.01691 +Epoch [800/4000] Training [6/16] Loss: 0.01579 +Epoch [800/4000] Training [7/16] Loss: 0.01977 +Epoch [800/4000] Training [8/16] Loss: 0.01712 +Epoch [800/4000] Training [9/16] Loss: 0.01519 +Epoch [800/4000] Training [10/16] Loss: 0.01589 +Epoch [800/4000] Training [11/16] Loss: 0.01675 +Epoch [800/4000] Training [12/16] Loss: 0.02379 +Epoch [800/4000] Training [13/16] Loss: 0.01689 +Epoch [800/4000] Training [14/16] Loss: 0.02148 +Epoch [800/4000] Training [15/16] Loss: 0.01363 +Epoch [800/4000] Training [16/16] Loss: 0.01746 +Epoch [800/4000] Training metric {'Train/mean dice_metric': 0.9879698157310486, 'Train/mean miou_metric': 0.9761447906494141, 'Train/mean f1': 0.98410564661026, 'Train/mean precision': 0.9799677729606628, 'Train/mean recall': 0.9882786273956299, 'Train/mean hd95_metric': 2.1715333461761475} +Epoch [800/4000] Validation [1/4] Loss: 0.18215 focal_loss 0.11351 dice_loss 0.06864 +Epoch [800/4000] Validation [2/4] Loss: 0.25112 focal_loss 0.10851 dice_loss 0.14261 +Epoch [800/4000] Validation [3/4] Loss: 0.16579 focal_loss 0.08181 dice_loss 0.08399 +Epoch [800/4000] Validation [4/4] Loss: 0.36170 focal_loss 0.18498 dice_loss 0.17672 +Epoch [800/4000] Validation metric {'Val/mean dice_metric': 0.9582868814468384, 'Val/mean miou_metric': 0.93354332447052, 'Val/mean f1': 0.9594927430152893, 'Val/mean precision': 0.9468960762023926, 'Val/mean recall': 0.9724290370941162, 'Val/mean hd95_metric': 9.33984661102295} +Cheakpoint... +Epoch [800/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9583], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9582868814468384, 'Val/mean miou_metric': 0.93354332447052, 'Val/mean f1': 0.9594927430152893, 'Val/mean precision': 0.9468960762023926, 'Val/mean recall': 0.9724290370941162, 'Val/mean hd95_metric': 9.33984661102295} +Epoch [801/4000] Training [1/16] Loss: 0.02456 +Epoch [801/4000] Training [2/16] Loss: 0.01138 +Epoch [801/4000] Training [3/16] Loss: 0.02324 +Epoch [801/4000] Training [4/16] Loss: 0.01292 +Epoch [801/4000] Training [5/16] Loss: 0.01408 +Epoch [801/4000] Training [6/16] Loss: 0.01594 +Epoch [801/4000] Training [7/16] Loss: 0.01437 +Epoch [801/4000] Training [8/16] Loss: 0.01291 +Epoch [801/4000] Training [9/16] Loss: 0.01703 +Epoch [801/4000] Training [10/16] Loss: 0.02892 +Epoch [801/4000] Training [11/16] Loss: 0.01463 +Epoch [801/4000] Training [12/16] Loss: 0.03164 +Epoch [801/4000] Training [13/16] Loss: 0.01285 +Epoch [801/4000] Training [14/16] Loss: 0.01270 +Epoch [801/4000] Training [15/16] Loss: 0.01929 +Epoch [801/4000] Training [16/16] Loss: 0.01627 +Epoch [801/4000] Training metric {'Train/mean dice_metric': 0.9877419471740723, 'Train/mean miou_metric': 0.9756848812103271, 'Train/mean f1': 0.9839778542518616, 'Train/mean precision': 0.979977011680603, 'Train/mean recall': 0.9880114793777466, 'Train/mean hd95_metric': 2.9673912525177} +Epoch [801/4000] Validation [1/4] Loss: 0.19786 focal_loss 0.11958 dice_loss 0.07828 +Epoch [801/4000] Validation [2/4] Loss: 0.19412 focal_loss 0.08754 dice_loss 0.10658 +Epoch [801/4000] Validation [3/4] Loss: 0.14123 focal_loss 0.07610 dice_loss 0.06512 +Epoch [801/4000] Validation [4/4] Loss: 0.41653 focal_loss 0.23744 dice_loss 0.17909 +Epoch [801/4000] Validation metric {'Val/mean dice_metric': 0.9633662104606628, 'Val/mean miou_metric': 0.939251720905304, 'Val/mean f1': 0.9638570547103882, 'Val/mean precision': 0.9594177007675171, 'Val/mean recall': 0.9683377742767334, 'Val/mean hd95_metric': 8.169591903686523} +Cheakpoint... +Epoch [801/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633662104606628, 'Val/mean miou_metric': 0.939251720905304, 'Val/mean f1': 0.9638570547103882, 'Val/mean precision': 0.9594177007675171, 'Val/mean recall': 0.9683377742767334, 'Val/mean hd95_metric': 8.169591903686523} +Epoch [802/4000] Training [1/16] Loss: 0.01556 +Epoch [802/4000] Training [2/16] Loss: 0.01839 +Epoch [802/4000] Training [3/16] Loss: 0.01232 +Epoch [802/4000] Training [4/16] Loss: 0.01573 +Epoch [802/4000] Training [5/16] Loss: 0.01365 +Epoch [802/4000] Training [6/16] Loss: 0.01324 +Epoch [802/4000] Training [7/16] Loss: 0.01720 +Epoch [802/4000] Training [8/16] Loss: 0.02167 +Epoch [802/4000] Training [9/16] Loss: 0.01773 +Epoch [802/4000] Training [10/16] Loss: 0.02204 +Epoch [802/4000] Training [11/16] Loss: 0.01382 +Epoch [802/4000] Training [12/16] Loss: 0.01154 +Epoch [802/4000] Training [13/16] Loss: 0.02053 +Epoch [802/4000] Training [14/16] Loss: 0.02785 +Epoch [802/4000] Training [15/16] Loss: 0.02322 +Epoch [802/4000] Training [16/16] Loss: 0.01417 +Epoch [802/4000] Training metric {'Train/mean dice_metric': 0.9870411157608032, 'Train/mean miou_metric': 0.9748225212097168, 'Train/mean f1': 0.9844235181808472, 'Train/mean precision': 0.9800270199775696, 'Train/mean recall': 0.9888597726821899, 'Train/mean hd95_metric': 2.4486823081970215} +Epoch [802/4000] Validation [1/4] Loss: 0.13391 focal_loss 0.06953 dice_loss 0.06439 +Epoch [802/4000] Validation [2/4] Loss: 0.15773 focal_loss 0.05605 dice_loss 0.10168 +Epoch [802/4000] Validation [3/4] Loss: 0.25552 focal_loss 0.13026 dice_loss 0.12526 +Epoch [802/4000] Validation [4/4] Loss: 0.20943 focal_loss 0.10201 dice_loss 0.10742 +Epoch [802/4000] Validation metric {'Val/mean dice_metric': 0.9614068865776062, 'Val/mean miou_metric': 0.9384088516235352, 'Val/mean f1': 0.9659702181816101, 'Val/mean precision': 0.965079128742218, 'Val/mean recall': 0.9668630957603455, 'Val/mean hd95_metric': 7.340200901031494} +Cheakpoint... +Epoch [802/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614068865776062, 'Val/mean miou_metric': 0.9384088516235352, 'Val/mean f1': 0.9659702181816101, 'Val/mean precision': 0.965079128742218, 'Val/mean recall': 0.9668630957603455, 'Val/mean hd95_metric': 7.340200901031494} +Epoch [803/4000] Training [1/16] Loss: 0.01775 +Epoch [803/4000] Training [2/16] Loss: 0.01654 +Epoch [803/4000] Training [3/16] Loss: 0.01346 +Epoch [803/4000] Training [4/16] Loss: 0.01790 +Epoch [803/4000] Training [5/16] Loss: 0.01520 +Epoch [803/4000] Training [6/16] Loss: 0.02173 +Epoch [803/4000] Training [7/16] Loss: 0.01522 +Epoch [803/4000] Training [8/16] Loss: 0.01431 +Epoch [803/4000] Training [9/16] Loss: 0.06886 +Epoch [803/4000] Training [10/16] Loss: 0.01509 +Epoch [803/4000] Training [11/16] Loss: 0.01788 +Epoch [803/4000] Training [12/16] Loss: 0.01354 +Epoch [803/4000] Training [13/16] Loss: 0.01644 +Epoch [803/4000] Training [14/16] Loss: 0.01567 +Epoch [803/4000] Training [15/16] Loss: 0.02725 +Epoch [803/4000] Training [16/16] Loss: 0.02358 +Epoch [803/4000] Training metric {'Train/mean dice_metric': 0.9880671501159668, 'Train/mean miou_metric': 0.9765026569366455, 'Train/mean f1': 0.9848752021789551, 'Train/mean precision': 0.9802401065826416, 'Train/mean recall': 0.9895543456077576, 'Train/mean hd95_metric': 2.46907377243042} +Epoch [803/4000] Validation [1/4] Loss: 0.22041 focal_loss 0.12774 dice_loss 0.09267 +Epoch [803/4000] Validation [2/4] Loss: 0.18242 focal_loss 0.07185 dice_loss 0.11057 +Epoch [803/4000] Validation [3/4] Loss: 0.28838 focal_loss 0.14487 dice_loss 0.14350 +Epoch [803/4000] Validation [4/4] Loss: 0.36454 focal_loss 0.21881 dice_loss 0.14573 +Epoch [803/4000] Validation metric {'Val/mean dice_metric': 0.9617109298706055, 'Val/mean miou_metric': 0.9365768432617188, 'Val/mean f1': 0.9628927707672119, 'Val/mean precision': 0.9617384672164917, 'Val/mean recall': 0.964049756526947, 'Val/mean hd95_metric': 8.722555160522461} +Cheakpoint... +Epoch [803/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9617109298706055, 'Val/mean miou_metric': 0.9365768432617188, 'Val/mean f1': 0.9628927707672119, 'Val/mean precision': 0.9617384672164917, 'Val/mean recall': 0.964049756526947, 'Val/mean hd95_metric': 8.722555160522461} +Epoch [804/4000] Training [1/16] Loss: 0.01595 +Epoch [804/4000] Training [2/16] Loss: 0.01607 +Epoch [804/4000] Training [3/16] Loss: 0.01410 +Epoch [804/4000] Training [4/16] Loss: 0.01377 +Epoch [804/4000] Training [5/16] Loss: 0.01910 +Epoch [804/4000] Training [6/16] Loss: 0.01498 +Epoch [804/4000] Training [7/16] Loss: 0.01677 +Epoch [804/4000] Training [8/16] Loss: 0.01307 +Epoch [804/4000] Training [9/16] Loss: 0.01905 +Epoch [804/4000] Training [10/16] Loss: 0.02429 +Epoch [804/4000] Training [11/16] Loss: 0.02326 +Epoch [804/4000] Training [12/16] Loss: 0.01936 +Epoch [804/4000] Training [13/16] Loss: 0.01570 +Epoch [804/4000] Training [14/16] Loss: 0.01595 +Epoch [804/4000] Training [15/16] Loss: 0.01314 +Epoch [804/4000] Training [16/16] Loss: 0.02572 +Epoch [804/4000] Training metric {'Train/mean dice_metric': 0.9872404932975769, 'Train/mean miou_metric': 0.9749225974082947, 'Train/mean f1': 0.9835886359214783, 'Train/mean precision': 0.9784239530563354, 'Train/mean recall': 0.9888080954551697, 'Train/mean hd95_metric': 3.9859938621520996} +Epoch [804/4000] Validation [1/4] Loss: 0.38166 focal_loss 0.25304 dice_loss 0.12862 +Epoch [804/4000] Validation [2/4] Loss: 0.22808 focal_loss 0.10049 dice_loss 0.12759 +Epoch [804/4000] Validation [3/4] Loss: 0.17511 focal_loss 0.08812 dice_loss 0.08700 +Epoch [804/4000] Validation [4/4] Loss: 0.33516 focal_loss 0.20159 dice_loss 0.13357 +Epoch [804/4000] Validation metric {'Val/mean dice_metric': 0.9616996645927429, 'Val/mean miou_metric': 0.9366628527641296, 'Val/mean f1': 0.9616028070449829, 'Val/mean precision': 0.9609598517417908, 'Val/mean recall': 0.9622465968132019, 'Val/mean hd95_metric': 9.567773818969727} +Cheakpoint... +Epoch [804/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9616996645927429, 'Val/mean miou_metric': 0.9366628527641296, 'Val/mean f1': 0.9616028070449829, 'Val/mean precision': 0.9609598517417908, 'Val/mean recall': 0.9622465968132019, 'Val/mean hd95_metric': 9.567773818969727} +Epoch [805/4000] Training [1/16] Loss: 0.02116 +Epoch [805/4000] Training [2/16] Loss: 0.01421 +Epoch [805/4000] Training [3/16] Loss: 0.02295 +Epoch [805/4000] Training [4/16] Loss: 0.01747 +Epoch [805/4000] Training [5/16] Loss: 0.01471 +Epoch [805/4000] Training [6/16] Loss: 0.01218 +Epoch [805/4000] Training [7/16] Loss: 0.01644 +Epoch [805/4000] Training [8/16] Loss: 0.01469 +Epoch [805/4000] Training [9/16] Loss: 0.01538 +Epoch [805/4000] Training [10/16] Loss: 0.01175 +Epoch [805/4000] Training [11/16] Loss: 0.02805 +Epoch [805/4000] Training [12/16] Loss: 0.01794 +Epoch [805/4000] Training [13/16] Loss: 0.01556 +Epoch [805/4000] Training [14/16] Loss: 0.01578 +Epoch [805/4000] Training [15/16] Loss: 0.01355 +Epoch [805/4000] Training [16/16] Loss: 0.01279 +Epoch [805/4000] Training metric {'Train/mean dice_metric': 0.9869568347930908, 'Train/mean miou_metric': 0.9755008816719055, 'Train/mean f1': 0.9852932095527649, 'Train/mean precision': 0.9805049896240234, 'Train/mean recall': 0.9901284575462341, 'Train/mean hd95_metric': 1.6661162376403809} +Epoch [805/4000] Validation [1/4] Loss: 0.20210 focal_loss 0.11670 dice_loss 0.08540 +Epoch [805/4000] Validation [2/4] Loss: 0.22574 focal_loss 0.10531 dice_loss 0.12043 +Epoch [805/4000] Validation [3/4] Loss: 0.17020 focal_loss 0.09041 dice_loss 0.07980 +Epoch [805/4000] Validation [4/4] Loss: 0.31572 focal_loss 0.18827 dice_loss 0.12745 +Epoch [805/4000] Validation metric {'Val/mean dice_metric': 0.9652605056762695, 'Val/mean miou_metric': 0.9412499666213989, 'Val/mean f1': 0.9663882851600647, 'Val/mean precision': 0.9660505056381226, 'Val/mean recall': 0.9667263031005859, 'Val/mean hd95_metric': 6.8694748878479} +Cheakpoint... +Epoch [805/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652605056762695, 'Val/mean miou_metric': 0.9412499666213989, 'Val/mean f1': 0.9663882851600647, 'Val/mean precision': 0.9660505056381226, 'Val/mean recall': 0.9667263031005859, 'Val/mean hd95_metric': 6.8694748878479} +Epoch [806/4000] Training [1/16] Loss: 0.01324 +Epoch [806/4000] Training [2/16] Loss: 0.01443 +Epoch [806/4000] Training [3/16] Loss: 0.01855 +Epoch [806/4000] Training [4/16] Loss: 0.02083 +Epoch [806/4000] Training [5/16] Loss: 0.01737 +Epoch [806/4000] Training [6/16] Loss: 0.01169 +Epoch [806/4000] Training [7/16] Loss: 0.01444 +Epoch [806/4000] Training [8/16] Loss: 0.01376 +Epoch [806/4000] Training [9/16] Loss: 0.01405 +Epoch [806/4000] Training [10/16] Loss: 0.01343 +Epoch [806/4000] Training [11/16] Loss: 0.02645 +Epoch [806/4000] Training [12/16] Loss: 0.01316 +Epoch [806/4000] Training [13/16] Loss: 0.01536 +Epoch [806/4000] Training [14/16] Loss: 0.02236 +Epoch [806/4000] Training [15/16] Loss: 0.01492 +Epoch [806/4000] Training [16/16] Loss: 0.01705 +Epoch [806/4000] Training metric {'Train/mean dice_metric': 0.9889054298400879, 'Train/mean miou_metric': 0.978183388710022, 'Train/mean f1': 0.9854838848114014, 'Train/mean precision': 0.9807354211807251, 'Train/mean recall': 0.9902786016464233, 'Train/mean hd95_metric': 1.5845483541488647} +Epoch [806/4000] Validation [1/4] Loss: 0.18501 focal_loss 0.11737 dice_loss 0.06764 +Epoch [806/4000] Validation [2/4] Loss: 0.44830 focal_loss 0.24609 dice_loss 0.20221 +Epoch [806/4000] Validation [3/4] Loss: 0.12038 focal_loss 0.06362 dice_loss 0.05675 +Epoch [806/4000] Validation [4/4] Loss: 0.28570 focal_loss 0.14802 dice_loss 0.13767 +Epoch [806/4000] Validation metric {'Val/mean dice_metric': 0.9639018774032593, 'Val/mean miou_metric': 0.9420539736747742, 'Val/mean f1': 0.9672290682792664, 'Val/mean precision': 0.9637154936790466, 'Val/mean recall': 0.970768392086029, 'Val/mean hd95_metric': 7.037498474121094} +Cheakpoint... +Epoch [806/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639018774032593, 'Val/mean miou_metric': 0.9420539736747742, 'Val/mean f1': 0.9672290682792664, 'Val/mean precision': 0.9637154936790466, 'Val/mean recall': 0.970768392086029, 'Val/mean hd95_metric': 7.037498474121094} +Epoch [807/4000] Training [1/16] Loss: 0.01416 +Epoch [807/4000] Training [2/16] Loss: 0.01228 +Epoch [807/4000] Training [3/16] Loss: 0.01583 +Epoch [807/4000] Training [4/16] Loss: 0.01345 +Epoch [807/4000] Training [5/16] Loss: 0.01516 +Epoch [807/4000] Training [6/16] Loss: 0.01649 +Epoch [807/4000] Training [7/16] Loss: 0.01345 +Epoch [807/4000] Training [8/16] Loss: 0.01874 +Epoch [807/4000] Training [9/16] Loss: 0.01281 +Epoch [807/4000] Training [10/16] Loss: 0.01311 +Epoch [807/4000] Training [11/16] Loss: 0.01018 +Epoch [807/4000] Training [12/16] Loss: 0.01193 +Epoch [807/4000] Training [13/16] Loss: 0.01620 +Epoch [807/4000] Training [14/16] Loss: 0.01224 +Epoch [807/4000] Training [15/16] Loss: 0.01051 +Epoch [807/4000] Training [16/16] Loss: 0.01108 +Epoch [807/4000] Training metric {'Train/mean dice_metric': 0.9905732870101929, 'Train/mean miou_metric': 0.981117844581604, 'Train/mean f1': 0.9873905777931213, 'Train/mean precision': 0.9829239249229431, 'Train/mean recall': 0.9918979406356812, 'Train/mean hd95_metric': 1.3429367542266846} +Epoch [807/4000] Validation [1/4] Loss: 0.20409 focal_loss 0.13057 dice_loss 0.07351 +Epoch [807/4000] Validation [2/4] Loss: 0.20996 focal_loss 0.09435 dice_loss 0.11560 +Epoch [807/4000] Validation [3/4] Loss: 0.13810 focal_loss 0.07924 dice_loss 0.05886 +Epoch [807/4000] Validation [4/4] Loss: 0.28528 focal_loss 0.16559 dice_loss 0.11968 +Epoch [807/4000] Validation metric {'Val/mean dice_metric': 0.9663738012313843, 'Val/mean miou_metric': 0.9452177882194519, 'Val/mean f1': 0.9694052338600159, 'Val/mean precision': 0.9684791564941406, 'Val/mean recall': 0.9703330993652344, 'Val/mean hd95_metric': 6.502545356750488} +Cheakpoint... +Epoch [807/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9663738012313843, 'Val/mean miou_metric': 0.9452177882194519, 'Val/mean f1': 0.9694052338600159, 'Val/mean precision': 0.9684791564941406, 'Val/mean recall': 0.9703330993652344, 'Val/mean hd95_metric': 6.502545356750488} +Epoch [808/4000] Training [1/16] Loss: 0.00978 +Epoch [808/4000] Training [2/16] Loss: 0.01236 +Epoch [808/4000] Training [3/16] Loss: 0.01002 +Epoch [808/4000] Training [4/16] Loss: 0.00968 +Epoch [808/4000] Training [5/16] Loss: 0.01195 +Epoch [808/4000] Training [6/16] Loss: 0.01031 +Epoch [808/4000] Training [7/16] Loss: 0.01476 +Epoch [808/4000] Training [8/16] Loss: 0.01088 +Epoch [808/4000] Training [9/16] Loss: 0.01192 +Epoch [808/4000] Training [10/16] Loss: 0.02130 +Epoch [808/4000] Training [11/16] Loss: 0.01092 +Epoch [808/4000] Training [12/16] Loss: 0.01237 +Epoch [808/4000] Training [13/16] Loss: 0.01178 +Epoch [808/4000] Training [14/16] Loss: 0.01185 +Epoch [808/4000] Training [15/16] Loss: 0.01443 +Epoch [808/4000] Training [16/16] Loss: 0.01212 +Epoch [808/4000] Training metric {'Train/mean dice_metric': 0.9914511442184448, 'Train/mean miou_metric': 0.9828283190727234, 'Train/mean f1': 0.9875286221504211, 'Train/mean precision': 0.9828387498855591, 'Train/mean recall': 0.9922634959220886, 'Train/mean hd95_metric': 1.5090118646621704} +Epoch [808/4000] Validation [1/4] Loss: 0.28582 focal_loss 0.19105 dice_loss 0.09478 +Epoch [808/4000] Validation [2/4] Loss: 0.17841 focal_loss 0.07844 dice_loss 0.09997 +Epoch [808/4000] Validation [3/4] Loss: 0.18274 focal_loss 0.10339 dice_loss 0.07935 +Epoch [808/4000] Validation [4/4] Loss: 0.30309 focal_loss 0.17172 dice_loss 0.13138 +Epoch [808/4000] Validation metric {'Val/mean dice_metric': 0.9673773050308228, 'Val/mean miou_metric': 0.9467323422431946, 'Val/mean f1': 0.9696527719497681, 'Val/mean precision': 0.965285062789917, 'Val/mean recall': 0.9740601778030396, 'Val/mean hd95_metric': 6.625058650970459} +Cheakpoint... +Epoch [808/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673773050308228, 'Val/mean miou_metric': 0.9467323422431946, 'Val/mean f1': 0.9696527719497681, 'Val/mean precision': 0.965285062789917, 'Val/mean recall': 0.9740601778030396, 'Val/mean hd95_metric': 6.625058650970459} +Epoch [809/4000] Training [1/16] Loss: 0.01502 +Epoch [809/4000] Training [2/16] Loss: 0.01153 +Epoch [809/4000] Training [3/16] Loss: 0.01551 +Epoch [809/4000] Training [4/16] Loss: 0.01517 +Epoch [809/4000] Training [5/16] Loss: 0.02721 +Epoch [809/4000] Training [6/16] Loss: 0.01945 +Epoch [809/4000] Training [7/16] Loss: 0.03895 +Epoch [809/4000] Training [8/16] Loss: 0.01149 +Epoch [809/4000] Training [9/16] Loss: 0.01464 +Epoch [809/4000] Training [10/16] Loss: 0.01047 +Epoch [809/4000] Training [11/16] Loss: 0.01194 +Epoch [809/4000] Training [12/16] Loss: 0.01652 +Epoch [809/4000] Training [13/16] Loss: 0.01951 +Epoch [809/4000] Training [14/16] Loss: 0.01509 +Epoch [809/4000] Training [15/16] Loss: 0.01208 +Epoch [809/4000] Training [16/16] Loss: 0.01348 +Epoch [809/4000] Training metric {'Train/mean dice_metric': 0.9897828698158264, 'Train/mean miou_metric': 0.9796534776687622, 'Train/mean f1': 0.9865414500236511, 'Train/mean precision': 0.9822507500648499, 'Train/mean recall': 0.9908698201179504, 'Train/mean hd95_metric': 1.8582179546356201} +Epoch [809/4000] Validation [1/4] Loss: 0.27970 focal_loss 0.16969 dice_loss 0.11002 +Epoch [809/4000] Validation [2/4] Loss: 0.18653 focal_loss 0.08632 dice_loss 0.10021 +Epoch [809/4000] Validation [3/4] Loss: 0.17323 focal_loss 0.10219 dice_loss 0.07104 +Epoch [809/4000] Validation [4/4] Loss: 0.32808 focal_loss 0.19848 dice_loss 0.12960 +Epoch [809/4000] Validation metric {'Val/mean dice_metric': 0.9674836993217468, 'Val/mean miou_metric': 0.9446558952331543, 'Val/mean f1': 0.9691846370697021, 'Val/mean precision': 0.9682134985923767, 'Val/mean recall': 0.9701577425003052, 'Val/mean hd95_metric': 6.719583034515381} +Cheakpoint... +Epoch [809/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674836993217468, 'Val/mean miou_metric': 0.9446558952331543, 'Val/mean f1': 0.9691846370697021, 'Val/mean precision': 0.9682134985923767, 'Val/mean recall': 0.9701577425003052, 'Val/mean hd95_metric': 6.719583034515381} +Epoch [810/4000] Training [1/16] Loss: 0.01636 +Epoch [810/4000] Training [2/16] Loss: 0.02324 +Epoch [810/4000] Training [3/16] Loss: 0.01113 +Epoch [810/4000] Training [4/16] Loss: 0.03581 +Epoch [810/4000] Training [5/16] Loss: 0.01363 +Epoch [810/4000] Training [6/16] Loss: 0.00993 +Epoch [810/4000] Training [7/16] Loss: 0.01292 +Epoch [810/4000] Training [8/16] Loss: 0.01233 +Epoch [810/4000] Training [9/16] Loss: 0.01726 +Epoch [810/4000] Training [10/16] Loss: 0.01451 +Epoch [810/4000] Training [11/16] Loss: 0.01134 +Epoch [810/4000] Training [12/16] Loss: 0.02097 +Epoch [810/4000] Training [13/16] Loss: 0.01197 +Epoch [810/4000] Training [14/16] Loss: 0.01472 +Epoch [810/4000] Training [15/16] Loss: 0.01271 +Epoch [810/4000] Training [16/16] Loss: 0.02276 +Epoch [810/4000] Training metric {'Train/mean dice_metric': 0.9899063110351562, 'Train/mean miou_metric': 0.9799232482910156, 'Train/mean f1': 0.9867534041404724, 'Train/mean precision': 0.9825290441513062, 'Train/mean recall': 0.9910141825675964, 'Train/mean hd95_metric': 2.0405521392822266} +Epoch [810/4000] Validation [1/4] Loss: 0.15436 focal_loss 0.08925 dice_loss 0.06511 +Epoch [810/4000] Validation [2/4] Loss: 0.17335 focal_loss 0.07811 dice_loss 0.09524 +Epoch [810/4000] Validation [3/4] Loss: 0.13071 focal_loss 0.06956 dice_loss 0.06116 +Epoch [810/4000] Validation [4/4] Loss: 0.17790 focal_loss 0.08806 dice_loss 0.08984 +Epoch [810/4000] Validation metric {'Val/mean dice_metric': 0.9678041338920593, 'Val/mean miou_metric': 0.9466843605041504, 'Val/mean f1': 0.9702374935150146, 'Val/mean precision': 0.9674186110496521, 'Val/mean recall': 0.9730728268623352, 'Val/mean hd95_metric': 6.11876106262207} +Cheakpoint... +Epoch [810/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678041338920593, 'Val/mean miou_metric': 0.9466843605041504, 'Val/mean f1': 0.9702374935150146, 'Val/mean precision': 0.9674186110496521, 'Val/mean recall': 0.9730728268623352, 'Val/mean hd95_metric': 6.11876106262207} +Epoch [811/4000] Training [1/16] Loss: 0.01470 +Epoch [811/4000] Training [2/16] Loss: 0.01540 +Epoch [811/4000] Training [3/16] Loss: 0.01166 +Epoch [811/4000] Training [4/16] Loss: 0.01466 +Epoch [811/4000] Training [5/16] Loss: 0.01388 +Epoch [811/4000] Training [6/16] Loss: 0.01210 +Epoch [811/4000] Training [7/16] Loss: 0.01042 +Epoch [811/4000] Training [8/16] Loss: 0.01670 +Epoch [811/4000] Training [9/16] Loss: 0.01642 +Epoch [811/4000] Training [10/16] Loss: 0.01378 +Epoch [811/4000] Training [11/16] Loss: 0.01625 +Epoch [811/4000] Training [12/16] Loss: 0.01190 +Epoch [811/4000] Training [13/16] Loss: 0.01032 +Epoch [811/4000] Training [14/16] Loss: 0.02256 +Epoch [811/4000] Training [15/16] Loss: 0.01272 +Epoch [811/4000] Training [16/16] Loss: 0.01753 +Epoch [811/4000] Training metric {'Train/mean dice_metric': 0.9903755187988281, 'Train/mean miou_metric': 0.9807268977165222, 'Train/mean f1': 0.9865013360977173, 'Train/mean precision': 0.9813334345817566, 'Train/mean recall': 0.991723895072937, 'Train/mean hd95_metric': 1.4818562269210815} +Epoch [811/4000] Validation [1/4] Loss: 0.19568 focal_loss 0.12584 dice_loss 0.06984 +Epoch [811/4000] Validation [2/4] Loss: 0.18999 focal_loss 0.06584 dice_loss 0.12415 +Epoch [811/4000] Validation [3/4] Loss: 0.20520 focal_loss 0.11645 dice_loss 0.08874 +Epoch [811/4000] Validation [4/4] Loss: 0.19146 focal_loss 0.09399 dice_loss 0.09747 +Epoch [811/4000] Validation metric {'Val/mean dice_metric': 0.9696962237358093, 'Val/mean miou_metric': 0.9482938051223755, 'Val/mean f1': 0.9691480994224548, 'Val/mean precision': 0.9627120494842529, 'Val/mean recall': 0.9756707549095154, 'Val/mean hd95_metric': 6.016996383666992} +Cheakpoint... +Epoch [811/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696962237358093, 'Val/mean miou_metric': 0.9482938051223755, 'Val/mean f1': 0.9691480994224548, 'Val/mean precision': 0.9627120494842529, 'Val/mean recall': 0.9756707549095154, 'Val/mean hd95_metric': 6.016996383666992} +Epoch [812/4000] Training [1/16] Loss: 0.01308 +Epoch [812/4000] Training [2/16] Loss: 0.01341 +Epoch [812/4000] Training [3/16] Loss: 0.01612 +Epoch [812/4000] Training [4/16] Loss: 0.01216 +Epoch [812/4000] Training [5/16] Loss: 0.01315 +Epoch [812/4000] Training [6/16] Loss: 0.01236 +Epoch [812/4000] Training [7/16] Loss: 0.01787 +Epoch [812/4000] Training [8/16] Loss: 0.01387 +Epoch [812/4000] Training [9/16] Loss: 0.02055 +Epoch [812/4000] Training [10/16] Loss: 0.01236 +Epoch [812/4000] Training [11/16] Loss: 0.01077 +Epoch [812/4000] Training [12/16] Loss: 0.01123 +Epoch [812/4000] Training [13/16] Loss: 0.01302 +Epoch [812/4000] Training [14/16] Loss: 0.01470 +Epoch [812/4000] Training [15/16] Loss: 0.01130 +Epoch [812/4000] Training [16/16] Loss: 0.01346 +Epoch [812/4000] Training metric {'Train/mean dice_metric': 0.9905749559402466, 'Train/mean miou_metric': 0.9811241626739502, 'Train/mean f1': 0.9876879453659058, 'Train/mean precision': 0.9832752346992493, 'Train/mean recall': 0.9921404123306274, 'Train/mean hd95_metric': 1.2278401851654053} +Epoch [812/4000] Validation [1/4] Loss: 0.29664 focal_loss 0.19903 dice_loss 0.09761 +Epoch [812/4000] Validation [2/4] Loss: 0.15432 focal_loss 0.06515 dice_loss 0.08917 +Epoch [812/4000] Validation [3/4] Loss: 0.11235 focal_loss 0.06153 dice_loss 0.05082 +Epoch [812/4000] Validation [4/4] Loss: 0.16014 focal_loss 0.07593 dice_loss 0.08421 +Epoch [812/4000] Validation metric {'Val/mean dice_metric': 0.9690991640090942, 'Val/mean miou_metric': 0.9482471346855164, 'Val/mean f1': 0.9716567397117615, 'Val/mean precision': 0.969253659248352, 'Val/mean recall': 0.9740718007087708, 'Val/mean hd95_metric': 5.383440971374512} +Cheakpoint... +Epoch [812/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690991640090942, 'Val/mean miou_metric': 0.9482471346855164, 'Val/mean f1': 0.9716567397117615, 'Val/mean precision': 0.969253659248352, 'Val/mean recall': 0.9740718007087708, 'Val/mean hd95_metric': 5.383440971374512} +Epoch [813/4000] Training [1/16] Loss: 0.01232 +Epoch [813/4000] Training [2/16] Loss: 0.01735 +Epoch [813/4000] Training [3/16] Loss: 0.02023 +Epoch [813/4000] Training [4/16] Loss: 0.01005 +Epoch [813/4000] Training [5/16] Loss: 0.01251 +Epoch [813/4000] Training [6/16] Loss: 0.01407 +Epoch [813/4000] Training [7/16] Loss: 0.01198 +Epoch [813/4000] Training [8/16] Loss: 0.01440 +Epoch [813/4000] Training [9/16] Loss: 0.01151 +Epoch [813/4000] Training [10/16] Loss: 0.01164 +Epoch [813/4000] Training [11/16] Loss: 0.01358 +Epoch [813/4000] Training [12/16] Loss: 0.01352 +Epoch [813/4000] Training [13/16] Loss: 0.01157 +Epoch [813/4000] Training [14/16] Loss: 0.01287 +Epoch [813/4000] Training [15/16] Loss: 0.01110 +Epoch [813/4000] Training [16/16] Loss: 0.01463 +Epoch [813/4000] Training metric {'Train/mean dice_metric': 0.9908834099769592, 'Train/mean miou_metric': 0.9817240238189697, 'Train/mean f1': 0.9878019690513611, 'Train/mean precision': 0.9833343625068665, 'Train/mean recall': 0.9923103451728821, 'Train/mean hd95_metric': 1.2318871021270752} +Epoch [813/4000] Validation [1/4] Loss: 0.22055 focal_loss 0.14061 dice_loss 0.07995 +Epoch [813/4000] Validation [2/4] Loss: 0.18453 focal_loss 0.07897 dice_loss 0.10556 +Epoch [813/4000] Validation [3/4] Loss: 0.11134 focal_loss 0.05307 dice_loss 0.05828 +Epoch [813/4000] Validation [4/4] Loss: 0.26449 focal_loss 0.12552 dice_loss 0.13898 +Epoch [813/4000] Validation metric {'Val/mean dice_metric': 0.970038890838623, 'Val/mean miou_metric': 0.949079155921936, 'Val/mean f1': 0.9710357189178467, 'Val/mean precision': 0.964031994342804, 'Val/mean recall': 0.9781419038772583, 'Val/mean hd95_metric': 5.958889961242676} +Cheakpoint... +Epoch [813/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970038890838623, 'Val/mean miou_metric': 0.949079155921936, 'Val/mean f1': 0.9710357189178467, 'Val/mean precision': 0.964031994342804, 'Val/mean recall': 0.9781419038772583, 'Val/mean hd95_metric': 5.958889961242676} +Epoch [814/4000] Training [1/16] Loss: 0.01310 +Epoch [814/4000] Training [2/16] Loss: 0.01282 +Epoch [814/4000] Training [3/16] Loss: 0.01084 +Epoch [814/4000] Training [4/16] Loss: 0.01029 +Epoch [814/4000] Training [5/16] Loss: 0.01367 +Epoch [814/4000] Training [6/16] Loss: 0.06517 +Epoch [814/4000] Training [7/16] Loss: 0.06943 +Epoch [814/4000] Training [8/16] Loss: 0.01214 +Epoch [814/4000] Training [9/16] Loss: 0.01296 +Epoch [814/4000] Training [10/16] Loss: 0.01332 +Epoch [814/4000] Training [11/16] Loss: 0.05123 +Epoch [814/4000] Training [12/16] Loss: 0.02911 +Epoch [814/4000] Training [13/16] Loss: 0.01755 +Epoch [814/4000] Training [14/16] Loss: 0.01483 +Epoch [814/4000] Training [15/16] Loss: 0.01357 +Epoch [814/4000] Training [16/16] Loss: 0.01978 +Epoch [814/4000] Training metric {'Train/mean dice_metric': 0.9859619736671448, 'Train/mean miou_metric': 0.9740586280822754, 'Train/mean f1': 0.9780275225639343, 'Train/mean precision': 0.9679194092750549, 'Train/mean recall': 0.9883489608764648, 'Train/mean hd95_metric': 3.4721107482910156} +Epoch [814/4000] Validation [1/4] Loss: 0.95145 focal_loss 0.72304 dice_loss 0.22841 +Epoch [814/4000] Validation [2/4] Loss: 0.52462 focal_loss 0.22817 dice_loss 0.29646 +Epoch [814/4000] Validation [3/4] Loss: 0.18875 focal_loss 0.10149 dice_loss 0.08726 +Epoch [814/4000] Validation [4/4] Loss: 0.43974 focal_loss 0.25363 dice_loss 0.18611 +Epoch [814/4000] Validation metric {'Val/mean dice_metric': 0.9504666328430176, 'Val/mean miou_metric': 0.9248010516166687, 'Val/mean f1': 0.9507670998573303, 'Val/mean precision': 0.9587768316268921, 'Val/mean recall': 0.9428900480270386, 'Val/mean hd95_metric': 9.323771476745605} +Cheakpoint... +Epoch [814/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9505], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9504666328430176, 'Val/mean miou_metric': 0.9248010516166687, 'Val/mean f1': 0.9507670998573303, 'Val/mean precision': 0.9587768316268921, 'Val/mean recall': 0.9428900480270386, 'Val/mean hd95_metric': 9.323771476745605} +Epoch [815/4000] Training [1/16] Loss: 0.02413 +Epoch [815/4000] Training [2/16] Loss: 0.02778 +Epoch [815/4000] Training [3/16] Loss: 0.05899 +Epoch [815/4000] Training [4/16] Loss: 0.02894 +Epoch [815/4000] Training [5/16] Loss: 0.02711 +Epoch [815/4000] Training [6/16] Loss: 0.26452 +Epoch [815/4000] Training [7/16] Loss: 0.01189 +Epoch [815/4000] Training [8/16] Loss: 0.02419 +Epoch [815/4000] Training [9/16] Loss: 0.02121 +Epoch [815/4000] Training [10/16] Loss: 0.02106 +Epoch [815/4000] Training [11/16] Loss: 0.02623 +Epoch [815/4000] Training [12/16] Loss: 0.02528 +Epoch [815/4000] Training [13/16] Loss: 0.02906 +Epoch [815/4000] Training [14/16] Loss: 0.02304 +Epoch [815/4000] Training [15/16] Loss: 0.01625 +Epoch [815/4000] Training [16/16] Loss: 0.01988 +Epoch [815/4000] Training metric {'Train/mean dice_metric': 0.9787288904190063, 'Train/mean miou_metric': 0.9606624841690063, 'Train/mean f1': 0.9667237997055054, 'Train/mean precision': 0.9670667052268982, 'Train/mean recall': 0.9663811922073364, 'Train/mean hd95_metric': 8.203155517578125} +Epoch [815/4000] Validation [1/4] Loss: 0.14283 focal_loss 0.07323 dice_loss 0.06960 +Epoch [815/4000] Validation [2/4] Loss: 0.31608 focal_loss 0.13779 dice_loss 0.17829 +Epoch [815/4000] Validation [3/4] Loss: 0.16086 focal_loss 0.07950 dice_loss 0.08136 +Epoch [815/4000] Validation [4/4] Loss: 0.28147 focal_loss 0.12207 dice_loss 0.15940 +Epoch [815/4000] Validation metric {'Val/mean dice_metric': 0.9541710019111633, 'Val/mean miou_metric': 0.9242674112319946, 'Val/mean f1': 0.9474368691444397, 'Val/mean precision': 0.9393186569213867, 'Val/mean recall': 0.9556967616081238, 'Val/mean hd95_metric': 14.69477367401123} +Cheakpoint... +Epoch [815/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9542], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9541710019111633, 'Val/mean miou_metric': 0.9242674112319946, 'Val/mean f1': 0.9474368691444397, 'Val/mean precision': 0.9393186569213867, 'Val/mean recall': 0.9556967616081238, 'Val/mean hd95_metric': 14.69477367401123} +Epoch [816/4000] Training [1/16] Loss: 0.01944 +Epoch [816/4000] Training [2/16] Loss: 0.01772 +Epoch [816/4000] Training [3/16] Loss: 0.01586 +Epoch [816/4000] Training [4/16] Loss: 0.01883 +Epoch [816/4000] Training [5/16] Loss: 0.02222 +Epoch [816/4000] Training [6/16] Loss: 0.02231 +Epoch [816/4000] Training [7/16] Loss: 0.01650 +Epoch [816/4000] Training [8/16] Loss: 0.02149 +Epoch [816/4000] Training [9/16] Loss: 0.01896 +Epoch [816/4000] Training [10/16] Loss: 0.02034 +Epoch [816/4000] Training [11/16] Loss: 0.02377 +Epoch [816/4000] Training [12/16] Loss: 0.02074 +Epoch [816/4000] Training [13/16] Loss: 0.01850 +Epoch [816/4000] Training [14/16] Loss: 0.01651 +Epoch [816/4000] Training [15/16] Loss: 0.02062 +Epoch [816/4000] Training [16/16] Loss: 0.01639 +Epoch [816/4000] Training metric {'Train/mean dice_metric': 0.9860486388206482, 'Train/mean miou_metric': 0.972434401512146, 'Train/mean f1': 0.9823353886604309, 'Train/mean precision': 0.9793153405189514, 'Train/mean recall': 0.9853741526603699, 'Train/mean hd95_metric': 3.0208282470703125} +Epoch [816/4000] Validation [1/4] Loss: 0.22153 focal_loss 0.13717 dice_loss 0.08435 +Epoch [816/4000] Validation [2/4] Loss: 0.15870 focal_loss 0.05405 dice_loss 0.10466 +Epoch [816/4000] Validation [3/4] Loss: 0.14702 focal_loss 0.07884 dice_loss 0.06817 +Epoch [816/4000] Validation [4/4] Loss: 0.35790 focal_loss 0.17911 dice_loss 0.17879 +Epoch [816/4000] Validation metric {'Val/mean dice_metric': 0.9610675573348999, 'Val/mean miou_metric': 0.935333251953125, 'Val/mean f1': 0.9610176086425781, 'Val/mean precision': 0.9563050866127014, 'Val/mean recall': 0.965776801109314, 'Val/mean hd95_metric': 9.29237174987793} +Cheakpoint... +Epoch [816/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9610675573348999, 'Val/mean miou_metric': 0.935333251953125, 'Val/mean f1': 0.9610176086425781, 'Val/mean precision': 0.9563050866127014, 'Val/mean recall': 0.965776801109314, 'Val/mean hd95_metric': 9.29237174987793} +Epoch [817/4000] Training [1/16] Loss: 0.01946 +Epoch [817/4000] Training [2/16] Loss: 0.02877 +Epoch [817/4000] Training [3/16] Loss: 0.01642 +Epoch [817/4000] Training [4/16] Loss: 0.01684 +Epoch [817/4000] Training [5/16] Loss: 0.01834 +Epoch [817/4000] Training [6/16] Loss: 0.01457 +Epoch [817/4000] Training [7/16] Loss: 0.01680 +Epoch [817/4000] Training [8/16] Loss: 0.01463 +Epoch [817/4000] Training [9/16] Loss: 0.01942 +Epoch [817/4000] Training [10/16] Loss: 0.01424 +Epoch [817/4000] Training [11/16] Loss: 0.01642 +Epoch [817/4000] Training [12/16] Loss: 0.01838 +Epoch [817/4000] Training [13/16] Loss: 0.01450 +Epoch [817/4000] Training [14/16] Loss: 0.01254 +Epoch [817/4000] Training [15/16] Loss: 0.01627 +Epoch [817/4000] Training [16/16] Loss: 0.01834 +Epoch [817/4000] Training metric {'Train/mean dice_metric': 0.9877153038978577, 'Train/mean miou_metric': 0.9755945205688477, 'Train/mean f1': 0.9842281341552734, 'Train/mean precision': 0.9792940616607666, 'Train/mean recall': 0.9892122149467468, 'Train/mean hd95_metric': 2.417292356491089} +Epoch [817/4000] Validation [1/4] Loss: 0.17205 focal_loss 0.10554 dice_loss 0.06650 +Epoch [817/4000] Validation [2/4] Loss: 0.22656 focal_loss 0.08469 dice_loss 0.14188 +Epoch [817/4000] Validation [3/4] Loss: 0.27155 focal_loss 0.15051 dice_loss 0.12104 +Epoch [817/4000] Validation [4/4] Loss: 0.34888 focal_loss 0.15575 dice_loss 0.19313 +Epoch [817/4000] Validation metric {'Val/mean dice_metric': 0.963170051574707, 'Val/mean miou_metric': 0.9391580820083618, 'Val/mean f1': 0.9650185108184814, 'Val/mean precision': 0.9558871388435364, 'Val/mean recall': 0.9743260741233826, 'Val/mean hd95_metric': 8.663220405578613} +Cheakpoint... +Epoch [817/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963170051574707, 'Val/mean miou_metric': 0.9391580820083618, 'Val/mean f1': 0.9650185108184814, 'Val/mean precision': 0.9558871388435364, 'Val/mean recall': 0.9743260741233826, 'Val/mean hd95_metric': 8.663220405578613} +Epoch [818/4000] Training [1/16] Loss: 0.01547 +Epoch [818/4000] Training [2/16] Loss: 0.01476 +Epoch [818/4000] Training [3/16] Loss: 0.01448 +Epoch [818/4000] Training [4/16] Loss: 0.01418 +Epoch [818/4000] Training [5/16] Loss: 0.01350 +Epoch [818/4000] Training [6/16] Loss: 0.01295 +Epoch [818/4000] Training [7/16] Loss: 0.02411 +Epoch [818/4000] Training [8/16] Loss: 0.01763 +Epoch [818/4000] Training [9/16] Loss: 0.01636 +Epoch [818/4000] Training [10/16] Loss: 0.01582 +Epoch [818/4000] Training [11/16] Loss: 0.01125 +Epoch [818/4000] Training [12/16] Loss: 0.01789 +Epoch [818/4000] Training [13/16] Loss: 0.01189 +Epoch [818/4000] Training [14/16] Loss: 0.01116 +Epoch [818/4000] Training [15/16] Loss: 0.01176 +Epoch [818/4000] Training [16/16] Loss: 0.01376 +Epoch [818/4000] Training metric {'Train/mean dice_metric': 0.9899569153785706, 'Train/mean miou_metric': 0.9799607992172241, 'Train/mean f1': 0.9862766861915588, 'Train/mean precision': 0.9813701510429382, 'Train/mean recall': 0.9912327527999878, 'Train/mean hd95_metric': 1.4357836246490479} +Epoch [818/4000] Validation [1/4] Loss: 0.14995 focal_loss 0.09033 dice_loss 0.05962 +Epoch [818/4000] Validation [2/4] Loss: 0.21894 focal_loss 0.08601 dice_loss 0.13293 +Epoch [818/4000] Validation [3/4] Loss: 0.15780 focal_loss 0.07436 dice_loss 0.08345 +Epoch [818/4000] Validation [4/4] Loss: 0.27171 focal_loss 0.13686 dice_loss 0.13485 +Epoch [818/4000] Validation metric {'Val/mean dice_metric': 0.9663515090942383, 'Val/mean miou_metric': 0.9443391561508179, 'Val/mean f1': 0.9672480821609497, 'Val/mean precision': 0.9573227167129517, 'Val/mean recall': 0.9773814678192139, 'Val/mean hd95_metric': 7.423165321350098} +Cheakpoint... +Epoch [818/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9663515090942383, 'Val/mean miou_metric': 0.9443391561508179, 'Val/mean f1': 0.9672480821609497, 'Val/mean precision': 0.9573227167129517, 'Val/mean recall': 0.9773814678192139, 'Val/mean hd95_metric': 7.423165321350098} +Epoch [819/4000] Training [1/16] Loss: 0.01344 +Epoch [819/4000] Training [2/16] Loss: 0.01360 +Epoch [819/4000] Training [3/16] Loss: 0.01179 +Epoch [819/4000] Training [4/16] Loss: 0.01237 +Epoch [819/4000] Training [5/16] Loss: 0.01629 +Epoch [819/4000] Training [6/16] Loss: 0.01988 +Epoch [819/4000] Training [7/16] Loss: 0.01427 +Epoch [819/4000] Training [8/16] Loss: 0.01213 +Epoch [819/4000] Training [9/16] Loss: 0.01116 +Epoch [819/4000] Training [10/16] Loss: 0.01646 +Epoch [819/4000] Training [11/16] Loss: 0.01504 +Epoch [819/4000] Training [12/16] Loss: 0.01512 +Epoch [819/4000] Training [13/16] Loss: 0.01343 +Epoch [819/4000] Training [14/16] Loss: 0.01416 +Epoch [819/4000] Training [15/16] Loss: 0.01241 +Epoch [819/4000] Training [16/16] Loss: 0.01218 +Epoch [819/4000] Training metric {'Train/mean dice_metric': 0.9908239841461182, 'Train/mean miou_metric': 0.9815987944602966, 'Train/mean f1': 0.9870629906654358, 'Train/mean precision': 0.9825984835624695, 'Train/mean recall': 0.9915683269500732, 'Train/mean hd95_metric': 1.5486265420913696} +Epoch [819/4000] Validation [1/4] Loss: 0.17364 focal_loss 0.09823 dice_loss 0.07542 +Epoch [819/4000] Validation [2/4] Loss: 0.40393 focal_loss 0.20648 dice_loss 0.19744 +Epoch [819/4000] Validation [3/4] Loss: 0.14688 focal_loss 0.07479 dice_loss 0.07209 +Epoch [819/4000] Validation [4/4] Loss: 0.23189 focal_loss 0.10269 dice_loss 0.12920 +Epoch [819/4000] Validation metric {'Val/mean dice_metric': 0.965377151966095, 'Val/mean miou_metric': 0.9435617327690125, 'Val/mean f1': 0.9666587710380554, 'Val/mean precision': 0.9552506804466248, 'Val/mean recall': 0.978342592716217, 'Val/mean hd95_metric': 8.006629943847656} +Cheakpoint... +Epoch [819/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965377151966095, 'Val/mean miou_metric': 0.9435617327690125, 'Val/mean f1': 0.9666587710380554, 'Val/mean precision': 0.9552506804466248, 'Val/mean recall': 0.978342592716217, 'Val/mean hd95_metric': 8.006629943847656} +Epoch [820/4000] Training [1/16] Loss: 0.01311 +Epoch [820/4000] Training [2/16] Loss: 0.01467 +Epoch [820/4000] Training [3/16] Loss: 0.01053 +Epoch [820/4000] Training [4/16] Loss: 0.01113 +Epoch [820/4000] Training [5/16] Loss: 0.01048 +Epoch [820/4000] Training [6/16] Loss: 0.01254 +Epoch [820/4000] Training [7/16] Loss: 0.01484 +Epoch [820/4000] Training [8/16] Loss: 0.01419 +Epoch [820/4000] Training [9/16] Loss: 0.01171 +Epoch [820/4000] Training [10/16] Loss: 0.01147 +Epoch [820/4000] Training [11/16] Loss: 0.01465 +Epoch [820/4000] Training [12/16] Loss: 0.01653 +Epoch [820/4000] Training [13/16] Loss: 0.01066 +Epoch [820/4000] Training [14/16] Loss: 0.01449 +Epoch [820/4000] Training [15/16] Loss: 0.01083 +Epoch [820/4000] Training [16/16] Loss: 0.01282 +Epoch [820/4000] Training metric {'Train/mean dice_metric': 0.9914031028747559, 'Train/mean miou_metric': 0.9827091693878174, 'Train/mean f1': 0.9865331649780273, 'Train/mean precision': 0.9811476469039917, 'Train/mean recall': 0.991978108882904, 'Train/mean hd95_metric': 1.4609336853027344} +Epoch [820/4000] Validation [1/4] Loss: 0.16991 focal_loss 0.10298 dice_loss 0.06693 +Epoch [820/4000] Validation [2/4] Loss: 0.26423 focal_loss 0.10897 dice_loss 0.15526 +Epoch [820/4000] Validation [3/4] Loss: 0.12792 focal_loss 0.06491 dice_loss 0.06302 +Epoch [820/4000] Validation [4/4] Loss: 0.21605 focal_loss 0.11972 dice_loss 0.09633 +Epoch [820/4000] Validation metric {'Val/mean dice_metric': 0.9694881439208984, 'Val/mean miou_metric': 0.9490609169006348, 'Val/mean f1': 0.9684537649154663, 'Val/mean precision': 0.9593782424926758, 'Val/mean recall': 0.9777025580406189, 'Val/mean hd95_metric': 6.950756072998047} +Cheakpoint... +Epoch [820/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694881439208984, 'Val/mean miou_metric': 0.9490609169006348, 'Val/mean f1': 0.9684537649154663, 'Val/mean precision': 0.9593782424926758, 'Val/mean recall': 0.9777025580406189, 'Val/mean hd95_metric': 6.950756072998047} +Epoch [821/4000] Training [1/16] Loss: 0.01043 +Epoch [821/4000] Training [2/16] Loss: 0.01360 +Epoch [821/4000] Training [3/16] Loss: 0.01154 +Epoch [821/4000] Training [4/16] Loss: 0.01199 +Epoch [821/4000] Training [5/16] Loss: 0.01440 +Epoch [821/4000] Training [6/16] Loss: 0.01124 +Epoch [821/4000] Training [7/16] Loss: 0.01534 +Epoch [821/4000] Training [8/16] Loss: 0.01373 +Epoch [821/4000] Training [9/16] Loss: 0.01606 +Epoch [821/4000] Training [10/16] Loss: 0.01029 +Epoch [821/4000] Training [11/16] Loss: 0.01225 +Epoch [821/4000] Training [12/16] Loss: 0.01828 +Epoch [821/4000] Training [13/16] Loss: 0.01195 +Epoch [821/4000] Training [14/16] Loss: 0.00965 +Epoch [821/4000] Training [15/16] Loss: 0.01072 +Epoch [821/4000] Training [16/16] Loss: 0.01148 +Epoch [821/4000] Training metric {'Train/mean dice_metric': 0.9914488792419434, 'Train/mean miou_metric': 0.982843816280365, 'Train/mean f1': 0.9882252216339111, 'Train/mean precision': 0.9838384985923767, 'Train/mean recall': 0.9926511645317078, 'Train/mean hd95_metric': 1.3565073013305664} +Epoch [821/4000] Validation [1/4] Loss: 0.27911 focal_loss 0.17746 dice_loss 0.10165 +Epoch [821/4000] Validation [2/4] Loss: 0.20835 focal_loss 0.09327 dice_loss 0.11509 +Epoch [821/4000] Validation [3/4] Loss: 0.22886 focal_loss 0.12461 dice_loss 0.10425 +Epoch [821/4000] Validation [4/4] Loss: 0.13626 focal_loss 0.05626 dice_loss 0.08000 +Epoch [821/4000] Validation metric {'Val/mean dice_metric': 0.9699934720993042, 'Val/mean miou_metric': 0.9495034217834473, 'Val/mean f1': 0.9695075154304504, 'Val/mean precision': 0.9611830115318298, 'Val/mean recall': 0.9779773354530334, 'Val/mean hd95_metric': 6.879730224609375} +Cheakpoint... +Epoch [821/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699934720993042, 'Val/mean miou_metric': 0.9495034217834473, 'Val/mean f1': 0.9695075154304504, 'Val/mean precision': 0.9611830115318298, 'Val/mean recall': 0.9779773354530334, 'Val/mean hd95_metric': 6.879730224609375} +Epoch [822/4000] Training [1/16] Loss: 0.01501 +Epoch [822/4000] Training [2/16] Loss: 0.00990 +Epoch [822/4000] Training [3/16] Loss: 0.01221 +Epoch [822/4000] Training [4/16] Loss: 0.01252 +Epoch [822/4000] Training [5/16] Loss: 0.01221 +Epoch [822/4000] Training [6/16] Loss: 0.01047 +Epoch [822/4000] Training [7/16] Loss: 0.01007 +Epoch [822/4000] Training [8/16] Loss: 0.01352 +Epoch [822/4000] Training [9/16] Loss: 0.02396 +Epoch [822/4000] Training [10/16] Loss: 0.01604 +Epoch [822/4000] Training [11/16] Loss: 0.01355 +Epoch [822/4000] Training [12/16] Loss: 0.01587 +Epoch [822/4000] Training [13/16] Loss: 0.01314 +Epoch [822/4000] Training [14/16] Loss: 0.01038 +Epoch [822/4000] Training [15/16] Loss: 0.01121 +Epoch [822/4000] Training [16/16] Loss: 0.01727 +Epoch [822/4000] Training metric {'Train/mean dice_metric': 0.9907410740852356, 'Train/mean miou_metric': 0.9814583659172058, 'Train/mean f1': 0.987501859664917, 'Train/mean precision': 0.9828211069107056, 'Train/mean recall': 0.99222731590271, 'Train/mean hd95_metric': 1.3660091161727905} +Epoch [822/4000] Validation [1/4] Loss: 0.18449 focal_loss 0.11776 dice_loss 0.06673 +Epoch [822/4000] Validation [2/4] Loss: 0.23514 focal_loss 0.09390 dice_loss 0.14124 +Epoch [822/4000] Validation [3/4] Loss: 0.27872 focal_loss 0.14675 dice_loss 0.13197 +Epoch [822/4000] Validation [4/4] Loss: 0.17252 focal_loss 0.07545 dice_loss 0.09707 +Epoch [822/4000] Validation metric {'Val/mean dice_metric': 0.9683831930160522, 'Val/mean miou_metric': 0.9468722343444824, 'Val/mean f1': 0.9688140749931335, 'Val/mean precision': 0.9595308303833008, 'Val/mean recall': 0.9782787561416626, 'Val/mean hd95_metric': 6.807269096374512} +Cheakpoint... +Epoch [822/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683831930160522, 'Val/mean miou_metric': 0.9468722343444824, 'Val/mean f1': 0.9688140749931335, 'Val/mean precision': 0.9595308303833008, 'Val/mean recall': 0.9782787561416626, 'Val/mean hd95_metric': 6.807269096374512} +Epoch [823/4000] Training [1/16] Loss: 0.01350 +Epoch [823/4000] Training [2/16] Loss: 0.02020 +Epoch [823/4000] Training [3/16] Loss: 0.02044 +Epoch [823/4000] Training [4/16] Loss: 0.01110 +Epoch [823/4000] Training [5/16] Loss: 0.01150 +Epoch [823/4000] Training [6/16] Loss: 0.01539 +Epoch [823/4000] Training [7/16] Loss: 0.01210 +Epoch [823/4000] Training [8/16] Loss: 0.01494 +Epoch [823/4000] Training [9/16] Loss: 0.01321 +Epoch [823/4000] Training [10/16] Loss: 0.01549 +Epoch [823/4000] Training [11/16] Loss: 0.01226 +Epoch [823/4000] Training [12/16] Loss: 0.01052 +Epoch [823/4000] Training [13/16] Loss: 0.01981 +Epoch [823/4000] Training [14/16] Loss: 0.01141 +Epoch [823/4000] Training [15/16] Loss: 0.01110 +Epoch [823/4000] Training [16/16] Loss: 0.01339 +Epoch [823/4000] Training metric {'Train/mean dice_metric': 0.9907976388931274, 'Train/mean miou_metric': 0.9815812110900879, 'Train/mean f1': 0.9872243404388428, 'Train/mean precision': 0.982404351234436, 'Train/mean recall': 0.9920918345451355, 'Train/mean hd95_metric': 1.4516286849975586} +Epoch [823/4000] Validation [1/4] Loss: 0.15601 focal_loss 0.08990 dice_loss 0.06610 +Epoch [823/4000] Validation [2/4] Loss: 0.28385 focal_loss 0.12250 dice_loss 0.16135 +Epoch [823/4000] Validation [3/4] Loss: 0.22990 focal_loss 0.12279 dice_loss 0.10711 +Epoch [823/4000] Validation [4/4] Loss: 0.23604 focal_loss 0.13075 dice_loss 0.10529 +Epoch [823/4000] Validation metric {'Val/mean dice_metric': 0.9676748514175415, 'Val/mean miou_metric': 0.9466249346733093, 'Val/mean f1': 0.9689527153968811, 'Val/mean precision': 0.9608423113822937, 'Val/mean recall': 0.9772012233734131, 'Val/mean hd95_metric': 6.641554355621338} +Cheakpoint... +Epoch [823/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676748514175415, 'Val/mean miou_metric': 0.9466249346733093, 'Val/mean f1': 0.9689527153968811, 'Val/mean precision': 0.9608423113822937, 'Val/mean recall': 0.9772012233734131, 'Val/mean hd95_metric': 6.641554355621338} +Epoch [824/4000] Training [1/16] Loss: 0.01341 +Epoch [824/4000] Training [2/16] Loss: 0.01202 +Epoch [824/4000] Training [3/16] Loss: 0.01410 +Epoch [824/4000] Training [4/16] Loss: 0.01195 +Epoch [824/4000] Training [5/16] Loss: 0.02023 +Epoch [824/4000] Training [6/16] Loss: 0.01275 +Epoch [824/4000] Training [7/16] Loss: 0.01966 +Epoch [824/4000] Training [8/16] Loss: 0.01485 +Epoch [824/4000] Training [9/16] Loss: 0.01199 +Epoch [824/4000] Training [10/16] Loss: 0.01531 +Epoch [824/4000] Training [11/16] Loss: 0.01370 +Epoch [824/4000] Training [12/16] Loss: 0.01075 +Epoch [824/4000] Training [13/16] Loss: 0.01931 +Epoch [824/4000] Training [14/16] Loss: 0.01203 +Epoch [824/4000] Training [15/16] Loss: 0.01266 +Epoch [824/4000] Training [16/16] Loss: 0.01564 +Epoch [824/4000] Training metric {'Train/mean dice_metric': 0.9901350140571594, 'Train/mean miou_metric': 0.98024982213974, 'Train/mean f1': 0.9868789911270142, 'Train/mean precision': 0.9826489090919495, 'Train/mean recall': 0.991145670413971, 'Train/mean hd95_metric': 1.428971767425537} +Epoch [824/4000] Validation [1/4] Loss: 0.67769 focal_loss 0.49480 dice_loss 0.18289 +Epoch [824/4000] Validation [2/4] Loss: 0.25685 focal_loss 0.09016 dice_loss 0.16669 +Epoch [824/4000] Validation [3/4] Loss: 0.28852 focal_loss 0.18286 dice_loss 0.10566 +Epoch [824/4000] Validation [4/4] Loss: 0.32675 focal_loss 0.17351 dice_loss 0.15324 +Epoch [824/4000] Validation metric {'Val/mean dice_metric': 0.9646869897842407, 'Val/mean miou_metric': 0.942899227142334, 'Val/mean f1': 0.9662632346153259, 'Val/mean precision': 0.9666465520858765, 'Val/mean recall': 0.9658802151679993, 'Val/mean hd95_metric': 6.642282009124756} +Cheakpoint... +Epoch [824/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646869897842407, 'Val/mean miou_metric': 0.942899227142334, 'Val/mean f1': 0.9662632346153259, 'Val/mean precision': 0.9666465520858765, 'Val/mean recall': 0.9658802151679993, 'Val/mean hd95_metric': 6.642282009124756} +Epoch [825/4000] Training [1/16] Loss: 0.01304 +Epoch [825/4000] Training [2/16] Loss: 0.01023 +Epoch [825/4000] Training [3/16] Loss: 0.01289 +Epoch [825/4000] Training [4/16] Loss: 0.01002 +Epoch [825/4000] Training [5/16] Loss: 0.01085 +Epoch [825/4000] Training [6/16] Loss: 0.01060 +Epoch [825/4000] Training [7/16] Loss: 0.01346 +Epoch [825/4000] Training [8/16] Loss: 0.01192 +Epoch [825/4000] Training [9/16] Loss: 0.01115 +Epoch [825/4000] Training [10/16] Loss: 0.02146 +Epoch [825/4000] Training [11/16] Loss: 0.01199 +Epoch [825/4000] Training [12/16] Loss: 0.01283 +Epoch [825/4000] Training [13/16] Loss: 0.01130 +Epoch [825/4000] Training [14/16] Loss: 0.01341 +Epoch [825/4000] Training [15/16] Loss: 0.01203 +Epoch [825/4000] Training [16/16] Loss: 0.01203 +Epoch [825/4000] Training metric {'Train/mean dice_metric': 0.9913074970245361, 'Train/mean miou_metric': 0.9825538992881775, 'Train/mean f1': 0.988031268119812, 'Train/mean precision': 0.9834397435188293, 'Train/mean recall': 0.9926658272743225, 'Train/mean hd95_metric': 1.1833853721618652} +Epoch [825/4000] Validation [1/4] Loss: 0.19756 focal_loss 0.11655 dice_loss 0.08101 +Epoch [825/4000] Validation [2/4] Loss: 0.19163 focal_loss 0.08232 dice_loss 0.10931 +Epoch [825/4000] Validation [3/4] Loss: 0.25832 focal_loss 0.16045 dice_loss 0.09787 +Epoch [825/4000] Validation [4/4] Loss: 0.25335 focal_loss 0.12670 dice_loss 0.12665 +Epoch [825/4000] Validation metric {'Val/mean dice_metric': 0.9658463597297668, 'Val/mean miou_metric': 0.944283664226532, 'Val/mean f1': 0.9669268131256104, 'Val/mean precision': 0.9613041877746582, 'Val/mean recall': 0.9726154804229736, 'Val/mean hd95_metric': 6.481846809387207} +Cheakpoint... +Epoch [825/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658463597297668, 'Val/mean miou_metric': 0.944283664226532, 'Val/mean f1': 0.9669268131256104, 'Val/mean precision': 0.9613041877746582, 'Val/mean recall': 0.9726154804229736, 'Val/mean hd95_metric': 6.481846809387207} +Epoch [826/4000] Training [1/16] Loss: 0.01286 +Epoch [826/4000] Training [2/16] Loss: 0.00940 +Epoch [826/4000] Training [3/16] Loss: 0.01098 +Epoch [826/4000] Training [4/16] Loss: 0.01803 +Epoch [826/4000] Training [5/16] Loss: 0.01094 +Epoch [826/4000] Training [6/16] Loss: 0.01182 +Epoch [826/4000] Training [7/16] Loss: 0.01147 +Epoch [826/4000] Training [8/16] Loss: 0.01661 +Epoch [826/4000] Training [9/16] Loss: 0.01389 +Epoch [826/4000] Training [10/16] Loss: 0.01251 +Epoch [826/4000] Training [11/16] Loss: 0.01338 +Epoch [826/4000] Training [12/16] Loss: 0.01551 +Epoch [826/4000] Training [13/16] Loss: 0.01126 +Epoch [826/4000] Training [14/16] Loss: 0.01624 +Epoch [826/4000] Training [15/16] Loss: 0.01695 +Epoch [826/4000] Training [16/16] Loss: 0.01206 +Epoch [826/4000] Training metric {'Train/mean dice_metric': 0.9908778667449951, 'Train/mean miou_metric': 0.9817047119140625, 'Train/mean f1': 0.9869107007980347, 'Train/mean precision': 0.9813915491104126, 'Train/mean recall': 0.9924923181533813, 'Train/mean hd95_metric': 1.2537742853164673} +Epoch [826/4000] Validation [1/4] Loss: 0.19118 focal_loss 0.11749 dice_loss 0.07368 +Epoch [826/4000] Validation [2/4] Loss: 0.29921 focal_loss 0.13768 dice_loss 0.16153 +Epoch [826/4000] Validation [3/4] Loss: 0.12247 focal_loss 0.05231 dice_loss 0.07015 +Epoch [826/4000] Validation [4/4] Loss: 0.22092 focal_loss 0.10861 dice_loss 0.11232 +Epoch [826/4000] Validation metric {'Val/mean dice_metric': 0.9677287340164185, 'Val/mean miou_metric': 0.9464559555053711, 'Val/mean f1': 0.9680529236793518, 'Val/mean precision': 0.9626360535621643, 'Val/mean recall': 0.973531186580658, 'Val/mean hd95_metric': 6.4354400634765625} +Cheakpoint... +Epoch [826/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677287340164185, 'Val/mean miou_metric': 0.9464559555053711, 'Val/mean f1': 0.9680529236793518, 'Val/mean precision': 0.9626360535621643, 'Val/mean recall': 0.973531186580658, 'Val/mean hd95_metric': 6.4354400634765625} +Epoch [827/4000] Training [1/16] Loss: 0.01041 +Epoch [827/4000] Training [2/16] Loss: 0.01405 +Epoch [827/4000] Training [3/16] Loss: 0.01190 +Epoch [827/4000] Training [4/16] Loss: 0.01161 +Epoch [827/4000] Training [5/16] Loss: 0.01181 +Epoch [827/4000] Training [6/16] Loss: 0.01262 +Epoch [827/4000] Training [7/16] Loss: 0.01487 +Epoch [827/4000] Training [8/16] Loss: 0.02030 +Epoch [827/4000] Training [9/16] Loss: 0.01379 +Epoch [827/4000] Training [10/16] Loss: 0.05361 +Epoch [827/4000] Training [11/16] Loss: 0.01324 +Epoch [827/4000] Training [12/16] Loss: 0.01185 +Epoch [827/4000] Training [13/16] Loss: 0.01177 +Epoch [827/4000] Training [14/16] Loss: 0.01197 +Epoch [827/4000] Training [15/16] Loss: 0.01281 +Epoch [827/4000] Training [16/16] Loss: 0.01533 +Epoch [827/4000] Training metric {'Train/mean dice_metric': 0.990343451499939, 'Train/mean miou_metric': 0.9808667898178101, 'Train/mean f1': 0.9869261384010315, 'Train/mean precision': 0.9819482564926147, 'Train/mean recall': 0.9919546246528625, 'Train/mean hd95_metric': 1.2664412260055542} +Epoch [827/4000] Validation [1/4] Loss: 0.19793 focal_loss 0.12201 dice_loss 0.07592 +Epoch [827/4000] Validation [2/4] Loss: 0.23442 focal_loss 0.10389 dice_loss 0.13054 +Epoch [827/4000] Validation [3/4] Loss: 0.18196 focal_loss 0.10250 dice_loss 0.07945 +Epoch [827/4000] Validation [4/4] Loss: 0.43984 focal_loss 0.23807 dice_loss 0.20176 +Epoch [827/4000] Validation metric {'Val/mean dice_metric': 0.9676788449287415, 'Val/mean miou_metric': 0.9461261630058289, 'Val/mean f1': 0.967573881149292, 'Val/mean precision': 0.9637224078178406, 'Val/mean recall': 0.9714562296867371, 'Val/mean hd95_metric': 6.0929083824157715} +Cheakpoint... +Epoch [827/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676788449287415, 'Val/mean miou_metric': 0.9461261630058289, 'Val/mean f1': 0.967573881149292, 'Val/mean precision': 0.9637224078178406, 'Val/mean recall': 0.9714562296867371, 'Val/mean hd95_metric': 6.0929083824157715} +Epoch [828/4000] Training [1/16] Loss: 0.00988 +Epoch [828/4000] Training [2/16] Loss: 0.01416 +Epoch [828/4000] Training [3/16] Loss: 0.01180 +Epoch [828/4000] Training [4/16] Loss: 0.01031 +Epoch [828/4000] Training [5/16] Loss: 0.01235 +Epoch [828/4000] Training [6/16] Loss: 0.01553 +Epoch [828/4000] Training [7/16] Loss: 0.03033 +Epoch [828/4000] Training [8/16] Loss: 0.01263 +Epoch [828/4000] Training [9/16] Loss: 0.01190 +Epoch [828/4000] Training [10/16] Loss: 0.01282 +Epoch [828/4000] Training [11/16] Loss: 0.01353 +Epoch [828/4000] Training [12/16] Loss: 0.01081 +Epoch [828/4000] Training [13/16] Loss: 0.00989 +Epoch [828/4000] Training [14/16] Loss: 0.01397 +Epoch [828/4000] Training [15/16] Loss: 0.01233 +Epoch [828/4000] Training [16/16] Loss: 0.01329 +Epoch [828/4000] Training metric {'Train/mean dice_metric': 0.9904404878616333, 'Train/mean miou_metric': 0.9809174537658691, 'Train/mean f1': 0.9877251386642456, 'Train/mean precision': 0.983221709728241, 'Train/mean recall': 0.9922699928283691, 'Train/mean hd95_metric': 1.400010585784912} +Epoch [828/4000] Validation [1/4] Loss: 0.20816 focal_loss 0.13063 dice_loss 0.07753 +Epoch [828/4000] Validation [2/4] Loss: 0.25603 focal_loss 0.10532 dice_loss 0.15071 +Epoch [828/4000] Validation [3/4] Loss: 0.25098 focal_loss 0.14705 dice_loss 0.10393 +Epoch [828/4000] Validation [4/4] Loss: 0.27622 focal_loss 0.14663 dice_loss 0.12959 +Epoch [828/4000] Validation metric {'Val/mean dice_metric': 0.9663354754447937, 'Val/mean miou_metric': 0.9444038271903992, 'Val/mean f1': 0.9680832028388977, 'Val/mean precision': 0.9627313613891602, 'Val/mean recall': 0.9734949469566345, 'Val/mean hd95_metric': 6.744464874267578} +Cheakpoint... +Epoch [828/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9663354754447937, 'Val/mean miou_metric': 0.9444038271903992, 'Val/mean f1': 0.9680832028388977, 'Val/mean precision': 0.9627313613891602, 'Val/mean recall': 0.9734949469566345, 'Val/mean hd95_metric': 6.744464874267578} +Epoch [829/4000] Training [1/16] Loss: 0.01100 +Epoch [829/4000] Training [2/16] Loss: 0.02817 +Epoch [829/4000] Training [3/16] Loss: 0.01629 +Epoch [829/4000] Training [4/16] Loss: 0.01136 +Epoch [829/4000] Training [5/16] Loss: 0.01724 +Epoch [829/4000] Training [6/16] Loss: 0.01051 +Epoch [829/4000] Training [7/16] Loss: 0.01318 +Epoch [829/4000] Training [8/16] Loss: 0.00977 +Epoch [829/4000] Training [9/16] Loss: 0.01250 +Epoch [829/4000] Training [10/16] Loss: 0.01345 +Epoch [829/4000] Training [11/16] Loss: 0.01095 +Epoch [829/4000] Training [12/16] Loss: 0.01612 +Epoch [829/4000] Training [13/16] Loss: 0.01135 +Epoch [829/4000] Training [14/16] Loss: 0.01264 +Epoch [829/4000] Training [15/16] Loss: 0.01337 +Epoch [829/4000] Training [16/16] Loss: 0.01254 +Epoch [829/4000] Training metric {'Train/mean dice_metric': 0.9907138347625732, 'Train/mean miou_metric': 0.9814189076423645, 'Train/mean f1': 0.9874468445777893, 'Train/mean precision': 0.9830800890922546, 'Train/mean recall': 0.9918526411056519, 'Train/mean hd95_metric': 1.550532579421997} +Epoch [829/4000] Validation [1/4] Loss: 0.19024 focal_loss 0.12623 dice_loss 0.06401 +Epoch [829/4000] Validation [2/4] Loss: 0.21245 focal_loss 0.10034 dice_loss 0.11210 +Epoch [829/4000] Validation [3/4] Loss: 0.22239 focal_loss 0.12780 dice_loss 0.09459 +Epoch [829/4000] Validation [4/4] Loss: 0.21758 focal_loss 0.10824 dice_loss 0.10934 +Epoch [829/4000] Validation metric {'Val/mean dice_metric': 0.968151867389679, 'Val/mean miou_metric': 0.947335422039032, 'Val/mean f1': 0.9696181416511536, 'Val/mean precision': 0.9611546993255615, 'Val/mean recall': 0.9782318472862244, 'Val/mean hd95_metric': 6.706948757171631} +Cheakpoint... +Epoch [829/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968151867389679, 'Val/mean miou_metric': 0.947335422039032, 'Val/mean f1': 0.9696181416511536, 'Val/mean precision': 0.9611546993255615, 'Val/mean recall': 0.9782318472862244, 'Val/mean hd95_metric': 6.706948757171631} +Epoch [830/4000] Training [1/16] Loss: 0.01471 +Epoch [830/4000] Training [2/16] Loss: 0.01325 +Epoch [830/4000] Training [3/16] Loss: 0.01211 +Epoch [830/4000] Training [4/16] Loss: 0.01224 +Epoch [830/4000] Training [5/16] Loss: 0.01303 +Epoch [830/4000] Training [6/16] Loss: 0.01280 +Epoch [830/4000] Training [7/16] Loss: 0.01101 +Epoch [830/4000] Training [8/16] Loss: 0.00970 +Epoch [830/4000] Training [9/16] Loss: 0.03108 +Epoch [830/4000] Training [10/16] Loss: 0.01048 +Epoch [830/4000] Training [11/16] Loss: 0.01223 +Epoch [830/4000] Training [12/16] Loss: 0.01520 +Epoch [830/4000] Training [13/16] Loss: 0.01064 +Epoch [830/4000] Training [14/16] Loss: 0.00894 +Epoch [830/4000] Training [15/16] Loss: 0.01175 +Epoch [830/4000] Training [16/16] Loss: 0.02940 +Epoch [830/4000] Training metric {'Train/mean dice_metric': 0.9911841154098511, 'Train/mean miou_metric': 0.9823293089866638, 'Train/mean f1': 0.9877793788909912, 'Train/mean precision': 0.9830184578895569, 'Train/mean recall': 0.9925865530967712, 'Train/mean hd95_metric': 1.4427709579467773} +Epoch [830/4000] Validation [1/4] Loss: 0.18247 focal_loss 0.11465 dice_loss 0.06781 +Epoch [830/4000] Validation [2/4] Loss: 0.20722 focal_loss 0.09531 dice_loss 0.11191 +Epoch [830/4000] Validation [3/4] Loss: 0.10323 focal_loss 0.05336 dice_loss 0.04987 +Epoch [830/4000] Validation [4/4] Loss: 0.18669 focal_loss 0.08332 dice_loss 0.10337 +Epoch [830/4000] Validation metric {'Val/mean dice_metric': 0.970284104347229, 'Val/mean miou_metric': 0.950518012046814, 'Val/mean f1': 0.9716815948486328, 'Val/mean precision': 0.9667074680328369, 'Val/mean recall': 0.9767072796821594, 'Val/mean hd95_metric': 5.703098297119141} +Cheakpoint... +Epoch [830/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970284104347229, 'Val/mean miou_metric': 0.950518012046814, 'Val/mean f1': 0.9716815948486328, 'Val/mean precision': 0.9667074680328369, 'Val/mean recall': 0.9767072796821594, 'Val/mean hd95_metric': 5.703098297119141} +Epoch [831/4000] Training [1/16] Loss: 0.01322 +Epoch [831/4000] Training [2/16] Loss: 0.01159 +Epoch [831/4000] Training [3/16] Loss: 0.01283 +Epoch [831/4000] Training [4/16] Loss: 0.01424 +Epoch [831/4000] Training [5/16] Loss: 0.00936 +Epoch [831/4000] Training [6/16] Loss: 0.01460 +Epoch [831/4000] Training [7/16] Loss: 0.01253 +Epoch [831/4000] Training [8/16] Loss: 0.01295 +Epoch [831/4000] Training [9/16] Loss: 0.01076 +Epoch [831/4000] Training [10/16] Loss: 0.01713 +Epoch [831/4000] Training [11/16] Loss: 0.01252 +Epoch [831/4000] Training [12/16] Loss: 0.01481 +Epoch [831/4000] Training [13/16] Loss: 0.01184 +Epoch [831/4000] Training [14/16] Loss: 0.01938 +Epoch [831/4000] Training [15/16] Loss: 0.01177 +Epoch [831/4000] Training [16/16] Loss: 0.01310 +Epoch [831/4000] Training metric {'Train/mean dice_metric': 0.9908900260925293, 'Train/mean miou_metric': 0.9817425012588501, 'Train/mean f1': 0.9878906607627869, 'Train/mean precision': 0.9834998846054077, 'Train/mean recall': 0.9923208355903625, 'Train/mean hd95_metric': 1.258646845817566} +Epoch [831/4000] Validation [1/4] Loss: 0.19015 focal_loss 0.12148 dice_loss 0.06867 +Epoch [831/4000] Validation [2/4] Loss: 0.21642 focal_loss 0.09450 dice_loss 0.12192 +Epoch [831/4000] Validation [3/4] Loss: 0.21059 focal_loss 0.11886 dice_loss 0.09173 +Epoch [831/4000] Validation [4/4] Loss: 0.19912 focal_loss 0.09837 dice_loss 0.10075 +Epoch [831/4000] Validation metric {'Val/mean dice_metric': 0.9680891036987305, 'Val/mean miou_metric': 0.9473302960395813, 'Val/mean f1': 0.9694592952728271, 'Val/mean precision': 0.9614371657371521, 'Val/mean recall': 0.9776163101196289, 'Val/mean hd95_metric': 6.302267074584961} +Cheakpoint... +Epoch [831/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680891036987305, 'Val/mean miou_metric': 0.9473302960395813, 'Val/mean f1': 0.9694592952728271, 'Val/mean precision': 0.9614371657371521, 'Val/mean recall': 0.9776163101196289, 'Val/mean hd95_metric': 6.302267074584961} +Epoch [832/4000] Training [1/16] Loss: 0.00990 +Epoch [832/4000] Training [2/16] Loss: 0.01348 +Epoch [832/4000] Training [3/16] Loss: 0.01259 +Epoch [832/4000] Training [4/16] Loss: 0.00960 +Epoch [832/4000] Training [5/16] Loss: 0.01288 +Epoch [832/4000] Training [6/16] Loss: 0.01031 +Epoch [832/4000] Training [7/16] Loss: 0.01392 +Epoch [832/4000] Training [8/16] Loss: 0.01354 +Epoch [832/4000] Training [9/16] Loss: 0.01385 +Epoch [832/4000] Training [10/16] Loss: 0.01535 +Epoch [832/4000] Training [11/16] Loss: 0.01075 +Epoch [832/4000] Training [12/16] Loss: 0.01532 +Epoch [832/4000] Training [13/16] Loss: 0.01282 +Epoch [832/4000] Training [14/16] Loss: 0.01338 +Epoch [832/4000] Training [15/16] Loss: 0.00943 +Epoch [832/4000] Training [16/16] Loss: 0.01395 +Epoch [832/4000] Training metric {'Train/mean dice_metric': 0.9904292225837708, 'Train/mean miou_metric': 0.9809505939483643, 'Train/mean f1': 0.9874525666236877, 'Train/mean precision': 0.9828673601150513, 'Train/mean recall': 0.9920806884765625, 'Train/mean hd95_metric': 1.3140544891357422} +Epoch [832/4000] Validation [1/4] Loss: 0.19601 focal_loss 0.12433 dice_loss 0.07168 +Epoch [832/4000] Validation [2/4] Loss: 0.16749 focal_loss 0.06799 dice_loss 0.09950 +Epoch [832/4000] Validation [3/4] Loss: 0.11941 focal_loss 0.06072 dice_loss 0.05869 +Epoch [832/4000] Validation [4/4] Loss: 0.23961 focal_loss 0.11580 dice_loss 0.12381 +Epoch [832/4000] Validation metric {'Val/mean dice_metric': 0.9679098129272461, 'Val/mean miou_metric': 0.9467751383781433, 'Val/mean f1': 0.9694002270698547, 'Val/mean precision': 0.9622727036476135, 'Val/mean recall': 0.9766342043876648, 'Val/mean hd95_metric': 6.601335048675537} +Cheakpoint... +Epoch [832/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679098129272461, 'Val/mean miou_metric': 0.9467751383781433, 'Val/mean f1': 0.9694002270698547, 'Val/mean precision': 0.9622727036476135, 'Val/mean recall': 0.9766342043876648, 'Val/mean hd95_metric': 6.601335048675537} +Epoch [833/4000] Training [1/16] Loss: 0.01197 +Epoch [833/4000] Training [2/16] Loss: 0.01243 +Epoch [833/4000] Training [3/16] Loss: 0.01148 +Epoch [833/4000] Training [4/16] Loss: 0.01580 +Epoch [833/4000] Training [5/16] Loss: 0.02036 +Epoch [833/4000] Training [6/16] Loss: 0.01246 +Epoch [833/4000] Training [7/16] Loss: 0.01614 +Epoch [833/4000] Training [8/16] Loss: 0.01420 +Epoch [833/4000] Training [9/16] Loss: 0.01505 +Epoch [833/4000] Training [10/16] Loss: 0.01144 +Epoch [833/4000] Training [11/16] Loss: 0.01401 +Epoch [833/4000] Training [12/16] Loss: 0.01164 +Epoch [833/4000] Training [13/16] Loss: 0.02179 +Epoch [833/4000] Training [14/16] Loss: 0.01379 +Epoch [833/4000] Training [15/16] Loss: 0.01426 +Epoch [833/4000] Training [16/16] Loss: 0.01274 +Epoch [833/4000] Training metric {'Train/mean dice_metric': 0.9906970262527466, 'Train/mean miou_metric': 0.9813606142997742, 'Train/mean f1': 0.9875341057777405, 'Train/mean precision': 0.9827672243118286, 'Train/mean recall': 0.9923474788665771, 'Train/mean hd95_metric': 1.469374418258667} +Epoch [833/4000] Validation [1/4] Loss: 0.21798 focal_loss 0.13187 dice_loss 0.08611 +Epoch [833/4000] Validation [2/4] Loss: 0.29482 focal_loss 0.13630 dice_loss 0.15851 +Epoch [833/4000] Validation [3/4] Loss: 0.15585 focal_loss 0.06681 dice_loss 0.08904 +Epoch [833/4000] Validation [4/4] Loss: 0.25599 focal_loss 0.14736 dice_loss 0.10863 +Epoch [833/4000] Validation metric {'Val/mean dice_metric': 0.9674711227416992, 'Val/mean miou_metric': 0.9456674456596375, 'Val/mean f1': 0.9681366086006165, 'Val/mean precision': 0.9659721851348877, 'Val/mean recall': 0.9703106880187988, 'Val/mean hd95_metric': 6.384798526763916} +Cheakpoint... +Epoch [833/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674711227416992, 'Val/mean miou_metric': 0.9456674456596375, 'Val/mean f1': 0.9681366086006165, 'Val/mean precision': 0.9659721851348877, 'Val/mean recall': 0.9703106880187988, 'Val/mean hd95_metric': 6.384798526763916} +Epoch [834/4000] Training [1/16] Loss: 0.01071 +Epoch [834/4000] Training [2/16] Loss: 0.01180 +Epoch [834/4000] Training [3/16] Loss: 0.01284 +Epoch [834/4000] Training [4/16] Loss: 0.01372 +Epoch [834/4000] Training [5/16] Loss: 0.01350 +Epoch [834/4000] Training [6/16] Loss: 0.01322 +Epoch [834/4000] Training [7/16] Loss: 0.01593 +Epoch [834/4000] Training [8/16] Loss: 0.01051 +Epoch [834/4000] Training [9/16] Loss: 0.01812 +Epoch [834/4000] Training [10/16] Loss: 0.01298 +Epoch [834/4000] Training [11/16] Loss: 0.01459 +Epoch [834/4000] Training [12/16] Loss: 0.01093 +Epoch [834/4000] Training [13/16] Loss: 0.01378 +Epoch [834/4000] Training [14/16] Loss: 0.01090 +Epoch [834/4000] Training [15/16] Loss: 0.01369 +Epoch [834/4000] Training [16/16] Loss: 0.01531 +Epoch [834/4000] Training metric {'Train/mean dice_metric': 0.9907543659210205, 'Train/mean miou_metric': 0.9814679026603699, 'Train/mean f1': 0.9873524904251099, 'Train/mean precision': 0.9826121926307678, 'Train/mean recall': 0.9921387434005737, 'Train/mean hd95_metric': 1.2628891468048096} +Epoch [834/4000] Validation [1/4] Loss: 0.21541 focal_loss 0.13395 dice_loss 0.08146 +Epoch [834/4000] Validation [2/4] Loss: 0.20920 focal_loss 0.09262 dice_loss 0.11657 +Epoch [834/4000] Validation [3/4] Loss: 0.12573 focal_loss 0.05950 dice_loss 0.06622 +Epoch [834/4000] Validation [4/4] Loss: 0.25207 focal_loss 0.13084 dice_loss 0.12122 +Epoch [834/4000] Validation metric {'Val/mean dice_metric': 0.9701007604598999, 'Val/mean miou_metric': 0.9490066766738892, 'Val/mean f1': 0.9702761769294739, 'Val/mean precision': 0.966641366481781, 'Val/mean recall': 0.9739384055137634, 'Val/mean hd95_metric': 5.5006866455078125} +Cheakpoint... +Epoch [834/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701007604598999, 'Val/mean miou_metric': 0.9490066766738892, 'Val/mean f1': 0.9702761769294739, 'Val/mean precision': 0.966641366481781, 'Val/mean recall': 0.9739384055137634, 'Val/mean hd95_metric': 5.5006866455078125} +Epoch [835/4000] Training [1/16] Loss: 0.01440 +Epoch [835/4000] Training [2/16] Loss: 0.01880 +Epoch [835/4000] Training [3/16] Loss: 0.01305 +Epoch [835/4000] Training [4/16] Loss: 0.01764 +Epoch [835/4000] Training [5/16] Loss: 0.01920 +Epoch [835/4000] Training [6/16] Loss: 0.01963 +Epoch [835/4000] Training [7/16] Loss: 0.01110 +Epoch [835/4000] Training [8/16] Loss: 0.01215 +Epoch [835/4000] Training [9/16] Loss: 0.01468 +Epoch [835/4000] Training [10/16] Loss: 0.01382 +Epoch [835/4000] Training [11/16] Loss: 0.01822 +Epoch [835/4000] Training [12/16] Loss: 0.01796 +Epoch [835/4000] Training [13/16] Loss: 0.01425 +Epoch [835/4000] Training [14/16] Loss: 0.01890 +Epoch [835/4000] Training [15/16] Loss: 0.01320 +Epoch [835/4000] Training [16/16] Loss: 0.01012 +Epoch [835/4000] Training metric {'Train/mean dice_metric': 0.9897935390472412, 'Train/mean miou_metric': 0.9796231985092163, 'Train/mean f1': 0.9869018793106079, 'Train/mean precision': 0.9824146628379822, 'Train/mean recall': 0.9914302825927734, 'Train/mean hd95_metric': 1.3535408973693848} +Epoch [835/4000] Validation [1/4] Loss: 0.26950 focal_loss 0.17486 dice_loss 0.09464 +Epoch [835/4000] Validation [2/4] Loss: 0.36359 focal_loss 0.19072 dice_loss 0.17288 +Epoch [835/4000] Validation [3/4] Loss: 0.18703 focal_loss 0.09548 dice_loss 0.09155 +Epoch [835/4000] Validation [4/4] Loss: 0.24283 focal_loss 0.14089 dice_loss 0.10194 +Epoch [835/4000] Validation metric {'Val/mean dice_metric': 0.9666205644607544, 'Val/mean miou_metric': 0.944758415222168, 'Val/mean f1': 0.9677567481994629, 'Val/mean precision': 0.9664725065231323, 'Val/mean recall': 0.9690442681312561, 'Val/mean hd95_metric': 6.257835388183594} +Cheakpoint... +Epoch [835/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666205644607544, 'Val/mean miou_metric': 0.944758415222168, 'Val/mean f1': 0.9677567481994629, 'Val/mean precision': 0.9664725065231323, 'Val/mean recall': 0.9690442681312561, 'Val/mean hd95_metric': 6.257835388183594} +Epoch [836/4000] Training [1/16] Loss: 0.01214 +Epoch [836/4000] Training [2/16] Loss: 0.01033 +Epoch [836/4000] Training [3/16] Loss: 0.00981 +Epoch [836/4000] Training [4/16] Loss: 0.01128 +Epoch [836/4000] Training [5/16] Loss: 0.01235 +Epoch [836/4000] Training [6/16] Loss: 0.00929 +Epoch [836/4000] Training [7/16] Loss: 0.01727 +Epoch [836/4000] Training [8/16] Loss: 0.01025 +Epoch [836/4000] Training [9/16] Loss: 0.01684 +Epoch [836/4000] Training [10/16] Loss: 0.01389 +Epoch [836/4000] Training [11/16] Loss: 0.01229 +Epoch [836/4000] Training [12/16] Loss: 0.01977 +Epoch [836/4000] Training [13/16] Loss: 0.01211 +Epoch [836/4000] Training [14/16] Loss: 0.00957 +Epoch [836/4000] Training [15/16] Loss: 0.01213 +Epoch [836/4000] Training [16/16] Loss: 0.02088 +Epoch [836/4000] Training metric {'Train/mean dice_metric': 0.9905937910079956, 'Train/mean miou_metric': 0.9811995029449463, 'Train/mean f1': 0.9878291487693787, 'Train/mean precision': 0.9833139181137085, 'Train/mean recall': 0.9923861026763916, 'Train/mean hd95_metric': 1.2690839767456055} +Epoch [836/4000] Validation [1/4] Loss: 0.23292 focal_loss 0.14827 dice_loss 0.08466 +Epoch [836/4000] Validation [2/4] Loss: 0.24357 focal_loss 0.10358 dice_loss 0.13999 +Epoch [836/4000] Validation [3/4] Loss: 0.21548 focal_loss 0.11796 dice_loss 0.09752 +Epoch [836/4000] Validation [4/4] Loss: 0.28488 focal_loss 0.15914 dice_loss 0.12574 +Epoch [836/4000] Validation metric {'Val/mean dice_metric': 0.9672335386276245, 'Val/mean miou_metric': 0.9455105066299438, 'Val/mean f1': 0.9681211113929749, 'Val/mean precision': 0.9652870297431946, 'Val/mean recall': 0.970971941947937, 'Val/mean hd95_metric': 6.199173927307129} +Cheakpoint... +Epoch [836/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672335386276245, 'Val/mean miou_metric': 0.9455105066299438, 'Val/mean f1': 0.9681211113929749, 'Val/mean precision': 0.9652870297431946, 'Val/mean recall': 0.970971941947937, 'Val/mean hd95_metric': 6.199173927307129} +Epoch [837/4000] Training [1/16] Loss: 0.01374 +Epoch [837/4000] Training [2/16] Loss: 0.01265 +Epoch [837/4000] Training [3/16] Loss: 0.01066 +Epoch [837/4000] Training [4/16] Loss: 0.01197 +Epoch [837/4000] Training [5/16] Loss: 0.01480 +Epoch [837/4000] Training [6/16] Loss: 0.01466 +Epoch [837/4000] Training [7/16] Loss: 0.01150 +Epoch [837/4000] Training [8/16] Loss: 0.01350 +Epoch [837/4000] Training [9/16] Loss: 0.01186 +Epoch [837/4000] Training [10/16] Loss: 0.07669 +Epoch [837/4000] Training [11/16] Loss: 0.01488 +Epoch [837/4000] Training [12/16] Loss: 0.02231 +Epoch [837/4000] Training [13/16] Loss: 0.01323 +Epoch [837/4000] Training [14/16] Loss: 0.01396 +Epoch [837/4000] Training [15/16] Loss: 0.01261 +Epoch [837/4000] Training [16/16] Loss: 0.01127 +Epoch [837/4000] Training metric {'Train/mean dice_metric': 0.9900867938995361, 'Train/mean miou_metric': 0.9806198477745056, 'Train/mean f1': 0.987809419631958, 'Train/mean precision': 0.983422577381134, 'Train/mean recall': 0.992235541343689, 'Train/mean hd95_metric': 1.334923267364502} +Epoch [837/4000] Validation [1/4] Loss: 0.25011 focal_loss 0.16110 dice_loss 0.08901 +Epoch [837/4000] Validation [2/4] Loss: 0.20149 focal_loss 0.09643 dice_loss 0.10506 +Epoch [837/4000] Validation [3/4] Loss: 0.16132 focal_loss 0.08658 dice_loss 0.07473 +Epoch [837/4000] Validation [4/4] Loss: 0.18290 focal_loss 0.09031 dice_loss 0.09258 +Epoch [837/4000] Validation metric {'Val/mean dice_metric': 0.9701805114746094, 'Val/mean miou_metric': 0.9491115808486938, 'Val/mean f1': 0.970256507396698, 'Val/mean precision': 0.9663549661636353, 'Val/mean recall': 0.9741896986961365, 'Val/mean hd95_metric': 5.9794111251831055} +Cheakpoint... +Epoch [837/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701805114746094, 'Val/mean miou_metric': 0.9491115808486938, 'Val/mean f1': 0.970256507396698, 'Val/mean precision': 0.9663549661636353, 'Val/mean recall': 0.9741896986961365, 'Val/mean hd95_metric': 5.9794111251831055} +Epoch [838/4000] Training [1/16] Loss: 0.01031 +Epoch [838/4000] Training [2/16] Loss: 0.01458 +Epoch [838/4000] Training [3/16] Loss: 0.01593 +Epoch [838/4000] Training [4/16] Loss: 0.01009 +Epoch [838/4000] Training [5/16] Loss: 0.01318 +Epoch [838/4000] Training [6/16] Loss: 0.01372 +Epoch [838/4000] Training [7/16] Loss: 0.01530 +Epoch [838/4000] Training [8/16] Loss: 0.01261 +Epoch [838/4000] Training [9/16] Loss: 0.01350 +Epoch [838/4000] Training [10/16] Loss: 0.01516 +Epoch [838/4000] Training [11/16] Loss: 0.01384 +Epoch [838/4000] Training [12/16] Loss: 0.01710 +Epoch [838/4000] Training [13/16] Loss: 0.01730 +Epoch [838/4000] Training [14/16] Loss: 0.01101 +Epoch [838/4000] Training [15/16] Loss: 0.01710 +Epoch [838/4000] Training [16/16] Loss: 0.02150 +Epoch [838/4000] Training metric {'Train/mean dice_metric': 0.9904403686523438, 'Train/mean miou_metric': 0.9808571338653564, 'Train/mean f1': 0.9874362349510193, 'Train/mean precision': 0.982643187046051, 'Train/mean recall': 0.9922762513160706, 'Train/mean hd95_metric': 1.2654385566711426} +Epoch [838/4000] Validation [1/4] Loss: 0.27800 focal_loss 0.18231 dice_loss 0.09570 +Epoch [838/4000] Validation [2/4] Loss: 0.17614 focal_loss 0.07717 dice_loss 0.09897 +Epoch [838/4000] Validation [3/4] Loss: 0.16913 focal_loss 0.08256 dice_loss 0.08656 +Epoch [838/4000] Validation [4/4] Loss: 0.19991 focal_loss 0.10406 dice_loss 0.09584 +Epoch [838/4000] Validation metric {'Val/mean dice_metric': 0.9670448303222656, 'Val/mean miou_metric': 0.9456817507743835, 'Val/mean f1': 0.9683853983879089, 'Val/mean precision': 0.9630544781684875, 'Val/mean recall': 0.9737756252288818, 'Val/mean hd95_metric': 6.454355716705322} +Cheakpoint... +Epoch [838/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670448303222656, 'Val/mean miou_metric': 0.9456817507743835, 'Val/mean f1': 0.9683853983879089, 'Val/mean precision': 0.9630544781684875, 'Val/mean recall': 0.9737756252288818, 'Val/mean hd95_metric': 6.454355716705322} +Epoch [839/4000] Training [1/16] Loss: 0.01024 +Epoch [839/4000] Training [2/16] Loss: 0.01163 +Epoch [839/4000] Training [3/16] Loss: 0.01499 +Epoch [839/4000] Training [4/16] Loss: 0.00998 +Epoch [839/4000] Training [5/16] Loss: 0.01492 +Epoch [839/4000] Training [6/16] Loss: 0.00912 +Epoch [839/4000] Training [7/16] Loss: 0.00981 +Epoch [839/4000] Training [8/16] Loss: 0.01624 +Epoch [839/4000] Training [9/16] Loss: 0.01407 +Epoch [839/4000] Training [10/16] Loss: 0.01245 +Epoch [839/4000] Training [11/16] Loss: 0.01684 +Epoch [839/4000] Training [12/16] Loss: 0.01194 +Epoch [839/4000] Training [13/16] Loss: 0.01446 +Epoch [839/4000] Training [14/16] Loss: 0.01675 +Epoch [839/4000] Training [15/16] Loss: 0.01123 +Epoch [839/4000] Training [16/16] Loss: 0.01722 +Epoch [839/4000] Training metric {'Train/mean dice_metric': 0.9911474585533142, 'Train/mean miou_metric': 0.9822364449501038, 'Train/mean f1': 0.9873305559158325, 'Train/mean precision': 0.9822837114334106, 'Train/mean recall': 0.9924294948577881, 'Train/mean hd95_metric': 1.2341268062591553} +Epoch [839/4000] Validation [1/4] Loss: 0.30186 focal_loss 0.20223 dice_loss 0.09963 +Epoch [839/4000] Validation [2/4] Loss: 0.46548 focal_loss 0.25933 dice_loss 0.20616 +Epoch [839/4000] Validation [3/4] Loss: 0.16604 focal_loss 0.09276 dice_loss 0.07328 +Epoch [839/4000] Validation [4/4] Loss: 0.17014 focal_loss 0.07824 dice_loss 0.09189 +Epoch [839/4000] Validation metric {'Val/mean dice_metric': 0.9673131704330444, 'Val/mean miou_metric': 0.9467668533325195, 'Val/mean f1': 0.9678671360015869, 'Val/mean precision': 0.9656735062599182, 'Val/mean recall': 0.9700709581375122, 'Val/mean hd95_metric': 6.0726470947265625} +Cheakpoint... +Epoch [839/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673131704330444, 'Val/mean miou_metric': 0.9467668533325195, 'Val/mean f1': 0.9678671360015869, 'Val/mean precision': 0.9656735062599182, 'Val/mean recall': 0.9700709581375122, 'Val/mean hd95_metric': 6.0726470947265625} +Epoch [840/4000] Training [1/16] Loss: 0.01069 +Epoch [840/4000] Training [2/16] Loss: 0.01357 +Epoch [840/4000] Training [3/16] Loss: 0.01091 +Epoch [840/4000] Training [4/16] Loss: 0.01213 +Epoch [840/4000] Training [5/16] Loss: 0.01287 +Epoch [840/4000] Training [6/16] Loss: 0.01608 +Epoch [840/4000] Training [7/16] Loss: 0.01203 +Epoch [840/4000] Training [8/16] Loss: 0.01115 +Epoch [840/4000] Training [9/16] Loss: 0.01276 +Epoch [840/4000] Training [10/16] Loss: 0.01682 +Epoch [840/4000] Training [11/16] Loss: 0.02044 +Epoch [840/4000] Training [12/16] Loss: 0.01103 +Epoch [840/4000] Training [13/16] Loss: 0.01086 +Epoch [840/4000] Training [14/16] Loss: 0.01176 +Epoch [840/4000] Training [15/16] Loss: 0.01175 +Epoch [840/4000] Training [16/16] Loss: 0.01760 +Epoch [840/4000] Training metric {'Train/mean dice_metric': 0.9909729361534119, 'Train/mean miou_metric': 0.9819408655166626, 'Train/mean f1': 0.9880949854850769, 'Train/mean precision': 0.9834555983543396, 'Train/mean recall': 0.9927783012390137, 'Train/mean hd95_metric': 1.2793022394180298} +Epoch [840/4000] Validation [1/4] Loss: 0.27391 focal_loss 0.17837 dice_loss 0.09553 +Epoch [840/4000] Validation [2/4] Loss: 0.34458 focal_loss 0.18857 dice_loss 0.15601 +Epoch [840/4000] Validation [3/4] Loss: 0.14333 focal_loss 0.06797 dice_loss 0.07537 +Epoch [840/4000] Validation [4/4] Loss: 0.22097 focal_loss 0.11337 dice_loss 0.10759 +Epoch [840/4000] Validation metric {'Val/mean dice_metric': 0.9693681597709656, 'Val/mean miou_metric': 0.948922336101532, 'Val/mean f1': 0.970198392868042, 'Val/mean precision': 0.9667643308639526, 'Val/mean recall': 0.9736568331718445, 'Val/mean hd95_metric': 6.26462459564209} +Cheakpoint... +Epoch [840/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693681597709656, 'Val/mean miou_metric': 0.948922336101532, 'Val/mean f1': 0.970198392868042, 'Val/mean precision': 0.9667643308639526, 'Val/mean recall': 0.9736568331718445, 'Val/mean hd95_metric': 6.26462459564209} +Epoch [841/4000] Training [1/16] Loss: 0.01591 +Epoch [841/4000] Training [2/16] Loss: 0.01353 +Epoch [841/4000] Training [3/16] Loss: 0.01219 +Epoch [841/4000] Training [4/16] Loss: 0.01272 +Epoch [841/4000] Training [5/16] Loss: 0.01128 +Epoch [841/4000] Training [6/16] Loss: 0.01204 +Epoch [841/4000] Training [7/16] Loss: 0.01264 +Epoch [841/4000] Training [8/16] Loss: 0.01317 +Epoch [841/4000] Training [9/16] Loss: 0.01212 +Epoch [841/4000] Training [10/16] Loss: 0.01314 +Epoch [841/4000] Training [11/16] Loss: 0.00890 +Epoch [841/4000] Training [12/16] Loss: 0.02974 +Epoch [841/4000] Training [13/16] Loss: 0.02309 +Epoch [841/4000] Training [14/16] Loss: 0.01103 +Epoch [841/4000] Training [15/16] Loss: 0.01373 +Epoch [841/4000] Training [16/16] Loss: 0.01366 +Epoch [841/4000] Training metric {'Train/mean dice_metric': 0.9904798269271851, 'Train/mean miou_metric': 0.9809931516647339, 'Train/mean f1': 0.987787663936615, 'Train/mean precision': 0.9831374883651733, 'Train/mean recall': 0.9924820065498352, 'Train/mean hd95_metric': 1.3181025981903076} +Epoch [841/4000] Validation [1/4] Loss: 0.34038 focal_loss 0.23719 dice_loss 0.10319 +Epoch [841/4000] Validation [2/4] Loss: 0.28032 focal_loss 0.17073 dice_loss 0.10959 +Epoch [841/4000] Validation [3/4] Loss: 0.16636 focal_loss 0.07524 dice_loss 0.09112 +Epoch [841/4000] Validation [4/4] Loss: 0.26872 focal_loss 0.15112 dice_loss 0.11760 +Epoch [841/4000] Validation metric {'Val/mean dice_metric': 0.9677959680557251, 'Val/mean miou_metric': 0.9457393884658813, 'Val/mean f1': 0.9686657786369324, 'Val/mean precision': 0.96358722448349, 'Val/mean recall': 0.9737979769706726, 'Val/mean hd95_metric': 7.290606498718262} +Cheakpoint... +Epoch [841/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677959680557251, 'Val/mean miou_metric': 0.9457393884658813, 'Val/mean f1': 0.9686657786369324, 'Val/mean precision': 0.96358722448349, 'Val/mean recall': 0.9737979769706726, 'Val/mean hd95_metric': 7.290606498718262} +Epoch [842/4000] Training [1/16] Loss: 0.01218 +Epoch [842/4000] Training [2/16] Loss: 0.01368 +Epoch [842/4000] Training [3/16] Loss: 0.01059 +Epoch [842/4000] Training [4/16] Loss: 0.01193 +Epoch [842/4000] Training [5/16] Loss: 0.01241 +Epoch [842/4000] Training [6/16] Loss: 0.01318 +Epoch [842/4000] Training [7/16] Loss: 0.00837 +Epoch [842/4000] Training [8/16] Loss: 0.01475 +Epoch [842/4000] Training [9/16] Loss: 0.01294 +Epoch [842/4000] Training [10/16] Loss: 0.01147 +Epoch [842/4000] Training [11/16] Loss: 0.01189 +Epoch [842/4000] Training [12/16] Loss: 0.01638 +Epoch [842/4000] Training [13/16] Loss: 0.01384 +Epoch [842/4000] Training [14/16] Loss: 0.00979 +Epoch [842/4000] Training [15/16] Loss: 0.01143 +Epoch [842/4000] Training [16/16] Loss: 0.02090 +Epoch [842/4000] Training metric {'Train/mean dice_metric': 0.9909310340881348, 'Train/mean miou_metric': 0.9818635582923889, 'Train/mean f1': 0.9879620671272278, 'Train/mean precision': 0.9837997555732727, 'Train/mean recall': 0.9921596050262451, 'Train/mean hd95_metric': 1.3970707654953003} +Epoch [842/4000] Validation [1/4] Loss: 0.38459 focal_loss 0.27539 dice_loss 0.10919 +Epoch [842/4000] Validation [2/4] Loss: 0.29826 focal_loss 0.14536 dice_loss 0.15290 +Epoch [842/4000] Validation [3/4] Loss: 0.14197 focal_loss 0.07638 dice_loss 0.06559 +Epoch [842/4000] Validation [4/4] Loss: 0.35360 focal_loss 0.18089 dice_loss 0.17271 +Epoch [842/4000] Validation metric {'Val/mean dice_metric': 0.9683575630187988, 'Val/mean miou_metric': 0.9475212097167969, 'Val/mean f1': 0.9695637226104736, 'Val/mean precision': 0.9678736329078674, 'Val/mean recall': 0.9712596535682678, 'Val/mean hd95_metric': 6.042080879211426} +Cheakpoint... +Epoch [842/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683575630187988, 'Val/mean miou_metric': 0.9475212097167969, 'Val/mean f1': 0.9695637226104736, 'Val/mean precision': 0.9678736329078674, 'Val/mean recall': 0.9712596535682678, 'Val/mean hd95_metric': 6.042080879211426} +Epoch [843/4000] Training [1/16] Loss: 0.01418 +Epoch [843/4000] Training [2/16] Loss: 0.00936 +Epoch [843/4000] Training [3/16] Loss: 0.01472 +Epoch [843/4000] Training [4/16] Loss: 0.01257 +Epoch [843/4000] Training [5/16] Loss: 0.01244 +Epoch [843/4000] Training [6/16] Loss: 0.01155 +Epoch [843/4000] Training [7/16] Loss: 0.01108 +Epoch [843/4000] Training [8/16] Loss: 0.01822 +Epoch [843/4000] Training [9/16] Loss: 0.01127 +Epoch [843/4000] Training [10/16] Loss: 0.01337 +Epoch [843/4000] Training [11/16] Loss: 0.02026 +Epoch [843/4000] Training [12/16] Loss: 0.01366 +Epoch [843/4000] Training [13/16] Loss: 0.01170 +Epoch [843/4000] Training [14/16] Loss: 0.01236 +Epoch [843/4000] Training [15/16] Loss: 0.01069 +Epoch [843/4000] Training [16/16] Loss: 0.01289 +Epoch [843/4000] Training metric {'Train/mean dice_metric': 0.9910868406295776, 'Train/mean miou_metric': 0.9821707010269165, 'Train/mean f1': 0.9879661202430725, 'Train/mean precision': 0.9830114841461182, 'Train/mean recall': 0.9929709434509277, 'Train/mean hd95_metric': 1.2558104991912842} +Epoch [843/4000] Validation [1/4] Loss: 0.26365 focal_loss 0.16831 dice_loss 0.09534 +Epoch [843/4000] Validation [2/4] Loss: 0.33066 focal_loss 0.17043 dice_loss 0.16023 +Epoch [843/4000] Validation [3/4] Loss: 0.13309 focal_loss 0.07382 dice_loss 0.05927 +Epoch [843/4000] Validation [4/4] Loss: 0.25894 focal_loss 0.14010 dice_loss 0.11884 +Epoch [843/4000] Validation metric {'Val/mean dice_metric': 0.9668609499931335, 'Val/mean miou_metric': 0.9458158612251282, 'Val/mean f1': 0.9679851531982422, 'Val/mean precision': 0.9661304950714111, 'Val/mean recall': 0.9698468446731567, 'Val/mean hd95_metric': 6.426849365234375} +Cheakpoint... +Epoch [843/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668609499931335, 'Val/mean miou_metric': 0.9458158612251282, 'Val/mean f1': 0.9679851531982422, 'Val/mean precision': 0.9661304950714111, 'Val/mean recall': 0.9698468446731567, 'Val/mean hd95_metric': 6.426849365234375} +Epoch [844/4000] Training [1/16] Loss: 0.01633 +Epoch [844/4000] Training [2/16] Loss: 0.01563 +Epoch [844/4000] Training [3/16] Loss: 0.01265 +Epoch [844/4000] Training [4/16] Loss: 0.01109 +Epoch [844/4000] Training [5/16] Loss: 0.01326 +Epoch [844/4000] Training [6/16] Loss: 0.01173 +Epoch [844/4000] Training [7/16] Loss: 0.01131 +Epoch [844/4000] Training [8/16] Loss: 0.00935 +Epoch [844/4000] Training [9/16] Loss: 0.01396 +Epoch [844/4000] Training [10/16] Loss: 0.01395 +Epoch [844/4000] Training [11/16] Loss: 0.01286 +Epoch [844/4000] Training [12/16] Loss: 0.01540 +Epoch [844/4000] Training [13/16] Loss: 0.01304 +Epoch [844/4000] Training [14/16] Loss: 0.01233 +Epoch [844/4000] Training [15/16] Loss: 0.00970 +Epoch [844/4000] Training [16/16] Loss: 0.01607 +Epoch [844/4000] Training metric {'Train/mean dice_metric': 0.9908794164657593, 'Train/mean miou_metric': 0.9817129373550415, 'Train/mean f1': 0.9876843094825745, 'Train/mean precision': 0.9830945134162903, 'Train/mean recall': 0.9923170804977417, 'Train/mean hd95_metric': 1.3814326524734497} +Epoch [844/4000] Validation [1/4] Loss: 0.17216 focal_loss 0.10305 dice_loss 0.06911 +Epoch [844/4000] Validation [2/4] Loss: 0.19593 focal_loss 0.09670 dice_loss 0.09924 +Epoch [844/4000] Validation [3/4] Loss: 0.22872 focal_loss 0.12017 dice_loss 0.10856 +Epoch [844/4000] Validation [4/4] Loss: 0.20346 focal_loss 0.10591 dice_loss 0.09755 +Epoch [844/4000] Validation metric {'Val/mean dice_metric': 0.9672309756278992, 'Val/mean miou_metric': 0.9460946917533875, 'Val/mean f1': 0.9688209891319275, 'Val/mean precision': 0.9664703607559204, 'Val/mean recall': 0.9711831212043762, 'Val/mean hd95_metric': 6.123166561126709} +Cheakpoint... +Epoch [844/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672309756278992, 'Val/mean miou_metric': 0.9460946917533875, 'Val/mean f1': 0.9688209891319275, 'Val/mean precision': 0.9664703607559204, 'Val/mean recall': 0.9711831212043762, 'Val/mean hd95_metric': 6.123166561126709} +Epoch [845/4000] Training [1/16] Loss: 0.01386 +Epoch [845/4000] Training [2/16] Loss: 0.01110 +Epoch [845/4000] Training [3/16] Loss: 0.08736 +Epoch [845/4000] Training [4/16] Loss: 0.01103 +Epoch [845/4000] Training [5/16] Loss: 0.01482 +Epoch [845/4000] Training [6/16] Loss: 0.01525 +Epoch [845/4000] Training [7/16] Loss: 0.01375 +Epoch [845/4000] Training [8/16] Loss: 0.01477 +Epoch [845/4000] Training [9/16] Loss: 0.01096 +Epoch [845/4000] Training [10/16] Loss: 0.02043 +Epoch [845/4000] Training [11/16] Loss: 0.01733 +Epoch [845/4000] Training [12/16] Loss: 0.00972 +Epoch [845/4000] Training [13/16] Loss: 0.01119 +Epoch [845/4000] Training [14/16] Loss: 0.01402 +Epoch [845/4000] Training [15/16] Loss: 0.01180 +Epoch [845/4000] Training [16/16] Loss: 0.01436 +Epoch [845/4000] Training metric {'Train/mean dice_metric': 0.9885516166687012, 'Train/mean miou_metric': 0.9780652523040771, 'Train/mean f1': 0.9867098927497864, 'Train/mean precision': 0.982227623462677, 'Train/mean recall': 0.991233229637146, 'Train/mean hd95_metric': 1.7773172855377197} +Epoch [845/4000] Validation [1/4] Loss: 0.35954 focal_loss 0.24877 dice_loss 0.11077 +Epoch [845/4000] Validation [2/4] Loss: 0.42361 focal_loss 0.22832 dice_loss 0.19529 +Epoch [845/4000] Validation [3/4] Loss: 0.12477 focal_loss 0.06210 dice_loss 0.06267 +Epoch [845/4000] Validation [4/4] Loss: 0.16716 focal_loss 0.09210 dice_loss 0.07507 +Epoch [845/4000] Validation metric {'Val/mean dice_metric': 0.9654321670532227, 'Val/mean miou_metric': 0.9443655014038086, 'Val/mean f1': 0.9676032066345215, 'Val/mean precision': 0.9658665060997009, 'Val/mean recall': 0.9693461656570435, 'Val/mean hd95_metric': 6.648142337799072} +Cheakpoint... +Epoch [845/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654321670532227, 'Val/mean miou_metric': 0.9443655014038086, 'Val/mean f1': 0.9676032066345215, 'Val/mean precision': 0.9658665060997009, 'Val/mean recall': 0.9693461656570435, 'Val/mean hd95_metric': 6.648142337799072} +Epoch [846/4000] Training [1/16] Loss: 0.01454 +Epoch [846/4000] Training [2/16] Loss: 0.01154 +Epoch [846/4000] Training [3/16] Loss: 0.01132 +Epoch [846/4000] Training [4/16] Loss: 0.01204 +Epoch [846/4000] Training [5/16] Loss: 0.01530 +Epoch [846/4000] Training [6/16] Loss: 0.01189 +Epoch [846/4000] Training [7/16] Loss: 0.01313 +Epoch [846/4000] Training [8/16] Loss: 0.01414 +Epoch [846/4000] Training [9/16] Loss: 0.01125 +Epoch [846/4000] Training [10/16] Loss: 0.01119 +Epoch [846/4000] Training [11/16] Loss: 0.01336 +Epoch [846/4000] Training [12/16] Loss: 0.01333 +Epoch [846/4000] Training [13/16] Loss: 0.01111 +Epoch [846/4000] Training [14/16] Loss: 0.01591 +Epoch [846/4000] Training [15/16] Loss: 0.06140 +Epoch [846/4000] Training [16/16] Loss: 0.01295 +Epoch [846/4000] Training metric {'Train/mean dice_metric': 0.9901849031448364, 'Train/mean miou_metric': 0.9806826114654541, 'Train/mean f1': 0.9868590831756592, 'Train/mean precision': 0.9817243218421936, 'Train/mean recall': 0.992047905921936, 'Train/mean hd95_metric': 1.7648029327392578} +Epoch [846/4000] Validation [1/4] Loss: 0.33554 focal_loss 0.23118 dice_loss 0.10436 +Epoch [846/4000] Validation [2/4] Loss: 0.40339 focal_loss 0.21572 dice_loss 0.18768 +Epoch [846/4000] Validation [3/4] Loss: 0.12582 focal_loss 0.06488 dice_loss 0.06094 +Epoch [846/4000] Validation [4/4] Loss: 0.20281 focal_loss 0.09180 dice_loss 0.11101 +Epoch [846/4000] Validation metric {'Val/mean dice_metric': 0.9666754007339478, 'Val/mean miou_metric': 0.9456802606582642, 'Val/mean f1': 0.9671123623847961, 'Val/mean precision': 0.9660980105400085, 'Val/mean recall': 0.9681289196014404, 'Val/mean hd95_metric': 5.901771545410156} +Cheakpoint... +Epoch [846/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666754007339478, 'Val/mean miou_metric': 0.9456802606582642, 'Val/mean f1': 0.9671123623847961, 'Val/mean precision': 0.9660980105400085, 'Val/mean recall': 0.9681289196014404, 'Val/mean hd95_metric': 5.901771545410156} +Epoch [847/4000] Training [1/16] Loss: 0.01320 +Epoch [847/4000] Training [2/16] Loss: 0.01441 +Epoch [847/4000] Training [3/16] Loss: 0.01080 +Epoch [847/4000] Training [4/16] Loss: 0.01201 +Epoch [847/4000] Training [5/16] Loss: 0.01208 +Epoch [847/4000] Training [6/16] Loss: 0.01352 +Epoch [847/4000] Training [7/16] Loss: 0.01477 +Epoch [847/4000] Training [8/16] Loss: 0.01754 +Epoch [847/4000] Training [9/16] Loss: 0.00982 +Epoch [847/4000] Training [10/16] Loss: 0.01128 +Epoch [847/4000] Training [11/16] Loss: 0.01228 +Epoch [847/4000] Training [12/16] Loss: 0.01275 +Epoch [847/4000] Training [13/16] Loss: 0.01215 +Epoch [847/4000] Training [14/16] Loss: 0.01354 +Epoch [847/4000] Training [15/16] Loss: 0.01312 +Epoch [847/4000] Training [16/16] Loss: 0.00946 +Epoch [847/4000] Training metric {'Train/mean dice_metric': 0.9910386800765991, 'Train/mean miou_metric': 0.982037365436554, 'Train/mean f1': 0.987909734249115, 'Train/mean precision': 0.9829990267753601, 'Train/mean recall': 0.9928697347640991, 'Train/mean hd95_metric': 1.2544400691986084} +Epoch [847/4000] Validation [1/4] Loss: 0.44375 focal_loss 0.32012 dice_loss 0.12364 +Epoch [847/4000] Validation [2/4] Loss: 0.27761 focal_loss 0.13355 dice_loss 0.14406 +Epoch [847/4000] Validation [3/4] Loss: 0.11572 focal_loss 0.05270 dice_loss 0.06302 +Epoch [847/4000] Validation [4/4] Loss: 0.22287 focal_loss 0.13020 dice_loss 0.09267 +Epoch [847/4000] Validation metric {'Val/mean dice_metric': 0.9680631756782532, 'Val/mean miou_metric': 0.9473028182983398, 'Val/mean f1': 0.9690355658531189, 'Val/mean precision': 0.9660099148750305, 'Val/mean recall': 0.9720803499221802, 'Val/mean hd95_metric': 6.040839672088623} +Cheakpoint... +Epoch [847/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680631756782532, 'Val/mean miou_metric': 0.9473028182983398, 'Val/mean f1': 0.9690355658531189, 'Val/mean precision': 0.9660099148750305, 'Val/mean recall': 0.9720803499221802, 'Val/mean hd95_metric': 6.040839672088623} +Epoch [848/4000] Training [1/16] Loss: 0.01452 +Epoch [848/4000] Training [2/16] Loss: 0.01430 +Epoch [848/4000] Training [3/16] Loss: 0.01048 +Epoch [848/4000] Training [4/16] Loss: 0.01405 +Epoch [848/4000] Training [5/16] Loss: 0.01000 +Epoch [848/4000] Training [6/16] Loss: 0.01240 +Epoch [848/4000] Training [7/16] Loss: 0.01185 +Epoch [848/4000] Training [8/16] Loss: 0.01245 +Epoch [848/4000] Training [9/16] Loss: 0.01581 +Epoch [848/4000] Training [10/16] Loss: 0.01399 +Epoch [848/4000] Training [11/16] Loss: 0.01241 +Epoch [848/4000] Training [12/16] Loss: 0.01137 +Epoch [848/4000] Training [13/16] Loss: 0.01478 +Epoch [848/4000] Training [14/16] Loss: 0.01070 +Epoch [848/4000] Training [15/16] Loss: 0.01931 +Epoch [848/4000] Training [16/16] Loss: 0.01966 +Epoch [848/4000] Training metric {'Train/mean dice_metric': 0.9904884696006775, 'Train/mean miou_metric': 0.9809991121292114, 'Train/mean f1': 0.9864082336425781, 'Train/mean precision': 0.9811813235282898, 'Train/mean recall': 0.9916911721229553, 'Train/mean hd95_metric': 1.4615840911865234} +Epoch [848/4000] Validation [1/4] Loss: 0.17988 focal_loss 0.10846 dice_loss 0.07143 +Epoch [848/4000] Validation [2/4] Loss: 0.15594 focal_loss 0.05746 dice_loss 0.09848 +Epoch [848/4000] Validation [3/4] Loss: 0.10927 focal_loss 0.05494 dice_loss 0.05433 +Epoch [848/4000] Validation [4/4] Loss: 0.27129 focal_loss 0.12788 dice_loss 0.14341 +Epoch [848/4000] Validation metric {'Val/mean dice_metric': 0.9694827795028687, 'Val/mean miou_metric': 0.9483293294906616, 'Val/mean f1': 0.9699769020080566, 'Val/mean precision': 0.9658904075622559, 'Val/mean recall': 0.9740981459617615, 'Val/mean hd95_metric': 5.59142541885376} +Cheakpoint... +Epoch [848/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694827795028687, 'Val/mean miou_metric': 0.9483293294906616, 'Val/mean f1': 0.9699769020080566, 'Val/mean precision': 0.9658904075622559, 'Val/mean recall': 0.9740981459617615, 'Val/mean hd95_metric': 5.59142541885376} +Epoch [849/4000] Training [1/16] Loss: 0.01288 +Epoch [849/4000] Training [2/16] Loss: 0.00966 +Epoch [849/4000] Training [3/16] Loss: 0.01448 +Epoch [849/4000] Training [4/16] Loss: 0.01074 +Epoch [849/4000] Training [5/16] Loss: 0.01579 +Epoch [849/4000] Training [6/16] Loss: 0.01720 +Epoch [849/4000] Training [7/16] Loss: 0.01769 +Epoch [849/4000] Training [8/16] Loss: 0.01275 +Epoch [849/4000] Training [9/16] Loss: 0.01127 +Epoch [849/4000] Training [10/16] Loss: 0.01422 +Epoch [849/4000] Training [11/16] Loss: 0.01160 +Epoch [849/4000] Training [12/16] Loss: 0.01403 +Epoch [849/4000] Training [13/16] Loss: 0.01186 +Epoch [849/4000] Training [14/16] Loss: 0.01023 +Epoch [849/4000] Training [15/16] Loss: 0.01596 +Epoch [849/4000] Training [16/16] Loss: 0.01357 +Epoch [849/4000] Training metric {'Train/mean dice_metric': 0.9895473718643188, 'Train/mean miou_metric': 0.9794111251831055, 'Train/mean f1': 0.986885130405426, 'Train/mean precision': 0.98240065574646, 'Train/mean recall': 0.9914107918739319, 'Train/mean hd95_metric': 1.5445530414581299} +Epoch [849/4000] Validation [1/4] Loss: 0.19136 focal_loss 0.11879 dice_loss 0.07257 +Epoch [849/4000] Validation [2/4] Loss: 0.36410 focal_loss 0.18071 dice_loss 0.18339 +Epoch [849/4000] Validation [3/4] Loss: 0.13688 focal_loss 0.06817 dice_loss 0.06871 +Epoch [849/4000] Validation [4/4] Loss: 0.29323 focal_loss 0.16191 dice_loss 0.13133 +Epoch [849/4000] Validation metric {'Val/mean dice_metric': 0.9654413461685181, 'Val/mean miou_metric': 0.9439916610717773, 'Val/mean f1': 0.9676542282104492, 'Val/mean precision': 0.9611046314239502, 'Val/mean recall': 0.9742937684059143, 'Val/mean hd95_metric': 6.616029262542725} +Cheakpoint... +Epoch [849/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654413461685181, 'Val/mean miou_metric': 0.9439916610717773, 'Val/mean f1': 0.9676542282104492, 'Val/mean precision': 0.9611046314239502, 'Val/mean recall': 0.9742937684059143, 'Val/mean hd95_metric': 6.616029262542725} +Epoch [850/4000] Training [1/16] Loss: 0.00876 +Epoch [850/4000] Training [2/16] Loss: 0.01012 +Epoch [850/4000] Training [3/16] Loss: 0.01198 +Epoch [850/4000] Training [4/16] Loss: 0.01299 +Epoch [850/4000] Training [5/16] Loss: 0.01508 +Epoch [850/4000] Training [6/16] Loss: 0.01016 +Epoch [850/4000] Training [7/16] Loss: 0.01461 +Epoch [850/4000] Training [8/16] Loss: 0.01033 +Epoch [850/4000] Training [9/16] Loss: 0.01272 +Epoch [850/4000] Training [10/16] Loss: 0.00889 +Epoch [850/4000] Training [11/16] Loss: 0.01114 +Epoch [850/4000] Training [12/16] Loss: 0.01090 +Epoch [850/4000] Training [13/16] Loss: 0.01985 +Epoch [850/4000] Training [14/16] Loss: 0.01473 +Epoch [850/4000] Training [15/16] Loss: 0.01407 +Epoch [850/4000] Training [16/16] Loss: 0.01157 +Epoch [850/4000] Training metric {'Train/mean dice_metric': 0.9910551309585571, 'Train/mean miou_metric': 0.9820960164070129, 'Train/mean f1': 0.9880596399307251, 'Train/mean precision': 0.9835303425788879, 'Train/mean recall': 0.9926307797431946, 'Train/mean hd95_metric': 1.2377586364746094} +Epoch [850/4000] Validation [1/4] Loss: 0.20173 focal_loss 0.13499 dice_loss 0.06674 +Epoch [850/4000] Validation [2/4] Loss: 0.20855 focal_loss 0.10283 dice_loss 0.10573 +Epoch [850/4000] Validation [3/4] Loss: 0.26087 focal_loss 0.12654 dice_loss 0.13433 +Epoch [850/4000] Validation [4/4] Loss: 0.25094 focal_loss 0.13626 dice_loss 0.11467 +Epoch [850/4000] Validation metric {'Val/mean dice_metric': 0.9668291807174683, 'Val/mean miou_metric': 0.9461790919303894, 'Val/mean f1': 0.9685267210006714, 'Val/mean precision': 0.9608643054962158, 'Val/mean recall': 0.9763122797012329, 'Val/mean hd95_metric': 6.463646411895752} +Cheakpoint... +Epoch [850/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668291807174683, 'Val/mean miou_metric': 0.9461790919303894, 'Val/mean f1': 0.9685267210006714, 'Val/mean precision': 0.9608643054962158, 'Val/mean recall': 0.9763122797012329, 'Val/mean hd95_metric': 6.463646411895752} +Epoch [851/4000] Training [1/16] Loss: 0.00987 +Epoch [851/4000] Training [2/16] Loss: 0.01436 +Epoch [851/4000] Training [3/16] Loss: 0.01122 +Epoch [851/4000] Training [4/16] Loss: 0.01514 +Epoch [851/4000] Training [5/16] Loss: 0.01286 +Epoch [851/4000] Training [6/16] Loss: 0.01471 +Epoch [851/4000] Training [7/16] Loss: 0.01224 +Epoch [851/4000] Training [8/16] Loss: 0.01405 +Epoch [851/4000] Training [9/16] Loss: 0.01141 +Epoch [851/4000] Training [10/16] Loss: 0.01602 +Epoch [851/4000] Training [11/16] Loss: 0.01410 +Epoch [851/4000] Training [12/16] Loss: 0.01690 +Epoch [851/4000] Training [13/16] Loss: 0.01539 +Epoch [851/4000] Training [14/16] Loss: 0.01236 +Epoch [851/4000] Training [15/16] Loss: 0.01140 +Epoch [851/4000] Training [16/16] Loss: 0.01130 +Epoch [851/4000] Training metric {'Train/mean dice_metric': 0.9899353981018066, 'Train/mean miou_metric': 0.9803122282028198, 'Train/mean f1': 0.9871925115585327, 'Train/mean precision': 0.9824974536895752, 'Train/mean recall': 0.9919326305389404, 'Train/mean hd95_metric': 1.5834319591522217} +Epoch [851/4000] Validation [1/4] Loss: 0.28142 focal_loss 0.18813 dice_loss 0.09329 +Epoch [851/4000] Validation [2/4] Loss: 0.31591 focal_loss 0.15019 dice_loss 0.16572 +Epoch [851/4000] Validation [3/4] Loss: 0.19751 focal_loss 0.12198 dice_loss 0.07553 +Epoch [851/4000] Validation [4/4] Loss: 0.41332 focal_loss 0.27256 dice_loss 0.14076 +Epoch [851/4000] Validation metric {'Val/mean dice_metric': 0.9654733538627625, 'Val/mean miou_metric': 0.943368136882782, 'Val/mean f1': 0.9657050371170044, 'Val/mean precision': 0.9685621857643127, 'Val/mean recall': 0.9628646969795227, 'Val/mean hd95_metric': 6.9459075927734375} +Cheakpoint... +Epoch [851/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654733538627625, 'Val/mean miou_metric': 0.943368136882782, 'Val/mean f1': 0.9657050371170044, 'Val/mean precision': 0.9685621857643127, 'Val/mean recall': 0.9628646969795227, 'Val/mean hd95_metric': 6.9459075927734375} +Epoch [852/4000] Training [1/16] Loss: 0.01342 +Epoch [852/4000] Training [2/16] Loss: 0.01312 +Epoch [852/4000] Training [3/16] Loss: 0.01292 +Epoch [852/4000] Training [4/16] Loss: 0.01223 +Epoch [852/4000] Training [5/16] Loss: 0.01077 +Epoch [852/4000] Training [6/16] Loss: 0.01124 +Epoch [852/4000] Training [7/16] Loss: 0.01515 +Epoch [852/4000] Training [8/16] Loss: 0.01125 +Epoch [852/4000] Training [9/16] Loss: 0.01201 +Epoch [852/4000] Training [10/16] Loss: 0.01187 +Epoch [852/4000] Training [11/16] Loss: 0.01073 +Epoch [852/4000] Training [12/16] Loss: 0.01151 +Epoch [852/4000] Training [13/16] Loss: 0.01115 +Epoch [852/4000] Training [14/16] Loss: 0.01581 +Epoch [852/4000] Training [15/16] Loss: 0.01212 +Epoch [852/4000] Training [16/16] Loss: 0.01217 +Epoch [852/4000] Training metric {'Train/mean dice_metric': 0.9911371469497681, 'Train/mean miou_metric': 0.9821959733963013, 'Train/mean f1': 0.987678587436676, 'Train/mean precision': 0.9830808639526367, 'Train/mean recall': 0.9923195242881775, 'Train/mean hd95_metric': 1.297066569328308} +Epoch [852/4000] Validation [1/4] Loss: 0.15494 focal_loss 0.09548 dice_loss 0.05946 +Epoch [852/4000] Validation [2/4] Loss: 0.20783 focal_loss 0.11035 dice_loss 0.09748 +Epoch [852/4000] Validation [3/4] Loss: 0.23717 focal_loss 0.14777 dice_loss 0.08940 +Epoch [852/4000] Validation [4/4] Loss: 0.24078 focal_loss 0.13413 dice_loss 0.10664 +Epoch [852/4000] Validation metric {'Val/mean dice_metric': 0.9688781499862671, 'Val/mean miou_metric': 0.9479935765266418, 'Val/mean f1': 0.9687860012054443, 'Val/mean precision': 0.9641075134277344, 'Val/mean recall': 0.9735099673271179, 'Val/mean hd95_metric': 6.565401554107666} +Cheakpoint... +Epoch [852/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688781499862671, 'Val/mean miou_metric': 0.9479935765266418, 'Val/mean f1': 0.9687860012054443, 'Val/mean precision': 0.9641075134277344, 'Val/mean recall': 0.9735099673271179, 'Val/mean hd95_metric': 6.565401554107666} +Epoch [853/4000] Training [1/16] Loss: 0.01623 +Epoch [853/4000] Training [2/16] Loss: 0.01353 +Epoch [853/4000] Training [3/16] Loss: 0.01242 +Epoch [853/4000] Training [4/16] Loss: 0.01048 +Epoch [853/4000] Training [5/16] Loss: 0.01202 +Epoch [853/4000] Training [6/16] Loss: 0.01470 +Epoch [853/4000] Training [7/16] Loss: 0.01703 +Epoch [853/4000] Training [8/16] Loss: 0.01218 +Epoch [853/4000] Training [9/16] Loss: 0.01555 +Epoch [853/4000] Training [10/16] Loss: 0.01473 +Epoch [853/4000] Training [11/16] Loss: 0.01058 +Epoch [853/4000] Training [12/16] Loss: 0.01398 +Epoch [853/4000] Training [13/16] Loss: 0.01088 +Epoch [853/4000] Training [14/16] Loss: 0.01274 +Epoch [853/4000] Training [15/16] Loss: 0.01121 +Epoch [853/4000] Training [16/16] Loss: 0.01541 +Epoch [853/4000] Training metric {'Train/mean dice_metric': 0.9907089471817017, 'Train/mean miou_metric': 0.9814336895942688, 'Train/mean f1': 0.9874268770217896, 'Train/mean precision': 0.9827077388763428, 'Train/mean recall': 0.9921916127204895, 'Train/mean hd95_metric': 1.3934681415557861} +Epoch [853/4000] Validation [1/4] Loss: 0.18594 focal_loss 0.11945 dice_loss 0.06649 +Epoch [853/4000] Validation [2/4] Loss: 0.47368 focal_loss 0.25940 dice_loss 0.21428 +Epoch [853/4000] Validation [3/4] Loss: 0.21291 focal_loss 0.12815 dice_loss 0.08475 +Epoch [853/4000] Validation [4/4] Loss: 0.25940 focal_loss 0.14678 dice_loss 0.11262 +Epoch [853/4000] Validation metric {'Val/mean dice_metric': 0.9633691906929016, 'Val/mean miou_metric': 0.9427087903022766, 'Val/mean f1': 0.9670144319534302, 'Val/mean precision': 0.9656086564064026, 'Val/mean recall': 0.9684243202209473, 'Val/mean hd95_metric': 6.5578765869140625} +Cheakpoint... +Epoch [853/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633691906929016, 'Val/mean miou_metric': 0.9427087903022766, 'Val/mean f1': 0.9670144319534302, 'Val/mean precision': 0.9656086564064026, 'Val/mean recall': 0.9684243202209473, 'Val/mean hd95_metric': 6.5578765869140625} +Epoch [854/4000] Training [1/16] Loss: 0.01862 +Epoch [854/4000] Training [2/16] Loss: 0.01171 +Epoch [854/4000] Training [3/16] Loss: 0.01055 +Epoch [854/4000] Training [4/16] Loss: 0.01609 +Epoch [854/4000] Training [5/16] Loss: 0.01247 +Epoch [854/4000] Training [6/16] Loss: 0.01247 +Epoch [854/4000] Training [7/16] Loss: 0.01148 +Epoch [854/4000] Training [8/16] Loss: 0.01268 +Epoch [854/4000] Training [9/16] Loss: 0.01160 +Epoch [854/4000] Training [10/16] Loss: 0.01247 +Epoch [854/4000] Training [11/16] Loss: 0.01099 +Epoch [854/4000] Training [12/16] Loss: 0.01274 +Epoch [854/4000] Training [13/16] Loss: 0.01172 +Epoch [854/4000] Training [14/16] Loss: 0.01035 +Epoch [854/4000] Training [15/16] Loss: 0.01374 +Epoch [854/4000] Training [16/16] Loss: 0.01006 +Epoch [854/4000] Training metric {'Train/mean dice_metric': 0.9917346239089966, 'Train/mean miou_metric': 0.9833704233169556, 'Train/mean f1': 0.9879757165908813, 'Train/mean precision': 0.9831311702728271, 'Train/mean recall': 0.9928682446479797, 'Train/mean hd95_metric': 1.2550032138824463} +Epoch [854/4000] Validation [1/4] Loss: 0.18333 focal_loss 0.11642 dice_loss 0.06690 +Epoch [854/4000] Validation [2/4] Loss: 0.23169 focal_loss 0.10018 dice_loss 0.13151 +Epoch [854/4000] Validation [3/4] Loss: 0.12571 focal_loss 0.06758 dice_loss 0.05812 +Epoch [854/4000] Validation [4/4] Loss: 0.17600 focal_loss 0.08301 dice_loss 0.09299 +Epoch [854/4000] Validation metric {'Val/mean dice_metric': 0.9684622883796692, 'Val/mean miou_metric': 0.9489591717720032, 'Val/mean f1': 0.9704920649528503, 'Val/mean precision': 0.96537184715271, 'Val/mean recall': 0.975666880607605, 'Val/mean hd95_metric': 5.862465858459473} +Cheakpoint... +Epoch [854/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684622883796692, 'Val/mean miou_metric': 0.9489591717720032, 'Val/mean f1': 0.9704920649528503, 'Val/mean precision': 0.96537184715271, 'Val/mean recall': 0.975666880607605, 'Val/mean hd95_metric': 5.862465858459473} +Epoch [855/4000] Training [1/16] Loss: 0.01193 +Epoch [855/4000] Training [2/16] Loss: 0.01228 +Epoch [855/4000] Training [3/16] Loss: 0.01313 +Epoch [855/4000] Training [4/16] Loss: 0.01275 +Epoch [855/4000] Training [5/16] Loss: 0.00867 +Epoch [855/4000] Training [6/16] Loss: 0.01046 +Epoch [855/4000] Training [7/16] Loss: 0.01317 +Epoch [855/4000] Training [8/16] Loss: 0.01710 +Epoch [855/4000] Training [9/16] Loss: 0.01007 +Epoch [855/4000] Training [10/16] Loss: 0.01303 +Epoch [855/4000] Training [11/16] Loss: 0.01046 +Epoch [855/4000] Training [12/16] Loss: 0.01033 +Epoch [855/4000] Training [13/16] Loss: 0.01239 +Epoch [855/4000] Training [14/16] Loss: 0.01186 +Epoch [855/4000] Training [15/16] Loss: 0.01015 +Epoch [855/4000] Training [16/16] Loss: 0.01100 +Epoch [855/4000] Training metric {'Train/mean dice_metric': 0.991295576095581, 'Train/mean miou_metric': 0.9825654029846191, 'Train/mean f1': 0.9880500435829163, 'Train/mean precision': 0.983273983001709, 'Train/mean recall': 0.9928727149963379, 'Train/mean hd95_metric': 1.257977843284607} +Epoch [855/4000] Validation [1/4] Loss: 0.16060 focal_loss 0.09881 dice_loss 0.06178 +Epoch [855/4000] Validation [2/4] Loss: 0.44845 focal_loss 0.26281 dice_loss 0.18564 +Epoch [855/4000] Validation [3/4] Loss: 0.11414 focal_loss 0.05990 dice_loss 0.05425 +Epoch [855/4000] Validation [4/4] Loss: 0.24580 focal_loss 0.13861 dice_loss 0.10719 +Epoch [855/4000] Validation metric {'Val/mean dice_metric': 0.9667728543281555, 'Val/mean miou_metric': 0.947087287902832, 'Val/mean f1': 0.9695848822593689, 'Val/mean precision': 0.9645838141441345, 'Val/mean recall': 0.974638044834137, 'Val/mean hd95_metric': 5.919910907745361} +Cheakpoint... +Epoch [855/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667728543281555, 'Val/mean miou_metric': 0.947087287902832, 'Val/mean f1': 0.9695848822593689, 'Val/mean precision': 0.9645838141441345, 'Val/mean recall': 0.974638044834137, 'Val/mean hd95_metric': 5.919910907745361} +Epoch [856/4000] Training [1/16] Loss: 0.01174 +Epoch [856/4000] Training [2/16] Loss: 0.01089 +Epoch [856/4000] Training [3/16] Loss: 0.01098 +Epoch [856/4000] Training [4/16] Loss: 0.00863 +Epoch [856/4000] Training [5/16] Loss: 0.01320 +Epoch [856/4000] Training [6/16] Loss: 0.01301 +Epoch [856/4000] Training [7/16] Loss: 0.01223 +Epoch [856/4000] Training [8/16] Loss: 0.01278 +Epoch [856/4000] Training [9/16] Loss: 0.01089 +Epoch [856/4000] Training [10/16] Loss: 0.01112 +Epoch [856/4000] Training [11/16] Loss: 0.01777 +Epoch [856/4000] Training [12/16] Loss: 0.01166 +Epoch [856/4000] Training [13/16] Loss: 0.01142 +Epoch [856/4000] Training [14/16] Loss: 0.01034 +Epoch [856/4000] Training [15/16] Loss: 0.01648 +Epoch [856/4000] Training [16/16] Loss: 0.01253 +Epoch [856/4000] Training metric {'Train/mean dice_metric': 0.9914140701293945, 'Train/mean miou_metric': 0.9827682375907898, 'Train/mean f1': 0.9882937073707581, 'Train/mean precision': 0.9840447306632996, 'Train/mean recall': 0.9925795197486877, 'Train/mean hd95_metric': 1.188783884048462} +Epoch [856/4000] Validation [1/4] Loss: 0.27006 focal_loss 0.17271 dice_loss 0.09735 +Epoch [856/4000] Validation [2/4] Loss: 0.45437 focal_loss 0.27618 dice_loss 0.17819 +Epoch [856/4000] Validation [3/4] Loss: 0.15934 focal_loss 0.08555 dice_loss 0.07379 +Epoch [856/4000] Validation [4/4] Loss: 0.24243 focal_loss 0.14087 dice_loss 0.10155 +Epoch [856/4000] Validation metric {'Val/mean dice_metric': 0.9659878015518188, 'Val/mean miou_metric': 0.945921778678894, 'Val/mean f1': 0.966740608215332, 'Val/mean precision': 0.9650596976280212, 'Val/mean recall': 0.968427300453186, 'Val/mean hd95_metric': 5.625153541564941} +Cheakpoint... +Epoch [856/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659878015518188, 'Val/mean miou_metric': 0.945921778678894, 'Val/mean f1': 0.966740608215332, 'Val/mean precision': 0.9650596976280212, 'Val/mean recall': 0.968427300453186, 'Val/mean hd95_metric': 5.625153541564941} +Epoch [857/4000] Training [1/16] Loss: 0.00979 +Epoch [857/4000] Training [2/16] Loss: 0.00916 +Epoch [857/4000] Training [3/16] Loss: 0.01274 +Epoch [857/4000] Training [4/16] Loss: 0.01200 +Epoch [857/4000] Training [5/16] Loss: 0.01544 +Epoch [857/4000] Training [6/16] Loss: 0.01180 +Epoch [857/4000] Training [7/16] Loss: 0.09488 +Epoch [857/4000] Training [8/16] Loss: 0.01412 +Epoch [857/4000] Training [9/16] Loss: 0.01102 +Epoch [857/4000] Training [10/16] Loss: 0.01074 +Epoch [857/4000] Training [11/16] Loss: 0.01266 +Epoch [857/4000] Training [12/16] Loss: 0.01292 +Epoch [857/4000] Training [13/16] Loss: 0.00915 +Epoch [857/4000] Training [14/16] Loss: 0.01157 +Epoch [857/4000] Training [15/16] Loss: 0.01549 +Epoch [857/4000] Training [16/16] Loss: 0.01083 +Epoch [857/4000] Training metric {'Train/mean dice_metric': 0.9911612868309021, 'Train/mean miou_metric': 0.9827980399131775, 'Train/mean f1': 0.9881332516670227, 'Train/mean precision': 0.9833242297172546, 'Train/mean recall': 0.9929895997047424, 'Train/mean hd95_metric': 1.3453173637390137} +Epoch [857/4000] Validation [1/4] Loss: 0.19826 focal_loss 0.12415 dice_loss 0.07411 +Epoch [857/4000] Validation [2/4] Loss: 0.22155 focal_loss 0.10590 dice_loss 0.11566 +Epoch [857/4000] Validation [3/4] Loss: 0.12254 focal_loss 0.06436 dice_loss 0.05818 +Epoch [857/4000] Validation [4/4] Loss: 0.22588 focal_loss 0.10961 dice_loss 0.11626 +Epoch [857/4000] Validation metric {'Val/mean dice_metric': 0.9644214510917664, 'Val/mean miou_metric': 0.9443243145942688, 'Val/mean f1': 0.968172013759613, 'Val/mean precision': 0.968484103679657, 'Val/mean recall': 0.9678601026535034, 'Val/mean hd95_metric': 6.2648725509643555} +Cheakpoint... +Epoch [857/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644214510917664, 'Val/mean miou_metric': 0.9443243145942688, 'Val/mean f1': 0.968172013759613, 'Val/mean precision': 0.968484103679657, 'Val/mean recall': 0.9678601026535034, 'Val/mean hd95_metric': 6.2648725509643555} +Epoch [858/4000] Training [1/16] Loss: 0.01543 +Epoch [858/4000] Training [2/16] Loss: 0.01081 +Epoch [858/4000] Training [3/16] Loss: 0.01501 +Epoch [858/4000] Training [4/16] Loss: 0.01362 +Epoch [858/4000] Training [5/16] Loss: 0.01915 +Epoch [858/4000] Training [6/16] Loss: 0.01090 +Epoch [858/4000] Training [7/16] Loss: 0.01252 +Epoch [858/4000] Training [8/16] Loss: 0.01384 +Epoch [858/4000] Training [9/16] Loss: 0.01337 +Epoch [858/4000] Training [10/16] Loss: 0.01432 +Epoch [858/4000] Training [11/16] Loss: 0.01040 +Epoch [858/4000] Training [12/16] Loss: 0.01056 +Epoch [858/4000] Training [13/16] Loss: 0.01577 +Epoch [858/4000] Training [14/16] Loss: 0.01682 +Epoch [858/4000] Training [15/16] Loss: 0.01358 +Epoch [858/4000] Training [16/16] Loss: 0.00925 +Epoch [858/4000] Training metric {'Train/mean dice_metric': 0.9909776449203491, 'Train/mean miou_metric': 0.9819235801696777, 'Train/mean f1': 0.9879423975944519, 'Train/mean precision': 0.9834909439086914, 'Train/mean recall': 0.9924343228340149, 'Train/mean hd95_metric': 1.236581802368164} +Epoch [858/4000] Validation [1/4] Loss: 0.46211 focal_loss 0.33997 dice_loss 0.12214 +Epoch [858/4000] Validation [2/4] Loss: 0.32969 focal_loss 0.15615 dice_loss 0.17354 +Epoch [858/4000] Validation [3/4] Loss: 0.13146 focal_loss 0.07518 dice_loss 0.05628 +Epoch [858/4000] Validation [4/4] Loss: 0.26785 focal_loss 0.15898 dice_loss 0.10887 +Epoch [858/4000] Validation metric {'Val/mean dice_metric': 0.9645126461982727, 'Val/mean miou_metric': 0.9443888664245605, 'Val/mean f1': 0.9678477644920349, 'Val/mean precision': 0.9671190977096558, 'Val/mean recall': 0.96857750415802, 'Val/mean hd95_metric': 5.968852519989014} +Cheakpoint... +Epoch [858/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645126461982727, 'Val/mean miou_metric': 0.9443888664245605, 'Val/mean f1': 0.9678477644920349, 'Val/mean precision': 0.9671190977096558, 'Val/mean recall': 0.96857750415802, 'Val/mean hd95_metric': 5.968852519989014} +Epoch [859/4000] Training [1/16] Loss: 0.00814 +Epoch [859/4000] Training [2/16] Loss: 0.04919 +Epoch [859/4000] Training [3/16] Loss: 0.01242 +Epoch [859/4000] Training [4/16] Loss: 0.01129 +Epoch [859/4000] Training [5/16] Loss: 0.01661 +Epoch [859/4000] Training [6/16] Loss: 0.01696 +Epoch [859/4000] Training [7/16] Loss: 0.02049 +Epoch [859/4000] Training [8/16] Loss: 0.01109 +Epoch [859/4000] Training [9/16] Loss: 0.01737 +Epoch [859/4000] Training [10/16] Loss: 0.01711 +Epoch [859/4000] Training [11/16] Loss: 0.01320 +Epoch [859/4000] Training [12/16] Loss: 0.01730 +Epoch [859/4000] Training [13/16] Loss: 0.01187 +Epoch [859/4000] Training [14/16] Loss: 0.01293 +Epoch [859/4000] Training [15/16] Loss: 0.01167 +Epoch [859/4000] Training [16/16] Loss: 0.01165 +Epoch [859/4000] Training metric {'Train/mean dice_metric': 0.989761233329773, 'Train/mean miou_metric': 0.9797513484954834, 'Train/mean f1': 0.9864776730537415, 'Train/mean precision': 0.9813544750213623, 'Train/mean recall': 0.9916546940803528, 'Train/mean hd95_metric': 1.4692226648330688} +Epoch [859/4000] Validation [1/4] Loss: 0.23178 focal_loss 0.14691 dice_loss 0.08487 +Epoch [859/4000] Validation [2/4] Loss: 0.29097 focal_loss 0.13542 dice_loss 0.15554 +Epoch [859/4000] Validation [3/4] Loss: 0.27497 focal_loss 0.17716 dice_loss 0.09781 +Epoch [859/4000] Validation [4/4] Loss: 0.27558 focal_loss 0.17396 dice_loss 0.10162 +Epoch [859/4000] Validation metric {'Val/mean dice_metric': 0.9673738479614258, 'Val/mean miou_metric': 0.944766640663147, 'Val/mean f1': 0.9676731824874878, 'Val/mean precision': 0.9628852009773254, 'Val/mean recall': 0.9725090265274048, 'Val/mean hd95_metric': 6.942442417144775} +Cheakpoint... +Epoch [859/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673738479614258, 'Val/mean miou_metric': 0.944766640663147, 'Val/mean f1': 0.9676731824874878, 'Val/mean precision': 0.9628852009773254, 'Val/mean recall': 0.9725090265274048, 'Val/mean hd95_metric': 6.942442417144775} +Epoch [860/4000] Training [1/16] Loss: 0.01417 +Epoch [860/4000] Training [2/16] Loss: 0.01156 +Epoch [860/4000] Training [3/16] Loss: 0.02302 +Epoch [860/4000] Training [4/16] Loss: 0.01836 +Epoch [860/4000] Training [5/16] Loss: 0.01301 +Epoch [860/4000] Training [6/16] Loss: 0.01558 +Epoch [860/4000] Training [7/16] Loss: 0.01296 +Epoch [860/4000] Training [8/16] Loss: 0.02001 +Epoch [860/4000] Training [9/16] Loss: 0.04563 +Epoch [860/4000] Training [10/16] Loss: 0.01223 +Epoch [860/4000] Training [11/16] Loss: 0.01153 +Epoch [860/4000] Training [12/16] Loss: 0.01138 +Epoch [860/4000] Training [13/16] Loss: 0.01203 +Epoch [860/4000] Training [14/16] Loss: 0.01106 +Epoch [860/4000] Training [15/16] Loss: 0.01471 +Epoch [860/4000] Training [16/16] Loss: 0.01986 +Epoch [860/4000] Training metric {'Train/mean dice_metric': 0.9891613721847534, 'Train/mean miou_metric': 0.9785698056221008, 'Train/mean f1': 0.9850223064422607, 'Train/mean precision': 0.9790428876876831, 'Train/mean recall': 0.9910751581192017, 'Train/mean hd95_metric': 1.7415223121643066} +Epoch [860/4000] Validation [1/4] Loss: 0.28694 focal_loss 0.19373 dice_loss 0.09321 +Epoch [860/4000] Validation [2/4] Loss: 0.41627 focal_loss 0.17796 dice_loss 0.23831 +Epoch [860/4000] Validation [3/4] Loss: 0.10611 focal_loss 0.05315 dice_loss 0.05296 +Epoch [860/4000] Validation [4/4] Loss: 0.22426 focal_loss 0.11859 dice_loss 0.10566 +Epoch [860/4000] Validation metric {'Val/mean dice_metric': 0.9634267687797546, 'Val/mean miou_metric': 0.9406954050064087, 'Val/mean f1': 0.9655284881591797, 'Val/mean precision': 0.9592946171760559, 'Val/mean recall': 0.9718437790870667, 'Val/mean hd95_metric': 6.476803779602051} +Cheakpoint... +Epoch [860/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9634267687797546, 'Val/mean miou_metric': 0.9406954050064087, 'Val/mean f1': 0.9655284881591797, 'Val/mean precision': 0.9592946171760559, 'Val/mean recall': 0.9718437790870667, 'Val/mean hd95_metric': 6.476803779602051} +Epoch [861/4000] Training [1/16] Loss: 0.01118 +Epoch [861/4000] Training [2/16] Loss: 0.01111 +Epoch [861/4000] Training [3/16] Loss: 0.01375 +Epoch [861/4000] Training [4/16] Loss: 0.01279 +Epoch [861/4000] Training [5/16] Loss: 0.01583 +Epoch [861/4000] Training [6/16] Loss: 0.01271 +Epoch [861/4000] Training [7/16] Loss: 0.02154 +Epoch [861/4000] Training [8/16] Loss: 0.01412 +Epoch [861/4000] Training [9/16] Loss: 0.01972 +Epoch [861/4000] Training [10/16] Loss: 0.01780 +Epoch [861/4000] Training [11/16] Loss: 0.01369 +Epoch [861/4000] Training [12/16] Loss: 0.02124 +Epoch [861/4000] Training [13/16] Loss: 0.01060 +Epoch [861/4000] Training [14/16] Loss: 0.01154 +Epoch [861/4000] Training [15/16] Loss: 0.01894 +Epoch [861/4000] Training [16/16] Loss: 0.01804 +Epoch [861/4000] Training metric {'Train/mean dice_metric': 0.9859014749526978, 'Train/mean miou_metric': 0.9750887155532837, 'Train/mean f1': 0.9853110909461975, 'Train/mean precision': 0.979631245136261, 'Train/mean recall': 0.9910572171211243, 'Train/mean hd95_metric': 2.0322775840759277} +Epoch [861/4000] Validation [1/4] Loss: 0.18407 focal_loss 0.11370 dice_loss 0.07037 +Epoch [861/4000] Validation [2/4] Loss: 0.21219 focal_loss 0.09244 dice_loss 0.11976 +Epoch [861/4000] Validation [3/4] Loss: 0.12242 focal_loss 0.06874 dice_loss 0.05368 +Epoch [861/4000] Validation [4/4] Loss: 0.25545 focal_loss 0.14602 dice_loss 0.10943 +Epoch [861/4000] Validation metric {'Val/mean dice_metric': 0.96367347240448, 'Val/mean miou_metric': 0.9412827491760254, 'Val/mean f1': 0.9674761891365051, 'Val/mean precision': 0.9617208242416382, 'Val/mean recall': 0.9733007550239563, 'Val/mean hd95_metric': 7.314826965332031} +Cheakpoint... +Epoch [861/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96367347240448, 'Val/mean miou_metric': 0.9412827491760254, 'Val/mean f1': 0.9674761891365051, 'Val/mean precision': 0.9617208242416382, 'Val/mean recall': 0.9733007550239563, 'Val/mean hd95_metric': 7.314826965332031} +Epoch [862/4000] Training [1/16] Loss: 0.01410 +Epoch [862/4000] Training [2/16] Loss: 0.01625 +Epoch [862/4000] Training [3/16] Loss: 0.01791 +Epoch [862/4000] Training [4/16] Loss: 0.01379 +Epoch [862/4000] Training [5/16] Loss: 0.01201 +Epoch [862/4000] Training [6/16] Loss: 0.01724 +Epoch [862/4000] Training [7/16] Loss: 0.01616 +Epoch [862/4000] Training [8/16] Loss: 0.04733 +Epoch [862/4000] Training [9/16] Loss: 0.02125 +Epoch [862/4000] Training [10/16] Loss: 0.01515 +Epoch [862/4000] Training [11/16] Loss: 0.01566 +Epoch [862/4000] Training [12/16] Loss: 0.02006 +Epoch [862/4000] Training [13/16] Loss: 0.01197 +Epoch [862/4000] Training [14/16] Loss: 0.01766 +Epoch [862/4000] Training [15/16] Loss: 0.01506 +Epoch [862/4000] Training [16/16] Loss: 0.01227 +Epoch [862/4000] Training metric {'Train/mean dice_metric': 0.986972987651825, 'Train/mean miou_metric': 0.9745863676071167, 'Train/mean f1': 0.9845157861709595, 'Train/mean precision': 0.9805191159248352, 'Train/mean recall': 0.9885451197624207, 'Train/mean hd95_metric': 2.5743391513824463} +Epoch [862/4000] Validation [1/4] Loss: 0.31873 focal_loss 0.19311 dice_loss 0.12562 +Epoch [862/4000] Validation [2/4] Loss: 0.24455 focal_loss 0.10406 dice_loss 0.14049 +Epoch [862/4000] Validation [3/4] Loss: 0.14423 focal_loss 0.08373 dice_loss 0.06050 +Epoch [862/4000] Validation [4/4] Loss: 0.29549 focal_loss 0.18402 dice_loss 0.11147 +Epoch [862/4000] Validation metric {'Val/mean dice_metric': 0.9617841839790344, 'Val/mean miou_metric': 0.9372550249099731, 'Val/mean f1': 0.9645593166351318, 'Val/mean precision': 0.9666662812232971, 'Val/mean recall': 0.9624614715576172, 'Val/mean hd95_metric': 7.474886894226074} +Cheakpoint... +Epoch [862/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9618], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9617841839790344, 'Val/mean miou_metric': 0.9372550249099731, 'Val/mean f1': 0.9645593166351318, 'Val/mean precision': 0.9666662812232971, 'Val/mean recall': 0.9624614715576172, 'Val/mean hd95_metric': 7.474886894226074} +Epoch [863/4000] Training [1/16] Loss: 0.02129 +Epoch [863/4000] Training [2/16] Loss: 0.02829 +Epoch [863/4000] Training [3/16] Loss: 0.01082 +Epoch [863/4000] Training [4/16] Loss: 0.01646 +Epoch [863/4000] Training [5/16] Loss: 0.01485 +Epoch [863/4000] Training [6/16] Loss: 0.01879 +Epoch [863/4000] Training [7/16] Loss: 0.01832 +Epoch [863/4000] Training [8/16] Loss: 0.01523 +Epoch [863/4000] Training [9/16] Loss: 0.01312 +Epoch [863/4000] Training [10/16] Loss: 0.02065 +Epoch [863/4000] Training [11/16] Loss: 0.01313 +Epoch [863/4000] Training [12/16] Loss: 0.01374 +Epoch [863/4000] Training [13/16] Loss: 0.01180 +Epoch [863/4000] Training [14/16] Loss: 0.01800 +Epoch [863/4000] Training [15/16] Loss: 0.02893 +Epoch [863/4000] Training [16/16] Loss: 0.01803 +Epoch [863/4000] Training metric {'Train/mean dice_metric': 0.9879099130630493, 'Train/mean miou_metric': 0.9761366248130798, 'Train/mean f1': 0.9842097759246826, 'Train/mean precision': 0.980014979839325, 'Train/mean recall': 0.9884406924247742, 'Train/mean hd95_metric': 2.224520206451416} +Epoch [863/4000] Validation [1/4] Loss: 0.16550 focal_loss 0.10519 dice_loss 0.06031 +Epoch [863/4000] Validation [2/4] Loss: 0.20998 focal_loss 0.10556 dice_loss 0.10441 +Epoch [863/4000] Validation [3/4] Loss: 0.21080 focal_loss 0.11478 dice_loss 0.09602 +Epoch [863/4000] Validation [4/4] Loss: 0.26249 focal_loss 0.15380 dice_loss 0.10868 +Epoch [863/4000] Validation metric {'Val/mean dice_metric': 0.9627869725227356, 'Val/mean miou_metric': 0.9391945004463196, 'Val/mean f1': 0.9617776274681091, 'Val/mean precision': 0.9488597512245178, 'Val/mean recall': 0.9750519394874573, 'Val/mean hd95_metric': 8.745938301086426} +Cheakpoint... +Epoch [863/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9628], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9627869725227356, 'Val/mean miou_metric': 0.9391945004463196, 'Val/mean f1': 0.9617776274681091, 'Val/mean precision': 0.9488597512245178, 'Val/mean recall': 0.9750519394874573, 'Val/mean hd95_metric': 8.745938301086426} +Epoch [864/4000] Training [1/16] Loss: 0.01077 +Epoch [864/4000] Training [2/16] Loss: 0.01918 +Epoch [864/4000] Training [3/16] Loss: 0.01484 +Epoch [864/4000] Training [4/16] Loss: 0.01932 +Epoch [864/4000] Training [5/16] Loss: 0.01286 +Epoch [864/4000] Training [6/16] Loss: 0.01338 +Epoch [864/4000] Training [7/16] Loss: 0.12533 +Epoch [864/4000] Training [8/16] Loss: 0.01257 +Epoch [864/4000] Training [9/16] Loss: 0.01301 +Epoch [864/4000] Training [10/16] Loss: 0.02261 +Epoch [864/4000] Training [11/16] Loss: 0.01558 +Epoch [864/4000] Training [12/16] Loss: 0.01424 +Epoch [864/4000] Training [13/16] Loss: 0.01288 +Epoch [864/4000] Training [14/16] Loss: 0.01315 +Epoch [864/4000] Training [15/16] Loss: 0.01310 +Epoch [864/4000] Training [16/16] Loss: 0.01597 +Epoch [864/4000] Training metric {'Train/mean dice_metric': 0.9881910085678101, 'Train/mean miou_metric': 0.9774074554443359, 'Train/mean f1': 0.9844421148300171, 'Train/mean precision': 0.9788141250610352, 'Train/mean recall': 0.9901351928710938, 'Train/mean hd95_metric': 2.4970598220825195} +Epoch [864/4000] Validation [1/4] Loss: 0.21361 focal_loss 0.12974 dice_loss 0.08387 +Epoch [864/4000] Validation [2/4] Loss: 0.29657 focal_loss 0.13932 dice_loss 0.15724 +Epoch [864/4000] Validation [3/4] Loss: 0.23946 focal_loss 0.14197 dice_loss 0.09749 +Epoch [864/4000] Validation [4/4] Loss: 0.15864 focal_loss 0.07527 dice_loss 0.08338 +Epoch [864/4000] Validation metric {'Val/mean dice_metric': 0.9649739265441895, 'Val/mean miou_metric': 0.9418522119522095, 'Val/mean f1': 0.96558678150177, 'Val/mean precision': 0.9621665477752686, 'Val/mean recall': 0.9690313339233398, 'Val/mean hd95_metric': 7.946229457855225} +Cheakpoint... +Epoch [864/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649739265441895, 'Val/mean miou_metric': 0.9418522119522095, 'Val/mean f1': 0.96558678150177, 'Val/mean precision': 0.9621665477752686, 'Val/mean recall': 0.9690313339233398, 'Val/mean hd95_metric': 7.946229457855225} +Epoch [865/4000] Training [1/16] Loss: 0.01552 +Epoch [865/4000] Training [2/16] Loss: 0.02778 +Epoch [865/4000] Training [3/16] Loss: 0.01879 +Epoch [865/4000] Training [4/16] Loss: 0.01137 +Epoch [865/4000] Training [5/16] Loss: 0.01819 +Epoch [865/4000] Training [6/16] Loss: 0.01203 +Epoch [865/4000] Training [7/16] Loss: 0.01428 +Epoch [865/4000] Training [8/16] Loss: 0.01448 +Epoch [865/4000] Training [9/16] Loss: 0.01818 +Epoch [865/4000] Training [10/16] Loss: 0.01457 +Epoch [865/4000] Training [11/16] Loss: 0.01707 +Epoch [865/4000] Training [12/16] Loss: 0.01674 +Epoch [865/4000] Training [13/16] Loss: 0.01338 +Epoch [865/4000] Training [14/16] Loss: 0.01690 +Epoch [865/4000] Training [15/16] Loss: 0.01738 +Epoch [865/4000] Training [16/16] Loss: 0.01082 +Epoch [865/4000] Training metric {'Train/mean dice_metric': 0.9890088438987732, 'Train/mean miou_metric': 0.9784415364265442, 'Train/mean f1': 0.9860877394676208, 'Train/mean precision': 0.9811862707138062, 'Train/mean recall': 0.9910383820533752, 'Train/mean hd95_metric': 2.104231834411621} +Epoch [865/4000] Validation [1/4] Loss: 0.18418 focal_loss 0.10595 dice_loss 0.07823 +Epoch [865/4000] Validation [2/4] Loss: 0.33702 focal_loss 0.15608 dice_loss 0.18094 +Epoch [865/4000] Validation [3/4] Loss: 0.11996 focal_loss 0.05779 dice_loss 0.06217 +Epoch [865/4000] Validation [4/4] Loss: 0.18524 focal_loss 0.10202 dice_loss 0.08322 +Epoch [865/4000] Validation metric {'Val/mean dice_metric': 0.9659997820854187, 'Val/mean miou_metric': 0.9431778788566589, 'Val/mean f1': 0.9668866395950317, 'Val/mean precision': 0.9620335102081299, 'Val/mean recall': 0.9717889428138733, 'Val/mean hd95_metric': 7.228175163269043} +Cheakpoint... +Epoch [865/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659997820854187, 'Val/mean miou_metric': 0.9431778788566589, 'Val/mean f1': 0.9668866395950317, 'Val/mean precision': 0.9620335102081299, 'Val/mean recall': 0.9717889428138733, 'Val/mean hd95_metric': 7.228175163269043} +Epoch [866/4000] Training [1/16] Loss: 0.01186 +Epoch [866/4000] Training [2/16] Loss: 0.01783 +Epoch [866/4000] Training [3/16] Loss: 0.01754 +Epoch [866/4000] Training [4/16] Loss: 0.01511 +Epoch [866/4000] Training [5/16] Loss: 0.01734 +Epoch [866/4000] Training [6/16] Loss: 0.01825 +Epoch [866/4000] Training [7/16] Loss: 0.01511 +Epoch [866/4000] Training [8/16] Loss: 0.02079 +Epoch [866/4000] Training [9/16] Loss: 0.01657 +Epoch [866/4000] Training [10/16] Loss: 0.03080 +Epoch [866/4000] Training [11/16] Loss: 0.01436 +Epoch [866/4000] Training [12/16] Loss: 0.01954 +Epoch [866/4000] Training [13/16] Loss: 0.01477 +Epoch [866/4000] Training [14/16] Loss: 0.01081 +Epoch [866/4000] Training [15/16] Loss: 0.01346 +Epoch [866/4000] Training [16/16] Loss: 0.01261 +Epoch [866/4000] Training metric {'Train/mean dice_metric': 0.989359974861145, 'Train/mean miou_metric': 0.9787793159484863, 'Train/mean f1': 0.9860460162162781, 'Train/mean precision': 0.9816749095916748, 'Train/mean recall': 0.990456223487854, 'Train/mean hd95_metric': 1.576965093612671} +Epoch [866/4000] Validation [1/4] Loss: 0.49709 focal_loss 0.35216 dice_loss 0.14493 +Epoch [866/4000] Validation [2/4] Loss: 0.33212 focal_loss 0.13762 dice_loss 0.19450 +Epoch [866/4000] Validation [3/4] Loss: 0.16400 focal_loss 0.09253 dice_loss 0.07147 +Epoch [866/4000] Validation [4/4] Loss: 0.20059 focal_loss 0.09875 dice_loss 0.10184 +Epoch [866/4000] Validation metric {'Val/mean dice_metric': 0.9636988639831543, 'Val/mean miou_metric': 0.9401704668998718, 'Val/mean f1': 0.9634384512901306, 'Val/mean precision': 0.9616251587867737, 'Val/mean recall': 0.9652587175369263, 'Val/mean hd95_metric': 7.531302452087402} +Cheakpoint... +Epoch [866/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636988639831543, 'Val/mean miou_metric': 0.9401704668998718, 'Val/mean f1': 0.9634384512901306, 'Val/mean precision': 0.9616251587867737, 'Val/mean recall': 0.9652587175369263, 'Val/mean hd95_metric': 7.531302452087402} +Epoch [867/4000] Training [1/16] Loss: 0.01484 +Epoch [867/4000] Training [2/16] Loss: 0.01303 +Epoch [867/4000] Training [3/16] Loss: 0.02203 +Epoch [867/4000] Training [4/16] Loss: 0.01320 +Epoch [867/4000] Training [5/16] Loss: 0.01558 +Epoch [867/4000] Training [6/16] Loss: 0.01230 +Epoch [867/4000] Training [7/16] Loss: 0.02228 +Epoch [867/4000] Training [8/16] Loss: 0.01505 +Epoch [867/4000] Training [9/16] Loss: 0.01143 +Epoch [867/4000] Training [10/16] Loss: 0.01927 +Epoch [867/4000] Training [11/16] Loss: 0.01614 +Epoch [867/4000] Training [12/16] Loss: 0.01696 +Epoch [867/4000] Training [13/16] Loss: 0.01562 +Epoch [867/4000] Training [14/16] Loss: 0.01609 +Epoch [867/4000] Training [15/16] Loss: 0.01902 +Epoch [867/4000] Training [16/16] Loss: 0.06069 +Epoch [867/4000] Training metric {'Train/mean dice_metric': 0.988170325756073, 'Train/mean miou_metric': 0.9765723943710327, 'Train/mean f1': 0.9855663180351257, 'Train/mean precision': 0.9809555411338806, 'Train/mean recall': 0.9902206659317017, 'Train/mean hd95_metric': 2.4372806549072266} +Epoch [867/4000] Validation [1/4] Loss: 0.36790 focal_loss 0.25740 dice_loss 0.11050 +Epoch [867/4000] Validation [2/4] Loss: 0.34933 focal_loss 0.17489 dice_loss 0.17445 +Epoch [867/4000] Validation [3/4] Loss: 0.12483 focal_loss 0.06211 dice_loss 0.06272 +Epoch [867/4000] Validation [4/4] Loss: 0.12170 focal_loss 0.05284 dice_loss 0.06887 +Epoch [867/4000] Validation metric {'Val/mean dice_metric': 0.9629878997802734, 'Val/mean miou_metric': 0.9397886395454407, 'Val/mean f1': 0.9655663371086121, 'Val/mean precision': 0.9606227278709412, 'Val/mean recall': 0.9705610871315002, 'Val/mean hd95_metric': 7.731854438781738} +Cheakpoint... +Epoch [867/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629878997802734, 'Val/mean miou_metric': 0.9397886395454407, 'Val/mean f1': 0.9655663371086121, 'Val/mean precision': 0.9606227278709412, 'Val/mean recall': 0.9705610871315002, 'Val/mean hd95_metric': 7.731854438781738} +Epoch [868/4000] Training [1/16] Loss: 0.01123 +Epoch [868/4000] Training [2/16] Loss: 0.01953 +Epoch [868/4000] Training [3/16] Loss: 0.01626 +Epoch [868/4000] Training [4/16] Loss: 0.01575 +Epoch [868/4000] Training [5/16] Loss: 0.01291 +Epoch [868/4000] Training [6/16] Loss: 0.01889 +Epoch [868/4000] Training [7/16] Loss: 0.01254 +Epoch [868/4000] Training [8/16] Loss: 0.01247 +Epoch [868/4000] Training [9/16] Loss: 0.01970 +Epoch [868/4000] Training [10/16] Loss: 0.01360 +Epoch [868/4000] Training [11/16] Loss: 0.01385 +Epoch [868/4000] Training [12/16] Loss: 0.01253 +Epoch [868/4000] Training [13/16] Loss: 0.01551 +Epoch [868/4000] Training [14/16] Loss: 0.02198 +Epoch [868/4000] Training [15/16] Loss: 0.01493 +Epoch [868/4000] Training [16/16] Loss: 0.01739 +Epoch [868/4000] Training metric {'Train/mean dice_metric': 0.9885976314544678, 'Train/mean miou_metric': 0.9785104990005493, 'Train/mean f1': 0.9868056178092957, 'Train/mean precision': 0.9823164343833923, 'Train/mean recall': 0.9913361668586731, 'Train/mean hd95_metric': 1.5977208614349365} +Epoch [868/4000] Validation [1/4] Loss: 0.50752 focal_loss 0.38685 dice_loss 0.12068 +Epoch [868/4000] Validation [2/4] Loss: 0.40152 focal_loss 0.20658 dice_loss 0.19494 +Epoch [868/4000] Validation [3/4] Loss: 0.13769 focal_loss 0.06900 dice_loss 0.06869 +Epoch [868/4000] Validation [4/4] Loss: 0.22915 focal_loss 0.15111 dice_loss 0.07804 +Epoch [868/4000] Validation metric {'Val/mean dice_metric': 0.9629789590835571, 'Val/mean miou_metric': 0.9402977228164673, 'Val/mean f1': 0.9649412035942078, 'Val/mean precision': 0.9630513191223145, 'Val/mean recall': 0.9668384790420532, 'Val/mean hd95_metric': 7.0378923416137695} +Cheakpoint... +Epoch [868/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629789590835571, 'Val/mean miou_metric': 0.9402977228164673, 'Val/mean f1': 0.9649412035942078, 'Val/mean precision': 0.9630513191223145, 'Val/mean recall': 0.9668384790420532, 'Val/mean hd95_metric': 7.0378923416137695} +Epoch [869/4000] Training [1/16] Loss: 0.01422 +Epoch [869/4000] Training [2/16] Loss: 0.01398 +Epoch [869/4000] Training [3/16] Loss: 0.01701 +Epoch [869/4000] Training [4/16] Loss: 0.01094 +Epoch [869/4000] Training [5/16] Loss: 0.01108 +Epoch [869/4000] Training [6/16] Loss: 0.01416 +Epoch [869/4000] Training [7/16] Loss: 0.01344 +Epoch [869/4000] Training [8/16] Loss: 0.01620 +Epoch [869/4000] Training [9/16] Loss: 0.01255 +Epoch [869/4000] Training [10/16] Loss: 0.01529 +Epoch [869/4000] Training [11/16] Loss: 0.01304 +Epoch [869/4000] Training [12/16] Loss: 0.01157 +Epoch [869/4000] Training [13/16] Loss: 0.01096 +Epoch [869/4000] Training [14/16] Loss: 0.01481 +Epoch [869/4000] Training [15/16] Loss: 0.01893 +Epoch [869/4000] Training [16/16] Loss: 0.00916 +Epoch [869/4000] Training metric {'Train/mean dice_metric': 0.9895053505897522, 'Train/mean miou_metric': 0.9796271920204163, 'Train/mean f1': 0.9872321486473083, 'Train/mean precision': 0.9825260043144226, 'Train/mean recall': 0.9919836521148682, 'Train/mean hd95_metric': 1.3974086046218872} +Epoch [869/4000] Validation [1/4] Loss: 0.28870 focal_loss 0.19537 dice_loss 0.09333 +Epoch [869/4000] Validation [2/4] Loss: 0.22767 focal_loss 0.10902 dice_loss 0.11865 +Epoch [869/4000] Validation [3/4] Loss: 0.13910 focal_loss 0.07255 dice_loss 0.06655 +Epoch [869/4000] Validation [4/4] Loss: 0.21716 focal_loss 0.12969 dice_loss 0.08747 +Epoch [869/4000] Validation metric {'Val/mean dice_metric': 0.9666793942451477, 'Val/mean miou_metric': 0.9451671838760376, 'Val/mean f1': 0.9685030579566956, 'Val/mean precision': 0.9639506936073303, 'Val/mean recall': 0.973098635673523, 'Val/mean hd95_metric': 6.091700077056885} +Cheakpoint... +Epoch [869/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666793942451477, 'Val/mean miou_metric': 0.9451671838760376, 'Val/mean f1': 0.9685030579566956, 'Val/mean precision': 0.9639506936073303, 'Val/mean recall': 0.973098635673523, 'Val/mean hd95_metric': 6.091700077056885} +Epoch [870/4000] Training [1/16] Loss: 0.01403 +Epoch [870/4000] Training [2/16] Loss: 0.01260 +Epoch [870/4000] Training [3/16] Loss: 0.01314 +Epoch [870/4000] Training [4/16] Loss: 0.00935 +Epoch [870/4000] Training [5/16] Loss: 0.01155 +Epoch [870/4000] Training [6/16] Loss: 0.01253 +Epoch [870/4000] Training [7/16] Loss: 0.01190 +Epoch [870/4000] Training [8/16] Loss: 0.01371 +Epoch [870/4000] Training [9/16] Loss: 0.01144 +Epoch [870/4000] Training [10/16] Loss: 0.01339 +Epoch [870/4000] Training [11/16] Loss: 0.01213 +Epoch [870/4000] Training [12/16] Loss: 0.01235 +Epoch [870/4000] Training [13/16] Loss: 0.01195 +Epoch [870/4000] Training [14/16] Loss: 0.01358 +Epoch [870/4000] Training [15/16] Loss: 0.01402 +Epoch [870/4000] Training [16/16] Loss: 0.00991 +Epoch [870/4000] Training metric {'Train/mean dice_metric': 0.988881528377533, 'Train/mean miou_metric': 0.9793602824211121, 'Train/mean f1': 0.9873141050338745, 'Train/mean precision': 0.9828813076019287, 'Train/mean recall': 0.9917870163917542, 'Train/mean hd95_metric': 1.6414649486541748} +Epoch [870/4000] Validation [1/4] Loss: 0.36818 focal_loss 0.26116 dice_loss 0.10702 +Epoch [870/4000] Validation [2/4] Loss: 0.29935 focal_loss 0.13569 dice_loss 0.16365 +Epoch [870/4000] Validation [3/4] Loss: 0.14397 focal_loss 0.07307 dice_loss 0.07091 +Epoch [870/4000] Validation [4/4] Loss: 0.31765 focal_loss 0.19061 dice_loss 0.12705 +Epoch [870/4000] Validation metric {'Val/mean dice_metric': 0.9645471572875977, 'Val/mean miou_metric': 0.9432541131973267, 'Val/mean f1': 0.9678803086280823, 'Val/mean precision': 0.967025876045227, 'Val/mean recall': 0.9687361717224121, 'Val/mean hd95_metric': 7.020521640777588} +Cheakpoint... +Epoch [870/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645471572875977, 'Val/mean miou_metric': 0.9432541131973267, 'Val/mean f1': 0.9678803086280823, 'Val/mean precision': 0.967025876045227, 'Val/mean recall': 0.9687361717224121, 'Val/mean hd95_metric': 7.020521640777588} +Epoch [871/4000] Training [1/16] Loss: 0.01892 +Epoch [871/4000] Training [2/16] Loss: 0.01188 +Epoch [871/4000] Training [3/16] Loss: 0.00997 +Epoch [871/4000] Training [4/16] Loss: 0.01144 +Epoch [871/4000] Training [5/16] Loss: 0.02015 +Epoch [871/4000] Training [6/16] Loss: 0.02021 +Epoch [871/4000] Training [7/16] Loss: 0.00861 +Epoch [871/4000] Training [8/16] Loss: 0.01274 +Epoch [871/4000] Training [9/16] Loss: 0.01192 +Epoch [871/4000] Training [10/16] Loss: 0.01204 +Epoch [871/4000] Training [11/16] Loss: 0.00993 +Epoch [871/4000] Training [12/16] Loss: 0.01012 +Epoch [871/4000] Training [13/16] Loss: 0.01297 +Epoch [871/4000] Training [14/16] Loss: 0.01383 +Epoch [871/4000] Training [15/16] Loss: 0.01185 +Epoch [871/4000] Training [16/16] Loss: 0.01259 +Epoch [871/4000] Training metric {'Train/mean dice_metric': 0.9898761510848999, 'Train/mean miou_metric': 0.9804213047027588, 'Train/mean f1': 0.9873890280723572, 'Train/mean precision': 0.9824500679969788, 'Train/mean recall': 0.9923778772354126, 'Train/mean hd95_metric': 1.8489136695861816} +Epoch [871/4000] Validation [1/4] Loss: 0.25795 focal_loss 0.16539 dice_loss 0.09256 +Epoch [871/4000] Validation [2/4] Loss: 0.20375 focal_loss 0.09410 dice_loss 0.10965 +Epoch [871/4000] Validation [3/4] Loss: 0.13768 focal_loss 0.06997 dice_loss 0.06771 +Epoch [871/4000] Validation [4/4] Loss: 0.28346 focal_loss 0.16719 dice_loss 0.11627 +Epoch [871/4000] Validation metric {'Val/mean dice_metric': 0.9664662480354309, 'Val/mean miou_metric': 0.9448363184928894, 'Val/mean f1': 0.9687284231185913, 'Val/mean precision': 0.9650846719741821, 'Val/mean recall': 0.9723997116088867, 'Val/mean hd95_metric': 6.871016025543213} +Cheakpoint... +Epoch [871/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664662480354309, 'Val/mean miou_metric': 0.9448363184928894, 'Val/mean f1': 0.9687284231185913, 'Val/mean precision': 0.9650846719741821, 'Val/mean recall': 0.9723997116088867, 'Val/mean hd95_metric': 6.871016025543213} +Epoch [872/4000] Training [1/16] Loss: 0.01224 +Epoch [872/4000] Training [2/16] Loss: 0.01161 +Epoch [872/4000] Training [3/16] Loss: 0.00892 +Epoch [872/4000] Training [4/16] Loss: 0.00887 +Epoch [872/4000] Training [5/16] Loss: 0.01669 +Epoch [872/4000] Training [6/16] Loss: 0.01007 +Epoch [872/4000] Training [7/16] Loss: 0.01072 +Epoch [872/4000] Training [8/16] Loss: 0.01268 +Epoch [872/4000] Training [9/16] Loss: 0.02085 +Epoch [872/4000] Training [10/16] Loss: 0.01546 +Epoch [872/4000] Training [11/16] Loss: 0.01226 +Epoch [872/4000] Training [12/16] Loss: 0.01195 +Epoch [872/4000] Training [13/16] Loss: 0.01289 +Epoch [872/4000] Training [14/16] Loss: 0.01155 +Epoch [872/4000] Training [15/16] Loss: 0.02022 +Epoch [872/4000] Training [16/16] Loss: 0.01512 +Epoch [872/4000] Training metric {'Train/mean dice_metric': 0.9908802509307861, 'Train/mean miou_metric': 0.9817509651184082, 'Train/mean f1': 0.9873062372207642, 'Train/mean precision': 0.9826840162277222, 'Train/mean recall': 0.9919721484184265, 'Train/mean hd95_metric': 1.3198816776275635} +Epoch [872/4000] Validation [1/4] Loss: 0.15905 focal_loss 0.09194 dice_loss 0.06712 +Epoch [872/4000] Validation [2/4] Loss: 0.50947 focal_loss 0.27276 dice_loss 0.23672 +Epoch [872/4000] Validation [3/4] Loss: 0.14055 focal_loss 0.06481 dice_loss 0.07574 +Epoch [872/4000] Validation [4/4] Loss: 0.16663 focal_loss 0.07529 dice_loss 0.09133 +Epoch [872/4000] Validation metric {'Val/mean dice_metric': 0.9654601216316223, 'Val/mean miou_metric': 0.9436195492744446, 'Val/mean f1': 0.9659948945045471, 'Val/mean precision': 0.9569250345230103, 'Val/mean recall': 0.9752383232116699, 'Val/mean hd95_metric': 7.5475053787231445} +Cheakpoint... +Epoch [872/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654601216316223, 'Val/mean miou_metric': 0.9436195492744446, 'Val/mean f1': 0.9659948945045471, 'Val/mean precision': 0.9569250345230103, 'Val/mean recall': 0.9752383232116699, 'Val/mean hd95_metric': 7.5475053787231445} +Epoch [873/4000] Training [1/16] Loss: 0.01437 +Epoch [873/4000] Training [2/16] Loss: 0.01577 +Epoch [873/4000] Training [3/16] Loss: 0.01078 +Epoch [873/4000] Training [4/16] Loss: 0.01326 +Epoch [873/4000] Training [5/16] Loss: 0.00961 +Epoch [873/4000] Training [6/16] Loss: 0.00981 +Epoch [873/4000] Training [7/16] Loss: 0.01421 +Epoch [873/4000] Training [8/16] Loss: 0.00986 +Epoch [873/4000] Training [9/16] Loss: 0.01592 +Epoch [873/4000] Training [10/16] Loss: 0.02261 +Epoch [873/4000] Training [11/16] Loss: 0.01050 +Epoch [873/4000] Training [12/16] Loss: 0.01479 +Epoch [873/4000] Training [13/16] Loss: 0.01127 +Epoch [873/4000] Training [14/16] Loss: 0.00989 +Epoch [873/4000] Training [15/16] Loss: 0.01715 +Epoch [873/4000] Training [16/16] Loss: 0.00897 +Epoch [873/4000] Training metric {'Train/mean dice_metric': 0.9912424087524414, 'Train/mean miou_metric': 0.9824261665344238, 'Train/mean f1': 0.9880420565605164, 'Train/mean precision': 0.983604371547699, 'Train/mean recall': 0.9925199747085571, 'Train/mean hd95_metric': 1.2341668605804443} +Epoch [873/4000] Validation [1/4] Loss: 0.18831 focal_loss 0.11603 dice_loss 0.07228 +Epoch [873/4000] Validation [2/4] Loss: 0.32033 focal_loss 0.12474 dice_loss 0.19558 +Epoch [873/4000] Validation [3/4] Loss: 0.12095 focal_loss 0.05918 dice_loss 0.06177 +Epoch [873/4000] Validation [4/4] Loss: 0.20690 focal_loss 0.08760 dice_loss 0.11930 +Epoch [873/4000] Validation metric {'Val/mean dice_metric': 0.9674950838088989, 'Val/mean miou_metric': 0.9465219378471375, 'Val/mean f1': 0.9693251252174377, 'Val/mean precision': 0.9631099700927734, 'Val/mean recall': 0.9756209850311279, 'Val/mean hd95_metric': 6.548872470855713} +Cheakpoint... +Epoch [873/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674950838088989, 'Val/mean miou_metric': 0.9465219378471375, 'Val/mean f1': 0.9693251252174377, 'Val/mean precision': 0.9631099700927734, 'Val/mean recall': 0.9756209850311279, 'Val/mean hd95_metric': 6.548872470855713} +Epoch [874/4000] Training [1/16] Loss: 0.01493 +Epoch [874/4000] Training [2/16] Loss: 0.05248 +Epoch [874/4000] Training [3/16] Loss: 0.00911 +Epoch [874/4000] Training [4/16] Loss: 0.00955 +Epoch [874/4000] Training [5/16] Loss: 0.01207 +Epoch [874/4000] Training [6/16] Loss: 0.01346 +Epoch [874/4000] Training [7/16] Loss: 0.01237 +Epoch [874/4000] Training [8/16] Loss: 0.01273 +Epoch [874/4000] Training [9/16] Loss: 0.01385 +Epoch [874/4000] Training [10/16] Loss: 0.01425 +Epoch [874/4000] Training [11/16] Loss: 0.01250 +Epoch [874/4000] Training [12/16] Loss: 0.01290 +Epoch [874/4000] Training [13/16] Loss: 0.01061 +Epoch [874/4000] Training [14/16] Loss: 0.01331 +Epoch [874/4000] Training [15/16] Loss: 0.00962 +Epoch [874/4000] Training [16/16] Loss: 0.03510 +Epoch [874/4000] Training metric {'Train/mean dice_metric': 0.990485668182373, 'Train/mean miou_metric': 0.9809941053390503, 'Train/mean f1': 0.9873842597007751, 'Train/mean precision': 0.9824865460395813, 'Train/mean recall': 0.9923310875892639, 'Train/mean hd95_metric': 1.463040828704834} +Epoch [874/4000] Validation [1/4] Loss: 0.19590 focal_loss 0.12333 dice_loss 0.07257 +Epoch [874/4000] Validation [2/4] Loss: 0.26760 focal_loss 0.12346 dice_loss 0.14414 +Epoch [874/4000] Validation [3/4] Loss: 0.16293 focal_loss 0.08654 dice_loss 0.07639 +Epoch [874/4000] Validation [4/4] Loss: 0.19939 focal_loss 0.10775 dice_loss 0.09164 +Epoch [874/4000] Validation metric {'Val/mean dice_metric': 0.966923713684082, 'Val/mean miou_metric': 0.9464426040649414, 'Val/mean f1': 0.9694052338600159, 'Val/mean precision': 0.9611142873764038, 'Val/mean recall': 0.9778403043746948, 'Val/mean hd95_metric': 7.097357273101807} +Cheakpoint... +Epoch [874/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966923713684082, 'Val/mean miou_metric': 0.9464426040649414, 'Val/mean f1': 0.9694052338600159, 'Val/mean precision': 0.9611142873764038, 'Val/mean recall': 0.9778403043746948, 'Val/mean hd95_metric': 7.097357273101807} +Epoch [875/4000] Training [1/16] Loss: 0.01513 +Epoch [875/4000] Training [2/16] Loss: 0.01087 +Epoch [875/4000] Training [3/16] Loss: 0.01230 +Epoch [875/4000] Training [4/16] Loss: 0.01639 +Epoch [875/4000] Training [5/16] Loss: 0.01244 +Epoch [875/4000] Training [6/16] Loss: 0.01349 +Epoch [875/4000] Training [7/16] Loss: 0.01269 +Epoch [875/4000] Training [8/16] Loss: 0.01705 +Epoch [875/4000] Training [9/16] Loss: 0.01468 +Epoch [875/4000] Training [10/16] Loss: 0.01455 +Epoch [875/4000] Training [11/16] Loss: 0.01083 +Epoch [875/4000] Training [12/16] Loss: 0.01267 +Epoch [875/4000] Training [13/16] Loss: 0.04648 +Epoch [875/4000] Training [14/16] Loss: 0.01134 +Epoch [875/4000] Training [15/16] Loss: 0.01259 +Epoch [875/4000] Training [16/16] Loss: 0.01732 +Epoch [875/4000] Training metric {'Train/mean dice_metric': 0.9899158477783203, 'Train/mean miou_metric': 0.9800251722335815, 'Train/mean f1': 0.9874138832092285, 'Train/mean precision': 0.9827988147735596, 'Train/mean recall': 0.9920725226402283, 'Train/mean hd95_metric': 1.9007130861282349} +Epoch [875/4000] Validation [1/4] Loss: 0.18554 focal_loss 0.11971 dice_loss 0.06582 +Epoch [875/4000] Validation [2/4] Loss: 0.38049 focal_loss 0.19085 dice_loss 0.18964 +Epoch [875/4000] Validation [3/4] Loss: 0.12000 focal_loss 0.05897 dice_loss 0.06103 +Epoch [875/4000] Validation [4/4] Loss: 0.22885 focal_loss 0.09356 dice_loss 0.13529 +Epoch [875/4000] Validation metric {'Val/mean dice_metric': 0.9651287198066711, 'Val/mean miou_metric': 0.9435359835624695, 'Val/mean f1': 0.9680247902870178, 'Val/mean precision': 0.963645339012146, 'Val/mean recall': 0.9724442362785339, 'Val/mean hd95_metric': 7.218686580657959} +Cheakpoint... +Epoch [875/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651287198066711, 'Val/mean miou_metric': 0.9435359835624695, 'Val/mean f1': 0.9680247902870178, 'Val/mean precision': 0.963645339012146, 'Val/mean recall': 0.9724442362785339, 'Val/mean hd95_metric': 7.218686580657959} +Epoch [876/4000] Training [1/16] Loss: 0.00994 +Epoch [876/4000] Training [2/16] Loss: 0.01517 +Epoch [876/4000] Training [3/16] Loss: 0.01278 +Epoch [876/4000] Training [4/16] Loss: 0.01236 +Epoch [876/4000] Training [5/16] Loss: 0.01723 +Epoch [876/4000] Training [6/16] Loss: 0.01668 +Epoch [876/4000] Training [7/16] Loss: 0.01687 +Epoch [876/4000] Training [8/16] Loss: 0.01257 +Epoch [876/4000] Training [9/16] Loss: 0.00942 +Epoch [876/4000] Training [10/16] Loss: 0.01269 +Epoch [876/4000] Training [11/16] Loss: 0.01555 +Epoch [876/4000] Training [12/16] Loss: 0.01205 +Epoch [876/4000] Training [13/16] Loss: 0.01471 +Epoch [876/4000] Training [14/16] Loss: 0.01478 +Epoch [876/4000] Training [15/16] Loss: 0.01119 +Epoch [876/4000] Training [16/16] Loss: 0.01175 +Epoch [876/4000] Training metric {'Train/mean dice_metric': 0.9896830916404724, 'Train/mean miou_metric': 0.9800392985343933, 'Train/mean f1': 0.9875192642211914, 'Train/mean precision': 0.9829225540161133, 'Train/mean recall': 0.9921591281890869, 'Train/mean hd95_metric': 1.5853915214538574} +Epoch [876/4000] Validation [1/4] Loss: 0.25039 focal_loss 0.14793 dice_loss 0.10245 +Epoch [876/4000] Validation [2/4] Loss: 0.45790 focal_loss 0.27996 dice_loss 0.17794 +Epoch [876/4000] Validation [3/4] Loss: 0.16703 focal_loss 0.09288 dice_loss 0.07414 +Epoch [876/4000] Validation [4/4] Loss: 0.22020 focal_loss 0.11318 dice_loss 0.10702 +Epoch [876/4000] Validation metric {'Val/mean dice_metric': 0.965058445930481, 'Val/mean miou_metric': 0.9433363676071167, 'Val/mean f1': 0.9686782956123352, 'Val/mean precision': 0.9652342200279236, 'Val/mean recall': 0.9721468687057495, 'Val/mean hd95_metric': 6.7489914894104} +Cheakpoint... +Epoch [876/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965058445930481, 'Val/mean miou_metric': 0.9433363676071167, 'Val/mean f1': 0.9686782956123352, 'Val/mean precision': 0.9652342200279236, 'Val/mean recall': 0.9721468687057495, 'Val/mean hd95_metric': 6.7489914894104} +Epoch [877/4000] Training [1/16] Loss: 0.01023 +Epoch [877/4000] Training [2/16] Loss: 0.01329 +Epoch [877/4000] Training [3/16] Loss: 0.01570 +Epoch [877/4000] Training [4/16] Loss: 0.01719 +Epoch [877/4000] Training [5/16] Loss: 0.01190 +Epoch [877/4000] Training [6/16] Loss: 0.01700 +Epoch [877/4000] Training [7/16] Loss: 0.01244 +Epoch [877/4000] Training [8/16] Loss: 0.01155 +Epoch [877/4000] Training [9/16] Loss: 0.01655 +Epoch [877/4000] Training [10/16] Loss: 0.01365 +Epoch [877/4000] Training [11/16] Loss: 0.01249 +Epoch [877/4000] Training [12/16] Loss: 0.01469 +Epoch [877/4000] Training [13/16] Loss: 0.01350 +Epoch [877/4000] Training [14/16] Loss: 0.01135 +Epoch [877/4000] Training [15/16] Loss: 0.01704 +Epoch [877/4000] Training [16/16] Loss: 0.01264 +Epoch [877/4000] Training metric {'Train/mean dice_metric': 0.9885717034339905, 'Train/mean miou_metric': 0.9776971340179443, 'Train/mean f1': 0.9867847561836243, 'Train/mean precision': 0.9827645421028137, 'Train/mean recall': 0.9908379912376404, 'Train/mean hd95_metric': 2.1116538047790527} +Epoch [877/4000] Validation [1/4] Loss: 0.39582 focal_loss 0.28470 dice_loss 0.11113 +Epoch [877/4000] Validation [2/4] Loss: 0.37913 focal_loss 0.18248 dice_loss 0.19665 +Epoch [877/4000] Validation [3/4] Loss: 0.12049 focal_loss 0.06092 dice_loss 0.05956 +Epoch [877/4000] Validation [4/4] Loss: 0.18837 focal_loss 0.10161 dice_loss 0.08676 +Epoch [877/4000] Validation metric {'Val/mean dice_metric': 0.9650289416313171, 'Val/mean miou_metric': 0.9422332048416138, 'Val/mean f1': 0.9669457674026489, 'Val/mean precision': 0.9677215218544006, 'Val/mean recall': 0.9661715030670166, 'Val/mean hd95_metric': 7.352206230163574} +Cheakpoint... +Epoch [877/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650289416313171, 'Val/mean miou_metric': 0.9422332048416138, 'Val/mean f1': 0.9669457674026489, 'Val/mean precision': 0.9677215218544006, 'Val/mean recall': 0.9661715030670166, 'Val/mean hd95_metric': 7.352206230163574} +Epoch [878/4000] Training [1/16] Loss: 0.01446 +Epoch [878/4000] Training [2/16] Loss: 0.01119 +Epoch [878/4000] Training [3/16] Loss: 0.01188 +Epoch [878/4000] Training [4/16] Loss: 0.01410 +Epoch [878/4000] Training [5/16] Loss: 0.00928 +Epoch [878/4000] Training [6/16] Loss: 0.01398 +Epoch [878/4000] Training [7/16] Loss: 0.01439 +Epoch [878/4000] Training [8/16] Loss: 0.01376 +Epoch [878/4000] Training [9/16] Loss: 0.00943 +Epoch [878/4000] Training [10/16] Loss: 0.01429 +Epoch [878/4000] Training [11/16] Loss: 0.00912 +Epoch [878/4000] Training [12/16] Loss: 0.01620 +Epoch [878/4000] Training [13/16] Loss: 0.01210 +Epoch [878/4000] Training [14/16] Loss: 0.01074 +Epoch [878/4000] Training [15/16] Loss: 0.01514 +Epoch [878/4000] Training [16/16] Loss: 0.01221 +Epoch [878/4000] Training metric {'Train/mean dice_metric': 0.9905359148979187, 'Train/mean miou_metric': 0.9812875986099243, 'Train/mean f1': 0.9875980019569397, 'Train/mean precision': 0.982657790184021, 'Train/mean recall': 0.9925881624221802, 'Train/mean hd95_metric': 1.3332420587539673} +Epoch [878/4000] Validation [1/4] Loss: 0.46575 focal_loss 0.34949 dice_loss 0.11626 +Epoch [878/4000] Validation [2/4] Loss: 0.56157 focal_loss 0.32399 dice_loss 0.23758 +Epoch [878/4000] Validation [3/4] Loss: 0.17898 focal_loss 0.10556 dice_loss 0.07342 +Epoch [878/4000] Validation [4/4] Loss: 0.27963 focal_loss 0.15459 dice_loss 0.12505 +Epoch [878/4000] Validation metric {'Val/mean dice_metric': 0.9678975939750671, 'Val/mean miou_metric': 0.9466885328292847, 'Val/mean f1': 0.9690407514572144, 'Val/mean precision': 0.9662207961082458, 'Val/mean recall': 0.9718772172927856, 'Val/mean hd95_metric': 6.473811149597168} +Cheakpoint... +Epoch [878/4000] best acc:tensor([0.9706], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678975939750671, 'Val/mean miou_metric': 0.9466885328292847, 'Val/mean f1': 0.9690407514572144, 'Val/mean precision': 0.9662207961082458, 'Val/mean recall': 0.9718772172927856, 'Val/mean hd95_metric': 6.473811149597168} +Epoch [879/4000] Training [1/16] Loss: 0.01017 +Epoch [879/4000] Training [2/16] Loss: 0.01068 +Epoch [879/4000] Training [3/16] Loss: 0.00978 +Epoch [879/4000] Training [4/16] Loss: 0.00801 +Epoch [879/4000] Training [5/16] Loss: 0.01258 +Epoch [879/4000] Training [6/16] Loss: 0.00962 +Epoch [879/4000] Training [7/16] Loss: 0.01638 +Epoch [879/4000] Training [8/16] Loss: 0.01853 +Epoch [879/4000] Training [9/16] Loss: 0.01153 +Epoch [879/4000] Training [10/16] Loss: 0.01137 +Epoch [879/4000] Training [11/16] Loss: 0.01013 +Epoch [879/4000] Training [12/16] Loss: 0.01323 +Epoch [879/4000] Training [13/16] Loss: 0.01056 +Epoch [879/4000] Training [14/16] Loss: 0.01557 +Epoch [879/4000] Training [15/16] Loss: 0.01230 +Epoch [879/4000] Training [16/16] Loss: 0.01312 +Epoch [879/4000] Training metric {'Train/mean dice_metric': 0.9913071990013123, 'Train/mean miou_metric': 0.9825809597969055, 'Train/mean f1': 0.9881988763809204, 'Train/mean precision': 0.9836849570274353, 'Train/mean recall': 0.9927544593811035, 'Train/mean hd95_metric': 1.268676519393921} +Epoch [879/4000] Validation [1/4] Loss: 0.52309 focal_loss 0.40643 dice_loss 0.11666 +Epoch [879/4000] Validation [2/4] Loss: 0.19792 focal_loss 0.08789 dice_loss 0.11003 +Epoch [879/4000] Validation [3/4] Loss: 0.15158 focal_loss 0.08003 dice_loss 0.07155 +Epoch [879/4000] Validation [4/4] Loss: 0.19263 focal_loss 0.09914 dice_loss 0.09348 +Epoch [879/4000] Validation metric {'Val/mean dice_metric': 0.9709838628768921, 'Val/mean miou_metric': 0.950985312461853, 'Val/mean f1': 0.9709698557853699, 'Val/mean precision': 0.967910647392273, 'Val/mean recall': 0.9740484356880188, 'Val/mean hd95_metric': 5.701230049133301} +Cheakpoint... +Epoch [879/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709838628768921, 'Val/mean miou_metric': 0.950985312461853, 'Val/mean f1': 0.9709698557853699, 'Val/mean precision': 0.967910647392273, 'Val/mean recall': 0.9740484356880188, 'Val/mean hd95_metric': 5.701230049133301} +Epoch [880/4000] Training [1/16] Loss: 0.02286 +Epoch [880/4000] Training [2/16] Loss: 0.01048 +Epoch [880/4000] Training [3/16] Loss: 0.01263 +Epoch [880/4000] Training [4/16] Loss: 0.01456 +Epoch [880/4000] Training [5/16] Loss: 0.01456 +Epoch [880/4000] Training [6/16] Loss: 0.01296 +Epoch [880/4000] Training [7/16] Loss: 0.01399 +Epoch [880/4000] Training [8/16] Loss: 0.01363 +Epoch [880/4000] Training [9/16] Loss: 0.01202 +Epoch [880/4000] Training [10/16] Loss: 0.01264 +Epoch [880/4000] Training [11/16] Loss: 0.01427 +Epoch [880/4000] Training [12/16] Loss: 0.00945 +Epoch [880/4000] Training [13/16] Loss: 0.00890 +Epoch [880/4000] Training [14/16] Loss: 0.01145 +Epoch [880/4000] Training [15/16] Loss: 0.01299 +Epoch [880/4000] Training [16/16] Loss: 0.01219 +Epoch [880/4000] Training metric {'Train/mean dice_metric': 0.9908044934272766, 'Train/mean miou_metric': 0.9816358089447021, 'Train/mean f1': 0.9873541593551636, 'Train/mean precision': 0.9820907115936279, 'Train/mean recall': 0.9926742315292358, 'Train/mean hd95_metric': 1.5589607954025269} +Epoch [880/4000] Validation [1/4] Loss: 0.17373 focal_loss 0.10769 dice_loss 0.06604 +Epoch [880/4000] Validation [2/4] Loss: 0.22272 focal_loss 0.11516 dice_loss 0.10757 +Epoch [880/4000] Validation [3/4] Loss: 0.18757 focal_loss 0.09684 dice_loss 0.09073 +Epoch [880/4000] Validation [4/4] Loss: 0.24198 focal_loss 0.13922 dice_loss 0.10276 +Epoch [880/4000] Validation metric {'Val/mean dice_metric': 0.9692211151123047, 'Val/mean miou_metric': 0.9485000371932983, 'Val/mean f1': 0.9696183204650879, 'Val/mean precision': 0.9639304280281067, 'Val/mean recall': 0.9753736853599548, 'Val/mean hd95_metric': 6.230499267578125} +Cheakpoint... +Epoch [880/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692211151123047, 'Val/mean miou_metric': 0.9485000371932983, 'Val/mean f1': 0.9696183204650879, 'Val/mean precision': 0.9639304280281067, 'Val/mean recall': 0.9753736853599548, 'Val/mean hd95_metric': 6.230499267578125} +Epoch [881/4000] Training [1/16] Loss: 0.00928 +Epoch [881/4000] Training [2/16] Loss: 0.01423 +Epoch [881/4000] Training [3/16] Loss: 0.01417 +Epoch [881/4000] Training [4/16] Loss: 0.02179 +Epoch [881/4000] Training [5/16] Loss: 0.01312 +Epoch [881/4000] Training [6/16] Loss: 0.01373 +Epoch [881/4000] Training [7/16] Loss: 0.01207 +Epoch [881/4000] Training [8/16] Loss: 0.03023 +Epoch [881/4000] Training [9/16] Loss: 0.01243 +Epoch [881/4000] Training [10/16] Loss: 0.01685 +Epoch [881/4000] Training [11/16] Loss: 0.01868 +Epoch [881/4000] Training [12/16] Loss: 0.01188 +Epoch [881/4000] Training [13/16] Loss: 0.01300 +Epoch [881/4000] Training [14/16] Loss: 0.01306 +Epoch [881/4000] Training [15/16] Loss: 0.01062 +Epoch [881/4000] Training [16/16] Loss: 0.01858 +Epoch [881/4000] Training metric {'Train/mean dice_metric': 0.9900617599487305, 'Train/mean miou_metric': 0.980381965637207, 'Train/mean f1': 0.9874879717826843, 'Train/mean precision': 0.982719361782074, 'Train/mean recall': 0.9923030734062195, 'Train/mean hd95_metric': 1.4734174013137817} +Epoch [881/4000] Validation [1/4] Loss: 0.26834 focal_loss 0.15221 dice_loss 0.11613 +Epoch [881/4000] Validation [2/4] Loss: 0.25764 focal_loss 0.13535 dice_loss 0.12229 +Epoch [881/4000] Validation [3/4] Loss: 0.16110 focal_loss 0.08590 dice_loss 0.07520 +Epoch [881/4000] Validation [4/4] Loss: 0.24040 focal_loss 0.13726 dice_loss 0.10314 +Epoch [881/4000] Validation metric {'Val/mean dice_metric': 0.9639075994491577, 'Val/mean miou_metric': 0.9424210786819458, 'Val/mean f1': 0.9677844047546387, 'Val/mean precision': 0.9651257991790771, 'Val/mean recall': 0.9704578518867493, 'Val/mean hd95_metric': 6.618231296539307} +Cheakpoint... +Epoch [881/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9639], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639075994491577, 'Val/mean miou_metric': 0.9424210786819458, 'Val/mean f1': 0.9677844047546387, 'Val/mean precision': 0.9651257991790771, 'Val/mean recall': 0.9704578518867493, 'Val/mean hd95_metric': 6.618231296539307} +Epoch [882/4000] Training [1/16] Loss: 0.01666 +Epoch [882/4000] Training [2/16] Loss: 0.01517 +Epoch [882/4000] Training [3/16] Loss: 0.01228 +Epoch [882/4000] Training [4/16] Loss: 0.01140 +Epoch [882/4000] Training [5/16] Loss: 0.01326 +Epoch [882/4000] Training [6/16] Loss: 0.01100 +Epoch [882/4000] Training [7/16] Loss: 0.11395 +Epoch [882/4000] Training [8/16] Loss: 0.01741 +Epoch [882/4000] Training [9/16] Loss: 0.01218 +Epoch [882/4000] Training [10/16] Loss: 0.01334 +Epoch [882/4000] Training [11/16] Loss: 0.01077 +Epoch [882/4000] Training [12/16] Loss: 0.01441 +Epoch [882/4000] Training [13/16] Loss: 0.01367 +Epoch [882/4000] Training [14/16] Loss: 0.01176 +Epoch [882/4000] Training [15/16] Loss: 0.01380 +Epoch [882/4000] Training [16/16] Loss: 0.01096 +Epoch [882/4000] Training metric {'Train/mean dice_metric': 0.9895738363265991, 'Train/mean miou_metric': 0.9799866676330566, 'Train/mean f1': 0.9873212575912476, 'Train/mean precision': 0.9825903177261353, 'Train/mean recall': 0.9920979738235474, 'Train/mean hd95_metric': 1.6424415111541748} +Epoch [882/4000] Validation [1/4] Loss: 0.45068 focal_loss 0.30485 dice_loss 0.14583 +Epoch [882/4000] Validation [2/4] Loss: 0.36320 focal_loss 0.18222 dice_loss 0.18098 +Epoch [882/4000] Validation [3/4] Loss: 0.18642 focal_loss 0.09795 dice_loss 0.08847 +Epoch [882/4000] Validation [4/4] Loss: 0.42363 focal_loss 0.23325 dice_loss 0.19038 +Epoch [882/4000] Validation metric {'Val/mean dice_metric': 0.9635523557662964, 'Val/mean miou_metric': 0.9419156908988953, 'Val/mean f1': 0.9670698642730713, 'Val/mean precision': 0.9707581400871277, 'Val/mean recall': 0.9634095430374146, 'Val/mean hd95_metric': 6.889060974121094} +Cheakpoint... +Epoch [882/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9635523557662964, 'Val/mean miou_metric': 0.9419156908988953, 'Val/mean f1': 0.9670698642730713, 'Val/mean precision': 0.9707581400871277, 'Val/mean recall': 0.9634095430374146, 'Val/mean hd95_metric': 6.889060974121094} +Epoch [883/4000] Training [1/16] Loss: 0.01609 +Epoch [883/4000] Training [2/16] Loss: 0.01567 +Epoch [883/4000] Training [3/16] Loss: 0.01120 +Epoch [883/4000] Training [4/16] Loss: 0.01924 +Epoch [883/4000] Training [5/16] Loss: 0.01629 +Epoch [883/4000] Training [6/16] Loss: 0.01596 +Epoch [883/4000] Training [7/16] Loss: 0.01312 +Epoch [883/4000] Training [8/16] Loss: 0.01400 +Epoch [883/4000] Training [9/16] Loss: 0.01070 +Epoch [883/4000] Training [10/16] Loss: 0.01193 +Epoch [883/4000] Training [11/16] Loss: 0.01316 +Epoch [883/4000] Training [12/16] Loss: 0.01321 +Epoch [883/4000] Training [13/16] Loss: 0.01119 +Epoch [883/4000] Training [14/16] Loss: 0.01154 +Epoch [883/4000] Training [15/16] Loss: 0.01095 +Epoch [883/4000] Training [16/16] Loss: 0.01505 +Epoch [883/4000] Training metric {'Train/mean dice_metric': 0.990573525428772, 'Train/mean miou_metric': 0.9811553955078125, 'Train/mean f1': 0.9867479801177979, 'Train/mean precision': 0.9816313982009888, 'Train/mean recall': 0.9919183254241943, 'Train/mean hd95_metric': 1.6070661544799805} +Epoch [883/4000] Validation [1/4] Loss: 0.20211 focal_loss 0.11283 dice_loss 0.08928 +Epoch [883/4000] Validation [2/4] Loss: 0.28524 focal_loss 0.13986 dice_loss 0.14538 +Epoch [883/4000] Validation [3/4] Loss: 0.13400 focal_loss 0.07633 dice_loss 0.05766 +Epoch [883/4000] Validation [4/4] Loss: 0.26222 focal_loss 0.15567 dice_loss 0.10655 +Epoch [883/4000] Validation metric {'Val/mean dice_metric': 0.9700458645820618, 'Val/mean miou_metric': 0.949363112449646, 'Val/mean f1': 0.9706315994262695, 'Val/mean precision': 0.9663198590278625, 'Val/mean recall': 0.9749819040298462, 'Val/mean hd95_metric': 6.281507968902588} +Cheakpoint... +Epoch [883/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700458645820618, 'Val/mean miou_metric': 0.949363112449646, 'Val/mean f1': 0.9706315994262695, 'Val/mean precision': 0.9663198590278625, 'Val/mean recall': 0.9749819040298462, 'Val/mean hd95_metric': 6.281507968902588} +Epoch [884/4000] Training [1/16] Loss: 0.01064 +Epoch [884/4000] Training [2/16] Loss: 0.01702 +Epoch [884/4000] Training [3/16] Loss: 0.01254 +Epoch [884/4000] Training [4/16] Loss: 0.01064 +Epoch [884/4000] Training [5/16] Loss: 0.01184 +Epoch [884/4000] Training [6/16] Loss: 0.00965 +Epoch [884/4000] Training [7/16] Loss: 0.00917 +Epoch [884/4000] Training [8/16] Loss: 0.01163 +Epoch [884/4000] Training [9/16] Loss: 0.01058 +Epoch [884/4000] Training [10/16] Loss: 0.00859 +Epoch [884/4000] Training [11/16] Loss: 0.01267 +Epoch [884/4000] Training [12/16] Loss: 0.01186 +Epoch [884/4000] Training [13/16] Loss: 0.01143 +Epoch [884/4000] Training [14/16] Loss: 0.01263 +Epoch [884/4000] Training [15/16] Loss: 0.01236 +Epoch [884/4000] Training [16/16] Loss: 0.00967 +Epoch [884/4000] Training metric {'Train/mean dice_metric': 0.9918749332427979, 'Train/mean miou_metric': 0.9837130308151245, 'Train/mean f1': 0.9885501861572266, 'Train/mean precision': 0.9841476082801819, 'Train/mean recall': 0.9929922819137573, 'Train/mean hd95_metric': 1.4397464990615845} +Epoch [884/4000] Validation [1/4] Loss: 0.16961 focal_loss 0.10319 dice_loss 0.06641 +Epoch [884/4000] Validation [2/4] Loss: 0.24004 focal_loss 0.11163 dice_loss 0.12841 +Epoch [884/4000] Validation [3/4] Loss: 0.14319 focal_loss 0.08523 dice_loss 0.05796 +Epoch [884/4000] Validation [4/4] Loss: 0.27310 focal_loss 0.13044 dice_loss 0.14266 +Epoch [884/4000] Validation metric {'Val/mean dice_metric': 0.9701930284500122, 'Val/mean miou_metric': 0.9503920674324036, 'Val/mean f1': 0.9721240401268005, 'Val/mean precision': 0.9651307463645935, 'Val/mean recall': 0.979219377040863, 'Val/mean hd95_metric': 6.714062690734863} +Cheakpoint... +Epoch [884/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701930284500122, 'Val/mean miou_metric': 0.9503920674324036, 'Val/mean f1': 0.9721240401268005, 'Val/mean precision': 0.9651307463645935, 'Val/mean recall': 0.979219377040863, 'Val/mean hd95_metric': 6.714062690734863} +Epoch [885/4000] Training [1/16] Loss: 0.01075 +Epoch [885/4000] Training [2/16] Loss: 0.03339 +Epoch [885/4000] Training [3/16] Loss: 0.01582 +Epoch [885/4000] Training [4/16] Loss: 0.01257 +Epoch [885/4000] Training [5/16] Loss: 0.01186 +Epoch [885/4000] Training [6/16] Loss: 0.01391 +Epoch [885/4000] Training [7/16] Loss: 0.01293 +Epoch [885/4000] Training [8/16] Loss: 0.01385 +Epoch [885/4000] Training [9/16] Loss: 0.01100 +Epoch [885/4000] Training [10/16] Loss: 0.01196 +Epoch [885/4000] Training [11/16] Loss: 0.00947 +Epoch [885/4000] Training [12/16] Loss: 0.01328 +Epoch [885/4000] Training [13/16] Loss: 0.01498 +Epoch [885/4000] Training [14/16] Loss: 0.01109 +Epoch [885/4000] Training [15/16] Loss: 0.01117 +Epoch [885/4000] Training [16/16] Loss: 0.01397 +Epoch [885/4000] Training metric {'Train/mean dice_metric': 0.9901994466781616, 'Train/mean miou_metric': 0.9809098243713379, 'Train/mean f1': 0.9871205687522888, 'Train/mean precision': 0.9823629260063171, 'Train/mean recall': 0.991924524307251, 'Train/mean hd95_metric': 1.6138535737991333} +Epoch [885/4000] Validation [1/4] Loss: 0.18407 focal_loss 0.11852 dice_loss 0.06555 +Epoch [885/4000] Validation [2/4] Loss: 0.19309 focal_loss 0.08242 dice_loss 0.11067 +Epoch [885/4000] Validation [3/4] Loss: 0.11729 focal_loss 0.06258 dice_loss 0.05471 +Epoch [885/4000] Validation [4/4] Loss: 0.29960 focal_loss 0.17043 dice_loss 0.12917 +Epoch [885/4000] Validation metric {'Val/mean dice_metric': 0.9695327877998352, 'Val/mean miou_metric': 0.9491245150566101, 'Val/mean f1': 0.9716967940330505, 'Val/mean precision': 0.9666827321052551, 'Val/mean recall': 0.9767632484436035, 'Val/mean hd95_metric': 6.225100040435791} +Cheakpoint... +Epoch [885/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695327877998352, 'Val/mean miou_metric': 0.9491245150566101, 'Val/mean f1': 0.9716967940330505, 'Val/mean precision': 0.9666827321052551, 'Val/mean recall': 0.9767632484436035, 'Val/mean hd95_metric': 6.225100040435791} +Epoch [886/4000] Training [1/16] Loss: 0.01016 +Epoch [886/4000] Training [2/16] Loss: 0.01061 +Epoch [886/4000] Training [3/16] Loss: 0.01149 +Epoch [886/4000] Training [4/16] Loss: 0.01050 +Epoch [886/4000] Training [5/16] Loss: 0.04850 +Epoch [886/4000] Training [6/16] Loss: 0.01857 +Epoch [886/4000] Training [7/16] Loss: 0.01217 +Epoch [886/4000] Training [8/16] Loss: 0.00931 +Epoch [886/4000] Training [9/16] Loss: 0.01184 +Epoch [886/4000] Training [10/16] Loss: 0.02399 +Epoch [886/4000] Training [11/16] Loss: 0.01328 +Epoch [886/4000] Training [12/16] Loss: 0.18767 +Epoch [886/4000] Training [13/16] Loss: 0.01324 +Epoch [886/4000] Training [14/16] Loss: 0.01355 +Epoch [886/4000] Training [15/16] Loss: 0.01311 +Epoch [886/4000] Training [16/16] Loss: 0.01767 +Epoch [886/4000] Training metric {'Train/mean dice_metric': 0.988836407661438, 'Train/mean miou_metric': 0.9791426658630371, 'Train/mean f1': 0.9869019985198975, 'Train/mean precision': 0.9828909635543823, 'Train/mean recall': 0.9909458756446838, 'Train/mean hd95_metric': 1.838489294052124} +Epoch [886/4000] Validation [1/4] Loss: 0.14147 focal_loss 0.08398 dice_loss 0.05749 +Epoch [886/4000] Validation [2/4] Loss: 0.20628 focal_loss 0.09276 dice_loss 0.11352 +Epoch [886/4000] Validation [3/4] Loss: 0.13982 focal_loss 0.07610 dice_loss 0.06372 +Epoch [886/4000] Validation [4/4] Loss: 0.31046 focal_loss 0.17846 dice_loss 0.13199 +Epoch [886/4000] Validation metric {'Val/mean dice_metric': 0.9644352197647095, 'Val/mean miou_metric': 0.9433498382568359, 'Val/mean f1': 0.9679061770439148, 'Val/mean precision': 0.9615315198898315, 'Val/mean recall': 0.9743658900260925, 'Val/mean hd95_metric': 7.691651344299316} +Cheakpoint... +Epoch [886/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644352197647095, 'Val/mean miou_metric': 0.9433498382568359, 'Val/mean f1': 0.9679061770439148, 'Val/mean precision': 0.9615315198898315, 'Val/mean recall': 0.9743658900260925, 'Val/mean hd95_metric': 7.691651344299316} +Epoch [887/4000] Training [1/16] Loss: 0.02299 +Epoch [887/4000] Training [2/16] Loss: 0.01422 +Epoch [887/4000] Training [3/16] Loss: 0.01600 +Epoch [887/4000] Training [4/16] Loss: 0.01351 +Epoch [887/4000] Training [5/16] Loss: 0.01589 +Epoch [887/4000] Training [6/16] Loss: 0.01500 +Epoch [887/4000] Training [7/16] Loss: 0.01215 +Epoch [887/4000] Training [8/16] Loss: 0.01517 +Epoch [887/4000] Training [9/16] Loss: 0.01763 +Epoch [887/4000] Training [10/16] Loss: 0.01459 +Epoch [887/4000] Training [11/16] Loss: 0.01608 +Epoch [887/4000] Training [12/16] Loss: 0.02771 +Epoch [887/4000] Training [13/16] Loss: 0.02285 +Epoch [887/4000] Training [14/16] Loss: 0.02600 +Epoch [887/4000] Training [15/16] Loss: 0.01498 +Epoch [887/4000] Training [16/16] Loss: 0.01675 +Epoch [887/4000] Training metric {'Train/mean dice_metric': 0.9847387075424194, 'Train/mean miou_metric': 0.9719170928001404, 'Train/mean f1': 0.9819831252098083, 'Train/mean precision': 0.9759957790374756, 'Train/mean recall': 0.9880443215370178, 'Train/mean hd95_metric': 3.7719597816467285} +Epoch [887/4000] Validation [1/4] Loss: 0.62062 focal_loss 0.49198 dice_loss 0.12864 +Epoch [887/4000] Validation [2/4] Loss: 0.58988 focal_loss 0.29789 dice_loss 0.29198 +Epoch [887/4000] Validation [3/4] Loss: 0.13153 focal_loss 0.07052 dice_loss 0.06101 +Epoch [887/4000] Validation [4/4] Loss: 0.27009 focal_loss 0.13813 dice_loss 0.13196 +Epoch [887/4000] Validation metric {'Val/mean dice_metric': 0.9508301019668579, 'Val/mean miou_metric': 0.9262204170227051, 'Val/mean f1': 0.9582582116127014, 'Val/mean precision': 0.9654565453529358, 'Val/mean recall': 0.9511664509773254, 'Val/mean hd95_metric': 8.407630920410156} +Cheakpoint... +Epoch [887/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9508], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9508301019668579, 'Val/mean miou_metric': 0.9262204170227051, 'Val/mean f1': 0.9582582116127014, 'Val/mean precision': 0.9654565453529358, 'Val/mean recall': 0.9511664509773254, 'Val/mean hd95_metric': 8.407630920410156} +Epoch [888/4000] Training [1/16] Loss: 0.01634 +Epoch [888/4000] Training [2/16] Loss: 0.02259 +Epoch [888/4000] Training [3/16] Loss: 0.01704 +Epoch [888/4000] Training [4/16] Loss: 0.01339 +Epoch [888/4000] Training [5/16] Loss: 0.01198 +Epoch [888/4000] Training [6/16] Loss: 0.01331 +Epoch [888/4000] Training [7/16] Loss: 0.01285 +Epoch [888/4000] Training [8/16] Loss: 0.02011 +Epoch [888/4000] Training [9/16] Loss: 0.02261 +Epoch [888/4000] Training [10/16] Loss: 0.02746 +Epoch [888/4000] Training [11/16] Loss: 0.02471 +Epoch [888/4000] Training [12/16] Loss: 0.02220 +Epoch [888/4000] Training [13/16] Loss: 0.02064 +Epoch [888/4000] Training [14/16] Loss: 0.01729 +Epoch [888/4000] Training [15/16] Loss: 0.01758 +Epoch [888/4000] Training [16/16] Loss: 0.01561 +Epoch [888/4000] Training metric {'Train/mean dice_metric': 0.9845662117004395, 'Train/mean miou_metric': 0.9711621403694153, 'Train/mean f1': 0.9803334474563599, 'Train/mean precision': 0.9768112897872925, 'Train/mean recall': 0.9838810563087463, 'Train/mean hd95_metric': 3.7843196392059326} +Epoch [888/4000] Validation [1/4] Loss: 0.21494 focal_loss 0.12909 dice_loss 0.08584 +Epoch [888/4000] Validation [2/4] Loss: 0.39395 focal_loss 0.17027 dice_loss 0.22368 +Epoch [888/4000] Validation [3/4] Loss: 0.25357 focal_loss 0.13784 dice_loss 0.11572 +Epoch [888/4000] Validation [4/4] Loss: 0.59090 focal_loss 0.43806 dice_loss 0.15284 +Epoch [888/4000] Validation metric {'Val/mean dice_metric': 0.9588945508003235, 'Val/mean miou_metric': 0.9335037469863892, 'Val/mean f1': 0.9591153264045715, 'Val/mean precision': 0.956430971622467, 'Val/mean recall': 0.9618149399757385, 'Val/mean hd95_metric': 9.746633529663086} +Cheakpoint... +Epoch [888/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9589], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9588945508003235, 'Val/mean miou_metric': 0.9335037469863892, 'Val/mean f1': 0.9591153264045715, 'Val/mean precision': 0.956430971622467, 'Val/mean recall': 0.9618149399757385, 'Val/mean hd95_metric': 9.746633529663086} +Epoch [889/4000] Training [1/16] Loss: 0.03596 +Epoch [889/4000] Training [2/16] Loss: 0.01945 +Epoch [889/4000] Training [3/16] Loss: 0.01565 +Epoch [889/4000] Training [4/16] Loss: 0.01475 +Epoch [889/4000] Training [5/16] Loss: 0.02323 +Epoch [889/4000] Training [6/16] Loss: 0.01542 +Epoch [889/4000] Training [7/16] Loss: 0.04045 +Epoch [889/4000] Training [8/16] Loss: 0.01411 +Epoch [889/4000] Training [9/16] Loss: 0.01546 +Epoch [889/4000] Training [10/16] Loss: 0.01491 +Epoch [889/4000] Training [11/16] Loss: 0.08831 +Epoch [889/4000] Training [12/16] Loss: 0.01590 +Epoch [889/4000] Training [13/16] Loss: 0.01514 +Epoch [889/4000] Training [14/16] Loss: 0.02464 +Epoch [889/4000] Training [15/16] Loss: 0.01624 +Epoch [889/4000] Training [16/16] Loss: 0.01548 +Epoch [889/4000] Training metric {'Train/mean dice_metric': 0.9879379272460938, 'Train/mean miou_metric': 0.9761885404586792, 'Train/mean f1': 0.9841110110282898, 'Train/mean precision': 0.9808087944984436, 'Train/mean recall': 0.987435519695282, 'Train/mean hd95_metric': 2.304727554321289} +Epoch [889/4000] Validation [1/4] Loss: 0.15971 focal_loss 0.09885 dice_loss 0.06086 +Epoch [889/4000] Validation [2/4] Loss: 0.34353 focal_loss 0.16123 dice_loss 0.18230 +Epoch [889/4000] Validation [3/4] Loss: 0.17733 focal_loss 0.08181 dice_loss 0.09552 +Epoch [889/4000] Validation [4/4] Loss: 0.29435 focal_loss 0.16154 dice_loss 0.13280 +Epoch [889/4000] Validation metric {'Val/mean dice_metric': 0.9632518887519836, 'Val/mean miou_metric': 0.9398956298828125, 'Val/mean f1': 0.9613372087478638, 'Val/mean precision': 0.9487403631210327, 'Val/mean recall': 0.9742729663848877, 'Val/mean hd95_metric': 8.354427337646484} +Cheakpoint... +Epoch [889/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632518887519836, 'Val/mean miou_metric': 0.9398956298828125, 'Val/mean f1': 0.9613372087478638, 'Val/mean precision': 0.9487403631210327, 'Val/mean recall': 0.9742729663848877, 'Val/mean hd95_metric': 8.354427337646484} +Epoch [890/4000] Training [1/16] Loss: 0.01360 +Epoch [890/4000] Training [2/16] Loss: 0.01237 +Epoch [890/4000] Training [3/16] Loss: 0.01782 +Epoch [890/4000] Training [4/16] Loss: 0.02118 +Epoch [890/4000] Training [5/16] Loss: 0.01993 +Epoch [890/4000] Training [6/16] Loss: 0.01731 +Epoch [890/4000] Training [7/16] Loss: 0.01318 +Epoch [890/4000] Training [8/16] Loss: 0.04258 +Epoch [890/4000] Training [9/16] Loss: 0.01617 +Epoch [890/4000] Training [10/16] Loss: 0.02501 +Epoch [890/4000] Training [11/16] Loss: 0.01224 +Epoch [890/4000] Training [12/16] Loss: 0.01995 +Epoch [890/4000] Training [13/16] Loss: 0.01628 +Epoch [890/4000] Training [14/16] Loss: 0.01316 +Epoch [890/4000] Training [15/16] Loss: 0.01468 +Epoch [890/4000] Training [16/16] Loss: 0.02341 +Epoch [890/4000] Training metric {'Train/mean dice_metric': 0.9879308342933655, 'Train/mean miou_metric': 0.9760886430740356, 'Train/mean f1': 0.9844686388969421, 'Train/mean precision': 0.9790436029434204, 'Train/mean recall': 0.9899541139602661, 'Train/mean hd95_metric': 2.472113609313965} +Epoch [890/4000] Validation [1/4] Loss: 0.15459 focal_loss 0.09858 dice_loss 0.05600 +Epoch [890/4000] Validation [2/4] Loss: 0.44066 focal_loss 0.22428 dice_loss 0.21637 +Epoch [890/4000] Validation [3/4] Loss: 0.11694 focal_loss 0.05679 dice_loss 0.06015 +Epoch [890/4000] Validation [4/4] Loss: 0.36129 focal_loss 0.21488 dice_loss 0.14642 +Epoch [890/4000] Validation metric {'Val/mean dice_metric': 0.9628741145133972, 'Val/mean miou_metric': 0.9400190114974976, 'Val/mean f1': 0.9609850645065308, 'Val/mean precision': 0.9474354982376099, 'Val/mean recall': 0.9749278426170349, 'Val/mean hd95_metric': 8.564214706420898} +Cheakpoint... +Epoch [890/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9629], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9628741145133972, 'Val/mean miou_metric': 0.9400190114974976, 'Val/mean f1': 0.9609850645065308, 'Val/mean precision': 0.9474354982376099, 'Val/mean recall': 0.9749278426170349, 'Val/mean hd95_metric': 8.564214706420898} +Epoch [891/4000] Training [1/16] Loss: 0.01114 +Epoch [891/4000] Training [2/16] Loss: 0.02462 +Epoch [891/4000] Training [3/16] Loss: 0.01407 +Epoch [891/4000] Training [4/16] Loss: 0.01898 +Epoch [891/4000] Training [5/16] Loss: 0.01760 +Epoch [891/4000] Training [6/16] Loss: 0.01899 +Epoch [891/4000] Training [7/16] Loss: 0.01642 +Epoch [891/4000] Training [8/16] Loss: 0.01995 +Epoch [891/4000] Training [9/16] Loss: 0.01459 +Epoch [891/4000] Training [10/16] Loss: 0.01240 +Epoch [891/4000] Training [11/16] Loss: 0.01354 +Epoch [891/4000] Training [12/16] Loss: 0.01716 +Epoch [891/4000] Training [13/16] Loss: 0.02149 +Epoch [891/4000] Training [14/16] Loss: 0.01551 +Epoch [891/4000] Training [15/16] Loss: 0.01224 +Epoch [891/4000] Training [16/16] Loss: 0.02325 +Epoch [891/4000] Training metric {'Train/mean dice_metric': 0.9882497191429138, 'Train/mean miou_metric': 0.9768178462982178, 'Train/mean f1': 0.984795868396759, 'Train/mean precision': 0.9800771474838257, 'Train/mean recall': 0.9895603060722351, 'Train/mean hd95_metric': 2.431391954421997} +Epoch [891/4000] Validation [1/4] Loss: 0.13775 focal_loss 0.07441 dice_loss 0.06334 +Epoch [891/4000] Validation [2/4] Loss: 0.23575 focal_loss 0.09791 dice_loss 0.13784 +Epoch [891/4000] Validation [3/4] Loss: 0.18306 focal_loss 0.09357 dice_loss 0.08949 +Epoch [891/4000] Validation [4/4] Loss: 0.28145 focal_loss 0.16017 dice_loss 0.12128 +Epoch [891/4000] Validation metric {'Val/mean dice_metric': 0.9632814526557922, 'Val/mean miou_metric': 0.939577579498291, 'Val/mean f1': 0.9657947421073914, 'Val/mean precision': 0.9666799306869507, 'Val/mean recall': 0.9649112224578857, 'Val/mean hd95_metric': 8.096609115600586} +Cheakpoint... +Epoch [891/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632814526557922, 'Val/mean miou_metric': 0.939577579498291, 'Val/mean f1': 0.9657947421073914, 'Val/mean precision': 0.9666799306869507, 'Val/mean recall': 0.9649112224578857, 'Val/mean hd95_metric': 8.096609115600586} +Epoch [892/4000] Training [1/16] Loss: 0.01188 +Epoch [892/4000] Training [2/16] Loss: 0.01076 +Epoch [892/4000] Training [3/16] Loss: 0.01401 +Epoch [892/4000] Training [4/16] Loss: 0.03227 +Epoch [892/4000] Training [5/16] Loss: 0.02540 +Epoch [892/4000] Training [6/16] Loss: 0.01622 +Epoch [892/4000] Training [7/16] Loss: 0.01029 +Epoch [892/4000] Training [8/16] Loss: 0.01616 +Epoch [892/4000] Training [9/16] Loss: 0.01771 +Epoch [892/4000] Training [10/16] Loss: 0.01650 +Epoch [892/4000] Training [11/16] Loss: 0.01424 +Epoch [892/4000] Training [12/16] Loss: 0.01831 +Epoch [892/4000] Training [13/16] Loss: 0.01254 +Epoch [892/4000] Training [14/16] Loss: 0.01634 +Epoch [892/4000] Training [15/16] Loss: 0.01376 +Epoch [892/4000] Training [16/16] Loss: 0.01145 +Epoch [892/4000] Training metric {'Train/mean dice_metric': 0.9892628192901611, 'Train/mean miou_metric': 0.9787695407867432, 'Train/mean f1': 0.9863383769989014, 'Train/mean precision': 0.9820926189422607, 'Train/mean recall': 0.9906209707260132, 'Train/mean hd95_metric': 1.823667287826538} +Epoch [892/4000] Validation [1/4] Loss: 0.29544 focal_loss 0.17939 dice_loss 0.11605 +Epoch [892/4000] Validation [2/4] Loss: 0.24207 focal_loss 0.09290 dice_loss 0.14917 +Epoch [892/4000] Validation [3/4] Loss: 0.10913 focal_loss 0.05532 dice_loss 0.05381 +Epoch [892/4000] Validation [4/4] Loss: 0.21586 focal_loss 0.11185 dice_loss 0.10401 +Epoch [892/4000] Validation metric {'Val/mean dice_metric': 0.9673063158988953, 'Val/mean miou_metric': 0.9453305006027222, 'Val/mean f1': 0.9702978730201721, 'Val/mean precision': 0.9667858481407166, 'Val/mean recall': 0.9738354682922363, 'Val/mean hd95_metric': 7.260138034820557} +Cheakpoint... +Epoch [892/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673063158988953, 'Val/mean miou_metric': 0.9453305006027222, 'Val/mean f1': 0.9702978730201721, 'Val/mean precision': 0.9667858481407166, 'Val/mean recall': 0.9738354682922363, 'Val/mean hd95_metric': 7.260138034820557} +Epoch [893/4000] Training [1/16] Loss: 0.01902 +Epoch [893/4000] Training [2/16] Loss: 0.00995 +Epoch [893/4000] Training [3/16] Loss: 0.01607 +Epoch [893/4000] Training [4/16] Loss: 0.01197 +Epoch [893/4000] Training [5/16] Loss: 0.00942 +Epoch [893/4000] Training [6/16] Loss: 0.01288 +Epoch [893/4000] Training [7/16] Loss: 0.01823 +Epoch [893/4000] Training [8/16] Loss: 0.01490 +Epoch [893/4000] Training [9/16] Loss: 0.02209 +Epoch [893/4000] Training [10/16] Loss: 0.01734 +Epoch [893/4000] Training [11/16] Loss: 0.01306 +Epoch [893/4000] Training [12/16] Loss: 0.01233 +Epoch [893/4000] Training [13/16] Loss: 0.01421 +Epoch [893/4000] Training [14/16] Loss: 0.01382 +Epoch [893/4000] Training [15/16] Loss: 0.01369 +Epoch [893/4000] Training [16/16] Loss: 0.01248 +Epoch [893/4000] Training metric {'Train/mean dice_metric': 0.9887999892234802, 'Train/mean miou_metric': 0.9781036376953125, 'Train/mean f1': 0.985566258430481, 'Train/mean precision': 0.9822260737419128, 'Train/mean recall': 0.9889291524887085, 'Train/mean hd95_metric': 1.8246337175369263} +Epoch [893/4000] Validation [1/4] Loss: 0.24027 focal_loss 0.14981 dice_loss 0.09046 +Epoch [893/4000] Validation [2/4] Loss: 0.36459 focal_loss 0.15660 dice_loss 0.20799 +Epoch [893/4000] Validation [3/4] Loss: 0.11300 focal_loss 0.06172 dice_loss 0.05128 +Epoch [893/4000] Validation [4/4] Loss: 0.29116 focal_loss 0.15878 dice_loss 0.13238 +Epoch [893/4000] Validation metric {'Val/mean dice_metric': 0.9668179750442505, 'Val/mean miou_metric': 0.9442976117134094, 'Val/mean f1': 0.9683548808097839, 'Val/mean precision': 0.9619672298431396, 'Val/mean recall': 0.9748280048370361, 'Val/mean hd95_metric': 6.682792663574219} +Cheakpoint... +Epoch [893/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668179750442505, 'Val/mean miou_metric': 0.9442976117134094, 'Val/mean f1': 0.9683548808097839, 'Val/mean precision': 0.9619672298431396, 'Val/mean recall': 0.9748280048370361, 'Val/mean hd95_metric': 6.682792663574219} +Epoch [894/4000] Training [1/16] Loss: 0.01341 +Epoch [894/4000] Training [2/16] Loss: 0.01346 +Epoch [894/4000] Training [3/16] Loss: 0.01736 +Epoch [894/4000] Training [4/16] Loss: 0.01253 +Epoch [894/4000] Training [5/16] Loss: 0.15106 +Epoch [894/4000] Training [6/16] Loss: 0.01340 +Epoch [894/4000] Training [7/16] Loss: 0.01061 +Epoch [894/4000] Training [8/16] Loss: 0.01325 +Epoch [894/4000] Training [9/16] Loss: 0.01240 +Epoch [894/4000] Training [10/16] Loss: 0.01507 +Epoch [894/4000] Training [11/16] Loss: 0.01053 +Epoch [894/4000] Training [12/16] Loss: 0.02095 +Epoch [894/4000] Training [13/16] Loss: 0.01492 +Epoch [894/4000] Training [14/16] Loss: 0.01633 +Epoch [894/4000] Training [15/16] Loss: 0.01254 +Epoch [894/4000] Training [16/16] Loss: 0.02191 +Epoch [894/4000] Training metric {'Train/mean dice_metric': 0.9879995584487915, 'Train/mean miou_metric': 0.9778226017951965, 'Train/mean f1': 0.9853204488754272, 'Train/mean precision': 0.9807628393173218, 'Train/mean recall': 0.9899206161499023, 'Train/mean hd95_metric': 2.7415757179260254} +Epoch [894/4000] Validation [1/4] Loss: 0.37413 focal_loss 0.24125 dice_loss 0.13288 +Epoch [894/4000] Validation [2/4] Loss: 0.49711 focal_loss 0.27138 dice_loss 0.22573 +Epoch [894/4000] Validation [3/4] Loss: 0.13128 focal_loss 0.07317 dice_loss 0.05811 +Epoch [894/4000] Validation [4/4] Loss: 0.29440 focal_loss 0.16619 dice_loss 0.12821 +Epoch [894/4000] Validation metric {'Val/mean dice_metric': 0.9622443318367004, 'Val/mean miou_metric': 0.9394987225532532, 'Val/mean f1': 0.9671747088432312, 'Val/mean precision': 0.9700788259506226, 'Val/mean recall': 0.9642878770828247, 'Val/mean hd95_metric': 7.9451003074646} +Cheakpoint... +Epoch [894/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9622], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9622443318367004, 'Val/mean miou_metric': 0.9394987225532532, 'Val/mean f1': 0.9671747088432312, 'Val/mean precision': 0.9700788259506226, 'Val/mean recall': 0.9642878770828247, 'Val/mean hd95_metric': 7.9451003074646} +Epoch [895/4000] Training [1/16] Loss: 0.01568 +Epoch [895/4000] Training [2/16] Loss: 0.01016 +Epoch [895/4000] Training [3/16] Loss: 0.01686 +Epoch [895/4000] Training [4/16] Loss: 0.01776 +Epoch [895/4000] Training [5/16] Loss: 0.01570 +Epoch [895/4000] Training [6/16] Loss: 0.01387 +Epoch [895/4000] Training [7/16] Loss: 0.01303 +Epoch [895/4000] Training [8/16] Loss: 0.01297 +Epoch [895/4000] Training [9/16] Loss: 0.01690 +Epoch [895/4000] Training [10/16] Loss: 0.01237 +Epoch [895/4000] Training [11/16] Loss: 0.01345 +Epoch [895/4000] Training [12/16] Loss: 0.04940 +Epoch [895/4000] Training [13/16] Loss: 0.01515 +Epoch [895/4000] Training [14/16] Loss: 0.01537 +Epoch [895/4000] Training [15/16] Loss: 0.01217 +Epoch [895/4000] Training [16/16] Loss: 0.01457 +Epoch [895/4000] Training metric {'Train/mean dice_metric': 0.9877820611000061, 'Train/mean miou_metric': 0.976792573928833, 'Train/mean f1': 0.9840857982635498, 'Train/mean precision': 0.9807469844818115, 'Train/mean recall': 0.9874475002288818, 'Train/mean hd95_metric': 2.2784974575042725} +Epoch [895/4000] Validation [1/4] Loss: 0.34594 focal_loss 0.23093 dice_loss 0.11501 +Epoch [895/4000] Validation [2/4] Loss: 0.50789 focal_loss 0.22844 dice_loss 0.27945 +Epoch [895/4000] Validation [3/4] Loss: 0.15849 focal_loss 0.08430 dice_loss 0.07419 +Epoch [895/4000] Validation [4/4] Loss: 0.37617 focal_loss 0.18648 dice_loss 0.18969 +Epoch [895/4000] Validation metric {'Val/mean dice_metric': 0.9627481698989868, 'Val/mean miou_metric': 0.9400506019592285, 'Val/mean f1': 0.9655662178993225, 'Val/mean precision': 0.9675429463386536, 'Val/mean recall': 0.9635976552963257, 'Val/mean hd95_metric': 6.940557956695557} +Cheakpoint... +Epoch [895/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9627], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9627481698989868, 'Val/mean miou_metric': 0.9400506019592285, 'Val/mean f1': 0.9655662178993225, 'Val/mean precision': 0.9675429463386536, 'Val/mean recall': 0.9635976552963257, 'Val/mean hd95_metric': 6.940557956695557} +Epoch [896/4000] Training [1/16] Loss: 0.01455 +Epoch [896/4000] Training [2/16] Loss: 0.01171 +Epoch [896/4000] Training [3/16] Loss: 0.01340 +Epoch [896/4000] Training [4/16] Loss: 0.01416 +Epoch [896/4000] Training [5/16] Loss: 0.01433 +Epoch [896/4000] Training [6/16] Loss: 0.01383 +Epoch [896/4000] Training [7/16] Loss: 0.01493 +Epoch [896/4000] Training [8/16] Loss: 0.01337 +Epoch [896/4000] Training [9/16] Loss: 0.01448 +Epoch [896/4000] Training [10/16] Loss: 0.02118 +Epoch [896/4000] Training [11/16] Loss: 0.01485 +Epoch [896/4000] Training [12/16] Loss: 0.04204 +Epoch [896/4000] Training [13/16] Loss: 0.01804 +Epoch [896/4000] Training [14/16] Loss: 0.01119 +Epoch [896/4000] Training [15/16] Loss: 0.01558 +Epoch [896/4000] Training [16/16] Loss: 0.01162 +Epoch [896/4000] Training metric {'Train/mean dice_metric': 0.9883925914764404, 'Train/mean miou_metric': 0.9770328998565674, 'Train/mean f1': 0.9842206835746765, 'Train/mean precision': 0.9783621430397034, 'Train/mean recall': 0.9901498556137085, 'Train/mean hd95_metric': 3.6778182983398438} +Epoch [896/4000] Validation [1/4] Loss: 0.13777 focal_loss 0.07240 dice_loss 0.06537 +Epoch [896/4000] Validation [2/4] Loss: 0.40393 focal_loss 0.21297 dice_loss 0.19096 +Epoch [896/4000] Validation [3/4] Loss: 0.14472 focal_loss 0.07614 dice_loss 0.06858 +Epoch [896/4000] Validation [4/4] Loss: 0.25668 focal_loss 0.11845 dice_loss 0.13824 +Epoch [896/4000] Validation metric {'Val/mean dice_metric': 0.9652924537658691, 'Val/mean miou_metric': 0.9424400329589844, 'Val/mean f1': 0.9677664041519165, 'Val/mean precision': 0.9649405479431152, 'Val/mean recall': 0.9706088900566101, 'Val/mean hd95_metric': 8.0347900390625} +Cheakpoint... +Epoch [896/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652924537658691, 'Val/mean miou_metric': 0.9424400329589844, 'Val/mean f1': 0.9677664041519165, 'Val/mean precision': 0.9649405479431152, 'Val/mean recall': 0.9706088900566101, 'Val/mean hd95_metric': 8.0347900390625} +Epoch [897/4000] Training [1/16] Loss: 0.01454 +Epoch [897/4000] Training [2/16] Loss: 0.01204 +Epoch [897/4000] Training [3/16] Loss: 0.01067 +Epoch [897/4000] Training [4/16] Loss: 0.01245 +Epoch [897/4000] Training [5/16] Loss: 0.01716 +Epoch [897/4000] Training [6/16] Loss: 0.01637 +Epoch [897/4000] Training [7/16] Loss: 0.01307 +Epoch [897/4000] Training [8/16] Loss: 0.01761 +Epoch [897/4000] Training [9/16] Loss: 0.01235 +Epoch [897/4000] Training [10/16] Loss: 0.01866 +Epoch [897/4000] Training [11/16] Loss: 0.01493 +Epoch [897/4000] Training [12/16] Loss: 0.01750 +Epoch [897/4000] Training [13/16] Loss: 0.01129 +Epoch [897/4000] Training [14/16] Loss: 0.01828 +Epoch [897/4000] Training [15/16] Loss: 0.01772 +Epoch [897/4000] Training [16/16] Loss: 0.01154 +Epoch [897/4000] Training metric {'Train/mean dice_metric': 0.9903320670127869, 'Train/mean miou_metric': 0.9806385040283203, 'Train/mean f1': 0.9866927266120911, 'Train/mean precision': 0.9825116395950317, 'Train/mean recall': 0.9909095168113708, 'Train/mean hd95_metric': 1.3547494411468506} +Epoch [897/4000] Validation [1/4] Loss: 0.15227 focal_loss 0.09196 dice_loss 0.06031 +Epoch [897/4000] Validation [2/4] Loss: 0.23018 focal_loss 0.11283 dice_loss 0.11735 +Epoch [897/4000] Validation [3/4] Loss: 0.16094 focal_loss 0.09882 dice_loss 0.06212 +Epoch [897/4000] Validation [4/4] Loss: 0.18452 focal_loss 0.08441 dice_loss 0.10011 +Epoch [897/4000] Validation metric {'Val/mean dice_metric': 0.9695067405700684, 'Val/mean miou_metric': 0.9477747678756714, 'Val/mean f1': 0.9695896506309509, 'Val/mean precision': 0.964190661907196, 'Val/mean recall': 0.9750494360923767, 'Val/mean hd95_metric': 6.781538486480713} +Cheakpoint... +Epoch [897/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695067405700684, 'Val/mean miou_metric': 0.9477747678756714, 'Val/mean f1': 0.9695896506309509, 'Val/mean precision': 0.964190661907196, 'Val/mean recall': 0.9750494360923767, 'Val/mean hd95_metric': 6.781538486480713} +Epoch [898/4000] Training [1/16] Loss: 0.00947 +Epoch [898/4000] Training [2/16] Loss: 0.01352 +Epoch [898/4000] Training [3/16] Loss: 0.01206 +Epoch [898/4000] Training [4/16] Loss: 0.01485 +Epoch [898/4000] Training [5/16] Loss: 0.01543 +Epoch [898/4000] Training [6/16] Loss: 0.01109 +Epoch [898/4000] Training [7/16] Loss: 0.01183 +Epoch [898/4000] Training [8/16] Loss: 0.01130 +Epoch [898/4000] Training [9/16] Loss: 0.01624 +Epoch [898/4000] Training [10/16] Loss: 0.01428 +Epoch [898/4000] Training [11/16] Loss: 0.01414 +Epoch [898/4000] Training [12/16] Loss: 0.01579 +Epoch [898/4000] Training [13/16] Loss: 0.01119 +Epoch [898/4000] Training [14/16] Loss: 0.01046 +Epoch [898/4000] Training [15/16] Loss: 0.00907 +Epoch [898/4000] Training [16/16] Loss: 0.01422 +Epoch [898/4000] Training metric {'Train/mean dice_metric': 0.9915310740470886, 'Train/mean miou_metric': 0.9829643368721008, 'Train/mean f1': 0.9873828887939453, 'Train/mean precision': 0.9823693633079529, 'Train/mean recall': 0.9924478530883789, 'Train/mean hd95_metric': 1.2312084436416626} +Epoch [898/4000] Validation [1/4] Loss: 0.14183 focal_loss 0.08191 dice_loss 0.05992 +Epoch [898/4000] Validation [2/4] Loss: 0.21069 focal_loss 0.10185 dice_loss 0.10884 +Epoch [898/4000] Validation [3/4] Loss: 0.13826 focal_loss 0.07792 dice_loss 0.06034 +Epoch [898/4000] Validation [4/4] Loss: 0.23860 focal_loss 0.10289 dice_loss 0.13571 +Epoch [898/4000] Validation metric {'Val/mean dice_metric': 0.969953179359436, 'Val/mean miou_metric': 0.9496897459030151, 'Val/mean f1': 0.971102237701416, 'Val/mean precision': 0.9640993475914001, 'Val/mean recall': 0.9782074689865112, 'Val/mean hd95_metric': 5.989602565765381} +Cheakpoint... +Epoch [898/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969953179359436, 'Val/mean miou_metric': 0.9496897459030151, 'Val/mean f1': 0.971102237701416, 'Val/mean precision': 0.9640993475914001, 'Val/mean recall': 0.9782074689865112, 'Val/mean hd95_metric': 5.989602565765381} +Epoch [899/4000] Training [1/16] Loss: 0.00937 +Epoch [899/4000] Training [2/16] Loss: 0.01149 +Epoch [899/4000] Training [3/16] Loss: 0.01487 +Epoch [899/4000] Training [4/16] Loss: 0.01065 +Epoch [899/4000] Training [5/16] Loss: 0.01061 +Epoch [899/4000] Training [6/16] Loss: 0.01021 +Epoch [899/4000] Training [7/16] Loss: 0.01025 +Epoch [899/4000] Training [8/16] Loss: 0.01261 +Epoch [899/4000] Training [9/16] Loss: 0.01131 +Epoch [899/4000] Training [10/16] Loss: 0.01322 +Epoch [899/4000] Training [11/16] Loss: 0.00924 +Epoch [899/4000] Training [12/16] Loss: 0.01109 +Epoch [899/4000] Training [13/16] Loss: 0.01128 +Epoch [899/4000] Training [14/16] Loss: 0.01012 +Epoch [899/4000] Training [15/16] Loss: 0.01164 +Epoch [899/4000] Training [16/16] Loss: 0.01057 +Epoch [899/4000] Training metric {'Train/mean dice_metric': 0.9920337200164795, 'Train/mean miou_metric': 0.9839611053466797, 'Train/mean f1': 0.988303542137146, 'Train/mean precision': 0.9835628271102905, 'Train/mean recall': 0.9930901527404785, 'Train/mean hd95_metric': 1.220387578010559} +Epoch [899/4000] Validation [1/4] Loss: 0.13439 focal_loss 0.07931 dice_loss 0.05509 +Epoch [899/4000] Validation [2/4] Loss: 0.23174 focal_loss 0.10208 dice_loss 0.12966 +Epoch [899/4000] Validation [3/4] Loss: 0.20971 focal_loss 0.10698 dice_loss 0.10273 +Epoch [899/4000] Validation [4/4] Loss: 0.20807 focal_loss 0.09179 dice_loss 0.11628 +Epoch [899/4000] Validation metric {'Val/mean dice_metric': 0.9697349667549133, 'Val/mean miou_metric': 0.9501584768295288, 'Val/mean f1': 0.9717373847961426, 'Val/mean precision': 0.9660414457321167, 'Val/mean recall': 0.977500855922699, 'Val/mean hd95_metric': 6.071310520172119} +Cheakpoint... +Epoch [899/4000] best acc:tensor([0.9710], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697349667549133, 'Val/mean miou_metric': 0.9501584768295288, 'Val/mean f1': 0.9717373847961426, 'Val/mean precision': 0.9660414457321167, 'Val/mean recall': 0.977500855922699, 'Val/mean hd95_metric': 6.071310520172119} +Epoch [900/4000] Training [1/16] Loss: 0.01656 +Epoch [900/4000] Training [2/16] Loss: 0.01088 +Epoch [900/4000] Training [3/16] Loss: 0.01212 +Epoch [900/4000] Training [4/16] Loss: 0.01345 +Epoch [900/4000] Training [5/16] Loss: 0.01656 +Epoch [900/4000] Training [6/16] Loss: 0.01057 +Epoch [900/4000] Training [7/16] Loss: 0.01358 +Epoch [900/4000] Training [8/16] Loss: 0.01016 +Epoch [900/4000] Training [9/16] Loss: 0.00831 +Epoch [900/4000] Training [10/16] Loss: 0.00975 +Epoch [900/4000] Training [11/16] Loss: 0.01323 +Epoch [900/4000] Training [12/16] Loss: 0.01059 +Epoch [900/4000] Training [13/16] Loss: 0.01053 +Epoch [900/4000] Training [14/16] Loss: 0.00945 +Epoch [900/4000] Training [15/16] Loss: 0.01053 +Epoch [900/4000] Training [16/16] Loss: 0.02262 +Epoch [900/4000] Training metric {'Train/mean dice_metric': 0.9914242625236511, 'Train/mean miou_metric': 0.9827774167060852, 'Train/mean f1': 0.9881286025047302, 'Train/mean precision': 0.9834380745887756, 'Train/mean recall': 0.9928640723228455, 'Train/mean hd95_metric': 1.1639151573181152} +Epoch [900/4000] Validation [1/4] Loss: 0.16768 focal_loss 0.10600 dice_loss 0.06168 +Epoch [900/4000] Validation [2/4] Loss: 0.24992 focal_loss 0.10917 dice_loss 0.14075 +Epoch [900/4000] Validation [3/4] Loss: 0.14290 focal_loss 0.08144 dice_loss 0.06146 +Epoch [900/4000] Validation [4/4] Loss: 0.25146 focal_loss 0.14065 dice_loss 0.11081 +Epoch [900/4000] Validation metric {'Val/mean dice_metric': 0.9711673855781555, 'Val/mean miou_metric': 0.9514340162277222, 'Val/mean f1': 0.9724718332290649, 'Val/mean precision': 0.9670870304107666, 'Val/mean recall': 0.977916955947876, 'Val/mean hd95_metric': 6.041950225830078} +Cheakpoint... +Epoch [900/4000] best acc:tensor([0.9712], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711673855781555, 'Val/mean miou_metric': 0.9514340162277222, 'Val/mean f1': 0.9724718332290649, 'Val/mean precision': 0.9670870304107666, 'Val/mean recall': 0.977916955947876, 'Val/mean hd95_metric': 6.041950225830078} +Epoch [901/4000] Training [1/16] Loss: 0.00906 +Epoch [901/4000] Training [2/16] Loss: 0.01395 +Epoch [901/4000] Training [3/16] Loss: 0.00918 +Epoch [901/4000] Training [4/16] Loss: 0.01230 +Epoch [901/4000] Training [5/16] Loss: 0.01070 +Epoch [901/4000] Training [6/16] Loss: 0.01363 +Epoch [901/4000] Training [7/16] Loss: 0.01332 +Epoch [901/4000] Training [8/16] Loss: 0.01366 +Epoch [901/4000] Training [9/16] Loss: 0.01045 +Epoch [901/4000] Training [10/16] Loss: 0.01438 +Epoch [901/4000] Training [11/16] Loss: 0.00966 +Epoch [901/4000] Training [12/16] Loss: 0.01539 +Epoch [901/4000] Training [13/16] Loss: 0.01466 +Epoch [901/4000] Training [14/16] Loss: 0.01063 +Epoch [901/4000] Training [15/16] Loss: 0.00897 +Epoch [901/4000] Training [16/16] Loss: 0.01029 +Epoch [901/4000] Training metric {'Train/mean dice_metric': 0.9915304780006409, 'Train/mean miou_metric': 0.982970118522644, 'Train/mean f1': 0.9875229597091675, 'Train/mean precision': 0.9823920726776123, 'Train/mean recall': 0.9927076697349548, 'Train/mean hd95_metric': 1.4881279468536377} +Epoch [901/4000] Validation [1/4] Loss: 0.17423 focal_loss 0.10778 dice_loss 0.06645 +Epoch [901/4000] Validation [2/4] Loss: 0.29894 focal_loss 0.15256 dice_loss 0.14638 +Epoch [901/4000] Validation [3/4] Loss: 0.13611 focal_loss 0.07083 dice_loss 0.06527 +Epoch [901/4000] Validation [4/4] Loss: 0.22881 focal_loss 0.11792 dice_loss 0.11090 +Epoch [901/4000] Validation metric {'Val/mean dice_metric': 0.9654402732849121, 'Val/mean miou_metric': 0.9454416036605835, 'Val/mean f1': 0.9708138704299927, 'Val/mean precision': 0.967299222946167, 'Val/mean recall': 0.9743540287017822, 'Val/mean hd95_metric': 6.456850528717041} +Cheakpoint... +Epoch [901/4000] best acc:tensor([0.9712], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654402732849121, 'Val/mean miou_metric': 0.9454416036605835, 'Val/mean f1': 0.9708138704299927, 'Val/mean precision': 0.967299222946167, 'Val/mean recall': 0.9743540287017822, 'Val/mean hd95_metric': 6.456850528717041} +Epoch [902/4000] Training [1/16] Loss: 0.01406 +Epoch [902/4000] Training [2/16] Loss: 0.00879 +Epoch [902/4000] Training [3/16] Loss: 0.01080 +Epoch [902/4000] Training [4/16] Loss: 0.01119 +Epoch [902/4000] Training [5/16] Loss: 0.01169 +Epoch [902/4000] Training [6/16] Loss: 0.01184 +Epoch [902/4000] Training [7/16] Loss: 0.01031 +Epoch [902/4000] Training [8/16] Loss: 0.01131 +Epoch [902/4000] Training [9/16] Loss: 0.00950 +Epoch [902/4000] Training [10/16] Loss: 0.01027 +Epoch [902/4000] Training [11/16] Loss: 0.01056 +Epoch [902/4000] Training [12/16] Loss: 0.01310 +Epoch [902/4000] Training [13/16] Loss: 0.01302 +Epoch [902/4000] Training [14/16] Loss: 0.01226 +Epoch [902/4000] Training [15/16] Loss: 0.01446 +Epoch [902/4000] Training [16/16] Loss: 0.01392 +Epoch [902/4000] Training metric {'Train/mean dice_metric': 0.9916795492172241, 'Train/mean miou_metric': 0.9832720160484314, 'Train/mean f1': 0.988426923751831, 'Train/mean precision': 0.9839792847633362, 'Train/mean recall': 0.9929149150848389, 'Train/mean hd95_metric': 1.1496552228927612} +Epoch [902/4000] Validation [1/4] Loss: 0.15797 focal_loss 0.09756 dice_loss 0.06041 +Epoch [902/4000] Validation [2/4] Loss: 0.18667 focal_loss 0.08022 dice_loss 0.10646 +Epoch [902/4000] Validation [3/4] Loss: 0.16322 focal_loss 0.09762 dice_loss 0.06560 +Epoch [902/4000] Validation [4/4] Loss: 0.23784 focal_loss 0.13854 dice_loss 0.09929 +Epoch [902/4000] Validation metric {'Val/mean dice_metric': 0.9716222882270813, 'Val/mean miou_metric': 0.9520736932754517, 'Val/mean f1': 0.9725009202957153, 'Val/mean precision': 0.9677379727363586, 'Val/mean recall': 0.9773110747337341, 'Val/mean hd95_metric': 5.41217565536499} +Cheakpoint... +Epoch [902/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716222882270813, 'Val/mean miou_metric': 0.9520736932754517, 'Val/mean f1': 0.9725009202957153, 'Val/mean precision': 0.9677379727363586, 'Val/mean recall': 0.9773110747337341, 'Val/mean hd95_metric': 5.41217565536499} +Epoch [903/4000] Training [1/16] Loss: 0.01348 +Epoch [903/4000] Training [2/16] Loss: 0.01192 +Epoch [903/4000] Training [3/16] Loss: 0.01052 +Epoch [903/4000] Training [4/16] Loss: 0.01217 +Epoch [903/4000] Training [5/16] Loss: 0.01505 +Epoch [903/4000] Training [6/16] Loss: 0.01085 +Epoch [903/4000] Training [7/16] Loss: 0.01188 +Epoch [903/4000] Training [8/16] Loss: 0.01532 +Epoch [903/4000] Training [9/16] Loss: 0.01026 +Epoch [903/4000] Training [10/16] Loss: 0.01407 +Epoch [903/4000] Training [11/16] Loss: 0.01401 +Epoch [903/4000] Training [12/16] Loss: 0.01224 +Epoch [903/4000] Training [13/16] Loss: 0.01750 +Epoch [903/4000] Training [14/16] Loss: 0.01148 +Epoch [903/4000] Training [15/16] Loss: 0.01738 +Epoch [903/4000] Training [16/16] Loss: 0.01618 +Epoch [903/4000] Training metric {'Train/mean dice_metric': 0.9909917712211609, 'Train/mean miou_metric': 0.9819244146347046, 'Train/mean f1': 0.9874775409698486, 'Train/mean precision': 0.9824079275131226, 'Train/mean recall': 0.9925997257232666, 'Train/mean hd95_metric': 1.2243680953979492} +Epoch [903/4000] Validation [1/4] Loss: 0.13633 focal_loss 0.07655 dice_loss 0.05978 +Epoch [903/4000] Validation [2/4] Loss: 0.18656 focal_loss 0.07751 dice_loss 0.10905 +Epoch [903/4000] Validation [3/4] Loss: 0.11105 focal_loss 0.05892 dice_loss 0.05213 +Epoch [903/4000] Validation [4/4] Loss: 0.24961 focal_loss 0.13729 dice_loss 0.11232 +Epoch [903/4000] Validation metric {'Val/mean dice_metric': 0.9690908193588257, 'Val/mean miou_metric': 0.9487583041191101, 'Val/mean f1': 0.9717614054679871, 'Val/mean precision': 0.966789722442627, 'Val/mean recall': 0.9767844676971436, 'Val/mean hd95_metric': 6.303773403167725} +Cheakpoint... +Epoch [903/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690908193588257, 'Val/mean miou_metric': 0.9487583041191101, 'Val/mean f1': 0.9717614054679871, 'Val/mean precision': 0.966789722442627, 'Val/mean recall': 0.9767844676971436, 'Val/mean hd95_metric': 6.303773403167725} +Epoch [904/4000] Training [1/16] Loss: 0.01252 +Epoch [904/4000] Training [2/16] Loss: 0.01209 +Epoch [904/4000] Training [3/16] Loss: 0.00933 +Epoch [904/4000] Training [4/16] Loss: 0.01394 +Epoch [904/4000] Training [5/16] Loss: 0.01346 +Epoch [904/4000] Training [6/16] Loss: 0.01113 +Epoch [904/4000] Training [7/16] Loss: 0.01526 +Epoch [904/4000] Training [8/16] Loss: 0.01035 +Epoch [904/4000] Training [9/16] Loss: 0.08354 +Epoch [904/4000] Training [10/16] Loss: 0.01068 +Epoch [904/4000] Training [11/16] Loss: 0.01457 +Epoch [904/4000] Training [12/16] Loss: 0.01323 +Epoch [904/4000] Training [13/16] Loss: 0.01469 +Epoch [904/4000] Training [14/16] Loss: 0.01419 +Epoch [904/4000] Training [15/16] Loss: 0.01327 +Epoch [904/4000] Training [16/16] Loss: 0.00965 +Epoch [904/4000] Training metric {'Train/mean dice_metric': 0.9886143803596497, 'Train/mean miou_metric': 0.9782963395118713, 'Train/mean f1': 0.9865847826004028, 'Train/mean precision': 0.9820443987846375, 'Train/mean recall': 0.9911673069000244, 'Train/mean hd95_metric': 2.1962122917175293} +Epoch [904/4000] Validation [1/4] Loss: 0.14419 focal_loss 0.08467 dice_loss 0.05952 +Epoch [904/4000] Validation [2/4] Loss: 0.16367 focal_loss 0.07397 dice_loss 0.08971 +Epoch [904/4000] Validation [3/4] Loss: 0.12168 focal_loss 0.05913 dice_loss 0.06255 +Epoch [904/4000] Validation [4/4] Loss: 0.17938 focal_loss 0.07754 dice_loss 0.10184 +Epoch [904/4000] Validation metric {'Val/mean dice_metric': 0.9674504995346069, 'Val/mean miou_metric': 0.9458484649658203, 'Val/mean f1': 0.9707155227661133, 'Val/mean precision': 0.9656878113746643, 'Val/mean recall': 0.9757958650588989, 'Val/mean hd95_metric': 6.9162750244140625} +Cheakpoint... +Epoch [904/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674504995346069, 'Val/mean miou_metric': 0.9458484649658203, 'Val/mean f1': 0.9707155227661133, 'Val/mean precision': 0.9656878113746643, 'Val/mean recall': 0.9757958650588989, 'Val/mean hd95_metric': 6.9162750244140625} +Epoch [905/4000] Training [1/16] Loss: 0.01033 +Epoch [905/4000] Training [2/16] Loss: 0.01692 +Epoch [905/4000] Training [3/16] Loss: 0.01543 +Epoch [905/4000] Training [4/16] Loss: 0.01785 +Epoch [905/4000] Training [5/16] Loss: 0.01119 +Epoch [905/4000] Training [6/16] Loss: 0.01822 +Epoch [905/4000] Training [7/16] Loss: 0.01217 +Epoch [905/4000] Training [8/16] Loss: 0.00964 +Epoch [905/4000] Training [9/16] Loss: 0.01353 +Epoch [905/4000] Training [10/16] Loss: 0.01341 +Epoch [905/4000] Training [11/16] Loss: 0.01335 +Epoch [905/4000] Training [12/16] Loss: 0.01030 +Epoch [905/4000] Training [13/16] Loss: 0.01500 +Epoch [905/4000] Training [14/16] Loss: 0.01411 +Epoch [905/4000] Training [15/16] Loss: 0.01058 +Epoch [905/4000] Training [16/16] Loss: 0.01820 +Epoch [905/4000] Training metric {'Train/mean dice_metric': 0.990125298500061, 'Train/mean miou_metric': 0.9802608489990234, 'Train/mean f1': 0.9869840145111084, 'Train/mean precision': 0.9820964336395264, 'Train/mean recall': 0.9919204711914062, 'Train/mean hd95_metric': 1.3430688381195068} +Epoch [905/4000] Validation [1/4] Loss: 0.31094 focal_loss 0.21615 dice_loss 0.09479 +Epoch [905/4000] Validation [2/4] Loss: 0.44004 focal_loss 0.24034 dice_loss 0.19970 +Epoch [905/4000] Validation [3/4] Loss: 0.27432 focal_loss 0.15140 dice_loss 0.12292 +Epoch [905/4000] Validation [4/4] Loss: 0.18244 focal_loss 0.09154 dice_loss 0.09090 +Epoch [905/4000] Validation metric {'Val/mean dice_metric': 0.9658054113388062, 'Val/mean miou_metric': 0.9438838958740234, 'Val/mean f1': 0.9672422409057617, 'Val/mean precision': 0.9666662216186523, 'Val/mean recall': 0.9678189754486084, 'Val/mean hd95_metric': 6.602400302886963} +Cheakpoint... +Epoch [905/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658054113388062, 'Val/mean miou_metric': 0.9438838958740234, 'Val/mean f1': 0.9672422409057617, 'Val/mean precision': 0.9666662216186523, 'Val/mean recall': 0.9678189754486084, 'Val/mean hd95_metric': 6.602400302886963} +Epoch [906/4000] Training [1/16] Loss: 0.01411 +Epoch [906/4000] Training [2/16] Loss: 0.01236 +Epoch [906/4000] Training [3/16] Loss: 0.00967 +Epoch [906/4000] Training [4/16] Loss: 0.01270 +Epoch [906/4000] Training [5/16] Loss: 0.01115 +Epoch [906/4000] Training [6/16] Loss: 0.01890 +Epoch [906/4000] Training [7/16] Loss: 0.01307 +Epoch [906/4000] Training [8/16] Loss: 0.01222 +Epoch [906/4000] Training [9/16] Loss: 0.00965 +Epoch [906/4000] Training [10/16] Loss: 0.01005 +Epoch [906/4000] Training [11/16] Loss: 0.01167 +Epoch [906/4000] Training [12/16] Loss: 0.01516 +Epoch [906/4000] Training [13/16] Loss: 0.01112 +Epoch [906/4000] Training [14/16] Loss: 0.01033 +Epoch [906/4000] Training [15/16] Loss: 0.01268 +Epoch [906/4000] Training [16/16] Loss: 0.01201 +Epoch [906/4000] Training metric {'Train/mean dice_metric': 0.9913660883903503, 'Train/mean miou_metric': 0.9826539754867554, 'Train/mean f1': 0.9879348874092102, 'Train/mean precision': 0.983282744884491, 'Train/mean recall': 0.9926313161849976, 'Train/mean hd95_metric': 1.2931848764419556} +Epoch [906/4000] Validation [1/4] Loss: 0.30064 focal_loss 0.21736 dice_loss 0.08328 +Epoch [906/4000] Validation [2/4] Loss: 0.25681 focal_loss 0.10708 dice_loss 0.14974 +Epoch [906/4000] Validation [3/4] Loss: 0.14882 focal_loss 0.08070 dice_loss 0.06812 +Epoch [906/4000] Validation [4/4] Loss: 0.24260 focal_loss 0.13559 dice_loss 0.10701 +Epoch [906/4000] Validation metric {'Val/mean dice_metric': 0.9667829275131226, 'Val/mean miou_metric': 0.9460350871086121, 'Val/mean f1': 0.9702060222625732, 'Val/mean precision': 0.9701595902442932, 'Val/mean recall': 0.9702526926994324, 'Val/mean hd95_metric': 5.712063312530518} +Cheakpoint... +Epoch [906/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667829275131226, 'Val/mean miou_metric': 0.9460350871086121, 'Val/mean f1': 0.9702060222625732, 'Val/mean precision': 0.9701595902442932, 'Val/mean recall': 0.9702526926994324, 'Val/mean hd95_metric': 5.712063312530518} +Epoch [907/4000] Training [1/16] Loss: 0.00987 +Epoch [907/4000] Training [2/16] Loss: 0.01212 +Epoch [907/4000] Training [3/16] Loss: 0.01239 +Epoch [907/4000] Training [4/16] Loss: 0.01034 +Epoch [907/4000] Training [5/16] Loss: 0.01313 +Epoch [907/4000] Training [6/16] Loss: 0.01365 +Epoch [907/4000] Training [7/16] Loss: 0.01284 +Epoch [907/4000] Training [8/16] Loss: 0.00991 +Epoch [907/4000] Training [9/16] Loss: 0.01452 +Epoch [907/4000] Training [10/16] Loss: 0.01415 +Epoch [907/4000] Training [11/16] Loss: 0.01313 +Epoch [907/4000] Training [12/16] Loss: 0.01476 +Epoch [907/4000] Training [13/16] Loss: 0.01095 +Epoch [907/4000] Training [14/16] Loss: 0.01172 +Epoch [907/4000] Training [15/16] Loss: 0.01982 +Epoch [907/4000] Training [16/16] Loss: 0.02938 +Epoch [907/4000] Training metric {'Train/mean dice_metric': 0.9911316633224487, 'Train/mean miou_metric': 0.9822885990142822, 'Train/mean f1': 0.9882003664970398, 'Train/mean precision': 0.9835687279701233, 'Train/mean recall': 0.9928758144378662, 'Train/mean hd95_metric': 1.2176036834716797} +Epoch [907/4000] Validation [1/4] Loss: 0.14284 focal_loss 0.08940 dice_loss 0.05344 +Epoch [907/4000] Validation [2/4] Loss: 0.25029 focal_loss 0.11522 dice_loss 0.13507 +Epoch [907/4000] Validation [3/4] Loss: 0.15531 focal_loss 0.07820 dice_loss 0.07711 +Epoch [907/4000] Validation [4/4] Loss: 0.31854 focal_loss 0.18813 dice_loss 0.13041 +Epoch [907/4000] Validation metric {'Val/mean dice_metric': 0.9684562683105469, 'Val/mean miou_metric': 0.9477447271347046, 'Val/mean f1': 0.9703741669654846, 'Val/mean precision': 0.9657538533210754, 'Val/mean recall': 0.9750390648841858, 'Val/mean hd95_metric': 6.532979488372803} +Cheakpoint... +Epoch [907/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684562683105469, 'Val/mean miou_metric': 0.9477447271347046, 'Val/mean f1': 0.9703741669654846, 'Val/mean precision': 0.9657538533210754, 'Val/mean recall': 0.9750390648841858, 'Val/mean hd95_metric': 6.532979488372803} +Epoch [908/4000] Training [1/16] Loss: 0.01378 +Epoch [908/4000] Training [2/16] Loss: 0.01165 +Epoch [908/4000] Training [3/16] Loss: 0.01153 +Epoch [908/4000] Training [4/16] Loss: 0.01006 +Epoch [908/4000] Training [5/16] Loss: 0.01492 +Epoch [908/4000] Training [6/16] Loss: 0.01209 +Epoch [908/4000] Training [7/16] Loss: 0.01507 +Epoch [908/4000] Training [8/16] Loss: 0.01215 +Epoch [908/4000] Training [9/16] Loss: 0.00950 +Epoch [908/4000] Training [10/16] Loss: 0.01581 +Epoch [908/4000] Training [11/16] Loss: 0.01424 +Epoch [908/4000] Training [12/16] Loss: 0.00861 +Epoch [908/4000] Training [13/16] Loss: 0.01687 +Epoch [908/4000] Training [14/16] Loss: 0.01730 +Epoch [908/4000] Training [15/16] Loss: 0.01210 +Epoch [908/4000] Training [16/16] Loss: 0.01065 +Epoch [908/4000] Training metric {'Train/mean dice_metric': 0.9912937879562378, 'Train/mean miou_metric': 0.9825199842453003, 'Train/mean f1': 0.9879071116447449, 'Train/mean precision': 0.9833151698112488, 'Train/mean recall': 0.9925421476364136, 'Train/mean hd95_metric': 1.1923280954360962} +Epoch [908/4000] Validation [1/4] Loss: 0.35312 focal_loss 0.25554 dice_loss 0.09758 +Epoch [908/4000] Validation [2/4] Loss: 0.30903 focal_loss 0.15408 dice_loss 0.15495 +Epoch [908/4000] Validation [3/4] Loss: 0.11582 focal_loss 0.05612 dice_loss 0.05970 +Epoch [908/4000] Validation [4/4] Loss: 0.21468 focal_loss 0.11886 dice_loss 0.09582 +Epoch [908/4000] Validation metric {'Val/mean dice_metric': 0.9678840637207031, 'Val/mean miou_metric': 0.9477971196174622, 'Val/mean f1': 0.9699230790138245, 'Val/mean precision': 0.9671940207481384, 'Val/mean recall': 0.9726676940917969, 'Val/mean hd95_metric': 5.868288993835449} +Cheakpoint... +Epoch [908/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678840637207031, 'Val/mean miou_metric': 0.9477971196174622, 'Val/mean f1': 0.9699230790138245, 'Val/mean precision': 0.9671940207481384, 'Val/mean recall': 0.9726676940917969, 'Val/mean hd95_metric': 5.868288993835449} +Epoch [909/4000] Training [1/16] Loss: 0.01201 +Epoch [909/4000] Training [2/16] Loss: 0.01355 +Epoch [909/4000] Training [3/16] Loss: 0.01035 +Epoch [909/4000] Training [4/16] Loss: 0.01038 +Epoch [909/4000] Training [5/16] Loss: 0.00949 +Epoch [909/4000] Training [6/16] Loss: 0.01143 +Epoch [909/4000] Training [7/16] Loss: 0.01700 +Epoch [909/4000] Training [8/16] Loss: 0.01098 +Epoch [909/4000] Training [9/16] Loss: 0.01054 +Epoch [909/4000] Training [10/16] Loss: 0.01056 +Epoch [909/4000] Training [11/16] Loss: 0.01239 +Epoch [909/4000] Training [12/16] Loss: 0.01172 +Epoch [909/4000] Training [13/16] Loss: 0.01195 +Epoch [909/4000] Training [14/16] Loss: 0.01245 +Epoch [909/4000] Training [15/16] Loss: 0.00946 +Epoch [909/4000] Training [16/16] Loss: 0.01646 +Epoch [909/4000] Training metric {'Train/mean dice_metric': 0.9921066164970398, 'Train/mean miou_metric': 0.9841275215148926, 'Train/mean f1': 0.9888041019439697, 'Train/mean precision': 0.9842714071273804, 'Train/mean recall': 0.993378758430481, 'Train/mean hd95_metric': 1.1651586294174194} +Epoch [909/4000] Validation [1/4] Loss: 0.22732 focal_loss 0.15260 dice_loss 0.07472 +Epoch [909/4000] Validation [2/4] Loss: 0.19581 focal_loss 0.09111 dice_loss 0.10469 +Epoch [909/4000] Validation [3/4] Loss: 0.14600 focal_loss 0.08504 dice_loss 0.06096 +Epoch [909/4000] Validation [4/4] Loss: 0.17198 focal_loss 0.08550 dice_loss 0.08648 +Epoch [909/4000] Validation metric {'Val/mean dice_metric': 0.9716132879257202, 'Val/mean miou_metric': 0.9522442817687988, 'Val/mean f1': 0.9726584553718567, 'Val/mean precision': 0.966710090637207, 'Val/mean recall': 0.978680431842804, 'Val/mean hd95_metric': 6.813704013824463} +Cheakpoint... +Epoch [909/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716132879257202, 'Val/mean miou_metric': 0.9522442817687988, 'Val/mean f1': 0.9726584553718567, 'Val/mean precision': 0.966710090637207, 'Val/mean recall': 0.978680431842804, 'Val/mean hd95_metric': 6.813704013824463} +Epoch [910/4000] Training [1/16] Loss: 0.01045 +Epoch [910/4000] Training [2/16] Loss: 0.01178 +Epoch [910/4000] Training [3/16] Loss: 0.01505 +Epoch [910/4000] Training [4/16] Loss: 0.01293 +Epoch [910/4000] Training [5/16] Loss: 0.00833 +Epoch [910/4000] Training [6/16] Loss: 0.01205 +Epoch [910/4000] Training [7/16] Loss: 0.01162 +Epoch [910/4000] Training [8/16] Loss: 0.01152 +Epoch [910/4000] Training [9/16] Loss: 0.00963 +Epoch [910/4000] Training [10/16] Loss: 0.01177 +Epoch [910/4000] Training [11/16] Loss: 0.01089 +Epoch [910/4000] Training [12/16] Loss: 0.01180 +Epoch [910/4000] Training [13/16] Loss: 0.01041 +Epoch [910/4000] Training [14/16] Loss: 0.01669 +Epoch [910/4000] Training [15/16] Loss: 0.01027 +Epoch [910/4000] Training [16/16] Loss: 0.01021 +Epoch [910/4000] Training metric {'Train/mean dice_metric': 0.9916043281555176, 'Train/mean miou_metric': 0.983143150806427, 'Train/mean f1': 0.9884631037712097, 'Train/mean precision': 0.9838303327560425, 'Train/mean recall': 0.9931397438049316, 'Train/mean hd95_metric': 1.2022054195404053} +Epoch [910/4000] Validation [1/4] Loss: 0.18007 focal_loss 0.11558 dice_loss 0.06449 +Epoch [910/4000] Validation [2/4] Loss: 0.22136 focal_loss 0.10474 dice_loss 0.11663 +Epoch [910/4000] Validation [3/4] Loss: 0.15741 focal_loss 0.08539 dice_loss 0.07202 +Epoch [910/4000] Validation [4/4] Loss: 0.15388 focal_loss 0.06694 dice_loss 0.08694 +Epoch [910/4000] Validation metric {'Val/mean dice_metric': 0.9707193374633789, 'Val/mean miou_metric': 0.9507724046707153, 'Val/mean f1': 0.9719101190567017, 'Val/mean precision': 0.966926097869873, 'Val/mean recall': 0.9769458770751953, 'Val/mean hd95_metric': 6.07968282699585} +Cheakpoint... +Epoch [910/4000] best acc:tensor([0.9716], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707193374633789, 'Val/mean miou_metric': 0.9507724046707153, 'Val/mean f1': 0.9719101190567017, 'Val/mean precision': 0.966926097869873, 'Val/mean recall': 0.9769458770751953, 'Val/mean hd95_metric': 6.07968282699585} +Epoch [911/4000] Training [1/16] Loss: 0.00911 +Epoch [911/4000] Training [2/16] Loss: 0.01134 +Epoch [911/4000] Training [3/16] Loss: 0.01133 +Epoch [911/4000] Training [4/16] Loss: 0.01285 +Epoch [911/4000] Training [5/16] Loss: 0.01391 +Epoch [911/4000] Training [6/16] Loss: 0.01264 +Epoch [911/4000] Training [7/16] Loss: 0.00984 +Epoch [911/4000] Training [8/16] Loss: 0.01710 +Epoch [911/4000] Training [9/16] Loss: 0.01268 +Epoch [911/4000] Training [10/16] Loss: 0.01150 +Epoch [911/4000] Training [11/16] Loss: 0.01174 +Epoch [911/4000] Training [12/16] Loss: 0.01064 +Epoch [911/4000] Training [13/16] Loss: 0.01274 +Epoch [911/4000] Training [14/16] Loss: 0.01533 +Epoch [911/4000] Training [15/16] Loss: 0.00897 +Epoch [911/4000] Training [16/16] Loss: 0.01587 +Epoch [911/4000] Training metric {'Train/mean dice_metric': 0.9914559721946716, 'Train/mean miou_metric': 0.982840895652771, 'Train/mean f1': 0.9882065057754517, 'Train/mean precision': 0.9837967753410339, 'Train/mean recall': 0.9926559925079346, 'Train/mean hd95_metric': 1.1536822319030762} +Epoch [911/4000] Validation [1/4] Loss: 0.15211 focal_loss 0.09435 dice_loss 0.05776 +Epoch [911/4000] Validation [2/4] Loss: 0.24486 focal_loss 0.13039 dice_loss 0.11448 +Epoch [911/4000] Validation [3/4] Loss: 0.22179 focal_loss 0.12778 dice_loss 0.09401 +Epoch [911/4000] Validation [4/4] Loss: 0.32782 focal_loss 0.18088 dice_loss 0.14695 +Epoch [911/4000] Validation metric {'Val/mean dice_metric': 0.9719256162643433, 'Val/mean miou_metric': 0.9514904022216797, 'Val/mean f1': 0.97231125831604, 'Val/mean precision': 0.9678407907485962, 'Val/mean recall': 0.9768233299255371, 'Val/mean hd95_metric': 5.848616123199463} +Cheakpoint... +Epoch [911/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719256162643433, 'Val/mean miou_metric': 0.9514904022216797, 'Val/mean f1': 0.97231125831604, 'Val/mean precision': 0.9678407907485962, 'Val/mean recall': 0.9768233299255371, 'Val/mean hd95_metric': 5.848616123199463} +Epoch [912/4000] Training [1/16] Loss: 0.00987 +Epoch [912/4000] Training [2/16] Loss: 0.01145 +Epoch [912/4000] Training [3/16] Loss: 0.00984 +Epoch [912/4000] Training [4/16] Loss: 0.01424 +Epoch [912/4000] Training [5/16] Loss: 0.01470 +Epoch [912/4000] Training [6/16] Loss: 0.01563 +Epoch [912/4000] Training [7/16] Loss: 0.01761 +Epoch [912/4000] Training [8/16] Loss: 0.00947 +Epoch [912/4000] Training [9/16] Loss: 0.01597 +Epoch [912/4000] Training [10/16] Loss: 0.01176 +Epoch [912/4000] Training [11/16] Loss: 0.00895 +Epoch [912/4000] Training [12/16] Loss: 0.01194 +Epoch [912/4000] Training [13/16] Loss: 0.01175 +Epoch [912/4000] Training [14/16] Loss: 0.00961 +Epoch [912/4000] Training [15/16] Loss: 0.01134 +Epoch [912/4000] Training [16/16] Loss: 0.01049 +Epoch [912/4000] Training metric {'Train/mean dice_metric': 0.9908924102783203, 'Train/mean miou_metric': 0.9817620515823364, 'Train/mean f1': 0.9881259202957153, 'Train/mean precision': 0.9836149215698242, 'Train/mean recall': 0.9926785230636597, 'Train/mean hd95_metric': 1.1624891757965088} +Epoch [912/4000] Validation [1/4] Loss: 0.19069 focal_loss 0.12472 dice_loss 0.06597 +Epoch [912/4000] Validation [2/4] Loss: 0.22889 focal_loss 0.10813 dice_loss 0.12076 +Epoch [912/4000] Validation [3/4] Loss: 0.16137 focal_loss 0.08379 dice_loss 0.07758 +Epoch [912/4000] Validation [4/4] Loss: 0.15750 focal_loss 0.07177 dice_loss 0.08573 +Epoch [912/4000] Validation metric {'Val/mean dice_metric': 0.9701927304267883, 'Val/mean miou_metric': 0.9498427510261536, 'Val/mean f1': 0.9721636772155762, 'Val/mean precision': 0.9653878808021545, 'Val/mean recall': 0.9790353775024414, 'Val/mean hd95_metric': 6.030787467956543} +Cheakpoint... +Epoch [912/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701927304267883, 'Val/mean miou_metric': 0.9498427510261536, 'Val/mean f1': 0.9721636772155762, 'Val/mean precision': 0.9653878808021545, 'Val/mean recall': 0.9790353775024414, 'Val/mean hd95_metric': 6.030787467956543} +Epoch [913/4000] Training [1/16] Loss: 0.01294 +Epoch [913/4000] Training [2/16] Loss: 0.01282 +Epoch [913/4000] Training [3/16] Loss: 0.01504 +Epoch [913/4000] Training [4/16] Loss: 0.01135 +Epoch [913/4000] Training [5/16] Loss: 0.01230 +Epoch [913/4000] Training [6/16] Loss: 0.01027 +Epoch [913/4000] Training [7/16] Loss: 0.01873 +Epoch [913/4000] Training [8/16] Loss: 0.01542 +Epoch [913/4000] Training [9/16] Loss: 0.01282 +Epoch [913/4000] Training [10/16] Loss: 0.01713 +Epoch [913/4000] Training [11/16] Loss: 0.01090 +Epoch [913/4000] Training [12/16] Loss: 0.01260 +Epoch [913/4000] Training [13/16] Loss: 0.01195 +Epoch [913/4000] Training [14/16] Loss: 0.01437 +Epoch [913/4000] Training [15/16] Loss: 0.01254 +Epoch [913/4000] Training [16/16] Loss: 0.01312 +Epoch [913/4000] Training metric {'Train/mean dice_metric': 0.9908897876739502, 'Train/mean miou_metric': 0.9817355871200562, 'Train/mean f1': 0.987870454788208, 'Train/mean precision': 0.983640193939209, 'Train/mean recall': 0.9921372532844543, 'Train/mean hd95_metric': 1.2176564931869507} +Epoch [913/4000] Validation [1/4] Loss: 0.16924 focal_loss 0.11253 dice_loss 0.05672 +Epoch [913/4000] Validation [2/4] Loss: 0.22451 focal_loss 0.11195 dice_loss 0.11256 +Epoch [913/4000] Validation [3/4] Loss: 0.12407 focal_loss 0.06699 dice_loss 0.05708 +Epoch [913/4000] Validation [4/4] Loss: 0.23151 focal_loss 0.12232 dice_loss 0.10919 +Epoch [913/4000] Validation metric {'Val/mean dice_metric': 0.9702962636947632, 'Val/mean miou_metric': 0.9502533078193665, 'Val/mean f1': 0.9717623591423035, 'Val/mean precision': 0.9660184979438782, 'Val/mean recall': 0.97757488489151, 'Val/mean hd95_metric': 5.771788120269775} +Cheakpoint... +Epoch [913/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702962636947632, 'Val/mean miou_metric': 0.9502533078193665, 'Val/mean f1': 0.9717623591423035, 'Val/mean precision': 0.9660184979438782, 'Val/mean recall': 0.97757488489151, 'Val/mean hd95_metric': 5.771788120269775} +Epoch [914/4000] Training [1/16] Loss: 0.01466 +Epoch [914/4000] Training [2/16] Loss: 0.01210 +Epoch [914/4000] Training [3/16] Loss: 0.01113 +Epoch [914/4000] Training [4/16] Loss: 0.01463 +Epoch [914/4000] Training [5/16] Loss: 0.01387 +Epoch [914/4000] Training [6/16] Loss: 0.01246 +Epoch [914/4000] Training [7/16] Loss: 0.01338 +Epoch [914/4000] Training [8/16] Loss: 0.01391 +Epoch [914/4000] Training [9/16] Loss: 0.01488 +Epoch [914/4000] Training [10/16] Loss: 0.01484 +Epoch [914/4000] Training [11/16] Loss: 0.01175 +Epoch [914/4000] Training [12/16] Loss: 0.01095 +Epoch [914/4000] Training [13/16] Loss: 0.01966 +Epoch [914/4000] Training [14/16] Loss: 0.00872 +Epoch [914/4000] Training [15/16] Loss: 0.01196 +Epoch [914/4000] Training [16/16] Loss: 0.01487 +Epoch [914/4000] Training metric {'Train/mean dice_metric': 0.9908344745635986, 'Train/mean miou_metric': 0.9816247224807739, 'Train/mean f1': 0.9877259135246277, 'Train/mean precision': 0.983017086982727, 'Train/mean recall': 0.9924800992012024, 'Train/mean hd95_metric': 1.323758840560913} +Epoch [914/4000] Validation [1/4] Loss: 0.16485 focal_loss 0.10583 dice_loss 0.05902 +Epoch [914/4000] Validation [2/4] Loss: 0.28060 focal_loss 0.15064 dice_loss 0.12996 +Epoch [914/4000] Validation [3/4] Loss: 0.12357 focal_loss 0.06693 dice_loss 0.05665 +Epoch [914/4000] Validation [4/4] Loss: 0.21721 focal_loss 0.12048 dice_loss 0.09673 +Epoch [914/4000] Validation metric {'Val/mean dice_metric': 0.9707315564155579, 'Val/mean miou_metric': 0.9501286745071411, 'Val/mean f1': 0.9718548059463501, 'Val/mean precision': 0.968183159828186, 'Val/mean recall': 0.9755544662475586, 'Val/mean hd95_metric': 6.1547532081604} +Cheakpoint... +Epoch [914/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707315564155579, 'Val/mean miou_metric': 0.9501286745071411, 'Val/mean f1': 0.9718548059463501, 'Val/mean precision': 0.968183159828186, 'Val/mean recall': 0.9755544662475586, 'Val/mean hd95_metric': 6.1547532081604} +Epoch [915/4000] Training [1/16] Loss: 0.09822 +Epoch [915/4000] Training [2/16] Loss: 0.01174 +Epoch [915/4000] Training [3/16] Loss: 0.01646 +Epoch [915/4000] Training [4/16] Loss: 0.01182 +Epoch [915/4000] Training [5/16] Loss: 0.01612 +Epoch [915/4000] Training [6/16] Loss: 0.01135 +Epoch [915/4000] Training [7/16] Loss: 0.01144 +Epoch [915/4000] Training [8/16] Loss: 0.01014 +Epoch [915/4000] Training [9/16] Loss: 0.01925 +Epoch [915/4000] Training [10/16] Loss: 0.01518 +Epoch [915/4000] Training [11/16] Loss: 0.01233 +Epoch [915/4000] Training [12/16] Loss: 0.00942 +Epoch [915/4000] Training [13/16] Loss: 0.01447 +Epoch [915/4000] Training [14/16] Loss: 0.01504 +Epoch [915/4000] Training [15/16] Loss: 0.01077 +Epoch [915/4000] Training [16/16] Loss: 0.01368 +Epoch [915/4000] Training metric {'Train/mean dice_metric': 0.990585446357727, 'Train/mean miou_metric': 0.9813536405563354, 'Train/mean f1': 0.9865846037864685, 'Train/mean precision': 0.9809392094612122, 'Train/mean recall': 0.9922953248023987, 'Train/mean hd95_metric': 1.2486162185668945} +Epoch [915/4000] Validation [1/4] Loss: 0.13484 focal_loss 0.08048 dice_loss 0.05435 +Epoch [915/4000] Validation [2/4] Loss: 0.33432 focal_loss 0.16674 dice_loss 0.16758 +Epoch [915/4000] Validation [3/4] Loss: 0.12546 focal_loss 0.06609 dice_loss 0.05937 +Epoch [915/4000] Validation [4/4] Loss: 0.20070 focal_loss 0.10212 dice_loss 0.09857 +Epoch [915/4000] Validation metric {'Val/mean dice_metric': 0.9703011512756348, 'Val/mean miou_metric': 0.949957013130188, 'Val/mean f1': 0.9706876277923584, 'Val/mean precision': 0.9636304974555969, 'Val/mean recall': 0.9778488874435425, 'Val/mean hd95_metric': 6.280035495758057} +Cheakpoint... +Epoch [915/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703011512756348, 'Val/mean miou_metric': 0.949957013130188, 'Val/mean f1': 0.9706876277923584, 'Val/mean precision': 0.9636304974555969, 'Val/mean recall': 0.9778488874435425, 'Val/mean hd95_metric': 6.280035495758057} +Epoch [916/4000] Training [1/16] Loss: 0.01111 +Epoch [916/4000] Training [2/16] Loss: 0.01151 +Epoch [916/4000] Training [3/16] Loss: 0.01125 +Epoch [916/4000] Training [4/16] Loss: 0.01452 +Epoch [916/4000] Training [5/16] Loss: 0.01193 +Epoch [916/4000] Training [6/16] Loss: 0.01031 +Epoch [916/4000] Training [7/16] Loss: 0.01385 +Epoch [916/4000] Training [8/16] Loss: 0.01500 +Epoch [916/4000] Training [9/16] Loss: 0.01289 +Epoch [916/4000] Training [10/16] Loss: 0.01186 +Epoch [916/4000] Training [11/16] Loss: 0.01061 +Epoch [916/4000] Training [12/16] Loss: 0.01924 +Epoch [916/4000] Training [13/16] Loss: 0.00954 +Epoch [916/4000] Training [14/16] Loss: 0.01415 +Epoch [916/4000] Training [15/16] Loss: 0.01413 +Epoch [916/4000] Training [16/16] Loss: 0.01531 +Epoch [916/4000] Training metric {'Train/mean dice_metric': 0.9913939237594604, 'Train/mean miou_metric': 0.982710599899292, 'Train/mean f1': 0.9876255989074707, 'Train/mean precision': 0.9824234843254089, 'Train/mean recall': 0.9928830862045288, 'Train/mean hd95_metric': 1.2001327276229858} +Epoch [916/4000] Validation [1/4] Loss: 0.35688 focal_loss 0.24527 dice_loss 0.11161 +Epoch [916/4000] Validation [2/4] Loss: 0.24044 focal_loss 0.10427 dice_loss 0.13617 +Epoch [916/4000] Validation [3/4] Loss: 0.18686 focal_loss 0.10571 dice_loss 0.08114 +Epoch [916/4000] Validation [4/4] Loss: 0.18286 focal_loss 0.09121 dice_loss 0.09165 +Epoch [916/4000] Validation metric {'Val/mean dice_metric': 0.9699662923812866, 'Val/mean miou_metric': 0.9496191143989563, 'Val/mean f1': 0.9686864614486694, 'Val/mean precision': 0.9653898477554321, 'Val/mean recall': 0.9720057845115662, 'Val/mean hd95_metric': 5.945700645446777} +Cheakpoint... +Epoch [916/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699662923812866, 'Val/mean miou_metric': 0.9496191143989563, 'Val/mean f1': 0.9686864614486694, 'Val/mean precision': 0.9653898477554321, 'Val/mean recall': 0.9720057845115662, 'Val/mean hd95_metric': 5.945700645446777} +Epoch [917/4000] Training [1/16] Loss: 0.01438 +Epoch [917/4000] Training [2/16] Loss: 0.01393 +Epoch [917/4000] Training [3/16] Loss: 0.01234 +Epoch [917/4000] Training [4/16] Loss: 0.01186 +Epoch [917/4000] Training [5/16] Loss: 0.01557 +Epoch [917/4000] Training [6/16] Loss: 0.01185 +Epoch [917/4000] Training [7/16] Loss: 0.01129 +Epoch [917/4000] Training [8/16] Loss: 0.01408 +Epoch [917/4000] Training [9/16] Loss: 0.01574 +Epoch [917/4000] Training [10/16] Loss: 0.01191 +Epoch [917/4000] Training [11/16] Loss: 0.01163 +Epoch [917/4000] Training [12/16] Loss: 0.01133 +Epoch [917/4000] Training [13/16] Loss: 0.01019 +Epoch [917/4000] Training [14/16] Loss: 0.00971 +Epoch [917/4000] Training [15/16] Loss: 0.01227 +Epoch [917/4000] Training [16/16] Loss: 0.01398 +Epoch [917/4000] Training metric {'Train/mean dice_metric': 0.9914537668228149, 'Train/mean miou_metric': 0.9828482866287231, 'Train/mean f1': 0.9884046316146851, 'Train/mean precision': 0.9840010404586792, 'Train/mean recall': 0.9928478598594666, 'Train/mean hd95_metric': 1.1640115976333618} +Epoch [917/4000] Validation [1/4] Loss: 0.34536 focal_loss 0.24209 dice_loss 0.10327 +Epoch [917/4000] Validation [2/4] Loss: 0.43325 focal_loss 0.21417 dice_loss 0.21908 +Epoch [917/4000] Validation [3/4] Loss: 0.17817 focal_loss 0.08489 dice_loss 0.09328 +Epoch [917/4000] Validation [4/4] Loss: 0.18102 focal_loss 0.08668 dice_loss 0.09434 +Epoch [917/4000] Validation metric {'Val/mean dice_metric': 0.9692277908325195, 'Val/mean miou_metric': 0.9492489695549011, 'Val/mean f1': 0.9708336591720581, 'Val/mean precision': 0.9707334041595459, 'Val/mean recall': 0.9709339141845703, 'Val/mean hd95_metric': 5.3046698570251465} +Cheakpoint... +Epoch [917/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692277908325195, 'Val/mean miou_metric': 0.9492489695549011, 'Val/mean f1': 0.9708336591720581, 'Val/mean precision': 0.9707334041595459, 'Val/mean recall': 0.9709339141845703, 'Val/mean hd95_metric': 5.3046698570251465} +Epoch [918/4000] Training [1/16] Loss: 0.01080 +Epoch [918/4000] Training [2/16] Loss: 0.01507 +Epoch [918/4000] Training [3/16] Loss: 0.01419 +Epoch [918/4000] Training [4/16] Loss: 0.01113 +Epoch [918/4000] Training [5/16] Loss: 0.01216 +Epoch [918/4000] Training [6/16] Loss: 0.01427 +Epoch [918/4000] Training [7/16] Loss: 0.01108 +Epoch [918/4000] Training [8/16] Loss: 0.01059 +Epoch [918/4000] Training [9/16] Loss: 0.01075 +Epoch [918/4000] Training [10/16] Loss: 0.01226 +Epoch [918/4000] Training [11/16] Loss: 0.00853 +Epoch [918/4000] Training [12/16] Loss: 0.00967 +Epoch [918/4000] Training [13/16] Loss: 0.01434 +Epoch [918/4000] Training [14/16] Loss: 0.00937 +Epoch [918/4000] Training [15/16] Loss: 0.01049 +Epoch [918/4000] Training [16/16] Loss: 0.01139 +Epoch [918/4000] Training metric {'Train/mean dice_metric': 0.9920607805252075, 'Train/mean miou_metric': 0.9840287566184998, 'Train/mean f1': 0.9888944029808044, 'Train/mean precision': 0.9843137264251709, 'Train/mean recall': 0.9935178756713867, 'Train/mean hd95_metric': 1.1209083795547485} +Epoch [918/4000] Validation [1/4] Loss: 0.27297 focal_loss 0.18347 dice_loss 0.08950 +Epoch [918/4000] Validation [2/4] Loss: 0.25344 focal_loss 0.12123 dice_loss 0.13220 +Epoch [918/4000] Validation [3/4] Loss: 0.20527 focal_loss 0.12676 dice_loss 0.07851 +Epoch [918/4000] Validation [4/4] Loss: 0.17306 focal_loss 0.09234 dice_loss 0.08072 +Epoch [918/4000] Validation metric {'Val/mean dice_metric': 0.9709993600845337, 'Val/mean miou_metric': 0.9510898590087891, 'Val/mean f1': 0.9709309935569763, 'Val/mean precision': 0.9690618515014648, 'Val/mean recall': 0.9728073477745056, 'Val/mean hd95_metric': 5.512256622314453} +Cheakpoint... +Epoch [918/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709993600845337, 'Val/mean miou_metric': 0.9510898590087891, 'Val/mean f1': 0.9709309935569763, 'Val/mean precision': 0.9690618515014648, 'Val/mean recall': 0.9728073477745056, 'Val/mean hd95_metric': 5.512256622314453} +Epoch [919/4000] Training [1/16] Loss: 0.00820 +Epoch [919/4000] Training [2/16] Loss: 0.01230 +Epoch [919/4000] Training [3/16] Loss: 0.01338 +Epoch [919/4000] Training [4/16] Loss: 0.01143 +Epoch [919/4000] Training [5/16] Loss: 0.01436 +Epoch [919/4000] Training [6/16] Loss: 0.01356 +Epoch [919/4000] Training [7/16] Loss: 0.01164 +Epoch [919/4000] Training [8/16] Loss: 0.01075 +Epoch [919/4000] Training [9/16] Loss: 0.00939 +Epoch [919/4000] Training [10/16] Loss: 0.00989 +Epoch [919/4000] Training [11/16] Loss: 0.00866 +Epoch [919/4000] Training [12/16] Loss: 0.01223 +Epoch [919/4000] Training [13/16] Loss: 0.01303 +Epoch [919/4000] Training [14/16] Loss: 0.01116 +Epoch [919/4000] Training [15/16] Loss: 0.01048 +Epoch [919/4000] Training [16/16] Loss: 0.01329 +Epoch [919/4000] Training metric {'Train/mean dice_metric': 0.9920143485069275, 'Train/mean miou_metric': 0.9839416742324829, 'Train/mean f1': 0.9886693358421326, 'Train/mean precision': 0.9842349290847778, 'Train/mean recall': 0.9931439161300659, 'Train/mean hd95_metric': 1.1457006931304932} +Epoch [919/4000] Validation [1/4] Loss: 0.20043 focal_loss 0.12600 dice_loss 0.07443 +Epoch [919/4000] Validation [2/4] Loss: 0.25498 focal_loss 0.12284 dice_loss 0.13214 +Epoch [919/4000] Validation [3/4] Loss: 0.27158 focal_loss 0.15977 dice_loss 0.11180 +Epoch [919/4000] Validation [4/4] Loss: 0.25298 focal_loss 0.13971 dice_loss 0.11327 +Epoch [919/4000] Validation metric {'Val/mean dice_metric': 0.9704073071479797, 'Val/mean miou_metric': 0.9500991702079773, 'Val/mean f1': 0.9709116816520691, 'Val/mean precision': 0.9665167331695557, 'Val/mean recall': 0.9753469228744507, 'Val/mean hd95_metric': 6.800454616546631} +Cheakpoint... +Epoch [919/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704073071479797, 'Val/mean miou_metric': 0.9500991702079773, 'Val/mean f1': 0.9709116816520691, 'Val/mean precision': 0.9665167331695557, 'Val/mean recall': 0.9753469228744507, 'Val/mean hd95_metric': 6.800454616546631} +Epoch [920/4000] Training [1/16] Loss: 0.00915 +Epoch [920/4000] Training [2/16] Loss: 0.01042 +Epoch [920/4000] Training [3/16] Loss: 0.01082 +Epoch [920/4000] Training [4/16] Loss: 0.01397 +Epoch [920/4000] Training [5/16] Loss: 0.01063 +Epoch [920/4000] Training [6/16] Loss: 0.01707 +Epoch [920/4000] Training [7/16] Loss: 0.01086 +Epoch [920/4000] Training [8/16] Loss: 0.01154 +Epoch [920/4000] Training [9/16] Loss: 0.01327 +Epoch [920/4000] Training [10/16] Loss: 0.01570 +Epoch [920/4000] Training [11/16] Loss: 0.01277 +Epoch [920/4000] Training [12/16] Loss: 0.01332 +Epoch [920/4000] Training [13/16] Loss: 0.01053 +Epoch [920/4000] Training [14/16] Loss: 0.01092 +Epoch [920/4000] Training [15/16] Loss: 0.01186 +Epoch [920/4000] Training [16/16] Loss: 0.00973 +Epoch [920/4000] Training metric {'Train/mean dice_metric': 0.9916408658027649, 'Train/mean miou_metric': 0.9831932783126831, 'Train/mean f1': 0.988564670085907, 'Train/mean precision': 0.9840015769004822, 'Train/mean recall': 0.9931702017784119, 'Train/mean hd95_metric': 1.135968804359436} +Epoch [920/4000] Validation [1/4] Loss: 0.16405 focal_loss 0.10040 dice_loss 0.06365 +Epoch [920/4000] Validation [2/4] Loss: 0.26151 focal_loss 0.12757 dice_loss 0.13394 +Epoch [920/4000] Validation [3/4] Loss: 0.16199 focal_loss 0.08191 dice_loss 0.08008 +Epoch [920/4000] Validation [4/4] Loss: 0.22644 focal_loss 0.11706 dice_loss 0.10938 +Epoch [920/4000] Validation metric {'Val/mean dice_metric': 0.9710162281990051, 'Val/mean miou_metric': 0.9506254196166992, 'Val/mean f1': 0.9720640778541565, 'Val/mean precision': 0.9674631357192993, 'Val/mean recall': 0.9767088890075684, 'Val/mean hd95_metric': 5.871114253997803} +Cheakpoint... +Epoch [920/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710162281990051, 'Val/mean miou_metric': 0.9506254196166992, 'Val/mean f1': 0.9720640778541565, 'Val/mean precision': 0.9674631357192993, 'Val/mean recall': 0.9767088890075684, 'Val/mean hd95_metric': 5.871114253997803} +Epoch [921/4000] Training [1/16] Loss: 0.01254 +Epoch [921/4000] Training [2/16] Loss: 0.00962 +Epoch [921/4000] Training [3/16] Loss: 0.01273 +Epoch [921/4000] Training [4/16] Loss: 0.00899 +Epoch [921/4000] Training [5/16] Loss: 0.01306 +Epoch [921/4000] Training [6/16] Loss: 0.01031 +Epoch [921/4000] Training [7/16] Loss: 0.01247 +Epoch [921/4000] Training [8/16] Loss: 0.01402 +Epoch [921/4000] Training [9/16] Loss: 0.01043 +Epoch [921/4000] Training [10/16] Loss: 0.00992 +Epoch [921/4000] Training [11/16] Loss: 0.00996 +Epoch [921/4000] Training [12/16] Loss: 0.01237 +Epoch [921/4000] Training [13/16] Loss: 0.01134 +Epoch [921/4000] Training [14/16] Loss: 0.01141 +Epoch [921/4000] Training [15/16] Loss: 0.01236 +Epoch [921/4000] Training [16/16] Loss: 0.01270 +Epoch [921/4000] Training metric {'Train/mean dice_metric': 0.9917211532592773, 'Train/mean miou_metric': 0.9833905696868896, 'Train/mean f1': 0.9886539578437805, 'Train/mean precision': 0.9842324256896973, 'Train/mean recall': 0.9931154847145081, 'Train/mean hd95_metric': 1.1240742206573486} +Epoch [921/4000] Validation [1/4] Loss: 0.33648 focal_loss 0.22692 dice_loss 0.10956 +Epoch [921/4000] Validation [2/4] Loss: 0.23145 focal_loss 0.11100 dice_loss 0.12045 +Epoch [921/4000] Validation [3/4] Loss: 0.26902 focal_loss 0.15731 dice_loss 0.11171 +Epoch [921/4000] Validation [4/4] Loss: 0.16029 focal_loss 0.07867 dice_loss 0.08162 +Epoch [921/4000] Validation metric {'Val/mean dice_metric': 0.9701642990112305, 'Val/mean miou_metric': 0.9501201510429382, 'Val/mean f1': 0.9707474708557129, 'Val/mean precision': 0.9663684368133545, 'Val/mean recall': 0.9751664996147156, 'Val/mean hd95_metric': 6.07212495803833} +Cheakpoint... +Epoch [921/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701642990112305, 'Val/mean miou_metric': 0.9501201510429382, 'Val/mean f1': 0.9707474708557129, 'Val/mean precision': 0.9663684368133545, 'Val/mean recall': 0.9751664996147156, 'Val/mean hd95_metric': 6.07212495803833} +Epoch [922/4000] Training [1/16] Loss: 0.00870 +Epoch [922/4000] Training [2/16] Loss: 0.01034 +Epoch [922/4000] Training [3/16] Loss: 0.01120 +Epoch [922/4000] Training [4/16] Loss: 0.01223 +Epoch [922/4000] Training [5/16] Loss: 0.01130 +Epoch [922/4000] Training [6/16] Loss: 0.01422 +Epoch [922/4000] Training [7/16] Loss: 0.01074 +Epoch [922/4000] Training [8/16] Loss: 0.01732 +Epoch [922/4000] Training [9/16] Loss: 0.01494 +Epoch [922/4000] Training [10/16] Loss: 0.00981 +Epoch [922/4000] Training [11/16] Loss: 0.02005 +Epoch [922/4000] Training [12/16] Loss: 0.01508 +Epoch [922/4000] Training [13/16] Loss: 0.01411 +Epoch [922/4000] Training [14/16] Loss: 0.01396 +Epoch [922/4000] Training [15/16] Loss: 0.01397 +Epoch [922/4000] Training [16/16] Loss: 0.01180 +Epoch [922/4000] Training metric {'Train/mean dice_metric': 0.9915773868560791, 'Train/mean miou_metric': 0.983085036277771, 'Train/mean f1': 0.9884162545204163, 'Train/mean precision': 0.9838892817497253, 'Train/mean recall': 0.9929850697517395, 'Train/mean hd95_metric': 1.1452531814575195} +Epoch [922/4000] Validation [1/4] Loss: 0.17403 focal_loss 0.10912 dice_loss 0.06491 +Epoch [922/4000] Validation [2/4] Loss: 0.22215 focal_loss 0.10681 dice_loss 0.11534 +Epoch [922/4000] Validation [3/4] Loss: 0.17990 focal_loss 0.09275 dice_loss 0.08716 +Epoch [922/4000] Validation [4/4] Loss: 0.19476 focal_loss 0.09633 dice_loss 0.09843 +Epoch [922/4000] Validation metric {'Val/mean dice_metric': 0.9714007377624512, 'Val/mean miou_metric': 0.9514180421829224, 'Val/mean f1': 0.9717457294464111, 'Val/mean precision': 0.9650355577468872, 'Val/mean recall': 0.9785498380661011, 'Val/mean hd95_metric': 5.87912654876709} +Cheakpoint... +Epoch [922/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714007377624512, 'Val/mean miou_metric': 0.9514180421829224, 'Val/mean f1': 0.9717457294464111, 'Val/mean precision': 0.9650355577468872, 'Val/mean recall': 0.9785498380661011, 'Val/mean hd95_metric': 5.87912654876709} +Epoch [923/4000] Training [1/16] Loss: 0.01153 +Epoch [923/4000] Training [2/16] Loss: 0.01437 +Epoch [923/4000] Training [3/16] Loss: 0.01348 +Epoch [923/4000] Training [4/16] Loss: 0.01399 +Epoch [923/4000] Training [5/16] Loss: 0.01142 +Epoch [923/4000] Training [6/16] Loss: 0.01232 +Epoch [923/4000] Training [7/16] Loss: 0.01116 +Epoch [923/4000] Training [8/16] Loss: 0.01483 +Epoch [923/4000] Training [9/16] Loss: 0.01318 +Epoch [923/4000] Training [10/16] Loss: 0.01168 +Epoch [923/4000] Training [11/16] Loss: 0.01612 +Epoch [923/4000] Training [12/16] Loss: 0.01723 +Epoch [923/4000] Training [13/16] Loss: 0.00948 +Epoch [923/4000] Training [14/16] Loss: 0.01240 +Epoch [923/4000] Training [15/16] Loss: 0.00895 +Epoch [923/4000] Training [16/16] Loss: 0.01175 +Epoch [923/4000] Training metric {'Train/mean dice_metric': 0.9908813834190369, 'Train/mean miou_metric': 0.9818307161331177, 'Train/mean f1': 0.9881553053855896, 'Train/mean precision': 0.9837642312049866, 'Train/mean recall': 0.9925857186317444, 'Train/mean hd95_metric': 1.2902512550354004} +Epoch [923/4000] Validation [1/4] Loss: 0.39647 focal_loss 0.28286 dice_loss 0.11361 +Epoch [923/4000] Validation [2/4] Loss: 0.23167 focal_loss 0.10117 dice_loss 0.13050 +Epoch [923/4000] Validation [3/4] Loss: 0.13088 focal_loss 0.07219 dice_loss 0.05870 +Epoch [923/4000] Validation [4/4] Loss: 0.27466 focal_loss 0.13061 dice_loss 0.14405 +Epoch [923/4000] Validation metric {'Val/mean dice_metric': 0.9680021405220032, 'Val/mean miou_metric': 0.9477015733718872, 'Val/mean f1': 0.970001220703125, 'Val/mean precision': 0.9669986367225647, 'Val/mean recall': 0.9730226397514343, 'Val/mean hd95_metric': 5.877684593200684} +Cheakpoint... +Epoch [923/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680021405220032, 'Val/mean miou_metric': 0.9477015733718872, 'Val/mean f1': 0.970001220703125, 'Val/mean precision': 0.9669986367225647, 'Val/mean recall': 0.9730226397514343, 'Val/mean hd95_metric': 5.877684593200684} +Epoch [924/4000] Training [1/16] Loss: 0.01241 +Epoch [924/4000] Training [2/16] Loss: 0.00913 +Epoch [924/4000] Training [3/16] Loss: 0.01189 +Epoch [924/4000] Training [4/16] Loss: 0.01407 +Epoch [924/4000] Training [5/16] Loss: 0.01264 +Epoch [924/4000] Training [6/16] Loss: 0.01232 +Epoch [924/4000] Training [7/16] Loss: 0.01076 +Epoch [924/4000] Training [8/16] Loss: 0.00903 +Epoch [924/4000] Training [9/16] Loss: 0.01240 +Epoch [924/4000] Training [10/16] Loss: 0.00943 +Epoch [924/4000] Training [11/16] Loss: 0.01079 +Epoch [924/4000] Training [12/16] Loss: 0.01239 +Epoch [924/4000] Training [13/16] Loss: 0.02020 +Epoch [924/4000] Training [14/16] Loss: 0.01190 +Epoch [924/4000] Training [15/16] Loss: 0.01361 +Epoch [924/4000] Training [16/16] Loss: 0.01209 +Epoch [924/4000] Training metric {'Train/mean dice_metric': 0.9912346601486206, 'Train/mean miou_metric': 0.9824351072311401, 'Train/mean f1': 0.9880634546279907, 'Train/mean precision': 0.9836869835853577, 'Train/mean recall': 0.9924790859222412, 'Train/mean hd95_metric': 1.2224174737930298} +Epoch [924/4000] Validation [1/4] Loss: 0.17319 focal_loss 0.11118 dice_loss 0.06200 +Epoch [924/4000] Validation [2/4] Loss: 0.20439 focal_loss 0.09549 dice_loss 0.10890 +Epoch [924/4000] Validation [3/4] Loss: 0.14204 focal_loss 0.08298 dice_loss 0.05906 +Epoch [924/4000] Validation [4/4] Loss: 0.24718 focal_loss 0.12675 dice_loss 0.12043 +Epoch [924/4000] Validation metric {'Val/mean dice_metric': 0.9707719683647156, 'Val/mean miou_metric': 0.9505122900009155, 'Val/mean f1': 0.9718425273895264, 'Val/mean precision': 0.9651039242744446, 'Val/mean recall': 0.9786758422851562, 'Val/mean hd95_metric': 6.038114070892334} +Cheakpoint... +Epoch [924/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707719683647156, 'Val/mean miou_metric': 0.9505122900009155, 'Val/mean f1': 0.9718425273895264, 'Val/mean precision': 0.9651039242744446, 'Val/mean recall': 0.9786758422851562, 'Val/mean hd95_metric': 6.038114070892334} +Epoch [925/4000] Training [1/16] Loss: 0.01834 +Epoch [925/4000] Training [2/16] Loss: 0.01272 +Epoch [925/4000] Training [3/16] Loss: 0.01346 +Epoch [925/4000] Training [4/16] Loss: 0.00951 +Epoch [925/4000] Training [5/16] Loss: 0.01134 +Epoch [925/4000] Training [6/16] Loss: 0.01219 +Epoch [925/4000] Training [7/16] Loss: 0.01057 +Epoch [925/4000] Training [8/16] Loss: 0.00810 +Epoch [925/4000] Training [9/16] Loss: 0.01567 +Epoch [925/4000] Training [10/16] Loss: 0.01240 +Epoch [925/4000] Training [11/16] Loss: 0.01839 +Epoch [925/4000] Training [12/16] Loss: 0.08117 +Epoch [925/4000] Training [13/16] Loss: 0.00939 +Epoch [925/4000] Training [14/16] Loss: 0.01413 +Epoch [925/4000] Training [15/16] Loss: 0.01367 +Epoch [925/4000] Training [16/16] Loss: 0.01149 +Epoch [925/4000] Training metric {'Train/mean dice_metric': 0.9910075068473816, 'Train/mean miou_metric': 0.982060432434082, 'Train/mean f1': 0.9869937896728516, 'Train/mean precision': 0.9816114902496338, 'Train/mean recall': 0.9924354553222656, 'Train/mean hd95_metric': 1.6297862529754639} +Epoch [925/4000] Validation [1/4] Loss: 0.37548 focal_loss 0.26175 dice_loss 0.11373 +Epoch [925/4000] Validation [2/4] Loss: 0.34988 focal_loss 0.17108 dice_loss 0.17881 +Epoch [925/4000] Validation [3/4] Loss: 0.17270 focal_loss 0.09004 dice_loss 0.08265 +Epoch [925/4000] Validation [4/4] Loss: 0.26758 focal_loss 0.14054 dice_loss 0.12704 +Epoch [925/4000] Validation metric {'Val/mean dice_metric': 0.9665921330451965, 'Val/mean miou_metric': 0.9462318420410156, 'Val/mean f1': 0.9679484963417053, 'Val/mean precision': 0.9697403907775879, 'Val/mean recall': 0.9661630988121033, 'Val/mean hd95_metric': 6.773198127746582} +Cheakpoint... +Epoch [925/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665921330451965, 'Val/mean miou_metric': 0.9462318420410156, 'Val/mean f1': 0.9679484963417053, 'Val/mean precision': 0.9697403907775879, 'Val/mean recall': 0.9661630988121033, 'Val/mean hd95_metric': 6.773198127746582} +Epoch [926/4000] Training [1/16] Loss: 0.01032 +Epoch [926/4000] Training [2/16] Loss: 0.01344 +Epoch [926/4000] Training [3/16] Loss: 0.00972 +Epoch [926/4000] Training [4/16] Loss: 0.01294 +Epoch [926/4000] Training [5/16] Loss: 0.01724 +Epoch [926/4000] Training [6/16] Loss: 0.01251 +Epoch [926/4000] Training [7/16] Loss: 0.01582 +Epoch [926/4000] Training [8/16] Loss: 0.01200 +Epoch [926/4000] Training [9/16] Loss: 0.01297 +Epoch [926/4000] Training [10/16] Loss: 0.01127 +Epoch [926/4000] Training [11/16] Loss: 0.01300 +Epoch [926/4000] Training [12/16] Loss: 0.01766 +Epoch [926/4000] Training [13/16] Loss: 0.01124 +Epoch [926/4000] Training [14/16] Loss: 0.01579 +Epoch [926/4000] Training [15/16] Loss: 0.01489 +Epoch [926/4000] Training [16/16] Loss: 0.01042 +Epoch [926/4000] Training metric {'Train/mean dice_metric': 0.991031289100647, 'Train/mean miou_metric': 0.9820315837860107, 'Train/mean f1': 0.9877002835273743, 'Train/mean precision': 0.9830530881881714, 'Train/mean recall': 0.9923915863037109, 'Train/mean hd95_metric': 1.3507100343704224} +Epoch [926/4000] Validation [1/4] Loss: 0.25135 focal_loss 0.16601 dice_loss 0.08534 +Epoch [926/4000] Validation [2/4] Loss: 0.30258 focal_loss 0.13110 dice_loss 0.17148 +Epoch [926/4000] Validation [3/4] Loss: 0.13340 focal_loss 0.07451 dice_loss 0.05889 +Epoch [926/4000] Validation [4/4] Loss: 0.25458 focal_loss 0.12636 dice_loss 0.12822 +Epoch [926/4000] Validation metric {'Val/mean dice_metric': 0.9706273078918457, 'Val/mean miou_metric': 0.9502156376838684, 'Val/mean f1': 0.9721785187721252, 'Val/mean precision': 0.9689530730247498, 'Val/mean recall': 0.9754254221916199, 'Val/mean hd95_metric': 6.649306297302246} +Cheakpoint... +Epoch [926/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706273078918457, 'Val/mean miou_metric': 0.9502156376838684, 'Val/mean f1': 0.9721785187721252, 'Val/mean precision': 0.9689530730247498, 'Val/mean recall': 0.9754254221916199, 'Val/mean hd95_metric': 6.649306297302246} +Epoch [927/4000] Training [1/16] Loss: 0.01301 +Epoch [927/4000] Training [2/16] Loss: 0.01480 +Epoch [927/4000] Training [3/16] Loss: 0.02612 +Epoch [927/4000] Training [4/16] Loss: 0.01370 +Epoch [927/4000] Training [5/16] Loss: 0.01274 +Epoch [927/4000] Training [6/16] Loss: 0.01257 +Epoch [927/4000] Training [7/16] Loss: 0.01489 +Epoch [927/4000] Training [8/16] Loss: 0.00997 +Epoch [927/4000] Training [9/16] Loss: 0.01283 +Epoch [927/4000] Training [10/16] Loss: 0.01170 +Epoch [927/4000] Training [11/16] Loss: 0.01130 +Epoch [927/4000] Training [12/16] Loss: 0.01038 +Epoch [927/4000] Training [13/16] Loss: 0.01333 +Epoch [927/4000] Training [14/16] Loss: 0.01216 +Epoch [927/4000] Training [15/16] Loss: 0.01261 +Epoch [927/4000] Training [16/16] Loss: 0.01462 +Epoch [927/4000] Training metric {'Train/mean dice_metric': 0.9903688430786133, 'Train/mean miou_metric': 0.9807531237602234, 'Train/mean f1': 0.9873027801513672, 'Train/mean precision': 0.9828740954399109, 'Train/mean recall': 0.9917715191841125, 'Train/mean hd95_metric': 1.9087908267974854} +Epoch [927/4000] Validation [1/4] Loss: 0.21709 focal_loss 0.13257 dice_loss 0.08451 +Epoch [927/4000] Validation [2/4] Loss: 0.30246 focal_loss 0.14381 dice_loss 0.15864 +Epoch [927/4000] Validation [3/4] Loss: 0.27694 focal_loss 0.16972 dice_loss 0.10722 +Epoch [927/4000] Validation [4/4] Loss: 0.24074 focal_loss 0.11567 dice_loss 0.12508 +Epoch [927/4000] Validation metric {'Val/mean dice_metric': 0.9692832231521606, 'Val/mean miou_metric': 0.9479305148124695, 'Val/mean f1': 0.9705972075462341, 'Val/mean precision': 0.967569887638092, 'Val/mean recall': 0.9736437201499939, 'Val/mean hd95_metric': 6.559329032897949} +Cheakpoint... +Epoch [927/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692832231521606, 'Val/mean miou_metric': 0.9479305148124695, 'Val/mean f1': 0.9705972075462341, 'Val/mean precision': 0.967569887638092, 'Val/mean recall': 0.9736437201499939, 'Val/mean hd95_metric': 6.559329032897949} +Epoch [928/4000] Training [1/16] Loss: 0.01323 +Epoch [928/4000] Training [2/16] Loss: 0.01145 +Epoch [928/4000] Training [3/16] Loss: 0.00935 +Epoch [928/4000] Training [4/16] Loss: 0.01397 +Epoch [928/4000] Training [5/16] Loss: 0.01738 +Epoch [928/4000] Training [6/16] Loss: 0.01135 +Epoch [928/4000] Training [7/16] Loss: 0.01089 +Epoch [928/4000] Training [8/16] Loss: 0.01662 +Epoch [928/4000] Training [9/16] Loss: 0.01410 +Epoch [928/4000] Training [10/16] Loss: 0.00961 +Epoch [928/4000] Training [11/16] Loss: 0.02020 +Epoch [928/4000] Training [12/16] Loss: 0.00911 +Epoch [928/4000] Training [13/16] Loss: 0.01234 +Epoch [928/4000] Training [14/16] Loss: 0.01181 +Epoch [928/4000] Training [15/16] Loss: 0.01319 +Epoch [928/4000] Training [16/16] Loss: 0.00996 +Epoch [928/4000] Training metric {'Train/mean dice_metric': 0.991435170173645, 'Train/mean miou_metric': 0.9827977418899536, 'Train/mean f1': 0.9870673418045044, 'Train/mean precision': 0.9822111129760742, 'Train/mean recall': 0.9919718503952026, 'Train/mean hd95_metric': 1.4350312948226929} +Epoch [928/4000] Validation [1/4] Loss: 0.15395 focal_loss 0.09762 dice_loss 0.05632 +Epoch [928/4000] Validation [2/4] Loss: 0.16464 focal_loss 0.06835 dice_loss 0.09629 +Epoch [928/4000] Validation [3/4] Loss: 0.29156 focal_loss 0.17130 dice_loss 0.12026 +Epoch [928/4000] Validation [4/4] Loss: 0.26910 focal_loss 0.13910 dice_loss 0.13000 +Epoch [928/4000] Validation metric {'Val/mean dice_metric': 0.9685617685317993, 'Val/mean miou_metric': 0.9482210278511047, 'Val/mean f1': 0.9684844017028809, 'Val/mean precision': 0.9572277665138245, 'Val/mean recall': 0.9800090193748474, 'Val/mean hd95_metric': 7.299363136291504} +Cheakpoint... +Epoch [928/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9685617685317993, 'Val/mean miou_metric': 0.9482210278511047, 'Val/mean f1': 0.9684844017028809, 'Val/mean precision': 0.9572277665138245, 'Val/mean recall': 0.9800090193748474, 'Val/mean hd95_metric': 7.299363136291504} +Epoch [929/4000] Training [1/16] Loss: 0.01149 +Epoch [929/4000] Training [2/16] Loss: 0.02004 +Epoch [929/4000] Training [3/16] Loss: 0.01283 +Epoch [929/4000] Training [4/16] Loss: 0.01009 +Epoch [929/4000] Training [5/16] Loss: 0.01351 +Epoch [929/4000] Training [6/16] Loss: 0.01007 +Epoch [929/4000] Training [7/16] Loss: 0.01924 +Epoch [929/4000] Training [8/16] Loss: 0.01220 +Epoch [929/4000] Training [9/16] Loss: 0.01141 +Epoch [929/4000] Training [10/16] Loss: 0.01529 +Epoch [929/4000] Training [11/16] Loss: 0.01544 +Epoch [929/4000] Training [12/16] Loss: 0.01449 +Epoch [929/4000] Training [13/16] Loss: 0.01154 +Epoch [929/4000] Training [14/16] Loss: 0.01064 +Epoch [929/4000] Training [15/16] Loss: 0.03343 +Epoch [929/4000] Training [16/16] Loss: 0.00980 +Epoch [929/4000] Training metric {'Train/mean dice_metric': 0.9906812906265259, 'Train/mean miou_metric': 0.9814369082450867, 'Train/mean f1': 0.987296462059021, 'Train/mean precision': 0.98264479637146, 'Train/mean recall': 0.9919924139976501, 'Train/mean hd95_metric': 1.7367732524871826} +Epoch [929/4000] Validation [1/4] Loss: 0.15482 focal_loss 0.08867 dice_loss 0.06615 +Epoch [929/4000] Validation [2/4] Loss: 0.26682 focal_loss 0.12555 dice_loss 0.14127 +Epoch [929/4000] Validation [3/4] Loss: 0.16513 focal_loss 0.09858 dice_loss 0.06656 +Epoch [929/4000] Validation [4/4] Loss: 0.28825 focal_loss 0.17192 dice_loss 0.11633 +Epoch [929/4000] Validation metric {'Val/mean dice_metric': 0.9668195843696594, 'Val/mean miou_metric': 0.9454706907272339, 'Val/mean f1': 0.9676649570465088, 'Val/mean precision': 0.9649147391319275, 'Val/mean recall': 0.9704309105873108, 'Val/mean hd95_metric': 6.778334140777588} +Cheakpoint... +Epoch [929/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668195843696594, 'Val/mean miou_metric': 0.9454706907272339, 'Val/mean f1': 0.9676649570465088, 'Val/mean precision': 0.9649147391319275, 'Val/mean recall': 0.9704309105873108, 'Val/mean hd95_metric': 6.778334140777588} +Epoch [930/4000] Training [1/16] Loss: 0.01254 +Epoch [930/4000] Training [2/16] Loss: 0.01357 +Epoch [930/4000] Training [3/16] Loss: 0.01492 +Epoch [930/4000] Training [4/16] Loss: 0.01166 +Epoch [930/4000] Training [5/16] Loss: 0.01384 +Epoch [930/4000] Training [6/16] Loss: 0.01263 +Epoch [930/4000] Training [7/16] Loss: 0.02044 +Epoch [930/4000] Training [8/16] Loss: 0.00900 +Epoch [930/4000] Training [9/16] Loss: 0.01518 +Epoch [930/4000] Training [10/16] Loss: 0.01858 +Epoch [930/4000] Training [11/16] Loss: 0.01230 +Epoch [930/4000] Training [12/16] Loss: 0.01517 +Epoch [930/4000] Training [13/16] Loss: 0.01645 +Epoch [930/4000] Training [14/16] Loss: 0.02350 +Epoch [930/4000] Training [15/16] Loss: 0.01754 +Epoch [930/4000] Training [16/16] Loss: 0.01825 +Epoch [930/4000] Training metric {'Train/mean dice_metric': 0.9892856478691101, 'Train/mean miou_metric': 0.9787449836730957, 'Train/mean f1': 0.9857522249221802, 'Train/mean precision': 0.9815636873245239, 'Train/mean recall': 0.989976704120636, 'Train/mean hd95_metric': 2.0242741107940674} +Epoch [930/4000] Validation [1/4] Loss: 0.24352 focal_loss 0.16139 dice_loss 0.08213 +Epoch [930/4000] Validation [2/4] Loss: 0.42849 focal_loss 0.19045 dice_loss 0.23805 +Epoch [930/4000] Validation [3/4] Loss: 0.64037 focal_loss 0.46201 dice_loss 0.17836 +Epoch [930/4000] Validation [4/4] Loss: 0.64192 focal_loss 0.38975 dice_loss 0.25217 +Epoch [930/4000] Validation metric {'Val/mean dice_metric': 0.9607486724853516, 'Val/mean miou_metric': 0.9375311136245728, 'Val/mean f1': 0.959522545337677, 'Val/mean precision': 0.943055272102356, 'Val/mean recall': 0.9765751957893372, 'Val/mean hd95_metric': 10.449429512023926} +Cheakpoint... +Epoch [930/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9607], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9607486724853516, 'Val/mean miou_metric': 0.9375311136245728, 'Val/mean f1': 0.959522545337677, 'Val/mean precision': 0.943055272102356, 'Val/mean recall': 0.9765751957893372, 'Val/mean hd95_metric': 10.449429512023926} +Epoch [931/4000] Training [1/16] Loss: 0.01288 +Epoch [931/4000] Training [2/16] Loss: 0.01369 +Epoch [931/4000] Training [3/16] Loss: 0.04928 +Epoch [931/4000] Training [4/16] Loss: 0.01483 +Epoch [931/4000] Training [5/16] Loss: 0.00974 +Epoch [931/4000] Training [6/16] Loss: 0.01176 +Epoch [931/4000] Training [7/16] Loss: 0.01160 +Epoch [931/4000] Training [8/16] Loss: 0.01453 +Epoch [931/4000] Training [9/16] Loss: 0.02235 +Epoch [931/4000] Training [10/16] Loss: 0.01419 +Epoch [931/4000] Training [11/16] Loss: 0.01375 +Epoch [931/4000] Training [12/16] Loss: 0.01318 +Epoch [931/4000] Training [13/16] Loss: 0.01667 +Epoch [931/4000] Training [14/16] Loss: 0.01171 +Epoch [931/4000] Training [15/16] Loss: 0.01751 +Epoch [931/4000] Training [16/16] Loss: 0.01337 +Epoch [931/4000] Training metric {'Train/mean dice_metric': 0.9885531663894653, 'Train/mean miou_metric': 0.9779120683670044, 'Train/mean f1': 0.9833483695983887, 'Train/mean precision': 0.9818335771560669, 'Train/mean recall': 0.984868049621582, 'Train/mean hd95_metric': 3.4415249824523926} +Epoch [931/4000] Validation [1/4] Loss: 0.37067 focal_loss 0.26075 dice_loss 0.10992 +Epoch [931/4000] Validation [2/4] Loss: 0.22601 focal_loss 0.10778 dice_loss 0.11823 +Epoch [931/4000] Validation [3/4] Loss: 0.12107 focal_loss 0.06411 dice_loss 0.05696 +Epoch [931/4000] Validation [4/4] Loss: 0.44913 focal_loss 0.28512 dice_loss 0.16401 +Epoch [931/4000] Validation metric {'Val/mean dice_metric': 0.9624806642532349, 'Val/mean miou_metric': 0.9382196664810181, 'Val/mean f1': 0.9599083662033081, 'Val/mean precision': 0.9643880128860474, 'Val/mean recall': 0.955470085144043, 'Val/mean hd95_metric': 8.917012214660645} +Cheakpoint... +Epoch [931/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9624806642532349, 'Val/mean miou_metric': 0.9382196664810181, 'Val/mean f1': 0.9599083662033081, 'Val/mean precision': 0.9643880128860474, 'Val/mean recall': 0.955470085144043, 'Val/mean hd95_metric': 8.917012214660645} +Epoch [932/4000] Training [1/16] Loss: 0.01088 +Epoch [932/4000] Training [2/16] Loss: 0.12670 +Epoch [932/4000] Training [3/16] Loss: 0.02365 +Epoch [932/4000] Training [4/16] Loss: 0.02680 +Epoch [932/4000] Training [5/16] Loss: 0.01585 +Epoch [932/4000] Training [6/16] Loss: 0.02419 +Epoch [932/4000] Training [7/16] Loss: 0.01966 +Epoch [932/4000] Training [8/16] Loss: 0.01311 +Epoch [932/4000] Training [9/16] Loss: 0.01476 +Epoch [932/4000] Training [10/16] Loss: 0.01692 +Epoch [932/4000] Training [11/16] Loss: 0.11652 +Epoch [932/4000] Training [12/16] Loss: 0.03228 +Epoch [932/4000] Training [13/16] Loss: 0.01793 +Epoch [932/4000] Training [14/16] Loss: 0.02493 +Epoch [932/4000] Training [15/16] Loss: 0.01820 +Epoch [932/4000] Training [16/16] Loss: 0.01493 +Epoch [932/4000] Training metric {'Train/mean dice_metric': 0.9851790070533752, 'Train/mean miou_metric': 0.9725282788276672, 'Train/mean f1': 0.9791675806045532, 'Train/mean precision': 0.9697328209877014, 'Train/mean recall': 0.9887877702713013, 'Train/mean hd95_metric': 5.038607120513916} +Epoch [932/4000] Validation [1/4] Loss: 0.39092 focal_loss 0.23823 dice_loss 0.15269 +Epoch [932/4000] Validation [2/4] Loss: 0.48192 focal_loss 0.20421 dice_loss 0.27771 +Epoch [932/4000] Validation [3/4] Loss: 0.19450 focal_loss 0.10958 dice_loss 0.08493 +Epoch [932/4000] Validation [4/4] Loss: 0.48009 focal_loss 0.31005 dice_loss 0.17004 +Epoch [932/4000] Validation metric {'Val/mean dice_metric': 0.9543138742446899, 'Val/mean miou_metric': 0.9278600811958313, 'Val/mean f1': 0.9550324082374573, 'Val/mean precision': 0.9567632675170898, 'Val/mean recall': 0.9533078074455261, 'Val/mean hd95_metric': 10.769437789916992} +Cheakpoint... +Epoch [932/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9543], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9543138742446899, 'Val/mean miou_metric': 0.9278600811958313, 'Val/mean f1': 0.9550324082374573, 'Val/mean precision': 0.9567632675170898, 'Val/mean recall': 0.9533078074455261, 'Val/mean hd95_metric': 10.769437789916992} +Epoch [933/4000] Training [1/16] Loss: 0.01447 +Epoch [933/4000] Training [2/16] Loss: 0.02195 +Epoch [933/4000] Training [3/16] Loss: 0.01965 +Epoch [933/4000] Training [4/16] Loss: 0.02999 +Epoch [933/4000] Training [5/16] Loss: 0.01481 +Epoch [933/4000] Training [6/16] Loss: 0.01543 +Epoch [933/4000] Training [7/16] Loss: 0.01641 +Epoch [933/4000] Training [8/16] Loss: 0.03860 +Epoch [933/4000] Training [9/16] Loss: 0.01756 +Epoch [933/4000] Training [10/16] Loss: 0.01637 +Epoch [933/4000] Training [11/16] Loss: 0.01628 +Epoch [933/4000] Training [12/16] Loss: 0.01605 +Epoch [933/4000] Training [13/16] Loss: 0.01824 +Epoch [933/4000] Training [14/16] Loss: 0.01416 +Epoch [933/4000] Training [15/16] Loss: 0.01911 +Epoch [933/4000] Training [16/16] Loss: 0.01631 +Epoch [933/4000] Training metric {'Train/mean dice_metric': 0.9857642650604248, 'Train/mean miou_metric': 0.9727239608764648, 'Train/mean f1': 0.9812746047973633, 'Train/mean precision': 0.9804581999778748, 'Train/mean recall': 0.9820924401283264, 'Train/mean hd95_metric': 3.288778305053711} +Epoch [933/4000] Validation [1/4] Loss: 0.34240 focal_loss 0.19756 dice_loss 0.14484 +Epoch [933/4000] Validation [2/4] Loss: 0.21684 focal_loss 0.07474 dice_loss 0.14210 +Epoch [933/4000] Validation [3/4] Loss: 0.13532 focal_loss 0.05683 dice_loss 0.07849 +Epoch [933/4000] Validation [4/4] Loss: 0.28770 focal_loss 0.10066 dice_loss 0.18704 +Epoch [933/4000] Validation metric {'Val/mean dice_metric': 0.9605517387390137, 'Val/mean miou_metric': 0.935725212097168, 'Val/mean f1': 0.9599538445472717, 'Val/mean precision': 0.9532492160797119, 'Val/mean recall': 0.9667534232139587, 'Val/mean hd95_metric': 9.491653442382812} +Cheakpoint... +Epoch [933/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9606], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9605517387390137, 'Val/mean miou_metric': 0.935725212097168, 'Val/mean f1': 0.9599538445472717, 'Val/mean precision': 0.9532492160797119, 'Val/mean recall': 0.9667534232139587, 'Val/mean hd95_metric': 9.491653442382812} +Epoch [934/4000] Training [1/16] Loss: 0.01358 +Epoch [934/4000] Training [2/16] Loss: 0.01462 +Epoch [934/4000] Training [3/16] Loss: 0.01246 +Epoch [934/4000] Training [4/16] Loss: 0.01466 +Epoch [934/4000] Training [5/16] Loss: 0.02282 +Epoch [934/4000] Training [6/16] Loss: 0.02011 +Epoch [934/4000] Training [7/16] Loss: 0.02044 +Epoch [934/4000] Training [8/16] Loss: 0.01312 +Epoch [934/4000] Training [9/16] Loss: 0.01294 +Epoch [934/4000] Training [10/16] Loss: 0.01320 +Epoch [934/4000] Training [11/16] Loss: 0.01312 +Epoch [934/4000] Training [12/16] Loss: 0.01147 +Epoch [934/4000] Training [13/16] Loss: 0.01486 +Epoch [934/4000] Training [14/16] Loss: 0.01930 +Epoch [934/4000] Training [15/16] Loss: 0.01454 +Epoch [934/4000] Training [16/16] Loss: 0.01368 +Epoch [934/4000] Training metric {'Train/mean dice_metric': 0.9897916316986084, 'Train/mean miou_metric': 0.9795891642570496, 'Train/mean f1': 0.9861431121826172, 'Train/mean precision': 0.9810711145401001, 'Train/mean recall': 0.991267740726471, 'Train/mean hd95_metric': 1.7380189895629883} +Epoch [934/4000] Validation [1/4] Loss: 0.24817 focal_loss 0.15714 dice_loss 0.09103 +Epoch [934/4000] Validation [2/4] Loss: 0.20366 focal_loss 0.07737 dice_loss 0.12629 +Epoch [934/4000] Validation [3/4] Loss: 0.23771 focal_loss 0.12509 dice_loss 0.11262 +Epoch [934/4000] Validation [4/4] Loss: 0.29757 focal_loss 0.13115 dice_loss 0.16643 +Epoch [934/4000] Validation metric {'Val/mean dice_metric': 0.9654134511947632, 'Val/mean miou_metric': 0.9430944323539734, 'Val/mean f1': 0.9643675684928894, 'Val/mean precision': 0.9532938599586487, 'Val/mean recall': 0.9757015705108643, 'Val/mean hd95_metric': 8.633886337280273} +Cheakpoint... +Epoch [934/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654134511947632, 'Val/mean miou_metric': 0.9430944323539734, 'Val/mean f1': 0.9643675684928894, 'Val/mean precision': 0.9532938599586487, 'Val/mean recall': 0.9757015705108643, 'Val/mean hd95_metric': 8.633886337280273} +Epoch [935/4000] Training [1/16] Loss: 0.01331 +Epoch [935/4000] Training [2/16] Loss: 0.01259 +Epoch [935/4000] Training [3/16] Loss: 0.01303 +Epoch [935/4000] Training [4/16] Loss: 0.01207 +Epoch [935/4000] Training [5/16] Loss: 0.01239 +Epoch [935/4000] Training [6/16] Loss: 0.01246 +Epoch [935/4000] Training [7/16] Loss: 0.01961 +Epoch [935/4000] Training [8/16] Loss: 0.01207 +Epoch [935/4000] Training [9/16] Loss: 0.01407 +Epoch [935/4000] Training [10/16] Loss: 0.01302 +Epoch [935/4000] Training [11/16] Loss: 0.01262 +Epoch [935/4000] Training [12/16] Loss: 0.01416 +Epoch [935/4000] Training [13/16] Loss: 0.01492 +Epoch [935/4000] Training [14/16] Loss: 0.01089 +Epoch [935/4000] Training [15/16] Loss: 0.01190 +Epoch [935/4000] Training [16/16] Loss: 0.01721 +Epoch [935/4000] Training metric {'Train/mean dice_metric': 0.9909365177154541, 'Train/mean miou_metric': 0.9818246960639954, 'Train/mean f1': 0.9871172904968262, 'Train/mean precision': 0.9825271964073181, 'Train/mean recall': 0.9917504787445068, 'Train/mean hd95_metric': 1.6333270072937012} +Epoch [935/4000] Validation [1/4] Loss: 0.22115 focal_loss 0.13802 dice_loss 0.08313 +Epoch [935/4000] Validation [2/4] Loss: 0.30927 focal_loss 0.14172 dice_loss 0.16755 +Epoch [935/4000] Validation [3/4] Loss: 0.16910 focal_loss 0.09070 dice_loss 0.07840 +Epoch [935/4000] Validation [4/4] Loss: 0.28454 focal_loss 0.14944 dice_loss 0.13509 +Epoch [935/4000] Validation metric {'Val/mean dice_metric': 0.9677066802978516, 'Val/mean miou_metric': 0.946721076965332, 'Val/mean f1': 0.9683551788330078, 'Val/mean precision': 0.96175217628479, 'Val/mean recall': 0.9750493764877319, 'Val/mean hd95_metric': 7.911057949066162} +Cheakpoint... +Epoch [935/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677066802978516, 'Val/mean miou_metric': 0.946721076965332, 'Val/mean f1': 0.9683551788330078, 'Val/mean precision': 0.96175217628479, 'Val/mean recall': 0.9750493764877319, 'Val/mean hd95_metric': 7.911057949066162} +Epoch [936/4000] Training [1/16] Loss: 0.01072 +Epoch [936/4000] Training [2/16] Loss: 0.01346 +Epoch [936/4000] Training [3/16] Loss: 0.01414 +Epoch [936/4000] Training [4/16] Loss: 0.00876 +Epoch [936/4000] Training [5/16] Loss: 0.01451 +Epoch [936/4000] Training [6/16] Loss: 0.00990 +Epoch [936/4000] Training [7/16] Loss: 0.01331 +Epoch [936/4000] Training [8/16] Loss: 0.02106 +Epoch [936/4000] Training [9/16] Loss: 0.01380 +Epoch [936/4000] Training [10/16] Loss: 0.01175 +Epoch [936/4000] Training [11/16] Loss: 0.00761 +Epoch [936/4000] Training [12/16] Loss: 0.01269 +Epoch [936/4000] Training [13/16] Loss: 0.00924 +Epoch [936/4000] Training [14/16] Loss: 0.01150 +Epoch [936/4000] Training [15/16] Loss: 0.01282 +Epoch [936/4000] Training [16/16] Loss: 0.00942 +Epoch [936/4000] Training metric {'Train/mean dice_metric': 0.9915752410888672, 'Train/mean miou_metric': 0.9831802845001221, 'Train/mean f1': 0.9882685542106628, 'Train/mean precision': 0.9839498400688171, 'Train/mean recall': 0.9926252961158752, 'Train/mean hd95_metric': 1.5531096458435059} +Epoch [936/4000] Validation [1/4] Loss: 0.17177 focal_loss 0.10641 dice_loss 0.06536 +Epoch [936/4000] Validation [2/4] Loss: 0.29384 focal_loss 0.12271 dice_loss 0.17113 +Epoch [936/4000] Validation [3/4] Loss: 0.23062 focal_loss 0.12166 dice_loss 0.10896 +Epoch [936/4000] Validation [4/4] Loss: 0.23315 focal_loss 0.12399 dice_loss 0.10916 +Epoch [936/4000] Validation metric {'Val/mean dice_metric': 0.9692796468734741, 'Val/mean miou_metric': 0.9494677782058716, 'Val/mean f1': 0.9699833393096924, 'Val/mean precision': 0.9641512632369995, 'Val/mean recall': 0.9758865833282471, 'Val/mean hd95_metric': 7.241274833679199} +Cheakpoint... +Epoch [936/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692796468734741, 'Val/mean miou_metric': 0.9494677782058716, 'Val/mean f1': 0.9699833393096924, 'Val/mean precision': 0.9641512632369995, 'Val/mean recall': 0.9758865833282471, 'Val/mean hd95_metric': 7.241274833679199} +Epoch [937/4000] Training [1/16] Loss: 0.01142 +Epoch [937/4000] Training [2/16] Loss: 0.01283 +Epoch [937/4000] Training [3/16] Loss: 0.01157 +Epoch [937/4000] Training [4/16] Loss: 0.00955 +Epoch [937/4000] Training [5/16] Loss: 0.01063 +Epoch [937/4000] Training [6/16] Loss: 0.01046 +Epoch [937/4000] Training [7/16] Loss: 0.01210 +Epoch [937/4000] Training [8/16] Loss: 0.01184 +Epoch [937/4000] Training [9/16] Loss: 0.01272 +Epoch [937/4000] Training [10/16] Loss: 0.02889 +Epoch [937/4000] Training [11/16] Loss: 0.01488 +Epoch [937/4000] Training [12/16] Loss: 0.01212 +Epoch [937/4000] Training [13/16] Loss: 0.01513 +Epoch [937/4000] Training [14/16] Loss: 0.01126 +Epoch [937/4000] Training [15/16] Loss: 0.00909 +Epoch [937/4000] Training [16/16] Loss: 0.01196 +Epoch [937/4000] Training metric {'Train/mean dice_metric': 0.9915217757225037, 'Train/mean miou_metric': 0.9829752445220947, 'Train/mean f1': 0.9874123930931091, 'Train/mean precision': 0.9823039174079895, 'Train/mean recall': 0.9925742745399475, 'Train/mean hd95_metric': 1.2093303203582764} +Epoch [937/4000] Validation [1/4] Loss: 0.18464 focal_loss 0.10597 dice_loss 0.07867 +Epoch [937/4000] Validation [2/4] Loss: 0.18519 focal_loss 0.06456 dice_loss 0.12063 +Epoch [937/4000] Validation [3/4] Loss: 0.19385 focal_loss 0.09701 dice_loss 0.09683 +Epoch [937/4000] Validation [4/4] Loss: 0.23329 focal_loss 0.11946 dice_loss 0.11383 +Epoch [937/4000] Validation metric {'Val/mean dice_metric': 0.9692291021347046, 'Val/mean miou_metric': 0.9488723874092102, 'Val/mean f1': 0.9688950777053833, 'Val/mean precision': 0.9606188535690308, 'Val/mean recall': 0.9773151278495789, 'Val/mean hd95_metric': 6.989457607269287} +Cheakpoint... +Epoch [937/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692291021347046, 'Val/mean miou_metric': 0.9488723874092102, 'Val/mean f1': 0.9688950777053833, 'Val/mean precision': 0.9606188535690308, 'Val/mean recall': 0.9773151278495789, 'Val/mean hd95_metric': 6.989457607269287} +Epoch [938/4000] Training [1/16] Loss: 0.01041 +Epoch [938/4000] Training [2/16] Loss: 0.01020 +Epoch [938/4000] Training [3/16] Loss: 0.00976 +Epoch [938/4000] Training [4/16] Loss: 0.01267 +Epoch [938/4000] Training [5/16] Loss: 0.01268 +Epoch [938/4000] Training [6/16] Loss: 0.00815 +Epoch [938/4000] Training [7/16] Loss: 0.01264 +Epoch [938/4000] Training [8/16] Loss: 0.01129 +Epoch [938/4000] Training [9/16] Loss: 0.01165 +Epoch [938/4000] Training [10/16] Loss: 0.01328 +Epoch [938/4000] Training [11/16] Loss: 0.01134 +Epoch [938/4000] Training [12/16] Loss: 0.01137 +Epoch [938/4000] Training [13/16] Loss: 0.01802 +Epoch [938/4000] Training [14/16] Loss: 0.01044 +Epoch [938/4000] Training [15/16] Loss: 0.00961 +Epoch [938/4000] Training [16/16] Loss: 0.01117 +Epoch [938/4000] Training metric {'Train/mean dice_metric': 0.9918643236160278, 'Train/mean miou_metric': 0.9836699962615967, 'Train/mean f1': 0.9882499575614929, 'Train/mean precision': 0.9838492274284363, 'Train/mean recall': 0.9926902651786804, 'Train/mean hd95_metric': 1.5920870304107666} +Epoch [938/4000] Validation [1/4] Loss: 0.22682 focal_loss 0.14269 dice_loss 0.08414 +Epoch [938/4000] Validation [2/4] Loss: 0.19804 focal_loss 0.09084 dice_loss 0.10720 +Epoch [938/4000] Validation [3/4] Loss: 0.17156 focal_loss 0.08221 dice_loss 0.08935 +Epoch [938/4000] Validation [4/4] Loss: 0.26706 focal_loss 0.13744 dice_loss 0.12962 +Epoch [938/4000] Validation metric {'Val/mean dice_metric': 0.9705281257629395, 'Val/mean miou_metric': 0.9505454897880554, 'Val/mean f1': 0.969764232635498, 'Val/mean precision': 0.9633342623710632, 'Val/mean recall': 0.9762805700302124, 'Val/mean hd95_metric': 6.55441427230835} +Cheakpoint... +Epoch [938/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705281257629395, 'Val/mean miou_metric': 0.9505454897880554, 'Val/mean f1': 0.969764232635498, 'Val/mean precision': 0.9633342623710632, 'Val/mean recall': 0.9762805700302124, 'Val/mean hd95_metric': 6.55441427230835} +Epoch [939/4000] Training [1/16] Loss: 0.01267 +Epoch [939/4000] Training [2/16] Loss: 0.00852 +Epoch [939/4000] Training [3/16] Loss: 0.01027 +Epoch [939/4000] Training [4/16] Loss: 0.01063 +Epoch [939/4000] Training [5/16] Loss: 0.00802 +Epoch [939/4000] Training [6/16] Loss: 0.01360 +Epoch [939/4000] Training [7/16] Loss: 0.00843 +Epoch [939/4000] Training [8/16] Loss: 0.00920 +Epoch [939/4000] Training [9/16] Loss: 0.01442 +Epoch [939/4000] Training [10/16] Loss: 0.00938 +Epoch [939/4000] Training [11/16] Loss: 0.00798 +Epoch [939/4000] Training [12/16] Loss: 0.01043 +Epoch [939/4000] Training [13/16] Loss: 0.00882 +Epoch [939/4000] Training [14/16] Loss: 0.00949 +Epoch [939/4000] Training [15/16] Loss: 0.01746 +Epoch [939/4000] Training [16/16] Loss: 0.01115 +Epoch [939/4000] Training metric {'Train/mean dice_metric': 0.9926953315734863, 'Train/mean miou_metric': 0.9852781891822815, 'Train/mean f1': 0.989075779914856, 'Train/mean precision': 0.9845502376556396, 'Train/mean recall': 0.9936429858207703, 'Train/mean hd95_metric': 1.1491284370422363} +Epoch [939/4000] Validation [1/4] Loss: 0.20840 focal_loss 0.13782 dice_loss 0.07058 +Epoch [939/4000] Validation [2/4] Loss: 0.31470 focal_loss 0.14047 dice_loss 0.17424 +Epoch [939/4000] Validation [3/4] Loss: 0.22163 focal_loss 0.12945 dice_loss 0.09217 +Epoch [939/4000] Validation [4/4] Loss: 0.26012 focal_loss 0.11917 dice_loss 0.14095 +Epoch [939/4000] Validation metric {'Val/mean dice_metric': 0.9703645706176758, 'Val/mean miou_metric': 0.9506889581680298, 'Val/mean f1': 0.9701961874961853, 'Val/mean precision': 0.963021993637085, 'Val/mean recall': 0.97747802734375, 'Val/mean hd95_metric': 6.8386640548706055} +Cheakpoint... +Epoch [939/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703645706176758, 'Val/mean miou_metric': 0.9506889581680298, 'Val/mean f1': 0.9701961874961853, 'Val/mean precision': 0.963021993637085, 'Val/mean recall': 0.97747802734375, 'Val/mean hd95_metric': 6.8386640548706055} +Epoch [940/4000] Training [1/16] Loss: 0.00967 +Epoch [940/4000] Training [2/16] Loss: 0.01338 +Epoch [940/4000] Training [3/16] Loss: 0.01036 +Epoch [940/4000] Training [4/16] Loss: 0.01502 +Epoch [940/4000] Training [5/16] Loss: 0.00795 +Epoch [940/4000] Training [6/16] Loss: 0.01000 +Epoch [940/4000] Training [7/16] Loss: 0.01333 +Epoch [940/4000] Training [8/16] Loss: 0.01109 +Epoch [940/4000] Training [9/16] Loss: 0.01096 +Epoch [940/4000] Training [10/16] Loss: 0.01006 +Epoch [940/4000] Training [11/16] Loss: 0.01564 +Epoch [940/4000] Training [12/16] Loss: 0.01361 +Epoch [940/4000] Training [13/16] Loss: 0.01297 +Epoch [940/4000] Training [14/16] Loss: 0.00891 +Epoch [940/4000] Training [15/16] Loss: 0.01193 +Epoch [940/4000] Training [16/16] Loss: 0.01394 +Epoch [940/4000] Training metric {'Train/mean dice_metric': 0.9917424917221069, 'Train/mean miou_metric': 0.9834147095680237, 'Train/mean f1': 0.9883154034614563, 'Train/mean precision': 0.9835613369941711, 'Train/mean recall': 0.9931156039237976, 'Train/mean hd95_metric': 1.2464849948883057} +Epoch [940/4000] Validation [1/4] Loss: 0.16303 focal_loss 0.09987 dice_loss 0.06316 +Epoch [940/4000] Validation [2/4] Loss: 0.19691 focal_loss 0.08935 dice_loss 0.10756 +Epoch [940/4000] Validation [3/4] Loss: 0.20189 focal_loss 0.10376 dice_loss 0.09812 +Epoch [940/4000] Validation [4/4] Loss: 0.27738 focal_loss 0.14832 dice_loss 0.12906 +Epoch [940/4000] Validation metric {'Val/mean dice_metric': 0.9698415994644165, 'Val/mean miou_metric': 0.9498251080513, 'Val/mean f1': 0.9697654843330383, 'Val/mean precision': 0.9616081714630127, 'Val/mean recall': 0.9780623912811279, 'Val/mean hd95_metric': 6.581623077392578} +Cheakpoint... +Epoch [940/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698415994644165, 'Val/mean miou_metric': 0.9498251080513, 'Val/mean f1': 0.9697654843330383, 'Val/mean precision': 0.9616081714630127, 'Val/mean recall': 0.9780623912811279, 'Val/mean hd95_metric': 6.581623077392578} +Epoch [941/4000] Training [1/16] Loss: 0.01381 +Epoch [941/4000] Training [2/16] Loss: 0.01064 +Epoch [941/4000] Training [3/16] Loss: 0.01381 +Epoch [941/4000] Training [4/16] Loss: 0.00923 +Epoch [941/4000] Training [5/16] Loss: 0.00955 +Epoch [941/4000] Training [6/16] Loss: 0.01228 +Epoch [941/4000] Training [7/16] Loss: 0.00910 +Epoch [941/4000] Training [8/16] Loss: 0.00925 +Epoch [941/4000] Training [9/16] Loss: 0.01028 +Epoch [941/4000] Training [10/16] Loss: 0.01550 +Epoch [941/4000] Training [11/16] Loss: 0.00840 +Epoch [941/4000] Training [12/16] Loss: 0.01058 +Epoch [941/4000] Training [13/16] Loss: 0.01213 +Epoch [941/4000] Training [14/16] Loss: 0.01031 +Epoch [941/4000] Training [15/16] Loss: 0.01184 +Epoch [941/4000] Training [16/16] Loss: 0.00828 +Epoch [941/4000] Training metric {'Train/mean dice_metric': 0.9924747347831726, 'Train/mean miou_metric': 0.9848271608352661, 'Train/mean f1': 0.9888836741447449, 'Train/mean precision': 0.9841915965080261, 'Train/mean recall': 0.9936206936836243, 'Train/mean hd95_metric': 1.1406402587890625} +Epoch [941/4000] Validation [1/4] Loss: 0.21384 focal_loss 0.14433 dice_loss 0.06950 +Epoch [941/4000] Validation [2/4] Loss: 0.30961 focal_loss 0.14625 dice_loss 0.16336 +Epoch [941/4000] Validation [3/4] Loss: 0.15745 focal_loss 0.07897 dice_loss 0.07848 +Epoch [941/4000] Validation [4/4] Loss: 0.22459 focal_loss 0.11674 dice_loss 0.10786 +Epoch [941/4000] Validation metric {'Val/mean dice_metric': 0.9704927206039429, 'Val/mean miou_metric': 0.9514459371566772, 'Val/mean f1': 0.9718828201293945, 'Val/mean precision': 0.9667956829071045, 'Val/mean recall': 0.9770236611366272, 'Val/mean hd95_metric': 6.497881889343262} +Cheakpoint... +Epoch [941/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704927206039429, 'Val/mean miou_metric': 0.9514459371566772, 'Val/mean f1': 0.9718828201293945, 'Val/mean precision': 0.9667956829071045, 'Val/mean recall': 0.9770236611366272, 'Val/mean hd95_metric': 6.497881889343262} +Epoch [942/4000] Training [1/16] Loss: 0.00809 +Epoch [942/4000] Training [2/16] Loss: 0.01057 +Epoch [942/4000] Training [3/16] Loss: 0.01416 +Epoch [942/4000] Training [4/16] Loss: 0.01153 +Epoch [942/4000] Training [5/16] Loss: 0.01087 +Epoch [942/4000] Training [6/16] Loss: 0.01029 +Epoch [942/4000] Training [7/16] Loss: 0.00804 +Epoch [942/4000] Training [8/16] Loss: 0.00847 +Epoch [942/4000] Training [9/16] Loss: 0.02823 +Epoch [942/4000] Training [10/16] Loss: 0.01173 +Epoch [942/4000] Training [11/16] Loss: 0.01103 +Epoch [942/4000] Training [12/16] Loss: 0.01197 +Epoch [942/4000] Training [13/16] Loss: 0.01171 +Epoch [942/4000] Training [14/16] Loss: 0.03984 +Epoch [942/4000] Training [15/16] Loss: 0.01426 +Epoch [942/4000] Training [16/16] Loss: 0.01168 +Epoch [942/4000] Training metric {'Train/mean dice_metric': 0.9916485548019409, 'Train/mean miou_metric': 0.9832544326782227, 'Train/mean f1': 0.988458514213562, 'Train/mean precision': 0.9840530157089233, 'Train/mean recall': 0.9929036498069763, 'Train/mean hd95_metric': 1.378469467163086} +Epoch [942/4000] Validation [1/4] Loss: 0.17951 focal_loss 0.11015 dice_loss 0.06936 +Epoch [942/4000] Validation [2/4] Loss: 0.22184 focal_loss 0.10063 dice_loss 0.12121 +Epoch [942/4000] Validation [3/4] Loss: 0.21130 focal_loss 0.11682 dice_loss 0.09448 +Epoch [942/4000] Validation [4/4] Loss: 0.21920 focal_loss 0.09522 dice_loss 0.12397 +Epoch [942/4000] Validation metric {'Val/mean dice_metric': 0.9691358804702759, 'Val/mean miou_metric': 0.9494926333427429, 'Val/mean f1': 0.9693355560302734, 'Val/mean precision': 0.9613723754882812, 'Val/mean recall': 0.9774316549301147, 'Val/mean hd95_metric': 6.973532199859619} +Cheakpoint... +Epoch [942/4000] best acc:tensor([0.9719], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691358804702759, 'Val/mean miou_metric': 0.9494926333427429, 'Val/mean f1': 0.9693355560302734, 'Val/mean precision': 0.9613723754882812, 'Val/mean recall': 0.9774316549301147, 'Val/mean hd95_metric': 6.973532199859619} +Epoch [943/4000] Training [1/16] Loss: 0.00944 +Epoch [943/4000] Training [2/16] Loss: 0.01367 +Epoch [943/4000] Training [3/16] Loss: 0.01362 +Epoch [943/4000] Training [4/16] Loss: 0.01372 +Epoch [943/4000] Training [5/16] Loss: 0.01321 +Epoch [943/4000] Training [6/16] Loss: 0.01114 +Epoch [943/4000] Training [7/16] Loss: 0.01298 +Epoch [943/4000] Training [8/16] Loss: 0.00865 +Epoch [943/4000] Training [9/16] Loss: 0.01904 +Epoch [943/4000] Training [10/16] Loss: 0.01115 +Epoch [943/4000] Training [11/16] Loss: 0.01221 +Epoch [943/4000] Training [12/16] Loss: 0.01036 +Epoch [943/4000] Training [13/16] Loss: 0.01819 +Epoch [943/4000] Training [14/16] Loss: 0.00945 +Epoch [943/4000] Training [15/16] Loss: 0.01124 +Epoch [943/4000] Training [16/16] Loss: 0.01324 +Epoch [943/4000] Training metric {'Train/mean dice_metric': 0.9913516044616699, 'Train/mean miou_metric': 0.9826326966285706, 'Train/mean f1': 0.9874536395072937, 'Train/mean precision': 0.9823433756828308, 'Train/mean recall': 0.9926173090934753, 'Train/mean hd95_metric': 1.1659305095672607} +Epoch [943/4000] Validation [1/4] Loss: 0.16235 focal_loss 0.10584 dice_loss 0.05651 +Epoch [943/4000] Validation [2/4] Loss: 0.26675 focal_loss 0.13458 dice_loss 0.13216 +Epoch [943/4000] Validation [3/4] Loss: 0.16592 focal_loss 0.09386 dice_loss 0.07205 +Epoch [943/4000] Validation [4/4] Loss: 0.27777 focal_loss 0.15668 dice_loss 0.12108 +Epoch [943/4000] Validation metric {'Val/mean dice_metric': 0.972198486328125, 'Val/mean miou_metric': 0.9519411325454712, 'Val/mean f1': 0.9711037278175354, 'Val/mean precision': 0.9643290638923645, 'Val/mean recall': 0.9779744148254395, 'Val/mean hd95_metric': 6.272805690765381} +Cheakpoint... +Epoch [943/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972198486328125, 'Val/mean miou_metric': 0.9519411325454712, 'Val/mean f1': 0.9711037278175354, 'Val/mean precision': 0.9643290638923645, 'Val/mean recall': 0.9779744148254395, 'Val/mean hd95_metric': 6.272805690765381} +Epoch [944/4000] Training [1/16] Loss: 0.01293 +Epoch [944/4000] Training [2/16] Loss: 0.01452 +Epoch [944/4000] Training [3/16] Loss: 0.01071 +Epoch [944/4000] Training [4/16] Loss: 0.00890 +Epoch [944/4000] Training [5/16] Loss: 0.01399 +Epoch [944/4000] Training [6/16] Loss: 0.01297 +Epoch [944/4000] Training [7/16] Loss: 0.01322 +Epoch [944/4000] Training [8/16] Loss: 0.01301 +Epoch [944/4000] Training [9/16] Loss: 0.01146 +Epoch [944/4000] Training [10/16] Loss: 0.01141 +Epoch [944/4000] Training [11/16] Loss: 0.01685 +Epoch [944/4000] Training [12/16] Loss: 0.01081 +Epoch [944/4000] Training [13/16] Loss: 0.01198 +Epoch [944/4000] Training [14/16] Loss: 0.01154 +Epoch [944/4000] Training [15/16] Loss: 0.00995 +Epoch [944/4000] Training [16/16] Loss: 0.01038 +Epoch [944/4000] Training metric {'Train/mean dice_metric': 0.9913969039916992, 'Train/mean miou_metric': 0.9827337265014648, 'Train/mean f1': 0.9881452322006226, 'Train/mean precision': 0.9835956692695618, 'Train/mean recall': 0.9927370548248291, 'Train/mean hd95_metric': 1.1825833320617676} +Epoch [944/4000] Validation [1/4] Loss: 0.17673 focal_loss 0.11103 dice_loss 0.06571 +Epoch [944/4000] Validation [2/4] Loss: 0.22119 focal_loss 0.09635 dice_loss 0.12484 +Epoch [944/4000] Validation [3/4] Loss: 0.22747 focal_loss 0.12502 dice_loss 0.10244 +Epoch [944/4000] Validation [4/4] Loss: 0.16642 focal_loss 0.08332 dice_loss 0.08310 +Epoch [944/4000] Validation metric {'Val/mean dice_metric': 0.9718731045722961, 'Val/mean miou_metric': 0.9516611099243164, 'Val/mean f1': 0.9719481468200684, 'Val/mean precision': 0.9666769504547119, 'Val/mean recall': 0.9772770404815674, 'Val/mean hd95_metric': 6.4031877517700195} +Cheakpoint... +Epoch [944/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718731045722961, 'Val/mean miou_metric': 0.9516611099243164, 'Val/mean f1': 0.9719481468200684, 'Val/mean precision': 0.9666769504547119, 'Val/mean recall': 0.9772770404815674, 'Val/mean hd95_metric': 6.4031877517700195} +Epoch [945/4000] Training [1/16] Loss: 0.01418 +Epoch [945/4000] Training [2/16] Loss: 0.00944 +Epoch [945/4000] Training [3/16] Loss: 0.01210 +Epoch [945/4000] Training [4/16] Loss: 0.01095 +Epoch [945/4000] Training [5/16] Loss: 0.01074 +Epoch [945/4000] Training [6/16] Loss: 0.01186 +Epoch [945/4000] Training [7/16] Loss: 0.01131 +Epoch [945/4000] Training [8/16] Loss: 0.00940 +Epoch [945/4000] Training [9/16] Loss: 0.00870 +Epoch [945/4000] Training [10/16] Loss: 0.00989 +Epoch [945/4000] Training [11/16] Loss: 0.01709 +Epoch [945/4000] Training [12/16] Loss: 0.01622 +Epoch [945/4000] Training [13/16] Loss: 0.01099 +Epoch [945/4000] Training [14/16] Loss: 0.02369 +Epoch [945/4000] Training [15/16] Loss: 0.02460 +Epoch [945/4000] Training [16/16] Loss: 0.00873 +Epoch [945/4000] Training metric {'Train/mean dice_metric': 0.9912599325180054, 'Train/mean miou_metric': 0.9824874401092529, 'Train/mean f1': 0.9882057905197144, 'Train/mean precision': 0.9835981726646423, 'Train/mean recall': 0.9928568005561829, 'Train/mean hd95_metric': 1.207794189453125} +Epoch [945/4000] Validation [1/4] Loss: 0.15208 focal_loss 0.08999 dice_loss 0.06209 +Epoch [945/4000] Validation [2/4] Loss: 0.33371 focal_loss 0.15092 dice_loss 0.18279 +Epoch [945/4000] Validation [3/4] Loss: 0.32237 focal_loss 0.19400 dice_loss 0.12837 +Epoch [945/4000] Validation [4/4] Loss: 0.29788 focal_loss 0.17517 dice_loss 0.12271 +Epoch [945/4000] Validation metric {'Val/mean dice_metric': 0.9695865511894226, 'Val/mean miou_metric': 0.9487819671630859, 'Val/mean f1': 0.9697741270065308, 'Val/mean precision': 0.9638203978538513, 'Val/mean recall': 0.975801944732666, 'Val/mean hd95_metric': 6.121890068054199} +Cheakpoint... +Epoch [945/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695865511894226, 'Val/mean miou_metric': 0.9487819671630859, 'Val/mean f1': 0.9697741270065308, 'Val/mean precision': 0.9638203978538513, 'Val/mean recall': 0.975801944732666, 'Val/mean hd95_metric': 6.121890068054199} +Epoch [946/4000] Training [1/16] Loss: 0.01442 +Epoch [946/4000] Training [2/16] Loss: 0.01056 +Epoch [946/4000] Training [3/16] Loss: 0.00862 +Epoch [946/4000] Training [4/16] Loss: 0.01181 +Epoch [946/4000] Training [5/16] Loss: 0.01018 +Epoch [946/4000] Training [6/16] Loss: 0.00782 +Epoch [946/4000] Training [7/16] Loss: 0.01079 +Epoch [946/4000] Training [8/16] Loss: 0.01069 +Epoch [946/4000] Training [9/16] Loss: 0.01136 +Epoch [946/4000] Training [10/16] Loss: 0.00918 +Epoch [946/4000] Training [11/16] Loss: 0.01191 +Epoch [946/4000] Training [12/16] Loss: 0.00797 +Epoch [946/4000] Training [13/16] Loss: 0.01434 +Epoch [946/4000] Training [14/16] Loss: 0.01368 +Epoch [946/4000] Training [15/16] Loss: 0.01445 +Epoch [946/4000] Training [16/16] Loss: 0.00929 +Epoch [946/4000] Training metric {'Train/mean dice_metric': 0.9921908378601074, 'Train/mean miou_metric': 0.9842504262924194, 'Train/mean f1': 0.9879588484764099, 'Train/mean precision': 0.9826367497444153, 'Train/mean recall': 0.9933388233184814, 'Train/mean hd95_metric': 1.2557448148727417} +Epoch [946/4000] Validation [1/4] Loss: 0.14078 focal_loss 0.07934 dice_loss 0.06144 +Epoch [946/4000] Validation [2/4] Loss: 0.46733 focal_loss 0.23700 dice_loss 0.23034 +Epoch [946/4000] Validation [3/4] Loss: 0.25245 focal_loss 0.13962 dice_loss 0.11283 +Epoch [946/4000] Validation [4/4] Loss: 0.28812 focal_loss 0.14004 dice_loss 0.14808 +Epoch [946/4000] Validation metric {'Val/mean dice_metric': 0.9687007665634155, 'Val/mean miou_metric': 0.9489429593086243, 'Val/mean f1': 0.9696781039237976, 'Val/mean precision': 0.9611544609069824, 'Val/mean recall': 0.9783541560173035, 'Val/mean hd95_metric': 6.704297065734863} +Cheakpoint... +Epoch [946/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687007665634155, 'Val/mean miou_metric': 0.9489429593086243, 'Val/mean f1': 0.9696781039237976, 'Val/mean precision': 0.9611544609069824, 'Val/mean recall': 0.9783541560173035, 'Val/mean hd95_metric': 6.704297065734863} +Epoch [947/4000] Training [1/16] Loss: 0.01160 +Epoch [947/4000] Training [2/16] Loss: 0.01763 +Epoch [947/4000] Training [3/16] Loss: 0.00993 +Epoch [947/4000] Training [4/16] Loss: 0.00864 +Epoch [947/4000] Training [5/16] Loss: 0.01302 +Epoch [947/4000] Training [6/16] Loss: 0.01008 +Epoch [947/4000] Training [7/16] Loss: 0.01301 +Epoch [947/4000] Training [8/16] Loss: 0.01322 +Epoch [947/4000] Training [9/16] Loss: 0.01348 +Epoch [947/4000] Training [10/16] Loss: 0.00915 +Epoch [947/4000] Training [11/16] Loss: 0.00973 +Epoch [947/4000] Training [12/16] Loss: 0.01230 +Epoch [947/4000] Training [13/16] Loss: 0.01207 +Epoch [947/4000] Training [14/16] Loss: 0.01141 +Epoch [947/4000] Training [15/16] Loss: 0.01530 +Epoch [947/4000] Training [16/16] Loss: 0.01065 +Epoch [947/4000] Training metric {'Train/mean dice_metric': 0.9920046329498291, 'Train/mean miou_metric': 0.9838839769363403, 'Train/mean f1': 0.9883370995521545, 'Train/mean precision': 0.9834066033363342, 'Train/mean recall': 0.993317186832428, 'Train/mean hd95_metric': 1.1523687839508057} +Epoch [947/4000] Validation [1/4] Loss: 0.22984 focal_loss 0.13572 dice_loss 0.09412 +Epoch [947/4000] Validation [2/4] Loss: 0.29616 focal_loss 0.15551 dice_loss 0.14065 +Epoch [947/4000] Validation [3/4] Loss: 0.12489 focal_loss 0.06631 dice_loss 0.05857 +Epoch [947/4000] Validation [4/4] Loss: 0.27546 focal_loss 0.17737 dice_loss 0.09809 +Epoch [947/4000] Validation metric {'Val/mean dice_metric': 0.9703127145767212, 'Val/mean miou_metric': 0.9509245753288269, 'Val/mean f1': 0.9709699153900146, 'Val/mean precision': 0.9670783877372742, 'Val/mean recall': 0.9748929142951965, 'Val/mean hd95_metric': 5.728104114532471} +Cheakpoint... +Epoch [947/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703127145767212, 'Val/mean miou_metric': 0.9509245753288269, 'Val/mean f1': 0.9709699153900146, 'Val/mean precision': 0.9670783877372742, 'Val/mean recall': 0.9748929142951965, 'Val/mean hd95_metric': 5.728104114532471} +Epoch [948/4000] Training [1/16] Loss: 0.01443 +Epoch [948/4000] Training [2/16] Loss: 0.01029 +Epoch [948/4000] Training [3/16] Loss: 0.01267 +Epoch [948/4000] Training [4/16] Loss: 0.00905 +Epoch [948/4000] Training [5/16] Loss: 0.01650 +Epoch [948/4000] Training [6/16] Loss: 0.01529 +Epoch [948/4000] Training [7/16] Loss: 0.00924 +Epoch [948/4000] Training [8/16] Loss: 0.01444 +Epoch [948/4000] Training [9/16] Loss: 0.01586 +Epoch [948/4000] Training [10/16] Loss: 0.01451 +Epoch [948/4000] Training [11/16] Loss: 0.00919 +Epoch [948/4000] Training [12/16] Loss: 0.01347 +Epoch [948/4000] Training [13/16] Loss: 0.01233 +Epoch [948/4000] Training [14/16] Loss: 0.01166 +Epoch [948/4000] Training [15/16] Loss: 0.01414 +Epoch [948/4000] Training [16/16] Loss: 0.01198 +Epoch [948/4000] Training metric {'Train/mean dice_metric': 0.9911671280860901, 'Train/mean miou_metric': 0.9823188185691833, 'Train/mean f1': 0.9882882237434387, 'Train/mean precision': 0.9839562773704529, 'Train/mean recall': 0.9926584959030151, 'Train/mean hd95_metric': 1.1918705701828003} +Epoch [948/4000] Validation [1/4] Loss: 0.17796 focal_loss 0.11569 dice_loss 0.06227 +Epoch [948/4000] Validation [2/4] Loss: 0.40008 focal_loss 0.21475 dice_loss 0.18533 +Epoch [948/4000] Validation [3/4] Loss: 0.18928 focal_loss 0.09877 dice_loss 0.09051 +Epoch [948/4000] Validation [4/4] Loss: 0.24903 focal_loss 0.14141 dice_loss 0.10762 +Epoch [948/4000] Validation metric {'Val/mean dice_metric': 0.9688884615898132, 'Val/mean miou_metric': 0.9487221837043762, 'Val/mean f1': 0.9707654118537903, 'Val/mean precision': 0.9648981094360352, 'Val/mean recall': 0.9767045974731445, 'Val/mean hd95_metric': 6.276288032531738} +Cheakpoint... +Epoch [948/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688884615898132, 'Val/mean miou_metric': 0.9487221837043762, 'Val/mean f1': 0.9707654118537903, 'Val/mean precision': 0.9648981094360352, 'Val/mean recall': 0.9767045974731445, 'Val/mean hd95_metric': 6.276288032531738} +Epoch [949/4000] Training [1/16] Loss: 0.01074 +Epoch [949/4000] Training [2/16] Loss: 0.00771 +Epoch [949/4000] Training [3/16] Loss: 0.01341 +Epoch [949/4000] Training [4/16] Loss: 0.01733 +Epoch [949/4000] Training [5/16] Loss: 0.01087 +Epoch [949/4000] Training [6/16] Loss: 0.01071 +Epoch [949/4000] Training [7/16] Loss: 0.00953 +Epoch [949/4000] Training [8/16] Loss: 0.01296 +Epoch [949/4000] Training [9/16] Loss: 0.01414 +Epoch [949/4000] Training [10/16] Loss: 0.01375 +Epoch [949/4000] Training [11/16] Loss: 0.01035 +Epoch [949/4000] Training [12/16] Loss: 0.01449 +Epoch [949/4000] Training [13/16] Loss: 0.01553 +Epoch [949/4000] Training [14/16] Loss: 0.01236 +Epoch [949/4000] Training [15/16] Loss: 0.01356 +Epoch [949/4000] Training [16/16] Loss: 0.01359 +Epoch [949/4000] Training metric {'Train/mean dice_metric': 0.989961564540863, 'Train/mean miou_metric': 0.9805499315261841, 'Train/mean f1': 0.9866583347320557, 'Train/mean precision': 0.9814616441726685, 'Train/mean recall': 0.9919103980064392, 'Train/mean hd95_metric': 2.3300867080688477} +Epoch [949/4000] Validation [1/4] Loss: 0.52167 focal_loss 0.35054 dice_loss 0.17113 +Epoch [949/4000] Validation [2/4] Loss: 0.23587 focal_loss 0.11064 dice_loss 0.12523 +Epoch [949/4000] Validation [3/4] Loss: 0.15393 focal_loss 0.08413 dice_loss 0.06980 +Epoch [949/4000] Validation [4/4] Loss: 0.48608 focal_loss 0.31961 dice_loss 0.16647 +Epoch [949/4000] Validation metric {'Val/mean dice_metric': 0.9595443606376648, 'Val/mean miou_metric': 0.9369619488716125, 'Val/mean f1': 0.9612933397293091, 'Val/mean precision': 0.9696410298347473, 'Val/mean recall': 0.9530881643295288, 'Val/mean hd95_metric': 8.375837326049805} +Cheakpoint... +Epoch [949/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9595], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9595443606376648, 'Val/mean miou_metric': 0.9369619488716125, 'Val/mean f1': 0.9612933397293091, 'Val/mean precision': 0.9696410298347473, 'Val/mean recall': 0.9530881643295288, 'Val/mean hd95_metric': 8.375837326049805} +Epoch [950/4000] Training [1/16] Loss: 0.01269 +Epoch [950/4000] Training [2/16] Loss: 0.02079 +Epoch [950/4000] Training [3/16] Loss: 0.01255 +Epoch [950/4000] Training [4/16] Loss: 0.01056 +Epoch [950/4000] Training [5/16] Loss: 0.01012 +Epoch [950/4000] Training [6/16] Loss: 0.02214 +Epoch [950/4000] Training [7/16] Loss: 0.01879 +Epoch [950/4000] Training [8/16] Loss: 0.01073 +Epoch [950/4000] Training [9/16] Loss: 0.01516 +Epoch [950/4000] Training [10/16] Loss: 0.01913 +Epoch [950/4000] Training [11/16] Loss: 0.01533 +Epoch [950/4000] Training [12/16] Loss: 0.01341 +Epoch [950/4000] Training [13/16] Loss: 0.01153 +Epoch [950/4000] Training [14/16] Loss: 0.02238 +Epoch [950/4000] Training [15/16] Loss: 0.01279 +Epoch [950/4000] Training [16/16] Loss: 0.01812 +Epoch [950/4000] Training metric {'Train/mean dice_metric': 0.988166332244873, 'Train/mean miou_metric': 0.9779393672943115, 'Train/mean f1': 0.9856743216514587, 'Train/mean precision': 0.9816428422927856, 'Train/mean recall': 0.9897390604019165, 'Train/mean hd95_metric': 2.8636860847473145} +Epoch [950/4000] Validation [1/4] Loss: 0.20211 focal_loss 0.10738 dice_loss 0.09473 +Epoch [950/4000] Validation [2/4] Loss: 0.24451 focal_loss 0.09956 dice_loss 0.14495 +Epoch [950/4000] Validation [3/4] Loss: 0.15260 focal_loss 0.07431 dice_loss 0.07830 +Epoch [950/4000] Validation [4/4] Loss: 0.52757 focal_loss 0.34706 dice_loss 0.18051 +Epoch [950/4000] Validation metric {'Val/mean dice_metric': 0.9651853442192078, 'Val/mean miou_metric': 0.9418283700942993, 'Val/mean f1': 0.9664414525032043, 'Val/mean precision': 0.9645507335662842, 'Val/mean recall': 0.9683395624160767, 'Val/mean hd95_metric': 9.408617973327637} +Cheakpoint... +Epoch [950/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9651853442192078, 'Val/mean miou_metric': 0.9418283700942993, 'Val/mean f1': 0.9664414525032043, 'Val/mean precision': 0.9645507335662842, 'Val/mean recall': 0.9683395624160767, 'Val/mean hd95_metric': 9.408617973327637} +Epoch [951/4000] Training [1/16] Loss: 0.01462 +Epoch [951/4000] Training [2/16] Loss: 0.01355 +Epoch [951/4000] Training [3/16] Loss: 0.01409 +Epoch [951/4000] Training [4/16] Loss: 0.01700 +Epoch [951/4000] Training [5/16] Loss: 0.01355 +Epoch [951/4000] Training [6/16] Loss: 0.01599 +Epoch [951/4000] Training [7/16] Loss: 0.01035 +Epoch [951/4000] Training [8/16] Loss: 0.01024 +Epoch [951/4000] Training [9/16] Loss: 0.01529 +Epoch [951/4000] Training [10/16] Loss: 0.01075 +Epoch [951/4000] Training [11/16] Loss: 0.01213 +Epoch [951/4000] Training [12/16] Loss: 0.01332 +Epoch [951/4000] Training [13/16] Loss: 0.01425 +Epoch [951/4000] Training [14/16] Loss: 0.01054 +Epoch [951/4000] Training [15/16] Loss: 0.01137 +Epoch [951/4000] Training [16/16] Loss: 0.01368 +Epoch [951/4000] Training metric {'Train/mean dice_metric': 0.9894665479660034, 'Train/mean miou_metric': 0.9792518615722656, 'Train/mean f1': 0.9860741496086121, 'Train/mean precision': 0.9820352792739868, 'Train/mean recall': 0.9901464581489563, 'Train/mean hd95_metric': 2.1378159523010254} +Epoch [951/4000] Validation [1/4] Loss: 0.17657 focal_loss 0.11002 dice_loss 0.06655 +Epoch [951/4000] Validation [2/4] Loss: 0.30124 focal_loss 0.13218 dice_loss 0.16906 +Epoch [951/4000] Validation [3/4] Loss: 0.18373 focal_loss 0.10594 dice_loss 0.07779 +Epoch [951/4000] Validation [4/4] Loss: 0.34536 focal_loss 0.20399 dice_loss 0.14137 +Epoch [951/4000] Validation metric {'Val/mean dice_metric': 0.9648672342300415, 'Val/mean miou_metric': 0.9425169229507446, 'Val/mean f1': 0.9677233099937439, 'Val/mean precision': 0.963557779788971, 'Val/mean recall': 0.9719250798225403, 'Val/mean hd95_metric': 7.539559841156006} +Cheakpoint... +Epoch [951/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648672342300415, 'Val/mean miou_metric': 0.9425169229507446, 'Val/mean f1': 0.9677233099937439, 'Val/mean precision': 0.963557779788971, 'Val/mean recall': 0.9719250798225403, 'Val/mean hd95_metric': 7.539559841156006} +Epoch [952/4000] Training [1/16] Loss: 0.01046 +Epoch [952/4000] Training [2/16] Loss: 0.01379 +Epoch [952/4000] Training [3/16] Loss: 0.01210 +Epoch [952/4000] Training [4/16] Loss: 0.01540 +Epoch [952/4000] Training [5/16] Loss: 0.01387 +Epoch [952/4000] Training [6/16] Loss: 0.01128 +Epoch [952/4000] Training [7/16] Loss: 0.00963 +Epoch [952/4000] Training [8/16] Loss: 0.03670 +Epoch [952/4000] Training [9/16] Loss: 0.01313 +Epoch [952/4000] Training [10/16] Loss: 0.01702 +Epoch [952/4000] Training [11/16] Loss: 0.01405 +Epoch [952/4000] Training [12/16] Loss: 0.01412 +Epoch [952/4000] Training [13/16] Loss: 0.02577 +Epoch [952/4000] Training [14/16] Loss: 0.01603 +Epoch [952/4000] Training [15/16] Loss: 0.01969 +Epoch [952/4000] Training [16/16] Loss: 0.01804 +Epoch [952/4000] Training metric {'Train/mean dice_metric': 0.9901200532913208, 'Train/mean miou_metric': 0.9802789092063904, 'Train/mean f1': 0.9863597750663757, 'Train/mean precision': 0.9810947179794312, 'Train/mean recall': 0.991681694984436, 'Train/mean hd95_metric': 2.8636982440948486} +Epoch [952/4000] Validation [1/4] Loss: 0.38767 focal_loss 0.24472 dice_loss 0.14295 +Epoch [952/4000] Validation [2/4] Loss: 0.21389 focal_loss 0.09582 dice_loss 0.11807 +Epoch [952/4000] Validation [3/4] Loss: 0.17294 focal_loss 0.09561 dice_loss 0.07733 +Epoch [952/4000] Validation [4/4] Loss: 0.45101 focal_loss 0.29680 dice_loss 0.15422 +Epoch [952/4000] Validation metric {'Val/mean dice_metric': 0.9631646275520325, 'Val/mean miou_metric': 0.9411710500717163, 'Val/mean f1': 0.9652141332626343, 'Val/mean precision': 0.9664008021354675, 'Val/mean recall': 0.9640303254127502, 'Val/mean hd95_metric': 8.517372131347656} +Cheakpoint... +Epoch [952/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631646275520325, 'Val/mean miou_metric': 0.9411710500717163, 'Val/mean f1': 0.9652141332626343, 'Val/mean precision': 0.9664008021354675, 'Val/mean recall': 0.9640303254127502, 'Val/mean hd95_metric': 8.517372131347656} +Epoch [953/4000] Training [1/16] Loss: 0.02351 +Epoch [953/4000] Training [2/16] Loss: 0.01468 +Epoch [953/4000] Training [3/16] Loss: 0.01002 +Epoch [953/4000] Training [4/16] Loss: 0.01670 +Epoch [953/4000] Training [5/16] Loss: 0.01014 +Epoch [953/4000] Training [6/16] Loss: 0.01337 +Epoch [953/4000] Training [7/16] Loss: 0.01442 +Epoch [953/4000] Training [8/16] Loss: 0.01332 +Epoch [953/4000] Training [9/16] Loss: 0.01564 +Epoch [953/4000] Training [10/16] Loss: 0.00975 +Epoch [953/4000] Training [11/16] Loss: 0.01238 +Epoch [953/4000] Training [12/16] Loss: 0.01698 +Epoch [953/4000] Training [13/16] Loss: 0.01165 +Epoch [953/4000] Training [14/16] Loss: 0.01393 +Epoch [953/4000] Training [15/16] Loss: 0.01303 +Epoch [953/4000] Training [16/16] Loss: 0.01404 +Epoch [953/4000] Training metric {'Train/mean dice_metric': 0.9890446662902832, 'Train/mean miou_metric': 0.9790548086166382, 'Train/mean f1': 0.9858893752098083, 'Train/mean precision': 0.982214093208313, 'Train/mean recall': 0.9895922541618347, 'Train/mean hd95_metric': 2.2150754928588867} +Epoch [953/4000] Validation [1/4] Loss: 0.15698 focal_loss 0.09887 dice_loss 0.05811 +Epoch [953/4000] Validation [2/4] Loss: 0.39854 focal_loss 0.20457 dice_loss 0.19398 +Epoch [953/4000] Validation [3/4] Loss: 0.16057 focal_loss 0.08109 dice_loss 0.07948 +Epoch [953/4000] Validation [4/4] Loss: 0.38040 focal_loss 0.22779 dice_loss 0.15261 +Epoch [953/4000] Validation metric {'Val/mean dice_metric': 0.9621356129646301, 'Val/mean miou_metric': 0.9409381151199341, 'Val/mean f1': 0.9639496803283691, 'Val/mean precision': 0.957802414894104, 'Val/mean recall': 0.9701763987541199, 'Val/mean hd95_metric': 8.000821113586426} +Cheakpoint... +Epoch [953/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9621], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9621356129646301, 'Val/mean miou_metric': 0.9409381151199341, 'Val/mean f1': 0.9639496803283691, 'Val/mean precision': 0.957802414894104, 'Val/mean recall': 0.9701763987541199, 'Val/mean hd95_metric': 8.000821113586426} +Epoch [954/4000] Training [1/16] Loss: 0.01352 +Epoch [954/4000] Training [2/16] Loss: 0.01361 +Epoch [954/4000] Training [3/16] Loss: 0.00979 +Epoch [954/4000] Training [4/16] Loss: 0.01158 +Epoch [954/4000] Training [5/16] Loss: 0.01617 +Epoch [954/4000] Training [6/16] Loss: 0.01361 +Epoch [954/4000] Training [7/16] Loss: 0.01229 +Epoch [954/4000] Training [8/16] Loss: 0.01425 +Epoch [954/4000] Training [9/16] Loss: 0.01181 +Epoch [954/4000] Training [10/16] Loss: 0.01073 +Epoch [954/4000] Training [11/16] Loss: 0.01282 +Epoch [954/4000] Training [12/16] Loss: 0.01131 +Epoch [954/4000] Training [13/16] Loss: 0.01376 +Epoch [954/4000] Training [14/16] Loss: 0.01322 +Epoch [954/4000] Training [15/16] Loss: 0.01264 +Epoch [954/4000] Training [16/16] Loss: 0.01485 +Epoch [954/4000] Training metric {'Train/mean dice_metric': 0.9909712076187134, 'Train/mean miou_metric': 0.9818762540817261, 'Train/mean f1': 0.9869830012321472, 'Train/mean precision': 0.9821836948394775, 'Train/mean recall': 0.9918294548988342, 'Train/mean hd95_metric': 1.5052050352096558} +Epoch [954/4000] Validation [1/4] Loss: 0.19107 focal_loss 0.11860 dice_loss 0.07248 +Epoch [954/4000] Validation [2/4] Loss: 0.16005 focal_loss 0.06618 dice_loss 0.09387 +Epoch [954/4000] Validation [3/4] Loss: 0.22614 focal_loss 0.12821 dice_loss 0.09793 +Epoch [954/4000] Validation [4/4] Loss: 0.27515 focal_loss 0.15796 dice_loss 0.11719 +Epoch [954/4000] Validation metric {'Val/mean dice_metric': 0.9679424166679382, 'Val/mean miou_metric': 0.9470571279525757, 'Val/mean f1': 0.9710750579833984, 'Val/mean precision': 0.9651723504066467, 'Val/mean recall': 0.9770503640174866, 'Val/mean hd95_metric': 6.615286827087402} +Cheakpoint... +Epoch [954/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679424166679382, 'Val/mean miou_metric': 0.9470571279525757, 'Val/mean f1': 0.9710750579833984, 'Val/mean precision': 0.9651723504066467, 'Val/mean recall': 0.9770503640174866, 'Val/mean hd95_metric': 6.615286827087402} +Epoch [955/4000] Training [1/16] Loss: 0.01812 +Epoch [955/4000] Training [2/16] Loss: 0.01536 +Epoch [955/4000] Training [3/16] Loss: 0.01234 +Epoch [955/4000] Training [4/16] Loss: 0.00952 +Epoch [955/4000] Training [5/16] Loss: 0.01173 +Epoch [955/4000] Training [6/16] Loss: 0.00966 +Epoch [955/4000] Training [7/16] Loss: 0.01260 +Epoch [955/4000] Training [8/16] Loss: 0.01007 +Epoch [955/4000] Training [9/16] Loss: 0.01365 +Epoch [955/4000] Training [10/16] Loss: 0.01122 +Epoch [955/4000] Training [11/16] Loss: 0.00947 +Epoch [955/4000] Training [12/16] Loss: 0.01604 +Epoch [955/4000] Training [13/16] Loss: 0.01337 +Epoch [955/4000] Training [14/16] Loss: 0.00831 +Epoch [955/4000] Training [15/16] Loss: 0.01090 +Epoch [955/4000] Training [16/16] Loss: 0.01146 +Epoch [955/4000] Training metric {'Train/mean dice_metric': 0.9918144345283508, 'Train/mean miou_metric': 0.9835449457168579, 'Train/mean f1': 0.9881330132484436, 'Train/mean precision': 0.9836804270744324, 'Train/mean recall': 0.9926260709762573, 'Train/mean hd95_metric': 1.3071333169937134} +Epoch [955/4000] Validation [1/4] Loss: 0.13078 focal_loss 0.07059 dice_loss 0.06020 +Epoch [955/4000] Validation [2/4] Loss: 0.37826 focal_loss 0.18896 dice_loss 0.18929 +Epoch [955/4000] Validation [3/4] Loss: 0.16563 focal_loss 0.09057 dice_loss 0.07506 +Epoch [955/4000] Validation [4/4] Loss: 0.19311 focal_loss 0.09062 dice_loss 0.10249 +Epoch [955/4000] Validation metric {'Val/mean dice_metric': 0.9689927101135254, 'Val/mean miou_metric': 0.9494578242301941, 'Val/mean f1': 0.9712095856666565, 'Val/mean precision': 0.9649506211280823, 'Val/mean recall': 0.9775503277778625, 'Val/mean hd95_metric': 6.298425674438477} +Cheakpoint... +Epoch [955/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689927101135254, 'Val/mean miou_metric': 0.9494578242301941, 'Val/mean f1': 0.9712095856666565, 'Val/mean precision': 0.9649506211280823, 'Val/mean recall': 0.9775503277778625, 'Val/mean hd95_metric': 6.298425674438477} +Epoch [956/4000] Training [1/16] Loss: 0.01174 +Epoch [956/4000] Training [2/16] Loss: 0.00884 +Epoch [956/4000] Training [3/16] Loss: 0.01139 +Epoch [956/4000] Training [4/16] Loss: 0.01101 +Epoch [956/4000] Training [5/16] Loss: 0.01332 +Epoch [956/4000] Training [6/16] Loss: 0.00860 +Epoch [956/4000] Training [7/16] Loss: 0.01668 +Epoch [956/4000] Training [8/16] Loss: 0.01452 +Epoch [956/4000] Training [9/16] Loss: 0.01222 +Epoch [956/4000] Training [10/16] Loss: 0.01023 +Epoch [956/4000] Training [11/16] Loss: 0.01239 +Epoch [956/4000] Training [12/16] Loss: 0.01040 +Epoch [956/4000] Training [13/16] Loss: 0.01050 +Epoch [956/4000] Training [14/16] Loss: 0.01036 +Epoch [956/4000] Training [15/16] Loss: 0.00947 +Epoch [956/4000] Training [16/16] Loss: 0.01327 +Epoch [956/4000] Training metric {'Train/mean dice_metric': 0.9920963048934937, 'Train/mean miou_metric': 0.9840813875198364, 'Train/mean f1': 0.9880175590515137, 'Train/mean precision': 0.983138382434845, 'Train/mean recall': 0.9929454326629639, 'Train/mean hd95_metric': 1.1784272193908691} +Epoch [956/4000] Validation [1/4] Loss: 0.19259 focal_loss 0.11861 dice_loss 0.07398 +Epoch [956/4000] Validation [2/4] Loss: 0.23904 focal_loss 0.11501 dice_loss 0.12403 +Epoch [956/4000] Validation [3/4] Loss: 0.19010 focal_loss 0.11107 dice_loss 0.07903 +Epoch [956/4000] Validation [4/4] Loss: 0.35228 focal_loss 0.20518 dice_loss 0.14710 +Epoch [956/4000] Validation metric {'Val/mean dice_metric': 0.9717003703117371, 'Val/mean miou_metric': 0.951865553855896, 'Val/mean f1': 0.9728154540061951, 'Val/mean precision': 0.9696759581565857, 'Val/mean recall': 0.9759753942489624, 'Val/mean hd95_metric': 5.44993782043457} +Cheakpoint... +Epoch [956/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717003703117371, 'Val/mean miou_metric': 0.951865553855896, 'Val/mean f1': 0.9728154540061951, 'Val/mean precision': 0.9696759581565857, 'Val/mean recall': 0.9759753942489624, 'Val/mean hd95_metric': 5.44993782043457} +Epoch [957/4000] Training [1/16] Loss: 0.00886 +Epoch [957/4000] Training [2/16] Loss: 0.01071 +Epoch [957/4000] Training [3/16] Loss: 0.01210 +Epoch [957/4000] Training [4/16] Loss: 0.01403 +Epoch [957/4000] Training [5/16] Loss: 0.01196 +Epoch [957/4000] Training [6/16] Loss: 0.00927 +Epoch [957/4000] Training [7/16] Loss: 0.01499 +Epoch [957/4000] Training [8/16] Loss: 0.00836 +Epoch [957/4000] Training [9/16] Loss: 0.01056 +Epoch [957/4000] Training [10/16] Loss: 0.00948 +Epoch [957/4000] Training [11/16] Loss: 0.01126 +Epoch [957/4000] Training [12/16] Loss: 0.01225 +Epoch [957/4000] Training [13/16] Loss: 0.00833 +Epoch [957/4000] Training [14/16] Loss: 0.01136 +Epoch [957/4000] Training [15/16] Loss: 0.00945 +Epoch [957/4000] Training [16/16] Loss: 0.01020 +Epoch [957/4000] Training metric {'Train/mean dice_metric': 0.9926350116729736, 'Train/mean miou_metric': 0.9851546883583069, 'Train/mean f1': 0.9891213178634644, 'Train/mean precision': 0.9845236539840698, 'Train/mean recall': 0.993762195110321, 'Train/mean hd95_metric': 1.132094383239746} +Epoch [957/4000] Validation [1/4] Loss: 0.16804 focal_loss 0.10320 dice_loss 0.06485 +Epoch [957/4000] Validation [2/4] Loss: 0.24777 focal_loss 0.12157 dice_loss 0.12620 +Epoch [957/4000] Validation [3/4] Loss: 0.24670 focal_loss 0.15272 dice_loss 0.09397 +Epoch [957/4000] Validation [4/4] Loss: 0.16883 focal_loss 0.09142 dice_loss 0.07741 +Epoch [957/4000] Validation metric {'Val/mean dice_metric': 0.9713387489318848, 'Val/mean miou_metric': 0.9524404406547546, 'Val/mean f1': 0.9732804298400879, 'Val/mean precision': 0.9689480662345886, 'Val/mean recall': 0.9776517152786255, 'Val/mean hd95_metric': 5.6958489418029785} +Cheakpoint... +Epoch [957/4000] best acc:tensor([0.9722], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713387489318848, 'Val/mean miou_metric': 0.9524404406547546, 'Val/mean f1': 0.9732804298400879, 'Val/mean precision': 0.9689480662345886, 'Val/mean recall': 0.9776517152786255, 'Val/mean hd95_metric': 5.6958489418029785} +Epoch [958/4000] Training [1/16] Loss: 0.01168 +Epoch [958/4000] Training [2/16] Loss: 0.01554 +Epoch [958/4000] Training [3/16] Loss: 0.00942 +Epoch [958/4000] Training [4/16] Loss: 0.00901 +Epoch [958/4000] Training [5/16] Loss: 0.01530 +Epoch [958/4000] Training [6/16] Loss: 0.01006 +Epoch [958/4000] Training [7/16] Loss: 0.01000 +Epoch [958/4000] Training [8/16] Loss: 0.01306 +Epoch [958/4000] Training [9/16] Loss: 0.01679 +Epoch [958/4000] Training [10/16] Loss: 0.00970 +Epoch [958/4000] Training [11/16] Loss: 0.00986 +Epoch [958/4000] Training [12/16] Loss: 0.01318 +Epoch [958/4000] Training [13/16] Loss: 0.00927 +Epoch [958/4000] Training [14/16] Loss: 0.01297 +Epoch [958/4000] Training [15/16] Loss: 0.01184 +Epoch [958/4000] Training [16/16] Loss: 0.01163 +Epoch [958/4000] Training metric {'Train/mean dice_metric': 0.9925406575202942, 'Train/mean miou_metric': 0.9849750995635986, 'Train/mean f1': 0.9892018437385559, 'Train/mean precision': 0.9847555756568909, 'Train/mean recall': 0.9936884641647339, 'Train/mean hd95_metric': 1.117922306060791} +Epoch [958/4000] Validation [1/4] Loss: 0.18446 focal_loss 0.11858 dice_loss 0.06588 +Epoch [958/4000] Validation [2/4] Loss: 0.22581 focal_loss 0.11284 dice_loss 0.11297 +Epoch [958/4000] Validation [3/4] Loss: 0.13062 focal_loss 0.06813 dice_loss 0.06249 +Epoch [958/4000] Validation [4/4] Loss: 0.27945 focal_loss 0.16056 dice_loss 0.11889 +Epoch [958/4000] Validation metric {'Val/mean dice_metric': 0.9724571108818054, 'Val/mean miou_metric': 0.9538758993148804, 'Val/mean f1': 0.9747675657272339, 'Val/mean precision': 0.9712253212928772, 'Val/mean recall': 0.9783359169960022, 'Val/mean hd95_metric': 5.360644340515137} +Cheakpoint... +Epoch [958/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724571108818054, 'Val/mean miou_metric': 0.9538758993148804, 'Val/mean f1': 0.9747675657272339, 'Val/mean precision': 0.9712253212928772, 'Val/mean recall': 0.9783359169960022, 'Val/mean hd95_metric': 5.360644340515137} +Epoch [959/4000] Training [1/16] Loss: 0.01061 +Epoch [959/4000] Training [2/16] Loss: 0.01142 +Epoch [959/4000] Training [3/16] Loss: 0.00834 +Epoch [959/4000] Training [4/16] Loss: 0.01002 +Epoch [959/4000] Training [5/16] Loss: 0.01178 +Epoch [959/4000] Training [6/16] Loss: 0.00831 +Epoch [959/4000] Training [7/16] Loss: 0.01333 +Epoch [959/4000] Training [8/16] Loss: 0.01498 +Epoch [959/4000] Training [9/16] Loss: 0.01358 +Epoch [959/4000] Training [10/16] Loss: 0.01290 +Epoch [959/4000] Training [11/16] Loss: 0.01048 +Epoch [959/4000] Training [12/16] Loss: 0.01386 +Epoch [959/4000] Training [13/16] Loss: 0.01194 +Epoch [959/4000] Training [14/16] Loss: 0.01208 +Epoch [959/4000] Training [15/16] Loss: 0.01453 +Epoch [959/4000] Training [16/16] Loss: 0.01009 +Epoch [959/4000] Training metric {'Train/mean dice_metric': 0.9906303882598877, 'Train/mean miou_metric': 0.9818692207336426, 'Train/mean f1': 0.9880542159080505, 'Train/mean precision': 0.9834424257278442, 'Train/mean recall': 0.9927094578742981, 'Train/mean hd95_metric': 1.6890084743499756} +Epoch [959/4000] Validation [1/4] Loss: 0.29447 focal_loss 0.19343 dice_loss 0.10103 +Epoch [959/4000] Validation [2/4] Loss: 0.36869 focal_loss 0.17054 dice_loss 0.19814 +Epoch [959/4000] Validation [3/4] Loss: 0.14766 focal_loss 0.08314 dice_loss 0.06452 +Epoch [959/4000] Validation [4/4] Loss: 0.23802 focal_loss 0.13219 dice_loss 0.10584 +Epoch [959/4000] Validation metric {'Val/mean dice_metric': 0.9679514169692993, 'Val/mean miou_metric': 0.9469860196113586, 'Val/mean f1': 0.9699053168296814, 'Val/mean precision': 0.9699094295501709, 'Val/mean recall': 0.9699010252952576, 'Val/mean hd95_metric': 6.636849403381348} +Cheakpoint... +Epoch [959/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679514169692993, 'Val/mean miou_metric': 0.9469860196113586, 'Val/mean f1': 0.9699053168296814, 'Val/mean precision': 0.9699094295501709, 'Val/mean recall': 0.9699010252952576, 'Val/mean hd95_metric': 6.636849403381348} +Epoch [960/4000] Training [1/16] Loss: 0.00996 +Epoch [960/4000] Training [2/16] Loss: 0.01097 +Epoch [960/4000] Training [3/16] Loss: 0.01337 +Epoch [960/4000] Training [4/16] Loss: 0.01045 +Epoch [960/4000] Training [5/16] Loss: 0.01334 +Epoch [960/4000] Training [6/16] Loss: 0.01195 +Epoch [960/4000] Training [7/16] Loss: 0.01065 +Epoch [960/4000] Training [8/16] Loss: 0.01331 +Epoch [960/4000] Training [9/16] Loss: 0.01073 +Epoch [960/4000] Training [10/16] Loss: 0.01249 +Epoch [960/4000] Training [11/16] Loss: 0.01084 +Epoch [960/4000] Training [12/16] Loss: 0.01185 +Epoch [960/4000] Training [13/16] Loss: 0.01286 +Epoch [960/4000] Training [14/16] Loss: 0.00830 +Epoch [960/4000] Training [15/16] Loss: 0.01022 +Epoch [960/4000] Training [16/16] Loss: 0.01763 +Epoch [960/4000] Training metric {'Train/mean dice_metric': 0.9916020631790161, 'Train/mean miou_metric': 0.9833944439888, 'Train/mean f1': 0.9882687926292419, 'Train/mean precision': 0.9840492010116577, 'Train/mean recall': 0.9925247430801392, 'Train/mean hd95_metric': 1.3646916151046753} +Epoch [960/4000] Validation [1/4] Loss: 0.25847 focal_loss 0.15577 dice_loss 0.10270 +Epoch [960/4000] Validation [2/4] Loss: 0.23367 focal_loss 0.10286 dice_loss 0.13080 +Epoch [960/4000] Validation [3/4] Loss: 0.19094 focal_loss 0.10694 dice_loss 0.08400 +Epoch [960/4000] Validation [4/4] Loss: 0.27925 focal_loss 0.15538 dice_loss 0.12387 +Epoch [960/4000] Validation metric {'Val/mean dice_metric': 0.9688620567321777, 'Val/mean miou_metric': 0.9483078122138977, 'Val/mean f1': 0.9703550934791565, 'Val/mean precision': 0.9701460003852844, 'Val/mean recall': 0.9705643653869629, 'Val/mean hd95_metric': 6.014873504638672} +Cheakpoint... +Epoch [960/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688620567321777, 'Val/mean miou_metric': 0.9483078122138977, 'Val/mean f1': 0.9703550934791565, 'Val/mean precision': 0.9701460003852844, 'Val/mean recall': 0.9705643653869629, 'Val/mean hd95_metric': 6.014873504638672} +Epoch [961/4000] Training [1/16] Loss: 0.00897 +Epoch [961/4000] Training [2/16] Loss: 0.01392 +Epoch [961/4000] Training [3/16] Loss: 0.00936 +Epoch [961/4000] Training [4/16] Loss: 0.01065 +Epoch [961/4000] Training [5/16] Loss: 0.01443 +Epoch [961/4000] Training [6/16] Loss: 0.01205 +Epoch [961/4000] Training [7/16] Loss: 0.01005 +Epoch [961/4000] Training [8/16] Loss: 0.02420 +Epoch [961/4000] Training [9/16] Loss: 0.00944 +Epoch [961/4000] Training [10/16] Loss: 0.01222 +Epoch [961/4000] Training [11/16] Loss: 0.00973 +Epoch [961/4000] Training [12/16] Loss: 0.00953 +Epoch [961/4000] Training [13/16] Loss: 0.01434 +Epoch [961/4000] Training [14/16] Loss: 0.01424 +Epoch [961/4000] Training [15/16] Loss: 0.01097 +Epoch [961/4000] Training [16/16] Loss: 0.01279 +Epoch [961/4000] Training metric {'Train/mean dice_metric': 0.9918869733810425, 'Train/mean miou_metric': 0.9836831092834473, 'Train/mean f1': 0.9878057241439819, 'Train/mean precision': 0.982966959476471, 'Train/mean recall': 0.9926922917366028, 'Train/mean hd95_metric': 1.229161024093628} +Epoch [961/4000] Validation [1/4] Loss: 0.15389 focal_loss 0.09142 dice_loss 0.06246 +Epoch [961/4000] Validation [2/4] Loss: 0.20866 focal_loss 0.08514 dice_loss 0.12352 +Epoch [961/4000] Validation [3/4] Loss: 0.20968 focal_loss 0.11785 dice_loss 0.09184 +Epoch [961/4000] Validation [4/4] Loss: 0.32116 focal_loss 0.18510 dice_loss 0.13606 +Epoch [961/4000] Validation metric {'Val/mean dice_metric': 0.9690931439399719, 'Val/mean miou_metric': 0.9487239718437195, 'Val/mean f1': 0.9716168642044067, 'Val/mean precision': 0.9640100002288818, 'Val/mean recall': 0.9793448448181152, 'Val/mean hd95_metric': 7.451111793518066} +Cheakpoint... +Epoch [961/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690931439399719, 'Val/mean miou_metric': 0.9487239718437195, 'Val/mean f1': 0.9716168642044067, 'Val/mean precision': 0.9640100002288818, 'Val/mean recall': 0.9793448448181152, 'Val/mean hd95_metric': 7.451111793518066} +Epoch [962/4000] Training [1/16] Loss: 0.01259 +Epoch [962/4000] Training [2/16] Loss: 0.01601 +Epoch [962/4000] Training [3/16] Loss: 0.02270 +Epoch [962/4000] Training [4/16] Loss: 0.02237 +Epoch [962/4000] Training [5/16] Loss: 0.01453 +Epoch [962/4000] Training [6/16] Loss: 0.01317 +Epoch [962/4000] Training [7/16] Loss: 0.01322 +Epoch [962/4000] Training [8/16] Loss: 0.01287 +Epoch [962/4000] Training [9/16] Loss: 0.01065 +Epoch [962/4000] Training [10/16] Loss: 0.01287 +Epoch [962/4000] Training [11/16] Loss: 0.01062 +Epoch [962/4000] Training [12/16] Loss: 0.01242 +Epoch [962/4000] Training [13/16] Loss: 0.01427 +Epoch [962/4000] Training [14/16] Loss: 0.00813 +Epoch [962/4000] Training [15/16] Loss: 0.01212 +Epoch [962/4000] Training [16/16] Loss: 0.00890 +Epoch [962/4000] Training metric {'Train/mean dice_metric': 0.9909830093383789, 'Train/mean miou_metric': 0.9819566607475281, 'Train/mean f1': 0.9880000948905945, 'Train/mean precision': 0.983356237411499, 'Train/mean recall': 0.992688000202179, 'Train/mean hd95_metric': 1.8368576765060425} +Epoch [962/4000] Validation [1/4] Loss: 0.17547 focal_loss 0.10865 dice_loss 0.06682 +Epoch [962/4000] Validation [2/4] Loss: 0.20107 focal_loss 0.09011 dice_loss 0.11097 +Epoch [962/4000] Validation [3/4] Loss: 0.25617 focal_loss 0.16041 dice_loss 0.09576 +Epoch [962/4000] Validation [4/4] Loss: 0.26878 focal_loss 0.13674 dice_loss 0.13204 +Epoch [962/4000] Validation metric {'Val/mean dice_metric': 0.9709724187850952, 'Val/mean miou_metric': 0.9500743746757507, 'Val/mean f1': 0.9722694158554077, 'Val/mean precision': 0.9664037227630615, 'Val/mean recall': 0.9782068133354187, 'Val/mean hd95_metric': 7.158023834228516} +Cheakpoint... +Epoch [962/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709724187850952, 'Val/mean miou_metric': 0.9500743746757507, 'Val/mean f1': 0.9722694158554077, 'Val/mean precision': 0.9664037227630615, 'Val/mean recall': 0.9782068133354187, 'Val/mean hd95_metric': 7.158023834228516} +Epoch [963/4000] Training [1/16] Loss: 0.00891 +Epoch [963/4000] Training [2/16] Loss: 0.01548 +Epoch [963/4000] Training [3/16] Loss: 0.01241 +Epoch [963/4000] Training [4/16] Loss: 0.01325 +Epoch [963/4000] Training [5/16] Loss: 0.01180 +Epoch [963/4000] Training [6/16] Loss: 0.00923 +Epoch [963/4000] Training [7/16] Loss: 0.01354 +Epoch [963/4000] Training [8/16] Loss: 0.00993 +Epoch [963/4000] Training [9/16] Loss: 0.01013 +Epoch [963/4000] Training [10/16] Loss: 0.01146 +Epoch [963/4000] Training [11/16] Loss: 0.00811 +Epoch [963/4000] Training [12/16] Loss: 0.01031 +Epoch [963/4000] Training [13/16] Loss: 0.01110 +Epoch [963/4000] Training [14/16] Loss: 0.01311 +Epoch [963/4000] Training [15/16] Loss: 0.01714 +Epoch [963/4000] Training [16/16] Loss: 0.01179 +Epoch [963/4000] Training metric {'Train/mean dice_metric': 0.9910705089569092, 'Train/mean miou_metric': 0.9822718501091003, 'Train/mean f1': 0.9879844784736633, 'Train/mean precision': 0.9835302233695984, 'Train/mean recall': 0.9924792647361755, 'Train/mean hd95_metric': 1.7641360759735107} +Epoch [963/4000] Validation [1/4] Loss: 0.15493 focal_loss 0.09976 dice_loss 0.05517 +Epoch [963/4000] Validation [2/4] Loss: 0.26048 focal_loss 0.11798 dice_loss 0.14250 +Epoch [963/4000] Validation [3/4] Loss: 0.25985 focal_loss 0.16666 dice_loss 0.09319 +Epoch [963/4000] Validation [4/4] Loss: 0.22332 focal_loss 0.09935 dice_loss 0.12397 +Epoch [963/4000] Validation metric {'Val/mean dice_metric': 0.9700237512588501, 'Val/mean miou_metric': 0.9496603012084961, 'Val/mean f1': 0.9723193645477295, 'Val/mean precision': 0.9653418660163879, 'Val/mean recall': 0.9793984889984131, 'Val/mean hd95_metric': 6.911669731140137} +Cheakpoint... +Epoch [963/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700237512588501, 'Val/mean miou_metric': 0.9496603012084961, 'Val/mean f1': 0.9723193645477295, 'Val/mean precision': 0.9653418660163879, 'Val/mean recall': 0.9793984889984131, 'Val/mean hd95_metric': 6.911669731140137} +Epoch [964/4000] Training [1/16] Loss: 0.00831 +Epoch [964/4000] Training [2/16] Loss: 0.01237 +Epoch [964/4000] Training [3/16] Loss: 0.01042 +Epoch [964/4000] Training [4/16] Loss: 0.00996 +Epoch [964/4000] Training [5/16] Loss: 0.01211 +Epoch [964/4000] Training [6/16] Loss: 0.01036 +Epoch [964/4000] Training [7/16] Loss: 0.01187 +Epoch [964/4000] Training [8/16] Loss: 0.01121 +Epoch [964/4000] Training [9/16] Loss: 0.00909 +Epoch [964/4000] Training [10/16] Loss: 0.00846 +Epoch [964/4000] Training [11/16] Loss: 0.01337 +Epoch [964/4000] Training [12/16] Loss: 0.01001 +Epoch [964/4000] Training [13/16] Loss: 0.00904 +Epoch [964/4000] Training [14/16] Loss: 0.01118 +Epoch [964/4000] Training [15/16] Loss: 0.01107 +Epoch [964/4000] Training [16/16] Loss: 0.01357 +Epoch [964/4000] Training metric {'Train/mean dice_metric': 0.9925374984741211, 'Train/mean miou_metric': 0.9849640130996704, 'Train/mean f1': 0.9890753030776978, 'Train/mean precision': 0.984283983707428, 'Train/mean recall': 0.993913471698761, 'Train/mean hd95_metric': 1.1768320798873901} +Epoch [964/4000] Validation [1/4] Loss: 0.14821 focal_loss 0.09021 dice_loss 0.05800 +Epoch [964/4000] Validation [2/4] Loss: 0.16914 focal_loss 0.07736 dice_loss 0.09177 +Epoch [964/4000] Validation [3/4] Loss: 0.22418 focal_loss 0.12945 dice_loss 0.09473 +Epoch [964/4000] Validation [4/4] Loss: 0.30817 focal_loss 0.17783 dice_loss 0.13034 +Epoch [964/4000] Validation metric {'Val/mean dice_metric': 0.9713985323905945, 'Val/mean miou_metric': 0.9520865678787231, 'Val/mean f1': 0.9726743698120117, 'Val/mean precision': 0.9650299549102783, 'Val/mean recall': 0.9804409146308899, 'Val/mean hd95_metric': 6.639227390289307} +Cheakpoint... +Epoch [964/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713985323905945, 'Val/mean miou_metric': 0.9520865678787231, 'Val/mean f1': 0.9726743698120117, 'Val/mean precision': 0.9650299549102783, 'Val/mean recall': 0.9804409146308899, 'Val/mean hd95_metric': 6.639227390289307} +Epoch [965/4000] Training [1/16] Loss: 0.01718 +Epoch [965/4000] Training [2/16] Loss: 0.01209 +Epoch [965/4000] Training [3/16] Loss: 0.01063 +Epoch [965/4000] Training [4/16] Loss: 0.00851 +Epoch [965/4000] Training [5/16] Loss: 0.01068 +Epoch [965/4000] Training [6/16] Loss: 0.01272 +Epoch [965/4000] Training [7/16] Loss: 0.00960 +Epoch [965/4000] Training [8/16] Loss: 0.01014 +Epoch [965/4000] Training [9/16] Loss: 0.00973 +Epoch [965/4000] Training [10/16] Loss: 0.01046 +Epoch [965/4000] Training [11/16] Loss: 0.01113 +Epoch [965/4000] Training [12/16] Loss: 0.00975 +Epoch [965/4000] Training [13/16] Loss: 0.01330 +Epoch [965/4000] Training [14/16] Loss: 0.01238 +Epoch [965/4000] Training [15/16] Loss: 0.00940 +Epoch [965/4000] Training [16/16] Loss: 0.01075 +Epoch [965/4000] Training metric {'Train/mean dice_metric': 0.9926074743270874, 'Train/mean miou_metric': 0.9850802421569824, 'Train/mean f1': 0.9891539216041565, 'Train/mean precision': 0.9847715497016907, 'Train/mean recall': 0.9935755133628845, 'Train/mean hd95_metric': 1.1084398031234741} +Epoch [965/4000] Validation [1/4] Loss: 0.18123 focal_loss 0.11799 dice_loss 0.06324 +Epoch [965/4000] Validation [2/4] Loss: 0.18037 focal_loss 0.08056 dice_loss 0.09981 +Epoch [965/4000] Validation [3/4] Loss: 0.21047 focal_loss 0.11150 dice_loss 0.09897 +Epoch [965/4000] Validation [4/4] Loss: 0.28545 focal_loss 0.17412 dice_loss 0.11133 +Epoch [965/4000] Validation metric {'Val/mean dice_metric': 0.9715865850448608, 'Val/mean miou_metric': 0.9523124694824219, 'Val/mean f1': 0.9736928343772888, 'Val/mean precision': 0.9680933356285095, 'Val/mean recall': 0.9793575406074524, 'Val/mean hd95_metric': 5.900623321533203} +Cheakpoint... +Epoch [965/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715865850448608, 'Val/mean miou_metric': 0.9523124694824219, 'Val/mean f1': 0.9736928343772888, 'Val/mean precision': 0.9680933356285095, 'Val/mean recall': 0.9793575406074524, 'Val/mean hd95_metric': 5.900623321533203} +Epoch [966/4000] Training [1/16] Loss: 0.01439 +Epoch [966/4000] Training [2/16] Loss: 0.01086 +Epoch [966/4000] Training [3/16] Loss: 0.01042 +Epoch [966/4000] Training [4/16] Loss: 0.01698 +Epoch [966/4000] Training [5/16] Loss: 0.01109 +Epoch [966/4000] Training [6/16] Loss: 0.01076 +Epoch [966/4000] Training [7/16] Loss: 0.00975 +Epoch [966/4000] Training [8/16] Loss: 0.01383 +Epoch [966/4000] Training [9/16] Loss: 0.00988 +Epoch [966/4000] Training [10/16] Loss: 0.01305 +Epoch [966/4000] Training [11/16] Loss: 0.01050 +Epoch [966/4000] Training [12/16] Loss: 0.01763 +Epoch [966/4000] Training [13/16] Loss: 0.00914 +Epoch [966/4000] Training [14/16] Loss: 0.01291 +Epoch [966/4000] Training [15/16] Loss: 0.01183 +Epoch [966/4000] Training [16/16] Loss: 0.01228 +Epoch [966/4000] Training metric {'Train/mean dice_metric': 0.9910954833030701, 'Train/mean miou_metric': 0.9823917150497437, 'Train/mean f1': 0.9883347749710083, 'Train/mean precision': 0.983708381652832, 'Train/mean recall': 0.9930048584938049, 'Train/mean hd95_metric': 1.7899177074432373} +Epoch [966/4000] Validation [1/4] Loss: 0.18827 focal_loss 0.12497 dice_loss 0.06329 +Epoch [966/4000] Validation [2/4] Loss: 0.32936 focal_loss 0.16370 dice_loss 0.16566 +Epoch [966/4000] Validation [3/4] Loss: 0.27632 focal_loss 0.18101 dice_loss 0.09530 +Epoch [966/4000] Validation [4/4] Loss: 0.26995 focal_loss 0.14541 dice_loss 0.12453 +Epoch [966/4000] Validation metric {'Val/mean dice_metric': 0.968736469745636, 'Val/mean miou_metric': 0.9483224749565125, 'Val/mean f1': 0.9715151786804199, 'Val/mean precision': 0.9656095504760742, 'Val/mean recall': 0.977493405342102, 'Val/mean hd95_metric': 7.050799369812012} +Cheakpoint... +Epoch [966/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968736469745636, 'Val/mean miou_metric': 0.9483224749565125, 'Val/mean f1': 0.9715151786804199, 'Val/mean precision': 0.9656095504760742, 'Val/mean recall': 0.977493405342102, 'Val/mean hd95_metric': 7.050799369812012} +Epoch [967/4000] Training [1/16] Loss: 0.00878 +Epoch [967/4000] Training [2/16] Loss: 0.00967 +Epoch [967/4000] Training [3/16] Loss: 0.01043 +Epoch [967/4000] Training [4/16] Loss: 0.01063 +Epoch [967/4000] Training [5/16] Loss: 0.01219 +Epoch [967/4000] Training [6/16] Loss: 0.01645 +Epoch [967/4000] Training [7/16] Loss: 0.01036 +Epoch [967/4000] Training [8/16] Loss: 0.01374 +Epoch [967/4000] Training [9/16] Loss: 0.00900 +Epoch [967/4000] Training [10/16] Loss: 0.01317 +Epoch [967/4000] Training [11/16] Loss: 0.01056 +Epoch [967/4000] Training [12/16] Loss: 0.01108 +Epoch [967/4000] Training [13/16] Loss: 0.00944 +Epoch [967/4000] Training [14/16] Loss: 0.01378 +Epoch [967/4000] Training [15/16] Loss: 0.01089 +Epoch [967/4000] Training [16/16] Loss: 0.00900 +Epoch [967/4000] Training metric {'Train/mean dice_metric': 0.9924551248550415, 'Train/mean miou_metric': 0.9847913980484009, 'Train/mean f1': 0.9888608455657959, 'Train/mean precision': 0.9841126799583435, 'Train/mean recall': 0.9936550855636597, 'Train/mean hd95_metric': 1.2197468280792236} +Epoch [967/4000] Validation [1/4] Loss: 0.16804 focal_loss 0.11256 dice_loss 0.05549 +Epoch [967/4000] Validation [2/4] Loss: 0.38950 focal_loss 0.21138 dice_loss 0.17812 +Epoch [967/4000] Validation [3/4] Loss: 0.24703 focal_loss 0.15635 dice_loss 0.09068 +Epoch [967/4000] Validation [4/4] Loss: 0.29769 focal_loss 0.15998 dice_loss 0.13771 +Epoch [967/4000] Validation metric {'Val/mean dice_metric': 0.9715433120727539, 'Val/mean miou_metric': 0.9527182579040527, 'Val/mean f1': 0.9738599061965942, 'Val/mean precision': 0.9704483151435852, 'Val/mean recall': 0.9772953987121582, 'Val/mean hd95_metric': 5.7742228507995605} +Cheakpoint... +Epoch [967/4000] best acc:tensor([0.9725], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715433120727539, 'Val/mean miou_metric': 0.9527182579040527, 'Val/mean f1': 0.9738599061965942, 'Val/mean precision': 0.9704483151435852, 'Val/mean recall': 0.9772953987121582, 'Val/mean hd95_metric': 5.7742228507995605} +Epoch [968/4000] Training [1/16] Loss: 0.00863 +Epoch [968/4000] Training [2/16] Loss: 0.00991 +Epoch [968/4000] Training [3/16] Loss: 0.01102 +Epoch [968/4000] Training [4/16] Loss: 0.00844 +Epoch [968/4000] Training [5/16] Loss: 0.01726 +Epoch [968/4000] Training [6/16] Loss: 0.01054 +Epoch [968/4000] Training [7/16] Loss: 0.01322 +Epoch [968/4000] Training [8/16] Loss: 0.01200 +Epoch [968/4000] Training [9/16] Loss: 0.00821 +Epoch [968/4000] Training [10/16] Loss: 0.00932 +Epoch [968/4000] Training [11/16] Loss: 0.00980 +Epoch [968/4000] Training [12/16] Loss: 0.01552 +Epoch [968/4000] Training [13/16] Loss: 0.01292 +Epoch [968/4000] Training [14/16] Loss: 0.00938 +Epoch [968/4000] Training [15/16] Loss: 0.01278 +Epoch [968/4000] Training [16/16] Loss: 0.01208 +Epoch [968/4000] Training metric {'Train/mean dice_metric': 0.992279052734375, 'Train/mean miou_metric': 0.9844650030136108, 'Train/mean f1': 0.9890321493148804, 'Train/mean precision': 0.9846020340919495, 'Train/mean recall': 0.9935022592544556, 'Train/mean hd95_metric': 1.1531583070755005} +Epoch [968/4000] Validation [1/4] Loss: 0.15929 focal_loss 0.10613 dice_loss 0.05316 +Epoch [968/4000] Validation [2/4] Loss: 0.23219 focal_loss 0.09784 dice_loss 0.13435 +Epoch [968/4000] Validation [3/4] Loss: 0.23058 focal_loss 0.14189 dice_loss 0.08869 +Epoch [968/4000] Validation [4/4] Loss: 0.28528 focal_loss 0.16013 dice_loss 0.12515 +Epoch [968/4000] Validation metric {'Val/mean dice_metric': 0.9726158380508423, 'Val/mean miou_metric': 0.9536163210868835, 'Val/mean f1': 0.975001871585846, 'Val/mean precision': 0.9697921276092529, 'Val/mean recall': 0.9802678823471069, 'Val/mean hd95_metric': 5.519521236419678} +Cheakpoint... +Epoch [968/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726158380508423, 'Val/mean miou_metric': 0.9536163210868835, 'Val/mean f1': 0.975001871585846, 'Val/mean precision': 0.9697921276092529, 'Val/mean recall': 0.9802678823471069, 'Val/mean hd95_metric': 5.519521236419678} +Epoch [969/4000] Training [1/16] Loss: 0.00991 +Epoch [969/4000] Training [2/16] Loss: 0.01630 +Epoch [969/4000] Training [3/16] Loss: 0.00976 +Epoch [969/4000] Training [4/16] Loss: 0.00828 +Epoch [969/4000] Training [5/16] Loss: 0.01157 +Epoch [969/4000] Training [6/16] Loss: 0.01241 +Epoch [969/4000] Training [7/16] Loss: 0.01813 +Epoch [969/4000] Training [8/16] Loss: 0.01243 +Epoch [969/4000] Training [9/16] Loss: 0.01089 +Epoch [969/4000] Training [10/16] Loss: 0.00964 +Epoch [969/4000] Training [11/16] Loss: 0.01114 +Epoch [969/4000] Training [12/16] Loss: 0.01270 +Epoch [969/4000] Training [13/16] Loss: 0.01021 +Epoch [969/4000] Training [14/16] Loss: 0.01017 +Epoch [969/4000] Training [15/16] Loss: 0.01199 +Epoch [969/4000] Training [16/16] Loss: 0.00901 +Epoch [969/4000] Training metric {'Train/mean dice_metric': 0.9922534227371216, 'Train/mean miou_metric': 0.9844063520431519, 'Train/mean f1': 0.9889944195747375, 'Train/mean precision': 0.9842060208320618, 'Train/mean recall': 0.9938296675682068, 'Train/mean hd95_metric': 1.143627405166626} +Epoch [969/4000] Validation [1/4] Loss: 0.16297 focal_loss 0.10116 dice_loss 0.06181 +Epoch [969/4000] Validation [2/4] Loss: 0.39887 focal_loss 0.22871 dice_loss 0.17016 +Epoch [969/4000] Validation [3/4] Loss: 0.25017 focal_loss 0.15359 dice_loss 0.09657 +Epoch [969/4000] Validation [4/4] Loss: 0.24708 focal_loss 0.12329 dice_loss 0.12380 +Epoch [969/4000] Validation metric {'Val/mean dice_metric': 0.9717141389846802, 'Val/mean miou_metric': 0.9523285031318665, 'Val/mean f1': 0.9734901189804077, 'Val/mean precision': 0.9686552286148071, 'Val/mean recall': 0.9783735275268555, 'Val/mean hd95_metric': 6.556406497955322} +Cheakpoint... +Epoch [969/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717141389846802, 'Val/mean miou_metric': 0.9523285031318665, 'Val/mean f1': 0.9734901189804077, 'Val/mean precision': 0.9686552286148071, 'Val/mean recall': 0.9783735275268555, 'Val/mean hd95_metric': 6.556406497955322} +Epoch [970/4000] Training [1/16] Loss: 0.01223 +Epoch [970/4000] Training [2/16] Loss: 0.00782 +Epoch [970/4000] Training [3/16] Loss: 0.01824 +Epoch [970/4000] Training [4/16] Loss: 0.01494 +Epoch [970/4000] Training [5/16] Loss: 0.01207 +Epoch [970/4000] Training [6/16] Loss: 0.01163 +Epoch [970/4000] Training [7/16] Loss: 0.01348 +Epoch [970/4000] Training [8/16] Loss: 0.01346 +Epoch [970/4000] Training [9/16] Loss: 0.01396 +Epoch [970/4000] Training [10/16] Loss: 0.01228 +Epoch [970/4000] Training [11/16] Loss: 0.01105 +Epoch [970/4000] Training [12/16] Loss: 0.01114 +Epoch [970/4000] Training [13/16] Loss: 0.00996 +Epoch [970/4000] Training [14/16] Loss: 0.01271 +Epoch [970/4000] Training [15/16] Loss: 0.01322 +Epoch [970/4000] Training [16/16] Loss: 0.01288 +Epoch [970/4000] Training metric {'Train/mean dice_metric': 0.9914289712905884, 'Train/mean miou_metric': 0.9828258156776428, 'Train/mean f1': 0.9881316423416138, 'Train/mean precision': 0.9842787981033325, 'Train/mean recall': 0.9920147657394409, 'Train/mean hd95_metric': 1.4746888875961304} +Epoch [970/4000] Validation [1/4] Loss: 0.18949 focal_loss 0.12409 dice_loss 0.06540 +Epoch [970/4000] Validation [2/4] Loss: 0.40703 focal_loss 0.22181 dice_loss 0.18522 +Epoch [970/4000] Validation [3/4] Loss: 0.14922 focal_loss 0.08293 dice_loss 0.06629 +Epoch [970/4000] Validation [4/4] Loss: 0.24305 focal_loss 0.10859 dice_loss 0.13446 +Epoch [970/4000] Validation metric {'Val/mean dice_metric': 0.9710686802864075, 'Val/mean miou_metric': 0.9508857727050781, 'Val/mean f1': 0.9724913835525513, 'Val/mean precision': 0.9680519104003906, 'Val/mean recall': 0.9769718050956726, 'Val/mean hd95_metric': 6.589720726013184} +Cheakpoint... +Epoch [970/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710686802864075, 'Val/mean miou_metric': 0.9508857727050781, 'Val/mean f1': 0.9724913835525513, 'Val/mean precision': 0.9680519104003906, 'Val/mean recall': 0.9769718050956726, 'Val/mean hd95_metric': 6.589720726013184} +Epoch [971/4000] Training [1/16] Loss: 0.01612 +Epoch [971/4000] Training [2/16] Loss: 0.01699 +Epoch [971/4000] Training [3/16] Loss: 0.01236 +Epoch [971/4000] Training [4/16] Loss: 0.01231 +Epoch [971/4000] Training [5/16] Loss: 0.01153 +Epoch [971/4000] Training [6/16] Loss: 0.04953 +Epoch [971/4000] Training [7/16] Loss: 0.01315 +Epoch [971/4000] Training [8/16] Loss: 0.00916 +Epoch [971/4000] Training [9/16] Loss: 0.01235 +Epoch [971/4000] Training [10/16] Loss: 0.01533 +Epoch [971/4000] Training [11/16] Loss: 0.01483 +Epoch [971/4000] Training [12/16] Loss: 0.01820 +Epoch [971/4000] Training [13/16] Loss: 0.01062 +Epoch [971/4000] Training [14/16] Loss: 0.01311 +Epoch [971/4000] Training [15/16] Loss: 0.01162 +Epoch [971/4000] Training [16/16] Loss: 0.01275 +Epoch [971/4000] Training metric {'Train/mean dice_metric': 0.990706205368042, 'Train/mean miou_metric': 0.9814109802246094, 'Train/mean f1': 0.9872370958328247, 'Train/mean precision': 0.9824075698852539, 'Train/mean recall': 0.9921143651008606, 'Train/mean hd95_metric': 1.7970067262649536} +Epoch [971/4000] Validation [1/4] Loss: 0.15998 focal_loss 0.10165 dice_loss 0.05833 +Epoch [971/4000] Validation [2/4] Loss: 0.29820 focal_loss 0.17576 dice_loss 0.12244 +Epoch [971/4000] Validation [3/4] Loss: 0.29345 focal_loss 0.19124 dice_loss 0.10220 +Epoch [971/4000] Validation [4/4] Loss: 0.28545 focal_loss 0.16038 dice_loss 0.12507 +Epoch [971/4000] Validation metric {'Val/mean dice_metric': 0.9691215753555298, 'Val/mean miou_metric': 0.9484079480171204, 'Val/mean f1': 0.970378041267395, 'Val/mean precision': 0.9650399684906006, 'Val/mean recall': 0.975775420665741, 'Val/mean hd95_metric': 6.789888858795166} +Cheakpoint... +Epoch [971/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691215753555298, 'Val/mean miou_metric': 0.9484079480171204, 'Val/mean f1': 0.970378041267395, 'Val/mean precision': 0.9650399684906006, 'Val/mean recall': 0.975775420665741, 'Val/mean hd95_metric': 6.789888858795166} +Epoch [972/4000] Training [1/16] Loss: 0.01311 +Epoch [972/4000] Training [2/16] Loss: 0.00864 +Epoch [972/4000] Training [3/16] Loss: 0.01123 +Epoch [972/4000] Training [4/16] Loss: 0.01316 +Epoch [972/4000] Training [5/16] Loss: 0.01057 +Epoch [972/4000] Training [6/16] Loss: 0.01101 +Epoch [972/4000] Training [7/16] Loss: 0.01134 +Epoch [972/4000] Training [8/16] Loss: 0.01672 +Epoch [972/4000] Training [9/16] Loss: 0.01804 +Epoch [972/4000] Training [10/16] Loss: 0.01142 +Epoch [972/4000] Training [11/16] Loss: 0.00904 +Epoch [972/4000] Training [12/16] Loss: 0.01459 +Epoch [972/4000] Training [13/16] Loss: 0.00984 +Epoch [972/4000] Training [14/16] Loss: 0.00987 +Epoch [972/4000] Training [15/16] Loss: 0.01275 +Epoch [972/4000] Training [16/16] Loss: 0.00971 +Epoch [972/4000] Training metric {'Train/mean dice_metric': 0.9898144006729126, 'Train/mean miou_metric': 0.9815096259117126, 'Train/mean f1': 0.9878831505775452, 'Train/mean precision': 0.9832736253738403, 'Train/mean recall': 0.9925361275672913, 'Train/mean hd95_metric': 1.6548073291778564} +Epoch [972/4000] Validation [1/4] Loss: 0.35197 focal_loss 0.22367 dice_loss 0.12831 +Epoch [972/4000] Validation [2/4] Loss: 0.42282 focal_loss 0.19357 dice_loss 0.22925 +Epoch [972/4000] Validation [3/4] Loss: 0.16251 focal_loss 0.08019 dice_loss 0.08232 +Epoch [972/4000] Validation [4/4] Loss: 0.21023 focal_loss 0.11853 dice_loss 0.09170 +Epoch [972/4000] Validation metric {'Val/mean dice_metric': 0.9649783372879028, 'Val/mean miou_metric': 0.9449948072433472, 'Val/mean f1': 0.9697036147117615, 'Val/mean precision': 0.9713336825370789, 'Val/mean recall': 0.9680788516998291, 'Val/mean hd95_metric': 6.212568759918213} +Cheakpoint... +Epoch [972/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649783372879028, 'Val/mean miou_metric': 0.9449948072433472, 'Val/mean f1': 0.9697036147117615, 'Val/mean precision': 0.9713336825370789, 'Val/mean recall': 0.9680788516998291, 'Val/mean hd95_metric': 6.212568759918213} +Epoch [973/4000] Training [1/16] Loss: 0.01381 +Epoch [973/4000] Training [2/16] Loss: 0.01075 +Epoch [973/4000] Training [3/16] Loss: 0.01257 +Epoch [973/4000] Training [4/16] Loss: 0.01018 +Epoch [973/4000] Training [5/16] Loss: 0.01991 +Epoch [973/4000] Training [6/16] Loss: 0.00906 +Epoch [973/4000] Training [7/16] Loss: 0.01271 +Epoch [973/4000] Training [8/16] Loss: 0.01558 +Epoch [973/4000] Training [9/16] Loss: 0.01181 +Epoch [973/4000] Training [10/16] Loss: 0.01289 +Epoch [973/4000] Training [11/16] Loss: 0.01003 +Epoch [973/4000] Training [12/16] Loss: 0.01019 +Epoch [973/4000] Training [13/16] Loss: 0.01116 +Epoch [973/4000] Training [14/16] Loss: 0.01325 +Epoch [973/4000] Training [15/16] Loss: 0.01026 +Epoch [973/4000] Training [16/16] Loss: 0.00906 +Epoch [973/4000] Training metric {'Train/mean dice_metric': 0.9918129444122314, 'Train/mean miou_metric': 0.9835518598556519, 'Train/mean f1': 0.9882939457893372, 'Train/mean precision': 0.983895480632782, 'Train/mean recall': 0.9927319288253784, 'Train/mean hd95_metric': 1.2605279684066772} +Epoch [973/4000] Validation [1/4] Loss: 0.13584 focal_loss 0.07242 dice_loss 0.06342 +Epoch [973/4000] Validation [2/4] Loss: 0.34138 focal_loss 0.17845 dice_loss 0.16293 +Epoch [973/4000] Validation [3/4] Loss: 0.22177 focal_loss 0.12608 dice_loss 0.09569 +Epoch [973/4000] Validation [4/4] Loss: 0.26047 focal_loss 0.12757 dice_loss 0.13290 +Epoch [973/4000] Validation metric {'Val/mean dice_metric': 0.9677009582519531, 'Val/mean miou_metric': 0.9470230937004089, 'Val/mean f1': 0.9712545871734619, 'Val/mean precision': 0.9711430072784424, 'Val/mean recall': 0.9713661670684814, 'Val/mean hd95_metric': 5.822321891784668} +Cheakpoint... +Epoch [973/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677009582519531, 'Val/mean miou_metric': 0.9470230937004089, 'Val/mean f1': 0.9712545871734619, 'Val/mean precision': 0.9711430072784424, 'Val/mean recall': 0.9713661670684814, 'Val/mean hd95_metric': 5.822321891784668} +Epoch [974/4000] Training [1/16] Loss: 0.01335 +Epoch [974/4000] Training [2/16] Loss: 0.01281 +Epoch [974/4000] Training [3/16] Loss: 0.01888 +Epoch [974/4000] Training [4/16] Loss: 0.01144 +Epoch [974/4000] Training [5/16] Loss: 0.01101 +Epoch [974/4000] Training [6/16] Loss: 0.01084 +Epoch [974/4000] Training [7/16] Loss: 0.00852 +Epoch [974/4000] Training [8/16] Loss: 0.00923 +Epoch [974/4000] Training [9/16] Loss: 0.01037 +Epoch [974/4000] Training [10/16] Loss: 0.01395 +Epoch [974/4000] Training [11/16] Loss: 0.01244 +Epoch [974/4000] Training [12/16] Loss: 0.01618 +Epoch [974/4000] Training [13/16] Loss: 0.01010 +Epoch [974/4000] Training [14/16] Loss: 0.01231 +Epoch [974/4000] Training [15/16] Loss: 0.01225 +Epoch [974/4000] Training [16/16] Loss: 0.01276 +Epoch [974/4000] Training metric {'Train/mean dice_metric': 0.9914299845695496, 'Train/mean miou_metric': 0.9828299283981323, 'Train/mean f1': 0.9880929589271545, 'Train/mean precision': 0.9834176898002625, 'Train/mean recall': 0.9928129315376282, 'Train/mean hd95_metric': 1.3289653062820435} +Epoch [974/4000] Validation [1/4] Loss: 0.24432 focal_loss 0.15572 dice_loss 0.08860 +Epoch [974/4000] Validation [2/4] Loss: 0.36685 focal_loss 0.19027 dice_loss 0.17658 +Epoch [974/4000] Validation [3/4] Loss: 0.27474 focal_loss 0.17582 dice_loss 0.09892 +Epoch [974/4000] Validation [4/4] Loss: 0.30165 focal_loss 0.17202 dice_loss 0.12963 +Epoch [974/4000] Validation metric {'Val/mean dice_metric': 0.966891884803772, 'Val/mean miou_metric': 0.9465001225471497, 'Val/mean f1': 0.9705700874328613, 'Val/mean precision': 0.9690669775009155, 'Val/mean recall': 0.9720779657363892, 'Val/mean hd95_metric': 5.721249580383301} +Cheakpoint... +Epoch [974/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966891884803772, 'Val/mean miou_metric': 0.9465001225471497, 'Val/mean f1': 0.9705700874328613, 'Val/mean precision': 0.9690669775009155, 'Val/mean recall': 0.9720779657363892, 'Val/mean hd95_metric': 5.721249580383301} +Epoch [975/4000] Training [1/16] Loss: 0.01004 +Epoch [975/4000] Training [2/16] Loss: 0.01532 +Epoch [975/4000] Training [3/16] Loss: 0.01178 +Epoch [975/4000] Training [4/16] Loss: 0.01170 +Epoch [975/4000] Training [5/16] Loss: 0.01191 +Epoch [975/4000] Training [6/16] Loss: 0.00861 +Epoch [975/4000] Training [7/16] Loss: 0.02240 +Epoch [975/4000] Training [8/16] Loss: 0.00938 +Epoch [975/4000] Training [9/16] Loss: 0.00958 +Epoch [975/4000] Training [10/16] Loss: 0.01901 +Epoch [975/4000] Training [11/16] Loss: 0.01003 +Epoch [975/4000] Training [12/16] Loss: 0.00826 +Epoch [975/4000] Training [13/16] Loss: 0.01317 +Epoch [975/4000] Training [14/16] Loss: 0.01147 +Epoch [975/4000] Training [15/16] Loss: 0.01247 +Epoch [975/4000] Training [16/16] Loss: 0.01722 +Epoch [975/4000] Training metric {'Train/mean dice_metric': 0.9916368722915649, 'Train/mean miou_metric': 0.9831944108009338, 'Train/mean f1': 0.987788736820221, 'Train/mean precision': 0.9826468229293823, 'Train/mean recall': 0.9929847121238708, 'Train/mean hd95_metric': 1.336722731590271} +Epoch [975/4000] Validation [1/4] Loss: 0.22379 focal_loss 0.14688 dice_loss 0.07690 +Epoch [975/4000] Validation [2/4] Loss: 0.32810 focal_loss 0.17791 dice_loss 0.15019 +Epoch [975/4000] Validation [3/4] Loss: 0.30769 focal_loss 0.19185 dice_loss 0.11584 +Epoch [975/4000] Validation [4/4] Loss: 0.35795 focal_loss 0.18057 dice_loss 0.17738 +Epoch [975/4000] Validation metric {'Val/mean dice_metric': 0.9629176259040833, 'Val/mean miou_metric': 0.9413393139839172, 'Val/mean f1': 0.9606975317001343, 'Val/mean precision': 0.9384717345237732, 'Val/mean recall': 0.9840016961097717, 'Val/mean hd95_metric': 9.288981437683105} +Cheakpoint... +Epoch [975/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9629], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629176259040833, 'Val/mean miou_metric': 0.9413393139839172, 'Val/mean f1': 0.9606975317001343, 'Val/mean precision': 0.9384717345237732, 'Val/mean recall': 0.9840016961097717, 'Val/mean hd95_metric': 9.288981437683105} +Epoch [976/4000] Training [1/16] Loss: 0.01212 +Epoch [976/4000] Training [2/16] Loss: 0.01104 +Epoch [976/4000] Training [3/16] Loss: 0.01147 +Epoch [976/4000] Training [4/16] Loss: 0.01475 +Epoch [976/4000] Training [5/16] Loss: 0.01250 +Epoch [976/4000] Training [6/16] Loss: 0.01000 +Epoch [976/4000] Training [7/16] Loss: 0.00952 +Epoch [976/4000] Training [8/16] Loss: 0.01149 +Epoch [976/4000] Training [9/16] Loss: 0.01215 +Epoch [976/4000] Training [10/16] Loss: 0.01640 +Epoch [976/4000] Training [11/16] Loss: 0.01170 +Epoch [976/4000] Training [12/16] Loss: 0.01575 +Epoch [976/4000] Training [13/16] Loss: 0.01226 +Epoch [976/4000] Training [14/16] Loss: 0.01350 +Epoch [976/4000] Training [15/16] Loss: 0.01119 +Epoch [976/4000] Training [16/16] Loss: 0.01987 +Epoch [976/4000] Training metric {'Train/mean dice_metric': 0.9912290573120117, 'Train/mean miou_metric': 0.982406497001648, 'Train/mean f1': 0.9879350662231445, 'Train/mean precision': 0.9837778806686401, 'Train/mean recall': 0.9921274781227112, 'Train/mean hd95_metric': 1.6454106569290161} +Epoch [976/4000] Validation [1/4] Loss: 0.16475 focal_loss 0.10210 dice_loss 0.06265 +Epoch [976/4000] Validation [2/4] Loss: 0.36804 focal_loss 0.18652 dice_loss 0.18152 +Epoch [976/4000] Validation [3/4] Loss: 0.28276 focal_loss 0.17570 dice_loss 0.10706 +Epoch [976/4000] Validation [4/4] Loss: 0.25665 focal_loss 0.14049 dice_loss 0.11616 +Epoch [976/4000] Validation metric {'Val/mean dice_metric': 0.9693683385848999, 'Val/mean miou_metric': 0.9485113024711609, 'Val/mean f1': 0.971590518951416, 'Val/mean precision': 0.9684979319572449, 'Val/mean recall': 0.9747030735015869, 'Val/mean hd95_metric': 6.113490104675293} +Cheakpoint... +Epoch [976/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693683385848999, 'Val/mean miou_metric': 0.9485113024711609, 'Val/mean f1': 0.971590518951416, 'Val/mean precision': 0.9684979319572449, 'Val/mean recall': 0.9747030735015869, 'Val/mean hd95_metric': 6.113490104675293} +Epoch [977/4000] Training [1/16] Loss: 0.01146 +Epoch [977/4000] Training [2/16] Loss: 0.01453 +Epoch [977/4000] Training [3/16] Loss: 0.01147 +Epoch [977/4000] Training [4/16] Loss: 0.01518 +Epoch [977/4000] Training [5/16] Loss: 0.00892 +Epoch [977/4000] Training [6/16] Loss: 0.00970 +Epoch [977/4000] Training [7/16] Loss: 0.04400 +Epoch [977/4000] Training [8/16] Loss: 0.01228 +Epoch [977/4000] Training [9/16] Loss: 0.01176 +Epoch [977/4000] Training [10/16] Loss: 0.01623 +Epoch [977/4000] Training [11/16] Loss: 0.01499 +Epoch [977/4000] Training [12/16] Loss: 0.01731 +Epoch [977/4000] Training [13/16] Loss: 0.01055 +Epoch [977/4000] Training [14/16] Loss: 0.01060 +Epoch [977/4000] Training [15/16] Loss: 0.01006 +Epoch [977/4000] Training [16/16] Loss: 0.01488 +Epoch [977/4000] Training metric {'Train/mean dice_metric': 0.9908143281936646, 'Train/mean miou_metric': 0.9817401170730591, 'Train/mean f1': 0.9876024723052979, 'Train/mean precision': 0.982900857925415, 'Train/mean recall': 0.9923492074012756, 'Train/mean hd95_metric': 1.4106991291046143} +Epoch [977/4000] Validation [1/4] Loss: 0.15378 focal_loss 0.09619 dice_loss 0.05760 +Epoch [977/4000] Validation [2/4] Loss: 0.65476 focal_loss 0.38407 dice_loss 0.27069 +Epoch [977/4000] Validation [3/4] Loss: 0.26318 focal_loss 0.16231 dice_loss 0.10087 +Epoch [977/4000] Validation [4/4] Loss: 0.39940 focal_loss 0.25207 dice_loss 0.14733 +Epoch [977/4000] Validation metric {'Val/mean dice_metric': 0.9673219919204712, 'Val/mean miou_metric': 0.9470565915107727, 'Val/mean f1': 0.9704443216323853, 'Val/mean precision': 0.9657608270645142, 'Val/mean recall': 0.9751734733581543, 'Val/mean hd95_metric': 6.394715309143066} +Cheakpoint... +Epoch [977/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673219919204712, 'Val/mean miou_metric': 0.9470565915107727, 'Val/mean f1': 0.9704443216323853, 'Val/mean precision': 0.9657608270645142, 'Val/mean recall': 0.9751734733581543, 'Val/mean hd95_metric': 6.394715309143066} +Epoch [978/4000] Training [1/16] Loss: 0.02410 +Epoch [978/4000] Training [2/16] Loss: 0.00976 +Epoch [978/4000] Training [3/16] Loss: 0.01203 +Epoch [978/4000] Training [4/16] Loss: 0.01149 +Epoch [978/4000] Training [5/16] Loss: 0.00927 +Epoch [978/4000] Training [6/16] Loss: 0.01432 +Epoch [978/4000] Training [7/16] Loss: 0.01160 +Epoch [978/4000] Training [8/16] Loss: 0.01144 +Epoch [978/4000] Training [9/16] Loss: 0.01283 +Epoch [978/4000] Training [10/16] Loss: 0.02364 +Epoch [978/4000] Training [11/16] Loss: 0.02171 +Epoch [978/4000] Training [12/16] Loss: 0.01288 +Epoch [978/4000] Training [13/16] Loss: 0.01303 +Epoch [978/4000] Training [14/16] Loss: 0.01692 +Epoch [978/4000] Training [15/16] Loss: 0.01479 +Epoch [978/4000] Training [16/16] Loss: 0.01788 +Epoch [978/4000] Training metric {'Train/mean dice_metric': 0.9890085458755493, 'Train/mean miou_metric': 0.978407084941864, 'Train/mean f1': 0.9863041639328003, 'Train/mean precision': 0.9819132685661316, 'Train/mean recall': 0.9907344579696655, 'Train/mean hd95_metric': 2.432227611541748} +Epoch [978/4000] Validation [1/4] Loss: 0.24581 focal_loss 0.13845 dice_loss 0.10736 +Epoch [978/4000] Validation [2/4] Loss: 0.48523 focal_loss 0.19514 dice_loss 0.29009 +Epoch [978/4000] Validation [3/4] Loss: 0.14605 focal_loss 0.07802 dice_loss 0.06803 +Epoch [978/4000] Validation [4/4] Loss: 0.31633 focal_loss 0.17232 dice_loss 0.14400 +Epoch [978/4000] Validation metric {'Val/mean dice_metric': 0.9608810544013977, 'Val/mean miou_metric': 0.9393375515937805, 'Val/mean f1': 0.968742311000824, 'Val/mean precision': 0.9688397645950317, 'Val/mean recall': 0.968644917011261, 'Val/mean hd95_metric': 6.972553730010986} +Cheakpoint... +Epoch [978/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9609], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9608810544013977, 'Val/mean miou_metric': 0.9393375515937805, 'Val/mean f1': 0.968742311000824, 'Val/mean precision': 0.9688397645950317, 'Val/mean recall': 0.968644917011261, 'Val/mean hd95_metric': 6.972553730010986} +Epoch [979/4000] Training [1/16] Loss: 0.01162 +Epoch [979/4000] Training [2/16] Loss: 0.01409 +Epoch [979/4000] Training [3/16] Loss: 0.01072 +Epoch [979/4000] Training [4/16] Loss: 0.01202 +Epoch [979/4000] Training [5/16] Loss: 0.01327 +Epoch [979/4000] Training [6/16] Loss: 0.01115 +Epoch [979/4000] Training [7/16] Loss: 0.01241 +Epoch [979/4000] Training [8/16] Loss: 0.01230 +Epoch [979/4000] Training [9/16] Loss: 0.01109 +Epoch [979/4000] Training [10/16] Loss: 0.01201 +Epoch [979/4000] Training [11/16] Loss: 0.00920 +Epoch [979/4000] Training [12/16] Loss: 0.01314 +Epoch [979/4000] Training [13/16] Loss: 0.01207 +Epoch [979/4000] Training [14/16] Loss: 0.01137 +Epoch [979/4000] Training [15/16] Loss: 0.01337 +Epoch [979/4000] Training [16/16] Loss: 0.01218 +Epoch [979/4000] Training metric {'Train/mean dice_metric': 0.9914941191673279, 'Train/mean miou_metric': 0.982914924621582, 'Train/mean f1': 0.9881962537765503, 'Train/mean precision': 0.9836803674697876, 'Train/mean recall': 0.992753803730011, 'Train/mean hd95_metric': 1.2351452112197876} +Epoch [979/4000] Validation [1/4] Loss: 0.15725 focal_loss 0.08940 dice_loss 0.06785 +Epoch [979/4000] Validation [2/4] Loss: 0.62726 focal_loss 0.33421 dice_loss 0.29305 +Epoch [979/4000] Validation [3/4] Loss: 0.29219 focal_loss 0.16856 dice_loss 0.12363 +Epoch [979/4000] Validation [4/4] Loss: 0.17904 focal_loss 0.07152 dice_loss 0.10752 +Epoch [979/4000] Validation metric {'Val/mean dice_metric': 0.9642165899276733, 'Val/mean miou_metric': 0.9447249174118042, 'Val/mean f1': 0.971674382686615, 'Val/mean precision': 0.9683622121810913, 'Val/mean recall': 0.9750093221664429, 'Val/mean hd95_metric': 5.725857734680176} +Cheakpoint... +Epoch [979/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9642], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9642165899276733, 'Val/mean miou_metric': 0.9447249174118042, 'Val/mean f1': 0.971674382686615, 'Val/mean precision': 0.9683622121810913, 'Val/mean recall': 0.9750093221664429, 'Val/mean hd95_metric': 5.725857734680176} +Epoch [980/4000] Training [1/16] Loss: 0.01724 +Epoch [980/4000] Training [2/16] Loss: 0.01493 +Epoch [980/4000] Training [3/16] Loss: 0.02758 +Epoch [980/4000] Training [4/16] Loss: 0.01526 +Epoch [980/4000] Training [5/16] Loss: 0.01258 +Epoch [980/4000] Training [6/16] Loss: 0.01136 +Epoch [980/4000] Training [7/16] Loss: 0.02344 +Epoch [980/4000] Training [8/16] Loss: 0.01882 +Epoch [980/4000] Training [9/16] Loss: 0.01036 +Epoch [980/4000] Training [10/16] Loss: 0.01037 +Epoch [980/4000] Training [11/16] Loss: 0.01431 +Epoch [980/4000] Training [12/16] Loss: 0.00922 +Epoch [980/4000] Training [13/16] Loss: 0.01334 +Epoch [980/4000] Training [14/16] Loss: 0.00816 +Epoch [980/4000] Training [15/16] Loss: 0.00926 +Epoch [980/4000] Training [16/16] Loss: 0.01095 +Epoch [980/4000] Training metric {'Train/mean dice_metric': 0.9918041229248047, 'Train/mean miou_metric': 0.9835712909698486, 'Train/mean f1': 0.9882727861404419, 'Train/mean precision': 0.9839030504226685, 'Train/mean recall': 0.9926815629005432, 'Train/mean hd95_metric': 1.3856029510498047} +Epoch [980/4000] Validation [1/4] Loss: 0.15674 focal_loss 0.10112 dice_loss 0.05562 +Epoch [980/4000] Validation [2/4] Loss: 0.31744 focal_loss 0.16625 dice_loss 0.15119 +Epoch [980/4000] Validation [3/4] Loss: 0.29801 focal_loss 0.18674 dice_loss 0.11127 +Epoch [980/4000] Validation [4/4] Loss: 0.36912 focal_loss 0.17811 dice_loss 0.19101 +Epoch [980/4000] Validation metric {'Val/mean dice_metric': 0.9645398855209351, 'Val/mean miou_metric': 0.9443193674087524, 'Val/mean f1': 0.9682709574699402, 'Val/mean precision': 0.9595580697059631, 'Val/mean recall': 0.9771435856819153, 'Val/mean hd95_metric': 8.504117012023926} +Cheakpoint... +Epoch [980/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645398855209351, 'Val/mean miou_metric': 0.9443193674087524, 'Val/mean f1': 0.9682709574699402, 'Val/mean precision': 0.9595580697059631, 'Val/mean recall': 0.9771435856819153, 'Val/mean hd95_metric': 8.504117012023926} +Epoch [981/4000] Training [1/16] Loss: 0.01087 +Epoch [981/4000] Training [2/16] Loss: 0.01300 +Epoch [981/4000] Training [3/16] Loss: 0.01269 +Epoch [981/4000] Training [4/16] Loss: 0.01497 +Epoch [981/4000] Training [5/16] Loss: 0.01165 +Epoch [981/4000] Training [6/16] Loss: 0.01092 +Epoch [981/4000] Training [7/16] Loss: 0.01143 +Epoch [981/4000] Training [8/16] Loss: 0.00777 +Epoch [981/4000] Training [9/16] Loss: 0.01274 +Epoch [981/4000] Training [10/16] Loss: 0.01073 +Epoch [981/4000] Training [11/16] Loss: 0.00868 +Epoch [981/4000] Training [12/16] Loss: 0.01255 +Epoch [981/4000] Training [13/16] Loss: 0.01069 +Epoch [981/4000] Training [14/16] Loss: 0.01065 +Epoch [981/4000] Training [15/16] Loss: 0.01344 +Epoch [981/4000] Training [16/16] Loss: 0.01326 +Epoch [981/4000] Training metric {'Train/mean dice_metric': 0.9913204908370972, 'Train/mean miou_metric': 0.9831234812736511, 'Train/mean f1': 0.9882789254188538, 'Train/mean precision': 0.9837849736213684, 'Train/mean recall': 0.9928140640258789, 'Train/mean hd95_metric': 1.328758716583252} +Epoch [981/4000] Validation [1/4] Loss: 0.18303 focal_loss 0.11986 dice_loss 0.06317 +Epoch [981/4000] Validation [2/4] Loss: 0.35610 focal_loss 0.20467 dice_loss 0.15143 +Epoch [981/4000] Validation [3/4] Loss: 0.29421 focal_loss 0.19196 dice_loss 0.10225 +Epoch [981/4000] Validation [4/4] Loss: 0.39994 focal_loss 0.21821 dice_loss 0.18173 +Epoch [981/4000] Validation metric {'Val/mean dice_metric': 0.964425265789032, 'Val/mean miou_metric': 0.9434162378311157, 'Val/mean f1': 0.9660739898681641, 'Val/mean precision': 0.9522038698196411, 'Val/mean recall': 0.9803542494773865, 'Val/mean hd95_metric': 9.305391311645508} +Cheakpoint... +Epoch [981/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964425265789032, 'Val/mean miou_metric': 0.9434162378311157, 'Val/mean f1': 0.9660739898681641, 'Val/mean precision': 0.9522038698196411, 'Val/mean recall': 0.9803542494773865, 'Val/mean hd95_metric': 9.305391311645508} +Epoch [982/4000] Training [1/16] Loss: 0.01227 +Epoch [982/4000] Training [2/16] Loss: 0.01028 +Epoch [982/4000] Training [3/16] Loss: 0.01326 +Epoch [982/4000] Training [4/16] Loss: 0.01169 +Epoch [982/4000] Training [5/16] Loss: 0.01087 +Epoch [982/4000] Training [6/16] Loss: 0.01030 +Epoch [982/4000] Training [7/16] Loss: 0.01603 +Epoch [982/4000] Training [8/16] Loss: 0.01154 +Epoch [982/4000] Training [9/16] Loss: 0.01355 +Epoch [982/4000] Training [10/16] Loss: 0.01018 +Epoch [982/4000] Training [11/16] Loss: 0.00953 +Epoch [982/4000] Training [12/16] Loss: 0.01057 +Epoch [982/4000] Training [13/16] Loss: 0.01332 +Epoch [982/4000] Training [14/16] Loss: 0.01655 +Epoch [982/4000] Training [15/16] Loss: 0.01195 +Epoch [982/4000] Training [16/16] Loss: 0.01300 +Epoch [982/4000] Training metric {'Train/mean dice_metric': 0.9902869462966919, 'Train/mean miou_metric': 0.9808750152587891, 'Train/mean f1': 0.987371027469635, 'Train/mean precision': 0.9821609854698181, 'Train/mean recall': 0.9926366806030273, 'Train/mean hd95_metric': 2.2736191749572754} +Epoch [982/4000] Validation [1/4] Loss: 0.14643 focal_loss 0.08421 dice_loss 0.06222 +Epoch [982/4000] Validation [2/4] Loss: 0.61202 focal_loss 0.30442 dice_loss 0.30761 +Epoch [982/4000] Validation [3/4] Loss: 0.20054 focal_loss 0.10760 dice_loss 0.09294 +Epoch [982/4000] Validation [4/4] Loss: 0.30633 focal_loss 0.16517 dice_loss 0.14116 +Epoch [982/4000] Validation metric {'Val/mean dice_metric': 0.9637746810913086, 'Val/mean miou_metric': 0.9427280426025391, 'Val/mean f1': 0.9683651328086853, 'Val/mean precision': 0.9615048766136169, 'Val/mean recall': 0.9753240942955017, 'Val/mean hd95_metric': 7.462279319763184} +Cheakpoint... +Epoch [982/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9638], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637746810913086, 'Val/mean miou_metric': 0.9427280426025391, 'Val/mean f1': 0.9683651328086853, 'Val/mean precision': 0.9615048766136169, 'Val/mean recall': 0.9753240942955017, 'Val/mean hd95_metric': 7.462279319763184} +Epoch [983/4000] Training [1/16] Loss: 0.02671 +Epoch [983/4000] Training [2/16] Loss: 0.01697 +Epoch [983/4000] Training [3/16] Loss: 0.01231 +Epoch [983/4000] Training [4/16] Loss: 0.01177 +Epoch [983/4000] Training [5/16] Loss: 0.01099 +Epoch [983/4000] Training [6/16] Loss: 0.01203 +Epoch [983/4000] Training [7/16] Loss: 0.01036 +Epoch [983/4000] Training [8/16] Loss: 0.01465 +Epoch [983/4000] Training [9/16] Loss: 0.01020 +Epoch [983/4000] Training [10/16] Loss: 0.01470 +Epoch [983/4000] Training [11/16] Loss: 0.00926 +Epoch [983/4000] Training [12/16] Loss: 0.01665 +Epoch [983/4000] Training [13/16] Loss: 0.01552 +Epoch [983/4000] Training [14/16] Loss: 0.01057 +Epoch [983/4000] Training [15/16] Loss: 0.01357 +Epoch [983/4000] Training [16/16] Loss: 0.00963 +Epoch [983/4000] Training metric {'Train/mean dice_metric': 0.9887868762016296, 'Train/mean miou_metric': 0.9785364866256714, 'Train/mean f1': 0.9865909218788147, 'Train/mean precision': 0.9824535846710205, 'Train/mean recall': 0.9907631874084473, 'Train/mean hd95_metric': 1.765312671661377} +Epoch [983/4000] Validation [1/4] Loss: 0.13754 focal_loss 0.08131 dice_loss 0.05623 +Epoch [983/4000] Validation [2/4] Loss: 0.34968 focal_loss 0.15857 dice_loss 0.19112 +Epoch [983/4000] Validation [3/4] Loss: 0.16451 focal_loss 0.07318 dice_loss 0.09133 +Epoch [983/4000] Validation [4/4] Loss: 0.36109 focal_loss 0.19998 dice_loss 0.16111 +Epoch [983/4000] Validation metric {'Val/mean dice_metric': 0.9670897722244263, 'Val/mean miou_metric': 0.9457054138183594, 'Val/mean f1': 0.9706545472145081, 'Val/mean precision': 0.965514600276947, 'Val/mean recall': 0.9758495688438416, 'Val/mean hd95_metric': 6.3454132080078125} +Cheakpoint... +Epoch [983/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670897722244263, 'Val/mean miou_metric': 0.9457054138183594, 'Val/mean f1': 0.9706545472145081, 'Val/mean precision': 0.965514600276947, 'Val/mean recall': 0.9758495688438416, 'Val/mean hd95_metric': 6.3454132080078125} +Epoch [984/4000] Training [1/16] Loss: 0.01374 +Epoch [984/4000] Training [2/16] Loss: 0.01125 +Epoch [984/4000] Training [3/16] Loss: 0.00939 +Epoch [984/4000] Training [4/16] Loss: 0.00990 +Epoch [984/4000] Training [5/16] Loss: 0.01364 +Epoch [984/4000] Training [6/16] Loss: 0.01489 +Epoch [984/4000] Training [7/16] Loss: 0.01468 +Epoch [984/4000] Training [8/16] Loss: 0.01621 +Epoch [984/4000] Training [9/16] Loss: 0.01070 +Epoch [984/4000] Training [10/16] Loss: 0.01368 +Epoch [984/4000] Training [11/16] Loss: 0.01068 +Epoch [984/4000] Training [12/16] Loss: 0.00956 +Epoch [984/4000] Training [13/16] Loss: 0.01234 +Epoch [984/4000] Training [14/16] Loss: 0.00956 +Epoch [984/4000] Training [15/16] Loss: 0.01103 +Epoch [984/4000] Training [16/16] Loss: 0.01274 +Epoch [984/4000] Training metric {'Train/mean dice_metric': 0.9915765523910522, 'Train/mean miou_metric': 0.9830870628356934, 'Train/mean f1': 0.9881827235221863, 'Train/mean precision': 0.9837459325790405, 'Train/mean recall': 0.9926597476005554, 'Train/mean hd95_metric': 1.3944430351257324} +Epoch [984/4000] Validation [1/4] Loss: 0.17678 focal_loss 0.11383 dice_loss 0.06295 +Epoch [984/4000] Validation [2/4] Loss: 0.45383 focal_loss 0.27573 dice_loss 0.17811 +Epoch [984/4000] Validation [3/4] Loss: 0.17974 focal_loss 0.08788 dice_loss 0.09186 +Epoch [984/4000] Validation [4/4] Loss: 0.28681 focal_loss 0.15625 dice_loss 0.13055 +Epoch [984/4000] Validation metric {'Val/mean dice_metric': 0.9696985483169556, 'Val/mean miou_metric': 0.9496723413467407, 'Val/mean f1': 0.9722742438316345, 'Val/mean precision': 0.9682392477989197, 'Val/mean recall': 0.9763430953025818, 'Val/mean hd95_metric': 5.9411540031433105} +Cheakpoint... +Epoch [984/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696985483169556, 'Val/mean miou_metric': 0.9496723413467407, 'Val/mean f1': 0.9722742438316345, 'Val/mean precision': 0.9682392477989197, 'Val/mean recall': 0.9763430953025818, 'Val/mean hd95_metric': 5.9411540031433105} +Epoch [985/4000] Training [1/16] Loss: 0.00849 +Epoch [985/4000] Training [2/16] Loss: 0.01266 +Epoch [985/4000] Training [3/16] Loss: 0.00975 +Epoch [985/4000] Training [4/16] Loss: 0.01596 +Epoch [985/4000] Training [5/16] Loss: 0.01003 +Epoch [985/4000] Training [6/16] Loss: 0.01206 +Epoch [985/4000] Training [7/16] Loss: 0.01098 +Epoch [985/4000] Training [8/16] Loss: 0.01249 +Epoch [985/4000] Training [9/16] Loss: 0.01354 +Epoch [985/4000] Training [10/16] Loss: 0.01064 +Epoch [985/4000] Training [11/16] Loss: 0.01139 +Epoch [985/4000] Training [12/16] Loss: 0.01220 +Epoch [985/4000] Training [13/16] Loss: 0.01026 +Epoch [985/4000] Training [14/16] Loss: 0.00995 +Epoch [985/4000] Training [15/16] Loss: 0.02242 +Epoch [985/4000] Training [16/16] Loss: 0.01033 +Epoch [985/4000] Training metric {'Train/mean dice_metric': 0.9911234378814697, 'Train/mean miou_metric': 0.9823736548423767, 'Train/mean f1': 0.9881279468536377, 'Train/mean precision': 0.9835672974586487, 'Train/mean recall': 0.9927310943603516, 'Train/mean hd95_metric': 1.3139641284942627} +Epoch [985/4000] Validation [1/4] Loss: 0.16766 focal_loss 0.10680 dice_loss 0.06086 +Epoch [985/4000] Validation [2/4] Loss: 0.33504 focal_loss 0.16462 dice_loss 0.17041 +Epoch [985/4000] Validation [3/4] Loss: 0.18405 focal_loss 0.09616 dice_loss 0.08789 +Epoch [985/4000] Validation [4/4] Loss: 0.25215 focal_loss 0.13168 dice_loss 0.12048 +Epoch [985/4000] Validation metric {'Val/mean dice_metric': 0.9691664576530457, 'Val/mean miou_metric': 0.9490560293197632, 'Val/mean f1': 0.9721354842185974, 'Val/mean precision': 0.966198742389679, 'Val/mean recall': 0.9781455397605896, 'Val/mean hd95_metric': 5.864903450012207} +Cheakpoint... +Epoch [985/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691664576530457, 'Val/mean miou_metric': 0.9490560293197632, 'Val/mean f1': 0.9721354842185974, 'Val/mean precision': 0.966198742389679, 'Val/mean recall': 0.9781455397605896, 'Val/mean hd95_metric': 5.864903450012207} +Epoch [986/4000] Training [1/16] Loss: 0.01135 +Epoch [986/4000] Training [2/16] Loss: 0.01161 +Epoch [986/4000] Training [3/16] Loss: 0.01012 +Epoch [986/4000] Training [4/16] Loss: 0.01390 +Epoch [986/4000] Training [5/16] Loss: 0.01186 +Epoch [986/4000] Training [6/16] Loss: 0.01472 +Epoch [986/4000] Training [7/16] Loss: 0.01398 +Epoch [986/4000] Training [8/16] Loss: 0.01062 +Epoch [986/4000] Training [9/16] Loss: 0.01223 +Epoch [986/4000] Training [10/16] Loss: 0.01601 +Epoch [986/4000] Training [11/16] Loss: 0.01402 +Epoch [986/4000] Training [12/16] Loss: 0.01079 +Epoch [986/4000] Training [13/16] Loss: 0.01064 +Epoch [986/4000] Training [14/16] Loss: 0.01041 +Epoch [986/4000] Training [15/16] Loss: 0.01087 +Epoch [986/4000] Training [16/16] Loss: 0.01017 +Epoch [986/4000] Training metric {'Train/mean dice_metric': 0.9909563064575195, 'Train/mean miou_metric': 0.9820190072059631, 'Train/mean f1': 0.9877794981002808, 'Train/mean precision': 0.9834442734718323, 'Train/mean recall': 0.9921531677246094, 'Train/mean hd95_metric': 1.51567804813385} +Epoch [986/4000] Validation [1/4] Loss: 0.17094 focal_loss 0.11168 dice_loss 0.05925 +Epoch [986/4000] Validation [2/4] Loss: 0.42313 focal_loss 0.23378 dice_loss 0.18935 +Epoch [986/4000] Validation [3/4] Loss: 0.18302 focal_loss 0.09573 dice_loss 0.08729 +Epoch [986/4000] Validation [4/4] Loss: 0.20967 focal_loss 0.09670 dice_loss 0.11298 +Epoch [986/4000] Validation metric {'Val/mean dice_metric': 0.9679385423660278, 'Val/mean miou_metric': 0.9474633932113647, 'Val/mean f1': 0.9704040884971619, 'Val/mean precision': 0.9654586911201477, 'Val/mean recall': 0.975400447845459, 'Val/mean hd95_metric': 5.947458744049072} +Cheakpoint... +Epoch [986/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679385423660278, 'Val/mean miou_metric': 0.9474633932113647, 'Val/mean f1': 0.9704040884971619, 'Val/mean precision': 0.9654586911201477, 'Val/mean recall': 0.975400447845459, 'Val/mean hd95_metric': 5.947458744049072} +Epoch [987/4000] Training [1/16] Loss: 0.01002 +Epoch [987/4000] Training [2/16] Loss: 0.01265 +Epoch [987/4000] Training [3/16] Loss: 0.01108 +Epoch [987/4000] Training [4/16] Loss: 0.00794 +Epoch [987/4000] Training [5/16] Loss: 0.01061 +Epoch [987/4000] Training [6/16] Loss: 0.01187 +Epoch [987/4000] Training [7/16] Loss: 0.01235 +Epoch [987/4000] Training [8/16] Loss: 0.01106 +Epoch [987/4000] Training [9/16] Loss: 0.01213 +Epoch [987/4000] Training [10/16] Loss: 0.01002 +Epoch [987/4000] Training [11/16] Loss: 0.01224 +Epoch [987/4000] Training [12/16] Loss: 0.01032 +Epoch [987/4000] Training [13/16] Loss: 0.01007 +Epoch [987/4000] Training [14/16] Loss: 0.00922 +Epoch [987/4000] Training [15/16] Loss: 0.00985 +Epoch [987/4000] Training [16/16] Loss: 0.00938 +Epoch [987/4000] Training metric {'Train/mean dice_metric': 0.9924687147140503, 'Train/mean miou_metric': 0.9848165512084961, 'Train/mean f1': 0.9889430999755859, 'Train/mean precision': 0.9843328595161438, 'Train/mean recall': 0.9935967922210693, 'Train/mean hd95_metric': 1.124938726425171} +Epoch [987/4000] Validation [1/4] Loss: 0.14746 focal_loss 0.09519 dice_loss 0.05227 +Epoch [987/4000] Validation [2/4] Loss: 0.43120 focal_loss 0.24058 dice_loss 0.19062 +Epoch [987/4000] Validation [3/4] Loss: 0.12752 focal_loss 0.06746 dice_loss 0.06005 +Epoch [987/4000] Validation [4/4] Loss: 0.19034 focal_loss 0.08372 dice_loss 0.10662 +Epoch [987/4000] Validation metric {'Val/mean dice_metric': 0.968376636505127, 'Val/mean miou_metric': 0.9508832693099976, 'Val/mean f1': 0.9736100435256958, 'Val/mean precision': 0.970832347869873, 'Val/mean recall': 0.9764035940170288, 'Val/mean hd95_metric': 5.16048002243042} +Cheakpoint... +Epoch [987/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968376636505127, 'Val/mean miou_metric': 0.9508832693099976, 'Val/mean f1': 0.9736100435256958, 'Val/mean precision': 0.970832347869873, 'Val/mean recall': 0.9764035940170288, 'Val/mean hd95_metric': 5.16048002243042} +Epoch [988/4000] Training [1/16] Loss: 0.01035 +Epoch [988/4000] Training [2/16] Loss: 0.01850 +Epoch [988/4000] Training [3/16] Loss: 0.00923 +Epoch [988/4000] Training [4/16] Loss: 0.14865 +Epoch [988/4000] Training [5/16] Loss: 0.01028 +Epoch [988/4000] Training [6/16] Loss: 0.01001 +Epoch [988/4000] Training [7/16] Loss: 0.01106 +Epoch [988/4000] Training [8/16] Loss: 0.01176 +Epoch [988/4000] Training [9/16] Loss: 0.00860 +Epoch [988/4000] Training [10/16] Loss: 0.01160 +Epoch [988/4000] Training [11/16] Loss: 0.01107 +Epoch [988/4000] Training [12/16] Loss: 0.01215 +Epoch [988/4000] Training [13/16] Loss: 0.00994 +Epoch [988/4000] Training [14/16] Loss: 0.00966 +Epoch [988/4000] Training [15/16] Loss: 0.00744 +Epoch [988/4000] Training [16/16] Loss: 0.01878 +Epoch [988/4000] Training metric {'Train/mean dice_metric': 0.9906097650527954, 'Train/mean miou_metric': 0.9828267097473145, 'Train/mean f1': 0.9887527823448181, 'Train/mean precision': 0.9841616153717041, 'Train/mean recall': 0.9933870434761047, 'Train/mean hd95_metric': 1.5002665519714355} +Epoch [988/4000] Validation [1/4] Loss: 0.18100 focal_loss 0.11330 dice_loss 0.06771 +Epoch [988/4000] Validation [2/4] Loss: 0.43294 focal_loss 0.23143 dice_loss 0.20151 +Epoch [988/4000] Validation [3/4] Loss: 0.24165 focal_loss 0.13013 dice_loss 0.11152 +Epoch [988/4000] Validation [4/4] Loss: 0.19682 focal_loss 0.10206 dice_loss 0.09475 +Epoch [988/4000] Validation metric {'Val/mean dice_metric': 0.9684684872627258, 'Val/mean miou_metric': 0.9491444826126099, 'Val/mean f1': 0.970874547958374, 'Val/mean precision': 0.9648717045783997, 'Val/mean recall': 0.9769523739814758, 'Val/mean hd95_metric': 6.246773719787598} +Cheakpoint... +Epoch [988/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684684872627258, 'Val/mean miou_metric': 0.9491444826126099, 'Val/mean f1': 0.970874547958374, 'Val/mean precision': 0.9648717045783997, 'Val/mean recall': 0.9769523739814758, 'Val/mean hd95_metric': 6.246773719787598} +Epoch [989/4000] Training [1/16] Loss: 0.00867 +Epoch [989/4000] Training [2/16] Loss: 0.00939 +Epoch [989/4000] Training [3/16] Loss: 0.18490 +Epoch [989/4000] Training [4/16] Loss: 0.01153 +Epoch [989/4000] Training [5/16] Loss: 0.00944 +Epoch [989/4000] Training [6/16] Loss: 0.01138 +Epoch [989/4000] Training [7/16] Loss: 0.01061 +Epoch [989/4000] Training [8/16] Loss: 0.01191 +Epoch [989/4000] Training [9/16] Loss: 0.01523 +Epoch [989/4000] Training [10/16] Loss: 0.01324 +Epoch [989/4000] Training [11/16] Loss: 0.01118 +Epoch [989/4000] Training [12/16] Loss: 0.01112 +Epoch [989/4000] Training [13/16] Loss: 0.01180 +Epoch [989/4000] Training [14/16] Loss: 0.01327 +Epoch [989/4000] Training [15/16] Loss: 0.02323 +Epoch [989/4000] Training [16/16] Loss: 0.01205 +Epoch [989/4000] Training metric {'Train/mean dice_metric': 0.9877305030822754, 'Train/mean miou_metric': 0.9789267778396606, 'Train/mean f1': 0.9865738153457642, 'Train/mean precision': 0.9823082685470581, 'Train/mean recall': 0.9908764958381653, 'Train/mean hd95_metric': 1.8081763982772827} +Epoch [989/4000] Validation [1/4] Loss: 0.55820 focal_loss 0.36230 dice_loss 0.19591 +Epoch [989/4000] Validation [2/4] Loss: 0.50269 focal_loss 0.20632 dice_loss 0.29637 +Epoch [989/4000] Validation [3/4] Loss: 0.14956 focal_loss 0.07713 dice_loss 0.07243 +Epoch [989/4000] Validation [4/4] Loss: 0.17265 focal_loss 0.07858 dice_loss 0.09407 +Epoch [989/4000] Validation metric {'Val/mean dice_metric': 0.9572307467460632, 'Val/mean miou_metric': 0.9365496635437012, 'Val/mean f1': 0.965711772441864, 'Val/mean precision': 0.9709241390228271, 'Val/mean recall': 0.9605550169944763, 'Val/mean hd95_metric': 6.67990255355835} +Cheakpoint... +Epoch [989/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9572], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9572307467460632, 'Val/mean miou_metric': 0.9365496635437012, 'Val/mean f1': 0.965711772441864, 'Val/mean precision': 0.9709241390228271, 'Val/mean recall': 0.9605550169944763, 'Val/mean hd95_metric': 6.67990255355835} +Epoch [990/4000] Training [1/16] Loss: 0.01828 +Epoch [990/4000] Training [2/16] Loss: 0.01653 +Epoch [990/4000] Training [3/16] Loss: 0.01021 +Epoch [990/4000] Training [4/16] Loss: 0.01047 +Epoch [990/4000] Training [5/16] Loss: 0.01133 +Epoch [990/4000] Training [6/16] Loss: 0.01031 +Epoch [990/4000] Training [7/16] Loss: 0.01143 +Epoch [990/4000] Training [8/16] Loss: 0.02241 +Epoch [990/4000] Training [9/16] Loss: 0.01105 +Epoch [990/4000] Training [10/16] Loss: 0.00978 +Epoch [990/4000] Training [11/16] Loss: 0.01031 +Epoch [990/4000] Training [12/16] Loss: 0.01702 +Epoch [990/4000] Training [13/16] Loss: 0.01062 +Epoch [990/4000] Training [14/16] Loss: 0.01215 +Epoch [990/4000] Training [15/16] Loss: 0.00964 +Epoch [990/4000] Training [16/16] Loss: 0.00980 +Epoch [990/4000] Training metric {'Train/mean dice_metric': 0.9903388023376465, 'Train/mean miou_metric': 0.9816298484802246, 'Train/mean f1': 0.9871140122413635, 'Train/mean precision': 0.981613278388977, 'Train/mean recall': 0.9926767349243164, 'Train/mean hd95_metric': 1.581208348274231} +Epoch [990/4000] Validation [1/4] Loss: 0.19595 focal_loss 0.12286 dice_loss 0.07309 +Epoch [990/4000] Validation [2/4] Loss: 0.28580 focal_loss 0.13577 dice_loss 0.15004 +Epoch [990/4000] Validation [3/4] Loss: 0.22454 focal_loss 0.12834 dice_loss 0.09620 +Epoch [990/4000] Validation [4/4] Loss: 0.30536 focal_loss 0.18034 dice_loss 0.12502 +Epoch [990/4000] Validation metric {'Val/mean dice_metric': 0.9691163897514343, 'Val/mean miou_metric': 0.9487737417221069, 'Val/mean f1': 0.9710864424705505, 'Val/mean precision': 0.9679787158966064, 'Val/mean recall': 0.9742141962051392, 'Val/mean hd95_metric': 6.524327278137207} +Cheakpoint... +Epoch [990/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691163897514343, 'Val/mean miou_metric': 0.9487737417221069, 'Val/mean f1': 0.9710864424705505, 'Val/mean precision': 0.9679787158966064, 'Val/mean recall': 0.9742141962051392, 'Val/mean hd95_metric': 6.524327278137207} +Epoch [991/4000] Training [1/16] Loss: 0.02257 +Epoch [991/4000] Training [2/16] Loss: 0.00914 +Epoch [991/4000] Training [3/16] Loss: 0.01012 +Epoch [991/4000] Training [4/16] Loss: 0.00999 +Epoch [991/4000] Training [5/16] Loss: 0.01271 +Epoch [991/4000] Training [6/16] Loss: 0.01229 +Epoch [991/4000] Training [7/16] Loss: 0.01010 +Epoch [991/4000] Training [8/16] Loss: 0.01410 +Epoch [991/4000] Training [9/16] Loss: 0.01264 +Epoch [991/4000] Training [10/16] Loss: 0.01238 +Epoch [991/4000] Training [11/16] Loss: 0.01129 +Epoch [991/4000] Training [12/16] Loss: 0.01052 +Epoch [991/4000] Training [13/16] Loss: 0.01244 +Epoch [991/4000] Training [14/16] Loss: 0.01628 +Epoch [991/4000] Training [15/16] Loss: 0.01927 +Epoch [991/4000] Training [16/16] Loss: 0.01058 +Epoch [991/4000] Training metric {'Train/mean dice_metric': 0.9912487268447876, 'Train/mean miou_metric': 0.982515811920166, 'Train/mean f1': 0.9878345131874084, 'Train/mean precision': 0.9830882549285889, 'Train/mean recall': 0.9926268458366394, 'Train/mean hd95_metric': 1.6406564712524414} +Epoch [991/4000] Validation [1/4] Loss: 0.16983 focal_loss 0.09387 dice_loss 0.07596 +Epoch [991/4000] Validation [2/4] Loss: 0.43360 focal_loss 0.16307 dice_loss 0.27053 +Epoch [991/4000] Validation [3/4] Loss: 0.22536 focal_loss 0.12005 dice_loss 0.10531 +Epoch [991/4000] Validation [4/4] Loss: 0.34268 focal_loss 0.19272 dice_loss 0.14996 +Epoch [991/4000] Validation metric {'Val/mean dice_metric': 0.963575541973114, 'Val/mean miou_metric': 0.9418907165527344, 'Val/mean f1': 0.9681706428527832, 'Val/mean precision': 0.9713358283042908, 'Val/mean recall': 0.9650261402130127, 'Val/mean hd95_metric': 6.434431552886963} +Cheakpoint... +Epoch [991/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963575541973114, 'Val/mean miou_metric': 0.9418907165527344, 'Val/mean f1': 0.9681706428527832, 'Val/mean precision': 0.9713358283042908, 'Val/mean recall': 0.9650261402130127, 'Val/mean hd95_metric': 6.434431552886963} +Epoch [992/4000] Training [1/16] Loss: 0.01128 +Epoch [992/4000] Training [2/16] Loss: 0.01030 +Epoch [992/4000] Training [3/16] Loss: 0.01295 +Epoch [992/4000] Training [4/16] Loss: 0.00979 +Epoch [992/4000] Training [5/16] Loss: 0.01471 +Epoch [992/4000] Training [6/16] Loss: 0.01310 +Epoch [992/4000] Training [7/16] Loss: 0.01227 +Epoch [992/4000] Training [8/16] Loss: 0.01140 +Epoch [992/4000] Training [9/16] Loss: 0.01037 +Epoch [992/4000] Training [10/16] Loss: 0.01091 +Epoch [992/4000] Training [11/16] Loss: 0.01136 +Epoch [992/4000] Training [12/16] Loss: 0.01192 +Epoch [992/4000] Training [13/16] Loss: 0.01153 +Epoch [992/4000] Training [14/16] Loss: 0.00988 +Epoch [992/4000] Training [15/16] Loss: 0.00993 +Epoch [992/4000] Training [16/16] Loss: 0.01592 +Epoch [992/4000] Training metric {'Train/mean dice_metric': 0.9919112920761108, 'Train/mean miou_metric': 0.9837689399719238, 'Train/mean f1': 0.988466203212738, 'Train/mean precision': 0.9841017723083496, 'Train/mean recall': 0.99286949634552, 'Train/mean hd95_metric': 1.2923378944396973} +Epoch [992/4000] Validation [1/4] Loss: 0.17902 focal_loss 0.10171 dice_loss 0.07731 +Epoch [992/4000] Validation [2/4] Loss: 0.40025 focal_loss 0.22635 dice_loss 0.17390 +Epoch [992/4000] Validation [3/4] Loss: 0.21100 focal_loss 0.11925 dice_loss 0.09175 +Epoch [992/4000] Validation [4/4] Loss: 0.19528 focal_loss 0.08654 dice_loss 0.10874 +Epoch [992/4000] Validation metric {'Val/mean dice_metric': 0.9696071743965149, 'Val/mean miou_metric': 0.9493907690048218, 'Val/mean f1': 0.9720900058746338, 'Val/mean precision': 0.9695977568626404, 'Val/mean recall': 0.9745951294898987, 'Val/mean hd95_metric': 5.7825422286987305} +Cheakpoint... +Epoch [992/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696071743965149, 'Val/mean miou_metric': 0.9493907690048218, 'Val/mean f1': 0.9720900058746338, 'Val/mean precision': 0.9695977568626404, 'Val/mean recall': 0.9745951294898987, 'Val/mean hd95_metric': 5.7825422286987305} +Epoch [993/4000] Training [1/16] Loss: 0.01419 +Epoch [993/4000] Training [2/16] Loss: 0.01174 +Epoch [993/4000] Training [3/16] Loss: 0.01349 +Epoch [993/4000] Training [4/16] Loss: 0.01648 +Epoch [993/4000] Training [5/16] Loss: 0.01054 +Epoch [993/4000] Training [6/16] Loss: 0.00869 +Epoch [993/4000] Training [7/16] Loss: 0.01176 +Epoch [993/4000] Training [8/16] Loss: 0.00908 +Epoch [993/4000] Training [9/16] Loss: 0.00829 +Epoch [993/4000] Training [10/16] Loss: 0.00976 +Epoch [993/4000] Training [11/16] Loss: 0.01138 +Epoch [993/4000] Training [12/16] Loss: 0.01265 +Epoch [993/4000] Training [13/16] Loss: 0.01092 +Epoch [993/4000] Training [14/16] Loss: 0.01042 +Epoch [993/4000] Training [15/16] Loss: 0.00910 +Epoch [993/4000] Training [16/16] Loss: 0.01138 +Epoch [993/4000] Training metric {'Train/mean dice_metric': 0.9918363094329834, 'Train/mean miou_metric': 0.9835977554321289, 'Train/mean f1': 0.9885210394859314, 'Train/mean precision': 0.9840578436851501, 'Train/mean recall': 0.9930249452590942, 'Train/mean hd95_metric': 1.204298496246338} +Epoch [993/4000] Validation [1/4] Loss: 0.21347 focal_loss 0.12082 dice_loss 0.09265 +Epoch [993/4000] Validation [2/4] Loss: 0.44379 focal_loss 0.20931 dice_loss 0.23448 +Epoch [993/4000] Validation [3/4] Loss: 0.20199 focal_loss 0.11075 dice_loss 0.09124 +Epoch [993/4000] Validation [4/4] Loss: 0.26962 focal_loss 0.15210 dice_loss 0.11752 +Epoch [993/4000] Validation metric {'Val/mean dice_metric': 0.9696294665336609, 'Val/mean miou_metric': 0.9498645663261414, 'Val/mean f1': 0.9727131128311157, 'Val/mean precision': 0.9711849093437195, 'Val/mean recall': 0.974246084690094, 'Val/mean hd95_metric': 5.58461856842041} +Cheakpoint... +Epoch [993/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696294665336609, 'Val/mean miou_metric': 0.9498645663261414, 'Val/mean f1': 0.9727131128311157, 'Val/mean precision': 0.9711849093437195, 'Val/mean recall': 0.974246084690094, 'Val/mean hd95_metric': 5.58461856842041} +Epoch [994/4000] Training [1/16] Loss: 0.00848 +Epoch [994/4000] Training [2/16] Loss: 0.00933 +Epoch [994/4000] Training [3/16] Loss: 0.01051 +Epoch [994/4000] Training [4/16] Loss: 0.01016 +Epoch [994/4000] Training [5/16] Loss: 0.00910 +Epoch [994/4000] Training [6/16] Loss: 0.01190 +Epoch [994/4000] Training [7/16] Loss: 0.05885 +Epoch [994/4000] Training [8/16] Loss: 0.00901 +Epoch [994/4000] Training [9/16] Loss: 0.00926 +Epoch [994/4000] Training [10/16] Loss: 0.01266 +Epoch [994/4000] Training [11/16] Loss: 0.01276 +Epoch [994/4000] Training [12/16] Loss: 0.01629 +Epoch [994/4000] Training [13/16] Loss: 0.01130 +Epoch [994/4000] Training [14/16] Loss: 0.00945 +Epoch [994/4000] Training [15/16] Loss: 0.01152 +Epoch [994/4000] Training [16/16] Loss: 0.01356 +Epoch [994/4000] Training metric {'Train/mean dice_metric': 0.9917423129081726, 'Train/mean miou_metric': 0.9837819337844849, 'Train/mean f1': 0.9889547228813171, 'Train/mean precision': 0.984270453453064, 'Train/mean recall': 0.9936837553977966, 'Train/mean hd95_metric': 1.4662854671478271} +Epoch [994/4000] Validation [1/4] Loss: 0.20357 focal_loss 0.11811 dice_loss 0.08545 +Epoch [994/4000] Validation [2/4] Loss: 0.26398 focal_loss 0.13133 dice_loss 0.13265 +Epoch [994/4000] Validation [3/4] Loss: 0.22379 focal_loss 0.12954 dice_loss 0.09425 +Epoch [994/4000] Validation [4/4] Loss: 0.20250 focal_loss 0.09438 dice_loss 0.10812 +Epoch [994/4000] Validation metric {'Val/mean dice_metric': 0.969051718711853, 'Val/mean miou_metric': 0.9487840533256531, 'Val/mean f1': 0.9718279838562012, 'Val/mean precision': 0.9698938727378845, 'Val/mean recall': 0.9737697243690491, 'Val/mean hd95_metric': 6.660334587097168} +Cheakpoint... +Epoch [994/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969051718711853, 'Val/mean miou_metric': 0.9487840533256531, 'Val/mean f1': 0.9718279838562012, 'Val/mean precision': 0.9698938727378845, 'Val/mean recall': 0.9737697243690491, 'Val/mean hd95_metric': 6.660334587097168} +Epoch [995/4000] Training [1/16] Loss: 0.01277 +Epoch [995/4000] Training [2/16] Loss: 0.01189 +Epoch [995/4000] Training [3/16] Loss: 0.01609 +Epoch [995/4000] Training [4/16] Loss: 0.01118 +Epoch [995/4000] Training [5/16] Loss: 0.01375 +Epoch [995/4000] Training [6/16] Loss: 0.01439 +Epoch [995/4000] Training [7/16] Loss: 0.01241 +Epoch [995/4000] Training [8/16] Loss: 0.01174 +Epoch [995/4000] Training [9/16] Loss: 0.00871 +Epoch [995/4000] Training [10/16] Loss: 0.01103 +Epoch [995/4000] Training [11/16] Loss: 0.01687 +Epoch [995/4000] Training [12/16] Loss: 0.01060 +Epoch [995/4000] Training [13/16] Loss: 0.01026 +Epoch [995/4000] Training [14/16] Loss: 0.01046 +Epoch [995/4000] Training [15/16] Loss: 0.01030 +Epoch [995/4000] Training [16/16] Loss: 0.01153 +Epoch [995/4000] Training metric {'Train/mean dice_metric': 0.991835355758667, 'Train/mean miou_metric': 0.9835980534553528, 'Train/mean f1': 0.9883949756622314, 'Train/mean precision': 0.9841019511222839, 'Train/mean recall': 0.992725670337677, 'Train/mean hd95_metric': 1.4344204664230347} +Epoch [995/4000] Validation [1/4] Loss: 0.22037 focal_loss 0.12095 dice_loss 0.09941 +Epoch [995/4000] Validation [2/4] Loss: 0.28754 focal_loss 0.14693 dice_loss 0.14061 +Epoch [995/4000] Validation [3/4] Loss: 0.20620 focal_loss 0.10642 dice_loss 0.09979 +Epoch [995/4000] Validation [4/4] Loss: 0.26312 focal_loss 0.14505 dice_loss 0.11807 +Epoch [995/4000] Validation metric {'Val/mean dice_metric': 0.9674171209335327, 'Val/mean miou_metric': 0.9475549459457397, 'Val/mean f1': 0.9709805846214294, 'Val/mean precision': 0.970899224281311, 'Val/mean recall': 0.9710620045661926, 'Val/mean hd95_metric': 6.348203182220459} +Cheakpoint... +Epoch [995/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674171209335327, 'Val/mean miou_metric': 0.9475549459457397, 'Val/mean f1': 0.9709805846214294, 'Val/mean precision': 0.970899224281311, 'Val/mean recall': 0.9710620045661926, 'Val/mean hd95_metric': 6.348203182220459} +Epoch [996/4000] Training [1/16] Loss: 0.01266 +Epoch [996/4000] Training [2/16] Loss: 0.01136 +Epoch [996/4000] Training [3/16] Loss: 0.01275 +Epoch [996/4000] Training [4/16] Loss: 0.01047 +Epoch [996/4000] Training [5/16] Loss: 0.00933 +Epoch [996/4000] Training [6/16] Loss: 0.01055 +Epoch [996/4000] Training [7/16] Loss: 0.01265 +Epoch [996/4000] Training [8/16] Loss: 0.01341 +Epoch [996/4000] Training [9/16] Loss: 0.01801 +Epoch [996/4000] Training [10/16] Loss: 0.01151 +Epoch [996/4000] Training [11/16] Loss: 0.00849 +Epoch [996/4000] Training [12/16] Loss: 0.01221 +Epoch [996/4000] Training [13/16] Loss: 0.02059 +Epoch [996/4000] Training [14/16] Loss: 0.01250 +Epoch [996/4000] Training [15/16] Loss: 0.01437 +Epoch [996/4000] Training [16/16] Loss: 0.00859 +Epoch [996/4000] Training metric {'Train/mean dice_metric': 0.9913828372955322, 'Train/mean miou_metric': 0.9827107191085815, 'Train/mean f1': 0.9876189827919006, 'Train/mean precision': 0.9826908111572266, 'Train/mean recall': 0.9925968050956726, 'Train/mean hd95_metric': 1.6012557744979858} +Epoch [996/4000] Validation [1/4] Loss: 0.14292 focal_loss 0.08334 dice_loss 0.05958 +Epoch [996/4000] Validation [2/4] Loss: 0.37046 focal_loss 0.16945 dice_loss 0.20101 +Epoch [996/4000] Validation [3/4] Loss: 0.15918 focal_loss 0.08794 dice_loss 0.07125 +Epoch [996/4000] Validation [4/4] Loss: 0.22184 focal_loss 0.12271 dice_loss 0.09913 +Epoch [996/4000] Validation metric {'Val/mean dice_metric': 0.9686649441719055, 'Val/mean miou_metric': 0.9491907358169556, 'Val/mean f1': 0.9713162183761597, 'Val/mean precision': 0.9667591452598572, 'Val/mean recall': 0.9759166240692139, 'Val/mean hd95_metric': 6.000458717346191} +Cheakpoint... +Epoch [996/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686649441719055, 'Val/mean miou_metric': 0.9491907358169556, 'Val/mean f1': 0.9713162183761597, 'Val/mean precision': 0.9667591452598572, 'Val/mean recall': 0.9759166240692139, 'Val/mean hd95_metric': 6.000458717346191} +Epoch [997/4000] Training [1/16] Loss: 0.00927 +Epoch [997/4000] Training [2/16] Loss: 0.01158 +Epoch [997/4000] Training [3/16] Loss: 0.01526 +Epoch [997/4000] Training [4/16] Loss: 0.01174 +Epoch [997/4000] Training [5/16] Loss: 0.01490 +Epoch [997/4000] Training [6/16] Loss: 0.01271 +Epoch [997/4000] Training [7/16] Loss: 0.01223 +Epoch [997/4000] Training [8/16] Loss: 0.01262 +Epoch [997/4000] Training [9/16] Loss: 0.01287 +Epoch [997/4000] Training [10/16] Loss: 0.00812 +Epoch [997/4000] Training [11/16] Loss: 0.02578 +Epoch [997/4000] Training [12/16] Loss: 0.01234 +Epoch [997/4000] Training [13/16] Loss: 0.01621 +Epoch [997/4000] Training [14/16] Loss: 0.01132 +Epoch [997/4000] Training [15/16] Loss: 0.01099 +Epoch [997/4000] Training [16/16] Loss: 0.01363 +Epoch [997/4000] Training metric {'Train/mean dice_metric': 0.9911015033721924, 'Train/mean miou_metric': 0.9821769595146179, 'Train/mean f1': 0.9879093766212463, 'Train/mean precision': 0.9832857847213745, 'Train/mean recall': 0.9925765991210938, 'Train/mean hd95_metric': 1.367189645767212} +Epoch [997/4000] Validation [1/4] Loss: 0.20354 focal_loss 0.13708 dice_loss 0.06646 +Epoch [997/4000] Validation [2/4] Loss: 0.47229 focal_loss 0.22773 dice_loss 0.24456 +Epoch [997/4000] Validation [3/4] Loss: 0.27331 focal_loss 0.17565 dice_loss 0.09766 +Epoch [997/4000] Validation [4/4] Loss: 0.28499 focal_loss 0.15272 dice_loss 0.13227 +Epoch [997/4000] Validation metric {'Val/mean dice_metric': 0.9686031341552734, 'Val/mean miou_metric': 0.9482248425483704, 'Val/mean f1': 0.9700819253921509, 'Val/mean precision': 0.9651452898979187, 'Val/mean recall': 0.9750694036483765, 'Val/mean hd95_metric': 6.294389247894287} +Cheakpoint... +Epoch [997/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686031341552734, 'Val/mean miou_metric': 0.9482248425483704, 'Val/mean f1': 0.9700819253921509, 'Val/mean precision': 0.9651452898979187, 'Val/mean recall': 0.9750694036483765, 'Val/mean hd95_metric': 6.294389247894287} +Epoch [998/4000] Training [1/16] Loss: 0.01214 +Epoch [998/4000] Training [2/16] Loss: 0.01471 +Epoch [998/4000] Training [3/16] Loss: 0.01342 +Epoch [998/4000] Training [4/16] Loss: 0.01276 +Epoch [998/4000] Training [5/16] Loss: 0.00972 +Epoch [998/4000] Training [6/16] Loss: 0.01133 +Epoch [998/4000] Training [7/16] Loss: 0.01627 +Epoch [998/4000] Training [8/16] Loss: 0.01195 +Epoch [998/4000] Training [9/16] Loss: 0.01409 +Epoch [998/4000] Training [10/16] Loss: 0.01279 +Epoch [998/4000] Training [11/16] Loss: 0.01201 +Epoch [998/4000] Training [12/16] Loss: 0.01234 +Epoch [998/4000] Training [13/16] Loss: 0.01051 +Epoch [998/4000] Training [14/16] Loss: 0.00790 +Epoch [998/4000] Training [15/16] Loss: 0.01195 +Epoch [998/4000] Training [16/16] Loss: 0.01075 +Epoch [998/4000] Training metric {'Train/mean dice_metric': 0.991759181022644, 'Train/mean miou_metric': 0.9834578037261963, 'Train/mean f1': 0.9884060621261597, 'Train/mean precision': 0.9839451909065247, 'Train/mean recall': 0.9929075837135315, 'Train/mean hd95_metric': 1.3362910747528076} +Epoch [998/4000] Validation [1/4] Loss: 0.14123 focal_loss 0.08142 dice_loss 0.05981 +Epoch [998/4000] Validation [2/4] Loss: 0.56099 focal_loss 0.32234 dice_loss 0.23864 +Epoch [998/4000] Validation [3/4] Loss: 0.25587 focal_loss 0.15377 dice_loss 0.10210 +Epoch [998/4000] Validation [4/4] Loss: 0.29201 focal_loss 0.15709 dice_loss 0.13492 +Epoch [998/4000] Validation metric {'Val/mean dice_metric': 0.968826174736023, 'Val/mean miou_metric': 0.9494132995605469, 'Val/mean f1': 0.9700047373771667, 'Val/mean precision': 0.9622833132743835, 'Val/mean recall': 0.9778510928153992, 'Val/mean hd95_metric': 6.741751194000244} +Cheakpoint... +Epoch [998/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968826174736023, 'Val/mean miou_metric': 0.9494132995605469, 'Val/mean f1': 0.9700047373771667, 'Val/mean precision': 0.9622833132743835, 'Val/mean recall': 0.9778510928153992, 'Val/mean hd95_metric': 6.741751194000244} +Epoch [999/4000] Training [1/16] Loss: 0.01164 +Epoch [999/4000] Training [2/16] Loss: 0.00904 +Epoch [999/4000] Training [3/16] Loss: 0.00886 +Epoch [999/4000] Training [4/16] Loss: 0.01216 +Epoch [999/4000] Training [5/16] Loss: 0.01538 +Epoch [999/4000] Training [6/16] Loss: 0.00956 +Epoch [999/4000] Training [7/16] Loss: 0.00854 +Epoch [999/4000] Training [8/16] Loss: 0.01332 +Epoch [999/4000] Training [9/16] Loss: 0.01110 +Epoch [999/4000] Training [10/16] Loss: 0.00870 +Epoch [999/4000] Training [11/16] Loss: 0.00947 +Epoch [999/4000] Training [12/16] Loss: 0.02371 +Epoch [999/4000] Training [13/16] Loss: 0.01462 +Epoch [999/4000] Training [14/16] Loss: 0.01277 +Epoch [999/4000] Training [15/16] Loss: 0.00831 +Epoch [999/4000] Training [16/16] Loss: 0.01206 +Epoch [999/4000] Training metric {'Train/mean dice_metric': 0.9921385049819946, 'Train/mean miou_metric': 0.9842221140861511, 'Train/mean f1': 0.9889035820960999, 'Train/mean precision': 0.9846304655075073, 'Train/mean recall': 0.993213951587677, 'Train/mean hd95_metric': 1.1678975820541382} +Epoch [999/4000] Validation [1/4] Loss: 0.19777 focal_loss 0.13307 dice_loss 0.06470 +Epoch [999/4000] Validation [2/4] Loss: 0.25086 focal_loss 0.12620 dice_loss 0.12466 +Epoch [999/4000] Validation [3/4] Loss: 0.26558 focal_loss 0.16682 dice_loss 0.09875 +Epoch [999/4000] Validation [4/4] Loss: 0.18983 focal_loss 0.09041 dice_loss 0.09942 +Epoch [999/4000] Validation metric {'Val/mean dice_metric': 0.9718558192253113, 'Val/mean miou_metric': 0.9529336094856262, 'Val/mean f1': 0.9739763140678406, 'Val/mean precision': 0.9701617360115051, 'Val/mean recall': 0.9778207540512085, 'Val/mean hd95_metric': 5.687644958496094} +Cheakpoint... +Epoch [999/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718558192253113, 'Val/mean miou_metric': 0.9529336094856262, 'Val/mean f1': 0.9739763140678406, 'Val/mean precision': 0.9701617360115051, 'Val/mean recall': 0.9778207540512085, 'Val/mean hd95_metric': 5.687644958496094} +Epoch [1000/4000] Training [1/16] Loss: 0.01401 +Epoch [1000/4000] Training [2/16] Loss: 0.01177 +Epoch [1000/4000] Training [3/16] Loss: 0.01194 +Epoch [1000/4000] Training [4/16] Loss: 0.01525 +Epoch [1000/4000] Training [5/16] Loss: 0.00977 +Epoch [1000/4000] Training [6/16] Loss: 0.00877 +Epoch [1000/4000] Training [7/16] Loss: 0.01307 +Epoch [1000/4000] Training [8/16] Loss: 0.00986 +Epoch [1000/4000] Training [9/16] Loss: 0.00825 +Epoch [1000/4000] Training [10/16] Loss: 0.01193 +Epoch [1000/4000] Training [11/16] Loss: 0.01209 +Epoch [1000/4000] Training [12/16] Loss: 0.00854 +Epoch [1000/4000] Training [13/16] Loss: 0.01099 +Epoch [1000/4000] Training [14/16] Loss: 0.00945 +Epoch [1000/4000] Training [15/16] Loss: 0.01292 +Epoch [1000/4000] Training [16/16] Loss: 0.01589 +Epoch [1000/4000] Training metric {'Train/mean dice_metric': 0.9922158718109131, 'Train/mean miou_metric': 0.984305202960968, 'Train/mean f1': 0.9883384108543396, 'Train/mean precision': 0.9831620454788208, 'Train/mean recall': 0.9935696125030518, 'Train/mean hd95_metric': 1.7398924827575684} +Epoch [1000/4000] Validation [1/4] Loss: 0.18317 focal_loss 0.11859 dice_loss 0.06458 +Epoch [1000/4000] Validation [2/4] Loss: 0.24995 focal_loss 0.11844 dice_loss 0.13151 +Epoch [1000/4000] Validation [3/4] Loss: 0.18555 focal_loss 0.10052 dice_loss 0.08503 +Epoch [1000/4000] Validation [4/4] Loss: 0.18333 focal_loss 0.09278 dice_loss 0.09055 +Epoch [1000/4000] Validation metric {'Val/mean dice_metric': 0.9703081250190735, 'Val/mean miou_metric': 0.9515830278396606, 'Val/mean f1': 0.9724793434143066, 'Val/mean precision': 0.9660084843635559, 'Val/mean recall': 0.9790374040603638, 'Val/mean hd95_metric': 6.387353420257568} +Cheakpoint... +Epoch [1000/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703081250190735, 'Val/mean miou_metric': 0.9515830278396606, 'Val/mean f1': 0.9724793434143066, 'Val/mean precision': 0.9660084843635559, 'Val/mean recall': 0.9790374040603638, 'Val/mean hd95_metric': 6.387353420257568} +Epoch [1001/4000] Training [1/16] Loss: 0.01119 +Epoch [1001/4000] Training [2/16] Loss: 0.01093 +Epoch [1001/4000] Training [3/16] Loss: 0.00925 +Epoch [1001/4000] Training [4/16] Loss: 0.00960 +Epoch [1001/4000] Training [5/16] Loss: 0.01323 +Epoch [1001/4000] Training [6/16] Loss: 0.01367 +Epoch [1001/4000] Training [7/16] Loss: 0.00911 +Epoch [1001/4000] Training [8/16] Loss: 0.00884 +Epoch [1001/4000] Training [9/16] Loss: 0.00823 +Epoch [1001/4000] Training [10/16] Loss: 0.01430 +Epoch [1001/4000] Training [11/16] Loss: 0.01725 +Epoch [1001/4000] Training [12/16] Loss: 0.01439 +Epoch [1001/4000] Training [13/16] Loss: 0.01660 +Epoch [1001/4000] Training [14/16] Loss: 0.01018 +Epoch [1001/4000] Training [15/16] Loss: 0.01007 +Epoch [1001/4000] Training [16/16] Loss: 0.01215 +Epoch [1001/4000] Training metric {'Train/mean dice_metric': 0.9918786287307739, 'Train/mean miou_metric': 0.9837062358856201, 'Train/mean f1': 0.9887264370918274, 'Train/mean precision': 0.9842122793197632, 'Train/mean recall': 0.9932821393013, 'Train/mean hd95_metric': 1.28580904006958} +Epoch [1001/4000] Validation [1/4] Loss: 0.15869 focal_loss 0.09455 dice_loss 0.06414 +Epoch [1001/4000] Validation [2/4] Loss: 0.40134 focal_loss 0.21952 dice_loss 0.18181 +Epoch [1001/4000] Validation [3/4] Loss: 0.27597 focal_loss 0.16925 dice_loss 0.10671 +Epoch [1001/4000] Validation [4/4] Loss: 0.24383 focal_loss 0.11876 dice_loss 0.12508 +Epoch [1001/4000] Validation metric {'Val/mean dice_metric': 0.9685361981391907, 'Val/mean miou_metric': 0.9492985010147095, 'Val/mean f1': 0.9720592498779297, 'Val/mean precision': 0.969009280204773, 'Val/mean recall': 0.9751283526420593, 'Val/mean hd95_metric': 6.097433567047119} +Cheakpoint... +Epoch [1001/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9685361981391907, 'Val/mean miou_metric': 0.9492985010147095, 'Val/mean f1': 0.9720592498779297, 'Val/mean precision': 0.969009280204773, 'Val/mean recall': 0.9751283526420593, 'Val/mean hd95_metric': 6.097433567047119} +Epoch [1002/4000] Training [1/16] Loss: 0.01112 +Epoch [1002/4000] Training [2/16] Loss: 0.00950 +Epoch [1002/4000] Training [3/16] Loss: 0.01164 +Epoch [1002/4000] Training [4/16] Loss: 0.01140 +Epoch [1002/4000] Training [5/16] Loss: 0.02209 +Epoch [1002/4000] Training [6/16] Loss: 0.01808 +Epoch [1002/4000] Training [7/16] Loss: 0.01513 +Epoch [1002/4000] Training [8/16] Loss: 0.01587 +Epoch [1002/4000] Training [9/16] Loss: 0.01244 +Epoch [1002/4000] Training [10/16] Loss: 0.01110 +Epoch [1002/4000] Training [11/16] Loss: 0.01363 +Epoch [1002/4000] Training [12/16] Loss: 0.01343 +Epoch [1002/4000] Training [13/16] Loss: 0.01319 +Epoch [1002/4000] Training [14/16] Loss: 0.01164 +Epoch [1002/4000] Training [15/16] Loss: 0.00937 +Epoch [1002/4000] Training [16/16] Loss: 0.01202 +Epoch [1002/4000] Training metric {'Train/mean dice_metric': 0.9910440444946289, 'Train/mean miou_metric': 0.9823180437088013, 'Train/mean f1': 0.9872553944587708, 'Train/mean precision': 0.9824419021606445, 'Train/mean recall': 0.992116391658783, 'Train/mean hd95_metric': 1.3342397212982178} +Epoch [1002/4000] Validation [1/4] Loss: 0.18450 focal_loss 0.12222 dice_loss 0.06228 +Epoch [1002/4000] Validation [2/4] Loss: 0.42365 focal_loss 0.20839 dice_loss 0.21526 +Epoch [1002/4000] Validation [3/4] Loss: 0.42775 focal_loss 0.29254 dice_loss 0.13521 +Epoch [1002/4000] Validation [4/4] Loss: 0.24812 focal_loss 0.11264 dice_loss 0.13548 +Epoch [1002/4000] Validation metric {'Val/mean dice_metric': 0.9667003750801086, 'Val/mean miou_metric': 0.945885181427002, 'Val/mean f1': 0.9686764478683472, 'Val/mean precision': 0.9616997241973877, 'Val/mean recall': 0.9757551550865173, 'Val/mean hd95_metric': 6.256591320037842} +Cheakpoint... +Epoch [1002/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667003750801086, 'Val/mean miou_metric': 0.945885181427002, 'Val/mean f1': 0.9686764478683472, 'Val/mean precision': 0.9616997241973877, 'Val/mean recall': 0.9757551550865173, 'Val/mean hd95_metric': 6.256591320037842} +Epoch [1003/4000] Training [1/16] Loss: 0.01076 +Epoch [1003/4000] Training [2/16] Loss: 0.01390 +Epoch [1003/4000] Training [3/16] Loss: 0.01556 +Epoch [1003/4000] Training [4/16] Loss: 0.01403 +Epoch [1003/4000] Training [5/16] Loss: 0.00914 +Epoch [1003/4000] Training [6/16] Loss: 0.01138 +Epoch [1003/4000] Training [7/16] Loss: 0.01009 +Epoch [1003/4000] Training [8/16] Loss: 0.03016 +Epoch [1003/4000] Training [9/16] Loss: 0.01209 +Epoch [1003/4000] Training [10/16] Loss: 0.00912 +Epoch [1003/4000] Training [11/16] Loss: 0.01293 +Epoch [1003/4000] Training [12/16] Loss: 0.01161 +Epoch [1003/4000] Training [13/16] Loss: 0.01440 +Epoch [1003/4000] Training [14/16] Loss: 0.01097 +Epoch [1003/4000] Training [15/16] Loss: 0.01726 +Epoch [1003/4000] Training [16/16] Loss: 0.00841 +Epoch [1003/4000] Training metric {'Train/mean dice_metric': 0.991140604019165, 'Train/mean miou_metric': 0.9822799563407898, 'Train/mean f1': 0.9879492521286011, 'Train/mean precision': 0.9835348725318909, 'Train/mean recall': 0.992403507232666, 'Train/mean hd95_metric': 1.3824487924575806} +Epoch [1003/4000] Validation [1/4] Loss: 0.32173 focal_loss 0.20214 dice_loss 0.11959 +Epoch [1003/4000] Validation [2/4] Loss: 0.54745 focal_loss 0.30479 dice_loss 0.24266 +Epoch [1003/4000] Validation [3/4] Loss: 0.28692 focal_loss 0.18352 dice_loss 0.10339 +Epoch [1003/4000] Validation [4/4] Loss: 0.26811 focal_loss 0.14193 dice_loss 0.12618 +Epoch [1003/4000] Validation metric {'Val/mean dice_metric': 0.9665887951850891, 'Val/mean miou_metric': 0.9458802938461304, 'Val/mean f1': 0.970048189163208, 'Val/mean precision': 0.9700608849525452, 'Val/mean recall': 0.9700354337692261, 'Val/mean hd95_metric': 6.254075527191162} +Cheakpoint... +Epoch [1003/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665887951850891, 'Val/mean miou_metric': 0.9458802938461304, 'Val/mean f1': 0.970048189163208, 'Val/mean precision': 0.9700608849525452, 'Val/mean recall': 0.9700354337692261, 'Val/mean hd95_metric': 6.254075527191162} +Epoch [1004/4000] Training [1/16] Loss: 0.01587 +Epoch [1004/4000] Training [2/16] Loss: 0.01297 +Epoch [1004/4000] Training [3/16] Loss: 0.01912 +Epoch [1004/4000] Training [4/16] Loss: 0.00922 +Epoch [1004/4000] Training [5/16] Loss: 0.01472 +Epoch [1004/4000] Training [6/16] Loss: 0.03168 +Epoch [1004/4000] Training [7/16] Loss: 0.01627 +Epoch [1004/4000] Training [8/16] Loss: 0.01709 +Epoch [1004/4000] Training [9/16] Loss: 0.02167 +Epoch [1004/4000] Training [10/16] Loss: 0.01135 +Epoch [1004/4000] Training [11/16] Loss: 0.00921 +Epoch [1004/4000] Training [12/16] Loss: 0.01024 +Epoch [1004/4000] Training [13/16] Loss: 0.01454 +Epoch [1004/4000] Training [14/16] Loss: 0.01454 +Epoch [1004/4000] Training [15/16] Loss: 0.01432 +Epoch [1004/4000] Training [16/16] Loss: 0.01226 +Epoch [1004/4000] Training metric {'Train/mean dice_metric': 0.9897435903549194, 'Train/mean miou_metric': 0.9798450469970703, 'Train/mean f1': 0.9861981868743896, 'Train/mean precision': 0.981037974357605, 'Train/mean recall': 0.9914129972457886, 'Train/mean hd95_metric': 2.249317169189453} +Epoch [1004/4000] Validation [1/4] Loss: 0.17004 focal_loss 0.10946 dice_loss 0.06059 +Epoch [1004/4000] Validation [2/4] Loss: 0.52219 focal_loss 0.26779 dice_loss 0.25441 +Epoch [1004/4000] Validation [3/4] Loss: 0.18895 focal_loss 0.09528 dice_loss 0.09367 +Epoch [1004/4000] Validation [4/4] Loss: 0.18895 focal_loss 0.09117 dice_loss 0.09778 +Epoch [1004/4000] Validation metric {'Val/mean dice_metric': 0.9660261273384094, 'Val/mean miou_metric': 0.9448725581169128, 'Val/mean f1': 0.9700576066970825, 'Val/mean precision': 0.965974748134613, 'Val/mean recall': 0.9741750955581665, 'Val/mean hd95_metric': 6.664935111999512} +Cheakpoint... +Epoch [1004/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660261273384094, 'Val/mean miou_metric': 0.9448725581169128, 'Val/mean f1': 0.9700576066970825, 'Val/mean precision': 0.965974748134613, 'Val/mean recall': 0.9741750955581665, 'Val/mean hd95_metric': 6.664935111999512} +Epoch [1005/4000] Training [1/16] Loss: 0.01483 +Epoch [1005/4000] Training [2/16] Loss: 0.03513 +Epoch [1005/4000] Training [3/16] Loss: 0.01001 +Epoch [1005/4000] Training [4/16] Loss: 0.01028 +Epoch [1005/4000] Training [5/16] Loss: 0.01087 +Epoch [1005/4000] Training [6/16] Loss: 0.01536 +Epoch [1005/4000] Training [7/16] Loss: 0.01070 +Epoch [1005/4000] Training [8/16] Loss: 0.01065 +Epoch [1005/4000] Training [9/16] Loss: 0.01415 +Epoch [1005/4000] Training [10/16] Loss: 0.00971 +Epoch [1005/4000] Training [11/16] Loss: 0.02378 +Epoch [1005/4000] Training [12/16] Loss: 0.01058 +Epoch [1005/4000] Training [13/16] Loss: 0.01142 +Epoch [1005/4000] Training [14/16] Loss: 0.01338 +Epoch [1005/4000] Training [15/16] Loss: 0.01844 +Epoch [1005/4000] Training [16/16] Loss: 0.01059 +Epoch [1005/4000] Training metric {'Train/mean dice_metric': 0.9903839826583862, 'Train/mean miou_metric': 0.9808680415153503, 'Train/mean f1': 0.9870352745056152, 'Train/mean precision': 0.982721745967865, 'Train/mean recall': 0.991386890411377, 'Train/mean hd95_metric': 1.6495869159698486} +Epoch [1005/4000] Validation [1/4] Loss: 0.21026 focal_loss 0.13785 dice_loss 0.07241 +Epoch [1005/4000] Validation [2/4] Loss: 0.25333 focal_loss 0.12095 dice_loss 0.13238 +Epoch [1005/4000] Validation [3/4] Loss: 0.26182 focal_loss 0.16026 dice_loss 0.10157 +Epoch [1005/4000] Validation [4/4] Loss: 0.42270 focal_loss 0.27075 dice_loss 0.15195 +Epoch [1005/4000] Validation metric {'Val/mean dice_metric': 0.9674335718154907, 'Val/mean miou_metric': 0.9460426568984985, 'Val/mean f1': 0.9694515466690063, 'Val/mean precision': 0.9697965979576111, 'Val/mean recall': 0.9691067934036255, 'Val/mean hd95_metric': 5.990899562835693} +Cheakpoint... +Epoch [1005/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674335718154907, 'Val/mean miou_metric': 0.9460426568984985, 'Val/mean f1': 0.9694515466690063, 'Val/mean precision': 0.9697965979576111, 'Val/mean recall': 0.9691067934036255, 'Val/mean hd95_metric': 5.990899562835693} +Epoch [1006/4000] Training [1/16] Loss: 0.01981 +Epoch [1006/4000] Training [2/16] Loss: 0.01673 +Epoch [1006/4000] Training [3/16] Loss: 0.01593 +Epoch [1006/4000] Training [4/16] Loss: 0.01372 +Epoch [1006/4000] Training [5/16] Loss: 0.01173 +Epoch [1006/4000] Training [6/16] Loss: 0.01433 +Epoch [1006/4000] Training [7/16] Loss: 0.01266 +Epoch [1006/4000] Training [8/16] Loss: 0.01130 +Epoch [1006/4000] Training [9/16] Loss: 0.02209 +Epoch [1006/4000] Training [10/16] Loss: 0.01071 +Epoch [1006/4000] Training [11/16] Loss: 0.01368 +Epoch [1006/4000] Training [12/16] Loss: 0.01177 +Epoch [1006/4000] Training [13/16] Loss: 0.01176 +Epoch [1006/4000] Training [14/16] Loss: 0.01137 +Epoch [1006/4000] Training [15/16] Loss: 0.01684 +Epoch [1006/4000] Training [16/16] Loss: 0.01254 +Epoch [1006/4000] Training metric {'Train/mean dice_metric': 0.98628169298172, 'Train/mean miou_metric': 0.9749876856803894, 'Train/mean f1': 0.9820483922958374, 'Train/mean precision': 0.9759295582771301, 'Train/mean recall': 0.9882444739341736, 'Train/mean hd95_metric': 3.1593129634857178} +Epoch [1006/4000] Validation [1/4] Loss: 0.19613 focal_loss 0.12645 dice_loss 0.06967 +Epoch [1006/4000] Validation [2/4] Loss: 0.25435 focal_loss 0.10930 dice_loss 0.14505 +Epoch [1006/4000] Validation [3/4] Loss: 0.43308 focal_loss 0.28749 dice_loss 0.14559 +Epoch [1006/4000] Validation [4/4] Loss: 0.25604 focal_loss 0.12011 dice_loss 0.13592 +Epoch [1006/4000] Validation metric {'Val/mean dice_metric': 0.9599195718765259, 'Val/mean miou_metric': 0.9360753893852234, 'Val/mean f1': 0.9597333073616028, 'Val/mean precision': 0.9481366276741028, 'Val/mean recall': 0.9716171622276306, 'Val/mean hd95_metric': 9.874173164367676} +Cheakpoint... +Epoch [1006/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9599], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599195718765259, 'Val/mean miou_metric': 0.9360753893852234, 'Val/mean f1': 0.9597333073616028, 'Val/mean precision': 0.9481366276741028, 'Val/mean recall': 0.9716171622276306, 'Val/mean hd95_metric': 9.874173164367676} +Epoch [1007/4000] Training [1/16] Loss: 0.01187 +Epoch [1007/4000] Training [2/16] Loss: 0.01549 +Epoch [1007/4000] Training [3/16] Loss: 0.01469 +Epoch [1007/4000] Training [4/16] Loss: 0.02119 +Epoch [1007/4000] Training [5/16] Loss: 0.02591 +Epoch [1007/4000] Training [6/16] Loss: 0.01583 +Epoch [1007/4000] Training [7/16] Loss: 0.01625 +Epoch [1007/4000] Training [8/16] Loss: 0.02200 +Epoch [1007/4000] Training [9/16] Loss: 0.02091 +Epoch [1007/4000] Training [10/16] Loss: 0.02408 +Epoch [1007/4000] Training [11/16] Loss: 0.01803 +Epoch [1007/4000] Training [12/16] Loss: 0.01978 +Epoch [1007/4000] Training [13/16] Loss: 0.01652 +Epoch [1007/4000] Training [14/16] Loss: 0.01475 +Epoch [1007/4000] Training [15/16] Loss: 0.02205 +Epoch [1007/4000] Training [16/16] Loss: 0.01613 +Epoch [1007/4000] Training metric {'Train/mean dice_metric': 0.987769603729248, 'Train/mean miou_metric': 0.9758476614952087, 'Train/mean f1': 0.9832314848899841, 'Train/mean precision': 0.9812275171279907, 'Train/mean recall': 0.9852437376976013, 'Train/mean hd95_metric': 3.930352210998535} +Epoch [1007/4000] Validation [1/4] Loss: 0.23832 focal_loss 0.14510 dice_loss 0.09322 +Epoch [1007/4000] Validation [2/4] Loss: 0.52113 focal_loss 0.27808 dice_loss 0.24305 +Epoch [1007/4000] Validation [3/4] Loss: 0.27731 focal_loss 0.17824 dice_loss 0.09907 +Epoch [1007/4000] Validation [4/4] Loss: 0.28673 focal_loss 0.16980 dice_loss 0.11693 +Epoch [1007/4000] Validation metric {'Val/mean dice_metric': 0.9631019830703735, 'Val/mean miou_metric': 0.9391347765922546, 'Val/mean f1': 0.9644607305526733, 'Val/mean precision': 0.9669978618621826, 'Val/mean recall': 0.9619370102882385, 'Val/mean hd95_metric': 8.926443099975586} +Cheakpoint... +Epoch [1007/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9631], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631019830703735, 'Val/mean miou_metric': 0.9391347765922546, 'Val/mean f1': 0.9644607305526733, 'Val/mean precision': 0.9669978618621826, 'Val/mean recall': 0.9619370102882385, 'Val/mean hd95_metric': 8.926443099975586} +Epoch [1008/4000] Training [1/16] Loss: 0.01762 +Epoch [1008/4000] Training [2/16] Loss: 0.01751 +Epoch [1008/4000] Training [3/16] Loss: 0.01746 +Epoch [1008/4000] Training [4/16] Loss: 0.01479 +Epoch [1008/4000] Training [5/16] Loss: 0.01169 +Epoch [1008/4000] Training [6/16] Loss: 0.01561 +Epoch [1008/4000] Training [7/16] Loss: 0.04572 +Epoch [1008/4000] Training [8/16] Loss: 0.02194 +Epoch [1008/4000] Training [9/16] Loss: 0.01568 +Epoch [1008/4000] Training [10/16] Loss: 0.02911 +Epoch [1008/4000] Training [11/16] Loss: 0.01191 +Epoch [1008/4000] Training [12/16] Loss: 0.01293 +Epoch [1008/4000] Training [13/16] Loss: 0.01744 +Epoch [1008/4000] Training [14/16] Loss: 0.01613 +Epoch [1008/4000] Training [15/16] Loss: 0.01411 +Epoch [1008/4000] Training [16/16] Loss: 0.01599 +Epoch [1008/4000] Training metric {'Train/mean dice_metric': 0.9881844520568848, 'Train/mean miou_metric': 0.9767507314682007, 'Train/mean f1': 0.983791708946228, 'Train/mean precision': 0.9769906401634216, 'Train/mean recall': 0.9906880855560303, 'Train/mean hd95_metric': 2.69122314453125} +Epoch [1008/4000] Validation [1/4] Loss: 0.63571 focal_loss 0.44217 dice_loss 0.19355 +Epoch [1008/4000] Validation [2/4] Loss: 0.38280 focal_loss 0.14577 dice_loss 0.23702 +Epoch [1008/4000] Validation [3/4] Loss: 0.30076 focal_loss 0.19095 dice_loss 0.10981 +Epoch [1008/4000] Validation [4/4] Loss: 0.36169 focal_loss 0.21424 dice_loss 0.14745 +Epoch [1008/4000] Validation metric {'Val/mean dice_metric': 0.9617210626602173, 'Val/mean miou_metric': 0.9377012252807617, 'Val/mean f1': 0.9619638323783875, 'Val/mean precision': 0.9604511857032776, 'Val/mean recall': 0.9634811878204346, 'Val/mean hd95_metric': 9.228093147277832} +Cheakpoint... +Epoch [1008/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9617210626602173, 'Val/mean miou_metric': 0.9377012252807617, 'Val/mean f1': 0.9619638323783875, 'Val/mean precision': 0.9604511857032776, 'Val/mean recall': 0.9634811878204346, 'Val/mean hd95_metric': 9.228093147277832} +Epoch [1009/4000] Training [1/16] Loss: 0.01373 +Epoch [1009/4000] Training [2/16] Loss: 0.01195 +Epoch [1009/4000] Training [3/16] Loss: 0.01395 +Epoch [1009/4000] Training [4/16] Loss: 0.01384 +Epoch [1009/4000] Training [5/16] Loss: 0.02208 +Epoch [1009/4000] Training [6/16] Loss: 0.01250 +Epoch [1009/4000] Training [7/16] Loss: 0.01423 +Epoch [1009/4000] Training [8/16] Loss: 0.01416 +Epoch [1009/4000] Training [9/16] Loss: 0.01135 +Epoch [1009/4000] Training [10/16] Loss: 0.01382 +Epoch [1009/4000] Training [11/16] Loss: 0.02401 +Epoch [1009/4000] Training [12/16] Loss: 0.01041 +Epoch [1009/4000] Training [13/16] Loss: 0.01230 +Epoch [1009/4000] Training [14/16] Loss: 0.01809 +Epoch [1009/4000] Training [15/16] Loss: 0.01283 +Epoch [1009/4000] Training [16/16] Loss: 0.01136 +Epoch [1009/4000] Training metric {'Train/mean dice_metric': 0.9898806810379028, 'Train/mean miou_metric': 0.9797865152359009, 'Train/mean f1': 0.9860044717788696, 'Train/mean precision': 0.9813469648361206, 'Train/mean recall': 0.9907063841819763, 'Train/mean hd95_metric': 1.7618389129638672} +Epoch [1009/4000] Validation [1/4] Loss: 0.41258 focal_loss 0.27141 dice_loss 0.14117 +Epoch [1009/4000] Validation [2/4] Loss: 0.28244 focal_loss 0.12176 dice_loss 0.16068 +Epoch [1009/4000] Validation [3/4] Loss: 0.30709 focal_loss 0.19653 dice_loss 0.11056 +Epoch [1009/4000] Validation [4/4] Loss: 0.33837 focal_loss 0.18479 dice_loss 0.15359 +Epoch [1009/4000] Validation metric {'Val/mean dice_metric': 0.9646800756454468, 'Val/mean miou_metric': 0.9413968324661255, 'Val/mean f1': 0.9648837447166443, 'Val/mean precision': 0.9646758437156677, 'Val/mean recall': 0.9650916457176208, 'Val/mean hd95_metric': 7.171048641204834} +Cheakpoint... +Epoch [1009/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646800756454468, 'Val/mean miou_metric': 0.9413968324661255, 'Val/mean f1': 0.9648837447166443, 'Val/mean precision': 0.9646758437156677, 'Val/mean recall': 0.9650916457176208, 'Val/mean hd95_metric': 7.171048641204834} +Epoch [1010/4000] Training [1/16] Loss: 0.00943 +Epoch [1010/4000] Training [2/16] Loss: 0.01211 +Epoch [1010/4000] Training [3/16] Loss: 0.01228 +Epoch [1010/4000] Training [4/16] Loss: 0.01819 +Epoch [1010/4000] Training [5/16] Loss: 0.00983 +Epoch [1010/4000] Training [6/16] Loss: 0.00995 +Epoch [1010/4000] Training [7/16] Loss: 0.02551 +Epoch [1010/4000] Training [8/16] Loss: 0.01173 +Epoch [1010/4000] Training [9/16] Loss: 0.01191 +Epoch [1010/4000] Training [10/16] Loss: 0.01165 +Epoch [1010/4000] Training [11/16] Loss: 0.01262 +Epoch [1010/4000] Training [12/16] Loss: 0.01335 +Epoch [1010/4000] Training [13/16] Loss: 0.01166 +Epoch [1010/4000] Training [14/16] Loss: 0.01265 +Epoch [1010/4000] Training [15/16] Loss: 0.01406 +Epoch [1010/4000] Training [16/16] Loss: 0.01206 +Epoch [1010/4000] Training metric {'Train/mean dice_metric': 0.9912737607955933, 'Train/mean miou_metric': 0.9825248718261719, 'Train/mean f1': 0.9875022172927856, 'Train/mean precision': 0.9830572605133057, 'Train/mean recall': 0.9919875264167786, 'Train/mean hd95_metric': 1.413283348083496} +Epoch [1010/4000] Validation [1/4] Loss: 0.21416 focal_loss 0.11799 dice_loss 0.09617 +Epoch [1010/4000] Validation [2/4] Loss: 0.36713 focal_loss 0.15151 dice_loss 0.21562 +Epoch [1010/4000] Validation [3/4] Loss: 0.29472 focal_loss 0.17609 dice_loss 0.11862 +Epoch [1010/4000] Validation [4/4] Loss: 0.34107 focal_loss 0.18620 dice_loss 0.15487 +Epoch [1010/4000] Validation metric {'Val/mean dice_metric': 0.96503746509552, 'Val/mean miou_metric': 0.9439002871513367, 'Val/mean f1': 0.9686068296432495, 'Val/mean precision': 0.9674205183982849, 'Val/mean recall': 0.9697959423065186, 'Val/mean hd95_metric': 6.274234771728516} +Cheakpoint... +Epoch [1010/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96503746509552, 'Val/mean miou_metric': 0.9439002871513367, 'Val/mean f1': 0.9686068296432495, 'Val/mean precision': 0.9674205183982849, 'Val/mean recall': 0.9697959423065186, 'Val/mean hd95_metric': 6.274234771728516} +Epoch [1011/4000] Training [1/16] Loss: 0.01277 +Epoch [1011/4000] Training [2/16] Loss: 0.01391 +Epoch [1011/4000] Training [3/16] Loss: 0.00917 +Epoch [1011/4000] Training [4/16] Loss: 0.01192 +Epoch [1011/4000] Training [5/16] Loss: 0.00895 +Epoch [1011/4000] Training [6/16] Loss: 0.00888 +Epoch [1011/4000] Training [7/16] Loss: 0.01407 +Epoch [1011/4000] Training [8/16] Loss: 0.01140 +Epoch [1011/4000] Training [9/16] Loss: 0.01155 +Epoch [1011/4000] Training [10/16] Loss: 0.01248 +Epoch [1011/4000] Training [11/16] Loss: 0.01077 +Epoch [1011/4000] Training [12/16] Loss: 0.00927 +Epoch [1011/4000] Training [13/16] Loss: 0.01197 +Epoch [1011/4000] Training [14/16] Loss: 0.01331 +Epoch [1011/4000] Training [15/16] Loss: 0.01180 +Epoch [1011/4000] Training [16/16] Loss: 0.00997 +Epoch [1011/4000] Training metric {'Train/mean dice_metric': 0.9913976192474365, 'Train/mean miou_metric': 0.9831465482711792, 'Train/mean f1': 0.9880420565605164, 'Train/mean precision': 0.9837899208068848, 'Train/mean recall': 0.9923311471939087, 'Train/mean hd95_metric': 1.3387691974639893} +Epoch [1011/4000] Validation [1/4] Loss: 0.61667 focal_loss 0.44667 dice_loss 0.17000 +Epoch [1011/4000] Validation [2/4] Loss: 0.49699 focal_loss 0.25581 dice_loss 0.24117 +Epoch [1011/4000] Validation [3/4] Loss: 0.27997 focal_loss 0.18180 dice_loss 0.09817 +Epoch [1011/4000] Validation [4/4] Loss: 0.25457 focal_loss 0.12989 dice_loss 0.12469 +Epoch [1011/4000] Validation metric {'Val/mean dice_metric': 0.9662460088729858, 'Val/mean miou_metric': 0.9464969635009766, 'Val/mean f1': 0.9689825177192688, 'Val/mean precision': 0.9673610925674438, 'Val/mean recall': 0.970609188079834, 'Val/mean hd95_metric': 6.006181716918945} +Cheakpoint... +Epoch [1011/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662460088729858, 'Val/mean miou_metric': 0.9464969635009766, 'Val/mean f1': 0.9689825177192688, 'Val/mean precision': 0.9673610925674438, 'Val/mean recall': 0.970609188079834, 'Val/mean hd95_metric': 6.006181716918945} +Epoch [1012/4000] Training [1/16] Loss: 0.01323 +Epoch [1012/4000] Training [2/16] Loss: 0.01134 +Epoch [1012/4000] Training [3/16] Loss: 0.01064 +Epoch [1012/4000] Training [4/16] Loss: 0.01447 +Epoch [1012/4000] Training [5/16] Loss: 0.01308 +Epoch [1012/4000] Training [6/16] Loss: 0.01412 +Epoch [1012/4000] Training [7/16] Loss: 0.01020 +Epoch [1012/4000] Training [8/16] Loss: 0.01329 +Epoch [1012/4000] Training [9/16] Loss: 0.01058 +Epoch [1012/4000] Training [10/16] Loss: 0.01397 +Epoch [1012/4000] Training [11/16] Loss: 0.02679 +Epoch [1012/4000] Training [12/16] Loss: 0.01377 +Epoch [1012/4000] Training [13/16] Loss: 0.01930 +Epoch [1012/4000] Training [14/16] Loss: 0.01264 +Epoch [1012/4000] Training [15/16] Loss: 0.01079 +Epoch [1012/4000] Training [16/16] Loss: 0.01096 +Epoch [1012/4000] Training metric {'Train/mean dice_metric': 0.9911801218986511, 'Train/mean miou_metric': 0.9823290109634399, 'Train/mean f1': 0.9875430464744568, 'Train/mean precision': 0.9826428890228271, 'Train/mean recall': 0.9924922585487366, 'Train/mean hd95_metric': 1.3270750045776367} +Epoch [1012/4000] Validation [1/4] Loss: 0.16522 focal_loss 0.09776 dice_loss 0.06747 +Epoch [1012/4000] Validation [2/4] Loss: 0.37090 focal_loss 0.13864 dice_loss 0.23226 +Epoch [1012/4000] Validation [3/4] Loss: 0.23782 focal_loss 0.12727 dice_loss 0.11054 +Epoch [1012/4000] Validation [4/4] Loss: 0.25175 focal_loss 0.12233 dice_loss 0.12941 +Epoch [1012/4000] Validation metric {'Val/mean dice_metric': 0.9640023112297058, 'Val/mean miou_metric': 0.9432357549667358, 'Val/mean f1': 0.9675743579864502, 'Val/mean precision': 0.9604784250259399, 'Val/mean recall': 0.9747759699821472, 'Val/mean hd95_metric': 7.345677375793457} +Cheakpoint... +Epoch [1012/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640023112297058, 'Val/mean miou_metric': 0.9432357549667358, 'Val/mean f1': 0.9675743579864502, 'Val/mean precision': 0.9604784250259399, 'Val/mean recall': 0.9747759699821472, 'Val/mean hd95_metric': 7.345677375793457} +Epoch [1013/4000] Training [1/16] Loss: 0.01045 +Epoch [1013/4000] Training [2/16] Loss: 0.00819 +Epoch [1013/4000] Training [3/16] Loss: 0.01072 +Epoch [1013/4000] Training [4/16] Loss: 0.01271 +Epoch [1013/4000] Training [5/16] Loss: 0.01551 +Epoch [1013/4000] Training [6/16] Loss: 0.01363 +Epoch [1013/4000] Training [7/16] Loss: 0.01153 +Epoch [1013/4000] Training [8/16] Loss: 0.01485 +Epoch [1013/4000] Training [9/16] Loss: 0.01197 +Epoch [1013/4000] Training [10/16] Loss: 0.00930 +Epoch [1013/4000] Training [11/16] Loss: 0.01528 +Epoch [1013/4000] Training [12/16] Loss: 0.00983 +Epoch [1013/4000] Training [13/16] Loss: 0.01278 +Epoch [1013/4000] Training [14/16] Loss: 0.01373 +Epoch [1013/4000] Training [15/16] Loss: 0.00973 +Epoch [1013/4000] Training [16/16] Loss: 0.01477 +Epoch [1013/4000] Training metric {'Train/mean dice_metric': 0.9915081262588501, 'Train/mean miou_metric': 0.9829332828521729, 'Train/mean f1': 0.987089991569519, 'Train/mean precision': 0.9818486571311951, 'Train/mean recall': 0.9923876523971558, 'Train/mean hd95_metric': 1.4991471767425537} +Epoch [1013/4000] Validation [1/4] Loss: 0.52096 focal_loss 0.37609 dice_loss 0.14487 +Epoch [1013/4000] Validation [2/4] Loss: 0.33781 focal_loss 0.13896 dice_loss 0.19885 +Epoch [1013/4000] Validation [3/4] Loss: 0.26671 focal_loss 0.16023 dice_loss 0.10649 +Epoch [1013/4000] Validation [4/4] Loss: 0.24702 focal_loss 0.12072 dice_loss 0.12629 +Epoch [1013/4000] Validation metric {'Val/mean dice_metric': 0.9661604762077332, 'Val/mean miou_metric': 0.9452544450759888, 'Val/mean f1': 0.9672049880027771, 'Val/mean precision': 0.9626451134681702, 'Val/mean recall': 0.9718084931373596, 'Val/mean hd95_metric': 7.170016288757324} +Cheakpoint... +Epoch [1013/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661604762077332, 'Val/mean miou_metric': 0.9452544450759888, 'Val/mean f1': 0.9672049880027771, 'Val/mean precision': 0.9626451134681702, 'Val/mean recall': 0.9718084931373596, 'Val/mean hd95_metric': 7.170016288757324} +Epoch [1014/4000] Training [1/16] Loss: 0.00997 +Epoch [1014/4000] Training [2/16] Loss: 0.01263 +Epoch [1014/4000] Training [3/16] Loss: 0.01051 +Epoch [1014/4000] Training [4/16] Loss: 0.01276 +Epoch [1014/4000] Training [5/16] Loss: 0.02233 +Epoch [1014/4000] Training [6/16] Loss: 0.00822 +Epoch [1014/4000] Training [7/16] Loss: 0.00861 +Epoch [1014/4000] Training [8/16] Loss: 0.01149 +Epoch [1014/4000] Training [9/16] Loss: 0.01204 +Epoch [1014/4000] Training [10/16] Loss: 0.01199 +Epoch [1014/4000] Training [11/16] Loss: 0.01177 +Epoch [1014/4000] Training [12/16] Loss: 0.01117 +Epoch [1014/4000] Training [13/16] Loss: 0.01563 +Epoch [1014/4000] Training [14/16] Loss: 0.00999 +Epoch [1014/4000] Training [15/16] Loss: 0.00923 +Epoch [1014/4000] Training [16/16] Loss: 0.01158 +Epoch [1014/4000] Training metric {'Train/mean dice_metric': 0.9918811321258545, 'Train/mean miou_metric': 0.983696699142456, 'Train/mean f1': 0.9879608750343323, 'Train/mean precision': 0.9827074408531189, 'Train/mean recall': 0.9932708144187927, 'Train/mean hd95_metric': 1.1886485815048218} +Epoch [1014/4000] Validation [1/4] Loss: 0.15864 focal_loss 0.09849 dice_loss 0.06015 +Epoch [1014/4000] Validation [2/4] Loss: 0.46666 focal_loss 0.21260 dice_loss 0.25407 +Epoch [1014/4000] Validation [3/4] Loss: 0.36128 focal_loss 0.23361 dice_loss 0.12767 +Epoch [1014/4000] Validation [4/4] Loss: 0.20848 focal_loss 0.09960 dice_loss 0.10888 +Epoch [1014/4000] Validation metric {'Val/mean dice_metric': 0.9677765965461731, 'Val/mean miou_metric': 0.9475261569023132, 'Val/mean f1': 0.9683563113212585, 'Val/mean precision': 0.9597113728523254, 'Val/mean recall': 0.9771583080291748, 'Val/mean hd95_metric': 6.797394752502441} +Cheakpoint... +Epoch [1014/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677765965461731, 'Val/mean miou_metric': 0.9475261569023132, 'Val/mean f1': 0.9683563113212585, 'Val/mean precision': 0.9597113728523254, 'Val/mean recall': 0.9771583080291748, 'Val/mean hd95_metric': 6.797394752502441} +Epoch [1015/4000] Training [1/16] Loss: 0.01121 +Epoch [1015/4000] Training [2/16] Loss: 0.00983 +Epoch [1015/4000] Training [3/16] Loss: 0.00846 +Epoch [1015/4000] Training [4/16] Loss: 0.01221 +Epoch [1015/4000] Training [5/16] Loss: 0.01118 +Epoch [1015/4000] Training [6/16] Loss: 0.01153 +Epoch [1015/4000] Training [7/16] Loss: 0.01037 +Epoch [1015/4000] Training [8/16] Loss: 0.01448 +Epoch [1015/4000] Training [9/16] Loss: 0.01150 +Epoch [1015/4000] Training [10/16] Loss: 0.01096 +Epoch [1015/4000] Training [11/16] Loss: 0.01085 +Epoch [1015/4000] Training [12/16] Loss: 0.01057 +Epoch [1015/4000] Training [13/16] Loss: 0.00900 +Epoch [1015/4000] Training [14/16] Loss: 0.01085 +Epoch [1015/4000] Training [15/16] Loss: 0.01367 +Epoch [1015/4000] Training [16/16] Loss: 0.01365 +Epoch [1015/4000] Training metric {'Train/mean dice_metric': 0.9915411472320557, 'Train/mean miou_metric': 0.9831136465072632, 'Train/mean f1': 0.987730860710144, 'Train/mean precision': 0.9827169179916382, 'Train/mean recall': 0.9927962422370911, 'Train/mean hd95_metric': 1.3474013805389404} +Epoch [1015/4000] Validation [1/4] Loss: 0.19074 focal_loss 0.12167 dice_loss 0.06906 +Epoch [1015/4000] Validation [2/4] Loss: 0.53976 focal_loss 0.25816 dice_loss 0.28160 +Epoch [1015/4000] Validation [3/4] Loss: 0.32693 focal_loss 0.21187 dice_loss 0.11505 +Epoch [1015/4000] Validation [4/4] Loss: 0.28956 focal_loss 0.14191 dice_loss 0.14765 +Epoch [1015/4000] Validation metric {'Val/mean dice_metric': 0.9648898839950562, 'Val/mean miou_metric': 0.9444746971130371, 'Val/mean f1': 0.9662904739379883, 'Val/mean precision': 0.9647526144981384, 'Val/mean recall': 0.9678333401679993, 'Val/mean hd95_metric': 6.281141757965088} +Cheakpoint... +Epoch [1015/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648898839950562, 'Val/mean miou_metric': 0.9444746971130371, 'Val/mean f1': 0.9662904739379883, 'Val/mean precision': 0.9647526144981384, 'Val/mean recall': 0.9678333401679993, 'Val/mean hd95_metric': 6.281141757965088} +Epoch [1016/4000] Training [1/16] Loss: 0.01142 +Epoch [1016/4000] Training [2/16] Loss: 0.00900 +Epoch [1016/4000] Training [3/16] Loss: 0.01327 +Epoch [1016/4000] Training [4/16] Loss: 0.01023 +Epoch [1016/4000] Training [5/16] Loss: 0.01173 +Epoch [1016/4000] Training [6/16] Loss: 0.01251 +Epoch [1016/4000] Training [7/16] Loss: 0.01073 +Epoch [1016/4000] Training [8/16] Loss: 0.01087 +Epoch [1016/4000] Training [9/16] Loss: 0.00923 +Epoch [1016/4000] Training [10/16] Loss: 0.00829 +Epoch [1016/4000] Training [11/16] Loss: 0.01422 +Epoch [1016/4000] Training [12/16] Loss: 0.01063 +Epoch [1016/4000] Training [13/16] Loss: 0.01131 +Epoch [1016/4000] Training [14/16] Loss: 0.01189 +Epoch [1016/4000] Training [15/16] Loss: 0.01723 +Epoch [1016/4000] Training [16/16] Loss: 0.01034 +Epoch [1016/4000] Training metric {'Train/mean dice_metric': 0.9921997785568237, 'Train/mean miou_metric': 0.9842841625213623, 'Train/mean f1': 0.9885798692703247, 'Train/mean precision': 0.9841659665107727, 'Train/mean recall': 0.9930335879325867, 'Train/mean hd95_metric': 1.2085751295089722} +Epoch [1016/4000] Validation [1/4] Loss: 0.15936 focal_loss 0.10373 dice_loss 0.05563 +Epoch [1016/4000] Validation [2/4] Loss: 0.31139 focal_loss 0.13994 dice_loss 0.17145 +Epoch [1016/4000] Validation [3/4] Loss: 0.27751 focal_loss 0.17558 dice_loss 0.10193 +Epoch [1016/4000] Validation [4/4] Loss: 0.34530 focal_loss 0.17769 dice_loss 0.16761 +Epoch [1016/4000] Validation metric {'Val/mean dice_metric': 0.9698833227157593, 'Val/mean miou_metric': 0.9498410224914551, 'Val/mean f1': 0.9705930352210999, 'Val/mean precision': 0.9669660329818726, 'Val/mean recall': 0.974247395992279, 'Val/mean hd95_metric': 6.331408977508545} +Cheakpoint... +Epoch [1016/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698833227157593, 'Val/mean miou_metric': 0.9498410224914551, 'Val/mean f1': 0.9705930352210999, 'Val/mean precision': 0.9669660329818726, 'Val/mean recall': 0.974247395992279, 'Val/mean hd95_metric': 6.331408977508545} +Epoch [1017/4000] Training [1/16] Loss: 0.01034 +Epoch [1017/4000] Training [2/16] Loss: 0.01698 +Epoch [1017/4000] Training [3/16] Loss: 0.00926 +Epoch [1017/4000] Training [4/16] Loss: 0.01301 +Epoch [1017/4000] Training [5/16] Loss: 0.01414 +Epoch [1017/4000] Training [6/16] Loss: 0.01239 +Epoch [1017/4000] Training [7/16] Loss: 0.01028 +Epoch [1017/4000] Training [8/16] Loss: 0.00856 +Epoch [1017/4000] Training [9/16] Loss: 0.00859 +Epoch [1017/4000] Training [10/16] Loss: 0.01106 +Epoch [1017/4000] Training [11/16] Loss: 0.01284 +Epoch [1017/4000] Training [12/16] Loss: 0.00856 +Epoch [1017/4000] Training [13/16] Loss: 0.01223 +Epoch [1017/4000] Training [14/16] Loss: 0.01116 +Epoch [1017/4000] Training [15/16] Loss: 0.02494 +Epoch [1017/4000] Training [16/16] Loss: 0.01136 +Epoch [1017/4000] Training metric {'Train/mean dice_metric': 0.9916918277740479, 'Train/mean miou_metric': 0.9833521842956543, 'Train/mean f1': 0.9883828163146973, 'Train/mean precision': 0.9836428165435791, 'Train/mean recall': 0.9931686520576477, 'Train/mean hd95_metric': 1.4745250940322876} +Epoch [1017/4000] Validation [1/4] Loss: 0.16836 focal_loss 0.10721 dice_loss 0.06115 +Epoch [1017/4000] Validation [2/4] Loss: 0.28809 focal_loss 0.14103 dice_loss 0.14705 +Epoch [1017/4000] Validation [3/4] Loss: 0.26738 focal_loss 0.17254 dice_loss 0.09484 +Epoch [1017/4000] Validation [4/4] Loss: 0.24538 focal_loss 0.12483 dice_loss 0.12055 +Epoch [1017/4000] Validation metric {'Val/mean dice_metric': 0.9688650369644165, 'Val/mean miou_metric': 0.948682427406311, 'Val/mean f1': 0.9707409143447876, 'Val/mean precision': 0.9661293625831604, 'Val/mean recall': 0.9753968119621277, 'Val/mean hd95_metric': 6.643872261047363} +Cheakpoint... +Epoch [1017/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688650369644165, 'Val/mean miou_metric': 0.948682427406311, 'Val/mean f1': 0.9707409143447876, 'Val/mean precision': 0.9661293625831604, 'Val/mean recall': 0.9753968119621277, 'Val/mean hd95_metric': 6.643872261047363} +Epoch [1018/4000] Training [1/16] Loss: 0.01376 +Epoch [1018/4000] Training [2/16] Loss: 0.00823 +Epoch [1018/4000] Training [3/16] Loss: 0.00979 +Epoch [1018/4000] Training [4/16] Loss: 0.01055 +Epoch [1018/4000] Training [5/16] Loss: 0.01236 +Epoch [1018/4000] Training [6/16] Loss: 0.01261 +Epoch [1018/4000] Training [7/16] Loss: 0.01033 +Epoch [1018/4000] Training [8/16] Loss: 0.01442 +Epoch [1018/4000] Training [9/16] Loss: 0.00992 +Epoch [1018/4000] Training [10/16] Loss: 0.00858 +Epoch [1018/4000] Training [11/16] Loss: 0.01127 +Epoch [1018/4000] Training [12/16] Loss: 0.01097 +Epoch [1018/4000] Training [13/16] Loss: 0.01234 +Epoch [1018/4000] Training [14/16] Loss: 0.01113 +Epoch [1018/4000] Training [15/16] Loss: 0.01375 +Epoch [1018/4000] Training [16/16] Loss: 0.01355 +Epoch [1018/4000] Training metric {'Train/mean dice_metric': 0.9919915199279785, 'Train/mean miou_metric': 0.9838693141937256, 'Train/mean f1': 0.9881671071052551, 'Train/mean precision': 0.9833806157112122, 'Train/mean recall': 0.9930004477500916, 'Train/mean hd95_metric': 1.1546270847320557} +Epoch [1018/4000] Validation [1/4] Loss: 0.19045 focal_loss 0.12538 dice_loss 0.06508 +Epoch [1018/4000] Validation [2/4] Loss: 0.36953 focal_loss 0.17607 dice_loss 0.19346 +Epoch [1018/4000] Validation [3/4] Loss: 0.30371 focal_loss 0.19846 dice_loss 0.10526 +Epoch [1018/4000] Validation [4/4] Loss: 0.23805 focal_loss 0.12253 dice_loss 0.11552 +Epoch [1018/4000] Validation metric {'Val/mean dice_metric': 0.9680534601211548, 'Val/mean miou_metric': 0.9478386640548706, 'Val/mean f1': 0.9692107439041138, 'Val/mean precision': 0.9651501774787903, 'Val/mean recall': 0.9733055233955383, 'Val/mean hd95_metric': 6.001961708068848} +Cheakpoint... +Epoch [1018/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680534601211548, 'Val/mean miou_metric': 0.9478386640548706, 'Val/mean f1': 0.9692107439041138, 'Val/mean precision': 0.9651501774787903, 'Val/mean recall': 0.9733055233955383, 'Val/mean hd95_metric': 6.001961708068848} +Epoch [1019/4000] Training [1/16] Loss: 0.01608 +Epoch [1019/4000] Training [2/16] Loss: 0.00724 +Epoch [1019/4000] Training [3/16] Loss: 0.00972 +Epoch [1019/4000] Training [4/16] Loss: 0.01147 +Epoch [1019/4000] Training [5/16] Loss: 0.01167 +Epoch [1019/4000] Training [6/16] Loss: 0.01075 +Epoch [1019/4000] Training [7/16] Loss: 0.01335 +Epoch [1019/4000] Training [8/16] Loss: 0.01368 +Epoch [1019/4000] Training [9/16] Loss: 0.01184 +Epoch [1019/4000] Training [10/16] Loss: 0.01552 +Epoch [1019/4000] Training [11/16] Loss: 0.00852 +Epoch [1019/4000] Training [12/16] Loss: 0.01164 +Epoch [1019/4000] Training [13/16] Loss: 0.00917 +Epoch [1019/4000] Training [14/16] Loss: 0.01069 +Epoch [1019/4000] Training [15/16] Loss: 0.00888 +Epoch [1019/4000] Training [16/16] Loss: 0.01164 +Epoch [1019/4000] Training metric {'Train/mean dice_metric': 0.9919530749320984, 'Train/mean miou_metric': 0.9838405251502991, 'Train/mean f1': 0.9885191321372986, 'Train/mean precision': 0.9837234020233154, 'Train/mean recall': 0.9933618903160095, 'Train/mean hd95_metric': 1.1777194738388062} +Epoch [1019/4000] Validation [1/4] Loss: 0.16086 focal_loss 0.10354 dice_loss 0.05732 +Epoch [1019/4000] Validation [2/4] Loss: 0.36448 focal_loss 0.18306 dice_loss 0.18142 +Epoch [1019/4000] Validation [3/4] Loss: 0.28444 focal_loss 0.18109 dice_loss 0.10335 +Epoch [1019/4000] Validation [4/4] Loss: 0.31936 focal_loss 0.18332 dice_loss 0.13604 +Epoch [1019/4000] Validation metric {'Val/mean dice_metric': 0.9677635431289673, 'Val/mean miou_metric': 0.9475845098495483, 'Val/mean f1': 0.9706231355667114, 'Val/mean precision': 0.9674714803695679, 'Val/mean recall': 0.9737954139709473, 'Val/mean hd95_metric': 6.165674686431885} +Cheakpoint... +Epoch [1019/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677635431289673, 'Val/mean miou_metric': 0.9475845098495483, 'Val/mean f1': 0.9706231355667114, 'Val/mean precision': 0.9674714803695679, 'Val/mean recall': 0.9737954139709473, 'Val/mean hd95_metric': 6.165674686431885} +Epoch [1020/4000] Training [1/16] Loss: 0.01076 +Epoch [1020/4000] Training [2/16] Loss: 0.01358 +Epoch [1020/4000] Training [3/16] Loss: 0.01932 +Epoch [1020/4000] Training [4/16] Loss: 0.01184 +Epoch [1020/4000] Training [5/16] Loss: 0.00998 +Epoch [1020/4000] Training [6/16] Loss: 0.00967 +Epoch [1020/4000] Training [7/16] Loss: 0.01258 +Epoch [1020/4000] Training [8/16] Loss: 0.01336 +Epoch [1020/4000] Training [9/16] Loss: 0.01035 +Epoch [1020/4000] Training [10/16] Loss: 0.00903 +Epoch [1020/4000] Training [11/16] Loss: 0.00854 +Epoch [1020/4000] Training [12/16] Loss: 0.01080 +Epoch [1020/4000] Training [13/16] Loss: 0.01418 +Epoch [1020/4000] Training [14/16] Loss: 0.01211 +Epoch [1020/4000] Training [15/16] Loss: 0.00983 +Epoch [1020/4000] Training [16/16] Loss: 0.01073 +Epoch [1020/4000] Training metric {'Train/mean dice_metric': 0.9919565916061401, 'Train/mean miou_metric': 0.9837929010391235, 'Train/mean f1': 0.9876807928085327, 'Train/mean precision': 0.9823439717292786, 'Train/mean recall': 0.9930758476257324, 'Train/mean hd95_metric': 1.3829470872879028} +Epoch [1020/4000] Validation [1/4] Loss: 0.17829 focal_loss 0.11692 dice_loss 0.06137 +Epoch [1020/4000] Validation [2/4] Loss: 0.25292 focal_loss 0.11978 dice_loss 0.13314 +Epoch [1020/4000] Validation [3/4] Loss: 0.30155 focal_loss 0.18092 dice_loss 0.12063 +Epoch [1020/4000] Validation [4/4] Loss: 0.30794 focal_loss 0.16300 dice_loss 0.14494 +Epoch [1020/4000] Validation metric {'Val/mean dice_metric': 0.9667569994926453, 'Val/mean miou_metric': 0.9469267129898071, 'Val/mean f1': 0.9687426686286926, 'Val/mean precision': 0.9592152237892151, 'Val/mean recall': 0.9784614443778992, 'Val/mean hd95_metric': 7.663488864898682} +Cheakpoint... +Epoch [1020/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667569994926453, 'Val/mean miou_metric': 0.9469267129898071, 'Val/mean f1': 0.9687426686286926, 'Val/mean precision': 0.9592152237892151, 'Val/mean recall': 0.9784614443778992, 'Val/mean hd95_metric': 7.663488864898682} +Epoch [1021/4000] Training [1/16] Loss: 0.00981 +Epoch [1021/4000] Training [2/16] Loss: 0.01159 +Epoch [1021/4000] Training [3/16] Loss: 0.01822 +Epoch [1021/4000] Training [4/16] Loss: 0.01052 +Epoch [1021/4000] Training [5/16] Loss: 0.01433 +Epoch [1021/4000] Training [6/16] Loss: 0.01056 +Epoch [1021/4000] Training [7/16] Loss: 0.00958 +Epoch [1021/4000] Training [8/16] Loss: 0.00978 +Epoch [1021/4000] Training [9/16] Loss: 0.01505 +Epoch [1021/4000] Training [10/16] Loss: 0.01308 +Epoch [1021/4000] Training [11/16] Loss: 0.00940 +Epoch [1021/4000] Training [12/16] Loss: 0.01567 +Epoch [1021/4000] Training [13/16] Loss: 0.01249 +Epoch [1021/4000] Training [14/16] Loss: 0.01005 +Epoch [1021/4000] Training [15/16] Loss: 0.01010 +Epoch [1021/4000] Training [16/16] Loss: 0.01233 +Epoch [1021/4000] Training metric {'Train/mean dice_metric': 0.9922492504119873, 'Train/mean miou_metric': 0.9843930006027222, 'Train/mean f1': 0.9886889457702637, 'Train/mean precision': 0.9841130375862122, 'Train/mean recall': 0.9933075904846191, 'Train/mean hd95_metric': 1.1529922485351562} +Epoch [1021/4000] Validation [1/4] Loss: 0.20263 focal_loss 0.12586 dice_loss 0.07677 +Epoch [1021/4000] Validation [2/4] Loss: 0.24646 focal_loss 0.11425 dice_loss 0.13221 +Epoch [1021/4000] Validation [3/4] Loss: 0.26234 focal_loss 0.16825 dice_loss 0.09409 +Epoch [1021/4000] Validation [4/4] Loss: 0.27547 focal_loss 0.15232 dice_loss 0.12314 +Epoch [1021/4000] Validation metric {'Val/mean dice_metric': 0.96861732006073, 'Val/mean miou_metric': 0.9490761756896973, 'Val/mean f1': 0.9704310894012451, 'Val/mean precision': 0.9645805954933167, 'Val/mean recall': 0.9763529300689697, 'Val/mean hd95_metric': 6.342926979064941} +Cheakpoint... +Epoch [1021/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96861732006073, 'Val/mean miou_metric': 0.9490761756896973, 'Val/mean f1': 0.9704310894012451, 'Val/mean precision': 0.9645805954933167, 'Val/mean recall': 0.9763529300689697, 'Val/mean hd95_metric': 6.342926979064941} +Epoch [1022/4000] Training [1/16] Loss: 0.01046 +Epoch [1022/4000] Training [2/16] Loss: 0.01004 +Epoch [1022/4000] Training [3/16] Loss: 0.00834 +Epoch [1022/4000] Training [4/16] Loss: 0.01400 +Epoch [1022/4000] Training [5/16] Loss: 0.00911 +Epoch [1022/4000] Training [6/16] Loss: 0.00968 +Epoch [1022/4000] Training [7/16] Loss: 0.01206 +Epoch [1022/4000] Training [8/16] Loss: 0.01256 +Epoch [1022/4000] Training [9/16] Loss: 0.01397 +Epoch [1022/4000] Training [10/16] Loss: 0.01243 +Epoch [1022/4000] Training [11/16] Loss: 0.00999 +Epoch [1022/4000] Training [12/16] Loss: 0.01408 +Epoch [1022/4000] Training [13/16] Loss: 0.01312 +Epoch [1022/4000] Training [14/16] Loss: 0.01324 +Epoch [1022/4000] Training [15/16] Loss: 0.01221 +Epoch [1022/4000] Training [16/16] Loss: 0.01279 +Epoch [1022/4000] Training metric {'Train/mean dice_metric': 0.9922351837158203, 'Train/mean miou_metric': 0.98433518409729, 'Train/mean f1': 0.9882202744483948, 'Train/mean precision': 0.9831112623214722, 'Train/mean recall': 0.9933826327323914, 'Train/mean hd95_metric': 1.362081527709961} +Epoch [1022/4000] Validation [1/4] Loss: 0.21651 focal_loss 0.13936 dice_loss 0.07715 +Epoch [1022/4000] Validation [2/4] Loss: 0.35262 focal_loss 0.19344 dice_loss 0.15918 +Epoch [1022/4000] Validation [3/4] Loss: 0.29620 focal_loss 0.19995 dice_loss 0.09626 +Epoch [1022/4000] Validation [4/4] Loss: 0.33716 focal_loss 0.16371 dice_loss 0.17346 +Epoch [1022/4000] Validation metric {'Val/mean dice_metric': 0.9687566757202148, 'Val/mean miou_metric': 0.9483609199523926, 'Val/mean f1': 0.9704968929290771, 'Val/mean precision': 0.9652485251426697, 'Val/mean recall': 0.9758025407791138, 'Val/mean hd95_metric': 6.785318851470947} +Cheakpoint... +Epoch [1022/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687566757202148, 'Val/mean miou_metric': 0.9483609199523926, 'Val/mean f1': 0.9704968929290771, 'Val/mean precision': 0.9652485251426697, 'Val/mean recall': 0.9758025407791138, 'Val/mean hd95_metric': 6.785318851470947} +Epoch [1023/4000] Training [1/16] Loss: 0.01171 +Epoch [1023/4000] Training [2/16] Loss: 0.01008 +Epoch [1023/4000] Training [3/16] Loss: 0.01357 +Epoch [1023/4000] Training [4/16] Loss: 0.00878 +Epoch [1023/4000] Training [5/16] Loss: 0.00783 +Epoch [1023/4000] Training [6/16] Loss: 0.00981 +Epoch [1023/4000] Training [7/16] Loss: 0.01559 +Epoch [1023/4000] Training [8/16] Loss: 0.01060 +Epoch [1023/4000] Training [9/16] Loss: 0.00944 +Epoch [1023/4000] Training [10/16] Loss: 0.00995 +Epoch [1023/4000] Training [11/16] Loss: 0.00947 +Epoch [1023/4000] Training [12/16] Loss: 0.00908 +Epoch [1023/4000] Training [13/16] Loss: 0.01329 +Epoch [1023/4000] Training [14/16] Loss: 0.01037 +Epoch [1023/4000] Training [15/16] Loss: 0.01044 +Epoch [1023/4000] Training [16/16] Loss: 0.01368 +Epoch [1023/4000] Training metric {'Train/mean dice_metric': 0.9923730492591858, 'Train/mean miou_metric': 0.9846314191818237, 'Train/mean f1': 0.9887913465499878, 'Train/mean precision': 0.9844251275062561, 'Train/mean recall': 0.9931965470314026, 'Train/mean hd95_metric': 1.2420613765716553} +Epoch [1023/4000] Validation [1/4] Loss: 0.17670 focal_loss 0.11183 dice_loss 0.06487 +Epoch [1023/4000] Validation [2/4] Loss: 0.26531 focal_loss 0.13251 dice_loss 0.13280 +Epoch [1023/4000] Validation [3/4] Loss: 0.25475 focal_loss 0.15922 dice_loss 0.09553 +Epoch [1023/4000] Validation [4/4] Loss: 0.28571 focal_loss 0.15950 dice_loss 0.12620 +Epoch [1023/4000] Validation metric {'Val/mean dice_metric': 0.9700595736503601, 'Val/mean miou_metric': 0.950472354888916, 'Val/mean f1': 0.9711077809333801, 'Val/mean precision': 0.9685751795768738, 'Val/mean recall': 0.9736536741256714, 'Val/mean hd95_metric': 5.743359565734863} +Cheakpoint... +Epoch [1023/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700595736503601, 'Val/mean miou_metric': 0.950472354888916, 'Val/mean f1': 0.9711077809333801, 'Val/mean precision': 0.9685751795768738, 'Val/mean recall': 0.9736536741256714, 'Val/mean hd95_metric': 5.743359565734863} +Epoch [1024/4000] Training [1/16] Loss: 0.01342 +Epoch [1024/4000] Training [2/16] Loss: 0.01463 +Epoch [1024/4000] Training [3/16] Loss: 0.01171 +Epoch [1024/4000] Training [4/16] Loss: 0.01124 +Epoch [1024/4000] Training [5/16] Loss: 0.01423 +Epoch [1024/4000] Training [6/16] Loss: 0.01510 +Epoch [1024/4000] Training [7/16] Loss: 0.00986 +Epoch [1024/4000] Training [8/16] Loss: 0.01214 +Epoch [1024/4000] Training [9/16] Loss: 0.01331 +Epoch [1024/4000] Training [10/16] Loss: 0.01216 +Epoch [1024/4000] Training [11/16] Loss: 0.01022 +Epoch [1024/4000] Training [12/16] Loss: 0.01223 +Epoch [1024/4000] Training [13/16] Loss: 0.01048 +Epoch [1024/4000] Training [14/16] Loss: 0.01037 +Epoch [1024/4000] Training [15/16] Loss: 0.01015 +Epoch [1024/4000] Training [16/16] Loss: 0.01031 +Epoch [1024/4000] Training metric {'Train/mean dice_metric': 0.9916375875473022, 'Train/mean miou_metric': 0.9832374453544617, 'Train/mean f1': 0.9883078336715698, 'Train/mean precision': 0.9837185144424438, 'Train/mean recall': 0.9929401874542236, 'Train/mean hd95_metric': 1.4705171585083008} +Epoch [1024/4000] Validation [1/4] Loss: 0.14569 focal_loss 0.08915 dice_loss 0.05654 +Epoch [1024/4000] Validation [2/4] Loss: 0.31712 focal_loss 0.15425 dice_loss 0.16288 +Epoch [1024/4000] Validation [3/4] Loss: 0.29211 focal_loss 0.18886 dice_loss 0.10325 +Epoch [1024/4000] Validation [4/4] Loss: 0.26552 focal_loss 0.14669 dice_loss 0.11883 +Epoch [1024/4000] Validation metric {'Val/mean dice_metric': 0.9698657989501953, 'Val/mean miou_metric': 0.9500154256820679, 'Val/mean f1': 0.9727190732955933, 'Val/mean precision': 0.9685623049736023, 'Val/mean recall': 0.9769117832183838, 'Val/mean hd95_metric': 6.146313667297363} +Cheakpoint... +Epoch [1024/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698657989501953, 'Val/mean miou_metric': 0.9500154256820679, 'Val/mean f1': 0.9727190732955933, 'Val/mean precision': 0.9685623049736023, 'Val/mean recall': 0.9769117832183838, 'Val/mean hd95_metric': 6.146313667297363} +Epoch [1025/4000] Training [1/16] Loss: 0.01093 +Epoch [1025/4000] Training [2/16] Loss: 0.01313 +Epoch [1025/4000] Training [3/16] Loss: 0.01178 +Epoch [1025/4000] Training [4/16] Loss: 0.01050 +Epoch [1025/4000] Training [5/16] Loss: 0.01357 +Epoch [1025/4000] Training [6/16] Loss: 0.01134 +Epoch [1025/4000] Training [7/16] Loss: 0.01897 +Epoch [1025/4000] Training [8/16] Loss: 0.00984 +Epoch [1025/4000] Training [9/16] Loss: 0.00915 +Epoch [1025/4000] Training [10/16] Loss: 0.01048 +Epoch [1025/4000] Training [11/16] Loss: 0.01436 +Epoch [1025/4000] Training [12/16] Loss: 0.01433 +Epoch [1025/4000] Training [13/16] Loss: 0.00892 +Epoch [1025/4000] Training [14/16] Loss: 0.01339 +Epoch [1025/4000] Training [15/16] Loss: 0.01095 +Epoch [1025/4000] Training [16/16] Loss: 0.01113 +Epoch [1025/4000] Training metric {'Train/mean dice_metric': 0.9918278455734253, 'Train/mean miou_metric': 0.9835730195045471, 'Train/mean f1': 0.9886153936386108, 'Train/mean precision': 0.9839425683021545, 'Train/mean recall': 0.9933327436447144, 'Train/mean hd95_metric': 1.134061574935913} +Epoch [1025/4000] Validation [1/4] Loss: 0.14021 focal_loss 0.08271 dice_loss 0.05750 +Epoch [1025/4000] Validation [2/4] Loss: 0.25345 focal_loss 0.11848 dice_loss 0.13498 +Epoch [1025/4000] Validation [3/4] Loss: 0.20629 focal_loss 0.11831 dice_loss 0.08798 +Epoch [1025/4000] Validation [4/4] Loss: 0.30502 focal_loss 0.17280 dice_loss 0.13222 +Epoch [1025/4000] Validation metric {'Val/mean dice_metric': 0.9689800143241882, 'Val/mean miou_metric': 0.9483222961425781, 'Val/mean f1': 0.9717662930488586, 'Val/mean precision': 0.9688398838043213, 'Val/mean recall': 0.9747104048728943, 'Val/mean hd95_metric': 6.333837509155273} +Cheakpoint... +Epoch [1025/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689800143241882, 'Val/mean miou_metric': 0.9483222961425781, 'Val/mean f1': 0.9717662930488586, 'Val/mean precision': 0.9688398838043213, 'Val/mean recall': 0.9747104048728943, 'Val/mean hd95_metric': 6.333837509155273} +Epoch [1026/4000] Training [1/16] Loss: 0.00827 +Epoch [1026/4000] Training [2/16] Loss: 0.00952 +Epoch [1026/4000] Training [3/16] Loss: 0.00872 +Epoch [1026/4000] Training [4/16] Loss: 0.01722 +Epoch [1026/4000] Training [5/16] Loss: 0.00929 +Epoch [1026/4000] Training [6/16] Loss: 0.01142 +Epoch [1026/4000] Training [7/16] Loss: 0.00988 +Epoch [1026/4000] Training [8/16] Loss: 0.01204 +Epoch [1026/4000] Training [9/16] Loss: 0.01004 +Epoch [1026/4000] Training [10/16] Loss: 0.01394 +Epoch [1026/4000] Training [11/16] Loss: 0.00980 +Epoch [1026/4000] Training [12/16] Loss: 0.01023 +Epoch [1026/4000] Training [13/16] Loss: 0.00876 +Epoch [1026/4000] Training [14/16] Loss: 0.01413 +Epoch [1026/4000] Training [15/16] Loss: 0.01415 +Epoch [1026/4000] Training [16/16] Loss: 0.01222 +Epoch [1026/4000] Training metric {'Train/mean dice_metric': 0.9920387864112854, 'Train/mean miou_metric': 0.9840260744094849, 'Train/mean f1': 0.9889652132987976, 'Train/mean precision': 0.9846522212028503, 'Train/mean recall': 0.9933161735534668, 'Train/mean hd95_metric': 1.1683876514434814} +Epoch [1026/4000] Validation [1/4] Loss: 0.20652 focal_loss 0.13511 dice_loss 0.07141 +Epoch [1026/4000] Validation [2/4] Loss: 0.19878 focal_loss 0.08409 dice_loss 0.11470 +Epoch [1026/4000] Validation [3/4] Loss: 0.26819 focal_loss 0.16827 dice_loss 0.09992 +Epoch [1026/4000] Validation [4/4] Loss: 0.24666 focal_loss 0.11776 dice_loss 0.12890 +Epoch [1026/4000] Validation metric {'Val/mean dice_metric': 0.968597412109375, 'Val/mean miou_metric': 0.948857307434082, 'Val/mean f1': 0.9716119170188904, 'Val/mean precision': 0.9655352830886841, 'Val/mean recall': 0.9777655601501465, 'Val/mean hd95_metric': 6.616238594055176} +Cheakpoint... +Epoch [1026/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968597412109375, 'Val/mean miou_metric': 0.948857307434082, 'Val/mean f1': 0.9716119170188904, 'Val/mean precision': 0.9655352830886841, 'Val/mean recall': 0.9777655601501465, 'Val/mean hd95_metric': 6.616238594055176} +Epoch [1027/4000] Training [1/16] Loss: 0.00924 +Epoch [1027/4000] Training [2/16] Loss: 0.01433 +Epoch [1027/4000] Training [3/16] Loss: 0.00937 +Epoch [1027/4000] Training [4/16] Loss: 0.01126 +Epoch [1027/4000] Training [5/16] Loss: 0.01269 +Epoch [1027/4000] Training [6/16] Loss: 0.01170 +Epoch [1027/4000] Training [7/16] Loss: 0.00998 +Epoch [1027/4000] Training [8/16] Loss: 0.01451 +Epoch [1027/4000] Training [9/16] Loss: 0.00797 +Epoch [1027/4000] Training [10/16] Loss: 0.01022 +Epoch [1027/4000] Training [11/16] Loss: 0.01012 +Epoch [1027/4000] Training [12/16] Loss: 0.01088 +Epoch [1027/4000] Training [13/16] Loss: 0.01161 +Epoch [1027/4000] Training [14/16] Loss: 0.01121 +Epoch [1027/4000] Training [15/16] Loss: 0.00982 +Epoch [1027/4000] Training [16/16] Loss: 0.01057 +Epoch [1027/4000] Training metric {'Train/mean dice_metric': 0.9917082786560059, 'Train/mean miou_metric': 0.9834442138671875, 'Train/mean f1': 0.9884364008903503, 'Train/mean precision': 0.9836803078651428, 'Train/mean recall': 0.993238627910614, 'Train/mean hd95_metric': 1.2920763492584229} +Epoch [1027/4000] Validation [1/4] Loss: 0.21600 focal_loss 0.15010 dice_loss 0.06590 +Epoch [1027/4000] Validation [2/4] Loss: 0.23595 focal_loss 0.09720 dice_loss 0.13874 +Epoch [1027/4000] Validation [3/4] Loss: 0.25929 focal_loss 0.15914 dice_loss 0.10015 +Epoch [1027/4000] Validation [4/4] Loss: 0.38785 focal_loss 0.21733 dice_loss 0.17052 +Epoch [1027/4000] Validation metric {'Val/mean dice_metric': 0.9660184979438782, 'Val/mean miou_metric': 0.9452847242355347, 'Val/mean f1': 0.9681405425071716, 'Val/mean precision': 0.9603510499000549, 'Val/mean recall': 0.9760573506355286, 'Val/mean hd95_metric': 7.3533525466918945} +Cheakpoint... +Epoch [1027/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660184979438782, 'Val/mean miou_metric': 0.9452847242355347, 'Val/mean f1': 0.9681405425071716, 'Val/mean precision': 0.9603510499000549, 'Val/mean recall': 0.9760573506355286, 'Val/mean hd95_metric': 7.3533525466918945} +Epoch [1028/4000] Training [1/16] Loss: 0.01081 +Epoch [1028/4000] Training [2/16] Loss: 0.04484 +Epoch [1028/4000] Training [3/16] Loss: 0.00753 +Epoch [1028/4000] Training [4/16] Loss: 0.00910 +Epoch [1028/4000] Training [5/16] Loss: 0.01507 +Epoch [1028/4000] Training [6/16] Loss: 0.01158 +Epoch [1028/4000] Training [7/16] Loss: 0.01528 +Epoch [1028/4000] Training [8/16] Loss: 0.01651 +Epoch [1028/4000] Training [9/16] Loss: 0.01506 +Epoch [1028/4000] Training [10/16] Loss: 0.01339 +Epoch [1028/4000] Training [11/16] Loss: 0.01268 +Epoch [1028/4000] Training [12/16] Loss: 0.01051 +Epoch [1028/4000] Training [13/16] Loss: 0.01096 +Epoch [1028/4000] Training [14/16] Loss: 0.01110 +Epoch [1028/4000] Training [15/16] Loss: 0.00993 +Epoch [1028/4000] Training [16/16] Loss: 0.00754 +Epoch [1028/4000] Training metric {'Train/mean dice_metric': 0.9912794828414917, 'Train/mean miou_metric': 0.9826229810714722, 'Train/mean f1': 0.9883659482002258, 'Train/mean precision': 0.9836421012878418, 'Train/mean recall': 0.993135392665863, 'Train/mean hd95_metric': 1.5046405792236328} +Epoch [1028/4000] Validation [1/4] Loss: 0.19014 focal_loss 0.12649 dice_loss 0.06365 +Epoch [1028/4000] Validation [2/4] Loss: 0.30611 focal_loss 0.14779 dice_loss 0.15831 +Epoch [1028/4000] Validation [3/4] Loss: 0.25755 focal_loss 0.15762 dice_loss 0.09994 +Epoch [1028/4000] Validation [4/4] Loss: 0.22240 focal_loss 0.09932 dice_loss 0.12307 +Epoch [1028/4000] Validation metric {'Val/mean dice_metric': 0.9655581712722778, 'Val/mean miou_metric': 0.9450578689575195, 'Val/mean f1': 0.9698475003242493, 'Val/mean precision': 0.9627248048782349, 'Val/mean recall': 0.9770764708518982, 'Val/mean hd95_metric': 7.388360500335693} +Cheakpoint... +Epoch [1028/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655581712722778, 'Val/mean miou_metric': 0.9450578689575195, 'Val/mean f1': 0.9698475003242493, 'Val/mean precision': 0.9627248048782349, 'Val/mean recall': 0.9770764708518982, 'Val/mean hd95_metric': 7.388360500335693} +Epoch [1029/4000] Training [1/16] Loss: 0.01051 +Epoch [1029/4000] Training [2/16] Loss: 0.00832 +Epoch [1029/4000] Training [3/16] Loss: 0.01340 +Epoch [1029/4000] Training [4/16] Loss: 0.01824 +Epoch [1029/4000] Training [5/16] Loss: 0.01813 +Epoch [1029/4000] Training [6/16] Loss: 0.01039 +Epoch [1029/4000] Training [7/16] Loss: 0.01235 +Epoch [1029/4000] Training [8/16] Loss: 0.01294 +Epoch [1029/4000] Training [9/16] Loss: 0.03196 +Epoch [1029/4000] Training [10/16] Loss: 0.01285 +Epoch [1029/4000] Training [11/16] Loss: 0.01620 +Epoch [1029/4000] Training [12/16] Loss: 0.00922 +Epoch [1029/4000] Training [13/16] Loss: 0.01472 +Epoch [1029/4000] Training [14/16] Loss: 0.00995 +Epoch [1029/4000] Training [15/16] Loss: 0.01572 +Epoch [1029/4000] Training [16/16] Loss: 0.01367 +Epoch [1029/4000] Training metric {'Train/mean dice_metric': 0.9876154065132141, 'Train/mean miou_metric': 0.9779947996139526, 'Train/mean f1': 0.9865921139717102, 'Train/mean precision': 0.981913149356842, 'Train/mean recall': 0.9913158416748047, 'Train/mean hd95_metric': 1.9187287092208862} +Epoch [1029/4000] Validation [1/4] Loss: 0.24326 focal_loss 0.14399 dice_loss 0.09928 +Epoch [1029/4000] Validation [2/4] Loss: 0.35931 focal_loss 0.16537 dice_loss 0.19394 +Epoch [1029/4000] Validation [3/4] Loss: 0.21159 focal_loss 0.13431 dice_loss 0.07728 +Epoch [1029/4000] Validation [4/4] Loss: 0.22743 focal_loss 0.10796 dice_loss 0.11947 +Epoch [1029/4000] Validation metric {'Val/mean dice_metric': 0.9624603390693665, 'Val/mean miou_metric': 0.941453754901886, 'Val/mean f1': 0.9648021459579468, 'Val/mean precision': 0.9585809111595154, 'Val/mean recall': 0.9711046814918518, 'Val/mean hd95_metric': 7.499507904052734} +Cheakpoint... +Epoch [1029/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9625], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9624603390693665, 'Val/mean miou_metric': 0.941453754901886, 'Val/mean f1': 0.9648021459579468, 'Val/mean precision': 0.9585809111595154, 'Val/mean recall': 0.9711046814918518, 'Val/mean hd95_metric': 7.499507904052734} +Epoch [1030/4000] Training [1/16] Loss: 0.01713 +Epoch [1030/4000] Training [2/16] Loss: 0.01488 +Epoch [1030/4000] Training [3/16] Loss: 0.01693 +Epoch [1030/4000] Training [4/16] Loss: 0.01517 +Epoch [1030/4000] Training [5/16] Loss: 0.01644 +Epoch [1030/4000] Training [6/16] Loss: 0.01476 +Epoch [1030/4000] Training [7/16] Loss: 0.01118 +Epoch [1030/4000] Training [8/16] Loss: 0.01265 +Epoch [1030/4000] Training [9/16] Loss: 0.01633 +Epoch [1030/4000] Training [10/16] Loss: 0.01351 +Epoch [1030/4000] Training [11/16] Loss: 0.01205 +Epoch [1030/4000] Training [12/16] Loss: 0.01808 +Epoch [1030/4000] Training [13/16] Loss: 0.01404 +Epoch [1030/4000] Training [14/16] Loss: 0.01634 +Epoch [1030/4000] Training [15/16] Loss: 0.01452 +Epoch [1030/4000] Training [16/16] Loss: 0.01513 +Epoch [1030/4000] Training metric {'Train/mean dice_metric': 0.9888088703155518, 'Train/mean miou_metric': 0.9779964089393616, 'Train/mean f1': 0.9854873418807983, 'Train/mean precision': 0.9818478226661682, 'Train/mean recall': 0.9891539216041565, 'Train/mean hd95_metric': 2.552294969558716} +Epoch [1030/4000] Validation [1/4] Loss: 0.25325 focal_loss 0.17749 dice_loss 0.07576 +Epoch [1030/4000] Validation [2/4] Loss: 0.70002 focal_loss 0.39651 dice_loss 0.30351 +Epoch [1030/4000] Validation [3/4] Loss: 0.18968 focal_loss 0.10377 dice_loss 0.08590 +Epoch [1030/4000] Validation [4/4] Loss: 0.32966 focal_loss 0.20166 dice_loss 0.12800 +Epoch [1030/4000] Validation metric {'Val/mean dice_metric': 0.9574222564697266, 'Val/mean miou_metric': 0.9343751668930054, 'Val/mean f1': 0.9603814482688904, 'Val/mean precision': 0.9610486030578613, 'Val/mean recall': 0.9597153067588806, 'Val/mean hd95_metric': 9.67003345489502} +Cheakpoint... +Epoch [1030/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9574], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9574222564697266, 'Val/mean miou_metric': 0.9343751668930054, 'Val/mean f1': 0.9603814482688904, 'Val/mean precision': 0.9610486030578613, 'Val/mean recall': 0.9597153067588806, 'Val/mean hd95_metric': 9.67003345489502} +Epoch [1031/4000] Training [1/16] Loss: 0.23089 +Epoch [1031/4000] Training [2/16] Loss: 0.01341 +Epoch [1031/4000] Training [3/16] Loss: 0.01161 +Epoch [1031/4000] Training [4/16] Loss: 0.01409 +Epoch [1031/4000] Training [5/16] Loss: 0.01643 +Epoch [1031/4000] Training [6/16] Loss: 0.01231 +Epoch [1031/4000] Training [7/16] Loss: 0.01278 +Epoch [1031/4000] Training [8/16] Loss: 0.01521 +Epoch [1031/4000] Training [9/16] Loss: 0.01184 +Epoch [1031/4000] Training [10/16] Loss: 0.01300 +Epoch [1031/4000] Training [11/16] Loss: 0.01431 +Epoch [1031/4000] Training [12/16] Loss: 0.01483 +Epoch [1031/4000] Training [13/16] Loss: 0.01348 +Epoch [1031/4000] Training [14/16] Loss: 0.01352 +Epoch [1031/4000] Training [15/16] Loss: 0.01811 +Epoch [1031/4000] Training [16/16] Loss: 0.01155 +Epoch [1031/4000] Training metric {'Train/mean dice_metric': 0.9880204200744629, 'Train/mean miou_metric': 0.9770665168762207, 'Train/mean f1': 0.9844887852668762, 'Train/mean precision': 0.9786645770072937, 'Train/mean recall': 0.9903826713562012, 'Train/mean hd95_metric': 2.8653690814971924} +Epoch [1031/4000] Validation [1/4] Loss: 0.43184 focal_loss 0.28246 dice_loss 0.14937 +Epoch [1031/4000] Validation [2/4] Loss: 0.38748 focal_loss 0.19919 dice_loss 0.18829 +Epoch [1031/4000] Validation [3/4] Loss: 0.18138 focal_loss 0.09040 dice_loss 0.09097 +Epoch [1031/4000] Validation [4/4] Loss: 0.53636 focal_loss 0.33613 dice_loss 0.20023 +Epoch [1031/4000] Validation metric {'Val/mean dice_metric': 0.9600628018379211, 'Val/mean miou_metric': 0.936430811882019, 'Val/mean f1': 0.9601060152053833, 'Val/mean precision': 0.9596462845802307, 'Val/mean recall': 0.9605662822723389, 'Val/mean hd95_metric': 8.852872848510742} +Cheakpoint... +Epoch [1031/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9601], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9600628018379211, 'Val/mean miou_metric': 0.936430811882019, 'Val/mean f1': 0.9601060152053833, 'Val/mean precision': 0.9596462845802307, 'Val/mean recall': 0.9605662822723389, 'Val/mean hd95_metric': 8.852872848510742} +Epoch [1032/4000] Training [1/16] Loss: 0.02273 +Epoch [1032/4000] Training [2/16] Loss: 0.01266 +Epoch [1032/4000] Training [3/16] Loss: 0.01291 +Epoch [1032/4000] Training [4/16] Loss: 0.01474 +Epoch [1032/4000] Training [5/16] Loss: 0.01671 +Epoch [1032/4000] Training [6/16] Loss: 0.01662 +Epoch [1032/4000] Training [7/16] Loss: 0.01386 +Epoch [1032/4000] Training [8/16] Loss: 0.01152 +Epoch [1032/4000] Training [9/16] Loss: 0.01773 +Epoch [1032/4000] Training [10/16] Loss: 0.01911 +Epoch [1032/4000] Training [11/16] Loss: 0.01451 +Epoch [1032/4000] Training [12/16] Loss: 0.01483 +Epoch [1032/4000] Training [13/16] Loss: 0.01741 +Epoch [1032/4000] Training [14/16] Loss: 0.02371 +Epoch [1032/4000] Training [15/16] Loss: 0.01764 +Epoch [1032/4000] Training [16/16] Loss: 0.01294 +Epoch [1032/4000] Training metric {'Train/mean dice_metric': 0.9892619848251343, 'Train/mean miou_metric': 0.9786974191665649, 'Train/mean f1': 0.984764575958252, 'Train/mean precision': 0.9812011122703552, 'Train/mean recall': 0.9883540272712708, 'Train/mean hd95_metric': 2.6343154907226562} +Epoch [1032/4000] Validation [1/4] Loss: 0.21132 focal_loss 0.13499 dice_loss 0.07633 +Epoch [1032/4000] Validation [2/4] Loss: 0.19302 focal_loss 0.07180 dice_loss 0.12122 +Epoch [1032/4000] Validation [3/4] Loss: 0.18969 focal_loss 0.08863 dice_loss 0.10106 +Epoch [1032/4000] Validation [4/4] Loss: 0.26125 focal_loss 0.14227 dice_loss 0.11899 +Epoch [1032/4000] Validation metric {'Val/mean dice_metric': 0.9639674425125122, 'Val/mean miou_metric': 0.9410027265548706, 'Val/mean f1': 0.9631808996200562, 'Val/mean precision': 0.9582917094230652, 'Val/mean recall': 0.9681203961372375, 'Val/mean hd95_metric': 9.197115898132324} +Cheakpoint... +Epoch [1032/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639674425125122, 'Val/mean miou_metric': 0.9410027265548706, 'Val/mean f1': 0.9631808996200562, 'Val/mean precision': 0.9582917094230652, 'Val/mean recall': 0.9681203961372375, 'Val/mean hd95_metric': 9.197115898132324} +Epoch [1033/4000] Training [1/16] Loss: 0.01085 +Epoch [1033/4000] Training [2/16] Loss: 0.02036 +Epoch [1033/4000] Training [3/16] Loss: 0.01115 +Epoch [1033/4000] Training [4/16] Loss: 0.01442 +Epoch [1033/4000] Training [5/16] Loss: 0.01209 +Epoch [1033/4000] Training [6/16] Loss: 0.01240 +Epoch [1033/4000] Training [7/16] Loss: 0.04251 +Epoch [1033/4000] Training [8/16] Loss: 0.01502 +Epoch [1033/4000] Training [9/16] Loss: 0.01121 +Epoch [1033/4000] Training [10/16] Loss: 0.01520 +Epoch [1033/4000] Training [11/16] Loss: 0.01321 +Epoch [1033/4000] Training [12/16] Loss: 0.01271 +Epoch [1033/4000] Training [13/16] Loss: 0.01154 +Epoch [1033/4000] Training [14/16] Loss: 0.03657 +Epoch [1033/4000] Training [15/16] Loss: 0.01055 +Epoch [1033/4000] Training [16/16] Loss: 0.01443 +Epoch [1033/4000] Training metric {'Train/mean dice_metric': 0.9900368452072144, 'Train/mean miou_metric': 0.9802923798561096, 'Train/mean f1': 0.9863302707672119, 'Train/mean precision': 0.9817991852760315, 'Train/mean recall': 0.990903377532959, 'Train/mean hd95_metric': 1.7630248069763184} +Epoch [1033/4000] Validation [1/4] Loss: 0.20825 focal_loss 0.14307 dice_loss 0.06517 +Epoch [1033/4000] Validation [2/4] Loss: 0.29445 focal_loss 0.11372 dice_loss 0.18073 +Epoch [1033/4000] Validation [3/4] Loss: 0.25103 focal_loss 0.12970 dice_loss 0.12133 +Epoch [1033/4000] Validation [4/4] Loss: 0.39251 focal_loss 0.22898 dice_loss 0.16353 +Epoch [1033/4000] Validation metric {'Val/mean dice_metric': 0.9636594653129578, 'Val/mean miou_metric': 0.942112922668457, 'Val/mean f1': 0.9630249738693237, 'Val/mean precision': 0.9487687349319458, 'Val/mean recall': 0.9777161478996277, 'Val/mean hd95_metric': 8.392086029052734} +Cheakpoint... +Epoch [1033/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636594653129578, 'Val/mean miou_metric': 0.942112922668457, 'Val/mean f1': 0.9630249738693237, 'Val/mean precision': 0.9487687349319458, 'Val/mean recall': 0.9777161478996277, 'Val/mean hd95_metric': 8.392086029052734} +Epoch [1034/4000] Training [1/16] Loss: 0.01120 +Epoch [1034/4000] Training [2/16] Loss: 0.01437 +Epoch [1034/4000] Training [3/16] Loss: 0.01711 +Epoch [1034/4000] Training [4/16] Loss: 0.01070 +Epoch [1034/4000] Training [5/16] Loss: 0.01226 +Epoch [1034/4000] Training [6/16] Loss: 0.01230 +Epoch [1034/4000] Training [7/16] Loss: 0.01641 +Epoch [1034/4000] Training [8/16] Loss: 0.01112 +Epoch [1034/4000] Training [9/16] Loss: 0.01772 +Epoch [1034/4000] Training [10/16] Loss: 0.01353 +Epoch [1034/4000] Training [11/16] Loss: 0.00895 +Epoch [1034/4000] Training [12/16] Loss: 0.01201 +Epoch [1034/4000] Training [13/16] Loss: 0.01455 +Epoch [1034/4000] Training [14/16] Loss: 0.01052 +Epoch [1034/4000] Training [15/16] Loss: 0.01229 +Epoch [1034/4000] Training [16/16] Loss: 0.01606 +Epoch [1034/4000] Training metric {'Train/mean dice_metric': 0.9908758401870728, 'Train/mean miou_metric': 0.9817500710487366, 'Train/mean f1': 0.9876036643981934, 'Train/mean precision': 0.9831801056861877, 'Train/mean recall': 0.992067277431488, 'Train/mean hd95_metric': 1.3956027030944824} +Epoch [1034/4000] Validation [1/4] Loss: 0.19794 focal_loss 0.11915 dice_loss 0.07878 +Epoch [1034/4000] Validation [2/4] Loss: 0.23867 focal_loss 0.09656 dice_loss 0.14210 +Epoch [1034/4000] Validation [3/4] Loss: 0.15012 focal_loss 0.08202 dice_loss 0.06810 +Epoch [1034/4000] Validation [4/4] Loss: 0.27082 focal_loss 0.15374 dice_loss 0.11708 +Epoch [1034/4000] Validation metric {'Val/mean dice_metric': 0.9678541421890259, 'Val/mean miou_metric': 0.9468391537666321, 'Val/mean f1': 0.9696025848388672, 'Val/mean precision': 0.9650189280509949, 'Val/mean recall': 0.9742298722267151, 'Val/mean hd95_metric': 6.444227695465088} +Cheakpoint... +Epoch [1034/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678541421890259, 'Val/mean miou_metric': 0.9468391537666321, 'Val/mean f1': 0.9696025848388672, 'Val/mean precision': 0.9650189280509949, 'Val/mean recall': 0.9742298722267151, 'Val/mean hd95_metric': 6.444227695465088} +Epoch [1035/4000] Training [1/16] Loss: 0.01420 +Epoch [1035/4000] Training [2/16] Loss: 0.00976 +Epoch [1035/4000] Training [3/16] Loss: 0.00891 +Epoch [1035/4000] Training [4/16] Loss: 0.00942 +Epoch [1035/4000] Training [5/16] Loss: 0.01051 +Epoch [1035/4000] Training [6/16] Loss: 0.01099 +Epoch [1035/4000] Training [7/16] Loss: 0.01052 +Epoch [1035/4000] Training [8/16] Loss: 0.01130 +Epoch [1035/4000] Training [9/16] Loss: 0.01054 +Epoch [1035/4000] Training [10/16] Loss: 0.00891 +Epoch [1035/4000] Training [11/16] Loss: 0.01207 +Epoch [1035/4000] Training [12/16] Loss: 0.01440 +Epoch [1035/4000] Training [13/16] Loss: 0.00991 +Epoch [1035/4000] Training [14/16] Loss: 0.00998 +Epoch [1035/4000] Training [15/16] Loss: 0.01019 +Epoch [1035/4000] Training [16/16] Loss: 0.01089 +Epoch [1035/4000] Training metric {'Train/mean dice_metric': 0.9927405118942261, 'Train/mean miou_metric': 0.9853529334068298, 'Train/mean f1': 0.9889376759529114, 'Train/mean precision': 0.9844265580177307, 'Train/mean recall': 0.9934903383255005, 'Train/mean hd95_metric': 1.1196105480194092} +Epoch [1035/4000] Validation [1/4] Loss: 0.21791 focal_loss 0.14534 dice_loss 0.07257 +Epoch [1035/4000] Validation [2/4] Loss: 0.19903 focal_loss 0.07099 dice_loss 0.12804 +Epoch [1035/4000] Validation [3/4] Loss: 0.16317 focal_loss 0.08264 dice_loss 0.08053 +Epoch [1035/4000] Validation [4/4] Loss: 0.24068 focal_loss 0.10945 dice_loss 0.13123 +Epoch [1035/4000] Validation metric {'Val/mean dice_metric': 0.9704912304878235, 'Val/mean miou_metric': 0.9513251185417175, 'Val/mean f1': 0.9692321419715881, 'Val/mean precision': 0.961275041103363, 'Val/mean recall': 0.9773221015930176, 'Val/mean hd95_metric': 6.212726593017578} +Cheakpoint... +Epoch [1035/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704912304878235, 'Val/mean miou_metric': 0.9513251185417175, 'Val/mean f1': 0.9692321419715881, 'Val/mean precision': 0.961275041103363, 'Val/mean recall': 0.9773221015930176, 'Val/mean hd95_metric': 6.212726593017578} +Epoch [1036/4000] Training [1/16] Loss: 0.01425 +Epoch [1036/4000] Training [2/16] Loss: 0.01142 +Epoch [1036/4000] Training [3/16] Loss: 0.01057 +Epoch [1036/4000] Training [4/16] Loss: 0.00756 +Epoch [1036/4000] Training [5/16] Loss: 0.00959 +Epoch [1036/4000] Training [6/16] Loss: 0.01463 +Epoch [1036/4000] Training [7/16] Loss: 0.01000 +Epoch [1036/4000] Training [8/16] Loss: 0.01126 +Epoch [1036/4000] Training [9/16] Loss: 0.01414 +Epoch [1036/4000] Training [10/16] Loss: 0.01091 +Epoch [1036/4000] Training [11/16] Loss: 0.00974 +Epoch [1036/4000] Training [12/16] Loss: 0.01005 +Epoch [1036/4000] Training [13/16] Loss: 0.01279 +Epoch [1036/4000] Training [14/16] Loss: 0.00777 +Epoch [1036/4000] Training [15/16] Loss: 0.01167 +Epoch [1036/4000] Training [16/16] Loss: 0.01241 +Epoch [1036/4000] Training metric {'Train/mean dice_metric': 0.992624819278717, 'Train/mean miou_metric': 0.9851637482643127, 'Train/mean f1': 0.9890583157539368, 'Train/mean precision': 0.9845576286315918, 'Train/mean recall': 0.9936003684997559, 'Train/mean hd95_metric': 1.1387901306152344} +Epoch [1036/4000] Validation [1/4] Loss: 0.19103 focal_loss 0.12821 dice_loss 0.06282 +Epoch [1036/4000] Validation [2/4] Loss: 0.27990 focal_loss 0.12803 dice_loss 0.15186 +Epoch [1036/4000] Validation [3/4] Loss: 0.25703 focal_loss 0.13656 dice_loss 0.12048 +Epoch [1036/4000] Validation [4/4] Loss: 0.29883 focal_loss 0.15579 dice_loss 0.14304 +Epoch [1036/4000] Validation metric {'Val/mean dice_metric': 0.9680708646774292, 'Val/mean miou_metric': 0.9482653737068176, 'Val/mean f1': 0.9689874053001404, 'Val/mean precision': 0.9591647386550903, 'Val/mean recall': 0.9790132641792297, 'Val/mean hd95_metric': 6.749503135681152} +Cheakpoint... +Epoch [1036/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680708646774292, 'Val/mean miou_metric': 0.9482653737068176, 'Val/mean f1': 0.9689874053001404, 'Val/mean precision': 0.9591647386550903, 'Val/mean recall': 0.9790132641792297, 'Val/mean hd95_metric': 6.749503135681152} +Epoch [1037/4000] Training [1/16] Loss: 0.01065 +Epoch [1037/4000] Training [2/16] Loss: 0.01174 +Epoch [1037/4000] Training [3/16] Loss: 0.00878 +Epoch [1037/4000] Training [4/16] Loss: 0.01208 +Epoch [1037/4000] Training [5/16] Loss: 0.00871 +Epoch [1037/4000] Training [6/16] Loss: 0.01135 +Epoch [1037/4000] Training [7/16] Loss: 0.01071 +Epoch [1037/4000] Training [8/16] Loss: 0.01117 +Epoch [1037/4000] Training [9/16] Loss: 0.00856 +Epoch [1037/4000] Training [10/16] Loss: 0.00961 +Epoch [1037/4000] Training [11/16] Loss: 0.01074 +Epoch [1037/4000] Training [12/16] Loss: 0.01122 +Epoch [1037/4000] Training [13/16] Loss: 0.00887 +Epoch [1037/4000] Training [14/16] Loss: 0.00833 +Epoch [1037/4000] Training [15/16] Loss: 0.01119 +Epoch [1037/4000] Training [16/16] Loss: 0.01166 +Epoch [1037/4000] Training metric {'Train/mean dice_metric': 0.9928784370422363, 'Train/mean miou_metric': 0.9856199026107788, 'Train/mean f1': 0.9892886281013489, 'Train/mean precision': 0.984862744808197, 'Train/mean recall': 0.9937544465065002, 'Train/mean hd95_metric': 1.1548762321472168} +Epoch [1037/4000] Validation [1/4] Loss: 0.16675 focal_loss 0.10233 dice_loss 0.06442 +Epoch [1037/4000] Validation [2/4] Loss: 0.39850 focal_loss 0.20849 dice_loss 0.19000 +Epoch [1037/4000] Validation [3/4] Loss: 0.21773 focal_loss 0.12630 dice_loss 0.09144 +Epoch [1037/4000] Validation [4/4] Loss: 0.23098 focal_loss 0.11983 dice_loss 0.11115 +Epoch [1037/4000] Validation metric {'Val/mean dice_metric': 0.9699773788452148, 'Val/mean miou_metric': 0.9509239196777344, 'Val/mean f1': 0.9709876179695129, 'Val/mean precision': 0.9647411108016968, 'Val/mean recall': 0.9773156642913818, 'Val/mean hd95_metric': 6.220253944396973} +Cheakpoint... +Epoch [1037/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699773788452148, 'Val/mean miou_metric': 0.9509239196777344, 'Val/mean f1': 0.9709876179695129, 'Val/mean precision': 0.9647411108016968, 'Val/mean recall': 0.9773156642913818, 'Val/mean hd95_metric': 6.220253944396973} +Epoch [1038/4000] Training [1/16] Loss: 0.00884 +Epoch [1038/4000] Training [2/16] Loss: 0.01161 +Epoch [1038/4000] Training [3/16] Loss: 0.00857 +Epoch [1038/4000] Training [4/16] Loss: 0.00712 +Epoch [1038/4000] Training [5/16] Loss: 0.01051 +Epoch [1038/4000] Training [6/16] Loss: 0.00918 +Epoch [1038/4000] Training [7/16] Loss: 0.01034 +Epoch [1038/4000] Training [8/16] Loss: 0.00951 +Epoch [1038/4000] Training [9/16] Loss: 0.01054 +Epoch [1038/4000] Training [10/16] Loss: 0.01156 +Epoch [1038/4000] Training [11/16] Loss: 0.01220 +Epoch [1038/4000] Training [12/16] Loss: 0.00876 +Epoch [1038/4000] Training [13/16] Loss: 0.01285 +Epoch [1038/4000] Training [14/16] Loss: 0.00743 +Epoch [1038/4000] Training [15/16] Loss: 0.01213 +Epoch [1038/4000] Training [16/16] Loss: 0.00892 +Epoch [1038/4000] Training metric {'Train/mean dice_metric': 0.9932441115379333, 'Train/mean miou_metric': 0.9863338470458984, 'Train/mean f1': 0.9895252585411072, 'Train/mean precision': 0.9849014282226562, 'Train/mean recall': 0.9941926598548889, 'Train/mean hd95_metric': 1.0682387351989746} +Epoch [1038/4000] Validation [1/4] Loss: 0.19898 focal_loss 0.13629 dice_loss 0.06269 +Epoch [1038/4000] Validation [2/4] Loss: 0.24954 focal_loss 0.12038 dice_loss 0.12916 +Epoch [1038/4000] Validation [3/4] Loss: 0.21864 focal_loss 0.11702 dice_loss 0.10162 +Epoch [1038/4000] Validation [4/4] Loss: 0.25186 focal_loss 0.13115 dice_loss 0.12070 +Epoch [1038/4000] Validation metric {'Val/mean dice_metric': 0.9700154066085815, 'Val/mean miou_metric': 0.9512308239936829, 'Val/mean f1': 0.9719159007072449, 'Val/mean precision': 0.9662249088287354, 'Val/mean recall': 0.9776741862297058, 'Val/mean hd95_metric': 5.892740249633789} +Cheakpoint... +Epoch [1038/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700154066085815, 'Val/mean miou_metric': 0.9512308239936829, 'Val/mean f1': 0.9719159007072449, 'Val/mean precision': 0.9662249088287354, 'Val/mean recall': 0.9776741862297058, 'Val/mean hd95_metric': 5.892740249633789} +Epoch [1039/4000] Training [1/16] Loss: 0.00845 +Epoch [1039/4000] Training [2/16] Loss: 0.01381 +Epoch [1039/4000] Training [3/16] Loss: 0.01004 +Epoch [1039/4000] Training [4/16] Loss: 0.00741 +Epoch [1039/4000] Training [5/16] Loss: 0.01304 +Epoch [1039/4000] Training [6/16] Loss: 0.01025 +Epoch [1039/4000] Training [7/16] Loss: 0.00930 +Epoch [1039/4000] Training [8/16] Loss: 0.01027 +Epoch [1039/4000] Training [9/16] Loss: 0.00950 +Epoch [1039/4000] Training [10/16] Loss: 0.00861 +Epoch [1039/4000] Training [11/16] Loss: 0.01134 +Epoch [1039/4000] Training [12/16] Loss: 0.01095 +Epoch [1039/4000] Training [13/16] Loss: 0.01346 +Epoch [1039/4000] Training [14/16] Loss: 0.01348 +Epoch [1039/4000] Training [15/16] Loss: 0.00958 +Epoch [1039/4000] Training [16/16] Loss: 0.01199 +Epoch [1039/4000] Training metric {'Train/mean dice_metric': 0.9926360845565796, 'Train/mean miou_metric': 0.9851495027542114, 'Train/mean f1': 0.9890844821929932, 'Train/mean precision': 0.9845462441444397, 'Train/mean recall': 0.9936647415161133, 'Train/mean hd95_metric': 1.1873217821121216} +Epoch [1039/4000] Validation [1/4] Loss: 0.19361 focal_loss 0.12810 dice_loss 0.06551 +Epoch [1039/4000] Validation [2/4] Loss: 0.33895 focal_loss 0.17828 dice_loss 0.16067 +Epoch [1039/4000] Validation [3/4] Loss: 0.26466 focal_loss 0.16482 dice_loss 0.09984 +Epoch [1039/4000] Validation [4/4] Loss: 0.28151 focal_loss 0.15510 dice_loss 0.12641 +Epoch [1039/4000] Validation metric {'Val/mean dice_metric': 0.9680427312850952, 'Val/mean miou_metric': 0.9485963582992554, 'Val/mean f1': 0.9704682230949402, 'Val/mean precision': 0.9654989838600159, 'Val/mean recall': 0.9754889011383057, 'Val/mean hd95_metric': 6.579655647277832} +Cheakpoint... +Epoch [1039/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680427312850952, 'Val/mean miou_metric': 0.9485963582992554, 'Val/mean f1': 0.9704682230949402, 'Val/mean precision': 0.9654989838600159, 'Val/mean recall': 0.9754889011383057, 'Val/mean hd95_metric': 6.579655647277832} +Epoch [1040/4000] Training [1/16] Loss: 0.01168 +Epoch [1040/4000] Training [2/16] Loss: 0.00973 +Epoch [1040/4000] Training [3/16] Loss: 0.01003 +Epoch [1040/4000] Training [4/16] Loss: 0.01375 +Epoch [1040/4000] Training [5/16] Loss: 0.01186 +Epoch [1040/4000] Training [6/16] Loss: 0.01130 +Epoch [1040/4000] Training [7/16] Loss: 0.01152 +Epoch [1040/4000] Training [8/16] Loss: 0.01119 +Epoch [1040/4000] Training [9/16] Loss: 0.01109 +Epoch [1040/4000] Training [10/16] Loss: 0.01505 +Epoch [1040/4000] Training [11/16] Loss: 0.00892 +Epoch [1040/4000] Training [12/16] Loss: 0.00934 +Epoch [1040/4000] Training [13/16] Loss: 0.00843 +Epoch [1040/4000] Training [14/16] Loss: 0.01309 +Epoch [1040/4000] Training [15/16] Loss: 0.00902 +Epoch [1040/4000] Training [16/16] Loss: 0.01207 +Epoch [1040/4000] Training metric {'Train/mean dice_metric': 0.9921689629554749, 'Train/mean miou_metric': 0.9842327833175659, 'Train/mean f1': 0.9886294603347778, 'Train/mean precision': 0.9838907718658447, 'Train/mean recall': 0.9934139251708984, 'Train/mean hd95_metric': 1.1441755294799805} +Epoch [1040/4000] Validation [1/4] Loss: 0.17315 focal_loss 0.11349 dice_loss 0.05966 +Epoch [1040/4000] Validation [2/4] Loss: 0.45650 focal_loss 0.23774 dice_loss 0.21876 +Epoch [1040/4000] Validation [3/4] Loss: 0.19464 focal_loss 0.10664 dice_loss 0.08800 +Epoch [1040/4000] Validation [4/4] Loss: 0.26910 focal_loss 0.16013 dice_loss 0.10896 +Epoch [1040/4000] Validation metric {'Val/mean dice_metric': 0.9684101939201355, 'Val/mean miou_metric': 0.9486947059631348, 'Val/mean f1': 0.9698870778083801, 'Val/mean precision': 0.9635476469993591, 'Val/mean recall': 0.9763104319572449, 'Val/mean hd95_metric': 5.991101264953613} +Cheakpoint... +Epoch [1040/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684101939201355, 'Val/mean miou_metric': 0.9486947059631348, 'Val/mean f1': 0.9698870778083801, 'Val/mean precision': 0.9635476469993591, 'Val/mean recall': 0.9763104319572449, 'Val/mean hd95_metric': 5.991101264953613} +Epoch [1041/4000] Training [1/16] Loss: 0.01040 +Epoch [1041/4000] Training [2/16] Loss: 0.01189 +Epoch [1041/4000] Training [3/16] Loss: 0.00941 +Epoch [1041/4000] Training [4/16] Loss: 0.01173 +Epoch [1041/4000] Training [5/16] Loss: 0.01243 +Epoch [1041/4000] Training [6/16] Loss: 0.00854 +Epoch [1041/4000] Training [7/16] Loss: 0.01001 +Epoch [1041/4000] Training [8/16] Loss: 0.00913 +Epoch [1041/4000] Training [9/16] Loss: 0.00977 +Epoch [1041/4000] Training [10/16] Loss: 0.01384 +Epoch [1041/4000] Training [11/16] Loss: 0.01723 +Epoch [1041/4000] Training [12/16] Loss: 0.01058 +Epoch [1041/4000] Training [13/16] Loss: 0.00912 +Epoch [1041/4000] Training [14/16] Loss: 0.00874 +Epoch [1041/4000] Training [15/16] Loss: 0.01484 +Epoch [1041/4000] Training [16/16] Loss: 0.00950 +Epoch [1041/4000] Training metric {'Train/mean dice_metric': 0.9925177097320557, 'Train/mean miou_metric': 0.9849044680595398, 'Train/mean f1': 0.9888692498207092, 'Train/mean precision': 0.9843311309814453, 'Train/mean recall': 0.9934495091438293, 'Train/mean hd95_metric': 1.1162492036819458} +Epoch [1041/4000] Validation [1/4] Loss: 0.15122 focal_loss 0.09171 dice_loss 0.05951 +Epoch [1041/4000] Validation [2/4] Loss: 0.47164 focal_loss 0.25213 dice_loss 0.21951 +Epoch [1041/4000] Validation [3/4] Loss: 0.26784 focal_loss 0.17305 dice_loss 0.09479 +Epoch [1041/4000] Validation [4/4] Loss: 0.32834 focal_loss 0.19638 dice_loss 0.13196 +Epoch [1041/4000] Validation metric {'Val/mean dice_metric': 0.9685674905776978, 'Val/mean miou_metric': 0.9492017030715942, 'Val/mean f1': 0.9700477719306946, 'Val/mean precision': 0.9633957743644714, 'Val/mean recall': 0.9767923951148987, 'Val/mean hd95_metric': 6.346304893493652} +Cheakpoint... +Epoch [1041/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9685674905776978, 'Val/mean miou_metric': 0.9492017030715942, 'Val/mean f1': 0.9700477719306946, 'Val/mean precision': 0.9633957743644714, 'Val/mean recall': 0.9767923951148987, 'Val/mean hd95_metric': 6.346304893493652} +Epoch [1042/4000] Training [1/16] Loss: 0.00900 +Epoch [1042/4000] Training [2/16] Loss: 0.00925 +Epoch [1042/4000] Training [3/16] Loss: 0.00898 +Epoch [1042/4000] Training [4/16] Loss: 0.00936 +Epoch [1042/4000] Training [5/16] Loss: 0.01142 +Epoch [1042/4000] Training [6/16] Loss: 0.00894 +Epoch [1042/4000] Training [7/16] Loss: 0.01047 +Epoch [1042/4000] Training [8/16] Loss: 0.01424 +Epoch [1042/4000] Training [9/16] Loss: 0.01043 +Epoch [1042/4000] Training [10/16] Loss: 0.01754 +Epoch [1042/4000] Training [11/16] Loss: 0.01164 +Epoch [1042/4000] Training [12/16] Loss: 0.01402 +Epoch [1042/4000] Training [13/16] Loss: 0.01246 +Epoch [1042/4000] Training [14/16] Loss: 0.01135 +Epoch [1042/4000] Training [15/16] Loss: 0.01323 +Epoch [1042/4000] Training [16/16] Loss: 0.00943 +Epoch [1042/4000] Training metric {'Train/mean dice_metric': 0.9925971031188965, 'Train/mean miou_metric': 0.9850575923919678, 'Train/mean f1': 0.9889509081840515, 'Train/mean precision': 0.984094500541687, 'Train/mean recall': 0.9938554763793945, 'Train/mean hd95_metric': 1.121608018875122} +Epoch [1042/4000] Validation [1/4] Loss: 0.24596 focal_loss 0.16510 dice_loss 0.08085 +Epoch [1042/4000] Validation [2/4] Loss: 0.30458 focal_loss 0.15133 dice_loss 0.15324 +Epoch [1042/4000] Validation [3/4] Loss: 0.23663 focal_loss 0.12743 dice_loss 0.10920 +Epoch [1042/4000] Validation [4/4] Loss: 0.21436 focal_loss 0.11615 dice_loss 0.09822 +Epoch [1042/4000] Validation metric {'Val/mean dice_metric': 0.9688253402709961, 'Val/mean miou_metric': 0.9492675065994263, 'Val/mean f1': 0.9703564643859863, 'Val/mean precision': 0.9648760557174683, 'Val/mean recall': 0.9758995175361633, 'Val/mean hd95_metric': 6.61354923248291} +Cheakpoint... +Epoch [1042/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688253402709961, 'Val/mean miou_metric': 0.9492675065994263, 'Val/mean f1': 0.9703564643859863, 'Val/mean precision': 0.9648760557174683, 'Val/mean recall': 0.9758995175361633, 'Val/mean hd95_metric': 6.61354923248291} +Epoch [1043/4000] Training [1/16] Loss: 0.01041 +Epoch [1043/4000] Training [2/16] Loss: 0.01204 +Epoch [1043/4000] Training [3/16] Loss: 0.01049 +Epoch [1043/4000] Training [4/16] Loss: 0.00836 +Epoch [1043/4000] Training [5/16] Loss: 0.00829 +Epoch [1043/4000] Training [6/16] Loss: 0.01244 +Epoch [1043/4000] Training [7/16] Loss: 0.00890 +Epoch [1043/4000] Training [8/16] Loss: 0.00895 +Epoch [1043/4000] Training [9/16] Loss: 0.00900 +Epoch [1043/4000] Training [10/16] Loss: 0.01127 +Epoch [1043/4000] Training [11/16] Loss: 0.01052 +Epoch [1043/4000] Training [12/16] Loss: 0.00819 +Epoch [1043/4000] Training [13/16] Loss: 0.01046 +Epoch [1043/4000] Training [14/16] Loss: 0.01394 +Epoch [1043/4000] Training [15/16] Loss: 0.00895 +Epoch [1043/4000] Training [16/16] Loss: 0.00865 +Epoch [1043/4000] Training metric {'Train/mean dice_metric': 0.9926027059555054, 'Train/mean miou_metric': 0.9850910902023315, 'Train/mean f1': 0.9892104864120483, 'Train/mean precision': 0.9846326112747192, 'Train/mean recall': 0.993831217288971, 'Train/mean hd95_metric': 1.119339942932129} +Epoch [1043/4000] Validation [1/4] Loss: 0.18780 focal_loss 0.12480 dice_loss 0.06300 +Epoch [1043/4000] Validation [2/4] Loss: 0.42461 focal_loss 0.22703 dice_loss 0.19757 +Epoch [1043/4000] Validation [3/4] Loss: 0.23057 focal_loss 0.14253 dice_loss 0.08804 +Epoch [1043/4000] Validation [4/4] Loss: 0.27923 focal_loss 0.16192 dice_loss 0.11731 +Epoch [1043/4000] Validation metric {'Val/mean dice_metric': 0.9676420092582703, 'Val/mean miou_metric': 0.9494023323059082, 'Val/mean f1': 0.9714838862419128, 'Val/mean precision': 0.9684552550315857, 'Val/mean recall': 0.9745315909385681, 'Val/mean hd95_metric': 5.749166965484619} +Cheakpoint... +Epoch [1043/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676420092582703, 'Val/mean miou_metric': 0.9494023323059082, 'Val/mean f1': 0.9714838862419128, 'Val/mean precision': 0.9684552550315857, 'Val/mean recall': 0.9745315909385681, 'Val/mean hd95_metric': 5.749166965484619} +Epoch [1044/4000] Training [1/16] Loss: 0.01198 +Epoch [1044/4000] Training [2/16] Loss: 0.01302 +Epoch [1044/4000] Training [3/16] Loss: 0.03303 +Epoch [1044/4000] Training [4/16] Loss: 0.01113 +Epoch [1044/4000] Training [5/16] Loss: 0.00948 +Epoch [1044/4000] Training [6/16] Loss: 0.01321 +Epoch [1044/4000] Training [7/16] Loss: 0.00723 +Epoch [1044/4000] Training [8/16] Loss: 0.01257 +Epoch [1044/4000] Training [9/16] Loss: 0.01081 +Epoch [1044/4000] Training [10/16] Loss: 0.01152 +Epoch [1044/4000] Training [11/16] Loss: 0.00985 +Epoch [1044/4000] Training [12/16] Loss: 0.00912 +Epoch [1044/4000] Training [13/16] Loss: 0.01109 +Epoch [1044/4000] Training [14/16] Loss: 0.00814 +Epoch [1044/4000] Training [15/16] Loss: 0.00969 +Epoch [1044/4000] Training [16/16] Loss: 0.00827 +Epoch [1044/4000] Training metric {'Train/mean dice_metric': 0.9919936656951904, 'Train/mean miou_metric': 0.9839670658111572, 'Train/mean f1': 0.9889668226242065, 'Train/mean precision': 0.9843132495880127, 'Train/mean recall': 0.993664562702179, 'Train/mean hd95_metric': 1.3162610530853271} +Epoch [1044/4000] Validation [1/4] Loss: 0.21721 focal_loss 0.15233 dice_loss 0.06488 +Epoch [1044/4000] Validation [2/4] Loss: 0.34199 focal_loss 0.17564 dice_loss 0.16634 +Epoch [1044/4000] Validation [3/4] Loss: 0.26827 focal_loss 0.17170 dice_loss 0.09657 +Epoch [1044/4000] Validation [4/4] Loss: 0.25481 focal_loss 0.15206 dice_loss 0.10275 +Epoch [1044/4000] Validation metric {'Val/mean dice_metric': 0.9678224325180054, 'Val/mean miou_metric': 0.948138415813446, 'Val/mean f1': 0.9714518785476685, 'Val/mean precision': 0.9719764590263367, 'Val/mean recall': 0.970927894115448, 'Val/mean hd95_metric': 5.949080467224121} +Cheakpoint... +Epoch [1044/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678224325180054, 'Val/mean miou_metric': 0.948138415813446, 'Val/mean f1': 0.9714518785476685, 'Val/mean precision': 0.9719764590263367, 'Val/mean recall': 0.970927894115448, 'Val/mean hd95_metric': 5.949080467224121} +Epoch [1045/4000] Training [1/16] Loss: 0.01080 +Epoch [1045/4000] Training [2/16] Loss: 0.01134 +Epoch [1045/4000] Training [3/16] Loss: 0.01298 +Epoch [1045/4000] Training [4/16] Loss: 0.01022 +Epoch [1045/4000] Training [5/16] Loss: 0.00890 +Epoch [1045/4000] Training [6/16] Loss: 0.01322 +Epoch [1045/4000] Training [7/16] Loss: 0.01062 +Epoch [1045/4000] Training [8/16] Loss: 0.01266 +Epoch [1045/4000] Training [9/16] Loss: 0.01316 +Epoch [1045/4000] Training [10/16] Loss: 0.00912 +Epoch [1045/4000] Training [11/16] Loss: 0.01027 +Epoch [1045/4000] Training [12/16] Loss: 0.01696 +Epoch [1045/4000] Training [13/16] Loss: 0.01089 +Epoch [1045/4000] Training [14/16] Loss: 0.00899 +Epoch [1045/4000] Training [15/16] Loss: 0.01221 +Epoch [1045/4000] Training [16/16] Loss: 0.01176 +Epoch [1045/4000] Training metric {'Train/mean dice_metric': 0.9916008710861206, 'Train/mean miou_metric': 0.9831998348236084, 'Train/mean f1': 0.9884107112884521, 'Train/mean precision': 0.9839403629302979, 'Train/mean recall': 0.9929218292236328, 'Train/mean hd95_metric': 1.3248600959777832} +Epoch [1045/4000] Validation [1/4] Loss: 0.25150 focal_loss 0.17313 dice_loss 0.07836 +Epoch [1045/4000] Validation [2/4] Loss: 0.45053 focal_loss 0.25155 dice_loss 0.19899 +Epoch [1045/4000] Validation [3/4] Loss: 0.29406 focal_loss 0.19409 dice_loss 0.09997 +Epoch [1045/4000] Validation [4/4] Loss: 0.21248 focal_loss 0.11208 dice_loss 0.10040 +Epoch [1045/4000] Validation metric {'Val/mean dice_metric': 0.9692405462265015, 'Val/mean miou_metric': 0.9494462013244629, 'Val/mean f1': 0.9721751809120178, 'Val/mean precision': 0.9679184556007385, 'Val/mean recall': 0.9764695763587952, 'Val/mean hd95_metric': 6.1966633796691895} +Cheakpoint... +Epoch [1045/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692405462265015, 'Val/mean miou_metric': 0.9494462013244629, 'Val/mean f1': 0.9721751809120178, 'Val/mean precision': 0.9679184556007385, 'Val/mean recall': 0.9764695763587952, 'Val/mean hd95_metric': 6.1966633796691895} +Epoch [1046/4000] Training [1/16] Loss: 0.01547 +Epoch [1046/4000] Training [2/16] Loss: 0.01585 +Epoch [1046/4000] Training [3/16] Loss: 0.01016 +Epoch [1046/4000] Training [4/16] Loss: 0.00953 +Epoch [1046/4000] Training [5/16] Loss: 0.00924 +Epoch [1046/4000] Training [6/16] Loss: 0.01008 +Epoch [1046/4000] Training [7/16] Loss: 0.00864 +Epoch [1046/4000] Training [8/16] Loss: 0.01466 +Epoch [1046/4000] Training [9/16] Loss: 0.01142 +Epoch [1046/4000] Training [10/16] Loss: 0.01477 +Epoch [1046/4000] Training [11/16] Loss: 0.01491 +Epoch [1046/4000] Training [12/16] Loss: 0.01165 +Epoch [1046/4000] Training [13/16] Loss: 0.01922 +Epoch [1046/4000] Training [14/16] Loss: 0.01258 +Epoch [1046/4000] Training [15/16] Loss: 0.01399 +Epoch [1046/4000] Training [16/16] Loss: 0.01232 +Epoch [1046/4000] Training metric {'Train/mean dice_metric': 0.991464376449585, 'Train/mean miou_metric': 0.9828686118125916, 'Train/mean f1': 0.9883384704589844, 'Train/mean precision': 0.9839498996734619, 'Train/mean recall': 0.9927663207054138, 'Train/mean hd95_metric': 1.3677555322647095} +Epoch [1046/4000] Validation [1/4] Loss: 0.17222 focal_loss 0.10492 dice_loss 0.06730 +Epoch [1046/4000] Validation [2/4] Loss: 0.54844 focal_loss 0.26279 dice_loss 0.28565 +Epoch [1046/4000] Validation [3/4] Loss: 0.14495 focal_loss 0.07340 dice_loss 0.07155 +Epoch [1046/4000] Validation [4/4] Loss: 0.21115 focal_loss 0.10280 dice_loss 0.10835 +Epoch [1046/4000] Validation metric {'Val/mean dice_metric': 0.9595848917961121, 'Val/mean miou_metric': 0.9401582479476929, 'Val/mean f1': 0.9692285060882568, 'Val/mean precision': 0.9700226783752441, 'Val/mean recall': 0.968435525894165, 'Val/mean hd95_metric': 5.850701332092285} +Cheakpoint... +Epoch [1046/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9596], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9595848917961121, 'Val/mean miou_metric': 0.9401582479476929, 'Val/mean f1': 0.9692285060882568, 'Val/mean precision': 0.9700226783752441, 'Val/mean recall': 0.968435525894165, 'Val/mean hd95_metric': 5.850701332092285} +Epoch [1047/4000] Training [1/16] Loss: 0.01032 +Epoch [1047/4000] Training [2/16] Loss: 0.01265 +Epoch [1047/4000] Training [3/16] Loss: 0.01419 +Epoch [1047/4000] Training [4/16] Loss: 0.01204 +Epoch [1047/4000] Training [5/16] Loss: 0.00839 +Epoch [1047/4000] Training [6/16] Loss: 0.01200 +Epoch [1047/4000] Training [7/16] Loss: 0.01369 +Epoch [1047/4000] Training [8/16] Loss: 0.01471 +Epoch [1047/4000] Training [9/16] Loss: 0.00797 +Epoch [1047/4000] Training [10/16] Loss: 0.01231 +Epoch [1047/4000] Training [11/16] Loss: 0.01093 +Epoch [1047/4000] Training [12/16] Loss: 0.01364 +Epoch [1047/4000] Training [13/16] Loss: 0.00936 +Epoch [1047/4000] Training [14/16] Loss: 0.01098 +Epoch [1047/4000] Training [15/16] Loss: 0.01625 +Epoch [1047/4000] Training [16/16] Loss: 0.01129 +Epoch [1047/4000] Training metric {'Train/mean dice_metric': 0.9921232461929321, 'Train/mean miou_metric': 0.9841595888137817, 'Train/mean f1': 0.9887508153915405, 'Train/mean precision': 0.9841604828834534, 'Train/mean recall': 0.9933841228485107, 'Train/mean hd95_metric': 1.2156484127044678} +Epoch [1047/4000] Validation [1/4] Loss: 0.14587 focal_loss 0.08544 dice_loss 0.06042 +Epoch [1047/4000] Validation [2/4] Loss: 0.64280 focal_loss 0.35080 dice_loss 0.29199 +Epoch [1047/4000] Validation [3/4] Loss: 0.23131 focal_loss 0.13831 dice_loss 0.09301 +Epoch [1047/4000] Validation [4/4] Loss: 0.33637 focal_loss 0.19608 dice_loss 0.14028 +Epoch [1047/4000] Validation metric {'Val/mean dice_metric': 0.9667423367500305, 'Val/mean miou_metric': 0.9475776553153992, 'Val/mean f1': 0.9715191125869751, 'Val/mean precision': 0.9678562879562378, 'Val/mean recall': 0.9752098321914673, 'Val/mean hd95_metric': 5.949387073516846} +Cheakpoint... +Epoch [1047/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667423367500305, 'Val/mean miou_metric': 0.9475776553153992, 'Val/mean f1': 0.9715191125869751, 'Val/mean precision': 0.9678562879562378, 'Val/mean recall': 0.9752098321914673, 'Val/mean hd95_metric': 5.949387073516846} +Epoch [1048/4000] Training [1/16] Loss: 0.01004 +Epoch [1048/4000] Training [2/16] Loss: 0.01666 +Epoch [1048/4000] Training [3/16] Loss: 0.01040 +Epoch [1048/4000] Training [4/16] Loss: 0.01535 +Epoch [1048/4000] Training [5/16] Loss: 0.01040 +Epoch [1048/4000] Training [6/16] Loss: 0.00916 +Epoch [1048/4000] Training [7/16] Loss: 0.00981 +Epoch [1048/4000] Training [8/16] Loss: 0.00839 +Epoch [1048/4000] Training [9/16] Loss: 0.01391 +Epoch [1048/4000] Training [10/16] Loss: 0.00966 +Epoch [1048/4000] Training [11/16] Loss: 0.01060 +Epoch [1048/4000] Training [12/16] Loss: 0.01075 +Epoch [1048/4000] Training [13/16] Loss: 0.00973 +Epoch [1048/4000] Training [14/16] Loss: 0.01536 +Epoch [1048/4000] Training [15/16] Loss: 0.01536 +Epoch [1048/4000] Training [16/16] Loss: 0.01363 +Epoch [1048/4000] Training metric {'Train/mean dice_metric': 0.9916987419128418, 'Train/mean miou_metric': 0.9833405017852783, 'Train/mean f1': 0.9884697198867798, 'Train/mean precision': 0.983919620513916, 'Train/mean recall': 0.9930620789527893, 'Train/mean hd95_metric': 1.1915334463119507} +Epoch [1048/4000] Validation [1/4] Loss: 0.40332 focal_loss 0.28926 dice_loss 0.11405 +Epoch [1048/4000] Validation [2/4] Loss: 0.26605 focal_loss 0.12209 dice_loss 0.14396 +Epoch [1048/4000] Validation [3/4] Loss: 0.19675 focal_loss 0.10121 dice_loss 0.09553 +Epoch [1048/4000] Validation [4/4] Loss: 0.23652 focal_loss 0.11726 dice_loss 0.11927 +Epoch [1048/4000] Validation metric {'Val/mean dice_metric': 0.9664071798324585, 'Val/mean miou_metric': 0.9465158581733704, 'Val/mean f1': 0.9697783589363098, 'Val/mean precision': 0.9689618945121765, 'Val/mean recall': 0.9705961346626282, 'Val/mean hd95_metric': 5.6697564125061035} +Cheakpoint... +Epoch [1048/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664071798324585, 'Val/mean miou_metric': 0.9465158581733704, 'Val/mean f1': 0.9697783589363098, 'Val/mean precision': 0.9689618945121765, 'Val/mean recall': 0.9705961346626282, 'Val/mean hd95_metric': 5.6697564125061035} +Epoch [1049/4000] Training [1/16] Loss: 0.00925 +Epoch [1049/4000] Training [2/16] Loss: 0.01280 +Epoch [1049/4000] Training [3/16] Loss: 0.01209 +Epoch [1049/4000] Training [4/16] Loss: 0.01313 +Epoch [1049/4000] Training [5/16] Loss: 0.00897 +Epoch [1049/4000] Training [6/16] Loss: 0.01261 +Epoch [1049/4000] Training [7/16] Loss: 0.01013 +Epoch [1049/4000] Training [8/16] Loss: 0.00806 +Epoch [1049/4000] Training [9/16] Loss: 0.01334 +Epoch [1049/4000] Training [10/16] Loss: 0.01092 +Epoch [1049/4000] Training [11/16] Loss: 0.01264 +Epoch [1049/4000] Training [12/16] Loss: 0.01623 +Epoch [1049/4000] Training [13/16] Loss: 0.01239 +Epoch [1049/4000] Training [14/16] Loss: 0.01281 +Epoch [1049/4000] Training [15/16] Loss: 0.01118 +Epoch [1049/4000] Training [16/16] Loss: 0.00809 +Epoch [1049/4000] Training metric {'Train/mean dice_metric': 0.9917182922363281, 'Train/mean miou_metric': 0.9833236932754517, 'Train/mean f1': 0.9871695041656494, 'Train/mean precision': 0.981317937374115, 'Train/mean recall': 0.9930912256240845, 'Train/mean hd95_metric': 1.2284398078918457} +Epoch [1049/4000] Validation [1/4] Loss: 0.21460 focal_loss 0.14415 dice_loss 0.07045 +Epoch [1049/4000] Validation [2/4] Loss: 0.47120 focal_loss 0.21223 dice_loss 0.25898 +Epoch [1049/4000] Validation [3/4] Loss: 0.30065 focal_loss 0.19057 dice_loss 0.11008 +Epoch [1049/4000] Validation [4/4] Loss: 0.37652 focal_loss 0.22640 dice_loss 0.15013 +Epoch [1049/4000] Validation metric {'Val/mean dice_metric': 0.9658258557319641, 'Val/mean miou_metric': 0.9463103413581848, 'Val/mean f1': 0.9700066447257996, 'Val/mean precision': 0.9660542011260986, 'Val/mean recall': 0.9739915132522583, 'Val/mean hd95_metric': 5.553938388824463} +Cheakpoint... +Epoch [1049/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658258557319641, 'Val/mean miou_metric': 0.9463103413581848, 'Val/mean f1': 0.9700066447257996, 'Val/mean precision': 0.9660542011260986, 'Val/mean recall': 0.9739915132522583, 'Val/mean hd95_metric': 5.553938388824463} +Epoch [1050/4000] Training [1/16] Loss: 0.00807 +Epoch [1050/4000] Training [2/16] Loss: 0.01141 +Epoch [1050/4000] Training [3/16] Loss: 0.01157 +Epoch [1050/4000] Training [4/16] Loss: 0.00940 +Epoch [1050/4000] Training [5/16] Loss: 0.01135 +Epoch [1050/4000] Training [6/16] Loss: 0.01017 +Epoch [1050/4000] Training [7/16] Loss: 0.01124 +Epoch [1050/4000] Training [8/16] Loss: 0.01557 +Epoch [1050/4000] Training [9/16] Loss: 0.01019 +Epoch [1050/4000] Training [10/16] Loss: 0.01250 +Epoch [1050/4000] Training [11/16] Loss: 0.01043 +Epoch [1050/4000] Training [12/16] Loss: 0.01137 +Epoch [1050/4000] Training [13/16] Loss: 0.01011 +Epoch [1050/4000] Training [14/16] Loss: 0.01138 +Epoch [1050/4000] Training [15/16] Loss: 0.00912 +Epoch [1050/4000] Training [16/16] Loss: 0.01145 +Epoch [1050/4000] Training metric {'Train/mean dice_metric': 0.9927006363868713, 'Train/mean miou_metric': 0.9852764010429382, 'Train/mean f1': 0.9889543056488037, 'Train/mean precision': 0.984372079372406, 'Train/mean recall': 0.9935793876647949, 'Train/mean hd95_metric': 1.1341114044189453} +Epoch [1050/4000] Validation [1/4] Loss: 0.20766 focal_loss 0.13774 dice_loss 0.06992 +Epoch [1050/4000] Validation [2/4] Loss: 0.23661 focal_loss 0.12178 dice_loss 0.11483 +Epoch [1050/4000] Validation [3/4] Loss: 0.21669 focal_loss 0.11075 dice_loss 0.10594 +Epoch [1050/4000] Validation [4/4] Loss: 0.30034 focal_loss 0.17568 dice_loss 0.12466 +Epoch [1050/4000] Validation metric {'Val/mean dice_metric': 0.9678783416748047, 'Val/mean miou_metric': 0.9488973617553711, 'Val/mean f1': 0.9712409377098083, 'Val/mean precision': 0.9659919142723083, 'Val/mean recall': 0.9765474200248718, 'Val/mean hd95_metric': 5.733428478240967} +Cheakpoint... +Epoch [1050/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678783416748047, 'Val/mean miou_metric': 0.9488973617553711, 'Val/mean f1': 0.9712409377098083, 'Val/mean precision': 0.9659919142723083, 'Val/mean recall': 0.9765474200248718, 'Val/mean hd95_metric': 5.733428478240967} +Epoch [1051/4000] Training [1/16] Loss: 0.01469 +Epoch [1051/4000] Training [2/16] Loss: 0.00991 +Epoch [1051/4000] Training [3/16] Loss: 0.01261 +Epoch [1051/4000] Training [4/16] Loss: 0.01323 +Epoch [1051/4000] Training [5/16] Loss: 0.01244 +Epoch [1051/4000] Training [6/16] Loss: 0.00847 +Epoch [1051/4000] Training [7/16] Loss: 0.00753 +Epoch [1051/4000] Training [8/16] Loss: 0.01461 +Epoch [1051/4000] Training [9/16] Loss: 0.01192 +Epoch [1051/4000] Training [10/16] Loss: 0.01116 +Epoch [1051/4000] Training [11/16] Loss: 0.01005 +Epoch [1051/4000] Training [12/16] Loss: 0.01099 +Epoch [1051/4000] Training [13/16] Loss: 0.00997 +Epoch [1051/4000] Training [14/16] Loss: 0.01054 +Epoch [1051/4000] Training [15/16] Loss: 0.01328 +Epoch [1051/4000] Training [16/16] Loss: 0.01016 +Epoch [1051/4000] Training metric {'Train/mean dice_metric': 0.9923069477081299, 'Train/mean miou_metric': 0.9844701886177063, 'Train/mean f1': 0.9880894422531128, 'Train/mean precision': 0.9825422763824463, 'Train/mean recall': 0.9936996102333069, 'Train/mean hd95_metric': 1.1551704406738281} +Epoch [1051/4000] Validation [1/4] Loss: 0.17534 focal_loss 0.10729 dice_loss 0.06805 +Epoch [1051/4000] Validation [2/4] Loss: 0.24774 focal_loss 0.12303 dice_loss 0.12471 +Epoch [1051/4000] Validation [3/4] Loss: 0.28303 focal_loss 0.18208 dice_loss 0.10095 +Epoch [1051/4000] Validation [4/4] Loss: 0.33960 focal_loss 0.20009 dice_loss 0.13951 +Epoch [1051/4000] Validation metric {'Val/mean dice_metric': 0.9698472023010254, 'Val/mean miou_metric': 0.9503127932548523, 'Val/mean f1': 0.9713693261146545, 'Val/mean precision': 0.9655575752258301, 'Val/mean recall': 0.9772514700889587, 'Val/mean hd95_metric': 5.844789028167725} +Cheakpoint... +Epoch [1051/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698472023010254, 'Val/mean miou_metric': 0.9503127932548523, 'Val/mean f1': 0.9713693261146545, 'Val/mean precision': 0.9655575752258301, 'Val/mean recall': 0.9772514700889587, 'Val/mean hd95_metric': 5.844789028167725} +Epoch [1052/4000] Training [1/16] Loss: 0.01037 +Epoch [1052/4000] Training [2/16] Loss: 0.00914 +Epoch [1052/4000] Training [3/16] Loss: 0.01247 +Epoch [1052/4000] Training [4/16] Loss: 0.01150 +Epoch [1052/4000] Training [5/16] Loss: 0.00922 +Epoch [1052/4000] Training [6/16] Loss: 0.00987 +Epoch [1052/4000] Training [7/16] Loss: 0.01871 +Epoch [1052/4000] Training [8/16] Loss: 0.01131 +Epoch [1052/4000] Training [9/16] Loss: 0.00836 +Epoch [1052/4000] Training [10/16] Loss: 0.01151 +Epoch [1052/4000] Training [11/16] Loss: 0.01203 +Epoch [1052/4000] Training [12/16] Loss: 0.01059 +Epoch [1052/4000] Training [13/16] Loss: 0.00919 +Epoch [1052/4000] Training [14/16] Loss: 0.01163 +Epoch [1052/4000] Training [15/16] Loss: 0.01468 +Epoch [1052/4000] Training [16/16] Loss: 0.01174 +Epoch [1052/4000] Training metric {'Train/mean dice_metric': 0.9924414157867432, 'Train/mean miou_metric': 0.9847779273986816, 'Train/mean f1': 0.9890482425689697, 'Train/mean precision': 0.9846828579902649, 'Train/mean recall': 0.9934525489807129, 'Train/mean hd95_metric': 1.101158857345581} +Epoch [1052/4000] Validation [1/4] Loss: 0.19030 focal_loss 0.12751 dice_loss 0.06279 +Epoch [1052/4000] Validation [2/4] Loss: 0.47716 focal_loss 0.29146 dice_loss 0.18571 +Epoch [1052/4000] Validation [3/4] Loss: 0.26038 focal_loss 0.15950 dice_loss 0.10088 +Epoch [1052/4000] Validation [4/4] Loss: 0.32979 focal_loss 0.19400 dice_loss 0.13579 +Epoch [1052/4000] Validation metric {'Val/mean dice_metric': 0.9692816734313965, 'Val/mean miou_metric': 0.9506310224533081, 'Val/mean f1': 0.9724376797676086, 'Val/mean precision': 0.9692423343658447, 'Val/mean recall': 0.9756540656089783, 'Val/mean hd95_metric': 5.616049766540527} +Cheakpoint... +Epoch [1052/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692816734313965, 'Val/mean miou_metric': 0.9506310224533081, 'Val/mean f1': 0.9724376797676086, 'Val/mean precision': 0.9692423343658447, 'Val/mean recall': 0.9756540656089783, 'Val/mean hd95_metric': 5.616049766540527} +Epoch [1053/4000] Training [1/16] Loss: 0.01694 +Epoch [1053/4000] Training [2/16] Loss: 0.00892 +Epoch [1053/4000] Training [3/16] Loss: 0.00825 +Epoch [1053/4000] Training [4/16] Loss: 0.01032 +Epoch [1053/4000] Training [5/16] Loss: 0.00954 +Epoch [1053/4000] Training [6/16] Loss: 0.01532 +Epoch [1053/4000] Training [7/16] Loss: 0.01412 +Epoch [1053/4000] Training [8/16] Loss: 0.00876 +Epoch [1053/4000] Training [9/16] Loss: 0.01215 +Epoch [1053/4000] Training [10/16] Loss: 0.00856 +Epoch [1053/4000] Training [11/16] Loss: 0.01114 +Epoch [1053/4000] Training [12/16] Loss: 0.00753 +Epoch [1053/4000] Training [13/16] Loss: 0.01092 +Epoch [1053/4000] Training [14/16] Loss: 0.01013 +Epoch [1053/4000] Training [15/16] Loss: 0.01024 +Epoch [1053/4000] Training [16/16] Loss: 0.00922 +Epoch [1053/4000] Training metric {'Train/mean dice_metric': 0.9923728704452515, 'Train/mean miou_metric': 0.9846459627151489, 'Train/mean f1': 0.9887438416481018, 'Train/mean precision': 0.9845350980758667, 'Train/mean recall': 0.9929887056350708, 'Train/mean hd95_metric': 1.1708152294158936} +Epoch [1053/4000] Validation [1/4] Loss: 0.18060 focal_loss 0.12161 dice_loss 0.05899 +Epoch [1053/4000] Validation [2/4] Loss: 0.57865 focal_loss 0.31993 dice_loss 0.25872 +Epoch [1053/4000] Validation [3/4] Loss: 0.29502 focal_loss 0.19460 dice_loss 0.10043 +Epoch [1053/4000] Validation [4/4] Loss: 0.29234 focal_loss 0.15740 dice_loss 0.13494 +Epoch [1053/4000] Validation metric {'Val/mean dice_metric': 0.9672700762748718, 'Val/mean miou_metric': 0.9480101466178894, 'Val/mean f1': 0.971473217010498, 'Val/mean precision': 0.9674522876739502, 'Val/mean recall': 0.9755276441574097, 'Val/mean hd95_metric': 5.924007892608643} +Cheakpoint... +Epoch [1053/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672700762748718, 'Val/mean miou_metric': 0.9480101466178894, 'Val/mean f1': 0.971473217010498, 'Val/mean precision': 0.9674522876739502, 'Val/mean recall': 0.9755276441574097, 'Val/mean hd95_metric': 5.924007892608643} +Epoch [1054/4000] Training [1/16] Loss: 0.01094 +Epoch [1054/4000] Training [2/16] Loss: 0.01040 +Epoch [1054/4000] Training [3/16] Loss: 0.01345 +Epoch [1054/4000] Training [4/16] Loss: 0.01061 +Epoch [1054/4000] Training [5/16] Loss: 0.00820 +Epoch [1054/4000] Training [6/16] Loss: 0.01173 +Epoch [1054/4000] Training [7/16] Loss: 0.01082 +Epoch [1054/4000] Training [8/16] Loss: 0.01025 +Epoch [1054/4000] Training [9/16] Loss: 0.01365 +Epoch [1054/4000] Training [10/16] Loss: 0.01555 +Epoch [1054/4000] Training [11/16] Loss: 0.01365 +Epoch [1054/4000] Training [12/16] Loss: 0.01058 +Epoch [1054/4000] Training [13/16] Loss: 0.01570 +Epoch [1054/4000] Training [14/16] Loss: 0.01270 +Epoch [1054/4000] Training [15/16] Loss: 0.01121 +Epoch [1054/4000] Training [16/16] Loss: 0.00945 +Epoch [1054/4000] Training metric {'Train/mean dice_metric': 0.9904415011405945, 'Train/mean miou_metric': 0.981559157371521, 'Train/mean f1': 0.9881853461265564, 'Train/mean precision': 0.9835229516029358, 'Train/mean recall': 0.9928921461105347, 'Train/mean hd95_metric': 1.362409234046936} +Epoch [1054/4000] Validation [1/4] Loss: 0.20290 focal_loss 0.14122 dice_loss 0.06168 +Epoch [1054/4000] Validation [2/4] Loss: 0.31512 focal_loss 0.17478 dice_loss 0.14034 +Epoch [1054/4000] Validation [3/4] Loss: 0.32729 focal_loss 0.22531 dice_loss 0.10199 +Epoch [1054/4000] Validation [4/4] Loss: 0.29825 focal_loss 0.17296 dice_loss 0.12529 +Epoch [1054/4000] Validation metric {'Val/mean dice_metric': 0.967241644859314, 'Val/mean miou_metric': 0.9466937780380249, 'Val/mean f1': 0.9702998399734497, 'Val/mean precision': 0.9633858799934387, 'Val/mean recall': 0.9773136377334595, 'Val/mean hd95_metric': 6.273043155670166} +Cheakpoint... +Epoch [1054/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967241644859314, 'Val/mean miou_metric': 0.9466937780380249, 'Val/mean f1': 0.9702998399734497, 'Val/mean precision': 0.9633858799934387, 'Val/mean recall': 0.9773136377334595, 'Val/mean hd95_metric': 6.273043155670166} +Epoch [1055/4000] Training [1/16] Loss: 0.00904 +Epoch [1055/4000] Training [2/16] Loss: 0.01123 +Epoch [1055/4000] Training [3/16] Loss: 0.01028 +Epoch [1055/4000] Training [4/16] Loss: 0.01089 +Epoch [1055/4000] Training [5/16] Loss: 0.01266 +Epoch [1055/4000] Training [6/16] Loss: 0.01008 +Epoch [1055/4000] Training [7/16] Loss: 0.00906 +Epoch [1055/4000] Training [8/16] Loss: 0.00778 +Epoch [1055/4000] Training [9/16] Loss: 0.01522 +Epoch [1055/4000] Training [10/16] Loss: 0.01014 +Epoch [1055/4000] Training [11/16] Loss: 0.00903 +Epoch [1055/4000] Training [12/16] Loss: 0.01009 +Epoch [1055/4000] Training [13/16] Loss: 0.00958 +Epoch [1055/4000] Training [14/16] Loss: 0.01336 +Epoch [1055/4000] Training [15/16] Loss: 0.01073 +Epoch [1055/4000] Training [16/16] Loss: 0.01047 +Epoch [1055/4000] Training metric {'Train/mean dice_metric': 0.9924201965332031, 'Train/mean miou_metric': 0.9847424030303955, 'Train/mean f1': 0.9888479113578796, 'Train/mean precision': 0.984136700630188, 'Train/mean recall': 0.9936044216156006, 'Train/mean hd95_metric': 1.290260910987854} +Epoch [1055/4000] Validation [1/4] Loss: 0.39629 focal_loss 0.28184 dice_loss 0.11445 +Epoch [1055/4000] Validation [2/4] Loss: 0.15759 focal_loss 0.07128 dice_loss 0.08630 +Epoch [1055/4000] Validation [3/4] Loss: 0.26362 focal_loss 0.16631 dice_loss 0.09731 +Epoch [1055/4000] Validation [4/4] Loss: 0.35427 focal_loss 0.20154 dice_loss 0.15273 +Epoch [1055/4000] Validation metric {'Val/mean dice_metric': 0.9698696136474609, 'Val/mean miou_metric': 0.949602484703064, 'Val/mean f1': 0.9690837860107422, 'Val/mean precision': 0.9675581455230713, 'Val/mean recall': 0.9706142544746399, 'Val/mean hd95_metric': 6.084004878997803} +Cheakpoint... +Epoch [1055/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698696136474609, 'Val/mean miou_metric': 0.949602484703064, 'Val/mean f1': 0.9690837860107422, 'Val/mean precision': 0.9675581455230713, 'Val/mean recall': 0.9706142544746399, 'Val/mean hd95_metric': 6.084004878997803} +Epoch [1056/4000] Training [1/16] Loss: 0.01067 +Epoch [1056/4000] Training [2/16] Loss: 0.01005 +Epoch [1056/4000] Training [3/16] Loss: 0.01120 +Epoch [1056/4000] Training [4/16] Loss: 0.01035 +Epoch [1056/4000] Training [5/16] Loss: 0.01141 +Epoch [1056/4000] Training [6/16] Loss: 0.01449 +Epoch [1056/4000] Training [7/16] Loss: 0.01055 +Epoch [1056/4000] Training [8/16] Loss: 0.01306 +Epoch [1056/4000] Training [9/16] Loss: 0.01190 +Epoch [1056/4000] Training [10/16] Loss: 0.00927 +Epoch [1056/4000] Training [11/16] Loss: 0.01142 +Epoch [1056/4000] Training [12/16] Loss: 0.01462 +Epoch [1056/4000] Training [13/16] Loss: 0.01102 +Epoch [1056/4000] Training [14/16] Loss: 0.00948 +Epoch [1056/4000] Training [15/16] Loss: 0.01113 +Epoch [1056/4000] Training [16/16] Loss: 0.01025 +Epoch [1056/4000] Training metric {'Train/mean dice_metric': 0.9916559457778931, 'Train/mean miou_metric': 0.9832754135131836, 'Train/mean f1': 0.987280547618866, 'Train/mean precision': 0.9818616509437561, 'Train/mean recall': 0.9927595257759094, 'Train/mean hd95_metric': 1.719085454940796} +Epoch [1056/4000] Validation [1/4] Loss: 0.19722 focal_loss 0.13484 dice_loss 0.06238 +Epoch [1056/4000] Validation [2/4] Loss: 0.38703 focal_loss 0.21037 dice_loss 0.17666 +Epoch [1056/4000] Validation [3/4] Loss: 0.29073 focal_loss 0.19379 dice_loss 0.09694 +Epoch [1056/4000] Validation [4/4] Loss: 0.27050 focal_loss 0.13665 dice_loss 0.13385 +Epoch [1056/4000] Validation metric {'Val/mean dice_metric': 0.9660933613777161, 'Val/mean miou_metric': 0.9456101655960083, 'Val/mean f1': 0.9677028059959412, 'Val/mean precision': 0.9633001685142517, 'Val/mean recall': 0.9721459746360779, 'Val/mean hd95_metric': 6.44595193862915} +Cheakpoint... +Epoch [1056/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660933613777161, 'Val/mean miou_metric': 0.9456101655960083, 'Val/mean f1': 0.9677028059959412, 'Val/mean precision': 0.9633001685142517, 'Val/mean recall': 0.9721459746360779, 'Val/mean hd95_metric': 6.44595193862915} +Epoch [1057/4000] Training [1/16] Loss: 0.01314 +Epoch [1057/4000] Training [2/16] Loss: 0.01011 +Epoch [1057/4000] Training [3/16] Loss: 0.01048 +Epoch [1057/4000] Training [4/16] Loss: 0.01206 +Epoch [1057/4000] Training [5/16] Loss: 0.01301 +Epoch [1057/4000] Training [6/16] Loss: 0.01243 +Epoch [1057/4000] Training [7/16] Loss: 0.01202 +Epoch [1057/4000] Training [8/16] Loss: 0.00904 +Epoch [1057/4000] Training [9/16] Loss: 0.03073 +Epoch [1057/4000] Training [10/16] Loss: 0.01040 +Epoch [1057/4000] Training [11/16] Loss: 0.01040 +Epoch [1057/4000] Training [12/16] Loss: 0.00945 +Epoch [1057/4000] Training [13/16] Loss: 0.02201 +Epoch [1057/4000] Training [14/16] Loss: 0.01768 +Epoch [1057/4000] Training [15/16] Loss: 0.01264 +Epoch [1057/4000] Training [16/16] Loss: 0.01595 +Epoch [1057/4000] Training metric {'Train/mean dice_metric': 0.9910995960235596, 'Train/mean miou_metric': 0.9822105765342712, 'Train/mean f1': 0.9870798587799072, 'Train/mean precision': 0.9827135801315308, 'Train/mean recall': 0.9914851188659668, 'Train/mean hd95_metric': 1.7390880584716797} +Epoch [1057/4000] Validation [1/4] Loss: 0.42715 focal_loss 0.31057 dice_loss 0.11658 +Epoch [1057/4000] Validation [2/4] Loss: 0.38987 focal_loss 0.18982 dice_loss 0.20006 +Epoch [1057/4000] Validation [3/4] Loss: 0.14085 focal_loss 0.06958 dice_loss 0.07127 +Epoch [1057/4000] Validation [4/4] Loss: 0.36222 focal_loss 0.19200 dice_loss 0.17022 +Epoch [1057/4000] Validation metric {'Val/mean dice_metric': 0.96210777759552, 'Val/mean miou_metric': 0.9401754140853882, 'Val/mean f1': 0.9604611992835999, 'Val/mean precision': 0.9516869783401489, 'Val/mean recall': 0.9693987965583801, 'Val/mean hd95_metric': 7.118666648864746} +Cheakpoint... +Epoch [1057/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9621], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96210777759552, 'Val/mean miou_metric': 0.9401754140853882, 'Val/mean f1': 0.9604611992835999, 'Val/mean precision': 0.9516869783401489, 'Val/mean recall': 0.9693987965583801, 'Val/mean hd95_metric': 7.118666648864746} +Epoch [1058/4000] Training [1/16] Loss: 0.01155 +Epoch [1058/4000] Training [2/16] Loss: 0.01300 +Epoch [1058/4000] Training [3/16] Loss: 0.01556 +Epoch [1058/4000] Training [4/16] Loss: 0.01460 +Epoch [1058/4000] Training [5/16] Loss: 0.01060 +Epoch [1058/4000] Training [6/16] Loss: 0.01139 +Epoch [1058/4000] Training [7/16] Loss: 0.07135 +Epoch [1058/4000] Training [8/16] Loss: 0.01429 +Epoch [1058/4000] Training [9/16] Loss: 0.00957 +Epoch [1058/4000] Training [10/16] Loss: 0.01616 +Epoch [1058/4000] Training [11/16] Loss: 0.01712 +Epoch [1058/4000] Training [12/16] Loss: 0.01099 +Epoch [1058/4000] Training [13/16] Loss: 0.01244 +Epoch [1058/4000] Training [14/16] Loss: 0.02105 +Epoch [1058/4000] Training [15/16] Loss: 0.01646 +Epoch [1058/4000] Training [16/16] Loss: 0.01471 +Epoch [1058/4000] Training metric {'Train/mean dice_metric': 0.9886237382888794, 'Train/mean miou_metric': 0.9781378507614136, 'Train/mean f1': 0.9838412404060364, 'Train/mean precision': 0.9815251231193542, 'Train/mean recall': 0.9861683249473572, 'Train/mean hd95_metric': 2.638129711151123} +Epoch [1058/4000] Validation [1/4] Loss: 0.47597 focal_loss 0.34738 dice_loss 0.12859 +Epoch [1058/4000] Validation [2/4] Loss: 0.27136 focal_loss 0.13567 dice_loss 0.13569 +Epoch [1058/4000] Validation [3/4] Loss: 0.39681 focal_loss 0.25826 dice_loss 0.13854 +Epoch [1058/4000] Validation [4/4] Loss: 0.31538 focal_loss 0.18407 dice_loss 0.13131 +Epoch [1058/4000] Validation metric {'Val/mean dice_metric': 0.9599620699882507, 'Val/mean miou_metric': 0.936221718788147, 'Val/mean f1': 0.9611354470252991, 'Val/mean precision': 0.9612300395965576, 'Val/mean recall': 0.9610407948493958, 'Val/mean hd95_metric': 8.457685470581055} +Cheakpoint... +Epoch [1058/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9600], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9599620699882507, 'Val/mean miou_metric': 0.936221718788147, 'Val/mean f1': 0.9611354470252991, 'Val/mean precision': 0.9612300395965576, 'Val/mean recall': 0.9610407948493958, 'Val/mean hd95_metric': 8.457685470581055} +Epoch [1059/4000] Training [1/16] Loss: 0.01646 +Epoch [1059/4000] Training [2/16] Loss: 0.02776 +Epoch [1059/4000] Training [3/16] Loss: 0.03135 +Epoch [1059/4000] Training [4/16] Loss: 0.01717 +Epoch [1059/4000] Training [5/16] Loss: 0.03573 +Epoch [1059/4000] Training [6/16] Loss: 0.01422 +Epoch [1059/4000] Training [7/16] Loss: 0.01032 +Epoch [1059/4000] Training [8/16] Loss: 0.01481 +Epoch [1059/4000] Training [9/16] Loss: 0.01540 +Epoch [1059/4000] Training [10/16] Loss: 0.04114 +Epoch [1059/4000] Training [11/16] Loss: 0.01237 +Epoch [1059/4000] Training [12/16] Loss: 0.01277 +Epoch [1059/4000] Training [13/16] Loss: 0.01667 +Epoch [1059/4000] Training [14/16] Loss: 0.01593 +Epoch [1059/4000] Training [15/16] Loss: 0.01723 +Epoch [1059/4000] Training [16/16] Loss: 0.01212 +Epoch [1059/4000] Training metric {'Train/mean dice_metric': 0.9882566928863525, 'Train/mean miou_metric': 0.9768213033676147, 'Train/mean f1': 0.9832140207290649, 'Train/mean precision': 0.9771848320960999, 'Train/mean recall': 0.9893180727958679, 'Train/mean hd95_metric': 3.615112781524658} +Epoch [1059/4000] Validation [1/4] Loss: 0.29461 focal_loss 0.19949 dice_loss 0.09511 +Epoch [1059/4000] Validation [2/4] Loss: 0.26929 focal_loss 0.11495 dice_loss 0.15433 +Epoch [1059/4000] Validation [3/4] Loss: 0.18734 focal_loss 0.09247 dice_loss 0.09487 +Epoch [1059/4000] Validation [4/4] Loss: 0.22157 focal_loss 0.11758 dice_loss 0.10399 +Epoch [1059/4000] Validation metric {'Val/mean dice_metric': 0.9617072939872742, 'Val/mean miou_metric': 0.9379348754882812, 'Val/mean f1': 0.9614593386650085, 'Val/mean precision': 0.9519373774528503, 'Val/mean recall': 0.9711736440658569, 'Val/mean hd95_metric': 8.600427627563477} +Cheakpoint... +Epoch [1059/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9617], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9617072939872742, 'Val/mean miou_metric': 0.9379348754882812, 'Val/mean f1': 0.9614593386650085, 'Val/mean precision': 0.9519373774528503, 'Val/mean recall': 0.9711736440658569, 'Val/mean hd95_metric': 8.600427627563477} +Epoch [1060/4000] Training [1/16] Loss: 0.01157 +Epoch [1060/4000] Training [2/16] Loss: 0.01383 +Epoch [1060/4000] Training [3/16] Loss: 0.01748 +Epoch [1060/4000] Training [4/16] Loss: 0.02146 +Epoch [1060/4000] Training [5/16] Loss: 0.01516 +Epoch [1060/4000] Training [6/16] Loss: 0.02151 +Epoch [1060/4000] Training [7/16] Loss: 0.01359 +Epoch [1060/4000] Training [8/16] Loss: 0.01039 +Epoch [1060/4000] Training [9/16] Loss: 0.00912 +Epoch [1060/4000] Training [10/16] Loss: 0.01333 +Epoch [1060/4000] Training [11/16] Loss: 0.01776 +Epoch [1060/4000] Training [12/16] Loss: 0.01414 +Epoch [1060/4000] Training [13/16] Loss: 0.01241 +Epoch [1060/4000] Training [14/16] Loss: 0.01196 +Epoch [1060/4000] Training [15/16] Loss: 0.01312 +Epoch [1060/4000] Training [16/16] Loss: 0.06504 +Epoch [1060/4000] Training metric {'Train/mean dice_metric': 0.9892410635948181, 'Train/mean miou_metric': 0.9789574146270752, 'Train/mean f1': 0.9861698150634766, 'Train/mean precision': 0.9820760488510132, 'Train/mean recall': 0.990297794342041, 'Train/mean hd95_metric': 2.615450143814087} +Epoch [1060/4000] Validation [1/4] Loss: 0.52178 focal_loss 0.37727 dice_loss 0.14451 +Epoch [1060/4000] Validation [2/4] Loss: 0.28532 focal_loss 0.11934 dice_loss 0.16598 +Epoch [1060/4000] Validation [3/4] Loss: 0.31028 focal_loss 0.16775 dice_loss 0.14253 +Epoch [1060/4000] Validation [4/4] Loss: 0.56111 focal_loss 0.33189 dice_loss 0.22922 +Epoch [1060/4000] Validation metric {'Val/mean dice_metric': 0.9595263600349426, 'Val/mean miou_metric': 0.9357999563217163, 'Val/mean f1': 0.9615811109542847, 'Val/mean precision': 0.9651110172271729, 'Val/mean recall': 0.9580768942832947, 'Val/mean hd95_metric': 7.949909210205078} +Cheakpoint... +Epoch [1060/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9595], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9595263600349426, 'Val/mean miou_metric': 0.9357999563217163, 'Val/mean f1': 0.9615811109542847, 'Val/mean precision': 0.9651110172271729, 'Val/mean recall': 0.9580768942832947, 'Val/mean hd95_metric': 7.949909210205078} +Epoch [1061/4000] Training [1/16] Loss: 0.01653 +Epoch [1061/4000] Training [2/16] Loss: 0.01948 +Epoch [1061/4000] Training [3/16] Loss: 0.01097 +Epoch [1061/4000] Training [4/16] Loss: 0.01561 +Epoch [1061/4000] Training [5/16] Loss: 0.01034 +Epoch [1061/4000] Training [6/16] Loss: 0.02117 +Epoch [1061/4000] Training [7/16] Loss: 0.01063 +Epoch [1061/4000] Training [8/16] Loss: 0.01474 +Epoch [1061/4000] Training [9/16] Loss: 0.01274 +Epoch [1061/4000] Training [10/16] Loss: 0.01840 +Epoch [1061/4000] Training [11/16] Loss: 0.01370 +Epoch [1061/4000] Training [12/16] Loss: 0.01015 +Epoch [1061/4000] Training [13/16] Loss: 0.01210 +Epoch [1061/4000] Training [14/16] Loss: 0.01835 +Epoch [1061/4000] Training [15/16] Loss: 0.01577 +Epoch [1061/4000] Training [16/16] Loss: 0.01080 +Epoch [1061/4000] Training metric {'Train/mean dice_metric': 0.9895652532577515, 'Train/mean miou_metric': 0.9795578718185425, 'Train/mean f1': 0.985855758190155, 'Train/mean precision': 0.9825259447097778, 'Train/mean recall': 0.9892082214355469, 'Train/mean hd95_metric': 1.8559296131134033} +Epoch [1061/4000] Validation [1/4] Loss: 0.31596 focal_loss 0.21741 dice_loss 0.09855 +Epoch [1061/4000] Validation [2/4] Loss: 0.40129 focal_loss 0.19742 dice_loss 0.20387 +Epoch [1061/4000] Validation [3/4] Loss: 0.25478 focal_loss 0.13548 dice_loss 0.11930 +Epoch [1061/4000] Validation [4/4] Loss: 0.33367 focal_loss 0.18775 dice_loss 0.14592 +Epoch [1061/4000] Validation metric {'Val/mean dice_metric': 0.9647461175918579, 'Val/mean miou_metric': 0.9421746134757996, 'Val/mean f1': 0.9648733139038086, 'Val/mean precision': 0.9621176719665527, 'Val/mean recall': 0.9676446914672852, 'Val/mean hd95_metric': 7.515460014343262} +Cheakpoint... +Epoch [1061/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647461175918579, 'Val/mean miou_metric': 0.9421746134757996, 'Val/mean f1': 0.9648733139038086, 'Val/mean precision': 0.9621176719665527, 'Val/mean recall': 0.9676446914672852, 'Val/mean hd95_metric': 7.515460014343262} +Epoch [1062/4000] Training [1/16] Loss: 0.01359 +Epoch [1062/4000] Training [2/16] Loss: 0.01246 +Epoch [1062/4000] Training [3/16] Loss: 0.01534 +Epoch [1062/4000] Training [4/16] Loss: 0.00928 +Epoch [1062/4000] Training [5/16] Loss: 0.01486 +Epoch [1062/4000] Training [6/16] Loss: 0.01459 +Epoch [1062/4000] Training [7/16] Loss: 0.01429 +Epoch [1062/4000] Training [8/16] Loss: 0.02260 +Epoch [1062/4000] Training [9/16] Loss: 0.01292 +Epoch [1062/4000] Training [10/16] Loss: 0.01130 +Epoch [1062/4000] Training [11/16] Loss: 0.01141 +Epoch [1062/4000] Training [12/16] Loss: 0.00977 +Epoch [1062/4000] Training [13/16] Loss: 0.01036 +Epoch [1062/4000] Training [14/16] Loss: 0.01046 +Epoch [1062/4000] Training [15/16] Loss: 0.01136 +Epoch [1062/4000] Training [16/16] Loss: 0.00978 +Epoch [1062/4000] Training metric {'Train/mean dice_metric': 0.9912916421890259, 'Train/mean miou_metric': 0.9825762510299683, 'Train/mean f1': 0.9877884387969971, 'Train/mean precision': 0.9825583100318909, 'Train/mean recall': 0.9930745363235474, 'Train/mean hd95_metric': 1.7513689994812012} +Epoch [1062/4000] Validation [1/4] Loss: 0.18737 focal_loss 0.12177 dice_loss 0.06560 +Epoch [1062/4000] Validation [2/4] Loss: 0.45280 focal_loss 0.25371 dice_loss 0.19909 +Epoch [1062/4000] Validation [3/4] Loss: 0.24705 focal_loss 0.14490 dice_loss 0.10215 +Epoch [1062/4000] Validation [4/4] Loss: 0.30360 focal_loss 0.14430 dice_loss 0.15930 +Epoch [1062/4000] Validation metric {'Val/mean dice_metric': 0.9644718170166016, 'Val/mean miou_metric': 0.9431869387626648, 'Val/mean f1': 0.9652521014213562, 'Val/mean precision': 0.954224705696106, 'Val/mean recall': 0.9765371084213257, 'Val/mean hd95_metric': 8.011204719543457} +Cheakpoint... +Epoch [1062/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644718170166016, 'Val/mean miou_metric': 0.9431869387626648, 'Val/mean f1': 0.9652521014213562, 'Val/mean precision': 0.954224705696106, 'Val/mean recall': 0.9765371084213257, 'Val/mean hd95_metric': 8.011204719543457} +Epoch [1063/4000] Training [1/16] Loss: 0.01624 +Epoch [1063/4000] Training [2/16] Loss: 0.01379 +Epoch [1063/4000] Training [3/16] Loss: 0.01014 +Epoch [1063/4000] Training [4/16] Loss: 0.01494 +Epoch [1063/4000] Training [5/16] Loss: 0.01256 +Epoch [1063/4000] Training [6/16] Loss: 0.01137 +Epoch [1063/4000] Training [7/16] Loss: 0.00945 +Epoch [1063/4000] Training [8/16] Loss: 0.01050 +Epoch [1063/4000] Training [9/16] Loss: 0.01382 +Epoch [1063/4000] Training [10/16] Loss: 0.01556 +Epoch [1063/4000] Training [11/16] Loss: 0.01187 +Epoch [1063/4000] Training [12/16] Loss: 0.01023 +Epoch [1063/4000] Training [13/16] Loss: 0.01097 +Epoch [1063/4000] Training [14/16] Loss: 0.00932 +Epoch [1063/4000] Training [15/16] Loss: 0.01582 +Epoch [1063/4000] Training [16/16] Loss: 0.01452 +Epoch [1063/4000] Training metric {'Train/mean dice_metric': 0.9911079406738281, 'Train/mean miou_metric': 0.9823411703109741, 'Train/mean f1': 0.9875867366790771, 'Train/mean precision': 0.9832250475883484, 'Train/mean recall': 0.9919873476028442, 'Train/mean hd95_metric': 1.822008728981018} +Epoch [1063/4000] Validation [1/4] Loss: 0.18294 focal_loss 0.11993 dice_loss 0.06301 +Epoch [1063/4000] Validation [2/4] Loss: 0.29030 focal_loss 0.11537 dice_loss 0.17493 +Epoch [1063/4000] Validation [3/4] Loss: 0.14836 focal_loss 0.07696 dice_loss 0.07140 +Epoch [1063/4000] Validation [4/4] Loss: 0.33733 focal_loss 0.20549 dice_loss 0.13184 +Epoch [1063/4000] Validation metric {'Val/mean dice_metric': 0.9645305871963501, 'Val/mean miou_metric': 0.9436332583427429, 'Val/mean f1': 0.9671381115913391, 'Val/mean precision': 0.9654291272163391, 'Val/mean recall': 0.9688531160354614, 'Val/mean hd95_metric': 6.8399457931518555} +Cheakpoint... +Epoch [1063/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645305871963501, 'Val/mean miou_metric': 0.9436332583427429, 'Val/mean f1': 0.9671381115913391, 'Val/mean precision': 0.9654291272163391, 'Val/mean recall': 0.9688531160354614, 'Val/mean hd95_metric': 6.8399457931518555} +Epoch [1064/4000] Training [1/16] Loss: 0.02016 +Epoch [1064/4000] Training [2/16] Loss: 0.00970 +Epoch [1064/4000] Training [3/16] Loss: 0.01156 +Epoch [1064/4000] Training [4/16] Loss: 0.00917 +Epoch [1064/4000] Training [5/16] Loss: 0.01061 +Epoch [1064/4000] Training [6/16] Loss: 0.01096 +Epoch [1064/4000] Training [7/16] Loss: 0.01475 +Epoch [1064/4000] Training [8/16] Loss: 0.01386 +Epoch [1064/4000] Training [9/16] Loss: 0.00891 +Epoch [1064/4000] Training [10/16] Loss: 0.01119 +Epoch [1064/4000] Training [11/16] Loss: 0.01148 +Epoch [1064/4000] Training [12/16] Loss: 0.00792 +Epoch [1064/4000] Training [13/16] Loss: 0.01039 +Epoch [1064/4000] Training [14/16] Loss: 0.01001 +Epoch [1064/4000] Training [15/16] Loss: 0.01025 +Epoch [1064/4000] Training [16/16] Loss: 0.01329 +Epoch [1064/4000] Training metric {'Train/mean dice_metric': 0.9923549890518188, 'Train/mean miou_metric': 0.9845622777938843, 'Train/mean f1': 0.9880195260047913, 'Train/mean precision': 0.9826668500900269, 'Train/mean recall': 0.9934307932853699, 'Train/mean hd95_metric': 1.1686254739761353} +Epoch [1064/4000] Validation [1/4] Loss: 0.20879 focal_loss 0.13841 dice_loss 0.07038 +Epoch [1064/4000] Validation [2/4] Loss: 0.41513 focal_loss 0.24421 dice_loss 0.17092 +Epoch [1064/4000] Validation [3/4] Loss: 0.22334 focal_loss 0.12321 dice_loss 0.10013 +Epoch [1064/4000] Validation [4/4] Loss: 0.24869 focal_loss 0.13799 dice_loss 0.11070 +Epoch [1064/4000] Validation metric {'Val/mean dice_metric': 0.9693841934204102, 'Val/mean miou_metric': 0.9501361846923828, 'Val/mean f1': 0.9702357053756714, 'Val/mean precision': 0.9653104543685913, 'Val/mean recall': 0.9752116203308105, 'Val/mean hd95_metric': 5.914198398590088} +Cheakpoint... +Epoch [1064/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693841934204102, 'Val/mean miou_metric': 0.9501361846923828, 'Val/mean f1': 0.9702357053756714, 'Val/mean precision': 0.9653104543685913, 'Val/mean recall': 0.9752116203308105, 'Val/mean hd95_metric': 5.914198398590088} +Epoch [1065/4000] Training [1/16] Loss: 0.01035 +Epoch [1065/4000] Training [2/16] Loss: 0.01239 +Epoch [1065/4000] Training [3/16] Loss: 0.00968 +Epoch [1065/4000] Training [4/16] Loss: 0.01405 +Epoch [1065/4000] Training [5/16] Loss: 0.00794 +Epoch [1065/4000] Training [6/16] Loss: 0.07421 +Epoch [1065/4000] Training [7/16] Loss: 0.01220 +Epoch [1065/4000] Training [8/16] Loss: 0.00861 +Epoch [1065/4000] Training [9/16] Loss: 0.01361 +Epoch [1065/4000] Training [10/16] Loss: 0.00924 +Epoch [1065/4000] Training [11/16] Loss: 0.00794 +Epoch [1065/4000] Training [12/16] Loss: 0.01187 +Epoch [1065/4000] Training [13/16] Loss: 0.00867 +Epoch [1065/4000] Training [14/16] Loss: 0.01035 +Epoch [1065/4000] Training [15/16] Loss: 0.00972 +Epoch [1065/4000] Training [16/16] Loss: 0.01156 +Epoch [1065/4000] Training metric {'Train/mean dice_metric': 0.9915924072265625, 'Train/mean miou_metric': 0.983575701713562, 'Train/mean f1': 0.988337516784668, 'Train/mean precision': 0.9837696552276611, 'Train/mean recall': 0.9929479956626892, 'Train/mean hd95_metric': 2.0908026695251465} +Epoch [1065/4000] Validation [1/4] Loss: 0.19972 focal_loss 0.13356 dice_loss 0.06616 +Epoch [1065/4000] Validation [2/4] Loss: 0.23898 focal_loss 0.11281 dice_loss 0.12616 +Epoch [1065/4000] Validation [3/4] Loss: 0.34054 focal_loss 0.19266 dice_loss 0.14788 +Epoch [1065/4000] Validation [4/4] Loss: 0.20187 focal_loss 0.10769 dice_loss 0.09418 +Epoch [1065/4000] Validation metric {'Val/mean dice_metric': 0.9690492749214172, 'Val/mean miou_metric': 0.9489234089851379, 'Val/mean f1': 0.9685995578765869, 'Val/mean precision': 0.9583090543746948, 'Val/mean recall': 0.9791135191917419, 'Val/mean hd95_metric': 7.897253513336182} +Cheakpoint... +Epoch [1065/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690492749214172, 'Val/mean miou_metric': 0.9489234089851379, 'Val/mean f1': 0.9685995578765869, 'Val/mean precision': 0.9583090543746948, 'Val/mean recall': 0.9791135191917419, 'Val/mean hd95_metric': 7.897253513336182} +Epoch [1066/4000] Training [1/16] Loss: 0.01310 +Epoch [1066/4000] Training [2/16] Loss: 0.01482 +Epoch [1066/4000] Training [3/16] Loss: 0.00975 +Epoch [1066/4000] Training [4/16] Loss: 0.01063 +Epoch [1066/4000] Training [5/16] Loss: 0.00947 +Epoch [1066/4000] Training [6/16] Loss: 0.01680 +Epoch [1066/4000] Training [7/16] Loss: 0.00977 +Epoch [1066/4000] Training [8/16] Loss: 0.00928 +Epoch [1066/4000] Training [9/16] Loss: 0.01082 +Epoch [1066/4000] Training [10/16] Loss: 0.01178 +Epoch [1066/4000] Training [11/16] Loss: 0.01199 +Epoch [1066/4000] Training [12/16] Loss: 0.01380 +Epoch [1066/4000] Training [13/16] Loss: 0.01305 +Epoch [1066/4000] Training [14/16] Loss: 0.01003 +Epoch [1066/4000] Training [15/16] Loss: 0.01337 +Epoch [1066/4000] Training [16/16] Loss: 0.01261 +Epoch [1066/4000] Training metric {'Train/mean dice_metric': 0.9921891093254089, 'Train/mean miou_metric': 0.9842503070831299, 'Train/mean f1': 0.9873965978622437, 'Train/mean precision': 0.9822413325309753, 'Train/mean recall': 0.9926062226295471, 'Train/mean hd95_metric': 1.714142918586731} +Epoch [1066/4000] Validation [1/4] Loss: 0.24650 focal_loss 0.15028 dice_loss 0.09622 +Epoch [1066/4000] Validation [2/4] Loss: 0.31358 focal_loss 0.13908 dice_loss 0.17451 +Epoch [1066/4000] Validation [3/4] Loss: 0.32675 focal_loss 0.19430 dice_loss 0.13245 +Epoch [1066/4000] Validation [4/4] Loss: 0.51512 focal_loss 0.32406 dice_loss 0.19106 +Epoch [1066/4000] Validation metric {'Val/mean dice_metric': 0.9646625518798828, 'Val/mean miou_metric': 0.9438045620918274, 'Val/mean f1': 0.9657305479049683, 'Val/mean precision': 0.9621835350990295, 'Val/mean recall': 0.9693037867546082, 'Val/mean hd95_metric': 7.352226257324219} +Cheakpoint... +Epoch [1066/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9646625518798828, 'Val/mean miou_metric': 0.9438045620918274, 'Val/mean f1': 0.9657305479049683, 'Val/mean precision': 0.9621835350990295, 'Val/mean recall': 0.9693037867546082, 'Val/mean hd95_metric': 7.352226257324219} +Epoch [1067/4000] Training [1/16] Loss: 0.01096 +Epoch [1067/4000] Training [2/16] Loss: 0.01411 +Epoch [1067/4000] Training [3/16] Loss: 0.01090 +Epoch [1067/4000] Training [4/16] Loss: 0.01280 +Epoch [1067/4000] Training [5/16] Loss: 0.01662 +Epoch [1067/4000] Training [6/16] Loss: 0.01391 +Epoch [1067/4000] Training [7/16] Loss: 0.01071 +Epoch [1067/4000] Training [8/16] Loss: 0.01020 +Epoch [1067/4000] Training [9/16] Loss: 0.01299 +Epoch [1067/4000] Training [10/16] Loss: 0.01009 +Epoch [1067/4000] Training [11/16] Loss: 0.01103 +Epoch [1067/4000] Training [12/16] Loss: 0.01022 +Epoch [1067/4000] Training [13/16] Loss: 0.01022 +Epoch [1067/4000] Training [14/16] Loss: 0.01046 +Epoch [1067/4000] Training [15/16] Loss: 0.01416 +Epoch [1067/4000] Training [16/16] Loss: 0.00907 +Epoch [1067/4000] Training metric {'Train/mean dice_metric': 0.9918032884597778, 'Train/mean miou_metric': 0.9835706353187561, 'Train/mean f1': 0.9883334636688232, 'Train/mean precision': 0.9838762283325195, 'Train/mean recall': 0.9928313493728638, 'Train/mean hd95_metric': 1.3982062339782715} +Epoch [1067/4000] Validation [1/4] Loss: 0.19091 focal_loss 0.12739 dice_loss 0.06352 +Epoch [1067/4000] Validation [2/4] Loss: 0.42328 focal_loss 0.21307 dice_loss 0.21021 +Epoch [1067/4000] Validation [3/4] Loss: 0.28893 focal_loss 0.17978 dice_loss 0.10915 +Epoch [1067/4000] Validation [4/4] Loss: 0.30957 focal_loss 0.16666 dice_loss 0.14291 +Epoch [1067/4000] Validation metric {'Val/mean dice_metric': 0.9667970538139343, 'Val/mean miou_metric': 0.9463062286376953, 'Val/mean f1': 0.9686766862869263, 'Val/mean precision': 0.961968183517456, 'Val/mean recall': 0.9754793643951416, 'Val/mean hd95_metric': 6.571078300476074} +Cheakpoint... +Epoch [1067/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667970538139343, 'Val/mean miou_metric': 0.9463062286376953, 'Val/mean f1': 0.9686766862869263, 'Val/mean precision': 0.961968183517456, 'Val/mean recall': 0.9754793643951416, 'Val/mean hd95_metric': 6.571078300476074} +Epoch [1068/4000] Training [1/16] Loss: 0.01138 +Epoch [1068/4000] Training [2/16] Loss: 0.00973 +Epoch [1068/4000] Training [3/16] Loss: 0.01102 +Epoch [1068/4000] Training [4/16] Loss: 0.00930 +Epoch [1068/4000] Training [5/16] Loss: 0.01012 +Epoch [1068/4000] Training [6/16] Loss: 0.01430 +Epoch [1068/4000] Training [7/16] Loss: 0.00931 +Epoch [1068/4000] Training [8/16] Loss: 0.01430 +Epoch [1068/4000] Training [9/16] Loss: 0.01219 +Epoch [1068/4000] Training [10/16] Loss: 0.00955 +Epoch [1068/4000] Training [11/16] Loss: 0.01144 +Epoch [1068/4000] Training [12/16] Loss: 0.01602 +Epoch [1068/4000] Training [13/16] Loss: 0.00912 +Epoch [1068/4000] Training [14/16] Loss: 0.00977 +Epoch [1068/4000] Training [15/16] Loss: 0.01058 +Epoch [1068/4000] Training [16/16] Loss: 0.01408 +Epoch [1068/4000] Training metric {'Train/mean dice_metric': 0.9915783405303955, 'Train/mean miou_metric': 0.9833115339279175, 'Train/mean f1': 0.9882959723472595, 'Train/mean precision': 0.9834778904914856, 'Train/mean recall': 0.9931615591049194, 'Train/mean hd95_metric': 1.7363553047180176} +Epoch [1068/4000] Validation [1/4] Loss: 0.25763 focal_loss 0.17726 dice_loss 0.08037 +Epoch [1068/4000] Validation [2/4] Loss: 0.48714 focal_loss 0.24695 dice_loss 0.24019 +Epoch [1068/4000] Validation [3/4] Loss: 0.25442 focal_loss 0.15849 dice_loss 0.09593 +Epoch [1068/4000] Validation [4/4] Loss: 0.29407 focal_loss 0.15582 dice_loss 0.13826 +Epoch [1068/4000] Validation metric {'Val/mean dice_metric': 0.9656341671943665, 'Val/mean miou_metric': 0.9448869824409485, 'Val/mean f1': 0.9673048853874207, 'Val/mean precision': 0.962640643119812, 'Val/mean recall': 0.9720146656036377, 'Val/mean hd95_metric': 6.897982597351074} +Cheakpoint... +Epoch [1068/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656341671943665, 'Val/mean miou_metric': 0.9448869824409485, 'Val/mean f1': 0.9673048853874207, 'Val/mean precision': 0.962640643119812, 'Val/mean recall': 0.9720146656036377, 'Val/mean hd95_metric': 6.897982597351074} +Epoch [1069/4000] Training [1/16] Loss: 0.01603 +Epoch [1069/4000] Training [2/16] Loss: 0.01259 +Epoch [1069/4000] Training [3/16] Loss: 0.00941 +Epoch [1069/4000] Training [4/16] Loss: 0.01022 +Epoch [1069/4000] Training [5/16] Loss: 0.01173 +Epoch [1069/4000] Training [6/16] Loss: 0.01094 +Epoch [1069/4000] Training [7/16] Loss: 0.01301 +Epoch [1069/4000] Training [8/16] Loss: 0.00823 +Epoch [1069/4000] Training [9/16] Loss: 0.01335 +Epoch [1069/4000] Training [10/16] Loss: 0.01089 +Epoch [1069/4000] Training [11/16] Loss: 0.01131 +Epoch [1069/4000] Training [12/16] Loss: 0.00850 +Epoch [1069/4000] Training [13/16] Loss: 0.07314 +Epoch [1069/4000] Training [14/16] Loss: 0.00961 +Epoch [1069/4000] Training [15/16] Loss: 0.00684 +Epoch [1069/4000] Training [16/16] Loss: 0.01108 +Epoch [1069/4000] Training metric {'Train/mean dice_metric': 0.9918185472488403, 'Train/mean miou_metric': 0.9840136766433716, 'Train/mean f1': 0.9886268973350525, 'Train/mean precision': 0.9839277267456055, 'Train/mean recall': 0.9933710694313049, 'Train/mean hd95_metric': 1.1852840185165405} +Epoch [1069/4000] Validation [1/4] Loss: 0.17552 focal_loss 0.10985 dice_loss 0.06567 +Epoch [1069/4000] Validation [2/4] Loss: 0.37355 focal_loss 0.17613 dice_loss 0.19742 +Epoch [1069/4000] Validation [3/4] Loss: 0.26504 focal_loss 0.16693 dice_loss 0.09811 +Epoch [1069/4000] Validation [4/4] Loss: 0.21757 focal_loss 0.10146 dice_loss 0.11611 +Epoch [1069/4000] Validation metric {'Val/mean dice_metric': 0.9678219556808472, 'Val/mean miou_metric': 0.9478487968444824, 'Val/mean f1': 0.9702357053756714, 'Val/mean precision': 0.964000940322876, 'Val/mean recall': 0.9765517115592957, 'Val/mean hd95_metric': 6.310255527496338} +Cheakpoint... +Epoch [1069/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678219556808472, 'Val/mean miou_metric': 0.9478487968444824, 'Val/mean f1': 0.9702357053756714, 'Val/mean precision': 0.964000940322876, 'Val/mean recall': 0.9765517115592957, 'Val/mean hd95_metric': 6.310255527496338} +Epoch [1070/4000] Training [1/16] Loss: 0.01274 +Epoch [1070/4000] Training [2/16] Loss: 0.01270 +Epoch [1070/4000] Training [3/16] Loss: 0.01325 +Epoch [1070/4000] Training [4/16] Loss: 0.00790 +Epoch [1070/4000] Training [5/16] Loss: 0.01006 +Epoch [1070/4000] Training [6/16] Loss: 0.01073 +Epoch [1070/4000] Training [7/16] Loss: 0.00891 +Epoch [1070/4000] Training [8/16] Loss: 0.00981 +Epoch [1070/4000] Training [9/16] Loss: 0.01325 +Epoch [1070/4000] Training [10/16] Loss: 0.00906 +Epoch [1070/4000] Training [11/16] Loss: 0.01104 +Epoch [1070/4000] Training [12/16] Loss: 0.00962 +Epoch [1070/4000] Training [13/16] Loss: 0.01013 +Epoch [1070/4000] Training [14/16] Loss: 0.01087 +Epoch [1070/4000] Training [15/16] Loss: 0.01079 +Epoch [1070/4000] Training [16/16] Loss: 0.00854 +Epoch [1070/4000] Training metric {'Train/mean dice_metric': 0.9928659200668335, 'Train/mean miou_metric': 0.9855961799621582, 'Train/mean f1': 0.9889775514602661, 'Train/mean precision': 0.9844380617141724, 'Train/mean recall': 0.9935592412948608, 'Train/mean hd95_metric': 1.1532564163208008} +Epoch [1070/4000] Validation [1/4] Loss: 0.17531 focal_loss 0.11411 dice_loss 0.06120 +Epoch [1070/4000] Validation [2/4] Loss: 0.44057 focal_loss 0.23415 dice_loss 0.20642 +Epoch [1070/4000] Validation [3/4] Loss: 0.30915 focal_loss 0.18775 dice_loss 0.12140 +Epoch [1070/4000] Validation [4/4] Loss: 0.40674 focal_loss 0.24979 dice_loss 0.15696 +Epoch [1070/4000] Validation metric {'Val/mean dice_metric': 0.9672872424125671, 'Val/mean miou_metric': 0.947521984577179, 'Val/mean f1': 0.968442440032959, 'Val/mean precision': 0.9624935984611511, 'Val/mean recall': 0.9744653105735779, 'Val/mean hd95_metric': 6.495693206787109} +Cheakpoint... +Epoch [1070/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672872424125671, 'Val/mean miou_metric': 0.947521984577179, 'Val/mean f1': 0.968442440032959, 'Val/mean precision': 0.9624935984611511, 'Val/mean recall': 0.9744653105735779, 'Val/mean hd95_metric': 6.495693206787109} +Epoch [1071/4000] Training [1/16] Loss: 0.01083 +Epoch [1071/4000] Training [2/16] Loss: 0.00950 +Epoch [1071/4000] Training [3/16] Loss: 0.01059 +Epoch [1071/4000] Training [4/16] Loss: 0.01026 +Epoch [1071/4000] Training [5/16] Loss: 0.00975 +Epoch [1071/4000] Training [6/16] Loss: 0.00934 +Epoch [1071/4000] Training [7/16] Loss: 0.01278 +Epoch [1071/4000] Training [8/16] Loss: 0.01034 +Epoch [1071/4000] Training [9/16] Loss: 0.01347 +Epoch [1071/4000] Training [10/16] Loss: 0.01297 +Epoch [1071/4000] Training [11/16] Loss: 0.01019 +Epoch [1071/4000] Training [12/16] Loss: 0.00994 +Epoch [1071/4000] Training [13/16] Loss: 0.00992 +Epoch [1071/4000] Training [14/16] Loss: 0.01153 +Epoch [1071/4000] Training [15/16] Loss: 0.01290 +Epoch [1071/4000] Training [16/16] Loss: 0.01027 +Epoch [1071/4000] Training metric {'Train/mean dice_metric': 0.9926879405975342, 'Train/mean miou_metric': 0.985257625579834, 'Train/mean f1': 0.9891482591629028, 'Train/mean precision': 0.9845721125602722, 'Train/mean recall': 0.9937672019004822, 'Train/mean hd95_metric': 1.335172414779663} +Epoch [1071/4000] Validation [1/4] Loss: 0.17083 focal_loss 0.10764 dice_loss 0.06319 +Epoch [1071/4000] Validation [2/4] Loss: 0.32370 focal_loss 0.14922 dice_loss 0.17448 +Epoch [1071/4000] Validation [3/4] Loss: 0.15817 focal_loss 0.07854 dice_loss 0.07964 +Epoch [1071/4000] Validation [4/4] Loss: 0.25145 focal_loss 0.15710 dice_loss 0.09436 +Epoch [1071/4000] Validation metric {'Val/mean dice_metric': 0.968071460723877, 'Val/mean miou_metric': 0.9491103887557983, 'Val/mean f1': 0.970648467540741, 'Val/mean precision': 0.9663123488426208, 'Val/mean recall': 0.975023627281189, 'Val/mean hd95_metric': 6.303792476654053} +Cheakpoint... +Epoch [1071/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968071460723877, 'Val/mean miou_metric': 0.9491103887557983, 'Val/mean f1': 0.970648467540741, 'Val/mean precision': 0.9663123488426208, 'Val/mean recall': 0.975023627281189, 'Val/mean hd95_metric': 6.303792476654053} +Epoch [1072/4000] Training [1/16] Loss: 0.00945 +Epoch [1072/4000] Training [2/16] Loss: 0.01208 +Epoch [1072/4000] Training [3/16] Loss: 0.01126 +Epoch [1072/4000] Training [4/16] Loss: 0.00840 +Epoch [1072/4000] Training [5/16] Loss: 0.00686 +Epoch [1072/4000] Training [6/16] Loss: 0.01262 +Epoch [1072/4000] Training [7/16] Loss: 0.01371 +Epoch [1072/4000] Training [8/16] Loss: 0.01061 +Epoch [1072/4000] Training [9/16] Loss: 0.00903 +Epoch [1072/4000] Training [10/16] Loss: 0.01014 +Epoch [1072/4000] Training [11/16] Loss: 0.01051 +Epoch [1072/4000] Training [12/16] Loss: 0.01070 +Epoch [1072/4000] Training [13/16] Loss: 0.01082 +Epoch [1072/4000] Training [14/16] Loss: 0.01101 +Epoch [1072/4000] Training [15/16] Loss: 0.01015 +Epoch [1072/4000] Training [16/16] Loss: 0.00957 +Epoch [1072/4000] Training metric {'Train/mean dice_metric': 0.9926434755325317, 'Train/mean miou_metric': 0.9851678609848022, 'Train/mean f1': 0.9891366958618164, 'Train/mean precision': 0.9846341609954834, 'Train/mean recall': 0.9936806559562683, 'Train/mean hd95_metric': 1.2170944213867188} +Epoch [1072/4000] Validation [1/4] Loss: 0.18930 focal_loss 0.12583 dice_loss 0.06347 +Epoch [1072/4000] Validation [2/4] Loss: 0.29867 focal_loss 0.14313 dice_loss 0.15554 +Epoch [1072/4000] Validation [3/4] Loss: 0.27952 focal_loss 0.18272 dice_loss 0.09680 +Epoch [1072/4000] Validation [4/4] Loss: 0.25141 focal_loss 0.13722 dice_loss 0.11419 +Epoch [1072/4000] Validation metric {'Val/mean dice_metric': 0.9679073095321655, 'Val/mean miou_metric': 0.9481194615364075, 'Val/mean f1': 0.9697312712669373, 'Val/mean precision': 0.9619410037994385, 'Val/mean recall': 0.977648913860321, 'Val/mean hd95_metric': 6.428226470947266} +Cheakpoint... +Epoch [1072/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679073095321655, 'Val/mean miou_metric': 0.9481194615364075, 'Val/mean f1': 0.9697312712669373, 'Val/mean precision': 0.9619410037994385, 'Val/mean recall': 0.977648913860321, 'Val/mean hd95_metric': 6.428226470947266} +Epoch [1073/4000] Training [1/16] Loss: 0.01424 +Epoch [1073/4000] Training [2/16] Loss: 0.01181 +Epoch [1073/4000] Training [3/16] Loss: 0.00945 +Epoch [1073/4000] Training [4/16] Loss: 0.01820 +Epoch [1073/4000] Training [5/16] Loss: 0.00971 +Epoch [1073/4000] Training [6/16] Loss: 0.00850 +Epoch [1073/4000] Training [7/16] Loss: 0.01156 +Epoch [1073/4000] Training [8/16] Loss: 0.00968 +Epoch [1073/4000] Training [9/16] Loss: 0.01065 +Epoch [1073/4000] Training [10/16] Loss: 0.01426 +Epoch [1073/4000] Training [11/16] Loss: 0.01170 +Epoch [1073/4000] Training [12/16] Loss: 0.01301 +Epoch [1073/4000] Training [13/16] Loss: 0.01249 +Epoch [1073/4000] Training [14/16] Loss: 0.01059 +Epoch [1073/4000] Training [15/16] Loss: 0.01090 +Epoch [1073/4000] Training [16/16] Loss: 0.01127 +Epoch [1073/4000] Training metric {'Train/mean dice_metric': 0.9919623136520386, 'Train/mean miou_metric': 0.9838435053825378, 'Train/mean f1': 0.9883870482444763, 'Train/mean precision': 0.9837655425071716, 'Train/mean recall': 0.9930521845817566, 'Train/mean hd95_metric': 1.2125656604766846} +Epoch [1073/4000] Validation [1/4] Loss: 0.20116 focal_loss 0.13518 dice_loss 0.06598 +Epoch [1073/4000] Validation [2/4] Loss: 0.30309 focal_loss 0.13836 dice_loss 0.16473 +Epoch [1073/4000] Validation [3/4] Loss: 0.28644 focal_loss 0.19804 dice_loss 0.08840 +Epoch [1073/4000] Validation [4/4] Loss: 0.27888 focal_loss 0.15755 dice_loss 0.12133 +Epoch [1073/4000] Validation metric {'Val/mean dice_metric': 0.9696536064147949, 'Val/mean miou_metric': 0.9500943422317505, 'Val/mean f1': 0.9715014100074768, 'Val/mean precision': 0.9687723517417908, 'Val/mean recall': 0.9742458462715149, 'Val/mean hd95_metric': 5.5348801612854} +Cheakpoint... +Epoch [1073/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696536064147949, 'Val/mean miou_metric': 0.9500943422317505, 'Val/mean f1': 0.9715014100074768, 'Val/mean precision': 0.9687723517417908, 'Val/mean recall': 0.9742458462715149, 'Val/mean hd95_metric': 5.5348801612854} +Epoch [1074/4000] Training [1/16] Loss: 0.00848 +Epoch [1074/4000] Training [2/16] Loss: 0.01491 +Epoch [1074/4000] Training [3/16] Loss: 0.00931 +Epoch [1074/4000] Training [4/16] Loss: 0.02051 +Epoch [1074/4000] Training [5/16] Loss: 0.01091 +Epoch [1074/4000] Training [6/16] Loss: 0.01007 +Epoch [1074/4000] Training [7/16] Loss: 0.02036 +Epoch [1074/4000] Training [8/16] Loss: 0.01182 +Epoch [1074/4000] Training [9/16] Loss: 0.00944 +Epoch [1074/4000] Training [10/16] Loss: 0.01146 +Epoch [1074/4000] Training [11/16] Loss: 0.01091 +Epoch [1074/4000] Training [12/16] Loss: 0.01074 +Epoch [1074/4000] Training [13/16] Loss: 0.00982 +Epoch [1074/4000] Training [14/16] Loss: 0.01368 +Epoch [1074/4000] Training [15/16] Loss: 0.01131 +Epoch [1074/4000] Training [16/16] Loss: 0.00875 +Epoch [1074/4000] Training metric {'Train/mean dice_metric': 0.9918832778930664, 'Train/mean miou_metric': 0.9837560653686523, 'Train/mean f1': 0.9887804388999939, 'Train/mean precision': 0.9842001795768738, 'Train/mean recall': 0.9934035539627075, 'Train/mean hd95_metric': 1.313378095626831} +Epoch [1074/4000] Validation [1/4] Loss: 0.21902 focal_loss 0.14157 dice_loss 0.07745 +Epoch [1074/4000] Validation [2/4] Loss: 0.28912 focal_loss 0.12639 dice_loss 0.16273 +Epoch [1074/4000] Validation [3/4] Loss: 0.15928 focal_loss 0.09155 dice_loss 0.06772 +Epoch [1074/4000] Validation [4/4] Loss: 0.38563 focal_loss 0.22910 dice_loss 0.15653 +Epoch [1074/4000] Validation metric {'Val/mean dice_metric': 0.9662595987319946, 'Val/mean miou_metric': 0.9463062286376953, 'Val/mean f1': 0.9697543382644653, 'Val/mean precision': 0.971558153629303, 'Val/mean recall': 0.967957079410553, 'Val/mean hd95_metric': 5.698078632354736} +Cheakpoint... +Epoch [1074/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662595987319946, 'Val/mean miou_metric': 0.9463062286376953, 'Val/mean f1': 0.9697543382644653, 'Val/mean precision': 0.971558153629303, 'Val/mean recall': 0.967957079410553, 'Val/mean hd95_metric': 5.698078632354736} +Epoch [1075/4000] Training [1/16] Loss: 0.01055 +Epoch [1075/4000] Training [2/16] Loss: 0.01117 +Epoch [1075/4000] Training [3/16] Loss: 0.00745 +Epoch [1075/4000] Training [4/16] Loss: 0.01246 +Epoch [1075/4000] Training [5/16] Loss: 0.00896 +Epoch [1075/4000] Training [6/16] Loss: 0.00890 +Epoch [1075/4000] Training [7/16] Loss: 0.00856 +Epoch [1075/4000] Training [8/16] Loss: 0.01500 +Epoch [1075/4000] Training [9/16] Loss: 0.00885 +Epoch [1075/4000] Training [10/16] Loss: 0.01408 +Epoch [1075/4000] Training [11/16] Loss: 0.01064 +Epoch [1075/4000] Training [12/16] Loss: 0.01386 +Epoch [1075/4000] Training [13/16] Loss: 0.00946 +Epoch [1075/4000] Training [14/16] Loss: 0.00972 +Epoch [1075/4000] Training [15/16] Loss: 0.00961 +Epoch [1075/4000] Training [16/16] Loss: 0.01139 +Epoch [1075/4000] Training metric {'Train/mean dice_metric': 0.9920859336853027, 'Train/mean miou_metric': 0.984067440032959, 'Train/mean f1': 0.9884963035583496, 'Train/mean precision': 0.983974814414978, 'Train/mean recall': 0.9930594563484192, 'Train/mean hd95_metric': 1.1837435960769653} +Epoch [1075/4000] Validation [1/4] Loss: 0.20513 focal_loss 0.12844 dice_loss 0.07669 +Epoch [1075/4000] Validation [2/4] Loss: 0.29855 focal_loss 0.15200 dice_loss 0.14655 +Epoch [1075/4000] Validation [3/4] Loss: 0.25985 focal_loss 0.16550 dice_loss 0.09435 +Epoch [1075/4000] Validation [4/4] Loss: 0.29075 focal_loss 0.16087 dice_loss 0.12989 +Epoch [1075/4000] Validation metric {'Val/mean dice_metric': 0.9679232835769653, 'Val/mean miou_metric': 0.9484115839004517, 'Val/mean f1': 0.9709272384643555, 'Val/mean precision': 0.9682481288909912, 'Val/mean recall': 0.9736211895942688, 'Val/mean hd95_metric': 5.973454475402832} +Cheakpoint... +Epoch [1075/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679232835769653, 'Val/mean miou_metric': 0.9484115839004517, 'Val/mean f1': 0.9709272384643555, 'Val/mean precision': 0.9682481288909912, 'Val/mean recall': 0.9736211895942688, 'Val/mean hd95_metric': 5.973454475402832} +Epoch [1076/4000] Training [1/16] Loss: 0.00873 +Epoch [1076/4000] Training [2/16] Loss: 0.01404 +Epoch [1076/4000] Training [3/16] Loss: 0.01243 +Epoch [1076/4000] Training [4/16] Loss: 0.01790 +Epoch [1076/4000] Training [5/16] Loss: 0.01054 +Epoch [1076/4000] Training [6/16] Loss: 0.00935 +Epoch [1076/4000] Training [7/16] Loss: 0.00769 +Epoch [1076/4000] Training [8/16] Loss: 0.01160 +Epoch [1076/4000] Training [9/16] Loss: 0.00892 +Epoch [1076/4000] Training [10/16] Loss: 0.01134 +Epoch [1076/4000] Training [11/16] Loss: 0.01184 +Epoch [1076/4000] Training [12/16] Loss: 0.01182 +Epoch [1076/4000] Training [13/16] Loss: 0.02057 +Epoch [1076/4000] Training [14/16] Loss: 0.00968 +Epoch [1076/4000] Training [15/16] Loss: 0.01030 +Epoch [1076/4000] Training [16/16] Loss: 0.01018 +Epoch [1076/4000] Training metric {'Train/mean dice_metric': 0.9925148487091064, 'Train/mean miou_metric': 0.9849271774291992, 'Train/mean f1': 0.9890961050987244, 'Train/mean precision': 0.9845610857009888, 'Train/mean recall': 0.9936730265617371, 'Train/mean hd95_metric': 1.1498210430145264} +Epoch [1076/4000] Validation [1/4] Loss: 0.17847 focal_loss 0.11881 dice_loss 0.05966 +Epoch [1076/4000] Validation [2/4] Loss: 0.43819 focal_loss 0.22230 dice_loss 0.21589 +Epoch [1076/4000] Validation [3/4] Loss: 0.17077 focal_loss 0.09125 dice_loss 0.07953 +Epoch [1076/4000] Validation [4/4] Loss: 0.22509 focal_loss 0.12319 dice_loss 0.10190 +Epoch [1076/4000] Validation metric {'Val/mean dice_metric': 0.9683269262313843, 'Val/mean miou_metric': 0.948530375957489, 'Val/mean f1': 0.9704450368881226, 'Val/mean precision': 0.9664140939712524, 'Val/mean recall': 0.9745097160339355, 'Val/mean hd95_metric': 6.740329742431641} +Cheakpoint... +Epoch [1076/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683269262313843, 'Val/mean miou_metric': 0.948530375957489, 'Val/mean f1': 0.9704450368881226, 'Val/mean precision': 0.9664140939712524, 'Val/mean recall': 0.9745097160339355, 'Val/mean hd95_metric': 6.740329742431641} +Epoch [1077/4000] Training [1/16] Loss: 0.01062 +Epoch [1077/4000] Training [2/16] Loss: 0.00828 +Epoch [1077/4000] Training [3/16] Loss: 0.01197 +Epoch [1077/4000] Training [4/16] Loss: 0.00938 +Epoch [1077/4000] Training [5/16] Loss: 0.00905 +Epoch [1077/4000] Training [6/16] Loss: 0.00949 +Epoch [1077/4000] Training [7/16] Loss: 0.01210 +Epoch [1077/4000] Training [8/16] Loss: 0.01093 +Epoch [1077/4000] Training [9/16] Loss: 0.01069 +Epoch [1077/4000] Training [10/16] Loss: 0.00928 +Epoch [1077/4000] Training [11/16] Loss: 0.00956 +Epoch [1077/4000] Training [12/16] Loss: 0.03780 +Epoch [1077/4000] Training [13/16] Loss: 0.01714 +Epoch [1077/4000] Training [14/16] Loss: 0.01190 +Epoch [1077/4000] Training [15/16] Loss: 0.01088 +Epoch [1077/4000] Training [16/16] Loss: 0.00938 +Epoch [1077/4000] Training metric {'Train/mean dice_metric': 0.9912967085838318, 'Train/mean miou_metric': 0.982686460018158, 'Train/mean f1': 0.9881973266601562, 'Train/mean precision': 0.9835337996482849, 'Train/mean recall': 0.9929051995277405, 'Train/mean hd95_metric': 1.7044689655303955} +Epoch [1077/4000] Validation [1/4] Loss: 0.14533 focal_loss 0.09418 dice_loss 0.05115 +Epoch [1077/4000] Validation [2/4] Loss: 0.28997 focal_loss 0.15419 dice_loss 0.13578 +Epoch [1077/4000] Validation [3/4] Loss: 0.30642 focal_loss 0.21368 dice_loss 0.09274 +Epoch [1077/4000] Validation [4/4] Loss: 0.32973 focal_loss 0.19077 dice_loss 0.13896 +Epoch [1077/4000] Validation metric {'Val/mean dice_metric': 0.9680944681167603, 'Val/mean miou_metric': 0.9478498697280884, 'Val/mean f1': 0.9692671895027161, 'Val/mean precision': 0.9622415900230408, 'Val/mean recall': 0.9763962626457214, 'Val/mean hd95_metric': 6.223829746246338} +Cheakpoint... +Epoch [1077/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680944681167603, 'Val/mean miou_metric': 0.9478498697280884, 'Val/mean f1': 0.9692671895027161, 'Val/mean precision': 0.9622415900230408, 'Val/mean recall': 0.9763962626457214, 'Val/mean hd95_metric': 6.223829746246338} +Epoch [1078/4000] Training [1/16] Loss: 0.01416 +Epoch [1078/4000] Training [2/16] Loss: 0.01214 +Epoch [1078/4000] Training [3/16] Loss: 0.00931 +Epoch [1078/4000] Training [4/16] Loss: 0.01317 +Epoch [1078/4000] Training [5/16] Loss: 0.01215 +Epoch [1078/4000] Training [6/16] Loss: 0.02374 +Epoch [1078/4000] Training [7/16] Loss: 0.01298 +Epoch [1078/4000] Training [8/16] Loss: 0.00975 +Epoch [1078/4000] Training [9/16] Loss: 0.01101 +Epoch [1078/4000] Training [10/16] Loss: 0.01197 +Epoch [1078/4000] Training [11/16] Loss: 0.01093 +Epoch [1078/4000] Training [12/16] Loss: 0.01041 +Epoch [1078/4000] Training [13/16] Loss: 0.01284 +Epoch [1078/4000] Training [14/16] Loss: 0.01042 +Epoch [1078/4000] Training [15/16] Loss: 0.01269 +Epoch [1078/4000] Training [16/16] Loss: 0.01455 +Epoch [1078/4000] Training metric {'Train/mean dice_metric': 0.9912622570991516, 'Train/mean miou_metric': 0.9825280904769897, 'Train/mean f1': 0.9880216717720032, 'Train/mean precision': 0.9834140539169312, 'Train/mean recall': 0.9926726222038269, 'Train/mean hd95_metric': 1.2812480926513672} +Epoch [1078/4000] Validation [1/4] Loss: 0.18074 focal_loss 0.11763 dice_loss 0.06311 +Epoch [1078/4000] Validation [2/4] Loss: 0.43658 focal_loss 0.23938 dice_loss 0.19720 +Epoch [1078/4000] Validation [3/4] Loss: 0.28821 focal_loss 0.17839 dice_loss 0.10982 +Epoch [1078/4000] Validation [4/4] Loss: 0.30066 focal_loss 0.15797 dice_loss 0.14269 +Epoch [1078/4000] Validation metric {'Val/mean dice_metric': 0.964402973651886, 'Val/mean miou_metric': 0.9438384175300598, 'Val/mean f1': 0.9687986373901367, 'Val/mean precision': 0.9644887447357178, 'Val/mean recall': 0.9731470942497253, 'Val/mean hd95_metric': 6.411807060241699} +Cheakpoint... +Epoch [1078/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964402973651886, 'Val/mean miou_metric': 0.9438384175300598, 'Val/mean f1': 0.9687986373901367, 'Val/mean precision': 0.9644887447357178, 'Val/mean recall': 0.9731470942497253, 'Val/mean hd95_metric': 6.411807060241699} +Epoch [1079/4000] Training [1/16] Loss: 0.00976 +Epoch [1079/4000] Training [2/16] Loss: 0.01971 +Epoch [1079/4000] Training [3/16] Loss: 0.01104 +Epoch [1079/4000] Training [4/16] Loss: 0.01168 +Epoch [1079/4000] Training [5/16] Loss: 0.00991 +Epoch [1079/4000] Training [6/16] Loss: 0.01037 +Epoch [1079/4000] Training [7/16] Loss: 0.00819 +Epoch [1079/4000] Training [8/16] Loss: 0.01520 +Epoch [1079/4000] Training [9/16] Loss: 0.00980 +Epoch [1079/4000] Training [10/16] Loss: 0.01670 +Epoch [1079/4000] Training [11/16] Loss: 0.03233 +Epoch [1079/4000] Training [12/16] Loss: 0.01204 +Epoch [1079/4000] Training [13/16] Loss: 0.01173 +Epoch [1079/4000] Training [14/16] Loss: 0.01150 +Epoch [1079/4000] Training [15/16] Loss: 0.00855 +Epoch [1079/4000] Training [16/16] Loss: 0.01120 +Epoch [1079/4000] Training metric {'Train/mean dice_metric': 0.9919664859771729, 'Train/mean miou_metric': 0.9839178323745728, 'Train/mean f1': 0.9886326193809509, 'Train/mean precision': 0.9836844205856323, 'Train/mean recall': 0.9936308264732361, 'Train/mean hd95_metric': 1.158482551574707} +Epoch [1079/4000] Validation [1/4] Loss: 0.18681 focal_loss 0.12740 dice_loss 0.05941 +Epoch [1079/4000] Validation [2/4] Loss: 0.23471 focal_loss 0.10439 dice_loss 0.13032 +Epoch [1079/4000] Validation [3/4] Loss: 0.29196 focal_loss 0.19535 dice_loss 0.09661 +Epoch [1079/4000] Validation [4/4] Loss: 0.46362 focal_loss 0.29582 dice_loss 0.16780 +Epoch [1079/4000] Validation metric {'Val/mean dice_metric': 0.9671165347099304, 'Val/mean miou_metric': 0.9463306665420532, 'Val/mean f1': 0.9690884947776794, 'Val/mean precision': 0.96393883228302, 'Val/mean recall': 0.9742935299873352, 'Val/mean hd95_metric': 7.020442008972168} +Cheakpoint... +Epoch [1079/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671165347099304, 'Val/mean miou_metric': 0.9463306665420532, 'Val/mean f1': 0.9690884947776794, 'Val/mean precision': 0.96393883228302, 'Val/mean recall': 0.9742935299873352, 'Val/mean hd95_metric': 7.020442008972168} +Epoch [1080/4000] Training [1/16] Loss: 0.01100 +Epoch [1080/4000] Training [2/16] Loss: 0.01183 +Epoch [1080/4000] Training [3/16] Loss: 0.01146 +Epoch [1080/4000] Training [4/16] Loss: 0.01656 +Epoch [1080/4000] Training [5/16] Loss: 0.00940 +Epoch [1080/4000] Training [6/16] Loss: 0.00764 +Epoch [1080/4000] Training [7/16] Loss: 0.01119 +Epoch [1080/4000] Training [8/16] Loss: 0.01035 +Epoch [1080/4000] Training [9/16] Loss: 0.01151 +Epoch [1080/4000] Training [10/16] Loss: 0.01112 +Epoch [1080/4000] Training [11/16] Loss: 0.01196 +Epoch [1080/4000] Training [12/16] Loss: 0.01558 +Epoch [1080/4000] Training [13/16] Loss: 0.01066 +Epoch [1080/4000] Training [14/16] Loss: 0.00855 +Epoch [1080/4000] Training [15/16] Loss: 0.00965 +Epoch [1080/4000] Training [16/16] Loss: 0.00937 +Epoch [1080/4000] Training metric {'Train/mean dice_metric': 0.9923986196517944, 'Train/mean miou_metric': 0.9846962094306946, 'Train/mean f1': 0.9889255166053772, 'Train/mean precision': 0.984442412853241, 'Train/mean recall': 0.9934496879577637, 'Train/mean hd95_metric': 1.1482003927230835} +Epoch [1080/4000] Validation [1/4] Loss: 0.17391 focal_loss 0.11679 dice_loss 0.05712 +Epoch [1080/4000] Validation [2/4] Loss: 0.24288 focal_loss 0.11975 dice_loss 0.12313 +Epoch [1080/4000] Validation [3/4] Loss: 0.23355 focal_loss 0.13287 dice_loss 0.10069 +Epoch [1080/4000] Validation [4/4] Loss: 0.30385 focal_loss 0.17837 dice_loss 0.12548 +Epoch [1080/4000] Validation metric {'Val/mean dice_metric': 0.9692996740341187, 'Val/mean miou_metric': 0.9496356844902039, 'Val/mean f1': 0.9709464311599731, 'Val/mean precision': 0.9677936434745789, 'Val/mean recall': 0.9741199016571045, 'Val/mean hd95_metric': 5.94083833694458} +Cheakpoint... +Epoch [1080/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692996740341187, 'Val/mean miou_metric': 0.9496356844902039, 'Val/mean f1': 0.9709464311599731, 'Val/mean precision': 0.9677936434745789, 'Val/mean recall': 0.9741199016571045, 'Val/mean hd95_metric': 5.94083833694458} +Epoch [1081/4000] Training [1/16] Loss: 0.01143 +Epoch [1081/4000] Training [2/16] Loss: 0.00679 +Epoch [1081/4000] Training [3/16] Loss: 0.00816 +Epoch [1081/4000] Training [4/16] Loss: 0.01264 +Epoch [1081/4000] Training [5/16] Loss: 0.01113 +Epoch [1081/4000] Training [6/16] Loss: 0.00931 +Epoch [1081/4000] Training [7/16] Loss: 0.01060 +Epoch [1081/4000] Training [8/16] Loss: 0.01073 +Epoch [1081/4000] Training [9/16] Loss: 0.01375 +Epoch [1081/4000] Training [10/16] Loss: 0.00756 +Epoch [1081/4000] Training [11/16] Loss: 0.01094 +Epoch [1081/4000] Training [12/16] Loss: 0.00933 +Epoch [1081/4000] Training [13/16] Loss: 0.01124 +Epoch [1081/4000] Training [14/16] Loss: 0.00966 +Epoch [1081/4000] Training [15/16] Loss: 0.00925 +Epoch [1081/4000] Training [16/16] Loss: 0.00775 +Epoch [1081/4000] Training metric {'Train/mean dice_metric': 0.993317186832428, 'Train/mean miou_metric': 0.9864786863327026, 'Train/mean f1': 0.9894198179244995, 'Train/mean precision': 0.9848508834838867, 'Train/mean recall': 0.9940313696861267, 'Train/mean hd95_metric': 1.149562120437622} +Epoch [1081/4000] Validation [1/4] Loss: 0.16904 focal_loss 0.10732 dice_loss 0.06173 +Epoch [1081/4000] Validation [2/4] Loss: 0.25625 focal_loss 0.12879 dice_loss 0.12746 +Epoch [1081/4000] Validation [3/4] Loss: 0.20160 focal_loss 0.11426 dice_loss 0.08733 +Epoch [1081/4000] Validation [4/4] Loss: 0.31287 focal_loss 0.17259 dice_loss 0.14028 +Epoch [1081/4000] Validation metric {'Val/mean dice_metric': 0.9703097343444824, 'Val/mean miou_metric': 0.9514654278755188, 'Val/mean f1': 0.97173672914505, 'Val/mean precision': 0.9666510820388794, 'Val/mean recall': 0.9768761396408081, 'Val/mean hd95_metric': 5.5847487449646} +Cheakpoint... +Epoch [1081/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703097343444824, 'Val/mean miou_metric': 0.9514654278755188, 'Val/mean f1': 0.97173672914505, 'Val/mean precision': 0.9666510820388794, 'Val/mean recall': 0.9768761396408081, 'Val/mean hd95_metric': 5.5847487449646} +Epoch [1082/4000] Training [1/16] Loss: 0.00996 +Epoch [1082/4000] Training [2/16] Loss: 0.00937 +Epoch [1082/4000] Training [3/16] Loss: 0.00965 +Epoch [1082/4000] Training [4/16] Loss: 0.00805 +Epoch [1082/4000] Training [5/16] Loss: 0.01128 +Epoch [1082/4000] Training [6/16] Loss: 0.01315 +Epoch [1082/4000] Training [7/16] Loss: 0.01088 +Epoch [1082/4000] Training [8/16] Loss: 0.01044 +Epoch [1082/4000] Training [9/16] Loss: 0.00903 +Epoch [1082/4000] Training [10/16] Loss: 0.00901 +Epoch [1082/4000] Training [11/16] Loss: 0.01142 +Epoch [1082/4000] Training [12/16] Loss: 0.00816 +Epoch [1082/4000] Training [13/16] Loss: 0.00990 +Epoch [1082/4000] Training [14/16] Loss: 0.00835 +Epoch [1082/4000] Training [15/16] Loss: 0.01797 +Epoch [1082/4000] Training [16/16] Loss: 0.01196 +Epoch [1082/4000] Training metric {'Train/mean dice_metric': 0.9911409616470337, 'Train/mean miou_metric': 0.9833121299743652, 'Train/mean f1': 0.9887765645980835, 'Train/mean precision': 0.984377384185791, 'Train/mean recall': 0.9932154417037964, 'Train/mean hd95_metric': 1.7177867889404297} +Epoch [1082/4000] Validation [1/4] Loss: 0.18455 focal_loss 0.11751 dice_loss 0.06704 +Epoch [1082/4000] Validation [2/4] Loss: 0.50100 focal_loss 0.29261 dice_loss 0.20839 +Epoch [1082/4000] Validation [3/4] Loss: 0.25636 focal_loss 0.15207 dice_loss 0.10428 +Epoch [1082/4000] Validation [4/4] Loss: 0.43991 focal_loss 0.27486 dice_loss 0.16506 +Epoch [1082/4000] Validation metric {'Val/mean dice_metric': 0.9665471315383911, 'Val/mean miou_metric': 0.9472362399101257, 'Val/mean f1': 0.9693571925163269, 'Val/mean precision': 0.9666696786880493, 'Val/mean recall': 0.9720596075057983, 'Val/mean hd95_metric': 6.743511199951172} +Cheakpoint... +Epoch [1082/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665471315383911, 'Val/mean miou_metric': 0.9472362399101257, 'Val/mean f1': 0.9693571925163269, 'Val/mean precision': 0.9666696786880493, 'Val/mean recall': 0.9720596075057983, 'Val/mean hd95_metric': 6.743511199951172} +Epoch [1083/4000] Training [1/16] Loss: 0.01072 +Epoch [1083/4000] Training [2/16] Loss: 0.00881 +Epoch [1083/4000] Training [3/16] Loss: 0.00942 +Epoch [1083/4000] Training [4/16] Loss: 0.01215 +Epoch [1083/4000] Training [5/16] Loss: 0.00899 +Epoch [1083/4000] Training [6/16] Loss: 0.01026 +Epoch [1083/4000] Training [7/16] Loss: 0.01602 +Epoch [1083/4000] Training [8/16] Loss: 0.01112 +Epoch [1083/4000] Training [9/16] Loss: 0.01084 +Epoch [1083/4000] Training [10/16] Loss: 0.01009 +Epoch [1083/4000] Training [11/16] Loss: 0.01438 +Epoch [1083/4000] Training [12/16] Loss: 0.01286 +Epoch [1083/4000] Training [13/16] Loss: 0.01041 +Epoch [1083/4000] Training [14/16] Loss: 0.01192 +Epoch [1083/4000] Training [15/16] Loss: 0.01322 +Epoch [1083/4000] Training [16/16] Loss: 0.00941 +Epoch [1083/4000] Training metric {'Train/mean dice_metric': 0.9919798970222473, 'Train/mean miou_metric': 0.9838691353797913, 'Train/mean f1': 0.9885876774787903, 'Train/mean precision': 0.9841849207878113, 'Train/mean recall': 0.9930300712585449, 'Train/mean hd95_metric': 1.5278362035751343} +Epoch [1083/4000] Validation [1/4] Loss: 0.55349 focal_loss 0.38646 dice_loss 0.16703 +Epoch [1083/4000] Validation [2/4] Loss: 0.28264 focal_loss 0.13757 dice_loss 0.14506 +Epoch [1083/4000] Validation [3/4] Loss: 0.18781 focal_loss 0.10411 dice_loss 0.08370 +Epoch [1083/4000] Validation [4/4] Loss: 0.24998 focal_loss 0.12764 dice_loss 0.12235 +Epoch [1083/4000] Validation metric {'Val/mean dice_metric': 0.9661137461662292, 'Val/mean miou_metric': 0.946088969707489, 'Val/mean f1': 0.9683607220649719, 'Val/mean precision': 0.9692081809043884, 'Val/mean recall': 0.96751469373703, 'Val/mean hd95_metric': 6.355380535125732} +Cheakpoint... +Epoch [1083/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661137461662292, 'Val/mean miou_metric': 0.946088969707489, 'Val/mean f1': 0.9683607220649719, 'Val/mean precision': 0.9692081809043884, 'Val/mean recall': 0.96751469373703, 'Val/mean hd95_metric': 6.355380535125732} +Epoch [1084/4000] Training [1/16] Loss: 0.00858 +Epoch [1084/4000] Training [2/16] Loss: 0.01298 +Epoch [1084/4000] Training [3/16] Loss: 0.01190 +Epoch [1084/4000] Training [4/16] Loss: 0.01357 +Epoch [1084/4000] Training [5/16] Loss: 0.00931 +Epoch [1084/4000] Training [6/16] Loss: 0.00779 +Epoch [1084/4000] Training [7/16] Loss: 0.00893 +Epoch [1084/4000] Training [8/16] Loss: 0.00951 +Epoch [1084/4000] Training [9/16] Loss: 0.01155 +Epoch [1084/4000] Training [10/16] Loss: 0.00966 +Epoch [1084/4000] Training [11/16] Loss: 0.00869 +Epoch [1084/4000] Training [12/16] Loss: 0.01174 +Epoch [1084/4000] Training [13/16] Loss: 0.01039 +Epoch [1084/4000] Training [14/16] Loss: 0.01167 +Epoch [1084/4000] Training [15/16] Loss: 0.01075 +Epoch [1084/4000] Training [16/16] Loss: 0.01179 +Epoch [1084/4000] Training metric {'Train/mean dice_metric': 0.9919792413711548, 'Train/mean miou_metric': 0.9839062690734863, 'Train/mean f1': 0.9887620210647583, 'Train/mean precision': 0.984138548374176, 'Train/mean recall': 0.9934291243553162, 'Train/mean hd95_metric': 1.3661279678344727} +Epoch [1084/4000] Validation [1/4] Loss: 0.47667 focal_loss 0.35006 dice_loss 0.12661 +Epoch [1084/4000] Validation [2/4] Loss: 0.23736 focal_loss 0.11029 dice_loss 0.12706 +Epoch [1084/4000] Validation [3/4] Loss: 0.15158 focal_loss 0.08874 dice_loss 0.06284 +Epoch [1084/4000] Validation [4/4] Loss: 0.21724 focal_loss 0.10638 dice_loss 0.11086 +Epoch [1084/4000] Validation metric {'Val/mean dice_metric': 0.9681224822998047, 'Val/mean miou_metric': 0.947650134563446, 'Val/mean f1': 0.969107449054718, 'Val/mean precision': 0.9701814651489258, 'Val/mean recall': 0.9680356979370117, 'Val/mean hd95_metric': 5.5398383140563965} +Cheakpoint... +Epoch [1084/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681224822998047, 'Val/mean miou_metric': 0.947650134563446, 'Val/mean f1': 0.969107449054718, 'Val/mean precision': 0.9701814651489258, 'Val/mean recall': 0.9680356979370117, 'Val/mean hd95_metric': 5.5398383140563965} +Epoch [1085/4000] Training [1/16] Loss: 0.01166 +Epoch [1085/4000] Training [2/16] Loss: 0.01347 +Epoch [1085/4000] Training [3/16] Loss: 0.01516 +Epoch [1085/4000] Training [4/16] Loss: 0.01147 +Epoch [1085/4000] Training [5/16] Loss: 0.00989 +Epoch [1085/4000] Training [6/16] Loss: 0.01312 +Epoch [1085/4000] Training [7/16] Loss: 0.00819 +Epoch [1085/4000] Training [8/16] Loss: 0.01063 +Epoch [1085/4000] Training [9/16] Loss: 0.01012 +Epoch [1085/4000] Training [10/16] Loss: 0.00856 +Epoch [1085/4000] Training [11/16] Loss: 0.00997 +Epoch [1085/4000] Training [12/16] Loss: 0.01198 +Epoch [1085/4000] Training [13/16] Loss: 0.00987 +Epoch [1085/4000] Training [14/16] Loss: 0.01088 +Epoch [1085/4000] Training [15/16] Loss: 0.01113 +Epoch [1085/4000] Training [16/16] Loss: 0.01025 +Epoch [1085/4000] Training metric {'Train/mean dice_metric': 0.9926234483718872, 'Train/mean miou_metric': 0.9850820302963257, 'Train/mean f1': 0.9883375763893127, 'Train/mean precision': 0.9833077788352966, 'Train/mean recall': 0.9934191107749939, 'Train/mean hd95_metric': 1.131603479385376} +Epoch [1085/4000] Validation [1/4] Loss: 0.21348 focal_loss 0.13708 dice_loss 0.07640 +Epoch [1085/4000] Validation [2/4] Loss: 0.47474 focal_loss 0.27798 dice_loss 0.19675 +Epoch [1085/4000] Validation [3/4] Loss: 0.18598 focal_loss 0.09961 dice_loss 0.08637 +Epoch [1085/4000] Validation [4/4] Loss: 0.21958 focal_loss 0.10332 dice_loss 0.11626 +Epoch [1085/4000] Validation metric {'Val/mean dice_metric': 0.9666988253593445, 'Val/mean miou_metric': 0.9470731616020203, 'Val/mean f1': 0.9688794016838074, 'Val/mean precision': 0.9675319194793701, 'Val/mean recall': 0.9702306389808655, 'Val/mean hd95_metric': 5.942703723907471} +Cheakpoint... +Epoch [1085/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666988253593445, 'Val/mean miou_metric': 0.9470731616020203, 'Val/mean f1': 0.9688794016838074, 'Val/mean precision': 0.9675319194793701, 'Val/mean recall': 0.9702306389808655, 'Val/mean hd95_metric': 5.942703723907471} +Epoch [1086/4000] Training [1/16] Loss: 0.01370 +Epoch [1086/4000] Training [2/16] Loss: 0.01409 +Epoch [1086/4000] Training [3/16] Loss: 0.00812 +Epoch [1086/4000] Training [4/16] Loss: 0.01033 +Epoch [1086/4000] Training [5/16] Loss: 0.00986 +Epoch [1086/4000] Training [6/16] Loss: 0.01348 +Epoch [1086/4000] Training [7/16] Loss: 0.01110 +Epoch [1086/4000] Training [8/16] Loss: 0.01127 +Epoch [1086/4000] Training [9/16] Loss: 0.01048 +Epoch [1086/4000] Training [10/16] Loss: 0.07004 +Epoch [1086/4000] Training [11/16] Loss: 0.01722 +Epoch [1086/4000] Training [12/16] Loss: 0.01138 +Epoch [1086/4000] Training [13/16] Loss: 0.00972 +Epoch [1086/4000] Training [14/16] Loss: 0.01023 +Epoch [1086/4000] Training [15/16] Loss: 0.01163 +Epoch [1086/4000] Training [16/16] Loss: 0.00797 +Epoch [1086/4000] Training metric {'Train/mean dice_metric': 0.9913718700408936, 'Train/mean miou_metric': 0.9831893444061279, 'Train/mean f1': 0.9888920783996582, 'Train/mean precision': 0.9843807220458984, 'Train/mean recall': 0.9934450387954712, 'Train/mean hd95_metric': 1.2983564138412476} +Epoch [1086/4000] Validation [1/4] Loss: 0.20999 focal_loss 0.13888 dice_loss 0.07111 +Epoch [1086/4000] Validation [2/4] Loss: 0.21886 focal_loss 0.09871 dice_loss 0.12015 +Epoch [1086/4000] Validation [3/4] Loss: 0.17803 focal_loss 0.10356 dice_loss 0.07447 +Epoch [1086/4000] Validation [4/4] Loss: 0.24687 focal_loss 0.12363 dice_loss 0.12325 +Epoch [1086/4000] Validation metric {'Val/mean dice_metric': 0.9678992033004761, 'Val/mean miou_metric': 0.9483358263969421, 'Val/mean f1': 0.9710184931755066, 'Val/mean precision': 0.966237485408783, 'Val/mean recall': 0.9758469462394714, 'Val/mean hd95_metric': 6.452389717102051} +Cheakpoint... +Epoch [1086/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678992033004761, 'Val/mean miou_metric': 0.9483358263969421, 'Val/mean f1': 0.9710184931755066, 'Val/mean precision': 0.966237485408783, 'Val/mean recall': 0.9758469462394714, 'Val/mean hd95_metric': 6.452389717102051} +Epoch [1087/4000] Training [1/16] Loss: 0.00981 +Epoch [1087/4000] Training [2/16] Loss: 0.00937 +Epoch [1087/4000] Training [3/16] Loss: 0.00792 +Epoch [1087/4000] Training [4/16] Loss: 0.01036 +Epoch [1087/4000] Training [5/16] Loss: 0.01099 +Epoch [1087/4000] Training [6/16] Loss: 0.01081 +Epoch [1087/4000] Training [7/16] Loss: 0.01169 +Epoch [1087/4000] Training [8/16] Loss: 0.01165 +Epoch [1087/4000] Training [9/16] Loss: 0.01374 +Epoch [1087/4000] Training [10/16] Loss: 0.01182 +Epoch [1087/4000] Training [11/16] Loss: 0.01150 +Epoch [1087/4000] Training [12/16] Loss: 0.01122 +Epoch [1087/4000] Training [13/16] Loss: 0.01349 +Epoch [1087/4000] Training [14/16] Loss: 0.01024 +Epoch [1087/4000] Training [15/16] Loss: 0.00932 +Epoch [1087/4000] Training [16/16] Loss: 0.03205 +Epoch [1087/4000] Training metric {'Train/mean dice_metric': 0.9922019243240356, 'Train/mean miou_metric': 0.9843399524688721, 'Train/mean f1': 0.9889134764671326, 'Train/mean precision': 0.9842637777328491, 'Train/mean recall': 0.9936072826385498, 'Train/mean hd95_metric': 1.317619800567627} +Epoch [1087/4000] Validation [1/4] Loss: 0.32174 focal_loss 0.22975 dice_loss 0.09199 +Epoch [1087/4000] Validation [2/4] Loss: 0.44614 focal_loss 0.25470 dice_loss 0.19144 +Epoch [1087/4000] Validation [3/4] Loss: 0.16081 focal_loss 0.08771 dice_loss 0.07310 +Epoch [1087/4000] Validation [4/4] Loss: 0.27724 focal_loss 0.15102 dice_loss 0.12622 +Epoch [1087/4000] Validation metric {'Val/mean dice_metric': 0.9710347056388855, 'Val/mean miou_metric': 0.9520033001899719, 'Val/mean f1': 0.9725956320762634, 'Val/mean precision': 0.9695640206336975, 'Val/mean recall': 0.9756462574005127, 'Val/mean hd95_metric': 6.024022579193115} +Cheakpoint... +Epoch [1087/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710347056388855, 'Val/mean miou_metric': 0.9520033001899719, 'Val/mean f1': 0.9725956320762634, 'Val/mean precision': 0.9695640206336975, 'Val/mean recall': 0.9756462574005127, 'Val/mean hd95_metric': 6.024022579193115} +Epoch [1088/4000] Training [1/16] Loss: 0.01067 +Epoch [1088/4000] Training [2/16] Loss: 0.00845 +Epoch [1088/4000] Training [3/16] Loss: 0.01210 +Epoch [1088/4000] Training [4/16] Loss: 0.02061 +Epoch [1088/4000] Training [5/16] Loss: 0.00883 +Epoch [1088/4000] Training [6/16] Loss: 0.00740 +Epoch [1088/4000] Training [7/16] Loss: 0.00868 +Epoch [1088/4000] Training [8/16] Loss: 0.06339 +Epoch [1088/4000] Training [9/16] Loss: 0.01196 +Epoch [1088/4000] Training [10/16] Loss: 0.01382 +Epoch [1088/4000] Training [11/16] Loss: 0.01003 +Epoch [1088/4000] Training [12/16] Loss: 0.01219 +Epoch [1088/4000] Training [13/16] Loss: 0.00928 +Epoch [1088/4000] Training [14/16] Loss: 0.01161 +Epoch [1088/4000] Training [15/16] Loss: 0.01691 +Epoch [1088/4000] Training [16/16] Loss: 0.02076 +Epoch [1088/4000] Training metric {'Train/mean dice_metric': 0.9911439418792725, 'Train/mean miou_metric': 0.982599139213562, 'Train/mean f1': 0.9875987768173218, 'Train/mean precision': 0.9830886721611023, 'Train/mean recall': 0.9921504259109497, 'Train/mean hd95_metric': 1.606096863746643} +Epoch [1088/4000] Validation [1/4] Loss: 0.26491 focal_loss 0.16159 dice_loss 0.10333 +Epoch [1088/4000] Validation [2/4] Loss: 0.25880 focal_loss 0.12393 dice_loss 0.13487 +Epoch [1088/4000] Validation [3/4] Loss: 0.23189 focal_loss 0.13190 dice_loss 0.09999 +Epoch [1088/4000] Validation [4/4] Loss: 0.44359 focal_loss 0.27771 dice_loss 0.16588 +Epoch [1088/4000] Validation metric {'Val/mean dice_metric': 0.9631778001785278, 'Val/mean miou_metric': 0.9416143298149109, 'Val/mean f1': 0.9655137062072754, 'Val/mean precision': 0.9647172093391418, 'Val/mean recall': 0.9663115739822388, 'Val/mean hd95_metric': 7.4748358726501465} +Cheakpoint... +Epoch [1088/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631778001785278, 'Val/mean miou_metric': 0.9416143298149109, 'Val/mean f1': 0.9655137062072754, 'Val/mean precision': 0.9647172093391418, 'Val/mean recall': 0.9663115739822388, 'Val/mean hd95_metric': 7.4748358726501465} +Epoch [1089/4000] Training [1/16] Loss: 0.01432 +Epoch [1089/4000] Training [2/16] Loss: 0.01143 +Epoch [1089/4000] Training [3/16] Loss: 0.01204 +Epoch [1089/4000] Training [4/16] Loss: 0.01135 +Epoch [1089/4000] Training [5/16] Loss: 0.01248 +Epoch [1089/4000] Training [6/16] Loss: 0.01138 +Epoch [1089/4000] Training [7/16] Loss: 0.01070 +Epoch [1089/4000] Training [8/16] Loss: 0.01416 +Epoch [1089/4000] Training [9/16] Loss: 0.00971 +Epoch [1089/4000] Training [10/16] Loss: 0.01110 +Epoch [1089/4000] Training [11/16] Loss: 0.01188 +Epoch [1089/4000] Training [12/16] Loss: 0.01166 +Epoch [1089/4000] Training [13/16] Loss: 0.01113 +Epoch [1089/4000] Training [14/16] Loss: 0.01129 +Epoch [1089/4000] Training [15/16] Loss: 0.01562 +Epoch [1089/4000] Training [16/16] Loss: 0.01210 +Epoch [1089/4000] Training metric {'Train/mean dice_metric': 0.9910386800765991, 'Train/mean miou_metric': 0.982100248336792, 'Train/mean f1': 0.9877753853797913, 'Train/mean precision': 0.9828119277954102, 'Train/mean recall': 0.9927892684936523, 'Train/mean hd95_metric': 1.6285436153411865} +Epoch [1089/4000] Validation [1/4] Loss: 0.19607 focal_loss 0.12865 dice_loss 0.06742 +Epoch [1089/4000] Validation [2/4] Loss: 0.47900 focal_loss 0.23087 dice_loss 0.24813 +Epoch [1089/4000] Validation [3/4] Loss: 0.38953 focal_loss 0.25718 dice_loss 0.13235 +Epoch [1089/4000] Validation [4/4] Loss: 0.31965 focal_loss 0.15203 dice_loss 0.16762 +Epoch [1089/4000] Validation metric {'Val/mean dice_metric': 0.9609485864639282, 'Val/mean miou_metric': 0.9396582841873169, 'Val/mean f1': 0.961209774017334, 'Val/mean precision': 0.9484891891479492, 'Val/mean recall': 0.9742761254310608, 'Val/mean hd95_metric': 8.317158699035645} +Cheakpoint... +Epoch [1089/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9609], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9609485864639282, 'Val/mean miou_metric': 0.9396582841873169, 'Val/mean f1': 0.961209774017334, 'Val/mean precision': 0.9484891891479492, 'Val/mean recall': 0.9742761254310608, 'Val/mean hd95_metric': 8.317158699035645} +Epoch [1090/4000] Training [1/16] Loss: 0.00911 +Epoch [1090/4000] Training [2/16] Loss: 0.01088 +Epoch [1090/4000] Training [3/16] Loss: 0.00828 +Epoch [1090/4000] Training [4/16] Loss: 0.01572 +Epoch [1090/4000] Training [5/16] Loss: 0.00972 +Epoch [1090/4000] Training [6/16] Loss: 0.00946 +Epoch [1090/4000] Training [7/16] Loss: 0.01949 +Epoch [1090/4000] Training [8/16] Loss: 0.02474 +Epoch [1090/4000] Training [9/16] Loss: 0.01244 +Epoch [1090/4000] Training [10/16] Loss: 0.01072 +Epoch [1090/4000] Training [11/16] Loss: 0.00885 +Epoch [1090/4000] Training [12/16] Loss: 0.01148 +Epoch [1090/4000] Training [13/16] Loss: 0.01254 +Epoch [1090/4000] Training [14/16] Loss: 0.01322 +Epoch [1090/4000] Training [15/16] Loss: 0.00972 +Epoch [1090/4000] Training [16/16] Loss: 0.05377 +Epoch [1090/4000] Training metric {'Train/mean dice_metric': 0.9919532537460327, 'Train/mean miou_metric': 0.9838935136795044, 'Train/mean f1': 0.9877298474311829, 'Train/mean precision': 0.9831312298774719, 'Train/mean recall': 0.992371678352356, 'Train/mean hd95_metric': 1.4693323373794556} +Epoch [1090/4000] Validation [1/4] Loss: 0.22775 focal_loss 0.15317 dice_loss 0.07458 +Epoch [1090/4000] Validation [2/4] Loss: 0.22417 focal_loss 0.10446 dice_loss 0.11972 +Epoch [1090/4000] Validation [3/4] Loss: 0.28269 focal_loss 0.16762 dice_loss 0.11507 +Epoch [1090/4000] Validation [4/4] Loss: 0.47659 focal_loss 0.27437 dice_loss 0.20222 +Epoch [1090/4000] Validation metric {'Val/mean dice_metric': 0.9656936526298523, 'Val/mean miou_metric': 0.9456831812858582, 'Val/mean f1': 0.9605429768562317, 'Val/mean precision': 0.9423589706420898, 'Val/mean recall': 0.9794426560401917, 'Val/mean hd95_metric': 7.688920497894287} +Cheakpoint... +Epoch [1090/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9657], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656936526298523, 'Val/mean miou_metric': 0.9456831812858582, 'Val/mean f1': 0.9605429768562317, 'Val/mean precision': 0.9423589706420898, 'Val/mean recall': 0.9794426560401917, 'Val/mean hd95_metric': 7.688920497894287} +Epoch [1091/4000] Training [1/16] Loss: 0.00878 +Epoch [1091/4000] Training [2/16] Loss: 0.01309 +Epoch [1091/4000] Training [3/16] Loss: 0.01109 +Epoch [1091/4000] Training [4/16] Loss: 0.00747 +Epoch [1091/4000] Training [5/16] Loss: 0.01352 +Epoch [1091/4000] Training [6/16] Loss: 0.01583 +Epoch [1091/4000] Training [7/16] Loss: 0.01736 +Epoch [1091/4000] Training [8/16] Loss: 0.01545 +Epoch [1091/4000] Training [9/16] Loss: 0.01370 +Epoch [1091/4000] Training [10/16] Loss: 0.01940 +Epoch [1091/4000] Training [11/16] Loss: 0.01189 +Epoch [1091/4000] Training [12/16] Loss: 0.01290 +Epoch [1091/4000] Training [13/16] Loss: 0.01484 +Epoch [1091/4000] Training [14/16] Loss: 0.01099 +Epoch [1091/4000] Training [15/16] Loss: 0.01199 +Epoch [1091/4000] Training [16/16] Loss: 0.01268 +Epoch [1091/4000] Training metric {'Train/mean dice_metric': 0.9882681369781494, 'Train/mean miou_metric': 0.9777085185050964, 'Train/mean f1': 0.9815769791603088, 'Train/mean precision': 0.9793128371238708, 'Train/mean recall': 0.9838516116142273, 'Train/mean hd95_metric': 3.492642402648926} +Epoch [1091/4000] Validation [1/4] Loss: 0.53536 focal_loss 0.40751 dice_loss 0.12786 +Epoch [1091/4000] Validation [2/4] Loss: 0.36109 focal_loss 0.17421 dice_loss 0.18687 +Epoch [1091/4000] Validation [3/4] Loss: 0.14350 focal_loss 0.06420 dice_loss 0.07930 +Epoch [1091/4000] Validation [4/4] Loss: 0.27304 focal_loss 0.12505 dice_loss 0.14799 +Epoch [1091/4000] Validation metric {'Val/mean dice_metric': 0.9631189107894897, 'Val/mean miou_metric': 0.939867377281189, 'Val/mean f1': 0.9588877558708191, 'Val/mean precision': 0.9523705840110779, 'Val/mean recall': 0.9654948115348816, 'Val/mean hd95_metric': 9.567628860473633} +Cheakpoint... +Epoch [1091/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9631], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631189107894897, 'Val/mean miou_metric': 0.939867377281189, 'Val/mean f1': 0.9588877558708191, 'Val/mean precision': 0.9523705840110779, 'Val/mean recall': 0.9654948115348816, 'Val/mean hd95_metric': 9.567628860473633} +Epoch [1092/4000] Training [1/16] Loss: 0.01484 +Epoch [1092/4000] Training [2/16] Loss: 0.01018 +Epoch [1092/4000] Training [3/16] Loss: 0.01667 +Epoch [1092/4000] Training [4/16] Loss: 0.01319 +Epoch [1092/4000] Training [5/16] Loss: 0.01228 +Epoch [1092/4000] Training [6/16] Loss: 0.02468 +Epoch [1092/4000] Training [7/16] Loss: 0.01525 +Epoch [1092/4000] Training [8/16] Loss: 0.01463 +Epoch [1092/4000] Training [9/16] Loss: 0.01339 +Epoch [1092/4000] Training [10/16] Loss: 0.02055 +Epoch [1092/4000] Training [11/16] Loss: 0.01439 +Epoch [1092/4000] Training [12/16] Loss: 0.01327 +Epoch [1092/4000] Training [13/16] Loss: 0.01335 +Epoch [1092/4000] Training [14/16] Loss: 0.01310 +Epoch [1092/4000] Training [15/16] Loss: 0.01561 +Epoch [1092/4000] Training [16/16] Loss: 0.01239 +Epoch [1092/4000] Training metric {'Train/mean dice_metric': 0.9900096654891968, 'Train/mean miou_metric': 0.9800934791564941, 'Train/mean f1': 0.9858078956604004, 'Train/mean precision': 0.9804678559303284, 'Train/mean recall': 0.9912064671516418, 'Train/mean hd95_metric': 2.3842759132385254} +Epoch [1092/4000] Validation [1/4] Loss: 0.20403 focal_loss 0.13257 dice_loss 0.07145 +Epoch [1092/4000] Validation [2/4] Loss: 0.61154 focal_loss 0.31590 dice_loss 0.29563 +Epoch [1092/4000] Validation [3/4] Loss: 0.33487 focal_loss 0.21994 dice_loss 0.11493 +Epoch [1092/4000] Validation [4/4] Loss: 0.50774 focal_loss 0.28392 dice_loss 0.22382 +Epoch [1092/4000] Validation metric {'Val/mean dice_metric': 0.9619242548942566, 'Val/mean miou_metric': 0.939212441444397, 'Val/mean f1': 0.9647287726402283, 'Val/mean precision': 0.9625864028930664, 'Val/mean recall': 0.9668807983398438, 'Val/mean hd95_metric': 8.729727745056152} +Cheakpoint... +Epoch [1092/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9619], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9619242548942566, 'Val/mean miou_metric': 0.939212441444397, 'Val/mean f1': 0.9647287726402283, 'Val/mean precision': 0.9625864028930664, 'Val/mean recall': 0.9668807983398438, 'Val/mean hd95_metric': 8.729727745056152} +Epoch [1093/4000] Training [1/16] Loss: 0.01142 +Epoch [1093/4000] Training [2/16] Loss: 0.01179 +Epoch [1093/4000] Training [3/16] Loss: 0.01037 +Epoch [1093/4000] Training [4/16] Loss: 0.01331 +Epoch [1093/4000] Training [5/16] Loss: 0.02025 +Epoch [1093/4000] Training [6/16] Loss: 0.02131 +Epoch [1093/4000] Training [7/16] Loss: 0.01262 +Epoch [1093/4000] Training [8/16] Loss: 0.00892 +Epoch [1093/4000] Training [9/16] Loss: 0.01221 +Epoch [1093/4000] Training [10/16] Loss: 0.01223 +Epoch [1093/4000] Training [11/16] Loss: 0.00863 +Epoch [1093/4000] Training [12/16] Loss: 0.01086 +Epoch [1093/4000] Training [13/16] Loss: 0.01008 +Epoch [1093/4000] Training [14/16] Loss: 0.00941 +Epoch [1093/4000] Training [15/16] Loss: 0.01543 +Epoch [1093/4000] Training [16/16] Loss: 0.01063 +Epoch [1093/4000] Training metric {'Train/mean dice_metric': 0.9917103052139282, 'Train/mean miou_metric': 0.9833214282989502, 'Train/mean f1': 0.9874611496925354, 'Train/mean precision': 0.982833206653595, 'Train/mean recall': 0.992132842540741, 'Train/mean hd95_metric': 1.4481148719787598} +Epoch [1093/4000] Validation [1/4] Loss: 0.16778 focal_loss 0.11025 dice_loss 0.05752 +Epoch [1093/4000] Validation [2/4] Loss: 0.17388 focal_loss 0.06585 dice_loss 0.10803 +Epoch [1093/4000] Validation [3/4] Loss: 0.26825 focal_loss 0.16243 dice_loss 0.10582 +Epoch [1093/4000] Validation [4/4] Loss: 0.26366 focal_loss 0.10849 dice_loss 0.15517 +Epoch [1093/4000] Validation metric {'Val/mean dice_metric': 0.9660911560058594, 'Val/mean miou_metric': 0.9456461071968079, 'Val/mean f1': 0.967099666595459, 'Val/mean precision': 0.9594762921333313, 'Val/mean recall': 0.9748451113700867, 'Val/mean hd95_metric': 7.932803153991699} +Cheakpoint... +Epoch [1093/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660911560058594, 'Val/mean miou_metric': 0.9456461071968079, 'Val/mean f1': 0.967099666595459, 'Val/mean precision': 0.9594762921333313, 'Val/mean recall': 0.9748451113700867, 'Val/mean hd95_metric': 7.932803153991699} +Epoch [1094/4000] Training [1/16] Loss: 0.01044 +Epoch [1094/4000] Training [2/16] Loss: 0.00959 +Epoch [1094/4000] Training [3/16] Loss: 0.01453 +Epoch [1094/4000] Training [4/16] Loss: 0.01062 +Epoch [1094/4000] Training [5/16] Loss: 0.01562 +Epoch [1094/4000] Training [6/16] Loss: 0.01217 +Epoch [1094/4000] Training [7/16] Loss: 0.00965 +Epoch [1094/4000] Training [8/16] Loss: 0.01283 +Epoch [1094/4000] Training [9/16] Loss: 0.00995 +Epoch [1094/4000] Training [10/16] Loss: 0.01296 +Epoch [1094/4000] Training [11/16] Loss: 0.01143 +Epoch [1094/4000] Training [12/16] Loss: 0.01113 +Epoch [1094/4000] Training [13/16] Loss: 0.01204 +Epoch [1094/4000] Training [14/16] Loss: 0.00884 +Epoch [1094/4000] Training [15/16] Loss: 0.01228 +Epoch [1094/4000] Training [16/16] Loss: 0.00857 +Epoch [1094/4000] Training metric {'Train/mean dice_metric': 0.9924861192703247, 'Train/mean miou_metric': 0.9848454594612122, 'Train/mean f1': 0.9886640906333923, 'Train/mean precision': 0.9840973615646362, 'Train/mean recall': 0.9932733774185181, 'Train/mean hd95_metric': 1.29055917263031} +Epoch [1094/4000] Validation [1/4] Loss: 0.17313 focal_loss 0.11735 dice_loss 0.05577 +Epoch [1094/4000] Validation [2/4] Loss: 0.25084 focal_loss 0.10586 dice_loss 0.14497 +Epoch [1094/4000] Validation [3/4] Loss: 0.25915 focal_loss 0.15158 dice_loss 0.10757 +Epoch [1094/4000] Validation [4/4] Loss: 0.30256 focal_loss 0.15407 dice_loss 0.14849 +Epoch [1094/4000] Validation metric {'Val/mean dice_metric': 0.9699633717536926, 'Val/mean miou_metric': 0.9502248764038086, 'Val/mean f1': 0.9700303673744202, 'Val/mean precision': 0.9629355669021606, 'Val/mean recall': 0.9772304892539978, 'Val/mean hd95_metric': 6.783242225646973} +Cheakpoint... +Epoch [1094/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699633717536926, 'Val/mean miou_metric': 0.9502248764038086, 'Val/mean f1': 0.9700303673744202, 'Val/mean precision': 0.9629355669021606, 'Val/mean recall': 0.9772304892539978, 'Val/mean hd95_metric': 6.783242225646973} +Epoch [1095/4000] Training [1/16] Loss: 0.01283 +Epoch [1095/4000] Training [2/16] Loss: 0.00893 +Epoch [1095/4000] Training [3/16] Loss: 0.01145 +Epoch [1095/4000] Training [4/16] Loss: 0.01415 +Epoch [1095/4000] Training [5/16] Loss: 0.00909 +Epoch [1095/4000] Training [6/16] Loss: 0.00839 +Epoch [1095/4000] Training [7/16] Loss: 0.01710 +Epoch [1095/4000] Training [8/16] Loss: 0.00744 +Epoch [1095/4000] Training [9/16] Loss: 0.01069 +Epoch [1095/4000] Training [10/16] Loss: 0.01153 +Epoch [1095/4000] Training [11/16] Loss: 0.00977 +Epoch [1095/4000] Training [12/16] Loss: 0.01482 +Epoch [1095/4000] Training [13/16] Loss: 0.00912 +Epoch [1095/4000] Training [14/16] Loss: 0.01100 +Epoch [1095/4000] Training [15/16] Loss: 0.01094 +Epoch [1095/4000] Training [16/16] Loss: 0.01039 +Epoch [1095/4000] Training metric {'Train/mean dice_metric': 0.9924412369728088, 'Train/mean miou_metric': 0.9847938418388367, 'Train/mean f1': 0.9889611601829529, 'Train/mean precision': 0.9844437837600708, 'Train/mean recall': 0.9935202598571777, 'Train/mean hd95_metric': 1.1499890089035034} +Epoch [1095/4000] Validation [1/4] Loss: 0.22998 focal_loss 0.15851 dice_loss 0.07147 +Epoch [1095/4000] Validation [2/4] Loss: 0.25286 focal_loss 0.11248 dice_loss 0.14037 +Epoch [1095/4000] Validation [3/4] Loss: 0.34324 focal_loss 0.22706 dice_loss 0.11618 +Epoch [1095/4000] Validation [4/4] Loss: 0.44821 focal_loss 0.19709 dice_loss 0.25112 +Epoch [1095/4000] Validation metric {'Val/mean dice_metric': 0.9663299322128296, 'Val/mean miou_metric': 0.945905327796936, 'Val/mean f1': 0.9674166440963745, 'Val/mean precision': 0.958000659942627, 'Val/mean recall': 0.9770196676254272, 'Val/mean hd95_metric': 7.496574401855469} +Cheakpoint... +Epoch [1095/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9663299322128296, 'Val/mean miou_metric': 0.945905327796936, 'Val/mean f1': 0.9674166440963745, 'Val/mean precision': 0.958000659942627, 'Val/mean recall': 0.9770196676254272, 'Val/mean hd95_metric': 7.496574401855469} +Epoch [1096/4000] Training [1/16] Loss: 0.00795 +Epoch [1096/4000] Training [2/16] Loss: 0.00934 +Epoch [1096/4000] Training [3/16] Loss: 0.00866 +Epoch [1096/4000] Training [4/16] Loss: 0.00820 +Epoch [1096/4000] Training [5/16] Loss: 0.00870 +Epoch [1096/4000] Training [6/16] Loss: 0.01018 +Epoch [1096/4000] Training [7/16] Loss: 0.01283 +Epoch [1096/4000] Training [8/16] Loss: 0.01289 +Epoch [1096/4000] Training [9/16] Loss: 0.00976 +Epoch [1096/4000] Training [10/16] Loss: 0.00998 +Epoch [1096/4000] Training [11/16] Loss: 0.01039 +Epoch [1096/4000] Training [12/16] Loss: 0.01195 +Epoch [1096/4000] Training [13/16] Loss: 0.00893 +Epoch [1096/4000] Training [14/16] Loss: 0.00861 +Epoch [1096/4000] Training [15/16] Loss: 0.01323 +Epoch [1096/4000] Training [16/16] Loss: 0.01251 +Epoch [1096/4000] Training metric {'Train/mean dice_metric': 0.9933836460113525, 'Train/mean miou_metric': 0.9866146445274353, 'Train/mean f1': 0.9895837903022766, 'Train/mean precision': 0.9850491881370544, 'Train/mean recall': 0.9941602945327759, 'Train/mean hd95_metric': 1.079590082168579} +Epoch [1096/4000] Validation [1/4] Loss: 0.19693 focal_loss 0.13279 dice_loss 0.06414 +Epoch [1096/4000] Validation [2/4] Loss: 0.41978 focal_loss 0.21481 dice_loss 0.20497 +Epoch [1096/4000] Validation [3/4] Loss: 0.56101 focal_loss 0.42019 dice_loss 0.14082 +Epoch [1096/4000] Validation [4/4] Loss: 0.23627 focal_loss 0.11474 dice_loss 0.12153 +Epoch [1096/4000] Validation metric {'Val/mean dice_metric': 0.9679967761039734, 'Val/mean miou_metric': 0.9482177495956421, 'Val/mean f1': 0.9677917957305908, 'Val/mean precision': 0.9557790160179138, 'Val/mean recall': 0.9801103472709656, 'Val/mean hd95_metric': 7.919847011566162} +Cheakpoint... +Epoch [1096/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679967761039734, 'Val/mean miou_metric': 0.9482177495956421, 'Val/mean f1': 0.9677917957305908, 'Val/mean precision': 0.9557790160179138, 'Val/mean recall': 0.9801103472709656, 'Val/mean hd95_metric': 7.919847011566162} +Epoch [1097/4000] Training [1/16] Loss: 0.01178 +Epoch [1097/4000] Training [2/16] Loss: 0.00945 +Epoch [1097/4000] Training [3/16] Loss: 0.01149 +Epoch [1097/4000] Training [4/16] Loss: 0.00791 +Epoch [1097/4000] Training [5/16] Loss: 0.00749 +Epoch [1097/4000] Training [6/16] Loss: 0.00903 +Epoch [1097/4000] Training [7/16] Loss: 0.01177 +Epoch [1097/4000] Training [8/16] Loss: 0.00960 +Epoch [1097/4000] Training [9/16] Loss: 0.00924 +Epoch [1097/4000] Training [10/16] Loss: 0.01110 +Epoch [1097/4000] Training [11/16] Loss: 0.00886 +Epoch [1097/4000] Training [12/16] Loss: 0.00721 +Epoch [1097/4000] Training [13/16] Loss: 0.01003 +Epoch [1097/4000] Training [14/16] Loss: 0.01025 +Epoch [1097/4000] Training [15/16] Loss: 0.00955 +Epoch [1097/4000] Training [16/16] Loss: 0.01247 +Epoch [1097/4000] Training metric {'Train/mean dice_metric': 0.9931795597076416, 'Train/mean miou_metric': 0.9862332940101624, 'Train/mean f1': 0.9895181059837341, 'Train/mean precision': 0.9851206541061401, 'Train/mean recall': 0.9939550161361694, 'Train/mean hd95_metric': 1.190199613571167} +Epoch [1097/4000] Validation [1/4] Loss: 0.26698 focal_loss 0.19406 dice_loss 0.07293 +Epoch [1097/4000] Validation [2/4] Loss: 0.35543 focal_loss 0.16006 dice_loss 0.19536 +Epoch [1097/4000] Validation [3/4] Loss: 0.43607 focal_loss 0.29650 dice_loss 0.13956 +Epoch [1097/4000] Validation [4/4] Loss: 0.26898 focal_loss 0.11627 dice_loss 0.15271 +Epoch [1097/4000] Validation metric {'Val/mean dice_metric': 0.9686948657035828, 'Val/mean miou_metric': 0.9497736096382141, 'Val/mean f1': 0.9680103659629822, 'Val/mean precision': 0.9571898579597473, 'Val/mean recall': 0.9790781736373901, 'Val/mean hd95_metric': 6.948748588562012} +Cheakpoint... +Epoch [1097/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686948657035828, 'Val/mean miou_metric': 0.9497736096382141, 'Val/mean f1': 0.9680103659629822, 'Val/mean precision': 0.9571898579597473, 'Val/mean recall': 0.9790781736373901, 'Val/mean hd95_metric': 6.948748588562012} +Epoch [1098/4000] Training [1/16] Loss: 0.00880 +Epoch [1098/4000] Training [2/16] Loss: 0.00764 +Epoch [1098/4000] Training [3/16] Loss: 0.00825 +Epoch [1098/4000] Training [4/16] Loss: 0.00774 +Epoch [1098/4000] Training [5/16] Loss: 0.01053 +Epoch [1098/4000] Training [6/16] Loss: 0.01405 +Epoch [1098/4000] Training [7/16] Loss: 0.00949 +Epoch [1098/4000] Training [8/16] Loss: 0.01097 +Epoch [1098/4000] Training [9/16] Loss: 0.00915 +Epoch [1098/4000] Training [10/16] Loss: 0.00823 +Epoch [1098/4000] Training [11/16] Loss: 0.01020 +Epoch [1098/4000] Training [12/16] Loss: 0.00802 +Epoch [1098/4000] Training [13/16] Loss: 0.01175 +Epoch [1098/4000] Training [14/16] Loss: 0.01104 +Epoch [1098/4000] Training [15/16] Loss: 0.00943 +Epoch [1098/4000] Training [16/16] Loss: 0.00975 +Epoch [1098/4000] Training metric {'Train/mean dice_metric': 0.9932582378387451, 'Train/mean miou_metric': 0.9863337278366089, 'Train/mean f1': 0.9887844920158386, 'Train/mean precision': 0.9834725856781006, 'Train/mean recall': 0.994154155254364, 'Train/mean hd95_metric': 1.0934507846832275} +Epoch [1098/4000] Validation [1/4] Loss: 0.18998 focal_loss 0.13041 dice_loss 0.05957 +Epoch [1098/4000] Validation [2/4] Loss: 0.35543 focal_loss 0.17859 dice_loss 0.17683 +Epoch [1098/4000] Validation [3/4] Loss: 0.14700 focal_loss 0.08591 dice_loss 0.06109 +Epoch [1098/4000] Validation [4/4] Loss: 0.25446 focal_loss 0.12256 dice_loss 0.13190 +Epoch [1098/4000] Validation metric {'Val/mean dice_metric': 0.9713796377182007, 'Val/mean miou_metric': 0.9523008465766907, 'Val/mean f1': 0.971617579460144, 'Val/mean precision': 0.964473307132721, 'Val/mean recall': 0.9788683652877808, 'Val/mean hd95_metric': 6.461601257324219} +Cheakpoint... +Epoch [1098/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713796377182007, 'Val/mean miou_metric': 0.9523008465766907, 'Val/mean f1': 0.971617579460144, 'Val/mean precision': 0.964473307132721, 'Val/mean recall': 0.9788683652877808, 'Val/mean hd95_metric': 6.461601257324219} +Epoch [1099/4000] Training [1/16] Loss: 0.01208 +Epoch [1099/4000] Training [2/16] Loss: 0.01155 +Epoch [1099/4000] Training [3/16] Loss: 0.01930 +Epoch [1099/4000] Training [4/16] Loss: 0.00853 +Epoch [1099/4000] Training [5/16] Loss: 0.00807 +Epoch [1099/4000] Training [6/16] Loss: 0.01094 +Epoch [1099/4000] Training [7/16] Loss: 0.01847 +Epoch [1099/4000] Training [8/16] Loss: 0.01227 +Epoch [1099/4000] Training [9/16] Loss: 0.00975 +Epoch [1099/4000] Training [10/16] Loss: 0.00978 +Epoch [1099/4000] Training [11/16] Loss: 0.00993 +Epoch [1099/4000] Training [12/16] Loss: 0.00856 +Epoch [1099/4000] Training [13/16] Loss: 0.00811 +Epoch [1099/4000] Training [14/16] Loss: 0.00901 +Epoch [1099/4000] Training [15/16] Loss: 0.00832 +Epoch [1099/4000] Training [16/16] Loss: 0.01117 +Epoch [1099/4000] Training metric {'Train/mean dice_metric': 0.9929274320602417, 'Train/mean miou_metric': 0.9857010841369629, 'Train/mean f1': 0.9891589283943176, 'Train/mean precision': 0.9844881296157837, 'Train/mean recall': 0.9938742518424988, 'Train/mean hd95_metric': 1.104468584060669} +Epoch [1099/4000] Validation [1/4] Loss: 0.20619 focal_loss 0.14601 dice_loss 0.06019 +Epoch [1099/4000] Validation [2/4] Loss: 0.21700 focal_loss 0.09817 dice_loss 0.11883 +Epoch [1099/4000] Validation [3/4] Loss: 0.20176 focal_loss 0.11109 dice_loss 0.09067 +Epoch [1099/4000] Validation [4/4] Loss: 0.23156 focal_loss 0.11445 dice_loss 0.11711 +Epoch [1099/4000] Validation metric {'Val/mean dice_metric': 0.9704796075820923, 'Val/mean miou_metric': 0.9513611793518066, 'Val/mean f1': 0.9712068438529968, 'Val/mean precision': 0.9637671113014221, 'Val/mean recall': 0.9787623286247253, 'Val/mean hd95_metric': 6.591378688812256} +Cheakpoint... +Epoch [1099/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704796075820923, 'Val/mean miou_metric': 0.9513611793518066, 'Val/mean f1': 0.9712068438529968, 'Val/mean precision': 0.9637671113014221, 'Val/mean recall': 0.9787623286247253, 'Val/mean hd95_metric': 6.591378688812256} +Epoch [1100/4000] Training [1/16] Loss: 0.00938 +Epoch [1100/4000] Training [2/16] Loss: 0.01105 +Epoch [1100/4000] Training [3/16] Loss: 0.01185 +Epoch [1100/4000] Training [4/16] Loss: 0.01103 +Epoch [1100/4000] Training [5/16] Loss: 0.00844 +Epoch [1100/4000] Training [6/16] Loss: 0.01325 +Epoch [1100/4000] Training [7/16] Loss: 0.00962 +Epoch [1100/4000] Training [8/16] Loss: 0.01196 +Epoch [1100/4000] Training [9/16] Loss: 0.00936 +Epoch [1100/4000] Training [10/16] Loss: 0.00864 +Epoch [1100/4000] Training [11/16] Loss: 0.01026 +Epoch [1100/4000] Training [12/16] Loss: 0.01010 +Epoch [1100/4000] Training [13/16] Loss: 0.01107 +Epoch [1100/4000] Training [14/16] Loss: 0.01595 +Epoch [1100/4000] Training [15/16] Loss: 0.01156 +Epoch [1100/4000] Training [16/16] Loss: 0.00989 +Epoch [1100/4000] Training metric {'Train/mean dice_metric': 0.9924538731575012, 'Train/mean miou_metric': 0.9848021864891052, 'Train/mean f1': 0.989094078540802, 'Train/mean precision': 0.984436571598053, 'Train/mean recall': 0.9937959313392639, 'Train/mean hd95_metric': 1.105129599571228} +Epoch [1100/4000] Validation [1/4] Loss: 0.25474 focal_loss 0.17851 dice_loss 0.07623 +Epoch [1100/4000] Validation [2/4] Loss: 0.38804 focal_loss 0.21206 dice_loss 0.17598 +Epoch [1100/4000] Validation [3/4] Loss: 0.30828 focal_loss 0.20682 dice_loss 0.10146 +Epoch [1100/4000] Validation [4/4] Loss: 0.29288 focal_loss 0.15708 dice_loss 0.13581 +Epoch [1100/4000] Validation metric {'Val/mean dice_metric': 0.9683371782302856, 'Val/mean miou_metric': 0.9485694766044617, 'Val/mean f1': 0.9685941338539124, 'Val/mean precision': 0.9591252207756042, 'Val/mean recall': 0.9782517552375793, 'Val/mean hd95_metric': 7.243985176086426} +Cheakpoint... +Epoch [1100/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683371782302856, 'Val/mean miou_metric': 0.9485694766044617, 'Val/mean f1': 0.9685941338539124, 'Val/mean precision': 0.9591252207756042, 'Val/mean recall': 0.9782517552375793, 'Val/mean hd95_metric': 7.243985176086426} +Epoch [1101/4000] Training [1/16] Loss: 0.00963 +Epoch [1101/4000] Training [2/16] Loss: 0.01000 +Epoch [1101/4000] Training [3/16] Loss: 0.00952 +Epoch [1101/4000] Training [4/16] Loss: 0.01215 +Epoch [1101/4000] Training [5/16] Loss: 0.01039 +Epoch [1101/4000] Training [6/16] Loss: 0.00974 +Epoch [1101/4000] Training [7/16] Loss: 0.00920 +Epoch [1101/4000] Training [8/16] Loss: 0.01021 +Epoch [1101/4000] Training [9/16] Loss: 0.01014 +Epoch [1101/4000] Training [10/16] Loss: 0.01243 +Epoch [1101/4000] Training [11/16] Loss: 0.00719 +Epoch [1101/4000] Training [12/16] Loss: 0.01287 +Epoch [1101/4000] Training [13/16] Loss: 0.01240 +Epoch [1101/4000] Training [14/16] Loss: 0.00884 +Epoch [1101/4000] Training [15/16] Loss: 0.01046 +Epoch [1101/4000] Training [16/16] Loss: 0.01388 +Epoch [1101/4000] Training metric {'Train/mean dice_metric': 0.992810845375061, 'Train/mean miou_metric': 0.9854896068572998, 'Train/mean f1': 0.9891862869262695, 'Train/mean precision': 0.9846364855766296, 'Train/mean recall': 0.9937783479690552, 'Train/mean hd95_metric': 1.0846776962280273} +Epoch [1101/4000] Validation [1/4] Loss: 0.24063 focal_loss 0.16898 dice_loss 0.07166 +Epoch [1101/4000] Validation [2/4] Loss: 0.36345 focal_loss 0.17866 dice_loss 0.18478 +Epoch [1101/4000] Validation [3/4] Loss: 0.31056 focal_loss 0.21132 dice_loss 0.09924 +Epoch [1101/4000] Validation [4/4] Loss: 0.29206 focal_loss 0.15156 dice_loss 0.14050 +Epoch [1101/4000] Validation metric {'Val/mean dice_metric': 0.9670257568359375, 'Val/mean miou_metric': 0.9480553865432739, 'Val/mean f1': 0.9683678150177002, 'Val/mean precision': 0.9612091779708862, 'Val/mean recall': 0.9756338596343994, 'Val/mean hd95_metric': 7.2906951904296875} +Cheakpoint... +Epoch [1101/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670257568359375, 'Val/mean miou_metric': 0.9480553865432739, 'Val/mean f1': 0.9683678150177002, 'Val/mean precision': 0.9612091779708862, 'Val/mean recall': 0.9756338596343994, 'Val/mean hd95_metric': 7.2906951904296875} +Epoch [1102/4000] Training [1/16] Loss: 0.01159 +Epoch [1102/4000] Training [2/16] Loss: 0.01484 +Epoch [1102/4000] Training [3/16] Loss: 0.00974 +Epoch [1102/4000] Training [4/16] Loss: 0.01188 +Epoch [1102/4000] Training [5/16] Loss: 0.01963 +Epoch [1102/4000] Training [6/16] Loss: 0.01054 +Epoch [1102/4000] Training [7/16] Loss: 0.01091 +Epoch [1102/4000] Training [8/16] Loss: 0.04685 +Epoch [1102/4000] Training [9/16] Loss: 0.00840 +Epoch [1102/4000] Training [10/16] Loss: 0.01088 +Epoch [1102/4000] Training [11/16] Loss: 0.01692 +Epoch [1102/4000] Training [12/16] Loss: 0.01137 +Epoch [1102/4000] Training [13/16] Loss: 0.01051 +Epoch [1102/4000] Training [14/16] Loss: 0.01030 +Epoch [1102/4000] Training [15/16] Loss: 0.01094 +Epoch [1102/4000] Training [16/16] Loss: 0.01035 +Epoch [1102/4000] Training metric {'Train/mean dice_metric': 0.9911338090896606, 'Train/mean miou_metric': 0.9823738932609558, 'Train/mean f1': 0.9875820875167847, 'Train/mean precision': 0.9823991060256958, 'Train/mean recall': 0.9928200244903564, 'Train/mean hd95_metric': 1.355836033821106} +Epoch [1102/4000] Validation [1/4] Loss: 0.21802 focal_loss 0.14603 dice_loss 0.07199 +Epoch [1102/4000] Validation [2/4] Loss: 0.36546 focal_loss 0.19876 dice_loss 0.16670 +Epoch [1102/4000] Validation [3/4] Loss: 0.30263 focal_loss 0.20440 dice_loss 0.09823 +Epoch [1102/4000] Validation [4/4] Loss: 0.24757 focal_loss 0.12068 dice_loss 0.12689 +Epoch [1102/4000] Validation metric {'Val/mean dice_metric': 0.9667223691940308, 'Val/mean miou_metric': 0.9463175535202026, 'Val/mean f1': 0.9683228135108948, 'Val/mean precision': 0.9604458212852478, 'Val/mean recall': 0.9763299822807312, 'Val/mean hd95_metric': 6.838747978210449} +Cheakpoint... +Epoch [1102/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667223691940308, 'Val/mean miou_metric': 0.9463175535202026, 'Val/mean f1': 0.9683228135108948, 'Val/mean precision': 0.9604458212852478, 'Val/mean recall': 0.9763299822807312, 'Val/mean hd95_metric': 6.838747978210449} +Epoch [1103/4000] Training [1/16] Loss: 0.00919 +Epoch [1103/4000] Training [2/16] Loss: 0.01171 +Epoch [1103/4000] Training [3/16] Loss: 0.01345 +Epoch [1103/4000] Training [4/16] Loss: 0.01054 +Epoch [1103/4000] Training [5/16] Loss: 0.01069 +Epoch [1103/4000] Training [6/16] Loss: 0.01135 +Epoch [1103/4000] Training [7/16] Loss: 0.00895 +Epoch [1103/4000] Training [8/16] Loss: 0.01327 +Epoch [1103/4000] Training [9/16] Loss: 0.01823 +Epoch [1103/4000] Training [10/16] Loss: 0.01377 +Epoch [1103/4000] Training [11/16] Loss: 0.01166 +Epoch [1103/4000] Training [12/16] Loss: 0.00978 +Epoch [1103/4000] Training [13/16] Loss: 0.01774 +Epoch [1103/4000] Training [14/16] Loss: 0.00962 +Epoch [1103/4000] Training [15/16] Loss: 0.00909 +Epoch [1103/4000] Training [16/16] Loss: 0.01036 +Epoch [1103/4000] Training metric {'Train/mean dice_metric': 0.9920310378074646, 'Train/mean miou_metric': 0.9840104579925537, 'Train/mean f1': 0.9884997606277466, 'Train/mean precision': 0.9842141270637512, 'Train/mean recall': 0.9928228259086609, 'Train/mean hd95_metric': 1.2324696779251099} +Epoch [1103/4000] Validation [1/4] Loss: 0.33556 focal_loss 0.23542 dice_loss 0.10014 +Epoch [1103/4000] Validation [2/4] Loss: 0.35076 focal_loss 0.17236 dice_loss 0.17841 +Epoch [1103/4000] Validation [3/4] Loss: 0.21446 focal_loss 0.11693 dice_loss 0.09753 +Epoch [1103/4000] Validation [4/4] Loss: 0.24952 focal_loss 0.12356 dice_loss 0.12596 +Epoch [1103/4000] Validation metric {'Val/mean dice_metric': 0.9689643979072571, 'Val/mean miou_metric': 0.9489356875419617, 'Val/mean f1': 0.970043957233429, 'Val/mean precision': 0.9685482978820801, 'Val/mean recall': 0.9715442061424255, 'Val/mean hd95_metric': 6.250058174133301} +Cheakpoint... +Epoch [1103/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689643979072571, 'Val/mean miou_metric': 0.9489356875419617, 'Val/mean f1': 0.970043957233429, 'Val/mean precision': 0.9685482978820801, 'Val/mean recall': 0.9715442061424255, 'Val/mean hd95_metric': 6.250058174133301} +Epoch [1104/4000] Training [1/16] Loss: 0.01020 +Epoch [1104/4000] Training [2/16] Loss: 0.01120 +Epoch [1104/4000] Training [3/16] Loss: 0.01161 +Epoch [1104/4000] Training [4/16] Loss: 0.01092 +Epoch [1104/4000] Training [5/16] Loss: 0.01038 +Epoch [1104/4000] Training [6/16] Loss: 0.01257 +Epoch [1104/4000] Training [7/16] Loss: 0.01176 +Epoch [1104/4000] Training [8/16] Loss: 0.01059 +Epoch [1104/4000] Training [9/16] Loss: 0.01464 +Epoch [1104/4000] Training [10/16] Loss: 0.01073 +Epoch [1104/4000] Training [11/16] Loss: 0.01221 +Epoch [1104/4000] Training [12/16] Loss: 0.00935 +Epoch [1104/4000] Training [13/16] Loss: 0.01071 +Epoch [1104/4000] Training [14/16] Loss: 0.01122 +Epoch [1104/4000] Training [15/16] Loss: 0.01007 +Epoch [1104/4000] Training [16/16] Loss: 0.01093 +Epoch [1104/4000] Training metric {'Train/mean dice_metric': 0.9922950267791748, 'Train/mean miou_metric': 0.9844778776168823, 'Train/mean f1': 0.9887323379516602, 'Train/mean precision': 0.9842028617858887, 'Train/mean recall': 0.993303656578064, 'Train/mean hd95_metric': 1.2484264373779297} +Epoch [1104/4000] Validation [1/4] Loss: 0.20365 focal_loss 0.13498 dice_loss 0.06867 +Epoch [1104/4000] Validation [2/4] Loss: 0.23670 focal_loss 0.11173 dice_loss 0.12497 +Epoch [1104/4000] Validation [3/4] Loss: 0.28123 focal_loss 0.18927 dice_loss 0.09196 +Epoch [1104/4000] Validation [4/4] Loss: 0.21969 focal_loss 0.10275 dice_loss 0.11693 +Epoch [1104/4000] Validation metric {'Val/mean dice_metric': 0.9667263031005859, 'Val/mean miou_metric': 0.9470564126968384, 'Val/mean f1': 0.97054523229599, 'Val/mean precision': 0.9698349237442017, 'Val/mean recall': 0.971256673336029, 'Val/mean hd95_metric': 5.863711833953857} +Cheakpoint... +Epoch [1104/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667263031005859, 'Val/mean miou_metric': 0.9470564126968384, 'Val/mean f1': 0.97054523229599, 'Val/mean precision': 0.9698349237442017, 'Val/mean recall': 0.971256673336029, 'Val/mean hd95_metric': 5.863711833953857} +Epoch [1105/4000] Training [1/16] Loss: 0.00950 +Epoch [1105/4000] Training [2/16] Loss: 0.01050 +Epoch [1105/4000] Training [3/16] Loss: 0.00984 +Epoch [1105/4000] Training [4/16] Loss: 0.01019 +Epoch [1105/4000] Training [5/16] Loss: 0.01010 +Epoch [1105/4000] Training [6/16] Loss: 0.01221 +Epoch [1105/4000] Training [7/16] Loss: 0.00936 +Epoch [1105/4000] Training [8/16] Loss: 0.00918 +Epoch [1105/4000] Training [9/16] Loss: 0.01626 +Epoch [1105/4000] Training [10/16] Loss: 0.00883 +Epoch [1105/4000] Training [11/16] Loss: 0.01734 +Epoch [1105/4000] Training [12/16] Loss: 0.01185 +Epoch [1105/4000] Training [13/16] Loss: 0.01233 +Epoch [1105/4000] Training [14/16] Loss: 0.00883 +Epoch [1105/4000] Training [15/16] Loss: 0.01472 +Epoch [1105/4000] Training [16/16] Loss: 0.02097 +Epoch [1105/4000] Training metric {'Train/mean dice_metric': 0.9920893907546997, 'Train/mean miou_metric': 0.9840809106826782, 'Train/mean f1': 0.9879083037376404, 'Train/mean precision': 0.9830631613731384, 'Train/mean recall': 0.9928014278411865, 'Train/mean hd95_metric': 1.270376205444336} +Epoch [1105/4000] Validation [1/4] Loss: 0.17524 focal_loss 0.11630 dice_loss 0.05894 +Epoch [1105/4000] Validation [2/4] Loss: 0.38995 focal_loss 0.16618 dice_loss 0.22377 +Epoch [1105/4000] Validation [3/4] Loss: 0.30235 focal_loss 0.20165 dice_loss 0.10070 +Epoch [1105/4000] Validation [4/4] Loss: 0.23441 focal_loss 0.11793 dice_loss 0.11647 +Epoch [1105/4000] Validation metric {'Val/mean dice_metric': 0.9656522870063782, 'Val/mean miou_metric': 0.9461771845817566, 'Val/mean f1': 0.9691583514213562, 'Val/mean precision': 0.96266770362854, 'Val/mean recall': 0.9757370948791504, 'Val/mean hd95_metric': 6.320021629333496} +Cheakpoint... +Epoch [1105/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9657], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656522870063782, 'Val/mean miou_metric': 0.9461771845817566, 'Val/mean f1': 0.9691583514213562, 'Val/mean precision': 0.96266770362854, 'Val/mean recall': 0.9757370948791504, 'Val/mean hd95_metric': 6.320021629333496} +Epoch [1106/4000] Training [1/16] Loss: 0.00883 +Epoch [1106/4000] Training [2/16] Loss: 0.01125 +Epoch [1106/4000] Training [3/16] Loss: 0.00911 +Epoch [1106/4000] Training [4/16] Loss: 0.00937 +Epoch [1106/4000] Training [5/16] Loss: 0.00705 +Epoch [1106/4000] Training [6/16] Loss: 0.01030 +Epoch [1106/4000] Training [7/16] Loss: 0.01166 +Epoch [1106/4000] Training [8/16] Loss: 0.00921 +Epoch [1106/4000] Training [9/16] Loss: 0.01469 +Epoch [1106/4000] Training [10/16] Loss: 0.01060 +Epoch [1106/4000] Training [11/16] Loss: 0.01278 +Epoch [1106/4000] Training [12/16] Loss: 0.01173 +Epoch [1106/4000] Training [13/16] Loss: 0.01211 +Epoch [1106/4000] Training [14/16] Loss: 0.00994 +Epoch [1106/4000] Training [15/16] Loss: 0.01062 +Epoch [1106/4000] Training [16/16] Loss: 0.00968 +Epoch [1106/4000] Training metric {'Train/mean dice_metric': 0.9927747249603271, 'Train/mean miou_metric': 0.9854206442832947, 'Train/mean f1': 0.989297091960907, 'Train/mean precision': 0.9847699999809265, 'Train/mean recall': 0.9938660264015198, 'Train/mean hd95_metric': 1.0709912776947021} +Epoch [1106/4000] Validation [1/4] Loss: 0.17045 focal_loss 0.11523 dice_loss 0.05522 +Epoch [1106/4000] Validation [2/4] Loss: 0.45517 focal_loss 0.24182 dice_loss 0.21335 +Epoch [1106/4000] Validation [3/4] Loss: 0.30268 focal_loss 0.20917 dice_loss 0.09352 +Epoch [1106/4000] Validation [4/4] Loss: 0.28734 focal_loss 0.14576 dice_loss 0.14158 +Epoch [1106/4000] Validation metric {'Val/mean dice_metric': 0.9684316515922546, 'Val/mean miou_metric': 0.9499143362045288, 'Val/mean f1': 0.969801664352417, 'Val/mean precision': 0.9603078961372375, 'Val/mean recall': 0.979485034942627, 'Val/mean hd95_metric': 5.77731990814209} +Cheakpoint... +Epoch [1106/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684316515922546, 'Val/mean miou_metric': 0.9499143362045288, 'Val/mean f1': 0.969801664352417, 'Val/mean precision': 0.9603078961372375, 'Val/mean recall': 0.979485034942627, 'Val/mean hd95_metric': 5.77731990814209} +Epoch [1107/4000] Training [1/16] Loss: 0.00955 +Epoch [1107/4000] Training [2/16] Loss: 0.00986 +Epoch [1107/4000] Training [3/16] Loss: 0.01118 +Epoch [1107/4000] Training [4/16] Loss: 0.01021 +Epoch [1107/4000] Training [5/16] Loss: 0.01008 +Epoch [1107/4000] Training [6/16] Loss: 0.00886 +Epoch [1107/4000] Training [7/16] Loss: 0.00902 +Epoch [1107/4000] Training [8/16] Loss: 0.01251 +Epoch [1107/4000] Training [9/16] Loss: 0.00959 +Epoch [1107/4000] Training [10/16] Loss: 0.01364 +Epoch [1107/4000] Training [11/16] Loss: 0.01392 +Epoch [1107/4000] Training [12/16] Loss: 0.00933 +Epoch [1107/4000] Training [13/16] Loss: 0.01150 +Epoch [1107/4000] Training [14/16] Loss: 0.01255 +Epoch [1107/4000] Training [15/16] Loss: 0.01201 +Epoch [1107/4000] Training [16/16] Loss: 0.01235 +Epoch [1107/4000] Training metric {'Train/mean dice_metric': 0.9924202561378479, 'Train/mean miou_metric': 0.9847357273101807, 'Train/mean f1': 0.9891605973243713, 'Train/mean precision': 0.98459792137146, 'Train/mean recall': 0.9937657117843628, 'Train/mean hd95_metric': 1.1560032367706299} +Epoch [1107/4000] Validation [1/4] Loss: 0.17577 focal_loss 0.11665 dice_loss 0.05913 +Epoch [1107/4000] Validation [2/4] Loss: 0.37994 focal_loss 0.18980 dice_loss 0.19014 +Epoch [1107/4000] Validation [3/4] Loss: 0.20357 focal_loss 0.10491 dice_loss 0.09866 +Epoch [1107/4000] Validation [4/4] Loss: 0.23107 focal_loss 0.11308 dice_loss 0.11799 +Epoch [1107/4000] Validation metric {'Val/mean dice_metric': 0.9678207635879517, 'Val/mean miou_metric': 0.948386549949646, 'Val/mean f1': 0.970424473285675, 'Val/mean precision': 0.9632965922355652, 'Val/mean recall': 0.977658748626709, 'Val/mean hd95_metric': 6.802037715911865} +Cheakpoint... +Epoch [1107/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678207635879517, 'Val/mean miou_metric': 0.948386549949646, 'Val/mean f1': 0.970424473285675, 'Val/mean precision': 0.9632965922355652, 'Val/mean recall': 0.977658748626709, 'Val/mean hd95_metric': 6.802037715911865} +Epoch [1108/4000] Training [1/16] Loss: 0.00993 +Epoch [1108/4000] Training [2/16] Loss: 0.01127 +Epoch [1108/4000] Training [3/16] Loss: 0.01058 +Epoch [1108/4000] Training [4/16] Loss: 0.01270 +Epoch [1108/4000] Training [5/16] Loss: 0.00972 +Epoch [1108/4000] Training [6/16] Loss: 0.01086 +Epoch [1108/4000] Training [7/16] Loss: 0.00938 +Epoch [1108/4000] Training [8/16] Loss: 0.01139 +Epoch [1108/4000] Training [9/16] Loss: 0.01145 +Epoch [1108/4000] Training [10/16] Loss: 0.01524 +Epoch [1108/4000] Training [11/16] Loss: 0.01684 +Epoch [1108/4000] Training [12/16] Loss: 0.00959 +Epoch [1108/4000] Training [13/16] Loss: 0.01349 +Epoch [1108/4000] Training [14/16] Loss: 0.01206 +Epoch [1108/4000] Training [15/16] Loss: 0.01565 +Epoch [1108/4000] Training [16/16] Loss: 0.01336 +Epoch [1108/4000] Training metric {'Train/mean dice_metric': 0.9921254515647888, 'Train/mean miou_metric': 0.9841702580451965, 'Train/mean f1': 0.9887086749076843, 'Train/mean precision': 0.9839112758636475, 'Train/mean recall': 0.9935531616210938, 'Train/mean hd95_metric': 1.2103019952774048} +Epoch [1108/4000] Validation [1/4] Loss: 0.22071 focal_loss 0.15387 dice_loss 0.06684 +Epoch [1108/4000] Validation [2/4] Loss: 0.61860 focal_loss 0.34770 dice_loss 0.27089 +Epoch [1108/4000] Validation [3/4] Loss: 0.30257 focal_loss 0.20816 dice_loss 0.09441 +Epoch [1108/4000] Validation [4/4] Loss: 0.18539 focal_loss 0.09250 dice_loss 0.09288 +Epoch [1108/4000] Validation metric {'Val/mean dice_metric': 0.969567596912384, 'Val/mean miou_metric': 0.9501244425773621, 'Val/mean f1': 0.9700583219528198, 'Val/mean precision': 0.9631592631340027, 'Val/mean recall': 0.9770570993423462, 'Val/mean hd95_metric': 6.425568580627441} +Cheakpoint... +Epoch [1108/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969567596912384, 'Val/mean miou_metric': 0.9501244425773621, 'Val/mean f1': 0.9700583219528198, 'Val/mean precision': 0.9631592631340027, 'Val/mean recall': 0.9770570993423462, 'Val/mean hd95_metric': 6.425568580627441} +Epoch [1109/4000] Training [1/16] Loss: 0.01046 +Epoch [1109/4000] Training [2/16] Loss: 0.01022 +Epoch [1109/4000] Training [3/16] Loss: 0.00900 +Epoch [1109/4000] Training [4/16] Loss: 0.01348 +Epoch [1109/4000] Training [5/16] Loss: 0.00789 +Epoch [1109/4000] Training [6/16] Loss: 0.00826 +Epoch [1109/4000] Training [7/16] Loss: 0.01324 +Epoch [1109/4000] Training [8/16] Loss: 0.00739 +Epoch [1109/4000] Training [9/16] Loss: 0.00926 +Epoch [1109/4000] Training [10/16] Loss: 0.01157 +Epoch [1109/4000] Training [11/16] Loss: 0.01185 +Epoch [1109/4000] Training [12/16] Loss: 0.00951 +Epoch [1109/4000] Training [13/16] Loss: 0.01540 +Epoch [1109/4000] Training [14/16] Loss: 0.00877 +Epoch [1109/4000] Training [15/16] Loss: 0.01151 +Epoch [1109/4000] Training [16/16] Loss: 0.01101 +Epoch [1109/4000] Training metric {'Train/mean dice_metric': 0.9919171929359436, 'Train/mean miou_metric': 0.9838184118270874, 'Train/mean f1': 0.9887601137161255, 'Train/mean precision': 0.9842129945755005, 'Train/mean recall': 0.9933496117591858, 'Train/mean hd95_metric': 1.1909605264663696} +Epoch [1109/4000] Validation [1/4] Loss: 0.17793 focal_loss 0.11750 dice_loss 0.06043 +Epoch [1109/4000] Validation [2/4] Loss: 0.24220 focal_loss 0.11049 dice_loss 0.13170 +Epoch [1109/4000] Validation [3/4] Loss: 0.33699 focal_loss 0.23273 dice_loss 0.10426 +Epoch [1109/4000] Validation [4/4] Loss: 0.24956 focal_loss 0.14188 dice_loss 0.10768 +Epoch [1109/4000] Validation metric {'Val/mean dice_metric': 0.9688695669174194, 'Val/mean miou_metric': 0.9487228393554688, 'Val/mean f1': 0.9708371162414551, 'Val/mean precision': 0.9644365906715393, 'Val/mean recall': 0.9773232340812683, 'Val/mean hd95_metric': 6.992198944091797} +Cheakpoint... +Epoch [1109/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688695669174194, 'Val/mean miou_metric': 0.9487228393554688, 'Val/mean f1': 0.9708371162414551, 'Val/mean precision': 0.9644365906715393, 'Val/mean recall': 0.9773232340812683, 'Val/mean hd95_metric': 6.992198944091797} +Epoch [1110/4000] Training [1/16] Loss: 0.00941 +Epoch [1110/4000] Training [2/16] Loss: 0.01007 +Epoch [1110/4000] Training [3/16] Loss: 0.00928 +Epoch [1110/4000] Training [4/16] Loss: 0.01023 +Epoch [1110/4000] Training [5/16] Loss: 0.01059 +Epoch [1110/4000] Training [6/16] Loss: 0.00823 +Epoch [1110/4000] Training [7/16] Loss: 0.00963 +Epoch [1110/4000] Training [8/16] Loss: 0.01151 +Epoch [1110/4000] Training [9/16] Loss: 0.00803 +Epoch [1110/4000] Training [10/16] Loss: 0.00928 +Epoch [1110/4000] Training [11/16] Loss: 0.00876 +Epoch [1110/4000] Training [12/16] Loss: 0.01126 +Epoch [1110/4000] Training [13/16] Loss: 0.01231 +Epoch [1110/4000] Training [14/16] Loss: 0.01339 +Epoch [1110/4000] Training [15/16] Loss: 0.01371 +Epoch [1110/4000] Training [16/16] Loss: 0.01257 +Epoch [1110/4000] Training metric {'Train/mean dice_metric': 0.9924548864364624, 'Train/mean miou_metric': 0.9847867488861084, 'Train/mean f1': 0.9884037375450134, 'Train/mean precision': 0.983121931552887, 'Train/mean recall': 0.9937426447868347, 'Train/mean hd95_metric': 1.424653172492981} +Epoch [1110/4000] Validation [1/4] Loss: 0.17034 focal_loss 0.11374 dice_loss 0.05660 +Epoch [1110/4000] Validation [2/4] Loss: 0.32799 focal_loss 0.16513 dice_loss 0.16285 +Epoch [1110/4000] Validation [3/4] Loss: 0.31671 focal_loss 0.19245 dice_loss 0.12426 +Epoch [1110/4000] Validation [4/4] Loss: 0.24061 focal_loss 0.11353 dice_loss 0.12708 +Epoch [1110/4000] Validation metric {'Val/mean dice_metric': 0.9682235717773438, 'Val/mean miou_metric': 0.9481865763664246, 'Val/mean f1': 0.9701573848724365, 'Val/mean precision': 0.9611647725105286, 'Val/mean recall': 0.9793199300765991, 'Val/mean hd95_metric': 6.707528591156006} +Cheakpoint... +Epoch [1110/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9682235717773438, 'Val/mean miou_metric': 0.9481865763664246, 'Val/mean f1': 0.9701573848724365, 'Val/mean precision': 0.9611647725105286, 'Val/mean recall': 0.9793199300765991, 'Val/mean hd95_metric': 6.707528591156006} +Epoch [1111/4000] Training [1/16] Loss: 0.00960 +Epoch [1111/4000] Training [2/16] Loss: 0.00912 +Epoch [1111/4000] Training [3/16] Loss: 0.01188 +Epoch [1111/4000] Training [4/16] Loss: 0.01019 +Epoch [1111/4000] Training [5/16] Loss: 0.01129 +Epoch [1111/4000] Training [6/16] Loss: 0.01241 +Epoch [1111/4000] Training [7/16] Loss: 0.01022 +Epoch [1111/4000] Training [8/16] Loss: 0.00948 +Epoch [1111/4000] Training [9/16] Loss: 0.01033 +Epoch [1111/4000] Training [10/16] Loss: 0.00926 +Epoch [1111/4000] Training [11/16] Loss: 0.00900 +Epoch [1111/4000] Training [12/16] Loss: 0.01075 +Epoch [1111/4000] Training [13/16] Loss: 0.00847 +Epoch [1111/4000] Training [14/16] Loss: 0.01505 +Epoch [1111/4000] Training [15/16] Loss: 0.01400 +Epoch [1111/4000] Training [16/16] Loss: 0.01001 +Epoch [1111/4000] Training metric {'Train/mean dice_metric': 0.9923900365829468, 'Train/mean miou_metric': 0.9846935272216797, 'Train/mean f1': 0.9890974164009094, 'Train/mean precision': 0.9845630526542664, 'Train/mean recall': 0.9936737418174744, 'Train/mean hd95_metric': 1.172810673713684} +Epoch [1111/4000] Validation [1/4] Loss: 0.21146 focal_loss 0.14651 dice_loss 0.06496 +Epoch [1111/4000] Validation [2/4] Loss: 0.41365 focal_loss 0.20965 dice_loss 0.20400 +Epoch [1111/4000] Validation [3/4] Loss: 0.30006 focal_loss 0.20508 dice_loss 0.09498 +Epoch [1111/4000] Validation [4/4] Loss: 0.31006 focal_loss 0.17300 dice_loss 0.13706 +Epoch [1111/4000] Validation metric {'Val/mean dice_metric': 0.9675033688545227, 'Val/mean miou_metric': 0.9476041793823242, 'Val/mean f1': 0.9700193405151367, 'Val/mean precision': 0.9643773436546326, 'Val/mean recall': 0.9757277369499207, 'Val/mean hd95_metric': 6.444705963134766} +Cheakpoint... +Epoch [1111/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675033688545227, 'Val/mean miou_metric': 0.9476041793823242, 'Val/mean f1': 0.9700193405151367, 'Val/mean precision': 0.9643773436546326, 'Val/mean recall': 0.9757277369499207, 'Val/mean hd95_metric': 6.444705963134766} +Epoch [1112/4000] Training [1/16] Loss: 0.01445 +Epoch [1112/4000] Training [2/16] Loss: 0.01411 +Epoch [1112/4000] Training [3/16] Loss: 0.00939 +Epoch [1112/4000] Training [4/16] Loss: 0.01310 +Epoch [1112/4000] Training [5/16] Loss: 0.01689 +Epoch [1112/4000] Training [6/16] Loss: 0.01182 +Epoch [1112/4000] Training [7/16] Loss: 0.01563 +Epoch [1112/4000] Training [8/16] Loss: 0.01278 +Epoch [1112/4000] Training [9/16] Loss: 0.01114 +Epoch [1112/4000] Training [10/16] Loss: 0.01416 +Epoch [1112/4000] Training [11/16] Loss: 0.01326 +Epoch [1112/4000] Training [12/16] Loss: 0.02164 +Epoch [1112/4000] Training [13/16] Loss: 0.01005 +Epoch [1112/4000] Training [14/16] Loss: 0.01179 +Epoch [1112/4000] Training [15/16] Loss: 0.01681 +Epoch [1112/4000] Training [16/16] Loss: 0.01017 +Epoch [1112/4000] Training metric {'Train/mean dice_metric': 0.9905268549919128, 'Train/mean miou_metric': 0.9814205169677734, 'Train/mean f1': 0.9865613579750061, 'Train/mean precision': 0.9809741377830505, 'Train/mean recall': 0.9922126531600952, 'Train/mean hd95_metric': 1.8965215682983398} +Epoch [1112/4000] Validation [1/4] Loss: 0.21415 focal_loss 0.14545 dice_loss 0.06870 +Epoch [1112/4000] Validation [2/4] Loss: 0.47413 focal_loss 0.23899 dice_loss 0.23514 +Epoch [1112/4000] Validation [3/4] Loss: 0.30893 focal_loss 0.19645 dice_loss 0.11248 +Epoch [1112/4000] Validation [4/4] Loss: 0.24332 focal_loss 0.13021 dice_loss 0.11311 +Epoch [1112/4000] Validation metric {'Val/mean dice_metric': 0.9673929214477539, 'Val/mean miou_metric': 0.9471162557601929, 'Val/mean f1': 0.9698776006698608, 'Val/mean precision': 0.9659854173660278, 'Val/mean recall': 0.9738011360168457, 'Val/mean hd95_metric': 6.362957000732422} +Cheakpoint... +Epoch [1112/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673929214477539, 'Val/mean miou_metric': 0.9471162557601929, 'Val/mean f1': 0.9698776006698608, 'Val/mean precision': 0.9659854173660278, 'Val/mean recall': 0.9738011360168457, 'Val/mean hd95_metric': 6.362957000732422} +Epoch [1113/4000] Training [1/16] Loss: 0.01277 +Epoch [1113/4000] Training [2/16] Loss: 0.01277 +Epoch [1113/4000] Training [3/16] Loss: 0.00972 +Epoch [1113/4000] Training [4/16] Loss: 0.01158 +Epoch [1113/4000] Training [5/16] Loss: 0.00773 +Epoch [1113/4000] Training [6/16] Loss: 0.00702 +Epoch [1113/4000] Training [7/16] Loss: 0.01345 +Epoch [1113/4000] Training [8/16] Loss: 0.00793 +Epoch [1113/4000] Training [9/16] Loss: 0.00926 +Epoch [1113/4000] Training [10/16] Loss: 0.01063 +Epoch [1113/4000] Training [11/16] Loss: 0.01036 +Epoch [1113/4000] Training [12/16] Loss: 0.01275 +Epoch [1113/4000] Training [13/16] Loss: 0.00941 +Epoch [1113/4000] Training [14/16] Loss: 0.01753 +Epoch [1113/4000] Training [15/16] Loss: 0.01298 +Epoch [1113/4000] Training [16/16] Loss: 0.01145 +Epoch [1113/4000] Training metric {'Train/mean dice_metric': 0.9927060604095459, 'Train/mean miou_metric': 0.9853068590164185, 'Train/mean f1': 0.9891188144683838, 'Train/mean precision': 0.9847045540809631, 'Train/mean recall': 0.9935728907585144, 'Train/mean hd95_metric': 1.5321180820465088} +Epoch [1113/4000] Validation [1/4] Loss: 0.16922 focal_loss 0.11208 dice_loss 0.05714 +Epoch [1113/4000] Validation [2/4] Loss: 0.25519 focal_loss 0.13236 dice_loss 0.12283 +Epoch [1113/4000] Validation [3/4] Loss: 0.29064 focal_loss 0.19116 dice_loss 0.09947 +Epoch [1113/4000] Validation [4/4] Loss: 0.32156 focal_loss 0.18260 dice_loss 0.13896 +Epoch [1113/4000] Validation metric {'Val/mean dice_metric': 0.9699819684028625, 'Val/mean miou_metric': 0.9506440162658691, 'Val/mean f1': 0.9725043773651123, 'Val/mean precision': 0.9685808420181274, 'Val/mean recall': 0.9764596819877625, 'Val/mean hd95_metric': 6.020427227020264} +Cheakpoint... +Epoch [1113/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699819684028625, 'Val/mean miou_metric': 0.9506440162658691, 'Val/mean f1': 0.9725043773651123, 'Val/mean precision': 0.9685808420181274, 'Val/mean recall': 0.9764596819877625, 'Val/mean hd95_metric': 6.020427227020264} +Epoch [1114/4000] Training [1/16] Loss: 0.02650 +Epoch [1114/4000] Training [2/16] Loss: 0.01357 +Epoch [1114/4000] Training [3/16] Loss: 0.01316 +Epoch [1114/4000] Training [4/16] Loss: 0.01191 +Epoch [1114/4000] Training [5/16] Loss: 0.00816 +Epoch [1114/4000] Training [6/16] Loss: 0.00923 +Epoch [1114/4000] Training [7/16] Loss: 0.00825 +Epoch [1114/4000] Training [8/16] Loss: 0.00992 +Epoch [1114/4000] Training [9/16] Loss: 0.01408 +Epoch [1114/4000] Training [10/16] Loss: 0.01162 +Epoch [1114/4000] Training [11/16] Loss: 0.00939 +Epoch [1114/4000] Training [12/16] Loss: 0.00932 +Epoch [1114/4000] Training [13/16] Loss: 0.00913 +Epoch [1114/4000] Training [14/16] Loss: 0.01290 +Epoch [1114/4000] Training [15/16] Loss: 0.00868 +Epoch [1114/4000] Training [16/16] Loss: 0.00962 +Epoch [1114/4000] Training metric {'Train/mean dice_metric': 0.9924125671386719, 'Train/mean miou_metric': 0.9847434759140015, 'Train/mean f1': 0.9890347123146057, 'Train/mean precision': 0.9845956563949585, 'Train/mean recall': 0.9935139417648315, 'Train/mean hd95_metric': 1.3120328187942505} +Epoch [1114/4000] Validation [1/4] Loss: 0.21174 focal_loss 0.13988 dice_loss 0.07185 +Epoch [1114/4000] Validation [2/4] Loss: 0.45445 focal_loss 0.22511 dice_loss 0.22934 +Epoch [1114/4000] Validation [3/4] Loss: 0.25920 focal_loss 0.16924 dice_loss 0.08996 +Epoch [1114/4000] Validation [4/4] Loss: 0.31705 focal_loss 0.17947 dice_loss 0.13758 +Epoch [1114/4000] Validation metric {'Val/mean dice_metric': 0.9676047563552856, 'Val/mean miou_metric': 0.9479219317436218, 'Val/mean f1': 0.9704781770706177, 'Val/mean precision': 0.9686404466629028, 'Val/mean recall': 0.9723227620124817, 'Val/mean hd95_metric': 6.1729607582092285} +Cheakpoint... +Epoch [1114/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676047563552856, 'Val/mean miou_metric': 0.9479219317436218, 'Val/mean f1': 0.9704781770706177, 'Val/mean precision': 0.9686404466629028, 'Val/mean recall': 0.9723227620124817, 'Val/mean hd95_metric': 6.1729607582092285} +Epoch [1115/4000] Training [1/16] Loss: 0.01182 +Epoch [1115/4000] Training [2/16] Loss: 0.00862 +Epoch [1115/4000] Training [3/16] Loss: 0.01049 +Epoch [1115/4000] Training [4/16] Loss: 0.00904 +Epoch [1115/4000] Training [5/16] Loss: 0.01136 +Epoch [1115/4000] Training [6/16] Loss: 0.01380 +Epoch [1115/4000] Training [7/16] Loss: 0.00776 +Epoch [1115/4000] Training [8/16] Loss: 0.01018 +Epoch [1115/4000] Training [9/16] Loss: 0.02064 +Epoch [1115/4000] Training [10/16] Loss: 0.00828 +Epoch [1115/4000] Training [11/16] Loss: 0.00983 +Epoch [1115/4000] Training [12/16] Loss: 0.01199 +Epoch [1115/4000] Training [13/16] Loss: 0.00875 +Epoch [1115/4000] Training [14/16] Loss: 0.01274 +Epoch [1115/4000] Training [15/16] Loss: 0.00937 +Epoch [1115/4000] Training [16/16] Loss: 0.01022 +Epoch [1115/4000] Training metric {'Train/mean dice_metric': 0.9930921196937561, 'Train/mean miou_metric': 0.9860446453094482, 'Train/mean f1': 0.9894645810127258, 'Train/mean precision': 0.9846280217170715, 'Train/mean recall': 0.99434894323349, 'Train/mean hd95_metric': 1.0798823833465576} +Epoch [1115/4000] Validation [1/4] Loss: 0.18118 focal_loss 0.11845 dice_loss 0.06272 +Epoch [1115/4000] Validation [2/4] Loss: 0.41472 focal_loss 0.18364 dice_loss 0.23108 +Epoch [1115/4000] Validation [3/4] Loss: 0.28868 focal_loss 0.18387 dice_loss 0.10482 +Epoch [1115/4000] Validation [4/4] Loss: 0.29567 focal_loss 0.14458 dice_loss 0.15109 +Epoch [1115/4000] Validation metric {'Val/mean dice_metric': 0.9656345248222351, 'Val/mean miou_metric': 0.9462863206863403, 'Val/mean f1': 0.9701484441757202, 'Val/mean precision': 0.9676437377929688, 'Val/mean recall': 0.972666323184967, 'Val/mean hd95_metric': 7.0021514892578125} +Cheakpoint... +Epoch [1115/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656345248222351, 'Val/mean miou_metric': 0.9462863206863403, 'Val/mean f1': 0.9701484441757202, 'Val/mean precision': 0.9676437377929688, 'Val/mean recall': 0.972666323184967, 'Val/mean hd95_metric': 7.0021514892578125} +Epoch [1116/4000] Training [1/16] Loss: 0.00862 +Epoch [1116/4000] Training [2/16] Loss: 0.01033 +Epoch [1116/4000] Training [3/16] Loss: 0.01056 +Epoch [1116/4000] Training [4/16] Loss: 0.01030 +Epoch [1116/4000] Training [5/16] Loss: 0.00854 +Epoch [1116/4000] Training [6/16] Loss: 0.01073 +Epoch [1116/4000] Training [7/16] Loss: 0.00880 +Epoch [1116/4000] Training [8/16] Loss: 0.00864 +Epoch [1116/4000] Training [9/16] Loss: 0.01047 +Epoch [1116/4000] Training [10/16] Loss: 0.01216 +Epoch [1116/4000] Training [11/16] Loss: 0.00864 +Epoch [1116/4000] Training [12/16] Loss: 0.00868 +Epoch [1116/4000] Training [13/16] Loss: 0.00969 +Epoch [1116/4000] Training [14/16] Loss: 0.00999 +Epoch [1116/4000] Training [15/16] Loss: 0.00940 +Epoch [1116/4000] Training [16/16] Loss: 0.00918 +Epoch [1116/4000] Training metric {'Train/mean dice_metric': 0.9931759834289551, 'Train/mean miou_metric': 0.9861956238746643, 'Train/mean f1': 0.9895152449607849, 'Train/mean precision': 0.9849185943603516, 'Train/mean recall': 0.9941549897193909, 'Train/mean hd95_metric': 1.07664155960083} +Epoch [1116/4000] Validation [1/4] Loss: 0.23530 focal_loss 0.15667 dice_loss 0.07863 +Epoch [1116/4000] Validation [2/4] Loss: 0.22618 focal_loss 0.11271 dice_loss 0.11347 +Epoch [1116/4000] Validation [3/4] Loss: 0.31621 focal_loss 0.20583 dice_loss 0.11038 +Epoch [1116/4000] Validation [4/4] Loss: 0.34701 focal_loss 0.20407 dice_loss 0.14294 +Epoch [1116/4000] Validation metric {'Val/mean dice_metric': 0.9710928797721863, 'Val/mean miou_metric': 0.9516245126724243, 'Val/mean f1': 0.9723028540611267, 'Val/mean precision': 0.970378577709198, 'Val/mean recall': 0.9742348194122314, 'Val/mean hd95_metric': 5.817325592041016} +Cheakpoint... +Epoch [1116/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710928797721863, 'Val/mean miou_metric': 0.9516245126724243, 'Val/mean f1': 0.9723028540611267, 'Val/mean precision': 0.970378577709198, 'Val/mean recall': 0.9742348194122314, 'Val/mean hd95_metric': 5.817325592041016} +Epoch [1117/4000] Training [1/16] Loss: 0.00860 +Epoch [1117/4000] Training [2/16] Loss: 0.01202 +Epoch [1117/4000] Training [3/16] Loss: 0.00688 +Epoch [1117/4000] Training [4/16] Loss: 0.00937 +Epoch [1117/4000] Training [5/16] Loss: 0.01131 +Epoch [1117/4000] Training [6/16] Loss: 0.00907 +Epoch [1117/4000] Training [7/16] Loss: 0.00951 +Epoch [1117/4000] Training [8/16] Loss: 0.00864 +Epoch [1117/4000] Training [9/16] Loss: 0.01072 +Epoch [1117/4000] Training [10/16] Loss: 0.01315 +Epoch [1117/4000] Training [11/16] Loss: 0.01154 +Epoch [1117/4000] Training [12/16] Loss: 0.00817 +Epoch [1117/4000] Training [13/16] Loss: 0.00851 +Epoch [1117/4000] Training [14/16] Loss: 0.00910 +Epoch [1117/4000] Training [15/16] Loss: 0.01130 +Epoch [1117/4000] Training [16/16] Loss: 0.01410 +Epoch [1117/4000] Training metric {'Train/mean dice_metric': 0.9929094314575195, 'Train/mean miou_metric': 0.9856820702552795, 'Train/mean f1': 0.9891179203987122, 'Train/mean precision': 0.9844939112663269, 'Train/mean recall': 0.993785560131073, 'Train/mean hd95_metric': 1.1228046417236328} +Epoch [1117/4000] Validation [1/4] Loss: 0.23012 focal_loss 0.15859 dice_loss 0.07153 +Epoch [1117/4000] Validation [2/4] Loss: 0.20385 focal_loss 0.10232 dice_loss 0.10153 +Epoch [1117/4000] Validation [3/4] Loss: 0.27033 focal_loss 0.17576 dice_loss 0.09457 +Epoch [1117/4000] Validation [4/4] Loss: 0.22994 focal_loss 0.11365 dice_loss 0.11630 +Epoch [1117/4000] Validation metric {'Val/mean dice_metric': 0.9704439043998718, 'Val/mean miou_metric': 0.9516227841377258, 'Val/mean f1': 0.9720678329467773, 'Val/mean precision': 0.9672713279724121, 'Val/mean recall': 0.9769120216369629, 'Val/mean hd95_metric': 5.761634826660156} +Cheakpoint... +Epoch [1117/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704439043998718, 'Val/mean miou_metric': 0.9516227841377258, 'Val/mean f1': 0.9720678329467773, 'Val/mean precision': 0.9672713279724121, 'Val/mean recall': 0.9769120216369629, 'Val/mean hd95_metric': 5.761634826660156} +Epoch [1118/4000] Training [1/16] Loss: 0.01008 +Epoch [1118/4000] Training [2/16] Loss: 0.00994 +Epoch [1118/4000] Training [3/16] Loss: 0.01307 +Epoch [1118/4000] Training [4/16] Loss: 0.00965 +Epoch [1118/4000] Training [5/16] Loss: 0.01024 +Epoch [1118/4000] Training [6/16] Loss: 0.00767 +Epoch [1118/4000] Training [7/16] Loss: 0.01328 +Epoch [1118/4000] Training [8/16] Loss: 0.00775 +Epoch [1118/4000] Training [9/16] Loss: 0.01868 +Epoch [1118/4000] Training [10/16] Loss: 0.01071 +Epoch [1118/4000] Training [11/16] Loss: 0.01171 +Epoch [1118/4000] Training [12/16] Loss: 0.01306 +Epoch [1118/4000] Training [13/16] Loss: 0.01232 +Epoch [1118/4000] Training [14/16] Loss: 0.00964 +Epoch [1118/4000] Training [15/16] Loss: 0.01177 +Epoch [1118/4000] Training [16/16] Loss: 0.00986 +Epoch [1118/4000] Training metric {'Train/mean dice_metric': 0.9921178817749023, 'Train/mean miou_metric': 0.9841489791870117, 'Train/mean f1': 0.9889655709266663, 'Train/mean precision': 0.9844531416893005, 'Train/mean recall': 0.9935197830200195, 'Train/mean hd95_metric': 1.156652569770813} +Epoch [1118/4000] Validation [1/4] Loss: 0.23128 focal_loss 0.16165 dice_loss 0.06963 +Epoch [1118/4000] Validation [2/4] Loss: 0.31483 focal_loss 0.13088 dice_loss 0.18395 +Epoch [1118/4000] Validation [3/4] Loss: 0.18626 focal_loss 0.10148 dice_loss 0.08477 +Epoch [1118/4000] Validation [4/4] Loss: 0.30390 focal_loss 0.16972 dice_loss 0.13418 +Epoch [1118/4000] Validation metric {'Val/mean dice_metric': 0.9679101705551147, 'Val/mean miou_metric': 0.9485366940498352, 'Val/mean f1': 0.9719823598861694, 'Val/mean precision': 0.96846604347229, 'Val/mean recall': 0.9755242466926575, 'Val/mean hd95_metric': 6.2953009605407715} +Cheakpoint... +Epoch [1118/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679101705551147, 'Val/mean miou_metric': 0.9485366940498352, 'Val/mean f1': 0.9719823598861694, 'Val/mean precision': 0.96846604347229, 'Val/mean recall': 0.9755242466926575, 'Val/mean hd95_metric': 6.2953009605407715} +Epoch [1119/4000] Training [1/16] Loss: 0.00862 +Epoch [1119/4000] Training [2/16] Loss: 0.01271 +Epoch [1119/4000] Training [3/16] Loss: 0.01144 +Epoch [1119/4000] Training [4/16] Loss: 0.01112 +Epoch [1119/4000] Training [5/16] Loss: 0.00841 +Epoch [1119/4000] Training [6/16] Loss: 0.01022 +Epoch [1119/4000] Training [7/16] Loss: 0.00880 +Epoch [1119/4000] Training [8/16] Loss: 0.00996 +Epoch [1119/4000] Training [9/16] Loss: 0.01072 +Epoch [1119/4000] Training [10/16] Loss: 0.00973 +Epoch [1119/4000] Training [11/16] Loss: 0.00854 +Epoch [1119/4000] Training [12/16] Loss: 0.00804 +Epoch [1119/4000] Training [13/16] Loss: 0.01022 +Epoch [1119/4000] Training [14/16] Loss: 0.01324 +Epoch [1119/4000] Training [15/16] Loss: 0.01301 +Epoch [1119/4000] Training [16/16] Loss: 0.01051 +Epoch [1119/4000] Training metric {'Train/mean dice_metric': 0.9930669069290161, 'Train/mean miou_metric': 0.9859942197799683, 'Train/mean f1': 0.9895539283752441, 'Train/mean precision': 0.9851427674293518, 'Train/mean recall': 0.9940047860145569, 'Train/mean hd95_metric': 1.0809533596038818} +Epoch [1119/4000] Validation [1/4] Loss: 0.20330 focal_loss 0.14117 dice_loss 0.06214 +Epoch [1119/4000] Validation [2/4] Loss: 0.17968 focal_loss 0.08272 dice_loss 0.09697 +Epoch [1119/4000] Validation [3/4] Loss: 0.27631 focal_loss 0.17797 dice_loss 0.09833 +Epoch [1119/4000] Validation [4/4] Loss: 0.19755 focal_loss 0.08995 dice_loss 0.10760 +Epoch [1119/4000] Validation metric {'Val/mean dice_metric': 0.9690153002738953, 'Val/mean miou_metric': 0.9505521059036255, 'Val/mean f1': 0.972050666809082, 'Val/mean precision': 0.9672480225563049, 'Val/mean recall': 0.9769010543823242, 'Val/mean hd95_metric': 5.926822662353516} +Cheakpoint... +Epoch [1119/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690153002738953, 'Val/mean miou_metric': 0.9505521059036255, 'Val/mean f1': 0.972050666809082, 'Val/mean precision': 0.9672480225563049, 'Val/mean recall': 0.9769010543823242, 'Val/mean hd95_metric': 5.926822662353516} +Epoch [1120/4000] Training [1/16] Loss: 0.00850 +Epoch [1120/4000] Training [2/16] Loss: 0.01553 +Epoch [1120/4000] Training [3/16] Loss: 0.00869 +Epoch [1120/4000] Training [4/16] Loss: 0.00752 +Epoch [1120/4000] Training [5/16] Loss: 0.01235 +Epoch [1120/4000] Training [6/16] Loss: 0.01122 +Epoch [1120/4000] Training [7/16] Loss: 0.01046 +Epoch [1120/4000] Training [8/16] Loss: 0.00867 +Epoch [1120/4000] Training [9/16] Loss: 0.01025 +Epoch [1120/4000] Training [10/16] Loss: 0.01054 +Epoch [1120/4000] Training [11/16] Loss: 0.00927 +Epoch [1120/4000] Training [12/16] Loss: 0.01001 +Epoch [1120/4000] Training [13/16] Loss: 0.01133 +Epoch [1120/4000] Training [14/16] Loss: 0.01227 +Epoch [1120/4000] Training [15/16] Loss: 0.00809 +Epoch [1120/4000] Training [16/16] Loss: 0.00822 +Epoch [1120/4000] Training metric {'Train/mean dice_metric': 0.9927375912666321, 'Train/mean miou_metric': 0.9853552579879761, 'Train/mean f1': 0.9893044829368591, 'Train/mean precision': 0.9847886562347412, 'Train/mean recall': 0.9938619136810303, 'Train/mean hd95_metric': 1.097292184829712} +Epoch [1120/4000] Validation [1/4] Loss: 0.40169 focal_loss 0.26643 dice_loss 0.13526 +Epoch [1120/4000] Validation [2/4] Loss: 0.46698 focal_loss 0.24332 dice_loss 0.22366 +Epoch [1120/4000] Validation [3/4] Loss: 0.31778 focal_loss 0.21381 dice_loss 0.10397 +Epoch [1120/4000] Validation [4/4] Loss: 0.29527 focal_loss 0.15573 dice_loss 0.13955 +Epoch [1120/4000] Validation metric {'Val/mean dice_metric': 0.9664484858512878, 'Val/mean miou_metric': 0.9473876953125, 'Val/mean f1': 0.9710819125175476, 'Val/mean precision': 0.9663095474243164, 'Val/mean recall': 0.9759016036987305, 'Val/mean hd95_metric': 5.991528511047363} +Cheakpoint... +Epoch [1120/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664484858512878, 'Val/mean miou_metric': 0.9473876953125, 'Val/mean f1': 0.9710819125175476, 'Val/mean precision': 0.9663095474243164, 'Val/mean recall': 0.9759016036987305, 'Val/mean hd95_metric': 5.991528511047363} +Epoch [1121/4000] Training [1/16] Loss: 0.01397 +Epoch [1121/4000] Training [2/16] Loss: 0.00869 +Epoch [1121/4000] Training [3/16] Loss: 0.00810 +Epoch [1121/4000] Training [4/16] Loss: 0.01085 +Epoch [1121/4000] Training [5/16] Loss: 0.00962 +Epoch [1121/4000] Training [6/16] Loss: 0.01090 +Epoch [1121/4000] Training [7/16] Loss: 0.00899 +Epoch [1121/4000] Training [8/16] Loss: 0.01121 +Epoch [1121/4000] Training [9/16] Loss: 0.00923 +Epoch [1121/4000] Training [10/16] Loss: 0.00999 +Epoch [1121/4000] Training [11/16] Loss: 0.01312 +Epoch [1121/4000] Training [12/16] Loss: 0.00838 +Epoch [1121/4000] Training [13/16] Loss: 0.00937 +Epoch [1121/4000] Training [14/16] Loss: 0.01052 +Epoch [1121/4000] Training [15/16] Loss: 0.01776 +Epoch [1121/4000] Training [16/16] Loss: 0.01059 +Epoch [1121/4000] Training metric {'Train/mean dice_metric': 0.9929561018943787, 'Train/mean miou_metric': 0.985755443572998, 'Train/mean f1': 0.9893711805343628, 'Train/mean precision': 0.9847050905227661, 'Train/mean recall': 0.9940817952156067, 'Train/mean hd95_metric': 1.0951931476593018} +Epoch [1121/4000] Validation [1/4] Loss: 0.20930 focal_loss 0.13795 dice_loss 0.07134 +Epoch [1121/4000] Validation [2/4] Loss: 0.18395 focal_loss 0.08208 dice_loss 0.10186 +Epoch [1121/4000] Validation [3/4] Loss: 0.32903 focal_loss 0.20258 dice_loss 0.12645 +Epoch [1121/4000] Validation [4/4] Loss: 0.32799 focal_loss 0.16877 dice_loss 0.15922 +Epoch [1121/4000] Validation metric {'Val/mean dice_metric': 0.9685611724853516, 'Val/mean miou_metric': 0.9494332075119019, 'Val/mean f1': 0.9705612659454346, 'Val/mean precision': 0.9641357064247131, 'Val/mean recall': 0.9770729541778564, 'Val/mean hd95_metric': 6.1511406898498535} +Cheakpoint... +Epoch [1121/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9685611724853516, 'Val/mean miou_metric': 0.9494332075119019, 'Val/mean f1': 0.9705612659454346, 'Val/mean precision': 0.9641357064247131, 'Val/mean recall': 0.9770729541778564, 'Val/mean hd95_metric': 6.1511406898498535} +Epoch [1122/4000] Training [1/16] Loss: 0.00892 +Epoch [1122/4000] Training [2/16] Loss: 0.00925 +Epoch [1122/4000] Training [3/16] Loss: 0.00988 +Epoch [1122/4000] Training [4/16] Loss: 0.00990 +Epoch [1122/4000] Training [5/16] Loss: 0.01070 +Epoch [1122/4000] Training [6/16] Loss: 0.00748 +Epoch [1122/4000] Training [7/16] Loss: 0.01144 +Epoch [1122/4000] Training [8/16] Loss: 0.01010 +Epoch [1122/4000] Training [9/16] Loss: 0.01375 +Epoch [1122/4000] Training [10/16] Loss: 0.00845 +Epoch [1122/4000] Training [11/16] Loss: 0.01114 +Epoch [1122/4000] Training [12/16] Loss: 0.01100 +Epoch [1122/4000] Training [13/16] Loss: 0.01239 +Epoch [1122/4000] Training [14/16] Loss: 0.01025 +Epoch [1122/4000] Training [15/16] Loss: 0.00981 +Epoch [1122/4000] Training [16/16] Loss: 0.00859 +Epoch [1122/4000] Training metric {'Train/mean dice_metric': 0.9927210807800293, 'Train/mean miou_metric': 0.9853129386901855, 'Train/mean f1': 0.989158570766449, 'Train/mean precision': 0.9844313859939575, 'Train/mean recall': 0.9939313530921936, 'Train/mean hd95_metric': 1.0872957706451416} +Epoch [1122/4000] Validation [1/4] Loss: 0.18459 focal_loss 0.12452 dice_loss 0.06008 +Epoch [1122/4000] Validation [2/4] Loss: 0.20745 focal_loss 0.09707 dice_loss 0.11037 +Epoch [1122/4000] Validation [3/4] Loss: 0.25035 focal_loss 0.14973 dice_loss 0.10062 +Epoch [1122/4000] Validation [4/4] Loss: 0.28218 focal_loss 0.15686 dice_loss 0.12531 +Epoch [1122/4000] Validation metric {'Val/mean dice_metric': 0.9692561030387878, 'Val/mean miou_metric': 0.9501725435256958, 'Val/mean f1': 0.9722738265991211, 'Val/mean precision': 0.9674093127250671, 'Val/mean recall': 0.9771873354911804, 'Val/mean hd95_metric': 5.889157772064209} +Cheakpoint... +Epoch [1122/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692561030387878, 'Val/mean miou_metric': 0.9501725435256958, 'Val/mean f1': 0.9722738265991211, 'Val/mean precision': 0.9674093127250671, 'Val/mean recall': 0.9771873354911804, 'Val/mean hd95_metric': 5.889157772064209} +Epoch [1123/4000] Training [1/16] Loss: 0.01134 +Epoch [1123/4000] Training [2/16] Loss: 0.01086 +Epoch [1123/4000] Training [3/16] Loss: 0.00951 +Epoch [1123/4000] Training [4/16] Loss: 0.01060 +Epoch [1123/4000] Training [5/16] Loss: 0.01274 +Epoch [1123/4000] Training [6/16] Loss: 0.00911 +Epoch [1123/4000] Training [7/16] Loss: 0.01094 +Epoch [1123/4000] Training [8/16] Loss: 0.00914 +Epoch [1123/4000] Training [9/16] Loss: 0.01697 +Epoch [1123/4000] Training [10/16] Loss: 0.01224 +Epoch [1123/4000] Training [11/16] Loss: 0.00852 +Epoch [1123/4000] Training [12/16] Loss: 0.01139 +Epoch [1123/4000] Training [13/16] Loss: 0.01040 +Epoch [1123/4000] Training [14/16] Loss: 0.00962 +Epoch [1123/4000] Training [15/16] Loss: 0.00924 +Epoch [1123/4000] Training [16/16] Loss: 0.01217 +Epoch [1123/4000] Training metric {'Train/mean dice_metric': 0.9922723174095154, 'Train/mean miou_metric': 0.9844584465026855, 'Train/mean f1': 0.9890124797821045, 'Train/mean precision': 0.9844717383384705, 'Train/mean recall': 0.9935952425003052, 'Train/mean hd95_metric': 1.127596139907837} +Epoch [1123/4000] Validation [1/4] Loss: 0.19134 focal_loss 0.13156 dice_loss 0.05978 +Epoch [1123/4000] Validation [2/4] Loss: 0.38014 focal_loss 0.15745 dice_loss 0.22269 +Epoch [1123/4000] Validation [3/4] Loss: 0.16332 focal_loss 0.08905 dice_loss 0.07427 +Epoch [1123/4000] Validation [4/4] Loss: 0.26675 focal_loss 0.13395 dice_loss 0.13280 +Epoch [1123/4000] Validation metric {'Val/mean dice_metric': 0.9680236577987671, 'Val/mean miou_metric': 0.9490278363227844, 'Val/mean f1': 0.9730932712554932, 'Val/mean precision': 0.9702487587928772, 'Val/mean recall': 0.975954532623291, 'Val/mean hd95_metric': 5.752673149108887} +Cheakpoint... +Epoch [1123/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680236577987671, 'Val/mean miou_metric': 0.9490278363227844, 'Val/mean f1': 0.9730932712554932, 'Val/mean precision': 0.9702487587928772, 'Val/mean recall': 0.975954532623291, 'Val/mean hd95_metric': 5.752673149108887} +Epoch [1124/4000] Training [1/16] Loss: 0.01209 +Epoch [1124/4000] Training [2/16] Loss: 0.01103 +Epoch [1124/4000] Training [3/16] Loss: 0.00966 +Epoch [1124/4000] Training [4/16] Loss: 0.01054 +Epoch [1124/4000] Training [5/16] Loss: 0.00978 +Epoch [1124/4000] Training [6/16] Loss: 0.01014 +Epoch [1124/4000] Training [7/16] Loss: 0.01123 +Epoch [1124/4000] Training [8/16] Loss: 0.01188 +Epoch [1124/4000] Training [9/16] Loss: 0.01180 +Epoch [1124/4000] Training [10/16] Loss: 0.00835 +Epoch [1124/4000] Training [11/16] Loss: 0.00702 +Epoch [1124/4000] Training [12/16] Loss: 0.01125 +Epoch [1124/4000] Training [13/16] Loss: 0.00939 +Epoch [1124/4000] Training [14/16] Loss: 0.01323 +Epoch [1124/4000] Training [15/16] Loss: 0.00950 +Epoch [1124/4000] Training [16/16] Loss: 0.00804 +Epoch [1124/4000] Training metric {'Train/mean dice_metric': 0.9927157163619995, 'Train/mean miou_metric': 0.9853054881095886, 'Train/mean f1': 0.9890433549880981, 'Train/mean precision': 0.9842647314071655, 'Train/mean recall': 0.9938686490058899, 'Train/mean hd95_metric': 1.4398391246795654} +Epoch [1124/4000] Validation [1/4] Loss: 0.52820 focal_loss 0.37067 dice_loss 0.15753 +Epoch [1124/4000] Validation [2/4] Loss: 0.40079 focal_loss 0.21066 dice_loss 0.19014 +Epoch [1124/4000] Validation [3/4] Loss: 0.19213 focal_loss 0.10585 dice_loss 0.08628 +Epoch [1124/4000] Validation [4/4] Loss: 0.36950 focal_loss 0.22613 dice_loss 0.14337 +Epoch [1124/4000] Validation metric {'Val/mean dice_metric': 0.9647709727287292, 'Val/mean miou_metric': 0.945639967918396, 'Val/mean f1': 0.9671884179115295, 'Val/mean precision': 0.9733001589775085, 'Val/mean recall': 0.9611527919769287, 'Val/mean hd95_metric': 5.949497222900391} +Cheakpoint... +Epoch [1124/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647709727287292, 'Val/mean miou_metric': 0.945639967918396, 'Val/mean f1': 0.9671884179115295, 'Val/mean precision': 0.9733001589775085, 'Val/mean recall': 0.9611527919769287, 'Val/mean hd95_metric': 5.949497222900391} +Epoch [1125/4000] Training [1/16] Loss: 0.00735 +Epoch [1125/4000] Training [2/16] Loss: 0.00951 +Epoch [1125/4000] Training [3/16] Loss: 0.00893 +Epoch [1125/4000] Training [4/16] Loss: 0.00753 +Epoch [1125/4000] Training [5/16] Loss: 0.01123 +Epoch [1125/4000] Training [6/16] Loss: 0.00946 +Epoch [1125/4000] Training [7/16] Loss: 0.01144 +Epoch [1125/4000] Training [8/16] Loss: 0.01254 +Epoch [1125/4000] Training [9/16] Loss: 0.01370 +Epoch [1125/4000] Training [10/16] Loss: 0.00829 +Epoch [1125/4000] Training [11/16] Loss: 0.01037 +Epoch [1125/4000] Training [12/16] Loss: 0.01010 +Epoch [1125/4000] Training [13/16] Loss: 0.01087 +Epoch [1125/4000] Training [14/16] Loss: 0.01108 +Epoch [1125/4000] Training [15/16] Loss: 0.00916 +Epoch [1125/4000] Training [16/16] Loss: 0.01089 +Epoch [1125/4000] Training metric {'Train/mean dice_metric': 0.9929293990135193, 'Train/mean miou_metric': 0.9857245087623596, 'Train/mean f1': 0.9892138242721558, 'Train/mean precision': 0.9845333695411682, 'Train/mean recall': 0.9939389228820801, 'Train/mean hd95_metric': 1.14695143699646} +Epoch [1125/4000] Validation [1/4] Loss: 0.28785 focal_loss 0.20228 dice_loss 0.08557 +Epoch [1125/4000] Validation [2/4] Loss: 0.17110 focal_loss 0.07378 dice_loss 0.09732 +Epoch [1125/4000] Validation [3/4] Loss: 0.28263 focal_loss 0.18568 dice_loss 0.09695 +Epoch [1125/4000] Validation [4/4] Loss: 0.25704 focal_loss 0.14168 dice_loss 0.11536 +Epoch [1125/4000] Validation metric {'Val/mean dice_metric': 0.9700557589530945, 'Val/mean miou_metric': 0.9509862065315247, 'Val/mean f1': 0.9712385535240173, 'Val/mean precision': 0.9664978981018066, 'Val/mean recall': 0.9760259389877319, 'Val/mean hd95_metric': 6.962805271148682} +Cheakpoint... +Epoch [1125/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700557589530945, 'Val/mean miou_metric': 0.9509862065315247, 'Val/mean f1': 0.9712385535240173, 'Val/mean precision': 0.9664978981018066, 'Val/mean recall': 0.9760259389877319, 'Val/mean hd95_metric': 6.962805271148682} +Epoch [1126/4000] Training [1/16] Loss: 0.00932 +Epoch [1126/4000] Training [2/16] Loss: 0.01229 +Epoch [1126/4000] Training [3/16] Loss: 0.01051 +Epoch [1126/4000] Training [4/16] Loss: 0.00921 +Epoch [1126/4000] Training [5/16] Loss: 0.00908 +Epoch [1126/4000] Training [6/16] Loss: 0.01010 +Epoch [1126/4000] Training [7/16] Loss: 0.01143 +Epoch [1126/4000] Training [8/16] Loss: 0.00960 +Epoch [1126/4000] Training [9/16] Loss: 0.00988 +Epoch [1126/4000] Training [10/16] Loss: 0.01206 +Epoch [1126/4000] Training [11/16] Loss: 0.01048 +Epoch [1126/4000] Training [12/16] Loss: 0.01499 +Epoch [1126/4000] Training [13/16] Loss: 0.01055 +Epoch [1126/4000] Training [14/16] Loss: 0.01172 +Epoch [1126/4000] Training [15/16] Loss: 0.00981 +Epoch [1126/4000] Training [16/16] Loss: 0.01190 +Epoch [1126/4000] Training metric {'Train/mean dice_metric': 0.9925581216812134, 'Train/mean miou_metric': 0.9850080013275146, 'Train/mean f1': 0.9891529083251953, 'Train/mean precision': 0.9847024083137512, 'Train/mean recall': 0.9936438202857971, 'Train/mean hd95_metric': 1.2807453870773315} +Epoch [1126/4000] Validation [1/4] Loss: 0.23857 focal_loss 0.14898 dice_loss 0.08959 +Epoch [1126/4000] Validation [2/4] Loss: 0.20725 focal_loss 0.09334 dice_loss 0.11391 +Epoch [1126/4000] Validation [3/4] Loss: 0.13579 focal_loss 0.07543 dice_loss 0.06036 +Epoch [1126/4000] Validation [4/4] Loss: 0.23030 focal_loss 0.12424 dice_loss 0.10605 +Epoch [1126/4000] Validation metric {'Val/mean dice_metric': 0.9680767059326172, 'Val/mean miou_metric': 0.948957085609436, 'Val/mean f1': 0.9704023599624634, 'Val/mean precision': 0.9692875146865845, 'Val/mean recall': 0.9715197086334229, 'Val/mean hd95_metric': 5.503252983093262} +Cheakpoint... +Epoch [1126/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680767059326172, 'Val/mean miou_metric': 0.948957085609436, 'Val/mean f1': 0.9704023599624634, 'Val/mean precision': 0.9692875146865845, 'Val/mean recall': 0.9715197086334229, 'Val/mean hd95_metric': 5.503252983093262} +Epoch [1127/4000] Training [1/16] Loss: 0.01068 +Epoch [1127/4000] Training [2/16] Loss: 0.01774 +Epoch [1127/4000] Training [3/16] Loss: 0.00853 +Epoch [1127/4000] Training [4/16] Loss: 0.00914 +Epoch [1127/4000] Training [5/16] Loss: 0.00904 +Epoch [1127/4000] Training [6/16] Loss: 0.01343 +Epoch [1127/4000] Training [7/16] Loss: 0.01134 +Epoch [1127/4000] Training [8/16] Loss: 0.00849 +Epoch [1127/4000] Training [9/16] Loss: 0.00955 +Epoch [1127/4000] Training [10/16] Loss: 0.01106 +Epoch [1127/4000] Training [11/16] Loss: 0.01173 +Epoch [1127/4000] Training [12/16] Loss: 0.01438 +Epoch [1127/4000] Training [13/16] Loss: 0.00911 +Epoch [1127/4000] Training [14/16] Loss: 0.01496 +Epoch [1127/4000] Training [15/16] Loss: 0.00913 +Epoch [1127/4000] Training [16/16] Loss: 0.01406 +Epoch [1127/4000] Training metric {'Train/mean dice_metric': 0.992730975151062, 'Train/mean miou_metric': 0.9853173494338989, 'Train/mean f1': 0.9885224103927612, 'Train/mean precision': 0.9835264086723328, 'Train/mean recall': 0.9935693144798279, 'Train/mean hd95_metric': 1.1596615314483643} +Epoch [1127/4000] Validation [1/4] Loss: 0.16945 focal_loss 0.10932 dice_loss 0.06012 +Epoch [1127/4000] Validation [2/4] Loss: 0.29340 focal_loss 0.13160 dice_loss 0.16181 +Epoch [1127/4000] Validation [3/4] Loss: 0.15826 focal_loss 0.09553 dice_loss 0.06273 +Epoch [1127/4000] Validation [4/4] Loss: 0.22191 focal_loss 0.12773 dice_loss 0.09418 +Epoch [1127/4000] Validation metric {'Val/mean dice_metric': 0.9680964350700378, 'Val/mean miou_metric': 0.9494562149047852, 'Val/mean f1': 0.971773624420166, 'Val/mean precision': 0.9696765542030334, 'Val/mean recall': 0.9738795757293701, 'Val/mean hd95_metric': 5.316958904266357} +Cheakpoint... +Epoch [1127/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680964350700378, 'Val/mean miou_metric': 0.9494562149047852, 'Val/mean f1': 0.971773624420166, 'Val/mean precision': 0.9696765542030334, 'Val/mean recall': 0.9738795757293701, 'Val/mean hd95_metric': 5.316958904266357} +Epoch [1128/4000] Training [1/16] Loss: 0.00885 +Epoch [1128/4000] Training [2/16] Loss: 0.01318 +Epoch [1128/4000] Training [3/16] Loss: 0.00905 +Epoch [1128/4000] Training [4/16] Loss: 0.01147 +Epoch [1128/4000] Training [5/16] Loss: 0.01087 +Epoch [1128/4000] Training [6/16] Loss: 0.00814 +Epoch [1128/4000] Training [7/16] Loss: 0.00915 +Epoch [1128/4000] Training [8/16] Loss: 0.00898 +Epoch [1128/4000] Training [9/16] Loss: 0.00927 +Epoch [1128/4000] Training [10/16] Loss: 0.00823 +Epoch [1128/4000] Training [11/16] Loss: 0.01050 +Epoch [1128/4000] Training [12/16] Loss: 0.00759 +Epoch [1128/4000] Training [13/16] Loss: 0.00918 +Epoch [1128/4000] Training [14/16] Loss: 0.00945 +Epoch [1128/4000] Training [15/16] Loss: 0.01225 +Epoch [1128/4000] Training [16/16] Loss: 0.01093 +Epoch [1128/4000] Training metric {'Train/mean dice_metric': 0.9931120276451111, 'Train/mean miou_metric': 0.9861112833023071, 'Train/mean f1': 0.989546000957489, 'Train/mean precision': 0.9851260185241699, 'Train/mean recall': 0.9940058588981628, 'Train/mean hd95_metric': 1.1700215339660645} +Epoch [1128/4000] Validation [1/4] Loss: 0.23137 focal_loss 0.16513 dice_loss 0.06624 +Epoch [1128/4000] Validation [2/4] Loss: 0.27985 focal_loss 0.12819 dice_loss 0.15167 +Epoch [1128/4000] Validation [3/4] Loss: 0.34335 focal_loss 0.21455 dice_loss 0.12880 +Epoch [1128/4000] Validation [4/4] Loss: 0.32655 focal_loss 0.17289 dice_loss 0.15366 +Epoch [1128/4000] Validation metric {'Val/mean dice_metric': 0.9679899215698242, 'Val/mean miou_metric': 0.9487420916557312, 'Val/mean f1': 0.9700632095336914, 'Val/mean precision': 0.9609214663505554, 'Val/mean recall': 0.9793804883956909, 'Val/mean hd95_metric': 7.729671478271484} +Cheakpoint... +Epoch [1128/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679899215698242, 'Val/mean miou_metric': 0.9487420916557312, 'Val/mean f1': 0.9700632095336914, 'Val/mean precision': 0.9609214663505554, 'Val/mean recall': 0.9793804883956909, 'Val/mean hd95_metric': 7.729671478271484} +Epoch [1129/4000] Training [1/16] Loss: 0.01006 +Epoch [1129/4000] Training [2/16] Loss: 0.01084 +Epoch [1129/4000] Training [3/16] Loss: 0.00840 +Epoch [1129/4000] Training [4/16] Loss: 0.01816 +Epoch [1129/4000] Training [5/16] Loss: 0.01313 +Epoch [1129/4000] Training [6/16] Loss: 0.00909 +Epoch [1129/4000] Training [7/16] Loss: 0.00979 +Epoch [1129/4000] Training [8/16] Loss: 0.01173 +Epoch [1129/4000] Training [9/16] Loss: 0.00990 +Epoch [1129/4000] Training [10/16] Loss: 0.01124 +Epoch [1129/4000] Training [11/16] Loss: 0.01265 +Epoch [1129/4000] Training [12/16] Loss: 0.01623 +Epoch [1129/4000] Training [13/16] Loss: 0.01369 +Epoch [1129/4000] Training [14/16] Loss: 0.01186 +Epoch [1129/4000] Training [15/16] Loss: 0.01504 +Epoch [1129/4000] Training [16/16] Loss: 0.01020 +Epoch [1129/4000] Training metric {'Train/mean dice_metric': 0.9922590255737305, 'Train/mean miou_metric': 0.9844546318054199, 'Train/mean f1': 0.9888458847999573, 'Train/mean precision': 0.9843530058860779, 'Train/mean recall': 0.9933799505233765, 'Train/mean hd95_metric': 1.5681753158569336} +Epoch [1129/4000] Validation [1/4] Loss: 0.33371 focal_loss 0.21810 dice_loss 0.11561 +Epoch [1129/4000] Validation [2/4] Loss: 0.47338 focal_loss 0.28282 dice_loss 0.19056 +Epoch [1129/4000] Validation [3/4] Loss: 0.23697 focal_loss 0.14039 dice_loss 0.09658 +Epoch [1129/4000] Validation [4/4] Loss: 0.34260 focal_loss 0.19371 dice_loss 0.14889 +Epoch [1129/4000] Validation metric {'Val/mean dice_metric': 0.9679198265075684, 'Val/mean miou_metric': 0.9481277465820312, 'Val/mean f1': 0.970213770866394, 'Val/mean precision': 0.9650679230690002, 'Val/mean recall': 0.9754148721694946, 'Val/mean hd95_metric': 7.3459296226501465} +Cheakpoint... +Epoch [1129/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679198265075684, 'Val/mean miou_metric': 0.9481277465820312, 'Val/mean f1': 0.970213770866394, 'Val/mean precision': 0.9650679230690002, 'Val/mean recall': 0.9754148721694946, 'Val/mean hd95_metric': 7.3459296226501465} +Epoch [1130/4000] Training [1/16] Loss: 0.01183 +Epoch [1130/4000] Training [2/16] Loss: 0.01005 +Epoch [1130/4000] Training [3/16] Loss: 0.01495 +Epoch [1130/4000] Training [4/16] Loss: 0.00879 +Epoch [1130/4000] Training [5/16] Loss: 0.00914 +Epoch [1130/4000] Training [6/16] Loss: 0.01066 +Epoch [1130/4000] Training [7/16] Loss: 0.00969 +Epoch [1130/4000] Training [8/16] Loss: 0.00879 +Epoch [1130/4000] Training [9/16] Loss: 0.01030 +Epoch [1130/4000] Training [10/16] Loss: 0.00998 +Epoch [1130/4000] Training [11/16] Loss: 0.00879 +Epoch [1130/4000] Training [12/16] Loss: 0.01071 +Epoch [1130/4000] Training [13/16] Loss: 0.01192 +Epoch [1130/4000] Training [14/16] Loss: 0.01575 +Epoch [1130/4000] Training [15/16] Loss: 0.00901 +Epoch [1130/4000] Training [16/16] Loss: 0.00874 +Epoch [1130/4000] Training metric {'Train/mean dice_metric': 0.9925025105476379, 'Train/mean miou_metric': 0.9848877787590027, 'Train/mean f1': 0.9888872504234314, 'Train/mean precision': 0.9841267466545105, 'Train/mean recall': 0.993694007396698, 'Train/mean hd95_metric': 1.118169903755188} +Epoch [1130/4000] Validation [1/4] Loss: 0.23050 focal_loss 0.15916 dice_loss 0.07134 +Epoch [1130/4000] Validation [2/4] Loss: 0.34333 focal_loss 0.15830 dice_loss 0.18504 +Epoch [1130/4000] Validation [3/4] Loss: 0.30052 focal_loss 0.18619 dice_loss 0.11433 +Epoch [1130/4000] Validation [4/4] Loss: 0.28294 focal_loss 0.13461 dice_loss 0.14833 +Epoch [1130/4000] Validation metric {'Val/mean dice_metric': 0.9672473073005676, 'Val/mean miou_metric': 0.9479222297668457, 'Val/mean f1': 0.9700941443443298, 'Val/mean precision': 0.9654939770698547, 'Val/mean recall': 0.9747384786605835, 'Val/mean hd95_metric': 6.191868782043457} +Cheakpoint... +Epoch [1130/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672473073005676, 'Val/mean miou_metric': 0.9479222297668457, 'Val/mean f1': 0.9700941443443298, 'Val/mean precision': 0.9654939770698547, 'Val/mean recall': 0.9747384786605835, 'Val/mean hd95_metric': 6.191868782043457} +Epoch [1131/4000] Training [1/16] Loss: 0.00807 +Epoch [1131/4000] Training [2/16] Loss: 0.00908 +Epoch [1131/4000] Training [3/16] Loss: 0.00959 +Epoch [1131/4000] Training [4/16] Loss: 0.01940 +Epoch [1131/4000] Training [5/16] Loss: 0.01281 +Epoch [1131/4000] Training [6/16] Loss: 0.01114 +Epoch [1131/4000] Training [7/16] Loss: 0.00937 +Epoch [1131/4000] Training [8/16] Loss: 0.00923 +Epoch [1131/4000] Training [9/16] Loss: 0.00814 +Epoch [1131/4000] Training [10/16] Loss: 0.00925 +Epoch [1131/4000] Training [11/16] Loss: 0.01651 +Epoch [1131/4000] Training [12/16] Loss: 0.01235 +Epoch [1131/4000] Training [13/16] Loss: 0.01060 +Epoch [1131/4000] Training [14/16] Loss: 0.00904 +Epoch [1131/4000] Training [15/16] Loss: 0.01035 +Epoch [1131/4000] Training [16/16] Loss: 0.00839 +Epoch [1131/4000] Training metric {'Train/mean dice_metric': 0.9930192232131958, 'Train/mean miou_metric': 0.9859524965286255, 'Train/mean f1': 0.9896554350852966, 'Train/mean precision': 0.9851883053779602, 'Train/mean recall': 0.9941632151603699, 'Train/mean hd95_metric': 1.0798180103302002} +Epoch [1131/4000] Validation [1/4] Loss: 0.18922 focal_loss 0.13090 dice_loss 0.05832 +Epoch [1131/4000] Validation [2/4] Loss: 0.67120 focal_loss 0.39474 dice_loss 0.27646 +Epoch [1131/4000] Validation [3/4] Loss: 0.28179 focal_loss 0.18575 dice_loss 0.09604 +Epoch [1131/4000] Validation [4/4] Loss: 0.33982 focal_loss 0.18333 dice_loss 0.15649 +Epoch [1131/4000] Validation metric {'Val/mean dice_metric': 0.9661380052566528, 'Val/mean miou_metric': 0.9472898244857788, 'Val/mean f1': 0.970417857170105, 'Val/mean precision': 0.9644502997398376, 'Val/mean recall': 0.9764597415924072, 'Val/mean hd95_metric': 7.090137481689453} +Cheakpoint... +Epoch [1131/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661380052566528, 'Val/mean miou_metric': 0.9472898244857788, 'Val/mean f1': 0.970417857170105, 'Val/mean precision': 0.9644502997398376, 'Val/mean recall': 0.9764597415924072, 'Val/mean hd95_metric': 7.090137481689453} +Epoch [1132/4000] Training [1/16] Loss: 0.00847 +Epoch [1132/4000] Training [2/16] Loss: 0.00869 +Epoch [1132/4000] Training [3/16] Loss: 0.00950 +Epoch [1132/4000] Training [4/16] Loss: 0.01026 +Epoch [1132/4000] Training [5/16] Loss: 0.01070 +Epoch [1132/4000] Training [6/16] Loss: 0.00858 +Epoch [1132/4000] Training [7/16] Loss: 0.00831 +Epoch [1132/4000] Training [8/16] Loss: 0.00992 +Epoch [1132/4000] Training [9/16] Loss: 0.01001 +Epoch [1132/4000] Training [10/16] Loss: 0.00747 +Epoch [1132/4000] Training [11/16] Loss: 0.01172 +Epoch [1132/4000] Training [12/16] Loss: 0.01047 +Epoch [1132/4000] Training [13/16] Loss: 0.01309 +Epoch [1132/4000] Training [14/16] Loss: 0.01156 +Epoch [1132/4000] Training [15/16] Loss: 0.01040 +Epoch [1132/4000] Training [16/16] Loss: 0.00804 +Epoch [1132/4000] Training metric {'Train/mean dice_metric': 0.9929087162017822, 'Train/mean miou_metric': 0.9856628775596619, 'Train/mean f1': 0.9887473583221436, 'Train/mean precision': 0.9838195443153381, 'Train/mean recall': 0.9937247633934021, 'Train/mean hd95_metric': 1.1237781047821045} +Epoch [1132/4000] Validation [1/4] Loss: 0.21201 focal_loss 0.14307 dice_loss 0.06894 +Epoch [1132/4000] Validation [2/4] Loss: 0.46395 focal_loss 0.24510 dice_loss 0.21885 +Epoch [1132/4000] Validation [3/4] Loss: 0.27788 focal_loss 0.18652 dice_loss 0.09136 +Epoch [1132/4000] Validation [4/4] Loss: 0.23211 focal_loss 0.12059 dice_loss 0.11151 +Epoch [1132/4000] Validation metric {'Val/mean dice_metric': 0.9676876068115234, 'Val/mean miou_metric': 0.9491158723831177, 'Val/mean f1': 0.9701200127601624, 'Val/mean precision': 0.9627668261528015, 'Val/mean recall': 0.9775863289833069, 'Val/mean hd95_metric': 7.013474464416504} +Cheakpoint... +Epoch [1132/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676876068115234, 'Val/mean miou_metric': 0.9491158723831177, 'Val/mean f1': 0.9701200127601624, 'Val/mean precision': 0.9627668261528015, 'Val/mean recall': 0.9775863289833069, 'Val/mean hd95_metric': 7.013474464416504} +Epoch [1133/4000] Training [1/16] Loss: 0.01059 +Epoch [1133/4000] Training [2/16] Loss: 0.01262 +Epoch [1133/4000] Training [3/16] Loss: 0.01049 +Epoch [1133/4000] Training [4/16] Loss: 0.01061 +Epoch [1133/4000] Training [5/16] Loss: 0.00896 +Epoch [1133/4000] Training [6/16] Loss: 0.02131 +Epoch [1133/4000] Training [7/16] Loss: 0.00964 +Epoch [1133/4000] Training [8/16] Loss: 0.00992 +Epoch [1133/4000] Training [9/16] Loss: 0.00977 +Epoch [1133/4000] Training [10/16] Loss: 0.00875 +Epoch [1133/4000] Training [11/16] Loss: 0.00738 +Epoch [1133/4000] Training [12/16] Loss: 0.01086 +Epoch [1133/4000] Training [13/16] Loss: 0.01228 +Epoch [1133/4000] Training [14/16] Loss: 0.01021 +Epoch [1133/4000] Training [15/16] Loss: 0.01382 +Epoch [1133/4000] Training [16/16] Loss: 0.00922 +Epoch [1133/4000] Training metric {'Train/mean dice_metric': 0.9926968812942505, 'Train/mean miou_metric': 0.9852862358093262, 'Train/mean f1': 0.9891765117645264, 'Train/mean precision': 0.9846913814544678, 'Train/mean recall': 0.9937026500701904, 'Train/mean hd95_metric': 1.1634478569030762} +Epoch [1133/4000] Validation [1/4] Loss: 0.20971 focal_loss 0.14415 dice_loss 0.06556 +Epoch [1133/4000] Validation [2/4] Loss: 0.23512 focal_loss 0.11138 dice_loss 0.12373 +Epoch [1133/4000] Validation [3/4] Loss: 0.23448 focal_loss 0.14218 dice_loss 0.09230 +Epoch [1133/4000] Validation [4/4] Loss: 0.21964 focal_loss 0.10839 dice_loss 0.11125 +Epoch [1133/4000] Validation metric {'Val/mean dice_metric': 0.969260573387146, 'Val/mean miou_metric': 0.9501960873603821, 'Val/mean f1': 0.9704530239105225, 'Val/mean precision': 0.9651890397071838, 'Val/mean recall': 0.9757747650146484, 'Val/mean hd95_metric': 6.115331172943115} +Cheakpoint... +Epoch [1133/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969260573387146, 'Val/mean miou_metric': 0.9501960873603821, 'Val/mean f1': 0.9704530239105225, 'Val/mean precision': 0.9651890397071838, 'Val/mean recall': 0.9757747650146484, 'Val/mean hd95_metric': 6.115331172943115} +Epoch [1134/4000] Training [1/16] Loss: 0.01260 +Epoch [1134/4000] Training [2/16] Loss: 0.00890 +Epoch [1134/4000] Training [3/16] Loss: 0.01348 +Epoch [1134/4000] Training [4/16] Loss: 0.00975 +Epoch [1134/4000] Training [5/16] Loss: 0.01000 +Epoch [1134/4000] Training [6/16] Loss: 0.01295 +Epoch [1134/4000] Training [7/16] Loss: 0.00914 +Epoch [1134/4000] Training [8/16] Loss: 0.01436 +Epoch [1134/4000] Training [9/16] Loss: 0.00982 +Epoch [1134/4000] Training [10/16] Loss: 0.00940 +Epoch [1134/4000] Training [11/16] Loss: 0.01134 +Epoch [1134/4000] Training [12/16] Loss: 0.00877 +Epoch [1134/4000] Training [13/16] Loss: 0.00782 +Epoch [1134/4000] Training [14/16] Loss: 0.00903 +Epoch [1134/4000] Training [15/16] Loss: 0.00924 +Epoch [1134/4000] Training [16/16] Loss: 0.01274 +Epoch [1134/4000] Training metric {'Train/mean dice_metric': 0.9906641244888306, 'Train/mean miou_metric': 0.9831692576408386, 'Train/mean f1': 0.9888886213302612, 'Train/mean precision': 0.9843747615814209, 'Train/mean recall': 0.9934440851211548, 'Train/mean hd95_metric': 1.972926139831543} +Epoch [1134/4000] Validation [1/4] Loss: 0.36468 focal_loss 0.24667 dice_loss 0.11801 +Epoch [1134/4000] Validation [2/4] Loss: 0.19807 focal_loss 0.09420 dice_loss 0.10387 +Epoch [1134/4000] Validation [3/4] Loss: 0.24292 focal_loss 0.14665 dice_loss 0.09627 +Epoch [1134/4000] Validation [4/4] Loss: 0.22405 focal_loss 0.11227 dice_loss 0.11178 +Epoch [1134/4000] Validation metric {'Val/mean dice_metric': 0.966724693775177, 'Val/mean miou_metric': 0.9476014375686646, 'Val/mean f1': 0.9713965654373169, 'Val/mean precision': 0.9670093655586243, 'Val/mean recall': 0.9758238792419434, 'Val/mean hd95_metric': 6.5573954582214355} +Cheakpoint... +Epoch [1134/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966724693775177, 'Val/mean miou_metric': 0.9476014375686646, 'Val/mean f1': 0.9713965654373169, 'Val/mean precision': 0.9670093655586243, 'Val/mean recall': 0.9758238792419434, 'Val/mean hd95_metric': 6.5573954582214355} +Epoch [1135/4000] Training [1/16] Loss: 0.00925 +Epoch [1135/4000] Training [2/16] Loss: 0.00900 +Epoch [1135/4000] Training [3/16] Loss: 0.01024 +Epoch [1135/4000] Training [4/16] Loss: 0.01342 +Epoch [1135/4000] Training [5/16] Loss: 0.01068 +Epoch [1135/4000] Training [6/16] Loss: 0.00949 +Epoch [1135/4000] Training [7/16] Loss: 0.00757 +Epoch [1135/4000] Training [8/16] Loss: 0.01020 +Epoch [1135/4000] Training [9/16] Loss: 0.00773 +Epoch [1135/4000] Training [10/16] Loss: 0.01150 +Epoch [1135/4000] Training [11/16] Loss: 0.01035 +Epoch [1135/4000] Training [12/16] Loss: 0.01537 +Epoch [1135/4000] Training [13/16] Loss: 0.00917 +Epoch [1135/4000] Training [14/16] Loss: 0.01102 +Epoch [1135/4000] Training [15/16] Loss: 0.00808 +Epoch [1135/4000] Training [16/16] Loss: 0.00957 +Epoch [1135/4000] Training metric {'Train/mean dice_metric': 0.9930925965309143, 'Train/mean miou_metric': 0.9860266447067261, 'Train/mean f1': 0.988442063331604, 'Train/mean precision': 0.9829212427139282, 'Train/mean recall': 0.9940251708030701, 'Train/mean hd95_metric': 1.1918492317199707} +Epoch [1135/4000] Validation [1/4] Loss: 0.18318 focal_loss 0.11962 dice_loss 0.06356 +Epoch [1135/4000] Validation [2/4] Loss: 0.19794 focal_loss 0.07968 dice_loss 0.11826 +Epoch [1135/4000] Validation [3/4] Loss: 0.28577 focal_loss 0.18092 dice_loss 0.10485 +Epoch [1135/4000] Validation [4/4] Loss: 0.24338 focal_loss 0.12624 dice_loss 0.11714 +Epoch [1135/4000] Validation metric {'Val/mean dice_metric': 0.969916820526123, 'Val/mean miou_metric': 0.9510976672172546, 'Val/mean f1': 0.9716524481773376, 'Val/mean precision': 0.9651552438735962, 'Val/mean recall': 0.9782378077507019, 'Val/mean hd95_metric': 6.115033149719238} +Cheakpoint... +Epoch [1135/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969916820526123, 'Val/mean miou_metric': 0.9510976672172546, 'Val/mean f1': 0.9716524481773376, 'Val/mean precision': 0.9651552438735962, 'Val/mean recall': 0.9782378077507019, 'Val/mean hd95_metric': 6.115033149719238} +Epoch [1136/4000] Training [1/16] Loss: 0.01129 +Epoch [1136/4000] Training [2/16] Loss: 0.00930 +Epoch [1136/4000] Training [3/16] Loss: 0.00949 +Epoch [1136/4000] Training [4/16] Loss: 0.01194 +Epoch [1136/4000] Training [5/16] Loss: 0.01041 +Epoch [1136/4000] Training [6/16] Loss: 0.01620 +Epoch [1136/4000] Training [7/16] Loss: 0.01211 +Epoch [1136/4000] Training [8/16] Loss: 0.01149 +Epoch [1136/4000] Training [9/16] Loss: 0.01004 +Epoch [1136/4000] Training [10/16] Loss: 0.01209 +Epoch [1136/4000] Training [11/16] Loss: 0.01063 +Epoch [1136/4000] Training [12/16] Loss: 0.01112 +Epoch [1136/4000] Training [13/16] Loss: 0.01126 +Epoch [1136/4000] Training [14/16] Loss: 0.00956 +Epoch [1136/4000] Training [15/16] Loss: 0.01093 +Epoch [1136/4000] Training [16/16] Loss: 0.00889 +Epoch [1136/4000] Training metric {'Train/mean dice_metric': 0.9923027753829956, 'Train/mean miou_metric': 0.9845283627510071, 'Train/mean f1': 0.9883403182029724, 'Train/mean precision': 0.984235942363739, 'Train/mean recall': 0.9924790859222412, 'Train/mean hd95_metric': 1.3241740465164185} +Epoch [1136/4000] Validation [1/4] Loss: 0.22681 focal_loss 0.15850 dice_loss 0.06831 +Epoch [1136/4000] Validation [2/4] Loss: 0.22658 focal_loss 0.11161 dice_loss 0.11497 +Epoch [1136/4000] Validation [3/4] Loss: 0.12609 focal_loss 0.06683 dice_loss 0.05926 +Epoch [1136/4000] Validation [4/4] Loss: 0.26704 focal_loss 0.15035 dice_loss 0.11670 +Epoch [1136/4000] Validation metric {'Val/mean dice_metric': 0.9687623977661133, 'Val/mean miou_metric': 0.9493051767349243, 'Val/mean f1': 0.9694448709487915, 'Val/mean precision': 0.9632695913314819, 'Val/mean recall': 0.9756999611854553, 'Val/mean hd95_metric': 6.47915506362915} +Cheakpoint... +Epoch [1136/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687623977661133, 'Val/mean miou_metric': 0.9493051767349243, 'Val/mean f1': 0.9694448709487915, 'Val/mean precision': 0.9632695913314819, 'Val/mean recall': 0.9756999611854553, 'Val/mean hd95_metric': 6.47915506362915} +Epoch [1137/4000] Training [1/16] Loss: 0.00919 +Epoch [1137/4000] Training [2/16] Loss: 0.01136 +Epoch [1137/4000] Training [3/16] Loss: 0.00921 +Epoch [1137/4000] Training [4/16] Loss: 0.01148 +Epoch [1137/4000] Training [5/16] Loss: 0.01019 +Epoch [1137/4000] Training [6/16] Loss: 0.01186 +Epoch [1137/4000] Training [7/16] Loss: 0.01156 +Epoch [1137/4000] Training [8/16] Loss: 0.01006 +Epoch [1137/4000] Training [9/16] Loss: 0.00953 +Epoch [1137/4000] Training [10/16] Loss: 0.00912 +Epoch [1137/4000] Training [11/16] Loss: 0.00844 +Epoch [1137/4000] Training [12/16] Loss: 0.01009 +Epoch [1137/4000] Training [13/16] Loss: 0.00965 +Epoch [1137/4000] Training [14/16] Loss: 0.01945 +Epoch [1137/4000] Training [15/16] Loss: 0.00961 +Epoch [1137/4000] Training [16/16] Loss: 0.00821 +Epoch [1137/4000] Training metric {'Train/mean dice_metric': 0.991741955280304, 'Train/mean miou_metric': 0.9836615324020386, 'Train/mean f1': 0.987648606300354, 'Train/mean precision': 0.9819297194480896, 'Train/mean recall': 0.993434488773346, 'Train/mean hd95_metric': 2.237813949584961} +Epoch [1137/4000] Validation [1/4] Loss: 0.27678 focal_loss 0.19744 dice_loss 0.07933 +Epoch [1137/4000] Validation [2/4] Loss: 0.30755 focal_loss 0.17772 dice_loss 0.12983 +Epoch [1137/4000] Validation [3/4] Loss: 0.23303 focal_loss 0.13716 dice_loss 0.09587 +Epoch [1137/4000] Validation [4/4] Loss: 0.34758 focal_loss 0.22133 dice_loss 0.12625 +Epoch [1137/4000] Validation metric {'Val/mean dice_metric': 0.9683189392089844, 'Val/mean miou_metric': 0.9484174847602844, 'Val/mean f1': 0.9679811000823975, 'Val/mean precision': 0.9586020708084106, 'Val/mean recall': 0.9775453209877014, 'Val/mean hd95_metric': 6.784567356109619} +Cheakpoint... +Epoch [1137/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683189392089844, 'Val/mean miou_metric': 0.9484174847602844, 'Val/mean f1': 0.9679811000823975, 'Val/mean precision': 0.9586020708084106, 'Val/mean recall': 0.9775453209877014, 'Val/mean hd95_metric': 6.784567356109619} +Epoch [1138/4000] Training [1/16] Loss: 0.00903 +Epoch [1138/4000] Training [2/16] Loss: 0.01034 +Epoch [1138/4000] Training [3/16] Loss: 0.01041 +Epoch [1138/4000] Training [4/16] Loss: 0.00927 +Epoch [1138/4000] Training [5/16] Loss: 0.01233 +Epoch [1138/4000] Training [6/16] Loss: 0.01300 +Epoch [1138/4000] Training [7/16] Loss: 0.01350 +Epoch [1138/4000] Training [8/16] Loss: 0.01055 +Epoch [1138/4000] Training [9/16] Loss: 0.01046 +Epoch [1138/4000] Training [10/16] Loss: 0.02444 +Epoch [1138/4000] Training [11/16] Loss: 0.00952 +Epoch [1138/4000] Training [12/16] Loss: 0.01283 +Epoch [1138/4000] Training [13/16] Loss: 0.01241 +Epoch [1138/4000] Training [14/16] Loss: 0.00982 +Epoch [1138/4000] Training [15/16] Loss: 0.01246 +Epoch [1138/4000] Training [16/16] Loss: 0.01128 +Epoch [1138/4000] Training metric {'Train/mean dice_metric': 0.9918854236602783, 'Train/mean miou_metric': 0.9837360978126526, 'Train/mean f1': 0.9882611632347107, 'Train/mean precision': 0.9839824438095093, 'Train/mean recall': 0.992577314376831, 'Train/mean hd95_metric': 1.36061429977417} +Epoch [1138/4000] Validation [1/4] Loss: 0.27387 focal_loss 0.19037 dice_loss 0.08349 +Epoch [1138/4000] Validation [2/4] Loss: 0.50575 focal_loss 0.33552 dice_loss 0.17023 +Epoch [1138/4000] Validation [3/4] Loss: 0.20841 focal_loss 0.11608 dice_loss 0.09232 +Epoch [1138/4000] Validation [4/4] Loss: 0.27190 focal_loss 0.15197 dice_loss 0.11994 +Epoch [1138/4000] Validation metric {'Val/mean dice_metric': 0.965131938457489, 'Val/mean miou_metric': 0.9452250599861145, 'Val/mean f1': 0.9664196372032166, 'Val/mean precision': 0.9611235857009888, 'Val/mean recall': 0.9717743396759033, 'Val/mean hd95_metric': 6.764203071594238} +Cheakpoint... +Epoch [1138/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965131938457489, 'Val/mean miou_metric': 0.9452250599861145, 'Val/mean f1': 0.9664196372032166, 'Val/mean precision': 0.9611235857009888, 'Val/mean recall': 0.9717743396759033, 'Val/mean hd95_metric': 6.764203071594238} +Epoch [1139/4000] Training [1/16] Loss: 0.01376 +Epoch [1139/4000] Training [2/16] Loss: 0.01205 +Epoch [1139/4000] Training [3/16] Loss: 0.01154 +Epoch [1139/4000] Training [4/16] Loss: 0.01410 +Epoch [1139/4000] Training [5/16] Loss: 0.01110 +Epoch [1139/4000] Training [6/16] Loss: 0.00911 +Epoch [1139/4000] Training [7/16] Loss: 0.00968 +Epoch [1139/4000] Training [8/16] Loss: 0.01031 +Epoch [1139/4000] Training [9/16] Loss: 0.01018 +Epoch [1139/4000] Training [10/16] Loss: 0.01621 +Epoch [1139/4000] Training [11/16] Loss: 0.01322 +Epoch [1139/4000] Training [12/16] Loss: 0.00841 +Epoch [1139/4000] Training [13/16] Loss: 0.01169 +Epoch [1139/4000] Training [14/16] Loss: 0.01154 +Epoch [1139/4000] Training [15/16] Loss: 0.00919 +Epoch [1139/4000] Training [16/16] Loss: 0.00983 +Epoch [1139/4000] Training metric {'Train/mean dice_metric': 0.9925094842910767, 'Train/mean miou_metric': 0.9849241971969604, 'Train/mean f1': 0.9883750677108765, 'Train/mean precision': 0.9841020703315735, 'Train/mean recall': 0.9926853775978088, 'Train/mean hd95_metric': 1.5086606740951538} +Epoch [1139/4000] Validation [1/4] Loss: 0.15986 focal_loss 0.10019 dice_loss 0.05966 +Epoch [1139/4000] Validation [2/4] Loss: 0.17491 focal_loss 0.07602 dice_loss 0.09889 +Epoch [1139/4000] Validation [3/4] Loss: 0.15732 focal_loss 0.08085 dice_loss 0.07647 +Epoch [1139/4000] Validation [4/4] Loss: 0.25737 focal_loss 0.14151 dice_loss 0.11586 +Epoch [1139/4000] Validation metric {'Val/mean dice_metric': 0.9685875773429871, 'Val/mean miou_metric': 0.9487244486808777, 'Val/mean f1': 0.9688994884490967, 'Val/mean precision': 0.9613819122314453, 'Val/mean recall': 0.9765355587005615, 'Val/mean hd95_metric': 6.643852233886719} +Cheakpoint... +Epoch [1139/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9685875773429871, 'Val/mean miou_metric': 0.9487244486808777, 'Val/mean f1': 0.9688994884490967, 'Val/mean precision': 0.9613819122314453, 'Val/mean recall': 0.9765355587005615, 'Val/mean hd95_metric': 6.643852233886719} +Epoch [1140/4000] Training [1/16] Loss: 0.01359 +Epoch [1140/4000] Training [2/16] Loss: 0.00985 +Epoch [1140/4000] Training [3/16] Loss: 0.01270 +Epoch [1140/4000] Training [4/16] Loss: 0.01529 +Epoch [1140/4000] Training [5/16] Loss: 0.00955 +Epoch [1140/4000] Training [6/16] Loss: 0.01728 +Epoch [1140/4000] Training [7/16] Loss: 0.01024 +Epoch [1140/4000] Training [8/16] Loss: 0.00843 +Epoch [1140/4000] Training [9/16] Loss: 0.01239 +Epoch [1140/4000] Training [10/16] Loss: 0.01082 +Epoch [1140/4000] Training [11/16] Loss: 0.01111 +Epoch [1140/4000] Training [12/16] Loss: 0.00849 +Epoch [1140/4000] Training [13/16] Loss: 0.01229 +Epoch [1140/4000] Training [14/16] Loss: 0.00829 +Epoch [1140/4000] Training [15/16] Loss: 0.01124 +Epoch [1140/4000] Training [16/16] Loss: 0.00968 +Epoch [1140/4000] Training metric {'Train/mean dice_metric': 0.9918169975280762, 'Train/mean miou_metric': 0.983920693397522, 'Train/mean f1': 0.9877883791923523, 'Train/mean precision': 0.982620358467102, 'Train/mean recall': 0.9930110573768616, 'Train/mean hd95_metric': 1.39479398727417} +Epoch [1140/4000] Validation [1/4] Loss: 0.24653 focal_loss 0.17318 dice_loss 0.07335 +Epoch [1140/4000] Validation [2/4] Loss: 0.42162 focal_loss 0.24235 dice_loss 0.17927 +Epoch [1140/4000] Validation [3/4] Loss: 0.17763 focal_loss 0.09506 dice_loss 0.08258 +Epoch [1140/4000] Validation [4/4] Loss: 0.21120 focal_loss 0.11746 dice_loss 0.09374 +Epoch [1140/4000] Validation metric {'Val/mean dice_metric': 0.9694749712944031, 'Val/mean miou_metric': 0.9498815536499023, 'Val/mean f1': 0.970649003982544, 'Val/mean precision': 0.9657320380210876, 'Val/mean recall': 0.9756163358688354, 'Val/mean hd95_metric': 5.631829261779785} +Cheakpoint... +Epoch [1140/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694749712944031, 'Val/mean miou_metric': 0.9498815536499023, 'Val/mean f1': 0.970649003982544, 'Val/mean precision': 0.9657320380210876, 'Val/mean recall': 0.9756163358688354, 'Val/mean hd95_metric': 5.631829261779785} +Epoch [1141/4000] Training [1/16] Loss: 0.00967 +Epoch [1141/4000] Training [2/16] Loss: 0.01456 +Epoch [1141/4000] Training [3/16] Loss: 0.01077 +Epoch [1141/4000] Training [4/16] Loss: 0.01106 +Epoch [1141/4000] Training [5/16] Loss: 0.01075 +Epoch [1141/4000] Training [6/16] Loss: 0.01121 +Epoch [1141/4000] Training [7/16] Loss: 0.01035 +Epoch [1141/4000] Training [8/16] Loss: 0.00896 +Epoch [1141/4000] Training [9/16] Loss: 0.00844 +Epoch [1141/4000] Training [10/16] Loss: 0.00742 +Epoch [1141/4000] Training [11/16] Loss: 0.01211 +Epoch [1141/4000] Training [12/16] Loss: 0.01037 +Epoch [1141/4000] Training [13/16] Loss: 0.00987 +Epoch [1141/4000] Training [14/16] Loss: 0.01003 +Epoch [1141/4000] Training [15/16] Loss: 0.00998 +Epoch [1141/4000] Training [16/16] Loss: 0.01191 +Epoch [1141/4000] Training metric {'Train/mean dice_metric': 0.9927451610565186, 'Train/mean miou_metric': 0.985365629196167, 'Train/mean f1': 0.9890994429588318, 'Train/mean precision': 0.9844915270805359, 'Train/mean recall': 0.9937506914138794, 'Train/mean hd95_metric': 1.1462041139602661} +Epoch [1141/4000] Validation [1/4] Loss: 0.17349 focal_loss 0.11430 dice_loss 0.05920 +Epoch [1141/4000] Validation [2/4] Loss: 0.29421 focal_loss 0.15422 dice_loss 0.13999 +Epoch [1141/4000] Validation [3/4] Loss: 0.14008 focal_loss 0.07209 dice_loss 0.06799 +Epoch [1141/4000] Validation [4/4] Loss: 0.21610 focal_loss 0.12430 dice_loss 0.09180 +Epoch [1141/4000] Validation metric {'Val/mean dice_metric': 0.9713514447212219, 'Val/mean miou_metric': 0.9523555636405945, 'Val/mean f1': 0.9729065299034119, 'Val/mean precision': 0.9680973291397095, 'Val/mean recall': 0.9777637124061584, 'Val/mean hd95_metric': 5.60727071762085} +Cheakpoint... +Epoch [1141/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713514447212219, 'Val/mean miou_metric': 0.9523555636405945, 'Val/mean f1': 0.9729065299034119, 'Val/mean precision': 0.9680973291397095, 'Val/mean recall': 0.9777637124061584, 'Val/mean hd95_metric': 5.60727071762085} +Epoch [1142/4000] Training [1/16] Loss: 0.01041 +Epoch [1142/4000] Training [2/16] Loss: 0.01356 +Epoch [1142/4000] Training [3/16] Loss: 0.00733 +Epoch [1142/4000] Training [4/16] Loss: 0.01090 +Epoch [1142/4000] Training [5/16] Loss: 0.00622 +Epoch [1142/4000] Training [6/16] Loss: 0.01391 +Epoch [1142/4000] Training [7/16] Loss: 0.00935 +Epoch [1142/4000] Training [8/16] Loss: 0.00843 +Epoch [1142/4000] Training [9/16] Loss: 0.01235 +Epoch [1142/4000] Training [10/16] Loss: 0.00834 +Epoch [1142/4000] Training [11/16] Loss: 0.00862 +Epoch [1142/4000] Training [12/16] Loss: 0.01066 +Epoch [1142/4000] Training [13/16] Loss: 0.00929 +Epoch [1142/4000] Training [14/16] Loss: 0.01046 +Epoch [1142/4000] Training [15/16] Loss: 0.01298 +Epoch [1142/4000] Training [16/16] Loss: 0.01231 +Epoch [1142/4000] Training metric {'Train/mean dice_metric': 0.993137001991272, 'Train/mean miou_metric': 0.9861412048339844, 'Train/mean f1': 0.9894702434539795, 'Train/mean precision': 0.9848893880844116, 'Train/mean recall': 0.9940938949584961, 'Train/mean hd95_metric': 1.0898274183273315} +Epoch [1142/4000] Validation [1/4] Loss: 0.20735 focal_loss 0.14615 dice_loss 0.06121 +Epoch [1142/4000] Validation [2/4] Loss: 0.46597 focal_loss 0.28722 dice_loss 0.17874 +Epoch [1142/4000] Validation [3/4] Loss: 0.16689 focal_loss 0.09139 dice_loss 0.07550 +Epoch [1142/4000] Validation [4/4] Loss: 0.21206 focal_loss 0.10063 dice_loss 0.11144 +Epoch [1142/4000] Validation metric {'Val/mean dice_metric': 0.9697955846786499, 'Val/mean miou_metric': 0.9512466192245483, 'Val/mean f1': 0.9723106026649475, 'Val/mean precision': 0.9667142629623413, 'Val/mean recall': 0.9779720902442932, 'Val/mean hd95_metric': 5.782273292541504} +Cheakpoint... +Epoch [1142/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697955846786499, 'Val/mean miou_metric': 0.9512466192245483, 'Val/mean f1': 0.9723106026649475, 'Val/mean precision': 0.9667142629623413, 'Val/mean recall': 0.9779720902442932, 'Val/mean hd95_metric': 5.782273292541504} +Epoch [1143/4000] Training [1/16] Loss: 0.00831 +Epoch [1143/4000] Training [2/16] Loss: 0.00870 +Epoch [1143/4000] Training [3/16] Loss: 0.01128 +Epoch [1143/4000] Training [4/16] Loss: 0.00784 +Epoch [1143/4000] Training [5/16] Loss: 0.00876 +Epoch [1143/4000] Training [6/16] Loss: 0.01371 +Epoch [1143/4000] Training [7/16] Loss: 0.00949 +Epoch [1143/4000] Training [8/16] Loss: 0.00714 +Epoch [1143/4000] Training [9/16] Loss: 0.01092 +Epoch [1143/4000] Training [10/16] Loss: 0.01095 +Epoch [1143/4000] Training [11/16] Loss: 0.02927 +Epoch [1143/4000] Training [12/16] Loss: 0.00787 +Epoch [1143/4000] Training [13/16] Loss: 0.00948 +Epoch [1143/4000] Training [14/16] Loss: 0.01061 +Epoch [1143/4000] Training [15/16] Loss: 0.01111 +Epoch [1143/4000] Training [16/16] Loss: 0.00941 +Epoch [1143/4000] Training metric {'Train/mean dice_metric': 0.99277263879776, 'Train/mean miou_metric': 0.985457181930542, 'Train/mean f1': 0.9892796277999878, 'Train/mean precision': 0.9846435785293579, 'Train/mean recall': 0.9939594268798828, 'Train/mean hd95_metric': 1.1665990352630615} +Epoch [1143/4000] Validation [1/4] Loss: 0.19657 focal_loss 0.13210 dice_loss 0.06447 +Epoch [1143/4000] Validation [2/4] Loss: 0.30057 focal_loss 0.17236 dice_loss 0.12820 +Epoch [1143/4000] Validation [3/4] Loss: 0.10860 focal_loss 0.05246 dice_loss 0.05614 +Epoch [1143/4000] Validation [4/4] Loss: 0.19461 focal_loss 0.08674 dice_loss 0.10787 +Epoch [1143/4000] Validation metric {'Val/mean dice_metric': 0.9708922505378723, 'Val/mean miou_metric': 0.9519820213317871, 'Val/mean f1': 0.9734225869178772, 'Val/mean precision': 0.9698991179466248, 'Val/mean recall': 0.9769717454910278, 'Val/mean hd95_metric': 5.472964763641357} +Cheakpoint... +Epoch [1143/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708922505378723, 'Val/mean miou_metric': 0.9519820213317871, 'Val/mean f1': 0.9734225869178772, 'Val/mean precision': 0.9698991179466248, 'Val/mean recall': 0.9769717454910278, 'Val/mean hd95_metric': 5.472964763641357} +Epoch [1144/4000] Training [1/16] Loss: 0.00930 +Epoch [1144/4000] Training [2/16] Loss: 0.01151 +Epoch [1144/4000] Training [3/16] Loss: 0.01035 +Epoch [1144/4000] Training [4/16] Loss: 0.00815 +Epoch [1144/4000] Training [5/16] Loss: 0.00846 +Epoch [1144/4000] Training [6/16] Loss: 0.00929 +Epoch [1144/4000] Training [7/16] Loss: 0.01189 +Epoch [1144/4000] Training [8/16] Loss: 0.01039 +Epoch [1144/4000] Training [9/16] Loss: 0.00911 +Epoch [1144/4000] Training [10/16] Loss: 0.00778 +Epoch [1144/4000] Training [11/16] Loss: 0.01078 +Epoch [1144/4000] Training [12/16] Loss: 0.01103 +Epoch [1144/4000] Training [13/16] Loss: 0.01165 +Epoch [1144/4000] Training [14/16] Loss: 0.01003 +Epoch [1144/4000] Training [15/16] Loss: 0.00830 +Epoch [1144/4000] Training [16/16] Loss: 0.01673 +Epoch [1144/4000] Training metric {'Train/mean dice_metric': 0.9928300380706787, 'Train/mean miou_metric': 0.9855906367301941, 'Train/mean f1': 0.9887524247169495, 'Train/mean precision': 0.9837141633033752, 'Train/mean recall': 0.993842601776123, 'Train/mean hd95_metric': 1.1532925367355347} +Epoch [1144/4000] Validation [1/4] Loss: 0.22961 focal_loss 0.16197 dice_loss 0.06763 +Epoch [1144/4000] Validation [2/4] Loss: 0.47472 focal_loss 0.27361 dice_loss 0.20111 +Epoch [1144/4000] Validation [3/4] Loss: 0.17831 focal_loss 0.09870 dice_loss 0.07960 +Epoch [1144/4000] Validation [4/4] Loss: 0.29486 focal_loss 0.16232 dice_loss 0.13253 +Epoch [1144/4000] Validation metric {'Val/mean dice_metric': 0.9677522778511047, 'Val/mean miou_metric': 0.9493692517280579, 'Val/mean f1': 0.9716029763221741, 'Val/mean precision': 0.96867835521698, 'Val/mean recall': 0.9745453000068665, 'Val/mean hd95_metric': 5.605954170227051} +Cheakpoint... +Epoch [1144/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677522778511047, 'Val/mean miou_metric': 0.9493692517280579, 'Val/mean f1': 0.9716029763221741, 'Val/mean precision': 0.96867835521698, 'Val/mean recall': 0.9745453000068665, 'Val/mean hd95_metric': 5.605954170227051} +Epoch [1145/4000] Training [1/16] Loss: 0.01254 +Epoch [1145/4000] Training [2/16] Loss: 0.00857 +Epoch [1145/4000] Training [3/16] Loss: 0.01484 +Epoch [1145/4000] Training [4/16] Loss: 0.00859 +Epoch [1145/4000] Training [5/16] Loss: 0.01224 +Epoch [1145/4000] Training [6/16] Loss: 0.01099 +Epoch [1145/4000] Training [7/16] Loss: 0.01664 +Epoch [1145/4000] Training [8/16] Loss: 0.01417 +Epoch [1145/4000] Training [9/16] Loss: 0.01120 +Epoch [1145/4000] Training [10/16] Loss: 0.00973 +Epoch [1145/4000] Training [11/16] Loss: 0.00870 +Epoch [1145/4000] Training [12/16] Loss: 0.01108 +Epoch [1145/4000] Training [13/16] Loss: 0.01062 +Epoch [1145/4000] Training [14/16] Loss: 0.01001 +Epoch [1145/4000] Training [15/16] Loss: 0.01107 +Epoch [1145/4000] Training [16/16] Loss: 0.01080 +Epoch [1145/4000] Training metric {'Train/mean dice_metric': 0.992439866065979, 'Train/mean miou_metric': 0.9847673177719116, 'Train/mean f1': 0.9889430403709412, 'Train/mean precision': 0.9844150543212891, 'Train/mean recall': 0.9935128688812256, 'Train/mean hd95_metric': 1.3474221229553223} +Epoch [1145/4000] Validation [1/4] Loss: 0.19376 focal_loss 0.12904 dice_loss 0.06472 +Epoch [1145/4000] Validation [2/4] Loss: 0.24223 focal_loss 0.12268 dice_loss 0.11955 +Epoch [1145/4000] Validation [3/4] Loss: 0.15405 focal_loss 0.08312 dice_loss 0.07092 +Epoch [1145/4000] Validation [4/4] Loss: 0.45310 focal_loss 0.29463 dice_loss 0.15847 +Epoch [1145/4000] Validation metric {'Val/mean dice_metric': 0.9700822830200195, 'Val/mean miou_metric': 0.9502111673355103, 'Val/mean f1': 0.9711344838142395, 'Val/mean precision': 0.9676983952522278, 'Val/mean recall': 0.9745950698852539, 'Val/mean hd95_metric': 6.09347677230835} +Cheakpoint... +Epoch [1145/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700822830200195, 'Val/mean miou_metric': 0.9502111673355103, 'Val/mean f1': 0.9711344838142395, 'Val/mean precision': 0.9676983952522278, 'Val/mean recall': 0.9745950698852539, 'Val/mean hd95_metric': 6.09347677230835} +Epoch [1146/4000] Training [1/16] Loss: 0.00708 +Epoch [1146/4000] Training [2/16] Loss: 0.00892 +Epoch [1146/4000] Training [3/16] Loss: 0.01021 +Epoch [1146/4000] Training [4/16] Loss: 0.01213 +Epoch [1146/4000] Training [5/16] Loss: 0.00909 +Epoch [1146/4000] Training [6/16] Loss: 0.00835 +Epoch [1146/4000] Training [7/16] Loss: 0.01047 +Epoch [1146/4000] Training [8/16] Loss: 0.01261 +Epoch [1146/4000] Training [9/16] Loss: 0.00925 +Epoch [1146/4000] Training [10/16] Loss: 0.00918 +Epoch [1146/4000] Training [11/16] Loss: 0.00916 +Epoch [1146/4000] Training [12/16] Loss: 0.00890 +Epoch [1146/4000] Training [13/16] Loss: 0.01025 +Epoch [1146/4000] Training [14/16] Loss: 0.01113 +Epoch [1146/4000] Training [15/16] Loss: 0.01260 +Epoch [1146/4000] Training [16/16] Loss: 0.01036 +Epoch [1146/4000] Training metric {'Train/mean dice_metric': 0.993208646774292, 'Train/mean miou_metric': 0.9862658977508545, 'Train/mean f1': 0.9894564747810364, 'Train/mean precision': 0.9849231243133545, 'Train/mean recall': 0.9940317869186401, 'Train/mean hd95_metric': 1.1096909046173096} +Epoch [1146/4000] Validation [1/4] Loss: 0.21837 focal_loss 0.14881 dice_loss 0.06955 +Epoch [1146/4000] Validation [2/4] Loss: 0.42284 focal_loss 0.23380 dice_loss 0.18904 +Epoch [1146/4000] Validation [3/4] Loss: 0.12399 focal_loss 0.06748 dice_loss 0.05651 +Epoch [1146/4000] Validation [4/4] Loss: 0.34624 focal_loss 0.19670 dice_loss 0.14954 +Epoch [1146/4000] Validation metric {'Val/mean dice_metric': 0.9692570567131042, 'Val/mean miou_metric': 0.9509226083755493, 'Val/mean f1': 0.9724375009536743, 'Val/mean precision': 0.970040500164032, 'Val/mean recall': 0.9748462438583374, 'Val/mean hd95_metric': 5.320070266723633} +Cheakpoint... +Epoch [1146/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692570567131042, 'Val/mean miou_metric': 0.9509226083755493, 'Val/mean f1': 0.9724375009536743, 'Val/mean precision': 0.970040500164032, 'Val/mean recall': 0.9748462438583374, 'Val/mean hd95_metric': 5.320070266723633} +Epoch [1147/4000] Training [1/16] Loss: 0.00785 +Epoch [1147/4000] Training [2/16] Loss: 0.01020 +Epoch [1147/4000] Training [3/16] Loss: 0.00896 +Epoch [1147/4000] Training [4/16] Loss: 0.00918 +Epoch [1147/4000] Training [5/16] Loss: 0.01258 +Epoch [1147/4000] Training [6/16] Loss: 0.01120 +Epoch [1147/4000] Training [7/16] Loss: 0.01091 +Epoch [1147/4000] Training [8/16] Loss: 0.00796 +Epoch [1147/4000] Training [9/16] Loss: 0.01171 +Epoch [1147/4000] Training [10/16] Loss: 0.00898 +Epoch [1147/4000] Training [11/16] Loss: 0.01121 +Epoch [1147/4000] Training [12/16] Loss: 0.00885 +Epoch [1147/4000] Training [13/16] Loss: 0.00819 +Epoch [1147/4000] Training [14/16] Loss: 0.01171 +Epoch [1147/4000] Training [15/16] Loss: 0.00819 +Epoch [1147/4000] Training [16/16] Loss: 0.01299 +Epoch [1147/4000] Training metric {'Train/mean dice_metric': 0.9931380748748779, 'Train/mean miou_metric': 0.9861387610435486, 'Train/mean f1': 0.9896238446235657, 'Train/mean precision': 0.984992504119873, 'Train/mean recall': 0.9942988753318787, 'Train/mean hd95_metric': 1.084587574005127} +Epoch [1147/4000] Validation [1/4] Loss: 0.23916 focal_loss 0.16435 dice_loss 0.07482 +Epoch [1147/4000] Validation [2/4] Loss: 0.33944 focal_loss 0.19041 dice_loss 0.14903 +Epoch [1147/4000] Validation [3/4] Loss: 0.13418 focal_loss 0.07484 dice_loss 0.05934 +Epoch [1147/4000] Validation [4/4] Loss: 0.20359 focal_loss 0.09897 dice_loss 0.10462 +Epoch [1147/4000] Validation metric {'Val/mean dice_metric': 0.9706951379776001, 'Val/mean miou_metric': 0.9516505002975464, 'Val/mean f1': 0.9724523425102234, 'Val/mean precision': 0.9681074023246765, 'Val/mean recall': 0.9768364429473877, 'Val/mean hd95_metric': 5.745162010192871} +Cheakpoint... +Epoch [1147/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706951379776001, 'Val/mean miou_metric': 0.9516505002975464, 'Val/mean f1': 0.9724523425102234, 'Val/mean precision': 0.9681074023246765, 'Val/mean recall': 0.9768364429473877, 'Val/mean hd95_metric': 5.745162010192871} +Epoch [1148/4000] Training [1/16] Loss: 0.01393 +Epoch [1148/4000] Training [2/16] Loss: 0.00680 +Epoch [1148/4000] Training [3/16] Loss: 0.01138 +Epoch [1148/4000] Training [4/16] Loss: 0.00620 +Epoch [1148/4000] Training [5/16] Loss: 0.00894 +Epoch [1148/4000] Training [6/16] Loss: 0.01118 +Epoch [1148/4000] Training [7/16] Loss: 0.00992 +Epoch [1148/4000] Training [8/16] Loss: 0.01256 +Epoch [1148/4000] Training [9/16] Loss: 0.01176 +Epoch [1148/4000] Training [10/16] Loss: 0.00935 +Epoch [1148/4000] Training [11/16] Loss: 0.00961 +Epoch [1148/4000] Training [12/16] Loss: 0.01274 +Epoch [1148/4000] Training [13/16] Loss: 0.00857 +Epoch [1148/4000] Training [14/16] Loss: 0.00911 +Epoch [1148/4000] Training [15/16] Loss: 0.00828 +Epoch [1148/4000] Training [16/16] Loss: 0.01033 +Epoch [1148/4000] Training metric {'Train/mean dice_metric': 0.9928343296051025, 'Train/mean miou_metric': 0.9855565428733826, 'Train/mean f1': 0.9893261194229126, 'Train/mean precision': 0.9847375750541687, 'Train/mean recall': 0.9939575791358948, 'Train/mean hd95_metric': 1.118647813796997} +Epoch [1148/4000] Validation [1/4] Loss: 0.16512 focal_loss 0.10752 dice_loss 0.05760 +Epoch [1148/4000] Validation [2/4] Loss: 0.29181 focal_loss 0.14938 dice_loss 0.14243 +Epoch [1148/4000] Validation [3/4] Loss: 0.17912 focal_loss 0.10323 dice_loss 0.07589 +Epoch [1148/4000] Validation [4/4] Loss: 0.22632 focal_loss 0.13003 dice_loss 0.09629 +Epoch [1148/4000] Validation metric {'Val/mean dice_metric': 0.9720533490180969, 'Val/mean miou_metric': 0.952601432800293, 'Val/mean f1': 0.9729219079017639, 'Val/mean precision': 0.9687753915786743, 'Val/mean recall': 0.9771038889884949, 'Val/mean hd95_metric': 5.4294962882995605} +Cheakpoint... +Epoch [1148/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720533490180969, 'Val/mean miou_metric': 0.952601432800293, 'Val/mean f1': 0.9729219079017639, 'Val/mean precision': 0.9687753915786743, 'Val/mean recall': 0.9771038889884949, 'Val/mean hd95_metric': 5.4294962882995605} +Epoch [1149/4000] Training [1/16] Loss: 0.00726 +Epoch [1149/4000] Training [2/16] Loss: 0.01219 +Epoch [1149/4000] Training [3/16] Loss: 0.01082 +Epoch [1149/4000] Training [4/16] Loss: 0.00997 +Epoch [1149/4000] Training [5/16] Loss: 0.00789 +Epoch [1149/4000] Training [6/16] Loss: 0.00814 +Epoch [1149/4000] Training [7/16] Loss: 0.01048 +Epoch [1149/4000] Training [8/16] Loss: 0.00839 +Epoch [1149/4000] Training [9/16] Loss: 0.00836 +Epoch [1149/4000] Training [10/16] Loss: 0.00992 +Epoch [1149/4000] Training [11/16] Loss: 0.00907 +Epoch [1149/4000] Training [12/16] Loss: 0.00967 +Epoch [1149/4000] Training [13/16] Loss: 0.01324 +Epoch [1149/4000] Training [14/16] Loss: 0.01064 +Epoch [1149/4000] Training [15/16] Loss: 0.00785 +Epoch [1149/4000] Training [16/16] Loss: 0.01248 +Epoch [1149/4000] Training metric {'Train/mean dice_metric': 0.9928165674209595, 'Train/mean miou_metric': 0.9855202436447144, 'Train/mean f1': 0.9895573854446411, 'Train/mean precision': 0.9853504300117493, 'Train/mean recall': 0.9938004016876221, 'Train/mean hd95_metric': 1.140211582183838} +Epoch [1149/4000] Validation [1/4] Loss: 0.18803 focal_loss 0.12515 dice_loss 0.06288 +Epoch [1149/4000] Validation [2/4] Loss: 0.32944 focal_loss 0.18257 dice_loss 0.14688 +Epoch [1149/4000] Validation [3/4] Loss: 0.19130 focal_loss 0.10766 dice_loss 0.08364 +Epoch [1149/4000] Validation [4/4] Loss: 0.18896 focal_loss 0.09233 dice_loss 0.09663 +Epoch [1149/4000] Validation metric {'Val/mean dice_metric': 0.9693567156791687, 'Val/mean miou_metric': 0.9506748914718628, 'Val/mean f1': 0.9727990031242371, 'Val/mean precision': 0.9683188199996948, 'Val/mean recall': 0.9773209691047668, 'Val/mean hd95_metric': 6.383523464202881} +Cheakpoint... +Epoch [1149/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693567156791687, 'Val/mean miou_metric': 0.9506748914718628, 'Val/mean f1': 0.9727990031242371, 'Val/mean precision': 0.9683188199996948, 'Val/mean recall': 0.9773209691047668, 'Val/mean hd95_metric': 6.383523464202881} +Epoch [1150/4000] Training [1/16] Loss: 0.00788 +Epoch [1150/4000] Training [2/16] Loss: 0.01391 +Epoch [1150/4000] Training [3/16] Loss: 0.01430 +Epoch [1150/4000] Training [4/16] Loss: 0.00930 +Epoch [1150/4000] Training [5/16] Loss: 0.01091 +Epoch [1150/4000] Training [6/16] Loss: 0.00828 +Epoch [1150/4000] Training [7/16] Loss: 0.00946 +Epoch [1150/4000] Training [8/16] Loss: 0.01008 +Epoch [1150/4000] Training [9/16] Loss: 0.01221 +Epoch [1150/4000] Training [10/16] Loss: 0.01064 +Epoch [1150/4000] Training [11/16] Loss: 0.01060 +Epoch [1150/4000] Training [12/16] Loss: 0.01090 +Epoch [1150/4000] Training [13/16] Loss: 0.01015 +Epoch [1150/4000] Training [14/16] Loss: 0.00896 +Epoch [1150/4000] Training [15/16] Loss: 0.01054 +Epoch [1150/4000] Training [16/16] Loss: 0.00775 +Epoch [1150/4000] Training metric {'Train/mean dice_metric': 0.9921081066131592, 'Train/mean miou_metric': 0.9843522906303406, 'Train/mean f1': 0.9892807602882385, 'Train/mean precision': 0.9847002029418945, 'Train/mean recall': 0.9939040541648865, 'Train/mean hd95_metric': 1.2194223403930664} +Epoch [1150/4000] Validation [1/4] Loss: 0.16251 focal_loss 0.10214 dice_loss 0.06038 +Epoch [1150/4000] Validation [2/4] Loss: 0.60786 focal_loss 0.34468 dice_loss 0.26318 +Epoch [1150/4000] Validation [3/4] Loss: 0.17802 focal_loss 0.09866 dice_loss 0.07936 +Epoch [1150/4000] Validation [4/4] Loss: 0.26591 focal_loss 0.15324 dice_loss 0.11267 +Epoch [1150/4000] Validation metric {'Val/mean dice_metric': 0.9670820236206055, 'Val/mean miou_metric': 0.9482342004776001, 'Val/mean f1': 0.9716737866401672, 'Val/mean precision': 0.9684043526649475, 'Val/mean recall': 0.9749653339385986, 'Val/mean hd95_metric': 5.944274425506592} +Cheakpoint... +Epoch [1150/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670820236206055, 'Val/mean miou_metric': 0.9482342004776001, 'Val/mean f1': 0.9716737866401672, 'Val/mean precision': 0.9684043526649475, 'Val/mean recall': 0.9749653339385986, 'Val/mean hd95_metric': 5.944274425506592} +Epoch [1151/4000] Training [1/16] Loss: 0.01771 +Epoch [1151/4000] Training [2/16] Loss: 0.00959 +Epoch [1151/4000] Training [3/16] Loss: 0.01478 +Epoch [1151/4000] Training [4/16] Loss: 0.01000 +Epoch [1151/4000] Training [5/16] Loss: 0.01205 +Epoch [1151/4000] Training [6/16] Loss: 0.00954 +Epoch [1151/4000] Training [7/16] Loss: 0.01071 +Epoch [1151/4000] Training [8/16] Loss: 0.01459 +Epoch [1151/4000] Training [9/16] Loss: 0.01090 +Epoch [1151/4000] Training [10/16] Loss: 0.01103 +Epoch [1151/4000] Training [11/16] Loss: 0.00875 +Epoch [1151/4000] Training [12/16] Loss: 0.00920 +Epoch [1151/4000] Training [13/16] Loss: 0.00825 +Epoch [1151/4000] Training [14/16] Loss: 0.00901 +Epoch [1151/4000] Training [15/16] Loss: 0.00983 +Epoch [1151/4000] Training [16/16] Loss: 0.01448 +Epoch [1151/4000] Training metric {'Train/mean dice_metric': 0.9924998879432678, 'Train/mean miou_metric': 0.9848665595054626, 'Train/mean f1': 0.9879662394523621, 'Train/mean precision': 0.9827018976211548, 'Train/mean recall': 0.9932873249053955, 'Train/mean hd95_metric': 1.3697562217712402} +Epoch [1151/4000] Validation [1/4] Loss: 0.16047 focal_loss 0.10142 dice_loss 0.05905 +Epoch [1151/4000] Validation [2/4] Loss: 0.33769 focal_loss 0.18436 dice_loss 0.15333 +Epoch [1151/4000] Validation [3/4] Loss: 0.27062 focal_loss 0.17497 dice_loss 0.09565 +Epoch [1151/4000] Validation [4/4] Loss: 0.27475 focal_loss 0.15633 dice_loss 0.11842 +Epoch [1151/4000] Validation metric {'Val/mean dice_metric': 0.9691728353500366, 'Val/mean miou_metric': 0.9488657116889954, 'Val/mean f1': 0.969628632068634, 'Val/mean precision': 0.9628686308860779, 'Val/mean recall': 0.9764842391014099, 'Val/mean hd95_metric': 7.24673318862915} +Cheakpoint... +Epoch [1151/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691728353500366, 'Val/mean miou_metric': 0.9488657116889954, 'Val/mean f1': 0.969628632068634, 'Val/mean precision': 0.9628686308860779, 'Val/mean recall': 0.9764842391014099, 'Val/mean hd95_metric': 7.24673318862915} +Epoch [1152/4000] Training [1/16] Loss: 0.01115 +Epoch [1152/4000] Training [2/16] Loss: 0.00766 +Epoch [1152/4000] Training [3/16] Loss: 0.01025 +Epoch [1152/4000] Training [4/16] Loss: 0.01423 +Epoch [1152/4000] Training [5/16] Loss: 0.00782 +Epoch [1152/4000] Training [6/16] Loss: 0.01177 +Epoch [1152/4000] Training [7/16] Loss: 0.01217 +Epoch [1152/4000] Training [8/16] Loss: 0.01073 +Epoch [1152/4000] Training [9/16] Loss: 0.00852 +Epoch [1152/4000] Training [10/16] Loss: 0.00885 +Epoch [1152/4000] Training [11/16] Loss: 0.01150 +Epoch [1152/4000] Training [12/16] Loss: 0.01562 +Epoch [1152/4000] Training [13/16] Loss: 0.01182 +Epoch [1152/4000] Training [14/16] Loss: 0.01120 +Epoch [1152/4000] Training [15/16] Loss: 0.00789 +Epoch [1152/4000] Training [16/16] Loss: 0.01114 +Epoch [1152/4000] Training metric {'Train/mean dice_metric': 0.992707371711731, 'Train/mean miou_metric': 0.9853028059005737, 'Train/mean f1': 0.9891417622566223, 'Train/mean precision': 0.9846407771110535, 'Train/mean recall': 0.9936841130256653, 'Train/mean hd95_metric': 1.1227688789367676} +Epoch [1152/4000] Validation [1/4] Loss: 0.28605 focal_loss 0.20531 dice_loss 0.08073 +Epoch [1152/4000] Validation [2/4] Loss: 0.38043 focal_loss 0.20785 dice_loss 0.17258 +Epoch [1152/4000] Validation [3/4] Loss: 0.29745 focal_loss 0.20114 dice_loss 0.09631 +Epoch [1152/4000] Validation [4/4] Loss: 0.22767 focal_loss 0.13242 dice_loss 0.09525 +Epoch [1152/4000] Validation metric {'Val/mean dice_metric': 0.969923198223114, 'Val/mean miou_metric': 0.9503830671310425, 'Val/mean f1': 0.9702200293540955, 'Val/mean precision': 0.963242769241333, 'Val/mean recall': 0.977299153804779, 'Val/mean hd95_metric': 6.9151611328125} +Cheakpoint... +Epoch [1152/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969923198223114, 'Val/mean miou_metric': 0.9503830671310425, 'Val/mean f1': 0.9702200293540955, 'Val/mean precision': 0.963242769241333, 'Val/mean recall': 0.977299153804779, 'Val/mean hd95_metric': 6.9151611328125} +Epoch [1153/4000] Training [1/16] Loss: 0.01118 +Epoch [1153/4000] Training [2/16] Loss: 0.00844 +Epoch [1153/4000] Training [3/16] Loss: 0.01372 +Epoch [1153/4000] Training [4/16] Loss: 0.01349 +Epoch [1153/4000] Training [5/16] Loss: 0.00817 +Epoch [1153/4000] Training [6/16] Loss: 0.00894 +Epoch [1153/4000] Training [7/16] Loss: 0.01051 +Epoch [1153/4000] Training [8/16] Loss: 0.00755 +Epoch [1153/4000] Training [9/16] Loss: 0.01034 +Epoch [1153/4000] Training [10/16] Loss: 0.01572 +Epoch [1153/4000] Training [11/16] Loss: 0.00839 +Epoch [1153/4000] Training [12/16] Loss: 0.00785 +Epoch [1153/4000] Training [13/16] Loss: 0.01046 +Epoch [1153/4000] Training [14/16] Loss: 0.00875 +Epoch [1153/4000] Training [15/16] Loss: 0.00971 +Epoch [1153/4000] Training [16/16] Loss: 0.00963 +Epoch [1153/4000] Training metric {'Train/mean dice_metric': 0.9931353330612183, 'Train/mean miou_metric': 0.9861235618591309, 'Train/mean f1': 0.9892575144767761, 'Train/mean precision': 0.9846415519714355, 'Train/mean recall': 0.993916928768158, 'Train/mean hd95_metric': 1.1118652820587158} +Epoch [1153/4000] Validation [1/4] Loss: 0.17291 focal_loss 0.11358 dice_loss 0.05933 +Epoch [1153/4000] Validation [2/4] Loss: 0.27932 focal_loss 0.15358 dice_loss 0.12575 +Epoch [1153/4000] Validation [3/4] Loss: 0.26702 focal_loss 0.17112 dice_loss 0.09590 +Epoch [1153/4000] Validation [4/4] Loss: 0.27368 focal_loss 0.15815 dice_loss 0.11553 +Epoch [1153/4000] Validation metric {'Val/mean dice_metric': 0.9706758260726929, 'Val/mean miou_metric': 0.9517711400985718, 'Val/mean f1': 0.9718082547187805, 'Val/mean precision': 0.9655367136001587, 'Val/mean recall': 0.9781616926193237, 'Val/mean hd95_metric': 5.992077827453613} +Cheakpoint... +Epoch [1153/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706758260726929, 'Val/mean miou_metric': 0.9517711400985718, 'Val/mean f1': 0.9718082547187805, 'Val/mean precision': 0.9655367136001587, 'Val/mean recall': 0.9781616926193237, 'Val/mean hd95_metric': 5.992077827453613} +Epoch [1154/4000] Training [1/16] Loss: 0.01068 +Epoch [1154/4000] Training [2/16] Loss: 0.00955 +Epoch [1154/4000] Training [3/16] Loss: 0.01211 +Epoch [1154/4000] Training [4/16] Loss: 0.00829 +Epoch [1154/4000] Training [5/16] Loss: 0.00856 +Epoch [1154/4000] Training [6/16] Loss: 0.00865 +Epoch [1154/4000] Training [7/16] Loss: 0.00846 +Epoch [1154/4000] Training [8/16] Loss: 0.00968 +Epoch [1154/4000] Training [9/16] Loss: 0.00815 +Epoch [1154/4000] Training [10/16] Loss: 0.01129 +Epoch [1154/4000] Training [11/16] Loss: 0.00864 +Epoch [1154/4000] Training [12/16] Loss: 0.00839 +Epoch [1154/4000] Training [13/16] Loss: 0.01103 +Epoch [1154/4000] Training [14/16] Loss: 0.01067 +Epoch [1154/4000] Training [15/16] Loss: 0.00801 +Epoch [1154/4000] Training [16/16] Loss: 0.01070 +Epoch [1154/4000] Training metric {'Train/mean dice_metric': 0.9922370910644531, 'Train/mean miou_metric': 0.9847489595413208, 'Train/mean f1': 0.9893213510513306, 'Train/mean precision': 0.9847081899642944, 'Train/mean recall': 0.993977963924408, 'Train/mean hd95_metric': 1.3683881759643555} +Epoch [1154/4000] Validation [1/4] Loss: 0.21074 focal_loss 0.14649 dice_loss 0.06425 +Epoch [1154/4000] Validation [2/4] Loss: 0.39502 focal_loss 0.21346 dice_loss 0.18156 +Epoch [1154/4000] Validation [3/4] Loss: 0.14428 focal_loss 0.07714 dice_loss 0.06714 +Epoch [1154/4000] Validation [4/4] Loss: 0.20415 focal_loss 0.10359 dice_loss 0.10055 +Epoch [1154/4000] Validation metric {'Val/mean dice_metric': 0.9655641317367554, 'Val/mean miou_metric': 0.9473819732666016, 'Val/mean f1': 0.9710327386856079, 'Val/mean precision': 0.9683974981307983, 'Val/mean recall': 0.9736825227737427, 'Val/mean hd95_metric': 6.4780778884887695} +Cheakpoint... +Epoch [1154/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655641317367554, 'Val/mean miou_metric': 0.9473819732666016, 'Val/mean f1': 0.9710327386856079, 'Val/mean precision': 0.9683974981307983, 'Val/mean recall': 0.9736825227737427, 'Val/mean hd95_metric': 6.4780778884887695} +Epoch [1155/4000] Training [1/16] Loss: 0.00929 +Epoch [1155/4000] Training [2/16] Loss: 0.00817 +Epoch [1155/4000] Training [3/16] Loss: 0.01060 +Epoch [1155/4000] Training [4/16] Loss: 0.00743 +Epoch [1155/4000] Training [5/16] Loss: 0.00872 +Epoch [1155/4000] Training [6/16] Loss: 0.00770 +Epoch [1155/4000] Training [7/16] Loss: 0.00770 +Epoch [1155/4000] Training [8/16] Loss: 0.00793 +Epoch [1155/4000] Training [9/16] Loss: 0.00958 +Epoch [1155/4000] Training [10/16] Loss: 0.00691 +Epoch [1155/4000] Training [11/16] Loss: 0.01132 +Epoch [1155/4000] Training [12/16] Loss: 0.01023 +Epoch [1155/4000] Training [13/16] Loss: 0.01068 +Epoch [1155/4000] Training [14/16] Loss: 0.03996 +Epoch [1155/4000] Training [15/16] Loss: 0.00828 +Epoch [1155/4000] Training [16/16] Loss: 0.00999 +Epoch [1155/4000] Training metric {'Train/mean dice_metric': 0.9931901693344116, 'Train/mean miou_metric': 0.9863032102584839, 'Train/mean f1': 0.9895278215408325, 'Train/mean precision': 0.9851551055908203, 'Train/mean recall': 0.9939395189285278, 'Train/mean hd95_metric': 1.1593976020812988} +Epoch [1155/4000] Validation [1/4] Loss: 0.27104 focal_loss 0.19168 dice_loss 0.07936 +Epoch [1155/4000] Validation [2/4] Loss: 0.34471 focal_loss 0.18662 dice_loss 0.15809 +Epoch [1155/4000] Validation [3/4] Loss: 0.14350 focal_loss 0.08174 dice_loss 0.06176 +Epoch [1155/4000] Validation [4/4] Loss: 0.26162 focal_loss 0.14164 dice_loss 0.11998 +Epoch [1155/4000] Validation metric {'Val/mean dice_metric': 0.9699560403823853, 'Val/mean miou_metric': 0.950800895690918, 'Val/mean f1': 0.9712516665458679, 'Val/mean precision': 0.9678013920783997, 'Val/mean recall': 0.9747267961502075, 'Val/mean hd95_metric': 6.543622016906738} +Cheakpoint... +Epoch [1155/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699560403823853, 'Val/mean miou_metric': 0.950800895690918, 'Val/mean f1': 0.9712516665458679, 'Val/mean precision': 0.9678013920783997, 'Val/mean recall': 0.9747267961502075, 'Val/mean hd95_metric': 6.543622016906738} +Epoch [1156/4000] Training [1/16] Loss: 0.01155 +Epoch [1156/4000] Training [2/16] Loss: 0.01030 +Epoch [1156/4000] Training [3/16] Loss: 0.00688 +Epoch [1156/4000] Training [4/16] Loss: 0.01123 +Epoch [1156/4000] Training [5/16] Loss: 0.00770 +Epoch [1156/4000] Training [6/16] Loss: 0.01514 +Epoch [1156/4000] Training [7/16] Loss: 0.01518 +Epoch [1156/4000] Training [8/16] Loss: 0.01052 +Epoch [1156/4000] Training [9/16] Loss: 0.01127 +Epoch [1156/4000] Training [10/16] Loss: 0.01024 +Epoch [1156/4000] Training [11/16] Loss: 0.01155 +Epoch [1156/4000] Training [12/16] Loss: 0.01135 +Epoch [1156/4000] Training [13/16] Loss: 0.00731 +Epoch [1156/4000] Training [14/16] Loss: 0.00705 +Epoch [1156/4000] Training [15/16] Loss: 0.01329 +Epoch [1156/4000] Training [16/16] Loss: 0.01209 +Epoch [1156/4000] Training metric {'Train/mean dice_metric': 0.9924962520599365, 'Train/mean miou_metric': 0.9848986864089966, 'Train/mean f1': 0.9890046715736389, 'Train/mean precision': 0.9844381809234619, 'Train/mean recall': 0.9936137199401855, 'Train/mean hd95_metric': 1.4252917766571045} +Epoch [1156/4000] Validation [1/4] Loss: 0.38226 focal_loss 0.29096 dice_loss 0.09131 +Epoch [1156/4000] Validation [2/4] Loss: 0.57504 focal_loss 0.31511 dice_loss 0.25993 +Epoch [1156/4000] Validation [3/4] Loss: 0.32267 focal_loss 0.21229 dice_loss 0.11038 +Epoch [1156/4000] Validation [4/4] Loss: 0.21769 focal_loss 0.11268 dice_loss 0.10501 +Epoch [1156/4000] Validation metric {'Val/mean dice_metric': 0.968532383441925, 'Val/mean miou_metric': 0.9485642313957214, 'Val/mean f1': 0.9680407643318176, 'Val/mean precision': 0.9597925543785095, 'Val/mean recall': 0.9764320254325867, 'Val/mean hd95_metric': 6.600222110748291} +Cheakpoint... +Epoch [1156/4000] best acc:tensor([0.9726], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968532383441925, 'Val/mean miou_metric': 0.9485642313957214, 'Val/mean f1': 0.9680407643318176, 'Val/mean precision': 0.9597925543785095, 'Val/mean recall': 0.9764320254325867, 'Val/mean hd95_metric': 6.600222110748291} +Epoch [1157/4000] Training [1/16] Loss: 0.00770 +Epoch [1157/4000] Training [2/16] Loss: 0.00899 +Epoch [1157/4000] Training [3/16] Loss: 0.00897 +Epoch [1157/4000] Training [4/16] Loss: 0.01341 +Epoch [1157/4000] Training [5/16] Loss: 0.01050 +Epoch [1157/4000] Training [6/16] Loss: 0.00883 +Epoch [1157/4000] Training [7/16] Loss: 0.01103 +Epoch [1157/4000] Training [8/16] Loss: 0.01060 +Epoch [1157/4000] Training [9/16] Loss: 0.01166 +Epoch [1157/4000] Training [10/16] Loss: 0.00824 +Epoch [1157/4000] Training [11/16] Loss: 0.00841 +Epoch [1157/4000] Training [12/16] Loss: 0.00960 +Epoch [1157/4000] Training [13/16] Loss: 0.01072 +Epoch [1157/4000] Training [14/16] Loss: 0.00830 +Epoch [1157/4000] Training [15/16] Loss: 0.00734 +Epoch [1157/4000] Training [16/16] Loss: 0.00762 +Epoch [1157/4000] Training metric {'Train/mean dice_metric': 0.9936918020248413, 'Train/mean miou_metric': 0.987207293510437, 'Train/mean f1': 0.9897250533103943, 'Train/mean precision': 0.9850360751152039, 'Train/mean recall': 0.994458794593811, 'Train/mean hd95_metric': 1.1110060214996338} +Epoch [1157/4000] Validation [1/4] Loss: 0.26747 focal_loss 0.19251 dice_loss 0.07496 +Epoch [1157/4000] Validation [2/4] Loss: 0.38302 focal_loss 0.22876 dice_loss 0.15426 +Epoch [1157/4000] Validation [3/4] Loss: 0.12404 focal_loss 0.06280 dice_loss 0.06123 +Epoch [1157/4000] Validation [4/4] Loss: 0.25098 focal_loss 0.13149 dice_loss 0.11949 +Epoch [1157/4000] Validation metric {'Val/mean dice_metric': 0.9734781384468079, 'Val/mean miou_metric': 0.9548174738883972, 'Val/mean f1': 0.9722177982330322, 'Val/mean precision': 0.9665513634681702, 'Val/mean recall': 0.9779511094093323, 'Val/mean hd95_metric': 6.105141639709473} +Cheakpoint... +Epoch [1157/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734781384468079, 'Val/mean miou_metric': 0.9548174738883972, 'Val/mean f1': 0.9722177982330322, 'Val/mean precision': 0.9665513634681702, 'Val/mean recall': 0.9779511094093323, 'Val/mean hd95_metric': 6.105141639709473} +Epoch [1158/4000] Training [1/16] Loss: 0.01101 +Epoch [1158/4000] Training [2/16] Loss: 0.00848 +Epoch [1158/4000] Training [3/16] Loss: 0.01014 +Epoch [1158/4000] Training [4/16] Loss: 0.00778 +Epoch [1158/4000] Training [5/16] Loss: 0.00882 +Epoch [1158/4000] Training [6/16] Loss: 0.01515 +Epoch [1158/4000] Training [7/16] Loss: 0.00827 +Epoch [1158/4000] Training [8/16] Loss: 0.01215 +Epoch [1158/4000] Training [9/16] Loss: 0.01281 +Epoch [1158/4000] Training [10/16] Loss: 0.00790 +Epoch [1158/4000] Training [11/16] Loss: 0.00973 +Epoch [1158/4000] Training [12/16] Loss: 0.00845 +Epoch [1158/4000] Training [13/16] Loss: 0.00702 +Epoch [1158/4000] Training [14/16] Loss: 0.00761 +Epoch [1158/4000] Training [15/16] Loss: 0.01012 +Epoch [1158/4000] Training [16/16] Loss: 0.00851 +Epoch [1158/4000] Training metric {'Train/mean dice_metric': 0.9937376976013184, 'Train/mean miou_metric': 0.9873285889625549, 'Train/mean f1': 0.9900801181793213, 'Train/mean precision': 0.9855633974075317, 'Train/mean recall': 0.9946384429931641, 'Train/mean hd95_metric': 1.0676171779632568} +Epoch [1158/4000] Validation [1/4] Loss: 0.31180 focal_loss 0.22776 dice_loss 0.08404 +Epoch [1158/4000] Validation [2/4] Loss: 0.31700 focal_loss 0.17635 dice_loss 0.14065 +Epoch [1158/4000] Validation [3/4] Loss: 0.19680 focal_loss 0.10381 dice_loss 0.09299 +Epoch [1158/4000] Validation [4/4] Loss: 0.26139 focal_loss 0.14785 dice_loss 0.11354 +Epoch [1158/4000] Validation metric {'Val/mean dice_metric': 0.9720419645309448, 'Val/mean miou_metric': 0.9530695676803589, 'Val/mean f1': 0.9715427160263062, 'Val/mean precision': 0.9652004241943359, 'Val/mean recall': 0.9779689908027649, 'Val/mean hd95_metric': 5.814231872558594} +Cheakpoint... +Epoch [1158/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720419645309448, 'Val/mean miou_metric': 0.9530695676803589, 'Val/mean f1': 0.9715427160263062, 'Val/mean precision': 0.9652004241943359, 'Val/mean recall': 0.9779689908027649, 'Val/mean hd95_metric': 5.814231872558594} +Epoch [1159/4000] Training [1/16] Loss: 0.00778 +Epoch [1159/4000] Training [2/16] Loss: 0.00800 +Epoch [1159/4000] Training [3/16] Loss: 0.01086 +Epoch [1159/4000] Training [4/16] Loss: 0.01044 +Epoch [1159/4000] Training [5/16] Loss: 0.00597 +Epoch [1159/4000] Training [6/16] Loss: 0.00842 +Epoch [1159/4000] Training [7/16] Loss: 0.01842 +Epoch [1159/4000] Training [8/16] Loss: 0.00820 +Epoch [1159/4000] Training [9/16] Loss: 0.01052 +Epoch [1159/4000] Training [10/16] Loss: 0.01113 +Epoch [1159/4000] Training [11/16] Loss: 0.01038 +Epoch [1159/4000] Training [12/16] Loss: 0.01006 +Epoch [1159/4000] Training [13/16] Loss: 0.00984 +Epoch [1159/4000] Training [14/16] Loss: 0.00930 +Epoch [1159/4000] Training [15/16] Loss: 0.00952 +Epoch [1159/4000] Training [16/16] Loss: 0.01123 +Epoch [1159/4000] Training metric {'Train/mean dice_metric': 0.9926486611366272, 'Train/mean miou_metric': 0.985209584236145, 'Train/mean f1': 0.9884504079818726, 'Train/mean precision': 0.9833186268806458, 'Train/mean recall': 0.9936360716819763, 'Train/mean hd95_metric': 1.2137480974197388} +Epoch [1159/4000] Validation [1/4] Loss: 0.26181 focal_loss 0.18723 dice_loss 0.07458 +Epoch [1159/4000] Validation [2/4] Loss: 0.30603 focal_loss 0.14433 dice_loss 0.16170 +Epoch [1159/4000] Validation [3/4] Loss: 0.12809 focal_loss 0.07484 dice_loss 0.05325 +Epoch [1159/4000] Validation [4/4] Loss: 0.21222 focal_loss 0.11484 dice_loss 0.09738 +Epoch [1159/4000] Validation metric {'Val/mean dice_metric': 0.9711000323295593, 'Val/mean miou_metric': 0.9517680406570435, 'Val/mean f1': 0.970589816570282, 'Val/mean precision': 0.9628191590309143, 'Val/mean recall': 0.978486955165863, 'Val/mean hd95_metric': 6.1649627685546875} +Cheakpoint... +Epoch [1159/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711000323295593, 'Val/mean miou_metric': 0.9517680406570435, 'Val/mean f1': 0.970589816570282, 'Val/mean precision': 0.9628191590309143, 'Val/mean recall': 0.978486955165863, 'Val/mean hd95_metric': 6.1649627685546875} +Epoch [1160/4000] Training [1/16] Loss: 0.00719 +Epoch [1160/4000] Training [2/16] Loss: 0.01091 +Epoch [1160/4000] Training [3/16] Loss: 0.01210 +Epoch [1160/4000] Training [4/16] Loss: 0.01134 +Epoch [1160/4000] Training [5/16] Loss: 0.00930 +Epoch [1160/4000] Training [6/16] Loss: 0.00941 +Epoch [1160/4000] Training [7/16] Loss: 0.01538 +Epoch [1160/4000] Training [8/16] Loss: 0.01454 +Epoch [1160/4000] Training [9/16] Loss: 0.00975 +Epoch [1160/4000] Training [10/16] Loss: 0.01085 +Epoch [1160/4000] Training [11/16] Loss: 0.00953 +Epoch [1160/4000] Training [12/16] Loss: 0.01200 +Epoch [1160/4000] Training [13/16] Loss: 0.00897 +Epoch [1160/4000] Training [14/16] Loss: 0.01392 +Epoch [1160/4000] Training [15/16] Loss: 0.00995 +Epoch [1160/4000] Training [16/16] Loss: 0.00906 +Epoch [1160/4000] Training metric {'Train/mean dice_metric': 0.9928077459335327, 'Train/mean miou_metric': 0.9854892492294312, 'Train/mean f1': 0.9891055226325989, 'Train/mean precision': 0.9843721985816956, 'Train/mean recall': 0.9938845634460449, 'Train/mean hd95_metric': 1.1910572052001953} +Epoch [1160/4000] Validation [1/4] Loss: 0.20537 focal_loss 0.12841 dice_loss 0.07696 +Epoch [1160/4000] Validation [2/4] Loss: 0.33943 focal_loss 0.15209 dice_loss 0.18733 +Epoch [1160/4000] Validation [3/4] Loss: 0.17763 focal_loss 0.09909 dice_loss 0.07854 +Epoch [1160/4000] Validation [4/4] Loss: 0.25456 focal_loss 0.14672 dice_loss 0.10784 +Epoch [1160/4000] Validation metric {'Val/mean dice_metric': 0.9688579440116882, 'Val/mean miou_metric': 0.9491987228393555, 'Val/mean f1': 0.9700241088867188, 'Val/mean precision': 0.9623734354972839, 'Val/mean recall': 0.9777973890304565, 'Val/mean hd95_metric': 6.722943305969238} +Cheakpoint... +Epoch [1160/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688579440116882, 'Val/mean miou_metric': 0.9491987228393555, 'Val/mean f1': 0.9700241088867188, 'Val/mean precision': 0.9623734354972839, 'Val/mean recall': 0.9777973890304565, 'Val/mean hd95_metric': 6.722943305969238} +Epoch [1161/4000] Training [1/16] Loss: 0.00720 +Epoch [1161/4000] Training [2/16] Loss: 0.00836 +Epoch [1161/4000] Training [3/16] Loss: 0.01396 +Epoch [1161/4000] Training [4/16] Loss: 0.00996 +Epoch [1161/4000] Training [5/16] Loss: 0.01248 +Epoch [1161/4000] Training [6/16] Loss: 0.01216 +Epoch [1161/4000] Training [7/16] Loss: 0.04844 +Epoch [1161/4000] Training [8/16] Loss: 0.01002 +Epoch [1161/4000] Training [9/16] Loss: 0.00747 +Epoch [1161/4000] Training [10/16] Loss: 0.01029 +Epoch [1161/4000] Training [11/16] Loss: 0.01446 +Epoch [1161/4000] Training [12/16] Loss: 0.00804 +Epoch [1161/4000] Training [13/16] Loss: 0.01209 +Epoch [1161/4000] Training [14/16] Loss: 0.01020 +Epoch [1161/4000] Training [15/16] Loss: 0.00762 +Epoch [1161/4000] Training [16/16] Loss: 0.00918 +Epoch [1161/4000] Training metric {'Train/mean dice_metric': 0.9925521612167358, 'Train/mean miou_metric': 0.9850301742553711, 'Train/mean f1': 0.9887341260910034, 'Train/mean precision': 0.9843135476112366, 'Train/mean recall': 0.9931945204734802, 'Train/mean hd95_metric': 1.3040059804916382} +Epoch [1161/4000] Validation [1/4] Loss: 0.20044 focal_loss 0.12775 dice_loss 0.07269 +Epoch [1161/4000] Validation [2/4] Loss: 0.46098 focal_loss 0.21787 dice_loss 0.24311 +Epoch [1161/4000] Validation [3/4] Loss: 0.25411 focal_loss 0.15368 dice_loss 0.10043 +Epoch [1161/4000] Validation [4/4] Loss: 0.29660 focal_loss 0.16547 dice_loss 0.13113 +Epoch [1161/4000] Validation metric {'Val/mean dice_metric': 0.9678971171379089, 'Val/mean miou_metric': 0.9480454325675964, 'Val/mean f1': 0.9697456955909729, 'Val/mean precision': 0.964008629322052, 'Val/mean recall': 0.9755515456199646, 'Val/mean hd95_metric': 7.116457939147949} +Cheakpoint... +Epoch [1161/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678971171379089, 'Val/mean miou_metric': 0.9480454325675964, 'Val/mean f1': 0.9697456955909729, 'Val/mean precision': 0.964008629322052, 'Val/mean recall': 0.9755515456199646, 'Val/mean hd95_metric': 7.116457939147949} +Epoch [1162/4000] Training [1/16] Loss: 0.00969 +Epoch [1162/4000] Training [2/16] Loss: 0.00689 +Epoch [1162/4000] Training [3/16] Loss: 0.00874 +Epoch [1162/4000] Training [4/16] Loss: 0.01046 +Epoch [1162/4000] Training [5/16] Loss: 0.01124 +Epoch [1162/4000] Training [6/16] Loss: 0.00850 +Epoch [1162/4000] Training [7/16] Loss: 0.00708 +Epoch [1162/4000] Training [8/16] Loss: 0.01082 +Epoch [1162/4000] Training [9/16] Loss: 0.01016 +Epoch [1162/4000] Training [10/16] Loss: 0.01132 +Epoch [1162/4000] Training [11/16] Loss: 0.00997 +Epoch [1162/4000] Training [12/16] Loss: 0.01705 +Epoch [1162/4000] Training [13/16] Loss: 0.00865 +Epoch [1162/4000] Training [14/16] Loss: 0.01000 +Epoch [1162/4000] Training [15/16] Loss: 0.00900 +Epoch [1162/4000] Training [16/16] Loss: 0.00921 +Epoch [1162/4000] Training metric {'Train/mean dice_metric': 0.9932477474212646, 'Train/mean miou_metric': 0.9863573908805847, 'Train/mean f1': 0.9896714091300964, 'Train/mean precision': 0.9851479530334473, 'Train/mean recall': 0.9942364692687988, 'Train/mean hd95_metric': 1.1108286380767822} +Epoch [1162/4000] Validation [1/4] Loss: 0.27370 focal_loss 0.19875 dice_loss 0.07495 +Epoch [1162/4000] Validation [2/4] Loss: 0.25484 focal_loss 0.12205 dice_loss 0.13280 +Epoch [1162/4000] Validation [3/4] Loss: 0.28538 focal_loss 0.18864 dice_loss 0.09674 +Epoch [1162/4000] Validation [4/4] Loss: 0.32249 focal_loss 0.17592 dice_loss 0.14657 +Epoch [1162/4000] Validation metric {'Val/mean dice_metric': 0.9674292802810669, 'Val/mean miou_metric': 0.9482719302177429, 'Val/mean f1': 0.9693818688392639, 'Val/mean precision': 0.9599058628082275, 'Val/mean recall': 0.9790468215942383, 'Val/mean hd95_metric': 7.352475166320801} +Cheakpoint... +Epoch [1162/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674292802810669, 'Val/mean miou_metric': 0.9482719302177429, 'Val/mean f1': 0.9693818688392639, 'Val/mean precision': 0.9599058628082275, 'Val/mean recall': 0.9790468215942383, 'Val/mean hd95_metric': 7.352475166320801} +Epoch [1163/4000] Training [1/16] Loss: 0.00927 +Epoch [1163/4000] Training [2/16] Loss: 0.00687 +Epoch [1163/4000] Training [3/16] Loss: 0.12294 +Epoch [1163/4000] Training [4/16] Loss: 0.00929 +Epoch [1163/4000] Training [5/16] Loss: 0.00812 +Epoch [1163/4000] Training [6/16] Loss: 0.01269 +Epoch [1163/4000] Training [7/16] Loss: 0.01644 +Epoch [1163/4000] Training [8/16] Loss: 0.00812 +Epoch [1163/4000] Training [9/16] Loss: 0.01082 +Epoch [1163/4000] Training [10/16] Loss: 0.01161 +Epoch [1163/4000] Training [11/16] Loss: 0.01365 +Epoch [1163/4000] Training [12/16] Loss: 0.01055 +Epoch [1163/4000] Training [13/16] Loss: 0.01487 +Epoch [1163/4000] Training [14/16] Loss: 0.00879 +Epoch [1163/4000] Training [15/16] Loss: 0.00767 +Epoch [1163/4000] Training [16/16] Loss: 0.01064 +Epoch [1163/4000] Training metric {'Train/mean dice_metric': 0.9919124841690063, 'Train/mean miou_metric': 0.9841970205307007, 'Train/mean f1': 0.9882876873016357, 'Train/mean precision': 0.9835124015808105, 'Train/mean recall': 0.9931095838546753, 'Train/mean hd95_metric': 1.6747114658355713} +Epoch [1163/4000] Validation [1/4] Loss: 0.30338 focal_loss 0.21672 dice_loss 0.08665 +Epoch [1163/4000] Validation [2/4] Loss: 0.38330 focal_loss 0.18262 dice_loss 0.20068 +Epoch [1163/4000] Validation [3/4] Loss: 0.16821 focal_loss 0.09402 dice_loss 0.07419 +Epoch [1163/4000] Validation [4/4] Loss: 0.25792 focal_loss 0.13928 dice_loss 0.11864 +Epoch [1163/4000] Validation metric {'Val/mean dice_metric': 0.9662971496582031, 'Val/mean miou_metric': 0.946282684803009, 'Val/mean f1': 0.9682371616363525, 'Val/mean precision': 0.9663394689559937, 'Val/mean recall': 0.9701423645019531, 'Val/mean hd95_metric': 6.587790012359619} +Cheakpoint... +Epoch [1163/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662971496582031, 'Val/mean miou_metric': 0.946282684803009, 'Val/mean f1': 0.9682371616363525, 'Val/mean precision': 0.9663394689559937, 'Val/mean recall': 0.9701423645019531, 'Val/mean hd95_metric': 6.587790012359619} +Epoch [1164/4000] Training [1/16] Loss: 0.01194 +Epoch [1164/4000] Training [2/16] Loss: 0.00856 +Epoch [1164/4000] Training [3/16] Loss: 0.01171 +Epoch [1164/4000] Training [4/16] Loss: 0.00980 +Epoch [1164/4000] Training [5/16] Loss: 0.00838 +Epoch [1164/4000] Training [6/16] Loss: 0.01304 +Epoch [1164/4000] Training [7/16] Loss: 0.01541 +Epoch [1164/4000] Training [8/16] Loss: 0.01011 +Epoch [1164/4000] Training [9/16] Loss: 0.01527 +Epoch [1164/4000] Training [10/16] Loss: 0.00955 +Epoch [1164/4000] Training [11/16] Loss: 0.01742 +Epoch [1164/4000] Training [12/16] Loss: 0.01130 +Epoch [1164/4000] Training [13/16] Loss: 0.01069 +Epoch [1164/4000] Training [14/16] Loss: 0.00949 +Epoch [1164/4000] Training [15/16] Loss: 0.02114 +Epoch [1164/4000] Training [16/16] Loss: 0.01362 +Epoch [1164/4000] Training metric {'Train/mean dice_metric': 0.9910300970077515, 'Train/mean miou_metric': 0.9823653101921082, 'Train/mean f1': 0.9880134463310242, 'Train/mean precision': 0.9836908578872681, 'Train/mean recall': 0.9923741817474365, 'Train/mean hd95_metric': 1.6299676895141602} +Epoch [1164/4000] Validation [1/4] Loss: 0.32443 focal_loss 0.23515 dice_loss 0.08928 +Epoch [1164/4000] Validation [2/4] Loss: 0.45382 focal_loss 0.23822 dice_loss 0.21560 +Epoch [1164/4000] Validation [3/4] Loss: 0.24855 focal_loss 0.15156 dice_loss 0.09699 +Epoch [1164/4000] Validation [4/4] Loss: 0.39044 focal_loss 0.22849 dice_loss 0.16196 +Epoch [1164/4000] Validation metric {'Val/mean dice_metric': 0.9686024785041809, 'Val/mean miou_metric': 0.9480065107345581, 'Val/mean f1': 0.9690325260162354, 'Val/mean precision': 0.967918872833252, 'Val/mean recall': 0.9701486825942993, 'Val/mean hd95_metric': 6.505284309387207} +Cheakpoint... +Epoch [1164/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686024785041809, 'Val/mean miou_metric': 0.9480065107345581, 'Val/mean f1': 0.9690325260162354, 'Val/mean precision': 0.967918872833252, 'Val/mean recall': 0.9701486825942993, 'Val/mean hd95_metric': 6.505284309387207} +Epoch [1165/4000] Training [1/16] Loss: 0.00775 +Epoch [1165/4000] Training [2/16] Loss: 0.01056 +Epoch [1165/4000] Training [3/16] Loss: 0.01234 +Epoch [1165/4000] Training [4/16] Loss: 0.00971 +Epoch [1165/4000] Training [5/16] Loss: 0.00907 +Epoch [1165/4000] Training [6/16] Loss: 0.00780 +Epoch [1165/4000] Training [7/16] Loss: 0.01161 +Epoch [1165/4000] Training [8/16] Loss: 0.01142 +Epoch [1165/4000] Training [9/16] Loss: 0.01303 +Epoch [1165/4000] Training [10/16] Loss: 0.01003 +Epoch [1165/4000] Training [11/16] Loss: 0.00838 +Epoch [1165/4000] Training [12/16] Loss: 0.01132 +Epoch [1165/4000] Training [13/16] Loss: 0.00974 +Epoch [1165/4000] Training [14/16] Loss: 0.01200 +Epoch [1165/4000] Training [15/16] Loss: 0.01278 +Epoch [1165/4000] Training [16/16] Loss: 0.01015 +Epoch [1165/4000] Training metric {'Train/mean dice_metric': 0.9920977354049683, 'Train/mean miou_metric': 0.984229326248169, 'Train/mean f1': 0.9878787994384766, 'Train/mean precision': 0.9826692938804626, 'Train/mean recall': 0.9931438565254211, 'Train/mean hd95_metric': 1.3356460332870483} +Epoch [1165/4000] Validation [1/4] Loss: 0.23468 focal_loss 0.15632 dice_loss 0.07836 +Epoch [1165/4000] Validation [2/4] Loss: 0.46789 focal_loss 0.21689 dice_loss 0.25100 +Epoch [1165/4000] Validation [3/4] Loss: 0.29619 focal_loss 0.19867 dice_loss 0.09751 +Epoch [1165/4000] Validation [4/4] Loss: 0.21805 focal_loss 0.11030 dice_loss 0.10775 +Epoch [1165/4000] Validation metric {'Val/mean dice_metric': 0.9673303365707397, 'Val/mean miou_metric': 0.9474157094955444, 'Val/mean f1': 0.9683205485343933, 'Val/mean precision': 0.9605453014373779, 'Val/mean recall': 0.976222813129425, 'Val/mean hd95_metric': 7.080308437347412} +Cheakpoint... +Epoch [1165/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673303365707397, 'Val/mean miou_metric': 0.9474157094955444, 'Val/mean f1': 0.9683205485343933, 'Val/mean precision': 0.9605453014373779, 'Val/mean recall': 0.976222813129425, 'Val/mean hd95_metric': 7.080308437347412} +Epoch [1166/4000] Training [1/16] Loss: 0.00977 +Epoch [1166/4000] Training [2/16] Loss: 0.01316 +Epoch [1166/4000] Training [3/16] Loss: 0.01175 +Epoch [1166/4000] Training [4/16] Loss: 0.00853 +Epoch [1166/4000] Training [5/16] Loss: 0.01217 +Epoch [1166/4000] Training [6/16] Loss: 0.00940 +Epoch [1166/4000] Training [7/16] Loss: 0.00789 +Epoch [1166/4000] Training [8/16] Loss: 0.01514 +Epoch [1166/4000] Training [9/16] Loss: 0.01000 +Epoch [1166/4000] Training [10/16] Loss: 0.01140 +Epoch [1166/4000] Training [11/16] Loss: 0.01111 +Epoch [1166/4000] Training [12/16] Loss: 0.00819 +Epoch [1166/4000] Training [13/16] Loss: 0.00992 +Epoch [1166/4000] Training [14/16] Loss: 0.00999 +Epoch [1166/4000] Training [15/16] Loss: 0.01009 +Epoch [1166/4000] Training [16/16] Loss: 0.00837 +Epoch [1166/4000] Training metric {'Train/mean dice_metric': 0.9928606748580933, 'Train/mean miou_metric': 0.9856042265892029, 'Train/mean f1': 0.9889130592346191, 'Train/mean precision': 0.9839518666267395, 'Train/mean recall': 0.9939245581626892, 'Train/mean hd95_metric': 1.4616485834121704} +Epoch [1166/4000] Validation [1/4] Loss: 0.21705 focal_loss 0.14721 dice_loss 0.06984 +Epoch [1166/4000] Validation [2/4] Loss: 0.33288 focal_loss 0.14413 dice_loss 0.18875 +Epoch [1166/4000] Validation [3/4] Loss: 0.12868 focal_loss 0.07533 dice_loss 0.05335 +Epoch [1166/4000] Validation [4/4] Loss: 0.33648 focal_loss 0.22009 dice_loss 0.11639 +Epoch [1166/4000] Validation metric {'Val/mean dice_metric': 0.9674003720283508, 'Val/mean miou_metric': 0.9484823346138, 'Val/mean f1': 0.9703295826911926, 'Val/mean precision': 0.9708150625228882, 'Val/mean recall': 0.9698446393013, 'Val/mean hd95_metric': 6.086843967437744} +Cheakpoint... +Epoch [1166/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674003720283508, 'Val/mean miou_metric': 0.9484823346138, 'Val/mean f1': 0.9703295826911926, 'Val/mean precision': 0.9708150625228882, 'Val/mean recall': 0.9698446393013, 'Val/mean hd95_metric': 6.086843967437744} +Epoch [1167/4000] Training [1/16] Loss: 0.01556 +Epoch [1167/4000] Training [2/16] Loss: 0.00985 +Epoch [1167/4000] Training [3/16] Loss: 0.00767 +Epoch [1167/4000] Training [4/16] Loss: 0.01018 +Epoch [1167/4000] Training [5/16] Loss: 0.01305 +Epoch [1167/4000] Training [6/16] Loss: 0.01262 +Epoch [1167/4000] Training [7/16] Loss: 0.00792 +Epoch [1167/4000] Training [8/16] Loss: 0.00861 +Epoch [1167/4000] Training [9/16] Loss: 0.01136 +Epoch [1167/4000] Training [10/16] Loss: 0.00722 +Epoch [1167/4000] Training [11/16] Loss: 0.01767 +Epoch [1167/4000] Training [12/16] Loss: 0.01469 +Epoch [1167/4000] Training [13/16] Loss: 0.00902 +Epoch [1167/4000] Training [14/16] Loss: 0.00858 +Epoch [1167/4000] Training [15/16] Loss: 0.01043 +Epoch [1167/4000] Training [16/16] Loss: 0.01063 +Epoch [1167/4000] Training metric {'Train/mean dice_metric': 0.9921530485153198, 'Train/mean miou_metric': 0.9842140674591064, 'Train/mean f1': 0.9877798557281494, 'Train/mean precision': 0.9829655289649963, 'Train/mean recall': 0.9926415681838989, 'Train/mean hd95_metric': 1.5777549743652344} +Epoch [1167/4000] Validation [1/4] Loss: 0.23845 focal_loss 0.16927 dice_loss 0.06918 +Epoch [1167/4000] Validation [2/4] Loss: 0.25430 focal_loss 0.11924 dice_loss 0.13506 +Epoch [1167/4000] Validation [3/4] Loss: 0.18339 focal_loss 0.10134 dice_loss 0.08206 +Epoch [1167/4000] Validation [4/4] Loss: 0.21598 focal_loss 0.10552 dice_loss 0.11046 +Epoch [1167/4000] Validation metric {'Val/mean dice_metric': 0.9679338335990906, 'Val/mean miou_metric': 0.94847172498703, 'Val/mean f1': 0.9709916710853577, 'Val/mean precision': 0.9677872061729431, 'Val/mean recall': 0.9742174744606018, 'Val/mean hd95_metric': 5.994040489196777} +Cheakpoint... +Epoch [1167/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679338335990906, 'Val/mean miou_metric': 0.94847172498703, 'Val/mean f1': 0.9709916710853577, 'Val/mean precision': 0.9677872061729431, 'Val/mean recall': 0.9742174744606018, 'Val/mean hd95_metric': 5.994040489196777} +Epoch [1168/4000] Training [1/16] Loss: 0.00823 +Epoch [1168/4000] Training [2/16] Loss: 0.01017 +Epoch [1168/4000] Training [3/16] Loss: 0.01178 +Epoch [1168/4000] Training [4/16] Loss: 0.00792 +Epoch [1168/4000] Training [5/16] Loss: 0.00830 +Epoch [1168/4000] Training [6/16] Loss: 0.00817 +Epoch [1168/4000] Training [7/16] Loss: 0.00818 +Epoch [1168/4000] Training [8/16] Loss: 0.01408 +Epoch [1168/4000] Training [9/16] Loss: 0.01028 +Epoch [1168/4000] Training [10/16] Loss: 0.00985 +Epoch [1168/4000] Training [11/16] Loss: 0.00940 +Epoch [1168/4000] Training [12/16] Loss: 0.01418 +Epoch [1168/4000] Training [13/16] Loss: 0.01019 +Epoch [1168/4000] Training [14/16] Loss: 0.00935 +Epoch [1168/4000] Training [15/16] Loss: 0.00913 +Epoch [1168/4000] Training [16/16] Loss: 0.00837 +Epoch [1168/4000] Training metric {'Train/mean dice_metric': 0.9934288263320923, 'Train/mean miou_metric': 0.9867169857025146, 'Train/mean f1': 0.9898144006729126, 'Train/mean precision': 0.9854511618614197, 'Train/mean recall': 0.9942163825035095, 'Train/mean hd95_metric': 1.1813161373138428} +Epoch [1168/4000] Validation [1/4] Loss: 0.41051 focal_loss 0.29106 dice_loss 0.11945 +Epoch [1168/4000] Validation [2/4] Loss: 0.22446 focal_loss 0.09907 dice_loss 0.12539 +Epoch [1168/4000] Validation [3/4] Loss: 0.20366 focal_loss 0.11656 dice_loss 0.08711 +Epoch [1168/4000] Validation [4/4] Loss: 0.31709 focal_loss 0.19046 dice_loss 0.12664 +Epoch [1168/4000] Validation metric {'Val/mean dice_metric': 0.9705638885498047, 'Val/mean miou_metric': 0.9518098831176758, 'Val/mean f1': 0.971534788608551, 'Val/mean precision': 0.9705837368965149, 'Val/mean recall': 0.9724876284599304, 'Val/mean hd95_metric': 5.282722473144531} +Cheakpoint... +Epoch [1168/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705638885498047, 'Val/mean miou_metric': 0.9518098831176758, 'Val/mean f1': 0.971534788608551, 'Val/mean precision': 0.9705837368965149, 'Val/mean recall': 0.9724876284599304, 'Val/mean hd95_metric': 5.282722473144531} +Epoch [1169/4000] Training [1/16] Loss: 0.00800 +Epoch [1169/4000] Training [2/16] Loss: 0.00811 +Epoch [1169/4000] Training [3/16] Loss: 0.01015 +Epoch [1169/4000] Training [4/16] Loss: 0.00865 +Epoch [1169/4000] Training [5/16] Loss: 0.01214 +Epoch [1169/4000] Training [6/16] Loss: 0.01012 +Epoch [1169/4000] Training [7/16] Loss: 0.01065 +Epoch [1169/4000] Training [8/16] Loss: 0.00936 +Epoch [1169/4000] Training [9/16] Loss: 0.01075 +Epoch [1169/4000] Training [10/16] Loss: 0.00918 +Epoch [1169/4000] Training [11/16] Loss: 0.00868 +Epoch [1169/4000] Training [12/16] Loss: 0.01202 +Epoch [1169/4000] Training [13/16] Loss: 0.01077 +Epoch [1169/4000] Training [14/16] Loss: 0.01103 +Epoch [1169/4000] Training [15/16] Loss: 0.00869 +Epoch [1169/4000] Training [16/16] Loss: 0.00913 +Epoch [1169/4000] Training metric {'Train/mean dice_metric': 0.9925358891487122, 'Train/mean miou_metric': 0.9851469993591309, 'Train/mean f1': 0.9889931082725525, 'Train/mean precision': 0.9849169254302979, 'Train/mean recall': 0.9931032657623291, 'Train/mean hd95_metric': 1.4846041202545166} +Epoch [1169/4000] Validation [1/4] Loss: 0.42788 focal_loss 0.28261 dice_loss 0.14527 +Epoch [1169/4000] Validation [2/4] Loss: 0.46359 focal_loss 0.25257 dice_loss 0.21102 +Epoch [1169/4000] Validation [3/4] Loss: 0.14360 focal_loss 0.08625 dice_loss 0.05735 +Epoch [1169/4000] Validation [4/4] Loss: 0.25854 focal_loss 0.15101 dice_loss 0.10753 +Epoch [1169/4000] Validation metric {'Val/mean dice_metric': 0.9653706550598145, 'Val/mean miou_metric': 0.9461167454719543, 'Val/mean f1': 0.9688891768455505, 'Val/mean precision': 0.972319483757019, 'Val/mean recall': 0.9654828310012817, 'Val/mean hd95_metric': 5.710680961608887} +Cheakpoint... +Epoch [1169/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653706550598145, 'Val/mean miou_metric': 0.9461167454719543, 'Val/mean f1': 0.9688891768455505, 'Val/mean precision': 0.972319483757019, 'Val/mean recall': 0.9654828310012817, 'Val/mean hd95_metric': 5.710680961608887} +Epoch [1170/4000] Training [1/16] Loss: 0.01148 +Epoch [1170/4000] Training [2/16] Loss: 0.00867 +Epoch [1170/4000] Training [3/16] Loss: 0.01117 +Epoch [1170/4000] Training [4/16] Loss: 0.00991 +Epoch [1170/4000] Training [5/16] Loss: 0.00960 +Epoch [1170/4000] Training [6/16] Loss: 0.01197 +Epoch [1170/4000] Training [7/16] Loss: 0.01141 +Epoch [1170/4000] Training [8/16] Loss: 0.01438 +Epoch [1170/4000] Training [9/16] Loss: 0.00848 +Epoch [1170/4000] Training [10/16] Loss: 0.00966 +Epoch [1170/4000] Training [11/16] Loss: 0.00941 +Epoch [1170/4000] Training [12/16] Loss: 0.01034 +Epoch [1170/4000] Training [13/16] Loss: 0.00990 +Epoch [1170/4000] Training [14/16] Loss: 0.01189 +Epoch [1170/4000] Training [15/16] Loss: 0.01168 +Epoch [1170/4000] Training [16/16] Loss: 0.01043 +Epoch [1170/4000] Training metric {'Train/mean dice_metric': 0.9922752380371094, 'Train/mean miou_metric': 0.9844673275947571, 'Train/mean f1': 0.9885303378105164, 'Train/mean precision': 0.9839334487915039, 'Train/mean recall': 0.9931703805923462, 'Train/mean hd95_metric': 1.8639118671417236} +Epoch [1170/4000] Validation [1/4] Loss: 0.28110 focal_loss 0.19830 dice_loss 0.08280 +Epoch [1170/4000] Validation [2/4] Loss: 0.26501 focal_loss 0.11970 dice_loss 0.14531 +Epoch [1170/4000] Validation [3/4] Loss: 0.15531 focal_loss 0.09423 dice_loss 0.06109 +Epoch [1170/4000] Validation [4/4] Loss: 0.19935 focal_loss 0.09355 dice_loss 0.10580 +Epoch [1170/4000] Validation metric {'Val/mean dice_metric': 0.9674100875854492, 'Val/mean miou_metric': 0.9475892782211304, 'Val/mean f1': 0.9685474038124084, 'Val/mean precision': 0.9670360684394836, 'Val/mean recall': 0.9700633883476257, 'Val/mean hd95_metric': 7.167747974395752} +Cheakpoint... +Epoch [1170/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674100875854492, 'Val/mean miou_metric': 0.9475892782211304, 'Val/mean f1': 0.9685474038124084, 'Val/mean precision': 0.9670360684394836, 'Val/mean recall': 0.9700633883476257, 'Val/mean hd95_metric': 7.167747974395752} +Epoch [1171/4000] Training [1/16] Loss: 0.01025 +Epoch [1171/4000] Training [2/16] Loss: 0.01181 +Epoch [1171/4000] Training [3/16] Loss: 0.00993 +Epoch [1171/4000] Training [4/16] Loss: 0.01258 +Epoch [1171/4000] Training [5/16] Loss: 0.01100 +Epoch [1171/4000] Training [6/16] Loss: 0.00984 +Epoch [1171/4000] Training [7/16] Loss: 0.00993 +Epoch [1171/4000] Training [8/16] Loss: 0.01077 +Epoch [1171/4000] Training [9/16] Loss: 0.01124 +Epoch [1171/4000] Training [10/16] Loss: 0.01175 +Epoch [1171/4000] Training [11/16] Loss: 0.01181 +Epoch [1171/4000] Training [12/16] Loss: 0.01301 +Epoch [1171/4000] Training [13/16] Loss: 0.01759 +Epoch [1171/4000] Training [14/16] Loss: 0.00886 +Epoch [1171/4000] Training [15/16] Loss: 0.01004 +Epoch [1171/4000] Training [16/16] Loss: 0.00729 +Epoch [1171/4000] Training metric {'Train/mean dice_metric': 0.9922976493835449, 'Train/mean miou_metric': 0.9845752716064453, 'Train/mean f1': 0.9883565306663513, 'Train/mean precision': 0.9838004112243652, 'Train/mean recall': 0.9929550886154175, 'Train/mean hd95_metric': 1.5681291818618774} +Epoch [1171/4000] Validation [1/4] Loss: 0.14137 focal_loss 0.08399 dice_loss 0.05738 +Epoch [1171/4000] Validation [2/4] Loss: 0.37177 focal_loss 0.17527 dice_loss 0.19650 +Epoch [1171/4000] Validation [3/4] Loss: 0.24009 focal_loss 0.13612 dice_loss 0.10397 +Epoch [1171/4000] Validation [4/4] Loss: 0.37461 focal_loss 0.23052 dice_loss 0.14409 +Epoch [1171/4000] Validation metric {'Val/mean dice_metric': 0.9694172143936157, 'Val/mean miou_metric': 0.949393630027771, 'Val/mean f1': 0.9703409075737, 'Val/mean precision': 0.9691134095191956, 'Val/mean recall': 0.9715714454650879, 'Val/mean hd95_metric': 6.5239763259887695} +Cheakpoint... +Epoch [1171/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694172143936157, 'Val/mean miou_metric': 0.949393630027771, 'Val/mean f1': 0.9703409075737, 'Val/mean precision': 0.9691134095191956, 'Val/mean recall': 0.9715714454650879, 'Val/mean hd95_metric': 6.5239763259887695} +Epoch [1172/4000] Training [1/16] Loss: 0.01278 +Epoch [1172/4000] Training [2/16] Loss: 0.01296 +Epoch [1172/4000] Training [3/16] Loss: 0.00988 +Epoch [1172/4000] Training [4/16] Loss: 0.01532 +Epoch [1172/4000] Training [5/16] Loss: 0.01122 +Epoch [1172/4000] Training [6/16] Loss: 0.00915 +Epoch [1172/4000] Training [7/16] Loss: 0.01046 +Epoch [1172/4000] Training [8/16] Loss: 0.01134 +Epoch [1172/4000] Training [9/16] Loss: 0.01053 +Epoch [1172/4000] Training [10/16] Loss: 0.01162 +Epoch [1172/4000] Training [11/16] Loss: 0.01875 +Epoch [1172/4000] Training [12/16] Loss: 0.00914 +Epoch [1172/4000] Training [13/16] Loss: 0.00827 +Epoch [1172/4000] Training [14/16] Loss: 0.01244 +Epoch [1172/4000] Training [15/16] Loss: 0.01217 +Epoch [1172/4000] Training [16/16] Loss: 0.00999 +Epoch [1172/4000] Training metric {'Train/mean dice_metric': 0.9926033020019531, 'Train/mean miou_metric': 0.9851111173629761, 'Train/mean f1': 0.988866925239563, 'Train/mean precision': 0.9843526482582092, 'Train/mean recall': 0.9934228658676147, 'Train/mean hd95_metric': 1.214461088180542} +Epoch [1172/4000] Validation [1/4] Loss: 0.21115 focal_loss 0.14165 dice_loss 0.06950 +Epoch [1172/4000] Validation [2/4] Loss: 0.25021 focal_loss 0.11568 dice_loss 0.13453 +Epoch [1172/4000] Validation [3/4] Loss: 0.24787 focal_loss 0.14753 dice_loss 0.10033 +Epoch [1172/4000] Validation [4/4] Loss: 0.18010 focal_loss 0.08922 dice_loss 0.09088 +Epoch [1172/4000] Validation metric {'Val/mean dice_metric': 0.969670295715332, 'Val/mean miou_metric': 0.9498919248580933, 'Val/mean f1': 0.9708054661750793, 'Val/mean precision': 0.9610170125961304, 'Val/mean recall': 0.9807954430580139, 'Val/mean hd95_metric': 6.421852111816406} +Cheakpoint... +Epoch [1172/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969670295715332, 'Val/mean miou_metric': 0.9498919248580933, 'Val/mean f1': 0.9708054661750793, 'Val/mean precision': 0.9610170125961304, 'Val/mean recall': 0.9807954430580139, 'Val/mean hd95_metric': 6.421852111816406} +Epoch [1173/4000] Training [1/16] Loss: 0.01227 +Epoch [1173/4000] Training [2/16] Loss: 0.00850 +Epoch [1173/4000] Training [3/16] Loss: 0.00899 +Epoch [1173/4000] Training [4/16] Loss: 0.01012 +Epoch [1173/4000] Training [5/16] Loss: 0.01041 +Epoch [1173/4000] Training [6/16] Loss: 0.00983 +Epoch [1173/4000] Training [7/16] Loss: 0.01346 +Epoch [1173/4000] Training [8/16] Loss: 0.00958 +Epoch [1173/4000] Training [9/16] Loss: 0.01116 +Epoch [1173/4000] Training [10/16] Loss: 0.00922 +Epoch [1173/4000] Training [11/16] Loss: 0.01139 +Epoch [1173/4000] Training [12/16] Loss: 0.00937 +Epoch [1173/4000] Training [13/16] Loss: 0.01269 +Epoch [1173/4000] Training [14/16] Loss: 0.01470 +Epoch [1173/4000] Training [15/16] Loss: 0.01054 +Epoch [1173/4000] Training [16/16] Loss: 0.01020 +Epoch [1173/4000] Training metric {'Train/mean dice_metric': 0.9922575950622559, 'Train/mean miou_metric': 0.9844377636909485, 'Train/mean f1': 0.9877529740333557, 'Train/mean precision': 0.982870876789093, 'Train/mean recall': 0.9926837086677551, 'Train/mean hd95_metric': 1.9873237609863281} +Epoch [1173/4000] Validation [1/4] Loss: 0.26874 focal_loss 0.18325 dice_loss 0.08549 +Epoch [1173/4000] Validation [2/4] Loss: 0.55522 focal_loss 0.30838 dice_loss 0.24684 +Epoch [1173/4000] Validation [3/4] Loss: 0.29748 focal_loss 0.18957 dice_loss 0.10791 +Epoch [1173/4000] Validation [4/4] Loss: 0.22300 focal_loss 0.11299 dice_loss 0.11000 +Epoch [1173/4000] Validation metric {'Val/mean dice_metric': 0.9675489664077759, 'Val/mean miou_metric': 0.947597324848175, 'Val/mean f1': 0.966643750667572, 'Val/mean precision': 0.959871232509613, 'Val/mean recall': 0.9735124707221985, 'Val/mean hd95_metric': 6.80231237411499} +Cheakpoint... +Epoch [1173/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675489664077759, 'Val/mean miou_metric': 0.947597324848175, 'Val/mean f1': 0.966643750667572, 'Val/mean precision': 0.959871232509613, 'Val/mean recall': 0.9735124707221985, 'Val/mean hd95_metric': 6.80231237411499} +Epoch [1174/4000] Training [1/16] Loss: 0.00839 +Epoch [1174/4000] Training [2/16] Loss: 0.01228 +Epoch [1174/4000] Training [3/16] Loss: 0.01059 +Epoch [1174/4000] Training [4/16] Loss: 0.00881 +Epoch [1174/4000] Training [5/16] Loss: 0.00945 +Epoch [1174/4000] Training [6/16] Loss: 0.00982 +Epoch [1174/4000] Training [7/16] Loss: 0.01050 +Epoch [1174/4000] Training [8/16] Loss: 0.00854 +Epoch [1174/4000] Training [9/16] Loss: 0.01089 +Epoch [1174/4000] Training [10/16] Loss: 0.00998 +Epoch [1174/4000] Training [11/16] Loss: 0.01126 +Epoch [1174/4000] Training [12/16] Loss: 0.01397 +Epoch [1174/4000] Training [13/16] Loss: 0.01034 +Epoch [1174/4000] Training [14/16] Loss: 0.00958 +Epoch [1174/4000] Training [15/16] Loss: 0.00918 +Epoch [1174/4000] Training [16/16] Loss: 0.00952 +Epoch [1174/4000] Training metric {'Train/mean dice_metric': 0.9928030967712402, 'Train/mean miou_metric': 0.9855009317398071, 'Train/mean f1': 0.988692581653595, 'Train/mean precision': 0.9839091300964355, 'Train/mean recall': 0.9935227036476135, 'Train/mean hd95_metric': 1.37738835811615} +Epoch [1174/4000] Validation [1/4] Loss: 0.44656 focal_loss 0.32513 dice_loss 0.12143 +Epoch [1174/4000] Validation [2/4] Loss: 0.42320 focal_loss 0.20509 dice_loss 0.21811 +Epoch [1174/4000] Validation [3/4] Loss: 0.25515 focal_loss 0.16423 dice_loss 0.09092 +Epoch [1174/4000] Validation [4/4] Loss: 0.18864 focal_loss 0.09670 dice_loss 0.09194 +Epoch [1174/4000] Validation metric {'Val/mean dice_metric': 0.9679557085037231, 'Val/mean miou_metric': 0.9485065340995789, 'Val/mean f1': 0.965968906879425, 'Val/mean precision': 0.9588994979858398, 'Val/mean recall': 0.9731433391571045, 'Val/mean hd95_metric': 6.63709020614624} +Cheakpoint... +Epoch [1174/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679557085037231, 'Val/mean miou_metric': 0.9485065340995789, 'Val/mean f1': 0.965968906879425, 'Val/mean precision': 0.9588994979858398, 'Val/mean recall': 0.9731433391571045, 'Val/mean hd95_metric': 6.63709020614624} +Epoch [1175/4000] Training [1/16] Loss: 0.00728 +Epoch [1175/4000] Training [2/16] Loss: 0.01089 +Epoch [1175/4000] Training [3/16] Loss: 0.00952 +Epoch [1175/4000] Training [4/16] Loss: 0.00851 +Epoch [1175/4000] Training [5/16] Loss: 0.01027 +Epoch [1175/4000] Training [6/16] Loss: 0.00919 +Epoch [1175/4000] Training [7/16] Loss: 0.01122 +Epoch [1175/4000] Training [8/16] Loss: 0.01374 +Epoch [1175/4000] Training [9/16] Loss: 0.01065 +Epoch [1175/4000] Training [10/16] Loss: 0.01101 +Epoch [1175/4000] Training [11/16] Loss: 0.01031 +Epoch [1175/4000] Training [12/16] Loss: 0.01133 +Epoch [1175/4000] Training [13/16] Loss: 0.01222 +Epoch [1175/4000] Training [14/16] Loss: 0.00730 +Epoch [1175/4000] Training [15/16] Loss: 0.01036 +Epoch [1175/4000] Training [16/16] Loss: 0.01264 +Epoch [1175/4000] Training metric {'Train/mean dice_metric': 0.9926835894584656, 'Train/mean miou_metric': 0.9853007793426514, 'Train/mean f1': 0.9883486032485962, 'Train/mean precision': 0.9837929606437683, 'Train/mean recall': 0.9929466843605042, 'Train/mean hd95_metric': 1.5352650880813599} +Epoch [1175/4000] Validation [1/4] Loss: 0.25513 focal_loss 0.16736 dice_loss 0.08778 +Epoch [1175/4000] Validation [2/4] Loss: 0.48501 focal_loss 0.26038 dice_loss 0.22463 +Epoch [1175/4000] Validation [3/4] Loss: 0.15298 focal_loss 0.08907 dice_loss 0.06391 +Epoch [1175/4000] Validation [4/4] Loss: 0.33835 focal_loss 0.20784 dice_loss 0.13051 +Epoch [1175/4000] Validation metric {'Val/mean dice_metric': 0.9688583612442017, 'Val/mean miou_metric': 0.9497729539871216, 'Val/mean f1': 0.9705662727355957, 'Val/mean precision': 0.9675160050392151, 'Val/mean recall': 0.9736359715461731, 'Val/mean hd95_metric': 6.268431663513184} +Cheakpoint... +Epoch [1175/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688583612442017, 'Val/mean miou_metric': 0.9497729539871216, 'Val/mean f1': 0.9705662727355957, 'Val/mean precision': 0.9675160050392151, 'Val/mean recall': 0.9736359715461731, 'Val/mean hd95_metric': 6.268431663513184} +Epoch [1176/4000] Training [1/16] Loss: 0.01051 +Epoch [1176/4000] Training [2/16] Loss: 0.01197 +Epoch [1176/4000] Training [3/16] Loss: 0.00907 +Epoch [1176/4000] Training [4/16] Loss: 0.01159 +Epoch [1176/4000] Training [5/16] Loss: 0.00959 +Epoch [1176/4000] Training [6/16] Loss: 0.01349 +Epoch [1176/4000] Training [7/16] Loss: 0.01982 +Epoch [1176/4000] Training [8/16] Loss: 0.00866 +Epoch [1176/4000] Training [9/16] Loss: 0.01118 +Epoch [1176/4000] Training [10/16] Loss: 0.00865 +Epoch [1176/4000] Training [11/16] Loss: 0.00997 +Epoch [1176/4000] Training [12/16] Loss: 0.00967 +Epoch [1176/4000] Training [13/16] Loss: 0.01022 +Epoch [1176/4000] Training [14/16] Loss: 0.00768 +Epoch [1176/4000] Training [15/16] Loss: 0.01285 +Epoch [1176/4000] Training [16/16] Loss: 0.01315 +Epoch [1176/4000] Training metric {'Train/mean dice_metric': 0.9930660128593445, 'Train/mean miou_metric': 0.9859815835952759, 'Train/mean f1': 0.988659679889679, 'Train/mean precision': 0.9838910102844238, 'Train/mean recall': 0.9934748411178589, 'Train/mean hd95_metric': 1.2350109815597534} +Epoch [1176/4000] Validation [1/4] Loss: 0.23448 focal_loss 0.15313 dice_loss 0.08135 +Epoch [1176/4000] Validation [2/4] Loss: 0.40120 focal_loss 0.18371 dice_loss 0.21749 +Epoch [1176/4000] Validation [3/4] Loss: 0.12774 focal_loss 0.07433 dice_loss 0.05341 +Epoch [1176/4000] Validation [4/4] Loss: 0.42920 focal_loss 0.28674 dice_loss 0.14246 +Epoch [1176/4000] Validation metric {'Val/mean dice_metric': 0.9674772024154663, 'Val/mean miou_metric': 0.9477140307426453, 'Val/mean f1': 0.9689643979072571, 'Val/mean precision': 0.9652596712112427, 'Val/mean recall': 0.9726976752281189, 'Val/mean hd95_metric': 6.398539066314697} +Cheakpoint... +Epoch [1176/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674772024154663, 'Val/mean miou_metric': 0.9477140307426453, 'Val/mean f1': 0.9689643979072571, 'Val/mean precision': 0.9652596712112427, 'Val/mean recall': 0.9726976752281189, 'Val/mean hd95_metric': 6.398539066314697} +Epoch [1177/4000] Training [1/16] Loss: 0.01074 +Epoch [1177/4000] Training [2/16] Loss: 0.00818 +Epoch [1177/4000] Training [3/16] Loss: 0.01061 +Epoch [1177/4000] Training [4/16] Loss: 0.00931 +Epoch [1177/4000] Training [5/16] Loss: 0.01049 +Epoch [1177/4000] Training [6/16] Loss: 0.01479 +Epoch [1177/4000] Training [7/16] Loss: 0.00915 +Epoch [1177/4000] Training [8/16] Loss: 0.01886 +Epoch [1177/4000] Training [9/16] Loss: 0.00888 +Epoch [1177/4000] Training [10/16] Loss: 0.01017 +Epoch [1177/4000] Training [11/16] Loss: 0.01509 +Epoch [1177/4000] Training [12/16] Loss: 0.00802 +Epoch [1177/4000] Training [13/16] Loss: 0.00938 +Epoch [1177/4000] Training [14/16] Loss: 0.00896 +Epoch [1177/4000] Training [15/16] Loss: 0.00951 +Epoch [1177/4000] Training [16/16] Loss: 0.01369 +Epoch [1177/4000] Training metric {'Train/mean dice_metric': 0.9927688837051392, 'Train/mean miou_metric': 0.985403299331665, 'Train/mean f1': 0.9888277053833008, 'Train/mean precision': 0.984018862247467, 'Train/mean recall': 0.9936838150024414, 'Train/mean hd95_metric': 1.405521273612976} +Epoch [1177/4000] Validation [1/4] Loss: 0.37320 focal_loss 0.25702 dice_loss 0.11618 +Epoch [1177/4000] Validation [2/4] Loss: 0.41563 focal_loss 0.19765 dice_loss 0.21798 +Epoch [1177/4000] Validation [3/4] Loss: 0.14485 focal_loss 0.07912 dice_loss 0.06574 +Epoch [1177/4000] Validation [4/4] Loss: 0.27128 focal_loss 0.13944 dice_loss 0.13184 +Epoch [1177/4000] Validation metric {'Val/mean dice_metric': 0.9674097299575806, 'Val/mean miou_metric': 0.9472141265869141, 'Val/mean f1': 0.969378650188446, 'Val/mean precision': 0.9699807167053223, 'Val/mean recall': 0.9687771797180176, 'Val/mean hd95_metric': 6.444781303405762} +Cheakpoint... +Epoch [1177/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674097299575806, 'Val/mean miou_metric': 0.9472141265869141, 'Val/mean f1': 0.969378650188446, 'Val/mean precision': 0.9699807167053223, 'Val/mean recall': 0.9687771797180176, 'Val/mean hd95_metric': 6.444781303405762} +Epoch [1178/4000] Training [1/16] Loss: 0.00914 +Epoch [1178/4000] Training [2/16] Loss: 0.00745 +Epoch [1178/4000] Training [3/16] Loss: 0.00922 +Epoch [1178/4000] Training [4/16] Loss: 0.01067 +Epoch [1178/4000] Training [5/16] Loss: 0.01340 +Epoch [1178/4000] Training [6/16] Loss: 0.00781 +Epoch [1178/4000] Training [7/16] Loss: 0.00798 +Epoch [1178/4000] Training [8/16] Loss: 0.00959 +Epoch [1178/4000] Training [9/16] Loss: 0.00866 +Epoch [1178/4000] Training [10/16] Loss: 0.00925 +Epoch [1178/4000] Training [11/16] Loss: 0.00996 +Epoch [1178/4000] Training [12/16] Loss: 0.01018 +Epoch [1178/4000] Training [13/16] Loss: 0.01122 +Epoch [1178/4000] Training [14/16] Loss: 0.01103 +Epoch [1178/4000] Training [15/16] Loss: 0.00998 +Epoch [1178/4000] Training [16/16] Loss: 0.00904 +Epoch [1178/4000] Training metric {'Train/mean dice_metric': 0.9934360980987549, 'Train/mean miou_metric': 0.9866709113121033, 'Train/mean f1': 0.9887433648109436, 'Train/mean precision': 0.9835306406021118, 'Train/mean recall': 0.9940115809440613, 'Train/mean hd95_metric': 1.1345908641815186} +Epoch [1178/4000] Validation [1/4] Loss: 0.46374 focal_loss 0.32658 dice_loss 0.13716 +Epoch [1178/4000] Validation [2/4] Loss: 0.41225 focal_loss 0.19784 dice_loss 0.21441 +Epoch [1178/4000] Validation [3/4] Loss: 0.16721 focal_loss 0.09346 dice_loss 0.07375 +Epoch [1178/4000] Validation [4/4] Loss: 0.38023 focal_loss 0.23195 dice_loss 0.14828 +Epoch [1178/4000] Validation metric {'Val/mean dice_metric': 0.9679826498031616, 'Val/mean miou_metric': 0.9483144879341125, 'Val/mean f1': 0.9700422286987305, 'Val/mean precision': 0.9671906232833862, 'Val/mean recall': 0.9729107618331909, 'Val/mean hd95_metric': 6.776752471923828} +Cheakpoint... +Epoch [1178/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679826498031616, 'Val/mean miou_metric': 0.9483144879341125, 'Val/mean f1': 0.9700422286987305, 'Val/mean precision': 0.9671906232833862, 'Val/mean recall': 0.9729107618331909, 'Val/mean hd95_metric': 6.776752471923828} +Epoch [1179/4000] Training [1/16] Loss: 0.00720 +Epoch [1179/4000] Training [2/16] Loss: 0.00899 +Epoch [1179/4000] Training [3/16] Loss: 0.00877 +Epoch [1179/4000] Training [4/16] Loss: 0.00919 +Epoch [1179/4000] Training [5/16] Loss: 0.00733 +Epoch [1179/4000] Training [6/16] Loss: 0.00991 +Epoch [1179/4000] Training [7/16] Loss: 0.00852 +Epoch [1179/4000] Training [8/16] Loss: 0.00925 +Epoch [1179/4000] Training [9/16] Loss: 0.01992 +Epoch [1179/4000] Training [10/16] Loss: 0.01123 +Epoch [1179/4000] Training [11/16] Loss: 0.00952 +Epoch [1179/4000] Training [12/16] Loss: 0.00768 +Epoch [1179/4000] Training [13/16] Loss: 0.00891 +Epoch [1179/4000] Training [14/16] Loss: 0.01143 +Epoch [1179/4000] Training [15/16] Loss: 0.00935 +Epoch [1179/4000] Training [16/16] Loss: 0.00848 +Epoch [1179/4000] Training metric {'Train/mean dice_metric': 0.9933241605758667, 'Train/mean miou_metric': 0.9864675998687744, 'Train/mean f1': 0.9889065623283386, 'Train/mean precision': 0.9837086200714111, 'Train/mean recall': 0.9941597580909729, 'Train/mean hd95_metric': 1.154971718788147} +Epoch [1179/4000] Validation [1/4] Loss: 0.35126 focal_loss 0.24633 dice_loss 0.10493 +Epoch [1179/4000] Validation [2/4] Loss: 0.47792 focal_loss 0.25161 dice_loss 0.22631 +Epoch [1179/4000] Validation [3/4] Loss: 0.17657 focal_loss 0.09801 dice_loss 0.07855 +Epoch [1179/4000] Validation [4/4] Loss: 0.25757 focal_loss 0.13589 dice_loss 0.12168 +Epoch [1179/4000] Validation metric {'Val/mean dice_metric': 0.9668992161750793, 'Val/mean miou_metric': 0.9471486806869507, 'Val/mean f1': 0.9690479040145874, 'Val/mean precision': 0.9644339680671692, 'Val/mean recall': 0.9737062454223633, 'Val/mean hd95_metric': 7.364144802093506} +Cheakpoint... +Epoch [1179/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668992161750793, 'Val/mean miou_metric': 0.9471486806869507, 'Val/mean f1': 0.9690479040145874, 'Val/mean precision': 0.9644339680671692, 'Val/mean recall': 0.9737062454223633, 'Val/mean hd95_metric': 7.364144802093506} +Epoch [1180/4000] Training [1/16] Loss: 0.01482 +Epoch [1180/4000] Training [2/16] Loss: 0.00954 +Epoch [1180/4000] Training [3/16] Loss: 0.00934 +Epoch [1180/4000] Training [4/16] Loss: 0.00932 +Epoch [1180/4000] Training [5/16] Loss: 0.00848 +Epoch [1180/4000] Training [6/16] Loss: 0.01107 +Epoch [1180/4000] Training [7/16] Loss: 0.00893 +Epoch [1180/4000] Training [8/16] Loss: 0.00860 +Epoch [1180/4000] Training [9/16] Loss: 0.01090 +Epoch [1180/4000] Training [10/16] Loss: 0.00882 +Epoch [1180/4000] Training [11/16] Loss: 0.00870 +Epoch [1180/4000] Training [12/16] Loss: 0.00976 +Epoch [1180/4000] Training [13/16] Loss: 0.00918 +Epoch [1180/4000] Training [14/16] Loss: 0.00936 +Epoch [1180/4000] Training [15/16] Loss: 0.00826 +Epoch [1180/4000] Training [16/16] Loss: 0.00963 +Epoch [1180/4000] Training metric {'Train/mean dice_metric': 0.9932160377502441, 'Train/mean miou_metric': 0.9862914085388184, 'Train/mean f1': 0.9895599484443665, 'Train/mean precision': 0.9849728941917419, 'Train/mean recall': 0.9941898584365845, 'Train/mean hd95_metric': 1.2565264701843262} +Epoch [1180/4000] Validation [1/4] Loss: 0.51706 focal_loss 0.37596 dice_loss 0.14109 +Epoch [1180/4000] Validation [2/4] Loss: 0.41354 focal_loss 0.19702 dice_loss 0.21652 +Epoch [1180/4000] Validation [3/4] Loss: 0.23014 focal_loss 0.13542 dice_loss 0.09472 +Epoch [1180/4000] Validation [4/4] Loss: 0.38996 focal_loss 0.23200 dice_loss 0.15797 +Epoch [1180/4000] Validation metric {'Val/mean dice_metric': 0.9655954241752625, 'Val/mean miou_metric': 0.945961594581604, 'Val/mean f1': 0.9699373841285706, 'Val/mean precision': 0.9692608714103699, 'Val/mean recall': 0.9706148505210876, 'Val/mean hd95_metric': 6.226543426513672} +Cheakpoint... +Epoch [1180/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655954241752625, 'Val/mean miou_metric': 0.945961594581604, 'Val/mean f1': 0.9699373841285706, 'Val/mean precision': 0.9692608714103699, 'Val/mean recall': 0.9706148505210876, 'Val/mean hd95_metric': 6.226543426513672} +Epoch [1181/4000] Training [1/16] Loss: 0.00903 +Epoch [1181/4000] Training [2/16] Loss: 0.00900 +Epoch [1181/4000] Training [3/16] Loss: 0.01331 +Epoch [1181/4000] Training [4/16] Loss: 0.00969 +Epoch [1181/4000] Training [5/16] Loss: 0.01259 +Epoch [1181/4000] Training [6/16] Loss: 0.01206 +Epoch [1181/4000] Training [7/16] Loss: 0.01023 +Epoch [1181/4000] Training [8/16] Loss: 0.00799 +Epoch [1181/4000] Training [9/16] Loss: 0.01252 +Epoch [1181/4000] Training [10/16] Loss: 0.01267 +Epoch [1181/4000] Training [11/16] Loss: 0.01229 +Epoch [1181/4000] Training [12/16] Loss: 0.01049 +Epoch [1181/4000] Training [13/16] Loss: 0.00856 +Epoch [1181/4000] Training [14/16] Loss: 0.01132 +Epoch [1181/4000] Training [15/16] Loss: 0.00931 +Epoch [1181/4000] Training [16/16] Loss: 0.01691 +Epoch [1181/4000] Training metric {'Train/mean dice_metric': 0.9919365048408508, 'Train/mean miou_metric': 0.9842658042907715, 'Train/mean f1': 0.9887277483940125, 'Train/mean precision': 0.9841808080673218, 'Train/mean recall': 0.9933168888092041, 'Train/mean hd95_metric': 1.1616802215576172} +Epoch [1181/4000] Validation [1/4] Loss: 0.53917 focal_loss 0.39398 dice_loss 0.14520 +Epoch [1181/4000] Validation [2/4] Loss: 0.46470 focal_loss 0.24658 dice_loss 0.21811 +Epoch [1181/4000] Validation [3/4] Loss: 0.16835 focal_loss 0.09147 dice_loss 0.07688 +Epoch [1181/4000] Validation [4/4] Loss: 0.30885 focal_loss 0.17052 dice_loss 0.13833 +Epoch [1181/4000] Validation metric {'Val/mean dice_metric': 0.9633609056472778, 'Val/mean miou_metric': 0.9430456161499023, 'Val/mean f1': 0.9674221873283386, 'Val/mean precision': 0.9657090902328491, 'Val/mean recall': 0.96914142370224, 'Val/mean hd95_metric': 6.698793888092041} +Cheakpoint... +Epoch [1181/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9634], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633609056472778, 'Val/mean miou_metric': 0.9430456161499023, 'Val/mean f1': 0.9674221873283386, 'Val/mean precision': 0.9657090902328491, 'Val/mean recall': 0.96914142370224, 'Val/mean hd95_metric': 6.698793888092041} +Epoch [1182/4000] Training [1/16] Loss: 0.00920 +Epoch [1182/4000] Training [2/16] Loss: 0.00956 +Epoch [1182/4000] Training [3/16] Loss: 0.01171 +Epoch [1182/4000] Training [4/16] Loss: 0.00940 +Epoch [1182/4000] Training [5/16] Loss: 0.01009 +Epoch [1182/4000] Training [6/16] Loss: 0.01018 +Epoch [1182/4000] Training [7/16] Loss: 0.00827 +Epoch [1182/4000] Training [8/16] Loss: 0.01111 +Epoch [1182/4000] Training [9/16] Loss: 0.00941 +Epoch [1182/4000] Training [10/16] Loss: 0.00980 +Epoch [1182/4000] Training [11/16] Loss: 0.01210 +Epoch [1182/4000] Training [12/16] Loss: 0.01047 +Epoch [1182/4000] Training [13/16] Loss: 0.00999 +Epoch [1182/4000] Training [14/16] Loss: 0.00792 +Epoch [1182/4000] Training [15/16] Loss: 0.00913 +Epoch [1182/4000] Training [16/16] Loss: 0.00790 +Epoch [1182/4000] Training metric {'Train/mean dice_metric': 0.9934428930282593, 'Train/mean miou_metric': 0.9867339730262756, 'Train/mean f1': 0.9895886778831482, 'Train/mean precision': 0.985111653804779, 'Train/mean recall': 0.9941065907478333, 'Train/mean hd95_metric': 1.0738115310668945} +Epoch [1182/4000] Validation [1/4] Loss: 0.32777 focal_loss 0.21906 dice_loss 0.10871 +Epoch [1182/4000] Validation [2/4] Loss: 0.30685 focal_loss 0.14153 dice_loss 0.16531 +Epoch [1182/4000] Validation [3/4] Loss: 0.26343 focal_loss 0.16648 dice_loss 0.09695 +Epoch [1182/4000] Validation [4/4] Loss: 0.19981 focal_loss 0.10265 dice_loss 0.09716 +Epoch [1182/4000] Validation metric {'Val/mean dice_metric': 0.9693306088447571, 'Val/mean miou_metric': 0.9497228860855103, 'Val/mean f1': 0.9700232744216919, 'Val/mean precision': 0.9682075381278992, 'Val/mean recall': 0.9718459248542786, 'Val/mean hd95_metric': 6.268946170806885} +Cheakpoint... +Epoch [1182/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693306088447571, 'Val/mean miou_metric': 0.9497228860855103, 'Val/mean f1': 0.9700232744216919, 'Val/mean precision': 0.9682075381278992, 'Val/mean recall': 0.9718459248542786, 'Val/mean hd95_metric': 6.268946170806885} +Epoch [1183/4000] Training [1/16] Loss: 0.01197 +Epoch [1183/4000] Training [2/16] Loss: 0.00990 +Epoch [1183/4000] Training [3/16] Loss: 0.00848 +Epoch [1183/4000] Training [4/16] Loss: 0.00601 +Epoch [1183/4000] Training [5/16] Loss: 0.00717 +Epoch [1183/4000] Training [6/16] Loss: 0.00990 +Epoch [1183/4000] Training [7/16] Loss: 0.00715 +Epoch [1183/4000] Training [8/16] Loss: 0.01472 +Epoch [1183/4000] Training [9/16] Loss: 0.01077 +Epoch [1183/4000] Training [10/16] Loss: 0.00911 +Epoch [1183/4000] Training [11/16] Loss: 0.00937 +Epoch [1183/4000] Training [12/16] Loss: 0.00896 +Epoch [1183/4000] Training [13/16] Loss: 0.00996 +Epoch [1183/4000] Training [14/16] Loss: 0.01395 +Epoch [1183/4000] Training [15/16] Loss: 0.00974 +Epoch [1183/4000] Training [16/16] Loss: 0.01209 +Epoch [1183/4000] Training metric {'Train/mean dice_metric': 0.9927920699119568, 'Train/mean miou_metric': 0.9856805205345154, 'Train/mean f1': 0.9891528487205505, 'Train/mean precision': 0.9843730330467224, 'Train/mean recall': 0.9939793348312378, 'Train/mean hd95_metric': 1.6384878158569336} +Epoch [1183/4000] Validation [1/4] Loss: 0.28770 focal_loss 0.19057 dice_loss 0.09714 +Epoch [1183/4000] Validation [2/4] Loss: 0.35551 focal_loss 0.18055 dice_loss 0.17496 +Epoch [1183/4000] Validation [3/4] Loss: 0.29437 focal_loss 0.18857 dice_loss 0.10580 +Epoch [1183/4000] Validation [4/4] Loss: 0.26298 focal_loss 0.15114 dice_loss 0.11184 +Epoch [1183/4000] Validation metric {'Val/mean dice_metric': 0.9677969217300415, 'Val/mean miou_metric': 0.9481069445610046, 'Val/mean f1': 0.9707347750663757, 'Val/mean precision': 0.9652948975563049, 'Val/mean recall': 0.9762361645698547, 'Val/mean hd95_metric': 7.439291477203369} +Cheakpoint... +Epoch [1183/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677969217300415, 'Val/mean miou_metric': 0.9481069445610046, 'Val/mean f1': 0.9707347750663757, 'Val/mean precision': 0.9652948975563049, 'Val/mean recall': 0.9762361645698547, 'Val/mean hd95_metric': 7.439291477203369} +Epoch [1184/4000] Training [1/16] Loss: 0.00914 +Epoch [1184/4000] Training [2/16] Loss: 0.01245 +Epoch [1184/4000] Training [3/16] Loss: 0.01296 +Epoch [1184/4000] Training [4/16] Loss: 0.00941 +Epoch [1184/4000] Training [5/16] Loss: 0.00908 +Epoch [1184/4000] Training [6/16] Loss: 0.01159 +Epoch [1184/4000] Training [7/16] Loss: 0.01151 +Epoch [1184/4000] Training [8/16] Loss: 0.00867 +Epoch [1184/4000] Training [9/16] Loss: 0.01099 +Epoch [1184/4000] Training [10/16] Loss: 0.00908 +Epoch [1184/4000] Training [11/16] Loss: 0.01110 +Epoch [1184/4000] Training [12/16] Loss: 0.00921 +Epoch [1184/4000] Training [13/16] Loss: 0.00773 +Epoch [1184/4000] Training [14/16] Loss: 0.01194 +Epoch [1184/4000] Training [15/16] Loss: 0.00830 +Epoch [1184/4000] Training [16/16] Loss: 0.00911 +Epoch [1184/4000] Training metric {'Train/mean dice_metric': 0.9920816421508789, 'Train/mean miou_metric': 0.9848561882972717, 'Train/mean f1': 0.9890784621238708, 'Train/mean precision': 0.9844107627868652, 'Train/mean recall': 0.9937906265258789, 'Train/mean hd95_metric': 1.6047546863555908} +Epoch [1184/4000] Validation [1/4] Loss: 0.29176 focal_loss 0.18408 dice_loss 0.10768 +Epoch [1184/4000] Validation [2/4] Loss: 0.22874 focal_loss 0.10984 dice_loss 0.11890 +Epoch [1184/4000] Validation [3/4] Loss: 0.27465 focal_loss 0.18204 dice_loss 0.09261 +Epoch [1184/4000] Validation [4/4] Loss: 0.30404 focal_loss 0.18430 dice_loss 0.11974 +Epoch [1184/4000] Validation metric {'Val/mean dice_metric': 0.9679247140884399, 'Val/mean miou_metric': 0.9485338926315308, 'Val/mean f1': 0.9717175960540771, 'Val/mean precision': 0.9678980708122253, 'Val/mean recall': 0.9755674600601196, 'Val/mean hd95_metric': 6.744541168212891} +Cheakpoint... +Epoch [1184/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679247140884399, 'Val/mean miou_metric': 0.9485338926315308, 'Val/mean f1': 0.9717175960540771, 'Val/mean precision': 0.9678980708122253, 'Val/mean recall': 0.9755674600601196, 'Val/mean hd95_metric': 6.744541168212891} +Epoch [1185/4000] Training [1/16] Loss: 0.01269 +Epoch [1185/4000] Training [2/16] Loss: 0.00940 +Epoch [1185/4000] Training [3/16] Loss: 0.01386 +Epoch [1185/4000] Training [4/16] Loss: 0.01173 +Epoch [1185/4000] Training [5/16] Loss: 0.01240 +Epoch [1185/4000] Training [6/16] Loss: 0.01150 +Epoch [1185/4000] Training [7/16] Loss: 0.01355 +Epoch [1185/4000] Training [8/16] Loss: 0.00997 +Epoch [1185/4000] Training [9/16] Loss: 0.00867 +Epoch [1185/4000] Training [10/16] Loss: 0.00888 +Epoch [1185/4000] Training [11/16] Loss: 0.01891 +Epoch [1185/4000] Training [12/16] Loss: 0.01017 +Epoch [1185/4000] Training [13/16] Loss: 0.01069 +Epoch [1185/4000] Training [14/16] Loss: 0.01087 +Epoch [1185/4000] Training [15/16] Loss: 0.01944 +Epoch [1185/4000] Training [16/16] Loss: 0.01109 +Epoch [1185/4000] Training metric {'Train/mean dice_metric': 0.9916243553161621, 'Train/mean miou_metric': 0.9833182096481323, 'Train/mean f1': 0.9877997040748596, 'Train/mean precision': 0.9831873178482056, 'Train/mean recall': 0.9924554824829102, 'Train/mean hd95_metric': 1.6055760383605957} +Epoch [1185/4000] Validation [1/4] Loss: 0.33519 focal_loss 0.21803 dice_loss 0.11715 +Epoch [1185/4000] Validation [2/4] Loss: 0.31461 focal_loss 0.14282 dice_loss 0.17179 +Epoch [1185/4000] Validation [3/4] Loss: 0.12661 focal_loss 0.06735 dice_loss 0.05926 +Epoch [1185/4000] Validation [4/4] Loss: 0.32990 focal_loss 0.18114 dice_loss 0.14876 +Epoch [1185/4000] Validation metric {'Val/mean dice_metric': 0.9662887454032898, 'Val/mean miou_metric': 0.9455875158309937, 'Val/mean f1': 0.9680861830711365, 'Val/mean precision': 0.9631179571151733, 'Val/mean recall': 0.9731058478355408, 'Val/mean hd95_metric': 7.3138556480407715} +Cheakpoint... +Epoch [1185/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662887454032898, 'Val/mean miou_metric': 0.9455875158309937, 'Val/mean f1': 0.9680861830711365, 'Val/mean precision': 0.9631179571151733, 'Val/mean recall': 0.9731058478355408, 'Val/mean hd95_metric': 7.3138556480407715} +Epoch [1186/4000] Training [1/16] Loss: 0.01193 +Epoch [1186/4000] Training [2/16] Loss: 0.01077 +Epoch [1186/4000] Training [3/16] Loss: 0.01385 +Epoch [1186/4000] Training [4/16] Loss: 0.00933 +Epoch [1186/4000] Training [5/16] Loss: 0.01333 +Epoch [1186/4000] Training [6/16] Loss: 0.01140 +Epoch [1186/4000] Training [7/16] Loss: 0.02162 +Epoch [1186/4000] Training [8/16] Loss: 0.00923 +Epoch [1186/4000] Training [9/16] Loss: 0.01120 +Epoch [1186/4000] Training [10/16] Loss: 0.00797 +Epoch [1186/4000] Training [11/16] Loss: 0.01520 +Epoch [1186/4000] Training [12/16] Loss: 0.01081 +Epoch [1186/4000] Training [13/16] Loss: 0.00988 +Epoch [1186/4000] Training [14/16] Loss: 0.01098 +Epoch [1186/4000] Training [15/16] Loss: 0.01023 +Epoch [1186/4000] Training [16/16] Loss: 0.01075 +Epoch [1186/4000] Training metric {'Train/mean dice_metric': 0.9914129376411438, 'Train/mean miou_metric': 0.9828868508338928, 'Train/mean f1': 0.9875536561012268, 'Train/mean precision': 0.9837731719017029, 'Train/mean recall': 0.9913632869720459, 'Train/mean hd95_metric': 2.927945613861084} +Epoch [1186/4000] Validation [1/4] Loss: 1.08893 focal_loss 0.88477 dice_loss 0.20416 +Epoch [1186/4000] Validation [2/4] Loss: 0.55236 focal_loss 0.31564 dice_loss 0.23673 +Epoch [1186/4000] Validation [3/4] Loss: 0.16651 focal_loss 0.09730 dice_loss 0.06921 +Epoch [1186/4000] Validation [4/4] Loss: 0.44954 focal_loss 0.30936 dice_loss 0.14018 +Epoch [1186/4000] Validation metric {'Val/mean dice_metric': 0.964523196220398, 'Val/mean miou_metric': 0.9434834718704224, 'Val/mean f1': 0.9634506702423096, 'Val/mean precision': 0.9700056314468384, 'Val/mean recall': 0.9569838047027588, 'Val/mean hd95_metric': 7.354611396789551} +Cheakpoint... +Epoch [1186/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964523196220398, 'Val/mean miou_metric': 0.9434834718704224, 'Val/mean f1': 0.9634506702423096, 'Val/mean precision': 0.9700056314468384, 'Val/mean recall': 0.9569838047027588, 'Val/mean hd95_metric': 7.354611396789551} +Epoch [1187/4000] Training [1/16] Loss: 0.00919 +Epoch [1187/4000] Training [2/16] Loss: 0.01852 +Epoch [1187/4000] Training [3/16] Loss: 0.01113 +Epoch [1187/4000] Training [4/16] Loss: 0.01083 +Epoch [1187/4000] Training [5/16] Loss: 0.01153 +Epoch [1187/4000] Training [6/16] Loss: 0.01470 +Epoch [1187/4000] Training [7/16] Loss: 0.01161 +Epoch [1187/4000] Training [8/16] Loss: 0.00865 +Epoch [1187/4000] Training [9/16] Loss: 0.11544 +Epoch [1187/4000] Training [10/16] Loss: 0.05177 +Epoch [1187/4000] Training [11/16] Loss: 0.01309 +Epoch [1187/4000] Training [12/16] Loss: 0.00983 +Epoch [1187/4000] Training [13/16] Loss: 0.01124 +Epoch [1187/4000] Training [14/16] Loss: 0.01256 +Epoch [1187/4000] Training [15/16] Loss: 0.01635 +Epoch [1187/4000] Training [16/16] Loss: 0.01845 +Epoch [1187/4000] Training metric {'Train/mean dice_metric': 0.9875842332839966, 'Train/mean miou_metric': 0.977759063243866, 'Train/mean f1': 0.98497074842453, 'Train/mean precision': 0.979127824306488, 'Train/mean recall': 0.9908838272094727, 'Train/mean hd95_metric': 3.6236515045166016} +Epoch [1187/4000] Validation [1/4] Loss: 0.52889 focal_loss 0.36262 dice_loss 0.16627 +Epoch [1187/4000] Validation [2/4] Loss: 0.42007 focal_loss 0.21386 dice_loss 0.20621 +Epoch [1187/4000] Validation [3/4] Loss: 0.18330 focal_loss 0.09388 dice_loss 0.08942 +Epoch [1187/4000] Validation [4/4] Loss: 0.55792 focal_loss 0.35592 dice_loss 0.20199 +Epoch [1187/4000] Validation metric {'Val/mean dice_metric': 0.9583514928817749, 'Val/mean miou_metric': 0.9350044131278992, 'Val/mean f1': 0.9608950018882751, 'Val/mean precision': 0.955846905708313, 'Val/mean recall': 0.9659969210624695, 'Val/mean hd95_metric': 10.930624008178711} +Cheakpoint... +Epoch [1187/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9584], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9583514928817749, 'Val/mean miou_metric': 0.9350044131278992, 'Val/mean f1': 0.9608950018882751, 'Val/mean precision': 0.955846905708313, 'Val/mean recall': 0.9659969210624695, 'Val/mean hd95_metric': 10.930624008178711} +Epoch [1188/4000] Training [1/16] Loss: 0.01262 +Epoch [1188/4000] Training [2/16] Loss: 0.02341 +Epoch [1188/4000] Training [3/16] Loss: 0.01512 +Epoch [1188/4000] Training [4/16] Loss: 0.01697 +Epoch [1188/4000] Training [5/16] Loss: 0.01358 +Epoch [1188/4000] Training [6/16] Loss: 0.01864 +Epoch [1188/4000] Training [7/16] Loss: 0.01326 +Epoch [1188/4000] Training [8/16] Loss: 0.01049 +Epoch [1188/4000] Training [9/16] Loss: 0.01064 +Epoch [1188/4000] Training [10/16] Loss: 0.01559 +Epoch [1188/4000] Training [11/16] Loss: 0.01438 +Epoch [1188/4000] Training [12/16] Loss: 0.01299 +Epoch [1188/4000] Training [13/16] Loss: 0.01219 +Epoch [1188/4000] Training [14/16] Loss: 0.00948 +Epoch [1188/4000] Training [15/16] Loss: 0.01373 +Epoch [1188/4000] Training [16/16] Loss: 0.01947 +Epoch [1188/4000] Training metric {'Train/mean dice_metric': 0.9906094670295715, 'Train/mean miou_metric': 0.9812756776809692, 'Train/mean f1': 0.9865119457244873, 'Train/mean precision': 0.9820388555526733, 'Train/mean recall': 0.9910259246826172, 'Train/mean hd95_metric': 2.7429091930389404} +Epoch [1188/4000] Validation [1/4] Loss: 0.14629 focal_loss 0.08080 dice_loss 0.06550 +Epoch [1188/4000] Validation [2/4] Loss: 0.24210 focal_loss 0.11673 dice_loss 0.12537 +Epoch [1188/4000] Validation [3/4] Loss: 0.12842 focal_loss 0.06406 dice_loss 0.06436 +Epoch [1188/4000] Validation [4/4] Loss: 0.23164 focal_loss 0.11045 dice_loss 0.12119 +Epoch [1188/4000] Validation metric {'Val/mean dice_metric': 0.9676157832145691, 'Val/mean miou_metric': 0.946358323097229, 'Val/mean f1': 0.9686022400856018, 'Val/mean precision': 0.9633339047431946, 'Val/mean recall': 0.9739286303520203, 'Val/mean hd95_metric': 7.206638336181641} +Cheakpoint... +Epoch [1188/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676157832145691, 'Val/mean miou_metric': 0.946358323097229, 'Val/mean f1': 0.9686022400856018, 'Val/mean precision': 0.9633339047431946, 'Val/mean recall': 0.9739286303520203, 'Val/mean hd95_metric': 7.206638336181641} +Epoch [1189/4000] Training [1/16] Loss: 0.01211 +Epoch [1189/4000] Training [2/16] Loss: 0.01031 +Epoch [1189/4000] Training [3/16] Loss: 0.01016 +Epoch [1189/4000] Training [4/16] Loss: 0.01261 +Epoch [1189/4000] Training [5/16] Loss: 0.01556 +Epoch [1189/4000] Training [6/16] Loss: 0.01405 +Epoch [1189/4000] Training [7/16] Loss: 0.01268 +Epoch [1189/4000] Training [8/16] Loss: 0.00998 +Epoch [1189/4000] Training [9/16] Loss: 0.01216 +Epoch [1189/4000] Training [10/16] Loss: 0.01282 +Epoch [1189/4000] Training [11/16] Loss: 0.01262 +Epoch [1189/4000] Training [12/16] Loss: 0.01556 +Epoch [1189/4000] Training [13/16] Loss: 0.00932 +Epoch [1189/4000] Training [14/16] Loss: 0.01093 +Epoch [1189/4000] Training [15/16] Loss: 0.01190 +Epoch [1189/4000] Training [16/16] Loss: 0.01093 +Epoch [1189/4000] Training metric {'Train/mean dice_metric': 0.9903671741485596, 'Train/mean miou_metric': 0.9815223217010498, 'Train/mean f1': 0.9876258969306946, 'Train/mean precision': 0.9831903576850891, 'Train/mean recall': 0.9921016097068787, 'Train/mean hd95_metric': 1.544179916381836} +Epoch [1189/4000] Validation [1/4] Loss: 0.44238 focal_loss 0.32427 dice_loss 0.11811 +Epoch [1189/4000] Validation [2/4] Loss: 0.57207 focal_loss 0.32038 dice_loss 0.25169 +Epoch [1189/4000] Validation [3/4] Loss: 0.15786 focal_loss 0.09959 dice_loss 0.05827 +Epoch [1189/4000] Validation [4/4] Loss: 0.27339 focal_loss 0.16516 dice_loss 0.10823 +Epoch [1189/4000] Validation metric {'Val/mean dice_metric': 0.965101420879364, 'Val/mean miou_metric': 0.9443279504776001, 'Val/mean f1': 0.9680095911026001, 'Val/mean precision': 0.9660385251045227, 'Val/mean recall': 0.9699886441230774, 'Val/mean hd95_metric': 7.337255001068115} +Cheakpoint... +Epoch [1189/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965101420879364, 'Val/mean miou_metric': 0.9443279504776001, 'Val/mean f1': 0.9680095911026001, 'Val/mean precision': 0.9660385251045227, 'Val/mean recall': 0.9699886441230774, 'Val/mean hd95_metric': 7.337255001068115} +Epoch [1190/4000] Training [1/16] Loss: 0.01274 +Epoch [1190/4000] Training [2/16] Loss: 0.01192 +Epoch [1190/4000] Training [3/16] Loss: 0.01073 +Epoch [1190/4000] Training [4/16] Loss: 0.01159 +Epoch [1190/4000] Training [5/16] Loss: 0.01225 +Epoch [1190/4000] Training [6/16] Loss: 0.00832 +Epoch [1190/4000] Training [7/16] Loss: 0.01098 +Epoch [1190/4000] Training [8/16] Loss: 0.01246 +Epoch [1190/4000] Training [9/16] Loss: 0.01168 +Epoch [1190/4000] Training [10/16] Loss: 0.01201 +Epoch [1190/4000] Training [11/16] Loss: 0.01115 +Epoch [1190/4000] Training [12/16] Loss: 0.01151 +Epoch [1190/4000] Training [13/16] Loss: 0.01260 +Epoch [1190/4000] Training [14/16] Loss: 0.01994 +Epoch [1190/4000] Training [15/16] Loss: 0.00903 +Epoch [1190/4000] Training [16/16] Loss: 0.01053 +Epoch [1190/4000] Training metric {'Train/mean dice_metric': 0.9920167922973633, 'Train/mean miou_metric': 0.9839533567428589, 'Train/mean f1': 0.988470196723938, 'Train/mean precision': 0.9842728972434998, 'Train/mean recall': 0.9927034974098206, 'Train/mean hd95_metric': 1.2487049102783203} +Epoch [1190/4000] Validation [1/4] Loss: 0.44981 focal_loss 0.33186 dice_loss 0.11795 +Epoch [1190/4000] Validation [2/4] Loss: 0.23603 focal_loss 0.11343 dice_loss 0.12261 +Epoch [1190/4000] Validation [3/4] Loss: 0.26631 focal_loss 0.16635 dice_loss 0.09996 +Epoch [1190/4000] Validation [4/4] Loss: 0.44503 focal_loss 0.27638 dice_loss 0.16865 +Epoch [1190/4000] Validation metric {'Val/mean dice_metric': 0.9654279947280884, 'Val/mean miou_metric': 0.9452570080757141, 'Val/mean f1': 0.9671854376792908, 'Val/mean precision': 0.9636049270629883, 'Val/mean recall': 0.9707927107810974, 'Val/mean hd95_metric': 7.601266384124756} +Cheakpoint... +Epoch [1190/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654279947280884, 'Val/mean miou_metric': 0.9452570080757141, 'Val/mean f1': 0.9671854376792908, 'Val/mean precision': 0.9636049270629883, 'Val/mean recall': 0.9707927107810974, 'Val/mean hd95_metric': 7.601266384124756} +Epoch [1191/4000] Training [1/16] Loss: 0.01741 +Epoch [1191/4000] Training [2/16] Loss: 0.00958 +Epoch [1191/4000] Training [3/16] Loss: 0.01094 +Epoch [1191/4000] Training [4/16] Loss: 0.01184 +Epoch [1191/4000] Training [5/16] Loss: 0.01691 +Epoch [1191/4000] Training [6/16] Loss: 0.01190 +Epoch [1191/4000] Training [7/16] Loss: 0.00841 +Epoch [1191/4000] Training [8/16] Loss: 0.01980 +Epoch [1191/4000] Training [9/16] Loss: 0.01582 +Epoch [1191/4000] Training [10/16] Loss: 0.00817 +Epoch [1191/4000] Training [11/16] Loss: 0.01078 +Epoch [1191/4000] Training [12/16] Loss: 0.01200 +Epoch [1191/4000] Training [13/16] Loss: 0.00856 +Epoch [1191/4000] Training [14/16] Loss: 0.00938 +Epoch [1191/4000] Training [15/16] Loss: 0.00858 +Epoch [1191/4000] Training [16/16] Loss: 0.01040 +Epoch [1191/4000] Training metric {'Train/mean dice_metric': 0.9916149973869324, 'Train/mean miou_metric': 0.9833775758743286, 'Train/mean f1': 0.9874704480171204, 'Train/mean precision': 0.9834712743759155, 'Train/mean recall': 0.9915022253990173, 'Train/mean hd95_metric': 1.9738973379135132} +Epoch [1191/4000] Validation [1/4] Loss: 0.20363 focal_loss 0.13571 dice_loss 0.06792 +Epoch [1191/4000] Validation [2/4] Loss: 0.34561 focal_loss 0.19245 dice_loss 0.15316 +Epoch [1191/4000] Validation [3/4] Loss: 0.26410 focal_loss 0.15860 dice_loss 0.10550 +Epoch [1191/4000] Validation [4/4] Loss: 0.18974 focal_loss 0.09406 dice_loss 0.09568 +Epoch [1191/4000] Validation metric {'Val/mean dice_metric': 0.9683647155761719, 'Val/mean miou_metric': 0.9474083185195923, 'Val/mean f1': 0.9692071080207825, 'Val/mean precision': 0.9688703417778015, 'Val/mean recall': 0.9695441722869873, 'Val/mean hd95_metric': 6.424479007720947} +Cheakpoint... +Epoch [1191/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683647155761719, 'Val/mean miou_metric': 0.9474083185195923, 'Val/mean f1': 0.9692071080207825, 'Val/mean precision': 0.9688703417778015, 'Val/mean recall': 0.9695441722869873, 'Val/mean hd95_metric': 6.424479007720947} +Epoch [1192/4000] Training [1/16] Loss: 0.01132 +Epoch [1192/4000] Training [2/16] Loss: 0.00872 +Epoch [1192/4000] Training [3/16] Loss: 0.01069 +Epoch [1192/4000] Training [4/16] Loss: 0.01062 +Epoch [1192/4000] Training [5/16] Loss: 0.02694 +Epoch [1192/4000] Training [6/16] Loss: 0.07371 +Epoch [1192/4000] Training [7/16] Loss: 0.01154 +Epoch [1192/4000] Training [8/16] Loss: 0.01212 +Epoch [1192/4000] Training [9/16] Loss: 0.00866 +Epoch [1192/4000] Training [10/16] Loss: 0.01574 +Epoch [1192/4000] Training [11/16] Loss: 0.01379 +Epoch [1192/4000] Training [12/16] Loss: 0.01188 +Epoch [1192/4000] Training [13/16] Loss: 0.00936 +Epoch [1192/4000] Training [14/16] Loss: 0.00830 +Epoch [1192/4000] Training [15/16] Loss: 0.01334 +Epoch [1192/4000] Training [16/16] Loss: 0.01220 +Epoch [1192/4000] Training metric {'Train/mean dice_metric': 0.9913519620895386, 'Train/mean miou_metric': 0.9831249713897705, 'Train/mean f1': 0.9885318875312805, 'Train/mean precision': 0.9837903380393982, 'Train/mean recall': 0.9933192729949951, 'Train/mean hd95_metric': 1.7914904356002808} +Epoch [1192/4000] Validation [1/4] Loss: 0.18661 focal_loss 0.12372 dice_loss 0.06289 +Epoch [1192/4000] Validation [2/4] Loss: 0.42702 focal_loss 0.24180 dice_loss 0.18522 +Epoch [1192/4000] Validation [3/4] Loss: 0.15095 focal_loss 0.08833 dice_loss 0.06262 +Epoch [1192/4000] Validation [4/4] Loss: 0.18644 focal_loss 0.08921 dice_loss 0.09723 +Epoch [1192/4000] Validation metric {'Val/mean dice_metric': 0.9681105613708496, 'Val/mean miou_metric': 0.9477651715278625, 'Val/mean f1': 0.9707257747650146, 'Val/mean precision': 0.9662558436393738, 'Val/mean recall': 0.9752371907234192, 'Val/mean hd95_metric': 7.113293647766113} +Cheakpoint... +Epoch [1192/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681105613708496, 'Val/mean miou_metric': 0.9477651715278625, 'Val/mean f1': 0.9707257747650146, 'Val/mean precision': 0.9662558436393738, 'Val/mean recall': 0.9752371907234192, 'Val/mean hd95_metric': 7.113293647766113} +Epoch [1193/4000] Training [1/16] Loss: 0.00807 +Epoch [1193/4000] Training [2/16] Loss: 0.00998 +Epoch [1193/4000] Training [3/16] Loss: 0.01204 +Epoch [1193/4000] Training [4/16] Loss: 0.00926 +Epoch [1193/4000] Training [5/16] Loss: 0.01034 +Epoch [1193/4000] Training [6/16] Loss: 0.01275 +Epoch [1193/4000] Training [7/16] Loss: 0.01058 +Epoch [1193/4000] Training [8/16] Loss: 0.00853 +Epoch [1193/4000] Training [9/16] Loss: 0.00697 +Epoch [1193/4000] Training [10/16] Loss: 0.01084 +Epoch [1193/4000] Training [11/16] Loss: 0.02070 +Epoch [1193/4000] Training [12/16] Loss: 0.00875 +Epoch [1193/4000] Training [13/16] Loss: 0.01250 +Epoch [1193/4000] Training [14/16] Loss: 0.00816 +Epoch [1193/4000] Training [15/16] Loss: 0.00895 +Epoch [1193/4000] Training [16/16] Loss: 0.01131 +Epoch [1193/4000] Training metric {'Train/mean dice_metric': 0.9929087162017822, 'Train/mean miou_metric': 0.9856582880020142, 'Train/mean f1': 0.9883760809898376, 'Train/mean precision': 0.9832391142845154, 'Train/mean recall': 0.9935669898986816, 'Train/mean hd95_metric': 1.4548931121826172} +Epoch [1193/4000] Validation [1/4] Loss: 0.22037 focal_loss 0.14130 dice_loss 0.07907 +Epoch [1193/4000] Validation [2/4] Loss: 0.34413 focal_loss 0.16936 dice_loss 0.17477 +Epoch [1193/4000] Validation [3/4] Loss: 0.21943 focal_loss 0.12412 dice_loss 0.09531 +Epoch [1193/4000] Validation [4/4] Loss: 0.15958 focal_loss 0.08136 dice_loss 0.07822 +Epoch [1193/4000] Validation metric {'Val/mean dice_metric': 0.9663718938827515, 'Val/mean miou_metric': 0.9471426010131836, 'Val/mean f1': 0.9705473184585571, 'Val/mean precision': 0.9665200710296631, 'Val/mean recall': 0.9746084213256836, 'Val/mean hd95_metric': 7.734260559082031} +Cheakpoint... +Epoch [1193/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9664], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9663718938827515, 'Val/mean miou_metric': 0.9471426010131836, 'Val/mean f1': 0.9705473184585571, 'Val/mean precision': 0.9665200710296631, 'Val/mean recall': 0.9746084213256836, 'Val/mean hd95_metric': 7.734260559082031} +Epoch [1194/4000] Training [1/16] Loss: 0.00994 +Epoch [1194/4000] Training [2/16] Loss: 0.00966 +Epoch [1194/4000] Training [3/16] Loss: 0.00715 +Epoch [1194/4000] Training [4/16] Loss: 0.01066 +Epoch [1194/4000] Training [5/16] Loss: 0.00902 +Epoch [1194/4000] Training [6/16] Loss: 0.01047 +Epoch [1194/4000] Training [7/16] Loss: 0.01079 +Epoch [1194/4000] Training [8/16] Loss: 0.01114 +Epoch [1194/4000] Training [9/16] Loss: 0.00854 +Epoch [1194/4000] Training [10/16] Loss: 0.01417 +Epoch [1194/4000] Training [11/16] Loss: 0.01015 +Epoch [1194/4000] Training [12/16] Loss: 0.01041 +Epoch [1194/4000] Training [13/16] Loss: 0.00891 +Epoch [1194/4000] Training [14/16] Loss: 0.00922 +Epoch [1194/4000] Training [15/16] Loss: 0.00902 +Epoch [1194/4000] Training [16/16] Loss: 0.01519 +Epoch [1194/4000] Training metric {'Train/mean dice_metric': 0.9928871989250183, 'Train/mean miou_metric': 0.985653281211853, 'Train/mean f1': 0.9891230463981628, 'Train/mean precision': 0.9841190576553345, 'Train/mean recall': 0.994178295135498, 'Train/mean hd95_metric': 1.153247356414795} +Epoch [1194/4000] Validation [1/4] Loss: 0.18337 focal_loss 0.12159 dice_loss 0.06178 +Epoch [1194/4000] Validation [2/4] Loss: 0.24072 focal_loss 0.11341 dice_loss 0.12731 +Epoch [1194/4000] Validation [3/4] Loss: 0.13536 focal_loss 0.07430 dice_loss 0.06107 +Epoch [1194/4000] Validation [4/4] Loss: 0.22592 focal_loss 0.11609 dice_loss 0.10983 +Epoch [1194/4000] Validation metric {'Val/mean dice_metric': 0.9675658941268921, 'Val/mean miou_metric': 0.9489821195602417, 'Val/mean f1': 0.9722246527671814, 'Val/mean precision': 0.968121349811554, 'Val/mean recall': 0.9763628244400024, 'Val/mean hd95_metric': 5.674322605133057} +Cheakpoint... +Epoch [1194/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675658941268921, 'Val/mean miou_metric': 0.9489821195602417, 'Val/mean f1': 0.9722246527671814, 'Val/mean precision': 0.968121349811554, 'Val/mean recall': 0.9763628244400024, 'Val/mean hd95_metric': 5.674322605133057} +Epoch [1195/4000] Training [1/16] Loss: 0.00916 +Epoch [1195/4000] Training [2/16] Loss: 0.01019 +Epoch [1195/4000] Training [3/16] Loss: 0.00940 +Epoch [1195/4000] Training [4/16] Loss: 0.00917 +Epoch [1195/4000] Training [5/16] Loss: 0.00854 +Epoch [1195/4000] Training [6/16] Loss: 0.00951 +Epoch [1195/4000] Training [7/16] Loss: 0.01154 +Epoch [1195/4000] Training [8/16] Loss: 0.01133 +Epoch [1195/4000] Training [9/16] Loss: 0.00831 +Epoch [1195/4000] Training [10/16] Loss: 0.01245 +Epoch [1195/4000] Training [11/16] Loss: 0.01017 +Epoch [1195/4000] Training [12/16] Loss: 0.01200 +Epoch [1195/4000] Training [13/16] Loss: 0.01050 +Epoch [1195/4000] Training [14/16] Loss: 0.01108 +Epoch [1195/4000] Training [15/16] Loss: 0.00730 +Epoch [1195/4000] Training [16/16] Loss: 0.01350 +Epoch [1195/4000] Training metric {'Train/mean dice_metric': 0.9923758506774902, 'Train/mean miou_metric': 0.9847038984298706, 'Train/mean f1': 0.9883186221122742, 'Train/mean precision': 0.9836522340774536, 'Train/mean recall': 0.9930295348167419, 'Train/mean hd95_metric': 1.4215314388275146} +Epoch [1195/4000] Validation [1/4] Loss: 0.45164 focal_loss 0.35248 dice_loss 0.09916 +Epoch [1195/4000] Validation [2/4] Loss: 0.48912 focal_loss 0.29026 dice_loss 0.19886 +Epoch [1195/4000] Validation [3/4] Loss: 0.18690 focal_loss 0.09799 dice_loss 0.08892 +Epoch [1195/4000] Validation [4/4] Loss: 0.25131 focal_loss 0.12178 dice_loss 0.12952 +Epoch [1195/4000] Validation metric {'Val/mean dice_metric': 0.9654489755630493, 'Val/mean miou_metric': 0.94537353515625, 'Val/mean f1': 0.9641768336296082, 'Val/mean precision': 0.9534533023834229, 'Val/mean recall': 0.9751442670822144, 'Val/mean hd95_metric': 8.401412010192871} +Cheakpoint... +Epoch [1195/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654489755630493, 'Val/mean miou_metric': 0.94537353515625, 'Val/mean f1': 0.9641768336296082, 'Val/mean precision': 0.9534533023834229, 'Val/mean recall': 0.9751442670822144, 'Val/mean hd95_metric': 8.401412010192871} +Epoch [1196/4000] Training [1/16] Loss: 0.01056 +Epoch [1196/4000] Training [2/16] Loss: 0.01068 +Epoch [1196/4000] Training [3/16] Loss: 0.01190 +Epoch [1196/4000] Training [4/16] Loss: 0.00804 +Epoch [1196/4000] Training [5/16] Loss: 0.01072 +Epoch [1196/4000] Training [6/16] Loss: 0.01146 +Epoch [1196/4000] Training [7/16] Loss: 0.01031 +Epoch [1196/4000] Training [8/16] Loss: 0.01285 +Epoch [1196/4000] Training [9/16] Loss: 0.01380 +Epoch [1196/4000] Training [10/16] Loss: 0.01009 +Epoch [1196/4000] Training [11/16] Loss: 0.00973 +Epoch [1196/4000] Training [12/16] Loss: 0.01259 +Epoch [1196/4000] Training [13/16] Loss: 0.01072 +Epoch [1196/4000] Training [14/16] Loss: 0.01307 +Epoch [1196/4000] Training [15/16] Loss: 0.00900 +Epoch [1196/4000] Training [16/16] Loss: 0.00734 +Epoch [1196/4000] Training metric {'Train/mean dice_metric': 0.9918110370635986, 'Train/mean miou_metric': 0.9837268590927124, 'Train/mean f1': 0.986662745475769, 'Train/mean precision': 0.9814258813858032, 'Train/mean recall': 0.9919558167457581, 'Train/mean hd95_metric': 1.8666558265686035} +Epoch [1196/4000] Validation [1/4] Loss: 0.16797 focal_loss 0.10628 dice_loss 0.06169 +Epoch [1196/4000] Validation [2/4] Loss: 0.48317 focal_loss 0.25422 dice_loss 0.22894 +Epoch [1196/4000] Validation [3/4] Loss: 0.15879 focal_loss 0.09102 dice_loss 0.06778 +Epoch [1196/4000] Validation [4/4] Loss: 0.31405 focal_loss 0.20066 dice_loss 0.11339 +Epoch [1196/4000] Validation metric {'Val/mean dice_metric': 0.9658309817314148, 'Val/mean miou_metric': 0.9451274871826172, 'Val/mean f1': 0.9652488827705383, 'Val/mean precision': 0.9567884802818298, 'Val/mean recall': 0.9738603234291077, 'Val/mean hd95_metric': 7.9085588455200195} +Cheakpoint... +Epoch [1196/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658309817314148, 'Val/mean miou_metric': 0.9451274871826172, 'Val/mean f1': 0.9652488827705383, 'Val/mean precision': 0.9567884802818298, 'Val/mean recall': 0.9738603234291077, 'Val/mean hd95_metric': 7.9085588455200195} +Epoch [1197/4000] Training [1/16] Loss: 0.01175 +Epoch [1197/4000] Training [2/16] Loss: 0.00954 +Epoch [1197/4000] Training [3/16] Loss: 0.01043 +Epoch [1197/4000] Training [4/16] Loss: 0.01107 +Epoch [1197/4000] Training [5/16] Loss: 0.00805 +Epoch [1197/4000] Training [6/16] Loss: 0.00973 +Epoch [1197/4000] Training [7/16] Loss: 0.00961 +Epoch [1197/4000] Training [8/16] Loss: 0.00770 +Epoch [1197/4000] Training [9/16] Loss: 0.01251 +Epoch [1197/4000] Training [10/16] Loss: 0.01320 +Epoch [1197/4000] Training [11/16] Loss: 0.00960 +Epoch [1197/4000] Training [12/16] Loss: 0.00938 +Epoch [1197/4000] Training [13/16] Loss: 0.01189 +Epoch [1197/4000] Training [14/16] Loss: 0.01332 +Epoch [1197/4000] Training [15/16] Loss: 0.01036 +Epoch [1197/4000] Training [16/16] Loss: 0.01523 +Epoch [1197/4000] Training metric {'Train/mean dice_metric': 0.9924126267433167, 'Train/mean miou_metric': 0.9847163558006287, 'Train/mean f1': 0.9881131052970886, 'Train/mean precision': 0.9835350513458252, 'Train/mean recall': 0.9927340149879456, 'Train/mean hd95_metric': 1.5617105960845947} +Epoch [1197/4000] Validation [1/4] Loss: 0.36357 focal_loss 0.24908 dice_loss 0.11449 +Epoch [1197/4000] Validation [2/4] Loss: 0.35740 focal_loss 0.15275 dice_loss 0.20465 +Epoch [1197/4000] Validation [3/4] Loss: 0.21862 focal_loss 0.10692 dice_loss 0.11170 +Epoch [1197/4000] Validation [4/4] Loss: 0.22795 focal_loss 0.11051 dice_loss 0.11744 +Epoch [1197/4000] Validation metric {'Val/mean dice_metric': 0.9652708768844604, 'Val/mean miou_metric': 0.9444780349731445, 'Val/mean f1': 0.9632707238197327, 'Val/mean precision': 0.9518996477127075, 'Val/mean recall': 0.9749166369438171, 'Val/mean hd95_metric': 8.011030197143555} +Cheakpoint... +Epoch [1197/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652708768844604, 'Val/mean miou_metric': 0.9444780349731445, 'Val/mean f1': 0.9632707238197327, 'Val/mean precision': 0.9518996477127075, 'Val/mean recall': 0.9749166369438171, 'Val/mean hd95_metric': 8.011030197143555} +Epoch [1198/4000] Training [1/16] Loss: 0.00980 +Epoch [1198/4000] Training [2/16] Loss: 0.01336 +Epoch [1198/4000] Training [3/16] Loss: 0.01228 +Epoch [1198/4000] Training [4/16] Loss: 0.01109 +Epoch [1198/4000] Training [5/16] Loss: 0.01433 +Epoch [1198/4000] Training [6/16] Loss: 0.01268 +Epoch [1198/4000] Training [7/16] Loss: 0.01725 +Epoch [1198/4000] Training [8/16] Loss: 0.01183 +Epoch [1198/4000] Training [9/16] Loss: 0.01010 +Epoch [1198/4000] Training [10/16] Loss: 0.01152 +Epoch [1198/4000] Training [11/16] Loss: 0.01544 +Epoch [1198/4000] Training [12/16] Loss: 0.01186 +Epoch [1198/4000] Training [13/16] Loss: 0.01033 +Epoch [1198/4000] Training [14/16] Loss: 0.00945 +Epoch [1198/4000] Training [15/16] Loss: 0.01156 +Epoch [1198/4000] Training [16/16] Loss: 0.01042 +Epoch [1198/4000] Training metric {'Train/mean dice_metric': 0.9923511743545532, 'Train/mean miou_metric': 0.9846124649047852, 'Train/mean f1': 0.9884064793586731, 'Train/mean precision': 0.9839498996734619, 'Train/mean recall': 0.9929035902023315, 'Train/mean hd95_metric': 1.3335182666778564} +Epoch [1198/4000] Validation [1/4] Loss: 0.13688 focal_loss 0.07778 dice_loss 0.05910 +Epoch [1198/4000] Validation [2/4] Loss: 0.27479 focal_loss 0.11574 dice_loss 0.15905 +Epoch [1198/4000] Validation [3/4] Loss: 0.13669 focal_loss 0.07661 dice_loss 0.06008 +Epoch [1198/4000] Validation [4/4] Loss: 0.24214 focal_loss 0.12376 dice_loss 0.11837 +Epoch [1198/4000] Validation metric {'Val/mean dice_metric': 0.9681099057197571, 'Val/mean miou_metric': 0.9480740427970886, 'Val/mean f1': 0.9682735800743103, 'Val/mean precision': 0.9584400653839111, 'Val/mean recall': 0.9783110022544861, 'Val/mean hd95_metric': 7.390232086181641} +Cheakpoint... +Epoch [1198/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681099057197571, 'Val/mean miou_metric': 0.9480740427970886, 'Val/mean f1': 0.9682735800743103, 'Val/mean precision': 0.9584400653839111, 'Val/mean recall': 0.9783110022544861, 'Val/mean hd95_metric': 7.390232086181641} +Epoch [1199/4000] Training [1/16] Loss: 0.01033 +Epoch [1199/4000] Training [2/16] Loss: 0.00980 +Epoch [1199/4000] Training [3/16] Loss: 0.01869 +Epoch [1199/4000] Training [4/16] Loss: 0.00968 +Epoch [1199/4000] Training [5/16] Loss: 0.01286 +Epoch [1199/4000] Training [6/16] Loss: 0.01095 +Epoch [1199/4000] Training [7/16] Loss: 0.01800 +Epoch [1199/4000] Training [8/16] Loss: 0.01238 +Epoch [1199/4000] Training [9/16] Loss: 0.00986 +Epoch [1199/4000] Training [10/16] Loss: 0.00929 +Epoch [1199/4000] Training [11/16] Loss: 0.01115 +Epoch [1199/4000] Training [12/16] Loss: 0.01102 +Epoch [1199/4000] Training [13/16] Loss: 0.01104 +Epoch [1199/4000] Training [14/16] Loss: 0.01037 +Epoch [1199/4000] Training [15/16] Loss: 0.00860 +Epoch [1199/4000] Training [16/16] Loss: 0.01067 +Epoch [1199/4000] Training metric {'Train/mean dice_metric': 0.9926198720932007, 'Train/mean miou_metric': 0.9851436018943787, 'Train/mean f1': 0.9890002608299255, 'Train/mean precision': 0.9846093654632568, 'Train/mean recall': 0.9934304356575012, 'Train/mean hd95_metric': 1.7087594270706177} +Epoch [1199/4000] Validation [1/4] Loss: 0.92515 focal_loss 0.77186 dice_loss 0.15329 +Epoch [1199/4000] Validation [2/4] Loss: 0.27712 focal_loss 0.13499 dice_loss 0.14213 +Epoch [1199/4000] Validation [3/4] Loss: 0.22181 focal_loss 0.12161 dice_loss 0.10020 +Epoch [1199/4000] Validation [4/4] Loss: 0.24533 focal_loss 0.13842 dice_loss 0.10691 +Epoch [1199/4000] Validation metric {'Val/mean dice_metric': 0.9663200378417969, 'Val/mean miou_metric': 0.9458778500556946, 'Val/mean f1': 0.9654756784439087, 'Val/mean precision': 0.9616588950157166, 'Val/mean recall': 0.9693230390548706, 'Val/mean hd95_metric': 8.242504119873047} +Cheakpoint... +Epoch [1199/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9663200378417969, 'Val/mean miou_metric': 0.9458778500556946, 'Val/mean f1': 0.9654756784439087, 'Val/mean precision': 0.9616588950157166, 'Val/mean recall': 0.9693230390548706, 'Val/mean hd95_metric': 8.242504119873047} +Epoch [1200/4000] Training [1/16] Loss: 0.01009 +Epoch [1200/4000] Training [2/16] Loss: 0.00826 +Epoch [1200/4000] Training [3/16] Loss: 0.01013 +Epoch [1200/4000] Training [4/16] Loss: 0.00867 +Epoch [1200/4000] Training [5/16] Loss: 0.00954 +Epoch [1200/4000] Training [6/16] Loss: 0.01034 +Epoch [1200/4000] Training [7/16] Loss: 0.00899 +Epoch [1200/4000] Training [8/16] Loss: 0.00787 +Epoch [1200/4000] Training [9/16] Loss: 0.01157 +Epoch [1200/4000] Training [10/16] Loss: 0.01247 +Epoch [1200/4000] Training [11/16] Loss: 0.01144 +Epoch [1200/4000] Training [12/16] Loss: 0.00996 +Epoch [1200/4000] Training [13/16] Loss: 0.01453 +Epoch [1200/4000] Training [14/16] Loss: 0.01140 +Epoch [1200/4000] Training [15/16] Loss: 0.00915 +Epoch [1200/4000] Training [16/16] Loss: 0.01068 +Epoch [1200/4000] Training metric {'Train/mean dice_metric': 0.9930583238601685, 'Train/mean miou_metric': 0.9859707951545715, 'Train/mean f1': 0.989266574382782, 'Train/mean precision': 0.9846578240394592, 'Train/mean recall': 0.9939186573028564, 'Train/mean hd95_metric': 1.3559410572052002} +Epoch [1200/4000] Validation [1/4] Loss: 0.48813 focal_loss 0.36805 dice_loss 0.12008 +Epoch [1200/4000] Validation [2/4] Loss: 0.37769 focal_loss 0.18721 dice_loss 0.19048 +Epoch [1200/4000] Validation [3/4] Loss: 0.19116 focal_loss 0.10605 dice_loss 0.08511 +Epoch [1200/4000] Validation [4/4] Loss: 0.20923 focal_loss 0.11318 dice_loss 0.09605 +Epoch [1200/4000] Validation metric {'Val/mean dice_metric': 0.9665080904960632, 'Val/mean miou_metric': 0.9470365643501282, 'Val/mean f1': 0.9662208557128906, 'Val/mean precision': 0.9615268111228943, 'Val/mean recall': 0.9709610342979431, 'Val/mean hd95_metric': 7.432318210601807} +Cheakpoint... +Epoch [1200/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665080904960632, 'Val/mean miou_metric': 0.9470365643501282, 'Val/mean f1': 0.9662208557128906, 'Val/mean precision': 0.9615268111228943, 'Val/mean recall': 0.9709610342979431, 'Val/mean hd95_metric': 7.432318210601807} +Epoch [1201/4000] Training [1/16] Loss: 0.00926 +Epoch [1201/4000] Training [2/16] Loss: 0.00913 +Epoch [1201/4000] Training [3/16] Loss: 0.00917 +Epoch [1201/4000] Training [4/16] Loss: 0.00730 +Epoch [1201/4000] Training [5/16] Loss: 0.00768 +Epoch [1201/4000] Training [6/16] Loss: 0.00942 +Epoch [1201/4000] Training [7/16] Loss: 0.01457 +Epoch [1201/4000] Training [8/16] Loss: 0.00837 +Epoch [1201/4000] Training [9/16] Loss: 0.00794 +Epoch [1201/4000] Training [10/16] Loss: 0.00895 +Epoch [1201/4000] Training [11/16] Loss: 0.00827 +Epoch [1201/4000] Training [12/16] Loss: 0.00948 +Epoch [1201/4000] Training [13/16] Loss: 0.00931 +Epoch [1201/4000] Training [14/16] Loss: 0.01215 +Epoch [1201/4000] Training [15/16] Loss: 0.00879 +Epoch [1201/4000] Training [16/16] Loss: 0.00879 +Epoch [1201/4000] Training metric {'Train/mean dice_metric': 0.9932020902633667, 'Train/mean miou_metric': 0.9862731695175171, 'Train/mean f1': 0.9895699620246887, 'Train/mean precision': 0.9849631786346436, 'Train/mean recall': 0.994219958782196, 'Train/mean hd95_metric': 1.3872838020324707} +Epoch [1201/4000] Validation [1/4] Loss: 0.22100 focal_loss 0.14312 dice_loss 0.07788 +Epoch [1201/4000] Validation [2/4] Loss: 0.35057 focal_loss 0.14972 dice_loss 0.20086 +Epoch [1201/4000] Validation [3/4] Loss: 0.16054 focal_loss 0.08848 dice_loss 0.07206 +Epoch [1201/4000] Validation [4/4] Loss: 0.19562 focal_loss 0.09405 dice_loss 0.10157 +Epoch [1201/4000] Validation metric {'Val/mean dice_metric': 0.9681839942932129, 'Val/mean miou_metric': 0.9492350816726685, 'Val/mean f1': 0.9681758284568787, 'Val/mean precision': 0.9602715373039246, 'Val/mean recall': 0.976211428642273, 'Val/mean hd95_metric': 7.036896705627441} +Cheakpoint... +Epoch [1201/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681839942932129, 'Val/mean miou_metric': 0.9492350816726685, 'Val/mean f1': 0.9681758284568787, 'Val/mean precision': 0.9602715373039246, 'Val/mean recall': 0.976211428642273, 'Val/mean hd95_metric': 7.036896705627441} +Epoch [1202/4000] Training [1/16] Loss: 0.01088 +Epoch [1202/4000] Training [2/16] Loss: 0.00829 +Epoch [1202/4000] Training [3/16] Loss: 0.00780 +Epoch [1202/4000] Training [4/16] Loss: 0.01077 +Epoch [1202/4000] Training [5/16] Loss: 0.00884 +Epoch [1202/4000] Training [6/16] Loss: 0.01021 +Epoch [1202/4000] Training [7/16] Loss: 0.00800 +Epoch [1202/4000] Training [8/16] Loss: 0.01017 +Epoch [1202/4000] Training [9/16] Loss: 0.00898 +Epoch [1202/4000] Training [10/16] Loss: 0.01054 +Epoch [1202/4000] Training [11/16] Loss: 0.00872 +Epoch [1202/4000] Training [12/16] Loss: 0.00898 +Epoch [1202/4000] Training [13/16] Loss: 0.01118 +Epoch [1202/4000] Training [14/16] Loss: 0.00804 +Epoch [1202/4000] Training [15/16] Loss: 0.01392 +Epoch [1202/4000] Training [16/16] Loss: 0.01109 +Epoch [1202/4000] Training metric {'Train/mean dice_metric': 0.9933285713195801, 'Train/mean miou_metric': 0.9865023493766785, 'Train/mean f1': 0.9895557761192322, 'Train/mean precision': 0.9850460886955261, 'Train/mean recall': 0.9941069483757019, 'Train/mean hd95_metric': 1.1657882928848267} +Epoch [1202/4000] Validation [1/4] Loss: 0.18056 focal_loss 0.11575 dice_loss 0.06480 +Epoch [1202/4000] Validation [2/4] Loss: 0.24149 focal_loss 0.11197 dice_loss 0.12951 +Epoch [1202/4000] Validation [3/4] Loss: 0.12540 focal_loss 0.07094 dice_loss 0.05447 +Epoch [1202/4000] Validation [4/4] Loss: 0.19044 focal_loss 0.08431 dice_loss 0.10613 +Epoch [1202/4000] Validation metric {'Val/mean dice_metric': 0.9699881672859192, 'Val/mean miou_metric': 0.9515329599380493, 'Val/mean f1': 0.9702784419059753, 'Val/mean precision': 0.9674122333526611, 'Val/mean recall': 0.9731617569923401, 'Val/mean hd95_metric': 6.077195167541504} +Cheakpoint... +Epoch [1202/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699881672859192, 'Val/mean miou_metric': 0.9515329599380493, 'Val/mean f1': 0.9702784419059753, 'Val/mean precision': 0.9674122333526611, 'Val/mean recall': 0.9731617569923401, 'Val/mean hd95_metric': 6.077195167541504} +Epoch [1203/4000] Training [1/16] Loss: 0.01340 +Epoch [1203/4000] Training [2/16] Loss: 0.00868 +Epoch [1203/4000] Training [3/16] Loss: 0.01082 +Epoch [1203/4000] Training [4/16] Loss: 0.00997 +Epoch [1203/4000] Training [5/16] Loss: 0.00953 +Epoch [1203/4000] Training [6/16] Loss: 0.00978 +Epoch [1203/4000] Training [7/16] Loss: 0.00817 +Epoch [1203/4000] Training [8/16] Loss: 0.00857 +Epoch [1203/4000] Training [9/16] Loss: 0.00999 +Epoch [1203/4000] Training [10/16] Loss: 0.00892 +Epoch [1203/4000] Training [11/16] Loss: 0.01571 +Epoch [1203/4000] Training [12/16] Loss: 0.01398 +Epoch [1203/4000] Training [13/16] Loss: 0.00978 +Epoch [1203/4000] Training [14/16] Loss: 0.01040 +Epoch [1203/4000] Training [15/16] Loss: 0.01072 +Epoch [1203/4000] Training [16/16] Loss: 0.00934 +Epoch [1203/4000] Training metric {'Train/mean dice_metric': 0.9927778840065002, 'Train/mean miou_metric': 0.9854334592819214, 'Train/mean f1': 0.9891394376754761, 'Train/mean precision': 0.9846686720848083, 'Train/mean recall': 0.9936509728431702, 'Train/mean hd95_metric': 1.1594955921173096} +Epoch [1203/4000] Validation [1/4] Loss: 0.18101 focal_loss 0.11817 dice_loss 0.06284 +Epoch [1203/4000] Validation [2/4] Loss: 0.26713 focal_loss 0.11155 dice_loss 0.15558 +Epoch [1203/4000] Validation [3/4] Loss: 0.24849 focal_loss 0.14859 dice_loss 0.09990 +Epoch [1203/4000] Validation [4/4] Loss: 0.19283 focal_loss 0.09676 dice_loss 0.09607 +Epoch [1203/4000] Validation metric {'Val/mean dice_metric': 0.969058632850647, 'Val/mean miou_metric': 0.9499211311340332, 'Val/mean f1': 0.9717594385147095, 'Val/mean precision': 0.966012179851532, 'Val/mean recall': 0.9775755405426025, 'Val/mean hd95_metric': 6.585310935974121} +Cheakpoint... +Epoch [1203/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969058632850647, 'Val/mean miou_metric': 0.9499211311340332, 'Val/mean f1': 0.9717594385147095, 'Val/mean precision': 0.966012179851532, 'Val/mean recall': 0.9775755405426025, 'Val/mean hd95_metric': 6.585310935974121} +Epoch [1204/4000] Training [1/16] Loss: 0.00742 +Epoch [1204/4000] Training [2/16] Loss: 0.01147 +Epoch [1204/4000] Training [3/16] Loss: 0.01084 +Epoch [1204/4000] Training [4/16] Loss: 0.01048 +Epoch [1204/4000] Training [5/16] Loss: 0.01215 +Epoch [1204/4000] Training [6/16] Loss: 0.00951 +Epoch [1204/4000] Training [7/16] Loss: 0.00723 +Epoch [1204/4000] Training [8/16] Loss: 0.01255 +Epoch [1204/4000] Training [9/16] Loss: 0.01041 +Epoch [1204/4000] Training [10/16] Loss: 0.01166 +Epoch [1204/4000] Training [11/16] Loss: 0.00786 +Epoch [1204/4000] Training [12/16] Loss: 0.01394 +Epoch [1204/4000] Training [13/16] Loss: 0.01007 +Epoch [1204/4000] Training [14/16] Loss: 0.00926 +Epoch [1204/4000] Training [15/16] Loss: 0.00840 +Epoch [1204/4000] Training [16/16] Loss: 0.00783 +Epoch [1204/4000] Training metric {'Train/mean dice_metric': 0.9932137727737427, 'Train/mean miou_metric': 0.9862658977508545, 'Train/mean f1': 0.9893556833267212, 'Train/mean precision': 0.9846884608268738, 'Train/mean recall': 0.994067370891571, 'Train/mean hd95_metric': 1.0834434032440186} +Epoch [1204/4000] Validation [1/4] Loss: 0.18667 focal_loss 0.12218 dice_loss 0.06449 +Epoch [1204/4000] Validation [2/4] Loss: 0.21268 focal_loss 0.09857 dice_loss 0.11411 +Epoch [1204/4000] Validation [3/4] Loss: 0.14024 focal_loss 0.08290 dice_loss 0.05734 +Epoch [1204/4000] Validation [4/4] Loss: 0.21999 focal_loss 0.11905 dice_loss 0.10094 +Epoch [1204/4000] Validation metric {'Val/mean dice_metric': 0.9711200594902039, 'Val/mean miou_metric': 0.9527000188827515, 'Val/mean f1': 0.9723603129386902, 'Val/mean precision': 0.9686763882637024, 'Val/mean recall': 0.9760723114013672, 'Val/mean hd95_metric': 5.504275321960449} +Cheakpoint... +Epoch [1204/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711200594902039, 'Val/mean miou_metric': 0.9527000188827515, 'Val/mean f1': 0.9723603129386902, 'Val/mean precision': 0.9686763882637024, 'Val/mean recall': 0.9760723114013672, 'Val/mean hd95_metric': 5.504275321960449} +Epoch [1205/4000] Training [1/16] Loss: 0.01043 +Epoch [1205/4000] Training [2/16] Loss: 0.01038 +Epoch [1205/4000] Training [3/16] Loss: 0.01144 +Epoch [1205/4000] Training [4/16] Loss: 0.00731 +Epoch [1205/4000] Training [5/16] Loss: 0.00966 +Epoch [1205/4000] Training [6/16] Loss: 0.01043 +Epoch [1205/4000] Training [7/16] Loss: 0.00829 +Epoch [1205/4000] Training [8/16] Loss: 0.00820 +Epoch [1205/4000] Training [9/16] Loss: 0.00975 +Epoch [1205/4000] Training [10/16] Loss: 0.01486 +Epoch [1205/4000] Training [11/16] Loss: 0.01278 +Epoch [1205/4000] Training [12/16] Loss: 0.00958 +Epoch [1205/4000] Training [13/16] Loss: 0.00956 +Epoch [1205/4000] Training [14/16] Loss: 0.01077 +Epoch [1205/4000] Training [15/16] Loss: 0.00963 +Epoch [1205/4000] Training [16/16] Loss: 0.00720 +Epoch [1205/4000] Training metric {'Train/mean dice_metric': 0.9933178424835205, 'Train/mean miou_metric': 0.986472487449646, 'Train/mean f1': 0.9890846014022827, 'Train/mean precision': 0.9839797616004944, 'Train/mean recall': 0.9942426681518555, 'Train/mean hd95_metric': 1.293109655380249} +Epoch [1205/4000] Validation [1/4] Loss: 0.15898 focal_loss 0.10203 dice_loss 0.05695 +Epoch [1205/4000] Validation [2/4] Loss: 0.45913 focal_loss 0.25669 dice_loss 0.20243 +Epoch [1205/4000] Validation [3/4] Loss: 0.12403 focal_loss 0.06925 dice_loss 0.05478 +Epoch [1205/4000] Validation [4/4] Loss: 0.29609 focal_loss 0.17679 dice_loss 0.11930 +Epoch [1205/4000] Validation metric {'Val/mean dice_metric': 0.9681270718574524, 'Val/mean miou_metric': 0.9497494697570801, 'Val/mean f1': 0.9710055589675903, 'Val/mean precision': 0.968161404132843, 'Val/mean recall': 0.9738665223121643, 'Val/mean hd95_metric': 6.056699752807617} +Cheakpoint... +Epoch [1205/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681270718574524, 'Val/mean miou_metric': 0.9497494697570801, 'Val/mean f1': 0.9710055589675903, 'Val/mean precision': 0.968161404132843, 'Val/mean recall': 0.9738665223121643, 'Val/mean hd95_metric': 6.056699752807617} +Epoch [1206/4000] Training [1/16] Loss: 0.00955 +Epoch [1206/4000] Training [2/16] Loss: 0.00908 +Epoch [1206/4000] Training [3/16] Loss: 0.01001 +Epoch [1206/4000] Training [4/16] Loss: 0.00894 +Epoch [1206/4000] Training [5/16] Loss: 0.00818 +Epoch [1206/4000] Training [6/16] Loss: 0.01071 +Epoch [1206/4000] Training [7/16] Loss: 0.01026 +Epoch [1206/4000] Training [8/16] Loss: 0.00843 +Epoch [1206/4000] Training [9/16] Loss: 0.01081 +Epoch [1206/4000] Training [10/16] Loss: 0.01174 +Epoch [1206/4000] Training [11/16] Loss: 0.00846 +Epoch [1206/4000] Training [12/16] Loss: 0.00822 +Epoch [1206/4000] Training [13/16] Loss: 0.00891 +Epoch [1206/4000] Training [14/16] Loss: 0.00906 +Epoch [1206/4000] Training [15/16] Loss: 0.01222 +Epoch [1206/4000] Training [16/16] Loss: 0.00942 +Epoch [1206/4000] Training metric {'Train/mean dice_metric': 0.9931707382202148, 'Train/mean miou_metric': 0.986189067363739, 'Train/mean f1': 0.9894101619720459, 'Train/mean precision': 0.9846807718276978, 'Train/mean recall': 0.9941852688789368, 'Train/mean hd95_metric': 1.0913543701171875} +Epoch [1206/4000] Validation [1/4] Loss: 0.16394 focal_loss 0.10499 dice_loss 0.05895 +Epoch [1206/4000] Validation [2/4] Loss: 0.26074 focal_loss 0.11684 dice_loss 0.14390 +Epoch [1206/4000] Validation [3/4] Loss: 0.16886 focal_loss 0.09365 dice_loss 0.07521 +Epoch [1206/4000] Validation [4/4] Loss: 0.26661 focal_loss 0.15301 dice_loss 0.11360 +Epoch [1206/4000] Validation metric {'Val/mean dice_metric': 0.969456672668457, 'Val/mean miou_metric': 0.9504234194755554, 'Val/mean f1': 0.9712634682655334, 'Val/mean precision': 0.9691081643104553, 'Val/mean recall': 0.9734282493591309, 'Val/mean hd95_metric': 6.120589256286621} +Cheakpoint... +Epoch [1206/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969456672668457, 'Val/mean miou_metric': 0.9504234194755554, 'Val/mean f1': 0.9712634682655334, 'Val/mean precision': 0.9691081643104553, 'Val/mean recall': 0.9734282493591309, 'Val/mean hd95_metric': 6.120589256286621} +Epoch [1207/4000] Training [1/16] Loss: 0.01270 +Epoch [1207/4000] Training [2/16] Loss: 0.01189 +Epoch [1207/4000] Training [3/16] Loss: 0.00960 +Epoch [1207/4000] Training [4/16] Loss: 0.01089 +Epoch [1207/4000] Training [5/16] Loss: 0.01100 +Epoch [1207/4000] Training [6/16] Loss: 0.01185 +Epoch [1207/4000] Training [7/16] Loss: 0.01174 +Epoch [1207/4000] Training [8/16] Loss: 0.00959 +Epoch [1207/4000] Training [9/16] Loss: 0.00895 +Epoch [1207/4000] Training [10/16] Loss: 0.01229 +Epoch [1207/4000] Training [11/16] Loss: 0.01021 +Epoch [1207/4000] Training [12/16] Loss: 0.01168 +Epoch [1207/4000] Training [13/16] Loss: 0.01424 +Epoch [1207/4000] Training [14/16] Loss: 0.00913 +Epoch [1207/4000] Training [15/16] Loss: 0.01035 +Epoch [1207/4000] Training [16/16] Loss: 0.00794 +Epoch [1207/4000] Training metric {'Train/mean dice_metric': 0.9925539493560791, 'Train/mean miou_metric': 0.9849938154220581, 'Train/mean f1': 0.9891079664230347, 'Train/mean precision': 0.9847719073295593, 'Train/mean recall': 0.9934824109077454, 'Train/mean hd95_metric': 1.1118793487548828} +Epoch [1207/4000] Validation [1/4] Loss: 0.17314 focal_loss 0.11366 dice_loss 0.05948 +Epoch [1207/4000] Validation [2/4] Loss: 0.24281 focal_loss 0.11966 dice_loss 0.12315 +Epoch [1207/4000] Validation [3/4] Loss: 0.11742 focal_loss 0.06279 dice_loss 0.05464 +Epoch [1207/4000] Validation [4/4] Loss: 0.36996 focal_loss 0.22249 dice_loss 0.14746 +Epoch [1207/4000] Validation metric {'Val/mean dice_metric': 0.9686548113822937, 'Val/mean miou_metric': 0.9492397308349609, 'Val/mean f1': 0.9718546867370605, 'Val/mean precision': 0.9707005620002747, 'Val/mean recall': 0.9730116724967957, 'Val/mean hd95_metric': 5.332065582275391} +Cheakpoint... +Epoch [1207/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686548113822937, 'Val/mean miou_metric': 0.9492397308349609, 'Val/mean f1': 0.9718546867370605, 'Val/mean precision': 0.9707005620002747, 'Val/mean recall': 0.9730116724967957, 'Val/mean hd95_metric': 5.332065582275391} +Epoch [1208/4000] Training [1/16] Loss: 0.00934 +Epoch [1208/4000] Training [2/16] Loss: 0.00899 +Epoch [1208/4000] Training [3/16] Loss: 0.00958 +Epoch [1208/4000] Training [4/16] Loss: 0.01178 +Epoch [1208/4000] Training [5/16] Loss: 0.01101 +Epoch [1208/4000] Training [6/16] Loss: 0.00994 +Epoch [1208/4000] Training [7/16] Loss: 0.03117 +Epoch [1208/4000] Training [8/16] Loss: 0.01155 +Epoch [1208/4000] Training [9/16] Loss: 0.00938 +Epoch [1208/4000] Training [10/16] Loss: 0.00941 +Epoch [1208/4000] Training [11/16] Loss: 0.01035 +Epoch [1208/4000] Training [12/16] Loss: 0.00921 +Epoch [1208/4000] Training [13/16] Loss: 0.01426 +Epoch [1208/4000] Training [14/16] Loss: 0.00854 +Epoch [1208/4000] Training [15/16] Loss: 0.01182 +Epoch [1208/4000] Training [16/16] Loss: 0.01225 +Epoch [1208/4000] Training metric {'Train/mean dice_metric': 0.9925539493560791, 'Train/mean miou_metric': 0.984983503818512, 'Train/mean f1': 0.9884404540061951, 'Train/mean precision': 0.9833245873451233, 'Train/mean recall': 0.9936097860336304, 'Train/mean hd95_metric': 1.1049648523330688} +Epoch [1208/4000] Validation [1/4] Loss: 0.24373 focal_loss 0.16150 dice_loss 0.08223 +Epoch [1208/4000] Validation [2/4] Loss: 0.29998 focal_loss 0.15767 dice_loss 0.14231 +Epoch [1208/4000] Validation [3/4] Loss: 0.14471 focal_loss 0.08025 dice_loss 0.06447 +Epoch [1208/4000] Validation [4/4] Loss: 0.18478 focal_loss 0.09448 dice_loss 0.09030 +Epoch [1208/4000] Validation metric {'Val/mean dice_metric': 0.9709938168525696, 'Val/mean miou_metric': 0.9516423940658569, 'Val/mean f1': 0.9720929265022278, 'Val/mean precision': 0.9665839672088623, 'Val/mean recall': 0.9776651859283447, 'Val/mean hd95_metric': 5.743443489074707} +Cheakpoint... +Epoch [1208/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709938168525696, 'Val/mean miou_metric': 0.9516423940658569, 'Val/mean f1': 0.9720929265022278, 'Val/mean precision': 0.9665839672088623, 'Val/mean recall': 0.9776651859283447, 'Val/mean hd95_metric': 5.743443489074707} +Epoch [1209/4000] Training [1/16] Loss: 0.01031 +Epoch [1209/4000] Training [2/16] Loss: 0.00951 +Epoch [1209/4000] Training [3/16] Loss: 0.01213 +Epoch [1209/4000] Training [4/16] Loss: 0.00889 +Epoch [1209/4000] Training [5/16] Loss: 0.00951 +Epoch [1209/4000] Training [6/16] Loss: 0.00921 +Epoch [1209/4000] Training [7/16] Loss: 0.01031 +Epoch [1209/4000] Training [8/16] Loss: 0.01305 +Epoch [1209/4000] Training [9/16] Loss: 0.01055 +Epoch [1209/4000] Training [10/16] Loss: 0.00791 +Epoch [1209/4000] Training [11/16] Loss: 0.01428 +Epoch [1209/4000] Training [12/16] Loss: 0.01056 +Epoch [1209/4000] Training [13/16] Loss: 0.01542 +Epoch [1209/4000] Training [14/16] Loss: 0.01125 +Epoch [1209/4000] Training [15/16] Loss: 0.00836 +Epoch [1209/4000] Training [16/16] Loss: 0.01360 +Epoch [1209/4000] Training metric {'Train/mean dice_metric': 0.9920008182525635, 'Train/mean miou_metric': 0.9841611385345459, 'Train/mean f1': 0.9888800382614136, 'Train/mean precision': 0.9842485785484314, 'Train/mean recall': 0.9935552477836609, 'Train/mean hd95_metric': 1.2642176151275635} +Epoch [1209/4000] Validation [1/4] Loss: 0.42610 focal_loss 0.31922 dice_loss 0.10688 +Epoch [1209/4000] Validation [2/4] Loss: 0.48271 focal_loss 0.29109 dice_loss 0.19162 +Epoch [1209/4000] Validation [3/4] Loss: 0.24803 focal_loss 0.15581 dice_loss 0.09222 +Epoch [1209/4000] Validation [4/4] Loss: 0.19222 focal_loss 0.10255 dice_loss 0.08967 +Epoch [1209/4000] Validation metric {'Val/mean dice_metric': 0.9697297215461731, 'Val/mean miou_metric': 0.9504299163818359, 'Val/mean f1': 0.9713383913040161, 'Val/mean precision': 0.9683970808982849, 'Val/mean recall': 0.9742976427078247, 'Val/mean hd95_metric': 5.539200782775879} +Cheakpoint... +Epoch [1209/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697297215461731, 'Val/mean miou_metric': 0.9504299163818359, 'Val/mean f1': 0.9713383913040161, 'Val/mean precision': 0.9683970808982849, 'Val/mean recall': 0.9742976427078247, 'Val/mean hd95_metric': 5.539200782775879} +Epoch [1210/4000] Training [1/16] Loss: 0.01119 +Epoch [1210/4000] Training [2/16] Loss: 0.01291 +Epoch [1210/4000] Training [3/16] Loss: 0.00949 +Epoch [1210/4000] Training [4/16] Loss: 0.01172 +Epoch [1210/4000] Training [5/16] Loss: 0.00933 +Epoch [1210/4000] Training [6/16] Loss: 0.00933 +Epoch [1210/4000] Training [7/16] Loss: 0.00840 +Epoch [1210/4000] Training [8/16] Loss: 0.01134 +Epoch [1210/4000] Training [9/16] Loss: 0.00901 +Epoch [1210/4000] Training [10/16] Loss: 0.00888 +Epoch [1210/4000] Training [11/16] Loss: 0.01084 +Epoch [1210/4000] Training [12/16] Loss: 0.01040 +Epoch [1210/4000] Training [13/16] Loss: 0.00865 +Epoch [1210/4000] Training [14/16] Loss: 0.00810 +Epoch [1210/4000] Training [15/16] Loss: 0.01256 +Epoch [1210/4000] Training [16/16] Loss: 0.01020 +Epoch [1210/4000] Training metric {'Train/mean dice_metric': 0.991997480392456, 'Train/mean miou_metric': 0.9840413331985474, 'Train/mean f1': 0.988510012626648, 'Train/mean precision': 0.9842108488082886, 'Train/mean recall': 0.9928467869758606, 'Train/mean hd95_metric': 1.7136077880859375} +Epoch [1210/4000] Validation [1/4] Loss: 0.19518 focal_loss 0.13109 dice_loss 0.06408 +Epoch [1210/4000] Validation [2/4] Loss: 0.26644 focal_loss 0.13573 dice_loss 0.13072 +Epoch [1210/4000] Validation [3/4] Loss: 0.16747 focal_loss 0.09153 dice_loss 0.07594 +Epoch [1210/4000] Validation [4/4] Loss: 0.25233 focal_loss 0.13959 dice_loss 0.11274 +Epoch [1210/4000] Validation metric {'Val/mean dice_metric': 0.9711721539497375, 'Val/mean miou_metric': 0.9514803886413574, 'Val/mean f1': 0.9719169735908508, 'Val/mean precision': 0.9670130014419556, 'Val/mean recall': 0.9768708944320679, 'Val/mean hd95_metric': 6.484961032867432} +Cheakpoint... +Epoch [1210/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711721539497375, 'Val/mean miou_metric': 0.9514803886413574, 'Val/mean f1': 0.9719169735908508, 'Val/mean precision': 0.9670130014419556, 'Val/mean recall': 0.9768708944320679, 'Val/mean hd95_metric': 6.484961032867432} +Epoch [1211/4000] Training [1/16] Loss: 0.00861 +Epoch [1211/4000] Training [2/16] Loss: 0.00914 +Epoch [1211/4000] Training [3/16] Loss: 0.01402 +Epoch [1211/4000] Training [4/16] Loss: 0.01028 +Epoch [1211/4000] Training [5/16] Loss: 0.01135 +Epoch [1211/4000] Training [6/16] Loss: 0.01107 +Epoch [1211/4000] Training [7/16] Loss: 0.01822 +Epoch [1211/4000] Training [8/16] Loss: 0.01083 +Epoch [1211/4000] Training [9/16] Loss: 0.01154 +Epoch [1211/4000] Training [10/16] Loss: 0.01251 +Epoch [1211/4000] Training [11/16] Loss: 0.00988 +Epoch [1211/4000] Training [12/16] Loss: 0.00865 +Epoch [1211/4000] Training [13/16] Loss: 0.01096 +Epoch [1211/4000] Training [14/16] Loss: 0.01365 +Epoch [1211/4000] Training [15/16] Loss: 0.01375 +Epoch [1211/4000] Training [16/16] Loss: 0.00927 +Epoch [1211/4000] Training metric {'Train/mean dice_metric': 0.9922858476638794, 'Train/mean miou_metric': 0.9844951629638672, 'Train/mean f1': 0.9889386892318726, 'Train/mean precision': 0.9843723773956299, 'Train/mean recall': 0.9935474991798401, 'Train/mean hd95_metric': 1.1636879444122314} +Epoch [1211/4000] Validation [1/4] Loss: 0.17457 focal_loss 0.11584 dice_loss 0.05873 +Epoch [1211/4000] Validation [2/4] Loss: 0.53680 focal_loss 0.33321 dice_loss 0.20360 +Epoch [1211/4000] Validation [3/4] Loss: 0.13888 focal_loss 0.07779 dice_loss 0.06109 +Epoch [1211/4000] Validation [4/4] Loss: 0.26354 focal_loss 0.12576 dice_loss 0.13778 +Epoch [1211/4000] Validation metric {'Val/mean dice_metric': 0.9695529937744141, 'Val/mean miou_metric': 0.9500282406806946, 'Val/mean f1': 0.9718203544616699, 'Val/mean precision': 0.9679592847824097, 'Val/mean recall': 0.9757124185562134, 'Val/mean hd95_metric': 6.386688232421875} +Cheakpoint... +Epoch [1211/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695529937744141, 'Val/mean miou_metric': 0.9500282406806946, 'Val/mean f1': 0.9718203544616699, 'Val/mean precision': 0.9679592847824097, 'Val/mean recall': 0.9757124185562134, 'Val/mean hd95_metric': 6.386688232421875} +Epoch [1212/4000] Training [1/16] Loss: 0.01133 +Epoch [1212/4000] Training [2/16] Loss: 0.00824 +Epoch [1212/4000] Training [3/16] Loss: 0.01206 +Epoch [1212/4000] Training [4/16] Loss: 0.01251 +Epoch [1212/4000] Training [5/16] Loss: 0.01259 +Epoch [1212/4000] Training [6/16] Loss: 0.01577 +Epoch [1212/4000] Training [7/16] Loss: 0.01240 +Epoch [1212/4000] Training [8/16] Loss: 0.01133 +Epoch [1212/4000] Training [9/16] Loss: 0.01114 +Epoch [1212/4000] Training [10/16] Loss: 0.00989 +Epoch [1212/4000] Training [11/16] Loss: 0.00771 +Epoch [1212/4000] Training [12/16] Loss: 0.01293 +Epoch [1212/4000] Training [13/16] Loss: 0.00935 +Epoch [1212/4000] Training [14/16] Loss: 0.01112 +Epoch [1212/4000] Training [15/16] Loss: 0.01024 +Epoch [1212/4000] Training [16/16] Loss: 0.00905 +Epoch [1212/4000] Training metric {'Train/mean dice_metric': 0.9924149513244629, 'Train/mean miou_metric': 0.9847480654716492, 'Train/mean f1': 0.9887272119522095, 'Train/mean precision': 0.9840958118438721, 'Train/mean recall': 0.9934024810791016, 'Train/mean hd95_metric': 1.6316373348236084} +Epoch [1212/4000] Validation [1/4] Loss: 0.50430 focal_loss 0.39078 dice_loss 0.11351 +Epoch [1212/4000] Validation [2/4] Loss: 0.50662 focal_loss 0.29129 dice_loss 0.21533 +Epoch [1212/4000] Validation [3/4] Loss: 0.17324 focal_loss 0.10281 dice_loss 0.07043 +Epoch [1212/4000] Validation [4/4] Loss: 0.30833 focal_loss 0.17074 dice_loss 0.13759 +Epoch [1212/4000] Validation metric {'Val/mean dice_metric': 0.966816246509552, 'Val/mean miou_metric': 0.946589469909668, 'Val/mean f1': 0.9691691994667053, 'Val/mean precision': 0.9694156646728516, 'Val/mean recall': 0.9689228534698486, 'Val/mean hd95_metric': 6.371664524078369} +Cheakpoint... +Epoch [1212/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.966816246509552, 'Val/mean miou_metric': 0.946589469909668, 'Val/mean f1': 0.9691691994667053, 'Val/mean precision': 0.9694156646728516, 'Val/mean recall': 0.9689228534698486, 'Val/mean hd95_metric': 6.371664524078369} +Epoch [1213/4000] Training [1/16] Loss: 0.01343 +Epoch [1213/4000] Training [2/16] Loss: 0.01055 +Epoch [1213/4000] Training [3/16] Loss: 0.01436 +Epoch [1213/4000] Training [4/16] Loss: 0.01001 +Epoch [1213/4000] Training [5/16] Loss: 0.00803 +Epoch [1213/4000] Training [6/16] Loss: 0.00751 +Epoch [1213/4000] Training [7/16] Loss: 0.00870 +Epoch [1213/4000] Training [8/16] Loss: 0.00868 +Epoch [1213/4000] Training [9/16] Loss: 0.01202 +Epoch [1213/4000] Training [10/16] Loss: 0.01294 +Epoch [1213/4000] Training [11/16] Loss: 0.01018 +Epoch [1213/4000] Training [12/16] Loss: 0.01275 +Epoch [1213/4000] Training [13/16] Loss: 0.00775 +Epoch [1213/4000] Training [14/16] Loss: 0.00811 +Epoch [1213/4000] Training [15/16] Loss: 0.00973 +Epoch [1213/4000] Training [16/16] Loss: 0.01212 +Epoch [1213/4000] Training metric {'Train/mean dice_metric': 0.9920685887336731, 'Train/mean miou_metric': 0.9845245480537415, 'Train/mean f1': 0.9891963601112366, 'Train/mean precision': 0.9846055507659912, 'Train/mean recall': 0.9938302040100098, 'Train/mean hd95_metric': 1.1812456846237183} +Epoch [1213/4000] Validation [1/4] Loss: 0.27456 focal_loss 0.19157 dice_loss 0.08299 +Epoch [1213/4000] Validation [2/4] Loss: 0.35495 focal_loss 0.20388 dice_loss 0.15107 +Epoch [1213/4000] Validation [3/4] Loss: 0.13736 focal_loss 0.07977 dice_loss 0.05760 +Epoch [1213/4000] Validation [4/4] Loss: 0.20625 focal_loss 0.11508 dice_loss 0.09117 +Epoch [1213/4000] Validation metric {'Val/mean dice_metric': 0.970136821269989, 'Val/mean miou_metric': 0.951158881187439, 'Val/mean f1': 0.9720839858055115, 'Val/mean precision': 0.968675971031189, 'Val/mean recall': 0.9755160212516785, 'Val/mean hd95_metric': 6.123934745788574} +Cheakpoint... +Epoch [1213/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970136821269989, 'Val/mean miou_metric': 0.951158881187439, 'Val/mean f1': 0.9720839858055115, 'Val/mean precision': 0.968675971031189, 'Val/mean recall': 0.9755160212516785, 'Val/mean hd95_metric': 6.123934745788574} +Epoch [1214/4000] Training [1/16] Loss: 0.01101 +Epoch [1214/4000] Training [2/16] Loss: 0.00823 +Epoch [1214/4000] Training [3/16] Loss: 0.00864 +Epoch [1214/4000] Training [4/16] Loss: 0.00896 +Epoch [1214/4000] Training [5/16] Loss: 0.00993 +Epoch [1214/4000] Training [6/16] Loss: 0.00936 +Epoch [1214/4000] Training [7/16] Loss: 0.00833 +Epoch [1214/4000] Training [8/16] Loss: 0.00924 +Epoch [1214/4000] Training [9/16] Loss: 0.00833 +Epoch [1214/4000] Training [10/16] Loss: 0.01004 +Epoch [1214/4000] Training [11/16] Loss: 0.01075 +Epoch [1214/4000] Training [12/16] Loss: 0.01085 +Epoch [1214/4000] Training [13/16] Loss: 0.01456 +Epoch [1214/4000] Training [14/16] Loss: 0.01135 +Epoch [1214/4000] Training [15/16] Loss: 0.01470 +Epoch [1214/4000] Training [16/16] Loss: 0.00997 +Epoch [1214/4000] Training metric {'Train/mean dice_metric': 0.9927016496658325, 'Train/mean miou_metric': 0.9852815866470337, 'Train/mean f1': 0.9886205792427063, 'Train/mean precision': 0.9834614396095276, 'Train/mean recall': 0.9938340783119202, 'Train/mean hd95_metric': 1.8104722499847412} +Epoch [1214/4000] Validation [1/4] Loss: 0.24579 focal_loss 0.16143 dice_loss 0.08436 +Epoch [1214/4000] Validation [2/4] Loss: 0.33734 focal_loss 0.16955 dice_loss 0.16779 +Epoch [1214/4000] Validation [3/4] Loss: 0.19850 focal_loss 0.11411 dice_loss 0.08438 +Epoch [1214/4000] Validation [4/4] Loss: 0.19906 focal_loss 0.10651 dice_loss 0.09255 +Epoch [1214/4000] Validation metric {'Val/mean dice_metric': 0.9692424535751343, 'Val/mean miou_metric': 0.9499605298042297, 'Val/mean f1': 0.9708565473556519, 'Val/mean precision': 0.9662990570068359, 'Val/mean recall': 0.9754573702812195, 'Val/mean hd95_metric': 6.903055667877197} +Cheakpoint... +Epoch [1214/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692424535751343, 'Val/mean miou_metric': 0.9499605298042297, 'Val/mean f1': 0.9708565473556519, 'Val/mean precision': 0.9662990570068359, 'Val/mean recall': 0.9754573702812195, 'Val/mean hd95_metric': 6.903055667877197} +Epoch [1215/4000] Training [1/16] Loss: 0.01312 +Epoch [1215/4000] Training [2/16] Loss: 0.01340 +Epoch [1215/4000] Training [3/16] Loss: 0.00824 +Epoch [1215/4000] Training [4/16] Loss: 0.00833 +Epoch [1215/4000] Training [5/16] Loss: 0.01280 +Epoch [1215/4000] Training [6/16] Loss: 0.00796 +Epoch [1215/4000] Training [7/16] Loss: 0.00923 +Epoch [1215/4000] Training [8/16] Loss: 0.01013 +Epoch [1215/4000] Training [9/16] Loss: 0.00769 +Epoch [1215/4000] Training [10/16] Loss: 0.01685 +Epoch [1215/4000] Training [11/16] Loss: 0.01136 +Epoch [1215/4000] Training [12/16] Loss: 0.01057 +Epoch [1215/4000] Training [13/16] Loss: 0.00841 +Epoch [1215/4000] Training [14/16] Loss: 0.00950 +Epoch [1215/4000] Training [15/16] Loss: 0.01442 +Epoch [1215/4000] Training [16/16] Loss: 0.01382 +Epoch [1215/4000] Training metric {'Train/mean dice_metric': 0.9928586483001709, 'Train/mean miou_metric': 0.9855825901031494, 'Train/mean f1': 0.9891037940979004, 'Train/mean precision': 0.9846768379211426, 'Train/mean recall': 0.9935707449913025, 'Train/mean hd95_metric': 1.1178529262542725} +Epoch [1215/4000] Validation [1/4] Loss: 0.44989 focal_loss 0.33750 dice_loss 0.11238 +Epoch [1215/4000] Validation [2/4] Loss: 0.49279 focal_loss 0.30797 dice_loss 0.18482 +Epoch [1215/4000] Validation [3/4] Loss: 0.14971 focal_loss 0.08389 dice_loss 0.06582 +Epoch [1215/4000] Validation [4/4] Loss: 0.26714 focal_loss 0.15115 dice_loss 0.11599 +Epoch [1215/4000] Validation metric {'Val/mean dice_metric': 0.9702167510986328, 'Val/mean miou_metric': 0.9506742358207703, 'Val/mean f1': 0.9712781310081482, 'Val/mean precision': 0.9705280661582947, 'Val/mean recall': 0.9720292687416077, 'Val/mean hd95_metric': 5.774163246154785} +Cheakpoint... +Epoch [1215/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702167510986328, 'Val/mean miou_metric': 0.9506742358207703, 'Val/mean f1': 0.9712781310081482, 'Val/mean precision': 0.9705280661582947, 'Val/mean recall': 0.9720292687416077, 'Val/mean hd95_metric': 5.774163246154785} +Epoch [1216/4000] Training [1/16] Loss: 0.00838 +Epoch [1216/4000] Training [2/16] Loss: 0.00703 +Epoch [1216/4000] Training [3/16] Loss: 0.01107 +Epoch [1216/4000] Training [4/16] Loss: 0.00945 +Epoch [1216/4000] Training [5/16] Loss: 0.00849 +Epoch [1216/4000] Training [6/16] Loss: 0.01360 +Epoch [1216/4000] Training [7/16] Loss: 0.00982 +Epoch [1216/4000] Training [8/16] Loss: 0.00761 +Epoch [1216/4000] Training [9/16] Loss: 0.01002 +Epoch [1216/4000] Training [10/16] Loss: 0.01028 +Epoch [1216/4000] Training [11/16] Loss: 0.01072 +Epoch [1216/4000] Training [12/16] Loss: 0.00830 +Epoch [1216/4000] Training [13/16] Loss: 0.00764 +Epoch [1216/4000] Training [14/16] Loss: 0.00841 +Epoch [1216/4000] Training [15/16] Loss: 0.00761 +Epoch [1216/4000] Training [16/16] Loss: 0.01241 +Epoch [1216/4000] Training metric {'Train/mean dice_metric': 0.9933896064758301, 'Train/mean miou_metric': 0.9866331815719604, 'Train/mean f1': 0.9899045825004578, 'Train/mean precision': 0.9853751063346863, 'Train/mean recall': 0.9944758415222168, 'Train/mean hd95_metric': 1.1118781566619873} +Epoch [1216/4000] Validation [1/4] Loss: 0.57543 focal_loss 0.43581 dice_loss 0.13962 +Epoch [1216/4000] Validation [2/4] Loss: 0.16905 focal_loss 0.06983 dice_loss 0.09921 +Epoch [1216/4000] Validation [3/4] Loss: 0.15706 focal_loss 0.09085 dice_loss 0.06622 +Epoch [1216/4000] Validation [4/4] Loss: 0.25873 focal_loss 0.14099 dice_loss 0.11774 +Epoch [1216/4000] Validation metric {'Val/mean dice_metric': 0.9709222912788391, 'Val/mean miou_metric': 0.9516080021858215, 'Val/mean f1': 0.9708917140960693, 'Val/mean precision': 0.9713705778121948, 'Val/mean recall': 0.9704132676124573, 'Val/mean hd95_metric': 5.162869453430176} +Cheakpoint... +Epoch [1216/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709222912788391, 'Val/mean miou_metric': 0.9516080021858215, 'Val/mean f1': 0.9708917140960693, 'Val/mean precision': 0.9713705778121948, 'Val/mean recall': 0.9704132676124573, 'Val/mean hd95_metric': 5.162869453430176} +Epoch [1217/4000] Training [1/16] Loss: 0.01004 +Epoch [1217/4000] Training [2/16] Loss: 0.00697 +Epoch [1217/4000] Training [3/16] Loss: 0.01178 +Epoch [1217/4000] Training [4/16] Loss: 0.00942 +Epoch [1217/4000] Training [5/16] Loss: 0.01153 +Epoch [1217/4000] Training [6/16] Loss: 0.01242 +Epoch [1217/4000] Training [7/16] Loss: 0.00816 +Epoch [1217/4000] Training [8/16] Loss: 0.01961 +Epoch [1217/4000] Training [9/16] Loss: 0.00927 +Epoch [1217/4000] Training [10/16] Loss: 0.00822 +Epoch [1217/4000] Training [11/16] Loss: 0.01064 +Epoch [1217/4000] Training [12/16] Loss: 0.01246 +Epoch [1217/4000] Training [13/16] Loss: 0.01190 +Epoch [1217/4000] Training [14/16] Loss: 0.01099 +Epoch [1217/4000] Training [15/16] Loss: 0.00902 +Epoch [1217/4000] Training [16/16] Loss: 0.00943 +Epoch [1217/4000] Training metric {'Train/mean dice_metric': 0.9925695061683655, 'Train/mean miou_metric': 0.9850417375564575, 'Train/mean f1': 0.9889602661132812, 'Train/mean precision': 0.9843282699584961, 'Train/mean recall': 0.9936360120773315, 'Train/mean hd95_metric': 1.201117992401123} +Epoch [1217/4000] Validation [1/4] Loss: 0.33596 focal_loss 0.24590 dice_loss 0.09006 +Epoch [1217/4000] Validation [2/4] Loss: 0.45097 focal_loss 0.27034 dice_loss 0.18062 +Epoch [1217/4000] Validation [3/4] Loss: 0.17772 focal_loss 0.09638 dice_loss 0.08134 +Epoch [1217/4000] Validation [4/4] Loss: 0.18946 focal_loss 0.09079 dice_loss 0.09867 +Epoch [1217/4000] Validation metric {'Val/mean dice_metric': 0.9690335988998413, 'Val/mean miou_metric': 0.9493147730827332, 'Val/mean f1': 0.9707536697387695, 'Val/mean precision': 0.9692270755767822, 'Val/mean recall': 0.9722850918769836, 'Val/mean hd95_metric': 6.162111282348633} +Cheakpoint... +Epoch [1217/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690335988998413, 'Val/mean miou_metric': 0.9493147730827332, 'Val/mean f1': 0.9707536697387695, 'Val/mean precision': 0.9692270755767822, 'Val/mean recall': 0.9722850918769836, 'Val/mean hd95_metric': 6.162111282348633} +Epoch [1218/4000] Training [1/16] Loss: 0.00840 +Epoch [1218/4000] Training [2/16] Loss: 0.00876 +Epoch [1218/4000] Training [3/16] Loss: 0.00961 +Epoch [1218/4000] Training [4/16] Loss: 0.01356 +Epoch [1218/4000] Training [5/16] Loss: 0.01026 +Epoch [1218/4000] Training [6/16] Loss: 0.01247 +Epoch [1218/4000] Training [7/16] Loss: 0.01182 +Epoch [1218/4000] Training [8/16] Loss: 0.00851 +Epoch [1218/4000] Training [9/16] Loss: 0.03072 +Epoch [1218/4000] Training [10/16] Loss: 0.01220 +Epoch [1218/4000] Training [11/16] Loss: 0.00959 +Epoch [1218/4000] Training [12/16] Loss: 0.01002 +Epoch [1218/4000] Training [13/16] Loss: 0.01302 +Epoch [1218/4000] Training [14/16] Loss: 0.00985 +Epoch [1218/4000] Training [15/16] Loss: 0.00902 +Epoch [1218/4000] Training [16/16] Loss: 0.01424 +Epoch [1218/4000] Training metric {'Train/mean dice_metric': 0.9925889372825623, 'Train/mean miou_metric': 0.9850897192955017, 'Train/mean f1': 0.9889904260635376, 'Train/mean precision': 0.9845467209815979, 'Train/mean recall': 0.9934743642807007, 'Train/mean hd95_metric': 1.1484615802764893} +Epoch [1218/4000] Validation [1/4] Loss: 0.59915 focal_loss 0.45813 dice_loss 0.14101 +Epoch [1218/4000] Validation [2/4] Loss: 0.33856 focal_loss 0.17675 dice_loss 0.16181 +Epoch [1218/4000] Validation [3/4] Loss: 0.29691 focal_loss 0.19385 dice_loss 0.10305 +Epoch [1218/4000] Validation [4/4] Loss: 0.19831 focal_loss 0.10125 dice_loss 0.09706 +Epoch [1218/4000] Validation metric {'Val/mean dice_metric': 0.9685922861099243, 'Val/mean miou_metric': 0.9488387107849121, 'Val/mean f1': 0.9693543910980225, 'Val/mean precision': 0.9668591618537903, 'Val/mean recall': 0.9718626141548157, 'Val/mean hd95_metric': 5.743859767913818} +Cheakpoint... +Epoch [1218/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9685922861099243, 'Val/mean miou_metric': 0.9488387107849121, 'Val/mean f1': 0.9693543910980225, 'Val/mean precision': 0.9668591618537903, 'Val/mean recall': 0.9718626141548157, 'Val/mean hd95_metric': 5.743859767913818} +Epoch [1219/4000] Training [1/16] Loss: 0.01268 +Epoch [1219/4000] Training [2/16] Loss: 0.01443 +Epoch [1219/4000] Training [3/16] Loss: 0.01060 +Epoch [1219/4000] Training [4/16] Loss: 0.00890 +Epoch [1219/4000] Training [5/16] Loss: 0.00898 +Epoch [1219/4000] Training [6/16] Loss: 0.00994 +Epoch [1219/4000] Training [7/16] Loss: 0.01262 +Epoch [1219/4000] Training [8/16] Loss: 0.01477 +Epoch [1219/4000] Training [9/16] Loss: 0.01029 +Epoch [1219/4000] Training [10/16] Loss: 0.00858 +Epoch [1219/4000] Training [11/16] Loss: 0.01238 +Epoch [1219/4000] Training [12/16] Loss: 0.01113 +Epoch [1219/4000] Training [13/16] Loss: 0.01068 +Epoch [1219/4000] Training [14/16] Loss: 0.00913 +Epoch [1219/4000] Training [15/16] Loss: 0.01339 +Epoch [1219/4000] Training [16/16] Loss: 0.01033 +Epoch [1219/4000] Training metric {'Train/mean dice_metric': 0.992530107498169, 'Train/mean miou_metric': 0.984974205493927, 'Train/mean f1': 0.9891343116760254, 'Train/mean precision': 0.984806478023529, 'Train/mean recall': 0.9935004115104675, 'Train/mean hd95_metric': 1.3336660861968994} +Epoch [1219/4000] Validation [1/4] Loss: 0.18154 focal_loss 0.11892 dice_loss 0.06262 +Epoch [1219/4000] Validation [2/4] Loss: 0.24526 focal_loss 0.11192 dice_loss 0.13335 +Epoch [1219/4000] Validation [3/4] Loss: 0.16234 focal_loss 0.09882 dice_loss 0.06352 +Epoch [1219/4000] Validation [4/4] Loss: 0.18321 focal_loss 0.09482 dice_loss 0.08839 +Epoch [1219/4000] Validation metric {'Val/mean dice_metric': 0.9709646105766296, 'Val/mean miou_metric': 0.9524054527282715, 'Val/mean f1': 0.972952127456665, 'Val/mean precision': 0.9671515226364136, 'Val/mean recall': 0.978822648525238, 'Val/mean hd95_metric': 5.602328777313232} +Cheakpoint... +Epoch [1219/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709646105766296, 'Val/mean miou_metric': 0.9524054527282715, 'Val/mean f1': 0.972952127456665, 'Val/mean precision': 0.9671515226364136, 'Val/mean recall': 0.978822648525238, 'Val/mean hd95_metric': 5.602328777313232} +Epoch [1220/4000] Training [1/16] Loss: 0.00669 +Epoch [1220/4000] Training [2/16] Loss: 0.00903 +Epoch [1220/4000] Training [3/16] Loss: 0.00913 +Epoch [1220/4000] Training [4/16] Loss: 0.00908 +Epoch [1220/4000] Training [5/16] Loss: 0.00780 +Epoch [1220/4000] Training [6/16] Loss: 0.00969 +Epoch [1220/4000] Training [7/16] Loss: 0.00722 +Epoch [1220/4000] Training [8/16] Loss: 0.00889 +Epoch [1220/4000] Training [9/16] Loss: 0.00885 +Epoch [1220/4000] Training [10/16] Loss: 0.01116 +Epoch [1220/4000] Training [11/16] Loss: 0.01626 +Epoch [1220/4000] Training [12/16] Loss: 0.01037 +Epoch [1220/4000] Training [13/16] Loss: 0.00803 +Epoch [1220/4000] Training [14/16] Loss: 0.00854 +Epoch [1220/4000] Training [15/16] Loss: 0.04737 +Epoch [1220/4000] Training [16/16] Loss: 0.00807 +Epoch [1220/4000] Training metric {'Train/mean dice_metric': 0.9934008121490479, 'Train/mean miou_metric': 0.9868009090423584, 'Train/mean f1': 0.9900112748146057, 'Train/mean precision': 0.9856094121932983, 'Train/mean recall': 0.994452714920044, 'Train/mean hd95_metric': 1.1396815776824951} +Epoch [1220/4000] Validation [1/4] Loss: 0.28795 focal_loss 0.19662 dice_loss 0.09133 +Epoch [1220/4000] Validation [2/4] Loss: 0.31314 focal_loss 0.16765 dice_loss 0.14549 +Epoch [1220/4000] Validation [3/4] Loss: 0.17537 focal_loss 0.10288 dice_loss 0.07249 +Epoch [1220/4000] Validation [4/4] Loss: 0.26622 focal_loss 0.13610 dice_loss 0.13012 +Epoch [1220/4000] Validation metric {'Val/mean dice_metric': 0.9713430404663086, 'Val/mean miou_metric': 0.9524514079093933, 'Val/mean f1': 0.9727818965911865, 'Val/mean precision': 0.9692420363426208, 'Val/mean recall': 0.9763476848602295, 'Val/mean hd95_metric': 5.8767781257629395} +Cheakpoint... +Epoch [1220/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713430404663086, 'Val/mean miou_metric': 0.9524514079093933, 'Val/mean f1': 0.9727818965911865, 'Val/mean precision': 0.9692420363426208, 'Val/mean recall': 0.9763476848602295, 'Val/mean hd95_metric': 5.8767781257629395} +Epoch [1221/4000] Training [1/16] Loss: 0.00787 +Epoch [1221/4000] Training [2/16] Loss: 0.00758 +Epoch [1221/4000] Training [3/16] Loss: 0.01118 +Epoch [1221/4000] Training [4/16] Loss: 0.01084 +Epoch [1221/4000] Training [5/16] Loss: 0.00649 +Epoch [1221/4000] Training [6/16] Loss: 0.00924 +Epoch [1221/4000] Training [7/16] Loss: 0.00938 +Epoch [1221/4000] Training [8/16] Loss: 0.00846 +Epoch [1221/4000] Training [9/16] Loss: 0.00800 +Epoch [1221/4000] Training [10/16] Loss: 0.01123 +Epoch [1221/4000] Training [11/16] Loss: 0.00937 +Epoch [1221/4000] Training [12/16] Loss: 0.01089 +Epoch [1221/4000] Training [13/16] Loss: 0.01010 +Epoch [1221/4000] Training [14/16] Loss: 0.00858 +Epoch [1221/4000] Training [15/16] Loss: 0.01018 +Epoch [1221/4000] Training [16/16] Loss: 0.00986 +Epoch [1221/4000] Training metric {'Train/mean dice_metric': 0.9932317733764648, 'Train/mean miou_metric': 0.9863108396530151, 'Train/mean f1': 0.9893621206283569, 'Train/mean precision': 0.9843105673789978, 'Train/mean recall': 0.9944658279418945, 'Train/mean hd95_metric': 1.121959924697876} +Epoch [1221/4000] Validation [1/4] Loss: 0.17531 focal_loss 0.12021 dice_loss 0.05510 +Epoch [1221/4000] Validation [2/4] Loss: 0.23787 focal_loss 0.11378 dice_loss 0.12410 +Epoch [1221/4000] Validation [3/4] Loss: 0.18034 focal_loss 0.10231 dice_loss 0.07803 +Epoch [1221/4000] Validation [4/4] Loss: 0.20045 focal_loss 0.11242 dice_loss 0.08803 +Epoch [1221/4000] Validation metric {'Val/mean dice_metric': 0.9709229469299316, 'Val/mean miou_metric': 0.9525182843208313, 'Val/mean f1': 0.972057044506073, 'Val/mean precision': 0.9689239859580994, 'Val/mean recall': 0.9752103686332703, 'Val/mean hd95_metric': 5.602803707122803} +Cheakpoint... +Epoch [1221/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709229469299316, 'Val/mean miou_metric': 0.9525182843208313, 'Val/mean f1': 0.972057044506073, 'Val/mean precision': 0.9689239859580994, 'Val/mean recall': 0.9752103686332703, 'Val/mean hd95_metric': 5.602803707122803} +Epoch [1222/4000] Training [1/16] Loss: 0.00877 +Epoch [1222/4000] Training [2/16] Loss: 0.00858 +Epoch [1222/4000] Training [3/16] Loss: 0.01112 +Epoch [1222/4000] Training [4/16] Loss: 0.00907 +Epoch [1222/4000] Training [5/16] Loss: 0.00913 +Epoch [1222/4000] Training [6/16] Loss: 0.01131 +Epoch [1222/4000] Training [7/16] Loss: 0.00912 +Epoch [1222/4000] Training [8/16] Loss: 0.01122 +Epoch [1222/4000] Training [9/16] Loss: 0.00970 +Epoch [1222/4000] Training [10/16] Loss: 0.00811 +Epoch [1222/4000] Training [11/16] Loss: 0.00936 +Epoch [1222/4000] Training [12/16] Loss: 0.01040 +Epoch [1222/4000] Training [13/16] Loss: 0.01077 +Epoch [1222/4000] Training [14/16] Loss: 0.00909 +Epoch [1222/4000] Training [15/16] Loss: 0.00800 +Epoch [1222/4000] Training [16/16] Loss: 0.00862 +Epoch [1222/4000] Training metric {'Train/mean dice_metric': 0.9932819604873657, 'Train/mean miou_metric': 0.9864112734794617, 'Train/mean f1': 0.9895721673965454, 'Train/mean precision': 0.9851101636886597, 'Train/mean recall': 0.9940747618675232, 'Train/mean hd95_metric': 1.1178503036499023} +Epoch [1222/4000] Validation [1/4] Loss: 0.24382 focal_loss 0.16735 dice_loss 0.07647 +Epoch [1222/4000] Validation [2/4] Loss: 0.22801 focal_loss 0.13082 dice_loss 0.09719 +Epoch [1222/4000] Validation [3/4] Loss: 0.17869 focal_loss 0.09888 dice_loss 0.07981 +Epoch [1222/4000] Validation [4/4] Loss: 0.21874 focal_loss 0.11997 dice_loss 0.09876 +Epoch [1222/4000] Validation metric {'Val/mean dice_metric': 0.9725082516670227, 'Val/mean miou_metric': 0.9538164138793945, 'Val/mean f1': 0.9729083776473999, 'Val/mean precision': 0.9689745306968689, 'Val/mean recall': 0.9768743515014648, 'Val/mean hd95_metric': 5.270577430725098} +Cheakpoint... +Epoch [1222/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725082516670227, 'Val/mean miou_metric': 0.9538164138793945, 'Val/mean f1': 0.9729083776473999, 'Val/mean precision': 0.9689745306968689, 'Val/mean recall': 0.9768743515014648, 'Val/mean hd95_metric': 5.270577430725098} +Epoch [1223/4000] Training [1/16] Loss: 0.01089 +Epoch [1223/4000] Training [2/16] Loss: 0.00954 +Epoch [1223/4000] Training [3/16] Loss: 0.01144 +Epoch [1223/4000] Training [4/16] Loss: 0.00778 +Epoch [1223/4000] Training [5/16] Loss: 0.00968 +Epoch [1223/4000] Training [6/16] Loss: 0.01021 +Epoch [1223/4000] Training [7/16] Loss: 0.01077 +Epoch [1223/4000] Training [8/16] Loss: 0.00956 +Epoch [1223/4000] Training [9/16] Loss: 0.00921 +Epoch [1223/4000] Training [10/16] Loss: 0.00936 +Epoch [1223/4000] Training [11/16] Loss: 0.00872 +Epoch [1223/4000] Training [12/16] Loss: 0.00882 +Epoch [1223/4000] Training [13/16] Loss: 0.00869 +Epoch [1223/4000] Training [14/16] Loss: 0.01167 +Epoch [1223/4000] Training [15/16] Loss: 0.01405 +Epoch [1223/4000] Training [16/16] Loss: 0.01386 +Epoch [1223/4000] Training metric {'Train/mean dice_metric': 0.9927912950515747, 'Train/mean miou_metric': 0.9854539632797241, 'Train/mean f1': 0.9892732501029968, 'Train/mean precision': 0.9847432374954224, 'Train/mean recall': 0.9938451647758484, 'Train/mean hd95_metric': 1.108330488204956} +Epoch [1223/4000] Validation [1/4] Loss: 0.18260 focal_loss 0.12215 dice_loss 0.06045 +Epoch [1223/4000] Validation [2/4] Loss: 0.17995 focal_loss 0.08313 dice_loss 0.09682 +Epoch [1223/4000] Validation [3/4] Loss: 0.26712 focal_loss 0.16031 dice_loss 0.10681 +Epoch [1223/4000] Validation [4/4] Loss: 0.25997 focal_loss 0.14146 dice_loss 0.11851 +Epoch [1223/4000] Validation metric {'Val/mean dice_metric': 0.9698880910873413, 'Val/mean miou_metric': 0.9508699178695679, 'Val/mean f1': 0.9724887013435364, 'Val/mean precision': 0.9667660593986511, 'Val/mean recall': 0.9782795310020447, 'Val/mean hd95_metric': 6.271912574768066} +Cheakpoint... +Epoch [1223/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698880910873413, 'Val/mean miou_metric': 0.9508699178695679, 'Val/mean f1': 0.9724887013435364, 'Val/mean precision': 0.9667660593986511, 'Val/mean recall': 0.9782795310020447, 'Val/mean hd95_metric': 6.271912574768066} +Epoch [1224/4000] Training [1/16] Loss: 0.00966 +Epoch [1224/4000] Training [2/16] Loss: 0.01226 +Epoch [1224/4000] Training [3/16] Loss: 0.00999 +Epoch [1224/4000] Training [4/16] Loss: 0.00972 +Epoch [1224/4000] Training [5/16] Loss: 0.00794 +Epoch [1224/4000] Training [6/16] Loss: 0.01020 +Epoch [1224/4000] Training [7/16] Loss: 0.00897 +Epoch [1224/4000] Training [8/16] Loss: 0.01046 +Epoch [1224/4000] Training [9/16] Loss: 0.01074 +Epoch [1224/4000] Training [10/16] Loss: 0.01128 +Epoch [1224/4000] Training [11/16] Loss: 0.01003 +Epoch [1224/4000] Training [12/16] Loss: 0.01137 +Epoch [1224/4000] Training [13/16] Loss: 0.01233 +Epoch [1224/4000] Training [14/16] Loss: 0.00964 +Epoch [1224/4000] Training [15/16] Loss: 0.00940 +Epoch [1224/4000] Training [16/16] Loss: 0.01100 +Epoch [1224/4000] Training metric {'Train/mean dice_metric': 0.9928324222564697, 'Train/mean miou_metric': 0.9855191707611084, 'Train/mean f1': 0.9891548752784729, 'Train/mean precision': 0.9843788743019104, 'Train/mean recall': 0.9939774870872498, 'Train/mean hd95_metric': 1.0895793437957764} +Epoch [1224/4000] Validation [1/4] Loss: 0.17817 focal_loss 0.11495 dice_loss 0.06322 +Epoch [1224/4000] Validation [2/4] Loss: 0.20118 focal_loss 0.10154 dice_loss 0.09963 +Epoch [1224/4000] Validation [3/4] Loss: 0.30748 focal_loss 0.19867 dice_loss 0.10882 +Epoch [1224/4000] Validation [4/4] Loss: 0.27043 focal_loss 0.15640 dice_loss 0.11403 +Epoch [1224/4000] Validation metric {'Val/mean dice_metric': 0.9681409597396851, 'Val/mean miou_metric': 0.9492790102958679, 'Val/mean f1': 0.9702479839324951, 'Val/mean precision': 0.9657309055328369, 'Val/mean recall': 0.9748073816299438, 'Val/mean hd95_metric': 6.215569019317627} +Cheakpoint... +Epoch [1224/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681409597396851, 'Val/mean miou_metric': 0.9492790102958679, 'Val/mean f1': 0.9702479839324951, 'Val/mean precision': 0.9657309055328369, 'Val/mean recall': 0.9748073816299438, 'Val/mean hd95_metric': 6.215569019317627} +Epoch [1225/4000] Training [1/16] Loss: 0.01278 +Epoch [1225/4000] Training [2/16] Loss: 0.01219 +Epoch [1225/4000] Training [3/16] Loss: 0.00896 +Epoch [1225/4000] Training [4/16] Loss: 0.00938 +Epoch [1225/4000] Training [5/16] Loss: 0.00878 +Epoch [1225/4000] Training [6/16] Loss: 0.00977 +Epoch [1225/4000] Training [7/16] Loss: 0.00889 +Epoch [1225/4000] Training [8/16] Loss: 0.00654 +Epoch [1225/4000] Training [9/16] Loss: 0.00831 +Epoch [1225/4000] Training [10/16] Loss: 0.00857 +Epoch [1225/4000] Training [11/16] Loss: 0.00901 +Epoch [1225/4000] Training [12/16] Loss: 0.01144 +Epoch [1225/4000] Training [13/16] Loss: 0.01113 +Epoch [1225/4000] Training [14/16] Loss: 0.01223 +Epoch [1225/4000] Training [15/16] Loss: 0.00789 +Epoch [1225/4000] Training [16/16] Loss: 0.00949 +Epoch [1225/4000] Training metric {'Train/mean dice_metric': 0.9929431080818176, 'Train/mean miou_metric': 0.9858172535896301, 'Train/mean f1': 0.9895802140235901, 'Train/mean precision': 0.9849239587783813, 'Train/mean recall': 0.9942806959152222, 'Train/mean hd95_metric': 1.0751049518585205} +Epoch [1225/4000] Validation [1/4] Loss: 0.18746 focal_loss 0.11865 dice_loss 0.06881 +Epoch [1225/4000] Validation [2/4] Loss: 0.27749 focal_loss 0.13904 dice_loss 0.13845 +Epoch [1225/4000] Validation [3/4] Loss: 0.15387 focal_loss 0.08682 dice_loss 0.06705 +Epoch [1225/4000] Validation [4/4] Loss: 0.27589 focal_loss 0.15267 dice_loss 0.12322 +Epoch [1225/4000] Validation metric {'Val/mean dice_metric': 0.96892249584198, 'Val/mean miou_metric': 0.9502285122871399, 'Val/mean f1': 0.9718946218490601, 'Val/mean precision': 0.9695324301719666, 'Val/mean recall': 0.9742681980133057, 'Val/mean hd95_metric': 5.698149681091309} +Cheakpoint... +Epoch [1225/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96892249584198, 'Val/mean miou_metric': 0.9502285122871399, 'Val/mean f1': 0.9718946218490601, 'Val/mean precision': 0.9695324301719666, 'Val/mean recall': 0.9742681980133057, 'Val/mean hd95_metric': 5.698149681091309} +Epoch [1226/4000] Training [1/16] Loss: 0.00968 +Epoch [1226/4000] Training [2/16] Loss: 0.00840 +Epoch [1226/4000] Training [3/16] Loss: 0.01394 +Epoch [1226/4000] Training [4/16] Loss: 0.01221 +Epoch [1226/4000] Training [5/16] Loss: 0.00856 +Epoch [1226/4000] Training [6/16] Loss: 0.00802 +Epoch [1226/4000] Training [7/16] Loss: 0.01272 +Epoch [1226/4000] Training [8/16] Loss: 0.01152 +Epoch [1226/4000] Training [9/16] Loss: 0.01089 +Epoch [1226/4000] Training [10/16] Loss: 0.01159 +Epoch [1226/4000] Training [11/16] Loss: 0.01671 +Epoch [1226/4000] Training [12/16] Loss: 0.00986 +Epoch [1226/4000] Training [13/16] Loss: 0.01129 +Epoch [1226/4000] Training [14/16] Loss: 0.00909 +Epoch [1226/4000] Training [15/16] Loss: 0.00895 +Epoch [1226/4000] Training [16/16] Loss: 0.00986 +Epoch [1226/4000] Training metric {'Train/mean dice_metric': 0.9928389191627502, 'Train/mean miou_metric': 0.9855258464813232, 'Train/mean f1': 0.989238440990448, 'Train/mean precision': 0.9845144748687744, 'Train/mean recall': 0.9940080046653748, 'Train/mean hd95_metric': 1.078120470046997} +Epoch [1226/4000] Validation [1/4] Loss: 0.47420 focal_loss 0.36674 dice_loss 0.10746 +Epoch [1226/4000] Validation [2/4] Loss: 0.25429 focal_loss 0.12737 dice_loss 0.12692 +Epoch [1226/4000] Validation [3/4] Loss: 0.20152 focal_loss 0.11129 dice_loss 0.09023 +Epoch [1226/4000] Validation [4/4] Loss: 0.24020 focal_loss 0.13119 dice_loss 0.10901 +Epoch [1226/4000] Validation metric {'Val/mean dice_metric': 0.9693554639816284, 'Val/mean miou_metric': 0.9499224424362183, 'Val/mean f1': 0.9704822301864624, 'Val/mean precision': 0.9669075012207031, 'Val/mean recall': 0.9740834832191467, 'Val/mean hd95_metric': 6.007491111755371} +Cheakpoint... +Epoch [1226/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693554639816284, 'Val/mean miou_metric': 0.9499224424362183, 'Val/mean f1': 0.9704822301864624, 'Val/mean precision': 0.9669075012207031, 'Val/mean recall': 0.9740834832191467, 'Val/mean hd95_metric': 6.007491111755371} +Epoch [1227/4000] Training [1/16] Loss: 0.01058 +Epoch [1227/4000] Training [2/16] Loss: 0.00965 +Epoch [1227/4000] Training [3/16] Loss: 0.01089 +Epoch [1227/4000] Training [4/16] Loss: 0.00945 +Epoch [1227/4000] Training [5/16] Loss: 0.01148 +Epoch [1227/4000] Training [6/16] Loss: 0.01475 +Epoch [1227/4000] Training [7/16] Loss: 0.00974 +Epoch [1227/4000] Training [8/16] Loss: 0.00765 +Epoch [1227/4000] Training [9/16] Loss: 0.01028 +Epoch [1227/4000] Training [10/16] Loss: 0.01000 +Epoch [1227/4000] Training [11/16] Loss: 0.00938 +Epoch [1227/4000] Training [12/16] Loss: 0.00666 +Epoch [1227/4000] Training [13/16] Loss: 0.01311 +Epoch [1227/4000] Training [14/16] Loss: 0.01177 +Epoch [1227/4000] Training [15/16] Loss: 0.01034 +Epoch [1227/4000] Training [16/16] Loss: 0.00853 +Epoch [1227/4000] Training metric {'Train/mean dice_metric': 0.9931116104125977, 'Train/mean miou_metric': 0.9860894680023193, 'Train/mean f1': 0.989557147026062, 'Train/mean precision': 0.9850084781646729, 'Train/mean recall': 0.9941480755805969, 'Train/mean hd95_metric': 1.3160110712051392} +Epoch [1227/4000] Validation [1/4] Loss: 0.19364 focal_loss 0.12697 dice_loss 0.06667 +Epoch [1227/4000] Validation [2/4] Loss: 0.29293 focal_loss 0.16122 dice_loss 0.13171 +Epoch [1227/4000] Validation [3/4] Loss: 0.18294 focal_loss 0.10126 dice_loss 0.08167 +Epoch [1227/4000] Validation [4/4] Loss: 0.21445 focal_loss 0.11521 dice_loss 0.09924 +Epoch [1227/4000] Validation metric {'Val/mean dice_metric': 0.9711389541625977, 'Val/mean miou_metric': 0.9523863792419434, 'Val/mean f1': 0.9716280102729797, 'Val/mean precision': 0.9679681658744812, 'Val/mean recall': 0.9753155708312988, 'Val/mean hd95_metric': 5.880246162414551} +Cheakpoint... +Epoch [1227/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711389541625977, 'Val/mean miou_metric': 0.9523863792419434, 'Val/mean f1': 0.9716280102729797, 'Val/mean precision': 0.9679681658744812, 'Val/mean recall': 0.9753155708312988, 'Val/mean hd95_metric': 5.880246162414551} +Epoch [1228/4000] Training [1/16] Loss: 0.00793 +Epoch [1228/4000] Training [2/16] Loss: 0.00868 +Epoch [1228/4000] Training [3/16] Loss: 0.00918 +Epoch [1228/4000] Training [4/16] Loss: 0.01045 +Epoch [1228/4000] Training [5/16] Loss: 0.00957 +Epoch [1228/4000] Training [6/16] Loss: 0.00914 +Epoch [1228/4000] Training [7/16] Loss: 0.00933 +Epoch [1228/4000] Training [8/16] Loss: 0.01045 +Epoch [1228/4000] Training [9/16] Loss: 0.00878 +Epoch [1228/4000] Training [10/16] Loss: 0.00845 +Epoch [1228/4000] Training [11/16] Loss: 0.01106 +Epoch [1228/4000] Training [12/16] Loss: 0.00666 +Epoch [1228/4000] Training [13/16] Loss: 0.00743 +Epoch [1228/4000] Training [14/16] Loss: 0.01245 +Epoch [1228/4000] Training [15/16] Loss: 0.00918 +Epoch [1228/4000] Training [16/16] Loss: 0.00875 +Epoch [1228/4000] Training metric {'Train/mean dice_metric': 0.9937583208084106, 'Train/mean miou_metric': 0.9873497486114502, 'Train/mean f1': 0.9900555610656738, 'Train/mean precision': 0.9857243299484253, 'Train/mean recall': 0.9944250583648682, 'Train/mean hd95_metric': 1.0543887615203857} +Epoch [1228/4000] Validation [1/4] Loss: 0.25121 focal_loss 0.16953 dice_loss 0.08168 +Epoch [1228/4000] Validation [2/4] Loss: 0.26313 focal_loss 0.13473 dice_loss 0.12839 +Epoch [1228/4000] Validation [3/4] Loss: 0.18059 focal_loss 0.09844 dice_loss 0.08216 +Epoch [1228/4000] Validation [4/4] Loss: 0.24267 focal_loss 0.13435 dice_loss 0.10832 +Epoch [1228/4000] Validation metric {'Val/mean dice_metric': 0.9699770212173462, 'Val/mean miou_metric': 0.9518305659294128, 'Val/mean f1': 0.9713509678840637, 'Val/mean precision': 0.9672781825065613, 'Val/mean recall': 0.9754581451416016, 'Val/mean hd95_metric': 6.2844414710998535} +Cheakpoint... +Epoch [1228/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699770212173462, 'Val/mean miou_metric': 0.9518305659294128, 'Val/mean f1': 0.9713509678840637, 'Val/mean precision': 0.9672781825065613, 'Val/mean recall': 0.9754581451416016, 'Val/mean hd95_metric': 6.2844414710998535} +Epoch [1229/4000] Training [1/16] Loss: 0.00773 +Epoch [1229/4000] Training [2/16] Loss: 0.01127 +Epoch [1229/4000] Training [3/16] Loss: 0.01275 +Epoch [1229/4000] Training [4/16] Loss: 0.00837 +Epoch [1229/4000] Training [5/16] Loss: 0.00800 +Epoch [1229/4000] Training [6/16] Loss: 0.01217 +Epoch [1229/4000] Training [7/16] Loss: 0.01081 +Epoch [1229/4000] Training [8/16] Loss: 0.01024 +Epoch [1229/4000] Training [9/16] Loss: 0.00697 +Epoch [1229/4000] Training [10/16] Loss: 0.01088 +Epoch [1229/4000] Training [11/16] Loss: 0.01509 +Epoch [1229/4000] Training [12/16] Loss: 0.00863 +Epoch [1229/4000] Training [13/16] Loss: 0.01181 +Epoch [1229/4000] Training [14/16] Loss: 0.00748 +Epoch [1229/4000] Training [15/16] Loss: 0.00882 +Epoch [1229/4000] Training [16/16] Loss: 0.01218 +Epoch [1229/4000] Training metric {'Train/mean dice_metric': 0.9929314851760864, 'Train/mean miou_metric': 0.9857522249221802, 'Train/mean f1': 0.9894879460334778, 'Train/mean precision': 0.9847506284713745, 'Train/mean recall': 0.9942710399627686, 'Train/mean hd95_metric': 1.1187858581542969} +Epoch [1229/4000] Validation [1/4] Loss: 0.44944 focal_loss 0.34522 dice_loss 0.10421 +Epoch [1229/4000] Validation [2/4] Loss: 0.43898 focal_loss 0.24580 dice_loss 0.19318 +Epoch [1229/4000] Validation [3/4] Loss: 0.14695 focal_loss 0.07965 dice_loss 0.06730 +Epoch [1229/4000] Validation [4/4] Loss: 0.21250 focal_loss 0.10674 dice_loss 0.10577 +Epoch [1229/4000] Validation metric {'Val/mean dice_metric': 0.9700508117675781, 'Val/mean miou_metric': 0.951817512512207, 'Val/mean f1': 0.9707289934158325, 'Val/mean precision': 0.9663529396057129, 'Val/mean recall': 0.9751448035240173, 'Val/mean hd95_metric': 5.620872974395752} +Cheakpoint... +Epoch [1229/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700508117675781, 'Val/mean miou_metric': 0.951817512512207, 'Val/mean f1': 0.9707289934158325, 'Val/mean precision': 0.9663529396057129, 'Val/mean recall': 0.9751448035240173, 'Val/mean hd95_metric': 5.620872974395752} +Epoch [1230/4000] Training [1/16] Loss: 0.00760 +Epoch [1230/4000] Training [2/16] Loss: 0.00811 +Epoch [1230/4000] Training [3/16] Loss: 0.01088 +Epoch [1230/4000] Training [4/16] Loss: 0.00730 +Epoch [1230/4000] Training [5/16] Loss: 0.00900 +Epoch [1230/4000] Training [6/16] Loss: 0.00864 +Epoch [1230/4000] Training [7/16] Loss: 0.01725 +Epoch [1230/4000] Training [8/16] Loss: 0.00685 +Epoch [1230/4000] Training [9/16] Loss: 0.01131 +Epoch [1230/4000] Training [10/16] Loss: 0.00957 +Epoch [1230/4000] Training [11/16] Loss: 0.01162 +Epoch [1230/4000] Training [12/16] Loss: 0.01406 +Epoch [1230/4000] Training [13/16] Loss: 0.00843 +Epoch [1230/4000] Training [14/16] Loss: 0.01436 +Epoch [1230/4000] Training [15/16] Loss: 0.00917 +Epoch [1230/4000] Training [16/16] Loss: 0.01204 +Epoch [1230/4000] Training metric {'Train/mean dice_metric': 0.9933750629425049, 'Train/mean miou_metric': 0.9866092801094055, 'Train/mean f1': 0.9899213314056396, 'Train/mean precision': 0.9857783913612366, 'Train/mean recall': 0.9940991997718811, 'Train/mean hd95_metric': 1.0626497268676758} +Epoch [1230/4000] Validation [1/4] Loss: 0.21613 focal_loss 0.14758 dice_loss 0.06855 +Epoch [1230/4000] Validation [2/4] Loss: 0.70925 focal_loss 0.40649 dice_loss 0.30276 +Epoch [1230/4000] Validation [3/4] Loss: 0.20514 focal_loss 0.11795 dice_loss 0.08718 +Epoch [1230/4000] Validation [4/4] Loss: 0.25859 focal_loss 0.14261 dice_loss 0.11597 +Epoch [1230/4000] Validation metric {'Val/mean dice_metric': 0.970725417137146, 'Val/mean miou_metric': 0.9527071118354797, 'Val/mean f1': 0.9729825854301453, 'Val/mean precision': 0.9685654640197754, 'Val/mean recall': 0.9774400591850281, 'Val/mean hd95_metric': 5.4179368019104} +Cheakpoint... +Epoch [1230/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970725417137146, 'Val/mean miou_metric': 0.9527071118354797, 'Val/mean f1': 0.9729825854301453, 'Val/mean precision': 0.9685654640197754, 'Val/mean recall': 0.9774400591850281, 'Val/mean hd95_metric': 5.4179368019104} +Epoch [1231/4000] Training [1/16] Loss: 0.00988 +Epoch [1231/4000] Training [2/16] Loss: 0.01271 +Epoch [1231/4000] Training [3/16] Loss: 0.00990 +Epoch [1231/4000] Training [4/16] Loss: 0.00744 +Epoch [1231/4000] Training [5/16] Loss: 0.00864 +Epoch [1231/4000] Training [6/16] Loss: 0.00859 +Epoch [1231/4000] Training [7/16] Loss: 0.00895 +Epoch [1231/4000] Training [8/16] Loss: 0.00932 +Epoch [1231/4000] Training [9/16] Loss: 0.01853 +Epoch [1231/4000] Training [10/16] Loss: 0.01055 +Epoch [1231/4000] Training [11/16] Loss: 0.01256 +Epoch [1231/4000] Training [12/16] Loss: 0.00722 +Epoch [1231/4000] Training [13/16] Loss: 0.01023 +Epoch [1231/4000] Training [14/16] Loss: 0.01051 +Epoch [1231/4000] Training [15/16] Loss: 0.01155 +Epoch [1231/4000] Training [16/16] Loss: 0.01161 +Epoch [1231/4000] Training metric {'Train/mean dice_metric': 0.9928689002990723, 'Train/mean miou_metric': 0.985698401927948, 'Train/mean f1': 0.9896495938301086, 'Train/mean precision': 0.9848517775535583, 'Train/mean recall': 0.9944943785667419, 'Train/mean hd95_metric': 1.162254810333252} +Epoch [1231/4000] Validation [1/4] Loss: 0.21591 focal_loss 0.14615 dice_loss 0.06976 +Epoch [1231/4000] Validation [2/4] Loss: 0.22493 focal_loss 0.11154 dice_loss 0.11339 +Epoch [1231/4000] Validation [3/4] Loss: 0.17442 focal_loss 0.09558 dice_loss 0.07884 +Epoch [1231/4000] Validation [4/4] Loss: 0.20540 focal_loss 0.10790 dice_loss 0.09749 +Epoch [1231/4000] Validation metric {'Val/mean dice_metric': 0.9691699147224426, 'Val/mean miou_metric': 0.9506117701530457, 'Val/mean f1': 0.9716839790344238, 'Val/mean precision': 0.9661690592765808, 'Val/mean recall': 0.9772624373435974, 'Val/mean hd95_metric': 6.4841108322143555} +Cheakpoint... +Epoch [1231/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691699147224426, 'Val/mean miou_metric': 0.9506117701530457, 'Val/mean f1': 0.9716839790344238, 'Val/mean precision': 0.9661690592765808, 'Val/mean recall': 0.9772624373435974, 'Val/mean hd95_metric': 6.4841108322143555} +Epoch [1232/4000] Training [1/16] Loss: 0.01199 +Epoch [1232/4000] Training [2/16] Loss: 0.01052 +Epoch [1232/4000] Training [3/16] Loss: 0.00747 +Epoch [1232/4000] Training [4/16] Loss: 0.00909 +Epoch [1232/4000] Training [5/16] Loss: 0.00877 +Epoch [1232/4000] Training [6/16] Loss: 0.00950 +Epoch [1232/4000] Training [7/16] Loss: 0.01116 +Epoch [1232/4000] Training [8/16] Loss: 0.00944 +Epoch [1232/4000] Training [9/16] Loss: 0.01177 +Epoch [1232/4000] Training [10/16] Loss: 0.01360 +Epoch [1232/4000] Training [11/16] Loss: 0.01287 +Epoch [1232/4000] Training [12/16] Loss: 0.00791 +Epoch [1232/4000] Training [13/16] Loss: 0.00681 +Epoch [1232/4000] Training [14/16] Loss: 0.01003 +Epoch [1232/4000] Training [15/16] Loss: 0.01538 +Epoch [1232/4000] Training [16/16] Loss: 0.01346 +Epoch [1232/4000] Training metric {'Train/mean dice_metric': 0.9927624464035034, 'Train/mean miou_metric': 0.9854140281677246, 'Train/mean f1': 0.989554226398468, 'Train/mean precision': 0.9850349426269531, 'Train/mean recall': 0.9941151738166809, 'Train/mean hd95_metric': 1.1540334224700928} +Epoch [1232/4000] Validation [1/4] Loss: 0.48064 focal_loss 0.37230 dice_loss 0.10834 +Epoch [1232/4000] Validation [2/4] Loss: 0.53283 focal_loss 0.29451 dice_loss 0.23832 +Epoch [1232/4000] Validation [3/4] Loss: 0.17692 focal_loss 0.09839 dice_loss 0.07853 +Epoch [1232/4000] Validation [4/4] Loss: 0.38948 focal_loss 0.23500 dice_loss 0.15448 +Epoch [1232/4000] Validation metric {'Val/mean dice_metric': 0.9662992358207703, 'Val/mean miou_metric': 0.9460433721542358, 'Val/mean f1': 0.9692633152008057, 'Val/mean precision': 0.9705701470375061, 'Val/mean recall': 0.9679600596427917, 'Val/mean hd95_metric': 6.195277214050293} +Cheakpoint... +Epoch [1232/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662992358207703, 'Val/mean miou_metric': 0.9460433721542358, 'Val/mean f1': 0.9692633152008057, 'Val/mean precision': 0.9705701470375061, 'Val/mean recall': 0.9679600596427917, 'Val/mean hd95_metric': 6.195277214050293} +Epoch [1233/4000] Training [1/16] Loss: 0.01208 +Epoch [1233/4000] Training [2/16] Loss: 0.01206 +Epoch [1233/4000] Training [3/16] Loss: 0.00900 +Epoch [1233/4000] Training [4/16] Loss: 0.00916 +Epoch [1233/4000] Training [5/16] Loss: 0.00844 +Epoch [1233/4000] Training [6/16] Loss: 0.01513 +Epoch [1233/4000] Training [7/16] Loss: 0.00920 +Epoch [1233/4000] Training [8/16] Loss: 0.01017 +Epoch [1233/4000] Training [9/16] Loss: 0.01114 +Epoch [1233/4000] Training [10/16] Loss: 0.00824 +Epoch [1233/4000] Training [11/16] Loss: 0.00935 +Epoch [1233/4000] Training [12/16] Loss: 0.01126 +Epoch [1233/4000] Training [13/16] Loss: 0.01498 +Epoch [1233/4000] Training [14/16] Loss: 0.01548 +Epoch [1233/4000] Training [15/16] Loss: 0.01047 +Epoch [1233/4000] Training [16/16] Loss: 0.00887 +Epoch [1233/4000] Training metric {'Train/mean dice_metric': 0.9921759366989136, 'Train/mean miou_metric': 0.9842853546142578, 'Train/mean f1': 0.9889942407608032, 'Train/mean precision': 0.9844462871551514, 'Train/mean recall': 0.993584394454956, 'Train/mean hd95_metric': 1.17454195022583} +Epoch [1233/4000] Validation [1/4] Loss: 0.26719 focal_loss 0.18229 dice_loss 0.08489 +Epoch [1233/4000] Validation [2/4] Loss: 0.33698 focal_loss 0.17835 dice_loss 0.15863 +Epoch [1233/4000] Validation [3/4] Loss: 0.19680 focal_loss 0.10891 dice_loss 0.08789 +Epoch [1233/4000] Validation [4/4] Loss: 0.24844 focal_loss 0.14426 dice_loss 0.10418 +Epoch [1233/4000] Validation metric {'Val/mean dice_metric': 0.9688140749931335, 'Val/mean miou_metric': 0.9486333727836609, 'Val/mean f1': 0.9676826000213623, 'Val/mean precision': 0.9593749046325684, 'Val/mean recall': 0.9761351943016052, 'Val/mean hd95_metric': 6.9325666427612305} +Cheakpoint... +Epoch [1233/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688140749931335, 'Val/mean miou_metric': 0.9486333727836609, 'Val/mean f1': 0.9676826000213623, 'Val/mean precision': 0.9593749046325684, 'Val/mean recall': 0.9761351943016052, 'Val/mean hd95_metric': 6.9325666427612305} +Epoch [1234/4000] Training [1/16] Loss: 0.00809 +Epoch [1234/4000] Training [2/16] Loss: 0.00846 +Epoch [1234/4000] Training [3/16] Loss: 0.00971 +Epoch [1234/4000] Training [4/16] Loss: 0.00942 +Epoch [1234/4000] Training [5/16] Loss: 0.00749 +Epoch [1234/4000] Training [6/16] Loss: 0.01042 +Epoch [1234/4000] Training [7/16] Loss: 0.00902 +Epoch [1234/4000] Training [8/16] Loss: 0.00750 +Epoch [1234/4000] Training [9/16] Loss: 0.01021 +Epoch [1234/4000] Training [10/16] Loss: 0.00972 +Epoch [1234/4000] Training [11/16] Loss: 0.00926 +Epoch [1234/4000] Training [12/16] Loss: 0.01004 +Epoch [1234/4000] Training [13/16] Loss: 0.01366 +Epoch [1234/4000] Training [14/16] Loss: 0.00880 +Epoch [1234/4000] Training [15/16] Loss: 0.01353 +Epoch [1234/4000] Training [16/16] Loss: 0.01055 +Epoch [1234/4000] Training metric {'Train/mean dice_metric': 0.9930332899093628, 'Train/mean miou_metric': 0.9859293699264526, 'Train/mean f1': 0.9894643425941467, 'Train/mean precision': 0.9850251078605652, 'Train/mean recall': 0.9939438104629517, 'Train/mean hd95_metric': 1.0963873863220215} +Epoch [1234/4000] Validation [1/4] Loss: 0.23454 focal_loss 0.15979 dice_loss 0.07475 +Epoch [1234/4000] Validation [2/4] Loss: 0.30971 focal_loss 0.15201 dice_loss 0.15770 +Epoch [1234/4000] Validation [3/4] Loss: 0.22307 focal_loss 0.12231 dice_loss 0.10076 +Epoch [1234/4000] Validation [4/4] Loss: 0.21105 focal_loss 0.11306 dice_loss 0.09799 +Epoch [1234/4000] Validation metric {'Val/mean dice_metric': 0.968277633190155, 'Val/mean miou_metric': 0.9495168924331665, 'Val/mean f1': 0.9645430445671082, 'Val/mean precision': 0.9529640078544617, 'Val/mean recall': 0.9764068126678467, 'Val/mean hd95_metric': 6.711211204528809} +Cheakpoint... +Epoch [1234/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968277633190155, 'Val/mean miou_metric': 0.9495168924331665, 'Val/mean f1': 0.9645430445671082, 'Val/mean precision': 0.9529640078544617, 'Val/mean recall': 0.9764068126678467, 'Val/mean hd95_metric': 6.711211204528809} +Epoch [1235/4000] Training [1/16] Loss: 0.00769 +Epoch [1235/4000] Training [2/16] Loss: 0.00811 +Epoch [1235/4000] Training [3/16] Loss: 0.00752 +Epoch [1235/4000] Training [4/16] Loss: 0.00872 +Epoch [1235/4000] Training [5/16] Loss: 0.01060 +Epoch [1235/4000] Training [6/16] Loss: 0.01363 +Epoch [1235/4000] Training [7/16] Loss: 0.01182 +Epoch [1235/4000] Training [8/16] Loss: 0.00988 +Epoch [1235/4000] Training [9/16] Loss: 0.01569 +Epoch [1235/4000] Training [10/16] Loss: 0.00742 +Epoch [1235/4000] Training [11/16] Loss: 0.00763 +Epoch [1235/4000] Training [12/16] Loss: 0.01239 +Epoch [1235/4000] Training [13/16] Loss: 0.01560 +Epoch [1235/4000] Training [14/16] Loss: 0.00914 +Epoch [1235/4000] Training [15/16] Loss: 0.00776 +Epoch [1235/4000] Training [16/16] Loss: 0.01031 +Epoch [1235/4000] Training metric {'Train/mean dice_metric': 0.9931849241256714, 'Train/mean miou_metric': 0.9862439632415771, 'Train/mean f1': 0.9895039200782776, 'Train/mean precision': 0.9850794672966003, 'Train/mean recall': 0.9939683079719543, 'Train/mean hd95_metric': 1.1424643993377686} +Epoch [1235/4000] Validation [1/4] Loss: 0.20532 focal_loss 0.13871 dice_loss 0.06660 +Epoch [1235/4000] Validation [2/4] Loss: 0.48336 focal_loss 0.26916 dice_loss 0.21420 +Epoch [1235/4000] Validation [3/4] Loss: 0.21575 focal_loss 0.12844 dice_loss 0.08731 +Epoch [1235/4000] Validation [4/4] Loss: 0.26871 focal_loss 0.15993 dice_loss 0.10878 +Epoch [1235/4000] Validation metric {'Val/mean dice_metric': 0.9689205288887024, 'Val/mean miou_metric': 0.9501177072525024, 'Val/mean f1': 0.968622088432312, 'Val/mean precision': 0.9617933034896851, 'Val/mean recall': 0.9755486249923706, 'Val/mean hd95_metric': 6.616192817687988} +Cheakpoint... +Epoch [1235/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689205288887024, 'Val/mean miou_metric': 0.9501177072525024, 'Val/mean f1': 0.968622088432312, 'Val/mean precision': 0.9617933034896851, 'Val/mean recall': 0.9755486249923706, 'Val/mean hd95_metric': 6.616192817687988} +Epoch [1236/4000] Training [1/16] Loss: 0.00916 +Epoch [1236/4000] Training [2/16] Loss: 0.01000 +Epoch [1236/4000] Training [3/16] Loss: 0.01040 +Epoch [1236/4000] Training [4/16] Loss: 0.00865 +Epoch [1236/4000] Training [5/16] Loss: 0.01246 +Epoch [1236/4000] Training [6/16] Loss: 0.01018 +Epoch [1236/4000] Training [7/16] Loss: 0.00832 +Epoch [1236/4000] Training [8/16] Loss: 0.00946 +Epoch [1236/4000] Training [9/16] Loss: 0.00888 +Epoch [1236/4000] Training [10/16] Loss: 0.00828 +Epoch [1236/4000] Training [11/16] Loss: 0.01040 +Epoch [1236/4000] Training [12/16] Loss: 0.00914 +Epoch [1236/4000] Training [13/16] Loss: 0.00751 +Epoch [1236/4000] Training [14/16] Loss: 0.01271 +Epoch [1236/4000] Training [15/16] Loss: 0.00795 +Epoch [1236/4000] Training [16/16] Loss: 0.00951 +Epoch [1236/4000] Training metric {'Train/mean dice_metric': 0.9934058785438538, 'Train/mean miou_metric': 0.986667275428772, 'Train/mean f1': 0.9897092580795288, 'Train/mean precision': 0.9851329922676086, 'Train/mean recall': 0.9943282604217529, 'Train/mean hd95_metric': 1.154269814491272} +Epoch [1236/4000] Validation [1/4] Loss: 0.18679 focal_loss 0.12064 dice_loss 0.06615 +Epoch [1236/4000] Validation [2/4] Loss: 0.34621 focal_loss 0.17311 dice_loss 0.17310 +Epoch [1236/4000] Validation [3/4] Loss: 0.22891 focal_loss 0.14131 dice_loss 0.08760 +Epoch [1236/4000] Validation [4/4] Loss: 0.22165 focal_loss 0.11966 dice_loss 0.10198 +Epoch [1236/4000] Validation metric {'Val/mean dice_metric': 0.9697666168212891, 'Val/mean miou_metric': 0.9512937664985657, 'Val/mean f1': 0.970321774482727, 'Val/mean precision': 0.9648712277412415, 'Val/mean recall': 0.9758344888687134, 'Val/mean hd95_metric': 6.309073448181152} +Cheakpoint... +Epoch [1236/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697666168212891, 'Val/mean miou_metric': 0.9512937664985657, 'Val/mean f1': 0.970321774482727, 'Val/mean precision': 0.9648712277412415, 'Val/mean recall': 0.9758344888687134, 'Val/mean hd95_metric': 6.309073448181152} +Epoch [1237/4000] Training [1/16] Loss: 0.00749 +Epoch [1237/4000] Training [2/16] Loss: 0.01338 +Epoch [1237/4000] Training [3/16] Loss: 0.01052 +Epoch [1237/4000] Training [4/16] Loss: 0.00944 +Epoch [1237/4000] Training [5/16] Loss: 0.00700 +Epoch [1237/4000] Training [6/16] Loss: 0.00887 +Epoch [1237/4000] Training [7/16] Loss: 0.00904 +Epoch [1237/4000] Training [8/16] Loss: 0.00880 +Epoch [1237/4000] Training [9/16] Loss: 0.00915 +Epoch [1237/4000] Training [10/16] Loss: 0.00921 +Epoch [1237/4000] Training [11/16] Loss: 0.05596 +Epoch [1237/4000] Training [12/16] Loss: 0.01149 +Epoch [1237/4000] Training [13/16] Loss: 0.01197 +Epoch [1237/4000] Training [14/16] Loss: 0.00714 +Epoch [1237/4000] Training [15/16] Loss: 0.00812 +Epoch [1237/4000] Training [16/16] Loss: 0.00994 +Epoch [1237/4000] Training metric {'Train/mean dice_metric': 0.9932330846786499, 'Train/mean miou_metric': 0.9864457845687866, 'Train/mean f1': 0.989595890045166, 'Train/mean precision': 0.9848651885986328, 'Train/mean recall': 0.9943723082542419, 'Train/mean hd95_metric': 1.3224430084228516} +Epoch [1237/4000] Validation [1/4] Loss: 0.25592 focal_loss 0.18131 dice_loss 0.07461 +Epoch [1237/4000] Validation [2/4] Loss: 0.22986 focal_loss 0.11772 dice_loss 0.11213 +Epoch [1237/4000] Validation [3/4] Loss: 0.27877 focal_loss 0.17765 dice_loss 0.10111 +Epoch [1237/4000] Validation [4/4] Loss: 0.18242 focal_loss 0.09373 dice_loss 0.08869 +Epoch [1237/4000] Validation metric {'Val/mean dice_metric': 0.9699661135673523, 'Val/mean miou_metric': 0.9509260058403015, 'Val/mean f1': 0.9712892174720764, 'Val/mean precision': 0.9688649773597717, 'Val/mean recall': 0.9737254977226257, 'Val/mean hd95_metric': 5.94019079208374} +Cheakpoint... +Epoch [1237/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699661135673523, 'Val/mean miou_metric': 0.9509260058403015, 'Val/mean f1': 0.9712892174720764, 'Val/mean precision': 0.9688649773597717, 'Val/mean recall': 0.9737254977226257, 'Val/mean hd95_metric': 5.94019079208374} +Epoch [1238/4000] Training [1/16] Loss: 0.01065 +Epoch [1238/4000] Training [2/16] Loss: 0.00779 +Epoch [1238/4000] Training [3/16] Loss: 0.00702 +Epoch [1238/4000] Training [4/16] Loss: 0.00964 +Epoch [1238/4000] Training [5/16] Loss: 0.00837 +Epoch [1238/4000] Training [6/16] Loss: 0.01156 +Epoch [1238/4000] Training [7/16] Loss: 0.01234 +Epoch [1238/4000] Training [8/16] Loss: 0.01045 +Epoch [1238/4000] Training [9/16] Loss: 0.00950 +Epoch [1238/4000] Training [10/16] Loss: 0.00996 +Epoch [1238/4000] Training [11/16] Loss: 0.01222 +Epoch [1238/4000] Training [12/16] Loss: 0.02167 +Epoch [1238/4000] Training [13/16] Loss: 0.00824 +Epoch [1238/4000] Training [14/16] Loss: 0.00892 +Epoch [1238/4000] Training [15/16] Loss: 0.00916 +Epoch [1238/4000] Training [16/16] Loss: 0.00875 +Epoch [1238/4000] Training metric {'Train/mean dice_metric': 0.9932695627212524, 'Train/mean miou_metric': 0.9864094853401184, 'Train/mean f1': 0.9897665977478027, 'Train/mean precision': 0.9850816130638123, 'Train/mean recall': 0.9944963455200195, 'Train/mean hd95_metric': 1.0813915729522705} +Epoch [1238/4000] Validation [1/4] Loss: 0.25291 focal_loss 0.17344 dice_loss 0.07947 +Epoch [1238/4000] Validation [2/4] Loss: 0.37439 focal_loss 0.18144 dice_loss 0.19294 +Epoch [1238/4000] Validation [3/4] Loss: 0.24860 focal_loss 0.15988 dice_loss 0.08871 +Epoch [1238/4000] Validation [4/4] Loss: 0.33316 focal_loss 0.19042 dice_loss 0.14274 +Epoch [1238/4000] Validation metric {'Val/mean dice_metric': 0.9682015180587769, 'Val/mean miou_metric': 0.949205756187439, 'Val/mean f1': 0.9715616106987, 'Val/mean precision': 0.9704355001449585, 'Val/mean recall': 0.9726902842521667, 'Val/mean hd95_metric': 5.673910617828369} +Cheakpoint... +Epoch [1238/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9682015180587769, 'Val/mean miou_metric': 0.949205756187439, 'Val/mean f1': 0.9715616106987, 'Val/mean precision': 0.9704355001449585, 'Val/mean recall': 0.9726902842521667, 'Val/mean hd95_metric': 5.673910617828369} +Epoch [1239/4000] Training [1/16] Loss: 0.01165 +Epoch [1239/4000] Training [2/16] Loss: 0.00960 +Epoch [1239/4000] Training [3/16] Loss: 0.00900 +Epoch [1239/4000] Training [4/16] Loss: 0.00840 +Epoch [1239/4000] Training [5/16] Loss: 0.01241 +Epoch [1239/4000] Training [6/16] Loss: 0.01506 +Epoch [1239/4000] Training [7/16] Loss: 0.01109 +Epoch [1239/4000] Training [8/16] Loss: 0.01520 +Epoch [1239/4000] Training [9/16] Loss: 0.00981 +Epoch [1239/4000] Training [10/16] Loss: 0.01226 +Epoch [1239/4000] Training [11/16] Loss: 0.00969 +Epoch [1239/4000] Training [12/16] Loss: 0.00765 +Epoch [1239/4000] Training [13/16] Loss: 0.02646 +Epoch [1239/4000] Training [14/16] Loss: 0.01087 +Epoch [1239/4000] Training [15/16] Loss: 0.01184 +Epoch [1239/4000] Training [16/16] Loss: 0.01118 +Epoch [1239/4000] Training metric {'Train/mean dice_metric': 0.9921773672103882, 'Train/mean miou_metric': 0.9844136238098145, 'Train/mean f1': 0.9887046217918396, 'Train/mean precision': 0.9842043519020081, 'Train/mean recall': 0.99324631690979, 'Train/mean hd95_metric': 1.5298622846603394} +Epoch [1239/4000] Validation [1/4] Loss: 0.17954 focal_loss 0.11816 dice_loss 0.06138 +Epoch [1239/4000] Validation [2/4] Loss: 0.36404 focal_loss 0.18667 dice_loss 0.17736 +Epoch [1239/4000] Validation [3/4] Loss: 0.25374 focal_loss 0.16166 dice_loss 0.09207 +Epoch [1239/4000] Validation [4/4] Loss: 0.22846 focal_loss 0.13028 dice_loss 0.09817 +Epoch [1239/4000] Validation metric {'Val/mean dice_metric': 0.9687978625297546, 'Val/mean miou_metric': 0.9494452476501465, 'Val/mean f1': 0.9713982939720154, 'Val/mean precision': 0.9666560292243958, 'Val/mean recall': 0.9761874079704285, 'Val/mean hd95_metric': 6.610201835632324} +Cheakpoint... +Epoch [1239/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687978625297546, 'Val/mean miou_metric': 0.9494452476501465, 'Val/mean f1': 0.9713982939720154, 'Val/mean precision': 0.9666560292243958, 'Val/mean recall': 0.9761874079704285, 'Val/mean hd95_metric': 6.610201835632324} +Epoch [1240/4000] Training [1/16] Loss: 0.00827 +Epoch [1240/4000] Training [2/16] Loss: 0.01795 +Epoch [1240/4000] Training [3/16] Loss: 0.01008 +Epoch [1240/4000] Training [4/16] Loss: 0.00882 +Epoch [1240/4000] Training [5/16] Loss: 0.01499 +Epoch [1240/4000] Training [6/16] Loss: 0.01160 +Epoch [1240/4000] Training [7/16] Loss: 0.01002 +Epoch [1240/4000] Training [8/16] Loss: 0.01022 +Epoch [1240/4000] Training [9/16] Loss: 0.00776 +Epoch [1240/4000] Training [10/16] Loss: 0.00828 +Epoch [1240/4000] Training [11/16] Loss: 0.02456 +Epoch [1240/4000] Training [12/16] Loss: 0.00852 +Epoch [1240/4000] Training [13/16] Loss: 0.00953 +Epoch [1240/4000] Training [14/16] Loss: 0.00851 +Epoch [1240/4000] Training [15/16] Loss: 0.01180 +Epoch [1240/4000] Training [16/16] Loss: 0.01447 +Epoch [1240/4000] Training metric {'Train/mean dice_metric': 0.992293119430542, 'Train/mean miou_metric': 0.9845447540283203, 'Train/mean f1': 0.9889854788780212, 'Train/mean precision': 0.9843851327896118, 'Train/mean recall': 0.9936290979385376, 'Train/mean hd95_metric': 1.401221752166748} +Epoch [1240/4000] Validation [1/4] Loss: 0.86352 focal_loss 0.66439 dice_loss 0.19913 +Epoch [1240/4000] Validation [2/4] Loss: 0.67952 focal_loss 0.38509 dice_loss 0.29444 +Epoch [1240/4000] Validation [3/4] Loss: 0.16934 focal_loss 0.09470 dice_loss 0.07464 +Epoch [1240/4000] Validation [4/4] Loss: 0.33165 focal_loss 0.18984 dice_loss 0.14180 +Epoch [1240/4000] Validation metric {'Val/mean dice_metric': 0.9580081105232239, 'Val/mean miou_metric': 0.9380132555961609, 'Val/mean f1': 0.9639419913291931, 'Val/mean precision': 0.9699575901031494, 'Val/mean recall': 0.9580006003379822, 'Val/mean hd95_metric': 6.264557361602783} +Cheakpoint... +Epoch [1240/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9580], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9580081105232239, 'Val/mean miou_metric': 0.9380132555961609, 'Val/mean f1': 0.9639419913291931, 'Val/mean precision': 0.9699575901031494, 'Val/mean recall': 0.9580006003379822, 'Val/mean hd95_metric': 6.264557361602783} +Epoch [1241/4000] Training [1/16] Loss: 0.00937 +Epoch [1241/4000] Training [2/16] Loss: 0.01049 +Epoch [1241/4000] Training [3/16] Loss: 0.01013 +Epoch [1241/4000] Training [4/16] Loss: 0.01145 +Epoch [1241/4000] Training [5/16] Loss: 0.01031 +Epoch [1241/4000] Training [6/16] Loss: 0.01454 +Epoch [1241/4000] Training [7/16] Loss: 0.02673 +Epoch [1241/4000] Training [8/16] Loss: 0.00902 +Epoch [1241/4000] Training [9/16] Loss: 0.01321 +Epoch [1241/4000] Training [10/16] Loss: 0.01037 +Epoch [1241/4000] Training [11/16] Loss: 0.01034 +Epoch [1241/4000] Training [12/16] Loss: 0.01103 +Epoch [1241/4000] Training [13/16] Loss: 0.01032 +Epoch [1241/4000] Training [14/16] Loss: 0.01021 +Epoch [1241/4000] Training [15/16] Loss: 0.01461 +Epoch [1241/4000] Training [16/16] Loss: 0.01534 +Epoch [1241/4000] Training metric {'Train/mean dice_metric': 0.9911773204803467, 'Train/mean miou_metric': 0.982498049736023, 'Train/mean f1': 0.9880189895629883, 'Train/mean precision': 0.9835253953933716, 'Train/mean recall': 0.9925537705421448, 'Train/mean hd95_metric': 1.9993631839752197} +Epoch [1241/4000] Validation [1/4] Loss: 0.52518 focal_loss 0.41487 dice_loss 0.11030 +Epoch [1241/4000] Validation [2/4] Loss: 0.32816 focal_loss 0.17872 dice_loss 0.14944 +Epoch [1241/4000] Validation [3/4] Loss: 0.27785 focal_loss 0.17579 dice_loss 0.10205 +Epoch [1241/4000] Validation [4/4] Loss: 0.27500 focal_loss 0.15080 dice_loss 0.12420 +Epoch [1241/4000] Validation metric {'Val/mean dice_metric': 0.9676061868667603, 'Val/mean miou_metric': 0.9469038248062134, 'Val/mean f1': 0.9697976112365723, 'Val/mean precision': 0.9657469987869263, 'Val/mean recall': 0.9738823175430298, 'Val/mean hd95_metric': 7.198359489440918} +Cheakpoint... +Epoch [1241/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676061868667603, 'Val/mean miou_metric': 0.9469038248062134, 'Val/mean f1': 0.9697976112365723, 'Val/mean precision': 0.9657469987869263, 'Val/mean recall': 0.9738823175430298, 'Val/mean hd95_metric': 7.198359489440918} +Epoch [1242/4000] Training [1/16] Loss: 0.01539 +Epoch [1242/4000] Training [2/16] Loss: 0.00982 +Epoch [1242/4000] Training [3/16] Loss: 0.01367 +Epoch [1242/4000] Training [4/16] Loss: 0.00915 +Epoch [1242/4000] Training [5/16] Loss: 0.01539 +Epoch [1242/4000] Training [6/16] Loss: 0.01426 +Epoch [1242/4000] Training [7/16] Loss: 0.00757 +Epoch [1242/4000] Training [8/16] Loss: 0.01561 +Epoch [1242/4000] Training [9/16] Loss: 0.00875 +Epoch [1242/4000] Training [10/16] Loss: 0.00907 +Epoch [1242/4000] Training [11/16] Loss: 0.01057 +Epoch [1242/4000] Training [12/16] Loss: 0.01029 +Epoch [1242/4000] Training [13/16] Loss: 0.00978 +Epoch [1242/4000] Training [14/16] Loss: 0.01105 +Epoch [1242/4000] Training [15/16] Loss: 0.01144 +Epoch [1242/4000] Training [16/16] Loss: 0.01371 +Epoch [1242/4000] Training metric {'Train/mean dice_metric': 0.9927356243133545, 'Train/mean miou_metric': 0.9853429794311523, 'Train/mean f1': 0.9889416098594666, 'Train/mean precision': 0.9841541647911072, 'Train/mean recall': 0.9937759041786194, 'Train/mean hd95_metric': 1.2167823314666748} +Epoch [1242/4000] Validation [1/4] Loss: 0.35735 focal_loss 0.26591 dice_loss 0.09144 +Epoch [1242/4000] Validation [2/4] Loss: 0.29673 focal_loss 0.16043 dice_loss 0.13630 +Epoch [1242/4000] Validation [3/4] Loss: 0.22367 focal_loss 0.13058 dice_loss 0.09309 +Epoch [1242/4000] Validation [4/4] Loss: 0.23287 focal_loss 0.13128 dice_loss 0.10158 +Epoch [1242/4000] Validation metric {'Val/mean dice_metric': 0.967136025428772, 'Val/mean miou_metric': 0.9479650259017944, 'Val/mean f1': 0.970425009727478, 'Val/mean precision': 0.965222179889679, 'Val/mean recall': 0.9756842851638794, 'Val/mean hd95_metric': 6.111888408660889} +Cheakpoint... +Epoch [1242/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967136025428772, 'Val/mean miou_metric': 0.9479650259017944, 'Val/mean f1': 0.970425009727478, 'Val/mean precision': 0.965222179889679, 'Val/mean recall': 0.9756842851638794, 'Val/mean hd95_metric': 6.111888408660889} +Epoch [1243/4000] Training [1/16] Loss: 0.00918 +Epoch [1243/4000] Training [2/16] Loss: 0.01061 +Epoch [1243/4000] Training [3/16] Loss: 0.00858 +Epoch [1243/4000] Training [4/16] Loss: 0.00974 +Epoch [1243/4000] Training [5/16] Loss: 0.00852 +Epoch [1243/4000] Training [6/16] Loss: 0.01243 +Epoch [1243/4000] Training [7/16] Loss: 0.00805 +Epoch [1243/4000] Training [8/16] Loss: 0.01079 +Epoch [1243/4000] Training [9/16] Loss: 0.00811 +Epoch [1243/4000] Training [10/16] Loss: 0.01293 +Epoch [1243/4000] Training [11/16] Loss: 0.00979 +Epoch [1243/4000] Training [12/16] Loss: 0.01265 +Epoch [1243/4000] Training [13/16] Loss: 0.01222 +Epoch [1243/4000] Training [14/16] Loss: 0.01236 +Epoch [1243/4000] Training [15/16] Loss: 0.02040 +Epoch [1243/4000] Training [16/16] Loss: 0.00920 +Epoch [1243/4000] Training metric {'Train/mean dice_metric': 0.9916175603866577, 'Train/mean miou_metric': 0.9838481545448303, 'Train/mean f1': 0.9884623289108276, 'Train/mean precision': 0.9838129878044128, 'Train/mean recall': 0.9931557774543762, 'Train/mean hd95_metric': 1.738344669342041} +Epoch [1243/4000] Validation [1/4] Loss: 0.14743 focal_loss 0.09296 dice_loss 0.05446 +Epoch [1243/4000] Validation [2/4] Loss: 0.36465 focal_loss 0.17798 dice_loss 0.18667 +Epoch [1243/4000] Validation [3/4] Loss: 0.35676 focal_loss 0.22192 dice_loss 0.13484 +Epoch [1243/4000] Validation [4/4] Loss: 0.21732 focal_loss 0.10345 dice_loss 0.11387 +Epoch [1243/4000] Validation metric {'Val/mean dice_metric': 0.9612763524055481, 'Val/mean miou_metric': 0.9414936900138855, 'Val/mean f1': 0.9684110879898071, 'Val/mean precision': 0.9642300009727478, 'Val/mean recall': 0.972628653049469, 'Val/mean hd95_metric': 7.429047584533691} +Cheakpoint... +Epoch [1243/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9613], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9612763524055481, 'Val/mean miou_metric': 0.9414936900138855, 'Val/mean f1': 0.9684110879898071, 'Val/mean precision': 0.9642300009727478, 'Val/mean recall': 0.972628653049469, 'Val/mean hd95_metric': 7.429047584533691} +Epoch [1244/4000] Training [1/16] Loss: 0.00908 +Epoch [1244/4000] Training [2/16] Loss: 0.01044 +Epoch [1244/4000] Training [3/16] Loss: 0.01017 +Epoch [1244/4000] Training [4/16] Loss: 0.00855 +Epoch [1244/4000] Training [5/16] Loss: 0.01027 +Epoch [1244/4000] Training [6/16] Loss: 0.01005 +Epoch [1244/4000] Training [7/16] Loss: 0.01049 +Epoch [1244/4000] Training [8/16] Loss: 0.01040 +Epoch [1244/4000] Training [9/16] Loss: 0.00884 +Epoch [1244/4000] Training [10/16] Loss: 0.01360 +Epoch [1244/4000] Training [11/16] Loss: 0.01571 +Epoch [1244/4000] Training [12/16] Loss: 0.01415 +Epoch [1244/4000] Training [13/16] Loss: 0.01249 +Epoch [1244/4000] Training [14/16] Loss: 0.00867 +Epoch [1244/4000] Training [15/16] Loss: 0.00954 +Epoch [1244/4000] Training [16/16] Loss: 0.01257 +Epoch [1244/4000] Training metric {'Train/mean dice_metric': 0.9911344051361084, 'Train/mean miou_metric': 0.9832813739776611, 'Train/mean f1': 0.9874736666679382, 'Train/mean precision': 0.9824785590171814, 'Train/mean recall': 0.992519736289978, 'Train/mean hd95_metric': 2.2316553592681885} +Epoch [1244/4000] Validation [1/4] Loss: 0.37602 focal_loss 0.21177 dice_loss 0.16425 +Epoch [1244/4000] Validation [2/4] Loss: 0.60260 focal_loss 0.33692 dice_loss 0.26568 +Epoch [1244/4000] Validation [3/4] Loss: 0.20428 focal_loss 0.11089 dice_loss 0.09339 +Epoch [1244/4000] Validation [4/4] Loss: 0.39571 focal_loss 0.20520 dice_loss 0.19051 +Epoch [1244/4000] Validation metric {'Val/mean dice_metric': 0.9540433883666992, 'Val/mean miou_metric': 0.9322707056999207, 'Val/mean f1': 0.9631187319755554, 'Val/mean precision': 0.971416711807251, 'Val/mean recall': 0.9549614191055298, 'Val/mean hd95_metric': 7.4896087646484375} +Cheakpoint... +Epoch [1244/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9540], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9540433883666992, 'Val/mean miou_metric': 0.9322707056999207, 'Val/mean f1': 0.9631187319755554, 'Val/mean precision': 0.971416711807251, 'Val/mean recall': 0.9549614191055298, 'Val/mean hd95_metric': 7.4896087646484375} +Epoch [1245/4000] Training [1/16] Loss: 0.01567 +Epoch [1245/4000] Training [2/16] Loss: 0.01001 +Epoch [1245/4000] Training [3/16] Loss: 0.02048 +Epoch [1245/4000] Training [4/16] Loss: 0.02281 +Epoch [1245/4000] Training [5/16] Loss: 0.00950 +Epoch [1245/4000] Training [6/16] Loss: 0.00859 +Epoch [1245/4000] Training [7/16] Loss: 0.01256 +Epoch [1245/4000] Training [8/16] Loss: 0.01759 +Epoch [1245/4000] Training [9/16] Loss: 0.00928 +Epoch [1245/4000] Training [10/16] Loss: 0.01161 +Epoch [1245/4000] Training [11/16] Loss: 0.01041 +Epoch [1245/4000] Training [12/16] Loss: 0.00915 +Epoch [1245/4000] Training [13/16] Loss: 0.01129 +Epoch [1245/4000] Training [14/16] Loss: 0.01301 +Epoch [1245/4000] Training [15/16] Loss: 0.00907 +Epoch [1245/4000] Training [16/16] Loss: 0.01140 +Epoch [1245/4000] Training metric {'Train/mean dice_metric': 0.991392195224762, 'Train/mean miou_metric': 0.982822835445404, 'Train/mean f1': 0.9873847961425781, 'Train/mean precision': 0.9827871918678284, 'Train/mean recall': 0.99202561378479, 'Train/mean hd95_metric': 2.042961597442627} +Epoch [1245/4000] Validation [1/4] Loss: 0.31995 focal_loss 0.23000 dice_loss 0.08995 +Epoch [1245/4000] Validation [2/4] Loss: 0.55815 focal_loss 0.29730 dice_loss 0.26085 +Epoch [1245/4000] Validation [3/4] Loss: 0.20533 focal_loss 0.12074 dice_loss 0.08459 +Epoch [1245/4000] Validation [4/4] Loss: 0.38782 focal_loss 0.22480 dice_loss 0.16302 +Epoch [1245/4000] Validation metric {'Val/mean dice_metric': 0.9614003300666809, 'Val/mean miou_metric': 0.9396520853042603, 'Val/mean f1': 0.9666054248809814, 'Val/mean precision': 0.9685914516448975, 'Val/mean recall': 0.9646273851394653, 'Val/mean hd95_metric': 9.540314674377441} +Cheakpoint... +Epoch [1245/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9614], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9614003300666809, 'Val/mean miou_metric': 0.9396520853042603, 'Val/mean f1': 0.9666054248809814, 'Val/mean precision': 0.9685914516448975, 'Val/mean recall': 0.9646273851394653, 'Val/mean hd95_metric': 9.540314674377441} +Epoch [1246/4000] Training [1/16] Loss: 0.01036 +Epoch [1246/4000] Training [2/16] Loss: 0.00974 +Epoch [1246/4000] Training [3/16] Loss: 0.01407 +Epoch [1246/4000] Training [4/16] Loss: 0.01065 +Epoch [1246/4000] Training [5/16] Loss: 0.01073 +Epoch [1246/4000] Training [6/16] Loss: 0.01488 +Epoch [1246/4000] Training [7/16] Loss: 0.01038 +Epoch [1246/4000] Training [8/16] Loss: 0.01094 +Epoch [1246/4000] Training [9/16] Loss: 0.01630 +Epoch [1246/4000] Training [10/16] Loss: 0.01467 +Epoch [1246/4000] Training [11/16] Loss: 0.01214 +Epoch [1246/4000] Training [12/16] Loss: 0.01414 +Epoch [1246/4000] Training [13/16] Loss: 0.00949 +Epoch [1246/4000] Training [14/16] Loss: 0.01032 +Epoch [1246/4000] Training [15/16] Loss: 0.00940 +Epoch [1246/4000] Training [16/16] Loss: 0.00941 +Epoch [1246/4000] Training metric {'Train/mean dice_metric': 0.9920026659965515, 'Train/mean miou_metric': 0.9839404821395874, 'Train/mean f1': 0.988195538520813, 'Train/mean precision': 0.9838994145393372, 'Train/mean recall': 0.9925293326377869, 'Train/mean hd95_metric': 1.5511292219161987} +Epoch [1246/4000] Validation [1/4] Loss: 0.21099 focal_loss 0.13536 dice_loss 0.07563 +Epoch [1246/4000] Validation [2/4] Loss: 0.48807 focal_loss 0.24049 dice_loss 0.24758 +Epoch [1246/4000] Validation [3/4] Loss: 0.34604 focal_loss 0.23918 dice_loss 0.10686 +Epoch [1246/4000] Validation [4/4] Loss: 0.31532 focal_loss 0.17939 dice_loss 0.13592 +Epoch [1246/4000] Validation metric {'Val/mean dice_metric': 0.9633343815803528, 'Val/mean miou_metric': 0.94276362657547, 'Val/mean f1': 0.967631995677948, 'Val/mean precision': 0.9664878249168396, 'Val/mean recall': 0.9687787294387817, 'Val/mean hd95_metric': 7.33908224105835} +Cheakpoint... +Epoch [1246/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9633343815803528, 'Val/mean miou_metric': 0.94276362657547, 'Val/mean f1': 0.967631995677948, 'Val/mean precision': 0.9664878249168396, 'Val/mean recall': 0.9687787294387817, 'Val/mean hd95_metric': 7.33908224105835} +Epoch [1247/4000] Training [1/16] Loss: 0.01661 +Epoch [1247/4000] Training [2/16] Loss: 0.01022 +Epoch [1247/4000] Training [3/16] Loss: 0.01314 +Epoch [1247/4000] Training [4/16] Loss: 0.01180 +Epoch [1247/4000] Training [5/16] Loss: 0.01043 +Epoch [1247/4000] Training [6/16] Loss: 0.01074 +Epoch [1247/4000] Training [7/16] Loss: 0.00780 +Epoch [1247/4000] Training [8/16] Loss: 0.00717 +Epoch [1247/4000] Training [9/16] Loss: 0.04371 +Epoch [1247/4000] Training [10/16] Loss: 0.00943 +Epoch [1247/4000] Training [11/16] Loss: 0.00863 +Epoch [1247/4000] Training [12/16] Loss: 0.01055 +Epoch [1247/4000] Training [13/16] Loss: 0.01532 +Epoch [1247/4000] Training [14/16] Loss: 0.02016 +Epoch [1247/4000] Training [15/16] Loss: 0.01300 +Epoch [1247/4000] Training [16/16] Loss: 0.01004 +Epoch [1247/4000] Training metric {'Train/mean dice_metric': 0.9919925332069397, 'Train/mean miou_metric': 0.9839382767677307, 'Train/mean f1': 0.9874056577682495, 'Train/mean precision': 0.9823018312454224, 'Train/mean recall': 0.9925627112388611, 'Train/mean hd95_metric': 1.7549329996109009} +Epoch [1247/4000] Validation [1/4] Loss: 0.85497 focal_loss 0.69290 dice_loss 0.16207 +Epoch [1247/4000] Validation [2/4] Loss: 0.54642 focal_loss 0.28023 dice_loss 0.26619 +Epoch [1247/4000] Validation [3/4] Loss: 0.38556 focal_loss 0.23924 dice_loss 0.14631 +Epoch [1247/4000] Validation [4/4] Loss: 0.36932 focal_loss 0.22751 dice_loss 0.14181 +Epoch [1247/4000] Validation metric {'Val/mean dice_metric': 0.9575796127319336, 'Val/mean miou_metric': 0.9364754557609558, 'Val/mean f1': 0.9624872803688049, 'Val/mean precision': 0.969351053237915, 'Val/mean recall': 0.9557200074195862, 'Val/mean hd95_metric': 7.095531463623047} +Cheakpoint... +Epoch [1247/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9576], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9575796127319336, 'Val/mean miou_metric': 0.9364754557609558, 'Val/mean f1': 0.9624872803688049, 'Val/mean precision': 0.969351053237915, 'Val/mean recall': 0.9557200074195862, 'Val/mean hd95_metric': 7.095531463623047} +Epoch [1248/4000] Training [1/16] Loss: 0.01165 +Epoch [1248/4000] Training [2/16] Loss: 0.00844 +Epoch [1248/4000] Training [3/16] Loss: 0.01056 +Epoch [1248/4000] Training [4/16] Loss: 0.01283 +Epoch [1248/4000] Training [5/16] Loss: 0.00950 +Epoch [1248/4000] Training [6/16] Loss: 0.01374 +Epoch [1248/4000] Training [7/16] Loss: 0.01086 +Epoch [1248/4000] Training [8/16] Loss: 0.01172 +Epoch [1248/4000] Training [9/16] Loss: 0.01130 +Epoch [1248/4000] Training [10/16] Loss: 0.01062 +Epoch [1248/4000] Training [11/16] Loss: 0.00850 +Epoch [1248/4000] Training [12/16] Loss: 0.01040 +Epoch [1248/4000] Training [13/16] Loss: 0.01770 +Epoch [1248/4000] Training [14/16] Loss: 0.01048 +Epoch [1248/4000] Training [15/16] Loss: 0.01184 +Epoch [1248/4000] Training [16/16] Loss: 0.00955 +Epoch [1248/4000] Training metric {'Train/mean dice_metric': 0.9926753640174866, 'Train/mean miou_metric': 0.9852503538131714, 'Train/mean f1': 0.9886688590049744, 'Train/mean precision': 0.9843575358390808, 'Train/mean recall': 0.9930180311203003, 'Train/mean hd95_metric': 1.604790210723877} +Epoch [1248/4000] Validation [1/4] Loss: 0.68276 focal_loss 0.55869 dice_loss 0.12408 +Epoch [1248/4000] Validation [2/4] Loss: 0.44249 focal_loss 0.24522 dice_loss 0.19727 +Epoch [1248/4000] Validation [3/4] Loss: 0.29421 focal_loss 0.19712 dice_loss 0.09709 +Epoch [1248/4000] Validation [4/4] Loss: 0.19634 focal_loss 0.10939 dice_loss 0.08696 +Epoch [1248/4000] Validation metric {'Val/mean dice_metric': 0.9688050150871277, 'Val/mean miou_metric': 0.948651134967804, 'Val/mean f1': 0.9693996906280518, 'Val/mean precision': 0.9689279794692993, 'Val/mean recall': 0.9698718190193176, 'Val/mean hd95_metric': 6.7666521072387695} +Cheakpoint... +Epoch [1248/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688050150871277, 'Val/mean miou_metric': 0.948651134967804, 'Val/mean f1': 0.9693996906280518, 'Val/mean precision': 0.9689279794692993, 'Val/mean recall': 0.9698718190193176, 'Val/mean hd95_metric': 6.7666521072387695} +Epoch [1249/4000] Training [1/16] Loss: 0.00900 +Epoch [1249/4000] Training [2/16] Loss: 0.01130 +Epoch [1249/4000] Training [3/16] Loss: 0.00912 +Epoch [1249/4000] Training [4/16] Loss: 0.00908 +Epoch [1249/4000] Training [5/16] Loss: 0.01045 +Epoch [1249/4000] Training [6/16] Loss: 0.00902 +Epoch [1249/4000] Training [7/16] Loss: 0.00978 +Epoch [1249/4000] Training [8/16] Loss: 0.00784 +Epoch [1249/4000] Training [9/16] Loss: 0.01029 +Epoch [1249/4000] Training [10/16] Loss: 0.00921 +Epoch [1249/4000] Training [11/16] Loss: 0.01268 +Epoch [1249/4000] Training [12/16] Loss: 0.01022 +Epoch [1249/4000] Training [13/16] Loss: 0.00952 +Epoch [1249/4000] Training [14/16] Loss: 0.01158 +Epoch [1249/4000] Training [15/16] Loss: 0.01553 +Epoch [1249/4000] Training [16/16] Loss: 0.02199 +Epoch [1249/4000] Training metric {'Train/mean dice_metric': 0.9930795431137085, 'Train/mean miou_metric': 0.9860077500343323, 'Train/mean f1': 0.9886500239372253, 'Train/mean precision': 0.9837031364440918, 'Train/mean recall': 0.9936469793319702, 'Train/mean hd95_metric': 1.476801872253418} +Epoch [1249/4000] Validation [1/4] Loss: 0.31197 focal_loss 0.21296 dice_loss 0.09901 +Epoch [1249/4000] Validation [2/4] Loss: 0.27675 focal_loss 0.14584 dice_loss 0.13091 +Epoch [1249/4000] Validation [3/4] Loss: 0.23027 focal_loss 0.13338 dice_loss 0.09688 +Epoch [1249/4000] Validation [4/4] Loss: 0.23841 focal_loss 0.12292 dice_loss 0.11549 +Epoch [1249/4000] Validation metric {'Val/mean dice_metric': 0.9666656255722046, 'Val/mean miou_metric': 0.9469959139823914, 'Val/mean f1': 0.9680299162864685, 'Val/mean precision': 0.9597049951553345, 'Val/mean recall': 0.9765004515647888, 'Val/mean hd95_metric': 7.231985569000244} +Cheakpoint... +Epoch [1249/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666656255722046, 'Val/mean miou_metric': 0.9469959139823914, 'Val/mean f1': 0.9680299162864685, 'Val/mean precision': 0.9597049951553345, 'Val/mean recall': 0.9765004515647888, 'Val/mean hd95_metric': 7.231985569000244} +Epoch [1250/4000] Training [1/16] Loss: 0.01295 +Epoch [1250/4000] Training [2/16] Loss: 0.01054 +Epoch [1250/4000] Training [3/16] Loss: 0.00859 +Epoch [1250/4000] Training [4/16] Loss: 0.01011 +Epoch [1250/4000] Training [5/16] Loss: 0.00899 +Epoch [1250/4000] Training [6/16] Loss: 0.01114 +Epoch [1250/4000] Training [7/16] Loss: 0.00844 +Epoch [1250/4000] Training [8/16] Loss: 0.01357 +Epoch [1250/4000] Training [9/16] Loss: 0.00876 +Epoch [1250/4000] Training [10/16] Loss: 0.01132 +Epoch [1250/4000] Training [11/16] Loss: 0.01163 +Epoch [1250/4000] Training [12/16] Loss: 0.01017 +Epoch [1250/4000] Training [13/16] Loss: 0.00920 +Epoch [1250/4000] Training [14/16] Loss: 0.00961 +Epoch [1250/4000] Training [15/16] Loss: 0.01360 +Epoch [1250/4000] Training [16/16] Loss: 0.01055 +Epoch [1250/4000] Training metric {'Train/mean dice_metric': 0.9925696849822998, 'Train/mean miou_metric': 0.9850825667381287, 'Train/mean f1': 0.9885662794113159, 'Train/mean precision': 0.983809232711792, 'Train/mean recall': 0.9933695197105408, 'Train/mean hd95_metric': 1.5972589254379272} +Epoch [1250/4000] Validation [1/4] Loss: 0.77417 focal_loss 0.59725 dice_loss 0.17692 +Epoch [1250/4000] Validation [2/4] Loss: 0.49603 focal_loss 0.29783 dice_loss 0.19820 +Epoch [1250/4000] Validation [3/4] Loss: 0.14434 focal_loss 0.07508 dice_loss 0.06927 +Epoch [1250/4000] Validation [4/4] Loss: 0.66691 focal_loss 0.41972 dice_loss 0.24719 +Epoch [1250/4000] Validation metric {'Val/mean dice_metric': 0.9584220051765442, 'Val/mean miou_metric': 0.9383241534233093, 'Val/mean f1': 0.9640451669692993, 'Val/mean precision': 0.9729117751121521, 'Val/mean recall': 0.9553385972976685, 'Val/mean hd95_metric': 6.161184310913086} +Cheakpoint... +Epoch [1250/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9584], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9584220051765442, 'Val/mean miou_metric': 0.9383241534233093, 'Val/mean f1': 0.9640451669692993, 'Val/mean precision': 0.9729117751121521, 'Val/mean recall': 0.9553385972976685, 'Val/mean hd95_metric': 6.161184310913086} +Epoch [1251/4000] Training [1/16] Loss: 0.00893 +Epoch [1251/4000] Training [2/16] Loss: 0.01430 +Epoch [1251/4000] Training [3/16] Loss: 0.01222 +Epoch [1251/4000] Training [4/16] Loss: 0.00965 +Epoch [1251/4000] Training [5/16] Loss: 0.01545 +Epoch [1251/4000] Training [6/16] Loss: 0.01089 +Epoch [1251/4000] Training [7/16] Loss: 0.00922 +Epoch [1251/4000] Training [8/16] Loss: 0.01115 +Epoch [1251/4000] Training [9/16] Loss: 0.01106 +Epoch [1251/4000] Training [10/16] Loss: 0.00722 +Epoch [1251/4000] Training [11/16] Loss: 0.01203 +Epoch [1251/4000] Training [12/16] Loss: 0.01415 +Epoch [1251/4000] Training [13/16] Loss: 0.00935 +Epoch [1251/4000] Training [14/16] Loss: 0.00856 +Epoch [1251/4000] Training [15/16] Loss: 0.01228 +Epoch [1251/4000] Training [16/16] Loss: 0.01147 +Epoch [1251/4000] Training metric {'Train/mean dice_metric': 0.9923921823501587, 'Train/mean miou_metric': 0.9847609400749207, 'Train/mean f1': 0.9887294769287109, 'Train/mean precision': 0.984452486038208, 'Train/mean recall': 0.9930437803268433, 'Train/mean hd95_metric': 1.5535547733306885} +Epoch [1251/4000] Validation [1/4] Loss: 0.43556 focal_loss 0.29907 dice_loss 0.13649 +Epoch [1251/4000] Validation [2/4] Loss: 0.49190 focal_loss 0.30392 dice_loss 0.18798 +Epoch [1251/4000] Validation [3/4] Loss: 0.24193 focal_loss 0.13960 dice_loss 0.10233 +Epoch [1251/4000] Validation [4/4] Loss: 0.49604 focal_loss 0.28916 dice_loss 0.20688 +Epoch [1251/4000] Validation metric {'Val/mean dice_metric': 0.9631231427192688, 'Val/mean miou_metric': 0.9428248405456543, 'Val/mean f1': 0.9661903381347656, 'Val/mean precision': 0.9700401425361633, 'Val/mean recall': 0.9623709917068481, 'Val/mean hd95_metric': 7.898629665374756} +Cheakpoint... +Epoch [1251/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9631], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9631231427192688, 'Val/mean miou_metric': 0.9428248405456543, 'Val/mean f1': 0.9661903381347656, 'Val/mean precision': 0.9700401425361633, 'Val/mean recall': 0.9623709917068481, 'Val/mean hd95_metric': 7.898629665374756} +Epoch [1252/4000] Training [1/16] Loss: 0.00867 +Epoch [1252/4000] Training [2/16] Loss: 0.01257 +Epoch [1252/4000] Training [3/16] Loss: 0.00801 +Epoch [1252/4000] Training [4/16] Loss: 0.01148 +Epoch [1252/4000] Training [5/16] Loss: 0.00881 +Epoch [1252/4000] Training [6/16] Loss: 0.02787 +Epoch [1252/4000] Training [7/16] Loss: 0.01152 +Epoch [1252/4000] Training [8/16] Loss: 0.00925 +Epoch [1252/4000] Training [9/16] Loss: 0.01097 +Epoch [1252/4000] Training [10/16] Loss: 0.00889 +Epoch [1252/4000] Training [11/16] Loss: 0.00905 +Epoch [1252/4000] Training [12/16] Loss: 0.03911 +Epoch [1252/4000] Training [13/16] Loss: 0.00994 +Epoch [1252/4000] Training [14/16] Loss: 0.00869 +Epoch [1252/4000] Training [15/16] Loss: 0.00941 +Epoch [1252/4000] Training [16/16] Loss: 0.01538 +Epoch [1252/4000] Training metric {'Train/mean dice_metric': 0.9929807186126709, 'Train/mean miou_metric': 0.9858360290527344, 'Train/mean f1': 0.9883335828781128, 'Train/mean precision': 0.9835638403892517, 'Train/mean recall': 0.993149995803833, 'Train/mean hd95_metric': 1.549001693725586} +Epoch [1252/4000] Validation [1/4] Loss: 0.18215 focal_loss 0.11573 dice_loss 0.06641 +Epoch [1252/4000] Validation [2/4] Loss: 0.59603 focal_loss 0.39679 dice_loss 0.19924 +Epoch [1252/4000] Validation [3/4] Loss: 0.27199 focal_loss 0.17077 dice_loss 0.10122 +Epoch [1252/4000] Validation [4/4] Loss: 0.36842 focal_loss 0.21852 dice_loss 0.14990 +Epoch [1252/4000] Validation metric {'Val/mean dice_metric': 0.9688164591789246, 'Val/mean miou_metric': 0.9487237930297852, 'Val/mean f1': 0.9687440395355225, 'Val/mean precision': 0.9653823375701904, 'Val/mean recall': 0.972129225730896, 'Val/mean hd95_metric': 6.763680458068848} +Cheakpoint... +Epoch [1252/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688164591789246, 'Val/mean miou_metric': 0.9487237930297852, 'Val/mean f1': 0.9687440395355225, 'Val/mean precision': 0.9653823375701904, 'Val/mean recall': 0.972129225730896, 'Val/mean hd95_metric': 6.763680458068848} +Epoch [1253/4000] Training [1/16] Loss: 0.01125 +Epoch [1253/4000] Training [2/16] Loss: 0.01261 +Epoch [1253/4000] Training [3/16] Loss: 0.01801 +Epoch [1253/4000] Training [4/16] Loss: 0.01148 +Epoch [1253/4000] Training [5/16] Loss: 0.01119 +Epoch [1253/4000] Training [6/16] Loss: 0.01154 +Epoch [1253/4000] Training [7/16] Loss: 0.01084 +Epoch [1253/4000] Training [8/16] Loss: 0.01122 +Epoch [1253/4000] Training [9/16] Loss: 0.01206 +Epoch [1253/4000] Training [10/16] Loss: 0.00849 +Epoch [1253/4000] Training [11/16] Loss: 0.01122 +Epoch [1253/4000] Training [12/16] Loss: 0.00906 +Epoch [1253/4000] Training [13/16] Loss: 0.00888 +Epoch [1253/4000] Training [14/16] Loss: 0.01112 +Epoch [1253/4000] Training [15/16] Loss: 0.00917 +Epoch [1253/4000] Training [16/16] Loss: 0.00932 +Epoch [1253/4000] Training metric {'Train/mean dice_metric': 0.9924756288528442, 'Train/mean miou_metric': 0.9848697185516357, 'Train/mean f1': 0.9885078072547913, 'Train/mean precision': 0.9841040968894958, 'Train/mean recall': 0.9929511547088623, 'Train/mean hd95_metric': 1.4474220275878906} +Epoch [1253/4000] Validation [1/4] Loss: 0.26373 focal_loss 0.18349 dice_loss 0.08023 +Epoch [1253/4000] Validation [2/4] Loss: 0.43440 focal_loss 0.24132 dice_loss 0.19308 +Epoch [1253/4000] Validation [3/4] Loss: 0.27730 focal_loss 0.16313 dice_loss 0.11418 +Epoch [1253/4000] Validation [4/4] Loss: 0.31247 focal_loss 0.16622 dice_loss 0.14625 +Epoch [1253/4000] Validation metric {'Val/mean dice_metric': 0.9674550294876099, 'Val/mean miou_metric': 0.9471451044082642, 'Val/mean f1': 0.9701663851737976, 'Val/mean precision': 0.9699528813362122, 'Val/mean recall': 0.9703798890113831, 'Val/mean hd95_metric': 6.76257848739624} +Cheakpoint... +Epoch [1253/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674550294876099, 'Val/mean miou_metric': 0.9471451044082642, 'Val/mean f1': 0.9701663851737976, 'Val/mean precision': 0.9699528813362122, 'Val/mean recall': 0.9703798890113831, 'Val/mean hd95_metric': 6.76257848739624} +Epoch [1254/4000] Training [1/16] Loss: 0.00791 +Epoch [1254/4000] Training [2/16] Loss: 0.00775 +Epoch [1254/4000] Training [3/16] Loss: 0.00939 +Epoch [1254/4000] Training [4/16] Loss: 0.00982 +Epoch [1254/4000] Training [5/16] Loss: 0.00931 +Epoch [1254/4000] Training [6/16] Loss: 0.00745 +Epoch [1254/4000] Training [7/16] Loss: 0.02938 +Epoch [1254/4000] Training [8/16] Loss: 0.00942 +Epoch [1254/4000] Training [9/16] Loss: 0.00935 +Epoch [1254/4000] Training [10/16] Loss: 0.01189 +Epoch [1254/4000] Training [11/16] Loss: 0.00904 +Epoch [1254/4000] Training [12/16] Loss: 0.00876 +Epoch [1254/4000] Training [13/16] Loss: 0.01047 +Epoch [1254/4000] Training [14/16] Loss: 0.01363 +Epoch [1254/4000] Training [15/16] Loss: 0.00866 +Epoch [1254/4000] Training [16/16] Loss: 0.00762 +Epoch [1254/4000] Training metric {'Train/mean dice_metric': 0.9932263493537903, 'Train/mean miou_metric': 0.9863408803939819, 'Train/mean f1': 0.9893653988838196, 'Train/mean precision': 0.9850806593894958, 'Train/mean recall': 0.9936875700950623, 'Train/mean hd95_metric': 1.404703974723816} +Epoch [1254/4000] Validation [1/4] Loss: 0.17811 focal_loss 0.11771 dice_loss 0.06040 +Epoch [1254/4000] Validation [2/4] Loss: 0.36169 focal_loss 0.20726 dice_loss 0.15443 +Epoch [1254/4000] Validation [3/4] Loss: 0.16601 focal_loss 0.08771 dice_loss 0.07830 +Epoch [1254/4000] Validation [4/4] Loss: 0.22734 focal_loss 0.13209 dice_loss 0.09525 +Epoch [1254/4000] Validation metric {'Val/mean dice_metric': 0.9697945713996887, 'Val/mean miou_metric': 0.9506627917289734, 'Val/mean f1': 0.9719985127449036, 'Val/mean precision': 0.9670208692550659, 'Val/mean recall': 0.9770275950431824, 'Val/mean hd95_metric': 6.884882926940918} +Cheakpoint... +Epoch [1254/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697945713996887, 'Val/mean miou_metric': 0.9506627917289734, 'Val/mean f1': 0.9719985127449036, 'Val/mean precision': 0.9670208692550659, 'Val/mean recall': 0.9770275950431824, 'Val/mean hd95_metric': 6.884882926940918} +Epoch [1255/4000] Training [1/16] Loss: 0.01071 +Epoch [1255/4000] Training [2/16] Loss: 0.01083 +Epoch [1255/4000] Training [3/16] Loss: 0.00833 +Epoch [1255/4000] Training [4/16] Loss: 0.00752 +Epoch [1255/4000] Training [5/16] Loss: 0.00869 +Epoch [1255/4000] Training [6/16] Loss: 0.00875 +Epoch [1255/4000] Training [7/16] Loss: 0.00789 +Epoch [1255/4000] Training [8/16] Loss: 0.00730 +Epoch [1255/4000] Training [9/16] Loss: 0.00874 +Epoch [1255/4000] Training [10/16] Loss: 0.01005 +Epoch [1255/4000] Training [11/16] Loss: 0.00839 +Epoch [1255/4000] Training [12/16] Loss: 0.01080 +Epoch [1255/4000] Training [13/16] Loss: 0.01263 +Epoch [1255/4000] Training [14/16] Loss: 0.00856 +Epoch [1255/4000] Training [15/16] Loss: 0.00820 +Epoch [1255/4000] Training [16/16] Loss: 0.00963 +Epoch [1255/4000] Training metric {'Train/mean dice_metric': 0.9936739206314087, 'Train/mean miou_metric': 0.9871858358383179, 'Train/mean f1': 0.9894819855690002, 'Train/mean precision': 0.9845764636993408, 'Train/mean recall': 0.9944366216659546, 'Train/mean hd95_metric': 1.1652805805206299} +Epoch [1255/4000] Validation [1/4] Loss: 0.18358 focal_loss 0.12471 dice_loss 0.05887 +Epoch [1255/4000] Validation [2/4] Loss: 0.51461 focal_loss 0.24962 dice_loss 0.26499 +Epoch [1255/4000] Validation [3/4] Loss: 0.21490 focal_loss 0.12042 dice_loss 0.09448 +Epoch [1255/4000] Validation [4/4] Loss: 0.20673 focal_loss 0.10816 dice_loss 0.09857 +Epoch [1255/4000] Validation metric {'Val/mean dice_metric': 0.9696758389472961, 'Val/mean miou_metric': 0.9514955282211304, 'Val/mean f1': 0.9720231294631958, 'Val/mean precision': 0.9660552144050598, 'Val/mean recall': 0.9780653715133667, 'Val/mean hd95_metric': 6.843095302581787} +Cheakpoint... +Epoch [1255/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696758389472961, 'Val/mean miou_metric': 0.9514955282211304, 'Val/mean f1': 0.9720231294631958, 'Val/mean precision': 0.9660552144050598, 'Val/mean recall': 0.9780653715133667, 'Val/mean hd95_metric': 6.843095302581787} +Epoch [1256/4000] Training [1/16] Loss: 0.00834 +Epoch [1256/4000] Training [2/16] Loss: 0.00789 +Epoch [1256/4000] Training [3/16] Loss: 0.01273 +Epoch [1256/4000] Training [4/16] Loss: 0.00923 +Epoch [1256/4000] Training [5/16] Loss: 0.01386 +Epoch [1256/4000] Training [6/16] Loss: 0.00880 +Epoch [1256/4000] Training [7/16] Loss: 0.01127 +Epoch [1256/4000] Training [8/16] Loss: 0.00847 +Epoch [1256/4000] Training [9/16] Loss: 0.00978 +Epoch [1256/4000] Training [10/16] Loss: 0.01138 +Epoch [1256/4000] Training [11/16] Loss: 0.00946 +Epoch [1256/4000] Training [12/16] Loss: 0.00805 +Epoch [1256/4000] Training [13/16] Loss: 0.00906 +Epoch [1256/4000] Training [14/16] Loss: 0.00991 +Epoch [1256/4000] Training [15/16] Loss: 0.00845 +Epoch [1256/4000] Training [16/16] Loss: 0.00776 +Epoch [1256/4000] Training metric {'Train/mean dice_metric': 0.9934577941894531, 'Train/mean miou_metric': 0.9867638349533081, 'Train/mean f1': 0.989676296710968, 'Train/mean precision': 0.9852484464645386, 'Train/mean recall': 0.9941443204879761, 'Train/mean hd95_metric': 1.0748605728149414} +Epoch [1256/4000] Validation [1/4] Loss: 0.24359 focal_loss 0.16546 dice_loss 0.07813 +Epoch [1256/4000] Validation [2/4] Loss: 0.34751 focal_loss 0.18240 dice_loss 0.16511 +Epoch [1256/4000] Validation [3/4] Loss: 0.21569 focal_loss 0.11815 dice_loss 0.09755 +Epoch [1256/4000] Validation [4/4] Loss: 0.21261 focal_loss 0.10358 dice_loss 0.10903 +Epoch [1256/4000] Validation metric {'Val/mean dice_metric': 0.9701989889144897, 'Val/mean miou_metric': 0.9511920809745789, 'Val/mean f1': 0.9716159701347351, 'Val/mean precision': 0.9678515195846558, 'Val/mean recall': 0.9754096269607544, 'Val/mean hd95_metric': 6.411864280700684} +Cheakpoint... +Epoch [1256/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701989889144897, 'Val/mean miou_metric': 0.9511920809745789, 'Val/mean f1': 0.9716159701347351, 'Val/mean precision': 0.9678515195846558, 'Val/mean recall': 0.9754096269607544, 'Val/mean hd95_metric': 6.411864280700684} +Epoch [1257/4000] Training [1/16] Loss: 0.00676 +Epoch [1257/4000] Training [2/16] Loss: 0.01144 +Epoch [1257/4000] Training [3/16] Loss: 0.01051 +Epoch [1257/4000] Training [4/16] Loss: 0.01163 +Epoch [1257/4000] Training [5/16] Loss: 0.00798 +Epoch [1257/4000] Training [6/16] Loss: 0.00936 +Epoch [1257/4000] Training [7/16] Loss: 0.00710 +Epoch [1257/4000] Training [8/16] Loss: 0.00887 +Epoch [1257/4000] Training [9/16] Loss: 0.00904 +Epoch [1257/4000] Training [10/16] Loss: 0.00820 +Epoch [1257/4000] Training [11/16] Loss: 0.00834 +Epoch [1257/4000] Training [12/16] Loss: 0.00866 +Epoch [1257/4000] Training [13/16] Loss: 0.00916 +Epoch [1257/4000] Training [14/16] Loss: 0.00978 +Epoch [1257/4000] Training [15/16] Loss: 0.00882 +Epoch [1257/4000] Training [16/16] Loss: 0.00768 +Epoch [1257/4000] Training metric {'Train/mean dice_metric': 0.9937831163406372, 'Train/mean miou_metric': 0.9874053001403809, 'Train/mean f1': 0.9900074601173401, 'Train/mean precision': 0.9854666590690613, 'Train/mean recall': 0.9945903420448303, 'Train/mean hd95_metric': 1.0456914901733398} +Epoch [1257/4000] Validation [1/4] Loss: 0.20599 focal_loss 0.14189 dice_loss 0.06409 +Epoch [1257/4000] Validation [2/4] Loss: 0.38726 focal_loss 0.20313 dice_loss 0.18414 +Epoch [1257/4000] Validation [3/4] Loss: 0.37420 focal_loss 0.24926 dice_loss 0.12494 +Epoch [1257/4000] Validation [4/4] Loss: 0.20575 focal_loss 0.08903 dice_loss 0.11672 +Epoch [1257/4000] Validation metric {'Val/mean dice_metric': 0.9704761505126953, 'Val/mean miou_metric': 0.9512645602226257, 'Val/mean f1': 0.9714382290840149, 'Val/mean precision': 0.9633264541625977, 'Val/mean recall': 0.9796878099441528, 'Val/mean hd95_metric': 6.727561950683594} +Cheakpoint... +Epoch [1257/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704761505126953, 'Val/mean miou_metric': 0.9512645602226257, 'Val/mean f1': 0.9714382290840149, 'Val/mean precision': 0.9633264541625977, 'Val/mean recall': 0.9796878099441528, 'Val/mean hd95_metric': 6.727561950683594} +Epoch [1258/4000] Training [1/16] Loss: 0.00774 +Epoch [1258/4000] Training [2/16] Loss: 0.00685 +Epoch [1258/4000] Training [3/16] Loss: 0.00866 +Epoch [1258/4000] Training [4/16] Loss: 0.01108 +Epoch [1258/4000] Training [5/16] Loss: 0.01320 +Epoch [1258/4000] Training [6/16] Loss: 0.00882 +Epoch [1258/4000] Training [7/16] Loss: 0.00829 +Epoch [1258/4000] Training [8/16] Loss: 0.00688 +Epoch [1258/4000] Training [9/16] Loss: 0.00858 +Epoch [1258/4000] Training [10/16] Loss: 0.00886 +Epoch [1258/4000] Training [11/16] Loss: 0.00862 +Epoch [1258/4000] Training [12/16] Loss: 0.00809 +Epoch [1258/4000] Training [13/16] Loss: 0.01128 +Epoch [1258/4000] Training [14/16] Loss: 0.01083 +Epoch [1258/4000] Training [15/16] Loss: 0.00875 +Epoch [1258/4000] Training [16/16] Loss: 0.01028 +Epoch [1258/4000] Training metric {'Train/mean dice_metric': 0.9935407638549805, 'Train/mean miou_metric': 0.9869225025177002, 'Train/mean f1': 0.9899049997329712, 'Train/mean precision': 0.9854332804679871, 'Train/mean recall': 0.9944174885749817, 'Train/mean hd95_metric': 1.237155795097351} +Epoch [1258/4000] Validation [1/4] Loss: 0.20880 focal_loss 0.14275 dice_loss 0.06605 +Epoch [1258/4000] Validation [2/4] Loss: 0.39941 focal_loss 0.21745 dice_loss 0.18196 +Epoch [1258/4000] Validation [3/4] Loss: 0.17239 focal_loss 0.09363 dice_loss 0.07876 +Epoch [1258/4000] Validation [4/4] Loss: 0.36387 focal_loss 0.22421 dice_loss 0.13966 +Epoch [1258/4000] Validation metric {'Val/mean dice_metric': 0.9690120816230774, 'Val/mean miou_metric': 0.9499069452285767, 'Val/mean f1': 0.9714330434799194, 'Val/mean precision': 0.9659903049468994, 'Val/mean recall': 0.9769374132156372, 'Val/mean hd95_metric': 6.750531196594238} +Cheakpoint... +Epoch [1258/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690120816230774, 'Val/mean miou_metric': 0.9499069452285767, 'Val/mean f1': 0.9714330434799194, 'Val/mean precision': 0.9659903049468994, 'Val/mean recall': 0.9769374132156372, 'Val/mean hd95_metric': 6.750531196594238} +Epoch [1259/4000] Training [1/16] Loss: 0.00759 +Epoch [1259/4000] Training [2/16] Loss: 0.00860 +Epoch [1259/4000] Training [3/16] Loss: 0.01062 +Epoch [1259/4000] Training [4/16] Loss: 0.01103 +Epoch [1259/4000] Training [5/16] Loss: 0.00858 +Epoch [1259/4000] Training [6/16] Loss: 0.00896 +Epoch [1259/4000] Training [7/16] Loss: 0.01286 +Epoch [1259/4000] Training [8/16] Loss: 0.00719 +Epoch [1259/4000] Training [9/16] Loss: 0.00828 +Epoch [1259/4000] Training [10/16] Loss: 0.01271 +Epoch [1259/4000] Training [11/16] Loss: 0.00868 +Epoch [1259/4000] Training [12/16] Loss: 0.00802 +Epoch [1259/4000] Training [13/16] Loss: 0.00807 +Epoch [1259/4000] Training [14/16] Loss: 0.00894 +Epoch [1259/4000] Training [15/16] Loss: 0.00870 +Epoch [1259/4000] Training [16/16] Loss: 0.01088 +Epoch [1259/4000] Training metric {'Train/mean dice_metric': 0.993431568145752, 'Train/mean miou_metric': 0.9867044687271118, 'Train/mean f1': 0.9895880818367004, 'Train/mean precision': 0.9850961565971375, 'Train/mean recall': 0.9941211938858032, 'Train/mean hd95_metric': 1.2798761129379272} +Epoch [1259/4000] Validation [1/4] Loss: 0.39939 focal_loss 0.29742 dice_loss 0.10196 +Epoch [1259/4000] Validation [2/4] Loss: 0.44223 focal_loss 0.19699 dice_loss 0.24524 +Epoch [1259/4000] Validation [3/4] Loss: 0.16300 focal_loss 0.09185 dice_loss 0.07116 +Epoch [1259/4000] Validation [4/4] Loss: 0.21157 focal_loss 0.09970 dice_loss 0.11187 +Epoch [1259/4000] Validation metric {'Val/mean dice_metric': 0.9664698839187622, 'Val/mean miou_metric': 0.9484394788742065, 'Val/mean f1': 0.9709010124206543, 'Val/mean precision': 0.9669564962387085, 'Val/mean recall': 0.9748778343200684, 'Val/mean hd95_metric': 6.1400580406188965} +Cheakpoint... +Epoch [1259/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664698839187622, 'Val/mean miou_metric': 0.9484394788742065, 'Val/mean f1': 0.9709010124206543, 'Val/mean precision': 0.9669564962387085, 'Val/mean recall': 0.9748778343200684, 'Val/mean hd95_metric': 6.1400580406188965} +Epoch [1260/4000] Training [1/16] Loss: 0.01267 +Epoch [1260/4000] Training [2/16] Loss: 0.00998 +Epoch [1260/4000] Training [3/16] Loss: 0.00717 +Epoch [1260/4000] Training [4/16] Loss: 0.01126 +Epoch [1260/4000] Training [5/16] Loss: 0.01015 +Epoch [1260/4000] Training [6/16] Loss: 0.01425 +Epoch [1260/4000] Training [7/16] Loss: 0.00971 +Epoch [1260/4000] Training [8/16] Loss: 0.01387 +Epoch [1260/4000] Training [9/16] Loss: 0.01182 +Epoch [1260/4000] Training [10/16] Loss: 0.00790 +Epoch [1260/4000] Training [11/16] Loss: 0.00968 +Epoch [1260/4000] Training [12/16] Loss: 0.00970 +Epoch [1260/4000] Training [13/16] Loss: 0.00982 +Epoch [1260/4000] Training [14/16] Loss: 0.00724 +Epoch [1260/4000] Training [15/16] Loss: 0.00958 +Epoch [1260/4000] Training [16/16] Loss: 0.01278 +Epoch [1260/4000] Training metric {'Train/mean dice_metric': 0.9925296306610107, 'Train/mean miou_metric': 0.9850828647613525, 'Train/mean f1': 0.9889925718307495, 'Train/mean precision': 0.9840878844261169, 'Train/mean recall': 0.993946373462677, 'Train/mean hd95_metric': 1.2074507474899292} +Epoch [1260/4000] Validation [1/4] Loss: 0.20192 focal_loss 0.13827 dice_loss 0.06366 +Epoch [1260/4000] Validation [2/4] Loss: 0.56689 focal_loss 0.34301 dice_loss 0.22388 +Epoch [1260/4000] Validation [3/4] Loss: 0.32862 focal_loss 0.20818 dice_loss 0.12044 +Epoch [1260/4000] Validation [4/4] Loss: 0.30870 focal_loss 0.17689 dice_loss 0.13180 +Epoch [1260/4000] Validation metric {'Val/mean dice_metric': 0.9696515798568726, 'Val/mean miou_metric': 0.9503270983695984, 'Val/mean f1': 0.970597505569458, 'Val/mean precision': 0.9645535349845886, 'Val/mean recall': 0.9767175316810608, 'Val/mean hd95_metric': 5.9356231689453125} +Cheakpoint... +Epoch [1260/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696515798568726, 'Val/mean miou_metric': 0.9503270983695984, 'Val/mean f1': 0.970597505569458, 'Val/mean precision': 0.9645535349845886, 'Val/mean recall': 0.9767175316810608, 'Val/mean hd95_metric': 5.9356231689453125} +Epoch [1261/4000] Training [1/16] Loss: 0.00874 +Epoch [1261/4000] Training [2/16] Loss: 0.00906 +Epoch [1261/4000] Training [3/16] Loss: 0.01145 +Epoch [1261/4000] Training [4/16] Loss: 0.00967 +Epoch [1261/4000] Training [5/16] Loss: 0.00665 +Epoch [1261/4000] Training [6/16] Loss: 0.02157 +Epoch [1261/4000] Training [7/16] Loss: 0.00712 +Epoch [1261/4000] Training [8/16] Loss: 0.00975 +Epoch [1261/4000] Training [9/16] Loss: 0.00802 +Epoch [1261/4000] Training [10/16] Loss: 0.00920 +Epoch [1261/4000] Training [11/16] Loss: 0.00856 +Epoch [1261/4000] Training [12/16] Loss: 0.00919 +Epoch [1261/4000] Training [13/16] Loss: 0.01053 +Epoch [1261/4000] Training [14/16] Loss: 0.01049 +Epoch [1261/4000] Training [15/16] Loss: 0.01003 +Epoch [1261/4000] Training [16/16] Loss: 0.00900 +Epoch [1261/4000] Training metric {'Train/mean dice_metric': 0.9931530356407166, 'Train/mean miou_metric': 0.9861658811569214, 'Train/mean f1': 0.9895108938217163, 'Train/mean precision': 0.9850233793258667, 'Train/mean recall': 0.9940394759178162, 'Train/mean hd95_metric': 1.1508904695510864} +Epoch [1261/4000] Validation [1/4] Loss: 0.41985 focal_loss 0.31687 dice_loss 0.10298 +Epoch [1261/4000] Validation [2/4] Loss: 0.45706 focal_loss 0.25435 dice_loss 0.20271 +Epoch [1261/4000] Validation [3/4] Loss: 0.25515 focal_loss 0.14429 dice_loss 0.11086 +Epoch [1261/4000] Validation [4/4] Loss: 0.25804 focal_loss 0.13676 dice_loss 0.12127 +Epoch [1261/4000] Validation metric {'Val/mean dice_metric': 0.9668291211128235, 'Val/mean miou_metric': 0.947714626789093, 'Val/mean f1': 0.9703586101531982, 'Val/mean precision': 0.9671013355255127, 'Val/mean recall': 0.9736379981040955, 'Val/mean hd95_metric': 5.997802734375} +Cheakpoint... +Epoch [1261/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668291211128235, 'Val/mean miou_metric': 0.947714626789093, 'Val/mean f1': 0.9703586101531982, 'Val/mean precision': 0.9671013355255127, 'Val/mean recall': 0.9736379981040955, 'Val/mean hd95_metric': 5.997802734375} +Epoch [1262/4000] Training [1/16] Loss: 0.00946 +Epoch [1262/4000] Training [2/16] Loss: 0.01031 +Epoch [1262/4000] Training [3/16] Loss: 0.00969 +Epoch [1262/4000] Training [4/16] Loss: 0.00795 +Epoch [1262/4000] Training [5/16] Loss: 0.01040 +Epoch [1262/4000] Training [6/16] Loss: 0.00878 +Epoch [1262/4000] Training [7/16] Loss: 0.01012 +Epoch [1262/4000] Training [8/16] Loss: 0.00910 +Epoch [1262/4000] Training [9/16] Loss: 0.01346 +Epoch [1262/4000] Training [10/16] Loss: 0.00877 +Epoch [1262/4000] Training [11/16] Loss: 0.03129 +Epoch [1262/4000] Training [12/16] Loss: 0.00950 +Epoch [1262/4000] Training [13/16] Loss: 0.00660 +Epoch [1262/4000] Training [14/16] Loss: 0.01030 +Epoch [1262/4000] Training [15/16] Loss: 0.01127 +Epoch [1262/4000] Training [16/16] Loss: 0.01365 +Epoch [1262/4000] Training metric {'Train/mean dice_metric': 0.992700457572937, 'Train/mean miou_metric': 0.9853494763374329, 'Train/mean f1': 0.9893743991851807, 'Train/mean precision': 0.9848461747169495, 'Train/mean recall': 0.9939444661140442, 'Train/mean hd95_metric': 1.2014102935791016} +Epoch [1262/4000] Validation [1/4] Loss: 0.40381 focal_loss 0.30526 dice_loss 0.09855 +Epoch [1262/4000] Validation [2/4] Loss: 0.54857 focal_loss 0.32351 dice_loss 0.22506 +Epoch [1262/4000] Validation [3/4] Loss: 0.29865 focal_loss 0.18965 dice_loss 0.10900 +Epoch [1262/4000] Validation [4/4] Loss: 0.20229 focal_loss 0.10120 dice_loss 0.10109 +Epoch [1262/4000] Validation metric {'Val/mean dice_metric': 0.9678573608398438, 'Val/mean miou_metric': 0.9492502212524414, 'Val/mean f1': 0.9709540009498596, 'Val/mean precision': 0.9697884321212769, 'Val/mean recall': 0.9721223711967468, 'Val/mean hd95_metric': 5.171631813049316} +Cheakpoint... +Epoch [1262/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678573608398438, 'Val/mean miou_metric': 0.9492502212524414, 'Val/mean f1': 0.9709540009498596, 'Val/mean precision': 0.9697884321212769, 'Val/mean recall': 0.9721223711967468, 'Val/mean hd95_metric': 5.171631813049316} +Epoch [1263/4000] Training [1/16] Loss: 0.00798 +Epoch [1263/4000] Training [2/16] Loss: 0.00705 +Epoch [1263/4000] Training [3/16] Loss: 0.00753 +Epoch [1263/4000] Training [4/16] Loss: 0.01157 +Epoch [1263/4000] Training [5/16] Loss: 0.00909 +Epoch [1263/4000] Training [6/16] Loss: 0.01057 +Epoch [1263/4000] Training [7/16] Loss: 0.00783 +Epoch [1263/4000] Training [8/16] Loss: 0.00883 +Epoch [1263/4000] Training [9/16] Loss: 0.00996 +Epoch [1263/4000] Training [10/16] Loss: 0.00899 +Epoch [1263/4000] Training [11/16] Loss: 0.01526 +Epoch [1263/4000] Training [12/16] Loss: 0.01159 +Epoch [1263/4000] Training [13/16] Loss: 0.01327 +Epoch [1263/4000] Training [14/16] Loss: 0.01087 +Epoch [1263/4000] Training [15/16] Loss: 0.02021 +Epoch [1263/4000] Training [16/16] Loss: 0.01272 +Epoch [1263/4000] Training metric {'Train/mean dice_metric': 0.9927721619606018, 'Train/mean miou_metric': 0.9854196310043335, 'Train/mean f1': 0.9893358945846558, 'Train/mean precision': 0.9844605326652527, 'Train/mean recall': 0.9942598342895508, 'Train/mean hd95_metric': 1.1875200271606445} +Epoch [1263/4000] Validation [1/4] Loss: 0.56210 focal_loss 0.44236 dice_loss 0.11974 +Epoch [1263/4000] Validation [2/4] Loss: 0.50899 focal_loss 0.30363 dice_loss 0.20536 +Epoch [1263/4000] Validation [3/4] Loss: 0.42359 focal_loss 0.28723 dice_loss 0.13636 +Epoch [1263/4000] Validation [4/4] Loss: 0.24068 focal_loss 0.13021 dice_loss 0.11047 +Epoch [1263/4000] Validation metric {'Val/mean dice_metric': 0.9654916524887085, 'Val/mean miou_metric': 0.9463445544242859, 'Val/mean f1': 0.969660758972168, 'Val/mean precision': 0.9690055251121521, 'Val/mean recall': 0.9703167676925659, 'Val/mean hd95_metric': 6.107571601867676} +Cheakpoint... +Epoch [1263/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654916524887085, 'Val/mean miou_metric': 0.9463445544242859, 'Val/mean f1': 0.969660758972168, 'Val/mean precision': 0.9690055251121521, 'Val/mean recall': 0.9703167676925659, 'Val/mean hd95_metric': 6.107571601867676} +Epoch [1264/4000] Training [1/16] Loss: 0.00785 +Epoch [1264/4000] Training [2/16] Loss: 0.00884 +Epoch [1264/4000] Training [3/16] Loss: 0.01016 +Epoch [1264/4000] Training [4/16] Loss: 0.00920 +Epoch [1264/4000] Training [5/16] Loss: 0.01486 +Epoch [1264/4000] Training [6/16] Loss: 0.00971 +Epoch [1264/4000] Training [7/16] Loss: 0.00887 +Epoch [1264/4000] Training [8/16] Loss: 0.00702 +Epoch [1264/4000] Training [9/16] Loss: 0.00764 +Epoch [1264/4000] Training [10/16] Loss: 0.00852 +Epoch [1264/4000] Training [11/16] Loss: 0.00901 +Epoch [1264/4000] Training [12/16] Loss: 0.00813 +Epoch [1264/4000] Training [13/16] Loss: 0.01000 +Epoch [1264/4000] Training [14/16] Loss: 0.00857 +Epoch [1264/4000] Training [15/16] Loss: 0.00891 +Epoch [1264/4000] Training [16/16] Loss: 0.01051 +Epoch [1264/4000] Training metric {'Train/mean dice_metric': 0.9934613704681396, 'Train/mean miou_metric': 0.9867590665817261, 'Train/mean f1': 0.9896817803382874, 'Train/mean precision': 0.9850890636444092, 'Train/mean recall': 0.9943174719810486, 'Train/mean hd95_metric': 1.0585622787475586} +Epoch [1264/4000] Validation [1/4] Loss: 0.24274 focal_loss 0.16747 dice_loss 0.07527 +Epoch [1264/4000] Validation [2/4] Loss: 0.35437 focal_loss 0.20678 dice_loss 0.14759 +Epoch [1264/4000] Validation [3/4] Loss: 0.39352 focal_loss 0.25613 dice_loss 0.13739 +Epoch [1264/4000] Validation [4/4] Loss: 0.24551 focal_loss 0.12216 dice_loss 0.12335 +Epoch [1264/4000] Validation metric {'Val/mean dice_metric': 0.969494640827179, 'Val/mean miou_metric': 0.9505010843276978, 'Val/mean f1': 0.9714058041572571, 'Val/mean precision': 0.9666969776153564, 'Val/mean recall': 0.9761607646942139, 'Val/mean hd95_metric': 6.01709508895874} +Cheakpoint... +Epoch [1264/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969494640827179, 'Val/mean miou_metric': 0.9505010843276978, 'Val/mean f1': 0.9714058041572571, 'Val/mean precision': 0.9666969776153564, 'Val/mean recall': 0.9761607646942139, 'Val/mean hd95_metric': 6.01709508895874} +Epoch [1265/4000] Training [1/16] Loss: 0.00916 +Epoch [1265/4000] Training [2/16] Loss: 0.00971 +Epoch [1265/4000] Training [3/16] Loss: 0.00922 +Epoch [1265/4000] Training [4/16] Loss: 0.01086 +Epoch [1265/4000] Training [5/16] Loss: 0.01410 +Epoch [1265/4000] Training [6/16] Loss: 0.00855 +Epoch [1265/4000] Training [7/16] Loss: 0.00883 +Epoch [1265/4000] Training [8/16] Loss: 0.01302 +Epoch [1265/4000] Training [9/16] Loss: 0.00832 +Epoch [1265/4000] Training [10/16] Loss: 0.00817 +Epoch [1265/4000] Training [11/16] Loss: 0.00990 +Epoch [1265/4000] Training [12/16] Loss: 0.00823 +Epoch [1265/4000] Training [13/16] Loss: 0.00651 +Epoch [1265/4000] Training [14/16] Loss: 0.01523 +Epoch [1265/4000] Training [15/16] Loss: 0.01022 +Epoch [1265/4000] Training [16/16] Loss: 0.01318 +Epoch [1265/4000] Training metric {'Train/mean dice_metric': 0.9929640293121338, 'Train/mean miou_metric': 0.985805869102478, 'Train/mean f1': 0.9892938137054443, 'Train/mean precision': 0.9847960472106934, 'Train/mean recall': 0.9938328266143799, 'Train/mean hd95_metric': 1.119305968284607} +Epoch [1265/4000] Validation [1/4] Loss: 0.51996 focal_loss 0.40904 dice_loss 0.11092 +Epoch [1265/4000] Validation [2/4] Loss: 0.42412 focal_loss 0.23793 dice_loss 0.18619 +Epoch [1265/4000] Validation [3/4] Loss: 0.25077 focal_loss 0.15749 dice_loss 0.09328 +Epoch [1265/4000] Validation [4/4] Loss: 0.25917 focal_loss 0.13304 dice_loss 0.12613 +Epoch [1265/4000] Validation metric {'Val/mean dice_metric': 0.9668083190917969, 'Val/mean miou_metric': 0.9481088519096375, 'Val/mean f1': 0.9696827530860901, 'Val/mean precision': 0.969971776008606, 'Val/mean recall': 0.9693938493728638, 'Val/mean hd95_metric': 5.890697002410889} +Cheakpoint... +Epoch [1265/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668083190917969, 'Val/mean miou_metric': 0.9481088519096375, 'Val/mean f1': 0.9696827530860901, 'Val/mean precision': 0.969971776008606, 'Val/mean recall': 0.9693938493728638, 'Val/mean hd95_metric': 5.890697002410889} +Epoch [1266/4000] Training [1/16] Loss: 0.01129 +Epoch [1266/4000] Training [2/16] Loss: 0.00720 +Epoch [1266/4000] Training [3/16] Loss: 0.00976 +Epoch [1266/4000] Training [4/16] Loss: 0.01061 +Epoch [1266/4000] Training [5/16] Loss: 0.00795 +Epoch [1266/4000] Training [6/16] Loss: 0.00896 +Epoch [1266/4000] Training [7/16] Loss: 0.00972 +Epoch [1266/4000] Training [8/16] Loss: 0.01167 +Epoch [1266/4000] Training [9/16] Loss: 0.00868 +Epoch [1266/4000] Training [10/16] Loss: 0.00937 +Epoch [1266/4000] Training [11/16] Loss: 0.00803 +Epoch [1266/4000] Training [12/16] Loss: 0.01246 +Epoch [1266/4000] Training [13/16] Loss: 0.00957 +Epoch [1266/4000] Training [14/16] Loss: 0.00731 +Epoch [1266/4000] Training [15/16] Loss: 0.00901 +Epoch [1266/4000] Training [16/16] Loss: 0.00999 +Epoch [1266/4000] Training metric {'Train/mean dice_metric': 0.9938084483146667, 'Train/mean miou_metric': 0.9874489903450012, 'Train/mean f1': 0.9899072647094727, 'Train/mean precision': 0.9851657748222351, 'Train/mean recall': 0.9946945905685425, 'Train/mean hd95_metric': 1.0555576086044312} +Epoch [1266/4000] Validation [1/4] Loss: 0.35656 focal_loss 0.26968 dice_loss 0.08688 +Epoch [1266/4000] Validation [2/4] Loss: 0.51240 focal_loss 0.31775 dice_loss 0.19464 +Epoch [1266/4000] Validation [3/4] Loss: 0.28631 focal_loss 0.17556 dice_loss 0.11075 +Epoch [1266/4000] Validation [4/4] Loss: 0.25537 focal_loss 0.13854 dice_loss 0.11684 +Epoch [1266/4000] Validation metric {'Val/mean dice_metric': 0.9678148031234741, 'Val/mean miou_metric': 0.9490342140197754, 'Val/mean f1': 0.9700166583061218, 'Val/mean precision': 0.9699850678443909, 'Val/mean recall': 0.9700483083724976, 'Val/mean hd95_metric': 5.8745574951171875} +Cheakpoint... +Epoch [1266/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678148031234741, 'Val/mean miou_metric': 0.9490342140197754, 'Val/mean f1': 0.9700166583061218, 'Val/mean precision': 0.9699850678443909, 'Val/mean recall': 0.9700483083724976, 'Val/mean hd95_metric': 5.8745574951171875} +Epoch [1267/4000] Training [1/16] Loss: 0.00774 +Epoch [1267/4000] Training [2/16] Loss: 0.01081 +Epoch [1267/4000] Training [3/16] Loss: 0.01005 +Epoch [1267/4000] Training [4/16] Loss: 0.00847 +Epoch [1267/4000] Training [5/16] Loss: 0.00818 +Epoch [1267/4000] Training [6/16] Loss: 0.00979 +Epoch [1267/4000] Training [7/16] Loss: 0.00876 +Epoch [1267/4000] Training [8/16] Loss: 0.00842 +Epoch [1267/4000] Training [9/16] Loss: 0.01152 +Epoch [1267/4000] Training [10/16] Loss: 0.00819 +Epoch [1267/4000] Training [11/16] Loss: 0.00867 +Epoch [1267/4000] Training [12/16] Loss: 0.00836 +Epoch [1267/4000] Training [13/16] Loss: 0.00739 +Epoch [1267/4000] Training [14/16] Loss: 0.00765 +Epoch [1267/4000] Training [15/16] Loss: 0.01003 +Epoch [1267/4000] Training [16/16] Loss: 0.01036 +Epoch [1267/4000] Training metric {'Train/mean dice_metric': 0.9934189319610596, 'Train/mean miou_metric': 0.9866927862167358, 'Train/mean f1': 0.9897563457489014, 'Train/mean precision': 0.9852584004402161, 'Train/mean recall': 0.994295597076416, 'Train/mean hd95_metric': 1.3706222772598267} +Epoch [1267/4000] Validation [1/4] Loss: 0.68607 focal_loss 0.56842 dice_loss 0.11764 +Epoch [1267/4000] Validation [2/4] Loss: 0.44117 focal_loss 0.23239 dice_loss 0.20878 +Epoch [1267/4000] Validation [3/4] Loss: 0.24688 focal_loss 0.13978 dice_loss 0.10710 +Epoch [1267/4000] Validation [4/4] Loss: 0.22085 focal_loss 0.10682 dice_loss 0.11403 +Epoch [1267/4000] Validation metric {'Val/mean dice_metric': 0.9671350717544556, 'Val/mean miou_metric': 0.9489368200302124, 'Val/mean f1': 0.9706417918205261, 'Val/mean precision': 0.9702063202857971, 'Val/mean recall': 0.9710777401924133, 'Val/mean hd95_metric': 5.880788803100586} +Cheakpoint... +Epoch [1267/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671350717544556, 'Val/mean miou_metric': 0.9489368200302124, 'Val/mean f1': 0.9706417918205261, 'Val/mean precision': 0.9702063202857971, 'Val/mean recall': 0.9710777401924133, 'Val/mean hd95_metric': 5.880788803100586} +Epoch [1268/4000] Training [1/16] Loss: 0.01136 +Epoch [1268/4000] Training [2/16] Loss: 0.00946 +Epoch [1268/4000] Training [3/16] Loss: 0.01084 +Epoch [1268/4000] Training [4/16] Loss: 0.00900 +Epoch [1268/4000] Training [5/16] Loss: 0.01929 +Epoch [1268/4000] Training [6/16] Loss: 0.00848 +Epoch [1268/4000] Training [7/16] Loss: 0.01410 +Epoch [1268/4000] Training [8/16] Loss: 0.00923 +Epoch [1268/4000] Training [9/16] Loss: 0.01122 +Epoch [1268/4000] Training [10/16] Loss: 0.01331 +Epoch [1268/4000] Training [11/16] Loss: 0.00886 +Epoch [1268/4000] Training [12/16] Loss: 0.00746 +Epoch [1268/4000] Training [13/16] Loss: 0.01959 +Epoch [1268/4000] Training [14/16] Loss: 0.00967 +Epoch [1268/4000] Training [15/16] Loss: 0.00932 +Epoch [1268/4000] Training [16/16] Loss: 0.01093 +Epoch [1268/4000] Training metric {'Train/mean dice_metric': 0.9925796985626221, 'Train/mean miou_metric': 0.9851187467575073, 'Train/mean f1': 0.9891770482063293, 'Train/mean precision': 0.9847443699836731, 'Train/mean recall': 0.9936498403549194, 'Train/mean hd95_metric': 1.4796932935714722} +Epoch [1268/4000] Validation [1/4] Loss: 0.90340 focal_loss 0.70063 dice_loss 0.20278 +Epoch [1268/4000] Validation [2/4] Loss: 0.77054 focal_loss 0.47361 dice_loss 0.29693 +Epoch [1268/4000] Validation [3/4] Loss: 0.21547 focal_loss 0.13919 dice_loss 0.07628 +Epoch [1268/4000] Validation [4/4] Loss: 0.46363 focal_loss 0.30089 dice_loss 0.16274 +Epoch [1268/4000] Validation metric {'Val/mean dice_metric': 0.961051344871521, 'Val/mean miou_metric': 0.9419136047363281, 'Val/mean f1': 0.9657105803489685, 'Val/mean precision': 0.973153829574585, 'Val/mean recall': 0.9583804607391357, 'Val/mean hd95_metric': 5.869402885437012} +Cheakpoint... +Epoch [1268/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961051344871521, 'Val/mean miou_metric': 0.9419136047363281, 'Val/mean f1': 0.9657105803489685, 'Val/mean precision': 0.973153829574585, 'Val/mean recall': 0.9583804607391357, 'Val/mean hd95_metric': 5.869402885437012} +Epoch [1269/4000] Training [1/16] Loss: 0.01132 +Epoch [1269/4000] Training [2/16] Loss: 0.00987 +Epoch [1269/4000] Training [3/16] Loss: 0.00894 +Epoch [1269/4000] Training [4/16] Loss: 0.00918 +Epoch [1269/4000] Training [5/16] Loss: 0.00743 +Epoch [1269/4000] Training [6/16] Loss: 0.01001 +Epoch [1269/4000] Training [7/16] Loss: 0.00883 +Epoch [1269/4000] Training [8/16] Loss: 0.00780 +Epoch [1269/4000] Training [9/16] Loss: 0.01210 +Epoch [1269/4000] Training [10/16] Loss: 0.00811 +Epoch [1269/4000] Training [11/16] Loss: 0.01126 +Epoch [1269/4000] Training [12/16] Loss: 0.00952 +Epoch [1269/4000] Training [13/16] Loss: 0.01161 +Epoch [1269/4000] Training [14/16] Loss: 0.01418 +Epoch [1269/4000] Training [15/16] Loss: 0.01037 +Epoch [1269/4000] Training [16/16] Loss: 0.01009 +Epoch [1269/4000] Training metric {'Train/mean dice_metric': 0.99311763048172, 'Train/mean miou_metric': 0.9860536456108093, 'Train/mean f1': 0.9887562990188599, 'Train/mean precision': 0.9835129380226135, 'Train/mean recall': 0.9940558671951294, 'Train/mean hd95_metric': 1.071569800376892} +Epoch [1269/4000] Validation [1/4] Loss: 0.72208 focal_loss 0.59658 dice_loss 0.12550 +Epoch [1269/4000] Validation [2/4] Loss: 0.45730 focal_loss 0.26071 dice_loss 0.19659 +Epoch [1269/4000] Validation [3/4] Loss: 0.21169 focal_loss 0.11704 dice_loss 0.09465 +Epoch [1269/4000] Validation [4/4] Loss: 0.22491 focal_loss 0.12290 dice_loss 0.10200 +Epoch [1269/4000] Validation metric {'Val/mean dice_metric': 0.9637657403945923, 'Val/mean miou_metric': 0.9451936483383179, 'Val/mean f1': 0.9679018259048462, 'Val/mean precision': 0.9696062207221985, 'Val/mean recall': 0.9662033915519714, 'Val/mean hd95_metric': 5.388637542724609} +Cheakpoint... +Epoch [1269/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9638], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637657403945923, 'Val/mean miou_metric': 0.9451936483383179, 'Val/mean f1': 0.9679018259048462, 'Val/mean precision': 0.9696062207221985, 'Val/mean recall': 0.9662033915519714, 'Val/mean hd95_metric': 5.388637542724609} +Epoch [1270/4000] Training [1/16] Loss: 0.00745 +Epoch [1270/4000] Training [2/16] Loss: 0.00921 +Epoch [1270/4000] Training [3/16] Loss: 0.01055 +Epoch [1270/4000] Training [4/16] Loss: 0.00742 +Epoch [1270/4000] Training [5/16] Loss: 0.00838 +Epoch [1270/4000] Training [6/16] Loss: 0.00980 +Epoch [1270/4000] Training [7/16] Loss: 0.00916 +Epoch [1270/4000] Training [8/16] Loss: 0.00977 +Epoch [1270/4000] Training [9/16] Loss: 0.01152 +Epoch [1270/4000] Training [10/16] Loss: 0.00863 +Epoch [1270/4000] Training [11/16] Loss: 0.00906 +Epoch [1270/4000] Training [12/16] Loss: 0.01039 +Epoch [1270/4000] Training [13/16] Loss: 0.00839 +Epoch [1270/4000] Training [14/16] Loss: 0.00815 +Epoch [1270/4000] Training [15/16] Loss: 0.01062 +Epoch [1270/4000] Training [16/16] Loss: 0.00779 +Epoch [1270/4000] Training metric {'Train/mean dice_metric': 0.9934189319610596, 'Train/mean miou_metric': 0.9866784811019897, 'Train/mean f1': 0.9898355603218079, 'Train/mean precision': 0.9852285981178284, 'Train/mean recall': 0.9944858551025391, 'Train/mean hd95_metric': 1.0601942539215088} +Epoch [1270/4000] Validation [1/4] Loss: 0.67629 focal_loss 0.54985 dice_loss 0.12644 +Epoch [1270/4000] Validation [2/4] Loss: 0.57222 focal_loss 0.37096 dice_loss 0.20126 +Epoch [1270/4000] Validation [3/4] Loss: 0.19143 focal_loss 0.10484 dice_loss 0.08659 +Epoch [1270/4000] Validation [4/4] Loss: 0.21986 focal_loss 0.11911 dice_loss 0.10075 +Epoch [1270/4000] Validation metric {'Val/mean dice_metric': 0.9676920771598816, 'Val/mean miou_metric': 0.9492227435112, 'Val/mean f1': 0.9702663421630859, 'Val/mean precision': 0.9715213179588318, 'Val/mean recall': 0.9690146446228027, 'Val/mean hd95_metric': 5.506667137145996} +Cheakpoint... +Epoch [1270/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676920771598816, 'Val/mean miou_metric': 0.9492227435112, 'Val/mean f1': 0.9702663421630859, 'Val/mean precision': 0.9715213179588318, 'Val/mean recall': 0.9690146446228027, 'Val/mean hd95_metric': 5.506667137145996} +Epoch [1271/4000] Training [1/16] Loss: 0.00803 +Epoch [1271/4000] Training [2/16] Loss: 0.01078 +Epoch [1271/4000] Training [3/16] Loss: 0.00989 +Epoch [1271/4000] Training [4/16] Loss: 0.00725 +Epoch [1271/4000] Training [5/16] Loss: 0.01306 +Epoch [1271/4000] Training [6/16] Loss: 0.01234 +Epoch [1271/4000] Training [7/16] Loss: 0.00755 +Epoch [1271/4000] Training [8/16] Loss: 0.00818 +Epoch [1271/4000] Training [9/16] Loss: 0.00983 +Epoch [1271/4000] Training [10/16] Loss: 0.00836 +Epoch [1271/4000] Training [11/16] Loss: 0.00881 +Epoch [1271/4000] Training [12/16] Loss: 0.01294 +Epoch [1271/4000] Training [13/16] Loss: 0.01054 +Epoch [1271/4000] Training [14/16] Loss: 0.00811 +Epoch [1271/4000] Training [15/16] Loss: 0.00986 +Epoch [1271/4000] Training [16/16] Loss: 0.01339 +Epoch [1271/4000] Training metric {'Train/mean dice_metric': 0.9929232001304626, 'Train/mean miou_metric': 0.9857447743415833, 'Train/mean f1': 0.9891798496246338, 'Train/mean precision': 0.9842966794967651, 'Train/mean recall': 0.9941117167472839, 'Train/mean hd95_metric': 1.2061681747436523} +Epoch [1271/4000] Validation [1/4] Loss: 0.72601 focal_loss 0.59704 dice_loss 0.12897 +Epoch [1271/4000] Validation [2/4] Loss: 0.51612 focal_loss 0.31771 dice_loss 0.19840 +Epoch [1271/4000] Validation [3/4] Loss: 0.39139 focal_loss 0.25728 dice_loss 0.13411 +Epoch [1271/4000] Validation [4/4] Loss: 0.30033 focal_loss 0.15543 dice_loss 0.14490 +Epoch [1271/4000] Validation metric {'Val/mean dice_metric': 0.9644172787666321, 'Val/mean miou_metric': 0.945120632648468, 'Val/mean f1': 0.9670194983482361, 'Val/mean precision': 0.968693196773529, 'Val/mean recall': 0.9653515219688416, 'Val/mean hd95_metric': 6.14126443862915} +Cheakpoint... +Epoch [1271/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644172787666321, 'Val/mean miou_metric': 0.945120632648468, 'Val/mean f1': 0.9670194983482361, 'Val/mean precision': 0.968693196773529, 'Val/mean recall': 0.9653515219688416, 'Val/mean hd95_metric': 6.14126443862915} +Epoch [1272/4000] Training [1/16] Loss: 0.00918 +Epoch [1272/4000] Training [2/16] Loss: 0.01347 +Epoch [1272/4000] Training [3/16] Loss: 0.01821 +Epoch [1272/4000] Training [4/16] Loss: 0.00717 +Epoch [1272/4000] Training [5/16] Loss: 0.00877 +Epoch [1272/4000] Training [6/16] Loss: 0.00733 +Epoch [1272/4000] Training [7/16] Loss: 0.00608 +Epoch [1272/4000] Training [8/16] Loss: 0.01085 +Epoch [1272/4000] Training [9/16] Loss: 0.00951 +Epoch [1272/4000] Training [10/16] Loss: 0.00889 +Epoch [1272/4000] Training [11/16] Loss: 0.00857 +Epoch [1272/4000] Training [12/16] Loss: 0.01109 +Epoch [1272/4000] Training [13/16] Loss: 0.01117 +Epoch [1272/4000] Training [14/16] Loss: 0.01015 +Epoch [1272/4000] Training [15/16] Loss: 0.00896 +Epoch [1272/4000] Training [16/16] Loss: 0.01303 +Epoch [1272/4000] Training metric {'Train/mean dice_metric': 0.9933947920799255, 'Train/mean miou_metric': 0.9865937232971191, 'Train/mean f1': 0.9886870384216309, 'Train/mean precision': 0.9835748076438904, 'Train/mean recall': 0.9938527345657349, 'Train/mean hd95_metric': 1.2187385559082031} +Epoch [1272/4000] Validation [1/4] Loss: 0.68167 focal_loss 0.55534 dice_loss 0.12633 +Epoch [1272/4000] Validation [2/4] Loss: 0.54220 focal_loss 0.35383 dice_loss 0.18837 +Epoch [1272/4000] Validation [3/4] Loss: 0.15653 focal_loss 0.08214 dice_loss 0.07439 +Epoch [1272/4000] Validation [4/4] Loss: 0.33586 focal_loss 0.20862 dice_loss 0.12724 +Epoch [1272/4000] Validation metric {'Val/mean dice_metric': 0.9658371210098267, 'Val/mean miou_metric': 0.9475962519645691, 'Val/mean f1': 0.9683791399002075, 'Val/mean precision': 0.9708546996116638, 'Val/mean recall': 0.9659161567687988, 'Val/mean hd95_metric': 5.835785865783691} +Cheakpoint... +Epoch [1272/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658371210098267, 'Val/mean miou_metric': 0.9475962519645691, 'Val/mean f1': 0.9683791399002075, 'Val/mean precision': 0.9708546996116638, 'Val/mean recall': 0.9659161567687988, 'Val/mean hd95_metric': 5.835785865783691} +Epoch [1273/4000] Training [1/16] Loss: 0.01209 +Epoch [1273/4000] Training [2/16] Loss: 0.00835 +Epoch [1273/4000] Training [3/16] Loss: 0.00999 +Epoch [1273/4000] Training [4/16] Loss: 0.00857 +Epoch [1273/4000] Training [5/16] Loss: 0.00944 +Epoch [1273/4000] Training [6/16] Loss: 0.01474 +Epoch [1273/4000] Training [7/16] Loss: 0.01107 +Epoch [1273/4000] Training [8/16] Loss: 0.00999 +Epoch [1273/4000] Training [9/16] Loss: 0.01125 +Epoch [1273/4000] Training [10/16] Loss: 0.01020 +Epoch [1273/4000] Training [11/16] Loss: 0.00845 +Epoch [1273/4000] Training [12/16] Loss: 0.00769 +Epoch [1273/4000] Training [13/16] Loss: 0.01024 +Epoch [1273/4000] Training [14/16] Loss: 0.01061 +Epoch [1273/4000] Training [15/16] Loss: 0.00763 +Epoch [1273/4000] Training [16/16] Loss: 0.01047 +Epoch [1273/4000] Training metric {'Train/mean dice_metric': 0.9929324388504028, 'Train/mean miou_metric': 0.985761284828186, 'Train/mean f1': 0.9892778396606445, 'Train/mean precision': 0.984470546245575, 'Train/mean recall': 0.9941323399543762, 'Train/mean hd95_metric': 1.123354196548462} +Epoch [1273/4000] Validation [1/4] Loss: 0.74293 focal_loss 0.61705 dice_loss 0.12588 +Epoch [1273/4000] Validation [2/4] Loss: 0.54964 focal_loss 0.36022 dice_loss 0.18942 +Epoch [1273/4000] Validation [3/4] Loss: 0.30167 focal_loss 0.20355 dice_loss 0.09812 +Epoch [1273/4000] Validation [4/4] Loss: 0.22994 focal_loss 0.12048 dice_loss 0.10946 +Epoch [1273/4000] Validation metric {'Val/mean dice_metric': 0.965863049030304, 'Val/mean miou_metric': 0.9474163055419922, 'Val/mean f1': 0.9683805704116821, 'Val/mean precision': 0.9685268402099609, 'Val/mean recall': 0.9682344794273376, 'Val/mean hd95_metric': 6.074962615966797} +Cheakpoint... +Epoch [1273/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965863049030304, 'Val/mean miou_metric': 0.9474163055419922, 'Val/mean f1': 0.9683805704116821, 'Val/mean precision': 0.9685268402099609, 'Val/mean recall': 0.9682344794273376, 'Val/mean hd95_metric': 6.074962615966797} +Epoch [1274/4000] Training [1/16] Loss: 0.00923 +Epoch [1274/4000] Training [2/16] Loss: 0.01142 +Epoch [1274/4000] Training [3/16] Loss: 0.00857 +Epoch [1274/4000] Training [4/16] Loss: 0.01160 +Epoch [1274/4000] Training [5/16] Loss: 0.01180 +Epoch [1274/4000] Training [6/16] Loss: 0.01481 +Epoch [1274/4000] Training [7/16] Loss: 0.01527 +Epoch [1274/4000] Training [8/16] Loss: 0.00870 +Epoch [1274/4000] Training [9/16] Loss: 0.00792 +Epoch [1274/4000] Training [10/16] Loss: 0.01045 +Epoch [1274/4000] Training [11/16] Loss: 0.00841 +Epoch [1274/4000] Training [12/16] Loss: 0.01292 +Epoch [1274/4000] Training [13/16] Loss: 0.00822 +Epoch [1274/4000] Training [14/16] Loss: 0.00919 +Epoch [1274/4000] Training [15/16] Loss: 0.00836 +Epoch [1274/4000] Training [16/16] Loss: 0.00748 +Epoch [1274/4000] Training metric {'Train/mean dice_metric': 0.9931575059890747, 'Train/mean miou_metric': 0.986201822757721, 'Train/mean f1': 0.9895925521850586, 'Train/mean precision': 0.9849792122840881, 'Train/mean recall': 0.9942492842674255, 'Train/mean hd95_metric': 1.2118782997131348} +Epoch [1274/4000] Validation [1/4] Loss: 0.62512 focal_loss 0.50721 dice_loss 0.11791 +Epoch [1274/4000] Validation [2/4] Loss: 0.59291 focal_loss 0.38060 dice_loss 0.21231 +Epoch [1274/4000] Validation [3/4] Loss: 0.22170 focal_loss 0.13082 dice_loss 0.09087 +Epoch [1274/4000] Validation [4/4] Loss: 0.25203 focal_loss 0.14429 dice_loss 0.10774 +Epoch [1274/4000] Validation metric {'Val/mean dice_metric': 0.9673858880996704, 'Val/mean miou_metric': 0.9482938051223755, 'Val/mean f1': 0.9688687324523926, 'Val/mean precision': 0.9705358147621155, 'Val/mean recall': 0.9672075510025024, 'Val/mean hd95_metric': 6.048727035522461} +Cheakpoint... +Epoch [1274/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673858880996704, 'Val/mean miou_metric': 0.9482938051223755, 'Val/mean f1': 0.9688687324523926, 'Val/mean precision': 0.9705358147621155, 'Val/mean recall': 0.9672075510025024, 'Val/mean hd95_metric': 6.048727035522461} +Epoch [1275/4000] Training [1/16] Loss: 0.00945 +Epoch [1275/4000] Training [2/16] Loss: 0.00997 +Epoch [1275/4000] Training [3/16] Loss: 0.00905 +Epoch [1275/4000] Training [4/16] Loss: 0.00739 +Epoch [1275/4000] Training [5/16] Loss: 0.00925 +Epoch [1275/4000] Training [6/16] Loss: 0.00927 +Epoch [1275/4000] Training [7/16] Loss: 0.01202 +Epoch [1275/4000] Training [8/16] Loss: 0.00806 +Epoch [1275/4000] Training [9/16] Loss: 0.00896 +Epoch [1275/4000] Training [10/16] Loss: 0.00698 +Epoch [1275/4000] Training [11/16] Loss: 0.00842 +Epoch [1275/4000] Training [12/16] Loss: 0.01022 +Epoch [1275/4000] Training [13/16] Loss: 0.00717 +Epoch [1275/4000] Training [14/16] Loss: 0.00666 +Epoch [1275/4000] Training [15/16] Loss: 0.00735 +Epoch [1275/4000] Training [16/16] Loss: 0.00821 +Epoch [1275/4000] Training metric {'Train/mean dice_metric': 0.9939379096031189, 'Train/mean miou_metric': 0.9876959919929504, 'Train/mean f1': 0.990037202835083, 'Train/mean precision': 0.985482931137085, 'Train/mean recall': 0.994633674621582, 'Train/mean hd95_metric': 1.0665532350540161} +Epoch [1275/4000] Validation [1/4] Loss: 0.57991 focal_loss 0.45979 dice_loss 0.12012 +Epoch [1275/4000] Validation [2/4] Loss: 0.50989 focal_loss 0.31858 dice_loss 0.19130 +Epoch [1275/4000] Validation [3/4] Loss: 0.20233 focal_loss 0.11117 dice_loss 0.09116 +Epoch [1275/4000] Validation [4/4] Loss: 0.26957 focal_loss 0.16474 dice_loss 0.10483 +Epoch [1275/4000] Validation metric {'Val/mean dice_metric': 0.9662968516349792, 'Val/mean miou_metric': 0.9487642049789429, 'Val/mean f1': 0.969575822353363, 'Val/mean precision': 0.9720094799995422, 'Val/mean recall': 0.9671544432640076, 'Val/mean hd95_metric': 5.263110160827637} +Cheakpoint... +Epoch [1275/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662968516349792, 'Val/mean miou_metric': 0.9487642049789429, 'Val/mean f1': 0.969575822353363, 'Val/mean precision': 0.9720094799995422, 'Val/mean recall': 0.9671544432640076, 'Val/mean hd95_metric': 5.263110160827637} +Epoch [1276/4000] Training [1/16] Loss: 0.00930 +Epoch [1276/4000] Training [2/16] Loss: 0.00863 +Epoch [1276/4000] Training [3/16] Loss: 0.00835 +Epoch [1276/4000] Training [4/16] Loss: 0.00701 +Epoch [1276/4000] Training [5/16] Loss: 0.00941 +Epoch [1276/4000] Training [6/16] Loss: 0.00739 +Epoch [1276/4000] Training [7/16] Loss: 0.00737 +Epoch [1276/4000] Training [8/16] Loss: 0.00983 +Epoch [1276/4000] Training [9/16] Loss: 0.01104 +Epoch [1276/4000] Training [10/16] Loss: 0.01023 +Epoch [1276/4000] Training [11/16] Loss: 0.00916 +Epoch [1276/4000] Training [12/16] Loss: 0.01632 +Epoch [1276/4000] Training [13/16] Loss: 0.00886 +Epoch [1276/4000] Training [14/16] Loss: 0.01209 +Epoch [1276/4000] Training [15/16] Loss: 0.01324 +Epoch [1276/4000] Training [16/16] Loss: 0.01001 +Epoch [1276/4000] Training metric {'Train/mean dice_metric': 0.9935158491134644, 'Train/mean miou_metric': 0.9868982434272766, 'Train/mean f1': 0.9898726940155029, 'Train/mean precision': 0.9854045510292053, 'Train/mean recall': 0.9943814873695374, 'Train/mean hd95_metric': 1.5046980381011963} +Epoch [1276/4000] Validation [1/4] Loss: 0.20418 focal_loss 0.14517 dice_loss 0.05901 +Epoch [1276/4000] Validation [2/4] Loss: 0.50329 focal_loss 0.31613 dice_loss 0.18716 +Epoch [1276/4000] Validation [3/4] Loss: 0.24176 focal_loss 0.14637 dice_loss 0.09539 +Epoch [1276/4000] Validation [4/4] Loss: 0.18055 focal_loss 0.10171 dice_loss 0.07884 +Epoch [1276/4000] Validation metric {'Val/mean dice_metric': 0.9687326550483704, 'Val/mean miou_metric': 0.9511844515800476, 'Val/mean f1': 0.9718331694602966, 'Val/mean precision': 0.9663987755775452, 'Val/mean recall': 0.9773289561271667, 'Val/mean hd95_metric': 6.412298679351807} +Cheakpoint... +Epoch [1276/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687326550483704, 'Val/mean miou_metric': 0.9511844515800476, 'Val/mean f1': 0.9718331694602966, 'Val/mean precision': 0.9663987755775452, 'Val/mean recall': 0.9773289561271667, 'Val/mean hd95_metric': 6.412298679351807} +Epoch [1277/4000] Training [1/16] Loss: 0.02030 +Epoch [1277/4000] Training [2/16] Loss: 0.00904 +Epoch [1277/4000] Training [3/16] Loss: 0.01338 +Epoch [1277/4000] Training [4/16] Loss: 0.00839 +Epoch [1277/4000] Training [5/16] Loss: 0.00867 +Epoch [1277/4000] Training [6/16] Loss: 0.01086 +Epoch [1277/4000] Training [7/16] Loss: 0.01022 +Epoch [1277/4000] Training [8/16] Loss: 0.00825 +Epoch [1277/4000] Training [9/16] Loss: 0.00899 +Epoch [1277/4000] Training [10/16] Loss: 0.01216 +Epoch [1277/4000] Training [11/16] Loss: 0.01074 +Epoch [1277/4000] Training [12/16] Loss: 0.01112 +Epoch [1277/4000] Training [13/16] Loss: 0.01019 +Epoch [1277/4000] Training [14/16] Loss: 0.02839 +Epoch [1277/4000] Training [15/16] Loss: 0.00798 +Epoch [1277/4000] Training [16/16] Loss: 0.00848 +Epoch [1277/4000] Training metric {'Train/mean dice_metric': 0.9925021529197693, 'Train/mean miou_metric': 0.9850679636001587, 'Train/mean f1': 0.9888553023338318, 'Train/mean precision': 0.9845847487449646, 'Train/mean recall': 0.9931631088256836, 'Train/mean hd95_metric': 1.5509679317474365} +Epoch [1277/4000] Validation [1/4] Loss: 0.34437 focal_loss 0.25030 dice_loss 0.09407 +Epoch [1277/4000] Validation [2/4] Loss: 0.66216 focal_loss 0.41675 dice_loss 0.24541 +Epoch [1277/4000] Validation [3/4] Loss: 0.38354 focal_loss 0.27239 dice_loss 0.11114 +Epoch [1277/4000] Validation [4/4] Loss: 0.42263 focal_loss 0.29371 dice_loss 0.12892 +Epoch [1277/4000] Validation metric {'Val/mean dice_metric': 0.964838981628418, 'Val/mean miou_metric': 0.944320797920227, 'Val/mean f1': 0.9638569355010986, 'Val/mean precision': 0.9598471522331238, 'Val/mean recall': 0.967900276184082, 'Val/mean hd95_metric': 7.476902008056641} +Cheakpoint... +Epoch [1277/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.964838981628418, 'Val/mean miou_metric': 0.944320797920227, 'Val/mean f1': 0.9638569355010986, 'Val/mean precision': 0.9598471522331238, 'Val/mean recall': 0.967900276184082, 'Val/mean hd95_metric': 7.476902008056641} +Epoch [1278/4000] Training [1/16] Loss: 0.01100 +Epoch [1278/4000] Training [2/16] Loss: 0.00798 +Epoch [1278/4000] Training [3/16] Loss: 0.01075 +Epoch [1278/4000] Training [4/16] Loss: 0.00945 +Epoch [1278/4000] Training [5/16] Loss: 0.01063 +Epoch [1278/4000] Training [6/16] Loss: 0.01767 +Epoch [1278/4000] Training [7/16] Loss: 0.01464 +Epoch [1278/4000] Training [8/16] Loss: 0.01105 +Epoch [1278/4000] Training [9/16] Loss: 0.03805 +Epoch [1278/4000] Training [10/16] Loss: 0.00852 +Epoch [1278/4000] Training [11/16] Loss: 0.01016 +Epoch [1278/4000] Training [12/16] Loss: 0.01029 +Epoch [1278/4000] Training [13/16] Loss: 0.00910 +Epoch [1278/4000] Training [14/16] Loss: 0.01045 +Epoch [1278/4000] Training [15/16] Loss: 0.00736 +Epoch [1278/4000] Training [16/16] Loss: 0.00833 +Epoch [1278/4000] Training metric {'Train/mean dice_metric': 0.9926457405090332, 'Train/mean miou_metric': 0.9851906895637512, 'Train/mean f1': 0.9885000586509705, 'Train/mean precision': 0.9840263724327087, 'Train/mean recall': 0.9930145740509033, 'Train/mean hd95_metric': 1.6450247764587402} +Epoch [1278/4000] Validation [1/4] Loss: 0.37562 focal_loss 0.24313 dice_loss 0.13248 +Epoch [1278/4000] Validation [2/4] Loss: 0.54536 focal_loss 0.32248 dice_loss 0.22288 +Epoch [1278/4000] Validation [3/4] Loss: 0.24569 focal_loss 0.15259 dice_loss 0.09310 +Epoch [1278/4000] Validation [4/4] Loss: 0.24114 focal_loss 0.11584 dice_loss 0.12530 +Epoch [1278/4000] Validation metric {'Val/mean dice_metric': 0.9632061719894409, 'Val/mean miou_metric': 0.9435321092605591, 'Val/mean f1': 0.9677726626396179, 'Val/mean precision': 0.9648019671440125, 'Val/mean recall': 0.9707618951797485, 'Val/mean hd95_metric': 7.896631240844727} +Cheakpoint... +Epoch [1278/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9632], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632061719894409, 'Val/mean miou_metric': 0.9435321092605591, 'Val/mean f1': 0.9677726626396179, 'Val/mean precision': 0.9648019671440125, 'Val/mean recall': 0.9707618951797485, 'Val/mean hd95_metric': 7.896631240844727} +Epoch [1279/4000] Training [1/16] Loss: 0.01144 +Epoch [1279/4000] Training [2/16] Loss: 0.01378 +Epoch [1279/4000] Training [3/16] Loss: 0.01116 +Epoch [1279/4000] Training [4/16] Loss: 0.00923 +Epoch [1279/4000] Training [5/16] Loss: 0.01006 +Epoch [1279/4000] Training [6/16] Loss: 0.01176 +Epoch [1279/4000] Training [7/16] Loss: 0.00836 +Epoch [1279/4000] Training [8/16] Loss: 0.01070 +Epoch [1279/4000] Training [9/16] Loss: 0.01167 +Epoch [1279/4000] Training [10/16] Loss: 0.00734 +Epoch [1279/4000] Training [11/16] Loss: 0.01128 +Epoch [1279/4000] Training [12/16] Loss: 0.01017 +Epoch [1279/4000] Training [13/16] Loss: 0.00942 +Epoch [1279/4000] Training [14/16] Loss: 0.01065 +Epoch [1279/4000] Training [15/16] Loss: 0.01050 +Epoch [1279/4000] Training [16/16] Loss: 0.01096 +Epoch [1279/4000] Training metric {'Train/mean dice_metric': 0.9913941621780396, 'Train/mean miou_metric': 0.9835218787193298, 'Train/mean f1': 0.9885621666908264, 'Train/mean precision': 0.9843137860298157, 'Train/mean recall': 0.9928473234176636, 'Train/mean hd95_metric': 1.2820323705673218} +Epoch [1279/4000] Validation [1/4] Loss: 0.20861 focal_loss 0.14335 dice_loss 0.06526 +Epoch [1279/4000] Validation [2/4] Loss: 0.30675 focal_loss 0.15991 dice_loss 0.14684 +Epoch [1279/4000] Validation [3/4] Loss: 0.49711 focal_loss 0.34626 dice_loss 0.15085 +Epoch [1279/4000] Validation [4/4] Loss: 0.28264 focal_loss 0.16506 dice_loss 0.11758 +Epoch [1279/4000] Validation metric {'Val/mean dice_metric': 0.9653310775756836, 'Val/mean miou_metric': 0.9452773928642273, 'Val/mean f1': 0.9691382646560669, 'Val/mean precision': 0.9621325731277466, 'Val/mean recall': 0.97624671459198, 'Val/mean hd95_metric': 7.852217197418213} +Cheakpoint... +Epoch [1279/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653310775756836, 'Val/mean miou_metric': 0.9452773928642273, 'Val/mean f1': 0.9691382646560669, 'Val/mean precision': 0.9621325731277466, 'Val/mean recall': 0.97624671459198, 'Val/mean hd95_metric': 7.852217197418213} +Epoch [1280/4000] Training [1/16] Loss: 0.00862 +Epoch [1280/4000] Training [2/16] Loss: 0.00934 +Epoch [1280/4000] Training [3/16] Loss: 0.00950 +Epoch [1280/4000] Training [4/16] Loss: 0.00856 +Epoch [1280/4000] Training [5/16] Loss: 0.01081 +Epoch [1280/4000] Training [6/16] Loss: 0.01113 +Epoch [1280/4000] Training [7/16] Loss: 0.01023 +Epoch [1280/4000] Training [8/16] Loss: 0.01192 +Epoch [1280/4000] Training [9/16] Loss: 0.01200 +Epoch [1280/4000] Training [10/16] Loss: 0.00989 +Epoch [1280/4000] Training [11/16] Loss: 0.01053 +Epoch [1280/4000] Training [12/16] Loss: 0.01154 +Epoch [1280/4000] Training [13/16] Loss: 0.01035 +Epoch [1280/4000] Training [14/16] Loss: 0.01082 +Epoch [1280/4000] Training [15/16] Loss: 0.05571 +Epoch [1280/4000] Training [16/16] Loss: 0.01777 +Epoch [1280/4000] Training metric {'Train/mean dice_metric': 0.9923839569091797, 'Train/mean miou_metric': 0.9846727848052979, 'Train/mean f1': 0.9884583353996277, 'Train/mean precision': 0.9844762682914734, 'Train/mean recall': 0.9924727082252502, 'Train/mean hd95_metric': 1.875655174255371} +Epoch [1280/4000] Validation [1/4] Loss: 0.23721 focal_loss 0.17220 dice_loss 0.06501 +Epoch [1280/4000] Validation [2/4] Loss: 0.28828 focal_loss 0.16317 dice_loss 0.12510 +Epoch [1280/4000] Validation [3/4] Loss: 0.35145 focal_loss 0.22656 dice_loss 0.12488 +Epoch [1280/4000] Validation [4/4] Loss: 0.36084 focal_loss 0.23515 dice_loss 0.12569 +Epoch [1280/4000] Validation metric {'Val/mean dice_metric': 0.9698467254638672, 'Val/mean miou_metric': 0.9498102068901062, 'Val/mean f1': 0.9711741209030151, 'Val/mean precision': 0.9668816328048706, 'Val/mean recall': 0.9755048155784607, 'Val/mean hd95_metric': 6.865495204925537} +Cheakpoint... +Epoch [1280/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698467254638672, 'Val/mean miou_metric': 0.9498102068901062, 'Val/mean f1': 0.9711741209030151, 'Val/mean precision': 0.9668816328048706, 'Val/mean recall': 0.9755048155784607, 'Val/mean hd95_metric': 6.865495204925537} +Epoch [1281/4000] Training [1/16] Loss: 0.00783 +Epoch [1281/4000] Training [2/16] Loss: 0.01188 +Epoch [1281/4000] Training [3/16] Loss: 0.01060 +Epoch [1281/4000] Training [4/16] Loss: 0.02340 +Epoch [1281/4000] Training [5/16] Loss: 0.01144 +Epoch [1281/4000] Training [6/16] Loss: 0.00920 +Epoch [1281/4000] Training [7/16] Loss: 0.01210 +Epoch [1281/4000] Training [8/16] Loss: 0.01401 +Epoch [1281/4000] Training [9/16] Loss: 0.01093 +Epoch [1281/4000] Training [10/16] Loss: 0.01128 +Epoch [1281/4000] Training [11/16] Loss: 0.00810 +Epoch [1281/4000] Training [12/16] Loss: 0.00884 +Epoch [1281/4000] Training [13/16] Loss: 0.01125 +Epoch [1281/4000] Training [14/16] Loss: 0.01555 +Epoch [1281/4000] Training [15/16] Loss: 0.00773 +Epoch [1281/4000] Training [16/16] Loss: 0.01369 +Epoch [1281/4000] Training metric {'Train/mean dice_metric': 0.9920750856399536, 'Train/mean miou_metric': 0.9840518236160278, 'Train/mean f1': 0.9878848195075989, 'Train/mean precision': 0.9824008345603943, 'Train/mean recall': 0.9934303760528564, 'Train/mean hd95_metric': 1.6335002183914185} +Epoch [1281/4000] Validation [1/4] Loss: 0.50083 focal_loss 0.36643 dice_loss 0.13440 +Epoch [1281/4000] Validation [2/4] Loss: 0.29076 focal_loss 0.12498 dice_loss 0.16578 +Epoch [1281/4000] Validation [3/4] Loss: 0.15744 focal_loss 0.08961 dice_loss 0.06783 +Epoch [1281/4000] Validation [4/4] Loss: 0.35779 focal_loss 0.22837 dice_loss 0.12942 +Epoch [1281/4000] Validation metric {'Val/mean dice_metric': 0.9632697105407715, 'Val/mean miou_metric': 0.9423463940620422, 'Val/mean f1': 0.9673340916633606, 'Val/mean precision': 0.9662273526191711, 'Val/mean recall': 0.9684433937072754, 'Val/mean hd95_metric': 6.5745158195495605} +Cheakpoint... +Epoch [1281/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9633], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9632697105407715, 'Val/mean miou_metric': 0.9423463940620422, 'Val/mean f1': 0.9673340916633606, 'Val/mean precision': 0.9662273526191711, 'Val/mean recall': 0.9684433937072754, 'Val/mean hd95_metric': 6.5745158195495605} +Epoch [1282/4000] Training [1/16] Loss: 0.00971 +Epoch [1282/4000] Training [2/16] Loss: 0.04958 +Epoch [1282/4000] Training [3/16] Loss: 0.01308 +Epoch [1282/4000] Training [4/16] Loss: 0.01727 +Epoch [1282/4000] Training [5/16] Loss: 0.00882 +Epoch [1282/4000] Training [6/16] Loss: 0.00934 +Epoch [1282/4000] Training [7/16] Loss: 0.00849 +Epoch [1282/4000] Training [8/16] Loss: 0.01014 +Epoch [1282/4000] Training [9/16] Loss: 0.00950 +Epoch [1282/4000] Training [10/16] Loss: 0.00921 +Epoch [1282/4000] Training [11/16] Loss: 0.01150 +Epoch [1282/4000] Training [12/16] Loss: 0.00842 +Epoch [1282/4000] Training [13/16] Loss: 0.00869 +Epoch [1282/4000] Training [14/16] Loss: 0.00766 +Epoch [1282/4000] Training [15/16] Loss: 0.00984 +Epoch [1282/4000] Training [16/16] Loss: 0.00924 +Epoch [1282/4000] Training metric {'Train/mean dice_metric': 0.992556631565094, 'Train/mean miou_metric': 0.9851489067077637, 'Train/mean f1': 0.9889596104621887, 'Train/mean precision': 0.9842226505279541, 'Train/mean recall': 0.9937423467636108, 'Train/mean hd95_metric': 1.426705241203308} +Epoch [1282/4000] Validation [1/4] Loss: 0.23248 focal_loss 0.16187 dice_loss 0.07061 +Epoch [1282/4000] Validation [2/4] Loss: 0.64251 focal_loss 0.33831 dice_loss 0.30421 +Epoch [1282/4000] Validation [3/4] Loss: 0.19609 focal_loss 0.11310 dice_loss 0.08299 +Epoch [1282/4000] Validation [4/4] Loss: 0.23336 focal_loss 0.12368 dice_loss 0.10967 +Epoch [1282/4000] Validation metric {'Val/mean dice_metric': 0.9636678695678711, 'Val/mean miou_metric': 0.9449833631515503, 'Val/mean f1': 0.969870924949646, 'Val/mean precision': 0.9661715030670166, 'Val/mean recall': 0.9735987186431885, 'Val/mean hd95_metric': 6.955945014953613} +Cheakpoint... +Epoch [1282/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636678695678711, 'Val/mean miou_metric': 0.9449833631515503, 'Val/mean f1': 0.969870924949646, 'Val/mean precision': 0.9661715030670166, 'Val/mean recall': 0.9735987186431885, 'Val/mean hd95_metric': 6.955945014953613} +Epoch [1283/4000] Training [1/16] Loss: 0.01186 +Epoch [1283/4000] Training [2/16] Loss: 0.00823 +Epoch [1283/4000] Training [3/16] Loss: 0.01006 +Epoch [1283/4000] Training [4/16] Loss: 0.01074 +Epoch [1283/4000] Training [5/16] Loss: 0.00853 +Epoch [1283/4000] Training [6/16] Loss: 0.01132 +Epoch [1283/4000] Training [7/16] Loss: 0.01238 +Epoch [1283/4000] Training [8/16] Loss: 0.01001 +Epoch [1283/4000] Training [9/16] Loss: 0.01110 +Epoch [1283/4000] Training [10/16] Loss: 0.00857 +Epoch [1283/4000] Training [11/16] Loss: 0.00868 +Epoch [1283/4000] Training [12/16] Loss: 0.01259 +Epoch [1283/4000] Training [13/16] Loss: 0.00834 +Epoch [1283/4000] Training [14/16] Loss: 0.00877 +Epoch [1283/4000] Training [15/16] Loss: 0.01076 +Epoch [1283/4000] Training [16/16] Loss: 0.01088 +Epoch [1283/4000] Training metric {'Train/mean dice_metric': 0.9933249354362488, 'Train/mean miou_metric': 0.9864823222160339, 'Train/mean f1': 0.9892668128013611, 'Train/mean precision': 0.9843879342079163, 'Train/mean recall': 0.9941943883895874, 'Train/mean hd95_metric': 1.1858960390090942} +Epoch [1283/4000] Validation [1/4] Loss: 0.28474 focal_loss 0.19920 dice_loss 0.08554 +Epoch [1283/4000] Validation [2/4] Loss: 0.42949 focal_loss 0.21656 dice_loss 0.21293 +Epoch [1283/4000] Validation [3/4] Loss: 0.29759 focal_loss 0.18726 dice_loss 0.11033 +Epoch [1283/4000] Validation [4/4] Loss: 0.28888 focal_loss 0.16361 dice_loss 0.12527 +Epoch [1283/4000] Validation metric {'Val/mean dice_metric': 0.967807948589325, 'Val/mean miou_metric': 0.9492474794387817, 'Val/mean f1': 0.9692087173461914, 'Val/mean precision': 0.9608652591705322, 'Val/mean recall': 0.9776982665061951, 'Val/mean hd95_metric': 7.056884765625} +Cheakpoint... +Epoch [1283/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967807948589325, 'Val/mean miou_metric': 0.9492474794387817, 'Val/mean f1': 0.9692087173461914, 'Val/mean precision': 0.9608652591705322, 'Val/mean recall': 0.9776982665061951, 'Val/mean hd95_metric': 7.056884765625} +Epoch [1284/4000] Training [1/16] Loss: 0.01081 +Epoch [1284/4000] Training [2/16] Loss: 0.01000 +Epoch [1284/4000] Training [3/16] Loss: 0.00738 +Epoch [1284/4000] Training [4/16] Loss: 0.01087 +Epoch [1284/4000] Training [5/16] Loss: 0.01004 +Epoch [1284/4000] Training [6/16] Loss: 0.00876 +Epoch [1284/4000] Training [7/16] Loss: 0.00932 +Epoch [1284/4000] Training [8/16] Loss: 0.00979 +Epoch [1284/4000] Training [9/16] Loss: 0.00825 +Epoch [1284/4000] Training [10/16] Loss: 0.01306 +Epoch [1284/4000] Training [11/16] Loss: 0.00860 +Epoch [1284/4000] Training [12/16] Loss: 0.00721 +Epoch [1284/4000] Training [13/16] Loss: 0.01041 +Epoch [1284/4000] Training [14/16] Loss: 0.00785 +Epoch [1284/4000] Training [15/16] Loss: 0.00911 +Epoch [1284/4000] Training [16/16] Loss: 0.00709 +Epoch [1284/4000] Training metric {'Train/mean dice_metric': 0.9936023354530334, 'Train/mean miou_metric': 0.9870504140853882, 'Train/mean f1': 0.9896020293235779, 'Train/mean precision': 0.9851542115211487, 'Train/mean recall': 0.99409019947052, 'Train/mean hd95_metric': 1.110613226890564} +Epoch [1284/4000] Validation [1/4] Loss: 0.24708 focal_loss 0.17511 dice_loss 0.07196 +Epoch [1284/4000] Validation [2/4] Loss: 0.45803 focal_loss 0.24368 dice_loss 0.21435 +Epoch [1284/4000] Validation [3/4] Loss: 0.35441 focal_loss 0.22855 dice_loss 0.12586 +Epoch [1284/4000] Validation [4/4] Loss: 0.19564 focal_loss 0.10876 dice_loss 0.08688 +Epoch [1284/4000] Validation metric {'Val/mean dice_metric': 0.9659711718559265, 'Val/mean miou_metric': 0.9464014172554016, 'Val/mean f1': 0.9682641625404358, 'Val/mean precision': 0.9643508791923523, 'Val/mean recall': 0.9722092151641846, 'Val/mean hd95_metric': 6.931509494781494} +Cheakpoint... +Epoch [1284/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659711718559265, 'Val/mean miou_metric': 0.9464014172554016, 'Val/mean f1': 0.9682641625404358, 'Val/mean precision': 0.9643508791923523, 'Val/mean recall': 0.9722092151641846, 'Val/mean hd95_metric': 6.931509494781494} +Epoch [1285/4000] Training [1/16] Loss: 0.00853 +Epoch [1285/4000] Training [2/16] Loss: 0.00733 +Epoch [1285/4000] Training [3/16] Loss: 0.00886 +Epoch [1285/4000] Training [4/16] Loss: 0.00870 +Epoch [1285/4000] Training [5/16] Loss: 0.01202 +Epoch [1285/4000] Training [6/16] Loss: 0.00811 +Epoch [1285/4000] Training [7/16] Loss: 0.01131 +Epoch [1285/4000] Training [8/16] Loss: 0.00818 +Epoch [1285/4000] Training [9/16] Loss: 0.00966 +Epoch [1285/4000] Training [10/16] Loss: 0.00964 +Epoch [1285/4000] Training [11/16] Loss: 0.00797 +Epoch [1285/4000] Training [12/16] Loss: 0.00989 +Epoch [1285/4000] Training [13/16] Loss: 0.00918 +Epoch [1285/4000] Training [14/16] Loss: 0.00715 +Epoch [1285/4000] Training [15/16] Loss: 0.01012 +Epoch [1285/4000] Training [16/16] Loss: 0.00785 +Epoch [1285/4000] Training metric {'Train/mean dice_metric': 0.993623673915863, 'Train/mean miou_metric': 0.9870927333831787, 'Train/mean f1': 0.989543080329895, 'Train/mean precision': 0.984963059425354, 'Train/mean recall': 0.9941657781600952, 'Train/mean hd95_metric': 1.3314857482910156} +Epoch [1285/4000] Validation [1/4] Loss: 0.26766 focal_loss 0.18539 dice_loss 0.08227 +Epoch [1285/4000] Validation [2/4] Loss: 0.36995 focal_loss 0.20295 dice_loss 0.16700 +Epoch [1285/4000] Validation [3/4] Loss: 0.48729 focal_loss 0.34838 dice_loss 0.13891 +Epoch [1285/4000] Validation [4/4] Loss: 0.19519 focal_loss 0.11729 dice_loss 0.07790 +Epoch [1285/4000] Validation metric {'Val/mean dice_metric': 0.9663179516792297, 'Val/mean miou_metric': 0.9473367929458618, 'Val/mean f1': 0.9688575863838196, 'Val/mean precision': 0.9631000757217407, 'Val/mean recall': 0.974684476852417, 'Val/mean hd95_metric': 7.463270664215088} +Cheakpoint... +Epoch [1285/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9663179516792297, 'Val/mean miou_metric': 0.9473367929458618, 'Val/mean f1': 0.9688575863838196, 'Val/mean precision': 0.9631000757217407, 'Val/mean recall': 0.974684476852417, 'Val/mean hd95_metric': 7.463270664215088} +Epoch [1286/4000] Training [1/16] Loss: 0.00810 +Epoch [1286/4000] Training [2/16] Loss: 0.00854 +Epoch [1286/4000] Training [3/16] Loss: 0.00913 +Epoch [1286/4000] Training [4/16] Loss: 0.00872 +Epoch [1286/4000] Training [5/16] Loss: 0.00991 +Epoch [1286/4000] Training [6/16] Loss: 0.01042 +Epoch [1286/4000] Training [7/16] Loss: 0.00791 +Epoch [1286/4000] Training [8/16] Loss: 0.00735 +Epoch [1286/4000] Training [9/16] Loss: 0.00867 +Epoch [1286/4000] Training [10/16] Loss: 0.00929 +Epoch [1286/4000] Training [11/16] Loss: 0.00921 +Epoch [1286/4000] Training [12/16] Loss: 0.00823 +Epoch [1286/4000] Training [13/16] Loss: 0.00895 +Epoch [1286/4000] Training [14/16] Loss: 0.00730 +Epoch [1286/4000] Training [15/16] Loss: 0.00933 +Epoch [1286/4000] Training [16/16] Loss: 0.00752 +Epoch [1286/4000] Training metric {'Train/mean dice_metric': 0.993982195854187, 'Train/mean miou_metric': 0.9877873063087463, 'Train/mean f1': 0.9900275468826294, 'Train/mean precision': 0.9855834245681763, 'Train/mean recall': 0.9945119619369507, 'Train/mean hd95_metric': 1.0765504837036133} +Epoch [1286/4000] Validation [1/4] Loss: 0.22509 focal_loss 0.15627 dice_loss 0.06882 +Epoch [1286/4000] Validation [2/4] Loss: 0.33602 focal_loss 0.17206 dice_loss 0.16397 +Epoch [1286/4000] Validation [3/4] Loss: 0.36719 focal_loss 0.25195 dice_loss 0.11524 +Epoch [1286/4000] Validation [4/4] Loss: 0.18811 focal_loss 0.10220 dice_loss 0.08591 +Epoch [1286/4000] Validation metric {'Val/mean dice_metric': 0.9704595804214478, 'Val/mean miou_metric': 0.9523633718490601, 'Val/mean f1': 0.971421480178833, 'Val/mean precision': 0.9673623442649841, 'Val/mean recall': 0.9755148887634277, 'Val/mean hd95_metric': 6.156290054321289} +Cheakpoint... +Epoch [1286/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704595804214478, 'Val/mean miou_metric': 0.9523633718490601, 'Val/mean f1': 0.971421480178833, 'Val/mean precision': 0.9673623442649841, 'Val/mean recall': 0.9755148887634277, 'Val/mean hd95_metric': 6.156290054321289} +Epoch [1287/4000] Training [1/16] Loss: 0.00822 +Epoch [1287/4000] Training [2/16] Loss: 0.00655 +Epoch [1287/4000] Training [3/16] Loss: 0.00826 +Epoch [1287/4000] Training [4/16] Loss: 0.00899 +Epoch [1287/4000] Training [5/16] Loss: 0.00746 +Epoch [1287/4000] Training [6/16] Loss: 0.00911 +Epoch [1287/4000] Training [7/16] Loss: 0.00973 +Epoch [1287/4000] Training [8/16] Loss: 0.00773 +Epoch [1287/4000] Training [9/16] Loss: 0.00847 +Epoch [1287/4000] Training [10/16] Loss: 0.00804 +Epoch [1287/4000] Training [11/16] Loss: 0.00869 +Epoch [1287/4000] Training [12/16] Loss: 0.00690 +Epoch [1287/4000] Training [13/16] Loss: 0.01005 +Epoch [1287/4000] Training [14/16] Loss: 0.01075 +Epoch [1287/4000] Training [15/16] Loss: 0.00798 +Epoch [1287/4000] Training [16/16] Loss: 0.00962 +Epoch [1287/4000] Training metric {'Train/mean dice_metric': 0.9940981864929199, 'Train/mean miou_metric': 0.9880210161209106, 'Train/mean f1': 0.9901842474937439, 'Train/mean precision': 0.9858025312423706, 'Train/mean recall': 0.9946050643920898, 'Train/mean hd95_metric': 1.0685434341430664} +Epoch [1287/4000] Validation [1/4] Loss: 0.33266 focal_loss 0.24925 dice_loss 0.08341 +Epoch [1287/4000] Validation [2/4] Loss: 0.45282 focal_loss 0.23684 dice_loss 0.21597 +Epoch [1287/4000] Validation [3/4] Loss: 0.36036 focal_loss 0.25408 dice_loss 0.10628 +Epoch [1287/4000] Validation [4/4] Loss: 0.22633 focal_loss 0.14803 dice_loss 0.07830 +Epoch [1287/4000] Validation metric {'Val/mean dice_metric': 0.9693053960800171, 'Val/mean miou_metric': 0.950769305229187, 'Val/mean f1': 0.9712475538253784, 'Val/mean precision': 0.9691838622093201, 'Val/mean recall': 0.9733200073242188, 'Val/mean hd95_metric': 6.583621978759766} +Cheakpoint... +Epoch [1287/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693053960800171, 'Val/mean miou_metric': 0.950769305229187, 'Val/mean f1': 0.9712475538253784, 'Val/mean precision': 0.9691838622093201, 'Val/mean recall': 0.9733200073242188, 'Val/mean hd95_metric': 6.583621978759766} +Epoch [1288/4000] Training [1/16] Loss: 0.00763 +Epoch [1288/4000] Training [2/16] Loss: 0.01909 +Epoch [1288/4000] Training [3/16] Loss: 0.00767 +Epoch [1288/4000] Training [4/16] Loss: 0.00886 +Epoch [1288/4000] Training [5/16] Loss: 0.00773 +Epoch [1288/4000] Training [6/16] Loss: 0.01021 +Epoch [1288/4000] Training [7/16] Loss: 0.00812 +Epoch [1288/4000] Training [8/16] Loss: 0.01023 +Epoch [1288/4000] Training [9/16] Loss: 0.00706 +Epoch [1288/4000] Training [10/16] Loss: 0.00828 +Epoch [1288/4000] Training [11/16] Loss: 0.01271 +Epoch [1288/4000] Training [12/16] Loss: 0.00896 +Epoch [1288/4000] Training [13/16] Loss: 0.01194 +Epoch [1288/4000] Training [14/16] Loss: 0.00867 +Epoch [1288/4000] Training [15/16] Loss: 0.00793 +Epoch [1288/4000] Training [16/16] Loss: 0.00885 +Epoch [1288/4000] Training metric {'Train/mean dice_metric': 0.9934011697769165, 'Train/mean miou_metric': 0.986760139465332, 'Train/mean f1': 0.989834725856781, 'Train/mean precision': 0.98543781042099, 'Train/mean recall': 0.9942710399627686, 'Train/mean hd95_metric': 1.233214020729065} +Epoch [1288/4000] Validation [1/4] Loss: 0.18670 focal_loss 0.12864 dice_loss 0.05807 +Epoch [1288/4000] Validation [2/4] Loss: 0.48526 focal_loss 0.26812 dice_loss 0.21714 +Epoch [1288/4000] Validation [3/4] Loss: 0.42164 focal_loss 0.30043 dice_loss 0.12121 +Epoch [1288/4000] Validation [4/4] Loss: 0.20769 focal_loss 0.12733 dice_loss 0.08036 +Epoch [1288/4000] Validation metric {'Val/mean dice_metric': 0.9707660675048828, 'Val/mean miou_metric': 0.9521431922912598, 'Val/mean f1': 0.9718982577323914, 'Val/mean precision': 0.964844286441803, 'Val/mean recall': 0.9790561199188232, 'Val/mean hd95_metric': 6.166922569274902} +Cheakpoint... +Epoch [1288/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707660675048828, 'Val/mean miou_metric': 0.9521431922912598, 'Val/mean f1': 0.9718982577323914, 'Val/mean precision': 0.964844286441803, 'Val/mean recall': 0.9790561199188232, 'Val/mean hd95_metric': 6.166922569274902} +Epoch [1289/4000] Training [1/16] Loss: 0.00966 +Epoch [1289/4000] Training [2/16] Loss: 0.00909 +Epoch [1289/4000] Training [3/16] Loss: 0.00829 +Epoch [1289/4000] Training [4/16] Loss: 0.01147 +Epoch [1289/4000] Training [5/16] Loss: 0.00841 +Epoch [1289/4000] Training [6/16] Loss: 0.00962 +Epoch [1289/4000] Training [7/16] Loss: 0.00834 +Epoch [1289/4000] Training [8/16] Loss: 0.00920 +Epoch [1289/4000] Training [9/16] Loss: 0.01104 +Epoch [1289/4000] Training [10/16] Loss: 0.01244 +Epoch [1289/4000] Training [11/16] Loss: 0.01126 +Epoch [1289/4000] Training [12/16] Loss: 0.01008 +Epoch [1289/4000] Training [13/16] Loss: 0.00963 +Epoch [1289/4000] Training [14/16] Loss: 0.00826 +Epoch [1289/4000] Training [15/16] Loss: 0.01066 +Epoch [1289/4000] Training [16/16] Loss: 0.01076 +Epoch [1289/4000] Training metric {'Train/mean dice_metric': 0.9926471710205078, 'Train/mean miou_metric': 0.9852924942970276, 'Train/mean f1': 0.989010214805603, 'Train/mean precision': 0.9841749668121338, 'Train/mean recall': 0.9938932657241821, 'Train/mean hd95_metric': 1.303390622138977} +Epoch [1289/4000] Validation [1/4] Loss: 0.26354 focal_loss 0.18355 dice_loss 0.07999 +Epoch [1289/4000] Validation [2/4] Loss: 0.37508 focal_loss 0.22225 dice_loss 0.15282 +Epoch [1289/4000] Validation [3/4] Loss: 0.18866 focal_loss 0.11354 dice_loss 0.07512 +Epoch [1289/4000] Validation [4/4] Loss: 0.30593 focal_loss 0.19889 dice_loss 0.10704 +Epoch [1289/4000] Validation metric {'Val/mean dice_metric': 0.968592643737793, 'Val/mean miou_metric': 0.9490569233894348, 'Val/mean f1': 0.9698094725608826, 'Val/mean precision': 0.9671344757080078, 'Val/mean recall': 0.9724993109703064, 'Val/mean hd95_metric': 7.134869575500488} +Cheakpoint... +Epoch [1289/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968592643737793, 'Val/mean miou_metric': 0.9490569233894348, 'Val/mean f1': 0.9698094725608826, 'Val/mean precision': 0.9671344757080078, 'Val/mean recall': 0.9724993109703064, 'Val/mean hd95_metric': 7.134869575500488} +Epoch [1290/4000] Training [1/16] Loss: 0.00897 +Epoch [1290/4000] Training [2/16] Loss: 0.00931 +Epoch [1290/4000] Training [3/16] Loss: 0.00786 +Epoch [1290/4000] Training [4/16] Loss: 0.01029 +Epoch [1290/4000] Training [5/16] Loss: 0.00907 +Epoch [1290/4000] Training [6/16] Loss: 0.00603 +Epoch [1290/4000] Training [7/16] Loss: 0.00801 +Epoch [1290/4000] Training [8/16] Loss: 0.00916 +Epoch [1290/4000] Training [9/16] Loss: 0.00819 +Epoch [1290/4000] Training [10/16] Loss: 0.00942 +Epoch [1290/4000] Training [11/16] Loss: 0.01117 +Epoch [1290/4000] Training [12/16] Loss: 0.01208 +Epoch [1290/4000] Training [13/16] Loss: 0.00921 +Epoch [1290/4000] Training [14/16] Loss: 0.00987 +Epoch [1290/4000] Training [15/16] Loss: 0.01186 +Epoch [1290/4000] Training [16/16] Loss: 0.01687 +Epoch [1290/4000] Training metric {'Train/mean dice_metric': 0.9931257963180542, 'Train/mean miou_metric': 0.9861390590667725, 'Train/mean f1': 0.9892919659614563, 'Train/mean precision': 0.9851990342140198, 'Train/mean recall': 0.9934189915657043, 'Train/mean hd95_metric': 1.259324312210083} +Epoch [1290/4000] Validation [1/4] Loss: 0.28542 focal_loss 0.21310 dice_loss 0.07232 +Epoch [1290/4000] Validation [2/4] Loss: 0.62426 focal_loss 0.42840 dice_loss 0.19586 +Epoch [1290/4000] Validation [3/4] Loss: 0.33574 focal_loss 0.22141 dice_loss 0.11433 +Epoch [1290/4000] Validation [4/4] Loss: 0.30779 focal_loss 0.18818 dice_loss 0.11961 +Epoch [1290/4000] Validation metric {'Val/mean dice_metric': 0.9668998718261719, 'Val/mean miou_metric': 0.947430431842804, 'Val/mean f1': 0.9695343971252441, 'Val/mean precision': 0.970904529094696, 'Val/mean recall': 0.9681680798530579, 'Val/mean hd95_metric': 6.9595842361450195} +Cheakpoint... +Epoch [1290/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668998718261719, 'Val/mean miou_metric': 0.947430431842804, 'Val/mean f1': 0.9695343971252441, 'Val/mean precision': 0.970904529094696, 'Val/mean recall': 0.9681680798530579, 'Val/mean hd95_metric': 6.9595842361450195} +Epoch [1291/4000] Training [1/16] Loss: 0.01068 +Epoch [1291/4000] Training [2/16] Loss: 0.01039 +Epoch [1291/4000] Training [3/16] Loss: 0.00987 +Epoch [1291/4000] Training [4/16] Loss: 0.01085 +Epoch [1291/4000] Training [5/16] Loss: 0.01866 +Epoch [1291/4000] Training [6/16] Loss: 0.00998 +Epoch [1291/4000] Training [7/16] Loss: 0.00970 +Epoch [1291/4000] Training [8/16] Loss: 0.00921 +Epoch [1291/4000] Training [9/16] Loss: 0.00784 +Epoch [1291/4000] Training [10/16] Loss: 0.00942 +Epoch [1291/4000] Training [11/16] Loss: 0.00843 +Epoch [1291/4000] Training [12/16] Loss: 0.01010 +Epoch [1291/4000] Training [13/16] Loss: 0.00974 +Epoch [1291/4000] Training [14/16] Loss: 0.01241 +Epoch [1291/4000] Training [15/16] Loss: 0.01148 +Epoch [1291/4000] Training [16/16] Loss: 0.01049 +Epoch [1291/4000] Training metric {'Train/mean dice_metric': 0.9923535585403442, 'Train/mean miou_metric': 0.9846829771995544, 'Train/mean f1': 0.9886763691902161, 'Train/mean precision': 0.9842584729194641, 'Train/mean recall': 0.9931341409683228, 'Train/mean hd95_metric': 1.453946828842163} +Epoch [1291/4000] Validation [1/4] Loss: 0.29221 focal_loss 0.19853 dice_loss 0.09368 +Epoch [1291/4000] Validation [2/4] Loss: 0.36902 focal_loss 0.18705 dice_loss 0.18197 +Epoch [1291/4000] Validation [3/4] Loss: 0.34234 focal_loss 0.22163 dice_loss 0.12071 +Epoch [1291/4000] Validation [4/4] Loss: 0.52411 focal_loss 0.37999 dice_loss 0.14412 +Epoch [1291/4000] Validation metric {'Val/mean dice_metric': 0.9652478098869324, 'Val/mean miou_metric': 0.9452556371688843, 'Val/mean f1': 0.9680983424186707, 'Val/mean precision': 0.9702121019363403, 'Val/mean recall': 0.9659939408302307, 'Val/mean hd95_metric': 6.038395881652832} +Cheakpoint... +Epoch [1291/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9652478098869324, 'Val/mean miou_metric': 0.9452556371688843, 'Val/mean f1': 0.9680983424186707, 'Val/mean precision': 0.9702121019363403, 'Val/mean recall': 0.9659939408302307, 'Val/mean hd95_metric': 6.038395881652832} +Epoch [1292/4000] Training [1/16] Loss: 0.01305 +Epoch [1292/4000] Training [2/16] Loss: 0.00681 +Epoch [1292/4000] Training [3/16] Loss: 0.00804 +Epoch [1292/4000] Training [4/16] Loss: 0.00934 +Epoch [1292/4000] Training [5/16] Loss: 0.01349 +Epoch [1292/4000] Training [6/16] Loss: 0.01277 +Epoch [1292/4000] Training [7/16] Loss: 0.01011 +Epoch [1292/4000] Training [8/16] Loss: 0.01233 +Epoch [1292/4000] Training [9/16] Loss: 0.01102 +Epoch [1292/4000] Training [10/16] Loss: 0.01183 +Epoch [1292/4000] Training [11/16] Loss: 0.00914 +Epoch [1292/4000] Training [12/16] Loss: 0.01556 +Epoch [1292/4000] Training [13/16] Loss: 0.01076 +Epoch [1292/4000] Training [14/16] Loss: 0.01007 +Epoch [1292/4000] Training [15/16] Loss: 0.00840 +Epoch [1292/4000] Training [16/16] Loss: 0.00897 +Epoch [1292/4000] Training metric {'Train/mean dice_metric': 0.9927608966827393, 'Train/mean miou_metric': 0.9854031801223755, 'Train/mean f1': 0.9891052842140198, 'Train/mean precision': 0.9843511581420898, 'Train/mean recall': 0.9939055442810059, 'Train/mean hd95_metric': 1.639260172843933} +Epoch [1292/4000] Validation [1/4] Loss: 0.23127 focal_loss 0.16004 dice_loss 0.07124 +Epoch [1292/4000] Validation [2/4] Loss: 0.45096 focal_loss 0.24579 dice_loss 0.20517 +Epoch [1292/4000] Validation [3/4] Loss: 0.26975 focal_loss 0.17543 dice_loss 0.09433 +Epoch [1292/4000] Validation [4/4] Loss: 0.20335 focal_loss 0.11483 dice_loss 0.08852 +Epoch [1292/4000] Validation metric {'Val/mean dice_metric': 0.9678424596786499, 'Val/mean miou_metric': 0.9495841860771179, 'Val/mean f1': 0.9714787006378174, 'Val/mean precision': 0.9668957591056824, 'Val/mean recall': 0.9761053919792175, 'Val/mean hd95_metric': 5.929422855377197} +Cheakpoint... +Epoch [1292/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678424596786499, 'Val/mean miou_metric': 0.9495841860771179, 'Val/mean f1': 0.9714787006378174, 'Val/mean precision': 0.9668957591056824, 'Val/mean recall': 0.9761053919792175, 'Val/mean hd95_metric': 5.929422855377197} +Epoch [1293/4000] Training [1/16] Loss: 0.00784 +Epoch [1293/4000] Training [2/16] Loss: 0.01402 +Epoch [1293/4000] Training [3/16] Loss: 0.01245 +Epoch [1293/4000] Training [4/16] Loss: 0.01000 +Epoch [1293/4000] Training [5/16] Loss: 0.00866 +Epoch [1293/4000] Training [6/16] Loss: 0.01809 +Epoch [1293/4000] Training [7/16] Loss: 0.00984 +Epoch [1293/4000] Training [8/16] Loss: 0.01188 +Epoch [1293/4000] Training [9/16] Loss: 0.01309 +Epoch [1293/4000] Training [10/16] Loss: 0.01092 +Epoch [1293/4000] Training [11/16] Loss: 0.00860 +Epoch [1293/4000] Training [12/16] Loss: 0.00979 +Epoch [1293/4000] Training [13/16] Loss: 0.00890 +Epoch [1293/4000] Training [14/16] Loss: 0.01050 +Epoch [1293/4000] Training [15/16] Loss: 0.00814 +Epoch [1293/4000] Training [16/16] Loss: 0.00970 +Epoch [1293/4000] Training metric {'Train/mean dice_metric': 0.9928380250930786, 'Train/mean miou_metric': 0.9855581521987915, 'Train/mean f1': 0.9886783361434937, 'Train/mean precision': 0.9842493534088135, 'Train/mean recall': 0.9931473731994629, 'Train/mean hd95_metric': 1.2478759288787842} +Epoch [1293/4000] Validation [1/4] Loss: 0.27200 focal_loss 0.19595 dice_loss 0.07604 +Epoch [1293/4000] Validation [2/4] Loss: 0.20091 focal_loss 0.09556 dice_loss 0.10535 +Epoch [1293/4000] Validation [3/4] Loss: 0.36577 focal_loss 0.23801 dice_loss 0.12776 +Epoch [1293/4000] Validation [4/4] Loss: 0.23070 focal_loss 0.12571 dice_loss 0.10499 +Epoch [1293/4000] Validation metric {'Val/mean dice_metric': 0.967227578163147, 'Val/mean miou_metric': 0.9477702379226685, 'Val/mean f1': 0.9692599773406982, 'Val/mean precision': 0.96100914478302, 'Val/mean recall': 0.9776536822319031, 'Val/mean hd95_metric': 7.010100364685059} +Cheakpoint... +Epoch [1293/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967227578163147, 'Val/mean miou_metric': 0.9477702379226685, 'Val/mean f1': 0.9692599773406982, 'Val/mean precision': 0.96100914478302, 'Val/mean recall': 0.9776536822319031, 'Val/mean hd95_metric': 7.010100364685059} +Epoch [1294/4000] Training [1/16] Loss: 0.01317 +Epoch [1294/4000] Training [2/16] Loss: 0.01158 +Epoch [1294/4000] Training [3/16] Loss: 0.00846 +Epoch [1294/4000] Training [4/16] Loss: 0.01028 +Epoch [1294/4000] Training [5/16] Loss: 0.02454 +Epoch [1294/4000] Training [6/16] Loss: 0.00873 +Epoch [1294/4000] Training [7/16] Loss: 0.00839 +Epoch [1294/4000] Training [8/16] Loss: 0.00848 +Epoch [1294/4000] Training [9/16] Loss: 0.01151 +Epoch [1294/4000] Training [10/16] Loss: 0.00908 +Epoch [1294/4000] Training [11/16] Loss: 0.01040 +Epoch [1294/4000] Training [12/16] Loss: 0.00865 +Epoch [1294/4000] Training [13/16] Loss: 0.01028 +Epoch [1294/4000] Training [14/16] Loss: 0.01169 +Epoch [1294/4000] Training [15/16] Loss: 0.01036 +Epoch [1294/4000] Training [16/16] Loss: 0.00976 +Epoch [1294/4000] Training metric {'Train/mean dice_metric': 0.9931411147117615, 'Train/mean miou_metric': 0.9861428737640381, 'Train/mean f1': 0.9895702004432678, 'Train/mean precision': 0.985216498374939, 'Train/mean recall': 0.9939625859260559, 'Train/mean hd95_metric': 1.6011890172958374} +Epoch [1294/4000] Validation [1/4] Loss: 0.26409 focal_loss 0.19470 dice_loss 0.06938 +Epoch [1294/4000] Validation [2/4] Loss: 0.21603 focal_loss 0.09607 dice_loss 0.11996 +Epoch [1294/4000] Validation [3/4] Loss: 0.27347 focal_loss 0.17061 dice_loss 0.10286 +Epoch [1294/4000] Validation [4/4] Loss: 0.26303 focal_loss 0.15940 dice_loss 0.10363 +Epoch [1294/4000] Validation metric {'Val/mean dice_metric': 0.9668115377426147, 'Val/mean miou_metric': 0.9479406476020813, 'Val/mean f1': 0.9692966938018799, 'Val/mean precision': 0.9654569029808044, 'Val/mean recall': 0.9731670618057251, 'Val/mean hd95_metric': 6.731101989746094} +Cheakpoint... +Epoch [1294/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668115377426147, 'Val/mean miou_metric': 0.9479406476020813, 'Val/mean f1': 0.9692966938018799, 'Val/mean precision': 0.9654569029808044, 'Val/mean recall': 0.9731670618057251, 'Val/mean hd95_metric': 6.731101989746094} +Epoch [1295/4000] Training [1/16] Loss: 0.01295 +Epoch [1295/4000] Training [2/16] Loss: 0.01209 +Epoch [1295/4000] Training [3/16] Loss: 0.01306 +Epoch [1295/4000] Training [4/16] Loss: 0.00942 +Epoch [1295/4000] Training [5/16] Loss: 0.00875 +Epoch [1295/4000] Training [6/16] Loss: 0.01010 +Epoch [1295/4000] Training [7/16] Loss: 0.00755 +Epoch [1295/4000] Training [8/16] Loss: 0.01374 +Epoch [1295/4000] Training [9/16] Loss: 0.00829 +Epoch [1295/4000] Training [10/16] Loss: 0.00857 +Epoch [1295/4000] Training [11/16] Loss: 0.01060 +Epoch [1295/4000] Training [12/16] Loss: 0.01646 +Epoch [1295/4000] Training [13/16] Loss: 0.00861 +Epoch [1295/4000] Training [14/16] Loss: 0.01062 +Epoch [1295/4000] Training [15/16] Loss: 0.00837 +Epoch [1295/4000] Training [16/16] Loss: 0.00787 +Epoch [1295/4000] Training metric {'Train/mean dice_metric': 0.9931400418281555, 'Train/mean miou_metric': 0.9861775636672974, 'Train/mean f1': 0.9895724058151245, 'Train/mean precision': 0.9851691722869873, 'Train/mean recall': 0.9940152168273926, 'Train/mean hd95_metric': 1.341029405593872} +Epoch [1295/4000] Validation [1/4] Loss: 0.28889 focal_loss 0.20917 dice_loss 0.07973 +Epoch [1295/4000] Validation [2/4] Loss: 0.34166 focal_loss 0.16449 dice_loss 0.17718 +Epoch [1295/4000] Validation [3/4] Loss: 0.36292 focal_loss 0.24434 dice_loss 0.11859 +Epoch [1295/4000] Validation [4/4] Loss: 0.21363 focal_loss 0.11898 dice_loss 0.09465 +Epoch [1295/4000] Validation metric {'Val/mean dice_metric': 0.9697410464286804, 'Val/mean miou_metric': 0.9504014849662781, 'Val/mean f1': 0.9698553681373596, 'Val/mean precision': 0.9657379984855652, 'Val/mean recall': 0.9740079641342163, 'Val/mean hd95_metric': 6.420027256011963} +Cheakpoint... +Epoch [1295/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697410464286804, 'Val/mean miou_metric': 0.9504014849662781, 'Val/mean f1': 0.9698553681373596, 'Val/mean precision': 0.9657379984855652, 'Val/mean recall': 0.9740079641342163, 'Val/mean hd95_metric': 6.420027256011963} +Epoch [1296/4000] Training [1/16] Loss: 0.00776 +Epoch [1296/4000] Training [2/16] Loss: 0.00878 +Epoch [1296/4000] Training [3/16] Loss: 0.00745 +Epoch [1296/4000] Training [4/16] Loss: 0.00838 +Epoch [1296/4000] Training [5/16] Loss: 0.00943 +Epoch [1296/4000] Training [6/16] Loss: 0.00799 +Epoch [1296/4000] Training [7/16] Loss: 0.01117 +Epoch [1296/4000] Training [8/16] Loss: 0.00922 +Epoch [1296/4000] Training [9/16] Loss: 0.00920 +Epoch [1296/4000] Training [10/16] Loss: 0.01096 +Epoch [1296/4000] Training [11/16] Loss: 0.00607 +Epoch [1296/4000] Training [12/16] Loss: 0.00764 +Epoch [1296/4000] Training [13/16] Loss: 0.00678 +Epoch [1296/4000] Training [14/16] Loss: 0.01119 +Epoch [1296/4000] Training [15/16] Loss: 0.00800 +Epoch [1296/4000] Training [16/16] Loss: 0.00953 +Epoch [1296/4000] Training metric {'Train/mean dice_metric': 0.9936947226524353, 'Train/mean miou_metric': 0.9872646331787109, 'Train/mean f1': 0.9899464845657349, 'Train/mean precision': 0.9853034615516663, 'Train/mean recall': 0.9946335554122925, 'Train/mean hd95_metric': 1.317138910293579} +Epoch [1296/4000] Validation [1/4] Loss: 0.28856 focal_loss 0.21209 dice_loss 0.07647 +Epoch [1296/4000] Validation [2/4] Loss: 0.42227 focal_loss 0.21697 dice_loss 0.20530 +Epoch [1296/4000] Validation [3/4] Loss: 0.31301 focal_loss 0.20854 dice_loss 0.10446 +Epoch [1296/4000] Validation [4/4] Loss: 0.21610 focal_loss 0.11317 dice_loss 0.10293 +Epoch [1296/4000] Validation metric {'Val/mean dice_metric': 0.967430591583252, 'Val/mean miou_metric': 0.9491545557975769, 'Val/mean f1': 0.9704341888427734, 'Val/mean precision': 0.966776430606842, 'Val/mean recall': 0.9741196632385254, 'Val/mean hd95_metric': 6.143548011779785} +Cheakpoint... +Epoch [1296/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967430591583252, 'Val/mean miou_metric': 0.9491545557975769, 'Val/mean f1': 0.9704341888427734, 'Val/mean precision': 0.966776430606842, 'Val/mean recall': 0.9741196632385254, 'Val/mean hd95_metric': 6.143548011779785} +Epoch [1297/4000] Training [1/16] Loss: 0.01036 +Epoch [1297/4000] Training [2/16] Loss: 0.00943 +Epoch [1297/4000] Training [3/16] Loss: 0.00926 +Epoch [1297/4000] Training [4/16] Loss: 0.00791 +Epoch [1297/4000] Training [5/16] Loss: 0.00828 +Epoch [1297/4000] Training [6/16] Loss: 0.00895 +Epoch [1297/4000] Training [7/16] Loss: 0.00771 +Epoch [1297/4000] Training [8/16] Loss: 0.01045 +Epoch [1297/4000] Training [9/16] Loss: 0.00783 +Epoch [1297/4000] Training [10/16] Loss: 0.00971 +Epoch [1297/4000] Training [11/16] Loss: 0.00758 +Epoch [1297/4000] Training [12/16] Loss: 0.01145 +Epoch [1297/4000] Training [13/16] Loss: 0.00944 +Epoch [1297/4000] Training [14/16] Loss: 0.01101 +Epoch [1297/4000] Training [15/16] Loss: 0.00894 +Epoch [1297/4000] Training [16/16] Loss: 0.02021 +Epoch [1297/4000] Training metric {'Train/mean dice_metric': 0.9933853149414062, 'Train/mean miou_metric': 0.98663330078125, 'Train/mean f1': 0.989785373210907, 'Train/mean precision': 0.9852689504623413, 'Train/mean recall': 0.9943433403968811, 'Train/mean hd95_metric': 1.145737886428833} +Epoch [1297/4000] Validation [1/4] Loss: 0.21024 focal_loss 0.14475 dice_loss 0.06549 +Epoch [1297/4000] Validation [2/4] Loss: 0.27733 focal_loss 0.14479 dice_loss 0.13253 +Epoch [1297/4000] Validation [3/4] Loss: 0.19767 focal_loss 0.10478 dice_loss 0.09289 +Epoch [1297/4000] Validation [4/4] Loss: 0.23287 focal_loss 0.13064 dice_loss 0.10223 +Epoch [1297/4000] Validation metric {'Val/mean dice_metric': 0.9699290990829468, 'Val/mean miou_metric': 0.9515403509140015, 'Val/mean f1': 0.9726800918579102, 'Val/mean precision': 0.9689125418663025, 'Val/mean recall': 0.9764770269393921, 'Val/mean hd95_metric': 5.766969203948975} +Cheakpoint... +Epoch [1297/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699290990829468, 'Val/mean miou_metric': 0.9515403509140015, 'Val/mean f1': 0.9726800918579102, 'Val/mean precision': 0.9689125418663025, 'Val/mean recall': 0.9764770269393921, 'Val/mean hd95_metric': 5.766969203948975} +Epoch [1298/4000] Training [1/16] Loss: 0.00751 +Epoch [1298/4000] Training [2/16] Loss: 0.00855 +Epoch [1298/4000] Training [3/16] Loss: 0.00766 +Epoch [1298/4000] Training [4/16] Loss: 0.00836 +Epoch [1298/4000] Training [5/16] Loss: 0.00824 +Epoch [1298/4000] Training [6/16] Loss: 0.00745 +Epoch [1298/4000] Training [7/16] Loss: 0.00834 +Epoch [1298/4000] Training [8/16] Loss: 0.00765 +Epoch [1298/4000] Training [9/16] Loss: 0.00764 +Epoch [1298/4000] Training [10/16] Loss: 0.00855 +Epoch [1298/4000] Training [11/16] Loss: 0.00835 +Epoch [1298/4000] Training [12/16] Loss: 0.00966 +Epoch [1298/4000] Training [13/16] Loss: 0.00980 +Epoch [1298/4000] Training [14/16] Loss: 0.01128 +Epoch [1298/4000] Training [15/16] Loss: 0.00961 +Epoch [1298/4000] Training [16/16] Loss: 0.00905 +Epoch [1298/4000] Training metric {'Train/mean dice_metric': 0.9940810203552246, 'Train/mean miou_metric': 0.9879755973815918, 'Train/mean f1': 0.9900409579277039, 'Train/mean precision': 0.9854504466056824, 'Train/mean recall': 0.9946743845939636, 'Train/mean hd95_metric': 1.1803284883499146} +Epoch [1298/4000] Validation [1/4] Loss: 0.27657 focal_loss 0.19866 dice_loss 0.07792 +Epoch [1298/4000] Validation [2/4] Loss: 0.34869 focal_loss 0.17816 dice_loss 0.17053 +Epoch [1298/4000] Validation [3/4] Loss: 0.25943 focal_loss 0.16989 dice_loss 0.08955 +Epoch [1298/4000] Validation [4/4] Loss: 0.36279 focal_loss 0.22803 dice_loss 0.13476 +Epoch [1298/4000] Validation metric {'Val/mean dice_metric': 0.970197319984436, 'Val/mean miou_metric': 0.9519051313400269, 'Val/mean f1': 0.9711386561393738, 'Val/mean precision': 0.9688957333564758, 'Val/mean recall': 0.9733918905258179, 'Val/mean hd95_metric': 5.877013683319092} +Cheakpoint... +Epoch [1298/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970197319984436, 'Val/mean miou_metric': 0.9519051313400269, 'Val/mean f1': 0.9711386561393738, 'Val/mean precision': 0.9688957333564758, 'Val/mean recall': 0.9733918905258179, 'Val/mean hd95_metric': 5.877013683319092} +Epoch [1299/4000] Training [1/16] Loss: 0.00964 +Epoch [1299/4000] Training [2/16] Loss: 0.00959 +Epoch [1299/4000] Training [3/16] Loss: 0.00916 +Epoch [1299/4000] Training [4/16] Loss: 0.00742 +Epoch [1299/4000] Training [5/16] Loss: 0.00924 +Epoch [1299/4000] Training [6/16] Loss: 0.00753 +Epoch [1299/4000] Training [7/16] Loss: 0.01143 +Epoch [1299/4000] Training [8/16] Loss: 0.00977 +Epoch [1299/4000] Training [9/16] Loss: 0.00780 +Epoch [1299/4000] Training [10/16] Loss: 0.00732 +Epoch [1299/4000] Training [11/16] Loss: 0.00935 +Epoch [1299/4000] Training [12/16] Loss: 0.01550 +Epoch [1299/4000] Training [13/16] Loss: 0.00857 +Epoch [1299/4000] Training [14/16] Loss: 0.00672 +Epoch [1299/4000] Training [15/16] Loss: 0.01045 +Epoch [1299/4000] Training [16/16] Loss: 0.00886 +Epoch [1299/4000] Training metric {'Train/mean dice_metric': 0.9938162565231323, 'Train/mean miou_metric': 0.9874703884124756, 'Train/mean f1': 0.9900877475738525, 'Train/mean precision': 0.9855484366416931, 'Train/mean recall': 0.9946690797805786, 'Train/mean hd95_metric': 1.0557464361190796} +Epoch [1299/4000] Validation [1/4] Loss: 0.15812 focal_loss 0.10131 dice_loss 0.05681 +Epoch [1299/4000] Validation [2/4] Loss: 0.22593 focal_loss 0.11435 dice_loss 0.11158 +Epoch [1299/4000] Validation [3/4] Loss: 0.20806 focal_loss 0.11821 dice_loss 0.08985 +Epoch [1299/4000] Validation [4/4] Loss: 0.20057 focal_loss 0.10841 dice_loss 0.09216 +Epoch [1299/4000] Validation metric {'Val/mean dice_metric': 0.9697281122207642, 'Val/mean miou_metric': 0.9519069790840149, 'Val/mean f1': 0.9723618626594543, 'Val/mean precision': 0.9678462743759155, 'Val/mean recall': 0.9769197702407837, 'Val/mean hd95_metric': 5.576954364776611} +Cheakpoint... +Epoch [1299/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697281122207642, 'Val/mean miou_metric': 0.9519069790840149, 'Val/mean f1': 0.9723618626594543, 'Val/mean precision': 0.9678462743759155, 'Val/mean recall': 0.9769197702407837, 'Val/mean hd95_metric': 5.576954364776611} +Epoch [1300/4000] Training [1/16] Loss: 0.00843 +Epoch [1300/4000] Training [2/16] Loss: 0.00808 +Epoch [1300/4000] Training [3/16] Loss: 0.01192 +Epoch [1300/4000] Training [4/16] Loss: 0.00913 +Epoch [1300/4000] Training [5/16] Loss: 0.01079 +Epoch [1300/4000] Training [6/16] Loss: 0.00861 +Epoch [1300/4000] Training [7/16] Loss: 0.00837 +Epoch [1300/4000] Training [8/16] Loss: 0.00876 +Epoch [1300/4000] Training [9/16] Loss: 0.00855 +Epoch [1300/4000] Training [10/16] Loss: 0.00863 +Epoch [1300/4000] Training [11/16] Loss: 0.00977 +Epoch [1300/4000] Training [12/16] Loss: 0.00852 +Epoch [1300/4000] Training [13/16] Loss: 0.01146 +Epoch [1300/4000] Training [14/16] Loss: 0.00662 +Epoch [1300/4000] Training [15/16] Loss: 0.01192 +Epoch [1300/4000] Training [16/16] Loss: 0.01186 +Epoch [1300/4000] Training metric {'Train/mean dice_metric': 0.993719220161438, 'Train/mean miou_metric': 0.9872725009918213, 'Train/mean f1': 0.9899386763572693, 'Train/mean precision': 0.9854094386100769, 'Train/mean recall': 0.9945096373558044, 'Train/mean hd95_metric': 1.0562832355499268} +Epoch [1300/4000] Validation [1/4] Loss: 0.18718 focal_loss 0.12384 dice_loss 0.06335 +Epoch [1300/4000] Validation [2/4] Loss: 0.24171 focal_loss 0.10692 dice_loss 0.13479 +Epoch [1300/4000] Validation [3/4] Loss: 0.29592 focal_loss 0.19368 dice_loss 0.10224 +Epoch [1300/4000] Validation [4/4] Loss: 0.20242 focal_loss 0.10847 dice_loss 0.09395 +Epoch [1300/4000] Validation metric {'Val/mean dice_metric': 0.9694644808769226, 'Val/mean miou_metric': 0.9511442184448242, 'Val/mean f1': 0.9715181589126587, 'Val/mean precision': 0.9659009575843811, 'Val/mean recall': 0.9772011637687683, 'Val/mean hd95_metric': 6.035094261169434} +Cheakpoint... +Epoch [1300/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694644808769226, 'Val/mean miou_metric': 0.9511442184448242, 'Val/mean f1': 0.9715181589126587, 'Val/mean precision': 0.9659009575843811, 'Val/mean recall': 0.9772011637687683, 'Val/mean hd95_metric': 6.035094261169434} +Epoch [1301/4000] Training [1/16] Loss: 0.00913 +Epoch [1301/4000] Training [2/16] Loss: 0.00825 +Epoch [1301/4000] Training [3/16] Loss: 0.01060 +Epoch [1301/4000] Training [4/16] Loss: 0.00689 +Epoch [1301/4000] Training [5/16] Loss: 0.00990 +Epoch [1301/4000] Training [6/16] Loss: 0.00963 +Epoch [1301/4000] Training [7/16] Loss: 0.00880 +Epoch [1301/4000] Training [8/16] Loss: 0.00864 +Epoch [1301/4000] Training [9/16] Loss: 0.00933 +Epoch [1301/4000] Training [10/16] Loss: 0.00974 +Epoch [1301/4000] Training [11/16] Loss: 0.00965 +Epoch [1301/4000] Training [12/16] Loss: 0.01114 +Epoch [1301/4000] Training [13/16] Loss: 0.01010 +Epoch [1301/4000] Training [14/16] Loss: 0.00927 +Epoch [1301/4000] Training [15/16] Loss: 0.01232 +Epoch [1301/4000] Training [16/16] Loss: 0.00858 +Epoch [1301/4000] Training metric {'Train/mean dice_metric': 0.9931530952453613, 'Train/mean miou_metric': 0.9861568212509155, 'Train/mean f1': 0.989353597164154, 'Train/mean precision': 0.9847484230995178, 'Train/mean recall': 0.994002103805542, 'Train/mean hd95_metric': 1.217775821685791} +Epoch [1301/4000] Validation [1/4] Loss: 0.22497 focal_loss 0.15996 dice_loss 0.06501 +Epoch [1301/4000] Validation [2/4] Loss: 0.33225 focal_loss 0.18114 dice_loss 0.15111 +Epoch [1301/4000] Validation [3/4] Loss: 0.21865 focal_loss 0.12352 dice_loss 0.09513 +Epoch [1301/4000] Validation [4/4] Loss: 0.29030 focal_loss 0.16086 dice_loss 0.12945 +Epoch [1301/4000] Validation metric {'Val/mean dice_metric': 0.9688254594802856, 'Val/mean miou_metric': 0.9505435824394226, 'Val/mean f1': 0.9725910425186157, 'Val/mean precision': 0.9691283106803894, 'Val/mean recall': 0.9760785102844238, 'Val/mean hd95_metric': 5.579208850860596} +Cheakpoint... +Epoch [1301/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688254594802856, 'Val/mean miou_metric': 0.9505435824394226, 'Val/mean f1': 0.9725910425186157, 'Val/mean precision': 0.9691283106803894, 'Val/mean recall': 0.9760785102844238, 'Val/mean hd95_metric': 5.579208850860596} +Epoch [1302/4000] Training [1/16] Loss: 0.01141 +Epoch [1302/4000] Training [2/16] Loss: 0.00860 +Epoch [1302/4000] Training [3/16] Loss: 0.01048 +Epoch [1302/4000] Training [4/16] Loss: 0.01345 +Epoch [1302/4000] Training [5/16] Loss: 0.00974 +Epoch [1302/4000] Training [6/16] Loss: 0.00966 +Epoch [1302/4000] Training [7/16] Loss: 0.00982 +Epoch [1302/4000] Training [8/16] Loss: 0.00880 +Epoch [1302/4000] Training [9/16] Loss: 0.00827 +Epoch [1302/4000] Training [10/16] Loss: 0.01049 +Epoch [1302/4000] Training [11/16] Loss: 0.00763 +Epoch [1302/4000] Training [12/16] Loss: 0.01145 +Epoch [1302/4000] Training [13/16] Loss: 0.01071 +Epoch [1302/4000] Training [14/16] Loss: 0.01007 +Epoch [1302/4000] Training [15/16] Loss: 0.01029 +Epoch [1302/4000] Training [16/16] Loss: 0.00857 +Epoch [1302/4000] Training metric {'Train/mean dice_metric': 0.9932920932769775, 'Train/mean miou_metric': 0.9864186644554138, 'Train/mean f1': 0.9893966317176819, 'Train/mean precision': 0.9844996929168701, 'Train/mean recall': 0.9943424463272095, 'Train/mean hd95_metric': 1.0775680541992188} +Epoch [1302/4000] Validation [1/4] Loss: 0.60778 focal_loss 0.48439 dice_loss 0.12340 +Epoch [1302/4000] Validation [2/4] Loss: 0.33640 focal_loss 0.20986 dice_loss 0.12654 +Epoch [1302/4000] Validation [3/4] Loss: 0.21527 focal_loss 0.11963 dice_loss 0.09564 +Epoch [1302/4000] Validation [4/4] Loss: 0.25950 focal_loss 0.15742 dice_loss 0.10208 +Epoch [1302/4000] Validation metric {'Val/mean dice_metric': 0.9675758481025696, 'Val/mean miou_metric': 0.9486290812492371, 'Val/mean f1': 0.9690767526626587, 'Val/mean precision': 0.9696046710014343, 'Val/mean recall': 0.9685493111610413, 'Val/mean hd95_metric': 5.578558921813965} +Cheakpoint... +Epoch [1302/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675758481025696, 'Val/mean miou_metric': 0.9486290812492371, 'Val/mean f1': 0.9690767526626587, 'Val/mean precision': 0.9696046710014343, 'Val/mean recall': 0.9685493111610413, 'Val/mean hd95_metric': 5.578558921813965} +Epoch [1303/4000] Training [1/16] Loss: 0.01262 +Epoch [1303/4000] Training [2/16] Loss: 0.00837 +Epoch [1303/4000] Training [3/16] Loss: 0.01329 +Epoch [1303/4000] Training [4/16] Loss: 0.00826 +Epoch [1303/4000] Training [5/16] Loss: 0.00717 +Epoch [1303/4000] Training [6/16] Loss: 0.01245 +Epoch [1303/4000] Training [7/16] Loss: 0.00791 +Epoch [1303/4000] Training [8/16] Loss: 0.00807 +Epoch [1303/4000] Training [9/16] Loss: 0.00774 +Epoch [1303/4000] Training [10/16] Loss: 0.01012 +Epoch [1303/4000] Training [11/16] Loss: 0.00719 +Epoch [1303/4000] Training [12/16] Loss: 0.00842 +Epoch [1303/4000] Training [13/16] Loss: 0.00798 +Epoch [1303/4000] Training [14/16] Loss: 0.00789 +Epoch [1303/4000] Training [15/16] Loss: 0.00845 +Epoch [1303/4000] Training [16/16] Loss: 0.00963 +Epoch [1303/4000] Training metric {'Train/mean dice_metric': 0.9933620691299438, 'Train/mean miou_metric': 0.9865818023681641, 'Train/mean f1': 0.9898021817207336, 'Train/mean precision': 0.9852303266525269, 'Train/mean recall': 0.9944166541099548, 'Train/mean hd95_metric': 1.1164175271987915} +Epoch [1303/4000] Validation [1/4] Loss: 0.37980 focal_loss 0.28324 dice_loss 0.09656 +Epoch [1303/4000] Validation [2/4] Loss: 0.34221 focal_loss 0.18842 dice_loss 0.15379 +Epoch [1303/4000] Validation [3/4] Loss: 0.22852 focal_loss 0.12787 dice_loss 0.10064 +Epoch [1303/4000] Validation [4/4] Loss: 0.24939 focal_loss 0.13872 dice_loss 0.11068 +Epoch [1303/4000] Validation metric {'Val/mean dice_metric': 0.968036949634552, 'Val/mean miou_metric': 0.9494997262954712, 'Val/mean f1': 0.9716156721115112, 'Val/mean precision': 0.9687834978103638, 'Val/mean recall': 0.9744643568992615, 'Val/mean hd95_metric': 5.811437129974365} +Cheakpoint... +Epoch [1303/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968036949634552, 'Val/mean miou_metric': 0.9494997262954712, 'Val/mean f1': 0.9716156721115112, 'Val/mean precision': 0.9687834978103638, 'Val/mean recall': 0.9744643568992615, 'Val/mean hd95_metric': 5.811437129974365} +Epoch [1304/4000] Training [1/16] Loss: 0.00863 +Epoch [1304/4000] Training [2/16] Loss: 0.00861 +Epoch [1304/4000] Training [3/16] Loss: 0.00969 +Epoch [1304/4000] Training [4/16] Loss: 0.00942 +Epoch [1304/4000] Training [5/16] Loss: 0.00915 +Epoch [1304/4000] Training [6/16] Loss: 0.00998 +Epoch [1304/4000] Training [7/16] Loss: 0.01016 +Epoch [1304/4000] Training [8/16] Loss: 0.01738 +Epoch [1304/4000] Training [9/16] Loss: 0.01315 +Epoch [1304/4000] Training [10/16] Loss: 0.00629 +Epoch [1304/4000] Training [11/16] Loss: 0.00883 +Epoch [1304/4000] Training [12/16] Loss: 0.00960 +Epoch [1304/4000] Training [13/16] Loss: 0.00929 +Epoch [1304/4000] Training [14/16] Loss: 0.00836 +Epoch [1304/4000] Training [15/16] Loss: 0.00733 +Epoch [1304/4000] Training [16/16] Loss: 0.01341 +Epoch [1304/4000] Training metric {'Train/mean dice_metric': 0.9930331707000732, 'Train/mean miou_metric': 0.9859124422073364, 'Train/mean f1': 0.9888441562652588, 'Train/mean precision': 0.98347407579422, 'Train/mean recall': 0.9942733645439148, 'Train/mean hd95_metric': 1.1708407402038574} +Epoch [1304/4000] Validation [1/4] Loss: 0.18782 focal_loss 0.12266 dice_loss 0.06516 +Epoch [1304/4000] Validation [2/4] Loss: 0.25816 focal_loss 0.13318 dice_loss 0.12499 +Epoch [1304/4000] Validation [3/4] Loss: 0.22533 focal_loss 0.13012 dice_loss 0.09522 +Epoch [1304/4000] Validation [4/4] Loss: 0.16708 focal_loss 0.08123 dice_loss 0.08585 +Epoch [1304/4000] Validation metric {'Val/mean dice_metric': 0.9704330563545227, 'Val/mean miou_metric': 0.951464056968689, 'Val/mean f1': 0.9722115397453308, 'Val/mean precision': 0.9657135605812073, 'Val/mean recall': 0.9787974953651428, 'Val/mean hd95_metric': 5.8874077796936035} +Cheakpoint... +Epoch [1304/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704330563545227, 'Val/mean miou_metric': 0.951464056968689, 'Val/mean f1': 0.9722115397453308, 'Val/mean precision': 0.9657135605812073, 'Val/mean recall': 0.9787974953651428, 'Val/mean hd95_metric': 5.8874077796936035} +Epoch [1305/4000] Training [1/16] Loss: 0.00789 +Epoch [1305/4000] Training [2/16] Loss: 0.00897 +Epoch [1305/4000] Training [3/16] Loss: 0.00879 +Epoch [1305/4000] Training [4/16] Loss: 0.00655 +Epoch [1305/4000] Training [5/16] Loss: 0.00848 +Epoch [1305/4000] Training [6/16] Loss: 0.01272 +Epoch [1305/4000] Training [7/16] Loss: 0.00868 +Epoch [1305/4000] Training [8/16] Loss: 0.01215 +Epoch [1305/4000] Training [9/16] Loss: 0.00820 +Epoch [1305/4000] Training [10/16] Loss: 0.00763 +Epoch [1305/4000] Training [11/16] Loss: 0.00766 +Epoch [1305/4000] Training [12/16] Loss: 0.00881 +Epoch [1305/4000] Training [13/16] Loss: 0.01018 +Epoch [1305/4000] Training [14/16] Loss: 0.01039 +Epoch [1305/4000] Training [15/16] Loss: 0.00947 +Epoch [1305/4000] Training [16/16] Loss: 0.01069 +Epoch [1305/4000] Training metric {'Train/mean dice_metric': 0.9937770366668701, 'Train/mean miou_metric': 0.9873911142349243, 'Train/mean f1': 0.9900757074356079, 'Train/mean precision': 0.985725462436676, 'Train/mean recall': 0.9944645166397095, 'Train/mean hd95_metric': 1.0534175634384155} +Epoch [1305/4000] Validation [1/4] Loss: 0.22238 focal_loss 0.15836 dice_loss 0.06402 +Epoch [1305/4000] Validation [2/4] Loss: 0.26718 focal_loss 0.13662 dice_loss 0.13056 +Epoch [1305/4000] Validation [3/4] Loss: 0.31979 focal_loss 0.20358 dice_loss 0.11622 +Epoch [1305/4000] Validation [4/4] Loss: 0.22222 focal_loss 0.12004 dice_loss 0.10218 +Epoch [1305/4000] Validation metric {'Val/mean dice_metric': 0.9692608118057251, 'Val/mean miou_metric': 0.9511154294013977, 'Val/mean f1': 0.9721187949180603, 'Val/mean precision': 0.9702390432357788, 'Val/mean recall': 0.9740056991577148, 'Val/mean hd95_metric': 5.505647659301758} +Cheakpoint... +Epoch [1305/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692608118057251, 'Val/mean miou_metric': 0.9511154294013977, 'Val/mean f1': 0.9721187949180603, 'Val/mean precision': 0.9702390432357788, 'Val/mean recall': 0.9740056991577148, 'Val/mean hd95_metric': 5.505647659301758} +Epoch [1306/4000] Training [1/16] Loss: 0.00827 +Epoch [1306/4000] Training [2/16] Loss: 0.00843 +Epoch [1306/4000] Training [3/16] Loss: 0.00778 +Epoch [1306/4000] Training [4/16] Loss: 0.01098 +Epoch [1306/4000] Training [5/16] Loss: 0.01126 +Epoch [1306/4000] Training [6/16] Loss: 0.00835 +Epoch [1306/4000] Training [7/16] Loss: 0.00795 +Epoch [1306/4000] Training [8/16] Loss: 0.00973 +Epoch [1306/4000] Training [9/16] Loss: 0.00607 +Epoch [1306/4000] Training [10/16] Loss: 0.01017 +Epoch [1306/4000] Training [11/16] Loss: 0.01336 +Epoch [1306/4000] Training [12/16] Loss: 0.00920 +Epoch [1306/4000] Training [13/16] Loss: 0.01370 +Epoch [1306/4000] Training [14/16] Loss: 0.01126 +Epoch [1306/4000] Training [15/16] Loss: 0.00993 +Epoch [1306/4000] Training [16/16] Loss: 0.00751 +Epoch [1306/4000] Training metric {'Train/mean dice_metric': 0.9933902621269226, 'Train/mean miou_metric': 0.9866139888763428, 'Train/mean f1': 0.9895898699760437, 'Train/mean precision': 0.9850088357925415, 'Train/mean recall': 0.9942136406898499, 'Train/mean hd95_metric': 1.05144202709198} +Epoch [1306/4000] Validation [1/4] Loss: 0.22765 focal_loss 0.16150 dice_loss 0.06615 +Epoch [1306/4000] Validation [2/4] Loss: 0.32633 focal_loss 0.17764 dice_loss 0.14869 +Epoch [1306/4000] Validation [3/4] Loss: 0.26842 focal_loss 0.16379 dice_loss 0.10463 +Epoch [1306/4000] Validation [4/4] Loss: 0.28744 focal_loss 0.15887 dice_loss 0.12857 +Epoch [1306/4000] Validation metric {'Val/mean dice_metric': 0.9699047207832336, 'Val/mean miou_metric': 0.9513245820999146, 'Val/mean f1': 0.9727869033813477, 'Val/mean precision': 0.9679123163223267, 'Val/mean recall': 0.9777109026908875, 'Val/mean hd95_metric': 5.521708965301514} +Cheakpoint... +Epoch [1306/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699047207832336, 'Val/mean miou_metric': 0.9513245820999146, 'Val/mean f1': 0.9727869033813477, 'Val/mean precision': 0.9679123163223267, 'Val/mean recall': 0.9777109026908875, 'Val/mean hd95_metric': 5.521708965301514} +Epoch [1307/4000] Training [1/16] Loss: 0.00716 +Epoch [1307/4000] Training [2/16] Loss: 0.00989 +Epoch [1307/4000] Training [3/16] Loss: 0.00879 +Epoch [1307/4000] Training [4/16] Loss: 0.01092 +Epoch [1307/4000] Training [5/16] Loss: 0.01023 +Epoch [1307/4000] Training [6/16] Loss: 0.00692 +Epoch [1307/4000] Training [7/16] Loss: 0.00906 +Epoch [1307/4000] Training [8/16] Loss: 0.00941 +Epoch [1307/4000] Training [9/16] Loss: 0.01056 +Epoch [1307/4000] Training [10/16] Loss: 0.00773 +Epoch [1307/4000] Training [11/16] Loss: 0.01018 +Epoch [1307/4000] Training [12/16] Loss: 0.01044 +Epoch [1307/4000] Training [13/16] Loss: 0.00899 +Epoch [1307/4000] Training [14/16] Loss: 0.00979 +Epoch [1307/4000] Training [15/16] Loss: 0.01143 +Epoch [1307/4000] Training [16/16] Loss: 0.01604 +Epoch [1307/4000] Training metric {'Train/mean dice_metric': 0.9929431676864624, 'Train/mean miou_metric': 0.9858965277671814, 'Train/mean f1': 0.9894821643829346, 'Train/mean precision': 0.9847413301467896, 'Train/mean recall': 0.9942687749862671, 'Train/mean hd95_metric': 1.3630045652389526} +Epoch [1307/4000] Validation [1/4] Loss: 0.22667 focal_loss 0.16292 dice_loss 0.06374 +Epoch [1307/4000] Validation [2/4] Loss: 0.58563 focal_loss 0.35668 dice_loss 0.22895 +Epoch [1307/4000] Validation [3/4] Loss: 0.36812 focal_loss 0.24570 dice_loss 0.12243 +Epoch [1307/4000] Validation [4/4] Loss: 0.24208 focal_loss 0.13684 dice_loss 0.10523 +Epoch [1307/4000] Validation metric {'Val/mean dice_metric': 0.9675613641738892, 'Val/mean miou_metric': 0.9492398500442505, 'Val/mean f1': 0.9710257649421692, 'Val/mean precision': 0.9638639092445374, 'Val/mean recall': 0.9782949090003967, 'Val/mean hd95_metric': 6.660121917724609} +Cheakpoint... +Epoch [1307/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675613641738892, 'Val/mean miou_metric': 0.9492398500442505, 'Val/mean f1': 0.9710257649421692, 'Val/mean precision': 0.9638639092445374, 'Val/mean recall': 0.9782949090003967, 'Val/mean hd95_metric': 6.660121917724609} +Epoch [1308/4000] Training [1/16] Loss: 0.00844 +Epoch [1308/4000] Training [2/16] Loss: 0.00923 +Epoch [1308/4000] Training [3/16] Loss: 0.00710 +Epoch [1308/4000] Training [4/16] Loss: 0.01057 +Epoch [1308/4000] Training [5/16] Loss: 0.01473 +Epoch [1308/4000] Training [6/16] Loss: 0.00809 +Epoch [1308/4000] Training [7/16] Loss: 0.00916 +Epoch [1308/4000] Training [8/16] Loss: 0.00843 +Epoch [1308/4000] Training [9/16] Loss: 0.01066 +Epoch [1308/4000] Training [10/16] Loss: 0.00807 +Epoch [1308/4000] Training [11/16] Loss: 0.00936 +Epoch [1308/4000] Training [12/16] Loss: 0.00921 +Epoch [1308/4000] Training [13/16] Loss: 0.01301 +Epoch [1308/4000] Training [14/16] Loss: 0.00843 +Epoch [1308/4000] Training [15/16] Loss: 0.00933 +Epoch [1308/4000] Training [16/16] Loss: 0.01207 +Epoch [1308/4000] Training metric {'Train/mean dice_metric': 0.9934444427490234, 'Train/mean miou_metric': 0.9866917729377747, 'Train/mean f1': 0.9885626435279846, 'Train/mean precision': 0.9831414818763733, 'Train/mean recall': 0.9940438866615295, 'Train/mean hd95_metric': 1.1577517986297607} +Epoch [1308/4000] Validation [1/4] Loss: 0.26129 focal_loss 0.18217 dice_loss 0.07912 +Epoch [1308/4000] Validation [2/4] Loss: 0.41825 focal_loss 0.25618 dice_loss 0.16207 +Epoch [1308/4000] Validation [3/4] Loss: 0.17397 focal_loss 0.11099 dice_loss 0.06298 +Epoch [1308/4000] Validation [4/4] Loss: 0.35559 focal_loss 0.22467 dice_loss 0.13092 +Epoch [1308/4000] Validation metric {'Val/mean dice_metric': 0.9691240191459656, 'Val/mean miou_metric': 0.9505739212036133, 'Val/mean f1': 0.9707678556442261, 'Val/mean precision': 0.9682602882385254, 'Val/mean recall': 0.9732885360717773, 'Val/mean hd95_metric': 5.604962348937988} +Cheakpoint... +Epoch [1308/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691240191459656, 'Val/mean miou_metric': 0.9505739212036133, 'Val/mean f1': 0.9707678556442261, 'Val/mean precision': 0.9682602882385254, 'Val/mean recall': 0.9732885360717773, 'Val/mean hd95_metric': 5.604962348937988} +Epoch [1309/4000] Training [1/16] Loss: 0.00867 +Epoch [1309/4000] Training [2/16] Loss: 0.00905 +Epoch [1309/4000] Training [3/16] Loss: 0.00791 +Epoch [1309/4000] Training [4/16] Loss: 0.00988 +Epoch [1309/4000] Training [5/16] Loss: 0.01163 +Epoch [1309/4000] Training [6/16] Loss: 0.00819 +Epoch [1309/4000] Training [7/16] Loss: 0.01170 +Epoch [1309/4000] Training [8/16] Loss: 0.00916 +Epoch [1309/4000] Training [9/16] Loss: 0.01137 +Epoch [1309/4000] Training [10/16] Loss: 0.01006 +Epoch [1309/4000] Training [11/16] Loss: 0.01011 +Epoch [1309/4000] Training [12/16] Loss: 0.01065 +Epoch [1309/4000] Training [13/16] Loss: 0.00781 +Epoch [1309/4000] Training [14/16] Loss: 0.00963 +Epoch [1309/4000] Training [15/16] Loss: 0.00970 +Epoch [1309/4000] Training [16/16] Loss: 0.01226 +Epoch [1309/4000] Training metric {'Train/mean dice_metric': 0.9931159019470215, 'Train/mean miou_metric': 0.9860920906066895, 'Train/mean f1': 0.9893141388893127, 'Train/mean precision': 0.9848860502243042, 'Train/mean recall': 0.9937821626663208, 'Train/mean hd95_metric': 1.1776467561721802} +Epoch [1309/4000] Validation [1/4] Loss: 0.19662 focal_loss 0.13884 dice_loss 0.05778 +Epoch [1309/4000] Validation [2/4] Loss: 0.34023 focal_loss 0.17591 dice_loss 0.16431 +Epoch [1309/4000] Validation [3/4] Loss: 0.38972 focal_loss 0.25954 dice_loss 0.13018 +Epoch [1309/4000] Validation [4/4] Loss: 0.41957 focal_loss 0.26986 dice_loss 0.14971 +Epoch [1309/4000] Validation metric {'Val/mean dice_metric': 0.9670614004135132, 'Val/mean miou_metric': 0.9468193054199219, 'Val/mean f1': 0.9655543565750122, 'Val/mean precision': 0.9512020945549011, 'Val/mean recall': 0.9803463220596313, 'Val/mean hd95_metric': 8.169233322143555} +Cheakpoint... +Epoch [1309/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670614004135132, 'Val/mean miou_metric': 0.9468193054199219, 'Val/mean f1': 0.9655543565750122, 'Val/mean precision': 0.9512020945549011, 'Val/mean recall': 0.9803463220596313, 'Val/mean hd95_metric': 8.169233322143555} +Epoch [1310/4000] Training [1/16] Loss: 0.00745 +Epoch [1310/4000] Training [2/16] Loss: 0.00971 +Epoch [1310/4000] Training [3/16] Loss: 0.01119 +Epoch [1310/4000] Training [4/16] Loss: 0.01368 +Epoch [1310/4000] Training [5/16] Loss: 0.01047 +Epoch [1310/4000] Training [6/16] Loss: 0.00968 +Epoch [1310/4000] Training [7/16] Loss: 0.00939 +Epoch [1310/4000] Training [8/16] Loss: 0.00926 +Epoch [1310/4000] Training [9/16] Loss: 0.00988 +Epoch [1310/4000] Training [10/16] Loss: 0.01148 +Epoch [1310/4000] Training [11/16] Loss: 0.01035 +Epoch [1310/4000] Training [12/16] Loss: 0.01130 +Epoch [1310/4000] Training [13/16] Loss: 0.00827 +Epoch [1310/4000] Training [14/16] Loss: 0.01338 +Epoch [1310/4000] Training [15/16] Loss: 0.01468 +Epoch [1310/4000] Training [16/16] Loss: 0.01465 +Epoch [1310/4000] Training metric {'Train/mean dice_metric': 0.9926259517669678, 'Train/mean miou_metric': 0.9851486682891846, 'Train/mean f1': 0.9886212348937988, 'Train/mean precision': 0.9841290712356567, 'Train/mean recall': 0.9931545257568359, 'Train/mean hd95_metric': 2.225314140319824} +Epoch [1310/4000] Validation [1/4] Loss: 0.30080 focal_loss 0.22171 dice_loss 0.07909 +Epoch [1310/4000] Validation [2/4] Loss: 0.54965 focal_loss 0.31857 dice_loss 0.23108 +Epoch [1310/4000] Validation [3/4] Loss: 0.23848 focal_loss 0.14506 dice_loss 0.09342 +Epoch [1310/4000] Validation [4/4] Loss: 0.27405 focal_loss 0.15044 dice_loss 0.12360 +Epoch [1310/4000] Validation metric {'Val/mean dice_metric': 0.9661535024642944, 'Val/mean miou_metric': 0.9461604952812195, 'Val/mean f1': 0.9692645072937012, 'Val/mean precision': 0.9660854339599609, 'Val/mean recall': 0.9724646210670471, 'Val/mean hd95_metric': 7.598332405090332} +Cheakpoint... +Epoch [1310/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661535024642944, 'Val/mean miou_metric': 0.9461604952812195, 'Val/mean f1': 0.9692645072937012, 'Val/mean precision': 0.9660854339599609, 'Val/mean recall': 0.9724646210670471, 'Val/mean hd95_metric': 7.598332405090332} +Epoch [1311/4000] Training [1/16] Loss: 0.01254 +Epoch [1311/4000] Training [2/16] Loss: 0.01205 +Epoch [1311/4000] Training [3/16] Loss: 0.01027 +Epoch [1311/4000] Training [4/16] Loss: 0.01143 +Epoch [1311/4000] Training [5/16] Loss: 0.00913 +Epoch [1311/4000] Training [6/16] Loss: 0.00989 +Epoch [1311/4000] Training [7/16] Loss: 0.00717 +Epoch [1311/4000] Training [8/16] Loss: 0.01052 +Epoch [1311/4000] Training [9/16] Loss: 0.00929 +Epoch [1311/4000] Training [10/16] Loss: 0.00938 +Epoch [1311/4000] Training [11/16] Loss: 0.00995 +Epoch [1311/4000] Training [12/16] Loss: 0.00786 +Epoch [1311/4000] Training [13/16] Loss: 0.01126 +Epoch [1311/4000] Training [14/16] Loss: 0.01231 +Epoch [1311/4000] Training [15/16] Loss: 0.01708 +Epoch [1311/4000] Training [16/16] Loss: 0.00976 +Epoch [1311/4000] Training metric {'Train/mean dice_metric': 0.9929484128952026, 'Train/mean miou_metric': 0.9857542514801025, 'Train/mean f1': 0.9889135360717773, 'Train/mean precision': 0.9841727018356323, 'Train/mean recall': 0.9937002658843994, 'Train/mean hd95_metric': 1.3342907428741455} +Epoch [1311/4000] Validation [1/4] Loss: 1.01314 focal_loss 0.86149 dice_loss 0.15165 +Epoch [1311/4000] Validation [2/4] Loss: 0.69931 focal_loss 0.38751 dice_loss 0.31180 +Epoch [1311/4000] Validation [3/4] Loss: 0.16645 focal_loss 0.10469 dice_loss 0.06176 +Epoch [1311/4000] Validation [4/4] Loss: 0.29216 focal_loss 0.15452 dice_loss 0.13764 +Epoch [1311/4000] Validation metric {'Val/mean dice_metric': 0.9597923159599304, 'Val/mean miou_metric': 0.94146728515625, 'Val/mean f1': 0.9663812518119812, 'Val/mean precision': 0.9721517562866211, 'Val/mean recall': 0.9606789946556091, 'Val/mean hd95_metric': 6.395133018493652} +Cheakpoint... +Epoch [1311/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9598], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9597923159599304, 'Val/mean miou_metric': 0.94146728515625, 'Val/mean f1': 0.9663812518119812, 'Val/mean precision': 0.9721517562866211, 'Val/mean recall': 0.9606789946556091, 'Val/mean hd95_metric': 6.395133018493652} +Epoch [1312/4000] Training [1/16] Loss: 0.01260 +Epoch [1312/4000] Training [2/16] Loss: 0.00999 +Epoch [1312/4000] Training [3/16] Loss: 0.00912 +Epoch [1312/4000] Training [4/16] Loss: 0.01035 +Epoch [1312/4000] Training [5/16] Loss: 0.00976 +Epoch [1312/4000] Training [6/16] Loss: 0.00968 +Epoch [1312/4000] Training [7/16] Loss: 0.01058 +Epoch [1312/4000] Training [8/16] Loss: 0.01159 +Epoch [1312/4000] Training [9/16] Loss: 0.01127 +Epoch [1312/4000] Training [10/16] Loss: 0.00846 +Epoch [1312/4000] Training [11/16] Loss: 0.01144 +Epoch [1312/4000] Training [12/16] Loss: 0.01089 +Epoch [1312/4000] Training [13/16] Loss: 0.00881 +Epoch [1312/4000] Training [14/16] Loss: 0.00931 +Epoch [1312/4000] Training [15/16] Loss: 0.00975 +Epoch [1312/4000] Training [16/16] Loss: 0.01067 +Epoch [1312/4000] Training metric {'Train/mean dice_metric': 0.9928358793258667, 'Train/mean miou_metric': 0.9855577349662781, 'Train/mean f1': 0.9891502261161804, 'Train/mean precision': 0.9845082759857178, 'Train/mean recall': 0.9938361644744873, 'Train/mean hd95_metric': 1.4028592109680176} +Epoch [1312/4000] Validation [1/4] Loss: 0.34340 focal_loss 0.23470 dice_loss 0.10871 +Epoch [1312/4000] Validation [2/4] Loss: 0.33499 focal_loss 0.15738 dice_loss 0.17762 +Epoch [1312/4000] Validation [3/4] Loss: 0.12941 focal_loss 0.07425 dice_loss 0.05517 +Epoch [1312/4000] Validation [4/4] Loss: 0.17872 focal_loss 0.07852 dice_loss 0.10020 +Epoch [1312/4000] Validation metric {'Val/mean dice_metric': 0.967249870300293, 'Val/mean miou_metric': 0.9480093121528625, 'Val/mean f1': 0.9696105718612671, 'Val/mean precision': 0.9684504866600037, 'Val/mean recall': 0.9707735180854797, 'Val/mean hd95_metric': 6.590190887451172} +Cheakpoint... +Epoch [1312/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967249870300293, 'Val/mean miou_metric': 0.9480093121528625, 'Val/mean f1': 0.9696105718612671, 'Val/mean precision': 0.9684504866600037, 'Val/mean recall': 0.9707735180854797, 'Val/mean hd95_metric': 6.590190887451172} +Epoch [1313/4000] Training [1/16] Loss: 0.01192 +Epoch [1313/4000] Training [2/16] Loss: 0.00921 +Epoch [1313/4000] Training [3/16] Loss: 0.00972 +Epoch [1313/4000] Training [4/16] Loss: 0.01046 +Epoch [1313/4000] Training [5/16] Loss: 0.00835 +Epoch [1313/4000] Training [6/16] Loss: 0.00879 +Epoch [1313/4000] Training [7/16] Loss: 0.00936 +Epoch [1313/4000] Training [8/16] Loss: 0.00791 +Epoch [1313/4000] Training [9/16] Loss: 0.01015 +Epoch [1313/4000] Training [10/16] Loss: 0.00804 +Epoch [1313/4000] Training [11/16] Loss: 0.00886 +Epoch [1313/4000] Training [12/16] Loss: 0.00974 +Epoch [1313/4000] Training [13/16] Loss: 0.00916 +Epoch [1313/4000] Training [14/16] Loss: 0.00845 +Epoch [1313/4000] Training [15/16] Loss: 0.00873 +Epoch [1313/4000] Training [16/16] Loss: 0.01589 +Epoch [1313/4000] Training metric {'Train/mean dice_metric': 0.9938558340072632, 'Train/mean miou_metric': 0.9875056147575378, 'Train/mean f1': 0.9890060424804688, 'Train/mean precision': 0.9836639761924744, 'Train/mean recall': 0.9944064021110535, 'Train/mean hd95_metric': 1.1216845512390137} +Epoch [1313/4000] Validation [1/4] Loss: 0.79729 focal_loss 0.64829 dice_loss 0.14900 +Epoch [1313/4000] Validation [2/4] Loss: 0.35715 focal_loss 0.18055 dice_loss 0.17660 +Epoch [1313/4000] Validation [3/4] Loss: 0.19740 focal_loss 0.11070 dice_loss 0.08670 +Epoch [1313/4000] Validation [4/4] Loss: 0.25311 focal_loss 0.14543 dice_loss 0.10768 +Epoch [1313/4000] Validation metric {'Val/mean dice_metric': 0.9675253629684448, 'Val/mean miou_metric': 0.9490150213241577, 'Val/mean f1': 0.9693191051483154, 'Val/mean precision': 0.97029048204422, 'Val/mean recall': 0.9683497548103333, 'Val/mean hd95_metric': 6.338424205780029} +Cheakpoint... +Epoch [1313/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675253629684448, 'Val/mean miou_metric': 0.9490150213241577, 'Val/mean f1': 0.9693191051483154, 'Val/mean precision': 0.97029048204422, 'Val/mean recall': 0.9683497548103333, 'Val/mean hd95_metric': 6.338424205780029} +Epoch [1314/4000] Training [1/16] Loss: 0.01134 +Epoch [1314/4000] Training [2/16] Loss: 0.00967 +Epoch [1314/4000] Training [3/16] Loss: 0.00989 +Epoch [1314/4000] Training [4/16] Loss: 0.00787 +Epoch [1314/4000] Training [5/16] Loss: 0.00638 +Epoch [1314/4000] Training [6/16] Loss: 0.00893 +Epoch [1314/4000] Training [7/16] Loss: 0.01232 +Epoch [1314/4000] Training [8/16] Loss: 0.01050 +Epoch [1314/4000] Training [9/16] Loss: 0.00860 +Epoch [1314/4000] Training [10/16] Loss: 0.00825 +Epoch [1314/4000] Training [11/16] Loss: 0.01045 +Epoch [1314/4000] Training [12/16] Loss: 0.00719 +Epoch [1314/4000] Training [13/16] Loss: 0.00902 +Epoch [1314/4000] Training [14/16] Loss: 0.01107 +Epoch [1314/4000] Training [15/16] Loss: 0.01274 +Epoch [1314/4000] Training [16/16] Loss: 0.00973 +Epoch [1314/4000] Training metric {'Train/mean dice_metric': 0.9937161207199097, 'Train/mean miou_metric': 0.9872682094573975, 'Train/mean f1': 0.9898301959037781, 'Train/mean precision': 0.9854433536529541, 'Train/mean recall': 0.994256317615509, 'Train/mean hd95_metric': 1.6226024627685547} +Epoch [1314/4000] Validation [1/4] Loss: 0.34079 focal_loss 0.24538 dice_loss 0.09541 +Epoch [1314/4000] Validation [2/4] Loss: 0.43823 focal_loss 0.25834 dice_loss 0.17988 +Epoch [1314/4000] Validation [3/4] Loss: 0.21218 focal_loss 0.13467 dice_loss 0.07752 +Epoch [1314/4000] Validation [4/4] Loss: 0.21627 focal_loss 0.10855 dice_loss 0.10772 +Epoch [1314/4000] Validation metric {'Val/mean dice_metric': 0.968745231628418, 'Val/mean miou_metric': 0.949997067451477, 'Val/mean f1': 0.9705581068992615, 'Val/mean precision': 0.9727205634117126, 'Val/mean recall': 0.9684053063392639, 'Val/mean hd95_metric': 6.122318744659424} +Cheakpoint... +Epoch [1314/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968745231628418, 'Val/mean miou_metric': 0.949997067451477, 'Val/mean f1': 0.9705581068992615, 'Val/mean precision': 0.9727205634117126, 'Val/mean recall': 0.9684053063392639, 'Val/mean hd95_metric': 6.122318744659424} +Epoch [1315/4000] Training [1/16] Loss: 0.00953 +Epoch [1315/4000] Training [2/16] Loss: 0.00767 +Epoch [1315/4000] Training [3/16] Loss: 0.00921 +Epoch [1315/4000] Training [4/16] Loss: 0.01020 +Epoch [1315/4000] Training [5/16] Loss: 0.00852 +Epoch [1315/4000] Training [6/16] Loss: 0.00748 +Epoch [1315/4000] Training [7/16] Loss: 0.00946 +Epoch [1315/4000] Training [8/16] Loss: 0.01126 +Epoch [1315/4000] Training [9/16] Loss: 0.01088 +Epoch [1315/4000] Training [10/16] Loss: 0.00662 +Epoch [1315/4000] Training [11/16] Loss: 0.01279 +Epoch [1315/4000] Training [12/16] Loss: 0.00868 +Epoch [1315/4000] Training [13/16] Loss: 0.00932 +Epoch [1315/4000] Training [14/16] Loss: 0.00861 +Epoch [1315/4000] Training [15/16] Loss: 0.00904 +Epoch [1315/4000] Training [16/16] Loss: 0.00858 +Epoch [1315/4000] Training metric {'Train/mean dice_metric': 0.993743360042572, 'Train/mean miou_metric': 0.9873210191726685, 'Train/mean f1': 0.9897116422653198, 'Train/mean precision': 0.9851909279823303, 'Train/mean recall': 0.9942740201950073, 'Train/mean hd95_metric': 1.1402448415756226} +Epoch [1315/4000] Validation [1/4] Loss: 0.24109 focal_loss 0.16846 dice_loss 0.07263 +Epoch [1315/4000] Validation [2/4] Loss: 0.26436 focal_loss 0.13917 dice_loss 0.12519 +Epoch [1315/4000] Validation [3/4] Loss: 0.13318 focal_loss 0.07485 dice_loss 0.05833 +Epoch [1315/4000] Validation [4/4] Loss: 0.25765 focal_loss 0.14340 dice_loss 0.11424 +Epoch [1315/4000] Validation metric {'Val/mean dice_metric': 0.9729898571968079, 'Val/mean miou_metric': 0.9547439813613892, 'Val/mean f1': 0.9736993312835693, 'Val/mean precision': 0.9726005792617798, 'Val/mean recall': 0.9748006463050842, 'Val/mean hd95_metric': 5.089901924133301} +Cheakpoint... +Epoch [1315/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729898571968079, 'Val/mean miou_metric': 0.9547439813613892, 'Val/mean f1': 0.9736993312835693, 'Val/mean precision': 0.9726005792617798, 'Val/mean recall': 0.9748006463050842, 'Val/mean hd95_metric': 5.089901924133301} +Epoch [1316/4000] Training [1/16] Loss: 0.01154 +Epoch [1316/4000] Training [2/16] Loss: 0.00977 +Epoch [1316/4000] Training [3/16] Loss: 0.00801 +Epoch [1316/4000] Training [4/16] Loss: 0.00718 +Epoch [1316/4000] Training [5/16] Loss: 0.00628 +Epoch [1316/4000] Training [6/16] Loss: 0.00969 +Epoch [1316/4000] Training [7/16] Loss: 0.00731 +Epoch [1316/4000] Training [8/16] Loss: 0.00715 +Epoch [1316/4000] Training [9/16] Loss: 0.00829 +Epoch [1316/4000] Training [10/16] Loss: 0.00765 +Epoch [1316/4000] Training [11/16] Loss: 0.00904 +Epoch [1316/4000] Training [12/16] Loss: 0.00663 +Epoch [1316/4000] Training [13/16] Loss: 0.00913 +Epoch [1316/4000] Training [14/16] Loss: 0.00688 +Epoch [1316/4000] Training [15/16] Loss: 0.01421 +Epoch [1316/4000] Training [16/16] Loss: 0.00859 +Epoch [1316/4000] Training metric {'Train/mean dice_metric': 0.9940909743309021, 'Train/mean miou_metric': 0.9879865646362305, 'Train/mean f1': 0.989930272102356, 'Train/mean precision': 0.9849737882614136, 'Train/mean recall': 0.9949368834495544, 'Train/mean hd95_metric': 1.044994592666626} +Epoch [1316/4000] Validation [1/4] Loss: 0.36333 focal_loss 0.24998 dice_loss 0.11334 +Epoch [1316/4000] Validation [2/4] Loss: 0.42253 focal_loss 0.23719 dice_loss 0.18534 +Epoch [1316/4000] Validation [3/4] Loss: 0.16685 focal_loss 0.10205 dice_loss 0.06480 +Epoch [1316/4000] Validation [4/4] Loss: 0.32498 focal_loss 0.20147 dice_loss 0.12351 +Epoch [1316/4000] Validation metric {'Val/mean dice_metric': 0.9710111618041992, 'Val/mean miou_metric': 0.9525080919265747, 'Val/mean f1': 0.972876787185669, 'Val/mean precision': 0.9714733958244324, 'Val/mean recall': 0.9742841124534607, 'Val/mean hd95_metric': 5.3647236824035645} +Cheakpoint... +Epoch [1316/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710111618041992, 'Val/mean miou_metric': 0.9525080919265747, 'Val/mean f1': 0.972876787185669, 'Val/mean precision': 0.9714733958244324, 'Val/mean recall': 0.9742841124534607, 'Val/mean hd95_metric': 5.3647236824035645} +Epoch [1317/4000] Training [1/16] Loss: 0.00955 +Epoch [1317/4000] Training [2/16] Loss: 0.00707 +Epoch [1317/4000] Training [3/16] Loss: 0.01082 +Epoch [1317/4000] Training [4/16] Loss: 0.00832 +Epoch [1317/4000] Training [5/16] Loss: 0.01172 +Epoch [1317/4000] Training [6/16] Loss: 0.00892 +Epoch [1317/4000] Training [7/16] Loss: 0.00782 +Epoch [1317/4000] Training [8/16] Loss: 0.00748 +Epoch [1317/4000] Training [9/16] Loss: 0.01016 +Epoch [1317/4000] Training [10/16] Loss: 0.01041 +Epoch [1317/4000] Training [11/16] Loss: 0.00903 +Epoch [1317/4000] Training [12/16] Loss: 0.00909 +Epoch [1317/4000] Training [13/16] Loss: 0.00896 +Epoch [1317/4000] Training [14/16] Loss: 0.00684 +Epoch [1317/4000] Training [15/16] Loss: 0.00783 +Epoch [1317/4000] Training [16/16] Loss: 0.00653 +Epoch [1317/4000] Training metric {'Train/mean dice_metric': 0.9939789772033691, 'Train/mean miou_metric': 0.9877808690071106, 'Train/mean f1': 0.9900386929512024, 'Train/mean precision': 0.9853844046592712, 'Train/mean recall': 0.9947371482849121, 'Train/mean hd95_metric': 1.086552619934082} +Epoch [1317/4000] Validation [1/4] Loss: 0.59731 focal_loss 0.45527 dice_loss 0.14204 +Epoch [1317/4000] Validation [2/4] Loss: 0.49902 focal_loss 0.30001 dice_loss 0.19900 +Epoch [1317/4000] Validation [3/4] Loss: 0.27250 focal_loss 0.17755 dice_loss 0.09495 +Epoch [1317/4000] Validation [4/4] Loss: 0.27565 focal_loss 0.16810 dice_loss 0.10755 +Epoch [1317/4000] Validation metric {'Val/mean dice_metric': 0.9705212712287903, 'Val/mean miou_metric': 0.9527271389961243, 'Val/mean f1': 0.97098708152771, 'Val/mean precision': 0.9721390008926392, 'Val/mean recall': 0.9698379635810852, 'Val/mean hd95_metric': 5.609518051147461} +Cheakpoint... +Epoch [1317/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705212712287903, 'Val/mean miou_metric': 0.9527271389961243, 'Val/mean f1': 0.97098708152771, 'Val/mean precision': 0.9721390008926392, 'Val/mean recall': 0.9698379635810852, 'Val/mean hd95_metric': 5.609518051147461} +Epoch [1318/4000] Training [1/16] Loss: 0.00993 +Epoch [1318/4000] Training [2/16] Loss: 0.01067 +Epoch [1318/4000] Training [3/16] Loss: 0.00836 +Epoch [1318/4000] Training [4/16] Loss: 0.00953 +Epoch [1318/4000] Training [5/16] Loss: 0.00728 +Epoch [1318/4000] Training [6/16] Loss: 0.01022 +Epoch [1318/4000] Training [7/16] Loss: 0.00856 +Epoch [1318/4000] Training [8/16] Loss: 0.01212 +Epoch [1318/4000] Training [9/16] Loss: 0.00790 +Epoch [1318/4000] Training [10/16] Loss: 0.00767 +Epoch [1318/4000] Training [11/16] Loss: 0.00805 +Epoch [1318/4000] Training [12/16] Loss: 0.00734 +Epoch [1318/4000] Training [13/16] Loss: 0.00678 +Epoch [1318/4000] Training [14/16] Loss: 0.00857 +Epoch [1318/4000] Training [15/16] Loss: 0.01082 +Epoch [1318/4000] Training [16/16] Loss: 0.00878 +Epoch [1318/4000] Training metric {'Train/mean dice_metric': 0.9939508438110352, 'Train/mean miou_metric': 0.9877048134803772, 'Train/mean f1': 0.9895142316818237, 'Train/mean precision': 0.9844977855682373, 'Train/mean recall': 0.9945822358131409, 'Train/mean hd95_metric': 1.0693035125732422} +Epoch [1318/4000] Validation [1/4] Loss: 0.16862 focal_loss 0.11547 dice_loss 0.05314 +Epoch [1318/4000] Validation [2/4] Loss: 0.39998 focal_loss 0.20315 dice_loss 0.19683 +Epoch [1318/4000] Validation [3/4] Loss: 0.14164 focal_loss 0.08161 dice_loss 0.06003 +Epoch [1318/4000] Validation [4/4] Loss: 0.25670 focal_loss 0.13437 dice_loss 0.12233 +Epoch [1318/4000] Validation metric {'Val/mean dice_metric': 0.9721294641494751, 'Val/mean miou_metric': 0.95428466796875, 'Val/mean f1': 0.9729017615318298, 'Val/mean precision': 0.9690380096435547, 'Val/mean recall': 0.9767963886260986, 'Val/mean hd95_metric': 5.312993049621582} +Cheakpoint... +Epoch [1318/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721294641494751, 'Val/mean miou_metric': 0.95428466796875, 'Val/mean f1': 0.9729017615318298, 'Val/mean precision': 0.9690380096435547, 'Val/mean recall': 0.9767963886260986, 'Val/mean hd95_metric': 5.312993049621582} +Epoch [1319/4000] Training [1/16] Loss: 0.00845 +Epoch [1319/4000] Training [2/16] Loss: 0.00964 +Epoch [1319/4000] Training [3/16] Loss: 0.00723 +Epoch [1319/4000] Training [4/16] Loss: 0.00719 +Epoch [1319/4000] Training [5/16] Loss: 0.00840 +Epoch [1319/4000] Training [6/16] Loss: 0.01033 +Epoch [1319/4000] Training [7/16] Loss: 0.00820 +Epoch [1319/4000] Training [8/16] Loss: 0.00773 +Epoch [1319/4000] Training [9/16] Loss: 0.00828 +Epoch [1319/4000] Training [10/16] Loss: 0.01123 +Epoch [1319/4000] Training [11/16] Loss: 0.00917 +Epoch [1319/4000] Training [12/16] Loss: 0.00955 +Epoch [1319/4000] Training [13/16] Loss: 0.01111 +Epoch [1319/4000] Training [14/16] Loss: 0.00803 +Epoch [1319/4000] Training [15/16] Loss: 0.00842 +Epoch [1319/4000] Training [16/16] Loss: 0.00914 +Epoch [1319/4000] Training metric {'Train/mean dice_metric': 0.9938586354255676, 'Train/mean miou_metric': 0.987545371055603, 'Train/mean f1': 0.9899806380271912, 'Train/mean precision': 0.9855127334594727, 'Train/mean recall': 0.9944891929626465, 'Train/mean hd95_metric': 1.0478172302246094} +Epoch [1319/4000] Validation [1/4] Loss: 0.53211 focal_loss 0.42181 dice_loss 0.11030 +Epoch [1319/4000] Validation [2/4] Loss: 0.60505 focal_loss 0.37189 dice_loss 0.23315 +Epoch [1319/4000] Validation [3/4] Loss: 0.28055 focal_loss 0.18262 dice_loss 0.09793 +Epoch [1319/4000] Validation [4/4] Loss: 0.18423 focal_loss 0.09659 dice_loss 0.08764 +Epoch [1319/4000] Validation metric {'Val/mean dice_metric': 0.9690302014350891, 'Val/mean miou_metric': 0.950626015663147, 'Val/mean f1': 0.9707831144332886, 'Val/mean precision': 0.9688491821289062, 'Val/mean recall': 0.9727246165275574, 'Val/mean hd95_metric': 5.771973609924316} +Cheakpoint... +Epoch [1319/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690302014350891, 'Val/mean miou_metric': 0.950626015663147, 'Val/mean f1': 0.9707831144332886, 'Val/mean precision': 0.9688491821289062, 'Val/mean recall': 0.9727246165275574, 'Val/mean hd95_metric': 5.771973609924316} +Epoch [1320/4000] Training [1/16] Loss: 0.00682 +Epoch [1320/4000] Training [2/16] Loss: 0.00958 +Epoch [1320/4000] Training [3/16] Loss: 0.00907 +Epoch [1320/4000] Training [4/16] Loss: 0.00809 +Epoch [1320/4000] Training [5/16] Loss: 0.00821 +Epoch [1320/4000] Training [6/16] Loss: 0.00982 +Epoch [1320/4000] Training [7/16] Loss: 0.00892 +Epoch [1320/4000] Training [8/16] Loss: 0.00851 +Epoch [1320/4000] Training [9/16] Loss: 0.00957 +Epoch [1320/4000] Training [10/16] Loss: 0.01028 +Epoch [1320/4000] Training [11/16] Loss: 0.00980 +Epoch [1320/4000] Training [12/16] Loss: 0.00778 +Epoch [1320/4000] Training [13/16] Loss: 0.01496 +Epoch [1320/4000] Training [14/16] Loss: 0.00941 +Epoch [1320/4000] Training [15/16] Loss: 0.00764 +Epoch [1320/4000] Training [16/16] Loss: 0.00713 +Epoch [1320/4000] Training metric {'Train/mean dice_metric': 0.9935381412506104, 'Train/mean miou_metric': 0.9869318604469299, 'Train/mean f1': 0.98958820104599, 'Train/mean precision': 0.9850268363952637, 'Train/mean recall': 0.9941920042037964, 'Train/mean hd95_metric': 1.1375597715377808} +Epoch [1320/4000] Validation [1/4] Loss: 0.16461 focal_loss 0.10507 dice_loss 0.05954 +Epoch [1320/4000] Validation [2/4] Loss: 0.23353 focal_loss 0.12533 dice_loss 0.10820 +Epoch [1320/4000] Validation [3/4] Loss: 0.27190 focal_loss 0.18046 dice_loss 0.09144 +Epoch [1320/4000] Validation [4/4] Loss: 0.27042 focal_loss 0.15725 dice_loss 0.11318 +Epoch [1320/4000] Validation metric {'Val/mean dice_metric': 0.9707170724868774, 'Val/mean miou_metric': 0.9520247578620911, 'Val/mean f1': 0.9711269736289978, 'Val/mean precision': 0.9630805253982544, 'Val/mean recall': 0.9793089628219604, 'Val/mean hd95_metric': 6.26818323135376} +Cheakpoint... +Epoch [1320/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707170724868774, 'Val/mean miou_metric': 0.9520247578620911, 'Val/mean f1': 0.9711269736289978, 'Val/mean precision': 0.9630805253982544, 'Val/mean recall': 0.9793089628219604, 'Val/mean hd95_metric': 6.26818323135376} +Epoch [1321/4000] Training [1/16] Loss: 0.01111 +Epoch [1321/4000] Training [2/16] Loss: 0.01100 +Epoch [1321/4000] Training [3/16] Loss: 0.01447 +Epoch [1321/4000] Training [4/16] Loss: 0.01065 +Epoch [1321/4000] Training [5/16] Loss: 0.00735 +Epoch [1321/4000] Training [6/16] Loss: 0.01125 +Epoch [1321/4000] Training [7/16] Loss: 0.00993 +Epoch [1321/4000] Training [8/16] Loss: 0.00795 +Epoch [1321/4000] Training [9/16] Loss: 0.01121 +Epoch [1321/4000] Training [10/16] Loss: 0.01175 +Epoch [1321/4000] Training [11/16] Loss: 0.00972 +Epoch [1321/4000] Training [12/16] Loss: 0.00810 +Epoch [1321/4000] Training [13/16] Loss: 0.00807 +Epoch [1321/4000] Training [14/16] Loss: 0.00948 +Epoch [1321/4000] Training [15/16] Loss: 0.01390 +Epoch [1321/4000] Training [16/16] Loss: 0.00997 +Epoch [1321/4000] Training metric {'Train/mean dice_metric': 0.9930199384689331, 'Train/mean miou_metric': 0.9859013557434082, 'Train/mean f1': 0.9893653392791748, 'Train/mean precision': 0.9849809408187866, 'Train/mean recall': 0.9937889575958252, 'Train/mean hd95_metric': 1.4196897745132446} +Epoch [1321/4000] Validation [1/4] Loss: 0.27431 focal_loss 0.18760 dice_loss 0.08670 +Epoch [1321/4000] Validation [2/4] Loss: 0.38780 focal_loss 0.21061 dice_loss 0.17719 +Epoch [1321/4000] Validation [3/4] Loss: 0.16613 focal_loss 0.09101 dice_loss 0.07511 +Epoch [1321/4000] Validation [4/4] Loss: 0.33201 focal_loss 0.19947 dice_loss 0.13254 +Epoch [1321/4000] Validation metric {'Val/mean dice_metric': 0.968213677406311, 'Val/mean miou_metric': 0.9487655758857727, 'Val/mean f1': 0.970799446105957, 'Val/mean precision': 0.9685764908790588, 'Val/mean recall': 0.9730327725410461, 'Val/mean hd95_metric': 6.444802284240723} +Cheakpoint... +Epoch [1321/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968213677406311, 'Val/mean miou_metric': 0.9487655758857727, 'Val/mean f1': 0.970799446105957, 'Val/mean precision': 0.9685764908790588, 'Val/mean recall': 0.9730327725410461, 'Val/mean hd95_metric': 6.444802284240723} +Epoch [1322/4000] Training [1/16] Loss: 0.00915 +Epoch [1322/4000] Training [2/16] Loss: 0.01162 +Epoch [1322/4000] Training [3/16] Loss: 0.00816 +Epoch [1322/4000] Training [4/16] Loss: 0.01165 +Epoch [1322/4000] Training [5/16] Loss: 0.00982 +Epoch [1322/4000] Training [6/16] Loss: 0.01075 +Epoch [1322/4000] Training [7/16] Loss: 0.00890 +Epoch [1322/4000] Training [8/16] Loss: 0.01110 +Epoch [1322/4000] Training [9/16] Loss: 0.01265 +Epoch [1322/4000] Training [10/16] Loss: 0.01284 +Epoch [1322/4000] Training [11/16] Loss: 0.01110 +Epoch [1322/4000] Training [12/16] Loss: 0.00758 +Epoch [1322/4000] Training [13/16] Loss: 0.00985 +Epoch [1322/4000] Training [14/16] Loss: 0.01240 +Epoch [1322/4000] Training [15/16] Loss: 0.01109 +Epoch [1322/4000] Training [16/16] Loss: 0.01265 +Epoch [1322/4000] Training metric {'Train/mean dice_metric': 0.9926658868789673, 'Train/mean miou_metric': 0.9852274060249329, 'Train/mean f1': 0.9882784485816956, 'Train/mean precision': 0.9836719036102295, 'Train/mean recall': 0.9929284453392029, 'Train/mean hd95_metric': 1.4389863014221191} +Epoch [1322/4000] Validation [1/4] Loss: 1.20756 focal_loss 1.00847 dice_loss 0.19908 +Epoch [1322/4000] Validation [2/4] Loss: 0.22800 focal_loss 0.12532 dice_loss 0.10268 +Epoch [1322/4000] Validation [3/4] Loss: 0.25419 focal_loss 0.15844 dice_loss 0.09574 +Epoch [1322/4000] Validation [4/4] Loss: 0.35988 focal_loss 0.22576 dice_loss 0.13412 +Epoch [1322/4000] Validation metric {'Val/mean dice_metric': 0.962868869304657, 'Val/mean miou_metric': 0.942919135093689, 'Val/mean f1': 0.9618159532546997, 'Val/mean precision': 0.9538134932518005, 'Val/mean recall': 0.9699539542198181, 'Val/mean hd95_metric': 9.311192512512207} +Cheakpoint... +Epoch [1322/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9629], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.962868869304657, 'Val/mean miou_metric': 0.942919135093689, 'Val/mean f1': 0.9618159532546997, 'Val/mean precision': 0.9538134932518005, 'Val/mean recall': 0.9699539542198181, 'Val/mean hd95_metric': 9.311192512512207} +Epoch [1323/4000] Training [1/16] Loss: 0.01070 +Epoch [1323/4000] Training [2/16] Loss: 0.01510 +Epoch [1323/4000] Training [3/16] Loss: 0.00951 +Epoch [1323/4000] Training [4/16] Loss: 0.01059 +Epoch [1323/4000] Training [5/16] Loss: 0.00847 +Epoch [1323/4000] Training [6/16] Loss: 0.00781 +Epoch [1323/4000] Training [7/16] Loss: 0.00688 +Epoch [1323/4000] Training [8/16] Loss: 0.01267 +Epoch [1323/4000] Training [9/16] Loss: 0.00956 +Epoch [1323/4000] Training [10/16] Loss: 0.01305 +Epoch [1323/4000] Training [11/16] Loss: 0.01415 +Epoch [1323/4000] Training [12/16] Loss: 0.00919 +Epoch [1323/4000] Training [13/16] Loss: 0.01219 +Epoch [1323/4000] Training [14/16] Loss: 0.01010 +Epoch [1323/4000] Training [15/16] Loss: 0.00753 +Epoch [1323/4000] Training [16/16] Loss: 0.01984 +Epoch [1323/4000] Training metric {'Train/mean dice_metric': 0.9925664663314819, 'Train/mean miou_metric': 0.9850285053253174, 'Train/mean f1': 0.98887038230896, 'Train/mean precision': 0.9843382239341736, 'Train/mean recall': 0.9934445023536682, 'Train/mean hd95_metric': 2.0263776779174805} +Epoch [1323/4000] Validation [1/4] Loss: 0.20285 focal_loss 0.13083 dice_loss 0.07201 +Epoch [1323/4000] Validation [2/4] Loss: 0.26456 focal_loss 0.11808 dice_loss 0.14648 +Epoch [1323/4000] Validation [3/4] Loss: 0.29334 focal_loss 0.18595 dice_loss 0.10739 +Epoch [1323/4000] Validation [4/4] Loss: 0.34930 focal_loss 0.21164 dice_loss 0.13765 +Epoch [1323/4000] Validation metric {'Val/mean dice_metric': 0.9691146016120911, 'Val/mean miou_metric': 0.9495776891708374, 'Val/mean f1': 0.9703502058982849, 'Val/mean precision': 0.9655545949935913, 'Val/mean recall': 0.9751935601234436, 'Val/mean hd95_metric': 6.8142523765563965} +Cheakpoint... +Epoch [1323/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691146016120911, 'Val/mean miou_metric': 0.9495776891708374, 'Val/mean f1': 0.9703502058982849, 'Val/mean precision': 0.9655545949935913, 'Val/mean recall': 0.9751935601234436, 'Val/mean hd95_metric': 6.8142523765563965} +Epoch [1324/4000] Training [1/16] Loss: 0.00838 +Epoch [1324/4000] Training [2/16] Loss: 0.01231 +Epoch [1324/4000] Training [3/16] Loss: 0.01178 +Epoch [1324/4000] Training [4/16] Loss: 0.01166 +Epoch [1324/4000] Training [5/16] Loss: 0.00959 +Epoch [1324/4000] Training [6/16] Loss: 0.01119 +Epoch [1324/4000] Training [7/16] Loss: 0.01267 +Epoch [1324/4000] Training [8/16] Loss: 0.01092 +Epoch [1324/4000] Training [9/16] Loss: 0.00736 +Epoch [1324/4000] Training [10/16] Loss: 0.00699 +Epoch [1324/4000] Training [11/16] Loss: 0.00635 +Epoch [1324/4000] Training [12/16] Loss: 0.01095 +Epoch [1324/4000] Training [13/16] Loss: 0.00851 +Epoch [1324/4000] Training [14/16] Loss: 0.00812 +Epoch [1324/4000] Training [15/16] Loss: 0.00920 +Epoch [1324/4000] Training [16/16] Loss: 0.00778 +Epoch [1324/4000] Training metric {'Train/mean dice_metric': 0.9936347007751465, 'Train/mean miou_metric': 0.9871124029159546, 'Train/mean f1': 0.9896539449691772, 'Train/mean precision': 0.9849810600280762, 'Train/mean recall': 0.9943712949752808, 'Train/mean hd95_metric': 1.2270276546478271} +Epoch [1324/4000] Validation [1/4] Loss: 0.19289 focal_loss 0.12432 dice_loss 0.06856 +Epoch [1324/4000] Validation [2/4] Loss: 0.42392 focal_loss 0.22648 dice_loss 0.19744 +Epoch [1324/4000] Validation [3/4] Loss: 0.22037 focal_loss 0.13686 dice_loss 0.08351 +Epoch [1324/4000] Validation [4/4] Loss: 0.25102 focal_loss 0.13503 dice_loss 0.11599 +Epoch [1324/4000] Validation metric {'Val/mean dice_metric': 0.9694897532463074, 'Val/mean miou_metric': 0.9506545066833496, 'Val/mean f1': 0.9700674414634705, 'Val/mean precision': 0.9613125920295715, 'Val/mean recall': 0.9789831638336182, 'Val/mean hd95_metric': 6.149562358856201} +Cheakpoint... +Epoch [1324/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694897532463074, 'Val/mean miou_metric': 0.9506545066833496, 'Val/mean f1': 0.9700674414634705, 'Val/mean precision': 0.9613125920295715, 'Val/mean recall': 0.9789831638336182, 'Val/mean hd95_metric': 6.149562358856201} +Epoch [1325/4000] Training [1/16] Loss: 0.01045 +Epoch [1325/4000] Training [2/16] Loss: 0.00777 +Epoch [1325/4000] Training [3/16] Loss: 0.01018 +Epoch [1325/4000] Training [4/16] Loss: 0.01339 +Epoch [1325/4000] Training [5/16] Loss: 0.00998 +Epoch [1325/4000] Training [6/16] Loss: 0.01051 +Epoch [1325/4000] Training [7/16] Loss: 0.00719 +Epoch [1325/4000] Training [8/16] Loss: 0.00917 +Epoch [1325/4000] Training [9/16] Loss: 0.00689 +Epoch [1325/4000] Training [10/16] Loss: 0.01026 +Epoch [1325/4000] Training [11/16] Loss: 0.00883 +Epoch [1325/4000] Training [12/16] Loss: 0.01037 +Epoch [1325/4000] Training [13/16] Loss: 0.00755 +Epoch [1325/4000] Training [14/16] Loss: 0.00879 +Epoch [1325/4000] Training [15/16] Loss: 0.00901 +Epoch [1325/4000] Training [16/16] Loss: 0.11829 +Epoch [1325/4000] Training metric {'Train/mean dice_metric': 0.9926092624664307, 'Train/mean miou_metric': 0.9854492545127869, 'Train/mean f1': 0.9878236651420593, 'Train/mean precision': 0.9814997315406799, 'Train/mean recall': 0.9942295551300049, 'Train/mean hd95_metric': 1.2481955289840698} +Epoch [1325/4000] Validation [1/4] Loss: 0.18420 focal_loss 0.11895 dice_loss 0.06525 +Epoch [1325/4000] Validation [2/4] Loss: 0.38077 focal_loss 0.18921 dice_loss 0.19155 +Epoch [1325/4000] Validation [3/4] Loss: 0.15660 focal_loss 0.09115 dice_loss 0.06545 +Epoch [1325/4000] Validation [4/4] Loss: 0.39888 focal_loss 0.24934 dice_loss 0.14954 +Epoch [1325/4000] Validation metric {'Val/mean dice_metric': 0.9704885482788086, 'Val/mean miou_metric': 0.9513860940933228, 'Val/mean f1': 0.9707110524177551, 'Val/mean precision': 0.9640028476715088, 'Val/mean recall': 0.9775133728981018, 'Val/mean hd95_metric': 5.6737470626831055} +Cheakpoint... +Epoch [1325/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704885482788086, 'Val/mean miou_metric': 0.9513860940933228, 'Val/mean f1': 0.9707110524177551, 'Val/mean precision': 0.9640028476715088, 'Val/mean recall': 0.9775133728981018, 'Val/mean hd95_metric': 5.6737470626831055} +Epoch [1326/4000] Training [1/16] Loss: 0.00856 +Epoch [1326/4000] Training [2/16] Loss: 0.00844 +Epoch [1326/4000] Training [3/16] Loss: 0.00871 +Epoch [1326/4000] Training [4/16] Loss: 0.00818 +Epoch [1326/4000] Training [5/16] Loss: 0.00993 +Epoch [1326/4000] Training [6/16] Loss: 0.00923 +Epoch [1326/4000] Training [7/16] Loss: 0.00839 +Epoch [1326/4000] Training [8/16] Loss: 0.01183 +Epoch [1326/4000] Training [9/16] Loss: 0.01115 +Epoch [1326/4000] Training [10/16] Loss: 0.00937 +Epoch [1326/4000] Training [11/16] Loss: 0.00816 +Epoch [1326/4000] Training [12/16] Loss: 0.00745 +Epoch [1326/4000] Training [13/16] Loss: 0.01024 +Epoch [1326/4000] Training [14/16] Loss: 0.02828 +Epoch [1326/4000] Training [15/16] Loss: 0.00877 +Epoch [1326/4000] Training [16/16] Loss: 0.01031 +Epoch [1326/4000] Training metric {'Train/mean dice_metric': 0.993053138256073, 'Train/mean miou_metric': 0.986003577709198, 'Train/mean f1': 0.9889592528343201, 'Train/mean precision': 0.9849082827568054, 'Train/mean recall': 0.9930436611175537, 'Train/mean hd95_metric': 1.6206600666046143} +Epoch [1326/4000] Validation [1/4] Loss: 0.57883 focal_loss 0.46323 dice_loss 0.11559 +Epoch [1326/4000] Validation [2/4] Loss: 0.34452 focal_loss 0.17637 dice_loss 0.16815 +Epoch [1326/4000] Validation [3/4] Loss: 0.13590 focal_loss 0.08392 dice_loss 0.05197 +Epoch [1326/4000] Validation [4/4] Loss: 0.26428 focal_loss 0.13236 dice_loss 0.13192 +Epoch [1326/4000] Validation metric {'Val/mean dice_metric': 0.9696285128593445, 'Val/mean miou_metric': 0.950644850730896, 'Val/mean f1': 0.970088541507721, 'Val/mean precision': 0.9687838554382324, 'Val/mean recall': 0.9713966846466064, 'Val/mean hd95_metric': 6.038809299468994} +Cheakpoint... +Epoch [1326/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696285128593445, 'Val/mean miou_metric': 0.950644850730896, 'Val/mean f1': 0.970088541507721, 'Val/mean precision': 0.9687838554382324, 'Val/mean recall': 0.9713966846466064, 'Val/mean hd95_metric': 6.038809299468994} +Epoch [1327/4000] Training [1/16] Loss: 0.00868 +Epoch [1327/4000] Training [2/16] Loss: 0.00999 +Epoch [1327/4000] Training [3/16] Loss: 0.00930 +Epoch [1327/4000] Training [4/16] Loss: 0.00828 +Epoch [1327/4000] Training [5/16] Loss: 0.00756 +Epoch [1327/4000] Training [6/16] Loss: 0.00914 +Epoch [1327/4000] Training [7/16] Loss: 0.00928 +Epoch [1327/4000] Training [8/16] Loss: 0.00954 +Epoch [1327/4000] Training [9/16] Loss: 0.00978 +Epoch [1327/4000] Training [10/16] Loss: 0.01116 +Epoch [1327/4000] Training [11/16] Loss: 0.01057 +Epoch [1327/4000] Training [12/16] Loss: 0.00977 +Epoch [1327/4000] Training [13/16] Loss: 0.02190 +Epoch [1327/4000] Training [14/16] Loss: 0.00816 +Epoch [1327/4000] Training [15/16] Loss: 0.00723 +Epoch [1327/4000] Training [16/16] Loss: 0.00756 +Epoch [1327/4000] Training metric {'Train/mean dice_metric': 0.9938764572143555, 'Train/mean miou_metric': 0.9875690937042236, 'Train/mean f1': 0.9896349906921387, 'Train/mean precision': 0.9848288893699646, 'Train/mean recall': 0.9944884181022644, 'Train/mean hd95_metric': 1.2445844411849976} +Epoch [1327/4000] Validation [1/4] Loss: 0.33124 focal_loss 0.23390 dice_loss 0.09735 +Epoch [1327/4000] Validation [2/4] Loss: 0.54015 focal_loss 0.34811 dice_loss 0.19203 +Epoch [1327/4000] Validation [3/4] Loss: 0.25341 focal_loss 0.15830 dice_loss 0.09511 +Epoch [1327/4000] Validation [4/4] Loss: 0.19089 focal_loss 0.10516 dice_loss 0.08573 +Epoch [1327/4000] Validation metric {'Val/mean dice_metric': 0.971318244934082, 'Val/mean miou_metric': 0.9528785943984985, 'Val/mean f1': 0.9711424708366394, 'Val/mean precision': 0.9692800641059875, 'Val/mean recall': 0.9730122089385986, 'Val/mean hd95_metric': 5.660585880279541} +Cheakpoint... +Epoch [1327/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971318244934082, 'Val/mean miou_metric': 0.9528785943984985, 'Val/mean f1': 0.9711424708366394, 'Val/mean precision': 0.9692800641059875, 'Val/mean recall': 0.9730122089385986, 'Val/mean hd95_metric': 5.660585880279541} +Epoch [1328/4000] Training [1/16] Loss: 0.01038 +Epoch [1328/4000] Training [2/16] Loss: 0.00686 +Epoch [1328/4000] Training [3/16] Loss: 0.00765 +Epoch [1328/4000] Training [4/16] Loss: 0.00844 +Epoch [1328/4000] Training [5/16] Loss: 0.00966 +Epoch [1328/4000] Training [6/16] Loss: 0.00766 +Epoch [1328/4000] Training [7/16] Loss: 0.00981 +Epoch [1328/4000] Training [8/16] Loss: 0.00821 +Epoch [1328/4000] Training [9/16] Loss: 0.00903 +Epoch [1328/4000] Training [10/16] Loss: 0.01209 +Epoch [1328/4000] Training [11/16] Loss: 0.00986 +Epoch [1328/4000] Training [12/16] Loss: 0.01263 +Epoch [1328/4000] Training [13/16] Loss: 0.01023 +Epoch [1328/4000] Training [14/16] Loss: 0.00857 +Epoch [1328/4000] Training [15/16] Loss: 0.00961 +Epoch [1328/4000] Training [16/16] Loss: 0.01146 +Epoch [1328/4000] Training metric {'Train/mean dice_metric': 0.9931522011756897, 'Train/mean miou_metric': 0.9861855506896973, 'Train/mean f1': 0.9892686009407043, 'Train/mean precision': 0.9848718047142029, 'Train/mean recall': 0.9937047958374023, 'Train/mean hd95_metric': 1.3135600090026855} +Epoch [1328/4000] Validation [1/4] Loss: 0.23443 focal_loss 0.16018 dice_loss 0.07424 +Epoch [1328/4000] Validation [2/4] Loss: 0.56173 focal_loss 0.37562 dice_loss 0.18611 +Epoch [1328/4000] Validation [3/4] Loss: 0.15513 focal_loss 0.09815 dice_loss 0.05698 +Epoch [1328/4000] Validation [4/4] Loss: 0.36766 focal_loss 0.23221 dice_loss 0.13545 +Epoch [1328/4000] Validation metric {'Val/mean dice_metric': 0.9708870053291321, 'Val/mean miou_metric': 0.952041506767273, 'Val/mean f1': 0.9716426730155945, 'Val/mean precision': 0.970294177532196, 'Val/mean recall': 0.9729950428009033, 'Val/mean hd95_metric': 5.834064960479736} +Cheakpoint... +Epoch [1328/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708870053291321, 'Val/mean miou_metric': 0.952041506767273, 'Val/mean f1': 0.9716426730155945, 'Val/mean precision': 0.970294177532196, 'Val/mean recall': 0.9729950428009033, 'Val/mean hd95_metric': 5.834064960479736} +Epoch [1329/4000] Training [1/16] Loss: 0.00831 +Epoch [1329/4000] Training [2/16] Loss: 0.00693 +Epoch [1329/4000] Training [3/16] Loss: 0.00812 +Epoch [1329/4000] Training [4/16] Loss: 0.01495 +Epoch [1329/4000] Training [5/16] Loss: 0.00848 +Epoch [1329/4000] Training [6/16] Loss: 0.00784 +Epoch [1329/4000] Training [7/16] Loss: 0.00913 +Epoch [1329/4000] Training [8/16] Loss: 0.00959 +Epoch [1329/4000] Training [9/16] Loss: 0.00809 +Epoch [1329/4000] Training [10/16] Loss: 0.00909 +Epoch [1329/4000] Training [11/16] Loss: 0.01012 +Epoch [1329/4000] Training [12/16] Loss: 0.00786 +Epoch [1329/4000] Training [13/16] Loss: 0.01814 +Epoch [1329/4000] Training [14/16] Loss: 0.00747 +Epoch [1329/4000] Training [15/16] Loss: 0.01191 +Epoch [1329/4000] Training [16/16] Loss: 0.00800 +Epoch [1329/4000] Training metric {'Train/mean dice_metric': 0.9934430122375488, 'Train/mean miou_metric': 0.9867549538612366, 'Train/mean f1': 0.9889238476753235, 'Train/mean precision': 0.9837722778320312, 'Train/mean recall': 0.9941296577453613, 'Train/mean hd95_metric': 1.4536974430084229} +Epoch [1329/4000] Validation [1/4] Loss: 0.21391 focal_loss 0.14170 dice_loss 0.07221 +Epoch [1329/4000] Validation [2/4] Loss: 0.64160 focal_loss 0.43982 dice_loss 0.20178 +Epoch [1329/4000] Validation [3/4] Loss: 0.20526 focal_loss 0.13946 dice_loss 0.06580 +Epoch [1329/4000] Validation [4/4] Loss: 0.21833 focal_loss 0.12191 dice_loss 0.09642 +Epoch [1329/4000] Validation metric {'Val/mean dice_metric': 0.970999538898468, 'Val/mean miou_metric': 0.9526851773262024, 'Val/mean f1': 0.9729443192481995, 'Val/mean precision': 0.9707288146018982, 'Val/mean recall': 0.9751700162887573, 'Val/mean hd95_metric': 6.031120300292969} +Cheakpoint... +Epoch [1329/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970999538898468, 'Val/mean miou_metric': 0.9526851773262024, 'Val/mean f1': 0.9729443192481995, 'Val/mean precision': 0.9707288146018982, 'Val/mean recall': 0.9751700162887573, 'Val/mean hd95_metric': 6.031120300292969} +Epoch [1330/4000] Training [1/16] Loss: 0.00855 +Epoch [1330/4000] Training [2/16] Loss: 0.00739 +Epoch [1330/4000] Training [3/16] Loss: 0.01110 +Epoch [1330/4000] Training [4/16] Loss: 0.00844 +Epoch [1330/4000] Training [5/16] Loss: 0.00969 +Epoch [1330/4000] Training [6/16] Loss: 0.00789 +Epoch [1330/4000] Training [7/16] Loss: 0.00765 +Epoch [1330/4000] Training [8/16] Loss: 0.00797 +Epoch [1330/4000] Training [9/16] Loss: 0.00899 +Epoch [1330/4000] Training [10/16] Loss: 0.00937 +Epoch [1330/4000] Training [11/16] Loss: 0.00878 +Epoch [1330/4000] Training [12/16] Loss: 0.22765 +Epoch [1330/4000] Training [13/16] Loss: 0.01089 +Epoch [1330/4000] Training [14/16] Loss: 0.00982 +Epoch [1330/4000] Training [15/16] Loss: 0.01331 +Epoch [1330/4000] Training [16/16] Loss: 0.00853 +Epoch [1330/4000] Training metric {'Train/mean dice_metric': 0.9925075769424438, 'Train/mean miou_metric': 0.9854134321212769, 'Train/mean f1': 0.988531231880188, 'Train/mean precision': 0.985100269317627, 'Train/mean recall': 0.9919861555099487, 'Train/mean hd95_metric': 1.3673795461654663} +Epoch [1330/4000] Validation [1/4] Loss: 0.15333 focal_loss 0.09638 dice_loss 0.05695 +Epoch [1330/4000] Validation [2/4] Loss: 0.61129 focal_loss 0.40375 dice_loss 0.20754 +Epoch [1330/4000] Validation [3/4] Loss: 0.18558 focal_loss 0.10782 dice_loss 0.07776 +Epoch [1330/4000] Validation [4/4] Loss: 0.30206 focal_loss 0.17459 dice_loss 0.12747 +Epoch [1330/4000] Validation metric {'Val/mean dice_metric': 0.9699888229370117, 'Val/mean miou_metric': 0.9510573148727417, 'Val/mean f1': 0.9725685715675354, 'Val/mean precision': 0.9704055190086365, 'Val/mean recall': 0.9747412204742432, 'Val/mean hd95_metric': 5.684574127197266} +Cheakpoint... +Epoch [1330/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699888229370117, 'Val/mean miou_metric': 0.9510573148727417, 'Val/mean f1': 0.9725685715675354, 'Val/mean precision': 0.9704055190086365, 'Val/mean recall': 0.9747412204742432, 'Val/mean hd95_metric': 5.684574127197266} +Epoch [1331/4000] Training [1/16] Loss: 0.00897 +Epoch [1331/4000] Training [2/16] Loss: 0.01013 +Epoch [1331/4000] Training [3/16] Loss: 0.01276 +Epoch [1331/4000] Training [4/16] Loss: 0.00722 +Epoch [1331/4000] Training [5/16] Loss: 0.01039 +Epoch [1331/4000] Training [6/16] Loss: 0.01139 +Epoch [1331/4000] Training [7/16] Loss: 0.01002 +Epoch [1331/4000] Training [8/16] Loss: 0.00873 +Epoch [1331/4000] Training [9/16] Loss: 0.00836 +Epoch [1331/4000] Training [10/16] Loss: 0.00881 +Epoch [1331/4000] Training [11/16] Loss: 0.00935 +Epoch [1331/4000] Training [12/16] Loss: 0.01143 +Epoch [1331/4000] Training [13/16] Loss: 0.01051 +Epoch [1331/4000] Training [14/16] Loss: 0.00971 +Epoch [1331/4000] Training [15/16] Loss: 0.00995 +Epoch [1331/4000] Training [16/16] Loss: 0.00874 +Epoch [1331/4000] Training metric {'Train/mean dice_metric': 0.9927458167076111, 'Train/mean miou_metric': 0.9853533506393433, 'Train/mean f1': 0.9882432818412781, 'Train/mean precision': 0.9830076694488525, 'Train/mean recall': 0.9935349225997925, 'Train/mean hd95_metric': 1.3346999883651733} +Epoch [1331/4000] Validation [1/4] Loss: 0.15021 focal_loss 0.09423 dice_loss 0.05598 +Epoch [1331/4000] Validation [2/4] Loss: 0.26089 focal_loss 0.13158 dice_loss 0.12930 +Epoch [1331/4000] Validation [3/4] Loss: 0.18903 focal_loss 0.09867 dice_loss 0.09036 +Epoch [1331/4000] Validation [4/4] Loss: 0.24569 focal_loss 0.14400 dice_loss 0.10169 +Epoch [1331/4000] Validation metric {'Val/mean dice_metric': 0.9713851809501648, 'Val/mean miou_metric': 0.9520384669303894, 'Val/mean f1': 0.9714237451553345, 'Val/mean precision': 0.9649624228477478, 'Val/mean recall': 0.977972149848938, 'Val/mean hd95_metric': 6.118501663208008} +Cheakpoint... +Epoch [1331/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713851809501648, 'Val/mean miou_metric': 0.9520384669303894, 'Val/mean f1': 0.9714237451553345, 'Val/mean precision': 0.9649624228477478, 'Val/mean recall': 0.977972149848938, 'Val/mean hd95_metric': 6.118501663208008} +Epoch [1332/4000] Training [1/16] Loss: 0.01254 +Epoch [1332/4000] Training [2/16] Loss: 0.00981 +Epoch [1332/4000] Training [3/16] Loss: 0.00937 +Epoch [1332/4000] Training [4/16] Loss: 0.01042 +Epoch [1332/4000] Training [5/16] Loss: 0.00729 +Epoch [1332/4000] Training [6/16] Loss: 0.01005 +Epoch [1332/4000] Training [7/16] Loss: 0.00914 +Epoch [1332/4000] Training [8/16] Loss: 0.00772 +Epoch [1332/4000] Training [9/16] Loss: 0.00813 +Epoch [1332/4000] Training [10/16] Loss: 0.01034 +Epoch [1332/4000] Training [11/16] Loss: 0.01146 +Epoch [1332/4000] Training [12/16] Loss: 0.00776 +Epoch [1332/4000] Training [13/16] Loss: 0.00949 +Epoch [1332/4000] Training [14/16] Loss: 0.00961 +Epoch [1332/4000] Training [15/16] Loss: 0.00932 +Epoch [1332/4000] Training [16/16] Loss: 0.01114 +Epoch [1332/4000] Training metric {'Train/mean dice_metric': 0.9933844804763794, 'Train/mean miou_metric': 0.9865868091583252, 'Train/mean f1': 0.988689124584198, 'Train/mean precision': 0.9834275245666504, 'Train/mean recall': 0.9940073490142822, 'Train/mean hd95_metric': 1.2391388416290283} +Epoch [1332/4000] Validation [1/4] Loss: 0.18154 focal_loss 0.11888 dice_loss 0.06266 +Epoch [1332/4000] Validation [2/4] Loss: 0.43948 focal_loss 0.24888 dice_loss 0.19060 +Epoch [1332/4000] Validation [3/4] Loss: 0.28029 focal_loss 0.17773 dice_loss 0.10256 +Epoch [1332/4000] Validation [4/4] Loss: 0.32536 focal_loss 0.17434 dice_loss 0.15102 +Epoch [1332/4000] Validation metric {'Val/mean dice_metric': 0.967971682548523, 'Val/mean miou_metric': 0.9489538073539734, 'Val/mean f1': 0.970253050327301, 'Val/mean precision': 0.9637482762336731, 'Val/mean recall': 0.9768462181091309, 'Val/mean hd95_metric': 6.329838275909424} +Cheakpoint... +Epoch [1332/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967971682548523, 'Val/mean miou_metric': 0.9489538073539734, 'Val/mean f1': 0.970253050327301, 'Val/mean precision': 0.9637482762336731, 'Val/mean recall': 0.9768462181091309, 'Val/mean hd95_metric': 6.329838275909424} +Epoch [1333/4000] Training [1/16] Loss: 0.00953 +Epoch [1333/4000] Training [2/16] Loss: 0.00900 +Epoch [1333/4000] Training [3/16] Loss: 0.00864 +Epoch [1333/4000] Training [4/16] Loss: 0.00991 +Epoch [1333/4000] Training [5/16] Loss: 0.00710 +Epoch [1333/4000] Training [6/16] Loss: 0.00780 +Epoch [1333/4000] Training [7/16] Loss: 0.00904 +Epoch [1333/4000] Training [8/16] Loss: 0.00831 +Epoch [1333/4000] Training [9/16] Loss: 0.01294 +Epoch [1333/4000] Training [10/16] Loss: 0.01189 +Epoch [1333/4000] Training [11/16] Loss: 0.01249 +Epoch [1333/4000] Training [12/16] Loss: 0.01579 +Epoch [1333/4000] Training [13/16] Loss: 0.01000 +Epoch [1333/4000] Training [14/16] Loss: 0.00851 +Epoch [1333/4000] Training [15/16] Loss: 0.00792 +Epoch [1333/4000] Training [16/16] Loss: 0.00765 +Epoch [1333/4000] Training metric {'Train/mean dice_metric': 0.9933085441589355, 'Train/mean miou_metric': 0.9864726066589355, 'Train/mean f1': 0.9887832999229431, 'Train/mean precision': 0.9838365912437439, 'Train/mean recall': 0.9937800168991089, 'Train/mean hd95_metric': 1.2479498386383057} +Epoch [1333/4000] Validation [1/4] Loss: 0.20195 focal_loss 0.13938 dice_loss 0.06258 +Epoch [1333/4000] Validation [2/4] Loss: 0.66287 focal_loss 0.44296 dice_loss 0.21990 +Epoch [1333/4000] Validation [3/4] Loss: 0.34023 focal_loss 0.23846 dice_loss 0.10178 +Epoch [1333/4000] Validation [4/4] Loss: 0.31539 focal_loss 0.18236 dice_loss 0.13303 +Epoch [1333/4000] Validation metric {'Val/mean dice_metric': 0.9683416485786438, 'Val/mean miou_metric': 0.9495794177055359, 'Val/mean f1': 0.970583975315094, 'Val/mean precision': 0.9647285342216492, 'Val/mean recall': 0.9765108227729797, 'Val/mean hd95_metric': 6.429591178894043} +Cheakpoint... +Epoch [1333/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683416485786438, 'Val/mean miou_metric': 0.9495794177055359, 'Val/mean f1': 0.970583975315094, 'Val/mean precision': 0.9647285342216492, 'Val/mean recall': 0.9765108227729797, 'Val/mean hd95_metric': 6.429591178894043} +Epoch [1334/4000] Training [1/16] Loss: 0.00886 +Epoch [1334/4000] Training [2/16] Loss: 0.01065 +Epoch [1334/4000] Training [3/16] Loss: 0.00654 +Epoch [1334/4000] Training [4/16] Loss: 0.00857 +Epoch [1334/4000] Training [5/16] Loss: 0.00859 +Epoch [1334/4000] Training [6/16] Loss: 0.01124 +Epoch [1334/4000] Training [7/16] Loss: 0.00916 +Epoch [1334/4000] Training [8/16] Loss: 0.00888 +Epoch [1334/4000] Training [9/16] Loss: 0.00837 +Epoch [1334/4000] Training [10/16] Loss: 0.01172 +Epoch [1334/4000] Training [11/16] Loss: 0.00894 +Epoch [1334/4000] Training [12/16] Loss: 0.00782 +Epoch [1334/4000] Training [13/16] Loss: 0.00895 +Epoch [1334/4000] Training [14/16] Loss: 0.01194 +Epoch [1334/4000] Training [15/16] Loss: 0.01066 +Epoch [1334/4000] Training [16/16] Loss: 0.00863 +Epoch [1334/4000] Training metric {'Train/mean dice_metric': 0.9938311576843262, 'Train/mean miou_metric': 0.9874973297119141, 'Train/mean f1': 0.9895225167274475, 'Train/mean precision': 0.9848944544792175, 'Train/mean recall': 0.9941942691802979, 'Train/mean hd95_metric': 1.1326427459716797} +Epoch [1334/4000] Validation [1/4] Loss: 0.17397 focal_loss 0.11376 dice_loss 0.06021 +Epoch [1334/4000] Validation [2/4] Loss: 0.57968 focal_loss 0.37290 dice_loss 0.20679 +Epoch [1334/4000] Validation [3/4] Loss: 0.30373 focal_loss 0.20800 dice_loss 0.09573 +Epoch [1334/4000] Validation [4/4] Loss: 0.29576 focal_loss 0.16116 dice_loss 0.13460 +Epoch [1334/4000] Validation metric {'Val/mean dice_metric': 0.9713603258132935, 'Val/mean miou_metric': 0.9531329870223999, 'Val/mean f1': 0.9716580510139465, 'Val/mean precision': 0.965899646282196, 'Val/mean recall': 0.9774855375289917, 'Val/mean hd95_metric': 5.620813369750977} +Cheakpoint... +Epoch [1334/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713603258132935, 'Val/mean miou_metric': 0.9531329870223999, 'Val/mean f1': 0.9716580510139465, 'Val/mean precision': 0.965899646282196, 'Val/mean recall': 0.9774855375289917, 'Val/mean hd95_metric': 5.620813369750977} +Epoch [1335/4000] Training [1/16] Loss: 0.01024 +Epoch [1335/4000] Training [2/16] Loss: 0.00885 +Epoch [1335/4000] Training [3/16] Loss: 0.00722 +Epoch [1335/4000] Training [4/16] Loss: 0.00784 +Epoch [1335/4000] Training [5/16] Loss: 0.01376 +Epoch [1335/4000] Training [6/16] Loss: 0.00796 +Epoch [1335/4000] Training [7/16] Loss: 0.00701 +Epoch [1335/4000] Training [8/16] Loss: 0.00996 +Epoch [1335/4000] Training [9/16] Loss: 0.00738 +Epoch [1335/4000] Training [10/16] Loss: 0.01068 +Epoch [1335/4000] Training [11/16] Loss: 0.00862 +Epoch [1335/4000] Training [12/16] Loss: 0.00769 +Epoch [1335/4000] Training [13/16] Loss: 0.00746 +Epoch [1335/4000] Training [14/16] Loss: 0.00858 +Epoch [1335/4000] Training [15/16] Loss: 0.00733 +Epoch [1335/4000] Training [16/16] Loss: 0.00928 +Epoch [1335/4000] Training metric {'Train/mean dice_metric': 0.9939050078392029, 'Train/mean miou_metric': 0.9876469969749451, 'Train/mean f1': 0.9898658394813538, 'Train/mean precision': 0.9855639934539795, 'Train/mean recall': 0.9942053556442261, 'Train/mean hd95_metric': 1.1649163961410522} +Epoch [1335/4000] Validation [1/4] Loss: 0.16860 focal_loss 0.10676 dice_loss 0.06184 +Epoch [1335/4000] Validation [2/4] Loss: 0.57193 focal_loss 0.37650 dice_loss 0.19543 +Epoch [1335/4000] Validation [3/4] Loss: 0.27338 focal_loss 0.17102 dice_loss 0.10235 +Epoch [1335/4000] Validation [4/4] Loss: 0.26285 focal_loss 0.14736 dice_loss 0.11548 +Epoch [1335/4000] Validation metric {'Val/mean dice_metric': 0.9692090749740601, 'Val/mean miou_metric': 0.9506171941757202, 'Val/mean f1': 0.9713278412818909, 'Val/mean precision': 0.965673565864563, 'Val/mean recall': 0.9770488142967224, 'Val/mean hd95_metric': 6.258776664733887} +Cheakpoint... +Epoch [1335/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692090749740601, 'Val/mean miou_metric': 0.9506171941757202, 'Val/mean f1': 0.9713278412818909, 'Val/mean precision': 0.965673565864563, 'Val/mean recall': 0.9770488142967224, 'Val/mean hd95_metric': 6.258776664733887} +Epoch [1336/4000] Training [1/16] Loss: 0.00911 +Epoch [1336/4000] Training [2/16] Loss: 0.00789 +Epoch [1336/4000] Training [3/16] Loss: 0.01069 +Epoch [1336/4000] Training [4/16] Loss: 0.00751 +Epoch [1336/4000] Training [5/16] Loss: 0.01005 +Epoch [1336/4000] Training [6/16] Loss: 0.00837 +Epoch [1336/4000] Training [7/16] Loss: 0.01006 +Epoch [1336/4000] Training [8/16] Loss: 0.00736 +Epoch [1336/4000] Training [9/16] Loss: 0.00752 +Epoch [1336/4000] Training [10/16] Loss: 0.00860 +Epoch [1336/4000] Training [11/16] Loss: 0.00992 +Epoch [1336/4000] Training [12/16] Loss: 0.00870 +Epoch [1336/4000] Training [13/16] Loss: 0.01451 +Epoch [1336/4000] Training [14/16] Loss: 0.01008 +Epoch [1336/4000] Training [15/16] Loss: 0.00792 +Epoch [1336/4000] Training [16/16] Loss: 0.00734 +Epoch [1336/4000] Training metric {'Train/mean dice_metric': 0.9937637448310852, 'Train/mean miou_metric': 0.987368106842041, 'Train/mean f1': 0.9899052381515503, 'Train/mean precision': 0.985630989074707, 'Train/mean recall': 0.9942166805267334, 'Train/mean hd95_metric': 1.2713816165924072} +Epoch [1336/4000] Validation [1/4] Loss: 0.18305 focal_loss 0.12039 dice_loss 0.06266 +Epoch [1336/4000] Validation [2/4] Loss: 0.56117 focal_loss 0.37910 dice_loss 0.18207 +Epoch [1336/4000] Validation [3/4] Loss: 0.27118 focal_loss 0.16895 dice_loss 0.10223 +Epoch [1336/4000] Validation [4/4] Loss: 0.31875 focal_loss 0.17584 dice_loss 0.14291 +Epoch [1336/4000] Validation metric {'Val/mean dice_metric': 0.9673684239387512, 'Val/mean miou_metric': 0.9488033056259155, 'Val/mean f1': 0.9709680080413818, 'Val/mean precision': 0.9640139937400818, 'Val/mean recall': 0.9780232310295105, 'Val/mean hd95_metric': 6.7855939865112305} +Cheakpoint... +Epoch [1336/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673684239387512, 'Val/mean miou_metric': 0.9488033056259155, 'Val/mean f1': 0.9709680080413818, 'Val/mean precision': 0.9640139937400818, 'Val/mean recall': 0.9780232310295105, 'Val/mean hd95_metric': 6.7855939865112305} +Epoch [1337/4000] Training [1/16] Loss: 0.00830 +Epoch [1337/4000] Training [2/16] Loss: 0.00711 +Epoch [1337/4000] Training [3/16] Loss: 0.00988 +Epoch [1337/4000] Training [4/16] Loss: 0.00915 +Epoch [1337/4000] Training [5/16] Loss: 0.00972 +Epoch [1337/4000] Training [6/16] Loss: 0.00763 +Epoch [1337/4000] Training [7/16] Loss: 0.00812 +Epoch [1337/4000] Training [8/16] Loss: 0.00892 +Epoch [1337/4000] Training [9/16] Loss: 0.00810 +Epoch [1337/4000] Training [10/16] Loss: 0.01102 +Epoch [1337/4000] Training [11/16] Loss: 0.00885 +Epoch [1337/4000] Training [12/16] Loss: 0.00849 +Epoch [1337/4000] Training [13/16] Loss: 0.01188 +Epoch [1337/4000] Training [14/16] Loss: 0.00653 +Epoch [1337/4000] Training [15/16] Loss: 0.01134 +Epoch [1337/4000] Training [16/16] Loss: 0.00964 +Epoch [1337/4000] Training metric {'Train/mean dice_metric': 0.9939284920692444, 'Train/mean miou_metric': 0.9876980781555176, 'Train/mean f1': 0.9900688529014587, 'Train/mean precision': 0.9855179190635681, 'Train/mean recall': 0.9946618676185608, 'Train/mean hd95_metric': 1.0764156579971313} +Epoch [1337/4000] Validation [1/4] Loss: 0.19082 focal_loss 0.13203 dice_loss 0.05879 +Epoch [1337/4000] Validation [2/4] Loss: 0.70256 focal_loss 0.41107 dice_loss 0.29149 +Epoch [1337/4000] Validation [3/4] Loss: 0.25946 focal_loss 0.16448 dice_loss 0.09498 +Epoch [1337/4000] Validation [4/4] Loss: 0.32144 focal_loss 0.17988 dice_loss 0.14156 +Epoch [1337/4000] Validation metric {'Val/mean dice_metric': 0.9655208587646484, 'Val/mean miou_metric': 0.9469758868217468, 'Val/mean f1': 0.9707679748535156, 'Val/mean precision': 0.9645588397979736, 'Val/mean recall': 0.9770575165748596, 'Val/mean hd95_metric': 6.717128276824951} +Cheakpoint... +Epoch [1337/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9655], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655208587646484, 'Val/mean miou_metric': 0.9469758868217468, 'Val/mean f1': 0.9707679748535156, 'Val/mean precision': 0.9645588397979736, 'Val/mean recall': 0.9770575165748596, 'Val/mean hd95_metric': 6.717128276824951} +Epoch [1338/4000] Training [1/16] Loss: 0.00865 +Epoch [1338/4000] Training [2/16] Loss: 0.00965 +Epoch [1338/4000] Training [3/16] Loss: 0.00855 +Epoch [1338/4000] Training [4/16] Loss: 0.00770 +Epoch [1338/4000] Training [5/16] Loss: 0.01155 +Epoch [1338/4000] Training [6/16] Loss: 0.00774 +Epoch [1338/4000] Training [7/16] Loss: 0.00980 +Epoch [1338/4000] Training [8/16] Loss: 0.00671 +Epoch [1338/4000] Training [9/16] Loss: 0.00768 +Epoch [1338/4000] Training [10/16] Loss: 0.00963 +Epoch [1338/4000] Training [11/16] Loss: 0.00896 +Epoch [1338/4000] Training [12/16] Loss: 0.01022 +Epoch [1338/4000] Training [13/16] Loss: 0.01027 +Epoch [1338/4000] Training [14/16] Loss: 0.00671 +Epoch [1338/4000] Training [15/16] Loss: 0.00723 +Epoch [1338/4000] Training [16/16] Loss: 0.00982 +Epoch [1338/4000] Training metric {'Train/mean dice_metric': 0.994136393070221, 'Train/mean miou_metric': 0.988089919090271, 'Train/mean f1': 0.9903099536895752, 'Train/mean precision': 0.9857297539710999, 'Train/mean recall': 0.9949329495429993, 'Train/mean hd95_metric': 1.037644863128662} +Epoch [1338/4000] Validation [1/4] Loss: 0.17964 focal_loss 0.12357 dice_loss 0.05608 +Epoch [1338/4000] Validation [2/4] Loss: 0.57043 focal_loss 0.31853 dice_loss 0.25189 +Epoch [1338/4000] Validation [3/4] Loss: 0.26874 focal_loss 0.17363 dice_loss 0.09511 +Epoch [1338/4000] Validation [4/4] Loss: 0.25727 focal_loss 0.12861 dice_loss 0.12866 +Epoch [1338/4000] Validation metric {'Val/mean dice_metric': 0.9665502309799194, 'Val/mean miou_metric': 0.9482122659683228, 'Val/mean f1': 0.9709110260009766, 'Val/mean precision': 0.9630624651908875, 'Val/mean recall': 0.9788885712623596, 'Val/mean hd95_metric': 7.163094997406006} +Cheakpoint... +Epoch [1338/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9665502309799194, 'Val/mean miou_metric': 0.9482122659683228, 'Val/mean f1': 0.9709110260009766, 'Val/mean precision': 0.9630624651908875, 'Val/mean recall': 0.9788885712623596, 'Val/mean hd95_metric': 7.163094997406006} +Epoch [1339/4000] Training [1/16] Loss: 0.00888 +Epoch [1339/4000] Training [2/16] Loss: 0.01316 +Epoch [1339/4000] Training [3/16] Loss: 0.00769 +Epoch [1339/4000] Training [4/16] Loss: 0.00845 +Epoch [1339/4000] Training [5/16] Loss: 0.00829 +Epoch [1339/4000] Training [6/16] Loss: 0.00712 +Epoch [1339/4000] Training [7/16] Loss: 0.01157 +Epoch [1339/4000] Training [8/16] Loss: 0.00796 +Epoch [1339/4000] Training [9/16] Loss: 0.01171 +Epoch [1339/4000] Training [10/16] Loss: 0.00654 +Epoch [1339/4000] Training [11/16] Loss: 0.00895 +Epoch [1339/4000] Training [12/16] Loss: 0.00777 +Epoch [1339/4000] Training [13/16] Loss: 0.00791 +Epoch [1339/4000] Training [14/16] Loss: 0.01016 +Epoch [1339/4000] Training [15/16] Loss: 0.00842 +Epoch [1339/4000] Training [16/16] Loss: 0.01239 +Epoch [1339/4000] Training metric {'Train/mean dice_metric': 0.9935805797576904, 'Train/mean miou_metric': 0.9869620203971863, 'Train/mean f1': 0.9888097047805786, 'Train/mean precision': 0.9833706617355347, 'Train/mean recall': 0.9943091869354248, 'Train/mean hd95_metric': 1.1929110288619995} +Epoch [1339/4000] Validation [1/4] Loss: 0.22575 focal_loss 0.15903 dice_loss 0.06672 +Epoch [1339/4000] Validation [2/4] Loss: 0.47700 focal_loss 0.28946 dice_loss 0.18753 +Epoch [1339/4000] Validation [3/4] Loss: 0.20046 focal_loss 0.11538 dice_loss 0.08508 +Epoch [1339/4000] Validation [4/4] Loss: 0.24652 focal_loss 0.15332 dice_loss 0.09320 +Epoch [1339/4000] Validation metric {'Val/mean dice_metric': 0.9696029424667358, 'Val/mean miou_metric': 0.9512690305709839, 'Val/mean f1': 0.9711625576019287, 'Val/mean precision': 0.9693484306335449, 'Val/mean recall': 0.9729835391044617, 'Val/mean hd95_metric': 6.3368940353393555} +Cheakpoint... +Epoch [1339/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696029424667358, 'Val/mean miou_metric': 0.9512690305709839, 'Val/mean f1': 0.9711625576019287, 'Val/mean precision': 0.9693484306335449, 'Val/mean recall': 0.9729835391044617, 'Val/mean hd95_metric': 6.3368940353393555} +Epoch [1340/4000] Training [1/16] Loss: 0.00992 +Epoch [1340/4000] Training [2/16] Loss: 0.01002 +Epoch [1340/4000] Training [3/16] Loss: 0.00888 +Epoch [1340/4000] Training [4/16] Loss: 0.00784 +Epoch [1340/4000] Training [5/16] Loss: 0.01062 +Epoch [1340/4000] Training [6/16] Loss: 0.00643 +Epoch [1340/4000] Training [7/16] Loss: 0.00801 +Epoch [1340/4000] Training [8/16] Loss: 0.00975 +Epoch [1340/4000] Training [9/16] Loss: 0.00750 +Epoch [1340/4000] Training [10/16] Loss: 0.00812 +Epoch [1340/4000] Training [11/16] Loss: 0.00869 +Epoch [1340/4000] Training [12/16] Loss: 0.00938 +Epoch [1340/4000] Training [13/16] Loss: 0.01147 +Epoch [1340/4000] Training [14/16] Loss: 0.01194 +Epoch [1340/4000] Training [15/16] Loss: 0.00928 +Epoch [1340/4000] Training [16/16] Loss: 0.01113 +Epoch [1340/4000] Training metric {'Train/mean dice_metric': 0.9934856295585632, 'Train/mean miou_metric': 0.9868369102478027, 'Train/mean f1': 0.9893820285797119, 'Train/mean precision': 0.9844490885734558, 'Train/mean recall': 0.9943646788597107, 'Train/mean hd95_metric': 1.1624189615249634} +Epoch [1340/4000] Validation [1/4] Loss: 0.29501 focal_loss 0.20132 dice_loss 0.09369 +Epoch [1340/4000] Validation [2/4] Loss: 0.58877 focal_loss 0.34605 dice_loss 0.24272 +Epoch [1340/4000] Validation [3/4] Loss: 0.20874 focal_loss 0.11828 dice_loss 0.09046 +Epoch [1340/4000] Validation [4/4] Loss: 0.30309 focal_loss 0.18217 dice_loss 0.12092 +Epoch [1340/4000] Validation metric {'Val/mean dice_metric': 0.9666496515274048, 'Val/mean miou_metric': 0.9473119974136353, 'Val/mean f1': 0.9684919714927673, 'Val/mean precision': 0.9688812494277954, 'Val/mean recall': 0.9681030511856079, 'Val/mean hd95_metric': 6.612518787384033} +Cheakpoint... +Epoch [1340/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666496515274048, 'Val/mean miou_metric': 0.9473119974136353, 'Val/mean f1': 0.9684919714927673, 'Val/mean precision': 0.9688812494277954, 'Val/mean recall': 0.9681030511856079, 'Val/mean hd95_metric': 6.612518787384033} +Epoch [1341/4000] Training [1/16] Loss: 0.00788 +Epoch [1341/4000] Training [2/16] Loss: 0.00835 +Epoch [1341/4000] Training [3/16] Loss: 0.00840 +Epoch [1341/4000] Training [4/16] Loss: 0.00782 +Epoch [1341/4000] Training [5/16] Loss: 0.00902 +Epoch [1341/4000] Training [6/16] Loss: 0.00732 +Epoch [1341/4000] Training [7/16] Loss: 0.00753 +Epoch [1341/4000] Training [8/16] Loss: 0.00873 +Epoch [1341/4000] Training [9/16] Loss: 0.00846 +Epoch [1341/4000] Training [10/16] Loss: 0.00989 +Epoch [1341/4000] Training [11/16] Loss: 0.00988 +Epoch [1341/4000] Training [12/16] Loss: 0.00957 +Epoch [1341/4000] Training [13/16] Loss: 0.01158 +Epoch [1341/4000] Training [14/16] Loss: 0.01227 +Epoch [1341/4000] Training [15/16] Loss: 0.00853 +Epoch [1341/4000] Training [16/16] Loss: 0.01014 +Epoch [1341/4000] Training metric {'Train/mean dice_metric': 0.9940093755722046, 'Train/mean miou_metric': 0.9878435134887695, 'Train/mean f1': 0.9903783798217773, 'Train/mean precision': 0.985785961151123, 'Train/mean recall': 0.9950137734413147, 'Train/mean hd95_metric': 1.0453495979309082} +Epoch [1341/4000] Validation [1/4] Loss: 0.31490 focal_loss 0.23002 dice_loss 0.08488 +Epoch [1341/4000] Validation [2/4] Loss: 0.51609 focal_loss 0.32046 dice_loss 0.19563 +Epoch [1341/4000] Validation [3/4] Loss: 0.14985 focal_loss 0.08369 dice_loss 0.06616 +Epoch [1341/4000] Validation [4/4] Loss: 0.29925 focal_loss 0.17719 dice_loss 0.12206 +Epoch [1341/4000] Validation metric {'Val/mean dice_metric': 0.9675464630126953, 'Val/mean miou_metric': 0.9495889544487, 'Val/mean f1': 0.9709893465042114, 'Val/mean precision': 0.968911349773407, 'Val/mean recall': 0.9730762243270874, 'Val/mean hd95_metric': 6.163074016571045} +Cheakpoint... +Epoch [1341/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675464630126953, 'Val/mean miou_metric': 0.9495889544487, 'Val/mean f1': 0.9709893465042114, 'Val/mean precision': 0.968911349773407, 'Val/mean recall': 0.9730762243270874, 'Val/mean hd95_metric': 6.163074016571045} +Epoch [1342/4000] Training [1/16] Loss: 0.00984 +Epoch [1342/4000] Training [2/16] Loss: 0.00594 +Epoch [1342/4000] Training [3/16] Loss: 0.00889 +Epoch [1342/4000] Training [4/16] Loss: 0.00922 +Epoch [1342/4000] Training [5/16] Loss: 0.01142 +Epoch [1342/4000] Training [6/16] Loss: 0.01050 +Epoch [1342/4000] Training [7/16] Loss: 0.01128 +Epoch [1342/4000] Training [8/16] Loss: 0.00921 +Epoch [1342/4000] Training [9/16] Loss: 0.00978 +Epoch [1342/4000] Training [10/16] Loss: 0.01328 +Epoch [1342/4000] Training [11/16] Loss: 0.00970 +Epoch [1342/4000] Training [12/16] Loss: 0.01009 +Epoch [1342/4000] Training [13/16] Loss: 0.00852 +Epoch [1342/4000] Training [14/16] Loss: 0.01151 +Epoch [1342/4000] Training [15/16] Loss: 0.01011 +Epoch [1342/4000] Training [16/16] Loss: 0.00722 +Epoch [1342/4000] Training metric {'Train/mean dice_metric': 0.9937820434570312, 'Train/mean miou_metric': 0.9874000549316406, 'Train/mean f1': 0.9900127053260803, 'Train/mean precision': 0.9853520393371582, 'Train/mean recall': 0.9947176575660706, 'Train/mean hd95_metric': 1.069462776184082} +Epoch [1342/4000] Validation [1/4] Loss: 0.17684 focal_loss 0.11573 dice_loss 0.06110 +Epoch [1342/4000] Validation [2/4] Loss: 0.33640 focal_loss 0.16673 dice_loss 0.16966 +Epoch [1342/4000] Validation [3/4] Loss: 0.22924 focal_loss 0.13298 dice_loss 0.09626 +Epoch [1342/4000] Validation [4/4] Loss: 0.21635 focal_loss 0.12282 dice_loss 0.09353 +Epoch [1342/4000] Validation metric {'Val/mean dice_metric': 0.9701488614082336, 'Val/mean miou_metric': 0.9516881704330444, 'Val/mean f1': 0.971935510635376, 'Val/mean precision': 0.9688583016395569, 'Val/mean recall': 0.975032389163971, 'Val/mean hd95_metric': 5.756594181060791} +Cheakpoint... +Epoch [1342/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701488614082336, 'Val/mean miou_metric': 0.9516881704330444, 'Val/mean f1': 0.971935510635376, 'Val/mean precision': 0.9688583016395569, 'Val/mean recall': 0.975032389163971, 'Val/mean hd95_metric': 5.756594181060791} +Epoch [1343/4000] Training [1/16] Loss: 0.00845 +Epoch [1343/4000] Training [2/16] Loss: 0.00898 +Epoch [1343/4000] Training [3/16] Loss: 0.00649 +Epoch [1343/4000] Training [4/16] Loss: 0.01228 +Epoch [1343/4000] Training [5/16] Loss: 0.01234 +Epoch [1343/4000] Training [6/16] Loss: 0.00900 +Epoch [1343/4000] Training [7/16] Loss: 0.00912 +Epoch [1343/4000] Training [8/16] Loss: 0.01013 +Epoch [1343/4000] Training [9/16] Loss: 0.01010 +Epoch [1343/4000] Training [10/16] Loss: 0.00843 +Epoch [1343/4000] Training [11/16] Loss: 0.00700 +Epoch [1343/4000] Training [12/16] Loss: 0.00800 +Epoch [1343/4000] Training [13/16] Loss: 0.01007 +Epoch [1343/4000] Training [14/16] Loss: 0.01210 +Epoch [1343/4000] Training [15/16] Loss: 0.01050 +Epoch [1343/4000] Training [16/16] Loss: 0.00980 +Epoch [1343/4000] Training metric {'Train/mean dice_metric': 0.993550181388855, 'Train/mean miou_metric': 0.986947774887085, 'Train/mean f1': 0.9897460341453552, 'Train/mean precision': 0.9851911664009094, 'Train/mean recall': 0.9943431615829468, 'Train/mean hd95_metric': 1.115847110748291} +Epoch [1343/4000] Validation [1/4] Loss: 0.24112 focal_loss 0.16338 dice_loss 0.07773 +Epoch [1343/4000] Validation [2/4] Loss: 0.42593 focal_loss 0.25334 dice_loss 0.17260 +Epoch [1343/4000] Validation [3/4] Loss: 0.19850 focal_loss 0.11100 dice_loss 0.08750 +Epoch [1343/4000] Validation [4/4] Loss: 0.24143 focal_loss 0.14180 dice_loss 0.09963 +Epoch [1343/4000] Validation metric {'Val/mean dice_metric': 0.9671964645385742, 'Val/mean miou_metric': 0.9493572115898132, 'Val/mean f1': 0.9707541465759277, 'Val/mean precision': 0.9682627320289612, 'Val/mean recall': 0.9732585549354553, 'Val/mean hd95_metric': 6.277444839477539} +Cheakpoint... +Epoch [1343/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671964645385742, 'Val/mean miou_metric': 0.9493572115898132, 'Val/mean f1': 0.9707541465759277, 'Val/mean precision': 0.9682627320289612, 'Val/mean recall': 0.9732585549354553, 'Val/mean hd95_metric': 6.277444839477539} +Epoch [1344/4000] Training [1/16] Loss: 0.01095 +Epoch [1344/4000] Training [2/16] Loss: 0.00711 +Epoch [1344/4000] Training [3/16] Loss: 0.00776 +Epoch [1344/4000] Training [4/16] Loss: 0.00830 +Epoch [1344/4000] Training [5/16] Loss: 0.01147 +Epoch [1344/4000] Training [6/16] Loss: 0.00963 +Epoch [1344/4000] Training [7/16] Loss: 0.01123 +Epoch [1344/4000] Training [8/16] Loss: 0.00904 +Epoch [1344/4000] Training [9/16] Loss: 0.00812 +Epoch [1344/4000] Training [10/16] Loss: 0.00940 +Epoch [1344/4000] Training [11/16] Loss: 0.01044 +Epoch [1344/4000] Training [12/16] Loss: 0.01110 +Epoch [1344/4000] Training [13/16] Loss: 0.00809 +Epoch [1344/4000] Training [14/16] Loss: 0.01521 +Epoch [1344/4000] Training [15/16] Loss: 0.00981 +Epoch [1344/4000] Training [16/16] Loss: 0.00884 +Epoch [1344/4000] Training metric {'Train/mean dice_metric': 0.9937055706977844, 'Train/mean miou_metric': 0.9872475862503052, 'Train/mean f1': 0.9900229573249817, 'Train/mean precision': 0.9855980277061462, 'Train/mean recall': 0.9944877624511719, 'Train/mean hd95_metric': 1.0650732517242432} +Epoch [1344/4000] Validation [1/4] Loss: 0.30239 focal_loss 0.21595 dice_loss 0.08644 +Epoch [1344/4000] Validation [2/4] Loss: 0.69394 focal_loss 0.44451 dice_loss 0.24943 +Epoch [1344/4000] Validation [3/4] Loss: 0.22732 focal_loss 0.12929 dice_loss 0.09803 +Epoch [1344/4000] Validation [4/4] Loss: 0.20392 focal_loss 0.10407 dice_loss 0.09986 +Epoch [1344/4000] Validation metric {'Val/mean dice_metric': 0.9692453145980835, 'Val/mean miou_metric': 0.9501196146011353, 'Val/mean f1': 0.9709821939468384, 'Val/mean precision': 0.9691221117973328, 'Val/mean recall': 0.972849428653717, 'Val/mean hd95_metric': 6.055907249450684} +Cheakpoint... +Epoch [1344/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692453145980835, 'Val/mean miou_metric': 0.9501196146011353, 'Val/mean f1': 0.9709821939468384, 'Val/mean precision': 0.9691221117973328, 'Val/mean recall': 0.972849428653717, 'Val/mean hd95_metric': 6.055907249450684} +Epoch [1345/4000] Training [1/16] Loss: 0.00742 +Epoch [1345/4000] Training [2/16] Loss: 0.00652 +Epoch [1345/4000] Training [3/16] Loss: 0.01049 +Epoch [1345/4000] Training [4/16] Loss: 0.00763 +Epoch [1345/4000] Training [5/16] Loss: 0.00903 +Epoch [1345/4000] Training [6/16] Loss: 0.05345 +Epoch [1345/4000] Training [7/16] Loss: 0.00722 +Epoch [1345/4000] Training [8/16] Loss: 0.00990 +Epoch [1345/4000] Training [9/16] Loss: 0.00867 +Epoch [1345/4000] Training [10/16] Loss: 0.00869 +Epoch [1345/4000] Training [11/16] Loss: 0.01001 +Epoch [1345/4000] Training [12/16] Loss: 0.00800 +Epoch [1345/4000] Training [13/16] Loss: 0.01327 +Epoch [1345/4000] Training [14/16] Loss: 0.00869 +Epoch [1345/4000] Training [15/16] Loss: 0.00828 +Epoch [1345/4000] Training [16/16] Loss: 0.00921 +Epoch [1345/4000] Training metric {'Train/mean dice_metric': 0.9937688112258911, 'Train/mean miou_metric': 0.9873915314674377, 'Train/mean f1': 0.9895734786987305, 'Train/mean precision': 0.9852194786071777, 'Train/mean recall': 0.9939661026000977, 'Train/mean hd95_metric': 1.4632015228271484} +Epoch [1345/4000] Validation [1/4] Loss: 0.20378 focal_loss 0.14101 dice_loss 0.06277 +Epoch [1345/4000] Validation [2/4] Loss: 0.35469 focal_loss 0.18013 dice_loss 0.17456 +Epoch [1345/4000] Validation [3/4] Loss: 0.25017 focal_loss 0.15761 dice_loss 0.09256 +Epoch [1345/4000] Validation [4/4] Loss: 0.27027 focal_loss 0.14399 dice_loss 0.12628 +Epoch [1345/4000] Validation metric {'Val/mean dice_metric': 0.9704850912094116, 'Val/mean miou_metric': 0.9512136578559875, 'Val/mean f1': 0.971640944480896, 'Val/mean precision': 0.9672360420227051, 'Val/mean recall': 0.9760861396789551, 'Val/mean hd95_metric': 6.9350481033325195} +Cheakpoint... +Epoch [1345/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704850912094116, 'Val/mean miou_metric': 0.9512136578559875, 'Val/mean f1': 0.971640944480896, 'Val/mean precision': 0.9672360420227051, 'Val/mean recall': 0.9760861396789551, 'Val/mean hd95_metric': 6.9350481033325195} +Epoch [1346/4000] Training [1/16] Loss: 0.00954 +Epoch [1346/4000] Training [2/16] Loss: 0.00933 +Epoch [1346/4000] Training [3/16] Loss: 0.00977 +Epoch [1346/4000] Training [4/16] Loss: 0.01173 +Epoch [1346/4000] Training [5/16] Loss: 0.01119 +Epoch [1346/4000] Training [6/16] Loss: 0.01034 +Epoch [1346/4000] Training [7/16] Loss: 0.00677 +Epoch [1346/4000] Training [8/16] Loss: 0.00686 +Epoch [1346/4000] Training [9/16] Loss: 0.01147 +Epoch [1346/4000] Training [10/16] Loss: 0.01420 +Epoch [1346/4000] Training [11/16] Loss: 0.00949 +Epoch [1346/4000] Training [12/16] Loss: 0.00941 +Epoch [1346/4000] Training [13/16] Loss: 0.00898 +Epoch [1346/4000] Training [14/16] Loss: 0.01233 +Epoch [1346/4000] Training [15/16] Loss: 0.01138 +Epoch [1346/4000] Training [16/16] Loss: 0.01584 +Epoch [1346/4000] Training metric {'Train/mean dice_metric': 0.9925925731658936, 'Train/mean miou_metric': 0.9851776361465454, 'Train/mean f1': 0.9884552955627441, 'Train/mean precision': 0.9843051433563232, 'Train/mean recall': 0.9926406741142273, 'Train/mean hd95_metric': 1.8594295978546143} +Epoch [1346/4000] Validation [1/4] Loss: 0.21849 focal_loss 0.15883 dice_loss 0.05966 +Epoch [1346/4000] Validation [2/4] Loss: 0.56310 focal_loss 0.30899 dice_loss 0.25411 +Epoch [1346/4000] Validation [3/4] Loss: 0.35889 focal_loss 0.24321 dice_loss 0.11568 +Epoch [1346/4000] Validation [4/4] Loss: 0.21915 focal_loss 0.10803 dice_loss 0.11112 +Epoch [1346/4000] Validation metric {'Val/mean dice_metric': 0.9654210209846497, 'Val/mean miou_metric': 0.945631206035614, 'Val/mean f1': 0.9677538871765137, 'Val/mean precision': 0.9594161510467529, 'Val/mean recall': 0.9762377142906189, 'Val/mean hd95_metric': 7.666313171386719} +Cheakpoint... +Epoch [1346/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9654210209846497, 'Val/mean miou_metric': 0.945631206035614, 'Val/mean f1': 0.9677538871765137, 'Val/mean precision': 0.9594161510467529, 'Val/mean recall': 0.9762377142906189, 'Val/mean hd95_metric': 7.666313171386719} +Epoch [1347/4000] Training [1/16] Loss: 0.00745 +Epoch [1347/4000] Training [2/16] Loss: 0.01253 +Epoch [1347/4000] Training [3/16] Loss: 0.01210 +Epoch [1347/4000] Training [4/16] Loss: 0.00915 +Epoch [1347/4000] Training [5/16] Loss: 0.00995 +Epoch [1347/4000] Training [6/16] Loss: 0.01138 +Epoch [1347/4000] Training [7/16] Loss: 0.01732 +Epoch [1347/4000] Training [8/16] Loss: 0.01066 +Epoch [1347/4000] Training [9/16] Loss: 0.01468 +Epoch [1347/4000] Training [10/16] Loss: 0.00867 +Epoch [1347/4000] Training [11/16] Loss: 0.01114 +Epoch [1347/4000] Training [12/16] Loss: 0.00827 +Epoch [1347/4000] Training [13/16] Loss: 0.00994 +Epoch [1347/4000] Training [14/16] Loss: 0.00969 +Epoch [1347/4000] Training [15/16] Loss: 0.00770 +Epoch [1347/4000] Training [16/16] Loss: 0.00963 +Epoch [1347/4000] Training metric {'Train/mean dice_metric': 0.9931164979934692, 'Train/mean miou_metric': 0.9860680103302002, 'Train/mean f1': 0.988597571849823, 'Train/mean precision': 0.9838975667953491, 'Train/mean recall': 0.9933426380157471, 'Train/mean hd95_metric': 1.5300419330596924} +Epoch [1347/4000] Validation [1/4] Loss: 0.32360 focal_loss 0.23860 dice_loss 0.08500 +Epoch [1347/4000] Validation [2/4] Loss: 0.48247 focal_loss 0.29697 dice_loss 0.18550 +Epoch [1347/4000] Validation [3/4] Loss: 0.17728 focal_loss 0.09783 dice_loss 0.07945 +Epoch [1347/4000] Validation [4/4] Loss: 0.27201 focal_loss 0.15713 dice_loss 0.11488 +Epoch [1347/4000] Validation metric {'Val/mean dice_metric': 0.9689413905143738, 'Val/mean miou_metric': 0.9497879147529602, 'Val/mean f1': 0.9706326723098755, 'Val/mean precision': 0.9692299962043762, 'Val/mean recall': 0.9720394015312195, 'Val/mean hd95_metric': 5.9902729988098145} +Cheakpoint... +Epoch [1347/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689413905143738, 'Val/mean miou_metric': 0.9497879147529602, 'Val/mean f1': 0.9706326723098755, 'Val/mean precision': 0.9692299962043762, 'Val/mean recall': 0.9720394015312195, 'Val/mean hd95_metric': 5.9902729988098145} +Epoch [1348/4000] Training [1/16] Loss: 0.00932 +Epoch [1348/4000] Training [2/16] Loss: 0.01305 +Epoch [1348/4000] Training [3/16] Loss: 0.00859 +Epoch [1348/4000] Training [4/16] Loss: 0.01761 +Epoch [1348/4000] Training [5/16] Loss: 0.00944 +Epoch [1348/4000] Training [6/16] Loss: 0.01032 +Epoch [1348/4000] Training [7/16] Loss: 0.01002 +Epoch [1348/4000] Training [8/16] Loss: 0.00851 +Epoch [1348/4000] Training [9/16] Loss: 0.00969 +Epoch [1348/4000] Training [10/16] Loss: 0.00770 +Epoch [1348/4000] Training [11/16] Loss: 0.00894 +Epoch [1348/4000] Training [12/16] Loss: 0.00780 +Epoch [1348/4000] Training [13/16] Loss: 0.00921 +Epoch [1348/4000] Training [14/16] Loss: 0.00838 +Epoch [1348/4000] Training [15/16] Loss: 0.00836 +Epoch [1348/4000] Training [16/16] Loss: 0.00925 +Epoch [1348/4000] Training metric {'Train/mean dice_metric': 0.9933950304985046, 'Train/mean miou_metric': 0.98661208152771, 'Train/mean f1': 0.9886574149131775, 'Train/mean precision': 0.9832886457443237, 'Train/mean recall': 0.9940851926803589, 'Train/mean hd95_metric': 1.1173982620239258} +Epoch [1348/4000] Validation [1/4] Loss: 0.45252 focal_loss 0.34820 dice_loss 0.10432 +Epoch [1348/4000] Validation [2/4] Loss: 0.29897 focal_loss 0.15389 dice_loss 0.14508 +Epoch [1348/4000] Validation [3/4] Loss: 0.29767 focal_loss 0.20289 dice_loss 0.09478 +Epoch [1348/4000] Validation [4/4] Loss: 0.28997 focal_loss 0.17470 dice_loss 0.11527 +Epoch [1348/4000] Validation metric {'Val/mean dice_metric': 0.9701770544052124, 'Val/mean miou_metric': 0.9515069723129272, 'Val/mean f1': 0.9702211022377014, 'Val/mean precision': 0.9672995805740356, 'Val/mean recall': 0.9731603860855103, 'Val/mean hd95_metric': 5.81350040435791} +Cheakpoint... +Epoch [1348/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701770544052124, 'Val/mean miou_metric': 0.9515069723129272, 'Val/mean f1': 0.9702211022377014, 'Val/mean precision': 0.9672995805740356, 'Val/mean recall': 0.9731603860855103, 'Val/mean hd95_metric': 5.81350040435791} +Epoch [1349/4000] Training [1/16] Loss: 0.00963 +Epoch [1349/4000] Training [2/16] Loss: 0.00923 +Epoch [1349/4000] Training [3/16] Loss: 0.00785 +Epoch [1349/4000] Training [4/16] Loss: 0.00735 +Epoch [1349/4000] Training [5/16] Loss: 0.00858 +Epoch [1349/4000] Training [6/16] Loss: 0.01029 +Epoch [1349/4000] Training [7/16] Loss: 0.01088 +Epoch [1349/4000] Training [8/16] Loss: 0.00774 +Epoch [1349/4000] Training [9/16] Loss: 0.01307 +Epoch [1349/4000] Training [10/16] Loss: 0.01192 +Epoch [1349/4000] Training [11/16] Loss: 0.00918 +Epoch [1349/4000] Training [12/16] Loss: 0.00873 +Epoch [1349/4000] Training [13/16] Loss: 0.00834 +Epoch [1349/4000] Training [14/16] Loss: 0.00878 +Epoch [1349/4000] Training [15/16] Loss: 0.00744 +Epoch [1349/4000] Training [16/16] Loss: 0.00919 +Epoch [1349/4000] Training metric {'Train/mean dice_metric': 0.9937268495559692, 'Train/mean miou_metric': 0.9872885346412659, 'Train/mean f1': 0.9897054433822632, 'Train/mean precision': 0.9849383234977722, 'Train/mean recall': 0.9945188760757446, 'Train/mean hd95_metric': 1.0592761039733887} +Epoch [1349/4000] Validation [1/4] Loss: 0.26040 focal_loss 0.19317 dice_loss 0.06723 +Epoch [1349/4000] Validation [2/4] Loss: 0.25313 focal_loss 0.13213 dice_loss 0.12100 +Epoch [1349/4000] Validation [3/4] Loss: 0.24829 focal_loss 0.15611 dice_loss 0.09218 +Epoch [1349/4000] Validation [4/4] Loss: 0.19010 focal_loss 0.08973 dice_loss 0.10037 +Epoch [1349/4000] Validation metric {'Val/mean dice_metric': 0.9720003008842468, 'Val/mean miou_metric': 0.9538758993148804, 'Val/mean f1': 0.9735460877418518, 'Val/mean precision': 0.96977698802948, 'Val/mean recall': 0.9773445129394531, 'Val/mean hd95_metric': 5.589413642883301} +Cheakpoint... +Epoch [1349/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720003008842468, 'Val/mean miou_metric': 0.9538758993148804, 'Val/mean f1': 0.9735460877418518, 'Val/mean precision': 0.96977698802948, 'Val/mean recall': 0.9773445129394531, 'Val/mean hd95_metric': 5.589413642883301} +Epoch [1350/4000] Training [1/16] Loss: 0.00806 +Epoch [1350/4000] Training [2/16] Loss: 0.00856 +Epoch [1350/4000] Training [3/16] Loss: 0.00766 +Epoch [1350/4000] Training [4/16] Loss: 0.00843 +Epoch [1350/4000] Training [5/16] Loss: 0.00878 +Epoch [1350/4000] Training [6/16] Loss: 0.01263 +Epoch [1350/4000] Training [7/16] Loss: 0.01264 +Epoch [1350/4000] Training [8/16] Loss: 0.00947 +Epoch [1350/4000] Training [9/16] Loss: 0.00740 +Epoch [1350/4000] Training [10/16] Loss: 0.00698 +Epoch [1350/4000] Training [11/16] Loss: 0.00783 +Epoch [1350/4000] Training [12/16] Loss: 0.00952 +Epoch [1350/4000] Training [13/16] Loss: 0.00963 +Epoch [1350/4000] Training [14/16] Loss: 0.01064 +Epoch [1350/4000] Training [15/16] Loss: 0.00732 +Epoch [1350/4000] Training [16/16] Loss: 0.00882 +Epoch [1350/4000] Training metric {'Train/mean dice_metric': 0.9940667748451233, 'Train/mean miou_metric': 0.987957775592804, 'Train/mean f1': 0.9903135895729065, 'Train/mean precision': 0.9859544038772583, 'Train/mean recall': 0.9947114586830139, 'Train/mean hd95_metric': 1.190390944480896} +Epoch [1350/4000] Validation [1/4] Loss: 0.23482 focal_loss 0.15690 dice_loss 0.07792 +Epoch [1350/4000] Validation [2/4] Loss: 0.44232 focal_loss 0.25814 dice_loss 0.18418 +Epoch [1350/4000] Validation [3/4] Loss: 0.25960 focal_loss 0.16858 dice_loss 0.09102 +Epoch [1350/4000] Validation [4/4] Loss: 0.46202 focal_loss 0.27197 dice_loss 0.19005 +Epoch [1350/4000] Validation metric {'Val/mean dice_metric': 0.9682567715644836, 'Val/mean miou_metric': 0.9501217603683472, 'Val/mean f1': 0.9725961089134216, 'Val/mean precision': 0.9715825915336609, 'Val/mean recall': 0.9736118316650391, 'Val/mean hd95_metric': 5.8705244064331055} +Cheakpoint... +Epoch [1350/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9682567715644836, 'Val/mean miou_metric': 0.9501217603683472, 'Val/mean f1': 0.9725961089134216, 'Val/mean precision': 0.9715825915336609, 'Val/mean recall': 0.9736118316650391, 'Val/mean hd95_metric': 5.8705244064331055} +Epoch [1351/4000] Training [1/16] Loss: 0.00817 +Epoch [1351/4000] Training [2/16] Loss: 0.00807 +Epoch [1351/4000] Training [3/16] Loss: 0.00886 +Epoch [1351/4000] Training [4/16] Loss: 0.00632 +Epoch [1351/4000] Training [5/16] Loss: 0.00972 +Epoch [1351/4000] Training [6/16] Loss: 0.00946 +Epoch [1351/4000] Training [7/16] Loss: 0.01028 +Epoch [1351/4000] Training [8/16] Loss: 0.00897 +Epoch [1351/4000] Training [9/16] Loss: 0.00855 +Epoch [1351/4000] Training [10/16] Loss: 0.00812 +Epoch [1351/4000] Training [11/16] Loss: 0.00672 +Epoch [1351/4000] Training [12/16] Loss: 0.00926 +Epoch [1351/4000] Training [13/16] Loss: 0.01171 +Epoch [1351/4000] Training [14/16] Loss: 0.00795 +Epoch [1351/4000] Training [15/16] Loss: 0.00906 +Epoch [1351/4000] Training [16/16] Loss: 0.00725 +Epoch [1351/4000] Training metric {'Train/mean dice_metric': 0.9941565990447998, 'Train/mean miou_metric': 0.9881328344345093, 'Train/mean f1': 0.9902528524398804, 'Train/mean precision': 0.9856618046760559, 'Train/mean recall': 0.9948868155479431, 'Train/mean hd95_metric': 1.0376408100128174} +Epoch [1351/4000] Validation [1/4] Loss: 0.17948 focal_loss 0.11897 dice_loss 0.06051 +Epoch [1351/4000] Validation [2/4] Loss: 0.25290 focal_loss 0.12897 dice_loss 0.12393 +Epoch [1351/4000] Validation [3/4] Loss: 0.28524 focal_loss 0.18434 dice_loss 0.10090 +Epoch [1351/4000] Validation [4/4] Loss: 0.23029 focal_loss 0.13949 dice_loss 0.09080 +Epoch [1351/4000] Validation metric {'Val/mean dice_metric': 0.9714365005493164, 'Val/mean miou_metric': 0.9533027410507202, 'Val/mean f1': 0.973461389541626, 'Val/mean precision': 0.9694978594779968, 'Val/mean recall': 0.9774573445320129, 'Val/mean hd95_metric': 5.395585060119629} +Cheakpoint... +Epoch [1351/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714365005493164, 'Val/mean miou_metric': 0.9533027410507202, 'Val/mean f1': 0.973461389541626, 'Val/mean precision': 0.9694978594779968, 'Val/mean recall': 0.9774573445320129, 'Val/mean hd95_metric': 5.395585060119629} +Epoch [1352/4000] Training [1/16] Loss: 0.00995 +Epoch [1352/4000] Training [2/16] Loss: 0.00678 +Epoch [1352/4000] Training [3/16] Loss: 0.00955 +Epoch [1352/4000] Training [4/16] Loss: 0.01253 +Epoch [1352/4000] Training [5/16] Loss: 0.00678 +Epoch [1352/4000] Training [6/16] Loss: 0.01135 +Epoch [1352/4000] Training [7/16] Loss: 0.00671 +Epoch [1352/4000] Training [8/16] Loss: 0.03959 +Epoch [1352/4000] Training [9/16] Loss: 0.00817 +Epoch [1352/4000] Training [10/16] Loss: 0.01057 +Epoch [1352/4000] Training [11/16] Loss: 0.01784 +Epoch [1352/4000] Training [12/16] Loss: 0.01314 +Epoch [1352/4000] Training [13/16] Loss: 0.01450 +Epoch [1352/4000] Training [14/16] Loss: 0.00938 +Epoch [1352/4000] Training [15/16] Loss: 0.00710 +Epoch [1352/4000] Training [16/16] Loss: 0.00773 +Epoch [1352/4000] Training metric {'Train/mean dice_metric': 0.9932342767715454, 'Train/mean miou_metric': 0.9864029288291931, 'Train/mean f1': 0.9895263314247131, 'Train/mean precision': 0.9846991896629333, 'Train/mean recall': 0.9944010376930237, 'Train/mean hd95_metric': 1.2169229984283447} +Epoch [1352/4000] Validation [1/4] Loss: 0.38792 focal_loss 0.28275 dice_loss 0.10517 +Epoch [1352/4000] Validation [2/4] Loss: 0.32297 focal_loss 0.16978 dice_loss 0.15319 +Epoch [1352/4000] Validation [3/4] Loss: 0.28856 focal_loss 0.19374 dice_loss 0.09482 +Epoch [1352/4000] Validation [4/4] Loss: 0.29112 focal_loss 0.15996 dice_loss 0.13116 +Epoch [1352/4000] Validation metric {'Val/mean dice_metric': 0.9672916531562805, 'Val/mean miou_metric': 0.9479734301567078, 'Val/mean f1': 0.9704828858375549, 'Val/mean precision': 0.9694178104400635, 'Val/mean recall': 0.9715503454208374, 'Val/mean hd95_metric': 5.872251033782959} +Cheakpoint... +Epoch [1352/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672916531562805, 'Val/mean miou_metric': 0.9479734301567078, 'Val/mean f1': 0.9704828858375549, 'Val/mean precision': 0.9694178104400635, 'Val/mean recall': 0.9715503454208374, 'Val/mean hd95_metric': 5.872251033782959} +Epoch [1353/4000] Training [1/16] Loss: 0.01070 +Epoch [1353/4000] Training [2/16] Loss: 0.00943 +Epoch [1353/4000] Training [3/16] Loss: 0.00665 +Epoch [1353/4000] Training [4/16] Loss: 0.01274 +Epoch [1353/4000] Training [5/16] Loss: 0.00820 +Epoch [1353/4000] Training [6/16] Loss: 0.01084 +Epoch [1353/4000] Training [7/16] Loss: 0.00839 +Epoch [1353/4000] Training [8/16] Loss: 0.01081 +Epoch [1353/4000] Training [9/16] Loss: 0.00927 +Epoch [1353/4000] Training [10/16] Loss: 0.01005 +Epoch [1353/4000] Training [11/16] Loss: 0.01126 +Epoch [1353/4000] Training [12/16] Loss: 0.00798 +Epoch [1353/4000] Training [13/16] Loss: 0.00978 +Epoch [1353/4000] Training [14/16] Loss: 0.01008 +Epoch [1353/4000] Training [15/16] Loss: 0.00792 +Epoch [1353/4000] Training [16/16] Loss: 0.01043 +Epoch [1353/4000] Training metric {'Train/mean dice_metric': 0.9915177822113037, 'Train/mean miou_metric': 0.984580934047699, 'Train/mean f1': 0.989126980304718, 'Train/mean precision': 0.985185980796814, 'Train/mean recall': 0.993099570274353, 'Train/mean hd95_metric': 1.4246102571487427} +Epoch [1353/4000] Validation [1/4] Loss: 0.22072 focal_loss 0.15478 dice_loss 0.06594 +Epoch [1353/4000] Validation [2/4] Loss: 0.23927 focal_loss 0.11762 dice_loss 0.12165 +Epoch [1353/4000] Validation [3/4] Loss: 0.17203 focal_loss 0.09160 dice_loss 0.08043 +Epoch [1353/4000] Validation [4/4] Loss: 0.22797 focal_loss 0.11696 dice_loss 0.11101 +Epoch [1353/4000] Validation metric {'Val/mean dice_metric': 0.9693486094474792, 'Val/mean miou_metric': 0.9505769610404968, 'Val/mean f1': 0.972166895866394, 'Val/mean precision': 0.9647569060325623, 'Val/mean recall': 0.9796916842460632, 'Val/mean hd95_metric': 6.752566337585449} +Cheakpoint... +Epoch [1353/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693486094474792, 'Val/mean miou_metric': 0.9505769610404968, 'Val/mean f1': 0.972166895866394, 'Val/mean precision': 0.9647569060325623, 'Val/mean recall': 0.9796916842460632, 'Val/mean hd95_metric': 6.752566337585449} +Epoch [1354/4000] Training [1/16] Loss: 0.00704 +Epoch [1354/4000] Training [2/16] Loss: 0.00778 +Epoch [1354/4000] Training [3/16] Loss: 0.00772 +Epoch [1354/4000] Training [4/16] Loss: 0.00906 +Epoch [1354/4000] Training [5/16] Loss: 0.00654 +Epoch [1354/4000] Training [6/16] Loss: 0.00954 +Epoch [1354/4000] Training [7/16] Loss: 0.00872 +Epoch [1354/4000] Training [8/16] Loss: 0.01006 +Epoch [1354/4000] Training [9/16] Loss: 0.01353 +Epoch [1354/4000] Training [10/16] Loss: 0.01022 +Epoch [1354/4000] Training [11/16] Loss: 0.00917 +Epoch [1354/4000] Training [12/16] Loss: 0.01214 +Epoch [1354/4000] Training [13/16] Loss: 0.01430 +Epoch [1354/4000] Training [14/16] Loss: 0.00799 +Epoch [1354/4000] Training [15/16] Loss: 0.01267 +Epoch [1354/4000] Training [16/16] Loss: 0.01144 +Epoch [1354/4000] Training metric {'Train/mean dice_metric': 0.9927726984024048, 'Train/mean miou_metric': 0.9856030941009521, 'Train/mean f1': 0.9893290400505066, 'Train/mean precision': 0.9844222068786621, 'Train/mean recall': 0.994284987449646, 'Train/mean hd95_metric': 2.332594871520996} +Epoch [1354/4000] Validation [1/4] Loss: 0.62787 focal_loss 0.51082 dice_loss 0.11705 +Epoch [1354/4000] Validation [2/4] Loss: 0.57820 focal_loss 0.33816 dice_loss 0.24004 +Epoch [1354/4000] Validation [3/4] Loss: 0.29898 focal_loss 0.18348 dice_loss 0.11549 +Epoch [1354/4000] Validation [4/4] Loss: 0.32806 focal_loss 0.18768 dice_loss 0.14038 +Epoch [1354/4000] Validation metric {'Val/mean dice_metric': 0.9659630060195923, 'Val/mean miou_metric': 0.945992112159729, 'Val/mean f1': 0.968309760093689, 'Val/mean precision': 0.9674628973007202, 'Val/mean recall': 0.9691580533981323, 'Val/mean hd95_metric': 7.370035648345947} +Cheakpoint... +Epoch [1354/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659630060195923, 'Val/mean miou_metric': 0.945992112159729, 'Val/mean f1': 0.968309760093689, 'Val/mean precision': 0.9674628973007202, 'Val/mean recall': 0.9691580533981323, 'Val/mean hd95_metric': 7.370035648345947} +Epoch [1355/4000] Training [1/16] Loss: 0.00846 +Epoch [1355/4000] Training [2/16] Loss: 0.01129 +Epoch [1355/4000] Training [3/16] Loss: 0.00940 +Epoch [1355/4000] Training [4/16] Loss: 0.01256 +Epoch [1355/4000] Training [5/16] Loss: 0.01030 +Epoch [1355/4000] Training [6/16] Loss: 0.01009 +Epoch [1355/4000] Training [7/16] Loss: 0.00947 +Epoch [1355/4000] Training [8/16] Loss: 0.00739 +Epoch [1355/4000] Training [9/16] Loss: 0.00965 +Epoch [1355/4000] Training [10/16] Loss: 0.00955 +Epoch [1355/4000] Training [11/16] Loss: 0.01127 +Epoch [1355/4000] Training [12/16] Loss: 0.00868 +Epoch [1355/4000] Training [13/16] Loss: 0.00864 +Epoch [1355/4000] Training [14/16] Loss: 0.01236 +Epoch [1355/4000] Training [15/16] Loss: 0.00819 +Epoch [1355/4000] Training [16/16] Loss: 0.01104 +Epoch [1355/4000] Training metric {'Train/mean dice_metric': 0.9922688603401184, 'Train/mean miou_metric': 0.9846974611282349, 'Train/mean f1': 0.9891766309738159, 'Train/mean precision': 0.984778106212616, 'Train/mean recall': 0.9936145544052124, 'Train/mean hd95_metric': 1.6845201253890991} +Epoch [1355/4000] Validation [1/4] Loss: 0.20272 focal_loss 0.13843 dice_loss 0.06429 +Epoch [1355/4000] Validation [2/4] Loss: 0.51668 focal_loss 0.30069 dice_loss 0.21599 +Epoch [1355/4000] Validation [3/4] Loss: 0.26805 focal_loss 0.17312 dice_loss 0.09493 +Epoch [1355/4000] Validation [4/4] Loss: 0.30038 focal_loss 0.18302 dice_loss 0.11736 +Epoch [1355/4000] Validation metric {'Val/mean dice_metric': 0.9675987362861633, 'Val/mean miou_metric': 0.9482089281082153, 'Val/mean f1': 0.9705706238746643, 'Val/mean precision': 0.9645414352416992, 'Val/mean recall': 0.9766756892204285, 'Val/mean hd95_metric': 7.317796230316162} +Cheakpoint... +Epoch [1355/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675987362861633, 'Val/mean miou_metric': 0.9482089281082153, 'Val/mean f1': 0.9705706238746643, 'Val/mean precision': 0.9645414352416992, 'Val/mean recall': 0.9766756892204285, 'Val/mean hd95_metric': 7.317796230316162} +Epoch [1356/4000] Training [1/16] Loss: 0.01002 +Epoch [1356/4000] Training [2/16] Loss: 0.00752 +Epoch [1356/4000] Training [3/16] Loss: 0.00968 +Epoch [1356/4000] Training [4/16] Loss: 0.00719 +Epoch [1356/4000] Training [5/16] Loss: 0.01362 +Epoch [1356/4000] Training [6/16] Loss: 0.01545 +Epoch [1356/4000] Training [7/16] Loss: 0.00862 +Epoch [1356/4000] Training [8/16] Loss: 0.00999 +Epoch [1356/4000] Training [9/16] Loss: 0.01020 +Epoch [1356/4000] Training [10/16] Loss: 0.01047 +Epoch [1356/4000] Training [11/16] Loss: 0.00762 +Epoch [1356/4000] Training [12/16] Loss: 0.00881 +Epoch [1356/4000] Training [13/16] Loss: 0.02497 +Epoch [1356/4000] Training [14/16] Loss: 0.00876 +Epoch [1356/4000] Training [15/16] Loss: 0.00708 +Epoch [1356/4000] Training [16/16] Loss: 0.01084 +Epoch [1356/4000] Training metric {'Train/mean dice_metric': 0.9925714135169983, 'Train/mean miou_metric': 0.9852002859115601, 'Train/mean f1': 0.9890955090522766, 'Train/mean precision': 0.9843917489051819, 'Train/mean recall': 0.9938444495201111, 'Train/mean hd95_metric': 1.9184813499450684} +Epoch [1356/4000] Validation [1/4] Loss: 0.19642 focal_loss 0.13262 dice_loss 0.06379 +Epoch [1356/4000] Validation [2/4] Loss: 0.71937 focal_loss 0.44419 dice_loss 0.27518 +Epoch [1356/4000] Validation [3/4] Loss: 0.21996 focal_loss 0.13033 dice_loss 0.08964 +Epoch [1356/4000] Validation [4/4] Loss: 0.39601 focal_loss 0.24387 dice_loss 0.15215 +Epoch [1356/4000] Validation metric {'Val/mean dice_metric': 0.9674800634384155, 'Val/mean miou_metric': 0.9479257464408875, 'Val/mean f1': 0.9711167812347412, 'Val/mean precision': 0.9653800129890442, 'Val/mean recall': 0.9769220352172852, 'Val/mean hd95_metric': 6.7989935874938965} +Cheakpoint... +Epoch [1356/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674800634384155, 'Val/mean miou_metric': 0.9479257464408875, 'Val/mean f1': 0.9711167812347412, 'Val/mean precision': 0.9653800129890442, 'Val/mean recall': 0.9769220352172852, 'Val/mean hd95_metric': 6.7989935874938965} +Epoch [1357/4000] Training [1/16] Loss: 0.01025 +Epoch [1357/4000] Training [2/16] Loss: 0.00940 +Epoch [1357/4000] Training [3/16] Loss: 0.00960 +Epoch [1357/4000] Training [4/16] Loss: 0.00874 +Epoch [1357/4000] Training [5/16] Loss: 0.00986 +Epoch [1357/4000] Training [6/16] Loss: 0.00875 +Epoch [1357/4000] Training [7/16] Loss: 0.01480 +Epoch [1357/4000] Training [8/16] Loss: 0.00911 +Epoch [1357/4000] Training [9/16] Loss: 0.01129 +Epoch [1357/4000] Training [10/16] Loss: 0.01005 +Epoch [1357/4000] Training [11/16] Loss: 0.01086 +Epoch [1357/4000] Training [12/16] Loss: 0.01346 +Epoch [1357/4000] Training [13/16] Loss: 0.01011 +Epoch [1357/4000] Training [14/16] Loss: 0.00999 +Epoch [1357/4000] Training [15/16] Loss: 0.01143 +Epoch [1357/4000] Training [16/16] Loss: 0.01073 +Epoch [1357/4000] Training metric {'Train/mean dice_metric': 0.9927054047584534, 'Train/mean miou_metric': 0.9852645993232727, 'Train/mean f1': 0.9882127642631531, 'Train/mean precision': 0.9831714034080505, 'Train/mean recall': 0.9933061003684998, 'Train/mean hd95_metric': 1.5217564105987549} +Epoch [1357/4000] Validation [1/4] Loss: 0.17178 focal_loss 0.10500 dice_loss 0.06679 +Epoch [1357/4000] Validation [2/4] Loss: 0.43797 focal_loss 0.23969 dice_loss 0.19828 +Epoch [1357/4000] Validation [3/4] Loss: 0.30283 focal_loss 0.19479 dice_loss 0.10804 +Epoch [1357/4000] Validation [4/4] Loss: 0.42777 focal_loss 0.26476 dice_loss 0.16301 +Epoch [1357/4000] Validation metric {'Val/mean dice_metric': 0.967932403087616, 'Val/mean miou_metric': 0.9477553367614746, 'Val/mean f1': 0.9685777425765991, 'Val/mean precision': 0.9652342796325684, 'Val/mean recall': 0.9719445705413818, 'Val/mean hd95_metric': 6.354560852050781} +Cheakpoint... +Epoch [1357/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967932403087616, 'Val/mean miou_metric': 0.9477553367614746, 'Val/mean f1': 0.9685777425765991, 'Val/mean precision': 0.9652342796325684, 'Val/mean recall': 0.9719445705413818, 'Val/mean hd95_metric': 6.354560852050781} +Epoch [1358/4000] Training [1/16] Loss: 0.01043 +Epoch [1358/4000] Training [2/16] Loss: 0.00751 +Epoch [1358/4000] Training [3/16] Loss: 0.00818 +Epoch [1358/4000] Training [4/16] Loss: 0.00948 +Epoch [1358/4000] Training [5/16] Loss: 0.01181 +Epoch [1358/4000] Training [6/16] Loss: 0.01219 +Epoch [1358/4000] Training [7/16] Loss: 0.00949 +Epoch [1358/4000] Training [8/16] Loss: 0.00818 +Epoch [1358/4000] Training [9/16] Loss: 0.03583 +Epoch [1358/4000] Training [10/16] Loss: 0.01007 +Epoch [1358/4000] Training [11/16] Loss: 0.00866 +Epoch [1358/4000] Training [12/16] Loss: 0.01126 +Epoch [1358/4000] Training [13/16] Loss: 0.00851 +Epoch [1358/4000] Training [14/16] Loss: 0.00749 +Epoch [1358/4000] Training [15/16] Loss: 0.01018 +Epoch [1358/4000] Training [16/16] Loss: 0.01044 +Epoch [1358/4000] Training metric {'Train/mean dice_metric': 0.9932491779327393, 'Train/mean miou_metric': 0.986436128616333, 'Train/mean f1': 0.9894983172416687, 'Train/mean precision': 0.9851273894309998, 'Train/mean recall': 0.9939082264900208, 'Train/mean hd95_metric': 1.2288811206817627} +Epoch [1358/4000] Validation [1/4] Loss: 0.25014 focal_loss 0.18051 dice_loss 0.06963 +Epoch [1358/4000] Validation [2/4] Loss: 0.27340 focal_loss 0.14338 dice_loss 0.13002 +Epoch [1358/4000] Validation [3/4] Loss: 0.19889 focal_loss 0.11074 dice_loss 0.08816 +Epoch [1358/4000] Validation [4/4] Loss: 0.26822 focal_loss 0.12850 dice_loss 0.13972 +Epoch [1358/4000] Validation metric {'Val/mean dice_metric': 0.9681230783462524, 'Val/mean miou_metric': 0.9488897323608398, 'Val/mean f1': 0.9718150496482849, 'Val/mean precision': 0.9686999320983887, 'Val/mean recall': 0.9749502539634705, 'Val/mean hd95_metric': 5.7063798904418945} +Cheakpoint... +Epoch [1358/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681230783462524, 'Val/mean miou_metric': 0.9488897323608398, 'Val/mean f1': 0.9718150496482849, 'Val/mean precision': 0.9686999320983887, 'Val/mean recall': 0.9749502539634705, 'Val/mean hd95_metric': 5.7063798904418945} +Epoch [1359/4000] Training [1/16] Loss: 0.01134 +Epoch [1359/4000] Training [2/16] Loss: 0.01243 +Epoch [1359/4000] Training [3/16] Loss: 0.00812 +Epoch [1359/4000] Training [4/16] Loss: 0.00774 +Epoch [1359/4000] Training [5/16] Loss: 0.01028 +Epoch [1359/4000] Training [6/16] Loss: 0.01143 +Epoch [1359/4000] Training [7/16] Loss: 0.00847 +Epoch [1359/4000] Training [8/16] Loss: 0.00868 +Epoch [1359/4000] Training [9/16] Loss: 0.00847 +Epoch [1359/4000] Training [10/16] Loss: 0.01161 +Epoch [1359/4000] Training [11/16] Loss: 0.00649 +Epoch [1359/4000] Training [12/16] Loss: 0.00698 +Epoch [1359/4000] Training [13/16] Loss: 0.00856 +Epoch [1359/4000] Training [14/16] Loss: 0.00820 +Epoch [1359/4000] Training [15/16] Loss: 0.01962 +Epoch [1359/4000] Training [16/16] Loss: 0.00772 +Epoch [1359/4000] Training metric {'Train/mean dice_metric': 0.9935939908027649, 'Train/mean miou_metric': 0.9870196580886841, 'Train/mean f1': 0.9895160794258118, 'Train/mean precision': 0.984723687171936, 'Train/mean recall': 0.994355320930481, 'Train/mean hd95_metric': 1.1322054862976074} +Epoch [1359/4000] Validation [1/4] Loss: 0.30902 focal_loss 0.22690 dice_loss 0.08212 +Epoch [1359/4000] Validation [2/4] Loss: 0.34756 focal_loss 0.16997 dice_loss 0.17759 +Epoch [1359/4000] Validation [3/4] Loss: 0.21625 focal_loss 0.12672 dice_loss 0.08953 +Epoch [1359/4000] Validation [4/4] Loss: 0.30916 focal_loss 0.18747 dice_loss 0.12168 +Epoch [1359/4000] Validation metric {'Val/mean dice_metric': 0.971676230430603, 'Val/mean miou_metric': 0.9526900053024292, 'Val/mean f1': 0.9723266363143921, 'Val/mean precision': 0.9671066999435425, 'Val/mean recall': 0.9776031374931335, 'Val/mean hd95_metric': 5.673637390136719} +Cheakpoint... +Epoch [1359/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971676230430603, 'Val/mean miou_metric': 0.9526900053024292, 'Val/mean f1': 0.9723266363143921, 'Val/mean precision': 0.9671066999435425, 'Val/mean recall': 0.9776031374931335, 'Val/mean hd95_metric': 5.673637390136719} +Epoch [1360/4000] Training [1/16] Loss: 0.01313 +Epoch [1360/4000] Training [2/16] Loss: 0.00787 +Epoch [1360/4000] Training [3/16] Loss: 0.00668 +Epoch [1360/4000] Training [4/16] Loss: 0.01032 +Epoch [1360/4000] Training [5/16] Loss: 0.00901 +Epoch [1360/4000] Training [6/16] Loss: 0.00740 +Epoch [1360/4000] Training [7/16] Loss: 0.00949 +Epoch [1360/4000] Training [8/16] Loss: 0.01022 +Epoch [1360/4000] Training [9/16] Loss: 0.00824 +Epoch [1360/4000] Training [10/16] Loss: 0.00751 +Epoch [1360/4000] Training [11/16] Loss: 0.02840 +Epoch [1360/4000] Training [12/16] Loss: 0.00980 +Epoch [1360/4000] Training [13/16] Loss: 0.00789 +Epoch [1360/4000] Training [14/16] Loss: 0.00805 +Epoch [1360/4000] Training [15/16] Loss: 0.00992 +Epoch [1360/4000] Training [16/16] Loss: 0.00824 +Epoch [1360/4000] Training metric {'Train/mean dice_metric': 0.9935041666030884, 'Train/mean miou_metric': 0.9869076013565063, 'Train/mean f1': 0.9897733926773071, 'Train/mean precision': 0.9851587414741516, 'Train/mean recall': 0.9944314956665039, 'Train/mean hd95_metric': 1.114198923110962} +Epoch [1360/4000] Validation [1/4] Loss: 0.32137 focal_loss 0.24281 dice_loss 0.07856 +Epoch [1360/4000] Validation [2/4] Loss: 0.46857 focal_loss 0.28248 dice_loss 0.18609 +Epoch [1360/4000] Validation [3/4] Loss: 0.19237 focal_loss 0.11166 dice_loss 0.08071 +Epoch [1360/4000] Validation [4/4] Loss: 0.20929 focal_loss 0.11325 dice_loss 0.09604 +Epoch [1360/4000] Validation metric {'Val/mean dice_metric': 0.969805896282196, 'Val/mean miou_metric': 0.9508331418037415, 'Val/mean f1': 0.9720533490180969, 'Val/mean precision': 0.9703457951545715, 'Val/mean recall': 0.973767101764679, 'Val/mean hd95_metric': 6.0305047035217285} +Cheakpoint... +Epoch [1360/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969805896282196, 'Val/mean miou_metric': 0.9508331418037415, 'Val/mean f1': 0.9720533490180969, 'Val/mean precision': 0.9703457951545715, 'Val/mean recall': 0.973767101764679, 'Val/mean hd95_metric': 6.0305047035217285} +Epoch [1361/4000] Training [1/16] Loss: 0.00802 +Epoch [1361/4000] Training [2/16] Loss: 0.00788 +Epoch [1361/4000] Training [3/16] Loss: 0.00678 +Epoch [1361/4000] Training [4/16] Loss: 0.00963 +Epoch [1361/4000] Training [5/16] Loss: 0.01094 +Epoch [1361/4000] Training [6/16] Loss: 0.00857 +Epoch [1361/4000] Training [7/16] Loss: 0.00742 +Epoch [1361/4000] Training [8/16] Loss: 0.00784 +Epoch [1361/4000] Training [9/16] Loss: 0.00782 +Epoch [1361/4000] Training [10/16] Loss: 0.00633 +Epoch [1361/4000] Training [11/16] Loss: 0.00819 +Epoch [1361/4000] Training [12/16] Loss: 0.00866 +Epoch [1361/4000] Training [13/16] Loss: 0.00727 +Epoch [1361/4000] Training [14/16] Loss: 0.00774 +Epoch [1361/4000] Training [15/16] Loss: 0.01377 +Epoch [1361/4000] Training [16/16] Loss: 0.00717 +Epoch [1361/4000] Training metric {'Train/mean dice_metric': 0.9941465854644775, 'Train/mean miou_metric': 0.9881112575531006, 'Train/mean f1': 0.9900705218315125, 'Train/mean precision': 0.9855290651321411, 'Train/mean recall': 0.99465411901474, 'Train/mean hd95_metric': 1.2174155712127686} +Epoch [1361/4000] Validation [1/4] Loss: 0.24180 focal_loss 0.16828 dice_loss 0.07352 +Epoch [1361/4000] Validation [2/4] Loss: 0.38978 focal_loss 0.21020 dice_loss 0.17958 +Epoch [1361/4000] Validation [3/4] Loss: 0.20551 focal_loss 0.12224 dice_loss 0.08328 +Epoch [1361/4000] Validation [4/4] Loss: 0.22201 focal_loss 0.12313 dice_loss 0.09888 +Epoch [1361/4000] Validation metric {'Val/mean dice_metric': 0.970615565776825, 'Val/mean miou_metric': 0.9528697729110718, 'Val/mean f1': 0.9731238484382629, 'Val/mean precision': 0.9704393744468689, 'Val/mean recall': 0.9758232831954956, 'Val/mean hd95_metric': 5.614203929901123} +Cheakpoint... +Epoch [1361/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970615565776825, 'Val/mean miou_metric': 0.9528697729110718, 'Val/mean f1': 0.9731238484382629, 'Val/mean precision': 0.9704393744468689, 'Val/mean recall': 0.9758232831954956, 'Val/mean hd95_metric': 5.614203929901123} +Epoch [1362/4000] Training [1/16] Loss: 0.00820 +Epoch [1362/4000] Training [2/16] Loss: 0.00837 +Epoch [1362/4000] Training [3/16] Loss: 0.00737 +Epoch [1362/4000] Training [4/16] Loss: 0.03115 +Epoch [1362/4000] Training [5/16] Loss: 0.00902 +Epoch [1362/4000] Training [6/16] Loss: 0.00963 +Epoch [1362/4000] Training [7/16] Loss: 0.00628 +Epoch [1362/4000] Training [8/16] Loss: 0.00862 +Epoch [1362/4000] Training [9/16] Loss: 0.00721 +Epoch [1362/4000] Training [10/16] Loss: 0.00911 +Epoch [1362/4000] Training [11/16] Loss: 0.00913 +Epoch [1362/4000] Training [12/16] Loss: 0.00714 +Epoch [1362/4000] Training [13/16] Loss: 0.00778 +Epoch [1362/4000] Training [14/16] Loss: 0.01043 +Epoch [1362/4000] Training [15/16] Loss: 0.00803 +Epoch [1362/4000] Training [16/16] Loss: 0.01586 +Epoch [1362/4000] Training metric {'Train/mean dice_metric': 0.9936845302581787, 'Train/mean miou_metric': 0.987295389175415, 'Train/mean f1': 0.9901686310768127, 'Train/mean precision': 0.9858304262161255, 'Train/mean recall': 0.9945451617240906, 'Train/mean hd95_metric': 1.1524392366409302} +Epoch [1362/4000] Validation [1/4] Loss: 0.23426 focal_loss 0.16937 dice_loss 0.06489 +Epoch [1362/4000] Validation [2/4] Loss: 0.32356 focal_loss 0.20111 dice_loss 0.12245 +Epoch [1362/4000] Validation [3/4] Loss: 0.22882 focal_loss 0.13785 dice_loss 0.09097 +Epoch [1362/4000] Validation [4/4] Loss: 0.29135 focal_loss 0.15920 dice_loss 0.13215 +Epoch [1362/4000] Validation metric {'Val/mean dice_metric': 0.9702649116516113, 'Val/mean miou_metric': 0.9520882368087769, 'Val/mean f1': 0.9721831679344177, 'Val/mean precision': 0.9681534171104431, 'Val/mean recall': 0.9762465953826904, 'Val/mean hd95_metric': 5.999239921569824} +Cheakpoint... +Epoch [1362/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702649116516113, 'Val/mean miou_metric': 0.9520882368087769, 'Val/mean f1': 0.9721831679344177, 'Val/mean precision': 0.9681534171104431, 'Val/mean recall': 0.9762465953826904, 'Val/mean hd95_metric': 5.999239921569824} +Epoch [1363/4000] Training [1/16] Loss: 0.00821 +Epoch [1363/4000] Training [2/16] Loss: 0.00862 +Epoch [1363/4000] Training [3/16] Loss: 0.00849 +Epoch [1363/4000] Training [4/16] Loss: 0.00989 +Epoch [1363/4000] Training [5/16] Loss: 0.00868 +Epoch [1363/4000] Training [6/16] Loss: 0.00720 +Epoch [1363/4000] Training [7/16] Loss: 0.00789 +Epoch [1363/4000] Training [8/16] Loss: 0.01121 +Epoch [1363/4000] Training [9/16] Loss: 0.01088 +Epoch [1363/4000] Training [10/16] Loss: 0.01105 +Epoch [1363/4000] Training [11/16] Loss: 0.00824 +Epoch [1363/4000] Training [12/16] Loss: 0.00923 +Epoch [1363/4000] Training [13/16] Loss: 0.00840 +Epoch [1363/4000] Training [14/16] Loss: 0.00671 +Epoch [1363/4000] Training [15/16] Loss: 0.00704 +Epoch [1363/4000] Training [16/16] Loss: 0.01036 +Epoch [1363/4000] Training metric {'Train/mean dice_metric': 0.9931294918060303, 'Train/mean miou_metric': 0.9863215684890747, 'Train/mean f1': 0.9896306395530701, 'Train/mean precision': 0.984913170337677, 'Train/mean recall': 0.994393527507782, 'Train/mean hd95_metric': 1.1703460216522217} +Epoch [1363/4000] Validation [1/4] Loss: 0.22725 focal_loss 0.16270 dice_loss 0.06455 +Epoch [1363/4000] Validation [2/4] Loss: 0.43071 focal_loss 0.26446 dice_loss 0.16625 +Epoch [1363/4000] Validation [3/4] Loss: 0.39417 focal_loss 0.27640 dice_loss 0.11777 +Epoch [1363/4000] Validation [4/4] Loss: 0.27236 focal_loss 0.12788 dice_loss 0.14449 +Epoch [1363/4000] Validation metric {'Val/mean dice_metric': 0.9688184857368469, 'Val/mean miou_metric': 0.9501972198486328, 'Val/mean f1': 0.9700629115104675, 'Val/mean precision': 0.9627133011817932, 'Val/mean recall': 0.9775257110595703, 'Val/mean hd95_metric': 6.276581764221191} +Cheakpoint... +Epoch [1363/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688184857368469, 'Val/mean miou_metric': 0.9501972198486328, 'Val/mean f1': 0.9700629115104675, 'Val/mean precision': 0.9627133011817932, 'Val/mean recall': 0.9775257110595703, 'Val/mean hd95_metric': 6.276581764221191} +Epoch [1364/4000] Training [1/16] Loss: 0.00801 +Epoch [1364/4000] Training [2/16] Loss: 0.00805 +Epoch [1364/4000] Training [3/16] Loss: 0.00718 +Epoch [1364/4000] Training [4/16] Loss: 0.01340 +Epoch [1364/4000] Training [5/16] Loss: 0.00711 +Epoch [1364/4000] Training [6/16] Loss: 0.00972 +Epoch [1364/4000] Training [7/16] Loss: 0.00781 +Epoch [1364/4000] Training [8/16] Loss: 0.00759 +Epoch [1364/4000] Training [9/16] Loss: 0.00973 +Epoch [1364/4000] Training [10/16] Loss: 0.01185 +Epoch [1364/4000] Training [11/16] Loss: 0.01133 +Epoch [1364/4000] Training [12/16] Loss: 0.00732 +Epoch [1364/4000] Training [13/16] Loss: 0.01367 +Epoch [1364/4000] Training [14/16] Loss: 0.00826 +Epoch [1364/4000] Training [15/16] Loss: 0.01120 +Epoch [1364/4000] Training [16/16] Loss: 0.00857 +Epoch [1364/4000] Training metric {'Train/mean dice_metric': 0.9922813177108765, 'Train/mean miou_metric': 0.9853402376174927, 'Train/mean f1': 0.9890092611312866, 'Train/mean precision': 0.9842100739479065, 'Train/mean recall': 0.9938554763793945, 'Train/mean hd95_metric': 1.5032309293746948} +Epoch [1364/4000] Validation [1/4] Loss: 0.27759 focal_loss 0.19700 dice_loss 0.08059 +Epoch [1364/4000] Validation [2/4] Loss: 0.39858 focal_loss 0.24376 dice_loss 0.15481 +Epoch [1364/4000] Validation [3/4] Loss: 0.37475 focal_loss 0.26663 dice_loss 0.10813 +Epoch [1364/4000] Validation [4/4] Loss: 0.24676 focal_loss 0.12741 dice_loss 0.11935 +Epoch [1364/4000] Validation metric {'Val/mean dice_metric': 0.9684501886367798, 'Val/mean miou_metric': 0.9487902522087097, 'Val/mean f1': 0.9691393971443176, 'Val/mean precision': 0.9662307500839233, 'Val/mean recall': 0.972065806388855, 'Val/mean hd95_metric': 6.419062614440918} +Cheakpoint... +Epoch [1364/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684501886367798, 'Val/mean miou_metric': 0.9487902522087097, 'Val/mean f1': 0.9691393971443176, 'Val/mean precision': 0.9662307500839233, 'Val/mean recall': 0.972065806388855, 'Val/mean hd95_metric': 6.419062614440918} +Epoch [1365/4000] Training [1/16] Loss: 0.00898 +Epoch [1365/4000] Training [2/16] Loss: 0.00910 +Epoch [1365/4000] Training [3/16] Loss: 0.01083 +Epoch [1365/4000] Training [4/16] Loss: 0.01162 +Epoch [1365/4000] Training [5/16] Loss: 0.01032 +Epoch [1365/4000] Training [6/16] Loss: 0.02109 +Epoch [1365/4000] Training [7/16] Loss: 0.01157 +Epoch [1365/4000] Training [8/16] Loss: 0.01967 +Epoch [1365/4000] Training [9/16] Loss: 0.00889 +Epoch [1365/4000] Training [10/16] Loss: 0.00748 +Epoch [1365/4000] Training [11/16] Loss: 0.01482 +Epoch [1365/4000] Training [12/16] Loss: 0.01228 +Epoch [1365/4000] Training [13/16] Loss: 0.01041 +Epoch [1365/4000] Training [14/16] Loss: 0.01108 +Epoch [1365/4000] Training [15/16] Loss: 0.05007 +Epoch [1365/4000] Training [16/16] Loss: 0.01043 +Epoch [1365/4000] Training metric {'Train/mean dice_metric': 0.9911994934082031, 'Train/mean miou_metric': 0.9826591610908508, 'Train/mean f1': 0.9868883490562439, 'Train/mean precision': 0.982303261756897, 'Train/mean recall': 0.9915164709091187, 'Train/mean hd95_metric': 2.111576795578003} +Epoch [1365/4000] Validation [1/4] Loss: 0.26806 focal_loss 0.19233 dice_loss 0.07573 +Epoch [1365/4000] Validation [2/4] Loss: 0.21662 focal_loss 0.10498 dice_loss 0.11164 +Epoch [1365/4000] Validation [3/4] Loss: 0.42840 focal_loss 0.29744 dice_loss 0.13096 +Epoch [1365/4000] Validation [4/4] Loss: 0.31679 focal_loss 0.19570 dice_loss 0.12110 +Epoch [1365/4000] Validation metric {'Val/mean dice_metric': 0.9666478037834167, 'Val/mean miou_metric': 0.9459436535835266, 'Val/mean f1': 0.9683240652084351, 'Val/mean precision': 0.9632338881492615, 'Val/mean recall': 0.9734683632850647, 'Val/mean hd95_metric': 7.067509651184082} +Cheakpoint... +Epoch [1365/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666478037834167, 'Val/mean miou_metric': 0.9459436535835266, 'Val/mean f1': 0.9683240652084351, 'Val/mean precision': 0.9632338881492615, 'Val/mean recall': 0.9734683632850647, 'Val/mean hd95_metric': 7.067509651184082} +Epoch [1366/4000] Training [1/16] Loss: 0.00966 +Epoch [1366/4000] Training [2/16] Loss: 0.01085 +Epoch [1366/4000] Training [3/16] Loss: 0.01487 +Epoch [1366/4000] Training [4/16] Loss: 0.00988 +Epoch [1366/4000] Training [5/16] Loss: 0.01022 +Epoch [1366/4000] Training [6/16] Loss: 0.01173 +Epoch [1366/4000] Training [7/16] Loss: 0.00831 +Epoch [1366/4000] Training [8/16] Loss: 0.01243 +Epoch [1366/4000] Training [9/16] Loss: 0.00726 +Epoch [1366/4000] Training [10/16] Loss: 0.01240 +Epoch [1366/4000] Training [11/16] Loss: 0.01000 +Epoch [1366/4000] Training [12/16] Loss: 0.00913 +Epoch [1366/4000] Training [13/16] Loss: 0.01111 +Epoch [1366/4000] Training [14/16] Loss: 0.00789 +Epoch [1366/4000] Training [15/16] Loss: 0.01213 +Epoch [1366/4000] Training [16/16] Loss: 0.01015 +Epoch [1366/4000] Training metric {'Train/mean dice_metric': 0.9924731254577637, 'Train/mean miou_metric': 0.9848302602767944, 'Train/mean f1': 0.988641083240509, 'Train/mean precision': 0.98419189453125, 'Train/mean recall': 0.993130624294281, 'Train/mean hd95_metric': 1.678767442703247} +Epoch [1366/4000] Validation [1/4] Loss: 0.20773 focal_loss 0.14934 dice_loss 0.05839 +Epoch [1366/4000] Validation [2/4] Loss: 0.55926 focal_loss 0.31570 dice_loss 0.24356 +Epoch [1366/4000] Validation [3/4] Loss: 0.19815 focal_loss 0.11334 dice_loss 0.08482 +Epoch [1366/4000] Validation [4/4] Loss: 0.29933 focal_loss 0.16791 dice_loss 0.13142 +Epoch [1366/4000] Validation metric {'Val/mean dice_metric': 0.9661872982978821, 'Val/mean miou_metric': 0.9470705986022949, 'Val/mean f1': 0.9718142151832581, 'Val/mean precision': 0.9687378406524658, 'Val/mean recall': 0.9749100804328918, 'Val/mean hd95_metric': 7.053030490875244} +Cheakpoint... +Epoch [1366/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661872982978821, 'Val/mean miou_metric': 0.9470705986022949, 'Val/mean f1': 0.9718142151832581, 'Val/mean precision': 0.9687378406524658, 'Val/mean recall': 0.9749100804328918, 'Val/mean hd95_metric': 7.053030490875244} +Epoch [1367/4000] Training [1/16] Loss: 0.00745 +Epoch [1367/4000] Training [2/16] Loss: 0.00795 +Epoch [1367/4000] Training [3/16] Loss: 0.01060 +Epoch [1367/4000] Training [4/16] Loss: 0.01474 +Epoch [1367/4000] Training [5/16] Loss: 0.01979 +Epoch [1367/4000] Training [6/16] Loss: 0.00964 +Epoch [1367/4000] Training [7/16] Loss: 0.01212 +Epoch [1367/4000] Training [8/16] Loss: 0.00816 +Epoch [1367/4000] Training [9/16] Loss: 0.01460 +Epoch [1367/4000] Training [10/16] Loss: 0.11306 +Epoch [1367/4000] Training [11/16] Loss: 0.01426 +Epoch [1367/4000] Training [12/16] Loss: 0.00991 +Epoch [1367/4000] Training [13/16] Loss: 0.09090 +Epoch [1367/4000] Training [14/16] Loss: 0.00865 +Epoch [1367/4000] Training [15/16] Loss: 0.00850 +Epoch [1367/4000] Training [16/16] Loss: 0.00962 +Epoch [1367/4000] Training metric {'Train/mean dice_metric': 0.9915052652359009, 'Train/mean miou_metric': 0.9832748174667358, 'Train/mean f1': 0.98701411485672, 'Train/mean precision': 0.9839286804199219, 'Train/mean recall': 0.9901189208030701, 'Train/mean hd95_metric': 2.142219305038452} +Epoch [1367/4000] Validation [1/4] Loss: 0.34452 focal_loss 0.25375 dice_loss 0.09077 +Epoch [1367/4000] Validation [2/4] Loss: 0.31308 focal_loss 0.16659 dice_loss 0.14648 +Epoch [1367/4000] Validation [3/4] Loss: 0.24713 focal_loss 0.15019 dice_loss 0.09693 +Epoch [1367/4000] Validation [4/4] Loss: 0.35195 focal_loss 0.20827 dice_loss 0.14369 +Epoch [1367/4000] Validation metric {'Val/mean dice_metric': 0.9659019708633423, 'Val/mean miou_metric': 0.9452922940254211, 'Val/mean f1': 0.9673814177513123, 'Val/mean precision': 0.9686510562896729, 'Val/mean recall': 0.9661151170730591, 'Val/mean hd95_metric': 7.1728668212890625} +Cheakpoint... +Epoch [1367/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9659019708633423, 'Val/mean miou_metric': 0.9452922940254211, 'Val/mean f1': 0.9673814177513123, 'Val/mean precision': 0.9686510562896729, 'Val/mean recall': 0.9661151170730591, 'Val/mean hd95_metric': 7.1728668212890625} +Epoch [1368/4000] Training [1/16] Loss: 0.01253 +Epoch [1368/4000] Training [2/16] Loss: 0.01609 +Epoch [1368/4000] Training [3/16] Loss: 0.01014 +Epoch [1368/4000] Training [4/16] Loss: 0.01077 +Epoch [1368/4000] Training [5/16] Loss: 0.01186 +Epoch [1368/4000] Training [6/16] Loss: 0.01324 +Epoch [1368/4000] Training [7/16] Loss: 0.01141 +Epoch [1368/4000] Training [8/16] Loss: 0.01368 +Epoch [1368/4000] Training [9/16] Loss: 0.02407 +Epoch [1368/4000] Training [10/16] Loss: 0.01016 +Epoch [1368/4000] Training [11/16] Loss: 0.01091 +Epoch [1368/4000] Training [12/16] Loss: 0.01093 +Epoch [1368/4000] Training [13/16] Loss: 0.01465 +Epoch [1368/4000] Training [14/16] Loss: 0.01141 +Epoch [1368/4000] Training [15/16] Loss: 0.03959 +Epoch [1368/4000] Training [16/16] Loss: 0.01136 +Epoch [1368/4000] Training metric {'Train/mean dice_metric': 0.9891383647918701, 'Train/mean miou_metric': 0.9790927171707153, 'Train/mean f1': 0.9853211045265198, 'Train/mean precision': 0.9797245860099792, 'Train/mean recall': 0.990981936454773, 'Train/mean hd95_metric': 3.5453686714172363} +Epoch [1368/4000] Validation [1/4] Loss: 0.97799 focal_loss 0.75574 dice_loss 0.22225 +Epoch [1368/4000] Validation [2/4] Loss: 0.68872 focal_loss 0.40896 dice_loss 0.27976 +Epoch [1368/4000] Validation [3/4] Loss: 0.21491 focal_loss 0.13037 dice_loss 0.08454 +Epoch [1368/4000] Validation [4/4] Loss: 0.38519 focal_loss 0.24182 dice_loss 0.14338 +Epoch [1368/4000] Validation metric {'Val/mean dice_metric': 0.9545745849609375, 'Val/mean miou_metric': 0.9302611351013184, 'Val/mean f1': 0.9559881687164307, 'Val/mean precision': 0.9641477465629578, 'Val/mean recall': 0.9479653835296631, 'Val/mean hd95_metric': 9.997553825378418} +Cheakpoint... +Epoch [1368/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9546], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9545745849609375, 'Val/mean miou_metric': 0.9302611351013184, 'Val/mean f1': 0.9559881687164307, 'Val/mean precision': 0.9641477465629578, 'Val/mean recall': 0.9479653835296631, 'Val/mean hd95_metric': 9.997553825378418} +Epoch [1369/4000] Training [1/16] Loss: 0.01305 +Epoch [1369/4000] Training [2/16] Loss: 0.01878 +Epoch [1369/4000] Training [3/16] Loss: 0.01463 +Epoch [1369/4000] Training [4/16] Loss: 0.01407 +Epoch [1369/4000] Training [5/16] Loss: 0.01002 +Epoch [1369/4000] Training [6/16] Loss: 0.01119 +Epoch [1369/4000] Training [7/16] Loss: 0.01188 +Epoch [1369/4000] Training [8/16] Loss: 0.00912 +Epoch [1369/4000] Training [9/16] Loss: 0.01116 +Epoch [1369/4000] Training [10/16] Loss: 0.01123 +Epoch [1369/4000] Training [11/16] Loss: 0.04322 +Epoch [1369/4000] Training [12/16] Loss: 0.01188 +Epoch [1369/4000] Training [13/16] Loss: 0.00970 +Epoch [1369/4000] Training [14/16] Loss: 0.00807 +Epoch [1369/4000] Training [15/16] Loss: 0.01003 +Epoch [1369/4000] Training [16/16] Loss: 0.01023 +Epoch [1369/4000] Training metric {'Train/mean dice_metric': 0.9901633262634277, 'Train/mean miou_metric': 0.9811853170394897, 'Train/mean f1': 0.9858454465866089, 'Train/mean precision': 0.9830906391143799, 'Train/mean recall': 0.9886157512664795, 'Train/mean hd95_metric': 3.2597153186798096} +Epoch [1369/4000] Validation [1/4] Loss: 0.20222 focal_loss 0.12563 dice_loss 0.07658 +Epoch [1369/4000] Validation [2/4] Loss: 0.36369 focal_loss 0.17005 dice_loss 0.19364 +Epoch [1369/4000] Validation [3/4] Loss: 0.14662 focal_loss 0.07671 dice_loss 0.06991 +Epoch [1369/4000] Validation [4/4] Loss: 0.56202 focal_loss 0.31507 dice_loss 0.24694 +Epoch [1369/4000] Validation metric {'Val/mean dice_metric': 0.9647639393806458, 'Val/mean miou_metric': 0.9437686800956726, 'Val/mean f1': 0.9645456075668335, 'Val/mean precision': 0.9559987783432007, 'Val/mean recall': 0.9732467532157898, 'Val/mean hd95_metric': 8.994460105895996} +Cheakpoint... +Epoch [1369/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647639393806458, 'Val/mean miou_metric': 0.9437686800956726, 'Val/mean f1': 0.9645456075668335, 'Val/mean precision': 0.9559987783432007, 'Val/mean recall': 0.9732467532157898, 'Val/mean hd95_metric': 8.994460105895996} +Epoch [1370/4000] Training [1/16] Loss: 0.00784 +Epoch [1370/4000] Training [2/16] Loss: 0.01202 +Epoch [1370/4000] Training [3/16] Loss: 0.00912 +Epoch [1370/4000] Training [4/16] Loss: 0.00851 +Epoch [1370/4000] Training [5/16] Loss: 0.01445 +Epoch [1370/4000] Training [6/16] Loss: 0.01094 +Epoch [1370/4000] Training [7/16] Loss: 0.06478 +Epoch [1370/4000] Training [8/16] Loss: 0.01256 +Epoch [1370/4000] Training [9/16] Loss: 0.02789 +Epoch [1370/4000] Training [10/16] Loss: 0.01131 +Epoch [1370/4000] Training [11/16] Loss: 0.00862 +Epoch [1370/4000] Training [12/16] Loss: 0.00994 +Epoch [1370/4000] Training [13/16] Loss: 0.01011 +Epoch [1370/4000] Training [14/16] Loss: 0.01304 +Epoch [1370/4000] Training [15/16] Loss: 0.01666 +Epoch [1370/4000] Training [16/16] Loss: 0.01459 +Epoch [1370/4000] Training metric {'Train/mean dice_metric': 0.9903179407119751, 'Train/mean miou_metric': 0.9812744855880737, 'Train/mean f1': 0.9860774874687195, 'Train/mean precision': 0.9805329442024231, 'Train/mean recall': 0.9916850924491882, 'Train/mean hd95_metric': 2.6527462005615234} +Epoch [1370/4000] Validation [1/4] Loss: 0.28792 focal_loss 0.20342 dice_loss 0.08449 +Epoch [1370/4000] Validation [2/4] Loss: 0.81091 focal_loss 0.50134 dice_loss 0.30958 +Epoch [1370/4000] Validation [3/4] Loss: 0.32370 focal_loss 0.21215 dice_loss 0.11155 +Epoch [1370/4000] Validation [4/4] Loss: 0.23882 focal_loss 0.11637 dice_loss 0.12245 +Epoch [1370/4000] Validation metric {'Val/mean dice_metric': 0.9629675149917603, 'Val/mean miou_metric': 0.941900372505188, 'Val/mean f1': 0.9654229283332825, 'Val/mean precision': 0.95947265625, 'Val/mean recall': 0.9714472889900208, 'Val/mean hd95_metric': 7.7516632080078125} +Cheakpoint... +Epoch [1370/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9630], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9629675149917603, 'Val/mean miou_metric': 0.941900372505188, 'Val/mean f1': 0.9654229283332825, 'Val/mean precision': 0.95947265625, 'Val/mean recall': 0.9714472889900208, 'Val/mean hd95_metric': 7.7516632080078125} +Epoch [1371/4000] Training [1/16] Loss: 0.01297 +Epoch [1371/4000] Training [2/16] Loss: 0.01111 +Epoch [1371/4000] Training [3/16] Loss: 0.01142 +Epoch [1371/4000] Training [4/16] Loss: 0.00920 +Epoch [1371/4000] Training [5/16] Loss: 0.01036 +Epoch [1371/4000] Training [6/16] Loss: 0.00785 +Epoch [1371/4000] Training [7/16] Loss: 0.03396 +Epoch [1371/4000] Training [8/16] Loss: 0.01250 +Epoch [1371/4000] Training [9/16] Loss: 0.01086 +Epoch [1371/4000] Training [10/16] Loss: 0.01712 +Epoch [1371/4000] Training [11/16] Loss: 0.01073 +Epoch [1371/4000] Training [12/16] Loss: 0.01630 +Epoch [1371/4000] Training [13/16] Loss: 0.01048 +Epoch [1371/4000] Training [14/16] Loss: 0.01292 +Epoch [1371/4000] Training [15/16] Loss: 0.01257 +Epoch [1371/4000] Training [16/16] Loss: 0.01140 +Epoch [1371/4000] Training metric {'Train/mean dice_metric': 0.9912118911743164, 'Train/mean miou_metric': 0.9825783967971802, 'Train/mean f1': 0.9873261451721191, 'Train/mean precision': 0.9830642938613892, 'Train/mean recall': 0.9916250109672546, 'Train/mean hd95_metric': 2.2524430751800537} +Epoch [1371/4000] Validation [1/4] Loss: 0.16253 focal_loss 0.09889 dice_loss 0.06364 +Epoch [1371/4000] Validation [2/4] Loss: 0.26295 focal_loss 0.12350 dice_loss 0.13945 +Epoch [1371/4000] Validation [3/4] Loss: 0.17455 focal_loss 0.10808 dice_loss 0.06648 +Epoch [1371/4000] Validation [4/4] Loss: 0.27000 focal_loss 0.13808 dice_loss 0.13192 +Epoch [1371/4000] Validation metric {'Val/mean dice_metric': 0.9675474166870117, 'Val/mean miou_metric': 0.9467803835868835, 'Val/mean f1': 0.9678370356559753, 'Val/mean precision': 0.9592150449752808, 'Val/mean recall': 0.9766154885292053, 'Val/mean hd95_metric': 7.631180763244629} +Cheakpoint... +Epoch [1371/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675474166870117, 'Val/mean miou_metric': 0.9467803835868835, 'Val/mean f1': 0.9678370356559753, 'Val/mean precision': 0.9592150449752808, 'Val/mean recall': 0.9766154885292053, 'Val/mean hd95_metric': 7.631180763244629} +Epoch [1372/4000] Training [1/16] Loss: 0.01283 +Epoch [1372/4000] Training [2/16] Loss: 0.01020 +Epoch [1372/4000] Training [3/16] Loss: 0.03110 +Epoch [1372/4000] Training [4/16] Loss: 0.01003 +Epoch [1372/4000] Training [5/16] Loss: 0.00929 +Epoch [1372/4000] Training [6/16] Loss: 0.01918 +Epoch [1372/4000] Training [7/16] Loss: 0.01220 +Epoch [1372/4000] Training [8/16] Loss: 0.01643 +Epoch [1372/4000] Training [9/16] Loss: 0.01198 +Epoch [1372/4000] Training [10/16] Loss: 0.00849 +Epoch [1372/4000] Training [11/16] Loss: 0.00862 +Epoch [1372/4000] Training [12/16] Loss: 0.00977 +Epoch [1372/4000] Training [13/16] Loss: 0.00863 +Epoch [1372/4000] Training [14/16] Loss: 0.01213 +Epoch [1372/4000] Training [15/16] Loss: 0.01529 +Epoch [1372/4000] Training [16/16] Loss: 0.01747 +Epoch [1372/4000] Training metric {'Train/mean dice_metric': 0.9915313720703125, 'Train/mean miou_metric': 0.9831597805023193, 'Train/mean f1': 0.9868992567062378, 'Train/mean precision': 0.9816965460777283, 'Train/mean recall': 0.9921574592590332, 'Train/mean hd95_metric': 1.5420852899551392} +Epoch [1372/4000] Validation [1/4] Loss: 0.24840 focal_loss 0.16503 dice_loss 0.08338 +Epoch [1372/4000] Validation [2/4] Loss: 0.73478 focal_loss 0.41076 dice_loss 0.32402 +Epoch [1372/4000] Validation [3/4] Loss: 0.12394 focal_loss 0.07046 dice_loss 0.05348 +Epoch [1372/4000] Validation [4/4] Loss: 0.25003 focal_loss 0.15752 dice_loss 0.09252 +Epoch [1372/4000] Validation metric {'Val/mean dice_metric': 0.965184211730957, 'Val/mean miou_metric': 0.9443863034248352, 'Val/mean f1': 0.9667014479637146, 'Val/mean precision': 0.9672812819480896, 'Val/mean recall': 0.9661223292350769, 'Val/mean hd95_metric': 7.119368076324463} +Cheakpoint... +Epoch [1372/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9652], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965184211730957, 'Val/mean miou_metric': 0.9443863034248352, 'Val/mean f1': 0.9667014479637146, 'Val/mean precision': 0.9672812819480896, 'Val/mean recall': 0.9661223292350769, 'Val/mean hd95_metric': 7.119368076324463} +Epoch [1373/4000] Training [1/16] Loss: 0.01523 +Epoch [1373/4000] Training [2/16] Loss: 0.01352 +Epoch [1373/4000] Training [3/16] Loss: 0.01509 +Epoch [1373/4000] Training [4/16] Loss: 0.00972 +Epoch [1373/4000] Training [5/16] Loss: 0.00952 +Epoch [1373/4000] Training [6/16] Loss: 0.00986 +Epoch [1373/4000] Training [7/16] Loss: 0.05605 +Epoch [1373/4000] Training [8/16] Loss: 0.00774 +Epoch [1373/4000] Training [9/16] Loss: 0.00915 +Epoch [1373/4000] Training [10/16] Loss: 0.01006 +Epoch [1373/4000] Training [11/16] Loss: 0.00950 +Epoch [1373/4000] Training [12/16] Loss: 0.01044 +Epoch [1373/4000] Training [13/16] Loss: 0.01301 +Epoch [1373/4000] Training [14/16] Loss: 0.01190 +Epoch [1373/4000] Training [15/16] Loss: 0.01639 +Epoch [1373/4000] Training [16/16] Loss: 0.00815 +Epoch [1373/4000] Training metric {'Train/mean dice_metric': 0.9919731020927429, 'Train/mean miou_metric': 0.9838950634002686, 'Train/mean f1': 0.9872109889984131, 'Train/mean precision': 0.9830897450447083, 'Train/mean recall': 0.9913669228553772, 'Train/mean hd95_metric': 1.6611547470092773} +Epoch [1373/4000] Validation [1/4] Loss: 0.22476 focal_loss 0.15136 dice_loss 0.07340 +Epoch [1373/4000] Validation [2/4] Loss: 0.31007 focal_loss 0.15897 dice_loss 0.15110 +Epoch [1373/4000] Validation [3/4] Loss: 0.20288 focal_loss 0.11625 dice_loss 0.08663 +Epoch [1373/4000] Validation [4/4] Loss: 0.17878 focal_loss 0.08697 dice_loss 0.09181 +Epoch [1373/4000] Validation metric {'Val/mean dice_metric': 0.9683722257614136, 'Val/mean miou_metric': 0.9477061033248901, 'Val/mean f1': 0.9678493738174438, 'Val/mean precision': 0.9608917236328125, 'Val/mean recall': 0.9749084711074829, 'Val/mean hd95_metric': 7.334425449371338} +Cheakpoint... +Epoch [1373/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683722257614136, 'Val/mean miou_metric': 0.9477061033248901, 'Val/mean f1': 0.9678493738174438, 'Val/mean precision': 0.9608917236328125, 'Val/mean recall': 0.9749084711074829, 'Val/mean hd95_metric': 7.334425449371338} +Epoch [1374/4000] Training [1/16] Loss: 0.00999 +Epoch [1374/4000] Training [2/16] Loss: 0.00760 +Epoch [1374/4000] Training [3/16] Loss: 0.00815 +Epoch [1374/4000] Training [4/16] Loss: 0.01354 +Epoch [1374/4000] Training [5/16] Loss: 0.01129 +Epoch [1374/4000] Training [6/16] Loss: 0.01035 +Epoch [1374/4000] Training [7/16] Loss: 0.01240 +Epoch [1374/4000] Training [8/16] Loss: 0.01075 +Epoch [1374/4000] Training [9/16] Loss: 0.00883 +Epoch [1374/4000] Training [10/16] Loss: 0.02171 +Epoch [1374/4000] Training [11/16] Loss: 0.00868 +Epoch [1374/4000] Training [12/16] Loss: 0.01179 +Epoch [1374/4000] Training [13/16] Loss: 0.00827 +Epoch [1374/4000] Training [14/16] Loss: 0.01448 +Epoch [1374/4000] Training [15/16] Loss: 0.01147 +Epoch [1374/4000] Training [16/16] Loss: 0.01169 +Epoch [1374/4000] Training metric {'Train/mean dice_metric': 0.9925779104232788, 'Train/mean miou_metric': 0.9850572943687439, 'Train/mean f1': 0.9887021780014038, 'Train/mean precision': 0.9841375946998596, 'Train/mean recall': 0.9933092594146729, 'Train/mean hd95_metric': 1.7659238576889038} +Epoch [1374/4000] Validation [1/4] Loss: 0.27407 focal_loss 0.19385 dice_loss 0.08022 +Epoch [1374/4000] Validation [2/4] Loss: 0.49932 focal_loss 0.27583 dice_loss 0.22349 +Epoch [1374/4000] Validation [3/4] Loss: 0.32370 focal_loss 0.21140 dice_loss 0.11231 +Epoch [1374/4000] Validation [4/4] Loss: 0.17145 focal_loss 0.08809 dice_loss 0.08336 +Epoch [1374/4000] Validation metric {'Val/mean dice_metric': 0.9687089920043945, 'Val/mean miou_metric': 0.9490184783935547, 'Val/mean f1': 0.9690032005310059, 'Val/mean precision': 0.9617436528205872, 'Val/mean recall': 0.9763731956481934, 'Val/mean hd95_metric': 7.552380561828613} +Cheakpoint... +Epoch [1374/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687089920043945, 'Val/mean miou_metric': 0.9490184783935547, 'Val/mean f1': 0.9690032005310059, 'Val/mean precision': 0.9617436528205872, 'Val/mean recall': 0.9763731956481934, 'Val/mean hd95_metric': 7.552380561828613} +Epoch [1375/4000] Training [1/16] Loss: 0.00889 +Epoch [1375/4000] Training [2/16] Loss: 0.00953 +Epoch [1375/4000] Training [3/16] Loss: 0.00860 +Epoch [1375/4000] Training [4/16] Loss: 0.01138 +Epoch [1375/4000] Training [5/16] Loss: 0.00981 +Epoch [1375/4000] Training [6/16] Loss: 0.00793 +Epoch [1375/4000] Training [7/16] Loss: 0.01344 +Epoch [1375/4000] Training [8/16] Loss: 0.01414 +Epoch [1375/4000] Training [9/16] Loss: 0.01305 +Epoch [1375/4000] Training [10/16] Loss: 0.00765 +Epoch [1375/4000] Training [11/16] Loss: 0.00880 +Epoch [1375/4000] Training [12/16] Loss: 0.01230 +Epoch [1375/4000] Training [13/16] Loss: 0.00929 +Epoch [1375/4000] Training [14/16] Loss: 0.01128 +Epoch [1375/4000] Training [15/16] Loss: 0.01103 +Epoch [1375/4000] Training [16/16] Loss: 0.00882 +Epoch [1375/4000] Training metric {'Train/mean dice_metric': 0.9930269122123718, 'Train/mean miou_metric': 0.9859184622764587, 'Train/mean f1': 0.9890020489692688, 'Train/mean precision': 0.9844772219657898, 'Train/mean recall': 0.9935687184333801, 'Train/mean hd95_metric': 1.1580173969268799} +Epoch [1375/4000] Validation [1/4] Loss: 0.24914 focal_loss 0.17709 dice_loss 0.07205 +Epoch [1375/4000] Validation [2/4] Loss: 0.19231 focal_loss 0.08635 dice_loss 0.10596 +Epoch [1375/4000] Validation [3/4] Loss: 0.34027 focal_loss 0.23775 dice_loss 0.10252 +Epoch [1375/4000] Validation [4/4] Loss: 0.17142 focal_loss 0.08634 dice_loss 0.08508 +Epoch [1375/4000] Validation metric {'Val/mean dice_metric': 0.9703463315963745, 'Val/mean miou_metric': 0.9510844349861145, 'Val/mean f1': 0.9712532758712769, 'Val/mean precision': 0.9657690525054932, 'Val/mean recall': 0.9768001437187195, 'Val/mean hd95_metric': 6.882229804992676} +Cheakpoint... +Epoch [1375/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703463315963745, 'Val/mean miou_metric': 0.9510844349861145, 'Val/mean f1': 0.9712532758712769, 'Val/mean precision': 0.9657690525054932, 'Val/mean recall': 0.9768001437187195, 'Val/mean hd95_metric': 6.882229804992676} +Epoch [1376/4000] Training [1/16] Loss: 0.00968 +Epoch [1376/4000] Training [2/16] Loss: 0.00754 +Epoch [1376/4000] Training [3/16] Loss: 0.00759 +Epoch [1376/4000] Training [4/16] Loss: 0.01049 +Epoch [1376/4000] Training [5/16] Loss: 0.00757 +Epoch [1376/4000] Training [6/16] Loss: 0.00957 +Epoch [1376/4000] Training [7/16] Loss: 0.00935 +Epoch [1376/4000] Training [8/16] Loss: 0.01064 +Epoch [1376/4000] Training [9/16] Loss: 0.00873 +Epoch [1376/4000] Training [10/16] Loss: 0.00780 +Epoch [1376/4000] Training [11/16] Loss: 0.00917 +Epoch [1376/4000] Training [12/16] Loss: 0.00972 +Epoch [1376/4000] Training [13/16] Loss: 0.00961 +Epoch [1376/4000] Training [14/16] Loss: 0.01174 +Epoch [1376/4000] Training [15/16] Loss: 0.00942 +Epoch [1376/4000] Training [16/16] Loss: 0.00814 +Epoch [1376/4000] Training metric {'Train/mean dice_metric': 0.9935691356658936, 'Train/mean miou_metric': 0.9869617819786072, 'Train/mean f1': 0.9889489412307739, 'Train/mean precision': 0.9838835597038269, 'Train/mean recall': 0.9940668344497681, 'Train/mean hd95_metric': 1.097804069519043} +Epoch [1376/4000] Validation [1/4] Loss: 0.24881 focal_loss 0.18022 dice_loss 0.06859 +Epoch [1376/4000] Validation [2/4] Loss: 0.20723 focal_loss 0.10344 dice_loss 0.10379 +Epoch [1376/4000] Validation [3/4] Loss: 0.18417 focal_loss 0.10128 dice_loss 0.08289 +Epoch [1376/4000] Validation [4/4] Loss: 0.30058 focal_loss 0.16574 dice_loss 0.13484 +Epoch [1376/4000] Validation metric {'Val/mean dice_metric': 0.9700679779052734, 'Val/mean miou_metric': 0.9513686895370483, 'Val/mean f1': 0.9697286486625671, 'Val/mean precision': 0.9615363478660583, 'Val/mean recall': 0.9780617356300354, 'Val/mean hd95_metric': 6.4198713302612305} +Cheakpoint... +Epoch [1376/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700679779052734, 'Val/mean miou_metric': 0.9513686895370483, 'Val/mean f1': 0.9697286486625671, 'Val/mean precision': 0.9615363478660583, 'Val/mean recall': 0.9780617356300354, 'Val/mean hd95_metric': 6.4198713302612305} +Epoch [1377/4000] Training [1/16] Loss: 0.00853 +Epoch [1377/4000] Training [2/16] Loss: 0.00687 +Epoch [1377/4000] Training [3/16] Loss: 0.00865 +Epoch [1377/4000] Training [4/16] Loss: 0.01257 +Epoch [1377/4000] Training [5/16] Loss: 0.01122 +Epoch [1377/4000] Training [6/16] Loss: 0.00764 +Epoch [1377/4000] Training [7/16] Loss: 0.02099 +Epoch [1377/4000] Training [8/16] Loss: 0.00837 +Epoch [1377/4000] Training [9/16] Loss: 0.00724 +Epoch [1377/4000] Training [10/16] Loss: 0.01425 +Epoch [1377/4000] Training [11/16] Loss: 0.00862 +Epoch [1377/4000] Training [12/16] Loss: 0.00874 +Epoch [1377/4000] Training [13/16] Loss: 0.00671 +Epoch [1377/4000] Training [14/16] Loss: 0.00775 +Epoch [1377/4000] Training [15/16] Loss: 0.00949 +Epoch [1377/4000] Training [16/16] Loss: 0.00868 +Epoch [1377/4000] Training metric {'Train/mean dice_metric': 0.9938617944717407, 'Train/mean miou_metric': 0.9875525236129761, 'Train/mean f1': 0.9895941019058228, 'Train/mean precision': 0.9848533272743225, 'Train/mean recall': 0.9943807721138, 'Train/mean hd95_metric': 1.2427788972854614} +Epoch [1377/4000] Validation [1/4] Loss: 0.16607 focal_loss 0.10971 dice_loss 0.05637 +Epoch [1377/4000] Validation [2/4] Loss: 0.19644 focal_loss 0.08788 dice_loss 0.10857 +Epoch [1377/4000] Validation [3/4] Loss: 0.14768 focal_loss 0.08310 dice_loss 0.06457 +Epoch [1377/4000] Validation [4/4] Loss: 0.22202 focal_loss 0.13005 dice_loss 0.09197 +Epoch [1377/4000] Validation metric {'Val/mean dice_metric': 0.971888542175293, 'Val/mean miou_metric': 0.9539492726325989, 'Val/mean f1': 0.9731951951980591, 'Val/mean precision': 0.967793345451355, 'Val/mean recall': 0.978657603263855, 'Val/mean hd95_metric': 6.289221286773682} +Cheakpoint... +Epoch [1377/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971888542175293, 'Val/mean miou_metric': 0.9539492726325989, 'Val/mean f1': 0.9731951951980591, 'Val/mean precision': 0.967793345451355, 'Val/mean recall': 0.978657603263855, 'Val/mean hd95_metric': 6.289221286773682} +Epoch [1378/4000] Training [1/16] Loss: 0.01010 +Epoch [1378/4000] Training [2/16] Loss: 0.00821 +Epoch [1378/4000] Training [3/16] Loss: 0.01001 +Epoch [1378/4000] Training [4/16] Loss: 0.00665 +Epoch [1378/4000] Training [5/16] Loss: 0.00737 +Epoch [1378/4000] Training [6/16] Loss: 0.00859 +Epoch [1378/4000] Training [7/16] Loss: 0.00761 +Epoch [1378/4000] Training [8/16] Loss: 0.00883 +Epoch [1378/4000] Training [9/16] Loss: 0.00903 +Epoch [1378/4000] Training [10/16] Loss: 0.00823 +Epoch [1378/4000] Training [11/16] Loss: 0.00782 +Epoch [1378/4000] Training [12/16] Loss: 0.00878 +Epoch [1378/4000] Training [13/16] Loss: 0.00902 +Epoch [1378/4000] Training [14/16] Loss: 0.00759 +Epoch [1378/4000] Training [15/16] Loss: 0.00604 +Epoch [1378/4000] Training [16/16] Loss: 0.00806 +Epoch [1378/4000] Training metric {'Train/mean dice_metric': 0.9942668676376343, 'Train/mean miou_metric': 0.9883525371551514, 'Train/mean f1': 0.9901911616325378, 'Train/mean precision': 0.9857648611068726, 'Train/mean recall': 0.9946574568748474, 'Train/mean hd95_metric': 1.37947678565979} +Epoch [1378/4000] Validation [1/4] Loss: 0.20664 focal_loss 0.13650 dice_loss 0.07013 +Epoch [1378/4000] Validation [2/4] Loss: 0.23233 focal_loss 0.11617 dice_loss 0.11616 +Epoch [1378/4000] Validation [3/4] Loss: 0.21991 focal_loss 0.12039 dice_loss 0.09952 +Epoch [1378/4000] Validation [4/4] Loss: 0.21928 focal_loss 0.11931 dice_loss 0.09997 +Epoch [1378/4000] Validation metric {'Val/mean dice_metric': 0.9722833633422852, 'Val/mean miou_metric': 0.9541925191879272, 'Val/mean f1': 0.97260582447052, 'Val/mean precision': 0.9666271805763245, 'Val/mean recall': 0.9786587953567505, 'Val/mean hd95_metric': 6.227750301361084} +Cheakpoint... +Epoch [1378/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722833633422852, 'Val/mean miou_metric': 0.9541925191879272, 'Val/mean f1': 0.97260582447052, 'Val/mean precision': 0.9666271805763245, 'Val/mean recall': 0.9786587953567505, 'Val/mean hd95_metric': 6.227750301361084} +Epoch [1379/4000] Training [1/16] Loss: 0.00665 +Epoch [1379/4000] Training [2/16] Loss: 0.00887 +Epoch [1379/4000] Training [3/16] Loss: 0.01031 +Epoch [1379/4000] Training [4/16] Loss: 0.00996 +Epoch [1379/4000] Training [5/16] Loss: 0.00785 +Epoch [1379/4000] Training [6/16] Loss: 0.01039 +Epoch [1379/4000] Training [7/16] Loss: 0.01228 +Epoch [1379/4000] Training [8/16] Loss: 0.00779 +Epoch [1379/4000] Training [9/16] Loss: 0.01408 +Epoch [1379/4000] Training [10/16] Loss: 0.00961 +Epoch [1379/4000] Training [11/16] Loss: 0.00733 +Epoch [1379/4000] Training [12/16] Loss: 0.00944 +Epoch [1379/4000] Training [13/16] Loss: 0.00998 +Epoch [1379/4000] Training [14/16] Loss: 0.00898 +Epoch [1379/4000] Training [15/16] Loss: 0.01007 +Epoch [1379/4000] Training [16/16] Loss: 0.01002 +Epoch [1379/4000] Training metric {'Train/mean dice_metric': 0.9937363862991333, 'Train/mean miou_metric': 0.9873141050338745, 'Train/mean f1': 0.9899510741233826, 'Train/mean precision': 0.9852514266967773, 'Train/mean recall': 0.9946958422660828, 'Train/mean hd95_metric': 1.0502097606658936} +Epoch [1379/4000] Validation [1/4] Loss: 0.21921 focal_loss 0.15328 dice_loss 0.06593 +Epoch [1379/4000] Validation [2/4] Loss: 0.21409 focal_loss 0.10187 dice_loss 0.11222 +Epoch [1379/4000] Validation [3/4] Loss: 0.18671 focal_loss 0.10484 dice_loss 0.08187 +Epoch [1379/4000] Validation [4/4] Loss: 0.16963 focal_loss 0.09080 dice_loss 0.07883 +Epoch [1379/4000] Validation metric {'Val/mean dice_metric': 0.9720308184623718, 'Val/mean miou_metric': 0.9539515376091003, 'Val/mean f1': 0.9731445908546448, 'Val/mean precision': 0.9672985672950745, 'Val/mean recall': 0.9790616631507874, 'Val/mean hd95_metric': 5.485311985015869} +Cheakpoint... +Epoch [1379/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720308184623718, 'Val/mean miou_metric': 0.9539515376091003, 'Val/mean f1': 0.9731445908546448, 'Val/mean precision': 0.9672985672950745, 'Val/mean recall': 0.9790616631507874, 'Val/mean hd95_metric': 5.485311985015869} +Epoch [1380/4000] Training [1/16] Loss: 0.00635 +Epoch [1380/4000] Training [2/16] Loss: 0.00848 +Epoch [1380/4000] Training [3/16] Loss: 0.00615 +Epoch [1380/4000] Training [4/16] Loss: 0.01030 +Epoch [1380/4000] Training [5/16] Loss: 0.00835 +Epoch [1380/4000] Training [6/16] Loss: 0.00972 +Epoch [1380/4000] Training [7/16] Loss: 0.00972 +Epoch [1380/4000] Training [8/16] Loss: 0.00901 +Epoch [1380/4000] Training [9/16] Loss: 0.00733 +Epoch [1380/4000] Training [10/16] Loss: 0.00887 +Epoch [1380/4000] Training [11/16] Loss: 0.00986 +Epoch [1380/4000] Training [12/16] Loss: 0.00897 +Epoch [1380/4000] Training [13/16] Loss: 0.00840 +Epoch [1380/4000] Training [14/16] Loss: 0.01001 +Epoch [1380/4000] Training [15/16] Loss: 0.01021 +Epoch [1380/4000] Training [16/16] Loss: 0.01007 +Epoch [1380/4000] Training metric {'Train/mean dice_metric': 0.9938232898712158, 'Train/mean miou_metric': 0.9874764084815979, 'Train/mean f1': 0.9899477362632751, 'Train/mean precision': 0.9854190349578857, 'Train/mean recall': 0.9945182800292969, 'Train/mean hd95_metric': 1.0579307079315186} +Epoch [1380/4000] Validation [1/4] Loss: 0.20553 focal_loss 0.14244 dice_loss 0.06309 +Epoch [1380/4000] Validation [2/4] Loss: 0.39288 focal_loss 0.21925 dice_loss 0.17362 +Epoch [1380/4000] Validation [3/4] Loss: 0.27269 focal_loss 0.18213 dice_loss 0.09056 +Epoch [1380/4000] Validation [4/4] Loss: 0.19344 focal_loss 0.11384 dice_loss 0.07961 +Epoch [1380/4000] Validation metric {'Val/mean dice_metric': 0.9703227281570435, 'Val/mean miou_metric': 0.9519580006599426, 'Val/mean f1': 0.97222900390625, 'Val/mean precision': 0.9666936993598938, 'Val/mean recall': 0.9778280258178711, 'Val/mean hd95_metric': 5.908985614776611} +Cheakpoint... +Epoch [1380/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703227281570435, 'Val/mean miou_metric': 0.9519580006599426, 'Val/mean f1': 0.97222900390625, 'Val/mean precision': 0.9666936993598938, 'Val/mean recall': 0.9778280258178711, 'Val/mean hd95_metric': 5.908985614776611} +Epoch [1381/4000] Training [1/16] Loss: 0.01257 +Epoch [1381/4000] Training [2/16] Loss: 0.00966 +Epoch [1381/4000] Training [3/16] Loss: 0.00834 +Epoch [1381/4000] Training [4/16] Loss: 0.00804 +Epoch [1381/4000] Training [5/16] Loss: 0.01074 +Epoch [1381/4000] Training [6/16] Loss: 0.00888 +Epoch [1381/4000] Training [7/16] Loss: 0.00928 +Epoch [1381/4000] Training [8/16] Loss: 0.00812 +Epoch [1381/4000] Training [9/16] Loss: 0.00862 +Epoch [1381/4000] Training [10/16] Loss: 0.00707 +Epoch [1381/4000] Training [11/16] Loss: 0.00932 +Epoch [1381/4000] Training [12/16] Loss: 0.00798 +Epoch [1381/4000] Training [13/16] Loss: 0.00815 +Epoch [1381/4000] Training [14/16] Loss: 0.00954 +Epoch [1381/4000] Training [15/16] Loss: 0.00971 +Epoch [1381/4000] Training [16/16] Loss: 0.00906 +Epoch [1381/4000] Training metric {'Train/mean dice_metric': 0.9936076402664185, 'Train/mean miou_metric': 0.987069308757782, 'Train/mean f1': 0.9898642301559448, 'Train/mean precision': 0.9855080246925354, 'Train/mean recall': 0.9942591786384583, 'Train/mean hd95_metric': 1.1092935800552368} +Epoch [1381/4000] Validation [1/4] Loss: 0.15176 focal_loss 0.09694 dice_loss 0.05482 +Epoch [1381/4000] Validation [2/4] Loss: 0.28668 focal_loss 0.15631 dice_loss 0.13036 +Epoch [1381/4000] Validation [3/4] Loss: 0.18336 focal_loss 0.10464 dice_loss 0.07872 +Epoch [1381/4000] Validation [4/4] Loss: 0.18097 focal_loss 0.09469 dice_loss 0.08628 +Epoch [1381/4000] Validation metric {'Val/mean dice_metric': 0.9709793329238892, 'Val/mean miou_metric': 0.9523893594741821, 'Val/mean f1': 0.9723997712135315, 'Val/mean precision': 0.9656177759170532, 'Val/mean recall': 0.9792776703834534, 'Val/mean hd95_metric': 5.898802757263184} +Cheakpoint... +Epoch [1381/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709793329238892, 'Val/mean miou_metric': 0.9523893594741821, 'Val/mean f1': 0.9723997712135315, 'Val/mean precision': 0.9656177759170532, 'Val/mean recall': 0.9792776703834534, 'Val/mean hd95_metric': 5.898802757263184} +Epoch [1382/4000] Training [1/16] Loss: 0.00860 +Epoch [1382/4000] Training [2/16] Loss: 0.00873 +Epoch [1382/4000] Training [3/16] Loss: 0.00894 +Epoch [1382/4000] Training [4/16] Loss: 0.00996 +Epoch [1382/4000] Training [5/16] Loss: 0.01099 +Epoch [1382/4000] Training [6/16] Loss: 0.00946 +Epoch [1382/4000] Training [7/16] Loss: 0.00917 +Epoch [1382/4000] Training [8/16] Loss: 0.01122 +Epoch [1382/4000] Training [9/16] Loss: 0.01605 +Epoch [1382/4000] Training [10/16] Loss: 0.00877 +Epoch [1382/4000] Training [11/16] Loss: 0.00989 +Epoch [1382/4000] Training [12/16] Loss: 0.00812 +Epoch [1382/4000] Training [13/16] Loss: 0.00840 +Epoch [1382/4000] Training [14/16] Loss: 0.00827 +Epoch [1382/4000] Training [15/16] Loss: 0.00927 +Epoch [1382/4000] Training [16/16] Loss: 0.01017 +Epoch [1382/4000] Training metric {'Train/mean dice_metric': 0.993247926235199, 'Train/mean miou_metric': 0.9863640069961548, 'Train/mean f1': 0.9896097779273987, 'Train/mean precision': 0.9852902293205261, 'Train/mean recall': 0.9939673542976379, 'Train/mean hd95_metric': 1.1192941665649414} +Epoch [1382/4000] Validation [1/4] Loss: 0.23105 focal_loss 0.16648 dice_loss 0.06457 +Epoch [1382/4000] Validation [2/4] Loss: 0.33669 focal_loss 0.16965 dice_loss 0.16704 +Epoch [1382/4000] Validation [3/4] Loss: 0.23722 focal_loss 0.13800 dice_loss 0.09922 +Epoch [1382/4000] Validation [4/4] Loss: 0.29985 focal_loss 0.16295 dice_loss 0.13689 +Epoch [1382/4000] Validation metric {'Val/mean dice_metric': 0.9668711423873901, 'Val/mean miou_metric': 0.9484567642211914, 'Val/mean f1': 0.9708441495895386, 'Val/mean precision': 0.9658369421958923, 'Val/mean recall': 0.975903332233429, 'Val/mean hd95_metric': 6.3588666915893555} +Cheakpoint... +Epoch [1382/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668711423873901, 'Val/mean miou_metric': 0.9484567642211914, 'Val/mean f1': 0.9708441495895386, 'Val/mean precision': 0.9658369421958923, 'Val/mean recall': 0.975903332233429, 'Val/mean hd95_metric': 6.3588666915893555} +Epoch [1383/4000] Training [1/16] Loss: 0.00915 +Epoch [1383/4000] Training [2/16] Loss: 0.00796 +Epoch [1383/4000] Training [3/16] Loss: 0.00985 +Epoch [1383/4000] Training [4/16] Loss: 0.01153 +Epoch [1383/4000] Training [5/16] Loss: 0.01063 +Epoch [1383/4000] Training [6/16] Loss: 0.00946 +Epoch [1383/4000] Training [7/16] Loss: 0.00924 +Epoch [1383/4000] Training [8/16] Loss: 0.01133 +Epoch [1383/4000] Training [9/16] Loss: 0.00913 +Epoch [1383/4000] Training [10/16] Loss: 0.01130 +Epoch [1383/4000] Training [11/16] Loss: 0.01124 +Epoch [1383/4000] Training [12/16] Loss: 0.00941 +Epoch [1383/4000] Training [13/16] Loss: 0.01387 +Epoch [1383/4000] Training [14/16] Loss: 0.03570 +Epoch [1383/4000] Training [15/16] Loss: 0.00787 +Epoch [1383/4000] Training [16/16] Loss: 0.00895 +Epoch [1383/4000] Training metric {'Train/mean dice_metric': 0.9926784038543701, 'Train/mean miou_metric': 0.9852635860443115, 'Train/mean f1': 0.9890711903572083, 'Train/mean precision': 0.9845263361930847, 'Train/mean recall': 0.9936582446098328, 'Train/mean hd95_metric': 1.4474999904632568} +Epoch [1383/4000] Validation [1/4] Loss: 0.29603 focal_loss 0.21922 dice_loss 0.07681 +Epoch [1383/4000] Validation [2/4] Loss: 0.46839 focal_loss 0.28045 dice_loss 0.18794 +Epoch [1383/4000] Validation [3/4] Loss: 0.31516 focal_loss 0.19840 dice_loss 0.11676 +Epoch [1383/4000] Validation [4/4] Loss: 0.41737 focal_loss 0.27286 dice_loss 0.14451 +Epoch [1383/4000] Validation metric {'Val/mean dice_metric': 0.9671953320503235, 'Val/mean miou_metric': 0.9473152160644531, 'Val/mean f1': 0.9673159718513489, 'Val/mean precision': 0.9623643159866333, 'Val/mean recall': 0.9723190069198608, 'Val/mean hd95_metric': 7.196604251861572} +Cheakpoint... +Epoch [1383/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671953320503235, 'Val/mean miou_metric': 0.9473152160644531, 'Val/mean f1': 0.9673159718513489, 'Val/mean precision': 0.9623643159866333, 'Val/mean recall': 0.9723190069198608, 'Val/mean hd95_metric': 7.196604251861572} +Epoch [1384/4000] Training [1/16] Loss: 0.00953 +Epoch [1384/4000] Training [2/16] Loss: 0.01150 +Epoch [1384/4000] Training [3/16] Loss: 0.01018 +Epoch [1384/4000] Training [4/16] Loss: 0.01311 +Epoch [1384/4000] Training [5/16] Loss: 0.00901 +Epoch [1384/4000] Training [6/16] Loss: 0.00957 +Epoch [1384/4000] Training [7/16] Loss: 0.01326 +Epoch [1384/4000] Training [8/16] Loss: 0.00751 +Epoch [1384/4000] Training [9/16] Loss: 0.00982 +Epoch [1384/4000] Training [10/16] Loss: 0.01001 +Epoch [1384/4000] Training [11/16] Loss: 0.00875 +Epoch [1384/4000] Training [12/16] Loss: 0.00915 +Epoch [1384/4000] Training [13/16] Loss: 0.01106 +Epoch [1384/4000] Training [14/16] Loss: 0.01187 +Epoch [1384/4000] Training [15/16] Loss: 0.01050 +Epoch [1384/4000] Training [16/16] Loss: 0.00813 +Epoch [1384/4000] Training metric {'Train/mean dice_metric': 0.9926502108573914, 'Train/mean miou_metric': 0.9855688810348511, 'Train/mean f1': 0.9891839027404785, 'Train/mean precision': 0.9840478897094727, 'Train/mean recall': 0.9943737983703613, 'Train/mean hd95_metric': 1.4739198684692383} +Epoch [1384/4000] Validation [1/4] Loss: 0.29597 focal_loss 0.19349 dice_loss 0.10248 +Epoch [1384/4000] Validation [2/4] Loss: 0.27463 focal_loss 0.15249 dice_loss 0.12215 +Epoch [1384/4000] Validation [3/4] Loss: 0.14321 focal_loss 0.08375 dice_loss 0.05946 +Epoch [1384/4000] Validation [4/4] Loss: 0.22623 focal_loss 0.12375 dice_loss 0.10248 +Epoch [1384/4000] Validation metric {'Val/mean dice_metric': 0.9672559499740601, 'Val/mean miou_metric': 0.9481619000434875, 'Val/mean f1': 0.9669479131698608, 'Val/mean precision': 0.960364818572998, 'Val/mean recall': 0.9736219048500061, 'Val/mean hd95_metric': 6.493415832519531} +Cheakpoint... +Epoch [1384/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672559499740601, 'Val/mean miou_metric': 0.9481619000434875, 'Val/mean f1': 0.9669479131698608, 'Val/mean precision': 0.960364818572998, 'Val/mean recall': 0.9736219048500061, 'Val/mean hd95_metric': 6.493415832519531} +Epoch [1385/4000] Training [1/16] Loss: 0.00987 +Epoch [1385/4000] Training [2/16] Loss: 0.01240 +Epoch [1385/4000] Training [3/16] Loss: 0.01511 +Epoch [1385/4000] Training [4/16] Loss: 0.00906 +Epoch [1385/4000] Training [5/16] Loss: 0.00949 +Epoch [1385/4000] Training [6/16] Loss: 0.00909 +Epoch [1385/4000] Training [7/16] Loss: 0.01463 +Epoch [1385/4000] Training [8/16] Loss: 0.00968 +Epoch [1385/4000] Training [9/16] Loss: 0.00922 +Epoch [1385/4000] Training [10/16] Loss: 0.01225 +Epoch [1385/4000] Training [11/16] Loss: 0.00917 +Epoch [1385/4000] Training [12/16] Loss: 0.01064 +Epoch [1385/4000] Training [13/16] Loss: 0.01090 +Epoch [1385/4000] Training [14/16] Loss: 0.01429 +Epoch [1385/4000] Training [15/16] Loss: 0.00922 +Epoch [1385/4000] Training [16/16] Loss: 0.01881 +Epoch [1385/4000] Training metric {'Train/mean dice_metric': 0.9907719492912292, 'Train/mean miou_metric': 0.9823474884033203, 'Train/mean f1': 0.9875108599662781, 'Train/mean precision': 0.9840126633644104, 'Train/mean recall': 0.9910340309143066, 'Train/mean hd95_metric': 1.655764102935791} +Epoch [1385/4000] Validation [1/4] Loss: 0.20362 focal_loss 0.13009 dice_loss 0.07353 +Epoch [1385/4000] Validation [2/4] Loss: 0.34536 focal_loss 0.19252 dice_loss 0.15284 +Epoch [1385/4000] Validation [3/4] Loss: 0.16848 focal_loss 0.09358 dice_loss 0.07490 +Epoch [1385/4000] Validation [4/4] Loss: 0.31416 focal_loss 0.15447 dice_loss 0.15968 +Epoch [1385/4000] Validation metric {'Val/mean dice_metric': 0.96314936876297, 'Val/mean miou_metric': 0.9423755407333374, 'Val/mean f1': 0.9664610028266907, 'Val/mean precision': 0.9607466459274292, 'Val/mean recall': 0.97224360704422, 'Val/mean hd95_metric': 6.647089958190918} +Cheakpoint... +Epoch [1385/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9631], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96314936876297, 'Val/mean miou_metric': 0.9423755407333374, 'Val/mean f1': 0.9664610028266907, 'Val/mean precision': 0.9607466459274292, 'Val/mean recall': 0.97224360704422, 'Val/mean hd95_metric': 6.647089958190918} +Epoch [1386/4000] Training [1/16] Loss: 0.00917 +Epoch [1386/4000] Training [2/16] Loss: 0.01118 +Epoch [1386/4000] Training [3/16] Loss: 0.01032 +Epoch [1386/4000] Training [4/16] Loss: 0.01254 +Epoch [1386/4000] Training [5/16] Loss: 0.01623 +Epoch [1386/4000] Training [6/16] Loss: 0.01209 +Epoch [1386/4000] Training [7/16] Loss: 0.01079 +Epoch [1386/4000] Training [8/16] Loss: 0.03745 +Epoch [1386/4000] Training [9/16] Loss: 0.01132 +Epoch [1386/4000] Training [10/16] Loss: 0.01401 +Epoch [1386/4000] Training [11/16] Loss: 0.01340 +Epoch [1386/4000] Training [12/16] Loss: 0.01023 +Epoch [1386/4000] Training [13/16] Loss: 0.00885 +Epoch [1386/4000] Training [14/16] Loss: 0.01186 +Epoch [1386/4000] Training [15/16] Loss: 0.01140 +Epoch [1386/4000] Training [16/16] Loss: 0.01009 +Epoch [1386/4000] Training metric {'Train/mean dice_metric': 0.9906911253929138, 'Train/mean miou_metric': 0.9816755056381226, 'Train/mean f1': 0.9878285527229309, 'Train/mean precision': 0.9834840893745422, 'Train/mean recall': 0.9922116994857788, 'Train/mean hd95_metric': 2.67996883392334} +Epoch [1386/4000] Validation [1/4] Loss: 0.27670 focal_loss 0.17980 dice_loss 0.09690 +Epoch [1386/4000] Validation [2/4] Loss: 0.30270 focal_loss 0.16062 dice_loss 0.14209 +Epoch [1386/4000] Validation [3/4] Loss: 0.12926 focal_loss 0.07016 dice_loss 0.05910 +Epoch [1386/4000] Validation [4/4] Loss: 0.42600 focal_loss 0.24001 dice_loss 0.18599 +Epoch [1386/4000] Validation metric {'Val/mean dice_metric': 0.961095929145813, 'Val/mean miou_metric': 0.9388772249221802, 'Val/mean f1': 0.9614590406417847, 'Val/mean precision': 0.9490171074867249, 'Val/mean recall': 0.974231481552124, 'Val/mean hd95_metric': 8.579176902770996} +Cheakpoint... +Epoch [1386/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9611], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.961095929145813, 'Val/mean miou_metric': 0.9388772249221802, 'Val/mean f1': 0.9614590406417847, 'Val/mean precision': 0.9490171074867249, 'Val/mean recall': 0.974231481552124, 'Val/mean hd95_metric': 8.579176902770996} +Epoch [1387/4000] Training [1/16] Loss: 0.01534 +Epoch [1387/4000] Training [2/16] Loss: 0.01317 +Epoch [1387/4000] Training [3/16] Loss: 0.00950 +Epoch [1387/4000] Training [4/16] Loss: 0.01310 +Epoch [1387/4000] Training [5/16] Loss: 0.00972 +Epoch [1387/4000] Training [6/16] Loss: 0.01156 +Epoch [1387/4000] Training [7/16] Loss: 0.01211 +Epoch [1387/4000] Training [8/16] Loss: 0.01513 +Epoch [1387/4000] Training [9/16] Loss: 0.02260 +Epoch [1387/4000] Training [10/16] Loss: 0.00998 +Epoch [1387/4000] Training [11/16] Loss: 0.01154 +Epoch [1387/4000] Training [12/16] Loss: 0.01274 +Epoch [1387/4000] Training [13/16] Loss: 0.01106 +Epoch [1387/4000] Training [14/16] Loss: 0.02692 +Epoch [1387/4000] Training [15/16] Loss: 0.01122 +Epoch [1387/4000] Training [16/16] Loss: 0.01046 +Epoch [1387/4000] Training metric {'Train/mean dice_metric': 0.990646481513977, 'Train/mean miou_metric': 0.9816315174102783, 'Train/mean f1': 0.9867424964904785, 'Train/mean precision': 0.9811609983444214, 'Train/mean recall': 0.9923878312110901, 'Train/mean hd95_metric': 2.1438026428222656} +Epoch [1387/4000] Validation [1/4] Loss: 0.20723 focal_loss 0.12388 dice_loss 0.08335 +Epoch [1387/4000] Validation [2/4] Loss: 0.40203 focal_loss 0.23632 dice_loss 0.16571 +Epoch [1387/4000] Validation [3/4] Loss: 0.14484 focal_loss 0.08206 dice_loss 0.06278 +Epoch [1387/4000] Validation [4/4] Loss: 0.30453 focal_loss 0.16748 dice_loss 0.13705 +Epoch [1387/4000] Validation metric {'Val/mean dice_metric': 0.9653478860855103, 'Val/mean miou_metric': 0.9441046714782715, 'Val/mean f1': 0.9666589498519897, 'Val/mean precision': 0.9634203910827637, 'Val/mean recall': 0.9699193835258484, 'Val/mean hd95_metric': 7.368546962738037} +Cheakpoint... +Epoch [1387/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9653], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9653478860855103, 'Val/mean miou_metric': 0.9441046714782715, 'Val/mean f1': 0.9666589498519897, 'Val/mean precision': 0.9634203910827637, 'Val/mean recall': 0.9699193835258484, 'Val/mean hd95_metric': 7.368546962738037} +Epoch [1388/4000] Training [1/16] Loss: 0.01540 +Epoch [1388/4000] Training [2/16] Loss: 0.00957 +Epoch [1388/4000] Training [3/16] Loss: 0.01013 +Epoch [1388/4000] Training [4/16] Loss: 0.00878 +Epoch [1388/4000] Training [5/16] Loss: 0.01014 +Epoch [1388/4000] Training [6/16] Loss: 0.00824 +Epoch [1388/4000] Training [7/16] Loss: 0.00979 +Epoch [1388/4000] Training [8/16] Loss: 0.00964 +Epoch [1388/4000] Training [9/16] Loss: 0.01055 +Epoch [1388/4000] Training [10/16] Loss: 0.00883 +Epoch [1388/4000] Training [11/16] Loss: 0.00963 +Epoch [1388/4000] Training [12/16] Loss: 0.01246 +Epoch [1388/4000] Training [13/16] Loss: 0.03329 +Epoch [1388/4000] Training [14/16] Loss: 0.01094 +Epoch [1388/4000] Training [15/16] Loss: 0.01159 +Epoch [1388/4000] Training [16/16] Loss: 0.01252 +Epoch [1388/4000] Training metric {'Train/mean dice_metric': 0.9925381541252136, 'Train/mean miou_metric': 0.9849696159362793, 'Train/mean f1': 0.9882967472076416, 'Train/mean precision': 0.9838060140609741, 'Train/mean recall': 0.9928286075592041, 'Train/mean hd95_metric': 1.4943454265594482} +Epoch [1388/4000] Validation [1/4] Loss: 0.14097 focal_loss 0.08117 dice_loss 0.05980 +Epoch [1388/4000] Validation [2/4] Loss: 0.44201 focal_loss 0.26388 dice_loss 0.17812 +Epoch [1388/4000] Validation [3/4] Loss: 0.15268 focal_loss 0.09087 dice_loss 0.06181 +Epoch [1388/4000] Validation [4/4] Loss: 0.29676 focal_loss 0.15704 dice_loss 0.13972 +Epoch [1388/4000] Validation metric {'Val/mean dice_metric': 0.9672566652297974, 'Val/mean miou_metric': 0.9479995965957642, 'Val/mean f1': 0.9684303998947144, 'Val/mean precision': 0.9660407304763794, 'Val/mean recall': 0.970832109451294, 'Val/mean hd95_metric': 6.179695129394531} +Cheakpoint... +Epoch [1388/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672566652297974, 'Val/mean miou_metric': 0.9479995965957642, 'Val/mean f1': 0.9684303998947144, 'Val/mean precision': 0.9660407304763794, 'Val/mean recall': 0.970832109451294, 'Val/mean hd95_metric': 6.179695129394531} +Epoch [1389/4000] Training [1/16] Loss: 0.01000 +Epoch [1389/4000] Training [2/16] Loss: 0.00949 +Epoch [1389/4000] Training [3/16] Loss: 0.00943 +Epoch [1389/4000] Training [4/16] Loss: 0.01154 +Epoch [1389/4000] Training [5/16] Loss: 0.01003 +Epoch [1389/4000] Training [6/16] Loss: 0.01039 +Epoch [1389/4000] Training [7/16] Loss: 0.01351 +Epoch [1389/4000] Training [8/16] Loss: 0.01015 +Epoch [1389/4000] Training [9/16] Loss: 0.01124 +Epoch [1389/4000] Training [10/16] Loss: 0.01206 +Epoch [1389/4000] Training [11/16] Loss: 0.00946 +Epoch [1389/4000] Training [12/16] Loss: 0.01055 +Epoch [1389/4000] Training [13/16] Loss: 0.01149 +Epoch [1389/4000] Training [14/16] Loss: 0.01014 +Epoch [1389/4000] Training [15/16] Loss: 0.00864 +Epoch [1389/4000] Training [16/16] Loss: 0.00909 +Epoch [1389/4000] Training metric {'Train/mean dice_metric': 0.9929172992706299, 'Train/mean miou_metric': 0.9856511354446411, 'Train/mean f1': 0.987835168838501, 'Train/mean precision': 0.9822893738746643, 'Train/mean recall': 0.9934439659118652, 'Train/mean hd95_metric': 1.333878993988037} +Epoch [1389/4000] Validation [1/4] Loss: 0.16479 focal_loss 0.10770 dice_loss 0.05710 +Epoch [1389/4000] Validation [2/4] Loss: 0.70156 focal_loss 0.43457 dice_loss 0.26698 +Epoch [1389/4000] Validation [3/4] Loss: 0.13536 focal_loss 0.08173 dice_loss 0.05363 +Epoch [1389/4000] Validation [4/4] Loss: 0.25718 focal_loss 0.13160 dice_loss 0.12558 +Epoch [1389/4000] Validation metric {'Val/mean dice_metric': 0.9668868780136108, 'Val/mean miou_metric': 0.9485589265823364, 'Val/mean f1': 0.9690364599227905, 'Val/mean precision': 0.9625670313835144, 'Val/mean recall': 0.9755933880805969, 'Val/mean hd95_metric': 6.079176425933838} +Cheakpoint... +Epoch [1389/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668868780136108, 'Val/mean miou_metric': 0.9485589265823364, 'Val/mean f1': 0.9690364599227905, 'Val/mean precision': 0.9625670313835144, 'Val/mean recall': 0.9755933880805969, 'Val/mean hd95_metric': 6.079176425933838} +Epoch [1390/4000] Training [1/16] Loss: 0.01056 +Epoch [1390/4000] Training [2/16] Loss: 0.00852 +Epoch [1390/4000] Training [3/16] Loss: 0.00876 +Epoch [1390/4000] Training [4/16] Loss: 0.00975 +Epoch [1390/4000] Training [5/16] Loss: 0.00849 +Epoch [1390/4000] Training [6/16] Loss: 0.00939 +Epoch [1390/4000] Training [7/16] Loss: 0.00795 +Epoch [1390/4000] Training [8/16] Loss: 0.01002 +Epoch [1390/4000] Training [9/16] Loss: 0.00818 +Epoch [1390/4000] Training [10/16] Loss: 0.01342 +Epoch [1390/4000] Training [11/16] Loss: 0.00851 +Epoch [1390/4000] Training [12/16] Loss: 0.00775 +Epoch [1390/4000] Training [13/16] Loss: 0.00790 +Epoch [1390/4000] Training [14/16] Loss: 0.01137 +Epoch [1390/4000] Training [15/16] Loss: 0.01318 +Epoch [1390/4000] Training [16/16] Loss: 0.00882 +Epoch [1390/4000] Training metric {'Train/mean dice_metric': 0.9932758212089539, 'Train/mean miou_metric': 0.9864077568054199, 'Train/mean f1': 0.9893854856491089, 'Train/mean precision': 0.9848306775093079, 'Train/mean recall': 0.9939826130867004, 'Train/mean hd95_metric': 1.1057369709014893} +Epoch [1390/4000] Validation [1/4] Loss: 0.16920 focal_loss 0.10673 dice_loss 0.06247 +Epoch [1390/4000] Validation [2/4] Loss: 0.37609 focal_loss 0.24449 dice_loss 0.13160 +Epoch [1390/4000] Validation [3/4] Loss: 0.17499 focal_loss 0.10407 dice_loss 0.07092 +Epoch [1390/4000] Validation [4/4] Loss: 0.28376 focal_loss 0.15393 dice_loss 0.12983 +Epoch [1390/4000] Validation metric {'Val/mean dice_metric': 0.9703289270401001, 'Val/mean miou_metric': 0.9516589045524597, 'Val/mean f1': 0.9717196822166443, 'Val/mean precision': 0.966011106967926, 'Val/mean recall': 0.9774962067604065, 'Val/mean hd95_metric': 5.865364074707031} +Cheakpoint... +Epoch [1390/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703289270401001, 'Val/mean miou_metric': 0.9516589045524597, 'Val/mean f1': 0.9717196822166443, 'Val/mean precision': 0.966011106967926, 'Val/mean recall': 0.9774962067604065, 'Val/mean hd95_metric': 5.865364074707031} +Epoch [1391/4000] Training [1/16] Loss: 0.00895 +Epoch [1391/4000] Training [2/16] Loss: 0.00733 +Epoch [1391/4000] Training [3/16] Loss: 0.00813 +Epoch [1391/4000] Training [4/16] Loss: 0.00660 +Epoch [1391/4000] Training [5/16] Loss: 0.01239 +Epoch [1391/4000] Training [6/16] Loss: 0.01096 +Epoch [1391/4000] Training [7/16] Loss: 0.00560 +Epoch [1391/4000] Training [8/16] Loss: 0.00806 +Epoch [1391/4000] Training [9/16] Loss: 0.00857 +Epoch [1391/4000] Training [10/16] Loss: 0.01221 +Epoch [1391/4000] Training [11/16] Loss: 0.00772 +Epoch [1391/4000] Training [12/16] Loss: 0.00831 +Epoch [1391/4000] Training [13/16] Loss: 0.00797 +Epoch [1391/4000] Training [14/16] Loss: 0.00602 +Epoch [1391/4000] Training [15/16] Loss: 0.00728 +Epoch [1391/4000] Training [16/16] Loss: 0.01211 +Epoch [1391/4000] Training metric {'Train/mean dice_metric': 0.9941496849060059, 'Train/mean miou_metric': 0.9880996942520142, 'Train/mean f1': 0.9896520376205444, 'Train/mean precision': 0.984767735004425, 'Train/mean recall': 0.9945849776268005, 'Train/mean hd95_metric': 1.0951370000839233} +Epoch [1391/4000] Validation [1/4] Loss: 0.16090 focal_loss 0.09579 dice_loss 0.06511 +Epoch [1391/4000] Validation [2/4] Loss: 0.37700 focal_loss 0.24093 dice_loss 0.13608 +Epoch [1391/4000] Validation [3/4] Loss: 0.19195 focal_loss 0.11025 dice_loss 0.08170 +Epoch [1391/4000] Validation [4/4] Loss: 0.22519 focal_loss 0.10900 dice_loss 0.11618 +Epoch [1391/4000] Validation metric {'Val/mean dice_metric': 0.969546914100647, 'Val/mean miou_metric': 0.951388955116272, 'Val/mean f1': 0.9707785248756409, 'Val/mean precision': 0.9675626754760742, 'Val/mean recall': 0.9740157723426819, 'Val/mean hd95_metric': 6.516770839691162} +Cheakpoint... +Epoch [1391/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969546914100647, 'Val/mean miou_metric': 0.951388955116272, 'Val/mean f1': 0.9707785248756409, 'Val/mean precision': 0.9675626754760742, 'Val/mean recall': 0.9740157723426819, 'Val/mean hd95_metric': 6.516770839691162} +Epoch [1392/4000] Training [1/16] Loss: 0.00930 +Epoch [1392/4000] Training [2/16] Loss: 0.04599 +Epoch [1392/4000] Training [3/16] Loss: 0.00766 +Epoch [1392/4000] Training [4/16] Loss: 0.00872 +Epoch [1392/4000] Training [5/16] Loss: 0.00805 +Epoch [1392/4000] Training [6/16] Loss: 0.00851 +Epoch [1392/4000] Training [7/16] Loss: 0.00734 +Epoch [1392/4000] Training [8/16] Loss: 0.00774 +Epoch [1392/4000] Training [9/16] Loss: 0.00974 +Epoch [1392/4000] Training [10/16] Loss: 0.00812 +Epoch [1392/4000] Training [11/16] Loss: 0.00900 +Epoch [1392/4000] Training [12/16] Loss: 0.01009 +Epoch [1392/4000] Training [13/16] Loss: 0.00707 +Epoch [1392/4000] Training [14/16] Loss: 0.00990 +Epoch [1392/4000] Training [15/16] Loss: 0.00768 +Epoch [1392/4000] Training [16/16] Loss: 0.00876 +Epoch [1392/4000] Training metric {'Train/mean dice_metric': 0.9935301542282104, 'Train/mean miou_metric': 0.9869765043258667, 'Train/mean f1': 0.989691436290741, 'Train/mean precision': 0.9852920770645142, 'Train/mean recall': 0.9941303133964539, 'Train/mean hd95_metric': 1.1420531272888184} +Epoch [1392/4000] Validation [1/4] Loss: 0.18057 focal_loss 0.12454 dice_loss 0.05602 +Epoch [1392/4000] Validation [2/4] Loss: 0.24376 focal_loss 0.11547 dice_loss 0.12830 +Epoch [1392/4000] Validation [3/4] Loss: 0.16445 focal_loss 0.09770 dice_loss 0.06676 +Epoch [1392/4000] Validation [4/4] Loss: 0.27872 focal_loss 0.16206 dice_loss 0.11665 +Epoch [1392/4000] Validation metric {'Val/mean dice_metric': 0.9696375131607056, 'Val/mean miou_metric': 0.9512244462966919, 'Val/mean f1': 0.9715284109115601, 'Val/mean precision': 0.9650751948356628, 'Val/mean recall': 0.978068470954895, 'Val/mean hd95_metric': 6.3898444175720215} +Cheakpoint... +Epoch [1392/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696375131607056, 'Val/mean miou_metric': 0.9512244462966919, 'Val/mean f1': 0.9715284109115601, 'Val/mean precision': 0.9650751948356628, 'Val/mean recall': 0.978068470954895, 'Val/mean hd95_metric': 6.3898444175720215} +Epoch [1393/4000] Training [1/16] Loss: 0.00768 +Epoch [1393/4000] Training [2/16] Loss: 0.01061 +Epoch [1393/4000] Training [3/16] Loss: 0.00708 +Epoch [1393/4000] Training [4/16] Loss: 0.00758 +Epoch [1393/4000] Training [5/16] Loss: 0.00795 +Epoch [1393/4000] Training [6/16] Loss: 0.01044 +Epoch [1393/4000] Training [7/16] Loss: 0.01307 +Epoch [1393/4000] Training [8/16] Loss: 0.00887 +Epoch [1393/4000] Training [9/16] Loss: 0.00842 +Epoch [1393/4000] Training [10/16] Loss: 0.00874 +Epoch [1393/4000] Training [11/16] Loss: 0.00701 +Epoch [1393/4000] Training [12/16] Loss: 0.00809 +Epoch [1393/4000] Training [13/16] Loss: 0.00945 +Epoch [1393/4000] Training [14/16] Loss: 0.00696 +Epoch [1393/4000] Training [15/16] Loss: 0.00660 +Epoch [1393/4000] Training [16/16] Loss: 0.00718 +Epoch [1393/4000] Training metric {'Train/mean dice_metric': 0.9943751096725464, 'Train/mean miou_metric': 0.988565981388092, 'Train/mean f1': 0.990515947341919, 'Train/mean precision': 0.9859467148780823, 'Train/mean recall': 0.9951276779174805, 'Train/mean hd95_metric': 1.050562858581543} +Epoch [1393/4000] Validation [1/4] Loss: 0.19284 focal_loss 0.12878 dice_loss 0.06406 +Epoch [1393/4000] Validation [2/4] Loss: 0.28626 focal_loss 0.16578 dice_loss 0.12049 +Epoch [1393/4000] Validation [3/4] Loss: 0.18082 focal_loss 0.09787 dice_loss 0.08295 +Epoch [1393/4000] Validation [4/4] Loss: 0.27599 focal_loss 0.14764 dice_loss 0.12835 +Epoch [1393/4000] Validation metric {'Val/mean dice_metric': 0.9705123901367188, 'Val/mean miou_metric': 0.9524391889572144, 'Val/mean f1': 0.9713515043258667, 'Val/mean precision': 0.964637815952301, 'Val/mean recall': 0.9781594276428223, 'Val/mean hd95_metric': 5.977582931518555} +Cheakpoint... +Epoch [1393/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705123901367188, 'Val/mean miou_metric': 0.9524391889572144, 'Val/mean f1': 0.9713515043258667, 'Val/mean precision': 0.964637815952301, 'Val/mean recall': 0.9781594276428223, 'Val/mean hd95_metric': 5.977582931518555} +Epoch [1394/4000] Training [1/16] Loss: 0.00998 +Epoch [1394/4000] Training [2/16] Loss: 0.00618 +Epoch [1394/4000] Training [3/16] Loss: 0.01053 +Epoch [1394/4000] Training [4/16] Loss: 0.00947 +Epoch [1394/4000] Training [5/16] Loss: 0.00761 +Epoch [1394/4000] Training [6/16] Loss: 0.00697 +Epoch [1394/4000] Training [7/16] Loss: 0.00912 +Epoch [1394/4000] Training [8/16] Loss: 0.01137 +Epoch [1394/4000] Training [9/16] Loss: 0.00694 +Epoch [1394/4000] Training [10/16] Loss: 0.01204 +Epoch [1394/4000] Training [11/16] Loss: 0.00853 +Epoch [1394/4000] Training [12/16] Loss: 0.00956 +Epoch [1394/4000] Training [13/16] Loss: 0.01339 +Epoch [1394/4000] Training [14/16] Loss: 0.00992 +Epoch [1394/4000] Training [15/16] Loss: 0.00802 +Epoch [1394/4000] Training [16/16] Loss: 0.00791 +Epoch [1394/4000] Training metric {'Train/mean dice_metric': 0.994216799736023, 'Train/mean miou_metric': 0.9882249236106873, 'Train/mean f1': 0.9893944263458252, 'Train/mean precision': 0.9842081665992737, 'Train/mean recall': 0.9946355819702148, 'Train/mean hd95_metric': 1.0903499126434326} +Epoch [1394/4000] Validation [1/4] Loss: 0.16886 focal_loss 0.11346 dice_loss 0.05540 +Epoch [1394/4000] Validation [2/4] Loss: 0.27338 focal_loss 0.16334 dice_loss 0.11004 +Epoch [1394/4000] Validation [3/4] Loss: 0.25107 focal_loss 0.15593 dice_loss 0.09514 +Epoch [1394/4000] Validation [4/4] Loss: 0.27478 focal_loss 0.15468 dice_loss 0.12009 +Epoch [1394/4000] Validation metric {'Val/mean dice_metric': 0.972577691078186, 'Val/mean miou_metric': 0.9545415043830872, 'Val/mean f1': 0.9721555709838867, 'Val/mean precision': 0.9639047384262085, 'Val/mean recall': 0.9805487990379333, 'Val/mean hd95_metric': 5.718979835510254} +Cheakpoint... +Epoch [1394/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972577691078186, 'Val/mean miou_metric': 0.9545415043830872, 'Val/mean f1': 0.9721555709838867, 'Val/mean precision': 0.9639047384262085, 'Val/mean recall': 0.9805487990379333, 'Val/mean hd95_metric': 5.718979835510254} +Epoch [1395/4000] Training [1/16] Loss: 0.00665 +Epoch [1395/4000] Training [2/16] Loss: 0.00716 +Epoch [1395/4000] Training [3/16] Loss: 0.00816 +Epoch [1395/4000] Training [4/16] Loss: 0.00639 +Epoch [1395/4000] Training [5/16] Loss: 0.01002 +Epoch [1395/4000] Training [6/16] Loss: 0.01451 +Epoch [1395/4000] Training [7/16] Loss: 0.00772 +Epoch [1395/4000] Training [8/16] Loss: 0.00772 +Epoch [1395/4000] Training [9/16] Loss: 0.00968 +Epoch [1395/4000] Training [10/16] Loss: 0.01053 +Epoch [1395/4000] Training [11/16] Loss: 0.01028 +Epoch [1395/4000] Training [12/16] Loss: 0.00792 +Epoch [1395/4000] Training [13/16] Loss: 0.00856 +Epoch [1395/4000] Training [14/16] Loss: 0.00806 +Epoch [1395/4000] Training [15/16] Loss: 0.00827 +Epoch [1395/4000] Training [16/16] Loss: 0.00839 +Epoch [1395/4000] Training metric {'Train/mean dice_metric': 0.9940736293792725, 'Train/mean miou_metric': 0.987964391708374, 'Train/mean f1': 0.9903371334075928, 'Train/mean precision': 0.985706627368927, 'Train/mean recall': 0.9950113296508789, 'Train/mean hd95_metric': 1.0501611232757568} +Epoch [1395/4000] Validation [1/4] Loss: 0.19605 focal_loss 0.13779 dice_loss 0.05827 +Epoch [1395/4000] Validation [2/4] Loss: 0.29511 focal_loss 0.17240 dice_loss 0.12271 +Epoch [1395/4000] Validation [3/4] Loss: 0.22900 focal_loss 0.13950 dice_loss 0.08950 +Epoch [1395/4000] Validation [4/4] Loss: 0.25519 focal_loss 0.13049 dice_loss 0.12470 +Epoch [1395/4000] Validation metric {'Val/mean dice_metric': 0.971071720123291, 'Val/mean miou_metric': 0.952847957611084, 'Val/mean f1': 0.9730536341667175, 'Val/mean precision': 0.9684525728225708, 'Val/mean recall': 0.9776985049247742, 'Val/mean hd95_metric': 6.512449741363525} +Cheakpoint... +Epoch [1395/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971071720123291, 'Val/mean miou_metric': 0.952847957611084, 'Val/mean f1': 0.9730536341667175, 'Val/mean precision': 0.9684525728225708, 'Val/mean recall': 0.9776985049247742, 'Val/mean hd95_metric': 6.512449741363525} +Epoch [1396/4000] Training [1/16] Loss: 0.00803 +Epoch [1396/4000] Training [2/16] Loss: 0.00815 +Epoch [1396/4000] Training [3/16] Loss: 0.00831 +Epoch [1396/4000] Training [4/16] Loss: 0.01099 +Epoch [1396/4000] Training [5/16] Loss: 0.01036 +Epoch [1396/4000] Training [6/16] Loss: 0.01078 +Epoch [1396/4000] Training [7/16] Loss: 0.00767 +Epoch [1396/4000] Training [8/16] Loss: 0.01056 +Epoch [1396/4000] Training [9/16] Loss: 0.00937 +Epoch [1396/4000] Training [10/16] Loss: 0.00968 +Epoch [1396/4000] Training [11/16] Loss: 0.00784 +Epoch [1396/4000] Training [12/16] Loss: 0.01022 +Epoch [1396/4000] Training [13/16] Loss: 0.01084 +Epoch [1396/4000] Training [14/16] Loss: 0.00697 +Epoch [1396/4000] Training [15/16] Loss: 0.00675 +Epoch [1396/4000] Training [16/16] Loss: 0.00885 +Epoch [1396/4000] Training metric {'Train/mean dice_metric': 0.9938032627105713, 'Train/mean miou_metric': 0.9874348640441895, 'Train/mean f1': 0.9899256229400635, 'Train/mean precision': 0.9854245781898499, 'Train/mean recall': 0.9944678544998169, 'Train/mean hd95_metric': 1.0740668773651123} +Epoch [1396/4000] Validation [1/4] Loss: 0.16976 focal_loss 0.11248 dice_loss 0.05728 +Epoch [1396/4000] Validation [2/4] Loss: 0.30126 focal_loss 0.18126 dice_loss 0.12001 +Epoch [1396/4000] Validation [3/4] Loss: 0.25579 focal_loss 0.16056 dice_loss 0.09523 +Epoch [1396/4000] Validation [4/4] Loss: 0.26495 focal_loss 0.13723 dice_loss 0.12772 +Epoch [1396/4000] Validation metric {'Val/mean dice_metric': 0.9718950390815735, 'Val/mean miou_metric': 0.9533754587173462, 'Val/mean f1': 0.9716575741767883, 'Val/mean precision': 0.9643051028251648, 'Val/mean recall': 0.979123055934906, 'Val/mean hd95_metric': 5.9219255447387695} +Cheakpoint... +Epoch [1396/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718950390815735, 'Val/mean miou_metric': 0.9533754587173462, 'Val/mean f1': 0.9716575741767883, 'Val/mean precision': 0.9643051028251648, 'Val/mean recall': 0.979123055934906, 'Val/mean hd95_metric': 5.9219255447387695} +Epoch [1397/4000] Training [1/16] Loss: 0.01200 +Epoch [1397/4000] Training [2/16] Loss: 0.00994 +Epoch [1397/4000] Training [3/16] Loss: 0.00809 +Epoch [1397/4000] Training [4/16] Loss: 0.01033 +Epoch [1397/4000] Training [5/16] Loss: 0.00872 +Epoch [1397/4000] Training [6/16] Loss: 0.00937 +Epoch [1397/4000] Training [7/16] Loss: 0.01048 +Epoch [1397/4000] Training [8/16] Loss: 0.00827 +Epoch [1397/4000] Training [9/16] Loss: 0.01191 +Epoch [1397/4000] Training [10/16] Loss: 0.00738 +Epoch [1397/4000] Training [11/16] Loss: 0.01547 +Epoch [1397/4000] Training [12/16] Loss: 0.00898 +Epoch [1397/4000] Training [13/16] Loss: 0.00875 +Epoch [1397/4000] Training [14/16] Loss: 0.00981 +Epoch [1397/4000] Training [15/16] Loss: 0.00918 +Epoch [1397/4000] Training [16/16] Loss: 0.00818 +Epoch [1397/4000] Training metric {'Train/mean dice_metric': 0.9931775331497192, 'Train/mean miou_metric': 0.9862246513366699, 'Train/mean f1': 0.9895808696746826, 'Train/mean precision': 0.985090970993042, 'Train/mean recall': 0.9941118359565735, 'Train/mean hd95_metric': 1.095543384552002} +Epoch [1397/4000] Validation [1/4] Loss: 0.17479 focal_loss 0.11379 dice_loss 0.06100 +Epoch [1397/4000] Validation [2/4] Loss: 0.33032 focal_loss 0.21414 dice_loss 0.11618 +Epoch [1397/4000] Validation [3/4] Loss: 0.17182 focal_loss 0.11086 dice_loss 0.06096 +Epoch [1397/4000] Validation [4/4] Loss: 0.28890 focal_loss 0.14576 dice_loss 0.14314 +Epoch [1397/4000] Validation metric {'Val/mean dice_metric': 0.9699037671089172, 'Val/mean miou_metric': 0.9507424235343933, 'Val/mean f1': 0.9697054624557495, 'Val/mean precision': 0.9623749852180481, 'Val/mean recall': 0.9771484732627869, 'Val/mean hd95_metric': 6.155461311340332} +Cheakpoint... +Epoch [1397/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699037671089172, 'Val/mean miou_metric': 0.9507424235343933, 'Val/mean f1': 0.9697054624557495, 'Val/mean precision': 0.9623749852180481, 'Val/mean recall': 0.9771484732627869, 'Val/mean hd95_metric': 6.155461311340332} +Epoch [1398/4000] Training [1/16] Loss: 0.01000 +Epoch [1398/4000] Training [2/16] Loss: 0.01134 +Epoch [1398/4000] Training [3/16] Loss: 0.00823 +Epoch [1398/4000] Training [4/16] Loss: 0.00912 +Epoch [1398/4000] Training [5/16] Loss: 0.01057 +Epoch [1398/4000] Training [6/16] Loss: 0.00937 +Epoch [1398/4000] Training [7/16] Loss: 0.00944 +Epoch [1398/4000] Training [8/16] Loss: 0.00951 +Epoch [1398/4000] Training [9/16] Loss: 0.01195 +Epoch [1398/4000] Training [10/16] Loss: 0.00881 +Epoch [1398/4000] Training [11/16] Loss: 0.00896 +Epoch [1398/4000] Training [12/16] Loss: 0.01227 +Epoch [1398/4000] Training [13/16] Loss: 0.00813 +Epoch [1398/4000] Training [14/16] Loss: 0.00855 +Epoch [1398/4000] Training [15/16] Loss: 0.01175 +Epoch [1398/4000] Training [16/16] Loss: 0.00872 +Epoch [1398/4000] Training metric {'Train/mean dice_metric': 0.9932646751403809, 'Train/mean miou_metric': 0.9863817095756531, 'Train/mean f1': 0.9896866083145142, 'Train/mean precision': 0.9852199554443359, 'Train/mean recall': 0.9941939115524292, 'Train/mean hd95_metric': 1.3994911909103394} +Epoch [1398/4000] Validation [1/4] Loss: 0.20001 focal_loss 0.13698 dice_loss 0.06303 +Epoch [1398/4000] Validation [2/4] Loss: 0.60038 focal_loss 0.36930 dice_loss 0.23108 +Epoch [1398/4000] Validation [3/4] Loss: 0.16743 focal_loss 0.10496 dice_loss 0.06247 +Epoch [1398/4000] Validation [4/4] Loss: 0.35657 focal_loss 0.21148 dice_loss 0.14509 +Epoch [1398/4000] Validation metric {'Val/mean dice_metric': 0.9690251350402832, 'Val/mean miou_metric': 0.9503399729728699, 'Val/mean f1': 0.9720262885093689, 'Val/mean precision': 0.9666289687156677, 'Val/mean recall': 0.9774841666221619, 'Val/mean hd95_metric': 6.40441370010376} +Cheakpoint... +Epoch [1398/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690251350402832, 'Val/mean miou_metric': 0.9503399729728699, 'Val/mean f1': 0.9720262885093689, 'Val/mean precision': 0.9666289687156677, 'Val/mean recall': 0.9774841666221619, 'Val/mean hd95_metric': 6.40441370010376} +Epoch [1399/4000] Training [1/16] Loss: 0.01366 +Epoch [1399/4000] Training [2/16] Loss: 0.00954 +Epoch [1399/4000] Training [3/16] Loss: 0.01267 +Epoch [1399/4000] Training [4/16] Loss: 0.00647 +Epoch [1399/4000] Training [5/16] Loss: 0.01016 +Epoch [1399/4000] Training [6/16] Loss: 0.00959 +Epoch [1399/4000] Training [7/16] Loss: 0.00806 +Epoch [1399/4000] Training [8/16] Loss: 0.01167 +Epoch [1399/4000] Training [9/16] Loss: 0.01043 +Epoch [1399/4000] Training [10/16] Loss: 0.00919 +Epoch [1399/4000] Training [11/16] Loss: 0.01026 +Epoch [1399/4000] Training [12/16] Loss: 0.00745 +Epoch [1399/4000] Training [13/16] Loss: 0.00796 +Epoch [1399/4000] Training [14/16] Loss: 0.01022 +Epoch [1399/4000] Training [15/16] Loss: 0.00841 +Epoch [1399/4000] Training [16/16] Loss: 0.00859 +Epoch [1399/4000] Training metric {'Train/mean dice_metric': 0.9935131072998047, 'Train/mean miou_metric': 0.9868507385253906, 'Train/mean f1': 0.9896584153175354, 'Train/mean precision': 0.9851493239402771, 'Train/mean recall': 0.9942089319229126, 'Train/mean hd95_metric': 1.117060661315918} +Epoch [1399/4000] Validation [1/4] Loss: 0.16781 focal_loss 0.11007 dice_loss 0.05774 +Epoch [1399/4000] Validation [2/4] Loss: 0.20729 focal_loss 0.10723 dice_loss 0.10005 +Epoch [1399/4000] Validation [3/4] Loss: 0.24587 focal_loss 0.16000 dice_loss 0.08587 +Epoch [1399/4000] Validation [4/4] Loss: 0.29479 focal_loss 0.16729 dice_loss 0.12751 +Epoch [1399/4000] Validation metric {'Val/mean dice_metric': 0.9720285534858704, 'Val/mean miou_metric': 0.9532024264335632, 'Val/mean f1': 0.9713439345359802, 'Val/mean precision': 0.965187132358551, 'Val/mean recall': 0.9775797724723816, 'Val/mean hd95_metric': 5.57177734375} +Cheakpoint... +Epoch [1399/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720285534858704, 'Val/mean miou_metric': 0.9532024264335632, 'Val/mean f1': 0.9713439345359802, 'Val/mean precision': 0.965187132358551, 'Val/mean recall': 0.9775797724723816, 'Val/mean hd95_metric': 5.57177734375} +Epoch [1400/4000] Training [1/16] Loss: 0.00785 +Epoch [1400/4000] Training [2/16] Loss: 0.00767 +Epoch [1400/4000] Training [3/16] Loss: 0.00793 +Epoch [1400/4000] Training [4/16] Loss: 0.00960 +Epoch [1400/4000] Training [5/16] Loss: 0.01159 +Epoch [1400/4000] Training [6/16] Loss: 0.01042 +Epoch [1400/4000] Training [7/16] Loss: 0.01094 +Epoch [1400/4000] Training [8/16] Loss: 0.00868 +Epoch [1400/4000] Training [9/16] Loss: 0.01157 +Epoch [1400/4000] Training [10/16] Loss: 0.00927 +Epoch [1400/4000] Training [11/16] Loss: 0.00771 +Epoch [1400/4000] Training [12/16] Loss: 0.01072 +Epoch [1400/4000] Training [13/16] Loss: 0.00749 +Epoch [1400/4000] Training [14/16] Loss: 0.00804 +Epoch [1400/4000] Training [15/16] Loss: 0.01200 +Epoch [1400/4000] Training [16/16] Loss: 0.01196 +Epoch [1400/4000] Training metric {'Train/mean dice_metric': 0.9937062859535217, 'Train/mean miou_metric': 0.9872450232505798, 'Train/mean f1': 0.9899457097053528, 'Train/mean precision': 0.9853895306587219, 'Train/mean recall': 0.9945441484451294, 'Train/mean hd95_metric': 1.0418518781661987} +Epoch [1400/4000] Validation [1/4] Loss: 0.20244 focal_loss 0.14199 dice_loss 0.06045 +Epoch [1400/4000] Validation [2/4] Loss: 0.35457 focal_loss 0.19037 dice_loss 0.16420 +Epoch [1400/4000] Validation [3/4] Loss: 0.24887 focal_loss 0.15197 dice_loss 0.09690 +Epoch [1400/4000] Validation [4/4] Loss: 0.24720 focal_loss 0.12839 dice_loss 0.11881 +Epoch [1400/4000] Validation metric {'Val/mean dice_metric': 0.9712309837341309, 'Val/mean miou_metric': 0.952767014503479, 'Val/mean f1': 0.9713799953460693, 'Val/mean precision': 0.9656937718391418, 'Val/mean recall': 0.9771336913108826, 'Val/mean hd95_metric': 5.700740814208984} +Cheakpoint... +Epoch [1400/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712309837341309, 'Val/mean miou_metric': 0.952767014503479, 'Val/mean f1': 0.9713799953460693, 'Val/mean precision': 0.9656937718391418, 'Val/mean recall': 0.9771336913108826, 'Val/mean hd95_metric': 5.700740814208984} +Epoch [1401/4000] Training [1/16] Loss: 0.00724 +Epoch [1401/4000] Training [2/16] Loss: 0.00936 +Epoch [1401/4000] Training [3/16] Loss: 0.00869 +Epoch [1401/4000] Training [4/16] Loss: 0.00977 +Epoch [1401/4000] Training [5/16] Loss: 0.00862 +Epoch [1401/4000] Training [6/16] Loss: 0.00768 +Epoch [1401/4000] Training [7/16] Loss: 0.00812 +Epoch [1401/4000] Training [8/16] Loss: 0.01239 +Epoch [1401/4000] Training [9/16] Loss: 0.00825 +Epoch [1401/4000] Training [10/16] Loss: 0.01049 +Epoch [1401/4000] Training [11/16] Loss: 0.00831 +Epoch [1401/4000] Training [12/16] Loss: 0.00762 +Epoch [1401/4000] Training [13/16] Loss: 0.01209 +Epoch [1401/4000] Training [14/16] Loss: 0.04415 +Epoch [1401/4000] Training [15/16] Loss: 0.01456 +Epoch [1401/4000] Training [16/16] Loss: 0.00903 +Epoch [1401/4000] Training metric {'Train/mean dice_metric': 0.9925413727760315, 'Train/mean miou_metric': 0.9852889776229858, 'Train/mean f1': 0.9893852472305298, 'Train/mean precision': 0.9847750663757324, 'Train/mean recall': 0.9940388202667236, 'Train/mean hd95_metric': 2.142179250717163} +Epoch [1401/4000] Validation [1/4] Loss: 0.16430 focal_loss 0.10701 dice_loss 0.05729 +Epoch [1401/4000] Validation [2/4] Loss: 0.36181 focal_loss 0.22828 dice_loss 0.13354 +Epoch [1401/4000] Validation [3/4] Loss: 0.44838 focal_loss 0.32042 dice_loss 0.12796 +Epoch [1401/4000] Validation [4/4] Loss: 0.31792 focal_loss 0.17955 dice_loss 0.13837 +Epoch [1401/4000] Validation metric {'Val/mean dice_metric': 0.9694429636001587, 'Val/mean miou_metric': 0.9498775601387024, 'Val/mean f1': 0.9698655009269714, 'Val/mean precision': 0.9619178175926208, 'Val/mean recall': 0.9779456257820129, 'Val/mean hd95_metric': 7.508954048156738} +Cheakpoint... +Epoch [1401/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694429636001587, 'Val/mean miou_metric': 0.9498775601387024, 'Val/mean f1': 0.9698655009269714, 'Val/mean precision': 0.9619178175926208, 'Val/mean recall': 0.9779456257820129, 'Val/mean hd95_metric': 7.508954048156738} +Epoch [1402/4000] Training [1/16] Loss: 0.00864 +Epoch [1402/4000] Training [2/16] Loss: 0.00939 +Epoch [1402/4000] Training [3/16] Loss: 0.00678 +Epoch [1402/4000] Training [4/16] Loss: 0.00955 +Epoch [1402/4000] Training [5/16] Loss: 0.01193 +Epoch [1402/4000] Training [6/16] Loss: 0.00712 +Epoch [1402/4000] Training [7/16] Loss: 0.01634 +Epoch [1402/4000] Training [8/16] Loss: 0.01845 +Epoch [1402/4000] Training [9/16] Loss: 0.01501 +Epoch [1402/4000] Training [10/16] Loss: 0.01546 +Epoch [1402/4000] Training [11/16] Loss: 0.01070 +Epoch [1402/4000] Training [12/16] Loss: 0.01298 +Epoch [1402/4000] Training [13/16] Loss: 0.00906 +Epoch [1402/4000] Training [14/16] Loss: 0.01228 +Epoch [1402/4000] Training [15/16] Loss: 0.01061 +Epoch [1402/4000] Training [16/16] Loss: 0.01163 +Epoch [1402/4000] Training metric {'Train/mean dice_metric': 0.9926666021347046, 'Train/mean miou_metric': 0.9851992130279541, 'Train/mean f1': 0.9889141917228699, 'Train/mean precision': 0.9844470620155334, 'Train/mean recall': 0.9934220314025879, 'Train/mean hd95_metric': 1.5350979566574097} +Epoch [1402/4000] Validation [1/4] Loss: 0.15424 focal_loss 0.09354 dice_loss 0.06070 +Epoch [1402/4000] Validation [2/4] Loss: 0.34290 focal_loss 0.19219 dice_loss 0.15071 +Epoch [1402/4000] Validation [3/4] Loss: 0.27961 focal_loss 0.17953 dice_loss 0.10008 +Epoch [1402/4000] Validation [4/4] Loss: 0.20843 focal_loss 0.11523 dice_loss 0.09320 +Epoch [1402/4000] Validation metric {'Val/mean dice_metric': 0.9676961898803711, 'Val/mean miou_metric': 0.9481415748596191, 'Val/mean f1': 0.9676943421363831, 'Val/mean precision': 0.9594221711158752, 'Val/mean recall': 0.9761103391647339, 'Val/mean hd95_metric': 6.532550811767578} +Cheakpoint... +Epoch [1402/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676961898803711, 'Val/mean miou_metric': 0.9481415748596191, 'Val/mean f1': 0.9676943421363831, 'Val/mean precision': 0.9594221711158752, 'Val/mean recall': 0.9761103391647339, 'Val/mean hd95_metric': 6.532550811767578} +Epoch [1403/4000] Training [1/16] Loss: 0.01240 +Epoch [1403/4000] Training [2/16] Loss: 0.01216 +Epoch [1403/4000] Training [3/16] Loss: 0.01072 +Epoch [1403/4000] Training [4/16] Loss: 0.00807 +Epoch [1403/4000] Training [5/16] Loss: 0.00952 +Epoch [1403/4000] Training [6/16] Loss: 0.01333 +Epoch [1403/4000] Training [7/16] Loss: 0.00935 +Epoch [1403/4000] Training [8/16] Loss: 0.00938 +Epoch [1403/4000] Training [9/16] Loss: 0.01152 +Epoch [1403/4000] Training [10/16] Loss: 0.00910 +Epoch [1403/4000] Training [11/16] Loss: 0.00824 +Epoch [1403/4000] Training [12/16] Loss: 0.14948 +Epoch [1403/4000] Training [13/16] Loss: 0.00822 +Epoch [1403/4000] Training [14/16] Loss: 0.01177 +Epoch [1403/4000] Training [15/16] Loss: 0.01337 +Epoch [1403/4000] Training [16/16] Loss: 0.02045 +Epoch [1403/4000] Training metric {'Train/mean dice_metric': 0.9914764165878296, 'Train/mean miou_metric': 0.983406662940979, 'Train/mean f1': 0.9882661700248718, 'Train/mean precision': 0.9832504391670227, 'Train/mean recall': 0.9933332800865173, 'Train/mean hd95_metric': 2.087773084640503} +Epoch [1403/4000] Validation [1/4] Loss: 0.22138 focal_loss 0.15913 dice_loss 0.06225 +Epoch [1403/4000] Validation [2/4] Loss: 0.42673 focal_loss 0.25191 dice_loss 0.17482 +Epoch [1403/4000] Validation [3/4] Loss: 0.34203 focal_loss 0.22961 dice_loss 0.11242 +Epoch [1403/4000] Validation [4/4] Loss: 0.31603 focal_loss 0.18236 dice_loss 0.13367 +Epoch [1403/4000] Validation metric {'Val/mean dice_metric': 0.9636114239692688, 'Val/mean miou_metric': 0.942897617816925, 'Val/mean f1': 0.9651740789413452, 'Val/mean precision': 0.9554210901260376, 'Val/mean recall': 0.975128173828125, 'Val/mean hd95_metric': 9.533430099487305} +Cheakpoint... +Epoch [1403/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9636], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9636114239692688, 'Val/mean miou_metric': 0.942897617816925, 'Val/mean f1': 0.9651740789413452, 'Val/mean precision': 0.9554210901260376, 'Val/mean recall': 0.975128173828125, 'Val/mean hd95_metric': 9.533430099487305} +Epoch [1404/4000] Training [1/16] Loss: 0.00918 +Epoch [1404/4000] Training [2/16] Loss: 0.01623 +Epoch [1404/4000] Training [3/16] Loss: 0.01188 +Epoch [1404/4000] Training [4/16] Loss: 0.01237 +Epoch [1404/4000] Training [5/16] Loss: 0.01035 +Epoch [1404/4000] Training [6/16] Loss: 0.00938 +Epoch [1404/4000] Training [7/16] Loss: 0.01056 +Epoch [1404/4000] Training [8/16] Loss: 0.01388 +Epoch [1404/4000] Training [9/16] Loss: 0.01158 +Epoch [1404/4000] Training [10/16] Loss: 0.01093 +Epoch [1404/4000] Training [11/16] Loss: 0.01048 +Epoch [1404/4000] Training [12/16] Loss: 0.01932 +Epoch [1404/4000] Training [13/16] Loss: 0.01305 +Epoch [1404/4000] Training [14/16] Loss: 0.00921 +Epoch [1404/4000] Training [15/16] Loss: 0.01023 +Epoch [1404/4000] Training [16/16] Loss: 0.01133 +Epoch [1404/4000] Training metric {'Train/mean dice_metric': 0.9914318323135376, 'Train/mean miou_metric': 0.982896625995636, 'Train/mean f1': 0.9882921576499939, 'Train/mean precision': 0.9839525818824768, 'Train/mean recall': 0.9926701188087463, 'Train/mean hd95_metric': 1.8584436178207397} +Epoch [1404/4000] Validation [1/4] Loss: 0.15810 focal_loss 0.10377 dice_loss 0.05433 +Epoch [1404/4000] Validation [2/4] Loss: 0.46748 focal_loss 0.28271 dice_loss 0.18477 +Epoch [1404/4000] Validation [3/4] Loss: 0.20523 focal_loss 0.11857 dice_loss 0.08666 +Epoch [1404/4000] Validation [4/4] Loss: 0.32930 focal_loss 0.18492 dice_loss 0.14438 +Epoch [1404/4000] Validation metric {'Val/mean dice_metric': 0.962405800819397, 'Val/mean miou_metric': 0.9417543411254883, 'Val/mean f1': 0.9671702980995178, 'Val/mean precision': 0.9652581810951233, 'Val/mean recall': 0.9690899848937988, 'Val/mean hd95_metric': 7.378811836242676} +Cheakpoint... +Epoch [1404/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9624], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.962405800819397, 'Val/mean miou_metric': 0.9417543411254883, 'Val/mean f1': 0.9671702980995178, 'Val/mean precision': 0.9652581810951233, 'Val/mean recall': 0.9690899848937988, 'Val/mean hd95_metric': 7.378811836242676} +Epoch [1405/4000] Training [1/16] Loss: 0.01446 +Epoch [1405/4000] Training [2/16] Loss: 0.01166 +Epoch [1405/4000] Training [3/16] Loss: 0.01137 +Epoch [1405/4000] Training [4/16] Loss: 0.00941 +Epoch [1405/4000] Training [5/16] Loss: 0.00951 +Epoch [1405/4000] Training [6/16] Loss: 0.01244 +Epoch [1405/4000] Training [7/16] Loss: 0.00921 +Epoch [1405/4000] Training [8/16] Loss: 0.00909 +Epoch [1405/4000] Training [9/16] Loss: 0.00857 +Epoch [1405/4000] Training [10/16] Loss: 0.00914 +Epoch [1405/4000] Training [11/16] Loss: 0.00997 +Epoch [1405/4000] Training [12/16] Loss: 0.01166 +Epoch [1405/4000] Training [13/16] Loss: 0.01205 +Epoch [1405/4000] Training [14/16] Loss: 0.00875 +Epoch [1405/4000] Training [15/16] Loss: 0.01003 +Epoch [1405/4000] Training [16/16] Loss: 0.00820 +Epoch [1405/4000] Training metric {'Train/mean dice_metric': 0.992458701133728, 'Train/mean miou_metric': 0.9848088026046753, 'Train/mean f1': 0.9888039827346802, 'Train/mean precision': 0.9845268726348877, 'Train/mean recall': 0.993118405342102, 'Train/mean hd95_metric': 1.3147460222244263} +Epoch [1405/4000] Validation [1/4] Loss: 0.16067 focal_loss 0.10176 dice_loss 0.05891 +Epoch [1405/4000] Validation [2/4] Loss: 0.37169 focal_loss 0.21593 dice_loss 0.15576 +Epoch [1405/4000] Validation [3/4] Loss: 0.24843 focal_loss 0.15626 dice_loss 0.09217 +Epoch [1405/4000] Validation [4/4] Loss: 0.23443 focal_loss 0.12072 dice_loss 0.11371 +Epoch [1405/4000] Validation metric {'Val/mean dice_metric': 0.9679731130599976, 'Val/mean miou_metric': 0.9487830996513367, 'Val/mean f1': 0.9717757701873779, 'Val/mean precision': 0.9703667759895325, 'Val/mean recall': 0.9731886982917786, 'Val/mean hd95_metric': 5.673031806945801} +Cheakpoint... +Epoch [1405/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679731130599976, 'Val/mean miou_metric': 0.9487830996513367, 'Val/mean f1': 0.9717757701873779, 'Val/mean precision': 0.9703667759895325, 'Val/mean recall': 0.9731886982917786, 'Val/mean hd95_metric': 5.673031806945801} +Epoch [1406/4000] Training [1/16] Loss: 0.00852 +Epoch [1406/4000] Training [2/16] Loss: 0.05339 +Epoch [1406/4000] Training [3/16] Loss: 0.00817 +Epoch [1406/4000] Training [4/16] Loss: 0.00819 +Epoch [1406/4000] Training [5/16] Loss: 0.01352 +Epoch [1406/4000] Training [6/16] Loss: 0.00947 +Epoch [1406/4000] Training [7/16] Loss: 0.01485 +Epoch [1406/4000] Training [8/16] Loss: 0.01308 +Epoch [1406/4000] Training [9/16] Loss: 0.01228 +Epoch [1406/4000] Training [10/16] Loss: 0.01317 +Epoch [1406/4000] Training [11/16] Loss: 0.00887 +Epoch [1406/4000] Training [12/16] Loss: 0.01312 +Epoch [1406/4000] Training [13/16] Loss: 0.01003 +Epoch [1406/4000] Training [14/16] Loss: 0.01022 +Epoch [1406/4000] Training [15/16] Loss: 0.01063 +Epoch [1406/4000] Training [16/16] Loss: 0.01134 +Epoch [1406/4000] Training metric {'Train/mean dice_metric': 0.9918245077133179, 'Train/mean miou_metric': 0.983818531036377, 'Train/mean f1': 0.9878267049789429, 'Train/mean precision': 0.9832537770271301, 'Train/mean recall': 0.9924423098564148, 'Train/mean hd95_metric': 1.7827708721160889} +Epoch [1406/4000] Validation [1/4] Loss: 0.49651 focal_loss 0.35694 dice_loss 0.13958 +Epoch [1406/4000] Validation [2/4] Loss: 0.62541 focal_loss 0.39567 dice_loss 0.22974 +Epoch [1406/4000] Validation [3/4] Loss: 0.26306 focal_loss 0.15756 dice_loss 0.10549 +Epoch [1406/4000] Validation [4/4] Loss: 0.25329 focal_loss 0.13756 dice_loss 0.11572 +Epoch [1406/4000] Validation metric {'Val/mean dice_metric': 0.9591286778450012, 'Val/mean miou_metric': 0.9385154843330383, 'Val/mean f1': 0.9627100825309753, 'Val/mean precision': 0.9694375991821289, 'Val/mean recall': 0.9560751914978027, 'Val/mean hd95_metric': 6.918005466461182} +Cheakpoint... +Epoch [1406/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9591], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9591286778450012, 'Val/mean miou_metric': 0.9385154843330383, 'Val/mean f1': 0.9627100825309753, 'Val/mean precision': 0.9694375991821289, 'Val/mean recall': 0.9560751914978027, 'Val/mean hd95_metric': 6.918005466461182} +Epoch [1407/4000] Training [1/16] Loss: 0.00891 +Epoch [1407/4000] Training [2/16] Loss: 0.01157 +Epoch [1407/4000] Training [3/16] Loss: 0.01882 +Epoch [1407/4000] Training [4/16] Loss: 0.00906 +Epoch [1407/4000] Training [5/16] Loss: 0.01499 +Epoch [1407/4000] Training [6/16] Loss: 0.01109 +Epoch [1407/4000] Training [7/16] Loss: 0.00963 +Epoch [1407/4000] Training [8/16] Loss: 0.01287 +Epoch [1407/4000] Training [9/16] Loss: 0.01195 +Epoch [1407/4000] Training [10/16] Loss: 0.00986 +Epoch [1407/4000] Training [11/16] Loss: 0.01446 +Epoch [1407/4000] Training [12/16] Loss: 0.00822 +Epoch [1407/4000] Training [13/16] Loss: 0.00803 +Epoch [1407/4000] Training [14/16] Loss: 0.01047 +Epoch [1407/4000] Training [15/16] Loss: 0.00897 +Epoch [1407/4000] Training [16/16] Loss: 0.00917 +Epoch [1407/4000] Training metric {'Train/mean dice_metric': 0.9927372932434082, 'Train/mean miou_metric': 0.9855719804763794, 'Train/mean f1': 0.9878158569335938, 'Train/mean precision': 0.9842991232872009, 'Train/mean recall': 0.9913578629493713, 'Train/mean hd95_metric': 2.223072052001953} +Epoch [1407/4000] Validation [1/4] Loss: 0.15408 focal_loss 0.09403 dice_loss 0.06004 +Epoch [1407/4000] Validation [2/4] Loss: 0.43763 focal_loss 0.24531 dice_loss 0.19232 +Epoch [1407/4000] Validation [3/4] Loss: 0.17136 focal_loss 0.10096 dice_loss 0.07040 +Epoch [1407/4000] Validation [4/4] Loss: 0.26714 focal_loss 0.12720 dice_loss 0.13994 +Epoch [1407/4000] Validation metric {'Val/mean dice_metric': 0.9660428762435913, 'Val/mean miou_metric': 0.9462639689445496, 'Val/mean f1': 0.9687831401824951, 'Val/mean precision': 0.9651702046394348, 'Val/mean recall': 0.9724231958389282, 'Val/mean hd95_metric': 8.201244354248047} +Cheakpoint... +Epoch [1407/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9660], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660428762435913, 'Val/mean miou_metric': 0.9462639689445496, 'Val/mean f1': 0.9687831401824951, 'Val/mean precision': 0.9651702046394348, 'Val/mean recall': 0.9724231958389282, 'Val/mean hd95_metric': 8.201244354248047} +Epoch [1408/4000] Training [1/16] Loss: 0.01316 +Epoch [1408/4000] Training [2/16] Loss: 0.01184 +Epoch [1408/4000] Training [3/16] Loss: 0.01284 +Epoch [1408/4000] Training [4/16] Loss: 0.00838 +Epoch [1408/4000] Training [5/16] Loss: 0.00877 +Epoch [1408/4000] Training [6/16] Loss: 0.00872 +Epoch [1408/4000] Training [7/16] Loss: 0.00932 +Epoch [1408/4000] Training [8/16] Loss: 0.01377 +Epoch [1408/4000] Training [9/16] Loss: 0.01386 +Epoch [1408/4000] Training [10/16] Loss: 0.01210 +Epoch [1408/4000] Training [11/16] Loss: 0.00867 +Epoch [1408/4000] Training [12/16] Loss: 0.00990 +Epoch [1408/4000] Training [13/16] Loss: 0.00911 +Epoch [1408/4000] Training [14/16] Loss: 0.01131 +Epoch [1408/4000] Training [15/16] Loss: 0.00772 +Epoch [1408/4000] Training [16/16] Loss: 0.00946 +Epoch [1408/4000] Training metric {'Train/mean dice_metric': 0.992928683757782, 'Train/mean miou_metric': 0.9856553077697754, 'Train/mean f1': 0.9874900579452515, 'Train/mean precision': 0.9813232421875, 'Train/mean recall': 0.9937348365783691, 'Train/mean hd95_metric': 1.9820518493652344} +Epoch [1408/4000] Validation [1/4] Loss: 0.16334 focal_loss 0.10571 dice_loss 0.05763 +Epoch [1408/4000] Validation [2/4] Loss: 0.36190 focal_loss 0.19476 dice_loss 0.16714 +Epoch [1408/4000] Validation [3/4] Loss: 0.21050 focal_loss 0.13414 dice_loss 0.07635 +Epoch [1408/4000] Validation [4/4] Loss: 0.21033 focal_loss 0.09642 dice_loss 0.11391 +Epoch [1408/4000] Validation metric {'Val/mean dice_metric': 0.9696620106697083, 'Val/mean miou_metric': 0.9502338171005249, 'Val/mean f1': 0.9696255922317505, 'Val/mean precision': 0.9652662873268127, 'Val/mean recall': 0.9740243554115295, 'Val/mean hd95_metric': 7.835880279541016} +Cheakpoint... +Epoch [1408/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696620106697083, 'Val/mean miou_metric': 0.9502338171005249, 'Val/mean f1': 0.9696255922317505, 'Val/mean precision': 0.9652662873268127, 'Val/mean recall': 0.9740243554115295, 'Val/mean hd95_metric': 7.835880279541016} +Epoch [1409/4000] Training [1/16] Loss: 0.01192 +Epoch [1409/4000] Training [2/16] Loss: 0.01335 +Epoch [1409/4000] Training [3/16] Loss: 0.01205 +Epoch [1409/4000] Training [4/16] Loss: 0.00915 +Epoch [1409/4000] Training [5/16] Loss: 0.01111 +Epoch [1409/4000] Training [6/16] Loss: 0.00874 +Epoch [1409/4000] Training [7/16] Loss: 0.00846 +Epoch [1409/4000] Training [8/16] Loss: 0.00895 +Epoch [1409/4000] Training [9/16] Loss: 0.03964 +Epoch [1409/4000] Training [10/16] Loss: 0.00697 +Epoch [1409/4000] Training [11/16] Loss: 0.01044 +Epoch [1409/4000] Training [12/16] Loss: 0.00858 +Epoch [1409/4000] Training [13/16] Loss: 0.01118 +Epoch [1409/4000] Training [14/16] Loss: 0.00848 +Epoch [1409/4000] Training [15/16] Loss: 0.00818 +Epoch [1409/4000] Training [16/16] Loss: 0.00877 +Epoch [1409/4000] Training metric {'Train/mean dice_metric': 0.9933220744132996, 'Train/mean miou_metric': 0.9865012168884277, 'Train/mean f1': 0.9887751340866089, 'Train/mean precision': 0.9840677380561829, 'Train/mean recall': 0.9935277700424194, 'Train/mean hd95_metric': 1.1813066005706787} +Epoch [1409/4000] Validation [1/4] Loss: 0.22648 focal_loss 0.16047 dice_loss 0.06601 +Epoch [1409/4000] Validation [2/4] Loss: 0.77532 focal_loss 0.45901 dice_loss 0.31631 +Epoch [1409/4000] Validation [3/4] Loss: 0.14007 focal_loss 0.08026 dice_loss 0.05981 +Epoch [1409/4000] Validation [4/4] Loss: 0.36116 focal_loss 0.22501 dice_loss 0.13615 +Epoch [1409/4000] Validation metric {'Val/mean dice_metric': 0.9658923149108887, 'Val/mean miou_metric': 0.9471752047538757, 'Val/mean f1': 0.968421220779419, 'Val/mean precision': 0.9659813642501831, 'Val/mean recall': 0.9708735346794128, 'Val/mean hd95_metric': 6.379560947418213} +Cheakpoint... +Epoch [1409/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9659], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9658923149108887, 'Val/mean miou_metric': 0.9471752047538757, 'Val/mean f1': 0.968421220779419, 'Val/mean precision': 0.9659813642501831, 'Val/mean recall': 0.9708735346794128, 'Val/mean hd95_metric': 6.379560947418213} +Epoch [1410/4000] Training [1/16] Loss: 0.00885 +Epoch [1410/4000] Training [2/16] Loss: 0.01183 +Epoch [1410/4000] Training [3/16] Loss: 0.00971 +Epoch [1410/4000] Training [4/16] Loss: 0.00725 +Epoch [1410/4000] Training [5/16] Loss: 0.01130 +Epoch [1410/4000] Training [6/16] Loss: 0.00756 +Epoch [1410/4000] Training [7/16] Loss: 0.01198 +Epoch [1410/4000] Training [8/16] Loss: 0.01437 +Epoch [1410/4000] Training [9/16] Loss: 0.01253 +Epoch [1410/4000] Training [10/16] Loss: 0.00949 +Epoch [1410/4000] Training [11/16] Loss: 0.00887 +Epoch [1410/4000] Training [12/16] Loss: 0.01161 +Epoch [1410/4000] Training [13/16] Loss: 0.00844 +Epoch [1410/4000] Training [14/16] Loss: 0.00627 +Epoch [1410/4000] Training [15/16] Loss: 0.01063 +Epoch [1410/4000] Training [16/16] Loss: 0.01151 +Epoch [1410/4000] Training metric {'Train/mean dice_metric': 0.9933335185050964, 'Train/mean miou_metric': 0.9865202307701111, 'Train/mean f1': 0.9894083142280579, 'Train/mean precision': 0.9847825765609741, 'Train/mean recall': 0.994077742099762, 'Train/mean hd95_metric': 1.4641878604888916} +Epoch [1410/4000] Validation [1/4] Loss: 0.30619 focal_loss 0.22739 dice_loss 0.07881 +Epoch [1410/4000] Validation [2/4] Loss: 0.38520 focal_loss 0.21215 dice_loss 0.17305 +Epoch [1410/4000] Validation [3/4] Loss: 0.35916 focal_loss 0.24997 dice_loss 0.10919 +Epoch [1410/4000] Validation [4/4] Loss: 0.23365 focal_loss 0.12791 dice_loss 0.10574 +Epoch [1410/4000] Validation metric {'Val/mean dice_metric': 0.9704650044441223, 'Val/mean miou_metric': 0.9508813619613647, 'Val/mean f1': 0.9704664349555969, 'Val/mean precision': 0.9668206572532654, 'Val/mean recall': 0.9741398096084595, 'Val/mean hd95_metric': 6.174485206604004} +Cheakpoint... +Epoch [1410/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704650044441223, 'Val/mean miou_metric': 0.9508813619613647, 'Val/mean f1': 0.9704664349555969, 'Val/mean precision': 0.9668206572532654, 'Val/mean recall': 0.9741398096084595, 'Val/mean hd95_metric': 6.174485206604004} +Epoch [1411/4000] Training [1/16] Loss: 0.00879 +Epoch [1411/4000] Training [2/16] Loss: 0.00853 +Epoch [1411/4000] Training [3/16] Loss: 0.00837 +Epoch [1411/4000] Training [4/16] Loss: 0.00949 +Epoch [1411/4000] Training [5/16] Loss: 0.00758 +Epoch [1411/4000] Training [6/16] Loss: 0.00625 +Epoch [1411/4000] Training [7/16] Loss: 0.00816 +Epoch [1411/4000] Training [8/16] Loss: 0.00711 +Epoch [1411/4000] Training [9/16] Loss: 0.00841 +Epoch [1411/4000] Training [10/16] Loss: 0.00834 +Epoch [1411/4000] Training [11/16] Loss: 0.00906 +Epoch [1411/4000] Training [12/16] Loss: 0.01063 +Epoch [1411/4000] Training [13/16] Loss: 0.04103 +Epoch [1411/4000] Training [14/16] Loss: 0.01089 +Epoch [1411/4000] Training [15/16] Loss: 0.00866 +Epoch [1411/4000] Training [16/16] Loss: 0.02296 +Epoch [1411/4000] Training metric {'Train/mean dice_metric': 0.9933657050132751, 'Train/mean miou_metric': 0.9867474436759949, 'Train/mean f1': 0.9890066981315613, 'Train/mean precision': 0.9839516282081604, 'Train/mean recall': 0.9941139221191406, 'Train/mean hd95_metric': 1.2244479656219482} +Epoch [1411/4000] Validation [1/4] Loss: 0.20875 focal_loss 0.14717 dice_loss 0.06158 +Epoch [1411/4000] Validation [2/4] Loss: 0.35516 focal_loss 0.20880 dice_loss 0.14636 +Epoch [1411/4000] Validation [3/4] Loss: 0.19027 focal_loss 0.11486 dice_loss 0.07542 +Epoch [1411/4000] Validation [4/4] Loss: 0.34845 focal_loss 0.21889 dice_loss 0.12956 +Epoch [1411/4000] Validation metric {'Val/mean dice_metric': 0.9714514017105103, 'Val/mean miou_metric': 0.9523624181747437, 'Val/mean f1': 0.9718166589736938, 'Val/mean precision': 0.9699202179908752, 'Val/mean recall': 0.9737204909324646, 'Val/mean hd95_metric': 5.729439735412598} +Cheakpoint... +Epoch [1411/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714514017105103, 'Val/mean miou_metric': 0.9523624181747437, 'Val/mean f1': 0.9718166589736938, 'Val/mean precision': 0.9699202179908752, 'Val/mean recall': 0.9737204909324646, 'Val/mean hd95_metric': 5.729439735412598} +Epoch [1412/4000] Training [1/16] Loss: 0.00861 +Epoch [1412/4000] Training [2/16] Loss: 0.00713 +Epoch [1412/4000] Training [3/16] Loss: 0.01109 +Epoch [1412/4000] Training [4/16] Loss: 0.00924 +Epoch [1412/4000] Training [5/16] Loss: 0.00985 +Epoch [1412/4000] Training [6/16] Loss: 0.00758 +Epoch [1412/4000] Training [7/16] Loss: 0.00863 +Epoch [1412/4000] Training [8/16] Loss: 0.00797 +Epoch [1412/4000] Training [9/16] Loss: 0.01260 +Epoch [1412/4000] Training [10/16] Loss: 0.00777 +Epoch [1412/4000] Training [11/16] Loss: 0.01052 +Epoch [1412/4000] Training [12/16] Loss: 0.01928 +Epoch [1412/4000] Training [13/16] Loss: 0.01032 +Epoch [1412/4000] Training [14/16] Loss: 0.01036 +Epoch [1412/4000] Training [15/16] Loss: 0.01478 +Epoch [1412/4000] Training [16/16] Loss: 0.00926 +Epoch [1412/4000] Training metric {'Train/mean dice_metric': 0.9937542080879211, 'Train/mean miou_metric': 0.9873268604278564, 'Train/mean f1': 0.9893395304679871, 'Train/mean precision': 0.9844988584518433, 'Train/mean recall': 0.9942280054092407, 'Train/mean hd95_metric': 1.1448264122009277} +Epoch [1412/4000] Validation [1/4] Loss: 0.19106 focal_loss 0.13538 dice_loss 0.05568 +Epoch [1412/4000] Validation [2/4] Loss: 0.28171 focal_loss 0.15845 dice_loss 0.12325 +Epoch [1412/4000] Validation [3/4] Loss: 0.22824 focal_loss 0.13618 dice_loss 0.09206 +Epoch [1412/4000] Validation [4/4] Loss: 0.22713 focal_loss 0.11737 dice_loss 0.10976 +Epoch [1412/4000] Validation metric {'Val/mean dice_metric': 0.9718509912490845, 'Val/mean miou_metric': 0.9533794522285461, 'Val/mean f1': 0.9726306796073914, 'Val/mean precision': 0.9698944091796875, 'Val/mean recall': 0.9753823280334473, 'Val/mean hd95_metric': 5.5766706466674805} +Cheakpoint... +Epoch [1412/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718509912490845, 'Val/mean miou_metric': 0.9533794522285461, 'Val/mean f1': 0.9726306796073914, 'Val/mean precision': 0.9698944091796875, 'Val/mean recall': 0.9753823280334473, 'Val/mean hd95_metric': 5.5766706466674805} +Epoch [1413/4000] Training [1/16] Loss: 0.00925 +Epoch [1413/4000] Training [2/16] Loss: 0.00692 +Epoch [1413/4000] Training [3/16] Loss: 0.00831 +Epoch [1413/4000] Training [4/16] Loss: 0.00733 +Epoch [1413/4000] Training [5/16] Loss: 0.01282 +Epoch [1413/4000] Training [6/16] Loss: 0.01126 +Epoch [1413/4000] Training [7/16] Loss: 0.00845 +Epoch [1413/4000] Training [8/16] Loss: 0.00773 +Epoch [1413/4000] Training [9/16] Loss: 0.01000 +Epoch [1413/4000] Training [10/16] Loss: 0.00918 +Epoch [1413/4000] Training [11/16] Loss: 0.00975 +Epoch [1413/4000] Training [12/16] Loss: 0.00821 +Epoch [1413/4000] Training [13/16] Loss: 0.00866 +Epoch [1413/4000] Training [14/16] Loss: 0.01032 +Epoch [1413/4000] Training [15/16] Loss: 0.00737 +Epoch [1413/4000] Training [16/16] Loss: 0.00920 +Epoch [1413/4000] Training metric {'Train/mean dice_metric': 0.993909478187561, 'Train/mean miou_metric': 0.9876281023025513, 'Train/mean f1': 0.9895932078361511, 'Train/mean precision': 0.9846287965774536, 'Train/mean recall': 0.9946079850196838, 'Train/mean hd95_metric': 1.1076717376708984} +Epoch [1413/4000] Validation [1/4] Loss: 0.23338 focal_loss 0.15116 dice_loss 0.08221 +Epoch [1413/4000] Validation [2/4] Loss: 0.29359 focal_loss 0.16363 dice_loss 0.12996 +Epoch [1413/4000] Validation [3/4] Loss: 0.19261 focal_loss 0.11691 dice_loss 0.07571 +Epoch [1413/4000] Validation [4/4] Loss: 0.23891 focal_loss 0.12718 dice_loss 0.11173 +Epoch [1413/4000] Validation metric {'Val/mean dice_metric': 0.9692876935005188, 'Val/mean miou_metric': 0.9507447481155396, 'Val/mean f1': 0.969563901424408, 'Val/mean precision': 0.963716983795166, 'Val/mean recall': 0.975482165813446, 'Val/mean hd95_metric': 6.394776344299316} +Cheakpoint... +Epoch [1413/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692876935005188, 'Val/mean miou_metric': 0.9507447481155396, 'Val/mean f1': 0.969563901424408, 'Val/mean precision': 0.963716983795166, 'Val/mean recall': 0.975482165813446, 'Val/mean hd95_metric': 6.394776344299316} +Epoch [1414/4000] Training [1/16] Loss: 0.00645 +Epoch [1414/4000] Training [2/16] Loss: 0.00820 +Epoch [1414/4000] Training [3/16] Loss: 0.01045 +Epoch [1414/4000] Training [4/16] Loss: 0.00990 +Epoch [1414/4000] Training [5/16] Loss: 0.01063 +Epoch [1414/4000] Training [6/16] Loss: 0.00746 +Epoch [1414/4000] Training [7/16] Loss: 0.01007 +Epoch [1414/4000] Training [8/16] Loss: 0.01040 +Epoch [1414/4000] Training [9/16] Loss: 0.00894 +Epoch [1414/4000] Training [10/16] Loss: 0.01324 +Epoch [1414/4000] Training [11/16] Loss: 0.00893 +Epoch [1414/4000] Training [12/16] Loss: 0.01064 +Epoch [1414/4000] Training [13/16] Loss: 0.00972 +Epoch [1414/4000] Training [14/16] Loss: 0.01288 +Epoch [1414/4000] Training [15/16] Loss: 0.00925 +Epoch [1414/4000] Training [16/16] Loss: 0.00797 +Epoch [1414/4000] Training metric {'Train/mean dice_metric': 0.9933927059173584, 'Train/mean miou_metric': 0.9866345524787903, 'Train/mean f1': 0.9896952509880066, 'Train/mean precision': 0.9851681590080261, 'Train/mean recall': 0.9942642450332642, 'Train/mean hd95_metric': 1.0729238986968994} +Epoch [1414/4000] Validation [1/4] Loss: 0.63789 focal_loss 0.51870 dice_loss 0.11919 +Epoch [1414/4000] Validation [2/4] Loss: 0.26566 focal_loss 0.13882 dice_loss 0.12684 +Epoch [1414/4000] Validation [3/4] Loss: 0.20784 focal_loss 0.13260 dice_loss 0.07524 +Epoch [1414/4000] Validation [4/4] Loss: 0.24370 focal_loss 0.13010 dice_loss 0.11360 +Epoch [1414/4000] Validation metric {'Val/mean dice_metric': 0.9692367315292358, 'Val/mean miou_metric': 0.949724555015564, 'Val/mean f1': 0.9703201651573181, 'Val/mean precision': 0.9703816771507263, 'Val/mean recall': 0.9702586531639099, 'Val/mean hd95_metric': 6.446234226226807} +Cheakpoint... +Epoch [1414/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692367315292358, 'Val/mean miou_metric': 0.949724555015564, 'Val/mean f1': 0.9703201651573181, 'Val/mean precision': 0.9703816771507263, 'Val/mean recall': 0.9702586531639099, 'Val/mean hd95_metric': 6.446234226226807} +Epoch [1415/4000] Training [1/16] Loss: 0.00701 +Epoch [1415/4000] Training [2/16] Loss: 0.00796 +Epoch [1415/4000] Training [3/16] Loss: 0.01159 +Epoch [1415/4000] Training [4/16] Loss: 0.00827 +Epoch [1415/4000] Training [5/16] Loss: 0.01038 +Epoch [1415/4000] Training [6/16] Loss: 0.01071 +Epoch [1415/4000] Training [7/16] Loss: 0.00839 +Epoch [1415/4000] Training [8/16] Loss: 0.00748 +Epoch [1415/4000] Training [9/16] Loss: 0.00862 +Epoch [1415/4000] Training [10/16] Loss: 0.00765 +Epoch [1415/4000] Training [11/16] Loss: 0.00932 +Epoch [1415/4000] Training [12/16] Loss: 0.01084 +Epoch [1415/4000] Training [13/16] Loss: 0.00903 +Epoch [1415/4000] Training [14/16] Loss: 0.00891 +Epoch [1415/4000] Training [15/16] Loss: 0.00716 +Epoch [1415/4000] Training [16/16] Loss: 0.01446 +Epoch [1415/4000] Training metric {'Train/mean dice_metric': 0.9936378002166748, 'Train/mean miou_metric': 0.9871124029159546, 'Train/mean f1': 0.9897919297218323, 'Train/mean precision': 0.9853472709655762, 'Train/mean recall': 0.9942768216133118, 'Train/mean hd95_metric': 1.119781494140625} +Epoch [1415/4000] Validation [1/4] Loss: 0.21608 focal_loss 0.14862 dice_loss 0.06746 +Epoch [1415/4000] Validation [2/4] Loss: 0.49372 focal_loss 0.30537 dice_loss 0.18835 +Epoch [1415/4000] Validation [3/4] Loss: 0.17879 focal_loss 0.10604 dice_loss 0.07274 +Epoch [1415/4000] Validation [4/4] Loss: 0.20127 focal_loss 0.09697 dice_loss 0.10430 +Epoch [1415/4000] Validation metric {'Val/mean dice_metric': 0.9708182215690613, 'Val/mean miou_metric': 0.9526597857475281, 'Val/mean f1': 0.9732178449630737, 'Val/mean precision': 0.970562219619751, 'Val/mean recall': 0.9758880138397217, 'Val/mean hd95_metric': 5.417283535003662} +Cheakpoint... +Epoch [1415/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708182215690613, 'Val/mean miou_metric': 0.9526597857475281, 'Val/mean f1': 0.9732178449630737, 'Val/mean precision': 0.970562219619751, 'Val/mean recall': 0.9758880138397217, 'Val/mean hd95_metric': 5.417283535003662} +Epoch [1416/4000] Training [1/16] Loss: 0.00706 +Epoch [1416/4000] Training [2/16] Loss: 0.01023 +Epoch [1416/4000] Training [3/16] Loss: 0.00954 +Epoch [1416/4000] Training [4/16] Loss: 0.00708 +Epoch [1416/4000] Training [5/16] Loss: 0.00765 +Epoch [1416/4000] Training [6/16] Loss: 0.00839 +Epoch [1416/4000] Training [7/16] Loss: 0.00983 +Epoch [1416/4000] Training [8/16] Loss: 0.00987 +Epoch [1416/4000] Training [9/16] Loss: 0.00986 +Epoch [1416/4000] Training [10/16] Loss: 0.00917 +Epoch [1416/4000] Training [11/16] Loss: 0.01318 +Epoch [1416/4000] Training [12/16] Loss: 0.01146 +Epoch [1416/4000] Training [13/16] Loss: 0.01029 +Epoch [1416/4000] Training [14/16] Loss: 0.00824 +Epoch [1416/4000] Training [15/16] Loss: 0.01116 +Epoch [1416/4000] Training [16/16] Loss: 0.00900 +Epoch [1416/4000] Training metric {'Train/mean dice_metric': 0.9937658309936523, 'Train/mean miou_metric': 0.9873790740966797, 'Train/mean f1': 0.9900034070014954, 'Train/mean precision': 0.985403299331665, 'Train/mean recall': 0.9946466684341431, 'Train/mean hd95_metric': 1.0764718055725098} +Epoch [1416/4000] Validation [1/4] Loss: 0.20533 focal_loss 0.13970 dice_loss 0.06563 +Epoch [1416/4000] Validation [2/4] Loss: 0.29538 focal_loss 0.16837 dice_loss 0.12701 +Epoch [1416/4000] Validation [3/4] Loss: 0.21250 focal_loss 0.11922 dice_loss 0.09328 +Epoch [1416/4000] Validation [4/4] Loss: 0.26609 focal_loss 0.14199 dice_loss 0.12410 +Epoch [1416/4000] Validation metric {'Val/mean dice_metric': 0.9716309309005737, 'Val/mean miou_metric': 0.9529529809951782, 'Val/mean f1': 0.971539318561554, 'Val/mean precision': 0.9668211340904236, 'Val/mean recall': 0.9763038754463196, 'Val/mean hd95_metric': 5.907830238342285} +Cheakpoint... +Epoch [1416/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716309309005737, 'Val/mean miou_metric': 0.9529529809951782, 'Val/mean f1': 0.971539318561554, 'Val/mean precision': 0.9668211340904236, 'Val/mean recall': 0.9763038754463196, 'Val/mean hd95_metric': 5.907830238342285} +Epoch [1417/4000] Training [1/16] Loss: 0.00623 +Epoch [1417/4000] Training [2/16] Loss: 0.01288 +Epoch [1417/4000] Training [3/16] Loss: 0.00849 +Epoch [1417/4000] Training [4/16] Loss: 0.00693 +Epoch [1417/4000] Training [5/16] Loss: 0.00988 +Epoch [1417/4000] Training [6/16] Loss: 0.00866 +Epoch [1417/4000] Training [7/16] Loss: 0.00814 +Epoch [1417/4000] Training [8/16] Loss: 0.01107 +Epoch [1417/4000] Training [9/16] Loss: 0.00684 +Epoch [1417/4000] Training [10/16] Loss: 0.00783 +Epoch [1417/4000] Training [11/16] Loss: 0.00725 +Epoch [1417/4000] Training [12/16] Loss: 0.01151 +Epoch [1417/4000] Training [13/16] Loss: 0.00816 +Epoch [1417/4000] Training [14/16] Loss: 0.00881 +Epoch [1417/4000] Training [15/16] Loss: 0.00958 +Epoch [1417/4000] Training [16/16] Loss: 0.00972 +Epoch [1417/4000] Training metric {'Train/mean dice_metric': 0.9939067363739014, 'Train/mean miou_metric': 0.9876455664634705, 'Train/mean f1': 0.9901832938194275, 'Train/mean precision': 0.9856218099594116, 'Train/mean recall': 0.9947872161865234, 'Train/mean hd95_metric': 1.0780669450759888} +Epoch [1417/4000] Validation [1/4] Loss: 0.17975 focal_loss 0.12060 dice_loss 0.05915 +Epoch [1417/4000] Validation [2/4] Loss: 0.29693 focal_loss 0.15403 dice_loss 0.14290 +Epoch [1417/4000] Validation [3/4] Loss: 0.24520 focal_loss 0.15736 dice_loss 0.08784 +Epoch [1417/4000] Validation [4/4] Loss: 0.21838 focal_loss 0.11728 dice_loss 0.10110 +Epoch [1417/4000] Validation metric {'Val/mean dice_metric': 0.970962405204773, 'Val/mean miou_metric': 0.9526243209838867, 'Val/mean f1': 0.9731384515762329, 'Val/mean precision': 0.9683438539505005, 'Val/mean recall': 0.9779807925224304, 'Val/mean hd95_metric': 5.819010257720947} +Cheakpoint... +Epoch [1417/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970962405204773, 'Val/mean miou_metric': 0.9526243209838867, 'Val/mean f1': 0.9731384515762329, 'Val/mean precision': 0.9683438539505005, 'Val/mean recall': 0.9779807925224304, 'Val/mean hd95_metric': 5.819010257720947} +Epoch [1418/4000] Training [1/16] Loss: 0.00932 +Epoch [1418/4000] Training [2/16] Loss: 0.00782 +Epoch [1418/4000] Training [3/16] Loss: 0.00736 +Epoch [1418/4000] Training [4/16] Loss: 0.00960 +Epoch [1418/4000] Training [5/16] Loss: 0.01060 +Epoch [1418/4000] Training [6/16] Loss: 0.00754 +Epoch [1418/4000] Training [7/16] Loss: 0.01003 +Epoch [1418/4000] Training [8/16] Loss: 0.00711 +Epoch [1418/4000] Training [9/16] Loss: 0.00729 +Epoch [1418/4000] Training [10/16] Loss: 0.01139 +Epoch [1418/4000] Training [11/16] Loss: 0.00847 +Epoch [1418/4000] Training [12/16] Loss: 0.00746 +Epoch [1418/4000] Training [13/16] Loss: 0.00860 +Epoch [1418/4000] Training [14/16] Loss: 0.00964 +Epoch [1418/4000] Training [15/16] Loss: 0.00933 +Epoch [1418/4000] Training [16/16] Loss: 0.01609 +Epoch [1418/4000] Training metric {'Train/mean dice_metric': 0.9936453104019165, 'Train/mean miou_metric': 0.9870820045471191, 'Train/mean f1': 0.9885201454162598, 'Train/mean precision': 0.9828981757164001, 'Train/mean recall': 0.9942067265510559, 'Train/mean hd95_metric': 1.0673487186431885} +Epoch [1418/4000] Validation [1/4] Loss: 0.17748 focal_loss 0.11836 dice_loss 0.05912 +Epoch [1418/4000] Validation [2/4] Loss: 0.45097 focal_loss 0.24723 dice_loss 0.20374 +Epoch [1418/4000] Validation [3/4] Loss: 0.23335 focal_loss 0.13047 dice_loss 0.10288 +Epoch [1418/4000] Validation [4/4] Loss: 0.26151 focal_loss 0.13614 dice_loss 0.12537 +Epoch [1418/4000] Validation metric {'Val/mean dice_metric': 0.9690054059028625, 'Val/mean miou_metric': 0.9502592086791992, 'Val/mean f1': 0.9709400534629822, 'Val/mean precision': 0.9647494554519653, 'Val/mean recall': 0.9772104620933533, 'Val/mean hd95_metric': 6.217698097229004} +Cheakpoint... +Epoch [1418/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690054059028625, 'Val/mean miou_metric': 0.9502592086791992, 'Val/mean f1': 0.9709400534629822, 'Val/mean precision': 0.9647494554519653, 'Val/mean recall': 0.9772104620933533, 'Val/mean hd95_metric': 6.217698097229004} +Epoch [1419/4000] Training [1/16] Loss: 0.00696 +Epoch [1419/4000] Training [2/16] Loss: 0.00915 +Epoch [1419/4000] Training [3/16] Loss: 0.00712 +Epoch [1419/4000] Training [4/16] Loss: 0.00708 +Epoch [1419/4000] Training [5/16] Loss: 0.00926 +Epoch [1419/4000] Training [6/16] Loss: 0.01165 +Epoch [1419/4000] Training [7/16] Loss: 0.00776 +Epoch [1419/4000] Training [8/16] Loss: 0.00690 +Epoch [1419/4000] Training [9/16] Loss: 0.00905 +Epoch [1419/4000] Training [10/16] Loss: 0.01257 +Epoch [1419/4000] Training [11/16] Loss: 0.00745 +Epoch [1419/4000] Training [12/16] Loss: 0.01240 +Epoch [1419/4000] Training [13/16] Loss: 0.00960 +Epoch [1419/4000] Training [14/16] Loss: 0.00882 +Epoch [1419/4000] Training [15/16] Loss: 0.00828 +Epoch [1419/4000] Training [16/16] Loss: 0.01034 +Epoch [1419/4000] Training metric {'Train/mean dice_metric': 0.9937269687652588, 'Train/mean miou_metric': 0.9873064756393433, 'Train/mean f1': 0.9899740219116211, 'Train/mean precision': 0.985389232635498, 'Train/mean recall': 0.9946017265319824, 'Train/mean hd95_metric': 1.1237297058105469} +Epoch [1419/4000] Validation [1/4] Loss: 0.19247 focal_loss 0.13221 dice_loss 0.06025 +Epoch [1419/4000] Validation [2/4] Loss: 0.29229 focal_loss 0.15361 dice_loss 0.13869 +Epoch [1419/4000] Validation [3/4] Loss: 0.15640 focal_loss 0.09690 dice_loss 0.05949 +Epoch [1419/4000] Validation [4/4] Loss: 0.18032 focal_loss 0.09237 dice_loss 0.08795 +Epoch [1419/4000] Validation metric {'Val/mean dice_metric': 0.9722288250923157, 'Val/mean miou_metric': 0.954450786113739, 'Val/mean f1': 0.9736244678497314, 'Val/mean precision': 0.9693626761436462, 'Val/mean recall': 0.9779239892959595, 'Val/mean hd95_metric': 5.457310676574707} +Cheakpoint... +Epoch [1419/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722288250923157, 'Val/mean miou_metric': 0.954450786113739, 'Val/mean f1': 0.9736244678497314, 'Val/mean precision': 0.9693626761436462, 'Val/mean recall': 0.9779239892959595, 'Val/mean hd95_metric': 5.457310676574707} +Epoch [1420/4000] Training [1/16] Loss: 0.00856 +Epoch [1420/4000] Training [2/16] Loss: 0.00911 +Epoch [1420/4000] Training [3/16] Loss: 0.00859 +Epoch [1420/4000] Training [4/16] Loss: 0.01144 +Epoch [1420/4000] Training [5/16] Loss: 0.00939 +Epoch [1420/4000] Training [6/16] Loss: 0.00941 +Epoch [1420/4000] Training [7/16] Loss: 0.00925 +Epoch [1420/4000] Training [8/16] Loss: 0.01003 +Epoch [1420/4000] Training [9/16] Loss: 0.01015 +Epoch [1420/4000] Training [10/16] Loss: 0.00851 +Epoch [1420/4000] Training [11/16] Loss: 0.00889 +Epoch [1420/4000] Training [12/16] Loss: 0.00857 +Epoch [1420/4000] Training [13/16] Loss: 0.00703 +Epoch [1420/4000] Training [14/16] Loss: 0.00914 +Epoch [1420/4000] Training [15/16] Loss: 0.00861 +Epoch [1420/4000] Training [16/16] Loss: 0.00908 +Epoch [1420/4000] Training metric {'Train/mean dice_metric': 0.9937387704849243, 'Train/mean miou_metric': 0.9872995018959045, 'Train/mean f1': 0.9893749952316284, 'Train/mean precision': 0.9842418432235718, 'Train/mean recall': 0.9945619702339172, 'Train/mean hd95_metric': 1.0573070049285889} +Epoch [1420/4000] Validation [1/4] Loss: 0.19276 focal_loss 0.12560 dice_loss 0.06716 +Epoch [1420/4000] Validation [2/4] Loss: 0.25376 focal_loss 0.13634 dice_loss 0.11742 +Epoch [1420/4000] Validation [3/4] Loss: 0.22168 focal_loss 0.12849 dice_loss 0.09319 +Epoch [1420/4000] Validation [4/4] Loss: 0.25866 focal_loss 0.14363 dice_loss 0.11502 +Epoch [1420/4000] Validation metric {'Val/mean dice_metric': 0.9721037149429321, 'Val/mean miou_metric': 0.9535142183303833, 'Val/mean f1': 0.972484827041626, 'Val/mean precision': 0.9678298234939575, 'Val/mean recall': 0.9771848320960999, 'Val/mean hd95_metric': 5.700875759124756} +Cheakpoint... +Epoch [1420/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721037149429321, 'Val/mean miou_metric': 0.9535142183303833, 'Val/mean f1': 0.972484827041626, 'Val/mean precision': 0.9678298234939575, 'Val/mean recall': 0.9771848320960999, 'Val/mean hd95_metric': 5.700875759124756} +Epoch [1421/4000] Training [1/16] Loss: 0.00798 +Epoch [1421/4000] Training [2/16] Loss: 0.00697 +Epoch [1421/4000] Training [3/16] Loss: 0.00804 +Epoch [1421/4000] Training [4/16] Loss: 0.00816 +Epoch [1421/4000] Training [5/16] Loss: 0.01138 +Epoch [1421/4000] Training [6/16] Loss: 0.01172 +Epoch [1421/4000] Training [7/16] Loss: 0.00943 +Epoch [1421/4000] Training [8/16] Loss: 0.00892 +Epoch [1421/4000] Training [9/16] Loss: 0.00805 +Epoch [1421/4000] Training [10/16] Loss: 0.00794 +Epoch [1421/4000] Training [11/16] Loss: 0.01011 +Epoch [1421/4000] Training [12/16] Loss: 0.00711 +Epoch [1421/4000] Training [13/16] Loss: 0.01322 +Epoch [1421/4000] Training [14/16] Loss: 0.00775 +Epoch [1421/4000] Training [15/16] Loss: 0.00787 +Epoch [1421/4000] Training [16/16] Loss: 0.00901 +Epoch [1421/4000] Training metric {'Train/mean dice_metric': 0.9938614368438721, 'Train/mean miou_metric': 0.9875267148017883, 'Train/mean f1': 0.9891946911811829, 'Train/mean precision': 0.9837775230407715, 'Train/mean recall': 0.9946718811988831, 'Train/mean hd95_metric': 1.0770211219787598} +Epoch [1421/4000] Validation [1/4] Loss: 0.15296 focal_loss 0.09260 dice_loss 0.06036 +Epoch [1421/4000] Validation [2/4] Loss: 0.32968 focal_loss 0.19247 dice_loss 0.13721 +Epoch [1421/4000] Validation [3/4] Loss: 0.13650 focal_loss 0.08188 dice_loss 0.05462 +Epoch [1421/4000] Validation [4/4] Loss: 0.22002 focal_loss 0.09830 dice_loss 0.12172 +Epoch [1421/4000] Validation metric {'Val/mean dice_metric': 0.9718707799911499, 'Val/mean miou_metric': 0.9541306495666504, 'Val/mean f1': 0.9740539789199829, 'Val/mean precision': 0.9699476361274719, 'Val/mean recall': 0.978195071220398, 'Val/mean hd95_metric': 5.453760623931885} +Cheakpoint... +Epoch [1421/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718707799911499, 'Val/mean miou_metric': 0.9541306495666504, 'Val/mean f1': 0.9740539789199829, 'Val/mean precision': 0.9699476361274719, 'Val/mean recall': 0.978195071220398, 'Val/mean hd95_metric': 5.453760623931885} +Epoch [1422/4000] Training [1/16] Loss: 0.00797 +Epoch [1422/4000] Training [2/16] Loss: 0.00913 +Epoch [1422/4000] Training [3/16] Loss: 0.00787 +Epoch [1422/4000] Training [4/16] Loss: 0.00921 +Epoch [1422/4000] Training [5/16] Loss: 0.00759 +Epoch [1422/4000] Training [6/16] Loss: 0.01026 +Epoch [1422/4000] Training [7/16] Loss: 0.00723 +Epoch [1422/4000] Training [8/16] Loss: 0.00867 +Epoch [1422/4000] Training [9/16] Loss: 0.00945 +Epoch [1422/4000] Training [10/16] Loss: 0.00923 +Epoch [1422/4000] Training [11/16] Loss: 0.00798 +Epoch [1422/4000] Training [12/16] Loss: 0.01241 +Epoch [1422/4000] Training [13/16] Loss: 0.00996 +Epoch [1422/4000] Training [14/16] Loss: 0.00717 +Epoch [1422/4000] Training [15/16] Loss: 0.00826 +Epoch [1422/4000] Training [16/16] Loss: 0.00638 +Epoch [1422/4000] Training metric {'Train/mean dice_metric': 0.9938054084777832, 'Train/mean miou_metric': 0.9874538779258728, 'Train/mean f1': 0.990192711353302, 'Train/mean precision': 0.9857100248336792, 'Train/mean recall': 0.9947163462638855, 'Train/mean hd95_metric': 1.0876376628875732} +Epoch [1422/4000] Validation [1/4] Loss: 0.22936 focal_loss 0.16286 dice_loss 0.06649 +Epoch [1422/4000] Validation [2/4] Loss: 0.31318 focal_loss 0.15863 dice_loss 0.15455 +Epoch [1422/4000] Validation [3/4] Loss: 0.23566 focal_loss 0.14441 dice_loss 0.09125 +Epoch [1422/4000] Validation [4/4] Loss: 0.21342 focal_loss 0.11078 dice_loss 0.10264 +Epoch [1422/4000] Validation metric {'Val/mean dice_metric': 0.9700329899787903, 'Val/mean miou_metric': 0.9518951177597046, 'Val/mean f1': 0.9723223447799683, 'Val/mean precision': 0.9676799178123474, 'Val/mean recall': 0.9770095348358154, 'Val/mean hd95_metric': 6.110043525695801} +Cheakpoint... +Epoch [1422/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700329899787903, 'Val/mean miou_metric': 0.9518951177597046, 'Val/mean f1': 0.9723223447799683, 'Val/mean precision': 0.9676799178123474, 'Val/mean recall': 0.9770095348358154, 'Val/mean hd95_metric': 6.110043525695801} +Epoch [1423/4000] Training [1/16] Loss: 0.00920 +Epoch [1423/4000] Training [2/16] Loss: 0.00694 +Epoch [1423/4000] Training [3/16] Loss: 0.00783 +Epoch [1423/4000] Training [4/16] Loss: 0.00718 +Epoch [1423/4000] Training [5/16] Loss: 0.01973 +Epoch [1423/4000] Training [6/16] Loss: 0.00883 +Epoch [1423/4000] Training [7/16] Loss: 0.00807 +Epoch [1423/4000] Training [8/16] Loss: 0.01128 +Epoch [1423/4000] Training [9/16] Loss: 0.00697 +Epoch [1423/4000] Training [10/16] Loss: 0.01067 +Epoch [1423/4000] Training [11/16] Loss: 0.01111 +Epoch [1423/4000] Training [12/16] Loss: 0.00766 +Epoch [1423/4000] Training [13/16] Loss: 0.00758 +Epoch [1423/4000] Training [14/16] Loss: 0.00768 +Epoch [1423/4000] Training [15/16] Loss: 0.00955 +Epoch [1423/4000] Training [16/16] Loss: 0.01159 +Epoch [1423/4000] Training metric {'Train/mean dice_metric': 0.993453860282898, 'Train/mean miou_metric': 0.9867703318595886, 'Train/mean f1': 0.989691972732544, 'Train/mean precision': 0.9850242733955383, 'Train/mean recall': 0.9944040775299072, 'Train/mean hd95_metric': 1.186289668083191} +Epoch [1423/4000] Validation [1/4] Loss: 0.21799 focal_loss 0.15442 dice_loss 0.06357 +Epoch [1423/4000] Validation [2/4] Loss: 0.41813 focal_loss 0.25448 dice_loss 0.16365 +Epoch [1423/4000] Validation [3/4] Loss: 0.28177 focal_loss 0.19020 dice_loss 0.09157 +Epoch [1423/4000] Validation [4/4] Loss: 0.25883 focal_loss 0.14595 dice_loss 0.11288 +Epoch [1423/4000] Validation metric {'Val/mean dice_metric': 0.9715217351913452, 'Val/mean miou_metric': 0.9527003169059753, 'Val/mean f1': 0.9723255634307861, 'Val/mean precision': 0.9665598273277283, 'Val/mean recall': 0.9781603217124939, 'Val/mean hd95_metric': 5.968850135803223} +Cheakpoint... +Epoch [1423/4000] best acc:tensor([0.9735], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715217351913452, 'Val/mean miou_metric': 0.9527003169059753, 'Val/mean f1': 0.9723255634307861, 'Val/mean precision': 0.9665598273277283, 'Val/mean recall': 0.9781603217124939, 'Val/mean hd95_metric': 5.968850135803223} +Epoch [1424/4000] Training [1/16] Loss: 0.00770 +Epoch [1424/4000] Training [2/16] Loss: 0.00786 +Epoch [1424/4000] Training [3/16] Loss: 0.00900 +Epoch [1424/4000] Training [4/16] Loss: 0.00889 +Epoch [1424/4000] Training [5/16] Loss: 0.00800 +Epoch [1424/4000] Training [6/16] Loss: 0.00888 +Epoch [1424/4000] Training [7/16] Loss: 0.00688 +Epoch [1424/4000] Training [8/16] Loss: 0.01053 +Epoch [1424/4000] Training [9/16] Loss: 0.01091 +Epoch [1424/4000] Training [10/16] Loss: 0.00962 +Epoch [1424/4000] Training [11/16] Loss: 0.00879 +Epoch [1424/4000] Training [12/16] Loss: 0.01088 +Epoch [1424/4000] Training [13/16] Loss: 0.00812 +Epoch [1424/4000] Training [14/16] Loss: 0.00726 +Epoch [1424/4000] Training [15/16] Loss: 0.01112 +Epoch [1424/4000] Training [16/16] Loss: 0.00915 +Epoch [1424/4000] Training metric {'Train/mean dice_metric': 0.9937882423400879, 'Train/mean miou_metric': 0.9874287843704224, 'Train/mean f1': 0.9899908900260925, 'Train/mean precision': 0.9854538440704346, 'Train/mean recall': 0.9945698976516724, 'Train/mean hd95_metric': 1.1398332118988037} +Epoch [1424/4000] Validation [1/4] Loss: 0.23041 focal_loss 0.16335 dice_loss 0.06706 +Epoch [1424/4000] Validation [2/4] Loss: 0.47940 focal_loss 0.28364 dice_loss 0.19576 +Epoch [1424/4000] Validation [3/4] Loss: 0.12730 focal_loss 0.07365 dice_loss 0.05365 +Epoch [1424/4000] Validation [4/4] Loss: 0.19930 focal_loss 0.09484 dice_loss 0.10446 +Epoch [1424/4000] Validation metric {'Val/mean dice_metric': 0.9736741781234741, 'Val/mean miou_metric': 0.9554994702339172, 'Val/mean f1': 0.9745646715164185, 'Val/mean precision': 0.9706151485443115, 'Val/mean recall': 0.9785463809967041, 'Val/mean hd95_metric': 5.146855354309082} +Cheakpoint... +Epoch [1424/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736741781234741, 'Val/mean miou_metric': 0.9554994702339172, 'Val/mean f1': 0.9745646715164185, 'Val/mean precision': 0.9706151485443115, 'Val/mean recall': 0.9785463809967041, 'Val/mean hd95_metric': 5.146855354309082} +Epoch [1425/4000] Training [1/16] Loss: 0.01045 +Epoch [1425/4000] Training [2/16] Loss: 0.00915 +Epoch [1425/4000] Training [3/16] Loss: 0.01212 +Epoch [1425/4000] Training [4/16] Loss: 0.00851 +Epoch [1425/4000] Training [5/16] Loss: 0.01198 +Epoch [1425/4000] Training [6/16] Loss: 0.01283 +Epoch [1425/4000] Training [7/16] Loss: 0.01105 +Epoch [1425/4000] Training [8/16] Loss: 0.00806 +Epoch [1425/4000] Training [9/16] Loss: 0.00720 +Epoch [1425/4000] Training [10/16] Loss: 0.00749 +Epoch [1425/4000] Training [11/16] Loss: 0.00831 +Epoch [1425/4000] Training [12/16] Loss: 0.00956 +Epoch [1425/4000] Training [13/16] Loss: 0.00776 +Epoch [1425/4000] Training [14/16] Loss: 0.01177 +Epoch [1425/4000] Training [15/16] Loss: 0.00981 +Epoch [1425/4000] Training [16/16] Loss: 0.00912 +Epoch [1425/4000] Training metric {'Train/mean dice_metric': 0.9931766986846924, 'Train/mean miou_metric': 0.9862264394760132, 'Train/mean f1': 0.9893510937690735, 'Train/mean precision': 0.9847161769866943, 'Train/mean recall': 0.9940298795700073, 'Train/mean hd95_metric': 1.1926484107971191} +Epoch [1425/4000] Validation [1/4] Loss: 0.27765 focal_loss 0.20808 dice_loss 0.06957 +Epoch [1425/4000] Validation [2/4] Loss: 0.40281 focal_loss 0.24009 dice_loss 0.16273 +Epoch [1425/4000] Validation [3/4] Loss: 0.28075 focal_loss 0.18520 dice_loss 0.09555 +Epoch [1425/4000] Validation [4/4] Loss: 0.19769 focal_loss 0.10230 dice_loss 0.09540 +Epoch [1425/4000] Validation metric {'Val/mean dice_metric': 0.9709762334823608, 'Val/mean miou_metric': 0.9517401456832886, 'Val/mean f1': 0.9713927507400513, 'Val/mean precision': 0.9683693647384644, 'Val/mean recall': 0.9744349718093872, 'Val/mean hd95_metric': 5.916234016418457} +Cheakpoint... +Epoch [1425/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709762334823608, 'Val/mean miou_metric': 0.9517401456832886, 'Val/mean f1': 0.9713927507400513, 'Val/mean precision': 0.9683693647384644, 'Val/mean recall': 0.9744349718093872, 'Val/mean hd95_metric': 5.916234016418457} +Epoch [1426/4000] Training [1/16] Loss: 0.00810 +Epoch [1426/4000] Training [2/16] Loss: 0.01217 +Epoch [1426/4000] Training [3/16] Loss: 0.00778 +Epoch [1426/4000] Training [4/16] Loss: 0.00612 +Epoch [1426/4000] Training [5/16] Loss: 0.00934 +Epoch [1426/4000] Training [6/16] Loss: 0.00729 +Epoch [1426/4000] Training [7/16] Loss: 0.01034 +Epoch [1426/4000] Training [8/16] Loss: 0.00910 +Epoch [1426/4000] Training [9/16] Loss: 0.00796 +Epoch [1426/4000] Training [10/16] Loss: 0.00867 +Epoch [1426/4000] Training [11/16] Loss: 0.00745 +Epoch [1426/4000] Training [12/16] Loss: 0.00729 +Epoch [1426/4000] Training [13/16] Loss: 0.00774 +Epoch [1426/4000] Training [14/16] Loss: 0.00731 +Epoch [1426/4000] Training [15/16] Loss: 0.01077 +Epoch [1426/4000] Training [16/16] Loss: 0.01047 +Epoch [1426/4000] Training metric {'Train/mean dice_metric': 0.9939926266670227, 'Train/mean miou_metric': 0.9878218770027161, 'Train/mean f1': 0.9901925921440125, 'Train/mean precision': 0.98569655418396, 'Train/mean recall': 0.9947298765182495, 'Train/mean hd95_metric': 1.0441250801086426} +Epoch [1426/4000] Validation [1/4] Loss: 0.23961 focal_loss 0.17250 dice_loss 0.06711 +Epoch [1426/4000] Validation [2/4] Loss: 0.29961 focal_loss 0.17238 dice_loss 0.12723 +Epoch [1426/4000] Validation [3/4] Loss: 0.33312 focal_loss 0.22414 dice_loss 0.10898 +Epoch [1426/4000] Validation [4/4] Loss: 0.26510 focal_loss 0.15716 dice_loss 0.10794 +Epoch [1426/4000] Validation metric {'Val/mean dice_metric': 0.972741961479187, 'Val/mean miou_metric': 0.9542720913887024, 'Val/mean f1': 0.9722000956535339, 'Val/mean precision': 0.9672079086303711, 'Val/mean recall': 0.9772440791130066, 'Val/mean hd95_metric': 5.498666763305664} +Cheakpoint... +Epoch [1426/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972741961479187, 'Val/mean miou_metric': 0.9542720913887024, 'Val/mean f1': 0.9722000956535339, 'Val/mean precision': 0.9672079086303711, 'Val/mean recall': 0.9772440791130066, 'Val/mean hd95_metric': 5.498666763305664} +Epoch [1427/4000] Training [1/16] Loss: 0.00911 +Epoch [1427/4000] Training [2/16] Loss: 0.01011 +Epoch [1427/4000] Training [3/16] Loss: 0.01040 +Epoch [1427/4000] Training [4/16] Loss: 0.01144 +Epoch [1427/4000] Training [5/16] Loss: 0.00727 +Epoch [1427/4000] Training [6/16] Loss: 0.00789 +Epoch [1427/4000] Training [7/16] Loss: 0.01098 +Epoch [1427/4000] Training [8/16] Loss: 0.00725 +Epoch [1427/4000] Training [9/16] Loss: 0.01001 +Epoch [1427/4000] Training [10/16] Loss: 0.01107 +Epoch [1427/4000] Training [11/16] Loss: 0.01003 +Epoch [1427/4000] Training [12/16] Loss: 0.01051 +Epoch [1427/4000] Training [13/16] Loss: 0.00930 +Epoch [1427/4000] Training [14/16] Loss: 0.00903 +Epoch [1427/4000] Training [15/16] Loss: 0.00709 +Epoch [1427/4000] Training [16/16] Loss: 0.00830 +Epoch [1427/4000] Training metric {'Train/mean dice_metric': 0.9934700727462769, 'Train/mean miou_metric': 0.9868029356002808, 'Train/mean f1': 0.9898138642311096, 'Train/mean precision': 0.9852714538574219, 'Train/mean recall': 0.994398295879364, 'Train/mean hd95_metric': 1.0870622396469116} +Epoch [1427/4000] Validation [1/4] Loss: 0.20395 focal_loss 0.13825 dice_loss 0.06569 +Epoch [1427/4000] Validation [2/4] Loss: 0.28252 focal_loss 0.16306 dice_loss 0.11946 +Epoch [1427/4000] Validation [3/4] Loss: 0.30001 focal_loss 0.20944 dice_loss 0.09057 +Epoch [1427/4000] Validation [4/4] Loss: 0.20128 focal_loss 0.10992 dice_loss 0.09136 +Epoch [1427/4000] Validation metric {'Val/mean dice_metric': 0.9723519086837769, 'Val/mean miou_metric': 0.9537035226821899, 'Val/mean f1': 0.9724817276000977, 'Val/mean precision': 0.9668208360671997, 'Val/mean recall': 0.9782094359397888, 'Val/mean hd95_metric': 5.712862968444824} +Cheakpoint... +Epoch [1427/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723519086837769, 'Val/mean miou_metric': 0.9537035226821899, 'Val/mean f1': 0.9724817276000977, 'Val/mean precision': 0.9668208360671997, 'Val/mean recall': 0.9782094359397888, 'Val/mean hd95_metric': 5.712862968444824} +Epoch [1428/4000] Training [1/16] Loss: 0.00580 +Epoch [1428/4000] Training [2/16] Loss: 0.01361 +Epoch [1428/4000] Training [3/16] Loss: 0.00723 +Epoch [1428/4000] Training [4/16] Loss: 0.01063 +Epoch [1428/4000] Training [5/16] Loss: 0.00716 +Epoch [1428/4000] Training [6/16] Loss: 0.00846 +Epoch [1428/4000] Training [7/16] Loss: 0.00977 +Epoch [1428/4000] Training [8/16] Loss: 0.00858 +Epoch [1428/4000] Training [9/16] Loss: 0.00938 +Epoch [1428/4000] Training [10/16] Loss: 0.01004 +Epoch [1428/4000] Training [11/16] Loss: 0.00990 +Epoch [1428/4000] Training [12/16] Loss: 0.01029 +Epoch [1428/4000] Training [13/16] Loss: 0.00723 +Epoch [1428/4000] Training [14/16] Loss: 0.00839 +Epoch [1428/4000] Training [15/16] Loss: 0.01013 +Epoch [1428/4000] Training [16/16] Loss: 0.01005 +Epoch [1428/4000] Training metric {'Train/mean dice_metric': 0.9938141703605652, 'Train/mean miou_metric': 0.9874618053436279, 'Train/mean f1': 0.9899217486381531, 'Train/mean precision': 0.9851882457733154, 'Train/mean recall': 0.9947009086608887, 'Train/mean hd95_metric': 1.064814805984497} +Epoch [1428/4000] Validation [1/4] Loss: 0.22744 focal_loss 0.16393 dice_loss 0.06351 +Epoch [1428/4000] Validation [2/4] Loss: 0.26799 focal_loss 0.13971 dice_loss 0.12828 +Epoch [1428/4000] Validation [3/4] Loss: 0.36918 focal_loss 0.26768 dice_loss 0.10150 +Epoch [1428/4000] Validation [4/4] Loss: 0.25423 focal_loss 0.15047 dice_loss 0.10375 +Epoch [1428/4000] Validation metric {'Val/mean dice_metric': 0.972584068775177, 'Val/mean miou_metric': 0.9542196393013, 'Val/mean f1': 0.9727299809455872, 'Val/mean precision': 0.9673181772232056, 'Val/mean recall': 0.9782028198242188, 'Val/mean hd95_metric': 5.435713768005371} +Cheakpoint... +Epoch [1428/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972584068775177, 'Val/mean miou_metric': 0.9542196393013, 'Val/mean f1': 0.9727299809455872, 'Val/mean precision': 0.9673181772232056, 'Val/mean recall': 0.9782028198242188, 'Val/mean hd95_metric': 5.435713768005371} +Epoch [1429/4000] Training [1/16] Loss: 0.01026 +Epoch [1429/4000] Training [2/16] Loss: 0.00999 +Epoch [1429/4000] Training [3/16] Loss: 0.00896 +Epoch [1429/4000] Training [4/16] Loss: 0.01220 +Epoch [1429/4000] Training [5/16] Loss: 0.01092 +Epoch [1429/4000] Training [6/16] Loss: 0.00803 +Epoch [1429/4000] Training [7/16] Loss: 0.00874 +Epoch [1429/4000] Training [8/16] Loss: 0.00855 +Epoch [1429/4000] Training [9/16] Loss: 0.00952 +Epoch [1429/4000] Training [10/16] Loss: 0.00899 +Epoch [1429/4000] Training [11/16] Loss: 0.00812 +Epoch [1429/4000] Training [12/16] Loss: 0.00642 +Epoch [1429/4000] Training [13/16] Loss: 0.00976 +Epoch [1429/4000] Training [14/16] Loss: 0.00845 +Epoch [1429/4000] Training [15/16] Loss: 0.00943 +Epoch [1429/4000] Training [16/16] Loss: 0.00950 +Epoch [1429/4000] Training metric {'Train/mean dice_metric': 0.9934663772583008, 'Train/mean miou_metric': 0.9868248701095581, 'Train/mean f1': 0.989250898361206, 'Train/mean precision': 0.9841752648353577, 'Train/mean recall': 0.9943791627883911, 'Train/mean hd95_metric': 1.1272165775299072} +Epoch [1429/4000] Validation [1/4] Loss: 0.25255 focal_loss 0.17987 dice_loss 0.07269 +Epoch [1429/4000] Validation [2/4] Loss: 0.31049 focal_loss 0.16306 dice_loss 0.14743 +Epoch [1429/4000] Validation [3/4] Loss: 0.17663 focal_loss 0.10248 dice_loss 0.07416 +Epoch [1429/4000] Validation [4/4] Loss: 0.24345 focal_loss 0.13462 dice_loss 0.10883 +Epoch [1429/4000] Validation metric {'Val/mean dice_metric': 0.9720175862312317, 'Val/mean miou_metric': 0.953046441078186, 'Val/mean f1': 0.9709954261779785, 'Val/mean precision': 0.9646980166435242, 'Val/mean recall': 0.9773756265640259, 'Val/mean hd95_metric': 6.197564601898193} +Cheakpoint... +Epoch [1429/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720175862312317, 'Val/mean miou_metric': 0.953046441078186, 'Val/mean f1': 0.9709954261779785, 'Val/mean precision': 0.9646980166435242, 'Val/mean recall': 0.9773756265640259, 'Val/mean hd95_metric': 6.197564601898193} +Epoch [1430/4000] Training [1/16] Loss: 0.01026 +Epoch [1430/4000] Training [2/16] Loss: 0.01619 +Epoch [1430/4000] Training [3/16] Loss: 0.01313 +Epoch [1430/4000] Training [4/16] Loss: 0.00745 +Epoch [1430/4000] Training [5/16] Loss: 0.00569 +Epoch [1430/4000] Training [6/16] Loss: 0.01096 +Epoch [1430/4000] Training [7/16] Loss: 0.00956 +Epoch [1430/4000] Training [8/16] Loss: 0.00798 +Epoch [1430/4000] Training [9/16] Loss: 0.00753 +Epoch [1430/4000] Training [10/16] Loss: 0.00951 +Epoch [1430/4000] Training [11/16] Loss: 0.01021 +Epoch [1430/4000] Training [12/16] Loss: 0.01102 +Epoch [1430/4000] Training [13/16] Loss: 0.00849 +Epoch [1430/4000] Training [14/16] Loss: 0.00727 +Epoch [1430/4000] Training [15/16] Loss: 0.01082 +Epoch [1430/4000] Training [16/16] Loss: 0.00775 +Epoch [1430/4000] Training metric {'Train/mean dice_metric': 0.9935332536697388, 'Train/mean miou_metric': 0.9869195222854614, 'Train/mean f1': 0.9899642467498779, 'Train/mean precision': 0.9854035377502441, 'Train/mean recall': 0.9945673942565918, 'Train/mean hd95_metric': 1.0948970317840576} +Epoch [1430/4000] Validation [1/4] Loss: 0.23474 focal_loss 0.17410 dice_loss 0.06064 +Epoch [1430/4000] Validation [2/4] Loss: 0.31045 focal_loss 0.17510 dice_loss 0.13535 +Epoch [1430/4000] Validation [3/4] Loss: 0.32765 focal_loss 0.21715 dice_loss 0.11050 +Epoch [1430/4000] Validation [4/4] Loss: 0.24399 focal_loss 0.13448 dice_loss 0.10951 +Epoch [1430/4000] Validation metric {'Val/mean dice_metric': 0.9703105688095093, 'Val/mean miou_metric': 0.9516666531562805, 'Val/mean f1': 0.969768226146698, 'Val/mean precision': 0.9592697024345398, 'Val/mean recall': 0.9804990887641907, 'Val/mean hd95_metric': 6.628736972808838} +Cheakpoint... +Epoch [1430/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703105688095093, 'Val/mean miou_metric': 0.9516666531562805, 'Val/mean f1': 0.969768226146698, 'Val/mean precision': 0.9592697024345398, 'Val/mean recall': 0.9804990887641907, 'Val/mean hd95_metric': 6.628736972808838} +Epoch [1431/4000] Training [1/16] Loss: 0.00770 +Epoch [1431/4000] Training [2/16] Loss: 0.00742 +Epoch [1431/4000] Training [3/16] Loss: 0.01159 +Epoch [1431/4000] Training [4/16] Loss: 0.00913 +Epoch [1431/4000] Training [5/16] Loss: 0.00848 +Epoch [1431/4000] Training [6/16] Loss: 0.01223 +Epoch [1431/4000] Training [7/16] Loss: 0.00986 +Epoch [1431/4000] Training [8/16] Loss: 0.00727 +Epoch [1431/4000] Training [9/16] Loss: 0.00991 +Epoch [1431/4000] Training [10/16] Loss: 0.00641 +Epoch [1431/4000] Training [11/16] Loss: 0.00911 +Epoch [1431/4000] Training [12/16] Loss: 0.00785 +Epoch [1431/4000] Training [13/16] Loss: 0.00885 +Epoch [1431/4000] Training [14/16] Loss: 0.00860 +Epoch [1431/4000] Training [15/16] Loss: 0.00715 +Epoch [1431/4000] Training [16/16] Loss: 0.00898 +Epoch [1431/4000] Training metric {'Train/mean dice_metric': 0.9941527843475342, 'Train/mean miou_metric': 0.9881199598312378, 'Train/mean f1': 0.99010169506073, 'Train/mean precision': 0.9852880835533142, 'Train/mean recall': 0.9949626326560974, 'Train/mean hd95_metric': 1.0450063943862915} +Epoch [1431/4000] Validation [1/4] Loss: 0.20618 focal_loss 0.14599 dice_loss 0.06019 +Epoch [1431/4000] Validation [2/4] Loss: 0.31802 focal_loss 0.16442 dice_loss 0.15360 +Epoch [1431/4000] Validation [3/4] Loss: 0.13637 focal_loss 0.07860 dice_loss 0.05777 +Epoch [1431/4000] Validation [4/4] Loss: 0.22261 focal_loss 0.12062 dice_loss 0.10200 +Epoch [1431/4000] Validation metric {'Val/mean dice_metric': 0.9715749621391296, 'Val/mean miou_metric': 0.9534746408462524, 'Val/mean f1': 0.970517098903656, 'Val/mean precision': 0.9628286957740784, 'Val/mean recall': 0.9783293008804321, 'Val/mean hd95_metric': 5.938448905944824} +Cheakpoint... +Epoch [1431/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715749621391296, 'Val/mean miou_metric': 0.9534746408462524, 'Val/mean f1': 0.970517098903656, 'Val/mean precision': 0.9628286957740784, 'Val/mean recall': 0.9783293008804321, 'Val/mean hd95_metric': 5.938448905944824} +Epoch [1432/4000] Training [1/16] Loss: 0.00787 +Epoch [1432/4000] Training [2/16] Loss: 0.00708 +Epoch [1432/4000] Training [3/16] Loss: 0.00848 +Epoch [1432/4000] Training [4/16] Loss: 0.01043 +Epoch [1432/4000] Training [5/16] Loss: 0.00753 +Epoch [1432/4000] Training [6/16] Loss: 0.01143 +Epoch [1432/4000] Training [7/16] Loss: 0.00657 +Epoch [1432/4000] Training [8/16] Loss: 0.00918 +Epoch [1432/4000] Training [9/16] Loss: 0.00771 +Epoch [1432/4000] Training [10/16] Loss: 0.00833 +Epoch [1432/4000] Training [11/16] Loss: 0.01030 +Epoch [1432/4000] Training [12/16] Loss: 0.00681 +Epoch [1432/4000] Training [13/16] Loss: 0.00957 +Epoch [1432/4000] Training [14/16] Loss: 0.00753 +Epoch [1432/4000] Training [15/16] Loss: 0.00856 +Epoch [1432/4000] Training [16/16] Loss: 0.00853 +Epoch [1432/4000] Training metric {'Train/mean dice_metric': 0.9937970042228699, 'Train/mean miou_metric': 0.9874523878097534, 'Train/mean f1': 0.9901993870735168, 'Train/mean precision': 0.9859067797660828, 'Train/mean recall': 0.9945294857025146, 'Train/mean hd95_metric': 1.0569665431976318} +Epoch [1432/4000] Validation [1/4] Loss: 0.29954 focal_loss 0.21863 dice_loss 0.08091 +Epoch [1432/4000] Validation [2/4] Loss: 0.41528 focal_loss 0.22876 dice_loss 0.18652 +Epoch [1432/4000] Validation [3/4] Loss: 0.26165 focal_loss 0.17610 dice_loss 0.08555 +Epoch [1432/4000] Validation [4/4] Loss: 0.17640 focal_loss 0.09599 dice_loss 0.08041 +Epoch [1432/4000] Validation metric {'Val/mean dice_metric': 0.9720872044563293, 'Val/mean miou_metric': 0.9539247751235962, 'Val/mean f1': 0.972425639629364, 'Val/mean precision': 0.9688484072685242, 'Val/mean recall': 0.9760294556617737, 'Val/mean hd95_metric': 5.675069808959961} +Cheakpoint... +Epoch [1432/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720872044563293, 'Val/mean miou_metric': 0.9539247751235962, 'Val/mean f1': 0.972425639629364, 'Val/mean precision': 0.9688484072685242, 'Val/mean recall': 0.9760294556617737, 'Val/mean hd95_metric': 5.675069808959961} +Epoch [1433/4000] Training [1/16] Loss: 0.00906 +Epoch [1433/4000] Training [2/16] Loss: 0.00855 +Epoch [1433/4000] Training [3/16] Loss: 0.00849 +Epoch [1433/4000] Training [4/16] Loss: 0.00770 +Epoch [1433/4000] Training [5/16] Loss: 0.01072 +Epoch [1433/4000] Training [6/16] Loss: 0.00738 +Epoch [1433/4000] Training [7/16] Loss: 0.00693 +Epoch [1433/4000] Training [8/16] Loss: 0.00750 +Epoch [1433/4000] Training [9/16] Loss: 0.00967 +Epoch [1433/4000] Training [10/16] Loss: 0.01893 +Epoch [1433/4000] Training [11/16] Loss: 0.01205 +Epoch [1433/4000] Training [12/16] Loss: 0.01258 +Epoch [1433/4000] Training [13/16] Loss: 0.00750 +Epoch [1433/4000] Training [14/16] Loss: 0.01185 +Epoch [1433/4000] Training [15/16] Loss: 0.00989 +Epoch [1433/4000] Training [16/16] Loss: 0.00813 +Epoch [1433/4000] Training metric {'Train/mean dice_metric': 0.9936212301254272, 'Train/mean miou_metric': 0.9870463013648987, 'Train/mean f1': 0.9892494082450867, 'Train/mean precision': 0.9840595722198486, 'Train/mean recall': 0.9944942593574524, 'Train/mean hd95_metric': 1.166884183883667} +Epoch [1433/4000] Validation [1/4] Loss: 0.19559 focal_loss 0.13725 dice_loss 0.05835 +Epoch [1433/4000] Validation [2/4] Loss: 0.36350 focal_loss 0.19420 dice_loss 0.16930 +Epoch [1433/4000] Validation [3/4] Loss: 0.14802 focal_loss 0.08807 dice_loss 0.05995 +Epoch [1433/4000] Validation [4/4] Loss: 0.22866 focal_loss 0.13179 dice_loss 0.09687 +Epoch [1433/4000] Validation metric {'Val/mean dice_metric': 0.9700428247451782, 'Val/mean miou_metric': 0.9513300061225891, 'Val/mean f1': 0.9675831198692322, 'Val/mean precision': 0.9563099145889282, 'Val/mean recall': 0.9791251420974731, 'Val/mean hd95_metric': 6.718833923339844} +Cheakpoint... +Epoch [1433/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700428247451782, 'Val/mean miou_metric': 0.9513300061225891, 'Val/mean f1': 0.9675831198692322, 'Val/mean precision': 0.9563099145889282, 'Val/mean recall': 0.9791251420974731, 'Val/mean hd95_metric': 6.718833923339844} +Epoch [1434/4000] Training [1/16] Loss: 0.00780 +Epoch [1434/4000] Training [2/16] Loss: 0.00814 +Epoch [1434/4000] Training [3/16] Loss: 0.01179 +Epoch [1434/4000] Training [4/16] Loss: 0.00981 +Epoch [1434/4000] Training [5/16] Loss: 0.01346 +Epoch [1434/4000] Training [6/16] Loss: 0.01077 +Epoch [1434/4000] Training [7/16] Loss: 0.00708 +Epoch [1434/4000] Training [8/16] Loss: 0.00745 +Epoch [1434/4000] Training [9/16] Loss: 0.00993 +Epoch [1434/4000] Training [10/16] Loss: 0.00999 +Epoch [1434/4000] Training [11/16] Loss: 0.01099 +Epoch [1434/4000] Training [12/16] Loss: 0.00869 +Epoch [1434/4000] Training [13/16] Loss: 0.00845 +Epoch [1434/4000] Training [14/16] Loss: 0.00808 +Epoch [1434/4000] Training [15/16] Loss: 0.00752 +Epoch [1434/4000] Training [16/16] Loss: 0.00981 +Epoch [1434/4000] Training metric {'Train/mean dice_metric': 0.9937411546707153, 'Train/mean miou_metric': 0.9872704744338989, 'Train/mean f1': 0.9890851378440857, 'Train/mean precision': 0.9836655259132385, 'Train/mean recall': 0.9945647120475769, 'Train/mean hd95_metric': 1.045822024345398} +Epoch [1434/4000] Validation [1/4] Loss: 0.21213 focal_loss 0.15454 dice_loss 0.05759 +Epoch [1434/4000] Validation [2/4] Loss: 0.33727 focal_loss 0.20105 dice_loss 0.13622 +Epoch [1434/4000] Validation [3/4] Loss: 0.28479 focal_loss 0.19285 dice_loss 0.09194 +Epoch [1434/4000] Validation [4/4] Loss: 0.21187 focal_loss 0.11103 dice_loss 0.10084 +Epoch [1434/4000] Validation metric {'Val/mean dice_metric': 0.9722593426704407, 'Val/mean miou_metric': 0.954135537147522, 'Val/mean f1': 0.9700965881347656, 'Val/mean precision': 0.9598138928413391, 'Val/mean recall': 0.9806020855903625, 'Val/mean hd95_metric': 6.033900260925293} +Cheakpoint... +Epoch [1434/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722593426704407, 'Val/mean miou_metric': 0.954135537147522, 'Val/mean f1': 0.9700965881347656, 'Val/mean precision': 0.9598138928413391, 'Val/mean recall': 0.9806020855903625, 'Val/mean hd95_metric': 6.033900260925293} +Epoch [1435/4000] Training [1/16] Loss: 0.00813 +Epoch [1435/4000] Training [2/16] Loss: 0.00791 +Epoch [1435/4000] Training [3/16] Loss: 0.00912 +Epoch [1435/4000] Training [4/16] Loss: 0.00775 +Epoch [1435/4000] Training [5/16] Loss: 0.01509 +Epoch [1435/4000] Training [6/16] Loss: 0.01192 +Epoch [1435/4000] Training [7/16] Loss: 0.00995 +Epoch [1435/4000] Training [8/16] Loss: 0.00726 +Epoch [1435/4000] Training [9/16] Loss: 0.00799 +Epoch [1435/4000] Training [10/16] Loss: 0.01075 +Epoch [1435/4000] Training [11/16] Loss: 0.01253 +Epoch [1435/4000] Training [12/16] Loss: 0.00971 +Epoch [1435/4000] Training [13/16] Loss: 0.00784 +Epoch [1435/4000] Training [14/16] Loss: 0.01103 +Epoch [1435/4000] Training [15/16] Loss: 0.00690 +Epoch [1435/4000] Training [16/16] Loss: 0.00851 +Epoch [1435/4000] Training metric {'Train/mean dice_metric': 0.9938082695007324, 'Train/mean miou_metric': 0.9874443411827087, 'Train/mean f1': 0.9899497032165527, 'Train/mean precision': 0.9851422905921936, 'Train/mean recall': 0.9948042035102844, 'Train/mean hd95_metric': 1.0595262050628662} +Epoch [1435/4000] Validation [1/4] Loss: 0.17722 focal_loss 0.11956 dice_loss 0.05766 +Epoch [1435/4000] Validation [2/4] Loss: 0.33526 focal_loss 0.19714 dice_loss 0.13812 +Epoch [1435/4000] Validation [3/4] Loss: 0.29410 focal_loss 0.18878 dice_loss 0.10533 +Epoch [1435/4000] Validation [4/4] Loss: 0.22325 focal_loss 0.12990 dice_loss 0.09335 +Epoch [1435/4000] Validation metric {'Val/mean dice_metric': 0.9734371900558472, 'Val/mean miou_metric': 0.9554312825202942, 'Val/mean f1': 0.9711944460868835, 'Val/mean precision': 0.9611281752586365, 'Val/mean recall': 0.9814738035202026, 'Val/mean hd95_metric': 6.0775885581970215} +Cheakpoint... +Epoch [1435/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734371900558472, 'Val/mean miou_metric': 0.9554312825202942, 'Val/mean f1': 0.9711944460868835, 'Val/mean precision': 0.9611281752586365, 'Val/mean recall': 0.9814738035202026, 'Val/mean hd95_metric': 6.0775885581970215} +Epoch [1436/4000] Training [1/16] Loss: 0.00940 +Epoch [1436/4000] Training [2/16] Loss: 0.00739 +Epoch [1436/4000] Training [3/16] Loss: 0.00784 +Epoch [1436/4000] Training [4/16] Loss: 0.00890 +Epoch [1436/4000] Training [5/16] Loss: 0.00855 +Epoch [1436/4000] Training [6/16] Loss: 0.01004 +Epoch [1436/4000] Training [7/16] Loss: 0.00804 +Epoch [1436/4000] Training [8/16] Loss: 0.00909 +Epoch [1436/4000] Training [9/16] Loss: 0.00763 +Epoch [1436/4000] Training [10/16] Loss: 0.00729 +Epoch [1436/4000] Training [11/16] Loss: 0.00774 +Epoch [1436/4000] Training [12/16] Loss: 0.00746 +Epoch [1436/4000] Training [13/16] Loss: 0.01157 +Epoch [1436/4000] Training [14/16] Loss: 0.00892 +Epoch [1436/4000] Training [15/16] Loss: 0.00750 +Epoch [1436/4000] Training [16/16] Loss: 0.00814 +Epoch [1436/4000] Training metric {'Train/mean dice_metric': 0.9939777255058289, 'Train/mean miou_metric': 0.9877820611000061, 'Train/mean f1': 0.9900224804878235, 'Train/mean precision': 0.9853419065475464, 'Train/mean recall': 0.9947477579116821, 'Train/mean hd95_metric': 1.0414960384368896} +Epoch [1436/4000] Validation [1/4] Loss: 0.18955 focal_loss 0.13505 dice_loss 0.05450 +Epoch [1436/4000] Validation [2/4] Loss: 0.50766 focal_loss 0.32027 dice_loss 0.18739 +Epoch [1436/4000] Validation [3/4] Loss: 0.28496 focal_loss 0.19624 dice_loss 0.08873 +Epoch [1436/4000] Validation [4/4] Loss: 0.29167 focal_loss 0.16600 dice_loss 0.12567 +Epoch [1436/4000] Validation metric {'Val/mean dice_metric': 0.9711118936538696, 'Val/mean miou_metric': 0.9525541067123413, 'Val/mean f1': 0.9703038930892944, 'Val/mean precision': 0.9636141061782837, 'Val/mean recall': 0.9770873188972473, 'Val/mean hd95_metric': 6.242238521575928} +Cheakpoint... +Epoch [1436/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711118936538696, 'Val/mean miou_metric': 0.9525541067123413, 'Val/mean f1': 0.9703038930892944, 'Val/mean precision': 0.9636141061782837, 'Val/mean recall': 0.9770873188972473, 'Val/mean hd95_metric': 6.242238521575928} +Epoch [1437/4000] Training [1/16] Loss: 0.00820 +Epoch [1437/4000] Training [2/16] Loss: 0.00778 +Epoch [1437/4000] Training [3/16] Loss: 0.00825 +Epoch [1437/4000] Training [4/16] Loss: 0.01173 +Epoch [1437/4000] Training [5/16] Loss: 0.01101 +Epoch [1437/4000] Training [6/16] Loss: 0.01209 +Epoch [1437/4000] Training [7/16] Loss: 0.01026 +Epoch [1437/4000] Training [8/16] Loss: 0.00762 +Epoch [1437/4000] Training [9/16] Loss: 0.00689 +Epoch [1437/4000] Training [10/16] Loss: 0.01163 +Epoch [1437/4000] Training [11/16] Loss: 0.00795 +Epoch [1437/4000] Training [12/16] Loss: 0.00855 +Epoch [1437/4000] Training [13/16] Loss: 0.01099 +Epoch [1437/4000] Training [14/16] Loss: 0.00808 +Epoch [1437/4000] Training [15/16] Loss: 0.01060 +Epoch [1437/4000] Training [16/16] Loss: 0.00742 +Epoch [1437/4000] Training metric {'Train/mean dice_metric': 0.9937459230422974, 'Train/mean miou_metric': 0.9873337149620056, 'Train/mean f1': 0.9900689125061035, 'Train/mean precision': 0.9853898286819458, 'Train/mean recall': 0.9947926998138428, 'Train/mean hd95_metric': 1.0609192848205566} +Epoch [1437/4000] Validation [1/4] Loss: 0.23840 focal_loss 0.17030 dice_loss 0.06810 +Epoch [1437/4000] Validation [2/4] Loss: 0.35641 focal_loss 0.20231 dice_loss 0.15410 +Epoch [1437/4000] Validation [3/4] Loss: 0.24093 focal_loss 0.15002 dice_loss 0.09091 +Epoch [1437/4000] Validation [4/4] Loss: 0.21448 focal_loss 0.11205 dice_loss 0.10243 +Epoch [1437/4000] Validation metric {'Val/mean dice_metric': 0.9710090756416321, 'Val/mean miou_metric': 0.952387809753418, 'Val/mean f1': 0.9724043011665344, 'Val/mean precision': 0.9695620536804199, 'Val/mean recall': 0.9752634167671204, 'Val/mean hd95_metric': 5.445496559143066} +Cheakpoint... +Epoch [1437/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710090756416321, 'Val/mean miou_metric': 0.952387809753418, 'Val/mean f1': 0.9724043011665344, 'Val/mean precision': 0.9695620536804199, 'Val/mean recall': 0.9752634167671204, 'Val/mean hd95_metric': 5.445496559143066} +Epoch [1438/4000] Training [1/16] Loss: 0.00887 +Epoch [1438/4000] Training [2/16] Loss: 0.01351 +Epoch [1438/4000] Training [3/16] Loss: 0.00838 +Epoch [1438/4000] Training [4/16] Loss: 0.01202 +Epoch [1438/4000] Training [5/16] Loss: 0.00817 +Epoch [1438/4000] Training [6/16] Loss: 0.00681 +Epoch [1438/4000] Training [7/16] Loss: 0.00693 +Epoch [1438/4000] Training [8/16] Loss: 0.00884 +Epoch [1438/4000] Training [9/16] Loss: 0.00747 +Epoch [1438/4000] Training [10/16] Loss: 0.00882 +Epoch [1438/4000] Training [11/16] Loss: 0.00800 +Epoch [1438/4000] Training [12/16] Loss: 0.00764 +Epoch [1438/4000] Training [13/16] Loss: 0.00984 +Epoch [1438/4000] Training [14/16] Loss: 0.01324 +Epoch [1438/4000] Training [15/16] Loss: 0.00774 +Epoch [1438/4000] Training [16/16] Loss: 0.00762 +Epoch [1438/4000] Training metric {'Train/mean dice_metric': 0.9938529133796692, 'Train/mean miou_metric': 0.9875262975692749, 'Train/mean f1': 0.9900806546211243, 'Train/mean precision': 0.985664427280426, 'Train/mean recall': 0.9945365786552429, 'Train/mean hd95_metric': 1.0639302730560303} +Epoch [1438/4000] Validation [1/4] Loss: 0.20222 focal_loss 0.14439 dice_loss 0.05783 +Epoch [1438/4000] Validation [2/4] Loss: 0.48630 focal_loss 0.28857 dice_loss 0.19773 +Epoch [1438/4000] Validation [3/4] Loss: 0.18607 focal_loss 0.10606 dice_loss 0.08001 +Epoch [1438/4000] Validation [4/4] Loss: 0.21371 focal_loss 0.12049 dice_loss 0.09322 +Epoch [1438/4000] Validation metric {'Val/mean dice_metric': 0.9699241518974304, 'Val/mean miou_metric': 0.9518686532974243, 'Val/mean f1': 0.9701252579689026, 'Val/mean precision': 0.9629971981048584, 'Val/mean recall': 0.9773598313331604, 'Val/mean hd95_metric': 6.212263584136963} +Cheakpoint... +Epoch [1438/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699241518974304, 'Val/mean miou_metric': 0.9518686532974243, 'Val/mean f1': 0.9701252579689026, 'Val/mean precision': 0.9629971981048584, 'Val/mean recall': 0.9773598313331604, 'Val/mean hd95_metric': 6.212263584136963} +Epoch [1439/4000] Training [1/16] Loss: 0.00863 +Epoch [1439/4000] Training [2/16] Loss: 0.00948 +Epoch [1439/4000] Training [3/16] Loss: 0.00816 +Epoch [1439/4000] Training [4/16] Loss: 0.01218 +Epoch [1439/4000] Training [5/16] Loss: 0.00874 +Epoch [1439/4000] Training [6/16] Loss: 0.00681 +Epoch [1439/4000] Training [7/16] Loss: 0.00750 +Epoch [1439/4000] Training [8/16] Loss: 0.00986 +Epoch [1439/4000] Training [9/16] Loss: 0.01081 +Epoch [1439/4000] Training [10/16] Loss: 0.00987 +Epoch [1439/4000] Training [11/16] Loss: 0.00943 +Epoch [1439/4000] Training [12/16] Loss: 0.01009 +Epoch [1439/4000] Training [13/16] Loss: 0.00749 +Epoch [1439/4000] Training [14/16] Loss: 0.00973 +Epoch [1439/4000] Training [15/16] Loss: 0.00688 +Epoch [1439/4000] Training [16/16] Loss: 0.00736 +Epoch [1439/4000] Training metric {'Train/mean dice_metric': 0.9936853647232056, 'Train/mean miou_metric': 0.9871485233306885, 'Train/mean f1': 0.9887403249740601, 'Train/mean precision': 0.9830096364021301, 'Train/mean recall': 0.9945381879806519, 'Train/mean hd95_metric': 1.1098958253860474} +Epoch [1439/4000] Validation [1/4] Loss: 0.20296 focal_loss 0.14618 dice_loss 0.05677 +Epoch [1439/4000] Validation [2/4] Loss: 0.34212 focal_loss 0.17567 dice_loss 0.16645 +Epoch [1439/4000] Validation [3/4] Loss: 0.17633 focal_loss 0.10417 dice_loss 0.07216 +Epoch [1439/4000] Validation [4/4] Loss: 0.17955 focal_loss 0.09246 dice_loss 0.08709 +Epoch [1439/4000] Validation metric {'Val/mean dice_metric': 0.9698358774185181, 'Val/mean miou_metric': 0.9514891505241394, 'Val/mean f1': 0.9692559838294983, 'Val/mean precision': 0.9621621966362, 'Val/mean recall': 0.9764553904533386, 'Val/mean hd95_metric': 6.366839408874512} +Cheakpoint... +Epoch [1439/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698358774185181, 'Val/mean miou_metric': 0.9514891505241394, 'Val/mean f1': 0.9692559838294983, 'Val/mean precision': 0.9621621966362, 'Val/mean recall': 0.9764553904533386, 'Val/mean hd95_metric': 6.366839408874512} +Epoch [1440/4000] Training [1/16] Loss: 0.00992 +Epoch [1440/4000] Training [2/16] Loss: 0.00638 +Epoch [1440/4000] Training [3/16] Loss: 0.00876 +Epoch [1440/4000] Training [4/16] Loss: 0.00893 +Epoch [1440/4000] Training [5/16] Loss: 0.00804 +Epoch [1440/4000] Training [6/16] Loss: 0.00813 +Epoch [1440/4000] Training [7/16] Loss: 0.00911 +Epoch [1440/4000] Training [8/16] Loss: 0.00920 +Epoch [1440/4000] Training [9/16] Loss: 0.01014 +Epoch [1440/4000] Training [10/16] Loss: 0.01087 +Epoch [1440/4000] Training [11/16] Loss: 0.00719 +Epoch [1440/4000] Training [12/16] Loss: 0.00837 +Epoch [1440/4000] Training [13/16] Loss: 0.00892 +Epoch [1440/4000] Training [14/16] Loss: 0.01158 +Epoch [1440/4000] Training [15/16] Loss: 0.01037 +Epoch [1440/4000] Training [16/16] Loss: 0.00793 +Epoch [1440/4000] Training metric {'Train/mean dice_metric': 0.9936063289642334, 'Train/mean miou_metric': 0.9870672225952148, 'Train/mean f1': 0.9899681806564331, 'Train/mean precision': 0.9855918288230896, 'Train/mean recall': 0.9943836331367493, 'Train/mean hd95_metric': 1.1229679584503174} +Epoch [1440/4000] Validation [1/4] Loss: 0.19578 focal_loss 0.14040 dice_loss 0.05538 +Epoch [1440/4000] Validation [2/4] Loss: 0.40490 focal_loss 0.23644 dice_loss 0.16847 +Epoch [1440/4000] Validation [3/4] Loss: 0.15216 focal_loss 0.09274 dice_loss 0.05942 +Epoch [1440/4000] Validation [4/4] Loss: 0.22459 focal_loss 0.12149 dice_loss 0.10310 +Epoch [1440/4000] Validation metric {'Val/mean dice_metric': 0.9717521667480469, 'Val/mean miou_metric': 0.953833281993866, 'Val/mean f1': 0.967299222946167, 'Val/mean precision': 0.954745352268219, 'Val/mean recall': 0.9801876544952393, 'Val/mean hd95_metric': 6.073958396911621} +Cheakpoint... +Epoch [1440/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717521667480469, 'Val/mean miou_metric': 0.953833281993866, 'Val/mean f1': 0.967299222946167, 'Val/mean precision': 0.954745352268219, 'Val/mean recall': 0.9801876544952393, 'Val/mean hd95_metric': 6.073958396911621} +Epoch [1441/4000] Training [1/16] Loss: 0.01179 +Epoch [1441/4000] Training [2/16] Loss: 0.00796 +Epoch [1441/4000] Training [3/16] Loss: 0.00979 +Epoch [1441/4000] Training [4/16] Loss: 0.00771 +Epoch [1441/4000] Training [5/16] Loss: 0.00936 +Epoch [1441/4000] Training [6/16] Loss: 0.00846 +Epoch [1441/4000] Training [7/16] Loss: 0.00876 +Epoch [1441/4000] Training [8/16] Loss: 0.00723 +Epoch [1441/4000] Training [9/16] Loss: 0.01088 +Epoch [1441/4000] Training [10/16] Loss: 0.00808 +Epoch [1441/4000] Training [11/16] Loss: 0.00697 +Epoch [1441/4000] Training [12/16] Loss: 0.00667 +Epoch [1441/4000] Training [13/16] Loss: 0.00645 +Epoch [1441/4000] Training [14/16] Loss: 0.00762 +Epoch [1441/4000] Training [15/16] Loss: 0.00940 +Epoch [1441/4000] Training [16/16] Loss: 0.00814 +Epoch [1441/4000] Training metric {'Train/mean dice_metric': 0.9939980506896973, 'Train/mean miou_metric': 0.9878436326980591, 'Train/mean f1': 0.9901885390281677, 'Train/mean precision': 0.9856671094894409, 'Train/mean recall': 0.9947515726089478, 'Train/mean hd95_metric': 1.08676016330719} +Epoch [1441/4000] Validation [1/4] Loss: 0.21651 focal_loss 0.15868 dice_loss 0.05783 +Epoch [1441/4000] Validation [2/4] Loss: 0.45893 focal_loss 0.28316 dice_loss 0.17577 +Epoch [1441/4000] Validation [3/4] Loss: 0.14849 focal_loss 0.09251 dice_loss 0.05599 +Epoch [1441/4000] Validation [4/4] Loss: 0.29153 focal_loss 0.16569 dice_loss 0.12584 +Epoch [1441/4000] Validation metric {'Val/mean dice_metric': 0.9704104661941528, 'Val/mean miou_metric': 0.9526964426040649, 'Val/mean f1': 0.9680582880973816, 'Val/mean precision': 0.9566108584403992, 'Val/mean recall': 0.9797831177711487, 'Val/mean hd95_metric': 6.156080722808838} +Cheakpoint... +Epoch [1441/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704104661941528, 'Val/mean miou_metric': 0.9526964426040649, 'Val/mean f1': 0.9680582880973816, 'Val/mean precision': 0.9566108584403992, 'Val/mean recall': 0.9797831177711487, 'Val/mean hd95_metric': 6.156080722808838} +Epoch [1442/4000] Training [1/16] Loss: 0.01169 +Epoch [1442/4000] Training [2/16] Loss: 0.00628 +Epoch [1442/4000] Training [3/16] Loss: 0.00884 +Epoch [1442/4000] Training [4/16] Loss: 0.00774 +Epoch [1442/4000] Training [5/16] Loss: 0.01393 +Epoch [1442/4000] Training [6/16] Loss: 0.00773 +Epoch [1442/4000] Training [7/16] Loss: 0.00943 +Epoch [1442/4000] Training [8/16] Loss: 0.00635 +Epoch [1442/4000] Training [9/16] Loss: 0.00908 +Epoch [1442/4000] Training [10/16] Loss: 0.00977 +Epoch [1442/4000] Training [11/16] Loss: 0.00867 +Epoch [1442/4000] Training [12/16] Loss: 0.00994 +Epoch [1442/4000] Training [13/16] Loss: 0.00644 +Epoch [1442/4000] Training [14/16] Loss: 0.01035 +Epoch [1442/4000] Training [15/16] Loss: 0.00723 +Epoch [1442/4000] Training [16/16] Loss: 0.00752 +Epoch [1442/4000] Training metric {'Train/mean dice_metric': 0.9937732219696045, 'Train/mean miou_metric': 0.9874027371406555, 'Train/mean f1': 0.9901731014251709, 'Train/mean precision': 0.9855625629425049, 'Train/mean recall': 0.9948270320892334, 'Train/mean hd95_metric': 1.105318546295166} +Epoch [1442/4000] Validation [1/4] Loss: 0.18261 focal_loss 0.12051 dice_loss 0.06210 +Epoch [1442/4000] Validation [2/4] Loss: 0.36163 focal_loss 0.22023 dice_loss 0.14140 +Epoch [1442/4000] Validation [3/4] Loss: 0.21765 focal_loss 0.12975 dice_loss 0.08789 +Epoch [1442/4000] Validation [4/4] Loss: 0.24587 focal_loss 0.13360 dice_loss 0.11227 +Epoch [1442/4000] Validation metric {'Val/mean dice_metric': 0.9705236554145813, 'Val/mean miou_metric': 0.9524275660514832, 'Val/mean f1': 0.970111608505249, 'Val/mean precision': 0.9622294902801514, 'Val/mean recall': 0.9781240224838257, 'Val/mean hd95_metric': 5.903144836425781} +Cheakpoint... +Epoch [1442/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705236554145813, 'Val/mean miou_metric': 0.9524275660514832, 'Val/mean f1': 0.970111608505249, 'Val/mean precision': 0.9622294902801514, 'Val/mean recall': 0.9781240224838257, 'Val/mean hd95_metric': 5.903144836425781} +Epoch [1443/4000] Training [1/16] Loss: 0.01251 +Epoch [1443/4000] Training [2/16] Loss: 0.00977 +Epoch [1443/4000] Training [3/16] Loss: 0.00996 +Epoch [1443/4000] Training [4/16] Loss: 0.00702 +Epoch [1443/4000] Training [5/16] Loss: 0.00903 +Epoch [1443/4000] Training [6/16] Loss: 0.00810 +Epoch [1443/4000] Training [7/16] Loss: 0.01176 +Epoch [1443/4000] Training [8/16] Loss: 0.00872 +Epoch [1443/4000] Training [9/16] Loss: 0.01358 +Epoch [1443/4000] Training [10/16] Loss: 0.00896 +Epoch [1443/4000] Training [11/16] Loss: 0.00984 +Epoch [1443/4000] Training [12/16] Loss: 0.00681 +Epoch [1443/4000] Training [13/16] Loss: 0.00973 +Epoch [1443/4000] Training [14/16] Loss: 0.00872 +Epoch [1443/4000] Training [15/16] Loss: 0.00817 +Epoch [1443/4000] Training [16/16] Loss: 0.00701 +Epoch [1443/4000] Training metric {'Train/mean dice_metric': 0.9937210083007812, 'Train/mean miou_metric': 0.9872776865959167, 'Train/mean f1': 0.9899163246154785, 'Train/mean precision': 0.9853504300117493, 'Train/mean recall': 0.9945247769355774, 'Train/mean hd95_metric': 1.1138949394226074} +Epoch [1443/4000] Validation [1/4] Loss: 0.17898 focal_loss 0.12163 dice_loss 0.05735 +Epoch [1443/4000] Validation [2/4] Loss: 0.41127 focal_loss 0.23812 dice_loss 0.17315 +Epoch [1443/4000] Validation [3/4] Loss: 0.14579 focal_loss 0.08629 dice_loss 0.05950 +Epoch [1443/4000] Validation [4/4] Loss: 0.24285 focal_loss 0.14541 dice_loss 0.09743 +Epoch [1443/4000] Validation metric {'Val/mean dice_metric': 0.971718430519104, 'Val/mean miou_metric': 0.9533886909484863, 'Val/mean f1': 0.9705075025558472, 'Val/mean precision': 0.9621602296829224, 'Val/mean recall': 0.979000985622406, 'Val/mean hd95_metric': 5.675034046173096} +Cheakpoint... +Epoch [1443/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971718430519104, 'Val/mean miou_metric': 0.9533886909484863, 'Val/mean f1': 0.9705075025558472, 'Val/mean precision': 0.9621602296829224, 'Val/mean recall': 0.979000985622406, 'Val/mean hd95_metric': 5.675034046173096} +Epoch [1444/4000] Training [1/16] Loss: 0.00838 +Epoch [1444/4000] Training [2/16] Loss: 0.01221 +Epoch [1444/4000] Training [3/16] Loss: 0.01029 +Epoch [1444/4000] Training [4/16] Loss: 0.00819 +Epoch [1444/4000] Training [5/16] Loss: 0.00947 +Epoch [1444/4000] Training [6/16] Loss: 0.01098 +Epoch [1444/4000] Training [7/16] Loss: 0.01215 +Epoch [1444/4000] Training [8/16] Loss: 0.00876 +Epoch [1444/4000] Training [9/16] Loss: 0.00888 +Epoch [1444/4000] Training [10/16] Loss: 0.00793 +Epoch [1444/4000] Training [11/16] Loss: 0.00721 +Epoch [1444/4000] Training [12/16] Loss: 0.01272 +Epoch [1444/4000] Training [13/16] Loss: 0.00728 +Epoch [1444/4000] Training [14/16] Loss: 0.01030 +Epoch [1444/4000] Training [15/16] Loss: 0.01424 +Epoch [1444/4000] Training [16/16] Loss: 0.00714 +Epoch [1444/4000] Training metric {'Train/mean dice_metric': 0.9936090707778931, 'Train/mean miou_metric': 0.9870741367340088, 'Train/mean f1': 0.9898884296417236, 'Train/mean precision': 0.9853299856185913, 'Train/mean recall': 0.9944891929626465, 'Train/mean hd95_metric': 1.093691349029541} +Epoch [1444/4000] Validation [1/4] Loss: 0.19991 focal_loss 0.14250 dice_loss 0.05741 +Epoch [1444/4000] Validation [2/4] Loss: 0.31728 focal_loss 0.17408 dice_loss 0.14320 +Epoch [1444/4000] Validation [3/4] Loss: 0.17986 focal_loss 0.10438 dice_loss 0.07548 +Epoch [1444/4000] Validation [4/4] Loss: 0.37139 focal_loss 0.23584 dice_loss 0.13555 +Epoch [1444/4000] Validation metric {'Val/mean dice_metric': 0.9714276194572449, 'Val/mean miou_metric': 0.9528552293777466, 'Val/mean f1': 0.9730733036994934, 'Val/mean precision': 0.967189610004425, 'Val/mean recall': 0.9790289402008057, 'Val/mean hd95_metric': 5.863955497741699} +Cheakpoint... +Epoch [1444/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714276194572449, 'Val/mean miou_metric': 0.9528552293777466, 'Val/mean f1': 0.9730733036994934, 'Val/mean precision': 0.967189610004425, 'Val/mean recall': 0.9790289402008057, 'Val/mean hd95_metric': 5.863955497741699} +Epoch [1445/4000] Training [1/16] Loss: 0.01804 +Epoch [1445/4000] Training [2/16] Loss: 0.00801 +Epoch [1445/4000] Training [3/16] Loss: 0.00954 +Epoch [1445/4000] Training [4/16] Loss: 0.01029 +Epoch [1445/4000] Training [5/16] Loss: 0.01050 +Epoch [1445/4000] Training [6/16] Loss: 0.00831 +Epoch [1445/4000] Training [7/16] Loss: 0.00969 +Epoch [1445/4000] Training [8/16] Loss: 0.00836 +Epoch [1445/4000] Training [9/16] Loss: 0.00957 +Epoch [1445/4000] Training [10/16] Loss: 0.01491 +Epoch [1445/4000] Training [11/16] Loss: 0.00959 +Epoch [1445/4000] Training [12/16] Loss: 0.01077 +Epoch [1445/4000] Training [13/16] Loss: 0.00940 +Epoch [1445/4000] Training [14/16] Loss: 0.02967 +Epoch [1445/4000] Training [15/16] Loss: 0.00811 +Epoch [1445/4000] Training [16/16] Loss: 0.00925 +Epoch [1445/4000] Training metric {'Train/mean dice_metric': 0.992836594581604, 'Train/mean miou_metric': 0.9856619834899902, 'Train/mean f1': 0.9895815253257751, 'Train/mean precision': 0.9852795600891113, 'Train/mean recall': 0.9939212203025818, 'Train/mean hd95_metric': 1.3634483814239502} +Epoch [1445/4000] Validation [1/4] Loss: 0.20055 focal_loss 0.13968 dice_loss 0.06087 +Epoch [1445/4000] Validation [2/4] Loss: 0.33541 focal_loss 0.20023 dice_loss 0.13519 +Epoch [1445/4000] Validation [3/4] Loss: 0.26897 focal_loss 0.18185 dice_loss 0.08712 +Epoch [1445/4000] Validation [4/4] Loss: 0.24807 focal_loss 0.13822 dice_loss 0.10986 +Epoch [1445/4000] Validation metric {'Val/mean dice_metric': 0.9703460931777954, 'Val/mean miou_metric': 0.9508922696113586, 'Val/mean f1': 0.9710614085197449, 'Val/mean precision': 0.9651013612747192, 'Val/mean recall': 0.9770955443382263, 'Val/mean hd95_metric': 6.5138373374938965} +Cheakpoint... +Epoch [1445/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703460931777954, 'Val/mean miou_metric': 0.9508922696113586, 'Val/mean f1': 0.9710614085197449, 'Val/mean precision': 0.9651013612747192, 'Val/mean recall': 0.9770955443382263, 'Val/mean hd95_metric': 6.5138373374938965} +Epoch [1446/4000] Training [1/16] Loss: 0.00995 +Epoch [1446/4000] Training [2/16] Loss: 0.00760 +Epoch [1446/4000] Training [3/16] Loss: 0.00783 +Epoch [1446/4000] Training [4/16] Loss: 0.01298 +Epoch [1446/4000] Training [5/16] Loss: 0.03240 +Epoch [1446/4000] Training [6/16] Loss: 0.00763 +Epoch [1446/4000] Training [7/16] Loss: 0.00775 +Epoch [1446/4000] Training [8/16] Loss: 0.01120 +Epoch [1446/4000] Training [9/16] Loss: 0.00903 +Epoch [1446/4000] Training [10/16] Loss: 0.01017 +Epoch [1446/4000] Training [11/16] Loss: 0.00737 +Epoch [1446/4000] Training [12/16] Loss: 0.01092 +Epoch [1446/4000] Training [13/16] Loss: 0.01058 +Epoch [1446/4000] Training [14/16] Loss: 0.00812 +Epoch [1446/4000] Training [15/16] Loss: 0.01051 +Epoch [1446/4000] Training [16/16] Loss: 0.01435 +Epoch [1446/4000] Training metric {'Train/mean dice_metric': 0.9929114580154419, 'Train/mean miou_metric': 0.9857327342033386, 'Train/mean f1': 0.9890082478523254, 'Train/mean precision': 0.9840282201766968, 'Train/mean recall': 0.9940389394760132, 'Train/mean hd95_metric': 2.4578709602355957} +Epoch [1446/4000] Validation [1/4] Loss: 0.25002 focal_loss 0.16186 dice_loss 0.08816 +Epoch [1446/4000] Validation [2/4] Loss: 0.41489 focal_loss 0.21228 dice_loss 0.20261 +Epoch [1446/4000] Validation [3/4] Loss: 0.13757 focal_loss 0.07930 dice_loss 0.05827 +Epoch [1446/4000] Validation [4/4] Loss: 0.36154 focal_loss 0.22380 dice_loss 0.13773 +Epoch [1446/4000] Validation metric {'Val/mean dice_metric': 0.9649556875228882, 'Val/mean miou_metric': 0.9461687207221985, 'Val/mean f1': 0.9691678881645203, 'Val/mean precision': 0.968137264251709, 'Val/mean recall': 0.9702008366584778, 'Val/mean hd95_metric': 6.652298450469971} +Cheakpoint... +Epoch [1446/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649556875228882, 'Val/mean miou_metric': 0.9461687207221985, 'Val/mean f1': 0.9691678881645203, 'Val/mean precision': 0.968137264251709, 'Val/mean recall': 0.9702008366584778, 'Val/mean hd95_metric': 6.652298450469971} +Epoch [1447/4000] Training [1/16] Loss: 0.01005 +Epoch [1447/4000] Training [2/16] Loss: 0.04482 +Epoch [1447/4000] Training [3/16] Loss: 0.01281 +Epoch [1447/4000] Training [4/16] Loss: 0.01158 +Epoch [1447/4000] Training [5/16] Loss: 0.01176 +Epoch [1447/4000] Training [6/16] Loss: 0.00945 +Epoch [1447/4000] Training [7/16] Loss: 0.00796 +Epoch [1447/4000] Training [8/16] Loss: 0.00890 +Epoch [1447/4000] Training [9/16] Loss: 0.00836 +Epoch [1447/4000] Training [10/16] Loss: 0.01497 +Epoch [1447/4000] Training [11/16] Loss: 0.01221 +Epoch [1447/4000] Training [12/16] Loss: 0.00859 +Epoch [1447/4000] Training [13/16] Loss: 0.01239 +Epoch [1447/4000] Training [14/16] Loss: 0.01095 +Epoch [1447/4000] Training [15/16] Loss: 0.01171 +Epoch [1447/4000] Training [16/16] Loss: 0.00811 +Epoch [1447/4000] Training metric {'Train/mean dice_metric': 0.9924973249435425, 'Train/mean miou_metric': 0.9850807189941406, 'Train/mean f1': 0.9891990423202515, 'Train/mean precision': 0.9847475290298462, 'Train/mean recall': 0.9936909079551697, 'Train/mean hd95_metric': 1.4753942489624023} +Epoch [1447/4000] Validation [1/4] Loss: 0.20779 focal_loss 0.14057 dice_loss 0.06722 +Epoch [1447/4000] Validation [2/4] Loss: 0.38581 focal_loss 0.21987 dice_loss 0.16594 +Epoch [1447/4000] Validation [3/4] Loss: 0.13276 focal_loss 0.07967 dice_loss 0.05309 +Epoch [1447/4000] Validation [4/4] Loss: 0.29415 focal_loss 0.17273 dice_loss 0.12142 +Epoch [1447/4000] Validation metric {'Val/mean dice_metric': 0.9670194387435913, 'Val/mean miou_metric': 0.9480071067810059, 'Val/mean f1': 0.9709967970848083, 'Val/mean precision': 0.9687528610229492, 'Val/mean recall': 0.973251223564148, 'Val/mean hd95_metric': 6.0120015144348145} +Cheakpoint... +Epoch [1447/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670194387435913, 'Val/mean miou_metric': 0.9480071067810059, 'Val/mean f1': 0.9709967970848083, 'Val/mean precision': 0.9687528610229492, 'Val/mean recall': 0.973251223564148, 'Val/mean hd95_metric': 6.0120015144348145} +Epoch [1448/4000] Training [1/16] Loss: 0.01070 +Epoch [1448/4000] Training [2/16] Loss: 0.00889 +Epoch [1448/4000] Training [3/16] Loss: 0.01053 +Epoch [1448/4000] Training [4/16] Loss: 0.01059 +Epoch [1448/4000] Training [5/16] Loss: 0.01223 +Epoch [1448/4000] Training [6/16] Loss: 0.01084 +Epoch [1448/4000] Training [7/16] Loss: 0.00861 +Epoch [1448/4000] Training [8/16] Loss: 0.00753 +Epoch [1448/4000] Training [9/16] Loss: 0.01270 +Epoch [1448/4000] Training [10/16] Loss: 0.00944 +Epoch [1448/4000] Training [11/16] Loss: 0.00922 +Epoch [1448/4000] Training [12/16] Loss: 0.00953 +Epoch [1448/4000] Training [13/16] Loss: 0.00773 +Epoch [1448/4000] Training [14/16] Loss: 0.00829 +Epoch [1448/4000] Training [15/16] Loss: 0.00861 +Epoch [1448/4000] Training [16/16] Loss: 0.00663 +Epoch [1448/4000] Training metric {'Train/mean dice_metric': 0.9936367273330688, 'Train/mean miou_metric': 0.9871236085891724, 'Train/mean f1': 0.9896603226661682, 'Train/mean precision': 0.9852375984191895, 'Train/mean recall': 0.9941229224205017, 'Train/mean hd95_metric': 1.2120484113693237} +Epoch [1448/4000] Validation [1/4] Loss: 0.23132 focal_loss 0.16158 dice_loss 0.06974 +Epoch [1448/4000] Validation [2/4] Loss: 0.36220 focal_loss 0.18243 dice_loss 0.17977 +Epoch [1448/4000] Validation [3/4] Loss: 0.15917 focal_loss 0.10439 dice_loss 0.05477 +Epoch [1448/4000] Validation [4/4] Loss: 0.35539 focal_loss 0.23240 dice_loss 0.12299 +Epoch [1448/4000] Validation metric {'Val/mean dice_metric': 0.9700263738632202, 'Val/mean miou_metric': 0.9514673352241516, 'Val/mean f1': 0.9718465805053711, 'Val/mean precision': 0.9693684577941895, 'Val/mean recall': 0.9743374586105347, 'Val/mean hd95_metric': 5.7401838302612305} +Cheakpoint... +Epoch [1448/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700263738632202, 'Val/mean miou_metric': 0.9514673352241516, 'Val/mean f1': 0.9718465805053711, 'Val/mean precision': 0.9693684577941895, 'Val/mean recall': 0.9743374586105347, 'Val/mean hd95_metric': 5.7401838302612305} +Epoch [1449/4000] Training [1/16] Loss: 0.00918 +Epoch [1449/4000] Training [2/16] Loss: 0.01196 +Epoch [1449/4000] Training [3/16] Loss: 0.00752 +Epoch [1449/4000] Training [4/16] Loss: 0.00816 +Epoch [1449/4000] Training [5/16] Loss: 0.01075 +Epoch [1449/4000] Training [6/16] Loss: 0.00938 +Epoch [1449/4000] Training [7/16] Loss: 0.01042 +Epoch [1449/4000] Training [8/16] Loss: 0.00934 +Epoch [1449/4000] Training [9/16] Loss: 0.01247 +Epoch [1449/4000] Training [10/16] Loss: 0.01343 +Epoch [1449/4000] Training [11/16] Loss: 0.00930 +Epoch [1449/4000] Training [12/16] Loss: 0.00760 +Epoch [1449/4000] Training [13/16] Loss: 0.01068 +Epoch [1449/4000] Training [14/16] Loss: 0.00741 +Epoch [1449/4000] Training [15/16] Loss: 0.00721 +Epoch [1449/4000] Training [16/16] Loss: 0.00669 +Epoch [1449/4000] Training metric {'Train/mean dice_metric': 0.9939426183700562, 'Train/mean miou_metric': 0.9877002239227295, 'Train/mean f1': 0.9899477958679199, 'Train/mean precision': 0.9852709770202637, 'Train/mean recall': 0.9946692585945129, 'Train/mean hd95_metric': 1.1549865007400513} +Epoch [1449/4000] Validation [1/4] Loss: 0.38649 focal_loss 0.28236 dice_loss 0.10414 +Epoch [1449/4000] Validation [2/4] Loss: 0.29089 focal_loss 0.15314 dice_loss 0.13775 +Epoch [1449/4000] Validation [3/4] Loss: 0.17333 focal_loss 0.11107 dice_loss 0.06227 +Epoch [1449/4000] Validation [4/4] Loss: 0.29178 focal_loss 0.17167 dice_loss 0.12011 +Epoch [1449/4000] Validation metric {'Val/mean dice_metric': 0.9722137451171875, 'Val/mean miou_metric': 0.9537404775619507, 'Val/mean f1': 0.9712284207344055, 'Val/mean precision': 0.9679495096206665, 'Val/mean recall': 0.9745296835899353, 'Val/mean hd95_metric': 5.6320061683654785} +Cheakpoint... +Epoch [1449/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722137451171875, 'Val/mean miou_metric': 0.9537404775619507, 'Val/mean f1': 0.9712284207344055, 'Val/mean precision': 0.9679495096206665, 'Val/mean recall': 0.9745296835899353, 'Val/mean hd95_metric': 5.6320061683654785} +Epoch [1450/4000] Training [1/16] Loss: 0.00774 +Epoch [1450/4000] Training [2/16] Loss: 0.01022 +Epoch [1450/4000] Training [3/16] Loss: 0.00789 +Epoch [1450/4000] Training [4/16] Loss: 0.01083 +Epoch [1450/4000] Training [5/16] Loss: 0.01019 +Epoch [1450/4000] Training [6/16] Loss: 0.00822 +Epoch [1450/4000] Training [7/16] Loss: 0.00986 +Epoch [1450/4000] Training [8/16] Loss: 0.00742 +Epoch [1450/4000] Training [9/16] Loss: 0.00622 +Epoch [1450/4000] Training [10/16] Loss: 0.00604 +Epoch [1450/4000] Training [11/16] Loss: 0.00762 +Epoch [1450/4000] Training [12/16] Loss: 0.00733 +Epoch [1450/4000] Training [13/16] Loss: 0.00737 +Epoch [1450/4000] Training [14/16] Loss: 0.00757 +Epoch [1450/4000] Training [15/16] Loss: 0.00554 +Epoch [1450/4000] Training [16/16] Loss: 0.00834 +Epoch [1450/4000] Training metric {'Train/mean dice_metric': 0.9943506717681885, 'Train/mean miou_metric': 0.9885293841362, 'Train/mean f1': 0.9902381896972656, 'Train/mean precision': 0.9855327606201172, 'Train/mean recall': 0.9949889779090881, 'Train/mean hd95_metric': 1.0713109970092773} +Epoch [1450/4000] Validation [1/4] Loss: 0.25397 focal_loss 0.16347 dice_loss 0.09050 +Epoch [1450/4000] Validation [2/4] Loss: 0.20979 focal_loss 0.10746 dice_loss 0.10233 +Epoch [1450/4000] Validation [3/4] Loss: 0.13474 focal_loss 0.08348 dice_loss 0.05126 +Epoch [1450/4000] Validation [4/4] Loss: 0.26513 focal_loss 0.14981 dice_loss 0.11533 +Epoch [1450/4000] Validation metric {'Val/mean dice_metric': 0.9716845750808716, 'Val/mean miou_metric': 0.9538939595222473, 'Val/mean f1': 0.9734101891517639, 'Val/mean precision': 0.9699914455413818, 'Val/mean recall': 0.9768531322479248, 'Val/mean hd95_metric': 5.492356777191162} +Cheakpoint... +Epoch [1450/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716845750808716, 'Val/mean miou_metric': 0.9538939595222473, 'Val/mean f1': 0.9734101891517639, 'Val/mean precision': 0.9699914455413818, 'Val/mean recall': 0.9768531322479248, 'Val/mean hd95_metric': 5.492356777191162} +Epoch [1451/4000] Training [1/16] Loss: 0.00793 +Epoch [1451/4000] Training [2/16] Loss: 0.00725 +Epoch [1451/4000] Training [3/16] Loss: 0.00819 +Epoch [1451/4000] Training [4/16] Loss: 0.00809 +Epoch [1451/4000] Training [5/16] Loss: 0.00833 +Epoch [1451/4000] Training [6/16] Loss: 0.00702 +Epoch [1451/4000] Training [7/16] Loss: 0.00785 +Epoch [1451/4000] Training [8/16] Loss: 0.00665 +Epoch [1451/4000] Training [9/16] Loss: 0.00842 +Epoch [1451/4000] Training [10/16] Loss: 0.00811 +Epoch [1451/4000] Training [11/16] Loss: 0.00860 +Epoch [1451/4000] Training [12/16] Loss: 0.00820 +Epoch [1451/4000] Training [13/16] Loss: 0.00648 +Epoch [1451/4000] Training [14/16] Loss: 0.01454 +Epoch [1451/4000] Training [15/16] Loss: 0.00831 +Epoch [1451/4000] Training [16/16] Loss: 0.00966 +Epoch [1451/4000] Training metric {'Train/mean dice_metric': 0.9927916526794434, 'Train/mean miou_metric': 0.9868533611297607, 'Train/mean f1': 0.9903056025505066, 'Train/mean precision': 0.9857832789421082, 'Train/mean recall': 0.994869589805603, 'Train/mean hd95_metric': 1.1644489765167236} +Epoch [1451/4000] Validation [1/4] Loss: 0.25021 focal_loss 0.17648 dice_loss 0.07373 +Epoch [1451/4000] Validation [2/4] Loss: 0.32709 focal_loss 0.18009 dice_loss 0.14701 +Epoch [1451/4000] Validation [3/4] Loss: 0.14391 focal_loss 0.09041 dice_loss 0.05350 +Epoch [1451/4000] Validation [4/4] Loss: 0.25094 focal_loss 0.14735 dice_loss 0.10359 +Epoch [1451/4000] Validation metric {'Val/mean dice_metric': 0.9690574407577515, 'Val/mean miou_metric': 0.9508999586105347, 'Val/mean f1': 0.9726353883743286, 'Val/mean precision': 0.9708444476127625, 'Val/mean recall': 0.9744331240653992, 'Val/mean hd95_metric': 5.492608547210693} +Cheakpoint... +Epoch [1451/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690574407577515, 'Val/mean miou_metric': 0.9508999586105347, 'Val/mean f1': 0.9726353883743286, 'Val/mean precision': 0.9708444476127625, 'Val/mean recall': 0.9744331240653992, 'Val/mean hd95_metric': 5.492608547210693} +Epoch [1452/4000] Training [1/16] Loss: 0.00809 +Epoch [1452/4000] Training [2/16] Loss: 0.00936 +Epoch [1452/4000] Training [3/16] Loss: 0.00961 +Epoch [1452/4000] Training [4/16] Loss: 0.00909 +Epoch [1452/4000] Training [5/16] Loss: 0.00849 +Epoch [1452/4000] Training [6/16] Loss: 0.00862 +Epoch [1452/4000] Training [7/16] Loss: 0.00812 +Epoch [1452/4000] Training [8/16] Loss: 0.00655 +Epoch [1452/4000] Training [9/16] Loss: 0.00980 +Epoch [1452/4000] Training [10/16] Loss: 0.01778 +Epoch [1452/4000] Training [11/16] Loss: 0.00831 +Epoch [1452/4000] Training [12/16] Loss: 0.00906 +Epoch [1452/4000] Training [13/16] Loss: 0.00731 +Epoch [1452/4000] Training [14/16] Loss: 0.01182 +Epoch [1452/4000] Training [15/16] Loss: 0.00934 +Epoch [1452/4000] Training [16/16] Loss: 0.00778 +Epoch [1452/4000] Training metric {'Train/mean dice_metric': 0.993315577507019, 'Train/mean miou_metric': 0.9867501258850098, 'Train/mean f1': 0.9896190166473389, 'Train/mean precision': 0.9851235151290894, 'Train/mean recall': 0.994155764579773, 'Train/mean hd95_metric': 1.4887683391571045} +Epoch [1452/4000] Validation [1/4] Loss: 0.20071 focal_loss 0.13920 dice_loss 0.06151 +Epoch [1452/4000] Validation [2/4] Loss: 0.24429 focal_loss 0.12690 dice_loss 0.11739 +Epoch [1452/4000] Validation [3/4] Loss: 0.17456 focal_loss 0.10412 dice_loss 0.07044 +Epoch [1452/4000] Validation [4/4] Loss: 0.18364 focal_loss 0.09978 dice_loss 0.08385 +Epoch [1452/4000] Validation metric {'Val/mean dice_metric': 0.9704080820083618, 'Val/mean miou_metric': 0.9518863558769226, 'Val/mean f1': 0.9715570211410522, 'Val/mean precision': 0.9656800627708435, 'Val/mean recall': 0.9775059223175049, 'Val/mean hd95_metric': 6.096519947052002} +Cheakpoint... +Epoch [1452/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704080820083618, 'Val/mean miou_metric': 0.9518863558769226, 'Val/mean f1': 0.9715570211410522, 'Val/mean precision': 0.9656800627708435, 'Val/mean recall': 0.9775059223175049, 'Val/mean hd95_metric': 6.096519947052002} +Epoch [1453/4000] Training [1/16] Loss: 0.00946 +Epoch [1453/4000] Training [2/16] Loss: 0.00698 +Epoch [1453/4000] Training [3/16] Loss: 0.00860 +Epoch [1453/4000] Training [4/16] Loss: 0.00840 +Epoch [1453/4000] Training [5/16] Loss: 0.01012 +Epoch [1453/4000] Training [6/16] Loss: 0.00668 +Epoch [1453/4000] Training [7/16] Loss: 0.00652 +Epoch [1453/4000] Training [8/16] Loss: 0.01156 +Epoch [1453/4000] Training [9/16] Loss: 0.00644 +Epoch [1453/4000] Training [10/16] Loss: 0.00814 +Epoch [1453/4000] Training [11/16] Loss: 0.00828 +Epoch [1453/4000] Training [12/16] Loss: 0.00990 +Epoch [1453/4000] Training [13/16] Loss: 0.00875 +Epoch [1453/4000] Training [14/16] Loss: 0.01078 +Epoch [1453/4000] Training [15/16] Loss: 0.00932 +Epoch [1453/4000] Training [16/16] Loss: 0.00873 +Epoch [1453/4000] Training metric {'Train/mean dice_metric': 0.9940509796142578, 'Train/mean miou_metric': 0.9879270792007446, 'Train/mean f1': 0.9899497032165527, 'Train/mean precision': 0.9853096604347229, 'Train/mean recall': 0.9946336150169373, 'Train/mean hd95_metric': 1.0793061256408691} +Epoch [1453/4000] Validation [1/4] Loss: 0.20166 focal_loss 0.14227 dice_loss 0.05939 +Epoch [1453/4000] Validation [2/4] Loss: 0.48432 focal_loss 0.25230 dice_loss 0.23202 +Epoch [1453/4000] Validation [3/4] Loss: 0.18751 focal_loss 0.11531 dice_loss 0.07219 +Epoch [1453/4000] Validation [4/4] Loss: 0.24931 focal_loss 0.13166 dice_loss 0.11765 +Epoch [1453/4000] Validation metric {'Val/mean dice_metric': 0.9696322679519653, 'Val/mean miou_metric': 0.952021598815918, 'Val/mean f1': 0.9711335897445679, 'Val/mean precision': 0.9654296040534973, 'Val/mean recall': 0.9769054651260376, 'Val/mean hd95_metric': 5.934756278991699} +Cheakpoint... +Epoch [1453/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696322679519653, 'Val/mean miou_metric': 0.952021598815918, 'Val/mean f1': 0.9711335897445679, 'Val/mean precision': 0.9654296040534973, 'Val/mean recall': 0.9769054651260376, 'Val/mean hd95_metric': 5.934756278991699} +Epoch [1454/4000] Training [1/16] Loss: 0.01045 +Epoch [1454/4000] Training [2/16] Loss: 0.00713 +Epoch [1454/4000] Training [3/16] Loss: 0.00878 +Epoch [1454/4000] Training [4/16] Loss: 0.00892 +Epoch [1454/4000] Training [5/16] Loss: 0.00987 +Epoch [1454/4000] Training [6/16] Loss: 0.01073 +Epoch [1454/4000] Training [7/16] Loss: 0.00753 +Epoch [1454/4000] Training [8/16] Loss: 0.01478 +Epoch [1454/4000] Training [9/16] Loss: 0.00627 +Epoch [1454/4000] Training [10/16] Loss: 0.00707 +Epoch [1454/4000] Training [11/16] Loss: 0.00750 +Epoch [1454/4000] Training [12/16] Loss: 0.00631 +Epoch [1454/4000] Training [13/16] Loss: 0.00827 +Epoch [1454/4000] Training [14/16] Loss: 0.00763 +Epoch [1454/4000] Training [15/16] Loss: 0.00934 +Epoch [1454/4000] Training [16/16] Loss: 0.01203 +Epoch [1454/4000] Training metric {'Train/mean dice_metric': 0.9933174252510071, 'Train/mean miou_metric': 0.9866396188735962, 'Train/mean f1': 0.9889910221099854, 'Train/mean precision': 0.9838057160377502, 'Train/mean recall': 0.9942312836647034, 'Train/mean hd95_metric': 1.1611605882644653} +Epoch [1454/4000] Validation [1/4] Loss: 0.20409 focal_loss 0.14442 dice_loss 0.05967 +Epoch [1454/4000] Validation [2/4] Loss: 0.26005 focal_loss 0.14814 dice_loss 0.11191 +Epoch [1454/4000] Validation [3/4] Loss: 0.22688 focal_loss 0.12852 dice_loss 0.09836 +Epoch [1454/4000] Validation [4/4] Loss: 0.21087 focal_loss 0.10094 dice_loss 0.10993 +Epoch [1454/4000] Validation metric {'Val/mean dice_metric': 0.9713195562362671, 'Val/mean miou_metric': 0.9527863264083862, 'Val/mean f1': 0.9717814326286316, 'Val/mean precision': 0.9645566344261169, 'Val/mean recall': 0.9791154265403748, 'Val/mean hd95_metric': 6.237273693084717} +Cheakpoint... +Epoch [1454/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713195562362671, 'Val/mean miou_metric': 0.9527863264083862, 'Val/mean f1': 0.9717814326286316, 'Val/mean precision': 0.9645566344261169, 'Val/mean recall': 0.9791154265403748, 'Val/mean hd95_metric': 6.237273693084717} +Epoch [1455/4000] Training [1/16] Loss: 0.00683 +Epoch [1455/4000] Training [2/16] Loss: 0.00776 +Epoch [1455/4000] Training [3/16] Loss: 0.00943 +Epoch [1455/4000] Training [4/16] Loss: 0.00899 +Epoch [1455/4000] Training [5/16] Loss: 0.00719 +Epoch [1455/4000] Training [6/16] Loss: 0.01005 +Epoch [1455/4000] Training [7/16] Loss: 0.01066 +Epoch [1455/4000] Training [8/16] Loss: 0.00760 +Epoch [1455/4000] Training [9/16] Loss: 0.00790 +Epoch [1455/4000] Training [10/16] Loss: 0.00787 +Epoch [1455/4000] Training [11/16] Loss: 0.00835 +Epoch [1455/4000] Training [12/16] Loss: 0.00925 +Epoch [1455/4000] Training [13/16] Loss: 0.01026 +Epoch [1455/4000] Training [14/16] Loss: 0.01050 +Epoch [1455/4000] Training [15/16] Loss: 0.01348 +Epoch [1455/4000] Training [16/16] Loss: 0.01248 +Epoch [1455/4000] Training metric {'Train/mean dice_metric': 0.9927089214324951, 'Train/mean miou_metric': 0.9855656623840332, 'Train/mean f1': 0.989115297794342, 'Train/mean precision': 0.9839901328086853, 'Train/mean recall': 0.9942941665649414, 'Train/mean hd95_metric': 1.7145884037017822} +Epoch [1455/4000] Validation [1/4] Loss: 0.17273 focal_loss 0.10808 dice_loss 0.06466 +Epoch [1455/4000] Validation [2/4] Loss: 0.48442 focal_loss 0.24321 dice_loss 0.24121 +Epoch [1455/4000] Validation [3/4] Loss: 0.15697 focal_loss 0.08208 dice_loss 0.07488 +Epoch [1455/4000] Validation [4/4] Loss: 0.15827 focal_loss 0.07303 dice_loss 0.08525 +Epoch [1455/4000] Validation metric {'Val/mean dice_metric': 0.9703388214111328, 'Val/mean miou_metric': 0.9512811899185181, 'Val/mean f1': 0.972736120223999, 'Val/mean precision': 0.9670886397361755, 'Val/mean recall': 0.978449821472168, 'Val/mean hd95_metric': 6.407147407531738} +Cheakpoint... +Epoch [1455/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703388214111328, 'Val/mean miou_metric': 0.9512811899185181, 'Val/mean f1': 0.972736120223999, 'Val/mean precision': 0.9670886397361755, 'Val/mean recall': 0.978449821472168, 'Val/mean hd95_metric': 6.407147407531738} +Epoch [1456/4000] Training [1/16] Loss: 0.00880 +Epoch [1456/4000] Training [2/16] Loss: 0.01073 +Epoch [1456/4000] Training [3/16] Loss: 0.00816 +Epoch [1456/4000] Training [4/16] Loss: 0.00643 +Epoch [1456/4000] Training [5/16] Loss: 0.00910 +Epoch [1456/4000] Training [6/16] Loss: 0.00880 +Epoch [1456/4000] Training [7/16] Loss: 0.01754 +Epoch [1456/4000] Training [8/16] Loss: 0.00941 +Epoch [1456/4000] Training [9/16] Loss: 0.02223 +Epoch [1456/4000] Training [10/16] Loss: 0.00727 +Epoch [1456/4000] Training [11/16] Loss: 0.00743 +Epoch [1456/4000] Training [12/16] Loss: 0.01079 +Epoch [1456/4000] Training [13/16] Loss: 0.00702 +Epoch [1456/4000] Training [14/16] Loss: 0.01018 +Epoch [1456/4000] Training [15/16] Loss: 0.00849 +Epoch [1456/4000] Training [16/16] Loss: 0.00688 +Epoch [1456/4000] Training metric {'Train/mean dice_metric': 0.9934324622154236, 'Train/mean miou_metric': 0.9867463111877441, 'Train/mean f1': 0.9897747039794922, 'Train/mean precision': 0.9852511882781982, 'Train/mean recall': 0.9943400025367737, 'Train/mean hd95_metric': 1.1448638439178467} +Epoch [1456/4000] Validation [1/4] Loss: 0.26466 focal_loss 0.19325 dice_loss 0.07141 +Epoch [1456/4000] Validation [2/4] Loss: 0.31184 focal_loss 0.15753 dice_loss 0.15431 +Epoch [1456/4000] Validation [3/4] Loss: 0.15221 focal_loss 0.09809 dice_loss 0.05412 +Epoch [1456/4000] Validation [4/4] Loss: 0.40675 focal_loss 0.26584 dice_loss 0.14091 +Epoch [1456/4000] Validation metric {'Val/mean dice_metric': 0.9694032669067383, 'Val/mean miou_metric': 0.9503602981567383, 'Val/mean f1': 0.9716562628746033, 'Val/mean precision': 0.968873143196106, 'Val/mean recall': 0.9744554758071899, 'Val/mean hd95_metric': 5.456235408782959} +Cheakpoint... +Epoch [1456/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694032669067383, 'Val/mean miou_metric': 0.9503602981567383, 'Val/mean f1': 0.9716562628746033, 'Val/mean precision': 0.968873143196106, 'Val/mean recall': 0.9744554758071899, 'Val/mean hd95_metric': 5.456235408782959} +Epoch [1457/4000] Training [1/16] Loss: 0.00796 +Epoch [1457/4000] Training [2/16] Loss: 0.01058 +Epoch [1457/4000] Training [3/16] Loss: 0.00781 +Epoch [1457/4000] Training [4/16] Loss: 0.01179 +Epoch [1457/4000] Training [5/16] Loss: 0.00681 +Epoch [1457/4000] Training [6/16] Loss: 0.01142 +Epoch [1457/4000] Training [7/16] Loss: 0.00649 +Epoch [1457/4000] Training [8/16] Loss: 0.00975 +Epoch [1457/4000] Training [9/16] Loss: 0.00890 +Epoch [1457/4000] Training [10/16] Loss: 0.00906 +Epoch [1457/4000] Training [11/16] Loss: 0.00888 +Epoch [1457/4000] Training [12/16] Loss: 0.00667 +Epoch [1457/4000] Training [13/16] Loss: 0.01078 +Epoch [1457/4000] Training [14/16] Loss: 0.01103 +Epoch [1457/4000] Training [15/16] Loss: 0.00888 +Epoch [1457/4000] Training [16/16] Loss: 0.01062 +Epoch [1457/4000] Training metric {'Train/mean dice_metric': 0.9938591718673706, 'Train/mean miou_metric': 0.9875853657722473, 'Train/mean f1': 0.989981472492218, 'Train/mean precision': 0.9853788018226624, 'Train/mean recall': 0.9946273565292358, 'Train/mean hd95_metric': 1.0808742046356201} +Epoch [1457/4000] Validation [1/4] Loss: 0.20212 focal_loss 0.13926 dice_loss 0.06286 +Epoch [1457/4000] Validation [2/4] Loss: 0.31209 focal_loss 0.16322 dice_loss 0.14887 +Epoch [1457/4000] Validation [3/4] Loss: 0.16248 focal_loss 0.10156 dice_loss 0.06091 +Epoch [1457/4000] Validation [4/4] Loss: 0.27904 focal_loss 0.15206 dice_loss 0.12698 +Epoch [1457/4000] Validation metric {'Val/mean dice_metric': 0.9708570241928101, 'Val/mean miou_metric': 0.9527020454406738, 'Val/mean f1': 0.9735302329063416, 'Val/mean precision': 0.9685502648353577, 'Val/mean recall': 0.9785617589950562, 'Val/mean hd95_metric': 5.318828582763672} +Cheakpoint... +Epoch [1457/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708570241928101, 'Val/mean miou_metric': 0.9527020454406738, 'Val/mean f1': 0.9735302329063416, 'Val/mean precision': 0.9685502648353577, 'Val/mean recall': 0.9785617589950562, 'Val/mean hd95_metric': 5.318828582763672} +Epoch [1458/4000] Training [1/16] Loss: 0.01335 +Epoch [1458/4000] Training [2/16] Loss: 0.00862 +Epoch [1458/4000] Training [3/16] Loss: 0.00800 +Epoch [1458/4000] Training [4/16] Loss: 0.00622 +Epoch [1458/4000] Training [5/16] Loss: 0.00670 +Epoch [1458/4000] Training [6/16] Loss: 0.00810 +Epoch [1458/4000] Training [7/16] Loss: 0.00634 +Epoch [1458/4000] Training [8/16] Loss: 0.00726 +Epoch [1458/4000] Training [9/16] Loss: 0.00750 +Epoch [1458/4000] Training [10/16] Loss: 0.00695 +Epoch [1458/4000] Training [11/16] Loss: 0.00911 +Epoch [1458/4000] Training [12/16] Loss: 0.00703 +Epoch [1458/4000] Training [13/16] Loss: 0.00778 +Epoch [1458/4000] Training [14/16] Loss: 0.01095 +Epoch [1458/4000] Training [15/16] Loss: 0.00693 +Epoch [1458/4000] Training [16/16] Loss: 0.00845 +Epoch [1458/4000] Training metric {'Train/mean dice_metric': 0.9945935606956482, 'Train/mean miou_metric': 0.9889975786209106, 'Train/mean f1': 0.9906065464019775, 'Train/mean precision': 0.9860245585441589, 'Train/mean recall': 0.9952312707901001, 'Train/mean hd95_metric': 1.3212881088256836} +Epoch [1458/4000] Validation [1/4] Loss: 0.20681 focal_loss 0.14345 dice_loss 0.06336 +Epoch [1458/4000] Validation [2/4] Loss: 0.32972 focal_loss 0.17692 dice_loss 0.15280 +Epoch [1458/4000] Validation [3/4] Loss: 0.13366 focal_loss 0.08218 dice_loss 0.05148 +Epoch [1458/4000] Validation [4/4] Loss: 0.24327 focal_loss 0.14319 dice_loss 0.10008 +Epoch [1458/4000] Validation metric {'Val/mean dice_metric': 0.9718014597892761, 'Val/mean miou_metric': 0.9542152285575867, 'Val/mean f1': 0.9733125567436218, 'Val/mean precision': 0.9693582057952881, 'Val/mean recall': 0.9772992134094238, 'Val/mean hd95_metric': 5.580286502838135} +Cheakpoint... +Epoch [1458/4000] best acc:tensor([0.9737], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718014597892761, 'Val/mean miou_metric': 0.9542152285575867, 'Val/mean f1': 0.9733125567436218, 'Val/mean precision': 0.9693582057952881, 'Val/mean recall': 0.9772992134094238, 'Val/mean hd95_metric': 5.580286502838135} +Epoch [1459/4000] Training [1/16] Loss: 0.01063 +Epoch [1459/4000] Training [2/16] Loss: 0.01533 +Epoch [1459/4000] Training [3/16] Loss: 0.00822 +Epoch [1459/4000] Training [4/16] Loss: 0.01096 +Epoch [1459/4000] Training [5/16] Loss: 0.00738 +Epoch [1459/4000] Training [6/16] Loss: 0.00969 +Epoch [1459/4000] Training [7/16] Loss: 0.01043 +Epoch [1459/4000] Training [8/16] Loss: 0.00795 +Epoch [1459/4000] Training [9/16] Loss: 0.01130 +Epoch [1459/4000] Training [10/16] Loss: 0.00626 +Epoch [1459/4000] Training [11/16] Loss: 0.00794 +Epoch [1459/4000] Training [12/16] Loss: 0.00868 +Epoch [1459/4000] Training [13/16] Loss: 0.00571 +Epoch [1459/4000] Training [14/16] Loss: 0.00811 +Epoch [1459/4000] Training [15/16] Loss: 0.00655 +Epoch [1459/4000] Training [16/16] Loss: 0.00904 +Epoch [1459/4000] Training metric {'Train/mean dice_metric': 0.9942134618759155, 'Train/mean miou_metric': 0.9882487058639526, 'Train/mean f1': 0.9902787208557129, 'Train/mean precision': 0.9857427477836609, 'Train/mean recall': 0.9948566555976868, 'Train/mean hd95_metric': 1.0993776321411133} +Epoch [1459/4000] Validation [1/4] Loss: 0.21102 focal_loss 0.15094 dice_loss 0.06008 +Epoch [1459/4000] Validation [2/4] Loss: 0.30366 focal_loss 0.13602 dice_loss 0.16765 +Epoch [1459/4000] Validation [3/4] Loss: 0.14344 focal_loss 0.08589 dice_loss 0.05755 +Epoch [1459/4000] Validation [4/4] Loss: 0.21086 focal_loss 0.10743 dice_loss 0.10343 +Epoch [1459/4000] Validation metric {'Val/mean dice_metric': 0.9742663502693176, 'Val/mean miou_metric': 0.9566437602043152, 'Val/mean f1': 0.9745071530342102, 'Val/mean precision': 0.970119297504425, 'Val/mean recall': 0.9789349436759949, 'Val/mean hd95_metric': 5.177316665649414} +Cheakpoint... +Epoch [1459/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742663502693176, 'Val/mean miou_metric': 0.9566437602043152, 'Val/mean f1': 0.9745071530342102, 'Val/mean precision': 0.970119297504425, 'Val/mean recall': 0.9789349436759949, 'Val/mean hd95_metric': 5.177316665649414} +Epoch [1460/4000] Training [1/16] Loss: 0.00911 +Epoch [1460/4000] Training [2/16] Loss: 0.00627 +Epoch [1460/4000] Training [3/16] Loss: 0.00895 +Epoch [1460/4000] Training [4/16] Loss: 0.01057 +Epoch [1460/4000] Training [5/16] Loss: 0.00767 +Epoch [1460/4000] Training [6/16] Loss: 0.00847 +Epoch [1460/4000] Training [7/16] Loss: 0.00829 +Epoch [1460/4000] Training [8/16] Loss: 0.00752 +Epoch [1460/4000] Training [9/16] Loss: 0.00902 +Epoch [1460/4000] Training [10/16] Loss: 0.01018 +Epoch [1460/4000] Training [11/16] Loss: 0.01060 +Epoch [1460/4000] Training [12/16] Loss: 0.00808 +Epoch [1460/4000] Training [13/16] Loss: 0.00792 +Epoch [1460/4000] Training [14/16] Loss: 0.00755 +Epoch [1460/4000] Training [15/16] Loss: 0.01052 +Epoch [1460/4000] Training [16/16] Loss: 0.00840 +Epoch [1460/4000] Training metric {'Train/mean dice_metric': 0.9940133094787598, 'Train/mean miou_metric': 0.987891435623169, 'Train/mean f1': 0.9904589653015137, 'Train/mean precision': 0.9859728217124939, 'Train/mean recall': 0.9949861764907837, 'Train/mean hd95_metric': 1.103669285774231} +Epoch [1460/4000] Validation [1/4] Loss: 0.18778 focal_loss 0.12203 dice_loss 0.06575 +Epoch [1460/4000] Validation [2/4] Loss: 0.31819 focal_loss 0.17661 dice_loss 0.14159 +Epoch [1460/4000] Validation [3/4] Loss: 0.14832 focal_loss 0.09278 dice_loss 0.05554 +Epoch [1460/4000] Validation [4/4] Loss: 0.31909 focal_loss 0.17963 dice_loss 0.13946 +Epoch [1460/4000] Validation metric {'Val/mean dice_metric': 0.9712932705879211, 'Val/mean miou_metric': 0.9530915021896362, 'Val/mean f1': 0.9734098315238953, 'Val/mean precision': 0.9702306985855103, 'Val/mean recall': 0.976610004901886, 'Val/mean hd95_metric': 5.089921951293945} +Cheakpoint... +Epoch [1460/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712932705879211, 'Val/mean miou_metric': 0.9530915021896362, 'Val/mean f1': 0.9734098315238953, 'Val/mean precision': 0.9702306985855103, 'Val/mean recall': 0.976610004901886, 'Val/mean hd95_metric': 5.089921951293945} +Epoch [1461/4000] Training [1/16] Loss: 0.00692 +Epoch [1461/4000] Training [2/16] Loss: 0.00678 +Epoch [1461/4000] Training [3/16] Loss: 0.00786 +Epoch [1461/4000] Training [4/16] Loss: 0.00860 +Epoch [1461/4000] Training [5/16] Loss: 0.01007 +Epoch [1461/4000] Training [6/16] Loss: 0.00520 +Epoch [1461/4000] Training [7/16] Loss: 0.00710 +Epoch [1461/4000] Training [8/16] Loss: 0.00700 +Epoch [1461/4000] Training [9/16] Loss: 0.01178 +Epoch [1461/4000] Training [10/16] Loss: 0.00592 +Epoch [1461/4000] Training [11/16] Loss: 0.00958 +Epoch [1461/4000] Training [12/16] Loss: 0.00692 +Epoch [1461/4000] Training [13/16] Loss: 0.01186 +Epoch [1461/4000] Training [14/16] Loss: 0.00910 +Epoch [1461/4000] Training [15/16] Loss: 0.00581 +Epoch [1461/4000] Training [16/16] Loss: 0.00971 +Epoch [1461/4000] Training metric {'Train/mean dice_metric': 0.9944206476211548, 'Train/mean miou_metric': 0.9886617660522461, 'Train/mean f1': 0.9905091524124146, 'Train/mean precision': 0.985953152179718, 'Train/mean recall': 0.9951074719429016, 'Train/mean hd95_metric': 1.0413768291473389} +Epoch [1461/4000] Validation [1/4] Loss: 0.21751 focal_loss 0.14735 dice_loss 0.07016 +Epoch [1461/4000] Validation [2/4] Loss: 0.47646 focal_loss 0.28138 dice_loss 0.19508 +Epoch [1461/4000] Validation [3/4] Loss: 0.15748 focal_loss 0.09815 dice_loss 0.05933 +Epoch [1461/4000] Validation [4/4] Loss: 0.29187 focal_loss 0.16939 dice_loss 0.12248 +Epoch [1461/4000] Validation metric {'Val/mean dice_metric': 0.9729778170585632, 'Val/mean miou_metric': 0.9549087285995483, 'Val/mean f1': 0.9731819033622742, 'Val/mean precision': 0.9694715142250061, 'Val/mean recall': 0.9769207835197449, 'Val/mean hd95_metric': 5.858458518981934} +Cheakpoint... +Epoch [1461/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729778170585632, 'Val/mean miou_metric': 0.9549087285995483, 'Val/mean f1': 0.9731819033622742, 'Val/mean precision': 0.9694715142250061, 'Val/mean recall': 0.9769207835197449, 'Val/mean hd95_metric': 5.858458518981934} +Epoch [1462/4000] Training [1/16] Loss: 0.00930 +Epoch [1462/4000] Training [2/16] Loss: 0.00725 +Epoch [1462/4000] Training [3/16] Loss: 0.00895 +Epoch [1462/4000] Training [4/16] Loss: 0.00890 +Epoch [1462/4000] Training [5/16] Loss: 0.00987 +Epoch [1462/4000] Training [6/16] Loss: 0.00847 +Epoch [1462/4000] Training [7/16] Loss: 0.00882 +Epoch [1462/4000] Training [8/16] Loss: 0.00591 +Epoch [1462/4000] Training [9/16] Loss: 0.00883 +Epoch [1462/4000] Training [10/16] Loss: 0.00642 +Epoch [1462/4000] Training [11/16] Loss: 0.00672 +Epoch [1462/4000] Training [12/16] Loss: 0.00668 +Epoch [1462/4000] Training [13/16] Loss: 0.00966 +Epoch [1462/4000] Training [14/16] Loss: 0.00927 +Epoch [1462/4000] Training [15/16] Loss: 0.00747 +Epoch [1462/4000] Training [16/16] Loss: 0.00753 +Epoch [1462/4000] Training metric {'Train/mean dice_metric': 0.9945580363273621, 'Train/mean miou_metric': 0.9889135956764221, 'Train/mean f1': 0.9904748797416687, 'Train/mean precision': 0.9857056736946106, 'Train/mean recall': 0.9952905178070068, 'Train/mean hd95_metric': 1.0829784870147705} +Epoch [1462/4000] Validation [1/4] Loss: 0.32680 focal_loss 0.23530 dice_loss 0.09149 +Epoch [1462/4000] Validation [2/4] Loss: 0.49436 focal_loss 0.30253 dice_loss 0.19183 +Epoch [1462/4000] Validation [3/4] Loss: 0.14922 focal_loss 0.09575 dice_loss 0.05348 +Epoch [1462/4000] Validation [4/4] Loss: 0.25409 focal_loss 0.14025 dice_loss 0.11384 +Epoch [1462/4000] Validation metric {'Val/mean dice_metric': 0.9704370498657227, 'Val/mean miou_metric': 0.9529992341995239, 'Val/mean f1': 0.9727298617362976, 'Val/mean precision': 0.9705548286437988, 'Val/mean recall': 0.97491455078125, 'Val/mean hd95_metric': 5.4596781730651855} +Cheakpoint... +Epoch [1462/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704370498657227, 'Val/mean miou_metric': 0.9529992341995239, 'Val/mean f1': 0.9727298617362976, 'Val/mean precision': 0.9705548286437988, 'Val/mean recall': 0.97491455078125, 'Val/mean hd95_metric': 5.4596781730651855} +Epoch [1463/4000] Training [1/16] Loss: 0.01131 +Epoch [1463/4000] Training [2/16] Loss: 0.01009 +Epoch [1463/4000] Training [3/16] Loss: 0.00838 +Epoch [1463/4000] Training [4/16] Loss: 0.00706 +Epoch [1463/4000] Training [5/16] Loss: 0.00708 +Epoch [1463/4000] Training [6/16] Loss: 0.00893 +Epoch [1463/4000] Training [7/16] Loss: 0.00691 +Epoch [1463/4000] Training [8/16] Loss: 0.00716 +Epoch [1463/4000] Training [9/16] Loss: 0.00819 +Epoch [1463/4000] Training [10/16] Loss: 0.00949 +Epoch [1463/4000] Training [11/16] Loss: 0.00741 +Epoch [1463/4000] Training [12/16] Loss: 0.01194 +Epoch [1463/4000] Training [13/16] Loss: 0.00823 +Epoch [1463/4000] Training [14/16] Loss: 0.00590 +Epoch [1463/4000] Training [15/16] Loss: 0.01229 +Epoch [1463/4000] Training [16/16] Loss: 0.00776 +Epoch [1463/4000] Training metric {'Train/mean dice_metric': 0.9939868450164795, 'Train/mean miou_metric': 0.9878132343292236, 'Train/mean f1': 0.9902576804161072, 'Train/mean precision': 0.9857487082481384, 'Train/mean recall': 0.9948080778121948, 'Train/mean hd95_metric': 1.098412275314331} +Epoch [1463/4000] Validation [1/4] Loss: 0.20431 focal_loss 0.13553 dice_loss 0.06878 +Epoch [1463/4000] Validation [2/4] Loss: 0.56868 focal_loss 0.36600 dice_loss 0.20268 +Epoch [1463/4000] Validation [3/4] Loss: 0.19286 focal_loss 0.12516 dice_loss 0.06770 +Epoch [1463/4000] Validation [4/4] Loss: 0.25328 focal_loss 0.13696 dice_loss 0.11631 +Epoch [1463/4000] Validation metric {'Val/mean dice_metric': 0.9703868627548218, 'Val/mean miou_metric': 0.952301025390625, 'Val/mean f1': 0.9730703234672546, 'Val/mean precision': 0.969817042350769, 'Val/mean recall': 0.9763454794883728, 'Val/mean hd95_metric': 6.05322265625} +Cheakpoint... +Epoch [1463/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703868627548218, 'Val/mean miou_metric': 0.952301025390625, 'Val/mean f1': 0.9730703234672546, 'Val/mean precision': 0.969817042350769, 'Val/mean recall': 0.9763454794883728, 'Val/mean hd95_metric': 6.05322265625} +Epoch [1464/4000] Training [1/16] Loss: 0.01086 +Epoch [1464/4000] Training [2/16] Loss: 0.00796 +Epoch [1464/4000] Training [3/16] Loss: 0.01654 +Epoch [1464/4000] Training [4/16] Loss: 0.01460 +Epoch [1464/4000] Training [5/16] Loss: 0.01031 +Epoch [1464/4000] Training [6/16] Loss: 0.00772 +Epoch [1464/4000] Training [7/16] Loss: 0.00877 +Epoch [1464/4000] Training [8/16] Loss: 0.01210 +Epoch [1464/4000] Training [9/16] Loss: 0.01018 +Epoch [1464/4000] Training [10/16] Loss: 0.00964 +Epoch [1464/4000] Training [11/16] Loss: 0.00708 +Epoch [1464/4000] Training [12/16] Loss: 0.00971 +Epoch [1464/4000] Training [13/16] Loss: 0.00837 +Epoch [1464/4000] Training [14/16] Loss: 0.00919 +Epoch [1464/4000] Training [15/16] Loss: 0.00737 +Epoch [1464/4000] Training [16/16] Loss: 0.01155 +Epoch [1464/4000] Training metric {'Train/mean dice_metric': 0.9921354055404663, 'Train/mean miou_metric': 0.984610915184021, 'Train/mean f1': 0.9895111322402954, 'Train/mean precision': 0.984863817691803, 'Train/mean recall': 0.9942024946212769, 'Train/mean hd95_metric': 1.3184702396392822} +Epoch [1464/4000] Validation [1/4] Loss: 0.30316 focal_loss 0.21399 dice_loss 0.08917 +Epoch [1464/4000] Validation [2/4] Loss: 0.30966 focal_loss 0.16146 dice_loss 0.14819 +Epoch [1464/4000] Validation [3/4] Loss: 0.16909 focal_loss 0.09749 dice_loss 0.07160 +Epoch [1464/4000] Validation [4/4] Loss: 0.23762 focal_loss 0.12712 dice_loss 0.11050 +Epoch [1464/4000] Validation metric {'Val/mean dice_metric': 0.9644899368286133, 'Val/mean miou_metric': 0.944017767906189, 'Val/mean f1': 0.9686920642852783, 'Val/mean precision': 0.9713650941848755, 'Val/mean recall': 0.9660336971282959, 'Val/mean hd95_metric': 6.414836883544922} +Cheakpoint... +Epoch [1464/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644899368286133, 'Val/mean miou_metric': 0.944017767906189, 'Val/mean f1': 0.9686920642852783, 'Val/mean precision': 0.9713650941848755, 'Val/mean recall': 0.9660336971282959, 'Val/mean hd95_metric': 6.414836883544922} +Epoch [1465/4000] Training [1/16] Loss: 0.01118 +Epoch [1465/4000] Training [2/16] Loss: 0.00719 +Epoch [1465/4000] Training [3/16] Loss: 0.01128 +Epoch [1465/4000] Training [4/16] Loss: 0.00757 +Epoch [1465/4000] Training [5/16] Loss: 0.00885 +Epoch [1465/4000] Training [6/16] Loss: 0.00826 +Epoch [1465/4000] Training [7/16] Loss: 0.00826 +Epoch [1465/4000] Training [8/16] Loss: 0.01032 +Epoch [1465/4000] Training [9/16] Loss: 0.00993 +Epoch [1465/4000] Training [10/16] Loss: 0.01191 +Epoch [1465/4000] Training [11/16] Loss: 0.00758 +Epoch [1465/4000] Training [12/16] Loss: 0.00838 +Epoch [1465/4000] Training [13/16] Loss: 0.00742 +Epoch [1465/4000] Training [14/16] Loss: 0.00839 +Epoch [1465/4000] Training [15/16] Loss: 0.01270 +Epoch [1465/4000] Training [16/16] Loss: 0.01183 +Epoch [1465/4000] Training metric {'Train/mean dice_metric': 0.9932599663734436, 'Train/mean miou_metric': 0.9863801598548889, 'Train/mean f1': 0.9896945357322693, 'Train/mean precision': 0.9851382970809937, 'Train/mean recall': 0.9942930936813354, 'Train/mean hd95_metric': 1.1646236181259155} +Epoch [1465/4000] Validation [1/4] Loss: 0.23647 focal_loss 0.17019 dice_loss 0.06629 +Epoch [1465/4000] Validation [2/4] Loss: 0.26210 focal_loss 0.14861 dice_loss 0.11349 +Epoch [1465/4000] Validation [3/4] Loss: 0.17804 focal_loss 0.11095 dice_loss 0.06710 +Epoch [1465/4000] Validation [4/4] Loss: 0.27040 focal_loss 0.15129 dice_loss 0.11911 +Epoch [1465/4000] Validation metric {'Val/mean dice_metric': 0.9699898958206177, 'Val/mean miou_metric': 0.9510217905044556, 'Val/mean f1': 0.9717932939529419, 'Val/mean precision': 0.9709436297416687, 'Val/mean recall': 0.9726444482803345, 'Val/mean hd95_metric': 5.313529968261719} +Cheakpoint... +Epoch [1465/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699898958206177, 'Val/mean miou_metric': 0.9510217905044556, 'Val/mean f1': 0.9717932939529419, 'Val/mean precision': 0.9709436297416687, 'Val/mean recall': 0.9726444482803345, 'Val/mean hd95_metric': 5.313529968261719} +Epoch [1466/4000] Training [1/16] Loss: 0.00780 +Epoch [1466/4000] Training [2/16] Loss: 0.00713 +Epoch [1466/4000] Training [3/16] Loss: 0.00966 +Epoch [1466/4000] Training [4/16] Loss: 0.00970 +Epoch [1466/4000] Training [5/16] Loss: 0.00972 +Epoch [1466/4000] Training [6/16] Loss: 0.00857 +Epoch [1466/4000] Training [7/16] Loss: 0.00783 +Epoch [1466/4000] Training [8/16] Loss: 0.00638 +Epoch [1466/4000] Training [9/16] Loss: 0.00868 +Epoch [1466/4000] Training [10/16] Loss: 0.01031 +Epoch [1466/4000] Training [11/16] Loss: 0.00719 +Epoch [1466/4000] Training [12/16] Loss: 0.00885 +Epoch [1466/4000] Training [13/16] Loss: 0.00763 +Epoch [1466/4000] Training [14/16] Loss: 0.00639 +Epoch [1466/4000] Training [15/16] Loss: 0.00872 +Epoch [1466/4000] Training [16/16] Loss: 0.00837 +Epoch [1466/4000] Training metric {'Train/mean dice_metric': 0.99341881275177, 'Train/mean miou_metric': 0.9869870543479919, 'Train/mean f1': 0.990049421787262, 'Train/mean precision': 0.9854638576507568, 'Train/mean recall': 0.9946779012680054, 'Train/mean hd95_metric': 1.235639214515686} +Epoch [1466/4000] Validation [1/4] Loss: 0.33764 focal_loss 0.23926 dice_loss 0.09839 +Epoch [1466/4000] Validation [2/4] Loss: 0.35050 focal_loss 0.18630 dice_loss 0.16420 +Epoch [1466/4000] Validation [3/4] Loss: 0.20146 focal_loss 0.12992 dice_loss 0.07154 +Epoch [1466/4000] Validation [4/4] Loss: 0.21115 focal_loss 0.11056 dice_loss 0.10060 +Epoch [1466/4000] Validation metric {'Val/mean dice_metric': 0.9688520431518555, 'Val/mean miou_metric': 0.9506157040596008, 'Val/mean f1': 0.9716379046440125, 'Val/mean precision': 0.9722447395324707, 'Val/mean recall': 0.9710318446159363, 'Val/mean hd95_metric': 5.9226884841918945} +Cheakpoint... +Epoch [1466/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688520431518555, 'Val/mean miou_metric': 0.9506157040596008, 'Val/mean f1': 0.9716379046440125, 'Val/mean precision': 0.9722447395324707, 'Val/mean recall': 0.9710318446159363, 'Val/mean hd95_metric': 5.9226884841918945} +Epoch [1467/4000] Training [1/16] Loss: 0.00775 +Epoch [1467/4000] Training [2/16] Loss: 0.00780 +Epoch [1467/4000] Training [3/16] Loss: 0.00942 +Epoch [1467/4000] Training [4/16] Loss: 0.00682 +Epoch [1467/4000] Training [5/16] Loss: 0.00737 +Epoch [1467/4000] Training [6/16] Loss: 0.00524 +Epoch [1467/4000] Training [7/16] Loss: 0.00761 +Epoch [1467/4000] Training [8/16] Loss: 0.01078 +Epoch [1467/4000] Training [9/16] Loss: 0.00853 +Epoch [1467/4000] Training [10/16] Loss: 0.01072 +Epoch [1467/4000] Training [11/16] Loss: 0.01589 +Epoch [1467/4000] Training [12/16] Loss: 0.01087 +Epoch [1467/4000] Training [13/16] Loss: 0.00867 +Epoch [1467/4000] Training [14/16] Loss: 0.00763 +Epoch [1467/4000] Training [15/16] Loss: 0.01511 +Epoch [1467/4000] Training [16/16] Loss: 0.00949 +Epoch [1467/4000] Training metric {'Train/mean dice_metric': 0.993923008441925, 'Train/mean miou_metric': 0.9876593351364136, 'Train/mean f1': 0.9895411729812622, 'Train/mean precision': 0.9844520688056946, 'Train/mean recall': 0.9946831464767456, 'Train/mean hd95_metric': 1.093103289604187} +Epoch [1467/4000] Validation [1/4] Loss: 0.29619 focal_loss 0.22296 dice_loss 0.07323 +Epoch [1467/4000] Validation [2/4] Loss: 0.25890 focal_loss 0.14689 dice_loss 0.11201 +Epoch [1467/4000] Validation [3/4] Loss: 0.20709 focal_loss 0.12367 dice_loss 0.08342 +Epoch [1467/4000] Validation [4/4] Loss: 0.23426 focal_loss 0.12875 dice_loss 0.10551 +Epoch [1467/4000] Validation metric {'Val/mean dice_metric': 0.9727432131767273, 'Val/mean miou_metric': 0.9542413949966431, 'Val/mean f1': 0.9731362462043762, 'Val/mean precision': 0.9732657074928284, 'Val/mean recall': 0.9730066657066345, 'Val/mean hd95_metric': 5.373307228088379} +Cheakpoint... +Epoch [1467/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727432131767273, 'Val/mean miou_metric': 0.9542413949966431, 'Val/mean f1': 0.9731362462043762, 'Val/mean precision': 0.9732657074928284, 'Val/mean recall': 0.9730066657066345, 'Val/mean hd95_metric': 5.373307228088379} +Epoch [1468/4000] Training [1/16] Loss: 0.01285 +Epoch [1468/4000] Training [2/16] Loss: 0.00962 +Epoch [1468/4000] Training [3/16] Loss: 0.00670 +Epoch [1468/4000] Training [4/16] Loss: 0.00782 +Epoch [1468/4000] Training [5/16] Loss: 0.00804 +Epoch [1468/4000] Training [6/16] Loss: 0.01185 +Epoch [1468/4000] Training [7/16] Loss: 0.00669 +Epoch [1468/4000] Training [8/16] Loss: 0.00631 +Epoch [1468/4000] Training [9/16] Loss: 0.00834 +Epoch [1468/4000] Training [10/16] Loss: 0.00932 +Epoch [1468/4000] Training [11/16] Loss: 0.00666 +Epoch [1468/4000] Training [12/16] Loss: 0.02159 +Epoch [1468/4000] Training [13/16] Loss: 0.00727 +Epoch [1468/4000] Training [14/16] Loss: 0.00732 +Epoch [1468/4000] Training [15/16] Loss: 0.00896 +Epoch [1468/4000] Training [16/16] Loss: 0.00948 +Epoch [1468/4000] Training metric {'Train/mean dice_metric': 0.994120717048645, 'Train/mean miou_metric': 0.988071620464325, 'Train/mean f1': 0.9903421998023987, 'Train/mean precision': 0.986008882522583, 'Train/mean recall': 0.9947137236595154, 'Train/mean hd95_metric': 1.0672520399093628} +Epoch [1468/4000] Validation [1/4] Loss: 0.26687 focal_loss 0.19649 dice_loss 0.07038 +Epoch [1468/4000] Validation [2/4] Loss: 0.23265 focal_loss 0.12937 dice_loss 0.10329 +Epoch [1468/4000] Validation [3/4] Loss: 0.19377 focal_loss 0.12475 dice_loss 0.06902 +Epoch [1468/4000] Validation [4/4] Loss: 0.26576 focal_loss 0.14865 dice_loss 0.11711 +Epoch [1468/4000] Validation metric {'Val/mean dice_metric': 0.971197783946991, 'Val/mean miou_metric': 0.9533311724662781, 'Val/mean f1': 0.972922682762146, 'Val/mean precision': 0.9731307029724121, 'Val/mean recall': 0.9727147221565247, 'Val/mean hd95_metric': 5.091794490814209} +Cheakpoint... +Epoch [1468/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971197783946991, 'Val/mean miou_metric': 0.9533311724662781, 'Val/mean f1': 0.972922682762146, 'Val/mean precision': 0.9731307029724121, 'Val/mean recall': 0.9727147221565247, 'Val/mean hd95_metric': 5.091794490814209} +Epoch [1469/4000] Training [1/16] Loss: 0.01104 +Epoch [1469/4000] Training [2/16] Loss: 0.00629 +Epoch [1469/4000] Training [3/16] Loss: 0.00817 +Epoch [1469/4000] Training [4/16] Loss: 0.00889 +Epoch [1469/4000] Training [5/16] Loss: 0.00814 +Epoch [1469/4000] Training [6/16] Loss: 0.00853 +Epoch [1469/4000] Training [7/16] Loss: 0.01265 +Epoch [1469/4000] Training [8/16] Loss: 0.00828 +Epoch [1469/4000] Training [9/16] Loss: 0.00780 +Epoch [1469/4000] Training [10/16] Loss: 0.00716 +Epoch [1469/4000] Training [11/16] Loss: 0.01105 +Epoch [1469/4000] Training [12/16] Loss: 0.01119 +Epoch [1469/4000] Training [13/16] Loss: 0.00759 +Epoch [1469/4000] Training [14/16] Loss: 0.00710 +Epoch [1469/4000] Training [15/16] Loss: 0.01310 +Epoch [1469/4000] Training [16/16] Loss: 0.00619 +Epoch [1469/4000] Training metric {'Train/mean dice_metric': 0.9935598969459534, 'Train/mean miou_metric': 0.9870072603225708, 'Train/mean f1': 0.9901422262191772, 'Train/mean precision': 0.9856048822402954, 'Train/mean recall': 0.994721531867981, 'Train/mean hd95_metric': 1.1002496480941772} +Epoch [1469/4000] Validation [1/4] Loss: 0.29239 focal_loss 0.21253 dice_loss 0.07985 +Epoch [1469/4000] Validation [2/4] Loss: 0.29122 focal_loss 0.16448 dice_loss 0.12674 +Epoch [1469/4000] Validation [3/4] Loss: 0.18770 focal_loss 0.11376 dice_loss 0.07394 +Epoch [1469/4000] Validation [4/4] Loss: 0.26553 focal_loss 0.15245 dice_loss 0.11308 +Epoch [1469/4000] Validation metric {'Val/mean dice_metric': 0.968713641166687, 'Val/mean miou_metric': 0.9501223564147949, 'Val/mean f1': 0.9719684720039368, 'Val/mean precision': 0.9720361828804016, 'Val/mean recall': 0.9719008803367615, 'Val/mean hd95_metric': 5.697798252105713} +Cheakpoint... +Epoch [1469/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968713641166687, 'Val/mean miou_metric': 0.9501223564147949, 'Val/mean f1': 0.9719684720039368, 'Val/mean precision': 0.9720361828804016, 'Val/mean recall': 0.9719008803367615, 'Val/mean hd95_metric': 5.697798252105713} +Epoch [1470/4000] Training [1/16] Loss: 0.00653 +Epoch [1470/4000] Training [2/16] Loss: 0.00942 +Epoch [1470/4000] Training [3/16] Loss: 0.00869 +Epoch [1470/4000] Training [4/16] Loss: 0.01012 +Epoch [1470/4000] Training [5/16] Loss: 0.00632 +Epoch [1470/4000] Training [6/16] Loss: 0.00920 +Epoch [1470/4000] Training [7/16] Loss: 0.00783 +Epoch [1470/4000] Training [8/16] Loss: 0.00921 +Epoch [1470/4000] Training [9/16] Loss: 0.00899 +Epoch [1470/4000] Training [10/16] Loss: 0.00778 +Epoch [1470/4000] Training [11/16] Loss: 0.00658 +Epoch [1470/4000] Training [12/16] Loss: 0.01032 +Epoch [1470/4000] Training [13/16] Loss: 0.00959 +Epoch [1470/4000] Training [14/16] Loss: 0.01003 +Epoch [1470/4000] Training [15/16] Loss: 0.00676 +Epoch [1470/4000] Training [16/16] Loss: 0.00756 +Epoch [1470/4000] Training metric {'Train/mean dice_metric': 0.9942533373832703, 'Train/mean miou_metric': 0.9883294105529785, 'Train/mean f1': 0.9904770851135254, 'Train/mean precision': 0.9859783053398132, 'Train/mean recall': 0.9950171709060669, 'Train/mean hd95_metric': 1.050434947013855} +Epoch [1470/4000] Validation [1/4] Loss: 0.24461 focal_loss 0.17155 dice_loss 0.07306 +Epoch [1470/4000] Validation [2/4] Loss: 0.26084 focal_loss 0.14550 dice_loss 0.11533 +Epoch [1470/4000] Validation [3/4] Loss: 0.19539 focal_loss 0.13011 dice_loss 0.06528 +Epoch [1470/4000] Validation [4/4] Loss: 0.32856 focal_loss 0.20140 dice_loss 0.12716 +Epoch [1470/4000] Validation metric {'Val/mean dice_metric': 0.9689604640007019, 'Val/mean miou_metric': 0.9508939981460571, 'Val/mean f1': 0.9718865156173706, 'Val/mean precision': 0.9717910885810852, 'Val/mean recall': 0.971981942653656, 'Val/mean hd95_metric': 5.278090000152588} +Cheakpoint... +Epoch [1470/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689604640007019, 'Val/mean miou_metric': 0.9508939981460571, 'Val/mean f1': 0.9718865156173706, 'Val/mean precision': 0.9717910885810852, 'Val/mean recall': 0.971981942653656, 'Val/mean hd95_metric': 5.278090000152588} +Epoch [1471/4000] Training [1/16] Loss: 0.00688 +Epoch [1471/4000] Training [2/16] Loss: 0.00623 +Epoch [1471/4000] Training [3/16] Loss: 0.00979 +Epoch [1471/4000] Training [4/16] Loss: 0.00770 +Epoch [1471/4000] Training [5/16] Loss: 0.00899 +Epoch [1471/4000] Training [6/16] Loss: 0.00832 +Epoch [1471/4000] Training [7/16] Loss: 0.00744 +Epoch [1471/4000] Training [8/16] Loss: 0.00944 +Epoch [1471/4000] Training [9/16] Loss: 0.00895 +Epoch [1471/4000] Training [10/16] Loss: 0.01157 +Epoch [1471/4000] Training [11/16] Loss: 0.00688 +Epoch [1471/4000] Training [12/16] Loss: 0.01131 +Epoch [1471/4000] Training [13/16] Loss: 0.00804 +Epoch [1471/4000] Training [14/16] Loss: 0.00981 +Epoch [1471/4000] Training [15/16] Loss: 0.00764 +Epoch [1471/4000] Training [16/16] Loss: 0.00726 +Epoch [1471/4000] Training metric {'Train/mean dice_metric': 0.9941956400871277, 'Train/mean miou_metric': 0.9882161021232605, 'Train/mean f1': 0.9903210997581482, 'Train/mean precision': 0.9856848120689392, 'Train/mean recall': 0.9950012564659119, 'Train/mean hd95_metric': 1.0667738914489746} +Epoch [1471/4000] Validation [1/4] Loss: 0.23750 focal_loss 0.16273 dice_loss 0.07477 +Epoch [1471/4000] Validation [2/4] Loss: 0.45546 focal_loss 0.24325 dice_loss 0.21221 +Epoch [1471/4000] Validation [3/4] Loss: 0.17084 focal_loss 0.10516 dice_loss 0.06568 +Epoch [1471/4000] Validation [4/4] Loss: 0.32048 focal_loss 0.18182 dice_loss 0.13866 +Epoch [1471/4000] Validation metric {'Val/mean dice_metric': 0.9699064493179321, 'Val/mean miou_metric': 0.9520845413208008, 'Val/mean f1': 0.9735661745071411, 'Val/mean precision': 0.9724735617637634, 'Val/mean recall': 0.9746612906455994, 'Val/mean hd95_metric': 5.5325493812561035} +Cheakpoint... +Epoch [1471/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699064493179321, 'Val/mean miou_metric': 0.9520845413208008, 'Val/mean f1': 0.9735661745071411, 'Val/mean precision': 0.9724735617637634, 'Val/mean recall': 0.9746612906455994, 'Val/mean hd95_metric': 5.5325493812561035} +Epoch [1472/4000] Training [1/16] Loss: 0.01071 +Epoch [1472/4000] Training [2/16] Loss: 0.00815 +Epoch [1472/4000] Training [3/16] Loss: 0.01194 +Epoch [1472/4000] Training [4/16] Loss: 0.00830 +Epoch [1472/4000] Training [5/16] Loss: 0.00704 +Epoch [1472/4000] Training [6/16] Loss: 0.00934 +Epoch [1472/4000] Training [7/16] Loss: 0.01228 +Epoch [1472/4000] Training [8/16] Loss: 0.00656 +Epoch [1472/4000] Training [9/16] Loss: 0.00747 +Epoch [1472/4000] Training [10/16] Loss: 0.00971 +Epoch [1472/4000] Training [11/16] Loss: 0.00826 +Epoch [1472/4000] Training [12/16] Loss: 0.00905 +Epoch [1472/4000] Training [13/16] Loss: 0.00704 +Epoch [1472/4000] Training [14/16] Loss: 0.00852 +Epoch [1472/4000] Training [15/16] Loss: 0.00725 +Epoch [1472/4000] Training [16/16] Loss: 0.00961 +Epoch [1472/4000] Training metric {'Train/mean dice_metric': 0.9938998222351074, 'Train/mean miou_metric': 0.9876664280891418, 'Train/mean f1': 0.9902898073196411, 'Train/mean precision': 0.9858480095863342, 'Train/mean recall': 0.9947718977928162, 'Train/mean hd95_metric': 1.1458784341812134} +Epoch [1472/4000] Validation [1/4] Loss: 0.27549 focal_loss 0.19686 dice_loss 0.07864 +Epoch [1472/4000] Validation [2/4] Loss: 0.46847 focal_loss 0.29710 dice_loss 0.17136 +Epoch [1472/4000] Validation [3/4] Loss: 0.17353 focal_loss 0.10782 dice_loss 0.06571 +Epoch [1472/4000] Validation [4/4] Loss: 0.28792 focal_loss 0.17195 dice_loss 0.11597 +Epoch [1472/4000] Validation metric {'Val/mean dice_metric': 0.9680557250976562, 'Val/mean miou_metric': 0.9496569633483887, 'Val/mean f1': 0.9711514711380005, 'Val/mean precision': 0.972906231880188, 'Val/mean recall': 0.9694029688835144, 'Val/mean hd95_metric': 5.473732948303223} +Cheakpoint... +Epoch [1472/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680557250976562, 'Val/mean miou_metric': 0.9496569633483887, 'Val/mean f1': 0.9711514711380005, 'Val/mean precision': 0.972906231880188, 'Val/mean recall': 0.9694029688835144, 'Val/mean hd95_metric': 5.473732948303223} +Epoch [1473/4000] Training [1/16] Loss: 0.00685 +Epoch [1473/4000] Training [2/16] Loss: 0.01007 +Epoch [1473/4000] Training [3/16] Loss: 0.01320 +Epoch [1473/4000] Training [4/16] Loss: 0.00623 +Epoch [1473/4000] Training [5/16] Loss: 0.00868 +Epoch [1473/4000] Training [6/16] Loss: 0.00941 +Epoch [1473/4000] Training [7/16] Loss: 0.00865 +Epoch [1473/4000] Training [8/16] Loss: 0.01112 +Epoch [1473/4000] Training [9/16] Loss: 0.00708 +Epoch [1473/4000] Training [10/16] Loss: 0.01018 +Epoch [1473/4000] Training [11/16] Loss: 0.00781 +Epoch [1473/4000] Training [12/16] Loss: 0.00849 +Epoch [1473/4000] Training [13/16] Loss: 0.00704 +Epoch [1473/4000] Training [14/16] Loss: 0.01042 +Epoch [1473/4000] Training [15/16] Loss: 0.01402 +Epoch [1473/4000] Training [16/16] Loss: 0.00820 +Epoch [1473/4000] Training metric {'Train/mean dice_metric': 0.993972897529602, 'Train/mean miou_metric': 0.9877221584320068, 'Train/mean f1': 0.9884860515594482, 'Train/mean precision': 0.9827249050140381, 'Train/mean recall': 0.9943150877952576, 'Train/mean hd95_metric': 1.2105352878570557} +Epoch [1473/4000] Validation [1/4] Loss: 0.24128 focal_loss 0.17417 dice_loss 0.06710 +Epoch [1473/4000] Validation [2/4] Loss: 0.34868 focal_loss 0.18482 dice_loss 0.16385 +Epoch [1473/4000] Validation [3/4] Loss: 0.16311 focal_loss 0.09995 dice_loss 0.06315 +Epoch [1473/4000] Validation [4/4] Loss: 0.32736 focal_loss 0.20428 dice_loss 0.12309 +Epoch [1473/4000] Validation metric {'Val/mean dice_metric': 0.9708912968635559, 'Val/mean miou_metric': 0.952627956867218, 'Val/mean f1': 0.9714480042457581, 'Val/mean precision': 0.9672225117683411, 'Val/mean recall': 0.9757104516029358, 'Val/mean hd95_metric': 6.1272077560424805} +Cheakpoint... +Epoch [1473/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708912968635559, 'Val/mean miou_metric': 0.952627956867218, 'Val/mean f1': 0.9714480042457581, 'Val/mean precision': 0.9672225117683411, 'Val/mean recall': 0.9757104516029358, 'Val/mean hd95_metric': 6.1272077560424805} +Epoch [1474/4000] Training [1/16] Loss: 0.00911 +Epoch [1474/4000] Training [2/16] Loss: 0.00662 +Epoch [1474/4000] Training [3/16] Loss: 0.00738 +Epoch [1474/4000] Training [4/16] Loss: 0.00785 +Epoch [1474/4000] Training [5/16] Loss: 0.01212 +Epoch [1474/4000] Training [6/16] Loss: 0.00994 +Epoch [1474/4000] Training [7/16] Loss: 0.00723 +Epoch [1474/4000] Training [8/16] Loss: 0.00637 +Epoch [1474/4000] Training [9/16] Loss: 0.00609 +Epoch [1474/4000] Training [10/16] Loss: 0.01271 +Epoch [1474/4000] Training [11/16] Loss: 0.00930 +Epoch [1474/4000] Training [12/16] Loss: 0.00854 +Epoch [1474/4000] Training [13/16] Loss: 0.00924 +Epoch [1474/4000] Training [14/16] Loss: 0.00935 +Epoch [1474/4000] Training [15/16] Loss: 0.01641 +Epoch [1474/4000] Training [16/16] Loss: 0.00805 +Epoch [1474/4000] Training metric {'Train/mean dice_metric': 0.9940187931060791, 'Train/mean miou_metric': 0.9878436923027039, 'Train/mean f1': 0.9895418882369995, 'Train/mean precision': 0.9844675660133362, 'Train/mean recall': 0.9946687817573547, 'Train/mean hd95_metric': 1.0589840412139893} +Epoch [1474/4000] Validation [1/4] Loss: 0.23089 focal_loss 0.16758 dice_loss 0.06331 +Epoch [1474/4000] Validation [2/4] Loss: 0.32819 focal_loss 0.19604 dice_loss 0.13215 +Epoch [1474/4000] Validation [3/4] Loss: 0.15890 focal_loss 0.09237 dice_loss 0.06653 +Epoch [1474/4000] Validation [4/4] Loss: 0.24601 focal_loss 0.13282 dice_loss 0.11319 +Epoch [1474/4000] Validation metric {'Val/mean dice_metric': 0.9709679484367371, 'Val/mean miou_metric': 0.9526914358139038, 'Val/mean f1': 0.9736451506614685, 'Val/mean precision': 0.9698861837387085, 'Val/mean recall': 0.9774335026741028, 'Val/mean hd95_metric': 5.296959400177002} +Cheakpoint... +Epoch [1474/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709679484367371, 'Val/mean miou_metric': 0.9526914358139038, 'Val/mean f1': 0.9736451506614685, 'Val/mean precision': 0.9698861837387085, 'Val/mean recall': 0.9774335026741028, 'Val/mean hd95_metric': 5.296959400177002} +Epoch [1475/4000] Training [1/16] Loss: 0.00699 +Epoch [1475/4000] Training [2/16] Loss: 0.01354 +Epoch [1475/4000] Training [3/16] Loss: 0.00587 +Epoch [1475/4000] Training [4/16] Loss: 0.00664 +Epoch [1475/4000] Training [5/16] Loss: 0.00921 +Epoch [1475/4000] Training [6/16] Loss: 0.01003 +Epoch [1475/4000] Training [7/16] Loss: 0.00988 +Epoch [1475/4000] Training [8/16] Loss: 0.00742 +Epoch [1475/4000] Training [9/16] Loss: 0.00703 +Epoch [1475/4000] Training [10/16] Loss: 0.01653 +Epoch [1475/4000] Training [11/16] Loss: 0.01063 +Epoch [1475/4000] Training [12/16] Loss: 0.00619 +Epoch [1475/4000] Training [13/16] Loss: 0.00890 +Epoch [1475/4000] Training [14/16] Loss: 0.00886 +Epoch [1475/4000] Training [15/16] Loss: 0.00776 +Epoch [1475/4000] Training [16/16] Loss: 0.00879 +Epoch [1475/4000] Training metric {'Train/mean dice_metric': 0.9936764240264893, 'Train/mean miou_metric': 0.9872161149978638, 'Train/mean f1': 0.9899025559425354, 'Train/mean precision': 0.9853314161300659, 'Train/mean recall': 0.9945162534713745, 'Train/mean hd95_metric': 1.2325537204742432} +Epoch [1475/4000] Validation [1/4] Loss: 0.20428 focal_loss 0.14817 dice_loss 0.05611 +Epoch [1475/4000] Validation [2/4] Loss: 0.28401 focal_loss 0.14896 dice_loss 0.13505 +Epoch [1475/4000] Validation [3/4] Loss: 0.18164 focal_loss 0.10542 dice_loss 0.07622 +Epoch [1475/4000] Validation [4/4] Loss: 0.28854 focal_loss 0.16869 dice_loss 0.11985 +Epoch [1475/4000] Validation metric {'Val/mean dice_metric': 0.969093918800354, 'Val/mean miou_metric': 0.9511257410049438, 'Val/mean f1': 0.9707114100456238, 'Val/mean precision': 0.9617908596992493, 'Val/mean recall': 0.9797987937927246, 'Val/mean hd95_metric': 6.6382904052734375} +Cheakpoint... +Epoch [1475/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969093918800354, 'Val/mean miou_metric': 0.9511257410049438, 'Val/mean f1': 0.9707114100456238, 'Val/mean precision': 0.9617908596992493, 'Val/mean recall': 0.9797987937927246, 'Val/mean hd95_metric': 6.6382904052734375} +Epoch [1476/4000] Training [1/16] Loss: 0.00702 +Epoch [1476/4000] Training [2/16] Loss: 0.01355 +Epoch [1476/4000] Training [3/16] Loss: 0.00778 +Epoch [1476/4000] Training [4/16] Loss: 0.01065 +Epoch [1476/4000] Training [5/16] Loss: 0.01242 +Epoch [1476/4000] Training [6/16] Loss: 0.01017 +Epoch [1476/4000] Training [7/16] Loss: 0.00741 +Epoch [1476/4000] Training [8/16] Loss: 0.00890 +Epoch [1476/4000] Training [9/16] Loss: 0.01307 +Epoch [1476/4000] Training [10/16] Loss: 0.00899 +Epoch [1476/4000] Training [11/16] Loss: 0.00793 +Epoch [1476/4000] Training [12/16] Loss: 0.01531 +Epoch [1476/4000] Training [13/16] Loss: 0.00749 +Epoch [1476/4000] Training [14/16] Loss: 0.01145 +Epoch [1476/4000] Training [15/16] Loss: 0.00681 +Epoch [1476/4000] Training [16/16] Loss: 0.01836 +Epoch [1476/4000] Training metric {'Train/mean dice_metric': 0.9932443499565125, 'Train/mean miou_metric': 0.9863705039024353, 'Train/mean f1': 0.9896818399429321, 'Train/mean precision': 0.9851973652839661, 'Train/mean recall': 0.9942073822021484, 'Train/mean hd95_metric': 1.714437484741211} +Epoch [1476/4000] Validation [1/4] Loss: 0.54713 focal_loss 0.44143 dice_loss 0.10569 +Epoch [1476/4000] Validation [2/4] Loss: 0.30106 focal_loss 0.17366 dice_loss 0.12740 +Epoch [1476/4000] Validation [3/4] Loss: 0.20913 focal_loss 0.13534 dice_loss 0.07379 +Epoch [1476/4000] Validation [4/4] Loss: 0.46964 focal_loss 0.30981 dice_loss 0.15982 +Epoch [1476/4000] Validation metric {'Val/mean dice_metric': 0.968224823474884, 'Val/mean miou_metric': 0.9481619000434875, 'Val/mean f1': 0.9684285521507263, 'Val/mean precision': 0.9713661670684814, 'Val/mean recall': 0.9655086994171143, 'Val/mean hd95_metric': 6.447029113769531} +Cheakpoint... +Epoch [1476/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968224823474884, 'Val/mean miou_metric': 0.9481619000434875, 'Val/mean f1': 0.9684285521507263, 'Val/mean precision': 0.9713661670684814, 'Val/mean recall': 0.9655086994171143, 'Val/mean hd95_metric': 6.447029113769531} +Epoch [1477/4000] Training [1/16] Loss: 0.00940 +Epoch [1477/4000] Training [2/16] Loss: 0.00931 +Epoch [1477/4000] Training [3/16] Loss: 0.00835 +Epoch [1477/4000] Training [4/16] Loss: 0.01386 +Epoch [1477/4000] Training [5/16] Loss: 0.01011 +Epoch [1477/4000] Training [6/16] Loss: 0.00731 +Epoch [1477/4000] Training [7/16] Loss: 0.00754 +Epoch [1477/4000] Training [8/16] Loss: 0.01062 +Epoch [1477/4000] Training [9/16] Loss: 0.00805 +Epoch [1477/4000] Training [10/16] Loss: 0.01016 +Epoch [1477/4000] Training [11/16] Loss: 0.00827 +Epoch [1477/4000] Training [12/16] Loss: 0.00949 +Epoch [1477/4000] Training [13/16] Loss: 0.00927 +Epoch [1477/4000] Training [14/16] Loss: 0.00736 +Epoch [1477/4000] Training [15/16] Loss: 0.01097 +Epoch [1477/4000] Training [16/16] Loss: 0.00837 +Epoch [1477/4000] Training metric {'Train/mean dice_metric': 0.9937044382095337, 'Train/mean miou_metric': 0.9872504472732544, 'Train/mean f1': 0.9896516799926758, 'Train/mean precision': 0.9850026369094849, 'Train/mean recall': 0.9943447709083557, 'Train/mean hd95_metric': 1.1715221405029297} +Epoch [1477/4000] Validation [1/4] Loss: 0.19547 focal_loss 0.13403 dice_loss 0.06144 +Epoch [1477/4000] Validation [2/4] Loss: 0.35057 focal_loss 0.19170 dice_loss 0.15887 +Epoch [1477/4000] Validation [3/4] Loss: 0.22274 focal_loss 0.13773 dice_loss 0.08501 +Epoch [1477/4000] Validation [4/4] Loss: 0.26289 focal_loss 0.14156 dice_loss 0.12133 +Epoch [1477/4000] Validation metric {'Val/mean dice_metric': 0.9690969586372375, 'Val/mean miou_metric': 0.9500217437744141, 'Val/mean f1': 0.9719233512878418, 'Val/mean precision': 0.969310462474823, 'Val/mean recall': 0.9745503067970276, 'Val/mean hd95_metric': 5.841852188110352} +Cheakpoint... +Epoch [1477/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690969586372375, 'Val/mean miou_metric': 0.9500217437744141, 'Val/mean f1': 0.9719233512878418, 'Val/mean precision': 0.969310462474823, 'Val/mean recall': 0.9745503067970276, 'Val/mean hd95_metric': 5.841852188110352} +Epoch [1478/4000] Training [1/16] Loss: 0.00709 +Epoch [1478/4000] Training [2/16] Loss: 0.01351 +Epoch [1478/4000] Training [3/16] Loss: 0.01396 +Epoch [1478/4000] Training [4/16] Loss: 0.00877 +Epoch [1478/4000] Training [5/16] Loss: 0.00756 +Epoch [1478/4000] Training [6/16] Loss: 0.00864 +Epoch [1478/4000] Training [7/16] Loss: 0.01018 +Epoch [1478/4000] Training [8/16] Loss: 0.01143 +Epoch [1478/4000] Training [9/16] Loss: 0.00858 +Epoch [1478/4000] Training [10/16] Loss: 0.00853 +Epoch [1478/4000] Training [11/16] Loss: 0.00912 +Epoch [1478/4000] Training [12/16] Loss: 0.00831 +Epoch [1478/4000] Training [13/16] Loss: 0.00699 +Epoch [1478/4000] Training [14/16] Loss: 0.00625 +Epoch [1478/4000] Training [15/16] Loss: 0.00668 +Epoch [1478/4000] Training [16/16] Loss: 0.00822 +Epoch [1478/4000] Training metric {'Train/mean dice_metric': 0.9940817952156067, 'Train/mean miou_metric': 0.9879595041275024, 'Train/mean f1': 0.9897493124008179, 'Train/mean precision': 0.9848921895027161, 'Train/mean recall': 0.994654655456543, 'Train/mean hd95_metric': 1.0644065141677856} +Epoch [1478/4000] Validation [1/4] Loss: 0.24244 focal_loss 0.17596 dice_loss 0.06648 +Epoch [1478/4000] Validation [2/4] Loss: 0.29088 focal_loss 0.17181 dice_loss 0.11907 +Epoch [1478/4000] Validation [3/4] Loss: 0.18114 focal_loss 0.11267 dice_loss 0.06847 +Epoch [1478/4000] Validation [4/4] Loss: 0.27994 focal_loss 0.15245 dice_loss 0.12749 +Epoch [1478/4000] Validation metric {'Val/mean dice_metric': 0.9717071652412415, 'Val/mean miou_metric': 0.9535459280014038, 'Val/mean f1': 0.9737147688865662, 'Val/mean precision': 0.9692252278327942, 'Val/mean recall': 0.9782460927963257, 'Val/mean hd95_metric': 5.289673328399658} +Cheakpoint... +Epoch [1478/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717071652412415, 'Val/mean miou_metric': 0.9535459280014038, 'Val/mean f1': 0.9737147688865662, 'Val/mean precision': 0.9692252278327942, 'Val/mean recall': 0.9782460927963257, 'Val/mean hd95_metric': 5.289673328399658} +Epoch [1479/4000] Training [1/16] Loss: 0.00679 +Epoch [1479/4000] Training [2/16] Loss: 0.01072 +Epoch [1479/4000] Training [3/16] Loss: 0.01000 +Epoch [1479/4000] Training [4/16] Loss: 0.00702 +Epoch [1479/4000] Training [5/16] Loss: 0.00841 +Epoch [1479/4000] Training [6/16] Loss: 0.01285 +Epoch [1479/4000] Training [7/16] Loss: 0.00835 +Epoch [1479/4000] Training [8/16] Loss: 0.00874 +Epoch [1479/4000] Training [9/16] Loss: 0.00807 +Epoch [1479/4000] Training [10/16] Loss: 0.00786 +Epoch [1479/4000] Training [11/16] Loss: 0.00915 +Epoch [1479/4000] Training [12/16] Loss: 0.00988 +Epoch [1479/4000] Training [13/16] Loss: 0.00643 +Epoch [1479/4000] Training [14/16] Loss: 0.00897 +Epoch [1479/4000] Training [15/16] Loss: 0.01034 +Epoch [1479/4000] Training [16/16] Loss: 0.00876 +Epoch [1479/4000] Training metric {'Train/mean dice_metric': 0.9942798614501953, 'Train/mean miou_metric': 0.9883609414100647, 'Train/mean f1': 0.9902947545051575, 'Train/mean precision': 0.9856519103050232, 'Train/mean recall': 0.9949814677238464, 'Train/mean hd95_metric': 1.0464389324188232} +Epoch [1479/4000] Validation [1/4] Loss: 0.21508 focal_loss 0.15475 dice_loss 0.06032 +Epoch [1479/4000] Validation [2/4] Loss: 0.32419 focal_loss 0.18389 dice_loss 0.14030 +Epoch [1479/4000] Validation [3/4] Loss: 0.17546 focal_loss 0.11388 dice_loss 0.06158 +Epoch [1479/4000] Validation [4/4] Loss: 0.22999 focal_loss 0.12149 dice_loss 0.10850 +Epoch [1479/4000] Validation metric {'Val/mean dice_metric': 0.9739581942558289, 'Val/mean miou_metric': 0.9562389254570007, 'Val/mean f1': 0.9751901626586914, 'Val/mean precision': 0.971695065498352, 'Val/mean recall': 0.9787103533744812, 'Val/mean hd95_metric': 5.37482213973999} +Cheakpoint... +Epoch [1479/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739581942558289, 'Val/mean miou_metric': 0.9562389254570007, 'Val/mean f1': 0.9751901626586914, 'Val/mean precision': 0.971695065498352, 'Val/mean recall': 0.9787103533744812, 'Val/mean hd95_metric': 5.37482213973999} +Epoch [1480/4000] Training [1/16] Loss: 0.00737 +Epoch [1480/4000] Training [2/16] Loss: 0.00879 +Epoch [1480/4000] Training [3/16] Loss: 0.00760 +Epoch [1480/4000] Training [4/16] Loss: 0.00759 +Epoch [1480/4000] Training [5/16] Loss: 0.00719 +Epoch [1480/4000] Training [6/16] Loss: 0.00994 +Epoch [1480/4000] Training [7/16] Loss: 0.00762 +Epoch [1480/4000] Training [8/16] Loss: 0.00786 +Epoch [1480/4000] Training [9/16] Loss: 0.00759 +Epoch [1480/4000] Training [10/16] Loss: 0.00723 +Epoch [1480/4000] Training [11/16] Loss: 0.00833 +Epoch [1480/4000] Training [12/16] Loss: 0.00797 +Epoch [1480/4000] Training [13/16] Loss: 0.01227 +Epoch [1480/4000] Training [14/16] Loss: 0.00904 +Epoch [1480/4000] Training [15/16] Loss: 0.01186 +Epoch [1480/4000] Training [16/16] Loss: 0.00882 +Epoch [1480/4000] Training metric {'Train/mean dice_metric': 0.994269847869873, 'Train/mean miou_metric': 0.9883571863174438, 'Train/mean f1': 0.9902263879776001, 'Train/mean precision': 0.9855296611785889, 'Train/mean recall': 0.9949679970741272, 'Train/mean hd95_metric': 1.3990662097930908} +Epoch [1480/4000] Validation [1/4] Loss: 0.18918 focal_loss 0.12882 dice_loss 0.06036 +Epoch [1480/4000] Validation [2/4] Loss: 0.33440 focal_loss 0.19545 dice_loss 0.13895 +Epoch [1480/4000] Validation [3/4] Loss: 0.27006 focal_loss 0.16719 dice_loss 0.10287 +Epoch [1480/4000] Validation [4/4] Loss: 0.31955 focal_loss 0.19502 dice_loss 0.12453 +Epoch [1480/4000] Validation metric {'Val/mean dice_metric': 0.9722853899002075, 'Val/mean miou_metric': 0.9541494250297546, 'Val/mean f1': 0.9733964800834656, 'Val/mean precision': 0.9675908088684082, 'Val/mean recall': 0.9792723059654236, 'Val/mean hd95_metric': 5.96703577041626} +Cheakpoint... +Epoch [1480/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722853899002075, 'Val/mean miou_metric': 0.9541494250297546, 'Val/mean f1': 0.9733964800834656, 'Val/mean precision': 0.9675908088684082, 'Val/mean recall': 0.9792723059654236, 'Val/mean hd95_metric': 5.96703577041626} +Epoch [1481/4000] Training [1/16] Loss: 0.00642 +Epoch [1481/4000] Training [2/16] Loss: 0.00792 +Epoch [1481/4000] Training [3/16] Loss: 0.00984 +Epoch [1481/4000] Training [4/16] Loss: 0.00997 +Epoch [1481/4000] Training [5/16] Loss: 0.00655 +Epoch [1481/4000] Training [6/16] Loss: 0.00724 +Epoch [1481/4000] Training [7/16] Loss: 0.01051 +Epoch [1481/4000] Training [8/16] Loss: 0.00786 +Epoch [1481/4000] Training [9/16] Loss: 0.00855 +Epoch [1481/4000] Training [10/16] Loss: 0.00775 +Epoch [1481/4000] Training [11/16] Loss: 0.01394 +Epoch [1481/4000] Training [12/16] Loss: 0.00807 +Epoch [1481/4000] Training [13/16] Loss: 0.00771 +Epoch [1481/4000] Training [14/16] Loss: 0.01014 +Epoch [1481/4000] Training [15/16] Loss: 0.00706 +Epoch [1481/4000] Training [16/16] Loss: 0.00919 +Epoch [1481/4000] Training metric {'Train/mean dice_metric': 0.9941415786743164, 'Train/mean miou_metric': 0.9880859851837158, 'Train/mean f1': 0.9900999665260315, 'Train/mean precision': 0.9853508472442627, 'Train/mean recall': 0.9948950409889221, 'Train/mean hd95_metric': 1.0547291040420532} +Epoch [1481/4000] Validation [1/4] Loss: 0.23454 focal_loss 0.16014 dice_loss 0.07440 +Epoch [1481/4000] Validation [2/4] Loss: 0.29663 focal_loss 0.17741 dice_loss 0.11922 +Epoch [1481/4000] Validation [3/4] Loss: 0.13682 focal_loss 0.08021 dice_loss 0.05660 +Epoch [1481/4000] Validation [4/4] Loss: 0.30427 focal_loss 0.17375 dice_loss 0.13052 +Epoch [1481/4000] Validation metric {'Val/mean dice_metric': 0.9712950587272644, 'Val/mean miou_metric': 0.9532250165939331, 'Val/mean f1': 0.9736489653587341, 'Val/mean precision': 0.9701164364814758, 'Val/mean recall': 0.977207362651825, 'Val/mean hd95_metric': 5.135911464691162} +Cheakpoint... +Epoch [1481/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712950587272644, 'Val/mean miou_metric': 0.9532250165939331, 'Val/mean f1': 0.9736489653587341, 'Val/mean precision': 0.9701164364814758, 'Val/mean recall': 0.977207362651825, 'Val/mean hd95_metric': 5.135911464691162} +Epoch [1482/4000] Training [1/16] Loss: 0.00734 +Epoch [1482/4000] Training [2/16] Loss: 0.00700 +Epoch [1482/4000] Training [3/16] Loss: 0.00800 +Epoch [1482/4000] Training [4/16] Loss: 0.00949 +Epoch [1482/4000] Training [5/16] Loss: 0.00782 +Epoch [1482/4000] Training [6/16] Loss: 0.00626 +Epoch [1482/4000] Training [7/16] Loss: 0.00932 +Epoch [1482/4000] Training [8/16] Loss: 0.00990 +Epoch [1482/4000] Training [9/16] Loss: 0.01050 +Epoch [1482/4000] Training [10/16] Loss: 0.01104 +Epoch [1482/4000] Training [11/16] Loss: 0.00946 +Epoch [1482/4000] Training [12/16] Loss: 0.00732 +Epoch [1482/4000] Training [13/16] Loss: 0.00735 +Epoch [1482/4000] Training [14/16] Loss: 0.00643 +Epoch [1482/4000] Training [15/16] Loss: 0.01075 +Epoch [1482/4000] Training [16/16] Loss: 0.01123 +Epoch [1482/4000] Training metric {'Train/mean dice_metric': 0.9932543635368347, 'Train/mean miou_metric': 0.986598014831543, 'Train/mean f1': 0.9900240302085876, 'Train/mean precision': 0.985819935798645, 'Train/mean recall': 0.9942641854286194, 'Train/mean hd95_metric': 1.1693713665008545} +Epoch [1482/4000] Validation [1/4] Loss: 0.18545 focal_loss 0.12690 dice_loss 0.05855 +Epoch [1482/4000] Validation [2/4] Loss: 0.34047 focal_loss 0.22316 dice_loss 0.11731 +Epoch [1482/4000] Validation [3/4] Loss: 0.19505 focal_loss 0.12332 dice_loss 0.07173 +Epoch [1482/4000] Validation [4/4] Loss: 0.38315 focal_loss 0.23439 dice_loss 0.14876 +Epoch [1482/4000] Validation metric {'Val/mean dice_metric': 0.971075713634491, 'Val/mean miou_metric': 0.9522596597671509, 'Val/mean f1': 0.9736781716346741, 'Val/mean precision': 0.9687243700027466, 'Val/mean recall': 0.9786828756332397, 'Val/mean hd95_metric': 5.375262260437012} +Cheakpoint... +Epoch [1482/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971075713634491, 'Val/mean miou_metric': 0.9522596597671509, 'Val/mean f1': 0.9736781716346741, 'Val/mean precision': 0.9687243700027466, 'Val/mean recall': 0.9786828756332397, 'Val/mean hd95_metric': 5.375262260437012} +Epoch [1483/4000] Training [1/16] Loss: 0.01046 +Epoch [1483/4000] Training [2/16] Loss: 0.00849 +Epoch [1483/4000] Training [3/16] Loss: 0.00875 +Epoch [1483/4000] Training [4/16] Loss: 0.00750 +Epoch [1483/4000] Training [5/16] Loss: 0.00989 +Epoch [1483/4000] Training [6/16] Loss: 0.00803 +Epoch [1483/4000] Training [7/16] Loss: 0.00856 +Epoch [1483/4000] Training [8/16] Loss: 0.00762 +Epoch [1483/4000] Training [9/16] Loss: 0.00877 +Epoch [1483/4000] Training [10/16] Loss: 0.00769 +Epoch [1483/4000] Training [11/16] Loss: 0.00957 +Epoch [1483/4000] Training [12/16] Loss: 0.01201 +Epoch [1483/4000] Training [13/16] Loss: 0.00963 +Epoch [1483/4000] Training [14/16] Loss: 0.00859 +Epoch [1483/4000] Training [15/16] Loss: 0.01066 +Epoch [1483/4000] Training [16/16] Loss: 0.00918 +Epoch [1483/4000] Training metric {'Train/mean dice_metric': 0.9939034581184387, 'Train/mean miou_metric': 0.9876195788383484, 'Train/mean f1': 0.9898642897605896, 'Train/mean precision': 0.9850359559059143, 'Train/mean recall': 0.9947402477264404, 'Train/mean hd95_metric': 1.477942943572998} +Epoch [1483/4000] Validation [1/4] Loss: 0.22489 focal_loss 0.16065 dice_loss 0.06424 +Epoch [1483/4000] Validation [2/4] Loss: 0.49063 focal_loss 0.31338 dice_loss 0.17726 +Epoch [1483/4000] Validation [3/4] Loss: 0.29452 focal_loss 0.19872 dice_loss 0.09580 +Epoch [1483/4000] Validation [4/4] Loss: 0.37073 focal_loss 0.22713 dice_loss 0.14361 +Epoch [1483/4000] Validation metric {'Val/mean dice_metric': 0.9679418802261353, 'Val/mean miou_metric': 0.9491678476333618, 'Val/mean f1': 0.9697022438049316, 'Val/mean precision': 0.9608135223388672, 'Val/mean recall': 0.9787569642066956, 'Val/mean hd95_metric': 8.268488883972168} +Cheakpoint... +Epoch [1483/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679418802261353, 'Val/mean miou_metric': 0.9491678476333618, 'Val/mean f1': 0.9697022438049316, 'Val/mean precision': 0.9608135223388672, 'Val/mean recall': 0.9787569642066956, 'Val/mean hd95_metric': 8.268488883972168} +Epoch [1484/4000] Training [1/16] Loss: 0.00792 +Epoch [1484/4000] Training [2/16] Loss: 0.00910 +Epoch [1484/4000] Training [3/16] Loss: 0.00641 +Epoch [1484/4000] Training [4/16] Loss: 0.01007 +Epoch [1484/4000] Training [5/16] Loss: 0.00777 +Epoch [1484/4000] Training [6/16] Loss: 0.00884 +Epoch [1484/4000] Training [7/16] Loss: 0.01035 +Epoch [1484/4000] Training [8/16] Loss: 0.00678 +Epoch [1484/4000] Training [9/16] Loss: 0.01129 +Epoch [1484/4000] Training [10/16] Loss: 0.00964 +Epoch [1484/4000] Training [11/16] Loss: 0.00991 +Epoch [1484/4000] Training [12/16] Loss: 0.00821 +Epoch [1484/4000] Training [13/16] Loss: 0.01048 +Epoch [1484/4000] Training [14/16] Loss: 0.00812 +Epoch [1484/4000] Training [15/16] Loss: 0.01007 +Epoch [1484/4000] Training [16/16] Loss: 0.00719 +Epoch [1484/4000] Training metric {'Train/mean dice_metric': 0.9935621023178101, 'Train/mean miou_metric': 0.9869908690452576, 'Train/mean f1': 0.9898694157600403, 'Train/mean precision': 0.985524594783783, 'Train/mean recall': 0.9942526817321777, 'Train/mean hd95_metric': 1.3338823318481445} +Epoch [1484/4000] Validation [1/4] Loss: 0.19087 focal_loss 0.13085 dice_loss 0.06002 +Epoch [1484/4000] Validation [2/4] Loss: 0.85208 focal_loss 0.56045 dice_loss 0.29163 +Epoch [1484/4000] Validation [3/4] Loss: 0.16638 focal_loss 0.10535 dice_loss 0.06103 +Epoch [1484/4000] Validation [4/4] Loss: 0.35755 focal_loss 0.21670 dice_loss 0.14085 +Epoch [1484/4000] Validation metric {'Val/mean dice_metric': 0.9682450294494629, 'Val/mean miou_metric': 0.9502342343330383, 'Val/mean f1': 0.9706265330314636, 'Val/mean precision': 0.9645136594772339, 'Val/mean recall': 0.9768173098564148, 'Val/mean hd95_metric': 6.205811977386475} +Cheakpoint... +Epoch [1484/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9682450294494629, 'Val/mean miou_metric': 0.9502342343330383, 'Val/mean f1': 0.9706265330314636, 'Val/mean precision': 0.9645136594772339, 'Val/mean recall': 0.9768173098564148, 'Val/mean hd95_metric': 6.205811977386475} +Epoch [1485/4000] Training [1/16] Loss: 0.00790 +Epoch [1485/4000] Training [2/16] Loss: 0.00628 +Epoch [1485/4000] Training [3/16] Loss: 0.01112 +Epoch [1485/4000] Training [4/16] Loss: 0.01045 +Epoch [1485/4000] Training [5/16] Loss: 0.00962 +Epoch [1485/4000] Training [6/16] Loss: 0.00718 +Epoch [1485/4000] Training [7/16] Loss: 0.01031 +Epoch [1485/4000] Training [8/16] Loss: 0.00825 +Epoch [1485/4000] Training [9/16] Loss: 0.00776 +Epoch [1485/4000] Training [10/16] Loss: 0.00846 +Epoch [1485/4000] Training [11/16] Loss: 0.00834 +Epoch [1485/4000] Training [12/16] Loss: 0.00797 +Epoch [1485/4000] Training [13/16] Loss: 0.00988 +Epoch [1485/4000] Training [14/16] Loss: 0.00991 +Epoch [1485/4000] Training [15/16] Loss: 0.00735 +Epoch [1485/4000] Training [16/16] Loss: 0.00773 +Epoch [1485/4000] Training metric {'Train/mean dice_metric': 0.9941135048866272, 'Train/mean miou_metric': 0.9880515336990356, 'Train/mean f1': 0.9902806878089905, 'Train/mean precision': 0.9856247901916504, 'Train/mean recall': 0.9949807524681091, 'Train/mean hd95_metric': 1.0448076725006104} +Epoch [1485/4000] Validation [1/4] Loss: 0.22657 focal_loss 0.16487 dice_loss 0.06170 +Epoch [1485/4000] Validation [2/4] Loss: 0.37332 focal_loss 0.23437 dice_loss 0.13895 +Epoch [1485/4000] Validation [3/4] Loss: 0.27347 focal_loss 0.17274 dice_loss 0.10073 +Epoch [1485/4000] Validation [4/4] Loss: 0.22788 focal_loss 0.12802 dice_loss 0.09986 +Epoch [1485/4000] Validation metric {'Val/mean dice_metric': 0.9716067314147949, 'Val/mean miou_metric': 0.9537006616592407, 'Val/mean f1': 0.973327100276947, 'Val/mean precision': 0.9681109189987183, 'Val/mean recall': 0.9785999059677124, 'Val/mean hd95_metric': 5.353963375091553} +Cheakpoint... +Epoch [1485/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716067314147949, 'Val/mean miou_metric': 0.9537006616592407, 'Val/mean f1': 0.973327100276947, 'Val/mean precision': 0.9681109189987183, 'Val/mean recall': 0.9785999059677124, 'Val/mean hd95_metric': 5.353963375091553} +Epoch [1486/4000] Training [1/16] Loss: 0.01502 +Epoch [1486/4000] Training [2/16] Loss: 0.00820 +Epoch [1486/4000] Training [3/16] Loss: 0.01153 +Epoch [1486/4000] Training [4/16] Loss: 0.00704 +Epoch [1486/4000] Training [5/16] Loss: 0.00816 +Epoch [1486/4000] Training [6/16] Loss: 0.00863 +Epoch [1486/4000] Training [7/16] Loss: 0.00792 +Epoch [1486/4000] Training [8/16] Loss: 0.00996 +Epoch [1486/4000] Training [9/16] Loss: 0.00799 +Epoch [1486/4000] Training [10/16] Loss: 0.00887 +Epoch [1486/4000] Training [11/16] Loss: 0.01043 +Epoch [1486/4000] Training [12/16] Loss: 0.00913 +Epoch [1486/4000] Training [13/16] Loss: 0.00706 +Epoch [1486/4000] Training [14/16] Loss: 0.00919 +Epoch [1486/4000] Training [15/16] Loss: 0.00825 +Epoch [1486/4000] Training [16/16] Loss: 0.00891 +Epoch [1486/4000] Training metric {'Train/mean dice_metric': 0.9931528568267822, 'Train/mean miou_metric': 0.9863681793212891, 'Train/mean f1': 0.9887565970420837, 'Train/mean precision': 0.9836079478263855, 'Train/mean recall': 0.9939594268798828, 'Train/mean hd95_metric': 1.3118188381195068} +Epoch [1486/4000] Validation [1/4] Loss: 0.19982 focal_loss 0.13174 dice_loss 0.06808 +Epoch [1486/4000] Validation [2/4] Loss: 0.54196 focal_loss 0.35684 dice_loss 0.18512 +Epoch [1486/4000] Validation [3/4] Loss: 0.20222 focal_loss 0.11511 dice_loss 0.08711 +Epoch [1486/4000] Validation [4/4] Loss: 0.23245 focal_loss 0.11686 dice_loss 0.11559 +Epoch [1486/4000] Validation metric {'Val/mean dice_metric': 0.971244215965271, 'Val/mean miou_metric': 0.9523237347602844, 'Val/mean f1': 0.9708352088928223, 'Val/mean precision': 0.9664140939712524, 'Val/mean recall': 0.9752968549728394, 'Val/mean hd95_metric': 5.814238548278809} +Cheakpoint... +Epoch [1486/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971244215965271, 'Val/mean miou_metric': 0.9523237347602844, 'Val/mean f1': 0.9708352088928223, 'Val/mean precision': 0.9664140939712524, 'Val/mean recall': 0.9752968549728394, 'Val/mean hd95_metric': 5.814238548278809} +Epoch [1487/4000] Training [1/16] Loss: 0.00751 +Epoch [1487/4000] Training [2/16] Loss: 0.01043 +Epoch [1487/4000] Training [3/16] Loss: 0.01172 +Epoch [1487/4000] Training [4/16] Loss: 0.01126 +Epoch [1487/4000] Training [5/16] Loss: 0.00941 +Epoch [1487/4000] Training [6/16] Loss: 0.00817 +Epoch [1487/4000] Training [7/16] Loss: 0.00857 +Epoch [1487/4000] Training [8/16] Loss: 0.00954 +Epoch [1487/4000] Training [9/16] Loss: 0.00955 +Epoch [1487/4000] Training [10/16] Loss: 0.00946 +Epoch [1487/4000] Training [11/16] Loss: 0.00846 +Epoch [1487/4000] Training [12/16] Loss: 0.00977 +Epoch [1487/4000] Training [13/16] Loss: 0.00932 +Epoch [1487/4000] Training [14/16] Loss: 0.00728 +Epoch [1487/4000] Training [15/16] Loss: 0.00813 +Epoch [1487/4000] Training [16/16] Loss: 0.00874 +Epoch [1487/4000] Training metric {'Train/mean dice_metric': 0.9936166405677795, 'Train/mean miou_metric': 0.9871066808700562, 'Train/mean f1': 0.9887719750404358, 'Train/mean precision': 0.9838295578956604, 'Train/mean recall': 0.9937642216682434, 'Train/mean hd95_metric': 1.2477116584777832} +Epoch [1487/4000] Validation [1/4] Loss: 0.21563 focal_loss 0.14983 dice_loss 0.06580 +Epoch [1487/4000] Validation [2/4] Loss: 0.40030 focal_loss 0.26317 dice_loss 0.13713 +Epoch [1487/4000] Validation [3/4] Loss: 0.15765 focal_loss 0.09698 dice_loss 0.06067 +Epoch [1487/4000] Validation [4/4] Loss: 0.36893 focal_loss 0.19491 dice_loss 0.17403 +Epoch [1487/4000] Validation metric {'Val/mean dice_metric': 0.9718519449234009, 'Val/mean miou_metric': 0.9531455039978027, 'Val/mean f1': 0.9711613655090332, 'Val/mean precision': 0.9645892977714539, 'Val/mean recall': 0.977823793888092, 'Val/mean hd95_metric': 6.011850833892822} +Cheakpoint... +Epoch [1487/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718519449234009, 'Val/mean miou_metric': 0.9531455039978027, 'Val/mean f1': 0.9711613655090332, 'Val/mean precision': 0.9645892977714539, 'Val/mean recall': 0.977823793888092, 'Val/mean hd95_metric': 6.011850833892822} +Epoch [1488/4000] Training [1/16] Loss: 0.00953 +Epoch [1488/4000] Training [2/16] Loss: 0.00890 +Epoch [1488/4000] Training [3/16] Loss: 0.00807 +Epoch [1488/4000] Training [4/16] Loss: 0.04079 +Epoch [1488/4000] Training [5/16] Loss: 0.00761 +Epoch [1488/4000] Training [6/16] Loss: 0.02984 +Epoch [1488/4000] Training [7/16] Loss: 0.00729 +Epoch [1488/4000] Training [8/16] Loss: 0.00776 +Epoch [1488/4000] Training [9/16] Loss: 0.00880 +Epoch [1488/4000] Training [10/16] Loss: 0.01069 +Epoch [1488/4000] Training [11/16] Loss: 0.00913 +Epoch [1488/4000] Training [12/16] Loss: 0.01330 +Epoch [1488/4000] Training [13/16] Loss: 0.01266 +Epoch [1488/4000] Training [14/16] Loss: 0.01480 +Epoch [1488/4000] Training [15/16] Loss: 0.00785 +Epoch [1488/4000] Training [16/16] Loss: 0.00956 +Epoch [1488/4000] Training metric {'Train/mean dice_metric': 0.9919906258583069, 'Train/mean miou_metric': 0.9842299222946167, 'Train/mean f1': 0.9883910417556763, 'Train/mean precision': 0.9837138652801514, 'Train/mean recall': 0.9931129217147827, 'Train/mean hd95_metric': 1.9521145820617676} +Epoch [1488/4000] Validation [1/4] Loss: 0.32340 focal_loss 0.22752 dice_loss 0.09588 +Epoch [1488/4000] Validation [2/4] Loss: 0.82617 focal_loss 0.57877 dice_loss 0.24740 +Epoch [1488/4000] Validation [3/4] Loss: 0.23299 focal_loss 0.14071 dice_loss 0.09228 +Epoch [1488/4000] Validation [4/4] Loss: 0.28777 focal_loss 0.15786 dice_loss 0.12991 +Epoch [1488/4000] Validation metric {'Val/mean dice_metric': 0.9640750885009766, 'Val/mean miou_metric': 0.943686842918396, 'Val/mean f1': 0.9648745656013489, 'Val/mean precision': 0.9601403474807739, 'Val/mean recall': 0.9696555733680725, 'Val/mean hd95_metric': 7.768136501312256} +Cheakpoint... +Epoch [1488/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9641], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9640750885009766, 'Val/mean miou_metric': 0.943686842918396, 'Val/mean f1': 0.9648745656013489, 'Val/mean precision': 0.9601403474807739, 'Val/mean recall': 0.9696555733680725, 'Val/mean hd95_metric': 7.768136501312256} +Epoch [1489/4000] Training [1/16] Loss: 0.01134 +Epoch [1489/4000] Training [2/16] Loss: 0.00984 +Epoch [1489/4000] Training [3/16] Loss: 0.00755 +Epoch [1489/4000] Training [4/16] Loss: 0.01066 +Epoch [1489/4000] Training [5/16] Loss: 0.00678 +Epoch [1489/4000] Training [6/16] Loss: 0.00824 +Epoch [1489/4000] Training [7/16] Loss: 0.00892 +Epoch [1489/4000] Training [8/16] Loss: 0.00961 +Epoch [1489/4000] Training [9/16] Loss: 0.01468 +Epoch [1489/4000] Training [10/16] Loss: 0.01053 +Epoch [1489/4000] Training [11/16] Loss: 0.01203 +Epoch [1489/4000] Training [12/16] Loss: 0.01502 +Epoch [1489/4000] Training [13/16] Loss: 0.01025 +Epoch [1489/4000] Training [14/16] Loss: 0.01169 +Epoch [1489/4000] Training [15/16] Loss: 0.00788 +Epoch [1489/4000] Training [16/16] Loss: 0.00904 +Epoch [1489/4000] Training metric {'Train/mean dice_metric': 0.99317467212677, 'Train/mean miou_metric': 0.9862667322158813, 'Train/mean f1': 0.9892687797546387, 'Train/mean precision': 0.9845955967903137, 'Train/mean recall': 0.9939865469932556, 'Train/mean hd95_metric': 1.3629275560379028} +Epoch [1489/4000] Validation [1/4] Loss: 0.62989 focal_loss 0.49358 dice_loss 0.13631 +Epoch [1489/4000] Validation [2/4] Loss: 0.30632 focal_loss 0.17030 dice_loss 0.13602 +Epoch [1489/4000] Validation [3/4] Loss: 0.30753 focal_loss 0.21686 dice_loss 0.09067 +Epoch [1489/4000] Validation [4/4] Loss: 0.22708 focal_loss 0.13589 dice_loss 0.09119 +Epoch [1489/4000] Validation metric {'Val/mean dice_metric': 0.968396782875061, 'Val/mean miou_metric': 0.9488393068313599, 'Val/mean f1': 0.968799352645874, 'Val/mean precision': 0.9661239385604858, 'Val/mean recall': 0.9714897274971008, 'Val/mean hd95_metric': 6.530836582183838} +Cheakpoint... +Epoch [1489/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9684], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968396782875061, 'Val/mean miou_metric': 0.9488393068313599, 'Val/mean f1': 0.968799352645874, 'Val/mean precision': 0.9661239385604858, 'Val/mean recall': 0.9714897274971008, 'Val/mean hd95_metric': 6.530836582183838} +Epoch [1490/4000] Training [1/16] Loss: 0.00886 +Epoch [1490/4000] Training [2/16] Loss: 0.00825 +Epoch [1490/4000] Training [3/16] Loss: 0.00709 +Epoch [1490/4000] Training [4/16] Loss: 0.00925 +Epoch [1490/4000] Training [5/16] Loss: 0.00700 +Epoch [1490/4000] Training [6/16] Loss: 0.00999 +Epoch [1490/4000] Training [7/16] Loss: 0.01055 +Epoch [1490/4000] Training [8/16] Loss: 0.01412 +Epoch [1490/4000] Training [9/16] Loss: 0.00765 +Epoch [1490/4000] Training [10/16] Loss: 0.00732 +Epoch [1490/4000] Training [11/16] Loss: 0.01119 +Epoch [1490/4000] Training [12/16] Loss: 0.00789 +Epoch [1490/4000] Training [13/16] Loss: 0.02492 +Epoch [1490/4000] Training [14/16] Loss: 0.01153 +Epoch [1490/4000] Training [15/16] Loss: 0.00894 +Epoch [1490/4000] Training [16/16] Loss: 0.00912 +Epoch [1490/4000] Training metric {'Train/mean dice_metric': 0.9929887056350708, 'Train/mean miou_metric': 0.9860725998878479, 'Train/mean f1': 0.9885532855987549, 'Train/mean precision': 0.9844478964805603, 'Train/mean recall': 0.9926930665969849, 'Train/mean hd95_metric': 1.4838290214538574} +Epoch [1490/4000] Validation [1/4] Loss: 0.25451 focal_loss 0.17814 dice_loss 0.07636 +Epoch [1490/4000] Validation [2/4] Loss: 0.53579 focal_loss 0.32780 dice_loss 0.20799 +Epoch [1490/4000] Validation [3/4] Loss: 0.37473 focal_loss 0.24872 dice_loss 0.12601 +Epoch [1490/4000] Validation [4/4] Loss: 0.27417 focal_loss 0.15613 dice_loss 0.11804 +Epoch [1490/4000] Validation metric {'Val/mean dice_metric': 0.9690240621566772, 'Val/mean miou_metric': 0.9501951932907104, 'Val/mean f1': 0.9699797630310059, 'Val/mean precision': 0.9634925723075867, 'Val/mean recall': 0.9765549898147583, 'Val/mean hd95_metric': 6.852588653564453} +Cheakpoint... +Epoch [1490/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690240621566772, 'Val/mean miou_metric': 0.9501951932907104, 'Val/mean f1': 0.9699797630310059, 'Val/mean precision': 0.9634925723075867, 'Val/mean recall': 0.9765549898147583, 'Val/mean hd95_metric': 6.852588653564453} +Epoch [1491/4000] Training [1/16] Loss: 0.01301 +Epoch [1491/4000] Training [2/16] Loss: 0.00884 +Epoch [1491/4000] Training [3/16] Loss: 0.01091 +Epoch [1491/4000] Training [4/16] Loss: 0.00959 +Epoch [1491/4000] Training [5/16] Loss: 0.00705 +Epoch [1491/4000] Training [6/16] Loss: 0.00980 +Epoch [1491/4000] Training [7/16] Loss: 0.00743 +Epoch [1491/4000] Training [8/16] Loss: 0.00719 +Epoch [1491/4000] Training [9/16] Loss: 0.00738 +Epoch [1491/4000] Training [10/16] Loss: 0.00829 +Epoch [1491/4000] Training [11/16] Loss: 0.00772 +Epoch [1491/4000] Training [12/16] Loss: 0.00955 +Epoch [1491/4000] Training [13/16] Loss: 0.00975 +Epoch [1491/4000] Training [14/16] Loss: 0.00861 +Epoch [1491/4000] Training [15/16] Loss: 0.00780 +Epoch [1491/4000] Training [16/16] Loss: 0.00777 +Epoch [1491/4000] Training metric {'Train/mean dice_metric': 0.9942662119865417, 'Train/mean miou_metric': 0.9883356690406799, 'Train/mean f1': 0.9900038242340088, 'Train/mean precision': 0.9854341745376587, 'Train/mean recall': 0.9946159720420837, 'Train/mean hd95_metric': 1.1664190292358398} +Epoch [1491/4000] Validation [1/4] Loss: 0.26535 focal_loss 0.18744 dice_loss 0.07791 +Epoch [1491/4000] Validation [2/4] Loss: 0.39491 focal_loss 0.24913 dice_loss 0.14578 +Epoch [1491/4000] Validation [3/4] Loss: 0.17300 focal_loss 0.10659 dice_loss 0.06640 +Epoch [1491/4000] Validation [4/4] Loss: 0.22900 focal_loss 0.12453 dice_loss 0.10447 +Epoch [1491/4000] Validation metric {'Val/mean dice_metric': 0.9703828692436218, 'Val/mean miou_metric': 0.952440083026886, 'Val/mean f1': 0.9695584177970886, 'Val/mean precision': 0.9611545205116272, 'Val/mean recall': 0.9781105518341064, 'Val/mean hd95_metric': 6.8929443359375} +Cheakpoint... +Epoch [1491/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703828692436218, 'Val/mean miou_metric': 0.952440083026886, 'Val/mean f1': 0.9695584177970886, 'Val/mean precision': 0.9611545205116272, 'Val/mean recall': 0.9781105518341064, 'Val/mean hd95_metric': 6.8929443359375} +Epoch [1492/4000] Training [1/16] Loss: 0.00736 +Epoch [1492/4000] Training [2/16] Loss: 0.01011 +Epoch [1492/4000] Training [3/16] Loss: 0.00625 +Epoch [1492/4000] Training [4/16] Loss: 0.00796 +Epoch [1492/4000] Training [5/16] Loss: 0.00615 +Epoch [1492/4000] Training [6/16] Loss: 0.01068 +Epoch [1492/4000] Training [7/16] Loss: 0.01237 +Epoch [1492/4000] Training [8/16] Loss: 0.01144 +Epoch [1492/4000] Training [9/16] Loss: 0.01328 +Epoch [1492/4000] Training [10/16] Loss: 0.00742 +Epoch [1492/4000] Training [11/16] Loss: 0.00734 +Epoch [1492/4000] Training [12/16] Loss: 0.00675 +Epoch [1492/4000] Training [13/16] Loss: 0.00890 +Epoch [1492/4000] Training [14/16] Loss: 0.00683 +Epoch [1492/4000] Training [15/16] Loss: 0.01902 +Epoch [1492/4000] Training [16/16] Loss: 0.00700 +Epoch [1492/4000] Training metric {'Train/mean dice_metric': 0.9941271543502808, 'Train/mean miou_metric': 0.9880832433700562, 'Train/mean f1': 0.9898730516433716, 'Train/mean precision': 0.9850479364395142, 'Train/mean recall': 0.994745671749115, 'Train/mean hd95_metric': 1.288696527481079} +Epoch [1492/4000] Validation [1/4] Loss: 0.23770 focal_loss 0.16187 dice_loss 0.07582 +Epoch [1492/4000] Validation [2/4] Loss: 0.36708 focal_loss 0.22689 dice_loss 0.14019 +Epoch [1492/4000] Validation [3/4] Loss: 0.33144 focal_loss 0.22411 dice_loss 0.10734 +Epoch [1492/4000] Validation [4/4] Loss: 0.32960 focal_loss 0.18223 dice_loss 0.14737 +Epoch [1492/4000] Validation metric {'Val/mean dice_metric': 0.9700638651847839, 'Val/mean miou_metric': 0.9515272378921509, 'Val/mean f1': 0.9706550240516663, 'Val/mean precision': 0.9645712971687317, 'Val/mean recall': 0.9768158793449402, 'Val/mean hd95_metric': 6.391934871673584} +Cheakpoint... +Epoch [1492/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700638651847839, 'Val/mean miou_metric': 0.9515272378921509, 'Val/mean f1': 0.9706550240516663, 'Val/mean precision': 0.9645712971687317, 'Val/mean recall': 0.9768158793449402, 'Val/mean hd95_metric': 6.391934871673584} +Epoch [1493/4000] Training [1/16] Loss: 0.00793 +Epoch [1493/4000] Training [2/16] Loss: 0.01082 +Epoch [1493/4000] Training [3/16] Loss: 0.00751 +Epoch [1493/4000] Training [4/16] Loss: 0.00785 +Epoch [1493/4000] Training [5/16] Loss: 0.00705 +Epoch [1493/4000] Training [6/16] Loss: 0.00714 +Epoch [1493/4000] Training [7/16] Loss: 0.00690 +Epoch [1493/4000] Training [8/16] Loss: 0.00994 +Epoch [1493/4000] Training [9/16] Loss: 0.00793 +Epoch [1493/4000] Training [10/16] Loss: 0.00847 +Epoch [1493/4000] Training [11/16] Loss: 0.00753 +Epoch [1493/4000] Training [12/16] Loss: 0.00876 +Epoch [1493/4000] Training [13/16] Loss: 0.01048 +Epoch [1493/4000] Training [14/16] Loss: 0.00837 +Epoch [1493/4000] Training [15/16] Loss: 0.00824 +Epoch [1493/4000] Training [16/16] Loss: 0.00835 +Epoch [1493/4000] Training metric {'Train/mean dice_metric': 0.9942567348480225, 'Train/mean miou_metric': 0.9883780479431152, 'Train/mean f1': 0.9900209903717041, 'Train/mean precision': 0.9851014614105225, 'Train/mean recall': 0.9949898719787598, 'Train/mean hd95_metric': 1.2086843252182007} +Epoch [1493/4000] Validation [1/4] Loss: 0.30766 focal_loss 0.22678 dice_loss 0.08088 +Epoch [1493/4000] Validation [2/4] Loss: 0.56966 focal_loss 0.38386 dice_loss 0.18580 +Epoch [1493/4000] Validation [3/4] Loss: 0.31160 focal_loss 0.21831 dice_loss 0.09329 +Epoch [1493/4000] Validation [4/4] Loss: 0.27746 focal_loss 0.17228 dice_loss 0.10517 +Epoch [1493/4000] Validation metric {'Val/mean dice_metric': 0.9706720113754272, 'Val/mean miou_metric': 0.9523748159408569, 'Val/mean f1': 0.9715818762779236, 'Val/mean precision': 0.9667250514030457, 'Val/mean recall': 0.9764876961708069, 'Val/mean hd95_metric': 6.124385833740234} +Cheakpoint... +Epoch [1493/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706720113754272, 'Val/mean miou_metric': 0.9523748159408569, 'Val/mean f1': 0.9715818762779236, 'Val/mean precision': 0.9667250514030457, 'Val/mean recall': 0.9764876961708069, 'Val/mean hd95_metric': 6.124385833740234} +Epoch [1494/4000] Training [1/16] Loss: 0.00813 +Epoch [1494/4000] Training [2/16] Loss: 0.00768 +Epoch [1494/4000] Training [3/16] Loss: 0.00866 +Epoch [1494/4000] Training [4/16] Loss: 0.00715 +Epoch [1494/4000] Training [5/16] Loss: 0.00811 +Epoch [1494/4000] Training [6/16] Loss: 0.01044 +Epoch [1494/4000] Training [7/16] Loss: 0.00845 +Epoch [1494/4000] Training [8/16] Loss: 0.00711 +Epoch [1494/4000] Training [9/16] Loss: 0.00746 +Epoch [1494/4000] Training [10/16] Loss: 0.01107 +Epoch [1494/4000] Training [11/16] Loss: 0.00733 +Epoch [1494/4000] Training [12/16] Loss: 0.01317 +Epoch [1494/4000] Training [13/16] Loss: 0.00761 +Epoch [1494/4000] Training [14/16] Loss: 0.01040 +Epoch [1494/4000] Training [15/16] Loss: 0.00655 +Epoch [1494/4000] Training [16/16] Loss: 0.00916 +Epoch [1494/4000] Training metric {'Train/mean dice_metric': 0.9944415092468262, 'Train/mean miou_metric': 0.988696277141571, 'Train/mean f1': 0.9903612732887268, 'Train/mean precision': 0.9858438968658447, 'Train/mean recall': 0.9949202537536621, 'Train/mean hd95_metric': 1.5100617408752441} +Epoch [1494/4000] Validation [1/4] Loss: 0.29803 focal_loss 0.21383 dice_loss 0.08420 +Epoch [1494/4000] Validation [2/4] Loss: 0.40211 focal_loss 0.23646 dice_loss 0.16565 +Epoch [1494/4000] Validation [3/4] Loss: 0.30268 focal_loss 0.20880 dice_loss 0.09388 +Epoch [1494/4000] Validation [4/4] Loss: 0.24062 focal_loss 0.13248 dice_loss 0.10814 +Epoch [1494/4000] Validation metric {'Val/mean dice_metric': 0.9710944890975952, 'Val/mean miou_metric': 0.9531797170639038, 'Val/mean f1': 0.9719667434692383, 'Val/mean precision': 0.9695094227790833, 'Val/mean recall': 0.974436342716217, 'Val/mean hd95_metric': 6.1868896484375} +Cheakpoint... +Epoch [1494/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710944890975952, 'Val/mean miou_metric': 0.9531797170639038, 'Val/mean f1': 0.9719667434692383, 'Val/mean precision': 0.9695094227790833, 'Val/mean recall': 0.974436342716217, 'Val/mean hd95_metric': 6.1868896484375} +Epoch [1495/4000] Training [1/16] Loss: 0.00908 +Epoch [1495/4000] Training [2/16] Loss: 0.00538 +Epoch [1495/4000] Training [3/16] Loss: 0.00713 +Epoch [1495/4000] Training [4/16] Loss: 0.00856 +Epoch [1495/4000] Training [5/16] Loss: 0.00871 +Epoch [1495/4000] Training [6/16] Loss: 0.00573 +Epoch [1495/4000] Training [7/16] Loss: 0.00763 +Epoch [1495/4000] Training [8/16] Loss: 0.00543 +Epoch [1495/4000] Training [9/16] Loss: 0.00837 +Epoch [1495/4000] Training [10/16] Loss: 0.00848 +Epoch [1495/4000] Training [11/16] Loss: 0.00721 +Epoch [1495/4000] Training [12/16] Loss: 0.00769 +Epoch [1495/4000] Training [13/16] Loss: 0.00686 +Epoch [1495/4000] Training [14/16] Loss: 0.00820 +Epoch [1495/4000] Training [15/16] Loss: 0.00824 +Epoch [1495/4000] Training [16/16] Loss: 0.00629 +Epoch [1495/4000] Training metric {'Train/mean dice_metric': 0.9943713545799255, 'Train/mean miou_metric': 0.9885706901550293, 'Train/mean f1': 0.9902350306510925, 'Train/mean precision': 0.9858484864234924, 'Train/mean recall': 0.9946607351303101, 'Train/mean hd95_metric': 1.1504110097885132} +Epoch [1495/4000] Validation [1/4] Loss: 0.47594 focal_loss 0.36138 dice_loss 0.11457 +Epoch [1495/4000] Validation [2/4] Loss: 0.39604 focal_loss 0.20930 dice_loss 0.18673 +Epoch [1495/4000] Validation [3/4] Loss: 0.18115 focal_loss 0.11161 dice_loss 0.06953 +Epoch [1495/4000] Validation [4/4] Loss: 0.35079 focal_loss 0.20453 dice_loss 0.14626 +Epoch [1495/4000] Validation metric {'Val/mean dice_metric': 0.9701789617538452, 'Val/mean miou_metric': 0.9515573382377625, 'Val/mean f1': 0.9717124700546265, 'Val/mean precision': 0.9683138132095337, 'Val/mean recall': 0.9751350283622742, 'Val/mean hd95_metric': 6.064635276794434} +Cheakpoint... +Epoch [1495/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701789617538452, 'Val/mean miou_metric': 0.9515573382377625, 'Val/mean f1': 0.9717124700546265, 'Val/mean precision': 0.9683138132095337, 'Val/mean recall': 0.9751350283622742, 'Val/mean hd95_metric': 6.064635276794434} +Epoch [1496/4000] Training [1/16] Loss: 0.00756 +Epoch [1496/4000] Training [2/16] Loss: 0.00947 +Epoch [1496/4000] Training [3/16] Loss: 0.00886 +Epoch [1496/4000] Training [4/16] Loss: 0.00817 +Epoch [1496/4000] Training [5/16] Loss: 0.00746 +Epoch [1496/4000] Training [6/16] Loss: 0.00804 +Epoch [1496/4000] Training [7/16] Loss: 0.01011 +Epoch [1496/4000] Training [8/16] Loss: 0.00680 +Epoch [1496/4000] Training [9/16] Loss: 0.00936 +Epoch [1496/4000] Training [10/16] Loss: 0.01039 +Epoch [1496/4000] Training [11/16] Loss: 0.00735 +Epoch [1496/4000] Training [12/16] Loss: 0.00703 +Epoch [1496/4000] Training [13/16] Loss: 0.01033 +Epoch [1496/4000] Training [14/16] Loss: 0.00693 +Epoch [1496/4000] Training [15/16] Loss: 0.00780 +Epoch [1496/4000] Training [16/16] Loss: 0.00648 +Epoch [1496/4000] Training metric {'Train/mean dice_metric': 0.9944543838500977, 'Train/mean miou_metric': 0.9887193441390991, 'Train/mean f1': 0.9903600811958313, 'Train/mean precision': 0.9857890009880066, 'Train/mean recall': 0.9949737787246704, 'Train/mean hd95_metric': 1.1200064420700073} +Epoch [1496/4000] Validation [1/4] Loss: 0.29181 focal_loss 0.21210 dice_loss 0.07971 +Epoch [1496/4000] Validation [2/4] Loss: 0.47061 focal_loss 0.29284 dice_loss 0.17778 +Epoch [1496/4000] Validation [3/4] Loss: 0.34232 focal_loss 0.23698 dice_loss 0.10534 +Epoch [1496/4000] Validation [4/4] Loss: 0.22963 focal_loss 0.12583 dice_loss 0.10380 +Epoch [1496/4000] Validation metric {'Val/mean dice_metric': 0.9722920656204224, 'Val/mean miou_metric': 0.954572856426239, 'Val/mean f1': 0.9725706577301025, 'Val/mean precision': 0.9677636623382568, 'Val/mean recall': 0.9774255752563477, 'Val/mean hd95_metric': 6.081079483032227} +Cheakpoint... +Epoch [1496/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722920656204224, 'Val/mean miou_metric': 0.954572856426239, 'Val/mean f1': 0.9725706577301025, 'Val/mean precision': 0.9677636623382568, 'Val/mean recall': 0.9774255752563477, 'Val/mean hd95_metric': 6.081079483032227} +Epoch [1497/4000] Training [1/16] Loss: 0.01015 +Epoch [1497/4000] Training [2/16] Loss: 0.00891 +Epoch [1497/4000] Training [3/16] Loss: 0.00750 +Epoch [1497/4000] Training [4/16] Loss: 0.00882 +Epoch [1497/4000] Training [5/16] Loss: 0.00713 +Epoch [1497/4000] Training [6/16] Loss: 0.01399 +Epoch [1497/4000] Training [7/16] Loss: 0.00762 +Epoch [1497/4000] Training [8/16] Loss: 0.00958 +Epoch [1497/4000] Training [9/16] Loss: 0.00725 +Epoch [1497/4000] Training [10/16] Loss: 0.00828 +Epoch [1497/4000] Training [11/16] Loss: 0.01168 +Epoch [1497/4000] Training [12/16] Loss: 0.00980 +Epoch [1497/4000] Training [13/16] Loss: 0.01047 +Epoch [1497/4000] Training [14/16] Loss: 0.00788 +Epoch [1497/4000] Training [15/16] Loss: 0.00859 +Epoch [1497/4000] Training [16/16] Loss: 0.01135 +Epoch [1497/4000] Training metric {'Train/mean dice_metric': 0.993671178817749, 'Train/mean miou_metric': 0.9872047305107117, 'Train/mean f1': 0.9898700714111328, 'Train/mean precision': 0.9852887392044067, 'Train/mean recall': 0.9944941997528076, 'Train/mean hd95_metric': 1.2251054048538208} +Epoch [1497/4000] Validation [1/4] Loss: 0.27204 focal_loss 0.19363 dice_loss 0.07841 +Epoch [1497/4000] Validation [2/4] Loss: 0.57355 focal_loss 0.36438 dice_loss 0.20916 +Epoch [1497/4000] Validation [3/4] Loss: 0.16834 focal_loss 0.10689 dice_loss 0.06145 +Epoch [1497/4000] Validation [4/4] Loss: 0.25796 focal_loss 0.15402 dice_loss 0.10394 +Epoch [1497/4000] Validation metric {'Val/mean dice_metric': 0.9703615307807922, 'Val/mean miou_metric': 0.9520515203475952, 'Val/mean f1': 0.9724469780921936, 'Val/mean precision': 0.9679100513458252, 'Val/mean recall': 0.9770265817642212, 'Val/mean hd95_metric': 5.494184970855713} +Cheakpoint... +Epoch [1497/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703615307807922, 'Val/mean miou_metric': 0.9520515203475952, 'Val/mean f1': 0.9724469780921936, 'Val/mean precision': 0.9679100513458252, 'Val/mean recall': 0.9770265817642212, 'Val/mean hd95_metric': 5.494184970855713} +Epoch [1498/4000] Training [1/16] Loss: 0.00926 +Epoch [1498/4000] Training [2/16] Loss: 0.00689 +Epoch [1498/4000] Training [3/16] Loss: 0.00716 +Epoch [1498/4000] Training [4/16] Loss: 0.00809 +Epoch [1498/4000] Training [5/16] Loss: 0.00777 +Epoch [1498/4000] Training [6/16] Loss: 0.00865 +Epoch [1498/4000] Training [7/16] Loss: 0.00717 +Epoch [1498/4000] Training [8/16] Loss: 0.00690 +Epoch [1498/4000] Training [9/16] Loss: 0.00735 +Epoch [1498/4000] Training [10/16] Loss: 0.00754 +Epoch [1498/4000] Training [11/16] Loss: 0.00832 +Epoch [1498/4000] Training [12/16] Loss: 0.00870 +Epoch [1498/4000] Training [13/16] Loss: 0.00740 +Epoch [1498/4000] Training [14/16] Loss: 0.00771 +Epoch [1498/4000] Training [15/16] Loss: 0.01026 +Epoch [1498/4000] Training [16/16] Loss: 0.00909 +Epoch [1498/4000] Training metric {'Train/mean dice_metric': 0.9946378469467163, 'Train/mean miou_metric': 0.9890792369842529, 'Train/mean f1': 0.9905300140380859, 'Train/mean precision': 0.9859046339988708, 'Train/mean recall': 0.9951989650726318, 'Train/mean hd95_metric': 1.080652117729187} +Epoch [1498/4000] Validation [1/4] Loss: 0.26138 focal_loss 0.19027 dice_loss 0.07111 +Epoch [1498/4000] Validation [2/4] Loss: 0.38677 focal_loss 0.22007 dice_loss 0.16670 +Epoch [1498/4000] Validation [3/4] Loss: 0.31631 focal_loss 0.21864 dice_loss 0.09767 +Epoch [1498/4000] Validation [4/4] Loss: 0.28521 focal_loss 0.17589 dice_loss 0.10932 +Epoch [1498/4000] Validation metric {'Val/mean dice_metric': 0.9714293479919434, 'Val/mean miou_metric': 0.9534025192260742, 'Val/mean f1': 0.9729456305503845, 'Val/mean precision': 0.968165934085846, 'Val/mean recall': 0.9777727127075195, 'Val/mean hd95_metric': 6.544227600097656} +Cheakpoint... +Epoch [1498/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714293479919434, 'Val/mean miou_metric': 0.9534025192260742, 'Val/mean f1': 0.9729456305503845, 'Val/mean precision': 0.968165934085846, 'Val/mean recall': 0.9777727127075195, 'Val/mean hd95_metric': 6.544227600097656} +Epoch [1499/4000] Training [1/16] Loss: 0.00767 +Epoch [1499/4000] Training [2/16] Loss: 0.00650 +Epoch [1499/4000] Training [3/16] Loss: 0.00753 +Epoch [1499/4000] Training [4/16] Loss: 0.00773 +Epoch [1499/4000] Training [5/16] Loss: 0.00677 +Epoch [1499/4000] Training [6/16] Loss: 0.00798 +Epoch [1499/4000] Training [7/16] Loss: 0.00722 +Epoch [1499/4000] Training [8/16] Loss: 0.00855 +Epoch [1499/4000] Training [9/16] Loss: 0.00947 +Epoch [1499/4000] Training [10/16] Loss: 0.01536 +Epoch [1499/4000] Training [11/16] Loss: 0.00799 +Epoch [1499/4000] Training [12/16] Loss: 0.01003 +Epoch [1499/4000] Training [13/16] Loss: 0.01025 +Epoch [1499/4000] Training [14/16] Loss: 0.00965 +Epoch [1499/4000] Training [15/16] Loss: 0.00823 +Epoch [1499/4000] Training [16/16] Loss: 0.00651 +Epoch [1499/4000] Training metric {'Train/mean dice_metric': 0.9935153722763062, 'Train/mean miou_metric': 0.9872428178787231, 'Train/mean f1': 0.989886462688446, 'Train/mean precision': 0.9851601719856262, 'Train/mean recall': 0.9946582317352295, 'Train/mean hd95_metric': 1.1942362785339355} +Epoch [1499/4000] Validation [1/4] Loss: 0.40982 focal_loss 0.30198 dice_loss 0.10784 +Epoch [1499/4000] Validation [2/4] Loss: 0.34464 focal_loss 0.20625 dice_loss 0.13839 +Epoch [1499/4000] Validation [3/4] Loss: 0.25080 focal_loss 0.14273 dice_loss 0.10807 +Epoch [1499/4000] Validation [4/4] Loss: 0.33589 focal_loss 0.18863 dice_loss 0.14727 +Epoch [1499/4000] Validation metric {'Val/mean dice_metric': 0.9697583913803101, 'Val/mean miou_metric': 0.9504108428955078, 'Val/mean f1': 0.9711564183235168, 'Val/mean precision': 0.9713799357414246, 'Val/mean recall': 0.9709330201148987, 'Val/mean hd95_metric': 5.438989162445068} +Cheakpoint... +Epoch [1499/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697583913803101, 'Val/mean miou_metric': 0.9504108428955078, 'Val/mean f1': 0.9711564183235168, 'Val/mean precision': 0.9713799357414246, 'Val/mean recall': 0.9709330201148987, 'Val/mean hd95_metric': 5.438989162445068} +Epoch [1500/4000] Training [1/16] Loss: 0.00598 +Epoch [1500/4000] Training [2/16] Loss: 0.00634 +Epoch [1500/4000] Training [3/16] Loss: 0.00791 +Epoch [1500/4000] Training [4/16] Loss: 0.00662 +Epoch [1500/4000] Training [5/16] Loss: 0.00751 +Epoch [1500/4000] Training [6/16] Loss: 0.00976 +Epoch [1500/4000] Training [7/16] Loss: 0.01140 +Epoch [1500/4000] Training [8/16] Loss: 0.00752 +Epoch [1500/4000] Training [9/16] Loss: 0.01029 +Epoch [1500/4000] Training [10/16] Loss: 0.01279 +Epoch [1500/4000] Training [11/16] Loss: 0.00673 +Epoch [1500/4000] Training [12/16] Loss: 0.00750 +Epoch [1500/4000] Training [13/16] Loss: 0.01061 +Epoch [1500/4000] Training [14/16] Loss: 0.00929 +Epoch [1500/4000] Training [15/16] Loss: 0.00779 +Epoch [1500/4000] Training [16/16] Loss: 0.01052 +Epoch [1500/4000] Training metric {'Train/mean dice_metric': 0.9941145777702332, 'Train/mean miou_metric': 0.9880589246749878, 'Train/mean f1': 0.9903324842453003, 'Train/mean precision': 0.9858431816101074, 'Train/mean recall': 0.9948628544807434, 'Train/mean hd95_metric': 1.051393985748291} +Epoch [1500/4000] Validation [1/4] Loss: 0.27516 focal_loss 0.19982 dice_loss 0.07534 +Epoch [1500/4000] Validation [2/4] Loss: 0.45160 focal_loss 0.25090 dice_loss 0.20069 +Epoch [1500/4000] Validation [3/4] Loss: 0.26708 focal_loss 0.17047 dice_loss 0.09661 +Epoch [1500/4000] Validation [4/4] Loss: 0.38473 focal_loss 0.25731 dice_loss 0.12742 +Epoch [1500/4000] Validation metric {'Val/mean dice_metric': 0.9698692560195923, 'Val/mean miou_metric': 0.9520522952079773, 'Val/mean f1': 0.972517192363739, 'Val/mean precision': 0.9719102382659912, 'Val/mean recall': 0.9731248617172241, 'Val/mean hd95_metric': 5.3974151611328125} +Cheakpoint... +Epoch [1500/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698692560195923, 'Val/mean miou_metric': 0.9520522952079773, 'Val/mean f1': 0.972517192363739, 'Val/mean precision': 0.9719102382659912, 'Val/mean recall': 0.9731248617172241, 'Val/mean hd95_metric': 5.3974151611328125} +Epoch [1501/4000] Training [1/16] Loss: 0.00708 +Epoch [1501/4000] Training [2/16] Loss: 0.00846 +Epoch [1501/4000] Training [3/16] Loss: 0.01007 +Epoch [1501/4000] Training [4/16] Loss: 0.00945 +Epoch [1501/4000] Training [5/16] Loss: 0.00752 +Epoch [1501/4000] Training [6/16] Loss: 0.00939 +Epoch [1501/4000] Training [7/16] Loss: 0.00884 +Epoch [1501/4000] Training [8/16] Loss: 0.00717 +Epoch [1501/4000] Training [9/16] Loss: 0.00713 +Epoch [1501/4000] Training [10/16] Loss: 0.00734 +Epoch [1501/4000] Training [11/16] Loss: 0.00881 +Epoch [1501/4000] Training [12/16] Loss: 0.00818 +Epoch [1501/4000] Training [13/16] Loss: 0.00885 +Epoch [1501/4000] Training [14/16] Loss: 0.00871 +Epoch [1501/4000] Training [15/16] Loss: 0.00875 +Epoch [1501/4000] Training [16/16] Loss: 0.00663 +Epoch [1501/4000] Training metric {'Train/mean dice_metric': 0.9940966367721558, 'Train/mean miou_metric': 0.9880025386810303, 'Train/mean f1': 0.9901822209358215, 'Train/mean precision': 0.9856153726577759, 'Train/mean recall': 0.9947916269302368, 'Train/mean hd95_metric': 1.0764248371124268} +Epoch [1501/4000] Validation [1/4] Loss: 0.32873 focal_loss 0.24053 dice_loss 0.08820 +Epoch [1501/4000] Validation [2/4] Loss: 0.50574 focal_loss 0.30888 dice_loss 0.19686 +Epoch [1501/4000] Validation [3/4] Loss: 0.27964 focal_loss 0.18804 dice_loss 0.09161 +Epoch [1501/4000] Validation [4/4] Loss: 0.35298 focal_loss 0.22773 dice_loss 0.12525 +Epoch [1501/4000] Validation metric {'Val/mean dice_metric': 0.9706958532333374, 'Val/mean miou_metric': 0.9526643753051758, 'Val/mean f1': 0.9724127650260925, 'Val/mean precision': 0.9707584977149963, 'Val/mean recall': 0.9740727543830872, 'Val/mean hd95_metric': 5.370144844055176} +Cheakpoint... +Epoch [1501/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706958532333374, 'Val/mean miou_metric': 0.9526643753051758, 'Val/mean f1': 0.9724127650260925, 'Val/mean precision': 0.9707584977149963, 'Val/mean recall': 0.9740727543830872, 'Val/mean hd95_metric': 5.370144844055176} +Epoch [1502/4000] Training [1/16] Loss: 0.00671 +Epoch [1502/4000] Training [2/16] Loss: 0.01087 +Epoch [1502/4000] Training [3/16] Loss: 0.00791 +Epoch [1502/4000] Training [4/16] Loss: 0.00659 +Epoch [1502/4000] Training [5/16] Loss: 0.00737 +Epoch [1502/4000] Training [6/16] Loss: 0.01042 +Epoch [1502/4000] Training [7/16] Loss: 0.01081 +Epoch [1502/4000] Training [8/16] Loss: 0.00712 +Epoch [1502/4000] Training [9/16] Loss: 0.00778 +Epoch [1502/4000] Training [10/16] Loss: 0.01017 +Epoch [1502/4000] Training [11/16] Loss: 0.01008 +Epoch [1502/4000] Training [12/16] Loss: 0.00744 +Epoch [1502/4000] Training [13/16] Loss: 0.00739 +Epoch [1502/4000] Training [14/16] Loss: 0.00641 +Epoch [1502/4000] Training [15/16] Loss: 0.00844 +Epoch [1502/4000] Training [16/16] Loss: 0.00633 +Epoch [1502/4000] Training metric {'Train/mean dice_metric': 0.9943346977233887, 'Train/mean miou_metric': 0.9884566068649292, 'Train/mean f1': 0.9898024201393127, 'Train/mean precision': 0.9846150875091553, 'Train/mean recall': 0.9950447678565979, 'Train/mean hd95_metric': 1.0596693754196167} +Epoch [1502/4000] Validation [1/4] Loss: 0.25874 focal_loss 0.18563 dice_loss 0.07311 +Epoch [1502/4000] Validation [2/4] Loss: 0.72760 focal_loss 0.42427 dice_loss 0.30332 +Epoch [1502/4000] Validation [3/4] Loss: 0.29502 focal_loss 0.20765 dice_loss 0.08737 +Epoch [1502/4000] Validation [4/4] Loss: 0.18710 focal_loss 0.09886 dice_loss 0.08824 +Epoch [1502/4000] Validation metric {'Val/mean dice_metric': 0.969504177570343, 'Val/mean miou_metric': 0.9517792463302612, 'Val/mean f1': 0.9718296527862549, 'Val/mean precision': 0.9695738554000854, 'Val/mean recall': 0.9740960597991943, 'Val/mean hd95_metric': 5.220030784606934} +Cheakpoint... +Epoch [1502/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969504177570343, 'Val/mean miou_metric': 0.9517792463302612, 'Val/mean f1': 0.9718296527862549, 'Val/mean precision': 0.9695738554000854, 'Val/mean recall': 0.9740960597991943, 'Val/mean hd95_metric': 5.220030784606934} +Epoch [1503/4000] Training [1/16] Loss: 0.00922 +Epoch [1503/4000] Training [2/16] Loss: 0.00814 +Epoch [1503/4000] Training [3/16] Loss: 0.00745 +Epoch [1503/4000] Training [4/16] Loss: 0.00689 +Epoch [1503/4000] Training [5/16] Loss: 0.00694 +Epoch [1503/4000] Training [6/16] Loss: 0.00686 +Epoch [1503/4000] Training [7/16] Loss: 0.00772 +Epoch [1503/4000] Training [8/16] Loss: 0.00836 +Epoch [1503/4000] Training [9/16] Loss: 0.00906 +Epoch [1503/4000] Training [10/16] Loss: 0.01041 +Epoch [1503/4000] Training [11/16] Loss: 0.00976 +Epoch [1503/4000] Training [12/16] Loss: 0.00745 +Epoch [1503/4000] Training [13/16] Loss: 0.00855 +Epoch [1503/4000] Training [14/16] Loss: 0.00813 +Epoch [1503/4000] Training [15/16] Loss: 0.01583 +Epoch [1503/4000] Training [16/16] Loss: 0.01039 +Epoch [1503/4000] Training metric {'Train/mean dice_metric': 0.9942867755889893, 'Train/mean miou_metric': 0.9883779883384705, 'Train/mean f1': 0.9901713132858276, 'Train/mean precision': 0.9854079484939575, 'Train/mean recall': 0.9949809908866882, 'Train/mean hd95_metric': 1.1040046215057373} +Epoch [1503/4000] Validation [1/4] Loss: 0.23185 focal_loss 0.16678 dice_loss 0.06507 +Epoch [1503/4000] Validation [2/4] Loss: 0.35512 focal_loss 0.21047 dice_loss 0.14465 +Epoch [1503/4000] Validation [3/4] Loss: 0.19132 focal_loss 0.11388 dice_loss 0.07744 +Epoch [1503/4000] Validation [4/4] Loss: 0.23678 focal_loss 0.12935 dice_loss 0.10743 +Epoch [1503/4000] Validation metric {'Val/mean dice_metric': 0.9722244143486023, 'Val/mean miou_metric': 0.9545924067497253, 'Val/mean f1': 0.9739471077919006, 'Val/mean precision': 0.9701718091964722, 'Val/mean recall': 0.9777519106864929, 'Val/mean hd95_metric': 5.3270416259765625} +Cheakpoint... +Epoch [1503/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722244143486023, 'Val/mean miou_metric': 0.9545924067497253, 'Val/mean f1': 0.9739471077919006, 'Val/mean precision': 0.9701718091964722, 'Val/mean recall': 0.9777519106864929, 'Val/mean hd95_metric': 5.3270416259765625} +Epoch [1504/4000] Training [1/16] Loss: 0.00685 +Epoch [1504/4000] Training [2/16] Loss: 0.00861 +Epoch [1504/4000] Training [3/16] Loss: 0.00781 +Epoch [1504/4000] Training [4/16] Loss: 0.00818 +Epoch [1504/4000] Training [5/16] Loss: 0.00739 +Epoch [1504/4000] Training [6/16] Loss: 0.00796 +Epoch [1504/4000] Training [7/16] Loss: 0.00775 +Epoch [1504/4000] Training [8/16] Loss: 0.00880 +Epoch [1504/4000] Training [9/16] Loss: 0.00801 +Epoch [1504/4000] Training [10/16] Loss: 0.00803 +Epoch [1504/4000] Training [11/16] Loss: 0.01028 +Epoch [1504/4000] Training [12/16] Loss: 0.01360 +Epoch [1504/4000] Training [13/16] Loss: 0.00837 +Epoch [1504/4000] Training [14/16] Loss: 0.00814 +Epoch [1504/4000] Training [15/16] Loss: 0.00555 +Epoch [1504/4000] Training [16/16] Loss: 0.00878 +Epoch [1504/4000] Training metric {'Train/mean dice_metric': 0.9944406747817993, 'Train/mean miou_metric': 0.9886984825134277, 'Train/mean f1': 0.9905122518539429, 'Train/mean precision': 0.9860454797744751, 'Train/mean recall': 0.9950196743011475, 'Train/mean hd95_metric': 1.0856499671936035} +Epoch [1504/4000] Validation [1/4] Loss: 0.27425 focal_loss 0.20054 dice_loss 0.07371 +Epoch [1504/4000] Validation [2/4] Loss: 0.37812 focal_loss 0.23402 dice_loss 0.14410 +Epoch [1504/4000] Validation [3/4] Loss: 0.31571 focal_loss 0.22308 dice_loss 0.09263 +Epoch [1504/4000] Validation [4/4] Loss: 0.25640 focal_loss 0.14815 dice_loss 0.10824 +Epoch [1504/4000] Validation metric {'Val/mean dice_metric': 0.973550021648407, 'Val/mean miou_metric': 0.9556277394294739, 'Val/mean f1': 0.9740437269210815, 'Val/mean precision': 0.9715225100517273, 'Val/mean recall': 0.9765780568122864, 'Val/mean hd95_metric': 5.118250846862793} +Cheakpoint... +Epoch [1504/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973550021648407, 'Val/mean miou_metric': 0.9556277394294739, 'Val/mean f1': 0.9740437269210815, 'Val/mean precision': 0.9715225100517273, 'Val/mean recall': 0.9765780568122864, 'Val/mean hd95_metric': 5.118250846862793} +Epoch [1505/4000] Training [1/16] Loss: 0.00912 +Epoch [1505/4000] Training [2/16] Loss: 0.01215 +Epoch [1505/4000] Training [3/16] Loss: 0.00778 +Epoch [1505/4000] Training [4/16] Loss: 0.00682 +Epoch [1505/4000] Training [5/16] Loss: 0.00633 +Epoch [1505/4000] Training [6/16] Loss: 0.00744 +Epoch [1505/4000] Training [7/16] Loss: 0.01569 +Epoch [1505/4000] Training [8/16] Loss: 0.00883 +Epoch [1505/4000] Training [9/16] Loss: 0.00584 +Epoch [1505/4000] Training [10/16] Loss: 0.00826 +Epoch [1505/4000] Training [11/16] Loss: 0.00612 +Epoch [1505/4000] Training [12/16] Loss: 0.00707 +Epoch [1505/4000] Training [13/16] Loss: 0.00676 +Epoch [1505/4000] Training [14/16] Loss: 0.01195 +Epoch [1505/4000] Training [15/16] Loss: 0.00610 +Epoch [1505/4000] Training [16/16] Loss: 0.00886 +Epoch [1505/4000] Training metric {'Train/mean dice_metric': 0.9940476417541504, 'Train/mean miou_metric': 0.9879316091537476, 'Train/mean f1': 0.9904387593269348, 'Train/mean precision': 0.9858957529067993, 'Train/mean recall': 0.9950239062309265, 'Train/mean hd95_metric': 1.078797698020935} +Epoch [1505/4000] Validation [1/4] Loss: 0.24872 focal_loss 0.17413 dice_loss 0.07459 +Epoch [1505/4000] Validation [2/4] Loss: 0.20887 focal_loss 0.09943 dice_loss 0.10944 +Epoch [1505/4000] Validation [3/4] Loss: 0.18455 focal_loss 0.11899 dice_loss 0.06556 +Epoch [1505/4000] Validation [4/4] Loss: 0.26014 focal_loss 0.16300 dice_loss 0.09714 +Epoch [1505/4000] Validation metric {'Val/mean dice_metric': 0.9709180593490601, 'Val/mean miou_metric': 0.9529441595077515, 'Val/mean f1': 0.9735363125801086, 'Val/mean precision': 0.9721658229827881, 'Val/mean recall': 0.9749106764793396, 'Val/mean hd95_metric': 5.48337984085083} +Cheakpoint... +Epoch [1505/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709180593490601, 'Val/mean miou_metric': 0.9529441595077515, 'Val/mean f1': 0.9735363125801086, 'Val/mean precision': 0.9721658229827881, 'Val/mean recall': 0.9749106764793396, 'Val/mean hd95_metric': 5.48337984085083} +Epoch [1506/4000] Training [1/16] Loss: 0.00579 +Epoch [1506/4000] Training [2/16] Loss: 0.00632 +Epoch [1506/4000] Training [3/16] Loss: 0.00809 +Epoch [1506/4000] Training [4/16] Loss: 0.00995 +Epoch [1506/4000] Training [5/16] Loss: 0.00995 +Epoch [1506/4000] Training [6/16] Loss: 0.00662 +Epoch [1506/4000] Training [7/16] Loss: 0.00586 +Epoch [1506/4000] Training [8/16] Loss: 0.00926 +Epoch [1506/4000] Training [9/16] Loss: 0.00662 +Epoch [1506/4000] Training [10/16] Loss: 0.00802 +Epoch [1506/4000] Training [11/16] Loss: 0.00894 +Epoch [1506/4000] Training [12/16] Loss: 0.00934 +Epoch [1506/4000] Training [13/16] Loss: 0.00696 +Epoch [1506/4000] Training [14/16] Loss: 0.00752 +Epoch [1506/4000] Training [15/16] Loss: 0.00878 +Epoch [1506/4000] Training [16/16] Loss: 0.00945 +Epoch [1506/4000] Training metric {'Train/mean dice_metric': 0.9944955110549927, 'Train/mean miou_metric': 0.9887707829475403, 'Train/mean f1': 0.9900932908058167, 'Train/mean precision': 0.9850262403488159, 'Train/mean recall': 0.9952126741409302, 'Train/mean hd95_metric': 1.031163215637207} +Epoch [1506/4000] Validation [1/4] Loss: 0.24919 focal_loss 0.18212 dice_loss 0.06708 +Epoch [1506/4000] Validation [2/4] Loss: 0.33474 focal_loss 0.20710 dice_loss 0.12764 +Epoch [1506/4000] Validation [3/4] Loss: 0.23095 focal_loss 0.14546 dice_loss 0.08549 +Epoch [1506/4000] Validation [4/4] Loss: 0.25787 focal_loss 0.15438 dice_loss 0.10349 +Epoch [1506/4000] Validation metric {'Val/mean dice_metric': 0.9710575342178345, 'Val/mean miou_metric': 0.9535425901412964, 'Val/mean f1': 0.9740864634513855, 'Val/mean precision': 0.9712884426116943, 'Val/mean recall': 0.9769004583358765, 'Val/mean hd95_metric': 5.073890209197998} +Cheakpoint... +Epoch [1506/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710575342178345, 'Val/mean miou_metric': 0.9535425901412964, 'Val/mean f1': 0.9740864634513855, 'Val/mean precision': 0.9712884426116943, 'Val/mean recall': 0.9769004583358765, 'Val/mean hd95_metric': 5.073890209197998} +Epoch [1507/4000] Training [1/16] Loss: 0.00700 +Epoch [1507/4000] Training [2/16] Loss: 0.00655 +Epoch [1507/4000] Training [3/16] Loss: 0.00714 +Epoch [1507/4000] Training [4/16] Loss: 0.00763 +Epoch [1507/4000] Training [5/16] Loss: 0.00746 +Epoch [1507/4000] Training [6/16] Loss: 0.00744 +Epoch [1507/4000] Training [7/16] Loss: 0.00681 +Epoch [1507/4000] Training [8/16] Loss: 0.00749 +Epoch [1507/4000] Training [9/16] Loss: 0.01216 +Epoch [1507/4000] Training [10/16] Loss: 0.00855 +Epoch [1507/4000] Training [11/16] Loss: 0.00920 +Epoch [1507/4000] Training [12/16] Loss: 0.00833 +Epoch [1507/4000] Training [13/16] Loss: 0.00602 +Epoch [1507/4000] Training [14/16] Loss: 0.00776 +Epoch [1507/4000] Training [15/16] Loss: 0.00873 +Epoch [1507/4000] Training [16/16] Loss: 0.00858 +Epoch [1507/4000] Training metric {'Train/mean dice_metric': 0.9943544864654541, 'Train/mean miou_metric': 0.9885010719299316, 'Train/mean f1': 0.9897859692573547, 'Train/mean precision': 0.9845837354660034, 'Train/mean recall': 0.9950435161590576, 'Train/mean hd95_metric': 1.0514910221099854} +Epoch [1507/4000] Validation [1/4] Loss: 0.25309 focal_loss 0.18616 dice_loss 0.06692 +Epoch [1507/4000] Validation [2/4] Loss: 0.35754 focal_loss 0.20738 dice_loss 0.15016 +Epoch [1507/4000] Validation [3/4] Loss: 0.28859 focal_loss 0.19626 dice_loss 0.09233 +Epoch [1507/4000] Validation [4/4] Loss: 0.19564 focal_loss 0.10275 dice_loss 0.09289 +Epoch [1507/4000] Validation metric {'Val/mean dice_metric': 0.9726211428642273, 'Val/mean miou_metric': 0.9551685452461243, 'Val/mean f1': 0.9742905497550964, 'Val/mean precision': 0.9711366295814514, 'Val/mean recall': 0.9774651527404785, 'Val/mean hd95_metric': 5.152219295501709} +Cheakpoint... +Epoch [1507/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726211428642273, 'Val/mean miou_metric': 0.9551685452461243, 'Val/mean f1': 0.9742905497550964, 'Val/mean precision': 0.9711366295814514, 'Val/mean recall': 0.9774651527404785, 'Val/mean hd95_metric': 5.152219295501709} +Epoch [1508/4000] Training [1/16] Loss: 0.00682 +Epoch [1508/4000] Training [2/16] Loss: 0.00859 +Epoch [1508/4000] Training [3/16] Loss: 0.00858 +Epoch [1508/4000] Training [4/16] Loss: 0.00866 +Epoch [1508/4000] Training [5/16] Loss: 0.00845 +Epoch [1508/4000] Training [6/16] Loss: 0.00929 +Epoch [1508/4000] Training [7/16] Loss: 0.00904 +Epoch [1508/4000] Training [8/16] Loss: 0.00745 +Epoch [1508/4000] Training [9/16] Loss: 0.00974 +Epoch [1508/4000] Training [10/16] Loss: 0.01008 +Epoch [1508/4000] Training [11/16] Loss: 0.00987 +Epoch [1508/4000] Training [12/16] Loss: 0.00955 +Epoch [1508/4000] Training [13/16] Loss: 0.00672 +Epoch [1508/4000] Training [14/16] Loss: 0.00683 +Epoch [1508/4000] Training [15/16] Loss: 0.00924 +Epoch [1508/4000] Training [16/16] Loss: 0.00886 +Epoch [1508/4000] Training metric {'Train/mean dice_metric': 0.9941343069076538, 'Train/mean miou_metric': 0.9880948066711426, 'Train/mean f1': 0.9904698729515076, 'Train/mean precision': 0.9861453771591187, 'Train/mean recall': 0.9948325157165527, 'Train/mean hd95_metric': 1.0264463424682617} +Epoch [1508/4000] Validation [1/4] Loss: 0.35939 focal_loss 0.26626 dice_loss 0.09314 +Epoch [1508/4000] Validation [2/4] Loss: 0.44494 focal_loss 0.24701 dice_loss 0.19792 +Epoch [1508/4000] Validation [3/4] Loss: 0.27572 focal_loss 0.18215 dice_loss 0.09357 +Epoch [1508/4000] Validation [4/4] Loss: 0.24359 focal_loss 0.13445 dice_loss 0.10914 +Epoch [1508/4000] Validation metric {'Val/mean dice_metric': 0.9708675146102905, 'Val/mean miou_metric': 0.9528557062149048, 'Val/mean f1': 0.9723697900772095, 'Val/mean precision': 0.971300482749939, 'Val/mean recall': 0.9734413623809814, 'Val/mean hd95_metric': 5.359011173248291} +Cheakpoint... +Epoch [1508/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708675146102905, 'Val/mean miou_metric': 0.9528557062149048, 'Val/mean f1': 0.9723697900772095, 'Val/mean precision': 0.971300482749939, 'Val/mean recall': 0.9734413623809814, 'Val/mean hd95_metric': 5.359011173248291} +Epoch [1509/4000] Training [1/16] Loss: 0.00837 +Epoch [1509/4000] Training [2/16] Loss: 0.00782 +Epoch [1509/4000] Training [3/16] Loss: 0.00970 +Epoch [1509/4000] Training [4/16] Loss: 0.00910 +Epoch [1509/4000] Training [5/16] Loss: 0.00805 +Epoch [1509/4000] Training [6/16] Loss: 0.00826 +Epoch [1509/4000] Training [7/16] Loss: 0.00764 +Epoch [1509/4000] Training [8/16] Loss: 0.01058 +Epoch [1509/4000] Training [9/16] Loss: 0.01128 +Epoch [1509/4000] Training [10/16] Loss: 0.00726 +Epoch [1509/4000] Training [11/16] Loss: 0.00887 +Epoch [1509/4000] Training [12/16] Loss: 0.01231 +Epoch [1509/4000] Training [13/16] Loss: 0.01145 +Epoch [1509/4000] Training [14/16] Loss: 0.00628 +Epoch [1509/4000] Training [15/16] Loss: 0.00663 +Epoch [1509/4000] Training [16/16] Loss: 0.01149 +Epoch [1509/4000] Training metric {'Train/mean dice_metric': 0.9940017461776733, 'Train/mean miou_metric': 0.9878397583961487, 'Train/mean f1': 0.9903714656829834, 'Train/mean precision': 0.9856497645378113, 'Train/mean recall': 0.9951385259628296, 'Train/mean hd95_metric': 1.039451241493225} +Epoch [1509/4000] Validation [1/4] Loss: 0.24582 focal_loss 0.17649 dice_loss 0.06933 +Epoch [1509/4000] Validation [2/4] Loss: 0.43352 focal_loss 0.25574 dice_loss 0.17777 +Epoch [1509/4000] Validation [3/4] Loss: 0.34979 focal_loss 0.25334 dice_loss 0.09644 +Epoch [1509/4000] Validation [4/4] Loss: 0.28356 focal_loss 0.16716 dice_loss 0.11640 +Epoch [1509/4000] Validation metric {'Val/mean dice_metric': 0.9713983535766602, 'Val/mean miou_metric': 0.9530576467514038, 'Val/mean f1': 0.9733295440673828, 'Val/mean precision': 0.96924889087677, 'Val/mean recall': 0.9774447083473206, 'Val/mean hd95_metric': 5.587413787841797} +Cheakpoint... +Epoch [1509/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713983535766602, 'Val/mean miou_metric': 0.9530576467514038, 'Val/mean f1': 0.9733295440673828, 'Val/mean precision': 0.96924889087677, 'Val/mean recall': 0.9774447083473206, 'Val/mean hd95_metric': 5.587413787841797} +Epoch [1510/4000] Training [1/16] Loss: 0.00701 +Epoch [1510/4000] Training [2/16] Loss: 0.00798 +Epoch [1510/4000] Training [3/16] Loss: 0.00819 +Epoch [1510/4000] Training [4/16] Loss: 0.00843 +Epoch [1510/4000] Training [5/16] Loss: 0.00934 +Epoch [1510/4000] Training [6/16] Loss: 0.00851 +Epoch [1510/4000] Training [7/16] Loss: 0.00887 +Epoch [1510/4000] Training [8/16] Loss: 0.00887 +Epoch [1510/4000] Training [9/16] Loss: 0.01122 +Epoch [1510/4000] Training [10/16] Loss: 0.01027 +Epoch [1510/4000] Training [11/16] Loss: 0.00911 +Epoch [1510/4000] Training [12/16] Loss: 0.01124 +Epoch [1510/4000] Training [13/16] Loss: 0.00630 +Epoch [1510/4000] Training [14/16] Loss: 0.00844 +Epoch [1510/4000] Training [15/16] Loss: 0.00736 +Epoch [1510/4000] Training [16/16] Loss: 0.00966 +Epoch [1510/4000] Training metric {'Train/mean dice_metric': 0.9937793612480164, 'Train/mean miou_metric': 0.9874016046524048, 'Train/mean f1': 0.9902111291885376, 'Train/mean precision': 0.9858258366584778, 'Train/mean recall': 0.9946355819702148, 'Train/mean hd95_metric': 1.038783073425293} +Epoch [1510/4000] Validation [1/4] Loss: 0.30407 focal_loss 0.22310 dice_loss 0.08097 +Epoch [1510/4000] Validation [2/4] Loss: 0.26538 focal_loss 0.13149 dice_loss 0.13389 +Epoch [1510/4000] Validation [3/4] Loss: 0.31993 focal_loss 0.22328 dice_loss 0.09665 +Epoch [1510/4000] Validation [4/4] Loss: 0.27589 focal_loss 0.15853 dice_loss 0.11736 +Epoch [1510/4000] Validation metric {'Val/mean dice_metric': 0.9714410901069641, 'Val/mean miou_metric': 0.9525500535964966, 'Val/mean f1': 0.9732003808021545, 'Val/mean precision': 0.9722420573234558, 'Val/mean recall': 0.9741604924201965, 'Val/mean hd95_metric': 5.536225318908691} +Cheakpoint... +Epoch [1510/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714410901069641, 'Val/mean miou_metric': 0.9525500535964966, 'Val/mean f1': 0.9732003808021545, 'Val/mean precision': 0.9722420573234558, 'Val/mean recall': 0.9741604924201965, 'Val/mean hd95_metric': 5.536225318908691} +Epoch [1511/4000] Training [1/16] Loss: 0.00971 +Epoch [1511/4000] Training [2/16] Loss: 0.00741 +Epoch [1511/4000] Training [3/16] Loss: 0.00895 +Epoch [1511/4000] Training [4/16] Loss: 0.00816 +Epoch [1511/4000] Training [5/16] Loss: 0.00775 +Epoch [1511/4000] Training [6/16] Loss: 0.01000 +Epoch [1511/4000] Training [7/16] Loss: 0.00930 +Epoch [1511/4000] Training [8/16] Loss: 0.01014 +Epoch [1511/4000] Training [9/16] Loss: 0.00875 +Epoch [1511/4000] Training [10/16] Loss: 0.00703 +Epoch [1511/4000] Training [11/16] Loss: 0.00766 +Epoch [1511/4000] Training [12/16] Loss: 0.01296 +Epoch [1511/4000] Training [13/16] Loss: 0.00618 +Epoch [1511/4000] Training [14/16] Loss: 0.00692 +Epoch [1511/4000] Training [15/16] Loss: 0.00934 +Epoch [1511/4000] Training [16/16] Loss: 0.00925 +Epoch [1511/4000] Training metric {'Train/mean dice_metric': 0.9941877126693726, 'Train/mean miou_metric': 0.9881715178489685, 'Train/mean f1': 0.9900856018066406, 'Train/mean precision': 0.985350489616394, 'Train/mean recall': 0.9948664307594299, 'Train/mean hd95_metric': 1.041414499282837} +Epoch [1511/4000] Validation [1/4] Loss: 0.29404 focal_loss 0.21543 dice_loss 0.07861 +Epoch [1511/4000] Validation [2/4] Loss: 0.42259 focal_loss 0.24504 dice_loss 0.17754 +Epoch [1511/4000] Validation [3/4] Loss: 0.34567 focal_loss 0.24138 dice_loss 0.10429 +Epoch [1511/4000] Validation [4/4] Loss: 0.30391 focal_loss 0.18390 dice_loss 0.12001 +Epoch [1511/4000] Validation metric {'Val/mean dice_metric': 0.973016619682312, 'Val/mean miou_metric': 0.9551456570625305, 'Val/mean f1': 0.9738909006118774, 'Val/mean precision': 0.9707126021385193, 'Val/mean recall': 0.9770899415016174, 'Val/mean hd95_metric': 4.852896690368652} +Cheakpoint... +Epoch [1511/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973016619682312, 'Val/mean miou_metric': 0.9551456570625305, 'Val/mean f1': 0.9738909006118774, 'Val/mean precision': 0.9707126021385193, 'Val/mean recall': 0.9770899415016174, 'Val/mean hd95_metric': 4.852896690368652} +Epoch [1512/4000] Training [1/16] Loss: 0.00729 +Epoch [1512/4000] Training [2/16] Loss: 0.01061 +Epoch [1512/4000] Training [3/16] Loss: 0.00931 +Epoch [1512/4000] Training [4/16] Loss: 0.00612 +Epoch [1512/4000] Training [5/16] Loss: 0.01296 +Epoch [1512/4000] Training [6/16] Loss: 0.00622 +Epoch [1512/4000] Training [7/16] Loss: 0.00984 +Epoch [1512/4000] Training [8/16] Loss: 0.01056 +Epoch [1512/4000] Training [9/16] Loss: 0.00937 +Epoch [1512/4000] Training [10/16] Loss: 0.01048 +Epoch [1512/4000] Training [11/16] Loss: 0.00875 +Epoch [1512/4000] Training [12/16] Loss: 0.00902 +Epoch [1512/4000] Training [13/16] Loss: 0.01058 +Epoch [1512/4000] Training [14/16] Loss: 0.01017 +Epoch [1512/4000] Training [15/16] Loss: 0.00923 +Epoch [1512/4000] Training [16/16] Loss: 0.00943 +Epoch [1512/4000] Training metric {'Train/mean dice_metric': 0.9940027594566345, 'Train/mean miou_metric': 0.9878234267234802, 'Train/mean f1': 0.9900457262992859, 'Train/mean precision': 0.985332190990448, 'Train/mean recall': 0.9948045611381531, 'Train/mean hd95_metric': 1.0436320304870605} +Epoch [1512/4000] Validation [1/4] Loss: 0.24355 focal_loss 0.17352 dice_loss 0.07004 +Epoch [1512/4000] Validation [2/4] Loss: 0.55645 focal_loss 0.35066 dice_loss 0.20579 +Epoch [1512/4000] Validation [3/4] Loss: 0.15862 focal_loss 0.10089 dice_loss 0.05773 +Epoch [1512/4000] Validation [4/4] Loss: 0.33835 focal_loss 0.20143 dice_loss 0.13692 +Epoch [1512/4000] Validation metric {'Val/mean dice_metric': 0.9718986749649048, 'Val/mean miou_metric': 0.9537093043327332, 'Val/mean f1': 0.9738253951072693, 'Val/mean precision': 0.9710693955421448, 'Val/mean recall': 0.9765971302986145, 'Val/mean hd95_metric': 5.174670219421387} +Cheakpoint... +Epoch [1512/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718986749649048, 'Val/mean miou_metric': 0.9537093043327332, 'Val/mean f1': 0.9738253951072693, 'Val/mean precision': 0.9710693955421448, 'Val/mean recall': 0.9765971302986145, 'Val/mean hd95_metric': 5.174670219421387} +Epoch [1513/4000] Training [1/16] Loss: 0.00968 +Epoch [1513/4000] Training [2/16] Loss: 0.00926 +Epoch [1513/4000] Training [3/16] Loss: 0.00690 +Epoch [1513/4000] Training [4/16] Loss: 0.00858 +Epoch [1513/4000] Training [5/16] Loss: 0.00762 +Epoch [1513/4000] Training [6/16] Loss: 0.00949 +Epoch [1513/4000] Training [7/16] Loss: 0.00972 +Epoch [1513/4000] Training [8/16] Loss: 0.00764 +Epoch [1513/4000] Training [9/16] Loss: 0.01223 +Epoch [1513/4000] Training [10/16] Loss: 0.00778 +Epoch [1513/4000] Training [11/16] Loss: 0.01765 +Epoch [1513/4000] Training [12/16] Loss: 0.00969 +Epoch [1513/4000] Training [13/16] Loss: 0.00767 +Epoch [1513/4000] Training [14/16] Loss: 0.00734 +Epoch [1513/4000] Training [15/16] Loss: 0.00906 +Epoch [1513/4000] Training [16/16] Loss: 0.00829 +Epoch [1513/4000] Training metric {'Train/mean dice_metric': 0.9941269755363464, 'Train/mean miou_metric': 0.9880806803703308, 'Train/mean f1': 0.9902400970458984, 'Train/mean precision': 0.9856715798377991, 'Train/mean recall': 0.9948511123657227, 'Train/mean hd95_metric': 1.0577452182769775} +Epoch [1513/4000] Validation [1/4] Loss: 0.21469 focal_loss 0.15162 dice_loss 0.06307 +Epoch [1513/4000] Validation [2/4] Loss: 0.21062 focal_loss 0.11517 dice_loss 0.09545 +Epoch [1513/4000] Validation [3/4] Loss: 0.19711 focal_loss 0.12679 dice_loss 0.07031 +Epoch [1513/4000] Validation [4/4] Loss: 0.26980 focal_loss 0.16688 dice_loss 0.10292 +Epoch [1513/4000] Validation metric {'Val/mean dice_metric': 0.9720781445503235, 'Val/mean miou_metric': 0.9543884992599487, 'Val/mean f1': 0.9742198586463928, 'Val/mean precision': 0.9702311754226685, 'Val/mean recall': 0.9782414436340332, 'Val/mean hd95_metric': 5.449488639831543} +Cheakpoint... +Epoch [1513/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720781445503235, 'Val/mean miou_metric': 0.9543884992599487, 'Val/mean f1': 0.9742198586463928, 'Val/mean precision': 0.9702311754226685, 'Val/mean recall': 0.9782414436340332, 'Val/mean hd95_metric': 5.449488639831543} +Epoch [1514/4000] Training [1/16] Loss: 0.00731 +Epoch [1514/4000] Training [2/16] Loss: 0.01220 +Epoch [1514/4000] Training [3/16] Loss: 0.00816 +Epoch [1514/4000] Training [4/16] Loss: 0.00847 +Epoch [1514/4000] Training [5/16] Loss: 0.04493 +Epoch [1514/4000] Training [6/16] Loss: 0.00668 +Epoch [1514/4000] Training [7/16] Loss: 0.00839 +Epoch [1514/4000] Training [8/16] Loss: 0.00696 +Epoch [1514/4000] Training [9/16] Loss: 0.00617 +Epoch [1514/4000] Training [10/16] Loss: 0.00685 +Epoch [1514/4000] Training [11/16] Loss: 0.00975 +Epoch [1514/4000] Training [12/16] Loss: 0.00771 +Epoch [1514/4000] Training [13/16] Loss: 0.01057 +Epoch [1514/4000] Training [14/16] Loss: 0.00888 +Epoch [1514/4000] Training [15/16] Loss: 0.00953 +Epoch [1514/4000] Training [16/16] Loss: 0.01037 +Epoch [1514/4000] Training metric {'Train/mean dice_metric': 0.9936232566833496, 'Train/mean miou_metric': 0.9871923923492432, 'Train/mean f1': 0.9902108907699585, 'Train/mean precision': 0.9857231378555298, 'Train/mean recall': 0.9947397112846375, 'Train/mean hd95_metric': 1.1794800758361816} +Epoch [1514/4000] Validation [1/4] Loss: 0.27014 focal_loss 0.18983 dice_loss 0.08031 +Epoch [1514/4000] Validation [2/4] Loss: 0.42211 focal_loss 0.23567 dice_loss 0.18645 +Epoch [1514/4000] Validation [3/4] Loss: 0.32849 focal_loss 0.22880 dice_loss 0.09969 +Epoch [1514/4000] Validation [4/4] Loss: 0.38611 focal_loss 0.25487 dice_loss 0.13124 +Epoch [1514/4000] Validation metric {'Val/mean dice_metric': 0.9697073698043823, 'Val/mean miou_metric': 0.9511598348617554, 'Val/mean f1': 0.9721770286560059, 'Val/mean precision': 0.9711810946464539, 'Val/mean recall': 0.9731752276420593, 'Val/mean hd95_metric': 5.661805152893066} +Cheakpoint... +Epoch [1514/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697073698043823, 'Val/mean miou_metric': 0.9511598348617554, 'Val/mean f1': 0.9721770286560059, 'Val/mean precision': 0.9711810946464539, 'Val/mean recall': 0.9731752276420593, 'Val/mean hd95_metric': 5.661805152893066} +Epoch [1515/4000] Training [1/16] Loss: 0.00956 +Epoch [1515/4000] Training [2/16] Loss: 0.00779 +Epoch [1515/4000] Training [3/16] Loss: 0.00741 +Epoch [1515/4000] Training [4/16] Loss: 0.01088 +Epoch [1515/4000] Training [5/16] Loss: 0.00964 +Epoch [1515/4000] Training [6/16] Loss: 0.00735 +Epoch [1515/4000] Training [7/16] Loss: 0.00880 +Epoch [1515/4000] Training [8/16] Loss: 0.00756 +Epoch [1515/4000] Training [9/16] Loss: 0.00899 +Epoch [1515/4000] Training [10/16] Loss: 0.00748 +Epoch [1515/4000] Training [11/16] Loss: 0.00818 +Epoch [1515/4000] Training [12/16] Loss: 0.00680 +Epoch [1515/4000] Training [13/16] Loss: 0.00801 +Epoch [1515/4000] Training [14/16] Loss: 0.00564 +Epoch [1515/4000] Training [15/16] Loss: 0.01014 +Epoch [1515/4000] Training [16/16] Loss: 0.01073 +Epoch [1515/4000] Training metric {'Train/mean dice_metric': 0.994268000125885, 'Train/mean miou_metric': 0.9883400797843933, 'Train/mean f1': 0.9900705218315125, 'Train/mean precision': 0.9851803779602051, 'Train/mean recall': 0.9950094223022461, 'Train/mean hd95_metric': 1.0464529991149902} +Epoch [1515/4000] Validation [1/4] Loss: 0.18984 focal_loss 0.13024 dice_loss 0.05960 +Epoch [1515/4000] Validation [2/4] Loss: 0.61533 focal_loss 0.42113 dice_loss 0.19419 +Epoch [1515/4000] Validation [3/4] Loss: 0.24205 focal_loss 0.15105 dice_loss 0.09100 +Epoch [1515/4000] Validation [4/4] Loss: 0.28187 focal_loss 0.16497 dice_loss 0.11690 +Epoch [1515/4000] Validation metric {'Val/mean dice_metric': 0.9718732833862305, 'Val/mean miou_metric': 0.9540656805038452, 'Val/mean f1': 0.972933292388916, 'Val/mean precision': 0.9684550166130066, 'Val/mean recall': 0.9774531722068787, 'Val/mean hd95_metric': 5.781263828277588} +Cheakpoint... +Epoch [1515/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718732833862305, 'Val/mean miou_metric': 0.9540656805038452, 'Val/mean f1': 0.972933292388916, 'Val/mean precision': 0.9684550166130066, 'Val/mean recall': 0.9774531722068787, 'Val/mean hd95_metric': 5.781263828277588} +Epoch [1516/4000] Training [1/16] Loss: 0.00861 +Epoch [1516/4000] Training [2/16] Loss: 0.00833 +Epoch [1516/4000] Training [3/16] Loss: 0.00971 +Epoch [1516/4000] Training [4/16] Loss: 0.00734 +Epoch [1516/4000] Training [5/16] Loss: 0.01076 +Epoch [1516/4000] Training [6/16] Loss: 0.00775 +Epoch [1516/4000] Training [7/16] Loss: 0.00787 +Epoch [1516/4000] Training [8/16] Loss: 0.00728 +Epoch [1516/4000] Training [9/16] Loss: 0.00879 +Epoch [1516/4000] Training [10/16] Loss: 0.01283 +Epoch [1516/4000] Training [11/16] Loss: 0.00787 +Epoch [1516/4000] Training [12/16] Loss: 0.00721 +Epoch [1516/4000] Training [13/16] Loss: 0.00668 +Epoch [1516/4000] Training [14/16] Loss: 0.00788 +Epoch [1516/4000] Training [15/16] Loss: 0.01154 +Epoch [1516/4000] Training [16/16] Loss: 0.00875 +Epoch [1516/4000] Training metric {'Train/mean dice_metric': 0.9941895008087158, 'Train/mean miou_metric': 0.9881885051727295, 'Train/mean f1': 0.9898163676261902, 'Train/mean precision': 0.9849663972854614, 'Train/mean recall': 0.9947143197059631, 'Train/mean hd95_metric': 1.0595979690551758} +Epoch [1516/4000] Validation [1/4] Loss: 0.21201 focal_loss 0.14374 dice_loss 0.06827 +Epoch [1516/4000] Validation [2/4] Loss: 0.54990 focal_loss 0.33305 dice_loss 0.21685 +Epoch [1516/4000] Validation [3/4] Loss: 0.28960 focal_loss 0.19203 dice_loss 0.09757 +Epoch [1516/4000] Validation [4/4] Loss: 0.36307 focal_loss 0.21799 dice_loss 0.14508 +Epoch [1516/4000] Validation metric {'Val/mean dice_metric': 0.9714123010635376, 'Val/mean miou_metric': 0.9528932571411133, 'Val/mean f1': 0.9727155566215515, 'Val/mean precision': 0.9690874218940735, 'Val/mean recall': 0.9763708710670471, 'Val/mean hd95_metric': 5.603429317474365} +Cheakpoint... +Epoch [1516/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714123010635376, 'Val/mean miou_metric': 0.9528932571411133, 'Val/mean f1': 0.9727155566215515, 'Val/mean precision': 0.9690874218940735, 'Val/mean recall': 0.9763708710670471, 'Val/mean hd95_metric': 5.603429317474365} +Epoch [1517/4000] Training [1/16] Loss: 0.00705 +Epoch [1517/4000] Training [2/16] Loss: 0.00648 +Epoch [1517/4000] Training [3/16] Loss: 0.00888 +Epoch [1517/4000] Training [4/16] Loss: 0.00736 +Epoch [1517/4000] Training [5/16] Loss: 0.01101 +Epoch [1517/4000] Training [6/16] Loss: 0.00903 +Epoch [1517/4000] Training [7/16] Loss: 0.00827 +Epoch [1517/4000] Training [8/16] Loss: 0.00688 +Epoch [1517/4000] Training [9/16] Loss: 0.00841 +Epoch [1517/4000] Training [10/16] Loss: 0.00746 +Epoch [1517/4000] Training [11/16] Loss: 0.00959 +Epoch [1517/4000] Training [12/16] Loss: 0.00875 +Epoch [1517/4000] Training [13/16] Loss: 0.00791 +Epoch [1517/4000] Training [14/16] Loss: 0.00992 +Epoch [1517/4000] Training [15/16] Loss: 0.00673 +Epoch [1517/4000] Training [16/16] Loss: 0.00812 +Epoch [1517/4000] Training metric {'Train/mean dice_metric': 0.9945027828216553, 'Train/mean miou_metric': 0.9887653589248657, 'Train/mean f1': 0.9895888566970825, 'Train/mean precision': 0.9841516613960266, 'Train/mean recall': 0.9950864315032959, 'Train/mean hd95_metric': 1.0232923030853271} +Epoch [1517/4000] Validation [1/4] Loss: 0.32571 focal_loss 0.23716 dice_loss 0.08855 +Epoch [1517/4000] Validation [2/4] Loss: 0.40967 focal_loss 0.23714 dice_loss 0.17253 +Epoch [1517/4000] Validation [3/4] Loss: 0.27017 focal_loss 0.17779 dice_loss 0.09238 +Epoch [1517/4000] Validation [4/4] Loss: 0.29664 focal_loss 0.16703 dice_loss 0.12961 +Epoch [1517/4000] Validation metric {'Val/mean dice_metric': 0.9719952344894409, 'Val/mean miou_metric': 0.9534537196159363, 'Val/mean f1': 0.9722586274147034, 'Val/mean precision': 0.9691917896270752, 'Val/mean recall': 0.9753450155258179, 'Val/mean hd95_metric': 5.73392391204834} +Cheakpoint... +Epoch [1517/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719952344894409, 'Val/mean miou_metric': 0.9534537196159363, 'Val/mean f1': 0.9722586274147034, 'Val/mean precision': 0.9691917896270752, 'Val/mean recall': 0.9753450155258179, 'Val/mean hd95_metric': 5.73392391204834} +Epoch [1518/4000] Training [1/16] Loss: 0.00985 +Epoch [1518/4000] Training [2/16] Loss: 0.00845 +Epoch [1518/4000] Training [3/16] Loss: 0.00995 +Epoch [1518/4000] Training [4/16] Loss: 0.00975 +Epoch [1518/4000] Training [5/16] Loss: 0.00579 +Epoch [1518/4000] Training [6/16] Loss: 0.01082 +Epoch [1518/4000] Training [7/16] Loss: 0.00873 +Epoch [1518/4000] Training [8/16] Loss: 0.00726 +Epoch [1518/4000] Training [9/16] Loss: 0.00565 +Epoch [1518/4000] Training [10/16] Loss: 0.00918 +Epoch [1518/4000] Training [11/16] Loss: 0.00602 +Epoch [1518/4000] Training [12/16] Loss: 0.00759 +Epoch [1518/4000] Training [13/16] Loss: 0.00889 +Epoch [1518/4000] Training [14/16] Loss: 0.01129 +Epoch [1518/4000] Training [15/16] Loss: 0.00713 +Epoch [1518/4000] Training [16/16] Loss: 0.00886 +Epoch [1518/4000] Training metric {'Train/mean dice_metric': 0.9944036602973938, 'Train/mean miou_metric': 0.9886265993118286, 'Train/mean f1': 0.9904448390007019, 'Train/mean precision': 0.9858331084251404, 'Train/mean recall': 0.9950999021530151, 'Train/mean hd95_metric': 1.04623544216156} +Epoch [1518/4000] Validation [1/4] Loss: 0.26361 focal_loss 0.17686 dice_loss 0.08675 +Epoch [1518/4000] Validation [2/4] Loss: 0.37101 focal_loss 0.21336 dice_loss 0.15764 +Epoch [1518/4000] Validation [3/4] Loss: 0.21669 focal_loss 0.13383 dice_loss 0.08287 +Epoch [1518/4000] Validation [4/4] Loss: 0.25036 focal_loss 0.11990 dice_loss 0.13047 +Epoch [1518/4000] Validation metric {'Val/mean dice_metric': 0.9724307060241699, 'Val/mean miou_metric': 0.9541225433349609, 'Val/mean f1': 0.9732763171195984, 'Val/mean precision': 0.9700556993484497, 'Val/mean recall': 0.9765186309814453, 'Val/mean hd95_metric': 5.814326763153076} +Cheakpoint... +Epoch [1518/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724307060241699, 'Val/mean miou_metric': 0.9541225433349609, 'Val/mean f1': 0.9732763171195984, 'Val/mean precision': 0.9700556993484497, 'Val/mean recall': 0.9765186309814453, 'Val/mean hd95_metric': 5.814326763153076} +Epoch [1519/4000] Training [1/16] Loss: 0.00766 +Epoch [1519/4000] Training [2/16] Loss: 0.00655 +Epoch [1519/4000] Training [3/16] Loss: 0.00887 +Epoch [1519/4000] Training [4/16] Loss: 0.01380 +Epoch [1519/4000] Training [5/16] Loss: 0.00892 +Epoch [1519/4000] Training [6/16] Loss: 0.00680 +Epoch [1519/4000] Training [7/16] Loss: 0.00847 +Epoch [1519/4000] Training [8/16] Loss: 0.00799 +Epoch [1519/4000] Training [9/16] Loss: 0.00742 +Epoch [1519/4000] Training [10/16] Loss: 0.01365 +Epoch [1519/4000] Training [11/16] Loss: 0.00877 +Epoch [1519/4000] Training [12/16] Loss: 0.01203 +Epoch [1519/4000] Training [13/16] Loss: 0.00844 +Epoch [1519/4000] Training [14/16] Loss: 0.00888 +Epoch [1519/4000] Training [15/16] Loss: 0.00758 +Epoch [1519/4000] Training [16/16] Loss: 0.01106 +Epoch [1519/4000] Training metric {'Train/mean dice_metric': 0.9937776327133179, 'Train/mean miou_metric': 0.9873908162117004, 'Train/mean f1': 0.9900104999542236, 'Train/mean precision': 0.9853837490081787, 'Train/mean recall': 0.9946808815002441, 'Train/mean hd95_metric': 1.2006261348724365} +Epoch [1519/4000] Validation [1/4] Loss: 0.32745 focal_loss 0.23127 dice_loss 0.09617 +Epoch [1519/4000] Validation [2/4] Loss: 0.43699 focal_loss 0.25943 dice_loss 0.17755 +Epoch [1519/4000] Validation [3/4] Loss: 0.19117 focal_loss 0.11246 dice_loss 0.07871 +Epoch [1519/4000] Validation [4/4] Loss: 0.27944 focal_loss 0.17148 dice_loss 0.10796 +Epoch [1519/4000] Validation metric {'Val/mean dice_metric': 0.9707338213920593, 'Val/mean miou_metric': 0.9520969390869141, 'Val/mean f1': 0.9725699424743652, 'Val/mean precision': 0.9711293578147888, 'Val/mean recall': 0.9740148782730103, 'Val/mean hd95_metric': 5.428982734680176} +Cheakpoint... +Epoch [1519/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707338213920593, 'Val/mean miou_metric': 0.9520969390869141, 'Val/mean f1': 0.9725699424743652, 'Val/mean precision': 0.9711293578147888, 'Val/mean recall': 0.9740148782730103, 'Val/mean hd95_metric': 5.428982734680176} +Epoch [1520/4000] Training [1/16] Loss: 0.00970 +Epoch [1520/4000] Training [2/16] Loss: 0.00874 +Epoch [1520/4000] Training [3/16] Loss: 0.00983 +Epoch [1520/4000] Training [4/16] Loss: 0.00825 +Epoch [1520/4000] Training [5/16] Loss: 0.00786 +Epoch [1520/4000] Training [6/16] Loss: 0.00832 +Epoch [1520/4000] Training [7/16] Loss: 0.00777 +Epoch [1520/4000] Training [8/16] Loss: 0.00796 +Epoch [1520/4000] Training [9/16] Loss: 0.00792 +Epoch [1520/4000] Training [10/16] Loss: 0.01420 +Epoch [1520/4000] Training [11/16] Loss: 0.00758 +Epoch [1520/4000] Training [12/16] Loss: 0.00705 +Epoch [1520/4000] Training [13/16] Loss: 0.00767 +Epoch [1520/4000] Training [14/16] Loss: 0.00857 +Epoch [1520/4000] Training [15/16] Loss: 0.01140 +Epoch [1520/4000] Training [16/16] Loss: 0.00675 +Epoch [1520/4000] Training metric {'Train/mean dice_metric': 0.9941318035125732, 'Train/mean miou_metric': 0.9880832433700562, 'Train/mean f1': 0.9903063774108887, 'Train/mean precision': 0.9856866002082825, 'Train/mean recall': 0.9949696660041809, 'Train/mean hd95_metric': 1.0918474197387695} +Epoch [1520/4000] Validation [1/4] Loss: 0.21934 focal_loss 0.15748 dice_loss 0.06186 +Epoch [1520/4000] Validation [2/4] Loss: 0.44282 focal_loss 0.27771 dice_loss 0.16511 +Epoch [1520/4000] Validation [3/4] Loss: 0.31418 focal_loss 0.21979 dice_loss 0.09439 +Epoch [1520/4000] Validation [4/4] Loss: 0.26755 focal_loss 0.16395 dice_loss 0.10359 +Epoch [1520/4000] Validation metric {'Val/mean dice_metric': 0.9741716384887695, 'Val/mean miou_metric': 0.9564390182495117, 'Val/mean f1': 0.9740632772445679, 'Val/mean precision': 0.9704012274742126, 'Val/mean recall': 0.9777531027793884, 'Val/mean hd95_metric': 5.560659885406494} +Cheakpoint... +Epoch [1520/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741716384887695, 'Val/mean miou_metric': 0.9564390182495117, 'Val/mean f1': 0.9740632772445679, 'Val/mean precision': 0.9704012274742126, 'Val/mean recall': 0.9777531027793884, 'Val/mean hd95_metric': 5.560659885406494} +Epoch [1521/4000] Training [1/16] Loss: 0.00869 +Epoch [1521/4000] Training [2/16] Loss: 0.01100 +Epoch [1521/4000] Training [3/16] Loss: 0.00906 +Epoch [1521/4000] Training [4/16] Loss: 0.00700 +Epoch [1521/4000] Training [5/16] Loss: 0.00994 +Epoch [1521/4000] Training [6/16] Loss: 0.00754 +Epoch [1521/4000] Training [7/16] Loss: 0.00713 +Epoch [1521/4000] Training [8/16] Loss: 0.00815 +Epoch [1521/4000] Training [9/16] Loss: 0.00704 +Epoch [1521/4000] Training [10/16] Loss: 0.00987 +Epoch [1521/4000] Training [11/16] Loss: 0.00978 +Epoch [1521/4000] Training [12/16] Loss: 0.00754 +Epoch [1521/4000] Training [13/16] Loss: 0.00883 +Epoch [1521/4000] Training [14/16] Loss: 0.00664 +Epoch [1521/4000] Training [15/16] Loss: 0.00798 +Epoch [1521/4000] Training [16/16] Loss: 0.00637 +Epoch [1521/4000] Training metric {'Train/mean dice_metric': 0.9944222569465637, 'Train/mean miou_metric': 0.9886565208435059, 'Train/mean f1': 0.9905545711517334, 'Train/mean precision': 0.9861060380935669, 'Train/mean recall': 0.9950433969497681, 'Train/mean hd95_metric': 1.0403386354446411} +Epoch [1521/4000] Validation [1/4] Loss: 0.24334 focal_loss 0.18122 dice_loss 0.06212 +Epoch [1521/4000] Validation [2/4] Loss: 0.31099 focal_loss 0.17932 dice_loss 0.13167 +Epoch [1521/4000] Validation [3/4] Loss: 0.39365 focal_loss 0.28475 dice_loss 0.10890 +Epoch [1521/4000] Validation [4/4] Loss: 0.42814 focal_loss 0.29773 dice_loss 0.13041 +Epoch [1521/4000] Validation metric {'Val/mean dice_metric': 0.9721840620040894, 'Val/mean miou_metric': 0.9541654586791992, 'Val/mean f1': 0.9731064438819885, 'Val/mean precision': 0.9678499698638916, 'Val/mean recall': 0.9784202575683594, 'Val/mean hd95_metric': 6.154516220092773} +Cheakpoint... +Epoch [1521/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721840620040894, 'Val/mean miou_metric': 0.9541654586791992, 'Val/mean f1': 0.9731064438819885, 'Val/mean precision': 0.9678499698638916, 'Val/mean recall': 0.9784202575683594, 'Val/mean hd95_metric': 6.154516220092773} +Epoch [1522/4000] Training [1/16] Loss: 0.00762 +Epoch [1522/4000] Training [2/16] Loss: 0.00671 +Epoch [1522/4000] Training [3/16] Loss: 0.00707 +Epoch [1522/4000] Training [4/16] Loss: 0.00801 +Epoch [1522/4000] Training [5/16] Loss: 0.00773 +Epoch [1522/4000] Training [6/16] Loss: 0.00771 +Epoch [1522/4000] Training [7/16] Loss: 0.00648 +Epoch [1522/4000] Training [8/16] Loss: 0.00974 +Epoch [1522/4000] Training [9/16] Loss: 0.00729 +Epoch [1522/4000] Training [10/16] Loss: 0.00930 +Epoch [1522/4000] Training [11/16] Loss: 0.01003 +Epoch [1522/4000] Training [12/16] Loss: 0.00984 +Epoch [1522/4000] Training [13/16] Loss: 0.00634 +Epoch [1522/4000] Training [14/16] Loss: 0.00884 +Epoch [1522/4000] Training [15/16] Loss: 0.01082 +Epoch [1522/4000] Training [16/16] Loss: 0.00700 +Epoch [1522/4000] Training metric {'Train/mean dice_metric': 0.994697630405426, 'Train/mean miou_metric': 0.9891897439956665, 'Train/mean f1': 0.9906315803527832, 'Train/mean precision': 0.9860414266586304, 'Train/mean recall': 0.9952645897865295, 'Train/mean hd95_metric': 1.2893447875976562} +Epoch [1522/4000] Validation [1/4] Loss: 0.23961 focal_loss 0.17275 dice_loss 0.06686 +Epoch [1522/4000] Validation [2/4] Loss: 0.41625 focal_loss 0.24921 dice_loss 0.16704 +Epoch [1522/4000] Validation [3/4] Loss: 0.30466 focal_loss 0.21319 dice_loss 0.09148 +Epoch [1522/4000] Validation [4/4] Loss: 0.29443 focal_loss 0.17439 dice_loss 0.12004 +Epoch [1522/4000] Validation metric {'Val/mean dice_metric': 0.9728517532348633, 'Val/mean miou_metric': 0.9550024271011353, 'Val/mean f1': 0.9730930924415588, 'Val/mean precision': 0.9687369465827942, 'Val/mean recall': 0.9774885177612305, 'Val/mean hd95_metric': 6.245600700378418} +Cheakpoint... +Epoch [1522/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728517532348633, 'Val/mean miou_metric': 0.9550024271011353, 'Val/mean f1': 0.9730930924415588, 'Val/mean precision': 0.9687369465827942, 'Val/mean recall': 0.9774885177612305, 'Val/mean hd95_metric': 6.245600700378418} +Epoch [1523/4000] Training [1/16] Loss: 0.00882 +Epoch [1523/4000] Training [2/16] Loss: 0.00940 +Epoch [1523/4000] Training [3/16] Loss: 0.00609 +Epoch [1523/4000] Training [4/16] Loss: 0.00754 +Epoch [1523/4000] Training [5/16] Loss: 0.00627 +Epoch [1523/4000] Training [6/16] Loss: 0.00732 +Epoch [1523/4000] Training [7/16] Loss: 0.00771 +Epoch [1523/4000] Training [8/16] Loss: 0.00857 +Epoch [1523/4000] Training [9/16] Loss: 0.00765 +Epoch [1523/4000] Training [10/16] Loss: 0.00694 +Epoch [1523/4000] Training [11/16] Loss: 0.00989 +Epoch [1523/4000] Training [12/16] Loss: 0.00833 +Epoch [1523/4000] Training [13/16] Loss: 0.01298 +Epoch [1523/4000] Training [14/16] Loss: 0.00714 +Epoch [1523/4000] Training [15/16] Loss: 0.00724 +Epoch [1523/4000] Training [16/16] Loss: 0.00990 +Epoch [1523/4000] Training metric {'Train/mean dice_metric': 0.9942711591720581, 'Train/mean miou_metric': 0.9883626103401184, 'Train/mean f1': 0.9903159737586975, 'Train/mean precision': 0.9857944846153259, 'Train/mean recall': 0.9948791265487671, 'Train/mean hd95_metric': 1.1560752391815186} +Epoch [1523/4000] Validation [1/4] Loss: 0.30068 focal_loss 0.22502 dice_loss 0.07566 +Epoch [1523/4000] Validation [2/4] Loss: 0.60274 focal_loss 0.38231 dice_loss 0.22043 +Epoch [1523/4000] Validation [3/4] Loss: 0.34289 focal_loss 0.22985 dice_loss 0.11304 +Epoch [1523/4000] Validation [4/4] Loss: 0.31823 focal_loss 0.20353 dice_loss 0.11470 +Epoch [1523/4000] Validation metric {'Val/mean dice_metric': 0.9708391427993774, 'Val/mean miou_metric': 0.9528841972351074, 'Val/mean f1': 0.9726612567901611, 'Val/mean precision': 0.9724269509315491, 'Val/mean recall': 0.972895622253418, 'Val/mean hd95_metric': 5.678834915161133} +Cheakpoint... +Epoch [1523/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708391427993774, 'Val/mean miou_metric': 0.9528841972351074, 'Val/mean f1': 0.9726612567901611, 'Val/mean precision': 0.9724269509315491, 'Val/mean recall': 0.972895622253418, 'Val/mean hd95_metric': 5.678834915161133} +Epoch [1524/4000] Training [1/16] Loss: 0.00930 +Epoch [1524/4000] Training [2/16] Loss: 0.00705 +Epoch [1524/4000] Training [3/16] Loss: 0.00850 +Epoch [1524/4000] Training [4/16] Loss: 0.00895 +Epoch [1524/4000] Training [5/16] Loss: 0.01161 +Epoch [1524/4000] Training [6/16] Loss: 0.00841 +Epoch [1524/4000] Training [7/16] Loss: 0.00905 +Epoch [1524/4000] Training [8/16] Loss: 0.00749 +Epoch [1524/4000] Training [9/16] Loss: 0.00793 +Epoch [1524/4000] Training [10/16] Loss: 0.00864 +Epoch [1524/4000] Training [11/16] Loss: 0.00811 +Epoch [1524/4000] Training [12/16] Loss: 0.00792 +Epoch [1524/4000] Training [13/16] Loss: 0.00853 +Epoch [1524/4000] Training [14/16] Loss: 0.01092 +Epoch [1524/4000] Training [15/16] Loss: 0.00714 +Epoch [1524/4000] Training [16/16] Loss: 0.00966 +Epoch [1524/4000] Training metric {'Train/mean dice_metric': 0.9940255880355835, 'Train/mean miou_metric': 0.9878532290458679, 'Train/mean f1': 0.98982834815979, 'Train/mean precision': 0.9848857522010803, 'Train/mean recall': 0.994820773601532, 'Train/mean hd95_metric': 1.089388370513916} +Epoch [1524/4000] Validation [1/4] Loss: 0.27690 focal_loss 0.20267 dice_loss 0.07423 +Epoch [1524/4000] Validation [2/4] Loss: 0.31269 focal_loss 0.18321 dice_loss 0.12948 +Epoch [1524/4000] Validation [3/4] Loss: 0.14922 focal_loss 0.09122 dice_loss 0.05801 +Epoch [1524/4000] Validation [4/4] Loss: 0.26980 focal_loss 0.15805 dice_loss 0.11175 +Epoch [1524/4000] Validation metric {'Val/mean dice_metric': 0.9736865162849426, 'Val/mean miou_metric': 0.9557176828384399, 'Val/mean f1': 0.9739725589752197, 'Val/mean precision': 0.9698920845985413, 'Val/mean recall': 0.9780876040458679, 'Val/mean hd95_metric': 5.442682266235352} +Cheakpoint... +Epoch [1524/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736865162849426, 'Val/mean miou_metric': 0.9557176828384399, 'Val/mean f1': 0.9739725589752197, 'Val/mean precision': 0.9698920845985413, 'Val/mean recall': 0.9780876040458679, 'Val/mean hd95_metric': 5.442682266235352} +Epoch [1525/4000] Training [1/16] Loss: 0.00625 +Epoch [1525/4000] Training [2/16] Loss: 0.01092 +Epoch [1525/4000] Training [3/16] Loss: 0.00805 +Epoch [1525/4000] Training [4/16] Loss: 0.00664 +Epoch [1525/4000] Training [5/16] Loss: 0.00882 +Epoch [1525/4000] Training [6/16] Loss: 0.00884 +Epoch [1525/4000] Training [7/16] Loss: 0.00871 +Epoch [1525/4000] Training [8/16] Loss: 0.00835 +Epoch [1525/4000] Training [9/16] Loss: 0.00789 +Epoch [1525/4000] Training [10/16] Loss: 0.00917 +Epoch [1525/4000] Training [11/16] Loss: 0.00849 +Epoch [1525/4000] Training [12/16] Loss: 0.01118 +Epoch [1525/4000] Training [13/16] Loss: 0.00746 +Epoch [1525/4000] Training [14/16] Loss: 0.00700 +Epoch [1525/4000] Training [15/16] Loss: 0.00789 +Epoch [1525/4000] Training [16/16] Loss: 0.00822 +Epoch [1525/4000] Training metric {'Train/mean dice_metric': 0.994479775428772, 'Train/mean miou_metric': 0.9887616634368896, 'Train/mean f1': 0.9904715418815613, 'Train/mean precision': 0.9860149621963501, 'Train/mean recall': 0.994968593120575, 'Train/mean hd95_metric': 1.035146951675415} +Epoch [1525/4000] Validation [1/4] Loss: 0.24934 focal_loss 0.18054 dice_loss 0.06880 +Epoch [1525/4000] Validation [2/4] Loss: 0.46201 focal_loss 0.26408 dice_loss 0.19793 +Epoch [1525/4000] Validation [3/4] Loss: 0.14764 focal_loss 0.09250 dice_loss 0.05514 +Epoch [1525/4000] Validation [4/4] Loss: 0.26145 focal_loss 0.14149 dice_loss 0.11997 +Epoch [1525/4000] Validation metric {'Val/mean dice_metric': 0.9732339978218079, 'Val/mean miou_metric': 0.9560537338256836, 'Val/mean f1': 0.9741008877754211, 'Val/mean precision': 0.9708921313285828, 'Val/mean recall': 0.9773311614990234, 'Val/mean hd95_metric': 4.986429691314697} +Cheakpoint... +Epoch [1525/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732339978218079, 'Val/mean miou_metric': 0.9560537338256836, 'Val/mean f1': 0.9741008877754211, 'Val/mean precision': 0.9708921313285828, 'Val/mean recall': 0.9773311614990234, 'Val/mean hd95_metric': 4.986429691314697} +Epoch [1526/4000] Training [1/16] Loss: 0.00635 +Epoch [1526/4000] Training [2/16] Loss: 0.00832 +Epoch [1526/4000] Training [3/16] Loss: 0.01213 +Epoch [1526/4000] Training [4/16] Loss: 0.00639 +Epoch [1526/4000] Training [5/16] Loss: 0.00819 +Epoch [1526/4000] Training [6/16] Loss: 0.00721 +Epoch [1526/4000] Training [7/16] Loss: 0.00592 +Epoch [1526/4000] Training [8/16] Loss: 0.00667 +Epoch [1526/4000] Training [9/16] Loss: 0.00653 +Epoch [1526/4000] Training [10/16] Loss: 0.00895 +Epoch [1526/4000] Training [11/16] Loss: 0.00875 +Epoch [1526/4000] Training [12/16] Loss: 0.00616 +Epoch [1526/4000] Training [13/16] Loss: 0.00636 +Epoch [1526/4000] Training [14/16] Loss: 0.00739 +Epoch [1526/4000] Training [15/16] Loss: 0.00791 +Epoch [1526/4000] Training [16/16] Loss: 0.00715 +Epoch [1526/4000] Training metric {'Train/mean dice_metric': 0.9949643611907959, 'Train/mean miou_metric': 0.9897289872169495, 'Train/mean f1': 0.9910063743591309, 'Train/mean precision': 0.9864540696144104, 'Train/mean recall': 0.9956009984016418, 'Train/mean hd95_metric': 1.0196144580841064} +Epoch [1526/4000] Validation [1/4] Loss: 0.24170 focal_loss 0.17546 dice_loss 0.06624 +Epoch [1526/4000] Validation [2/4] Loss: 0.35403 focal_loss 0.21447 dice_loss 0.13955 +Epoch [1526/4000] Validation [3/4] Loss: 0.16626 focal_loss 0.09610 dice_loss 0.07017 +Epoch [1526/4000] Validation [4/4] Loss: 0.27714 focal_loss 0.16951 dice_loss 0.10764 +Epoch [1526/4000] Validation metric {'Val/mean dice_metric': 0.9730123281478882, 'Val/mean miou_metric': 0.9553106427192688, 'Val/mean f1': 0.974144697189331, 'Val/mean precision': 0.9709775447845459, 'Val/mean recall': 0.9773326516151428, 'Val/mean hd95_metric': 5.461587905883789} +Cheakpoint... +Epoch [1526/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730123281478882, 'Val/mean miou_metric': 0.9553106427192688, 'Val/mean f1': 0.974144697189331, 'Val/mean precision': 0.9709775447845459, 'Val/mean recall': 0.9773326516151428, 'Val/mean hd95_metric': 5.461587905883789} +Epoch [1527/4000] Training [1/16] Loss: 0.00831 +Epoch [1527/4000] Training [2/16] Loss: 0.00736 +Epoch [1527/4000] Training [3/16] Loss: 0.00813 +Epoch [1527/4000] Training [4/16] Loss: 0.00871 +Epoch [1527/4000] Training [5/16] Loss: 0.00642 +Epoch [1527/4000] Training [6/16] Loss: 0.01094 +Epoch [1527/4000] Training [7/16] Loss: 0.00577 +Epoch [1527/4000] Training [8/16] Loss: 0.00820 +Epoch [1527/4000] Training [9/16] Loss: 0.00735 +Epoch [1527/4000] Training [10/16] Loss: 0.00865 +Epoch [1527/4000] Training [11/16] Loss: 0.00845 +Epoch [1527/4000] Training [12/16] Loss: 0.00662 +Epoch [1527/4000] Training [13/16] Loss: 0.00955 +Epoch [1527/4000] Training [14/16] Loss: 0.00869 +Epoch [1527/4000] Training [15/16] Loss: 0.00768 +Epoch [1527/4000] Training [16/16] Loss: 0.00886 +Epoch [1527/4000] Training metric {'Train/mean dice_metric': 0.9943600296974182, 'Train/mean miou_metric': 0.9885362386703491, 'Train/mean f1': 0.9904918074607849, 'Train/mean precision': 0.9859124422073364, 'Train/mean recall': 0.9951138496398926, 'Train/mean hd95_metric': 1.0582088232040405} +Epoch [1527/4000] Validation [1/4] Loss: 0.22369 focal_loss 0.16034 dice_loss 0.06335 +Epoch [1527/4000] Validation [2/4] Loss: 0.37053 focal_loss 0.22988 dice_loss 0.14065 +Epoch [1527/4000] Validation [3/4] Loss: 0.23974 focal_loss 0.14995 dice_loss 0.08979 +Epoch [1527/4000] Validation [4/4] Loss: 0.37620 focal_loss 0.25075 dice_loss 0.12545 +Epoch [1527/4000] Validation metric {'Val/mean dice_metric': 0.9724327921867371, 'Val/mean miou_metric': 0.9549132585525513, 'Val/mean f1': 0.9733150005340576, 'Val/mean precision': 0.9693173766136169, 'Val/mean recall': 0.9773457646369934, 'Val/mean hd95_metric': 5.440737724304199} +Cheakpoint... +Epoch [1527/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724327921867371, 'Val/mean miou_metric': 0.9549132585525513, 'Val/mean f1': 0.9733150005340576, 'Val/mean precision': 0.9693173766136169, 'Val/mean recall': 0.9773457646369934, 'Val/mean hd95_metric': 5.440737724304199} +Epoch [1528/4000] Training [1/16] Loss: 0.00791 +Epoch [1528/4000] Training [2/16] Loss: 0.00736 +Epoch [1528/4000] Training [3/16] Loss: 0.01082 +Epoch [1528/4000] Training [4/16] Loss: 0.00851 +Epoch [1528/4000] Training [5/16] Loss: 0.00710 +Epoch [1528/4000] Training [6/16] Loss: 0.00759 +Epoch [1528/4000] Training [7/16] Loss: 0.00766 +Epoch [1528/4000] Training [8/16] Loss: 0.00552 +Epoch [1528/4000] Training [9/16] Loss: 0.01392 +Epoch [1528/4000] Training [10/16] Loss: 0.00874 +Epoch [1528/4000] Training [11/16] Loss: 0.00686 +Epoch [1528/4000] Training [12/16] Loss: 0.01225 +Epoch [1528/4000] Training [13/16] Loss: 0.00918 +Epoch [1528/4000] Training [14/16] Loss: 0.01070 +Epoch [1528/4000] Training [15/16] Loss: 0.00927 +Epoch [1528/4000] Training [16/16] Loss: 0.00692 +Epoch [1528/4000] Training metric {'Train/mean dice_metric': 0.9939566254615784, 'Train/mean miou_metric': 0.9877321720123291, 'Train/mean f1': 0.9896080493927002, 'Train/mean precision': 0.9845925569534302, 'Train/mean recall': 0.9946749210357666, 'Train/mean hd95_metric': 1.367375373840332} +Epoch [1528/4000] Validation [1/4] Loss: 0.23072 focal_loss 0.16611 dice_loss 0.06461 +Epoch [1528/4000] Validation [2/4] Loss: 0.42536 focal_loss 0.24031 dice_loss 0.18505 +Epoch [1528/4000] Validation [3/4] Loss: 0.16352 focal_loss 0.09450 dice_loss 0.06902 +Epoch [1528/4000] Validation [4/4] Loss: 0.22904 focal_loss 0.12138 dice_loss 0.10767 +Epoch [1528/4000] Validation metric {'Val/mean dice_metric': 0.9701858758926392, 'Val/mean miou_metric': 0.9524458050727844, 'Val/mean f1': 0.9732223749160767, 'Val/mean precision': 0.969648003578186, 'Val/mean recall': 0.9768233299255371, 'Val/mean hd95_metric': 5.711523056030273} +Cheakpoint... +Epoch [1528/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701858758926392, 'Val/mean miou_metric': 0.9524458050727844, 'Val/mean f1': 0.9732223749160767, 'Val/mean precision': 0.969648003578186, 'Val/mean recall': 0.9768233299255371, 'Val/mean hd95_metric': 5.711523056030273} +Epoch [1529/4000] Training [1/16] Loss: 0.00643 +Epoch [1529/4000] Training [2/16] Loss: 0.00794 +Epoch [1529/4000] Training [3/16] Loss: 0.00571 +Epoch [1529/4000] Training [4/16] Loss: 0.01447 +Epoch [1529/4000] Training [5/16] Loss: 0.00959 +Epoch [1529/4000] Training [6/16] Loss: 0.00983 +Epoch [1529/4000] Training [7/16] Loss: 0.00737 +Epoch [1529/4000] Training [8/16] Loss: 0.00908 +Epoch [1529/4000] Training [9/16] Loss: 0.00760 +Epoch [1529/4000] Training [10/16] Loss: 0.01051 +Epoch [1529/4000] Training [11/16] Loss: 0.00770 +Epoch [1529/4000] Training [12/16] Loss: 0.00608 +Epoch [1529/4000] Training [13/16] Loss: 0.00884 +Epoch [1529/4000] Training [14/16] Loss: 0.01185 +Epoch [1529/4000] Training [15/16] Loss: 0.00658 +Epoch [1529/4000] Training [16/16] Loss: 0.01066 +Epoch [1529/4000] Training metric {'Train/mean dice_metric': 0.9942499399185181, 'Train/mean miou_metric': 0.9882781505584717, 'Train/mean f1': 0.9895955920219421, 'Train/mean precision': 0.9844591021537781, 'Train/mean recall': 0.9947859048843384, 'Train/mean hd95_metric': 1.0748324394226074} +Epoch [1529/4000] Validation [1/4] Loss: 0.32189 focal_loss 0.23712 dice_loss 0.08478 +Epoch [1529/4000] Validation [2/4] Loss: 0.46132 focal_loss 0.27083 dice_loss 0.19049 +Epoch [1529/4000] Validation [3/4] Loss: 0.16125 focal_loss 0.09522 dice_loss 0.06604 +Epoch [1529/4000] Validation [4/4] Loss: 0.21698 focal_loss 0.10426 dice_loss 0.11271 +Epoch [1529/4000] Validation metric {'Val/mean dice_metric': 0.9686581492424011, 'Val/mean miou_metric': 0.9509559869766235, 'Val/mean f1': 0.9722438454627991, 'Val/mean precision': 0.9723109602928162, 'Val/mean recall': 0.9721768498420715, 'Val/mean hd95_metric': 5.077428817749023} +Cheakpoint... +Epoch [1529/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686581492424011, 'Val/mean miou_metric': 0.9509559869766235, 'Val/mean f1': 0.9722438454627991, 'Val/mean precision': 0.9723109602928162, 'Val/mean recall': 0.9721768498420715, 'Val/mean hd95_metric': 5.077428817749023} +Epoch [1530/4000] Training [1/16] Loss: 0.00860 +Epoch [1530/4000] Training [2/16] Loss: 0.00800 +Epoch [1530/4000] Training [3/16] Loss: 0.01002 +Epoch [1530/4000] Training [4/16] Loss: 0.00837 +Epoch [1530/4000] Training [5/16] Loss: 0.00847 +Epoch [1530/4000] Training [6/16] Loss: 0.00887 +Epoch [1530/4000] Training [7/16] Loss: 0.00721 +Epoch [1530/4000] Training [8/16] Loss: 0.00991 +Epoch [1530/4000] Training [9/16] Loss: 0.01067 +Epoch [1530/4000] Training [10/16] Loss: 0.00951 +Epoch [1530/4000] Training [11/16] Loss: 0.00604 +Epoch [1530/4000] Training [12/16] Loss: 0.00939 +Epoch [1530/4000] Training [13/16] Loss: 0.00761 +Epoch [1530/4000] Training [14/16] Loss: 0.00801 +Epoch [1530/4000] Training [15/16] Loss: 0.00875 +Epoch [1530/4000] Training [16/16] Loss: 0.00655 +Epoch [1530/4000] Training metric {'Train/mean dice_metric': 0.994486927986145, 'Train/mean miou_metric': 0.9887841939926147, 'Train/mean f1': 0.9903900027275085, 'Train/mean precision': 0.985814094543457, 'Train/mean recall': 0.9950085878372192, 'Train/mean hd95_metric': 1.0404207706451416} +Epoch [1530/4000] Validation [1/4] Loss: 0.22975 focal_loss 0.15627 dice_loss 0.07348 +Epoch [1530/4000] Validation [2/4] Loss: 0.49923 focal_loss 0.28614 dice_loss 0.21309 +Epoch [1530/4000] Validation [3/4] Loss: 0.17150 focal_loss 0.10763 dice_loss 0.06387 +Epoch [1530/4000] Validation [4/4] Loss: 0.28629 focal_loss 0.15403 dice_loss 0.13225 +Epoch [1530/4000] Validation metric {'Val/mean dice_metric': 0.9683092832565308, 'Val/mean miou_metric': 0.9508986473083496, 'Val/mean f1': 0.9714019298553467, 'Val/mean precision': 0.9703688621520996, 'Val/mean recall': 0.9724369645118713, 'Val/mean hd95_metric': 5.298003673553467} +Cheakpoint... +Epoch [1530/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683092832565308, 'Val/mean miou_metric': 0.9508986473083496, 'Val/mean f1': 0.9714019298553467, 'Val/mean precision': 0.9703688621520996, 'Val/mean recall': 0.9724369645118713, 'Val/mean hd95_metric': 5.298003673553467} +Epoch [1531/4000] Training [1/16] Loss: 0.00998 +Epoch [1531/4000] Training [2/16] Loss: 0.01008 +Epoch [1531/4000] Training [3/16] Loss: 0.00697 +Epoch [1531/4000] Training [4/16] Loss: 0.00729 +Epoch [1531/4000] Training [5/16] Loss: 0.00732 +Epoch [1531/4000] Training [6/16] Loss: 0.00742 +Epoch [1531/4000] Training [7/16] Loss: 0.00537 +Epoch [1531/4000] Training [8/16] Loss: 0.00951 +Epoch [1531/4000] Training [9/16] Loss: 0.00961 +Epoch [1531/4000] Training [10/16] Loss: 0.00775 +Epoch [1531/4000] Training [11/16] Loss: 0.00954 +Epoch [1531/4000] Training [12/16] Loss: 0.01136 +Epoch [1531/4000] Training [13/16] Loss: 0.01145 +Epoch [1531/4000] Training [14/16] Loss: 0.00972 +Epoch [1531/4000] Training [15/16] Loss: 0.00821 +Epoch [1531/4000] Training [16/16] Loss: 0.00982 +Epoch [1531/4000] Training metric {'Train/mean dice_metric': 0.9936789274215698, 'Train/mean miou_metric': 0.9872291684150696, 'Train/mean f1': 0.9901071190834045, 'Train/mean precision': 0.9855176210403442, 'Train/mean recall': 0.9947395324707031, 'Train/mean hd95_metric': 1.1162859201431274} +Epoch [1531/4000] Validation [1/4] Loss: 0.60463 focal_loss 0.48871 dice_loss 0.11592 +Epoch [1531/4000] Validation [2/4] Loss: 0.61999 focal_loss 0.41194 dice_loss 0.20805 +Epoch [1531/4000] Validation [3/4] Loss: 0.35105 focal_loss 0.22833 dice_loss 0.12272 +Epoch [1531/4000] Validation [4/4] Loss: 0.42613 focal_loss 0.29847 dice_loss 0.12767 +Epoch [1531/4000] Validation metric {'Val/mean dice_metric': 0.9644322395324707, 'Val/mean miou_metric': 0.9454366564750671, 'Val/mean f1': 0.9677203297615051, 'Val/mean precision': 0.9739444255828857, 'Val/mean recall': 0.9615753293037415, 'Val/mean hd95_metric': 5.736754894256592} +Cheakpoint... +Epoch [1531/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9644], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9644322395324707, 'Val/mean miou_metric': 0.9454366564750671, 'Val/mean f1': 0.9677203297615051, 'Val/mean precision': 0.9739444255828857, 'Val/mean recall': 0.9615753293037415, 'Val/mean hd95_metric': 5.736754894256592} +Epoch [1532/4000] Training [1/16] Loss: 0.00838 +Epoch [1532/4000] Training [2/16] Loss: 0.00924 +Epoch [1532/4000] Training [3/16] Loss: 0.00862 +Epoch [1532/4000] Training [4/16] Loss: 0.00601 +Epoch [1532/4000] Training [5/16] Loss: 0.00977 +Epoch [1532/4000] Training [6/16] Loss: 0.00832 +Epoch [1532/4000] Training [7/16] Loss: 0.00732 +Epoch [1532/4000] Training [8/16] Loss: 0.00815 +Epoch [1532/4000] Training [9/16] Loss: 0.00919 +Epoch [1532/4000] Training [10/16] Loss: 0.00810 +Epoch [1532/4000] Training [11/16] Loss: 0.00763 +Epoch [1532/4000] Training [12/16] Loss: 0.00798 +Epoch [1532/4000] Training [13/16] Loss: 0.00680 +Epoch [1532/4000] Training [14/16] Loss: 0.00822 +Epoch [1532/4000] Training [15/16] Loss: 0.00647 +Epoch [1532/4000] Training [16/16] Loss: 0.01001 +Epoch [1532/4000] Training metric {'Train/mean dice_metric': 0.9944435954093933, 'Train/mean miou_metric': 0.9887059926986694, 'Train/mean f1': 0.9904415607452393, 'Train/mean precision': 0.9859462380409241, 'Train/mean recall': 0.9949780702590942, 'Train/mean hd95_metric': 1.0910238027572632} +Epoch [1532/4000] Validation [1/4] Loss: 0.27985 focal_loss 0.20473 dice_loss 0.07512 +Epoch [1532/4000] Validation [2/4] Loss: 0.46396 focal_loss 0.28081 dice_loss 0.18315 +Epoch [1532/4000] Validation [3/4] Loss: 0.47217 focal_loss 0.34613 dice_loss 0.12604 +Epoch [1532/4000] Validation [4/4] Loss: 0.29825 focal_loss 0.18976 dice_loss 0.10849 +Epoch [1532/4000] Validation metric {'Val/mean dice_metric': 0.9699380993843079, 'Val/mean miou_metric': 0.9526988863945007, 'Val/mean f1': 0.9729994535446167, 'Val/mean precision': 0.9702799916267395, 'Val/mean recall': 0.9757340550422668, 'Val/mean hd95_metric': 5.7629289627075195} +Cheakpoint... +Epoch [1532/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699380993843079, 'Val/mean miou_metric': 0.9526988863945007, 'Val/mean f1': 0.9729994535446167, 'Val/mean precision': 0.9702799916267395, 'Val/mean recall': 0.9757340550422668, 'Val/mean hd95_metric': 5.7629289627075195} +Epoch [1533/4000] Training [1/16] Loss: 0.00884 +Epoch [1533/4000] Training [2/16] Loss: 0.01175 +Epoch [1533/4000] Training [3/16] Loss: 0.00602 +Epoch [1533/4000] Training [4/16] Loss: 0.00967 +Epoch [1533/4000] Training [5/16] Loss: 0.00740 +Epoch [1533/4000] Training [6/16] Loss: 0.01044 +Epoch [1533/4000] Training [7/16] Loss: 0.00772 +Epoch [1533/4000] Training [8/16] Loss: 0.00783 +Epoch [1533/4000] Training [9/16] Loss: 0.00809 +Epoch [1533/4000] Training [10/16] Loss: 0.00895 +Epoch [1533/4000] Training [11/16] Loss: 0.01140 +Epoch [1533/4000] Training [12/16] Loss: 0.00688 +Epoch [1533/4000] Training [13/16] Loss: 0.00816 +Epoch [1533/4000] Training [14/16] Loss: 0.00833 +Epoch [1533/4000] Training [15/16] Loss: 0.00748 +Epoch [1533/4000] Training [16/16] Loss: 0.01019 +Epoch [1533/4000] Training metric {'Train/mean dice_metric': 0.9940186738967896, 'Train/mean miou_metric': 0.9878826141357422, 'Train/mean f1': 0.9903205633163452, 'Train/mean precision': 0.9859225153923035, 'Train/mean recall': 0.9947580099105835, 'Train/mean hd95_metric': 1.303621530532837} +Epoch [1533/4000] Validation [1/4] Loss: 0.25946 focal_loss 0.18871 dice_loss 0.07076 +Epoch [1533/4000] Validation [2/4] Loss: 0.49939 focal_loss 0.30629 dice_loss 0.19310 +Epoch [1533/4000] Validation [3/4] Loss: 0.34525 focal_loss 0.24640 dice_loss 0.09885 +Epoch [1533/4000] Validation [4/4] Loss: 0.27252 focal_loss 0.13882 dice_loss 0.13370 +Epoch [1533/4000] Validation metric {'Val/mean dice_metric': 0.9705899953842163, 'Val/mean miou_metric': 0.9525812268257141, 'Val/mean f1': 0.9730368852615356, 'Val/mean precision': 0.9695192575454712, 'Val/mean recall': 0.9765801429748535, 'Val/mean hd95_metric': 5.898337364196777} +Cheakpoint... +Epoch [1533/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705899953842163, 'Val/mean miou_metric': 0.9525812268257141, 'Val/mean f1': 0.9730368852615356, 'Val/mean precision': 0.9695192575454712, 'Val/mean recall': 0.9765801429748535, 'Val/mean hd95_metric': 5.898337364196777} +Epoch [1534/4000] Training [1/16] Loss: 0.00770 +Epoch [1534/4000] Training [2/16] Loss: 0.00652 +Epoch [1534/4000] Training [3/16] Loss: 0.00827 +Epoch [1534/4000] Training [4/16] Loss: 0.00884 +Epoch [1534/4000] Training [5/16] Loss: 0.00850 +Epoch [1534/4000] Training [6/16] Loss: 0.00968 +Epoch [1534/4000] Training [7/16] Loss: 0.01052 +Epoch [1534/4000] Training [8/16] Loss: 0.00675 +Epoch [1534/4000] Training [9/16] Loss: 0.00881 +Epoch [1534/4000] Training [10/16] Loss: 0.00961 +Epoch [1534/4000] Training [11/16] Loss: 0.00834 +Epoch [1534/4000] Training [12/16] Loss: 0.00889 +Epoch [1534/4000] Training [13/16] Loss: 0.00621 +Epoch [1534/4000] Training [14/16] Loss: 0.00688 +Epoch [1534/4000] Training [15/16] Loss: 0.00836 +Epoch [1534/4000] Training [16/16] Loss: 0.00648 +Epoch [1534/4000] Training metric {'Train/mean dice_metric': 0.9943391680717468, 'Train/mean miou_metric': 0.9884976148605347, 'Train/mean f1': 0.9902490377426147, 'Train/mean precision': 0.9857505559921265, 'Train/mean recall': 0.9947887659072876, 'Train/mean hd95_metric': 1.2410192489624023} +Epoch [1534/4000] Validation [1/4] Loss: 0.27584 focal_loss 0.19973 dice_loss 0.07610 +Epoch [1534/4000] Validation [2/4] Loss: 0.39251 focal_loss 0.22483 dice_loss 0.16768 +Epoch [1534/4000] Validation [3/4] Loss: 0.50602 focal_loss 0.38244 dice_loss 0.12358 +Epoch [1534/4000] Validation [4/4] Loss: 0.23154 focal_loss 0.13422 dice_loss 0.09731 +Epoch [1534/4000] Validation metric {'Val/mean dice_metric': 0.9707006216049194, 'Val/mean miou_metric': 0.9525512456893921, 'Val/mean f1': 0.9715529680252075, 'Val/mean precision': 0.9659198522567749, 'Val/mean recall': 0.9772521257400513, 'Val/mean hd95_metric': 6.247642517089844} +Cheakpoint... +Epoch [1534/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707006216049194, 'Val/mean miou_metric': 0.9525512456893921, 'Val/mean f1': 0.9715529680252075, 'Val/mean precision': 0.9659198522567749, 'Val/mean recall': 0.9772521257400513, 'Val/mean hd95_metric': 6.247642517089844} +Epoch [1535/4000] Training [1/16] Loss: 0.00699 +Epoch [1535/4000] Training [2/16] Loss: 0.00855 +Epoch [1535/4000] Training [3/16] Loss: 0.00872 +Epoch [1535/4000] Training [4/16] Loss: 0.01197 +Epoch [1535/4000] Training [5/16] Loss: 0.03886 +Epoch [1535/4000] Training [6/16] Loss: 0.01046 +Epoch [1535/4000] Training [7/16] Loss: 0.00611 +Epoch [1535/4000] Training [8/16] Loss: 0.00890 +Epoch [1535/4000] Training [9/16] Loss: 0.01312 +Epoch [1535/4000] Training [10/16] Loss: 0.00783 +Epoch [1535/4000] Training [11/16] Loss: 0.00603 +Epoch [1535/4000] Training [12/16] Loss: 0.00675 +Epoch [1535/4000] Training [13/16] Loss: 0.00774 +Epoch [1535/4000] Training [14/16] Loss: 0.00822 +Epoch [1535/4000] Training [15/16] Loss: 0.01053 +Epoch [1535/4000] Training [16/16] Loss: 0.01090 +Epoch [1535/4000] Training metric {'Train/mean dice_metric': 0.9931716918945312, 'Train/mean miou_metric': 0.9864820241928101, 'Train/mean f1': 0.9891904592514038, 'Train/mean precision': 0.9840288162231445, 'Train/mean recall': 0.9944065809249878, 'Train/mean hd95_metric': 1.378482699394226} +Epoch [1535/4000] Validation [1/4] Loss: 0.23015 focal_loss 0.16025 dice_loss 0.06989 +Epoch [1535/4000] Validation [2/4] Loss: 0.43652 focal_loss 0.25015 dice_loss 0.18637 +Epoch [1535/4000] Validation [3/4] Loss: 0.24702 focal_loss 0.17047 dice_loss 0.07656 +Epoch [1535/4000] Validation [4/4] Loss: 0.28686 focal_loss 0.17903 dice_loss 0.10783 +Epoch [1535/4000] Validation metric {'Val/mean dice_metric': 0.9708903431892395, 'Val/mean miou_metric': 0.9527165293693542, 'Val/mean f1': 0.9720569849014282, 'Val/mean precision': 0.9706198573112488, 'Val/mean recall': 0.9734982848167419, 'Val/mean hd95_metric': 5.367559432983398} +Cheakpoint... +Epoch [1535/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708903431892395, 'Val/mean miou_metric': 0.9527165293693542, 'Val/mean f1': 0.9720569849014282, 'Val/mean precision': 0.9706198573112488, 'Val/mean recall': 0.9734982848167419, 'Val/mean hd95_metric': 5.367559432983398} +Epoch [1536/4000] Training [1/16] Loss: 0.00805 +Epoch [1536/4000] Training [2/16] Loss: 0.00793 +Epoch [1536/4000] Training [3/16] Loss: 0.00640 +Epoch [1536/4000] Training [4/16] Loss: 0.01087 +Epoch [1536/4000] Training [5/16] Loss: 0.00791 +Epoch [1536/4000] Training [6/16] Loss: 0.00665 +Epoch [1536/4000] Training [7/16] Loss: 0.00885 +Epoch [1536/4000] Training [8/16] Loss: 0.00499 +Epoch [1536/4000] Training [9/16] Loss: 0.00731 +Epoch [1536/4000] Training [10/16] Loss: 0.00865 +Epoch [1536/4000] Training [11/16] Loss: 0.00721 +Epoch [1536/4000] Training [12/16] Loss: 0.00967 +Epoch [1536/4000] Training [13/16] Loss: 0.00615 +Epoch [1536/4000] Training [14/16] Loss: 0.00824 +Epoch [1536/4000] Training [15/16] Loss: 0.00779 +Epoch [1536/4000] Training [16/16] Loss: 0.00848 +Epoch [1536/4000] Training metric {'Train/mean dice_metric': 0.9945392608642578, 'Train/mean miou_metric': 0.9888929128646851, 'Train/mean f1': 0.9906492233276367, 'Train/mean precision': 0.9860051274299622, 'Train/mean recall': 0.995337188243866, 'Train/mean hd95_metric': 1.069615364074707} +Epoch [1536/4000] Validation [1/4] Loss: 0.26396 focal_loss 0.19117 dice_loss 0.07279 +Epoch [1536/4000] Validation [2/4] Loss: 0.42674 focal_loss 0.24535 dice_loss 0.18139 +Epoch [1536/4000] Validation [3/4] Loss: 0.14458 focal_loss 0.08983 dice_loss 0.05475 +Epoch [1536/4000] Validation [4/4] Loss: 0.26437 focal_loss 0.15323 dice_loss 0.11113 +Epoch [1536/4000] Validation metric {'Val/mean dice_metric': 0.9711330533027649, 'Val/mean miou_metric': 0.9538410305976868, 'Val/mean f1': 0.9731363654136658, 'Val/mean precision': 0.9723566770553589, 'Val/mean recall': 0.9739172458648682, 'Val/mean hd95_metric': 5.334652423858643} +Cheakpoint... +Epoch [1536/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711330533027649, 'Val/mean miou_metric': 0.9538410305976868, 'Val/mean f1': 0.9731363654136658, 'Val/mean precision': 0.9723566770553589, 'Val/mean recall': 0.9739172458648682, 'Val/mean hd95_metric': 5.334652423858643} +Epoch [1537/4000] Training [1/16] Loss: 0.00745 +Epoch [1537/4000] Training [2/16] Loss: 0.00746 +Epoch [1537/4000] Training [3/16] Loss: 0.00577 +Epoch [1537/4000] Training [4/16] Loss: 0.01052 +Epoch [1537/4000] Training [5/16] Loss: 0.01199 +Epoch [1537/4000] Training [6/16] Loss: 0.00649 +Epoch [1537/4000] Training [7/16] Loss: 0.00603 +Epoch [1537/4000] Training [8/16] Loss: 0.00713 +Epoch [1537/4000] Training [9/16] Loss: 0.00943 +Epoch [1537/4000] Training [10/16] Loss: 0.00760 +Epoch [1537/4000] Training [11/16] Loss: 0.00860 +Epoch [1537/4000] Training [12/16] Loss: 0.00835 +Epoch [1537/4000] Training [13/16] Loss: 0.01298 +Epoch [1537/4000] Training [14/16] Loss: 0.00868 +Epoch [1537/4000] Training [15/16] Loss: 0.00700 +Epoch [1537/4000] Training [16/16] Loss: 0.00904 +Epoch [1537/4000] Training metric {'Train/mean dice_metric': 0.9933258295059204, 'Train/mean miou_metric': 0.9870162010192871, 'Train/mean f1': 0.9897786378860474, 'Train/mean precision': 0.985701858997345, 'Train/mean recall': 0.9938892126083374, 'Train/mean hd95_metric': 1.2785156965255737} +Epoch [1537/4000] Validation [1/4] Loss: 0.30263 focal_loss 0.22530 dice_loss 0.07733 +Epoch [1537/4000] Validation [2/4] Loss: 0.26176 focal_loss 0.13593 dice_loss 0.12583 +Epoch [1537/4000] Validation [3/4] Loss: 0.16935 focal_loss 0.10598 dice_loss 0.06338 +Epoch [1537/4000] Validation [4/4] Loss: 0.30322 focal_loss 0.18670 dice_loss 0.11652 +Epoch [1537/4000] Validation metric {'Val/mean dice_metric': 0.972705066204071, 'Val/mean miou_metric': 0.9544330835342407, 'Val/mean f1': 0.9730717539787292, 'Val/mean precision': 0.9666451215744019, 'Val/mean recall': 0.9795843958854675, 'Val/mean hd95_metric': 5.840479850769043} +Cheakpoint... +Epoch [1537/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972705066204071, 'Val/mean miou_metric': 0.9544330835342407, 'Val/mean f1': 0.9730717539787292, 'Val/mean precision': 0.9666451215744019, 'Val/mean recall': 0.9795843958854675, 'Val/mean hd95_metric': 5.840479850769043} +Epoch [1538/4000] Training [1/16] Loss: 0.00913 +Epoch [1538/4000] Training [2/16] Loss: 0.00696 +Epoch [1538/4000] Training [3/16] Loss: 0.00716 +Epoch [1538/4000] Training [4/16] Loss: 0.00837 +Epoch [1538/4000] Training [5/16] Loss: 0.00629 +Epoch [1538/4000] Training [6/16] Loss: 0.01130 +Epoch [1538/4000] Training [7/16] Loss: 0.00664 +Epoch [1538/4000] Training [8/16] Loss: 0.00739 +Epoch [1538/4000] Training [9/16] Loss: 0.01146 +Epoch [1538/4000] Training [10/16] Loss: 0.00704 +Epoch [1538/4000] Training [11/16] Loss: 0.00914 +Epoch [1538/4000] Training [12/16] Loss: 0.00738 +Epoch [1538/4000] Training [13/16] Loss: 0.01151 +Epoch [1538/4000] Training [14/16] Loss: 0.00842 +Epoch [1538/4000] Training [15/16] Loss: 0.00713 +Epoch [1538/4000] Training [16/16] Loss: 0.00753 +Epoch [1538/4000] Training metric {'Train/mean dice_metric': 0.9942757487297058, 'Train/mean miou_metric': 0.9883872270584106, 'Train/mean f1': 0.9900004863739014, 'Train/mean precision': 0.9852105379104614, 'Train/mean recall': 0.99483722448349, 'Train/mean hd95_metric': 2.1930060386657715} +Epoch [1538/4000] Validation [1/4] Loss: 0.25205 focal_loss 0.17873 dice_loss 0.07332 +Epoch [1538/4000] Validation [2/4] Loss: 0.60175 focal_loss 0.34388 dice_loss 0.25788 +Epoch [1538/4000] Validation [3/4] Loss: 0.21695 focal_loss 0.13032 dice_loss 0.08663 +Epoch [1538/4000] Validation [4/4] Loss: 0.30451 focal_loss 0.17025 dice_loss 0.13426 +Epoch [1538/4000] Validation metric {'Val/mean dice_metric': 0.968087375164032, 'Val/mean miou_metric': 0.9498814344406128, 'Val/mean f1': 0.9678585529327393, 'Val/mean precision': 0.9585409760475159, 'Val/mean recall': 0.9773590564727783, 'Val/mean hd95_metric': 7.891252040863037} +Cheakpoint... +Epoch [1538/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968087375164032, 'Val/mean miou_metric': 0.9498814344406128, 'Val/mean f1': 0.9678585529327393, 'Val/mean precision': 0.9585409760475159, 'Val/mean recall': 0.9773590564727783, 'Val/mean hd95_metric': 7.891252040863037} +Epoch [1539/4000] Training [1/16] Loss: 0.01224 +Epoch [1539/4000] Training [2/16] Loss: 0.00818 +Epoch [1539/4000] Training [3/16] Loss: 0.00803 +Epoch [1539/4000] Training [4/16] Loss: 0.01040 +Epoch [1539/4000] Training [5/16] Loss: 0.01032 +Epoch [1539/4000] Training [6/16] Loss: 0.01198 +Epoch [1539/4000] Training [7/16] Loss: 0.01520 +Epoch [1539/4000] Training [8/16] Loss: 0.00768 +Epoch [1539/4000] Training [9/16] Loss: 0.00789 +Epoch [1539/4000] Training [10/16] Loss: 0.00645 +Epoch [1539/4000] Training [11/16] Loss: 0.00730 +Epoch [1539/4000] Training [12/16] Loss: 0.00613 +Epoch [1539/4000] Training [13/16] Loss: 0.00810 +Epoch [1539/4000] Training [14/16] Loss: 0.00814 +Epoch [1539/4000] Training [15/16] Loss: 0.00827 +Epoch [1539/4000] Training [16/16] Loss: 0.00708 +Epoch [1539/4000] Training metric {'Train/mean dice_metric': 0.994291365146637, 'Train/mean miou_metric': 0.9884091019630432, 'Train/mean f1': 0.9903251528739929, 'Train/mean precision': 0.9858383536338806, 'Train/mean recall': 0.9948529601097107, 'Train/mean hd95_metric': 1.1321109533309937} +Epoch [1539/4000] Validation [1/4] Loss: 0.21016 focal_loss 0.14185 dice_loss 0.06830 +Epoch [1539/4000] Validation [2/4] Loss: 0.34521 focal_loss 0.18997 dice_loss 0.15524 +Epoch [1539/4000] Validation [3/4] Loss: 0.28364 focal_loss 0.18865 dice_loss 0.09499 +Epoch [1539/4000] Validation [4/4] Loss: 0.29674 focal_loss 0.16675 dice_loss 0.12999 +Epoch [1539/4000] Validation metric {'Val/mean dice_metric': 0.9696977734565735, 'Val/mean miou_metric': 0.9513823390007019, 'Val/mean f1': 0.9685319662094116, 'Val/mean precision': 0.960381805896759, 'Val/mean recall': 0.976821780204773, 'Val/mean hd95_metric': 6.754965305328369} +Cheakpoint... +Epoch [1539/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696977734565735, 'Val/mean miou_metric': 0.9513823390007019, 'Val/mean f1': 0.9685319662094116, 'Val/mean precision': 0.960381805896759, 'Val/mean recall': 0.976821780204773, 'Val/mean hd95_metric': 6.754965305328369} +Epoch [1540/4000] Training [1/16] Loss: 0.01141 +Epoch [1540/4000] Training [2/16] Loss: 0.01072 +Epoch [1540/4000] Training [3/16] Loss: 0.01024 +Epoch [1540/4000] Training [4/16] Loss: 0.00686 +Epoch [1540/4000] Training [5/16] Loss: 0.00545 +Epoch [1540/4000] Training [6/16] Loss: 0.01075 +Epoch [1540/4000] Training [7/16] Loss: 0.00968 +Epoch [1540/4000] Training [8/16] Loss: 0.00853 +Epoch [1540/4000] Training [9/16] Loss: 0.00638 +Epoch [1540/4000] Training [10/16] Loss: 0.00704 +Epoch [1540/4000] Training [11/16] Loss: 0.00791 +Epoch [1540/4000] Training [12/16] Loss: 0.01527 +Epoch [1540/4000] Training [13/16] Loss: 0.01168 +Epoch [1540/4000] Training [14/16] Loss: 0.00671 +Epoch [1540/4000] Training [15/16] Loss: 0.00849 +Epoch [1540/4000] Training [16/16] Loss: 0.00670 +Epoch [1540/4000] Training metric {'Train/mean dice_metric': 0.9944139122962952, 'Train/mean miou_metric': 0.9886190295219421, 'Train/mean f1': 0.9900408983230591, 'Train/mean precision': 0.9850857257843018, 'Train/mean recall': 0.9950462579727173, 'Train/mean hd95_metric': 1.196422815322876} +Epoch [1540/4000] Validation [1/4] Loss: 0.23770 focal_loss 0.17457 dice_loss 0.06312 +Epoch [1540/4000] Validation [2/4] Loss: 0.35240 focal_loss 0.19558 dice_loss 0.15682 +Epoch [1540/4000] Validation [3/4] Loss: 0.17741 focal_loss 0.10555 dice_loss 0.07185 +Epoch [1540/4000] Validation [4/4] Loss: 0.19907 focal_loss 0.11553 dice_loss 0.08354 +Epoch [1540/4000] Validation metric {'Val/mean dice_metric': 0.971178412437439, 'Val/mean miou_metric': 0.9537577629089355, 'Val/mean f1': 0.9700887799263, 'Val/mean precision': 0.9606840014457703, 'Val/mean recall': 0.9796794056892395, 'Val/mean hd95_metric': 6.464046478271484} +Cheakpoint... +Epoch [1540/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971178412437439, 'Val/mean miou_metric': 0.9537577629089355, 'Val/mean f1': 0.9700887799263, 'Val/mean precision': 0.9606840014457703, 'Val/mean recall': 0.9796794056892395, 'Val/mean hd95_metric': 6.464046478271484} +Epoch [1541/4000] Training [1/16] Loss: 0.00814 +Epoch [1541/4000] Training [2/16] Loss: 0.00586 +Epoch [1541/4000] Training [3/16] Loss: 0.00746 +Epoch [1541/4000] Training [4/16] Loss: 0.00799 +Epoch [1541/4000] Training [5/16] Loss: 0.00928 +Epoch [1541/4000] Training [6/16] Loss: 0.00834 +Epoch [1541/4000] Training [7/16] Loss: 0.00646 +Epoch [1541/4000] Training [8/16] Loss: 0.00866 +Epoch [1541/4000] Training [9/16] Loss: 0.00539 +Epoch [1541/4000] Training [10/16] Loss: 0.00892 +Epoch [1541/4000] Training [11/16] Loss: 0.00838 +Epoch [1541/4000] Training [12/16] Loss: 0.00916 +Epoch [1541/4000] Training [13/16] Loss: 0.00610 +Epoch [1541/4000] Training [14/16] Loss: 0.00866 +Epoch [1541/4000] Training [15/16] Loss: 0.00707 +Epoch [1541/4000] Training [16/16] Loss: 0.00915 +Epoch [1541/4000] Training metric {'Train/mean dice_metric': 0.9946454763412476, 'Train/mean miou_metric': 0.9890779852867126, 'Train/mean f1': 0.9903513789176941, 'Train/mean precision': 0.9855344891548157, 'Train/mean recall': 0.9952155351638794, 'Train/mean hd95_metric': 1.0339112281799316} +Epoch [1541/4000] Validation [1/4] Loss: 0.26510 focal_loss 0.19898 dice_loss 0.06612 +Epoch [1541/4000] Validation [2/4] Loss: 0.30557 focal_loss 0.17392 dice_loss 0.13166 +Epoch [1541/4000] Validation [3/4] Loss: 0.17465 focal_loss 0.10645 dice_loss 0.06820 +Epoch [1541/4000] Validation [4/4] Loss: 0.28330 focal_loss 0.17497 dice_loss 0.10833 +Epoch [1541/4000] Validation metric {'Val/mean dice_metric': 0.9728354215621948, 'Val/mean miou_metric': 0.9550184011459351, 'Val/mean f1': 0.9718451499938965, 'Val/mean precision': 0.964928388595581, 'Val/mean recall': 0.9788616895675659, 'Val/mean hd95_metric': 6.200484275817871} +Cheakpoint... +Epoch [1541/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728354215621948, 'Val/mean miou_metric': 0.9550184011459351, 'Val/mean f1': 0.9718451499938965, 'Val/mean precision': 0.964928388595581, 'Val/mean recall': 0.9788616895675659, 'Val/mean hd95_metric': 6.200484275817871} +Epoch [1542/4000] Training [1/16] Loss: 0.00927 +Epoch [1542/4000] Training [2/16] Loss: 0.01168 +Epoch [1542/4000] Training [3/16] Loss: 0.01029 +Epoch [1542/4000] Training [4/16] Loss: 0.00871 +Epoch [1542/4000] Training [5/16] Loss: 0.00930 +Epoch [1542/4000] Training [6/16] Loss: 0.00789 +Epoch [1542/4000] Training [7/16] Loss: 0.00811 +Epoch [1542/4000] Training [8/16] Loss: 0.00686 +Epoch [1542/4000] Training [9/16] Loss: 0.00820 +Epoch [1542/4000] Training [10/16] Loss: 0.00630 +Epoch [1542/4000] Training [11/16] Loss: 0.00979 +Epoch [1542/4000] Training [12/16] Loss: 0.00752 +Epoch [1542/4000] Training [13/16] Loss: 0.00641 +Epoch [1542/4000] Training [14/16] Loss: 0.00885 +Epoch [1542/4000] Training [15/16] Loss: 0.00737 +Epoch [1542/4000] Training [16/16] Loss: 0.00646 +Epoch [1542/4000] Training metric {'Train/mean dice_metric': 0.9946210384368896, 'Train/mean miou_metric': 0.9890437126159668, 'Train/mean f1': 0.9906151294708252, 'Train/mean precision': 0.9860731363296509, 'Train/mean recall': 0.9951990842819214, 'Train/mean hd95_metric': 1.0474334955215454} +Epoch [1542/4000] Validation [1/4] Loss: 0.21861 focal_loss 0.15151 dice_loss 0.06710 +Epoch [1542/4000] Validation [2/4] Loss: 0.25223 focal_loss 0.13707 dice_loss 0.11516 +Epoch [1542/4000] Validation [3/4] Loss: 0.16913 focal_loss 0.10533 dice_loss 0.06381 +Epoch [1542/4000] Validation [4/4] Loss: 0.23749 focal_loss 0.11797 dice_loss 0.11952 +Epoch [1542/4000] Validation metric {'Val/mean dice_metric': 0.9725099802017212, 'Val/mean miou_metric': 0.9552428126335144, 'Val/mean f1': 0.97157883644104, 'Val/mean precision': 0.9637467861175537, 'Val/mean recall': 0.9795393347740173, 'Val/mean hd95_metric': 5.8780598640441895} +Cheakpoint... +Epoch [1542/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725099802017212, 'Val/mean miou_metric': 0.9552428126335144, 'Val/mean f1': 0.97157883644104, 'Val/mean precision': 0.9637467861175537, 'Val/mean recall': 0.9795393347740173, 'Val/mean hd95_metric': 5.8780598640441895} +Epoch [1543/4000] Training [1/16] Loss: 0.00520 +Epoch [1543/4000] Training [2/16] Loss: 0.00743 +Epoch [1543/4000] Training [3/16] Loss: 0.00810 +Epoch [1543/4000] Training [4/16] Loss: 0.00687 +Epoch [1543/4000] Training [5/16] Loss: 0.00661 +Epoch [1543/4000] Training [6/16] Loss: 0.00663 +Epoch [1543/4000] Training [7/16] Loss: 0.00655 +Epoch [1543/4000] Training [8/16] Loss: 0.00711 +Epoch [1543/4000] Training [9/16] Loss: 0.00778 +Epoch [1543/4000] Training [10/16] Loss: 0.00803 +Epoch [1543/4000] Training [11/16] Loss: 0.00599 +Epoch [1543/4000] Training [12/16] Loss: 0.00559 +Epoch [1543/4000] Training [13/16] Loss: 0.00844 +Epoch [1543/4000] Training [14/16] Loss: 0.00617 +Epoch [1543/4000] Training [15/16] Loss: 0.00709 +Epoch [1543/4000] Training [16/16] Loss: 0.00606 +Epoch [1543/4000] Training metric {'Train/mean dice_metric': 0.9952039122581482, 'Train/mean miou_metric': 0.9901964068412781, 'Train/mean f1': 0.9912136197090149, 'Train/mean precision': 0.9866255521774292, 'Train/mean recall': 0.9958445429801941, 'Train/mean hd95_metric': 1.010434865951538} +Epoch [1543/4000] Validation [1/4] Loss: 0.26929 focal_loss 0.19426 dice_loss 0.07504 +Epoch [1543/4000] Validation [2/4] Loss: 0.25485 focal_loss 0.13750 dice_loss 0.11735 +Epoch [1543/4000] Validation [3/4] Loss: 0.19771 focal_loss 0.11382 dice_loss 0.08390 +Epoch [1543/4000] Validation [4/4] Loss: 0.29767 focal_loss 0.16910 dice_loss 0.12857 +Epoch [1543/4000] Validation metric {'Val/mean dice_metric': 0.9734244346618652, 'Val/mean miou_metric': 0.9562527537345886, 'Val/mean f1': 0.9727988839149475, 'Val/mean precision': 0.966548502445221, 'Val/mean recall': 0.9791305661201477, 'Val/mean hd95_metric': 5.7335944175720215} +Cheakpoint... +Epoch [1543/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734244346618652, 'Val/mean miou_metric': 0.9562527537345886, 'Val/mean f1': 0.9727988839149475, 'Val/mean precision': 0.966548502445221, 'Val/mean recall': 0.9791305661201477, 'Val/mean hd95_metric': 5.7335944175720215} +Epoch [1544/4000] Training [1/16] Loss: 0.00630 +Epoch [1544/4000] Training [2/16] Loss: 0.00550 +Epoch [1544/4000] Training [3/16] Loss: 0.00738 +Epoch [1544/4000] Training [4/16] Loss: 0.00632 +Epoch [1544/4000] Training [5/16] Loss: 0.00743 +Epoch [1544/4000] Training [6/16] Loss: 0.00787 +Epoch [1544/4000] Training [7/16] Loss: 0.00836 +Epoch [1544/4000] Training [8/16] Loss: 0.00850 +Epoch [1544/4000] Training [9/16] Loss: 0.00801 +Epoch [1544/4000] Training [10/16] Loss: 0.00848 +Epoch [1544/4000] Training [11/16] Loss: 0.00637 +Epoch [1544/4000] Training [12/16] Loss: 0.00966 +Epoch [1544/4000] Training [13/16] Loss: 0.00748 +Epoch [1544/4000] Training [14/16] Loss: 0.00915 +Epoch [1544/4000] Training [15/16] Loss: 0.00578 +Epoch [1544/4000] Training [16/16] Loss: 0.00735 +Epoch [1544/4000] Training metric {'Train/mean dice_metric': 0.9949724674224854, 'Train/mean miou_metric': 0.9897266626358032, 'Train/mean f1': 0.9907986521720886, 'Train/mean precision': 0.9860794544219971, 'Train/mean recall': 0.995563268661499, 'Train/mean hd95_metric': 1.0190739631652832} +Epoch [1544/4000] Validation [1/4] Loss: 0.23408 focal_loss 0.17043 dice_loss 0.06365 +Epoch [1544/4000] Validation [2/4] Loss: 0.30102 focal_loss 0.15925 dice_loss 0.14177 +Epoch [1544/4000] Validation [3/4] Loss: 0.15543 focal_loss 0.09841 dice_loss 0.05702 +Epoch [1544/4000] Validation [4/4] Loss: 0.34318 focal_loss 0.20508 dice_loss 0.13810 +Epoch [1544/4000] Validation metric {'Val/mean dice_metric': 0.972579300403595, 'Val/mean miou_metric': 0.9550842046737671, 'Val/mean f1': 0.9727874994277954, 'Val/mean precision': 0.968055248260498, 'Val/mean recall': 0.9775663018226624, 'Val/mean hd95_metric': 5.4017205238342285} +Cheakpoint... +Epoch [1544/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972579300403595, 'Val/mean miou_metric': 0.9550842046737671, 'Val/mean f1': 0.9727874994277954, 'Val/mean precision': 0.968055248260498, 'Val/mean recall': 0.9775663018226624, 'Val/mean hd95_metric': 5.4017205238342285} +Epoch [1545/4000] Training [1/16] Loss: 0.00787 +Epoch [1545/4000] Training [2/16] Loss: 0.01215 +Epoch [1545/4000] Training [3/16] Loss: 0.00744 +Epoch [1545/4000] Training [4/16] Loss: 0.00699 +Epoch [1545/4000] Training [5/16] Loss: 0.00572 +Epoch [1545/4000] Training [6/16] Loss: 0.00655 +Epoch [1545/4000] Training [7/16] Loss: 0.00775 +Epoch [1545/4000] Training [8/16] Loss: 0.00761 +Epoch [1545/4000] Training [9/16] Loss: 0.00734 +Epoch [1545/4000] Training [10/16] Loss: 0.00804 +Epoch [1545/4000] Training [11/16] Loss: 0.00757 +Epoch [1545/4000] Training [12/16] Loss: 0.00649 +Epoch [1545/4000] Training [13/16] Loss: 0.00758 +Epoch [1545/4000] Training [14/16] Loss: 0.00782 +Epoch [1545/4000] Training [15/16] Loss: 0.00951 +Epoch [1545/4000] Training [16/16] Loss: 0.00841 +Epoch [1545/4000] Training metric {'Train/mean dice_metric': 0.9947402477264404, 'Train/mean miou_metric': 0.9892803430557251, 'Train/mean f1': 0.9905692338943481, 'Train/mean precision': 0.9861441254615784, 'Train/mean recall': 0.9950342178344727, 'Train/mean hd95_metric': 1.264435887336731} +Epoch [1545/4000] Validation [1/4] Loss: 0.20329 focal_loss 0.14086 dice_loss 0.06243 +Epoch [1545/4000] Validation [2/4] Loss: 0.49741 focal_loss 0.30263 dice_loss 0.19478 +Epoch [1545/4000] Validation [3/4] Loss: 0.32186 focal_loss 0.22113 dice_loss 0.10073 +Epoch [1545/4000] Validation [4/4] Loss: 0.33259 focal_loss 0.19694 dice_loss 0.13565 +Epoch [1545/4000] Validation metric {'Val/mean dice_metric': 0.9714828729629517, 'Val/mean miou_metric': 0.9538087844848633, 'Val/mean f1': 0.9734517931938171, 'Val/mean precision': 0.9682808518409729, 'Val/mean recall': 0.9786783456802368, 'Val/mean hd95_metric': 6.403693199157715} +Cheakpoint... +Epoch [1545/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714828729629517, 'Val/mean miou_metric': 0.9538087844848633, 'Val/mean f1': 0.9734517931938171, 'Val/mean precision': 0.9682808518409729, 'Val/mean recall': 0.9786783456802368, 'Val/mean hd95_metric': 6.403693199157715} +Epoch [1546/4000] Training [1/16] Loss: 0.00861 +Epoch [1546/4000] Training [2/16] Loss: 0.00691 +Epoch [1546/4000] Training [3/16] Loss: 0.00962 +Epoch [1546/4000] Training [4/16] Loss: 0.00825 +Epoch [1546/4000] Training [5/16] Loss: 0.00882 +Epoch [1546/4000] Training [6/16] Loss: 0.00732 +Epoch [1546/4000] Training [7/16] Loss: 0.00856 +Epoch [1546/4000] Training [8/16] Loss: 0.01069 +Epoch [1546/4000] Training [9/16] Loss: 0.00964 +Epoch [1546/4000] Training [10/16] Loss: 0.00712 +Epoch [1546/4000] Training [11/16] Loss: 0.00793 +Epoch [1546/4000] Training [12/16] Loss: 0.00694 +Epoch [1546/4000] Training [13/16] Loss: 0.00909 +Epoch [1546/4000] Training [14/16] Loss: 0.00774 +Epoch [1546/4000] Training [15/16] Loss: 0.00940 +Epoch [1546/4000] Training [16/16] Loss: 0.00845 +Epoch [1546/4000] Training metric {'Train/mean dice_metric': 0.993443489074707, 'Train/mean miou_metric': 0.987083911895752, 'Train/mean f1': 0.9898784160614014, 'Train/mean precision': 0.9852619767189026, 'Train/mean recall': 0.9945382475852966, 'Train/mean hd95_metric': 1.164684534072876} +Epoch [1546/4000] Validation [1/4] Loss: 0.24369 focal_loss 0.17571 dice_loss 0.06799 +Epoch [1546/4000] Validation [2/4] Loss: 0.32561 focal_loss 0.20055 dice_loss 0.12506 +Epoch [1546/4000] Validation [3/4] Loss: 0.26218 focal_loss 0.18010 dice_loss 0.08209 +Epoch [1546/4000] Validation [4/4] Loss: 0.31447 focal_loss 0.18987 dice_loss 0.12461 +Epoch [1546/4000] Validation metric {'Val/mean dice_metric': 0.9716312289237976, 'Val/mean miou_metric': 0.953369140625, 'Val/mean f1': 0.9731795191764832, 'Val/mean precision': 0.9684160947799683, 'Val/mean recall': 0.9779900908470154, 'Val/mean hd95_metric': 5.6631693840026855} +Cheakpoint... +Epoch [1546/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716312289237976, 'Val/mean miou_metric': 0.953369140625, 'Val/mean f1': 0.9731795191764832, 'Val/mean precision': 0.9684160947799683, 'Val/mean recall': 0.9779900908470154, 'Val/mean hd95_metric': 5.6631693840026855} +Epoch [1547/4000] Training [1/16] Loss: 0.00756 +Epoch [1547/4000] Training [2/16] Loss: 0.00853 +Epoch [1547/4000] Training [3/16] Loss: 0.00663 +Epoch [1547/4000] Training [4/16] Loss: 0.00837 +Epoch [1547/4000] Training [5/16] Loss: 0.00750 +Epoch [1547/4000] Training [6/16] Loss: 0.00814 +Epoch [1547/4000] Training [7/16] Loss: 0.00713 +Epoch [1547/4000] Training [8/16] Loss: 0.00722 +Epoch [1547/4000] Training [9/16] Loss: 0.00911 +Epoch [1547/4000] Training [10/16] Loss: 0.02057 +Epoch [1547/4000] Training [11/16] Loss: 0.00908 +Epoch [1547/4000] Training [12/16] Loss: 0.00758 +Epoch [1547/4000] Training [13/16] Loss: 0.00694 +Epoch [1547/4000] Training [14/16] Loss: 0.00926 +Epoch [1547/4000] Training [15/16] Loss: 0.00789 +Epoch [1547/4000] Training [16/16] Loss: 0.00750 +Epoch [1547/4000] Training metric {'Train/mean dice_metric': 0.994193434715271, 'Train/mean miou_metric': 0.988254189491272, 'Train/mean f1': 0.9904793500900269, 'Train/mean precision': 0.9858689904212952, 'Train/mean recall': 0.9951329827308655, 'Train/mean hd95_metric': 1.1468303203582764} +Epoch [1547/4000] Validation [1/4] Loss: 0.27294 focal_loss 0.20116 dice_loss 0.07178 +Epoch [1547/4000] Validation [2/4] Loss: 0.48253 focal_loss 0.28731 dice_loss 0.19521 +Epoch [1547/4000] Validation [3/4] Loss: 0.31234 focal_loss 0.22051 dice_loss 0.09183 +Epoch [1547/4000] Validation [4/4] Loss: 0.23535 focal_loss 0.15138 dice_loss 0.08397 +Epoch [1547/4000] Validation metric {'Val/mean dice_metric': 0.9712988138198853, 'Val/mean miou_metric': 0.9535864591598511, 'Val/mean f1': 0.9735016226768494, 'Val/mean precision': 0.9700811505317688, 'Val/mean recall': 0.9769462943077087, 'Val/mean hd95_metric': 5.646702289581299} +Cheakpoint... +Epoch [1547/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712988138198853, 'Val/mean miou_metric': 0.9535864591598511, 'Val/mean f1': 0.9735016226768494, 'Val/mean precision': 0.9700811505317688, 'Val/mean recall': 0.9769462943077087, 'Val/mean hd95_metric': 5.646702289581299} +Epoch [1548/4000] Training [1/16] Loss: 0.00958 +Epoch [1548/4000] Training [2/16] Loss: 0.00877 +Epoch [1548/4000] Training [3/16] Loss: 0.01048 +Epoch [1548/4000] Training [4/16] Loss: 0.01128 +Epoch [1548/4000] Training [5/16] Loss: 0.00743 +Epoch [1548/4000] Training [6/16] Loss: 0.00761 +Epoch [1548/4000] Training [7/16] Loss: 0.00935 +Epoch [1548/4000] Training [8/16] Loss: 0.00588 +Epoch [1548/4000] Training [9/16] Loss: 0.00813 +Epoch [1548/4000] Training [10/16] Loss: 0.00617 +Epoch [1548/4000] Training [11/16] Loss: 0.00744 +Epoch [1548/4000] Training [12/16] Loss: 0.00958 +Epoch [1548/4000] Training [13/16] Loss: 0.00868 +Epoch [1548/4000] Training [14/16] Loss: 0.00842 +Epoch [1548/4000] Training [15/16] Loss: 0.00894 +Epoch [1548/4000] Training [16/16] Loss: 0.00653 +Epoch [1548/4000] Training metric {'Train/mean dice_metric': 0.9944395422935486, 'Train/mean miou_metric': 0.9886531829833984, 'Train/mean f1': 0.9899126887321472, 'Train/mean precision': 0.98491370677948, 'Train/mean recall': 0.9949626326560974, 'Train/mean hd95_metric': 1.0786616802215576} +Epoch [1548/4000] Validation [1/4] Loss: 0.26381 focal_loss 0.19138 dice_loss 0.07243 +Epoch [1548/4000] Validation [2/4] Loss: 0.44917 focal_loss 0.27264 dice_loss 0.17653 +Epoch [1548/4000] Validation [3/4] Loss: 0.30799 focal_loss 0.21750 dice_loss 0.09049 +Epoch [1548/4000] Validation [4/4] Loss: 0.19998 focal_loss 0.10823 dice_loss 0.09174 +Epoch [1548/4000] Validation metric {'Val/mean dice_metric': 0.9715082049369812, 'Val/mean miou_metric': 0.9542921185493469, 'Val/mean f1': 0.9731215834617615, 'Val/mean precision': 0.9693006873130798, 'Val/mean recall': 0.9769726991653442, 'Val/mean hd95_metric': 5.73075008392334} +Cheakpoint... +Epoch [1548/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715082049369812, 'Val/mean miou_metric': 0.9542921185493469, 'Val/mean f1': 0.9731215834617615, 'Val/mean precision': 0.9693006873130798, 'Val/mean recall': 0.9769726991653442, 'Val/mean hd95_metric': 5.73075008392334} +Epoch [1549/4000] Training [1/16] Loss: 0.00644 +Epoch [1549/4000] Training [2/16] Loss: 0.00894 +Epoch [1549/4000] Training [3/16] Loss: 0.00707 +Epoch [1549/4000] Training [4/16] Loss: 0.00935 +Epoch [1549/4000] Training [5/16] Loss: 0.00903 +Epoch [1549/4000] Training [6/16] Loss: 0.01328 +Epoch [1549/4000] Training [7/16] Loss: 0.00748 +Epoch [1549/4000] Training [8/16] Loss: 0.00809 +Epoch [1549/4000] Training [9/16] Loss: 0.00649 +Epoch [1549/4000] Training [10/16] Loss: 0.00740 +Epoch [1549/4000] Training [11/16] Loss: 0.00554 +Epoch [1549/4000] Training [12/16] Loss: 0.00718 +Epoch [1549/4000] Training [13/16] Loss: 0.00653 +Epoch [1549/4000] Training [14/16] Loss: 0.00851 +Epoch [1549/4000] Training [15/16] Loss: 0.00680 +Epoch [1549/4000] Training [16/16] Loss: 0.00726 +Epoch [1549/4000] Training metric {'Train/mean dice_metric': 0.994914174079895, 'Train/mean miou_metric': 0.9896288514137268, 'Train/mean f1': 0.9909265637397766, 'Train/mean precision': 0.9864038228988647, 'Train/mean recall': 0.9954910278320312, 'Train/mean hd95_metric': 1.0791293382644653} +Epoch [1549/4000] Validation [1/4] Loss: 0.32129 focal_loss 0.23892 dice_loss 0.08237 +Epoch [1549/4000] Validation [2/4] Loss: 0.47609 focal_loss 0.29998 dice_loss 0.17610 +Epoch [1549/4000] Validation [3/4] Loss: 0.35985 focal_loss 0.25976 dice_loss 0.10009 +Epoch [1549/4000] Validation [4/4] Loss: 0.33780 focal_loss 0.20432 dice_loss 0.13348 +Epoch [1549/4000] Validation metric {'Val/mean dice_metric': 0.9704809188842773, 'Val/mean miou_metric': 0.9527952075004578, 'Val/mean f1': 0.9727420806884766, 'Val/mean precision': 0.9714317321777344, 'Val/mean recall': 0.9740558862686157, 'Val/mean hd95_metric': 5.800207614898682} +Cheakpoint... +Epoch [1549/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704809188842773, 'Val/mean miou_metric': 0.9527952075004578, 'Val/mean f1': 0.9727420806884766, 'Val/mean precision': 0.9714317321777344, 'Val/mean recall': 0.9740558862686157, 'Val/mean hd95_metric': 5.800207614898682} +Epoch [1550/4000] Training [1/16] Loss: 0.00712 +Epoch [1550/4000] Training [2/16] Loss: 0.00607 +Epoch [1550/4000] Training [3/16] Loss: 0.00702 +Epoch [1550/4000] Training [4/16] Loss: 0.00712 +Epoch [1550/4000] Training [5/16] Loss: 0.00753 +Epoch [1550/4000] Training [6/16] Loss: 0.00620 +Epoch [1550/4000] Training [7/16] Loss: 0.00842 +Epoch [1550/4000] Training [8/16] Loss: 0.00788 +Epoch [1550/4000] Training [9/16] Loss: 0.00722 +Epoch [1550/4000] Training [10/16] Loss: 0.00763 +Epoch [1550/4000] Training [11/16] Loss: 0.00636 +Epoch [1550/4000] Training [12/16] Loss: 0.00657 +Epoch [1550/4000] Training [13/16] Loss: 0.00970 +Epoch [1550/4000] Training [14/16] Loss: 0.01311 +Epoch [1550/4000] Training [15/16] Loss: 0.00950 +Epoch [1550/4000] Training [16/16] Loss: 0.00776 +Epoch [1550/4000] Training metric {'Train/mean dice_metric': 0.9949575662612915, 'Train/mean miou_metric': 0.9896887540817261, 'Train/mean f1': 0.9904929995536804, 'Train/mean precision': 0.9857012033462524, 'Train/mean recall': 0.9953315854072571, 'Train/mean hd95_metric': 1.021808385848999} +Epoch [1550/4000] Validation [1/4] Loss: 0.32831 focal_loss 0.24108 dice_loss 0.08723 +Epoch [1550/4000] Validation [2/4] Loss: 0.22860 focal_loss 0.12422 dice_loss 0.10438 +Epoch [1550/4000] Validation [3/4] Loss: 0.25954 focal_loss 0.17072 dice_loss 0.08881 +Epoch [1550/4000] Validation [4/4] Loss: 0.44882 focal_loss 0.30011 dice_loss 0.14870 +Epoch [1550/4000] Validation metric {'Val/mean dice_metric': 0.9705196619033813, 'Val/mean miou_metric': 0.9527748823165894, 'Val/mean f1': 0.9726719856262207, 'Val/mean precision': 0.9731098413467407, 'Val/mean recall': 0.9722343683242798, 'Val/mean hd95_metric': 5.482695579528809} +Cheakpoint... +Epoch [1550/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705196619033813, 'Val/mean miou_metric': 0.9527748823165894, 'Val/mean f1': 0.9726719856262207, 'Val/mean precision': 0.9731098413467407, 'Val/mean recall': 0.9722343683242798, 'Val/mean hd95_metric': 5.482695579528809} +Epoch [1551/4000] Training [1/16] Loss: 0.01230 +Epoch [1551/4000] Training [2/16] Loss: 0.00788 +Epoch [1551/4000] Training [3/16] Loss: 0.00983 +Epoch [1551/4000] Training [4/16] Loss: 0.00812 +Epoch [1551/4000] Training [5/16] Loss: 0.00726 +Epoch [1551/4000] Training [6/16] Loss: 0.00594 +Epoch [1551/4000] Training [7/16] Loss: 0.00835 +Epoch [1551/4000] Training [8/16] Loss: 0.01086 +Epoch [1551/4000] Training [9/16] Loss: 0.00721 +Epoch [1551/4000] Training [10/16] Loss: 0.00942 +Epoch [1551/4000] Training [11/16] Loss: 0.00684 +Epoch [1551/4000] Training [12/16] Loss: 0.00836 +Epoch [1551/4000] Training [13/16] Loss: 0.00694 +Epoch [1551/4000] Training [14/16] Loss: 0.00746 +Epoch [1551/4000] Training [15/16] Loss: 0.00777 +Epoch [1551/4000] Training [16/16] Loss: 0.00646 +Epoch [1551/4000] Training metric {'Train/mean dice_metric': 0.9946178197860718, 'Train/mean miou_metric': 0.9890396595001221, 'Train/mean f1': 0.9905872344970703, 'Train/mean precision': 0.9859771132469177, 'Train/mean recall': 0.9952406287193298, 'Train/mean hd95_metric': 1.037176489830017} +Epoch [1551/4000] Validation [1/4] Loss: 0.26906 focal_loss 0.19701 dice_loss 0.07205 +Epoch [1551/4000] Validation [2/4] Loss: 0.46727 focal_loss 0.27440 dice_loss 0.19287 +Epoch [1551/4000] Validation [3/4] Loss: 0.21113 focal_loss 0.13231 dice_loss 0.07882 +Epoch [1551/4000] Validation [4/4] Loss: 0.41103 focal_loss 0.26630 dice_loss 0.14473 +Epoch [1551/4000] Validation metric {'Val/mean dice_metric': 0.969099223613739, 'Val/mean miou_metric': 0.9514694213867188, 'Val/mean f1': 0.9726070165634155, 'Val/mean precision': 0.9711570143699646, 'Val/mean recall': 0.9740612506866455, 'Val/mean hd95_metric': 5.834865570068359} +Cheakpoint... +Epoch [1551/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969099223613739, 'Val/mean miou_metric': 0.9514694213867188, 'Val/mean f1': 0.9726070165634155, 'Val/mean precision': 0.9711570143699646, 'Val/mean recall': 0.9740612506866455, 'Val/mean hd95_metric': 5.834865570068359} +Epoch [1552/4000] Training [1/16] Loss: 0.00753 +Epoch [1552/4000] Training [2/16] Loss: 0.00770 +Epoch [1552/4000] Training [3/16] Loss: 0.00678 +Epoch [1552/4000] Training [4/16] Loss: 0.00758 +Epoch [1552/4000] Training [5/16] Loss: 0.00863 +Epoch [1552/4000] Training [6/16] Loss: 0.01388 +Epoch [1552/4000] Training [7/16] Loss: 0.00664 +Epoch [1552/4000] Training [8/16] Loss: 0.00882 +Epoch [1552/4000] Training [9/16] Loss: 0.01112 +Epoch [1552/4000] Training [10/16] Loss: 0.00753 +Epoch [1552/4000] Training [11/16] Loss: 0.00674 +Epoch [1552/4000] Training [12/16] Loss: 0.00766 +Epoch [1552/4000] Training [13/16] Loss: 0.00870 +Epoch [1552/4000] Training [14/16] Loss: 0.00800 +Epoch [1552/4000] Training [15/16] Loss: 0.00618 +Epoch [1552/4000] Training [16/16] Loss: 0.00650 +Epoch [1552/4000] Training metric {'Train/mean dice_metric': 0.9944421052932739, 'Train/mean miou_metric': 0.988703727722168, 'Train/mean f1': 0.9906890392303467, 'Train/mean precision': 0.9861197471618652, 'Train/mean recall': 0.9953008890151978, 'Train/mean hd95_metric': 1.0379301309585571} +Epoch [1552/4000] Validation [1/4] Loss: 0.24915 focal_loss 0.18143 dice_loss 0.06772 +Epoch [1552/4000] Validation [2/4] Loss: 0.22660 focal_loss 0.12543 dice_loss 0.10117 +Epoch [1552/4000] Validation [3/4] Loss: 0.16428 focal_loss 0.10490 dice_loss 0.05938 +Epoch [1552/4000] Validation [4/4] Loss: 0.30768 focal_loss 0.19482 dice_loss 0.11286 +Epoch [1552/4000] Validation metric {'Val/mean dice_metric': 0.9714124798774719, 'Val/mean miou_metric': 0.954128623008728, 'Val/mean f1': 0.9738027453422546, 'Val/mean precision': 0.9711688756942749, 'Val/mean recall': 0.9764508008956909, 'Val/mean hd95_metric': 5.5878801345825195} +Cheakpoint... +Epoch [1552/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714124798774719, 'Val/mean miou_metric': 0.954128623008728, 'Val/mean f1': 0.9738027453422546, 'Val/mean precision': 0.9711688756942749, 'Val/mean recall': 0.9764508008956909, 'Val/mean hd95_metric': 5.5878801345825195} +Epoch [1553/4000] Training [1/16] Loss: 0.00684 +Epoch [1553/4000] Training [2/16] Loss: 0.00682 +Epoch [1553/4000] Training [3/16] Loss: 0.00566 +Epoch [1553/4000] Training [4/16] Loss: 0.00665 +Epoch [1553/4000] Training [5/16] Loss: 0.00616 +Epoch [1553/4000] Training [6/16] Loss: 0.00739 +Epoch [1553/4000] Training [7/16] Loss: 0.00747 +Epoch [1553/4000] Training [8/16] Loss: 0.00879 +Epoch [1553/4000] Training [9/16] Loss: 0.00693 +Epoch [1553/4000] Training [10/16] Loss: 0.00597 +Epoch [1553/4000] Training [11/16] Loss: 0.00704 +Epoch [1553/4000] Training [12/16] Loss: 0.00639 +Epoch [1553/4000] Training [13/16] Loss: 0.00693 +Epoch [1553/4000] Training [14/16] Loss: 0.00681 +Epoch [1553/4000] Training [15/16] Loss: 0.00897 +Epoch [1553/4000] Training [16/16] Loss: 0.00850 +Epoch [1553/4000] Training metric {'Train/mean dice_metric': 0.9944358468055725, 'Train/mean miou_metric': 0.988970935344696, 'Train/mean f1': 0.9906699061393738, 'Train/mean precision': 0.9857321381568909, 'Train/mean recall': 0.9956573843955994, 'Train/mean hd95_metric': 1.1686683893203735} +Epoch [1553/4000] Validation [1/4] Loss: 0.26272 focal_loss 0.18924 dice_loss 0.07349 +Epoch [1553/4000] Validation [2/4] Loss: 0.24287 focal_loss 0.13307 dice_loss 0.10980 +Epoch [1553/4000] Validation [3/4] Loss: 0.33279 focal_loss 0.23599 dice_loss 0.09680 +Epoch [1553/4000] Validation [4/4] Loss: 0.26007 focal_loss 0.17025 dice_loss 0.08982 +Epoch [1553/4000] Validation metric {'Val/mean dice_metric': 0.9709981083869934, 'Val/mean miou_metric': 0.9538089632987976, 'Val/mean f1': 0.9738720655441284, 'Val/mean precision': 0.9707585573196411, 'Val/mean recall': 0.9770057201385498, 'Val/mean hd95_metric': 5.428858757019043} +Cheakpoint... +Epoch [1553/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709981083869934, 'Val/mean miou_metric': 0.9538089632987976, 'Val/mean f1': 0.9738720655441284, 'Val/mean precision': 0.9707585573196411, 'Val/mean recall': 0.9770057201385498, 'Val/mean hd95_metric': 5.428858757019043} +Epoch [1554/4000] Training [1/16] Loss: 0.00658 +Epoch [1554/4000] Training [2/16] Loss: 0.00697 +Epoch [1554/4000] Training [3/16] Loss: 0.01008 +Epoch [1554/4000] Training [4/16] Loss: 0.00704 +Epoch [1554/4000] Training [5/16] Loss: 0.00688 +Epoch [1554/4000] Training [6/16] Loss: 0.00599 +Epoch [1554/4000] Training [7/16] Loss: 0.00751 +Epoch [1554/4000] Training [8/16] Loss: 0.01019 +Epoch [1554/4000] Training [9/16] Loss: 0.01277 +Epoch [1554/4000] Training [10/16] Loss: 0.00625 +Epoch [1554/4000] Training [11/16] Loss: 0.00655 +Epoch [1554/4000] Training [12/16] Loss: 0.00667 +Epoch [1554/4000] Training [13/16] Loss: 0.01031 +Epoch [1554/4000] Training [14/16] Loss: 0.00937 +Epoch [1554/4000] Training [15/16] Loss: 0.00831 +Epoch [1554/4000] Training [16/16] Loss: 0.00849 +Epoch [1554/4000] Training metric {'Train/mean dice_metric': 0.9930880069732666, 'Train/mean miou_metric': 0.9865886569023132, 'Train/mean f1': 0.9901535511016846, 'Train/mean precision': 0.9859362840652466, 'Train/mean recall': 0.994407057762146, 'Train/mean hd95_metric': 1.273905873298645} +Epoch [1554/4000] Validation [1/4] Loss: 0.43012 focal_loss 0.33455 dice_loss 0.09557 +Epoch [1554/4000] Validation [2/4] Loss: 0.60528 focal_loss 0.36289 dice_loss 0.24239 +Epoch [1554/4000] Validation [3/4] Loss: 0.28898 focal_loss 0.20678 dice_loss 0.08220 +Epoch [1554/4000] Validation [4/4] Loss: 0.32463 focal_loss 0.19615 dice_loss 0.12848 +Epoch [1554/4000] Validation metric {'Val/mean dice_metric': 0.9670194387435913, 'Val/mean miou_metric': 0.9485004544258118, 'Val/mean f1': 0.9701181054115295, 'Val/mean precision': 0.9675237536430359, 'Val/mean recall': 0.9727264046669006, 'Val/mean hd95_metric': 6.497516632080078} +Cheakpoint... +Epoch [1554/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670194387435913, 'Val/mean miou_metric': 0.9485004544258118, 'Val/mean f1': 0.9701181054115295, 'Val/mean precision': 0.9675237536430359, 'Val/mean recall': 0.9727264046669006, 'Val/mean hd95_metric': 6.497516632080078} +Epoch [1555/4000] Training [1/16] Loss: 0.01270 +Epoch [1555/4000] Training [2/16] Loss: 0.00840 +Epoch [1555/4000] Training [3/16] Loss: 0.01319 +Epoch [1555/4000] Training [4/16] Loss: 0.01168 +Epoch [1555/4000] Training [5/16] Loss: 0.00737 +Epoch [1555/4000] Training [6/16] Loss: 0.00840 +Epoch [1555/4000] Training [7/16] Loss: 0.00964 +Epoch [1555/4000] Training [8/16] Loss: 0.00907 +Epoch [1555/4000] Training [9/16] Loss: 0.01307 +Epoch [1555/4000] Training [10/16] Loss: 0.00799 +Epoch [1555/4000] Training [11/16] Loss: 0.00817 +Epoch [1555/4000] Training [12/16] Loss: 0.00857 +Epoch [1555/4000] Training [13/16] Loss: 0.00968 +Epoch [1555/4000] Training [14/16] Loss: 0.00847 +Epoch [1555/4000] Training [15/16] Loss: 0.00824 +Epoch [1555/4000] Training [16/16] Loss: 0.00734 +Epoch [1555/4000] Training metric {'Train/mean dice_metric': 0.9926345944404602, 'Train/mean miou_metric': 0.985581636428833, 'Train/mean f1': 0.9894356727600098, 'Train/mean precision': 0.9849519729614258, 'Train/mean recall': 0.993960440158844, 'Train/mean hd95_metric': 1.5412018299102783} +Epoch [1555/4000] Validation [1/4] Loss: 0.21960 focal_loss 0.15795 dice_loss 0.06165 +Epoch [1555/4000] Validation [2/4] Loss: 0.61143 focal_loss 0.41183 dice_loss 0.19961 +Epoch [1555/4000] Validation [3/4] Loss: 0.31307 focal_loss 0.22522 dice_loss 0.08785 +Epoch [1555/4000] Validation [4/4] Loss: 0.34475 focal_loss 0.22337 dice_loss 0.12138 +Epoch [1555/4000] Validation metric {'Val/mean dice_metric': 0.9668627977371216, 'Val/mean miou_metric': 0.9487531781196594, 'Val/mean f1': 0.9718518853187561, 'Val/mean precision': 0.9696753025054932, 'Val/mean recall': 0.9740383625030518, 'Val/mean hd95_metric': 6.9631853103637695} +Cheakpoint... +Epoch [1555/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9668627977371216, 'Val/mean miou_metric': 0.9487531781196594, 'Val/mean f1': 0.9718518853187561, 'Val/mean precision': 0.9696753025054932, 'Val/mean recall': 0.9740383625030518, 'Val/mean hd95_metric': 6.9631853103637695} +Epoch [1556/4000] Training [1/16] Loss: 0.00859 +Epoch [1556/4000] Training [2/16] Loss: 0.00830 +Epoch [1556/4000] Training [3/16] Loss: 0.00902 +Epoch [1556/4000] Training [4/16] Loss: 0.03306 +Epoch [1556/4000] Training [5/16] Loss: 0.00858 +Epoch [1556/4000] Training [6/16] Loss: 0.00951 +Epoch [1556/4000] Training [7/16] Loss: 0.00687 +Epoch [1556/4000] Training [8/16] Loss: 0.01020 +Epoch [1556/4000] Training [9/16] Loss: 0.00855 +Epoch [1556/4000] Training [10/16] Loss: 0.00793 +Epoch [1556/4000] Training [11/16] Loss: 0.00822 +Epoch [1556/4000] Training [12/16] Loss: 0.00688 +Epoch [1556/4000] Training [13/16] Loss: 0.00887 +Epoch [1556/4000] Training [14/16] Loss: 0.00902 +Epoch [1556/4000] Training [15/16] Loss: 0.00663 +Epoch [1556/4000] Training [16/16] Loss: 0.01417 +Epoch [1556/4000] Training metric {'Train/mean dice_metric': 0.9938945174217224, 'Train/mean miou_metric': 0.9876495003700256, 'Train/mean f1': 0.9900959134101868, 'Train/mean precision': 0.9856821298599243, 'Train/mean recall': 0.9945493340492249, 'Train/mean hd95_metric': 1.239749789237976} +Epoch [1556/4000] Validation [1/4] Loss: 0.21252 focal_loss 0.15224 dice_loss 0.06029 +Epoch [1556/4000] Validation [2/4] Loss: 0.24723 focal_loss 0.12921 dice_loss 0.11803 +Epoch [1556/4000] Validation [3/4] Loss: 0.27859 focal_loss 0.19058 dice_loss 0.08802 +Epoch [1556/4000] Validation [4/4] Loss: 0.35887 focal_loss 0.22709 dice_loss 0.13178 +Epoch [1556/4000] Validation metric {'Val/mean dice_metric': 0.9690691232681274, 'Val/mean miou_metric': 0.951259970664978, 'Val/mean f1': 0.9731419682502747, 'Val/mean precision': 0.9704419374465942, 'Val/mean recall': 0.9758572578430176, 'Val/mean hd95_metric': 6.190312385559082} +Cheakpoint... +Epoch [1556/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690691232681274, 'Val/mean miou_metric': 0.951259970664978, 'Val/mean f1': 0.9731419682502747, 'Val/mean precision': 0.9704419374465942, 'Val/mean recall': 0.9758572578430176, 'Val/mean hd95_metric': 6.190312385559082} +Epoch [1557/4000] Training [1/16] Loss: 0.00804 +Epoch [1557/4000] Training [2/16] Loss: 0.00899 +Epoch [1557/4000] Training [3/16] Loss: 0.00678 +Epoch [1557/4000] Training [4/16] Loss: 0.00814 +Epoch [1557/4000] Training [5/16] Loss: 0.01344 +Epoch [1557/4000] Training [6/16] Loss: 0.00895 +Epoch [1557/4000] Training [7/16] Loss: 0.00676 +Epoch [1557/4000] Training [8/16] Loss: 0.01209 +Epoch [1557/4000] Training [9/16] Loss: 0.00732 +Epoch [1557/4000] Training [10/16] Loss: 0.00974 +Epoch [1557/4000] Training [11/16] Loss: 0.00730 +Epoch [1557/4000] Training [12/16] Loss: 0.00577 +Epoch [1557/4000] Training [13/16] Loss: 0.00759 +Epoch [1557/4000] Training [14/16] Loss: 0.00820 +Epoch [1557/4000] Training [15/16] Loss: 0.00780 +Epoch [1557/4000] Training [16/16] Loss: 0.00821 +Epoch [1557/4000] Training metric {'Train/mean dice_metric': 0.9942688941955566, 'Train/mean miou_metric': 0.9883631467819214, 'Train/mean f1': 0.9903877377510071, 'Train/mean precision': 0.9859811663627625, 'Train/mean recall': 0.9948339462280273, 'Train/mean hd95_metric': 1.08855402469635} +Epoch [1557/4000] Validation [1/4] Loss: 0.26705 focal_loss 0.19767 dice_loss 0.06938 +Epoch [1557/4000] Validation [2/4] Loss: 0.36741 focal_loss 0.22664 dice_loss 0.14078 +Epoch [1557/4000] Validation [3/4] Loss: 0.17378 focal_loss 0.10834 dice_loss 0.06544 +Epoch [1557/4000] Validation [4/4] Loss: 0.28591 focal_loss 0.17863 dice_loss 0.10728 +Epoch [1557/4000] Validation metric {'Val/mean dice_metric': 0.967941403388977, 'Val/mean miou_metric': 0.9504114389419556, 'Val/mean f1': 0.9712061882019043, 'Val/mean precision': 0.9710352420806885, 'Val/mean recall': 0.9713771343231201, 'Val/mean hd95_metric': 5.406856536865234} +Cheakpoint... +Epoch [1557/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.967941403388977, 'Val/mean miou_metric': 0.9504114389419556, 'Val/mean f1': 0.9712061882019043, 'Val/mean precision': 0.9710352420806885, 'Val/mean recall': 0.9713771343231201, 'Val/mean hd95_metric': 5.406856536865234} +Epoch [1558/4000] Training [1/16] Loss: 0.00770 +Epoch [1558/4000] Training [2/16] Loss: 0.00809 +Epoch [1558/4000] Training [3/16] Loss: 0.00859 +Epoch [1558/4000] Training [4/16] Loss: 0.00908 +Epoch [1558/4000] Training [5/16] Loss: 0.00919 +Epoch [1558/4000] Training [6/16] Loss: 0.00797 +Epoch [1558/4000] Training [7/16] Loss: 0.00632 +Epoch [1558/4000] Training [8/16] Loss: 0.00650 +Epoch [1558/4000] Training [9/16] Loss: 0.00594 +Epoch [1558/4000] Training [10/16] Loss: 0.00694 +Epoch [1558/4000] Training [11/16] Loss: 0.00843 +Epoch [1558/4000] Training [12/16] Loss: 0.00783 +Epoch [1558/4000] Training [13/16] Loss: 0.00624 +Epoch [1558/4000] Training [14/16] Loss: 0.00754 +Epoch [1558/4000] Training [15/16] Loss: 0.00849 +Epoch [1558/4000] Training [16/16] Loss: 0.00717 +Epoch [1558/4000] Training metric {'Train/mean dice_metric': 0.9950016736984253, 'Train/mean miou_metric': 0.9897861480712891, 'Train/mean f1': 0.9907240867614746, 'Train/mean precision': 0.9860090017318726, 'Train/mean recall': 0.995484471321106, 'Train/mean hd95_metric': 1.054640769958496} +Epoch [1558/4000] Validation [1/4] Loss: 0.21814 focal_loss 0.14860 dice_loss 0.06954 +Epoch [1558/4000] Validation [2/4] Loss: 0.28495 focal_loss 0.16329 dice_loss 0.12167 +Epoch [1558/4000] Validation [3/4] Loss: 0.16275 focal_loss 0.09984 dice_loss 0.06291 +Epoch [1558/4000] Validation [4/4] Loss: 0.24508 focal_loss 0.15128 dice_loss 0.09380 +Epoch [1558/4000] Validation metric {'Val/mean dice_metric': 0.9716653823852539, 'Val/mean miou_metric': 0.9545966982841492, 'Val/mean f1': 0.974311888217926, 'Val/mean precision': 0.9735593795776367, 'Val/mean recall': 0.9750654697418213, 'Val/mean hd95_metric': 5.052828788757324} +Cheakpoint... +Epoch [1558/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716653823852539, 'Val/mean miou_metric': 0.9545966982841492, 'Val/mean f1': 0.974311888217926, 'Val/mean precision': 0.9735593795776367, 'Val/mean recall': 0.9750654697418213, 'Val/mean hd95_metric': 5.052828788757324} +Epoch [1559/4000] Training [1/16] Loss: 0.00604 +Epoch [1559/4000] Training [2/16] Loss: 0.00655 +Epoch [1559/4000] Training [3/16] Loss: 0.00775 +Epoch [1559/4000] Training [4/16] Loss: 0.00793 +Epoch [1559/4000] Training [5/16] Loss: 0.00860 +Epoch [1559/4000] Training [6/16] Loss: 0.00641 +Epoch [1559/4000] Training [7/16] Loss: 0.00986 +Epoch [1559/4000] Training [8/16] Loss: 0.00548 +Epoch [1559/4000] Training [9/16] Loss: 0.01187 +Epoch [1559/4000] Training [10/16] Loss: 0.01049 +Epoch [1559/4000] Training [11/16] Loss: 0.00691 +Epoch [1559/4000] Training [12/16] Loss: 0.00718 +Epoch [1559/4000] Training [13/16] Loss: 0.00869 +Epoch [1559/4000] Training [14/16] Loss: 0.00687 +Epoch [1559/4000] Training [15/16] Loss: 0.00776 +Epoch [1559/4000] Training [16/16] Loss: 0.00950 +Epoch [1559/4000] Training metric {'Train/mean dice_metric': 0.9946471452713013, 'Train/mean miou_metric': 0.989081859588623, 'Train/mean f1': 0.9900346994400024, 'Train/mean precision': 0.9850345849990845, 'Train/mean recall': 0.9950857758522034, 'Train/mean hd95_metric': 1.0638675689697266} +Epoch [1559/4000] Validation [1/4] Loss: 0.29120 focal_loss 0.21893 dice_loss 0.07228 +Epoch [1559/4000] Validation [2/4] Loss: 0.24648 focal_loss 0.13444 dice_loss 0.11204 +Epoch [1559/4000] Validation [3/4] Loss: 0.29172 focal_loss 0.19412 dice_loss 0.09759 +Epoch [1559/4000] Validation [4/4] Loss: 0.22850 focal_loss 0.13410 dice_loss 0.09440 +Epoch [1559/4000] Validation metric {'Val/mean dice_metric': 0.9714115858078003, 'Val/mean miou_metric': 0.9536319971084595, 'Val/mean f1': 0.9729276895523071, 'Val/mean precision': 0.9707539081573486, 'Val/mean recall': 0.975111186504364, 'Val/mean hd95_metric': 5.289801597595215} +Cheakpoint... +Epoch [1559/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714115858078003, 'Val/mean miou_metric': 0.9536319971084595, 'Val/mean f1': 0.9729276895523071, 'Val/mean precision': 0.9707539081573486, 'Val/mean recall': 0.975111186504364, 'Val/mean hd95_metric': 5.289801597595215} +Epoch [1560/4000] Training [1/16] Loss: 0.00903 +Epoch [1560/4000] Training [2/16] Loss: 0.00748 +Epoch [1560/4000] Training [3/16] Loss: 0.01203 +Epoch [1560/4000] Training [4/16] Loss: 0.00795 +Epoch [1560/4000] Training [5/16] Loss: 0.00723 +Epoch [1560/4000] Training [6/16] Loss: 0.00639 +Epoch [1560/4000] Training [7/16] Loss: 0.00971 +Epoch [1560/4000] Training [8/16] Loss: 0.00971 +Epoch [1560/4000] Training [9/16] Loss: 0.00711 +Epoch [1560/4000] Training [10/16] Loss: 0.01008 +Epoch [1560/4000] Training [11/16] Loss: 0.00767 +Epoch [1560/4000] Training [12/16] Loss: 0.01123 +Epoch [1560/4000] Training [13/16] Loss: 0.00958 +Epoch [1560/4000] Training [14/16] Loss: 0.00889 +Epoch [1560/4000] Training [15/16] Loss: 0.01043 +Epoch [1560/4000] Training [16/16] Loss: 0.00550 +Epoch [1560/4000] Training metric {'Train/mean dice_metric': 0.9934053421020508, 'Train/mean miou_metric': 0.9872050285339355, 'Train/mean f1': 0.9896401762962341, 'Train/mean precision': 0.9844778180122375, 'Train/mean recall': 0.9948569536209106, 'Train/mean hd95_metric': 1.4638020992279053} +Epoch [1560/4000] Validation [1/4] Loss: 0.34722 focal_loss 0.24295 dice_loss 0.10427 +Epoch [1560/4000] Validation [2/4] Loss: 0.44571 focal_loss 0.26215 dice_loss 0.18356 +Epoch [1560/4000] Validation [3/4] Loss: 0.35098 focal_loss 0.25054 dice_loss 0.10045 +Epoch [1560/4000] Validation [4/4] Loss: 0.33426 focal_loss 0.20717 dice_loss 0.12709 +Epoch [1560/4000] Validation metric {'Val/mean dice_metric': 0.9675742983818054, 'Val/mean miou_metric': 0.9490803480148315, 'Val/mean f1': 0.970600962638855, 'Val/mean precision': 0.9708080887794495, 'Val/mean recall': 0.9703938364982605, 'Val/mean hd95_metric': 6.048934459686279} +Cheakpoint... +Epoch [1560/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675742983818054, 'Val/mean miou_metric': 0.9490803480148315, 'Val/mean f1': 0.970600962638855, 'Val/mean precision': 0.9708080887794495, 'Val/mean recall': 0.9703938364982605, 'Val/mean hd95_metric': 6.048934459686279} +Epoch [1561/4000] Training [1/16] Loss: 0.00758 +Epoch [1561/4000] Training [2/16] Loss: 0.01090 +Epoch [1561/4000] Training [3/16] Loss: 0.00646 +Epoch [1561/4000] Training [4/16] Loss: 0.00885 +Epoch [1561/4000] Training [5/16] Loss: 0.00728 +Epoch [1561/4000] Training [6/16] Loss: 0.01158 +Epoch [1561/4000] Training [7/16] Loss: 0.00738 +Epoch [1561/4000] Training [8/16] Loss: 0.00936 +Epoch [1561/4000] Training [9/16] Loss: 0.01064 +Epoch [1561/4000] Training [10/16] Loss: 0.00615 +Epoch [1561/4000] Training [11/16] Loss: 0.00725 +Epoch [1561/4000] Training [12/16] Loss: 0.01082 +Epoch [1561/4000] Training [13/16] Loss: 0.00682 +Epoch [1561/4000] Training [14/16] Loss: 0.00614 +Epoch [1561/4000] Training [15/16] Loss: 0.00826 +Epoch [1561/4000] Training [16/16] Loss: 0.00819 +Epoch [1561/4000] Training metric {'Train/mean dice_metric': 0.9943687319755554, 'Train/mean miou_metric': 0.9885430932044983, 'Train/mean f1': 0.9900195002555847, 'Train/mean precision': 0.9850468635559082, 'Train/mean recall': 0.9950425624847412, 'Train/mean hd95_metric': 1.1853067874908447} +Epoch [1561/4000] Validation [1/4] Loss: 0.27977 focal_loss 0.20420 dice_loss 0.07557 +Epoch [1561/4000] Validation [2/4] Loss: 0.72178 focal_loss 0.46118 dice_loss 0.26060 +Epoch [1561/4000] Validation [3/4] Loss: 0.15823 focal_loss 0.09844 dice_loss 0.05980 +Epoch [1561/4000] Validation [4/4] Loss: 0.23500 focal_loss 0.14426 dice_loss 0.09075 +Epoch [1561/4000] Validation metric {'Val/mean dice_metric': 0.9684654474258423, 'Val/mean miou_metric': 0.9510335922241211, 'Val/mean f1': 0.9707008600234985, 'Val/mean precision': 0.9702350497245789, 'Val/mean recall': 0.9711670875549316, 'Val/mean hd95_metric': 5.458861351013184} +Cheakpoint... +Epoch [1561/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9684654474258423, 'Val/mean miou_metric': 0.9510335922241211, 'Val/mean f1': 0.9707008600234985, 'Val/mean precision': 0.9702350497245789, 'Val/mean recall': 0.9711670875549316, 'Val/mean hd95_metric': 5.458861351013184} +Epoch [1562/4000] Training [1/16] Loss: 0.00653 +Epoch [1562/4000] Training [2/16] Loss: 0.00677 +Epoch [1562/4000] Training [3/16] Loss: 0.00792 +Epoch [1562/4000] Training [4/16] Loss: 0.01140 +Epoch [1562/4000] Training [5/16] Loss: 0.00654 +Epoch [1562/4000] Training [6/16] Loss: 0.00808 +Epoch [1562/4000] Training [7/16] Loss: 0.00684 +Epoch [1562/4000] Training [8/16] Loss: 0.00789 +Epoch [1562/4000] Training [9/16] Loss: 0.00671 +Epoch [1562/4000] Training [10/16] Loss: 0.00755 +Epoch [1562/4000] Training [11/16] Loss: 0.00919 +Epoch [1562/4000] Training [12/16] Loss: 0.00889 +Epoch [1562/4000] Training [13/16] Loss: 0.00663 +Epoch [1562/4000] Training [14/16] Loss: 0.00716 +Epoch [1562/4000] Training [15/16] Loss: 0.00686 +Epoch [1562/4000] Training [16/16] Loss: 0.00793 +Epoch [1562/4000] Training metric {'Train/mean dice_metric': 0.9950119256973267, 'Train/mean miou_metric': 0.9898073673248291, 'Train/mean f1': 0.9908113479614258, 'Train/mean precision': 0.9861971139907837, 'Train/mean recall': 0.9954689741134644, 'Train/mean hd95_metric': 1.0205544233322144} +Epoch [1562/4000] Validation [1/4] Loss: 0.27718 focal_loss 0.20127 dice_loss 0.07591 +Epoch [1562/4000] Validation [2/4] Loss: 0.51907 focal_loss 0.32190 dice_loss 0.19716 +Epoch [1562/4000] Validation [3/4] Loss: 0.24942 focal_loss 0.15618 dice_loss 0.09324 +Epoch [1562/4000] Validation [4/4] Loss: 0.17185 focal_loss 0.09668 dice_loss 0.07518 +Epoch [1562/4000] Validation metric {'Val/mean dice_metric': 0.9714807271957397, 'Val/mean miou_metric': 0.9548850059509277, 'Val/mean f1': 0.973964512348175, 'Val/mean precision': 0.9720689058303833, 'Val/mean recall': 0.9758674502372742, 'Val/mean hd95_metric': 5.063383102416992} +Cheakpoint... +Epoch [1562/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714807271957397, 'Val/mean miou_metric': 0.9548850059509277, 'Val/mean f1': 0.973964512348175, 'Val/mean precision': 0.9720689058303833, 'Val/mean recall': 0.9758674502372742, 'Val/mean hd95_metric': 5.063383102416992} +Epoch [1563/4000] Training [1/16] Loss: 0.00848 +Epoch [1563/4000] Training [2/16] Loss: 0.00761 +Epoch [1563/4000] Training [3/16] Loss: 0.00749 +Epoch [1563/4000] Training [4/16] Loss: 0.00812 +Epoch [1563/4000] Training [5/16] Loss: 0.00789 +Epoch [1563/4000] Training [6/16] Loss: 0.00800 +Epoch [1563/4000] Training [7/16] Loss: 0.00728 +Epoch [1563/4000] Training [8/16] Loss: 0.00670 +Epoch [1563/4000] Training [9/16] Loss: 0.00749 +Epoch [1563/4000] Training [10/16] Loss: 0.00657 +Epoch [1563/4000] Training [11/16] Loss: 0.00715 +Epoch [1563/4000] Training [12/16] Loss: 0.00615 +Epoch [1563/4000] Training [13/16] Loss: 0.00729 +Epoch [1563/4000] Training [14/16] Loss: 0.00689 +Epoch [1563/4000] Training [15/16] Loss: 0.00650 +Epoch [1563/4000] Training [16/16] Loss: 0.00733 +Epoch [1563/4000] Training metric {'Train/mean dice_metric': 0.9950605630874634, 'Train/mean miou_metric': 0.9899139404296875, 'Train/mean f1': 0.9910807609558105, 'Train/mean precision': 0.9864742159843445, 'Train/mean recall': 0.995730459690094, 'Train/mean hd95_metric': 1.0207397937774658} +Epoch [1563/4000] Validation [1/4] Loss: 0.23359 focal_loss 0.16496 dice_loss 0.06863 +Epoch [1563/4000] Validation [2/4] Loss: 0.36209 focal_loss 0.22002 dice_loss 0.14207 +Epoch [1563/4000] Validation [3/4] Loss: 0.34291 focal_loss 0.24230 dice_loss 0.10061 +Epoch [1563/4000] Validation [4/4] Loss: 0.34184 focal_loss 0.21459 dice_loss 0.12726 +Epoch [1563/4000] Validation metric {'Val/mean dice_metric': 0.969267725944519, 'Val/mean miou_metric': 0.952287495136261, 'Val/mean f1': 0.972359299659729, 'Val/mean precision': 0.9715921878814697, 'Val/mean recall': 0.9731276035308838, 'Val/mean hd95_metric': 5.395400047302246} +Cheakpoint... +Epoch [1563/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969267725944519, 'Val/mean miou_metric': 0.952287495136261, 'Val/mean f1': 0.972359299659729, 'Val/mean precision': 0.9715921878814697, 'Val/mean recall': 0.9731276035308838, 'Val/mean hd95_metric': 5.395400047302246} +Epoch [1564/4000] Training [1/16] Loss: 0.00603 +Epoch [1564/4000] Training [2/16] Loss: 0.00574 +Epoch [1564/4000] Training [3/16] Loss: 0.00842 +Epoch [1564/4000] Training [4/16] Loss: 0.00773 +Epoch [1564/4000] Training [5/16] Loss: 0.01023 +Epoch [1564/4000] Training [6/16] Loss: 0.00739 +Epoch [1564/4000] Training [7/16] Loss: 0.00826 +Epoch [1564/4000] Training [8/16] Loss: 0.00634 +Epoch [1564/4000] Training [9/16] Loss: 0.00670 +Epoch [1564/4000] Training [10/16] Loss: 0.00969 +Epoch [1564/4000] Training [11/16] Loss: 0.00807 +Epoch [1564/4000] Training [12/16] Loss: 0.00694 +Epoch [1564/4000] Training [13/16] Loss: 0.00648 +Epoch [1564/4000] Training [14/16] Loss: 0.00690 +Epoch [1564/4000] Training [15/16] Loss: 0.00562 +Epoch [1564/4000] Training [16/16] Loss: 0.00784 +Epoch [1564/4000] Training metric {'Train/mean dice_metric': 0.9948002099990845, 'Train/mean miou_metric': 0.9894030094146729, 'Train/mean f1': 0.9908852577209473, 'Train/mean precision': 0.9862690567970276, 'Train/mean recall': 0.9955448508262634, 'Train/mean hd95_metric': 1.081397533416748} +Epoch [1564/4000] Validation [1/4] Loss: 0.29715 focal_loss 0.21941 dice_loss 0.07775 +Epoch [1564/4000] Validation [2/4] Loss: 0.48521 focal_loss 0.29605 dice_loss 0.18916 +Epoch [1564/4000] Validation [3/4] Loss: 0.15168 focal_loss 0.09371 dice_loss 0.05797 +Epoch [1564/4000] Validation [4/4] Loss: 0.32086 focal_loss 0.21674 dice_loss 0.10412 +Epoch [1564/4000] Validation metric {'Val/mean dice_metric': 0.9709442257881165, 'Val/mean miou_metric': 0.9538248181343079, 'Val/mean f1': 0.9729584455490112, 'Val/mean precision': 0.972895622253418, 'Val/mean recall': 0.9730212688446045, 'Val/mean hd95_metric': 5.287326812744141} +Cheakpoint... +Epoch [1564/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709442257881165, 'Val/mean miou_metric': 0.9538248181343079, 'Val/mean f1': 0.9729584455490112, 'Val/mean precision': 0.972895622253418, 'Val/mean recall': 0.9730212688446045, 'Val/mean hd95_metric': 5.287326812744141} +Epoch [1565/4000] Training [1/16] Loss: 0.00752 +Epoch [1565/4000] Training [2/16] Loss: 0.00715 +Epoch [1565/4000] Training [3/16] Loss: 0.00765 +Epoch [1565/4000] Training [4/16] Loss: 0.00969 +Epoch [1565/4000] Training [5/16] Loss: 0.00872 +Epoch [1565/4000] Training [6/16] Loss: 0.00614 +Epoch [1565/4000] Training [7/16] Loss: 0.00549 +Epoch [1565/4000] Training [8/16] Loss: 0.00824 +Epoch [1565/4000] Training [9/16] Loss: 0.00880 +Epoch [1565/4000] Training [10/16] Loss: 0.00843 +Epoch [1565/4000] Training [11/16] Loss: 0.00988 +Epoch [1565/4000] Training [12/16] Loss: 0.00777 +Epoch [1565/4000] Training [13/16] Loss: 0.00835 +Epoch [1565/4000] Training [14/16] Loss: 0.00863 +Epoch [1565/4000] Training [15/16] Loss: 0.00771 +Epoch [1565/4000] Training [16/16] Loss: 0.00780 +Epoch [1565/4000] Training metric {'Train/mean dice_metric': 0.9948589205741882, 'Train/mean miou_metric': 0.9895034432411194, 'Train/mean f1': 0.9906182289123535, 'Train/mean precision': 0.9859887361526489, 'Train/mean recall': 0.9952914714813232, 'Train/mean hd95_metric': 1.0357797145843506} +Epoch [1565/4000] Validation [1/4] Loss: 0.57215 focal_loss 0.46005 dice_loss 0.11210 +Epoch [1565/4000] Validation [2/4] Loss: 0.44078 focal_loss 0.25882 dice_loss 0.18196 +Epoch [1565/4000] Validation [3/4] Loss: 0.16192 focal_loss 0.09944 dice_loss 0.06248 +Epoch [1565/4000] Validation [4/4] Loss: 0.23487 focal_loss 0.14083 dice_loss 0.09404 +Epoch [1565/4000] Validation metric {'Val/mean dice_metric': 0.9688474535942078, 'Val/mean miou_metric': 0.9521471261978149, 'Val/mean f1': 0.9716938138008118, 'Val/mean precision': 0.9745868444442749, 'Val/mean recall': 0.9688178896903992, 'Val/mean hd95_metric': 4.795833110809326} +Cheakpoint... +Epoch [1565/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688474535942078, 'Val/mean miou_metric': 0.9521471261978149, 'Val/mean f1': 0.9716938138008118, 'Val/mean precision': 0.9745868444442749, 'Val/mean recall': 0.9688178896903992, 'Val/mean hd95_metric': 4.795833110809326} +Epoch [1566/4000] Training [1/16] Loss: 0.00837 +Epoch [1566/4000] Training [2/16] Loss: 0.00695 +Epoch [1566/4000] Training [3/16] Loss: 0.00780 +Epoch [1566/4000] Training [4/16] Loss: 0.00947 +Epoch [1566/4000] Training [5/16] Loss: 0.00588 +Epoch [1566/4000] Training [6/16] Loss: 0.00666 +Epoch [1566/4000] Training [7/16] Loss: 0.00854 +Epoch [1566/4000] Training [8/16] Loss: 0.00678 +Epoch [1566/4000] Training [9/16] Loss: 0.00740 +Epoch [1566/4000] Training [10/16] Loss: 0.00811 +Epoch [1566/4000] Training [11/16] Loss: 0.00667 +Epoch [1566/4000] Training [12/16] Loss: 0.00888 +Epoch [1566/4000] Training [13/16] Loss: 0.00817 +Epoch [1566/4000] Training [14/16] Loss: 0.00830 +Epoch [1566/4000] Training [15/16] Loss: 0.00768 +Epoch [1566/4000] Training [16/16] Loss: 0.00686 +Epoch [1566/4000] Training metric {'Train/mean dice_metric': 0.9947752952575684, 'Train/mean miou_metric': 0.9893521070480347, 'Train/mean f1': 0.9907517433166504, 'Train/mean precision': 0.9861361980438232, 'Train/mean recall': 0.9954107403755188, 'Train/mean hd95_metric': 1.032773733139038} +Epoch [1566/4000] Validation [1/4] Loss: 0.23154 focal_loss 0.16493 dice_loss 0.06661 +Epoch [1566/4000] Validation [2/4] Loss: 0.35177 focal_loss 0.19906 dice_loss 0.15271 +Epoch [1566/4000] Validation [3/4] Loss: 0.21024 focal_loss 0.12727 dice_loss 0.08298 +Epoch [1566/4000] Validation [4/4] Loss: 0.24879 focal_loss 0.14331 dice_loss 0.10547 +Epoch [1566/4000] Validation metric {'Val/mean dice_metric': 0.9721078872680664, 'Val/mean miou_metric': 0.9548056721687317, 'Val/mean f1': 0.9741167426109314, 'Val/mean precision': 0.9720766544342041, 'Val/mean recall': 0.9761654138565063, 'Val/mean hd95_metric': 5.222198486328125} +Cheakpoint... +Epoch [1566/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721078872680664, 'Val/mean miou_metric': 0.9548056721687317, 'Val/mean f1': 0.9741167426109314, 'Val/mean precision': 0.9720766544342041, 'Val/mean recall': 0.9761654138565063, 'Val/mean hd95_metric': 5.222198486328125} +Epoch [1567/4000] Training [1/16] Loss: 0.00584 +Epoch [1567/4000] Training [2/16] Loss: 0.00727 +Epoch [1567/4000] Training [3/16] Loss: 0.00677 +Epoch [1567/4000] Training [4/16] Loss: 0.01208 +Epoch [1567/4000] Training [5/16] Loss: 0.00747 +Epoch [1567/4000] Training [6/16] Loss: 0.01023 +Epoch [1567/4000] Training [7/16] Loss: 0.00669 +Epoch [1567/4000] Training [8/16] Loss: 0.00527 +Epoch [1567/4000] Training [9/16] Loss: 0.00624 +Epoch [1567/4000] Training [10/16] Loss: 0.00814 +Epoch [1567/4000] Training [11/16] Loss: 0.00730 +Epoch [1567/4000] Training [12/16] Loss: 0.00942 +Epoch [1567/4000] Training [13/16] Loss: 0.00932 +Epoch [1567/4000] Training [14/16] Loss: 0.00693 +Epoch [1567/4000] Training [15/16] Loss: 0.00737 +Epoch [1567/4000] Training [16/16] Loss: 0.00834 +Epoch [1567/4000] Training metric {'Train/mean dice_metric': 0.9945740103721619, 'Train/mean miou_metric': 0.9889585375785828, 'Train/mean f1': 0.990872323513031, 'Train/mean precision': 0.9863144755363464, 'Train/mean recall': 0.9954724907875061, 'Train/mean hd95_metric': 1.0260717868804932} +Epoch [1567/4000] Validation [1/4] Loss: 0.67703 focal_loss 0.53336 dice_loss 0.14367 +Epoch [1567/4000] Validation [2/4] Loss: 0.63325 focal_loss 0.39647 dice_loss 0.23678 +Epoch [1567/4000] Validation [3/4] Loss: 0.20807 focal_loss 0.12720 dice_loss 0.08087 +Epoch [1567/4000] Validation [4/4] Loss: 0.20675 focal_loss 0.11490 dice_loss 0.09185 +Epoch [1567/4000] Validation metric {'Val/mean dice_metric': 0.9691047668457031, 'Val/mean miou_metric': 0.9516595602035522, 'Val/mean f1': 0.9730095863342285, 'Val/mean precision': 0.9739798307418823, 'Val/mean recall': 0.9720413684844971, 'Val/mean hd95_metric': 5.2712507247924805} +Cheakpoint... +Epoch [1567/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691047668457031, 'Val/mean miou_metric': 0.9516595602035522, 'Val/mean f1': 0.9730095863342285, 'Val/mean precision': 0.9739798307418823, 'Val/mean recall': 0.9720413684844971, 'Val/mean hd95_metric': 5.2712507247924805} +Epoch [1568/4000] Training [1/16] Loss: 0.00486 +Epoch [1568/4000] Training [2/16] Loss: 0.00689 +Epoch [1568/4000] Training [3/16] Loss: 0.00718 +Epoch [1568/4000] Training [4/16] Loss: 0.00898 +Epoch [1568/4000] Training [5/16] Loss: 0.01114 +Epoch [1568/4000] Training [6/16] Loss: 0.00796 +Epoch [1568/4000] Training [7/16] Loss: 0.00658 +Epoch [1568/4000] Training [8/16] Loss: 0.00914 +Epoch [1568/4000] Training [9/16] Loss: 0.00671 +Epoch [1568/4000] Training [10/16] Loss: 0.00718 +Epoch [1568/4000] Training [11/16] Loss: 0.00917 +Epoch [1568/4000] Training [12/16] Loss: 0.00713 +Epoch [1568/4000] Training [13/16] Loss: 0.00746 +Epoch [1568/4000] Training [14/16] Loss: 0.00833 +Epoch [1568/4000] Training [15/16] Loss: 0.00616 +Epoch [1568/4000] Training [16/16] Loss: 0.00778 +Epoch [1568/4000] Training metric {'Train/mean dice_metric': 0.9947360754013062, 'Train/mean miou_metric': 0.989252507686615, 'Train/mean f1': 0.9906411170959473, 'Train/mean precision': 0.9859304428100586, 'Train/mean recall': 0.9953970313072205, 'Train/mean hd95_metric': 1.0795104503631592} +Epoch [1568/4000] Validation [1/4] Loss: 0.25042 focal_loss 0.18226 dice_loss 0.06816 +Epoch [1568/4000] Validation [2/4] Loss: 0.50586 focal_loss 0.31127 dice_loss 0.19459 +Epoch [1568/4000] Validation [3/4] Loss: 0.31101 focal_loss 0.21394 dice_loss 0.09707 +Epoch [1568/4000] Validation [4/4] Loss: 0.21579 focal_loss 0.12332 dice_loss 0.09246 +Epoch [1568/4000] Validation metric {'Val/mean dice_metric': 0.9699592590332031, 'Val/mean miou_metric': 0.9531055688858032, 'Val/mean f1': 0.9734815359115601, 'Val/mean precision': 0.9717278480529785, 'Val/mean recall': 0.9752417206764221, 'Val/mean hd95_metric': 5.429141044616699} +Cheakpoint... +Epoch [1568/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699592590332031, 'Val/mean miou_metric': 0.9531055688858032, 'Val/mean f1': 0.9734815359115601, 'Val/mean precision': 0.9717278480529785, 'Val/mean recall': 0.9752417206764221, 'Val/mean hd95_metric': 5.429141044616699} +Epoch [1569/4000] Training [1/16] Loss: 0.00879 +Epoch [1569/4000] Training [2/16] Loss: 0.00692 +Epoch [1569/4000] Training [3/16] Loss: 0.00710 +Epoch [1569/4000] Training [4/16] Loss: 0.00713 +Epoch [1569/4000] Training [5/16] Loss: 0.00804 +Epoch [1569/4000] Training [6/16] Loss: 0.00755 +Epoch [1569/4000] Training [7/16] Loss: 0.00859 +Epoch [1569/4000] Training [8/16] Loss: 0.00936 +Epoch [1569/4000] Training [9/16] Loss: 0.00699 +Epoch [1569/4000] Training [10/16] Loss: 0.00743 +Epoch [1569/4000] Training [11/16] Loss: 0.00672 +Epoch [1569/4000] Training [12/16] Loss: 0.00844 +Epoch [1569/4000] Training [13/16] Loss: 0.00784 +Epoch [1569/4000] Training [14/16] Loss: 0.00770 +Epoch [1569/4000] Training [15/16] Loss: 0.00940 +Epoch [1569/4000] Training [16/16] Loss: 0.01076 +Epoch [1569/4000] Training metric {'Train/mean dice_metric': 0.9940723180770874, 'Train/mean miou_metric': 0.9879806041717529, 'Train/mean f1': 0.9902650713920593, 'Train/mean precision': 0.9855531454086304, 'Train/mean recall': 0.9950222969055176, 'Train/mean hd95_metric': 1.0565673112869263} +Epoch [1569/4000] Validation [1/4] Loss: 0.27623 focal_loss 0.19554 dice_loss 0.08069 +Epoch [1569/4000] Validation [2/4] Loss: 0.31043 focal_loss 0.18521 dice_loss 0.12522 +Epoch [1569/4000] Validation [3/4] Loss: 0.13431 focal_loss 0.08032 dice_loss 0.05400 +Epoch [1569/4000] Validation [4/4] Loss: 0.44757 focal_loss 0.28804 dice_loss 0.15953 +Epoch [1569/4000] Validation metric {'Val/mean dice_metric': 0.968497097492218, 'Val/mean miou_metric': 0.9502334594726562, 'Val/mean f1': 0.9715291261672974, 'Val/mean precision': 0.9720224142074585, 'Val/mean recall': 0.9710363149642944, 'Val/mean hd95_metric': 5.063443183898926} +Cheakpoint... +Epoch [1569/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968497097492218, 'Val/mean miou_metric': 0.9502334594726562, 'Val/mean f1': 0.9715291261672974, 'Val/mean precision': 0.9720224142074585, 'Val/mean recall': 0.9710363149642944, 'Val/mean hd95_metric': 5.063443183898926} +Epoch [1570/4000] Training [1/16] Loss: 0.00648 +Epoch [1570/4000] Training [2/16] Loss: 0.00632 +Epoch [1570/4000] Training [3/16] Loss: 0.00810 +Epoch [1570/4000] Training [4/16] Loss: 0.00924 +Epoch [1570/4000] Training [5/16] Loss: 0.00820 +Epoch [1570/4000] Training [6/16] Loss: 0.00805 +Epoch [1570/4000] Training [7/16] Loss: 0.00658 +Epoch [1570/4000] Training [8/16] Loss: 0.00799 +Epoch [1570/4000] Training [9/16] Loss: 0.00938 +Epoch [1570/4000] Training [10/16] Loss: 0.00880 +Epoch [1570/4000] Training [11/16] Loss: 0.00725 +Epoch [1570/4000] Training [12/16] Loss: 0.00736 +Epoch [1570/4000] Training [13/16] Loss: 0.00847 +Epoch [1570/4000] Training [14/16] Loss: 0.00835 +Epoch [1570/4000] Training [15/16] Loss: 0.01012 +Epoch [1570/4000] Training [16/16] Loss: 0.00879 +Epoch [1570/4000] Training metric {'Train/mean dice_metric': 0.9945076704025269, 'Train/mean miou_metric': 0.9888211488723755, 'Train/mean f1': 0.9905288219451904, 'Train/mean precision': 0.9858756065368652, 'Train/mean recall': 0.9952261447906494, 'Train/mean hd95_metric': 1.0264573097229004} +Epoch [1570/4000] Validation [1/4] Loss: 0.27939 focal_loss 0.19477 dice_loss 0.08462 +Epoch [1570/4000] Validation [2/4] Loss: 0.48712 focal_loss 0.29077 dice_loss 0.19635 +Epoch [1570/4000] Validation [3/4] Loss: 0.14549 focal_loss 0.08917 dice_loss 0.05633 +Epoch [1570/4000] Validation [4/4] Loss: 0.20723 focal_loss 0.12942 dice_loss 0.07780 +Epoch [1570/4000] Validation metric {'Val/mean dice_metric': 0.969935417175293, 'Val/mean miou_metric': 0.9533422589302063, 'Val/mean f1': 0.974385678768158, 'Val/mean precision': 0.9741644859313965, 'Val/mean recall': 0.974606990814209, 'Val/mean hd95_metric': 4.746941089630127} +Cheakpoint... +Epoch [1570/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969935417175293, 'Val/mean miou_metric': 0.9533422589302063, 'Val/mean f1': 0.974385678768158, 'Val/mean precision': 0.9741644859313965, 'Val/mean recall': 0.974606990814209, 'Val/mean hd95_metric': 4.746941089630127} +Epoch [1571/4000] Training [1/16] Loss: 0.00782 +Epoch [1571/4000] Training [2/16] Loss: 0.00777 +Epoch [1571/4000] Training [3/16] Loss: 0.00642 +Epoch [1571/4000] Training [4/16] Loss: 0.00783 +Epoch [1571/4000] Training [5/16] Loss: 0.00663 +Epoch [1571/4000] Training [6/16] Loss: 0.01031 +Epoch [1571/4000] Training [7/16] Loss: 0.00543 +Epoch [1571/4000] Training [8/16] Loss: 0.00640 +Epoch [1571/4000] Training [9/16] Loss: 0.00947 +Epoch [1571/4000] Training [10/16] Loss: 0.00802 +Epoch [1571/4000] Training [11/16] Loss: 0.00861 +Epoch [1571/4000] Training [12/16] Loss: 0.00863 +Epoch [1571/4000] Training [13/16] Loss: 0.00825 +Epoch [1571/4000] Training [14/16] Loss: 0.00752 +Epoch [1571/4000] Training [15/16] Loss: 0.00676 +Epoch [1571/4000] Training [16/16] Loss: 0.00859 +Epoch [1571/4000] Training metric {'Train/mean dice_metric': 0.9944657683372498, 'Train/mean miou_metric': 0.9887412190437317, 'Train/mean f1': 0.9906151294708252, 'Train/mean precision': 0.986117422580719, 'Train/mean recall': 0.9951541423797607, 'Train/mean hd95_metric': 1.0412507057189941} +Epoch [1571/4000] Validation [1/4] Loss: 0.24817 focal_loss 0.18461 dice_loss 0.06356 +Epoch [1571/4000] Validation [2/4] Loss: 0.26805 focal_loss 0.15185 dice_loss 0.11620 +Epoch [1571/4000] Validation [3/4] Loss: 0.19168 focal_loss 0.11572 dice_loss 0.07596 +Epoch [1571/4000] Validation [4/4] Loss: 0.32992 focal_loss 0.21249 dice_loss 0.11742 +Epoch [1571/4000] Validation metric {'Val/mean dice_metric': 0.9708678126335144, 'Val/mean miou_metric': 0.9537962079048157, 'Val/mean f1': 0.974926769733429, 'Val/mean precision': 0.9714683294296265, 'Val/mean recall': 0.9784098863601685, 'Val/mean hd95_metric': 4.931298732757568} +Cheakpoint... +Epoch [1571/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708678126335144, 'Val/mean miou_metric': 0.9537962079048157, 'Val/mean f1': 0.974926769733429, 'Val/mean precision': 0.9714683294296265, 'Val/mean recall': 0.9784098863601685, 'Val/mean hd95_metric': 4.931298732757568} +Epoch [1572/4000] Training [1/16] Loss: 0.00862 +Epoch [1572/4000] Training [2/16] Loss: 0.00618 +Epoch [1572/4000] Training [3/16] Loss: 0.00680 +Epoch [1572/4000] Training [4/16] Loss: 0.00883 +Epoch [1572/4000] Training [5/16] Loss: 0.00874 +Epoch [1572/4000] Training [6/16] Loss: 0.00729 +Epoch [1572/4000] Training [7/16] Loss: 0.01012 +Epoch [1572/4000] Training [8/16] Loss: 0.00941 +Epoch [1572/4000] Training [9/16] Loss: 0.00617 +Epoch [1572/4000] Training [10/16] Loss: 0.00845 +Epoch [1572/4000] Training [11/16] Loss: 0.00918 +Epoch [1572/4000] Training [12/16] Loss: 0.00710 +Epoch [1572/4000] Training [13/16] Loss: 0.00601 +Epoch [1572/4000] Training [14/16] Loss: 0.00684 +Epoch [1572/4000] Training [15/16] Loss: 0.00881 +Epoch [1572/4000] Training [16/16] Loss: 0.00819 +Epoch [1572/4000] Training metric {'Train/mean dice_metric': 0.9945193529129028, 'Train/mean miou_metric': 0.9888569712638855, 'Train/mean f1': 0.9905548095703125, 'Train/mean precision': 0.9858739972114563, 'Train/mean recall': 0.9952802658081055, 'Train/mean hd95_metric': 1.0709213018417358} +Epoch [1572/4000] Validation [1/4] Loss: 0.21551 focal_loss 0.15633 dice_loss 0.05918 +Epoch [1572/4000] Validation [2/4] Loss: 0.30858 focal_loss 0.17919 dice_loss 0.12938 +Epoch [1572/4000] Validation [3/4] Loss: 0.22552 focal_loss 0.14004 dice_loss 0.08548 +Epoch [1572/4000] Validation [4/4] Loss: 0.22416 focal_loss 0.13550 dice_loss 0.08866 +Epoch [1572/4000] Validation metric {'Val/mean dice_metric': 0.9710066914558411, 'Val/mean miou_metric': 0.9539159536361694, 'Val/mean f1': 0.9745245575904846, 'Val/mean precision': 0.9713443517684937, 'Val/mean recall': 0.977725625038147, 'Val/mean hd95_metric': 5.363551139831543} +Cheakpoint... +Epoch [1572/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710066914558411, 'Val/mean miou_metric': 0.9539159536361694, 'Val/mean f1': 0.9745245575904846, 'Val/mean precision': 0.9713443517684937, 'Val/mean recall': 0.977725625038147, 'Val/mean hd95_metric': 5.363551139831543} +Epoch [1573/4000] Training [1/16] Loss: 0.02371 +Epoch [1573/4000] Training [2/16] Loss: 0.00671 +Epoch [1573/4000] Training [3/16] Loss: 0.00829 +Epoch [1573/4000] Training [4/16] Loss: 0.00715 +Epoch [1573/4000] Training [5/16] Loss: 0.00677 +Epoch [1573/4000] Training [6/16] Loss: 0.00920 +Epoch [1573/4000] Training [7/16] Loss: 0.01025 +Epoch [1573/4000] Training [8/16] Loss: 0.00663 +Epoch [1573/4000] Training [9/16] Loss: 0.00795 +Epoch [1573/4000] Training [10/16] Loss: 0.00680 +Epoch [1573/4000] Training [11/16] Loss: 0.00780 +Epoch [1573/4000] Training [12/16] Loss: 0.00755 +Epoch [1573/4000] Training [13/16] Loss: 0.00798 +Epoch [1573/4000] Training [14/16] Loss: 0.00748 +Epoch [1573/4000] Training [15/16] Loss: 0.00676 +Epoch [1573/4000] Training [16/16] Loss: 0.00698 +Epoch [1573/4000] Training metric {'Train/mean dice_metric': 0.9946902990341187, 'Train/mean miou_metric': 0.9892104864120483, 'Train/mean f1': 0.9906723499298096, 'Train/mean precision': 0.986049234867096, 'Train/mean recall': 0.995339035987854, 'Train/mean hd95_metric': 1.029131531715393} +Epoch [1573/4000] Validation [1/4] Loss: 0.24547 focal_loss 0.18190 dice_loss 0.06358 +Epoch [1573/4000] Validation [2/4] Loss: 0.56085 focal_loss 0.34562 dice_loss 0.21523 +Epoch [1573/4000] Validation [3/4] Loss: 0.26365 focal_loss 0.17239 dice_loss 0.09127 +Epoch [1573/4000] Validation [4/4] Loss: 0.23872 focal_loss 0.14177 dice_loss 0.09696 +Epoch [1573/4000] Validation metric {'Val/mean dice_metric': 0.9703153371810913, 'Val/mean miou_metric': 0.9534076452255249, 'Val/mean f1': 0.9737110733985901, 'Val/mean precision': 0.9709508419036865, 'Val/mean recall': 0.9764871597290039, 'Val/mean hd95_metric': 5.46262788772583} +Cheakpoint... +Epoch [1573/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703153371810913, 'Val/mean miou_metric': 0.9534076452255249, 'Val/mean f1': 0.9737110733985901, 'Val/mean precision': 0.9709508419036865, 'Val/mean recall': 0.9764871597290039, 'Val/mean hd95_metric': 5.46262788772583} +Epoch [1574/4000] Training [1/16] Loss: 0.00919 +Epoch [1574/4000] Training [2/16] Loss: 0.00854 +Epoch [1574/4000] Training [3/16] Loss: 0.00658 +Epoch [1574/4000] Training [4/16] Loss: 0.00832 +Epoch [1574/4000] Training [5/16] Loss: 0.00653 +Epoch [1574/4000] Training [6/16] Loss: 0.00888 +Epoch [1574/4000] Training [7/16] Loss: 0.00807 +Epoch [1574/4000] Training [8/16] Loss: 0.00809 +Epoch [1574/4000] Training [9/16] Loss: 0.00833 +Epoch [1574/4000] Training [10/16] Loss: 0.00682 +Epoch [1574/4000] Training [11/16] Loss: 0.00575 +Epoch [1574/4000] Training [12/16] Loss: 0.00855 +Epoch [1574/4000] Training [13/16] Loss: 0.00721 +Epoch [1574/4000] Training [14/16] Loss: 0.00683 +Epoch [1574/4000] Training [15/16] Loss: 0.00637 +Epoch [1574/4000] Training [16/16] Loss: 0.00804 +Epoch [1574/4000] Training metric {'Train/mean dice_metric': 0.9945369958877563, 'Train/mean miou_metric': 0.9888902902603149, 'Train/mean f1': 0.9906763434410095, 'Train/mean precision': 0.9862469434738159, 'Train/mean recall': 0.9951456189155579, 'Train/mean hd95_metric': 1.0574181079864502} +Epoch [1574/4000] Validation [1/4] Loss: 0.27149 focal_loss 0.19963 dice_loss 0.07186 +Epoch [1574/4000] Validation [2/4] Loss: 0.60748 focal_loss 0.34327 dice_loss 0.26421 +Epoch [1574/4000] Validation [3/4] Loss: 0.13418 focal_loss 0.08482 dice_loss 0.04936 +Epoch [1574/4000] Validation [4/4] Loss: 0.21190 focal_loss 0.11799 dice_loss 0.09391 +Epoch [1574/4000] Validation metric {'Val/mean dice_metric': 0.9699853658676147, 'Val/mean miou_metric': 0.9536125063896179, 'Val/mean f1': 0.9740656614303589, 'Val/mean precision': 0.9718372821807861, 'Val/mean recall': 0.9763042330741882, 'Val/mean hd95_metric': 4.777336597442627} +Cheakpoint... +Epoch [1574/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699853658676147, 'Val/mean miou_metric': 0.9536125063896179, 'Val/mean f1': 0.9740656614303589, 'Val/mean precision': 0.9718372821807861, 'Val/mean recall': 0.9763042330741882, 'Val/mean hd95_metric': 4.777336597442627} +Epoch [1575/4000] Training [1/16] Loss: 0.00847 +Epoch [1575/4000] Training [2/16] Loss: 0.00716 +Epoch [1575/4000] Training [3/16] Loss: 0.01053 +Epoch [1575/4000] Training [4/16] Loss: 0.00775 +Epoch [1575/4000] Training [5/16] Loss: 0.00762 +Epoch [1575/4000] Training [6/16] Loss: 0.00590 +Epoch [1575/4000] Training [7/16] Loss: 0.00861 +Epoch [1575/4000] Training [8/16] Loss: 0.00843 +Epoch [1575/4000] Training [9/16] Loss: 0.00759 +Epoch [1575/4000] Training [10/16] Loss: 0.00674 +Epoch [1575/4000] Training [11/16] Loss: 0.00628 +Epoch [1575/4000] Training [12/16] Loss: 0.00685 +Epoch [1575/4000] Training [13/16] Loss: 0.00724 +Epoch [1575/4000] Training [14/16] Loss: 0.00687 +Epoch [1575/4000] Training [15/16] Loss: 0.00685 +Epoch [1575/4000] Training [16/16] Loss: 0.00819 +Epoch [1575/4000] Training metric {'Train/mean dice_metric': 0.9944940805435181, 'Train/mean miou_metric': 0.988825798034668, 'Train/mean f1': 0.9907190203666687, 'Train/mean precision': 0.9860466122627258, 'Train/mean recall': 0.995435893535614, 'Train/mean hd95_metric': 1.0372743606567383} +Epoch [1575/4000] Validation [1/4] Loss: 0.25397 focal_loss 0.18333 dice_loss 0.07064 +Epoch [1575/4000] Validation [2/4] Loss: 0.42517 focal_loss 0.26782 dice_loss 0.15735 +Epoch [1575/4000] Validation [3/4] Loss: 0.15070 focal_loss 0.09372 dice_loss 0.05698 +Epoch [1575/4000] Validation [4/4] Loss: 0.24192 focal_loss 0.14496 dice_loss 0.09696 +Epoch [1575/4000] Validation metric {'Val/mean dice_metric': 0.9722474217414856, 'Val/mean miou_metric': 0.9547159075737, 'Val/mean f1': 0.9738209843635559, 'Val/mean precision': 0.9718273878097534, 'Val/mean recall': 0.9758226275444031, 'Val/mean hd95_metric': 5.2441558837890625} +Cheakpoint... +Epoch [1575/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722474217414856, 'Val/mean miou_metric': 0.9547159075737, 'Val/mean f1': 0.9738209843635559, 'Val/mean precision': 0.9718273878097534, 'Val/mean recall': 0.9758226275444031, 'Val/mean hd95_metric': 5.2441558837890625} +Epoch [1576/4000] Training [1/16] Loss: 0.00739 +Epoch [1576/4000] Training [2/16] Loss: 0.01148 +Epoch [1576/4000] Training [3/16] Loss: 0.00794 +Epoch [1576/4000] Training [4/16] Loss: 0.00855 +Epoch [1576/4000] Training [5/16] Loss: 0.00906 +Epoch [1576/4000] Training [6/16] Loss: 0.00692 +Epoch [1576/4000] Training [7/16] Loss: 0.01015 +Epoch [1576/4000] Training [8/16] Loss: 0.00736 +Epoch [1576/4000] Training [9/16] Loss: 0.00781 +Epoch [1576/4000] Training [10/16] Loss: 0.00706 +Epoch [1576/4000] Training [11/16] Loss: 0.00580 +Epoch [1576/4000] Training [12/16] Loss: 0.01034 +Epoch [1576/4000] Training [13/16] Loss: 0.00702 +Epoch [1576/4000] Training [14/16] Loss: 0.00731 +Epoch [1576/4000] Training [15/16] Loss: 0.00654 +Epoch [1576/4000] Training [16/16] Loss: 0.00794 +Epoch [1576/4000] Training metric {'Train/mean dice_metric': 0.9944692850112915, 'Train/mean miou_metric': 0.9887394309043884, 'Train/mean f1': 0.9905261397361755, 'Train/mean precision': 0.9860526919364929, 'Train/mean recall': 0.9950404167175293, 'Train/mean hd95_metric': 1.2940367460250854} +Epoch [1576/4000] Validation [1/4] Loss: 0.29041 focal_loss 0.21575 dice_loss 0.07466 +Epoch [1576/4000] Validation [2/4] Loss: 0.45908 focal_loss 0.28589 dice_loss 0.17319 +Epoch [1576/4000] Validation [3/4] Loss: 0.31613 focal_loss 0.21398 dice_loss 0.10215 +Epoch [1576/4000] Validation [4/4] Loss: 0.25311 focal_loss 0.14611 dice_loss 0.10699 +Epoch [1576/4000] Validation metric {'Val/mean dice_metric': 0.9729183316230774, 'Val/mean miou_metric': 0.9549417495727539, 'Val/mean f1': 0.9734964966773987, 'Val/mean precision': 0.9712420701980591, 'Val/mean recall': 0.9757614135742188, 'Val/mean hd95_metric': 5.284958839416504} +Cheakpoint... +Epoch [1576/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729183316230774, 'Val/mean miou_metric': 0.9549417495727539, 'Val/mean f1': 0.9734964966773987, 'Val/mean precision': 0.9712420701980591, 'Val/mean recall': 0.9757614135742188, 'Val/mean hd95_metric': 5.284958839416504} +Epoch [1577/4000] Training [1/16] Loss: 0.00733 +Epoch [1577/4000] Training [2/16] Loss: 0.01014 +Epoch [1577/4000] Training [3/16] Loss: 0.00744 +Epoch [1577/4000] Training [4/16] Loss: 0.00686 +Epoch [1577/4000] Training [5/16] Loss: 0.00793 +Epoch [1577/4000] Training [6/16] Loss: 0.00951 +Epoch [1577/4000] Training [7/16] Loss: 0.00987 +Epoch [1577/4000] Training [8/16] Loss: 0.00601 +Epoch [1577/4000] Training [9/16] Loss: 0.00775 +Epoch [1577/4000] Training [10/16] Loss: 0.00895 +Epoch [1577/4000] Training [11/16] Loss: 0.00665 +Epoch [1577/4000] Training [12/16] Loss: 0.00690 +Epoch [1577/4000] Training [13/16] Loss: 0.00816 +Epoch [1577/4000] Training [14/16] Loss: 0.00677 +Epoch [1577/4000] Training [15/16] Loss: 0.00699 +Epoch [1577/4000] Training [16/16] Loss: 0.00827 +Epoch [1577/4000] Training metric {'Train/mean dice_metric': 0.9946293830871582, 'Train/mean miou_metric': 0.9890647530555725, 'Train/mean f1': 0.9906226396560669, 'Train/mean precision': 0.9861329197883606, 'Train/mean recall': 0.9951534867286682, 'Train/mean hd95_metric': 1.0372587442398071} +Epoch [1577/4000] Validation [1/4] Loss: 0.22965 focal_loss 0.16378 dice_loss 0.06587 +Epoch [1577/4000] Validation [2/4] Loss: 0.25028 focal_loss 0.13865 dice_loss 0.11163 +Epoch [1577/4000] Validation [3/4] Loss: 0.29125 focal_loss 0.20356 dice_loss 0.08769 +Epoch [1577/4000] Validation [4/4] Loss: 0.23348 focal_loss 0.13969 dice_loss 0.09379 +Epoch [1577/4000] Validation metric {'Val/mean dice_metric': 0.9729048013687134, 'Val/mean miou_metric': 0.9555157423019409, 'Val/mean f1': 0.9736489653587341, 'Val/mean precision': 0.9686334133148193, 'Val/mean recall': 0.9787166714668274, 'Val/mean hd95_metric': 5.825918674468994} +Cheakpoint... +Epoch [1577/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729048013687134, 'Val/mean miou_metric': 0.9555157423019409, 'Val/mean f1': 0.9736489653587341, 'Val/mean precision': 0.9686334133148193, 'Val/mean recall': 0.9787166714668274, 'Val/mean hd95_metric': 5.825918674468994} +Epoch [1578/4000] Training [1/16] Loss: 0.00716 +Epoch [1578/4000] Training [2/16] Loss: 0.00692 +Epoch [1578/4000] Training [3/16] Loss: 0.00711 +Epoch [1578/4000] Training [4/16] Loss: 0.00691 +Epoch [1578/4000] Training [5/16] Loss: 0.00860 +Epoch [1578/4000] Training [6/16] Loss: 0.00679 +Epoch [1578/4000] Training [7/16] Loss: 0.00774 +Epoch [1578/4000] Training [8/16] Loss: 0.01112 +Epoch [1578/4000] Training [9/16] Loss: 0.00591 +Epoch [1578/4000] Training [10/16] Loss: 0.00660 +Epoch [1578/4000] Training [11/16] Loss: 0.00714 +Epoch [1578/4000] Training [12/16] Loss: 0.00679 +Epoch [1578/4000] Training [13/16] Loss: 0.00698 +Epoch [1578/4000] Training [14/16] Loss: 0.00796 +Epoch [1578/4000] Training [15/16] Loss: 0.00723 +Epoch [1578/4000] Training [16/16] Loss: 0.01339 +Epoch [1578/4000] Training metric {'Train/mean dice_metric': 0.9946516156196594, 'Train/mean miou_metric': 0.9891239404678345, 'Train/mean f1': 0.9908871054649353, 'Train/mean precision': 0.9863179922103882, 'Train/mean recall': 0.995498776435852, 'Train/mean hd95_metric': 1.0410866737365723} +Epoch [1578/4000] Validation [1/4] Loss: 0.23913 focal_loss 0.17191 dice_loss 0.06722 +Epoch [1578/4000] Validation [2/4] Loss: 0.25062 focal_loss 0.13388 dice_loss 0.11674 +Epoch [1578/4000] Validation [3/4] Loss: 0.16206 focal_loss 0.10187 dice_loss 0.06019 +Epoch [1578/4000] Validation [4/4] Loss: 0.23300 focal_loss 0.13662 dice_loss 0.09638 +Epoch [1578/4000] Validation metric {'Val/mean dice_metric': 0.971678614616394, 'Val/mean miou_metric': 0.9547999501228333, 'Val/mean f1': 0.9743112921714783, 'Val/mean precision': 0.9718316197395325, 'Val/mean recall': 0.976803719997406, 'Val/mean hd95_metric': 5.426987171173096} +Cheakpoint... +Epoch [1578/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971678614616394, 'Val/mean miou_metric': 0.9547999501228333, 'Val/mean f1': 0.9743112921714783, 'Val/mean precision': 0.9718316197395325, 'Val/mean recall': 0.976803719997406, 'Val/mean hd95_metric': 5.426987171173096} +Epoch [1579/4000] Training [1/16] Loss: 0.00880 +Epoch [1579/4000] Training [2/16] Loss: 0.00806 +Epoch [1579/4000] Training [3/16] Loss: 0.00756 +Epoch [1579/4000] Training [4/16] Loss: 0.00634 +Epoch [1579/4000] Training [5/16] Loss: 0.00769 +Epoch [1579/4000] Training [6/16] Loss: 0.00629 +Epoch [1579/4000] Training [7/16] Loss: 0.00928 +Epoch [1579/4000] Training [8/16] Loss: 0.00991 +Epoch [1579/4000] Training [9/16] Loss: 0.00889 +Epoch [1579/4000] Training [10/16] Loss: 0.00883 +Epoch [1579/4000] Training [11/16] Loss: 0.01120 +Epoch [1579/4000] Training [12/16] Loss: 0.00999 +Epoch [1579/4000] Training [13/16] Loss: 0.01013 +Epoch [1579/4000] Training [14/16] Loss: 0.01063 +Epoch [1579/4000] Training [15/16] Loss: 0.00831 +Epoch [1579/4000] Training [16/16] Loss: 0.00747 +Epoch [1579/4000] Training metric {'Train/mean dice_metric': 0.9944851994514465, 'Train/mean miou_metric': 0.9887451529502869, 'Train/mean f1': 0.9894524812698364, 'Train/mean precision': 0.9839785695075989, 'Train/mean recall': 0.9949876070022583, 'Train/mean hd95_metric': 1.047151803970337} +Epoch [1579/4000] Validation [1/4] Loss: 0.40979 focal_loss 0.30870 dice_loss 0.10109 +Epoch [1579/4000] Validation [2/4] Loss: 0.37609 focal_loss 0.22346 dice_loss 0.15263 +Epoch [1579/4000] Validation [3/4] Loss: 0.19013 focal_loss 0.11140 dice_loss 0.07873 +Epoch [1579/4000] Validation [4/4] Loss: 0.21497 focal_loss 0.11945 dice_loss 0.09552 +Epoch [1579/4000] Validation metric {'Val/mean dice_metric': 0.9715118408203125, 'Val/mean miou_metric': 0.9537453651428223, 'Val/mean f1': 0.9722630977630615, 'Val/mean precision': 0.9703635573387146, 'Val/mean recall': 0.9741701483726501, 'Val/mean hd95_metric': 5.3728132247924805} +Cheakpoint... +Epoch [1579/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715118408203125, 'Val/mean miou_metric': 0.9537453651428223, 'Val/mean f1': 0.9722630977630615, 'Val/mean precision': 0.9703635573387146, 'Val/mean recall': 0.9741701483726501, 'Val/mean hd95_metric': 5.3728132247924805} +Epoch [1580/4000] Training [1/16] Loss: 0.00969 +Epoch [1580/4000] Training [2/16] Loss: 0.00574 +Epoch [1580/4000] Training [3/16] Loss: 0.00933 +Epoch [1580/4000] Training [4/16] Loss: 0.00622 +Epoch [1580/4000] Training [5/16] Loss: 0.01354 +Epoch [1580/4000] Training [6/16] Loss: 0.00817 +Epoch [1580/4000] Training [7/16] Loss: 0.00992 +Epoch [1580/4000] Training [8/16] Loss: 0.00697 +Epoch [1580/4000] Training [9/16] Loss: 0.00761 +Epoch [1580/4000] Training [10/16] Loss: 0.00677 +Epoch [1580/4000] Training [11/16] Loss: 0.00627 +Epoch [1580/4000] Training [12/16] Loss: 0.01047 +Epoch [1580/4000] Training [13/16] Loss: 0.00626 +Epoch [1580/4000] Training [14/16] Loss: 0.00772 +Epoch [1580/4000] Training [15/16] Loss: 0.00845 +Epoch [1580/4000] Training [16/16] Loss: 0.01041 +Epoch [1580/4000] Training metric {'Train/mean dice_metric': 0.9945749044418335, 'Train/mean miou_metric': 0.9889035224914551, 'Train/mean f1': 0.9892426133155823, 'Train/mean precision': 0.9834120869636536, 'Train/mean recall': 0.9951426386833191, 'Train/mean hd95_metric': 1.0440852642059326} +Epoch [1580/4000] Validation [1/4] Loss: 0.27002 focal_loss 0.20107 dice_loss 0.06896 +Epoch [1580/4000] Validation [2/4] Loss: 0.29137 focal_loss 0.16343 dice_loss 0.12794 +Epoch [1580/4000] Validation [3/4] Loss: 0.29175 focal_loss 0.19349 dice_loss 0.09826 +Epoch [1580/4000] Validation [4/4] Loss: 0.22664 focal_loss 0.11773 dice_loss 0.10891 +Epoch [1580/4000] Validation metric {'Val/mean dice_metric': 0.9732195138931274, 'Val/mean miou_metric': 0.955361008644104, 'Val/mean f1': 0.9734622240066528, 'Val/mean precision': 0.969781219959259, 'Val/mean recall': 0.9771713614463806, 'Val/mean hd95_metric': 5.261547565460205} +Cheakpoint... +Epoch [1580/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732195138931274, 'Val/mean miou_metric': 0.955361008644104, 'Val/mean f1': 0.9734622240066528, 'Val/mean precision': 0.969781219959259, 'Val/mean recall': 0.9771713614463806, 'Val/mean hd95_metric': 5.261547565460205} +Epoch [1581/4000] Training [1/16] Loss: 0.00796 +Epoch [1581/4000] Training [2/16] Loss: 0.00716 +Epoch [1581/4000] Training [3/16] Loss: 0.01221 +Epoch [1581/4000] Training [4/16] Loss: 0.01100 +Epoch [1581/4000] Training [5/16] Loss: 0.00877 +Epoch [1581/4000] Training [6/16] Loss: 0.00993 +Epoch [1581/4000] Training [7/16] Loss: 0.00650 +Epoch [1581/4000] Training [8/16] Loss: 0.00762 +Epoch [1581/4000] Training [9/16] Loss: 0.00647 +Epoch [1581/4000] Training [10/16] Loss: 0.00638 +Epoch [1581/4000] Training [11/16] Loss: 0.00624 +Epoch [1581/4000] Training [12/16] Loss: 0.00906 +Epoch [1581/4000] Training [13/16] Loss: 0.00738 +Epoch [1581/4000] Training [14/16] Loss: 0.00732 +Epoch [1581/4000] Training [15/16] Loss: 0.00899 +Epoch [1581/4000] Training [16/16] Loss: 0.00888 +Epoch [1581/4000] Training metric {'Train/mean dice_metric': 0.9946514368057251, 'Train/mean miou_metric': 0.9890975952148438, 'Train/mean f1': 0.9905744194984436, 'Train/mean precision': 0.9858840107917786, 'Train/mean recall': 0.9953097105026245, 'Train/mean hd95_metric': 1.0431630611419678} +Epoch [1581/4000] Validation [1/4] Loss: 0.24806 focal_loss 0.17609 dice_loss 0.07197 +Epoch [1581/4000] Validation [2/4] Loss: 0.52781 focal_loss 0.32382 dice_loss 0.20399 +Epoch [1581/4000] Validation [3/4] Loss: 0.16615 focal_loss 0.09927 dice_loss 0.06688 +Epoch [1581/4000] Validation [4/4] Loss: 0.19385 focal_loss 0.10893 dice_loss 0.08492 +Epoch [1581/4000] Validation metric {'Val/mean dice_metric': 0.9730501174926758, 'Val/mean miou_metric': 0.9556350708007812, 'Val/mean f1': 0.9746282696723938, 'Val/mean precision': 0.9731269478797913, 'Val/mean recall': 0.9761341214179993, 'Val/mean hd95_metric': 5.2158026695251465} +Cheakpoint... +Epoch [1581/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730501174926758, 'Val/mean miou_metric': 0.9556350708007812, 'Val/mean f1': 0.9746282696723938, 'Val/mean precision': 0.9731269478797913, 'Val/mean recall': 0.9761341214179993, 'Val/mean hd95_metric': 5.2158026695251465} +Epoch [1582/4000] Training [1/16] Loss: 0.00902 +Epoch [1582/4000] Training [2/16] Loss: 0.00692 +Epoch [1582/4000] Training [3/16] Loss: 0.00773 +Epoch [1582/4000] Training [4/16] Loss: 0.00618 +Epoch [1582/4000] Training [5/16] Loss: 0.00625 +Epoch [1582/4000] Training [6/16] Loss: 0.00757 +Epoch [1582/4000] Training [7/16] Loss: 0.00745 +Epoch [1582/4000] Training [8/16] Loss: 0.00585 +Epoch [1582/4000] Training [9/16] Loss: 0.00681 +Epoch [1582/4000] Training [10/16] Loss: 0.00924 +Epoch [1582/4000] Training [11/16] Loss: 0.00864 +Epoch [1582/4000] Training [12/16] Loss: 0.00852 +Epoch [1582/4000] Training [13/16] Loss: 0.01106 +Epoch [1582/4000] Training [14/16] Loss: 0.00954 +Epoch [1582/4000] Training [15/16] Loss: 0.01005 +Epoch [1582/4000] Training [16/16] Loss: 0.00701 +Epoch [1582/4000] Training metric {'Train/mean dice_metric': 0.9945230484008789, 'Train/mean miou_metric': 0.9888283610343933, 'Train/mean f1': 0.9902642369270325, 'Train/mean precision': 0.9856085181236267, 'Train/mean recall': 0.9949641227722168, 'Train/mean hd95_metric': 1.0454893112182617} +Epoch [1582/4000] Validation [1/4] Loss: 0.36731 focal_loss 0.27602 dice_loss 0.09129 +Epoch [1582/4000] Validation [2/4] Loss: 0.32637 focal_loss 0.18674 dice_loss 0.13963 +Epoch [1582/4000] Validation [3/4] Loss: 0.33496 focal_loss 0.23655 dice_loss 0.09841 +Epoch [1582/4000] Validation [4/4] Loss: 0.23359 focal_loss 0.13711 dice_loss 0.09648 +Epoch [1582/4000] Validation metric {'Val/mean dice_metric': 0.9729433059692383, 'Val/mean miou_metric': 0.9547374844551086, 'Val/mean f1': 0.9733465313911438, 'Val/mean precision': 0.9705486297607422, 'Val/mean recall': 0.9761605262756348, 'Val/mean hd95_metric': 5.778910160064697} +Cheakpoint... +Epoch [1582/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729433059692383, 'Val/mean miou_metric': 0.9547374844551086, 'Val/mean f1': 0.9733465313911438, 'Val/mean precision': 0.9705486297607422, 'Val/mean recall': 0.9761605262756348, 'Val/mean hd95_metric': 5.778910160064697} +Epoch [1583/4000] Training [1/16] Loss: 0.01493 +Epoch [1583/4000] Training [2/16] Loss: 0.00921 +Epoch [1583/4000] Training [3/16] Loss: 0.00670 +Epoch [1583/4000] Training [4/16] Loss: 0.00860 +Epoch [1583/4000] Training [5/16] Loss: 0.00837 +Epoch [1583/4000] Training [6/16] Loss: 0.00709 +Epoch [1583/4000] Training [7/16] Loss: 0.00657 +Epoch [1583/4000] Training [8/16] Loss: 0.00610 +Epoch [1583/4000] Training [9/16] Loss: 0.00663 +Epoch [1583/4000] Training [10/16] Loss: 0.00665 +Epoch [1583/4000] Training [11/16] Loss: 0.00666 +Epoch [1583/4000] Training [12/16] Loss: 0.00938 +Epoch [1583/4000] Training [13/16] Loss: 0.00776 +Epoch [1583/4000] Training [14/16] Loss: 0.00685 +Epoch [1583/4000] Training [15/16] Loss: 0.00642 +Epoch [1583/4000] Training [16/16] Loss: 0.00682 +Epoch [1583/4000] Training metric {'Train/mean dice_metric': 0.9946273565292358, 'Train/mean miou_metric': 0.989062488079071, 'Train/mean f1': 0.9906893372535706, 'Train/mean precision': 0.9860469102859497, 'Train/mean recall': 0.9953756332397461, 'Train/mean hd95_metric': 1.05629563331604} +Epoch [1583/4000] Validation [1/4] Loss: 0.23255 focal_loss 0.17297 dice_loss 0.05958 +Epoch [1583/4000] Validation [2/4] Loss: 0.23060 focal_loss 0.12229 dice_loss 0.10831 +Epoch [1583/4000] Validation [3/4] Loss: 0.32312 focal_loss 0.22704 dice_loss 0.09608 +Epoch [1583/4000] Validation [4/4] Loss: 0.31259 focal_loss 0.19356 dice_loss 0.11904 +Epoch [1583/4000] Validation metric {'Val/mean dice_metric': 0.9729232788085938, 'Val/mean miou_metric': 0.9553141593933105, 'Val/mean f1': 0.9737086892127991, 'Val/mean precision': 0.9677667617797852, 'Val/mean recall': 0.979724109172821, 'Val/mean hd95_metric': 5.812295436859131} +Cheakpoint... +Epoch [1583/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729232788085938, 'Val/mean miou_metric': 0.9553141593933105, 'Val/mean f1': 0.9737086892127991, 'Val/mean precision': 0.9677667617797852, 'Val/mean recall': 0.979724109172821, 'Val/mean hd95_metric': 5.812295436859131} +Epoch [1584/4000] Training [1/16] Loss: 0.00880 +Epoch [1584/4000] Training [2/16] Loss: 0.00684 +Epoch [1584/4000] Training [3/16] Loss: 0.00664 +Epoch [1584/4000] Training [4/16] Loss: 0.00629 +Epoch [1584/4000] Training [5/16] Loss: 0.00800 +Epoch [1584/4000] Training [6/16] Loss: 0.00625 +Epoch [1584/4000] Training [7/16] Loss: 0.00915 +Epoch [1584/4000] Training [8/16] Loss: 0.01174 +Epoch [1584/4000] Training [9/16] Loss: 0.00641 +Epoch [1584/4000] Training [10/16] Loss: 0.00898 +Epoch [1584/4000] Training [11/16] Loss: 0.00686 +Epoch [1584/4000] Training [12/16] Loss: 0.00693 +Epoch [1584/4000] Training [13/16] Loss: 0.01090 +Epoch [1584/4000] Training [14/16] Loss: 0.00658 +Epoch [1584/4000] Training [15/16] Loss: 0.00835 +Epoch [1584/4000] Training [16/16] Loss: 0.01211 +Epoch [1584/4000] Training metric {'Train/mean dice_metric': 0.9944612383842468, 'Train/mean miou_metric': 0.9886965751647949, 'Train/mean f1': 0.9900872111320496, 'Train/mean precision': 0.9851224422454834, 'Train/mean recall': 0.9951021671295166, 'Train/mean hd95_metric': 1.0417708158493042} +Epoch [1584/4000] Validation [1/4] Loss: 0.29612 focal_loss 0.22188 dice_loss 0.07424 +Epoch [1584/4000] Validation [2/4] Loss: 0.34771 focal_loss 0.20095 dice_loss 0.14676 +Epoch [1584/4000] Validation [3/4] Loss: 0.27317 focal_loss 0.18588 dice_loss 0.08729 +Epoch [1584/4000] Validation [4/4] Loss: 0.23573 focal_loss 0.14899 dice_loss 0.08674 +Epoch [1584/4000] Validation metric {'Val/mean dice_metric': 0.9707986116409302, 'Val/mean miou_metric': 0.9532512426376343, 'Val/mean f1': 0.9734416007995605, 'Val/mean precision': 0.9699361324310303, 'Val/mean recall': 0.9769725203514099, 'Val/mean hd95_metric': 6.16837215423584} +Cheakpoint... +Epoch [1584/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707986116409302, 'Val/mean miou_metric': 0.9532512426376343, 'Val/mean f1': 0.9734416007995605, 'Val/mean precision': 0.9699361324310303, 'Val/mean recall': 0.9769725203514099, 'Val/mean hd95_metric': 6.16837215423584} +Epoch [1585/4000] Training [1/16] Loss: 0.00607 +Epoch [1585/4000] Training [2/16] Loss: 0.00548 +Epoch [1585/4000] Training [3/16] Loss: 0.00613 +Epoch [1585/4000] Training [4/16] Loss: 0.00925 +Epoch [1585/4000] Training [5/16] Loss: 0.01097 +Epoch [1585/4000] Training [6/16] Loss: 0.00981 +Epoch [1585/4000] Training [7/16] Loss: 0.00696 +Epoch [1585/4000] Training [8/16] Loss: 0.00849 +Epoch [1585/4000] Training [9/16] Loss: 0.00735 +Epoch [1585/4000] Training [10/16] Loss: 0.00568 +Epoch [1585/4000] Training [11/16] Loss: 0.00692 +Epoch [1585/4000] Training [12/16] Loss: 0.00725 +Epoch [1585/4000] Training [13/16] Loss: 0.00813 +Epoch [1585/4000] Training [14/16] Loss: 0.00851 +Epoch [1585/4000] Training [15/16] Loss: 0.00754 +Epoch [1585/4000] Training [16/16] Loss: 0.00765 +Epoch [1585/4000] Training metric {'Train/mean dice_metric': 0.9947999715805054, 'Train/mean miou_metric': 0.9893956184387207, 'Train/mean f1': 0.9907131791114807, 'Train/mean precision': 0.9859572052955627, 'Train/mean recall': 0.9955152869224548, 'Train/mean hd95_metric': 1.0209972858428955} +Epoch [1585/4000] Validation [1/4] Loss: 0.30249 focal_loss 0.22885 dice_loss 0.07364 +Epoch [1585/4000] Validation [2/4] Loss: 0.54315 focal_loss 0.33344 dice_loss 0.20971 +Epoch [1585/4000] Validation [3/4] Loss: 0.15569 focal_loss 0.08782 dice_loss 0.06787 +Epoch [1585/4000] Validation [4/4] Loss: 0.22210 focal_loss 0.13246 dice_loss 0.08965 +Epoch [1585/4000] Validation metric {'Val/mean dice_metric': 0.9715476036071777, 'Val/mean miou_metric': 0.9549436569213867, 'Val/mean f1': 0.9741652011871338, 'Val/mean precision': 0.9717043042182922, 'Val/mean recall': 0.9766386151313782, 'Val/mean hd95_metric': 5.141016960144043} +Cheakpoint... +Epoch [1585/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715476036071777, 'Val/mean miou_metric': 0.9549436569213867, 'Val/mean f1': 0.9741652011871338, 'Val/mean precision': 0.9717043042182922, 'Val/mean recall': 0.9766386151313782, 'Val/mean hd95_metric': 5.141016960144043} +Epoch [1586/4000] Training [1/16] Loss: 0.01041 +Epoch [1586/4000] Training [2/16] Loss: 0.00778 +Epoch [1586/4000] Training [3/16] Loss: 0.00637 +Epoch [1586/4000] Training [4/16] Loss: 0.00848 +Epoch [1586/4000] Training [5/16] Loss: 0.00997 +Epoch [1586/4000] Training [6/16] Loss: 0.00995 +Epoch [1586/4000] Training [7/16] Loss: 0.00703 +Epoch [1586/4000] Training [8/16] Loss: 0.01126 +Epoch [1586/4000] Training [9/16] Loss: 0.00676 +Epoch [1586/4000] Training [10/16] Loss: 0.00579 +Epoch [1586/4000] Training [11/16] Loss: 0.00734 +Epoch [1586/4000] Training [12/16] Loss: 0.00983 +Epoch [1586/4000] Training [13/16] Loss: 0.00645 +Epoch [1586/4000] Training [14/16] Loss: 0.00780 +Epoch [1586/4000] Training [15/16] Loss: 0.01071 +Epoch [1586/4000] Training [16/16] Loss: 0.00758 +Epoch [1586/4000] Training metric {'Train/mean dice_metric': 0.9943071007728577, 'Train/mean miou_metric': 0.9884364604949951, 'Train/mean f1': 0.9904980063438416, 'Train/mean precision': 0.9859803318977356, 'Train/mean recall': 0.9950572848320007, 'Train/mean hd95_metric': 1.0634418725967407} +Epoch [1586/4000] Validation [1/4] Loss: 0.34647 focal_loss 0.26312 dice_loss 0.08335 +Epoch [1586/4000] Validation [2/4] Loss: 0.34562 focal_loss 0.19601 dice_loss 0.14961 +Epoch [1586/4000] Validation [3/4] Loss: 0.20860 focal_loss 0.12764 dice_loss 0.08096 +Epoch [1586/4000] Validation [4/4] Loss: 0.19412 focal_loss 0.10043 dice_loss 0.09369 +Epoch [1586/4000] Validation metric {'Val/mean dice_metric': 0.9716609716415405, 'Val/mean miou_metric': 0.9535433053970337, 'Val/mean f1': 0.9728017449378967, 'Val/mean precision': 0.9692292213439941, 'Val/mean recall': 0.9764006733894348, 'Val/mean hd95_metric': 6.00469446182251} +Cheakpoint... +Epoch [1586/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716609716415405, 'Val/mean miou_metric': 0.9535433053970337, 'Val/mean f1': 0.9728017449378967, 'Val/mean precision': 0.9692292213439941, 'Val/mean recall': 0.9764006733894348, 'Val/mean hd95_metric': 6.00469446182251} +Epoch [1587/4000] Training [1/16] Loss: 0.00677 +Epoch [1587/4000] Training [2/16] Loss: 0.00718 +Epoch [1587/4000] Training [3/16] Loss: 0.00718 +Epoch [1587/4000] Training [4/16] Loss: 0.00873 +Epoch [1587/4000] Training [5/16] Loss: 0.00668 +Epoch [1587/4000] Training [6/16] Loss: 0.00722 +Epoch [1587/4000] Training [7/16] Loss: 0.00711 +Epoch [1587/4000] Training [8/16] Loss: 0.00649 +Epoch [1587/4000] Training [9/16] Loss: 0.00638 +Epoch [1587/4000] Training [10/16] Loss: 0.00814 +Epoch [1587/4000] Training [11/16] Loss: 0.00815 +Epoch [1587/4000] Training [12/16] Loss: 0.00794 +Epoch [1587/4000] Training [13/16] Loss: 0.00655 +Epoch [1587/4000] Training [14/16] Loss: 0.00735 +Epoch [1587/4000] Training [15/16] Loss: 0.00755 +Epoch [1587/4000] Training [16/16] Loss: 0.00855 +Epoch [1587/4000] Training metric {'Train/mean dice_metric': 0.9947773218154907, 'Train/mean miou_metric': 0.9893511533737183, 'Train/mean f1': 0.9905315041542053, 'Train/mean precision': 0.9856727123260498, 'Train/mean recall': 0.9954385161399841, 'Train/mean hd95_metric': 1.0374622344970703} +Epoch [1587/4000] Validation [1/4] Loss: 0.32748 focal_loss 0.23998 dice_loss 0.08750 +Epoch [1587/4000] Validation [2/4] Loss: 0.24007 focal_loss 0.12944 dice_loss 0.11064 +Epoch [1587/4000] Validation [3/4] Loss: 0.17590 focal_loss 0.11141 dice_loss 0.06449 +Epoch [1587/4000] Validation [4/4] Loss: 0.24412 focal_loss 0.14276 dice_loss 0.10136 +Epoch [1587/4000] Validation metric {'Val/mean dice_metric': 0.9714639782905579, 'Val/mean miou_metric': 0.9538288116455078, 'Val/mean f1': 0.9722879528999329, 'Val/mean precision': 0.9699273705482483, 'Val/mean recall': 0.9746602177619934, 'Val/mean hd95_metric': 5.7585039138793945} +Cheakpoint... +Epoch [1587/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714639782905579, 'Val/mean miou_metric': 0.9538288116455078, 'Val/mean f1': 0.9722879528999329, 'Val/mean precision': 0.9699273705482483, 'Val/mean recall': 0.9746602177619934, 'Val/mean hd95_metric': 5.7585039138793945} +Epoch [1588/4000] Training [1/16] Loss: 0.00894 +Epoch [1588/4000] Training [2/16] Loss: 0.00977 +Epoch [1588/4000] Training [3/16] Loss: 0.00877 +Epoch [1588/4000] Training [4/16] Loss: 0.00670 +Epoch [1588/4000] Training [5/16] Loss: 0.00637 +Epoch [1588/4000] Training [6/16] Loss: 0.00651 +Epoch [1588/4000] Training [7/16] Loss: 0.00769 +Epoch [1588/4000] Training [8/16] Loss: 0.00826 +Epoch [1588/4000] Training [9/16] Loss: 0.00810 +Epoch [1588/4000] Training [10/16] Loss: 0.00686 +Epoch [1588/4000] Training [11/16] Loss: 0.00667 +Epoch [1588/4000] Training [12/16] Loss: 0.00713 +Epoch [1588/4000] Training [13/16] Loss: 0.00822 +Epoch [1588/4000] Training [14/16] Loss: 0.00835 +Epoch [1588/4000] Training [15/16] Loss: 0.00594 +Epoch [1588/4000] Training [16/16] Loss: 0.00695 +Epoch [1588/4000] Training metric {'Train/mean dice_metric': 0.9946249723434448, 'Train/mean miou_metric': 0.9890570044517517, 'Train/mean f1': 0.990726113319397, 'Train/mean precision': 0.9863131046295166, 'Train/mean recall': 0.995178759098053, 'Train/mean hd95_metric': 1.0370502471923828} +Epoch [1588/4000] Validation [1/4] Loss: 0.27719 focal_loss 0.20699 dice_loss 0.07021 +Epoch [1588/4000] Validation [2/4] Loss: 0.40967 focal_loss 0.23993 dice_loss 0.16975 +Epoch [1588/4000] Validation [3/4] Loss: 0.18167 focal_loss 0.11418 dice_loss 0.06748 +Epoch [1588/4000] Validation [4/4] Loss: 0.22135 focal_loss 0.12367 dice_loss 0.09768 +Epoch [1588/4000] Validation metric {'Val/mean dice_metric': 0.9724262356758118, 'Val/mean miou_metric': 0.9547377824783325, 'Val/mean f1': 0.974186897277832, 'Val/mean precision': 0.9679891467094421, 'Val/mean recall': 0.9804646968841553, 'Val/mean hd95_metric': 6.0337395668029785} +Cheakpoint... +Epoch [1588/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724262356758118, 'Val/mean miou_metric': 0.9547377824783325, 'Val/mean f1': 0.974186897277832, 'Val/mean precision': 0.9679891467094421, 'Val/mean recall': 0.9804646968841553, 'Val/mean hd95_metric': 6.0337395668029785} +Epoch [1589/4000] Training [1/16] Loss: 0.00638 +Epoch [1589/4000] Training [2/16] Loss: 0.00802 +Epoch [1589/4000] Training [3/16] Loss: 0.01098 +Epoch [1589/4000] Training [4/16] Loss: 0.01050 +Epoch [1589/4000] Training [5/16] Loss: 0.00922 +Epoch [1589/4000] Training [6/16] Loss: 0.01607 +Epoch [1589/4000] Training [7/16] Loss: 0.00837 +Epoch [1589/4000] Training [8/16] Loss: 0.01232 +Epoch [1589/4000] Training [9/16] Loss: 0.00859 +Epoch [1589/4000] Training [10/16] Loss: 0.00690 +Epoch [1589/4000] Training [11/16] Loss: 0.00731 +Epoch [1589/4000] Training [12/16] Loss: 0.00593 +Epoch [1589/4000] Training [13/16] Loss: 0.00786 +Epoch [1589/4000] Training [14/16] Loss: 0.01034 +Epoch [1589/4000] Training [15/16] Loss: 0.01068 +Epoch [1589/4000] Training [16/16] Loss: 0.01034 +Epoch [1589/4000] Training metric {'Train/mean dice_metric': 0.993808388710022, 'Train/mean miou_metric': 0.9875001907348633, 'Train/mean f1': 0.9897269606590271, 'Train/mean precision': 0.9851070642471313, 'Train/mean recall': 0.9943903684616089, 'Train/mean hd95_metric': 1.6300649642944336} +Epoch [1589/4000] Validation [1/4] Loss: 0.78389 focal_loss 0.58530 dice_loss 0.19859 +Epoch [1589/4000] Validation [2/4] Loss: 0.33140 focal_loss 0.19312 dice_loss 0.13828 +Epoch [1589/4000] Validation [3/4] Loss: 0.28004 focal_loss 0.18965 dice_loss 0.09039 +Epoch [1589/4000] Validation [4/4] Loss: 0.33165 focal_loss 0.22139 dice_loss 0.11026 +Epoch [1589/4000] Validation metric {'Val/mean dice_metric': 0.9661521911621094, 'Val/mean miou_metric': 0.9472484588623047, 'Val/mean f1': 0.9680226445198059, 'Val/mean precision': 0.9712700247764587, 'Val/mean recall': 0.9647969007492065, 'Val/mean hd95_metric': 6.589535236358643} +Cheakpoint... +Epoch [1589/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661521911621094, 'Val/mean miou_metric': 0.9472484588623047, 'Val/mean f1': 0.9680226445198059, 'Val/mean precision': 0.9712700247764587, 'Val/mean recall': 0.9647969007492065, 'Val/mean hd95_metric': 6.589535236358643} +Epoch [1590/4000] Training [1/16] Loss: 0.01197 +Epoch [1590/4000] Training [2/16] Loss: 0.00843 +Epoch [1590/4000] Training [3/16] Loss: 0.00730 +Epoch [1590/4000] Training [4/16] Loss: 0.00653 +Epoch [1590/4000] Training [5/16] Loss: 0.00778 +Epoch [1590/4000] Training [6/16] Loss: 0.00646 +Epoch [1590/4000] Training [7/16] Loss: 0.00907 +Epoch [1590/4000] Training [8/16] Loss: 0.00742 +Epoch [1590/4000] Training [9/16] Loss: 0.00763 +Epoch [1590/4000] Training [10/16] Loss: 0.00860 +Epoch [1590/4000] Training [11/16] Loss: 0.00821 +Epoch [1590/4000] Training [12/16] Loss: 0.00723 +Epoch [1590/4000] Training [13/16] Loss: 0.00656 +Epoch [1590/4000] Training [14/16] Loss: 0.00748 +Epoch [1590/4000] Training [15/16] Loss: 0.00975 +Epoch [1590/4000] Training [16/16] Loss: 0.00932 +Epoch [1590/4000] Training metric {'Train/mean dice_metric': 0.9944480657577515, 'Train/mean miou_metric': 0.9887336492538452, 'Train/mean f1': 0.99037766456604, 'Train/mean precision': 0.9857460856437683, 'Train/mean recall': 0.9950529932975769, 'Train/mean hd95_metric': 1.306678295135498} +Epoch [1590/4000] Validation [1/4] Loss: 0.34105 focal_loss 0.24551 dice_loss 0.09554 +Epoch [1590/4000] Validation [2/4] Loss: 0.84709 focal_loss 0.55286 dice_loss 0.29423 +Epoch [1590/4000] Validation [3/4] Loss: 0.34230 focal_loss 0.24696 dice_loss 0.09534 +Epoch [1590/4000] Validation [4/4] Loss: 0.25708 focal_loss 0.16261 dice_loss 0.09447 +Epoch [1590/4000] Validation metric {'Val/mean dice_metric': 0.9661951065063477, 'Val/mean miou_metric': 0.9479919672012329, 'Val/mean f1': 0.9695850610733032, 'Val/mean precision': 0.9670161604881287, 'Val/mean recall': 0.9721676707267761, 'Val/mean hd95_metric': 6.758014678955078} +Cheakpoint... +Epoch [1590/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661951065063477, 'Val/mean miou_metric': 0.9479919672012329, 'Val/mean f1': 0.9695850610733032, 'Val/mean precision': 0.9670161604881287, 'Val/mean recall': 0.9721676707267761, 'Val/mean hd95_metric': 6.758014678955078} +Epoch [1591/4000] Training [1/16] Loss: 0.01040 +Epoch [1591/4000] Training [2/16] Loss: 0.00788 +Epoch [1591/4000] Training [3/16] Loss: 0.01632 +Epoch [1591/4000] Training [4/16] Loss: 0.00837 +Epoch [1591/4000] Training [5/16] Loss: 0.00643 +Epoch [1591/4000] Training [6/16] Loss: 0.00623 +Epoch [1591/4000] Training [7/16] Loss: 0.01067 +Epoch [1591/4000] Training [8/16] Loss: 0.01036 +Epoch [1591/4000] Training [9/16] Loss: 0.00902 +Epoch [1591/4000] Training [10/16] Loss: 0.00641 +Epoch [1591/4000] Training [11/16] Loss: 0.01268 +Epoch [1591/4000] Training [12/16] Loss: 0.00850 +Epoch [1591/4000] Training [13/16] Loss: 0.01592 +Epoch [1591/4000] Training [14/16] Loss: 0.00864 +Epoch [1591/4000] Training [15/16] Loss: 0.00875 +Epoch [1591/4000] Training [16/16] Loss: 0.01176 +Epoch [1591/4000] Training metric {'Train/mean dice_metric': 0.993596076965332, 'Train/mean miou_metric': 0.9870786666870117, 'Train/mean f1': 0.9898563623428345, 'Train/mean precision': 0.9856444001197815, 'Train/mean recall': 0.9941046833992004, 'Train/mean hd95_metric': 2.121786594390869} +Epoch [1591/4000] Validation [1/4] Loss: 0.20269 focal_loss 0.14420 dice_loss 0.05850 +Epoch [1591/4000] Validation [2/4] Loss: 0.57420 focal_loss 0.38250 dice_loss 0.19171 +Epoch [1591/4000] Validation [3/4] Loss: 0.26794 focal_loss 0.18851 dice_loss 0.07943 +Epoch [1591/4000] Validation [4/4] Loss: 0.57758 focal_loss 0.42562 dice_loss 0.15195 +Epoch [1591/4000] Validation metric {'Val/mean dice_metric': 0.9671250581741333, 'Val/mean miou_metric': 0.9480471611022949, 'Val/mean f1': 0.969713032245636, 'Val/mean precision': 0.967323362827301, 'Val/mean recall': 0.9721143841743469, 'Val/mean hd95_metric': 7.154564380645752} +Cheakpoint... +Epoch [1591/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9671250581741333, 'Val/mean miou_metric': 0.9480471611022949, 'Val/mean f1': 0.969713032245636, 'Val/mean precision': 0.967323362827301, 'Val/mean recall': 0.9721143841743469, 'Val/mean hd95_metric': 7.154564380645752} +Epoch [1592/4000] Training [1/16] Loss: 0.00690 +Epoch [1592/4000] Training [2/16] Loss: 0.00980 +Epoch [1592/4000] Training [3/16] Loss: 0.00656 +Epoch [1592/4000] Training [4/16] Loss: 0.00660 +Epoch [1592/4000] Training [5/16] Loss: 0.00985 +Epoch [1592/4000] Training [6/16] Loss: 0.00763 +Epoch [1592/4000] Training [7/16] Loss: 0.00969 +Epoch [1592/4000] Training [8/16] Loss: 0.00829 +Epoch [1592/4000] Training [9/16] Loss: 0.00758 +Epoch [1592/4000] Training [10/16] Loss: 0.00951 +Epoch [1592/4000] Training [11/16] Loss: 0.00870 +Epoch [1592/4000] Training [12/16] Loss: 0.01092 +Epoch [1592/4000] Training [13/16] Loss: 0.00875 +Epoch [1592/4000] Training [14/16] Loss: 0.00783 +Epoch [1592/4000] Training [15/16] Loss: 0.00791 +Epoch [1592/4000] Training [16/16] Loss: 0.00719 +Epoch [1592/4000] Training metric {'Train/mean dice_metric': 0.9943504929542542, 'Train/mean miou_metric': 0.9885157942771912, 'Train/mean f1': 0.990185022354126, 'Train/mean precision': 0.9856412410736084, 'Train/mean recall': 0.994770884513855, 'Train/mean hd95_metric': 1.104435682296753} +Epoch [1592/4000] Validation [1/4] Loss: 0.23560 focal_loss 0.16803 dice_loss 0.06757 +Epoch [1592/4000] Validation [2/4] Loss: 0.72900 focal_loss 0.42558 dice_loss 0.30342 +Epoch [1592/4000] Validation [3/4] Loss: 0.26018 focal_loss 0.18525 dice_loss 0.07492 +Epoch [1592/4000] Validation [4/4] Loss: 0.53765 focal_loss 0.39513 dice_loss 0.14253 +Epoch [1592/4000] Validation metric {'Val/mean dice_metric': 0.9697011709213257, 'Val/mean miou_metric': 0.9516140222549438, 'Val/mean f1': 0.970568060874939, 'Val/mean precision': 0.9687145948410034, 'Val/mean recall': 0.9724286794662476, 'Val/mean hd95_metric': 5.736406326293945} +Cheakpoint... +Epoch [1592/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697011709213257, 'Val/mean miou_metric': 0.9516140222549438, 'Val/mean f1': 0.970568060874939, 'Val/mean precision': 0.9687145948410034, 'Val/mean recall': 0.9724286794662476, 'Val/mean hd95_metric': 5.736406326293945} +Epoch [1593/4000] Training [1/16] Loss: 0.00638 +Epoch [1593/4000] Training [2/16] Loss: 0.00698 +Epoch [1593/4000] Training [3/16] Loss: 0.00696 +Epoch [1593/4000] Training [4/16] Loss: 0.00615 +Epoch [1593/4000] Training [5/16] Loss: 0.00985 +Epoch [1593/4000] Training [6/16] Loss: 0.00945 +Epoch [1593/4000] Training [7/16] Loss: 0.01302 +Epoch [1593/4000] Training [8/16] Loss: 0.01190 +Epoch [1593/4000] Training [9/16] Loss: 0.00610 +Epoch [1593/4000] Training [10/16] Loss: 0.00750 +Epoch [1593/4000] Training [11/16] Loss: 0.00817 +Epoch [1593/4000] Training [12/16] Loss: 0.00755 +Epoch [1593/4000] Training [13/16] Loss: 0.00643 +Epoch [1593/4000] Training [14/16] Loss: 0.00755 +Epoch [1593/4000] Training [15/16] Loss: 0.01171 +Epoch [1593/4000] Training [16/16] Loss: 0.00606 +Epoch [1593/4000] Training metric {'Train/mean dice_metric': 0.994699239730835, 'Train/mean miou_metric': 0.9891732931137085, 'Train/mean f1': 0.9900073409080505, 'Train/mean precision': 0.9848898649215698, 'Train/mean recall': 0.9951784610748291, 'Train/mean hd95_metric': 1.073844075202942} +Epoch [1593/4000] Validation [1/4] Loss: 0.18082 focal_loss 0.12266 dice_loss 0.05816 +Epoch [1593/4000] Validation [2/4] Loss: 0.41137 focal_loss 0.24429 dice_loss 0.16708 +Epoch [1593/4000] Validation [3/4] Loss: 0.16691 focal_loss 0.09903 dice_loss 0.06787 +Epoch [1593/4000] Validation [4/4] Loss: 0.23129 focal_loss 0.12570 dice_loss 0.10559 +Epoch [1593/4000] Validation metric {'Val/mean dice_metric': 0.9719563722610474, 'Val/mean miou_metric': 0.9546571969985962, 'Val/mean f1': 0.9731247425079346, 'Val/mean precision': 0.9692250490188599, 'Val/mean recall': 0.9770558476448059, 'Val/mean hd95_metric': 5.294506549835205} +Cheakpoint... +Epoch [1593/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719563722610474, 'Val/mean miou_metric': 0.9546571969985962, 'Val/mean f1': 0.9731247425079346, 'Val/mean precision': 0.9692250490188599, 'Val/mean recall': 0.9770558476448059, 'Val/mean hd95_metric': 5.294506549835205} +Epoch [1594/4000] Training [1/16] Loss: 0.00741 +Epoch [1594/4000] Training [2/16] Loss: 0.00656 +Epoch [1594/4000] Training [3/16] Loss: 0.00843 +Epoch [1594/4000] Training [4/16] Loss: 0.00900 +Epoch [1594/4000] Training [5/16] Loss: 0.00657 +Epoch [1594/4000] Training [6/16] Loss: 0.00884 +Epoch [1594/4000] Training [7/16] Loss: 0.00564 +Epoch [1594/4000] Training [8/16] Loss: 0.00890 +Epoch [1594/4000] Training [9/16] Loss: 0.00665 +Epoch [1594/4000] Training [10/16] Loss: 0.00564 +Epoch [1594/4000] Training [11/16] Loss: 0.00684 +Epoch [1594/4000] Training [12/16] Loss: 0.00669 +Epoch [1594/4000] Training [13/16] Loss: 0.00799 +Epoch [1594/4000] Training [14/16] Loss: 0.00725 +Epoch [1594/4000] Training [15/16] Loss: 0.00640 +Epoch [1594/4000] Training [16/16] Loss: 0.00696 +Epoch [1594/4000] Training metric {'Train/mean dice_metric': 0.9950734376907349, 'Train/mean miou_metric': 0.9899287223815918, 'Train/mean f1': 0.9907535910606384, 'Train/mean precision': 0.986046552658081, 'Train/mean recall': 0.9955058097839355, 'Train/mean hd95_metric': 1.0285909175872803} +Epoch [1594/4000] Validation [1/4] Loss: 0.21788 focal_loss 0.15422 dice_loss 0.06366 +Epoch [1594/4000] Validation [2/4] Loss: 0.30266 focal_loss 0.17726 dice_loss 0.12540 +Epoch [1594/4000] Validation [3/4] Loss: 0.22088 focal_loss 0.14081 dice_loss 0.08007 +Epoch [1594/4000] Validation [4/4] Loss: 0.36247 focal_loss 0.22283 dice_loss 0.13963 +Epoch [1594/4000] Validation metric {'Val/mean dice_metric': 0.9717779159545898, 'Val/mean miou_metric': 0.9541195034980774, 'Val/mean f1': 0.9732719659805298, 'Val/mean precision': 0.9684597849845886, 'Val/mean recall': 0.9781320691108704, 'Val/mean hd95_metric': 5.826815128326416} +Cheakpoint... +Epoch [1594/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717779159545898, 'Val/mean miou_metric': 0.9541195034980774, 'Val/mean f1': 0.9732719659805298, 'Val/mean precision': 0.9684597849845886, 'Val/mean recall': 0.9781320691108704, 'Val/mean hd95_metric': 5.826815128326416} +Epoch [1595/4000] Training [1/16] Loss: 0.00718 +Epoch [1595/4000] Training [2/16] Loss: 0.00635 +Epoch [1595/4000] Training [3/16] Loss: 0.00925 +Epoch [1595/4000] Training [4/16] Loss: 0.00749 +Epoch [1595/4000] Training [5/16] Loss: 0.00602 +Epoch [1595/4000] Training [6/16] Loss: 0.00936 +Epoch [1595/4000] Training [7/16] Loss: 0.00676 +Epoch [1595/4000] Training [8/16] Loss: 0.00600 +Epoch [1595/4000] Training [9/16] Loss: 0.00828 +Epoch [1595/4000] Training [10/16] Loss: 0.00569 +Epoch [1595/4000] Training [11/16] Loss: 0.01138 +Epoch [1595/4000] Training [12/16] Loss: 0.00699 +Epoch [1595/4000] Training [13/16] Loss: 0.00669 +Epoch [1595/4000] Training [14/16] Loss: 0.00613 +Epoch [1595/4000] Training [15/16] Loss: 0.00481 +Epoch [1595/4000] Training [16/16] Loss: 0.00778 +Epoch [1595/4000] Training metric {'Train/mean dice_metric': 0.9949124455451965, 'Train/mean miou_metric': 0.9895936250686646, 'Train/mean f1': 0.9898833632469177, 'Train/mean precision': 0.9844622611999512, 'Train/mean recall': 0.9953644871711731, 'Train/mean hd95_metric': 1.0539147853851318} +Epoch [1595/4000] Validation [1/4] Loss: 0.22776 focal_loss 0.15928 dice_loss 0.06847 +Epoch [1595/4000] Validation [2/4] Loss: 0.23439 focal_loss 0.13155 dice_loss 0.10283 +Epoch [1595/4000] Validation [3/4] Loss: 0.20530 focal_loss 0.11885 dice_loss 0.08645 +Epoch [1595/4000] Validation [4/4] Loss: 0.24659 focal_loss 0.14023 dice_loss 0.10636 +Epoch [1595/4000] Validation metric {'Val/mean dice_metric': 0.9736760258674622, 'Val/mean miou_metric': 0.9563512802124023, 'Val/mean f1': 0.9735987186431885, 'Val/mean precision': 0.9680168628692627, 'Val/mean recall': 0.9792452454566956, 'Val/mean hd95_metric': 5.300017356872559} +Cheakpoint... +Epoch [1595/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736760258674622, 'Val/mean miou_metric': 0.9563512802124023, 'Val/mean f1': 0.9735987186431885, 'Val/mean precision': 0.9680168628692627, 'Val/mean recall': 0.9792452454566956, 'Val/mean hd95_metric': 5.300017356872559} +Epoch [1596/4000] Training [1/16] Loss: 0.00574 +Epoch [1596/4000] Training [2/16] Loss: 0.01055 +Epoch [1596/4000] Training [3/16] Loss: 0.00621 +Epoch [1596/4000] Training [4/16] Loss: 0.00764 +Epoch [1596/4000] Training [5/16] Loss: 0.01564 +Epoch [1596/4000] Training [6/16] Loss: 0.00827 +Epoch [1596/4000] Training [7/16] Loss: 0.00793 +Epoch [1596/4000] Training [8/16] Loss: 0.00732 +Epoch [1596/4000] Training [9/16] Loss: 0.00581 +Epoch [1596/4000] Training [10/16] Loss: 0.00653 +Epoch [1596/4000] Training [11/16] Loss: 0.00633 +Epoch [1596/4000] Training [12/16] Loss: 0.00788 +Epoch [1596/4000] Training [13/16] Loss: 0.00592 +Epoch [1596/4000] Training [14/16] Loss: 0.00666 +Epoch [1596/4000] Training [15/16] Loss: 0.00670 +Epoch [1596/4000] Training [16/16] Loss: 0.00864 +Epoch [1596/4000] Training metric {'Train/mean dice_metric': 0.9949660897254944, 'Train/mean miou_metric': 0.9897137880325317, 'Train/mean f1': 0.9903546571731567, 'Train/mean precision': 0.9854401350021362, 'Train/mean recall': 0.9953184723854065, 'Train/mean hd95_metric': 1.0508116483688354} +Epoch [1596/4000] Validation [1/4] Loss: 0.23187 focal_loss 0.16904 dice_loss 0.06283 +Epoch [1596/4000] Validation [2/4] Loss: 0.24241 focal_loss 0.13835 dice_loss 0.10406 +Epoch [1596/4000] Validation [3/4] Loss: 0.22324 focal_loss 0.13296 dice_loss 0.09028 +Epoch [1596/4000] Validation [4/4] Loss: 0.28936 focal_loss 0.15657 dice_loss 0.13280 +Epoch [1596/4000] Validation metric {'Val/mean dice_metric': 0.9712980389595032, 'Val/mean miou_metric': 0.9540053606033325, 'Val/mean f1': 0.9740020632743835, 'Val/mean precision': 0.9687390327453613, 'Val/mean recall': 0.9793226718902588, 'Val/mean hd95_metric': 6.159176826477051} +Cheakpoint... +Epoch [1596/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712980389595032, 'Val/mean miou_metric': 0.9540053606033325, 'Val/mean f1': 0.9740020632743835, 'Val/mean precision': 0.9687390327453613, 'Val/mean recall': 0.9793226718902588, 'Val/mean hd95_metric': 6.159176826477051} +Epoch [1597/4000] Training [1/16] Loss: 0.00585 +Epoch [1597/4000] Training [2/16] Loss: 0.00528 +Epoch [1597/4000] Training [3/16] Loss: 0.00669 +Epoch [1597/4000] Training [4/16] Loss: 0.00747 +Epoch [1597/4000] Training [5/16] Loss: 0.00865 +Epoch [1597/4000] Training [6/16] Loss: 0.00788 +Epoch [1597/4000] Training [7/16] Loss: 0.00776 +Epoch [1597/4000] Training [8/16] Loss: 0.00719 +Epoch [1597/4000] Training [9/16] Loss: 0.00627 +Epoch [1597/4000] Training [10/16] Loss: 0.00740 +Epoch [1597/4000] Training [11/16] Loss: 0.00753 +Epoch [1597/4000] Training [12/16] Loss: 0.00687 +Epoch [1597/4000] Training [13/16] Loss: 0.01023 +Epoch [1597/4000] Training [14/16] Loss: 0.00616 +Epoch [1597/4000] Training [15/16] Loss: 0.00634 +Epoch [1597/4000] Training [16/16] Loss: 0.00587 +Epoch [1597/4000] Training metric {'Train/mean dice_metric': 0.9952903985977173, 'Train/mean miou_metric': 0.9903779625892639, 'Train/mean f1': 0.9912437796592712, 'Train/mean precision': 0.9867285490036011, 'Train/mean recall': 0.9958006143569946, 'Train/mean hd95_metric': 1.0285313129425049} +Epoch [1597/4000] Validation [1/4] Loss: 0.31194 focal_loss 0.23272 dice_loss 0.07922 +Epoch [1597/4000] Validation [2/4] Loss: 0.24198 focal_loss 0.13735 dice_loss 0.10463 +Epoch [1597/4000] Validation [3/4] Loss: 0.26418 focal_loss 0.17321 dice_loss 0.09097 +Epoch [1597/4000] Validation [4/4] Loss: 0.29836 focal_loss 0.19049 dice_loss 0.10787 +Epoch [1597/4000] Validation metric {'Val/mean dice_metric': 0.9721072912216187, 'Val/mean miou_metric': 0.9549201726913452, 'Val/mean f1': 0.9743918180465698, 'Val/mean precision': 0.9697572588920593, 'Val/mean recall': 0.9790709614753723, 'Val/mean hd95_metric': 5.5999884605407715} +Cheakpoint... +Epoch [1597/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721072912216187, 'Val/mean miou_metric': 0.9549201726913452, 'Val/mean f1': 0.9743918180465698, 'Val/mean precision': 0.9697572588920593, 'Val/mean recall': 0.9790709614753723, 'Val/mean hd95_metric': 5.5999884605407715} +Epoch [1598/4000] Training [1/16] Loss: 0.00720 +Epoch [1598/4000] Training [2/16] Loss: 0.00797 +Epoch [1598/4000] Training [3/16] Loss: 0.00936 +Epoch [1598/4000] Training [4/16] Loss: 0.00616 +Epoch [1598/4000] Training [5/16] Loss: 0.00509 +Epoch [1598/4000] Training [6/16] Loss: 0.01050 +Epoch [1598/4000] Training [7/16] Loss: 0.00700 +Epoch [1598/4000] Training [8/16] Loss: 0.00728 +Epoch [1598/4000] Training [9/16] Loss: 0.00651 +Epoch [1598/4000] Training [10/16] Loss: 0.00558 +Epoch [1598/4000] Training [11/16] Loss: 0.00845 +Epoch [1598/4000] Training [12/16] Loss: 0.00829 +Epoch [1598/4000] Training [13/16] Loss: 0.00911 +Epoch [1598/4000] Training [14/16] Loss: 0.00542 +Epoch [1598/4000] Training [15/16] Loss: 0.00891 +Epoch [1598/4000] Training [16/16] Loss: 0.00575 +Epoch [1598/4000] Training metric {'Train/mean dice_metric': 0.9950562715530396, 'Train/mean miou_metric': 0.9899019002914429, 'Train/mean f1': 0.9909055829048157, 'Train/mean precision': 0.9863376021385193, 'Train/mean recall': 0.9955160021781921, 'Train/mean hd95_metric': 1.0405123233795166} +Epoch [1598/4000] Validation [1/4] Loss: 0.27615 focal_loss 0.20301 dice_loss 0.07313 +Epoch [1598/4000] Validation [2/4] Loss: 0.41393 focal_loss 0.26077 dice_loss 0.15317 +Epoch [1598/4000] Validation [3/4] Loss: 0.18225 focal_loss 0.12032 dice_loss 0.06193 +Epoch [1598/4000] Validation [4/4] Loss: 0.24700 focal_loss 0.15285 dice_loss 0.09415 +Epoch [1598/4000] Validation metric {'Val/mean dice_metric': 0.9729152917861938, 'Val/mean miou_metric': 0.9562761187553406, 'Val/mean f1': 0.9732930064201355, 'Val/mean precision': 0.9666699767112732, 'Val/mean recall': 0.9800074696540833, 'Val/mean hd95_metric': 5.970056056976318} +Cheakpoint... +Epoch [1598/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729152917861938, 'Val/mean miou_metric': 0.9562761187553406, 'Val/mean f1': 0.9732930064201355, 'Val/mean precision': 0.9666699767112732, 'Val/mean recall': 0.9800074696540833, 'Val/mean hd95_metric': 5.970056056976318} +Epoch [1599/4000] Training [1/16] Loss: 0.00758 +Epoch [1599/4000] Training [2/16] Loss: 0.00688 +Epoch [1599/4000] Training [3/16] Loss: 0.00725 +Epoch [1599/4000] Training [4/16] Loss: 0.00844 +Epoch [1599/4000] Training [5/16] Loss: 0.00645 +Epoch [1599/4000] Training [6/16] Loss: 0.00778 +Epoch [1599/4000] Training [7/16] Loss: 0.02780 +Epoch [1599/4000] Training [8/16] Loss: 0.00849 +Epoch [1599/4000] Training [9/16] Loss: 0.00739 +Epoch [1599/4000] Training [10/16] Loss: 0.00825 +Epoch [1599/4000] Training [11/16] Loss: 0.00767 +Epoch [1599/4000] Training [12/16] Loss: 0.00748 +Epoch [1599/4000] Training [13/16] Loss: 0.00626 +Epoch [1599/4000] Training [14/16] Loss: 0.00868 +Epoch [1599/4000] Training [15/16] Loss: 0.00622 +Epoch [1599/4000] Training [16/16] Loss: 0.00673 +Epoch [1599/4000] Training metric {'Train/mean dice_metric': 0.9946056008338928, 'Train/mean miou_metric': 0.9890303611755371, 'Train/mean f1': 0.9901346564292908, 'Train/mean precision': 0.9848160147666931, 'Train/mean recall': 0.995510995388031, 'Train/mean hd95_metric': 1.0430583953857422} +Epoch [1599/4000] Validation [1/4] Loss: 0.31001 focal_loss 0.22863 dice_loss 0.08138 +Epoch [1599/4000] Validation [2/4] Loss: 0.20993 focal_loss 0.10883 dice_loss 0.10110 +Epoch [1599/4000] Validation [3/4] Loss: 0.21069 focal_loss 0.12781 dice_loss 0.08288 +Epoch [1599/4000] Validation [4/4] Loss: 0.36873 focal_loss 0.22117 dice_loss 0.14757 +Epoch [1599/4000] Validation metric {'Val/mean dice_metric': 0.9707885980606079, 'Val/mean miou_metric': 0.9525409936904907, 'Val/mean f1': 0.972389280796051, 'Val/mean precision': 0.9679251909255981, 'Val/mean recall': 0.9768948554992676, 'Val/mean hd95_metric': 6.206099510192871} +Cheakpoint... +Epoch [1599/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707885980606079, 'Val/mean miou_metric': 0.9525409936904907, 'Val/mean f1': 0.972389280796051, 'Val/mean precision': 0.9679251909255981, 'Val/mean recall': 0.9768948554992676, 'Val/mean hd95_metric': 6.206099510192871} +Epoch [1600/4000] Training [1/16] Loss: 0.00723 +Epoch [1600/4000] Training [2/16] Loss: 0.01156 +Epoch [1600/4000] Training [3/16] Loss: 0.00646 +Epoch [1600/4000] Training [4/16] Loss: 0.00700 +Epoch [1600/4000] Training [5/16] Loss: 0.00728 +Epoch [1600/4000] Training [6/16] Loss: 0.00976 +Epoch [1600/4000] Training [7/16] Loss: 0.01035 +Epoch [1600/4000] Training [8/16] Loss: 0.00566 +Epoch [1600/4000] Training [9/16] Loss: 0.00837 +Epoch [1600/4000] Training [10/16] Loss: 0.00801 +Epoch [1600/4000] Training [11/16] Loss: 0.00643 +Epoch [1600/4000] Training [12/16] Loss: 0.00927 +Epoch [1600/4000] Training [13/16] Loss: 0.00854 +Epoch [1600/4000] Training [14/16] Loss: 0.00815 +Epoch [1600/4000] Training [15/16] Loss: 0.00674 +Epoch [1600/4000] Training [16/16] Loss: 0.00652 +Epoch [1600/4000] Training metric {'Train/mean dice_metric': 0.9946796894073486, 'Train/mean miou_metric': 0.9891711473464966, 'Train/mean f1': 0.9907100200653076, 'Train/mean precision': 0.9861506223678589, 'Train/mean recall': 0.9953116774559021, 'Train/mean hd95_metric': 1.0459494590759277} +Epoch [1600/4000] Validation [1/4] Loss: 0.35963 focal_loss 0.27305 dice_loss 0.08657 +Epoch [1600/4000] Validation [2/4] Loss: 0.51422 focal_loss 0.33785 dice_loss 0.17637 +Epoch [1600/4000] Validation [3/4] Loss: 0.18233 focal_loss 0.11066 dice_loss 0.07167 +Epoch [1600/4000] Validation [4/4] Loss: 0.33430 focal_loss 0.19991 dice_loss 0.13439 +Epoch [1600/4000] Validation metric {'Val/mean dice_metric': 0.9707010984420776, 'Val/mean miou_metric': 0.9533994793891907, 'Val/mean f1': 0.9734563827514648, 'Val/mean precision': 0.9718730449676514, 'Val/mean recall': 0.9750450253486633, 'Val/mean hd95_metric': 6.022995471954346} +Cheakpoint... +Epoch [1600/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707010984420776, 'Val/mean miou_metric': 0.9533994793891907, 'Val/mean f1': 0.9734563827514648, 'Val/mean precision': 0.9718730449676514, 'Val/mean recall': 0.9750450253486633, 'Val/mean hd95_metric': 6.022995471954346} +Epoch [1601/4000] Training [1/16] Loss: 0.00564 +Epoch [1601/4000] Training [2/16] Loss: 0.00668 +Epoch [1601/4000] Training [3/16] Loss: 0.00626 +Epoch [1601/4000] Training [4/16] Loss: 0.01246 +Epoch [1601/4000] Training [5/16] Loss: 0.00742 +Epoch [1601/4000] Training [6/16] Loss: 0.00824 +Epoch [1601/4000] Training [7/16] Loss: 0.00853 +Epoch [1601/4000] Training [8/16] Loss: 0.00853 +Epoch [1601/4000] Training [9/16] Loss: 0.00654 +Epoch [1601/4000] Training [10/16] Loss: 0.00662 +Epoch [1601/4000] Training [11/16] Loss: 0.00700 +Epoch [1601/4000] Training [12/16] Loss: 0.00612 +Epoch [1601/4000] Training [13/16] Loss: 0.00603 +Epoch [1601/4000] Training [14/16] Loss: 0.00651 +Epoch [1601/4000] Training [15/16] Loss: 0.00770 +Epoch [1601/4000] Training [16/16] Loss: 0.00624 +Epoch [1601/4000] Training metric {'Train/mean dice_metric': 0.9948399662971497, 'Train/mean miou_metric': 0.9894769787788391, 'Train/mean f1': 0.9907130599021912, 'Train/mean precision': 0.986110508441925, 'Train/mean recall': 0.9953587651252747, 'Train/mean hd95_metric': 1.0438663959503174} +Epoch [1601/4000] Validation [1/4] Loss: 0.25353 focal_loss 0.18674 dice_loss 0.06679 +Epoch [1601/4000] Validation [2/4] Loss: 0.32319 focal_loss 0.19559 dice_loss 0.12760 +Epoch [1601/4000] Validation [3/4] Loss: 0.33559 focal_loss 0.23104 dice_loss 0.10455 +Epoch [1601/4000] Validation [4/4] Loss: 0.28962 focal_loss 0.17729 dice_loss 0.11233 +Epoch [1601/4000] Validation metric {'Val/mean dice_metric': 0.9703129529953003, 'Val/mean miou_metric': 0.9526877403259277, 'Val/mean f1': 0.9729599952697754, 'Val/mean precision': 0.9694226980209351, 'Val/mean recall': 0.9765232801437378, 'Val/mean hd95_metric': 5.99785041809082} +Cheakpoint... +Epoch [1601/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703129529953003, 'Val/mean miou_metric': 0.9526877403259277, 'Val/mean f1': 0.9729599952697754, 'Val/mean precision': 0.9694226980209351, 'Val/mean recall': 0.9765232801437378, 'Val/mean hd95_metric': 5.99785041809082} +Epoch [1602/4000] Training [1/16] Loss: 0.00629 +Epoch [1602/4000] Training [2/16] Loss: 0.00855 +Epoch [1602/4000] Training [3/16] Loss: 0.00829 +Epoch [1602/4000] Training [4/16] Loss: 0.00550 +Epoch [1602/4000] Training [5/16] Loss: 0.00613 +Epoch [1602/4000] Training [6/16] Loss: 0.00629 +Epoch [1602/4000] Training [7/16] Loss: 0.00701 +Epoch [1602/4000] Training [8/16] Loss: 0.00745 +Epoch [1602/4000] Training [9/16] Loss: 0.00757 +Epoch [1602/4000] Training [10/16] Loss: 0.00988 +Epoch [1602/4000] Training [11/16] Loss: 0.00866 +Epoch [1602/4000] Training [12/16] Loss: 0.00927 +Epoch [1602/4000] Training [13/16] Loss: 0.01018 +Epoch [1602/4000] Training [14/16] Loss: 0.00841 +Epoch [1602/4000] Training [15/16] Loss: 0.00662 +Epoch [1602/4000] Training [16/16] Loss: 0.00580 +Epoch [1602/4000] Training metric {'Train/mean dice_metric': 0.9949096441268921, 'Train/mean miou_metric': 0.9896210432052612, 'Train/mean f1': 0.9909639358520508, 'Train/mean precision': 0.9865117073059082, 'Train/mean recall': 0.9954565167427063, 'Train/mean hd95_metric': 1.0277341604232788} +Epoch [1602/4000] Validation [1/4] Loss: 0.23171 focal_loss 0.16736 dice_loss 0.06435 +Epoch [1602/4000] Validation [2/4] Loss: 0.66845 focal_loss 0.38711 dice_loss 0.28135 +Epoch [1602/4000] Validation [3/4] Loss: 0.27952 focal_loss 0.18792 dice_loss 0.09160 +Epoch [1602/4000] Validation [4/4] Loss: 0.30820 focal_loss 0.19503 dice_loss 0.11317 +Epoch [1602/4000] Validation metric {'Val/mean dice_metric': 0.9673764109611511, 'Val/mean miou_metric': 0.9510718584060669, 'Val/mean f1': 0.9726898074150085, 'Val/mean precision': 0.9720689058303833, 'Val/mean recall': 0.9733113050460815, 'Val/mean hd95_metric': 5.386206150054932} +Cheakpoint... +Epoch [1602/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673764109611511, 'Val/mean miou_metric': 0.9510718584060669, 'Val/mean f1': 0.9726898074150085, 'Val/mean precision': 0.9720689058303833, 'Val/mean recall': 0.9733113050460815, 'Val/mean hd95_metric': 5.386206150054932} +Epoch [1603/4000] Training [1/16] Loss: 0.00776 +Epoch [1603/4000] Training [2/16] Loss: 0.00630 +Epoch [1603/4000] Training [3/16] Loss: 0.00958 +Epoch [1603/4000] Training [4/16] Loss: 0.00859 +Epoch [1603/4000] Training [5/16] Loss: 0.00665 +Epoch [1603/4000] Training [6/16] Loss: 0.00979 +Epoch [1603/4000] Training [7/16] Loss: 0.00694 +Epoch [1603/4000] Training [8/16] Loss: 0.00587 +Epoch [1603/4000] Training [9/16] Loss: 0.00692 +Epoch [1603/4000] Training [10/16] Loss: 0.00944 +Epoch [1603/4000] Training [11/16] Loss: 0.00931 +Epoch [1603/4000] Training [12/16] Loss: 0.00726 +Epoch [1603/4000] Training [13/16] Loss: 0.00979 +Epoch [1603/4000] Training [14/16] Loss: 0.00705 +Epoch [1603/4000] Training [15/16] Loss: 0.00661 +Epoch [1603/4000] Training [16/16] Loss: 0.00498 +Epoch [1603/4000] Training metric {'Train/mean dice_metric': 0.994940459728241, 'Train/mean miou_metric': 0.9896721839904785, 'Train/mean f1': 0.9909462928771973, 'Train/mean precision': 0.9863121509552002, 'Train/mean recall': 0.9956241846084595, 'Train/mean hd95_metric': 1.02388334274292} +Epoch [1603/4000] Validation [1/4] Loss: 0.35498 focal_loss 0.26502 dice_loss 0.08996 +Epoch [1603/4000] Validation [2/4] Loss: 0.49740 focal_loss 0.29264 dice_loss 0.20476 +Epoch [1603/4000] Validation [3/4] Loss: 0.27091 focal_loss 0.17794 dice_loss 0.09297 +Epoch [1603/4000] Validation [4/4] Loss: 0.24913 focal_loss 0.14523 dice_loss 0.10390 +Epoch [1603/4000] Validation metric {'Val/mean dice_metric': 0.9676688313484192, 'Val/mean miou_metric': 0.9502660632133484, 'Val/mean f1': 0.9720802307128906, 'Val/mean precision': 0.9718021154403687, 'Val/mean recall': 0.9723585247993469, 'Val/mean hd95_metric': 6.2108540534973145} +Cheakpoint... +Epoch [1603/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676688313484192, 'Val/mean miou_metric': 0.9502660632133484, 'Val/mean f1': 0.9720802307128906, 'Val/mean precision': 0.9718021154403687, 'Val/mean recall': 0.9723585247993469, 'Val/mean hd95_metric': 6.2108540534973145} +Epoch [1604/4000] Training [1/16] Loss: 0.00570 +Epoch [1604/4000] Training [2/16] Loss: 0.00646 +Epoch [1604/4000] Training [3/16] Loss: 0.00638 +Epoch [1604/4000] Training [4/16] Loss: 0.00825 +Epoch [1604/4000] Training [5/16] Loss: 0.00794 +Epoch [1604/4000] Training [6/16] Loss: 0.01052 +Epoch [1604/4000] Training [7/16] Loss: 0.00811 +Epoch [1604/4000] Training [8/16] Loss: 0.00676 +Epoch [1604/4000] Training [9/16] Loss: 0.00962 +Epoch [1604/4000] Training [10/16] Loss: 0.00672 +Epoch [1604/4000] Training [11/16] Loss: 0.00767 +Epoch [1604/4000] Training [12/16] Loss: 0.00619 +Epoch [1604/4000] Training [13/16] Loss: 0.00796 +Epoch [1604/4000] Training [14/16] Loss: 0.00728 +Epoch [1604/4000] Training [15/16] Loss: 0.01013 +Epoch [1604/4000] Training [16/16] Loss: 0.00759 +Epoch [1604/4000] Training metric {'Train/mean dice_metric': 0.9946192502975464, 'Train/mean miou_metric': 0.9890323877334595, 'Train/mean f1': 0.9906342029571533, 'Train/mean precision': 0.9859791994094849, 'Train/mean recall': 0.9953333139419556, 'Train/mean hd95_metric': 1.0395817756652832} +Epoch [1604/4000] Validation [1/4] Loss: 0.39308 focal_loss 0.28825 dice_loss 0.10482 +Epoch [1604/4000] Validation [2/4] Loss: 0.34589 focal_loss 0.20054 dice_loss 0.14535 +Epoch [1604/4000] Validation [3/4] Loss: 0.24446 focal_loss 0.15551 dice_loss 0.08895 +Epoch [1604/4000] Validation [4/4] Loss: 0.24802 focal_loss 0.14139 dice_loss 0.10663 +Epoch [1604/4000] Validation metric {'Val/mean dice_metric': 0.97113037109375, 'Val/mean miou_metric': 0.9529994130134583, 'Val/mean f1': 0.9723049402236938, 'Val/mean precision': 0.9705987572669983, 'Val/mean recall': 0.9740170240402222, 'Val/mean hd95_metric': 5.213610649108887} +Cheakpoint... +Epoch [1604/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97113037109375, 'Val/mean miou_metric': 0.9529994130134583, 'Val/mean f1': 0.9723049402236938, 'Val/mean precision': 0.9705987572669983, 'Val/mean recall': 0.9740170240402222, 'Val/mean hd95_metric': 5.213610649108887} +Epoch [1605/4000] Training [1/16] Loss: 0.00817 +Epoch [1605/4000] Training [2/16] Loss: 0.00943 +Epoch [1605/4000] Training [3/16] Loss: 0.00813 +Epoch [1605/4000] Training [4/16] Loss: 0.00846 +Epoch [1605/4000] Training [5/16] Loss: 0.00682 +Epoch [1605/4000] Training [6/16] Loss: 0.00716 +Epoch [1605/4000] Training [7/16] Loss: 0.00790 +Epoch [1605/4000] Training [8/16] Loss: 0.00607 +Epoch [1605/4000] Training [9/16] Loss: 0.00719 +Epoch [1605/4000] Training [10/16] Loss: 0.00817 +Epoch [1605/4000] Training [11/16] Loss: 0.00758 +Epoch [1605/4000] Training [12/16] Loss: 0.01038 +Epoch [1605/4000] Training [13/16] Loss: 0.00894 +Epoch [1605/4000] Training [14/16] Loss: 0.00799 +Epoch [1605/4000] Training [15/16] Loss: 0.00794 +Epoch [1605/4000] Training [16/16] Loss: 0.00679 +Epoch [1605/4000] Training metric {'Train/mean dice_metric': 0.9946070909500122, 'Train/mean miou_metric': 0.9890222549438477, 'Train/mean f1': 0.9907602667808533, 'Train/mean precision': 0.9862604737281799, 'Train/mean recall': 0.9953013062477112, 'Train/mean hd95_metric': 1.024436593055725} +Epoch [1605/4000] Validation [1/4] Loss: 0.39700 focal_loss 0.30413 dice_loss 0.09287 +Epoch [1605/4000] Validation [2/4] Loss: 0.57355 focal_loss 0.33200 dice_loss 0.24155 +Epoch [1605/4000] Validation [3/4] Loss: 0.30135 focal_loss 0.20431 dice_loss 0.09704 +Epoch [1605/4000] Validation [4/4] Loss: 0.36448 focal_loss 0.23208 dice_loss 0.13241 +Epoch [1605/4000] Validation metric {'Val/mean dice_metric': 0.9683040380477905, 'Val/mean miou_metric': 0.9504350423812866, 'Val/mean f1': 0.971546471118927, 'Val/mean precision': 0.9685290455818176, 'Val/mean recall': 0.9745826721191406, 'Val/mean hd95_metric': 6.38845682144165} +Cheakpoint... +Epoch [1605/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9683040380477905, 'Val/mean miou_metric': 0.9504350423812866, 'Val/mean f1': 0.971546471118927, 'Val/mean precision': 0.9685290455818176, 'Val/mean recall': 0.9745826721191406, 'Val/mean hd95_metric': 6.38845682144165} +Epoch [1606/4000] Training [1/16] Loss: 0.00805 +Epoch [1606/4000] Training [2/16] Loss: 0.00677 +Epoch [1606/4000] Training [3/16] Loss: 0.00724 +Epoch [1606/4000] Training [4/16] Loss: 0.00769 +Epoch [1606/4000] Training [5/16] Loss: 0.00854 +Epoch [1606/4000] Training [6/16] Loss: 0.00953 +Epoch [1606/4000] Training [7/16] Loss: 0.00737 +Epoch [1606/4000] Training [8/16] Loss: 0.00913 +Epoch [1606/4000] Training [9/16] Loss: 0.00886 +Epoch [1606/4000] Training [10/16] Loss: 0.00889 +Epoch [1606/4000] Training [11/16] Loss: 0.00799 +Epoch [1606/4000] Training [12/16] Loss: 0.00782 +Epoch [1606/4000] Training [13/16] Loss: 0.00782 +Epoch [1606/4000] Training [14/16] Loss: 0.00849 +Epoch [1606/4000] Training [15/16] Loss: 0.01222 +Epoch [1606/4000] Training [16/16] Loss: 0.00799 +Epoch [1606/4000] Training metric {'Train/mean dice_metric': 0.9942057132720947, 'Train/mean miou_metric': 0.9882391691207886, 'Train/mean f1': 0.9905490875244141, 'Train/mean precision': 0.986011266708374, 'Train/mean recall': 0.995128870010376, 'Train/mean hd95_metric': 1.0582737922668457} +Epoch [1606/4000] Validation [1/4] Loss: 0.29447 focal_loss 0.21723 dice_loss 0.07724 +Epoch [1606/4000] Validation [2/4] Loss: 0.28307 focal_loss 0.16367 dice_loss 0.11940 +Epoch [1606/4000] Validation [3/4] Loss: 0.28157 focal_loss 0.18810 dice_loss 0.09347 +Epoch [1606/4000] Validation [4/4] Loss: 0.23510 focal_loss 0.12978 dice_loss 0.10532 +Epoch [1606/4000] Validation metric {'Val/mean dice_metric': 0.9709224700927734, 'Val/mean miou_metric': 0.9527961015701294, 'Val/mean f1': 0.9732292294502258, 'Val/mean precision': 0.9696966409683228, 'Val/mean recall': 0.9767876267433167, 'Val/mean hd95_metric': 5.900468349456787} +Cheakpoint... +Epoch [1606/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709224700927734, 'Val/mean miou_metric': 0.9527961015701294, 'Val/mean f1': 0.9732292294502258, 'Val/mean precision': 0.9696966409683228, 'Val/mean recall': 0.9767876267433167, 'Val/mean hd95_metric': 5.900468349456787} +Epoch [1607/4000] Training [1/16] Loss: 0.00694 +Epoch [1607/4000] Training [2/16] Loss: 0.00669 +Epoch [1607/4000] Training [3/16] Loss: 0.00654 +Epoch [1607/4000] Training [4/16] Loss: 0.00774 +Epoch [1607/4000] Training [5/16] Loss: 0.00690 +Epoch [1607/4000] Training [6/16] Loss: 0.00755 +Epoch [1607/4000] Training [7/16] Loss: 0.00691 +Epoch [1607/4000] Training [8/16] Loss: 0.00974 +Epoch [1607/4000] Training [9/16] Loss: 0.00541 +Epoch [1607/4000] Training [10/16] Loss: 0.00773 +Epoch [1607/4000] Training [11/16] Loss: 0.00935 +Epoch [1607/4000] Training [12/16] Loss: 0.00824 +Epoch [1607/4000] Training [13/16] Loss: 0.00716 +Epoch [1607/4000] Training [14/16] Loss: 0.00874 +Epoch [1607/4000] Training [15/16] Loss: 0.01045 +Epoch [1607/4000] Training [16/16] Loss: 0.00619 +Epoch [1607/4000] Training metric {'Train/mean dice_metric': 0.9949119687080383, 'Train/mean miou_metric': 0.9895766973495483, 'Train/mean f1': 0.9899243116378784, 'Train/mean precision': 0.9844954013824463, 'Train/mean recall': 0.9954134821891785, 'Train/mean hd95_metric': 1.0288045406341553} +Epoch [1607/4000] Validation [1/4] Loss: 0.34277 focal_loss 0.25727 dice_loss 0.08550 +Epoch [1607/4000] Validation [2/4] Loss: 0.39442 focal_loss 0.24192 dice_loss 0.15249 +Epoch [1607/4000] Validation [3/4] Loss: 0.15651 focal_loss 0.09720 dice_loss 0.05931 +Epoch [1607/4000] Validation [4/4] Loss: 0.19852 focal_loss 0.10703 dice_loss 0.09149 +Epoch [1607/4000] Validation metric {'Val/mean dice_metric': 0.9719430804252625, 'Val/mean miou_metric': 0.954455554485321, 'Val/mean f1': 0.9720355272293091, 'Val/mean precision': 0.9703690409660339, 'Val/mean recall': 0.9737077355384827, 'Val/mean hd95_metric': 5.221758842468262} +Cheakpoint... +Epoch [1607/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719430804252625, 'Val/mean miou_metric': 0.954455554485321, 'Val/mean f1': 0.9720355272293091, 'Val/mean precision': 0.9703690409660339, 'Val/mean recall': 0.9737077355384827, 'Val/mean hd95_metric': 5.221758842468262} +Epoch [1608/4000] Training [1/16] Loss: 0.00885 +Epoch [1608/4000] Training [2/16] Loss: 0.01099 +Epoch [1608/4000] Training [3/16] Loss: 0.00656 +Epoch [1608/4000] Training [4/16] Loss: 0.00624 +Epoch [1608/4000] Training [5/16] Loss: 0.00551 +Epoch [1608/4000] Training [6/16] Loss: 0.00841 +Epoch [1608/4000] Training [7/16] Loss: 0.00601 +Epoch [1608/4000] Training [8/16] Loss: 0.00859 +Epoch [1608/4000] Training [9/16] Loss: 0.00735 +Epoch [1608/4000] Training [10/16] Loss: 0.00756 +Epoch [1608/4000] Training [11/16] Loss: 0.00741 +Epoch [1608/4000] Training [12/16] Loss: 0.00533 +Epoch [1608/4000] Training [13/16] Loss: 0.00720 +Epoch [1608/4000] Training [14/16] Loss: 0.00669 +Epoch [1608/4000] Training [15/16] Loss: 0.00750 +Epoch [1608/4000] Training [16/16] Loss: 0.00931 +Epoch [1608/4000] Training metric {'Train/mean dice_metric': 0.9947164058685303, 'Train/mean miou_metric': 0.9892420768737793, 'Train/mean f1': 0.9906873106956482, 'Train/mean precision': 0.9862527847290039, 'Train/mean recall': 0.9951618313789368, 'Train/mean hd95_metric': 1.0526936054229736} +Epoch [1608/4000] Validation [1/4] Loss: 0.28657 focal_loss 0.21132 dice_loss 0.07525 +Epoch [1608/4000] Validation [2/4] Loss: 0.42106 focal_loss 0.24726 dice_loss 0.17380 +Epoch [1608/4000] Validation [3/4] Loss: 0.23639 focal_loss 0.14223 dice_loss 0.09416 +Epoch [1608/4000] Validation [4/4] Loss: 0.25197 focal_loss 0.14978 dice_loss 0.10218 +Epoch [1608/4000] Validation metric {'Val/mean dice_metric': 0.9722537994384766, 'Val/mean miou_metric': 0.95464688539505, 'Val/mean f1': 0.9724788665771484, 'Val/mean precision': 0.9690777659416199, 'Val/mean recall': 0.9759038686752319, 'Val/mean hd95_metric': 5.818971633911133} +Cheakpoint... +Epoch [1608/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722537994384766, 'Val/mean miou_metric': 0.95464688539505, 'Val/mean f1': 0.9724788665771484, 'Val/mean precision': 0.9690777659416199, 'Val/mean recall': 0.9759038686752319, 'Val/mean hd95_metric': 5.818971633911133} +Epoch [1609/4000] Training [1/16] Loss: 0.00864 +Epoch [1609/4000] Training [2/16] Loss: 0.00660 +Epoch [1609/4000] Training [3/16] Loss: 0.01597 +Epoch [1609/4000] Training [4/16] Loss: 0.00602 +Epoch [1609/4000] Training [5/16] Loss: 0.00838 +Epoch [1609/4000] Training [6/16] Loss: 0.00725 +Epoch [1609/4000] Training [7/16] Loss: 0.00706 +Epoch [1609/4000] Training [8/16] Loss: 0.00764 +Epoch [1609/4000] Training [9/16] Loss: 0.00542 +Epoch [1609/4000] Training [10/16] Loss: 0.00909 +Epoch [1609/4000] Training [11/16] Loss: 0.00674 +Epoch [1609/4000] Training [12/16] Loss: 0.01177 +Epoch [1609/4000] Training [13/16] Loss: 0.00698 +Epoch [1609/4000] Training [14/16] Loss: 0.00718 +Epoch [1609/4000] Training [15/16] Loss: 0.00831 +Epoch [1609/4000] Training [16/16] Loss: 0.01050 +Epoch [1609/4000] Training metric {'Train/mean dice_metric': 0.9944582581520081, 'Train/mean miou_metric': 0.9887377023696899, 'Train/mean f1': 0.9907581210136414, 'Train/mean precision': 0.9862986207008362, 'Train/mean recall': 0.9952583312988281, 'Train/mean hd95_metric': 1.0629172325134277} +Epoch [1609/4000] Validation [1/4] Loss: 0.27878 focal_loss 0.20715 dice_loss 0.07163 +Epoch [1609/4000] Validation [2/4] Loss: 0.62021 focal_loss 0.37013 dice_loss 0.25008 +Epoch [1609/4000] Validation [3/4] Loss: 0.30083 focal_loss 0.20678 dice_loss 0.09405 +Epoch [1609/4000] Validation [4/4] Loss: 0.25746 focal_loss 0.14712 dice_loss 0.11034 +Epoch [1609/4000] Validation metric {'Val/mean dice_metric': 0.9693611264228821, 'Val/mean miou_metric': 0.9517005681991577, 'Val/mean f1': 0.9725664854049683, 'Val/mean precision': 0.9683740139007568, 'Val/mean recall': 0.9767953157424927, 'Val/mean hd95_metric': 6.195637226104736} +Cheakpoint... +Epoch [1609/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693611264228821, 'Val/mean miou_metric': 0.9517005681991577, 'Val/mean f1': 0.9725664854049683, 'Val/mean precision': 0.9683740139007568, 'Val/mean recall': 0.9767953157424927, 'Val/mean hd95_metric': 6.195637226104736} +Epoch [1610/4000] Training [1/16] Loss: 0.00786 +Epoch [1610/4000] Training [2/16] Loss: 0.00785 +Epoch [1610/4000] Training [3/16] Loss: 0.00780 +Epoch [1610/4000] Training [4/16] Loss: 0.00595 +Epoch [1610/4000] Training [5/16] Loss: 0.00665 +Epoch [1610/4000] Training [6/16] Loss: 0.00658 +Epoch [1610/4000] Training [7/16] Loss: 0.00674 +Epoch [1610/4000] Training [8/16] Loss: 0.00639 +Epoch [1610/4000] Training [9/16] Loss: 0.00929 +Epoch [1610/4000] Training [10/16] Loss: 0.00640 +Epoch [1610/4000] Training [11/16] Loss: 0.00671 +Epoch [1610/4000] Training [12/16] Loss: 0.01002 +Epoch [1610/4000] Training [13/16] Loss: 0.00909 +Epoch [1610/4000] Training [14/16] Loss: 0.00734 +Epoch [1610/4000] Training [15/16] Loss: 0.00650 +Epoch [1610/4000] Training [16/16] Loss: 0.01078 +Epoch [1610/4000] Training metric {'Train/mean dice_metric': 0.9946433305740356, 'Train/mean miou_metric': 0.9890919923782349, 'Train/mean f1': 0.9907806515693665, 'Train/mean precision': 0.9861498475074768, 'Train/mean recall': 0.9954550862312317, 'Train/mean hd95_metric': 1.0189754962921143} +Epoch [1610/4000] Validation [1/4] Loss: 0.26361 focal_loss 0.18984 dice_loss 0.07377 +Epoch [1610/4000] Validation [2/4] Loss: 0.68028 focal_loss 0.41091 dice_loss 0.26937 +Epoch [1610/4000] Validation [3/4] Loss: 0.26073 focal_loss 0.17484 dice_loss 0.08589 +Epoch [1610/4000] Validation [4/4] Loss: 0.22527 focal_loss 0.13602 dice_loss 0.08925 +Epoch [1610/4000] Validation metric {'Val/mean dice_metric': 0.9697878956794739, 'Val/mean miou_metric': 0.9523825645446777, 'Val/mean f1': 0.9737451672554016, 'Val/mean precision': 0.9717409014701843, 'Val/mean recall': 0.9757577180862427, 'Val/mean hd95_metric': 5.711721897125244} +Cheakpoint... +Epoch [1610/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697878956794739, 'Val/mean miou_metric': 0.9523825645446777, 'Val/mean f1': 0.9737451672554016, 'Val/mean precision': 0.9717409014701843, 'Val/mean recall': 0.9757577180862427, 'Val/mean hd95_metric': 5.711721897125244} +Epoch [1611/4000] Training [1/16] Loss: 0.01883 +Epoch [1611/4000] Training [2/16] Loss: 0.00577 +Epoch [1611/4000] Training [3/16] Loss: 0.00640 +Epoch [1611/4000] Training [4/16] Loss: 0.00571 +Epoch [1611/4000] Training [5/16] Loss: 0.00815 +Epoch [1611/4000] Training [6/16] Loss: 0.01038 +Epoch [1611/4000] Training [7/16] Loss: 0.00832 +Epoch [1611/4000] Training [8/16] Loss: 0.00686 +Epoch [1611/4000] Training [9/16] Loss: 0.00729 +Epoch [1611/4000] Training [10/16] Loss: 0.00694 +Epoch [1611/4000] Training [11/16] Loss: 0.00695 +Epoch [1611/4000] Training [12/16] Loss: 0.00740 +Epoch [1611/4000] Training [13/16] Loss: 0.00849 +Epoch [1611/4000] Training [14/16] Loss: 0.00828 +Epoch [1611/4000] Training [15/16] Loss: 0.00791 +Epoch [1611/4000] Training [16/16] Loss: 0.00628 +Epoch [1611/4000] Training metric {'Train/mean dice_metric': 0.9945036172866821, 'Train/mean miou_metric': 0.9888526797294617, 'Train/mean f1': 0.9908194541931152, 'Train/mean precision': 0.9864194393157959, 'Train/mean recall': 0.9952589273452759, 'Train/mean hd95_metric': 1.0381160974502563} +Epoch [1611/4000] Validation [1/4] Loss: 0.33524 focal_loss 0.25585 dice_loss 0.07939 +Epoch [1611/4000] Validation [2/4] Loss: 0.47010 focal_loss 0.29023 dice_loss 0.17987 +Epoch [1611/4000] Validation [3/4] Loss: 0.26708 focal_loss 0.17466 dice_loss 0.09242 +Epoch [1611/4000] Validation [4/4] Loss: 0.26021 focal_loss 0.14338 dice_loss 0.11683 +Epoch [1611/4000] Validation metric {'Val/mean dice_metric': 0.971277117729187, 'Val/mean miou_metric': 0.9536353945732117, 'Val/mean f1': 0.9728586077690125, 'Val/mean precision': 0.9696662425994873, 'Val/mean recall': 0.9760719537734985, 'Val/mean hd95_metric': 5.869267463684082} +Cheakpoint... +Epoch [1611/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971277117729187, 'Val/mean miou_metric': 0.9536353945732117, 'Val/mean f1': 0.9728586077690125, 'Val/mean precision': 0.9696662425994873, 'Val/mean recall': 0.9760719537734985, 'Val/mean hd95_metric': 5.869267463684082} +Epoch [1612/4000] Training [1/16] Loss: 0.00730 +Epoch [1612/4000] Training [2/16] Loss: 0.01052 +Epoch [1612/4000] Training [3/16] Loss: 0.00783 +Epoch [1612/4000] Training [4/16] Loss: 0.00862 +Epoch [1612/4000] Training [5/16] Loss: 0.00836 +Epoch [1612/4000] Training [6/16] Loss: 0.01340 +Epoch [1612/4000] Training [7/16] Loss: 0.00550 +Epoch [1612/4000] Training [8/16] Loss: 0.00598 +Epoch [1612/4000] Training [9/16] Loss: 0.00807 +Epoch [1612/4000] Training [10/16] Loss: 0.00822 +Epoch [1612/4000] Training [11/16] Loss: 0.00991 +Epoch [1612/4000] Training [12/16] Loss: 0.01116 +Epoch [1612/4000] Training [13/16] Loss: 0.00701 +Epoch [1612/4000] Training [14/16] Loss: 0.00928 +Epoch [1612/4000] Training [15/16] Loss: 0.00810 +Epoch [1612/4000] Training [16/16] Loss: 0.00604 +Epoch [1612/4000] Training metric {'Train/mean dice_metric': 0.994267463684082, 'Train/mean miou_metric': 0.9883532524108887, 'Train/mean f1': 0.9901610612869263, 'Train/mean precision': 0.9854265451431274, 'Train/mean recall': 0.9949412941932678, 'Train/mean hd95_metric': 1.0860176086425781} +Epoch [1612/4000] Validation [1/4] Loss: 0.29082 focal_loss 0.21672 dice_loss 0.07410 +Epoch [1612/4000] Validation [2/4] Loss: 0.40920 focal_loss 0.23720 dice_loss 0.17200 +Epoch [1612/4000] Validation [3/4] Loss: 0.31246 focal_loss 0.19637 dice_loss 0.11608 +Epoch [1612/4000] Validation [4/4] Loss: 0.23625 focal_loss 0.13950 dice_loss 0.09675 +Epoch [1612/4000] Validation metric {'Val/mean dice_metric': 0.9703590273857117, 'Val/mean miou_metric': 0.9526381492614746, 'Val/mean f1': 0.9723427891731262, 'Val/mean precision': 0.9679517149925232, 'Val/mean recall': 0.9767739176750183, 'Val/mean hd95_metric': 5.81221866607666} +Cheakpoint... +Epoch [1612/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703590273857117, 'Val/mean miou_metric': 0.9526381492614746, 'Val/mean f1': 0.9723427891731262, 'Val/mean precision': 0.9679517149925232, 'Val/mean recall': 0.9767739176750183, 'Val/mean hd95_metric': 5.81221866607666} +Epoch [1613/4000] Training [1/16] Loss: 0.00707 +Epoch [1613/4000] Training [2/16] Loss: 0.00846 +Epoch [1613/4000] Training [3/16] Loss: 0.00874 +Epoch [1613/4000] Training [4/16] Loss: 0.00740 +Epoch [1613/4000] Training [5/16] Loss: 0.00793 +Epoch [1613/4000] Training [6/16] Loss: 0.00913 +Epoch [1613/4000] Training [7/16] Loss: 0.00546 +Epoch [1613/4000] Training [8/16] Loss: 0.00703 +Epoch [1613/4000] Training [9/16] Loss: 0.01011 +Epoch [1613/4000] Training [10/16] Loss: 0.00803 +Epoch [1613/4000] Training [11/16] Loss: 0.00654 +Epoch [1613/4000] Training [12/16] Loss: 0.00708 +Epoch [1613/4000] Training [13/16] Loss: 0.00899 +Epoch [1613/4000] Training [14/16] Loss: 0.00896 +Epoch [1613/4000] Training [15/16] Loss: 0.00631 +Epoch [1613/4000] Training [16/16] Loss: 0.00864 +Epoch [1613/4000] Training metric {'Train/mean dice_metric': 0.9948581457138062, 'Train/mean miou_metric': 0.9895176887512207, 'Train/mean f1': 0.9908145070075989, 'Train/mean precision': 0.9863327741622925, 'Train/mean recall': 0.9953372478485107, 'Train/mean hd95_metric': 1.0214157104492188} +Epoch [1613/4000] Validation [1/4] Loss: 0.34624 focal_loss 0.25694 dice_loss 0.08929 +Epoch [1613/4000] Validation [2/4] Loss: 0.31651 focal_loss 0.17131 dice_loss 0.14520 +Epoch [1613/4000] Validation [3/4] Loss: 0.24433 focal_loss 0.15472 dice_loss 0.08962 +Epoch [1613/4000] Validation [4/4] Loss: 0.29452 focal_loss 0.17162 dice_loss 0.12290 +Epoch [1613/4000] Validation metric {'Val/mean dice_metric': 0.9710443615913391, 'Val/mean miou_metric': 0.9529653787612915, 'Val/mean f1': 0.9727661609649658, 'Val/mean precision': 0.9696585536003113, 'Val/mean recall': 0.9758936166763306, 'Val/mean hd95_metric': 5.986620903015137} +Cheakpoint... +Epoch [1613/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710443615913391, 'Val/mean miou_metric': 0.9529653787612915, 'Val/mean f1': 0.9727661609649658, 'Val/mean precision': 0.9696585536003113, 'Val/mean recall': 0.9758936166763306, 'Val/mean hd95_metric': 5.986620903015137} +Epoch [1614/4000] Training [1/16] Loss: 0.00662 +Epoch [1614/4000] Training [2/16] Loss: 0.00631 +Epoch [1614/4000] Training [3/16] Loss: 0.00692 +Epoch [1614/4000] Training [4/16] Loss: 0.00887 +Epoch [1614/4000] Training [5/16] Loss: 0.02072 +Epoch [1614/4000] Training [6/16] Loss: 0.00745 +Epoch [1614/4000] Training [7/16] Loss: 0.00909 +Epoch [1614/4000] Training [8/16] Loss: 0.00678 +Epoch [1614/4000] Training [9/16] Loss: 0.00665 +Epoch [1614/4000] Training [10/16] Loss: 0.00869 +Epoch [1614/4000] Training [11/16] Loss: 0.00928 +Epoch [1614/4000] Training [12/16] Loss: 0.00844 +Epoch [1614/4000] Training [13/16] Loss: 0.03286 +Epoch [1614/4000] Training [14/16] Loss: 0.00703 +Epoch [1614/4000] Training [15/16] Loss: 0.00930 +Epoch [1614/4000] Training [16/16] Loss: 0.01491 +Epoch [1614/4000] Training metric {'Train/mean dice_metric': 0.9937453269958496, 'Train/mean miou_metric': 0.9874150156974792, 'Train/mean f1': 0.9898539185523987, 'Train/mean precision': 0.9854313731193542, 'Train/mean recall': 0.9943163990974426, 'Train/mean hd95_metric': 1.4339998960494995} +Epoch [1614/4000] Validation [1/4] Loss: 0.22534 focal_loss 0.16278 dice_loss 0.06256 +Epoch [1614/4000] Validation [2/4] Loss: 0.51355 focal_loss 0.31116 dice_loss 0.20239 +Epoch [1614/4000] Validation [3/4] Loss: 0.19895 focal_loss 0.11522 dice_loss 0.08373 +Epoch [1614/4000] Validation [4/4] Loss: 0.34841 focal_loss 0.20692 dice_loss 0.14149 +Epoch [1614/4000] Validation metric {'Val/mean dice_metric': 0.9693166613578796, 'Val/mean miou_metric': 0.9507578015327454, 'Val/mean f1': 0.9722276329994202, 'Val/mean precision': 0.9678570628166199, 'Val/mean recall': 0.9766378998756409, 'Val/mean hd95_metric': 6.482235908508301} +Cheakpoint... +Epoch [1614/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693166613578796, 'Val/mean miou_metric': 0.9507578015327454, 'Val/mean f1': 0.9722276329994202, 'Val/mean precision': 0.9678570628166199, 'Val/mean recall': 0.9766378998756409, 'Val/mean hd95_metric': 6.482235908508301} +Epoch [1615/4000] Training [1/16] Loss: 0.00721 +Epoch [1615/4000] Training [2/16] Loss: 0.00650 +Epoch [1615/4000] Training [3/16] Loss: 0.00856 +Epoch [1615/4000] Training [4/16] Loss: 0.00675 +Epoch [1615/4000] Training [5/16] Loss: 0.00977 +Epoch [1615/4000] Training [6/16] Loss: 0.00921 +Epoch [1615/4000] Training [7/16] Loss: 0.00818 +Epoch [1615/4000] Training [8/16] Loss: 0.00780 +Epoch [1615/4000] Training [9/16] Loss: 0.01071 +Epoch [1615/4000] Training [10/16] Loss: 0.00666 +Epoch [1615/4000] Training [11/16] Loss: 0.00989 +Epoch [1615/4000] Training [12/16] Loss: 0.00701 +Epoch [1615/4000] Training [13/16] Loss: 0.00743 +Epoch [1615/4000] Training [14/16] Loss: 0.00769 +Epoch [1615/4000] Training [15/16] Loss: 0.00702 +Epoch [1615/4000] Training [16/16] Loss: 0.00840 +Epoch [1615/4000] Training metric {'Train/mean dice_metric': 0.994112491607666, 'Train/mean miou_metric': 0.9881019592285156, 'Train/mean f1': 0.989745557308197, 'Train/mean precision': 0.9846009016036987, 'Train/mean recall': 0.9949443340301514, 'Train/mean hd95_metric': 1.2430044412612915} +Epoch [1615/4000] Validation [1/4] Loss: 0.52849 focal_loss 0.39554 dice_loss 0.13296 +Epoch [1615/4000] Validation [2/4] Loss: 0.44822 focal_loss 0.27481 dice_loss 0.17341 +Epoch [1615/4000] Validation [3/4] Loss: 0.17495 focal_loss 0.10525 dice_loss 0.06970 +Epoch [1615/4000] Validation [4/4] Loss: 0.40005 focal_loss 0.25916 dice_loss 0.14089 +Epoch [1615/4000] Validation metric {'Val/mean dice_metric': 0.9662715792655945, 'Val/mean miou_metric': 0.9478557705879211, 'Val/mean f1': 0.9696904420852661, 'Val/mean precision': 0.9720215201377869, 'Val/mean recall': 0.9673705101013184, 'Val/mean hd95_metric': 6.30826473236084} +Cheakpoint... +Epoch [1615/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9663], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9662715792655945, 'Val/mean miou_metric': 0.9478557705879211, 'Val/mean f1': 0.9696904420852661, 'Val/mean precision': 0.9720215201377869, 'Val/mean recall': 0.9673705101013184, 'Val/mean hd95_metric': 6.30826473236084} +Epoch [1616/4000] Training [1/16] Loss: 0.00790 +Epoch [1616/4000] Training [2/16] Loss: 0.00862 +Epoch [1616/4000] Training [3/16] Loss: 0.00814 +Epoch [1616/4000] Training [4/16] Loss: 0.01015 +Epoch [1616/4000] Training [5/16] Loss: 0.00868 +Epoch [1616/4000] Training [6/16] Loss: 0.00808 +Epoch [1616/4000] Training [7/16] Loss: 0.01011 +Epoch [1616/4000] Training [8/16] Loss: 0.00946 +Epoch [1616/4000] Training [9/16] Loss: 0.00669 +Epoch [1616/4000] Training [10/16] Loss: 0.00749 +Epoch [1616/4000] Training [11/16] Loss: 0.00866 +Epoch [1616/4000] Training [12/16] Loss: 0.00933 +Epoch [1616/4000] Training [13/16] Loss: 0.00974 +Epoch [1616/4000] Training [14/16] Loss: 0.00977 +Epoch [1616/4000] Training [15/16] Loss: 0.01101 +Epoch [1616/4000] Training [16/16] Loss: 0.00687 +Epoch [1616/4000] Training metric {'Train/mean dice_metric': 0.9939035177230835, 'Train/mean miou_metric': 0.9876661896705627, 'Train/mean f1': 0.9897387027740479, 'Train/mean precision': 0.9857687950134277, 'Train/mean recall': 0.9937406778335571, 'Train/mean hd95_metric': 1.3971768617630005} +Epoch [1616/4000] Validation [1/4] Loss: 0.40560 focal_loss 0.31282 dice_loss 0.09278 +Epoch [1616/4000] Validation [2/4] Loss: 0.50625 focal_loss 0.26261 dice_loss 0.24364 +Epoch [1616/4000] Validation [3/4] Loss: 0.16762 focal_loss 0.10158 dice_loss 0.06604 +Epoch [1616/4000] Validation [4/4] Loss: 0.50370 focal_loss 0.32823 dice_loss 0.17547 +Epoch [1616/4000] Validation metric {'Val/mean dice_metric': 0.9637487530708313, 'Val/mean miou_metric': 0.9448396563529968, 'Val/mean f1': 0.9688184857368469, 'Val/mean precision': 0.9690712094306946, 'Val/mean recall': 0.9685659408569336, 'Val/mean hd95_metric': 7.113598346710205} +Cheakpoint... +Epoch [1616/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9637487530708313, 'Val/mean miou_metric': 0.9448396563529968, 'Val/mean f1': 0.9688184857368469, 'Val/mean precision': 0.9690712094306946, 'Val/mean recall': 0.9685659408569336, 'Val/mean hd95_metric': 7.113598346710205} +Epoch [1617/4000] Training [1/16] Loss: 0.00829 +Epoch [1617/4000] Training [2/16] Loss: 0.01075 +Epoch [1617/4000] Training [3/16] Loss: 0.00759 +Epoch [1617/4000] Training [4/16] Loss: 0.01000 +Epoch [1617/4000] Training [5/16] Loss: 0.00830 +Epoch [1617/4000] Training [6/16] Loss: 0.00631 +Epoch [1617/4000] Training [7/16] Loss: 0.00668 +Epoch [1617/4000] Training [8/16] Loss: 0.01003 +Epoch [1617/4000] Training [9/16] Loss: 0.01028 +Epoch [1617/4000] Training [10/16] Loss: 0.00837 +Epoch [1617/4000] Training [11/16] Loss: 0.00877 +Epoch [1617/4000] Training [12/16] Loss: 0.00834 +Epoch [1617/4000] Training [13/16] Loss: 0.00725 +Epoch [1617/4000] Training [14/16] Loss: 0.00829 +Epoch [1617/4000] Training [15/16] Loss: 0.00851 +Epoch [1617/4000] Training [16/16] Loss: 0.00805 +Epoch [1617/4000] Training metric {'Train/mean dice_metric': 0.9939359426498413, 'Train/mean miou_metric': 0.9876885414123535, 'Train/mean f1': 0.9895685315132141, 'Train/mean precision': 0.9844834804534912, 'Train/mean recall': 0.9947062730789185, 'Train/mean hd95_metric': 1.1910027265548706} +Epoch [1617/4000] Validation [1/4] Loss: 0.17975 focal_loss 0.11903 dice_loss 0.06073 +Epoch [1617/4000] Validation [2/4] Loss: 0.45205 focal_loss 0.26751 dice_loss 0.18453 +Epoch [1617/4000] Validation [3/4] Loss: 0.14657 focal_loss 0.08953 dice_loss 0.05704 +Epoch [1617/4000] Validation [4/4] Loss: 0.44074 focal_loss 0.26660 dice_loss 0.17414 +Epoch [1617/4000] Validation metric {'Val/mean dice_metric': 0.9682737588882446, 'Val/mean miou_metric': 0.9499821662902832, 'Val/mean f1': 0.9718565344810486, 'Val/mean precision': 0.9697742462158203, 'Val/mean recall': 0.9739477634429932, 'Val/mean hd95_metric': 6.109433650970459} +Cheakpoint... +Epoch [1617/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9683], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9682737588882446, 'Val/mean miou_metric': 0.9499821662902832, 'Val/mean f1': 0.9718565344810486, 'Val/mean precision': 0.9697742462158203, 'Val/mean recall': 0.9739477634429932, 'Val/mean hd95_metric': 6.109433650970459} +Epoch [1618/4000] Training [1/16] Loss: 0.00677 +Epoch [1618/4000] Training [2/16] Loss: 0.00951 +Epoch [1618/4000] Training [3/16] Loss: 0.00565 +Epoch [1618/4000] Training [4/16] Loss: 0.00896 +Epoch [1618/4000] Training [5/16] Loss: 0.00553 +Epoch [1618/4000] Training [6/16] Loss: 0.00676 +Epoch [1618/4000] Training [7/16] Loss: 0.00714 +Epoch [1618/4000] Training [8/16] Loss: 0.00788 +Epoch [1618/4000] Training [9/16] Loss: 0.00823 +Epoch [1618/4000] Training [10/16] Loss: 0.01289 +Epoch [1618/4000] Training [11/16] Loss: 0.00688 +Epoch [1618/4000] Training [12/16] Loss: 0.00889 +Epoch [1618/4000] Training [13/16] Loss: 0.00710 +Epoch [1618/4000] Training [14/16] Loss: 0.00797 +Epoch [1618/4000] Training [15/16] Loss: 0.00619 +Epoch [1618/4000] Training [16/16] Loss: 0.00880 +Epoch [1618/4000] Training metric {'Train/mean dice_metric': 0.9944188594818115, 'Train/mean miou_metric': 0.9886528253555298, 'Train/mean f1': 0.9901518821716309, 'Train/mean precision': 0.9858959317207336, 'Train/mean recall': 0.9944447875022888, 'Train/mean hd95_metric': 1.5851534605026245} +Epoch [1618/4000] Validation [1/4] Loss: 0.26691 focal_loss 0.19742 dice_loss 0.06949 +Epoch [1618/4000] Validation [2/4] Loss: 0.23300 focal_loss 0.11704 dice_loss 0.11596 +Epoch [1618/4000] Validation [3/4] Loss: 0.34768 focal_loss 0.24509 dice_loss 0.10259 +Epoch [1618/4000] Validation [4/4] Loss: 0.35655 focal_loss 0.22110 dice_loss 0.13545 +Epoch [1618/4000] Validation metric {'Val/mean dice_metric': 0.9692943692207336, 'Val/mean miou_metric': 0.9505297541618347, 'Val/mean f1': 0.9701933264732361, 'Val/mean precision': 0.9634854197502136, 'Val/mean recall': 0.9769951105117798, 'Val/mean hd95_metric': 7.743862152099609} +Cheakpoint... +Epoch [1618/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692943692207336, 'Val/mean miou_metric': 0.9505297541618347, 'Val/mean f1': 0.9701933264732361, 'Val/mean precision': 0.9634854197502136, 'Val/mean recall': 0.9769951105117798, 'Val/mean hd95_metric': 7.743862152099609} +Epoch [1619/4000] Training [1/16] Loss: 0.00653 +Epoch [1619/4000] Training [2/16] Loss: 0.01130 +Epoch [1619/4000] Training [3/16] Loss: 0.00861 +Epoch [1619/4000] Training [4/16] Loss: 0.00841 +Epoch [1619/4000] Training [5/16] Loss: 0.00791 +Epoch [1619/4000] Training [6/16] Loss: 0.00854 +Epoch [1619/4000] Training [7/16] Loss: 0.00829 +Epoch [1619/4000] Training [8/16] Loss: 0.00848 +Epoch [1619/4000] Training [9/16] Loss: 0.00674 +Epoch [1619/4000] Training [10/16] Loss: 0.00781 +Epoch [1619/4000] Training [11/16] Loss: 0.00791 +Epoch [1619/4000] Training [12/16] Loss: 0.00789 +Epoch [1619/4000] Training [13/16] Loss: 0.00810 +Epoch [1619/4000] Training [14/16] Loss: 0.00556 +Epoch [1619/4000] Training [15/16] Loss: 0.00740 +Epoch [1619/4000] Training [16/16] Loss: 0.00644 +Epoch [1619/4000] Training metric {'Train/mean dice_metric': 0.9948261380195618, 'Train/mean miou_metric': 0.9894528985023499, 'Train/mean f1': 0.9905668497085571, 'Train/mean precision': 0.9861537218093872, 'Train/mean recall': 0.9950196146965027, 'Train/mean hd95_metric': 1.2334790229797363} +Epoch [1619/4000] Validation [1/4] Loss: 0.24983 focal_loss 0.17740 dice_loss 0.07242 +Epoch [1619/4000] Validation [2/4] Loss: 0.36314 focal_loss 0.22453 dice_loss 0.13861 +Epoch [1619/4000] Validation [3/4] Loss: 0.20574 focal_loss 0.11958 dice_loss 0.08616 +Epoch [1619/4000] Validation [4/4] Loss: 0.31565 focal_loss 0.18765 dice_loss 0.12801 +Epoch [1619/4000] Validation metric {'Val/mean dice_metric': 0.9688865542411804, 'Val/mean miou_metric': 0.9512189626693726, 'Val/mean f1': 0.9720587730407715, 'Val/mean precision': 0.9670739769935608, 'Val/mean recall': 0.9770954251289368, 'Val/mean hd95_metric': 6.8708624839782715} +Cheakpoint... +Epoch [1619/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688865542411804, 'Val/mean miou_metric': 0.9512189626693726, 'Val/mean f1': 0.9720587730407715, 'Val/mean precision': 0.9670739769935608, 'Val/mean recall': 0.9770954251289368, 'Val/mean hd95_metric': 6.8708624839782715} +Epoch [1620/4000] Training [1/16] Loss: 0.00988 +Epoch [1620/4000] Training [2/16] Loss: 0.00694 +Epoch [1620/4000] Training [3/16] Loss: 0.00878 +Epoch [1620/4000] Training [4/16] Loss: 0.00624 +Epoch [1620/4000] Training [5/16] Loss: 0.00724 +Epoch [1620/4000] Training [6/16] Loss: 0.00718 +Epoch [1620/4000] Training [7/16] Loss: 0.00736 +Epoch [1620/4000] Training [8/16] Loss: 0.01111 +Epoch [1620/4000] Training [9/16] Loss: 0.00943 +Epoch [1620/4000] Training [10/16] Loss: 0.01106 +Epoch [1620/4000] Training [11/16] Loss: 0.00716 +Epoch [1620/4000] Training [12/16] Loss: 0.00542 +Epoch [1620/4000] Training [13/16] Loss: 0.00853 +Epoch [1620/4000] Training [14/16] Loss: 0.00608 +Epoch [1620/4000] Training [15/16] Loss: 0.00639 +Epoch [1620/4000] Training [16/16] Loss: 0.00809 +Epoch [1620/4000] Training metric {'Train/mean dice_metric': 0.9950287938117981, 'Train/mean miou_metric': 0.9898281097412109, 'Train/mean f1': 0.9903879165649414, 'Train/mean precision': 0.9854716658592224, 'Train/mean recall': 0.9953534603118896, 'Train/mean hd95_metric': 1.0494611263275146} +Epoch [1620/4000] Validation [1/4] Loss: 0.40122 focal_loss 0.31243 dice_loss 0.08879 +Epoch [1620/4000] Validation [2/4] Loss: 0.23408 focal_loss 0.12329 dice_loss 0.11079 +Epoch [1620/4000] Validation [3/4] Loss: 0.16318 focal_loss 0.10373 dice_loss 0.05945 +Epoch [1620/4000] Validation [4/4] Loss: 0.29165 focal_loss 0.16863 dice_loss 0.12302 +Epoch [1620/4000] Validation metric {'Val/mean dice_metric': 0.9711675643920898, 'Val/mean miou_metric': 0.9537906646728516, 'Val/mean f1': 0.9731141328811646, 'Val/mean precision': 0.9703294038772583, 'Val/mean recall': 0.9759148359298706, 'Val/mean hd95_metric': 5.952549457550049} +Cheakpoint... +Epoch [1620/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711675643920898, 'Val/mean miou_metric': 0.9537906646728516, 'Val/mean f1': 0.9731141328811646, 'Val/mean precision': 0.9703294038772583, 'Val/mean recall': 0.9759148359298706, 'Val/mean hd95_metric': 5.952549457550049} +Epoch [1621/4000] Training [1/16] Loss: 0.00820 +Epoch [1621/4000] Training [2/16] Loss: 0.00620 +Epoch [1621/4000] Training [3/16] Loss: 0.00634 +Epoch [1621/4000] Training [4/16] Loss: 0.00935 +Epoch [1621/4000] Training [5/16] Loss: 0.00921 +Epoch [1621/4000] Training [6/16] Loss: 0.00633 +Epoch [1621/4000] Training [7/16] Loss: 0.00635 +Epoch [1621/4000] Training [8/16] Loss: 0.00573 +Epoch [1621/4000] Training [9/16] Loss: 0.00925 +Epoch [1621/4000] Training [10/16] Loss: 0.00612 +Epoch [1621/4000] Training [11/16] Loss: 0.00968 +Epoch [1621/4000] Training [12/16] Loss: 0.00739 +Epoch [1621/4000] Training [13/16] Loss: 0.00740 +Epoch [1621/4000] Training [14/16] Loss: 0.00802 +Epoch [1621/4000] Training [15/16] Loss: 0.00658 +Epoch [1621/4000] Training [16/16] Loss: 0.00714 +Epoch [1621/4000] Training metric {'Train/mean dice_metric': 0.995184063911438, 'Train/mean miou_metric': 0.9901342988014221, 'Train/mean f1': 0.9903073906898499, 'Train/mean precision': 0.9851038455963135, 'Train/mean recall': 0.995566189289093, 'Train/mean hd95_metric': 1.0221885442733765} +Epoch [1621/4000] Validation [1/4] Loss: 0.25665 focal_loss 0.19299 dice_loss 0.06366 +Epoch [1621/4000] Validation [2/4] Loss: 0.34151 focal_loss 0.20311 dice_loss 0.13840 +Epoch [1621/4000] Validation [3/4] Loss: 0.19047 focal_loss 0.12564 dice_loss 0.06483 +Epoch [1621/4000] Validation [4/4] Loss: 0.31871 focal_loss 0.17197 dice_loss 0.14674 +Epoch [1621/4000] Validation metric {'Val/mean dice_metric': 0.9710294604301453, 'Val/mean miou_metric': 0.9537284970283508, 'Val/mean f1': 0.9712852239608765, 'Val/mean precision': 0.9622727632522583, 'Val/mean recall': 0.9804680943489075, 'Val/mean hd95_metric': 6.717043399810791} +Cheakpoint... +Epoch [1621/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710294604301453, 'Val/mean miou_metric': 0.9537284970283508, 'Val/mean f1': 0.9712852239608765, 'Val/mean precision': 0.9622727632522583, 'Val/mean recall': 0.9804680943489075, 'Val/mean hd95_metric': 6.717043399810791} +Epoch [1622/4000] Training [1/16] Loss: 0.00560 +Epoch [1622/4000] Training [2/16] Loss: 0.00537 +Epoch [1622/4000] Training [3/16] Loss: 0.00618 +Epoch [1622/4000] Training [4/16] Loss: 0.00683 +Epoch [1622/4000] Training [5/16] Loss: 0.00544 +Epoch [1622/4000] Training [6/16] Loss: 0.00731 +Epoch [1622/4000] Training [7/16] Loss: 0.00577 +Epoch [1622/4000] Training [8/16] Loss: 0.00605 +Epoch [1622/4000] Training [9/16] Loss: 0.00672 +Epoch [1622/4000] Training [10/16] Loss: 0.00687 +Epoch [1622/4000] Training [11/16] Loss: 0.00606 +Epoch [1622/4000] Training [12/16] Loss: 0.00646 +Epoch [1622/4000] Training [13/16] Loss: 0.00681 +Epoch [1622/4000] Training [14/16] Loss: 0.00931 +Epoch [1622/4000] Training [15/16] Loss: 0.00691 +Epoch [1622/4000] Training [16/16] Loss: 0.00753 +Epoch [1622/4000] Training metric {'Train/mean dice_metric': 0.995495080947876, 'Train/mean miou_metric': 0.9907640218734741, 'Train/mean f1': 0.9912849068641663, 'Train/mean precision': 0.9865742325782776, 'Train/mean recall': 0.9960407614707947, 'Train/mean hd95_metric': 1.0097780227661133} +Epoch [1622/4000] Validation [1/4] Loss: 0.29904 focal_loss 0.22548 dice_loss 0.07355 +Epoch [1622/4000] Validation [2/4] Loss: 0.20869 focal_loss 0.10889 dice_loss 0.09980 +Epoch [1622/4000] Validation [3/4] Loss: 0.17785 focal_loss 0.12060 dice_loss 0.05725 +Epoch [1622/4000] Validation [4/4] Loss: 0.32702 focal_loss 0.18582 dice_loss 0.14120 +Epoch [1622/4000] Validation metric {'Val/mean dice_metric': 0.9736175537109375, 'Val/mean miou_metric': 0.9561910629272461, 'Val/mean f1': 0.9736237525939941, 'Val/mean precision': 0.9664797186851501, 'Val/mean recall': 0.9808743000030518, 'Val/mean hd95_metric': 6.258403301239014} +Cheakpoint... +Epoch [1622/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736175537109375, 'Val/mean miou_metric': 0.9561910629272461, 'Val/mean f1': 0.9736237525939941, 'Val/mean precision': 0.9664797186851501, 'Val/mean recall': 0.9808743000030518, 'Val/mean hd95_metric': 6.258403301239014} +Epoch [1623/4000] Training [1/16] Loss: 0.00622 +Epoch [1623/4000] Training [2/16] Loss: 0.00691 +Epoch [1623/4000] Training [3/16] Loss: 0.00909 +Epoch [1623/4000] Training [4/16] Loss: 0.01074 +Epoch [1623/4000] Training [5/16] Loss: 0.00961 +Epoch [1623/4000] Training [6/16] Loss: 0.00653 +Epoch [1623/4000] Training [7/16] Loss: 0.00686 +Epoch [1623/4000] Training [8/16] Loss: 0.00577 +Epoch [1623/4000] Training [9/16] Loss: 0.00539 +Epoch [1623/4000] Training [10/16] Loss: 0.01472 +Epoch [1623/4000] Training [11/16] Loss: 0.00646 +Epoch [1623/4000] Training [12/16] Loss: 0.00671 +Epoch [1623/4000] Training [13/16] Loss: 0.00734 +Epoch [1623/4000] Training [14/16] Loss: 0.00626 +Epoch [1623/4000] Training [15/16] Loss: 0.00710 +Epoch [1623/4000] Training [16/16] Loss: 0.00661 +Epoch [1623/4000] Training metric {'Train/mean dice_metric': 0.9951038360595703, 'Train/mean miou_metric': 0.9900010228157043, 'Train/mean f1': 0.9910421371459961, 'Train/mean precision': 0.9865809082984924, 'Train/mean recall': 0.9955439567565918, 'Train/mean hd95_metric': 1.031193733215332} +Epoch [1623/4000] Validation [1/4] Loss: 0.28501 focal_loss 0.21058 dice_loss 0.07443 +Epoch [1623/4000] Validation [2/4] Loss: 0.59495 focal_loss 0.37473 dice_loss 0.22023 +Epoch [1623/4000] Validation [3/4] Loss: 0.22416 focal_loss 0.14521 dice_loss 0.07895 +Epoch [1623/4000] Validation [4/4] Loss: 0.26996 focal_loss 0.15964 dice_loss 0.11032 +Epoch [1623/4000] Validation metric {'Val/mean dice_metric': 0.970278263092041, 'Val/mean miou_metric': 0.9535280466079712, 'Val/mean f1': 0.9730848670005798, 'Val/mean precision': 0.9669910669326782, 'Val/mean recall': 0.9792560338973999, 'Val/mean hd95_metric': 6.0852766036987305} +Cheakpoint... +Epoch [1623/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970278263092041, 'Val/mean miou_metric': 0.9535280466079712, 'Val/mean f1': 0.9730848670005798, 'Val/mean precision': 0.9669910669326782, 'Val/mean recall': 0.9792560338973999, 'Val/mean hd95_metric': 6.0852766036987305} +Epoch [1624/4000] Training [1/16] Loss: 0.00784 +Epoch [1624/4000] Training [2/16] Loss: 0.00742 +Epoch [1624/4000] Training [3/16] Loss: 0.00726 +Epoch [1624/4000] Training [4/16] Loss: 0.00700 +Epoch [1624/4000] Training [5/16] Loss: 0.00979 +Epoch [1624/4000] Training [6/16] Loss: 0.00786 +Epoch [1624/4000] Training [7/16] Loss: 0.00861 +Epoch [1624/4000] Training [8/16] Loss: 0.00677 +Epoch [1624/4000] Training [9/16] Loss: 0.00863 +Epoch [1624/4000] Training [10/16] Loss: 0.00700 +Epoch [1624/4000] Training [11/16] Loss: 0.00954 +Epoch [1624/4000] Training [12/16] Loss: 0.02511 +Epoch [1624/4000] Training [13/16] Loss: 0.00648 +Epoch [1624/4000] Training [14/16] Loss: 0.00839 +Epoch [1624/4000] Training [15/16] Loss: 0.00692 +Epoch [1624/4000] Training [16/16] Loss: 0.00901 +Epoch [1624/4000] Training metric {'Train/mean dice_metric': 0.9944475293159485, 'Train/mean miou_metric': 0.9887531399726868, 'Train/mean f1': 0.990654706954956, 'Train/mean precision': 0.9861022233963013, 'Train/mean recall': 0.9952493906021118, 'Train/mean hd95_metric': 1.1460940837860107} +Epoch [1624/4000] Validation [1/4] Loss: 0.24024 focal_loss 0.17315 dice_loss 0.06709 +Epoch [1624/4000] Validation [2/4] Loss: 0.46637 focal_loss 0.27626 dice_loss 0.19011 +Epoch [1624/4000] Validation [3/4] Loss: 0.17706 focal_loss 0.11270 dice_loss 0.06436 +Epoch [1624/4000] Validation [4/4] Loss: 0.23699 focal_loss 0.12872 dice_loss 0.10827 +Epoch [1624/4000] Validation metric {'Val/mean dice_metric': 0.9694194793701172, 'Val/mean miou_metric': 0.9520851373672485, 'Val/mean f1': 0.9730440378189087, 'Val/mean precision': 0.9691416025161743, 'Val/mean recall': 0.9769781827926636, 'Val/mean hd95_metric': 5.916961193084717} +Cheakpoint... +Epoch [1624/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694194793701172, 'Val/mean miou_metric': 0.9520851373672485, 'Val/mean f1': 0.9730440378189087, 'Val/mean precision': 0.9691416025161743, 'Val/mean recall': 0.9769781827926636, 'Val/mean hd95_metric': 5.916961193084717} +Epoch [1625/4000] Training [1/16] Loss: 0.00656 +Epoch [1625/4000] Training [2/16] Loss: 0.00723 +Epoch [1625/4000] Training [3/16] Loss: 0.00707 +Epoch [1625/4000] Training [4/16] Loss: 0.00713 +Epoch [1625/4000] Training [5/16] Loss: 0.00861 +Epoch [1625/4000] Training [6/16] Loss: 0.00812 +Epoch [1625/4000] Training [7/16] Loss: 0.00687 +Epoch [1625/4000] Training [8/16] Loss: 0.00638 +Epoch [1625/4000] Training [9/16] Loss: 0.00674 +Epoch [1625/4000] Training [10/16] Loss: 0.00743 +Epoch [1625/4000] Training [11/16] Loss: 0.00773 +Epoch [1625/4000] Training [12/16] Loss: 0.00546 +Epoch [1625/4000] Training [13/16] Loss: 0.00573 +Epoch [1625/4000] Training [14/16] Loss: 0.00779 +Epoch [1625/4000] Training [15/16] Loss: 0.00759 +Epoch [1625/4000] Training [16/16] Loss: 0.00753 +Epoch [1625/4000] Training metric {'Train/mean dice_metric': 0.9950006008148193, 'Train/mean miou_metric': 0.9897992610931396, 'Train/mean f1': 0.9910752177238464, 'Train/mean precision': 0.9866076111793518, 'Train/mean recall': 0.9955834150314331, 'Train/mean hd95_metric': 1.0257185697555542} +Epoch [1625/4000] Validation [1/4] Loss: 0.36758 focal_loss 0.27898 dice_loss 0.08859 +Epoch [1625/4000] Validation [2/4] Loss: 0.45062 focal_loss 0.27016 dice_loss 0.18046 +Epoch [1625/4000] Validation [3/4] Loss: 0.17549 focal_loss 0.11387 dice_loss 0.06162 +Epoch [1625/4000] Validation [4/4] Loss: 0.31439 focal_loss 0.18727 dice_loss 0.12711 +Epoch [1625/4000] Validation metric {'Val/mean dice_metric': 0.9707088470458984, 'Val/mean miou_metric': 0.9532113075256348, 'Val/mean f1': 0.9731613397598267, 'Val/mean precision': 0.970608651638031, 'Val/mean recall': 0.9757275581359863, 'Val/mean hd95_metric': 5.697973728179932} +Cheakpoint... +Epoch [1625/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707088470458984, 'Val/mean miou_metric': 0.9532113075256348, 'Val/mean f1': 0.9731613397598267, 'Val/mean precision': 0.970608651638031, 'Val/mean recall': 0.9757275581359863, 'Val/mean hd95_metric': 5.697973728179932} +Epoch [1626/4000] Training [1/16] Loss: 0.00606 +Epoch [1626/4000] Training [2/16] Loss: 0.00742 +Epoch [1626/4000] Training [3/16] Loss: 0.00820 +Epoch [1626/4000] Training [4/16] Loss: 0.00880 +Epoch [1626/4000] Training [5/16] Loss: 0.00890 +Epoch [1626/4000] Training [6/16] Loss: 0.00995 +Epoch [1626/4000] Training [7/16] Loss: 0.00750 +Epoch [1626/4000] Training [8/16] Loss: 0.00874 +Epoch [1626/4000] Training [9/16] Loss: 0.00826 +Epoch [1626/4000] Training [10/16] Loss: 0.00782 +Epoch [1626/4000] Training [11/16] Loss: 0.00608 +Epoch [1626/4000] Training [12/16] Loss: 0.00914 +Epoch [1626/4000] Training [13/16] Loss: 0.00620 +Epoch [1626/4000] Training [14/16] Loss: 0.01121 +Epoch [1626/4000] Training [15/16] Loss: 0.00814 +Epoch [1626/4000] Training [16/16] Loss: 0.00669 +Epoch [1626/4000] Training metric {'Train/mean dice_metric': 0.9937807321548462, 'Train/mean miou_metric': 0.9877156019210815, 'Train/mean f1': 0.9904623031616211, 'Train/mean precision': 0.9859883785247803, 'Train/mean recall': 0.9949769973754883, 'Train/mean hd95_metric': 1.2554222345352173} +Epoch [1626/4000] Validation [1/4] Loss: 0.35141 focal_loss 0.26474 dice_loss 0.08667 +Epoch [1626/4000] Validation [2/4] Loss: 0.53325 focal_loss 0.34464 dice_loss 0.18861 +Epoch [1626/4000] Validation [3/4] Loss: 0.18748 focal_loss 0.11301 dice_loss 0.07447 +Epoch [1626/4000] Validation [4/4] Loss: 0.27448 focal_loss 0.15385 dice_loss 0.12063 +Epoch [1626/4000] Validation metric {'Val/mean dice_metric': 0.9713563919067383, 'Val/mean miou_metric': 0.9532346725463867, 'Val/mean f1': 0.9731593728065491, 'Val/mean precision': 0.9694210290908813, 'Val/mean recall': 0.9769267439842224, 'Val/mean hd95_metric': 5.925853729248047} +Cheakpoint... +Epoch [1626/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713563919067383, 'Val/mean miou_metric': 0.9532346725463867, 'Val/mean f1': 0.9731593728065491, 'Val/mean precision': 0.9694210290908813, 'Val/mean recall': 0.9769267439842224, 'Val/mean hd95_metric': 5.925853729248047} +Epoch [1627/4000] Training [1/16] Loss: 0.00646 +Epoch [1627/4000] Training [2/16] Loss: 0.00785 +Epoch [1627/4000] Training [3/16] Loss: 0.00902 +Epoch [1627/4000] Training [4/16] Loss: 0.01086 +Epoch [1627/4000] Training [5/16] Loss: 0.00861 +Epoch [1627/4000] Training [6/16] Loss: 0.00538 +Epoch [1627/4000] Training [7/16] Loss: 0.00728 +Epoch [1627/4000] Training [8/16] Loss: 0.00780 +Epoch [1627/4000] Training [9/16] Loss: 0.00727 +Epoch [1627/4000] Training [10/16] Loss: 0.00961 +Epoch [1627/4000] Training [11/16] Loss: 0.00857 +Epoch [1627/4000] Training [12/16] Loss: 0.00769 +Epoch [1627/4000] Training [13/16] Loss: 0.00755 +Epoch [1627/4000] Training [14/16] Loss: 0.00645 +Epoch [1627/4000] Training [15/16] Loss: 0.00639 +Epoch [1627/4000] Training [16/16] Loss: 0.00959 +Epoch [1627/4000] Training metric {'Train/mean dice_metric': 0.994727373123169, 'Train/mean miou_metric': 0.9892501831054688, 'Train/mean f1': 0.9906371235847473, 'Train/mean precision': 0.9860188364982605, 'Train/mean recall': 0.9952989220619202, 'Train/mean hd95_metric': 1.0377709865570068} +Epoch [1627/4000] Validation [1/4] Loss: 0.28135 focal_loss 0.20741 dice_loss 0.07395 +Epoch [1627/4000] Validation [2/4] Loss: 0.56517 focal_loss 0.36031 dice_loss 0.20486 +Epoch [1627/4000] Validation [3/4] Loss: 0.20586 focal_loss 0.12433 dice_loss 0.08153 +Epoch [1627/4000] Validation [4/4] Loss: 0.38313 focal_loss 0.21366 dice_loss 0.16947 +Epoch [1627/4000] Validation metric {'Val/mean dice_metric': 0.9711107015609741, 'Val/mean miou_metric': 0.9533251523971558, 'Val/mean f1': 0.9733694791793823, 'Val/mean precision': 0.9688803553581238, 'Val/mean recall': 0.9779004454612732, 'Val/mean hd95_metric': 6.2639994621276855} +Cheakpoint... +Epoch [1627/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711107015609741, 'Val/mean miou_metric': 0.9533251523971558, 'Val/mean f1': 0.9733694791793823, 'Val/mean precision': 0.9688803553581238, 'Val/mean recall': 0.9779004454612732, 'Val/mean hd95_metric': 6.2639994621276855} +Epoch [1628/4000] Training [1/16] Loss: 0.00810 +Epoch [1628/4000] Training [2/16] Loss: 0.01039 +Epoch [1628/4000] Training [3/16] Loss: 0.00806 +Epoch [1628/4000] Training [4/16] Loss: 0.01231 +Epoch [1628/4000] Training [5/16] Loss: 0.00843 +Epoch [1628/4000] Training [6/16] Loss: 0.00659 +Epoch [1628/4000] Training [7/16] Loss: 0.00580 +Epoch [1628/4000] Training [8/16] Loss: 0.00592 +Epoch [1628/4000] Training [9/16] Loss: 0.00859 +Epoch [1628/4000] Training [10/16] Loss: 0.01225 +Epoch [1628/4000] Training [11/16] Loss: 0.00814 +Epoch [1628/4000] Training [12/16] Loss: 0.00797 +Epoch [1628/4000] Training [13/16] Loss: 0.00823 +Epoch [1628/4000] Training [14/16] Loss: 0.00686 +Epoch [1628/4000] Training [15/16] Loss: 0.00780 +Epoch [1628/4000] Training [16/16] Loss: 0.00816 +Epoch [1628/4000] Training metric {'Train/mean dice_metric': 0.9947821497917175, 'Train/mean miou_metric': 0.9893416166305542, 'Train/mean f1': 0.9899562001228333, 'Train/mean precision': 0.9847880601882935, 'Train/mean recall': 0.9951788783073425, 'Train/mean hd95_metric': 1.0695972442626953} +Epoch [1628/4000] Validation [1/4] Loss: 0.31598 focal_loss 0.23937 dice_loss 0.07660 +Epoch [1628/4000] Validation [2/4] Loss: 0.59874 focal_loss 0.35916 dice_loss 0.23959 +Epoch [1628/4000] Validation [3/4] Loss: 0.31562 focal_loss 0.21838 dice_loss 0.09723 +Epoch [1628/4000] Validation [4/4] Loss: 0.33008 focal_loss 0.18852 dice_loss 0.14156 +Epoch [1628/4000] Validation metric {'Val/mean dice_metric': 0.9698041677474976, 'Val/mean miou_metric': 0.9521608352661133, 'Val/mean f1': 0.971980631351471, 'Val/mean precision': 0.9666587114334106, 'Val/mean recall': 0.9773615598678589, 'Val/mean hd95_metric': 5.837342739105225} +Cheakpoint... +Epoch [1628/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698041677474976, 'Val/mean miou_metric': 0.9521608352661133, 'Val/mean f1': 0.971980631351471, 'Val/mean precision': 0.9666587114334106, 'Val/mean recall': 0.9773615598678589, 'Val/mean hd95_metric': 5.837342739105225} +Epoch [1629/4000] Training [1/16] Loss: 0.00625 +Epoch [1629/4000] Training [2/16] Loss: 0.01017 +Epoch [1629/4000] Training [3/16] Loss: 0.00784 +Epoch [1629/4000] Training [4/16] Loss: 0.00697 +Epoch [1629/4000] Training [5/16] Loss: 0.00731 +Epoch [1629/4000] Training [6/16] Loss: 0.00803 +Epoch [1629/4000] Training [7/16] Loss: 0.00618 +Epoch [1629/4000] Training [8/16] Loss: 0.00755 +Epoch [1629/4000] Training [9/16] Loss: 0.00741 +Epoch [1629/4000] Training [10/16] Loss: 0.00542 +Epoch [1629/4000] Training [11/16] Loss: 0.00884 +Epoch [1629/4000] Training [12/16] Loss: 0.00825 +Epoch [1629/4000] Training [13/16] Loss: 0.00714 +Epoch [1629/4000] Training [14/16] Loss: 0.00703 +Epoch [1629/4000] Training [15/16] Loss: 0.00795 +Epoch [1629/4000] Training [16/16] Loss: 0.00933 +Epoch [1629/4000] Training metric {'Train/mean dice_metric': 0.9941665530204773, 'Train/mean miou_metric': 0.9884157180786133, 'Train/mean f1': 0.9896767735481262, 'Train/mean precision': 0.984350860118866, 'Train/mean recall': 0.9950606822967529, 'Train/mean hd95_metric': 1.138105034828186} +Epoch [1629/4000] Validation [1/4] Loss: 0.37411 focal_loss 0.28160 dice_loss 0.09251 +Epoch [1629/4000] Validation [2/4] Loss: 0.40935 focal_loss 0.22108 dice_loss 0.18827 +Epoch [1629/4000] Validation [3/4] Loss: 0.23488 focal_loss 0.13933 dice_loss 0.09556 +Epoch [1629/4000] Validation [4/4] Loss: 0.41217 focal_loss 0.25692 dice_loss 0.15525 +Epoch [1629/4000] Validation metric {'Val/mean dice_metric': 0.9669249653816223, 'Val/mean miou_metric': 0.9485626220703125, 'Val/mean f1': 0.9707832932472229, 'Val/mean precision': 0.971442461013794, 'Val/mean recall': 0.9701250791549683, 'Val/mean hd95_metric': 5.9661688804626465} +Cheakpoint... +Epoch [1629/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669249653816223, 'Val/mean miou_metric': 0.9485626220703125, 'Val/mean f1': 0.9707832932472229, 'Val/mean precision': 0.971442461013794, 'Val/mean recall': 0.9701250791549683, 'Val/mean hd95_metric': 5.9661688804626465} +Epoch [1630/4000] Training [1/16] Loss: 0.00604 +Epoch [1630/4000] Training [2/16] Loss: 0.01055 +Epoch [1630/4000] Training [3/16] Loss: 0.00760 +Epoch [1630/4000] Training [4/16] Loss: 0.00632 +Epoch [1630/4000] Training [5/16] Loss: 0.00706 +Epoch [1630/4000] Training [6/16] Loss: 0.00588 +Epoch [1630/4000] Training [7/16] Loss: 0.00769 +Epoch [1630/4000] Training [8/16] Loss: 0.00664 +Epoch [1630/4000] Training [9/16] Loss: 0.00749 +Epoch [1630/4000] Training [10/16] Loss: 0.00663 +Epoch [1630/4000] Training [11/16] Loss: 0.00683 +Epoch [1630/4000] Training [12/16] Loss: 0.00731 +Epoch [1630/4000] Training [13/16] Loss: 0.00542 +Epoch [1630/4000] Training [14/16] Loss: 0.00911 +Epoch [1630/4000] Training [15/16] Loss: 0.00941 +Epoch [1630/4000] Training [16/16] Loss: 0.00817 +Epoch [1630/4000] Training metric {'Train/mean dice_metric': 0.9948427081108093, 'Train/mean miou_metric': 0.9894894361495972, 'Train/mean f1': 0.9906690716743469, 'Train/mean precision': 0.9860169887542725, 'Train/mean recall': 0.9953652024269104, 'Train/mean hd95_metric': 1.1887718439102173} +Epoch [1630/4000] Validation [1/4] Loss: 0.43232 focal_loss 0.32572 dice_loss 0.10660 +Epoch [1630/4000] Validation [2/4] Loss: 0.51641 focal_loss 0.32219 dice_loss 0.19422 +Epoch [1630/4000] Validation [3/4] Loss: 0.16078 focal_loss 0.09487 dice_loss 0.06591 +Epoch [1630/4000] Validation [4/4] Loss: 0.25283 focal_loss 0.14428 dice_loss 0.10855 +Epoch [1630/4000] Validation metric {'Val/mean dice_metric': 0.9681393504142761, 'Val/mean miou_metric': 0.9509576559066772, 'Val/mean f1': 0.9711394309997559, 'Val/mean precision': 0.9718459248542786, 'Val/mean recall': 0.9704340100288391, 'Val/mean hd95_metric': 5.384294033050537} +Cheakpoint... +Epoch [1630/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681393504142761, 'Val/mean miou_metric': 0.9509576559066772, 'Val/mean f1': 0.9711394309997559, 'Val/mean precision': 0.9718459248542786, 'Val/mean recall': 0.9704340100288391, 'Val/mean hd95_metric': 5.384294033050537} +Epoch [1631/4000] Training [1/16] Loss: 0.00686 +Epoch [1631/4000] Training [2/16] Loss: 0.00885 +Epoch [1631/4000] Training [3/16] Loss: 0.00730 +Epoch [1631/4000] Training [4/16] Loss: 0.00740 +Epoch [1631/4000] Training [5/16] Loss: 0.00752 +Epoch [1631/4000] Training [6/16] Loss: 0.00555 +Epoch [1631/4000] Training [7/16] Loss: 0.00994 +Epoch [1631/4000] Training [8/16] Loss: 0.00796 +Epoch [1631/4000] Training [9/16] Loss: 0.00684 +Epoch [1631/4000] Training [10/16] Loss: 0.00667 +Epoch [1631/4000] Training [11/16] Loss: 0.00972 +Epoch [1631/4000] Training [12/16] Loss: 0.00623 +Epoch [1631/4000] Training [13/16] Loss: 0.00684 +Epoch [1631/4000] Training [14/16] Loss: 0.00731 +Epoch [1631/4000] Training [15/16] Loss: 0.00665 +Epoch [1631/4000] Training [16/16] Loss: 0.00705 +Epoch [1631/4000] Training metric {'Train/mean dice_metric': 0.9948979020118713, 'Train/mean miou_metric': 0.9895721673965454, 'Train/mean f1': 0.990152895450592, 'Train/mean precision': 0.9850011467933655, 'Train/mean recall': 0.9953588247299194, 'Train/mean hd95_metric': 1.4885437488555908} +Epoch [1631/4000] Validation [1/4] Loss: 0.72068 focal_loss 0.56041 dice_loss 0.16026 +Epoch [1631/4000] Validation [2/4] Loss: 0.60059 focal_loss 0.40225 dice_loss 0.19834 +Epoch [1631/4000] Validation [3/4] Loss: 0.16026 focal_loss 0.09292 dice_loss 0.06734 +Epoch [1631/4000] Validation [4/4] Loss: 0.22874 focal_loss 0.12287 dice_loss 0.10586 +Epoch [1631/4000] Validation metric {'Val/mean dice_metric': 0.9674798846244812, 'Val/mean miou_metric': 0.949925422668457, 'Val/mean f1': 0.969626784324646, 'Val/mean precision': 0.9723281264305115, 'Val/mean recall': 0.9669404625892639, 'Val/mean hd95_metric': 6.06492280960083} +Cheakpoint... +Epoch [1631/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674798846244812, 'Val/mean miou_metric': 0.949925422668457, 'Val/mean f1': 0.969626784324646, 'Val/mean precision': 0.9723281264305115, 'Val/mean recall': 0.9669404625892639, 'Val/mean hd95_metric': 6.06492280960083} +Epoch [1632/4000] Training [1/16] Loss: 0.00588 +Epoch [1632/4000] Training [2/16] Loss: 0.00687 +Epoch [1632/4000] Training [3/16] Loss: 0.00700 +Epoch [1632/4000] Training [4/16] Loss: 0.00816 +Epoch [1632/4000] Training [5/16] Loss: 0.00623 +Epoch [1632/4000] Training [6/16] Loss: 0.00802 +Epoch [1632/4000] Training [7/16] Loss: 0.00743 +Epoch [1632/4000] Training [8/16] Loss: 0.00709 +Epoch [1632/4000] Training [9/16] Loss: 0.01130 +Epoch [1632/4000] Training [10/16] Loss: 0.01057 +Epoch [1632/4000] Training [11/16] Loss: 0.00984 +Epoch [1632/4000] Training [12/16] Loss: 0.00659 +Epoch [1632/4000] Training [13/16] Loss: 0.01125 +Epoch [1632/4000] Training [14/16] Loss: 0.00698 +Epoch [1632/4000] Training [15/16] Loss: 0.00580 +Epoch [1632/4000] Training [16/16] Loss: 0.00706 +Epoch [1632/4000] Training metric {'Train/mean dice_metric': 0.9945587515830994, 'Train/mean miou_metric': 0.9889779090881348, 'Train/mean f1': 0.9906235337257385, 'Train/mean precision': 0.986112117767334, 'Train/mean recall': 0.9951763153076172, 'Train/mean hd95_metric': 1.0917580127716064} +Epoch [1632/4000] Validation [1/4] Loss: 0.52850 focal_loss 0.40040 dice_loss 0.12810 +Epoch [1632/4000] Validation [2/4] Loss: 0.54671 focal_loss 0.35520 dice_loss 0.19151 +Epoch [1632/4000] Validation [3/4] Loss: 0.26601 focal_loss 0.16943 dice_loss 0.09658 +Epoch [1632/4000] Validation [4/4] Loss: 0.41695 focal_loss 0.26459 dice_loss 0.15236 +Epoch [1632/4000] Validation metric {'Val/mean dice_metric': 0.9675667881965637, 'Val/mean miou_metric': 0.9495565295219421, 'Val/mean f1': 0.9703381061553955, 'Val/mean precision': 0.9721988439559937, 'Val/mean recall': 0.9684844613075256, 'Val/mean hd95_metric': 6.2864484786987305} +Cheakpoint... +Epoch [1632/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675667881965637, 'Val/mean miou_metric': 0.9495565295219421, 'Val/mean f1': 0.9703381061553955, 'Val/mean precision': 0.9721988439559937, 'Val/mean recall': 0.9684844613075256, 'Val/mean hd95_metric': 6.2864484786987305} +Epoch [1633/4000] Training [1/16] Loss: 0.00700 +Epoch [1633/4000] Training [2/16] Loss: 0.00568 +Epoch [1633/4000] Training [3/16] Loss: 0.00644 +Epoch [1633/4000] Training [4/16] Loss: 0.00849 +Epoch [1633/4000] Training [5/16] Loss: 0.01077 +Epoch [1633/4000] Training [6/16] Loss: 0.00712 +Epoch [1633/4000] Training [7/16] Loss: 0.01804 +Epoch [1633/4000] Training [8/16] Loss: 0.00803 +Epoch [1633/4000] Training [9/16] Loss: 0.00716 +Epoch [1633/4000] Training [10/16] Loss: 0.00759 +Epoch [1633/4000] Training [11/16] Loss: 0.00830 +Epoch [1633/4000] Training [12/16] Loss: 0.00633 +Epoch [1633/4000] Training [13/16] Loss: 0.01023 +Epoch [1633/4000] Training [14/16] Loss: 0.00639 +Epoch [1633/4000] Training [15/16] Loss: 0.00751 +Epoch [1633/4000] Training [16/16] Loss: 0.00903 +Epoch [1633/4000] Training metric {'Train/mean dice_metric': 0.9947091341018677, 'Train/mean miou_metric': 0.9892011880874634, 'Train/mean f1': 0.9905452132225037, 'Train/mean precision': 0.985893964767456, 'Train/mean recall': 0.9952406287193298, 'Train/mean hd95_metric': 1.1389557123184204} +Epoch [1633/4000] Validation [1/4] Loss: 0.31929 focal_loss 0.22844 dice_loss 0.09085 +Epoch [1633/4000] Validation [2/4] Loss: 0.37736 focal_loss 0.22984 dice_loss 0.14751 +Epoch [1633/4000] Validation [3/4] Loss: 0.26166 focal_loss 0.16399 dice_loss 0.09768 +Epoch [1633/4000] Validation [4/4] Loss: 0.27452 focal_loss 0.16811 dice_loss 0.10642 +Epoch [1633/4000] Validation metric {'Val/mean dice_metric': 0.970609188079834, 'Val/mean miou_metric': 0.9523838758468628, 'Val/mean f1': 0.9725137948989868, 'Val/mean precision': 0.968879759311676, 'Val/mean recall': 0.9761751890182495, 'Val/mean hd95_metric': 6.453481197357178} +Cheakpoint... +Epoch [1633/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970609188079834, 'Val/mean miou_metric': 0.9523838758468628, 'Val/mean f1': 0.9725137948989868, 'Val/mean precision': 0.968879759311676, 'Val/mean recall': 0.9761751890182495, 'Val/mean hd95_metric': 6.453481197357178} +Epoch [1634/4000] Training [1/16] Loss: 0.00730 +Epoch [1634/4000] Training [2/16] Loss: 0.00709 +Epoch [1634/4000] Training [3/16] Loss: 0.01024 +Epoch [1634/4000] Training [4/16] Loss: 0.00583 +Epoch [1634/4000] Training [5/16] Loss: 0.00880 +Epoch [1634/4000] Training [6/16] Loss: 0.00790 +Epoch [1634/4000] Training [7/16] Loss: 0.00836 +Epoch [1634/4000] Training [8/16] Loss: 0.00829 +Epoch [1634/4000] Training [9/16] Loss: 0.00666 +Epoch [1634/4000] Training [10/16] Loss: 0.00850 +Epoch [1634/4000] Training [11/16] Loss: 0.00636 +Epoch [1634/4000] Training [12/16] Loss: 0.00624 +Epoch [1634/4000] Training [13/16] Loss: 0.00824 +Epoch [1634/4000] Training [14/16] Loss: 0.00853 +Epoch [1634/4000] Training [15/16] Loss: 0.00922 +Epoch [1634/4000] Training [16/16] Loss: 0.00896 +Epoch [1634/4000] Training metric {'Train/mean dice_metric': 0.9945245981216431, 'Train/mean miou_metric': 0.988862156867981, 'Train/mean f1': 0.9905500411987305, 'Train/mean precision': 0.9861043691635132, 'Train/mean recall': 0.9950360655784607, 'Train/mean hd95_metric': 1.0711016654968262} +Epoch [1634/4000] Validation [1/4] Loss: 0.39832 focal_loss 0.29187 dice_loss 0.10645 +Epoch [1634/4000] Validation [2/4] Loss: 0.27676 focal_loss 0.15350 dice_loss 0.12326 +Epoch [1634/4000] Validation [3/4] Loss: 0.31615 focal_loss 0.21379 dice_loss 0.10236 +Epoch [1634/4000] Validation [4/4] Loss: 0.27650 focal_loss 0.16594 dice_loss 0.11056 +Epoch [1634/4000] Validation metric {'Val/mean dice_metric': 0.969329833984375, 'Val/mean miou_metric': 0.9507061839103699, 'Val/mean f1': 0.9718801975250244, 'Val/mean precision': 0.9709336757659912, 'Val/mean recall': 0.9728286266326904, 'Val/mean hd95_metric': 6.3153462409973145} +Cheakpoint... +Epoch [1634/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969329833984375, 'Val/mean miou_metric': 0.9507061839103699, 'Val/mean f1': 0.9718801975250244, 'Val/mean precision': 0.9709336757659912, 'Val/mean recall': 0.9728286266326904, 'Val/mean hd95_metric': 6.3153462409973145} +Epoch [1635/4000] Training [1/16] Loss: 0.01110 +Epoch [1635/4000] Training [2/16] Loss: 0.00850 +Epoch [1635/4000] Training [3/16] Loss: 0.00577 +Epoch [1635/4000] Training [4/16] Loss: 0.00720 +Epoch [1635/4000] Training [5/16] Loss: 0.00617 +Epoch [1635/4000] Training [6/16] Loss: 0.00701 +Epoch [1635/4000] Training [7/16] Loss: 0.00701 +Epoch [1635/4000] Training [8/16] Loss: 0.00656 +Epoch [1635/4000] Training [9/16] Loss: 0.00882 +Epoch [1635/4000] Training [10/16] Loss: 0.00833 +Epoch [1635/4000] Training [11/16] Loss: 0.01131 +Epoch [1635/4000] Training [12/16] Loss: 0.00756 +Epoch [1635/4000] Training [13/16] Loss: 0.00783 +Epoch [1635/4000] Training [14/16] Loss: 0.00530 +Epoch [1635/4000] Training [15/16] Loss: 0.00722 +Epoch [1635/4000] Training [16/16] Loss: 0.00614 +Epoch [1635/4000] Training metric {'Train/mean dice_metric': 0.9946893453598022, 'Train/mean miou_metric': 0.9891875386238098, 'Train/mean f1': 0.990790843963623, 'Train/mean precision': 0.986322283744812, 'Train/mean recall': 0.9953000545501709, 'Train/mean hd95_metric': 1.0326504707336426} +Epoch [1635/4000] Validation [1/4] Loss: 0.26445 focal_loss 0.19375 dice_loss 0.07070 +Epoch [1635/4000] Validation [2/4] Loss: 0.38115 focal_loss 0.24574 dice_loss 0.13541 +Epoch [1635/4000] Validation [3/4] Loss: 0.30784 focal_loss 0.20624 dice_loss 0.10160 +Epoch [1635/4000] Validation [4/4] Loss: 0.23150 focal_loss 0.12736 dice_loss 0.10414 +Epoch [1635/4000] Validation metric {'Val/mean dice_metric': 0.9697653651237488, 'Val/mean miou_metric': 0.9518642425537109, 'Val/mean f1': 0.9725964069366455, 'Val/mean precision': 0.9685205817222595, 'Val/mean recall': 0.9767068028450012, 'Val/mean hd95_metric': 6.078498363494873} +Cheakpoint... +Epoch [1635/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697653651237488, 'Val/mean miou_metric': 0.9518642425537109, 'Val/mean f1': 0.9725964069366455, 'Val/mean precision': 0.9685205817222595, 'Val/mean recall': 0.9767068028450012, 'Val/mean hd95_metric': 6.078498363494873} +Epoch [1636/4000] Training [1/16] Loss: 0.00785 +Epoch [1636/4000] Training [2/16] Loss: 0.00861 +Epoch [1636/4000] Training [3/16] Loss: 0.00569 +Epoch [1636/4000] Training [4/16] Loss: 0.01098 +Epoch [1636/4000] Training [5/16] Loss: 0.00845 +Epoch [1636/4000] Training [6/16] Loss: 0.01140 +Epoch [1636/4000] Training [7/16] Loss: 0.01070 +Epoch [1636/4000] Training [8/16] Loss: 0.00657 +Epoch [1636/4000] Training [9/16] Loss: 0.00781 +Epoch [1636/4000] Training [10/16] Loss: 0.00888 +Epoch [1636/4000] Training [11/16] Loss: 0.00742 +Epoch [1636/4000] Training [12/16] Loss: 0.00750 +Epoch [1636/4000] Training [13/16] Loss: 0.00688 +Epoch [1636/4000] Training [14/16] Loss: 0.00817 +Epoch [1636/4000] Training [15/16] Loss: 0.01222 +Epoch [1636/4000] Training [16/16] Loss: 0.00678 +Epoch [1636/4000] Training metric {'Train/mean dice_metric': 0.9942102432250977, 'Train/mean miou_metric': 0.988194465637207, 'Train/mean f1': 0.989232063293457, 'Train/mean precision': 0.983565092086792, 'Train/mean recall': 0.9949647784233093, 'Train/mean hd95_metric': 1.0630507469177246} +Epoch [1636/4000] Validation [1/4] Loss: 0.29849 focal_loss 0.21691 dice_loss 0.08158 +Epoch [1636/4000] Validation [2/4] Loss: 0.35964 focal_loss 0.21375 dice_loss 0.14589 +Epoch [1636/4000] Validation [3/4] Loss: 0.27717 focal_loss 0.17732 dice_loss 0.09984 +Epoch [1636/4000] Validation [4/4] Loss: 0.27692 focal_loss 0.15962 dice_loss 0.11729 +Epoch [1636/4000] Validation metric {'Val/mean dice_metric': 0.9696030616760254, 'Val/mean miou_metric': 0.9511796236038208, 'Val/mean f1': 0.9703298807144165, 'Val/mean precision': 0.9667148590087891, 'Val/mean recall': 0.9739721417427063, 'Val/mean hd95_metric': 6.201016426086426} +Cheakpoint... +Epoch [1636/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696030616760254, 'Val/mean miou_metric': 0.9511796236038208, 'Val/mean f1': 0.9703298807144165, 'Val/mean precision': 0.9667148590087891, 'Val/mean recall': 0.9739721417427063, 'Val/mean hd95_metric': 6.201016426086426} +Epoch [1637/4000] Training [1/16] Loss: 0.00664 +Epoch [1637/4000] Training [2/16] Loss: 0.00648 +Epoch [1637/4000] Training [3/16] Loss: 0.00731 +Epoch [1637/4000] Training [4/16] Loss: 0.00663 +Epoch [1637/4000] Training [5/16] Loss: 0.00885 +Epoch [1637/4000] Training [6/16] Loss: 0.00830 +Epoch [1637/4000] Training [7/16] Loss: 0.00653 +Epoch [1637/4000] Training [8/16] Loss: 0.00851 +Epoch [1637/4000] Training [9/16] Loss: 0.00596 +Epoch [1637/4000] Training [10/16] Loss: 0.00655 +Epoch [1637/4000] Training [11/16] Loss: 0.00715 +Epoch [1637/4000] Training [12/16] Loss: 0.00568 +Epoch [1637/4000] Training [13/16] Loss: 0.00673 +Epoch [1637/4000] Training [14/16] Loss: 0.00687 +Epoch [1637/4000] Training [15/16] Loss: 0.00591 +Epoch [1637/4000] Training [16/16] Loss: 0.00728 +Epoch [1637/4000] Training metric {'Train/mean dice_metric': 0.9952352643013, 'Train/mean miou_metric': 0.9902390837669373, 'Train/mean f1': 0.9908421039581299, 'Train/mean precision': 0.986045777797699, 'Train/mean recall': 0.9956855177879333, 'Train/mean hd95_metric': 1.015554666519165} +Epoch [1637/4000] Validation [1/4] Loss: 0.28124 focal_loss 0.21296 dice_loss 0.06827 +Epoch [1637/4000] Validation [2/4] Loss: 0.44286 focal_loss 0.27743 dice_loss 0.16544 +Epoch [1637/4000] Validation [3/4] Loss: 0.29585 focal_loss 0.19618 dice_loss 0.09967 +Epoch [1637/4000] Validation [4/4] Loss: 0.37050 focal_loss 0.22752 dice_loss 0.14299 +Epoch [1637/4000] Validation metric {'Val/mean dice_metric': 0.9735067486763, 'Val/mean miou_metric': 0.9556633234024048, 'Val/mean f1': 0.9741361141204834, 'Val/mean precision': 0.9712074995040894, 'Val/mean recall': 0.977082371711731, 'Val/mean hd95_metric': 5.419098854064941} +Cheakpoint... +Epoch [1637/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735067486763, 'Val/mean miou_metric': 0.9556633234024048, 'Val/mean f1': 0.9741361141204834, 'Val/mean precision': 0.9712074995040894, 'Val/mean recall': 0.977082371711731, 'Val/mean hd95_metric': 5.419098854064941} +Epoch [1638/4000] Training [1/16] Loss: 0.00641 +Epoch [1638/4000] Training [2/16] Loss: 0.00683 +Epoch [1638/4000] Training [3/16] Loss: 0.00660 +Epoch [1638/4000] Training [4/16] Loss: 0.00568 +Epoch [1638/4000] Training [5/16] Loss: 0.00609 +Epoch [1638/4000] Training [6/16] Loss: 0.00765 +Epoch [1638/4000] Training [7/16] Loss: 0.00874 +Epoch [1638/4000] Training [8/16] Loss: 0.00719 +Epoch [1638/4000] Training [9/16] Loss: 0.00738 +Epoch [1638/4000] Training [10/16] Loss: 0.00593 +Epoch [1638/4000] Training [11/16] Loss: 0.01030 +Epoch [1638/4000] Training [12/16] Loss: 0.00813 +Epoch [1638/4000] Training [13/16] Loss: 0.00670 +Epoch [1638/4000] Training [14/16] Loss: 0.00561 +Epoch [1638/4000] Training [15/16] Loss: 0.00734 +Epoch [1638/4000] Training [16/16] Loss: 0.00731 +Epoch [1638/4000] Training metric {'Train/mean dice_metric': 0.9952725768089294, 'Train/mean miou_metric': 0.9903115034103394, 'Train/mean f1': 0.9908687472343445, 'Train/mean precision': 0.9860569834709167, 'Train/mean recall': 0.9957277774810791, 'Train/mean hd95_metric': 1.2214906215667725} +Epoch [1638/4000] Validation [1/4] Loss: 0.38474 focal_loss 0.28531 dice_loss 0.09943 +Epoch [1638/4000] Validation [2/4] Loss: 0.22208 focal_loss 0.12142 dice_loss 0.10066 +Epoch [1638/4000] Validation [3/4] Loss: 0.30431 focal_loss 0.19452 dice_loss 0.10979 +Epoch [1638/4000] Validation [4/4] Loss: 0.35277 focal_loss 0.23001 dice_loss 0.12277 +Epoch [1638/4000] Validation metric {'Val/mean dice_metric': 0.971523642539978, 'Val/mean miou_metric': 0.9539926648139954, 'Val/mean f1': 0.972707986831665, 'Val/mean precision': 0.9693931937217712, 'Val/mean recall': 0.9760456681251526, 'Val/mean hd95_metric': 5.940107345581055} +Cheakpoint... +Epoch [1638/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971523642539978, 'Val/mean miou_metric': 0.9539926648139954, 'Val/mean f1': 0.972707986831665, 'Val/mean precision': 0.9693931937217712, 'Val/mean recall': 0.9760456681251526, 'Val/mean hd95_metric': 5.940107345581055} +Epoch [1639/4000] Training [1/16] Loss: 0.00741 +Epoch [1639/4000] Training [2/16] Loss: 0.00746 +Epoch [1639/4000] Training [3/16] Loss: 0.00908 +Epoch [1639/4000] Training [4/16] Loss: 0.00710 +Epoch [1639/4000] Training [5/16] Loss: 0.01022 +Epoch [1639/4000] Training [6/16] Loss: 0.00678 +Epoch [1639/4000] Training [7/16] Loss: 0.00765 +Epoch [1639/4000] Training [8/16] Loss: 0.00573 +Epoch [1639/4000] Training [9/16] Loss: 0.00711 +Epoch [1639/4000] Training [10/16] Loss: 0.00918 +Epoch [1639/4000] Training [11/16] Loss: 0.00836 +Epoch [1639/4000] Training [12/16] Loss: 0.01039 +Epoch [1639/4000] Training [13/16] Loss: 0.00949 +Epoch [1639/4000] Training [14/16] Loss: 0.01015 +Epoch [1639/4000] Training [15/16] Loss: 0.00627 +Epoch [1639/4000] Training [16/16] Loss: 0.00966 +Epoch [1639/4000] Training metric {'Train/mean dice_metric': 0.9942116141319275, 'Train/mean miou_metric': 0.9882515072822571, 'Train/mean f1': 0.9901334047317505, 'Train/mean precision': 0.9853185415267944, 'Train/mean recall': 0.9949955940246582, 'Train/mean hd95_metric': 1.090976595878601} +Epoch [1639/4000] Validation [1/4] Loss: 0.24776 focal_loss 0.18422 dice_loss 0.06354 +Epoch [1639/4000] Validation [2/4] Loss: 0.22676 focal_loss 0.13276 dice_loss 0.09400 +Epoch [1639/4000] Validation [3/4] Loss: 0.17345 focal_loss 0.10909 dice_loss 0.06436 +Epoch [1639/4000] Validation [4/4] Loss: 0.27894 focal_loss 0.16601 dice_loss 0.11293 +Epoch [1639/4000] Validation metric {'Val/mean dice_metric': 0.9719030261039734, 'Val/mean miou_metric': 0.9539042711257935, 'Val/mean f1': 0.9736737608909607, 'Val/mean precision': 0.9680574536323547, 'Val/mean recall': 0.9793555736541748, 'Val/mean hd95_metric': 5.8775482177734375} +Cheakpoint... +Epoch [1639/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719030261039734, 'Val/mean miou_metric': 0.9539042711257935, 'Val/mean f1': 0.9736737608909607, 'Val/mean precision': 0.9680574536323547, 'Val/mean recall': 0.9793555736541748, 'Val/mean hd95_metric': 5.8775482177734375} +Epoch [1640/4000] Training [1/16] Loss: 0.00796 +Epoch [1640/4000] Training [2/16] Loss: 0.00688 +Epoch [1640/4000] Training [3/16] Loss: 0.00619 +Epoch [1640/4000] Training [4/16] Loss: 0.00828 +Epoch [1640/4000] Training [5/16] Loss: 0.00648 +Epoch [1640/4000] Training [6/16] Loss: 0.00731 +Epoch [1640/4000] Training [7/16] Loss: 0.00854 +Epoch [1640/4000] Training [8/16] Loss: 0.00795 +Epoch [1640/4000] Training [9/16] Loss: 0.00822 +Epoch [1640/4000] Training [10/16] Loss: 0.00929 +Epoch [1640/4000] Training [11/16] Loss: 0.00870 +Epoch [1640/4000] Training [12/16] Loss: 0.00745 +Epoch [1640/4000] Training [13/16] Loss: 0.01002 +Epoch [1640/4000] Training [14/16] Loss: 0.00959 +Epoch [1640/4000] Training [15/16] Loss: 0.00763 +Epoch [1640/4000] Training [16/16] Loss: 0.00655 +Epoch [1640/4000] Training metric {'Train/mean dice_metric': 0.9948293566703796, 'Train/mean miou_metric': 0.9894279837608337, 'Train/mean f1': 0.9900235533714294, 'Train/mean precision': 0.9850279688835144, 'Train/mean recall': 0.9950700402259827, 'Train/mean hd95_metric': 1.0307176113128662} +Epoch [1640/4000] Validation [1/4] Loss: 0.34558 focal_loss 0.25183 dice_loss 0.09375 +Epoch [1640/4000] Validation [2/4] Loss: 0.40888 focal_loss 0.23454 dice_loss 0.17434 +Epoch [1640/4000] Validation [3/4] Loss: 0.24163 focal_loss 0.14950 dice_loss 0.09213 +Epoch [1640/4000] Validation [4/4] Loss: 0.30435 focal_loss 0.17813 dice_loss 0.12622 +Epoch [1640/4000] Validation metric {'Val/mean dice_metric': 0.9697380065917969, 'Val/mean miou_metric': 0.9516439437866211, 'Val/mean f1': 0.9713032841682434, 'Val/mean precision': 0.9683358073234558, 'Val/mean recall': 0.974289059638977, 'Val/mean hd95_metric': 6.0016374588012695} +Cheakpoint... +Epoch [1640/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697380065917969, 'Val/mean miou_metric': 0.9516439437866211, 'Val/mean f1': 0.9713032841682434, 'Val/mean precision': 0.9683358073234558, 'Val/mean recall': 0.974289059638977, 'Val/mean hd95_metric': 6.0016374588012695} +Epoch [1641/4000] Training [1/16] Loss: 0.00715 +Epoch [1641/4000] Training [2/16] Loss: 0.01083 +Epoch [1641/4000] Training [3/16] Loss: 0.00957 +Epoch [1641/4000] Training [4/16] Loss: 0.00719 +Epoch [1641/4000] Training [5/16] Loss: 0.00649 +Epoch [1641/4000] Training [6/16] Loss: 0.00887 +Epoch [1641/4000] Training [7/16] Loss: 0.00924 +Epoch [1641/4000] Training [8/16] Loss: 0.00694 +Epoch [1641/4000] Training [9/16] Loss: 0.00757 +Epoch [1641/4000] Training [10/16] Loss: 0.00564 +Epoch [1641/4000] Training [11/16] Loss: 0.00960 +Epoch [1641/4000] Training [12/16] Loss: 0.00789 +Epoch [1641/4000] Training [13/16] Loss: 0.00937 +Epoch [1641/4000] Training [14/16] Loss: 0.00813 +Epoch [1641/4000] Training [15/16] Loss: 0.00641 +Epoch [1641/4000] Training [16/16] Loss: 0.00659 +Epoch [1641/4000] Training metric {'Train/mean dice_metric': 0.9948171973228455, 'Train/mean miou_metric': 0.9894391298294067, 'Train/mean f1': 0.9908923506736755, 'Train/mean precision': 0.9863445162773132, 'Train/mean recall': 0.9954823851585388, 'Train/mean hd95_metric': 1.048703908920288} +Epoch [1641/4000] Validation [1/4] Loss: 0.21906 focal_loss 0.15505 dice_loss 0.06401 +Epoch [1641/4000] Validation [2/4] Loss: 0.14887 focal_loss 0.07683 dice_loss 0.07204 +Epoch [1641/4000] Validation [3/4] Loss: 0.17855 focal_loss 0.11057 dice_loss 0.06798 +Epoch [1641/4000] Validation [4/4] Loss: 0.29477 focal_loss 0.17276 dice_loss 0.12201 +Epoch [1641/4000] Validation metric {'Val/mean dice_metric': 0.9715679287910461, 'Val/mean miou_metric': 0.9545699954032898, 'Val/mean f1': 0.9744617342948914, 'Val/mean precision': 0.9703002572059631, 'Val/mean recall': 0.9786590337753296, 'Val/mean hd95_metric': 5.5062785148620605} +Cheakpoint... +Epoch [1641/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715679287910461, 'Val/mean miou_metric': 0.9545699954032898, 'Val/mean f1': 0.9744617342948914, 'Val/mean precision': 0.9703002572059631, 'Val/mean recall': 0.9786590337753296, 'Val/mean hd95_metric': 5.5062785148620605} +Epoch [1642/4000] Training [1/16] Loss: 0.00759 +Epoch [1642/4000] Training [2/16] Loss: 0.00547 +Epoch [1642/4000] Training [3/16] Loss: 0.00573 +Epoch [1642/4000] Training [4/16] Loss: 0.01128 +Epoch [1642/4000] Training [5/16] Loss: 0.00601 +Epoch [1642/4000] Training [6/16] Loss: 0.00681 +Epoch [1642/4000] Training [7/16] Loss: 0.00734 +Epoch [1642/4000] Training [8/16] Loss: 0.00679 +Epoch [1642/4000] Training [9/16] Loss: 0.01303 +Epoch [1642/4000] Training [10/16] Loss: 0.00890 +Epoch [1642/4000] Training [11/16] Loss: 0.00586 +Epoch [1642/4000] Training [12/16] Loss: 0.00576 +Epoch [1642/4000] Training [13/16] Loss: 0.00758 +Epoch [1642/4000] Training [14/16] Loss: 0.00683 +Epoch [1642/4000] Training [15/16] Loss: 0.00747 +Epoch [1642/4000] Training [16/16] Loss: 0.01108 +Epoch [1642/4000] Training metric {'Train/mean dice_metric': 0.9946644306182861, 'Train/mean miou_metric': 0.989179253578186, 'Train/mean f1': 0.9898906350135803, 'Train/mean precision': 0.9846546053886414, 'Train/mean recall': 0.9951826333999634, 'Train/mean hd95_metric': 1.1865806579589844} +Epoch [1642/4000] Validation [1/4] Loss: 0.25954 focal_loss 0.18694 dice_loss 0.07259 +Epoch [1642/4000] Validation [2/4] Loss: 0.52277 focal_loss 0.31397 dice_loss 0.20880 +Epoch [1642/4000] Validation [3/4] Loss: 0.25103 focal_loss 0.16577 dice_loss 0.08526 +Epoch [1642/4000] Validation [4/4] Loss: 0.32199 focal_loss 0.19413 dice_loss 0.12786 +Epoch [1642/4000] Validation metric {'Val/mean dice_metric': 0.9696375727653503, 'Val/mean miou_metric': 0.9516106843948364, 'Val/mean f1': 0.9717068076133728, 'Val/mean precision': 0.9681284427642822, 'Val/mean recall': 0.9753117561340332, 'Val/mean hd95_metric': 6.636775493621826} +Cheakpoint... +Epoch [1642/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696375727653503, 'Val/mean miou_metric': 0.9516106843948364, 'Val/mean f1': 0.9717068076133728, 'Val/mean precision': 0.9681284427642822, 'Val/mean recall': 0.9753117561340332, 'Val/mean hd95_metric': 6.636775493621826} +Epoch [1643/4000] Training [1/16] Loss: 0.00734 +Epoch [1643/4000] Training [2/16] Loss: 0.00598 +Epoch [1643/4000] Training [3/16] Loss: 0.00596 +Epoch [1643/4000] Training [4/16] Loss: 0.00689 +Epoch [1643/4000] Training [5/16] Loss: 0.00694 +Epoch [1643/4000] Training [6/16] Loss: 0.00890 +Epoch [1643/4000] Training [7/16] Loss: 0.00901 +Epoch [1643/4000] Training [8/16] Loss: 0.00796 +Epoch [1643/4000] Training [9/16] Loss: 0.00878 +Epoch [1643/4000] Training [10/16] Loss: 0.00683 +Epoch [1643/4000] Training [11/16] Loss: 0.00857 +Epoch [1643/4000] Training [12/16] Loss: 0.00918 +Epoch [1643/4000] Training [13/16] Loss: 0.00657 +Epoch [1643/4000] Training [14/16] Loss: 0.00623 +Epoch [1643/4000] Training [15/16] Loss: 0.00753 +Epoch [1643/4000] Training [16/16] Loss: 0.00817 +Epoch [1643/4000] Training metric {'Train/mean dice_metric': 0.9950358867645264, 'Train/mean miou_metric': 0.989855170249939, 'Train/mean f1': 0.9908880591392517, 'Train/mean precision': 0.986327052116394, 'Train/mean recall': 0.9954913258552551, 'Train/mean hd95_metric': 1.2084195613861084} +Epoch [1643/4000] Validation [1/4] Loss: 0.26272 focal_loss 0.19293 dice_loss 0.06979 +Epoch [1643/4000] Validation [2/4] Loss: 0.24467 focal_loss 0.14399 dice_loss 0.10068 +Epoch [1643/4000] Validation [3/4] Loss: 0.16867 focal_loss 0.10551 dice_loss 0.06316 +Epoch [1643/4000] Validation [4/4] Loss: 0.26904 focal_loss 0.14714 dice_loss 0.12189 +Epoch [1643/4000] Validation metric {'Val/mean dice_metric': 0.9729833602905273, 'Val/mean miou_metric': 0.9559341669082642, 'Val/mean f1': 0.9738942980766296, 'Val/mean precision': 0.9694468379020691, 'Val/mean recall': 0.9783827066421509, 'Val/mean hd95_metric': 6.2238311767578125} +Cheakpoint... +Epoch [1643/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729833602905273, 'Val/mean miou_metric': 0.9559341669082642, 'Val/mean f1': 0.9738942980766296, 'Val/mean precision': 0.9694468379020691, 'Val/mean recall': 0.9783827066421509, 'Val/mean hd95_metric': 6.2238311767578125} +Epoch [1644/4000] Training [1/16] Loss: 0.00661 +Epoch [1644/4000] Training [2/16] Loss: 0.00986 +Epoch [1644/4000] Training [3/16] Loss: 0.00653 +Epoch [1644/4000] Training [4/16] Loss: 0.01369 +Epoch [1644/4000] Training [5/16] Loss: 0.00804 +Epoch [1644/4000] Training [6/16] Loss: 0.00720 +Epoch [1644/4000] Training [7/16] Loss: 0.00836 +Epoch [1644/4000] Training [8/16] Loss: 0.00604 +Epoch [1644/4000] Training [9/16] Loss: 0.00568 +Epoch [1644/4000] Training [10/16] Loss: 0.00811 +Epoch [1644/4000] Training [11/16] Loss: 0.00728 +Epoch [1644/4000] Training [12/16] Loss: 0.00684 +Epoch [1644/4000] Training [13/16] Loss: 0.00925 +Epoch [1644/4000] Training [14/16] Loss: 0.00631 +Epoch [1644/4000] Training [15/16] Loss: 0.00640 +Epoch [1644/4000] Training [16/16] Loss: 0.00648 +Epoch [1644/4000] Training metric {'Train/mean dice_metric': 0.9948395490646362, 'Train/mean miou_metric': 0.9894963502883911, 'Train/mean f1': 0.9908938407897949, 'Train/mean precision': 0.9864110946655273, 'Train/mean recall': 0.9954175353050232, 'Train/mean hd95_metric': 1.0651633739471436} +Epoch [1644/4000] Validation [1/4] Loss: 0.25469 focal_loss 0.18878 dice_loss 0.06590 +Epoch [1644/4000] Validation [2/4] Loss: 0.21054 focal_loss 0.11680 dice_loss 0.09374 +Epoch [1644/4000] Validation [3/4] Loss: 0.19538 focal_loss 0.11502 dice_loss 0.08036 +Epoch [1644/4000] Validation [4/4] Loss: 0.25802 focal_loss 0.14657 dice_loss 0.11145 +Epoch [1644/4000] Validation metric {'Val/mean dice_metric': 0.9705173373222351, 'Val/mean miou_metric': 0.9533414840698242, 'Val/mean f1': 0.972864031791687, 'Val/mean precision': 0.9678612351417542, 'Val/mean recall': 0.9779187440872192, 'Val/mean hd95_metric': 6.486448764801025} +Cheakpoint... +Epoch [1644/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705173373222351, 'Val/mean miou_metric': 0.9533414840698242, 'Val/mean f1': 0.972864031791687, 'Val/mean precision': 0.9678612351417542, 'Val/mean recall': 0.9779187440872192, 'Val/mean hd95_metric': 6.486448764801025} +Epoch [1645/4000] Training [1/16] Loss: 0.00778 +Epoch [1645/4000] Training [2/16] Loss: 0.00649 +Epoch [1645/4000] Training [3/16] Loss: 0.00599 +Epoch [1645/4000] Training [4/16] Loss: 0.01028 +Epoch [1645/4000] Training [5/16] Loss: 0.00716 +Epoch [1645/4000] Training [6/16] Loss: 0.00680 +Epoch [1645/4000] Training [7/16] Loss: 0.00681 +Epoch [1645/4000] Training [8/16] Loss: 0.00893 +Epoch [1645/4000] Training [9/16] Loss: 0.00912 +Epoch [1645/4000] Training [10/16] Loss: 0.00584 +Epoch [1645/4000] Training [11/16] Loss: 0.00766 +Epoch [1645/4000] Training [12/16] Loss: 0.00990 +Epoch [1645/4000] Training [13/16] Loss: 0.00602 +Epoch [1645/4000] Training [14/16] Loss: 0.00799 +Epoch [1645/4000] Training [15/16] Loss: 0.00599 +Epoch [1645/4000] Training [16/16] Loss: 0.00810 +Epoch [1645/4000] Training metric {'Train/mean dice_metric': 0.995042622089386, 'Train/mean miou_metric': 0.9898805022239685, 'Train/mean f1': 0.991097629070282, 'Train/mean precision': 0.9865708351135254, 'Train/mean recall': 0.9956662654876709, 'Train/mean hd95_metric': 1.0164802074432373} +Epoch [1645/4000] Validation [1/4] Loss: 0.32935 focal_loss 0.24610 dice_loss 0.08325 +Epoch [1645/4000] Validation [2/4] Loss: 0.44934 focal_loss 0.26837 dice_loss 0.18097 +Epoch [1645/4000] Validation [3/4] Loss: 0.20837 focal_loss 0.13071 dice_loss 0.07766 +Epoch [1645/4000] Validation [4/4] Loss: 0.24655 focal_loss 0.12962 dice_loss 0.11693 +Epoch [1645/4000] Validation metric {'Val/mean dice_metric': 0.9687650799751282, 'Val/mean miou_metric': 0.9515576362609863, 'Val/mean f1': 0.9722579717636108, 'Val/mean precision': 0.9694918394088745, 'Val/mean recall': 0.9750397801399231, 'Val/mean hd95_metric': 6.558084011077881} +Cheakpoint... +Epoch [1645/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687650799751282, 'Val/mean miou_metric': 0.9515576362609863, 'Val/mean f1': 0.9722579717636108, 'Val/mean precision': 0.9694918394088745, 'Val/mean recall': 0.9750397801399231, 'Val/mean hd95_metric': 6.558084011077881} +Epoch [1646/4000] Training [1/16] Loss: 0.00644 +Epoch [1646/4000] Training [2/16] Loss: 0.00660 +Epoch [1646/4000] Training [3/16] Loss: 0.00687 +Epoch [1646/4000] Training [4/16] Loss: 0.00701 +Epoch [1646/4000] Training [5/16] Loss: 0.00679 +Epoch [1646/4000] Training [6/16] Loss: 0.00662 +Epoch [1646/4000] Training [7/16] Loss: 0.00751 +Epoch [1646/4000] Training [8/16] Loss: 0.00609 +Epoch [1646/4000] Training [9/16] Loss: 0.00711 +Epoch [1646/4000] Training [10/16] Loss: 0.00679 +Epoch [1646/4000] Training [11/16] Loss: 0.00788 +Epoch [1646/4000] Training [12/16] Loss: 0.00675 +Epoch [1646/4000] Training [13/16] Loss: 0.00634 +Epoch [1646/4000] Training [14/16] Loss: 0.00620 +Epoch [1646/4000] Training [15/16] Loss: 0.00646 +Epoch [1646/4000] Training [16/16] Loss: 0.01007 +Epoch [1646/4000] Training metric {'Train/mean dice_metric': 0.9952756762504578, 'Train/mean miou_metric': 0.9903393983840942, 'Train/mean f1': 0.9913765788078308, 'Train/mean precision': 0.9868910312652588, 'Train/mean recall': 0.9959030747413635, 'Train/mean hd95_metric': 1.0178557634353638} +Epoch [1646/4000] Validation [1/4] Loss: 0.27348 focal_loss 0.20022 dice_loss 0.07326 +Epoch [1646/4000] Validation [2/4] Loss: 0.46567 focal_loss 0.30004 dice_loss 0.16563 +Epoch [1646/4000] Validation [3/4] Loss: 0.18549 focal_loss 0.11619 dice_loss 0.06930 +Epoch [1646/4000] Validation [4/4] Loss: 0.25938 focal_loss 0.14278 dice_loss 0.11660 +Epoch [1646/4000] Validation metric {'Val/mean dice_metric': 0.9707955121994019, 'Val/mean miou_metric': 0.953930675983429, 'Val/mean f1': 0.9739760160446167, 'Val/mean precision': 0.9722782373428345, 'Val/mean recall': 0.9756798148155212, 'Val/mean hd95_metric': 5.957736492156982} +Cheakpoint... +Epoch [1646/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707955121994019, 'Val/mean miou_metric': 0.953930675983429, 'Val/mean f1': 0.9739760160446167, 'Val/mean precision': 0.9722782373428345, 'Val/mean recall': 0.9756798148155212, 'Val/mean hd95_metric': 5.957736492156982} +Epoch [1647/4000] Training [1/16] Loss: 0.00777 +Epoch [1647/4000] Training [2/16] Loss: 0.00618 +Epoch [1647/4000] Training [3/16] Loss: 0.01006 +Epoch [1647/4000] Training [4/16] Loss: 0.00596 +Epoch [1647/4000] Training [5/16] Loss: 0.00683 +Epoch [1647/4000] Training [6/16] Loss: 0.00504 +Epoch [1647/4000] Training [7/16] Loss: 0.00759 +Epoch [1647/4000] Training [8/16] Loss: 0.00702 +Epoch [1647/4000] Training [9/16] Loss: 0.00766 +Epoch [1647/4000] Training [10/16] Loss: 0.00556 +Epoch [1647/4000] Training [11/16] Loss: 0.00764 +Epoch [1647/4000] Training [12/16] Loss: 0.00821 +Epoch [1647/4000] Training [13/16] Loss: 0.00781 +Epoch [1647/4000] Training [14/16] Loss: 0.00510 +Epoch [1647/4000] Training [15/16] Loss: 0.01133 +Epoch [1647/4000] Training [16/16] Loss: 0.00670 +Epoch [1647/4000] Training metric {'Train/mean dice_metric': 0.9951486587524414, 'Train/mean miou_metric': 0.9900722503662109, 'Train/mean f1': 0.990927517414093, 'Train/mean precision': 0.9862226247787476, 'Train/mean recall': 0.9956775307655334, 'Train/mean hd95_metric': 1.017981767654419} +Epoch [1647/4000] Validation [1/4] Loss: 0.25537 focal_loss 0.18162 dice_loss 0.07375 +Epoch [1647/4000] Validation [2/4] Loss: 0.77072 focal_loss 0.49306 dice_loss 0.27765 +Epoch [1647/4000] Validation [3/4] Loss: 0.22074 focal_loss 0.13800 dice_loss 0.08275 +Epoch [1647/4000] Validation [4/4] Loss: 0.26188 focal_loss 0.14987 dice_loss 0.11201 +Epoch [1647/4000] Validation metric {'Val/mean dice_metric': 0.9672912359237671, 'Val/mean miou_metric': 0.9506487846374512, 'Val/mean f1': 0.9712701439857483, 'Val/mean precision': 0.9698496460914612, 'Val/mean recall': 0.9726948142051697, 'Val/mean hd95_metric': 6.216526031494141} +Cheakpoint... +Epoch [1647/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672912359237671, 'Val/mean miou_metric': 0.9506487846374512, 'Val/mean f1': 0.9712701439857483, 'Val/mean precision': 0.9698496460914612, 'Val/mean recall': 0.9726948142051697, 'Val/mean hd95_metric': 6.216526031494141} +Epoch [1648/4000] Training [1/16] Loss: 0.00821 +Epoch [1648/4000] Training [2/16] Loss: 0.00667 +Epoch [1648/4000] Training [3/16] Loss: 0.00989 +Epoch [1648/4000] Training [4/16] Loss: 0.00691 +Epoch [1648/4000] Training [5/16] Loss: 0.00717 +Epoch [1648/4000] Training [6/16] Loss: 0.00685 +Epoch [1648/4000] Training [7/16] Loss: 0.00763 +Epoch [1648/4000] Training [8/16] Loss: 0.00719 +Epoch [1648/4000] Training [9/16] Loss: 0.00609 +Epoch [1648/4000] Training [10/16] Loss: 0.00864 +Epoch [1648/4000] Training [11/16] Loss: 0.00797 +Epoch [1648/4000] Training [12/16] Loss: 0.00642 +Epoch [1648/4000] Training [13/16] Loss: 0.00874 +Epoch [1648/4000] Training [14/16] Loss: 0.00715 +Epoch [1648/4000] Training [15/16] Loss: 0.00736 +Epoch [1648/4000] Training [16/16] Loss: 0.00808 +Epoch [1648/4000] Training metric {'Train/mean dice_metric': 0.9948874711990356, 'Train/mean miou_metric': 0.9895960688591003, 'Train/mean f1': 0.9909139275550842, 'Train/mean precision': 0.9863463640213013, 'Train/mean recall': 0.9955240488052368, 'Train/mean hd95_metric': 1.2299258708953857} +Epoch [1648/4000] Validation [1/4] Loss: 0.33067 focal_loss 0.24102 dice_loss 0.08965 +Epoch [1648/4000] Validation [2/4] Loss: 0.51050 focal_loss 0.31703 dice_loss 0.19347 +Epoch [1648/4000] Validation [3/4] Loss: 0.20902 focal_loss 0.12330 dice_loss 0.08572 +Epoch [1648/4000] Validation [4/4] Loss: 0.21131 focal_loss 0.11195 dice_loss 0.09936 +Epoch [1648/4000] Validation metric {'Val/mean dice_metric': 0.968466579914093, 'Val/mean miou_metric': 0.9517858624458313, 'Val/mean f1': 0.9724040031433105, 'Val/mean precision': 0.9736437201499939, 'Val/mean recall': 0.9711674451828003, 'Val/mean hd95_metric': 4.68562126159668} +Cheakpoint... +Epoch [1648/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968466579914093, 'Val/mean miou_metric': 0.9517858624458313, 'Val/mean f1': 0.9724040031433105, 'Val/mean precision': 0.9736437201499939, 'Val/mean recall': 0.9711674451828003, 'Val/mean hd95_metric': 4.68562126159668} +Epoch [1649/4000] Training [1/16] Loss: 0.00735 +Epoch [1649/4000] Training [2/16] Loss: 0.00810 +Epoch [1649/4000] Training [3/16] Loss: 0.00720 +Epoch [1649/4000] Training [4/16] Loss: 0.00657 +Epoch [1649/4000] Training [5/16] Loss: 0.00843 +Epoch [1649/4000] Training [6/16] Loss: 0.00822 +Epoch [1649/4000] Training [7/16] Loss: 0.00944 +Epoch [1649/4000] Training [8/16] Loss: 0.00781 +Epoch [1649/4000] Training [9/16] Loss: 0.01040 +Epoch [1649/4000] Training [10/16] Loss: 0.00703 +Epoch [1649/4000] Training [11/16] Loss: 0.00681 +Epoch [1649/4000] Training [12/16] Loss: 0.00804 +Epoch [1649/4000] Training [13/16] Loss: 0.00634 +Epoch [1649/4000] Training [14/16] Loss: 0.00815 +Epoch [1649/4000] Training [15/16] Loss: 0.00936 +Epoch [1649/4000] Training [16/16] Loss: 0.00697 +Epoch [1649/4000] Training metric {'Train/mean dice_metric': 0.9947956800460815, 'Train/mean miou_metric': 0.9893568754196167, 'Train/mean f1': 0.9900032877922058, 'Train/mean precision': 0.9847770929336548, 'Train/mean recall': 0.995285153388977, 'Train/mean hd95_metric': 1.0194737911224365} +Epoch [1649/4000] Validation [1/4] Loss: 0.28352 focal_loss 0.21205 dice_loss 0.07146 +Epoch [1649/4000] Validation [2/4] Loss: 0.52144 focal_loss 0.33536 dice_loss 0.18608 +Epoch [1649/4000] Validation [3/4] Loss: 0.27616 focal_loss 0.17887 dice_loss 0.09729 +Epoch [1649/4000] Validation [4/4] Loss: 0.22586 focal_loss 0.11719 dice_loss 0.10868 +Epoch [1649/4000] Validation metric {'Val/mean dice_metric': 0.969528079032898, 'Val/mean miou_metric': 0.9527082443237305, 'Val/mean f1': 0.9728233218193054, 'Val/mean precision': 0.9701117277145386, 'Val/mean recall': 0.9755500555038452, 'Val/mean hd95_metric': 5.442274570465088} +Cheakpoint... +Epoch [1649/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969528079032898, 'Val/mean miou_metric': 0.9527082443237305, 'Val/mean f1': 0.9728233218193054, 'Val/mean precision': 0.9701117277145386, 'Val/mean recall': 0.9755500555038452, 'Val/mean hd95_metric': 5.442274570465088} +Epoch [1650/4000] Training [1/16] Loss: 0.00738 +Epoch [1650/4000] Training [2/16] Loss: 0.00587 +Epoch [1650/4000] Training [3/16] Loss: 0.00639 +Epoch [1650/4000] Training [4/16] Loss: 0.00673 +Epoch [1650/4000] Training [5/16] Loss: 0.00678 +Epoch [1650/4000] Training [6/16] Loss: 0.00943 +Epoch [1650/4000] Training [7/16] Loss: 0.00732 +Epoch [1650/4000] Training [8/16] Loss: 0.00798 +Epoch [1650/4000] Training [9/16] Loss: 0.00634 +Epoch [1650/4000] Training [10/16] Loss: 0.00631 +Epoch [1650/4000] Training [11/16] Loss: 0.00858 +Epoch [1650/4000] Training [12/16] Loss: 0.00677 +Epoch [1650/4000] Training [13/16] Loss: 0.00696 +Epoch [1650/4000] Training [14/16] Loss: 0.00814 +Epoch [1650/4000] Training [15/16] Loss: 0.00871 +Epoch [1650/4000] Training [16/16] Loss: 0.00647 +Epoch [1650/4000] Training metric {'Train/mean dice_metric': 0.9951518774032593, 'Train/mean miou_metric': 0.9900937080383301, 'Train/mean f1': 0.9910732507705688, 'Train/mean precision': 0.986524224281311, 'Train/mean recall': 0.9956643581390381, 'Train/mean hd95_metric': 1.0149548053741455} +Epoch [1650/4000] Validation [1/4] Loss: 0.26604 focal_loss 0.19400 dice_loss 0.07205 +Epoch [1650/4000] Validation [2/4] Loss: 0.27835 focal_loss 0.15104 dice_loss 0.12731 +Epoch [1650/4000] Validation [3/4] Loss: 0.20947 focal_loss 0.12568 dice_loss 0.08379 +Epoch [1650/4000] Validation [4/4] Loss: 0.27487 focal_loss 0.16073 dice_loss 0.11414 +Epoch [1650/4000] Validation metric {'Val/mean dice_metric': 0.9720479249954224, 'Val/mean miou_metric': 0.9553101658821106, 'Val/mean f1': 0.9742918610572815, 'Val/mean precision': 0.971252977848053, 'Val/mean recall': 0.9773498177528381, 'Val/mean hd95_metric': 5.55835485458374} +Cheakpoint... +Epoch [1650/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720479249954224, 'Val/mean miou_metric': 0.9553101658821106, 'Val/mean f1': 0.9742918610572815, 'Val/mean precision': 0.971252977848053, 'Val/mean recall': 0.9773498177528381, 'Val/mean hd95_metric': 5.55835485458374} +Epoch [1651/4000] Training [1/16] Loss: 0.00658 +Epoch [1651/4000] Training [2/16] Loss: 0.00729 +Epoch [1651/4000] Training [3/16] Loss: 0.00665 +Epoch [1651/4000] Training [4/16] Loss: 0.00655 +Epoch [1651/4000] Training [5/16] Loss: 0.00721 +Epoch [1651/4000] Training [6/16] Loss: 0.00680 +Epoch [1651/4000] Training [7/16] Loss: 0.00863 +Epoch [1651/4000] Training [8/16] Loss: 0.00578 +Epoch [1651/4000] Training [9/16] Loss: 0.00790 +Epoch [1651/4000] Training [10/16] Loss: 0.00577 +Epoch [1651/4000] Training [11/16] Loss: 0.00794 +Epoch [1651/4000] Training [12/16] Loss: 0.00570 +Epoch [1651/4000] Training [13/16] Loss: 0.00713 +Epoch [1651/4000] Training [14/16] Loss: 0.00907 +Epoch [1651/4000] Training [15/16] Loss: 0.00818 +Epoch [1651/4000] Training [16/16] Loss: 0.00695 +Epoch [1651/4000] Training metric {'Train/mean dice_metric': 0.9952698945999146, 'Train/mean miou_metric': 0.9903262257575989, 'Train/mean f1': 0.9911551475524902, 'Train/mean precision': 0.9866852760314941, 'Train/mean recall': 0.9956657290458679, 'Train/mean hd95_metric': 1.020568609237671} +Epoch [1651/4000] Validation [1/4] Loss: 0.23237 focal_loss 0.16859 dice_loss 0.06377 +Epoch [1651/4000] Validation [2/4] Loss: 0.29759 focal_loss 0.16486 dice_loss 0.13273 +Epoch [1651/4000] Validation [3/4] Loss: 0.19100 focal_loss 0.11118 dice_loss 0.07983 +Epoch [1651/4000] Validation [4/4] Loss: 0.20308 focal_loss 0.10604 dice_loss 0.09704 +Epoch [1651/4000] Validation metric {'Val/mean dice_metric': 0.9716941714286804, 'Val/mean miou_metric': 0.954795241355896, 'Val/mean f1': 0.9742146134376526, 'Val/mean precision': 0.9707084894180298, 'Val/mean recall': 0.9777463674545288, 'Val/mean hd95_metric': 5.3257598876953125} +Cheakpoint... +Epoch [1651/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716941714286804, 'Val/mean miou_metric': 0.954795241355896, 'Val/mean f1': 0.9742146134376526, 'Val/mean precision': 0.9707084894180298, 'Val/mean recall': 0.9777463674545288, 'Val/mean hd95_metric': 5.3257598876953125} +Epoch [1652/4000] Training [1/16] Loss: 0.00702 +Epoch [1652/4000] Training [2/16] Loss: 0.00532 +Epoch [1652/4000] Training [3/16] Loss: 0.00940 +Epoch [1652/4000] Training [4/16] Loss: 0.00633 +Epoch [1652/4000] Training [5/16] Loss: 0.00533 +Epoch [1652/4000] Training [6/16] Loss: 0.00705 +Epoch [1652/4000] Training [7/16] Loss: 0.00712 +Epoch [1652/4000] Training [8/16] Loss: 0.00572 +Epoch [1652/4000] Training [9/16] Loss: 0.00676 +Epoch [1652/4000] Training [10/16] Loss: 0.00752 +Epoch [1652/4000] Training [11/16] Loss: 0.00656 +Epoch [1652/4000] Training [12/16] Loss: 0.00823 +Epoch [1652/4000] Training [13/16] Loss: 0.00653 +Epoch [1652/4000] Training [14/16] Loss: 0.00676 +Epoch [1652/4000] Training [15/16] Loss: 0.00719 +Epoch [1652/4000] Training [16/16] Loss: 0.00637 +Epoch [1652/4000] Training metric {'Train/mean dice_metric': 0.9954049587249756, 'Train/mean miou_metric': 0.9906004071235657, 'Train/mean f1': 0.9911372065544128, 'Train/mean precision': 0.9864252209663391, 'Train/mean recall': 0.9958944320678711, 'Train/mean hd95_metric': 1.058937430381775} +Epoch [1652/4000] Validation [1/4] Loss: 0.36010 focal_loss 0.27910 dice_loss 0.08101 +Epoch [1652/4000] Validation [2/4] Loss: 0.28297 focal_loss 0.16546 dice_loss 0.11751 +Epoch [1652/4000] Validation [3/4] Loss: 0.25244 focal_loss 0.15488 dice_loss 0.09756 +Epoch [1652/4000] Validation [4/4] Loss: 0.25625 focal_loss 0.14433 dice_loss 0.11191 +Epoch [1652/4000] Validation metric {'Val/mean dice_metric': 0.9714691042900085, 'Val/mean miou_metric': 0.9547315835952759, 'Val/mean f1': 0.9734008312225342, 'Val/mean precision': 0.9691125750541687, 'Val/mean recall': 0.9777271151542664, 'Val/mean hd95_metric': 5.536006927490234} +Cheakpoint... +Epoch [1652/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714691042900085, 'Val/mean miou_metric': 0.9547315835952759, 'Val/mean f1': 0.9734008312225342, 'Val/mean precision': 0.9691125750541687, 'Val/mean recall': 0.9777271151542664, 'Val/mean hd95_metric': 5.536006927490234} +Epoch [1653/4000] Training [1/16] Loss: 0.00542 +Epoch [1653/4000] Training [2/16] Loss: 0.00486 +Epoch [1653/4000] Training [3/16] Loss: 0.00560 +Epoch [1653/4000] Training [4/16] Loss: 0.00758 +Epoch [1653/4000] Training [5/16] Loss: 0.00598 +Epoch [1653/4000] Training [6/16] Loss: 0.00724 +Epoch [1653/4000] Training [7/16] Loss: 0.00732 +Epoch [1653/4000] Training [8/16] Loss: 0.00729 +Epoch [1653/4000] Training [9/16] Loss: 0.00629 +Epoch [1653/4000] Training [10/16] Loss: 0.00724 +Epoch [1653/4000] Training [11/16] Loss: 0.00838 +Epoch [1653/4000] Training [12/16] Loss: 0.00762 +Epoch [1653/4000] Training [13/16] Loss: 0.00731 +Epoch [1653/4000] Training [14/16] Loss: 0.00625 +Epoch [1653/4000] Training [15/16] Loss: 0.00751 +Epoch [1653/4000] Training [16/16] Loss: 0.00709 +Epoch [1653/4000] Training metric {'Train/mean dice_metric': 0.995233416557312, 'Train/mean miou_metric': 0.9902583956718445, 'Train/mean f1': 0.9912364482879639, 'Train/mean precision': 0.986764132976532, 'Train/mean recall': 0.9957495331764221, 'Train/mean hd95_metric': 1.0193359851837158} +Epoch [1653/4000] Validation [1/4] Loss: 0.25812 focal_loss 0.19181 dice_loss 0.06631 +Epoch [1653/4000] Validation [2/4] Loss: 0.33235 focal_loss 0.18230 dice_loss 0.15005 +Epoch [1653/4000] Validation [3/4] Loss: 0.18975 focal_loss 0.11484 dice_loss 0.07491 +Epoch [1653/4000] Validation [4/4] Loss: 0.24309 focal_loss 0.13635 dice_loss 0.10674 +Epoch [1653/4000] Validation metric {'Val/mean dice_metric': 0.9729806184768677, 'Val/mean miou_metric': 0.9559570550918579, 'Val/mean f1': 0.9745200872421265, 'Val/mean precision': 0.9702053666114807, 'Val/mean recall': 0.9788733720779419, 'Val/mean hd95_metric': 5.305191993713379} +Cheakpoint... +Epoch [1653/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729806184768677, 'Val/mean miou_metric': 0.9559570550918579, 'Val/mean f1': 0.9745200872421265, 'Val/mean precision': 0.9702053666114807, 'Val/mean recall': 0.9788733720779419, 'Val/mean hd95_metric': 5.305191993713379} +Epoch [1654/4000] Training [1/16] Loss: 0.00668 +Epoch [1654/4000] Training [2/16] Loss: 0.00789 +Epoch [1654/4000] Training [3/16] Loss: 0.00763 +Epoch [1654/4000] Training [4/16] Loss: 0.00642 +Epoch [1654/4000] Training [5/16] Loss: 0.00584 +Epoch [1654/4000] Training [6/16] Loss: 0.00754 +Epoch [1654/4000] Training [7/16] Loss: 0.00704 +Epoch [1654/4000] Training [8/16] Loss: 0.00714 +Epoch [1654/4000] Training [9/16] Loss: 0.00582 +Epoch [1654/4000] Training [10/16] Loss: 0.00689 +Epoch [1654/4000] Training [11/16] Loss: 0.00659 +Epoch [1654/4000] Training [12/16] Loss: 0.00686 +Epoch [1654/4000] Training [13/16] Loss: 0.00769 +Epoch [1654/4000] Training [14/16] Loss: 0.00733 +Epoch [1654/4000] Training [15/16] Loss: 0.00748 +Epoch [1654/4000] Training [16/16] Loss: 0.00751 +Epoch [1654/4000] Training metric {'Train/mean dice_metric': 0.9951013922691345, 'Train/mean miou_metric': 0.9899688363075256, 'Train/mean f1': 0.9905807971954346, 'Train/mean precision': 0.9854687452316284, 'Train/mean recall': 0.9957461357116699, 'Train/mean hd95_metric': 1.0228708982467651} +Epoch [1654/4000] Validation [1/4] Loss: 0.23827 focal_loss 0.17958 dice_loss 0.05868 +Epoch [1654/4000] Validation [2/4] Loss: 0.30494 focal_loss 0.16251 dice_loss 0.14243 +Epoch [1654/4000] Validation [3/4] Loss: 0.27185 focal_loss 0.17757 dice_loss 0.09427 +Epoch [1654/4000] Validation [4/4] Loss: 0.27386 focal_loss 0.15801 dice_loss 0.11585 +Epoch [1654/4000] Validation metric {'Val/mean dice_metric': 0.9717761874198914, 'Val/mean miou_metric': 0.954734206199646, 'Val/mean f1': 0.9744111895561218, 'Val/mean precision': 0.9697898626327515, 'Val/mean recall': 0.9790766835212708, 'Val/mean hd95_metric': 5.4671759605407715} +Cheakpoint... +Epoch [1654/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717761874198914, 'Val/mean miou_metric': 0.954734206199646, 'Val/mean f1': 0.9744111895561218, 'Val/mean precision': 0.9697898626327515, 'Val/mean recall': 0.9790766835212708, 'Val/mean hd95_metric': 5.4671759605407715} +Epoch [1655/4000] Training [1/16] Loss: 0.00932 +Epoch [1655/4000] Training [2/16] Loss: 0.00882 +Epoch [1655/4000] Training [3/16] Loss: 0.00699 +Epoch [1655/4000] Training [4/16] Loss: 0.00646 +Epoch [1655/4000] Training [5/16] Loss: 0.01285 +Epoch [1655/4000] Training [6/16] Loss: 0.00728 +Epoch [1655/4000] Training [7/16] Loss: 0.00633 +Epoch [1655/4000] Training [8/16] Loss: 0.00610 +Epoch [1655/4000] Training [9/16] Loss: 0.00662 +Epoch [1655/4000] Training [10/16] Loss: 0.01132 +Epoch [1655/4000] Training [11/16] Loss: 0.00893 +Epoch [1655/4000] Training [12/16] Loss: 0.01009 +Epoch [1655/4000] Training [13/16] Loss: 0.00781 +Epoch [1655/4000] Training [14/16] Loss: 0.00854 +Epoch [1655/4000] Training [15/16] Loss: 0.00704 +Epoch [1655/4000] Training [16/16] Loss: 0.00591 +Epoch [1655/4000] Training metric {'Train/mean dice_metric': 0.9946146011352539, 'Train/mean miou_metric': 0.9890477061271667, 'Train/mean f1': 0.990681529045105, 'Train/mean precision': 0.9861949682235718, 'Train/mean recall': 0.9952090978622437, 'Train/mean hd95_metric': 1.1090246438980103} +Epoch [1655/4000] Validation [1/4] Loss: 0.25266 focal_loss 0.18532 dice_loss 0.06734 +Epoch [1655/4000] Validation [2/4] Loss: 0.38708 focal_loss 0.22657 dice_loss 0.16051 +Epoch [1655/4000] Validation [3/4] Loss: 0.45070 focal_loss 0.32962 dice_loss 0.12107 +Epoch [1655/4000] Validation [4/4] Loss: 0.25121 focal_loss 0.14317 dice_loss 0.10805 +Epoch [1655/4000] Validation metric {'Val/mean dice_metric': 0.9698110818862915, 'Val/mean miou_metric': 0.9517068862915039, 'Val/mean f1': 0.9719676375389099, 'Val/mean precision': 0.9637126326560974, 'Val/mean recall': 0.9803652763366699, 'Val/mean hd95_metric': 6.858438014984131} +Cheakpoint... +Epoch [1655/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698110818862915, 'Val/mean miou_metric': 0.9517068862915039, 'Val/mean f1': 0.9719676375389099, 'Val/mean precision': 0.9637126326560974, 'Val/mean recall': 0.9803652763366699, 'Val/mean hd95_metric': 6.858438014984131} +Epoch [1656/4000] Training [1/16] Loss: 0.00692 +Epoch [1656/4000] Training [2/16] Loss: 0.00518 +Epoch [1656/4000] Training [3/16] Loss: 0.00561 +Epoch [1656/4000] Training [4/16] Loss: 0.00606 +Epoch [1656/4000] Training [5/16] Loss: 0.00969 +Epoch [1656/4000] Training [6/16] Loss: 0.00821 +Epoch [1656/4000] Training [7/16] Loss: 0.00658 +Epoch [1656/4000] Training [8/16] Loss: 0.00979 +Epoch [1656/4000] Training [9/16] Loss: 0.01076 +Epoch [1656/4000] Training [10/16] Loss: 0.00552 +Epoch [1656/4000] Training [11/16] Loss: 0.00548 +Epoch [1656/4000] Training [12/16] Loss: 0.00856 +Epoch [1656/4000] Training [13/16] Loss: 0.00878 +Epoch [1656/4000] Training [14/16] Loss: 0.00479 +Epoch [1656/4000] Training [15/16] Loss: 0.00760 +Epoch [1656/4000] Training [16/16] Loss: 0.01088 +Epoch [1656/4000] Training metric {'Train/mean dice_metric': 0.9949169158935547, 'Train/mean miou_metric': 0.9896453022956848, 'Train/mean f1': 0.9910326600074768, 'Train/mean precision': 0.9865062832832336, 'Train/mean recall': 0.9956007599830627, 'Train/mean hd95_metric': 1.1715338230133057} +Epoch [1656/4000] Validation [1/4] Loss: 0.23894 focal_loss 0.17756 dice_loss 0.06138 +Epoch [1656/4000] Validation [2/4] Loss: 0.35472 focal_loss 0.21565 dice_loss 0.13907 +Epoch [1656/4000] Validation [3/4] Loss: 0.23359 focal_loss 0.14161 dice_loss 0.09198 +Epoch [1656/4000] Validation [4/4] Loss: 0.38586 focal_loss 0.24874 dice_loss 0.13713 +Epoch [1656/4000] Validation metric {'Val/mean dice_metric': 0.9722484350204468, 'Val/mean miou_metric': 0.9546650052070618, 'Val/mean f1': 0.9728853106498718, 'Val/mean precision': 0.9670432806015015, 'Val/mean recall': 0.9787983894348145, 'Val/mean hd95_metric': 6.236499786376953} +Cheakpoint... +Epoch [1656/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722484350204468, 'Val/mean miou_metric': 0.9546650052070618, 'Val/mean f1': 0.9728853106498718, 'Val/mean precision': 0.9670432806015015, 'Val/mean recall': 0.9787983894348145, 'Val/mean hd95_metric': 6.236499786376953} +Epoch [1657/4000] Training [1/16] Loss: 0.00584 +Epoch [1657/4000] Training [2/16] Loss: 0.01021 +Epoch [1657/4000] Training [3/16] Loss: 0.00770 +Epoch [1657/4000] Training [4/16] Loss: 0.00677 +Epoch [1657/4000] Training [5/16] Loss: 0.00514 +Epoch [1657/4000] Training [6/16] Loss: 0.00693 +Epoch [1657/4000] Training [7/16] Loss: 0.00770 +Epoch [1657/4000] Training [8/16] Loss: 0.00813 +Epoch [1657/4000] Training [9/16] Loss: 0.00673 +Epoch [1657/4000] Training [10/16] Loss: 0.01071 +Epoch [1657/4000] Training [11/16] Loss: 0.00732 +Epoch [1657/4000] Training [12/16] Loss: 0.00656 +Epoch [1657/4000] Training [13/16] Loss: 0.00740 +Epoch [1657/4000] Training [14/16] Loss: 0.00754 +Epoch [1657/4000] Training [15/16] Loss: 0.00747 +Epoch [1657/4000] Training [16/16] Loss: 0.00638 +Epoch [1657/4000] Training metric {'Train/mean dice_metric': 0.9949924945831299, 'Train/mean miou_metric': 0.9897830486297607, 'Train/mean f1': 0.9910064935684204, 'Train/mean precision': 0.986508309841156, 'Train/mean recall': 0.9955458045005798, 'Train/mean hd95_metric': 1.0308201313018799} +Epoch [1657/4000] Validation [1/4] Loss: 0.23981 focal_loss 0.17394 dice_loss 0.06587 +Epoch [1657/4000] Validation [2/4] Loss: 0.44480 focal_loss 0.26206 dice_loss 0.18274 +Epoch [1657/4000] Validation [3/4] Loss: 0.32426 focal_loss 0.22272 dice_loss 0.10154 +Epoch [1657/4000] Validation [4/4] Loss: 0.30984 focal_loss 0.18021 dice_loss 0.12963 +Epoch [1657/4000] Validation metric {'Val/mean dice_metric': 0.9705092310905457, 'Val/mean miou_metric': 0.9526826739311218, 'Val/mean f1': 0.9721817374229431, 'Val/mean precision': 0.9684334397315979, 'Val/mean recall': 0.9759592413902283, 'Val/mean hd95_metric': 5.886017799377441} +Cheakpoint... +Epoch [1657/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705092310905457, 'Val/mean miou_metric': 0.9526826739311218, 'Val/mean f1': 0.9721817374229431, 'Val/mean precision': 0.9684334397315979, 'Val/mean recall': 0.9759592413902283, 'Val/mean hd95_metric': 5.886017799377441} +Epoch [1658/4000] Training [1/16] Loss: 0.00649 +Epoch [1658/4000] Training [2/16] Loss: 0.00619 +Epoch [1658/4000] Training [3/16] Loss: 0.00540 +Epoch [1658/4000] Training [4/16] Loss: 0.01076 +Epoch [1658/4000] Training [5/16] Loss: 0.00721 +Epoch [1658/4000] Training [6/16] Loss: 0.00866 +Epoch [1658/4000] Training [7/16] Loss: 0.00610 +Epoch [1658/4000] Training [8/16] Loss: 0.00760 +Epoch [1658/4000] Training [9/16] Loss: 0.00628 +Epoch [1658/4000] Training [10/16] Loss: 0.00542 +Epoch [1658/4000] Training [11/16] Loss: 0.00707 +Epoch [1658/4000] Training [12/16] Loss: 0.00787 +Epoch [1658/4000] Training [13/16] Loss: 0.00793 +Epoch [1658/4000] Training [14/16] Loss: 0.00727 +Epoch [1658/4000] Training [15/16] Loss: 0.00728 +Epoch [1658/4000] Training [16/16] Loss: 0.00785 +Epoch [1658/4000] Training metric {'Train/mean dice_metric': 0.994843602180481, 'Train/mean miou_metric': 0.9894844889640808, 'Train/mean f1': 0.9902970194816589, 'Train/mean precision': 0.9853256344795227, 'Train/mean recall': 0.9953188300132751, 'Train/mean hd95_metric': 1.0964441299438477} +Epoch [1658/4000] Validation [1/4] Loss: 0.25023 focal_loss 0.18123 dice_loss 0.06900 +Epoch [1658/4000] Validation [2/4] Loss: 0.25286 focal_loss 0.13717 dice_loss 0.11569 +Epoch [1658/4000] Validation [3/4] Loss: 0.23995 focal_loss 0.14036 dice_loss 0.09959 +Epoch [1658/4000] Validation [4/4] Loss: 0.30921 focal_loss 0.16952 dice_loss 0.13969 +Epoch [1658/4000] Validation metric {'Val/mean dice_metric': 0.9693153500556946, 'Val/mean miou_metric': 0.9518438577651978, 'Val/mean f1': 0.9721524715423584, 'Val/mean precision': 0.9674620032310486, 'Val/mean recall': 0.9768885374069214, 'Val/mean hd95_metric': 6.788065433502197} +Cheakpoint... +Epoch [1658/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693153500556946, 'Val/mean miou_metric': 0.9518438577651978, 'Val/mean f1': 0.9721524715423584, 'Val/mean precision': 0.9674620032310486, 'Val/mean recall': 0.9768885374069214, 'Val/mean hd95_metric': 6.788065433502197} +Epoch [1659/4000] Training [1/16] Loss: 0.00693 +Epoch [1659/4000] Training [2/16] Loss: 0.00643 +Epoch [1659/4000] Training [3/16] Loss: 0.00558 +Epoch [1659/4000] Training [4/16] Loss: 0.00635 +Epoch [1659/4000] Training [5/16] Loss: 0.00782 +Epoch [1659/4000] Training [6/16] Loss: 0.00739 +Epoch [1659/4000] Training [7/16] Loss: 0.00556 +Epoch [1659/4000] Training [8/16] Loss: 0.00545 +Epoch [1659/4000] Training [9/16] Loss: 0.01202 +Epoch [1659/4000] Training [10/16] Loss: 0.00988 +Epoch [1659/4000] Training [11/16] Loss: 0.00532 +Epoch [1659/4000] Training [12/16] Loss: 0.00568 +Epoch [1659/4000] Training [13/16] Loss: 0.00617 +Epoch [1659/4000] Training [14/16] Loss: 0.00781 +Epoch [1659/4000] Training [15/16] Loss: 0.00690 +Epoch [1659/4000] Training [16/16] Loss: 0.00905 +Epoch [1659/4000] Training metric {'Train/mean dice_metric': 0.9948982000350952, 'Train/mean miou_metric': 0.9895943403244019, 'Train/mean f1': 0.9907057285308838, 'Train/mean precision': 0.9858677983283997, 'Train/mean recall': 0.9955913424491882, 'Train/mean hd95_metric': 1.0589148998260498} +Epoch [1659/4000] Validation [1/4] Loss: 0.29329 focal_loss 0.22287 dice_loss 0.07041 +Epoch [1659/4000] Validation [2/4] Loss: 0.56817 focal_loss 0.35173 dice_loss 0.21644 +Epoch [1659/4000] Validation [3/4] Loss: 0.17724 focal_loss 0.10856 dice_loss 0.06869 +Epoch [1659/4000] Validation [4/4] Loss: 0.28071 focal_loss 0.16347 dice_loss 0.11724 +Epoch [1659/4000] Validation metric {'Val/mean dice_metric': 0.9680013656616211, 'Val/mean miou_metric': 0.9508154988288879, 'Val/mean f1': 0.9722353219985962, 'Val/mean precision': 0.9684520959854126, 'Val/mean recall': 0.9760481715202332, 'Val/mean hd95_metric': 6.486475467681885} +Cheakpoint... +Epoch [1659/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680013656616211, 'Val/mean miou_metric': 0.9508154988288879, 'Val/mean f1': 0.9722353219985962, 'Val/mean precision': 0.9684520959854126, 'Val/mean recall': 0.9760481715202332, 'Val/mean hd95_metric': 6.486475467681885} +Epoch [1660/4000] Training [1/16] Loss: 0.01183 +Epoch [1660/4000] Training [2/16] Loss: 0.00744 +Epoch [1660/4000] Training [3/16] Loss: 0.00715 +Epoch [1660/4000] Training [4/16] Loss: 0.00692 +Epoch [1660/4000] Training [5/16] Loss: 0.00889 +Epoch [1660/4000] Training [6/16] Loss: 0.00705 +Epoch [1660/4000] Training [7/16] Loss: 0.00653 +Epoch [1660/4000] Training [8/16] Loss: 0.00720 +Epoch [1660/4000] Training [9/16] Loss: 0.00774 +Epoch [1660/4000] Training [10/16] Loss: 0.00646 +Epoch [1660/4000] Training [11/16] Loss: 0.01061 +Epoch [1660/4000] Training [12/16] Loss: 0.00772 +Epoch [1660/4000] Training [13/16] Loss: 0.00591 +Epoch [1660/4000] Training [14/16] Loss: 0.00747 +Epoch [1660/4000] Training [15/16] Loss: 0.00714 +Epoch [1660/4000] Training [16/16] Loss: 0.01104 +Epoch [1660/4000] Training metric {'Train/mean dice_metric': 0.9947742819786072, 'Train/mean miou_metric': 0.9893515110015869, 'Train/mean f1': 0.9907248020172119, 'Train/mean precision': 0.9861200451850891, 'Train/mean recall': 0.9953728318214417, 'Train/mean hd95_metric': 1.1487658023834229} +Epoch [1660/4000] Validation [1/4] Loss: 0.26512 focal_loss 0.19876 dice_loss 0.06636 +Epoch [1660/4000] Validation [2/4] Loss: 0.42696 focal_loss 0.23565 dice_loss 0.19130 +Epoch [1660/4000] Validation [3/4] Loss: 0.20419 focal_loss 0.13387 dice_loss 0.07032 +Epoch [1660/4000] Validation [4/4] Loss: 0.20872 focal_loss 0.11441 dice_loss 0.09430 +Epoch [1660/4000] Validation metric {'Val/mean dice_metric': 0.9710327386856079, 'Val/mean miou_metric': 0.9539912939071655, 'Val/mean f1': 0.973333477973938, 'Val/mean precision': 0.969572901725769, 'Val/mean recall': 0.9771232604980469, 'Val/mean hd95_metric': 5.554417133331299} +Cheakpoint... +Epoch [1660/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710327386856079, 'Val/mean miou_metric': 0.9539912939071655, 'Val/mean f1': 0.973333477973938, 'Val/mean precision': 0.969572901725769, 'Val/mean recall': 0.9771232604980469, 'Val/mean hd95_metric': 5.554417133331299} +Epoch [1661/4000] Training [1/16] Loss: 0.00746 +Epoch [1661/4000] Training [2/16] Loss: 0.00612 +Epoch [1661/4000] Training [3/16] Loss: 0.00768 +Epoch [1661/4000] Training [4/16] Loss: 0.01270 +Epoch [1661/4000] Training [5/16] Loss: 0.00854 +Epoch [1661/4000] Training [6/16] Loss: 0.01743 +Epoch [1661/4000] Training [7/16] Loss: 0.00760 +Epoch [1661/4000] Training [8/16] Loss: 0.00726 +Epoch [1661/4000] Training [9/16] Loss: 0.00573 +Epoch [1661/4000] Training [10/16] Loss: 0.00973 +Epoch [1661/4000] Training [11/16] Loss: 0.00702 +Epoch [1661/4000] Training [12/16] Loss: 0.00787 +Epoch [1661/4000] Training [13/16] Loss: 0.00655 +Epoch [1661/4000] Training [14/16] Loss: 0.00565 +Epoch [1661/4000] Training [15/16] Loss: 0.00778 +Epoch [1661/4000] Training [16/16] Loss: 0.00911 +Epoch [1661/4000] Training metric {'Train/mean dice_metric': 0.9946624040603638, 'Train/mean miou_metric': 0.989142656326294, 'Train/mean f1': 0.9906849265098572, 'Train/mean precision': 0.9863104224205017, 'Train/mean recall': 0.9950984120368958, 'Train/mean hd95_metric': 1.0491498708724976} +Epoch [1661/4000] Validation [1/4] Loss: 0.22980 focal_loss 0.16584 dice_loss 0.06396 +Epoch [1661/4000] Validation [2/4] Loss: 0.40929 focal_loss 0.24443 dice_loss 0.16485 +Epoch [1661/4000] Validation [3/4] Loss: 0.17840 focal_loss 0.11502 dice_loss 0.06338 +Epoch [1661/4000] Validation [4/4] Loss: 0.28844 focal_loss 0.17024 dice_loss 0.11820 +Epoch [1661/4000] Validation metric {'Val/mean dice_metric': 0.9693354368209839, 'Val/mean miou_metric': 0.9518779516220093, 'Val/mean f1': 0.971441924571991, 'Val/mean precision': 0.9677007794380188, 'Val/mean recall': 0.9752119779586792, 'Val/mean hd95_metric': 5.643702030181885} +Cheakpoint... +Epoch [1661/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693354368209839, 'Val/mean miou_metric': 0.9518779516220093, 'Val/mean f1': 0.971441924571991, 'Val/mean precision': 0.9677007794380188, 'Val/mean recall': 0.9752119779586792, 'Val/mean hd95_metric': 5.643702030181885} +Epoch [1662/4000] Training [1/16] Loss: 0.00635 +Epoch [1662/4000] Training [2/16] Loss: 0.00725 +Epoch [1662/4000] Training [3/16] Loss: 0.00903 +Epoch [1662/4000] Training [4/16] Loss: 0.00630 +Epoch [1662/4000] Training [5/16] Loss: 0.00658 +Epoch [1662/4000] Training [6/16] Loss: 0.00719 +Epoch [1662/4000] Training [7/16] Loss: 0.00775 +Epoch [1662/4000] Training [8/16] Loss: 0.00587 +Epoch [1662/4000] Training [9/16] Loss: 0.00811 +Epoch [1662/4000] Training [10/16] Loss: 0.00567 +Epoch [1662/4000] Training [11/16] Loss: 0.00687 +Epoch [1662/4000] Training [12/16] Loss: 0.00815 +Epoch [1662/4000] Training [13/16] Loss: 0.00698 +Epoch [1662/4000] Training [14/16] Loss: 0.00947 +Epoch [1662/4000] Training [15/16] Loss: 0.00639 +Epoch [1662/4000] Training [16/16] Loss: 0.00675 +Epoch [1662/4000] Training metric {'Train/mean dice_metric': 0.9950226545333862, 'Train/mean miou_metric': 0.9898407459259033, 'Train/mean f1': 0.9909895658493042, 'Train/mean precision': 0.9864729046821594, 'Train/mean recall': 0.9955478310585022, 'Train/mean hd95_metric': 1.0219018459320068} +Epoch [1662/4000] Validation [1/4] Loss: 0.27083 focal_loss 0.19866 dice_loss 0.07217 +Epoch [1662/4000] Validation [2/4] Loss: 0.30312 focal_loss 0.17274 dice_loss 0.13038 +Epoch [1662/4000] Validation [3/4] Loss: 0.22815 focal_loss 0.14125 dice_loss 0.08690 +Epoch [1662/4000] Validation [4/4] Loss: 0.34100 focal_loss 0.21110 dice_loss 0.12990 +Epoch [1662/4000] Validation metric {'Val/mean dice_metric': 0.9708755612373352, 'Val/mean miou_metric': 0.9531499743461609, 'Val/mean f1': 0.9722614288330078, 'Val/mean precision': 0.9672480225563049, 'Val/mean recall': 0.9773270487785339, 'Val/mean hd95_metric': 6.271961212158203} +Cheakpoint... +Epoch [1662/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708755612373352, 'Val/mean miou_metric': 0.9531499743461609, 'Val/mean f1': 0.9722614288330078, 'Val/mean precision': 0.9672480225563049, 'Val/mean recall': 0.9773270487785339, 'Val/mean hd95_metric': 6.271961212158203} +Epoch [1663/4000] Training [1/16] Loss: 0.00883 +Epoch [1663/4000] Training [2/16] Loss: 0.00630 +Epoch [1663/4000] Training [3/16] Loss: 0.00846 +Epoch [1663/4000] Training [4/16] Loss: 0.00745 +Epoch [1663/4000] Training [5/16] Loss: 0.00612 +Epoch [1663/4000] Training [6/16] Loss: 0.00783 +Epoch [1663/4000] Training [7/16] Loss: 0.00847 +Epoch [1663/4000] Training [8/16] Loss: 0.00581 +Epoch [1663/4000] Training [9/16] Loss: 0.01109 +Epoch [1663/4000] Training [10/16] Loss: 0.00764 +Epoch [1663/4000] Training [11/16] Loss: 0.00865 +Epoch [1663/4000] Training [12/16] Loss: 0.01048 +Epoch [1663/4000] Training [13/16] Loss: 0.00895 +Epoch [1663/4000] Training [14/16] Loss: 0.00542 +Epoch [1663/4000] Training [15/16] Loss: 0.00589 +Epoch [1663/4000] Training [16/16] Loss: 0.00789 +Epoch [1663/4000] Training metric {'Train/mean dice_metric': 0.9946541786193848, 'Train/mean miou_metric': 0.9891359806060791, 'Train/mean f1': 0.9909226894378662, 'Train/mean precision': 0.9863276481628418, 'Train/mean recall': 0.9955606460571289, 'Train/mean hd95_metric': 1.0646488666534424} +Epoch [1663/4000] Validation [1/4] Loss: 0.34256 focal_loss 0.25661 dice_loss 0.08594 +Epoch [1663/4000] Validation [2/4] Loss: 0.59161 focal_loss 0.39448 dice_loss 0.19712 +Epoch [1663/4000] Validation [3/4] Loss: 0.21219 focal_loss 0.13447 dice_loss 0.07772 +Epoch [1663/4000] Validation [4/4] Loss: 0.21564 focal_loss 0.12092 dice_loss 0.09471 +Epoch [1663/4000] Validation metric {'Val/mean dice_metric': 0.9690219759941101, 'Val/mean miou_metric': 0.9520060420036316, 'Val/mean f1': 0.9722018837928772, 'Val/mean precision': 0.9730099439620972, 'Val/mean recall': 0.9713950157165527, 'Val/mean hd95_metric': 5.729065895080566} +Cheakpoint... +Epoch [1663/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690219759941101, 'Val/mean miou_metric': 0.9520060420036316, 'Val/mean f1': 0.9722018837928772, 'Val/mean precision': 0.9730099439620972, 'Val/mean recall': 0.9713950157165527, 'Val/mean hd95_metric': 5.729065895080566} +Epoch [1664/4000] Training [1/16] Loss: 0.00585 +Epoch [1664/4000] Training [2/16] Loss: 0.00699 +Epoch [1664/4000] Training [3/16] Loss: 0.00839 +Epoch [1664/4000] Training [4/16] Loss: 0.00791 +Epoch [1664/4000] Training [5/16] Loss: 0.00728 +Epoch [1664/4000] Training [6/16] Loss: 0.00614 +Epoch [1664/4000] Training [7/16] Loss: 0.00510 +Epoch [1664/4000] Training [8/16] Loss: 0.00504 +Epoch [1664/4000] Training [9/16] Loss: 0.00663 +Epoch [1664/4000] Training [10/16] Loss: 0.01024 +Epoch [1664/4000] Training [11/16] Loss: 0.00927 +Epoch [1664/4000] Training [12/16] Loss: 0.00736 +Epoch [1664/4000] Training [13/16] Loss: 0.00559 +Epoch [1664/4000] Training [14/16] Loss: 0.00886 +Epoch [1664/4000] Training [15/16] Loss: 0.00681 +Epoch [1664/4000] Training [16/16] Loss: 0.01040 +Epoch [1664/4000] Training metric {'Train/mean dice_metric': 0.9951695799827576, 'Train/mean miou_metric': 0.9901362657546997, 'Train/mean f1': 0.991207480430603, 'Train/mean precision': 0.986799418926239, 'Train/mean recall': 0.9956551194190979, 'Train/mean hd95_metric': 1.0245988368988037} +Epoch [1664/4000] Validation [1/4] Loss: 0.25781 focal_loss 0.18878 dice_loss 0.06903 +Epoch [1664/4000] Validation [2/4] Loss: 0.55670 focal_loss 0.35942 dice_loss 0.19728 +Epoch [1664/4000] Validation [3/4] Loss: 0.20418 focal_loss 0.13087 dice_loss 0.07331 +Epoch [1664/4000] Validation [4/4] Loss: 0.30710 focal_loss 0.17629 dice_loss 0.13081 +Epoch [1664/4000] Validation metric {'Val/mean dice_metric': 0.9708070755004883, 'Val/mean miou_metric': 0.9540778994560242, 'Val/mean f1': 0.9739280939102173, 'Val/mean precision': 0.9703510403633118, 'Val/mean recall': 0.9775316715240479, 'Val/mean hd95_metric': 5.557152271270752} +Cheakpoint... +Epoch [1664/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708070755004883, 'Val/mean miou_metric': 0.9540778994560242, 'Val/mean f1': 0.9739280939102173, 'Val/mean precision': 0.9703510403633118, 'Val/mean recall': 0.9775316715240479, 'Val/mean hd95_metric': 5.557152271270752} +Epoch [1665/4000] Training [1/16] Loss: 0.00702 +Epoch [1665/4000] Training [2/16] Loss: 0.00477 +Epoch [1665/4000] Training [3/16] Loss: 0.00539 +Epoch [1665/4000] Training [4/16] Loss: 0.00606 +Epoch [1665/4000] Training [5/16] Loss: 0.00602 +Epoch [1665/4000] Training [6/16] Loss: 0.00684 +Epoch [1665/4000] Training [7/16] Loss: 0.00726 +Epoch [1665/4000] Training [8/16] Loss: 0.00912 +Epoch [1665/4000] Training [9/16] Loss: 0.00647 +Epoch [1665/4000] Training [10/16] Loss: 0.01331 +Epoch [1665/4000] Training [11/16] Loss: 0.00504 +Epoch [1665/4000] Training [12/16] Loss: 0.00775 +Epoch [1665/4000] Training [13/16] Loss: 0.00724 +Epoch [1665/4000] Training [14/16] Loss: 0.00571 +Epoch [1665/4000] Training [15/16] Loss: 0.00647 +Epoch [1665/4000] Training [16/16] Loss: 0.00726 +Epoch [1665/4000] Training metric {'Train/mean dice_metric': 0.9952726364135742, 'Train/mean miou_metric': 0.9903141856193542, 'Train/mean f1': 0.9907103180885315, 'Train/mean precision': 0.9855361580848694, 'Train/mean recall': 0.9959390759468079, 'Train/mean hd95_metric': 1.2923970222473145} +Epoch [1665/4000] Validation [1/4] Loss: 0.21625 focal_loss 0.15574 dice_loss 0.06051 +Epoch [1665/4000] Validation [2/4] Loss: 0.46189 focal_loss 0.26025 dice_loss 0.20164 +Epoch [1665/4000] Validation [3/4] Loss: 0.17551 focal_loss 0.11416 dice_loss 0.06136 +Epoch [1665/4000] Validation [4/4] Loss: 0.21357 focal_loss 0.11157 dice_loss 0.10200 +Epoch [1665/4000] Validation metric {'Val/mean dice_metric': 0.9708102345466614, 'Val/mean miou_metric': 0.9539083242416382, 'Val/mean f1': 0.9727516770362854, 'Val/mean precision': 0.9673565030097961, 'Val/mean recall': 0.9782072305679321, 'Val/mean hd95_metric': 6.006793022155762} +Cheakpoint... +Epoch [1665/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708102345466614, 'Val/mean miou_metric': 0.9539083242416382, 'Val/mean f1': 0.9727516770362854, 'Val/mean precision': 0.9673565030097961, 'Val/mean recall': 0.9782072305679321, 'Val/mean hd95_metric': 6.006793022155762} +Epoch [1666/4000] Training [1/16] Loss: 0.01053 +Epoch [1666/4000] Training [2/16] Loss: 0.00683 +Epoch [1666/4000] Training [3/16] Loss: 0.00568 +Epoch [1666/4000] Training [4/16] Loss: 0.00602 +Epoch [1666/4000] Training [5/16] Loss: 0.00674 +Epoch [1666/4000] Training [6/16] Loss: 0.00694 +Epoch [1666/4000] Training [7/16] Loss: 0.00701 +Epoch [1666/4000] Training [8/16] Loss: 0.00695 +Epoch [1666/4000] Training [9/16] Loss: 0.00699 +Epoch [1666/4000] Training [10/16] Loss: 0.00836 +Epoch [1666/4000] Training [11/16] Loss: 0.00551 +Epoch [1666/4000] Training [12/16] Loss: 0.00835 +Epoch [1666/4000] Training [13/16] Loss: 0.00841 +Epoch [1666/4000] Training [14/16] Loss: 0.00978 +Epoch [1666/4000] Training [15/16] Loss: 0.00573 +Epoch [1666/4000] Training [16/16] Loss: 0.00806 +Epoch [1666/4000] Training metric {'Train/mean dice_metric': 0.9948869943618774, 'Train/mean miou_metric': 0.9896955490112305, 'Train/mean f1': 0.9908047318458557, 'Train/mean precision': 0.9861639738082886, 'Train/mean recall': 0.9954894185066223, 'Train/mean hd95_metric': 1.3946197032928467} +Epoch [1666/4000] Validation [1/4] Loss: 0.25682 focal_loss 0.18473 dice_loss 0.07210 +Epoch [1666/4000] Validation [2/4] Loss: 0.40444 focal_loss 0.21200 dice_loss 0.19245 +Epoch [1666/4000] Validation [3/4] Loss: 0.15982 focal_loss 0.09986 dice_loss 0.05996 +Epoch [1666/4000] Validation [4/4] Loss: 0.42973 focal_loss 0.27952 dice_loss 0.15020 +Epoch [1666/4000] Validation metric {'Val/mean dice_metric': 0.9681089520454407, 'Val/mean miou_metric': 0.9512394070625305, 'Val/mean f1': 0.9731148481369019, 'Val/mean precision': 0.9725512862205505, 'Val/mean recall': 0.9736791253089905, 'Val/mean hd95_metric': 5.274129867553711} +Cheakpoint... +Epoch [1666/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9681089520454407, 'Val/mean miou_metric': 0.9512394070625305, 'Val/mean f1': 0.9731148481369019, 'Val/mean precision': 0.9725512862205505, 'Val/mean recall': 0.9736791253089905, 'Val/mean hd95_metric': 5.274129867553711} +Epoch [1667/4000] Training [1/16] Loss: 0.00834 +Epoch [1667/4000] Training [2/16] Loss: 0.00754 +Epoch [1667/4000] Training [3/16] Loss: 0.00680 +Epoch [1667/4000] Training [4/16] Loss: 0.00701 +Epoch [1667/4000] Training [5/16] Loss: 0.00719 +Epoch [1667/4000] Training [6/16] Loss: 0.00672 +Epoch [1667/4000] Training [7/16] Loss: 0.00965 +Epoch [1667/4000] Training [8/16] Loss: 0.00757 +Epoch [1667/4000] Training [9/16] Loss: 0.00667 +Epoch [1667/4000] Training [10/16] Loss: 0.00732 +Epoch [1667/4000] Training [11/16] Loss: 0.00850 +Epoch [1667/4000] Training [12/16] Loss: 0.00837 +Epoch [1667/4000] Training [13/16] Loss: 0.00944 +Epoch [1667/4000] Training [14/16] Loss: 0.00994 +Epoch [1667/4000] Training [15/16] Loss: 0.00702 +Epoch [1667/4000] Training [16/16] Loss: 0.01021 +Epoch [1667/4000] Training metric {'Train/mean dice_metric': 0.994561493396759, 'Train/mean miou_metric': 0.9889367818832397, 'Train/mean f1': 0.990512490272522, 'Train/mean precision': 0.9860193133354187, 'Train/mean recall': 0.9950467944145203, 'Train/mean hd95_metric': 1.0450021028518677} +Epoch [1667/4000] Validation [1/4] Loss: 0.69219 focal_loss 0.54678 dice_loss 0.14541 +Epoch [1667/4000] Validation [2/4] Loss: 0.80452 focal_loss 0.51426 dice_loss 0.29026 +Epoch [1667/4000] Validation [3/4] Loss: 0.16542 focal_loss 0.10637 dice_loss 0.05906 +Epoch [1667/4000] Validation [4/4] Loss: 0.50631 focal_loss 0.35687 dice_loss 0.14945 +Epoch [1667/4000] Validation metric {'Val/mean dice_metric': 0.9593479037284851, 'Val/mean miou_metric': 0.941200852394104, 'Val/mean f1': 0.9643886089324951, 'Val/mean precision': 0.9720463752746582, 'Val/mean recall': 0.9568505883216858, 'Val/mean hd95_metric': 5.881857395172119} +Cheakpoint... +Epoch [1667/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9593], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9593479037284851, 'Val/mean miou_metric': 0.941200852394104, 'Val/mean f1': 0.9643886089324951, 'Val/mean precision': 0.9720463752746582, 'Val/mean recall': 0.9568505883216858, 'Val/mean hd95_metric': 5.881857395172119} +Epoch [1668/4000] Training [1/16] Loss: 0.00747 +Epoch [1668/4000] Training [2/16] Loss: 0.00946 +Epoch [1668/4000] Training [3/16] Loss: 0.00864 +Epoch [1668/4000] Training [4/16] Loss: 0.00699 +Epoch [1668/4000] Training [5/16] Loss: 0.00626 +Epoch [1668/4000] Training [6/16] Loss: 0.00763 +Epoch [1668/4000] Training [7/16] Loss: 0.00667 +Epoch [1668/4000] Training [8/16] Loss: 0.00786 +Epoch [1668/4000] Training [9/16] Loss: 0.00608 +Epoch [1668/4000] Training [10/16] Loss: 0.00877 +Epoch [1668/4000] Training [11/16] Loss: 0.00539 +Epoch [1668/4000] Training [12/16] Loss: 0.00670 +Epoch [1668/4000] Training [13/16] Loss: 0.00900 +Epoch [1668/4000] Training [14/16] Loss: 0.01415 +Epoch [1668/4000] Training [15/16] Loss: 0.00851 +Epoch [1668/4000] Training [16/16] Loss: 0.00692 +Epoch [1668/4000] Training metric {'Train/mean dice_metric': 0.9945873618125916, 'Train/mean miou_metric': 0.9889929294586182, 'Train/mean f1': 0.9905737042427063, 'Train/mean precision': 0.9860146641731262, 'Train/mean recall': 0.9951751232147217, 'Train/mean hd95_metric': 1.066264271736145} +Epoch [1668/4000] Validation [1/4] Loss: 0.29975 focal_loss 0.22444 dice_loss 0.07531 +Epoch [1668/4000] Validation [2/4] Loss: 0.66055 focal_loss 0.40302 dice_loss 0.25753 +Epoch [1668/4000] Validation [3/4] Loss: 0.17665 focal_loss 0.11072 dice_loss 0.06593 +Epoch [1668/4000] Validation [4/4] Loss: 0.31437 focal_loss 0.19284 dice_loss 0.12153 +Epoch [1668/4000] Validation metric {'Val/mean dice_metric': 0.9670600891113281, 'Val/mean miou_metric': 0.9503461718559265, 'Val/mean f1': 0.9727541208267212, 'Val/mean precision': 0.972435474395752, 'Val/mean recall': 0.9730729460716248, 'Val/mean hd95_metric': 4.6961846351623535} +Cheakpoint... +Epoch [1668/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9671], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670600891113281, 'Val/mean miou_metric': 0.9503461718559265, 'Val/mean f1': 0.9727541208267212, 'Val/mean precision': 0.972435474395752, 'Val/mean recall': 0.9730729460716248, 'Val/mean hd95_metric': 4.6961846351623535} +Epoch [1669/4000] Training [1/16] Loss: 0.00647 +Epoch [1669/4000] Training [2/16] Loss: 0.00587 +Epoch [1669/4000] Training [3/16] Loss: 0.00614 +Epoch [1669/4000] Training [4/16] Loss: 0.00781 +Epoch [1669/4000] Training [5/16] Loss: 0.00742 +Epoch [1669/4000] Training [6/16] Loss: 0.00776 +Epoch [1669/4000] Training [7/16] Loss: 0.00646 +Epoch [1669/4000] Training [8/16] Loss: 0.00873 +Epoch [1669/4000] Training [9/16] Loss: 0.00615 +Epoch [1669/4000] Training [10/16] Loss: 0.00587 +Epoch [1669/4000] Training [11/16] Loss: 0.00715 +Epoch [1669/4000] Training [12/16] Loss: 0.00787 +Epoch [1669/4000] Training [13/16] Loss: 0.00699 +Epoch [1669/4000] Training [14/16] Loss: 0.00743 +Epoch [1669/4000] Training [15/16] Loss: 0.00610 +Epoch [1669/4000] Training [16/16] Loss: 0.00782 +Epoch [1669/4000] Training metric {'Train/mean dice_metric': 0.9952332973480225, 'Train/mean miou_metric': 0.9902536273002625, 'Train/mean f1': 0.9909737706184387, 'Train/mean precision': 0.9863996505737305, 'Train/mean recall': 0.9955905079841614, 'Train/mean hd95_metric': 1.0259346961975098} +Epoch [1669/4000] Validation [1/4] Loss: 0.26370 focal_loss 0.19837 dice_loss 0.06533 +Epoch [1669/4000] Validation [2/4] Loss: 0.98907 focal_loss 0.67924 dice_loss 0.30982 +Epoch [1669/4000] Validation [3/4] Loss: 0.20214 focal_loss 0.13337 dice_loss 0.06877 +Epoch [1669/4000] Validation [4/4] Loss: 0.26730 focal_loss 0.15687 dice_loss 0.11043 +Epoch [1669/4000] Validation metric {'Val/mean dice_metric': 0.968920111656189, 'Val/mean miou_metric': 0.9523859024047852, 'Val/mean f1': 0.9732335805892944, 'Val/mean precision': 0.9709976315498352, 'Val/mean recall': 0.9754799604415894, 'Val/mean hd95_metric': 5.3516621589660645} +Cheakpoint... +Epoch [1669/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968920111656189, 'Val/mean miou_metric': 0.9523859024047852, 'Val/mean f1': 0.9732335805892944, 'Val/mean precision': 0.9709976315498352, 'Val/mean recall': 0.9754799604415894, 'Val/mean hd95_metric': 5.3516621589660645} +Epoch [1670/4000] Training [1/16] Loss: 0.00544 +Epoch [1670/4000] Training [2/16] Loss: 0.00785 +Epoch [1670/4000] Training [3/16] Loss: 0.00704 +Epoch [1670/4000] Training [4/16] Loss: 0.00527 +Epoch [1670/4000] Training [5/16] Loss: 0.00534 +Epoch [1670/4000] Training [6/16] Loss: 0.00880 +Epoch [1670/4000] Training [7/16] Loss: 0.00673 +Epoch [1670/4000] Training [8/16] Loss: 0.00771 +Epoch [1670/4000] Training [9/16] Loss: 0.00813 +Epoch [1670/4000] Training [10/16] Loss: 0.00788 +Epoch [1670/4000] Training [11/16] Loss: 0.00710 +Epoch [1670/4000] Training [12/16] Loss: 0.00930 +Epoch [1670/4000] Training [13/16] Loss: 0.00630 +Epoch [1670/4000] Training [14/16] Loss: 0.00613 +Epoch [1670/4000] Training [15/16] Loss: 0.00699 +Epoch [1670/4000] Training [16/16] Loss: 0.00779 +Epoch [1670/4000] Training metric {'Train/mean dice_metric': 0.995316207408905, 'Train/mean miou_metric': 0.9904090762138367, 'Train/mean f1': 0.9907442331314087, 'Train/mean precision': 0.9859921336174011, 'Train/mean recall': 0.9955422878265381, 'Train/mean hd95_metric': 1.0663065910339355} +Epoch [1670/4000] Validation [1/4] Loss: 0.21144 focal_loss 0.14798 dice_loss 0.06346 +Epoch [1670/4000] Validation [2/4] Loss: 0.46515 focal_loss 0.28399 dice_loss 0.18116 +Epoch [1670/4000] Validation [3/4] Loss: 0.16384 focal_loss 0.10590 dice_loss 0.05794 +Epoch [1670/4000] Validation [4/4] Loss: 0.33835 focal_loss 0.21809 dice_loss 0.12026 +Epoch [1670/4000] Validation metric {'Val/mean dice_metric': 0.9704826474189758, 'Val/mean miou_metric': 0.9537976980209351, 'Val/mean f1': 0.9734967947006226, 'Val/mean precision': 0.9712730646133423, 'Val/mean recall': 0.9757307171821594, 'Val/mean hd95_metric': 5.33994197845459} +Cheakpoint... +Epoch [1670/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704826474189758, 'Val/mean miou_metric': 0.9537976980209351, 'Val/mean f1': 0.9734967947006226, 'Val/mean precision': 0.9712730646133423, 'Val/mean recall': 0.9757307171821594, 'Val/mean hd95_metric': 5.33994197845459} +Epoch [1671/4000] Training [1/16] Loss: 0.00686 +Epoch [1671/4000] Training [2/16] Loss: 0.00573 +Epoch [1671/4000] Training [3/16] Loss: 0.00692 +Epoch [1671/4000] Training [4/16] Loss: 0.00643 +Epoch [1671/4000] Training [5/16] Loss: 0.01616 +Epoch [1671/4000] Training [6/16] Loss: 0.00565 +Epoch [1671/4000] Training [7/16] Loss: 0.00933 +Epoch [1671/4000] Training [8/16] Loss: 0.01042 +Epoch [1671/4000] Training [9/16] Loss: 0.00783 +Epoch [1671/4000] Training [10/16] Loss: 0.00891 +Epoch [1671/4000] Training [11/16] Loss: 0.00804 +Epoch [1671/4000] Training [12/16] Loss: 0.00749 +Epoch [1671/4000] Training [13/16] Loss: 0.00774 +Epoch [1671/4000] Training [14/16] Loss: 0.01214 +Epoch [1671/4000] Training [15/16] Loss: 0.00989 +Epoch [1671/4000] Training [16/16] Loss: 0.00793 +Epoch [1671/4000] Training metric {'Train/mean dice_metric': 0.9948128461837769, 'Train/mean miou_metric': 0.9894217252731323, 'Train/mean f1': 0.9905149936676025, 'Train/mean precision': 0.9856538772583008, 'Train/mean recall': 0.9954242706298828, 'Train/mean hd95_metric': 1.0380772352218628} +Epoch [1671/4000] Validation [1/4] Loss: 0.31342 focal_loss 0.22925 dice_loss 0.08417 +Epoch [1671/4000] Validation [2/4] Loss: 0.25502 focal_loss 0.14203 dice_loss 0.11299 +Epoch [1671/4000] Validation [3/4] Loss: 0.16386 focal_loss 0.10588 dice_loss 0.05799 +Epoch [1671/4000] Validation [4/4] Loss: 0.28227 focal_loss 0.17480 dice_loss 0.10747 +Epoch [1671/4000] Validation metric {'Val/mean dice_metric': 0.970241904258728, 'Val/mean miou_metric': 0.9529770016670227, 'Val/mean f1': 0.9733126759529114, 'Val/mean precision': 0.9721885323524475, 'Val/mean recall': 0.974439263343811, 'Val/mean hd95_metric': 5.534546375274658} +Cheakpoint... +Epoch [1671/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970241904258728, 'Val/mean miou_metric': 0.9529770016670227, 'Val/mean f1': 0.9733126759529114, 'Val/mean precision': 0.9721885323524475, 'Val/mean recall': 0.974439263343811, 'Val/mean hd95_metric': 5.534546375274658} +Epoch [1672/4000] Training [1/16] Loss: 0.00453 +Epoch [1672/4000] Training [2/16] Loss: 0.00630 +Epoch [1672/4000] Training [3/16] Loss: 0.00832 +Epoch [1672/4000] Training [4/16] Loss: 0.00811 +Epoch [1672/4000] Training [5/16] Loss: 0.00720 +Epoch [1672/4000] Training [6/16] Loss: 0.00727 +Epoch [1672/4000] Training [7/16] Loss: 0.00642 +Epoch [1672/4000] Training [8/16] Loss: 0.00633 +Epoch [1672/4000] Training [9/16] Loss: 0.01333 +Epoch [1672/4000] Training [10/16] Loss: 0.00902 +Epoch [1672/4000] Training [11/16] Loss: 0.00767 +Epoch [1672/4000] Training [12/16] Loss: 0.00687 +Epoch [1672/4000] Training [13/16] Loss: 0.00607 +Epoch [1672/4000] Training [14/16] Loss: 0.00629 +Epoch [1672/4000] Training [15/16] Loss: 0.00651 +Epoch [1672/4000] Training [16/16] Loss: 0.00876 +Epoch [1672/4000] Training metric {'Train/mean dice_metric': 0.9954055547714233, 'Train/mean miou_metric': 0.9906052947044373, 'Train/mean f1': 0.9913629293441772, 'Train/mean precision': 0.986839771270752, 'Train/mean recall': 0.9959277510643005, 'Train/mean hd95_metric': 1.0282777547836304} +Epoch [1672/4000] Validation [1/4] Loss: 0.71163 focal_loss 0.57190 dice_loss 0.13973 +Epoch [1672/4000] Validation [2/4] Loss: 0.29133 focal_loss 0.15608 dice_loss 0.13524 +Epoch [1672/4000] Validation [3/4] Loss: 0.15643 focal_loss 0.09556 dice_loss 0.06086 +Epoch [1672/4000] Validation [4/4] Loss: 0.25664 focal_loss 0.14487 dice_loss 0.11177 +Epoch [1672/4000] Validation metric {'Val/mean dice_metric': 0.9705021977424622, 'Val/mean miou_metric': 0.9536048769950867, 'Val/mean f1': 0.9720050692558289, 'Val/mean precision': 0.973210334777832, 'Val/mean recall': 0.970802903175354, 'Val/mean hd95_metric': 5.352864742279053} +Cheakpoint... +Epoch [1672/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705021977424622, 'Val/mean miou_metric': 0.9536048769950867, 'Val/mean f1': 0.9720050692558289, 'Val/mean precision': 0.973210334777832, 'Val/mean recall': 0.970802903175354, 'Val/mean hd95_metric': 5.352864742279053} +Epoch [1673/4000] Training [1/16] Loss: 0.00808 +Epoch [1673/4000] Training [2/16] Loss: 0.00949 +Epoch [1673/4000] Training [3/16] Loss: 0.00627 +Epoch [1673/4000] Training [4/16] Loss: 0.00627 +Epoch [1673/4000] Training [5/16] Loss: 0.00689 +Epoch [1673/4000] Training [6/16] Loss: 0.01242 +Epoch [1673/4000] Training [7/16] Loss: 0.00877 +Epoch [1673/4000] Training [8/16] Loss: 0.00543 +Epoch [1673/4000] Training [9/16] Loss: 0.01028 +Epoch [1673/4000] Training [10/16] Loss: 0.00642 +Epoch [1673/4000] Training [11/16] Loss: 0.00926 +Epoch [1673/4000] Training [12/16] Loss: 0.00682 +Epoch [1673/4000] Training [13/16] Loss: 0.00771 +Epoch [1673/4000] Training [14/16] Loss: 0.00640 +Epoch [1673/4000] Training [15/16] Loss: 0.00709 +Epoch [1673/4000] Training [16/16] Loss: 0.01068 +Epoch [1673/4000] Training metric {'Train/mean dice_metric': 0.9948275089263916, 'Train/mean miou_metric': 0.989422082901001, 'Train/mean f1': 0.989901602268219, 'Train/mean precision': 0.984604001045227, 'Train/mean recall': 0.9952564835548401, 'Train/mean hd95_metric': 1.0449683666229248} +Epoch [1673/4000] Validation [1/4] Loss: 0.27636 focal_loss 0.20916 dice_loss 0.06720 +Epoch [1673/4000] Validation [2/4] Loss: 0.26496 focal_loss 0.15001 dice_loss 0.11495 +Epoch [1673/4000] Validation [3/4] Loss: 0.15742 focal_loss 0.09848 dice_loss 0.05894 +Epoch [1673/4000] Validation [4/4] Loss: 0.25113 focal_loss 0.14630 dice_loss 0.10484 +Epoch [1673/4000] Validation metric {'Val/mean dice_metric': 0.9721843004226685, 'Val/mean miou_metric': 0.9550668001174927, 'Val/mean f1': 0.9727872014045715, 'Val/mean precision': 0.9707862734794617, 'Val/mean recall': 0.97479647397995, 'Val/mean hd95_metric': 5.9699201583862305} +Cheakpoint... +Epoch [1673/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721843004226685, 'Val/mean miou_metric': 0.9550668001174927, 'Val/mean f1': 0.9727872014045715, 'Val/mean precision': 0.9707862734794617, 'Val/mean recall': 0.97479647397995, 'Val/mean hd95_metric': 5.9699201583862305} +Epoch [1674/4000] Training [1/16] Loss: 0.00756 +Epoch [1674/4000] Training [2/16] Loss: 0.00970 +Epoch [1674/4000] Training [3/16] Loss: 0.00958 +Epoch [1674/4000] Training [4/16] Loss: 0.00690 +Epoch [1674/4000] Training [5/16] Loss: 0.00789 +Epoch [1674/4000] Training [6/16] Loss: 0.00648 +Epoch [1674/4000] Training [7/16] Loss: 0.00533 +Epoch [1674/4000] Training [8/16] Loss: 0.00713 +Epoch [1674/4000] Training [9/16] Loss: 0.00538 +Epoch [1674/4000] Training [10/16] Loss: 0.00573 +Epoch [1674/4000] Training [11/16] Loss: 0.00947 +Epoch [1674/4000] Training [12/16] Loss: 0.00853 +Epoch [1674/4000] Training [13/16] Loss: 0.00777 +Epoch [1674/4000] Training [14/16] Loss: 0.00727 +Epoch [1674/4000] Training [15/16] Loss: 0.00533 +Epoch [1674/4000] Training [16/16] Loss: 0.00733 +Epoch [1674/4000] Training metric {'Train/mean dice_metric': 0.9952284097671509, 'Train/mean miou_metric': 0.9902323484420776, 'Train/mean f1': 0.9909847378730774, 'Train/mean precision': 0.986350953578949, 'Train/mean recall': 0.995662271976471, 'Train/mean hd95_metric': 1.0234649181365967} +Epoch [1674/4000] Validation [1/4] Loss: 0.26864 focal_loss 0.19586 dice_loss 0.07278 +Epoch [1674/4000] Validation [2/4] Loss: 0.33846 focal_loss 0.17246 dice_loss 0.16600 +Epoch [1674/4000] Validation [3/4] Loss: 0.15701 focal_loss 0.09284 dice_loss 0.06416 +Epoch [1674/4000] Validation [4/4] Loss: 0.22901 focal_loss 0.14008 dice_loss 0.08894 +Epoch [1674/4000] Validation metric {'Val/mean dice_metric': 0.9711405038833618, 'Val/mean miou_metric': 0.9540046453475952, 'Val/mean f1': 0.973794162273407, 'Val/mean precision': 0.9715414643287659, 'Val/mean recall': 0.9760574698448181, 'Val/mean hd95_metric': 5.694061279296875} +Cheakpoint... +Epoch [1674/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711405038833618, 'Val/mean miou_metric': 0.9540046453475952, 'Val/mean f1': 0.973794162273407, 'Val/mean precision': 0.9715414643287659, 'Val/mean recall': 0.9760574698448181, 'Val/mean hd95_metric': 5.694061279296875} +Epoch [1675/4000] Training [1/16] Loss: 0.00685 +Epoch [1675/4000] Training [2/16] Loss: 0.00802 +Epoch [1675/4000] Training [3/16] Loss: 0.00753 +Epoch [1675/4000] Training [4/16] Loss: 0.00718 +Epoch [1675/4000] Training [5/16] Loss: 0.00726 +Epoch [1675/4000] Training [6/16] Loss: 0.00528 +Epoch [1675/4000] Training [7/16] Loss: 0.00793 +Epoch [1675/4000] Training [8/16] Loss: 0.00810 +Epoch [1675/4000] Training [9/16] Loss: 0.00839 +Epoch [1675/4000] Training [10/16] Loss: 0.00535 +Epoch [1675/4000] Training [11/16] Loss: 0.00638 +Epoch [1675/4000] Training [12/16] Loss: 0.00711 +Epoch [1675/4000] Training [13/16] Loss: 0.00702 +Epoch [1675/4000] Training [14/16] Loss: 0.00655 +Epoch [1675/4000] Training [15/16] Loss: 0.01362 +Epoch [1675/4000] Training [16/16] Loss: 0.00598 +Epoch [1675/4000] Training metric {'Train/mean dice_metric': 0.9950494170188904, 'Train/mean miou_metric': 0.9898918271064758, 'Train/mean f1': 0.9910776615142822, 'Train/mean precision': 0.9864784479141235, 'Train/mean recall': 0.9957199692726135, 'Train/mean hd95_metric': 1.1033189296722412} +Epoch [1675/4000] Validation [1/4] Loss: 0.25979 focal_loss 0.19148 dice_loss 0.06832 +Epoch [1675/4000] Validation [2/4] Loss: 0.28810 focal_loss 0.16285 dice_loss 0.12525 +Epoch [1675/4000] Validation [3/4] Loss: 0.22205 focal_loss 0.13371 dice_loss 0.08834 +Epoch [1675/4000] Validation [4/4] Loss: 0.26525 focal_loss 0.16395 dice_loss 0.10130 +Epoch [1675/4000] Validation metric {'Val/mean dice_metric': 0.9714983105659485, 'Val/mean miou_metric': 0.9542614221572876, 'Val/mean f1': 0.973395586013794, 'Val/mean precision': 0.9709103107452393, 'Val/mean recall': 0.9758938550949097, 'Val/mean hd95_metric': 5.864152908325195} +Cheakpoint... +Epoch [1675/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714983105659485, 'Val/mean miou_metric': 0.9542614221572876, 'Val/mean f1': 0.973395586013794, 'Val/mean precision': 0.9709103107452393, 'Val/mean recall': 0.9758938550949097, 'Val/mean hd95_metric': 5.864152908325195} +Epoch [1676/4000] Training [1/16] Loss: 0.00658 +Epoch [1676/4000] Training [2/16] Loss: 0.00504 +Epoch [1676/4000] Training [3/16] Loss: 0.00618 +Epoch [1676/4000] Training [4/16] Loss: 0.00641 +Epoch [1676/4000] Training [5/16] Loss: 0.00698 +Epoch [1676/4000] Training [6/16] Loss: 0.00770 +Epoch [1676/4000] Training [7/16] Loss: 0.00737 +Epoch [1676/4000] Training [8/16] Loss: 0.00587 +Epoch [1676/4000] Training [9/16] Loss: 0.00859 +Epoch [1676/4000] Training [10/16] Loss: 0.00686 +Epoch [1676/4000] Training [11/16] Loss: 0.00628 +Epoch [1676/4000] Training [12/16] Loss: 0.00837 +Epoch [1676/4000] Training [13/16] Loss: 0.00770 +Epoch [1676/4000] Training [14/16] Loss: 0.00915 +Epoch [1676/4000] Training [15/16] Loss: 0.00801 +Epoch [1676/4000] Training [16/16] Loss: 0.00919 +Epoch [1676/4000] Training metric {'Train/mean dice_metric': 0.9950752258300781, 'Train/mean miou_metric': 0.9899528622627258, 'Train/mean f1': 0.9910969138145447, 'Train/mean precision': 0.9865890145301819, 'Train/mean recall': 0.9956461787223816, 'Train/mean hd95_metric': 1.0510549545288086} +Epoch [1676/4000] Validation [1/4] Loss: 0.50374 focal_loss 0.39531 dice_loss 0.10843 +Epoch [1676/4000] Validation [2/4] Loss: 0.27443 focal_loss 0.13565 dice_loss 0.13878 +Epoch [1676/4000] Validation [3/4] Loss: 0.27758 focal_loss 0.17939 dice_loss 0.09818 +Epoch [1676/4000] Validation [4/4] Loss: 0.24563 focal_loss 0.14692 dice_loss 0.09871 +Epoch [1676/4000] Validation metric {'Val/mean dice_metric': 0.9722170829772949, 'Val/mean miou_metric': 0.9544395208358765, 'Val/mean f1': 0.9732956290245056, 'Val/mean precision': 0.9727585315704346, 'Val/mean recall': 0.9738332629203796, 'Val/mean hd95_metric': 5.977173805236816} +Cheakpoint... +Epoch [1676/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722170829772949, 'Val/mean miou_metric': 0.9544395208358765, 'Val/mean f1': 0.9732956290245056, 'Val/mean precision': 0.9727585315704346, 'Val/mean recall': 0.9738332629203796, 'Val/mean hd95_metric': 5.977173805236816} +Epoch [1677/4000] Training [1/16] Loss: 0.00693 +Epoch [1677/4000] Training [2/16] Loss: 0.01105 +Epoch [1677/4000] Training [3/16] Loss: 0.00649 +Epoch [1677/4000] Training [4/16] Loss: 0.00665 +Epoch [1677/4000] Training [5/16] Loss: 0.00818 +Epoch [1677/4000] Training [6/16] Loss: 0.00671 +Epoch [1677/4000] Training [7/16] Loss: 0.00850 +Epoch [1677/4000] Training [8/16] Loss: 0.00984 +Epoch [1677/4000] Training [9/16] Loss: 0.00606 +Epoch [1677/4000] Training [10/16] Loss: 0.00738 +Epoch [1677/4000] Training [11/16] Loss: 0.00704 +Epoch [1677/4000] Training [12/16] Loss: 0.00817 +Epoch [1677/4000] Training [13/16] Loss: 0.00608 +Epoch [1677/4000] Training [14/16] Loss: 0.00815 +Epoch [1677/4000] Training [15/16] Loss: 0.00855 +Epoch [1677/4000] Training [16/16] Loss: 0.00674 +Epoch [1677/4000] Training metric {'Train/mean dice_metric': 0.9947300553321838, 'Train/mean miou_metric': 0.9892675280570984, 'Train/mean f1': 0.9907992482185364, 'Train/mean precision': 0.9863309264183044, 'Train/mean recall': 0.9953081607818604, 'Train/mean hd95_metric': 1.0293009281158447} +Epoch [1677/4000] Validation [1/4] Loss: 0.24516 focal_loss 0.17916 dice_loss 0.06600 +Epoch [1677/4000] Validation [2/4] Loss: 0.28245 focal_loss 0.16156 dice_loss 0.12089 +Epoch [1677/4000] Validation [3/4] Loss: 0.20992 focal_loss 0.13126 dice_loss 0.07866 +Epoch [1677/4000] Validation [4/4] Loss: 0.24012 focal_loss 0.14077 dice_loss 0.09935 +Epoch [1677/4000] Validation metric {'Val/mean dice_metric': 0.9703973531723022, 'Val/mean miou_metric': 0.9536473155021667, 'Val/mean f1': 0.974051833152771, 'Val/mean precision': 0.9715457558631897, 'Val/mean recall': 0.9765710234642029, 'Val/mean hd95_metric': 5.122462749481201} +Cheakpoint... +Epoch [1677/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703973531723022, 'Val/mean miou_metric': 0.9536473155021667, 'Val/mean f1': 0.974051833152771, 'Val/mean precision': 0.9715457558631897, 'Val/mean recall': 0.9765710234642029, 'Val/mean hd95_metric': 5.122462749481201} +Epoch [1678/4000] Training [1/16] Loss: 0.01131 +Epoch [1678/4000] Training [2/16] Loss: 0.00568 +Epoch [1678/4000] Training [3/16] Loss: 0.00718 +Epoch [1678/4000] Training [4/16] Loss: 0.00823 +Epoch [1678/4000] Training [5/16] Loss: 0.00643 +Epoch [1678/4000] Training [6/16] Loss: 0.00717 +Epoch [1678/4000] Training [7/16] Loss: 0.00768 +Epoch [1678/4000] Training [8/16] Loss: 0.00596 +Epoch [1678/4000] Training [9/16] Loss: 0.00899 +Epoch [1678/4000] Training [10/16] Loss: 0.00696 +Epoch [1678/4000] Training [11/16] Loss: 0.00639 +Epoch [1678/4000] Training [12/16] Loss: 0.00771 +Epoch [1678/4000] Training [13/16] Loss: 0.01363 +Epoch [1678/4000] Training [14/16] Loss: 0.00615 +Epoch [1678/4000] Training [15/16] Loss: 0.00896 +Epoch [1678/4000] Training [16/16] Loss: 0.01262 +Epoch [1678/4000] Training metric {'Train/mean dice_metric': 0.9944645166397095, 'Train/mean miou_metric': 0.988767683506012, 'Train/mean f1': 0.989936351776123, 'Train/mean precision': 0.9852298498153687, 'Train/mean recall': 0.9946880340576172, 'Train/mean hd95_metric': 1.4351274967193604} +Epoch [1678/4000] Validation [1/4] Loss: 1.23083 focal_loss 1.02993 dice_loss 0.20090 +Epoch [1678/4000] Validation [2/4] Loss: 0.51396 focal_loss 0.31430 dice_loss 0.19966 +Epoch [1678/4000] Validation [3/4] Loss: 0.22795 focal_loss 0.15178 dice_loss 0.07617 +Epoch [1678/4000] Validation [4/4] Loss: 0.39339 focal_loss 0.27061 dice_loss 0.12278 +Epoch [1678/4000] Validation metric {'Val/mean dice_metric': 0.965114951133728, 'Val/mean miou_metric': 0.9471074938774109, 'Val/mean f1': 0.9664666056632996, 'Val/mean precision': 0.9708505272865295, 'Val/mean recall': 0.9621221423149109, 'Val/mean hd95_metric': 6.797503471374512} +Cheakpoint... +Epoch [1678/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965114951133728, 'Val/mean miou_metric': 0.9471074938774109, 'Val/mean f1': 0.9664666056632996, 'Val/mean precision': 0.9708505272865295, 'Val/mean recall': 0.9621221423149109, 'Val/mean hd95_metric': 6.797503471374512} +Epoch [1679/4000] Training [1/16] Loss: 0.00798 +Epoch [1679/4000] Training [2/16] Loss: 0.00707 +Epoch [1679/4000] Training [3/16] Loss: 0.00803 +Epoch [1679/4000] Training [4/16] Loss: 0.00807 +Epoch [1679/4000] Training [5/16] Loss: 0.01176 +Epoch [1679/4000] Training [6/16] Loss: 0.01170 +Epoch [1679/4000] Training [7/16] Loss: 0.11140 +Epoch [1679/4000] Training [8/16] Loss: 0.01910 +Epoch [1679/4000] Training [9/16] Loss: 0.00818 +Epoch [1679/4000] Training [10/16] Loss: 0.01293 +Epoch [1679/4000] Training [11/16] Loss: 0.00967 +Epoch [1679/4000] Training [12/16] Loss: 0.00650 +Epoch [1679/4000] Training [13/16] Loss: 0.00924 +Epoch [1679/4000] Training [14/16] Loss: 0.00846 +Epoch [1679/4000] Training [15/16] Loss: 0.00962 +Epoch [1679/4000] Training [16/16] Loss: 0.01071 +Epoch [1679/4000] Training metric {'Train/mean dice_metric': 0.9920875430107117, 'Train/mean miou_metric': 0.9845635890960693, 'Train/mean f1': 0.9864955544471741, 'Train/mean precision': 0.9843955039978027, 'Train/mean recall': 0.9886046051979065, 'Train/mean hd95_metric': 2.2723898887634277} +Epoch [1679/4000] Validation [1/4] Loss: 0.29029 focal_loss 0.21326 dice_loss 0.07704 +Epoch [1679/4000] Validation [2/4] Loss: 0.64999 focal_loss 0.39000 dice_loss 0.26000 +Epoch [1679/4000] Validation [3/4] Loss: 0.32913 focal_loss 0.22644 dice_loss 0.10269 +Epoch [1679/4000] Validation [4/4] Loss: 0.35250 focal_loss 0.21701 dice_loss 0.13549 +Epoch [1679/4000] Validation metric {'Val/mean dice_metric': 0.9669018983840942, 'Val/mean miou_metric': 0.9470196962356567, 'Val/mean f1': 0.967372715473175, 'Val/mean precision': 0.9633380174636841, 'Val/mean recall': 0.9714412689208984, 'Val/mean hd95_metric': 8.189718246459961} +Cheakpoint... +Epoch [1679/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9669], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9669018983840942, 'Val/mean miou_metric': 0.9470196962356567, 'Val/mean f1': 0.967372715473175, 'Val/mean precision': 0.9633380174636841, 'Val/mean recall': 0.9714412689208984, 'Val/mean hd95_metric': 8.189718246459961} +Epoch [1680/4000] Training [1/16] Loss: 0.00865 +Epoch [1680/4000] Training [2/16] Loss: 0.00878 +Epoch [1680/4000] Training [3/16] Loss: 0.00746 +Epoch [1680/4000] Training [4/16] Loss: 0.00919 +Epoch [1680/4000] Training [5/16] Loss: 0.01363 +Epoch [1680/4000] Training [6/16] Loss: 0.00892 +Epoch [1680/4000] Training [7/16] Loss: 0.01003 +Epoch [1680/4000] Training [8/16] Loss: 0.01098 +Epoch [1680/4000] Training [9/16] Loss: 0.00864 +Epoch [1680/4000] Training [10/16] Loss: 0.01003 +Epoch [1680/4000] Training [11/16] Loss: 0.00853 +Epoch [1680/4000] Training [12/16] Loss: 0.00744 +Epoch [1680/4000] Training [13/16] Loss: 0.00795 +Epoch [1680/4000] Training [14/16] Loss: 0.00762 +Epoch [1680/4000] Training [15/16] Loss: 0.00854 +Epoch [1680/4000] Training [16/16] Loss: 0.00918 +Epoch [1680/4000] Training metric {'Train/mean dice_metric': 0.9938175678253174, 'Train/mean miou_metric': 0.9875105619430542, 'Train/mean f1': 0.9900137782096863, 'Train/mean precision': 0.9853993058204651, 'Train/mean recall': 0.994671642780304, 'Train/mean hd95_metric': 1.5728304386138916} +Epoch [1680/4000] Validation [1/4] Loss: 0.33016 focal_loss 0.25072 dice_loss 0.07943 +Epoch [1680/4000] Validation [2/4] Loss: 0.51891 focal_loss 0.27466 dice_loss 0.24424 +Epoch [1680/4000] Validation [3/4] Loss: 0.15841 focal_loss 0.09443 dice_loss 0.06398 +Epoch [1680/4000] Validation [4/4] Loss: 0.23048 focal_loss 0.13142 dice_loss 0.09906 +Epoch [1680/4000] Validation metric {'Val/mean dice_metric': 0.9690815210342407, 'Val/mean miou_metric': 0.9501908421516418, 'Val/mean f1': 0.9702346324920654, 'Val/mean precision': 0.9672173261642456, 'Val/mean recall': 0.9732708930969238, 'Val/mean hd95_metric': 6.615979194641113} +Cheakpoint... +Epoch [1680/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690815210342407, 'Val/mean miou_metric': 0.9501908421516418, 'Val/mean f1': 0.9702346324920654, 'Val/mean precision': 0.9672173261642456, 'Val/mean recall': 0.9732708930969238, 'Val/mean hd95_metric': 6.615979194641113} +Epoch [1681/4000] Training [1/16] Loss: 0.00670 +Epoch [1681/4000] Training [2/16] Loss: 0.01057 +Epoch [1681/4000] Training [3/16] Loss: 0.00693 +Epoch [1681/4000] Training [4/16] Loss: 0.00931 +Epoch [1681/4000] Training [5/16] Loss: 0.00726 +Epoch [1681/4000] Training [6/16] Loss: 0.00667 +Epoch [1681/4000] Training [7/16] Loss: 0.00663 +Epoch [1681/4000] Training [8/16] Loss: 0.01008 +Epoch [1681/4000] Training [9/16] Loss: 0.00593 +Epoch [1681/4000] Training [10/16] Loss: 0.00597 +Epoch [1681/4000] Training [11/16] Loss: 0.00857 +Epoch [1681/4000] Training [12/16] Loss: 0.00699 +Epoch [1681/4000] Training [13/16] Loss: 0.00579 +Epoch [1681/4000] Training [14/16] Loss: 0.00754 +Epoch [1681/4000] Training [15/16] Loss: 0.00628 +Epoch [1681/4000] Training [16/16] Loss: 0.01024 +Epoch [1681/4000] Training metric {'Train/mean dice_metric': 0.9948561191558838, 'Train/mean miou_metric': 0.9895105957984924, 'Train/mean f1': 0.9905827045440674, 'Train/mean precision': 0.9861421585083008, 'Train/mean recall': 0.9950633645057678, 'Train/mean hd95_metric': 1.0869840383529663} +Epoch [1681/4000] Validation [1/4] Loss: 0.24340 focal_loss 0.18163 dice_loss 0.06177 +Epoch [1681/4000] Validation [2/4] Loss: 0.37050 focal_loss 0.20250 dice_loss 0.16800 +Epoch [1681/4000] Validation [3/4] Loss: 0.31635 focal_loss 0.22222 dice_loss 0.09414 +Epoch [1681/4000] Validation [4/4] Loss: 0.35591 focal_loss 0.21071 dice_loss 0.14520 +Epoch [1681/4000] Validation metric {'Val/mean dice_metric': 0.973228931427002, 'Val/mean miou_metric': 0.9556461572647095, 'Val/mean f1': 0.9742102026939392, 'Val/mean precision': 0.9700316190719604, 'Val/mean recall': 0.9784249663352966, 'Val/mean hd95_metric': 5.8618483543396} +Cheakpoint... +Epoch [1681/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973228931427002, 'Val/mean miou_metric': 0.9556461572647095, 'Val/mean f1': 0.9742102026939392, 'Val/mean precision': 0.9700316190719604, 'Val/mean recall': 0.9784249663352966, 'Val/mean hd95_metric': 5.8618483543396} +Epoch [1682/4000] Training [1/16] Loss: 0.00922 +Epoch [1682/4000] Training [2/16] Loss: 0.00673 +Epoch [1682/4000] Training [3/16] Loss: 0.00893 +Epoch [1682/4000] Training [4/16] Loss: 0.00849 +Epoch [1682/4000] Training [5/16] Loss: 0.00614 +Epoch [1682/4000] Training [6/16] Loss: 0.00784 +Epoch [1682/4000] Training [7/16] Loss: 0.00753 +Epoch [1682/4000] Training [8/16] Loss: 0.00825 +Epoch [1682/4000] Training [9/16] Loss: 0.00618 +Epoch [1682/4000] Training [10/16] Loss: 0.00765 +Epoch [1682/4000] Training [11/16] Loss: 0.00693 +Epoch [1682/4000] Training [12/16] Loss: 0.00872 +Epoch [1682/4000] Training [13/16] Loss: 0.00563 +Epoch [1682/4000] Training [14/16] Loss: 0.00827 +Epoch [1682/4000] Training [15/16] Loss: 0.00573 +Epoch [1682/4000] Training [16/16] Loss: 0.00887 +Epoch [1682/4000] Training metric {'Train/mean dice_metric': 0.9948872327804565, 'Train/mean miou_metric': 0.9895841479301453, 'Train/mean f1': 0.9907870888710022, 'Train/mean precision': 0.9862284064292908, 'Train/mean recall': 0.9953881502151489, 'Train/mean hd95_metric': 1.0676004886627197} +Epoch [1682/4000] Validation [1/4] Loss: 0.39137 focal_loss 0.30286 dice_loss 0.08851 +Epoch [1682/4000] Validation [2/4] Loss: 0.46449 focal_loss 0.29915 dice_loss 0.16533 +Epoch [1682/4000] Validation [3/4] Loss: 0.28072 focal_loss 0.18593 dice_loss 0.09479 +Epoch [1682/4000] Validation [4/4] Loss: 0.25038 focal_loss 0.13691 dice_loss 0.11346 +Epoch [1682/4000] Validation metric {'Val/mean dice_metric': 0.9718044400215149, 'Val/mean miou_metric': 0.9534422159194946, 'Val/mean f1': 0.9718713760375977, 'Val/mean precision': 0.9677980542182922, 'Val/mean recall': 0.9759792685508728, 'Val/mean hd95_metric': 6.280551910400391} +Cheakpoint... +Epoch [1682/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718044400215149, 'Val/mean miou_metric': 0.9534422159194946, 'Val/mean f1': 0.9718713760375977, 'Val/mean precision': 0.9677980542182922, 'Val/mean recall': 0.9759792685508728, 'Val/mean hd95_metric': 6.280551910400391} +Epoch [1683/4000] Training [1/16] Loss: 0.00762 +Epoch [1683/4000] Training [2/16] Loss: 0.01013 +Epoch [1683/4000] Training [3/16] Loss: 0.00784 +Epoch [1683/4000] Training [4/16] Loss: 0.00669 +Epoch [1683/4000] Training [5/16] Loss: 0.00832 +Epoch [1683/4000] Training [6/16] Loss: 0.00708 +Epoch [1683/4000] Training [7/16] Loss: 0.00571 +Epoch [1683/4000] Training [8/16] Loss: 0.00675 +Epoch [1683/4000] Training [9/16] Loss: 0.00758 +Epoch [1683/4000] Training [10/16] Loss: 0.00700 +Epoch [1683/4000] Training [11/16] Loss: 0.00658 +Epoch [1683/4000] Training [12/16] Loss: 0.00796 +Epoch [1683/4000] Training [13/16] Loss: 0.00809 +Epoch [1683/4000] Training [14/16] Loss: 0.00812 +Epoch [1683/4000] Training [15/16] Loss: 0.00947 +Epoch [1683/4000] Training [16/16] Loss: 0.00635 +Epoch [1683/4000] Training metric {'Train/mean dice_metric': 0.9946606159210205, 'Train/mean miou_metric': 0.9891364574432373, 'Train/mean f1': 0.9906968474388123, 'Train/mean precision': 0.9860943555831909, 'Train/mean recall': 0.995342493057251, 'Train/mean hd95_metric': 1.3104822635650635} +Epoch [1683/4000] Validation [1/4] Loss: 0.25145 focal_loss 0.18353 dice_loss 0.06791 +Epoch [1683/4000] Validation [2/4] Loss: 0.60637 focal_loss 0.37488 dice_loss 0.23149 +Epoch [1683/4000] Validation [3/4] Loss: 0.29897 focal_loss 0.20786 dice_loss 0.09111 +Epoch [1683/4000] Validation [4/4] Loss: 0.31472 focal_loss 0.18364 dice_loss 0.13108 +Epoch [1683/4000] Validation metric {'Val/mean dice_metric': 0.9723626971244812, 'Val/mean miou_metric': 0.9546235799789429, 'Val/mean f1': 0.973789393901825, 'Val/mean precision': 0.9705137610435486, 'Val/mean recall': 0.977087140083313, 'Val/mean hd95_metric': 5.792595863342285} +Cheakpoint... +Epoch [1683/4000] best acc:tensor([0.9743], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723626971244812, 'Val/mean miou_metric': 0.9546235799789429, 'Val/mean f1': 0.973789393901825, 'Val/mean precision': 0.9705137610435486, 'Val/mean recall': 0.977087140083313, 'Val/mean hd95_metric': 5.792595863342285} +Epoch [1684/4000] Training [1/16] Loss: 0.00664 +Epoch [1684/4000] Training [2/16] Loss: 0.00784 +Epoch [1684/4000] Training [3/16] Loss: 0.00596 +Epoch [1684/4000] Training [4/16] Loss: 0.00871 +Epoch [1684/4000] Training [5/16] Loss: 0.00483 +Epoch [1684/4000] Training [6/16] Loss: 0.00640 +Epoch [1684/4000] Training [7/16] Loss: 0.00645 +Epoch [1684/4000] Training [8/16] Loss: 0.00751 +Epoch [1684/4000] Training [9/16] Loss: 0.00677 +Epoch [1684/4000] Training [10/16] Loss: 0.00448 +Epoch [1684/4000] Training [11/16] Loss: 0.00831 +Epoch [1684/4000] Training [12/16] Loss: 0.00614 +Epoch [1684/4000] Training [13/16] Loss: 0.00538 +Epoch [1684/4000] Training [14/16] Loss: 0.00545 +Epoch [1684/4000] Training [15/16] Loss: 0.00449 +Epoch [1684/4000] Training [16/16] Loss: 0.00585 +Epoch [1684/4000] Training metric {'Train/mean dice_metric': 0.9959174990653992, 'Train/mean miou_metric': 0.9916054010391235, 'Train/mean f1': 0.9915304780006409, 'Train/mean precision': 0.9868975877761841, 'Train/mean recall': 0.9962071180343628, 'Train/mean hd95_metric': 1.0098663568496704} +Epoch [1684/4000] Validation [1/4] Loss: 0.27127 focal_loss 0.20200 dice_loss 0.06927 +Epoch [1684/4000] Validation [2/4] Loss: 0.43334 focal_loss 0.26353 dice_loss 0.16982 +Epoch [1684/4000] Validation [3/4] Loss: 0.22869 focal_loss 0.14143 dice_loss 0.08726 +Epoch [1684/4000] Validation [4/4] Loss: 0.24286 focal_loss 0.13680 dice_loss 0.10606 +Epoch [1684/4000] Validation metric {'Val/mean dice_metric': 0.974490761756897, 'Val/mean miou_metric': 0.9578000903129578, 'Val/mean f1': 0.9749509692192078, 'Val/mean precision': 0.9714872241020203, 'Val/mean recall': 0.978439450263977, 'Val/mean hd95_metric': 5.673511505126953} +Cheakpoint... +Epoch [1684/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974490761756897, 'Val/mean miou_metric': 0.9578000903129578, 'Val/mean f1': 0.9749509692192078, 'Val/mean precision': 0.9714872241020203, 'Val/mean recall': 0.978439450263977, 'Val/mean hd95_metric': 5.673511505126953} +Epoch [1685/4000] Training [1/16] Loss: 0.00733 +Epoch [1685/4000] Training [2/16] Loss: 0.00678 +Epoch [1685/4000] Training [3/16] Loss: 0.00616 +Epoch [1685/4000] Training [4/16] Loss: 0.00568 +Epoch [1685/4000] Training [5/16] Loss: 0.00617 +Epoch [1685/4000] Training [6/16] Loss: 0.00893 +Epoch [1685/4000] Training [7/16] Loss: 0.00680 +Epoch [1685/4000] Training [8/16] Loss: 0.00568 +Epoch [1685/4000] Training [9/16] Loss: 0.00613 +Epoch [1685/4000] Training [10/16] Loss: 0.00562 +Epoch [1685/4000] Training [11/16] Loss: 0.00641 +Epoch [1685/4000] Training [12/16] Loss: 0.00732 +Epoch [1685/4000] Training [13/16] Loss: 0.00668 +Epoch [1685/4000] Training [14/16] Loss: 0.00757 +Epoch [1685/4000] Training [15/16] Loss: 0.00715 +Epoch [1685/4000] Training [16/16] Loss: 0.00668 +Epoch [1685/4000] Training metric {'Train/mean dice_metric': 0.9955528974533081, 'Train/mean miou_metric': 0.9908825159072876, 'Train/mean f1': 0.9912845492362976, 'Train/mean precision': 0.9866164326667786, 'Train/mean recall': 0.9959970116615295, 'Train/mean hd95_metric': 1.0134015083312988} +Epoch [1685/4000] Validation [1/4] Loss: 0.27052 focal_loss 0.19906 dice_loss 0.07147 +Epoch [1685/4000] Validation [2/4] Loss: 0.46183 focal_loss 0.28686 dice_loss 0.17496 +Epoch [1685/4000] Validation [3/4] Loss: 0.34246 focal_loss 0.23826 dice_loss 0.10420 +Epoch [1685/4000] Validation [4/4] Loss: 0.23806 focal_loss 0.13030 dice_loss 0.10776 +Epoch [1685/4000] Validation metric {'Val/mean dice_metric': 0.9735304117202759, 'Val/mean miou_metric': 0.9564123153686523, 'Val/mean f1': 0.9745458960533142, 'Val/mean precision': 0.9714942574501038, 'Val/mean recall': 0.9776167273521423, 'Val/mean hd95_metric': 5.651289463043213} +Cheakpoint... +Epoch [1685/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735304117202759, 'Val/mean miou_metric': 0.9564123153686523, 'Val/mean f1': 0.9745458960533142, 'Val/mean precision': 0.9714942574501038, 'Val/mean recall': 0.9776167273521423, 'Val/mean hd95_metric': 5.651289463043213} +Epoch [1686/4000] Training [1/16] Loss: 0.00648 +Epoch [1686/4000] Training [2/16] Loss: 0.00641 +Epoch [1686/4000] Training [3/16] Loss: 0.00547 +Epoch [1686/4000] Training [4/16] Loss: 0.00573 +Epoch [1686/4000] Training [5/16] Loss: 0.00900 +Epoch [1686/4000] Training [6/16] Loss: 0.00576 +Epoch [1686/4000] Training [7/16] Loss: 0.00575 +Epoch [1686/4000] Training [8/16] Loss: 0.00718 +Epoch [1686/4000] Training [9/16] Loss: 0.00704 +Epoch [1686/4000] Training [10/16] Loss: 0.00834 +Epoch [1686/4000] Training [11/16] Loss: 0.00558 +Epoch [1686/4000] Training [12/16] Loss: 0.00917 +Epoch [1686/4000] Training [13/16] Loss: 0.00569 +Epoch [1686/4000] Training [14/16] Loss: 0.00810 +Epoch [1686/4000] Training [15/16] Loss: 0.00634 +Epoch [1686/4000] Training [16/16] Loss: 0.00668 +Epoch [1686/4000] Training metric {'Train/mean dice_metric': 0.9955422282218933, 'Train/mean miou_metric': 0.9908692836761475, 'Train/mean f1': 0.9914343953132629, 'Train/mean precision': 0.986953616142273, 'Train/mean recall': 0.9959560632705688, 'Train/mean hd95_metric': 1.0272860527038574} +Epoch [1686/4000] Validation [1/4] Loss: 0.26452 focal_loss 0.19753 dice_loss 0.06699 +Epoch [1686/4000] Validation [2/4] Loss: 0.32547 focal_loss 0.18224 dice_loss 0.14323 +Epoch [1686/4000] Validation [3/4] Loss: 0.19646 focal_loss 0.12288 dice_loss 0.07358 +Epoch [1686/4000] Validation [4/4] Loss: 0.27479 focal_loss 0.14957 dice_loss 0.12522 +Epoch [1686/4000] Validation metric {'Val/mean dice_metric': 0.9742766618728638, 'Val/mean miou_metric': 0.9574225544929504, 'Val/mean f1': 0.9756631255149841, 'Val/mean precision': 0.9726710915565491, 'Val/mean recall': 0.9786736369132996, 'Val/mean hd95_metric': 5.523026943206787} +Cheakpoint... +Epoch [1686/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742766618728638, 'Val/mean miou_metric': 0.9574225544929504, 'Val/mean f1': 0.9756631255149841, 'Val/mean precision': 0.9726710915565491, 'Val/mean recall': 0.9786736369132996, 'Val/mean hd95_metric': 5.523026943206787} +Epoch [1687/4000] Training [1/16] Loss: 0.00605 +Epoch [1687/4000] Training [2/16] Loss: 0.00702 +Epoch [1687/4000] Training [3/16] Loss: 0.00559 +Epoch [1687/4000] Training [4/16] Loss: 0.00634 +Epoch [1687/4000] Training [5/16] Loss: 0.00560 +Epoch [1687/4000] Training [6/16] Loss: 0.00602 +Epoch [1687/4000] Training [7/16] Loss: 0.00716 +Epoch [1687/4000] Training [8/16] Loss: 0.00667 +Epoch [1687/4000] Training [9/16] Loss: 0.00583 +Epoch [1687/4000] Training [10/16] Loss: 0.00663 +Epoch [1687/4000] Training [11/16] Loss: 0.00620 +Epoch [1687/4000] Training [12/16] Loss: 0.00726 +Epoch [1687/4000] Training [13/16] Loss: 0.00713 +Epoch [1687/4000] Training [14/16] Loss: 0.00583 +Epoch [1687/4000] Training [15/16] Loss: 0.00895 +Epoch [1687/4000] Training [16/16] Loss: 0.00506 +Epoch [1687/4000] Training metric {'Train/mean dice_metric': 0.9954698085784912, 'Train/mean miou_metric': 0.990720272064209, 'Train/mean f1': 0.991287887096405, 'Train/mean precision': 0.9868634939193726, 'Train/mean recall': 0.995752215385437, 'Train/mean hd95_metric': 1.0070159435272217} +Epoch [1687/4000] Validation [1/4] Loss: 0.26471 focal_loss 0.19357 dice_loss 0.07114 +Epoch [1687/4000] Validation [2/4] Loss: 0.43918 focal_loss 0.27418 dice_loss 0.16499 +Epoch [1687/4000] Validation [3/4] Loss: 0.35678 focal_loss 0.25534 dice_loss 0.10144 +Epoch [1687/4000] Validation [4/4] Loss: 0.26434 focal_loss 0.15100 dice_loss 0.11334 +Epoch [1687/4000] Validation metric {'Val/mean dice_metric': 0.9736258387565613, 'Val/mean miou_metric': 0.9562411308288574, 'Val/mean f1': 0.9738777875900269, 'Val/mean precision': 0.9682148098945618, 'Val/mean recall': 0.9796074032783508, 'Val/mean hd95_metric': 6.024161338806152} +Cheakpoint... +Epoch [1687/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736258387565613, 'Val/mean miou_metric': 0.9562411308288574, 'Val/mean f1': 0.9738777875900269, 'Val/mean precision': 0.9682148098945618, 'Val/mean recall': 0.9796074032783508, 'Val/mean hd95_metric': 6.024161338806152} +Epoch [1688/4000] Training [1/16] Loss: 0.00994 +Epoch [1688/4000] Training [2/16] Loss: 0.00714 +Epoch [1688/4000] Training [3/16] Loss: 0.00571 +Epoch [1688/4000] Training [4/16] Loss: 0.00654 +Epoch [1688/4000] Training [5/16] Loss: 0.00715 +Epoch [1688/4000] Training [6/16] Loss: 0.00528 +Epoch [1688/4000] Training [7/16] Loss: 0.00628 +Epoch [1688/4000] Training [8/16] Loss: 0.00889 +Epoch [1688/4000] Training [9/16] Loss: 0.00721 +Epoch [1688/4000] Training [10/16] Loss: 0.01000 +Epoch [1688/4000] Training [11/16] Loss: 0.00805 +Epoch [1688/4000] Training [12/16] Loss: 0.00672 +Epoch [1688/4000] Training [13/16] Loss: 0.00682 +Epoch [1688/4000] Training [14/16] Loss: 0.00656 +Epoch [1688/4000] Training [15/16] Loss: 0.00647 +Epoch [1688/4000] Training [16/16] Loss: 0.00518 +Epoch [1688/4000] Training metric {'Train/mean dice_metric': 0.9951011538505554, 'Train/mean miou_metric': 0.989989161491394, 'Train/mean f1': 0.9909041523933411, 'Train/mean precision': 0.9861790537834167, 'Train/mean recall': 0.995674729347229, 'Train/mean hd95_metric': 1.0391696691513062} +Epoch [1688/4000] Validation [1/4] Loss: 0.24337 focal_loss 0.17653 dice_loss 0.06684 +Epoch [1688/4000] Validation [2/4] Loss: 0.45384 focal_loss 0.29350 dice_loss 0.16034 +Epoch [1688/4000] Validation [3/4] Loss: 0.21075 focal_loss 0.13117 dice_loss 0.07958 +Epoch [1688/4000] Validation [4/4] Loss: 0.27147 focal_loss 0.14714 dice_loss 0.12433 +Epoch [1688/4000] Validation metric {'Val/mean dice_metric': 0.972516655921936, 'Val/mean miou_metric': 0.9553871154785156, 'Val/mean f1': 0.9744881391525269, 'Val/mean precision': 0.9693618416786194, 'Val/mean recall': 0.9796690940856934, 'Val/mean hd95_metric': 5.91271448135376} +Cheakpoint... +Epoch [1688/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972516655921936, 'Val/mean miou_metric': 0.9553871154785156, 'Val/mean f1': 0.9744881391525269, 'Val/mean precision': 0.9693618416786194, 'Val/mean recall': 0.9796690940856934, 'Val/mean hd95_metric': 5.91271448135376} +Epoch [1689/4000] Training [1/16] Loss: 0.00638 +Epoch [1689/4000] Training [2/16] Loss: 0.00788 +Epoch [1689/4000] Training [3/16] Loss: 0.00739 +Epoch [1689/4000] Training [4/16] Loss: 0.00515 +Epoch [1689/4000] Training [5/16] Loss: 0.00831 +Epoch [1689/4000] Training [6/16] Loss: 0.00699 +Epoch [1689/4000] Training [7/16] Loss: 0.00617 +Epoch [1689/4000] Training [8/16] Loss: 0.00644 +Epoch [1689/4000] Training [9/16] Loss: 0.00863 +Epoch [1689/4000] Training [10/16] Loss: 0.00772 +Epoch [1689/4000] Training [11/16] Loss: 0.00605 +Epoch [1689/4000] Training [12/16] Loss: 0.00899 +Epoch [1689/4000] Training [13/16] Loss: 0.00746 +Epoch [1689/4000] Training [14/16] Loss: 0.00836 +Epoch [1689/4000] Training [15/16] Loss: 0.00654 +Epoch [1689/4000] Training [16/16] Loss: 0.00783 +Epoch [1689/4000] Training metric {'Train/mean dice_metric': 0.9952336549758911, 'Train/mean miou_metric': 0.9902586936950684, 'Train/mean f1': 0.9911525845527649, 'Train/mean precision': 0.9867250323295593, 'Train/mean recall': 0.9956200122833252, 'Train/mean hd95_metric': 1.0464222431182861} +Epoch [1689/4000] Validation [1/4] Loss: 0.24880 focal_loss 0.17939 dice_loss 0.06941 +Epoch [1689/4000] Validation [2/4] Loss: 0.25505 focal_loss 0.14825 dice_loss 0.10680 +Epoch [1689/4000] Validation [3/4] Loss: 0.18605 focal_loss 0.12022 dice_loss 0.06583 +Epoch [1689/4000] Validation [4/4] Loss: 0.35302 focal_loss 0.22049 dice_loss 0.13253 +Epoch [1689/4000] Validation metric {'Val/mean dice_metric': 0.9735563397407532, 'Val/mean miou_metric': 0.9563051462173462, 'Val/mean f1': 0.9742757678031921, 'Val/mean precision': 0.9699559807777405, 'Val/mean recall': 0.978634238243103, 'Val/mean hd95_metric': 5.839227199554443} +Cheakpoint... +Epoch [1689/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735563397407532, 'Val/mean miou_metric': 0.9563051462173462, 'Val/mean f1': 0.9742757678031921, 'Val/mean precision': 0.9699559807777405, 'Val/mean recall': 0.978634238243103, 'Val/mean hd95_metric': 5.839227199554443} +Epoch [1690/4000] Training [1/16] Loss: 0.00753 +Epoch [1690/4000] Training [2/16] Loss: 0.00866 +Epoch [1690/4000] Training [3/16] Loss: 0.00665 +Epoch [1690/4000] Training [4/16] Loss: 0.00715 +Epoch [1690/4000] Training [5/16] Loss: 0.00708 +Epoch [1690/4000] Training [6/16] Loss: 0.00700 +Epoch [1690/4000] Training [7/16] Loss: 0.01063 +Epoch [1690/4000] Training [8/16] Loss: 0.00552 +Epoch [1690/4000] Training [9/16] Loss: 0.01113 +Epoch [1690/4000] Training [10/16] Loss: 0.00727 +Epoch [1690/4000] Training [11/16] Loss: 0.00694 +Epoch [1690/4000] Training [12/16] Loss: 0.00762 +Epoch [1690/4000] Training [13/16] Loss: 0.00867 +Epoch [1690/4000] Training [14/16] Loss: 0.01032 +Epoch [1690/4000] Training [15/16] Loss: 0.00746 +Epoch [1690/4000] Training [16/16] Loss: 0.00728 +Epoch [1690/4000] Training metric {'Train/mean dice_metric': 0.994545578956604, 'Train/mean miou_metric': 0.9889517426490784, 'Train/mean f1': 0.9902775287628174, 'Train/mean precision': 0.985508143901825, 'Train/mean recall': 0.9950932860374451, 'Train/mean hd95_metric': 1.1274588108062744} +Epoch [1690/4000] Validation [1/4] Loss: 1.31400 focal_loss 1.11072 dice_loss 0.20328 +Epoch [1690/4000] Validation [2/4] Loss: 0.31436 focal_loss 0.19774 dice_loss 0.11662 +Epoch [1690/4000] Validation [3/4] Loss: 0.36544 focal_loss 0.26161 dice_loss 0.10383 +Epoch [1690/4000] Validation [4/4] Loss: 0.30246 focal_loss 0.17842 dice_loss 0.12404 +Epoch [1690/4000] Validation metric {'Val/mean dice_metric': 0.9692190289497375, 'Val/mean miou_metric': 0.9502643346786499, 'Val/mean f1': 0.9692195057868958, 'Val/mean precision': 0.9703941941261292, 'Val/mean recall': 0.9680476188659668, 'Val/mean hd95_metric': 6.6984686851501465} +Cheakpoint... +Epoch [1690/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692190289497375, 'Val/mean miou_metric': 0.9502643346786499, 'Val/mean f1': 0.9692195057868958, 'Val/mean precision': 0.9703941941261292, 'Val/mean recall': 0.9680476188659668, 'Val/mean hd95_metric': 6.6984686851501465} +Epoch [1691/4000] Training [1/16] Loss: 0.00875 +Epoch [1691/4000] Training [2/16] Loss: 0.00491 +Epoch [1691/4000] Training [3/16] Loss: 0.00651 +Epoch [1691/4000] Training [4/16] Loss: 0.00625 +Epoch [1691/4000] Training [5/16] Loss: 0.00886 +Epoch [1691/4000] Training [6/16] Loss: 0.00596 +Epoch [1691/4000] Training [7/16] Loss: 0.00854 +Epoch [1691/4000] Training [8/16] Loss: 0.00789 +Epoch [1691/4000] Training [9/16] Loss: 0.00677 +Epoch [1691/4000] Training [10/16] Loss: 0.00921 +Epoch [1691/4000] Training [11/16] Loss: 0.00663 +Epoch [1691/4000] Training [12/16] Loss: 0.00896 +Epoch [1691/4000] Training [13/16] Loss: 0.00770 +Epoch [1691/4000] Training [14/16] Loss: 0.00839 +Epoch [1691/4000] Training [15/16] Loss: 0.00743 +Epoch [1691/4000] Training [16/16] Loss: 0.00896 +Epoch [1691/4000] Training metric {'Train/mean dice_metric': 0.9947704076766968, 'Train/mean miou_metric': 0.9893432259559631, 'Train/mean f1': 0.9907673001289368, 'Train/mean precision': 0.9860544204711914, 'Train/mean recall': 0.9955254793167114, 'Train/mean hd95_metric': 1.447867751121521} +Epoch [1691/4000] Validation [1/4] Loss: 0.30022 focal_loss 0.22008 dice_loss 0.08014 +Epoch [1691/4000] Validation [2/4] Loss: 0.29351 focal_loss 0.17829 dice_loss 0.11522 +Epoch [1691/4000] Validation [3/4] Loss: 0.32347 focal_loss 0.23286 dice_loss 0.09061 +Epoch [1691/4000] Validation [4/4] Loss: 0.20192 focal_loss 0.11177 dice_loss 0.09015 +Epoch [1691/4000] Validation metric {'Val/mean dice_metric': 0.9717052578926086, 'Val/mean miou_metric': 0.9542018175125122, 'Val/mean f1': 0.9740769863128662, 'Val/mean precision': 0.971060037612915, 'Val/mean recall': 0.9771127700805664, 'Val/mean hd95_metric': 6.180241584777832} +Cheakpoint... +Epoch [1691/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717052578926086, 'Val/mean miou_metric': 0.9542018175125122, 'Val/mean f1': 0.9740769863128662, 'Val/mean precision': 0.971060037612915, 'Val/mean recall': 0.9771127700805664, 'Val/mean hd95_metric': 6.180241584777832} +Epoch [1692/4000] Training [1/16] Loss: 0.00644 +Epoch [1692/4000] Training [2/16] Loss: 0.00877 +Epoch [1692/4000] Training [3/16] Loss: 0.00670 +Epoch [1692/4000] Training [4/16] Loss: 0.00773 +Epoch [1692/4000] Training [5/16] Loss: 0.00699 +Epoch [1692/4000] Training [6/16] Loss: 0.00611 +Epoch [1692/4000] Training [7/16] Loss: 0.00710 +Epoch [1692/4000] Training [8/16] Loss: 0.00737 +Epoch [1692/4000] Training [9/16] Loss: 0.00659 +Epoch [1692/4000] Training [10/16] Loss: 0.00722 +Epoch [1692/4000] Training [11/16] Loss: 0.00834 +Epoch [1692/4000] Training [12/16] Loss: 0.00612 +Epoch [1692/4000] Training [13/16] Loss: 0.00973 +Epoch [1692/4000] Training [14/16] Loss: 0.00780 +Epoch [1692/4000] Training [15/16] Loss: 0.00769 +Epoch [1692/4000] Training [16/16] Loss: 0.00656 +Epoch [1692/4000] Training metric {'Train/mean dice_metric': 0.9951792359352112, 'Train/mean miou_metric': 0.9901385307312012, 'Train/mean f1': 0.9909352660179138, 'Train/mean precision': 0.986303448677063, 'Train/mean recall': 0.9956107139587402, 'Train/mean hd95_metric': 1.0766682624816895} +Epoch [1692/4000] Validation [1/4] Loss: 0.24640 focal_loss 0.18442 dice_loss 0.06198 +Epoch [1692/4000] Validation [2/4] Loss: 0.47052 focal_loss 0.28899 dice_loss 0.18153 +Epoch [1692/4000] Validation [3/4] Loss: 0.29110 focal_loss 0.20342 dice_loss 0.08769 +Epoch [1692/4000] Validation [4/4] Loss: 0.39087 focal_loss 0.24326 dice_loss 0.14761 +Epoch [1692/4000] Validation metric {'Val/mean dice_metric': 0.9723604321479797, 'Val/mean miou_metric': 0.9554117321968079, 'Val/mean f1': 0.9745829701423645, 'Val/mean precision': 0.9691145420074463, 'Val/mean recall': 0.9801135659217834, 'Val/mean hd95_metric': 6.076104640960693} +Cheakpoint... +Epoch [1692/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723604321479797, 'Val/mean miou_metric': 0.9554117321968079, 'Val/mean f1': 0.9745829701423645, 'Val/mean precision': 0.9691145420074463, 'Val/mean recall': 0.9801135659217834, 'Val/mean hd95_metric': 6.076104640960693} +Epoch [1693/4000] Training [1/16] Loss: 0.00741 +Epoch [1693/4000] Training [2/16] Loss: 0.00631 +Epoch [1693/4000] Training [3/16] Loss: 0.00536 +Epoch [1693/4000] Training [4/16] Loss: 0.00913 +Epoch [1693/4000] Training [5/16] Loss: 0.00648 +Epoch [1693/4000] Training [6/16] Loss: 0.00588 +Epoch [1693/4000] Training [7/16] Loss: 0.00658 +Epoch [1693/4000] Training [8/16] Loss: 0.00847 +Epoch [1693/4000] Training [9/16] Loss: 0.00578 +Epoch [1693/4000] Training [10/16] Loss: 0.00549 +Epoch [1693/4000] Training [11/16] Loss: 0.00661 +Epoch [1693/4000] Training [12/16] Loss: 0.00570 +Epoch [1693/4000] Training [13/16] Loss: 0.00635 +Epoch [1693/4000] Training [14/16] Loss: 0.00630 +Epoch [1693/4000] Training [15/16] Loss: 0.00531 +Epoch [1693/4000] Training [16/16] Loss: 0.00557 +Epoch [1693/4000] Training metric {'Train/mean dice_metric': 0.9954611659049988, 'Train/mean miou_metric': 0.9907094836235046, 'Train/mean f1': 0.9913642406463623, 'Train/mean precision': 0.9867462515830994, 'Train/mean recall': 0.9960256814956665, 'Train/mean hd95_metric': 1.0191758871078491} +Epoch [1693/4000] Validation [1/4] Loss: 0.23409 focal_loss 0.17483 dice_loss 0.05926 +Epoch [1693/4000] Validation [2/4] Loss: 0.37313 focal_loss 0.21065 dice_loss 0.16248 +Epoch [1693/4000] Validation [3/4] Loss: 0.33712 focal_loss 0.23373 dice_loss 0.10340 +Epoch [1693/4000] Validation [4/4] Loss: 0.27894 focal_loss 0.16452 dice_loss 0.11442 +Epoch [1693/4000] Validation metric {'Val/mean dice_metric': 0.9722070693969727, 'Val/mean miou_metric': 0.955489456653595, 'Val/mean f1': 0.9747793078422546, 'Val/mean precision': 0.9701495170593262, 'Val/mean recall': 0.9794533848762512, 'Val/mean hd95_metric': 6.4064130783081055} +Cheakpoint... +Epoch [1693/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722070693969727, 'Val/mean miou_metric': 0.955489456653595, 'Val/mean f1': 0.9747793078422546, 'Val/mean precision': 0.9701495170593262, 'Val/mean recall': 0.9794533848762512, 'Val/mean hd95_metric': 6.4064130783081055} +Epoch [1694/4000] Training [1/16] Loss: 0.00665 +Epoch [1694/4000] Training [2/16] Loss: 0.00849 +Epoch [1694/4000] Training [3/16] Loss: 0.00572 +Epoch [1694/4000] Training [4/16] Loss: 0.00594 +Epoch [1694/4000] Training [5/16] Loss: 0.01028 +Epoch [1694/4000] Training [6/16] Loss: 0.00490 +Epoch [1694/4000] Training [7/16] Loss: 0.00485 +Epoch [1694/4000] Training [8/16] Loss: 0.00767 +Epoch [1694/4000] Training [9/16] Loss: 0.00678 +Epoch [1694/4000] Training [10/16] Loss: 0.00569 +Epoch [1694/4000] Training [11/16] Loss: 0.00874 +Epoch [1694/4000] Training [12/16] Loss: 0.00795 +Epoch [1694/4000] Training [13/16] Loss: 0.00690 +Epoch [1694/4000] Training [14/16] Loss: 0.00866 +Epoch [1694/4000] Training [15/16] Loss: 0.00953 +Epoch [1694/4000] Training [16/16] Loss: 0.00672 +Epoch [1694/4000] Training metric {'Train/mean dice_metric': 0.9948907494544983, 'Train/mean miou_metric': 0.9896156787872314, 'Train/mean f1': 0.9905620217323303, 'Train/mean precision': 0.9863144159317017, 'Train/mean recall': 0.9948464035987854, 'Train/mean hd95_metric': 1.675307273864746} +Epoch [1694/4000] Validation [1/4] Loss: 0.20358 focal_loss 0.14640 dice_loss 0.05718 +Epoch [1694/4000] Validation [2/4] Loss: 0.28268 focal_loss 0.15578 dice_loss 0.12690 +Epoch [1694/4000] Validation [3/4] Loss: 0.35012 focal_loss 0.24670 dice_loss 0.10343 +Epoch [1694/4000] Validation [4/4] Loss: 0.47018 focal_loss 0.29448 dice_loss 0.17570 +Epoch [1694/4000] Validation metric {'Val/mean dice_metric': 0.9675508737564087, 'Val/mean miou_metric': 0.9495202898979187, 'Val/mean f1': 0.9698723554611206, 'Val/mean precision': 0.960759162902832, 'Val/mean recall': 0.9791600108146667, 'Val/mean hd95_metric': 8.108109474182129} +Cheakpoint... +Epoch [1694/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675508737564087, 'Val/mean miou_metric': 0.9495202898979187, 'Val/mean f1': 0.9698723554611206, 'Val/mean precision': 0.960759162902832, 'Val/mean recall': 0.9791600108146667, 'Val/mean hd95_metric': 8.108109474182129} +Epoch [1695/4000] Training [1/16] Loss: 0.00843 +Epoch [1695/4000] Training [2/16] Loss: 0.00645 +Epoch [1695/4000] Training [3/16] Loss: 0.01258 +Epoch [1695/4000] Training [4/16] Loss: 0.00725 +Epoch [1695/4000] Training [5/16] Loss: 0.00520 +Epoch [1695/4000] Training [6/16] Loss: 0.00706 +Epoch [1695/4000] Training [7/16] Loss: 0.00904 +Epoch [1695/4000] Training [8/16] Loss: 0.00657 +Epoch [1695/4000] Training [9/16] Loss: 0.00603 +Epoch [1695/4000] Training [10/16] Loss: 0.00706 +Epoch [1695/4000] Training [11/16] Loss: 0.00523 +Epoch [1695/4000] Training [12/16] Loss: 0.00669 +Epoch [1695/4000] Training [13/16] Loss: 0.00946 +Epoch [1695/4000] Training [14/16] Loss: 0.01004 +Epoch [1695/4000] Training [15/16] Loss: 0.00642 +Epoch [1695/4000] Training [16/16] Loss: 0.00613 +Epoch [1695/4000] Training metric {'Train/mean dice_metric': 0.9951971769332886, 'Train/mean miou_metric': 0.9901905059814453, 'Train/mean f1': 0.9908789992332458, 'Train/mean precision': 0.9863517880439758, 'Train/mean recall': 0.9954479336738586, 'Train/mean hd95_metric': 1.4228342771530151} +Epoch [1695/4000] Validation [1/4] Loss: 0.35177 focal_loss 0.25890 dice_loss 0.09287 +Epoch [1695/4000] Validation [2/4] Loss: 0.40895 focal_loss 0.21850 dice_loss 0.19045 +Epoch [1695/4000] Validation [3/4] Loss: 0.18801 focal_loss 0.12214 dice_loss 0.06587 +Epoch [1695/4000] Validation [4/4] Loss: 0.46134 focal_loss 0.30713 dice_loss 0.15422 +Epoch [1695/4000] Validation metric {'Val/mean dice_metric': 0.9702200889587402, 'Val/mean miou_metric': 0.9526392221450806, 'Val/mean f1': 0.9714946746826172, 'Val/mean precision': 0.9693549871444702, 'Val/mean recall': 0.9736437797546387, 'Val/mean hd95_metric': 5.553975582122803} +Cheakpoint... +Epoch [1695/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702200889587402, 'Val/mean miou_metric': 0.9526392221450806, 'Val/mean f1': 0.9714946746826172, 'Val/mean precision': 0.9693549871444702, 'Val/mean recall': 0.9736437797546387, 'Val/mean hd95_metric': 5.553975582122803} +Epoch [1696/4000] Training [1/16] Loss: 0.00687 +Epoch [1696/4000] Training [2/16] Loss: 0.00678 +Epoch [1696/4000] Training [3/16] Loss: 0.00891 +Epoch [1696/4000] Training [4/16] Loss: 0.00681 +Epoch [1696/4000] Training [5/16] Loss: 0.00716 +Epoch [1696/4000] Training [6/16] Loss: 0.00695 +Epoch [1696/4000] Training [7/16] Loss: 0.00628 +Epoch [1696/4000] Training [8/16] Loss: 0.00779 +Epoch [1696/4000] Training [9/16] Loss: 0.00812 +Epoch [1696/4000] Training [10/16] Loss: 0.00983 +Epoch [1696/4000] Training [11/16] Loss: 0.00828 +Epoch [1696/4000] Training [12/16] Loss: 0.00647 +Epoch [1696/4000] Training [13/16] Loss: 0.00672 +Epoch [1696/4000] Training [14/16] Loss: 0.00632 +Epoch [1696/4000] Training [15/16] Loss: 0.00649 +Epoch [1696/4000] Training [16/16] Loss: 0.00829 +Epoch [1696/4000] Training metric {'Train/mean dice_metric': 0.995202362537384, 'Train/mean miou_metric': 0.9901913404464722, 'Train/mean f1': 0.9909348487854004, 'Train/mean precision': 0.9863916635513306, 'Train/mean recall': 0.9955200552940369, 'Train/mean hd95_metric': 1.021230697631836} +Epoch [1696/4000] Validation [1/4] Loss: 0.42085 focal_loss 0.32411 dice_loss 0.09674 +Epoch [1696/4000] Validation [2/4] Loss: 0.32994 focal_loss 0.17249 dice_loss 0.15745 +Epoch [1696/4000] Validation [3/4] Loss: 0.17553 focal_loss 0.10976 dice_loss 0.06577 +Epoch [1696/4000] Validation [4/4] Loss: 0.20222 focal_loss 0.11147 dice_loss 0.09075 +Epoch [1696/4000] Validation metric {'Val/mean dice_metric': 0.9729615449905396, 'Val/mean miou_metric': 0.9555865526199341, 'Val/mean f1': 0.9741133451461792, 'Val/mean precision': 0.9724723696708679, 'Val/mean recall': 0.9757598638534546, 'Val/mean hd95_metric': 5.077122688293457} +Cheakpoint... +Epoch [1696/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729615449905396, 'Val/mean miou_metric': 0.9555865526199341, 'Val/mean f1': 0.9741133451461792, 'Val/mean precision': 0.9724723696708679, 'Val/mean recall': 0.9757598638534546, 'Val/mean hd95_metric': 5.077122688293457} +Epoch [1697/4000] Training [1/16] Loss: 0.00718 +Epoch [1697/4000] Training [2/16] Loss: 0.00790 +Epoch [1697/4000] Training [3/16] Loss: 0.00805 +Epoch [1697/4000] Training [4/16] Loss: 0.00658 +Epoch [1697/4000] Training [5/16] Loss: 0.00579 +Epoch [1697/4000] Training [6/16] Loss: 0.00565 +Epoch [1697/4000] Training [7/16] Loss: 0.00605 +Epoch [1697/4000] Training [8/16] Loss: 0.01044 +Epoch [1697/4000] Training [9/16] Loss: 0.00586 +Epoch [1697/4000] Training [10/16] Loss: 0.00717 +Epoch [1697/4000] Training [11/16] Loss: 0.00811 +Epoch [1697/4000] Training [12/16] Loss: 0.00597 +Epoch [1697/4000] Training [13/16] Loss: 0.00705 +Epoch [1697/4000] Training [14/16] Loss: 0.00557 +Epoch [1697/4000] Training [15/16] Loss: 0.00790 +Epoch [1697/4000] Training [16/16] Loss: 0.00656 +Epoch [1697/4000] Training metric {'Train/mean dice_metric': 0.9955617189407349, 'Train/mean miou_metric': 0.9908989667892456, 'Train/mean f1': 0.9912746548652649, 'Train/mean precision': 0.9867445230484009, 'Train/mean recall': 0.9958466291427612, 'Train/mean hd95_metric': 1.0082290172576904} +Epoch [1697/4000] Validation [1/4] Loss: 0.24616 focal_loss 0.18314 dice_loss 0.06302 +Epoch [1697/4000] Validation [2/4] Loss: 0.37058 focal_loss 0.22658 dice_loss 0.14399 +Epoch [1697/4000] Validation [3/4] Loss: 0.22773 focal_loss 0.14339 dice_loss 0.08434 +Epoch [1697/4000] Validation [4/4] Loss: 0.33842 focal_loss 0.20599 dice_loss 0.13244 +Epoch [1697/4000] Validation metric {'Val/mean dice_metric': 0.9735881686210632, 'Val/mean miou_metric': 0.9561297297477722, 'Val/mean f1': 0.9745528697967529, 'Val/mean precision': 0.9727847576141357, 'Val/mean recall': 0.9763275384902954, 'Val/mean hd95_metric': 5.24007511138916} +Cheakpoint... +Epoch [1697/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735881686210632, 'Val/mean miou_metric': 0.9561297297477722, 'Val/mean f1': 0.9745528697967529, 'Val/mean precision': 0.9727847576141357, 'Val/mean recall': 0.9763275384902954, 'Val/mean hd95_metric': 5.24007511138916} +Epoch [1698/4000] Training [1/16] Loss: 0.00616 +Epoch [1698/4000] Training [2/16] Loss: 0.00670 +Epoch [1698/4000] Training [3/16] Loss: 0.00626 +Epoch [1698/4000] Training [4/16] Loss: 0.00708 +Epoch [1698/4000] Training [5/16] Loss: 0.00510 +Epoch [1698/4000] Training [6/16] Loss: 0.00765 +Epoch [1698/4000] Training [7/16] Loss: 0.00766 +Epoch [1698/4000] Training [8/16] Loss: 0.00609 +Epoch [1698/4000] Training [9/16] Loss: 0.00500 +Epoch [1698/4000] Training [10/16] Loss: 0.00594 +Epoch [1698/4000] Training [11/16] Loss: 0.00735 +Epoch [1698/4000] Training [12/16] Loss: 0.00720 +Epoch [1698/4000] Training [13/16] Loss: 0.00606 +Epoch [1698/4000] Training [14/16] Loss: 0.00864 +Epoch [1698/4000] Training [15/16] Loss: 0.00699 +Epoch [1698/4000] Training [16/16] Loss: 0.00559 +Epoch [1698/4000] Training metric {'Train/mean dice_metric': 0.9956028461456299, 'Train/mean miou_metric': 0.9909758567810059, 'Train/mean f1': 0.9913684725761414, 'Train/mean precision': 0.9867010116577148, 'Train/mean recall': 0.9960802793502808, 'Train/mean hd95_metric': 1.012118935585022} +Epoch [1698/4000] Validation [1/4] Loss: 0.25629 focal_loss 0.19031 dice_loss 0.06598 +Epoch [1698/4000] Validation [2/4] Loss: 0.46029 focal_loss 0.27198 dice_loss 0.18831 +Epoch [1698/4000] Validation [3/4] Loss: 0.22675 focal_loss 0.14538 dice_loss 0.08137 +Epoch [1698/4000] Validation [4/4] Loss: 0.27446 focal_loss 0.16527 dice_loss 0.10919 +Epoch [1698/4000] Validation metric {'Val/mean dice_metric': 0.9733225107192993, 'Val/mean miou_metric': 0.9559968709945679, 'Val/mean f1': 0.9737234711647034, 'Val/mean precision': 0.9707570672035217, 'Val/mean recall': 0.9767080545425415, 'Val/mean hd95_metric': 5.308404445648193} +Cheakpoint... +Epoch [1698/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733225107192993, 'Val/mean miou_metric': 0.9559968709945679, 'Val/mean f1': 0.9737234711647034, 'Val/mean precision': 0.9707570672035217, 'Val/mean recall': 0.9767080545425415, 'Val/mean hd95_metric': 5.308404445648193} +Epoch [1699/4000] Training [1/16] Loss: 0.00697 +Epoch [1699/4000] Training [2/16] Loss: 0.00576 +Epoch [1699/4000] Training [3/16] Loss: 0.00626 +Epoch [1699/4000] Training [4/16] Loss: 0.00686 +Epoch [1699/4000] Training [5/16] Loss: 0.00763 +Epoch [1699/4000] Training [6/16] Loss: 0.00907 +Epoch [1699/4000] Training [7/16] Loss: 0.00555 +Epoch [1699/4000] Training [8/16] Loss: 0.00524 +Epoch [1699/4000] Training [9/16] Loss: 0.00724 +Epoch [1699/4000] Training [10/16] Loss: 0.00598 +Epoch [1699/4000] Training [11/16] Loss: 0.00709 +Epoch [1699/4000] Training [12/16] Loss: 0.01023 +Epoch [1699/4000] Training [13/16] Loss: 0.00725 +Epoch [1699/4000] Training [14/16] Loss: 0.00779 +Epoch [1699/4000] Training [15/16] Loss: 0.00594 +Epoch [1699/4000] Training [16/16] Loss: 0.00631 +Epoch [1699/4000] Training metric {'Train/mean dice_metric': 0.9952342510223389, 'Train/mean miou_metric': 0.9902362823486328, 'Train/mean f1': 0.9903659224510193, 'Train/mean precision': 0.9852588176727295, 'Train/mean recall': 0.9955264329910278, 'Train/mean hd95_metric': 1.0271967649459839} +Epoch [1699/4000] Validation [1/4] Loss: 0.34717 focal_loss 0.27256 dice_loss 0.07461 +Epoch [1699/4000] Validation [2/4] Loss: 0.42971 focal_loss 0.26530 dice_loss 0.16441 +Epoch [1699/4000] Validation [3/4] Loss: 0.24834 focal_loss 0.16151 dice_loss 0.08683 +Epoch [1699/4000] Validation [4/4] Loss: 0.24207 focal_loss 0.14524 dice_loss 0.09683 +Epoch [1699/4000] Validation metric {'Val/mean dice_metric': 0.9743474721908569, 'Val/mean miou_metric': 0.9572946429252625, 'Val/mean f1': 0.9737630486488342, 'Val/mean precision': 0.9675628542900085, 'Val/mean recall': 0.9800432324409485, 'Val/mean hd95_metric': 5.588497638702393} +Cheakpoint... +Epoch [1699/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743474721908569, 'Val/mean miou_metric': 0.9572946429252625, 'Val/mean f1': 0.9737630486488342, 'Val/mean precision': 0.9675628542900085, 'Val/mean recall': 0.9800432324409485, 'Val/mean hd95_metric': 5.588497638702393} +Epoch [1700/4000] Training [1/16] Loss: 0.00689 +Epoch [1700/4000] Training [2/16] Loss: 0.00557 +Epoch [1700/4000] Training [3/16] Loss: 0.00596 +Epoch [1700/4000] Training [4/16] Loss: 0.00673 +Epoch [1700/4000] Training [5/16] Loss: 0.00595 +Epoch [1700/4000] Training [6/16] Loss: 0.00699 +Epoch [1700/4000] Training [7/16] Loss: 0.00625 +Epoch [1700/4000] Training [8/16] Loss: 0.00631 +Epoch [1700/4000] Training [9/16] Loss: 0.00697 +Epoch [1700/4000] Training [10/16] Loss: 0.00940 +Epoch [1700/4000] Training [11/16] Loss: 0.00603 +Epoch [1700/4000] Training [12/16] Loss: 0.00558 +Epoch [1700/4000] Training [13/16] Loss: 0.00662 +Epoch [1700/4000] Training [14/16] Loss: 0.00578 +Epoch [1700/4000] Training [15/16] Loss: 0.00682 +Epoch [1700/4000] Training [16/16] Loss: 0.00904 +Epoch [1700/4000] Training metric {'Train/mean dice_metric': 0.9953703880310059, 'Train/mean miou_metric': 0.9905029535293579, 'Train/mean f1': 0.990780234336853, 'Train/mean precision': 0.9858299493789673, 'Train/mean recall': 0.9957804679870605, 'Train/mean hd95_metric': 1.0913411378860474} +Epoch [1700/4000] Validation [1/4] Loss: 0.28437 focal_loss 0.20575 dice_loss 0.07862 +Epoch [1700/4000] Validation [2/4] Loss: 0.32932 focal_loss 0.18775 dice_loss 0.14157 +Epoch [1700/4000] Validation [3/4] Loss: 0.26551 focal_loss 0.17350 dice_loss 0.09202 +Epoch [1700/4000] Validation [4/4] Loss: 0.36354 focal_loss 0.22896 dice_loss 0.13458 +Epoch [1700/4000] Validation metric {'Val/mean dice_metric': 0.9721397161483765, 'Val/mean miou_metric': 0.9545164108276367, 'Val/mean f1': 0.9728683829307556, 'Val/mean precision': 0.9708635210990906, 'Val/mean recall': 0.9748814702033997, 'Val/mean hd95_metric': 5.859654426574707} +Cheakpoint... +Epoch [1700/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721397161483765, 'Val/mean miou_metric': 0.9545164108276367, 'Val/mean f1': 0.9728683829307556, 'Val/mean precision': 0.9708635210990906, 'Val/mean recall': 0.9748814702033997, 'Val/mean hd95_metric': 5.859654426574707} +Epoch [1701/4000] Training [1/16] Loss: 0.00663 +Epoch [1701/4000] Training [2/16] Loss: 0.00714 +Epoch [1701/4000] Training [3/16] Loss: 0.00919 +Epoch [1701/4000] Training [4/16] Loss: 0.00586 +Epoch [1701/4000] Training [5/16] Loss: 0.00860 +Epoch [1701/4000] Training [6/16] Loss: 0.00567 +Epoch [1701/4000] Training [7/16] Loss: 0.00785 +Epoch [1701/4000] Training [8/16] Loss: 0.01016 +Epoch [1701/4000] Training [9/16] Loss: 0.00781 +Epoch [1701/4000] Training [10/16] Loss: 0.00815 +Epoch [1701/4000] Training [11/16] Loss: 0.00667 +Epoch [1701/4000] Training [12/16] Loss: 0.01138 +Epoch [1701/4000] Training [13/16] Loss: 0.00582 +Epoch [1701/4000] Training [14/16] Loss: 0.00742 +Epoch [1701/4000] Training [15/16] Loss: 0.00715 +Epoch [1701/4000] Training [16/16] Loss: 0.00781 +Epoch [1701/4000] Training metric {'Train/mean dice_metric': 0.9950140714645386, 'Train/mean miou_metric': 0.9898260831832886, 'Train/mean f1': 0.9910424947738647, 'Train/mean precision': 0.9866185784339905, 'Train/mean recall': 0.9955062866210938, 'Train/mean hd95_metric': 1.0270280838012695} +Epoch [1701/4000] Validation [1/4] Loss: 0.24866 focal_loss 0.18519 dice_loss 0.06347 +Epoch [1701/4000] Validation [2/4] Loss: 0.64927 focal_loss 0.39141 dice_loss 0.25786 +Epoch [1701/4000] Validation [3/4] Loss: 0.18663 focal_loss 0.11630 dice_loss 0.07033 +Epoch [1701/4000] Validation [4/4] Loss: 0.32250 focal_loss 0.18806 dice_loss 0.13444 +Epoch [1701/4000] Validation metric {'Val/mean dice_metric': 0.9707099795341492, 'Val/mean miou_metric': 0.9535536766052246, 'Val/mean f1': 0.9735665917396545, 'Val/mean precision': 0.9727008938789368, 'Val/mean recall': 0.9744338393211365, 'Val/mean hd95_metric': 5.491466522216797} +Cheakpoint... +Epoch [1701/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707099795341492, 'Val/mean miou_metric': 0.9535536766052246, 'Val/mean f1': 0.9735665917396545, 'Val/mean precision': 0.9727008938789368, 'Val/mean recall': 0.9744338393211365, 'Val/mean hd95_metric': 5.491466522216797} +Epoch [1702/4000] Training [1/16] Loss: 0.00654 +Epoch [1702/4000] Training [2/16] Loss: 0.00920 +Epoch [1702/4000] Training [3/16] Loss: 0.00764 +Epoch [1702/4000] Training [4/16] Loss: 0.01146 +Epoch [1702/4000] Training [5/16] Loss: 0.00750 +Epoch [1702/4000] Training [6/16] Loss: 0.00521 +Epoch [1702/4000] Training [7/16] Loss: 0.00671 +Epoch [1702/4000] Training [8/16] Loss: 0.00720 +Epoch [1702/4000] Training [9/16] Loss: 0.00593 +Epoch [1702/4000] Training [10/16] Loss: 0.00994 +Epoch [1702/4000] Training [11/16] Loss: 0.00727 +Epoch [1702/4000] Training [12/16] Loss: 0.00694 +Epoch [1702/4000] Training [13/16] Loss: 0.00800 +Epoch [1702/4000] Training [14/16] Loss: 0.00779 +Epoch [1702/4000] Training [15/16] Loss: 0.00841 +Epoch [1702/4000] Training [16/16] Loss: 0.00775 +Epoch [1702/4000] Training metric {'Train/mean dice_metric': 0.9938516616821289, 'Train/mean miou_metric': 0.9883707761764526, 'Train/mean f1': 0.9903923869132996, 'Train/mean precision': 0.9862980246543884, 'Train/mean recall': 0.994520902633667, 'Train/mean hd95_metric': 1.3173775672912598} +Epoch [1702/4000] Validation [1/4] Loss: 0.27464 focal_loss 0.20306 dice_loss 0.07158 +Epoch [1702/4000] Validation [2/4] Loss: 0.67093 focal_loss 0.42036 dice_loss 0.25057 +Epoch [1702/4000] Validation [3/4] Loss: 0.33283 focal_loss 0.23163 dice_loss 0.10120 +Epoch [1702/4000] Validation [4/4] Loss: 0.39410 focal_loss 0.23570 dice_loss 0.15840 +Epoch [1702/4000] Validation metric {'Val/mean dice_metric': 0.9707253575325012, 'Val/mean miou_metric': 0.952759861946106, 'Val/mean f1': 0.9732841849327087, 'Val/mean precision': 0.9702741503715515, 'Val/mean recall': 0.976313054561615, 'Val/mean hd95_metric': 5.710106372833252} +Cheakpoint... +Epoch [1702/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707253575325012, 'Val/mean miou_metric': 0.952759861946106, 'Val/mean f1': 0.9732841849327087, 'Val/mean precision': 0.9702741503715515, 'Val/mean recall': 0.976313054561615, 'Val/mean hd95_metric': 5.710106372833252} +Epoch [1703/4000] Training [1/16] Loss: 0.01046 +Epoch [1703/4000] Training [2/16] Loss: 0.00666 +Epoch [1703/4000] Training [3/16] Loss: 0.00660 +Epoch [1703/4000] Training [4/16] Loss: 0.00620 +Epoch [1703/4000] Training [5/16] Loss: 0.00507 +Epoch [1703/4000] Training [6/16] Loss: 0.00814 +Epoch [1703/4000] Training [7/16] Loss: 0.00764 +Epoch [1703/4000] Training [8/16] Loss: 0.00575 +Epoch [1703/4000] Training [9/16] Loss: 0.00595 +Epoch [1703/4000] Training [10/16] Loss: 0.00930 +Epoch [1703/4000] Training [11/16] Loss: 0.00517 +Epoch [1703/4000] Training [12/16] Loss: 0.00766 +Epoch [1703/4000] Training [13/16] Loss: 0.00831 +Epoch [1703/4000] Training [14/16] Loss: 0.00754 +Epoch [1703/4000] Training [15/16] Loss: 0.00603 +Epoch [1703/4000] Training [16/16] Loss: 0.00603 +Epoch [1703/4000] Training metric {'Train/mean dice_metric': 0.9952044486999512, 'Train/mean miou_metric': 0.9901983737945557, 'Train/mean f1': 0.9910195469856262, 'Train/mean precision': 0.9866472482681274, 'Train/mean recall': 0.9954307675361633, 'Train/mean hd95_metric': 1.0203733444213867} +Epoch [1703/4000] Validation [1/4] Loss: 0.23741 focal_loss 0.17344 dice_loss 0.06397 +Epoch [1703/4000] Validation [2/4] Loss: 0.29702 focal_loss 0.16382 dice_loss 0.13320 +Epoch [1703/4000] Validation [3/4] Loss: 0.29179 focal_loss 0.20058 dice_loss 0.09121 +Epoch [1703/4000] Validation [4/4] Loss: 0.27201 focal_loss 0.16219 dice_loss 0.10982 +Epoch [1703/4000] Validation metric {'Val/mean dice_metric': 0.972986102104187, 'Val/mean miou_metric': 0.9558912515640259, 'Val/mean f1': 0.974899411201477, 'Val/mean precision': 0.9714999794960022, 'Val/mean recall': 0.9783228039741516, 'Val/mean hd95_metric': 5.5497612953186035} +Cheakpoint... +Epoch [1703/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972986102104187, 'Val/mean miou_metric': 0.9558912515640259, 'Val/mean f1': 0.974899411201477, 'Val/mean precision': 0.9714999794960022, 'Val/mean recall': 0.9783228039741516, 'Val/mean hd95_metric': 5.5497612953186035} +Epoch [1704/4000] Training [1/16] Loss: 0.00575 +Epoch [1704/4000] Training [2/16] Loss: 0.00664 +Epoch [1704/4000] Training [3/16] Loss: 0.00647 +Epoch [1704/4000] Training [4/16] Loss: 0.00762 +Epoch [1704/4000] Training [5/16] Loss: 0.00656 +Epoch [1704/4000] Training [6/16] Loss: 0.00556 +Epoch [1704/4000] Training [7/16] Loss: 0.00752 +Epoch [1704/4000] Training [8/16] Loss: 0.00874 +Epoch [1704/4000] Training [9/16] Loss: 0.00682 +Epoch [1704/4000] Training [10/16] Loss: 0.00704 +Epoch [1704/4000] Training [11/16] Loss: 0.00693 +Epoch [1704/4000] Training [12/16] Loss: 0.00903 +Epoch [1704/4000] Training [13/16] Loss: 0.00585 +Epoch [1704/4000] Training [14/16] Loss: 0.00657 +Epoch [1704/4000] Training [15/16] Loss: 0.00741 +Epoch [1704/4000] Training [16/16] Loss: 0.00612 +Epoch [1704/4000] Training metric {'Train/mean dice_metric': 0.9953430891036987, 'Train/mean miou_metric': 0.9904690384864807, 'Train/mean f1': 0.9910904169082642, 'Train/mean precision': 0.9864947199821472, 'Train/mean recall': 0.9957291483879089, 'Train/mean hd95_metric': 1.0141512155532837} +Epoch [1704/4000] Validation [1/4] Loss: 0.30647 focal_loss 0.23236 dice_loss 0.07411 +Epoch [1704/4000] Validation [2/4] Loss: 0.33280 focal_loss 0.20586 dice_loss 0.12694 +Epoch [1704/4000] Validation [3/4] Loss: 0.30655 focal_loss 0.21460 dice_loss 0.09195 +Epoch [1704/4000] Validation [4/4] Loss: 0.28019 focal_loss 0.18283 dice_loss 0.09736 +Epoch [1704/4000] Validation metric {'Val/mean dice_metric': 0.9715042114257812, 'Val/mean miou_metric': 0.9546144604682922, 'Val/mean f1': 0.9731537699699402, 'Val/mean precision': 0.9703037738800049, 'Val/mean recall': 0.9760206341743469, 'Val/mean hd95_metric': 5.789927005767822} +Cheakpoint... +Epoch [1704/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715042114257812, 'Val/mean miou_metric': 0.9546144604682922, 'Val/mean f1': 0.9731537699699402, 'Val/mean precision': 0.9703037738800049, 'Val/mean recall': 0.9760206341743469, 'Val/mean hd95_metric': 5.789927005767822} +Epoch [1705/4000] Training [1/16] Loss: 0.00702 +Epoch [1705/4000] Training [2/16] Loss: 0.00735 +Epoch [1705/4000] Training [3/16] Loss: 0.00569 +Epoch [1705/4000] Training [4/16] Loss: 0.00893 +Epoch [1705/4000] Training [5/16] Loss: 0.00646 +Epoch [1705/4000] Training [6/16] Loss: 0.00775 +Epoch [1705/4000] Training [7/16] Loss: 0.01121 +Epoch [1705/4000] Training [8/16] Loss: 0.00906 +Epoch [1705/4000] Training [9/16] Loss: 0.00694 +Epoch [1705/4000] Training [10/16] Loss: 0.00779 +Epoch [1705/4000] Training [11/16] Loss: 0.00745 +Epoch [1705/4000] Training [12/16] Loss: 0.00786 +Epoch [1705/4000] Training [13/16] Loss: 0.00790 +Epoch [1705/4000] Training [14/16] Loss: 0.00505 +Epoch [1705/4000] Training [15/16] Loss: 0.00723 +Epoch [1705/4000] Training [16/16] Loss: 0.00875 +Epoch [1705/4000] Training metric {'Train/mean dice_metric': 0.9949387907981873, 'Train/mean miou_metric': 0.9896539449691772, 'Train/mean f1': 0.9904190897941589, 'Train/mean precision': 0.9852616190910339, 'Train/mean recall': 0.9956308007240295, 'Train/mean hd95_metric': 1.0340008735656738} +Epoch [1705/4000] Validation [1/4] Loss: 0.21426 focal_loss 0.15504 dice_loss 0.05922 +Epoch [1705/4000] Validation [2/4] Loss: 0.34186 focal_loss 0.20818 dice_loss 0.13369 +Epoch [1705/4000] Validation [3/4] Loss: 0.36164 focal_loss 0.25361 dice_loss 0.10802 +Epoch [1705/4000] Validation [4/4] Loss: 0.31010 focal_loss 0.18969 dice_loss 0.12041 +Epoch [1705/4000] Validation metric {'Val/mean dice_metric': 0.9730304479598999, 'Val/mean miou_metric': 0.9556506872177124, 'Val/mean f1': 0.9745373725891113, 'Val/mean precision': 0.9718471765518188, 'Val/mean recall': 0.977242648601532, 'Val/mean hd95_metric': 5.6931233406066895} +Cheakpoint... +Epoch [1705/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730304479598999, 'Val/mean miou_metric': 0.9556506872177124, 'Val/mean f1': 0.9745373725891113, 'Val/mean precision': 0.9718471765518188, 'Val/mean recall': 0.977242648601532, 'Val/mean hd95_metric': 5.6931233406066895} +Epoch [1706/4000] Training [1/16] Loss: 0.00570 +Epoch [1706/4000] Training [2/16] Loss: 0.00596 +Epoch [1706/4000] Training [3/16] Loss: 0.00693 +Epoch [1706/4000] Training [4/16] Loss: 0.00799 +Epoch [1706/4000] Training [5/16] Loss: 0.00878 +Epoch [1706/4000] Training [6/16] Loss: 0.00667 +Epoch [1706/4000] Training [7/16] Loss: 0.00774 +Epoch [1706/4000] Training [8/16] Loss: 0.00751 +Epoch [1706/4000] Training [9/16] Loss: 0.00616 +Epoch [1706/4000] Training [10/16] Loss: 0.00618 +Epoch [1706/4000] Training [11/16] Loss: 0.00895 +Epoch [1706/4000] Training [12/16] Loss: 0.00687 +Epoch [1706/4000] Training [13/16] Loss: 0.00850 +Epoch [1706/4000] Training [14/16] Loss: 0.00762 +Epoch [1706/4000] Training [15/16] Loss: 0.00677 +Epoch [1706/4000] Training [16/16] Loss: 0.00743 +Epoch [1706/4000] Training metric {'Train/mean dice_metric': 0.9949368238449097, 'Train/mean miou_metric': 0.9896557331085205, 'Train/mean f1': 0.990348756313324, 'Train/mean precision': 0.9853557348251343, 'Train/mean recall': 0.9953926205635071, 'Train/mean hd95_metric': 1.0667915344238281} +Epoch [1706/4000] Validation [1/4] Loss: 0.21264 focal_loss 0.15136 dice_loss 0.06127 +Epoch [1706/4000] Validation [2/4] Loss: 0.32724 focal_loss 0.19592 dice_loss 0.13132 +Epoch [1706/4000] Validation [3/4] Loss: 0.29783 focal_loss 0.20334 dice_loss 0.09449 +Epoch [1706/4000] Validation [4/4] Loss: 0.29626 focal_loss 0.17502 dice_loss 0.12123 +Epoch [1706/4000] Validation metric {'Val/mean dice_metric': 0.9716989398002625, 'Val/mean miou_metric': 0.9545629620552063, 'Val/mean f1': 0.9740698337554932, 'Val/mean precision': 0.9706800580024719, 'Val/mean recall': 0.9774831533432007, 'Val/mean hd95_metric': 5.43269681930542} +Cheakpoint... +Epoch [1706/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716989398002625, 'Val/mean miou_metric': 0.9545629620552063, 'Val/mean f1': 0.9740698337554932, 'Val/mean precision': 0.9706800580024719, 'Val/mean recall': 0.9774831533432007, 'Val/mean hd95_metric': 5.43269681930542} +Epoch [1707/4000] Training [1/16] Loss: 0.00566 +Epoch [1707/4000] Training [2/16] Loss: 0.00732 +Epoch [1707/4000] Training [3/16] Loss: 0.00777 +Epoch [1707/4000] Training [4/16] Loss: 0.00916 +Epoch [1707/4000] Training [5/16] Loss: 0.00690 +Epoch [1707/4000] Training [6/16] Loss: 0.00733 +Epoch [1707/4000] Training [7/16] Loss: 0.00705 +Epoch [1707/4000] Training [8/16] Loss: 0.00763 +Epoch [1707/4000] Training [9/16] Loss: 0.00888 +Epoch [1707/4000] Training [10/16] Loss: 0.00587 +Epoch [1707/4000] Training [11/16] Loss: 0.00622 +Epoch [1707/4000] Training [12/16] Loss: 0.00655 +Epoch [1707/4000] Training [13/16] Loss: 0.00636 +Epoch [1707/4000] Training [14/16] Loss: 0.00725 +Epoch [1707/4000] Training [15/16] Loss: 0.00763 +Epoch [1707/4000] Training [16/16] Loss: 0.00806 +Epoch [1707/4000] Training metric {'Train/mean dice_metric': 0.9950339794158936, 'Train/mean miou_metric': 0.9898653030395508, 'Train/mean f1': 0.9909771680831909, 'Train/mean precision': 0.9864527583122253, 'Train/mean recall': 0.9955433011054993, 'Train/mean hd95_metric': 1.0237839221954346} +Epoch [1707/4000] Validation [1/4] Loss: 0.62420 focal_loss 0.50299 dice_loss 0.12121 +Epoch [1707/4000] Validation [2/4] Loss: 0.33286 focal_loss 0.19805 dice_loss 0.13480 +Epoch [1707/4000] Validation [3/4] Loss: 0.26194 focal_loss 0.17417 dice_loss 0.08777 +Epoch [1707/4000] Validation [4/4] Loss: 0.38987 focal_loss 0.22661 dice_loss 0.16326 +Epoch [1707/4000] Validation metric {'Val/mean dice_metric': 0.9697633981704712, 'Val/mean miou_metric': 0.9515401721000671, 'Val/mean f1': 0.9714608788490295, 'Val/mean precision': 0.9737149477005005, 'Val/mean recall': 0.9692173004150391, 'Val/mean hd95_metric': 5.298064708709717} +Cheakpoint... +Epoch [1707/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697633981704712, 'Val/mean miou_metric': 0.9515401721000671, 'Val/mean f1': 0.9714608788490295, 'Val/mean precision': 0.9737149477005005, 'Val/mean recall': 0.9692173004150391, 'Val/mean hd95_metric': 5.298064708709717} +Epoch [1708/4000] Training [1/16] Loss: 0.00908 +Epoch [1708/4000] Training [2/16] Loss: 0.01214 +Epoch [1708/4000] Training [3/16] Loss: 0.00706 +Epoch [1708/4000] Training [4/16] Loss: 0.00658 +Epoch [1708/4000] Training [5/16] Loss: 0.00878 +Epoch [1708/4000] Training [6/16] Loss: 0.00629 +Epoch [1708/4000] Training [7/16] Loss: 0.00635 +Epoch [1708/4000] Training [8/16] Loss: 0.00640 +Epoch [1708/4000] Training [9/16] Loss: 0.00783 +Epoch [1708/4000] Training [10/16] Loss: 0.00681 +Epoch [1708/4000] Training [11/16] Loss: 0.00820 +Epoch [1708/4000] Training [12/16] Loss: 0.00619 +Epoch [1708/4000] Training [13/16] Loss: 0.00709 +Epoch [1708/4000] Training [14/16] Loss: 0.00593 +Epoch [1708/4000] Training [15/16] Loss: 0.00870 +Epoch [1708/4000] Training [16/16] Loss: 0.00701 +Epoch [1708/4000] Training metric {'Train/mean dice_metric': 0.9950025081634521, 'Train/mean miou_metric': 0.9897674322128296, 'Train/mean f1': 0.9902175664901733, 'Train/mean precision': 0.98506098985672, 'Train/mean recall': 0.9954283833503723, 'Train/mean hd95_metric': 1.032952070236206} +Epoch [1708/4000] Validation [1/4] Loss: 0.28953 focal_loss 0.20220 dice_loss 0.08733 +Epoch [1708/4000] Validation [2/4] Loss: 0.65216 focal_loss 0.39261 dice_loss 0.25955 +Epoch [1708/4000] Validation [3/4] Loss: 0.22526 focal_loss 0.14341 dice_loss 0.08185 +Epoch [1708/4000] Validation [4/4] Loss: 0.25760 focal_loss 0.15959 dice_loss 0.09800 +Epoch [1708/4000] Validation metric {'Val/mean dice_metric': 0.9678462147712708, 'Val/mean miou_metric': 0.9505723714828491, 'Val/mean f1': 0.9716812372207642, 'Val/mean precision': 0.9717289805412292, 'Val/mean recall': 0.9716336131095886, 'Val/mean hd95_metric': 5.301670074462891} +Cheakpoint... +Epoch [1708/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678462147712708, 'Val/mean miou_metric': 0.9505723714828491, 'Val/mean f1': 0.9716812372207642, 'Val/mean precision': 0.9717289805412292, 'Val/mean recall': 0.9716336131095886, 'Val/mean hd95_metric': 5.301670074462891} +Epoch [1709/4000] Training [1/16] Loss: 0.00754 +Epoch [1709/4000] Training [2/16] Loss: 0.01126 +Epoch [1709/4000] Training [3/16] Loss: 0.00622 +Epoch [1709/4000] Training [4/16] Loss: 0.00657 +Epoch [1709/4000] Training [5/16] Loss: 0.00865 +Epoch [1709/4000] Training [6/16] Loss: 0.01191 +Epoch [1709/4000] Training [7/16] Loss: 0.00743 +Epoch [1709/4000] Training [8/16] Loss: 0.00738 +Epoch [1709/4000] Training [9/16] Loss: 0.00696 +Epoch [1709/4000] Training [10/16] Loss: 0.00626 +Epoch [1709/4000] Training [11/16] Loss: 0.00741 +Epoch [1709/4000] Training [12/16] Loss: 0.00910 +Epoch [1709/4000] Training [13/16] Loss: 0.00569 +Epoch [1709/4000] Training [14/16] Loss: 0.00853 +Epoch [1709/4000] Training [15/16] Loss: 0.00771 +Epoch [1709/4000] Training [16/16] Loss: 0.00732 +Epoch [1709/4000] Training metric {'Train/mean dice_metric': 0.994562029838562, 'Train/mean miou_metric': 0.9889286160469055, 'Train/mean f1': 0.9906254410743713, 'Train/mean precision': 0.9859707951545715, 'Train/mean recall': 0.9953242540359497, 'Train/mean hd95_metric': 1.030522346496582} +Epoch [1709/4000] Validation [1/4] Loss: 0.53618 focal_loss 0.41875 dice_loss 0.11742 +Epoch [1709/4000] Validation [2/4] Loss: 0.38486 focal_loss 0.23402 dice_loss 0.15084 +Epoch [1709/4000] Validation [3/4] Loss: 0.18992 focal_loss 0.12490 dice_loss 0.06502 +Epoch [1709/4000] Validation [4/4] Loss: 0.21904 focal_loss 0.13277 dice_loss 0.08627 +Epoch [1709/4000] Validation metric {'Val/mean dice_metric': 0.9718542098999023, 'Val/mean miou_metric': 0.9543204307556152, 'Val/mean f1': 0.9731234312057495, 'Val/mean precision': 0.9736907482147217, 'Val/mean recall': 0.9725566506385803, 'Val/mean hd95_metric': 4.841299533843994} +Cheakpoint... +Epoch [1709/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718542098999023, 'Val/mean miou_metric': 0.9543204307556152, 'Val/mean f1': 0.9731234312057495, 'Val/mean precision': 0.9736907482147217, 'Val/mean recall': 0.9725566506385803, 'Val/mean hd95_metric': 4.841299533843994} +Epoch [1710/4000] Training [1/16] Loss: 0.00755 +Epoch [1710/4000] Training [2/16] Loss: 0.00585 +Epoch [1710/4000] Training [3/16] Loss: 0.00642 +Epoch [1710/4000] Training [4/16] Loss: 0.00774 +Epoch [1710/4000] Training [5/16] Loss: 0.00591 +Epoch [1710/4000] Training [6/16] Loss: 0.01092 +Epoch [1710/4000] Training [7/16] Loss: 0.00753 +Epoch [1710/4000] Training [8/16] Loss: 0.00656 +Epoch [1710/4000] Training [9/16] Loss: 0.00662 +Epoch [1710/4000] Training [10/16] Loss: 0.00641 +Epoch [1710/4000] Training [11/16] Loss: 0.00836 +Epoch [1710/4000] Training [12/16] Loss: 0.00809 +Epoch [1710/4000] Training [13/16] Loss: 0.00861 +Epoch [1710/4000] Training [14/16] Loss: 0.00887 +Epoch [1710/4000] Training [15/16] Loss: 0.00664 +Epoch [1710/4000] Training [16/16] Loss: 0.00922 +Epoch [1710/4000] Training metric {'Train/mean dice_metric': 0.994698166847229, 'Train/mean miou_metric': 0.9891947507858276, 'Train/mean f1': 0.9907877445220947, 'Train/mean precision': 0.9861486554145813, 'Train/mean recall': 0.9954707026481628, 'Train/mean hd95_metric': 1.0315848588943481} +Epoch [1710/4000] Validation [1/4] Loss: 0.19604 focal_loss 0.13923 dice_loss 0.05680 +Epoch [1710/4000] Validation [2/4] Loss: 0.35415 focal_loss 0.21609 dice_loss 0.13806 +Epoch [1710/4000] Validation [3/4] Loss: 0.14898 focal_loss 0.09439 dice_loss 0.05459 +Epoch [1710/4000] Validation [4/4] Loss: 0.29588 focal_loss 0.17293 dice_loss 0.12295 +Epoch [1710/4000] Validation metric {'Val/mean dice_metric': 0.9725855588912964, 'Val/mean miou_metric': 0.9550504684448242, 'Val/mean f1': 0.975458562374115, 'Val/mean precision': 0.9733977317810059, 'Val/mean recall': 0.9775280356407166, 'Val/mean hd95_metric': 5.1442131996154785} +Cheakpoint... +Epoch [1710/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725855588912964, 'Val/mean miou_metric': 0.9550504684448242, 'Val/mean f1': 0.975458562374115, 'Val/mean precision': 0.9733977317810059, 'Val/mean recall': 0.9775280356407166, 'Val/mean hd95_metric': 5.1442131996154785} +Epoch [1711/4000] Training [1/16] Loss: 0.00594 +Epoch [1711/4000] Training [2/16] Loss: 0.00860 +Epoch [1711/4000] Training [3/16] Loss: 0.00771 +Epoch [1711/4000] Training [4/16] Loss: 0.00752 +Epoch [1711/4000] Training [5/16] Loss: 0.00765 +Epoch [1711/4000] Training [6/16] Loss: 0.00587 +Epoch [1711/4000] Training [7/16] Loss: 0.00893 +Epoch [1711/4000] Training [8/16] Loss: 0.00974 +Epoch [1711/4000] Training [9/16] Loss: 0.00782 +Epoch [1711/4000] Training [10/16] Loss: 0.00885 +Epoch [1711/4000] Training [11/16] Loss: 0.00878 +Epoch [1711/4000] Training [12/16] Loss: 0.00707 +Epoch [1711/4000] Training [13/16] Loss: 0.00881 +Epoch [1711/4000] Training [14/16] Loss: 0.00774 +Epoch [1711/4000] Training [15/16] Loss: 0.00696 +Epoch [1711/4000] Training [16/16] Loss: 0.00712 +Epoch [1711/4000] Training metric {'Train/mean dice_metric': 0.9948867559432983, 'Train/mean miou_metric': 0.989577054977417, 'Train/mean f1': 0.9908407926559448, 'Train/mean precision': 0.9861924052238464, 'Train/mean recall': 0.9955332279205322, 'Train/mean hd95_metric': 1.074770450592041} +Epoch [1711/4000] Validation [1/4] Loss: 0.23850 focal_loss 0.17583 dice_loss 0.06268 +Epoch [1711/4000] Validation [2/4] Loss: 0.42494 focal_loss 0.26633 dice_loss 0.15861 +Epoch [1711/4000] Validation [3/4] Loss: 0.20641 focal_loss 0.13212 dice_loss 0.07429 +Epoch [1711/4000] Validation [4/4] Loss: 0.29227 focal_loss 0.17194 dice_loss 0.12034 +Epoch [1711/4000] Validation metric {'Val/mean dice_metric': 0.9713985323905945, 'Val/mean miou_metric': 0.9546721577644348, 'Val/mean f1': 0.9741915464401245, 'Val/mean precision': 0.9680870771408081, 'Val/mean recall': 0.9803735613822937, 'Val/mean hd95_metric': 5.889008045196533} +Cheakpoint... +Epoch [1711/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713985323905945, 'Val/mean miou_metric': 0.9546721577644348, 'Val/mean f1': 0.9741915464401245, 'Val/mean precision': 0.9680870771408081, 'Val/mean recall': 0.9803735613822937, 'Val/mean hd95_metric': 5.889008045196533} +Epoch [1712/4000] Training [1/16] Loss: 0.00672 +Epoch [1712/4000] Training [2/16] Loss: 0.00659 +Epoch [1712/4000] Training [3/16] Loss: 0.00770 +Epoch [1712/4000] Training [4/16] Loss: 0.00689 +Epoch [1712/4000] Training [5/16] Loss: 0.00557 +Epoch [1712/4000] Training [6/16] Loss: 0.01009 +Epoch [1712/4000] Training [7/16] Loss: 0.01143 +Epoch [1712/4000] Training [8/16] Loss: 0.00635 +Epoch [1712/4000] Training [9/16] Loss: 0.00873 +Epoch [1712/4000] Training [10/16] Loss: 0.00675 +Epoch [1712/4000] Training [11/16] Loss: 0.00855 +Epoch [1712/4000] Training [12/16] Loss: 0.01001 +Epoch [1712/4000] Training [13/16] Loss: 0.00636 +Epoch [1712/4000] Training [14/16] Loss: 0.00617 +Epoch [1712/4000] Training [15/16] Loss: 0.00724 +Epoch [1712/4000] Training [16/16] Loss: 0.00558 +Epoch [1712/4000] Training metric {'Train/mean dice_metric': 0.995114803314209, 'Train/mean miou_metric': 0.9900296926498413, 'Train/mean f1': 0.9910697340965271, 'Train/mean precision': 0.9866384267807007, 'Train/mean recall': 0.9955410361289978, 'Train/mean hd95_metric': 1.0333739519119263} +Epoch [1712/4000] Validation [1/4] Loss: 0.21996 focal_loss 0.16230 dice_loss 0.05767 +Epoch [1712/4000] Validation [2/4] Loss: 0.40897 focal_loss 0.24330 dice_loss 0.16568 +Epoch [1712/4000] Validation [3/4] Loss: 0.17161 focal_loss 0.10611 dice_loss 0.06550 +Epoch [1712/4000] Validation [4/4] Loss: 0.29093 focal_loss 0.18036 dice_loss 0.11056 +Epoch [1712/4000] Validation metric {'Val/mean dice_metric': 0.9721075296401978, 'Val/mean miou_metric': 0.9550636410713196, 'Val/mean f1': 0.9741894602775574, 'Val/mean precision': 0.9712992906570435, 'Val/mean recall': 0.9770967960357666, 'Val/mean hd95_metric': 5.561918258666992} +Cheakpoint... +Epoch [1712/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721075296401978, 'Val/mean miou_metric': 0.9550636410713196, 'Val/mean f1': 0.9741894602775574, 'Val/mean precision': 0.9712992906570435, 'Val/mean recall': 0.9770967960357666, 'Val/mean hd95_metric': 5.561918258666992} +Epoch [1713/4000] Training [1/16] Loss: 0.00803 +Epoch [1713/4000] Training [2/16] Loss: 0.00898 +Epoch [1713/4000] Training [3/16] Loss: 0.00871 +Epoch [1713/4000] Training [4/16] Loss: 0.00864 +Epoch [1713/4000] Training [5/16] Loss: 0.00718 +Epoch [1713/4000] Training [6/16] Loss: 0.00613 +Epoch [1713/4000] Training [7/16] Loss: 0.00578 +Epoch [1713/4000] Training [8/16] Loss: 0.00749 +Epoch [1713/4000] Training [9/16] Loss: 0.00666 +Epoch [1713/4000] Training [10/16] Loss: 0.00577 +Epoch [1713/4000] Training [11/16] Loss: 0.00683 +Epoch [1713/4000] Training [12/16] Loss: 0.00889 +Epoch [1713/4000] Training [13/16] Loss: 0.00700 +Epoch [1713/4000] Training [14/16] Loss: 0.00541 +Epoch [1713/4000] Training [15/16] Loss: 0.00831 +Epoch [1713/4000] Training [16/16] Loss: 0.00746 +Epoch [1713/4000] Training metric {'Train/mean dice_metric': 0.9952355623245239, 'Train/mean miou_metric': 0.9902485013008118, 'Train/mean f1': 0.9910918474197388, 'Train/mean precision': 0.9864410161972046, 'Train/mean recall': 0.9957866668701172, 'Train/mean hd95_metric': 1.0247917175292969} +Epoch [1713/4000] Validation [1/4] Loss: 0.26042 focal_loss 0.19493 dice_loss 0.06549 +Epoch [1713/4000] Validation [2/4] Loss: 0.42003 focal_loss 0.25483 dice_loss 0.16520 +Epoch [1713/4000] Validation [3/4] Loss: 0.35795 focal_loss 0.25314 dice_loss 0.10481 +Epoch [1713/4000] Validation [4/4] Loss: 0.39223 focal_loss 0.25161 dice_loss 0.14062 +Epoch [1713/4000] Validation metric {'Val/mean dice_metric': 0.9715651273727417, 'Val/mean miou_metric': 0.9542644619941711, 'Val/mean f1': 0.9738286733627319, 'Val/mean precision': 0.9701472520828247, 'Val/mean recall': 0.9775380492210388, 'Val/mean hd95_metric': 5.765658855438232} +Cheakpoint... +Epoch [1713/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715651273727417, 'Val/mean miou_metric': 0.9542644619941711, 'Val/mean f1': 0.9738286733627319, 'Val/mean precision': 0.9701472520828247, 'Val/mean recall': 0.9775380492210388, 'Val/mean hd95_metric': 5.765658855438232} +Epoch [1714/4000] Training [1/16] Loss: 0.00898 +Epoch [1714/4000] Training [2/16] Loss: 0.00565 +Epoch [1714/4000] Training [3/16] Loss: 0.00727 +Epoch [1714/4000] Training [4/16] Loss: 0.00764 +Epoch [1714/4000] Training [5/16] Loss: 0.00565 +Epoch [1714/4000] Training [6/16] Loss: 0.00742 +Epoch [1714/4000] Training [7/16] Loss: 0.01092 +Epoch [1714/4000] Training [8/16] Loss: 0.00850 +Epoch [1714/4000] Training [9/16] Loss: 0.00769 +Epoch [1714/4000] Training [10/16] Loss: 0.00719 +Epoch [1714/4000] Training [11/16] Loss: 0.01187 +Epoch [1714/4000] Training [12/16] Loss: 0.00620 +Epoch [1714/4000] Training [13/16] Loss: 0.00553 +Epoch [1714/4000] Training [14/16] Loss: 0.00597 +Epoch [1714/4000] Training [15/16] Loss: 0.00675 +Epoch [1714/4000] Training [16/16] Loss: 0.00832 +Epoch [1714/4000] Training metric {'Train/mean dice_metric': 0.99515700340271, 'Train/mean miou_metric': 0.9900916218757629, 'Train/mean f1': 0.9909579753875732, 'Train/mean precision': 0.9863014817237854, 'Train/mean recall': 0.9956586360931396, 'Train/mean hd95_metric': 1.123702049255371} +Epoch [1714/4000] Validation [1/4] Loss: 0.22215 focal_loss 0.15895 dice_loss 0.06320 +Epoch [1714/4000] Validation [2/4] Loss: 0.74467 focal_loss 0.47061 dice_loss 0.27406 +Epoch [1714/4000] Validation [3/4] Loss: 0.29400 focal_loss 0.19820 dice_loss 0.09581 +Epoch [1714/4000] Validation [4/4] Loss: 0.35396 focal_loss 0.21134 dice_loss 0.14262 +Epoch [1714/4000] Validation metric {'Val/mean dice_metric': 0.9688707590103149, 'Val/mean miou_metric': 0.9514411687850952, 'Val/mean f1': 0.9728911519050598, 'Val/mean precision': 0.9708814024925232, 'Val/mean recall': 0.9749093651771545, 'Val/mean hd95_metric': 5.912322998046875} +Cheakpoint... +Epoch [1714/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688707590103149, 'Val/mean miou_metric': 0.9514411687850952, 'Val/mean f1': 0.9728911519050598, 'Val/mean precision': 0.9708814024925232, 'Val/mean recall': 0.9749093651771545, 'Val/mean hd95_metric': 5.912322998046875} +Epoch [1715/4000] Training [1/16] Loss: 0.00981 +Epoch [1715/4000] Training [2/16] Loss: 0.00821 +Epoch [1715/4000] Training [3/16] Loss: 0.00781 +Epoch [1715/4000] Training [4/16] Loss: 0.00854 +Epoch [1715/4000] Training [5/16] Loss: 0.00712 +Epoch [1715/4000] Training [6/16] Loss: 0.00746 +Epoch [1715/4000] Training [7/16] Loss: 0.00801 +Epoch [1715/4000] Training [8/16] Loss: 0.00571 +Epoch [1715/4000] Training [9/16] Loss: 0.00748 +Epoch [1715/4000] Training [10/16] Loss: 0.00583 +Epoch [1715/4000] Training [11/16] Loss: 0.00892 +Epoch [1715/4000] Training [12/16] Loss: 0.00730 +Epoch [1715/4000] Training [13/16] Loss: 0.00760 +Epoch [1715/4000] Training [14/16] Loss: 0.00921 +Epoch [1715/4000] Training [15/16] Loss: 0.00616 +Epoch [1715/4000] Training [16/16] Loss: 0.00778 +Epoch [1715/4000] Training metric {'Train/mean dice_metric': 0.9947373867034912, 'Train/mean miou_metric': 0.9892916083335876, 'Train/mean f1': 0.9908265471458435, 'Train/mean precision': 0.9862284660339355, 'Train/mean recall': 0.9954676628112793, 'Train/mean hd95_metric': 1.0474872589111328} +Epoch [1715/4000] Validation [1/4] Loss: 0.27199 focal_loss 0.20567 dice_loss 0.06633 +Epoch [1715/4000] Validation [2/4] Loss: 0.58244 focal_loss 0.36889 dice_loss 0.21355 +Epoch [1715/4000] Validation [3/4] Loss: 0.35075 focal_loss 0.25051 dice_loss 0.10024 +Epoch [1715/4000] Validation [4/4] Loss: 0.31782 focal_loss 0.19698 dice_loss 0.12085 +Epoch [1715/4000] Validation metric {'Val/mean dice_metric': 0.971556544303894, 'Val/mean miou_metric': 0.9544388055801392, 'Val/mean f1': 0.9740661382675171, 'Val/mean precision': 0.9694417119026184, 'Val/mean recall': 0.9787348508834839, 'Val/mean hd95_metric': 5.437648296356201} +Cheakpoint... +Epoch [1715/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971556544303894, 'Val/mean miou_metric': 0.9544388055801392, 'Val/mean f1': 0.9740661382675171, 'Val/mean precision': 0.9694417119026184, 'Val/mean recall': 0.9787348508834839, 'Val/mean hd95_metric': 5.437648296356201} +Epoch [1716/4000] Training [1/16] Loss: 0.00617 +Epoch [1716/4000] Training [2/16] Loss: 0.00679 +Epoch [1716/4000] Training [3/16] Loss: 0.00566 +Epoch [1716/4000] Training [4/16] Loss: 0.00878 +Epoch [1716/4000] Training [5/16] Loss: 0.00664 +Epoch [1716/4000] Training [6/16] Loss: 0.00651 +Epoch [1716/4000] Training [7/16] Loss: 0.00756 +Epoch [1716/4000] Training [8/16] Loss: 0.00623 +Epoch [1716/4000] Training [9/16] Loss: 0.00793 +Epoch [1716/4000] Training [10/16] Loss: 0.00766 +Epoch [1716/4000] Training [11/16] Loss: 0.00733 +Epoch [1716/4000] Training [12/16] Loss: 0.00663 +Epoch [1716/4000] Training [13/16] Loss: 0.00913 +Epoch [1716/4000] Training [14/16] Loss: 0.00581 +Epoch [1716/4000] Training [15/16] Loss: 0.01169 +Epoch [1716/4000] Training [16/16] Loss: 0.00781 +Epoch [1716/4000] Training metric {'Train/mean dice_metric': 0.9950112104415894, 'Train/mean miou_metric': 0.989814281463623, 'Train/mean f1': 0.9908812046051025, 'Train/mean precision': 0.9862930774688721, 'Train/mean recall': 0.9955121874809265, 'Train/mean hd95_metric': 1.023841142654419} +Epoch [1716/4000] Validation [1/4] Loss: 0.29660 focal_loss 0.21952 dice_loss 0.07708 +Epoch [1716/4000] Validation [2/4] Loss: 0.45932 focal_loss 0.28073 dice_loss 0.17860 +Epoch [1716/4000] Validation [3/4] Loss: 0.20836 focal_loss 0.13090 dice_loss 0.07746 +Epoch [1716/4000] Validation [4/4] Loss: 0.29808 focal_loss 0.16956 dice_loss 0.12852 +Epoch [1716/4000] Validation metric {'Val/mean dice_metric': 0.970916748046875, 'Val/mean miou_metric': 0.9534955024719238, 'Val/mean f1': 0.9735280871391296, 'Val/mean precision': 0.9721230864524841, 'Val/mean recall': 0.9749372005462646, 'Val/mean hd95_metric': 5.5223798751831055} +Cheakpoint... +Epoch [1716/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970916748046875, 'Val/mean miou_metric': 0.9534955024719238, 'Val/mean f1': 0.9735280871391296, 'Val/mean precision': 0.9721230864524841, 'Val/mean recall': 0.9749372005462646, 'Val/mean hd95_metric': 5.5223798751831055} +Epoch [1717/4000] Training [1/16] Loss: 0.00600 +Epoch [1717/4000] Training [2/16] Loss: 0.00691 +Epoch [1717/4000] Training [3/16] Loss: 0.00858 +Epoch [1717/4000] Training [4/16] Loss: 0.00582 +Epoch [1717/4000] Training [5/16] Loss: 0.00721 +Epoch [1717/4000] Training [6/16] Loss: 0.00540 +Epoch [1717/4000] Training [7/16] Loss: 0.00863 +Epoch [1717/4000] Training [8/16] Loss: 0.00963 +Epoch [1717/4000] Training [9/16] Loss: 0.00839 +Epoch [1717/4000] Training [10/16] Loss: 0.00764 +Epoch [1717/4000] Training [11/16] Loss: 0.00776 +Epoch [1717/4000] Training [12/16] Loss: 0.00587 +Epoch [1717/4000] Training [13/16] Loss: 0.00613 +Epoch [1717/4000] Training [14/16] Loss: 0.00669 +Epoch [1717/4000] Training [15/16] Loss: 0.00676 +Epoch [1717/4000] Training [16/16] Loss: 0.00721 +Epoch [1717/4000] Training metric {'Train/mean dice_metric': 0.9950039982795715, 'Train/mean miou_metric': 0.9898110628128052, 'Train/mean f1': 0.9909958839416504, 'Train/mean precision': 0.9865405559539795, 'Train/mean recall': 0.9954915642738342, 'Train/mean hd95_metric': 1.0179946422576904} +Epoch [1717/4000] Validation [1/4] Loss: 0.22789 focal_loss 0.16286 dice_loss 0.06503 +Epoch [1717/4000] Validation [2/4] Loss: 0.25212 focal_loss 0.14369 dice_loss 0.10842 +Epoch [1717/4000] Validation [3/4] Loss: 0.15919 focal_loss 0.09942 dice_loss 0.05977 +Epoch [1717/4000] Validation [4/4] Loss: 0.27991 focal_loss 0.16162 dice_loss 0.11829 +Epoch [1717/4000] Validation metric {'Val/mean dice_metric': 0.9741184115409851, 'Val/mean miou_metric': 0.9569609761238098, 'Val/mean f1': 0.9755288362503052, 'Val/mean precision': 0.9727575182914734, 'Val/mean recall': 0.9783158302307129, 'Val/mean hd95_metric': 4.840315818786621} +Cheakpoint... +Epoch [1717/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741184115409851, 'Val/mean miou_metric': 0.9569609761238098, 'Val/mean f1': 0.9755288362503052, 'Val/mean precision': 0.9727575182914734, 'Val/mean recall': 0.9783158302307129, 'Val/mean hd95_metric': 4.840315818786621} +Epoch [1718/4000] Training [1/16] Loss: 0.00635 +Epoch [1718/4000] Training [2/16] Loss: 0.00843 +Epoch [1718/4000] Training [3/16] Loss: 0.00772 +Epoch [1718/4000] Training [4/16] Loss: 0.00901 +Epoch [1718/4000] Training [5/16] Loss: 0.00517 +Epoch [1718/4000] Training [6/16] Loss: 0.00790 +Epoch [1718/4000] Training [7/16] Loss: 0.00575 +Epoch [1718/4000] Training [8/16] Loss: 0.00490 +Epoch [1718/4000] Training [9/16] Loss: 0.00655 +Epoch [1718/4000] Training [10/16] Loss: 0.00832 +Epoch [1718/4000] Training [11/16] Loss: 0.00769 +Epoch [1718/4000] Training [12/16] Loss: 0.00830 +Epoch [1718/4000] Training [13/16] Loss: 0.00776 +Epoch [1718/4000] Training [14/16] Loss: 0.00619 +Epoch [1718/4000] Training [15/16] Loss: 0.00895 +Epoch [1718/4000] Training [16/16] Loss: 0.00587 +Epoch [1718/4000] Training metric {'Train/mean dice_metric': 0.9951976537704468, 'Train/mean miou_metric': 0.9901610612869263, 'Train/mean f1': 0.9906359910964966, 'Train/mean precision': 0.9854894876480103, 'Train/mean recall': 0.9958364367485046, 'Train/mean hd95_metric': 1.0264153480529785} +Epoch [1718/4000] Validation [1/4] Loss: 0.27695 focal_loss 0.20512 dice_loss 0.07184 +Epoch [1718/4000] Validation [2/4] Loss: 0.38919 focal_loss 0.23078 dice_loss 0.15841 +Epoch [1718/4000] Validation [3/4] Loss: 0.26085 focal_loss 0.17231 dice_loss 0.08855 +Epoch [1718/4000] Validation [4/4] Loss: 0.38725 focal_loss 0.24551 dice_loss 0.14174 +Epoch [1718/4000] Validation metric {'Val/mean dice_metric': 0.9711670875549316, 'Val/mean miou_metric': 0.9538100361824036, 'Val/mean f1': 0.9729657173156738, 'Val/mean precision': 0.9702081084251404, 'Val/mean recall': 0.9757391810417175, 'Val/mean hd95_metric': 5.281775951385498} +Cheakpoint... +Epoch [1718/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711670875549316, 'Val/mean miou_metric': 0.9538100361824036, 'Val/mean f1': 0.9729657173156738, 'Val/mean precision': 0.9702081084251404, 'Val/mean recall': 0.9757391810417175, 'Val/mean hd95_metric': 5.281775951385498} +Epoch [1719/4000] Training [1/16] Loss: 0.00554 +Epoch [1719/4000] Training [2/16] Loss: 0.00645 +Epoch [1719/4000] Training [3/16] Loss: 0.00598 +Epoch [1719/4000] Training [4/16] Loss: 0.00514 +Epoch [1719/4000] Training [5/16] Loss: 0.00633 +Epoch [1719/4000] Training [6/16] Loss: 0.00877 +Epoch [1719/4000] Training [7/16] Loss: 0.00762 +Epoch [1719/4000] Training [8/16] Loss: 0.00903 +Epoch [1719/4000] Training [9/16] Loss: 0.00896 +Epoch [1719/4000] Training [10/16] Loss: 0.00685 +Epoch [1719/4000] Training [11/16] Loss: 0.00612 +Epoch [1719/4000] Training [12/16] Loss: 0.02064 +Epoch [1719/4000] Training [13/16] Loss: 0.00850 +Epoch [1719/4000] Training [14/16] Loss: 0.00828 +Epoch [1719/4000] Training [15/16] Loss: 0.00842 +Epoch [1719/4000] Training [16/16] Loss: 0.00627 +Epoch [1719/4000] Training metric {'Train/mean dice_metric': 0.9946159720420837, 'Train/mean miou_metric': 0.9890538454055786, 'Train/mean f1': 0.9908117651939392, 'Train/mean precision': 0.9863560795783997, 'Train/mean recall': 0.9953079223632812, 'Train/mean hd95_metric': 1.1260193586349487} +Epoch [1719/4000] Validation [1/4] Loss: 0.24647 focal_loss 0.17825 dice_loss 0.06822 +Epoch [1719/4000] Validation [2/4] Loss: 0.48031 focal_loss 0.30419 dice_loss 0.17612 +Epoch [1719/4000] Validation [3/4] Loss: 0.16539 focal_loss 0.10248 dice_loss 0.06291 +Epoch [1719/4000] Validation [4/4] Loss: 0.23636 focal_loss 0.12786 dice_loss 0.10850 +Epoch [1719/4000] Validation metric {'Val/mean dice_metric': 0.9692153930664062, 'Val/mean miou_metric': 0.9524425268173218, 'Val/mean f1': 0.9740922451019287, 'Val/mean precision': 0.9711329936981201, 'Val/mean recall': 0.977069616317749, 'Val/mean hd95_metric': 5.56785249710083} +Cheakpoint... +Epoch [1719/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692153930664062, 'Val/mean miou_metric': 0.9524425268173218, 'Val/mean f1': 0.9740922451019287, 'Val/mean precision': 0.9711329936981201, 'Val/mean recall': 0.977069616317749, 'Val/mean hd95_metric': 5.56785249710083} +Epoch [1720/4000] Training [1/16] Loss: 0.00575 +Epoch [1720/4000] Training [2/16] Loss: 0.00736 +Epoch [1720/4000] Training [3/16] Loss: 0.00761 +Epoch [1720/4000] Training [4/16] Loss: 0.00675 +Epoch [1720/4000] Training [5/16] Loss: 0.00615 +Epoch [1720/4000] Training [6/16] Loss: 0.01827 +Epoch [1720/4000] Training [7/16] Loss: 0.00639 +Epoch [1720/4000] Training [8/16] Loss: 0.00816 +Epoch [1720/4000] Training [9/16] Loss: 0.01002 +Epoch [1720/4000] Training [10/16] Loss: 0.00656 +Epoch [1720/4000] Training [11/16] Loss: 0.00646 +Epoch [1720/4000] Training [12/16] Loss: 0.00967 +Epoch [1720/4000] Training [13/16] Loss: 0.00865 +Epoch [1720/4000] Training [14/16] Loss: 0.00821 +Epoch [1720/4000] Training [15/16] Loss: 0.00975 +Epoch [1720/4000] Training [16/16] Loss: 0.00600 +Epoch [1720/4000] Training metric {'Train/mean dice_metric': 0.9950364828109741, 'Train/mean miou_metric': 0.9898926019668579, 'Train/mean f1': 0.9911323189735413, 'Train/mean precision': 0.9867497086524963, 'Train/mean recall': 0.9955540299415588, 'Train/mean hd95_metric': 1.0341686010360718} +Epoch [1720/4000] Validation [1/4] Loss: 0.24428 focal_loss 0.17070 dice_loss 0.07358 +Epoch [1720/4000] Validation [2/4] Loss: 0.47859 focal_loss 0.30771 dice_loss 0.17087 +Epoch [1720/4000] Validation [3/4] Loss: 0.20226 focal_loss 0.11491 dice_loss 0.08735 +Epoch [1720/4000] Validation [4/4] Loss: 0.23896 focal_loss 0.13710 dice_loss 0.10186 +Epoch [1720/4000] Validation metric {'Val/mean dice_metric': 0.9698971509933472, 'Val/mean miou_metric': 0.9532018899917603, 'Val/mean f1': 0.9747634530067444, 'Val/mean precision': 0.9729974865913391, 'Val/mean recall': 0.9765357971191406, 'Val/mean hd95_metric': 5.427496910095215} +Cheakpoint... +Epoch [1720/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698971509933472, 'Val/mean miou_metric': 0.9532018899917603, 'Val/mean f1': 0.9747634530067444, 'Val/mean precision': 0.9729974865913391, 'Val/mean recall': 0.9765357971191406, 'Val/mean hd95_metric': 5.427496910095215} +Epoch [1721/4000] Training [1/16] Loss: 0.00620 +Epoch [1721/4000] Training [2/16] Loss: 0.01152 +Epoch [1721/4000] Training [3/16] Loss: 0.00782 +Epoch [1721/4000] Training [4/16] Loss: 0.00709 +Epoch [1721/4000] Training [5/16] Loss: 0.00867 +Epoch [1721/4000] Training [6/16] Loss: 0.00711 +Epoch [1721/4000] Training [7/16] Loss: 0.00734 +Epoch [1721/4000] Training [8/16] Loss: 0.00654 +Epoch [1721/4000] Training [9/16] Loss: 0.00613 +Epoch [1721/4000] Training [10/16] Loss: 0.00757 +Epoch [1721/4000] Training [11/16] Loss: 0.00735 +Epoch [1721/4000] Training [12/16] Loss: 0.00700 +Epoch [1721/4000] Training [13/16] Loss: 0.00674 +Epoch [1721/4000] Training [14/16] Loss: 0.01034 +Epoch [1721/4000] Training [15/16] Loss: 0.00629 +Epoch [1721/4000] Training [16/16] Loss: 0.00668 +Epoch [1721/4000] Training metric {'Train/mean dice_metric': 0.9952883124351501, 'Train/mean miou_metric': 0.9903643727302551, 'Train/mean f1': 0.9913302063941956, 'Train/mean precision': 0.9869334101676941, 'Train/mean recall': 0.9957663416862488, 'Train/mean hd95_metric': 1.014869213104248} +Epoch [1721/4000] Validation [1/4] Loss: 0.22823 focal_loss 0.16591 dice_loss 0.06232 +Epoch [1721/4000] Validation [2/4] Loss: 0.33386 focal_loss 0.20264 dice_loss 0.13123 +Epoch [1721/4000] Validation [3/4] Loss: 0.18673 focal_loss 0.11854 dice_loss 0.06818 +Epoch [1721/4000] Validation [4/4] Loss: 0.31756 focal_loss 0.20057 dice_loss 0.11700 +Epoch [1721/4000] Validation metric {'Val/mean dice_metric': 0.9716191291809082, 'Val/mean miou_metric': 0.9545187950134277, 'Val/mean f1': 0.9750636219978333, 'Val/mean precision': 0.9730351567268372, 'Val/mean recall': 0.9771006107330322, 'Val/mean hd95_metric': 5.4200439453125} +Cheakpoint... +Epoch [1721/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716191291809082, 'Val/mean miou_metric': 0.9545187950134277, 'Val/mean f1': 0.9750636219978333, 'Val/mean precision': 0.9730351567268372, 'Val/mean recall': 0.9771006107330322, 'Val/mean hd95_metric': 5.4200439453125} +Epoch [1722/4000] Training [1/16] Loss: 0.00743 +Epoch [1722/4000] Training [2/16] Loss: 0.00785 +Epoch [1722/4000] Training [3/16] Loss: 0.01547 +Epoch [1722/4000] Training [4/16] Loss: 0.00599 +Epoch [1722/4000] Training [5/16] Loss: 0.00798 +Epoch [1722/4000] Training [6/16] Loss: 0.00767 +Epoch [1722/4000] Training [7/16] Loss: 0.00829 +Epoch [1722/4000] Training [8/16] Loss: 0.00696 +Epoch [1722/4000] Training [9/16] Loss: 0.00631 +Epoch [1722/4000] Training [10/16] Loss: 0.00566 +Epoch [1722/4000] Training [11/16] Loss: 0.00560 +Epoch [1722/4000] Training [12/16] Loss: 0.00817 +Epoch [1722/4000] Training [13/16] Loss: 0.00624 +Epoch [1722/4000] Training [14/16] Loss: 0.00702 +Epoch [1722/4000] Training [15/16] Loss: 0.00751 +Epoch [1722/4000] Training [16/16] Loss: 0.00543 +Epoch [1722/4000] Training metric {'Train/mean dice_metric': 0.9950571656227112, 'Train/mean miou_metric': 0.9898930788040161, 'Train/mean f1': 0.9906997084617615, 'Train/mean precision': 0.9858642816543579, 'Train/mean recall': 0.9955827593803406, 'Train/mean hd95_metric': 1.0606415271759033} +Epoch [1722/4000] Validation [1/4] Loss: 0.35405 focal_loss 0.25630 dice_loss 0.09774 +Epoch [1722/4000] Validation [2/4] Loss: 0.37421 focal_loss 0.24188 dice_loss 0.13232 +Epoch [1722/4000] Validation [3/4] Loss: 0.15753 focal_loss 0.10024 dice_loss 0.05729 +Epoch [1722/4000] Validation [4/4] Loss: 0.18144 focal_loss 0.10826 dice_loss 0.07319 +Epoch [1722/4000] Validation metric {'Val/mean dice_metric': 0.9712244272232056, 'Val/mean miou_metric': 0.9544976949691772, 'Val/mean f1': 0.9737269878387451, 'Val/mean precision': 0.9745934009552002, 'Val/mean recall': 0.9728620648384094, 'Val/mean hd95_metric': 5.1059770584106445} +Cheakpoint... +Epoch [1722/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712244272232056, 'Val/mean miou_metric': 0.9544976949691772, 'Val/mean f1': 0.9737269878387451, 'Val/mean precision': 0.9745934009552002, 'Val/mean recall': 0.9728620648384094, 'Val/mean hd95_metric': 5.1059770584106445} +Epoch [1723/4000] Training [1/16] Loss: 0.00544 +Epoch [1723/4000] Training [2/16] Loss: 0.00568 +Epoch [1723/4000] Training [3/16] Loss: 0.00628 +Epoch [1723/4000] Training [4/16] Loss: 0.00694 +Epoch [1723/4000] Training [5/16] Loss: 0.00515 +Epoch [1723/4000] Training [6/16] Loss: 0.00681 +Epoch [1723/4000] Training [7/16] Loss: 0.00667 +Epoch [1723/4000] Training [8/16] Loss: 0.00675 +Epoch [1723/4000] Training [9/16] Loss: 0.00676 +Epoch [1723/4000] Training [10/16] Loss: 0.00631 +Epoch [1723/4000] Training [11/16] Loss: 0.00712 +Epoch [1723/4000] Training [12/16] Loss: 0.00658 +Epoch [1723/4000] Training [13/16] Loss: 0.00604 +Epoch [1723/4000] Training [14/16] Loss: 0.01020 +Epoch [1723/4000] Training [15/16] Loss: 0.00838 +Epoch [1723/4000] Training [16/16] Loss: 0.00598 +Epoch [1723/4000] Training metric {'Train/mean dice_metric': 0.9954307675361633, 'Train/mean miou_metric': 0.9906059503555298, 'Train/mean f1': 0.9906217455863953, 'Train/mean precision': 0.9854789972305298, 'Train/mean recall': 0.9958184361457825, 'Train/mean hd95_metric': 1.0106210708618164} +Epoch [1723/4000] Validation [1/4] Loss: 0.50162 focal_loss 0.38195 dice_loss 0.11968 +Epoch [1723/4000] Validation [2/4] Loss: 0.43783 focal_loss 0.26725 dice_loss 0.17058 +Epoch [1723/4000] Validation [3/4] Loss: 0.16798 focal_loss 0.10384 dice_loss 0.06414 +Epoch [1723/4000] Validation [4/4] Loss: 0.22757 focal_loss 0.14295 dice_loss 0.08462 +Epoch [1723/4000] Validation metric {'Val/mean dice_metric': 0.9717363119125366, 'Val/mean miou_metric': 0.9544979929924011, 'Val/mean f1': 0.9723696112632751, 'Val/mean precision': 0.9736371040344238, 'Val/mean recall': 0.9711055755615234, 'Val/mean hd95_metric': 5.312160491943359} +Cheakpoint... +Epoch [1723/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717363119125366, 'Val/mean miou_metric': 0.9544979929924011, 'Val/mean f1': 0.9723696112632751, 'Val/mean precision': 0.9736371040344238, 'Val/mean recall': 0.9711055755615234, 'Val/mean hd95_metric': 5.312160491943359} +Epoch [1724/4000] Training [1/16] Loss: 0.00699 +Epoch [1724/4000] Training [2/16] Loss: 0.00756 +Epoch [1724/4000] Training [3/16] Loss: 0.00602 +Epoch [1724/4000] Training [4/16] Loss: 0.00765 +Epoch [1724/4000] Training [5/16] Loss: 0.00918 +Epoch [1724/4000] Training [6/16] Loss: 0.00648 +Epoch [1724/4000] Training [7/16] Loss: 0.00638 +Epoch [1724/4000] Training [8/16] Loss: 0.00508 +Epoch [1724/4000] Training [9/16] Loss: 0.00919 +Epoch [1724/4000] Training [10/16] Loss: 0.00705 +Epoch [1724/4000] Training [11/16] Loss: 0.00700 +Epoch [1724/4000] Training [12/16] Loss: 0.00801 +Epoch [1724/4000] Training [13/16] Loss: 0.00839 +Epoch [1724/4000] Training [14/16] Loss: 0.00627 +Epoch [1724/4000] Training [15/16] Loss: 0.01121 +Epoch [1724/4000] Training [16/16] Loss: 0.00820 +Epoch [1724/4000] Training metric {'Train/mean dice_metric': 0.9946949481964111, 'Train/mean miou_metric': 0.9892030954360962, 'Train/mean f1': 0.9907666444778442, 'Train/mean precision': 0.9860565662384033, 'Train/mean recall': 0.9955218434333801, 'Train/mean hd95_metric': 1.0384198427200317} +Epoch [1724/4000] Validation [1/4] Loss: 0.61020 focal_loss 0.45823 dice_loss 0.15197 +Epoch [1724/4000] Validation [2/4] Loss: 0.49275 focal_loss 0.30816 dice_loss 0.18460 +Epoch [1724/4000] Validation [3/4] Loss: 0.18912 focal_loss 0.11905 dice_loss 0.07007 +Epoch [1724/4000] Validation [4/4] Loss: 0.20999 focal_loss 0.11732 dice_loss 0.09267 +Epoch [1724/4000] Validation metric {'Val/mean dice_metric': 0.9719109535217285, 'Val/mean miou_metric': 0.9537954330444336, 'Val/mean f1': 0.9717236161231995, 'Val/mean precision': 0.9743074178695679, 'Val/mean recall': 0.9691533446311951, 'Val/mean hd95_metric': 5.214039325714111} +Cheakpoint... +Epoch [1724/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719109535217285, 'Val/mean miou_metric': 0.9537954330444336, 'Val/mean f1': 0.9717236161231995, 'Val/mean precision': 0.9743074178695679, 'Val/mean recall': 0.9691533446311951, 'Val/mean hd95_metric': 5.214039325714111} +Epoch [1725/4000] Training [1/16] Loss: 0.00608 +Epoch [1725/4000] Training [2/16] Loss: 0.00635 +Epoch [1725/4000] Training [3/16] Loss: 0.00527 +Epoch [1725/4000] Training [4/16] Loss: 0.00616 +Epoch [1725/4000] Training [5/16] Loss: 0.00672 +Epoch [1725/4000] Training [6/16] Loss: 0.00679 +Epoch [1725/4000] Training [7/16] Loss: 0.00548 +Epoch [1725/4000] Training [8/16] Loss: 0.00817 +Epoch [1725/4000] Training [9/16] Loss: 0.00483 +Epoch [1725/4000] Training [10/16] Loss: 0.00916 +Epoch [1725/4000] Training [11/16] Loss: 0.00713 +Epoch [1725/4000] Training [12/16] Loss: 0.00523 +Epoch [1725/4000] Training [13/16] Loss: 0.00770 +Epoch [1725/4000] Training [14/16] Loss: 0.00634 +Epoch [1725/4000] Training [15/16] Loss: 0.00666 +Epoch [1725/4000] Training [16/16] Loss: 0.00697 +Epoch [1725/4000] Training metric {'Train/mean dice_metric': 0.9955559968948364, 'Train/mean miou_metric': 0.9908888339996338, 'Train/mean f1': 0.9914103746414185, 'Train/mean precision': 0.9869376420974731, 'Train/mean recall': 0.9959237575531006, 'Train/mean hd95_metric': 1.0221530199050903} +Epoch [1725/4000] Validation [1/4] Loss: 0.28486 focal_loss 0.20242 dice_loss 0.08244 +Epoch [1725/4000] Validation [2/4] Loss: 0.42383 focal_loss 0.25779 dice_loss 0.16604 +Epoch [1725/4000] Validation [3/4] Loss: 0.35116 focal_loss 0.24871 dice_loss 0.10245 +Epoch [1725/4000] Validation [4/4] Loss: 0.22271 focal_loss 0.13376 dice_loss 0.08895 +Epoch [1725/4000] Validation metric {'Val/mean dice_metric': 0.9713095426559448, 'Val/mean miou_metric': 0.9540027379989624, 'Val/mean f1': 0.9740188717842102, 'Val/mean precision': 0.9738119840621948, 'Val/mean recall': 0.9742256999015808, 'Val/mean hd95_metric': 5.461733818054199} +Cheakpoint... +Epoch [1725/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713095426559448, 'Val/mean miou_metric': 0.9540027379989624, 'Val/mean f1': 0.9740188717842102, 'Val/mean precision': 0.9738119840621948, 'Val/mean recall': 0.9742256999015808, 'Val/mean hd95_metric': 5.461733818054199} +Epoch [1726/4000] Training [1/16] Loss: 0.00594 +Epoch [1726/4000] Training [2/16] Loss: 0.00630 +Epoch [1726/4000] Training [3/16] Loss: 0.00745 +Epoch [1726/4000] Training [4/16] Loss: 0.00601 +Epoch [1726/4000] Training [5/16] Loss: 0.00447 +Epoch [1726/4000] Training [6/16] Loss: 0.00983 +Epoch [1726/4000] Training [7/16] Loss: 0.00657 +Epoch [1726/4000] Training [8/16] Loss: 0.00637 +Epoch [1726/4000] Training [9/16] Loss: 0.00578 +Epoch [1726/4000] Training [10/16] Loss: 0.00652 +Epoch [1726/4000] Training [11/16] Loss: 0.00673 +Epoch [1726/4000] Training [12/16] Loss: 0.00680 +Epoch [1726/4000] Training [13/16] Loss: 0.00853 +Epoch [1726/4000] Training [14/16] Loss: 0.00607 +Epoch [1726/4000] Training [15/16] Loss: 0.00514 +Epoch [1726/4000] Training [16/16] Loss: 0.00891 +Epoch [1726/4000] Training metric {'Train/mean dice_metric': 0.9953096508979797, 'Train/mean miou_metric': 0.9904103875160217, 'Train/mean f1': 0.9913897514343262, 'Train/mean precision': 0.9869331121444702, 'Train/mean recall': 0.9958867430686951, 'Train/mean hd95_metric': 1.0226393938064575} +Epoch [1726/4000] Validation [1/4] Loss: 0.52837 focal_loss 0.41201 dice_loss 0.11636 +Epoch [1726/4000] Validation [2/4] Loss: 0.30726 focal_loss 0.18590 dice_loss 0.12136 +Epoch [1726/4000] Validation [3/4] Loss: 0.26690 focal_loss 0.18333 dice_loss 0.08357 +Epoch [1726/4000] Validation [4/4] Loss: 0.18856 focal_loss 0.09912 dice_loss 0.08944 +Epoch [1726/4000] Validation metric {'Val/mean dice_metric': 0.9713493585586548, 'Val/mean miou_metric': 0.9536802172660828, 'Val/mean f1': 0.9728139042854309, 'Val/mean precision': 0.9748997092247009, 'Val/mean recall': 0.9707369208335876, 'Val/mean hd95_metric': 5.0892558097839355} +Cheakpoint... +Epoch [1726/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713493585586548, 'Val/mean miou_metric': 0.9536802172660828, 'Val/mean f1': 0.9728139042854309, 'Val/mean precision': 0.9748997092247009, 'Val/mean recall': 0.9707369208335876, 'Val/mean hd95_metric': 5.0892558097839355} +Epoch [1727/4000] Training [1/16] Loss: 0.00632 +Epoch [1727/4000] Training [2/16] Loss: 0.00738 +Epoch [1727/4000] Training [3/16] Loss: 0.00706 +Epoch [1727/4000] Training [4/16] Loss: 0.00774 +Epoch [1727/4000] Training [5/16] Loss: 0.00756 +Epoch [1727/4000] Training [6/16] Loss: 0.00555 +Epoch [1727/4000] Training [7/16] Loss: 0.00698 +Epoch [1727/4000] Training [8/16] Loss: 0.00591 +Epoch [1727/4000] Training [9/16] Loss: 0.00720 +Epoch [1727/4000] Training [10/16] Loss: 0.00851 +Epoch [1727/4000] Training [11/16] Loss: 0.00828 +Epoch [1727/4000] Training [12/16] Loss: 0.00597 +Epoch [1727/4000] Training [13/16] Loss: 0.00655 +Epoch [1727/4000] Training [14/16] Loss: 0.00568 +Epoch [1727/4000] Training [15/16] Loss: 0.00884 +Epoch [1727/4000] Training [16/16] Loss: 0.00650 +Epoch [1727/4000] Training metric {'Train/mean dice_metric': 0.9950912594795227, 'Train/mean miou_metric': 0.9899727702140808, 'Train/mean f1': 0.9909754395484924, 'Train/mean precision': 0.9862837791442871, 'Train/mean recall': 0.9957119822502136, 'Train/mean hd95_metric': 1.0425703525543213} +Epoch [1727/4000] Validation [1/4] Loss: 0.47188 focal_loss 0.36458 dice_loss 0.10731 +Epoch [1727/4000] Validation [2/4] Loss: 0.81678 focal_loss 0.51892 dice_loss 0.29786 +Epoch [1727/4000] Validation [3/4] Loss: 0.15356 focal_loss 0.09627 dice_loss 0.05729 +Epoch [1727/4000] Validation [4/4] Loss: 0.24570 focal_loss 0.14712 dice_loss 0.09858 +Epoch [1727/4000] Validation metric {'Val/mean dice_metric': 0.9714195132255554, 'Val/mean miou_metric': 0.9542516469955444, 'Val/mean f1': 0.9732859134674072, 'Val/mean precision': 0.9751647114753723, 'Val/mean recall': 0.9714144468307495, 'Val/mean hd95_metric': 4.869835376739502} +Cheakpoint... +Epoch [1727/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714195132255554, 'Val/mean miou_metric': 0.9542516469955444, 'Val/mean f1': 0.9732859134674072, 'Val/mean precision': 0.9751647114753723, 'Val/mean recall': 0.9714144468307495, 'Val/mean hd95_metric': 4.869835376739502} +Epoch [1728/4000] Training [1/16] Loss: 0.00697 +Epoch [1728/4000] Training [2/16] Loss: 0.00716 +Epoch [1728/4000] Training [3/16] Loss: 0.00567 +Epoch [1728/4000] Training [4/16] Loss: 0.00655 +Epoch [1728/4000] Training [5/16] Loss: 0.00737 +Epoch [1728/4000] Training [6/16] Loss: 0.00518 +Epoch [1728/4000] Training [7/16] Loss: 0.00615 +Epoch [1728/4000] Training [8/16] Loss: 0.00683 +Epoch [1728/4000] Training [9/16] Loss: 0.00961 +Epoch [1728/4000] Training [10/16] Loss: 0.00808 +Epoch [1728/4000] Training [11/16] Loss: 0.00808 +Epoch [1728/4000] Training [12/16] Loss: 0.00630 +Epoch [1728/4000] Training [13/16] Loss: 0.00784 +Epoch [1728/4000] Training [14/16] Loss: 0.00829 +Epoch [1728/4000] Training [15/16] Loss: 0.00771 +Epoch [1728/4000] Training [16/16] Loss: 0.00553 +Epoch [1728/4000] Training metric {'Train/mean dice_metric': 0.994956374168396, 'Train/mean miou_metric': 0.9896979928016663, 'Train/mean f1': 0.9906565546989441, 'Train/mean precision': 0.9858381152153015, 'Train/mean recall': 0.9955223202705383, 'Train/mean hd95_metric': 1.0628782510757446} +Epoch [1728/4000] Validation [1/4] Loss: 0.25646 focal_loss 0.18923 dice_loss 0.06723 +Epoch [1728/4000] Validation [2/4] Loss: 0.37201 focal_loss 0.21755 dice_loss 0.15447 +Epoch [1728/4000] Validation [3/4] Loss: 0.19943 focal_loss 0.12380 dice_loss 0.07563 +Epoch [1728/4000] Validation [4/4] Loss: 0.29364 focal_loss 0.18436 dice_loss 0.10928 +Epoch [1728/4000] Validation metric {'Val/mean dice_metric': 0.9721752405166626, 'Val/mean miou_metric': 0.9540689587593079, 'Val/mean f1': 0.9737827181816101, 'Val/mean precision': 0.973532497882843, 'Val/mean recall': 0.974032998085022, 'Val/mean hd95_metric': 5.391078472137451} +Cheakpoint... +Epoch [1728/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721752405166626, 'Val/mean miou_metric': 0.9540689587593079, 'Val/mean f1': 0.9737827181816101, 'Val/mean precision': 0.973532497882843, 'Val/mean recall': 0.974032998085022, 'Val/mean hd95_metric': 5.391078472137451} +Epoch [1729/4000] Training [1/16] Loss: 0.00678 +Epoch [1729/4000] Training [2/16] Loss: 0.00765 +Epoch [1729/4000] Training [3/16] Loss: 0.00784 +Epoch [1729/4000] Training [4/16] Loss: 0.01148 +Epoch [1729/4000] Training [5/16] Loss: 0.00987 +Epoch [1729/4000] Training [6/16] Loss: 0.01053 +Epoch [1729/4000] Training [7/16] Loss: 0.00843 +Epoch [1729/4000] Training [8/16] Loss: 0.00652 +Epoch [1729/4000] Training [9/16] Loss: 0.00900 +Epoch [1729/4000] Training [10/16] Loss: 0.01203 +Epoch [1729/4000] Training [11/16] Loss: 0.00566 +Epoch [1729/4000] Training [12/16] Loss: 0.00645 +Epoch [1729/4000] Training [13/16] Loss: 0.00621 +Epoch [1729/4000] Training [14/16] Loss: 0.00700 +Epoch [1729/4000] Training [15/16] Loss: 0.00658 +Epoch [1729/4000] Training [16/16] Loss: 0.00714 +Epoch [1729/4000] Training metric {'Train/mean dice_metric': 0.9945106506347656, 'Train/mean miou_metric': 0.9888542294502258, 'Train/mean f1': 0.9908232688903809, 'Train/mean precision': 0.9864166975021362, 'Train/mean recall': 0.9952693581581116, 'Train/mean hd95_metric': 1.1586148738861084} +Epoch [1729/4000] Validation [1/4] Loss: 0.88499 focal_loss 0.74321 dice_loss 0.14178 +Epoch [1729/4000] Validation [2/4] Loss: 0.76450 focal_loss 0.45461 dice_loss 0.30989 +Epoch [1729/4000] Validation [3/4] Loss: 0.18297 focal_loss 0.11301 dice_loss 0.06996 +Epoch [1729/4000] Validation [4/4] Loss: 0.31764 focal_loss 0.20199 dice_loss 0.11565 +Epoch [1729/4000] Validation metric {'Val/mean dice_metric': 0.9656481742858887, 'Val/mean miou_metric': 0.9481526613235474, 'Val/mean f1': 0.968711793422699, 'Val/mean precision': 0.975358247756958, 'Val/mean recall': 0.9621553421020508, 'Val/mean hd95_metric': 5.360766410827637} +Cheakpoint... +Epoch [1729/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9656481742858887, 'Val/mean miou_metric': 0.9481526613235474, 'Val/mean f1': 0.968711793422699, 'Val/mean precision': 0.975358247756958, 'Val/mean recall': 0.9621553421020508, 'Val/mean hd95_metric': 5.360766410827637} +Epoch [1730/4000] Training [1/16] Loss: 0.00805 +Epoch [1730/4000] Training [2/16] Loss: 0.00558 +Epoch [1730/4000] Training [3/16] Loss: 0.00613 +Epoch [1730/4000] Training [4/16] Loss: 0.00632 +Epoch [1730/4000] Training [5/16] Loss: 0.00717 +Epoch [1730/4000] Training [6/16] Loss: 0.01009 +Epoch [1730/4000] Training [7/16] Loss: 0.00621 +Epoch [1730/4000] Training [8/16] Loss: 0.00742 +Epoch [1730/4000] Training [9/16] Loss: 0.00777 +Epoch [1730/4000] Training [10/16] Loss: 0.01121 +Epoch [1730/4000] Training [11/16] Loss: 0.00672 +Epoch [1730/4000] Training [12/16] Loss: 0.00552 +Epoch [1730/4000] Training [13/16] Loss: 0.00658 +Epoch [1730/4000] Training [14/16] Loss: 0.00763 +Epoch [1730/4000] Training [15/16] Loss: 0.00670 +Epoch [1730/4000] Training [16/16] Loss: 0.00511 +Epoch [1730/4000] Training metric {'Train/mean dice_metric': 0.9953168630599976, 'Train/mean miou_metric': 0.9904084205627441, 'Train/mean f1': 0.9910284876823425, 'Train/mean precision': 0.986248791217804, 'Train/mean recall': 0.9958547949790955, 'Train/mean hd95_metric': 1.0286428928375244} +Epoch [1730/4000] Validation [1/4] Loss: 0.88393 focal_loss 0.69532 dice_loss 0.18861 +Epoch [1730/4000] Validation [2/4] Loss: 0.33672 focal_loss 0.19874 dice_loss 0.13798 +Epoch [1730/4000] Validation [3/4] Loss: 0.14146 focal_loss 0.08733 dice_loss 0.05413 +Epoch [1730/4000] Validation [4/4] Loss: 0.23338 focal_loss 0.13722 dice_loss 0.09616 +Epoch [1730/4000] Validation metric {'Val/mean dice_metric': 0.9676801562309265, 'Val/mean miou_metric': 0.9514114260673523, 'Val/mean f1': 0.9706668853759766, 'Val/mean precision': 0.9743874669075012, 'Val/mean recall': 0.9669747948646545, 'Val/mean hd95_metric': 5.390261173248291} +Cheakpoint... +Epoch [1730/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676801562309265, 'Val/mean miou_metric': 0.9514114260673523, 'Val/mean f1': 0.9706668853759766, 'Val/mean precision': 0.9743874669075012, 'Val/mean recall': 0.9669747948646545, 'Val/mean hd95_metric': 5.390261173248291} +Epoch [1731/4000] Training [1/16] Loss: 0.00596 +Epoch [1731/4000] Training [2/16] Loss: 0.00693 +Epoch [1731/4000] Training [3/16] Loss: 0.00460 +Epoch [1731/4000] Training [4/16] Loss: 0.00689 +Epoch [1731/4000] Training [5/16] Loss: 0.01557 +Epoch [1731/4000] Training [6/16] Loss: 0.00607 +Epoch [1731/4000] Training [7/16] Loss: 0.00764 +Epoch [1731/4000] Training [8/16] Loss: 0.00930 +Epoch [1731/4000] Training [9/16] Loss: 0.00689 +Epoch [1731/4000] Training [10/16] Loss: 0.01812 +Epoch [1731/4000] Training [11/16] Loss: 0.00489 +Epoch [1731/4000] Training [12/16] Loss: 0.01049 +Epoch [1731/4000] Training [13/16] Loss: 0.00612 +Epoch [1731/4000] Training [14/16] Loss: 0.00666 +Epoch [1731/4000] Training [15/16] Loss: 0.00906 +Epoch [1731/4000] Training [16/16] Loss: 0.00817 +Epoch [1731/4000] Training metric {'Train/mean dice_metric': 0.9948312044143677, 'Train/mean miou_metric': 0.9894936084747314, 'Train/mean f1': 0.9909945726394653, 'Train/mean precision': 0.9864403009414673, 'Train/mean recall': 0.9955911040306091, 'Train/mean hd95_metric': 1.0857172012329102} +Epoch [1731/4000] Validation [1/4] Loss: 0.93834 focal_loss 0.79435 dice_loss 0.14399 +Epoch [1731/4000] Validation [2/4] Loss: 0.35879 focal_loss 0.20341 dice_loss 0.15539 +Epoch [1731/4000] Validation [3/4] Loss: 0.14829 focal_loss 0.09795 dice_loss 0.05034 +Epoch [1731/4000] Validation [4/4] Loss: 0.36048 focal_loss 0.22410 dice_loss 0.13637 +Epoch [1731/4000] Validation metric {'Val/mean dice_metric': 0.9680862426757812, 'Val/mean miou_metric': 0.9508072733879089, 'Val/mean f1': 0.9702108502388, 'Val/mean precision': 0.9712682366371155, 'Val/mean recall': 0.9691558480262756, 'Val/mean hd95_metric': 5.5182204246521} +Cheakpoint... +Epoch [1731/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680862426757812, 'Val/mean miou_metric': 0.9508072733879089, 'Val/mean f1': 0.9702108502388, 'Val/mean precision': 0.9712682366371155, 'Val/mean recall': 0.9691558480262756, 'Val/mean hd95_metric': 5.5182204246521} +Epoch [1732/4000] Training [1/16] Loss: 0.00830 +Epoch [1732/4000] Training [2/16] Loss: 0.00632 +Epoch [1732/4000] Training [3/16] Loss: 0.00689 +Epoch [1732/4000] Training [4/16] Loss: 0.00578 +Epoch [1732/4000] Training [5/16] Loss: 0.00682 +Epoch [1732/4000] Training [6/16] Loss: 0.00713 +Epoch [1732/4000] Training [7/16] Loss: 0.00622 +Epoch [1732/4000] Training [8/16] Loss: 0.00565 +Epoch [1732/4000] Training [9/16] Loss: 0.00647 +Epoch [1732/4000] Training [10/16] Loss: 0.00790 +Epoch [1732/4000] Training [11/16] Loss: 0.00670 +Epoch [1732/4000] Training [12/16] Loss: 0.00923 +Epoch [1732/4000] Training [13/16] Loss: 0.00676 +Epoch [1732/4000] Training [14/16] Loss: 0.00586 +Epoch [1732/4000] Training [15/16] Loss: 0.00915 +Epoch [1732/4000] Training [16/16] Loss: 0.00741 +Epoch [1732/4000] Training metric {'Train/mean dice_metric': 0.9952355027198792, 'Train/mean miou_metric': 0.9902430176734924, 'Train/mean f1': 0.9908856749534607, 'Train/mean precision': 0.986095130443573, 'Train/mean recall': 0.9957230091094971, 'Train/mean hd95_metric': 1.058412790298462} +Epoch [1732/4000] Validation [1/4] Loss: 0.46564 focal_loss 0.35010 dice_loss 0.11554 +Epoch [1732/4000] Validation [2/4] Loss: 0.89866 focal_loss 0.63359 dice_loss 0.26507 +Epoch [1732/4000] Validation [3/4] Loss: 0.24873 focal_loss 0.15716 dice_loss 0.09158 +Epoch [1732/4000] Validation [4/4] Loss: 0.29366 focal_loss 0.17870 dice_loss 0.11496 +Epoch [1732/4000] Validation metric {'Val/mean dice_metric': 0.9675582051277161, 'Val/mean miou_metric': 0.9499484896659851, 'Val/mean f1': 0.9701917767524719, 'Val/mean precision': 0.9695264101028442, 'Val/mean recall': 0.9708579778671265, 'Val/mean hd95_metric': 5.5473480224609375} +Cheakpoint... +Epoch [1732/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675582051277161, 'Val/mean miou_metric': 0.9499484896659851, 'Val/mean f1': 0.9701917767524719, 'Val/mean precision': 0.9695264101028442, 'Val/mean recall': 0.9708579778671265, 'Val/mean hd95_metric': 5.5473480224609375} +Epoch [1733/4000] Training [1/16] Loss: 0.00614 +Epoch [1733/4000] Training [2/16] Loss: 0.00686 +Epoch [1733/4000] Training [3/16] Loss: 0.00722 +Epoch [1733/4000] Training [4/16] Loss: 0.00683 +Epoch [1733/4000] Training [5/16] Loss: 0.00721 +Epoch [1733/4000] Training [6/16] Loss: 0.00605 +Epoch [1733/4000] Training [7/16] Loss: 0.00591 +Epoch [1733/4000] Training [8/16] Loss: 0.00637 +Epoch [1733/4000] Training [9/16] Loss: 0.00936 +Epoch [1733/4000] Training [10/16] Loss: 0.00877 +Epoch [1733/4000] Training [11/16] Loss: 0.00949 +Epoch [1733/4000] Training [12/16] Loss: 0.00772 +Epoch [1733/4000] Training [13/16] Loss: 0.00813 +Epoch [1733/4000] Training [14/16] Loss: 0.00819 +Epoch [1733/4000] Training [15/16] Loss: 0.00823 +Epoch [1733/4000] Training [16/16] Loss: 0.00738 +Epoch [1733/4000] Training metric {'Train/mean dice_metric': 0.9950469136238098, 'Train/mean miou_metric': 0.9898797273635864, 'Train/mean f1': 0.9908844828605652, 'Train/mean precision': 0.9863017201423645, 'Train/mean recall': 0.9955099821090698, 'Train/mean hd95_metric': 1.0587674379348755} +Epoch [1733/4000] Validation [1/4] Loss: 0.41316 focal_loss 0.30895 dice_loss 0.10421 +Epoch [1733/4000] Validation [2/4] Loss: 0.62058 focal_loss 0.39376 dice_loss 0.22682 +Epoch [1733/4000] Validation [3/4] Loss: 0.28752 focal_loss 0.19454 dice_loss 0.09298 +Epoch [1733/4000] Validation [4/4] Loss: 0.25739 focal_loss 0.14861 dice_loss 0.10878 +Epoch [1733/4000] Validation metric {'Val/mean dice_metric': 0.9679843783378601, 'Val/mean miou_metric': 0.9506756663322449, 'Val/mean f1': 0.9713913202285767, 'Val/mean precision': 0.9701569676399231, 'Val/mean recall': 0.9726287722587585, 'Val/mean hd95_metric': 5.693561553955078} +Cheakpoint... +Epoch [1733/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679843783378601, 'Val/mean miou_metric': 0.9506756663322449, 'Val/mean f1': 0.9713913202285767, 'Val/mean precision': 0.9701569676399231, 'Val/mean recall': 0.9726287722587585, 'Val/mean hd95_metric': 5.693561553955078} +Epoch [1734/4000] Training [1/16] Loss: 0.00709 +Epoch [1734/4000] Training [2/16] Loss: 0.00709 +Epoch [1734/4000] Training [3/16] Loss: 0.01634 +Epoch [1734/4000] Training [4/16] Loss: 0.00898 +Epoch [1734/4000] Training [5/16] Loss: 0.00853 +Epoch [1734/4000] Training [6/16] Loss: 0.00664 +Epoch [1734/4000] Training [7/16] Loss: 0.00660 +Epoch [1734/4000] Training [8/16] Loss: 0.00720 +Epoch [1734/4000] Training [9/16] Loss: 0.00579 +Epoch [1734/4000] Training [10/16] Loss: 0.00648 +Epoch [1734/4000] Training [11/16] Loss: 0.00712 +Epoch [1734/4000] Training [12/16] Loss: 0.00760 +Epoch [1734/4000] Training [13/16] Loss: 0.00916 +Epoch [1734/4000] Training [14/16] Loss: 0.00622 +Epoch [1734/4000] Training [15/16] Loss: 0.00767 +Epoch [1734/4000] Training [16/16] Loss: 0.00746 +Epoch [1734/4000] Training metric {'Train/mean dice_metric': 0.9948514699935913, 'Train/mean miou_metric': 0.9895237684249878, 'Train/mean f1': 0.9910095930099487, 'Train/mean precision': 0.9865631461143494, 'Train/mean recall': 0.9954962730407715, 'Train/mean hd95_metric': 1.047914981842041} +Epoch [1734/4000] Validation [1/4] Loss: 0.28165 focal_loss 0.21863 dice_loss 0.06302 +Epoch [1734/4000] Validation [2/4] Loss: 0.35566 focal_loss 0.20138 dice_loss 0.15429 +Epoch [1734/4000] Validation [3/4] Loss: 0.22125 focal_loss 0.13963 dice_loss 0.08162 +Epoch [1734/4000] Validation [4/4] Loss: 0.24061 focal_loss 0.15231 dice_loss 0.08830 +Epoch [1734/4000] Validation metric {'Val/mean dice_metric': 0.9734538197517395, 'Val/mean miou_metric': 0.9564306139945984, 'Val/mean f1': 0.9757348299026489, 'Val/mean precision': 0.972627580165863, 'Val/mean recall': 0.9788620471954346, 'Val/mean hd95_metric': 5.744070529937744} +Cheakpoint... +Epoch [1734/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734538197517395, 'Val/mean miou_metric': 0.9564306139945984, 'Val/mean f1': 0.9757348299026489, 'Val/mean precision': 0.972627580165863, 'Val/mean recall': 0.9788620471954346, 'Val/mean hd95_metric': 5.744070529937744} +Epoch [1735/4000] Training [1/16] Loss: 0.00604 +Epoch [1735/4000] Training [2/16] Loss: 0.00565 +Epoch [1735/4000] Training [3/16] Loss: 0.00557 +Epoch [1735/4000] Training [4/16] Loss: 0.00522 +Epoch [1735/4000] Training [5/16] Loss: 0.00523 +Epoch [1735/4000] Training [6/16] Loss: 0.00665 +Epoch [1735/4000] Training [7/16] Loss: 0.00665 +Epoch [1735/4000] Training [8/16] Loss: 0.00516 +Epoch [1735/4000] Training [9/16] Loss: 0.00687 +Epoch [1735/4000] Training [10/16] Loss: 0.00613 +Epoch [1735/4000] Training [11/16] Loss: 0.00695 +Epoch [1735/4000] Training [12/16] Loss: 0.00722 +Epoch [1735/4000] Training [13/16] Loss: 0.00705 +Epoch [1735/4000] Training [14/16] Loss: 0.00759 +Epoch [1735/4000] Training [15/16] Loss: 0.00661 +Epoch [1735/4000] Training [16/16] Loss: 0.01472 +Epoch [1735/4000] Training metric {'Train/mean dice_metric': 0.9956064820289612, 'Train/mean miou_metric': 0.9909375905990601, 'Train/mean f1': 0.9902381896972656, 'Train/mean precision': 0.9847000241279602, 'Train/mean recall': 0.9958390593528748, 'Train/mean hd95_metric': 1.0235247611999512} +Epoch [1735/4000] Validation [1/4] Loss: 0.31392 focal_loss 0.24048 dice_loss 0.07344 +Epoch [1735/4000] Validation [2/4] Loss: 0.29986 focal_loss 0.16663 dice_loss 0.13324 +Epoch [1735/4000] Validation [3/4] Loss: 0.24895 focal_loss 0.16134 dice_loss 0.08761 +Epoch [1735/4000] Validation [4/4] Loss: 0.21286 focal_loss 0.11573 dice_loss 0.09713 +Epoch [1735/4000] Validation metric {'Val/mean dice_metric': 0.9721781611442566, 'Val/mean miou_metric': 0.9557892084121704, 'Val/mean f1': 0.9736400246620178, 'Val/mean precision': 0.9704996347427368, 'Val/mean recall': 0.9768007397651672, 'Val/mean hd95_metric': 5.747422695159912} +Cheakpoint... +Epoch [1735/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721781611442566, 'Val/mean miou_metric': 0.9557892084121704, 'Val/mean f1': 0.9736400246620178, 'Val/mean precision': 0.9704996347427368, 'Val/mean recall': 0.9768007397651672, 'Val/mean hd95_metric': 5.747422695159912} +Epoch [1736/4000] Training [1/16] Loss: 0.00675 +Epoch [1736/4000] Training [2/16] Loss: 0.00545 +Epoch [1736/4000] Training [3/16] Loss: 0.00879 +Epoch [1736/4000] Training [4/16] Loss: 0.00651 +Epoch [1736/4000] Training [5/16] Loss: 0.01093 +Epoch [1736/4000] Training [6/16] Loss: 0.00770 +Epoch [1736/4000] Training [7/16] Loss: 0.00508 +Epoch [1736/4000] Training [8/16] Loss: 0.00564 +Epoch [1736/4000] Training [9/16] Loss: 0.00856 +Epoch [1736/4000] Training [10/16] Loss: 0.00565 +Epoch [1736/4000] Training [11/16] Loss: 0.00787 +Epoch [1736/4000] Training [12/16] Loss: 0.00675 +Epoch [1736/4000] Training [13/16] Loss: 0.00635 +Epoch [1736/4000] Training [14/16] Loss: 0.01173 +Epoch [1736/4000] Training [15/16] Loss: 0.00522 +Epoch [1736/4000] Training [16/16] Loss: 0.00701 +Epoch [1736/4000] Training metric {'Train/mean dice_metric': 0.9951159954071045, 'Train/mean miou_metric': 0.990016758441925, 'Train/mean f1': 0.990805447101593, 'Train/mean precision': 0.9861290454864502, 'Train/mean recall': 0.9955264925956726, 'Train/mean hd95_metric': 1.087791919708252} +Epoch [1736/4000] Validation [1/4] Loss: 0.32643 focal_loss 0.24349 dice_loss 0.08294 +Epoch [1736/4000] Validation [2/4] Loss: 0.52379 focal_loss 0.33179 dice_loss 0.19200 +Epoch [1736/4000] Validation [3/4] Loss: 0.30511 focal_loss 0.21319 dice_loss 0.09192 +Epoch [1736/4000] Validation [4/4] Loss: 0.19914 focal_loss 0.11172 dice_loss 0.08742 +Epoch [1736/4000] Validation metric {'Val/mean dice_metric': 0.9738920331001282, 'Val/mean miou_metric': 0.9559240341186523, 'Val/mean f1': 0.9736507534980774, 'Val/mean precision': 0.9721737504005432, 'Val/mean recall': 0.9751322865486145, 'Val/mean hd95_metric': 5.567731857299805} +Cheakpoint... +Epoch [1736/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738920331001282, 'Val/mean miou_metric': 0.9559240341186523, 'Val/mean f1': 0.9736507534980774, 'Val/mean precision': 0.9721737504005432, 'Val/mean recall': 0.9751322865486145, 'Val/mean hd95_metric': 5.567731857299805} +Epoch [1737/4000] Training [1/16] Loss: 0.00780 +Epoch [1737/4000] Training [2/16] Loss: 0.00831 +Epoch [1737/4000] Training [3/16] Loss: 0.00763 +Epoch [1737/4000] Training [4/16] Loss: 0.00693 +Epoch [1737/4000] Training [5/16] Loss: 0.00633 +Epoch [1737/4000] Training [6/16] Loss: 0.00535 +Epoch [1737/4000] Training [7/16] Loss: 0.00471 +Epoch [1737/4000] Training [8/16] Loss: 0.00830 +Epoch [1737/4000] Training [9/16] Loss: 0.00697 +Epoch [1737/4000] Training [10/16] Loss: 0.00665 +Epoch [1737/4000] Training [11/16] Loss: 0.00628 +Epoch [1737/4000] Training [12/16] Loss: 0.00737 +Epoch [1737/4000] Training [13/16] Loss: 0.00578 +Epoch [1737/4000] Training [14/16] Loss: 0.00667 +Epoch [1737/4000] Training [15/16] Loss: 0.00755 +Epoch [1737/4000] Training [16/16] Loss: 0.00679 +Epoch [1737/4000] Training metric {'Train/mean dice_metric': 0.9953830242156982, 'Train/mean miou_metric': 0.9905469417572021, 'Train/mean f1': 0.991217851638794, 'Train/mean precision': 0.9865902066230774, 'Train/mean recall': 0.9958891868591309, 'Train/mean hd95_metric': 1.0193812847137451} +Epoch [1737/4000] Validation [1/4] Loss: 0.26484 focal_loss 0.20021 dice_loss 0.06463 +Epoch [1737/4000] Validation [2/4] Loss: 0.30458 focal_loss 0.17459 dice_loss 0.12999 +Epoch [1737/4000] Validation [3/4] Loss: 0.36901 focal_loss 0.26272 dice_loss 0.10629 +Epoch [1737/4000] Validation [4/4] Loss: 0.26429 focal_loss 0.17022 dice_loss 0.09407 +Epoch [1737/4000] Validation metric {'Val/mean dice_metric': 0.9732387661933899, 'Val/mean miou_metric': 0.9558820724487305, 'Val/mean f1': 0.9745556116104126, 'Val/mean precision': 0.9702481627464294, 'Val/mean recall': 0.9789013862609863, 'Val/mean hd95_metric': 5.439175605773926} +Cheakpoint... +Epoch [1737/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732387661933899, 'Val/mean miou_metric': 0.9558820724487305, 'Val/mean f1': 0.9745556116104126, 'Val/mean precision': 0.9702481627464294, 'Val/mean recall': 0.9789013862609863, 'Val/mean hd95_metric': 5.439175605773926} +Epoch [1738/4000] Training [1/16] Loss: 0.00887 +Epoch [1738/4000] Training [2/16] Loss: 0.00606 +Epoch [1738/4000] Training [3/16] Loss: 0.00726 +Epoch [1738/4000] Training [4/16] Loss: 0.00636 +Epoch [1738/4000] Training [5/16] Loss: 0.00542 +Epoch [1738/4000] Training [6/16] Loss: 0.00841 +Epoch [1738/4000] Training [7/16] Loss: 0.01023 +Epoch [1738/4000] Training [8/16] Loss: 0.00786 +Epoch [1738/4000] Training [9/16] Loss: 0.00741 +Epoch [1738/4000] Training [10/16] Loss: 0.00742 +Epoch [1738/4000] Training [11/16] Loss: 0.00569 +Epoch [1738/4000] Training [12/16] Loss: 0.00580 +Epoch [1738/4000] Training [13/16] Loss: 0.00656 +Epoch [1738/4000] Training [14/16] Loss: 0.00672 +Epoch [1738/4000] Training [15/16] Loss: 0.00670 +Epoch [1738/4000] Training [16/16] Loss: 0.00817 +Epoch [1738/4000] Training metric {'Train/mean dice_metric': 0.9952664375305176, 'Train/mean miou_metric': 0.9902997016906738, 'Train/mean f1': 0.9905608296394348, 'Train/mean precision': 0.9854041337966919, 'Train/mean recall': 0.9957717657089233, 'Train/mean hd95_metric': 1.0130596160888672} +Epoch [1738/4000] Validation [1/4] Loss: 0.25639 focal_loss 0.19424 dice_loss 0.06215 +Epoch [1738/4000] Validation [2/4] Loss: 0.62057 focal_loss 0.40443 dice_loss 0.21614 +Epoch [1738/4000] Validation [3/4] Loss: 0.30098 focal_loss 0.20838 dice_loss 0.09260 +Epoch [1738/4000] Validation [4/4] Loss: 0.26081 focal_loss 0.15573 dice_loss 0.10508 +Epoch [1738/4000] Validation metric {'Val/mean dice_metric': 0.9735921621322632, 'Val/mean miou_metric': 0.956642746925354, 'Val/mean f1': 0.9747158885002136, 'Val/mean precision': 0.9707470536231995, 'Val/mean recall': 0.9787174463272095, 'Val/mean hd95_metric': 5.395281791687012} +Cheakpoint... +Epoch [1738/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735921621322632, 'Val/mean miou_metric': 0.956642746925354, 'Val/mean f1': 0.9747158885002136, 'Val/mean precision': 0.9707470536231995, 'Val/mean recall': 0.9787174463272095, 'Val/mean hd95_metric': 5.395281791687012} +Epoch [1739/4000] Training [1/16] Loss: 0.00675 +Epoch [1739/4000] Training [2/16] Loss: 0.00870 +Epoch [1739/4000] Training [3/16] Loss: 0.00487 +Epoch [1739/4000] Training [4/16] Loss: 0.00819 +Epoch [1739/4000] Training [5/16] Loss: 0.00595 +Epoch [1739/4000] Training [6/16] Loss: 0.00548 +Epoch [1739/4000] Training [7/16] Loss: 0.00764 +Epoch [1739/4000] Training [8/16] Loss: 0.03314 +Epoch [1739/4000] Training [9/16] Loss: 0.00716 +Epoch [1739/4000] Training [10/16] Loss: 0.00735 +Epoch [1739/4000] Training [11/16] Loss: 0.00650 +Epoch [1739/4000] Training [12/16] Loss: 0.00670 +Epoch [1739/4000] Training [13/16] Loss: 0.00705 +Epoch [1739/4000] Training [14/16] Loss: 0.00767 +Epoch [1739/4000] Training [15/16] Loss: 0.00734 +Epoch [1739/4000] Training [16/16] Loss: 0.00612 +Epoch [1739/4000] Training metric {'Train/mean dice_metric': 0.9948251247406006, 'Train/mean miou_metric': 0.9895406365394592, 'Train/mean f1': 0.9910591244697571, 'Train/mean precision': 0.9865860342979431, 'Train/mean recall': 0.9955728650093079, 'Train/mean hd95_metric': 1.261529564857483} +Epoch [1739/4000] Validation [1/4] Loss: 0.61066 focal_loss 0.49886 dice_loss 0.11181 +Epoch [1739/4000] Validation [2/4] Loss: 0.67967 focal_loss 0.43838 dice_loss 0.24128 +Epoch [1739/4000] Validation [3/4] Loss: 0.15703 focal_loss 0.09780 dice_loss 0.05923 +Epoch [1739/4000] Validation [4/4] Loss: 0.32439 focal_loss 0.19800 dice_loss 0.12639 +Epoch [1739/4000] Validation metric {'Val/mean dice_metric': 0.9666105508804321, 'Val/mean miou_metric': 0.9487981796264648, 'Val/mean f1': 0.9706464409828186, 'Val/mean precision': 0.9749455451965332, 'Val/mean recall': 0.9663850665092468, 'Val/mean hd95_metric': 5.191713809967041} +Cheakpoint... +Epoch [1739/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9666], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9666105508804321, 'Val/mean miou_metric': 0.9487981796264648, 'Val/mean f1': 0.9706464409828186, 'Val/mean precision': 0.9749455451965332, 'Val/mean recall': 0.9663850665092468, 'Val/mean hd95_metric': 5.191713809967041} +Epoch [1740/4000] Training [1/16] Loss: 0.00632 +Epoch [1740/4000] Training [2/16] Loss: 0.00617 +Epoch [1740/4000] Training [3/16] Loss: 0.00676 +Epoch [1740/4000] Training [4/16] Loss: 0.00719 +Epoch [1740/4000] Training [5/16] Loss: 0.00635 +Epoch [1740/4000] Training [6/16] Loss: 0.00872 +Epoch [1740/4000] Training [7/16] Loss: 0.00628 +Epoch [1740/4000] Training [8/16] Loss: 0.00673 +Epoch [1740/4000] Training [9/16] Loss: 0.00641 +Epoch [1740/4000] Training [10/16] Loss: 0.00634 +Epoch [1740/4000] Training [11/16] Loss: 0.00701 +Epoch [1740/4000] Training [12/16] Loss: 0.00613 +Epoch [1740/4000] Training [13/16] Loss: 0.00697 +Epoch [1740/4000] Training [14/16] Loss: 0.00623 +Epoch [1740/4000] Training [15/16] Loss: 0.00716 +Epoch [1740/4000] Training [16/16] Loss: 0.00642 +Epoch [1740/4000] Training metric {'Train/mean dice_metric': 0.9954109787940979, 'Train/mean miou_metric': 0.9906071424484253, 'Train/mean f1': 0.99122554063797, 'Train/mean precision': 0.9866676330566406, 'Train/mean recall': 0.9958257079124451, 'Train/mean hd95_metric': 1.0110416412353516} +Epoch [1740/4000] Validation [1/4] Loss: 0.61170 focal_loss 0.50625 dice_loss 0.10545 +Epoch [1740/4000] Validation [2/4] Loss: 0.60535 focal_loss 0.41458 dice_loss 0.19077 +Epoch [1740/4000] Validation [3/4] Loss: 0.30677 focal_loss 0.20492 dice_loss 0.10185 +Epoch [1740/4000] Validation [4/4] Loss: 0.20385 focal_loss 0.11731 dice_loss 0.08654 +Epoch [1740/4000] Validation metric {'Val/mean dice_metric': 0.9670357704162598, 'Val/mean miou_metric': 0.9509401321411133, 'Val/mean f1': 0.9722001552581787, 'Val/mean precision': 0.9738784432411194, 'Val/mean recall': 0.9705275893211365, 'Val/mean hd95_metric': 4.935754299163818} +Cheakpoint... +Epoch [1740/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670357704162598, 'Val/mean miou_metric': 0.9509401321411133, 'Val/mean f1': 0.9722001552581787, 'Val/mean precision': 0.9738784432411194, 'Val/mean recall': 0.9705275893211365, 'Val/mean hd95_metric': 4.935754299163818} +Epoch [1741/4000] Training [1/16] Loss: 0.00769 +Epoch [1741/4000] Training [2/16] Loss: 0.00653 +Epoch [1741/4000] Training [3/16] Loss: 0.00765 +Epoch [1741/4000] Training [4/16] Loss: 0.00703 +Epoch [1741/4000] Training [5/16] Loss: 0.00513 +Epoch [1741/4000] Training [6/16] Loss: 0.00656 +Epoch [1741/4000] Training [7/16] Loss: 0.00600 +Epoch [1741/4000] Training [8/16] Loss: 0.00663 +Epoch [1741/4000] Training [9/16] Loss: 0.00774 +Epoch [1741/4000] Training [10/16] Loss: 0.00616 +Epoch [1741/4000] Training [11/16] Loss: 0.00830 +Epoch [1741/4000] Training [12/16] Loss: 0.00696 +Epoch [1741/4000] Training [13/16] Loss: 0.00777 +Epoch [1741/4000] Training [14/16] Loss: 0.00715 +Epoch [1741/4000] Training [15/16] Loss: 0.00612 +Epoch [1741/4000] Training [16/16] Loss: 0.00766 +Epoch [1741/4000] Training metric {'Train/mean dice_metric': 0.9951496720314026, 'Train/mean miou_metric': 0.9900913238525391, 'Train/mean f1': 0.9910693764686584, 'Train/mean precision': 0.986571192741394, 'Train/mean recall': 0.9956087470054626, 'Train/mean hd95_metric': 1.0608844757080078} +Epoch [1741/4000] Validation [1/4] Loss: 0.52712 focal_loss 0.43966 dice_loss 0.08747 +Epoch [1741/4000] Validation [2/4] Loss: 0.60594 focal_loss 0.38448 dice_loss 0.22146 +Epoch [1741/4000] Validation [3/4] Loss: 0.19014 focal_loss 0.12831 dice_loss 0.06183 +Epoch [1741/4000] Validation [4/4] Loss: 0.22176 focal_loss 0.12972 dice_loss 0.09205 +Epoch [1741/4000] Validation metric {'Val/mean dice_metric': 0.9693588018417358, 'Val/mean miou_metric': 0.9530290365219116, 'Val/mean f1': 0.9729580283164978, 'Val/mean precision': 0.9721882939338684, 'Val/mean recall': 0.9737289547920227, 'Val/mean hd95_metric': 4.679242134094238} +Cheakpoint... +Epoch [1741/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693588018417358, 'Val/mean miou_metric': 0.9530290365219116, 'Val/mean f1': 0.9729580283164978, 'Val/mean precision': 0.9721882939338684, 'Val/mean recall': 0.9737289547920227, 'Val/mean hd95_metric': 4.679242134094238} +Epoch [1742/4000] Training [1/16] Loss: 0.00681 +Epoch [1742/4000] Training [2/16] Loss: 0.00682 +Epoch [1742/4000] Training [3/16] Loss: 0.00688 +Epoch [1742/4000] Training [4/16] Loss: 0.00743 +Epoch [1742/4000] Training [5/16] Loss: 0.00590 +Epoch [1742/4000] Training [6/16] Loss: 0.00698 +Epoch [1742/4000] Training [7/16] Loss: 0.00676 +Epoch [1742/4000] Training [8/16] Loss: 0.00578 +Epoch [1742/4000] Training [9/16] Loss: 0.00496 +Epoch [1742/4000] Training [10/16] Loss: 0.00619 +Epoch [1742/4000] Training [11/16] Loss: 0.00769 +Epoch [1742/4000] Training [12/16] Loss: 0.00579 +Epoch [1742/4000] Training [13/16] Loss: 0.00906 +Epoch [1742/4000] Training [14/16] Loss: 0.00588 +Epoch [1742/4000] Training [15/16] Loss: 0.00777 +Epoch [1742/4000] Training [16/16] Loss: 0.00877 +Epoch [1742/4000] Training metric {'Train/mean dice_metric': 0.9954248666763306, 'Train/mean miou_metric': 0.9905970096588135, 'Train/mean f1': 0.9904264211654663, 'Train/mean precision': 0.9852354526519775, 'Train/mean recall': 0.9956722855567932, 'Train/mean hd95_metric': 1.0352156162261963} +Epoch [1742/4000] Validation [1/4] Loss: 0.50177 focal_loss 0.40658 dice_loss 0.09519 +Epoch [1742/4000] Validation [2/4] Loss: 0.52569 focal_loss 0.33956 dice_loss 0.18613 +Epoch [1742/4000] Validation [3/4] Loss: 0.16586 focal_loss 0.10621 dice_loss 0.05965 +Epoch [1742/4000] Validation [4/4] Loss: 0.21226 focal_loss 0.13101 dice_loss 0.08125 +Epoch [1742/4000] Validation metric {'Val/mean dice_metric': 0.9710849523544312, 'Val/mean miou_metric': 0.954862117767334, 'Val/mean f1': 0.9731906056404114, 'Val/mean precision': 0.9736587405204773, 'Val/mean recall': 0.9727230668067932, 'Val/mean hd95_metric': 4.878416538238525} +Cheakpoint... +Epoch [1742/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710849523544312, 'Val/mean miou_metric': 0.954862117767334, 'Val/mean f1': 0.9731906056404114, 'Val/mean precision': 0.9736587405204773, 'Val/mean recall': 0.9727230668067932, 'Val/mean hd95_metric': 4.878416538238525} +Epoch [1743/4000] Training [1/16] Loss: 0.00604 +Epoch [1743/4000] Training [2/16] Loss: 0.00762 +Epoch [1743/4000] Training [3/16] Loss: 0.00749 +Epoch [1743/4000] Training [4/16] Loss: 0.00683 +Epoch [1743/4000] Training [5/16] Loss: 0.00788 +Epoch [1743/4000] Training [6/16] Loss: 0.00657 +Epoch [1743/4000] Training [7/16] Loss: 0.00878 +Epoch [1743/4000] Training [8/16] Loss: 0.00969 +Epoch [1743/4000] Training [9/16] Loss: 0.00554 +Epoch [1743/4000] Training [10/16] Loss: 0.00775 +Epoch [1743/4000] Training [11/16] Loss: 0.00543 +Epoch [1743/4000] Training [12/16] Loss: 0.00624 +Epoch [1743/4000] Training [13/16] Loss: 0.00604 +Epoch [1743/4000] Training [14/16] Loss: 0.00499 +Epoch [1743/4000] Training [15/16] Loss: 0.00491 +Epoch [1743/4000] Training [16/16] Loss: 0.01017 +Epoch [1743/4000] Training metric {'Train/mean dice_metric': 0.9954038858413696, 'Train/mean miou_metric': 0.990582287311554, 'Train/mean f1': 0.9912974238395691, 'Train/mean precision': 0.9865683913230896, 'Train/mean recall': 0.9960720539093018, 'Train/mean hd95_metric': 1.0166044235229492} +Epoch [1743/4000] Validation [1/4] Loss: 0.58301 focal_loss 0.47455 dice_loss 0.10846 +Epoch [1743/4000] Validation [2/4] Loss: 0.68835 focal_loss 0.47042 dice_loss 0.21793 +Epoch [1743/4000] Validation [3/4] Loss: 0.24974 focal_loss 0.16643 dice_loss 0.08331 +Epoch [1743/4000] Validation [4/4] Loss: 0.25415 focal_loss 0.16639 dice_loss 0.08776 +Epoch [1743/4000] Validation metric {'Val/mean dice_metric': 0.9687700271606445, 'Val/mean miou_metric': 0.9525201916694641, 'Val/mean f1': 0.9733084440231323, 'Val/mean precision': 0.9740959405899048, 'Val/mean recall': 0.9725221991539001, 'Val/mean hd95_metric': 5.337968826293945} +Cheakpoint... +Epoch [1743/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687700271606445, 'Val/mean miou_metric': 0.9525201916694641, 'Val/mean f1': 0.9733084440231323, 'Val/mean precision': 0.9740959405899048, 'Val/mean recall': 0.9725221991539001, 'Val/mean hd95_metric': 5.337968826293945} +Epoch [1744/4000] Training [1/16] Loss: 0.00625 +Epoch [1744/4000] Training [2/16] Loss: 0.00677 +Epoch [1744/4000] Training [3/16] Loss: 0.00603 +Epoch [1744/4000] Training [4/16] Loss: 0.00704 +Epoch [1744/4000] Training [5/16] Loss: 0.00644 +Epoch [1744/4000] Training [6/16] Loss: 0.00686 +Epoch [1744/4000] Training [7/16] Loss: 0.00856 +Epoch [1744/4000] Training [8/16] Loss: 0.00839 +Epoch [1744/4000] Training [9/16] Loss: 0.00759 +Epoch [1744/4000] Training [10/16] Loss: 0.00635 +Epoch [1744/4000] Training [11/16] Loss: 0.00747 +Epoch [1744/4000] Training [12/16] Loss: 0.00742 +Epoch [1744/4000] Training [13/16] Loss: 0.00663 +Epoch [1744/4000] Training [14/16] Loss: 0.01207 +Epoch [1744/4000] Training [15/16] Loss: 0.00591 +Epoch [1744/4000] Training [16/16] Loss: 0.01018 +Epoch [1744/4000] Training metric {'Train/mean dice_metric': 0.9950636625289917, 'Train/mean miou_metric': 0.9899205565452576, 'Train/mean f1': 0.9911445379257202, 'Train/mean precision': 0.9867202043533325, 'Train/mean recall': 0.9956086874008179, 'Train/mean hd95_metric': 1.0269920825958252} +Epoch [1744/4000] Validation [1/4] Loss: 0.66107 focal_loss 0.54647 dice_loss 0.11460 +Epoch [1744/4000] Validation [2/4] Loss: 0.50863 focal_loss 0.30217 dice_loss 0.20646 +Epoch [1744/4000] Validation [3/4] Loss: 0.36147 focal_loss 0.26174 dice_loss 0.09972 +Epoch [1744/4000] Validation [4/4] Loss: 0.25585 focal_loss 0.15449 dice_loss 0.10136 +Epoch [1744/4000] Validation metric {'Val/mean dice_metric': 0.9697917699813843, 'Val/mean miou_metric': 0.9522913098335266, 'Val/mean f1': 0.9721177816390991, 'Val/mean precision': 0.9716070294380188, 'Val/mean recall': 0.9726291298866272, 'Val/mean hd95_metric': 5.360701560974121} +Cheakpoint... +Epoch [1744/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697917699813843, 'Val/mean miou_metric': 0.9522913098335266, 'Val/mean f1': 0.9721177816390991, 'Val/mean precision': 0.9716070294380188, 'Val/mean recall': 0.9726291298866272, 'Val/mean hd95_metric': 5.360701560974121} +Epoch [1745/4000] Training [1/16] Loss: 0.00601 +Epoch [1745/4000] Training [2/16] Loss: 0.00728 +Epoch [1745/4000] Training [3/16] Loss: 0.00574 +Epoch [1745/4000] Training [4/16] Loss: 0.00627 +Epoch [1745/4000] Training [5/16] Loss: 0.00570 +Epoch [1745/4000] Training [6/16] Loss: 0.00627 +Epoch [1745/4000] Training [7/16] Loss: 0.00804 +Epoch [1745/4000] Training [8/16] Loss: 0.00695 +Epoch [1745/4000] Training [9/16] Loss: 0.00976 +Epoch [1745/4000] Training [10/16] Loss: 0.00535 +Epoch [1745/4000] Training [11/16] Loss: 0.00592 +Epoch [1745/4000] Training [12/16] Loss: 0.00734 +Epoch [1745/4000] Training [13/16] Loss: 0.00814 +Epoch [1745/4000] Training [14/16] Loss: 0.00569 +Epoch [1745/4000] Training [15/16] Loss: 0.00615 +Epoch [1745/4000] Training [16/16] Loss: 0.00673 +Epoch [1745/4000] Training metric {'Train/mean dice_metric': 0.99549800157547, 'Train/mean miou_metric': 0.9907728433609009, 'Train/mean f1': 0.9913404583930969, 'Train/mean precision': 0.9866442680358887, 'Train/mean recall': 0.9960815906524658, 'Train/mean hd95_metric': 1.0133427381515503} +Epoch [1745/4000] Validation [1/4] Loss: 0.22220 focal_loss 0.16268 dice_loss 0.05951 +Epoch [1745/4000] Validation [2/4] Loss: 0.58242 focal_loss 0.38928 dice_loss 0.19314 +Epoch [1745/4000] Validation [3/4] Loss: 0.20001 focal_loss 0.12797 dice_loss 0.07205 +Epoch [1745/4000] Validation [4/4] Loss: 0.38759 focal_loss 0.25214 dice_loss 0.13545 +Epoch [1745/4000] Validation metric {'Val/mean dice_metric': 0.9703570604324341, 'Val/mean miou_metric': 0.9536954164505005, 'Val/mean f1': 0.9731236696243286, 'Val/mean precision': 0.9712644219398499, 'Val/mean recall': 0.9749899506568909, 'Val/mean hd95_metric': 5.283890247344971} +Cheakpoint... +Epoch [1745/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703570604324341, 'Val/mean miou_metric': 0.9536954164505005, 'Val/mean f1': 0.9731236696243286, 'Val/mean precision': 0.9712644219398499, 'Val/mean recall': 0.9749899506568909, 'Val/mean hd95_metric': 5.283890247344971} +Epoch [1746/4000] Training [1/16] Loss: 0.00729 +Epoch [1746/4000] Training [2/16] Loss: 0.00488 +Epoch [1746/4000] Training [3/16] Loss: 0.00624 +Epoch [1746/4000] Training [4/16] Loss: 0.00655 +Epoch [1746/4000] Training [5/16] Loss: 0.01442 +Epoch [1746/4000] Training [6/16] Loss: 0.00592 +Epoch [1746/4000] Training [7/16] Loss: 0.00952 +Epoch [1746/4000] Training [8/16] Loss: 0.00636 +Epoch [1746/4000] Training [9/16] Loss: 0.01106 +Epoch [1746/4000] Training [10/16] Loss: 0.00498 +Epoch [1746/4000] Training [11/16] Loss: 0.00755 +Epoch [1746/4000] Training [12/16] Loss: 0.00689 +Epoch [1746/4000] Training [13/16] Loss: 0.00625 +Epoch [1746/4000] Training [14/16] Loss: 0.00747 +Epoch [1746/4000] Training [15/16] Loss: 0.00793 +Epoch [1746/4000] Training [16/16] Loss: 0.00576 +Epoch [1746/4000] Training metric {'Train/mean dice_metric': 0.9952349662780762, 'Train/mean miou_metric': 0.9902718663215637, 'Train/mean f1': 0.9913205504417419, 'Train/mean precision': 0.9869788885116577, 'Train/mean recall': 0.9957005977630615, 'Train/mean hd95_metric': 1.0198147296905518} +Epoch [1746/4000] Validation [1/4] Loss: 0.69660 focal_loss 0.57707 dice_loss 0.11954 +Epoch [1746/4000] Validation [2/4] Loss: 0.51461 focal_loss 0.32944 dice_loss 0.18517 +Epoch [1746/4000] Validation [3/4] Loss: 0.21905 focal_loss 0.14304 dice_loss 0.07601 +Epoch [1746/4000] Validation [4/4] Loss: 0.42442 focal_loss 0.30029 dice_loss 0.12413 +Epoch [1746/4000] Validation metric {'Val/mean dice_metric': 0.968603789806366, 'Val/mean miou_metric': 0.9518834352493286, 'Val/mean f1': 0.9716248512268066, 'Val/mean precision': 0.97217857837677, 'Val/mean recall': 0.971071720123291, 'Val/mean hd95_metric': 5.621769905090332} +Cheakpoint... +Epoch [1746/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9686], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968603789806366, 'Val/mean miou_metric': 0.9518834352493286, 'Val/mean f1': 0.9716248512268066, 'Val/mean precision': 0.97217857837677, 'Val/mean recall': 0.971071720123291, 'Val/mean hd95_metric': 5.621769905090332} +Epoch [1747/4000] Training [1/16] Loss: 0.00583 +Epoch [1747/4000] Training [2/16] Loss: 0.00611 +Epoch [1747/4000] Training [3/16] Loss: 0.00619 +Epoch [1747/4000] Training [4/16] Loss: 0.00830 +Epoch [1747/4000] Training [5/16] Loss: 0.00720 +Epoch [1747/4000] Training [6/16] Loss: 0.00884 +Epoch [1747/4000] Training [7/16] Loss: 0.00558 +Epoch [1747/4000] Training [8/16] Loss: 0.00572 +Epoch [1747/4000] Training [9/16] Loss: 0.00647 +Epoch [1747/4000] Training [10/16] Loss: 0.00986 +Epoch [1747/4000] Training [11/16] Loss: 0.01098 +Epoch [1747/4000] Training [12/16] Loss: 0.00779 +Epoch [1747/4000] Training [13/16] Loss: 0.00753 +Epoch [1747/4000] Training [14/16] Loss: 0.00833 +Epoch [1747/4000] Training [15/16] Loss: 0.00679 +Epoch [1747/4000] Training [16/16] Loss: 0.01020 +Epoch [1747/4000] Training metric {'Train/mean dice_metric': 0.994853138923645, 'Train/mean miou_metric': 0.9895952939987183, 'Train/mean f1': 0.991058886051178, 'Train/mean precision': 0.98653644323349, 'Train/mean recall': 0.9956229329109192, 'Train/mean hd95_metric': 1.089792251586914} +Epoch [1747/4000] Validation [1/4] Loss: 0.37654 focal_loss 0.29213 dice_loss 0.08441 +Epoch [1747/4000] Validation [2/4] Loss: 0.59618 focal_loss 0.40082 dice_loss 0.19536 +Epoch [1747/4000] Validation [3/4] Loss: 0.16643 focal_loss 0.10215 dice_loss 0.06428 +Epoch [1747/4000] Validation [4/4] Loss: 0.32320 focal_loss 0.21832 dice_loss 0.10489 +Epoch [1747/4000] Validation metric {'Val/mean dice_metric': 0.9707387089729309, 'Val/mean miou_metric': 0.953987717628479, 'Val/mean f1': 0.9742664098739624, 'Val/mean precision': 0.9738869667053223, 'Val/mean recall': 0.9746460318565369, 'Val/mean hd95_metric': 5.048778057098389} +Cheakpoint... +Epoch [1747/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707387089729309, 'Val/mean miou_metric': 0.953987717628479, 'Val/mean f1': 0.9742664098739624, 'Val/mean precision': 0.9738869667053223, 'Val/mean recall': 0.9746460318565369, 'Val/mean hd95_metric': 5.048778057098389} +Epoch [1748/4000] Training [1/16] Loss: 0.00753 +Epoch [1748/4000] Training [2/16] Loss: 0.00626 +Epoch [1748/4000] Training [3/16] Loss: 0.00809 +Epoch [1748/4000] Training [4/16] Loss: 0.00850 +Epoch [1748/4000] Training [5/16] Loss: 0.00794 +Epoch [1748/4000] Training [6/16] Loss: 0.00758 +Epoch [1748/4000] Training [7/16] Loss: 0.00703 +Epoch [1748/4000] Training [8/16] Loss: 0.00826 +Epoch [1748/4000] Training [9/16] Loss: 0.00934 +Epoch [1748/4000] Training [10/16] Loss: 0.00783 +Epoch [1748/4000] Training [11/16] Loss: 0.00602 +Epoch [1748/4000] Training [12/16] Loss: 0.00797 +Epoch [1748/4000] Training [13/16] Loss: 0.00677 +Epoch [1748/4000] Training [14/16] Loss: 0.00577 +Epoch [1748/4000] Training [15/16] Loss: 0.00865 +Epoch [1748/4000] Training [16/16] Loss: 0.00716 +Epoch [1748/4000] Training metric {'Train/mean dice_metric': 0.9945695996284485, 'Train/mean miou_metric': 0.9889825582504272, 'Train/mean f1': 0.990705668926239, 'Train/mean precision': 0.9862249493598938, 'Train/mean recall': 0.9952272176742554, 'Train/mean hd95_metric': 1.0835953950881958} +Epoch [1748/4000] Validation [1/4] Loss: 0.58610 focal_loss 0.47791 dice_loss 0.10819 +Epoch [1748/4000] Validation [2/4] Loss: 0.91140 focal_loss 0.61237 dice_loss 0.29903 +Epoch [1748/4000] Validation [3/4] Loss: 0.18736 focal_loss 0.12515 dice_loss 0.06221 +Epoch [1748/4000] Validation [4/4] Loss: 0.27766 focal_loss 0.17380 dice_loss 0.10386 +Epoch [1748/4000] Validation metric {'Val/mean dice_metric': 0.9676187634468079, 'Val/mean miou_metric': 0.9503704309463501, 'Val/mean f1': 0.9722945690155029, 'Val/mean precision': 0.9739664793014526, 'Val/mean recall': 0.9706283807754517, 'Val/mean hd95_metric': 5.19959020614624} +Cheakpoint... +Epoch [1748/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676187634468079, 'Val/mean miou_metric': 0.9503704309463501, 'Val/mean f1': 0.9722945690155029, 'Val/mean precision': 0.9739664793014526, 'Val/mean recall': 0.9706283807754517, 'Val/mean hd95_metric': 5.19959020614624} +Epoch [1749/4000] Training [1/16] Loss: 0.00796 +Epoch [1749/4000] Training [2/16] Loss: 0.00619 +Epoch [1749/4000] Training [3/16] Loss: 0.00576 +Epoch [1749/4000] Training [4/16] Loss: 0.00867 +Epoch [1749/4000] Training [5/16] Loss: 0.00641 +Epoch [1749/4000] Training [6/16] Loss: 0.00968 +Epoch [1749/4000] Training [7/16] Loss: 0.00596 +Epoch [1749/4000] Training [8/16] Loss: 0.00523 +Epoch [1749/4000] Training [9/16] Loss: 0.00607 +Epoch [1749/4000] Training [10/16] Loss: 0.00570 +Epoch [1749/4000] Training [11/16] Loss: 0.00624 +Epoch [1749/4000] Training [12/16] Loss: 0.00944 +Epoch [1749/4000] Training [13/16] Loss: 0.00526 +Epoch [1749/4000] Training [14/16] Loss: 0.00627 +Epoch [1749/4000] Training [15/16] Loss: 0.00940 +Epoch [1749/4000] Training [16/16] Loss: 0.00852 +Epoch [1749/4000] Training metric {'Train/mean dice_metric': 0.9952726364135742, 'Train/mean miou_metric': 0.9903191328048706, 'Train/mean f1': 0.9909662008285522, 'Train/mean precision': 0.9861645698547363, 'Train/mean recall': 0.995814859867096, 'Train/mean hd95_metric': 1.0198243856430054} +Epoch [1749/4000] Validation [1/4] Loss: 0.41836 focal_loss 0.33073 dice_loss 0.08763 +Epoch [1749/4000] Validation [2/4] Loss: 0.62394 focal_loss 0.37234 dice_loss 0.25160 +Epoch [1749/4000] Validation [3/4] Loss: 0.19893 focal_loss 0.12694 dice_loss 0.07199 +Epoch [1749/4000] Validation [4/4] Loss: 0.34737 focal_loss 0.21828 dice_loss 0.12909 +Epoch [1749/4000] Validation metric {'Val/mean dice_metric': 0.969275176525116, 'Val/mean miou_metric': 0.9520162343978882, 'Val/mean f1': 0.9718344807624817, 'Val/mean precision': 0.9707083702087402, 'Val/mean recall': 0.9729632139205933, 'Val/mean hd95_metric': 5.438531398773193} +Cheakpoint... +Epoch [1749/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969275176525116, 'Val/mean miou_metric': 0.9520162343978882, 'Val/mean f1': 0.9718344807624817, 'Val/mean precision': 0.9707083702087402, 'Val/mean recall': 0.9729632139205933, 'Val/mean hd95_metric': 5.438531398773193} +Epoch [1750/4000] Training [1/16] Loss: 0.00915 +Epoch [1750/4000] Training [2/16] Loss: 0.00665 +Epoch [1750/4000] Training [3/16] Loss: 0.00657 +Epoch [1750/4000] Training [4/16] Loss: 0.00732 +Epoch [1750/4000] Training [5/16] Loss: 0.01347 +Epoch [1750/4000] Training [6/16] Loss: 0.00935 +Epoch [1750/4000] Training [7/16] Loss: 0.00756 +Epoch [1750/4000] Training [8/16] Loss: 0.01265 +Epoch [1750/4000] Training [9/16] Loss: 0.00594 +Epoch [1750/4000] Training [10/16] Loss: 0.00521 +Epoch [1750/4000] Training [11/16] Loss: 0.00872 +Epoch [1750/4000] Training [12/16] Loss: 0.00733 +Epoch [1750/4000] Training [13/16] Loss: 0.01018 +Epoch [1750/4000] Training [14/16] Loss: 0.00603 +Epoch [1750/4000] Training [15/16] Loss: 0.00843 +Epoch [1750/4000] Training [16/16] Loss: 0.00808 +Epoch [1750/4000] Training metric {'Train/mean dice_metric': 0.9946491718292236, 'Train/mean miou_metric': 0.989094078540802, 'Train/mean f1': 0.9899932146072388, 'Train/mean precision': 0.9846064448356628, 'Train/mean recall': 0.9954392313957214, 'Train/mean hd95_metric': 1.0400006771087646} +Epoch [1750/4000] Validation [1/4] Loss: 0.51958 focal_loss 0.42002 dice_loss 0.09955 +Epoch [1750/4000] Validation [2/4] Loss: 0.29967 focal_loss 0.18173 dice_loss 0.11794 +Epoch [1750/4000] Validation [3/4] Loss: 0.23985 focal_loss 0.15688 dice_loss 0.08297 +Epoch [1750/4000] Validation [4/4] Loss: 0.38214 focal_loss 0.24658 dice_loss 0.13556 +Epoch [1750/4000] Validation metric {'Val/mean dice_metric': 0.9704116582870483, 'Val/mean miou_metric': 0.9526703953742981, 'Val/mean f1': 0.9709715247154236, 'Val/mean precision': 0.9689066410064697, 'Val/mean recall': 0.9730451703071594, 'Val/mean hd95_metric': 5.80510950088501} +Cheakpoint... +Epoch [1750/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704116582870483, 'Val/mean miou_metric': 0.9526703953742981, 'Val/mean f1': 0.9709715247154236, 'Val/mean precision': 0.9689066410064697, 'Val/mean recall': 0.9730451703071594, 'Val/mean hd95_metric': 5.80510950088501} +Epoch [1751/4000] Training [1/16] Loss: 0.00844 +Epoch [1751/4000] Training [2/16] Loss: 0.00655 +Epoch [1751/4000] Training [3/16] Loss: 0.00688 +Epoch [1751/4000] Training [4/16] Loss: 0.00578 +Epoch [1751/4000] Training [5/16] Loss: 0.00884 +Epoch [1751/4000] Training [6/16] Loss: 0.00652 +Epoch [1751/4000] Training [7/16] Loss: 0.00512 +Epoch [1751/4000] Training [8/16] Loss: 0.00603 +Epoch [1751/4000] Training [9/16] Loss: 0.00818 +Epoch [1751/4000] Training [10/16] Loss: 0.00631 +Epoch [1751/4000] Training [11/16] Loss: 0.00691 +Epoch [1751/4000] Training [12/16] Loss: 0.00622 +Epoch [1751/4000] Training [13/16] Loss: 0.01031 +Epoch [1751/4000] Training [14/16] Loss: 0.00567 +Epoch [1751/4000] Training [15/16] Loss: 0.00574 +Epoch [1751/4000] Training [16/16] Loss: 0.00574 +Epoch [1751/4000] Training metric {'Train/mean dice_metric': 0.995282769203186, 'Train/mean miou_metric': 0.9903495907783508, 'Train/mean f1': 0.9912529587745667, 'Train/mean precision': 0.9867780208587646, 'Train/mean recall': 0.995768666267395, 'Train/mean hd95_metric': 1.1938509941101074} +Epoch [1751/4000] Validation [1/4] Loss: 0.42485 focal_loss 0.33859 dice_loss 0.08626 +Epoch [1751/4000] Validation [2/4] Loss: 0.36086 focal_loss 0.21997 dice_loss 0.14089 +Epoch [1751/4000] Validation [3/4] Loss: 0.24120 focal_loss 0.15358 dice_loss 0.08762 +Epoch [1751/4000] Validation [4/4] Loss: 0.23861 focal_loss 0.15270 dice_loss 0.08591 +Epoch [1751/4000] Validation metric {'Val/mean dice_metric': 0.9713042378425598, 'Val/mean miou_metric': 0.9542913436889648, 'Val/mean f1': 0.9740138649940491, 'Val/mean precision': 0.9721420407295227, 'Val/mean recall': 0.975892961025238, 'Val/mean hd95_metric': 5.834012031555176} +Cheakpoint... +Epoch [1751/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713042378425598, 'Val/mean miou_metric': 0.9542913436889648, 'Val/mean f1': 0.9740138649940491, 'Val/mean precision': 0.9721420407295227, 'Val/mean recall': 0.975892961025238, 'Val/mean hd95_metric': 5.834012031555176} +Epoch [1752/4000] Training [1/16] Loss: 0.00574 +Epoch [1752/4000] Training [2/16] Loss: 0.00482 +Epoch [1752/4000] Training [3/16] Loss: 0.00576 +Epoch [1752/4000] Training [4/16] Loss: 0.00685 +Epoch [1752/4000] Training [5/16] Loss: 0.00918 +Epoch [1752/4000] Training [6/16] Loss: 0.00590 +Epoch [1752/4000] Training [7/16] Loss: 0.00657 +Epoch [1752/4000] Training [8/16] Loss: 0.00588 +Epoch [1752/4000] Training [9/16] Loss: 0.00518 +Epoch [1752/4000] Training [10/16] Loss: 0.00632 +Epoch [1752/4000] Training [11/16] Loss: 0.00681 +Epoch [1752/4000] Training [12/16] Loss: 0.00559 +Epoch [1752/4000] Training [13/16] Loss: 0.00570 +Epoch [1752/4000] Training [14/16] Loss: 0.00717 +Epoch [1752/4000] Training [15/16] Loss: 0.00531 +Epoch [1752/4000] Training [16/16] Loss: 0.00649 +Epoch [1752/4000] Training metric {'Train/mean dice_metric': 0.9957602024078369, 'Train/mean miou_metric': 0.9912965297698975, 'Train/mean f1': 0.9915466904640198, 'Train/mean precision': 0.9869911670684814, 'Train/mean recall': 0.9961444735527039, 'Train/mean hd95_metric': 1.0077872276306152} +Epoch [1752/4000] Validation [1/4] Loss: 0.46440 focal_loss 0.36951 dice_loss 0.09489 +Epoch [1752/4000] Validation [2/4] Loss: 0.28134 focal_loss 0.16858 dice_loss 0.11276 +Epoch [1752/4000] Validation [3/4] Loss: 0.29029 focal_loss 0.20081 dice_loss 0.08948 +Epoch [1752/4000] Validation [4/4] Loss: 0.30450 focal_loss 0.19608 dice_loss 0.10841 +Epoch [1752/4000] Validation metric {'Val/mean dice_metric': 0.9708276987075806, 'Val/mean miou_metric': 0.9543695449829102, 'Val/mean f1': 0.9734317660331726, 'Val/mean precision': 0.9722201228141785, 'Val/mean recall': 0.9746463894844055, 'Val/mean hd95_metric': 5.49348258972168} +Cheakpoint... +Epoch [1752/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708276987075806, 'Val/mean miou_metric': 0.9543695449829102, 'Val/mean f1': 0.9734317660331726, 'Val/mean precision': 0.9722201228141785, 'Val/mean recall': 0.9746463894844055, 'Val/mean hd95_metric': 5.49348258972168} +Epoch [1753/4000] Training [1/16] Loss: 0.00737 +Epoch [1753/4000] Training [2/16] Loss: 0.00509 +Epoch [1753/4000] Training [3/16] Loss: 0.00774 +Epoch [1753/4000] Training [4/16] Loss: 0.00724 +Epoch [1753/4000] Training [5/16] Loss: 0.00685 +Epoch [1753/4000] Training [6/16] Loss: 0.00652 +Epoch [1753/4000] Training [7/16] Loss: 0.00538 +Epoch [1753/4000] Training [8/16] Loss: 0.00576 +Epoch [1753/4000] Training [9/16] Loss: 0.00623 +Epoch [1753/4000] Training [10/16] Loss: 0.00568 +Epoch [1753/4000] Training [11/16] Loss: 0.00529 +Epoch [1753/4000] Training [12/16] Loss: 0.00864 +Epoch [1753/4000] Training [13/16] Loss: 0.00476 +Epoch [1753/4000] Training [14/16] Loss: 0.00890 +Epoch [1753/4000] Training [15/16] Loss: 0.00638 +Epoch [1753/4000] Training [16/16] Loss: 0.00640 +Epoch [1753/4000] Training metric {'Train/mean dice_metric': 0.9956231713294983, 'Train/mean miou_metric': 0.9910507202148438, 'Train/mean f1': 0.9916014075279236, 'Train/mean precision': 0.9870409965515137, 'Train/mean recall': 0.9962041974067688, 'Train/mean hd95_metric': 1.037621021270752} +Epoch [1753/4000] Validation [1/4] Loss: 0.50128 focal_loss 0.40141 dice_loss 0.09987 +Epoch [1753/4000] Validation [2/4] Loss: 0.33191 focal_loss 0.19868 dice_loss 0.13323 +Epoch [1753/4000] Validation [3/4] Loss: 0.28843 focal_loss 0.19686 dice_loss 0.09157 +Epoch [1753/4000] Validation [4/4] Loss: 0.38963 focal_loss 0.24632 dice_loss 0.14331 +Epoch [1753/4000] Validation metric {'Val/mean dice_metric': 0.9710458517074585, 'Val/mean miou_metric': 0.9534031748771667, 'Val/mean f1': 0.9729291796684265, 'Val/mean precision': 0.9726545810699463, 'Val/mean recall': 0.9732038974761963, 'Val/mean hd95_metric': 5.768056392669678} +Cheakpoint... +Epoch [1753/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710458517074585, 'Val/mean miou_metric': 0.9534031748771667, 'Val/mean f1': 0.9729291796684265, 'Val/mean precision': 0.9726545810699463, 'Val/mean recall': 0.9732038974761963, 'Val/mean hd95_metric': 5.768056392669678} +Epoch [1754/4000] Training [1/16] Loss: 0.00583 +Epoch [1754/4000] Training [2/16] Loss: 0.00588 +Epoch [1754/4000] Training [3/16] Loss: 0.00868 +Epoch [1754/4000] Training [4/16] Loss: 0.01052 +Epoch [1754/4000] Training [5/16] Loss: 0.00604 +Epoch [1754/4000] Training [6/16] Loss: 0.00903 +Epoch [1754/4000] Training [7/16] Loss: 0.00630 +Epoch [1754/4000] Training [8/16] Loss: 0.00938 +Epoch [1754/4000] Training [9/16] Loss: 0.00492 +Epoch [1754/4000] Training [10/16] Loss: 0.00671 +Epoch [1754/4000] Training [11/16] Loss: 0.00660 +Epoch [1754/4000] Training [12/16] Loss: 0.00510 +Epoch [1754/4000] Training [13/16] Loss: 0.00588 +Epoch [1754/4000] Training [14/16] Loss: 0.00643 +Epoch [1754/4000] Training [15/16] Loss: 0.00795 +Epoch [1754/4000] Training [16/16] Loss: 0.00556 +Epoch [1754/4000] Training metric {'Train/mean dice_metric': 0.9953798055648804, 'Train/mean miou_metric': 0.9905523061752319, 'Train/mean f1': 0.9913726449012756, 'Train/mean precision': 0.986876904964447, 'Train/mean recall': 0.9959095120429993, 'Train/mean hd95_metric': 1.0353426933288574} +Epoch [1754/4000] Validation [1/4] Loss: 0.27165 focal_loss 0.20506 dice_loss 0.06659 +Epoch [1754/4000] Validation [2/4] Loss: 0.34288 focal_loss 0.20426 dice_loss 0.13862 +Epoch [1754/4000] Validation [3/4] Loss: 0.22909 focal_loss 0.15018 dice_loss 0.07891 +Epoch [1754/4000] Validation [4/4] Loss: 0.26145 focal_loss 0.16294 dice_loss 0.09850 +Epoch [1754/4000] Validation metric {'Val/mean dice_metric': 0.9724218249320984, 'Val/mean miou_metric': 0.9558857083320618, 'Val/mean f1': 0.9748514890670776, 'Val/mean precision': 0.971271276473999, 'Val/mean recall': 0.9784579873085022, 'Val/mean hd95_metric': 5.076936721801758} +Cheakpoint... +Epoch [1754/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724218249320984, 'Val/mean miou_metric': 0.9558857083320618, 'Val/mean f1': 0.9748514890670776, 'Val/mean precision': 0.971271276473999, 'Val/mean recall': 0.9784579873085022, 'Val/mean hd95_metric': 5.076936721801758} +Epoch [1755/4000] Training [1/16] Loss: 0.00710 +Epoch [1755/4000] Training [2/16] Loss: 0.00902 +Epoch [1755/4000] Training [3/16] Loss: 0.00605 +Epoch [1755/4000] Training [4/16] Loss: 0.00562 +Epoch [1755/4000] Training [5/16] Loss: 0.00699 +Epoch [1755/4000] Training [6/16] Loss: 0.00810 +Epoch [1755/4000] Training [7/16] Loss: 0.00591 +Epoch [1755/4000] Training [8/16] Loss: 0.00753 +Epoch [1755/4000] Training [9/16] Loss: 0.01015 +Epoch [1755/4000] Training [10/16] Loss: 0.00556 +Epoch [1755/4000] Training [11/16] Loss: 0.00904 +Epoch [1755/4000] Training [12/16] Loss: 0.00572 +Epoch [1755/4000] Training [13/16] Loss: 0.00636 +Epoch [1755/4000] Training [14/16] Loss: 0.00744 +Epoch [1755/4000] Training [15/16] Loss: 0.00661 +Epoch [1755/4000] Training [16/16] Loss: 0.00716 +Epoch [1755/4000] Training metric {'Train/mean dice_metric': 0.9951898455619812, 'Train/mean miou_metric': 0.9901775121688843, 'Train/mean f1': 0.99125736951828, 'Train/mean precision': 0.9866945743560791, 'Train/mean recall': 0.9958627820014954, 'Train/mean hd95_metric': 1.011596441268921} +Epoch [1755/4000] Validation [1/4] Loss: 0.26513 focal_loss 0.19994 dice_loss 0.06518 +Epoch [1755/4000] Validation [2/4] Loss: 0.60060 focal_loss 0.37263 dice_loss 0.22797 +Epoch [1755/4000] Validation [3/4] Loss: 0.27755 focal_loss 0.18078 dice_loss 0.09677 +Epoch [1755/4000] Validation [4/4] Loss: 0.33618 focal_loss 0.21312 dice_loss 0.12306 +Epoch [1755/4000] Validation metric {'Val/mean dice_metric': 0.9691766500473022, 'Val/mean miou_metric': 0.9526267051696777, 'Val/mean f1': 0.9739072918891907, 'Val/mean precision': 0.9690439105033875, 'Val/mean recall': 0.9788197875022888, 'Val/mean hd95_metric': 5.149775981903076} +Cheakpoint... +Epoch [1755/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691766500473022, 'Val/mean miou_metric': 0.9526267051696777, 'Val/mean f1': 0.9739072918891907, 'Val/mean precision': 0.9690439105033875, 'Val/mean recall': 0.9788197875022888, 'Val/mean hd95_metric': 5.149775981903076} +Epoch [1756/4000] Training [1/16] Loss: 0.00542 +Epoch [1756/4000] Training [2/16] Loss: 0.00609 +Epoch [1756/4000] Training [3/16] Loss: 0.00883 +Epoch [1756/4000] Training [4/16] Loss: 0.00647 +Epoch [1756/4000] Training [5/16] Loss: 0.00586 +Epoch [1756/4000] Training [6/16] Loss: 0.00539 +Epoch [1756/4000] Training [7/16] Loss: 0.00571 +Epoch [1756/4000] Training [8/16] Loss: 0.00690 +Epoch [1756/4000] Training [9/16] Loss: 0.00658 +Epoch [1756/4000] Training [10/16] Loss: 0.00799 +Epoch [1756/4000] Training [11/16] Loss: 0.00673 +Epoch [1756/4000] Training [12/16] Loss: 0.00725 +Epoch [1756/4000] Training [13/16] Loss: 0.00560 +Epoch [1756/4000] Training [14/16] Loss: 0.00707 +Epoch [1756/4000] Training [15/16] Loss: 0.00791 +Epoch [1756/4000] Training [16/16] Loss: 0.00553 +Epoch [1756/4000] Training metric {'Train/mean dice_metric': 0.995358407497406, 'Train/mean miou_metric': 0.9904927015304565, 'Train/mean f1': 0.9911478161811829, 'Train/mean precision': 0.9864668250083923, 'Train/mean recall': 0.9958735108375549, 'Train/mean hd95_metric': 1.0216658115386963} +Epoch [1756/4000] Validation [1/4] Loss: 0.30503 focal_loss 0.23198 dice_loss 0.07306 +Epoch [1756/4000] Validation [2/4] Loss: 0.29253 focal_loss 0.17611 dice_loss 0.11642 +Epoch [1756/4000] Validation [3/4] Loss: 0.34746 focal_loss 0.25542 dice_loss 0.09204 +Epoch [1756/4000] Validation [4/4] Loss: 0.37816 focal_loss 0.26478 dice_loss 0.11338 +Epoch [1756/4000] Validation metric {'Val/mean dice_metric': 0.9726004600524902, 'Val/mean miou_metric': 0.9552175402641296, 'Val/mean f1': 0.9746435284614563, 'Val/mean precision': 0.9718506336212158, 'Val/mean recall': 0.9774523973464966, 'Val/mean hd95_metric': 5.436115264892578} +Cheakpoint... +Epoch [1756/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726004600524902, 'Val/mean miou_metric': 0.9552175402641296, 'Val/mean f1': 0.9746435284614563, 'Val/mean precision': 0.9718506336212158, 'Val/mean recall': 0.9774523973464966, 'Val/mean hd95_metric': 5.436115264892578} +Epoch [1757/4000] Training [1/16] Loss: 0.00548 +Epoch [1757/4000] Training [2/16] Loss: 0.00570 +Epoch [1757/4000] Training [3/16] Loss: 0.00717 +Epoch [1757/4000] Training [4/16] Loss: 0.00793 +Epoch [1757/4000] Training [5/16] Loss: 0.00899 +Epoch [1757/4000] Training [6/16] Loss: 0.00875 +Epoch [1757/4000] Training [7/16] Loss: 0.00880 +Epoch [1757/4000] Training [8/16] Loss: 0.00609 +Epoch [1757/4000] Training [9/16] Loss: 0.00818 +Epoch [1757/4000] Training [10/16] Loss: 0.00488 +Epoch [1757/4000] Training [11/16] Loss: 0.00710 +Epoch [1757/4000] Training [12/16] Loss: 0.00591 +Epoch [1757/4000] Training [13/16] Loss: 0.00605 +Epoch [1757/4000] Training [14/16] Loss: 0.00677 +Epoch [1757/4000] Training [15/16] Loss: 0.00861 +Epoch [1757/4000] Training [16/16] Loss: 0.00569 +Epoch [1757/4000] Training metric {'Train/mean dice_metric': 0.9952670931816101, 'Train/mean miou_metric': 0.9902898073196411, 'Train/mean f1': 0.990450382232666, 'Train/mean precision': 0.9851617813110352, 'Train/mean recall': 0.9957960247993469, 'Train/mean hd95_metric': 1.026953935623169} +Epoch [1757/4000] Validation [1/4] Loss: 0.26110 focal_loss 0.19360 dice_loss 0.06749 +Epoch [1757/4000] Validation [2/4] Loss: 0.29116 focal_loss 0.16872 dice_loss 0.12245 +Epoch [1757/4000] Validation [3/4] Loss: 0.31787 focal_loss 0.22593 dice_loss 0.09195 +Epoch [1757/4000] Validation [4/4] Loss: 0.31855 focal_loss 0.19898 dice_loss 0.11957 +Epoch [1757/4000] Validation metric {'Val/mean dice_metric': 0.972169041633606, 'Val/mean miou_metric': 0.9548476934432983, 'Val/mean f1': 0.9738844037055969, 'Val/mean precision': 0.9693911671638489, 'Val/mean recall': 0.978419303894043, 'Val/mean hd95_metric': 5.504003047943115} +Cheakpoint... +Epoch [1757/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972169041633606, 'Val/mean miou_metric': 0.9548476934432983, 'Val/mean f1': 0.9738844037055969, 'Val/mean precision': 0.9693911671638489, 'Val/mean recall': 0.978419303894043, 'Val/mean hd95_metric': 5.504003047943115} +Epoch [1758/4000] Training [1/16] Loss: 0.00625 +Epoch [1758/4000] Training [2/16] Loss: 0.01075 +Epoch [1758/4000] Training [3/16] Loss: 0.00602 +Epoch [1758/4000] Training [4/16] Loss: 0.00711 +Epoch [1758/4000] Training [5/16] Loss: 0.00762 +Epoch [1758/4000] Training [6/16] Loss: 0.00617 +Epoch [1758/4000] Training [7/16] Loss: 0.00726 +Epoch [1758/4000] Training [8/16] Loss: 0.00565 +Epoch [1758/4000] Training [9/16] Loss: 0.00715 +Epoch [1758/4000] Training [10/16] Loss: 0.00718 +Epoch [1758/4000] Training [11/16] Loss: 0.00745 +Epoch [1758/4000] Training [12/16] Loss: 0.00618 +Epoch [1758/4000] Training [13/16] Loss: 0.00563 +Epoch [1758/4000] Training [14/16] Loss: 0.00918 +Epoch [1758/4000] Training [15/16] Loss: 0.00793 +Epoch [1758/4000] Training [16/16] Loss: 0.00793 +Epoch [1758/4000] Training metric {'Train/mean dice_metric': 0.9950595498085022, 'Train/mean miou_metric': 0.9899106025695801, 'Train/mean f1': 0.9907858371734619, 'Train/mean precision': 0.9860576391220093, 'Train/mean recall': 0.9955596327781677, 'Train/mean hd95_metric': 1.033010721206665} +Epoch [1758/4000] Validation [1/4] Loss: 0.28524 focal_loss 0.21165 dice_loss 0.07359 +Epoch [1758/4000] Validation [2/4] Loss: 0.34518 focal_loss 0.20974 dice_loss 0.13544 +Epoch [1758/4000] Validation [3/4] Loss: 0.29448 focal_loss 0.19654 dice_loss 0.09794 +Epoch [1758/4000] Validation [4/4] Loss: 0.23474 focal_loss 0.15434 dice_loss 0.08040 +Epoch [1758/4000] Validation metric {'Val/mean dice_metric': 0.9723001718521118, 'Val/mean miou_metric': 0.9550977945327759, 'Val/mean f1': 0.9741252660751343, 'Val/mean precision': 0.97283935546875, 'Val/mean recall': 0.9754146337509155, 'Val/mean hd95_metric': 5.5292649269104} +Cheakpoint... +Epoch [1758/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723001718521118, 'Val/mean miou_metric': 0.9550977945327759, 'Val/mean f1': 0.9741252660751343, 'Val/mean precision': 0.97283935546875, 'Val/mean recall': 0.9754146337509155, 'Val/mean hd95_metric': 5.5292649269104} +Epoch [1759/4000] Training [1/16] Loss: 0.01076 +Epoch [1759/4000] Training [2/16] Loss: 0.00517 +Epoch [1759/4000] Training [3/16] Loss: 0.00794 +Epoch [1759/4000] Training [4/16] Loss: 0.00574 +Epoch [1759/4000] Training [5/16] Loss: 0.00546 +Epoch [1759/4000] Training [6/16] Loss: 0.00828 +Epoch [1759/4000] Training [7/16] Loss: 0.00511 +Epoch [1759/4000] Training [8/16] Loss: 0.00567 +Epoch [1759/4000] Training [9/16] Loss: 0.00850 +Epoch [1759/4000] Training [10/16] Loss: 0.00606 +Epoch [1759/4000] Training [11/16] Loss: 0.01045 +Epoch [1759/4000] Training [12/16] Loss: 0.00721 +Epoch [1759/4000] Training [13/16] Loss: 0.00943 +Epoch [1759/4000] Training [14/16] Loss: 0.00734 +Epoch [1759/4000] Training [15/16] Loss: 0.00540 +Epoch [1759/4000] Training [16/16] Loss: 0.00694 +Epoch [1759/4000] Training metric {'Train/mean dice_metric': 0.995215892791748, 'Train/mean miou_metric': 0.9902316331863403, 'Train/mean f1': 0.9911575317382812, 'Train/mean precision': 0.9866188764572144, 'Train/mean recall': 0.9957380890846252, 'Train/mean hd95_metric': 1.1367870569229126} +Epoch [1759/4000] Validation [1/4] Loss: 0.54251 focal_loss 0.44283 dice_loss 0.09967 +Epoch [1759/4000] Validation [2/4] Loss: 0.25179 focal_loss 0.14391 dice_loss 0.10788 +Epoch [1759/4000] Validation [3/4] Loss: 0.27737 focal_loss 0.18500 dice_loss 0.09236 +Epoch [1759/4000] Validation [4/4] Loss: 0.39195 focal_loss 0.24998 dice_loss 0.14197 +Epoch [1759/4000] Validation metric {'Val/mean dice_metric': 0.9721726179122925, 'Val/mean miou_metric': 0.9545878171920776, 'Val/mean f1': 0.9732616543769836, 'Val/mean precision': 0.9729167222976685, 'Val/mean recall': 0.9736068844795227, 'Val/mean hd95_metric': 5.3813982009887695} +Cheakpoint... +Epoch [1759/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721726179122925, 'Val/mean miou_metric': 0.9545878171920776, 'Val/mean f1': 0.9732616543769836, 'Val/mean precision': 0.9729167222976685, 'Val/mean recall': 0.9736068844795227, 'Val/mean hd95_metric': 5.3813982009887695} +Epoch [1760/4000] Training [1/16] Loss: 0.00554 +Epoch [1760/4000] Training [2/16] Loss: 0.00886 +Epoch [1760/4000] Training [3/16] Loss: 0.00712 +Epoch [1760/4000] Training [4/16] Loss: 0.00718 +Epoch [1760/4000] Training [5/16] Loss: 0.00813 +Epoch [1760/4000] Training [6/16] Loss: 0.01369 +Epoch [1760/4000] Training [7/16] Loss: 0.00672 +Epoch [1760/4000] Training [8/16] Loss: 0.00720 +Epoch [1760/4000] Training [9/16] Loss: 0.01172 +Epoch [1760/4000] Training [10/16] Loss: 0.00590 +Epoch [1760/4000] Training [11/16] Loss: 0.00780 +Epoch [1760/4000] Training [12/16] Loss: 0.00573 +Epoch [1760/4000] Training [13/16] Loss: 0.00775 +Epoch [1760/4000] Training [14/16] Loss: 0.00875 +Epoch [1760/4000] Training [15/16] Loss: 0.00545 +Epoch [1760/4000] Training [16/16] Loss: 0.00740 +Epoch [1760/4000] Training metric {'Train/mean dice_metric': 0.9947105646133423, 'Train/mean miou_metric': 0.9892597198486328, 'Train/mean f1': 0.9908711910247803, 'Train/mean precision': 0.9863228797912598, 'Train/mean recall': 0.995461642742157, 'Train/mean hd95_metric': 1.1020541191101074} +Epoch [1760/4000] Validation [1/4] Loss: 0.26642 focal_loss 0.19676 dice_loss 0.06966 +Epoch [1760/4000] Validation [2/4] Loss: 0.40980 focal_loss 0.24284 dice_loss 0.16696 +Epoch [1760/4000] Validation [3/4] Loss: 0.25419 focal_loss 0.16779 dice_loss 0.08640 +Epoch [1760/4000] Validation [4/4] Loss: 0.46095 focal_loss 0.30750 dice_loss 0.15346 +Epoch [1760/4000] Validation metric {'Val/mean dice_metric': 0.9685007333755493, 'Val/mean miou_metric': 0.9511318206787109, 'Val/mean f1': 0.9714599847793579, 'Val/mean precision': 0.9662575721740723, 'Val/mean recall': 0.9767188429832458, 'Val/mean hd95_metric': 6.466082572937012} +Cheakpoint... +Epoch [1760/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9685], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9685007333755493, 'Val/mean miou_metric': 0.9511318206787109, 'Val/mean f1': 0.9714599847793579, 'Val/mean precision': 0.9662575721740723, 'Val/mean recall': 0.9767188429832458, 'Val/mean hd95_metric': 6.466082572937012} +Epoch [1761/4000] Training [1/16] Loss: 0.00846 +Epoch [1761/4000] Training [2/16] Loss: 0.00722 +Epoch [1761/4000] Training [3/16] Loss: 0.00566 +Epoch [1761/4000] Training [4/16] Loss: 0.00737 +Epoch [1761/4000] Training [5/16] Loss: 0.00597 +Epoch [1761/4000] Training [6/16] Loss: 0.00985 +Epoch [1761/4000] Training [7/16] Loss: 0.00840 +Epoch [1761/4000] Training [8/16] Loss: 0.00491 +Epoch [1761/4000] Training [9/16] Loss: 0.00557 +Epoch [1761/4000] Training [10/16] Loss: 0.01137 +Epoch [1761/4000] Training [11/16] Loss: 0.00538 +Epoch [1761/4000] Training [12/16] Loss: 0.00805 +Epoch [1761/4000] Training [13/16] Loss: 0.00553 +Epoch [1761/4000] Training [14/16] Loss: 0.00653 +Epoch [1761/4000] Training [15/16] Loss: 0.01698 +Epoch [1761/4000] Training [16/16] Loss: 0.00580 +Epoch [1761/4000] Training metric {'Train/mean dice_metric': 0.9952056407928467, 'Train/mean miou_metric': 0.9901865720748901, 'Train/mean f1': 0.990908682346344, 'Train/mean precision': 0.9861170649528503, 'Train/mean recall': 0.9957471489906311, 'Train/mean hd95_metric': 1.2592511177062988} +Epoch [1761/4000] Validation [1/4] Loss: 0.21368 focal_loss 0.15412 dice_loss 0.05956 +Epoch [1761/4000] Validation [2/4] Loss: 0.32174 focal_loss 0.19512 dice_loss 0.12662 +Epoch [1761/4000] Validation [3/4] Loss: 0.28886 focal_loss 0.19762 dice_loss 0.09124 +Epoch [1761/4000] Validation [4/4] Loss: 0.27190 focal_loss 0.16748 dice_loss 0.10442 +Epoch [1761/4000] Validation metric {'Val/mean dice_metric': 0.972787082195282, 'Val/mean miou_metric': 0.95564204454422, 'Val/mean f1': 0.9748392701148987, 'Val/mean precision': 0.9720661640167236, 'Val/mean recall': 0.9776282906532288, 'Val/mean hd95_metric': 5.785956859588623} +Cheakpoint... +Epoch [1761/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972787082195282, 'Val/mean miou_metric': 0.95564204454422, 'Val/mean f1': 0.9748392701148987, 'Val/mean precision': 0.9720661640167236, 'Val/mean recall': 0.9776282906532288, 'Val/mean hd95_metric': 5.785956859588623} +Epoch [1762/4000] Training [1/16] Loss: 0.00574 +Epoch [1762/4000] Training [2/16] Loss: 0.00621 +Epoch [1762/4000] Training [3/16] Loss: 0.00633 +Epoch [1762/4000] Training [4/16] Loss: 0.00714 +Epoch [1762/4000] Training [5/16] Loss: 0.00744 +Epoch [1762/4000] Training [6/16] Loss: 0.00821 +Epoch [1762/4000] Training [7/16] Loss: 0.00734 +Epoch [1762/4000] Training [8/16] Loss: 0.00771 +Epoch [1762/4000] Training [9/16] Loss: 0.01034 +Epoch [1762/4000] Training [10/16] Loss: 0.00769 +Epoch [1762/4000] Training [11/16] Loss: 0.00800 +Epoch [1762/4000] Training [12/16] Loss: 0.00532 +Epoch [1762/4000] Training [13/16] Loss: 0.00671 +Epoch [1762/4000] Training [14/16] Loss: 0.00672 +Epoch [1762/4000] Training [15/16] Loss: 0.00640 +Epoch [1762/4000] Training [16/16] Loss: 0.00869 +Epoch [1762/4000] Training metric {'Train/mean dice_metric': 0.9953200817108154, 'Train/mean miou_metric': 0.9904258847236633, 'Train/mean f1': 0.9911193251609802, 'Train/mean precision': 0.9865592122077942, 'Train/mean recall': 0.9957217574119568, 'Train/mean hd95_metric': 1.0185948610305786} +Epoch [1762/4000] Validation [1/4] Loss: 0.22684 focal_loss 0.16813 dice_loss 0.05871 +Epoch [1762/4000] Validation [2/4] Loss: 0.55302 focal_loss 0.35787 dice_loss 0.19514 +Epoch [1762/4000] Validation [3/4] Loss: 0.22795 focal_loss 0.14521 dice_loss 0.08274 +Epoch [1762/4000] Validation [4/4] Loss: 0.36721 focal_loss 0.23523 dice_loss 0.13198 +Epoch [1762/4000] Validation metric {'Val/mean dice_metric': 0.97125643491745, 'Val/mean miou_metric': 0.9542579650878906, 'Val/mean f1': 0.9731730222702026, 'Val/mean precision': 0.97040194272995, 'Val/mean recall': 0.9759600758552551, 'Val/mean hd95_metric': 5.6931610107421875} +Cheakpoint... +Epoch [1762/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97125643491745, 'Val/mean miou_metric': 0.9542579650878906, 'Val/mean f1': 0.9731730222702026, 'Val/mean precision': 0.97040194272995, 'Val/mean recall': 0.9759600758552551, 'Val/mean hd95_metric': 5.6931610107421875} +Epoch [1763/4000] Training [1/16] Loss: 0.00672 +Epoch [1763/4000] Training [2/16] Loss: 0.00727 +Epoch [1763/4000] Training [3/16] Loss: 0.01074 +Epoch [1763/4000] Training [4/16] Loss: 0.00558 +Epoch [1763/4000] Training [5/16] Loss: 0.00661 +Epoch [1763/4000] Training [6/16] Loss: 0.00803 +Epoch [1763/4000] Training [7/16] Loss: 0.00841 +Epoch [1763/4000] Training [8/16] Loss: 0.00570 +Epoch [1763/4000] Training [9/16] Loss: 0.00541 +Epoch [1763/4000] Training [10/16] Loss: 0.00598 +Epoch [1763/4000] Training [11/16] Loss: 0.00933 +Epoch [1763/4000] Training [12/16] Loss: 0.00671 +Epoch [1763/4000] Training [13/16] Loss: 0.00783 +Epoch [1763/4000] Training [14/16] Loss: 0.00756 +Epoch [1763/4000] Training [15/16] Loss: 0.00733 +Epoch [1763/4000] Training [16/16] Loss: 0.01117 +Epoch [1763/4000] Training metric {'Train/mean dice_metric': 0.9930202960968018, 'Train/mean miou_metric': 0.9877817034721375, 'Train/mean f1': 0.9909133315086365, 'Train/mean precision': 0.9865263104438782, 'Train/mean recall': 0.995339572429657, 'Train/mean hd95_metric': 1.2141551971435547} +Epoch [1763/4000] Validation [1/4] Loss: 0.35106 focal_loss 0.27057 dice_loss 0.08049 +Epoch [1763/4000] Validation [2/4] Loss: 0.29380 focal_loss 0.17299 dice_loss 0.12081 +Epoch [1763/4000] Validation [3/4] Loss: 0.17779 focal_loss 0.11471 dice_loss 0.06309 +Epoch [1763/4000] Validation [4/4] Loss: 0.47187 focal_loss 0.32514 dice_loss 0.14673 +Epoch [1763/4000] Validation metric {'Val/mean dice_metric': 0.9718050956726074, 'Val/mean miou_metric': 0.9541074633598328, 'Val/mean f1': 0.9742996096611023, 'Val/mean precision': 0.9732910394668579, 'Val/mean recall': 0.9753102660179138, 'Val/mean hd95_metric': 5.1425323486328125} +Cheakpoint... +Epoch [1763/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718050956726074, 'Val/mean miou_metric': 0.9541074633598328, 'Val/mean f1': 0.9742996096611023, 'Val/mean precision': 0.9732910394668579, 'Val/mean recall': 0.9753102660179138, 'Val/mean hd95_metric': 5.1425323486328125} +Epoch [1764/4000] Training [1/16] Loss: 0.00505 +Epoch [1764/4000] Training [2/16] Loss: 0.00721 +Epoch [1764/4000] Training [3/16] Loss: 0.00752 +Epoch [1764/4000] Training [4/16] Loss: 0.00652 +Epoch [1764/4000] Training [5/16] Loss: 0.00560 +Epoch [1764/4000] Training [6/16] Loss: 0.00807 +Epoch [1764/4000] Training [7/16] Loss: 0.00612 +Epoch [1764/4000] Training [8/16] Loss: 0.00500 +Epoch [1764/4000] Training [9/16] Loss: 0.00490 +Epoch [1764/4000] Training [10/16] Loss: 0.00706 +Epoch [1764/4000] Training [11/16] Loss: 0.00739 +Epoch [1764/4000] Training [12/16] Loss: 0.00767 +Epoch [1764/4000] Training [13/16] Loss: 0.00633 +Epoch [1764/4000] Training [14/16] Loss: 0.00574 +Epoch [1764/4000] Training [15/16] Loss: 0.00646 +Epoch [1764/4000] Training [16/16] Loss: 0.00692 +Epoch [1764/4000] Training metric {'Train/mean dice_metric': 0.9954432249069214, 'Train/mean miou_metric': 0.9906637668609619, 'Train/mean f1': 0.9910786151885986, 'Train/mean precision': 0.9864548444747925, 'Train/mean recall': 0.9957458972930908, 'Train/mean hd95_metric': 1.0624592304229736} +Epoch [1764/4000] Validation [1/4] Loss: 0.45444 focal_loss 0.35339 dice_loss 0.10106 +Epoch [1764/4000] Validation [2/4] Loss: 0.34760 focal_loss 0.18613 dice_loss 0.16147 +Epoch [1764/4000] Validation [3/4] Loss: 0.23416 focal_loss 0.14748 dice_loss 0.08669 +Epoch [1764/4000] Validation [4/4] Loss: 0.26920 focal_loss 0.15925 dice_loss 0.10995 +Epoch [1764/4000] Validation metric {'Val/mean dice_metric': 0.9705380201339722, 'Val/mean miou_metric': 0.953621506690979, 'Val/mean f1': 0.9718546867370605, 'Val/mean precision': 0.9720513224601746, 'Val/mean recall': 0.9716581702232361, 'Val/mean hd95_metric': 5.96215295791626} +Cheakpoint... +Epoch [1764/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705380201339722, 'Val/mean miou_metric': 0.953621506690979, 'Val/mean f1': 0.9718546867370605, 'Val/mean precision': 0.9720513224601746, 'Val/mean recall': 0.9716581702232361, 'Val/mean hd95_metric': 5.96215295791626} +Epoch [1765/4000] Training [1/16] Loss: 0.00520 +Epoch [1765/4000] Training [2/16] Loss: 0.00460 +Epoch [1765/4000] Training [3/16] Loss: 0.00484 +Epoch [1765/4000] Training [4/16] Loss: 0.00714 +Epoch [1765/4000] Training [5/16] Loss: 0.00710 +Epoch [1765/4000] Training [6/16] Loss: 0.00740 +Epoch [1765/4000] Training [7/16] Loss: 0.00678 +Epoch [1765/4000] Training [8/16] Loss: 0.00572 +Epoch [1765/4000] Training [9/16] Loss: 0.00664 +Epoch [1765/4000] Training [10/16] Loss: 0.00590 +Epoch [1765/4000] Training [11/16] Loss: 0.00804 +Epoch [1765/4000] Training [12/16] Loss: 0.00611 +Epoch [1765/4000] Training [13/16] Loss: 0.00676 +Epoch [1765/4000] Training [14/16] Loss: 0.00802 +Epoch [1765/4000] Training [15/16] Loss: 0.00815 +Epoch [1765/4000] Training [16/16] Loss: 0.00709 +Epoch [1765/4000] Training metric {'Train/mean dice_metric': 0.9954859018325806, 'Train/mean miou_metric': 0.9907465577125549, 'Train/mean f1': 0.9911644458770752, 'Train/mean precision': 0.9864354133605957, 'Train/mean recall': 0.9959391355514526, 'Train/mean hd95_metric': 1.029088020324707} +Epoch [1765/4000] Validation [1/4] Loss: 0.45478 focal_loss 0.36313 dice_loss 0.09165 +Epoch [1765/4000] Validation [2/4] Loss: 0.70390 focal_loss 0.41268 dice_loss 0.29122 +Epoch [1765/4000] Validation [3/4] Loss: 0.16532 focal_loss 0.10930 dice_loss 0.05602 +Epoch [1765/4000] Validation [4/4] Loss: 0.37623 focal_loss 0.24978 dice_loss 0.12645 +Epoch [1765/4000] Validation metric {'Val/mean dice_metric': 0.9715415835380554, 'Val/mean miou_metric': 0.9545095562934875, 'Val/mean f1': 0.9723130464553833, 'Val/mean precision': 0.9725554585456848, 'Val/mean recall': 0.9720709323883057, 'Val/mean hd95_metric': 5.480988502502441} +Cheakpoint... +Epoch [1765/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715415835380554, 'Val/mean miou_metric': 0.9545095562934875, 'Val/mean f1': 0.9723130464553833, 'Val/mean precision': 0.9725554585456848, 'Val/mean recall': 0.9720709323883057, 'Val/mean hd95_metric': 5.480988502502441} +Epoch [1766/4000] Training [1/16] Loss: 0.00597 +Epoch [1766/4000] Training [2/16] Loss: 0.00495 +Epoch [1766/4000] Training [3/16] Loss: 0.00696 +Epoch [1766/4000] Training [4/16] Loss: 0.00596 +Epoch [1766/4000] Training [5/16] Loss: 0.00716 +Epoch [1766/4000] Training [6/16] Loss: 0.00602 +Epoch [1766/4000] Training [7/16] Loss: 0.01825 +Epoch [1766/4000] Training [8/16] Loss: 0.00657 +Epoch [1766/4000] Training [9/16] Loss: 0.01011 +Epoch [1766/4000] Training [10/16] Loss: 0.00742 +Epoch [1766/4000] Training [11/16] Loss: 0.00646 +Epoch [1766/4000] Training [12/16] Loss: 0.00532 +Epoch [1766/4000] Training [13/16] Loss: 0.00566 +Epoch [1766/4000] Training [14/16] Loss: 0.00862 +Epoch [1766/4000] Training [15/16] Loss: 0.00563 +Epoch [1766/4000] Training [16/16] Loss: 0.00677 +Epoch [1766/4000] Training metric {'Train/mean dice_metric': 0.9955446720123291, 'Train/mean miou_metric': 0.9908926486968994, 'Train/mean f1': 0.9914499521255493, 'Train/mean precision': 0.9867756366729736, 'Train/mean recall': 0.9961687326431274, 'Train/mean hd95_metric': 1.0477492809295654} +Epoch [1766/4000] Validation [1/4] Loss: 0.50472 focal_loss 0.40222 dice_loss 0.10250 +Epoch [1766/4000] Validation [2/4] Loss: 0.58463 focal_loss 0.35135 dice_loss 0.23328 +Epoch [1766/4000] Validation [3/4] Loss: 0.22498 focal_loss 0.14412 dice_loss 0.08087 +Epoch [1766/4000] Validation [4/4] Loss: 0.35933 focal_loss 0.23112 dice_loss 0.12821 +Epoch [1766/4000] Validation metric {'Val/mean dice_metric': 0.9707750082015991, 'Val/mean miou_metric': 0.9537078738212585, 'Val/mean f1': 0.9730687141418457, 'Val/mean precision': 0.9737668633460999, 'Val/mean recall': 0.9723716974258423, 'Val/mean hd95_metric': 5.748969554901123} +Cheakpoint... +Epoch [1766/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707750082015991, 'Val/mean miou_metric': 0.9537078738212585, 'Val/mean f1': 0.9730687141418457, 'Val/mean precision': 0.9737668633460999, 'Val/mean recall': 0.9723716974258423, 'Val/mean hd95_metric': 5.748969554901123} +Epoch [1767/4000] Training [1/16] Loss: 0.00603 +Epoch [1767/4000] Training [2/16] Loss: 0.00666 +Epoch [1767/4000] Training [3/16] Loss: 0.00746 +Epoch [1767/4000] Training [4/16] Loss: 0.00630 +Epoch [1767/4000] Training [5/16] Loss: 0.00806 +Epoch [1767/4000] Training [6/16] Loss: 0.00983 +Epoch [1767/4000] Training [7/16] Loss: 0.01049 +Epoch [1767/4000] Training [8/16] Loss: 0.00613 +Epoch [1767/4000] Training [9/16] Loss: 0.00569 +Epoch [1767/4000] Training [10/16] Loss: 0.00568 +Epoch [1767/4000] Training [11/16] Loss: 0.00600 +Epoch [1767/4000] Training [12/16] Loss: 0.00777 +Epoch [1767/4000] Training [13/16] Loss: 0.00836 +Epoch [1767/4000] Training [14/16] Loss: 0.00603 +Epoch [1767/4000] Training [15/16] Loss: 0.00712 +Epoch [1767/4000] Training [16/16] Loss: 0.00786 +Epoch [1767/4000] Training metric {'Train/mean dice_metric': 0.9950306415557861, 'Train/mean miou_metric': 0.9899024963378906, 'Train/mean f1': 0.9912033081054688, 'Train/mean precision': 0.986667811870575, 'Train/mean recall': 0.9957807064056396, 'Train/mean hd95_metric': 1.1143407821655273} +Epoch [1767/4000] Validation [1/4] Loss: 0.54228 focal_loss 0.38805 dice_loss 0.15423 +Epoch [1767/4000] Validation [2/4] Loss: 0.26325 focal_loss 0.14087 dice_loss 0.12238 +Epoch [1767/4000] Validation [3/4] Loss: 0.22071 focal_loss 0.14091 dice_loss 0.07981 +Epoch [1767/4000] Validation [4/4] Loss: 0.31625 focal_loss 0.18189 dice_loss 0.13436 +Epoch [1767/4000] Validation metric {'Val/mean dice_metric': 0.9700967669487, 'Val/mean miou_metric': 0.9522453546524048, 'Val/mean f1': 0.9723385572433472, 'Val/mean precision': 0.9725326895713806, 'Val/mean recall': 0.9721445441246033, 'Val/mean hd95_metric': 6.162194728851318} +Cheakpoint... +Epoch [1767/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700967669487, 'Val/mean miou_metric': 0.9522453546524048, 'Val/mean f1': 0.9723385572433472, 'Val/mean precision': 0.9725326895713806, 'Val/mean recall': 0.9721445441246033, 'Val/mean hd95_metric': 6.162194728851318} +Epoch [1768/4000] Training [1/16] Loss: 0.00779 +Epoch [1768/4000] Training [2/16] Loss: 0.00646 +Epoch [1768/4000] Training [3/16] Loss: 0.00629 +Epoch [1768/4000] Training [4/16] Loss: 0.00655 +Epoch [1768/4000] Training [5/16] Loss: 0.00682 +Epoch [1768/4000] Training [6/16] Loss: 0.00716 +Epoch [1768/4000] Training [7/16] Loss: 0.00508 +Epoch [1768/4000] Training [8/16] Loss: 0.00953 +Epoch [1768/4000] Training [9/16] Loss: 0.00603 +Epoch [1768/4000] Training [10/16] Loss: 0.00531 +Epoch [1768/4000] Training [11/16] Loss: 0.00768 +Epoch [1768/4000] Training [12/16] Loss: 0.00831 +Epoch [1768/4000] Training [13/16] Loss: 0.00817 +Epoch [1768/4000] Training [14/16] Loss: 0.00642 +Epoch [1768/4000] Training [15/16] Loss: 0.00631 +Epoch [1768/4000] Training [16/16] Loss: 0.00944 +Epoch [1768/4000] Training metric {'Train/mean dice_metric': 0.995339035987854, 'Train/mean miou_metric': 0.990452766418457, 'Train/mean f1': 0.991025984287262, 'Train/mean precision': 0.9864314794540405, 'Train/mean recall': 0.9956634640693665, 'Train/mean hd95_metric': 1.0708731412887573} +Epoch [1768/4000] Validation [1/4] Loss: 0.31539 focal_loss 0.24060 dice_loss 0.07479 +Epoch [1768/4000] Validation [2/4] Loss: 0.30496 focal_loss 0.15260 dice_loss 0.15236 +Epoch [1768/4000] Validation [3/4] Loss: 0.30803 focal_loss 0.20924 dice_loss 0.09879 +Epoch [1768/4000] Validation [4/4] Loss: 0.39282 focal_loss 0.25148 dice_loss 0.14134 +Epoch [1768/4000] Validation metric {'Val/mean dice_metric': 0.9735907316207886, 'Val/mean miou_metric': 0.9562927484512329, 'Val/mean f1': 0.9737985730171204, 'Val/mean precision': 0.9707878828048706, 'Val/mean recall': 0.9768280386924744, 'Val/mean hd95_metric': 5.641623497009277} +Cheakpoint... +Epoch [1768/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735907316207886, 'Val/mean miou_metric': 0.9562927484512329, 'Val/mean f1': 0.9737985730171204, 'Val/mean precision': 0.9707878828048706, 'Val/mean recall': 0.9768280386924744, 'Val/mean hd95_metric': 5.641623497009277} +Epoch [1769/4000] Training [1/16] Loss: 0.00602 +Epoch [1769/4000] Training [2/16] Loss: 0.00768 +Epoch [1769/4000] Training [3/16] Loss: 0.00777 +Epoch [1769/4000] Training [4/16] Loss: 0.00868 +Epoch [1769/4000] Training [5/16] Loss: 0.00674 +Epoch [1769/4000] Training [6/16] Loss: 0.01035 +Epoch [1769/4000] Training [7/16] Loss: 0.00975 +Epoch [1769/4000] Training [8/16] Loss: 0.00525 +Epoch [1769/4000] Training [9/16] Loss: 0.00501 +Epoch [1769/4000] Training [10/16] Loss: 0.00703 +Epoch [1769/4000] Training [11/16] Loss: 0.00780 +Epoch [1769/4000] Training [12/16] Loss: 0.00593 +Epoch [1769/4000] Training [13/16] Loss: 0.00484 +Epoch [1769/4000] Training [14/16] Loss: 0.00527 +Epoch [1769/4000] Training [15/16] Loss: 0.00659 +Epoch [1769/4000] Training [16/16] Loss: 0.00428 +Epoch [1769/4000] Training metric {'Train/mean dice_metric': 0.9954470992088318, 'Train/mean miou_metric': 0.9906903505325317, 'Train/mean f1': 0.9913423657417297, 'Train/mean precision': 0.9869042038917542, 'Train/mean recall': 0.9958205819129944, 'Train/mean hd95_metric': 1.0621453523635864} +Epoch [1769/4000] Validation [1/4] Loss: 0.29633 focal_loss 0.22546 dice_loss 0.07087 +Epoch [1769/4000] Validation [2/4] Loss: 0.25687 focal_loss 0.13768 dice_loss 0.11919 +Epoch [1769/4000] Validation [3/4] Loss: 0.25493 focal_loss 0.16340 dice_loss 0.09154 +Epoch [1769/4000] Validation [4/4] Loss: 0.26702 focal_loss 0.15412 dice_loss 0.11290 +Epoch [1769/4000] Validation metric {'Val/mean dice_metric': 0.9744057655334473, 'Val/mean miou_metric': 0.9574276804924011, 'Val/mean f1': 0.9747387170791626, 'Val/mean precision': 0.9703664779663086, 'Val/mean recall': 0.9791505336761475, 'Val/mean hd95_metric': 6.256551742553711} +Cheakpoint... +Epoch [1769/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744057655334473, 'Val/mean miou_metric': 0.9574276804924011, 'Val/mean f1': 0.9747387170791626, 'Val/mean precision': 0.9703664779663086, 'Val/mean recall': 0.9791505336761475, 'Val/mean hd95_metric': 6.256551742553711} +Epoch [1770/4000] Training [1/16] Loss: 0.00582 +Epoch [1770/4000] Training [2/16] Loss: 0.00619 +Epoch [1770/4000] Training [3/16] Loss: 0.00882 +Epoch [1770/4000] Training [4/16] Loss: 0.00553 +Epoch [1770/4000] Training [5/16] Loss: 0.00650 +Epoch [1770/4000] Training [6/16] Loss: 0.00457 +Epoch [1770/4000] Training [7/16] Loss: 0.00812 +Epoch [1770/4000] Training [8/16] Loss: 0.00543 +Epoch [1770/4000] Training [9/16] Loss: 0.00665 +Epoch [1770/4000] Training [10/16] Loss: 0.00710 +Epoch [1770/4000] Training [11/16] Loss: 0.00685 +Epoch [1770/4000] Training [12/16] Loss: 0.00565 +Epoch [1770/4000] Training [13/16] Loss: 0.00839 +Epoch [1770/4000] Training [14/16] Loss: 0.00581 +Epoch [1770/4000] Training [15/16] Loss: 0.00535 +Epoch [1770/4000] Training [16/16] Loss: 0.00607 +Epoch [1770/4000] Training metric {'Train/mean dice_metric': 0.995849609375, 'Train/mean miou_metric': 0.9914519786834717, 'Train/mean f1': 0.9914490580558777, 'Train/mean precision': 0.9867615699768066, 'Train/mean recall': 0.996181309223175, 'Train/mean hd95_metric': 1.0081074237823486} +Epoch [1770/4000] Validation [1/4] Loss: 0.22460 focal_loss 0.15929 dice_loss 0.06532 +Epoch [1770/4000] Validation [2/4] Loss: 0.24317 focal_loss 0.13027 dice_loss 0.11291 +Epoch [1770/4000] Validation [3/4] Loss: 0.37583 focal_loss 0.26440 dice_loss 0.11144 +Epoch [1770/4000] Validation [4/4] Loss: 0.34101 focal_loss 0.20830 dice_loss 0.13271 +Epoch [1770/4000] Validation metric {'Val/mean dice_metric': 0.9741790890693665, 'Val/mean miou_metric': 0.9573603868484497, 'Val/mean f1': 0.9737126231193542, 'Val/mean precision': 0.9687372446060181, 'Val/mean recall': 0.978739321231842, 'Val/mean hd95_metric': 5.8383660316467285} +Cheakpoint... +Epoch [1770/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741790890693665, 'Val/mean miou_metric': 0.9573603868484497, 'Val/mean f1': 0.9737126231193542, 'Val/mean precision': 0.9687372446060181, 'Val/mean recall': 0.978739321231842, 'Val/mean hd95_metric': 5.8383660316467285} +Epoch [1771/4000] Training [1/16] Loss: 0.00703 +Epoch [1771/4000] Training [2/16] Loss: 0.00649 +Epoch [1771/4000] Training [3/16] Loss: 0.00697 +Epoch [1771/4000] Training [4/16] Loss: 0.00848 +Epoch [1771/4000] Training [5/16] Loss: 0.00661 +Epoch [1771/4000] Training [6/16] Loss: 0.00753 +Epoch [1771/4000] Training [7/16] Loss: 0.00808 +Epoch [1771/4000] Training [8/16] Loss: 0.00672 +Epoch [1771/4000] Training [9/16] Loss: 0.00699 +Epoch [1771/4000] Training [10/16] Loss: 0.00752 +Epoch [1771/4000] Training [11/16] Loss: 0.00822 +Epoch [1771/4000] Training [12/16] Loss: 0.00650 +Epoch [1771/4000] Training [13/16] Loss: 0.00530 +Epoch [1771/4000] Training [14/16] Loss: 0.00540 +Epoch [1771/4000] Training [15/16] Loss: 0.00677 +Epoch [1771/4000] Training [16/16] Loss: 0.00889 +Epoch [1771/4000] Training metric {'Train/mean dice_metric': 0.9951861500740051, 'Train/mean miou_metric': 0.9901647567749023, 'Train/mean f1': 0.9910109043121338, 'Train/mean precision': 0.9863985776901245, 'Train/mean recall': 0.9956666231155396, 'Train/mean hd95_metric': 1.032245397567749} +Epoch [1771/4000] Validation [1/4] Loss: 0.27280 focal_loss 0.20487 dice_loss 0.06793 +Epoch [1771/4000] Validation [2/4] Loss: 0.44783 focal_loss 0.30658 dice_loss 0.14124 +Epoch [1771/4000] Validation [3/4] Loss: 0.38510 focal_loss 0.29512 dice_loss 0.08999 +Epoch [1771/4000] Validation [4/4] Loss: 0.53932 focal_loss 0.37228 dice_loss 0.16705 +Epoch [1771/4000] Validation metric {'Val/mean dice_metric': 0.9725335836410522, 'Val/mean miou_metric': 0.9546493291854858, 'Val/mean f1': 0.9728977680206299, 'Val/mean precision': 0.9664759635925293, 'Val/mean recall': 0.979405403137207, 'Val/mean hd95_metric': 6.299180030822754} +Cheakpoint... +Epoch [1771/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725335836410522, 'Val/mean miou_metric': 0.9546493291854858, 'Val/mean f1': 0.9728977680206299, 'Val/mean precision': 0.9664759635925293, 'Val/mean recall': 0.979405403137207, 'Val/mean hd95_metric': 6.299180030822754} +Epoch [1772/4000] Training [1/16] Loss: 0.00656 +Epoch [1772/4000] Training [2/16] Loss: 0.00771 +Epoch [1772/4000] Training [3/16] Loss: 0.00549 +Epoch [1772/4000] Training [4/16] Loss: 0.00589 +Epoch [1772/4000] Training [5/16] Loss: 0.00855 +Epoch [1772/4000] Training [6/16] Loss: 0.00551 +Epoch [1772/4000] Training [7/16] Loss: 0.00617 +Epoch [1772/4000] Training [8/16] Loss: 0.00690 +Epoch [1772/4000] Training [9/16] Loss: 0.00577 +Epoch [1772/4000] Training [10/16] Loss: 0.00480 +Epoch [1772/4000] Training [11/16] Loss: 0.00665 +Epoch [1772/4000] Training [12/16] Loss: 0.00749 +Epoch [1772/4000] Training [13/16] Loss: 0.00616 +Epoch [1772/4000] Training [14/16] Loss: 0.00570 +Epoch [1772/4000] Training [15/16] Loss: 0.00593 +Epoch [1772/4000] Training [16/16] Loss: 0.00579 +Epoch [1772/4000] Training metric {'Train/mean dice_metric': 0.9956499934196472, 'Train/mean miou_metric': 0.9910540580749512, 'Train/mean f1': 0.9910721778869629, 'Train/mean precision': 0.9860639572143555, 'Train/mean recall': 0.9961315393447876, 'Train/mean hd95_metric': 1.015695333480835} +Epoch [1772/4000] Validation [1/4] Loss: 0.29151 focal_loss 0.21987 dice_loss 0.07163 +Epoch [1772/4000] Validation [2/4] Loss: 0.38506 focal_loss 0.24566 dice_loss 0.13941 +Epoch [1772/4000] Validation [3/4] Loss: 0.38412 focal_loss 0.28953 dice_loss 0.09459 +Epoch [1772/4000] Validation [4/4] Loss: 0.50919 focal_loss 0.34134 dice_loss 0.16784 +Epoch [1772/4000] Validation metric {'Val/mean dice_metric': 0.9737936854362488, 'Val/mean miou_metric': 0.9566669464111328, 'Val/mean f1': 0.9734027981758118, 'Val/mean precision': 0.9648904204368591, 'Val/mean recall': 0.9820665717124939, 'Val/mean hd95_metric': 6.328115940093994} +Cheakpoint... +Epoch [1772/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737936854362488, 'Val/mean miou_metric': 0.9566669464111328, 'Val/mean f1': 0.9734027981758118, 'Val/mean precision': 0.9648904204368591, 'Val/mean recall': 0.9820665717124939, 'Val/mean hd95_metric': 6.328115940093994} +Epoch [1773/4000] Training [1/16] Loss: 0.00958 +Epoch [1773/4000] Training [2/16] Loss: 0.00643 +Epoch [1773/4000] Training [3/16] Loss: 0.00539 +Epoch [1773/4000] Training [4/16] Loss: 0.00991 +Epoch [1773/4000] Training [5/16] Loss: 0.00556 +Epoch [1773/4000] Training [6/16] Loss: 0.00656 +Epoch [1773/4000] Training [7/16] Loss: 0.00584 +Epoch [1773/4000] Training [8/16] Loss: 0.00582 +Epoch [1773/4000] Training [9/16] Loss: 0.00691 +Epoch [1773/4000] Training [10/16] Loss: 0.00547 +Epoch [1773/4000] Training [11/16] Loss: 0.00611 +Epoch [1773/4000] Training [12/16] Loss: 0.00607 +Epoch [1773/4000] Training [13/16] Loss: 0.00964 +Epoch [1773/4000] Training [14/16] Loss: 0.00563 +Epoch [1773/4000] Training [15/16] Loss: 0.00579 +Epoch [1773/4000] Training [16/16] Loss: 0.00856 +Epoch [1773/4000] Training metric {'Train/mean dice_metric': 0.9952704906463623, 'Train/mean miou_metric': 0.9902989268302917, 'Train/mean f1': 0.9910242557525635, 'Train/mean precision': 0.9863315224647522, 'Train/mean recall': 0.9957618713378906, 'Train/mean hd95_metric': 1.0250444412231445} +Epoch [1773/4000] Validation [1/4] Loss: 0.28585 focal_loss 0.21503 dice_loss 0.07082 +Epoch [1773/4000] Validation [2/4] Loss: 0.35300 focal_loss 0.21602 dice_loss 0.13698 +Epoch [1773/4000] Validation [3/4] Loss: 0.36832 focal_loss 0.27686 dice_loss 0.09146 +Epoch [1773/4000] Validation [4/4] Loss: 0.47666 focal_loss 0.30012 dice_loss 0.17654 +Epoch [1773/4000] Validation metric {'Val/mean dice_metric': 0.9727977514266968, 'Val/mean miou_metric': 0.9556446075439453, 'Val/mean f1': 0.9728803038597107, 'Val/mean precision': 0.9654327630996704, 'Val/mean recall': 0.9804437160491943, 'Val/mean hd95_metric': 6.849191188812256} +Cheakpoint... +Epoch [1773/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727977514266968, 'Val/mean miou_metric': 0.9556446075439453, 'Val/mean f1': 0.9728803038597107, 'Val/mean precision': 0.9654327630996704, 'Val/mean recall': 0.9804437160491943, 'Val/mean hd95_metric': 6.849191188812256} +Epoch [1774/4000] Training [1/16] Loss: 0.00913 +Epoch [1774/4000] Training [2/16] Loss: 0.00651 +Epoch [1774/4000] Training [3/16] Loss: 0.00501 +Epoch [1774/4000] Training [4/16] Loss: 0.00626 +Epoch [1774/4000] Training [5/16] Loss: 0.00657 +Epoch [1774/4000] Training [6/16] Loss: 0.00688 +Epoch [1774/4000] Training [7/16] Loss: 0.00685 +Epoch [1774/4000] Training [8/16] Loss: 0.00633 +Epoch [1774/4000] Training [9/16] Loss: 0.00796 +Epoch [1774/4000] Training [10/16] Loss: 0.00668 +Epoch [1774/4000] Training [11/16] Loss: 0.00494 +Epoch [1774/4000] Training [12/16] Loss: 0.00581 +Epoch [1774/4000] Training [13/16] Loss: 0.11893 +Epoch [1774/4000] Training [14/16] Loss: 0.00715 +Epoch [1774/4000] Training [15/16] Loss: 0.00659 +Epoch [1774/4000] Training [16/16] Loss: 0.00692 +Epoch [1774/4000] Training metric {'Train/mean dice_metric': 0.9940823912620544, 'Train/mean miou_metric': 0.9886564016342163, 'Train/mean f1': 0.9898364543914795, 'Train/mean precision': 0.9839776754379272, 'Train/mean recall': 0.9957653880119324, 'Train/mean hd95_metric': 1.498982548713684} +Epoch [1774/4000] Validation [1/4] Loss: 0.44136 focal_loss 0.34020 dice_loss 0.10116 +Epoch [1774/4000] Validation [2/4] Loss: 0.78520 focal_loss 0.49477 dice_loss 0.29043 +Epoch [1774/4000] Validation [3/4] Loss: 0.39467 focal_loss 0.29744 dice_loss 0.09723 +Epoch [1774/4000] Validation [4/4] Loss: 0.40029 focal_loss 0.25572 dice_loss 0.14457 +Epoch [1774/4000] Validation metric {'Val/mean dice_metric': 0.9697040319442749, 'Val/mean miou_metric': 0.9514358639717102, 'Val/mean f1': 0.9693965911865234, 'Val/mean precision': 0.9651666283607483, 'Val/mean recall': 0.9736638069152832, 'Val/mean hd95_metric': 6.895749092102051} +Cheakpoint... +Epoch [1774/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697040319442749, 'Val/mean miou_metric': 0.9514358639717102, 'Val/mean f1': 0.9693965911865234, 'Val/mean precision': 0.9651666283607483, 'Val/mean recall': 0.9736638069152832, 'Val/mean hd95_metric': 6.895749092102051} +Epoch [1775/4000] Training [1/16] Loss: 0.00720 +Epoch [1775/4000] Training [2/16] Loss: 0.00640 +Epoch [1775/4000] Training [3/16] Loss: 0.00641 +Epoch [1775/4000] Training [4/16] Loss: 0.00737 +Epoch [1775/4000] Training [5/16] Loss: 0.00746 +Epoch [1775/4000] Training [6/16] Loss: 0.00560 +Epoch [1775/4000] Training [7/16] Loss: 0.00628 +Epoch [1775/4000] Training [8/16] Loss: 0.00626 +Epoch [1775/4000] Training [9/16] Loss: 0.00828 +Epoch [1775/4000] Training [10/16] Loss: 0.00672 +Epoch [1775/4000] Training [11/16] Loss: 0.00845 +Epoch [1775/4000] Training [12/16] Loss: 0.00558 +Epoch [1775/4000] Training [13/16] Loss: 0.00727 +Epoch [1775/4000] Training [14/16] Loss: 0.00743 +Epoch [1775/4000] Training [15/16] Loss: 0.00758 +Epoch [1775/4000] Training [16/16] Loss: 0.00729 +Epoch [1775/4000] Training metric {'Train/mean dice_metric': 0.9951814413070679, 'Train/mean miou_metric': 0.9901766777038574, 'Train/mean f1': 0.9912174940109253, 'Train/mean precision': 0.9869760274887085, 'Train/mean recall': 0.995495617389679, 'Train/mean hd95_metric': 1.5681240558624268} +Epoch [1775/4000] Validation [1/4] Loss: 0.52834 focal_loss 0.42018 dice_loss 0.10816 +Epoch [1775/4000] Validation [2/4] Loss: 0.31075 focal_loss 0.18049 dice_loss 0.13027 +Epoch [1775/4000] Validation [3/4] Loss: 0.37927 focal_loss 0.26750 dice_loss 0.11177 +Epoch [1775/4000] Validation [4/4] Loss: 0.29217 focal_loss 0.18077 dice_loss 0.11140 +Epoch [1775/4000] Validation metric {'Val/mean dice_metric': 0.9702262878417969, 'Val/mean miou_metric': 0.952104389667511, 'Val/mean f1': 0.970680832862854, 'Val/mean precision': 0.9688968062400818, 'Val/mean recall': 0.972471296787262, 'Val/mean hd95_metric': 7.252648830413818} +Cheakpoint... +Epoch [1775/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702262878417969, 'Val/mean miou_metric': 0.952104389667511, 'Val/mean f1': 0.970680832862854, 'Val/mean precision': 0.9688968062400818, 'Val/mean recall': 0.972471296787262, 'Val/mean hd95_metric': 7.252648830413818} +Epoch [1776/4000] Training [1/16] Loss: 0.00692 +Epoch [1776/4000] Training [2/16] Loss: 0.00828 +Epoch [1776/4000] Training [3/16] Loss: 0.00777 +Epoch [1776/4000] Training [4/16] Loss: 0.00836 +Epoch [1776/4000] Training [5/16] Loss: 0.00614 +Epoch [1776/4000] Training [6/16] Loss: 0.00608 +Epoch [1776/4000] Training [7/16] Loss: 0.00695 +Epoch [1776/4000] Training [8/16] Loss: 0.00641 +Epoch [1776/4000] Training [9/16] Loss: 0.00894 +Epoch [1776/4000] Training [10/16] Loss: 0.00895 +Epoch [1776/4000] Training [11/16] Loss: 0.00659 +Epoch [1776/4000] Training [12/16] Loss: 0.00778 +Epoch [1776/4000] Training [13/16] Loss: 0.00750 +Epoch [1776/4000] Training [14/16] Loss: 0.00758 +Epoch [1776/4000] Training [15/16] Loss: 0.00529 +Epoch [1776/4000] Training [16/16] Loss: 0.00616 +Epoch [1776/4000] Training metric {'Train/mean dice_metric': 0.9954284429550171, 'Train/mean miou_metric': 0.9906409978866577, 'Train/mean f1': 0.9912957549095154, 'Train/mean precision': 0.986743688583374, 'Train/mean recall': 0.9958900809288025, 'Train/mean hd95_metric': 1.0135431289672852} +Epoch [1776/4000] Validation [1/4] Loss: 0.54107 focal_loss 0.43167 dice_loss 0.10940 +Epoch [1776/4000] Validation [2/4] Loss: 0.43428 focal_loss 0.26928 dice_loss 0.16499 +Epoch [1776/4000] Validation [3/4] Loss: 0.32056 focal_loss 0.22588 dice_loss 0.09468 +Epoch [1776/4000] Validation [4/4] Loss: 0.33923 focal_loss 0.21007 dice_loss 0.12917 +Epoch [1776/4000] Validation metric {'Val/mean dice_metric': 0.9705983400344849, 'Val/mean miou_metric': 0.9527425765991211, 'Val/mean f1': 0.9721277952194214, 'Val/mean precision': 0.970870316028595, 'Val/mean recall': 0.9733884334564209, 'Val/mean hd95_metric': 6.172572135925293} +Cheakpoint... +Epoch [1776/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705983400344849, 'Val/mean miou_metric': 0.9527425765991211, 'Val/mean f1': 0.9721277952194214, 'Val/mean precision': 0.970870316028595, 'Val/mean recall': 0.9733884334564209, 'Val/mean hd95_metric': 6.172572135925293} +Epoch [1777/4000] Training [1/16] Loss: 0.00946 +Epoch [1777/4000] Training [2/16] Loss: 0.00844 +Epoch [1777/4000] Training [3/16] Loss: 0.00633 +Epoch [1777/4000] Training [4/16] Loss: 0.00632 +Epoch [1777/4000] Training [5/16] Loss: 0.00615 +Epoch [1777/4000] Training [6/16] Loss: 0.00843 +Epoch [1777/4000] Training [7/16] Loss: 0.00923 +Epoch [1777/4000] Training [8/16] Loss: 0.00605 +Epoch [1777/4000] Training [9/16] Loss: 0.01035 +Epoch [1777/4000] Training [10/16] Loss: 0.00560 +Epoch [1777/4000] Training [11/16] Loss: 0.00824 +Epoch [1777/4000] Training [12/16] Loss: 0.00745 +Epoch [1777/4000] Training [13/16] Loss: 0.00872 +Epoch [1777/4000] Training [14/16] Loss: 0.00806 +Epoch [1777/4000] Training [15/16] Loss: 0.00826 +Epoch [1777/4000] Training [16/16] Loss: 0.00626 +Epoch [1777/4000] Training metric {'Train/mean dice_metric': 0.99335116147995, 'Train/mean miou_metric': 0.9869288206100464, 'Train/mean f1': 0.9899262189865112, 'Train/mean precision': 0.9856347441673279, 'Train/mean recall': 0.9942551851272583, 'Train/mean hd95_metric': 1.6967737674713135} +Epoch [1777/4000] Validation [1/4] Loss: 0.45319 focal_loss 0.35506 dice_loss 0.09813 +Epoch [1777/4000] Validation [2/4] Loss: 0.53814 focal_loss 0.32127 dice_loss 0.21686 +Epoch [1777/4000] Validation [3/4] Loss: 0.38483 focal_loss 0.29051 dice_loss 0.09433 +Epoch [1777/4000] Validation [4/4] Loss: 0.46556 focal_loss 0.27753 dice_loss 0.18803 +Epoch [1777/4000] Validation metric {'Val/mean dice_metric': 0.9691526293754578, 'Val/mean miou_metric': 0.9499391317367554, 'Val/mean f1': 0.9699369668960571, 'Val/mean precision': 0.965129017829895, 'Val/mean recall': 0.9747931957244873, 'Val/mean hd95_metric': 7.066318511962891} +Cheakpoint... +Epoch [1777/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691526293754578, 'Val/mean miou_metric': 0.9499391317367554, 'Val/mean f1': 0.9699369668960571, 'Val/mean precision': 0.965129017829895, 'Val/mean recall': 0.9747931957244873, 'Val/mean hd95_metric': 7.066318511962891} +Epoch [1778/4000] Training [1/16] Loss: 0.00579 +Epoch [1778/4000] Training [2/16] Loss: 0.00595 +Epoch [1778/4000] Training [3/16] Loss: 0.00671 +Epoch [1778/4000] Training [4/16] Loss: 0.02130 +Epoch [1778/4000] Training [5/16] Loss: 0.00904 +Epoch [1778/4000] Training [6/16] Loss: 0.00805 +Epoch [1778/4000] Training [7/16] Loss: 0.00612 +Epoch [1778/4000] Training [8/16] Loss: 0.00607 +Epoch [1778/4000] Training [9/16] Loss: 0.00891 +Epoch [1778/4000] Training [10/16] Loss: 0.00643 +Epoch [1778/4000] Training [11/16] Loss: 0.00695 +Epoch [1778/4000] Training [12/16] Loss: 0.00508 +Epoch [1778/4000] Training [13/16] Loss: 0.00558 +Epoch [1778/4000] Training [14/16] Loss: 0.01078 +Epoch [1778/4000] Training [15/16] Loss: 0.00819 +Epoch [1778/4000] Training [16/16] Loss: 0.00918 +Epoch [1778/4000] Training metric {'Train/mean dice_metric': 0.9949401021003723, 'Train/mean miou_metric': 0.9896764755249023, 'Train/mean f1': 0.99046790599823, 'Train/mean precision': 0.9853570461273193, 'Train/mean recall': 0.9956321120262146, 'Train/mean hd95_metric': 1.2119128704071045} +Epoch [1778/4000] Validation [1/4] Loss: 0.30961 focal_loss 0.22668 dice_loss 0.08294 +Epoch [1778/4000] Validation [2/4] Loss: 0.30932 focal_loss 0.15825 dice_loss 0.15107 +Epoch [1778/4000] Validation [3/4] Loss: 0.36668 focal_loss 0.27463 dice_loss 0.09204 +Epoch [1778/4000] Validation [4/4] Loss: 0.28998 focal_loss 0.17700 dice_loss 0.11297 +Epoch [1778/4000] Validation metric {'Val/mean dice_metric': 0.9715312123298645, 'Val/mean miou_metric': 0.9534339904785156, 'Val/mean f1': 0.97159343957901, 'Val/mean precision': 0.968826174736023, 'Val/mean recall': 0.9743765592575073, 'Val/mean hd95_metric': 7.192902565002441} +Cheakpoint... +Epoch [1778/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715312123298645, 'Val/mean miou_metric': 0.9534339904785156, 'Val/mean f1': 0.97159343957901, 'Val/mean precision': 0.968826174736023, 'Val/mean recall': 0.9743765592575073, 'Val/mean hd95_metric': 7.192902565002441} +Epoch [1779/4000] Training [1/16] Loss: 0.00879 +Epoch [1779/4000] Training [2/16] Loss: 0.00566 +Epoch [1779/4000] Training [3/16] Loss: 0.00953 +Epoch [1779/4000] Training [4/16] Loss: 0.00776 +Epoch [1779/4000] Training [5/16] Loss: 0.00725 +Epoch [1779/4000] Training [6/16] Loss: 0.00975 +Epoch [1779/4000] Training [7/16] Loss: 0.00593 +Epoch [1779/4000] Training [8/16] Loss: 0.00860 +Epoch [1779/4000] Training [9/16] Loss: 0.00760 +Epoch [1779/4000] Training [10/16] Loss: 0.00554 +Epoch [1779/4000] Training [11/16] Loss: 0.00856 +Epoch [1779/4000] Training [12/16] Loss: 0.00700 +Epoch [1779/4000] Training [13/16] Loss: 0.00716 +Epoch [1779/4000] Training [14/16] Loss: 0.00893 +Epoch [1779/4000] Training [15/16] Loss: 0.00486 +Epoch [1779/4000] Training [16/16] Loss: 0.00786 +Epoch [1779/4000] Training metric {'Train/mean dice_metric': 0.9951932430267334, 'Train/mean miou_metric': 0.9901801347732544, 'Train/mean f1': 0.9909246563911438, 'Train/mean precision': 0.9864265322685242, 'Train/mean recall': 0.9954639673233032, 'Train/mean hd95_metric': 1.2483185529708862} +Epoch [1779/4000] Validation [1/4] Loss: 0.35080 focal_loss 0.25979 dice_loss 0.09101 +Epoch [1779/4000] Validation [2/4] Loss: 0.30424 focal_loss 0.17351 dice_loss 0.13073 +Epoch [1779/4000] Validation [3/4] Loss: 0.37931 focal_loss 0.27712 dice_loss 0.10219 +Epoch [1779/4000] Validation [4/4] Loss: 0.29072 focal_loss 0.17879 dice_loss 0.11193 +Epoch [1779/4000] Validation metric {'Val/mean dice_metric': 0.972852349281311, 'Val/mean miou_metric': 0.9552633166313171, 'Val/mean f1': 0.9721794724464417, 'Val/mean precision': 0.9687678217887878, 'Val/mean recall': 0.9756152033805847, 'Val/mean hd95_metric': 6.67730712890625} +Cheakpoint... +Epoch [1779/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972852349281311, 'Val/mean miou_metric': 0.9552633166313171, 'Val/mean f1': 0.9721794724464417, 'Val/mean precision': 0.9687678217887878, 'Val/mean recall': 0.9756152033805847, 'Val/mean hd95_metric': 6.67730712890625} +Epoch [1780/4000] Training [1/16] Loss: 0.00771 +Epoch [1780/4000] Training [2/16] Loss: 0.00674 +Epoch [1780/4000] Training [3/16] Loss: 0.00553 +Epoch [1780/4000] Training [4/16] Loss: 0.00849 +Epoch [1780/4000] Training [5/16] Loss: 0.00709 +Epoch [1780/4000] Training [6/16] Loss: 0.00769 +Epoch [1780/4000] Training [7/16] Loss: 0.00779 +Epoch [1780/4000] Training [8/16] Loss: 0.00829 +Epoch [1780/4000] Training [9/16] Loss: 0.00843 +Epoch [1780/4000] Training [10/16] Loss: 0.00648 +Epoch [1780/4000] Training [11/16] Loss: 0.00590 +Epoch [1780/4000] Training [12/16] Loss: 0.00786 +Epoch [1780/4000] Training [13/16] Loss: 0.00664 +Epoch [1780/4000] Training [14/16] Loss: 0.00658 +Epoch [1780/4000] Training [15/16] Loss: 0.00583 +Epoch [1780/4000] Training [16/16] Loss: 0.00733 +Epoch [1780/4000] Training metric {'Train/mean dice_metric': 0.9951539635658264, 'Train/mean miou_metric': 0.9900856018066406, 'Train/mean f1': 0.9906482100486755, 'Train/mean precision': 0.9857639074325562, 'Train/mean recall': 0.9955812096595764, 'Train/mean hd95_metric': 1.444889783859253} +Epoch [1780/4000] Validation [1/4] Loss: 0.30245 focal_loss 0.22565 dice_loss 0.07680 +Epoch [1780/4000] Validation [2/4] Loss: 0.74211 focal_loss 0.44168 dice_loss 0.30043 +Epoch [1780/4000] Validation [3/4] Loss: 0.20228 focal_loss 0.12436 dice_loss 0.07792 +Epoch [1780/4000] Validation [4/4] Loss: 0.34168 focal_loss 0.20834 dice_loss 0.13334 +Epoch [1780/4000] Validation metric {'Val/mean dice_metric': 0.9688459634780884, 'Val/mean miou_metric': 0.9518036842346191, 'Val/mean f1': 0.9719979166984558, 'Val/mean precision': 0.9693019986152649, 'Val/mean recall': 0.9747088551521301, 'Val/mean hd95_metric': 6.340590953826904} +Cheakpoint... +Epoch [1780/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688459634780884, 'Val/mean miou_metric': 0.9518036842346191, 'Val/mean f1': 0.9719979166984558, 'Val/mean precision': 0.9693019986152649, 'Val/mean recall': 0.9747088551521301, 'Val/mean hd95_metric': 6.340590953826904} +Epoch [1781/4000] Training [1/16] Loss: 0.00780 +Epoch [1781/4000] Training [2/16] Loss: 0.00510 +Epoch [1781/4000] Training [3/16] Loss: 0.00935 +Epoch [1781/4000] Training [4/16] Loss: 0.00620 +Epoch [1781/4000] Training [5/16] Loss: 0.00568 +Epoch [1781/4000] Training [6/16] Loss: 0.00985 +Epoch [1781/4000] Training [7/16] Loss: 0.00536 +Epoch [1781/4000] Training [8/16] Loss: 0.00837 +Epoch [1781/4000] Training [9/16] Loss: 0.00738 +Epoch [1781/4000] Training [10/16] Loss: 0.00595 +Epoch [1781/4000] Training [11/16] Loss: 0.00697 +Epoch [1781/4000] Training [12/16] Loss: 0.00769 +Epoch [1781/4000] Training [13/16] Loss: 0.00706 +Epoch [1781/4000] Training [14/16] Loss: 0.00784 +Epoch [1781/4000] Training [15/16] Loss: 0.00625 +Epoch [1781/4000] Training [16/16] Loss: 0.00634 +Epoch [1781/4000] Training metric {'Train/mean dice_metric': 0.9954077005386353, 'Train/mean miou_metric': 0.9905809164047241, 'Train/mean f1': 0.9907918572425842, 'Train/mean precision': 0.9862757921218872, 'Train/mean recall': 0.9953494668006897, 'Train/mean hd95_metric': 1.431114673614502} +Epoch [1781/4000] Validation [1/4] Loss: 0.61731 focal_loss 0.50630 dice_loss 0.11101 +Epoch [1781/4000] Validation [2/4] Loss: 0.44070 focal_loss 0.25435 dice_loss 0.18636 +Epoch [1781/4000] Validation [3/4] Loss: 0.18684 focal_loss 0.12518 dice_loss 0.06166 +Epoch [1781/4000] Validation [4/4] Loss: 0.21781 focal_loss 0.12792 dice_loss 0.08989 +Epoch [1781/4000] Validation metric {'Val/mean dice_metric': 0.9710792303085327, 'Val/mean miou_metric': 0.9528137445449829, 'Val/mean f1': 0.9704853296279907, 'Val/mean precision': 0.9717231392860413, 'Val/mean recall': 0.9692506790161133, 'Val/mean hd95_metric': 6.337416648864746} +Cheakpoint... +Epoch [1781/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710792303085327, 'Val/mean miou_metric': 0.9528137445449829, 'Val/mean f1': 0.9704853296279907, 'Val/mean precision': 0.9717231392860413, 'Val/mean recall': 0.9692506790161133, 'Val/mean hd95_metric': 6.337416648864746} +Epoch [1782/4000] Training [1/16] Loss: 0.00807 +Epoch [1782/4000] Training [2/16] Loss: 0.00699 +Epoch [1782/4000] Training [3/16] Loss: 0.00744 +Epoch [1782/4000] Training [4/16] Loss: 0.00695 +Epoch [1782/4000] Training [5/16] Loss: 0.00715 +Epoch [1782/4000] Training [6/16] Loss: 0.00750 +Epoch [1782/4000] Training [7/16] Loss: 0.00697 +Epoch [1782/4000] Training [8/16] Loss: 0.00613 +Epoch [1782/4000] Training [9/16] Loss: 0.00707 +Epoch [1782/4000] Training [10/16] Loss: 0.00889 +Epoch [1782/4000] Training [11/16] Loss: 0.00553 +Epoch [1782/4000] Training [12/16] Loss: 0.00775 +Epoch [1782/4000] Training [13/16] Loss: 0.00640 +Epoch [1782/4000] Training [14/16] Loss: 0.00619 +Epoch [1782/4000] Training [15/16] Loss: 0.00893 +Epoch [1782/4000] Training [16/16] Loss: 0.01113 +Epoch [1782/4000] Training metric {'Train/mean dice_metric': 0.995183527469635, 'Train/mean miou_metric': 0.9901285767555237, 'Train/mean f1': 0.9906675219535828, 'Train/mean precision': 0.9857624769210815, 'Train/mean recall': 0.9956216216087341, 'Train/mean hd95_metric': 1.0328404903411865} +Epoch [1782/4000] Validation [1/4] Loss: 0.39942 focal_loss 0.31196 dice_loss 0.08746 +Epoch [1782/4000] Validation [2/4] Loss: 0.32160 focal_loss 0.18400 dice_loss 0.13760 +Epoch [1782/4000] Validation [3/4] Loss: 0.32412 focal_loss 0.22277 dice_loss 0.10136 +Epoch [1782/4000] Validation [4/4] Loss: 0.24209 focal_loss 0.13304 dice_loss 0.10905 +Epoch [1782/4000] Validation metric {'Val/mean dice_metric': 0.9710248708724976, 'Val/mean miou_metric': 0.9535890817642212, 'Val/mean f1': 0.9728213548660278, 'Val/mean precision': 0.9689180254936218, 'Val/mean recall': 0.9767563343048096, 'Val/mean hd95_metric': 6.425131320953369} +Cheakpoint... +Epoch [1782/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710248708724976, 'Val/mean miou_metric': 0.9535890817642212, 'Val/mean f1': 0.9728213548660278, 'Val/mean precision': 0.9689180254936218, 'Val/mean recall': 0.9767563343048096, 'Val/mean hd95_metric': 6.425131320953369} +Epoch [1783/4000] Training [1/16] Loss: 0.00576 +Epoch [1783/4000] Training [2/16] Loss: 0.00671 +Epoch [1783/4000] Training [3/16] Loss: 0.00564 +Epoch [1783/4000] Training [4/16] Loss: 0.00511 +Epoch [1783/4000] Training [5/16] Loss: 0.00540 +Epoch [1783/4000] Training [6/16] Loss: 0.00646 +Epoch [1783/4000] Training [7/16] Loss: 0.00631 +Epoch [1783/4000] Training [8/16] Loss: 0.00605 +Epoch [1783/4000] Training [9/16] Loss: 0.00642 +Epoch [1783/4000] Training [10/16] Loss: 0.00616 +Epoch [1783/4000] Training [11/16] Loss: 0.00447 +Epoch [1783/4000] Training [12/16] Loss: 0.00610 +Epoch [1783/4000] Training [13/16] Loss: 0.00591 +Epoch [1783/4000] Training [14/16] Loss: 0.00698 +Epoch [1783/4000] Training [15/16] Loss: 0.00749 +Epoch [1783/4000] Training [16/16] Loss: 0.00587 +Epoch [1783/4000] Training metric {'Train/mean dice_metric': 0.9959057569503784, 'Train/mean miou_metric': 0.9915602207183838, 'Train/mean f1': 0.9909738898277283, 'Train/mean precision': 0.9858012199401855, 'Train/mean recall': 0.9962011575698853, 'Train/mean hd95_metric': 1.084951400756836} +Epoch [1783/4000] Validation [1/4] Loss: 0.37009 focal_loss 0.28922 dice_loss 0.08087 +Epoch [1783/4000] Validation [2/4] Loss: 0.42880 focal_loss 0.27607 dice_loss 0.15274 +Epoch [1783/4000] Validation [3/4] Loss: 0.18723 focal_loss 0.12473 dice_loss 0.06250 +Epoch [1783/4000] Validation [4/4] Loss: 0.46448 focal_loss 0.31046 dice_loss 0.15402 +Epoch [1783/4000] Validation metric {'Val/mean dice_metric': 0.9726337194442749, 'Val/mean miou_metric': 0.9550905227661133, 'Val/mean f1': 0.9721636176109314, 'Val/mean precision': 0.9684301018714905, 'Val/mean recall': 0.975925862789154, 'Val/mean hd95_metric': 6.435835361480713} +Cheakpoint... +Epoch [1783/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726337194442749, 'Val/mean miou_metric': 0.9550905227661133, 'Val/mean f1': 0.9721636176109314, 'Val/mean precision': 0.9684301018714905, 'Val/mean recall': 0.975925862789154, 'Val/mean hd95_metric': 6.435835361480713} +Epoch [1784/4000] Training [1/16] Loss: 0.00679 +Epoch [1784/4000] Training [2/16] Loss: 0.00918 +Epoch [1784/4000] Training [3/16] Loss: 0.00468 +Epoch [1784/4000] Training [4/16] Loss: 0.00703 +Epoch [1784/4000] Training [5/16] Loss: 0.00709 +Epoch [1784/4000] Training [6/16] Loss: 0.00569 +Epoch [1784/4000] Training [7/16] Loss: 0.00578 +Epoch [1784/4000] Training [8/16] Loss: 0.00744 +Epoch [1784/4000] Training [9/16] Loss: 0.00588 +Epoch [1784/4000] Training [10/16] Loss: 0.00606 +Epoch [1784/4000] Training [11/16] Loss: 0.00574 +Epoch [1784/4000] Training [12/16] Loss: 0.00633 +Epoch [1784/4000] Training [13/16] Loss: 0.00629 +Epoch [1784/4000] Training [14/16] Loss: 0.00747 +Epoch [1784/4000] Training [15/16] Loss: 0.00579 +Epoch [1784/4000] Training [16/16] Loss: 0.00663 +Epoch [1784/4000] Training metric {'Train/mean dice_metric': 0.9958429932594299, 'Train/mean miou_metric': 0.9914568662643433, 'Train/mean f1': 0.9915391206741333, 'Train/mean precision': 0.9870659112930298, 'Train/mean recall': 0.9960530400276184, 'Train/mean hd95_metric': 1.0130224227905273} +Epoch [1784/4000] Validation [1/4] Loss: 0.42780 focal_loss 0.33274 dice_loss 0.09505 +Epoch [1784/4000] Validation [2/4] Loss: 0.25754 focal_loss 0.13754 dice_loss 0.12001 +Epoch [1784/4000] Validation [3/4] Loss: 0.16779 focal_loss 0.10865 dice_loss 0.05915 +Epoch [1784/4000] Validation [4/4] Loss: 0.30997 focal_loss 0.19435 dice_loss 0.11562 +Epoch [1784/4000] Validation metric {'Val/mean dice_metric': 0.973008930683136, 'Val/mean miou_metric': 0.9561976194381714, 'Val/mean f1': 0.9740805625915527, 'Val/mean precision': 0.9738368391990662, 'Val/mean recall': 0.9743244051933289, 'Val/mean hd95_metric': 5.710567474365234} +Cheakpoint... +Epoch [1784/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973008930683136, 'Val/mean miou_metric': 0.9561976194381714, 'Val/mean f1': 0.9740805625915527, 'Val/mean precision': 0.9738368391990662, 'Val/mean recall': 0.9743244051933289, 'Val/mean hd95_metric': 5.710567474365234} +Epoch [1785/4000] Training [1/16] Loss: 0.00646 +Epoch [1785/4000] Training [2/16] Loss: 0.02010 +Epoch [1785/4000] Training [3/16] Loss: 0.00561 +Epoch [1785/4000] Training [4/16] Loss: 0.00619 +Epoch [1785/4000] Training [5/16] Loss: 0.00580 +Epoch [1785/4000] Training [6/16] Loss: 0.00562 +Epoch [1785/4000] Training [7/16] Loss: 0.00600 +Epoch [1785/4000] Training [8/16] Loss: 0.00635 +Epoch [1785/4000] Training [9/16] Loss: 0.00594 +Epoch [1785/4000] Training [10/16] Loss: 0.00585 +Epoch [1785/4000] Training [11/16] Loss: 0.01351 +Epoch [1785/4000] Training [12/16] Loss: 0.00581 +Epoch [1785/4000] Training [13/16] Loss: 0.00682 +Epoch [1785/4000] Training [14/16] Loss: 0.00609 +Epoch [1785/4000] Training [15/16] Loss: 0.00619 +Epoch [1785/4000] Training [16/16] Loss: 0.00650 +Epoch [1785/4000] Training metric {'Train/mean dice_metric': 0.9958032369613647, 'Train/mean miou_metric': 0.9913747310638428, 'Train/mean f1': 0.9910977482795715, 'Train/mean precision': 0.9864246845245361, 'Train/mean recall': 0.9958152770996094, 'Train/mean hd95_metric': 1.2977280616760254} +Epoch [1785/4000] Validation [1/4] Loss: 0.30974 focal_loss 0.23548 dice_loss 0.07425 +Epoch [1785/4000] Validation [2/4] Loss: 0.56765 focal_loss 0.36336 dice_loss 0.20429 +Epoch [1785/4000] Validation [3/4] Loss: 0.24516 focal_loss 0.16162 dice_loss 0.08354 +Epoch [1785/4000] Validation [4/4] Loss: 0.26925 focal_loss 0.15621 dice_loss 0.11304 +Epoch [1785/4000] Validation metric {'Val/mean dice_metric': 0.9689494967460632, 'Val/mean miou_metric': 0.9512065649032593, 'Val/mean f1': 0.9713922142982483, 'Val/mean precision': 0.9708731770515442, 'Val/mean recall': 0.9719117879867554, 'Val/mean hd95_metric': 7.295373439788818} +Cheakpoint... +Epoch [1785/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689494967460632, 'Val/mean miou_metric': 0.9512065649032593, 'Val/mean f1': 0.9713922142982483, 'Val/mean precision': 0.9708731770515442, 'Val/mean recall': 0.9719117879867554, 'Val/mean hd95_metric': 7.295373439788818} +Epoch [1786/4000] Training [1/16] Loss: 0.00673 +Epoch [1786/4000] Training [2/16] Loss: 0.00837 +Epoch [1786/4000] Training [3/16] Loss: 0.00658 +Epoch [1786/4000] Training [4/16] Loss: 0.00795 +Epoch [1786/4000] Training [5/16] Loss: 0.00852 +Epoch [1786/4000] Training [6/16] Loss: 0.00665 +Epoch [1786/4000] Training [7/16] Loss: 0.00719 +Epoch [1786/4000] Training [8/16] Loss: 0.00565 +Epoch [1786/4000] Training [9/16] Loss: 0.00716 +Epoch [1786/4000] Training [10/16] Loss: 0.00654 +Epoch [1786/4000] Training [11/16] Loss: 0.00819 +Epoch [1786/4000] Training [12/16] Loss: 0.00612 +Epoch [1786/4000] Training [13/16] Loss: 0.00674 +Epoch [1786/4000] Training [14/16] Loss: 0.01098 +Epoch [1786/4000] Training [15/16] Loss: 0.00498 +Epoch [1786/4000] Training [16/16] Loss: 0.00690 +Epoch [1786/4000] Training metric {'Train/mean dice_metric': 0.9953143000602722, 'Train/mean miou_metric': 0.9904069900512695, 'Train/mean f1': 0.9909098148345947, 'Train/mean precision': 0.9865148067474365, 'Train/mean recall': 0.9953441619873047, 'Train/mean hd95_metric': 1.0643374919891357} +Epoch [1786/4000] Validation [1/4] Loss: 0.44405 focal_loss 0.33288 dice_loss 0.11116 +Epoch [1786/4000] Validation [2/4] Loss: 0.21476 focal_loss 0.11411 dice_loss 0.10065 +Epoch [1786/4000] Validation [3/4] Loss: 0.22909 focal_loss 0.15958 dice_loss 0.06951 +Epoch [1786/4000] Validation [4/4] Loss: 0.29847 focal_loss 0.17106 dice_loss 0.12741 +Epoch [1786/4000] Validation metric {'Val/mean dice_metric': 0.9698997735977173, 'Val/mean miou_metric': 0.9518140554428101, 'Val/mean f1': 0.9699344635009766, 'Val/mean precision': 0.9694551825523376, 'Val/mean recall': 0.9704141020774841, 'Val/mean hd95_metric': 7.049346923828125} +Cheakpoint... +Epoch [1786/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698997735977173, 'Val/mean miou_metric': 0.9518140554428101, 'Val/mean f1': 0.9699344635009766, 'Val/mean precision': 0.9694551825523376, 'Val/mean recall': 0.9704141020774841, 'Val/mean hd95_metric': 7.049346923828125} +Epoch [1787/4000] Training [1/16] Loss: 0.00702 +Epoch [1787/4000] Training [2/16] Loss: 0.00841 +Epoch [1787/4000] Training [3/16] Loss: 0.00569 +Epoch [1787/4000] Training [4/16] Loss: 0.00865 +Epoch [1787/4000] Training [5/16] Loss: 0.00946 +Epoch [1787/4000] Training [6/16] Loss: 0.00651 +Epoch [1787/4000] Training [7/16] Loss: 0.00753 +Epoch [1787/4000] Training [8/16] Loss: 0.00752 +Epoch [1787/4000] Training [9/16] Loss: 0.00561 +Epoch [1787/4000] Training [10/16] Loss: 0.00961 +Epoch [1787/4000] Training [11/16] Loss: 0.00832 +Epoch [1787/4000] Training [12/16] Loss: 0.01528 +Epoch [1787/4000] Training [13/16] Loss: 0.00560 +Epoch [1787/4000] Training [14/16] Loss: 0.00596 +Epoch [1787/4000] Training [15/16] Loss: 0.00439 +Epoch [1787/4000] Training [16/16] Loss: 0.00710 +Epoch [1787/4000] Training metric {'Train/mean dice_metric': 0.9947645664215088, 'Train/mean miou_metric': 0.9892663359642029, 'Train/mean f1': 0.9894529581069946, 'Train/mean precision': 0.9839484691619873, 'Train/mean recall': 0.9950193762779236, 'Train/mean hd95_metric': 1.1229956150054932} +Epoch [1787/4000] Validation [1/4] Loss: 0.29816 focal_loss 0.22921 dice_loss 0.06895 +Epoch [1787/4000] Validation [2/4] Loss: 0.36409 focal_loss 0.22244 dice_loss 0.14164 +Epoch [1787/4000] Validation [3/4] Loss: 0.34117 focal_loss 0.24540 dice_loss 0.09577 +Epoch [1787/4000] Validation [4/4] Loss: 0.33858 focal_loss 0.20696 dice_loss 0.13163 +Epoch [1787/4000] Validation metric {'Val/mean dice_metric': 0.9693552851676941, 'Val/mean miou_metric': 0.9503822326660156, 'Val/mean f1': 0.9675666093826294, 'Val/mean precision': 0.9536262154579163, 'Val/mean recall': 0.9819207787513733, 'Val/mean hd95_metric': 7.531233787536621} +Cheakpoint... +Epoch [1787/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693552851676941, 'Val/mean miou_metric': 0.9503822326660156, 'Val/mean f1': 0.9675666093826294, 'Val/mean precision': 0.9536262154579163, 'Val/mean recall': 0.9819207787513733, 'Val/mean hd95_metric': 7.531233787536621} +Epoch [1788/4000] Training [1/16] Loss: 0.00543 +Epoch [1788/4000] Training [2/16] Loss: 0.01830 +Epoch [1788/4000] Training [3/16] Loss: 0.00771 +Epoch [1788/4000] Training [4/16] Loss: 0.00639 +Epoch [1788/4000] Training [5/16] Loss: 0.00567 +Epoch [1788/4000] Training [6/16] Loss: 0.00921 +Epoch [1788/4000] Training [7/16] Loss: 0.00740 +Epoch [1788/4000] Training [8/16] Loss: 0.00634 +Epoch [1788/4000] Training [9/16] Loss: 0.00719 +Epoch [1788/4000] Training [10/16] Loss: 0.00697 +Epoch [1788/4000] Training [11/16] Loss: 0.00722 +Epoch [1788/4000] Training [12/16] Loss: 0.00670 +Epoch [1788/4000] Training [13/16] Loss: 0.01161 +Epoch [1788/4000] Training [14/16] Loss: 0.00648 +Epoch [1788/4000] Training [15/16] Loss: 0.00745 +Epoch [1788/4000] Training [16/16] Loss: 0.00729 +Epoch [1788/4000] Training metric {'Train/mean dice_metric': 0.994106650352478, 'Train/mean miou_metric': 0.9883818030357361, 'Train/mean f1': 0.9896761178970337, 'Train/mean precision': 0.9846315979957581, 'Train/mean recall': 0.9947726130485535, 'Train/mean hd95_metric': 2.148303747177124} +Epoch [1788/4000] Validation [1/4] Loss: 0.64974 focal_loss 0.49744 dice_loss 0.15230 +Epoch [1788/4000] Validation [2/4] Loss: 0.69716 focal_loss 0.42240 dice_loss 0.27475 +Epoch [1788/4000] Validation [3/4] Loss: 0.19994 focal_loss 0.13299 dice_loss 0.06695 +Epoch [1788/4000] Validation [4/4] Loss: 0.77382 focal_loss 0.57999 dice_loss 0.19383 +Epoch [1788/4000] Validation metric {'Val/mean dice_metric': 0.9620906710624695, 'Val/mean miou_metric': 0.9424230456352234, 'Val/mean f1': 0.9645741581916809, 'Val/mean precision': 0.9724754095077515, 'Val/mean recall': 0.9568001627922058, 'Val/mean hd95_metric': 8.141145706176758} +Cheakpoint... +Epoch [1788/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9621], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9620906710624695, 'Val/mean miou_metric': 0.9424230456352234, 'Val/mean f1': 0.9645741581916809, 'Val/mean precision': 0.9724754095077515, 'Val/mean recall': 0.9568001627922058, 'Val/mean hd95_metric': 8.141145706176758} +Epoch [1789/4000] Training [1/16] Loss: 0.00858 +Epoch [1789/4000] Training [2/16] Loss: 0.00978 +Epoch [1789/4000] Training [3/16] Loss: 0.01300 +Epoch [1789/4000] Training [4/16] Loss: 0.01049 +Epoch [1789/4000] Training [5/16] Loss: 0.01159 +Epoch [1789/4000] Training [6/16] Loss: 0.01145 +Epoch [1789/4000] Training [7/16] Loss: 0.00974 +Epoch [1789/4000] Training [8/16] Loss: 0.00926 +Epoch [1789/4000] Training [9/16] Loss: 0.00654 +Epoch [1789/4000] Training [10/16] Loss: 0.00774 +Epoch [1789/4000] Training [11/16] Loss: 0.00751 +Epoch [1789/4000] Training [12/16] Loss: 0.01209 +Epoch [1789/4000] Training [13/16] Loss: 0.00792 +Epoch [1789/4000] Training [14/16] Loss: 0.01121 +Epoch [1789/4000] Training [15/16] Loss: 0.00704 +Epoch [1789/4000] Training [16/16] Loss: 0.00730 +Epoch [1789/4000] Training metric {'Train/mean dice_metric': 0.9937019348144531, 'Train/mean miou_metric': 0.9872794151306152, 'Train/mean f1': 0.9895455837249756, 'Train/mean precision': 0.9852277040481567, 'Train/mean recall': 0.9939014911651611, 'Train/mean hd95_metric': 1.6330723762512207} +Epoch [1789/4000] Validation [1/4] Loss: 0.49244 focal_loss 0.39635 dice_loss 0.09609 +Epoch [1789/4000] Validation [2/4] Loss: 0.69492 focal_loss 0.40665 dice_loss 0.28828 +Epoch [1789/4000] Validation [3/4] Loss: 0.17884 focal_loss 0.11589 dice_loss 0.06295 +Epoch [1789/4000] Validation [4/4] Loss: 0.28320 focal_loss 0.16836 dice_loss 0.11484 +Epoch [1789/4000] Validation metric {'Val/mean dice_metric': 0.9667556881904602, 'Val/mean miou_metric': 0.9481474161148071, 'Val/mean f1': 0.9691423177719116, 'Val/mean precision': 0.9695765376091003, 'Val/mean recall': 0.9687085151672363, 'Val/mean hd95_metric': 7.021966457366943} +Cheakpoint... +Epoch [1789/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9668], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667556881904602, 'Val/mean miou_metric': 0.9481474161148071, 'Val/mean f1': 0.9691423177719116, 'Val/mean precision': 0.9695765376091003, 'Val/mean recall': 0.9687085151672363, 'Val/mean hd95_metric': 7.021966457366943} +Epoch [1790/4000] Training [1/16] Loss: 0.00823 +Epoch [1790/4000] Training [2/16] Loss: 0.00806 +Epoch [1790/4000] Training [3/16] Loss: 0.00830 +Epoch [1790/4000] Training [4/16] Loss: 0.00775 +Epoch [1790/4000] Training [5/16] Loss: 0.00845 +Epoch [1790/4000] Training [6/16] Loss: 0.00761 +Epoch [1790/4000] Training [7/16] Loss: 0.00794 +Epoch [1790/4000] Training [8/16] Loss: 0.00729 +Epoch [1790/4000] Training [9/16] Loss: 0.00573 +Epoch [1790/4000] Training [10/16] Loss: 0.00807 +Epoch [1790/4000] Training [11/16] Loss: 0.00685 +Epoch [1790/4000] Training [12/16] Loss: 0.00598 +Epoch [1790/4000] Training [13/16] Loss: 0.00653 +Epoch [1790/4000] Training [14/16] Loss: 0.00692 +Epoch [1790/4000] Training [15/16] Loss: 0.00603 +Epoch [1790/4000] Training [16/16] Loss: 0.01406 +Epoch [1790/4000] Training metric {'Train/mean dice_metric': 0.994685173034668, 'Train/mean miou_metric': 0.9892175197601318, 'Train/mean f1': 0.9904811382293701, 'Train/mean precision': 0.9860822558403015, 'Train/mean recall': 0.9949194192886353, 'Train/mean hd95_metric': 1.103339672088623} +Epoch [1790/4000] Validation [1/4] Loss: 0.26193 focal_loss 0.19349 dice_loss 0.06844 +Epoch [1790/4000] Validation [2/4] Loss: 0.49878 focal_loss 0.31359 dice_loss 0.18519 +Epoch [1790/4000] Validation [3/4] Loss: 0.22561 focal_loss 0.15641 dice_loss 0.06920 +Epoch [1790/4000] Validation [4/4] Loss: 0.31006 focal_loss 0.20569 dice_loss 0.10438 +Epoch [1790/4000] Validation metric {'Val/mean dice_metric': 0.9706411361694336, 'Val/mean miou_metric': 0.9527971148490906, 'Val/mean f1': 0.9723424315452576, 'Val/mean precision': 0.9690388441085815, 'Val/mean recall': 0.9756686687469482, 'Val/mean hd95_metric': 6.360487937927246} +Cheakpoint... +Epoch [1790/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706411361694336, 'Val/mean miou_metric': 0.9527971148490906, 'Val/mean f1': 0.9723424315452576, 'Val/mean precision': 0.9690388441085815, 'Val/mean recall': 0.9756686687469482, 'Val/mean hd95_metric': 6.360487937927246} +Epoch [1791/4000] Training [1/16] Loss: 0.00739 +Epoch [1791/4000] Training [2/16] Loss: 0.00698 +Epoch [1791/4000] Training [3/16] Loss: 0.00699 +Epoch [1791/4000] Training [4/16] Loss: 0.00563 +Epoch [1791/4000] Training [5/16] Loss: 0.00830 +Epoch [1791/4000] Training [6/16] Loss: 0.00641 +Epoch [1791/4000] Training [7/16] Loss: 0.00734 +Epoch [1791/4000] Training [8/16] Loss: 0.00730 +Epoch [1791/4000] Training [9/16] Loss: 0.00692 +Epoch [1791/4000] Training [10/16] Loss: 0.00575 +Epoch [1791/4000] Training [11/16] Loss: 0.00661 +Epoch [1791/4000] Training [12/16] Loss: 0.00851 +Epoch [1791/4000] Training [13/16] Loss: 0.00601 +Epoch [1791/4000] Training [14/16] Loss: 0.00754 +Epoch [1791/4000] Training [15/16] Loss: 0.00786 +Epoch [1791/4000] Training [16/16] Loss: 0.01442 +Epoch [1791/4000] Training metric {'Train/mean dice_metric': 0.9952629804611206, 'Train/mean miou_metric': 0.9902826547622681, 'Train/mean f1': 0.9900661706924438, 'Train/mean precision': 0.9847912788391113, 'Train/mean recall': 0.9953978061676025, 'Train/mean hd95_metric': 1.0937402248382568} +Epoch [1791/4000] Validation [1/4] Loss: 0.38115 focal_loss 0.29311 dice_loss 0.08804 +Epoch [1791/4000] Validation [2/4] Loss: 0.28200 focal_loss 0.16365 dice_loss 0.11835 +Epoch [1791/4000] Validation [3/4] Loss: 0.19094 focal_loss 0.12031 dice_loss 0.07063 +Epoch [1791/4000] Validation [4/4] Loss: 0.29396 focal_loss 0.17760 dice_loss 0.11636 +Epoch [1791/4000] Validation metric {'Val/mean dice_metric': 0.9720891714096069, 'Val/mean miou_metric': 0.9538202285766602, 'Val/mean f1': 0.9715381264686584, 'Val/mean precision': 0.9684543013572693, 'Val/mean recall': 0.974641740322113, 'Val/mean hd95_metric': 6.653881072998047} +Cheakpoint... +Epoch [1791/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720891714096069, 'Val/mean miou_metric': 0.9538202285766602, 'Val/mean f1': 0.9715381264686584, 'Val/mean precision': 0.9684543013572693, 'Val/mean recall': 0.974641740322113, 'Val/mean hd95_metric': 6.653881072998047} +Epoch [1792/4000] Training [1/16] Loss: 0.00656 +Epoch [1792/4000] Training [2/16] Loss: 0.00689 +Epoch [1792/4000] Training [3/16] Loss: 0.00750 +Epoch [1792/4000] Training [4/16] Loss: 0.00576 +Epoch [1792/4000] Training [5/16] Loss: 0.00537 +Epoch [1792/4000] Training [6/16] Loss: 0.00928 +Epoch [1792/4000] Training [7/16] Loss: 0.00628 +Epoch [1792/4000] Training [8/16] Loss: 0.00746 +Epoch [1792/4000] Training [9/16] Loss: 0.00645 +Epoch [1792/4000] Training [10/16] Loss: 0.00627 +Epoch [1792/4000] Training [11/16] Loss: 0.00759 +Epoch [1792/4000] Training [12/16] Loss: 0.00660 +Epoch [1792/4000] Training [13/16] Loss: 0.00666 +Epoch [1792/4000] Training [14/16] Loss: 0.00552 +Epoch [1792/4000] Training [15/16] Loss: 0.00612 +Epoch [1792/4000] Training [16/16] Loss: 0.00813 +Epoch [1792/4000] Training metric {'Train/mean dice_metric': 0.9956459403038025, 'Train/mean miou_metric': 0.9910709857940674, 'Train/mean f1': 0.9912375807762146, 'Train/mean precision': 0.9867425560951233, 'Train/mean recall': 0.9957737922668457, 'Train/mean hd95_metric': 1.2859857082366943} +Epoch [1792/4000] Validation [1/4] Loss: 0.91100 focal_loss 0.78758 dice_loss 0.12342 +Epoch [1792/4000] Validation [2/4] Loss: 0.38263 focal_loss 0.21875 dice_loss 0.16388 +Epoch [1792/4000] Validation [3/4] Loss: 0.18746 focal_loss 0.12422 dice_loss 0.06323 +Epoch [1792/4000] Validation [4/4] Loss: 0.30774 focal_loss 0.18313 dice_loss 0.12461 +Epoch [1792/4000] Validation metric {'Val/mean dice_metric': 0.9702246785163879, 'Val/mean miou_metric': 0.9525457620620728, 'Val/mean f1': 0.9700237512588501, 'Val/mean precision': 0.9703313112258911, 'Val/mean recall': 0.9697164297103882, 'Val/mean hd95_metric': 6.245998382568359} +Cheakpoint... +Epoch [1792/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702246785163879, 'Val/mean miou_metric': 0.9525457620620728, 'Val/mean f1': 0.9700237512588501, 'Val/mean precision': 0.9703313112258911, 'Val/mean recall': 0.9697164297103882, 'Val/mean hd95_metric': 6.245998382568359} +Epoch [1793/4000] Training [1/16] Loss: 0.00945 +Epoch [1793/4000] Training [2/16] Loss: 0.00636 +Epoch [1793/4000] Training [3/16] Loss: 0.00568 +Epoch [1793/4000] Training [4/16] Loss: 0.00514 +Epoch [1793/4000] Training [5/16] Loss: 0.00593 +Epoch [1793/4000] Training [6/16] Loss: 0.00673 +Epoch [1793/4000] Training [7/16] Loss: 0.01633 +Epoch [1793/4000] Training [8/16] Loss: 0.00567 +Epoch [1793/4000] Training [9/16] Loss: 0.00677 +Epoch [1793/4000] Training [10/16] Loss: 0.00902 +Epoch [1793/4000] Training [11/16] Loss: 0.00736 +Epoch [1793/4000] Training [12/16] Loss: 0.00677 +Epoch [1793/4000] Training [13/16] Loss: 0.00856 +Epoch [1793/4000] Training [14/16] Loss: 0.00627 +Epoch [1793/4000] Training [15/16] Loss: 0.00849 +Epoch [1793/4000] Training [16/16] Loss: 0.00567 +Epoch [1793/4000] Training metric {'Train/mean dice_metric': 0.9954192638397217, 'Train/mean miou_metric': 0.9906320571899414, 'Train/mean f1': 0.9912404417991638, 'Train/mean precision': 0.9866794943809509, 'Train/mean recall': 0.9958437085151672, 'Train/mean hd95_metric': 1.03621506690979} +Epoch [1793/4000] Validation [1/4] Loss: 0.88703 focal_loss 0.76190 dice_loss 0.12513 +Epoch [1793/4000] Validation [2/4] Loss: 0.20433 focal_loss 0.10452 dice_loss 0.09980 +Epoch [1793/4000] Validation [3/4] Loss: 0.17665 focal_loss 0.11805 dice_loss 0.05860 +Epoch [1793/4000] Validation [4/4] Loss: 0.25007 focal_loss 0.15494 dice_loss 0.09512 +Epoch [1793/4000] Validation metric {'Val/mean dice_metric': 0.9711828231811523, 'Val/mean miou_metric': 0.9541996121406555, 'Val/mean f1': 0.9715005159378052, 'Val/mean precision': 0.973676860332489, 'Val/mean recall': 0.969334065914154, 'Val/mean hd95_metric': 5.417996406555176} +Cheakpoint... +Epoch [1793/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711828231811523, 'Val/mean miou_metric': 0.9541996121406555, 'Val/mean f1': 0.9715005159378052, 'Val/mean precision': 0.973676860332489, 'Val/mean recall': 0.969334065914154, 'Val/mean hd95_metric': 5.417996406555176} +Epoch [1794/4000] Training [1/16] Loss: 0.00735 +Epoch [1794/4000] Training [2/16] Loss: 0.00777 +Epoch [1794/4000] Training [3/16] Loss: 0.00758 +Epoch [1794/4000] Training [4/16] Loss: 0.00476 +Epoch [1794/4000] Training [5/16] Loss: 0.00544 +Epoch [1794/4000] Training [6/16] Loss: 0.00620 +Epoch [1794/4000] Training [7/16] Loss: 0.00589 +Epoch [1794/4000] Training [8/16] Loss: 0.00892 +Epoch [1794/4000] Training [9/16] Loss: 0.00658 +Epoch [1794/4000] Training [10/16] Loss: 0.00644 +Epoch [1794/4000] Training [11/16] Loss: 0.00544 +Epoch [1794/4000] Training [12/16] Loss: 0.00793 +Epoch [1794/4000] Training [13/16] Loss: 0.00548 +Epoch [1794/4000] Training [14/16] Loss: 0.00803 +Epoch [1794/4000] Training [15/16] Loss: 0.00798 +Epoch [1794/4000] Training [16/16] Loss: 0.00655 +Epoch [1794/4000] Training metric {'Train/mean dice_metric': 0.9954763650894165, 'Train/mean miou_metric': 0.9907439947128296, 'Train/mean f1': 0.9911734461784363, 'Train/mean precision': 0.9866504073143005, 'Train/mean recall': 0.9957380294799805, 'Train/mean hd95_metric': 1.023842215538025} +Epoch [1794/4000] Validation [1/4] Loss: 0.76086 focal_loss 0.64535 dice_loss 0.11552 +Epoch [1794/4000] Validation [2/4] Loss: 0.40761 focal_loss 0.25968 dice_loss 0.14793 +Epoch [1794/4000] Validation [3/4] Loss: 0.17226 focal_loss 0.11421 dice_loss 0.05805 +Epoch [1794/4000] Validation [4/4] Loss: 0.50525 focal_loss 0.35534 dice_loss 0.14991 +Epoch [1794/4000] Validation metric {'Val/mean dice_metric': 0.9708564877510071, 'Val/mean miou_metric': 0.9531930685043335, 'Val/mean f1': 0.9704470038414001, 'Val/mean precision': 0.971476674079895, 'Val/mean recall': 0.9694196581840515, 'Val/mean hd95_metric': 5.6178483963012695} +Cheakpoint... +Epoch [1794/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708564877510071, 'Val/mean miou_metric': 0.9531930685043335, 'Val/mean f1': 0.9704470038414001, 'Val/mean precision': 0.971476674079895, 'Val/mean recall': 0.9694196581840515, 'Val/mean hd95_metric': 5.6178483963012695} +Epoch [1795/4000] Training [1/16] Loss: 0.00798 +Epoch [1795/4000] Training [2/16] Loss: 0.00657 +Epoch [1795/4000] Training [3/16] Loss: 0.00987 +Epoch [1795/4000] Training [4/16] Loss: 0.00660 +Epoch [1795/4000] Training [5/16] Loss: 0.00515 +Epoch [1795/4000] Training [6/16] Loss: 0.00533 +Epoch [1795/4000] Training [7/16] Loss: 0.00546 +Epoch [1795/4000] Training [8/16] Loss: 0.00596 +Epoch [1795/4000] Training [9/16] Loss: 0.00595 +Epoch [1795/4000] Training [10/16] Loss: 0.00628 +Epoch [1795/4000] Training [11/16] Loss: 0.00519 +Epoch [1795/4000] Training [12/16] Loss: 0.00533 +Epoch [1795/4000] Training [13/16] Loss: 0.00649 +Epoch [1795/4000] Training [14/16] Loss: 0.00525 +Epoch [1795/4000] Training [15/16] Loss: 0.00550 +Epoch [1795/4000] Training [16/16] Loss: 0.00581 +Epoch [1795/4000] Training metric {'Train/mean dice_metric': 0.9960511922836304, 'Train/mean miou_metric': 0.9918270111083984, 'Train/mean f1': 0.9907443523406982, 'Train/mean precision': 0.9854192733764648, 'Train/mean recall': 0.9961272478103638, 'Train/mean hd95_metric': 1.0153048038482666} +Epoch [1795/4000] Validation [1/4] Loss: 0.73494 focal_loss 0.62155 dice_loss 0.11339 +Epoch [1795/4000] Validation [2/4] Loss: 0.23663 focal_loss 0.13201 dice_loss 0.10462 +Epoch [1795/4000] Validation [3/4] Loss: 0.16732 focal_loss 0.10464 dice_loss 0.06268 +Epoch [1795/4000] Validation [4/4] Loss: 0.27963 focal_loss 0.17044 dice_loss 0.10919 +Epoch [1795/4000] Validation metric {'Val/mean dice_metric': 0.9709653854370117, 'Val/mean miou_metric': 0.9536652565002441, 'Val/mean f1': 0.971017599105835, 'Val/mean precision': 0.9702787399291992, 'Val/mean recall': 0.9717575907707214, 'Val/mean hd95_metric': 5.819972038269043} +Cheakpoint... +Epoch [1795/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709653854370117, 'Val/mean miou_metric': 0.9536652565002441, 'Val/mean f1': 0.971017599105835, 'Val/mean precision': 0.9702787399291992, 'Val/mean recall': 0.9717575907707214, 'Val/mean hd95_metric': 5.819972038269043} +Epoch [1796/4000] Training [1/16] Loss: 0.00538 +Epoch [1796/4000] Training [2/16] Loss: 0.00584 +Epoch [1796/4000] Training [3/16] Loss: 0.00588 +Epoch [1796/4000] Training [4/16] Loss: 0.00604 +Epoch [1796/4000] Training [5/16] Loss: 0.00471 +Epoch [1796/4000] Training [6/16] Loss: 0.00491 +Epoch [1796/4000] Training [7/16] Loss: 0.00728 +Epoch [1796/4000] Training [8/16] Loss: 0.00565 +Epoch [1796/4000] Training [9/16] Loss: 0.00657 +Epoch [1796/4000] Training [10/16] Loss: 0.00529 +Epoch [1796/4000] Training [11/16] Loss: 0.00612 +Epoch [1796/4000] Training [12/16] Loss: 0.00495 +Epoch [1796/4000] Training [13/16] Loss: 0.00674 +Epoch [1796/4000] Training [14/16] Loss: 0.00752 +Epoch [1796/4000] Training [15/16] Loss: 0.00537 +Epoch [1796/4000] Training [16/16] Loss: 0.00556 +Epoch [1796/4000] Training metric {'Train/mean dice_metric': 0.9960533976554871, 'Train/mean miou_metric': 0.9918703436851501, 'Train/mean f1': 0.9917713403701782, 'Train/mean precision': 0.9872415065765381, 'Train/mean recall': 0.9963429570198059, 'Train/mean hd95_metric': 1.0205469131469727} +Epoch [1796/4000] Validation [1/4] Loss: 0.60366 focal_loss 0.49323 dice_loss 0.11043 +Epoch [1796/4000] Validation [2/4] Loss: 0.25506 focal_loss 0.14558 dice_loss 0.10948 +Epoch [1796/4000] Validation [3/4] Loss: 0.20462 focal_loss 0.13688 dice_loss 0.06774 +Epoch [1796/4000] Validation [4/4] Loss: 0.31859 focal_loss 0.19652 dice_loss 0.12207 +Epoch [1796/4000] Validation metric {'Val/mean dice_metric': 0.9718185663223267, 'Val/mean miou_metric': 0.9542443156242371, 'Val/mean f1': 0.9725783467292786, 'Val/mean precision': 0.9745091199874878, 'Val/mean recall': 0.9706552028656006, 'Val/mean hd95_metric': 5.71908712387085} +Cheakpoint... +Epoch [1796/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718185663223267, 'Val/mean miou_metric': 0.9542443156242371, 'Val/mean f1': 0.9725783467292786, 'Val/mean precision': 0.9745091199874878, 'Val/mean recall': 0.9706552028656006, 'Val/mean hd95_metric': 5.71908712387085} +Epoch [1797/4000] Training [1/16] Loss: 0.00606 +Epoch [1797/4000] Training [2/16] Loss: 0.00722 +Epoch [1797/4000] Training [3/16] Loss: 0.00662 +Epoch [1797/4000] Training [4/16] Loss: 0.00652 +Epoch [1797/4000] Training [5/16] Loss: 0.00408 +Epoch [1797/4000] Training [6/16] Loss: 0.00652 +Epoch [1797/4000] Training [7/16] Loss: 0.00609 +Epoch [1797/4000] Training [8/16] Loss: 0.00455 +Epoch [1797/4000] Training [9/16] Loss: 0.00494 +Epoch [1797/4000] Training [10/16] Loss: 0.00665 +Epoch [1797/4000] Training [11/16] Loss: 0.00501 +Epoch [1797/4000] Training [12/16] Loss: 0.00543 +Epoch [1797/4000] Training [13/16] Loss: 0.00639 +Epoch [1797/4000] Training [14/16] Loss: 0.00654 +Epoch [1797/4000] Training [15/16] Loss: 0.00567 +Epoch [1797/4000] Training [16/16] Loss: 0.00788 +Epoch [1797/4000] Training metric {'Train/mean dice_metric': 0.9953181743621826, 'Train/mean miou_metric': 0.9906487464904785, 'Train/mean f1': 0.9910063147544861, 'Train/mean precision': 0.9869804382324219, 'Train/mean recall': 0.9950651526451111, 'Train/mean hd95_metric': 1.1528844833374023} +Epoch [1797/4000] Validation [1/4] Loss: 0.28734 focal_loss 0.21748 dice_loss 0.06985 +Epoch [1797/4000] Validation [2/4] Loss: 0.25578 focal_loss 0.14506 dice_loss 0.11072 +Epoch [1797/4000] Validation [3/4] Loss: 0.21279 focal_loss 0.14741 dice_loss 0.06538 +Epoch [1797/4000] Validation [4/4] Loss: 0.24197 focal_loss 0.15257 dice_loss 0.08940 +Epoch [1797/4000] Validation metric {'Val/mean dice_metric': 0.9744645357131958, 'Val/mean miou_metric': 0.9576597213745117, 'Val/mean f1': 0.9749496579170227, 'Val/mean precision': 0.9724698662757874, 'Val/mean recall': 0.9774420857429504, 'Val/mean hd95_metric': 5.23654317855835} +Cheakpoint... +Epoch [1797/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744645357131958, 'Val/mean miou_metric': 0.9576597213745117, 'Val/mean f1': 0.9749496579170227, 'Val/mean precision': 0.9724698662757874, 'Val/mean recall': 0.9774420857429504, 'Val/mean hd95_metric': 5.23654317855835} +Epoch [1798/4000] Training [1/16] Loss: 0.00615 +Epoch [1798/4000] Training [2/16] Loss: 0.00756 +Epoch [1798/4000] Training [3/16] Loss: 0.00545 +Epoch [1798/4000] Training [4/16] Loss: 0.00675 +Epoch [1798/4000] Training [5/16] Loss: 0.00619 +Epoch [1798/4000] Training [6/16] Loss: 0.00720 +Epoch [1798/4000] Training [7/16] Loss: 0.00692 +Epoch [1798/4000] Training [8/16] Loss: 0.00707 +Epoch [1798/4000] Training [9/16] Loss: 0.00537 +Epoch [1798/4000] Training [10/16] Loss: 0.00854 +Epoch [1798/4000] Training [11/16] Loss: 0.00613 +Epoch [1798/4000] Training [12/16] Loss: 0.00721 +Epoch [1798/4000] Training [13/16] Loss: 0.01049 +Epoch [1798/4000] Training [14/16] Loss: 0.00571 +Epoch [1798/4000] Training [15/16] Loss: 0.00706 +Epoch [1798/4000] Training [16/16] Loss: 0.00555 +Epoch [1798/4000] Training metric {'Train/mean dice_metric': 0.9951303005218506, 'Train/mean miou_metric': 0.9901190996170044, 'Train/mean f1': 0.9907059073448181, 'Train/mean precision': 0.985659658908844, 'Train/mean recall': 0.9958041310310364, 'Train/mean hd95_metric': 1.8820569515228271} +Epoch [1798/4000] Validation [1/4] Loss: 0.22631 focal_loss 0.16267 dice_loss 0.06363 +Epoch [1798/4000] Validation [2/4] Loss: 0.49440 focal_loss 0.33209 dice_loss 0.16231 +Epoch [1798/4000] Validation [3/4] Loss: 0.17776 focal_loss 0.12088 dice_loss 0.05688 +Epoch [1798/4000] Validation [4/4] Loss: 0.33950 focal_loss 0.21198 dice_loss 0.12752 +Epoch [1798/4000] Validation metric {'Val/mean dice_metric': 0.9708735346794128, 'Val/mean miou_metric': 0.9530696868896484, 'Val/mean f1': 0.9724951386451721, 'Val/mean precision': 0.9681692123413086, 'Val/mean recall': 0.9768598675727844, 'Val/mean hd95_metric': 7.142469882965088} +Cheakpoint... +Epoch [1798/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708735346794128, 'Val/mean miou_metric': 0.9530696868896484, 'Val/mean f1': 0.9724951386451721, 'Val/mean precision': 0.9681692123413086, 'Val/mean recall': 0.9768598675727844, 'Val/mean hd95_metric': 7.142469882965088} +Epoch [1799/4000] Training [1/16] Loss: 0.00651 +Epoch [1799/4000] Training [2/16] Loss: 0.00624 +Epoch [1799/4000] Training [3/16] Loss: 0.00763 +Epoch [1799/4000] Training [4/16] Loss: 0.00735 +Epoch [1799/4000] Training [5/16] Loss: 0.00727 +Epoch [1799/4000] Training [6/16] Loss: 0.00673 +Epoch [1799/4000] Training [7/16] Loss: 0.00692 +Epoch [1799/4000] Training [8/16] Loss: 0.00798 +Epoch [1799/4000] Training [9/16] Loss: 0.00871 +Epoch [1799/4000] Training [10/16] Loss: 0.00817 +Epoch [1799/4000] Training [11/16] Loss: 0.00671 +Epoch [1799/4000] Training [12/16] Loss: 0.00748 +Epoch [1799/4000] Training [13/16] Loss: 0.00872 +Epoch [1799/4000] Training [14/16] Loss: 0.00854 +Epoch [1799/4000] Training [15/16] Loss: 0.00854 +Epoch [1799/4000] Training [16/16] Loss: 0.00850 +Epoch [1799/4000] Training metric {'Train/mean dice_metric': 0.994758665561676, 'Train/mean miou_metric': 0.9893505573272705, 'Train/mean f1': 0.9899594783782959, 'Train/mean precision': 0.9859448671340942, 'Train/mean recall': 0.9940069317817688, 'Train/mean hd95_metric': 1.3055323362350464} +Epoch [1799/4000] Validation [1/4] Loss: 0.19619 focal_loss 0.14034 dice_loss 0.05585 +Epoch [1799/4000] Validation [2/4] Loss: 0.36729 focal_loss 0.21734 dice_loss 0.14995 +Epoch [1799/4000] Validation [3/4] Loss: 0.21432 focal_loss 0.13774 dice_loss 0.07658 +Epoch [1799/4000] Validation [4/4] Loss: 0.36672 focal_loss 0.21914 dice_loss 0.14758 +Epoch [1799/4000] Validation metric {'Val/mean dice_metric': 0.968026340007782, 'Val/mean miou_metric': 0.9502477645874023, 'Val/mean f1': 0.970181941986084, 'Val/mean precision': 0.9636396169662476, 'Val/mean recall': 0.9768136739730835, 'Val/mean hd95_metric': 7.248734951019287} +Cheakpoint... +Epoch [1799/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968026340007782, 'Val/mean miou_metric': 0.9502477645874023, 'Val/mean f1': 0.970181941986084, 'Val/mean precision': 0.9636396169662476, 'Val/mean recall': 0.9768136739730835, 'Val/mean hd95_metric': 7.248734951019287} +Epoch [1800/4000] Training [1/16] Loss: 0.00780 +Epoch [1800/4000] Training [2/16] Loss: 0.00653 +Epoch [1800/4000] Training [3/16] Loss: 0.00840 +Epoch [1800/4000] Training [4/16] Loss: 0.02291 +Epoch [1800/4000] Training [5/16] Loss: 0.00607 +Epoch [1800/4000] Training [6/16] Loss: 0.00856 +Epoch [1800/4000] Training [7/16] Loss: 0.00898 +Epoch [1800/4000] Training [8/16] Loss: 0.00873 +Epoch [1800/4000] Training [9/16] Loss: 0.00785 +Epoch [1800/4000] Training [10/16] Loss: 0.00776 +Epoch [1800/4000] Training [11/16] Loss: 0.00611 +Epoch [1800/4000] Training [12/16] Loss: 0.00597 +Epoch [1800/4000] Training [13/16] Loss: 0.00575 +Epoch [1800/4000] Training [14/16] Loss: 0.00524 +Epoch [1800/4000] Training [15/16] Loss: 0.00795 +Epoch [1800/4000] Training [16/16] Loss: 0.00712 +Epoch [1800/4000] Training metric {'Train/mean dice_metric': 0.9942435026168823, 'Train/mean miou_metric': 0.9884220361709595, 'Train/mean f1': 0.9895448088645935, 'Train/mean precision': 0.984167218208313, 'Train/mean recall': 0.9949813485145569, 'Train/mean hd95_metric': 1.322495937347412} +Epoch [1800/4000] Validation [1/4] Loss: 0.80044 focal_loss 0.58845 dice_loss 0.21199 +Epoch [1800/4000] Validation [2/4] Loss: 0.50450 focal_loss 0.31172 dice_loss 0.19278 +Epoch [1800/4000] Validation [3/4] Loss: 0.24785 focal_loss 0.16052 dice_loss 0.08733 +Epoch [1800/4000] Validation [4/4] Loss: 0.60575 focal_loss 0.42127 dice_loss 0.18447 +Epoch [1800/4000] Validation metric {'Val/mean dice_metric': 0.9657529592514038, 'Val/mean miou_metric': 0.9466546773910522, 'Val/mean f1': 0.9657031893730164, 'Val/mean precision': 0.9690082669258118, 'Val/mean recall': 0.9624205827713013, 'Val/mean hd95_metric': 7.195765495300293} +Cheakpoint... +Epoch [1800/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9658], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9657529592514038, 'Val/mean miou_metric': 0.9466546773910522, 'Val/mean f1': 0.9657031893730164, 'Val/mean precision': 0.9690082669258118, 'Val/mean recall': 0.9624205827713013, 'Val/mean hd95_metric': 7.195765495300293} +Epoch [1801/4000] Training [1/16] Loss: 0.00689 +Epoch [1801/4000] Training [2/16] Loss: 0.13908 +Epoch [1801/4000] Training [3/16] Loss: 0.00592 +Epoch [1801/4000] Training [4/16] Loss: 0.00713 +Epoch [1801/4000] Training [5/16] Loss: 0.00716 +Epoch [1801/4000] Training [6/16] Loss: 0.00791 +Epoch [1801/4000] Training [7/16] Loss: 0.00939 +Epoch [1801/4000] Training [8/16] Loss: 0.01104 +Epoch [1801/4000] Training [9/16] Loss: 0.00905 +Epoch [1801/4000] Training [10/16] Loss: 0.00933 +Epoch [1801/4000] Training [11/16] Loss: 0.00681 +Epoch [1801/4000] Training [12/16] Loss: 0.00810 +Epoch [1801/4000] Training [13/16] Loss: 0.00853 +Epoch [1801/4000] Training [14/16] Loss: 0.01049 +Epoch [1801/4000] Training [15/16] Loss: 0.00926 +Epoch [1801/4000] Training [16/16] Loss: 0.00533 +Epoch [1801/4000] Training metric {'Train/mean dice_metric': 0.9936659336090088, 'Train/mean miou_metric': 0.9874459505081177, 'Train/mean f1': 0.9890016317367554, 'Train/mean precision': 0.9852176308631897, 'Train/mean recall': 0.9928147792816162, 'Train/mean hd95_metric': 2.214139938354492} +Epoch [1801/4000] Validation [1/4] Loss: 0.46733 focal_loss 0.36062 dice_loss 0.10671 +Epoch [1801/4000] Validation [2/4] Loss: 0.21851 focal_loss 0.10827 dice_loss 0.11024 +Epoch [1801/4000] Validation [3/4] Loss: 0.20196 focal_loss 0.13090 dice_loss 0.07106 +Epoch [1801/4000] Validation [4/4] Loss: 0.58857 focal_loss 0.39835 dice_loss 0.19022 +Epoch [1801/4000] Validation metric {'Val/mean dice_metric': 0.965397834777832, 'Val/mean miou_metric': 0.9461233019828796, 'Val/mean f1': 0.9605859518051147, 'Val/mean precision': 0.9471926093101501, 'Val/mean recall': 0.9743636250495911, 'Val/mean hd95_metric': 9.757925987243652} +Cheakpoint... +Epoch [1801/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9654], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.965397834777832, 'Val/mean miou_metric': 0.9461233019828796, 'Val/mean f1': 0.9605859518051147, 'Val/mean precision': 0.9471926093101501, 'Val/mean recall': 0.9743636250495911, 'Val/mean hd95_metric': 9.757925987243652} +Epoch [1802/4000] Training [1/16] Loss: 0.03069 +Epoch [1802/4000] Training [2/16] Loss: 0.00828 +Epoch [1802/4000] Training [3/16] Loss: 0.00724 +Epoch [1802/4000] Training [4/16] Loss: 0.00682 +Epoch [1802/4000] Training [5/16] Loss: 0.00747 +Epoch [1802/4000] Training [6/16] Loss: 0.00802 +Epoch [1802/4000] Training [7/16] Loss: 0.00797 +Epoch [1802/4000] Training [8/16] Loss: 0.00649 +Epoch [1802/4000] Training [9/16] Loss: 0.00743 +Epoch [1802/4000] Training [10/16] Loss: 0.00753 +Epoch [1802/4000] Training [11/16] Loss: 0.00678 +Epoch [1802/4000] Training [12/16] Loss: 0.00719 +Epoch [1802/4000] Training [13/16] Loss: 0.00779 +Epoch [1802/4000] Training [14/16] Loss: 0.02060 +Epoch [1802/4000] Training [15/16] Loss: 0.00764 +Epoch [1802/4000] Training [16/16] Loss: 0.01121 +Epoch [1802/4000] Training metric {'Train/mean dice_metric': 0.9928551316261292, 'Train/mean miou_metric': 0.9867235422134399, 'Train/mean f1': 0.9888586401939392, 'Train/mean precision': 0.9849594831466675, 'Train/mean recall': 0.9927887916564941, 'Train/mean hd95_metric': 1.3978761434555054} +Epoch [1802/4000] Validation [1/4] Loss: 0.66012 focal_loss 0.54614 dice_loss 0.11398 +Epoch [1802/4000] Validation [2/4] Loss: 0.21053 focal_loss 0.11293 dice_loss 0.09760 +Epoch [1802/4000] Validation [3/4] Loss: 0.30033 focal_loss 0.21816 dice_loss 0.08218 +Epoch [1802/4000] Validation [4/4] Loss: 0.43400 focal_loss 0.28055 dice_loss 0.15345 +Epoch [1802/4000] Validation metric {'Val/mean dice_metric': 0.9664648175239563, 'Val/mean miou_metric': 0.9471477270126343, 'Val/mean f1': 0.9659811854362488, 'Val/mean precision': 0.9644555449485779, 'Val/mean recall': 0.9675115942955017, 'Val/mean hd95_metric': 7.62912654876709} +Cheakpoint... +Epoch [1802/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9665], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9664648175239563, 'Val/mean miou_metric': 0.9471477270126343, 'Val/mean f1': 0.9659811854362488, 'Val/mean precision': 0.9644555449485779, 'Val/mean recall': 0.9675115942955017, 'Val/mean hd95_metric': 7.62912654876709} +Epoch [1803/4000] Training [1/16] Loss: 0.00863 +Epoch [1803/4000] Training [2/16] Loss: 0.00683 +Epoch [1803/4000] Training [3/16] Loss: 0.00813 +Epoch [1803/4000] Training [4/16] Loss: 0.00904 +Epoch [1803/4000] Training [5/16] Loss: 0.00863 +Epoch [1803/4000] Training [6/16] Loss: 0.01078 +Epoch [1803/4000] Training [7/16] Loss: 0.00743 +Epoch [1803/4000] Training [8/16] Loss: 0.01111 +Epoch [1803/4000] Training [9/16] Loss: 0.01062 +Epoch [1803/4000] Training [10/16] Loss: 0.00952 +Epoch [1803/4000] Training [11/16] Loss: 0.00761 +Epoch [1803/4000] Training [12/16] Loss: 0.00923 +Epoch [1803/4000] Training [13/16] Loss: 0.01038 +Epoch [1803/4000] Training [14/16] Loss: 0.00639 +Epoch [1803/4000] Training [15/16] Loss: 0.01283 +Epoch [1803/4000] Training [16/16] Loss: 0.01023 +Epoch [1803/4000] Training metric {'Train/mean dice_metric': 0.9935526847839355, 'Train/mean miou_metric': 0.9870681762695312, 'Train/mean f1': 0.989430844783783, 'Train/mean precision': 0.9845091700553894, 'Train/mean recall': 0.9944019913673401, 'Train/mean hd95_metric': 2.23087739944458} +Epoch [1803/4000] Validation [1/4] Loss: 0.25971 focal_loss 0.18614 dice_loss 0.07357 +Epoch [1803/4000] Validation [2/4] Loss: 0.19475 focal_loss 0.09557 dice_loss 0.09918 +Epoch [1803/4000] Validation [3/4] Loss: 0.18693 focal_loss 0.11571 dice_loss 0.07121 +Epoch [1803/4000] Validation [4/4] Loss: 0.37752 focal_loss 0.24036 dice_loss 0.13717 +Epoch [1803/4000] Validation metric {'Val/mean dice_metric': 0.9679729342460632, 'Val/mean miou_metric': 0.948760986328125, 'Val/mean f1': 0.9670454859733582, 'Val/mean precision': 0.9581902623176575, 'Val/mean recall': 0.976065993309021, 'Val/mean hd95_metric': 8.333478927612305} +Cheakpoint... +Epoch [1803/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679729342460632, 'Val/mean miou_metric': 0.948760986328125, 'Val/mean f1': 0.9670454859733582, 'Val/mean precision': 0.9581902623176575, 'Val/mean recall': 0.976065993309021, 'Val/mean hd95_metric': 8.333478927612305} +Epoch [1804/4000] Training [1/16] Loss: 0.00912 +Epoch [1804/4000] Training [2/16] Loss: 0.00578 +Epoch [1804/4000] Training [3/16] Loss: 0.00612 +Epoch [1804/4000] Training [4/16] Loss: 0.00810 +Epoch [1804/4000] Training [5/16] Loss: 0.01089 +Epoch [1804/4000] Training [6/16] Loss: 0.00669 +Epoch [1804/4000] Training [7/16] Loss: 0.00572 +Epoch [1804/4000] Training [8/16] Loss: 0.00901 +Epoch [1804/4000] Training [9/16] Loss: 0.00914 +Epoch [1804/4000] Training [10/16] Loss: 0.01313 +Epoch [1804/4000] Training [11/16] Loss: 0.00790 +Epoch [1804/4000] Training [12/16] Loss: 0.00606 +Epoch [1804/4000] Training [13/16] Loss: 0.00779 +Epoch [1804/4000] Training [14/16] Loss: 0.00762 +Epoch [1804/4000] Training [15/16] Loss: 0.01001 +Epoch [1804/4000] Training [16/16] Loss: 0.01192 +Epoch [1804/4000] Training metric {'Train/mean dice_metric': 0.9944225549697876, 'Train/mean miou_metric': 0.9886536598205566, 'Train/mean f1': 0.9899645447731018, 'Train/mean precision': 0.985221803188324, 'Train/mean recall': 0.9947531819343567, 'Train/mean hd95_metric': 1.298583745956421} +Epoch [1804/4000] Validation [1/4] Loss: 0.21353 focal_loss 0.14156 dice_loss 0.07197 +Epoch [1804/4000] Validation [2/4] Loss: 0.20494 focal_loss 0.09841 dice_loss 0.10653 +Epoch [1804/4000] Validation [3/4] Loss: 0.19756 focal_loss 0.12629 dice_loss 0.07126 +Epoch [1804/4000] Validation [4/4] Loss: 0.55300 focal_loss 0.37223 dice_loss 0.18077 +Epoch [1804/4000] Validation metric {'Val/mean dice_metric': 0.9689041972160339, 'Val/mean miou_metric': 0.9498242139816284, 'Val/mean f1': 0.9694127440452576, 'Val/mean precision': 0.9629431366920471, 'Val/mean recall': 0.9759699106216431, 'Val/mean hd95_metric': 6.58223819732666} +Cheakpoint... +Epoch [1804/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689041972160339, 'Val/mean miou_metric': 0.9498242139816284, 'Val/mean f1': 0.9694127440452576, 'Val/mean precision': 0.9629431366920471, 'Val/mean recall': 0.9759699106216431, 'Val/mean hd95_metric': 6.58223819732666} +Epoch [1805/4000] Training [1/16] Loss: 0.01196 +Epoch [1805/4000] Training [2/16] Loss: 0.01071 +Epoch [1805/4000] Training [3/16] Loss: 0.00709 +Epoch [1805/4000] Training [4/16] Loss: 0.00829 +Epoch [1805/4000] Training [5/16] Loss: 0.00981 +Epoch [1805/4000] Training [6/16] Loss: 0.01597 +Epoch [1805/4000] Training [7/16] Loss: 0.00860 +Epoch [1805/4000] Training [8/16] Loss: 0.00633 +Epoch [1805/4000] Training [9/16] Loss: 0.00605 +Epoch [1805/4000] Training [10/16] Loss: 0.00755 +Epoch [1805/4000] Training [11/16] Loss: 0.00662 +Epoch [1805/4000] Training [12/16] Loss: 0.00755 +Epoch [1805/4000] Training [13/16] Loss: 0.00831 +Epoch [1805/4000] Training [14/16] Loss: 0.00736 +Epoch [1805/4000] Training [15/16] Loss: 0.01298 +Epoch [1805/4000] Training [16/16] Loss: 0.00650 +Epoch [1805/4000] Training metric {'Train/mean dice_metric': 0.9940959215164185, 'Train/mean miou_metric': 0.988127589225769, 'Train/mean f1': 0.9899210929870605, 'Train/mean precision': 0.9853701591491699, 'Train/mean recall': 0.9945142269134521, 'Train/mean hd95_metric': 1.437183141708374} +Epoch [1805/4000] Validation [1/4] Loss: 0.41121 focal_loss 0.30926 dice_loss 0.10194 +Epoch [1805/4000] Validation [2/4] Loss: 0.20242 focal_loss 0.10841 dice_loss 0.09400 +Epoch [1805/4000] Validation [3/4] Loss: 0.15333 focal_loss 0.08871 dice_loss 0.06462 +Epoch [1805/4000] Validation [4/4] Loss: 0.62896 focal_loss 0.42794 dice_loss 0.20102 +Epoch [1805/4000] Validation metric {'Val/mean dice_metric': 0.9648640751838684, 'Val/mean miou_metric': 0.946179986000061, 'Val/mean f1': 0.9668815732002258, 'Val/mean precision': 0.9630367159843445, 'Val/mean recall': 0.9707574844360352, 'Val/mean hd95_metric': 7.356001853942871} +Cheakpoint... +Epoch [1805/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9649], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9648640751838684, 'Val/mean miou_metric': 0.946179986000061, 'Val/mean f1': 0.9668815732002258, 'Val/mean precision': 0.9630367159843445, 'Val/mean recall': 0.9707574844360352, 'Val/mean hd95_metric': 7.356001853942871} +Epoch [1806/4000] Training [1/16] Loss: 0.00641 +Epoch [1806/4000] Training [2/16] Loss: 0.00640 +Epoch [1806/4000] Training [3/16] Loss: 0.00790 +Epoch [1806/4000] Training [4/16] Loss: 0.00492 +Epoch [1806/4000] Training [5/16] Loss: 0.01300 +Epoch [1806/4000] Training [6/16] Loss: 0.00724 +Epoch [1806/4000] Training [7/16] Loss: 0.00561 +Epoch [1806/4000] Training [8/16] Loss: 0.00708 +Epoch [1806/4000] Training [9/16] Loss: 0.00788 +Epoch [1806/4000] Training [10/16] Loss: 0.00704 +Epoch [1806/4000] Training [11/16] Loss: 0.00729 +Epoch [1806/4000] Training [12/16] Loss: 0.00704 +Epoch [1806/4000] Training [13/16] Loss: 0.00613 +Epoch [1806/4000] Training [14/16] Loss: 0.00799 +Epoch [1806/4000] Training [15/16] Loss: 0.00950 +Epoch [1806/4000] Training [16/16] Loss: 0.00497 +Epoch [1806/4000] Training metric {'Train/mean dice_metric': 0.9954544305801392, 'Train/mean miou_metric': 0.9906907677650452, 'Train/mean f1': 0.9910890460014343, 'Train/mean precision': 0.9866521954536438, 'Train/mean recall': 0.9955659508705139, 'Train/mean hd95_metric': 1.1404101848602295} +Epoch [1806/4000] Validation [1/4] Loss: 0.38995 focal_loss 0.29548 dice_loss 0.09447 +Epoch [1806/4000] Validation [2/4] Loss: 0.30485 focal_loss 0.17203 dice_loss 0.13283 +Epoch [1806/4000] Validation [3/4] Loss: 0.16789 focal_loss 0.10284 dice_loss 0.06505 +Epoch [1806/4000] Validation [4/4] Loss: 0.52167 focal_loss 0.37084 dice_loss 0.15083 +Epoch [1806/4000] Validation metric {'Val/mean dice_metric': 0.9675811529159546, 'Val/mean miou_metric': 0.9505475163459778, 'Val/mean f1': 0.9702101349830627, 'Val/mean precision': 0.970281720161438, 'Val/mean recall': 0.9701386094093323, 'Val/mean hd95_metric': 6.220841884613037} +Cheakpoint... +Epoch [1806/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9676], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9675811529159546, 'Val/mean miou_metric': 0.9505475163459778, 'Val/mean f1': 0.9702101349830627, 'Val/mean precision': 0.970281720161438, 'Val/mean recall': 0.9701386094093323, 'Val/mean hd95_metric': 6.220841884613037} +Epoch [1807/4000] Training [1/16] Loss: 0.00642 +Epoch [1807/4000] Training [2/16] Loss: 0.00819 +Epoch [1807/4000] Training [3/16] Loss: 0.00686 +Epoch [1807/4000] Training [4/16] Loss: 0.00795 +Epoch [1807/4000] Training [5/16] Loss: 0.00719 +Epoch [1807/4000] Training [6/16] Loss: 0.00960 +Epoch [1807/4000] Training [7/16] Loss: 0.00998 +Epoch [1807/4000] Training [8/16] Loss: 0.00695 +Epoch [1807/4000] Training [9/16] Loss: 0.00951 +Epoch [1807/4000] Training [10/16] Loss: 0.00731 +Epoch [1807/4000] Training [11/16] Loss: 0.01029 +Epoch [1807/4000] Training [12/16] Loss: 0.02685 +Epoch [1807/4000] Training [13/16] Loss: 0.00730 +Epoch [1807/4000] Training [14/16] Loss: 0.00608 +Epoch [1807/4000] Training [15/16] Loss: 0.00717 +Epoch [1807/4000] Training [16/16] Loss: 0.00812 +Epoch [1807/4000] Training metric {'Train/mean dice_metric': 0.9948517084121704, 'Train/mean miou_metric': 0.98949134349823, 'Train/mean f1': 0.9903758764266968, 'Train/mean precision': 0.9856696128845215, 'Train/mean recall': 0.995127260684967, 'Train/mean hd95_metric': 1.0814472436904907} +Epoch [1807/4000] Validation [1/4] Loss: 0.37112 focal_loss 0.28785 dice_loss 0.08328 +Epoch [1807/4000] Validation [2/4] Loss: 0.49079 focal_loss 0.29635 dice_loss 0.19444 +Epoch [1807/4000] Validation [3/4] Loss: 0.22321 focal_loss 0.14179 dice_loss 0.08142 +Epoch [1807/4000] Validation [4/4] Loss: 0.47510 focal_loss 0.31966 dice_loss 0.15543 +Epoch [1807/4000] Validation metric {'Val/mean dice_metric': 0.9689987301826477, 'Val/mean miou_metric': 0.9514955282211304, 'Val/mean f1': 0.9701963067054749, 'Val/mean precision': 0.9662818312644958, 'Val/mean recall': 0.9741424918174744, 'Val/mean hd95_metric': 6.092692852020264} +Cheakpoint... +Epoch [1807/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689987301826477, 'Val/mean miou_metric': 0.9514955282211304, 'Val/mean f1': 0.9701963067054749, 'Val/mean precision': 0.9662818312644958, 'Val/mean recall': 0.9741424918174744, 'Val/mean hd95_metric': 6.092692852020264} +Epoch [1808/4000] Training [1/16] Loss: 0.00836 +Epoch [1808/4000] Training [2/16] Loss: 0.00791 +Epoch [1808/4000] Training [3/16] Loss: 0.00535 +Epoch [1808/4000] Training [4/16] Loss: 0.00817 +Epoch [1808/4000] Training [5/16] Loss: 0.00677 +Epoch [1808/4000] Training [6/16] Loss: 0.04204 +Epoch [1808/4000] Training [7/16] Loss: 0.00675 +Epoch [1808/4000] Training [8/16] Loss: 0.00728 +Epoch [1808/4000] Training [9/16] Loss: 0.00558 +Epoch [1808/4000] Training [10/16] Loss: 0.00818 +Epoch [1808/4000] Training [11/16] Loss: 0.00704 +Epoch [1808/4000] Training [12/16] Loss: 0.00717 +Epoch [1808/4000] Training [13/16] Loss: 0.06269 +Epoch [1808/4000] Training [14/16] Loss: 0.00620 +Epoch [1808/4000] Training [15/16] Loss: 0.01062 +Epoch [1808/4000] Training [16/16] Loss: 0.00635 +Epoch [1808/4000] Training metric {'Train/mean dice_metric': 0.9943556785583496, 'Train/mean miou_metric': 0.9887239933013916, 'Train/mean f1': 0.9900182485580444, 'Train/mean precision': 0.9858993291854858, 'Train/mean recall': 0.9941717386245728, 'Train/mean hd95_metric': 1.393669605255127} +Epoch [1808/4000] Validation [1/4] Loss: 0.93116 focal_loss 0.76161 dice_loss 0.16955 +Epoch [1808/4000] Validation [2/4] Loss: 0.62903 focal_loss 0.41630 dice_loss 0.21273 +Epoch [1808/4000] Validation [3/4] Loss: 0.20197 focal_loss 0.13603 dice_loss 0.06594 +Epoch [1808/4000] Validation [4/4] Loss: 0.49637 focal_loss 0.34190 dice_loss 0.15447 +Epoch [1808/4000] Validation metric {'Val/mean dice_metric': 0.963671863079071, 'Val/mean miou_metric': 0.9455661773681641, 'Val/mean f1': 0.9658738374710083, 'Val/mean precision': 0.9691668152809143, 'Val/mean recall': 0.9626031517982483, 'Val/mean hd95_metric': 6.8060455322265625} +Cheakpoint... +Epoch [1808/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9637], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.963671863079071, 'Val/mean miou_metric': 0.9455661773681641, 'Val/mean f1': 0.9658738374710083, 'Val/mean precision': 0.9691668152809143, 'Val/mean recall': 0.9626031517982483, 'Val/mean hd95_metric': 6.8060455322265625} +Epoch [1809/4000] Training [1/16] Loss: 0.00981 +Epoch [1809/4000] Training [2/16] Loss: 0.00576 +Epoch [1809/4000] Training [3/16] Loss: 0.00995 +Epoch [1809/4000] Training [4/16] Loss: 0.00672 +Epoch [1809/4000] Training [5/16] Loss: 0.00626 +Epoch [1809/4000] Training [6/16] Loss: 0.00608 +Epoch [1809/4000] Training [7/16] Loss: 0.00845 +Epoch [1809/4000] Training [8/16] Loss: 0.00818 +Epoch [1809/4000] Training [9/16] Loss: 0.00872 +Epoch [1809/4000] Training [10/16] Loss: 0.00734 +Epoch [1809/4000] Training [11/16] Loss: 0.00763 +Epoch [1809/4000] Training [12/16] Loss: 0.00669 +Epoch [1809/4000] Training [13/16] Loss: 0.00738 +Epoch [1809/4000] Training [14/16] Loss: 0.00956 +Epoch [1809/4000] Training [15/16] Loss: 0.02192 +Epoch [1809/4000] Training [16/16] Loss: 0.00836 +Epoch [1809/4000] Training metric {'Train/mean dice_metric': 0.9942488074302673, 'Train/mean miou_metric': 0.9884217977523804, 'Train/mean f1': 0.9891425967216492, 'Train/mean precision': 0.9848727583885193, 'Train/mean recall': 0.9934496283531189, 'Train/mean hd95_metric': 1.5068936347961426} +Epoch [1809/4000] Validation [1/4] Loss: 1.00009 focal_loss 0.85247 dice_loss 0.14761 +Epoch [1809/4000] Validation [2/4] Loss: 0.22568 focal_loss 0.13801 dice_loss 0.08768 +Epoch [1809/4000] Validation [3/4] Loss: 0.28217 focal_loss 0.18878 dice_loss 0.09339 +Epoch [1809/4000] Validation [4/4] Loss: 0.48452 focal_loss 0.31137 dice_loss 0.17315 +Epoch [1809/4000] Validation metric {'Val/mean dice_metric': 0.9674144983291626, 'Val/mean miou_metric': 0.9484924077987671, 'Val/mean f1': 0.9663133025169373, 'Val/mean precision': 0.9627185463905334, 'Val/mean recall': 0.9699350595474243, 'Val/mean hd95_metric': 7.263128757476807} +Cheakpoint... +Epoch [1809/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9674], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674144983291626, 'Val/mean miou_metric': 0.9484924077987671, 'Val/mean f1': 0.9663133025169373, 'Val/mean precision': 0.9627185463905334, 'Val/mean recall': 0.9699350595474243, 'Val/mean hd95_metric': 7.263128757476807} +Epoch [1810/4000] Training [1/16] Loss: 0.00796 +Epoch [1810/4000] Training [2/16] Loss: 0.00652 +Epoch [1810/4000] Training [3/16] Loss: 0.04123 +Epoch [1810/4000] Training [4/16] Loss: 0.00688 +Epoch [1810/4000] Training [5/16] Loss: 0.00879 +Epoch [1810/4000] Training [6/16] Loss: 0.01497 +Epoch [1810/4000] Training [7/16] Loss: 0.00945 +Epoch [1810/4000] Training [8/16] Loss: 0.00610 +Epoch [1810/4000] Training [9/16] Loss: 0.00836 +Epoch [1810/4000] Training [10/16] Loss: 0.00881 +Epoch [1810/4000] Training [11/16] Loss: 0.00883 +Epoch [1810/4000] Training [12/16] Loss: 0.04984 +Epoch [1810/4000] Training [13/16] Loss: 0.00710 +Epoch [1810/4000] Training [14/16] Loss: 0.00761 +Epoch [1810/4000] Training [15/16] Loss: 0.00960 +Epoch [1810/4000] Training [16/16] Loss: 0.00736 +Epoch [1810/4000] Training metric {'Train/mean dice_metric': 0.9929769039154053, 'Train/mean miou_metric': 0.9860843420028687, 'Train/mean f1': 0.989260196685791, 'Train/mean precision': 0.984570324420929, 'Train/mean recall': 0.9939950108528137, 'Train/mean hd95_metric': 2.977905750274658} +Epoch [1810/4000] Validation [1/4] Loss: 0.80783 focal_loss 0.61008 dice_loss 0.19776 +Epoch [1810/4000] Validation [2/4] Loss: 0.24462 focal_loss 0.12762 dice_loss 0.11700 +Epoch [1810/4000] Validation [3/4] Loss: 0.17534 focal_loss 0.09875 dice_loss 0.07659 +Epoch [1810/4000] Validation [4/4] Loss: 0.39048 focal_loss 0.26914 dice_loss 0.12134 +Epoch [1810/4000] Validation metric {'Val/mean dice_metric': 0.9639555811882019, 'Val/mean miou_metric': 0.9447742700576782, 'Val/mean f1': 0.9670459032058716, 'Val/mean precision': 0.9723988175392151, 'Val/mean recall': 0.9617515802383423, 'Val/mean hd95_metric': 8.347804069519043} +Cheakpoint... +Epoch [1810/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9640], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9639555811882019, 'Val/mean miou_metric': 0.9447742700576782, 'Val/mean f1': 0.9670459032058716, 'Val/mean precision': 0.9723988175392151, 'Val/mean recall': 0.9617515802383423, 'Val/mean hd95_metric': 8.347804069519043} +Epoch [1811/4000] Training [1/16] Loss: 0.01049 +Epoch [1811/4000] Training [2/16] Loss: 0.00802 +Epoch [1811/4000] Training [3/16] Loss: 0.01802 +Epoch [1811/4000] Training [4/16] Loss: 0.01038 +Epoch [1811/4000] Training [5/16] Loss: 0.00875 +Epoch [1811/4000] Training [6/16] Loss: 0.00762 +Epoch [1811/4000] Training [7/16] Loss: 0.00890 +Epoch [1811/4000] Training [8/16] Loss: 0.00713 +Epoch [1811/4000] Training [9/16] Loss: 0.00992 +Epoch [1811/4000] Training [10/16] Loss: 0.00904 +Epoch [1811/4000] Training [11/16] Loss: 0.00732 +Epoch [1811/4000] Training [12/16] Loss: 0.00809 +Epoch [1811/4000] Training [13/16] Loss: 0.00768 +Epoch [1811/4000] Training [14/16] Loss: 0.00853 +Epoch [1811/4000] Training [15/16] Loss: 0.00780 +Epoch [1811/4000] Training [16/16] Loss: 0.00791 +Epoch [1811/4000] Training metric {'Train/mean dice_metric': 0.9939901828765869, 'Train/mean miou_metric': 0.9877994656562805, 'Train/mean f1': 0.9897210001945496, 'Train/mean precision': 0.9849526286125183, 'Train/mean recall': 0.9945357441902161, 'Train/mean hd95_metric': 1.1459816694259644} +Epoch [1811/4000] Validation [1/4] Loss: 0.71329 focal_loss 0.57349 dice_loss 0.13980 +Epoch [1811/4000] Validation [2/4] Loss: 0.27345 focal_loss 0.14104 dice_loss 0.13242 +Epoch [1811/4000] Validation [3/4] Loss: 0.17950 focal_loss 0.11091 dice_loss 0.06859 +Epoch [1811/4000] Validation [4/4] Loss: 0.47521 focal_loss 0.31771 dice_loss 0.15750 +Epoch [1811/4000] Validation metric {'Val/mean dice_metric': 0.9645277857780457, 'Val/mean miou_metric': 0.9454959630966187, 'Val/mean f1': 0.9676538109779358, 'Val/mean precision': 0.9698164463043213, 'Val/mean recall': 0.9655007719993591, 'Val/mean hd95_metric': 7.125210762023926} +Cheakpoint... +Epoch [1811/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9645], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9645277857780457, 'Val/mean miou_metric': 0.9454959630966187, 'Val/mean f1': 0.9676538109779358, 'Val/mean precision': 0.9698164463043213, 'Val/mean recall': 0.9655007719993591, 'Val/mean hd95_metric': 7.125210762023926} +Epoch [1812/4000] Training [1/16] Loss: 0.00906 +Epoch [1812/4000] Training [2/16] Loss: 0.00841 +Epoch [1812/4000] Training [3/16] Loss: 0.00620 +Epoch [1812/4000] Training [4/16] Loss: 0.00587 +Epoch [1812/4000] Training [5/16] Loss: 0.00590 +Epoch [1812/4000] Training [6/16] Loss: 0.00988 +Epoch [1812/4000] Training [7/16] Loss: 0.00606 +Epoch [1812/4000] Training [8/16] Loss: 0.00745 +Epoch [1812/4000] Training [9/16] Loss: 0.00869 +Epoch [1812/4000] Training [10/16] Loss: 0.00730 +Epoch [1812/4000] Training [11/16] Loss: 0.00810 +Epoch [1812/4000] Training [12/16] Loss: 0.00745 +Epoch [1812/4000] Training [13/16] Loss: 0.00629 +Epoch [1812/4000] Training [14/16] Loss: 0.01900 +Epoch [1812/4000] Training [15/16] Loss: 0.00823 +Epoch [1812/4000] Training [16/16] Loss: 0.00732 +Epoch [1812/4000] Training metric {'Train/mean dice_metric': 0.9943662881851196, 'Train/mean miou_metric': 0.9886890649795532, 'Train/mean f1': 0.9895923137664795, 'Train/mean precision': 0.9845240116119385, 'Train/mean recall': 0.9947129487991333, 'Train/mean hd95_metric': 1.1445003747940063} +Epoch [1812/4000] Validation [1/4] Loss: 0.28189 focal_loss 0.21584 dice_loss 0.06605 +Epoch [1812/4000] Validation [2/4] Loss: 0.55146 focal_loss 0.34818 dice_loss 0.20328 +Epoch [1812/4000] Validation [3/4] Loss: 0.21025 focal_loss 0.12966 dice_loss 0.08058 +Epoch [1812/4000] Validation [4/4] Loss: 0.38879 focal_loss 0.24264 dice_loss 0.14615 +Epoch [1812/4000] Validation metric {'Val/mean dice_metric': 0.9655596017837524, 'Val/mean miou_metric': 0.9474905133247375, 'Val/mean f1': 0.9687575697898865, 'Val/mean precision': 0.966606855392456, 'Val/mean recall': 0.9709178805351257, 'Val/mean hd95_metric': 7.284834861755371} +Cheakpoint... +Epoch [1812/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9656], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9655596017837524, 'Val/mean miou_metric': 0.9474905133247375, 'Val/mean f1': 0.9687575697898865, 'Val/mean precision': 0.966606855392456, 'Val/mean recall': 0.9709178805351257, 'Val/mean hd95_metric': 7.284834861755371} +Epoch [1813/4000] Training [1/16] Loss: 0.00826 +Epoch [1813/4000] Training [2/16] Loss: 0.00761 +Epoch [1813/4000] Training [3/16] Loss: 0.00562 +Epoch [1813/4000] Training [4/16] Loss: 0.00605 +Epoch [1813/4000] Training [5/16] Loss: 0.01013 +Epoch [1813/4000] Training [6/16] Loss: 0.01373 +Epoch [1813/4000] Training [7/16] Loss: 0.00622 +Epoch [1813/4000] Training [8/16] Loss: 0.00699 +Epoch [1813/4000] Training [9/16] Loss: 0.00866 +Epoch [1813/4000] Training [10/16] Loss: 0.00873 +Epoch [1813/4000] Training [11/16] Loss: 0.00588 +Epoch [1813/4000] Training [12/16] Loss: 0.01042 +Epoch [1813/4000] Training [13/16] Loss: 0.00797 +Epoch [1813/4000] Training [14/16] Loss: 0.00778 +Epoch [1813/4000] Training [15/16] Loss: 0.00770 +Epoch [1813/4000] Training [16/16] Loss: 0.00661 +Epoch [1813/4000] Training metric {'Train/mean dice_metric': 0.9933091402053833, 'Train/mean miou_metric': 0.9869863390922546, 'Train/mean f1': 0.9894486665725708, 'Train/mean precision': 0.9855016469955444, 'Train/mean recall': 0.9934273958206177, 'Train/mean hd95_metric': 1.8304967880249023} +Epoch [1813/4000] Validation [1/4] Loss: 0.25651 focal_loss 0.18567 dice_loss 0.07084 +Epoch [1813/4000] Validation [2/4] Loss: 0.23137 focal_loss 0.11405 dice_loss 0.11732 +Epoch [1813/4000] Validation [3/4] Loss: 0.17165 focal_loss 0.09847 dice_loss 0.07318 +Epoch [1813/4000] Validation [4/4] Loss: 0.30311 focal_loss 0.16158 dice_loss 0.14154 +Epoch [1813/4000] Validation metric {'Val/mean dice_metric': 0.9667434692382812, 'Val/mean miou_metric': 0.9474865198135376, 'Val/mean f1': 0.9681465029716492, 'Val/mean precision': 0.9573373198509216, 'Val/mean recall': 0.9792025089263916, 'Val/mean hd95_metric': 9.726515769958496} +Cheakpoint... +Epoch [1813/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9667], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9667434692382812, 'Val/mean miou_metric': 0.9474865198135376, 'Val/mean f1': 0.9681465029716492, 'Val/mean precision': 0.9573373198509216, 'Val/mean recall': 0.9792025089263916, 'Val/mean hd95_metric': 9.726515769958496} +Epoch [1814/4000] Training [1/16] Loss: 0.00874 +Epoch [1814/4000] Training [2/16] Loss: 0.00824 +Epoch [1814/4000] Training [3/16] Loss: 0.00664 +Epoch [1814/4000] Training [4/16] Loss: 0.00775 +Epoch [1814/4000] Training [5/16] Loss: 0.00884 +Epoch [1814/4000] Training [6/16] Loss: 0.01012 +Epoch [1814/4000] Training [7/16] Loss: 0.00526 +Epoch [1814/4000] Training [8/16] Loss: 0.00608 +Epoch [1814/4000] Training [9/16] Loss: 0.00983 +Epoch [1814/4000] Training [10/16] Loss: 0.00682 +Epoch [1814/4000] Training [11/16] Loss: 0.01084 +Epoch [1814/4000] Training [12/16] Loss: 0.00737 +Epoch [1814/4000] Training [13/16] Loss: 0.01017 +Epoch [1814/4000] Training [14/16] Loss: 0.00713 +Epoch [1814/4000] Training [15/16] Loss: 0.00674 +Epoch [1814/4000] Training [16/16] Loss: 0.04885 +Epoch [1814/4000] Training metric {'Train/mean dice_metric': 0.9939390420913696, 'Train/mean miou_metric': 0.9879798889160156, 'Train/mean f1': 0.9893538355827332, 'Train/mean precision': 0.9837418794631958, 'Train/mean recall': 0.9950301647186279, 'Train/mean hd95_metric': 1.7132385969161987} +Epoch [1814/4000] Validation [1/4] Loss: 0.46813 focal_loss 0.35334 dice_loss 0.11479 +Epoch [1814/4000] Validation [2/4] Loss: 0.47960 focal_loss 0.25184 dice_loss 0.22776 +Epoch [1814/4000] Validation [3/4] Loss: 0.17993 focal_loss 0.11770 dice_loss 0.06223 +Epoch [1814/4000] Validation [4/4] Loss: 0.33563 focal_loss 0.22021 dice_loss 0.11543 +Epoch [1814/4000] Validation metric {'Val/mean dice_metric': 0.9650571942329407, 'Val/mean miou_metric': 0.9463992118835449, 'Val/mean f1': 0.9673341512680054, 'Val/mean precision': 0.9671385884284973, 'Val/mean recall': 0.9675296545028687, 'Val/mean hd95_metric': 7.571014404296875} +Cheakpoint... +Epoch [1814/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9651], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9650571942329407, 'Val/mean miou_metric': 0.9463992118835449, 'Val/mean f1': 0.9673341512680054, 'Val/mean precision': 0.9671385884284973, 'Val/mean recall': 0.9675296545028687, 'Val/mean hd95_metric': 7.571014404296875} +Epoch [1815/4000] Training [1/16] Loss: 0.00676 +Epoch [1815/4000] Training [2/16] Loss: 0.00738 +Epoch [1815/4000] Training [3/16] Loss: 0.00723 +Epoch [1815/4000] Training [4/16] Loss: 0.00748 +Epoch [1815/4000] Training [5/16] Loss: 0.00725 +Epoch [1815/4000] Training [6/16] Loss: 0.00751 +Epoch [1815/4000] Training [7/16] Loss: 0.02086 +Epoch [1815/4000] Training [8/16] Loss: 0.02088 +Epoch [1815/4000] Training [9/16] Loss: 0.03471 +Epoch [1815/4000] Training [10/16] Loss: 0.00785 +Epoch [1815/4000] Training [11/16] Loss: 0.00919 +Epoch [1815/4000] Training [12/16] Loss: 0.00984 +Epoch [1815/4000] Training [13/16] Loss: 0.01474 +Epoch [1815/4000] Training [14/16] Loss: 0.00989 +Epoch [1815/4000] Training [15/16] Loss: 0.00927 +Epoch [1815/4000] Training [16/16] Loss: 0.00827 +Epoch [1815/4000] Training metric {'Train/mean dice_metric': 0.9934125542640686, 'Train/mean miou_metric': 0.9867911338806152, 'Train/mean f1': 0.9892697334289551, 'Train/mean precision': 0.9854905605316162, 'Train/mean recall': 0.9930779933929443, 'Train/mean hd95_metric': 1.6267147064208984} +Epoch [1815/4000] Validation [1/4] Loss: 0.59700 focal_loss 0.44872 dice_loss 0.14828 +Epoch [1815/4000] Validation [2/4] Loss: 0.58006 focal_loss 0.37188 dice_loss 0.20818 +Epoch [1815/4000] Validation [3/4] Loss: 0.35664 focal_loss 0.24882 dice_loss 0.10782 +Epoch [1815/4000] Validation [4/4] Loss: 0.34420 focal_loss 0.22157 dice_loss 0.12263 +Epoch [1815/4000] Validation metric {'Val/mean dice_metric': 0.9660625457763672, 'Val/mean miou_metric': 0.9469105005264282, 'Val/mean f1': 0.9669110774993896, 'Val/mean precision': 0.9685825705528259, 'Val/mean recall': 0.9652453064918518, 'Val/mean hd95_metric': 6.575779914855957} +Cheakpoint... +Epoch [1815/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9661], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9660625457763672, 'Val/mean miou_metric': 0.9469105005264282, 'Val/mean f1': 0.9669110774993896, 'Val/mean precision': 0.9685825705528259, 'Val/mean recall': 0.9652453064918518, 'Val/mean hd95_metric': 6.575779914855957} +Epoch [1816/4000] Training [1/16] Loss: 0.00640 +Epoch [1816/4000] Training [2/16] Loss: 0.00775 +Epoch [1816/4000] Training [3/16] Loss: 0.00661 +Epoch [1816/4000] Training [4/16] Loss: 0.01037 +Epoch [1816/4000] Training [5/16] Loss: 0.00697 +Epoch [1816/4000] Training [6/16] Loss: 0.00811 +Epoch [1816/4000] Training [7/16] Loss: 0.00654 +Epoch [1816/4000] Training [8/16] Loss: 0.00650 +Epoch [1816/4000] Training [9/16] Loss: 0.00753 +Epoch [1816/4000] Training [10/16] Loss: 0.00805 +Epoch [1816/4000] Training [11/16] Loss: 0.00819 +Epoch [1816/4000] Training [12/16] Loss: 0.00555 +Epoch [1816/4000] Training [13/16] Loss: 0.01002 +Epoch [1816/4000] Training [14/16] Loss: 0.00637 +Epoch [1816/4000] Training [15/16] Loss: 0.00726 +Epoch [1816/4000] Training [16/16] Loss: 0.00680 +Epoch [1816/4000] Training metric {'Train/mean dice_metric': 0.9949769973754883, 'Train/mean miou_metric': 0.9897459149360657, 'Train/mean f1': 0.990749180316925, 'Train/mean precision': 0.9859880805015564, 'Train/mean recall': 0.9955565333366394, 'Train/mean hd95_metric': 1.0755188465118408} +Epoch [1816/4000] Validation [1/4] Loss: 0.29743 focal_loss 0.22952 dice_loss 0.06791 +Epoch [1816/4000] Validation [2/4] Loss: 0.25079 focal_loss 0.13214 dice_loss 0.11865 +Epoch [1816/4000] Validation [3/4] Loss: 0.34651 focal_loss 0.24807 dice_loss 0.09844 +Epoch [1816/4000] Validation [4/4] Loss: 0.28460 focal_loss 0.17715 dice_loss 0.10745 +Epoch [1816/4000] Validation metric {'Val/mean dice_metric': 0.9720665216445923, 'Val/mean miou_metric': 0.9542834162712097, 'Val/mean f1': 0.9732077121734619, 'Val/mean precision': 0.9688630104064941, 'Val/mean recall': 0.9775915741920471, 'Val/mean hd95_metric': 6.417738437652588} +Cheakpoint... +Epoch [1816/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720665216445923, 'Val/mean miou_metric': 0.9542834162712097, 'Val/mean f1': 0.9732077121734619, 'Val/mean precision': 0.9688630104064941, 'Val/mean recall': 0.9775915741920471, 'Val/mean hd95_metric': 6.417738437652588} +Epoch [1817/4000] Training [1/16] Loss: 0.00756 +Epoch [1817/4000] Training [2/16] Loss: 0.01014 +Epoch [1817/4000] Training [3/16] Loss: 0.00669 +Epoch [1817/4000] Training [4/16] Loss: 0.00746 +Epoch [1817/4000] Training [5/16] Loss: 0.00641 +Epoch [1817/4000] Training [6/16] Loss: 0.00583 +Epoch [1817/4000] Training [7/16] Loss: 0.00742 +Epoch [1817/4000] Training [8/16] Loss: 0.00848 +Epoch [1817/4000] Training [9/16] Loss: 0.00940 +Epoch [1817/4000] Training [10/16] Loss: 0.00723 +Epoch [1817/4000] Training [11/16] Loss: 0.00648 +Epoch [1817/4000] Training [12/16] Loss: 0.00799 +Epoch [1817/4000] Training [13/16] Loss: 0.00720 +Epoch [1817/4000] Training [14/16] Loss: 0.00700 +Epoch [1817/4000] Training [15/16] Loss: 0.00891 +Epoch [1817/4000] Training [16/16] Loss: 0.00649 +Epoch [1817/4000] Training metric {'Train/mean dice_metric': 0.994828462600708, 'Train/mean miou_metric': 0.989474892616272, 'Train/mean f1': 0.9908023476600647, 'Train/mean precision': 0.9863078594207764, 'Train/mean recall': 0.995337963104248, 'Train/mean hd95_metric': 1.0892741680145264} +Epoch [1817/4000] Validation [1/4] Loss: 0.41818 focal_loss 0.31610 dice_loss 0.10209 +Epoch [1817/4000] Validation [2/4] Loss: 0.21527 focal_loss 0.11429 dice_loss 0.10098 +Epoch [1817/4000] Validation [3/4] Loss: 0.43194 focal_loss 0.31103 dice_loss 0.12091 +Epoch [1817/4000] Validation [4/4] Loss: 0.26142 focal_loss 0.16286 dice_loss 0.09855 +Epoch [1817/4000] Validation metric {'Val/mean dice_metric': 0.9722760319709778, 'Val/mean miou_metric': 0.9542765617370605, 'Val/mean f1': 0.9721912741661072, 'Val/mean precision': 0.9698641300201416, 'Val/mean recall': 0.9745296835899353, 'Val/mean hd95_metric': 6.198803424835205} +Cheakpoint... +Epoch [1817/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722760319709778, 'Val/mean miou_metric': 0.9542765617370605, 'Val/mean f1': 0.9721912741661072, 'Val/mean precision': 0.9698641300201416, 'Val/mean recall': 0.9745296835899353, 'Val/mean hd95_metric': 6.198803424835205} +Epoch [1818/4000] Training [1/16] Loss: 0.00705 +Epoch [1818/4000] Training [2/16] Loss: 0.00530 +Epoch [1818/4000] Training [3/16] Loss: 0.00665 +Epoch [1818/4000] Training [4/16] Loss: 0.00554 +Epoch [1818/4000] Training [5/16] Loss: 0.00614 +Epoch [1818/4000] Training [6/16] Loss: 0.00648 +Epoch [1818/4000] Training [7/16] Loss: 0.00673 +Epoch [1818/4000] Training [8/16] Loss: 0.00771 +Epoch [1818/4000] Training [9/16] Loss: 0.00534 +Epoch [1818/4000] Training [10/16] Loss: 0.00493 +Epoch [1818/4000] Training [11/16] Loss: 0.00842 +Epoch [1818/4000] Training [12/16] Loss: 0.00675 +Epoch [1818/4000] Training [13/16] Loss: 0.00600 +Epoch [1818/4000] Training [14/16] Loss: 0.00632 +Epoch [1818/4000] Training [15/16] Loss: 0.00574 +Epoch [1818/4000] Training [16/16] Loss: 0.00772 +Epoch [1818/4000] Training metric {'Train/mean dice_metric': 0.9957104921340942, 'Train/mean miou_metric': 0.9911952018737793, 'Train/mean f1': 0.9913636445999146, 'Train/mean precision': 0.9869251847267151, 'Train/mean recall': 0.9958420395851135, 'Train/mean hd95_metric': 1.0119800567626953} +Epoch [1818/4000] Validation [1/4] Loss: 0.60229 focal_loss 0.44158 dice_loss 0.16071 +Epoch [1818/4000] Validation [2/4] Loss: 0.37358 focal_loss 0.21183 dice_loss 0.16175 +Epoch [1818/4000] Validation [3/4] Loss: 0.36557 focal_loss 0.25394 dice_loss 0.11163 +Epoch [1818/4000] Validation [4/4] Loss: 0.19228 focal_loss 0.10853 dice_loss 0.08375 +Epoch [1818/4000] Validation metric {'Val/mean dice_metric': 0.9679193496704102, 'Val/mean miou_metric': 0.950738787651062, 'Val/mean f1': 0.9701417088508606, 'Val/mean precision': 0.9706791043281555, 'Val/mean recall': 0.9696049690246582, 'Val/mean hd95_metric': 6.501922607421875} +Cheakpoint... +Epoch [1818/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9679], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9679193496704102, 'Val/mean miou_metric': 0.950738787651062, 'Val/mean f1': 0.9701417088508606, 'Val/mean precision': 0.9706791043281555, 'Val/mean recall': 0.9696049690246582, 'Val/mean hd95_metric': 6.501922607421875} +Epoch [1819/4000] Training [1/16] Loss: 0.00739 +Epoch [1819/4000] Training [2/16] Loss: 0.00523 +Epoch [1819/4000] Training [3/16] Loss: 0.00825 +Epoch [1819/4000] Training [4/16] Loss: 0.00799 +Epoch [1819/4000] Training [5/16] Loss: 0.00585 +Epoch [1819/4000] Training [6/16] Loss: 0.00683 +Epoch [1819/4000] Training [7/16] Loss: 0.00478 +Epoch [1819/4000] Training [8/16] Loss: 0.00888 +Epoch [1819/4000] Training [9/16] Loss: 0.00583 +Epoch [1819/4000] Training [10/16] Loss: 0.00560 +Epoch [1819/4000] Training [11/16] Loss: 0.00715 +Epoch [1819/4000] Training [12/16] Loss: 0.00689 +Epoch [1819/4000] Training [13/16] Loss: 0.00604 +Epoch [1819/4000] Training [14/16] Loss: 0.00626 +Epoch [1819/4000] Training [15/16] Loss: 0.00737 +Epoch [1819/4000] Training [16/16] Loss: 0.00641 +Epoch [1819/4000] Training metric {'Train/mean dice_metric': 0.9956709146499634, 'Train/mean miou_metric': 0.9910906553268433, 'Train/mean f1': 0.990666389465332, 'Train/mean precision': 0.9856022000312805, 'Train/mean recall': 0.9957828521728516, 'Train/mean hd95_metric': 1.0477960109710693} +Epoch [1819/4000] Validation [1/4] Loss: 0.32367 focal_loss 0.24536 dice_loss 0.07831 +Epoch [1819/4000] Validation [2/4] Loss: 0.36037 focal_loss 0.19231 dice_loss 0.16807 +Epoch [1819/4000] Validation [3/4] Loss: 0.30925 focal_loss 0.20943 dice_loss 0.09982 +Epoch [1819/4000] Validation [4/4] Loss: 0.33523 focal_loss 0.21002 dice_loss 0.12521 +Epoch [1819/4000] Validation metric {'Val/mean dice_metric': 0.970733642578125, 'Val/mean miou_metric': 0.9542719721794128, 'Val/mean f1': 0.9723210334777832, 'Val/mean precision': 0.9724632501602173, 'Val/mean recall': 0.9721789956092834, 'Val/mean hd95_metric': 5.758115291595459} +Cheakpoint... +Epoch [1819/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970733642578125, 'Val/mean miou_metric': 0.9542719721794128, 'Val/mean f1': 0.9723210334777832, 'Val/mean precision': 0.9724632501602173, 'Val/mean recall': 0.9721789956092834, 'Val/mean hd95_metric': 5.758115291595459} +Epoch [1820/4000] Training [1/16] Loss: 0.00683 +Epoch [1820/4000] Training [2/16] Loss: 0.00671 +Epoch [1820/4000] Training [3/16] Loss: 0.00657 +Epoch [1820/4000] Training [4/16] Loss: 0.02081 +Epoch [1820/4000] Training [5/16] Loss: 0.00530 +Epoch [1820/4000] Training [6/16] Loss: 0.00607 +Epoch [1820/4000] Training [7/16] Loss: 0.00610 +Epoch [1820/4000] Training [8/16] Loss: 0.00752 +Epoch [1820/4000] Training [9/16] Loss: 0.00866 +Epoch [1820/4000] Training [10/16] Loss: 0.00543 +Epoch [1820/4000] Training [11/16] Loss: 0.00605 +Epoch [1820/4000] Training [12/16] Loss: 0.00685 +Epoch [1820/4000] Training [13/16] Loss: 0.00710 +Epoch [1820/4000] Training [14/16] Loss: 0.00790 +Epoch [1820/4000] Training [15/16] Loss: 0.00690 +Epoch [1820/4000] Training [16/16] Loss: 0.00728 +Epoch [1820/4000] Training metric {'Train/mean dice_metric': 0.9954255819320679, 'Train/mean miou_metric': 0.9906487464904785, 'Train/mean f1': 0.9911321997642517, 'Train/mean precision': 0.9864656329154968, 'Train/mean recall': 0.9958431720733643, 'Train/mean hd95_metric': 1.0330642461776733} +Epoch [1820/4000] Validation [1/4] Loss: 0.46439 focal_loss 0.36510 dice_loss 0.09928 +Epoch [1820/4000] Validation [2/4] Loss: 0.20879 focal_loss 0.11188 dice_loss 0.09691 +Epoch [1820/4000] Validation [3/4] Loss: 0.26354 focal_loss 0.16685 dice_loss 0.09668 +Epoch [1820/4000] Validation [4/4] Loss: 0.32201 focal_loss 0.20563 dice_loss 0.11638 +Epoch [1820/4000] Validation metric {'Val/mean dice_metric': 0.9728094339370728, 'Val/mean miou_metric': 0.9554683566093445, 'Val/mean f1': 0.9732710719108582, 'Val/mean precision': 0.9707498550415039, 'Val/mean recall': 0.9758053421974182, 'Val/mean hd95_metric': 5.507880210876465} +Cheakpoint... +Epoch [1820/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728094339370728, 'Val/mean miou_metric': 0.9554683566093445, 'Val/mean f1': 0.9732710719108582, 'Val/mean precision': 0.9707498550415039, 'Val/mean recall': 0.9758053421974182, 'Val/mean hd95_metric': 5.507880210876465} +Epoch [1821/4000] Training [1/16] Loss: 0.00633 +Epoch [1821/4000] Training [2/16] Loss: 0.01055 +Epoch [1821/4000] Training [3/16] Loss: 0.00698 +Epoch [1821/4000] Training [4/16] Loss: 0.00619 +Epoch [1821/4000] Training [5/16] Loss: 0.00857 +Epoch [1821/4000] Training [6/16] Loss: 0.00652 +Epoch [1821/4000] Training [7/16] Loss: 0.00688 +Epoch [1821/4000] Training [8/16] Loss: 0.00712 +Epoch [1821/4000] Training [9/16] Loss: 0.00651 +Epoch [1821/4000] Training [10/16] Loss: 0.00562 +Epoch [1821/4000] Training [11/16] Loss: 0.00554 +Epoch [1821/4000] Training [12/16] Loss: 0.00510 +Epoch [1821/4000] Training [13/16] Loss: 0.00582 +Epoch [1821/4000] Training [14/16] Loss: 0.00742 +Epoch [1821/4000] Training [15/16] Loss: 0.00710 +Epoch [1821/4000] Training [16/16] Loss: 0.00832 +Epoch [1821/4000] Training metric {'Train/mean dice_metric': 0.9954643249511719, 'Train/mean miou_metric': 0.9907180070877075, 'Train/mean f1': 0.9913513660430908, 'Train/mean precision': 0.986881673336029, 'Train/mean recall': 0.9958617687225342, 'Train/mean hd95_metric': 1.0225037336349487} +Epoch [1821/4000] Validation [1/4] Loss: 0.33088 focal_loss 0.25219 dice_loss 0.07869 +Epoch [1821/4000] Validation [2/4] Loss: 0.17280 focal_loss 0.09267 dice_loss 0.08013 +Epoch [1821/4000] Validation [3/4] Loss: 0.23243 focal_loss 0.14252 dice_loss 0.08991 +Epoch [1821/4000] Validation [4/4] Loss: 0.29084 focal_loss 0.16885 dice_loss 0.12199 +Epoch [1821/4000] Validation metric {'Val/mean dice_metric': 0.9717365503311157, 'Val/mean miou_metric': 0.9545952081680298, 'Val/mean f1': 0.973570704460144, 'Val/mean precision': 0.9718986749649048, 'Val/mean recall': 0.9752485752105713, 'Val/mean hd95_metric': 5.762938499450684} +Cheakpoint... +Epoch [1821/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717365503311157, 'Val/mean miou_metric': 0.9545952081680298, 'Val/mean f1': 0.973570704460144, 'Val/mean precision': 0.9718986749649048, 'Val/mean recall': 0.9752485752105713, 'Val/mean hd95_metric': 5.762938499450684} +Epoch [1822/4000] Training [1/16] Loss: 0.00659 +Epoch [1822/4000] Training [2/16] Loss: 0.00575 +Epoch [1822/4000] Training [3/16] Loss: 0.00484 +Epoch [1822/4000] Training [4/16] Loss: 0.00667 +Epoch [1822/4000] Training [5/16] Loss: 0.00656 +Epoch [1822/4000] Training [6/16] Loss: 0.00554 +Epoch [1822/4000] Training [7/16] Loss: 0.00787 +Epoch [1822/4000] Training [8/16] Loss: 0.00527 +Epoch [1822/4000] Training [9/16] Loss: 0.00684 +Epoch [1822/4000] Training [10/16] Loss: 0.00760 +Epoch [1822/4000] Training [11/16] Loss: 0.00857 +Epoch [1822/4000] Training [12/16] Loss: 0.00601 +Epoch [1822/4000] Training [13/16] Loss: 0.00696 +Epoch [1822/4000] Training [14/16] Loss: 0.00546 +Epoch [1822/4000] Training [15/16] Loss: 0.00772 +Epoch [1822/4000] Training [16/16] Loss: 0.00752 +Epoch [1822/4000] Training metric {'Train/mean dice_metric': 0.9954984188079834, 'Train/mean miou_metric': 0.9907703399658203, 'Train/mean f1': 0.9913604259490967, 'Train/mean precision': 0.9867870807647705, 'Train/mean recall': 0.9959763884544373, 'Train/mean hd95_metric': 1.0131404399871826} +Epoch [1822/4000] Validation [1/4] Loss: 0.56938 focal_loss 0.45438 dice_loss 0.11499 +Epoch [1822/4000] Validation [2/4] Loss: 0.20918 focal_loss 0.11735 dice_loss 0.09184 +Epoch [1822/4000] Validation [3/4] Loss: 0.22752 focal_loss 0.14073 dice_loss 0.08679 +Epoch [1822/4000] Validation [4/4] Loss: 0.26237 focal_loss 0.15912 dice_loss 0.10324 +Epoch [1822/4000] Validation metric {'Val/mean dice_metric': 0.9719556570053101, 'Val/mean miou_metric': 0.9551016092300415, 'Val/mean f1': 0.973308801651001, 'Val/mean precision': 0.9727065563201904, 'Val/mean recall': 0.9739118218421936, 'Val/mean hd95_metric': 5.722724437713623} +Cheakpoint... +Epoch [1822/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719556570053101, 'Val/mean miou_metric': 0.9551016092300415, 'Val/mean f1': 0.973308801651001, 'Val/mean precision': 0.9727065563201904, 'Val/mean recall': 0.9739118218421936, 'Val/mean hd95_metric': 5.722724437713623} +Epoch [1823/4000] Training [1/16] Loss: 0.00595 +Epoch [1823/4000] Training [2/16] Loss: 0.00902 +Epoch [1823/4000] Training [3/16] Loss: 0.00658 +Epoch [1823/4000] Training [4/16] Loss: 0.00668 +Epoch [1823/4000] Training [5/16] Loss: 0.00671 +Epoch [1823/4000] Training [6/16] Loss: 0.00675 +Epoch [1823/4000] Training [7/16] Loss: 0.00695 +Epoch [1823/4000] Training [8/16] Loss: 0.00692 +Epoch [1823/4000] Training [9/16] Loss: 0.00576 +Epoch [1823/4000] Training [10/16] Loss: 0.00710 +Epoch [1823/4000] Training [11/16] Loss: 0.00600 +Epoch [1823/4000] Training [12/16] Loss: 0.00560 +Epoch [1823/4000] Training [13/16] Loss: 0.00810 +Epoch [1823/4000] Training [14/16] Loss: 0.00922 +Epoch [1823/4000] Training [15/16] Loss: 0.00654 +Epoch [1823/4000] Training [16/16] Loss: 0.00644 +Epoch [1823/4000] Training metric {'Train/mean dice_metric': 0.9954999685287476, 'Train/mean miou_metric': 0.9907727837562561, 'Train/mean f1': 0.9911718964576721, 'Train/mean precision': 0.9865394234657288, 'Train/mean recall': 0.9958480596542358, 'Train/mean hd95_metric': 1.0164332389831543} +Epoch [1823/4000] Validation [1/4] Loss: 0.34060 focal_loss 0.26326 dice_loss 0.07734 +Epoch [1823/4000] Validation [2/4] Loss: 0.52869 focal_loss 0.32102 dice_loss 0.20767 +Epoch [1823/4000] Validation [3/4] Loss: 0.31498 focal_loss 0.21627 dice_loss 0.09871 +Epoch [1823/4000] Validation [4/4] Loss: 0.18208 focal_loss 0.10438 dice_loss 0.07770 +Epoch [1823/4000] Validation metric {'Val/mean dice_metric': 0.9735203981399536, 'Val/mean miou_metric': 0.9566119909286499, 'Val/mean f1': 0.9736959338188171, 'Val/mean precision': 0.9702572822570801, 'Val/mean recall': 0.9771592020988464, 'Val/mean hd95_metric': 5.509421348571777} +Cheakpoint... +Epoch [1823/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735203981399536, 'Val/mean miou_metric': 0.9566119909286499, 'Val/mean f1': 0.9736959338188171, 'Val/mean precision': 0.9702572822570801, 'Val/mean recall': 0.9771592020988464, 'Val/mean hd95_metric': 5.509421348571777} +Epoch [1824/4000] Training [1/16] Loss: 0.01536 +Epoch [1824/4000] Training [2/16] Loss: 0.00576 +Epoch [1824/4000] Training [3/16] Loss: 0.00570 +Epoch [1824/4000] Training [4/16] Loss: 0.00525 +Epoch [1824/4000] Training [5/16] Loss: 0.00488 +Epoch [1824/4000] Training [6/16] Loss: 0.00596 +Epoch [1824/4000] Training [7/16] Loss: 0.00675 +Epoch [1824/4000] Training [8/16] Loss: 0.00861 +Epoch [1824/4000] Training [9/16] Loss: 0.00617 +Epoch [1824/4000] Training [10/16] Loss: 0.00526 +Epoch [1824/4000] Training [11/16] Loss: 0.00593 +Epoch [1824/4000] Training [12/16] Loss: 0.00682 +Epoch [1824/4000] Training [13/16] Loss: 0.00875 +Epoch [1824/4000] Training [14/16] Loss: 0.00693 +Epoch [1824/4000] Training [15/16] Loss: 0.00711 +Epoch [1824/4000] Training [16/16] Loss: 0.00849 +Epoch [1824/4000] Training metric {'Train/mean dice_metric': 0.9952008128166199, 'Train/mean miou_metric': 0.9901833534240723, 'Train/mean f1': 0.990860641002655, 'Train/mean precision': 0.9859981536865234, 'Train/mean recall': 0.9957712888717651, 'Train/mean hd95_metric': 1.054832935333252} +Epoch [1824/4000] Validation [1/4] Loss: 0.27563 focal_loss 0.20785 dice_loss 0.06778 +Epoch [1824/4000] Validation [2/4] Loss: 0.26065 focal_loss 0.14369 dice_loss 0.11696 +Epoch [1824/4000] Validation [3/4] Loss: 0.27735 focal_loss 0.18708 dice_loss 0.09027 +Epoch [1824/4000] Validation [4/4] Loss: 0.18007 focal_loss 0.09512 dice_loss 0.08496 +Epoch [1824/4000] Validation metric {'Val/mean dice_metric': 0.9721114039421082, 'Val/mean miou_metric': 0.9547864198684692, 'Val/mean f1': 0.9742935299873352, 'Val/mean precision': 0.9721367955207825, 'Val/mean recall': 0.9764598608016968, 'Val/mean hd95_metric': 5.595093727111816} +Cheakpoint... +Epoch [1824/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721114039421082, 'Val/mean miou_metric': 0.9547864198684692, 'Val/mean f1': 0.9742935299873352, 'Val/mean precision': 0.9721367955207825, 'Val/mean recall': 0.9764598608016968, 'Val/mean hd95_metric': 5.595093727111816} +Epoch [1825/4000] Training [1/16] Loss: 0.00879 +Epoch [1825/4000] Training [2/16] Loss: 0.00660 +Epoch [1825/4000] Training [3/16] Loss: 0.00631 +Epoch [1825/4000] Training [4/16] Loss: 0.00635 +Epoch [1825/4000] Training [5/16] Loss: 0.00659 +Epoch [1825/4000] Training [6/16] Loss: 0.00560 +Epoch [1825/4000] Training [7/16] Loss: 0.00807 +Epoch [1825/4000] Training [8/16] Loss: 0.00722 +Epoch [1825/4000] Training [9/16] Loss: 0.00807 +Epoch [1825/4000] Training [10/16] Loss: 0.00572 +Epoch [1825/4000] Training [11/16] Loss: 0.00787 +Epoch [1825/4000] Training [12/16] Loss: 0.00592 +Epoch [1825/4000] Training [13/16] Loss: 0.00662 +Epoch [1825/4000] Training [14/16] Loss: 0.00743 +Epoch [1825/4000] Training [15/16] Loss: 0.00597 +Epoch [1825/4000] Training [16/16] Loss: 0.00564 +Epoch [1825/4000] Training metric {'Train/mean dice_metric': 0.9953230619430542, 'Train/mean miou_metric': 0.9904316663742065, 'Train/mean f1': 0.9913285374641418, 'Train/mean precision': 0.9869526624679565, 'Train/mean recall': 0.9957433938980103, 'Train/mean hd95_metric': 1.0178673267364502} +Epoch [1825/4000] Validation [1/4] Loss: 0.24622 focal_loss 0.18154 dice_loss 0.06468 +Epoch [1825/4000] Validation [2/4] Loss: 0.27754 focal_loss 0.15747 dice_loss 0.12007 +Epoch [1825/4000] Validation [3/4] Loss: 0.31681 focal_loss 0.21591 dice_loss 0.10091 +Epoch [1825/4000] Validation [4/4] Loss: 0.27501 focal_loss 0.15979 dice_loss 0.11522 +Epoch [1825/4000] Validation metric {'Val/mean dice_metric': 0.9722169637680054, 'Val/mean miou_metric': 0.9550117254257202, 'Val/mean f1': 0.9743332862854004, 'Val/mean precision': 0.969885528087616, 'Val/mean recall': 0.9788221120834351, 'Val/mean hd95_metric': 5.433821201324463} +Cheakpoint... +Epoch [1825/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722169637680054, 'Val/mean miou_metric': 0.9550117254257202, 'Val/mean f1': 0.9743332862854004, 'Val/mean precision': 0.969885528087616, 'Val/mean recall': 0.9788221120834351, 'Val/mean hd95_metric': 5.433821201324463} +Epoch [1826/4000] Training [1/16] Loss: 0.00555 +Epoch [1826/4000] Training [2/16] Loss: 0.00845 +Epoch [1826/4000] Training [3/16] Loss: 0.00610 +Epoch [1826/4000] Training [4/16] Loss: 0.00582 +Epoch [1826/4000] Training [5/16] Loss: 0.00977 +Epoch [1826/4000] Training [6/16] Loss: 0.00670 +Epoch [1826/4000] Training [7/16] Loss: 0.00726 +Epoch [1826/4000] Training [8/16] Loss: 0.00675 +Epoch [1826/4000] Training [9/16] Loss: 0.00620 +Epoch [1826/4000] Training [10/16] Loss: 0.00877 +Epoch [1826/4000] Training [11/16] Loss: 0.00992 +Epoch [1826/4000] Training [12/16] Loss: 0.00626 +Epoch [1826/4000] Training [13/16] Loss: 0.00670 +Epoch [1826/4000] Training [14/16] Loss: 0.00758 +Epoch [1826/4000] Training [15/16] Loss: 0.00669 +Epoch [1826/4000] Training [16/16] Loss: 0.00817 +Epoch [1826/4000] Training metric {'Train/mean dice_metric': 0.9952925443649292, 'Train/mean miou_metric': 0.9903566837310791, 'Train/mean f1': 0.9911521077156067, 'Train/mean precision': 0.9865517616271973, 'Train/mean recall': 0.9957956075668335, 'Train/mean hd95_metric': 1.0251126289367676} +Epoch [1826/4000] Validation [1/4] Loss: 0.37968 focal_loss 0.29374 dice_loss 0.08595 +Epoch [1826/4000] Validation [2/4] Loss: 0.33216 focal_loss 0.16802 dice_loss 0.16414 +Epoch [1826/4000] Validation [3/4] Loss: 0.17166 focal_loss 0.10030 dice_loss 0.07136 +Epoch [1826/4000] Validation [4/4] Loss: 0.17982 focal_loss 0.10226 dice_loss 0.07756 +Epoch [1826/4000] Validation metric {'Val/mean dice_metric': 0.9699837565422058, 'Val/mean miou_metric': 0.9534801244735718, 'Val/mean f1': 0.9734523892402649, 'Val/mean precision': 0.9714730381965637, 'Val/mean recall': 0.9754399657249451, 'Val/mean hd95_metric': 5.891904354095459} +Cheakpoint... +Epoch [1826/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699837565422058, 'Val/mean miou_metric': 0.9534801244735718, 'Val/mean f1': 0.9734523892402649, 'Val/mean precision': 0.9714730381965637, 'Val/mean recall': 0.9754399657249451, 'Val/mean hd95_metric': 5.891904354095459} +Epoch [1827/4000] Training [1/16] Loss: 0.00611 +Epoch [1827/4000] Training [2/16] Loss: 0.00595 +Epoch [1827/4000] Training [3/16] Loss: 0.00707 +Epoch [1827/4000] Training [4/16] Loss: 0.00825 +Epoch [1827/4000] Training [5/16] Loss: 0.00774 +Epoch [1827/4000] Training [6/16] Loss: 0.00486 +Epoch [1827/4000] Training [7/16] Loss: 0.00666 +Epoch [1827/4000] Training [8/16] Loss: 0.00623 +Epoch [1827/4000] Training [9/16] Loss: 0.00553 +Epoch [1827/4000] Training [10/16] Loss: 0.00565 +Epoch [1827/4000] Training [11/16] Loss: 0.01161 +Epoch [1827/4000] Training [12/16] Loss: 0.00830 +Epoch [1827/4000] Training [13/16] Loss: 0.00847 +Epoch [1827/4000] Training [14/16] Loss: 0.00760 +Epoch [1827/4000] Training [15/16] Loss: 0.00770 +Epoch [1827/4000] Training [16/16] Loss: 0.00766 +Epoch [1827/4000] Training metric {'Train/mean dice_metric': 0.9952354431152344, 'Train/mean miou_metric': 0.9902647137641907, 'Train/mean f1': 0.9910652041435242, 'Train/mean precision': 0.9865534901618958, 'Train/mean recall': 0.9956184029579163, 'Train/mean hd95_metric': 1.0256420373916626} +Epoch [1827/4000] Validation [1/4] Loss: 0.56717 focal_loss 0.45752 dice_loss 0.10965 +Epoch [1827/4000] Validation [2/4] Loss: 0.24825 focal_loss 0.14532 dice_loss 0.10293 +Epoch [1827/4000] Validation [3/4] Loss: 0.21750 focal_loss 0.13481 dice_loss 0.08269 +Epoch [1827/4000] Validation [4/4] Loss: 0.21532 focal_loss 0.13457 dice_loss 0.08076 +Epoch [1827/4000] Validation metric {'Val/mean dice_metric': 0.9711592793464661, 'Val/mean miou_metric': 0.9540761709213257, 'Val/mean f1': 0.9722451567649841, 'Val/mean precision': 0.9727088809013367, 'Val/mean recall': 0.9717820286750793, 'Val/mean hd95_metric': 5.573155879974365} +Cheakpoint... +Epoch [1827/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711592793464661, 'Val/mean miou_metric': 0.9540761709213257, 'Val/mean f1': 0.9722451567649841, 'Val/mean precision': 0.9727088809013367, 'Val/mean recall': 0.9717820286750793, 'Val/mean hd95_metric': 5.573155879974365} +Epoch [1828/4000] Training [1/16] Loss: 0.00685 +Epoch [1828/4000] Training [2/16] Loss: 0.00565 +Epoch [1828/4000] Training [3/16] Loss: 0.00565 +Epoch [1828/4000] Training [4/16] Loss: 0.00668 +Epoch [1828/4000] Training [5/16] Loss: 0.00944 +Epoch [1828/4000] Training [6/16] Loss: 0.00675 +Epoch [1828/4000] Training [7/16] Loss: 0.00940 +Epoch [1828/4000] Training [8/16] Loss: 0.00589 +Epoch [1828/4000] Training [9/16] Loss: 0.00661 +Epoch [1828/4000] Training [10/16] Loss: 0.00724 +Epoch [1828/4000] Training [11/16] Loss: 0.00634 +Epoch [1828/4000] Training [12/16] Loss: 0.00752 +Epoch [1828/4000] Training [13/16] Loss: 0.00702 +Epoch [1828/4000] Training [14/16] Loss: 0.00673 +Epoch [1828/4000] Training [15/16] Loss: 0.00529 +Epoch [1828/4000] Training [16/16] Loss: 0.00658 +Epoch [1828/4000] Training metric {'Train/mean dice_metric': 0.9955071210861206, 'Train/mean miou_metric': 0.9908008575439453, 'Train/mean f1': 0.9914085268974304, 'Train/mean precision': 0.9868460297584534, 'Train/mean recall': 0.9960134029388428, 'Train/mean hd95_metric': 1.0123118162155151} +Epoch [1828/4000] Validation [1/4] Loss: 0.25725 focal_loss 0.18787 dice_loss 0.06938 +Epoch [1828/4000] Validation [2/4] Loss: 0.80667 focal_loss 0.51389 dice_loss 0.29279 +Epoch [1828/4000] Validation [3/4] Loss: 0.25019 focal_loss 0.16216 dice_loss 0.08804 +Epoch [1828/4000] Validation [4/4] Loss: 0.21571 focal_loss 0.13043 dice_loss 0.08528 +Epoch [1828/4000] Validation metric {'Val/mean dice_metric': 0.9692298173904419, 'Val/mean miou_metric': 0.9531185030937195, 'Val/mean f1': 0.9738108515739441, 'Val/mean precision': 0.9710173606872559, 'Val/mean recall': 0.9766204953193665, 'Val/mean hd95_metric': 5.861137866973877} +Cheakpoint... +Epoch [1828/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692298173904419, 'Val/mean miou_metric': 0.9531185030937195, 'Val/mean f1': 0.9738108515739441, 'Val/mean precision': 0.9710173606872559, 'Val/mean recall': 0.9766204953193665, 'Val/mean hd95_metric': 5.861137866973877} +Epoch [1829/4000] Training [1/16] Loss: 0.00994 +Epoch [1829/4000] Training [2/16] Loss: 0.00580 +Epoch [1829/4000] Training [3/16] Loss: 0.00495 +Epoch [1829/4000] Training [4/16] Loss: 0.00776 +Epoch [1829/4000] Training [5/16] Loss: 0.01005 +Epoch [1829/4000] Training [6/16] Loss: 0.00642 +Epoch [1829/4000] Training [7/16] Loss: 0.00662 +Epoch [1829/4000] Training [8/16] Loss: 0.00519 +Epoch [1829/4000] Training [9/16] Loss: 0.00592 +Epoch [1829/4000] Training [10/16] Loss: 0.00541 +Epoch [1829/4000] Training [11/16] Loss: 0.00645 +Epoch [1829/4000] Training [12/16] Loss: 0.00695 +Epoch [1829/4000] Training [13/16] Loss: 0.00653 +Epoch [1829/4000] Training [14/16] Loss: 0.00788 +Epoch [1829/4000] Training [15/16] Loss: 0.00623 +Epoch [1829/4000] Training [16/16] Loss: 0.00908 +Epoch [1829/4000] Training metric {'Train/mean dice_metric': 0.9953845739364624, 'Train/mean miou_metric': 0.9905513525009155, 'Train/mean f1': 0.9912267923355103, 'Train/mean precision': 0.9865854978561401, 'Train/mean recall': 0.9959118366241455, 'Train/mean hd95_metric': 1.0173002481460571} +Epoch [1829/4000] Validation [1/4] Loss: 0.29347 focal_loss 0.22243 dice_loss 0.07104 +Epoch [1829/4000] Validation [2/4] Loss: 0.21737 focal_loss 0.11917 dice_loss 0.09820 +Epoch [1829/4000] Validation [3/4] Loss: 0.16932 focal_loss 0.11116 dice_loss 0.05816 +Epoch [1829/4000] Validation [4/4] Loss: 0.33426 focal_loss 0.20994 dice_loss 0.12432 +Epoch [1829/4000] Validation metric {'Val/mean dice_metric': 0.9726072549819946, 'Val/mean miou_metric': 0.9552046060562134, 'Val/mean f1': 0.9734028577804565, 'Val/mean precision': 0.9726721048355103, 'Val/mean recall': 0.9741347432136536, 'Val/mean hd95_metric': 5.341769695281982} +Cheakpoint... +Epoch [1829/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726072549819946, 'Val/mean miou_metric': 0.9552046060562134, 'Val/mean f1': 0.9734028577804565, 'Val/mean precision': 0.9726721048355103, 'Val/mean recall': 0.9741347432136536, 'Val/mean hd95_metric': 5.341769695281982} +Epoch [1830/4000] Training [1/16] Loss: 0.00756 +Epoch [1830/4000] Training [2/16] Loss: 0.00764 +Epoch [1830/4000] Training [3/16] Loss: 0.00890 +Epoch [1830/4000] Training [4/16] Loss: 0.00751 +Epoch [1830/4000] Training [5/16] Loss: 0.00552 +Epoch [1830/4000] Training [6/16] Loss: 0.00500 +Epoch [1830/4000] Training [7/16] Loss: 0.00645 +Epoch [1830/4000] Training [8/16] Loss: 0.00861 +Epoch [1830/4000] Training [9/16] Loss: 0.00581 +Epoch [1830/4000] Training [10/16] Loss: 0.00495 +Epoch [1830/4000] Training [11/16] Loss: 0.00539 +Epoch [1830/4000] Training [12/16] Loss: 0.00761 +Epoch [1830/4000] Training [13/16] Loss: 0.00568 +Epoch [1830/4000] Training [14/16] Loss: 0.00712 +Epoch [1830/4000] Training [15/16] Loss: 0.00747 +Epoch [1830/4000] Training [16/16] Loss: 0.00682 +Epoch [1830/4000] Training metric {'Train/mean dice_metric': 0.9953293204307556, 'Train/mean miou_metric': 0.9904547929763794, 'Train/mean f1': 0.9914606213569641, 'Train/mean precision': 0.9870219826698303, 'Train/mean recall': 0.9959394335746765, 'Train/mean hd95_metric': 1.0167324542999268} +Epoch [1830/4000] Validation [1/4] Loss: 0.24647 focal_loss 0.18559 dice_loss 0.06088 +Epoch [1830/4000] Validation [2/4] Loss: 0.78064 focal_loss 0.50002 dice_loss 0.28062 +Epoch [1830/4000] Validation [3/4] Loss: 0.19969 focal_loss 0.12371 dice_loss 0.07598 +Epoch [1830/4000] Validation [4/4] Loss: 0.19126 focal_loss 0.09864 dice_loss 0.09262 +Epoch [1830/4000] Validation metric {'Val/mean dice_metric': 0.9705813527107239, 'Val/mean miou_metric': 0.9540989995002747, 'Val/mean f1': 0.9746133685112, 'Val/mean precision': 0.9732736349105835, 'Val/mean recall': 0.9759566783905029, 'Val/mean hd95_metric': 5.712601661682129} +Cheakpoint... +Epoch [1830/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705813527107239, 'Val/mean miou_metric': 0.9540989995002747, 'Val/mean f1': 0.9746133685112, 'Val/mean precision': 0.9732736349105835, 'Val/mean recall': 0.9759566783905029, 'Val/mean hd95_metric': 5.712601661682129} +Epoch [1831/4000] Training [1/16] Loss: 0.00559 +Epoch [1831/4000] Training [2/16] Loss: 0.00827 +Epoch [1831/4000] Training [3/16] Loss: 0.00688 +Epoch [1831/4000] Training [4/16] Loss: 0.00825 +Epoch [1831/4000] Training [5/16] Loss: 0.00528 +Epoch [1831/4000] Training [6/16] Loss: 0.00732 +Epoch [1831/4000] Training [7/16] Loss: 0.00711 +Epoch [1831/4000] Training [8/16] Loss: 0.00486 +Epoch [1831/4000] Training [9/16] Loss: 0.01090 +Epoch [1831/4000] Training [10/16] Loss: 0.00602 +Epoch [1831/4000] Training [11/16] Loss: 0.00684 +Epoch [1831/4000] Training [12/16] Loss: 0.00730 +Epoch [1831/4000] Training [13/16] Loss: 0.00721 +Epoch [1831/4000] Training [14/16] Loss: 0.00715 +Epoch [1831/4000] Training [15/16] Loss: 0.00718 +Epoch [1831/4000] Training [16/16] Loss: 0.00955 +Epoch [1831/4000] Training metric {'Train/mean dice_metric': 0.995063304901123, 'Train/mean miou_metric': 0.9899280071258545, 'Train/mean f1': 0.9909379482269287, 'Train/mean precision': 0.9863747358322144, 'Train/mean recall': 0.9955435991287231, 'Train/mean hd95_metric': 1.0454199314117432} +Epoch [1831/4000] Validation [1/4] Loss: 0.42304 focal_loss 0.32882 dice_loss 0.09422 +Epoch [1831/4000] Validation [2/4] Loss: 0.24604 focal_loss 0.14759 dice_loss 0.09846 +Epoch [1831/4000] Validation [3/4] Loss: 0.20100 focal_loss 0.12011 dice_loss 0.08089 +Epoch [1831/4000] Validation [4/4] Loss: 0.25655 focal_loss 0.15890 dice_loss 0.09765 +Epoch [1831/4000] Validation metric {'Val/mean dice_metric': 0.9716216921806335, 'Val/mean miou_metric': 0.9540902972221375, 'Val/mean f1': 0.9721255898475647, 'Val/mean precision': 0.9722837805747986, 'Val/mean recall': 0.9719673991203308, 'Val/mean hd95_metric': 5.378658294677734} +Cheakpoint... +Epoch [1831/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716216921806335, 'Val/mean miou_metric': 0.9540902972221375, 'Val/mean f1': 0.9721255898475647, 'Val/mean precision': 0.9722837805747986, 'Val/mean recall': 0.9719673991203308, 'Val/mean hd95_metric': 5.378658294677734} +Epoch [1832/4000] Training [1/16] Loss: 0.00563 +Epoch [1832/4000] Training [2/16] Loss: 0.00635 +Epoch [1832/4000] Training [3/16] Loss: 0.00668 +Epoch [1832/4000] Training [4/16] Loss: 0.00760 +Epoch [1832/4000] Training [5/16] Loss: 0.00609 +Epoch [1832/4000] Training [6/16] Loss: 0.00929 +Epoch [1832/4000] Training [7/16] Loss: 0.00970 +Epoch [1832/4000] Training [8/16] Loss: 0.00682 +Epoch [1832/4000] Training [9/16] Loss: 0.00945 +Epoch [1832/4000] Training [10/16] Loss: 0.00665 +Epoch [1832/4000] Training [11/16] Loss: 0.00956 +Epoch [1832/4000] Training [12/16] Loss: 0.00628 +Epoch [1832/4000] Training [13/16] Loss: 0.00584 +Epoch [1832/4000] Training [14/16] Loss: 0.00696 +Epoch [1832/4000] Training [15/16] Loss: 0.00872 +Epoch [1832/4000] Training [16/16] Loss: 0.00684 +Epoch [1832/4000] Training metric {'Train/mean dice_metric': 0.9951450228691101, 'Train/mean miou_metric': 0.9900627136230469, 'Train/mean f1': 0.9907218217849731, 'Train/mean precision': 0.985710859298706, 'Train/mean recall': 0.9957839250564575, 'Train/mean hd95_metric': 1.0182677507400513} +Epoch [1832/4000] Validation [1/4] Loss: 0.55835 focal_loss 0.44573 dice_loss 0.11263 +Epoch [1832/4000] Validation [2/4] Loss: 0.30126 focal_loss 0.17814 dice_loss 0.12312 +Epoch [1832/4000] Validation [3/4] Loss: 0.18904 focal_loss 0.11169 dice_loss 0.07735 +Epoch [1832/4000] Validation [4/4] Loss: 0.36700 focal_loss 0.23483 dice_loss 0.13217 +Epoch [1832/4000] Validation metric {'Val/mean dice_metric': 0.9701347351074219, 'Val/mean miou_metric': 0.9524446725845337, 'Val/mean f1': 0.9720980525016785, 'Val/mean precision': 0.9746763110160828, 'Val/mean recall': 0.9695333242416382, 'Val/mean hd95_metric': 5.439527988433838} +Cheakpoint... +Epoch [1832/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701347351074219, 'Val/mean miou_metric': 0.9524446725845337, 'Val/mean f1': 0.9720980525016785, 'Val/mean precision': 0.9746763110160828, 'Val/mean recall': 0.9695333242416382, 'Val/mean hd95_metric': 5.439527988433838} +Epoch [1833/4000] Training [1/16] Loss: 0.00487 +Epoch [1833/4000] Training [2/16] Loss: 0.00495 +Epoch [1833/4000] Training [3/16] Loss: 0.00817 +Epoch [1833/4000] Training [4/16] Loss: 0.00866 +Epoch [1833/4000] Training [5/16] Loss: 0.00819 +Epoch [1833/4000] Training [6/16] Loss: 0.00694 +Epoch [1833/4000] Training [7/16] Loss: 0.00598 +Epoch [1833/4000] Training [8/16] Loss: 0.00610 +Epoch [1833/4000] Training [9/16] Loss: 0.00693 +Epoch [1833/4000] Training [10/16] Loss: 0.00897 +Epoch [1833/4000] Training [11/16] Loss: 0.00665 +Epoch [1833/4000] Training [12/16] Loss: 0.01162 +Epoch [1833/4000] Training [13/16] Loss: 0.00774 +Epoch [1833/4000] Training [14/16] Loss: 0.00617 +Epoch [1833/4000] Training [15/16] Loss: 0.00786 +Epoch [1833/4000] Training [16/16] Loss: 0.00796 +Epoch [1833/4000] Training metric {'Train/mean dice_metric': 0.9952660799026489, 'Train/mean miou_metric': 0.9903191328048706, 'Train/mean f1': 0.9911044836044312, 'Train/mean precision': 0.9865838885307312, 'Train/mean recall': 0.9956667423248291, 'Train/mean hd95_metric': 1.0238749980926514} +Epoch [1833/4000] Validation [1/4] Loss: 0.45963 focal_loss 0.35684 dice_loss 0.10279 +Epoch [1833/4000] Validation [2/4] Loss: 0.50859 focal_loss 0.31043 dice_loss 0.19816 +Epoch [1833/4000] Validation [3/4] Loss: 0.30133 focal_loss 0.19653 dice_loss 0.10480 +Epoch [1833/4000] Validation [4/4] Loss: 0.24351 focal_loss 0.14763 dice_loss 0.09588 +Epoch [1833/4000] Validation metric {'Val/mean dice_metric': 0.9694440960884094, 'Val/mean miou_metric': 0.9523948431015015, 'Val/mean f1': 0.972065269947052, 'Val/mean precision': 0.9735419750213623, 'Val/mean recall': 0.9705930948257446, 'Val/mean hd95_metric': 5.410887718200684} +Cheakpoint... +Epoch [1833/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694440960884094, 'Val/mean miou_metric': 0.9523948431015015, 'Val/mean f1': 0.972065269947052, 'Val/mean precision': 0.9735419750213623, 'Val/mean recall': 0.9705930948257446, 'Val/mean hd95_metric': 5.410887718200684} +Epoch [1834/4000] Training [1/16] Loss: 0.00713 +Epoch [1834/4000] Training [2/16] Loss: 0.00599 +Epoch [1834/4000] Training [3/16] Loss: 0.00780 +Epoch [1834/4000] Training [4/16] Loss: 0.00626 +Epoch [1834/4000] Training [5/16] Loss: 0.00616 +Epoch [1834/4000] Training [6/16] Loss: 0.00472 +Epoch [1834/4000] Training [7/16] Loss: 0.00739 +Epoch [1834/4000] Training [8/16] Loss: 0.00649 +Epoch [1834/4000] Training [9/16] Loss: 0.00867 +Epoch [1834/4000] Training [10/16] Loss: 0.00494 +Epoch [1834/4000] Training [11/16] Loss: 0.00669 +Epoch [1834/4000] Training [12/16] Loss: 0.00759 +Epoch [1834/4000] Training [13/16] Loss: 0.00617 +Epoch [1834/4000] Training [14/16] Loss: 0.00886 +Epoch [1834/4000] Training [15/16] Loss: 0.00916 +Epoch [1834/4000] Training [16/16] Loss: 0.00512 +Epoch [1834/4000] Training metric {'Train/mean dice_metric': 0.9951830506324768, 'Train/mean miou_metric': 0.9901615381240845, 'Train/mean f1': 0.9911935329437256, 'Train/mean precision': 0.9865997433662415, 'Train/mean recall': 0.995830237865448, 'Train/mean hd95_metric': 1.0097936391830444} +Epoch [1834/4000] Validation [1/4] Loss: 0.43373 focal_loss 0.34016 dice_loss 0.09357 +Epoch [1834/4000] Validation [2/4] Loss: 0.28147 focal_loss 0.16801 dice_loss 0.11345 +Epoch [1834/4000] Validation [3/4] Loss: 0.27889 focal_loss 0.19179 dice_loss 0.08710 +Epoch [1834/4000] Validation [4/4] Loss: 0.31969 focal_loss 0.21347 dice_loss 0.10622 +Epoch [1834/4000] Validation metric {'Val/mean dice_metric': 0.9718500375747681, 'Val/mean miou_metric': 0.954256534576416, 'Val/mean f1': 0.9729185700416565, 'Val/mean precision': 0.9724805355072021, 'Val/mean recall': 0.9733568429946899, 'Val/mean hd95_metric': 5.470413684844971} +Cheakpoint... +Epoch [1834/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718500375747681, 'Val/mean miou_metric': 0.954256534576416, 'Val/mean f1': 0.9729185700416565, 'Val/mean precision': 0.9724805355072021, 'Val/mean recall': 0.9733568429946899, 'Val/mean hd95_metric': 5.470413684844971} +Epoch [1835/4000] Training [1/16] Loss: 0.00759 +Epoch [1835/4000] Training [2/16] Loss: 0.00753 +Epoch [1835/4000] Training [3/16] Loss: 0.00658 +Epoch [1835/4000] Training [4/16] Loss: 0.00791 +Epoch [1835/4000] Training [5/16] Loss: 0.00678 +Epoch [1835/4000] Training [6/16] Loss: 0.00648 +Epoch [1835/4000] Training [7/16] Loss: 0.00865 +Epoch [1835/4000] Training [8/16] Loss: 0.00587 +Epoch [1835/4000] Training [9/16] Loss: 0.00620 +Epoch [1835/4000] Training [10/16] Loss: 0.00644 +Epoch [1835/4000] Training [11/16] Loss: 0.00710 +Epoch [1835/4000] Training [12/16] Loss: 0.00579 +Epoch [1835/4000] Training [13/16] Loss: 0.00632 +Epoch [1835/4000] Training [14/16] Loss: 0.00544 +Epoch [1835/4000] Training [15/16] Loss: 0.00814 +Epoch [1835/4000] Training [16/16] Loss: 0.00543 +Epoch [1835/4000] Training metric {'Train/mean dice_metric': 0.9955438375473022, 'Train/mean miou_metric': 0.9908674955368042, 'Train/mean f1': 0.9913561940193176, 'Train/mean precision': 0.9868136644363403, 'Train/mean recall': 0.9959406852722168, 'Train/mean hd95_metric': 1.0184694528579712} +Epoch [1835/4000] Validation [1/4] Loss: 0.24673 focal_loss 0.18282 dice_loss 0.06391 +Epoch [1835/4000] Validation [2/4] Loss: 0.43988 focal_loss 0.29006 dice_loss 0.14982 +Epoch [1835/4000] Validation [3/4] Loss: 0.19372 focal_loss 0.12136 dice_loss 0.07236 +Epoch [1835/4000] Validation [4/4] Loss: 0.25365 focal_loss 0.15815 dice_loss 0.09551 +Epoch [1835/4000] Validation metric {'Val/mean dice_metric': 0.9722447395324707, 'Val/mean miou_metric': 0.955236554145813, 'Val/mean f1': 0.9734269976615906, 'Val/mean precision': 0.9704567193984985, 'Val/mean recall': 0.9764153957366943, 'Val/mean hd95_metric': 5.2576212882995605} +Cheakpoint... +Epoch [1835/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722447395324707, 'Val/mean miou_metric': 0.955236554145813, 'Val/mean f1': 0.9734269976615906, 'Val/mean precision': 0.9704567193984985, 'Val/mean recall': 0.9764153957366943, 'Val/mean hd95_metric': 5.2576212882995605} +Epoch [1836/4000] Training [1/16] Loss: 0.00572 +Epoch [1836/4000] Training [2/16] Loss: 0.00690 +Epoch [1836/4000] Training [3/16] Loss: 0.00654 +Epoch [1836/4000] Training [4/16] Loss: 0.00666 +Epoch [1836/4000] Training [5/16] Loss: 0.00591 +Epoch [1836/4000] Training [6/16] Loss: 0.00686 +Epoch [1836/4000] Training [7/16] Loss: 0.00603 +Epoch [1836/4000] Training [8/16] Loss: 0.00793 +Epoch [1836/4000] Training [9/16] Loss: 0.00652 +Epoch [1836/4000] Training [10/16] Loss: 0.00777 +Epoch [1836/4000] Training [11/16] Loss: 0.00579 +Epoch [1836/4000] Training [12/16] Loss: 0.00625 +Epoch [1836/4000] Training [13/16] Loss: 0.00685 +Epoch [1836/4000] Training [14/16] Loss: 0.00575 +Epoch [1836/4000] Training [15/16] Loss: 0.00970 +Epoch [1836/4000] Training [16/16] Loss: 0.01019 +Epoch [1836/4000] Training metric {'Train/mean dice_metric': 0.9954464435577393, 'Train/mean miou_metric': 0.9906660318374634, 'Train/mean f1': 0.9911498427391052, 'Train/mean precision': 0.9865025281906128, 'Train/mean recall': 0.9958410859107971, 'Train/mean hd95_metric': 1.4510174989700317} +Epoch [1836/4000] Validation [1/4] Loss: 0.25367 focal_loss 0.18361 dice_loss 0.07006 +Epoch [1836/4000] Validation [2/4] Loss: 0.24945 focal_loss 0.14260 dice_loss 0.10685 +Epoch [1836/4000] Validation [3/4] Loss: 0.31865 focal_loss 0.22890 dice_loss 0.08975 +Epoch [1836/4000] Validation [4/4] Loss: 0.22770 focal_loss 0.13873 dice_loss 0.08897 +Epoch [1836/4000] Validation metric {'Val/mean dice_metric': 0.9733104705810547, 'Val/mean miou_metric': 0.9562074542045593, 'Val/mean f1': 0.9738091230392456, 'Val/mean precision': 0.9715590476989746, 'Val/mean recall': 0.9760696291923523, 'Val/mean hd95_metric': 5.756739616394043} +Cheakpoint... +Epoch [1836/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733104705810547, 'Val/mean miou_metric': 0.9562074542045593, 'Val/mean f1': 0.9738091230392456, 'Val/mean precision': 0.9715590476989746, 'Val/mean recall': 0.9760696291923523, 'Val/mean hd95_metric': 5.756739616394043} +Epoch [1837/4000] Training [1/16] Loss: 0.00674 +Epoch [1837/4000] Training [2/16] Loss: 0.00826 +Epoch [1837/4000] Training [3/16] Loss: 0.00580 +Epoch [1837/4000] Training [4/16] Loss: 0.00643 +Epoch [1837/4000] Training [5/16] Loss: 0.00715 +Epoch [1837/4000] Training [6/16] Loss: 0.00706 +Epoch [1837/4000] Training [7/16] Loss: 0.00762 +Epoch [1837/4000] Training [8/16] Loss: 0.00916 +Epoch [1837/4000] Training [9/16] Loss: 0.00656 +Epoch [1837/4000] Training [10/16] Loss: 0.00704 +Epoch [1837/4000] Training [11/16] Loss: 0.00659 +Epoch [1837/4000] Training [12/16] Loss: 0.00772 +Epoch [1837/4000] Training [13/16] Loss: 0.00508 +Epoch [1837/4000] Training [14/16] Loss: 0.00838 +Epoch [1837/4000] Training [15/16] Loss: 0.00816 +Epoch [1837/4000] Training [16/16] Loss: 0.00678 +Epoch [1837/4000] Training metric {'Train/mean dice_metric': 0.9952654838562012, 'Train/mean miou_metric': 0.9903208017349243, 'Train/mean f1': 0.9911345839500427, 'Train/mean precision': 0.9868057370185852, 'Train/mean recall': 0.9955016374588013, 'Train/mean hd95_metric': 1.0526704788208008} +Epoch [1837/4000] Validation [1/4] Loss: 0.54032 focal_loss 0.42526 dice_loss 0.11506 +Epoch [1837/4000] Validation [2/4] Loss: 0.24408 focal_loss 0.14030 dice_loss 0.10377 +Epoch [1837/4000] Validation [3/4] Loss: 0.20182 focal_loss 0.12477 dice_loss 0.07705 +Epoch [1837/4000] Validation [4/4] Loss: 0.27671 focal_loss 0.16752 dice_loss 0.10919 +Epoch [1837/4000] Validation metric {'Val/mean dice_metric': 0.9728361368179321, 'Val/mean miou_metric': 0.9548219442367554, 'Val/mean f1': 0.9725924730300903, 'Val/mean precision': 0.9736315011978149, 'Val/mean recall': 0.9715557098388672, 'Val/mean hd95_metric': 5.50153112411499} +Cheakpoint... +Epoch [1837/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728361368179321, 'Val/mean miou_metric': 0.9548219442367554, 'Val/mean f1': 0.9725924730300903, 'Val/mean precision': 0.9736315011978149, 'Val/mean recall': 0.9715557098388672, 'Val/mean hd95_metric': 5.50153112411499} +Epoch [1838/4000] Training [1/16] Loss: 0.00482 +Epoch [1838/4000] Training [2/16] Loss: 0.00594 +Epoch [1838/4000] Training [3/16] Loss: 0.00863 +Epoch [1838/4000] Training [4/16] Loss: 0.00629 +Epoch [1838/4000] Training [5/16] Loss: 0.00580 +Epoch [1838/4000] Training [6/16] Loss: 0.00564 +Epoch [1838/4000] Training [7/16] Loss: 0.00604 +Epoch [1838/4000] Training [8/16] Loss: 0.00649 +Epoch [1838/4000] Training [9/16] Loss: 0.00844 +Epoch [1838/4000] Training [10/16] Loss: 0.00615 +Epoch [1838/4000] Training [11/16] Loss: 0.00686 +Epoch [1838/4000] Training [12/16] Loss: 0.00624 +Epoch [1838/4000] Training [13/16] Loss: 0.01443 +Epoch [1838/4000] Training [14/16] Loss: 0.01132 +Epoch [1838/4000] Training [15/16] Loss: 0.00570 +Epoch [1838/4000] Training [16/16] Loss: 0.00558 +Epoch [1838/4000] Training metric {'Train/mean dice_metric': 0.9952194690704346, 'Train/mean miou_metric': 0.990243673324585, 'Train/mean f1': 0.9911489486694336, 'Train/mean precision': 0.9865471124649048, 'Train/mean recall': 0.9957939386367798, 'Train/mean hd95_metric': 1.0647532939910889} +Epoch [1838/4000] Validation [1/4] Loss: 0.56237 focal_loss 0.43220 dice_loss 0.13018 +Epoch [1838/4000] Validation [2/4] Loss: 0.39837 focal_loss 0.23413 dice_loss 0.16424 +Epoch [1838/4000] Validation [3/4] Loss: 0.18002 focal_loss 0.11990 dice_loss 0.06012 +Epoch [1838/4000] Validation [4/4] Loss: 0.21758 focal_loss 0.12219 dice_loss 0.09539 +Epoch [1838/4000] Validation metric {'Val/mean dice_metric': 0.9700435400009155, 'Val/mean miou_metric': 0.9528670310974121, 'Val/mean f1': 0.9716432690620422, 'Val/mean precision': 0.9731261134147644, 'Val/mean recall': 0.9701648950576782, 'Val/mean hd95_metric': 5.117622375488281} +Cheakpoint... +Epoch [1838/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700435400009155, 'Val/mean miou_metric': 0.9528670310974121, 'Val/mean f1': 0.9716432690620422, 'Val/mean precision': 0.9731261134147644, 'Val/mean recall': 0.9701648950576782, 'Val/mean hd95_metric': 5.117622375488281} +Epoch [1839/4000] Training [1/16] Loss: 0.01389 +Epoch [1839/4000] Training [2/16] Loss: 0.00765 +Epoch [1839/4000] Training [3/16] Loss: 0.00600 +Epoch [1839/4000] Training [4/16] Loss: 0.00764 +Epoch [1839/4000] Training [5/16] Loss: 0.01587 +Epoch [1839/4000] Training [6/16] Loss: 0.00594 +Epoch [1839/4000] Training [7/16] Loss: 0.00621 +Epoch [1839/4000] Training [8/16] Loss: 0.00671 +Epoch [1839/4000] Training [9/16] Loss: 0.00555 +Epoch [1839/4000] Training [10/16] Loss: 0.00849 +Epoch [1839/4000] Training [11/16] Loss: 0.00607 +Epoch [1839/4000] Training [12/16] Loss: 0.00674 +Epoch [1839/4000] Training [13/16] Loss: 0.00583 +Epoch [1839/4000] Training [14/16] Loss: 0.00576 +Epoch [1839/4000] Training [15/16] Loss: 0.00625 +Epoch [1839/4000] Training [16/16] Loss: 0.00783 +Epoch [1839/4000] Training metric {'Train/mean dice_metric': 0.9950259923934937, 'Train/mean miou_metric': 0.9898607730865479, 'Train/mean f1': 0.9910019040107727, 'Train/mean precision': 0.9863200187683105, 'Train/mean recall': 0.9957284927368164, 'Train/mean hd95_metric': 1.3381824493408203} +Epoch [1839/4000] Validation [1/4] Loss: 0.48242 focal_loss 0.37483 dice_loss 0.10759 +Epoch [1839/4000] Validation [2/4] Loss: 0.22125 focal_loss 0.12480 dice_loss 0.09645 +Epoch [1839/4000] Validation [3/4] Loss: 0.28336 focal_loss 0.18435 dice_loss 0.09901 +Epoch [1839/4000] Validation [4/4] Loss: 0.30476 focal_loss 0.18811 dice_loss 0.11665 +Epoch [1839/4000] Validation metric {'Val/mean dice_metric': 0.970324695110321, 'Val/mean miou_metric': 0.9522992372512817, 'Val/mean f1': 0.9718295335769653, 'Val/mean precision': 0.9717426300048828, 'Val/mean recall': 0.9719165563583374, 'Val/mean hd95_metric': 5.7187581062316895} +Cheakpoint... +Epoch [1839/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970324695110321, 'Val/mean miou_metric': 0.9522992372512817, 'Val/mean f1': 0.9718295335769653, 'Val/mean precision': 0.9717426300048828, 'Val/mean recall': 0.9719165563583374, 'Val/mean hd95_metric': 5.7187581062316895} +Epoch [1840/4000] Training [1/16] Loss: 0.00805 +Epoch [1840/4000] Training [2/16] Loss: 0.00870 +Epoch [1840/4000] Training [3/16] Loss: 0.00544 +Epoch [1840/4000] Training [4/16] Loss: 0.00651 +Epoch [1840/4000] Training [5/16] Loss: 0.00679 +Epoch [1840/4000] Training [6/16] Loss: 0.00688 +Epoch [1840/4000] Training [7/16] Loss: 0.00672 +Epoch [1840/4000] Training [8/16] Loss: 0.00577 +Epoch [1840/4000] Training [9/16] Loss: 0.00657 +Epoch [1840/4000] Training [10/16] Loss: 0.00592 +Epoch [1840/4000] Training [11/16] Loss: 0.00786 +Epoch [1840/4000] Training [12/16] Loss: 0.00586 +Epoch [1840/4000] Training [13/16] Loss: 0.00560 +Epoch [1840/4000] Training [14/16] Loss: 0.00667 +Epoch [1840/4000] Training [15/16] Loss: 0.00696 +Epoch [1840/4000] Training [16/16] Loss: 0.00758 +Epoch [1840/4000] Training metric {'Train/mean dice_metric': 0.9952836036682129, 'Train/mean miou_metric': 0.9903442859649658, 'Train/mean f1': 0.991161048412323, 'Train/mean precision': 0.9866383075714111, 'Train/mean recall': 0.9957254528999329, 'Train/mean hd95_metric': 1.0113271474838257} +Epoch [1840/4000] Validation [1/4] Loss: 0.50860 focal_loss 0.39816 dice_loss 0.11044 +Epoch [1840/4000] Validation [2/4] Loss: 0.57345 focal_loss 0.37502 dice_loss 0.19843 +Epoch [1840/4000] Validation [3/4] Loss: 0.17353 focal_loss 0.11698 dice_loss 0.05655 +Epoch [1840/4000] Validation [4/4] Loss: 0.33108 focal_loss 0.20980 dice_loss 0.12128 +Epoch [1840/4000] Validation metric {'Val/mean dice_metric': 0.9708009958267212, 'Val/mean miou_metric': 0.9538071751594543, 'Val/mean f1': 0.9719838500022888, 'Val/mean precision': 0.9738099575042725, 'Val/mean recall': 0.9701646566390991, 'Val/mean hd95_metric': 4.474248886108398} +Cheakpoint... +Epoch [1840/4000] best acc:tensor([0.9745], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708009958267212, 'Val/mean miou_metric': 0.9538071751594543, 'Val/mean f1': 0.9719838500022888, 'Val/mean precision': 0.9738099575042725, 'Val/mean recall': 0.9701646566390991, 'Val/mean hd95_metric': 4.474248886108398} +Epoch [1841/4000] Training [1/16] Loss: 0.00685 +Epoch [1841/4000] Training [2/16] Loss: 0.01467 +Epoch [1841/4000] Training [3/16] Loss: 0.00730 +Epoch [1841/4000] Training [4/16] Loss: 0.00638 +Epoch [1841/4000] Training [5/16] Loss: 0.00650 +Epoch [1841/4000] Training [6/16] Loss: 0.00558 +Epoch [1841/4000] Training [7/16] Loss: 0.00529 +Epoch [1841/4000] Training [8/16] Loss: 0.00666 +Epoch [1841/4000] Training [9/16] Loss: 0.00735 +Epoch [1841/4000] Training [10/16] Loss: 0.00654 +Epoch [1841/4000] Training [11/16] Loss: 0.00763 +Epoch [1841/4000] Training [12/16] Loss: 0.00755 +Epoch [1841/4000] Training [13/16] Loss: 0.00525 +Epoch [1841/4000] Training [14/16] Loss: 0.00632 +Epoch [1841/4000] Training [15/16] Loss: 0.01112 +Epoch [1841/4000] Training [16/16] Loss: 0.00620 +Epoch [1841/4000] Training metric {'Train/mean dice_metric': 0.995172917842865, 'Train/mean miou_metric': 0.9901472330093384, 'Train/mean f1': 0.9911056756973267, 'Train/mean precision': 0.9865829348564148, 'Train/mean recall': 0.9956700801849365, 'Train/mean hd95_metric': 1.0878150463104248} +Epoch [1841/4000] Validation [1/4] Loss: 0.47711 focal_loss 0.37108 dice_loss 0.10603 +Epoch [1841/4000] Validation [2/4] Loss: 0.24169 focal_loss 0.14104 dice_loss 0.10065 +Epoch [1841/4000] Validation [3/4] Loss: 0.16945 focal_loss 0.11475 dice_loss 0.05470 +Epoch [1841/4000] Validation [4/4] Loss: 0.24913 focal_loss 0.14970 dice_loss 0.09943 +Epoch [1841/4000] Validation metric {'Val/mean dice_metric': 0.9745834469795227, 'Val/mean miou_metric': 0.9573799967765808, 'Val/mean f1': 0.9743310809135437, 'Val/mean precision': 0.9726064801216125, 'Val/mean recall': 0.9760618805885315, 'Val/mean hd95_metric': 4.934278964996338} +Cheakpoint... +Epoch [1841/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745834469795227, 'Val/mean miou_metric': 0.9573799967765808, 'Val/mean f1': 0.9743310809135437, 'Val/mean precision': 0.9726064801216125, 'Val/mean recall': 0.9760618805885315, 'Val/mean hd95_metric': 4.934278964996338} +Epoch [1842/4000] Training [1/16] Loss: 0.00654 +Epoch [1842/4000] Training [2/16] Loss: 0.00504 +Epoch [1842/4000] Training [3/16] Loss: 0.00552 +Epoch [1842/4000] Training [4/16] Loss: 0.00662 +Epoch [1842/4000] Training [5/16] Loss: 0.00664 +Epoch [1842/4000] Training [6/16] Loss: 0.00503 +Epoch [1842/4000] Training [7/16] Loss: 0.00591 +Epoch [1842/4000] Training [8/16] Loss: 0.02127 +Epoch [1842/4000] Training [9/16] Loss: 0.00753 +Epoch [1842/4000] Training [10/16] Loss: 0.00570 +Epoch [1842/4000] Training [11/16] Loss: 0.00661 +Epoch [1842/4000] Training [12/16] Loss: 0.00535 +Epoch [1842/4000] Training [13/16] Loss: 0.00619 +Epoch [1842/4000] Training [14/16] Loss: 0.00816 +Epoch [1842/4000] Training [15/16] Loss: 0.00503 +Epoch [1842/4000] Training [16/16] Loss: 0.00558 +Epoch [1842/4000] Training metric {'Train/mean dice_metric': 0.9954968690872192, 'Train/mean miou_metric': 0.9907858371734619, 'Train/mean f1': 0.9910784959793091, 'Train/mean precision': 0.986230194568634, 'Train/mean recall': 0.9959747195243835, 'Train/mean hd95_metric': 1.0544650554656982} +Epoch [1842/4000] Validation [1/4] Loss: 0.33959 focal_loss 0.26106 dice_loss 0.07853 +Epoch [1842/4000] Validation [2/4] Loss: 0.20834 focal_loss 0.11827 dice_loss 0.09006 +Epoch [1842/4000] Validation [3/4] Loss: 0.31310 focal_loss 0.22063 dice_loss 0.09247 +Epoch [1842/4000] Validation [4/4] Loss: 0.22631 focal_loss 0.13730 dice_loss 0.08901 +Epoch [1842/4000] Validation metric {'Val/mean dice_metric': 0.972308337688446, 'Val/mean miou_metric': 0.9555503129959106, 'Val/mean f1': 0.9742538332939148, 'Val/mean precision': 0.9715344309806824, 'Val/mean recall': 0.9769884943962097, 'Val/mean hd95_metric': 5.458272933959961} +Cheakpoint... +Epoch [1842/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972308337688446, 'Val/mean miou_metric': 0.9555503129959106, 'Val/mean f1': 0.9742538332939148, 'Val/mean precision': 0.9715344309806824, 'Val/mean recall': 0.9769884943962097, 'Val/mean hd95_metric': 5.458272933959961} +Epoch [1843/4000] Training [1/16] Loss: 0.00610 +Epoch [1843/4000] Training [2/16] Loss: 0.00887 +Epoch [1843/4000] Training [3/16] Loss: 0.00998 +Epoch [1843/4000] Training [4/16] Loss: 0.00690 +Epoch [1843/4000] Training [5/16] Loss: 0.00580 +Epoch [1843/4000] Training [6/16] Loss: 0.00513 +Epoch [1843/4000] Training [7/16] Loss: 0.00774 +Epoch [1843/4000] Training [8/16] Loss: 0.00460 +Epoch [1843/4000] Training [9/16] Loss: 0.00490 +Epoch [1843/4000] Training [10/16] Loss: 0.00613 +Epoch [1843/4000] Training [11/16] Loss: 0.00505 +Epoch [1843/4000] Training [12/16] Loss: 0.00540 +Epoch [1843/4000] Training [13/16] Loss: 0.00653 +Epoch [1843/4000] Training [14/16] Loss: 0.00576 +Epoch [1843/4000] Training [15/16] Loss: 0.00483 +Epoch [1843/4000] Training [16/16] Loss: 0.00803 +Epoch [1843/4000] Training metric {'Train/mean dice_metric': 0.9954994916915894, 'Train/mean miou_metric': 0.9907656311988831, 'Train/mean f1': 0.9906371235847473, 'Train/mean precision': 0.9853327870368958, 'Train/mean recall': 0.9959988594055176, 'Train/mean hd95_metric': 1.032282829284668} +Epoch [1843/4000] Validation [1/4] Loss: 0.31021 focal_loss 0.23317 dice_loss 0.07704 +Epoch [1843/4000] Validation [2/4] Loss: 0.22209 focal_loss 0.12670 dice_loss 0.09539 +Epoch [1843/4000] Validation [3/4] Loss: 0.33194 focal_loss 0.23707 dice_loss 0.09487 +Epoch [1843/4000] Validation [4/4] Loss: 0.32668 focal_loss 0.20612 dice_loss 0.12056 +Epoch [1843/4000] Validation metric {'Val/mean dice_metric': 0.9732601046562195, 'Val/mean miou_metric': 0.9560809135437012, 'Val/mean f1': 0.9734204411506653, 'Val/mean precision': 0.9705147743225098, 'Val/mean recall': 0.97634357213974, 'Val/mean hd95_metric': 5.40762186050415} +Cheakpoint... +Epoch [1843/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732601046562195, 'Val/mean miou_metric': 0.9560809135437012, 'Val/mean f1': 0.9734204411506653, 'Val/mean precision': 0.9705147743225098, 'Val/mean recall': 0.97634357213974, 'Val/mean hd95_metric': 5.40762186050415} +Epoch [1844/4000] Training [1/16] Loss: 0.00554 +Epoch [1844/4000] Training [2/16] Loss: 0.00707 +Epoch [1844/4000] Training [3/16] Loss: 0.00805 +Epoch [1844/4000] Training [4/16] Loss: 0.00621 +Epoch [1844/4000] Training [5/16] Loss: 0.00684 +Epoch [1844/4000] Training [6/16] Loss: 0.00796 +Epoch [1844/4000] Training [7/16] Loss: 0.00635 +Epoch [1844/4000] Training [8/16] Loss: 0.01048 +Epoch [1844/4000] Training [9/16] Loss: 0.00551 +Epoch [1844/4000] Training [10/16] Loss: 0.00903 +Epoch [1844/4000] Training [11/16] Loss: 0.00855 +Epoch [1844/4000] Training [12/16] Loss: 0.00691 +Epoch [1844/4000] Training [13/16] Loss: 0.00546 +Epoch [1844/4000] Training [14/16] Loss: 0.00714 +Epoch [1844/4000] Training [15/16] Loss: 0.00512 +Epoch [1844/4000] Training [16/16] Loss: 0.00618 +Epoch [1844/4000] Training metric {'Train/mean dice_metric': 0.9956136345863342, 'Train/mean miou_metric': 0.9910105466842651, 'Train/mean f1': 0.9915805459022522, 'Train/mean precision': 0.9871565103530884, 'Train/mean recall': 0.9960444569587708, 'Train/mean hd95_metric': 1.0162959098815918} +Epoch [1844/4000] Validation [1/4] Loss: 0.28675 focal_loss 0.21001 dice_loss 0.07674 +Epoch [1844/4000] Validation [2/4] Loss: 0.25185 focal_loss 0.15015 dice_loss 0.10170 +Epoch [1844/4000] Validation [3/4] Loss: 0.17229 focal_loss 0.11570 dice_loss 0.05659 +Epoch [1844/4000] Validation [4/4] Loss: 0.36794 focal_loss 0.23381 dice_loss 0.13413 +Epoch [1844/4000] Validation metric {'Val/mean dice_metric': 0.9738931655883789, 'Val/mean miou_metric': 0.9567903280258179, 'Val/mean f1': 0.9743000268936157, 'Val/mean precision': 0.9730219841003418, 'Val/mean recall': 0.9755814671516418, 'Val/mean hd95_metric': 5.353302955627441} +Cheakpoint... +Epoch [1844/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738931655883789, 'Val/mean miou_metric': 0.9567903280258179, 'Val/mean f1': 0.9743000268936157, 'Val/mean precision': 0.9730219841003418, 'Val/mean recall': 0.9755814671516418, 'Val/mean hd95_metric': 5.353302955627441} +Epoch [1845/4000] Training [1/16] Loss: 0.00631 +Epoch [1845/4000] Training [2/16] Loss: 0.00610 +Epoch [1845/4000] Training [3/16] Loss: 0.00653 +Epoch [1845/4000] Training [4/16] Loss: 0.00685 +Epoch [1845/4000] Training [5/16] Loss: 0.00454 +Epoch [1845/4000] Training [6/16] Loss: 0.00653 +Epoch [1845/4000] Training [7/16] Loss: 0.00583 +Epoch [1845/4000] Training [8/16] Loss: 0.00652 +Epoch [1845/4000] Training [9/16] Loss: 0.00586 +Epoch [1845/4000] Training [10/16] Loss: 0.00657 +Epoch [1845/4000] Training [11/16] Loss: 0.00784 +Epoch [1845/4000] Training [12/16] Loss: 0.01249 +Epoch [1845/4000] Training [13/16] Loss: 0.00540 +Epoch [1845/4000] Training [14/16] Loss: 0.00573 +Epoch [1845/4000] Training [15/16] Loss: 0.00981 +Epoch [1845/4000] Training [16/16] Loss: 0.00980 +Epoch [1845/4000] Training metric {'Train/mean dice_metric': 0.9955074191093445, 'Train/mean miou_metric': 0.9907788038253784, 'Train/mean f1': 0.9907604455947876, 'Train/mean precision': 0.9856643080711365, 'Train/mean recall': 0.995909571647644, 'Train/mean hd95_metric': 1.0251476764678955} +Epoch [1845/4000] Validation [1/4] Loss: 0.42048 focal_loss 0.32697 dice_loss 0.09352 +Epoch [1845/4000] Validation [2/4] Loss: 0.25781 focal_loss 0.15887 dice_loss 0.09895 +Epoch [1845/4000] Validation [3/4] Loss: 0.30288 focal_loss 0.21360 dice_loss 0.08928 +Epoch [1845/4000] Validation [4/4] Loss: 0.25911 focal_loss 0.16769 dice_loss 0.09142 +Epoch [1845/4000] Validation metric {'Val/mean dice_metric': 0.9741758108139038, 'Val/mean miou_metric': 0.9569493532180786, 'Val/mean f1': 0.9733452200889587, 'Val/mean precision': 0.9721532464027405, 'Val/mean recall': 0.9745402336120605, 'Val/mean hd95_metric': 5.670225143432617} +Cheakpoint... +Epoch [1845/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741758108139038, 'Val/mean miou_metric': 0.9569493532180786, 'Val/mean f1': 0.9733452200889587, 'Val/mean precision': 0.9721532464027405, 'Val/mean recall': 0.9745402336120605, 'Val/mean hd95_metric': 5.670225143432617} +Epoch [1846/4000] Training [1/16] Loss: 0.00566 +Epoch [1846/4000] Training [2/16] Loss: 0.00511 +Epoch [1846/4000] Training [3/16] Loss: 0.00614 +Epoch [1846/4000] Training [4/16] Loss: 0.00838 +Epoch [1846/4000] Training [5/16] Loss: 0.00653 +Epoch [1846/4000] Training [6/16] Loss: 0.00558 +Epoch [1846/4000] Training [7/16] Loss: 0.00588 +Epoch [1846/4000] Training [8/16] Loss: 0.00664 +Epoch [1846/4000] Training [9/16] Loss: 0.00595 +Epoch [1846/4000] Training [10/16] Loss: 0.00753 +Epoch [1846/4000] Training [11/16] Loss: 0.00806 +Epoch [1846/4000] Training [12/16] Loss: 0.00627 +Epoch [1846/4000] Training [13/16] Loss: 0.01013 +Epoch [1846/4000] Training [14/16] Loss: 0.00699 +Epoch [1846/4000] Training [15/16] Loss: 0.00543 +Epoch [1846/4000] Training [16/16] Loss: 0.00739 +Epoch [1846/4000] Training metric {'Train/mean dice_metric': 0.9953281879425049, 'Train/mean miou_metric': 0.9904423952102661, 'Train/mean f1': 0.9912710189819336, 'Train/mean precision': 0.986783504486084, 'Train/mean recall': 0.9957994818687439, 'Train/mean hd95_metric': 1.0599510669708252} +Epoch [1846/4000] Validation [1/4] Loss: 0.23431 focal_loss 0.17028 dice_loss 0.06403 +Epoch [1846/4000] Validation [2/4] Loss: 0.52009 focal_loss 0.34843 dice_loss 0.17165 +Epoch [1846/4000] Validation [3/4] Loss: 0.27323 focal_loss 0.18420 dice_loss 0.08903 +Epoch [1846/4000] Validation [4/4] Loss: 0.32110 focal_loss 0.19869 dice_loss 0.12241 +Epoch [1846/4000] Validation metric {'Val/mean dice_metric': 0.9734988212585449, 'Val/mean miou_metric': 0.9568687677383423, 'Val/mean f1': 0.9746264815330505, 'Val/mean precision': 0.9720157980918884, 'Val/mean recall': 0.9772512912750244, 'Val/mean hd95_metric': 5.226275444030762} +Cheakpoint... +Epoch [1846/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734988212585449, 'Val/mean miou_metric': 0.9568687677383423, 'Val/mean f1': 0.9746264815330505, 'Val/mean precision': 0.9720157980918884, 'Val/mean recall': 0.9772512912750244, 'Val/mean hd95_metric': 5.226275444030762} +Epoch [1847/4000] Training [1/16] Loss: 0.00503 +Epoch [1847/4000] Training [2/16] Loss: 0.01070 +Epoch [1847/4000] Training [3/16] Loss: 0.00606 +Epoch [1847/4000] Training [4/16] Loss: 0.01360 +Epoch [1847/4000] Training [5/16] Loss: 0.00717 +Epoch [1847/4000] Training [6/16] Loss: 0.00628 +Epoch [1847/4000] Training [7/16] Loss: 0.01140 +Epoch [1847/4000] Training [8/16] Loss: 0.00878 +Epoch [1847/4000] Training [9/16] Loss: 0.03526 +Epoch [1847/4000] Training [10/16] Loss: 0.00799 +Epoch [1847/4000] Training [11/16] Loss: 0.00577 +Epoch [1847/4000] Training [12/16] Loss: 0.00611 +Epoch [1847/4000] Training [13/16] Loss: 0.00905 +Epoch [1847/4000] Training [14/16] Loss: 0.00511 +Epoch [1847/4000] Training [15/16] Loss: 0.00621 +Epoch [1847/4000] Training [16/16] Loss: 0.00973 +Epoch [1847/4000] Training metric {'Train/mean dice_metric': 0.9948279857635498, 'Train/mean miou_metric': 0.9894742369651794, 'Train/mean f1': 0.9907976984977722, 'Train/mean precision': 0.9861456155776978, 'Train/mean recall': 0.9954939484596252, 'Train/mean hd95_metric': 1.2437682151794434} +Epoch [1847/4000] Validation [1/4] Loss: 0.24474 focal_loss 0.18207 dice_loss 0.06267 +Epoch [1847/4000] Validation [2/4] Loss: 0.73288 focal_loss 0.46430 dice_loss 0.26858 +Epoch [1847/4000] Validation [3/4] Loss: 0.15301 focal_loss 0.09627 dice_loss 0.05674 +Epoch [1847/4000] Validation [4/4] Loss: 0.32391 focal_loss 0.18679 dice_loss 0.13712 +Epoch [1847/4000] Validation metric {'Val/mean dice_metric': 0.9686505198478699, 'Val/mean miou_metric': 0.9516990780830383, 'Val/mean f1': 0.9735676050186157, 'Val/mean precision': 0.9718536734580994, 'Val/mean recall': 0.9752877950668335, 'Val/mean hd95_metric': 5.770329475402832} +Cheakpoint... +Epoch [1847/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686505198478699, 'Val/mean miou_metric': 0.9516990780830383, 'Val/mean f1': 0.9735676050186157, 'Val/mean precision': 0.9718536734580994, 'Val/mean recall': 0.9752877950668335, 'Val/mean hd95_metric': 5.770329475402832} +Epoch [1848/4000] Training [1/16] Loss: 0.00546 +Epoch [1848/4000] Training [2/16] Loss: 0.00672 +Epoch [1848/4000] Training [3/16] Loss: 0.00567 +Epoch [1848/4000] Training [4/16] Loss: 0.00508 +Epoch [1848/4000] Training [5/16] Loss: 0.00607 +Epoch [1848/4000] Training [6/16] Loss: 0.00743 +Epoch [1848/4000] Training [7/16] Loss: 0.00617 +Epoch [1848/4000] Training [8/16] Loss: 0.00664 +Epoch [1848/4000] Training [9/16] Loss: 0.00553 +Epoch [1848/4000] Training [10/16] Loss: 0.00693 +Epoch [1848/4000] Training [11/16] Loss: 0.00533 +Epoch [1848/4000] Training [12/16] Loss: 0.00713 +Epoch [1848/4000] Training [13/16] Loss: 0.00502 +Epoch [1848/4000] Training [14/16] Loss: 0.00960 +Epoch [1848/4000] Training [15/16] Loss: 0.00692 +Epoch [1848/4000] Training [16/16] Loss: 0.00653 +Epoch [1848/4000] Training metric {'Train/mean dice_metric': 0.9955277442932129, 'Train/mean miou_metric': 0.9908308982849121, 'Train/mean f1': 0.9913060665130615, 'Train/mean precision': 0.9868251085281372, 'Train/mean recall': 0.9958280920982361, 'Train/mean hd95_metric': 1.037886619567871} +Epoch [1848/4000] Validation [1/4] Loss: 0.22780 focal_loss 0.16354 dice_loss 0.06426 +Epoch [1848/4000] Validation [2/4] Loss: 0.56416 focal_loss 0.36154 dice_loss 0.20262 +Epoch [1848/4000] Validation [3/4] Loss: 0.33263 focal_loss 0.23475 dice_loss 0.09788 +Epoch [1848/4000] Validation [4/4] Loss: 0.25057 focal_loss 0.14752 dice_loss 0.10305 +Epoch [1848/4000] Validation metric {'Val/mean dice_metric': 0.9676817059516907, 'Val/mean miou_metric': 0.9510000348091125, 'Val/mean f1': 0.9723297953605652, 'Val/mean precision': 0.972011387348175, 'Val/mean recall': 0.9726483225822449, 'Val/mean hd95_metric': 5.650938510894775} +Cheakpoint... +Epoch [1848/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676817059516907, 'Val/mean miou_metric': 0.9510000348091125, 'Val/mean f1': 0.9723297953605652, 'Val/mean precision': 0.972011387348175, 'Val/mean recall': 0.9726483225822449, 'Val/mean hd95_metric': 5.650938510894775} +Epoch [1849/4000] Training [1/16] Loss: 0.00596 +Epoch [1849/4000] Training [2/16] Loss: 0.00498 +Epoch [1849/4000] Training [3/16] Loss: 0.00556 +Epoch [1849/4000] Training [4/16] Loss: 0.00679 +Epoch [1849/4000] Training [5/16] Loss: 0.00839 +Epoch [1849/4000] Training [6/16] Loss: 0.00717 +Epoch [1849/4000] Training [7/16] Loss: 0.01130 +Epoch [1849/4000] Training [8/16] Loss: 0.00562 +Epoch [1849/4000] Training [9/16] Loss: 0.00616 +Epoch [1849/4000] Training [10/16] Loss: 0.00671 +Epoch [1849/4000] Training [11/16] Loss: 0.00650 +Epoch [1849/4000] Training [12/16] Loss: 0.00527 +Epoch [1849/4000] Training [13/16] Loss: 0.00680 +Epoch [1849/4000] Training [14/16] Loss: 0.00789 +Epoch [1849/4000] Training [15/16] Loss: 0.00527 +Epoch [1849/4000] Training [16/16] Loss: 0.00767 +Epoch [1849/4000] Training metric {'Train/mean dice_metric': 0.9955394864082336, 'Train/mean miou_metric': 0.9908679723739624, 'Train/mean f1': 0.9912511110305786, 'Train/mean precision': 0.9866428971290588, 'Train/mean recall': 0.9959025979042053, 'Train/mean hd95_metric': 1.0621567964553833} +Epoch [1849/4000] Validation [1/4] Loss: 0.24834 focal_loss 0.17945 dice_loss 0.06889 +Epoch [1849/4000] Validation [2/4] Loss: 0.24425 focal_loss 0.13537 dice_loss 0.10888 +Epoch [1849/4000] Validation [3/4] Loss: 0.22974 focal_loss 0.14446 dice_loss 0.08528 +Epoch [1849/4000] Validation [4/4] Loss: 0.30910 focal_loss 0.18427 dice_loss 0.12483 +Epoch [1849/4000] Validation metric {'Val/mean dice_metric': 0.9694725275039673, 'Val/mean miou_metric': 0.9527524709701538, 'Val/mean f1': 0.9725531339645386, 'Val/mean precision': 0.9718447923660278, 'Val/mean recall': 0.9732625484466553, 'Val/mean hd95_metric': 5.583122253417969} +Cheakpoint... +Epoch [1849/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694725275039673, 'Val/mean miou_metric': 0.9527524709701538, 'Val/mean f1': 0.9725531339645386, 'Val/mean precision': 0.9718447923660278, 'Val/mean recall': 0.9732625484466553, 'Val/mean hd95_metric': 5.583122253417969} +Epoch [1850/4000] Training [1/16] Loss: 0.00835 +Epoch [1850/4000] Training [2/16] Loss: 0.00726 +Epoch [1850/4000] Training [3/16] Loss: 0.00661 +Epoch [1850/4000] Training [4/16] Loss: 0.00773 +Epoch [1850/4000] Training [5/16] Loss: 0.00548 +Epoch [1850/4000] Training [6/16] Loss: 0.00738 +Epoch [1850/4000] Training [7/16] Loss: 0.00500 +Epoch [1850/4000] Training [8/16] Loss: 0.00850 +Epoch [1850/4000] Training [9/16] Loss: 0.00690 +Epoch [1850/4000] Training [10/16] Loss: 0.00638 +Epoch [1850/4000] Training [11/16] Loss: 0.00606 +Epoch [1850/4000] Training [12/16] Loss: 0.00699 +Epoch [1850/4000] Training [13/16] Loss: 0.00630 +Epoch [1850/4000] Training [14/16] Loss: 0.00527 +Epoch [1850/4000] Training [15/16] Loss: 0.00713 +Epoch [1850/4000] Training [16/16] Loss: 0.00751 +Epoch [1850/4000] Training metric {'Train/mean dice_metric': 0.9954088926315308, 'Train/mean miou_metric': 0.9905945062637329, 'Train/mean f1': 0.9912675619125366, 'Train/mean precision': 0.9868513941764832, 'Train/mean recall': 0.9957234263420105, 'Train/mean hd95_metric': 1.023369550704956} +Epoch [1850/4000] Validation [1/4] Loss: 0.31418 focal_loss 0.24053 dice_loss 0.07365 +Epoch [1850/4000] Validation [2/4] Loss: 0.27080 focal_loss 0.16008 dice_loss 0.11072 +Epoch [1850/4000] Validation [3/4] Loss: 0.30490 focal_loss 0.21449 dice_loss 0.09042 +Epoch [1850/4000] Validation [4/4] Loss: 0.28681 focal_loss 0.16145 dice_loss 0.12535 +Epoch [1850/4000] Validation metric {'Val/mean dice_metric': 0.9703687429428101, 'Val/mean miou_metric': 0.9536740183830261, 'Val/mean f1': 0.9741109609603882, 'Val/mean precision': 0.9730657339096069, 'Val/mean recall': 0.9751584529876709, 'Val/mean hd95_metric': 5.0746941566467285} +Cheakpoint... +Epoch [1850/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703687429428101, 'Val/mean miou_metric': 0.9536740183830261, 'Val/mean f1': 0.9741109609603882, 'Val/mean precision': 0.9730657339096069, 'Val/mean recall': 0.9751584529876709, 'Val/mean hd95_metric': 5.0746941566467285} +Epoch [1851/4000] Training [1/16] Loss: 0.00569 +Epoch [1851/4000] Training [2/16] Loss: 0.00589 +Epoch [1851/4000] Training [3/16] Loss: 0.00638 +Epoch [1851/4000] Training [4/16] Loss: 0.00745 +Epoch [1851/4000] Training [5/16] Loss: 0.00587 +Epoch [1851/4000] Training [6/16] Loss: 0.01606 +Epoch [1851/4000] Training [7/16] Loss: 0.00560 +Epoch [1851/4000] Training [8/16] Loss: 0.00876 +Epoch [1851/4000] Training [9/16] Loss: 0.00616 +Epoch [1851/4000] Training [10/16] Loss: 0.00730 +Epoch [1851/4000] Training [11/16] Loss: 0.00905 +Epoch [1851/4000] Training [12/16] Loss: 0.00862 +Epoch [1851/4000] Training [13/16] Loss: 0.00801 +Epoch [1851/4000] Training [14/16] Loss: 0.00650 +Epoch [1851/4000] Training [15/16] Loss: 0.00796 +Epoch [1851/4000] Training [16/16] Loss: 0.00687 +Epoch [1851/4000] Training metric {'Train/mean dice_metric': 0.995339035987854, 'Train/mean miou_metric': 0.9904730319976807, 'Train/mean f1': 0.9910039901733398, 'Train/mean precision': 0.9861805438995361, 'Train/mean recall': 0.99587482213974, 'Train/mean hd95_metric': 1.0353436470031738} +Epoch [1851/4000] Validation [1/4] Loss: 0.40233 focal_loss 0.31662 dice_loss 0.08570 +Epoch [1851/4000] Validation [2/4] Loss: 0.24126 focal_loss 0.14170 dice_loss 0.09956 +Epoch [1851/4000] Validation [3/4] Loss: 0.29367 focal_loss 0.19883 dice_loss 0.09484 +Epoch [1851/4000] Validation [4/4] Loss: 0.26630 focal_loss 0.15884 dice_loss 0.10746 +Epoch [1851/4000] Validation metric {'Val/mean dice_metric': 0.9706073999404907, 'Val/mean miou_metric': 0.9538208842277527, 'Val/mean f1': 0.9737462997436523, 'Val/mean precision': 0.9723053574562073, 'Val/mean recall': 0.9751913547515869, 'Val/mean hd95_metric': 5.555553913116455} +Cheakpoint... +Epoch [1851/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706073999404907, 'Val/mean miou_metric': 0.9538208842277527, 'Val/mean f1': 0.9737462997436523, 'Val/mean precision': 0.9723053574562073, 'Val/mean recall': 0.9751913547515869, 'Val/mean hd95_metric': 5.555553913116455} +Epoch [1852/4000] Training [1/16] Loss: 0.00805 +Epoch [1852/4000] Training [2/16] Loss: 0.00982 +Epoch [1852/4000] Training [3/16] Loss: 0.00613 +Epoch [1852/4000] Training [4/16] Loss: 0.00724 +Epoch [1852/4000] Training [5/16] Loss: 0.00517 +Epoch [1852/4000] Training [6/16] Loss: 0.00627 +Epoch [1852/4000] Training [7/16] Loss: 0.00576 +Epoch [1852/4000] Training [8/16] Loss: 0.00635 +Epoch [1852/4000] Training [9/16] Loss: 0.00749 +Epoch [1852/4000] Training [10/16] Loss: 0.00623 +Epoch [1852/4000] Training [11/16] Loss: 0.00692 +Epoch [1852/4000] Training [12/16] Loss: 0.00660 +Epoch [1852/4000] Training [13/16] Loss: 0.00701 +Epoch [1852/4000] Training [14/16] Loss: 0.01032 +Epoch [1852/4000] Training [15/16] Loss: 0.00495 +Epoch [1852/4000] Training [16/16] Loss: 0.00568 +Epoch [1852/4000] Training metric {'Train/mean dice_metric': 0.9954925775527954, 'Train/mean miou_metric': 0.9907427430152893, 'Train/mean f1': 0.9911448955535889, 'Train/mean precision': 0.9865068197250366, 'Train/mean recall': 0.9958267211914062, 'Train/mean hd95_metric': 1.0441431999206543} +Epoch [1852/4000] Validation [1/4] Loss: 0.34151 focal_loss 0.26467 dice_loss 0.07684 +Epoch [1852/4000] Validation [2/4] Loss: 0.47503 focal_loss 0.28578 dice_loss 0.18925 +Epoch [1852/4000] Validation [3/4] Loss: 0.19748 focal_loss 0.12546 dice_loss 0.07202 +Epoch [1852/4000] Validation [4/4] Loss: 0.24922 focal_loss 0.14592 dice_loss 0.10330 +Epoch [1852/4000] Validation metric {'Val/mean dice_metric': 0.9716941714286804, 'Val/mean miou_metric': 0.9550172686576843, 'Val/mean f1': 0.9733161926269531, 'Val/mean precision': 0.9715624451637268, 'Val/mean recall': 0.9750763177871704, 'Val/mean hd95_metric': 5.8823442459106445} +Cheakpoint... +Epoch [1852/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716941714286804, 'Val/mean miou_metric': 0.9550172686576843, 'Val/mean f1': 0.9733161926269531, 'Val/mean precision': 0.9715624451637268, 'Val/mean recall': 0.9750763177871704, 'Val/mean hd95_metric': 5.8823442459106445} +Epoch [1853/4000] Training [1/16] Loss: 0.00996 +Epoch [1853/4000] Training [2/16] Loss: 0.01029 +Epoch [1853/4000] Training [3/16] Loss: 0.00699 +Epoch [1853/4000] Training [4/16] Loss: 0.00647 +Epoch [1853/4000] Training [5/16] Loss: 0.00710 +Epoch [1853/4000] Training [6/16] Loss: 0.00703 +Epoch [1853/4000] Training [7/16] Loss: 0.00672 +Epoch [1853/4000] Training [8/16] Loss: 0.00512 +Epoch [1853/4000] Training [9/16] Loss: 0.00552 +Epoch [1853/4000] Training [10/16] Loss: 0.00831 +Epoch [1853/4000] Training [11/16] Loss: 0.00736 +Epoch [1853/4000] Training [12/16] Loss: 0.00689 +Epoch [1853/4000] Training [13/16] Loss: 0.00720 +Epoch [1853/4000] Training [14/16] Loss: 0.00815 +Epoch [1853/4000] Training [15/16] Loss: 0.00801 +Epoch [1853/4000] Training [16/16] Loss: 0.00643 +Epoch [1853/4000] Training metric {'Train/mean dice_metric': 0.9951481819152832, 'Train/mean miou_metric': 0.9900767803192139, 'Train/mean f1': 0.9905333518981934, 'Train/mean precision': 0.9854414463043213, 'Train/mean recall': 0.9956781268119812, 'Train/mean hd95_metric': 1.05928635597229} +Epoch [1853/4000] Validation [1/4] Loss: 0.55449 focal_loss 0.44355 dice_loss 0.11094 +Epoch [1853/4000] Validation [2/4] Loss: 0.30688 focal_loss 0.18315 dice_loss 0.12373 +Epoch [1853/4000] Validation [3/4] Loss: 0.34294 focal_loss 0.24833 dice_loss 0.09460 +Epoch [1853/4000] Validation [4/4] Loss: 0.29137 focal_loss 0.17895 dice_loss 0.11243 +Epoch [1853/4000] Validation metric {'Val/mean dice_metric': 0.9716108441352844, 'Val/mean miou_metric': 0.9535531997680664, 'Val/mean f1': 0.9717825055122375, 'Val/mean precision': 0.9707632660865784, 'Val/mean recall': 0.9728040099143982, 'Val/mean hd95_metric': 5.619032382965088} +Cheakpoint... +Epoch [1853/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716108441352844, 'Val/mean miou_metric': 0.9535531997680664, 'Val/mean f1': 0.9717825055122375, 'Val/mean precision': 0.9707632660865784, 'Val/mean recall': 0.9728040099143982, 'Val/mean hd95_metric': 5.619032382965088} +Epoch [1854/4000] Training [1/16] Loss: 0.00542 +Epoch [1854/4000] Training [2/16] Loss: 0.00495 +Epoch [1854/4000] Training [3/16] Loss: 0.00522 +Epoch [1854/4000] Training [4/16] Loss: 0.00592 +Epoch [1854/4000] Training [5/16] Loss: 0.00726 +Epoch [1854/4000] Training [6/16] Loss: 0.00633 +Epoch [1854/4000] Training [7/16] Loss: 0.00869 +Epoch [1854/4000] Training [8/16] Loss: 0.00626 +Epoch [1854/4000] Training [9/16] Loss: 0.00482 +Epoch [1854/4000] Training [10/16] Loss: 0.00967 +Epoch [1854/4000] Training [11/16] Loss: 0.00606 +Epoch [1854/4000] Training [12/16] Loss: 0.00800 +Epoch [1854/4000] Training [13/16] Loss: 0.00713 +Epoch [1854/4000] Training [14/16] Loss: 0.00782 +Epoch [1854/4000] Training [15/16] Loss: 0.00608 +Epoch [1854/4000] Training [16/16] Loss: 0.00925 +Epoch [1854/4000] Training metric {'Train/mean dice_metric': 0.9953370094299316, 'Train/mean miou_metric': 0.990470290184021, 'Train/mean f1': 0.9913042783737183, 'Train/mean precision': 0.9867823719978333, 'Train/mean recall': 0.9958678483963013, 'Train/mean hd95_metric': 1.0287582874298096} +Epoch [1854/4000] Validation [1/4] Loss: 0.22693 focal_loss 0.16696 dice_loss 0.05997 +Epoch [1854/4000] Validation [2/4] Loss: 0.29170 focal_loss 0.17215 dice_loss 0.11955 +Epoch [1854/4000] Validation [3/4] Loss: 0.33880 focal_loss 0.24223 dice_loss 0.09658 +Epoch [1854/4000] Validation [4/4] Loss: 0.25602 focal_loss 0.15394 dice_loss 0.10208 +Epoch [1854/4000] Validation metric {'Val/mean dice_metric': 0.9729057550430298, 'Val/mean miou_metric': 0.9562126398086548, 'Val/mean f1': 0.974504292011261, 'Val/mean precision': 0.9704525470733643, 'Val/mean recall': 0.9785899519920349, 'Val/mean hd95_metric': 5.463403224945068} +Cheakpoint... +Epoch [1854/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729057550430298, 'Val/mean miou_metric': 0.9562126398086548, 'Val/mean f1': 0.974504292011261, 'Val/mean precision': 0.9704525470733643, 'Val/mean recall': 0.9785899519920349, 'Val/mean hd95_metric': 5.463403224945068} +Epoch [1855/4000] Training [1/16] Loss: 0.00687 +Epoch [1855/4000] Training [2/16] Loss: 0.00640 +Epoch [1855/4000] Training [3/16] Loss: 0.00575 +Epoch [1855/4000] Training [4/16] Loss: 0.00675 +Epoch [1855/4000] Training [5/16] Loss: 0.00626 +Epoch [1855/4000] Training [6/16] Loss: 0.00746 +Epoch [1855/4000] Training [7/16] Loss: 0.00748 +Epoch [1855/4000] Training [8/16] Loss: 0.01010 +Epoch [1855/4000] Training [9/16] Loss: 0.00957 +Epoch [1855/4000] Training [10/16] Loss: 0.00947 +Epoch [1855/4000] Training [11/16] Loss: 0.00836 +Epoch [1855/4000] Training [12/16] Loss: 0.00660 +Epoch [1855/4000] Training [13/16] Loss: 0.00569 +Epoch [1855/4000] Training [14/16] Loss: 0.00527 +Epoch [1855/4000] Training [15/16] Loss: 0.00612 +Epoch [1855/4000] Training [16/16] Loss: 0.00881 +Epoch [1855/4000] Training metric {'Train/mean dice_metric': 0.9949014782905579, 'Train/mean miou_metric': 0.9896742105484009, 'Train/mean f1': 0.9909986853599548, 'Train/mean precision': 0.9864513874053955, 'Train/mean recall': 0.9955880641937256, 'Train/mean hd95_metric': 1.177466630935669} +Epoch [1855/4000] Validation [1/4] Loss: 0.46443 focal_loss 0.36474 dice_loss 0.09969 +Epoch [1855/4000] Validation [2/4] Loss: 0.30291 focal_loss 0.18435 dice_loss 0.11856 +Epoch [1855/4000] Validation [3/4] Loss: 0.27772 focal_loss 0.18382 dice_loss 0.09390 +Epoch [1855/4000] Validation [4/4] Loss: 0.35390 focal_loss 0.23706 dice_loss 0.11684 +Epoch [1855/4000] Validation metric {'Val/mean dice_metric': 0.9706886410713196, 'Val/mean miou_metric': 0.9529867172241211, 'Val/mean f1': 0.9721710085868835, 'Val/mean precision': 0.9708104729652405, 'Val/mean recall': 0.9735354781150818, 'Val/mean hd95_metric': 5.973166465759277} +Cheakpoint... +Epoch [1855/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706886410713196, 'Val/mean miou_metric': 0.9529867172241211, 'Val/mean f1': 0.9721710085868835, 'Val/mean precision': 0.9708104729652405, 'Val/mean recall': 0.9735354781150818, 'Val/mean hd95_metric': 5.973166465759277} +Epoch [1856/4000] Training [1/16] Loss: 0.01011 +Epoch [1856/4000] Training [2/16] Loss: 0.00625 +Epoch [1856/4000] Training [3/16] Loss: 0.00901 +Epoch [1856/4000] Training [4/16] Loss: 0.00655 +Epoch [1856/4000] Training [5/16] Loss: 0.00596 +Epoch [1856/4000] Training [6/16] Loss: 0.00591 +Epoch [1856/4000] Training [7/16] Loss: 0.00621 +Epoch [1856/4000] Training [8/16] Loss: 0.00554 +Epoch [1856/4000] Training [9/16] Loss: 0.00661 +Epoch [1856/4000] Training [10/16] Loss: 0.00707 +Epoch [1856/4000] Training [11/16] Loss: 0.00672 +Epoch [1856/4000] Training [12/16] Loss: 0.00788 +Epoch [1856/4000] Training [13/16] Loss: 0.00631 +Epoch [1856/4000] Training [14/16] Loss: 0.00801 +Epoch [1856/4000] Training [15/16] Loss: 0.00614 +Epoch [1856/4000] Training [16/16] Loss: 0.00661 +Epoch [1856/4000] Training metric {'Train/mean dice_metric': 0.9953418374061584, 'Train/mean miou_metric': 0.9904506206512451, 'Train/mean f1': 0.9908884763717651, 'Train/mean precision': 0.9859917759895325, 'Train/mean recall': 0.9958339929580688, 'Train/mean hd95_metric': 1.0250416994094849} +Epoch [1856/4000] Validation [1/4] Loss: 0.39913 focal_loss 0.30581 dice_loss 0.09332 +Epoch [1856/4000] Validation [2/4] Loss: 0.21853 focal_loss 0.11876 dice_loss 0.09976 +Epoch [1856/4000] Validation [3/4] Loss: 0.30289 focal_loss 0.20843 dice_loss 0.09446 +Epoch [1856/4000] Validation [4/4] Loss: 0.22187 focal_loss 0.12148 dice_loss 0.10039 +Epoch [1856/4000] Validation metric {'Val/mean dice_metric': 0.9716620445251465, 'Val/mean miou_metric': 0.955074667930603, 'Val/mean f1': 0.9731236100196838, 'Val/mean precision': 0.9687283039093018, 'Val/mean recall': 0.9775589108467102, 'Val/mean hd95_metric': 6.042040824890137} +Cheakpoint... +Epoch [1856/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716620445251465, 'Val/mean miou_metric': 0.955074667930603, 'Val/mean f1': 0.9731236100196838, 'Val/mean precision': 0.9687283039093018, 'Val/mean recall': 0.9775589108467102, 'Val/mean hd95_metric': 6.042040824890137} +Epoch [1857/4000] Training [1/16] Loss: 0.00877 +Epoch [1857/4000] Training [2/16] Loss: 0.00620 +Epoch [1857/4000] Training [3/16] Loss: 0.00908 +Epoch [1857/4000] Training [4/16] Loss: 0.00807 +Epoch [1857/4000] Training [5/16] Loss: 0.00506 +Epoch [1857/4000] Training [6/16] Loss: 0.00598 +Epoch [1857/4000] Training [7/16] Loss: 0.00519 +Epoch [1857/4000] Training [8/16] Loss: 0.01772 +Epoch [1857/4000] Training [9/16] Loss: 0.00687 +Epoch [1857/4000] Training [10/16] Loss: 0.00671 +Epoch [1857/4000] Training [11/16] Loss: 0.00734 +Epoch [1857/4000] Training [12/16] Loss: 0.00523 +Epoch [1857/4000] Training [13/16] Loss: 0.00649 +Epoch [1857/4000] Training [14/16] Loss: 0.00746 +Epoch [1857/4000] Training [15/16] Loss: 0.00536 +Epoch [1857/4000] Training [16/16] Loss: 0.01428 +Epoch [1857/4000] Training metric {'Train/mean dice_metric': 0.995280921459198, 'Train/mean miou_metric': 0.9903669357299805, 'Train/mean f1': 0.9912451505661011, 'Train/mean precision': 0.9867268800735474, 'Train/mean recall': 0.995805025100708, 'Train/mean hd95_metric': 1.473010778427124} +Epoch [1857/4000] Validation [1/4] Loss: 0.33945 focal_loss 0.26363 dice_loss 0.07582 +Epoch [1857/4000] Validation [2/4] Loss: 0.19488 focal_loss 0.10648 dice_loss 0.08839 +Epoch [1857/4000] Validation [3/4] Loss: 0.33784 focal_loss 0.23966 dice_loss 0.09818 +Epoch [1857/4000] Validation [4/4] Loss: 0.21842 focal_loss 0.12546 dice_loss 0.09296 +Epoch [1857/4000] Validation metric {'Val/mean dice_metric': 0.9711670875549316, 'Val/mean miou_metric': 0.9546453356742859, 'Val/mean f1': 0.9739250540733337, 'Val/mean precision': 0.9687722325325012, 'Val/mean recall': 0.9791330099105835, 'Val/mean hd95_metric': 6.48700475692749} +Cheakpoint... +Epoch [1857/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711670875549316, 'Val/mean miou_metric': 0.9546453356742859, 'Val/mean f1': 0.9739250540733337, 'Val/mean precision': 0.9687722325325012, 'Val/mean recall': 0.9791330099105835, 'Val/mean hd95_metric': 6.48700475692749} +Epoch [1858/4000] Training [1/16] Loss: 0.00655 +Epoch [1858/4000] Training [2/16] Loss: 0.00689 +Epoch [1858/4000] Training [3/16] Loss: 0.00507 +Epoch [1858/4000] Training [4/16] Loss: 0.00546 +Epoch [1858/4000] Training [5/16] Loss: 0.00571 +Epoch [1858/4000] Training [6/16] Loss: 0.00721 +Epoch [1858/4000] Training [7/16] Loss: 0.00565 +Epoch [1858/4000] Training [8/16] Loss: 0.00770 +Epoch [1858/4000] Training [9/16] Loss: 0.00559 +Epoch [1858/4000] Training [10/16] Loss: 0.00655 +Epoch [1858/4000] Training [11/16] Loss: 0.00632 +Epoch [1858/4000] Training [12/16] Loss: 0.00542 +Epoch [1858/4000] Training [13/16] Loss: 0.00497 +Epoch [1858/4000] Training [14/16] Loss: 0.00829 +Epoch [1858/4000] Training [15/16] Loss: 0.00813 +Epoch [1858/4000] Training [16/16] Loss: 0.00778 +Epoch [1858/4000] Training metric {'Train/mean dice_metric': 0.9957115650177002, 'Train/mean miou_metric': 0.9912055730819702, 'Train/mean f1': 0.9914866089820862, 'Train/mean precision': 0.9868517518043518, 'Train/mean recall': 0.9961652159690857, 'Train/mean hd95_metric': 1.0128173828125} +Epoch [1858/4000] Validation [1/4] Loss: 0.34482 focal_loss 0.26738 dice_loss 0.07744 +Epoch [1858/4000] Validation [2/4] Loss: 0.43796 focal_loss 0.27034 dice_loss 0.16761 +Epoch [1858/4000] Validation [3/4] Loss: 0.38475 focal_loss 0.28666 dice_loss 0.09809 +Epoch [1858/4000] Validation [4/4] Loss: 0.24324 focal_loss 0.14988 dice_loss 0.09336 +Epoch [1858/4000] Validation metric {'Val/mean dice_metric': 0.9724491238594055, 'Val/mean miou_metric': 0.9552532434463501, 'Val/mean f1': 0.9731392860412598, 'Val/mean precision': 0.9679226279258728, 'Val/mean recall': 0.9784126281738281, 'Val/mean hd95_metric': 6.653261661529541} +Cheakpoint... +Epoch [1858/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724491238594055, 'Val/mean miou_metric': 0.9552532434463501, 'Val/mean f1': 0.9731392860412598, 'Val/mean precision': 0.9679226279258728, 'Val/mean recall': 0.9784126281738281, 'Val/mean hd95_metric': 6.653261661529541} +Epoch [1859/4000] Training [1/16] Loss: 0.00870 +Epoch [1859/4000] Training [2/16] Loss: 0.00644 +Epoch [1859/4000] Training [3/16] Loss: 0.00682 +Epoch [1859/4000] Training [4/16] Loss: 0.00931 +Epoch [1859/4000] Training [5/16] Loss: 0.00673 +Epoch [1859/4000] Training [6/16] Loss: 0.00514 +Epoch [1859/4000] Training [7/16] Loss: 0.00581 +Epoch [1859/4000] Training [8/16] Loss: 0.00832 +Epoch [1859/4000] Training [9/16] Loss: 0.00865 +Epoch [1859/4000] Training [10/16] Loss: 0.00664 +Epoch [1859/4000] Training [11/16] Loss: 0.00706 +Epoch [1859/4000] Training [12/16] Loss: 0.00647 +Epoch [1859/4000] Training [13/16] Loss: 0.00666 +Epoch [1859/4000] Training [14/16] Loss: 0.01038 +Epoch [1859/4000] Training [15/16] Loss: 0.00609 +Epoch [1859/4000] Training [16/16] Loss: 0.00874 +Epoch [1859/4000] Training metric {'Train/mean dice_metric': 0.99334716796875, 'Train/mean miou_metric': 0.9878880381584167, 'Train/mean f1': 0.9898742437362671, 'Train/mean precision': 0.9850754737854004, 'Train/mean recall': 0.9947200417518616, 'Train/mean hd95_metric': 1.3202052116394043} +Epoch [1859/4000] Validation [1/4] Loss: 0.31156 focal_loss 0.22982 dice_loss 0.08174 +Epoch [1859/4000] Validation [2/4] Loss: 0.49610 focal_loss 0.29430 dice_loss 0.20180 +Epoch [1859/4000] Validation [3/4] Loss: 0.36205 focal_loss 0.26302 dice_loss 0.09904 +Epoch [1859/4000] Validation [4/4] Loss: 0.17627 focal_loss 0.09995 dice_loss 0.07632 +Epoch [1859/4000] Validation metric {'Val/mean dice_metric': 0.9698526263237, 'Val/mean miou_metric': 0.9519408345222473, 'Val/mean f1': 0.9725702404975891, 'Val/mean precision': 0.9705464243888855, 'Val/mean recall': 0.974602460861206, 'Val/mean hd95_metric': 5.804902076721191} +Cheakpoint... +Epoch [1859/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698526263237, 'Val/mean miou_metric': 0.9519408345222473, 'Val/mean f1': 0.9725702404975891, 'Val/mean precision': 0.9705464243888855, 'Val/mean recall': 0.974602460861206, 'Val/mean hd95_metric': 5.804902076721191} +Epoch [1860/4000] Training [1/16] Loss: 0.01055 +Epoch [1860/4000] Training [2/16] Loss: 0.00686 +Epoch [1860/4000] Training [3/16] Loss: 0.00894 +Epoch [1860/4000] Training [4/16] Loss: 0.00593 +Epoch [1860/4000] Training [5/16] Loss: 0.01062 +Epoch [1860/4000] Training [6/16] Loss: 0.00669 +Epoch [1860/4000] Training [7/16] Loss: 0.00608 +Epoch [1860/4000] Training [8/16] Loss: 0.00855 +Epoch [1860/4000] Training [9/16] Loss: 0.00666 +Epoch [1860/4000] Training [10/16] Loss: 0.00655 +Epoch [1860/4000] Training [11/16] Loss: 0.00686 +Epoch [1860/4000] Training [12/16] Loss: 0.00654 +Epoch [1860/4000] Training [13/16] Loss: 0.00638 +Epoch [1860/4000] Training [14/16] Loss: 0.00649 +Epoch [1860/4000] Training [15/16] Loss: 0.01027 +Epoch [1860/4000] Training [16/16] Loss: 0.00533 +Epoch [1860/4000] Training metric {'Train/mean dice_metric': 0.9953263998031616, 'Train/mean miou_metric': 0.9904090166091919, 'Train/mean f1': 0.9905276298522949, 'Train/mean precision': 0.9854508638381958, 'Train/mean recall': 0.9956571459770203, 'Train/mean hd95_metric': 1.084923267364502} +Epoch [1860/4000] Validation [1/4] Loss: 0.31529 focal_loss 0.23303 dice_loss 0.08227 +Epoch [1860/4000] Validation [2/4] Loss: 0.24266 focal_loss 0.14323 dice_loss 0.09942 +Epoch [1860/4000] Validation [3/4] Loss: 0.33235 focal_loss 0.24337 dice_loss 0.08898 +Epoch [1860/4000] Validation [4/4] Loss: 0.24397 focal_loss 0.14661 dice_loss 0.09736 +Epoch [1860/4000] Validation metric {'Val/mean dice_metric': 0.9727064967155457, 'Val/mean miou_metric': 0.9549745321273804, 'Val/mean f1': 0.9729710817337036, 'Val/mean precision': 0.9692586064338684, 'Val/mean recall': 0.9767121076583862, 'Val/mean hd95_metric': 5.579827308654785} +Cheakpoint... +Epoch [1860/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727064967155457, 'Val/mean miou_metric': 0.9549745321273804, 'Val/mean f1': 0.9729710817337036, 'Val/mean precision': 0.9692586064338684, 'Val/mean recall': 0.9767121076583862, 'Val/mean hd95_metric': 5.579827308654785} +Epoch [1861/4000] Training [1/16] Loss: 0.00567 +Epoch [1861/4000] Training [2/16] Loss: 0.00673 +Epoch [1861/4000] Training [3/16] Loss: 0.00680 +Epoch [1861/4000] Training [4/16] Loss: 0.00493 +Epoch [1861/4000] Training [5/16] Loss: 0.00569 +Epoch [1861/4000] Training [6/16] Loss: 0.00797 +Epoch [1861/4000] Training [7/16] Loss: 0.00615 +Epoch [1861/4000] Training [8/16] Loss: 0.00658 +Epoch [1861/4000] Training [9/16] Loss: 0.00718 +Epoch [1861/4000] Training [10/16] Loss: 0.00570 +Epoch [1861/4000] Training [11/16] Loss: 0.00609 +Epoch [1861/4000] Training [12/16] Loss: 0.00669 +Epoch [1861/4000] Training [13/16] Loss: 0.00620 +Epoch [1861/4000] Training [14/16] Loss: 0.00636 +Epoch [1861/4000] Training [15/16] Loss: 0.00586 +Epoch [1861/4000] Training [16/16] Loss: 0.00446 +Epoch [1861/4000] Training metric {'Train/mean dice_metric': 0.9957104921340942, 'Train/mean miou_metric': 0.991199791431427, 'Train/mean f1': 0.9916167259216309, 'Train/mean precision': 0.987203061580658, 'Train/mean recall': 0.9960700273513794, 'Train/mean hd95_metric': 1.0165925025939941} +Epoch [1861/4000] Validation [1/4] Loss: 0.29483 focal_loss 0.22423 dice_loss 0.07060 +Epoch [1861/4000] Validation [2/4] Loss: 0.48978 focal_loss 0.33203 dice_loss 0.15776 +Epoch [1861/4000] Validation [3/4] Loss: 0.17767 focal_loss 0.12001 dice_loss 0.05766 +Epoch [1861/4000] Validation [4/4] Loss: 0.23172 focal_loss 0.14098 dice_loss 0.09074 +Epoch [1861/4000] Validation metric {'Val/mean dice_metric': 0.973395824432373, 'Val/mean miou_metric': 0.9565225839614868, 'Val/mean f1': 0.9748282432556152, 'Val/mean precision': 0.9702919721603394, 'Val/mean recall': 0.9794070720672607, 'Val/mean hd95_metric': 5.3498215675354} +Cheakpoint... +Epoch [1861/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973395824432373, 'Val/mean miou_metric': 0.9565225839614868, 'Val/mean f1': 0.9748282432556152, 'Val/mean precision': 0.9702919721603394, 'Val/mean recall': 0.9794070720672607, 'Val/mean hd95_metric': 5.3498215675354} +Epoch [1862/4000] Training [1/16] Loss: 0.00604 +Epoch [1862/4000] Training [2/16] Loss: 0.00774 +Epoch [1862/4000] Training [3/16] Loss: 0.00636 +Epoch [1862/4000] Training [4/16] Loss: 0.00694 +Epoch [1862/4000] Training [5/16] Loss: 0.00564 +Epoch [1862/4000] Training [6/16] Loss: 0.00591 +Epoch [1862/4000] Training [7/16] Loss: 0.00607 +Epoch [1862/4000] Training [8/16] Loss: 0.00741 +Epoch [1862/4000] Training [9/16] Loss: 0.00769 +Epoch [1862/4000] Training [10/16] Loss: 0.00903 +Epoch [1862/4000] Training [11/16] Loss: 0.00594 +Epoch [1862/4000] Training [12/16] Loss: 0.00620 +Epoch [1862/4000] Training [13/16] Loss: 0.00596 +Epoch [1862/4000] Training [14/16] Loss: 0.00724 +Epoch [1862/4000] Training [15/16] Loss: 0.00436 +Epoch [1862/4000] Training [16/16] Loss: 0.00449 +Epoch [1862/4000] Training metric {'Train/mean dice_metric': 0.995821475982666, 'Train/mean miou_metric': 0.9914169311523438, 'Train/mean f1': 0.9915071129798889, 'Train/mean precision': 0.98686683177948, 'Train/mean recall': 0.996191143989563, 'Train/mean hd95_metric': 1.0200337171554565} +Epoch [1862/4000] Validation [1/4] Loss: 0.28522 focal_loss 0.21901 dice_loss 0.06621 +Epoch [1862/4000] Validation [2/4] Loss: 0.50813 focal_loss 0.30802 dice_loss 0.20010 +Epoch [1862/4000] Validation [3/4] Loss: 0.32565 focal_loss 0.23565 dice_loss 0.09000 +Epoch [1862/4000] Validation [4/4] Loss: 0.31999 focal_loss 0.20734 dice_loss 0.11265 +Epoch [1862/4000] Validation metric {'Val/mean dice_metric': 0.9713611602783203, 'Val/mean miou_metric': 0.9551283717155457, 'Val/mean f1': 0.973206102848053, 'Val/mean precision': 0.9680325984954834, 'Val/mean recall': 0.9784350991249084, 'Val/mean hd95_metric': 5.85647439956665} +Cheakpoint... +Epoch [1862/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713611602783203, 'Val/mean miou_metric': 0.9551283717155457, 'Val/mean f1': 0.973206102848053, 'Val/mean precision': 0.9680325984954834, 'Val/mean recall': 0.9784350991249084, 'Val/mean hd95_metric': 5.85647439956665} +Epoch [1863/4000] Training [1/16] Loss: 0.00666 +Epoch [1863/4000] Training [2/16] Loss: 0.00526 +Epoch [1863/4000] Training [3/16] Loss: 0.00620 +Epoch [1863/4000] Training [4/16] Loss: 0.00848 +Epoch [1863/4000] Training [5/16] Loss: 0.00638 +Epoch [1863/4000] Training [6/16] Loss: 0.00699 +Epoch [1863/4000] Training [7/16] Loss: 0.00554 +Epoch [1863/4000] Training [8/16] Loss: 0.00717 +Epoch [1863/4000] Training [9/16] Loss: 0.00957 +Epoch [1863/4000] Training [10/16] Loss: 0.00585 +Epoch [1863/4000] Training [11/16] Loss: 0.00779 +Epoch [1863/4000] Training [12/16] Loss: 0.00562 +Epoch [1863/4000] Training [13/16] Loss: 0.00429 +Epoch [1863/4000] Training [14/16] Loss: 0.00507 +Epoch [1863/4000] Training [15/16] Loss: 0.00603 +Epoch [1863/4000] Training [16/16] Loss: 0.00563 +Epoch [1863/4000] Training metric {'Train/mean dice_metric': 0.9956334829330444, 'Train/mean miou_metric': 0.9910505414009094, 'Train/mean f1': 0.9913986325263977, 'Train/mean precision': 0.986865222454071, 'Train/mean recall': 0.9959738850593567, 'Train/mean hd95_metric': 1.4994540214538574} +Epoch [1863/4000] Validation [1/4] Loss: 0.24690 focal_loss 0.18141 dice_loss 0.06549 +Epoch [1863/4000] Validation [2/4] Loss: 0.21467 focal_loss 0.12290 dice_loss 0.09178 +Epoch [1863/4000] Validation [3/4] Loss: 0.15583 focal_loss 0.09593 dice_loss 0.05990 +Epoch [1863/4000] Validation [4/4] Loss: 0.22506 focal_loss 0.13245 dice_loss 0.09261 +Epoch [1863/4000] Validation metric {'Val/mean dice_metric': 0.9737814664840698, 'Val/mean miou_metric': 0.9572561979293823, 'Val/mean f1': 0.9753187894821167, 'Val/mean precision': 0.9717051982879639, 'Val/mean recall': 0.9789593815803528, 'Val/mean hd95_metric': 6.11826229095459} +Cheakpoint... +Epoch [1863/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737814664840698, 'Val/mean miou_metric': 0.9572561979293823, 'Val/mean f1': 0.9753187894821167, 'Val/mean precision': 0.9717051982879639, 'Val/mean recall': 0.9789593815803528, 'Val/mean hd95_metric': 6.11826229095459} +Epoch [1864/4000] Training [1/16] Loss: 0.00902 +Epoch [1864/4000] Training [2/16] Loss: 0.00618 +Epoch [1864/4000] Training [3/16] Loss: 0.00571 +Epoch [1864/4000] Training [4/16] Loss: 0.00541 +Epoch [1864/4000] Training [5/16] Loss: 0.00660 +Epoch [1864/4000] Training [6/16] Loss: 0.00491 +Epoch [1864/4000] Training [7/16] Loss: 0.00620 +Epoch [1864/4000] Training [8/16] Loss: 0.00796 +Epoch [1864/4000] Training [9/16] Loss: 0.00513 +Epoch [1864/4000] Training [10/16] Loss: 0.00529 +Epoch [1864/4000] Training [11/16] Loss: 0.00643 +Epoch [1864/4000] Training [12/16] Loss: 0.00594 +Epoch [1864/4000] Training [13/16] Loss: 0.00826 +Epoch [1864/4000] Training [14/16] Loss: 0.00703 +Epoch [1864/4000] Training [15/16] Loss: 0.00876 +Epoch [1864/4000] Training [16/16] Loss: 0.00748 +Epoch [1864/4000] Training metric {'Train/mean dice_metric': 0.9958110451698303, 'Train/mean miou_metric': 0.9913989305496216, 'Train/mean f1': 0.9916010499000549, 'Train/mean precision': 0.9872295260429382, 'Train/mean recall': 0.9960114359855652, 'Train/mean hd95_metric': 1.0151958465576172} +Epoch [1864/4000] Validation [1/4] Loss: 0.24050 focal_loss 0.18120 dice_loss 0.05930 +Epoch [1864/4000] Validation [2/4] Loss: 0.25099 focal_loss 0.13745 dice_loss 0.11355 +Epoch [1864/4000] Validation [3/4] Loss: 0.33886 focal_loss 0.24821 dice_loss 0.09065 +Epoch [1864/4000] Validation [4/4] Loss: 0.22731 focal_loss 0.13160 dice_loss 0.09570 +Epoch [1864/4000] Validation metric {'Val/mean dice_metric': 0.9731777310371399, 'Val/mean miou_metric': 0.9564332962036133, 'Val/mean f1': 0.974878191947937, 'Val/mean precision': 0.97004634141922, 'Val/mean recall': 0.9797582626342773, 'Val/mean hd95_metric': 5.802870273590088} +Cheakpoint... +Epoch [1864/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731777310371399, 'Val/mean miou_metric': 0.9564332962036133, 'Val/mean f1': 0.974878191947937, 'Val/mean precision': 0.97004634141922, 'Val/mean recall': 0.9797582626342773, 'Val/mean hd95_metric': 5.802870273590088} +Epoch [1865/4000] Training [1/16] Loss: 0.00705 +Epoch [1865/4000] Training [2/16] Loss: 0.00824 +Epoch [1865/4000] Training [3/16] Loss: 0.00601 +Epoch [1865/4000] Training [4/16] Loss: 0.00546 +Epoch [1865/4000] Training [5/16] Loss: 0.00708 +Epoch [1865/4000] Training [6/16] Loss: 0.00678 +Epoch [1865/4000] Training [7/16] Loss: 0.00818 +Epoch [1865/4000] Training [8/16] Loss: 0.00768 +Epoch [1865/4000] Training [9/16] Loss: 0.00791 +Epoch [1865/4000] Training [10/16] Loss: 0.00655 +Epoch [1865/4000] Training [11/16] Loss: 0.00548 +Epoch [1865/4000] Training [12/16] Loss: 0.00547 +Epoch [1865/4000] Training [13/16] Loss: 0.00694 +Epoch [1865/4000] Training [14/16] Loss: 0.00848 +Epoch [1865/4000] Training [15/16] Loss: 0.00700 +Epoch [1865/4000] Training [16/16] Loss: 0.00574 +Epoch [1865/4000] Training metric {'Train/mean dice_metric': 0.9954639077186584, 'Train/mean miou_metric': 0.9907039999961853, 'Train/mean f1': 0.9911607503890991, 'Train/mean precision': 0.9863399267196655, 'Train/mean recall': 0.9960288405418396, 'Train/mean hd95_metric': 1.0283368825912476} +Epoch [1865/4000] Validation [1/4] Loss: 0.28248 focal_loss 0.21566 dice_loss 0.06682 +Epoch [1865/4000] Validation [2/4] Loss: 0.27862 focal_loss 0.15420 dice_loss 0.12442 +Epoch [1865/4000] Validation [3/4] Loss: 0.24704 focal_loss 0.15588 dice_loss 0.09116 +Epoch [1865/4000] Validation [4/4] Loss: 0.22297 focal_loss 0.13717 dice_loss 0.08580 +Epoch [1865/4000] Validation metric {'Val/mean dice_metric': 0.9740104675292969, 'Val/mean miou_metric': 0.9570305943489075, 'Val/mean f1': 0.9747722148895264, 'Val/mean precision': 0.9698598384857178, 'Val/mean recall': 0.9797345399856567, 'Val/mean hd95_metric': 5.434915065765381} +Cheakpoint... +Epoch [1865/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740104675292969, 'Val/mean miou_metric': 0.9570305943489075, 'Val/mean f1': 0.9747722148895264, 'Val/mean precision': 0.9698598384857178, 'Val/mean recall': 0.9797345399856567, 'Val/mean hd95_metric': 5.434915065765381} +Epoch [1866/4000] Training [1/16] Loss: 0.00645 +Epoch [1866/4000] Training [2/16] Loss: 0.00709 +Epoch [1866/4000] Training [3/16] Loss: 0.00521 +Epoch [1866/4000] Training [4/16] Loss: 0.00835 +Epoch [1866/4000] Training [5/16] Loss: 0.00754 +Epoch [1866/4000] Training [6/16] Loss: 0.00941 +Epoch [1866/4000] Training [7/16] Loss: 0.00907 +Epoch [1866/4000] Training [8/16] Loss: 0.00472 +Epoch [1866/4000] Training [9/16] Loss: 0.00744 +Epoch [1866/4000] Training [10/16] Loss: 0.00802 +Epoch [1866/4000] Training [11/16] Loss: 0.00607 +Epoch [1866/4000] Training [12/16] Loss: 0.00541 +Epoch [1866/4000] Training [13/16] Loss: 0.00674 +Epoch [1866/4000] Training [14/16] Loss: 0.00774 +Epoch [1866/4000] Training [15/16] Loss: 0.00615 +Epoch [1866/4000] Training [16/16] Loss: 0.01155 +Epoch [1866/4000] Training metric {'Train/mean dice_metric': 0.9951585531234741, 'Train/mean miou_metric': 0.9901130199432373, 'Train/mean f1': 0.9911569952964783, 'Train/mean precision': 0.9866365790367126, 'Train/mean recall': 0.9957189559936523, 'Train/mean hd95_metric': 1.0493755340576172} +Epoch [1866/4000] Validation [1/4] Loss: 0.26015 focal_loss 0.19727 dice_loss 0.06288 +Epoch [1866/4000] Validation [2/4] Loss: 0.55619 focal_loss 0.35479 dice_loss 0.20140 +Epoch [1866/4000] Validation [3/4] Loss: 0.16108 focal_loss 0.10419 dice_loss 0.05689 +Epoch [1866/4000] Validation [4/4] Loss: 0.35211 focal_loss 0.22576 dice_loss 0.12635 +Epoch [1866/4000] Validation metric {'Val/mean dice_metric': 0.9723684191703796, 'Val/mean miou_metric': 0.9550584554672241, 'Val/mean f1': 0.9744714498519897, 'Val/mean precision': 0.9696000218391418, 'Val/mean recall': 0.9793921113014221, 'Val/mean hd95_metric': 5.435685634613037} +Cheakpoint... +Epoch [1866/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723684191703796, 'Val/mean miou_metric': 0.9550584554672241, 'Val/mean f1': 0.9744714498519897, 'Val/mean precision': 0.9696000218391418, 'Val/mean recall': 0.9793921113014221, 'Val/mean hd95_metric': 5.435685634613037} +Epoch [1867/4000] Training [1/16] Loss: 0.00612 +Epoch [1867/4000] Training [2/16] Loss: 0.00689 +Epoch [1867/4000] Training [3/16] Loss: 0.00693 +Epoch [1867/4000] Training [4/16] Loss: 0.00520 +Epoch [1867/4000] Training [5/16] Loss: 0.00549 +Epoch [1867/4000] Training [6/16] Loss: 0.00439 +Epoch [1867/4000] Training [7/16] Loss: 0.00526 +Epoch [1867/4000] Training [8/16] Loss: 0.00563 +Epoch [1867/4000] Training [9/16] Loss: 0.00647 +Epoch [1867/4000] Training [10/16] Loss: 0.00730 +Epoch [1867/4000] Training [11/16] Loss: 0.00709 +Epoch [1867/4000] Training [12/16] Loss: 0.00595 +Epoch [1867/4000] Training [13/16] Loss: 0.00668 +Epoch [1867/4000] Training [14/16] Loss: 0.00594 +Epoch [1867/4000] Training [15/16] Loss: 0.00771 +Epoch [1867/4000] Training [16/16] Loss: 0.00979 +Epoch [1867/4000] Training metric {'Train/mean dice_metric': 0.9958350658416748, 'Train/mean miou_metric': 0.9914353489875793, 'Train/mean f1': 0.9914945363998413, 'Train/mean precision': 0.9870518445968628, 'Train/mean recall': 0.9959774017333984, 'Train/mean hd95_metric': 1.0090030431747437} +Epoch [1867/4000] Validation [1/4] Loss: 0.25612 focal_loss 0.19082 dice_loss 0.06530 +Epoch [1867/4000] Validation [2/4] Loss: 0.28726 focal_loss 0.15100 dice_loss 0.13626 +Epoch [1867/4000] Validation [3/4] Loss: 0.28708 focal_loss 0.19299 dice_loss 0.09409 +Epoch [1867/4000] Validation [4/4] Loss: 0.17674 focal_loss 0.10018 dice_loss 0.07656 +Epoch [1867/4000] Validation metric {'Val/mean dice_metric': 0.9735119938850403, 'Val/mean miou_metric': 0.956429123878479, 'Val/mean f1': 0.9746244549751282, 'Val/mean precision': 0.9698746204376221, 'Val/mean recall': 0.9794210195541382, 'Val/mean hd95_metric': 5.702691555023193} +Cheakpoint... +Epoch [1867/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735119938850403, 'Val/mean miou_metric': 0.956429123878479, 'Val/mean f1': 0.9746244549751282, 'Val/mean precision': 0.9698746204376221, 'Val/mean recall': 0.9794210195541382, 'Val/mean hd95_metric': 5.702691555023193} +Epoch [1868/4000] Training [1/16] Loss: 0.00834 +Epoch [1868/4000] Training [2/16] Loss: 0.00537 +Epoch [1868/4000] Training [3/16] Loss: 0.00597 +Epoch [1868/4000] Training [4/16] Loss: 0.00576 +Epoch [1868/4000] Training [5/16] Loss: 0.01035 +Epoch [1868/4000] Training [6/16] Loss: 0.00904 +Epoch [1868/4000] Training [7/16] Loss: 0.00872 +Epoch [1868/4000] Training [8/16] Loss: 0.00567 +Epoch [1868/4000] Training [9/16] Loss: 0.00592 +Epoch [1868/4000] Training [10/16] Loss: 0.00505 +Epoch [1868/4000] Training [11/16] Loss: 0.00618 +Epoch [1868/4000] Training [12/16] Loss: 0.00732 +Epoch [1868/4000] Training [13/16] Loss: 0.00607 +Epoch [1868/4000] Training [14/16] Loss: 0.00606 +Epoch [1868/4000] Training [15/16] Loss: 0.00644 +Epoch [1868/4000] Training [16/16] Loss: 0.00609 +Epoch [1868/4000] Training metric {'Train/mean dice_metric': 0.9954939484596252, 'Train/mean miou_metric': 0.9907572865486145, 'Train/mean f1': 0.9911417365074158, 'Train/mean precision': 0.9862611889839172, 'Train/mean recall': 0.9960708022117615, 'Train/mean hd95_metric': 1.0092006921768188} +Epoch [1868/4000] Validation [1/4] Loss: 0.26658 focal_loss 0.19876 dice_loss 0.06782 +Epoch [1868/4000] Validation [2/4] Loss: 0.23138 focal_loss 0.13346 dice_loss 0.09792 +Epoch [1868/4000] Validation [3/4] Loss: 0.36803 focal_loss 0.26481 dice_loss 0.10323 +Epoch [1868/4000] Validation [4/4] Loss: 0.25650 focal_loss 0.16175 dice_loss 0.09475 +Epoch [1868/4000] Validation metric {'Val/mean dice_metric': 0.973972499370575, 'Val/mean miou_metric': 0.9573127627372742, 'Val/mean f1': 0.9752404689788818, 'Val/mean precision': 0.9718984961509705, 'Val/mean recall': 0.9786054491996765, 'Val/mean hd95_metric': 5.221930503845215} +Cheakpoint... +Epoch [1868/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973972499370575, 'Val/mean miou_metric': 0.9573127627372742, 'Val/mean f1': 0.9752404689788818, 'Val/mean precision': 0.9718984961509705, 'Val/mean recall': 0.9786054491996765, 'Val/mean hd95_metric': 5.221930503845215} +Epoch [1869/4000] Training [1/16] Loss: 0.00532 +Epoch [1869/4000] Training [2/16] Loss: 0.00734 +Epoch [1869/4000] Training [3/16] Loss: 0.00534 +Epoch [1869/4000] Training [4/16] Loss: 0.00455 +Epoch [1869/4000] Training [5/16] Loss: 0.00670 +Epoch [1869/4000] Training [6/16] Loss: 0.00482 +Epoch [1869/4000] Training [7/16] Loss: 0.00798 +Epoch [1869/4000] Training [8/16] Loss: 0.00489 +Epoch [1869/4000] Training [9/16] Loss: 0.00687 +Epoch [1869/4000] Training [10/16] Loss: 0.00739 +Epoch [1869/4000] Training [11/16] Loss: 0.00470 +Epoch [1869/4000] Training [12/16] Loss: 0.00767 +Epoch [1869/4000] Training [13/16] Loss: 0.00749 +Epoch [1869/4000] Training [14/16] Loss: 0.00655 +Epoch [1869/4000] Training [15/16] Loss: 0.00679 +Epoch [1869/4000] Training [16/16] Loss: 0.00572 +Epoch [1869/4000] Training metric {'Train/mean dice_metric': 0.9958285093307495, 'Train/mean miou_metric': 0.9914355874061584, 'Train/mean f1': 0.9916510581970215, 'Train/mean precision': 0.9871824979782104, 'Train/mean recall': 0.9961602687835693, 'Train/mean hd95_metric': 1.0039293766021729} +Epoch [1869/4000] Validation [1/4] Loss: 0.25263 focal_loss 0.18596 dice_loss 0.06667 +Epoch [1869/4000] Validation [2/4] Loss: 0.46343 focal_loss 0.31095 dice_loss 0.15248 +Epoch [1869/4000] Validation [3/4] Loss: 0.38134 focal_loss 0.28142 dice_loss 0.09992 +Epoch [1869/4000] Validation [4/4] Loss: 0.25432 focal_loss 0.16097 dice_loss 0.09334 +Epoch [1869/4000] Validation metric {'Val/mean dice_metric': 0.9743226766586304, 'Val/mean miou_metric': 0.9575357437133789, 'Val/mean f1': 0.9745742082595825, 'Val/mean precision': 0.9704523086547852, 'Val/mean recall': 0.9787312746047974, 'Val/mean hd95_metric': 5.474725246429443} +Cheakpoint... +Epoch [1869/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743226766586304, 'Val/mean miou_metric': 0.9575357437133789, 'Val/mean f1': 0.9745742082595825, 'Val/mean precision': 0.9704523086547852, 'Val/mean recall': 0.9787312746047974, 'Val/mean hd95_metric': 5.474725246429443} +Epoch [1870/4000] Training [1/16] Loss: 0.00605 +Epoch [1870/4000] Training [2/16] Loss: 0.00584 +Epoch [1870/4000] Training [3/16] Loss: 0.00559 +Epoch [1870/4000] Training [4/16] Loss: 0.00501 +Epoch [1870/4000] Training [5/16] Loss: 0.00835 +Epoch [1870/4000] Training [6/16] Loss: 0.01325 +Epoch [1870/4000] Training [7/16] Loss: 0.00448 +Epoch [1870/4000] Training [8/16] Loss: 0.00679 +Epoch [1870/4000] Training [9/16] Loss: 0.00551 +Epoch [1870/4000] Training [10/16] Loss: 0.00549 +Epoch [1870/4000] Training [11/16] Loss: 0.00524 +Epoch [1870/4000] Training [12/16] Loss: 0.00660 +Epoch [1870/4000] Training [13/16] Loss: 0.00756 +Epoch [1870/4000] Training [14/16] Loss: 0.00675 +Epoch [1870/4000] Training [15/16] Loss: 0.00867 +Epoch [1870/4000] Training [16/16] Loss: 0.00545 +Epoch [1870/4000] Training metric {'Train/mean dice_metric': 0.9938533306121826, 'Train/mean miou_metric': 0.9888439178466797, 'Train/mean f1': 0.9905461668968201, 'Train/mean precision': 0.9854840040206909, 'Train/mean recall': 0.9956604838371277, 'Train/mean hd95_metric': 1.4997106790542603} +Epoch [1870/4000] Validation [1/4] Loss: 0.41483 focal_loss 0.32697 dice_loss 0.08786 +Epoch [1870/4000] Validation [2/4] Loss: 0.52192 focal_loss 0.32566 dice_loss 0.19626 +Epoch [1870/4000] Validation [3/4] Loss: 0.35429 focal_loss 0.25942 dice_loss 0.09487 +Epoch [1870/4000] Validation [4/4] Loss: 0.42432 focal_loss 0.29286 dice_loss 0.13145 +Epoch [1870/4000] Validation metric {'Val/mean dice_metric': 0.968787670135498, 'Val/mean miou_metric': 0.9508447647094727, 'Val/mean f1': 0.9710547924041748, 'Val/mean precision': 0.9713395833969116, 'Val/mean recall': 0.9707700610160828, 'Val/mean hd95_metric': 5.892341136932373} +Cheakpoint... +Epoch [1870/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.968787670135498, 'Val/mean miou_metric': 0.9508447647094727, 'Val/mean f1': 0.9710547924041748, 'Val/mean precision': 0.9713395833969116, 'Val/mean recall': 0.9707700610160828, 'Val/mean hd95_metric': 5.892341136932373} +Epoch [1871/4000] Training [1/16] Loss: 0.00957 +Epoch [1871/4000] Training [2/16] Loss: 0.00831 +Epoch [1871/4000] Training [3/16] Loss: 0.00701 +Epoch [1871/4000] Training [4/16] Loss: 0.00624 +Epoch [1871/4000] Training [5/16] Loss: 0.00529 +Epoch [1871/4000] Training [6/16] Loss: 0.00478 +Epoch [1871/4000] Training [7/16] Loss: 0.00706 +Epoch [1871/4000] Training [8/16] Loss: 0.00504 +Epoch [1871/4000] Training [9/16] Loss: 0.00493 +Epoch [1871/4000] Training [10/16] Loss: 0.00773 +Epoch [1871/4000] Training [11/16] Loss: 0.00813 +Epoch [1871/4000] Training [12/16] Loss: 0.00656 +Epoch [1871/4000] Training [13/16] Loss: 0.00519 +Epoch [1871/4000] Training [14/16] Loss: 0.00675 +Epoch [1871/4000] Training [15/16] Loss: 0.00577 +Epoch [1871/4000] Training [16/16] Loss: 0.00871 +Epoch [1871/4000] Training metric {'Train/mean dice_metric': 0.9955800771713257, 'Train/mean miou_metric': 0.9909414649009705, 'Train/mean f1': 0.9913972616195679, 'Train/mean precision': 0.9869132041931152, 'Train/mean recall': 0.9959222078323364, 'Train/mean hd95_metric': 1.0212552547454834} +Epoch [1871/4000] Validation [1/4] Loss: 0.39626 focal_loss 0.30916 dice_loss 0.08711 +Epoch [1871/4000] Validation [2/4] Loss: 0.23620 focal_loss 0.13391 dice_loss 0.10228 +Epoch [1871/4000] Validation [3/4] Loss: 0.29220 focal_loss 0.20174 dice_loss 0.09046 +Epoch [1871/4000] Validation [4/4] Loss: 0.21620 focal_loss 0.13960 dice_loss 0.07660 +Epoch [1871/4000] Validation metric {'Val/mean dice_metric': 0.974356472492218, 'Val/mean miou_metric': 0.9573901295661926, 'Val/mean f1': 0.9738893508911133, 'Val/mean precision': 0.9727615118026733, 'Val/mean recall': 0.9750196933746338, 'Val/mean hd95_metric': 5.147744178771973} +Cheakpoint... +Epoch [1871/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974356472492218, 'Val/mean miou_metric': 0.9573901295661926, 'Val/mean f1': 0.9738893508911133, 'Val/mean precision': 0.9727615118026733, 'Val/mean recall': 0.9750196933746338, 'Val/mean hd95_metric': 5.147744178771973} +Epoch [1872/4000] Training [1/16] Loss: 0.00752 +Epoch [1872/4000] Training [2/16] Loss: 0.00563 +Epoch [1872/4000] Training [3/16] Loss: 0.00871 +Epoch [1872/4000] Training [4/16] Loss: 0.00693 +Epoch [1872/4000] Training [5/16] Loss: 0.00591 +Epoch [1872/4000] Training [6/16] Loss: 0.00759 +Epoch [1872/4000] Training [7/16] Loss: 0.00692 +Epoch [1872/4000] Training [8/16] Loss: 0.00759 +Epoch [1872/4000] Training [9/16] Loss: 0.00576 +Epoch [1872/4000] Training [10/16] Loss: 0.00585 +Epoch [1872/4000] Training [11/16] Loss: 0.00504 +Epoch [1872/4000] Training [12/16] Loss: 0.00637 +Epoch [1872/4000] Training [13/16] Loss: 0.00610 +Epoch [1872/4000] Training [14/16] Loss: 0.00908 +Epoch [1872/4000] Training [15/16] Loss: 0.00735 +Epoch [1872/4000] Training [16/16] Loss: 0.00594 +Epoch [1872/4000] Training metric {'Train/mean dice_metric': 0.9954410195350647, 'Train/mean miou_metric': 0.9906598329544067, 'Train/mean f1': 0.9913111925125122, 'Train/mean precision': 0.986638605594635, 'Train/mean recall': 0.9960282444953918, 'Train/mean hd95_metric': 1.0545432567596436} +Epoch [1872/4000] Validation [1/4] Loss: 0.28502 focal_loss 0.21302 dice_loss 0.07200 +Epoch [1872/4000] Validation [2/4] Loss: 0.61687 focal_loss 0.40003 dice_loss 0.21684 +Epoch [1872/4000] Validation [3/4] Loss: 0.31762 focal_loss 0.22404 dice_loss 0.09358 +Epoch [1872/4000] Validation [4/4] Loss: 0.32662 focal_loss 0.21844 dice_loss 0.10818 +Epoch [1872/4000] Validation metric {'Val/mean dice_metric': 0.9711230993270874, 'Val/mean miou_metric': 0.9537313580513, 'Val/mean f1': 0.9722994565963745, 'Val/mean precision': 0.9705173373222351, 'Val/mean recall': 0.9740881323814392, 'Val/mean hd95_metric': 5.393820762634277} +Cheakpoint... +Epoch [1872/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711230993270874, 'Val/mean miou_metric': 0.9537313580513, 'Val/mean f1': 0.9722994565963745, 'Val/mean precision': 0.9705173373222351, 'Val/mean recall': 0.9740881323814392, 'Val/mean hd95_metric': 5.393820762634277} +Epoch [1873/4000] Training [1/16] Loss: 0.00903 +Epoch [1873/4000] Training [2/16] Loss: 0.00699 +Epoch [1873/4000] Training [3/16] Loss: 0.00601 +Epoch [1873/4000] Training [4/16] Loss: 0.00661 +Epoch [1873/4000] Training [5/16] Loss: 0.00619 +Epoch [1873/4000] Training [6/16] Loss: 0.00717 +Epoch [1873/4000] Training [7/16] Loss: 0.01222 +Epoch [1873/4000] Training [8/16] Loss: 0.01022 +Epoch [1873/4000] Training [9/16] Loss: 0.00599 +Epoch [1873/4000] Training [10/16] Loss: 0.00667 +Epoch [1873/4000] Training [11/16] Loss: 0.00562 +Epoch [1873/4000] Training [12/16] Loss: 0.00602 +Epoch [1873/4000] Training [13/16] Loss: 0.00625 +Epoch [1873/4000] Training [14/16] Loss: 0.00693 +Epoch [1873/4000] Training [15/16] Loss: 0.00924 +Epoch [1873/4000] Training [16/16] Loss: 0.00712 +Epoch [1873/4000] Training metric {'Train/mean dice_metric': 0.9950650930404663, 'Train/mean miou_metric': 0.9899442195892334, 'Train/mean f1': 0.991154670715332, 'Train/mean precision': 0.9865788817405701, 'Train/mean recall': 0.9957731366157532, 'Train/mean hd95_metric': 1.0310002565383911} +Epoch [1873/4000] Validation [1/4] Loss: 0.24603 focal_loss 0.17459 dice_loss 0.07144 +Epoch [1873/4000] Validation [2/4] Loss: 0.32402 focal_loss 0.19745 dice_loss 0.12657 +Epoch [1873/4000] Validation [3/4] Loss: 0.33419 focal_loss 0.23817 dice_loss 0.09602 +Epoch [1873/4000] Validation [4/4] Loss: 0.19648 focal_loss 0.11368 dice_loss 0.08280 +Epoch [1873/4000] Validation metric {'Val/mean dice_metric': 0.9722188711166382, 'Val/mean miou_metric': 0.9550796747207642, 'Val/mean f1': 0.9739814400672913, 'Val/mean precision': 0.9720017910003662, 'Val/mean recall': 0.9759693145751953, 'Val/mean hd95_metric': 5.006590366363525} +Cheakpoint... +Epoch [1873/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722188711166382, 'Val/mean miou_metric': 0.9550796747207642, 'Val/mean f1': 0.9739814400672913, 'Val/mean precision': 0.9720017910003662, 'Val/mean recall': 0.9759693145751953, 'Val/mean hd95_metric': 5.006590366363525} +Epoch [1874/4000] Training [1/16] Loss: 0.00636 +Epoch [1874/4000] Training [2/16] Loss: 0.00541 +Epoch [1874/4000] Training [3/16] Loss: 0.00677 +Epoch [1874/4000] Training [4/16] Loss: 0.00623 +Epoch [1874/4000] Training [5/16] Loss: 0.00763 +Epoch [1874/4000] Training [6/16] Loss: 0.00705 +Epoch [1874/4000] Training [7/16] Loss: 0.00692 +Epoch [1874/4000] Training [8/16] Loss: 0.00769 +Epoch [1874/4000] Training [9/16] Loss: 0.00830 +Epoch [1874/4000] Training [10/16] Loss: 0.00682 +Epoch [1874/4000] Training [11/16] Loss: 0.00603 +Epoch [1874/4000] Training [12/16] Loss: 0.00931 +Epoch [1874/4000] Training [13/16] Loss: 0.00824 +Epoch [1874/4000] Training [14/16] Loss: 0.00771 +Epoch [1874/4000] Training [15/16] Loss: 0.00584 +Epoch [1874/4000] Training [16/16] Loss: 0.00641 +Epoch [1874/4000] Training metric {'Train/mean dice_metric': 0.994748055934906, 'Train/mean miou_metric': 0.9897421598434448, 'Train/mean f1': 0.9911467432975769, 'Train/mean precision': 0.9865961074829102, 'Train/mean recall': 0.9957395792007446, 'Train/mean hd95_metric': 1.065617322921753} +Epoch [1874/4000] Validation [1/4] Loss: 0.20971 focal_loss 0.14737 dice_loss 0.06234 +Epoch [1874/4000] Validation [2/4] Loss: 0.55862 focal_loss 0.35836 dice_loss 0.20027 +Epoch [1874/4000] Validation [3/4] Loss: 0.33271 focal_loss 0.23857 dice_loss 0.09414 +Epoch [1874/4000] Validation [4/4] Loss: 0.25506 focal_loss 0.15381 dice_loss 0.10124 +Epoch [1874/4000] Validation metric {'Val/mean dice_metric': 0.9710578918457031, 'Val/mean miou_metric': 0.9540239572525024, 'Val/mean f1': 0.9747012853622437, 'Val/mean precision': 0.9737358093261719, 'Val/mean recall': 0.975668728351593, 'Val/mean hd95_metric': 5.3760199546813965} +Cheakpoint... +Epoch [1874/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710578918457031, 'Val/mean miou_metric': 0.9540239572525024, 'Val/mean f1': 0.9747012853622437, 'Val/mean precision': 0.9737358093261719, 'Val/mean recall': 0.975668728351593, 'Val/mean hd95_metric': 5.3760199546813965} +Epoch [1875/4000] Training [1/16] Loss: 0.00550 +Epoch [1875/4000] Training [2/16] Loss: 0.00572 +Epoch [1875/4000] Training [3/16] Loss: 0.00686 +Epoch [1875/4000] Training [4/16] Loss: 0.00676 +Epoch [1875/4000] Training [5/16] Loss: 0.00591 +Epoch [1875/4000] Training [6/16] Loss: 0.00720 +Epoch [1875/4000] Training [7/16] Loss: 0.00535 +Epoch [1875/4000] Training [8/16] Loss: 0.00682 +Epoch [1875/4000] Training [9/16] Loss: 0.00739 +Epoch [1875/4000] Training [10/16] Loss: 0.00663 +Epoch [1875/4000] Training [11/16] Loss: 0.00810 +Epoch [1875/4000] Training [12/16] Loss: 0.00621 +Epoch [1875/4000] Training [13/16] Loss: 0.00540 +Epoch [1875/4000] Training [14/16] Loss: 0.00761 +Epoch [1875/4000] Training [15/16] Loss: 0.00870 +Epoch [1875/4000] Training [16/16] Loss: 0.00566 +Epoch [1875/4000] Training metric {'Train/mean dice_metric': 0.9956757426261902, 'Train/mean miou_metric': 0.9911293387413025, 'Train/mean f1': 0.991506814956665, 'Train/mean precision': 0.9870882630348206, 'Train/mean recall': 0.9959651231765747, 'Train/mean hd95_metric': 1.0226284265518188} +Epoch [1875/4000] Validation [1/4] Loss: 0.23980 focal_loss 0.17542 dice_loss 0.06438 +Epoch [1875/4000] Validation [2/4] Loss: 0.90652 focal_loss 0.60573 dice_loss 0.30079 +Epoch [1875/4000] Validation [3/4] Loss: 0.36492 focal_loss 0.26542 dice_loss 0.09950 +Epoch [1875/4000] Validation [4/4] Loss: 0.21881 focal_loss 0.13394 dice_loss 0.08487 +Epoch [1875/4000] Validation metric {'Val/mean dice_metric': 0.9722797274589539, 'Val/mean miou_metric': 0.9563773274421692, 'Val/mean f1': 0.9749799370765686, 'Val/mean precision': 0.9699493050575256, 'Val/mean recall': 0.9800630211830139, 'Val/mean hd95_metric': 5.373558044433594} +Cheakpoint... +Epoch [1875/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722797274589539, 'Val/mean miou_metric': 0.9563773274421692, 'Val/mean f1': 0.9749799370765686, 'Val/mean precision': 0.9699493050575256, 'Val/mean recall': 0.9800630211830139, 'Val/mean hd95_metric': 5.373558044433594} +Epoch [1876/4000] Training [1/16] Loss: 0.00676 +Epoch [1876/4000] Training [2/16] Loss: 0.00740 +Epoch [1876/4000] Training [3/16] Loss: 0.00533 +Epoch [1876/4000] Training [4/16] Loss: 0.00527 +Epoch [1876/4000] Training [5/16] Loss: 0.00774 +Epoch [1876/4000] Training [6/16] Loss: 0.00609 +Epoch [1876/4000] Training [7/16] Loss: 0.00580 +Epoch [1876/4000] Training [8/16] Loss: 0.00510 +Epoch [1876/4000] Training [9/16] Loss: 0.00769 +Epoch [1876/4000] Training [10/16] Loss: 0.00675 +Epoch [1876/4000] Training [11/16] Loss: 0.00717 +Epoch [1876/4000] Training [12/16] Loss: 0.00540 +Epoch [1876/4000] Training [13/16] Loss: 0.00586 +Epoch [1876/4000] Training [14/16] Loss: 0.00698 +Epoch [1876/4000] Training [15/16] Loss: 0.00602 +Epoch [1876/4000] Training [16/16] Loss: 0.00855 +Epoch [1876/4000] Training metric {'Train/mean dice_metric': 0.995672881603241, 'Train/mean miou_metric': 0.9911173582077026, 'Train/mean f1': 0.9914173483848572, 'Train/mean precision': 0.9868692755699158, 'Train/mean recall': 0.9960075616836548, 'Train/mean hd95_metric': 1.0108481645584106} +Epoch [1876/4000] Validation [1/4] Loss: 0.27691 focal_loss 0.20912 dice_loss 0.06779 +Epoch [1876/4000] Validation [2/4] Loss: 0.32502 focal_loss 0.18905 dice_loss 0.13597 +Epoch [1876/4000] Validation [3/4] Loss: 0.35242 focal_loss 0.25644 dice_loss 0.09598 +Epoch [1876/4000] Validation [4/4] Loss: 0.26402 focal_loss 0.16195 dice_loss 0.10208 +Epoch [1876/4000] Validation metric {'Val/mean dice_metric': 0.9717022180557251, 'Val/mean miou_metric': 0.9545654058456421, 'Val/mean f1': 0.9730391502380371, 'Val/mean precision': 0.9697098135948181, 'Val/mean recall': 0.9763914942741394, 'Val/mean hd95_metric': 5.905413627624512} +Cheakpoint... +Epoch [1876/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717022180557251, 'Val/mean miou_metric': 0.9545654058456421, 'Val/mean f1': 0.9730391502380371, 'Val/mean precision': 0.9697098135948181, 'Val/mean recall': 0.9763914942741394, 'Val/mean hd95_metric': 5.905413627624512} +Epoch [1877/4000] Training [1/16] Loss: 0.00748 +Epoch [1877/4000] Training [2/16] Loss: 0.00570 +Epoch [1877/4000] Training [3/16] Loss: 0.00567 +Epoch [1877/4000] Training [4/16] Loss: 0.00591 +Epoch [1877/4000] Training [5/16] Loss: 0.00650 +Epoch [1877/4000] Training [6/16] Loss: 0.00655 +Epoch [1877/4000] Training [7/16] Loss: 0.00562 +Epoch [1877/4000] Training [8/16] Loss: 0.00511 +Epoch [1877/4000] Training [9/16] Loss: 0.00626 +Epoch [1877/4000] Training [10/16] Loss: 0.00781 +Epoch [1877/4000] Training [11/16] Loss: 0.00829 +Epoch [1877/4000] Training [12/16] Loss: 0.00456 +Epoch [1877/4000] Training [13/16] Loss: 0.00793 +Epoch [1877/4000] Training [14/16] Loss: 0.00575 +Epoch [1877/4000] Training [15/16] Loss: 0.00581 +Epoch [1877/4000] Training [16/16] Loss: 0.00766 +Epoch [1877/4000] Training metric {'Train/mean dice_metric': 0.9957265853881836, 'Train/mean miou_metric': 0.9912363290786743, 'Train/mean f1': 0.9916656613349915, 'Train/mean precision': 0.9871799945831299, 'Train/mean recall': 0.9961923360824585, 'Train/mean hd95_metric': 1.006995439529419} +Epoch [1877/4000] Validation [1/4] Loss: 0.26410 focal_loss 0.20130 dice_loss 0.06280 +Epoch [1877/4000] Validation [2/4] Loss: 0.28127 focal_loss 0.17025 dice_loss 0.11102 +Epoch [1877/4000] Validation [3/4] Loss: 0.32862 focal_loss 0.23629 dice_loss 0.09233 +Epoch [1877/4000] Validation [4/4] Loss: 0.25897 focal_loss 0.16053 dice_loss 0.09844 +Epoch [1877/4000] Validation metric {'Val/mean dice_metric': 0.9743224382400513, 'Val/mean miou_metric': 0.9577504396438599, 'Val/mean f1': 0.9752996563911438, 'Val/mean precision': 0.97261643409729, 'Val/mean recall': 0.9779977202415466, 'Val/mean hd95_metric': 5.436119079589844} +Cheakpoint... +Epoch [1877/4000] best acc:tensor([0.9746], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743224382400513, 'Val/mean miou_metric': 0.9577504396438599, 'Val/mean f1': 0.9752996563911438, 'Val/mean precision': 0.97261643409729, 'Val/mean recall': 0.9779977202415466, 'Val/mean hd95_metric': 5.436119079589844} +Epoch [1878/4000] Training [1/16] Loss: 0.00494 +Epoch [1878/4000] Training [2/16] Loss: 0.00770 +Epoch [1878/4000] Training [3/16] Loss: 0.00553 +Epoch [1878/4000] Training [4/16] Loss: 0.00560 +Epoch [1878/4000] Training [5/16] Loss: 0.00510 +Epoch [1878/4000] Training [6/16] Loss: 0.00711 +Epoch [1878/4000] Training [7/16] Loss: 0.00654 +Epoch [1878/4000] Training [8/16] Loss: 0.00599 +Epoch [1878/4000] Training [9/16] Loss: 0.00514 +Epoch [1878/4000] Training [10/16] Loss: 0.00642 +Epoch [1878/4000] Training [11/16] Loss: 0.00518 +Epoch [1878/4000] Training [12/16] Loss: 0.00741 +Epoch [1878/4000] Training [13/16] Loss: 0.00579 +Epoch [1878/4000] Training [14/16] Loss: 0.00668 +Epoch [1878/4000] Training [15/16] Loss: 0.00644 +Epoch [1878/4000] Training [16/16] Loss: 0.00823 +Epoch [1878/4000] Training metric {'Train/mean dice_metric': 0.9959638118743896, 'Train/mean miou_metric': 0.9917019009590149, 'Train/mean f1': 0.9916665554046631, 'Train/mean precision': 0.9870598912239075, 'Train/mean recall': 0.9963164329528809, 'Train/mean hd95_metric': 1.0051432847976685} +Epoch [1878/4000] Validation [1/4] Loss: 0.23061 focal_loss 0.16652 dice_loss 0.06409 +Epoch [1878/4000] Validation [2/4] Loss: 0.30049 focal_loss 0.18296 dice_loss 0.11753 +Epoch [1878/4000] Validation [3/4] Loss: 0.30787 focal_loss 0.21601 dice_loss 0.09186 +Epoch [1878/4000] Validation [4/4] Loss: 0.20862 focal_loss 0.12045 dice_loss 0.08817 +Epoch [1878/4000] Validation metric {'Val/mean dice_metric': 0.9758739471435547, 'Val/mean miou_metric': 0.9593409299850464, 'Val/mean f1': 0.9762205481529236, 'Val/mean precision': 0.9722182750701904, 'Val/mean recall': 0.9802559614181519, 'Val/mean hd95_metric': 5.105853080749512} +Cheakpoint... +Epoch [1878/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758739471435547, 'Val/mean miou_metric': 0.9593409299850464, 'Val/mean f1': 0.9762205481529236, 'Val/mean precision': 0.9722182750701904, 'Val/mean recall': 0.9802559614181519, 'Val/mean hd95_metric': 5.105853080749512} +Epoch [1879/4000] Training [1/16] Loss: 0.00582 +Epoch [1879/4000] Training [2/16] Loss: 0.00603 +Epoch [1879/4000] Training [3/16] Loss: 0.00587 +Epoch [1879/4000] Training [4/16] Loss: 0.00551 +Epoch [1879/4000] Training [5/16] Loss: 0.00652 +Epoch [1879/4000] Training [6/16] Loss: 0.00649 +Epoch [1879/4000] Training [7/16] Loss: 0.00597 +Epoch [1879/4000] Training [8/16] Loss: 0.00572 +Epoch [1879/4000] Training [9/16] Loss: 0.00517 +Epoch [1879/4000] Training [10/16] Loss: 0.00629 +Epoch [1879/4000] Training [11/16] Loss: 0.01059 +Epoch [1879/4000] Training [12/16] Loss: 0.00562 +Epoch [1879/4000] Training [13/16] Loss: 0.00753 +Epoch [1879/4000] Training [14/16] Loss: 0.00544 +Epoch [1879/4000] Training [15/16] Loss: 0.00513 +Epoch [1879/4000] Training [16/16] Loss: 0.00978 +Epoch [1879/4000] Training metric {'Train/mean dice_metric': 0.9957259893417358, 'Train/mean miou_metric': 0.9912335276603699, 'Train/mean f1': 0.9917518496513367, 'Train/mean precision': 0.9873790144920349, 'Train/mean recall': 0.996163547039032, 'Train/mean hd95_metric': 1.011857509613037} +Epoch [1879/4000] Validation [1/4] Loss: 0.30832 focal_loss 0.23526 dice_loss 0.07306 +Epoch [1879/4000] Validation [2/4] Loss: 0.58231 focal_loss 0.37186 dice_loss 0.21045 +Epoch [1879/4000] Validation [3/4] Loss: 0.31390 focal_loss 0.22189 dice_loss 0.09201 +Epoch [1879/4000] Validation [4/4] Loss: 0.20409 focal_loss 0.11924 dice_loss 0.08485 +Epoch [1879/4000] Validation metric {'Val/mean dice_metric': 0.9717361330986023, 'Val/mean miou_metric': 0.9556055068969727, 'Val/mean f1': 0.9744913578033447, 'Val/mean precision': 0.972213625907898, 'Val/mean recall': 0.9767798185348511, 'Val/mean hd95_metric': 5.212954998016357} +Cheakpoint... +Epoch [1879/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717361330986023, 'Val/mean miou_metric': 0.9556055068969727, 'Val/mean f1': 0.9744913578033447, 'Val/mean precision': 0.972213625907898, 'Val/mean recall': 0.9767798185348511, 'Val/mean hd95_metric': 5.212954998016357} +Epoch [1880/4000] Training [1/16] Loss: 0.00903 +Epoch [1880/4000] Training [2/16] Loss: 0.00556 +Epoch [1880/4000] Training [3/16] Loss: 0.00485 +Epoch [1880/4000] Training [4/16] Loss: 0.00777 +Epoch [1880/4000] Training [5/16] Loss: 0.00561 +Epoch [1880/4000] Training [6/16] Loss: 0.00653 +Epoch [1880/4000] Training [7/16] Loss: 0.00691 +Epoch [1880/4000] Training [8/16] Loss: 0.00647 +Epoch [1880/4000] Training [9/16] Loss: 0.00778 +Epoch [1880/4000] Training [10/16] Loss: 0.00621 +Epoch [1880/4000] Training [11/16] Loss: 0.00682 +Epoch [1880/4000] Training [12/16] Loss: 0.00644 +Epoch [1880/4000] Training [13/16] Loss: 0.00589 +Epoch [1880/4000] Training [14/16] Loss: 0.00426 +Epoch [1880/4000] Training [15/16] Loss: 0.00596 +Epoch [1880/4000] Training [16/16] Loss: 0.00698 +Epoch [1880/4000] Training metric {'Train/mean dice_metric': 0.9957443475723267, 'Train/mean miou_metric': 0.9912270903587341, 'Train/mean f1': 0.9907622933387756, 'Train/mean precision': 0.9853747487068176, 'Train/mean recall': 0.9962089657783508, 'Train/mean hd95_metric': 1.0107169151306152} +Epoch [1880/4000] Validation [1/4] Loss: 0.29088 focal_loss 0.21494 dice_loss 0.07593 +Epoch [1880/4000] Validation [2/4] Loss: 0.27078 focal_loss 0.16084 dice_loss 0.10995 +Epoch [1880/4000] Validation [3/4] Loss: 0.35055 focal_loss 0.25598 dice_loss 0.09456 +Epoch [1880/4000] Validation [4/4] Loss: 0.23865 focal_loss 0.14181 dice_loss 0.09684 +Epoch [1880/4000] Validation metric {'Val/mean dice_metric': 0.9737429618835449, 'Val/mean miou_metric': 0.9571934938430786, 'Val/mean f1': 0.9741463661193848, 'Val/mean precision': 0.9704893827438354, 'Val/mean recall': 0.9778311252593994, 'Val/mean hd95_metric': 5.196812629699707} +Cheakpoint... +Epoch [1880/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737429618835449, 'Val/mean miou_metric': 0.9571934938430786, 'Val/mean f1': 0.9741463661193848, 'Val/mean precision': 0.9704893827438354, 'Val/mean recall': 0.9778311252593994, 'Val/mean hd95_metric': 5.196812629699707} +Epoch [1881/4000] Training [1/16] Loss: 0.00585 +Epoch [1881/4000] Training [2/16] Loss: 0.00801 +Epoch [1881/4000] Training [3/16] Loss: 0.00719 +Epoch [1881/4000] Training [4/16] Loss: 0.00569 +Epoch [1881/4000] Training [5/16] Loss: 0.00442 +Epoch [1881/4000] Training [6/16] Loss: 0.00999 +Epoch [1881/4000] Training [7/16] Loss: 0.00716 +Epoch [1881/4000] Training [8/16] Loss: 0.00646 +Epoch [1881/4000] Training [9/16] Loss: 0.00683 +Epoch [1881/4000] Training [10/16] Loss: 0.00622 +Epoch [1881/4000] Training [11/16] Loss: 0.00555 +Epoch [1881/4000] Training [12/16] Loss: 0.00554 +Epoch [1881/4000] Training [13/16] Loss: 0.00627 +Epoch [1881/4000] Training [14/16] Loss: 0.01428 +Epoch [1881/4000] Training [15/16] Loss: 0.00585 +Epoch [1881/4000] Training [16/16] Loss: 0.00536 +Epoch [1881/4000] Training metric {'Train/mean dice_metric': 0.9955847263336182, 'Train/mean miou_metric': 0.9909586906433105, 'Train/mean f1': 0.9915381669998169, 'Train/mean precision': 0.9869319200515747, 'Train/mean recall': 0.9961875677108765, 'Train/mean hd95_metric': 1.0467185974121094} +Epoch [1881/4000] Validation [1/4] Loss: 0.25723 focal_loss 0.19070 dice_loss 0.06653 +Epoch [1881/4000] Validation [2/4] Loss: 0.32313 focal_loss 0.20169 dice_loss 0.12144 +Epoch [1881/4000] Validation [3/4] Loss: 0.35919 focal_loss 0.26026 dice_loss 0.09892 +Epoch [1881/4000] Validation [4/4] Loss: 0.32400 focal_loss 0.20578 dice_loss 0.11822 +Epoch [1881/4000] Validation metric {'Val/mean dice_metric': 0.9731433987617493, 'Val/mean miou_metric': 0.9562146067619324, 'Val/mean f1': 0.9746925234794617, 'Val/mean precision': 0.9736911058425903, 'Val/mean recall': 0.9756959676742554, 'Val/mean hd95_metric': 5.622925758361816} +Cheakpoint... +Epoch [1881/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731433987617493, 'Val/mean miou_metric': 0.9562146067619324, 'Val/mean f1': 0.9746925234794617, 'Val/mean precision': 0.9736911058425903, 'Val/mean recall': 0.9756959676742554, 'Val/mean hd95_metric': 5.622925758361816} +Epoch [1882/4000] Training [1/16] Loss: 0.00442 +Epoch [1882/4000] Training [2/16] Loss: 0.00511 +Epoch [1882/4000] Training [3/16] Loss: 0.00527 +Epoch [1882/4000] Training [4/16] Loss: 0.00592 +Epoch [1882/4000] Training [5/16] Loss: 0.00684 +Epoch [1882/4000] Training [6/16] Loss: 0.00624 +Epoch [1882/4000] Training [7/16] Loss: 0.00699 +Epoch [1882/4000] Training [8/16] Loss: 0.00703 +Epoch [1882/4000] Training [9/16] Loss: 0.00712 +Epoch [1882/4000] Training [10/16] Loss: 0.00663 +Epoch [1882/4000] Training [11/16] Loss: 0.00587 +Epoch [1882/4000] Training [12/16] Loss: 0.00772 +Epoch [1882/4000] Training [13/16] Loss: 0.00466 +Epoch [1882/4000] Training [14/16] Loss: 0.00666 +Epoch [1882/4000] Training [15/16] Loss: 0.00659 +Epoch [1882/4000] Training [16/16] Loss: 0.00886 +Epoch [1882/4000] Training metric {'Train/mean dice_metric': 0.995500385761261, 'Train/mean miou_metric': 0.9907721281051636, 'Train/mean f1': 0.991157591342926, 'Train/mean precision': 0.9865119457244873, 'Train/mean recall': 0.9958473443984985, 'Train/mean hd95_metric': 1.0192863941192627} +Epoch [1882/4000] Validation [1/4] Loss: 0.23339 focal_loss 0.16864 dice_loss 0.06474 +Epoch [1882/4000] Validation [2/4] Loss: 0.31911 focal_loss 0.19207 dice_loss 0.12704 +Epoch [1882/4000] Validation [3/4] Loss: 0.23980 focal_loss 0.14979 dice_loss 0.09002 +Epoch [1882/4000] Validation [4/4] Loss: 0.31874 focal_loss 0.19774 dice_loss 0.12100 +Epoch [1882/4000] Validation metric {'Val/mean dice_metric': 0.9715030789375305, 'Val/mean miou_metric': 0.9543437957763672, 'Val/mean f1': 0.9740238189697266, 'Val/mean precision': 0.9725180864334106, 'Val/mean recall': 0.9755343198776245, 'Val/mean hd95_metric': 5.426880836486816} +Cheakpoint... +Epoch [1882/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715030789375305, 'Val/mean miou_metric': 0.9543437957763672, 'Val/mean f1': 0.9740238189697266, 'Val/mean precision': 0.9725180864334106, 'Val/mean recall': 0.9755343198776245, 'Val/mean hd95_metric': 5.426880836486816} +Epoch [1883/4000] Training [1/16] Loss: 0.00583 +Epoch [1883/4000] Training [2/16] Loss: 0.00479 +Epoch [1883/4000] Training [3/16] Loss: 0.00539 +Epoch [1883/4000] Training [4/16] Loss: 0.00643 +Epoch [1883/4000] Training [5/16] Loss: 0.00704 +Epoch [1883/4000] Training [6/16] Loss: 0.00595 +Epoch [1883/4000] Training [7/16] Loss: 0.00600 +Epoch [1883/4000] Training [8/16] Loss: 0.00562 +Epoch [1883/4000] Training [9/16] Loss: 0.00588 +Epoch [1883/4000] Training [10/16] Loss: 0.00719 +Epoch [1883/4000] Training [11/16] Loss: 0.00902 +Epoch [1883/4000] Training [12/16] Loss: 0.00841 +Epoch [1883/4000] Training [13/16] Loss: 0.00574 +Epoch [1883/4000] Training [14/16] Loss: 0.00625 +Epoch [1883/4000] Training [15/16] Loss: 0.00886 +Epoch [1883/4000] Training [16/16] Loss: 0.00672 +Epoch [1883/4000] Training metric {'Train/mean dice_metric': 0.9954303503036499, 'Train/mean miou_metric': 0.9906442165374756, 'Train/mean f1': 0.9913560748100281, 'Train/mean precision': 0.9868367910385132, 'Train/mean recall': 0.9959168434143066, 'Train/mean hd95_metric': 1.0156848430633545} +Epoch [1883/4000] Validation [1/4] Loss: 0.35541 focal_loss 0.26388 dice_loss 0.09153 +Epoch [1883/4000] Validation [2/4] Loss: 0.31154 focal_loss 0.19268 dice_loss 0.11886 +Epoch [1883/4000] Validation [3/4] Loss: 0.30229 focal_loss 0.20851 dice_loss 0.09378 +Epoch [1883/4000] Validation [4/4] Loss: 0.43713 focal_loss 0.28203 dice_loss 0.15510 +Epoch [1883/4000] Validation metric {'Val/mean dice_metric': 0.9699841737747192, 'Val/mean miou_metric': 0.9526581764221191, 'Val/mean f1': 0.9722460508346558, 'Val/mean precision': 0.9724500179290771, 'Val/mean recall': 0.9720422625541687, 'Val/mean hd95_metric': 5.0928802490234375} +Cheakpoint... +Epoch [1883/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699841737747192, 'Val/mean miou_metric': 0.9526581764221191, 'Val/mean f1': 0.9722460508346558, 'Val/mean precision': 0.9724500179290771, 'Val/mean recall': 0.9720422625541687, 'Val/mean hd95_metric': 5.0928802490234375} +Epoch [1884/4000] Training [1/16] Loss: 0.01277 +Epoch [1884/4000] Training [2/16] Loss: 0.00570 +Epoch [1884/4000] Training [3/16] Loss: 0.00507 +Epoch [1884/4000] Training [4/16] Loss: 0.00595 +Epoch [1884/4000] Training [5/16] Loss: 0.00729 +Epoch [1884/4000] Training [6/16] Loss: 0.00686 +Epoch [1884/4000] Training [7/16] Loss: 0.00555 +Epoch [1884/4000] Training [8/16] Loss: 0.00833 +Epoch [1884/4000] Training [9/16] Loss: 0.00498 +Epoch [1884/4000] Training [10/16] Loss: 0.00672 +Epoch [1884/4000] Training [11/16] Loss: 0.00601 +Epoch [1884/4000] Training [12/16] Loss: 0.00524 +Epoch [1884/4000] Training [13/16] Loss: 0.00723 +Epoch [1884/4000] Training [14/16] Loss: 0.00775 +Epoch [1884/4000] Training [15/16] Loss: 0.00679 +Epoch [1884/4000] Training [16/16] Loss: 0.00662 +Epoch [1884/4000] Training metric {'Train/mean dice_metric': 0.9954224824905396, 'Train/mean miou_metric': 0.9906269907951355, 'Train/mean f1': 0.9913217425346375, 'Train/mean precision': 0.986786425113678, 'Train/mean recall': 0.995898962020874, 'Train/mean hd95_metric': 1.0253757238388062} +Epoch [1884/4000] Validation [1/4] Loss: 0.25472 focal_loss 0.19064 dice_loss 0.06408 +Epoch [1884/4000] Validation [2/4] Loss: 0.48404 focal_loss 0.31469 dice_loss 0.16935 +Epoch [1884/4000] Validation [3/4] Loss: 0.36431 focal_loss 0.26898 dice_loss 0.09533 +Epoch [1884/4000] Validation [4/4] Loss: 0.41396 focal_loss 0.26859 dice_loss 0.14537 +Epoch [1884/4000] Validation metric {'Val/mean dice_metric': 0.9717143177986145, 'Val/mean miou_metric': 0.9549808502197266, 'Val/mean f1': 0.9739477634429932, 'Val/mean precision': 0.9708441495895386, 'Val/mean recall': 0.9770711660385132, 'Val/mean hd95_metric': 5.243062973022461} +Cheakpoint... +Epoch [1884/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717143177986145, 'Val/mean miou_metric': 0.9549808502197266, 'Val/mean f1': 0.9739477634429932, 'Val/mean precision': 0.9708441495895386, 'Val/mean recall': 0.9770711660385132, 'Val/mean hd95_metric': 5.243062973022461} +Epoch [1885/4000] Training [1/16] Loss: 0.00611 +Epoch [1885/4000] Training [2/16] Loss: 0.00530 +Epoch [1885/4000] Training [3/16] Loss: 0.00491 +Epoch [1885/4000] Training [4/16] Loss: 0.01140 +Epoch [1885/4000] Training [5/16] Loss: 0.00793 +Epoch [1885/4000] Training [6/16] Loss: 0.00760 +Epoch [1885/4000] Training [7/16] Loss: 0.00599 +Epoch [1885/4000] Training [8/16] Loss: 0.00674 +Epoch [1885/4000] Training [9/16] Loss: 0.01200 +Epoch [1885/4000] Training [10/16] Loss: 0.00683 +Epoch [1885/4000] Training [11/16] Loss: 0.00946 +Epoch [1885/4000] Training [12/16] Loss: 0.00581 +Epoch [1885/4000] Training [13/16] Loss: 0.00466 +Epoch [1885/4000] Training [14/16] Loss: 0.00715 +Epoch [1885/4000] Training [15/16] Loss: 0.00693 +Epoch [1885/4000] Training [16/16] Loss: 0.00763 +Epoch [1885/4000] Training metric {'Train/mean dice_metric': 0.9953691363334656, 'Train/mean miou_metric': 0.990501880645752, 'Train/mean f1': 0.9906609058380127, 'Train/mean precision': 0.9855973720550537, 'Train/mean recall': 0.9957767724990845, 'Train/mean hd95_metric': 1.0288257598876953} +Epoch [1885/4000] Validation [1/4] Loss: 0.26886 focal_loss 0.20223 dice_loss 0.06664 +Epoch [1885/4000] Validation [2/4] Loss: 0.29246 focal_loss 0.17949 dice_loss 0.11297 +Epoch [1885/4000] Validation [3/4] Loss: 0.36691 focal_loss 0.27509 dice_loss 0.09183 +Epoch [1885/4000] Validation [4/4] Loss: 0.35837 focal_loss 0.22498 dice_loss 0.13339 +Epoch [1885/4000] Validation metric {'Val/mean dice_metric': 0.9738913774490356, 'Val/mean miou_metric': 0.956381618976593, 'Val/mean f1': 0.9740888476371765, 'Val/mean precision': 0.9698595404624939, 'Val/mean recall': 0.978355348110199, 'Val/mean hd95_metric': 5.72739839553833} +Cheakpoint... +Epoch [1885/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738913774490356, 'Val/mean miou_metric': 0.956381618976593, 'Val/mean f1': 0.9740888476371765, 'Val/mean precision': 0.9698595404624939, 'Val/mean recall': 0.978355348110199, 'Val/mean hd95_metric': 5.72739839553833} +Epoch [1886/4000] Training [1/16] Loss: 0.00999 +Epoch [1886/4000] Training [2/16] Loss: 0.00719 +Epoch [1886/4000] Training [3/16] Loss: 0.00945 +Epoch [1886/4000] Training [4/16] Loss: 0.01708 +Epoch [1886/4000] Training [5/16] Loss: 0.00641 +Epoch [1886/4000] Training [6/16] Loss: 0.00588 +Epoch [1886/4000] Training [7/16] Loss: 0.00565 +Epoch [1886/4000] Training [8/16] Loss: 0.00433 +Epoch [1886/4000] Training [9/16] Loss: 0.00999 +Epoch [1886/4000] Training [10/16] Loss: 0.00590 +Epoch [1886/4000] Training [11/16] Loss: 0.00705 +Epoch [1886/4000] Training [12/16] Loss: 0.00719 +Epoch [1886/4000] Training [13/16] Loss: 0.00856 +Epoch [1886/4000] Training [14/16] Loss: 0.00550 +Epoch [1886/4000] Training [15/16] Loss: 0.00556 +Epoch [1886/4000] Training [16/16] Loss: 0.00644 +Epoch [1886/4000] Training metric {'Train/mean dice_metric': 0.9949359893798828, 'Train/mean miou_metric': 0.9896910786628723, 'Train/mean f1': 0.9911112189292908, 'Train/mean precision': 0.9866030216217041, 'Train/mean recall': 0.9956607818603516, 'Train/mean hd95_metric': 1.098620891571045} +Epoch [1886/4000] Validation [1/4] Loss: 0.30607 focal_loss 0.22415 dice_loss 0.08192 +Epoch [1886/4000] Validation [2/4] Loss: 0.31566 focal_loss 0.19347 dice_loss 0.12220 +Epoch [1886/4000] Validation [3/4] Loss: 0.34588 focal_loss 0.25409 dice_loss 0.09178 +Epoch [1886/4000] Validation [4/4] Loss: 0.29846 focal_loss 0.18972 dice_loss 0.10874 +Epoch [1886/4000] Validation metric {'Val/mean dice_metric': 0.9725321531295776, 'Val/mean miou_metric': 0.9546530842781067, 'Val/mean f1': 0.9738196134567261, 'Val/mean precision': 0.9730221033096313, 'Val/mean recall': 0.9746185541152954, 'Val/mean hd95_metric': 5.814951419830322} +Cheakpoint... +Epoch [1886/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725321531295776, 'Val/mean miou_metric': 0.9546530842781067, 'Val/mean f1': 0.9738196134567261, 'Val/mean precision': 0.9730221033096313, 'Val/mean recall': 0.9746185541152954, 'Val/mean hd95_metric': 5.814951419830322} +Epoch [1887/4000] Training [1/16] Loss: 0.00772 +Epoch [1887/4000] Training [2/16] Loss: 0.00566 +Epoch [1887/4000] Training [3/16] Loss: 0.00782 +Epoch [1887/4000] Training [4/16] Loss: 0.01084 +Epoch [1887/4000] Training [5/16] Loss: 0.00592 +Epoch [1887/4000] Training [6/16] Loss: 0.00736 +Epoch [1887/4000] Training [7/16] Loss: 0.00572 +Epoch [1887/4000] Training [8/16] Loss: 0.00958 +Epoch [1887/4000] Training [9/16] Loss: 0.00871 +Epoch [1887/4000] Training [10/16] Loss: 0.00928 +Epoch [1887/4000] Training [11/16] Loss: 0.00694 +Epoch [1887/4000] Training [12/16] Loss: 0.00794 +Epoch [1887/4000] Training [13/16] Loss: 0.00798 +Epoch [1887/4000] Training [14/16] Loss: 0.00637 +Epoch [1887/4000] Training [15/16] Loss: 0.00582 +Epoch [1887/4000] Training [16/16] Loss: 0.00531 +Epoch [1887/4000] Training metric {'Train/mean dice_metric': 0.9952962398529053, 'Train/mean miou_metric': 0.9903862476348877, 'Train/mean f1': 0.9911437630653381, 'Train/mean precision': 0.9866107106208801, 'Train/mean recall': 0.9957187175750732, 'Train/mean hd95_metric': 1.019229769706726} +Epoch [1887/4000] Validation [1/4] Loss: 0.29350 focal_loss 0.21615 dice_loss 0.07735 +Epoch [1887/4000] Validation [2/4] Loss: 0.27722 focal_loss 0.17059 dice_loss 0.10663 +Epoch [1887/4000] Validation [3/4] Loss: 0.32269 focal_loss 0.22949 dice_loss 0.09319 +Epoch [1887/4000] Validation [4/4] Loss: 0.32516 focal_loss 0.20089 dice_loss 0.12427 +Epoch [1887/4000] Validation metric {'Val/mean dice_metric': 0.9748433828353882, 'Val/mean miou_metric': 0.9575087428092957, 'Val/mean f1': 0.9748250246047974, 'Val/mean precision': 0.9720767140388489, 'Val/mean recall': 0.9775888919830322, 'Val/mean hd95_metric': 5.099100112915039} +Cheakpoint... +Epoch [1887/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748433828353882, 'Val/mean miou_metric': 0.9575087428092957, 'Val/mean f1': 0.9748250246047974, 'Val/mean precision': 0.9720767140388489, 'Val/mean recall': 0.9775888919830322, 'Val/mean hd95_metric': 5.099100112915039} +Epoch [1888/4000] Training [1/16] Loss: 0.00798 +Epoch [1888/4000] Training [2/16] Loss: 0.00672 +Epoch [1888/4000] Training [3/16] Loss: 0.00648 +Epoch [1888/4000] Training [4/16] Loss: 0.00639 +Epoch [1888/4000] Training [5/16] Loss: 0.00779 +Epoch [1888/4000] Training [6/16] Loss: 0.00574 +Epoch [1888/4000] Training [7/16] Loss: 0.00538 +Epoch [1888/4000] Training [8/16] Loss: 0.00661 +Epoch [1888/4000] Training [9/16] Loss: 0.00461 +Epoch [1888/4000] Training [10/16] Loss: 0.00950 +Epoch [1888/4000] Training [11/16] Loss: 0.00674 +Epoch [1888/4000] Training [12/16] Loss: 0.00703 +Epoch [1888/4000] Training [13/16] Loss: 0.00894 +Epoch [1888/4000] Training [14/16] Loss: 0.00657 +Epoch [1888/4000] Training [15/16] Loss: 0.00664 +Epoch [1888/4000] Training [16/16] Loss: 0.00526 +Epoch [1888/4000] Training metric {'Train/mean dice_metric': 0.9955374002456665, 'Train/mean miou_metric': 0.9908323884010315, 'Train/mean f1': 0.9906935691833496, 'Train/mean precision': 0.9856882691383362, 'Train/mean recall': 0.9957500696182251, 'Train/mean hd95_metric': 1.1906249523162842} +Epoch [1888/4000] Validation [1/4] Loss: 0.30895 focal_loss 0.23439 dice_loss 0.07455 +Epoch [1888/4000] Validation [2/4] Loss: 0.62561 focal_loss 0.42259 dice_loss 0.20302 +Epoch [1888/4000] Validation [3/4] Loss: 0.25074 focal_loss 0.15584 dice_loss 0.09490 +Epoch [1888/4000] Validation [4/4] Loss: 0.27958 focal_loss 0.17184 dice_loss 0.10775 +Epoch [1888/4000] Validation metric {'Val/mean dice_metric': 0.9729811549186707, 'Val/mean miou_metric': 0.9564154744148254, 'Val/mean f1': 0.9737716317176819, 'Val/mean precision': 0.9703326225280762, 'Val/mean recall': 0.9772350788116455, 'Val/mean hd95_metric': 5.60598087310791} +Cheakpoint... +Epoch [1888/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729811549186707, 'Val/mean miou_metric': 0.9564154744148254, 'Val/mean f1': 0.9737716317176819, 'Val/mean precision': 0.9703326225280762, 'Val/mean recall': 0.9772350788116455, 'Val/mean hd95_metric': 5.60598087310791} +Epoch [1889/4000] Training [1/16] Loss: 0.00843 +Epoch [1889/4000] Training [2/16] Loss: 0.00942 +Epoch [1889/4000] Training [3/16] Loss: 0.00900 +Epoch [1889/4000] Training [4/16] Loss: 0.00734 +Epoch [1889/4000] Training [5/16] Loss: 0.00578 +Epoch [1889/4000] Training [6/16] Loss: 0.00655 +Epoch [1889/4000] Training [7/16] Loss: 0.00743 +Epoch [1889/4000] Training [8/16] Loss: 0.00669 +Epoch [1889/4000] Training [9/16] Loss: 0.00638 +Epoch [1889/4000] Training [10/16] Loss: 0.00592 +Epoch [1889/4000] Training [11/16] Loss: 0.00546 +Epoch [1889/4000] Training [12/16] Loss: 0.00862 +Epoch [1889/4000] Training [13/16] Loss: 0.00548 +Epoch [1889/4000] Training [14/16] Loss: 0.00558 +Epoch [1889/4000] Training [15/16] Loss: 0.00474 +Epoch [1889/4000] Training [16/16] Loss: 0.00530 +Epoch [1889/4000] Training metric {'Train/mean dice_metric': 0.9954366087913513, 'Train/mean miou_metric': 0.9906197786331177, 'Train/mean f1': 0.9903727769851685, 'Train/mean precision': 0.9849802851676941, 'Train/mean recall': 0.9958245754241943, 'Train/mean hd95_metric': 1.1843969821929932} +Epoch [1889/4000] Validation [1/4] Loss: 0.24633 focal_loss 0.17584 dice_loss 0.07050 +Epoch [1889/4000] Validation [2/4] Loss: 0.32922 focal_loss 0.20522 dice_loss 0.12400 +Epoch [1889/4000] Validation [3/4] Loss: 0.33395 focal_loss 0.23893 dice_loss 0.09502 +Epoch [1889/4000] Validation [4/4] Loss: 0.28130 focal_loss 0.16648 dice_loss 0.11482 +Epoch [1889/4000] Validation metric {'Val/mean dice_metric': 0.9736852645874023, 'Val/mean miou_metric': 0.9564361572265625, 'Val/mean f1': 0.9728747606277466, 'Val/mean precision': 0.9699587225914001, 'Val/mean recall': 0.9758084416389465, 'Val/mean hd95_metric': 5.407162666320801} +Cheakpoint... +Epoch [1889/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736852645874023, 'Val/mean miou_metric': 0.9564361572265625, 'Val/mean f1': 0.9728747606277466, 'Val/mean precision': 0.9699587225914001, 'Val/mean recall': 0.9758084416389465, 'Val/mean hd95_metric': 5.407162666320801} +Epoch [1890/4000] Training [1/16] Loss: 0.00594 +Epoch [1890/4000] Training [2/16] Loss: 0.00724 +Epoch [1890/4000] Training [3/16] Loss: 0.01112 +Epoch [1890/4000] Training [4/16] Loss: 0.00655 +Epoch [1890/4000] Training [5/16] Loss: 0.00573 +Epoch [1890/4000] Training [6/16] Loss: 0.00513 +Epoch [1890/4000] Training [7/16] Loss: 0.00714 +Epoch [1890/4000] Training [8/16] Loss: 0.00650 +Epoch [1890/4000] Training [9/16] Loss: 0.00775 +Epoch [1890/4000] Training [10/16] Loss: 0.00644 +Epoch [1890/4000] Training [11/16] Loss: 0.00617 +Epoch [1890/4000] Training [12/16] Loss: 0.00596 +Epoch [1890/4000] Training [13/16] Loss: 0.00660 +Epoch [1890/4000] Training [14/16] Loss: 0.01018 +Epoch [1890/4000] Training [15/16] Loss: 0.00735 +Epoch [1890/4000] Training [16/16] Loss: 0.00643 +Epoch [1890/4000] Training metric {'Train/mean dice_metric': 0.9955118894577026, 'Train/mean miou_metric': 0.9908187389373779, 'Train/mean f1': 0.9912948608398438, 'Train/mean precision': 0.9868971109390259, 'Train/mean recall': 0.9957319498062134, 'Train/mean hd95_metric': 1.1067861318588257} +Epoch [1890/4000] Validation [1/4] Loss: 0.23284 focal_loss 0.17003 dice_loss 0.06281 +Epoch [1890/4000] Validation [2/4] Loss: 0.64867 focal_loss 0.42465 dice_loss 0.22402 +Epoch [1890/4000] Validation [3/4] Loss: 0.17171 focal_loss 0.11219 dice_loss 0.05953 +Epoch [1890/4000] Validation [4/4] Loss: 0.27477 focal_loss 0.14899 dice_loss 0.12578 +Epoch [1890/4000] Validation metric {'Val/mean dice_metric': 0.9738649129867554, 'Val/mean miou_metric': 0.9569927453994751, 'Val/mean f1': 0.9746891856193542, 'Val/mean precision': 0.9687517881393433, 'Val/mean recall': 0.980699896812439, 'Val/mean hd95_metric': 5.925766468048096} +Cheakpoint... +Epoch [1890/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738649129867554, 'Val/mean miou_metric': 0.9569927453994751, 'Val/mean f1': 0.9746891856193542, 'Val/mean precision': 0.9687517881393433, 'Val/mean recall': 0.980699896812439, 'Val/mean hd95_metric': 5.925766468048096} +Epoch [1891/4000] Training [1/16] Loss: 0.00465 +Epoch [1891/4000] Training [2/16] Loss: 0.00790 +Epoch [1891/4000] Training [3/16] Loss: 0.00543 +Epoch [1891/4000] Training [4/16] Loss: 0.00613 +Epoch [1891/4000] Training [5/16] Loss: 0.00662 +Epoch [1891/4000] Training [6/16] Loss: 0.00516 +Epoch [1891/4000] Training [7/16] Loss: 0.00904 +Epoch [1891/4000] Training [8/16] Loss: 0.00441 +Epoch [1891/4000] Training [9/16] Loss: 0.00676 +Epoch [1891/4000] Training [10/16] Loss: 0.00593 +Epoch [1891/4000] Training [11/16] Loss: 0.00724 +Epoch [1891/4000] Training [12/16] Loss: 0.00637 +Epoch [1891/4000] Training [13/16] Loss: 0.00609 +Epoch [1891/4000] Training [14/16] Loss: 0.00519 +Epoch [1891/4000] Training [15/16] Loss: 0.00581 +Epoch [1891/4000] Training [16/16] Loss: 0.00737 +Epoch [1891/4000] Training metric {'Train/mean dice_metric': 0.9958366751670837, 'Train/mean miou_metric': 0.9914499521255493, 'Train/mean f1': 0.9915626645088196, 'Train/mean precision': 0.9870316386222839, 'Train/mean recall': 0.9961355328559875, 'Train/mean hd95_metric': 1.0559959411621094} +Epoch [1891/4000] Validation [1/4] Loss: 0.21960 focal_loss 0.16442 dice_loss 0.05518 +Epoch [1891/4000] Validation [2/4] Loss: 0.61648 focal_loss 0.41235 dice_loss 0.20413 +Epoch [1891/4000] Validation [3/4] Loss: 0.36910 focal_loss 0.26728 dice_loss 0.10182 +Epoch [1891/4000] Validation [4/4] Loss: 0.43091 focal_loss 0.29235 dice_loss 0.13856 +Epoch [1891/4000] Validation metric {'Val/mean dice_metric': 0.9707228541374207, 'Val/mean miou_metric': 0.9538887739181519, 'Val/mean f1': 0.9730704426765442, 'Val/mean precision': 0.970058798789978, 'Val/mean recall': 0.9761009216308594, 'Val/mean hd95_metric': 5.7617506980896} +Cheakpoint... +Epoch [1891/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707228541374207, 'Val/mean miou_metric': 0.9538887739181519, 'Val/mean f1': 0.9730704426765442, 'Val/mean precision': 0.970058798789978, 'Val/mean recall': 0.9761009216308594, 'Val/mean hd95_metric': 5.7617506980896} +Epoch [1892/4000] Training [1/16] Loss: 0.00545 +Epoch [1892/4000] Training [2/16] Loss: 0.00947 +Epoch [1892/4000] Training [3/16] Loss: 0.00587 +Epoch [1892/4000] Training [4/16] Loss: 0.00663 +Epoch [1892/4000] Training [5/16] Loss: 0.00612 +Epoch [1892/4000] Training [6/16] Loss: 0.00777 +Epoch [1892/4000] Training [7/16] Loss: 0.00602 +Epoch [1892/4000] Training [8/16] Loss: 0.00554 +Epoch [1892/4000] Training [9/16] Loss: 0.00689 +Epoch [1892/4000] Training [10/16] Loss: 0.00561 +Epoch [1892/4000] Training [11/16] Loss: 0.00636 +Epoch [1892/4000] Training [12/16] Loss: 0.00576 +Epoch [1892/4000] Training [13/16] Loss: 0.00563 +Epoch [1892/4000] Training [14/16] Loss: 0.00660 +Epoch [1892/4000] Training [15/16] Loss: 0.00550 +Epoch [1892/4000] Training [16/16] Loss: 0.00765 +Epoch [1892/4000] Training metric {'Train/mean dice_metric': 0.9957190752029419, 'Train/mean miou_metric': 0.9912039041519165, 'Train/mean f1': 0.991312563419342, 'Train/mean precision': 0.9865780472755432, 'Train/mean recall': 0.996092677116394, 'Train/mean hd95_metric': 1.1533117294311523} +Epoch [1892/4000] Validation [1/4] Loss: 0.44469 focal_loss 0.34688 dice_loss 0.09781 +Epoch [1892/4000] Validation [2/4] Loss: 0.60842 focal_loss 0.40562 dice_loss 0.20281 +Epoch [1892/4000] Validation [3/4] Loss: 0.30587 focal_loss 0.21549 dice_loss 0.09038 +Epoch [1892/4000] Validation [4/4] Loss: 0.25047 focal_loss 0.14993 dice_loss 0.10054 +Epoch [1892/4000] Validation metric {'Val/mean dice_metric': 0.9701813459396362, 'Val/mean miou_metric': 0.9537956118583679, 'Val/mean f1': 0.9727188944816589, 'Val/mean precision': 0.9742925763130188, 'Val/mean recall': 0.9711503386497498, 'Val/mean hd95_metric': 5.20045280456543} +Cheakpoint... +Epoch [1892/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701813459396362, 'Val/mean miou_metric': 0.9537956118583679, 'Val/mean f1': 0.9727188944816589, 'Val/mean precision': 0.9742925763130188, 'Val/mean recall': 0.9711503386497498, 'Val/mean hd95_metric': 5.20045280456543} +Epoch [1893/4000] Training [1/16] Loss: 0.00782 +Epoch [1893/4000] Training [2/16] Loss: 0.00764 +Epoch [1893/4000] Training [3/16] Loss: 0.01035 +Epoch [1893/4000] Training [4/16] Loss: 0.00713 +Epoch [1893/4000] Training [5/16] Loss: 0.00535 +Epoch [1893/4000] Training [6/16] Loss: 0.00683 +Epoch [1893/4000] Training [7/16] Loss: 0.00632 +Epoch [1893/4000] Training [8/16] Loss: 0.00453 +Epoch [1893/4000] Training [9/16] Loss: 0.00527 +Epoch [1893/4000] Training [10/16] Loss: 0.00579 +Epoch [1893/4000] Training [11/16] Loss: 0.00432 +Epoch [1893/4000] Training [12/16] Loss: 0.00549 +Epoch [1893/4000] Training [13/16] Loss: 0.00547 +Epoch [1893/4000] Training [14/16] Loss: 0.00752 +Epoch [1893/4000] Training [15/16] Loss: 0.00565 +Epoch [1893/4000] Training [16/16] Loss: 0.00806 +Epoch [1893/4000] Training metric {'Train/mean dice_metric': 0.9956412315368652, 'Train/mean miou_metric': 0.9910468459129333, 'Train/mean f1': 0.9910898208618164, 'Train/mean precision': 0.9863588809967041, 'Train/mean recall': 0.9958663582801819, 'Train/mean hd95_metric': 1.0461169481277466} +Epoch [1893/4000] Validation [1/4] Loss: 0.23371 focal_loss 0.16862 dice_loss 0.06509 +Epoch [1893/4000] Validation [2/4] Loss: 0.35340 focal_loss 0.21979 dice_loss 0.13362 +Epoch [1893/4000] Validation [3/4] Loss: 0.19253 focal_loss 0.12941 dice_loss 0.06312 +Epoch [1893/4000] Validation [4/4] Loss: 0.26832 focal_loss 0.15164 dice_loss 0.11668 +Epoch [1893/4000] Validation metric {'Val/mean dice_metric': 0.972043514251709, 'Val/mean miou_metric': 0.955491840839386, 'Val/mean f1': 0.9740071296691895, 'Val/mean precision': 0.9731327891349792, 'Val/mean recall': 0.9748830199241638, 'Val/mean hd95_metric': 4.882081985473633} +Cheakpoint... +Epoch [1893/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972043514251709, 'Val/mean miou_metric': 0.955491840839386, 'Val/mean f1': 0.9740071296691895, 'Val/mean precision': 0.9731327891349792, 'Val/mean recall': 0.9748830199241638, 'Val/mean hd95_metric': 4.882081985473633} +Epoch [1894/4000] Training [1/16] Loss: 0.00837 +Epoch [1894/4000] Training [2/16] Loss: 0.00564 +Epoch [1894/4000] Training [3/16] Loss: 0.00587 +Epoch [1894/4000] Training [4/16] Loss: 0.00683 +Epoch [1894/4000] Training [5/16] Loss: 0.00752 +Epoch [1894/4000] Training [6/16] Loss: 0.00651 +Epoch [1894/4000] Training [7/16] Loss: 0.00818 +Epoch [1894/4000] Training [8/16] Loss: 0.00522 +Epoch [1894/4000] Training [9/16] Loss: 0.00762 +Epoch [1894/4000] Training [10/16] Loss: 0.01125 +Epoch [1894/4000] Training [11/16] Loss: 0.00768 +Epoch [1894/4000] Training [12/16] Loss: 0.00742 +Epoch [1894/4000] Training [13/16] Loss: 0.00564 +Epoch [1894/4000] Training [14/16] Loss: 0.00738 +Epoch [1894/4000] Training [15/16] Loss: 0.00557 +Epoch [1894/4000] Training [16/16] Loss: 0.00481 +Epoch [1894/4000] Training metric {'Train/mean dice_metric': 0.9953193664550781, 'Train/mean miou_metric': 0.9904352426528931, 'Train/mean f1': 0.9912617206573486, 'Train/mean precision': 0.9867543578147888, 'Train/mean recall': 0.9958103895187378, 'Train/mean hd95_metric': 1.086290717124939} +Epoch [1894/4000] Validation [1/4] Loss: 0.59683 focal_loss 0.48427 dice_loss 0.11256 +Epoch [1894/4000] Validation [2/4] Loss: 0.70307 focal_loss 0.42063 dice_loss 0.28244 +Epoch [1894/4000] Validation [3/4] Loss: 0.25544 focal_loss 0.16266 dice_loss 0.09278 +Epoch [1894/4000] Validation [4/4] Loss: 0.20878 focal_loss 0.12632 dice_loss 0.08246 +Epoch [1894/4000] Validation metric {'Val/mean dice_metric': 0.9687013626098633, 'Val/mean miou_metric': 0.9518786668777466, 'Val/mean f1': 0.971841037273407, 'Val/mean precision': 0.9736957550048828, 'Val/mean recall': 0.9699934124946594, 'Val/mean hd95_metric': 5.471011638641357} +Cheakpoint... +Epoch [1894/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687013626098633, 'Val/mean miou_metric': 0.9518786668777466, 'Val/mean f1': 0.971841037273407, 'Val/mean precision': 0.9736957550048828, 'Val/mean recall': 0.9699934124946594, 'Val/mean hd95_metric': 5.471011638641357} +Epoch [1895/4000] Training [1/16] Loss: 0.00713 +Epoch [1895/4000] Training [2/16] Loss: 0.00594 +Epoch [1895/4000] Training [3/16] Loss: 0.00671 +Epoch [1895/4000] Training [4/16] Loss: 0.00611 +Epoch [1895/4000] Training [5/16] Loss: 0.00664 +Epoch [1895/4000] Training [6/16] Loss: 0.00666 +Epoch [1895/4000] Training [7/16] Loss: 0.00644 +Epoch [1895/4000] Training [8/16] Loss: 0.00481 +Epoch [1895/4000] Training [9/16] Loss: 0.00724 +Epoch [1895/4000] Training [10/16] Loss: 0.00632 +Epoch [1895/4000] Training [11/16] Loss: 0.00525 +Epoch [1895/4000] Training [12/16] Loss: 0.00548 +Epoch [1895/4000] Training [13/16] Loss: 0.00705 +Epoch [1895/4000] Training [14/16] Loss: 0.00570 +Epoch [1895/4000] Training [15/16] Loss: 0.00686 +Epoch [1895/4000] Training [16/16] Loss: 0.00608 +Epoch [1895/4000] Training metric {'Train/mean dice_metric': 0.995873212814331, 'Train/mean miou_metric': 0.9914976358413696, 'Train/mean f1': 0.9910795092582703, 'Train/mean precision': 0.9860356450080872, 'Train/mean recall': 0.996175229549408, 'Train/mean hd95_metric': 1.0099049806594849} +Epoch [1895/4000] Validation [1/4] Loss: 0.34606 focal_loss 0.26627 dice_loss 0.07979 +Epoch [1895/4000] Validation [2/4] Loss: 0.50319 focal_loss 0.31329 dice_loss 0.18990 +Epoch [1895/4000] Validation [3/4] Loss: 0.20081 focal_loss 0.13713 dice_loss 0.06368 +Epoch [1895/4000] Validation [4/4] Loss: 0.43979 focal_loss 0.29203 dice_loss 0.14776 +Epoch [1895/4000] Validation metric {'Val/mean dice_metric': 0.9706805944442749, 'Val/mean miou_metric': 0.9542950391769409, 'Val/mean f1': 0.972902238368988, 'Val/mean precision': 0.9725050330162048, 'Val/mean recall': 0.9732996821403503, 'Val/mean hd95_metric': 5.661323070526123} +Cheakpoint... +Epoch [1895/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706805944442749, 'Val/mean miou_metric': 0.9542950391769409, 'Val/mean f1': 0.972902238368988, 'Val/mean precision': 0.9725050330162048, 'Val/mean recall': 0.9732996821403503, 'Val/mean hd95_metric': 5.661323070526123} +Epoch [1896/4000] Training [1/16] Loss: 0.00718 +Epoch [1896/4000] Training [2/16] Loss: 0.00522 +Epoch [1896/4000] Training [3/16] Loss: 0.00451 +Epoch [1896/4000] Training [4/16] Loss: 0.01041 +Epoch [1896/4000] Training [5/16] Loss: 0.00840 +Epoch [1896/4000] Training [6/16] Loss: 0.00557 +Epoch [1896/4000] Training [7/16] Loss: 0.00468 +Epoch [1896/4000] Training [8/16] Loss: 0.00737 +Epoch [1896/4000] Training [9/16] Loss: 0.00606 +Epoch [1896/4000] Training [10/16] Loss: 0.00596 +Epoch [1896/4000] Training [11/16] Loss: 0.00550 +Epoch [1896/4000] Training [12/16] Loss: 0.00765 +Epoch [1896/4000] Training [13/16] Loss: 0.00477 +Epoch [1896/4000] Training [14/16] Loss: 0.00469 +Epoch [1896/4000] Training [15/16] Loss: 0.00863 +Epoch [1896/4000] Training [16/16] Loss: 0.00560 +Epoch [1896/4000] Training metric {'Train/mean dice_metric': 0.9954429268836975, 'Train/mean miou_metric': 0.9906584024429321, 'Train/mean f1': 0.9911465644836426, 'Train/mean precision': 0.986349880695343, 'Train/mean recall': 0.9959903359413147, 'Train/mean hd95_metric': 1.0214251279830933} +Epoch [1896/4000] Validation [1/4] Loss: 0.29760 focal_loss 0.22091 dice_loss 0.07669 +Epoch [1896/4000] Validation [2/4] Loss: 0.66862 focal_loss 0.46180 dice_loss 0.20681 +Epoch [1896/4000] Validation [3/4] Loss: 0.19540 focal_loss 0.13475 dice_loss 0.06065 +Epoch [1896/4000] Validation [4/4] Loss: 0.25516 focal_loss 0.14878 dice_loss 0.10638 +Epoch [1896/4000] Validation metric {'Val/mean dice_metric': 0.9709137678146362, 'Val/mean miou_metric': 0.9544145464897156, 'Val/mean f1': 0.9739518761634827, 'Val/mean precision': 0.9733760952949524, 'Val/mean recall': 0.9745282530784607, 'Val/mean hd95_metric': 4.825397968292236} +Cheakpoint... +Epoch [1896/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709137678146362, 'Val/mean miou_metric': 0.9544145464897156, 'Val/mean f1': 0.9739518761634827, 'Val/mean precision': 0.9733760952949524, 'Val/mean recall': 0.9745282530784607, 'Val/mean hd95_metric': 4.825397968292236} +Epoch [1897/4000] Training [1/16] Loss: 0.00561 +Epoch [1897/4000] Training [2/16] Loss: 0.00496 +Epoch [1897/4000] Training [3/16] Loss: 0.00808 +Epoch [1897/4000] Training [4/16] Loss: 0.00587 +Epoch [1897/4000] Training [5/16] Loss: 0.00577 +Epoch [1897/4000] Training [6/16] Loss: 0.00591 +Epoch [1897/4000] Training [7/16] Loss: 0.00855 +Epoch [1897/4000] Training [8/16] Loss: 0.00552 +Epoch [1897/4000] Training [9/16] Loss: 0.00659 +Epoch [1897/4000] Training [10/16] Loss: 0.00722 +Epoch [1897/4000] Training [11/16] Loss: 0.00632 +Epoch [1897/4000] Training [12/16] Loss: 0.00545 +Epoch [1897/4000] Training [13/16] Loss: 0.00642 +Epoch [1897/4000] Training [14/16] Loss: 0.00866 +Epoch [1897/4000] Training [15/16] Loss: 0.00692 +Epoch [1897/4000] Training [16/16] Loss: 0.00494 +Epoch [1897/4000] Training metric {'Train/mean dice_metric': 0.9956627488136292, 'Train/mean miou_metric': 0.9911166429519653, 'Train/mean f1': 0.9915633201599121, 'Train/mean precision': 0.9869388937950134, 'Train/mean recall': 0.996231198310852, 'Train/mean hd95_metric': 1.030802607536316} +Epoch [1897/4000] Validation [1/4] Loss: 0.46931 focal_loss 0.36444 dice_loss 0.10487 +Epoch [1897/4000] Validation [2/4] Loss: 0.38113 focal_loss 0.24595 dice_loss 0.13517 +Epoch [1897/4000] Validation [3/4] Loss: 0.34383 focal_loss 0.24613 dice_loss 0.09771 +Epoch [1897/4000] Validation [4/4] Loss: 0.25901 focal_loss 0.14760 dice_loss 0.11141 +Epoch [1897/4000] Validation metric {'Val/mean dice_metric': 0.9706336855888367, 'Val/mean miou_metric': 0.9535681009292603, 'Val/mean f1': 0.973103404045105, 'Val/mean precision': 0.9703123569488525, 'Val/mean recall': 0.9759107828140259, 'Val/mean hd95_metric': 5.777374267578125} +Cheakpoint... +Epoch [1897/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706336855888367, 'Val/mean miou_metric': 0.9535681009292603, 'Val/mean f1': 0.973103404045105, 'Val/mean precision': 0.9703123569488525, 'Val/mean recall': 0.9759107828140259, 'Val/mean hd95_metric': 5.777374267578125} +Epoch [1898/4000] Training [1/16] Loss: 0.00638 +Epoch [1898/4000] Training [2/16] Loss: 0.00638 +Epoch [1898/4000] Training [3/16] Loss: 0.00595 +Epoch [1898/4000] Training [4/16] Loss: 0.00670 +Epoch [1898/4000] Training [5/16] Loss: 0.00663 +Epoch [1898/4000] Training [6/16] Loss: 0.00701 +Epoch [1898/4000] Training [7/16] Loss: 0.00508 +Epoch [1898/4000] Training [8/16] Loss: 0.00582 +Epoch [1898/4000] Training [9/16] Loss: 0.00566 +Epoch [1898/4000] Training [10/16] Loss: 0.00713 +Epoch [1898/4000] Training [11/16] Loss: 0.00625 +Epoch [1898/4000] Training [12/16] Loss: 0.00549 +Epoch [1898/4000] Training [13/16] Loss: 0.00534 +Epoch [1898/4000] Training [14/16] Loss: 0.00629 +Epoch [1898/4000] Training [15/16] Loss: 0.00764 +Epoch [1898/4000] Training [16/16] Loss: 0.00694 +Epoch [1898/4000] Training metric {'Train/mean dice_metric': 0.9956756830215454, 'Train/mean miou_metric': 0.9910850524902344, 'Train/mean f1': 0.9907185435295105, 'Train/mean precision': 0.985564649105072, 'Train/mean recall': 0.9959266781806946, 'Train/mean hd95_metric': 1.0179357528686523} +Epoch [1898/4000] Validation [1/4] Loss: 0.34734 focal_loss 0.26774 dice_loss 0.07959 +Epoch [1898/4000] Validation [2/4] Loss: 0.85719 focal_loss 0.61789 dice_loss 0.23930 +Epoch [1898/4000] Validation [3/4] Loss: 0.36551 focal_loss 0.26296 dice_loss 0.10255 +Epoch [1898/4000] Validation [4/4] Loss: 0.28928 focal_loss 0.17428 dice_loss 0.11499 +Epoch [1898/4000] Validation metric {'Val/mean dice_metric': 0.9688943028450012, 'Val/mean miou_metric': 0.9523814916610718, 'Val/mean f1': 0.9723259806632996, 'Val/mean precision': 0.9694442749023438, 'Val/mean recall': 0.9752249121665955, 'Val/mean hd95_metric': 6.114370346069336} +Cheakpoint... +Epoch [1898/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688943028450012, 'Val/mean miou_metric': 0.9523814916610718, 'Val/mean f1': 0.9723259806632996, 'Val/mean precision': 0.9694442749023438, 'Val/mean recall': 0.9752249121665955, 'Val/mean hd95_metric': 6.114370346069336} +Epoch [1899/4000] Training [1/16] Loss: 0.00957 +Epoch [1899/4000] Training [2/16] Loss: 0.00579 +Epoch [1899/4000] Training [3/16] Loss: 0.00674 +Epoch [1899/4000] Training [4/16] Loss: 0.00819 +Epoch [1899/4000] Training [5/16] Loss: 0.00646 +Epoch [1899/4000] Training [6/16] Loss: 0.00526 +Epoch [1899/4000] Training [7/16] Loss: 0.00614 +Epoch [1899/4000] Training [8/16] Loss: 0.00541 +Epoch [1899/4000] Training [9/16] Loss: 0.00681 +Epoch [1899/4000] Training [10/16] Loss: 0.00642 +Epoch [1899/4000] Training [11/16] Loss: 0.01607 +Epoch [1899/4000] Training [12/16] Loss: 0.00647 +Epoch [1899/4000] Training [13/16] Loss: 0.00614 +Epoch [1899/4000] Training [14/16] Loss: 0.00728 +Epoch [1899/4000] Training [15/16] Loss: 0.00723 +Epoch [1899/4000] Training [16/16] Loss: 0.00675 +Epoch [1899/4000] Training metric {'Train/mean dice_metric': 0.9953197836875916, 'Train/mean miou_metric': 0.9904506206512451, 'Train/mean f1': 0.991371750831604, 'Train/mean precision': 0.9868358969688416, 'Train/mean recall': 0.9959494471549988, 'Train/mean hd95_metric': 1.1208367347717285} +Epoch [1899/4000] Validation [1/4] Loss: 0.30955 focal_loss 0.24377 dice_loss 0.06578 +Epoch [1899/4000] Validation [2/4] Loss: 0.29003 focal_loss 0.18010 dice_loss 0.10994 +Epoch [1899/4000] Validation [3/4] Loss: 0.39576 focal_loss 0.29539 dice_loss 0.10037 +Epoch [1899/4000] Validation [4/4] Loss: 0.21791 focal_loss 0.13035 dice_loss 0.08756 +Epoch [1899/4000] Validation metric {'Val/mean dice_metric': 0.9731358289718628, 'Val/mean miou_metric': 0.9563820958137512, 'Val/mean f1': 0.9749032855033875, 'Val/mean precision': 0.971314013004303, 'Val/mean recall': 0.9785192012786865, 'Val/mean hd95_metric': 5.597846031188965} +Cheakpoint... +Epoch [1899/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731358289718628, 'Val/mean miou_metric': 0.9563820958137512, 'Val/mean f1': 0.9749032855033875, 'Val/mean precision': 0.971314013004303, 'Val/mean recall': 0.9785192012786865, 'Val/mean hd95_metric': 5.597846031188965} +Epoch [1900/4000] Training [1/16] Loss: 0.00799 +Epoch [1900/4000] Training [2/16] Loss: 0.00644 +Epoch [1900/4000] Training [3/16] Loss: 0.00577 +Epoch [1900/4000] Training [4/16] Loss: 0.01265 +Epoch [1900/4000] Training [5/16] Loss: 0.00639 +Epoch [1900/4000] Training [6/16] Loss: 0.00849 +Epoch [1900/4000] Training [7/16] Loss: 0.00567 +Epoch [1900/4000] Training [8/16] Loss: 0.00452 +Epoch [1900/4000] Training [9/16] Loss: 0.00519 +Epoch [1900/4000] Training [10/16] Loss: 0.01645 +Epoch [1900/4000] Training [11/16] Loss: 0.00560 +Epoch [1900/4000] Training [12/16] Loss: 0.00595 +Epoch [1900/4000] Training [13/16] Loss: 0.00908 +Epoch [1900/4000] Training [14/16] Loss: 0.00689 +Epoch [1900/4000] Training [15/16] Loss: 0.00813 +Epoch [1900/4000] Training [16/16] Loss: 0.00608 +Epoch [1900/4000] Training metric {'Train/mean dice_metric': 0.9953833818435669, 'Train/mean miou_metric': 0.9905656576156616, 'Train/mean f1': 0.9913205504417419, 'Train/mean precision': 0.9866970181465149, 'Train/mean recall': 0.995987594127655, 'Train/mean hd95_metric': 1.0718169212341309} +Epoch [1900/4000] Validation [1/4] Loss: 0.28630 focal_loss 0.21591 dice_loss 0.07039 +Epoch [1900/4000] Validation [2/4] Loss: 0.25486 focal_loss 0.15196 dice_loss 0.10291 +Epoch [1900/4000] Validation [3/4] Loss: 0.34029 focal_loss 0.24328 dice_loss 0.09701 +Epoch [1900/4000] Validation [4/4] Loss: 0.40112 focal_loss 0.25007 dice_loss 0.15105 +Epoch [1900/4000] Validation metric {'Val/mean dice_metric': 0.9740328788757324, 'Val/mean miou_metric': 0.9564641118049622, 'Val/mean f1': 0.9742213487625122, 'Val/mean precision': 0.9714784026145935, 'Val/mean recall': 0.9769797325134277, 'Val/mean hd95_metric': 5.452454566955566} +Cheakpoint... +Epoch [1900/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740328788757324, 'Val/mean miou_metric': 0.9564641118049622, 'Val/mean f1': 0.9742213487625122, 'Val/mean precision': 0.9714784026145935, 'Val/mean recall': 0.9769797325134277, 'Val/mean hd95_metric': 5.452454566955566} +Epoch [1901/4000] Training [1/16] Loss: 0.00763 +Epoch [1901/4000] Training [2/16] Loss: 0.00614 +Epoch [1901/4000] Training [3/16] Loss: 0.00553 +Epoch [1901/4000] Training [4/16] Loss: 0.00642 +Epoch [1901/4000] Training [5/16] Loss: 0.00615 +Epoch [1901/4000] Training [6/16] Loss: 0.00527 +Epoch [1901/4000] Training [7/16] Loss: 0.00743 +Epoch [1901/4000] Training [8/16] Loss: 0.01443 +Epoch [1901/4000] Training [9/16] Loss: 0.00561 +Epoch [1901/4000] Training [10/16] Loss: 0.00556 +Epoch [1901/4000] Training [11/16] Loss: 0.00808 +Epoch [1901/4000] Training [12/16] Loss: 0.00484 +Epoch [1901/4000] Training [13/16] Loss: 0.00634 +Epoch [1901/4000] Training [14/16] Loss: 0.00705 +Epoch [1901/4000] Training [15/16] Loss: 0.00702 +Epoch [1901/4000] Training [16/16] Loss: 0.00692 +Epoch [1901/4000] Training metric {'Train/mean dice_metric': 0.995169997215271, 'Train/mean miou_metric': 0.9902539253234863, 'Train/mean f1': 0.9907101988792419, 'Train/mean precision': 0.9861342906951904, 'Train/mean recall': 0.9953287839889526, 'Train/mean hd95_metric': 1.1079353094100952} +Epoch [1901/4000] Validation [1/4] Loss: 0.33289 focal_loss 0.24463 dice_loss 0.08826 +Epoch [1901/4000] Validation [2/4] Loss: 0.29783 focal_loss 0.17415 dice_loss 0.12368 +Epoch [1901/4000] Validation [3/4] Loss: 0.32423 focal_loss 0.22471 dice_loss 0.09952 +Epoch [1901/4000] Validation [4/4] Loss: 0.24304 focal_loss 0.14823 dice_loss 0.09480 +Epoch [1901/4000] Validation metric {'Val/mean dice_metric': 0.9703105688095093, 'Val/mean miou_metric': 0.9530566334724426, 'Val/mean f1': 0.9720532894134521, 'Val/mean precision': 0.9677233695983887, 'Val/mean recall': 0.9764220118522644, 'Val/mean hd95_metric': 6.000107765197754} +Cheakpoint... +Epoch [1901/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703105688095093, 'Val/mean miou_metric': 0.9530566334724426, 'Val/mean f1': 0.9720532894134521, 'Val/mean precision': 0.9677233695983887, 'Val/mean recall': 0.9764220118522644, 'Val/mean hd95_metric': 6.000107765197754} +Epoch [1902/4000] Training [1/16] Loss: 0.00632 +Epoch [1902/4000] Training [2/16] Loss: 0.00711 +Epoch [1902/4000] Training [3/16] Loss: 0.00767 +Epoch [1902/4000] Training [4/16] Loss: 0.00569 +Epoch [1902/4000] Training [5/16] Loss: 0.00629 +Epoch [1902/4000] Training [6/16] Loss: 0.01991 +Epoch [1902/4000] Training [7/16] Loss: 0.00749 +Epoch [1902/4000] Training [8/16] Loss: 0.00629 +Epoch [1902/4000] Training [9/16] Loss: 0.00473 +Epoch [1902/4000] Training [10/16] Loss: 0.00650 +Epoch [1902/4000] Training [11/16] Loss: 0.00584 +Epoch [1902/4000] Training [12/16] Loss: 0.00830 +Epoch [1902/4000] Training [13/16] Loss: 0.00605 +Epoch [1902/4000] Training [14/16] Loss: 0.00497 +Epoch [1902/4000] Training [15/16] Loss: 0.00940 +Epoch [1902/4000] Training [16/16] Loss: 0.00563 +Epoch [1902/4000] Training metric {'Train/mean dice_metric': 0.9952881336212158, 'Train/mean miou_metric': 0.9903758764266968, 'Train/mean f1': 0.9911279082298279, 'Train/mean precision': 0.9863725900650024, 'Train/mean recall': 0.9959293603897095, 'Train/mean hd95_metric': 1.0835269689559937} +Epoch [1902/4000] Validation [1/4] Loss: 0.22846 focal_loss 0.17006 dice_loss 0.05840 +Epoch [1902/4000] Validation [2/4] Loss: 0.24734 focal_loss 0.14546 dice_loss 0.10188 +Epoch [1902/4000] Validation [3/4] Loss: 0.21995 focal_loss 0.14985 dice_loss 0.07010 +Epoch [1902/4000] Validation [4/4] Loss: 0.51667 focal_loss 0.34659 dice_loss 0.17008 +Epoch [1902/4000] Validation metric {'Val/mean dice_metric': 0.9718373417854309, 'Val/mean miou_metric': 0.9547065496444702, 'Val/mean f1': 0.9737735986709595, 'Val/mean precision': 0.9692658185958862, 'Val/mean recall': 0.9783234000205994, 'Val/mean hd95_metric': 5.529324531555176} +Cheakpoint... +Epoch [1902/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718373417854309, 'Val/mean miou_metric': 0.9547065496444702, 'Val/mean f1': 0.9737735986709595, 'Val/mean precision': 0.9692658185958862, 'Val/mean recall': 0.9783234000205994, 'Val/mean hd95_metric': 5.529324531555176} +Epoch [1903/4000] Training [1/16] Loss: 0.00619 +Epoch [1903/4000] Training [2/16] Loss: 0.00615 +Epoch [1903/4000] Training [3/16] Loss: 0.00533 +Epoch [1903/4000] Training [4/16] Loss: 0.00757 +Epoch [1903/4000] Training [5/16] Loss: 0.00643 +Epoch [1903/4000] Training [6/16] Loss: 0.00525 +Epoch [1903/4000] Training [7/16] Loss: 0.00852 +Epoch [1903/4000] Training [8/16] Loss: 0.00916 +Epoch [1903/4000] Training [9/16] Loss: 0.00462 +Epoch [1903/4000] Training [10/16] Loss: 0.00708 +Epoch [1903/4000] Training [11/16] Loss: 0.00648 +Epoch [1903/4000] Training [12/16] Loss: 0.00605 +Epoch [1903/4000] Training [13/16] Loss: 0.00777 +Epoch [1903/4000] Training [14/16] Loss: 0.00661 +Epoch [1903/4000] Training [15/16] Loss: 0.00671 +Epoch [1903/4000] Training [16/16] Loss: 0.00854 +Epoch [1903/4000] Training metric {'Train/mean dice_metric': 0.9956039190292358, 'Train/mean miou_metric': 0.9909656643867493, 'Train/mean f1': 0.9910933375358582, 'Train/mean precision': 0.9862837195396423, 'Train/mean recall': 0.9959501028060913, 'Train/mean hd95_metric': 1.5597635507583618} +Epoch [1903/4000] Validation [1/4] Loss: 0.28486 focal_loss 0.21923 dice_loss 0.06563 +Epoch [1903/4000] Validation [2/4] Loss: 0.54062 focal_loss 0.36068 dice_loss 0.17994 +Epoch [1903/4000] Validation [3/4] Loss: 0.29904 focal_loss 0.20271 dice_loss 0.09633 +Epoch [1903/4000] Validation [4/4] Loss: 0.35442 focal_loss 0.22063 dice_loss 0.13379 +Epoch [1903/4000] Validation metric {'Val/mean dice_metric': 0.971588134765625, 'Val/mean miou_metric': 0.9552658200263977, 'Val/mean f1': 0.973576009273529, 'Val/mean precision': 0.9685839414596558, 'Val/mean recall': 0.9786198735237122, 'Val/mean hd95_metric': 5.97426700592041} +Cheakpoint... +Epoch [1903/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971588134765625, 'Val/mean miou_metric': 0.9552658200263977, 'Val/mean f1': 0.973576009273529, 'Val/mean precision': 0.9685839414596558, 'Val/mean recall': 0.9786198735237122, 'Val/mean hd95_metric': 5.97426700592041} +Epoch [1904/4000] Training [1/16] Loss: 0.00763 +Epoch [1904/4000] Training [2/16] Loss: 0.00562 +Epoch [1904/4000] Training [3/16] Loss: 0.00541 +Epoch [1904/4000] Training [4/16] Loss: 0.00473 +Epoch [1904/4000] Training [5/16] Loss: 0.00632 +Epoch [1904/4000] Training [6/16] Loss: 0.00803 +Epoch [1904/4000] Training [7/16] Loss: 0.00718 +Epoch [1904/4000] Training [8/16] Loss: 0.00522 +Epoch [1904/4000] Training [9/16] Loss: 0.00681 +Epoch [1904/4000] Training [10/16] Loss: 0.00480 +Epoch [1904/4000] Training [11/16] Loss: 0.00684 +Epoch [1904/4000] Training [12/16] Loss: 0.00609 +Epoch [1904/4000] Training [13/16] Loss: 0.00462 +Epoch [1904/4000] Training [14/16] Loss: 0.00463 +Epoch [1904/4000] Training [15/16] Loss: 0.00574 +Epoch [1904/4000] Training [16/16] Loss: 0.01149 +Epoch [1904/4000] Training metric {'Train/mean dice_metric': 0.9958751797676086, 'Train/mean miou_metric': 0.9914830327033997, 'Train/mean f1': 0.9908681511878967, 'Train/mean precision': 0.9856483936309814, 'Train/mean recall': 0.9961435198783875, 'Train/mean hd95_metric': 1.0201513767242432} +Epoch [1904/4000] Validation [1/4] Loss: 0.24423 focal_loss 0.17978 dice_loss 0.06445 +Epoch [1904/4000] Validation [2/4] Loss: 0.52272 focal_loss 0.33552 dice_loss 0.18720 +Epoch [1904/4000] Validation [3/4] Loss: 0.38566 focal_loss 0.27883 dice_loss 0.10683 +Epoch [1904/4000] Validation [4/4] Loss: 0.28641 focal_loss 0.16764 dice_loss 0.11878 +Epoch [1904/4000] Validation metric {'Val/mean dice_metric': 0.9715055227279663, 'Val/mean miou_metric': 0.9553742408752441, 'Val/mean f1': 0.9730132818222046, 'Val/mean precision': 0.96766597032547, 'Val/mean recall': 0.9784200191497803, 'Val/mean hd95_metric': 5.662134170532227} +Cheakpoint... +Epoch [1904/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715055227279663, 'Val/mean miou_metric': 0.9553742408752441, 'Val/mean f1': 0.9730132818222046, 'Val/mean precision': 0.96766597032547, 'Val/mean recall': 0.9784200191497803, 'Val/mean hd95_metric': 5.662134170532227} +Epoch [1905/4000] Training [1/16] Loss: 0.00514 +Epoch [1905/4000] Training [2/16] Loss: 0.00677 +Epoch [1905/4000] Training [3/16] Loss: 0.00826 +Epoch [1905/4000] Training [4/16] Loss: 0.00595 +Epoch [1905/4000] Training [5/16] Loss: 0.00498 +Epoch [1905/4000] Training [6/16] Loss: 0.00721 +Epoch [1905/4000] Training [7/16] Loss: 0.00478 +Epoch [1905/4000] Training [8/16] Loss: 0.00821 +Epoch [1905/4000] Training [9/16] Loss: 0.00610 +Epoch [1905/4000] Training [10/16] Loss: 0.00699 +Epoch [1905/4000] Training [11/16] Loss: 0.00781 +Epoch [1905/4000] Training [12/16] Loss: 0.00619 +Epoch [1905/4000] Training [13/16] Loss: 0.00627 +Epoch [1905/4000] Training [14/16] Loss: 0.00673 +Epoch [1905/4000] Training [15/16] Loss: 0.00548 +Epoch [1905/4000] Training [16/16] Loss: 0.00640 +Epoch [1905/4000] Training metric {'Train/mean dice_metric': 0.9959708452224731, 'Train/mean miou_metric': 0.9916970133781433, 'Train/mean f1': 0.9913679957389832, 'Train/mean precision': 0.9866152405738831, 'Train/mean recall': 0.9961667060852051, 'Train/mean hd95_metric': 1.0082337856292725} +Epoch [1905/4000] Validation [1/4] Loss: 0.27892 focal_loss 0.20766 dice_loss 0.07126 +Epoch [1905/4000] Validation [2/4] Loss: 0.26671 focal_loss 0.16033 dice_loss 0.10639 +Epoch [1905/4000] Validation [3/4] Loss: 0.38673 focal_loss 0.29191 dice_loss 0.09482 +Epoch [1905/4000] Validation [4/4] Loss: 0.30556 focal_loss 0.18975 dice_loss 0.11582 +Epoch [1905/4000] Validation metric {'Val/mean dice_metric': 0.9733730554580688, 'Val/mean miou_metric': 0.9571225047111511, 'Val/mean f1': 0.9743742346763611, 'Val/mean precision': 0.970116138458252, 'Val/mean recall': 0.9786700010299683, 'Val/mean hd95_metric': 5.366713523864746} +Cheakpoint... +Epoch [1905/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733730554580688, 'Val/mean miou_metric': 0.9571225047111511, 'Val/mean f1': 0.9743742346763611, 'Val/mean precision': 0.970116138458252, 'Val/mean recall': 0.9786700010299683, 'Val/mean hd95_metric': 5.366713523864746} +Epoch [1906/4000] Training [1/16] Loss: 0.00982 +Epoch [1906/4000] Training [2/16] Loss: 0.00963 +Epoch [1906/4000] Training [3/16] Loss: 0.00812 +Epoch [1906/4000] Training [4/16] Loss: 0.00542 +Epoch [1906/4000] Training [5/16] Loss: 0.00872 +Epoch [1906/4000] Training [6/16] Loss: 0.00532 +Epoch [1906/4000] Training [7/16] Loss: 0.00543 +Epoch [1906/4000] Training [8/16] Loss: 0.00570 +Epoch [1906/4000] Training [9/16] Loss: 0.00694 +Epoch [1906/4000] Training [10/16] Loss: 0.00497 +Epoch [1906/4000] Training [11/16] Loss: 0.00692 +Epoch [1906/4000] Training [12/16] Loss: 0.00543 +Epoch [1906/4000] Training [13/16] Loss: 0.00519 +Epoch [1906/4000] Training [14/16] Loss: 0.00730 +Epoch [1906/4000] Training [15/16] Loss: 0.00561 +Epoch [1906/4000] Training [16/16] Loss: 0.00646 +Epoch [1906/4000] Training metric {'Train/mean dice_metric': 0.9954341053962708, 'Train/mean miou_metric': 0.9906481504440308, 'Train/mean f1': 0.9911166429519653, 'Train/mean precision': 0.9863322377204895, 'Train/mean recall': 0.9959476590156555, 'Train/mean hd95_metric': 1.052735447883606} +Epoch [1906/4000] Validation [1/4] Loss: 0.23730 focal_loss 0.17239 dice_loss 0.06491 +Epoch [1906/4000] Validation [2/4] Loss: 0.51521 focal_loss 0.31513 dice_loss 0.20008 +Epoch [1906/4000] Validation [3/4] Loss: 0.31568 focal_loss 0.22243 dice_loss 0.09325 +Epoch [1906/4000] Validation [4/4] Loss: 0.31770 focal_loss 0.18881 dice_loss 0.12889 +Epoch [1906/4000] Validation metric {'Val/mean dice_metric': 0.9694768786430359, 'Val/mean miou_metric': 0.9526176452636719, 'Val/mean f1': 0.9728941321372986, 'Val/mean precision': 0.9698944687843323, 'Val/mean recall': 0.9759124517440796, 'Val/mean hd95_metric': 6.013460636138916} +Cheakpoint... +Epoch [1906/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694768786430359, 'Val/mean miou_metric': 0.9526176452636719, 'Val/mean f1': 0.9728941321372986, 'Val/mean precision': 0.9698944687843323, 'Val/mean recall': 0.9759124517440796, 'Val/mean hd95_metric': 6.013460636138916} +Epoch [1907/4000] Training [1/16] Loss: 0.00499 +Epoch [1907/4000] Training [2/16] Loss: 0.00619 +Epoch [1907/4000] Training [3/16] Loss: 0.00631 +Epoch [1907/4000] Training [4/16] Loss: 0.00570 +Epoch [1907/4000] Training [5/16] Loss: 0.00716 +Epoch [1907/4000] Training [6/16] Loss: 0.00469 +Epoch [1907/4000] Training [7/16] Loss: 0.00682 +Epoch [1907/4000] Training [8/16] Loss: 0.00599 +Epoch [1907/4000] Training [9/16] Loss: 0.00692 +Epoch [1907/4000] Training [10/16] Loss: 0.00720 +Epoch [1907/4000] Training [11/16] Loss: 0.00751 +Epoch [1907/4000] Training [12/16] Loss: 0.00614 +Epoch [1907/4000] Training [13/16] Loss: 0.00615 +Epoch [1907/4000] Training [14/16] Loss: 0.00638 +Epoch [1907/4000] Training [15/16] Loss: 0.00684 +Epoch [1907/4000] Training [16/16] Loss: 0.00509 +Epoch [1907/4000] Training metric {'Train/mean dice_metric': 0.9958335161209106, 'Train/mean miou_metric': 0.9914361834526062, 'Train/mean f1': 0.9914656281471252, 'Train/mean precision': 0.9868744015693665, 'Train/mean recall': 0.9960998296737671, 'Train/mean hd95_metric': 1.0141741037368774} +Epoch [1907/4000] Validation [1/4] Loss: 0.25065 focal_loss 0.19048 dice_loss 0.06017 +Epoch [1907/4000] Validation [2/4] Loss: 0.33239 focal_loss 0.19866 dice_loss 0.13373 +Epoch [1907/4000] Validation [3/4] Loss: 0.19633 focal_loss 0.13567 dice_loss 0.06066 +Epoch [1907/4000] Validation [4/4] Loss: 0.25138 focal_loss 0.15843 dice_loss 0.09295 +Epoch [1907/4000] Validation metric {'Val/mean dice_metric': 0.9732236862182617, 'Val/mean miou_metric': 0.956800103187561, 'Val/mean f1': 0.9744198322296143, 'Val/mean precision': 0.9709913730621338, 'Val/mean recall': 0.9778726696968079, 'Val/mean hd95_metric': 5.414383888244629} +Cheakpoint... +Epoch [1907/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732236862182617, 'Val/mean miou_metric': 0.956800103187561, 'Val/mean f1': 0.9744198322296143, 'Val/mean precision': 0.9709913730621338, 'Val/mean recall': 0.9778726696968079, 'Val/mean hd95_metric': 5.414383888244629} +Epoch [1908/4000] Training [1/16] Loss: 0.00886 +Epoch [1908/4000] Training [2/16] Loss: 0.00882 +Epoch [1908/4000] Training [3/16] Loss: 0.00840 +Epoch [1908/4000] Training [4/16] Loss: 0.00785 +Epoch [1908/4000] Training [5/16] Loss: 0.00630 +Epoch [1908/4000] Training [6/16] Loss: 0.00639 +Epoch [1908/4000] Training [7/16] Loss: 0.00562 +Epoch [1908/4000] Training [8/16] Loss: 0.00514 +Epoch [1908/4000] Training [9/16] Loss: 0.00557 +Epoch [1908/4000] Training [10/16] Loss: 0.00511 +Epoch [1908/4000] Training [11/16] Loss: 0.00603 +Epoch [1908/4000] Training [12/16] Loss: 0.00781 +Epoch [1908/4000] Training [13/16] Loss: 0.00655 +Epoch [1908/4000] Training [14/16] Loss: 0.00477 +Epoch [1908/4000] Training [15/16] Loss: 0.00547 +Epoch [1908/4000] Training [16/16] Loss: 0.00869 +Epoch [1908/4000] Training metric {'Train/mean dice_metric': 0.9957178831100464, 'Train/mean miou_metric': 0.991195559501648, 'Train/mean f1': 0.9912157654762268, 'Train/mean precision': 0.9863935112953186, 'Train/mean recall': 0.9960854649543762, 'Train/mean hd95_metric': 1.0169994831085205} +Epoch [1908/4000] Validation [1/4] Loss: 0.25843 focal_loss 0.19775 dice_loss 0.06068 +Epoch [1908/4000] Validation [2/4] Loss: 0.53024 focal_loss 0.34428 dice_loss 0.18596 +Epoch [1908/4000] Validation [3/4] Loss: 0.33480 focal_loss 0.24375 dice_loss 0.09105 +Epoch [1908/4000] Validation [4/4] Loss: 0.26252 focal_loss 0.16605 dice_loss 0.09647 +Epoch [1908/4000] Validation metric {'Val/mean dice_metric': 0.9715486764907837, 'Val/mean miou_metric': 0.9554790258407593, 'Val/mean f1': 0.9741340279579163, 'Val/mean precision': 0.9704282283782959, 'Val/mean recall': 0.9778681397438049, 'Val/mean hd95_metric': 5.281240463256836} +Cheakpoint... +Epoch [1908/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715486764907837, 'Val/mean miou_metric': 0.9554790258407593, 'Val/mean f1': 0.9741340279579163, 'Val/mean precision': 0.9704282283782959, 'Val/mean recall': 0.9778681397438049, 'Val/mean hd95_metric': 5.281240463256836} +Epoch [1909/4000] Training [1/16] Loss: 0.00731 +Epoch [1909/4000] Training [2/16] Loss: 0.00576 +Epoch [1909/4000] Training [3/16] Loss: 0.01222 +Epoch [1909/4000] Training [4/16] Loss: 0.01146 +Epoch [1909/4000] Training [5/16] Loss: 0.00602 +Epoch [1909/4000] Training [6/16] Loss: 0.00651 +Epoch [1909/4000] Training [7/16] Loss: 0.00678 +Epoch [1909/4000] Training [8/16] Loss: 0.00600 +Epoch [1909/4000] Training [9/16] Loss: 0.00597 +Epoch [1909/4000] Training [10/16] Loss: 0.00627 +Epoch [1909/4000] Training [11/16] Loss: 0.00493 +Epoch [1909/4000] Training [12/16] Loss: 0.00803 +Epoch [1909/4000] Training [13/16] Loss: 0.00795 +Epoch [1909/4000] Training [14/16] Loss: 0.00573 +Epoch [1909/4000] Training [15/16] Loss: 0.00735 +Epoch [1909/4000] Training [16/16] Loss: 0.00522 +Epoch [1909/4000] Training metric {'Train/mean dice_metric': 0.9952206611633301, 'Train/mean miou_metric': 0.9902434349060059, 'Train/mean f1': 0.990917980670929, 'Train/mean precision': 0.9860678911209106, 'Train/mean recall': 0.9958159923553467, 'Train/mean hd95_metric': 1.054898977279663} +Epoch [1909/4000] Validation [1/4] Loss: 0.29233 focal_loss 0.23027 dice_loss 0.06206 +Epoch [1909/4000] Validation [2/4] Loss: 0.29171 focal_loss 0.16503 dice_loss 0.12668 +Epoch [1909/4000] Validation [3/4] Loss: 0.37132 focal_loss 0.27641 dice_loss 0.09492 +Epoch [1909/4000] Validation [4/4] Loss: 0.26495 focal_loss 0.16458 dice_loss 0.10037 +Epoch [1909/4000] Validation metric {'Val/mean dice_metric': 0.9718788266181946, 'Val/mean miou_metric': 0.9544818997383118, 'Val/mean f1': 0.9728072881698608, 'Val/mean precision': 0.9674980640411377, 'Val/mean recall': 0.9781752824783325, 'Val/mean hd95_metric': 5.939123153686523} +Cheakpoint... +Epoch [1909/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718788266181946, 'Val/mean miou_metric': 0.9544818997383118, 'Val/mean f1': 0.9728072881698608, 'Val/mean precision': 0.9674980640411377, 'Val/mean recall': 0.9781752824783325, 'Val/mean hd95_metric': 5.939123153686523} +Epoch [1910/4000] Training [1/16] Loss: 0.00497 +Epoch [1910/4000] Training [2/16] Loss: 0.00642 +Epoch [1910/4000] Training [3/16] Loss: 0.00754 +Epoch [1910/4000] Training [4/16] Loss: 0.01259 +Epoch [1910/4000] Training [5/16] Loss: 0.00641 +Epoch [1910/4000] Training [6/16] Loss: 0.00631 +Epoch [1910/4000] Training [7/16] Loss: 0.00687 +Epoch [1910/4000] Training [8/16] Loss: 0.00536 +Epoch [1910/4000] Training [9/16] Loss: 0.00714 +Epoch [1910/4000] Training [10/16] Loss: 0.00663 +Epoch [1910/4000] Training [11/16] Loss: 0.00516 +Epoch [1910/4000] Training [12/16] Loss: 0.00758 +Epoch [1910/4000] Training [13/16] Loss: 0.00632 +Epoch [1910/4000] Training [14/16] Loss: 0.00814 +Epoch [1910/4000] Training [15/16] Loss: 0.00916 +Epoch [1910/4000] Training [16/16] Loss: 0.00540 +Epoch [1910/4000] Training metric {'Train/mean dice_metric': 0.9951084852218628, 'Train/mean miou_metric': 0.9900420904159546, 'Train/mean f1': 0.9911629557609558, 'Train/mean precision': 0.9866031408309937, 'Train/mean recall': 0.995765209197998, 'Train/mean hd95_metric': 1.1355124711990356} +Epoch [1910/4000] Validation [1/4] Loss: 0.36715 focal_loss 0.29288 dice_loss 0.07427 +Epoch [1910/4000] Validation [2/4] Loss: 0.41331 focal_loss 0.24579 dice_loss 0.16752 +Epoch [1910/4000] Validation [3/4] Loss: 0.37821 focal_loss 0.27888 dice_loss 0.09933 +Epoch [1910/4000] Validation [4/4] Loss: 0.36714 focal_loss 0.26772 dice_loss 0.09942 +Epoch [1910/4000] Validation metric {'Val/mean dice_metric': 0.9701949954032898, 'Val/mean miou_metric': 0.9528071284294128, 'Val/mean f1': 0.9724220037460327, 'Val/mean precision': 0.9718227386474609, 'Val/mean recall': 0.9730218052864075, 'Val/mean hd95_metric': 5.738234519958496} +Cheakpoint... +Epoch [1910/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701949954032898, 'Val/mean miou_metric': 0.9528071284294128, 'Val/mean f1': 0.9724220037460327, 'Val/mean precision': 0.9718227386474609, 'Val/mean recall': 0.9730218052864075, 'Val/mean hd95_metric': 5.738234519958496} +Epoch [1911/4000] Training [1/16] Loss: 0.00806 +Epoch [1911/4000] Training [2/16] Loss: 0.01172 +Epoch [1911/4000] Training [3/16] Loss: 0.00779 +Epoch [1911/4000] Training [4/16] Loss: 0.00758 +Epoch [1911/4000] Training [5/16] Loss: 0.00637 +Epoch [1911/4000] Training [6/16] Loss: 0.00713 +Epoch [1911/4000] Training [7/16] Loss: 0.00650 +Epoch [1911/4000] Training [8/16] Loss: 0.00599 +Epoch [1911/4000] Training [9/16] Loss: 0.00754 +Epoch [1911/4000] Training [10/16] Loss: 0.00873 +Epoch [1911/4000] Training [11/16] Loss: 0.00793 +Epoch [1911/4000] Training [12/16] Loss: 0.00610 +Epoch [1911/4000] Training [13/16] Loss: 0.00597 +Epoch [1911/4000] Training [14/16] Loss: 0.00500 +Epoch [1911/4000] Training [15/16] Loss: 0.00795 +Epoch [1911/4000] Training [16/16] Loss: 0.00592 +Epoch [1911/4000] Training metric {'Train/mean dice_metric': 0.9952144026756287, 'Train/mean miou_metric': 0.9902305603027344, 'Train/mean f1': 0.9911373257637024, 'Train/mean precision': 0.9865623712539673, 'Train/mean recall': 0.9957548975944519, 'Train/mean hd95_metric': 1.0910905599594116} +Epoch [1911/4000] Validation [1/4] Loss: 0.28375 focal_loss 0.21712 dice_loss 0.06663 +Epoch [1911/4000] Validation [2/4] Loss: 0.84179 focal_loss 0.60515 dice_loss 0.23665 +Epoch [1911/4000] Validation [3/4] Loss: 0.35923 focal_loss 0.26291 dice_loss 0.09632 +Epoch [1911/4000] Validation [4/4] Loss: 0.36401 focal_loss 0.23876 dice_loss 0.12525 +Epoch [1911/4000] Validation metric {'Val/mean dice_metric': 0.96892911195755, 'Val/mean miou_metric': 0.9516328573226929, 'Val/mean f1': 0.9725031852722168, 'Val/mean precision': 0.9678416848182678, 'Val/mean recall': 0.9772099256515503, 'Val/mean hd95_metric': 5.6804518699646} +Cheakpoint... +Epoch [1911/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96892911195755, 'Val/mean miou_metric': 0.9516328573226929, 'Val/mean f1': 0.9725031852722168, 'Val/mean precision': 0.9678416848182678, 'Val/mean recall': 0.9772099256515503, 'Val/mean hd95_metric': 5.6804518699646} +Epoch [1912/4000] Training [1/16] Loss: 0.00659 +Epoch [1912/4000] Training [2/16] Loss: 0.00632 +Epoch [1912/4000] Training [3/16] Loss: 0.00631 +Epoch [1912/4000] Training [4/16] Loss: 0.00497 +Epoch [1912/4000] Training [5/16] Loss: 0.00525 +Epoch [1912/4000] Training [6/16] Loss: 0.00751 +Epoch [1912/4000] Training [7/16] Loss: 0.00572 +Epoch [1912/4000] Training [8/16] Loss: 0.00688 +Epoch [1912/4000] Training [9/16] Loss: 0.00615 +Epoch [1912/4000] Training [10/16] Loss: 0.00515 +Epoch [1912/4000] Training [11/16] Loss: 0.00581 +Epoch [1912/4000] Training [12/16] Loss: 0.00609 +Epoch [1912/4000] Training [13/16] Loss: 0.00651 +Epoch [1912/4000] Training [14/16] Loss: 0.00622 +Epoch [1912/4000] Training [15/16] Loss: 0.00510 +Epoch [1912/4000] Training [16/16] Loss: 0.00480 +Epoch [1912/4000] Training metric {'Train/mean dice_metric': 0.9957791566848755, 'Train/mean miou_metric': 0.9913389682769775, 'Train/mean f1': 0.9916311502456665, 'Train/mean precision': 0.9870786070823669, 'Train/mean recall': 0.996225893497467, 'Train/mean hd95_metric': 1.0100297927856445} +Epoch [1912/4000] Validation [1/4] Loss: 0.27183 focal_loss 0.20900 dice_loss 0.06283 +Epoch [1912/4000] Validation [2/4] Loss: 0.30202 focal_loss 0.16712 dice_loss 0.13490 +Epoch [1912/4000] Validation [3/4] Loss: 0.38532 focal_loss 0.29036 dice_loss 0.09496 +Epoch [1912/4000] Validation [4/4] Loss: 0.26457 focal_loss 0.15805 dice_loss 0.10653 +Epoch [1912/4000] Validation metric {'Val/mean dice_metric': 0.9710022211074829, 'Val/mean miou_metric': 0.954012393951416, 'Val/mean f1': 0.972952127456665, 'Val/mean precision': 0.9665395617485046, 'Val/mean recall': 0.9794504046440125, 'Val/mean hd95_metric': 6.2611284255981445} +Cheakpoint... +Epoch [1912/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710022211074829, 'Val/mean miou_metric': 0.954012393951416, 'Val/mean f1': 0.972952127456665, 'Val/mean precision': 0.9665395617485046, 'Val/mean recall': 0.9794504046440125, 'Val/mean hd95_metric': 6.2611284255981445} +Epoch [1913/4000] Training [1/16] Loss: 0.00621 +Epoch [1913/4000] Training [2/16] Loss: 0.00444 +Epoch [1913/4000] Training [3/16] Loss: 0.00490 +Epoch [1913/4000] Training [4/16] Loss: 0.00833 +Epoch [1913/4000] Training [5/16] Loss: 0.00817 +Epoch [1913/4000] Training [6/16] Loss: 0.00585 +Epoch [1913/4000] Training [7/16] Loss: 0.00930 +Epoch [1913/4000] Training [8/16] Loss: 0.00812 +Epoch [1913/4000] Training [9/16] Loss: 0.00645 +Epoch [1913/4000] Training [10/16] Loss: 0.00800 +Epoch [1913/4000] Training [11/16] Loss: 0.00751 +Epoch [1913/4000] Training [12/16] Loss: 0.00613 +Epoch [1913/4000] Training [13/16] Loss: 0.00670 +Epoch [1913/4000] Training [14/16] Loss: 0.00795 +Epoch [1913/4000] Training [15/16] Loss: 0.00591 +Epoch [1913/4000] Training [16/16] Loss: 0.00809 +Epoch [1913/4000] Training metric {'Train/mean dice_metric': 0.9953532218933105, 'Train/mean miou_metric': 0.9905118942260742, 'Train/mean f1': 0.9913652539253235, 'Train/mean precision': 0.9869790077209473, 'Train/mean recall': 0.9957907199859619, 'Train/mean hd95_metric': 1.0512144565582275} +Epoch [1913/4000] Validation [1/4] Loss: 0.29023 focal_loss 0.21772 dice_loss 0.07251 +Epoch [1913/4000] Validation [2/4] Loss: 0.57504 focal_loss 0.38692 dice_loss 0.18812 +Epoch [1913/4000] Validation [3/4] Loss: 0.30535 focal_loss 0.21306 dice_loss 0.09229 +Epoch [1913/4000] Validation [4/4] Loss: 0.31635 focal_loss 0.19599 dice_loss 0.12036 +Epoch [1913/4000] Validation metric {'Val/mean dice_metric': 0.9689043164253235, 'Val/mean miou_metric': 0.9522868990898132, 'Val/mean f1': 0.9730691313743591, 'Val/mean precision': 0.9708554744720459, 'Val/mean recall': 0.9752929210662842, 'Val/mean hd95_metric': 6.346522331237793} +Cheakpoint... +Epoch [1913/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689043164253235, 'Val/mean miou_metric': 0.9522868990898132, 'Val/mean f1': 0.9730691313743591, 'Val/mean precision': 0.9708554744720459, 'Val/mean recall': 0.9752929210662842, 'Val/mean hd95_metric': 6.346522331237793} +Epoch [1914/4000] Training [1/16] Loss: 0.00682 +Epoch [1914/4000] Training [2/16] Loss: 0.00626 +Epoch [1914/4000] Training [3/16] Loss: 0.00657 +Epoch [1914/4000] Training [4/16] Loss: 0.00791 +Epoch [1914/4000] Training [5/16] Loss: 0.00707 +Epoch [1914/4000] Training [6/16] Loss: 0.00850 +Epoch [1914/4000] Training [7/16] Loss: 0.00490 +Epoch [1914/4000] Training [8/16] Loss: 0.00474 +Epoch [1914/4000] Training [9/16] Loss: 0.00711 +Epoch [1914/4000] Training [10/16] Loss: 0.00499 +Epoch [1914/4000] Training [11/16] Loss: 0.00485 +Epoch [1914/4000] Training [12/16] Loss: 0.00796 +Epoch [1914/4000] Training [13/16] Loss: 0.00495 +Epoch [1914/4000] Training [14/16] Loss: 0.00585 +Epoch [1914/4000] Training [15/16] Loss: 0.00721 +Epoch [1914/4000] Training [16/16] Loss: 0.00663 +Epoch [1914/4000] Training metric {'Train/mean dice_metric': 0.9957112073898315, 'Train/mean miou_metric': 0.9911917448043823, 'Train/mean f1': 0.9914143085479736, 'Train/mean precision': 0.9867562651634216, 'Train/mean recall': 0.996116578578949, 'Train/mean hd95_metric': 1.016913652420044} +Epoch [1914/4000] Validation [1/4] Loss: 0.27615 focal_loss 0.20692 dice_loss 0.06923 +Epoch [1914/4000] Validation [2/4] Loss: 0.67575 focal_loss 0.47022 dice_loss 0.20553 +Epoch [1914/4000] Validation [3/4] Loss: 0.34965 focal_loss 0.25721 dice_loss 0.09244 +Epoch [1914/4000] Validation [4/4] Loss: 0.29544 focal_loss 0.17415 dice_loss 0.12129 +Epoch [1914/4000] Validation metric {'Val/mean dice_metric': 0.969809353351593, 'Val/mean miou_metric': 0.9529293775558472, 'Val/mean f1': 0.9732599854469299, 'Val/mean precision': 0.9717974662780762, 'Val/mean recall': 0.9747268557548523, 'Val/mean hd95_metric': 6.073958873748779} +Cheakpoint... +Epoch [1914/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969809353351593, 'Val/mean miou_metric': 0.9529293775558472, 'Val/mean f1': 0.9732599854469299, 'Val/mean precision': 0.9717974662780762, 'Val/mean recall': 0.9747268557548523, 'Val/mean hd95_metric': 6.073958873748779} +Epoch [1915/4000] Training [1/16] Loss: 0.00703 +Epoch [1915/4000] Training [2/16] Loss: 0.00511 +Epoch [1915/4000] Training [3/16] Loss: 0.00627 +Epoch [1915/4000] Training [4/16] Loss: 0.00602 +Epoch [1915/4000] Training [5/16] Loss: 0.00758 +Epoch [1915/4000] Training [6/16] Loss: 0.00475 +Epoch [1915/4000] Training [7/16] Loss: 0.00466 +Epoch [1915/4000] Training [8/16] Loss: 0.00678 +Epoch [1915/4000] Training [9/16] Loss: 0.00677 +Epoch [1915/4000] Training [10/16] Loss: 0.00545 +Epoch [1915/4000] Training [11/16] Loss: 0.00535 +Epoch [1915/4000] Training [12/16] Loss: 0.00882 +Epoch [1915/4000] Training [13/16] Loss: 0.00441 +Epoch [1915/4000] Training [14/16] Loss: 0.00487 +Epoch [1915/4000] Training [15/16] Loss: 0.00662 +Epoch [1915/4000] Training [16/16] Loss: 0.00916 +Epoch [1915/4000] Training metric {'Train/mean dice_metric': 0.9957254528999329, 'Train/mean miou_metric': 0.9912664294242859, 'Train/mean f1': 0.9915977716445923, 'Train/mean precision': 0.9870728850364685, 'Train/mean recall': 0.9961643218994141, 'Train/mean hd95_metric': 1.0687761306762695} +Epoch [1915/4000] Validation [1/4] Loss: 0.31875 focal_loss 0.25036 dice_loss 0.06838 +Epoch [1915/4000] Validation [2/4] Loss: 0.50891 focal_loss 0.32272 dice_loss 0.18620 +Epoch [1915/4000] Validation [3/4] Loss: 0.32059 focal_loss 0.23097 dice_loss 0.08961 +Epoch [1915/4000] Validation [4/4] Loss: 0.33496 focal_loss 0.21759 dice_loss 0.11737 +Epoch [1915/4000] Validation metric {'Val/mean dice_metric': 0.9701553583145142, 'Val/mean miou_metric': 0.9536382555961609, 'Val/mean f1': 0.973375678062439, 'Val/mean precision': 0.9707943797111511, 'Val/mean recall': 0.9759708642959595, 'Val/mean hd95_metric': 6.446062088012695} +Cheakpoint... +Epoch [1915/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701553583145142, 'Val/mean miou_metric': 0.9536382555961609, 'Val/mean f1': 0.973375678062439, 'Val/mean precision': 0.9707943797111511, 'Val/mean recall': 0.9759708642959595, 'Val/mean hd95_metric': 6.446062088012695} +Epoch [1916/4000] Training [1/16] Loss: 0.00596 +Epoch [1916/4000] Training [2/16] Loss: 0.00772 +Epoch [1916/4000] Training [3/16] Loss: 0.00400 +Epoch [1916/4000] Training [4/16] Loss: 0.00844 +Epoch [1916/4000] Training [5/16] Loss: 0.00546 +Epoch [1916/4000] Training [6/16] Loss: 0.00440 +Epoch [1916/4000] Training [7/16] Loss: 0.01065 +Epoch [1916/4000] Training [8/16] Loss: 0.00473 +Epoch [1916/4000] Training [9/16] Loss: 0.00682 +Epoch [1916/4000] Training [10/16] Loss: 0.00618 +Epoch [1916/4000] Training [11/16] Loss: 0.00668 +Epoch [1916/4000] Training [12/16] Loss: 0.00588 +Epoch [1916/4000] Training [13/16] Loss: 0.00624 +Epoch [1916/4000] Training [14/16] Loss: 0.00759 +Epoch [1916/4000] Training [15/16] Loss: 0.00608 +Epoch [1916/4000] Training [16/16] Loss: 0.00785 +Epoch [1916/4000] Training metric {'Train/mean dice_metric': 0.9958686828613281, 'Train/mean miou_metric': 0.9915165901184082, 'Train/mean f1': 0.9915702939033508, 'Train/mean precision': 0.9870307445526123, 'Train/mean recall': 0.9961517453193665, 'Train/mean hd95_metric': 1.038446307182312} +Epoch [1916/4000] Validation [1/4] Loss: 0.24760 focal_loss 0.18917 dice_loss 0.05843 +Epoch [1916/4000] Validation [2/4] Loss: 0.22595 focal_loss 0.13421 dice_loss 0.09173 +Epoch [1916/4000] Validation [3/4] Loss: 0.40475 focal_loss 0.29682 dice_loss 0.10793 +Epoch [1916/4000] Validation [4/4] Loss: 0.20582 focal_loss 0.13356 dice_loss 0.07227 +Epoch [1916/4000] Validation metric {'Val/mean dice_metric': 0.9720109105110168, 'Val/mean miou_metric': 0.9557741284370422, 'Val/mean f1': 0.9737855792045593, 'Val/mean precision': 0.9690900444984436, 'Val/mean recall': 0.9785268306732178, 'Val/mean hd95_metric': 6.356162071228027} +Cheakpoint... +Epoch [1916/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720109105110168, 'Val/mean miou_metric': 0.9557741284370422, 'Val/mean f1': 0.9737855792045593, 'Val/mean precision': 0.9690900444984436, 'Val/mean recall': 0.9785268306732178, 'Val/mean hd95_metric': 6.356162071228027} +Epoch [1917/4000] Training [1/16] Loss: 0.00632 +Epoch [1917/4000] Training [2/16] Loss: 0.00864 +Epoch [1917/4000] Training [3/16] Loss: 0.00848 +Epoch [1917/4000] Training [4/16] Loss: 0.00657 +Epoch [1917/4000] Training [5/16] Loss: 0.00778 +Epoch [1917/4000] Training [6/16] Loss: 0.00490 +Epoch [1917/4000] Training [7/16] Loss: 0.00593 +Epoch [1917/4000] Training [8/16] Loss: 0.00458 +Epoch [1917/4000] Training [9/16] Loss: 0.00754 +Epoch [1917/4000] Training [10/16] Loss: 0.00607 +Epoch [1917/4000] Training [11/16] Loss: 0.00670 +Epoch [1917/4000] Training [12/16] Loss: 0.00596 +Epoch [1917/4000] Training [13/16] Loss: 0.00752 +Epoch [1917/4000] Training [14/16] Loss: 0.00554 +Epoch [1917/4000] Training [15/16] Loss: 0.00683 +Epoch [1917/4000] Training [16/16] Loss: 0.00717 +Epoch [1917/4000] Training metric {'Train/mean dice_metric': 0.9955117106437683, 'Train/mean miou_metric': 0.9908090829849243, 'Train/mean f1': 0.9914812445640564, 'Train/mean precision': 0.9870256781578064, 'Train/mean recall': 0.9959772229194641, 'Train/mean hd95_metric': 1.286198377609253} +Epoch [1917/4000] Validation [1/4] Loss: 0.24677 focal_loss 0.18488 dice_loss 0.06189 +Epoch [1917/4000] Validation [2/4] Loss: 0.60022 focal_loss 0.40189 dice_loss 0.19833 +Epoch [1917/4000] Validation [3/4] Loss: 0.21268 focal_loss 0.13212 dice_loss 0.08056 +Epoch [1917/4000] Validation [4/4] Loss: 0.28823 focal_loss 0.18261 dice_loss 0.10563 +Epoch [1917/4000] Validation metric {'Val/mean dice_metric': 0.9704810976982117, 'Val/mean miou_metric': 0.953476071357727, 'Val/mean f1': 0.9730516672134399, 'Val/mean precision': 0.9706649780273438, 'Val/mean recall': 0.9754500985145569, 'Val/mean hd95_metric': 5.874247074127197} +Cheakpoint... +Epoch [1917/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704810976982117, 'Val/mean miou_metric': 0.953476071357727, 'Val/mean f1': 0.9730516672134399, 'Val/mean precision': 0.9706649780273438, 'Val/mean recall': 0.9754500985145569, 'Val/mean hd95_metric': 5.874247074127197} +Epoch [1918/4000] Training [1/16] Loss: 0.00709 +Epoch [1918/4000] Training [2/16] Loss: 0.00554 +Epoch [1918/4000] Training [3/16] Loss: 0.00430 +Epoch [1918/4000] Training [4/16] Loss: 0.00728 +Epoch [1918/4000] Training [5/16] Loss: 0.00503 +Epoch [1918/4000] Training [6/16] Loss: 0.00504 +Epoch [1918/4000] Training [7/16] Loss: 0.00616 +Epoch [1918/4000] Training [8/16] Loss: 0.00501 +Epoch [1918/4000] Training [9/16] Loss: 0.00628 +Epoch [1918/4000] Training [10/16] Loss: 0.00866 +Epoch [1918/4000] Training [11/16] Loss: 0.00819 +Epoch [1918/4000] Training [12/16] Loss: 0.00829 +Epoch [1918/4000] Training [13/16] Loss: 0.00814 +Epoch [1918/4000] Training [14/16] Loss: 0.00536 +Epoch [1918/4000] Training [15/16] Loss: 0.00646 +Epoch [1918/4000] Training [16/16] Loss: 0.00869 +Epoch [1918/4000] Training metric {'Train/mean dice_metric': 0.9956177473068237, 'Train/mean miou_metric': 0.9909641742706299, 'Train/mean f1': 0.9899402856826782, 'Train/mean precision': 0.9840618968009949, 'Train/mean recall': 0.9958893656730652, 'Train/mean hd95_metric': 1.0518238544464111} +Epoch [1918/4000] Validation [1/4] Loss: 0.24464 focal_loss 0.18245 dice_loss 0.06218 +Epoch [1918/4000] Validation [2/4] Loss: 0.81804 focal_loss 0.58608 dice_loss 0.23196 +Epoch [1918/4000] Validation [3/4] Loss: 0.29217 focal_loss 0.20074 dice_loss 0.09143 +Epoch [1918/4000] Validation [4/4] Loss: 0.25342 focal_loss 0.15677 dice_loss 0.09665 +Epoch [1918/4000] Validation metric {'Val/mean dice_metric': 0.9688913226127625, 'Val/mean miou_metric': 0.9523252248764038, 'Val/mean f1': 0.9722961187362671, 'Val/mean precision': 0.9687498211860657, 'Val/mean recall': 0.9758685827255249, 'Val/mean hd95_metric': 5.541258811950684} +Cheakpoint... +Epoch [1918/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688913226127625, 'Val/mean miou_metric': 0.9523252248764038, 'Val/mean f1': 0.9722961187362671, 'Val/mean precision': 0.9687498211860657, 'Val/mean recall': 0.9758685827255249, 'Val/mean hd95_metric': 5.541258811950684} +Epoch [1919/4000] Training [1/16] Loss: 0.00679 +Epoch [1919/4000] Training [2/16] Loss: 0.00603 +Epoch [1919/4000] Training [3/16] Loss: 0.00675 +Epoch [1919/4000] Training [4/16] Loss: 0.00504 +Epoch [1919/4000] Training [5/16] Loss: 0.00670 +Epoch [1919/4000] Training [6/16] Loss: 0.00782 +Epoch [1919/4000] Training [7/16] Loss: 0.00498 +Epoch [1919/4000] Training [8/16] Loss: 0.00832 +Epoch [1919/4000] Training [9/16] Loss: 0.00587 +Epoch [1919/4000] Training [10/16] Loss: 0.00557 +Epoch [1919/4000] Training [11/16] Loss: 0.00671 +Epoch [1919/4000] Training [12/16] Loss: 0.00763 +Epoch [1919/4000] Training [13/16] Loss: 0.00657 +Epoch [1919/4000] Training [14/16] Loss: 0.00631 +Epoch [1919/4000] Training [15/16] Loss: 0.00723 +Epoch [1919/4000] Training [16/16] Loss: 0.00594 +Epoch [1919/4000] Training metric {'Train/mean dice_metric': 0.9958748817443848, 'Train/mean miou_metric': 0.9915227890014648, 'Train/mean f1': 0.9916045665740967, 'Train/mean precision': 0.9871091246604919, 'Train/mean recall': 0.9961411952972412, 'Train/mean hd95_metric': 1.0133118629455566} +Epoch [1919/4000] Validation [1/4] Loss: 0.25565 focal_loss 0.19166 dice_loss 0.06399 +Epoch [1919/4000] Validation [2/4] Loss: 0.59031 focal_loss 0.40191 dice_loss 0.18840 +Epoch [1919/4000] Validation [3/4] Loss: 0.18502 focal_loss 0.12660 dice_loss 0.05841 +Epoch [1919/4000] Validation [4/4] Loss: 0.24836 focal_loss 0.14945 dice_loss 0.09891 +Epoch [1919/4000] Validation metric {'Val/mean dice_metric': 0.9704353213310242, 'Val/mean miou_metric': 0.9543906450271606, 'Val/mean f1': 0.974616527557373, 'Val/mean precision': 0.9731903672218323, 'Val/mean recall': 0.9760469198226929, 'Val/mean hd95_metric': 5.454070091247559} +Cheakpoint... +Epoch [1919/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704353213310242, 'Val/mean miou_metric': 0.9543906450271606, 'Val/mean f1': 0.974616527557373, 'Val/mean precision': 0.9731903672218323, 'Val/mean recall': 0.9760469198226929, 'Val/mean hd95_metric': 5.454070091247559} +Epoch [1920/4000] Training [1/16] Loss: 0.00493 +Epoch [1920/4000] Training [2/16] Loss: 0.00577 +Epoch [1920/4000] Training [3/16] Loss: 0.00487 +Epoch [1920/4000] Training [4/16] Loss: 0.00608 +Epoch [1920/4000] Training [5/16] Loss: 0.00487 +Epoch [1920/4000] Training [6/16] Loss: 0.00594 +Epoch [1920/4000] Training [7/16] Loss: 0.00475 +Epoch [1920/4000] Training [8/16] Loss: 0.00805 +Epoch [1920/4000] Training [9/16] Loss: 0.00660 +Epoch [1920/4000] Training [10/16] Loss: 0.00704 +Epoch [1920/4000] Training [11/16] Loss: 0.00591 +Epoch [1920/4000] Training [12/16] Loss: 0.00640 +Epoch [1920/4000] Training [13/16] Loss: 0.00826 +Epoch [1920/4000] Training [14/16] Loss: 0.00674 +Epoch [1920/4000] Training [15/16] Loss: 0.00777 +Epoch [1920/4000] Training [16/16] Loss: 0.00810 +Epoch [1920/4000] Training metric {'Train/mean dice_metric': 0.9958236217498779, 'Train/mean miou_metric': 0.991428017616272, 'Train/mean f1': 0.9916782379150391, 'Train/mean precision': 0.9871306419372559, 'Train/mean recall': 0.9962678551673889, 'Train/mean hd95_metric': 1.0236047506332397} +Epoch [1920/4000] Validation [1/4] Loss: 0.25519 focal_loss 0.19010 dice_loss 0.06509 +Epoch [1920/4000] Validation [2/4] Loss: 0.85527 focal_loss 0.61617 dice_loss 0.23910 +Epoch [1920/4000] Validation [3/4] Loss: 0.22493 focal_loss 0.14718 dice_loss 0.07776 +Epoch [1920/4000] Validation [4/4] Loss: 0.29913 focal_loss 0.18431 dice_loss 0.11481 +Epoch [1920/4000] Validation metric {'Val/mean dice_metric': 0.9709054231643677, 'Val/mean miou_metric': 0.9543721079826355, 'Val/mean f1': 0.9742539525032043, 'Val/mean precision': 0.9716414213180542, 'Val/mean recall': 0.976880669593811, 'Val/mean hd95_metric': 5.608400821685791} +Cheakpoint... +Epoch [1920/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709054231643677, 'Val/mean miou_metric': 0.9543721079826355, 'Val/mean f1': 0.9742539525032043, 'Val/mean precision': 0.9716414213180542, 'Val/mean recall': 0.976880669593811, 'Val/mean hd95_metric': 5.608400821685791} +Epoch [1921/4000] Training [1/16] Loss: 0.00532 +Epoch [1921/4000] Training [2/16] Loss: 0.00667 +Epoch [1921/4000] Training [3/16] Loss: 0.00576 +Epoch [1921/4000] Training [4/16] Loss: 0.00529 +Epoch [1921/4000] Training [5/16] Loss: 0.00573 +Epoch [1921/4000] Training [6/16] Loss: 0.00529 +Epoch [1921/4000] Training [7/16] Loss: 0.00714 +Epoch [1921/4000] Training [8/16] Loss: 0.00609 +Epoch [1921/4000] Training [9/16] Loss: 0.00547 +Epoch [1921/4000] Training [10/16] Loss: 0.00639 +Epoch [1921/4000] Training [11/16] Loss: 0.00565 +Epoch [1921/4000] Training [12/16] Loss: 0.00652 +Epoch [1921/4000] Training [13/16] Loss: 0.00462 +Epoch [1921/4000] Training [14/16] Loss: 0.00521 +Epoch [1921/4000] Training [15/16] Loss: 0.00612 +Epoch [1921/4000] Training [16/16] Loss: 0.00624 +Epoch [1921/4000] Training metric {'Train/mean dice_metric': 0.9961137175559998, 'Train/mean miou_metric': 0.991992712020874, 'Train/mean f1': 0.9917663931846619, 'Train/mean precision': 0.9872194528579712, 'Train/mean recall': 0.9963553547859192, 'Train/mean hd95_metric': 1.0044634342193604} +Epoch [1921/4000] Validation [1/4] Loss: 0.27909 focal_loss 0.21350 dice_loss 0.06559 +Epoch [1921/4000] Validation [2/4] Loss: 0.60618 focal_loss 0.42375 dice_loss 0.18243 +Epoch [1921/4000] Validation [3/4] Loss: 0.18945 focal_loss 0.12644 dice_loss 0.06302 +Epoch [1921/4000] Validation [4/4] Loss: 0.25470 focal_loss 0.15396 dice_loss 0.10074 +Epoch [1921/4000] Validation metric {'Val/mean dice_metric': 0.972588062286377, 'Val/mean miou_metric': 0.9568403363227844, 'Val/mean f1': 0.9748833179473877, 'Val/mean precision': 0.9718989729881287, 'Val/mean recall': 0.9778860211372375, 'Val/mean hd95_metric': 5.378324508666992} +Cheakpoint... +Epoch [1921/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972588062286377, 'Val/mean miou_metric': 0.9568403363227844, 'Val/mean f1': 0.9748833179473877, 'Val/mean precision': 0.9718989729881287, 'Val/mean recall': 0.9778860211372375, 'Val/mean hd95_metric': 5.378324508666992} +Epoch [1922/4000] Training [1/16] Loss: 0.00902 +Epoch [1922/4000] Training [2/16] Loss: 0.00450 +Epoch [1922/4000] Training [3/16] Loss: 0.00885 +Epoch [1922/4000] Training [4/16] Loss: 0.00610 +Epoch [1922/4000] Training [5/16] Loss: 0.00758 +Epoch [1922/4000] Training [6/16] Loss: 0.00530 +Epoch [1922/4000] Training [7/16] Loss: 0.00976 +Epoch [1922/4000] Training [8/16] Loss: 0.00695 +Epoch [1922/4000] Training [9/16] Loss: 0.00704 +Epoch [1922/4000] Training [10/16] Loss: 0.00687 +Epoch [1922/4000] Training [11/16] Loss: 0.00508 +Epoch [1922/4000] Training [12/16] Loss: 0.00571 +Epoch [1922/4000] Training [13/16] Loss: 0.00589 +Epoch [1922/4000] Training [14/16] Loss: 0.00812 +Epoch [1922/4000] Training [15/16] Loss: 0.00789 +Epoch [1922/4000] Training [16/16] Loss: 0.00556 +Epoch [1922/4000] Training metric {'Train/mean dice_metric': 0.9954422116279602, 'Train/mean miou_metric': 0.9906784296035767, 'Train/mean f1': 0.9911983013153076, 'Train/mean precision': 0.9867232441902161, 'Train/mean recall': 0.9957141280174255, 'Train/mean hd95_metric': 1.1629160642623901} +Epoch [1922/4000] Validation [1/4] Loss: 0.30916 focal_loss 0.24146 dice_loss 0.06770 +Epoch [1922/4000] Validation [2/4] Loss: 0.35438 focal_loss 0.22954 dice_loss 0.12484 +Epoch [1922/4000] Validation [3/4] Loss: 0.21368 focal_loss 0.14504 dice_loss 0.06863 +Epoch [1922/4000] Validation [4/4] Loss: 0.25203 focal_loss 0.15244 dice_loss 0.09959 +Epoch [1922/4000] Validation metric {'Val/mean dice_metric': 0.9709680676460266, 'Val/mean miou_metric': 0.9539505243301392, 'Val/mean f1': 0.9741551876068115, 'Val/mean precision': 0.9723179936408997, 'Val/mean recall': 0.9759992957115173, 'Val/mean hd95_metric': 6.120449542999268} +Cheakpoint... +Epoch [1922/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709680676460266, 'Val/mean miou_metric': 0.9539505243301392, 'Val/mean f1': 0.9741551876068115, 'Val/mean precision': 0.9723179936408997, 'Val/mean recall': 0.9759992957115173, 'Val/mean hd95_metric': 6.120449542999268} +Epoch [1923/4000] Training [1/16] Loss: 0.00560 +Epoch [1923/4000] Training [2/16] Loss: 0.00610 +Epoch [1923/4000] Training [3/16] Loss: 0.00641 +Epoch [1923/4000] Training [4/16] Loss: 0.00594 +Epoch [1923/4000] Training [5/16] Loss: 0.00489 +Epoch [1923/4000] Training [6/16] Loss: 0.00627 +Epoch [1923/4000] Training [7/16] Loss: 0.00460 +Epoch [1923/4000] Training [8/16] Loss: 0.00529 +Epoch [1923/4000] Training [9/16] Loss: 0.00653 +Epoch [1923/4000] Training [10/16] Loss: 0.00662 +Epoch [1923/4000] Training [11/16] Loss: 0.00612 +Epoch [1923/4000] Training [12/16] Loss: 0.00670 +Epoch [1923/4000] Training [13/16] Loss: 0.00671 +Epoch [1923/4000] Training [14/16] Loss: 0.00427 +Epoch [1923/4000] Training [15/16] Loss: 0.00789 +Epoch [1923/4000] Training [16/16] Loss: 0.00468 +Epoch [1923/4000] Training metric {'Train/mean dice_metric': 0.9960827827453613, 'Train/mean miou_metric': 0.9919185638427734, 'Train/mean f1': 0.9915556907653809, 'Train/mean precision': 0.9867013096809387, 'Train/mean recall': 0.9964579939842224, 'Train/mean hd95_metric': 1.0114485025405884} +Epoch [1923/4000] Validation [1/4] Loss: 0.22867 focal_loss 0.16932 dice_loss 0.05935 +Epoch [1923/4000] Validation [2/4] Loss: 0.64435 focal_loss 0.45498 dice_loss 0.18938 +Epoch [1923/4000] Validation [3/4] Loss: 0.20382 focal_loss 0.13103 dice_loss 0.07279 +Epoch [1923/4000] Validation [4/4] Loss: 0.26976 focal_loss 0.16777 dice_loss 0.10199 +Epoch [1923/4000] Validation metric {'Val/mean dice_metric': 0.9712543487548828, 'Val/mean miou_metric': 0.9555202722549438, 'Val/mean f1': 0.9744916558265686, 'Val/mean precision': 0.9726704955101013, 'Val/mean recall': 0.9763195514678955, 'Val/mean hd95_metric': 5.551527976989746} +Cheakpoint... +Epoch [1923/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712543487548828, 'Val/mean miou_metric': 0.9555202722549438, 'Val/mean f1': 0.9744916558265686, 'Val/mean precision': 0.9726704955101013, 'Val/mean recall': 0.9763195514678955, 'Val/mean hd95_metric': 5.551527976989746} +Epoch [1924/4000] Training [1/16] Loss: 0.00702 +Epoch [1924/4000] Training [2/16] Loss: 0.00639 +Epoch [1924/4000] Training [3/16] Loss: 0.00559 +Epoch [1924/4000] Training [4/16] Loss: 0.00548 +Epoch [1924/4000] Training [5/16] Loss: 0.00819 +Epoch [1924/4000] Training [6/16] Loss: 0.00718 +Epoch [1924/4000] Training [7/16] Loss: 0.00529 +Epoch [1924/4000] Training [8/16] Loss: 0.00569 +Epoch [1924/4000] Training [9/16] Loss: 0.00620 +Epoch [1924/4000] Training [10/16] Loss: 0.00491 +Epoch [1924/4000] Training [11/16] Loss: 0.00578 +Epoch [1924/4000] Training [12/16] Loss: 0.00767 +Epoch [1924/4000] Training [13/16] Loss: 0.00624 +Epoch [1924/4000] Training [14/16] Loss: 0.00998 +Epoch [1924/4000] Training [15/16] Loss: 0.00671 +Epoch [1924/4000] Training [16/16] Loss: 0.00691 +Epoch [1924/4000] Training metric {'Train/mean dice_metric': 0.9956220388412476, 'Train/mean miou_metric': 0.9910150766372681, 'Train/mean f1': 0.9913551211357117, 'Train/mean precision': 0.9867919683456421, 'Train/mean recall': 0.9959605932235718, 'Train/mean hd95_metric': 1.029493808746338} +Epoch [1924/4000] Validation [1/4] Loss: 0.23488 focal_loss 0.17616 dice_loss 0.05872 +Epoch [1924/4000] Validation [2/4] Loss: 0.76731 focal_loss 0.54812 dice_loss 0.21919 +Epoch [1924/4000] Validation [3/4] Loss: 0.21980 focal_loss 0.14869 dice_loss 0.07112 +Epoch [1924/4000] Validation [4/4] Loss: 0.32234 focal_loss 0.20176 dice_loss 0.12058 +Epoch [1924/4000] Validation metric {'Val/mean dice_metric': 0.9695976376533508, 'Val/mean miou_metric': 0.9530481100082397, 'Val/mean f1': 0.9737880825996399, 'Val/mean precision': 0.9720750451087952, 'Val/mean recall': 0.9755073189735413, 'Val/mean hd95_metric': 5.803320407867432} +Cheakpoint... +Epoch [1924/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695976376533508, 'Val/mean miou_metric': 0.9530481100082397, 'Val/mean f1': 0.9737880825996399, 'Val/mean precision': 0.9720750451087952, 'Val/mean recall': 0.9755073189735413, 'Val/mean hd95_metric': 5.803320407867432} +Epoch [1925/4000] Training [1/16] Loss: 0.00561 +Epoch [1925/4000] Training [2/16] Loss: 0.00644 +Epoch [1925/4000] Training [3/16] Loss: 0.00637 +Epoch [1925/4000] Training [4/16] Loss: 0.00635 +Epoch [1925/4000] Training [5/16] Loss: 0.00631 +Epoch [1925/4000] Training [6/16] Loss: 0.00548 +Epoch [1925/4000] Training [7/16] Loss: 0.00840 +Epoch [1925/4000] Training [8/16] Loss: 0.00524 +Epoch [1925/4000] Training [9/16] Loss: 0.00480 +Epoch [1925/4000] Training [10/16] Loss: 0.00533 +Epoch [1925/4000] Training [11/16] Loss: 0.00723 +Epoch [1925/4000] Training [12/16] Loss: 0.00580 +Epoch [1925/4000] Training [13/16] Loss: 0.00688 +Epoch [1925/4000] Training [14/16] Loss: 0.00803 +Epoch [1925/4000] Training [15/16] Loss: 0.00567 +Epoch [1925/4000] Training [16/16] Loss: 0.00631 +Epoch [1925/4000] Training metric {'Train/mean dice_metric': 0.9957371950149536, 'Train/mean miou_metric': 0.9912485480308533, 'Train/mean f1': 0.9914945960044861, 'Train/mean precision': 0.9867753982543945, 'Train/mean recall': 0.9962591528892517, 'Train/mean hd95_metric': 1.0161068439483643} +Epoch [1925/4000] Validation [1/4] Loss: 0.27586 focal_loss 0.20317 dice_loss 0.07269 +Epoch [1925/4000] Validation [2/4] Loss: 0.46606 focal_loss 0.29122 dice_loss 0.17485 +Epoch [1925/4000] Validation [3/4] Loss: 0.20328 focal_loss 0.14266 dice_loss 0.06063 +Epoch [1925/4000] Validation [4/4] Loss: 0.22981 focal_loss 0.14738 dice_loss 0.08243 +Epoch [1925/4000] Validation metric {'Val/mean dice_metric': 0.9725587964057922, 'Val/mean miou_metric': 0.956321120262146, 'Val/mean f1': 0.9737521409988403, 'Val/mean precision': 0.9713067412376404, 'Val/mean recall': 0.9762098789215088, 'Val/mean hd95_metric': 4.979778289794922} +Cheakpoint... +Epoch [1925/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725587964057922, 'Val/mean miou_metric': 0.956321120262146, 'Val/mean f1': 0.9737521409988403, 'Val/mean precision': 0.9713067412376404, 'Val/mean recall': 0.9762098789215088, 'Val/mean hd95_metric': 4.979778289794922} +Epoch [1926/4000] Training [1/16] Loss: 0.00580 +Epoch [1926/4000] Training [2/16] Loss: 0.00645 +Epoch [1926/4000] Training [3/16] Loss: 0.00714 +Epoch [1926/4000] Training [4/16] Loss: 0.00478 +Epoch [1926/4000] Training [5/16] Loss: 0.00588 +Epoch [1926/4000] Training [6/16] Loss: 0.00645 +Epoch [1926/4000] Training [7/16] Loss: 0.00701 +Epoch [1926/4000] Training [8/16] Loss: 0.00550 +Epoch [1926/4000] Training [9/16] Loss: 0.00569 +Epoch [1926/4000] Training [10/16] Loss: 0.00608 +Epoch [1926/4000] Training [11/16] Loss: 0.00548 +Epoch [1926/4000] Training [12/16] Loss: 0.00766 +Epoch [1926/4000] Training [13/16] Loss: 0.00644 +Epoch [1926/4000] Training [14/16] Loss: 0.00736 +Epoch [1926/4000] Training [15/16] Loss: 0.00731 +Epoch [1926/4000] Training [16/16] Loss: 0.00731 +Epoch [1926/4000] Training metric {'Train/mean dice_metric': 0.9958350658416748, 'Train/mean miou_metric': 0.9914274215698242, 'Train/mean f1': 0.9914512038230896, 'Train/mean precision': 0.9868322014808655, 'Train/mean recall': 0.9961135983467102, 'Train/mean hd95_metric': 1.0140299797058105} +Epoch [1926/4000] Validation [1/4] Loss: 0.28159 focal_loss 0.21760 dice_loss 0.06399 +Epoch [1926/4000] Validation [2/4] Loss: 0.69264 focal_loss 0.47259 dice_loss 0.22004 +Epoch [1926/4000] Validation [3/4] Loss: 0.37410 focal_loss 0.27633 dice_loss 0.09777 +Epoch [1926/4000] Validation [4/4] Loss: 0.36121 focal_loss 0.22480 dice_loss 0.13641 +Epoch [1926/4000] Validation metric {'Val/mean dice_metric': 0.9715120196342468, 'Val/mean miou_metric': 0.954594612121582, 'Val/mean f1': 0.9736654758453369, 'Val/mean precision': 0.9704071283340454, 'Val/mean recall': 0.9769456386566162, 'Val/mean hd95_metric': 5.2445173263549805} +Cheakpoint... +Epoch [1926/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715120196342468, 'Val/mean miou_metric': 0.954594612121582, 'Val/mean f1': 0.9736654758453369, 'Val/mean precision': 0.9704071283340454, 'Val/mean recall': 0.9769456386566162, 'Val/mean hd95_metric': 5.2445173263549805} +Epoch [1927/4000] Training [1/16] Loss: 0.00517 +Epoch [1927/4000] Training [2/16] Loss: 0.00582 +Epoch [1927/4000] Training [3/16] Loss: 0.00727 +Epoch [1927/4000] Training [4/16] Loss: 0.00536 +Epoch [1927/4000] Training [5/16] Loss: 0.00748 +Epoch [1927/4000] Training [6/16] Loss: 0.00658 +Epoch [1927/4000] Training [7/16] Loss: 0.00678 +Epoch [1927/4000] Training [8/16] Loss: 0.00599 +Epoch [1927/4000] Training [9/16] Loss: 0.00586 +Epoch [1927/4000] Training [10/16] Loss: 0.00479 +Epoch [1927/4000] Training [11/16] Loss: 0.00683 +Epoch [1927/4000] Training [12/16] Loss: 0.00820 +Epoch [1927/4000] Training [13/16] Loss: 0.00871 +Epoch [1927/4000] Training [14/16] Loss: 0.00646 +Epoch [1927/4000] Training [15/16] Loss: 0.00662 +Epoch [1927/4000] Training [16/16] Loss: 0.00916 +Epoch [1927/4000] Training metric {'Train/mean dice_metric': 0.9956614971160889, 'Train/mean miou_metric': 0.9911030530929565, 'Train/mean f1': 0.9916325807571411, 'Train/mean precision': 0.9871416091918945, 'Train/mean recall': 0.9961645603179932, 'Train/mean hd95_metric': 1.0123095512390137} +Epoch [1927/4000] Validation [1/4] Loss: 0.23172 focal_loss 0.17485 dice_loss 0.05688 +Epoch [1927/4000] Validation [2/4] Loss: 0.34502 focal_loss 0.22023 dice_loss 0.12479 +Epoch [1927/4000] Validation [3/4] Loss: 0.33822 focal_loss 0.24190 dice_loss 0.09633 +Epoch [1927/4000] Validation [4/4] Loss: 0.22018 focal_loss 0.13482 dice_loss 0.08537 +Epoch [1927/4000] Validation metric {'Val/mean dice_metric': 0.9722864031791687, 'Val/mean miou_metric': 0.9555717706680298, 'Val/mean f1': 0.9747480154037476, 'Val/mean precision': 0.9719204902648926, 'Val/mean recall': 0.977591872215271, 'Val/mean hd95_metric': 5.253207683563232} +Cheakpoint... +Epoch [1927/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722864031791687, 'Val/mean miou_metric': 0.9555717706680298, 'Val/mean f1': 0.9747480154037476, 'Val/mean precision': 0.9719204902648926, 'Val/mean recall': 0.977591872215271, 'Val/mean hd95_metric': 5.253207683563232} +Epoch [1928/4000] Training [1/16] Loss: 0.00601 +Epoch [1928/4000] Training [2/16] Loss: 0.00666 +Epoch [1928/4000] Training [3/16] Loss: 0.00499 +Epoch [1928/4000] Training [4/16] Loss: 0.00853 +Epoch [1928/4000] Training [5/16] Loss: 0.00550 +Epoch [1928/4000] Training [6/16] Loss: 0.00610 +Epoch [1928/4000] Training [7/16] Loss: 0.00678 +Epoch [1928/4000] Training [8/16] Loss: 0.00729 +Epoch [1928/4000] Training [9/16] Loss: 0.00513 +Epoch [1928/4000] Training [10/16] Loss: 0.01167 +Epoch [1928/4000] Training [11/16] Loss: 0.00544 +Epoch [1928/4000] Training [12/16] Loss: 0.00802 +Epoch [1928/4000] Training [13/16] Loss: 0.00723 +Epoch [1928/4000] Training [14/16] Loss: 0.00457 +Epoch [1928/4000] Training [15/16] Loss: 0.00631 +Epoch [1928/4000] Training [16/16] Loss: 0.00714 +Epoch [1928/4000] Training metric {'Train/mean dice_metric': 0.9955265522003174, 'Train/mean miou_metric': 0.9908083081245422, 'Train/mean f1': 0.99125075340271, 'Train/mean precision': 0.9865937232971191, 'Train/mean recall': 0.9959518909454346, 'Train/mean hd95_metric': 1.0083379745483398} +Epoch [1928/4000] Validation [1/4] Loss: 0.32758 focal_loss 0.25283 dice_loss 0.07475 +Epoch [1928/4000] Validation [2/4] Loss: 0.35406 focal_loss 0.23093 dice_loss 0.12313 +Epoch [1928/4000] Validation [3/4] Loss: 0.20444 focal_loss 0.14068 dice_loss 0.06376 +Epoch [1928/4000] Validation [4/4] Loss: 0.35737 focal_loss 0.23483 dice_loss 0.12253 +Epoch [1928/4000] Validation metric {'Val/mean dice_metric': 0.9720802307128906, 'Val/mean miou_metric': 0.9549134969711304, 'Val/mean f1': 0.973590612411499, 'Val/mean precision': 0.9713743925094604, 'Val/mean recall': 0.975817084312439, 'Val/mean hd95_metric': 5.451481342315674} +Cheakpoint... +Epoch [1928/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720802307128906, 'Val/mean miou_metric': 0.9549134969711304, 'Val/mean f1': 0.973590612411499, 'Val/mean precision': 0.9713743925094604, 'Val/mean recall': 0.975817084312439, 'Val/mean hd95_metric': 5.451481342315674} +Epoch [1929/4000] Training [1/16] Loss: 0.00739 +Epoch [1929/4000] Training [2/16] Loss: 0.00573 +Epoch [1929/4000] Training [3/16] Loss: 0.00511 +Epoch [1929/4000] Training [4/16] Loss: 0.00766 +Epoch [1929/4000] Training [5/16] Loss: 0.01083 +Epoch [1929/4000] Training [6/16] Loss: 0.00532 +Epoch [1929/4000] Training [7/16] Loss: 0.00654 +Epoch [1929/4000] Training [8/16] Loss: 0.00649 +Epoch [1929/4000] Training [9/16] Loss: 0.00477 +Epoch [1929/4000] Training [10/16] Loss: 0.00691 +Epoch [1929/4000] Training [11/16] Loss: 0.00568 +Epoch [1929/4000] Training [12/16] Loss: 0.00841 +Epoch [1929/4000] Training [13/16] Loss: 0.00609 +Epoch [1929/4000] Training [14/16] Loss: 0.01065 +Epoch [1929/4000] Training [15/16] Loss: 0.00564 +Epoch [1929/4000] Training [16/16] Loss: 0.00557 +Epoch [1929/4000] Training metric {'Train/mean dice_metric': 0.9955834150314331, 'Train/mean miou_metric': 0.9909762144088745, 'Train/mean f1': 0.9916922450065613, 'Train/mean precision': 0.9872041940689087, 'Train/mean recall': 0.9962212443351746, 'Train/mean hd95_metric': 1.0160536766052246} +Epoch [1929/4000] Validation [1/4] Loss: 0.22870 focal_loss 0.16695 dice_loss 0.06175 +Epoch [1929/4000] Validation [2/4] Loss: 0.76503 focal_loss 0.54334 dice_loss 0.22170 +Epoch [1929/4000] Validation [3/4] Loss: 0.19215 focal_loss 0.13017 dice_loss 0.06199 +Epoch [1929/4000] Validation [4/4] Loss: 0.26820 focal_loss 0.16652 dice_loss 0.10168 +Epoch [1929/4000] Validation metric {'Val/mean dice_metric': 0.9695137143135071, 'Val/mean miou_metric': 0.9531987905502319, 'Val/mean f1': 0.9741030931472778, 'Val/mean precision': 0.9735338687896729, 'Val/mean recall': 0.9746729731559753, 'Val/mean hd95_metric': 5.158833026885986} +Cheakpoint... +Epoch [1929/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695137143135071, 'Val/mean miou_metric': 0.9531987905502319, 'Val/mean f1': 0.9741030931472778, 'Val/mean precision': 0.9735338687896729, 'Val/mean recall': 0.9746729731559753, 'Val/mean hd95_metric': 5.158833026885986} +Epoch [1930/4000] Training [1/16] Loss: 0.00555 +Epoch [1930/4000] Training [2/16] Loss: 0.01063 +Epoch [1930/4000] Training [3/16] Loss: 0.00822 +Epoch [1930/4000] Training [4/16] Loss: 0.00667 +Epoch [1930/4000] Training [5/16] Loss: 0.00712 +Epoch [1930/4000] Training [6/16] Loss: 0.00627 +Epoch [1930/4000] Training [7/16] Loss: 0.00602 +Epoch [1930/4000] Training [8/16] Loss: 0.00574 +Epoch [1930/4000] Training [9/16] Loss: 0.00566 +Epoch [1930/4000] Training [10/16] Loss: 0.00584 +Epoch [1930/4000] Training [11/16] Loss: 0.00483 +Epoch [1930/4000] Training [12/16] Loss: 0.00606 +Epoch [1930/4000] Training [13/16] Loss: 0.00615 +Epoch [1930/4000] Training [14/16] Loss: 0.00613 +Epoch [1930/4000] Training [15/16] Loss: 0.00649 +Epoch [1930/4000] Training [16/16] Loss: 0.00628 +Epoch [1930/4000] Training metric {'Train/mean dice_metric': 0.9955501556396484, 'Train/mean miou_metric': 0.9908719062805176, 'Train/mean f1': 0.99112468957901, 'Train/mean precision': 0.9862997531890869, 'Train/mean recall': 0.9959970116615295, 'Train/mean hd95_metric': 1.07063889503479} +Epoch [1930/4000] Validation [1/4] Loss: 0.25621 focal_loss 0.19313 dice_loss 0.06308 +Epoch [1930/4000] Validation [2/4] Loss: 0.50076 focal_loss 0.32779 dice_loss 0.17297 +Epoch [1930/4000] Validation [3/4] Loss: 0.27314 focal_loss 0.17987 dice_loss 0.09327 +Epoch [1930/4000] Validation [4/4] Loss: 0.52727 focal_loss 0.38709 dice_loss 0.14018 +Epoch [1930/4000] Validation metric {'Val/mean dice_metric': 0.9688223004341125, 'Val/mean miou_metric': 0.9520007371902466, 'Val/mean f1': 0.9732173085212708, 'Val/mean precision': 0.973619282245636, 'Val/mean recall': 0.972815752029419, 'Val/mean hd95_metric': 5.8468241691589355} +Cheakpoint... +Epoch [1930/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688223004341125, 'Val/mean miou_metric': 0.9520007371902466, 'Val/mean f1': 0.9732173085212708, 'Val/mean precision': 0.973619282245636, 'Val/mean recall': 0.972815752029419, 'Val/mean hd95_metric': 5.8468241691589355} +Epoch [1931/4000] Training [1/16] Loss: 0.00537 +Epoch [1931/4000] Training [2/16] Loss: 0.00650 +Epoch [1931/4000] Training [3/16] Loss: 0.00775 +Epoch [1931/4000] Training [4/16] Loss: 0.01058 +Epoch [1931/4000] Training [5/16] Loss: 0.00535 +Epoch [1931/4000] Training [6/16] Loss: 0.00603 +Epoch [1931/4000] Training [7/16] Loss: 0.00528 +Epoch [1931/4000] Training [8/16] Loss: 0.00587 +Epoch [1931/4000] Training [9/16] Loss: 0.00494 +Epoch [1931/4000] Training [10/16] Loss: 0.00713 +Epoch [1931/4000] Training [11/16] Loss: 0.00715 +Epoch [1931/4000] Training [12/16] Loss: 0.00599 +Epoch [1931/4000] Training [13/16] Loss: 0.00690 +Epoch [1931/4000] Training [14/16] Loss: 0.00572 +Epoch [1931/4000] Training [15/16] Loss: 0.00680 +Epoch [1931/4000] Training [16/16] Loss: 0.00768 +Epoch [1931/4000] Training metric {'Train/mean dice_metric': 0.9956783056259155, 'Train/mean miou_metric': 0.9911332726478577, 'Train/mean f1': 0.9913884997367859, 'Train/mean precision': 0.9868422150611877, 'Train/mean recall': 0.9959768652915955, 'Train/mean hd95_metric': 1.0305352210998535} +Epoch [1931/4000] Validation [1/4] Loss: 0.28642 focal_loss 0.21423 dice_loss 0.07219 +Epoch [1931/4000] Validation [2/4] Loss: 0.66358 focal_loss 0.44647 dice_loss 0.21711 +Epoch [1931/4000] Validation [3/4] Loss: 0.25708 focal_loss 0.16659 dice_loss 0.09049 +Epoch [1931/4000] Validation [4/4] Loss: 0.24346 focal_loss 0.14557 dice_loss 0.09789 +Epoch [1931/4000] Validation metric {'Val/mean dice_metric': 0.9730022549629211, 'Val/mean miou_metric': 0.9562951922416687, 'Val/mean f1': 0.9744709730148315, 'Val/mean precision': 0.9723725318908691, 'Val/mean recall': 0.9765785336494446, 'Val/mean hd95_metric': 5.12495231628418} +Cheakpoint... +Epoch [1931/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730022549629211, 'Val/mean miou_metric': 0.9562951922416687, 'Val/mean f1': 0.9744709730148315, 'Val/mean precision': 0.9723725318908691, 'Val/mean recall': 0.9765785336494446, 'Val/mean hd95_metric': 5.12495231628418} +Epoch [1932/4000] Training [1/16] Loss: 0.00587 +Epoch [1932/4000] Training [2/16] Loss: 0.00559 +Epoch [1932/4000] Training [3/16] Loss: 0.00431 +Epoch [1932/4000] Training [4/16] Loss: 0.00704 +Epoch [1932/4000] Training [5/16] Loss: 0.00637 +Epoch [1932/4000] Training [6/16] Loss: 0.00481 +Epoch [1932/4000] Training [7/16] Loss: 0.00557 +Epoch [1932/4000] Training [8/16] Loss: 0.00668 +Epoch [1932/4000] Training [9/16] Loss: 0.00796 +Epoch [1932/4000] Training [10/16] Loss: 0.00524 +Epoch [1932/4000] Training [11/16] Loss: 0.00672 +Epoch [1932/4000] Training [12/16] Loss: 0.00518 +Epoch [1932/4000] Training [13/16] Loss: 0.00503 +Epoch [1932/4000] Training [14/16] Loss: 0.00615 +Epoch [1932/4000] Training [15/16] Loss: 0.00471 +Epoch [1932/4000] Training [16/16] Loss: 0.00667 +Epoch [1932/4000] Training metric {'Train/mean dice_metric': 0.9960556030273438, 'Train/mean miou_metric': 0.9918770790100098, 'Train/mean f1': 0.9917536973953247, 'Train/mean precision': 0.9872105121612549, 'Train/mean recall': 0.9963388442993164, 'Train/mean hd95_metric': 1.003697156906128} +Epoch [1932/4000] Validation [1/4] Loss: 0.22843 focal_loss 0.16768 dice_loss 0.06075 +Epoch [1932/4000] Validation [2/4] Loss: 0.34917 focal_loss 0.22532 dice_loss 0.12385 +Epoch [1932/4000] Validation [3/4] Loss: 0.19922 focal_loss 0.13256 dice_loss 0.06666 +Epoch [1932/4000] Validation [4/4] Loss: 0.28855 focal_loss 0.16699 dice_loss 0.12156 +Epoch [1932/4000] Validation metric {'Val/mean dice_metric': 0.9728363156318665, 'Val/mean miou_metric': 0.9563873410224915, 'Val/mean f1': 0.9747019410133362, 'Val/mean precision': 0.971890926361084, 'Val/mean recall': 0.9775294065475464, 'Val/mean hd95_metric': 5.346152305603027} +Cheakpoint... +Epoch [1932/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728363156318665, 'Val/mean miou_metric': 0.9563873410224915, 'Val/mean f1': 0.9747019410133362, 'Val/mean precision': 0.971890926361084, 'Val/mean recall': 0.9775294065475464, 'Val/mean hd95_metric': 5.346152305603027} +Epoch [1933/4000] Training [1/16] Loss: 0.00613 +Epoch [1933/4000] Training [2/16] Loss: 0.00841 +Epoch [1933/4000] Training [3/16] Loss: 0.00698 +Epoch [1933/4000] Training [4/16] Loss: 0.00683 +Epoch [1933/4000] Training [5/16] Loss: 0.00593 +Epoch [1933/4000] Training [6/16] Loss: 0.00731 +Epoch [1933/4000] Training [7/16] Loss: 0.00560 +Epoch [1933/4000] Training [8/16] Loss: 0.00551 +Epoch [1933/4000] Training [9/16] Loss: 0.00643 +Epoch [1933/4000] Training [10/16] Loss: 0.00621 +Epoch [1933/4000] Training [11/16] Loss: 0.00811 +Epoch [1933/4000] Training [12/16] Loss: 0.00666 +Epoch [1933/4000] Training [13/16] Loss: 0.00593 +Epoch [1933/4000] Training [14/16] Loss: 0.00669 +Epoch [1933/4000] Training [15/16] Loss: 0.00501 +Epoch [1933/4000] Training [16/16] Loss: 0.00478 +Epoch [1933/4000] Training metric {'Train/mean dice_metric': 0.9956780672073364, 'Train/mean miou_metric': 0.9911218881607056, 'Train/mean f1': 0.9914724826812744, 'Train/mean precision': 0.9869266152381897, 'Train/mean recall': 0.9960604906082153, 'Train/mean hd95_metric': 1.0045182704925537} +Epoch [1933/4000] Validation [1/4] Loss: 0.24516 focal_loss 0.18375 dice_loss 0.06142 +Epoch [1933/4000] Validation [2/4] Loss: 0.91026 focal_loss 0.65899 dice_loss 0.25127 +Epoch [1933/4000] Validation [3/4] Loss: 0.31880 focal_loss 0.21843 dice_loss 0.10038 +Epoch [1933/4000] Validation [4/4] Loss: 0.23521 focal_loss 0.13714 dice_loss 0.09808 +Epoch [1933/4000] Validation metric {'Val/mean dice_metric': 0.9702838659286499, 'Val/mean miou_metric': 0.95427405834198, 'Val/mean f1': 0.9737433791160583, 'Val/mean precision': 0.9707774519920349, 'Val/mean recall': 0.9767274856567383, 'Val/mean hd95_metric': 5.270389556884766} +Cheakpoint... +Epoch [1933/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702838659286499, 'Val/mean miou_metric': 0.95427405834198, 'Val/mean f1': 0.9737433791160583, 'Val/mean precision': 0.9707774519920349, 'Val/mean recall': 0.9767274856567383, 'Val/mean hd95_metric': 5.270389556884766} +Epoch [1934/4000] Training [1/16] Loss: 0.00530 +Epoch [1934/4000] Training [2/16] Loss: 0.00773 +Epoch [1934/4000] Training [3/16] Loss: 0.00564 +Epoch [1934/4000] Training [4/16] Loss: 0.00517 +Epoch [1934/4000] Training [5/16] Loss: 0.00454 +Epoch [1934/4000] Training [6/16] Loss: 0.00597 +Epoch [1934/4000] Training [7/16] Loss: 0.00759 +Epoch [1934/4000] Training [8/16] Loss: 0.00606 +Epoch [1934/4000] Training [9/16] Loss: 0.00642 +Epoch [1934/4000] Training [10/16] Loss: 0.00784 +Epoch [1934/4000] Training [11/16] Loss: 0.00664 +Epoch [1934/4000] Training [12/16] Loss: 0.00505 +Epoch [1934/4000] Training [13/16] Loss: 0.00852 +Epoch [1934/4000] Training [14/16] Loss: 0.00640 +Epoch [1934/4000] Training [15/16] Loss: 0.00621 +Epoch [1934/4000] Training [16/16] Loss: 0.00553 +Epoch [1934/4000] Training metric {'Train/mean dice_metric': 0.9959125518798828, 'Train/mean miou_metric': 0.991590142250061, 'Train/mean f1': 0.9916332364082336, 'Train/mean precision': 0.9870945811271667, 'Train/mean recall': 0.9962138533592224, 'Train/mean hd95_metric': 1.0045061111450195} +Epoch [1934/4000] Validation [1/4] Loss: 0.30044 focal_loss 0.23172 dice_loss 0.06872 +Epoch [1934/4000] Validation [2/4] Loss: 0.60438 focal_loss 0.41117 dice_loss 0.19321 +Epoch [1934/4000] Validation [3/4] Loss: 0.19230 focal_loss 0.12601 dice_loss 0.06630 +Epoch [1934/4000] Validation [4/4] Loss: 0.23236 focal_loss 0.12461 dice_loss 0.10775 +Epoch [1934/4000] Validation metric {'Val/mean dice_metric': 0.9716556668281555, 'Val/mean miou_metric': 0.9552688598632812, 'Val/mean f1': 0.974330723285675, 'Val/mean precision': 0.9717837572097778, 'Val/mean recall': 0.976891040802002, 'Val/mean hd95_metric': 5.199459075927734} +Cheakpoint... +Epoch [1934/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716556668281555, 'Val/mean miou_metric': 0.9552688598632812, 'Val/mean f1': 0.974330723285675, 'Val/mean precision': 0.9717837572097778, 'Val/mean recall': 0.976891040802002, 'Val/mean hd95_metric': 5.199459075927734} +Epoch [1935/4000] Training [1/16] Loss: 0.00799 +Epoch [1935/4000] Training [2/16] Loss: 0.00470 +Epoch [1935/4000] Training [3/16] Loss: 0.00552 +Epoch [1935/4000] Training [4/16] Loss: 0.00590 +Epoch [1935/4000] Training [5/16] Loss: 0.00628 +Epoch [1935/4000] Training [6/16] Loss: 0.00632 +Epoch [1935/4000] Training [7/16] Loss: 0.00548 +Epoch [1935/4000] Training [8/16] Loss: 0.00517 +Epoch [1935/4000] Training [9/16] Loss: 0.00539 +Epoch [1935/4000] Training [10/16] Loss: 0.00571 +Epoch [1935/4000] Training [11/16] Loss: 0.00609 +Epoch [1935/4000] Training [12/16] Loss: 0.00510 +Epoch [1935/4000] Training [13/16] Loss: 0.00544 +Epoch [1935/4000] Training [14/16] Loss: 0.00727 +Epoch [1935/4000] Training [15/16] Loss: 0.00600 +Epoch [1935/4000] Training [16/16] Loss: 0.00588 +Epoch [1935/4000] Training metric {'Train/mean dice_metric': 0.9958974123001099, 'Train/mean miou_metric': 0.9915671348571777, 'Train/mean f1': 0.9915690422058105, 'Train/mean precision': 0.9869245886802673, 'Train/mean recall': 0.9962574243545532, 'Train/mean hd95_metric': 1.009401798248291} +Epoch [1935/4000] Validation [1/4] Loss: 0.26358 focal_loss 0.19795 dice_loss 0.06563 +Epoch [1935/4000] Validation [2/4] Loss: 0.62202 focal_loss 0.42217 dice_loss 0.19985 +Epoch [1935/4000] Validation [3/4] Loss: 0.32700 focal_loss 0.23421 dice_loss 0.09279 +Epoch [1935/4000] Validation [4/4] Loss: 0.27223 focal_loss 0.16980 dice_loss 0.10244 +Epoch [1935/4000] Validation metric {'Val/mean dice_metric': 0.9706795811653137, 'Val/mean miou_metric': 0.9544571042060852, 'Val/mean f1': 0.9734377861022949, 'Val/mean precision': 0.9712885618209839, 'Val/mean recall': 0.9755966067314148, 'Val/mean hd95_metric': 5.731146335601807} +Cheakpoint... +Epoch [1935/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706795811653137, 'Val/mean miou_metric': 0.9544571042060852, 'Val/mean f1': 0.9734377861022949, 'Val/mean precision': 0.9712885618209839, 'Val/mean recall': 0.9755966067314148, 'Val/mean hd95_metric': 5.731146335601807} +Epoch [1936/4000] Training [1/16] Loss: 0.00764 +Epoch [1936/4000] Training [2/16] Loss: 0.00660 +Epoch [1936/4000] Training [3/16] Loss: 0.00511 +Epoch [1936/4000] Training [4/16] Loss: 0.01457 +Epoch [1936/4000] Training [5/16] Loss: 0.00669 +Epoch [1936/4000] Training [6/16] Loss: 0.00625 +Epoch [1936/4000] Training [7/16] Loss: 0.00553 +Epoch [1936/4000] Training [8/16] Loss: 0.00508 +Epoch [1936/4000] Training [9/16] Loss: 0.00533 +Epoch [1936/4000] Training [10/16] Loss: 0.00754 +Epoch [1936/4000] Training [11/16] Loss: 0.00612 +Epoch [1936/4000] Training [12/16] Loss: 0.00569 +Epoch [1936/4000] Training [13/16] Loss: 0.00561 +Epoch [1936/4000] Training [14/16] Loss: 0.00560 +Epoch [1936/4000] Training [15/16] Loss: 0.00689 +Epoch [1936/4000] Training [16/16] Loss: 0.00813 +Epoch [1936/4000] Training metric {'Train/mean dice_metric': 0.9954326152801514, 'Train/mean miou_metric': 0.9906610250473022, 'Train/mean f1': 0.9911670684814453, 'Train/mean precision': 0.9867691993713379, 'Train/mean recall': 0.9956042766571045, 'Train/mean hd95_metric': 1.1935222148895264} +Epoch [1936/4000] Validation [1/4] Loss: 0.29991 focal_loss 0.23351 dice_loss 0.06639 +Epoch [1936/4000] Validation [2/4] Loss: 0.64686 focal_loss 0.44905 dice_loss 0.19781 +Epoch [1936/4000] Validation [3/4] Loss: 0.29895 focal_loss 0.20353 dice_loss 0.09541 +Epoch [1936/4000] Validation [4/4] Loss: 0.23209 focal_loss 0.13905 dice_loss 0.09304 +Epoch [1936/4000] Validation metric {'Val/mean dice_metric': 0.9694707989692688, 'Val/mean miou_metric': 0.9528011083602905, 'Val/mean f1': 0.9729264974594116, 'Val/mean precision': 0.9714658856391907, 'Val/mean recall': 0.9743912816047668, 'Val/mean hd95_metric': 6.187016010284424} +Cheakpoint... +Epoch [1936/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9694707989692688, 'Val/mean miou_metric': 0.9528011083602905, 'Val/mean f1': 0.9729264974594116, 'Val/mean precision': 0.9714658856391907, 'Val/mean recall': 0.9743912816047668, 'Val/mean hd95_metric': 6.187016010284424} +Epoch [1937/4000] Training [1/16] Loss: 0.00599 +Epoch [1937/4000] Training [2/16] Loss: 0.00886 +Epoch [1937/4000] Training [3/16] Loss: 0.00541 +Epoch [1937/4000] Training [4/16] Loss: 0.00584 +Epoch [1937/4000] Training [5/16] Loss: 0.01011 +Epoch [1937/4000] Training [6/16] Loss: 0.00705 +Epoch [1937/4000] Training [7/16] Loss: 0.00814 +Epoch [1937/4000] Training [8/16] Loss: 0.00679 +Epoch [1937/4000] Training [9/16] Loss: 0.00823 +Epoch [1937/4000] Training [10/16] Loss: 0.00571 +Epoch [1937/4000] Training [11/16] Loss: 0.00615 +Epoch [1937/4000] Training [12/16] Loss: 0.00510 +Epoch [1937/4000] Training [13/16] Loss: 0.00655 +Epoch [1937/4000] Training [14/16] Loss: 0.00822 +Epoch [1937/4000] Training [15/16] Loss: 0.00692 +Epoch [1937/4000] Training [16/16] Loss: 0.00782 +Epoch [1937/4000] Training metric {'Train/mean dice_metric': 0.9953387975692749, 'Train/mean miou_metric': 0.990471363067627, 'Train/mean f1': 0.9912311434745789, 'Train/mean precision': 0.9865050911903381, 'Train/mean recall': 0.9960026741027832, 'Train/mean hd95_metric': 1.0377366542816162} +Epoch [1937/4000] Validation [1/4] Loss: 0.23754 focal_loss 0.17505 dice_loss 0.06249 +Epoch [1937/4000] Validation [2/4] Loss: 0.61380 focal_loss 0.42327 dice_loss 0.19053 +Epoch [1937/4000] Validation [3/4] Loss: 0.31861 focal_loss 0.22804 dice_loss 0.09058 +Epoch [1937/4000] Validation [4/4] Loss: 0.21050 focal_loss 0.12490 dice_loss 0.08560 +Epoch [1937/4000] Validation metric {'Val/mean dice_metric': 0.9691429138183594, 'Val/mean miou_metric': 0.9524469375610352, 'Val/mean f1': 0.9732303619384766, 'Val/mean precision': 0.9709595441818237, 'Val/mean recall': 0.9755118489265442, 'Val/mean hd95_metric': 6.112635135650635} +Cheakpoint... +Epoch [1937/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691429138183594, 'Val/mean miou_metric': 0.9524469375610352, 'Val/mean f1': 0.9732303619384766, 'Val/mean precision': 0.9709595441818237, 'Val/mean recall': 0.9755118489265442, 'Val/mean hd95_metric': 6.112635135650635} +Epoch [1938/4000] Training [1/16] Loss: 0.00763 +Epoch [1938/4000] Training [2/16] Loss: 0.00566 +Epoch [1938/4000] Training [3/16] Loss: 0.00936 +Epoch [1938/4000] Training [4/16] Loss: 0.00615 +Epoch [1938/4000] Training [5/16] Loss: 0.00899 +Epoch [1938/4000] Training [6/16] Loss: 0.00587 +Epoch [1938/4000] Training [7/16] Loss: 0.00499 +Epoch [1938/4000] Training [8/16] Loss: 0.00820 +Epoch [1938/4000] Training [9/16] Loss: 0.00588 +Epoch [1938/4000] Training [10/16] Loss: 0.00522 +Epoch [1938/4000] Training [11/16] Loss: 0.01280 +Epoch [1938/4000] Training [12/16] Loss: 0.00772 +Epoch [1938/4000] Training [13/16] Loss: 0.00696 +Epoch [1938/4000] Training [14/16] Loss: 0.00758 +Epoch [1938/4000] Training [15/16] Loss: 0.00807 +Epoch [1938/4000] Training [16/16] Loss: 0.00588 +Epoch [1938/4000] Training metric {'Train/mean dice_metric': 0.995445966720581, 'Train/mean miou_metric': 0.9906810522079468, 'Train/mean f1': 0.9913867712020874, 'Train/mean precision': 0.9868762493133545, 'Train/mean recall': 0.9959386587142944, 'Train/mean hd95_metric': 1.0281039476394653} +Epoch [1938/4000] Validation [1/4] Loss: 0.25799 focal_loss 0.19819 dice_loss 0.05980 +Epoch [1938/4000] Validation [2/4] Loss: 0.58747 focal_loss 0.39242 dice_loss 0.19505 +Epoch [1938/4000] Validation [3/4] Loss: 0.30601 focal_loss 0.21407 dice_loss 0.09194 +Epoch [1938/4000] Validation [4/4] Loss: 0.25380 focal_loss 0.15849 dice_loss 0.09531 +Epoch [1938/4000] Validation metric {'Val/mean dice_metric': 0.97040855884552, 'Val/mean miou_metric': 0.9536981582641602, 'Val/mean f1': 0.9733968377113342, 'Val/mean precision': 0.971590518951416, 'Val/mean recall': 0.9752098917961121, 'Val/mean hd95_metric': 5.706049919128418} +Cheakpoint... +Epoch [1938/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97040855884552, 'Val/mean miou_metric': 0.9536981582641602, 'Val/mean f1': 0.9733968377113342, 'Val/mean precision': 0.971590518951416, 'Val/mean recall': 0.9752098917961121, 'Val/mean hd95_metric': 5.706049919128418} +Epoch [1939/4000] Training [1/16] Loss: 0.00768 +Epoch [1939/4000] Training [2/16] Loss: 0.00867 +Epoch [1939/4000] Training [3/16] Loss: 0.00625 +Epoch [1939/4000] Training [4/16] Loss: 0.00511 +Epoch [1939/4000] Training [5/16] Loss: 0.00679 +Epoch [1939/4000] Training [6/16] Loss: 0.00469 +Epoch [1939/4000] Training [7/16] Loss: 0.00667 +Epoch [1939/4000] Training [8/16] Loss: 0.00624 +Epoch [1939/4000] Training [9/16] Loss: 0.00600 +Epoch [1939/4000] Training [10/16] Loss: 0.00539 +Epoch [1939/4000] Training [11/16] Loss: 0.00714 +Epoch [1939/4000] Training [12/16] Loss: 0.00599 +Epoch [1939/4000] Training [13/16] Loss: 0.00932 +Epoch [1939/4000] Training [14/16] Loss: 0.00596 +Epoch [1939/4000] Training [15/16] Loss: 0.00697 +Epoch [1939/4000] Training [16/16] Loss: 0.00642 +Epoch [1939/4000] Training metric {'Train/mean dice_metric': 0.9955293536186218, 'Train/mean miou_metric': 0.9908267259597778, 'Train/mean f1': 0.9910693168640137, 'Train/mean precision': 0.9863103032112122, 'Train/mean recall': 0.9958744645118713, 'Train/mean hd95_metric': 1.0151249170303345} +Epoch [1939/4000] Validation [1/4] Loss: 0.27727 focal_loss 0.21304 dice_loss 0.06423 +Epoch [1939/4000] Validation [2/4] Loss: 0.47996 focal_loss 0.30778 dice_loss 0.17218 +Epoch [1939/4000] Validation [3/4] Loss: 0.30650 focal_loss 0.21673 dice_loss 0.08977 +Epoch [1939/4000] Validation [4/4] Loss: 0.23970 focal_loss 0.15049 dice_loss 0.08921 +Epoch [1939/4000] Validation metric {'Val/mean dice_metric': 0.9705225825309753, 'Val/mean miou_metric': 0.9540818333625793, 'Val/mean f1': 0.973914384841919, 'Val/mean precision': 0.972217857837677, 'Val/mean recall': 0.9756166934967041, 'Val/mean hd95_metric': 5.495377063751221} +Cheakpoint... +Epoch [1939/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705225825309753, 'Val/mean miou_metric': 0.9540818333625793, 'Val/mean f1': 0.973914384841919, 'Val/mean precision': 0.972217857837677, 'Val/mean recall': 0.9756166934967041, 'Val/mean hd95_metric': 5.495377063751221} +Epoch [1940/4000] Training [1/16] Loss: 0.00503 +Epoch [1940/4000] Training [2/16] Loss: 0.00768 +Epoch [1940/4000] Training [3/16] Loss: 0.00723 +Epoch [1940/4000] Training [4/16] Loss: 0.00578 +Epoch [1940/4000] Training [5/16] Loss: 0.00663 +Epoch [1940/4000] Training [6/16] Loss: 0.00629 +Epoch [1940/4000] Training [7/16] Loss: 0.00622 +Epoch [1940/4000] Training [8/16] Loss: 0.00704 +Epoch [1940/4000] Training [9/16] Loss: 0.01040 +Epoch [1940/4000] Training [10/16] Loss: 0.00627 +Epoch [1940/4000] Training [11/16] Loss: 0.00730 +Epoch [1940/4000] Training [12/16] Loss: 0.00719 +Epoch [1940/4000] Training [13/16] Loss: 0.00540 +Epoch [1940/4000] Training [14/16] Loss: 0.00527 +Epoch [1940/4000] Training [15/16] Loss: 0.00815 +Epoch [1940/4000] Training [16/16] Loss: 0.00578 +Epoch [1940/4000] Training metric {'Train/mean dice_metric': 0.9956943392753601, 'Train/mean miou_metric': 0.9911497235298157, 'Train/mean f1': 0.9907144904136658, 'Train/mean precision': 0.9855570793151855, 'Train/mean recall': 0.9959262013435364, 'Train/mean hd95_metric': 1.0169048309326172} +Epoch [1940/4000] Validation [1/4] Loss: 0.37883 focal_loss 0.29733 dice_loss 0.08150 +Epoch [1940/4000] Validation [2/4] Loss: 0.53900 focal_loss 0.34822 dice_loss 0.19078 +Epoch [1940/4000] Validation [3/4] Loss: 0.16915 focal_loss 0.11104 dice_loss 0.05811 +Epoch [1940/4000] Validation [4/4] Loss: 0.24930 focal_loss 0.15213 dice_loss 0.09717 +Epoch [1940/4000] Validation metric {'Val/mean dice_metric': 0.9691165685653687, 'Val/mean miou_metric': 0.9524573087692261, 'Val/mean f1': 0.9721729159355164, 'Val/mean precision': 0.9723789095878601, 'Val/mean recall': 0.9719669222831726, 'Val/mean hd95_metric': 5.1383957862854} +Cheakpoint... +Epoch [1940/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691165685653687, 'Val/mean miou_metric': 0.9524573087692261, 'Val/mean f1': 0.9721729159355164, 'Val/mean precision': 0.9723789095878601, 'Val/mean recall': 0.9719669222831726, 'Val/mean hd95_metric': 5.1383957862854} +Epoch [1941/4000] Training [1/16] Loss: 0.00644 +Epoch [1941/4000] Training [2/16] Loss: 0.00502 +Epoch [1941/4000] Training [3/16] Loss: 0.00499 +Epoch [1941/4000] Training [4/16] Loss: 0.00624 +Epoch [1941/4000] Training [5/16] Loss: 0.00744 +Epoch [1941/4000] Training [6/16] Loss: 0.00696 +Epoch [1941/4000] Training [7/16] Loss: 0.00479 +Epoch [1941/4000] Training [8/16] Loss: 0.00614 +Epoch [1941/4000] Training [9/16] Loss: 0.00584 +Epoch [1941/4000] Training [10/16] Loss: 0.00617 +Epoch [1941/4000] Training [11/16] Loss: 0.00509 +Epoch [1941/4000] Training [12/16] Loss: 0.00622 +Epoch [1941/4000] Training [13/16] Loss: 0.00576 +Epoch [1941/4000] Training [14/16] Loss: 0.00589 +Epoch [1941/4000] Training [15/16] Loss: 0.00515 +Epoch [1941/4000] Training [16/16] Loss: 0.00533 +Epoch [1941/4000] Training metric {'Train/mean dice_metric': 0.9962120056152344, 'Train/mean miou_metric': 0.9921383857727051, 'Train/mean f1': 0.9908490180969238, 'Train/mean precision': 0.9853992462158203, 'Train/mean recall': 0.9963594079017639, 'Train/mean hd95_metric': 1.0037099123001099} +Epoch [1941/4000] Validation [1/4] Loss: 0.29528 focal_loss 0.21272 dice_loss 0.08255 +Epoch [1941/4000] Validation [2/4] Loss: 0.68304 focal_loss 0.47738 dice_loss 0.20566 +Epoch [1941/4000] Validation [3/4] Loss: 0.33398 focal_loss 0.23922 dice_loss 0.09476 +Epoch [1941/4000] Validation [4/4] Loss: 0.25662 focal_loss 0.16300 dice_loss 0.09362 +Epoch [1941/4000] Validation metric {'Val/mean dice_metric': 0.9707239270210266, 'Val/mean miou_metric': 0.954503059387207, 'Val/mean f1': 0.9724249839782715, 'Val/mean precision': 0.9714739322662354, 'Val/mean recall': 0.97337806224823, 'Val/mean hd95_metric': 5.397699356079102} +Cheakpoint... +Epoch [1941/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707239270210266, 'Val/mean miou_metric': 0.954503059387207, 'Val/mean f1': 0.9724249839782715, 'Val/mean precision': 0.9714739322662354, 'Val/mean recall': 0.97337806224823, 'Val/mean hd95_metric': 5.397699356079102} +Epoch [1942/4000] Training [1/16] Loss: 0.00673 +Epoch [1942/4000] Training [2/16] Loss: 0.00465 +Epoch [1942/4000] Training [3/16] Loss: 0.00656 +Epoch [1942/4000] Training [4/16] Loss: 0.00557 +Epoch [1942/4000] Training [5/16] Loss: 0.00490 +Epoch [1942/4000] Training [6/16] Loss: 0.01017 +Epoch [1942/4000] Training [7/16] Loss: 0.00606 +Epoch [1942/4000] Training [8/16] Loss: 0.00583 +Epoch [1942/4000] Training [9/16] Loss: 0.00524 +Epoch [1942/4000] Training [10/16] Loss: 0.00643 +Epoch [1942/4000] Training [11/16] Loss: 0.00548 +Epoch [1942/4000] Training [12/16] Loss: 0.00566 +Epoch [1942/4000] Training [13/16] Loss: 0.00700 +Epoch [1942/4000] Training [14/16] Loss: 0.00646 +Epoch [1942/4000] Training [15/16] Loss: 0.00548 +Epoch [1942/4000] Training [16/16] Loss: 0.00667 +Epoch [1942/4000] Training metric {'Train/mean dice_metric': 0.9960877299308777, 'Train/mean miou_metric': 0.9919100999832153, 'Train/mean f1': 0.9911022782325745, 'Train/mean precision': 0.9859300851821899, 'Train/mean recall': 0.9963290691375732, 'Train/mean hd95_metric': 1.0153546333312988} +Epoch [1942/4000] Validation [1/4] Loss: 0.25657 focal_loss 0.19135 dice_loss 0.06522 +Epoch [1942/4000] Validation [2/4] Loss: 0.72161 focal_loss 0.49059 dice_loss 0.23101 +Epoch [1942/4000] Validation [3/4] Loss: 0.18439 focal_loss 0.12602 dice_loss 0.05838 +Epoch [1942/4000] Validation [4/4] Loss: 0.28304 focal_loss 0.18219 dice_loss 0.10085 +Epoch [1942/4000] Validation metric {'Val/mean dice_metric': 0.9726858139038086, 'Val/mean miou_metric': 0.9563859701156616, 'Val/mean f1': 0.9746768474578857, 'Val/mean precision': 0.9727655053138733, 'Val/mean recall': 0.9765955209732056, 'Val/mean hd95_metric': 5.032827854156494} +Cheakpoint... +Epoch [1942/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726858139038086, 'Val/mean miou_metric': 0.9563859701156616, 'Val/mean f1': 0.9746768474578857, 'Val/mean precision': 0.9727655053138733, 'Val/mean recall': 0.9765955209732056, 'Val/mean hd95_metric': 5.032827854156494} +Epoch [1943/4000] Training [1/16] Loss: 0.00528 +Epoch [1943/4000] Training [2/16] Loss: 0.00584 +Epoch [1943/4000] Training [3/16] Loss: 0.00591 +Epoch [1943/4000] Training [4/16] Loss: 0.00561 +Epoch [1943/4000] Training [5/16] Loss: 0.00817 +Epoch [1943/4000] Training [6/16] Loss: 0.00415 +Epoch [1943/4000] Training [7/16] Loss: 0.00736 +Epoch [1943/4000] Training [8/16] Loss: 0.00549 +Epoch [1943/4000] Training [9/16] Loss: 0.00456 +Epoch [1943/4000] Training [10/16] Loss: 0.00621 +Epoch [1943/4000] Training [11/16] Loss: 0.00903 +Epoch [1943/4000] Training [12/16] Loss: 0.00547 +Epoch [1943/4000] Training [13/16] Loss: 0.00532 +Epoch [1943/4000] Training [14/16] Loss: 0.00606 +Epoch [1943/4000] Training [15/16] Loss: 0.00615 +Epoch [1943/4000] Training [16/16] Loss: 0.00699 +Epoch [1943/4000] Training metric {'Train/mean dice_metric': 0.9959268569946289, 'Train/mean miou_metric': 0.9916115999221802, 'Train/mean f1': 0.9916196465492249, 'Train/mean precision': 0.9870591163635254, 'Train/mean recall': 0.9962224960327148, 'Train/mean hd95_metric': 1.003697156906128} +Epoch [1943/4000] Validation [1/4] Loss: 0.23875 focal_loss 0.17899 dice_loss 0.05976 +Epoch [1943/4000] Validation [2/4] Loss: 0.91742 focal_loss 0.64966 dice_loss 0.26776 +Epoch [1943/4000] Validation [3/4] Loss: 0.18525 focal_loss 0.12388 dice_loss 0.06137 +Epoch [1943/4000] Validation [4/4] Loss: 0.23702 focal_loss 0.14832 dice_loss 0.08870 +Epoch [1943/4000] Validation metric {'Val/mean dice_metric': 0.9719859957695007, 'Val/mean miou_metric': 0.9557703137397766, 'Val/mean f1': 0.974493682384491, 'Val/mean precision': 0.9714770913124084, 'Val/mean recall': 0.977528989315033, 'Val/mean hd95_metric': 5.663182258605957} +Cheakpoint... +Epoch [1943/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719859957695007, 'Val/mean miou_metric': 0.9557703137397766, 'Val/mean f1': 0.974493682384491, 'Val/mean precision': 0.9714770913124084, 'Val/mean recall': 0.977528989315033, 'Val/mean hd95_metric': 5.663182258605957} +Epoch [1944/4000] Training [1/16] Loss: 0.00588 +Epoch [1944/4000] Training [2/16] Loss: 0.00745 +Epoch [1944/4000] Training [3/16] Loss: 0.00627 +Epoch [1944/4000] Training [4/16] Loss: 0.00556 +Epoch [1944/4000] Training [5/16] Loss: 0.00458 +Epoch [1944/4000] Training [6/16] Loss: 0.00595 +Epoch [1944/4000] Training [7/16] Loss: 0.00648 +Epoch [1944/4000] Training [8/16] Loss: 0.00682 +Epoch [1944/4000] Training [9/16] Loss: 0.00469 +Epoch [1944/4000] Training [10/16] Loss: 0.00597 +Epoch [1944/4000] Training [11/16] Loss: 0.00726 +Epoch [1944/4000] Training [12/16] Loss: 0.00607 +Epoch [1944/4000] Training [13/16] Loss: 0.00643 +Epoch [1944/4000] Training [14/16] Loss: 0.00630 +Epoch [1944/4000] Training [15/16] Loss: 0.00817 +Epoch [1944/4000] Training [16/16] Loss: 0.00683 +Epoch [1944/4000] Training metric {'Train/mean dice_metric': 0.9956338405609131, 'Train/mean miou_metric': 0.991050124168396, 'Train/mean f1': 0.9915550351142883, 'Train/mean precision': 0.9869734048843384, 'Train/mean recall': 0.9961794018745422, 'Train/mean hd95_metric': 1.0188610553741455} +Epoch [1944/4000] Validation [1/4] Loss: 0.29368 focal_loss 0.22716 dice_loss 0.06653 +Epoch [1944/4000] Validation [2/4] Loss: 0.87960 focal_loss 0.62853 dice_loss 0.25107 +Epoch [1944/4000] Validation [3/4] Loss: 0.33175 focal_loss 0.23892 dice_loss 0.09282 +Epoch [1944/4000] Validation [4/4] Loss: 0.23351 focal_loss 0.14578 dice_loss 0.08773 +Epoch [1944/4000] Validation metric {'Val/mean dice_metric': 0.9727432131767273, 'Val/mean miou_metric': 0.95599764585495, 'Val/mean f1': 0.9743350148200989, 'Val/mean precision': 0.9714521169662476, 'Val/mean recall': 0.9772351384162903, 'Val/mean hd95_metric': 5.5078020095825195} +Cheakpoint... +Epoch [1944/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727432131767273, 'Val/mean miou_metric': 0.95599764585495, 'Val/mean f1': 0.9743350148200989, 'Val/mean precision': 0.9714521169662476, 'Val/mean recall': 0.9772351384162903, 'Val/mean hd95_metric': 5.5078020095825195} +Epoch [1945/4000] Training [1/16] Loss: 0.00479 +Epoch [1945/4000] Training [2/16] Loss: 0.00611 +Epoch [1945/4000] Training [3/16] Loss: 0.00590 +Epoch [1945/4000] Training [4/16] Loss: 0.00618 +Epoch [1945/4000] Training [5/16] Loss: 0.00585 +Epoch [1945/4000] Training [6/16] Loss: 0.00676 +Epoch [1945/4000] Training [7/16] Loss: 0.00576 +Epoch [1945/4000] Training [8/16] Loss: 0.00543 +Epoch [1945/4000] Training [9/16] Loss: 0.00586 +Epoch [1945/4000] Training [10/16] Loss: 0.00654 +Epoch [1945/4000] Training [11/16] Loss: 0.00638 +Epoch [1945/4000] Training [12/16] Loss: 0.00699 +Epoch [1945/4000] Training [13/16] Loss: 0.00598 +Epoch [1945/4000] Training [14/16] Loss: 0.00475 +Epoch [1945/4000] Training [15/16] Loss: 0.00665 +Epoch [1945/4000] Training [16/16] Loss: 0.00668 +Epoch [1945/4000] Training metric {'Train/mean dice_metric': 0.9958929419517517, 'Train/mean miou_metric': 0.9915585517883301, 'Train/mean f1': 0.9916059970855713, 'Train/mean precision': 0.9871572852134705, 'Train/mean recall': 0.9960950016975403, 'Train/mean hd95_metric': 1.0124094486236572} +Epoch [1945/4000] Validation [1/4] Loss: 0.43070 focal_loss 0.34680 dice_loss 0.08389 +Epoch [1945/4000] Validation [2/4] Loss: 0.30955 focal_loss 0.19564 dice_loss 0.11391 +Epoch [1945/4000] Validation [3/4] Loss: 0.18069 focal_loss 0.11978 dice_loss 0.06091 +Epoch [1945/4000] Validation [4/4] Loss: 0.25184 focal_loss 0.15769 dice_loss 0.09415 +Epoch [1945/4000] Validation metric {'Val/mean dice_metric': 0.972694993019104, 'Val/mean miou_metric': 0.9557088613510132, 'Val/mean f1': 0.9741796255111694, 'Val/mean precision': 0.9734882116317749, 'Val/mean recall': 0.9748719334602356, 'Val/mean hd95_metric': 4.928753852844238} +Cheakpoint... +Epoch [1945/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972694993019104, 'Val/mean miou_metric': 0.9557088613510132, 'Val/mean f1': 0.9741796255111694, 'Val/mean precision': 0.9734882116317749, 'Val/mean recall': 0.9748719334602356, 'Val/mean hd95_metric': 4.928753852844238} +Epoch [1946/4000] Training [1/16] Loss: 0.00612 +Epoch [1946/4000] Training [2/16] Loss: 0.00599 +Epoch [1946/4000] Training [3/16] Loss: 0.00514 +Epoch [1946/4000] Training [4/16] Loss: 0.00465 +Epoch [1946/4000] Training [5/16] Loss: 0.00517 +Epoch [1946/4000] Training [6/16] Loss: 0.00624 +Epoch [1946/4000] Training [7/16] Loss: 0.00581 +Epoch [1946/4000] Training [8/16] Loss: 0.00578 +Epoch [1946/4000] Training [9/16] Loss: 0.00566 +Epoch [1946/4000] Training [10/16] Loss: 0.00695 +Epoch [1946/4000] Training [11/16] Loss: 0.00976 +Epoch [1946/4000] Training [12/16] Loss: 0.00597 +Epoch [1946/4000] Training [13/16] Loss: 0.00574 +Epoch [1946/4000] Training [14/16] Loss: 0.00623 +Epoch [1946/4000] Training [15/16] Loss: 0.00671 +Epoch [1946/4000] Training [16/16] Loss: 0.00547 +Epoch [1946/4000] Training metric {'Train/mean dice_metric': 0.995966911315918, 'Train/mean miou_metric': 0.9917078614234924, 'Train/mean f1': 0.9917430877685547, 'Train/mean precision': 0.9871757626533508, 'Train/mean recall': 0.9963529109954834, 'Train/mean hd95_metric': 1.006962776184082} +Epoch [1946/4000] Validation [1/4] Loss: 0.30218 focal_loss 0.23661 dice_loss 0.06557 +Epoch [1946/4000] Validation [2/4] Loss: 0.63162 focal_loss 0.42486 dice_loss 0.20676 +Epoch [1946/4000] Validation [3/4] Loss: 0.18935 focal_loss 0.13207 dice_loss 0.05728 +Epoch [1946/4000] Validation [4/4] Loss: 0.31658 focal_loss 0.20508 dice_loss 0.11150 +Epoch [1946/4000] Validation metric {'Val/mean dice_metric': 0.9725397229194641, 'Val/mean miou_metric': 0.9562274813652039, 'Val/mean f1': 0.9745413064956665, 'Val/mean precision': 0.9712695479393005, 'Val/mean recall': 0.9778351783752441, 'Val/mean hd95_metric': 5.433329105377197} +Cheakpoint... +Epoch [1946/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725397229194641, 'Val/mean miou_metric': 0.9562274813652039, 'Val/mean f1': 0.9745413064956665, 'Val/mean precision': 0.9712695479393005, 'Val/mean recall': 0.9778351783752441, 'Val/mean hd95_metric': 5.433329105377197} +Epoch [1947/4000] Training [1/16] Loss: 0.00462 +Epoch [1947/4000] Training [2/16] Loss: 0.00598 +Epoch [1947/4000] Training [3/16] Loss: 0.00621 +Epoch [1947/4000] Training [4/16] Loss: 0.00606 +Epoch [1947/4000] Training [5/16] Loss: 0.00448 +Epoch [1947/4000] Training [6/16] Loss: 0.00629 +Epoch [1947/4000] Training [7/16] Loss: 0.00806 +Epoch [1947/4000] Training [8/16] Loss: 0.00754 +Epoch [1947/4000] Training [9/16] Loss: 0.00538 +Epoch [1947/4000] Training [10/16] Loss: 0.01056 +Epoch [1947/4000] Training [11/16] Loss: 0.00715 +Epoch [1947/4000] Training [12/16] Loss: 0.00596 +Epoch [1947/4000] Training [13/16] Loss: 0.00831 +Epoch [1947/4000] Training [14/16] Loss: 0.00539 +Epoch [1947/4000] Training [15/16] Loss: 0.00664 +Epoch [1947/4000] Training [16/16] Loss: 0.00725 +Epoch [1947/4000] Training metric {'Train/mean dice_metric': 0.9958056211471558, 'Train/mean miou_metric': 0.9913685321807861, 'Train/mean f1': 0.9913783073425293, 'Train/mean precision': 0.9866438508033752, 'Train/mean recall': 0.9961584806442261, 'Train/mean hd95_metric': 1.0155110359191895} +Epoch [1947/4000] Validation [1/4] Loss: 0.36419 focal_loss 0.28980 dice_loss 0.07439 +Epoch [1947/4000] Validation [2/4] Loss: 0.86219 focal_loss 0.58995 dice_loss 0.27223 +Epoch [1947/4000] Validation [3/4] Loss: 0.34838 focal_loss 0.25116 dice_loss 0.09722 +Epoch [1947/4000] Validation [4/4] Loss: 0.21528 focal_loss 0.12591 dice_loss 0.08937 +Epoch [1947/4000] Validation metric {'Val/mean dice_metric': 0.9714322090148926, 'Val/mean miou_metric': 0.9550652503967285, 'Val/mean f1': 0.9739145040512085, 'Val/mean precision': 0.972091555595398, 'Val/mean recall': 0.9757442474365234, 'Val/mean hd95_metric': 5.26351261138916} +Cheakpoint... +Epoch [1947/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714322090148926, 'Val/mean miou_metric': 0.9550652503967285, 'Val/mean f1': 0.9739145040512085, 'Val/mean precision': 0.972091555595398, 'Val/mean recall': 0.9757442474365234, 'Val/mean hd95_metric': 5.26351261138916} +Epoch [1948/4000] Training [1/16] Loss: 0.00619 +Epoch [1948/4000] Training [2/16] Loss: 0.00830 +Epoch [1948/4000] Training [3/16] Loss: 0.00699 +Epoch [1948/4000] Training [4/16] Loss: 0.00577 +Epoch [1948/4000] Training [5/16] Loss: 0.00503 +Epoch [1948/4000] Training [6/16] Loss: 0.00618 +Epoch [1948/4000] Training [7/16] Loss: 0.00488 +Epoch [1948/4000] Training [8/16] Loss: 0.00700 +Epoch [1948/4000] Training [9/16] Loss: 0.00655 +Epoch [1948/4000] Training [10/16] Loss: 0.00482 +Epoch [1948/4000] Training [11/16] Loss: 0.00723 +Epoch [1948/4000] Training [12/16] Loss: 0.00679 +Epoch [1948/4000] Training [13/16] Loss: 0.00707 +Epoch [1948/4000] Training [14/16] Loss: 0.00642 +Epoch [1948/4000] Training [15/16] Loss: 0.00572 +Epoch [1948/4000] Training [16/16] Loss: 0.00559 +Epoch [1948/4000] Training metric {'Train/mean dice_metric': 0.9958429336547852, 'Train/mean miou_metric': 0.991413950920105, 'Train/mean f1': 0.9906916618347168, 'Train/mean precision': 0.9853321313858032, 'Train/mean recall': 0.9961097836494446, 'Train/mean hd95_metric': 1.0154292583465576} +Epoch [1948/4000] Validation [1/4] Loss: 0.32264 focal_loss 0.25437 dice_loss 0.06827 +Epoch [1948/4000] Validation [2/4] Loss: 0.55812 focal_loss 0.39076 dice_loss 0.16736 +Epoch [1948/4000] Validation [3/4] Loss: 0.16741 focal_loss 0.10823 dice_loss 0.05918 +Epoch [1948/4000] Validation [4/4] Loss: 0.23911 focal_loss 0.15084 dice_loss 0.08827 +Epoch [1948/4000] Validation metric {'Val/mean dice_metric': 0.9724985361099243, 'Val/mean miou_metric': 0.9557090997695923, 'Val/mean f1': 0.9741429686546326, 'Val/mean precision': 0.9705317616462708, 'Val/mean recall': 0.9777810573577881, 'Val/mean hd95_metric': 5.287496089935303} +Cheakpoint... +Epoch [1948/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724985361099243, 'Val/mean miou_metric': 0.9557090997695923, 'Val/mean f1': 0.9741429686546326, 'Val/mean precision': 0.9705317616462708, 'Val/mean recall': 0.9777810573577881, 'Val/mean hd95_metric': 5.287496089935303} +Epoch [1949/4000] Training [1/16] Loss: 0.00589 +Epoch [1949/4000] Training [2/16] Loss: 0.00550 +Epoch [1949/4000] Training [3/16] Loss: 0.00705 +Epoch [1949/4000] Training [4/16] Loss: 0.00628 +Epoch [1949/4000] Training [5/16] Loss: 0.00535 +Epoch [1949/4000] Training [6/16] Loss: 0.00510 +Epoch [1949/4000] Training [7/16] Loss: 0.00892 +Epoch [1949/4000] Training [8/16] Loss: 0.00537 +Epoch [1949/4000] Training [9/16] Loss: 0.00722 +Epoch [1949/4000] Training [10/16] Loss: 0.00430 +Epoch [1949/4000] Training [11/16] Loss: 0.00685 +Epoch [1949/4000] Training [12/16] Loss: 0.00669 +Epoch [1949/4000] Training [13/16] Loss: 0.00676 +Epoch [1949/4000] Training [14/16] Loss: 0.00687 +Epoch [1949/4000] Training [15/16] Loss: 0.00764 +Epoch [1949/4000] Training [16/16] Loss: 0.00485 +Epoch [1949/4000] Training metric {'Train/mean dice_metric': 0.9960299730300903, 'Train/mean miou_metric': 0.9918238520622253, 'Train/mean f1': 0.9916636943817139, 'Train/mean precision': 0.9869580268859863, 'Train/mean recall': 0.9964144825935364, 'Train/mean hd95_metric': 1.013160228729248} +Epoch [1949/4000] Validation [1/4] Loss: 0.30786 focal_loss 0.23697 dice_loss 0.07089 +Epoch [1949/4000] Validation [2/4] Loss: 0.46317 focal_loss 0.26140 dice_loss 0.20177 +Epoch [1949/4000] Validation [3/4] Loss: 0.37474 focal_loss 0.28089 dice_loss 0.09385 +Epoch [1949/4000] Validation [4/4] Loss: 0.24365 focal_loss 0.15160 dice_loss 0.09206 +Epoch [1949/4000] Validation metric {'Val/mean dice_metric': 0.9712945818901062, 'Val/mean miou_metric': 0.9539188146591187, 'Val/mean f1': 0.973120927810669, 'Val/mean precision': 0.9698114991188049, 'Val/mean recall': 0.9764530658721924, 'Val/mean hd95_metric': 5.96198034286499} +Cheakpoint... +Epoch [1949/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712945818901062, 'Val/mean miou_metric': 0.9539188146591187, 'Val/mean f1': 0.973120927810669, 'Val/mean precision': 0.9698114991188049, 'Val/mean recall': 0.9764530658721924, 'Val/mean hd95_metric': 5.96198034286499} +Epoch [1950/4000] Training [1/16] Loss: 0.00661 +Epoch [1950/4000] Training [2/16] Loss: 0.00477 +Epoch [1950/4000] Training [3/16] Loss: 0.00740 +Epoch [1950/4000] Training [4/16] Loss: 0.00610 +Epoch [1950/4000] Training [5/16] Loss: 0.00500 +Epoch [1950/4000] Training [6/16] Loss: 0.00697 +Epoch [1950/4000] Training [7/16] Loss: 0.00635 +Epoch [1950/4000] Training [8/16] Loss: 0.00646 +Epoch [1950/4000] Training [9/16] Loss: 0.00631 +Epoch [1950/4000] Training [10/16] Loss: 0.00544 +Epoch [1950/4000] Training [11/16] Loss: 0.01145 +Epoch [1950/4000] Training [12/16] Loss: 0.00777 +Epoch [1950/4000] Training [13/16] Loss: 0.00946 +Epoch [1950/4000] Training [14/16] Loss: 0.00808 +Epoch [1950/4000] Training [15/16] Loss: 0.00553 +Epoch [1950/4000] Training [16/16] Loss: 0.00626 +Epoch [1950/4000] Training metric {'Train/mean dice_metric': 0.9957171678543091, 'Train/mean miou_metric': 0.9912031292915344, 'Train/mean f1': 0.9914318323135376, 'Train/mean precision': 0.9867735505104065, 'Train/mean recall': 0.9961342811584473, 'Train/mean hd95_metric': 1.0218943357467651} +Epoch [1950/4000] Validation [1/4] Loss: 0.41696 focal_loss 0.33421 dice_loss 0.08275 +Epoch [1950/4000] Validation [2/4] Loss: 0.30076 focal_loss 0.18088 dice_loss 0.11988 +Epoch [1950/4000] Validation [3/4] Loss: 0.18884 focal_loss 0.12991 dice_loss 0.05892 +Epoch [1950/4000] Validation [4/4] Loss: 0.24033 focal_loss 0.14202 dice_loss 0.09831 +Epoch [1950/4000] Validation metric {'Val/mean dice_metric': 0.9732791781425476, 'Val/mean miou_metric': 0.9561769366264343, 'Val/mean f1': 0.9739030599594116, 'Val/mean precision': 0.9714198112487793, 'Val/mean recall': 0.9763989448547363, 'Val/mean hd95_metric': 5.22467565536499} +Cheakpoint... +Epoch [1950/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732791781425476, 'Val/mean miou_metric': 0.9561769366264343, 'Val/mean f1': 0.9739030599594116, 'Val/mean precision': 0.9714198112487793, 'Val/mean recall': 0.9763989448547363, 'Val/mean hd95_metric': 5.22467565536499} +Epoch [1951/4000] Training [1/16] Loss: 0.00831 +Epoch [1951/4000] Training [2/16] Loss: 0.00690 +Epoch [1951/4000] Training [3/16] Loss: 0.00437 +Epoch [1951/4000] Training [4/16] Loss: 0.00541 +Epoch [1951/4000] Training [5/16] Loss: 0.00693 +Epoch [1951/4000] Training [6/16] Loss: 0.00509 +Epoch [1951/4000] Training [7/16] Loss: 0.00648 +Epoch [1951/4000] Training [8/16] Loss: 0.00546 +Epoch [1951/4000] Training [9/16] Loss: 0.00592 +Epoch [1951/4000] Training [10/16] Loss: 0.00693 +Epoch [1951/4000] Training [11/16] Loss: 0.00493 +Epoch [1951/4000] Training [12/16] Loss: 0.00681 +Epoch [1951/4000] Training [13/16] Loss: 0.00598 +Epoch [1951/4000] Training [14/16] Loss: 0.00751 +Epoch [1951/4000] Training [15/16] Loss: 0.00524 +Epoch [1951/4000] Training [16/16] Loss: 0.00600 +Epoch [1951/4000] Training metric {'Train/mean dice_metric': 0.9959272146224976, 'Train/mean miou_metric': 0.9916204214096069, 'Train/mean f1': 0.9915830492973328, 'Train/mean precision': 0.9870855212211609, 'Train/mean recall': 0.9961217641830444, 'Train/mean hd95_metric': 1.000473976135254} +Epoch [1951/4000] Validation [1/4] Loss: 0.29705 focal_loss 0.22318 dice_loss 0.07387 +Epoch [1951/4000] Validation [2/4] Loss: 0.56135 focal_loss 0.36608 dice_loss 0.19527 +Epoch [1951/4000] Validation [3/4] Loss: 0.40139 focal_loss 0.29297 dice_loss 0.10842 +Epoch [1951/4000] Validation [4/4] Loss: 0.18663 focal_loss 0.11220 dice_loss 0.07444 +Epoch [1951/4000] Validation metric {'Val/mean dice_metric': 0.9716099500656128, 'Val/mean miou_metric': 0.9554519653320312, 'Val/mean f1': 0.9738202691078186, 'Val/mean precision': 0.9710590839385986, 'Val/mean recall': 0.9765971302986145, 'Val/mean hd95_metric': 6.17171049118042} +Cheakpoint... +Epoch [1951/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716099500656128, 'Val/mean miou_metric': 0.9554519653320312, 'Val/mean f1': 0.9738202691078186, 'Val/mean precision': 0.9710590839385986, 'Val/mean recall': 0.9765971302986145, 'Val/mean hd95_metric': 6.17171049118042} +Epoch [1952/4000] Training [1/16] Loss: 0.00526 +Epoch [1952/4000] Training [2/16] Loss: 0.00687 +Epoch [1952/4000] Training [3/16] Loss: 0.00619 +Epoch [1952/4000] Training [4/16] Loss: 0.00688 +Epoch [1952/4000] Training [5/16] Loss: 0.00532 +Epoch [1952/4000] Training [6/16] Loss: 0.00583 +Epoch [1952/4000] Training [7/16] Loss: 0.00530 +Epoch [1952/4000] Training [8/16] Loss: 0.00754 +Epoch [1952/4000] Training [9/16] Loss: 0.00604 +Epoch [1952/4000] Training [10/16] Loss: 0.00741 +Epoch [1952/4000] Training [11/16] Loss: 0.00817 +Epoch [1952/4000] Training [12/16] Loss: 0.00575 +Epoch [1952/4000] Training [13/16] Loss: 0.00732 +Epoch [1952/4000] Training [14/16] Loss: 0.00705 +Epoch [1952/4000] Training [15/16] Loss: 0.00534 +Epoch [1952/4000] Training [16/16] Loss: 0.00541 +Epoch [1952/4000] Training metric {'Train/mean dice_metric': 0.9956701397895813, 'Train/mean miou_metric': 0.9911180138587952, 'Train/mean f1': 0.9915268421173096, 'Train/mean precision': 0.9869884848594666, 'Train/mean recall': 0.9961071610450745, 'Train/mean hd95_metric': 1.066758394241333} +Epoch [1952/4000] Validation [1/4] Loss: 0.31701 focal_loss 0.24635 dice_loss 0.07066 +Epoch [1952/4000] Validation [2/4] Loss: 0.76614 focal_loss 0.50038 dice_loss 0.26576 +Epoch [1952/4000] Validation [3/4] Loss: 0.33345 focal_loss 0.24469 dice_loss 0.08876 +Epoch [1952/4000] Validation [4/4] Loss: 0.22742 focal_loss 0.13761 dice_loss 0.08981 +Epoch [1952/4000] Validation metric {'Val/mean dice_metric': 0.9714913368225098, 'Val/mean miou_metric': 0.954798698425293, 'Val/mean f1': 0.9739043116569519, 'Val/mean precision': 0.972350537776947, 'Val/mean recall': 0.9754630923271179, 'Val/mean hd95_metric': 5.424519062042236} +Cheakpoint... +Epoch [1952/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714913368225098, 'Val/mean miou_metric': 0.954798698425293, 'Val/mean f1': 0.9739043116569519, 'Val/mean precision': 0.972350537776947, 'Val/mean recall': 0.9754630923271179, 'Val/mean hd95_metric': 5.424519062042236} +Epoch [1953/4000] Training [1/16] Loss: 0.00611 +Epoch [1953/4000] Training [2/16] Loss: 0.00616 +Epoch [1953/4000] Training [3/16] Loss: 0.00473 +Epoch [1953/4000] Training [4/16] Loss: 0.00640 +Epoch [1953/4000] Training [5/16] Loss: 0.00473 +Epoch [1953/4000] Training [6/16] Loss: 0.00706 +Epoch [1953/4000] Training [7/16] Loss: 0.00534 +Epoch [1953/4000] Training [8/16] Loss: 0.00778 +Epoch [1953/4000] Training [9/16] Loss: 0.00581 +Epoch [1953/4000] Training [10/16] Loss: 0.00719 +Epoch [1953/4000] Training [11/16] Loss: 0.00724 +Epoch [1953/4000] Training [12/16] Loss: 0.00559 +Epoch [1953/4000] Training [13/16] Loss: 0.00664 +Epoch [1953/4000] Training [14/16] Loss: 0.00876 +Epoch [1953/4000] Training [15/16] Loss: 0.00495 +Epoch [1953/4000] Training [16/16] Loss: 0.00557 +Epoch [1953/4000] Training metric {'Train/mean dice_metric': 0.99567049741745, 'Train/mean miou_metric': 0.9911060929298401, 'Train/mean f1': 0.9913480281829834, 'Train/mean precision': 0.9866663217544556, 'Train/mean recall': 0.996074378490448, 'Train/mean hd95_metric': 1.0054203271865845} +Epoch [1953/4000] Validation [1/4] Loss: 0.28669 focal_loss 0.21982 dice_loss 0.06688 +Epoch [1953/4000] Validation [2/4] Loss: 0.44473 focal_loss 0.27786 dice_loss 0.16686 +Epoch [1953/4000] Validation [3/4] Loss: 0.36142 focal_loss 0.26578 dice_loss 0.09564 +Epoch [1953/4000] Validation [4/4] Loss: 0.23791 focal_loss 0.15050 dice_loss 0.08742 +Epoch [1953/4000] Validation metric {'Val/mean dice_metric': 0.9718610644340515, 'Val/mean miou_metric': 0.9554251432418823, 'Val/mean f1': 0.974048376083374, 'Val/mean precision': 0.9739247560501099, 'Val/mean recall': 0.9741718173027039, 'Val/mean hd95_metric': 4.989912509918213} +Cheakpoint... +Epoch [1953/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718610644340515, 'Val/mean miou_metric': 0.9554251432418823, 'Val/mean f1': 0.974048376083374, 'Val/mean precision': 0.9739247560501099, 'Val/mean recall': 0.9741718173027039, 'Val/mean hd95_metric': 4.989912509918213} +Epoch [1954/4000] Training [1/16] Loss: 0.00736 +Epoch [1954/4000] Training [2/16] Loss: 0.00664 +Epoch [1954/4000] Training [3/16] Loss: 0.00532 +Epoch [1954/4000] Training [4/16] Loss: 0.00667 +Epoch [1954/4000] Training [5/16] Loss: 0.00618 +Epoch [1954/4000] Training [6/16] Loss: 0.00769 +Epoch [1954/4000] Training [7/16] Loss: 0.00702 +Epoch [1954/4000] Training [8/16] Loss: 0.00610 +Epoch [1954/4000] Training [9/16] Loss: 0.00609 +Epoch [1954/4000] Training [10/16] Loss: 0.00699 +Epoch [1954/4000] Training [11/16] Loss: 0.00544 +Epoch [1954/4000] Training [12/16] Loss: 0.00494 +Epoch [1954/4000] Training [13/16] Loss: 0.00781 +Epoch [1954/4000] Training [14/16] Loss: 0.00417 +Epoch [1954/4000] Training [15/16] Loss: 0.00839 +Epoch [1954/4000] Training [16/16] Loss: 0.00833 +Epoch [1954/4000] Training metric {'Train/mean dice_metric': 0.9957245588302612, 'Train/mean miou_metric': 0.9912195801734924, 'Train/mean f1': 0.9914085268974304, 'Train/mean precision': 0.9866906404495239, 'Train/mean recall': 0.9961717128753662, 'Train/mean hd95_metric': 1.0108075141906738} +Epoch [1954/4000] Validation [1/4] Loss: 0.39245 focal_loss 0.30297 dice_loss 0.08949 +Epoch [1954/4000] Validation [2/4] Loss: 0.69115 focal_loss 0.49240 dice_loss 0.19875 +Epoch [1954/4000] Validation [3/4] Loss: 0.36238 focal_loss 0.26550 dice_loss 0.09687 +Epoch [1954/4000] Validation [4/4] Loss: 0.22885 focal_loss 0.14009 dice_loss 0.08876 +Epoch [1954/4000] Validation metric {'Val/mean dice_metric': 0.9696361422538757, 'Val/mean miou_metric': 0.9528623819351196, 'Val/mean f1': 0.9727931618690491, 'Val/mean precision': 0.9724183082580566, 'Val/mean recall': 0.9731683135032654, 'Val/mean hd95_metric': 5.155387878417969} +Cheakpoint... +Epoch [1954/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696361422538757, 'Val/mean miou_metric': 0.9528623819351196, 'Val/mean f1': 0.9727931618690491, 'Val/mean precision': 0.9724183082580566, 'Val/mean recall': 0.9731683135032654, 'Val/mean hd95_metric': 5.155387878417969} +Epoch [1955/4000] Training [1/16] Loss: 0.00541 +Epoch [1955/4000] Training [2/16] Loss: 0.00451 +Epoch [1955/4000] Training [3/16] Loss: 0.00413 +Epoch [1955/4000] Training [4/16] Loss: 0.00445 +Epoch [1955/4000] Training [5/16] Loss: 0.00630 +Epoch [1955/4000] Training [6/16] Loss: 0.00790 +Epoch [1955/4000] Training [7/16] Loss: 0.00712 +Epoch [1955/4000] Training [8/16] Loss: 0.00589 +Epoch [1955/4000] Training [9/16] Loss: 0.00675 +Epoch [1955/4000] Training [10/16] Loss: 0.00695 +Epoch [1955/4000] Training [11/16] Loss: 0.00728 +Epoch [1955/4000] Training [12/16] Loss: 0.00529 +Epoch [1955/4000] Training [13/16] Loss: 0.00783 +Epoch [1955/4000] Training [14/16] Loss: 0.00665 +Epoch [1955/4000] Training [15/16] Loss: 0.00799 +Epoch [1955/4000] Training [16/16] Loss: 0.00609 +Epoch [1955/4000] Training metric {'Train/mean dice_metric': 0.9957988262176514, 'Train/mean miou_metric': 0.9913722276687622, 'Train/mean f1': 0.9916321039199829, 'Train/mean precision': 0.9870559573173523, 'Train/mean recall': 0.9962508082389832, 'Train/mean hd95_metric': 1.014926552772522} +Epoch [1955/4000] Validation [1/4] Loss: 0.50380 focal_loss 0.38959 dice_loss 0.11421 +Epoch [1955/4000] Validation [2/4] Loss: 0.64081 focal_loss 0.43775 dice_loss 0.20305 +Epoch [1955/4000] Validation [3/4] Loss: 0.17883 focal_loss 0.12360 dice_loss 0.05523 +Epoch [1955/4000] Validation [4/4] Loss: 0.23571 focal_loss 0.13286 dice_loss 0.10285 +Epoch [1955/4000] Validation metric {'Val/mean dice_metric': 0.9705494046211243, 'Val/mean miou_metric': 0.9539899826049805, 'Val/mean f1': 0.9735562205314636, 'Val/mean precision': 0.9753074049949646, 'Val/mean recall': 0.9718113541603088, 'Val/mean hd95_metric': 4.711591720581055} +Cheakpoint... +Epoch [1955/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705494046211243, 'Val/mean miou_metric': 0.9539899826049805, 'Val/mean f1': 0.9735562205314636, 'Val/mean precision': 0.9753074049949646, 'Val/mean recall': 0.9718113541603088, 'Val/mean hd95_metric': 4.711591720581055} +Epoch [1956/4000] Training [1/16] Loss: 0.00598 +Epoch [1956/4000] Training [2/16] Loss: 0.00822 +Epoch [1956/4000] Training [3/16] Loss: 0.00641 +Epoch [1956/4000] Training [4/16] Loss: 0.00740 +Epoch [1956/4000] Training [5/16] Loss: 0.00670 +Epoch [1956/4000] Training [6/16] Loss: 0.00544 +Epoch [1956/4000] Training [7/16] Loss: 0.00674 +Epoch [1956/4000] Training [8/16] Loss: 0.00785 +Epoch [1956/4000] Training [9/16] Loss: 0.00636 +Epoch [1956/4000] Training [10/16] Loss: 0.00571 +Epoch [1956/4000] Training [11/16] Loss: 0.00869 +Epoch [1956/4000] Training [12/16] Loss: 0.00551 +Epoch [1956/4000] Training [13/16] Loss: 0.00679 +Epoch [1956/4000] Training [14/16] Loss: 0.00649 +Epoch [1956/4000] Training [15/16] Loss: 0.00516 +Epoch [1956/4000] Training [16/16] Loss: 0.00548 +Epoch [1956/4000] Training metric {'Train/mean dice_metric': 0.9956473112106323, 'Train/mean miou_metric': 0.991060733795166, 'Train/mean f1': 0.9913955330848694, 'Train/mean precision': 0.9867128133773804, 'Train/mean recall': 0.9961228370666504, 'Train/mean hd95_metric': 1.086301565170288} +Epoch [1956/4000] Validation [1/4] Loss: 0.27917 focal_loss 0.21071 dice_loss 0.06846 +Epoch [1956/4000] Validation [2/4] Loss: 0.59784 focal_loss 0.39591 dice_loss 0.20193 +Epoch [1956/4000] Validation [3/4] Loss: 0.47022 focal_loss 0.36065 dice_loss 0.10956 +Epoch [1956/4000] Validation [4/4] Loss: 0.24195 focal_loss 0.15183 dice_loss 0.09012 +Epoch [1956/4000] Validation metric {'Val/mean dice_metric': 0.971265435218811, 'Val/mean miou_metric': 0.9548288583755493, 'Val/mean f1': 0.9745057225227356, 'Val/mean precision': 0.9743649959564209, 'Val/mean recall': 0.9746463894844055, 'Val/mean hd95_metric': 5.495333194732666} +Cheakpoint... +Epoch [1956/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971265435218811, 'Val/mean miou_metric': 0.9548288583755493, 'Val/mean f1': 0.9745057225227356, 'Val/mean precision': 0.9743649959564209, 'Val/mean recall': 0.9746463894844055, 'Val/mean hd95_metric': 5.495333194732666} +Epoch [1957/4000] Training [1/16] Loss: 0.00667 +Epoch [1957/4000] Training [2/16] Loss: 0.00590 +Epoch [1957/4000] Training [3/16] Loss: 0.00617 +Epoch [1957/4000] Training [4/16] Loss: 0.00518 +Epoch [1957/4000] Training [5/16] Loss: 0.00634 +Epoch [1957/4000] Training [6/16] Loss: 0.00569 +Epoch [1957/4000] Training [7/16] Loss: 0.00549 +Epoch [1957/4000] Training [8/16] Loss: 0.00826 +Epoch [1957/4000] Training [9/16] Loss: 0.00595 +Epoch [1957/4000] Training [10/16] Loss: 0.00437 +Epoch [1957/4000] Training [11/16] Loss: 0.00466 +Epoch [1957/4000] Training [12/16] Loss: 0.00706 +Epoch [1957/4000] Training [13/16] Loss: 0.00764 +Epoch [1957/4000] Training [14/16] Loss: 0.00497 +Epoch [1957/4000] Training [15/16] Loss: 0.00703 +Epoch [1957/4000] Training [16/16] Loss: 0.01004 +Epoch [1957/4000] Training metric {'Train/mean dice_metric': 0.9956858158111572, 'Train/mean miou_metric': 0.9911298751831055, 'Train/mean f1': 0.991333544254303, 'Train/mean precision': 0.9866824150085449, 'Train/mean recall': 0.9960286617279053, 'Train/mean hd95_metric': 1.0244882106781006} +Epoch [1957/4000] Validation [1/4] Loss: 0.27338 focal_loss 0.20838 dice_loss 0.06500 +Epoch [1957/4000] Validation [2/4] Loss: 0.67484 focal_loss 0.46806 dice_loss 0.20679 +Epoch [1957/4000] Validation [3/4] Loss: 0.34805 focal_loss 0.25769 dice_loss 0.09036 +Epoch [1957/4000] Validation [4/4] Loss: 0.21469 focal_loss 0.12277 dice_loss 0.09193 +Epoch [1957/4000] Validation metric {'Val/mean dice_metric': 0.9738644361495972, 'Val/mean miou_metric': 0.9572212100028992, 'Val/mean f1': 0.9747530221939087, 'Val/mean precision': 0.9747077226638794, 'Val/mean recall': 0.9747982621192932, 'Val/mean hd95_metric': 5.017210006713867} +Cheakpoint... +Epoch [1957/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738644361495972, 'Val/mean miou_metric': 0.9572212100028992, 'Val/mean f1': 0.9747530221939087, 'Val/mean precision': 0.9747077226638794, 'Val/mean recall': 0.9747982621192932, 'Val/mean hd95_metric': 5.017210006713867} +Epoch [1958/4000] Training [1/16] Loss: 0.00738 +Epoch [1958/4000] Training [2/16] Loss: 0.00622 +Epoch [1958/4000] Training [3/16] Loss: 0.00581 +Epoch [1958/4000] Training [4/16] Loss: 0.00761 +Epoch [1958/4000] Training [5/16] Loss: 0.00632 +Epoch [1958/4000] Training [6/16] Loss: 0.00653 +Epoch [1958/4000] Training [7/16] Loss: 0.00449 +Epoch [1958/4000] Training [8/16] Loss: 0.00596 +Epoch [1958/4000] Training [9/16] Loss: 0.00737 +Epoch [1958/4000] Training [10/16] Loss: 0.00437 +Epoch [1958/4000] Training [11/16] Loss: 0.00631 +Epoch [1958/4000] Training [12/16] Loss: 0.00464 +Epoch [1958/4000] Training [13/16] Loss: 0.00604 +Epoch [1958/4000] Training [14/16] Loss: 0.00491 +Epoch [1958/4000] Training [15/16] Loss: 0.00641 +Epoch [1958/4000] Training [16/16] Loss: 0.00587 +Epoch [1958/4000] Training metric {'Train/mean dice_metric': 0.9958428144454956, 'Train/mean miou_metric': 0.9914470314979553, 'Train/mean f1': 0.9913920760154724, 'Train/mean precision': 0.986700713634491, 'Train/mean recall': 0.996128261089325, 'Train/mean hd95_metric': 1.263309359550476} +Epoch [1958/4000] Validation [1/4] Loss: 0.29938 focal_loss 0.22274 dice_loss 0.07665 +Epoch [1958/4000] Validation [2/4] Loss: 0.61838 focal_loss 0.42504 dice_loss 0.19334 +Epoch [1958/4000] Validation [3/4] Loss: 0.16182 focal_loss 0.10709 dice_loss 0.05473 +Epoch [1958/4000] Validation [4/4] Loss: 0.29927 focal_loss 0.19808 dice_loss 0.10119 +Epoch [1958/4000] Validation metric {'Val/mean dice_metric': 0.9696692228317261, 'Val/mean miou_metric': 0.9530094861984253, 'Val/mean f1': 0.9734447002410889, 'Val/mean precision': 0.9742982983589172, 'Val/mean recall': 0.972592830657959, 'Val/mean hd95_metric': 5.234756946563721} +Cheakpoint... +Epoch [1958/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696692228317261, 'Val/mean miou_metric': 0.9530094861984253, 'Val/mean f1': 0.9734447002410889, 'Val/mean precision': 0.9742982983589172, 'Val/mean recall': 0.972592830657959, 'Val/mean hd95_metric': 5.234756946563721} +Epoch [1959/4000] Training [1/16] Loss: 0.00522 +Epoch [1959/4000] Training [2/16] Loss: 0.00522 +Epoch [1959/4000] Training [3/16] Loss: 0.00694 +Epoch [1959/4000] Training [4/16] Loss: 0.00504 +Epoch [1959/4000] Training [5/16] Loss: 0.00536 +Epoch [1959/4000] Training [6/16] Loss: 0.00579 +Epoch [1959/4000] Training [7/16] Loss: 0.00507 +Epoch [1959/4000] Training [8/16] Loss: 0.00624 +Epoch [1959/4000] Training [9/16] Loss: 0.00592 +Epoch [1959/4000] Training [10/16] Loss: 0.00441 +Epoch [1959/4000] Training [11/16] Loss: 0.00742 +Epoch [1959/4000] Training [12/16] Loss: 0.00532 +Epoch [1959/4000] Training [13/16] Loss: 0.00639 +Epoch [1959/4000] Training [14/16] Loss: 0.00620 +Epoch [1959/4000] Training [15/16] Loss: 0.00514 +Epoch [1959/4000] Training [16/16] Loss: 0.00489 +Epoch [1959/4000] Training metric {'Train/mean dice_metric': 0.9961901903152466, 'Train/mean miou_metric': 0.9921388626098633, 'Train/mean f1': 0.991797685623169, 'Train/mean precision': 0.9871542453765869, 'Train/mean recall': 0.9964850544929504, 'Train/mean hd95_metric': 1.0115714073181152} +Epoch [1959/4000] Validation [1/4] Loss: 0.24794 focal_loss 0.18668 dice_loss 0.06126 +Epoch [1959/4000] Validation [2/4] Loss: 0.55600 focal_loss 0.36864 dice_loss 0.18736 +Epoch [1959/4000] Validation [3/4] Loss: 0.25335 focal_loss 0.16316 dice_loss 0.09018 +Epoch [1959/4000] Validation [4/4] Loss: 0.26297 focal_loss 0.16387 dice_loss 0.09910 +Epoch [1959/4000] Validation metric {'Val/mean dice_metric': 0.9717532992362976, 'Val/mean miou_metric': 0.9558466076850891, 'Val/mean f1': 0.9752979278564453, 'Val/mean precision': 0.9745302200317383, 'Val/mean recall': 0.9760669469833374, 'Val/mean hd95_metric': 5.072057247161865} +Cheakpoint... +Epoch [1959/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717532992362976, 'Val/mean miou_metric': 0.9558466076850891, 'Val/mean f1': 0.9752979278564453, 'Val/mean precision': 0.9745302200317383, 'Val/mean recall': 0.9760669469833374, 'Val/mean hd95_metric': 5.072057247161865} +Epoch [1960/4000] Training [1/16] Loss: 0.00581 +Epoch [1960/4000] Training [2/16] Loss: 0.01028 +Epoch [1960/4000] Training [3/16] Loss: 0.00688 +Epoch [1960/4000] Training [4/16] Loss: 0.00598 +Epoch [1960/4000] Training [5/16] Loss: 0.00462 +Epoch [1960/4000] Training [6/16] Loss: 0.00879 +Epoch [1960/4000] Training [7/16] Loss: 0.00553 +Epoch [1960/4000] Training [8/16] Loss: 0.00604 +Epoch [1960/4000] Training [9/16] Loss: 0.00566 +Epoch [1960/4000] Training [10/16] Loss: 0.00828 +Epoch [1960/4000] Training [11/16] Loss: 0.00780 +Epoch [1960/4000] Training [12/16] Loss: 0.01079 +Epoch [1960/4000] Training [13/16] Loss: 0.00538 +Epoch [1960/4000] Training [14/16] Loss: 0.00513 +Epoch [1960/4000] Training [15/16] Loss: 0.00607 +Epoch [1960/4000] Training [16/16] Loss: 0.00738 +Epoch [1960/4000] Training metric {'Train/mean dice_metric': 0.9955952167510986, 'Train/mean miou_metric': 0.9909746646881104, 'Train/mean f1': 0.9913937449455261, 'Train/mean precision': 0.9868625998497009, 'Train/mean recall': 0.9959666728973389, 'Train/mean hd95_metric': 1.1975491046905518} +Epoch [1960/4000] Validation [1/4] Loss: 0.23405 focal_loss 0.17520 dice_loss 0.05885 +Epoch [1960/4000] Validation [2/4] Loss: 0.54562 focal_loss 0.36069 dice_loss 0.18493 +Epoch [1960/4000] Validation [3/4] Loss: 0.29688 focal_loss 0.20131 dice_loss 0.09558 +Epoch [1960/4000] Validation [4/4] Loss: 0.29598 focal_loss 0.18268 dice_loss 0.11330 +Epoch [1960/4000] Validation metric {'Val/mean dice_metric': 0.9704341888427734, 'Val/mean miou_metric': 0.9540961384773254, 'Val/mean f1': 0.9732409715652466, 'Val/mean precision': 0.9722939133644104, 'Val/mean recall': 0.974189817905426, 'Val/mean hd95_metric': 5.528951644897461} +Cheakpoint... +Epoch [1960/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704341888427734, 'Val/mean miou_metric': 0.9540961384773254, 'Val/mean f1': 0.9732409715652466, 'Val/mean precision': 0.9722939133644104, 'Val/mean recall': 0.974189817905426, 'Val/mean hd95_metric': 5.528951644897461} +Epoch [1961/4000] Training [1/16] Loss: 0.00752 +Epoch [1961/4000] Training [2/16] Loss: 0.00553 +Epoch [1961/4000] Training [3/16] Loss: 0.00567 +Epoch [1961/4000] Training [4/16] Loss: 0.00572 +Epoch [1961/4000] Training [5/16] Loss: 0.00507 +Epoch [1961/4000] Training [6/16] Loss: 0.00559 +Epoch [1961/4000] Training [7/16] Loss: 0.00646 +Epoch [1961/4000] Training [8/16] Loss: 0.00626 +Epoch [1961/4000] Training [9/16] Loss: 0.00488 +Epoch [1961/4000] Training [10/16] Loss: 0.00494 +Epoch [1961/4000] Training [11/16] Loss: 0.00688 +Epoch [1961/4000] Training [12/16] Loss: 0.00536 +Epoch [1961/4000] Training [13/16] Loss: 0.00531 +Epoch [1961/4000] Training [14/16] Loss: 0.00606 +Epoch [1961/4000] Training [15/16] Loss: 0.00472 +Epoch [1961/4000] Training [16/16] Loss: 0.00627 +Epoch [1961/4000] Training metric {'Train/mean dice_metric': 0.9959301948547363, 'Train/mean miou_metric': 0.9916274547576904, 'Train/mean f1': 0.9915329217910767, 'Train/mean precision': 0.9868847727775574, 'Train/mean recall': 0.996225118637085, 'Train/mean hd95_metric': 1.0255188941955566} +Epoch [1961/4000] Validation [1/4] Loss: 0.35134 focal_loss 0.27027 dice_loss 0.08107 +Epoch [1961/4000] Validation [2/4] Loss: 0.61664 focal_loss 0.42599 dice_loss 0.19065 +Epoch [1961/4000] Validation [3/4] Loss: 0.30888 focal_loss 0.21280 dice_loss 0.09609 +Epoch [1961/4000] Validation [4/4] Loss: 0.24775 focal_loss 0.15497 dice_loss 0.09278 +Epoch [1961/4000] Validation metric {'Val/mean dice_metric': 0.9686640501022339, 'Val/mean miou_metric': 0.951850414276123, 'Val/mean f1': 0.971943199634552, 'Val/mean precision': 0.9746419191360474, 'Val/mean recall': 0.9692593216896057, 'Val/mean hd95_metric': 5.612922191619873} +Cheakpoint... +Epoch [1961/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9686640501022339, 'Val/mean miou_metric': 0.951850414276123, 'Val/mean f1': 0.971943199634552, 'Val/mean precision': 0.9746419191360474, 'Val/mean recall': 0.9692593216896057, 'Val/mean hd95_metric': 5.612922191619873} +Epoch [1962/4000] Training [1/16] Loss: 0.00755 +Epoch [1962/4000] Training [2/16] Loss: 0.00525 +Epoch [1962/4000] Training [3/16] Loss: 0.00611 +Epoch [1962/4000] Training [4/16] Loss: 0.00768 +Epoch [1962/4000] Training [5/16] Loss: 0.00774 +Epoch [1962/4000] Training [6/16] Loss: 0.00866 +Epoch [1962/4000] Training [7/16] Loss: 0.00708 +Epoch [1962/4000] Training [8/16] Loss: 0.00717 +Epoch [1962/4000] Training [9/16] Loss: 0.00694 +Epoch [1962/4000] Training [10/16] Loss: 0.00683 +Epoch [1962/4000] Training [11/16] Loss: 0.00848 +Epoch [1962/4000] Training [12/16] Loss: 0.00631 +Epoch [1962/4000] Training [13/16] Loss: 0.00666 +Epoch [1962/4000] Training [14/16] Loss: 0.00568 +Epoch [1962/4000] Training [15/16] Loss: 0.00717 +Epoch [1962/4000] Training [16/16] Loss: 0.01016 +Epoch [1962/4000] Training metric {'Train/mean dice_metric': 0.9953742623329163, 'Train/mean miou_metric': 0.9905458092689514, 'Train/mean f1': 0.9913380742073059, 'Train/mean precision': 0.9867620468139648, 'Train/mean recall': 0.9959567785263062, 'Train/mean hd95_metric': 1.033642053604126} +Epoch [1962/4000] Validation [1/4] Loss: 0.23663 focal_loss 0.17697 dice_loss 0.05966 +Epoch [1962/4000] Validation [2/4] Loss: 0.41029 focal_loss 0.23388 dice_loss 0.17641 +Epoch [1962/4000] Validation [3/4] Loss: 0.25381 focal_loss 0.16697 dice_loss 0.08683 +Epoch [1962/4000] Validation [4/4] Loss: 0.30260 focal_loss 0.18589 dice_loss 0.11671 +Epoch [1962/4000] Validation metric {'Val/mean dice_metric': 0.9716779589653015, 'Val/mean miou_metric': 0.9545437097549438, 'Val/mean f1': 0.9742174744606018, 'Val/mean precision': 0.9713076949119568, 'Val/mean recall': 0.9771448373794556, 'Val/mean hd95_metric': 5.525191307067871} +Cheakpoint... +Epoch [1962/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716779589653015, 'Val/mean miou_metric': 0.9545437097549438, 'Val/mean f1': 0.9742174744606018, 'Val/mean precision': 0.9713076949119568, 'Val/mean recall': 0.9771448373794556, 'Val/mean hd95_metric': 5.525191307067871} +Epoch [1963/4000] Training [1/16] Loss: 0.00500 +Epoch [1963/4000] Training [2/16] Loss: 0.01071 +Epoch [1963/4000] Training [3/16] Loss: 0.00674 +Epoch [1963/4000] Training [4/16] Loss: 0.00693 +Epoch [1963/4000] Training [5/16] Loss: 0.00751 +Epoch [1963/4000] Training [6/16] Loss: 0.00612 +Epoch [1963/4000] Training [7/16] Loss: 0.00867 +Epoch [1963/4000] Training [8/16] Loss: 0.00560 +Epoch [1963/4000] Training [9/16] Loss: 0.00672 +Epoch [1963/4000] Training [10/16] Loss: 0.00467 +Epoch [1963/4000] Training [11/16] Loss: 0.00633 +Epoch [1963/4000] Training [12/16] Loss: 0.00514 +Epoch [1963/4000] Training [13/16] Loss: 0.00585 +Epoch [1963/4000] Training [14/16] Loss: 0.00570 +Epoch [1963/4000] Training [15/16] Loss: 0.00862 +Epoch [1963/4000] Training [16/16] Loss: 0.00638 +Epoch [1963/4000] Training metric {'Train/mean dice_metric': 0.9955836534500122, 'Train/mean miou_metric': 0.990938663482666, 'Train/mean f1': 0.9912516474723816, 'Train/mean precision': 0.9867129921913147, 'Train/mean recall': 0.9958322644233704, 'Train/mean hd95_metric': 1.0247045755386353} +Epoch [1963/4000] Validation [1/4] Loss: 0.25443 focal_loss 0.18856 dice_loss 0.06587 +Epoch [1963/4000] Validation [2/4] Loss: 0.29592 focal_loss 0.16062 dice_loss 0.13530 +Epoch [1963/4000] Validation [3/4] Loss: 0.27551 focal_loss 0.19060 dice_loss 0.08491 +Epoch [1963/4000] Validation [4/4] Loss: 0.21572 focal_loss 0.12215 dice_loss 0.09357 +Epoch [1963/4000] Validation metric {'Val/mean dice_metric': 0.9728293418884277, 'Val/mean miou_metric': 0.9557077288627625, 'Val/mean f1': 0.9741132855415344, 'Val/mean precision': 0.9710347652435303, 'Val/mean recall': 0.9772112965583801, 'Val/mean hd95_metric': 5.782862663269043} +Cheakpoint... +Epoch [1963/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728293418884277, 'Val/mean miou_metric': 0.9557077288627625, 'Val/mean f1': 0.9741132855415344, 'Val/mean precision': 0.9710347652435303, 'Val/mean recall': 0.9772112965583801, 'Val/mean hd95_metric': 5.782862663269043} +Epoch [1964/4000] Training [1/16] Loss: 0.00723 +Epoch [1964/4000] Training [2/16] Loss: 0.00423 +Epoch [1964/4000] Training [3/16] Loss: 0.00546 +Epoch [1964/4000] Training [4/16] Loss: 0.00643 +Epoch [1964/4000] Training [5/16] Loss: 0.00639 +Epoch [1964/4000] Training [6/16] Loss: 0.00692 +Epoch [1964/4000] Training [7/16] Loss: 0.00651 +Epoch [1964/4000] Training [8/16] Loss: 0.00651 +Epoch [1964/4000] Training [9/16] Loss: 0.00606 +Epoch [1964/4000] Training [10/16] Loss: 0.00553 +Epoch [1964/4000] Training [11/16] Loss: 0.00685 +Epoch [1964/4000] Training [12/16] Loss: 0.00539 +Epoch [1964/4000] Training [13/16] Loss: 0.00572 +Epoch [1964/4000] Training [14/16] Loss: 0.00641 +Epoch [1964/4000] Training [15/16] Loss: 0.00649 +Epoch [1964/4000] Training [16/16] Loss: 0.00873 +Epoch [1964/4000] Training metric {'Train/mean dice_metric': 0.9956810474395752, 'Train/mean miou_metric': 0.9911121129989624, 'Train/mean f1': 0.9910768270492554, 'Train/mean precision': 0.9862309098243713, 'Train/mean recall': 0.9959705471992493, 'Train/mean hd95_metric': 1.0189428329467773} +Epoch [1964/4000] Validation [1/4] Loss: 0.29962 focal_loss 0.22546 dice_loss 0.07416 +Epoch [1964/4000] Validation [2/4] Loss: 0.32878 focal_loss 0.21308 dice_loss 0.11571 +Epoch [1964/4000] Validation [3/4] Loss: 0.32178 focal_loss 0.23468 dice_loss 0.08710 +Epoch [1964/4000] Validation [4/4] Loss: 0.16444 focal_loss 0.09847 dice_loss 0.06597 +Epoch [1964/4000] Validation metric {'Val/mean dice_metric': 0.9737828969955444, 'Val/mean miou_metric': 0.9571586847305298, 'Val/mean f1': 0.9739437103271484, 'Val/mean precision': 0.9701051712036133, 'Val/mean recall': 0.9778127074241638, 'Val/mean hd95_metric': 5.8033037185668945} +Cheakpoint... +Epoch [1964/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737828969955444, 'Val/mean miou_metric': 0.9571586847305298, 'Val/mean f1': 0.9739437103271484, 'Val/mean precision': 0.9701051712036133, 'Val/mean recall': 0.9778127074241638, 'Val/mean hd95_metric': 5.8033037185668945} +Epoch [1965/4000] Training [1/16] Loss: 0.00729 +Epoch [1965/4000] Training [2/16] Loss: 0.00660 +Epoch [1965/4000] Training [3/16] Loss: 0.00671 +Epoch [1965/4000] Training [4/16] Loss: 0.00392 +Epoch [1965/4000] Training [5/16] Loss: 0.00539 +Epoch [1965/4000] Training [6/16] Loss: 0.00556 +Epoch [1965/4000] Training [7/16] Loss: 0.00665 +Epoch [1965/4000] Training [8/16] Loss: 0.00683 +Epoch [1965/4000] Training [9/16] Loss: 0.00605 +Epoch [1965/4000] Training [10/16] Loss: 0.00768 +Epoch [1965/4000] Training [11/16] Loss: 0.00744 +Epoch [1965/4000] Training [12/16] Loss: 0.00624 +Epoch [1965/4000] Training [13/16] Loss: 0.00513 +Epoch [1965/4000] Training [14/16] Loss: 0.00532 +Epoch [1965/4000] Training [15/16] Loss: 0.00608 +Epoch [1965/4000] Training [16/16] Loss: 0.00379 +Epoch [1965/4000] Training metric {'Train/mean dice_metric': 0.9959390163421631, 'Train/mean miou_metric': 0.991639256477356, 'Train/mean f1': 0.9915617108345032, 'Train/mean precision': 0.9868782758712769, 'Train/mean recall': 0.9962897896766663, 'Train/mean hd95_metric': 1.0725150108337402} +Epoch [1965/4000] Validation [1/4] Loss: 0.24213 focal_loss 0.18380 dice_loss 0.05833 +Epoch [1965/4000] Validation [2/4] Loss: 0.32689 focal_loss 0.20917 dice_loss 0.11771 +Epoch [1965/4000] Validation [3/4] Loss: 0.31451 focal_loss 0.22414 dice_loss 0.09037 +Epoch [1965/4000] Validation [4/4] Loss: 0.15927 focal_loss 0.09359 dice_loss 0.06568 +Epoch [1965/4000] Validation metric {'Val/mean dice_metric': 0.9750049710273743, 'Val/mean miou_metric': 0.9584677815437317, 'Val/mean f1': 0.9750369191169739, 'Val/mean precision': 0.9716684222221375, 'Val/mean recall': 0.9784287810325623, 'Val/mean hd95_metric': 5.471271514892578} +Cheakpoint... +Epoch [1965/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750049710273743, 'Val/mean miou_metric': 0.9584677815437317, 'Val/mean f1': 0.9750369191169739, 'Val/mean precision': 0.9716684222221375, 'Val/mean recall': 0.9784287810325623, 'Val/mean hd95_metric': 5.471271514892578} +Epoch [1966/4000] Training [1/16] Loss: 0.00629 +Epoch [1966/4000] Training [2/16] Loss: 0.00468 +Epoch [1966/4000] Training [3/16] Loss: 0.00427 +Epoch [1966/4000] Training [4/16] Loss: 0.00529 +Epoch [1966/4000] Training [5/16] Loss: 0.01275 +Epoch [1966/4000] Training [6/16] Loss: 0.00617 +Epoch [1966/4000] Training [7/16] Loss: 0.00576 +Epoch [1966/4000] Training [8/16] Loss: 0.00680 +Epoch [1966/4000] Training [9/16] Loss: 0.00670 +Epoch [1966/4000] Training [10/16] Loss: 0.00475 +Epoch [1966/4000] Training [11/16] Loss: 0.00774 +Epoch [1966/4000] Training [12/16] Loss: 0.00629 +Epoch [1966/4000] Training [13/16] Loss: 0.00558 +Epoch [1966/4000] Training [14/16] Loss: 0.00526 +Epoch [1966/4000] Training [15/16] Loss: 0.00501 +Epoch [1966/4000] Training [16/16] Loss: 0.00604 +Epoch [1966/4000] Training metric {'Train/mean dice_metric': 0.9961080551147461, 'Train/mean miou_metric': 0.9919666051864624, 'Train/mean f1': 0.9916118383407593, 'Train/mean precision': 0.9868956208229065, 'Train/mean recall': 0.9963732957839966, 'Train/mean hd95_metric': 1.006472110748291} +Epoch [1966/4000] Validation [1/4] Loss: 0.24617 focal_loss 0.18447 dice_loss 0.06170 +Epoch [1966/4000] Validation [2/4] Loss: 0.32183 focal_loss 0.17747 dice_loss 0.14436 +Epoch [1966/4000] Validation [3/4] Loss: 0.33558 focal_loss 0.24556 dice_loss 0.09002 +Epoch [1966/4000] Validation [4/4] Loss: 0.28940 focal_loss 0.17847 dice_loss 0.11093 +Epoch [1966/4000] Validation metric {'Val/mean dice_metric': 0.9740591049194336, 'Val/mean miou_metric': 0.9576541781425476, 'Val/mean f1': 0.9750586748123169, 'Val/mean precision': 0.9717617630958557, 'Val/mean recall': 0.9783778190612793, 'Val/mean hd95_metric': 5.335361003875732} +Cheakpoint... +Epoch [1966/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740591049194336, 'Val/mean miou_metric': 0.9576541781425476, 'Val/mean f1': 0.9750586748123169, 'Val/mean precision': 0.9717617630958557, 'Val/mean recall': 0.9783778190612793, 'Val/mean hd95_metric': 5.335361003875732} +Epoch [1967/4000] Training [1/16] Loss: 0.00591 +Epoch [1967/4000] Training [2/16] Loss: 0.00434 +Epoch [1967/4000] Training [3/16] Loss: 0.00511 +Epoch [1967/4000] Training [4/16] Loss: 0.00676 +Epoch [1967/4000] Training [5/16] Loss: 0.00660 +Epoch [1967/4000] Training [6/16] Loss: 0.00554 +Epoch [1967/4000] Training [7/16] Loss: 0.00413 +Epoch [1967/4000] Training [8/16] Loss: 0.00524 +Epoch [1967/4000] Training [9/16] Loss: 0.00635 +Epoch [1967/4000] Training [10/16] Loss: 0.00886 +Epoch [1967/4000] Training [11/16] Loss: 0.00517 +Epoch [1967/4000] Training [12/16] Loss: 0.00626 +Epoch [1967/4000] Training [13/16] Loss: 0.00608 +Epoch [1967/4000] Training [14/16] Loss: 0.00416 +Epoch [1967/4000] Training [15/16] Loss: 0.00524 +Epoch [1967/4000] Training [16/16] Loss: 0.00649 +Epoch [1967/4000] Training metric {'Train/mean dice_metric': 0.9960414171218872, 'Train/mean miou_metric': 0.9918554425239563, 'Train/mean f1': 0.9917492866516113, 'Train/mean precision': 0.9871574640274048, 'Train/mean recall': 0.9963840246200562, 'Train/mean hd95_metric': 1.005998134613037} +Epoch [1967/4000] Validation [1/4] Loss: 0.53719 focal_loss 0.42706 dice_loss 0.11013 +Epoch [1967/4000] Validation [2/4] Loss: 0.54589 focal_loss 0.35045 dice_loss 0.19544 +Epoch [1967/4000] Validation [3/4] Loss: 0.34581 focal_loss 0.24882 dice_loss 0.09699 +Epoch [1967/4000] Validation [4/4] Loss: 0.29182 focal_loss 0.17594 dice_loss 0.11588 +Epoch [1967/4000] Validation metric {'Val/mean dice_metric': 0.9714531898498535, 'Val/mean miou_metric': 0.9550644159317017, 'Val/mean f1': 0.9729549884796143, 'Val/mean precision': 0.971500039100647, 'Val/mean recall': 0.9744141697883606, 'Val/mean hd95_metric': 5.3160247802734375} +Cheakpoint... +Epoch [1967/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714531898498535, 'Val/mean miou_metric': 0.9550644159317017, 'Val/mean f1': 0.9729549884796143, 'Val/mean precision': 0.971500039100647, 'Val/mean recall': 0.9744141697883606, 'Val/mean hd95_metric': 5.3160247802734375} +Epoch [1968/4000] Training [1/16] Loss: 0.00613 +Epoch [1968/4000] Training [2/16] Loss: 0.00566 +Epoch [1968/4000] Training [3/16] Loss: 0.00508 +Epoch [1968/4000] Training [4/16] Loss: 0.00659 +Epoch [1968/4000] Training [5/16] Loss: 0.00574 +Epoch [1968/4000] Training [6/16] Loss: 0.00728 +Epoch [1968/4000] Training [7/16] Loss: 0.00742 +Epoch [1968/4000] Training [8/16] Loss: 0.00768 +Epoch [1968/4000] Training [9/16] Loss: 0.00639 +Epoch [1968/4000] Training [10/16] Loss: 0.00765 +Epoch [1968/4000] Training [11/16] Loss: 0.00850 +Epoch [1968/4000] Training [12/16] Loss: 0.00718 +Epoch [1968/4000] Training [13/16] Loss: 0.00447 +Epoch [1968/4000] Training [14/16] Loss: 0.00509 +Epoch [1968/4000] Training [15/16] Loss: 0.00640 +Epoch [1968/4000] Training [16/16] Loss: 0.01017 +Epoch [1968/4000] Training metric {'Train/mean dice_metric': 0.9957356452941895, 'Train/mean miou_metric': 0.9912530779838562, 'Train/mean f1': 0.9916039109230042, 'Train/mean precision': 0.9872115850448608, 'Train/mean recall': 0.9960355162620544, 'Train/mean hd95_metric': 1.0233780145645142} +Epoch [1968/4000] Validation [1/4] Loss: 0.29925 focal_loss 0.22986 dice_loss 0.06939 +Epoch [1968/4000] Validation [2/4] Loss: 0.47245 focal_loss 0.28338 dice_loss 0.18908 +Epoch [1968/4000] Validation [3/4] Loss: 0.35048 focal_loss 0.25774 dice_loss 0.09274 +Epoch [1968/4000] Validation [4/4] Loss: 0.31325 focal_loss 0.20065 dice_loss 0.11260 +Epoch [1968/4000] Validation metric {'Val/mean dice_metric': 0.9715579748153687, 'Val/mean miou_metric': 0.9548227190971375, 'Val/mean f1': 0.9736647605895996, 'Val/mean precision': 0.9715602397918701, 'Val/mean recall': 0.9757785797119141, 'Val/mean hd95_metric': 5.66980504989624} +Cheakpoint... +Epoch [1968/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715579748153687, 'Val/mean miou_metric': 0.9548227190971375, 'Val/mean f1': 0.9736647605895996, 'Val/mean precision': 0.9715602397918701, 'Val/mean recall': 0.9757785797119141, 'Val/mean hd95_metric': 5.66980504989624} +Epoch [1969/4000] Training [1/16] Loss: 0.00485 +Epoch [1969/4000] Training [2/16] Loss: 0.00585 +Epoch [1969/4000] Training [3/16] Loss: 0.00460 +Epoch [1969/4000] Training [4/16] Loss: 0.00788 +Epoch [1969/4000] Training [5/16] Loss: 0.00579 +Epoch [1969/4000] Training [6/16] Loss: 0.00695 +Epoch [1969/4000] Training [7/16] Loss: 0.00576 +Epoch [1969/4000] Training [8/16] Loss: 0.00487 +Epoch [1969/4000] Training [9/16] Loss: 0.00653 +Epoch [1969/4000] Training [10/16] Loss: 0.00612 +Epoch [1969/4000] Training [11/16] Loss: 0.00562 +Epoch [1969/4000] Training [12/16] Loss: 0.00640 +Epoch [1969/4000] Training [13/16] Loss: 0.00643 +Epoch [1969/4000] Training [14/16] Loss: 0.00406 +Epoch [1969/4000] Training [15/16] Loss: 0.00515 +Epoch [1969/4000] Training [16/16] Loss: 0.00737 +Epoch [1969/4000] Training metric {'Train/mean dice_metric': 0.9961816072463989, 'Train/mean miou_metric': 0.9921286106109619, 'Train/mean f1': 0.9919144511222839, 'Train/mean precision': 0.9872711896896362, 'Train/mean recall': 0.9966015815734863, 'Train/mean hd95_metric': 1.0017855167388916} +Epoch [1969/4000] Validation [1/4] Loss: 0.32602 focal_loss 0.25099 dice_loss 0.07503 +Epoch [1969/4000] Validation [2/4] Loss: 0.32130 focal_loss 0.19901 dice_loss 0.12228 +Epoch [1969/4000] Validation [3/4] Loss: 0.30356 focal_loss 0.21395 dice_loss 0.08961 +Epoch [1969/4000] Validation [4/4] Loss: 0.30100 focal_loss 0.19203 dice_loss 0.10898 +Epoch [1969/4000] Validation metric {'Val/mean dice_metric': 0.9723770022392273, 'Val/mean miou_metric': 0.9560564160346985, 'Val/mean f1': 0.9745286703109741, 'Val/mean precision': 0.9724156260490417, 'Val/mean recall': 0.9766508936882019, 'Val/mean hd95_metric': 5.728931903839111} +Cheakpoint... +Epoch [1969/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723770022392273, 'Val/mean miou_metric': 0.9560564160346985, 'Val/mean f1': 0.9745286703109741, 'Val/mean precision': 0.9724156260490417, 'Val/mean recall': 0.9766508936882019, 'Val/mean hd95_metric': 5.728931903839111} +Epoch [1970/4000] Training [1/16] Loss: 0.00700 +Epoch [1970/4000] Training [2/16] Loss: 0.00551 +Epoch [1970/4000] Training [3/16] Loss: 0.00688 +Epoch [1970/4000] Training [4/16] Loss: 0.00518 +Epoch [1970/4000] Training [5/16] Loss: 0.00658 +Epoch [1970/4000] Training [6/16] Loss: 0.00647 +Epoch [1970/4000] Training [7/16] Loss: 0.00675 +Epoch [1970/4000] Training [8/16] Loss: 0.00498 +Epoch [1970/4000] Training [9/16] Loss: 0.00866 +Epoch [1970/4000] Training [10/16] Loss: 0.00546 +Epoch [1970/4000] Training [11/16] Loss: 0.00495 +Epoch [1970/4000] Training [12/16] Loss: 0.00707 +Epoch [1970/4000] Training [13/16] Loss: 0.00744 +Epoch [1970/4000] Training [14/16] Loss: 0.00755 +Epoch [1970/4000] Training [15/16] Loss: 0.00477 +Epoch [1970/4000] Training [16/16] Loss: 0.00520 +Epoch [1970/4000] Training metric {'Train/mean dice_metric': 0.99592125415802, 'Train/mean miou_metric': 0.9916089177131653, 'Train/mean f1': 0.9915575385093689, 'Train/mean precision': 0.9870373606681824, 'Train/mean recall': 0.9961192607879639, 'Train/mean hd95_metric': 1.126596212387085} +Epoch [1970/4000] Validation [1/4] Loss: 0.48791 focal_loss 0.38848 dice_loss 0.09944 +Epoch [1970/4000] Validation [2/4] Loss: 0.59276 focal_loss 0.39426 dice_loss 0.19849 +Epoch [1970/4000] Validation [3/4] Loss: 0.18396 focal_loss 0.12180 dice_loss 0.06216 +Epoch [1970/4000] Validation [4/4] Loss: 0.34734 focal_loss 0.23171 dice_loss 0.11563 +Epoch [1970/4000] Validation metric {'Val/mean dice_metric': 0.9705787897109985, 'Val/mean miou_metric': 0.9538895487785339, 'Val/mean f1': 0.9723131656646729, 'Val/mean precision': 0.9730421900749207, 'Val/mean recall': 0.9715851545333862, 'Val/mean hd95_metric': 6.027116298675537} +Cheakpoint... +Epoch [1970/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705787897109985, 'Val/mean miou_metric': 0.9538895487785339, 'Val/mean f1': 0.9723131656646729, 'Val/mean precision': 0.9730421900749207, 'Val/mean recall': 0.9715851545333862, 'Val/mean hd95_metric': 6.027116298675537} +Epoch [1971/4000] Training [1/16] Loss: 0.00538 +Epoch [1971/4000] Training [2/16] Loss: 0.00548 +Epoch [1971/4000] Training [3/16] Loss: 0.00507 +Epoch [1971/4000] Training [4/16] Loss: 0.00636 +Epoch [1971/4000] Training [5/16] Loss: 0.00562 +Epoch [1971/4000] Training [6/16] Loss: 0.00397 +Epoch [1971/4000] Training [7/16] Loss: 0.00956 +Epoch [1971/4000] Training [8/16] Loss: 0.00438 +Epoch [1971/4000] Training [9/16] Loss: 0.00725 +Epoch [1971/4000] Training [10/16] Loss: 0.00560 +Epoch [1971/4000] Training [11/16] Loss: 0.00643 +Epoch [1971/4000] Training [12/16] Loss: 0.00818 +Epoch [1971/4000] Training [13/16] Loss: 0.00635 +Epoch [1971/4000] Training [14/16] Loss: 0.00584 +Epoch [1971/4000] Training [15/16] Loss: 0.00613 +Epoch [1971/4000] Training [16/16] Loss: 0.01045 +Epoch [1971/4000] Training metric {'Train/mean dice_metric': 0.9957880973815918, 'Train/mean miou_metric': 0.9913482666015625, 'Train/mean f1': 0.9914523363113403, 'Train/mean precision': 0.9867393374443054, 'Train/mean recall': 0.996210515499115, 'Train/mean hd95_metric': 1.0268003940582275} +Epoch [1971/4000] Validation [1/4] Loss: 0.63827 focal_loss 0.52073 dice_loss 0.11754 +Epoch [1971/4000] Validation [2/4] Loss: 0.53167 focal_loss 0.34061 dice_loss 0.19106 +Epoch [1971/4000] Validation [3/4] Loss: 0.33878 focal_loss 0.24607 dice_loss 0.09271 +Epoch [1971/4000] Validation [4/4] Loss: 0.22491 focal_loss 0.13513 dice_loss 0.08977 +Epoch [1971/4000] Validation metric {'Val/mean dice_metric': 0.9716888666152954, 'Val/mean miou_metric': 0.9551202654838562, 'Val/mean f1': 0.9726992845535278, 'Val/mean precision': 0.9718459248542786, 'Val/mean recall': 0.9735541343688965, 'Val/mean hd95_metric': 5.333917140960693} +Cheakpoint... +Epoch [1971/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716888666152954, 'Val/mean miou_metric': 0.9551202654838562, 'Val/mean f1': 0.9726992845535278, 'Val/mean precision': 0.9718459248542786, 'Val/mean recall': 0.9735541343688965, 'Val/mean hd95_metric': 5.333917140960693} +Epoch [1972/4000] Training [1/16] Loss: 0.00617 +Epoch [1972/4000] Training [2/16] Loss: 0.00485 +Epoch [1972/4000] Training [3/16] Loss: 0.00609 +Epoch [1972/4000] Training [4/16] Loss: 0.00676 +Epoch [1972/4000] Training [5/16] Loss: 0.00701 +Epoch [1972/4000] Training [6/16] Loss: 0.00481 +Epoch [1972/4000] Training [7/16] Loss: 0.00650 +Epoch [1972/4000] Training [8/16] Loss: 0.00542 +Epoch [1972/4000] Training [9/16] Loss: 0.00571 +Epoch [1972/4000] Training [10/16] Loss: 0.00537 +Epoch [1972/4000] Training [11/16] Loss: 0.00549 +Epoch [1972/4000] Training [12/16] Loss: 0.00714 +Epoch [1972/4000] Training [13/16] Loss: 0.00836 +Epoch [1972/4000] Training [14/16] Loss: 0.00795 +Epoch [1972/4000] Training [15/16] Loss: 0.00600 +Epoch [1972/4000] Training [16/16] Loss: 0.00449 +Epoch [1972/4000] Training metric {'Train/mean dice_metric': 0.9961010217666626, 'Train/mean miou_metric': 0.9919648766517639, 'Train/mean f1': 0.9917457699775696, 'Train/mean precision': 0.987194299697876, 'Train/mean recall': 0.9963394403457642, 'Train/mean hd95_metric': 1.0097954273223877} +Epoch [1972/4000] Validation [1/4] Loss: 0.78252 focal_loss 0.65140 dice_loss 0.13112 +Epoch [1972/4000] Validation [2/4] Loss: 0.67478 focal_loss 0.48164 dice_loss 0.19314 +Epoch [1972/4000] Validation [3/4] Loss: 0.28545 focal_loss 0.19392 dice_loss 0.09153 +Epoch [1972/4000] Validation [4/4] Loss: 0.24398 focal_loss 0.14549 dice_loss 0.09850 +Epoch [1972/4000] Validation metric {'Val/mean dice_metric': 0.9702606201171875, 'Val/mean miou_metric': 0.9538573026657104, 'Val/mean f1': 0.9717300534248352, 'Val/mean precision': 0.9734991192817688, 'Val/mean recall': 0.9699673056602478, 'Val/mean hd95_metric': 5.608725070953369} +Cheakpoint... +Epoch [1972/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702606201171875, 'Val/mean miou_metric': 0.9538573026657104, 'Val/mean f1': 0.9717300534248352, 'Val/mean precision': 0.9734991192817688, 'Val/mean recall': 0.9699673056602478, 'Val/mean hd95_metric': 5.608725070953369} +Epoch [1973/4000] Training [1/16] Loss: 0.00489 +Epoch [1973/4000] Training [2/16] Loss: 0.00467 +Epoch [1973/4000] Training [3/16] Loss: 0.00523 +Epoch [1973/4000] Training [4/16] Loss: 0.00658 +Epoch [1973/4000] Training [5/16] Loss: 0.00570 +Epoch [1973/4000] Training [6/16] Loss: 0.00463 +Epoch [1973/4000] Training [7/16] Loss: 0.00575 +Epoch [1973/4000] Training [8/16] Loss: 0.00729 +Epoch [1973/4000] Training [9/16] Loss: 0.00533 +Epoch [1973/4000] Training [10/16] Loss: 0.00458 +Epoch [1973/4000] Training [11/16] Loss: 0.00666 +Epoch [1973/4000] Training [12/16] Loss: 0.00591 +Epoch [1973/4000] Training [13/16] Loss: 0.00507 +Epoch [1973/4000] Training [14/16] Loss: 0.00726 +Epoch [1973/4000] Training [15/16] Loss: 0.00465 +Epoch [1973/4000] Training [16/16] Loss: 0.00557 +Epoch [1973/4000] Training metric {'Train/mean dice_metric': 0.9961038827896118, 'Train/mean miou_metric': 0.9919874668121338, 'Train/mean f1': 0.9919473528862, 'Train/mean precision': 0.9873491525650024, 'Train/mean recall': 0.9965885877609253, 'Train/mean hd95_metric': 1.0321333408355713} +Epoch [1973/4000] Validation [1/4] Loss: 0.43052 focal_loss 0.34265 dice_loss 0.08787 +Epoch [1973/4000] Validation [2/4] Loss: 0.33981 focal_loss 0.22056 dice_loss 0.11925 +Epoch [1973/4000] Validation [3/4] Loss: 0.33327 focal_loss 0.24244 dice_loss 0.09083 +Epoch [1973/4000] Validation [4/4] Loss: 0.27140 focal_loss 0.17072 dice_loss 0.10068 +Epoch [1973/4000] Validation metric {'Val/mean dice_metric': 0.9715604782104492, 'Val/mean miou_metric': 0.9546585083007812, 'Val/mean f1': 0.9730937480926514, 'Val/mean precision': 0.9734741449356079, 'Val/mean recall': 0.9727135300636292, 'Val/mean hd95_metric': 5.565120220184326} +Cheakpoint... +Epoch [1973/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715604782104492, 'Val/mean miou_metric': 0.9546585083007812, 'Val/mean f1': 0.9730937480926514, 'Val/mean precision': 0.9734741449356079, 'Val/mean recall': 0.9727135300636292, 'Val/mean hd95_metric': 5.565120220184326} +Epoch [1974/4000] Training [1/16] Loss: 0.00584 +Epoch [1974/4000] Training [2/16] Loss: 0.00703 +Epoch [1974/4000] Training [3/16] Loss: 0.00567 +Epoch [1974/4000] Training [4/16] Loss: 0.00546 +Epoch [1974/4000] Training [5/16] Loss: 0.00509 +Epoch [1974/4000] Training [6/16] Loss: 0.00577 +Epoch [1974/4000] Training [7/16] Loss: 0.00753 +Epoch [1974/4000] Training [8/16] Loss: 0.00606 +Epoch [1974/4000] Training [9/16] Loss: 0.00497 +Epoch [1974/4000] Training [10/16] Loss: 0.00484 +Epoch [1974/4000] Training [11/16] Loss: 0.00780 +Epoch [1974/4000] Training [12/16] Loss: 0.00584 +Epoch [1974/4000] Training [13/16] Loss: 0.00648 +Epoch [1974/4000] Training [14/16] Loss: 0.00636 +Epoch [1974/4000] Training [15/16] Loss: 0.00801 +Epoch [1974/4000] Training [16/16] Loss: 0.00655 +Epoch [1974/4000] Training metric {'Train/mean dice_metric': 0.9960192441940308, 'Train/mean miou_metric': 0.991808295249939, 'Train/mean f1': 0.9918228983879089, 'Train/mean precision': 0.9874160289764404, 'Train/mean recall': 0.9962692260742188, 'Train/mean hd95_metric': 1.0095694065093994} +Epoch [1974/4000] Validation [1/4] Loss: 0.32482 focal_loss 0.25641 dice_loss 0.06841 +Epoch [1974/4000] Validation [2/4] Loss: 0.40246 focal_loss 0.25710 dice_loss 0.14536 +Epoch [1974/4000] Validation [3/4] Loss: 0.28502 focal_loss 0.19699 dice_loss 0.08803 +Epoch [1974/4000] Validation [4/4] Loss: 0.55437 focal_loss 0.39888 dice_loss 0.15549 +Epoch [1974/4000] Validation metric {'Val/mean dice_metric': 0.9709299206733704, 'Val/mean miou_metric': 0.9538954496383667, 'Val/mean f1': 0.9730921387672424, 'Val/mean precision': 0.9734522700309753, 'Val/mean recall': 0.9727321267127991, 'Val/mean hd95_metric': 5.6197710037231445} +Cheakpoint... +Epoch [1974/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709299206733704, 'Val/mean miou_metric': 0.9538954496383667, 'Val/mean f1': 0.9730921387672424, 'Val/mean precision': 0.9734522700309753, 'Val/mean recall': 0.9727321267127991, 'Val/mean hd95_metric': 5.6197710037231445} +Epoch [1975/4000] Training [1/16] Loss: 0.00478 +Epoch [1975/4000] Training [2/16] Loss: 0.00701 +Epoch [1975/4000] Training [3/16] Loss: 0.00679 +Epoch [1975/4000] Training [4/16] Loss: 0.00703 +Epoch [1975/4000] Training [5/16] Loss: 0.00537 +Epoch [1975/4000] Training [6/16] Loss: 0.00618 +Epoch [1975/4000] Training [7/16] Loss: 0.00717 +Epoch [1975/4000] Training [8/16] Loss: 0.00672 +Epoch [1975/4000] Training [9/16] Loss: 0.00458 +Epoch [1975/4000] Training [10/16] Loss: 0.00582 +Epoch [1975/4000] Training [11/16] Loss: 0.00666 +Epoch [1975/4000] Training [12/16] Loss: 0.00634 +Epoch [1975/4000] Training [13/16] Loss: 0.00692 +Epoch [1975/4000] Training [14/16] Loss: 0.00626 +Epoch [1975/4000] Training [15/16] Loss: 0.00603 +Epoch [1975/4000] Training [16/16] Loss: 0.00462 +Epoch [1975/4000] Training metric {'Train/mean dice_metric': 0.9959244728088379, 'Train/mean miou_metric': 0.9916006326675415, 'Train/mean f1': 0.9910907745361328, 'Train/mean precision': 0.9860256910324097, 'Train/mean recall': 0.996208131313324, 'Train/mean hd95_metric': 1.0070384740829468} +Epoch [1975/4000] Validation [1/4] Loss: 0.31289 focal_loss 0.23483 dice_loss 0.07806 +Epoch [1975/4000] Validation [2/4] Loss: 0.63512 focal_loss 0.44584 dice_loss 0.18928 +Epoch [1975/4000] Validation [3/4] Loss: 0.18043 focal_loss 0.11857 dice_loss 0.06186 +Epoch [1975/4000] Validation [4/4] Loss: 0.34358 focal_loss 0.21614 dice_loss 0.12744 +Epoch [1975/4000] Validation metric {'Val/mean dice_metric': 0.9703658819198608, 'Val/mean miou_metric': 0.9541781544685364, 'Val/mean f1': 0.97236567735672, 'Val/mean precision': 0.9708030819892883, 'Val/mean recall': 0.9739331603050232, 'Val/mean hd95_metric': 5.407597541809082} +Cheakpoint... +Epoch [1975/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703658819198608, 'Val/mean miou_metric': 0.9541781544685364, 'Val/mean f1': 0.97236567735672, 'Val/mean precision': 0.9708030819892883, 'Val/mean recall': 0.9739331603050232, 'Val/mean hd95_metric': 5.407597541809082} +Epoch [1976/4000] Training [1/16] Loss: 0.00792 +Epoch [1976/4000] Training [2/16] Loss: 0.00468 +Epoch [1976/4000] Training [3/16] Loss: 0.00838 +Epoch [1976/4000] Training [4/16] Loss: 0.00501 +Epoch [1976/4000] Training [5/16] Loss: 0.00522 +Epoch [1976/4000] Training [6/16] Loss: 0.00541 +Epoch [1976/4000] Training [7/16] Loss: 0.00692 +Epoch [1976/4000] Training [8/16] Loss: 0.00573 +Epoch [1976/4000] Training [9/16] Loss: 0.00632 +Epoch [1976/4000] Training [10/16] Loss: 0.00585 +Epoch [1976/4000] Training [11/16] Loss: 0.00434 +Epoch [1976/4000] Training [12/16] Loss: 0.00596 +Epoch [1976/4000] Training [13/16] Loss: 0.00586 +Epoch [1976/4000] Training [14/16] Loss: 0.00835 +Epoch [1976/4000] Training [15/16] Loss: 0.00741 +Epoch [1976/4000] Training [16/16] Loss: 0.00676 +Epoch [1976/4000] Training metric {'Train/mean dice_metric': 0.9958726167678833, 'Train/mean miou_metric': 0.9915181994438171, 'Train/mean f1': 0.9916814565658569, 'Train/mean precision': 0.9870989918708801, 'Train/mean recall': 0.9963066577911377, 'Train/mean hd95_metric': 1.012595534324646} +Epoch [1976/4000] Validation [1/4] Loss: 0.26843 focal_loss 0.20233 dice_loss 0.06610 +Epoch [1976/4000] Validation [2/4] Loss: 0.38585 focal_loss 0.25337 dice_loss 0.13247 +Epoch [1976/4000] Validation [3/4] Loss: 0.29539 focal_loss 0.20306 dice_loss 0.09233 +Epoch [1976/4000] Validation [4/4] Loss: 0.23811 focal_loss 0.14380 dice_loss 0.09431 +Epoch [1976/4000] Validation metric {'Val/mean dice_metric': 0.9715034365653992, 'Val/mean miou_metric': 0.9547499418258667, 'Val/mean f1': 0.9740380644798279, 'Val/mean precision': 0.9722076654434204, 'Val/mean recall': 0.9758754372596741, 'Val/mean hd95_metric': 5.809372901916504} +Cheakpoint... +Epoch [1976/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715034365653992, 'Val/mean miou_metric': 0.9547499418258667, 'Val/mean f1': 0.9740380644798279, 'Val/mean precision': 0.9722076654434204, 'Val/mean recall': 0.9758754372596741, 'Val/mean hd95_metric': 5.809372901916504} +Epoch [1977/4000] Training [1/16] Loss: 0.00644 +Epoch [1977/4000] Training [2/16] Loss: 0.00487 +Epoch [1977/4000] Training [3/16] Loss: 0.00666 +Epoch [1977/4000] Training [4/16] Loss: 0.00535 +Epoch [1977/4000] Training [5/16] Loss: 0.01202 +Epoch [1977/4000] Training [6/16] Loss: 0.00594 +Epoch [1977/4000] Training [7/16] Loss: 0.00578 +Epoch [1977/4000] Training [8/16] Loss: 0.00779 +Epoch [1977/4000] Training [9/16] Loss: 0.00595 +Epoch [1977/4000] Training [10/16] Loss: 0.00605 +Epoch [1977/4000] Training [11/16] Loss: 0.00596 +Epoch [1977/4000] Training [12/16] Loss: 0.00495 +Epoch [1977/4000] Training [13/16] Loss: 0.00624 +Epoch [1977/4000] Training [14/16] Loss: 0.00531 +Epoch [1977/4000] Training [15/16] Loss: 0.00602 +Epoch [1977/4000] Training [16/16] Loss: 0.00605 +Epoch [1977/4000] Training metric {'Train/mean dice_metric': 0.9961720705032349, 'Train/mean miou_metric': 0.9921144247055054, 'Train/mean f1': 0.9919384121894836, 'Train/mean precision': 0.9875588417053223, 'Train/mean recall': 0.9963569045066833, 'Train/mean hd95_metric': 1.0067691802978516} +Epoch [1977/4000] Validation [1/4] Loss: 0.32418 focal_loss 0.24926 dice_loss 0.07491 +Epoch [1977/4000] Validation [2/4] Loss: 0.36624 focal_loss 0.24181 dice_loss 0.12443 +Epoch [1977/4000] Validation [3/4] Loss: 0.37196 focal_loss 0.26770 dice_loss 0.10426 +Epoch [1977/4000] Validation [4/4] Loss: 0.23885 focal_loss 0.13912 dice_loss 0.09973 +Epoch [1977/4000] Validation metric {'Val/mean dice_metric': 0.9715415835380554, 'Val/mean miou_metric': 0.9548614621162415, 'Val/mean f1': 0.9738231301307678, 'Val/mean precision': 0.9726043343544006, 'Val/mean recall': 0.9750449657440186, 'Val/mean hd95_metric': 5.526252746582031} +Cheakpoint... +Epoch [1977/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715415835380554, 'Val/mean miou_metric': 0.9548614621162415, 'Val/mean f1': 0.9738231301307678, 'Val/mean precision': 0.9726043343544006, 'Val/mean recall': 0.9750449657440186, 'Val/mean hd95_metric': 5.526252746582031} +Epoch [1978/4000] Training [1/16] Loss: 0.00693 +Epoch [1978/4000] Training [2/16] Loss: 0.00424 +Epoch [1978/4000] Training [3/16] Loss: 0.00613 +Epoch [1978/4000] Training [4/16] Loss: 0.00456 +Epoch [1978/4000] Training [5/16] Loss: 0.00638 +Epoch [1978/4000] Training [6/16] Loss: 0.00751 +Epoch [1978/4000] Training [7/16] Loss: 0.00731 +Epoch [1978/4000] Training [8/16] Loss: 0.00806 +Epoch [1978/4000] Training [9/16] Loss: 0.00554 +Epoch [1978/4000] Training [10/16] Loss: 0.00746 +Epoch [1978/4000] Training [11/16] Loss: 0.00465 +Epoch [1978/4000] Training [12/16] Loss: 0.00873 +Epoch [1978/4000] Training [13/16] Loss: 0.00575 +Epoch [1978/4000] Training [14/16] Loss: 0.00645 +Epoch [1978/4000] Training [15/16] Loss: 0.00658 +Epoch [1978/4000] Training [16/16] Loss: 0.00553 +Epoch [1978/4000] Training metric {'Train/mean dice_metric': 0.9955586791038513, 'Train/mean miou_metric': 0.9909056425094604, 'Train/mean f1': 0.991470456123352, 'Train/mean precision': 0.9867741465568542, 'Train/mean recall': 0.9962117075920105, 'Train/mean hd95_metric': 1.0449845790863037} +Epoch [1978/4000] Validation [1/4] Loss: 0.52345 focal_loss 0.41532 dice_loss 0.10813 +Epoch [1978/4000] Validation [2/4] Loss: 0.48345 focal_loss 0.30207 dice_loss 0.18138 +Epoch [1978/4000] Validation [3/4] Loss: 0.34766 focal_loss 0.24731 dice_loss 0.10035 +Epoch [1978/4000] Validation [4/4] Loss: 0.36035 focal_loss 0.22397 dice_loss 0.13638 +Epoch [1978/4000] Validation metric {'Val/mean dice_metric': 0.9695297479629517, 'Val/mean miou_metric': 0.9523088335990906, 'Val/mean f1': 0.9715009927749634, 'Val/mean precision': 0.9715192914009094, 'Val/mean recall': 0.9714826941490173, 'Val/mean hd95_metric': 5.667729377746582} +Cheakpoint... +Epoch [1978/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695297479629517, 'Val/mean miou_metric': 0.9523088335990906, 'Val/mean f1': 0.9715009927749634, 'Val/mean precision': 0.9715192914009094, 'Val/mean recall': 0.9714826941490173, 'Val/mean hd95_metric': 5.667729377746582} +Epoch [1979/4000] Training [1/16] Loss: 0.00708 +Epoch [1979/4000] Training [2/16] Loss: 0.00633 +Epoch [1979/4000] Training [3/16] Loss: 0.00639 +Epoch [1979/4000] Training [4/16] Loss: 0.00486 +Epoch [1979/4000] Training [5/16] Loss: 0.00509 +Epoch [1979/4000] Training [6/16] Loss: 0.00531 +Epoch [1979/4000] Training [7/16] Loss: 0.00597 +Epoch [1979/4000] Training [8/16] Loss: 0.00587 +Epoch [1979/4000] Training [9/16] Loss: 0.00800 +Epoch [1979/4000] Training [10/16] Loss: 0.00619 +Epoch [1979/4000] Training [11/16] Loss: 0.00500 +Epoch [1979/4000] Training [12/16] Loss: 0.00873 +Epoch [1979/4000] Training [13/16] Loss: 0.00616 +Epoch [1979/4000] Training [14/16] Loss: 0.00676 +Epoch [1979/4000] Training [15/16] Loss: 0.00535 +Epoch [1979/4000] Training [16/16] Loss: 0.00699 +Epoch [1979/4000] Training metric {'Train/mean dice_metric': 0.9959088563919067, 'Train/mean miou_metric': 0.9915982484817505, 'Train/mean f1': 0.9917951226234436, 'Train/mean precision': 0.9873688817024231, 'Train/mean recall': 0.9962611794471741, 'Train/mean hd95_metric': 1.0145411491394043} +Epoch [1979/4000] Validation [1/4] Loss: 0.27256 focal_loss 0.20553 dice_loss 0.06703 +Epoch [1979/4000] Validation [2/4] Loss: 0.56689 focal_loss 0.38902 dice_loss 0.17787 +Epoch [1979/4000] Validation [3/4] Loss: 0.33563 focal_loss 0.23143 dice_loss 0.10420 +Epoch [1979/4000] Validation [4/4] Loss: 0.28306 focal_loss 0.18432 dice_loss 0.09874 +Epoch [1979/4000] Validation metric {'Val/mean dice_metric': 0.9711054563522339, 'Val/mean miou_metric': 0.9542236328125, 'Val/mean f1': 0.9739350080490112, 'Val/mean precision': 0.9710647463798523, 'Val/mean recall': 0.9768222570419312, 'Val/mean hd95_metric': 5.616866111755371} +Cheakpoint... +Epoch [1979/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711054563522339, 'Val/mean miou_metric': 0.9542236328125, 'Val/mean f1': 0.9739350080490112, 'Val/mean precision': 0.9710647463798523, 'Val/mean recall': 0.9768222570419312, 'Val/mean hd95_metric': 5.616866111755371} +Epoch [1980/4000] Training [1/16] Loss: 0.00535 +Epoch [1980/4000] Training [2/16] Loss: 0.00641 +Epoch [1980/4000] Training [3/16] Loss: 0.00597 +Epoch [1980/4000] Training [4/16] Loss: 0.00700 +Epoch [1980/4000] Training [5/16] Loss: 0.00586 +Epoch [1980/4000] Training [6/16] Loss: 0.00472 +Epoch [1980/4000] Training [7/16] Loss: 0.00509 +Epoch [1980/4000] Training [8/16] Loss: 0.00489 +Epoch [1980/4000] Training [9/16] Loss: 0.00677 +Epoch [1980/4000] Training [10/16] Loss: 0.00693 +Epoch [1980/4000] Training [11/16] Loss: 0.00511 +Epoch [1980/4000] Training [12/16] Loss: 0.00590 +Epoch [1980/4000] Training [13/16] Loss: 0.00516 +Epoch [1980/4000] Training [14/16] Loss: 0.00520 +Epoch [1980/4000] Training [15/16] Loss: 0.00510 +Epoch [1980/4000] Training [16/16] Loss: 0.00760 +Epoch [1980/4000] Training metric {'Train/mean dice_metric': 0.9960911870002747, 'Train/mean miou_metric': 0.9919438362121582, 'Train/mean f1': 0.9916877746582031, 'Train/mean precision': 0.9870701432228088, 'Train/mean recall': 0.9963487982749939, 'Train/mean hd95_metric': 1.0250167846679688} +Epoch [1980/4000] Validation [1/4] Loss: 0.30609 focal_loss 0.23612 dice_loss 0.06997 +Epoch [1980/4000] Validation [2/4] Loss: 0.37680 focal_loss 0.24082 dice_loss 0.13598 +Epoch [1980/4000] Validation [3/4] Loss: 0.35185 focal_loss 0.25485 dice_loss 0.09700 +Epoch [1980/4000] Validation [4/4] Loss: 0.47065 focal_loss 0.32773 dice_loss 0.14292 +Epoch [1980/4000] Validation metric {'Val/mean dice_metric': 0.9717524647712708, 'Val/mean miou_metric': 0.9550298452377319, 'Val/mean f1': 0.973827600479126, 'Val/mean precision': 0.9722683429718018, 'Val/mean recall': 0.9753919243812561, 'Val/mean hd95_metric': 5.54749059677124} +Cheakpoint... +Epoch [1980/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717524647712708, 'Val/mean miou_metric': 0.9550298452377319, 'Val/mean f1': 0.973827600479126, 'Val/mean precision': 0.9722683429718018, 'Val/mean recall': 0.9753919243812561, 'Val/mean hd95_metric': 5.54749059677124} +Epoch [1981/4000] Training [1/16] Loss: 0.00735 +Epoch [1981/4000] Training [2/16] Loss: 0.00747 +Epoch [1981/4000] Training [3/16] Loss: 0.00582 +Epoch [1981/4000] Training [4/16] Loss: 0.00531 +Epoch [1981/4000] Training [5/16] Loss: 0.00837 +Epoch [1981/4000] Training [6/16] Loss: 0.00485 +Epoch [1981/4000] Training [7/16] Loss: 0.00653 +Epoch [1981/4000] Training [8/16] Loss: 0.00735 +Epoch [1981/4000] Training [9/16] Loss: 0.00863 +Epoch [1981/4000] Training [10/16] Loss: 0.01230 +Epoch [1981/4000] Training [11/16] Loss: 0.00732 +Epoch [1981/4000] Training [12/16] Loss: 0.00830 +Epoch [1981/4000] Training [13/16] Loss: 0.00527 +Epoch [1981/4000] Training [14/16] Loss: 0.00610 +Epoch [1981/4000] Training [15/16] Loss: 0.00605 +Epoch [1981/4000] Training [16/16] Loss: 0.00687 +Epoch [1981/4000] Training metric {'Train/mean dice_metric': 0.995658278465271, 'Train/mean miou_metric': 0.9910696744918823, 'Train/mean f1': 0.9909681081771851, 'Train/mean precision': 0.9860866069793701, 'Train/mean recall': 0.9958981871604919, 'Train/mean hd95_metric': 1.0673092603683472} +Epoch [1981/4000] Validation [1/4] Loss: 0.29979 focal_loss 0.22675 dice_loss 0.07304 +Epoch [1981/4000] Validation [2/4] Loss: 0.54903 focal_loss 0.35619 dice_loss 0.19284 +Epoch [1981/4000] Validation [3/4] Loss: 0.18523 focal_loss 0.12805 dice_loss 0.05718 +Epoch [1981/4000] Validation [4/4] Loss: 0.21702 focal_loss 0.13476 dice_loss 0.08226 +Epoch [1981/4000] Validation metric {'Val/mean dice_metric': 0.9716426730155945, 'Val/mean miou_metric': 0.9552319645881653, 'Val/mean f1': 0.9731611609458923, 'Val/mean precision': 0.9695615768432617, 'Val/mean recall': 0.9767875671386719, 'Val/mean hd95_metric': 5.1604084968566895} +Cheakpoint... +Epoch [1981/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716426730155945, 'Val/mean miou_metric': 0.9552319645881653, 'Val/mean f1': 0.9731611609458923, 'Val/mean precision': 0.9695615768432617, 'Val/mean recall': 0.9767875671386719, 'Val/mean hd95_metric': 5.1604084968566895} +Epoch [1982/4000] Training [1/16] Loss: 0.00523 +Epoch [1982/4000] Training [2/16] Loss: 0.00577 +Epoch [1982/4000] Training [3/16] Loss: 0.00783 +Epoch [1982/4000] Training [4/16] Loss: 0.00555 +Epoch [1982/4000] Training [5/16] Loss: 0.00692 +Epoch [1982/4000] Training [6/16] Loss: 0.00568 +Epoch [1982/4000] Training [7/16] Loss: 0.02224 +Epoch [1982/4000] Training [8/16] Loss: 0.00787 +Epoch [1982/4000] Training [9/16] Loss: 0.00640 +Epoch [1982/4000] Training [10/16] Loss: 0.00513 +Epoch [1982/4000] Training [11/16] Loss: 0.00687 +Epoch [1982/4000] Training [12/16] Loss: 0.01209 +Epoch [1982/4000] Training [13/16] Loss: 0.00587 +Epoch [1982/4000] Training [14/16] Loss: 0.00540 +Epoch [1982/4000] Training [15/16] Loss: 0.00438 +Epoch [1982/4000] Training [16/16] Loss: 0.00618 +Epoch [1982/4000] Training metric {'Train/mean dice_metric': 0.9955938458442688, 'Train/mean miou_metric': 0.9909510612487793, 'Train/mean f1': 0.990630030632019, 'Train/mean precision': 0.9853197336196899, 'Train/mean recall': 0.9959978461265564, 'Train/mean hd95_metric': 1.0428184270858765} +Epoch [1982/4000] Validation [1/4] Loss: 0.43037 focal_loss 0.34147 dice_loss 0.08890 +Epoch [1982/4000] Validation [2/4] Loss: 0.55416 focal_loss 0.36931 dice_loss 0.18485 +Epoch [1982/4000] Validation [3/4] Loss: 0.16949 focal_loss 0.11460 dice_loss 0.05490 +Epoch [1982/4000] Validation [4/4] Loss: 0.36766 focal_loss 0.23944 dice_loss 0.12822 +Epoch [1982/4000] Validation metric {'Val/mean dice_metric': 0.9700745344161987, 'Val/mean miou_metric': 0.9529303312301636, 'Val/mean f1': 0.9713017344474792, 'Val/mean precision': 0.9706346988677979, 'Val/mean recall': 0.9719696044921875, 'Val/mean hd95_metric': 5.482517242431641} +Cheakpoint... +Epoch [1982/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700745344161987, 'Val/mean miou_metric': 0.9529303312301636, 'Val/mean f1': 0.9713017344474792, 'Val/mean precision': 0.9706346988677979, 'Val/mean recall': 0.9719696044921875, 'Val/mean hd95_metric': 5.482517242431641} +Epoch [1983/4000] Training [1/16] Loss: 0.00637 +Epoch [1983/4000] Training [2/16] Loss: 0.00588 +Epoch [1983/4000] Training [3/16] Loss: 0.00518 +Epoch [1983/4000] Training [4/16] Loss: 0.00589 +Epoch [1983/4000] Training [5/16] Loss: 0.00732 +Epoch [1983/4000] Training [6/16] Loss: 0.00616 +Epoch [1983/4000] Training [7/16] Loss: 0.00673 +Epoch [1983/4000] Training [8/16] Loss: 0.00461 +Epoch [1983/4000] Training [9/16] Loss: 0.00597 +Epoch [1983/4000] Training [10/16] Loss: 0.00467 +Epoch [1983/4000] Training [11/16] Loss: 0.00514 +Epoch [1983/4000] Training [12/16] Loss: 0.00474 +Epoch [1983/4000] Training [13/16] Loss: 0.00564 +Epoch [1983/4000] Training [14/16] Loss: 0.00564 +Epoch [1983/4000] Training [15/16] Loss: 0.00558 +Epoch [1983/4000] Training [16/16] Loss: 0.00568 +Epoch [1983/4000] Training metric {'Train/mean dice_metric': 0.996221125125885, 'Train/mean miou_metric': 0.9921934604644775, 'Train/mean f1': 0.9914416670799255, 'Train/mean precision': 0.9865281581878662, 'Train/mean recall': 0.9964044094085693, 'Train/mean hd95_metric': 1.039603352546692} +Epoch [1983/4000] Validation [1/4] Loss: 0.32158 focal_loss 0.24378 dice_loss 0.07780 +Epoch [1983/4000] Validation [2/4] Loss: 0.52047 focal_loss 0.33724 dice_loss 0.18323 +Epoch [1983/4000] Validation [3/4] Loss: 0.28934 focal_loss 0.19871 dice_loss 0.09063 +Epoch [1983/4000] Validation [4/4] Loss: 0.43803 focal_loss 0.32034 dice_loss 0.11769 +Epoch [1983/4000] Validation metric {'Val/mean dice_metric': 0.9720419049263, 'Val/mean miou_metric': 0.9559314846992493, 'Val/mean f1': 0.973549485206604, 'Val/mean precision': 0.9721132516860962, 'Val/mean recall': 0.9749897718429565, 'Val/mean hd95_metric': 5.754472255706787} +Cheakpoint... +Epoch [1983/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720419049263, 'Val/mean miou_metric': 0.9559314846992493, 'Val/mean f1': 0.973549485206604, 'Val/mean precision': 0.9721132516860962, 'Val/mean recall': 0.9749897718429565, 'Val/mean hd95_metric': 5.754472255706787} +Epoch [1984/4000] Training [1/16] Loss: 0.00667 +Epoch [1984/4000] Training [2/16] Loss: 0.00468 +Epoch [1984/4000] Training [3/16] Loss: 0.00530 +Epoch [1984/4000] Training [4/16] Loss: 0.00618 +Epoch [1984/4000] Training [5/16] Loss: 0.00658 +Epoch [1984/4000] Training [6/16] Loss: 0.01041 +Epoch [1984/4000] Training [7/16] Loss: 0.00456 +Epoch [1984/4000] Training [8/16] Loss: 0.00576 +Epoch [1984/4000] Training [9/16] Loss: 0.00855 +Epoch [1984/4000] Training [10/16] Loss: 0.01092 +Epoch [1984/4000] Training [11/16] Loss: 0.00841 +Epoch [1984/4000] Training [12/16] Loss: 0.00770 +Epoch [1984/4000] Training [13/16] Loss: 0.00681 +Epoch [1984/4000] Training [14/16] Loss: 0.00543 +Epoch [1984/4000] Training [15/16] Loss: 0.00652 +Epoch [1984/4000] Training [16/16] Loss: 0.00646 +Epoch [1984/4000] Training metric {'Train/mean dice_metric': 0.9955788254737854, 'Train/mean miou_metric': 0.9909558892250061, 'Train/mean f1': 0.9914948344230652, 'Train/mean precision': 0.9869841933250427, 'Train/mean recall': 0.9960469007492065, 'Train/mean hd95_metric': 1.109729528427124} +Epoch [1984/4000] Validation [1/4] Loss: 0.46239 focal_loss 0.36550 dice_loss 0.09689 +Epoch [1984/4000] Validation [2/4] Loss: 0.41295 focal_loss 0.25075 dice_loss 0.16220 +Epoch [1984/4000] Validation [3/4] Loss: 0.21779 focal_loss 0.14563 dice_loss 0.07216 +Epoch [1984/4000] Validation [4/4] Loss: 0.28889 focal_loss 0.18373 dice_loss 0.10516 +Epoch [1984/4000] Validation metric {'Val/mean dice_metric': 0.9710434079170227, 'Val/mean miou_metric': 0.9538652300834656, 'Val/mean f1': 0.9721014499664307, 'Val/mean precision': 0.9727952480316162, 'Val/mean recall': 0.9714086055755615, 'Val/mean hd95_metric': 5.564123153686523} +Cheakpoint... +Epoch [1984/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710434079170227, 'Val/mean miou_metric': 0.9538652300834656, 'Val/mean f1': 0.9721014499664307, 'Val/mean precision': 0.9727952480316162, 'Val/mean recall': 0.9714086055755615, 'Val/mean hd95_metric': 5.564123153686523} +Epoch [1985/4000] Training [1/16] Loss: 0.00557 +Epoch [1985/4000] Training [2/16] Loss: 0.00596 +Epoch [1985/4000] Training [3/16] Loss: 0.00768 +Epoch [1985/4000] Training [4/16] Loss: 0.00574 +Epoch [1985/4000] Training [5/16] Loss: 0.00646 +Epoch [1985/4000] Training [6/16] Loss: 0.00526 +Epoch [1985/4000] Training [7/16] Loss: 0.01151 +Epoch [1985/4000] Training [8/16] Loss: 0.00506 +Epoch [1985/4000] Training [9/16] Loss: 0.00664 +Epoch [1985/4000] Training [10/16] Loss: 0.00481 +Epoch [1985/4000] Training [11/16] Loss: 0.00695 +Epoch [1985/4000] Training [12/16] Loss: 0.00790 +Epoch [1985/4000] Training [13/16] Loss: 0.00708 +Epoch [1985/4000] Training [14/16] Loss: 0.00578 +Epoch [1985/4000] Training [15/16] Loss: 0.00451 +Epoch [1985/4000] Training [16/16] Loss: 0.00569 +Epoch [1985/4000] Training metric {'Train/mean dice_metric': 0.9957676529884338, 'Train/mean miou_metric': 0.9913217425346375, 'Train/mean f1': 0.991629421710968, 'Train/mean precision': 0.9870117902755737, 'Train/mean recall': 0.9962904453277588, 'Train/mean hd95_metric': 1.0121887922286987} +Epoch [1985/4000] Validation [1/4] Loss: 0.28920 focal_loss 0.22162 dice_loss 0.06757 +Epoch [1985/4000] Validation [2/4] Loss: 0.49251 focal_loss 0.33133 dice_loss 0.16118 +Epoch [1985/4000] Validation [3/4] Loss: 0.29238 focal_loss 0.20334 dice_loss 0.08905 +Epoch [1985/4000] Validation [4/4] Loss: 0.26077 focal_loss 0.15436 dice_loss 0.10641 +Epoch [1985/4000] Validation metric {'Val/mean dice_metric': 0.9723323583602905, 'Val/mean miou_metric': 0.9556756019592285, 'Val/mean f1': 0.9739372134208679, 'Val/mean precision': 0.9713249206542969, 'Val/mean recall': 0.9765636920928955, 'Val/mean hd95_metric': 5.253093719482422} +Cheakpoint... +Epoch [1985/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723323583602905, 'Val/mean miou_metric': 0.9556756019592285, 'Val/mean f1': 0.9739372134208679, 'Val/mean precision': 0.9713249206542969, 'Val/mean recall': 0.9765636920928955, 'Val/mean hd95_metric': 5.253093719482422} +Epoch [1986/4000] Training [1/16] Loss: 0.00559 +Epoch [1986/4000] Training [2/16] Loss: 0.00625 +Epoch [1986/4000] Training [3/16] Loss: 0.00656 +Epoch [1986/4000] Training [4/16] Loss: 0.00512 +Epoch [1986/4000] Training [5/16] Loss: 0.00794 +Epoch [1986/4000] Training [6/16] Loss: 0.00476 +Epoch [1986/4000] Training [7/16] Loss: 0.00524 +Epoch [1986/4000] Training [8/16] Loss: 0.00798 +Epoch [1986/4000] Training [9/16] Loss: 0.00535 +Epoch [1986/4000] Training [10/16] Loss: 0.00531 +Epoch [1986/4000] Training [11/16] Loss: 0.00676 +Epoch [1986/4000] Training [12/16] Loss: 0.00444 +Epoch [1986/4000] Training [13/16] Loss: 0.00701 +Epoch [1986/4000] Training [14/16] Loss: 0.00577 +Epoch [1986/4000] Training [15/16] Loss: 0.00673 +Epoch [1986/4000] Training [16/16] Loss: 0.00635 +Epoch [1986/4000] Training metric {'Train/mean dice_metric': 0.9955935478210449, 'Train/mean miou_metric': 0.9910736083984375, 'Train/mean f1': 0.9910604953765869, 'Train/mean precision': 0.9863986968994141, 'Train/mean recall': 0.9957665205001831, 'Train/mean hd95_metric': 1.0870294570922852} +Epoch [1986/4000] Validation [1/4] Loss: 0.35064 focal_loss 0.27530 dice_loss 0.07534 +Epoch [1986/4000] Validation [2/4] Loss: 0.29000 focal_loss 0.18538 dice_loss 0.10463 +Epoch [1986/4000] Validation [3/4] Loss: 0.18070 focal_loss 0.12251 dice_loss 0.05819 +Epoch [1986/4000] Validation [4/4] Loss: 0.29183 focal_loss 0.18054 dice_loss 0.11129 +Epoch [1986/4000] Validation metric {'Val/mean dice_metric': 0.9712114334106445, 'Val/mean miou_metric': 0.9544219970703125, 'Val/mean f1': 0.9732040762901306, 'Val/mean precision': 0.9718859195709229, 'Val/mean recall': 0.9745258688926697, 'Val/mean hd95_metric': 5.300538539886475} +Cheakpoint... +Epoch [1986/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712114334106445, 'Val/mean miou_metric': 0.9544219970703125, 'Val/mean f1': 0.9732040762901306, 'Val/mean precision': 0.9718859195709229, 'Val/mean recall': 0.9745258688926697, 'Val/mean hd95_metric': 5.300538539886475} +Epoch [1987/4000] Training [1/16] Loss: 0.00826 +Epoch [1987/4000] Training [2/16] Loss: 0.00735 +Epoch [1987/4000] Training [3/16] Loss: 0.00587 +Epoch [1987/4000] Training [4/16] Loss: 0.00443 +Epoch [1987/4000] Training [5/16] Loss: 0.00771 +Epoch [1987/4000] Training [6/16] Loss: 0.00782 +Epoch [1987/4000] Training [7/16] Loss: 0.00847 +Epoch [1987/4000] Training [8/16] Loss: 0.00623 +Epoch [1987/4000] Training [9/16] Loss: 0.00623 +Epoch [1987/4000] Training [10/16] Loss: 0.00554 +Epoch [1987/4000] Training [11/16] Loss: 0.00649 +Epoch [1987/4000] Training [12/16] Loss: 0.00552 +Epoch [1987/4000] Training [13/16] Loss: 0.00769 +Epoch [1987/4000] Training [14/16] Loss: 0.00653 +Epoch [1987/4000] Training [15/16] Loss: 0.00561 +Epoch [1987/4000] Training [16/16] Loss: 0.00731 +Epoch [1987/4000] Training metric {'Train/mean dice_metric': 0.9957093000411987, 'Train/mean miou_metric': 0.9912026524543762, 'Train/mean f1': 0.9915374517440796, 'Train/mean precision': 0.9871351718902588, 'Train/mean recall': 0.9959791898727417, 'Train/mean hd95_metric': 1.0157063007354736} +Epoch [1987/4000] Validation [1/4] Loss: 0.31340 focal_loss 0.23841 dice_loss 0.07498 +Epoch [1987/4000] Validation [2/4] Loss: 0.29082 focal_loss 0.16153 dice_loss 0.12929 +Epoch [1987/4000] Validation [3/4] Loss: 0.29236 focal_loss 0.20275 dice_loss 0.08961 +Epoch [1987/4000] Validation [4/4] Loss: 0.55389 focal_loss 0.42707 dice_loss 0.12682 +Epoch [1987/4000] Validation metric {'Val/mean dice_metric': 0.9695731997489929, 'Val/mean miou_metric': 0.9527274966239929, 'Val/mean f1': 0.9723894000053406, 'Val/mean precision': 0.9709122180938721, 'Val/mean recall': 0.9738710522651672, 'Val/mean hd95_metric': 6.1767425537109375} +Cheakpoint... +Epoch [1987/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695731997489929, 'Val/mean miou_metric': 0.9527274966239929, 'Val/mean f1': 0.9723894000053406, 'Val/mean precision': 0.9709122180938721, 'Val/mean recall': 0.9738710522651672, 'Val/mean hd95_metric': 6.1767425537109375} +Epoch [1988/4000] Training [1/16] Loss: 0.00483 +Epoch [1988/4000] Training [2/16] Loss: 0.00640 +Epoch [1988/4000] Training [3/16] Loss: 0.00526 +Epoch [1988/4000] Training [4/16] Loss: 0.00778 +Epoch [1988/4000] Training [5/16] Loss: 0.00624 +Epoch [1988/4000] Training [6/16] Loss: 0.01725 +Epoch [1988/4000] Training [7/16] Loss: 0.00550 +Epoch [1988/4000] Training [8/16] Loss: 0.00648 +Epoch [1988/4000] Training [9/16] Loss: 0.00614 +Epoch [1988/4000] Training [10/16] Loss: 0.00889 +Epoch [1988/4000] Training [11/16] Loss: 0.00613 +Epoch [1988/4000] Training [12/16] Loss: 0.00628 +Epoch [1988/4000] Training [13/16] Loss: 0.00546 +Epoch [1988/4000] Training [14/16] Loss: 0.00497 +Epoch [1988/4000] Training [15/16] Loss: 0.00467 +Epoch [1988/4000] Training [16/16] Loss: 0.00784 +Epoch [1988/4000] Training metric {'Train/mean dice_metric': 0.9959324598312378, 'Train/mean miou_metric': 0.9916512966156006, 'Train/mean f1': 0.9915624260902405, 'Train/mean precision': 0.986977756023407, 'Train/mean recall': 0.9961898326873779, 'Train/mean hd95_metric': 1.0610072612762451} +Epoch [1988/4000] Validation [1/4] Loss: 0.29282 focal_loss 0.22149 dice_loss 0.07133 +Epoch [1988/4000] Validation [2/4] Loss: 0.21027 focal_loss 0.11669 dice_loss 0.09358 +Epoch [1988/4000] Validation [3/4] Loss: 0.19188 focal_loss 0.13455 dice_loss 0.05733 +Epoch [1988/4000] Validation [4/4] Loss: 0.24766 focal_loss 0.15201 dice_loss 0.09565 +Epoch [1988/4000] Validation metric {'Val/mean dice_metric': 0.9740012884140015, 'Val/mean miou_metric': 0.9576464891433716, 'Val/mean f1': 0.9748564958572388, 'Val/mean precision': 0.9711359143257141, 'Val/mean recall': 0.9786056876182556, 'Val/mean hd95_metric': 5.125616073608398} +Cheakpoint... +Epoch [1988/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740012884140015, 'Val/mean miou_metric': 0.9576464891433716, 'Val/mean f1': 0.9748564958572388, 'Val/mean precision': 0.9711359143257141, 'Val/mean recall': 0.9786056876182556, 'Val/mean hd95_metric': 5.125616073608398} +Epoch [1989/4000] Training [1/16] Loss: 0.00903 +Epoch [1989/4000] Training [2/16] Loss: 0.00555 +Epoch [1989/4000] Training [3/16] Loss: 0.00801 +Epoch [1989/4000] Training [4/16] Loss: 0.00845 +Epoch [1989/4000] Training [5/16] Loss: 0.00919 +Epoch [1989/4000] Training [6/16] Loss: 0.00610 +Epoch [1989/4000] Training [7/16] Loss: 0.00711 +Epoch [1989/4000] Training [8/16] Loss: 0.00649 +Epoch [1989/4000] Training [9/16] Loss: 0.00626 +Epoch [1989/4000] Training [10/16] Loss: 0.00482 +Epoch [1989/4000] Training [11/16] Loss: 0.00588 +Epoch [1989/4000] Training [12/16] Loss: 0.00689 +Epoch [1989/4000] Training [13/16] Loss: 0.00500 +Epoch [1989/4000] Training [14/16] Loss: 0.00596 +Epoch [1989/4000] Training [15/16] Loss: 0.00605 +Epoch [1989/4000] Training [16/16] Loss: 0.00618 +Epoch [1989/4000] Training metric {'Train/mean dice_metric': 0.9958139061927795, 'Train/mean miou_metric': 0.9913930892944336, 'Train/mean f1': 0.9913095831871033, 'Train/mean precision': 0.9865599870681763, 'Train/mean recall': 0.9961051940917969, 'Train/mean hd95_metric': 1.023084044456482} +Epoch [1989/4000] Validation [1/4] Loss: 0.26300 focal_loss 0.20275 dice_loss 0.06025 +Epoch [1989/4000] Validation [2/4] Loss: 0.52456 focal_loss 0.33673 dice_loss 0.18783 +Epoch [1989/4000] Validation [3/4] Loss: 0.36978 focal_loss 0.27693 dice_loss 0.09285 +Epoch [1989/4000] Validation [4/4] Loss: 0.23142 focal_loss 0.13616 dice_loss 0.09527 +Epoch [1989/4000] Validation metric {'Val/mean dice_metric': 0.9719963073730469, 'Val/mean miou_metric': 0.9560114741325378, 'Val/mean f1': 0.9736912846565247, 'Val/mean precision': 0.9701926112174988, 'Val/mean recall': 0.9772152304649353, 'Val/mean hd95_metric': 5.5359086990356445} +Cheakpoint... +Epoch [1989/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719963073730469, 'Val/mean miou_metric': 0.9560114741325378, 'Val/mean f1': 0.9736912846565247, 'Val/mean precision': 0.9701926112174988, 'Val/mean recall': 0.9772152304649353, 'Val/mean hd95_metric': 5.5359086990356445} +Epoch [1990/4000] Training [1/16] Loss: 0.00516 +Epoch [1990/4000] Training [2/16] Loss: 0.00616 +Epoch [1990/4000] Training [3/16] Loss: 0.00517 +Epoch [1990/4000] Training [4/16] Loss: 0.00706 +Epoch [1990/4000] Training [5/16] Loss: 0.00774 +Epoch [1990/4000] Training [6/16] Loss: 0.00668 +Epoch [1990/4000] Training [7/16] Loss: 0.00788 +Epoch [1990/4000] Training [8/16] Loss: 0.00554 +Epoch [1990/4000] Training [9/16] Loss: 0.00560 +Epoch [1990/4000] Training [10/16] Loss: 0.00599 +Epoch [1990/4000] Training [11/16] Loss: 0.00739 +Epoch [1990/4000] Training [12/16] Loss: 0.00532 +Epoch [1990/4000] Training [13/16] Loss: 0.00479 +Epoch [1990/4000] Training [14/16] Loss: 0.00742 +Epoch [1990/4000] Training [15/16] Loss: 0.00544 +Epoch [1990/4000] Training [16/16] Loss: 0.00563 +Epoch [1990/4000] Training metric {'Train/mean dice_metric': 0.9960323572158813, 'Train/mean miou_metric': 0.9918339848518372, 'Train/mean f1': 0.9917935729026794, 'Train/mean precision': 0.9872506260871887, 'Train/mean recall': 0.9963785409927368, 'Train/mean hd95_metric': 1.013110637664795} +Epoch [1990/4000] Validation [1/4] Loss: 0.29770 focal_loss 0.22846 dice_loss 0.06924 +Epoch [1990/4000] Validation [2/4] Loss: 0.21457 focal_loss 0.12752 dice_loss 0.08705 +Epoch [1990/4000] Validation [3/4] Loss: 0.40137 focal_loss 0.30541 dice_loss 0.09596 +Epoch [1990/4000] Validation [4/4] Loss: 0.28879 focal_loss 0.18750 dice_loss 0.10129 +Epoch [1990/4000] Validation metric {'Val/mean dice_metric': 0.9730434417724609, 'Val/mean miou_metric': 0.9561834335327148, 'Val/mean f1': 0.9741883873939514, 'Val/mean precision': 0.9707117080688477, 'Val/mean recall': 0.9776899814605713, 'Val/mean hd95_metric': 6.131664276123047} +Cheakpoint... +Epoch [1990/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730434417724609, 'Val/mean miou_metric': 0.9561834335327148, 'Val/mean f1': 0.9741883873939514, 'Val/mean precision': 0.9707117080688477, 'Val/mean recall': 0.9776899814605713, 'Val/mean hd95_metric': 6.131664276123047} +Epoch [1991/4000] Training [1/16] Loss: 0.00617 +Epoch [1991/4000] Training [2/16] Loss: 0.00485 +Epoch [1991/4000] Training [3/16] Loss: 0.00479 +Epoch [1991/4000] Training [4/16] Loss: 0.00804 +Epoch [1991/4000] Training [5/16] Loss: 0.00682 +Epoch [1991/4000] Training [6/16] Loss: 0.00665 +Epoch [1991/4000] Training [7/16] Loss: 0.00595 +Epoch [1991/4000] Training [8/16] Loss: 0.00538 +Epoch [1991/4000] Training [9/16] Loss: 0.00604 +Epoch [1991/4000] Training [10/16] Loss: 0.00552 +Epoch [1991/4000] Training [11/16] Loss: 0.00681 +Epoch [1991/4000] Training [12/16] Loss: 0.00615 +Epoch [1991/4000] Training [13/16] Loss: 0.00568 +Epoch [1991/4000] Training [14/16] Loss: 0.00557 +Epoch [1991/4000] Training [15/16] Loss: 0.00479 +Epoch [1991/4000] Training [16/16] Loss: 0.00533 +Epoch [1991/4000] Training metric {'Train/mean dice_metric': 0.9962552785873413, 'Train/mean miou_metric': 0.9922753572463989, 'Train/mean f1': 0.9917977452278137, 'Train/mean precision': 0.9871801733970642, 'Train/mean recall': 0.9964587092399597, 'Train/mean hd95_metric': 1.0476386547088623} +Epoch [1991/4000] Validation [1/4] Loss: 0.26578 focal_loss 0.20056 dice_loss 0.06521 +Epoch [1991/4000] Validation [2/4] Loss: 0.19971 focal_loss 0.11517 dice_loss 0.08455 +Epoch [1991/4000] Validation [3/4] Loss: 0.36770 focal_loss 0.27618 dice_loss 0.09152 +Epoch [1991/4000] Validation [4/4] Loss: 0.37656 focal_loss 0.25356 dice_loss 0.12300 +Epoch [1991/4000] Validation metric {'Val/mean dice_metric': 0.9735572934150696, 'Val/mean miou_metric': 0.9572302103042603, 'Val/mean f1': 0.9745499491691589, 'Val/mean precision': 0.9705696702003479, 'Val/mean recall': 0.9785628914833069, 'Val/mean hd95_metric': 5.795104026794434} +Cheakpoint... +Epoch [1991/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735572934150696, 'Val/mean miou_metric': 0.9572302103042603, 'Val/mean f1': 0.9745499491691589, 'Val/mean precision': 0.9705696702003479, 'Val/mean recall': 0.9785628914833069, 'Val/mean hd95_metric': 5.795104026794434} +Epoch [1992/4000] Training [1/16] Loss: 0.00680 +Epoch [1992/4000] Training [2/16] Loss: 0.00610 +Epoch [1992/4000] Training [3/16] Loss: 0.00475 +Epoch [1992/4000] Training [4/16] Loss: 0.00664 +Epoch [1992/4000] Training [5/16] Loss: 0.00544 +Epoch [1992/4000] Training [6/16] Loss: 0.00591 +Epoch [1992/4000] Training [7/16] Loss: 0.00527 +Epoch [1992/4000] Training [8/16] Loss: 0.00551 +Epoch [1992/4000] Training [9/16] Loss: 0.00674 +Epoch [1992/4000] Training [10/16] Loss: 0.00568 +Epoch [1992/4000] Training [11/16] Loss: 0.00609 +Epoch [1992/4000] Training [12/16] Loss: 0.00636 +Epoch [1992/4000] Training [13/16] Loss: 0.00580 +Epoch [1992/4000] Training [14/16] Loss: 0.00569 +Epoch [1992/4000] Training [15/16] Loss: 0.00576 +Epoch [1992/4000] Training [16/16] Loss: 0.00646 +Epoch [1992/4000] Training metric {'Train/mean dice_metric': 0.9960383176803589, 'Train/mean miou_metric': 0.9918175935745239, 'Train/mean f1': 0.9913009405136108, 'Train/mean precision': 0.9863674640655518, 'Train/mean recall': 0.996284008026123, 'Train/mean hd95_metric': 1.0033082962036133} +Epoch [1992/4000] Validation [1/4] Loss: 0.34066 focal_loss 0.26431 dice_loss 0.07635 +Epoch [1992/4000] Validation [2/4] Loss: 0.24589 focal_loss 0.14433 dice_loss 0.10156 +Epoch [1992/4000] Validation [3/4] Loss: 0.35048 focal_loss 0.25444 dice_loss 0.09604 +Epoch [1992/4000] Validation [4/4] Loss: 0.35762 focal_loss 0.24517 dice_loss 0.11245 +Epoch [1992/4000] Validation metric {'Val/mean dice_metric': 0.9734390377998352, 'Val/mean miou_metric': 0.9567057490348816, 'Val/mean f1': 0.9740474224090576, 'Val/mean precision': 0.9705783128738403, 'Val/mean recall': 0.9775413274765015, 'Val/mean hd95_metric': 5.435037136077881} +Cheakpoint... +Epoch [1992/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734390377998352, 'Val/mean miou_metric': 0.9567057490348816, 'Val/mean f1': 0.9740474224090576, 'Val/mean precision': 0.9705783128738403, 'Val/mean recall': 0.9775413274765015, 'Val/mean hd95_metric': 5.435037136077881} +Epoch [1993/4000] Training [1/16] Loss: 0.01526 +Epoch [1993/4000] Training [2/16] Loss: 0.00458 +Epoch [1993/4000] Training [3/16] Loss: 0.00740 +Epoch [1993/4000] Training [4/16] Loss: 0.00630 +Epoch [1993/4000] Training [5/16] Loss: 0.00577 +Epoch [1993/4000] Training [6/16] Loss: 0.00540 +Epoch [1993/4000] Training [7/16] Loss: 0.00487 +Epoch [1993/4000] Training [8/16] Loss: 0.00693 +Epoch [1993/4000] Training [9/16] Loss: 0.00636 +Epoch [1993/4000] Training [10/16] Loss: 0.00557 +Epoch [1993/4000] Training [11/16] Loss: 0.00551 +Epoch [1993/4000] Training [12/16] Loss: 0.00594 +Epoch [1993/4000] Training [13/16] Loss: 0.00575 +Epoch [1993/4000] Training [14/16] Loss: 0.00562 +Epoch [1993/4000] Training [15/16] Loss: 0.00574 +Epoch [1993/4000] Training [16/16] Loss: 0.00515 +Epoch [1993/4000] Training metric {'Train/mean dice_metric': 0.9957797527313232, 'Train/mean miou_metric': 0.9913327693939209, 'Train/mean f1': 0.9914709329605103, 'Train/mean precision': 0.986824631690979, 'Train/mean recall': 0.996161162853241, 'Train/mean hd95_metric': 1.0360944271087646} +Epoch [1993/4000] Validation [1/4] Loss: 0.29508 focal_loss 0.22660 dice_loss 0.06848 +Epoch [1993/4000] Validation [2/4] Loss: 0.25100 focal_loss 0.15303 dice_loss 0.09797 +Epoch [1993/4000] Validation [3/4] Loss: 0.40734 focal_loss 0.31191 dice_loss 0.09543 +Epoch [1993/4000] Validation [4/4] Loss: 0.20110 focal_loss 0.11389 dice_loss 0.08721 +Epoch [1993/4000] Validation metric {'Val/mean dice_metric': 0.975231945514679, 'Val/mean miou_metric': 0.9586651921272278, 'Val/mean f1': 0.9749060869216919, 'Val/mean precision': 0.9692538380622864, 'Val/mean recall': 0.9806246757507324, 'Val/mean hd95_metric': 5.881691932678223} +Cheakpoint... +Epoch [1993/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975231945514679, 'Val/mean miou_metric': 0.9586651921272278, 'Val/mean f1': 0.9749060869216919, 'Val/mean precision': 0.9692538380622864, 'Val/mean recall': 0.9806246757507324, 'Val/mean hd95_metric': 5.881691932678223} +Epoch [1994/4000] Training [1/16] Loss: 0.00604 +Epoch [1994/4000] Training [2/16] Loss: 0.00617 +Epoch [1994/4000] Training [3/16] Loss: 0.00642 +Epoch [1994/4000] Training [4/16] Loss: 0.00701 +Epoch [1994/4000] Training [5/16] Loss: 0.00521 +Epoch [1994/4000] Training [6/16] Loss: 0.00484 +Epoch [1994/4000] Training [7/16] Loss: 0.00685 +Epoch [1994/4000] Training [8/16] Loss: 0.00710 +Epoch [1994/4000] Training [9/16] Loss: 0.00628 +Epoch [1994/4000] Training [10/16] Loss: 0.00543 +Epoch [1994/4000] Training [11/16] Loss: 0.00586 +Epoch [1994/4000] Training [12/16] Loss: 0.00775 +Epoch [1994/4000] Training [13/16] Loss: 0.00486 +Epoch [1994/4000] Training [14/16] Loss: 0.00591 +Epoch [1994/4000] Training [15/16] Loss: 0.00750 +Epoch [1994/4000] Training [16/16] Loss: 0.00512 +Epoch [1994/4000] Training metric {'Train/mean dice_metric': 0.9959361553192139, 'Train/mean miou_metric': 0.9916282892227173, 'Train/mean f1': 0.9916077852249146, 'Train/mean precision': 0.9868953824043274, 'Train/mean recall': 0.996365487575531, 'Train/mean hd95_metric': 1.030113697052002} +Epoch [1994/4000] Validation [1/4] Loss: 0.22830 focal_loss 0.16814 dice_loss 0.06016 +Epoch [1994/4000] Validation [2/4] Loss: 0.33649 focal_loss 0.21345 dice_loss 0.12304 +Epoch [1994/4000] Validation [3/4] Loss: 0.36413 focal_loss 0.26855 dice_loss 0.09559 +Epoch [1994/4000] Validation [4/4] Loss: 0.29557 focal_loss 0.18354 dice_loss 0.11203 +Epoch [1994/4000] Validation metric {'Val/mean dice_metric': 0.9733583331108093, 'Val/mean miou_metric': 0.9570783376693726, 'Val/mean f1': 0.9745611548423767, 'Val/mean precision': 0.9700266122817993, 'Val/mean recall': 0.979138195514679, 'Val/mean hd95_metric': 5.782749176025391} +Cheakpoint... +Epoch [1994/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733583331108093, 'Val/mean miou_metric': 0.9570783376693726, 'Val/mean f1': 0.9745611548423767, 'Val/mean precision': 0.9700266122817993, 'Val/mean recall': 0.979138195514679, 'Val/mean hd95_metric': 5.782749176025391} +Epoch [1995/4000] Training [1/16] Loss: 0.00501 +Epoch [1995/4000] Training [2/16] Loss: 0.01021 +Epoch [1995/4000] Training [3/16] Loss: 0.00536 +Epoch [1995/4000] Training [4/16] Loss: 0.00837 +Epoch [1995/4000] Training [5/16] Loss: 0.00651 +Epoch [1995/4000] Training [6/16] Loss: 0.00643 +Epoch [1995/4000] Training [7/16] Loss: 0.00625 +Epoch [1995/4000] Training [8/16] Loss: 0.00709 +Epoch [1995/4000] Training [9/16] Loss: 0.00584 +Epoch [1995/4000] Training [10/16] Loss: 0.00726 +Epoch [1995/4000] Training [11/16] Loss: 0.00730 +Epoch [1995/4000] Training [12/16] Loss: 0.00574 +Epoch [1995/4000] Training [13/16] Loss: 0.00541 +Epoch [1995/4000] Training [14/16] Loss: 0.00522 +Epoch [1995/4000] Training [15/16] Loss: 0.00715 +Epoch [1995/4000] Training [16/16] Loss: 0.00563 +Epoch [1995/4000] Training metric {'Train/mean dice_metric': 0.9957143068313599, 'Train/mean miou_metric': 0.9912112951278687, 'Train/mean f1': 0.9916382431983948, 'Train/mean precision': 0.9871526956558228, 'Train/mean recall': 0.9961647987365723, 'Train/mean hd95_metric': 0.9949074983596802} +Epoch [1995/4000] Validation [1/4] Loss: 0.29183 focal_loss 0.22319 dice_loss 0.06863 +Epoch [1995/4000] Validation [2/4] Loss: 0.32257 focal_loss 0.17348 dice_loss 0.14909 +Epoch [1995/4000] Validation [3/4] Loss: 0.31753 focal_loss 0.22823 dice_loss 0.08930 +Epoch [1995/4000] Validation [4/4] Loss: 0.28966 focal_loss 0.18665 dice_loss 0.10301 +Epoch [1995/4000] Validation metric {'Val/mean dice_metric': 0.9725030064582825, 'Val/mean miou_metric': 0.9559757113456726, 'Val/mean f1': 0.9738442301750183, 'Val/mean precision': 0.9703609943389893, 'Val/mean recall': 0.9773526787757874, 'Val/mean hd95_metric': 5.860600471496582} +Cheakpoint... +Epoch [1995/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725030064582825, 'Val/mean miou_metric': 0.9559757113456726, 'Val/mean f1': 0.9738442301750183, 'Val/mean precision': 0.9703609943389893, 'Val/mean recall': 0.9773526787757874, 'Val/mean hd95_metric': 5.860600471496582} +Epoch [1996/4000] Training [1/16] Loss: 0.00678 +Epoch [1996/4000] Training [2/16] Loss: 0.00507 +Epoch [1996/4000] Training [3/16] Loss: 0.00610 +Epoch [1996/4000] Training [4/16] Loss: 0.00536 +Epoch [1996/4000] Training [5/16] Loss: 0.00653 +Epoch [1996/4000] Training [6/16] Loss: 0.00597 +Epoch [1996/4000] Training [7/16] Loss: 0.00592 +Epoch [1996/4000] Training [8/16] Loss: 0.00815 +Epoch [1996/4000] Training [9/16] Loss: 0.00618 +Epoch [1996/4000] Training [10/16] Loss: 0.00642 +Epoch [1996/4000] Training [11/16] Loss: 0.00537 +Epoch [1996/4000] Training [12/16] Loss: 0.00789 +Epoch [1996/4000] Training [13/16] Loss: 0.00542 +Epoch [1996/4000] Training [14/16] Loss: 0.00530 +Epoch [1996/4000] Training [15/16] Loss: 0.00613 +Epoch [1996/4000] Training [16/16] Loss: 0.00652 +Epoch [1996/4000] Training metric {'Train/mean dice_metric': 0.9958446621894836, 'Train/mean miou_metric': 0.9914231300354004, 'Train/mean f1': 0.9907068610191345, 'Train/mean precision': 0.9852769374847412, 'Train/mean recall': 0.9961969256401062, 'Train/mean hd95_metric': 1.0108678340911865} +Epoch [1996/4000] Validation [1/4] Loss: 0.27530 focal_loss 0.20762 dice_loss 0.06768 +Epoch [1996/4000] Validation [2/4] Loss: 0.36466 focal_loss 0.24443 dice_loss 0.12023 +Epoch [1996/4000] Validation [3/4] Loss: 0.39447 focal_loss 0.30434 dice_loss 0.09012 +Epoch [1996/4000] Validation [4/4] Loss: 0.35081 focal_loss 0.23659 dice_loss 0.11422 +Epoch [1996/4000] Validation metric {'Val/mean dice_metric': 0.9729171991348267, 'Val/mean miou_metric': 0.956154465675354, 'Val/mean f1': 0.9735196232795715, 'Val/mean precision': 0.9694526195526123, 'Val/mean recall': 0.9776208996772766, 'Val/mean hd95_metric': 5.781161308288574} +Cheakpoint... +Epoch [1996/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729171991348267, 'Val/mean miou_metric': 0.956154465675354, 'Val/mean f1': 0.9735196232795715, 'Val/mean precision': 0.9694526195526123, 'Val/mean recall': 0.9776208996772766, 'Val/mean hd95_metric': 5.781161308288574} +Epoch [1997/4000] Training [1/16] Loss: 0.00492 +Epoch [1997/4000] Training [2/16] Loss: 0.00550 +Epoch [1997/4000] Training [3/16] Loss: 0.00560 +Epoch [1997/4000] Training [4/16] Loss: 0.00585 +Epoch [1997/4000] Training [5/16] Loss: 0.00617 +Epoch [1997/4000] Training [6/16] Loss: 0.00394 +Epoch [1997/4000] Training [7/16] Loss: 0.00603 +Epoch [1997/4000] Training [8/16] Loss: 0.00465 +Epoch [1997/4000] Training [9/16] Loss: 0.00660 +Epoch [1997/4000] Training [10/16] Loss: 0.00778 +Epoch [1997/4000] Training [11/16] Loss: 0.00585 +Epoch [1997/4000] Training [12/16] Loss: 0.00716 +Epoch [1997/4000] Training [13/16] Loss: 0.00582 +Epoch [1997/4000] Training [14/16] Loss: 0.00724 +Epoch [1997/4000] Training [15/16] Loss: 0.00503 +Epoch [1997/4000] Training [16/16] Loss: 0.00417 +Epoch [1997/4000] Training metric {'Train/mean dice_metric': 0.9961280226707458, 'Train/mean miou_metric': 0.9920046329498291, 'Train/mean f1': 0.9916788339614868, 'Train/mean precision': 0.9870781302452087, 'Train/mean recall': 0.9963225722312927, 'Train/mean hd95_metric': 1.0093436241149902} +Epoch [1997/4000] Validation [1/4] Loss: 0.30038 focal_loss 0.23289 dice_loss 0.06748 +Epoch [1997/4000] Validation [2/4] Loss: 0.34513 focal_loss 0.21874 dice_loss 0.12639 +Epoch [1997/4000] Validation [3/4] Loss: 0.17661 focal_loss 0.12014 dice_loss 0.05647 +Epoch [1997/4000] Validation [4/4] Loss: 0.32392 focal_loss 0.20988 dice_loss 0.11404 +Epoch [1997/4000] Validation metric {'Val/mean dice_metric': 0.972969651222229, 'Val/mean miou_metric': 0.9566352963447571, 'Val/mean f1': 0.974116325378418, 'Val/mean precision': 0.9707011580467224, 'Val/mean recall': 0.9775555729866028, 'Val/mean hd95_metric': 5.5560173988342285} +Cheakpoint... +Epoch [1997/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972969651222229, 'Val/mean miou_metric': 0.9566352963447571, 'Val/mean f1': 0.974116325378418, 'Val/mean precision': 0.9707011580467224, 'Val/mean recall': 0.9775555729866028, 'Val/mean hd95_metric': 5.5560173988342285} +Epoch [1998/4000] Training [1/16] Loss: 0.00648 +Epoch [1998/4000] Training [2/16] Loss: 0.00768 +Epoch [1998/4000] Training [3/16] Loss: 0.00470 +Epoch [1998/4000] Training [4/16] Loss: 0.00555 +Epoch [1998/4000] Training [5/16] Loss: 0.00782 +Epoch [1998/4000] Training [6/16] Loss: 0.00540 +Epoch [1998/4000] Training [7/16] Loss: 0.00870 +Epoch [1998/4000] Training [8/16] Loss: 0.00620 +Epoch [1998/4000] Training [9/16] Loss: 0.00661 +Epoch [1998/4000] Training [10/16] Loss: 0.00734 +Epoch [1998/4000] Training [11/16] Loss: 0.00504 +Epoch [1998/4000] Training [12/16] Loss: 0.00745 +Epoch [1998/4000] Training [13/16] Loss: 0.00678 +Epoch [1998/4000] Training [14/16] Loss: 0.00486 +Epoch [1998/4000] Training [15/16] Loss: 0.00671 +Epoch [1998/4000] Training [16/16] Loss: 0.00640 +Epoch [1998/4000] Training metric {'Train/mean dice_metric': 0.9956191182136536, 'Train/mean miou_metric': 0.9910104274749756, 'Train/mean f1': 0.9913824796676636, 'Train/mean precision': 0.986737072467804, 'Train/mean recall': 0.9960718154907227, 'Train/mean hd95_metric': 1.0222816467285156} +Epoch [1998/4000] Validation [1/4] Loss: 0.33552 focal_loss 0.26048 dice_loss 0.07504 +Epoch [1998/4000] Validation [2/4] Loss: 0.58689 focal_loss 0.39458 dice_loss 0.19232 +Epoch [1998/4000] Validation [3/4] Loss: 0.36003 focal_loss 0.26645 dice_loss 0.09358 +Epoch [1998/4000] Validation [4/4] Loss: 0.26702 focal_loss 0.16475 dice_loss 0.10227 +Epoch [1998/4000] Validation metric {'Val/mean dice_metric': 0.9724022150039673, 'Val/mean miou_metric': 0.9558069109916687, 'Val/mean f1': 0.9741145968437195, 'Val/mean precision': 0.9713170528411865, 'Val/mean recall': 0.9769283533096313, 'Val/mean hd95_metric': 5.506474494934082} +Cheakpoint... +Epoch [1998/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724022150039673, 'Val/mean miou_metric': 0.9558069109916687, 'Val/mean f1': 0.9741145968437195, 'Val/mean precision': 0.9713170528411865, 'Val/mean recall': 0.9769283533096313, 'Val/mean hd95_metric': 5.506474494934082} +Epoch [1999/4000] Training [1/16] Loss: 0.00531 +Epoch [1999/4000] Training [2/16] Loss: 0.00516 +Epoch [1999/4000] Training [3/16] Loss: 0.00675 +Epoch [1999/4000] Training [4/16] Loss: 0.00602 +Epoch [1999/4000] Training [5/16] Loss: 0.00611 +Epoch [1999/4000] Training [6/16] Loss: 0.00772 +Epoch [1999/4000] Training [7/16] Loss: 0.00681 +Epoch [1999/4000] Training [8/16] Loss: 0.00489 +Epoch [1999/4000] Training [9/16] Loss: 0.00590 +Epoch [1999/4000] Training [10/16] Loss: 0.00614 +Epoch [1999/4000] Training [11/16] Loss: 0.00527 +Epoch [1999/4000] Training [12/16] Loss: 0.00739 +Epoch [1999/4000] Training [13/16] Loss: 0.00549 +Epoch [1999/4000] Training [14/16] Loss: 0.00852 +Epoch [1999/4000] Training [15/16] Loss: 0.00743 +Epoch [1999/4000] Training [16/16] Loss: 0.00638 +Epoch [1999/4000] Training metric {'Train/mean dice_metric': 0.9959083795547485, 'Train/mean miou_metric': 0.9915891885757446, 'Train/mean f1': 0.9916458129882812, 'Train/mean precision': 0.9871596097946167, 'Train/mean recall': 0.9961729645729065, 'Train/mean hd95_metric': 1.017554521560669} +Epoch [1999/4000] Validation [1/4] Loss: 0.29473 focal_loss 0.22858 dice_loss 0.06616 +Epoch [1999/4000] Validation [2/4] Loss: 0.48118 focal_loss 0.28825 dice_loss 0.19293 +Epoch [1999/4000] Validation [3/4] Loss: 0.36733 focal_loss 0.27262 dice_loss 0.09470 +Epoch [1999/4000] Validation [4/4] Loss: 0.31887 focal_loss 0.20399 dice_loss 0.11488 +Epoch [1999/4000] Validation metric {'Val/mean dice_metric': 0.9744182825088501, 'Val/mean miou_metric': 0.9583007097244263, 'Val/mean f1': 0.9751722812652588, 'Val/mean precision': 0.9710401892662048, 'Val/mean recall': 0.9793396592140198, 'Val/mean hd95_metric': 5.2819952964782715} +Cheakpoint... +Epoch [1999/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744182825088501, 'Val/mean miou_metric': 0.9583007097244263, 'Val/mean f1': 0.9751722812652588, 'Val/mean precision': 0.9710401892662048, 'Val/mean recall': 0.9793396592140198, 'Val/mean hd95_metric': 5.2819952964782715} +Epoch [2000/4000] Training [1/16] Loss: 0.00789 +Epoch [2000/4000] Training [2/16] Loss: 0.00486 +Epoch [2000/4000] Training [3/16] Loss: 0.00793 +Epoch [2000/4000] Training [4/16] Loss: 0.00677 +Epoch [2000/4000] Training [5/16] Loss: 0.00680 +Epoch [2000/4000] Training [6/16] Loss: 0.00503 +Epoch [2000/4000] Training [7/16] Loss: 0.00619 +Epoch [2000/4000] Training [8/16] Loss: 0.00626 +Epoch [2000/4000] Training [9/16] Loss: 0.00570 +Epoch [2000/4000] Training [10/16] Loss: 0.00445 +Epoch [2000/4000] Training [11/16] Loss: 0.00531 +Epoch [2000/4000] Training [12/16] Loss: 0.00624 +Epoch [2000/4000] Training [13/16] Loss: 0.00597 +Epoch [2000/4000] Training [14/16] Loss: 0.00581 +Epoch [2000/4000] Training [15/16] Loss: 0.00562 +Epoch [2000/4000] Training [16/16] Loss: 0.00646 +Epoch [2000/4000] Training metric {'Train/mean dice_metric': 0.9958761930465698, 'Train/mean miou_metric': 0.9915114641189575, 'Train/mean f1': 0.9915047287940979, 'Train/mean precision': 0.9867972135543823, 'Train/mean recall': 0.9962573051452637, 'Train/mean hd95_metric': 1.009792447090149} +Epoch [2000/4000] Validation [1/4] Loss: 0.27609 focal_loss 0.21136 dice_loss 0.06473 +Epoch [2000/4000] Validation [2/4] Loss: 0.32730 focal_loss 0.20602 dice_loss 0.12128 +Epoch [2000/4000] Validation [3/4] Loss: 0.31350 focal_loss 0.22577 dice_loss 0.08773 +Epoch [2000/4000] Validation [4/4] Loss: 0.25906 focal_loss 0.16890 dice_loss 0.09017 +Epoch [2000/4000] Validation metric {'Val/mean dice_metric': 0.9723402261734009, 'Val/mean miou_metric': 0.9558151960372925, 'Val/mean f1': 0.9734100103378296, 'Val/mean precision': 0.9706827402114868, 'Val/mean recall': 0.9761524796485901, 'Val/mean hd95_metric': 5.321765899658203} +Cheakpoint... +Epoch [2000/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723402261734009, 'Val/mean miou_metric': 0.9558151960372925, 'Val/mean f1': 0.9734100103378296, 'Val/mean precision': 0.9706827402114868, 'Val/mean recall': 0.9761524796485901, 'Val/mean hd95_metric': 5.321765899658203} +Epoch [2001/4000] Training [1/16] Loss: 0.00661 +Epoch [2001/4000] Training [2/16] Loss: 0.00666 +Epoch [2001/4000] Training [3/16] Loss: 0.00740 +Epoch [2001/4000] Training [4/16] Loss: 0.00495 +Epoch [2001/4000] Training [5/16] Loss: 0.00527 +Epoch [2001/4000] Training [6/16] Loss: 0.00507 +Epoch [2001/4000] Training [7/16] Loss: 0.00702 +Epoch [2001/4000] Training [8/16] Loss: 0.00563 +Epoch [2001/4000] Training [9/16] Loss: 0.00524 +Epoch [2001/4000] Training [10/16] Loss: 0.00613 +Epoch [2001/4000] Training [11/16] Loss: 0.00870 +Epoch [2001/4000] Training [12/16] Loss: 0.00623 +Epoch [2001/4000] Training [13/16] Loss: 0.00632 +Epoch [2001/4000] Training [14/16] Loss: 0.00433 +Epoch [2001/4000] Training [15/16] Loss: 0.00668 +Epoch [2001/4000] Training [16/16] Loss: 0.00501 +Epoch [2001/4000] Training metric {'Train/mean dice_metric': 0.9961026906967163, 'Train/mean miou_metric': 0.9919753074645996, 'Train/mean f1': 0.9918860197067261, 'Train/mean precision': 0.9873672127723694, 'Train/mean recall': 0.9964463114738464, 'Train/mean hd95_metric': 1.0080773830413818} +Epoch [2001/4000] Validation [1/4] Loss: 0.31927 focal_loss 0.24556 dice_loss 0.07372 +Epoch [2001/4000] Validation [2/4] Loss: 0.29997 focal_loss 0.19148 dice_loss 0.10849 +Epoch [2001/4000] Validation [3/4] Loss: 0.24563 focal_loss 0.16150 dice_loss 0.08413 +Epoch [2001/4000] Validation [4/4] Loss: 0.31767 focal_loss 0.19767 dice_loss 0.12000 +Epoch [2001/4000] Validation metric {'Val/mean dice_metric': 0.9732456207275391, 'Val/mean miou_metric': 0.9569045305252075, 'Val/mean f1': 0.974748969078064, 'Val/mean precision': 0.9720266461372375, 'Val/mean recall': 0.9774866700172424, 'Val/mean hd95_metric': 5.313894748687744} +Cheakpoint... +Epoch [2001/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732456207275391, 'Val/mean miou_metric': 0.9569045305252075, 'Val/mean f1': 0.974748969078064, 'Val/mean precision': 0.9720266461372375, 'Val/mean recall': 0.9774866700172424, 'Val/mean hd95_metric': 5.313894748687744} +Epoch [2002/4000] Training [1/16] Loss: 0.00609 +Epoch [2002/4000] Training [2/16] Loss: 0.00853 +Epoch [2002/4000] Training [3/16] Loss: 0.00545 +Epoch [2002/4000] Training [4/16] Loss: 0.00747 +Epoch [2002/4000] Training [5/16] Loss: 0.00763 +Epoch [2002/4000] Training [6/16] Loss: 0.00543 +Epoch [2002/4000] Training [7/16] Loss: 0.00615 +Epoch [2002/4000] Training [8/16] Loss: 0.00706 +Epoch [2002/4000] Training [9/16] Loss: 0.00509 +Epoch [2002/4000] Training [10/16] Loss: 0.00476 +Epoch [2002/4000] Training [11/16] Loss: 0.00532 +Epoch [2002/4000] Training [12/16] Loss: 0.00535 +Epoch [2002/4000] Training [13/16] Loss: 0.00887 +Epoch [2002/4000] Training [14/16] Loss: 0.00699 +Epoch [2002/4000] Training [15/16] Loss: 0.00752 +Epoch [2002/4000] Training [16/16] Loss: 0.00542 +Epoch [2002/4000] Training metric {'Train/mean dice_metric': 0.9956182837486267, 'Train/mean miou_metric': 0.9910037517547607, 'Train/mean f1': 0.9913013577461243, 'Train/mean precision': 0.9866319298744202, 'Train/mean recall': 0.996015191078186, 'Train/mean hd95_metric': 1.0229250192642212} +Epoch [2002/4000] Validation [1/4] Loss: 0.34556 focal_loss 0.27162 dice_loss 0.07394 +Epoch [2002/4000] Validation [2/4] Loss: 0.29036 focal_loss 0.18319 dice_loss 0.10717 +Epoch [2002/4000] Validation [3/4] Loss: 0.36985 focal_loss 0.27432 dice_loss 0.09552 +Epoch [2002/4000] Validation [4/4] Loss: 0.26001 focal_loss 0.16178 dice_loss 0.09823 +Epoch [2002/4000] Validation metric {'Val/mean dice_metric': 0.9738180041313171, 'Val/mean miou_metric': 0.9571583867073059, 'Val/mean f1': 0.9744620323181152, 'Val/mean precision': 0.9711427688598633, 'Val/mean recall': 0.9778040051460266, 'Val/mean hd95_metric': 5.362516403198242} +Cheakpoint... +Epoch [2002/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738180041313171, 'Val/mean miou_metric': 0.9571583867073059, 'Val/mean f1': 0.9744620323181152, 'Val/mean precision': 0.9711427688598633, 'Val/mean recall': 0.9778040051460266, 'Val/mean hd95_metric': 5.362516403198242} +Epoch [2003/4000] Training [1/16] Loss: 0.00468 +Epoch [2003/4000] Training [2/16] Loss: 0.00652 +Epoch [2003/4000] Training [3/16] Loss: 0.00673 +Epoch [2003/4000] Training [4/16] Loss: 0.00661 +Epoch [2003/4000] Training [5/16] Loss: 0.00574 +Epoch [2003/4000] Training [6/16] Loss: 0.00544 +Epoch [2003/4000] Training [7/16] Loss: 0.00504 +Epoch [2003/4000] Training [8/16] Loss: 0.00589 +Epoch [2003/4000] Training [9/16] Loss: 0.00643 +Epoch [2003/4000] Training [10/16] Loss: 0.00667 +Epoch [2003/4000] Training [11/16] Loss: 0.00499 +Epoch [2003/4000] Training [12/16] Loss: 0.00571 +Epoch [2003/4000] Training [13/16] Loss: 0.00501 +Epoch [2003/4000] Training [14/16] Loss: 0.00747 +Epoch [2003/4000] Training [15/16] Loss: 0.00617 +Epoch [2003/4000] Training [16/16] Loss: 0.00530 +Epoch [2003/4000] Training metric {'Train/mean dice_metric': 0.996071994304657, 'Train/mean miou_metric': 0.9919106960296631, 'Train/mean f1': 0.9917595386505127, 'Train/mean precision': 0.9871772527694702, 'Train/mean recall': 0.9963846206665039, 'Train/mean hd95_metric': 1.0027530193328857} +Epoch [2003/4000] Validation [1/4] Loss: 0.23717 focal_loss 0.17910 dice_loss 0.05806 +Epoch [2003/4000] Validation [2/4] Loss: 0.35066 focal_loss 0.21153 dice_loss 0.13913 +Epoch [2003/4000] Validation [3/4] Loss: 0.31006 focal_loss 0.21821 dice_loss 0.09185 +Epoch [2003/4000] Validation [4/4] Loss: 0.25054 focal_loss 0.16340 dice_loss 0.08714 +Epoch [2003/4000] Validation metric {'Val/mean dice_metric': 0.9728790521621704, 'Val/mean miou_metric': 0.9564234614372253, 'Val/mean f1': 0.9736779928207397, 'Val/mean precision': 0.971939742565155, 'Val/mean recall': 0.9754226207733154, 'Val/mean hd95_metric': 5.503149032592773} +Cheakpoint... +Epoch [2003/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728790521621704, 'Val/mean miou_metric': 0.9564234614372253, 'Val/mean f1': 0.9736779928207397, 'Val/mean precision': 0.971939742565155, 'Val/mean recall': 0.9754226207733154, 'Val/mean hd95_metric': 5.503149032592773} +Epoch [2004/4000] Training [1/16] Loss: 0.00584 +Epoch [2004/4000] Training [2/16] Loss: 0.00418 +Epoch [2004/4000] Training [3/16] Loss: 0.00641 +Epoch [2004/4000] Training [4/16] Loss: 0.00602 +Epoch [2004/4000] Training [5/16] Loss: 0.00570 +Epoch [2004/4000] Training [6/16] Loss: 0.00533 +Epoch [2004/4000] Training [7/16] Loss: 0.00615 +Epoch [2004/4000] Training [8/16] Loss: 0.00387 +Epoch [2004/4000] Training [9/16] Loss: 0.00629 +Epoch [2004/4000] Training [10/16] Loss: 0.00457 +Epoch [2004/4000] Training [11/16] Loss: 0.00497 +Epoch [2004/4000] Training [12/16] Loss: 0.00527 +Epoch [2004/4000] Training [13/16] Loss: 0.00641 +Epoch [2004/4000] Training [14/16] Loss: 0.00605 +Epoch [2004/4000] Training [15/16] Loss: 0.00556 +Epoch [2004/4000] Training [16/16] Loss: 0.00552 +Epoch [2004/4000] Training metric {'Train/mean dice_metric': 0.9961399435997009, 'Train/mean miou_metric': 0.992037832736969, 'Train/mean f1': 0.9917728304862976, 'Train/mean precision': 0.9872783422470093, 'Train/mean recall': 0.996308445930481, 'Train/mean hd95_metric': 1.0092496871948242} +Epoch [2004/4000] Validation [1/4] Loss: 0.47055 focal_loss 0.37851 dice_loss 0.09204 +Epoch [2004/4000] Validation [2/4] Loss: 0.53689 focal_loss 0.37301 dice_loss 0.16387 +Epoch [2004/4000] Validation [3/4] Loss: 0.20128 focal_loss 0.13582 dice_loss 0.06547 +Epoch [2004/4000] Validation [4/4] Loss: 0.27211 focal_loss 0.17486 dice_loss 0.09725 +Epoch [2004/4000] Validation metric {'Val/mean dice_metric': 0.9719831347465515, 'Val/mean miou_metric': 0.9556587338447571, 'Val/mean f1': 0.9735639095306396, 'Val/mean precision': 0.9727774262428284, 'Val/mean recall': 0.9743517637252808, 'Val/mean hd95_metric': 5.093524932861328} +Cheakpoint... +Epoch [2004/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719831347465515, 'Val/mean miou_metric': 0.9556587338447571, 'Val/mean f1': 0.9735639095306396, 'Val/mean precision': 0.9727774262428284, 'Val/mean recall': 0.9743517637252808, 'Val/mean hd95_metric': 5.093524932861328} +Epoch [2005/4000] Training [1/16] Loss: 0.00465 +Epoch [2005/4000] Training [2/16] Loss: 0.00510 +Epoch [2005/4000] Training [3/16] Loss: 0.00671 +Epoch [2005/4000] Training [4/16] Loss: 0.00470 +Epoch [2005/4000] Training [5/16] Loss: 0.00540 +Epoch [2005/4000] Training [6/16] Loss: 0.00507 +Epoch [2005/4000] Training [7/16] Loss: 0.00582 +Epoch [2005/4000] Training [8/16] Loss: 0.00692 +Epoch [2005/4000] Training [9/16] Loss: 0.00571 +Epoch [2005/4000] Training [10/16] Loss: 0.00670 +Epoch [2005/4000] Training [11/16] Loss: 0.00503 +Epoch [2005/4000] Training [12/16] Loss: 0.00428 +Epoch [2005/4000] Training [13/16] Loss: 0.00590 +Epoch [2005/4000] Training [14/16] Loss: 0.00469 +Epoch [2005/4000] Training [15/16] Loss: 0.00592 +Epoch [2005/4000] Training [16/16] Loss: 0.00623 +Epoch [2005/4000] Training metric {'Train/mean dice_metric': 0.9963759779930115, 'Train/mean miou_metric': 0.9925157427787781, 'Train/mean f1': 0.9920207858085632, 'Train/mean precision': 0.9875182509422302, 'Train/mean recall': 0.996564507484436, 'Train/mean hd95_metric': 1.0032360553741455} +Epoch [2005/4000] Validation [1/4] Loss: 0.34888 focal_loss 0.27122 dice_loss 0.07765 +Epoch [2005/4000] Validation [2/4] Loss: 0.53332 focal_loss 0.36958 dice_loss 0.16374 +Epoch [2005/4000] Validation [3/4] Loss: 0.19882 focal_loss 0.13453 dice_loss 0.06429 +Epoch [2005/4000] Validation [4/4] Loss: 0.27102 focal_loss 0.16778 dice_loss 0.10324 +Epoch [2005/4000] Validation metric {'Val/mean dice_metric': 0.9715491533279419, 'Val/mean miou_metric': 0.9555619955062866, 'Val/mean f1': 0.9739522337913513, 'Val/mean precision': 0.9716743230819702, 'Val/mean recall': 0.9762409329414368, 'Val/mean hd95_metric': 5.677148818969727} +Cheakpoint... +Epoch [2005/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715491533279419, 'Val/mean miou_metric': 0.9555619955062866, 'Val/mean f1': 0.9739522337913513, 'Val/mean precision': 0.9716743230819702, 'Val/mean recall': 0.9762409329414368, 'Val/mean hd95_metric': 5.677148818969727} +Epoch [2006/4000] Training [1/16] Loss: 0.00759 +Epoch [2006/4000] Training [2/16] Loss: 0.00461 +Epoch [2006/4000] Training [3/16] Loss: 0.00830 +Epoch [2006/4000] Training [4/16] Loss: 0.00490 +Epoch [2006/4000] Training [5/16] Loss: 0.00530 +Epoch [2006/4000] Training [6/16] Loss: 0.00471 +Epoch [2006/4000] Training [7/16] Loss: 0.00479 +Epoch [2006/4000] Training [8/16] Loss: 0.00657 +Epoch [2006/4000] Training [9/16] Loss: 0.00764 +Epoch [2006/4000] Training [10/16] Loss: 0.00520 +Epoch [2006/4000] Training [11/16] Loss: 0.00722 +Epoch [2006/4000] Training [12/16] Loss: 0.00789 +Epoch [2006/4000] Training [13/16] Loss: 0.00516 +Epoch [2006/4000] Training [14/16] Loss: 0.00707 +Epoch [2006/4000] Training [15/16] Loss: 0.00581 +Epoch [2006/4000] Training [16/16] Loss: 0.00576 +Epoch [2006/4000] Training metric {'Train/mean dice_metric': 0.9959732294082642, 'Train/mean miou_metric': 0.9917212724685669, 'Train/mean f1': 0.9917277693748474, 'Train/mean precision': 0.9871935844421387, 'Train/mean recall': 0.9963037371635437, 'Train/mean hd95_metric': 1.0482317209243774} +Epoch [2006/4000] Validation [1/4] Loss: 0.39354 focal_loss 0.30480 dice_loss 0.08874 +Epoch [2006/4000] Validation [2/4] Loss: 0.53151 focal_loss 0.33415 dice_loss 0.19736 +Epoch [2006/4000] Validation [3/4] Loss: 0.29795 focal_loss 0.20516 dice_loss 0.09279 +Epoch [2006/4000] Validation [4/4] Loss: 0.32126 focal_loss 0.21392 dice_loss 0.10733 +Epoch [2006/4000] Validation metric {'Val/mean dice_metric': 0.9717367887496948, 'Val/mean miou_metric': 0.9551900029182434, 'Val/mean f1': 0.9733912944793701, 'Val/mean precision': 0.9725133776664734, 'Val/mean recall': 0.9742707014083862, 'Val/mean hd95_metric': 5.344521522521973} +Cheakpoint... +Epoch [2006/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717367887496948, 'Val/mean miou_metric': 0.9551900029182434, 'Val/mean f1': 0.9733912944793701, 'Val/mean precision': 0.9725133776664734, 'Val/mean recall': 0.9742707014083862, 'Val/mean hd95_metric': 5.344521522521973} +Epoch [2007/4000] Training [1/16] Loss: 0.00582 +Epoch [2007/4000] Training [2/16] Loss: 0.00381 +Epoch [2007/4000] Training [3/16] Loss: 0.00613 +Epoch [2007/4000] Training [4/16] Loss: 0.00596 +Epoch [2007/4000] Training [5/16] Loss: 0.00654 +Epoch [2007/4000] Training [6/16] Loss: 0.00583 +Epoch [2007/4000] Training [7/16] Loss: 0.00526 +Epoch [2007/4000] Training [8/16] Loss: 0.00425 +Epoch [2007/4000] Training [9/16] Loss: 0.00475 +Epoch [2007/4000] Training [10/16] Loss: 0.00779 +Epoch [2007/4000] Training [11/16] Loss: 0.00580 +Epoch [2007/4000] Training [12/16] Loss: 0.00748 +Epoch [2007/4000] Training [13/16] Loss: 0.00584 +Epoch [2007/4000] Training [14/16] Loss: 0.00536 +Epoch [2007/4000] Training [15/16] Loss: 0.00514 +Epoch [2007/4000] Training [16/16] Loss: 0.00703 +Epoch [2007/4000] Training metric {'Train/mean dice_metric': 0.9960115551948547, 'Train/mean miou_metric': 0.9917913675308228, 'Train/mean f1': 0.9916890263557434, 'Train/mean precision': 0.9870694279670715, 'Train/mean recall': 0.9963520765304565, 'Train/mean hd95_metric': 1.0360604524612427} +Epoch [2007/4000] Validation [1/4] Loss: 0.32163 focal_loss 0.25263 dice_loss 0.06900 +Epoch [2007/4000] Validation [2/4] Loss: 0.33877 focal_loss 0.20515 dice_loss 0.13362 +Epoch [2007/4000] Validation [3/4] Loss: 0.33859 focal_loss 0.23110 dice_loss 0.10748 +Epoch [2007/4000] Validation [4/4] Loss: 0.46613 focal_loss 0.32151 dice_loss 0.14462 +Epoch [2007/4000] Validation metric {'Val/mean dice_metric': 0.9708884358406067, 'Val/mean miou_metric': 0.9533096551895142, 'Val/mean f1': 0.9723908305168152, 'Val/mean precision': 0.9746694564819336, 'Val/mean recall': 0.9701228141784668, 'Val/mean hd95_metric': 5.323224067687988} +Cheakpoint... +Epoch [2007/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708884358406067, 'Val/mean miou_metric': 0.9533096551895142, 'Val/mean f1': 0.9723908305168152, 'Val/mean precision': 0.9746694564819336, 'Val/mean recall': 0.9701228141784668, 'Val/mean hd95_metric': 5.323224067687988} +Epoch [2008/4000] Training [1/16] Loss: 0.00580 +Epoch [2008/4000] Training [2/16] Loss: 0.00472 +Epoch [2008/4000] Training [3/16] Loss: 0.00507 +Epoch [2008/4000] Training [4/16] Loss: 0.00516 +Epoch [2008/4000] Training [5/16] Loss: 0.00460 +Epoch [2008/4000] Training [6/16] Loss: 0.00512 +Epoch [2008/4000] Training [7/16] Loss: 0.00939 +Epoch [2008/4000] Training [8/16] Loss: 0.00602 +Epoch [2008/4000] Training [9/16] Loss: 0.00619 +Epoch [2008/4000] Training [10/16] Loss: 0.00475 +Epoch [2008/4000] Training [11/16] Loss: 0.00385 +Epoch [2008/4000] Training [12/16] Loss: 0.00433 +Epoch [2008/4000] Training [13/16] Loss: 0.01121 +Epoch [2008/4000] Training [14/16] Loss: 0.00552 +Epoch [2008/4000] Training [15/16] Loss: 0.00801 +Epoch [2008/4000] Training [16/16] Loss: 0.00719 +Epoch [2008/4000] Training metric {'Train/mean dice_metric': 0.995769202709198, 'Train/mean miou_metric': 0.9912909269332886, 'Train/mean f1': 0.9908972382545471, 'Train/mean precision': 0.9857247471809387, 'Train/mean recall': 0.996124267578125, 'Train/mean hd95_metric': 1.3376245498657227} +Epoch [2008/4000] Validation [1/4] Loss: 0.33765 focal_loss 0.25828 dice_loss 0.07936 +Epoch [2008/4000] Validation [2/4] Loss: 0.36193 focal_loss 0.24074 dice_loss 0.12119 +Epoch [2008/4000] Validation [3/4] Loss: 0.39205 focal_loss 0.29236 dice_loss 0.09969 +Epoch [2008/4000] Validation [4/4] Loss: 0.32614 focal_loss 0.21901 dice_loss 0.10713 +Epoch [2008/4000] Validation metric {'Val/mean dice_metric': 0.9732059240341187, 'Val/mean miou_metric': 0.9560054540634155, 'Val/mean f1': 0.9735509753227234, 'Val/mean precision': 0.971936047077179, 'Val/mean recall': 0.9751712083816528, 'Val/mean hd95_metric': 5.584617614746094} +Cheakpoint... +Epoch [2008/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732059240341187, 'Val/mean miou_metric': 0.9560054540634155, 'Val/mean f1': 0.9735509753227234, 'Val/mean precision': 0.971936047077179, 'Val/mean recall': 0.9751712083816528, 'Val/mean hd95_metric': 5.584617614746094} +Epoch [2009/4000] Training [1/16] Loss: 0.00595 +Epoch [2009/4000] Training [2/16] Loss: 0.00648 +Epoch [2009/4000] Training [3/16] Loss: 0.00642 +Epoch [2009/4000] Training [4/16] Loss: 0.00695 +Epoch [2009/4000] Training [5/16] Loss: 0.01052 +Epoch [2009/4000] Training [6/16] Loss: 0.00487 +Epoch [2009/4000] Training [7/16] Loss: 0.00596 +Epoch [2009/4000] Training [8/16] Loss: 0.00649 +Epoch [2009/4000] Training [9/16] Loss: 0.00553 +Epoch [2009/4000] Training [10/16] Loss: 0.00726 +Epoch [2009/4000] Training [11/16] Loss: 0.00760 +Epoch [2009/4000] Training [12/16] Loss: 0.00804 +Epoch [2009/4000] Training [13/16] Loss: 0.00785 +Epoch [2009/4000] Training [14/16] Loss: 0.00554 +Epoch [2009/4000] Training [15/16] Loss: 0.00592 +Epoch [2009/4000] Training [16/16] Loss: 0.00477 +Epoch [2009/4000] Training metric {'Train/mean dice_metric': 0.9957428574562073, 'Train/mean miou_metric': 0.9912590980529785, 'Train/mean f1': 0.9913747906684875, 'Train/mean precision': 0.9867446422576904, 'Train/mean recall': 0.9960485696792603, 'Train/mean hd95_metric': 1.0065643787384033} +Epoch [2009/4000] Validation [1/4] Loss: 0.56627 focal_loss 0.47030 dice_loss 0.09597 +Epoch [2009/4000] Validation [2/4] Loss: 0.64402 focal_loss 0.44008 dice_loss 0.20394 +Epoch [2009/4000] Validation [3/4] Loss: 0.22628 focal_loss 0.16119 dice_loss 0.06509 +Epoch [2009/4000] Validation [4/4] Loss: 0.26834 focal_loss 0.16952 dice_loss 0.09882 +Epoch [2009/4000] Validation metric {'Val/mean dice_metric': 0.9709887504577637, 'Val/mean miou_metric': 0.9541109204292297, 'Val/mean f1': 0.9724913835525513, 'Val/mean precision': 0.9727731943130493, 'Val/mean recall': 0.9722098112106323, 'Val/mean hd95_metric': 5.045379638671875} +Cheakpoint... +Epoch [2009/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709887504577637, 'Val/mean miou_metric': 0.9541109204292297, 'Val/mean f1': 0.9724913835525513, 'Val/mean precision': 0.9727731943130493, 'Val/mean recall': 0.9722098112106323, 'Val/mean hd95_metric': 5.045379638671875} +Epoch [2010/4000] Training [1/16] Loss: 0.00512 +Epoch [2010/4000] Training [2/16] Loss: 0.00564 +Epoch [2010/4000] Training [3/16] Loss: 0.00483 +Epoch [2010/4000] Training [4/16] Loss: 0.00617 +Epoch [2010/4000] Training [5/16] Loss: 0.00793 +Epoch [2010/4000] Training [6/16] Loss: 0.00577 +Epoch [2010/4000] Training [7/16] Loss: 0.00428 +Epoch [2010/4000] Training [8/16] Loss: 0.00688 +Epoch [2010/4000] Training [9/16] Loss: 0.00624 +Epoch [2010/4000] Training [10/16] Loss: 0.00460 +Epoch [2010/4000] Training [11/16] Loss: 0.00712 +Epoch [2010/4000] Training [12/16] Loss: 0.00623 +Epoch [2010/4000] Training [13/16] Loss: 0.00727 +Epoch [2010/4000] Training [14/16] Loss: 0.00595 +Epoch [2010/4000] Training [15/16] Loss: 0.00405 +Epoch [2010/4000] Training [16/16] Loss: 0.00624 +Epoch [2010/4000] Training metric {'Train/mean dice_metric': 0.9962986707687378, 'Train/mean miou_metric': 0.9923602342605591, 'Train/mean f1': 0.9919748306274414, 'Train/mean precision': 0.9875984787940979, 'Train/mean recall': 0.9963901042938232, 'Train/mean hd95_metric': 1.01072359085083} +Epoch [2010/4000] Validation [1/4] Loss: 0.37302 focal_loss 0.29283 dice_loss 0.08019 +Epoch [2010/4000] Validation [2/4] Loss: 0.64903 focal_loss 0.44243 dice_loss 0.20660 +Epoch [2010/4000] Validation [3/4] Loss: 0.39736 focal_loss 0.30300 dice_loss 0.09436 +Epoch [2010/4000] Validation [4/4] Loss: 0.26569 focal_loss 0.17415 dice_loss 0.09153 +Epoch [2010/4000] Validation metric {'Val/mean dice_metric': 0.9717336893081665, 'Val/mean miou_metric': 0.9551135897636414, 'Val/mean f1': 0.9735285639762878, 'Val/mean precision': 0.9727615118026733, 'Val/mean recall': 0.9742968082427979, 'Val/mean hd95_metric': 5.320792198181152} +Cheakpoint... +Epoch [2010/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717336893081665, 'Val/mean miou_metric': 0.9551135897636414, 'Val/mean f1': 0.9735285639762878, 'Val/mean precision': 0.9727615118026733, 'Val/mean recall': 0.9742968082427979, 'Val/mean hd95_metric': 5.320792198181152} +Epoch [2011/4000] Training [1/16] Loss: 0.00936 +Epoch [2011/4000] Training [2/16] Loss: 0.00584 +Epoch [2011/4000] Training [3/16] Loss: 0.00479 +Epoch [2011/4000] Training [4/16] Loss: 0.00666 +Epoch [2011/4000] Training [5/16] Loss: 0.00538 +Epoch [2011/4000] Training [6/16] Loss: 0.00435 +Epoch [2011/4000] Training [7/16] Loss: 0.00549 +Epoch [2011/4000] Training [8/16] Loss: 0.00426 +Epoch [2011/4000] Training [9/16] Loss: 0.00462 +Epoch [2011/4000] Training [10/16] Loss: 0.00696 +Epoch [2011/4000] Training [11/16] Loss: 0.00570 +Epoch [2011/4000] Training [12/16] Loss: 0.00545 +Epoch [2011/4000] Training [13/16] Loss: 0.00583 +Epoch [2011/4000] Training [14/16] Loss: 0.00488 +Epoch [2011/4000] Training [15/16] Loss: 0.00463 +Epoch [2011/4000] Training [16/16] Loss: 0.00503 +Epoch [2011/4000] Training metric {'Train/mean dice_metric': 0.9962329864501953, 'Train/mean miou_metric': 0.9922362565994263, 'Train/mean f1': 0.9918801784515381, 'Train/mean precision': 0.9871858954429626, 'Train/mean recall': 0.9966192841529846, 'Train/mean hd95_metric': 1.0012812614440918} +Epoch [2011/4000] Validation [1/4] Loss: 0.53081 focal_loss 0.43011 dice_loss 0.10070 +Epoch [2011/4000] Validation [2/4] Loss: 0.33773 focal_loss 0.22386 dice_loss 0.11388 +Epoch [2011/4000] Validation [3/4] Loss: 0.39480 focal_loss 0.30073 dice_loss 0.09407 +Epoch [2011/4000] Validation [4/4] Loss: 0.23192 focal_loss 0.15124 dice_loss 0.08067 +Epoch [2011/4000] Validation metric {'Val/mean dice_metric': 0.9723387956619263, 'Val/mean miou_metric': 0.9553510546684265, 'Val/mean f1': 0.9728643894195557, 'Val/mean precision': 0.9730797410011292, 'Val/mean recall': 0.9726490378379822, 'Val/mean hd95_metric': 5.283884048461914} +Cheakpoint... +Epoch [2011/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723387956619263, 'Val/mean miou_metric': 0.9553510546684265, 'Val/mean f1': 0.9728643894195557, 'Val/mean precision': 0.9730797410011292, 'Val/mean recall': 0.9726490378379822, 'Val/mean hd95_metric': 5.283884048461914} +Epoch [2012/4000] Training [1/16] Loss: 0.00443 +Epoch [2012/4000] Training [2/16] Loss: 0.00467 +Epoch [2012/4000] Training [3/16] Loss: 0.00620 +Epoch [2012/4000] Training [4/16] Loss: 0.00684 +Epoch [2012/4000] Training [5/16] Loss: 0.00646 +Epoch [2012/4000] Training [6/16] Loss: 0.00548 +Epoch [2012/4000] Training [7/16] Loss: 0.00542 +Epoch [2012/4000] Training [8/16] Loss: 0.00459 +Epoch [2012/4000] Training [9/16] Loss: 0.00589 +Epoch [2012/4000] Training [10/16] Loss: 0.00626 +Epoch [2012/4000] Training [11/16] Loss: 0.00544 +Epoch [2012/4000] Training [12/16] Loss: 0.00527 +Epoch [2012/4000] Training [13/16] Loss: 0.00645 +Epoch [2012/4000] Training [14/16] Loss: 0.00675 +Epoch [2012/4000] Training [15/16] Loss: 0.00472 +Epoch [2012/4000] Training [16/16] Loss: 0.00586 +Epoch [2012/4000] Training metric {'Train/mean dice_metric': 0.9961365461349487, 'Train/mean miou_metric': 0.9920340776443481, 'Train/mean f1': 0.9917488098144531, 'Train/mean precision': 0.9871839284896851, 'Train/mean recall': 0.9963561296463013, 'Train/mean hd95_metric': 1.0093046426773071} +Epoch [2012/4000] Validation [1/4] Loss: 0.28238 focal_loss 0.21540 dice_loss 0.06699 +Epoch [2012/4000] Validation [2/4] Loss: 0.64715 focal_loss 0.46136 dice_loss 0.18579 +Epoch [2012/4000] Validation [3/4] Loss: 0.39400 focal_loss 0.29544 dice_loss 0.09856 +Epoch [2012/4000] Validation [4/4] Loss: 0.29288 focal_loss 0.18438 dice_loss 0.10850 +Epoch [2012/4000] Validation metric {'Val/mean dice_metric': 0.9727007150650024, 'Val/mean miou_metric': 0.9563699960708618, 'Val/mean f1': 0.9741700887680054, 'Val/mean precision': 0.9732857346534729, 'Val/mean recall': 0.9750561714172363, 'Val/mean hd95_metric': 5.466787338256836} +Cheakpoint... +Epoch [2012/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727007150650024, 'Val/mean miou_metric': 0.9563699960708618, 'Val/mean f1': 0.9741700887680054, 'Val/mean precision': 0.9732857346534729, 'Val/mean recall': 0.9750561714172363, 'Val/mean hd95_metric': 5.466787338256836} +Epoch [2013/4000] Training [1/16] Loss: 0.00604 +Epoch [2013/4000] Training [2/16] Loss: 0.00466 +Epoch [2013/4000] Training [3/16] Loss: 0.00611 +Epoch [2013/4000] Training [4/16] Loss: 0.00526 +Epoch [2013/4000] Training [5/16] Loss: 0.00602 +Epoch [2013/4000] Training [6/16] Loss: 0.00420 +Epoch [2013/4000] Training [7/16] Loss: 0.00623 +Epoch [2013/4000] Training [8/16] Loss: 0.00577 +Epoch [2013/4000] Training [9/16] Loss: 0.00877 +Epoch [2013/4000] Training [10/16] Loss: 0.00576 +Epoch [2013/4000] Training [11/16] Loss: 0.00623 +Epoch [2013/4000] Training [12/16] Loss: 0.00705 +Epoch [2013/4000] Training [13/16] Loss: 0.00685 +Epoch [2013/4000] Training [14/16] Loss: 0.00566 +Epoch [2013/4000] Training [15/16] Loss: 0.00515 +Epoch [2013/4000] Training [16/16] Loss: 0.00500 +Epoch [2013/4000] Training metric {'Train/mean dice_metric': 0.9961183071136475, 'Train/mean miou_metric': 0.9919648766517639, 'Train/mean f1': 0.9910293221473694, 'Train/mean precision': 0.9858160614967346, 'Train/mean recall': 0.9962980151176453, 'Train/mean hd95_metric': 1.0279896259307861} +Epoch [2013/4000] Validation [1/4] Loss: 0.30092 focal_loss 0.23434 dice_loss 0.06657 +Epoch [2013/4000] Validation [2/4] Loss: 0.61216 focal_loss 0.42305 dice_loss 0.18912 +Epoch [2013/4000] Validation [3/4] Loss: 0.37747 focal_loss 0.28120 dice_loss 0.09627 +Epoch [2013/4000] Validation [4/4] Loss: 0.20878 focal_loss 0.13206 dice_loss 0.07672 +Epoch [2013/4000] Validation metric {'Val/mean dice_metric': 0.9725723266601562, 'Val/mean miou_metric': 0.9566888809204102, 'Val/mean f1': 0.9743388295173645, 'Val/mean precision': 0.9701307415962219, 'Val/mean recall': 0.9785833954811096, 'Val/mean hd95_metric': 5.212972164154053} +Cheakpoint... +Epoch [2013/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725723266601562, 'Val/mean miou_metric': 0.9566888809204102, 'Val/mean f1': 0.9743388295173645, 'Val/mean precision': 0.9701307415962219, 'Val/mean recall': 0.9785833954811096, 'Val/mean hd95_metric': 5.212972164154053} +Epoch [2014/4000] Training [1/16] Loss: 0.00754 +Epoch [2014/4000] Training [2/16] Loss: 0.00485 +Epoch [2014/4000] Training [3/16] Loss: 0.00516 +Epoch [2014/4000] Training [4/16] Loss: 0.00772 +Epoch [2014/4000] Training [5/16] Loss: 0.00538 +Epoch [2014/4000] Training [6/16] Loss: 0.00417 +Epoch [2014/4000] Training [7/16] Loss: 0.00597 +Epoch [2014/4000] Training [8/16] Loss: 0.00429 +Epoch [2014/4000] Training [9/16] Loss: 0.00556 +Epoch [2014/4000] Training [10/16] Loss: 0.00542 +Epoch [2014/4000] Training [11/16] Loss: 0.00764 +Epoch [2014/4000] Training [12/16] Loss: 0.00399 +Epoch [2014/4000] Training [13/16] Loss: 0.00481 +Epoch [2014/4000] Training [14/16] Loss: 0.00678 +Epoch [2014/4000] Training [15/16] Loss: 0.00558 +Epoch [2014/4000] Training [16/16] Loss: 0.00534 +Epoch [2014/4000] Training metric {'Train/mean dice_metric': 0.9962300062179565, 'Train/mean miou_metric': 0.9922142028808594, 'Train/mean f1': 0.9916815161705017, 'Train/mean precision': 0.9868914484977722, 'Train/mean recall': 0.9965182542800903, 'Train/mean hd95_metric': 1.00229012966156} +Epoch [2014/4000] Validation [1/4] Loss: 0.40349 focal_loss 0.31479 dice_loss 0.08869 +Epoch [2014/4000] Validation [2/4] Loss: 0.99759 focal_loss 0.75177 dice_loss 0.24582 +Epoch [2014/4000] Validation [3/4] Loss: 0.37562 focal_loss 0.28054 dice_loss 0.09508 +Epoch [2014/4000] Validation [4/4] Loss: 0.31784 focal_loss 0.21092 dice_loss 0.10692 +Epoch [2014/4000] Validation metric {'Val/mean dice_metric': 0.9714740514755249, 'Val/mean miou_metric': 0.9548803567886353, 'Val/mean f1': 0.9731757640838623, 'Val/mean precision': 0.9718051552772522, 'Val/mean recall': 0.9745503664016724, 'Val/mean hd95_metric': 5.439687728881836} +Cheakpoint... +Epoch [2014/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714740514755249, 'Val/mean miou_metric': 0.9548803567886353, 'Val/mean f1': 0.9731757640838623, 'Val/mean precision': 0.9718051552772522, 'Val/mean recall': 0.9745503664016724, 'Val/mean hd95_metric': 5.439687728881836} +Epoch [2015/4000] Training [1/16] Loss: 0.00479 +Epoch [2015/4000] Training [2/16] Loss: 0.00546 +Epoch [2015/4000] Training [3/16] Loss: 0.00532 +Epoch [2015/4000] Training [4/16] Loss: 0.00704 +Epoch [2015/4000] Training [5/16] Loss: 0.00709 +Epoch [2015/4000] Training [6/16] Loss: 0.00499 +Epoch [2015/4000] Training [7/16] Loss: 0.00654 +Epoch [2015/4000] Training [8/16] Loss: 0.00499 +Epoch [2015/4000] Training [9/16] Loss: 0.00625 +Epoch [2015/4000] Training [10/16] Loss: 0.00649 +Epoch [2015/4000] Training [11/16] Loss: 0.00531 +Epoch [2015/4000] Training [12/16] Loss: 0.00549 +Epoch [2015/4000] Training [13/16] Loss: 0.00559 +Epoch [2015/4000] Training [14/16] Loss: 0.00405 +Epoch [2015/4000] Training [15/16] Loss: 0.00668 +Epoch [2015/4000] Training [16/16] Loss: 0.00662 +Epoch [2015/4000] Training metric {'Train/mean dice_metric': 0.9962271451950073, 'Train/mean miou_metric': 0.9921830892562866, 'Train/mean f1': 0.9911798238754272, 'Train/mean precision': 0.9860513806343079, 'Train/mean recall': 0.9963619709014893, 'Train/mean hd95_metric': 1.004930019378662} +Epoch [2015/4000] Validation [1/4] Loss: 0.25624 focal_loss 0.19042 dice_loss 0.06582 +Epoch [2015/4000] Validation [2/4] Loss: 0.39835 focal_loss 0.26628 dice_loss 0.13207 +Epoch [2015/4000] Validation [3/4] Loss: 0.37334 focal_loss 0.28024 dice_loss 0.09310 +Epoch [2015/4000] Validation [4/4] Loss: 0.35788 focal_loss 0.22990 dice_loss 0.12799 +Epoch [2015/4000] Validation metric {'Val/mean dice_metric': 0.9727867841720581, 'Val/mean miou_metric': 0.9560521841049194, 'Val/mean f1': 0.9740273952484131, 'Val/mean precision': 0.9721556305885315, 'Val/mean recall': 0.9759063720703125, 'Val/mean hd95_metric': 5.495239734649658} +Cheakpoint... +Epoch [2015/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727867841720581, 'Val/mean miou_metric': 0.9560521841049194, 'Val/mean f1': 0.9740273952484131, 'Val/mean precision': 0.9721556305885315, 'Val/mean recall': 0.9759063720703125, 'Val/mean hd95_metric': 5.495239734649658} +Epoch [2016/4000] Training [1/16] Loss: 0.00539 +Epoch [2016/4000] Training [2/16] Loss: 0.00431 +Epoch [2016/4000] Training [3/16] Loss: 0.00637 +Epoch [2016/4000] Training [4/16] Loss: 0.00690 +Epoch [2016/4000] Training [5/16] Loss: 0.00452 +Epoch [2016/4000] Training [6/16] Loss: 0.00511 +Epoch [2016/4000] Training [7/16] Loss: 0.00594 +Epoch [2016/4000] Training [8/16] Loss: 0.00751 +Epoch [2016/4000] Training [9/16] Loss: 0.00549 +Epoch [2016/4000] Training [10/16] Loss: 0.00516 +Epoch [2016/4000] Training [11/16] Loss: 0.00565 +Epoch [2016/4000] Training [12/16] Loss: 0.00469 +Epoch [2016/4000] Training [13/16] Loss: 0.00584 +Epoch [2016/4000] Training [14/16] Loss: 0.00606 +Epoch [2016/4000] Training [15/16] Loss: 0.00733 +Epoch [2016/4000] Training [16/16] Loss: 0.00624 +Epoch [2016/4000] Training metric {'Train/mean dice_metric': 0.9961288571357727, 'Train/mean miou_metric': 0.9920293092727661, 'Train/mean f1': 0.9918961524963379, 'Train/mean precision': 0.987270176410675, 'Train/mean recall': 0.9965656399726868, 'Train/mean hd95_metric': 1.0101821422576904} +Epoch [2016/4000] Validation [1/4] Loss: 0.33940 focal_loss 0.26520 dice_loss 0.07419 +Epoch [2016/4000] Validation [2/4] Loss: 0.38486 focal_loss 0.26315 dice_loss 0.12171 +Epoch [2016/4000] Validation [3/4] Loss: 0.18676 focal_loss 0.12964 dice_loss 0.05712 +Epoch [2016/4000] Validation [4/4] Loss: 0.38012 focal_loss 0.25149 dice_loss 0.12863 +Epoch [2016/4000] Validation metric {'Val/mean dice_metric': 0.9736649394035339, 'Val/mean miou_metric': 0.9570821523666382, 'Val/mean f1': 0.9746965765953064, 'Val/mean precision': 0.9727901220321655, 'Val/mean recall': 0.976610541343689, 'Val/mean hd95_metric': 5.523237228393555} +Cheakpoint... +Epoch [2016/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736649394035339, 'Val/mean miou_metric': 0.9570821523666382, 'Val/mean f1': 0.9746965765953064, 'Val/mean precision': 0.9727901220321655, 'Val/mean recall': 0.976610541343689, 'Val/mean hd95_metric': 5.523237228393555} +Epoch [2017/4000] Training [1/16] Loss: 0.00627 +Epoch [2017/4000] Training [2/16] Loss: 0.00559 +Epoch [2017/4000] Training [3/16] Loss: 0.00476 +Epoch [2017/4000] Training [4/16] Loss: 0.00540 +Epoch [2017/4000] Training [5/16] Loss: 0.00520 +Epoch [2017/4000] Training [6/16] Loss: 0.00593 +Epoch [2017/4000] Training [7/16] Loss: 0.00373 +Epoch [2017/4000] Training [8/16] Loss: 0.00540 +Epoch [2017/4000] Training [9/16] Loss: 0.00597 +Epoch [2017/4000] Training [10/16] Loss: 0.00715 +Epoch [2017/4000] Training [11/16] Loss: 0.00539 +Epoch [2017/4000] Training [12/16] Loss: 0.00749 +Epoch [2017/4000] Training [13/16] Loss: 0.00686 +Epoch [2017/4000] Training [14/16] Loss: 0.00460 +Epoch [2017/4000] Training [15/16] Loss: 0.00556 +Epoch [2017/4000] Training [16/16] Loss: 0.00566 +Epoch [2017/4000] Training metric {'Train/mean dice_metric': 0.9961355924606323, 'Train/mean miou_metric': 0.9920247197151184, 'Train/mean f1': 0.9918606281280518, 'Train/mean precision': 0.987366795539856, 'Train/mean recall': 0.9963955283164978, 'Train/mean hd95_metric': 1.0005062818527222} +Epoch [2017/4000] Validation [1/4] Loss: 0.33435 focal_loss 0.25616 dice_loss 0.07820 +Epoch [2017/4000] Validation [2/4] Loss: 0.72570 focal_loss 0.49244 dice_loss 0.23326 +Epoch [2017/4000] Validation [3/4] Loss: 0.17743 focal_loss 0.12096 dice_loss 0.05648 +Epoch [2017/4000] Validation [4/4] Loss: 0.26587 focal_loss 0.16818 dice_loss 0.09768 +Epoch [2017/4000] Validation metric {'Val/mean dice_metric': 0.9709972143173218, 'Val/mean miou_metric': 0.9547855257987976, 'Val/mean f1': 0.9736002087593079, 'Val/mean precision': 0.9726539254188538, 'Val/mean recall': 0.9745483994483948, 'Val/mean hd95_metric': 5.589101791381836} +Cheakpoint... +Epoch [2017/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709972143173218, 'Val/mean miou_metric': 0.9547855257987976, 'Val/mean f1': 0.9736002087593079, 'Val/mean precision': 0.9726539254188538, 'Val/mean recall': 0.9745483994483948, 'Val/mean hd95_metric': 5.589101791381836} +Epoch [2018/4000] Training [1/16] Loss: 0.00517 +Epoch [2018/4000] Training [2/16] Loss: 0.00481 +Epoch [2018/4000] Training [3/16] Loss: 0.00468 +Epoch [2018/4000] Training [4/16] Loss: 0.00434 +Epoch [2018/4000] Training [5/16] Loss: 0.00629 +Epoch [2018/4000] Training [6/16] Loss: 0.00453 +Epoch [2018/4000] Training [7/16] Loss: 0.00457 +Epoch [2018/4000] Training [8/16] Loss: 0.00524 +Epoch [2018/4000] Training [9/16] Loss: 0.00775 +Epoch [2018/4000] Training [10/16] Loss: 0.00514 +Epoch [2018/4000] Training [11/16] Loss: 0.00624 +Epoch [2018/4000] Training [12/16] Loss: 0.00612 +Epoch [2018/4000] Training [13/16] Loss: 0.00635 +Epoch [2018/4000] Training [14/16] Loss: 0.00637 +Epoch [2018/4000] Training [15/16] Loss: 0.00470 +Epoch [2018/4000] Training [16/16] Loss: 0.00746 +Epoch [2018/4000] Training metric {'Train/mean dice_metric': 0.9962106943130493, 'Train/mean miou_metric': 0.9921586513519287, 'Train/mean f1': 0.9917439818382263, 'Train/mean precision': 0.9870101809501648, 'Train/mean recall': 0.9965234398841858, 'Train/mean hd95_metric': 0.999745786190033} +Epoch [2018/4000] Validation [1/4] Loss: 0.36328 focal_loss 0.28013 dice_loss 0.08315 +Epoch [2018/4000] Validation [2/4] Loss: 0.40178 focal_loss 0.27747 dice_loss 0.12432 +Epoch [2018/4000] Validation [3/4] Loss: 0.35121 focal_loss 0.25598 dice_loss 0.09523 +Epoch [2018/4000] Validation [4/4] Loss: 0.23774 focal_loss 0.15399 dice_loss 0.08375 +Epoch [2018/4000] Validation metric {'Val/mean dice_metric': 0.9726999402046204, 'Val/mean miou_metric': 0.9557768106460571, 'Val/mean f1': 0.9723033308982849, 'Val/mean precision': 0.9720327258110046, 'Val/mean recall': 0.9725740551948547, 'Val/mean hd95_metric': 5.502865791320801} +Cheakpoint... +Epoch [2018/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726999402046204, 'Val/mean miou_metric': 0.9557768106460571, 'Val/mean f1': 0.9723033308982849, 'Val/mean precision': 0.9720327258110046, 'Val/mean recall': 0.9725740551948547, 'Val/mean hd95_metric': 5.502865791320801} +Epoch [2019/4000] Training [1/16] Loss: 0.00564 +Epoch [2019/4000] Training [2/16] Loss: 0.00597 +Epoch [2019/4000] Training [3/16] Loss: 0.00741 +Epoch [2019/4000] Training [4/16] Loss: 0.00490 +Epoch [2019/4000] Training [5/16] Loss: 0.00535 +Epoch [2019/4000] Training [6/16] Loss: 0.00743 +Epoch [2019/4000] Training [7/16] Loss: 0.00542 +Epoch [2019/4000] Training [8/16] Loss: 0.00619 +Epoch [2019/4000] Training [9/16] Loss: 0.00587 +Epoch [2019/4000] Training [10/16] Loss: 0.00604 +Epoch [2019/4000] Training [11/16] Loss: 0.00525 +Epoch [2019/4000] Training [12/16] Loss: 0.00704 +Epoch [2019/4000] Training [13/16] Loss: 0.00471 +Epoch [2019/4000] Training [14/16] Loss: 0.00818 +Epoch [2019/4000] Training [15/16] Loss: 0.00540 +Epoch [2019/4000] Training [16/16] Loss: 0.00695 +Epoch [2019/4000] Training metric {'Train/mean dice_metric': 0.9960762858390808, 'Train/mean miou_metric': 0.9919223785400391, 'Train/mean f1': 0.9919218420982361, 'Train/mean precision': 0.9874035120010376, 'Train/mean recall': 0.9964816570281982, 'Train/mean hd95_metric': 1.005056381225586} +Epoch [2019/4000] Validation [1/4] Loss: 0.30291 focal_loss 0.23119 dice_loss 0.07172 +Epoch [2019/4000] Validation [2/4] Loss: 0.58390 focal_loss 0.39928 dice_loss 0.18462 +Epoch [2019/4000] Validation [3/4] Loss: 0.46053 focal_loss 0.35086 dice_loss 0.10968 +Epoch [2019/4000] Validation [4/4] Loss: 0.30284 focal_loss 0.19271 dice_loss 0.11013 +Epoch [2019/4000] Validation metric {'Val/mean dice_metric': 0.9718945622444153, 'Val/mean miou_metric': 0.9554276466369629, 'Val/mean f1': 0.9743172526359558, 'Val/mean precision': 0.9724640846252441, 'Val/mean recall': 0.976177453994751, 'Val/mean hd95_metric': 5.515139579772949} +Cheakpoint... +Epoch [2019/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718945622444153, 'Val/mean miou_metric': 0.9554276466369629, 'Val/mean f1': 0.9743172526359558, 'Val/mean precision': 0.9724640846252441, 'Val/mean recall': 0.976177453994751, 'Val/mean hd95_metric': 5.515139579772949} +Epoch [2020/4000] Training [1/16] Loss: 0.00862 +Epoch [2020/4000] Training [2/16] Loss: 0.00560 +Epoch [2020/4000] Training [3/16] Loss: 0.00792 +Epoch [2020/4000] Training [4/16] Loss: 0.00604 +Epoch [2020/4000] Training [5/16] Loss: 0.04388 +Epoch [2020/4000] Training [6/16] Loss: 0.00623 +Epoch [2020/4000] Training [7/16] Loss: 0.00452 +Epoch [2020/4000] Training [8/16] Loss: 0.00673 +Epoch [2020/4000] Training [9/16] Loss: 0.00641 +Epoch [2020/4000] Training [10/16] Loss: 0.00643 +Epoch [2020/4000] Training [11/16] Loss: 0.00722 +Epoch [2020/4000] Training [12/16] Loss: 0.00767 +Epoch [2020/4000] Training [13/16] Loss: 0.00498 +Epoch [2020/4000] Training [14/16] Loss: 0.00775 +Epoch [2020/4000] Training [15/16] Loss: 0.00805 +Epoch [2020/4000] Training [16/16] Loss: 0.00745 +Epoch [2020/4000] Training metric {'Train/mean dice_metric': 0.9950950145721436, 'Train/mean miou_metric': 0.9901751279830933, 'Train/mean f1': 0.9912090301513672, 'Train/mean precision': 0.9865442514419556, 'Train/mean recall': 0.9959180951118469, 'Train/mean hd95_metric': 1.1146206855773926} +Epoch [2020/4000] Validation [1/4] Loss: 0.32160 focal_loss 0.25052 dice_loss 0.07108 +Epoch [2020/4000] Validation [2/4] Loss: 0.37445 focal_loss 0.24875 dice_loss 0.12569 +Epoch [2020/4000] Validation [3/4] Loss: 0.19072 focal_loss 0.13403 dice_loss 0.05669 +Epoch [2020/4000] Validation [4/4] Loss: 0.33414 focal_loss 0.22491 dice_loss 0.10922 +Epoch [2020/4000] Validation metric {'Val/mean dice_metric': 0.9746707081794739, 'Val/mean miou_metric': 0.9574819803237915, 'Val/mean f1': 0.9748049974441528, 'Val/mean precision': 0.9718113541603088, 'Val/mean recall': 0.977817177772522, 'Val/mean hd95_metric': 4.9310503005981445} +Cheakpoint... +Epoch [2020/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746707081794739, 'Val/mean miou_metric': 0.9574819803237915, 'Val/mean f1': 0.9748049974441528, 'Val/mean precision': 0.9718113541603088, 'Val/mean recall': 0.977817177772522, 'Val/mean hd95_metric': 4.9310503005981445} +Epoch [2021/4000] Training [1/16] Loss: 0.00520 +Epoch [2021/4000] Training [2/16] Loss: 0.00550 +Epoch [2021/4000] Training [3/16] Loss: 0.00718 +Epoch [2021/4000] Training [4/16] Loss: 0.00429 +Epoch [2021/4000] Training [5/16] Loss: 0.01008 +Epoch [2021/4000] Training [6/16] Loss: 0.00641 +Epoch [2021/4000] Training [7/16] Loss: 0.00658 +Epoch [2021/4000] Training [8/16] Loss: 0.00541 +Epoch [2021/4000] Training [9/16] Loss: 0.00486 +Epoch [2021/4000] Training [10/16] Loss: 0.00593 +Epoch [2021/4000] Training [11/16] Loss: 0.00663 +Epoch [2021/4000] Training [12/16] Loss: 0.00814 +Epoch [2021/4000] Training [13/16] Loss: 0.00692 +Epoch [2021/4000] Training [14/16] Loss: 0.00519 +Epoch [2021/4000] Training [15/16] Loss: 0.00811 +Epoch [2021/4000] Training [16/16] Loss: 0.00613 +Epoch [2021/4000] Training metric {'Train/mean dice_metric': 0.9958504438400269, 'Train/mean miou_metric': 0.9914729595184326, 'Train/mean f1': 0.9917442202568054, 'Train/mean precision': 0.9873219132423401, 'Train/mean recall': 0.9962063431739807, 'Train/mean hd95_metric': 1.0184910297393799} +Epoch [2021/4000] Validation [1/4] Loss: 0.38956 focal_loss 0.30768 dice_loss 0.08188 +Epoch [2021/4000] Validation [2/4] Loss: 0.37762 focal_loss 0.25291 dice_loss 0.12471 +Epoch [2021/4000] Validation [3/4] Loss: 0.30546 focal_loss 0.21303 dice_loss 0.09243 +Epoch [2021/4000] Validation [4/4] Loss: 0.28035 focal_loss 0.18256 dice_loss 0.09779 +Epoch [2021/4000] Validation metric {'Val/mean dice_metric': 0.9730002284049988, 'Val/mean miou_metric': 0.9561376571655273, 'Val/mean f1': 0.9740272760391235, 'Val/mean precision': 0.9725013971328735, 'Val/mean recall': 0.9755579829216003, 'Val/mean hd95_metric': 5.3672075271606445} +Cheakpoint... +Epoch [2021/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730002284049988, 'Val/mean miou_metric': 0.9561376571655273, 'Val/mean f1': 0.9740272760391235, 'Val/mean precision': 0.9725013971328735, 'Val/mean recall': 0.9755579829216003, 'Val/mean hd95_metric': 5.3672075271606445} +Epoch [2022/4000] Training [1/16] Loss: 0.00672 +Epoch [2022/4000] Training [2/16] Loss: 0.00494 +Epoch [2022/4000] Training [3/16] Loss: 0.00644 +Epoch [2022/4000] Training [4/16] Loss: 0.00624 +Epoch [2022/4000] Training [5/16] Loss: 0.00852 +Epoch [2022/4000] Training [6/16] Loss: 0.00569 +Epoch [2022/4000] Training [7/16] Loss: 0.00623 +Epoch [2022/4000] Training [8/16] Loss: 0.00573 +Epoch [2022/4000] Training [9/16] Loss: 0.00734 +Epoch [2022/4000] Training [10/16] Loss: 0.00546 +Epoch [2022/4000] Training [11/16] Loss: 0.00723 +Epoch [2022/4000] Training [12/16] Loss: 0.00533 +Epoch [2022/4000] Training [13/16] Loss: 0.00528 +Epoch [2022/4000] Training [14/16] Loss: 0.00504 +Epoch [2022/4000] Training [15/16] Loss: 0.00733 +Epoch [2022/4000] Training [16/16] Loss: 0.00578 +Epoch [2022/4000] Training metric {'Train/mean dice_metric': 0.9961135387420654, 'Train/mean miou_metric': 0.9919723272323608, 'Train/mean f1': 0.991118848323822, 'Train/mean precision': 0.9858275055885315, 'Train/mean recall': 0.9964672923088074, 'Train/mean hd95_metric': 1.0120668411254883} +Epoch [2022/4000] Validation [1/4] Loss: 0.35537 focal_loss 0.28116 dice_loss 0.07422 +Epoch [2022/4000] Validation [2/4] Loss: 0.69755 focal_loss 0.48990 dice_loss 0.20765 +Epoch [2022/4000] Validation [3/4] Loss: 0.37115 focal_loss 0.27897 dice_loss 0.09218 +Epoch [2022/4000] Validation [4/4] Loss: 0.25013 focal_loss 0.15683 dice_loss 0.09330 +Epoch [2022/4000] Validation metric {'Val/mean dice_metric': 0.9716881513595581, 'Val/mean miou_metric': 0.9557258486747742, 'Val/mean f1': 0.9735543131828308, 'Val/mean precision': 0.9710450172424316, 'Val/mean recall': 0.976076602935791, 'Val/mean hd95_metric': 4.969094276428223} +Cheakpoint... +Epoch [2022/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716881513595581, 'Val/mean miou_metric': 0.9557258486747742, 'Val/mean f1': 0.9735543131828308, 'Val/mean precision': 0.9710450172424316, 'Val/mean recall': 0.976076602935791, 'Val/mean hd95_metric': 4.969094276428223} +Epoch [2023/4000] Training [1/16] Loss: 0.00546 +Epoch [2023/4000] Training [2/16] Loss: 0.00948 +Epoch [2023/4000] Training [3/16] Loss: 0.00472 +Epoch [2023/4000] Training [4/16] Loss: 0.00547 +Epoch [2023/4000] Training [5/16] Loss: 0.00695 +Epoch [2023/4000] Training [6/16] Loss: 0.00610 +Epoch [2023/4000] Training [7/16] Loss: 0.00484 +Epoch [2023/4000] Training [8/16] Loss: 0.00596 +Epoch [2023/4000] Training [9/16] Loss: 0.00528 +Epoch [2023/4000] Training [10/16] Loss: 0.00477 +Epoch [2023/4000] Training [11/16] Loss: 0.00733 +Epoch [2023/4000] Training [12/16] Loss: 0.00762 +Epoch [2023/4000] Training [13/16] Loss: 0.00796 +Epoch [2023/4000] Training [14/16] Loss: 0.00703 +Epoch [2023/4000] Training [15/16] Loss: 0.00568 +Epoch [2023/4000] Training [16/16] Loss: 0.01195 +Epoch [2023/4000] Training metric {'Train/mean dice_metric': 0.9959231615066528, 'Train/mean miou_metric': 0.9916361570358276, 'Train/mean f1': 0.9917373657226562, 'Train/mean precision': 0.9873789548873901, 'Train/mean recall': 0.9961344599723816, 'Train/mean hd95_metric': 1.010977864265442} +Epoch [2023/4000] Validation [1/4] Loss: 0.64757 focal_loss 0.53612 dice_loss 0.11146 +Epoch [2023/4000] Validation [2/4] Loss: 0.35700 focal_loss 0.23711 dice_loss 0.11988 +Epoch [2023/4000] Validation [3/4] Loss: 0.32941 focal_loss 0.24042 dice_loss 0.08898 +Epoch [2023/4000] Validation [4/4] Loss: 0.24624 focal_loss 0.15040 dice_loss 0.09585 +Epoch [2023/4000] Validation metric {'Val/mean dice_metric': 0.9718488454818726, 'Val/mean miou_metric': 0.9550444483757019, 'Val/mean f1': 0.9719441533088684, 'Val/mean precision': 0.9715425372123718, 'Val/mean recall': 0.9723461270332336, 'Val/mean hd95_metric': 5.604856491088867} +Cheakpoint... +Epoch [2023/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718488454818726, 'Val/mean miou_metric': 0.9550444483757019, 'Val/mean f1': 0.9719441533088684, 'Val/mean precision': 0.9715425372123718, 'Val/mean recall': 0.9723461270332336, 'Val/mean hd95_metric': 5.604856491088867} +Epoch [2024/4000] Training [1/16] Loss: 0.00842 +Epoch [2024/4000] Training [2/16] Loss: 0.00677 +Epoch [2024/4000] Training [3/16] Loss: 0.01124 +Epoch [2024/4000] Training [4/16] Loss: 0.00477 +Epoch [2024/4000] Training [5/16] Loss: 0.00499 +Epoch [2024/4000] Training [6/16] Loss: 0.00815 +Epoch [2024/4000] Training [7/16] Loss: 0.00461 +Epoch [2024/4000] Training [8/16] Loss: 0.00636 +Epoch [2024/4000] Training [9/16] Loss: 0.00505 +Epoch [2024/4000] Training [10/16] Loss: 0.00639 +Epoch [2024/4000] Training [11/16] Loss: 0.00637 +Epoch [2024/4000] Training [12/16] Loss: 0.00758 +Epoch [2024/4000] Training [13/16] Loss: 0.00703 +Epoch [2024/4000] Training [14/16] Loss: 0.00476 +Epoch [2024/4000] Training [15/16] Loss: 0.00598 +Epoch [2024/4000] Training [16/16] Loss: 0.00516 +Epoch [2024/4000] Training metric {'Train/mean dice_metric': 0.9959887862205505, 'Train/mean miou_metric': 0.9917335510253906, 'Train/mean f1': 0.9914359450340271, 'Train/mean precision': 0.9865447878837585, 'Train/mean recall': 0.9963758587837219, 'Train/mean hd95_metric': 1.03338623046875} +Epoch [2024/4000] Validation [1/4] Loss: 0.39241 focal_loss 0.31068 dice_loss 0.08173 +Epoch [2024/4000] Validation [2/4] Loss: 0.69616 focal_loss 0.49719 dice_loss 0.19897 +Epoch [2024/4000] Validation [3/4] Loss: 0.33091 focal_loss 0.24278 dice_loss 0.08813 +Epoch [2024/4000] Validation [4/4] Loss: 0.23208 focal_loss 0.13981 dice_loss 0.09227 +Epoch [2024/4000] Validation metric {'Val/mean dice_metric': 0.9716289639472961, 'Val/mean miou_metric': 0.9554848670959473, 'Val/mean f1': 0.9727953672409058, 'Val/mean precision': 0.9713159203529358, 'Val/mean recall': 0.9742794632911682, 'Val/mean hd95_metric': 5.36252498626709} +Cheakpoint... +Epoch [2024/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716289639472961, 'Val/mean miou_metric': 0.9554848670959473, 'Val/mean f1': 0.9727953672409058, 'Val/mean precision': 0.9713159203529358, 'Val/mean recall': 0.9742794632911682, 'Val/mean hd95_metric': 5.36252498626709} +Epoch [2025/4000] Training [1/16] Loss: 0.00718 +Epoch [2025/4000] Training [2/16] Loss: 0.00459 +Epoch [2025/4000] Training [3/16] Loss: 0.00495 +Epoch [2025/4000] Training [4/16] Loss: 0.00568 +Epoch [2025/4000] Training [5/16] Loss: 0.00626 +Epoch [2025/4000] Training [6/16] Loss: 0.00485 +Epoch [2025/4000] Training [7/16] Loss: 0.00492 +Epoch [2025/4000] Training [8/16] Loss: 0.00827 +Epoch [2025/4000] Training [9/16] Loss: 0.00554 +Epoch [2025/4000] Training [10/16] Loss: 0.00598 +Epoch [2025/4000] Training [11/16] Loss: 0.00612 +Epoch [2025/4000] Training [12/16] Loss: 0.00434 +Epoch [2025/4000] Training [13/16] Loss: 0.00491 +Epoch [2025/4000] Training [14/16] Loss: 0.00520 +Epoch [2025/4000] Training [15/16] Loss: 0.00516 +Epoch [2025/4000] Training [16/16] Loss: 0.00681 +Epoch [2025/4000] Training metric {'Train/mean dice_metric': 0.9962180852890015, 'Train/mean miou_metric': 0.9922032356262207, 'Train/mean f1': 0.9919298887252808, 'Train/mean precision': 0.9875035881996155, 'Train/mean recall': 0.9963960647583008, 'Train/mean hd95_metric': 0.9976847171783447} +Epoch [2025/4000] Validation [1/4] Loss: 0.48259 focal_loss 0.38386 dice_loss 0.09873 +Epoch [2025/4000] Validation [2/4] Loss: 0.82258 focal_loss 0.57859 dice_loss 0.24399 +Epoch [2025/4000] Validation [3/4] Loss: 0.33110 focal_loss 0.23949 dice_loss 0.09162 +Epoch [2025/4000] Validation [4/4] Loss: 0.27493 focal_loss 0.17468 dice_loss 0.10025 +Epoch [2025/4000] Validation metric {'Val/mean dice_metric': 0.9711881875991821, 'Val/mean miou_metric': 0.9546316266059875, 'Val/mean f1': 0.9723305106163025, 'Val/mean precision': 0.9705756306648254, 'Val/mean recall': 0.9740917086601257, 'Val/mean hd95_metric': 5.533181190490723} +Cheakpoint... +Epoch [2025/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711881875991821, 'Val/mean miou_metric': 0.9546316266059875, 'Val/mean f1': 0.9723305106163025, 'Val/mean precision': 0.9705756306648254, 'Val/mean recall': 0.9740917086601257, 'Val/mean hd95_metric': 5.533181190490723} +Epoch [2026/4000] Training [1/16] Loss: 0.00454 +Epoch [2026/4000] Training [2/16] Loss: 0.00628 +Epoch [2026/4000] Training [3/16] Loss: 0.00561 +Epoch [2026/4000] Training [4/16] Loss: 0.00430 +Epoch [2026/4000] Training [5/16] Loss: 0.00416 +Epoch [2026/4000] Training [6/16] Loss: 0.00507 +Epoch [2026/4000] Training [7/16] Loss: 0.00439 +Epoch [2026/4000] Training [8/16] Loss: 0.00564 +Epoch [2026/4000] Training [9/16] Loss: 0.00851 +Epoch [2026/4000] Training [10/16] Loss: 0.00555 +Epoch [2026/4000] Training [11/16] Loss: 0.00601 +Epoch [2026/4000] Training [12/16] Loss: 0.00499 +Epoch [2026/4000] Training [13/16] Loss: 0.00603 +Epoch [2026/4000] Training [14/16] Loss: 0.00531 +Epoch [2026/4000] Training [15/16] Loss: 0.00579 +Epoch [2026/4000] Training [16/16] Loss: 0.00434 +Epoch [2026/4000] Training metric {'Train/mean dice_metric': 0.9963521361351013, 'Train/mean miou_metric': 0.9924655556678772, 'Train/mean f1': 0.9920527935028076, 'Train/mean precision': 0.9874589443206787, 'Train/mean recall': 0.9966897368431091, 'Train/mean hd95_metric': 1.045247197151184} +Epoch [2026/4000] Validation [1/4] Loss: 0.28090 focal_loss 0.21342 dice_loss 0.06748 +Epoch [2026/4000] Validation [2/4] Loss: 0.29284 focal_loss 0.18185 dice_loss 0.11100 +Epoch [2026/4000] Validation [3/4] Loss: 0.17508 focal_loss 0.12043 dice_loss 0.05464 +Epoch [2026/4000] Validation [4/4] Loss: 0.21877 focal_loss 0.12865 dice_loss 0.09012 +Epoch [2026/4000] Validation metric {'Val/mean dice_metric': 0.9745933413505554, 'Val/mean miou_metric': 0.9583995938301086, 'Val/mean f1': 0.9749093055725098, 'Val/mean precision': 0.9729704856872559, 'Val/mean recall': 0.9768559336662292, 'Val/mean hd95_metric': 5.2528557777404785} +Cheakpoint... +Epoch [2026/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745933413505554, 'Val/mean miou_metric': 0.9583995938301086, 'Val/mean f1': 0.9749093055725098, 'Val/mean precision': 0.9729704856872559, 'Val/mean recall': 0.9768559336662292, 'Val/mean hd95_metric': 5.2528557777404785} +Epoch [2027/4000] Training [1/16] Loss: 0.00574 +Epoch [2027/4000] Training [2/16] Loss: 0.00531 +Epoch [2027/4000] Training [3/16] Loss: 0.00551 +Epoch [2027/4000] Training [4/16] Loss: 0.00549 +Epoch [2027/4000] Training [5/16] Loss: 0.00381 +Epoch [2027/4000] Training [6/16] Loss: 0.00487 +Epoch [2027/4000] Training [7/16] Loss: 0.00588 +Epoch [2027/4000] Training [8/16] Loss: 0.00444 +Epoch [2027/4000] Training [9/16] Loss: 0.00645 +Epoch [2027/4000] Training [10/16] Loss: 0.00463 +Epoch [2027/4000] Training [11/16] Loss: 0.00542 +Epoch [2027/4000] Training [12/16] Loss: 0.02029 +Epoch [2027/4000] Training [13/16] Loss: 0.00796 +Epoch [2027/4000] Training [14/16] Loss: 0.00552 +Epoch [2027/4000] Training [15/16] Loss: 0.00708 +Epoch [2027/4000] Training [16/16] Loss: 0.00462 +Epoch [2027/4000] Training metric {'Train/mean dice_metric': 0.9961691498756409, 'Train/mean miou_metric': 0.9921131730079651, 'Train/mean f1': 0.9918318390846252, 'Train/mean precision': 0.9872584939002991, 'Train/mean recall': 0.9964478611946106, 'Train/mean hd95_metric': 1.0468491315841675} +Epoch [2027/4000] Validation [1/4] Loss: 0.46249 focal_loss 0.37267 dice_loss 0.08982 +Epoch [2027/4000] Validation [2/4] Loss: 0.70466 focal_loss 0.50906 dice_loss 0.19560 +Epoch [2027/4000] Validation [3/4] Loss: 0.36483 focal_loss 0.27008 dice_loss 0.09475 +Epoch [2027/4000] Validation [4/4] Loss: 0.27473 focal_loss 0.17017 dice_loss 0.10457 +Epoch [2027/4000] Validation metric {'Val/mean dice_metric': 0.9710956811904907, 'Val/mean miou_metric': 0.9541174173355103, 'Val/mean f1': 0.9723406434059143, 'Val/mean precision': 0.9726959466934204, 'Val/mean recall': 0.9719854593276978, 'Val/mean hd95_metric': 5.616099834442139} +Cheakpoint... +Epoch [2027/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710956811904907, 'Val/mean miou_metric': 0.9541174173355103, 'Val/mean f1': 0.9723406434059143, 'Val/mean precision': 0.9726959466934204, 'Val/mean recall': 0.9719854593276978, 'Val/mean hd95_metric': 5.616099834442139} +Epoch [2028/4000] Training [1/16] Loss: 0.00718 +Epoch [2028/4000] Training [2/16] Loss: 0.00424 +Epoch [2028/4000] Training [3/16] Loss: 0.00665 +Epoch [2028/4000] Training [4/16] Loss: 0.00542 +Epoch [2028/4000] Training [5/16] Loss: 0.00594 +Epoch [2028/4000] Training [6/16] Loss: 0.00632 +Epoch [2028/4000] Training [7/16] Loss: 0.00409 +Epoch [2028/4000] Training [8/16] Loss: 0.00660 +Epoch [2028/4000] Training [9/16] Loss: 0.00658 +Epoch [2028/4000] Training [10/16] Loss: 0.00471 +Epoch [2028/4000] Training [11/16] Loss: 0.00629 +Epoch [2028/4000] Training [12/16] Loss: 0.00538 +Epoch [2028/4000] Training [13/16] Loss: 0.00777 +Epoch [2028/4000] Training [14/16] Loss: 0.00418 +Epoch [2028/4000] Training [15/16] Loss: 0.00702 +Epoch [2028/4000] Training [16/16] Loss: 0.00561 +Epoch [2028/4000] Training metric {'Train/mean dice_metric': 0.9961056709289551, 'Train/mean miou_metric': 0.9919499754905701, 'Train/mean f1': 0.9910518527030945, 'Train/mean precision': 0.9858238101005554, 'Train/mean recall': 0.9963356852531433, 'Train/mean hd95_metric': 1.0178300142288208} +Epoch [2028/4000] Validation [1/4] Loss: 0.31842 focal_loss 0.24622 dice_loss 0.07220 +Epoch [2028/4000] Validation [2/4] Loss: 0.58783 focal_loss 0.39452 dice_loss 0.19331 +Epoch [2028/4000] Validation [3/4] Loss: 0.17840 focal_loss 0.12375 dice_loss 0.05465 +Epoch [2028/4000] Validation [4/4] Loss: 0.31829 focal_loss 0.20515 dice_loss 0.11314 +Epoch [2028/4000] Validation metric {'Val/mean dice_metric': 0.969738781452179, 'Val/mean miou_metric': 0.9532594680786133, 'Val/mean f1': 0.9729790687561035, 'Val/mean precision': 0.9731042981147766, 'Val/mean recall': 0.9728536605834961, 'Val/mean hd95_metric': 5.668102264404297} +Cheakpoint... +Epoch [2028/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969738781452179, 'Val/mean miou_metric': 0.9532594680786133, 'Val/mean f1': 0.9729790687561035, 'Val/mean precision': 0.9731042981147766, 'Val/mean recall': 0.9728536605834961, 'Val/mean hd95_metric': 5.668102264404297} +Epoch [2029/4000] Training [1/16] Loss: 0.00584 +Epoch [2029/4000] Training [2/16] Loss: 0.00542 +Epoch [2029/4000] Training [3/16] Loss: 0.00459 +Epoch [2029/4000] Training [4/16] Loss: 0.00627 +Epoch [2029/4000] Training [5/16] Loss: 0.00596 +Epoch [2029/4000] Training [6/16] Loss: 0.00404 +Epoch [2029/4000] Training [7/16] Loss: 0.00686 +Epoch [2029/4000] Training [8/16] Loss: 0.00622 +Epoch [2029/4000] Training [9/16] Loss: 0.00867 +Epoch [2029/4000] Training [10/16] Loss: 0.00545 +Epoch [2029/4000] Training [11/16] Loss: 0.00688 +Epoch [2029/4000] Training [12/16] Loss: 0.00560 +Epoch [2029/4000] Training [13/16] Loss: 0.00503 +Epoch [2029/4000] Training [14/16] Loss: 0.00750 +Epoch [2029/4000] Training [15/16] Loss: 0.00603 +Epoch [2029/4000] Training [16/16] Loss: 0.00435 +Epoch [2029/4000] Training metric {'Train/mean dice_metric': 0.9960919618606567, 'Train/mean miou_metric': 0.9919549822807312, 'Train/mean f1': 0.991865336894989, 'Train/mean precision': 0.9875101447105408, 'Train/mean recall': 0.9962591528892517, 'Train/mean hd95_metric': 1.0052450895309448} +Epoch [2029/4000] Validation [1/4] Loss: 0.28908 focal_loss 0.22286 dice_loss 0.06622 +Epoch [2029/4000] Validation [2/4] Loss: 0.37979 focal_loss 0.26058 dice_loss 0.11921 +Epoch [2029/4000] Validation [3/4] Loss: 0.42706 focal_loss 0.32327 dice_loss 0.10378 +Epoch [2029/4000] Validation [4/4] Loss: 0.23047 focal_loss 0.14057 dice_loss 0.08990 +Epoch [2029/4000] Validation metric {'Val/mean dice_metric': 0.9731259346008301, 'Val/mean miou_metric': 0.956429123878479, 'Val/mean f1': 0.9741460084915161, 'Val/mean precision': 0.9702823758125305, 'Val/mean recall': 0.9780405759811401, 'Val/mean hd95_metric': 6.032086372375488} +Cheakpoint... +Epoch [2029/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731259346008301, 'Val/mean miou_metric': 0.956429123878479, 'Val/mean f1': 0.9741460084915161, 'Val/mean precision': 0.9702823758125305, 'Val/mean recall': 0.9780405759811401, 'Val/mean hd95_metric': 6.032086372375488} +Epoch [2030/4000] Training [1/16] Loss: 0.00444 +Epoch [2030/4000] Training [2/16] Loss: 0.00662 +Epoch [2030/4000] Training [3/16] Loss: 0.00651 +Epoch [2030/4000] Training [4/16] Loss: 0.00597 +Epoch [2030/4000] Training [5/16] Loss: 0.00558 +Epoch [2030/4000] Training [6/16] Loss: 0.00530 +Epoch [2030/4000] Training [7/16] Loss: 0.00997 +Epoch [2030/4000] Training [8/16] Loss: 0.00649 +Epoch [2030/4000] Training [9/16] Loss: 0.00652 +Epoch [2030/4000] Training [10/16] Loss: 0.00963 +Epoch [2030/4000] Training [11/16] Loss: 0.00728 +Epoch [2030/4000] Training [12/16] Loss: 0.00720 +Epoch [2030/4000] Training [13/16] Loss: 0.00952 +Epoch [2030/4000] Training [14/16] Loss: 0.00619 +Epoch [2030/4000] Training [15/16] Loss: 0.00548 +Epoch [2030/4000] Training [16/16] Loss: 0.00503 +Epoch [2030/4000] Training metric {'Train/mean dice_metric': 0.9958654642105103, 'Train/mean miou_metric': 0.9915140271186829, 'Train/mean f1': 0.9916492700576782, 'Train/mean precision': 0.9871716499328613, 'Train/mean recall': 0.9961677193641663, 'Train/mean hd95_metric': 1.087557315826416} +Epoch [2030/4000] Validation [1/4] Loss: 0.25499 focal_loss 0.19507 dice_loss 0.05992 +Epoch [2030/4000] Validation [2/4] Loss: 0.36477 focal_loss 0.22857 dice_loss 0.13620 +Epoch [2030/4000] Validation [3/4] Loss: 0.17144 focal_loss 0.11649 dice_loss 0.05496 +Epoch [2030/4000] Validation [4/4] Loss: 0.23346 focal_loss 0.15394 dice_loss 0.07952 +Epoch [2030/4000] Validation metric {'Val/mean dice_metric': 0.9759475588798523, 'Val/mean miou_metric': 0.9594641923904419, 'Val/mean f1': 0.9757977724075317, 'Val/mean precision': 0.9734297394752502, 'Val/mean recall': 0.9781771898269653, 'Val/mean hd95_metric': 4.886665344238281} +Cheakpoint... +Epoch [2030/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759475588798523, 'Val/mean miou_metric': 0.9594641923904419, 'Val/mean f1': 0.9757977724075317, 'Val/mean precision': 0.9734297394752502, 'Val/mean recall': 0.9781771898269653, 'Val/mean hd95_metric': 4.886665344238281} +Epoch [2031/4000] Training [1/16] Loss: 0.00613 +Epoch [2031/4000] Training [2/16] Loss: 0.00478 +Epoch [2031/4000] Training [3/16] Loss: 0.00514 +Epoch [2031/4000] Training [4/16] Loss: 0.00608 +Epoch [2031/4000] Training [5/16] Loss: 0.00673 +Epoch [2031/4000] Training [6/16] Loss: 0.00555 +Epoch [2031/4000] Training [7/16] Loss: 0.00551 +Epoch [2031/4000] Training [8/16] Loss: 0.00601 +Epoch [2031/4000] Training [9/16] Loss: 0.00736 +Epoch [2031/4000] Training [10/16] Loss: 0.00757 +Epoch [2031/4000] Training [11/16] Loss: 0.00870 +Epoch [2031/4000] Training [12/16] Loss: 0.00445 +Epoch [2031/4000] Training [13/16] Loss: 0.00427 +Epoch [2031/4000] Training [14/16] Loss: 0.00669 +Epoch [2031/4000] Training [15/16] Loss: 0.00775 +Epoch [2031/4000] Training [16/16] Loss: 0.00491 +Epoch [2031/4000] Training metric {'Train/mean dice_metric': 0.9960414171218872, 'Train/mean miou_metric': 0.9918640851974487, 'Train/mean f1': 0.9915837645530701, 'Train/mean precision': 0.9868353009223938, 'Train/mean recall': 0.9963780641555786, 'Train/mean hd95_metric': 1.049560308456421} +Epoch [2031/4000] Validation [1/4] Loss: 0.26731 focal_loss 0.20939 dice_loss 0.05792 +Epoch [2031/4000] Validation [2/4] Loss: 0.27002 focal_loss 0.15439 dice_loss 0.11563 +Epoch [2031/4000] Validation [3/4] Loss: 0.18439 focal_loss 0.13014 dice_loss 0.05425 +Epoch [2031/4000] Validation [4/4] Loss: 0.32401 focal_loss 0.22766 dice_loss 0.09634 +Epoch [2031/4000] Validation metric {'Val/mean dice_metric': 0.9735028147697449, 'Val/mean miou_metric': 0.9576120376586914, 'Val/mean f1': 0.9755319952964783, 'Val/mean precision': 0.9723066091537476, 'Val/mean recall': 0.9787788391113281, 'Val/mean hd95_metric': 5.008028030395508} +Cheakpoint... +Epoch [2031/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735028147697449, 'Val/mean miou_metric': 0.9576120376586914, 'Val/mean f1': 0.9755319952964783, 'Val/mean precision': 0.9723066091537476, 'Val/mean recall': 0.9787788391113281, 'Val/mean hd95_metric': 5.008028030395508} +Epoch [2032/4000] Training [1/16] Loss: 0.00612 +Epoch [2032/4000] Training [2/16] Loss: 0.00453 +Epoch [2032/4000] Training [3/16] Loss: 0.00586 +Epoch [2032/4000] Training [4/16] Loss: 0.00667 +Epoch [2032/4000] Training [5/16] Loss: 0.00654 +Epoch [2032/4000] Training [6/16] Loss: 0.00475 +Epoch [2032/4000] Training [7/16] Loss: 0.00690 +Epoch [2032/4000] Training [8/16] Loss: 0.00731 +Epoch [2032/4000] Training [9/16] Loss: 0.00725 +Epoch [2032/4000] Training [10/16] Loss: 0.00478 +Epoch [2032/4000] Training [11/16] Loss: 0.00646 +Epoch [2032/4000] Training [12/16] Loss: 0.00440 +Epoch [2032/4000] Training [13/16] Loss: 0.00804 +Epoch [2032/4000] Training [14/16] Loss: 0.00654 +Epoch [2032/4000] Training [15/16] Loss: 0.00482 +Epoch [2032/4000] Training [16/16] Loss: 0.00658 +Epoch [2032/4000] Training metric {'Train/mean dice_metric': 0.9960214495658875, 'Train/mean miou_metric': 0.9918091297149658, 'Train/mean f1': 0.9917293787002563, 'Train/mean precision': 0.9871805310249329, 'Train/mean recall': 0.996320366859436, 'Train/mean hd95_metric': 1.0086743831634521} +Epoch [2032/4000] Validation [1/4] Loss: 0.30997 focal_loss 0.23873 dice_loss 0.07124 +Epoch [2032/4000] Validation [2/4] Loss: 0.35382 focal_loss 0.23361 dice_loss 0.12021 +Epoch [2032/4000] Validation [3/4] Loss: 0.28631 focal_loss 0.20047 dice_loss 0.08584 +Epoch [2032/4000] Validation [4/4] Loss: 0.25383 focal_loss 0.16437 dice_loss 0.08946 +Epoch [2032/4000] Validation metric {'Val/mean dice_metric': 0.9705455899238586, 'Val/mean miou_metric': 0.9540435671806335, 'Val/mean f1': 0.9738296866416931, 'Val/mean precision': 0.9723011255264282, 'Val/mean recall': 0.9753631353378296, 'Val/mean hd95_metric': 5.668795108795166} +Cheakpoint... +Epoch [2032/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705455899238586, 'Val/mean miou_metric': 0.9540435671806335, 'Val/mean f1': 0.9738296866416931, 'Val/mean precision': 0.9723011255264282, 'Val/mean recall': 0.9753631353378296, 'Val/mean hd95_metric': 5.668795108795166} +Epoch [2033/4000] Training [1/16] Loss: 0.00772 +Epoch [2033/4000] Training [2/16] Loss: 0.00459 +Epoch [2033/4000] Training [3/16] Loss: 0.00586 +Epoch [2033/4000] Training [4/16] Loss: 0.00753 +Epoch [2033/4000] Training [5/16] Loss: 0.00645 +Epoch [2033/4000] Training [6/16] Loss: 0.00628 +Epoch [2033/4000] Training [7/16] Loss: 0.00459 +Epoch [2033/4000] Training [8/16] Loss: 0.00601 +Epoch [2033/4000] Training [9/16] Loss: 0.00644 +Epoch [2033/4000] Training [10/16] Loss: 0.00598 +Epoch [2033/4000] Training [11/16] Loss: 0.00517 +Epoch [2033/4000] Training [12/16] Loss: 0.00422 +Epoch [2033/4000] Training [13/16] Loss: 0.00598 +Epoch [2033/4000] Training [14/16] Loss: 0.00636 +Epoch [2033/4000] Training [15/16] Loss: 0.00436 +Epoch [2033/4000] Training [16/16] Loss: 0.00484 +Epoch [2033/4000] Training metric {'Train/mean dice_metric': 0.9959928393363953, 'Train/mean miou_metric': 0.9917554259300232, 'Train/mean f1': 0.9910027980804443, 'Train/mean precision': 0.985669732093811, 'Train/mean recall': 0.9963938593864441, 'Train/mean hd95_metric': 1.0146669149398804} +Epoch [2033/4000] Validation [1/4] Loss: 0.34810 focal_loss 0.27488 dice_loss 0.07322 +Epoch [2033/4000] Validation [2/4] Loss: 0.73377 focal_loss 0.50160 dice_loss 0.23216 +Epoch [2033/4000] Validation [3/4] Loss: 0.32238 focal_loss 0.23246 dice_loss 0.08992 +Epoch [2033/4000] Validation [4/4] Loss: 0.29240 focal_loss 0.19147 dice_loss 0.10092 +Epoch [2033/4000] Validation metric {'Val/mean dice_metric': 0.9719297289848328, 'Val/mean miou_metric': 0.9551035761833191, 'Val/mean f1': 0.9715605974197388, 'Val/mean precision': 0.9693296551704407, 'Val/mean recall': 0.973801851272583, 'Val/mean hd95_metric': 5.7907915115356445} +Cheakpoint... +Epoch [2033/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719297289848328, 'Val/mean miou_metric': 0.9551035761833191, 'Val/mean f1': 0.9715605974197388, 'Val/mean precision': 0.9693296551704407, 'Val/mean recall': 0.973801851272583, 'Val/mean hd95_metric': 5.7907915115356445} +Epoch [2034/4000] Training [1/16] Loss: 0.00578 +Epoch [2034/4000] Training [2/16] Loss: 0.01097 +Epoch [2034/4000] Training [3/16] Loss: 0.00926 +Epoch [2034/4000] Training [4/16] Loss: 0.00447 +Epoch [2034/4000] Training [5/16] Loss: 0.01072 +Epoch [2034/4000] Training [6/16] Loss: 0.00578 +Epoch [2034/4000] Training [7/16] Loss: 0.00394 +Epoch [2034/4000] Training [8/16] Loss: 0.00525 +Epoch [2034/4000] Training [9/16] Loss: 0.00544 +Epoch [2034/4000] Training [10/16] Loss: 0.00547 +Epoch [2034/4000] Training [11/16] Loss: 0.00566 +Epoch [2034/4000] Training [12/16] Loss: 0.00432 +Epoch [2034/4000] Training [13/16] Loss: 0.00467 +Epoch [2034/4000] Training [14/16] Loss: 0.00491 +Epoch [2034/4000] Training [15/16] Loss: 0.00535 +Epoch [2034/4000] Training [16/16] Loss: 0.00672 +Epoch [2034/4000] Training metric {'Train/mean dice_metric': 0.9959253072738647, 'Train/mean miou_metric': 0.9916090965270996, 'Train/mean f1': 0.9914442300796509, 'Train/mean precision': 0.9867777824401855, 'Train/mean recall': 0.9961550235748291, 'Train/mean hd95_metric': 1.0158610343933105} +Epoch [2034/4000] Validation [1/4] Loss: 0.32650 focal_loss 0.25671 dice_loss 0.06979 +Epoch [2034/4000] Validation [2/4] Loss: 0.77891 focal_loss 0.57459 dice_loss 0.20432 +Epoch [2034/4000] Validation [3/4] Loss: 0.34807 focal_loss 0.25487 dice_loss 0.09320 +Epoch [2034/4000] Validation [4/4] Loss: 0.21223 focal_loss 0.13017 dice_loss 0.08206 +Epoch [2034/4000] Validation metric {'Val/mean dice_metric': 0.9721255302429199, 'Val/mean miou_metric': 0.9557304382324219, 'Val/mean f1': 0.9735426306724548, 'Val/mean precision': 0.9716306924819946, 'Val/mean recall': 0.9754621386528015, 'Val/mean hd95_metric': 5.274627685546875} +Cheakpoint... +Epoch [2034/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721255302429199, 'Val/mean miou_metric': 0.9557304382324219, 'Val/mean f1': 0.9735426306724548, 'Val/mean precision': 0.9716306924819946, 'Val/mean recall': 0.9754621386528015, 'Val/mean hd95_metric': 5.274627685546875} +Epoch [2035/4000] Training [1/16] Loss: 0.00497 +Epoch [2035/4000] Training [2/16] Loss: 0.00558 +Epoch [2035/4000] Training [3/16] Loss: 0.00486 +Epoch [2035/4000] Training [4/16] Loss: 0.00605 +Epoch [2035/4000] Training [5/16] Loss: 0.00525 +Epoch [2035/4000] Training [6/16] Loss: 0.00467 +Epoch [2035/4000] Training [7/16] Loss: 0.00807 +Epoch [2035/4000] Training [8/16] Loss: 0.00672 +Epoch [2035/4000] Training [9/16] Loss: 0.00464 +Epoch [2035/4000] Training [10/16] Loss: 0.00637 +Epoch [2035/4000] Training [11/16] Loss: 0.00422 +Epoch [2035/4000] Training [12/16] Loss: 0.00406 +Epoch [2035/4000] Training [13/16] Loss: 0.00916 +Epoch [2035/4000] Training [14/16] Loss: 0.00842 +Epoch [2035/4000] Training [15/16] Loss: 0.00491 +Epoch [2035/4000] Training [16/16] Loss: 0.00452 +Epoch [2035/4000] Training metric {'Train/mean dice_metric': 0.9963436126708984, 'Train/mean miou_metric': 0.9924348592758179, 'Train/mean f1': 0.9918667078018188, 'Train/mean precision': 0.9871648550033569, 'Train/mean recall': 0.9966135621070862, 'Train/mean hd95_metric': 1.0082921981811523} +Epoch [2035/4000] Validation [1/4] Loss: 0.29720 focal_loss 0.22985 dice_loss 0.06735 +Epoch [2035/4000] Validation [2/4] Loss: 0.33387 focal_loss 0.22124 dice_loss 0.11263 +Epoch [2035/4000] Validation [3/4] Loss: 0.31829 focal_loss 0.22923 dice_loss 0.08906 +Epoch [2035/4000] Validation [4/4] Loss: 0.45260 focal_loss 0.31895 dice_loss 0.13366 +Epoch [2035/4000] Validation metric {'Val/mean dice_metric': 0.9737554788589478, 'Val/mean miou_metric': 0.9575449228286743, 'Val/mean f1': 0.9741635918617249, 'Val/mean precision': 0.9718379974365234, 'Val/mean recall': 0.9765001535415649, 'Val/mean hd95_metric': 5.62724494934082} +Cheakpoint... +Epoch [2035/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737554788589478, 'Val/mean miou_metric': 0.9575449228286743, 'Val/mean f1': 0.9741635918617249, 'Val/mean precision': 0.9718379974365234, 'Val/mean recall': 0.9765001535415649, 'Val/mean hd95_metric': 5.62724494934082} +Epoch [2036/4000] Training [1/16] Loss: 0.00511 +Epoch [2036/4000] Training [2/16] Loss: 0.00463 +Epoch [2036/4000] Training [3/16] Loss: 0.00636 +Epoch [2036/4000] Training [4/16] Loss: 0.00861 +Epoch [2036/4000] Training [5/16] Loss: 0.00684 +Epoch [2036/4000] Training [6/16] Loss: 0.00501 +Epoch [2036/4000] Training [7/16] Loss: 0.00499 +Epoch [2036/4000] Training [8/16] Loss: 0.00546 +Epoch [2036/4000] Training [9/16] Loss: 0.00624 +Epoch [2036/4000] Training [10/16] Loss: 0.00446 +Epoch [2036/4000] Training [11/16] Loss: 0.00498 +Epoch [2036/4000] Training [12/16] Loss: 0.00991 +Epoch [2036/4000] Training [13/16] Loss: 0.00659 +Epoch [2036/4000] Training [14/16] Loss: 0.00649 +Epoch [2036/4000] Training [15/16] Loss: 0.00617 +Epoch [2036/4000] Training [16/16] Loss: 0.00555 +Epoch [2036/4000] Training metric {'Train/mean dice_metric': 0.9959776401519775, 'Train/mean miou_metric': 0.9916954040527344, 'Train/mean f1': 0.9914038181304932, 'Train/mean precision': 0.9865157008171082, 'Train/mean recall': 0.9963406324386597, 'Train/mean hd95_metric': 1.0016052722930908} +Epoch [2036/4000] Validation [1/4] Loss: 0.36432 focal_loss 0.29090 dice_loss 0.07342 +Epoch [2036/4000] Validation [2/4] Loss: 0.74292 focal_loss 0.52272 dice_loss 0.22020 +Epoch [2036/4000] Validation [3/4] Loss: 0.34171 focal_loss 0.25157 dice_loss 0.09015 +Epoch [2036/4000] Validation [4/4] Loss: 0.43377 focal_loss 0.30762 dice_loss 0.12615 +Epoch [2036/4000] Validation metric {'Val/mean dice_metric': 0.971783459186554, 'Val/mean miou_metric': 0.9550315141677856, 'Val/mean f1': 0.9732854962348938, 'Val/mean precision': 0.9706624150276184, 'Val/mean recall': 0.9759227633476257, 'Val/mean hd95_metric': 5.512064456939697} +Cheakpoint... +Epoch [2036/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971783459186554, 'Val/mean miou_metric': 0.9550315141677856, 'Val/mean f1': 0.9732854962348938, 'Val/mean precision': 0.9706624150276184, 'Val/mean recall': 0.9759227633476257, 'Val/mean hd95_metric': 5.512064456939697} +Epoch [2037/4000] Training [1/16] Loss: 0.00542 +Epoch [2037/4000] Training [2/16] Loss: 0.00514 +Epoch [2037/4000] Training [3/16] Loss: 0.00499 +Epoch [2037/4000] Training [4/16] Loss: 0.00659 +Epoch [2037/4000] Training [5/16] Loss: 0.00640 +Epoch [2037/4000] Training [6/16] Loss: 0.00593 +Epoch [2037/4000] Training [7/16] Loss: 0.00507 +Epoch [2037/4000] Training [8/16] Loss: 0.00487 +Epoch [2037/4000] Training [9/16] Loss: 0.00486 +Epoch [2037/4000] Training [10/16] Loss: 0.00454 +Epoch [2037/4000] Training [11/16] Loss: 0.00689 +Epoch [2037/4000] Training [12/16] Loss: 0.00606 +Epoch [2037/4000] Training [13/16] Loss: 0.00552 +Epoch [2037/4000] Training [14/16] Loss: 0.00624 +Epoch [2037/4000] Training [15/16] Loss: 0.00686 +Epoch [2037/4000] Training [16/16] Loss: 0.00880 +Epoch [2037/4000] Training metric {'Train/mean dice_metric': 0.9953303337097168, 'Train/mean miou_metric': 0.9908904433250427, 'Train/mean f1': 0.9914814829826355, 'Train/mean precision': 0.9867081046104431, 'Train/mean recall': 0.9963012337684631, 'Train/mean hd95_metric': 1.070955753326416} +Epoch [2037/4000] Validation [1/4] Loss: 0.90275 focal_loss 0.78518 dice_loss 0.11757 +Epoch [2037/4000] Validation [2/4] Loss: 0.75017 focal_loss 0.52852 dice_loss 0.22164 +Epoch [2037/4000] Validation [3/4] Loss: 0.34469 focal_loss 0.25378 dice_loss 0.09091 +Epoch [2037/4000] Validation [4/4] Loss: 0.26246 focal_loss 0.17010 dice_loss 0.09236 +Epoch [2037/4000] Validation metric {'Val/mean dice_metric': 0.9701663851737976, 'Val/mean miou_metric': 0.9534627795219421, 'Val/mean f1': 0.9713302254676819, 'Val/mean precision': 0.9714287519454956, 'Val/mean recall': 0.9712318181991577, 'Val/mean hd95_metric': 5.200589656829834} +Cheakpoint... +Epoch [2037/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701663851737976, 'Val/mean miou_metric': 0.9534627795219421, 'Val/mean f1': 0.9713302254676819, 'Val/mean precision': 0.9714287519454956, 'Val/mean recall': 0.9712318181991577, 'Val/mean hd95_metric': 5.200589656829834} +Epoch [2038/4000] Training [1/16] Loss: 0.00626 +Epoch [2038/4000] Training [2/16] Loss: 0.00485 +Epoch [2038/4000] Training [3/16] Loss: 0.00415 +Epoch [2038/4000] Training [4/16] Loss: 0.00445 +Epoch [2038/4000] Training [5/16] Loss: 0.00475 +Epoch [2038/4000] Training [6/16] Loss: 0.00466 +Epoch [2038/4000] Training [7/16] Loss: 0.00614 +Epoch [2038/4000] Training [8/16] Loss: 0.00702 +Epoch [2038/4000] Training [9/16] Loss: 0.00641 +Epoch [2038/4000] Training [10/16] Loss: 0.00628 +Epoch [2038/4000] Training [11/16] Loss: 0.00542 +Epoch [2038/4000] Training [12/16] Loss: 0.00589 +Epoch [2038/4000] Training [13/16] Loss: 0.00475 +Epoch [2038/4000] Training [14/16] Loss: 0.00659 +Epoch [2038/4000] Training [15/16] Loss: 0.00473 +Epoch [2038/4000] Training [16/16] Loss: 0.00628 +Epoch [2038/4000] Training metric {'Train/mean dice_metric': 0.9963995814323425, 'Train/mean miou_metric': 0.992527961730957, 'Train/mean f1': 0.9912842512130737, 'Train/mean precision': 0.9860361814498901, 'Train/mean recall': 0.996588408946991, 'Train/mean hd95_metric': 1.050443172454834} +Epoch [2038/4000] Validation [1/4] Loss: 1.17053 focal_loss 1.02423 dice_loss 0.14630 +Epoch [2038/4000] Validation [2/4] Loss: 0.78605 focal_loss 0.59379 dice_loss 0.19226 +Epoch [2038/4000] Validation [3/4] Loss: 0.42450 focal_loss 0.31843 dice_loss 0.10608 +Epoch [2038/4000] Validation [4/4] Loss: 0.24859 focal_loss 0.16530 dice_loss 0.08329 +Epoch [2038/4000] Validation metric {'Val/mean dice_metric': 0.9647024273872375, 'Val/mean miou_metric': 0.9491952657699585, 'Val/mean f1': 0.9686034321784973, 'Val/mean precision': 0.9727764129638672, 'Val/mean recall': 0.9644661545753479, 'Val/mean hd95_metric': 5.393681049346924} +Cheakpoint... +Epoch [2038/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9647], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647024273872375, 'Val/mean miou_metric': 0.9491952657699585, 'Val/mean f1': 0.9686034321784973, 'Val/mean precision': 0.9727764129638672, 'Val/mean recall': 0.9644661545753479, 'Val/mean hd95_metric': 5.393681049346924} +Epoch [2039/4000] Training [1/16] Loss: 0.00705 +Epoch [2039/4000] Training [2/16] Loss: 0.00488 +Epoch [2039/4000] Training [3/16] Loss: 0.00559 +Epoch [2039/4000] Training [4/16] Loss: 0.00431 +Epoch [2039/4000] Training [5/16] Loss: 0.00748 +Epoch [2039/4000] Training [6/16] Loss: 0.00474 +Epoch [2039/4000] Training [7/16] Loss: 0.00485 +Epoch [2039/4000] Training [8/16] Loss: 0.00434 +Epoch [2039/4000] Training [9/16] Loss: 0.00525 +Epoch [2039/4000] Training [10/16] Loss: 0.00503 +Epoch [2039/4000] Training [11/16] Loss: 0.00732 +Epoch [2039/4000] Training [12/16] Loss: 0.00529 +Epoch [2039/4000] Training [13/16] Loss: 0.00610 +Epoch [2039/4000] Training [14/16] Loss: 0.00433 +Epoch [2039/4000] Training [15/16] Loss: 0.00490 +Epoch [2039/4000] Training [16/16] Loss: 0.00872 +Epoch [2039/4000] Training metric {'Train/mean dice_metric': 0.9961032867431641, 'Train/mean miou_metric': 0.9919431209564209, 'Train/mean f1': 0.9910650849342346, 'Train/mean precision': 0.9858294129371643, 'Train/mean recall': 0.9963566064834595, 'Train/mean hd95_metric': 1.0229053497314453} +Epoch [2039/4000] Validation [1/4] Loss: 1.22932 focal_loss 1.07926 dice_loss 0.15006 +Epoch [2039/4000] Validation [2/4] Loss: 1.08803 focal_loss 0.78908 dice_loss 0.29895 +Epoch [2039/4000] Validation [3/4] Loss: 0.30075 focal_loss 0.20736 dice_loss 0.09339 +Epoch [2039/4000] Validation [4/4] Loss: 0.49433 focal_loss 0.35359 dice_loss 0.14074 +Epoch [2039/4000] Validation metric {'Val/mean dice_metric': 0.9647696614265442, 'Val/mean miou_metric': 0.9485191106796265, 'Val/mean f1': 0.9690258502960205, 'Val/mean precision': 0.9739478230476379, 'Val/mean recall': 0.9641534686088562, 'Val/mean hd95_metric': 5.654165744781494} +Cheakpoint... +Epoch [2039/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9648], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9647696614265442, 'Val/mean miou_metric': 0.9485191106796265, 'Val/mean f1': 0.9690258502960205, 'Val/mean precision': 0.9739478230476379, 'Val/mean recall': 0.9641534686088562, 'Val/mean hd95_metric': 5.654165744781494} +Epoch [2040/4000] Training [1/16] Loss: 0.00564 +Epoch [2040/4000] Training [2/16] Loss: 0.00611 +Epoch [2040/4000] Training [3/16] Loss: 0.00590 +Epoch [2040/4000] Training [4/16] Loss: 0.00557 +Epoch [2040/4000] Training [5/16] Loss: 0.00568 +Epoch [2040/4000] Training [6/16] Loss: 0.00544 +Epoch [2040/4000] Training [7/16] Loss: 0.00612 +Epoch [2040/4000] Training [8/16] Loss: 0.00530 +Epoch [2040/4000] Training [9/16] Loss: 0.00441 +Epoch [2040/4000] Training [10/16] Loss: 0.00681 +Epoch [2040/4000] Training [11/16] Loss: 0.00593 +Epoch [2040/4000] Training [12/16] Loss: 0.00707 +Epoch [2040/4000] Training [13/16] Loss: 0.00677 +Epoch [2040/4000] Training [14/16] Loss: 0.00501 +Epoch [2040/4000] Training [15/16] Loss: 0.00504 +Epoch [2040/4000] Training [16/16] Loss: 0.00548 +Epoch [2040/4000] Training metric {'Train/mean dice_metric': 0.9961453676223755, 'Train/mean miou_metric': 0.9920661449432373, 'Train/mean f1': 0.9920405149459839, 'Train/mean precision': 0.9875501394271851, 'Train/mean recall': 0.996571958065033, 'Train/mean hd95_metric': 0.9977117776870728} +Epoch [2040/4000] Validation [1/4] Loss: 1.24803 focal_loss 1.08421 dice_loss 0.16382 +Epoch [2040/4000] Validation [2/4] Loss: 0.97339 focal_loss 0.77078 dice_loss 0.20261 +Epoch [2040/4000] Validation [3/4] Loss: 0.27384 focal_loss 0.18911 dice_loss 0.08473 +Epoch [2040/4000] Validation [4/4] Loss: 0.25454 focal_loss 0.16315 dice_loss 0.09139 +Epoch [2040/4000] Validation metric {'Val/mean dice_metric': 0.9661657214164734, 'Val/mean miou_metric': 0.9496925473213196, 'Val/mean f1': 0.9704329371452332, 'Val/mean precision': 0.9735715985298157, 'Val/mean recall': 0.9673144817352295, 'Val/mean hd95_metric': 5.448338508605957} +Cheakpoint... +Epoch [2040/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9662], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9661657214164734, 'Val/mean miou_metric': 0.9496925473213196, 'Val/mean f1': 0.9704329371452332, 'Val/mean precision': 0.9735715985298157, 'Val/mean recall': 0.9673144817352295, 'Val/mean hd95_metric': 5.448338508605957} +Epoch [2041/4000] Training [1/16] Loss: 0.00356 +Epoch [2041/4000] Training [2/16] Loss: 0.00609 +Epoch [2041/4000] Training [3/16] Loss: 0.00746 +Epoch [2041/4000] Training [4/16] Loss: 0.00659 +Epoch [2041/4000] Training [5/16] Loss: 0.00735 +Epoch [2041/4000] Training [6/16] Loss: 0.00514 +Epoch [2041/4000] Training [7/16] Loss: 0.00837 +Epoch [2041/4000] Training [8/16] Loss: 0.00445 +Epoch [2041/4000] Training [9/16] Loss: 0.00681 +Epoch [2041/4000] Training [10/16] Loss: 0.00646 +Epoch [2041/4000] Training [11/16] Loss: 0.00919 +Epoch [2041/4000] Training [12/16] Loss: 0.00691 +Epoch [2041/4000] Training [13/16] Loss: 0.00644 +Epoch [2041/4000] Training [14/16] Loss: 0.00462 +Epoch [2041/4000] Training [15/16] Loss: 0.00806 +Epoch [2041/4000] Training [16/16] Loss: 0.00560 +Epoch [2041/4000] Training metric {'Train/mean dice_metric': 0.9938370585441589, 'Train/mean miou_metric': 0.9892708659172058, 'Train/mean f1': 0.9911032319068909, 'Train/mean precision': 0.9868969321250916, 'Train/mean recall': 0.9953454732894897, 'Train/mean hd95_metric': 1.2247717380523682} +Epoch [2041/4000] Validation [1/4] Loss: 0.78905 focal_loss 0.66048 dice_loss 0.12857 +Epoch [2041/4000] Validation [2/4] Loss: 0.48074 focal_loss 0.29936 dice_loss 0.18138 +Epoch [2041/4000] Validation [3/4] Loss: 0.43963 focal_loss 0.33485 dice_loss 0.10479 +Epoch [2041/4000] Validation [4/4] Loss: 0.31049 focal_loss 0.20059 dice_loss 0.10990 +Epoch [2041/4000] Validation metric {'Val/mean dice_metric': 0.9682043194770813, 'Val/mean miou_metric': 0.9514471292495728, 'Val/mean f1': 0.9711630940437317, 'Val/mean precision': 0.9702308177947998, 'Val/mean recall': 0.9720971584320068, 'Val/mean hd95_metric': 5.866418838500977} +Cheakpoint... +Epoch [2041/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9682], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9682043194770813, 'Val/mean miou_metric': 0.9514471292495728, 'Val/mean f1': 0.9711630940437317, 'Val/mean precision': 0.9702308177947998, 'Val/mean recall': 0.9720971584320068, 'Val/mean hd95_metric': 5.866418838500977} +Epoch [2042/4000] Training [1/16] Loss: 0.00796 +Epoch [2042/4000] Training [2/16] Loss: 0.00841 +Epoch [2042/4000] Training [3/16] Loss: 0.00478 +Epoch [2042/4000] Training [4/16] Loss: 0.00540 +Epoch [2042/4000] Training [5/16] Loss: 0.00852 +Epoch [2042/4000] Training [6/16] Loss: 0.00542 +Epoch [2042/4000] Training [7/16] Loss: 0.00649 +Epoch [2042/4000] Training [8/16] Loss: 0.00609 +Epoch [2042/4000] Training [9/16] Loss: 0.00692 +Epoch [2042/4000] Training [10/16] Loss: 0.00480 +Epoch [2042/4000] Training [11/16] Loss: 0.00557 +Epoch [2042/4000] Training [12/16] Loss: 0.00643 +Epoch [2042/4000] Training [13/16] Loss: 0.00611 +Epoch [2042/4000] Training [14/16] Loss: 0.00569 +Epoch [2042/4000] Training [15/16] Loss: 0.00715 +Epoch [2042/4000] Training [16/16] Loss: 0.00761 +Epoch [2042/4000] Training metric {'Train/mean dice_metric': 0.9956442713737488, 'Train/mean miou_metric': 0.9910640716552734, 'Train/mean f1': 0.9911683201789856, 'Train/mean precision': 0.9864636659622192, 'Train/mean recall': 0.9959181547164917, 'Train/mean hd95_metric': 1.2138079404830933} +Epoch [2042/4000] Validation [1/4] Loss: 0.66565 focal_loss 0.54856 dice_loss 0.11709 +Epoch [2042/4000] Validation [2/4] Loss: 0.41089 focal_loss 0.29146 dice_loss 0.11942 +Epoch [2042/4000] Validation [3/4] Loss: 0.41508 focal_loss 0.32129 dice_loss 0.09379 +Epoch [2042/4000] Validation [4/4] Loss: 0.23442 focal_loss 0.14802 dice_loss 0.08641 +Epoch [2042/4000] Validation metric {'Val/mean dice_metric': 0.9725080728530884, 'Val/mean miou_metric': 0.955710232257843, 'Val/mean f1': 0.9729440212249756, 'Val/mean precision': 0.9704685211181641, 'Val/mean recall': 0.975432276725769, 'Val/mean hd95_metric': 5.767800331115723} +Cheakpoint... +Epoch [2042/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725080728530884, 'Val/mean miou_metric': 0.955710232257843, 'Val/mean f1': 0.9729440212249756, 'Val/mean precision': 0.9704685211181641, 'Val/mean recall': 0.975432276725769, 'Val/mean hd95_metric': 5.767800331115723} +Epoch [2043/4000] Training [1/16] Loss: 0.00498 +Epoch [2043/4000] Training [2/16] Loss: 0.00694 +Epoch [2043/4000] Training [3/16] Loss: 0.00601 +Epoch [2043/4000] Training [4/16] Loss: 0.00479 +Epoch [2043/4000] Training [5/16] Loss: 0.00702 +Epoch [2043/4000] Training [6/16] Loss: 0.00801 +Epoch [2043/4000] Training [7/16] Loss: 0.00643 +Epoch [2043/4000] Training [8/16] Loss: 0.00583 +Epoch [2043/4000] Training [9/16] Loss: 0.00533 +Epoch [2043/4000] Training [10/16] Loss: 0.00646 +Epoch [2043/4000] Training [11/16] Loss: 0.00553 +Epoch [2043/4000] Training [12/16] Loss: 0.00511 +Epoch [2043/4000] Training [13/16] Loss: 0.00481 +Epoch [2043/4000] Training [14/16] Loss: 0.00921 +Epoch [2043/4000] Training [15/16] Loss: 0.00591 +Epoch [2043/4000] Training [16/16] Loss: 0.00562 +Epoch [2043/4000] Training metric {'Train/mean dice_metric': 0.995972752571106, 'Train/mean miou_metric': 0.991722822189331, 'Train/mean f1': 0.9918317198753357, 'Train/mean precision': 0.9873600602149963, 'Train/mean recall': 0.9963439702987671, 'Train/mean hd95_metric': 1.09867262840271} +Epoch [2043/4000] Validation [1/4] Loss: 0.37552 focal_loss 0.29452 dice_loss 0.08100 +Epoch [2043/4000] Validation [2/4] Loss: 0.69127 focal_loss 0.45686 dice_loss 0.23441 +Epoch [2043/4000] Validation [3/4] Loss: 0.36506 focal_loss 0.27760 dice_loss 0.08746 +Epoch [2043/4000] Validation [4/4] Loss: 0.30117 focal_loss 0.18683 dice_loss 0.11434 +Epoch [2043/4000] Validation metric {'Val/mean dice_metric': 0.9719492197036743, 'Val/mean miou_metric': 0.9549447894096375, 'Val/mean f1': 0.9728988409042358, 'Val/mean precision': 0.9708145260810852, 'Val/mean recall': 0.974992036819458, 'Val/mean hd95_metric': 5.740782737731934} +Cheakpoint... +Epoch [2043/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719492197036743, 'Val/mean miou_metric': 0.9549447894096375, 'Val/mean f1': 0.9728988409042358, 'Val/mean precision': 0.9708145260810852, 'Val/mean recall': 0.974992036819458, 'Val/mean hd95_metric': 5.740782737731934} +Epoch [2044/4000] Training [1/16] Loss: 0.00611 +Epoch [2044/4000] Training [2/16] Loss: 0.00734 +Epoch [2044/4000] Training [3/16] Loss: 0.00717 +Epoch [2044/4000] Training [4/16] Loss: 0.00490 +Epoch [2044/4000] Training [5/16] Loss: 0.00691 +Epoch [2044/4000] Training [6/16] Loss: 0.00506 +Epoch [2044/4000] Training [7/16] Loss: 0.00537 +Epoch [2044/4000] Training [8/16] Loss: 0.00604 +Epoch [2044/4000] Training [9/16] Loss: 0.00504 +Epoch [2044/4000] Training [10/16] Loss: 0.00500 +Epoch [2044/4000] Training [11/16] Loss: 0.00420 +Epoch [2044/4000] Training [12/16] Loss: 0.00585 +Epoch [2044/4000] Training [13/16] Loss: 0.00536 +Epoch [2044/4000] Training [14/16] Loss: 0.00517 +Epoch [2044/4000] Training [15/16] Loss: 0.00514 +Epoch [2044/4000] Training [16/16] Loss: 0.00500 +Epoch [2044/4000] Training metric {'Train/mean dice_metric': 0.996518611907959, 'Train/mean miou_metric': 0.9927957057952881, 'Train/mean f1': 0.992107629776001, 'Train/mean precision': 0.9876221418380737, 'Train/mean recall': 0.9966341257095337, 'Train/mean hd95_metric': 0.9965324997901917} +Epoch [2044/4000] Validation [1/4] Loss: 0.35494 focal_loss 0.27839 dice_loss 0.07655 +Epoch [2044/4000] Validation [2/4] Loss: 0.61711 focal_loss 0.39520 dice_loss 0.22191 +Epoch [2044/4000] Validation [3/4] Loss: 0.17057 focal_loss 0.11631 dice_loss 0.05427 +Epoch [2044/4000] Validation [4/4] Loss: 0.25314 focal_loss 0.15560 dice_loss 0.09753 +Epoch [2044/4000] Validation metric {'Val/mean dice_metric': 0.9710725545883179, 'Val/mean miou_metric': 0.955047607421875, 'Val/mean f1': 0.9734534621238708, 'Val/mean precision': 0.9721781611442566, 'Val/mean recall': 0.9747321605682373, 'Val/mean hd95_metric': 5.858268737792969} +Cheakpoint... +Epoch [2044/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710725545883179, 'Val/mean miou_metric': 0.955047607421875, 'Val/mean f1': 0.9734534621238708, 'Val/mean precision': 0.9721781611442566, 'Val/mean recall': 0.9747321605682373, 'Val/mean hd95_metric': 5.858268737792969} +Epoch [2045/4000] Training [1/16] Loss: 0.00496 +Epoch [2045/4000] Training [2/16] Loss: 0.00652 +Epoch [2045/4000] Training [3/16] Loss: 0.00652 +Epoch [2045/4000] Training [4/16] Loss: 0.00666 +Epoch [2045/4000] Training [5/16] Loss: 0.00520 +Epoch [2045/4000] Training [6/16] Loss: 0.00582 +Epoch [2045/4000] Training [7/16] Loss: 0.00627 +Epoch [2045/4000] Training [8/16] Loss: 0.04197 +Epoch [2045/4000] Training [9/16] Loss: 0.00687 +Epoch [2045/4000] Training [10/16] Loss: 0.00602 +Epoch [2045/4000] Training [11/16] Loss: 0.00492 +Epoch [2045/4000] Training [12/16] Loss: 0.00527 +Epoch [2045/4000] Training [13/16] Loss: 0.00479 +Epoch [2045/4000] Training [14/16] Loss: 0.00688 +Epoch [2045/4000] Training [15/16] Loss: 0.00650 +Epoch [2045/4000] Training [16/16] Loss: 0.00472 +Epoch [2045/4000] Training metric {'Train/mean dice_metric': 0.9957476258277893, 'Train/mean miou_metric': 0.9913638830184937, 'Train/mean f1': 0.9908838868141174, 'Train/mean precision': 0.9856715202331543, 'Train/mean recall': 0.9961516261100769, 'Train/mean hd95_metric': 1.3638920783996582} +Epoch [2045/4000] Validation [1/4] Loss: 0.74413 focal_loss 0.62224 dice_loss 0.12189 +Epoch [2045/4000] Validation [2/4] Loss: 0.74763 focal_loss 0.51164 dice_loss 0.23599 +Epoch [2045/4000] Validation [3/4] Loss: 0.63221 focal_loss 0.50538 dice_loss 0.12682 +Epoch [2045/4000] Validation [4/4] Loss: 0.27471 focal_loss 0.18934 dice_loss 0.08536 +Epoch [2045/4000] Validation metric {'Val/mean dice_metric': 0.9691154360771179, 'Val/mean miou_metric': 0.9516718983650208, 'Val/mean f1': 0.969260573387146, 'Val/mean precision': 0.9709625244140625, 'Val/mean recall': 0.967564582824707, 'Val/mean hd95_metric': 6.626750469207764} +Cheakpoint... +Epoch [2045/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691154360771179, 'Val/mean miou_metric': 0.9516718983650208, 'Val/mean f1': 0.969260573387146, 'Val/mean precision': 0.9709625244140625, 'Val/mean recall': 0.967564582824707, 'Val/mean hd95_metric': 6.626750469207764} +Epoch [2046/4000] Training [1/16] Loss: 0.00503 +Epoch [2046/4000] Training [2/16] Loss: 0.00673 +Epoch [2046/4000] Training [3/16] Loss: 0.00750 +Epoch [2046/4000] Training [4/16] Loss: 0.00518 +Epoch [2046/4000] Training [5/16] Loss: 0.00563 +Epoch [2046/4000] Training [6/16] Loss: 0.00536 +Epoch [2046/4000] Training [7/16] Loss: 0.00431 +Epoch [2046/4000] Training [8/16] Loss: 0.00621 +Epoch [2046/4000] Training [9/16] Loss: 0.00548 +Epoch [2046/4000] Training [10/16] Loss: 0.00533 +Epoch [2046/4000] Training [11/16] Loss: 0.00504 +Epoch [2046/4000] Training [12/16] Loss: 0.00603 +Epoch [2046/4000] Training [13/16] Loss: 0.00548 +Epoch [2046/4000] Training [14/16] Loss: 0.00713 +Epoch [2046/4000] Training [15/16] Loss: 0.00529 +Epoch [2046/4000] Training [16/16] Loss: 0.00400 +Epoch [2046/4000] Training metric {'Train/mean dice_metric': 0.9964301586151123, 'Train/mean miou_metric': 0.9926176071166992, 'Train/mean f1': 0.9918286800384521, 'Train/mean precision': 0.9871754050254822, 'Train/mean recall': 0.9965259432792664, 'Train/mean hd95_metric': 1.0090597867965698} +Epoch [2046/4000] Validation [1/4] Loss: 0.77836 focal_loss 0.65884 dice_loss 0.11952 +Epoch [2046/4000] Validation [2/4] Loss: 0.45132 focal_loss 0.30585 dice_loss 0.14547 +Epoch [2046/4000] Validation [3/4] Loss: 0.36709 focal_loss 0.27569 dice_loss 0.09140 +Epoch [2046/4000] Validation [4/4] Loss: 0.26787 focal_loss 0.16800 dice_loss 0.09987 +Epoch [2046/4000] Validation metric {'Val/mean dice_metric': 0.9724550247192383, 'Val/mean miou_metric': 0.9559217691421509, 'Val/mean f1': 0.9719454050064087, 'Val/mean precision': 0.9728116393089294, 'Val/mean recall': 0.9710807204246521, 'Val/mean hd95_metric': 5.580625057220459} +Cheakpoint... +Epoch [2046/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724550247192383, 'Val/mean miou_metric': 0.9559217691421509, 'Val/mean f1': 0.9719454050064087, 'Val/mean precision': 0.9728116393089294, 'Val/mean recall': 0.9710807204246521, 'Val/mean hd95_metric': 5.580625057220459} +Epoch [2047/4000] Training [1/16] Loss: 0.00404 +Epoch [2047/4000] Training [2/16] Loss: 0.00608 +Epoch [2047/4000] Training [3/16] Loss: 0.00494 +Epoch [2047/4000] Training [4/16] Loss: 0.00450 +Epoch [2047/4000] Training [5/16] Loss: 0.00459 +Epoch [2047/4000] Training [6/16] Loss: 0.00527 +Epoch [2047/4000] Training [7/16] Loss: 0.00662 +Epoch [2047/4000] Training [8/16] Loss: 0.00553 +Epoch [2047/4000] Training [9/16] Loss: 0.00510 +Epoch [2047/4000] Training [10/16] Loss: 0.00590 +Epoch [2047/4000] Training [11/16] Loss: 0.00484 +Epoch [2047/4000] Training [12/16] Loss: 0.00453 +Epoch [2047/4000] Training [13/16] Loss: 0.00726 +Epoch [2047/4000] Training [14/16] Loss: 0.00660 +Epoch [2047/4000] Training [15/16] Loss: 0.00694 +Epoch [2047/4000] Training [16/16] Loss: 0.00617 +Epoch [2047/4000] Training metric {'Train/mean dice_metric': 0.9963879585266113, 'Train/mean miou_metric': 0.9925045967102051, 'Train/mean f1': 0.9912492036819458, 'Train/mean precision': 0.9860933423042297, 'Train/mean recall': 0.9964591860771179, 'Train/mean hd95_metric': 1.001003384590149} +Epoch [2047/4000] Validation [1/4] Loss: 0.94338 focal_loss 0.81680 dice_loss 0.12658 +Epoch [2047/4000] Validation [2/4] Loss: 1.10730 focal_loss 0.79446 dice_loss 0.31284 +Epoch [2047/4000] Validation [3/4] Loss: 0.36255 focal_loss 0.27266 dice_loss 0.08989 +Epoch [2047/4000] Validation [4/4] Loss: 0.37515 focal_loss 0.25267 dice_loss 0.12248 +Epoch [2047/4000] Validation metric {'Val/mean dice_metric': 0.9673446416854858, 'Val/mean miou_metric': 0.9510974884033203, 'Val/mean f1': 0.9703880548477173, 'Val/mean precision': 0.9708262085914612, 'Val/mean recall': 0.9699504971504211, 'Val/mean hd95_metric': 5.580378532409668} +Cheakpoint... +Epoch [2047/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673446416854858, 'Val/mean miou_metric': 0.9510974884033203, 'Val/mean f1': 0.9703880548477173, 'Val/mean precision': 0.9708262085914612, 'Val/mean recall': 0.9699504971504211, 'Val/mean hd95_metric': 5.580378532409668} +Epoch [2048/4000] Training [1/16] Loss: 0.00579 +Epoch [2048/4000] Training [2/16] Loss: 0.00531 +Epoch [2048/4000] Training [3/16] Loss: 0.00514 +Epoch [2048/4000] Training [4/16] Loss: 0.00385 +Epoch [2048/4000] Training [5/16] Loss: 0.00449 +Epoch [2048/4000] Training [6/16] Loss: 0.00440 +Epoch [2048/4000] Training [7/16] Loss: 0.00649 +Epoch [2048/4000] Training [8/16] Loss: 0.00502 +Epoch [2048/4000] Training [9/16] Loss: 0.00535 +Epoch [2048/4000] Training [10/16] Loss: 0.00397 +Epoch [2048/4000] Training [11/16] Loss: 0.00499 +Epoch [2048/4000] Training [12/16] Loss: 0.00462 +Epoch [2048/4000] Training [13/16] Loss: 0.00544 +Epoch [2048/4000] Training [14/16] Loss: 0.00490 +Epoch [2048/4000] Training [15/16] Loss: 0.00610 +Epoch [2048/4000] Training [16/16] Loss: 0.00472 +Epoch [2048/4000] Training metric {'Train/mean dice_metric': 0.9967792630195618, 'Train/mean miou_metric': 0.9933071136474609, 'Train/mean f1': 0.9922693967819214, 'Train/mean precision': 0.9876998662948608, 'Train/mean recall': 0.996881365776062, 'Train/mean hd95_metric': 0.9873602390289307} +Epoch [2048/4000] Validation [1/4] Loss: 0.91614 focal_loss 0.78772 dice_loss 0.12841 +Epoch [2048/4000] Validation [2/4] Loss: 0.47874 focal_loss 0.31552 dice_loss 0.16322 +Epoch [2048/4000] Validation [3/4] Loss: 0.36622 focal_loss 0.27850 dice_loss 0.08772 +Epoch [2048/4000] Validation [4/4] Loss: 0.23872 focal_loss 0.15730 dice_loss 0.08141 +Epoch [2048/4000] Validation metric {'Val/mean dice_metric': 0.9713080525398254, 'Val/mean miou_metric': 0.9552478790283203, 'Val/mean f1': 0.9722885489463806, 'Val/mean precision': 0.9733701348304749, 'Val/mean recall': 0.9712094068527222, 'Val/mean hd95_metric': 5.698574066162109} +Cheakpoint... +Epoch [2048/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713080525398254, 'Val/mean miou_metric': 0.9552478790283203, 'Val/mean f1': 0.9722885489463806, 'Val/mean precision': 0.9733701348304749, 'Val/mean recall': 0.9712094068527222, 'Val/mean hd95_metric': 5.698574066162109} +Epoch [2049/4000] Training [1/16] Loss: 0.00506 +Epoch [2049/4000] Training [2/16] Loss: 0.00499 +Epoch [2049/4000] Training [3/16] Loss: 0.00502 +Epoch [2049/4000] Training [4/16] Loss: 0.00688 +Epoch [2049/4000] Training [5/16] Loss: 0.00579 +Epoch [2049/4000] Training [6/16] Loss: 0.00472 +Epoch [2049/4000] Training [7/16] Loss: 0.00537 +Epoch [2049/4000] Training [8/16] Loss: 0.00590 +Epoch [2049/4000] Training [9/16] Loss: 0.00528 +Epoch [2049/4000] Training [10/16] Loss: 0.00709 +Epoch [2049/4000] Training [11/16] Loss: 0.00591 +Epoch [2049/4000] Training [12/16] Loss: 0.00475 +Epoch [2049/4000] Training [13/16] Loss: 0.00525 +Epoch [2049/4000] Training [14/16] Loss: 0.00449 +Epoch [2049/4000] Training [15/16] Loss: 0.00583 +Epoch [2049/4000] Training [16/16] Loss: 0.00494 +Epoch [2049/4000] Training metric {'Train/mean dice_metric': 0.9965459704399109, 'Train/mean miou_metric': 0.9928463101387024, 'Train/mean f1': 0.992192268371582, 'Train/mean precision': 0.98766028881073, 'Train/mean recall': 0.9967660307884216, 'Train/mean hd95_metric': 0.991881251335144} +Epoch [2049/4000] Validation [1/4] Loss: 0.96381 focal_loss 0.83571 dice_loss 0.12810 +Epoch [2049/4000] Validation [2/4] Loss: 0.74924 focal_loss 0.54809 dice_loss 0.20115 +Epoch [2049/4000] Validation [3/4] Loss: 0.37309 focal_loss 0.28209 dice_loss 0.09100 +Epoch [2049/4000] Validation [4/4] Loss: 0.22684 focal_loss 0.14800 dice_loss 0.07884 +Epoch [2049/4000] Validation metric {'Val/mean dice_metric': 0.9700492024421692, 'Val/mean miou_metric': 0.9539794921875, 'Val/mean f1': 0.9720787405967712, 'Val/mean precision': 0.9732650518417358, 'Val/mean recall': 0.9708953499794006, 'Val/mean hd95_metric': 5.991799831390381} +Cheakpoint... +Epoch [2049/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9700492024421692, 'Val/mean miou_metric': 0.9539794921875, 'Val/mean f1': 0.9720787405967712, 'Val/mean precision': 0.9732650518417358, 'Val/mean recall': 0.9708953499794006, 'Val/mean hd95_metric': 5.991799831390381} +Epoch [2050/4000] Training [1/16] Loss: 0.00487 +Epoch [2050/4000] Training [2/16] Loss: 0.00662 +Epoch [2050/4000] Training [3/16] Loss: 0.00621 +Epoch [2050/4000] Training [4/16] Loss: 0.00413 +Epoch [2050/4000] Training [5/16] Loss: 0.00604 +Epoch [2050/4000] Training [6/16] Loss: 0.00607 +Epoch [2050/4000] Training [7/16] Loss: 0.00672 +Epoch [2050/4000] Training [8/16] Loss: 0.00627 +Epoch [2050/4000] Training [9/16] Loss: 0.00477 +Epoch [2050/4000] Training [10/16] Loss: 0.00592 +Epoch [2050/4000] Training [11/16] Loss: 0.00498 +Epoch [2050/4000] Training [12/16] Loss: 0.00543 +Epoch [2050/4000] Training [13/16] Loss: 0.00507 +Epoch [2050/4000] Training [14/16] Loss: 0.00491 +Epoch [2050/4000] Training [15/16] Loss: 0.00538 +Epoch [2050/4000] Training [16/16] Loss: 0.00560 +Epoch [2050/4000] Training metric {'Train/mean dice_metric': 0.9963868260383606, 'Train/mean miou_metric': 0.9925408959388733, 'Train/mean f1': 0.9918817281723022, 'Train/mean precision': 0.9873456954956055, 'Train/mean recall': 0.9964596033096313, 'Train/mean hd95_metric': 1.0536975860595703} +Epoch [2050/4000] Validation [1/4] Loss: 0.60750 focal_loss 0.50269 dice_loss 0.10481 +Epoch [2050/4000] Validation [2/4] Loss: 0.59498 focal_loss 0.40181 dice_loss 0.19317 +Epoch [2050/4000] Validation [3/4] Loss: 0.56526 focal_loss 0.44414 dice_loss 0.12112 +Epoch [2050/4000] Validation [4/4] Loss: 0.22865 focal_loss 0.15012 dice_loss 0.07853 +Epoch [2050/4000] Validation metric {'Val/mean dice_metric': 0.9687232971191406, 'Val/mean miou_metric': 0.9522361755371094, 'Val/mean f1': 0.9706969857215881, 'Val/mean precision': 0.9744449257850647, 'Val/mean recall': 0.9669777154922485, 'Val/mean hd95_metric': 5.8079729080200195} +Cheakpoint... +Epoch [2050/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687232971191406, 'Val/mean miou_metric': 0.9522361755371094, 'Val/mean f1': 0.9706969857215881, 'Val/mean precision': 0.9744449257850647, 'Val/mean recall': 0.9669777154922485, 'Val/mean hd95_metric': 5.8079729080200195} +Epoch [2051/4000] Training [1/16] Loss: 0.00741 +Epoch [2051/4000] Training [2/16] Loss: 0.00459 +Epoch [2051/4000] Training [3/16] Loss: 0.00465 +Epoch [2051/4000] Training [4/16] Loss: 0.00717 +Epoch [2051/4000] Training [5/16] Loss: 0.00633 +Epoch [2051/4000] Training [6/16] Loss: 0.00542 +Epoch [2051/4000] Training [7/16] Loss: 0.00493 +Epoch [2051/4000] Training [8/16] Loss: 0.00759 +Epoch [2051/4000] Training [9/16] Loss: 0.00472 +Epoch [2051/4000] Training [10/16] Loss: 0.00492 +Epoch [2051/4000] Training [11/16] Loss: 0.00454 +Epoch [2051/4000] Training [12/16] Loss: 0.00473 +Epoch [2051/4000] Training [13/16] Loss: 0.00476 +Epoch [2051/4000] Training [14/16] Loss: 0.00635 +Epoch [2051/4000] Training [15/16] Loss: 0.00624 +Epoch [2051/4000] Training [16/16] Loss: 0.01118 +Epoch [2051/4000] Training metric {'Train/mean dice_metric': 0.9950236082077026, 'Train/mean miou_metric': 0.99038165807724, 'Train/mean f1': 0.9898202419281006, 'Train/mean precision': 0.9842714667320251, 'Train/mean recall': 0.9954318404197693, 'Train/mean hd95_metric': 1.6455475091934204} +Epoch [2051/4000] Validation [1/4] Loss: 0.36036 focal_loss 0.28590 dice_loss 0.07446 +Epoch [2051/4000] Validation [2/4] Loss: 0.70560 focal_loss 0.47846 dice_loss 0.22714 +Epoch [2051/4000] Validation [3/4] Loss: 0.54826 focal_loss 0.42669 dice_loss 0.12156 +Epoch [2051/4000] Validation [4/4] Loss: 0.32088 focal_loss 0.21861 dice_loss 0.10227 +Epoch [2051/4000] Validation metric {'Val/mean dice_metric': 0.9693918228149414, 'Val/mean miou_metric': 0.9526451230049133, 'Val/mean f1': 0.9703473448753357, 'Val/mean precision': 0.9665356278419495, 'Val/mean recall': 0.974189281463623, 'Val/mean hd95_metric': 6.967898368835449} +Cheakpoint... +Epoch [2051/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693918228149414, 'Val/mean miou_metric': 0.9526451230049133, 'Val/mean f1': 0.9703473448753357, 'Val/mean precision': 0.9665356278419495, 'Val/mean recall': 0.974189281463623, 'Val/mean hd95_metric': 6.967898368835449} +Epoch [2052/4000] Training [1/16] Loss: 0.00506 +Epoch [2052/4000] Training [2/16] Loss: 0.00639 +Epoch [2052/4000] Training [3/16] Loss: 0.00624 +Epoch [2052/4000] Training [4/16] Loss: 0.00689 +Epoch [2052/4000] Training [5/16] Loss: 0.01094 +Epoch [2052/4000] Training [6/16] Loss: 0.00824 +Epoch [2052/4000] Training [7/16] Loss: 0.00512 +Epoch [2052/4000] Training [8/16] Loss: 0.00531 +Epoch [2052/4000] Training [9/16] Loss: 0.00666 +Epoch [2052/4000] Training [10/16] Loss: 0.00639 +Epoch [2052/4000] Training [11/16] Loss: 0.00903 +Epoch [2052/4000] Training [12/16] Loss: 0.00737 +Epoch [2052/4000] Training [13/16] Loss: 0.00582 +Epoch [2052/4000] Training [14/16] Loss: 0.01051 +Epoch [2052/4000] Training [15/16] Loss: 0.00686 +Epoch [2052/4000] Training [16/16] Loss: 0.00743 +Epoch [2052/4000] Training metric {'Train/mean dice_metric': 0.9955805540084839, 'Train/mean miou_metric': 0.9909335374832153, 'Train/mean f1': 0.9909967184066772, 'Train/mean precision': 0.9866030812263489, 'Train/mean recall': 0.9954296350479126, 'Train/mean hd95_metric': 1.2127965688705444} +Epoch [2052/4000] Validation [1/4] Loss: 0.45874 focal_loss 0.36707 dice_loss 0.09167 +Epoch [2052/4000] Validation [2/4] Loss: 0.41265 focal_loss 0.24788 dice_loss 0.16477 +Epoch [2052/4000] Validation [3/4] Loss: 0.18199 focal_loss 0.12385 dice_loss 0.05815 +Epoch [2052/4000] Validation [4/4] Loss: 0.33414 focal_loss 0.23072 dice_loss 0.10341 +Epoch [2052/4000] Validation metric {'Val/mean dice_metric': 0.9691351056098938, 'Val/mean miou_metric': 0.9513372182846069, 'Val/mean f1': 0.9712850451469421, 'Val/mean precision': 0.9727991819381714, 'Val/mean recall': 0.9697757959365845, 'Val/mean hd95_metric': 6.855283260345459} +Cheakpoint... +Epoch [2052/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691351056098938, 'Val/mean miou_metric': 0.9513372182846069, 'Val/mean f1': 0.9712850451469421, 'Val/mean precision': 0.9727991819381714, 'Val/mean recall': 0.9697757959365845, 'Val/mean hd95_metric': 6.855283260345459} +Epoch [2053/4000] Training [1/16] Loss: 0.00579 +Epoch [2053/4000] Training [2/16] Loss: 0.00546 +Epoch [2053/4000] Training [3/16] Loss: 0.00492 +Epoch [2053/4000] Training [4/16] Loss: 0.00440 +Epoch [2053/4000] Training [5/16] Loss: 0.00636 +Epoch [2053/4000] Training [6/16] Loss: 0.00533 +Epoch [2053/4000] Training [7/16] Loss: 0.00988 +Epoch [2053/4000] Training [8/16] Loss: 0.00827 +Epoch [2053/4000] Training [9/16] Loss: 0.00464 +Epoch [2053/4000] Training [10/16] Loss: 0.00663 +Epoch [2053/4000] Training [11/16] Loss: 0.00517 +Epoch [2053/4000] Training [12/16] Loss: 0.00793 +Epoch [2053/4000] Training [13/16] Loss: 0.00648 +Epoch [2053/4000] Training [14/16] Loss: 0.00682 +Epoch [2053/4000] Training [15/16] Loss: 0.00662 +Epoch [2053/4000] Training [16/16] Loss: 0.00599 +Epoch [2053/4000] Training metric {'Train/mean dice_metric': 0.995694637298584, 'Train/mean miou_metric': 0.9911942481994629, 'Train/mean f1': 0.9913157820701599, 'Train/mean precision': 0.9866641163825989, 'Train/mean recall': 0.9960115551948547, 'Train/mean hd95_metric': 1.2563071250915527} +Epoch [2053/4000] Validation [1/4] Loss: 0.43034 focal_loss 0.33524 dice_loss 0.09510 +Epoch [2053/4000] Validation [2/4] Loss: 0.28731 focal_loss 0.17715 dice_loss 0.11017 +Epoch [2053/4000] Validation [3/4] Loss: 0.37791 focal_loss 0.26888 dice_loss 0.10903 +Epoch [2053/4000] Validation [4/4] Loss: 0.25455 focal_loss 0.15956 dice_loss 0.09499 +Epoch [2053/4000] Validation metric {'Val/mean dice_metric': 0.9703871607780457, 'Val/mean miou_metric': 0.952979564666748, 'Val/mean f1': 0.9714428782463074, 'Val/mean precision': 0.9727359414100647, 'Val/mean recall': 0.9701534509658813, 'Val/mean hd95_metric': 6.782476902008057} +Cheakpoint... +Epoch [2053/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703871607780457, 'Val/mean miou_metric': 0.952979564666748, 'Val/mean f1': 0.9714428782463074, 'Val/mean precision': 0.9727359414100647, 'Val/mean recall': 0.9701534509658813, 'Val/mean hd95_metric': 6.782476902008057} +Epoch [2054/4000] Training [1/16] Loss: 0.00723 +Epoch [2054/4000] Training [2/16] Loss: 0.00514 +Epoch [2054/4000] Training [3/16] Loss: 0.00752 +Epoch [2054/4000] Training [4/16] Loss: 0.00575 +Epoch [2054/4000] Training [5/16] Loss: 0.00573 +Epoch [2054/4000] Training [6/16] Loss: 0.00523 +Epoch [2054/4000] Training [7/16] Loss: 0.00619 +Epoch [2054/4000] Training [8/16] Loss: 0.00584 +Epoch [2054/4000] Training [9/16] Loss: 0.00639 +Epoch [2054/4000] Training [10/16] Loss: 0.00619 +Epoch [2054/4000] Training [11/16] Loss: 0.00504 +Epoch [2054/4000] Training [12/16] Loss: 0.00467 +Epoch [2054/4000] Training [13/16] Loss: 0.00496 +Epoch [2054/4000] Training [14/16] Loss: 0.00363 +Epoch [2054/4000] Training [15/16] Loss: 0.00535 +Epoch [2054/4000] Training [16/16] Loss: 0.00592 +Epoch [2054/4000] Training metric {'Train/mean dice_metric': 0.9960411190986633, 'Train/mean miou_metric': 0.9918262362480164, 'Train/mean f1': 0.9905413389205933, 'Train/mean precision': 0.9857088327407837, 'Train/mean recall': 0.9954214692115784, 'Train/mean hd95_metric': 1.1057226657867432} +Epoch [2054/4000] Validation [1/4] Loss: 0.26849 focal_loss 0.20152 dice_loss 0.06696 +Epoch [2054/4000] Validation [2/4] Loss: 0.30139 focal_loss 0.18685 dice_loss 0.11454 +Epoch [2054/4000] Validation [3/4] Loss: 0.36406 focal_loss 0.28046 dice_loss 0.08360 +Epoch [2054/4000] Validation [4/4] Loss: 0.30249 focal_loss 0.18839 dice_loss 0.11409 +Epoch [2054/4000] Validation metric {'Val/mean dice_metric': 0.9751704931259155, 'Val/mean miou_metric': 0.9580858945846558, 'Val/mean f1': 0.9731053113937378, 'Val/mean precision': 0.9679253101348877, 'Val/mean recall': 0.9783411622047424, 'Val/mean hd95_metric': 5.913968563079834} +Cheakpoint... +Epoch [2054/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751704931259155, 'Val/mean miou_metric': 0.9580858945846558, 'Val/mean f1': 0.9731053113937378, 'Val/mean precision': 0.9679253101348877, 'Val/mean recall': 0.9783411622047424, 'Val/mean hd95_metric': 5.913968563079834} +Epoch [2055/4000] Training [1/16] Loss: 0.00466 +Epoch [2055/4000] Training [2/16] Loss: 0.00495 +Epoch [2055/4000] Training [3/16] Loss: 0.00684 +Epoch [2055/4000] Training [4/16] Loss: 0.00586 +Epoch [2055/4000] Training [5/16] Loss: 0.00596 +Epoch [2055/4000] Training [6/16] Loss: 0.00509 +Epoch [2055/4000] Training [7/16] Loss: 0.00595 +Epoch [2055/4000] Training [8/16] Loss: 0.00587 +Epoch [2055/4000] Training [9/16] Loss: 0.00722 +Epoch [2055/4000] Training [10/16] Loss: 0.00664 +Epoch [2055/4000] Training [11/16] Loss: 0.00616 +Epoch [2055/4000] Training [12/16] Loss: 0.00596 +Epoch [2055/4000] Training [13/16] Loss: 0.00528 +Epoch [2055/4000] Training [14/16] Loss: 0.00636 +Epoch [2055/4000] Training [15/16] Loss: 0.00430 +Epoch [2055/4000] Training [16/16] Loss: 0.00754 +Epoch [2055/4000] Training metric {'Train/mean dice_metric': 0.9961493015289307, 'Train/mean miou_metric': 0.9920668005943298, 'Train/mean f1': 0.9917916059494019, 'Train/mean precision': 0.9872609376907349, 'Train/mean recall': 0.9963640570640564, 'Train/mean hd95_metric': 0.9994112253189087} +Epoch [2055/4000] Validation [1/4] Loss: 0.37011 focal_loss 0.28805 dice_loss 0.08206 +Epoch [2055/4000] Validation [2/4] Loss: 0.35676 focal_loss 0.21798 dice_loss 0.13878 +Epoch [2055/4000] Validation [3/4] Loss: 0.26946 focal_loss 0.18762 dice_loss 0.08184 +Epoch [2055/4000] Validation [4/4] Loss: 0.41277 focal_loss 0.27952 dice_loss 0.13325 +Epoch [2055/4000] Validation metric {'Val/mean dice_metric': 0.970472514629364, 'Val/mean miou_metric': 0.9534136652946472, 'Val/mean f1': 0.9713538885116577, 'Val/mean precision': 0.9650778770446777, 'Val/mean recall': 0.9777121543884277, 'Val/mean hd95_metric': 7.431742191314697} +Cheakpoint... +Epoch [2055/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970472514629364, 'Val/mean miou_metric': 0.9534136652946472, 'Val/mean f1': 0.9713538885116577, 'Val/mean precision': 0.9650778770446777, 'Val/mean recall': 0.9777121543884277, 'Val/mean hd95_metric': 7.431742191314697} +Epoch [2056/4000] Training [1/16] Loss: 0.00531 +Epoch [2056/4000] Training [2/16] Loss: 0.00583 +Epoch [2056/4000] Training [3/16] Loss: 0.00587 +Epoch [2056/4000] Training [4/16] Loss: 0.00515 +Epoch [2056/4000] Training [5/16] Loss: 0.00457 +Epoch [2056/4000] Training [6/16] Loss: 0.00972 +Epoch [2056/4000] Training [7/16] Loss: 0.00407 +Epoch [2056/4000] Training [8/16] Loss: 0.00444 +Epoch [2056/4000] Training [9/16] Loss: 0.00447 +Epoch [2056/4000] Training [10/16] Loss: 0.00636 +Epoch [2056/4000] Training [11/16] Loss: 0.00672 +Epoch [2056/4000] Training [12/16] Loss: 0.00913 +Epoch [2056/4000] Training [13/16] Loss: 0.00439 +Epoch [2056/4000] Training [14/16] Loss: 0.00729 +Epoch [2056/4000] Training [15/16] Loss: 0.00500 +Epoch [2056/4000] Training [16/16] Loss: 0.00464 +Epoch [2056/4000] Training metric {'Train/mean dice_metric': 0.9965137243270874, 'Train/mean miou_metric': 0.9927650094032288, 'Train/mean f1': 0.9918065071105957, 'Train/mean precision': 0.9871334433555603, 'Train/mean recall': 0.9965239763259888, 'Train/mean hd95_metric': 0.9957795143127441} +Epoch [2056/4000] Validation [1/4] Loss: 0.23758 focal_loss 0.18097 dice_loss 0.05661 +Epoch [2056/4000] Validation [2/4] Loss: 0.28095 focal_loss 0.17120 dice_loss 0.10975 +Epoch [2056/4000] Validation [3/4] Loss: 0.37090 focal_loss 0.28125 dice_loss 0.08964 +Epoch [2056/4000] Validation [4/4] Loss: 0.27377 focal_loss 0.16962 dice_loss 0.10415 +Epoch [2056/4000] Validation metric {'Val/mean dice_metric': 0.9739883542060852, 'Val/mean miou_metric': 0.9582940340042114, 'Val/mean f1': 0.9744306206703186, 'Val/mean precision': 0.9682673215866089, 'Val/mean recall': 0.9806728363037109, 'Val/mean hd95_metric': 6.0626702308654785} +Cheakpoint... +Epoch [2056/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739883542060852, 'Val/mean miou_metric': 0.9582940340042114, 'Val/mean f1': 0.9744306206703186, 'Val/mean precision': 0.9682673215866089, 'Val/mean recall': 0.9806728363037109, 'Val/mean hd95_metric': 6.0626702308654785} +Epoch [2057/4000] Training [1/16] Loss: 0.00605 +Epoch [2057/4000] Training [2/16] Loss: 0.00620 +Epoch [2057/4000] Training [3/16] Loss: 0.00572 +Epoch [2057/4000] Training [4/16] Loss: 0.00418 +Epoch [2057/4000] Training [5/16] Loss: 0.00562 +Epoch [2057/4000] Training [6/16] Loss: 0.00425 +Epoch [2057/4000] Training [7/16] Loss: 0.00540 +Epoch [2057/4000] Training [8/16] Loss: 0.00497 +Epoch [2057/4000] Training [9/16] Loss: 0.00612 +Epoch [2057/4000] Training [10/16] Loss: 0.00507 +Epoch [2057/4000] Training [11/16] Loss: 0.00742 +Epoch [2057/4000] Training [12/16] Loss: 0.00608 +Epoch [2057/4000] Training [13/16] Loss: 0.01184 +Epoch [2057/4000] Training [14/16] Loss: 0.00580 +Epoch [2057/4000] Training [15/16] Loss: 0.00534 +Epoch [2057/4000] Training [16/16] Loss: 0.00652 +Epoch [2057/4000] Training metric {'Train/mean dice_metric': 0.9958600997924805, 'Train/mean miou_metric': 0.991572916507721, 'Train/mean f1': 0.991467297077179, 'Train/mean precision': 0.9868239164352417, 'Train/mean recall': 0.9961546063423157, 'Train/mean hd95_metric': 1.641095519065857} +Epoch [2057/4000] Validation [1/4] Loss: 0.32708 focal_loss 0.25408 dice_loss 0.07300 +Epoch [2057/4000] Validation [2/4] Loss: 0.29231 focal_loss 0.15960 dice_loss 0.13271 +Epoch [2057/4000] Validation [3/4] Loss: 0.39877 focal_loss 0.29119 dice_loss 0.10757 +Epoch [2057/4000] Validation [4/4] Loss: 0.25273 focal_loss 0.16102 dice_loss 0.09171 +Epoch [2057/4000] Validation metric {'Val/mean dice_metric': 0.972030758857727, 'Val/mean miou_metric': 0.9548841714859009, 'Val/mean f1': 0.9713738560676575, 'Val/mean precision': 0.9655762910842896, 'Val/mean recall': 0.9772413969039917, 'Val/mean hd95_metric': 7.342283725738525} +Cheakpoint... +Epoch [2057/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972030758857727, 'Val/mean miou_metric': 0.9548841714859009, 'Val/mean f1': 0.9713738560676575, 'Val/mean precision': 0.9655762910842896, 'Val/mean recall': 0.9772413969039917, 'Val/mean hd95_metric': 7.342283725738525} +Epoch [2058/4000] Training [1/16] Loss: 0.00474 +Epoch [2058/4000] Training [2/16] Loss: 0.00602 +Epoch [2058/4000] Training [3/16] Loss: 0.00527 +Epoch [2058/4000] Training [4/16] Loss: 0.00752 +Epoch [2058/4000] Training [5/16] Loss: 0.00648 +Epoch [2058/4000] Training [6/16] Loss: 0.00612 +Epoch [2058/4000] Training [7/16] Loss: 0.00614 +Epoch [2058/4000] Training [8/16] Loss: 0.00562 +Epoch [2058/4000] Training [9/16] Loss: 0.00555 +Epoch [2058/4000] Training [10/16] Loss: 0.00673 +Epoch [2058/4000] Training [11/16] Loss: 0.00571 +Epoch [2058/4000] Training [12/16] Loss: 0.00600 +Epoch [2058/4000] Training [13/16] Loss: 0.00497 +Epoch [2058/4000] Training [14/16] Loss: 0.00493 +Epoch [2058/4000] Training [15/16] Loss: 0.00654 +Epoch [2058/4000] Training [16/16] Loss: 0.00619 +Epoch [2058/4000] Training metric {'Train/mean dice_metric': 0.9959958791732788, 'Train/mean miou_metric': 0.9917417764663696, 'Train/mean f1': 0.9914265871047974, 'Train/mean precision': 0.9868418574333191, 'Train/mean recall': 0.9960541725158691, 'Train/mean hd95_metric': 1.036388635635376} +Epoch [2058/4000] Validation [1/4] Loss: 0.63461 focal_loss 0.51743 dice_loss 0.11719 +Epoch [2058/4000] Validation [2/4] Loss: 0.26525 focal_loss 0.15154 dice_loss 0.11372 +Epoch [2058/4000] Validation [3/4] Loss: 0.17918 focal_loss 0.11248 dice_loss 0.06670 +Epoch [2058/4000] Validation [4/4] Loss: 0.41812 focal_loss 0.29298 dice_loss 0.12513 +Epoch [2058/4000] Validation metric {'Val/mean dice_metric': 0.9690834283828735, 'Val/mean miou_metric': 0.9515953063964844, 'Val/mean f1': 0.9704232811927795, 'Val/mean precision': 0.9710233807563782, 'Val/mean recall': 0.9698238968849182, 'Val/mean hd95_metric': 6.700685024261475} +Cheakpoint... +Epoch [2058/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690834283828735, 'Val/mean miou_metric': 0.9515953063964844, 'Val/mean f1': 0.9704232811927795, 'Val/mean precision': 0.9710233807563782, 'Val/mean recall': 0.9698238968849182, 'Val/mean hd95_metric': 6.700685024261475} +Epoch [2059/4000] Training [1/16] Loss: 0.00511 +Epoch [2059/4000] Training [2/16] Loss: 0.00560 +Epoch [2059/4000] Training [3/16] Loss: 0.00493 +Epoch [2059/4000] Training [4/16] Loss: 0.00496 +Epoch [2059/4000] Training [5/16] Loss: 0.00424 +Epoch [2059/4000] Training [6/16] Loss: 0.00510 +Epoch [2059/4000] Training [7/16] Loss: 0.00561 +Epoch [2059/4000] Training [8/16] Loss: 0.00534 +Epoch [2059/4000] Training [9/16] Loss: 0.00490 +Epoch [2059/4000] Training [10/16] Loss: 0.00434 +Epoch [2059/4000] Training [11/16] Loss: 0.00420 +Epoch [2059/4000] Training [12/16] Loss: 0.00551 +Epoch [2059/4000] Training [13/16] Loss: 0.00558 +Epoch [2059/4000] Training [14/16] Loss: 0.00612 +Epoch [2059/4000] Training [15/16] Loss: 0.00667 +Epoch [2059/4000] Training [16/16] Loss: 0.00597 +Epoch [2059/4000] Training metric {'Train/mean dice_metric': 0.9961358308792114, 'Train/mean miou_metric': 0.9921534061431885, 'Train/mean f1': 0.9917250871658325, 'Train/mean precision': 0.987066924571991, 'Train/mean recall': 0.9964273571968079, 'Train/mean hd95_metric': 1.0398468971252441} +Epoch [2059/4000] Validation [1/4] Loss: 0.37059 focal_loss 0.28783 dice_loss 0.08276 +Epoch [2059/4000] Validation [2/4] Loss: 0.39329 focal_loss 0.25419 dice_loss 0.13910 +Epoch [2059/4000] Validation [3/4] Loss: 0.34913 focal_loss 0.24883 dice_loss 0.10030 +Epoch [2059/4000] Validation [4/4] Loss: 0.27389 focal_loss 0.17571 dice_loss 0.09818 +Epoch [2059/4000] Validation metric {'Val/mean dice_metric': 0.9708161354064941, 'Val/mean miou_metric': 0.9541730880737305, 'Val/mean f1': 0.9725288152694702, 'Val/mean precision': 0.9696686863899231, 'Val/mean recall': 0.9754058122634888, 'Val/mean hd95_metric': 6.32603120803833} +Cheakpoint... +Epoch [2059/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708161354064941, 'Val/mean miou_metric': 0.9541730880737305, 'Val/mean f1': 0.9725288152694702, 'Val/mean precision': 0.9696686863899231, 'Val/mean recall': 0.9754058122634888, 'Val/mean hd95_metric': 6.32603120803833} +Epoch [2060/4000] Training [1/16] Loss: 0.00606 +Epoch [2060/4000] Training [2/16] Loss: 0.00585 +Epoch [2060/4000] Training [3/16] Loss: 0.00661 +Epoch [2060/4000] Training [4/16] Loss: 0.00596 +Epoch [2060/4000] Training [5/16] Loss: 0.00717 +Epoch [2060/4000] Training [6/16] Loss: 0.00642 +Epoch [2060/4000] Training [7/16] Loss: 0.03425 +Epoch [2060/4000] Training [8/16] Loss: 0.00589 +Epoch [2060/4000] Training [9/16] Loss: 0.00699 +Epoch [2060/4000] Training [10/16] Loss: 0.00658 +Epoch [2060/4000] Training [11/16] Loss: 0.00692 +Epoch [2060/4000] Training [12/16] Loss: 0.00502 +Epoch [2060/4000] Training [13/16] Loss: 0.00482 +Epoch [2060/4000] Training [14/16] Loss: 0.00758 +Epoch [2060/4000] Training [15/16] Loss: 0.00497 +Epoch [2060/4000] Training [16/16] Loss: 0.00634 +Epoch [2060/4000] Training metric {'Train/mean dice_metric': 0.9960212707519531, 'Train/mean miou_metric': 0.9918010830879211, 'Train/mean f1': 0.9912065863609314, 'Train/mean precision': 0.9861571192741394, 'Train/mean recall': 0.9963080883026123, 'Train/mean hd95_metric': 1.0857040882110596} +Epoch [2060/4000] Validation [1/4] Loss: 0.51129 focal_loss 0.40775 dice_loss 0.10354 +Epoch [2060/4000] Validation [2/4] Loss: 0.96000 focal_loss 0.70799 dice_loss 0.25201 +Epoch [2060/4000] Validation [3/4] Loss: 0.40332 focal_loss 0.30080 dice_loss 0.10252 +Epoch [2060/4000] Validation [4/4] Loss: 0.34856 focal_loss 0.24104 dice_loss 0.10752 +Epoch [2060/4000] Validation metric {'Val/mean dice_metric': 0.9687138795852661, 'Val/mean miou_metric': 0.9515018463134766, 'Val/mean f1': 0.9703829288482666, 'Val/mean precision': 0.9710959196090698, 'Val/mean recall': 0.9696708917617798, 'Val/mean hd95_metric': 5.991054534912109} +Cheakpoint... +Epoch [2060/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687138795852661, 'Val/mean miou_metric': 0.9515018463134766, 'Val/mean f1': 0.9703829288482666, 'Val/mean precision': 0.9710959196090698, 'Val/mean recall': 0.9696708917617798, 'Val/mean hd95_metric': 5.991054534912109} +Epoch [2061/4000] Training [1/16] Loss: 0.00600 +Epoch [2061/4000] Training [2/16] Loss: 0.00944 +Epoch [2061/4000] Training [3/16] Loss: 0.00693 +Epoch [2061/4000] Training [4/16] Loss: 0.00692 +Epoch [2061/4000] Training [5/16] Loss: 0.00664 +Epoch [2061/4000] Training [6/16] Loss: 0.00738 +Epoch [2061/4000] Training [7/16] Loss: 0.00412 +Epoch [2061/4000] Training [8/16] Loss: 0.00619 +Epoch [2061/4000] Training [9/16] Loss: 0.00632 +Epoch [2061/4000] Training [10/16] Loss: 0.00468 +Epoch [2061/4000] Training [11/16] Loss: 0.00563 +Epoch [2061/4000] Training [12/16] Loss: 0.00404 +Epoch [2061/4000] Training [13/16] Loss: 0.00888 +Epoch [2061/4000] Training [14/16] Loss: 0.00487 +Epoch [2061/4000] Training [15/16] Loss: 0.00525 +Epoch [2061/4000] Training [16/16] Loss: 0.00728 +Epoch [2061/4000] Training metric {'Train/mean dice_metric': 0.9957760572433472, 'Train/mean miou_metric': 0.9914126396179199, 'Train/mean f1': 0.9914326667785645, 'Train/mean precision': 0.9869360327720642, 'Train/mean recall': 0.9959704875946045, 'Train/mean hd95_metric': 1.2165553569793701} +Epoch [2061/4000] Validation [1/4] Loss: 0.74898 focal_loss 0.61667 dice_loss 0.13231 +Epoch [2061/4000] Validation [2/4] Loss: 0.51292 focal_loss 0.37149 dice_loss 0.14143 +Epoch [2061/4000] Validation [3/4] Loss: 0.40817 focal_loss 0.29165 dice_loss 0.11652 +Epoch [2061/4000] Validation [4/4] Loss: 0.49247 focal_loss 0.35199 dice_loss 0.14048 +Epoch [2061/4000] Validation metric {'Val/mean dice_metric': 0.9703755378723145, 'Val/mean miou_metric': 0.9524642825126648, 'Val/mean f1': 0.9704594612121582, 'Val/mean precision': 0.9734363555908203, 'Val/mean recall': 0.967500627040863, 'Val/mean hd95_metric': 6.217367649078369} +Cheakpoint... +Epoch [2061/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703755378723145, 'Val/mean miou_metric': 0.9524642825126648, 'Val/mean f1': 0.9704594612121582, 'Val/mean precision': 0.9734363555908203, 'Val/mean recall': 0.967500627040863, 'Val/mean hd95_metric': 6.217367649078369} +Epoch [2062/4000] Training [1/16] Loss: 0.00599 +Epoch [2062/4000] Training [2/16] Loss: 0.00636 +Epoch [2062/4000] Training [3/16] Loss: 0.00513 +Epoch [2062/4000] Training [4/16] Loss: 0.00497 +Epoch [2062/4000] Training [5/16] Loss: 0.00460 +Epoch [2062/4000] Training [6/16] Loss: 0.01563 +Epoch [2062/4000] Training [7/16] Loss: 0.00590 +Epoch [2062/4000] Training [8/16] Loss: 0.00581 +Epoch [2062/4000] Training [9/16] Loss: 0.00511 +Epoch [2062/4000] Training [10/16] Loss: 0.00577 +Epoch [2062/4000] Training [11/16] Loss: 0.00575 +Epoch [2062/4000] Training [12/16] Loss: 0.00767 +Epoch [2062/4000] Training [13/16] Loss: 0.00550 +Epoch [2062/4000] Training [14/16] Loss: 0.00480 +Epoch [2062/4000] Training [15/16] Loss: 0.00396 +Epoch [2062/4000] Training [16/16] Loss: 0.00578 +Epoch [2062/4000] Training metric {'Train/mean dice_metric': 0.9961519241333008, 'Train/mean miou_metric': 0.9920579195022583, 'Train/mean f1': 0.9914910197257996, 'Train/mean precision': 0.9868661165237427, 'Train/mean recall': 0.9961594343185425, 'Train/mean hd95_metric': 1.0750112533569336} +Epoch [2062/4000] Validation [1/4] Loss: 0.79562 focal_loss 0.64525 dice_loss 0.15037 +Epoch [2062/4000] Validation [2/4] Loss: 0.44512 focal_loss 0.32286 dice_loss 0.12227 +Epoch [2062/4000] Validation [3/4] Loss: 0.33914 focal_loss 0.24994 dice_loss 0.08920 +Epoch [2062/4000] Validation [4/4] Loss: 0.46108 focal_loss 0.32500 dice_loss 0.13607 +Epoch [2062/4000] Validation metric {'Val/mean dice_metric': 0.9689168930053711, 'Val/mean miou_metric': 0.9512613415718079, 'Val/mean f1': 0.9701062440872192, 'Val/mean precision': 0.9740262627601624, 'Val/mean recall': 0.9662175178527832, 'Val/mean hd95_metric': 6.14743709564209} +Cheakpoint... +Epoch [2062/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9689], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9689168930053711, 'Val/mean miou_metric': 0.9512613415718079, 'Val/mean f1': 0.9701062440872192, 'Val/mean precision': 0.9740262627601624, 'Val/mean recall': 0.9662175178527832, 'Val/mean hd95_metric': 6.14743709564209} +Epoch [2063/4000] Training [1/16] Loss: 0.00557 +Epoch [2063/4000] Training [2/16] Loss: 0.00498 +Epoch [2063/4000] Training [3/16] Loss: 0.00688 +Epoch [2063/4000] Training [4/16] Loss: 0.00557 +Epoch [2063/4000] Training [5/16] Loss: 0.00788 +Epoch [2063/4000] Training [6/16] Loss: 0.00436 +Epoch [2063/4000] Training [7/16] Loss: 0.00702 +Epoch [2063/4000] Training [8/16] Loss: 0.00466 +Epoch [2063/4000] Training [9/16] Loss: 0.00715 +Epoch [2063/4000] Training [10/16] Loss: 0.00603 +Epoch [2063/4000] Training [11/16] Loss: 0.00508 +Epoch [2063/4000] Training [12/16] Loss: 0.00582 +Epoch [2063/4000] Training [13/16] Loss: 0.00487 +Epoch [2063/4000] Training [14/16] Loss: 0.00437 +Epoch [2063/4000] Training [15/16] Loss: 0.00579 +Epoch [2063/4000] Training [16/16] Loss: 0.00511 +Epoch [2063/4000] Training metric {'Train/mean dice_metric': 0.9963414669036865, 'Train/mean miou_metric': 0.9924571514129639, 'Train/mean f1': 0.9919273853302002, 'Train/mean precision': 0.987442672252655, 'Train/mean recall': 0.9964531064033508, 'Train/mean hd95_metric': 1.0356738567352295} +Epoch [2063/4000] Validation [1/4] Loss: 0.71282 focal_loss 0.59194 dice_loss 0.12089 +Epoch [2063/4000] Validation [2/4] Loss: 0.41673 focal_loss 0.30230 dice_loss 0.11442 +Epoch [2063/4000] Validation [3/4] Loss: 0.35628 focal_loss 0.26213 dice_loss 0.09415 +Epoch [2063/4000] Validation [4/4] Loss: 0.30691 focal_loss 0.19213 dice_loss 0.11478 +Epoch [2063/4000] Validation metric {'Val/mean dice_metric': 0.9695425033569336, 'Val/mean miou_metric': 0.9525648355484009, 'Val/mean f1': 0.9703271389007568, 'Val/mean precision': 0.9731417894363403, 'Val/mean recall': 0.967528760433197, 'Val/mean hd95_metric': 5.777249336242676} +Cheakpoint... +Epoch [2063/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9695], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695425033569336, 'Val/mean miou_metric': 0.9525648355484009, 'Val/mean f1': 0.9703271389007568, 'Val/mean precision': 0.9731417894363403, 'Val/mean recall': 0.967528760433197, 'Val/mean hd95_metric': 5.777249336242676} +Epoch [2064/4000] Training [1/16] Loss: 0.00448 +Epoch [2064/4000] Training [2/16] Loss: 0.00431 +Epoch [2064/4000] Training [3/16] Loss: 0.00548 +Epoch [2064/4000] Training [4/16] Loss: 0.00475 +Epoch [2064/4000] Training [5/16] Loss: 0.00494 +Epoch [2064/4000] Training [6/16] Loss: 0.00572 +Epoch [2064/4000] Training [7/16] Loss: 0.00393 +Epoch [2064/4000] Training [8/16] Loss: 0.00540 +Epoch [2064/4000] Training [9/16] Loss: 0.00411 +Epoch [2064/4000] Training [10/16] Loss: 0.00555 +Epoch [2064/4000] Training [11/16] Loss: 0.00476 +Epoch [2064/4000] Training [12/16] Loss: 0.00451 +Epoch [2064/4000] Training [13/16] Loss: 0.00815 +Epoch [2064/4000] Training [14/16] Loss: 0.00506 +Epoch [2064/4000] Training [15/16] Loss: 0.00553 +Epoch [2064/4000] Training [16/16] Loss: 0.00731 +Epoch [2064/4000] Training metric {'Train/mean dice_metric': 0.9966210126876831, 'Train/mean miou_metric': 0.9930047988891602, 'Train/mean f1': 0.9921621680259705, 'Train/mean precision': 0.98751300573349, 'Train/mean recall': 0.9968553781509399, 'Train/mean hd95_metric': 1.0123134851455688} +Epoch [2064/4000] Validation [1/4] Loss: 0.51546 focal_loss 0.40779 dice_loss 0.10768 +Epoch [2064/4000] Validation [2/4] Loss: 0.34949 focal_loss 0.20452 dice_loss 0.14497 +Epoch [2064/4000] Validation [3/4] Loss: 0.37733 focal_loss 0.28432 dice_loss 0.09301 +Epoch [2064/4000] Validation [4/4] Loss: 0.25157 focal_loss 0.15793 dice_loss 0.09364 +Epoch [2064/4000] Validation metric {'Val/mean dice_metric': 0.9743038415908813, 'Val/mean miou_metric': 0.9577266573905945, 'Val/mean f1': 0.9733611941337585, 'Val/mean precision': 0.9723246693611145, 'Val/mean recall': 0.974399983882904, 'Val/mean hd95_metric': 5.264876365661621} +Cheakpoint... +Epoch [2064/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743038415908813, 'Val/mean miou_metric': 0.9577266573905945, 'Val/mean f1': 0.9733611941337585, 'Val/mean precision': 0.9723246693611145, 'Val/mean recall': 0.974399983882904, 'Val/mean hd95_metric': 5.264876365661621} +Epoch [2065/4000] Training [1/16] Loss: 0.00657 +Epoch [2065/4000] Training [2/16] Loss: 0.00411 +Epoch [2065/4000] Training [3/16] Loss: 0.00603 +Epoch [2065/4000] Training [4/16] Loss: 0.00461 +Epoch [2065/4000] Training [5/16] Loss: 0.00617 +Epoch [2065/4000] Training [6/16] Loss: 0.00503 +Epoch [2065/4000] Training [7/16] Loss: 0.00459 +Epoch [2065/4000] Training [8/16] Loss: 0.00658 +Epoch [2065/4000] Training [9/16] Loss: 0.00647 +Epoch [2065/4000] Training [10/16] Loss: 0.00439 +Epoch [2065/4000] Training [11/16] Loss: 0.00503 +Epoch [2065/4000] Training [12/16] Loss: 0.00651 +Epoch [2065/4000] Training [13/16] Loss: 0.00527 +Epoch [2065/4000] Training [14/16] Loss: 0.00456 +Epoch [2065/4000] Training [15/16] Loss: 0.00422 +Epoch [2065/4000] Training [16/16] Loss: 0.00547 +Epoch [2065/4000] Training metric {'Train/mean dice_metric': 0.9966303110122681, 'Train/mean miou_metric': 0.993018627166748, 'Train/mean f1': 0.9921724200248718, 'Train/mean precision': 0.987649142742157, 'Train/mean recall': 0.9967373013496399, 'Train/mean hd95_metric': 0.9918380379676819} +Epoch [2065/4000] Validation [1/4] Loss: 0.30023 focal_loss 0.22906 dice_loss 0.07116 +Epoch [2065/4000] Validation [2/4] Loss: 0.38746 focal_loss 0.26561 dice_loss 0.12185 +Epoch [2065/4000] Validation [3/4] Loss: 0.36664 focal_loss 0.27858 dice_loss 0.08806 +Epoch [2065/4000] Validation [4/4] Loss: 0.25628 focal_loss 0.15883 dice_loss 0.09745 +Epoch [2065/4000] Validation metric {'Val/mean dice_metric': 0.9721585512161255, 'Val/mean miou_metric': 0.9560664892196655, 'Val/mean f1': 0.97379469871521, 'Val/mean precision': 0.9728919267654419, 'Val/mean recall': 0.9746992588043213, 'Val/mean hd95_metric': 5.344054698944092} +Cheakpoint... +Epoch [2065/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721585512161255, 'Val/mean miou_metric': 0.9560664892196655, 'Val/mean f1': 0.97379469871521, 'Val/mean precision': 0.9728919267654419, 'Val/mean recall': 0.9746992588043213, 'Val/mean hd95_metric': 5.344054698944092} +Epoch [2066/4000] Training [1/16] Loss: 0.00580 +Epoch [2066/4000] Training [2/16] Loss: 0.00593 +Epoch [2066/4000] Training [3/16] Loss: 0.00508 +Epoch [2066/4000] Training [4/16] Loss: 0.00497 +Epoch [2066/4000] Training [5/16] Loss: 0.00503 +Epoch [2066/4000] Training [6/16] Loss: 0.00392 +Epoch [2066/4000] Training [7/16] Loss: 0.00457 +Epoch [2066/4000] Training [8/16] Loss: 0.00450 +Epoch [2066/4000] Training [9/16] Loss: 0.00507 +Epoch [2066/4000] Training [10/16] Loss: 0.00491 +Epoch [2066/4000] Training [11/16] Loss: 0.00495 +Epoch [2066/4000] Training [12/16] Loss: 0.00683 +Epoch [2066/4000] Training [13/16] Loss: 0.00635 +Epoch [2066/4000] Training [14/16] Loss: 0.00596 +Epoch [2066/4000] Training [15/16] Loss: 0.00451 +Epoch [2066/4000] Training [16/16] Loss: 0.00471 +Epoch [2066/4000] Training metric {'Train/mean dice_metric': 0.9966822862625122, 'Train/mean miou_metric': 0.9931213855743408, 'Train/mean f1': 0.9922516345977783, 'Train/mean precision': 0.9877333045005798, 'Train/mean recall': 0.9968115091323853, 'Train/mean hd95_metric': 0.989550769329071} +Epoch [2066/4000] Validation [1/4] Loss: 0.53471 focal_loss 0.42878 dice_loss 0.10593 +Epoch [2066/4000] Validation [2/4] Loss: 0.70787 focal_loss 0.49586 dice_loss 0.21200 +Epoch [2066/4000] Validation [3/4] Loss: 0.37796 focal_loss 0.28938 dice_loss 0.08858 +Epoch [2066/4000] Validation [4/4] Loss: 0.17761 focal_loss 0.09902 dice_loss 0.07858 +Epoch [2066/4000] Validation metric {'Val/mean dice_metric': 0.9707778692245483, 'Val/mean miou_metric': 0.9546211361885071, 'Val/mean f1': 0.9725106358528137, 'Val/mean precision': 0.971477210521698, 'Val/mean recall': 0.9735463857650757, 'Val/mean hd95_metric': 5.785465240478516} +Cheakpoint... +Epoch [2066/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707778692245483, 'Val/mean miou_metric': 0.9546211361885071, 'Val/mean f1': 0.9725106358528137, 'Val/mean precision': 0.971477210521698, 'Val/mean recall': 0.9735463857650757, 'Val/mean hd95_metric': 5.785465240478516} +Epoch [2067/4000] Training [1/16] Loss: 0.00544 +Epoch [2067/4000] Training [2/16] Loss: 0.00605 +Epoch [2067/4000] Training [3/16] Loss: 0.00415 +Epoch [2067/4000] Training [4/16] Loss: 0.00652 +Epoch [2067/4000] Training [5/16] Loss: 0.00462 +Epoch [2067/4000] Training [6/16] Loss: 0.00418 +Epoch [2067/4000] Training [7/16] Loss: 0.00466 +Epoch [2067/4000] Training [8/16] Loss: 0.00571 +Epoch [2067/4000] Training [9/16] Loss: 0.00693 +Epoch [2067/4000] Training [10/16] Loss: 0.00532 +Epoch [2067/4000] Training [11/16] Loss: 0.00432 +Epoch [2067/4000] Training [12/16] Loss: 0.00794 +Epoch [2067/4000] Training [13/16] Loss: 0.00529 +Epoch [2067/4000] Training [14/16] Loss: 0.00450 +Epoch [2067/4000] Training [15/16] Loss: 0.00414 +Epoch [2067/4000] Training [16/16] Loss: 0.00682 +Epoch [2067/4000] Training metric {'Train/mean dice_metric': 0.9964828491210938, 'Train/mean miou_metric': 0.992708683013916, 'Train/mean f1': 0.991827130317688, 'Train/mean precision': 0.9871065616607666, 'Train/mean recall': 0.9965931177139282, 'Train/mean hd95_metric': 1.00773024559021} +Epoch [2067/4000] Validation [1/4] Loss: 0.35090 focal_loss 0.27537 dice_loss 0.07554 +Epoch [2067/4000] Validation [2/4] Loss: 0.50871 focal_loss 0.35409 dice_loss 0.15463 +Epoch [2067/4000] Validation [3/4] Loss: 0.38999 focal_loss 0.29784 dice_loss 0.09215 +Epoch [2067/4000] Validation [4/4] Loss: 0.32491 focal_loss 0.20852 dice_loss 0.11640 +Epoch [2067/4000] Validation metric {'Val/mean dice_metric': 0.9721525311470032, 'Val/mean miou_metric': 0.9552879333496094, 'Val/mean f1': 0.9735876321792603, 'Val/mean precision': 0.9711045026779175, 'Val/mean recall': 0.9760834574699402, 'Val/mean hd95_metric': 5.694446086883545} +Cheakpoint... +Epoch [2067/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721525311470032, 'Val/mean miou_metric': 0.9552879333496094, 'Val/mean f1': 0.9735876321792603, 'Val/mean precision': 0.9711045026779175, 'Val/mean recall': 0.9760834574699402, 'Val/mean hd95_metric': 5.694446086883545} +Epoch [2068/4000] Training [1/16] Loss: 0.00620 +Epoch [2068/4000] Training [2/16] Loss: 0.00570 +Epoch [2068/4000] Training [3/16] Loss: 0.00447 +Epoch [2068/4000] Training [4/16] Loss: 0.00587 +Epoch [2068/4000] Training [5/16] Loss: 0.00466 +Epoch [2068/4000] Training [6/16] Loss: 0.00461 +Epoch [2068/4000] Training [7/16] Loss: 0.00462 +Epoch [2068/4000] Training [8/16] Loss: 0.00705 +Epoch [2068/4000] Training [9/16] Loss: 0.00742 +Epoch [2068/4000] Training [10/16] Loss: 0.00463 +Epoch [2068/4000] Training [11/16] Loss: 0.00611 +Epoch [2068/4000] Training [12/16] Loss: 0.00452 +Epoch [2068/4000] Training [13/16] Loss: 0.00431 +Epoch [2068/4000] Training [14/16] Loss: 0.00662 +Epoch [2068/4000] Training [15/16] Loss: 0.00605 +Epoch [2068/4000] Training [16/16] Loss: 0.00608 +Epoch [2068/4000] Training metric {'Train/mean dice_metric': 0.9964052438735962, 'Train/mean miou_metric': 0.9925694465637207, 'Train/mean f1': 0.9918725490570068, 'Train/mean precision': 0.9871645569801331, 'Train/mean recall': 0.9966259002685547, 'Train/mean hd95_metric': 0.9997687935829163} +Epoch [2068/4000] Validation [1/4] Loss: 0.43298 focal_loss 0.33132 dice_loss 0.10166 +Epoch [2068/4000] Validation [2/4] Loss: 0.30900 focal_loss 0.19888 dice_loss 0.11012 +Epoch [2068/4000] Validation [3/4] Loss: 0.37562 focal_loss 0.28563 dice_loss 0.08999 +Epoch [2068/4000] Validation [4/4] Loss: 0.22142 focal_loss 0.13027 dice_loss 0.09116 +Epoch [2068/4000] Validation metric {'Val/mean dice_metric': 0.971579909324646, 'Val/mean miou_metric': 0.9549629092216492, 'Val/mean f1': 0.9731363654136658, 'Val/mean precision': 0.9726390838623047, 'Val/mean recall': 0.9736341834068298, 'Val/mean hd95_metric': 6.5594987869262695} +Cheakpoint... +Epoch [2068/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971579909324646, 'Val/mean miou_metric': 0.9549629092216492, 'Val/mean f1': 0.9731363654136658, 'Val/mean precision': 0.9726390838623047, 'Val/mean recall': 0.9736341834068298, 'Val/mean hd95_metric': 6.5594987869262695} +Epoch [2069/4000] Training [1/16] Loss: 0.00562 +Epoch [2069/4000] Training [2/16] Loss: 0.00627 +Epoch [2069/4000] Training [3/16] Loss: 0.00542 +Epoch [2069/4000] Training [4/16] Loss: 0.00612 +Epoch [2069/4000] Training [5/16] Loss: 0.00511 +Epoch [2069/4000] Training [6/16] Loss: 0.00523 +Epoch [2069/4000] Training [7/16] Loss: 0.00514 +Epoch [2069/4000] Training [8/16] Loss: 0.00544 +Epoch [2069/4000] Training [9/16] Loss: 0.00476 +Epoch [2069/4000] Training [10/16] Loss: 0.00692 +Epoch [2069/4000] Training [11/16] Loss: 0.00559 +Epoch [2069/4000] Training [12/16] Loss: 0.00930 +Epoch [2069/4000] Training [13/16] Loss: 0.00619 +Epoch [2069/4000] Training [14/16] Loss: 0.00679 +Epoch [2069/4000] Training [15/16] Loss: 0.00590 +Epoch [2069/4000] Training [16/16] Loss: 0.00565 +Epoch [2069/4000] Training metric {'Train/mean dice_metric': 0.9960681200027466, 'Train/mean miou_metric': 0.9918949604034424, 'Train/mean f1': 0.9917007684707642, 'Train/mean precision': 0.9871079921722412, 'Train/mean recall': 0.9963364601135254, 'Train/mean hd95_metric': 1.0224255323410034} +Epoch [2069/4000] Validation [1/4] Loss: 0.76467 focal_loss 0.63610 dice_loss 0.12857 +Epoch [2069/4000] Validation [2/4] Loss: 0.38222 focal_loss 0.25883 dice_loss 0.12339 +Epoch [2069/4000] Validation [3/4] Loss: 0.35369 focal_loss 0.26025 dice_loss 0.09344 +Epoch [2069/4000] Validation [4/4] Loss: 0.39719 focal_loss 0.27168 dice_loss 0.12551 +Epoch [2069/4000] Validation metric {'Val/mean dice_metric': 0.9707996249198914, 'Val/mean miou_metric': 0.9533761739730835, 'Val/mean f1': 0.9707403779029846, 'Val/mean precision': 0.9734387993812561, 'Val/mean recall': 0.9680567383766174, 'Val/mean hd95_metric': 5.4580535888671875} +Cheakpoint... +Epoch [2069/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707996249198914, 'Val/mean miou_metric': 0.9533761739730835, 'Val/mean f1': 0.9707403779029846, 'Val/mean precision': 0.9734387993812561, 'Val/mean recall': 0.9680567383766174, 'Val/mean hd95_metric': 5.4580535888671875} +Epoch [2070/4000] Training [1/16] Loss: 0.00681 +Epoch [2070/4000] Training [2/16] Loss: 0.00486 +Epoch [2070/4000] Training [3/16] Loss: 0.00534 +Epoch [2070/4000] Training [4/16] Loss: 0.00582 +Epoch [2070/4000] Training [5/16] Loss: 0.00576 +Epoch [2070/4000] Training [6/16] Loss: 0.00530 +Epoch [2070/4000] Training [7/16] Loss: 0.00546 +Epoch [2070/4000] Training [8/16] Loss: 0.00460 +Epoch [2070/4000] Training [9/16] Loss: 0.00475 +Epoch [2070/4000] Training [10/16] Loss: 0.00707 +Epoch [2070/4000] Training [11/16] Loss: 0.00793 +Epoch [2070/4000] Training [12/16] Loss: 0.00483 +Epoch [2070/4000] Training [13/16] Loss: 0.00665 +Epoch [2070/4000] Training [14/16] Loss: 0.00551 +Epoch [2070/4000] Training [15/16] Loss: 0.00581 +Epoch [2070/4000] Training [16/16] Loss: 0.00613 +Epoch [2070/4000] Training metric {'Train/mean dice_metric': 0.996260404586792, 'Train/mean miou_metric': 0.9922876954078674, 'Train/mean f1': 0.9918574094772339, 'Train/mean precision': 0.9874480366706848, 'Train/mean recall': 0.9963063597679138, 'Train/mean hd95_metric': 1.097301959991455} +Epoch [2070/4000] Validation [1/4] Loss: 0.26451 focal_loss 0.20095 dice_loss 0.06356 +Epoch [2070/4000] Validation [2/4] Loss: 0.39879 focal_loss 0.25317 dice_loss 0.14562 +Epoch [2070/4000] Validation [3/4] Loss: 0.58611 focal_loss 0.45797 dice_loss 0.12814 +Epoch [2070/4000] Validation [4/4] Loss: 0.26709 focal_loss 0.17258 dice_loss 0.09451 +Epoch [2070/4000] Validation metric {'Val/mean dice_metric': 0.9731704592704773, 'Val/mean miou_metric': 0.9564679861068726, 'Val/mean f1': 0.9742881655693054, 'Val/mean precision': 0.9695751070976257, 'Val/mean recall': 0.9790473580360413, 'Val/mean hd95_metric': 5.974246978759766} +Cheakpoint... +Epoch [2070/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731704592704773, 'Val/mean miou_metric': 0.9564679861068726, 'Val/mean f1': 0.9742881655693054, 'Val/mean precision': 0.9695751070976257, 'Val/mean recall': 0.9790473580360413, 'Val/mean hd95_metric': 5.974246978759766} +Epoch [2071/4000] Training [1/16] Loss: 0.00748 +Epoch [2071/4000] Training [2/16] Loss: 0.00491 +Epoch [2071/4000] Training [3/16] Loss: 0.00538 +Epoch [2071/4000] Training [4/16] Loss: 0.00568 +Epoch [2071/4000] Training [5/16] Loss: 0.00488 +Epoch [2071/4000] Training [6/16] Loss: 0.00609 +Epoch [2071/4000] Training [7/16] Loss: 0.00450 +Epoch [2071/4000] Training [8/16] Loss: 0.00615 +Epoch [2071/4000] Training [9/16] Loss: 0.00856 +Epoch [2071/4000] Training [10/16] Loss: 0.00550 +Epoch [2071/4000] Training [11/16] Loss: 0.00499 +Epoch [2071/4000] Training [12/16] Loss: 0.00459 +Epoch [2071/4000] Training [13/16] Loss: 0.00617 +Epoch [2071/4000] Training [14/16] Loss: 0.00595 +Epoch [2071/4000] Training [15/16] Loss: 0.00458 +Epoch [2071/4000] Training [16/16] Loss: 0.00543 +Epoch [2071/4000] Training metric {'Train/mean dice_metric': 0.996078610420227, 'Train/mean miou_metric': 0.9919297695159912, 'Train/mean f1': 0.991953432559967, 'Train/mean precision': 0.9875190854072571, 'Train/mean recall': 0.9964277148246765, 'Train/mean hd95_metric': 1.0182933807373047} +Epoch [2071/4000] Validation [1/4] Loss: 0.25836 focal_loss 0.20170 dice_loss 0.05667 +Epoch [2071/4000] Validation [2/4] Loss: 0.67955 focal_loss 0.48201 dice_loss 0.19754 +Epoch [2071/4000] Validation [3/4] Loss: 0.39711 focal_loss 0.29503 dice_loss 0.10208 +Epoch [2071/4000] Validation [4/4] Loss: 0.22398 focal_loss 0.13750 dice_loss 0.08647 +Epoch [2071/4000] Validation metric {'Val/mean dice_metric': 0.9742143750190735, 'Val/mean miou_metric': 0.9577115774154663, 'Val/mean f1': 0.9750953316688538, 'Val/mean precision': 0.9698746204376221, 'Val/mean recall': 0.9803726077079773, 'Val/mean hd95_metric': 5.73955774307251} +Cheakpoint... +Epoch [2071/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742143750190735, 'Val/mean miou_metric': 0.9577115774154663, 'Val/mean f1': 0.9750953316688538, 'Val/mean precision': 0.9698746204376221, 'Val/mean recall': 0.9803726077079773, 'Val/mean hd95_metric': 5.73955774307251} +Epoch [2072/4000] Training [1/16] Loss: 0.00549 +Epoch [2072/4000] Training [2/16] Loss: 0.00539 +Epoch [2072/4000] Training [3/16] Loss: 0.00689 +Epoch [2072/4000] Training [4/16] Loss: 0.00555 +Epoch [2072/4000] Training [5/16] Loss: 0.00438 +Epoch [2072/4000] Training [6/16] Loss: 0.00704 +Epoch [2072/4000] Training [7/16] Loss: 0.00901 +Epoch [2072/4000] Training [8/16] Loss: 0.00539 +Epoch [2072/4000] Training [9/16] Loss: 0.00439 +Epoch [2072/4000] Training [10/16] Loss: 0.00555 +Epoch [2072/4000] Training [11/16] Loss: 0.00516 +Epoch [2072/4000] Training [12/16] Loss: 0.00668 +Epoch [2072/4000] Training [13/16] Loss: 0.00561 +Epoch [2072/4000] Training [14/16] Loss: 0.00476 +Epoch [2072/4000] Training [15/16] Loss: 0.00432 +Epoch [2072/4000] Training [16/16] Loss: 0.00457 +Epoch [2072/4000] Training metric {'Train/mean dice_metric': 0.9963249564170837, 'Train/mean miou_metric': 0.9924113750457764, 'Train/mean f1': 0.9920611381530762, 'Train/mean precision': 0.9875161647796631, 'Train/mean recall': 0.9966481328010559, 'Train/mean hd95_metric': 0.9966849684715271} +Epoch [2072/4000] Validation [1/4] Loss: 0.31285 focal_loss 0.24928 dice_loss 0.06357 +Epoch [2072/4000] Validation [2/4] Loss: 0.29426 focal_loss 0.18479 dice_loss 0.10947 +Epoch [2072/4000] Validation [3/4] Loss: 0.21858 focal_loss 0.14696 dice_loss 0.07162 +Epoch [2072/4000] Validation [4/4] Loss: 0.27326 focal_loss 0.17628 dice_loss 0.09697 +Epoch [2072/4000] Validation metric {'Val/mean dice_metric': 0.973890483379364, 'Val/mean miou_metric': 0.957341194152832, 'Val/mean f1': 0.97536301612854, 'Val/mean precision': 0.9724718928337097, 'Val/mean recall': 0.9782711863517761, 'Val/mean hd95_metric': 5.363127708435059} +Cheakpoint... +Epoch [2072/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973890483379364, 'Val/mean miou_metric': 0.957341194152832, 'Val/mean f1': 0.97536301612854, 'Val/mean precision': 0.9724718928337097, 'Val/mean recall': 0.9782711863517761, 'Val/mean hd95_metric': 5.363127708435059} +Epoch [2073/4000] Training [1/16] Loss: 0.00623 +Epoch [2073/4000] Training [2/16] Loss: 0.00808 +Epoch [2073/4000] Training [3/16] Loss: 0.00535 +Epoch [2073/4000] Training [4/16] Loss: 0.00453 +Epoch [2073/4000] Training [5/16] Loss: 0.00466 +Epoch [2073/4000] Training [6/16] Loss: 0.00450 +Epoch [2073/4000] Training [7/16] Loss: 0.00544 +Epoch [2073/4000] Training [8/16] Loss: 0.00697 +Epoch [2073/4000] Training [9/16] Loss: 0.00659 +Epoch [2073/4000] Training [10/16] Loss: 0.00669 +Epoch [2073/4000] Training [11/16] Loss: 0.00430 +Epoch [2073/4000] Training [12/16] Loss: 0.00513 +Epoch [2073/4000] Training [13/16] Loss: 0.00712 +Epoch [2073/4000] Training [14/16] Loss: 0.00884 +Epoch [2073/4000] Training [15/16] Loss: 0.00630 +Epoch [2073/4000] Training [16/16] Loss: 0.00530 +Epoch [2073/4000] Training metric {'Train/mean dice_metric': 0.9959292411804199, 'Train/mean miou_metric': 0.9916487336158752, 'Train/mean f1': 0.9915063977241516, 'Train/mean precision': 0.9868661165237427, 'Train/mean recall': 0.9961904883384705, 'Train/mean hd95_metric': 1.0353736877441406} +Epoch [2073/4000] Validation [1/4] Loss: 0.30361 focal_loss 0.23673 dice_loss 0.06688 +Epoch [2073/4000] Validation [2/4] Loss: 0.40464 focal_loss 0.24875 dice_loss 0.15589 +Epoch [2073/4000] Validation [3/4] Loss: 0.33122 focal_loss 0.24163 dice_loss 0.08959 +Epoch [2073/4000] Validation [4/4] Loss: 0.28632 focal_loss 0.17375 dice_loss 0.11257 +Epoch [2073/4000] Validation metric {'Val/mean dice_metric': 0.9701288342475891, 'Val/mean miou_metric': 0.9536218643188477, 'Val/mean f1': 0.9737574458122253, 'Val/mean precision': 0.9726585149765015, 'Val/mean recall': 0.9748589396476746, 'Val/mean hd95_metric': 6.009425640106201} +Cheakpoint... +Epoch [2073/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701288342475891, 'Val/mean miou_metric': 0.9536218643188477, 'Val/mean f1': 0.9737574458122253, 'Val/mean precision': 0.9726585149765015, 'Val/mean recall': 0.9748589396476746, 'Val/mean hd95_metric': 6.009425640106201} +Epoch [2074/4000] Training [1/16] Loss: 0.00541 +Epoch [2074/4000] Training [2/16] Loss: 0.00808 +Epoch [2074/4000] Training [3/16] Loss: 0.00492 +Epoch [2074/4000] Training [4/16] Loss: 0.00489 +Epoch [2074/4000] Training [5/16] Loss: 0.00793 +Epoch [2074/4000] Training [6/16] Loss: 0.00539 +Epoch [2074/4000] Training [7/16] Loss: 0.00598 +Epoch [2074/4000] Training [8/16] Loss: 0.00527 +Epoch [2074/4000] Training [9/16] Loss: 0.00871 +Epoch [2074/4000] Training [10/16] Loss: 0.00685 +Epoch [2074/4000] Training [11/16] Loss: 0.00600 +Epoch [2074/4000] Training [12/16] Loss: 0.00488 +Epoch [2074/4000] Training [13/16] Loss: 0.00773 +Epoch [2074/4000] Training [14/16] Loss: 0.00500 +Epoch [2074/4000] Training [15/16] Loss: 0.00652 +Epoch [2074/4000] Training [16/16] Loss: 0.00487 +Epoch [2074/4000] Training metric {'Train/mean dice_metric': 0.9961026310920715, 'Train/mean miou_metric': 0.991976261138916, 'Train/mean f1': 0.9917009472846985, 'Train/mean precision': 0.9872756600379944, 'Train/mean recall': 0.9961661100387573, 'Train/mean hd95_metric': 1.0210678577423096} +Epoch [2074/4000] Validation [1/4] Loss: 0.34400 focal_loss 0.27178 dice_loss 0.07222 +Epoch [2074/4000] Validation [2/4] Loss: 0.59508 focal_loss 0.41036 dice_loss 0.18472 +Epoch [2074/4000] Validation [3/4] Loss: 0.35464 focal_loss 0.26464 dice_loss 0.09000 +Epoch [2074/4000] Validation [4/4] Loss: 0.26006 focal_loss 0.16214 dice_loss 0.09792 +Epoch [2074/4000] Validation metric {'Val/mean dice_metric': 0.9720751047134399, 'Val/mean miou_metric': 0.9557682871818542, 'Val/mean f1': 0.9748475551605225, 'Val/mean precision': 0.9722884297370911, 'Val/mean recall': 0.9774202108383179, 'Val/mean hd95_metric': 5.6846537590026855} +Cheakpoint... +Epoch [2074/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720751047134399, 'Val/mean miou_metric': 0.9557682871818542, 'Val/mean f1': 0.9748475551605225, 'Val/mean precision': 0.9722884297370911, 'Val/mean recall': 0.9774202108383179, 'Val/mean hd95_metric': 5.6846537590026855} +Epoch [2075/4000] Training [1/16] Loss: 0.00552 +Epoch [2075/4000] Training [2/16] Loss: 0.00417 +Epoch [2075/4000] Training [3/16] Loss: 0.00527 +Epoch [2075/4000] Training [4/16] Loss: 0.00617 +Epoch [2075/4000] Training [5/16] Loss: 0.00701 +Epoch [2075/4000] Training [6/16] Loss: 0.00508 +Epoch [2075/4000] Training [7/16] Loss: 0.00505 +Epoch [2075/4000] Training [8/16] Loss: 0.00677 +Epoch [2075/4000] Training [9/16] Loss: 0.00460 +Epoch [2075/4000] Training [10/16] Loss: 0.00644 +Epoch [2075/4000] Training [11/16] Loss: 0.00512 +Epoch [2075/4000] Training [12/16] Loss: 0.00599 +Epoch [2075/4000] Training [13/16] Loss: 0.00664 +Epoch [2075/4000] Training [14/16] Loss: 0.00764 +Epoch [2075/4000] Training [15/16] Loss: 0.00658 +Epoch [2075/4000] Training [16/16] Loss: 0.00598 +Epoch [2075/4000] Training metric {'Train/mean dice_metric': 0.9960436224937439, 'Train/mean miou_metric': 0.9918237924575806, 'Train/mean f1': 0.9915416836738586, 'Train/mean precision': 0.9868379831314087, 'Train/mean recall': 0.9962905049324036, 'Train/mean hd95_metric': 1.0635287761688232} +Epoch [2075/4000] Validation [1/4] Loss: 0.32356 focal_loss 0.24865 dice_loss 0.07492 +Epoch [2075/4000] Validation [2/4] Loss: 0.73228 focal_loss 0.49581 dice_loss 0.23647 +Epoch [2075/4000] Validation [3/4] Loss: 0.36456 focal_loss 0.27204 dice_loss 0.09252 +Epoch [2075/4000] Validation [4/4] Loss: 0.28421 focal_loss 0.17264 dice_loss 0.11157 +Epoch [2075/4000] Validation metric {'Val/mean dice_metric': 0.9704490900039673, 'Val/mean miou_metric': 0.9538761973381042, 'Val/mean f1': 0.9737427830696106, 'Val/mean precision': 0.9716264605522156, 'Val/mean recall': 0.9758683443069458, 'Val/mean hd95_metric': 5.891378402709961} +Cheakpoint... +Epoch [2075/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704490900039673, 'Val/mean miou_metric': 0.9538761973381042, 'Val/mean f1': 0.9737427830696106, 'Val/mean precision': 0.9716264605522156, 'Val/mean recall': 0.9758683443069458, 'Val/mean hd95_metric': 5.891378402709961} +Epoch [2076/4000] Training [1/16] Loss: 0.00642 +Epoch [2076/4000] Training [2/16] Loss: 0.00523 +Epoch [2076/4000] Training [3/16] Loss: 0.00634 +Epoch [2076/4000] Training [4/16] Loss: 0.00458 +Epoch [2076/4000] Training [5/16] Loss: 0.00671 +Epoch [2076/4000] Training [6/16] Loss: 0.00614 +Epoch [2076/4000] Training [7/16] Loss: 0.00514 +Epoch [2076/4000] Training [8/16] Loss: 0.00560 +Epoch [2076/4000] Training [9/16] Loss: 0.01055 +Epoch [2076/4000] Training [10/16] Loss: 0.00450 +Epoch [2076/4000] Training [11/16] Loss: 0.00490 +Epoch [2076/4000] Training [12/16] Loss: 0.00689 +Epoch [2076/4000] Training [13/16] Loss: 0.00516 +Epoch [2076/4000] Training [14/16] Loss: 0.00465 +Epoch [2076/4000] Training [15/16] Loss: 0.00642 +Epoch [2076/4000] Training [16/16] Loss: 0.00512 +Epoch [2076/4000] Training metric {'Train/mean dice_metric': 0.9963349103927612, 'Train/mean miou_metric': 0.9924282431602478, 'Train/mean f1': 0.9918949604034424, 'Train/mean precision': 0.9872594475746155, 'Train/mean recall': 0.9965742826461792, 'Train/mean hd95_metric': 0.9995372295379639} +Epoch [2076/4000] Validation [1/4] Loss: 0.25967 focal_loss 0.19914 dice_loss 0.06053 +Epoch [2076/4000] Validation [2/4] Loss: 0.71634 focal_loss 0.51734 dice_loss 0.19900 +Epoch [2076/4000] Validation [3/4] Loss: 0.20255 focal_loss 0.13287 dice_loss 0.06967 +Epoch [2076/4000] Validation [4/4] Loss: 0.25089 focal_loss 0.15429 dice_loss 0.09660 +Epoch [2076/4000] Validation metric {'Val/mean dice_metric': 0.9722440838813782, 'Val/mean miou_metric': 0.9561649560928345, 'Val/mean f1': 0.9753651022911072, 'Val/mean precision': 0.9733414649963379, 'Val/mean recall': 0.9773973822593689, 'Val/mean hd95_metric': 4.793626308441162} +Cheakpoint... +Epoch [2076/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722440838813782, 'Val/mean miou_metric': 0.9561649560928345, 'Val/mean f1': 0.9753651022911072, 'Val/mean precision': 0.9733414649963379, 'Val/mean recall': 0.9773973822593689, 'Val/mean hd95_metric': 4.793626308441162} +Epoch [2077/4000] Training [1/16] Loss: 0.00660 +Epoch [2077/4000] Training [2/16] Loss: 0.00494 +Epoch [2077/4000] Training [3/16] Loss: 0.00808 +Epoch [2077/4000] Training [4/16] Loss: 0.00764 +Epoch [2077/4000] Training [5/16] Loss: 0.00415 +Epoch [2077/4000] Training [6/16] Loss: 0.00978 +Epoch [2077/4000] Training [7/16] Loss: 0.00443 +Epoch [2077/4000] Training [8/16] Loss: 0.00719 +Epoch [2077/4000] Training [9/16] Loss: 0.00606 +Epoch [2077/4000] Training [10/16] Loss: 0.00548 +Epoch [2077/4000] Training [11/16] Loss: 0.00503 +Epoch [2077/4000] Training [12/16] Loss: 0.00970 +Epoch [2077/4000] Training [13/16] Loss: 0.00580 +Epoch [2077/4000] Training [14/16] Loss: 0.00498 +Epoch [2077/4000] Training [15/16] Loss: 0.00730 +Epoch [2077/4000] Training [16/16] Loss: 0.00425 +Epoch [2077/4000] Training metric {'Train/mean dice_metric': 0.996141791343689, 'Train/mean miou_metric': 0.9920409917831421, 'Train/mean f1': 0.9916127324104309, 'Train/mean precision': 0.9869381189346313, 'Train/mean recall': 0.9963318109512329, 'Train/mean hd95_metric': 1.0022907257080078} +Epoch [2077/4000] Validation [1/4] Loss: 0.24857 focal_loss 0.19058 dice_loss 0.05800 +Epoch [2077/4000] Validation [2/4] Loss: 0.70484 focal_loss 0.49618 dice_loss 0.20866 +Epoch [2077/4000] Validation [3/4] Loss: 0.42913 focal_loss 0.32634 dice_loss 0.10279 +Epoch [2077/4000] Validation [4/4] Loss: 0.24498 focal_loss 0.15773 dice_loss 0.08725 +Epoch [2077/4000] Validation metric {'Val/mean dice_metric': 0.9712751507759094, 'Val/mean miou_metric': 0.9552372694015503, 'Val/mean f1': 0.9743418097496033, 'Val/mean precision': 0.9720750451087952, 'Val/mean recall': 0.9766190648078918, 'Val/mean hd95_metric': 5.478543281555176} +Cheakpoint... +Epoch [2077/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712751507759094, 'Val/mean miou_metric': 0.9552372694015503, 'Val/mean f1': 0.9743418097496033, 'Val/mean precision': 0.9720750451087952, 'Val/mean recall': 0.9766190648078918, 'Val/mean hd95_metric': 5.478543281555176} +Epoch [2078/4000] Training [1/16] Loss: 0.00487 +Epoch [2078/4000] Training [2/16] Loss: 0.00560 +Epoch [2078/4000] Training [3/16] Loss: 0.00636 +Epoch [2078/4000] Training [4/16] Loss: 0.00674 +Epoch [2078/4000] Training [5/16] Loss: 0.00547 +Epoch [2078/4000] Training [6/16] Loss: 0.00606 +Epoch [2078/4000] Training [7/16] Loss: 0.00414 +Epoch [2078/4000] Training [8/16] Loss: 0.00592 +Epoch [2078/4000] Training [9/16] Loss: 0.00472 +Epoch [2078/4000] Training [10/16] Loss: 0.00546 +Epoch [2078/4000] Training [11/16] Loss: 0.00946 +Epoch [2078/4000] Training [12/16] Loss: 0.00465 +Epoch [2078/4000] Training [13/16] Loss: 0.00492 +Epoch [2078/4000] Training [14/16] Loss: 0.00607 +Epoch [2078/4000] Training [15/16] Loss: 0.00427 +Epoch [2078/4000] Training [16/16] Loss: 0.00427 +Epoch [2078/4000] Training metric {'Train/mean dice_metric': 0.9965885877609253, 'Train/mean miou_metric': 0.9929254651069641, 'Train/mean f1': 0.9921324253082275, 'Train/mean precision': 0.9875423312187195, 'Train/mean recall': 0.9967653751373291, 'Train/mean hd95_metric': 1.0041532516479492} +Epoch [2078/4000] Validation [1/4] Loss: 0.36198 focal_loss 0.28439 dice_loss 0.07759 +Epoch [2078/4000] Validation [2/4] Loss: 0.56340 focal_loss 0.35688 dice_loss 0.20652 +Epoch [2078/4000] Validation [3/4] Loss: 0.40517 focal_loss 0.30311 dice_loss 0.10206 +Epoch [2078/4000] Validation [4/4] Loss: 0.20096 focal_loss 0.11478 dice_loss 0.08617 +Epoch [2078/4000] Validation metric {'Val/mean dice_metric': 0.9711893200874329, 'Val/mean miou_metric': 0.9551572799682617, 'Val/mean f1': 0.9724733233451843, 'Val/mean precision': 0.9721135497093201, 'Val/mean recall': 0.9728332757949829, 'Val/mean hd95_metric': 5.600585460662842} +Cheakpoint... +Epoch [2078/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711893200874329, 'Val/mean miou_metric': 0.9551572799682617, 'Val/mean f1': 0.9724733233451843, 'Val/mean precision': 0.9721135497093201, 'Val/mean recall': 0.9728332757949829, 'Val/mean hd95_metric': 5.600585460662842} +Epoch [2079/4000] Training [1/16] Loss: 0.00554 +Epoch [2079/4000] Training [2/16] Loss: 0.00596 +Epoch [2079/4000] Training [3/16] Loss: 0.00607 +Epoch [2079/4000] Training [4/16] Loss: 0.00493 +Epoch [2079/4000] Training [5/16] Loss: 0.00459 +Epoch [2079/4000] Training [6/16] Loss: 0.00797 +Epoch [2079/4000] Training [7/16] Loss: 0.00704 +Epoch [2079/4000] Training [8/16] Loss: 0.00480 +Epoch [2079/4000] Training [9/16] Loss: 0.00633 +Epoch [2079/4000] Training [10/16] Loss: 0.00697 +Epoch [2079/4000] Training [11/16] Loss: 0.00624 +Epoch [2079/4000] Training [12/16] Loss: 0.00641 +Epoch [2079/4000] Training [13/16] Loss: 0.00449 +Epoch [2079/4000] Training [14/16] Loss: 0.00469 +Epoch [2079/4000] Training [15/16] Loss: 0.00584 +Epoch [2079/4000] Training [16/16] Loss: 0.00600 +Epoch [2079/4000] Training metric {'Train/mean dice_metric': 0.9962155818939209, 'Train/mean miou_metric': 0.9922022819519043, 'Train/mean f1': 0.9919713139533997, 'Train/mean precision': 0.987547755241394, 'Train/mean recall': 0.99643474817276, 'Train/mean hd95_metric': 1.000612735748291} +Epoch [2079/4000] Validation [1/4] Loss: 0.27951 focal_loss 0.21868 dice_loss 0.06082 +Epoch [2079/4000] Validation [2/4] Loss: 0.40904 focal_loss 0.26946 dice_loss 0.13957 +Epoch [2079/4000] Validation [3/4] Loss: 0.39036 focal_loss 0.29136 dice_loss 0.09900 +Epoch [2079/4000] Validation [4/4] Loss: 0.21276 focal_loss 0.12743 dice_loss 0.08533 +Epoch [2079/4000] Validation metric {'Val/mean dice_metric': 0.9717670679092407, 'Val/mean miou_metric': 0.9557361602783203, 'Val/mean f1': 0.9741352796554565, 'Val/mean precision': 0.9724843502044678, 'Val/mean recall': 0.9757917523384094, 'Val/mean hd95_metric': 5.951417922973633} +Cheakpoint... +Epoch [2079/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717670679092407, 'Val/mean miou_metric': 0.9557361602783203, 'Val/mean f1': 0.9741352796554565, 'Val/mean precision': 0.9724843502044678, 'Val/mean recall': 0.9757917523384094, 'Val/mean hd95_metric': 5.951417922973633} +Epoch [2080/4000] Training [1/16] Loss: 0.00631 +Epoch [2080/4000] Training [2/16] Loss: 0.00686 +Epoch [2080/4000] Training [3/16] Loss: 0.00568 +Epoch [2080/4000] Training [4/16] Loss: 0.00526 +Epoch [2080/4000] Training [5/16] Loss: 0.00510 +Epoch [2080/4000] Training [6/16] Loss: 0.00600 +Epoch [2080/4000] Training [7/16] Loss: 0.00594 +Epoch [2080/4000] Training [8/16] Loss: 0.00797 +Epoch [2080/4000] Training [9/16] Loss: 0.01012 +Epoch [2080/4000] Training [10/16] Loss: 0.00563 +Epoch [2080/4000] Training [11/16] Loss: 0.00549 +Epoch [2080/4000] Training [12/16] Loss: 0.00644 +Epoch [2080/4000] Training [13/16] Loss: 0.00494 +Epoch [2080/4000] Training [14/16] Loss: 0.00597 +Epoch [2080/4000] Training [15/16] Loss: 0.00489 +Epoch [2080/4000] Training [16/16] Loss: 0.00532 +Epoch [2080/4000] Training metric {'Train/mean dice_metric': 0.995818018913269, 'Train/mean miou_metric': 0.9914019107818604, 'Train/mean f1': 0.9911016225814819, 'Train/mean precision': 0.9860607981681824, 'Train/mean recall': 0.9961941838264465, 'Train/mean hd95_metric': 1.1351546049118042} +Epoch [2080/4000] Validation [1/4] Loss: 0.25906 focal_loss 0.19771 dice_loss 0.06135 +Epoch [2080/4000] Validation [2/4] Loss: 0.37333 focal_loss 0.23991 dice_loss 0.13342 +Epoch [2080/4000] Validation [3/4] Loss: 0.23515 focal_loss 0.14753 dice_loss 0.08762 +Epoch [2080/4000] Validation [4/4] Loss: 0.28107 focal_loss 0.17398 dice_loss 0.10709 +Epoch [2080/4000] Validation metric {'Val/mean dice_metric': 0.9726266860961914, 'Val/mean miou_metric': 0.9558790326118469, 'Val/mean f1': 0.9742922782897949, 'Val/mean precision': 0.9721437692642212, 'Val/mean recall': 0.9764501452445984, 'Val/mean hd95_metric': 6.044914245605469} +Cheakpoint... +Epoch [2080/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726266860961914, 'Val/mean miou_metric': 0.9558790326118469, 'Val/mean f1': 0.9742922782897949, 'Val/mean precision': 0.9721437692642212, 'Val/mean recall': 0.9764501452445984, 'Val/mean hd95_metric': 6.044914245605469} +Epoch [2081/4000] Training [1/16] Loss: 0.00538 +Epoch [2081/4000] Training [2/16] Loss: 0.00513 +Epoch [2081/4000] Training [3/16] Loss: 0.00577 +Epoch [2081/4000] Training [4/16] Loss: 0.00473 +Epoch [2081/4000] Training [5/16] Loss: 0.00510 +Epoch [2081/4000] Training [6/16] Loss: 0.00778 +Epoch [2081/4000] Training [7/16] Loss: 0.00537 +Epoch [2081/4000] Training [8/16] Loss: 0.00504 +Epoch [2081/4000] Training [9/16] Loss: 0.00619 +Epoch [2081/4000] Training [10/16] Loss: 0.00446 +Epoch [2081/4000] Training [11/16] Loss: 0.00522 +Epoch [2081/4000] Training [12/16] Loss: 0.00478 +Epoch [2081/4000] Training [13/16] Loss: 0.00805 +Epoch [2081/4000] Training [14/16] Loss: 0.00604 +Epoch [2081/4000] Training [15/16] Loss: 0.00613 +Epoch [2081/4000] Training [16/16] Loss: 0.00515 +Epoch [2081/4000] Training metric {'Train/mean dice_metric': 0.996303915977478, 'Train/mean miou_metric': 0.9923684597015381, 'Train/mean f1': 0.9920250773429871, 'Train/mean precision': 0.9875050783157349, 'Train/mean recall': 0.9965866804122925, 'Train/mean hd95_metric': 0.999552845954895} +Epoch [2081/4000] Validation [1/4] Loss: 0.28637 focal_loss 0.21417 dice_loss 0.07220 +Epoch [2081/4000] Validation [2/4] Loss: 0.29550 focal_loss 0.18281 dice_loss 0.11269 +Epoch [2081/4000] Validation [3/4] Loss: 0.19940 focal_loss 0.14001 dice_loss 0.05939 +Epoch [2081/4000] Validation [4/4] Loss: 0.37907 focal_loss 0.25209 dice_loss 0.12698 +Epoch [2081/4000] Validation metric {'Val/mean dice_metric': 0.9712194204330444, 'Val/mean miou_metric': 0.9550344347953796, 'Val/mean f1': 0.9741811156272888, 'Val/mean precision': 0.9735060930252075, 'Val/mean recall': 0.9748570322990417, 'Val/mean hd95_metric': 5.494441986083984} +Cheakpoint... +Epoch [2081/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712194204330444, 'Val/mean miou_metric': 0.9550344347953796, 'Val/mean f1': 0.9741811156272888, 'Val/mean precision': 0.9735060930252075, 'Val/mean recall': 0.9748570322990417, 'Val/mean hd95_metric': 5.494441986083984} +Epoch [2082/4000] Training [1/16] Loss: 0.00606 +Epoch [2082/4000] Training [2/16] Loss: 0.00878 +Epoch [2082/4000] Training [3/16] Loss: 0.00591 +Epoch [2082/4000] Training [4/16] Loss: 0.00576 +Epoch [2082/4000] Training [5/16] Loss: 0.00661 +Epoch [2082/4000] Training [6/16] Loss: 0.00763 +Epoch [2082/4000] Training [7/16] Loss: 0.00513 +Epoch [2082/4000] Training [8/16] Loss: 0.00410 +Epoch [2082/4000] Training [9/16] Loss: 0.00741 +Epoch [2082/4000] Training [10/16] Loss: 0.00662 +Epoch [2082/4000] Training [11/16] Loss: 0.00544 +Epoch [2082/4000] Training [12/16] Loss: 0.00829 +Epoch [2082/4000] Training [13/16] Loss: 0.00670 +Epoch [2082/4000] Training [14/16] Loss: 0.00700 +Epoch [2082/4000] Training [15/16] Loss: 0.00483 +Epoch [2082/4000] Training [16/16] Loss: 0.00425 +Epoch [2082/4000] Training metric {'Train/mean dice_metric': 0.9960740208625793, 'Train/mean miou_metric': 0.9919217228889465, 'Train/mean f1': 0.9918117523193359, 'Train/mean precision': 0.9873620271682739, 'Train/mean recall': 0.9963017106056213, 'Train/mean hd95_metric': 1.033968210220337} +Epoch [2082/4000] Validation [1/4] Loss: 0.28434 focal_loss 0.21958 dice_loss 0.06476 +Epoch [2082/4000] Validation [2/4] Loss: 0.38253 focal_loss 0.24679 dice_loss 0.13574 +Epoch [2082/4000] Validation [3/4] Loss: 0.43569 focal_loss 0.33251 dice_loss 0.10318 +Epoch [2082/4000] Validation [4/4] Loss: 0.26773 focal_loss 0.15948 dice_loss 0.10825 +Epoch [2082/4000] Validation metric {'Val/mean dice_metric': 0.9706512689590454, 'Val/mean miou_metric': 0.9542679786682129, 'Val/mean f1': 0.9737511277198792, 'Val/mean precision': 0.9719967842102051, 'Val/mean recall': 0.975511908531189, 'Val/mean hd95_metric': 6.027224063873291} +Cheakpoint... +Epoch [2082/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706512689590454, 'Val/mean miou_metric': 0.9542679786682129, 'Val/mean f1': 0.9737511277198792, 'Val/mean precision': 0.9719967842102051, 'Val/mean recall': 0.975511908531189, 'Val/mean hd95_metric': 6.027224063873291} +Epoch [2083/4000] Training [1/16] Loss: 0.00438 +Epoch [2083/4000] Training [2/16] Loss: 0.00544 +Epoch [2083/4000] Training [3/16] Loss: 0.00421 +Epoch [2083/4000] Training [4/16] Loss: 0.00434 +Epoch [2083/4000] Training [5/16] Loss: 0.00465 +Epoch [2083/4000] Training [6/16] Loss: 0.00592 +Epoch [2083/4000] Training [7/16] Loss: 0.00715 +Epoch [2083/4000] Training [8/16] Loss: 0.00461 +Epoch [2083/4000] Training [9/16] Loss: 0.00669 +Epoch [2083/4000] Training [10/16] Loss: 0.00599 +Epoch [2083/4000] Training [11/16] Loss: 0.01130 +Epoch [2083/4000] Training [12/16] Loss: 0.00581 +Epoch [2083/4000] Training [13/16] Loss: 0.00494 +Epoch [2083/4000] Training [14/16] Loss: 0.00629 +Epoch [2083/4000] Training [15/16] Loss: 0.00696 +Epoch [2083/4000] Training [16/16] Loss: 0.00787 +Epoch [2083/4000] Training metric {'Train/mean dice_metric': 0.9959604144096375, 'Train/mean miou_metric': 0.9916884303092957, 'Train/mean f1': 0.9915241003036499, 'Train/mean precision': 0.986844003200531, 'Train/mean recall': 0.9962488412857056, 'Train/mean hd95_metric': 1.0775868892669678} +Epoch [2083/4000] Validation [1/4] Loss: 0.33609 focal_loss 0.26696 dice_loss 0.06913 +Epoch [2083/4000] Validation [2/4] Loss: 0.43903 focal_loss 0.28925 dice_loss 0.14978 +Epoch [2083/4000] Validation [3/4] Loss: 0.20380 focal_loss 0.14125 dice_loss 0.06254 +Epoch [2083/4000] Validation [4/4] Loss: 0.22975 focal_loss 0.14418 dice_loss 0.08556 +Epoch [2083/4000] Validation metric {'Val/mean dice_metric': 0.972647488117218, 'Val/mean miou_metric': 0.9563765525817871, 'Val/mean f1': 0.9742359519004822, 'Val/mean precision': 0.9710770845413208, 'Val/mean recall': 0.9774154424667358, 'Val/mean hd95_metric': 6.077356338500977} +Cheakpoint... +Epoch [2083/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972647488117218, 'Val/mean miou_metric': 0.9563765525817871, 'Val/mean f1': 0.9742359519004822, 'Val/mean precision': 0.9710770845413208, 'Val/mean recall': 0.9774154424667358, 'Val/mean hd95_metric': 6.077356338500977} +Epoch [2084/4000] Training [1/16] Loss: 0.00463 +Epoch [2084/4000] Training [2/16] Loss: 0.00489 +Epoch [2084/4000] Training [3/16] Loss: 0.00650 +Epoch [2084/4000] Training [4/16] Loss: 0.00479 +Epoch [2084/4000] Training [5/16] Loss: 0.00822 +Epoch [2084/4000] Training [6/16] Loss: 0.00475 +Epoch [2084/4000] Training [7/16] Loss: 0.00543 +Epoch [2084/4000] Training [8/16] Loss: 0.00585 +Epoch [2084/4000] Training [9/16] Loss: 0.00712 +Epoch [2084/4000] Training [10/16] Loss: 0.00508 +Epoch [2084/4000] Training [11/16] Loss: 0.00576 +Epoch [2084/4000] Training [12/16] Loss: 0.00612 +Epoch [2084/4000] Training [13/16] Loss: 0.00538 +Epoch [2084/4000] Training [14/16] Loss: 0.00538 +Epoch [2084/4000] Training [15/16] Loss: 0.00503 +Epoch [2084/4000] Training [16/16] Loss: 0.00805 +Epoch [2084/4000] Training metric {'Train/mean dice_metric': 0.9961206912994385, 'Train/mean miou_metric': 0.9920212030410767, 'Train/mean f1': 0.9917120933532715, 'Train/mean precision': 0.9872145056724548, 'Train/mean recall': 0.9962508678436279, 'Train/mean hd95_metric': 1.0336661338806152} +Epoch [2084/4000] Validation [1/4] Loss: 0.27564 focal_loss 0.21249 dice_loss 0.06314 +Epoch [2084/4000] Validation [2/4] Loss: 0.66980 focal_loss 0.45070 dice_loss 0.21910 +Epoch [2084/4000] Validation [3/4] Loss: 0.43428 focal_loss 0.33450 dice_loss 0.09979 +Epoch [2084/4000] Validation [4/4] Loss: 0.25800 focal_loss 0.15696 dice_loss 0.10103 +Epoch [2084/4000] Validation metric {'Val/mean dice_metric': 0.9702825546264648, 'Val/mean miou_metric': 0.9541701078414917, 'Val/mean f1': 0.9724097847938538, 'Val/mean precision': 0.9662725329399109, 'Val/mean recall': 0.9786255359649658, 'Val/mean hd95_metric': 6.614904880523682} +Cheakpoint... +Epoch [2084/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702825546264648, 'Val/mean miou_metric': 0.9541701078414917, 'Val/mean f1': 0.9724097847938538, 'Val/mean precision': 0.9662725329399109, 'Val/mean recall': 0.9786255359649658, 'Val/mean hd95_metric': 6.614904880523682} +Epoch [2085/4000] Training [1/16] Loss: 0.00602 +Epoch [2085/4000] Training [2/16] Loss: 0.00700 +Epoch [2085/4000] Training [3/16] Loss: 0.00504 +Epoch [2085/4000] Training [4/16] Loss: 0.00615 +Epoch [2085/4000] Training [5/16] Loss: 0.00578 +Epoch [2085/4000] Training [6/16] Loss: 0.00514 +Epoch [2085/4000] Training [7/16] Loss: 0.00644 +Epoch [2085/4000] Training [8/16] Loss: 0.00670 +Epoch [2085/4000] Training [9/16] Loss: 0.00644 +Epoch [2085/4000] Training [10/16] Loss: 0.00600 +Epoch [2085/4000] Training [11/16] Loss: 0.00491 +Epoch [2085/4000] Training [12/16] Loss: 0.00615 +Epoch [2085/4000] Training [13/16] Loss: 0.00518 +Epoch [2085/4000] Training [14/16] Loss: 0.00877 +Epoch [2085/4000] Training [15/16] Loss: 0.00423 +Epoch [2085/4000] Training [16/16] Loss: 0.00553 +Epoch [2085/4000] Training metric {'Train/mean dice_metric': 0.995661735534668, 'Train/mean miou_metric': 0.9911943674087524, 'Train/mean f1': 0.9915809631347656, 'Train/mean precision': 0.9868137836456299, 'Train/mean recall': 0.9963943958282471, 'Train/mean hd95_metric': 1.3560922145843506} +Epoch [2085/4000] Validation [1/4] Loss: 0.26508 focal_loss 0.20565 dice_loss 0.05944 +Epoch [2085/4000] Validation [2/4] Loss: 0.26422 focal_loss 0.15811 dice_loss 0.10612 +Epoch [2085/4000] Validation [3/4] Loss: 0.38668 focal_loss 0.28687 dice_loss 0.09981 +Epoch [2085/4000] Validation [4/4] Loss: 0.27264 focal_loss 0.17336 dice_loss 0.09928 +Epoch [2085/4000] Validation metric {'Val/mean dice_metric': 0.9708911776542664, 'Val/mean miou_metric': 0.9540802240371704, 'Val/mean f1': 0.9731330871582031, 'Val/mean precision': 0.9674218893051147, 'Val/mean recall': 0.9789121150970459, 'Val/mean hd95_metric': 6.580447196960449} +Cheakpoint... +Epoch [2085/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708911776542664, 'Val/mean miou_metric': 0.9540802240371704, 'Val/mean f1': 0.9731330871582031, 'Val/mean precision': 0.9674218893051147, 'Val/mean recall': 0.9789121150970459, 'Val/mean hd95_metric': 6.580447196960449} +Epoch [2086/4000] Training [1/16] Loss: 0.00559 +Epoch [2086/4000] Training [2/16] Loss: 0.00576 +Epoch [2086/4000] Training [3/16] Loss: 0.00673 +Epoch [2086/4000] Training [4/16] Loss: 0.00612 +Epoch [2086/4000] Training [5/16] Loss: 0.00605 +Epoch [2086/4000] Training [6/16] Loss: 0.00561 +Epoch [2086/4000] Training [7/16] Loss: 0.00570 +Epoch [2086/4000] Training [8/16] Loss: 0.00646 +Epoch [2086/4000] Training [9/16] Loss: 0.00858 +Epoch [2086/4000] Training [10/16] Loss: 0.00797 +Epoch [2086/4000] Training [11/16] Loss: 0.00446 +Epoch [2086/4000] Training [12/16] Loss: 0.00888 +Epoch [2086/4000] Training [13/16] Loss: 0.00594 +Epoch [2086/4000] Training [14/16] Loss: 0.07009 +Epoch [2086/4000] Training [15/16] Loss: 0.00672 +Epoch [2086/4000] Training [16/16] Loss: 0.00589 +Epoch [2086/4000] Training metric {'Train/mean dice_metric': 0.9956084489822388, 'Train/mean miou_metric': 0.9911133050918579, 'Train/mean f1': 0.9913612008094788, 'Train/mean precision': 0.9870417714118958, 'Train/mean recall': 0.9957185387611389, 'Train/mean hd95_metric': 1.1153430938720703} +Epoch [2086/4000] Validation [1/4] Loss: 0.23713 focal_loss 0.17793 dice_loss 0.05919 +Epoch [2086/4000] Validation [2/4] Loss: 0.28791 focal_loss 0.17629 dice_loss 0.11162 +Epoch [2086/4000] Validation [3/4] Loss: 0.38964 focal_loss 0.29112 dice_loss 0.09852 +Epoch [2086/4000] Validation [4/4] Loss: 0.57334 focal_loss 0.43833 dice_loss 0.13501 +Epoch [2086/4000] Validation metric {'Val/mean dice_metric': 0.9711686968803406, 'Val/mean miou_metric': 0.9543243646621704, 'Val/mean f1': 0.9732590317726135, 'Val/mean precision': 0.9718149900436401, 'Val/mean recall': 0.9747071862220764, 'Val/mean hd95_metric': 6.232535362243652} +Cheakpoint... +Epoch [2086/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711686968803406, 'Val/mean miou_metric': 0.9543243646621704, 'Val/mean f1': 0.9732590317726135, 'Val/mean precision': 0.9718149900436401, 'Val/mean recall': 0.9747071862220764, 'Val/mean hd95_metric': 6.232535362243652} +Epoch [2087/4000] Training [1/16] Loss: 0.00495 +Epoch [2087/4000] Training [2/16] Loss: 0.00667 +Epoch [2087/4000] Training [3/16] Loss: 0.00474 +Epoch [2087/4000] Training [4/16] Loss: 0.00672 +Epoch [2087/4000] Training [5/16] Loss: 0.00453 +Epoch [2087/4000] Training [6/16] Loss: 0.00497 +Epoch [2087/4000] Training [7/16] Loss: 0.00585 +Epoch [2087/4000] Training [8/16] Loss: 0.00718 +Epoch [2087/4000] Training [9/16] Loss: 0.00591 +Epoch [2087/4000] Training [10/16] Loss: 0.00817 +Epoch [2087/4000] Training [11/16] Loss: 0.00434 +Epoch [2087/4000] Training [12/16] Loss: 0.00491 +Epoch [2087/4000] Training [13/16] Loss: 0.00573 +Epoch [2087/4000] Training [14/16] Loss: 0.00686 +Epoch [2087/4000] Training [15/16] Loss: 0.00740 +Epoch [2087/4000] Training [16/16] Loss: 0.00499 +Epoch [2087/4000] Training metric {'Train/mean dice_metric': 0.9961171746253967, 'Train/mean miou_metric': 0.9919918775558472, 'Train/mean f1': 0.991725504398346, 'Train/mean precision': 0.9871074557304382, 'Train/mean recall': 0.9963870644569397, 'Train/mean hd95_metric': 1.1046404838562012} +Epoch [2087/4000] Validation [1/4] Loss: 0.22161 focal_loss 0.16315 dice_loss 0.05845 +Epoch [2087/4000] Validation [2/4] Loss: 0.24688 focal_loss 0.14690 dice_loss 0.09998 +Epoch [2087/4000] Validation [3/4] Loss: 0.46733 focal_loss 0.34674 dice_loss 0.12059 +Epoch [2087/4000] Validation [4/4] Loss: 0.31642 focal_loss 0.19435 dice_loss 0.12206 +Epoch [2087/4000] Validation metric {'Val/mean dice_metric': 0.9728225469589233, 'Val/mean miou_metric': 0.9560213088989258, 'Val/mean f1': 0.9735024571418762, 'Val/mean precision': 0.9660980105400085, 'Val/mean recall': 0.9810212254524231, 'Val/mean hd95_metric': 7.0104804039001465} +Cheakpoint... +Epoch [2087/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728225469589233, 'Val/mean miou_metric': 0.9560213088989258, 'Val/mean f1': 0.9735024571418762, 'Val/mean precision': 0.9660980105400085, 'Val/mean recall': 0.9810212254524231, 'Val/mean hd95_metric': 7.0104804039001465} +Epoch [2088/4000] Training [1/16] Loss: 0.00401 +Epoch [2088/4000] Training [2/16] Loss: 0.00520 +Epoch [2088/4000] Training [3/16] Loss: 0.00493 +Epoch [2088/4000] Training [4/16] Loss: 0.00593 +Epoch [2088/4000] Training [5/16] Loss: 0.00410 +Epoch [2088/4000] Training [6/16] Loss: 0.00922 +Epoch [2088/4000] Training [7/16] Loss: 0.00596 +Epoch [2088/4000] Training [8/16] Loss: 0.00635 +Epoch [2088/4000] Training [9/16] Loss: 0.00437 +Epoch [2088/4000] Training [10/16] Loss: 0.00444 +Epoch [2088/4000] Training [11/16] Loss: 0.00451 +Epoch [2088/4000] Training [12/16] Loss: 0.00530 +Epoch [2088/4000] Training [13/16] Loss: 0.00818 +Epoch [2088/4000] Training [14/16] Loss: 0.00708 +Epoch [2088/4000] Training [15/16] Loss: 0.00590 +Epoch [2088/4000] Training [16/16] Loss: 0.00515 +Epoch [2088/4000] Training metric {'Train/mean dice_metric': 0.9963239431381226, 'Train/mean miou_metric': 0.9923972487449646, 'Train/mean f1': 0.9917922616004944, 'Train/mean precision': 0.9872171878814697, 'Train/mean recall': 0.9964098930358887, 'Train/mean hd95_metric': 1.393218994140625} +Epoch [2088/4000] Validation [1/4] Loss: 0.30990 focal_loss 0.24231 dice_loss 0.06759 +Epoch [2088/4000] Validation [2/4] Loss: 0.62502 focal_loss 0.41819 dice_loss 0.20683 +Epoch [2088/4000] Validation [3/4] Loss: 0.34091 focal_loss 0.24789 dice_loss 0.09302 +Epoch [2088/4000] Validation [4/4] Loss: 0.21806 focal_loss 0.12301 dice_loss 0.09505 +Epoch [2088/4000] Validation metric {'Val/mean dice_metric': 0.9721143841743469, 'Val/mean miou_metric': 0.9560537338256836, 'Val/mean f1': 0.9725911617279053, 'Val/mean precision': 0.9673150777816772, 'Val/mean recall': 0.977925181388855, 'Val/mean hd95_metric': 6.644135475158691} +Cheakpoint... +Epoch [2088/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721143841743469, 'Val/mean miou_metric': 0.9560537338256836, 'Val/mean f1': 0.9725911617279053, 'Val/mean precision': 0.9673150777816772, 'Val/mean recall': 0.977925181388855, 'Val/mean hd95_metric': 6.644135475158691} +Epoch [2089/4000] Training [1/16] Loss: 0.00602 +Epoch [2089/4000] Training [2/16] Loss: 0.00515 +Epoch [2089/4000] Training [3/16] Loss: 0.00490 +Epoch [2089/4000] Training [4/16] Loss: 0.00453 +Epoch [2089/4000] Training [5/16] Loss: 0.00439 +Epoch [2089/4000] Training [6/16] Loss: 0.00578 +Epoch [2089/4000] Training [7/16] Loss: 0.00527 +Epoch [2089/4000] Training [8/16] Loss: 0.00506 +Epoch [2089/4000] Training [9/16] Loss: 0.00510 +Epoch [2089/4000] Training [10/16] Loss: 0.00624 +Epoch [2089/4000] Training [11/16] Loss: 0.00502 +Epoch [2089/4000] Training [12/16] Loss: 0.00644 +Epoch [2089/4000] Training [13/16] Loss: 0.00574 +Epoch [2089/4000] Training [14/16] Loss: 0.00959 +Epoch [2089/4000] Training [15/16] Loss: 0.00418 +Epoch [2089/4000] Training [16/16] Loss: 0.00779 +Epoch [2089/4000] Training metric {'Train/mean dice_metric': 0.9961122274398804, 'Train/mean miou_metric': 0.9920042753219604, 'Train/mean f1': 0.9918486475944519, 'Train/mean precision': 0.9873947501182556, 'Train/mean recall': 0.9963428974151611, 'Train/mean hd95_metric': 1.0898864269256592} +Epoch [2089/4000] Validation [1/4] Loss: 0.29879 focal_loss 0.22840 dice_loss 0.07039 +Epoch [2089/4000] Validation [2/4] Loss: 0.75193 focal_loss 0.55282 dice_loss 0.19912 +Epoch [2089/4000] Validation [3/4] Loss: 0.22053 focal_loss 0.15215 dice_loss 0.06838 +Epoch [2089/4000] Validation [4/4] Loss: 0.30342 focal_loss 0.19504 dice_loss 0.10838 +Epoch [2089/4000] Validation metric {'Val/mean dice_metric': 0.9720436334609985, 'Val/mean miou_metric': 0.9558275938034058, 'Val/mean f1': 0.974972128868103, 'Val/mean precision': 0.9732624888420105, 'Val/mean recall': 0.9766876697540283, 'Val/mean hd95_metric': 5.746508598327637} +Cheakpoint... +Epoch [2089/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720436334609985, 'Val/mean miou_metric': 0.9558275938034058, 'Val/mean f1': 0.974972128868103, 'Val/mean precision': 0.9732624888420105, 'Val/mean recall': 0.9766876697540283, 'Val/mean hd95_metric': 5.746508598327637} +Epoch [2090/4000] Training [1/16] Loss: 0.00425 +Epoch [2090/4000] Training [2/16] Loss: 0.00576 +Epoch [2090/4000] Training [3/16] Loss: 0.00435 +Epoch [2090/4000] Training [4/16] Loss: 0.00676 +Epoch [2090/4000] Training [5/16] Loss: 0.00516 +Epoch [2090/4000] Training [6/16] Loss: 0.00514 +Epoch [2090/4000] Training [7/16] Loss: 0.00518 +Epoch [2090/4000] Training [8/16] Loss: 0.00487 +Epoch [2090/4000] Training [9/16] Loss: 0.00523 +Epoch [2090/4000] Training [10/16] Loss: 0.00446 +Epoch [2090/4000] Training [11/16] Loss: 0.00402 +Epoch [2090/4000] Training [12/16] Loss: 0.00629 +Epoch [2090/4000] Training [13/16] Loss: 0.00660 +Epoch [2090/4000] Training [14/16] Loss: 0.00625 +Epoch [2090/4000] Training [15/16] Loss: 0.00443 +Epoch [2090/4000] Training [16/16] Loss: 0.00565 +Epoch [2090/4000] Training metric {'Train/mean dice_metric': 0.9965795278549194, 'Train/mean miou_metric': 0.9929036498069763, 'Train/mean f1': 0.9918838143348694, 'Train/mean precision': 0.9871757626533508, 'Train/mean recall': 0.9966369867324829, 'Train/mean hd95_metric': 0.9964427351951599} +Epoch [2090/4000] Validation [1/4] Loss: 0.29534 focal_loss 0.23028 dice_loss 0.06506 +Epoch [2090/4000] Validation [2/4] Loss: 0.68860 focal_loss 0.51654 dice_loss 0.17205 +Epoch [2090/4000] Validation [3/4] Loss: 0.37017 focal_loss 0.27169 dice_loss 0.09848 +Epoch [2090/4000] Validation [4/4] Loss: 0.35156 focal_loss 0.24248 dice_loss 0.10908 +Epoch [2090/4000] Validation metric {'Val/mean dice_metric': 0.9726289510726929, 'Val/mean miou_metric': 0.9570060968399048, 'Val/mean f1': 0.9750645756721497, 'Val/mean precision': 0.9725221395492554, 'Val/mean recall': 0.9776202440261841, 'Val/mean hd95_metric': 5.634466648101807} +Cheakpoint... +Epoch [2090/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726289510726929, 'Val/mean miou_metric': 0.9570060968399048, 'Val/mean f1': 0.9750645756721497, 'Val/mean precision': 0.9725221395492554, 'Val/mean recall': 0.9776202440261841, 'Val/mean hd95_metric': 5.634466648101807} +Epoch [2091/4000] Training [1/16] Loss: 0.00499 +Epoch [2091/4000] Training [2/16] Loss: 0.00557 +Epoch [2091/4000] Training [3/16] Loss: 0.00615 +Epoch [2091/4000] Training [4/16] Loss: 0.00470 +Epoch [2091/4000] Training [5/16] Loss: 0.00600 +Epoch [2091/4000] Training [6/16] Loss: 0.00469 +Epoch [2091/4000] Training [7/16] Loss: 0.00494 +Epoch [2091/4000] Training [8/16] Loss: 0.00557 +Epoch [2091/4000] Training [9/16] Loss: 0.00488 +Epoch [2091/4000] Training [10/16] Loss: 0.00605 +Epoch [2091/4000] Training [11/16] Loss: 0.00465 +Epoch [2091/4000] Training [12/16] Loss: 0.00420 +Epoch [2091/4000] Training [13/16] Loss: 0.00458 +Epoch [2091/4000] Training [14/16] Loss: 0.00444 +Epoch [2091/4000] Training [15/16] Loss: 0.00449 +Epoch [2091/4000] Training [16/16] Loss: 0.00525 +Epoch [2091/4000] Training metric {'Train/mean dice_metric': 0.9967404007911682, 'Train/mean miou_metric': 0.993234395980835, 'Train/mean f1': 0.9921529293060303, 'Train/mean precision': 0.9876028299331665, 'Train/mean recall': 0.9967451691627502, 'Train/mean hd95_metric': 0.9807121157646179} +Epoch [2091/4000] Validation [1/4] Loss: 0.32077 focal_loss 0.23809 dice_loss 0.08268 +Epoch [2091/4000] Validation [2/4] Loss: 0.75086 focal_loss 0.56648 dice_loss 0.18438 +Epoch [2091/4000] Validation [3/4] Loss: 0.38681 focal_loss 0.28728 dice_loss 0.09953 +Epoch [2091/4000] Validation [4/4] Loss: 0.23913 focal_loss 0.15432 dice_loss 0.08482 +Epoch [2091/4000] Validation metric {'Val/mean dice_metric': 0.9734107851982117, 'Val/mean miou_metric': 0.9578498601913452, 'Val/mean f1': 0.9747276902198792, 'Val/mean precision': 0.9720383286476135, 'Val/mean recall': 0.9774319529533386, 'Val/mean hd95_metric': 5.763857364654541} +Cheakpoint... +Epoch [2091/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734107851982117, 'Val/mean miou_metric': 0.9578498601913452, 'Val/mean f1': 0.9747276902198792, 'Val/mean precision': 0.9720383286476135, 'Val/mean recall': 0.9774319529533386, 'Val/mean hd95_metric': 5.763857364654541} +Epoch [2092/4000] Training [1/16] Loss: 0.00469 +Epoch [2092/4000] Training [2/16] Loss: 0.00457 +Epoch [2092/4000] Training [3/16] Loss: 0.00601 +Epoch [2092/4000] Training [4/16] Loss: 0.00522 +Epoch [2092/4000] Training [5/16] Loss: 0.00474 +Epoch [2092/4000] Training [6/16] Loss: 0.00633 +Epoch [2092/4000] Training [7/16] Loss: 0.00453 +Epoch [2092/4000] Training [8/16] Loss: 0.00508 +Epoch [2092/4000] Training [9/16] Loss: 0.00486 +Epoch [2092/4000] Training [10/16] Loss: 0.00461 +Epoch [2092/4000] Training [11/16] Loss: 0.00599 +Epoch [2092/4000] Training [12/16] Loss: 0.00509 +Epoch [2092/4000] Training [13/16] Loss: 0.00648 +Epoch [2092/4000] Training [14/16] Loss: 0.00616 +Epoch [2092/4000] Training [15/16] Loss: 0.00543 +Epoch [2092/4000] Training [16/16] Loss: 0.00486 +Epoch [2092/4000] Training metric {'Train/mean dice_metric': 0.9965652823448181, 'Train/mean miou_metric': 0.9928855895996094, 'Train/mean f1': 0.9921500086784363, 'Train/mean precision': 0.9876493215560913, 'Train/mean recall': 0.9966917634010315, 'Train/mean hd95_metric': 0.9929265975952148} +Epoch [2092/4000] Validation [1/4] Loss: 0.32479 focal_loss 0.24722 dice_loss 0.07757 +Epoch [2092/4000] Validation [2/4] Loss: 1.03421 focal_loss 0.76825 dice_loss 0.26596 +Epoch [2092/4000] Validation [3/4] Loss: 0.38865 focal_loss 0.29075 dice_loss 0.09790 +Epoch [2092/4000] Validation [4/4] Loss: 0.36681 focal_loss 0.25279 dice_loss 0.11402 +Epoch [2092/4000] Validation metric {'Val/mean dice_metric': 0.9719134569168091, 'Val/mean miou_metric': 0.9559532999992371, 'Val/mean f1': 0.9745513200759888, 'Val/mean precision': 0.9716832041740417, 'Val/mean recall': 0.9774364233016968, 'Val/mean hd95_metric': 5.4939374923706055} +Cheakpoint... +Epoch [2092/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719134569168091, 'Val/mean miou_metric': 0.9559532999992371, 'Val/mean f1': 0.9745513200759888, 'Val/mean precision': 0.9716832041740417, 'Val/mean recall': 0.9774364233016968, 'Val/mean hd95_metric': 5.4939374923706055} +Epoch [2093/4000] Training [1/16] Loss: 0.00511 +Epoch [2093/4000] Training [2/16] Loss: 0.00594 +Epoch [2093/4000] Training [3/16] Loss: 0.00449 +Epoch [2093/4000] Training [4/16] Loss: 0.00450 +Epoch [2093/4000] Training [5/16] Loss: 0.00492 +Epoch [2093/4000] Training [6/16] Loss: 0.00555 +Epoch [2093/4000] Training [7/16] Loss: 0.00488 +Epoch [2093/4000] Training [8/16] Loss: 0.00497 +Epoch [2093/4000] Training [9/16] Loss: 0.00540 +Epoch [2093/4000] Training [10/16] Loss: 0.00474 +Epoch [2093/4000] Training [11/16] Loss: 0.00535 +Epoch [2093/4000] Training [12/16] Loss: 0.00631 +Epoch [2093/4000] Training [13/16] Loss: 0.00685 +Epoch [2093/4000] Training [14/16] Loss: 0.00615 +Epoch [2093/4000] Training [15/16] Loss: 0.00591 +Epoch [2093/4000] Training [16/16] Loss: 0.00521 +Epoch [2093/4000] Training metric {'Train/mean dice_metric': 0.9961554408073425, 'Train/mean miou_metric': 0.9920843243598938, 'Train/mean f1': 0.9918341040611267, 'Train/mean precision': 0.9872579574584961, 'Train/mean recall': 0.9964528679847717, 'Train/mean hd95_metric': 1.0577136278152466} +Epoch [2093/4000] Validation [1/4] Loss: 0.30720 focal_loss 0.24383 dice_loss 0.06337 +Epoch [2093/4000] Validation [2/4] Loss: 0.20681 focal_loss 0.11862 dice_loss 0.08819 +Epoch [2093/4000] Validation [3/4] Loss: 0.43864 focal_loss 0.32639 dice_loss 0.11225 +Epoch [2093/4000] Validation [4/4] Loss: 0.35997 focal_loss 0.22462 dice_loss 0.13535 +Epoch [2093/4000] Validation metric {'Val/mean dice_metric': 0.972221851348877, 'Val/mean miou_metric': 0.9553769826889038, 'Val/mean f1': 0.9738562107086182, 'Val/mean precision': 0.966724693775177, 'Val/mean recall': 0.9810936450958252, 'Val/mean hd95_metric': 6.409040927886963} +Cheakpoint... +Epoch [2093/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972221851348877, 'Val/mean miou_metric': 0.9553769826889038, 'Val/mean f1': 0.9738562107086182, 'Val/mean precision': 0.966724693775177, 'Val/mean recall': 0.9810936450958252, 'Val/mean hd95_metric': 6.409040927886963} +Epoch [2094/4000] Training [1/16] Loss: 0.00526 +Epoch [2094/4000] Training [2/16] Loss: 0.00593 +Epoch [2094/4000] Training [3/16] Loss: 0.00882 +Epoch [2094/4000] Training [4/16] Loss: 0.00491 +Epoch [2094/4000] Training [5/16] Loss: 0.00590 +Epoch [2094/4000] Training [6/16] Loss: 0.00505 +Epoch [2094/4000] Training [7/16] Loss: 0.00607 +Epoch [2094/4000] Training [8/16] Loss: 0.00405 +Epoch [2094/4000] Training [9/16] Loss: 0.00497 +Epoch [2094/4000] Training [10/16] Loss: 0.00423 +Epoch [2094/4000] Training [11/16] Loss: 0.00530 +Epoch [2094/4000] Training [12/16] Loss: 0.00414 +Epoch [2094/4000] Training [13/16] Loss: 0.00424 +Epoch [2094/4000] Training [14/16] Loss: 0.00431 +Epoch [2094/4000] Training [15/16] Loss: 0.00457 +Epoch [2094/4000] Training [16/16] Loss: 0.01185 +Epoch [2094/4000] Training metric {'Train/mean dice_metric': 0.9962842464447021, 'Train/mean miou_metric': 0.9923382997512817, 'Train/mean f1': 0.9919029474258423, 'Train/mean precision': 0.9873944520950317, 'Train/mean recall': 0.996452808380127, 'Train/mean hd95_metric': 1.0148935317993164} +Epoch [2094/4000] Validation [1/4] Loss: 0.28467 focal_loss 0.22208 dice_loss 0.06259 +Epoch [2094/4000] Validation [2/4] Loss: 0.35649 focal_loss 0.23354 dice_loss 0.12294 +Epoch [2094/4000] Validation [3/4] Loss: 0.39286 focal_loss 0.30221 dice_loss 0.09065 +Epoch [2094/4000] Validation [4/4] Loss: 0.26143 focal_loss 0.15294 dice_loss 0.10849 +Epoch [2094/4000] Validation metric {'Val/mean dice_metric': 0.9729894399642944, 'Val/mean miou_metric': 0.9566397666931152, 'Val/mean f1': 0.9746352434158325, 'Val/mean precision': 0.96873939037323, 'Val/mean recall': 0.9806033372879028, 'Val/mean hd95_metric': 5.911304950714111} +Cheakpoint... +Epoch [2094/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729894399642944, 'Val/mean miou_metric': 0.9566397666931152, 'Val/mean f1': 0.9746352434158325, 'Val/mean precision': 0.96873939037323, 'Val/mean recall': 0.9806033372879028, 'Val/mean hd95_metric': 5.911304950714111} +Epoch [2095/4000] Training [1/16] Loss: 0.00359 +Epoch [2095/4000] Training [2/16] Loss: 0.00525 +Epoch [2095/4000] Training [3/16] Loss: 0.00744 +Epoch [2095/4000] Training [4/16] Loss: 0.00418 +Epoch [2095/4000] Training [5/16] Loss: 0.00462 +Epoch [2095/4000] Training [6/16] Loss: 0.00642 +Epoch [2095/4000] Training [7/16] Loss: 0.00513 +Epoch [2095/4000] Training [8/16] Loss: 0.00619 +Epoch [2095/4000] Training [9/16] Loss: 0.00608 +Epoch [2095/4000] Training [10/16] Loss: 0.00374 +Epoch [2095/4000] Training [11/16] Loss: 0.00562 +Epoch [2095/4000] Training [12/16] Loss: 0.01017 +Epoch [2095/4000] Training [13/16] Loss: 0.00747 +Epoch [2095/4000] Training [14/16] Loss: 0.00666 +Epoch [2095/4000] Training [15/16] Loss: 0.00539 +Epoch [2095/4000] Training [16/16] Loss: 0.00746 +Epoch [2095/4000] Training metric {'Train/mean dice_metric': 0.9964522123336792, 'Train/mean miou_metric': 0.9926708936691284, 'Train/mean f1': 0.9920987486839294, 'Train/mean precision': 0.9876306056976318, 'Train/mean recall': 0.9966074824333191, 'Train/mean hd95_metric': 1.0229557752609253} +Epoch [2095/4000] Validation [1/4] Loss: 0.28493 focal_loss 0.22068 dice_loss 0.06426 +Epoch [2095/4000] Validation [2/4] Loss: 0.22427 focal_loss 0.12827 dice_loss 0.09600 +Epoch [2095/4000] Validation [3/4] Loss: 0.36095 focal_loss 0.27007 dice_loss 0.09088 +Epoch [2095/4000] Validation [4/4] Loss: 0.33102 focal_loss 0.20588 dice_loss 0.12515 +Epoch [2095/4000] Validation metric {'Val/mean dice_metric': 0.9728351831436157, 'Val/mean miou_metric': 0.9566690325737, 'Val/mean f1': 0.975081205368042, 'Val/mean precision': 0.9716156125068665, 'Val/mean recall': 0.9785716533660889, 'Val/mean hd95_metric': 6.024798393249512} +Cheakpoint... +Epoch [2095/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728351831436157, 'Val/mean miou_metric': 0.9566690325737, 'Val/mean f1': 0.975081205368042, 'Val/mean precision': 0.9716156125068665, 'Val/mean recall': 0.9785716533660889, 'Val/mean hd95_metric': 6.024798393249512} +Epoch [2096/4000] Training [1/16] Loss: 0.00960 +Epoch [2096/4000] Training [2/16] Loss: 0.00580 +Epoch [2096/4000] Training [3/16] Loss: 0.00471 +Epoch [2096/4000] Training [4/16] Loss: 0.00523 +Epoch [2096/4000] Training [5/16] Loss: 0.00447 +Epoch [2096/4000] Training [6/16] Loss: 0.00557 +Epoch [2096/4000] Training [7/16] Loss: 0.00463 +Epoch [2096/4000] Training [8/16] Loss: 0.00511 +Epoch [2096/4000] Training [9/16] Loss: 0.00559 +Epoch [2096/4000] Training [10/16] Loss: 0.00468 +Epoch [2096/4000] Training [11/16] Loss: 0.00490 +Epoch [2096/4000] Training [12/16] Loss: 0.00512 +Epoch [2096/4000] Training [13/16] Loss: 0.00521 +Epoch [2096/4000] Training [14/16] Loss: 0.00646 +Epoch [2096/4000] Training [15/16] Loss: 0.00528 +Epoch [2096/4000] Training [16/16] Loss: 0.00580 +Epoch [2096/4000] Training metric {'Train/mean dice_metric': 0.9964403510093689, 'Train/mean miou_metric': 0.9926443099975586, 'Train/mean f1': 0.9919907450675964, 'Train/mean precision': 0.9874566793441772, 'Train/mean recall': 0.9965665936470032, 'Train/mean hd95_metric': 1.0004040002822876} +Epoch [2096/4000] Validation [1/4] Loss: 0.28191 focal_loss 0.22189 dice_loss 0.06002 +Epoch [2096/4000] Validation [2/4] Loss: 0.74186 focal_loss 0.54266 dice_loss 0.19920 +Epoch [2096/4000] Validation [3/4] Loss: 0.29163 focal_loss 0.19567 dice_loss 0.09596 +Epoch [2096/4000] Validation [4/4] Loss: 0.47191 focal_loss 0.31393 dice_loss 0.15798 +Epoch [2096/4000] Validation metric {'Val/mean dice_metric': 0.9735492467880249, 'Val/mean miou_metric': 0.9572084546089172, 'Val/mean f1': 0.974115788936615, 'Val/mean precision': 0.9703406095504761, 'Val/mean recall': 0.977920413017273, 'Val/mean hd95_metric': 5.6570940017700195} +Cheakpoint... +Epoch [2096/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735492467880249, 'Val/mean miou_metric': 0.9572084546089172, 'Val/mean f1': 0.974115788936615, 'Val/mean precision': 0.9703406095504761, 'Val/mean recall': 0.977920413017273, 'Val/mean hd95_metric': 5.6570940017700195} +Epoch [2097/4000] Training [1/16] Loss: 0.00453 +Epoch [2097/4000] Training [2/16] Loss: 0.00544 +Epoch [2097/4000] Training [3/16] Loss: 0.00550 +Epoch [2097/4000] Training [4/16] Loss: 0.02011 +Epoch [2097/4000] Training [5/16] Loss: 0.00718 +Epoch [2097/4000] Training [6/16] Loss: 0.00478 +Epoch [2097/4000] Training [7/16] Loss: 0.00475 +Epoch [2097/4000] Training [8/16] Loss: 0.00539 +Epoch [2097/4000] Training [9/16] Loss: 0.00451 +Epoch [2097/4000] Training [10/16] Loss: 0.00408 +Epoch [2097/4000] Training [11/16] Loss: 0.00878 +Epoch [2097/4000] Training [12/16] Loss: 0.00456 +Epoch [2097/4000] Training [13/16] Loss: 0.00640 +Epoch [2097/4000] Training [14/16] Loss: 0.00664 +Epoch [2097/4000] Training [15/16] Loss: 0.00609 +Epoch [2097/4000] Training [16/16] Loss: 0.00776 +Epoch [2097/4000] Training metric {'Train/mean dice_metric': 0.9962093830108643, 'Train/mean miou_metric': 0.9921910762786865, 'Train/mean f1': 0.9918551445007324, 'Train/mean precision': 0.9873160719871521, 'Train/mean recall': 0.9964361786842346, 'Train/mean hd95_metric': 1.072177767753601} +Epoch [2097/4000] Validation [1/4] Loss: 0.36494 focal_loss 0.28380 dice_loss 0.08113 +Epoch [2097/4000] Validation [2/4] Loss: 0.44974 focal_loss 0.31877 dice_loss 0.13096 +Epoch [2097/4000] Validation [3/4] Loss: 0.20824 focal_loss 0.13745 dice_loss 0.07079 +Epoch [2097/4000] Validation [4/4] Loss: 0.23103 focal_loss 0.14723 dice_loss 0.08380 +Epoch [2097/4000] Validation metric {'Val/mean dice_metric': 0.9724026918411255, 'Val/mean miou_metric': 0.9560181498527527, 'Val/mean f1': 0.9743294715881348, 'Val/mean precision': 0.972834587097168, 'Val/mean recall': 0.9758290648460388, 'Val/mean hd95_metric': 6.3256425857543945} +Cheakpoint... +Epoch [2097/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724026918411255, 'Val/mean miou_metric': 0.9560181498527527, 'Val/mean f1': 0.9743294715881348, 'Val/mean precision': 0.972834587097168, 'Val/mean recall': 0.9758290648460388, 'Val/mean hd95_metric': 6.3256425857543945} +Epoch [2098/4000] Training [1/16] Loss: 0.00545 +Epoch [2098/4000] Training [2/16] Loss: 0.00574 +Epoch [2098/4000] Training [3/16] Loss: 0.00405 +Epoch [2098/4000] Training [4/16] Loss: 0.00585 +Epoch [2098/4000] Training [5/16] Loss: 0.00579 +Epoch [2098/4000] Training [6/16] Loss: 0.00608 +Epoch [2098/4000] Training [7/16] Loss: 0.00586 +Epoch [2098/4000] Training [8/16] Loss: 0.00586 +Epoch [2098/4000] Training [9/16] Loss: 0.00610 +Epoch [2098/4000] Training [10/16] Loss: 0.00710 +Epoch [2098/4000] Training [11/16] Loss: 0.00593 +Epoch [2098/4000] Training [12/16] Loss: 0.00605 +Epoch [2098/4000] Training [13/16] Loss: 0.00760 +Epoch [2098/4000] Training [14/16] Loss: 0.00560 +Epoch [2098/4000] Training [15/16] Loss: 0.00520 +Epoch [2098/4000] Training [16/16] Loss: 0.00642 +Epoch [2098/4000] Training metric {'Train/mean dice_metric': 0.9962130784988403, 'Train/mean miou_metric': 0.9921771287918091, 'Train/mean f1': 0.9917165637016296, 'Train/mean precision': 0.9869542121887207, 'Train/mean recall': 0.9965250492095947, 'Train/mean hd95_metric': 1.0236648321151733} +Epoch [2098/4000] Validation [1/4] Loss: 0.29773 focal_loss 0.23030 dice_loss 0.06743 +Epoch [2098/4000] Validation [2/4] Loss: 0.40228 focal_loss 0.28225 dice_loss 0.12003 +Epoch [2098/4000] Validation [3/4] Loss: 0.39803 focal_loss 0.28786 dice_loss 0.11017 +Epoch [2098/4000] Validation [4/4] Loss: 0.28364 focal_loss 0.17096 dice_loss 0.11268 +Epoch [2098/4000] Validation metric {'Val/mean dice_metric': 0.9720080494880676, 'Val/mean miou_metric': 0.955107569694519, 'Val/mean f1': 0.9725545048713684, 'Val/mean precision': 0.9710748195648193, 'Val/mean recall': 0.9740386605262756, 'Val/mean hd95_metric': 6.093624591827393} +Cheakpoint... +Epoch [2098/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720080494880676, 'Val/mean miou_metric': 0.955107569694519, 'Val/mean f1': 0.9725545048713684, 'Val/mean precision': 0.9710748195648193, 'Val/mean recall': 0.9740386605262756, 'Val/mean hd95_metric': 6.093624591827393} +Epoch [2099/4000] Training [1/16] Loss: 0.00686 +Epoch [2099/4000] Training [2/16] Loss: 0.00481 +Epoch [2099/4000] Training [3/16] Loss: 0.00685 +Epoch [2099/4000] Training [4/16] Loss: 0.00676 +Epoch [2099/4000] Training [5/16] Loss: 0.00653 +Epoch [2099/4000] Training [6/16] Loss: 0.00478 +Epoch [2099/4000] Training [7/16] Loss: 0.00415 +Epoch [2099/4000] Training [8/16] Loss: 0.00558 +Epoch [2099/4000] Training [9/16] Loss: 0.00568 +Epoch [2099/4000] Training [10/16] Loss: 0.00435 +Epoch [2099/4000] Training [11/16] Loss: 0.00859 +Epoch [2099/4000] Training [12/16] Loss: 0.00495 +Epoch [2099/4000] Training [13/16] Loss: 0.00706 +Epoch [2099/4000] Training [14/16] Loss: 0.00502 +Epoch [2099/4000] Training [15/16] Loss: 0.00586 +Epoch [2099/4000] Training [16/16] Loss: 0.00592 +Epoch [2099/4000] Training metric {'Train/mean dice_metric': 0.9963608980178833, 'Train/mean miou_metric': 0.9924702644348145, 'Train/mean f1': 0.9918983578681946, 'Train/mean precision': 0.9871324896812439, 'Train/mean recall': 0.996710479259491, 'Train/mean hd95_metric': 1.0016722679138184} +Epoch [2099/4000] Validation [1/4] Loss: 0.33787 focal_loss 0.26228 dice_loss 0.07560 +Epoch [2099/4000] Validation [2/4] Loss: 0.37786 focal_loss 0.21547 dice_loss 0.16239 +Epoch [2099/4000] Validation [3/4] Loss: 0.38602 focal_loss 0.29540 dice_loss 0.09062 +Epoch [2099/4000] Validation [4/4] Loss: 0.28403 focal_loss 0.17175 dice_loss 0.11228 +Epoch [2099/4000] Validation metric {'Val/mean dice_metric': 0.9721115231513977, 'Val/mean miou_metric': 0.955746054649353, 'Val/mean f1': 0.9736995100975037, 'Val/mean precision': 0.9710055589675903, 'Val/mean recall': 0.9764084815979004, 'Val/mean hd95_metric': 5.536783218383789} +Cheakpoint... +Epoch [2099/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721115231513977, 'Val/mean miou_metric': 0.955746054649353, 'Val/mean f1': 0.9736995100975037, 'Val/mean precision': 0.9710055589675903, 'Val/mean recall': 0.9764084815979004, 'Val/mean hd95_metric': 5.536783218383789} +Epoch [2100/4000] Training [1/16] Loss: 0.00569 +Epoch [2100/4000] Training [2/16] Loss: 0.00415 +Epoch [2100/4000] Training [3/16] Loss: 0.00650 +Epoch [2100/4000] Training [4/16] Loss: 0.00555 +Epoch [2100/4000] Training [5/16] Loss: 0.00570 +Epoch [2100/4000] Training [6/16] Loss: 0.00545 +Epoch [2100/4000] Training [7/16] Loss: 0.00563 +Epoch [2100/4000] Training [8/16] Loss: 0.00796 +Epoch [2100/4000] Training [9/16] Loss: 0.00530 +Epoch [2100/4000] Training [10/16] Loss: 0.00460 +Epoch [2100/4000] Training [11/16] Loss: 0.00702 +Epoch [2100/4000] Training [12/16] Loss: 0.00554 +Epoch [2100/4000] Training [13/16] Loss: 0.00475 +Epoch [2100/4000] Training [14/16] Loss: 0.00791 +Epoch [2100/4000] Training [15/16] Loss: 0.00488 +Epoch [2100/4000] Training [16/16] Loss: 0.00448 +Epoch [2100/4000] Training metric {'Train/mean dice_metric': 0.996313750743866, 'Train/mean miou_metric': 0.9923785924911499, 'Train/mean f1': 0.9919567704200745, 'Train/mean precision': 0.9874634742736816, 'Train/mean recall': 0.9964911341667175, 'Train/mean hd95_metric': 1.0048413276672363} +Epoch [2100/4000] Validation [1/4] Loss: 0.27028 focal_loss 0.20710 dice_loss 0.06319 +Epoch [2100/4000] Validation [2/4] Loss: 0.37391 focal_loss 0.25828 dice_loss 0.11563 +Epoch [2100/4000] Validation [3/4] Loss: 0.37887 focal_loss 0.27902 dice_loss 0.09985 +Epoch [2100/4000] Validation [4/4] Loss: 0.37180 focal_loss 0.25171 dice_loss 0.12008 +Epoch [2100/4000] Validation metric {'Val/mean dice_metric': 0.9733816385269165, 'Val/mean miou_metric': 0.9566966891288757, 'Val/mean f1': 0.9743799567222595, 'Val/mean precision': 0.9724118709564209, 'Val/mean recall': 0.9763559699058533, 'Val/mean hd95_metric': 5.799858093261719} +Cheakpoint... +Epoch [2100/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733816385269165, 'Val/mean miou_metric': 0.9566966891288757, 'Val/mean f1': 0.9743799567222595, 'Val/mean precision': 0.9724118709564209, 'Val/mean recall': 0.9763559699058533, 'Val/mean hd95_metric': 5.799858093261719} +Epoch [2101/4000] Training [1/16] Loss: 0.00843 +Epoch [2101/4000] Training [2/16] Loss: 0.00602 +Epoch [2101/4000] Training [3/16] Loss: 0.00606 +Epoch [2101/4000] Training [4/16] Loss: 0.00495 +Epoch [2101/4000] Training [5/16] Loss: 0.00627 +Epoch [2101/4000] Training [6/16] Loss: 0.00680 +Epoch [2101/4000] Training [7/16] Loss: 0.00431 +Epoch [2101/4000] Training [8/16] Loss: 0.00516 +Epoch [2101/4000] Training [9/16] Loss: 0.00456 +Epoch [2101/4000] Training [10/16] Loss: 0.00424 +Epoch [2101/4000] Training [11/16] Loss: 0.00543 +Epoch [2101/4000] Training [12/16] Loss: 0.00551 +Epoch [2101/4000] Training [13/16] Loss: 0.00717 +Epoch [2101/4000] Training [14/16] Loss: 0.00623 +Epoch [2101/4000] Training [15/16] Loss: 0.00559 +Epoch [2101/4000] Training [16/16] Loss: 0.00532 +Epoch [2101/4000] Training metric {'Train/mean dice_metric': 0.9961385130882263, 'Train/mean miou_metric': 0.9920504689216614, 'Train/mean f1': 0.9918835163116455, 'Train/mean precision': 0.9874594807624817, 'Train/mean recall': 0.9963473677635193, 'Train/mean hd95_metric': 1.0047951936721802} +Epoch [2101/4000] Validation [1/4] Loss: 0.33159 focal_loss 0.26107 dice_loss 0.07053 +Epoch [2101/4000] Validation [2/4] Loss: 0.34486 focal_loss 0.23975 dice_loss 0.10511 +Epoch [2101/4000] Validation [3/4] Loss: 0.19695 focal_loss 0.13137 dice_loss 0.06559 +Epoch [2101/4000] Validation [4/4] Loss: 0.34126 focal_loss 0.21435 dice_loss 0.12691 +Epoch [2101/4000] Validation metric {'Val/mean dice_metric': 0.9740683436393738, 'Val/mean miou_metric': 0.957707405090332, 'Val/mean f1': 0.9753315448760986, 'Val/mean precision': 0.9725088477134705, 'Val/mean recall': 0.9781707525253296, 'Val/mean hd95_metric': 5.386992454528809} +Cheakpoint... +Epoch [2101/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740683436393738, 'Val/mean miou_metric': 0.957707405090332, 'Val/mean f1': 0.9753315448760986, 'Val/mean precision': 0.9725088477134705, 'Val/mean recall': 0.9781707525253296, 'Val/mean hd95_metric': 5.386992454528809} +Epoch [2102/4000] Training [1/16] Loss: 0.00533 +Epoch [2102/4000] Training [2/16] Loss: 0.00568 +Epoch [2102/4000] Training [3/16] Loss: 0.00517 +Epoch [2102/4000] Training [4/16] Loss: 0.00544 +Epoch [2102/4000] Training [5/16] Loss: 0.00572 +Epoch [2102/4000] Training [6/16] Loss: 0.00621 +Epoch [2102/4000] Training [7/16] Loss: 0.00673 +Epoch [2102/4000] Training [8/16] Loss: 0.00559 +Epoch [2102/4000] Training [9/16] Loss: 0.00438 +Epoch [2102/4000] Training [10/16] Loss: 0.00501 +Epoch [2102/4000] Training [11/16] Loss: 0.00522 +Epoch [2102/4000] Training [12/16] Loss: 0.00568 +Epoch [2102/4000] Training [13/16] Loss: 0.00853 +Epoch [2102/4000] Training [14/16] Loss: 0.00456 +Epoch [2102/4000] Training [15/16] Loss: 0.00442 +Epoch [2102/4000] Training [16/16] Loss: 0.00639 +Epoch [2102/4000] Training metric {'Train/mean dice_metric': 0.9960646629333496, 'Train/mean miou_metric': 0.991870641708374, 'Train/mean f1': 0.9914708137512207, 'Train/mean precision': 0.9866688847541809, 'Train/mean recall': 0.9963197112083435, 'Train/mean hd95_metric': 0.9985207915306091} +Epoch [2102/4000] Validation [1/4] Loss: 0.30169 focal_loss 0.23658 dice_loss 0.06511 +Epoch [2102/4000] Validation [2/4] Loss: 0.57741 focal_loss 0.39319 dice_loss 0.18422 +Epoch [2102/4000] Validation [3/4] Loss: 0.39295 focal_loss 0.29988 dice_loss 0.09307 +Epoch [2102/4000] Validation [4/4] Loss: 0.27641 focal_loss 0.17315 dice_loss 0.10326 +Epoch [2102/4000] Validation metric {'Val/mean dice_metric': 0.9734534025192261, 'Val/mean miou_metric': 0.9575886726379395, 'Val/mean f1': 0.9750292897224426, 'Val/mean precision': 0.9717922210693359, 'Val/mean recall': 0.9782879948616028, 'Val/mean hd95_metric': 5.588473320007324} +Cheakpoint... +Epoch [2102/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734534025192261, 'Val/mean miou_metric': 0.9575886726379395, 'Val/mean f1': 0.9750292897224426, 'Val/mean precision': 0.9717922210693359, 'Val/mean recall': 0.9782879948616028, 'Val/mean hd95_metric': 5.588473320007324} +Epoch [2103/4000] Training [1/16] Loss: 0.00571 +Epoch [2103/4000] Training [2/16] Loss: 0.00546 +Epoch [2103/4000] Training [3/16] Loss: 0.00707 +Epoch [2103/4000] Training [4/16] Loss: 0.00679 +Epoch [2103/4000] Training [5/16] Loss: 0.00527 +Epoch [2103/4000] Training [6/16] Loss: 0.00554 +Epoch [2103/4000] Training [7/16] Loss: 0.00476 +Epoch [2103/4000] Training [8/16] Loss: 0.00504 +Epoch [2103/4000] Training [9/16] Loss: 0.00598 +Epoch [2103/4000] Training [10/16] Loss: 0.00717 +Epoch [2103/4000] Training [11/16] Loss: 0.00579 +Epoch [2103/4000] Training [12/16] Loss: 0.00515 +Epoch [2103/4000] Training [13/16] Loss: 0.00472 +Epoch [2103/4000] Training [14/16] Loss: 0.00438 +Epoch [2103/4000] Training [15/16] Loss: 0.00651 +Epoch [2103/4000] Training [16/16] Loss: 0.00525 +Epoch [2103/4000] Training metric {'Train/mean dice_metric': 0.9961440563201904, 'Train/mean miou_metric': 0.9920346736907959, 'Train/mean f1': 0.9913500547409058, 'Train/mean precision': 0.9862738847732544, 'Train/mean recall': 0.996478796005249, 'Train/mean hd95_metric': 1.0030834674835205} +Epoch [2103/4000] Validation [1/4] Loss: 0.30130 focal_loss 0.23839 dice_loss 0.06291 +Epoch [2103/4000] Validation [2/4] Loss: 0.23342 focal_loss 0.14382 dice_loss 0.08960 +Epoch [2103/4000] Validation [3/4] Loss: 0.38508 focal_loss 0.29153 dice_loss 0.09355 +Epoch [2103/4000] Validation [4/4] Loss: 0.29697 focal_loss 0.17749 dice_loss 0.11947 +Epoch [2103/4000] Validation metric {'Val/mean dice_metric': 0.9748477935791016, 'Val/mean miou_metric': 0.9580354690551758, 'Val/mean f1': 0.9743652939796448, 'Val/mean precision': 0.97027587890625, 'Val/mean recall': 0.9784892797470093, 'Val/mean hd95_metric': 5.611515522003174} +Cheakpoint... +Epoch [2103/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748477935791016, 'Val/mean miou_metric': 0.9580354690551758, 'Val/mean f1': 0.9743652939796448, 'Val/mean precision': 0.97027587890625, 'Val/mean recall': 0.9784892797470093, 'Val/mean hd95_metric': 5.611515522003174} +Epoch [2104/4000] Training [1/16] Loss: 0.00412 +Epoch [2104/4000] Training [2/16] Loss: 0.00394 +Epoch [2104/4000] Training [3/16] Loss: 0.00506 +Epoch [2104/4000] Training [4/16] Loss: 0.00536 +Epoch [2104/4000] Training [5/16] Loss: 0.00414 +Epoch [2104/4000] Training [6/16] Loss: 0.00421 +Epoch [2104/4000] Training [7/16] Loss: 0.01411 +Epoch [2104/4000] Training [8/16] Loss: 0.00639 +Epoch [2104/4000] Training [9/16] Loss: 0.00531 +Epoch [2104/4000] Training [10/16] Loss: 0.00515 +Epoch [2104/4000] Training [11/16] Loss: 0.00779 +Epoch [2104/4000] Training [12/16] Loss: 0.00516 +Epoch [2104/4000] Training [13/16] Loss: 0.00486 +Epoch [2104/4000] Training [14/16] Loss: 0.00544 +Epoch [2104/4000] Training [15/16] Loss: 0.00703 +Epoch [2104/4000] Training [16/16] Loss: 0.00580 +Epoch [2104/4000] Training metric {'Train/mean dice_metric': 0.9963870048522949, 'Train/mean miou_metric': 0.9925463199615479, 'Train/mean f1': 0.9921603202819824, 'Train/mean precision': 0.9876604080200195, 'Train/mean recall': 0.9967014789581299, 'Train/mean hd95_metric': 1.0122992992401123} +Epoch [2104/4000] Validation [1/4] Loss: 0.30304 focal_loss 0.23805 dice_loss 0.06499 +Epoch [2104/4000] Validation [2/4] Loss: 0.33967 focal_loss 0.23621 dice_loss 0.10346 +Epoch [2104/4000] Validation [3/4] Loss: 0.37973 focal_loss 0.28792 dice_loss 0.09181 +Epoch [2104/4000] Validation [4/4] Loss: 0.30361 focal_loss 0.19766 dice_loss 0.10594 +Epoch [2104/4000] Validation metric {'Val/mean dice_metric': 0.9739526510238647, 'Val/mean miou_metric': 0.9578746557235718, 'Val/mean f1': 0.9753791093826294, 'Val/mean precision': 0.9720391035079956, 'Val/mean recall': 0.9787420630455017, 'Val/mean hd95_metric': 5.584001541137695} +Cheakpoint... +Epoch [2104/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739526510238647, 'Val/mean miou_metric': 0.9578746557235718, 'Val/mean f1': 0.9753791093826294, 'Val/mean precision': 0.9720391035079956, 'Val/mean recall': 0.9787420630455017, 'Val/mean hd95_metric': 5.584001541137695} +Epoch [2105/4000] Training [1/16] Loss: 0.00682 +Epoch [2105/4000] Training [2/16] Loss: 0.00564 +Epoch [2105/4000] Training [3/16] Loss: 0.00570 +Epoch [2105/4000] Training [4/16] Loss: 0.00524 +Epoch [2105/4000] Training [5/16] Loss: 0.00585 +Epoch [2105/4000] Training [6/16] Loss: 0.00588 +Epoch [2105/4000] Training [7/16] Loss: 0.00463 +Epoch [2105/4000] Training [8/16] Loss: 0.00544 +Epoch [2105/4000] Training [9/16] Loss: 0.00656 +Epoch [2105/4000] Training [10/16] Loss: 0.00634 +Epoch [2105/4000] Training [11/16] Loss: 0.00661 +Epoch [2105/4000] Training [12/16] Loss: 0.00680 +Epoch [2105/4000] Training [13/16] Loss: 0.00711 +Epoch [2105/4000] Training [14/16] Loss: 0.00517 +Epoch [2105/4000] Training [15/16] Loss: 0.00830 +Epoch [2105/4000] Training [16/16] Loss: 0.00526 +Epoch [2105/4000] Training metric {'Train/mean dice_metric': 0.9960704445838928, 'Train/mean miou_metric': 0.9918765425682068, 'Train/mean f1': 0.9909497499465942, 'Train/mean precision': 0.9856618046760559, 'Train/mean recall': 0.9962947368621826, 'Train/mean hd95_metric': 1.0127009153366089} +Epoch [2105/4000] Validation [1/4] Loss: 0.26796 focal_loss 0.20818 dice_loss 0.05978 +Epoch [2105/4000] Validation [2/4] Loss: 0.35776 focal_loss 0.20201 dice_loss 0.15575 +Epoch [2105/4000] Validation [3/4] Loss: 0.41428 focal_loss 0.31708 dice_loss 0.09720 +Epoch [2105/4000] Validation [4/4] Loss: 0.33841 focal_loss 0.21595 dice_loss 0.12246 +Epoch [2105/4000] Validation metric {'Val/mean dice_metric': 0.9732375144958496, 'Val/mean miou_metric': 0.9572886228561401, 'Val/mean f1': 0.9740393161773682, 'Val/mean precision': 0.9697505235671997, 'Val/mean recall': 0.9783663153648376, 'Val/mean hd95_metric': 5.2975921630859375} +Cheakpoint... +Epoch [2105/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732375144958496, 'Val/mean miou_metric': 0.9572886228561401, 'Val/mean f1': 0.9740393161773682, 'Val/mean precision': 0.9697505235671997, 'Val/mean recall': 0.9783663153648376, 'Val/mean hd95_metric': 5.2975921630859375} +Epoch [2106/4000] Training [1/16] Loss: 0.00646 +Epoch [2106/4000] Training [2/16] Loss: 0.00474 +Epoch [2106/4000] Training [3/16] Loss: 0.00421 +Epoch [2106/4000] Training [4/16] Loss: 0.00502 +Epoch [2106/4000] Training [5/16] Loss: 0.00602 +Epoch [2106/4000] Training [6/16] Loss: 0.00471 +Epoch [2106/4000] Training [7/16] Loss: 0.00483 +Epoch [2106/4000] Training [8/16] Loss: 0.00470 +Epoch [2106/4000] Training [9/16] Loss: 0.00527 +Epoch [2106/4000] Training [10/16] Loss: 0.00418 +Epoch [2106/4000] Training [11/16] Loss: 0.00512 +Epoch [2106/4000] Training [12/16] Loss: 0.00611 +Epoch [2106/4000] Training [13/16] Loss: 0.00611 +Epoch [2106/4000] Training [14/16] Loss: 0.00528 +Epoch [2106/4000] Training [15/16] Loss: 0.00550 +Epoch [2106/4000] Training [16/16] Loss: 0.00431 +Epoch [2106/4000] Training metric {'Train/mean dice_metric': 0.9965024590492249, 'Train/mean miou_metric': 0.992730975151062, 'Train/mean f1': 0.9912760257720947, 'Train/mean precision': 0.9859125018119812, 'Train/mean recall': 0.996698260307312, 'Train/mean hd95_metric': 0.9966760277748108} +Epoch [2106/4000] Validation [1/4] Loss: 0.38087 focal_loss 0.30492 dice_loss 0.07595 +Epoch [2106/4000] Validation [2/4] Loss: 0.62306 focal_loss 0.41473 dice_loss 0.20833 +Epoch [2106/4000] Validation [3/4] Loss: 0.41603 focal_loss 0.32046 dice_loss 0.09557 +Epoch [2106/4000] Validation [4/4] Loss: 0.26323 focal_loss 0.17644 dice_loss 0.08679 +Epoch [2106/4000] Validation metric {'Val/mean dice_metric': 0.9738090634346008, 'Val/mean miou_metric': 0.9575735330581665, 'Val/mean f1': 0.9741507768630981, 'Val/mean precision': 0.972210705280304, 'Val/mean recall': 0.9760984778404236, 'Val/mean hd95_metric': 5.651110649108887} +Cheakpoint... +Epoch [2106/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738090634346008, 'Val/mean miou_metric': 0.9575735330581665, 'Val/mean f1': 0.9741507768630981, 'Val/mean precision': 0.972210705280304, 'Val/mean recall': 0.9760984778404236, 'Val/mean hd95_metric': 5.651110649108887} +Epoch [2107/4000] Training [1/16] Loss: 0.00569 +Epoch [2107/4000] Training [2/16] Loss: 0.00925 +Epoch [2107/4000] Training [3/16] Loss: 0.00626 +Epoch [2107/4000] Training [4/16] Loss: 0.00638 +Epoch [2107/4000] Training [5/16] Loss: 0.00644 +Epoch [2107/4000] Training [6/16] Loss: 0.00798 +Epoch [2107/4000] Training [7/16] Loss: 0.00395 +Epoch [2107/4000] Training [8/16] Loss: 0.00493 +Epoch [2107/4000] Training [9/16] Loss: 0.00476 +Epoch [2107/4000] Training [10/16] Loss: 0.00520 +Epoch [2107/4000] Training [11/16] Loss: 0.00721 +Epoch [2107/4000] Training [12/16] Loss: 0.00572 +Epoch [2107/4000] Training [13/16] Loss: 0.00510 +Epoch [2107/4000] Training [14/16] Loss: 0.00530 +Epoch [2107/4000] Training [15/16] Loss: 0.00621 +Epoch [2107/4000] Training [16/16] Loss: 0.00612 +Epoch [2107/4000] Training metric {'Train/mean dice_metric': 0.9960802793502808, 'Train/mean miou_metric': 0.9919315576553345, 'Train/mean f1': 0.9917685985565186, 'Train/mean precision': 0.9872819781303406, 'Train/mean recall': 0.9962961077690125, 'Train/mean hd95_metric': 1.0053279399871826} +Epoch [2107/4000] Validation [1/4] Loss: 0.35048 focal_loss 0.27545 dice_loss 0.07503 +Epoch [2107/4000] Validation [2/4] Loss: 0.49540 focal_loss 0.33435 dice_loss 0.16106 +Epoch [2107/4000] Validation [3/4] Loss: 0.40659 focal_loss 0.30896 dice_loss 0.09762 +Epoch [2107/4000] Validation [4/4] Loss: 0.33775 focal_loss 0.21230 dice_loss 0.12545 +Epoch [2107/4000] Validation metric {'Val/mean dice_metric': 0.9723474383354187, 'Val/mean miou_metric': 0.955579400062561, 'Val/mean f1': 0.973421573638916, 'Val/mean precision': 0.9707340002059937, 'Val/mean recall': 0.976124107837677, 'Val/mean hd95_metric': 5.5318756103515625} +Cheakpoint... +Epoch [2107/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723474383354187, 'Val/mean miou_metric': 0.955579400062561, 'Val/mean f1': 0.973421573638916, 'Val/mean precision': 0.9707340002059937, 'Val/mean recall': 0.976124107837677, 'Val/mean hd95_metric': 5.5318756103515625} +Epoch [2108/4000] Training [1/16] Loss: 0.00835 +Epoch [2108/4000] Training [2/16] Loss: 0.00651 +Epoch [2108/4000] Training [3/16] Loss: 0.00721 +Epoch [2108/4000] Training [4/16] Loss: 0.00529 +Epoch [2108/4000] Training [5/16] Loss: 0.00514 +Epoch [2108/4000] Training [6/16] Loss: 0.00661 +Epoch [2108/4000] Training [7/16] Loss: 0.00652 +Epoch [2108/4000] Training [8/16] Loss: 0.00597 +Epoch [2108/4000] Training [9/16] Loss: 0.00664 +Epoch [2108/4000] Training [10/16] Loss: 0.00454 +Epoch [2108/4000] Training [11/16] Loss: 0.00431 +Epoch [2108/4000] Training [12/16] Loss: 0.00700 +Epoch [2108/4000] Training [13/16] Loss: 0.00809 +Epoch [2108/4000] Training [14/16] Loss: 0.00551 +Epoch [2108/4000] Training [15/16] Loss: 0.00547 +Epoch [2108/4000] Training [16/16] Loss: 0.00622 +Epoch [2108/4000] Training metric {'Train/mean dice_metric': 0.9957715272903442, 'Train/mean miou_metric': 0.9913287162780762, 'Train/mean f1': 0.9916722774505615, 'Train/mean precision': 0.9872640371322632, 'Train/mean recall': 0.996120035648346, 'Train/mean hd95_metric': 1.0228023529052734} +Epoch [2108/4000] Validation [1/4] Loss: 0.28513 focal_loss 0.22215 dice_loss 0.06298 +Epoch [2108/4000] Validation [2/4] Loss: 0.65453 focal_loss 0.43497 dice_loss 0.21956 +Epoch [2108/4000] Validation [3/4] Loss: 0.42071 focal_loss 0.32496 dice_loss 0.09576 +Epoch [2108/4000] Validation [4/4] Loss: 0.28657 focal_loss 0.18028 dice_loss 0.10629 +Epoch [2108/4000] Validation metric {'Val/mean dice_metric': 0.9725910425186157, 'Val/mean miou_metric': 0.9561643600463867, 'Val/mean f1': 0.9745862483978271, 'Val/mean precision': 0.9705339670181274, 'Val/mean recall': 0.978672444820404, 'Val/mean hd95_metric': 5.962296485900879} +Cheakpoint... +Epoch [2108/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725910425186157, 'Val/mean miou_metric': 0.9561643600463867, 'Val/mean f1': 0.9745862483978271, 'Val/mean precision': 0.9705339670181274, 'Val/mean recall': 0.978672444820404, 'Val/mean hd95_metric': 5.962296485900879} +Epoch [2109/4000] Training [1/16] Loss: 0.00624 +Epoch [2109/4000] Training [2/16] Loss: 0.00826 +Epoch [2109/4000] Training [3/16] Loss: 0.00505 +Epoch [2109/4000] Training [4/16] Loss: 0.00903 +Epoch [2109/4000] Training [5/16] Loss: 0.00622 +Epoch [2109/4000] Training [6/16] Loss: 0.00748 +Epoch [2109/4000] Training [7/16] Loss: 0.00757 +Epoch [2109/4000] Training [8/16] Loss: 0.00621 +Epoch [2109/4000] Training [9/16] Loss: 0.00496 +Epoch [2109/4000] Training [10/16] Loss: 0.00406 +Epoch [2109/4000] Training [11/16] Loss: 0.00571 +Epoch [2109/4000] Training [12/16] Loss: 0.00907 +Epoch [2109/4000] Training [13/16] Loss: 0.00631 +Epoch [2109/4000] Training [14/16] Loss: 0.00485 +Epoch [2109/4000] Training [15/16] Loss: 0.00917 +Epoch [2109/4000] Training [16/16] Loss: 0.00457 +Epoch [2109/4000] Training metric {'Train/mean dice_metric': 0.995680570602417, 'Train/mean miou_metric': 0.9911525249481201, 'Train/mean f1': 0.9914965033531189, 'Train/mean precision': 0.986915647983551, 'Train/mean recall': 0.996120035648346, 'Train/mean hd95_metric': 1.0679734945297241} +Epoch [2109/4000] Validation [1/4] Loss: 0.41382 focal_loss 0.32563 dice_loss 0.08820 +Epoch [2109/4000] Validation [2/4] Loss: 0.39810 focal_loss 0.26598 dice_loss 0.13212 +Epoch [2109/4000] Validation [3/4] Loss: 0.36834 focal_loss 0.27264 dice_loss 0.09571 +Epoch [2109/4000] Validation [4/4] Loss: 0.34762 focal_loss 0.21157 dice_loss 0.13605 +Epoch [2109/4000] Validation metric {'Val/mean dice_metric': 0.9716062545776367, 'Val/mean miou_metric': 0.953987717628479, 'Val/mean f1': 0.9721600413322449, 'Val/mean precision': 0.9718385338783264, 'Val/mean recall': 0.9724816679954529, 'Val/mean hd95_metric': 5.8155293464660645} +Cheakpoint... +Epoch [2109/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716062545776367, 'Val/mean miou_metric': 0.953987717628479, 'Val/mean f1': 0.9721600413322449, 'Val/mean precision': 0.9718385338783264, 'Val/mean recall': 0.9724816679954529, 'Val/mean hd95_metric': 5.8155293464660645} +Epoch [2110/4000] Training [1/16] Loss: 0.00821 +Epoch [2110/4000] Training [2/16] Loss: 0.00480 +Epoch [2110/4000] Training [3/16] Loss: 0.00511 +Epoch [2110/4000] Training [4/16] Loss: 0.00609 +Epoch [2110/4000] Training [5/16] Loss: 0.00513 +Epoch [2110/4000] Training [6/16] Loss: 0.00540 +Epoch [2110/4000] Training [7/16] Loss: 0.00498 +Epoch [2110/4000] Training [8/16] Loss: 0.00662 +Epoch [2110/4000] Training [9/16] Loss: 0.00520 +Epoch [2110/4000] Training [10/16] Loss: 0.00755 +Epoch [2110/4000] Training [11/16] Loss: 0.00423 +Epoch [2110/4000] Training [12/16] Loss: 0.00524 +Epoch [2110/4000] Training [13/16] Loss: 0.00613 +Epoch [2110/4000] Training [14/16] Loss: 0.00667 +Epoch [2110/4000] Training [15/16] Loss: 0.00510 +Epoch [2110/4000] Training [16/16] Loss: 0.00505 +Epoch [2110/4000] Training metric {'Train/mean dice_metric': 0.9961877465248108, 'Train/mean miou_metric': 0.9921393394470215, 'Train/mean f1': 0.9916715621948242, 'Train/mean precision': 0.9870008826255798, 'Train/mean recall': 0.9963865876197815, 'Train/mean hd95_metric': 1.012829065322876} +Epoch [2110/4000] Validation [1/4] Loss: 0.49892 focal_loss 0.40138 dice_loss 0.09754 +Epoch [2110/4000] Validation [2/4] Loss: 0.80175 focal_loss 0.57346 dice_loss 0.22828 +Epoch [2110/4000] Validation [3/4] Loss: 0.40003 focal_loss 0.30787 dice_loss 0.09216 +Epoch [2110/4000] Validation [4/4] Loss: 0.28572 focal_loss 0.17653 dice_loss 0.10919 +Epoch [2110/4000] Validation metric {'Val/mean dice_metric': 0.9707131385803223, 'Val/mean miou_metric': 0.953671932220459, 'Val/mean f1': 0.9722473621368408, 'Val/mean precision': 0.9717376232147217, 'Val/mean recall': 0.9727575778961182, 'Val/mean hd95_metric': 6.172300815582275} +Cheakpoint... +Epoch [2110/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707131385803223, 'Val/mean miou_metric': 0.953671932220459, 'Val/mean f1': 0.9722473621368408, 'Val/mean precision': 0.9717376232147217, 'Val/mean recall': 0.9727575778961182, 'Val/mean hd95_metric': 6.172300815582275} +Epoch [2111/4000] Training [1/16] Loss: 0.00447 +Epoch [2111/4000] Training [2/16] Loss: 0.00659 +Epoch [2111/4000] Training [3/16] Loss: 0.00544 +Epoch [2111/4000] Training [4/16] Loss: 0.00710 +Epoch [2111/4000] Training [5/16] Loss: 0.00449 +Epoch [2111/4000] Training [6/16] Loss: 0.00785 +Epoch [2111/4000] Training [7/16] Loss: 0.00556 +Epoch [2111/4000] Training [8/16] Loss: 0.00646 +Epoch [2111/4000] Training [9/16] Loss: 0.00462 +Epoch [2111/4000] Training [10/16] Loss: 0.00801 +Epoch [2111/4000] Training [11/16] Loss: 0.00582 +Epoch [2111/4000] Training [12/16] Loss: 0.00630 +Epoch [2111/4000] Training [13/16] Loss: 0.00685 +Epoch [2111/4000] Training [14/16] Loss: 0.00492 +Epoch [2111/4000] Training [15/16] Loss: 0.00594 +Epoch [2111/4000] Training [16/16] Loss: 0.00560 +Epoch [2111/4000] Training metric {'Train/mean dice_metric': 0.9961991310119629, 'Train/mean miou_metric': 0.9921708703041077, 'Train/mean f1': 0.9918943047523499, 'Train/mean precision': 0.9873477816581726, 'Train/mean recall': 0.9964829087257385, 'Train/mean hd95_metric': 1.2355530261993408} +Epoch [2111/4000] Validation [1/4] Loss: 0.37028 focal_loss 0.29207 dice_loss 0.07822 +Epoch [2111/4000] Validation [2/4] Loss: 0.38913 focal_loss 0.26334 dice_loss 0.12578 +Epoch [2111/4000] Validation [3/4] Loss: 0.37843 focal_loss 0.28739 dice_loss 0.09104 +Epoch [2111/4000] Validation [4/4] Loss: 0.23562 focal_loss 0.14736 dice_loss 0.08826 +Epoch [2111/4000] Validation metric {'Val/mean dice_metric': 0.9742706418037415, 'Val/mean miou_metric': 0.9576901197433472, 'Val/mean f1': 0.9741323590278625, 'Val/mean precision': 0.9720436334609985, 'Val/mean recall': 0.9762300848960876, 'Val/mean hd95_metric': 6.44503927230835} +Cheakpoint... +Epoch [2111/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742706418037415, 'Val/mean miou_metric': 0.9576901197433472, 'Val/mean f1': 0.9741323590278625, 'Val/mean precision': 0.9720436334609985, 'Val/mean recall': 0.9762300848960876, 'Val/mean hd95_metric': 6.44503927230835} +Epoch [2112/4000] Training [1/16] Loss: 0.00439 +Epoch [2112/4000] Training [2/16] Loss: 0.00459 +Epoch [2112/4000] Training [3/16] Loss: 0.00510 +Epoch [2112/4000] Training [4/16] Loss: 0.00568 +Epoch [2112/4000] Training [5/16] Loss: 0.00475 +Epoch [2112/4000] Training [6/16] Loss: 0.00765 +Epoch [2112/4000] Training [7/16] Loss: 0.00581 +Epoch [2112/4000] Training [8/16] Loss: 0.00536 +Epoch [2112/4000] Training [9/16] Loss: 0.00808 +Epoch [2112/4000] Training [10/16] Loss: 0.00594 +Epoch [2112/4000] Training [11/16] Loss: 0.00471 +Epoch [2112/4000] Training [12/16] Loss: 0.00497 +Epoch [2112/4000] Training [13/16] Loss: 0.00415 +Epoch [2112/4000] Training [14/16] Loss: 0.00586 +Epoch [2112/4000] Training [15/16] Loss: 0.00633 +Epoch [2112/4000] Training [16/16] Loss: 0.00538 +Epoch [2112/4000] Training metric {'Train/mean dice_metric': 0.9964776635169983, 'Train/mean miou_metric': 0.9927150011062622, 'Train/mean f1': 0.9920873641967773, 'Train/mean precision': 0.9877111315727234, 'Train/mean recall': 0.9965025186538696, 'Train/mean hd95_metric': 0.9973488450050354} +Epoch [2112/4000] Validation [1/4] Loss: 0.35490 focal_loss 0.28239 dice_loss 0.07251 +Epoch [2112/4000] Validation [2/4] Loss: 0.38455 focal_loss 0.25890 dice_loss 0.12564 +Epoch [2112/4000] Validation [3/4] Loss: 0.36762 focal_loss 0.27414 dice_loss 0.09348 +Epoch [2112/4000] Validation [4/4] Loss: 0.23469 focal_loss 0.15332 dice_loss 0.08137 +Epoch [2112/4000] Validation metric {'Val/mean dice_metric': 0.9751914143562317, 'Val/mean miou_metric': 0.9589969515800476, 'Val/mean f1': 0.9746696352958679, 'Val/mean precision': 0.9723231792449951, 'Val/mean recall': 0.977027416229248, 'Val/mean hd95_metric': 5.635364055633545} +Cheakpoint... +Epoch [2112/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751914143562317, 'Val/mean miou_metric': 0.9589969515800476, 'Val/mean f1': 0.9746696352958679, 'Val/mean precision': 0.9723231792449951, 'Val/mean recall': 0.977027416229248, 'Val/mean hd95_metric': 5.635364055633545} +Epoch [2113/4000] Training [1/16] Loss: 0.00673 +Epoch [2113/4000] Training [2/16] Loss: 0.00741 +Epoch [2113/4000] Training [3/16] Loss: 0.00552 +Epoch [2113/4000] Training [4/16] Loss: 0.00530 +Epoch [2113/4000] Training [5/16] Loss: 0.00494 +Epoch [2113/4000] Training [6/16] Loss: 0.00459 +Epoch [2113/4000] Training [7/16] Loss: 0.00475 +Epoch [2113/4000] Training [8/16] Loss: 0.00662 +Epoch [2113/4000] Training [9/16] Loss: 0.00534 +Epoch [2113/4000] Training [10/16] Loss: 0.00572 +Epoch [2113/4000] Training [11/16] Loss: 0.00455 +Epoch [2113/4000] Training [12/16] Loss: 0.00722 +Epoch [2113/4000] Training [13/16] Loss: 0.01003 +Epoch [2113/4000] Training [14/16] Loss: 0.00565 +Epoch [2113/4000] Training [15/16] Loss: 0.00661 +Epoch [2113/4000] Training [16/16] Loss: 0.00643 +Epoch [2113/4000] Training metric {'Train/mean dice_metric': 0.9962034225463867, 'Train/mean miou_metric': 0.9921715259552002, 'Train/mean f1': 0.991793692111969, 'Train/mean precision': 0.987035870552063, 'Train/mean recall': 0.9965975284576416, 'Train/mean hd95_metric': 1.161810040473938} +Epoch [2113/4000] Validation [1/4] Loss: 0.36018 focal_loss 0.28830 dice_loss 0.07188 +Epoch [2113/4000] Validation [2/4] Loss: 0.41860 focal_loss 0.27813 dice_loss 0.14047 +Epoch [2113/4000] Validation [3/4] Loss: 0.37364 focal_loss 0.27928 dice_loss 0.09436 +Epoch [2113/4000] Validation [4/4] Loss: 0.68745 focal_loss 0.50700 dice_loss 0.18045 +Epoch [2113/4000] Validation metric {'Val/mean dice_metric': 0.9713912010192871, 'Val/mean miou_metric': 0.9545186161994934, 'Val/mean f1': 0.9733049273490906, 'Val/mean precision': 0.9737698435783386, 'Val/mean recall': 0.972840428352356, 'Val/mean hd95_metric': 6.225689888000488} +Cheakpoint... +Epoch [2113/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713912010192871, 'Val/mean miou_metric': 0.9545186161994934, 'Val/mean f1': 0.9733049273490906, 'Val/mean precision': 0.9737698435783386, 'Val/mean recall': 0.972840428352356, 'Val/mean hd95_metric': 6.225689888000488} +Epoch [2114/4000] Training [1/16] Loss: 0.00532 +Epoch [2114/4000] Training [2/16] Loss: 0.00552 +Epoch [2114/4000] Training [3/16] Loss: 0.00788 +Epoch [2114/4000] Training [4/16] Loss: 0.00604 +Epoch [2114/4000] Training [5/16] Loss: 0.00559 +Epoch [2114/4000] Training [6/16] Loss: 0.00475 +Epoch [2114/4000] Training [7/16] Loss: 0.00739 +Epoch [2114/4000] Training [8/16] Loss: 0.00502 +Epoch [2114/4000] Training [9/16] Loss: 0.00382 +Epoch [2114/4000] Training [10/16] Loss: 0.00597 +Epoch [2114/4000] Training [11/16] Loss: 0.00543 +Epoch [2114/4000] Training [12/16] Loss: 0.00744 +Epoch [2114/4000] Training [13/16] Loss: 0.00637 +Epoch [2114/4000] Training [14/16] Loss: 0.00566 +Epoch [2114/4000] Training [15/16] Loss: 0.00849 +Epoch [2114/4000] Training [16/16] Loss: 0.00494 +Epoch [2114/4000] Training metric {'Train/mean dice_metric': 0.9960225224494934, 'Train/mean miou_metric': 0.9918513894081116, 'Train/mean f1': 0.9918567538261414, 'Train/mean precision': 0.9874157905578613, 'Train/mean recall': 0.9963378310203552, 'Train/mean hd95_metric': 1.079420804977417} +Epoch [2114/4000] Validation [1/4] Loss: 0.39626 focal_loss 0.31731 dice_loss 0.07895 +Epoch [2114/4000] Validation [2/4] Loss: 0.38700 focal_loss 0.25258 dice_loss 0.13442 +Epoch [2114/4000] Validation [3/4] Loss: 0.37040 focal_loss 0.27993 dice_loss 0.09047 +Epoch [2114/4000] Validation [4/4] Loss: 0.28112 focal_loss 0.18097 dice_loss 0.10014 +Epoch [2114/4000] Validation metric {'Val/mean dice_metric': 0.9732096791267395, 'Val/mean miou_metric': 0.9564638137817383, 'Val/mean f1': 0.974725067615509, 'Val/mean precision': 0.9722716212272644, 'Val/mean recall': 0.9771908521652222, 'Val/mean hd95_metric': 5.5053815841674805} +Cheakpoint... +Epoch [2114/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732096791267395, 'Val/mean miou_metric': 0.9564638137817383, 'Val/mean f1': 0.974725067615509, 'Val/mean precision': 0.9722716212272644, 'Val/mean recall': 0.9771908521652222, 'Val/mean hd95_metric': 5.5053815841674805} +Epoch [2115/4000] Training [1/16] Loss: 0.00588 +Epoch [2115/4000] Training [2/16] Loss: 0.00659 +Epoch [2115/4000] Training [3/16] Loss: 0.00663 +Epoch [2115/4000] Training [4/16] Loss: 0.00632 +Epoch [2115/4000] Training [5/16] Loss: 0.00567 +Epoch [2115/4000] Training [6/16] Loss: 0.00701 +Epoch [2115/4000] Training [7/16] Loss: 0.00529 +Epoch [2115/4000] Training [8/16] Loss: 0.00568 +Epoch [2115/4000] Training [9/16] Loss: 0.00407 +Epoch [2115/4000] Training [10/16] Loss: 0.00659 +Epoch [2115/4000] Training [11/16] Loss: 0.00671 +Epoch [2115/4000] Training [12/16] Loss: 0.00479 +Epoch [2115/4000] Training [13/16] Loss: 0.00549 +Epoch [2115/4000] Training [14/16] Loss: 0.00792 +Epoch [2115/4000] Training [15/16] Loss: 0.00528 +Epoch [2115/4000] Training [16/16] Loss: 0.00595 +Epoch [2115/4000] Training metric {'Train/mean dice_metric': 0.9960624575614929, 'Train/mean miou_metric': 0.9918816685676575, 'Train/mean f1': 0.9916590452194214, 'Train/mean precision': 0.9869790077209473, 'Train/mean recall': 0.9963837265968323, 'Train/mean hd95_metric': 1.0025744438171387} +Epoch [2115/4000] Validation [1/4] Loss: 0.32295 focal_loss 0.25611 dice_loss 0.06683 +Epoch [2115/4000] Validation [2/4] Loss: 0.32453 focal_loss 0.21364 dice_loss 0.11089 +Epoch [2115/4000] Validation [3/4] Loss: 0.36659 focal_loss 0.27594 dice_loss 0.09066 +Epoch [2115/4000] Validation [4/4] Loss: 0.27532 focal_loss 0.17680 dice_loss 0.09852 +Epoch [2115/4000] Validation metric {'Val/mean dice_metric': 0.9742617607116699, 'Val/mean miou_metric': 0.9581656455993652, 'Val/mean f1': 0.9753584265708923, 'Val/mean precision': 0.9708775281906128, 'Val/mean recall': 0.9798808693885803, 'Val/mean hd95_metric': 5.622725486755371} +Cheakpoint... +Epoch [2115/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742617607116699, 'Val/mean miou_metric': 0.9581656455993652, 'Val/mean f1': 0.9753584265708923, 'Val/mean precision': 0.9708775281906128, 'Val/mean recall': 0.9798808693885803, 'Val/mean hd95_metric': 5.622725486755371} +Epoch [2116/4000] Training [1/16] Loss: 0.00591 +Epoch [2116/4000] Training [2/16] Loss: 0.00642 +Epoch [2116/4000] Training [3/16] Loss: 0.00615 +Epoch [2116/4000] Training [4/16] Loss: 0.00550 +Epoch [2116/4000] Training [5/16] Loss: 0.00602 +Epoch [2116/4000] Training [6/16] Loss: 0.00550 +Epoch [2116/4000] Training [7/16] Loss: 0.00439 +Epoch [2116/4000] Training [8/16] Loss: 0.00690 +Epoch [2116/4000] Training [9/16] Loss: 0.00583 +Epoch [2116/4000] Training [10/16] Loss: 0.00552 +Epoch [2116/4000] Training [11/16] Loss: 0.00529 +Epoch [2116/4000] Training [12/16] Loss: 0.00531 +Epoch [2116/4000] Training [13/16] Loss: 0.00533 +Epoch [2116/4000] Training [14/16] Loss: 0.00510 +Epoch [2116/4000] Training [15/16] Loss: 0.00490 +Epoch [2116/4000] Training [16/16] Loss: 0.00472 +Epoch [2116/4000] Training metric {'Train/mean dice_metric': 0.9964032173156738, 'Train/mean miou_metric': 0.9925419092178345, 'Train/mean f1': 0.9915497303009033, 'Train/mean precision': 0.9865220785140991, 'Train/mean recall': 0.9966288805007935, 'Train/mean hd95_metric': 0.9930034875869751} +Epoch [2116/4000] Validation [1/4] Loss: 0.33968 focal_loss 0.27180 dice_loss 0.06788 +Epoch [2116/4000] Validation [2/4] Loss: 0.58973 focal_loss 0.39976 dice_loss 0.18997 +Epoch [2116/4000] Validation [3/4] Loss: 0.19614 focal_loss 0.13618 dice_loss 0.05996 +Epoch [2116/4000] Validation [4/4] Loss: 0.44962 focal_loss 0.28736 dice_loss 0.16227 +Epoch [2116/4000] Validation metric {'Val/mean dice_metric': 0.9734816551208496, 'Val/mean miou_metric': 0.9574630856513977, 'Val/mean f1': 0.9746957421302795, 'Val/mean precision': 0.9712247252464294, 'Val/mean recall': 0.9781916737556458, 'Val/mean hd95_metric': 5.39629602432251} +Cheakpoint... +Epoch [2116/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734816551208496, 'Val/mean miou_metric': 0.9574630856513977, 'Val/mean f1': 0.9746957421302795, 'Val/mean precision': 0.9712247252464294, 'Val/mean recall': 0.9781916737556458, 'Val/mean hd95_metric': 5.39629602432251} +Epoch [2117/4000] Training [1/16] Loss: 0.00510 +Epoch [2117/4000] Training [2/16] Loss: 0.00534 +Epoch [2117/4000] Training [3/16] Loss: 0.00494 +Epoch [2117/4000] Training [4/16] Loss: 0.00732 +Epoch [2117/4000] Training [5/16] Loss: 0.00577 +Epoch [2117/4000] Training [6/16] Loss: 0.00500 +Epoch [2117/4000] Training [7/16] Loss: 0.00505 +Epoch [2117/4000] Training [8/16] Loss: 0.00416 +Epoch [2117/4000] Training [9/16] Loss: 0.00666 +Epoch [2117/4000] Training [10/16] Loss: 0.00734 +Epoch [2117/4000] Training [11/16] Loss: 0.00445 +Epoch [2117/4000] Training [12/16] Loss: 0.00509 +Epoch [2117/4000] Training [13/16] Loss: 0.00581 +Epoch [2117/4000] Training [14/16] Loss: 0.00601 +Epoch [2117/4000] Training [15/16] Loss: 0.00501 +Epoch [2117/4000] Training [16/16] Loss: 0.00646 +Epoch [2117/4000] Training metric {'Train/mean dice_metric': 0.996221661567688, 'Train/mean miou_metric': 0.9922049045562744, 'Train/mean f1': 0.9918732047080994, 'Train/mean precision': 0.9873773455619812, 'Train/mean recall': 0.9964101314544678, 'Train/mean hd95_metric': 1.053945541381836} +Epoch [2117/4000] Validation [1/4] Loss: 0.26488 focal_loss 0.20695 dice_loss 0.05793 +Epoch [2117/4000] Validation [2/4] Loss: 0.29592 focal_loss 0.19249 dice_loss 0.10343 +Epoch [2117/4000] Validation [3/4] Loss: 0.43158 focal_loss 0.33166 dice_loss 0.09992 +Epoch [2117/4000] Validation [4/4] Loss: 0.23175 focal_loss 0.15220 dice_loss 0.07956 +Epoch [2117/4000] Validation metric {'Val/mean dice_metric': 0.9738801121711731, 'Val/mean miou_metric': 0.9578485488891602, 'Val/mean f1': 0.9751990437507629, 'Val/mean precision': 0.9702017903327942, 'Val/mean recall': 0.9802479147911072, 'Val/mean hd95_metric': 5.690488815307617} +Cheakpoint... +Epoch [2117/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738801121711731, 'Val/mean miou_metric': 0.9578485488891602, 'Val/mean f1': 0.9751990437507629, 'Val/mean precision': 0.9702017903327942, 'Val/mean recall': 0.9802479147911072, 'Val/mean hd95_metric': 5.690488815307617} +Epoch [2118/4000] Training [1/16] Loss: 0.00519 +Epoch [2118/4000] Training [2/16] Loss: 0.00528 +Epoch [2118/4000] Training [3/16] Loss: 0.00763 +Epoch [2118/4000] Training [4/16] Loss: 0.00520 +Epoch [2118/4000] Training [5/16] Loss: 0.01345 +Epoch [2118/4000] Training [6/16] Loss: 0.00396 +Epoch [2118/4000] Training [7/16] Loss: 0.00390 +Epoch [2118/4000] Training [8/16] Loss: 0.00819 +Epoch [2118/4000] Training [9/16] Loss: 0.00592 +Epoch [2118/4000] Training [10/16] Loss: 0.00756 +Epoch [2118/4000] Training [11/16] Loss: 0.00551 +Epoch [2118/4000] Training [12/16] Loss: 0.00479 +Epoch [2118/4000] Training [13/16] Loss: 0.00562 +Epoch [2118/4000] Training [14/16] Loss: 0.00416 +Epoch [2118/4000] Training [15/16] Loss: 0.00636 +Epoch [2118/4000] Training [16/16] Loss: 0.00520 +Epoch [2118/4000] Training metric {'Train/mean dice_metric': 0.996211051940918, 'Train/mean miou_metric': 0.9921863079071045, 'Train/mean f1': 0.9917271733283997, 'Train/mean precision': 0.9870672821998596, 'Train/mean recall': 0.9964314699172974, 'Train/mean hd95_metric': 1.0384092330932617} +Epoch [2118/4000] Validation [1/4] Loss: 0.28712 focal_loss 0.21795 dice_loss 0.06917 +Epoch [2118/4000] Validation [2/4] Loss: 0.65363 focal_loss 0.41902 dice_loss 0.23461 +Epoch [2118/4000] Validation [3/4] Loss: 0.37366 focal_loss 0.27893 dice_loss 0.09473 +Epoch [2118/4000] Validation [4/4] Loss: 0.35372 focal_loss 0.23253 dice_loss 0.12119 +Epoch [2118/4000] Validation metric {'Val/mean dice_metric': 0.9727476239204407, 'Val/mean miou_metric': 0.9566097259521484, 'Val/mean f1': 0.9745686054229736, 'Val/mean precision': 0.9719584584236145, 'Val/mean recall': 0.977192759513855, 'Val/mean hd95_metric': 5.543845176696777} +Cheakpoint... +Epoch [2118/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727476239204407, 'Val/mean miou_metric': 0.9566097259521484, 'Val/mean f1': 0.9745686054229736, 'Val/mean precision': 0.9719584584236145, 'Val/mean recall': 0.977192759513855, 'Val/mean hd95_metric': 5.543845176696777} +Epoch [2119/4000] Training [1/16] Loss: 0.00533 +Epoch [2119/4000] Training [2/16] Loss: 0.00666 +Epoch [2119/4000] Training [3/16] Loss: 0.00545 +Epoch [2119/4000] Training [4/16] Loss: 0.00566 +Epoch [2119/4000] Training [5/16] Loss: 0.00555 +Epoch [2119/4000] Training [6/16] Loss: 0.00631 +Epoch [2119/4000] Training [7/16] Loss: 0.00413 +Epoch [2119/4000] Training [8/16] Loss: 0.00533 +Epoch [2119/4000] Training [9/16] Loss: 0.00606 +Epoch [2119/4000] Training [10/16] Loss: 0.00515 +Epoch [2119/4000] Training [11/16] Loss: 0.00642 +Epoch [2119/4000] Training [12/16] Loss: 0.00563 +Epoch [2119/4000] Training [13/16] Loss: 0.00496 +Epoch [2119/4000] Training [14/16] Loss: 0.00698 +Epoch [2119/4000] Training [15/16] Loss: 0.00665 +Epoch [2119/4000] Training [16/16] Loss: 0.00558 +Epoch [2119/4000] Training metric {'Train/mean dice_metric': 0.9962644577026367, 'Train/mean miou_metric': 0.9922731518745422, 'Train/mean f1': 0.9915276765823364, 'Train/mean precision': 0.9867429733276367, 'Train/mean recall': 0.9963589906692505, 'Train/mean hd95_metric': 1.0004438161849976} +Epoch [2119/4000] Validation [1/4] Loss: 0.29874 focal_loss 0.23464 dice_loss 0.06410 +Epoch [2119/4000] Validation [2/4] Loss: 0.79796 focal_loss 0.55952 dice_loss 0.23844 +Epoch [2119/4000] Validation [3/4] Loss: 0.30269 focal_loss 0.20757 dice_loss 0.09511 +Epoch [2119/4000] Validation [4/4] Loss: 0.28873 focal_loss 0.18655 dice_loss 0.10218 +Epoch [2119/4000] Validation metric {'Val/mean dice_metric': 0.9715995788574219, 'Val/mean miou_metric': 0.9552251696586609, 'Val/mean f1': 0.9741344451904297, 'Val/mean precision': 0.9711219668388367, 'Val/mean recall': 0.9771657586097717, 'Val/mean hd95_metric': 5.378758907318115} +Cheakpoint... +Epoch [2119/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715995788574219, 'Val/mean miou_metric': 0.9552251696586609, 'Val/mean f1': 0.9741344451904297, 'Val/mean precision': 0.9711219668388367, 'Val/mean recall': 0.9771657586097717, 'Val/mean hd95_metric': 5.378758907318115} +Epoch [2120/4000] Training [1/16] Loss: 0.00458 +Epoch [2120/4000] Training [2/16] Loss: 0.00824 +Epoch [2120/4000] Training [3/16] Loss: 0.00584 +Epoch [2120/4000] Training [4/16] Loss: 0.00767 +Epoch [2120/4000] Training [5/16] Loss: 0.00529 +Epoch [2120/4000] Training [6/16] Loss: 0.00564 +Epoch [2120/4000] Training [7/16] Loss: 0.00658 +Epoch [2120/4000] Training [8/16] Loss: 0.00523 +Epoch [2120/4000] Training [9/16] Loss: 0.00667 +Epoch [2120/4000] Training [10/16] Loss: 0.00681 +Epoch [2120/4000] Training [11/16] Loss: 0.00553 +Epoch [2120/4000] Training [12/16] Loss: 0.00445 +Epoch [2120/4000] Training [13/16] Loss: 0.00466 +Epoch [2120/4000] Training [14/16] Loss: 0.00583 +Epoch [2120/4000] Training [15/16] Loss: 0.01083 +Epoch [2120/4000] Training [16/16] Loss: 0.00556 +Epoch [2120/4000] Training metric {'Train/mean dice_metric': 0.9960653781890869, 'Train/mean miou_metric': 0.9919033050537109, 'Train/mean f1': 0.9916532039642334, 'Train/mean precision': 0.9871567487716675, 'Train/mean recall': 0.9961908459663391, 'Train/mean hd95_metric': 1.0275821685791016} +Epoch [2120/4000] Validation [1/4] Loss: 0.28263 focal_loss 0.22132 dice_loss 0.06131 +Epoch [2120/4000] Validation [2/4] Loss: 0.37919 focal_loss 0.25669 dice_loss 0.12249 +Epoch [2120/4000] Validation [3/4] Loss: 0.36420 focal_loss 0.26564 dice_loss 0.09856 +Epoch [2120/4000] Validation [4/4] Loss: 0.30468 focal_loss 0.19594 dice_loss 0.10874 +Epoch [2120/4000] Validation metric {'Val/mean dice_metric': 0.972996711730957, 'Val/mean miou_metric': 0.9565030932426453, 'Val/mean f1': 0.9742769002914429, 'Val/mean precision': 0.9708495140075684, 'Val/mean recall': 0.9777286052703857, 'Val/mean hd95_metric': 5.482078552246094} +Cheakpoint... +Epoch [2120/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972996711730957, 'Val/mean miou_metric': 0.9565030932426453, 'Val/mean f1': 0.9742769002914429, 'Val/mean precision': 0.9708495140075684, 'Val/mean recall': 0.9777286052703857, 'Val/mean hd95_metric': 5.482078552246094} +Epoch [2121/4000] Training [1/16] Loss: 0.00454 +Epoch [2121/4000] Training [2/16] Loss: 0.00457 +Epoch [2121/4000] Training [3/16] Loss: 0.00425 +Epoch [2121/4000] Training [4/16] Loss: 0.00570 +Epoch [2121/4000] Training [5/16] Loss: 0.01003 +Epoch [2121/4000] Training [6/16] Loss: 0.00535 +Epoch [2121/4000] Training [7/16] Loss: 0.00583 +Epoch [2121/4000] Training [8/16] Loss: 0.00576 +Epoch [2121/4000] Training [9/16] Loss: 0.00597 +Epoch [2121/4000] Training [10/16] Loss: 0.00591 +Epoch [2121/4000] Training [11/16] Loss: 0.00510 +Epoch [2121/4000] Training [12/16] Loss: 0.00502 +Epoch [2121/4000] Training [13/16] Loss: 0.00621 +Epoch [2121/4000] Training [14/16] Loss: 0.00570 +Epoch [2121/4000] Training [15/16] Loss: 0.00547 +Epoch [2121/4000] Training [16/16] Loss: 0.00652 +Epoch [2121/4000] Training metric {'Train/mean dice_metric': 0.9964843988418579, 'Train/mean miou_metric': 0.9927201271057129, 'Train/mean f1': 0.9918320178985596, 'Train/mean precision': 0.986951470375061, 'Train/mean recall': 0.9967610239982605, 'Train/mean hd95_metric': 0.9959816932678223} +Epoch [2121/4000] Validation [1/4] Loss: 0.32822 focal_loss 0.25977 dice_loss 0.06845 +Epoch [2121/4000] Validation [2/4] Loss: 0.34021 focal_loss 0.22976 dice_loss 0.11045 +Epoch [2121/4000] Validation [3/4] Loss: 0.30958 focal_loss 0.21260 dice_loss 0.09698 +Epoch [2121/4000] Validation [4/4] Loss: 0.30756 focal_loss 0.19676 dice_loss 0.11081 +Epoch [2121/4000] Validation metric {'Val/mean dice_metric': 0.9744313359260559, 'Val/mean miou_metric': 0.9583274722099304, 'Val/mean f1': 0.9745193719863892, 'Val/mean precision': 0.9699034690856934, 'Val/mean recall': 0.9791792035102844, 'Val/mean hd95_metric': 5.524664402008057} +Cheakpoint... +Epoch [2121/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744313359260559, 'Val/mean miou_metric': 0.9583274722099304, 'Val/mean f1': 0.9745193719863892, 'Val/mean precision': 0.9699034690856934, 'Val/mean recall': 0.9791792035102844, 'Val/mean hd95_metric': 5.524664402008057} +Epoch [2122/4000] Training [1/16] Loss: 0.00406 +Epoch [2122/4000] Training [2/16] Loss: 0.00528 +Epoch [2122/4000] Training [3/16] Loss: 0.00564 +Epoch [2122/4000] Training [4/16] Loss: 0.00531 +Epoch [2122/4000] Training [5/16] Loss: 0.00536 +Epoch [2122/4000] Training [6/16] Loss: 0.00525 +Epoch [2122/4000] Training [7/16] Loss: 0.00580 +Epoch [2122/4000] Training [8/16] Loss: 0.00488 +Epoch [2122/4000] Training [9/16] Loss: 0.00484 +Epoch [2122/4000] Training [10/16] Loss: 0.00476 +Epoch [2122/4000] Training [11/16] Loss: 0.00431 +Epoch [2122/4000] Training [12/16] Loss: 0.00650 +Epoch [2122/4000] Training [13/16] Loss: 0.00438 +Epoch [2122/4000] Training [14/16] Loss: 0.00680 +Epoch [2122/4000] Training [15/16] Loss: 0.00412 +Epoch [2122/4000] Training [16/16] Loss: 0.00452 +Epoch [2122/4000] Training metric {'Train/mean dice_metric': 0.9966612458229065, 'Train/mean miou_metric': 0.9930785894393921, 'Train/mean f1': 0.9921895861625671, 'Train/mean precision': 0.9876945614814758, 'Train/mean recall': 0.9967257976531982, 'Train/mean hd95_metric': 0.9876110553741455} +Epoch [2122/4000] Validation [1/4] Loss: 0.24797 focal_loss 0.18713 dice_loss 0.06084 +Epoch [2122/4000] Validation [2/4] Loss: 0.34890 focal_loss 0.23767 dice_loss 0.11123 +Epoch [2122/4000] Validation [3/4] Loss: 0.35527 focal_loss 0.25758 dice_loss 0.09768 +Epoch [2122/4000] Validation [4/4] Loss: 0.38203 focal_loss 0.26360 dice_loss 0.11842 +Epoch [2122/4000] Validation metric {'Val/mean dice_metric': 0.9743587374687195, 'Val/mean miou_metric': 0.958551287651062, 'Val/mean f1': 0.975554347038269, 'Val/mean precision': 0.9719411730766296, 'Val/mean recall': 0.9791944622993469, 'Val/mean hd95_metric': 5.645696640014648} +Cheakpoint... +Epoch [2122/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743587374687195, 'Val/mean miou_metric': 0.958551287651062, 'Val/mean f1': 0.975554347038269, 'Val/mean precision': 0.9719411730766296, 'Val/mean recall': 0.9791944622993469, 'Val/mean hd95_metric': 5.645696640014648} +Epoch [2123/4000] Training [1/16] Loss: 0.00716 +Epoch [2123/4000] Training [2/16] Loss: 0.00365 +Epoch [2123/4000] Training [3/16] Loss: 0.00645 +Epoch [2123/4000] Training [4/16] Loss: 0.00541 +Epoch [2123/4000] Training [5/16] Loss: 0.00445 +Epoch [2123/4000] Training [6/16] Loss: 0.00442 +Epoch [2123/4000] Training [7/16] Loss: 0.00598 +Epoch [2123/4000] Training [8/16] Loss: 0.00514 +Epoch [2123/4000] Training [9/16] Loss: 0.00641 +Epoch [2123/4000] Training [10/16] Loss: 0.00512 +Epoch [2123/4000] Training [11/16] Loss: 0.00482 +Epoch [2123/4000] Training [12/16] Loss: 0.00428 +Epoch [2123/4000] Training [13/16] Loss: 0.00375 +Epoch [2123/4000] Training [14/16] Loss: 0.00339 +Epoch [2123/4000] Training [15/16] Loss: 0.00507 +Epoch [2123/4000] Training [16/16] Loss: 0.00404 +Epoch [2123/4000] Training metric {'Train/mean dice_metric': 0.9967649579048157, 'Train/mean miou_metric': 0.9932639002799988, 'Train/mean f1': 0.9920971989631653, 'Train/mean precision': 0.9874725341796875, 'Train/mean recall': 0.9967653155326843, 'Train/mean hd95_metric': 0.9949496388435364} +Epoch [2123/4000] Validation [1/4] Loss: 0.29587 focal_loss 0.22987 dice_loss 0.06599 +Epoch [2123/4000] Validation [2/4] Loss: 0.61069 focal_loss 0.42437 dice_loss 0.18632 +Epoch [2123/4000] Validation [3/4] Loss: 0.34923 focal_loss 0.25021 dice_loss 0.09901 +Epoch [2123/4000] Validation [4/4] Loss: 0.45789 focal_loss 0.31613 dice_loss 0.14176 +Epoch [2123/4000] Validation metric {'Val/mean dice_metric': 0.9736531376838684, 'Val/mean miou_metric': 0.9582401514053345, 'Val/mean f1': 0.9751643538475037, 'Val/mean precision': 0.9711975455284119, 'Val/mean recall': 0.9791637063026428, 'Val/mean hd95_metric': 5.067042827606201} +Cheakpoint... +Epoch [2123/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736531376838684, 'Val/mean miou_metric': 0.9582401514053345, 'Val/mean f1': 0.9751643538475037, 'Val/mean precision': 0.9711975455284119, 'Val/mean recall': 0.9791637063026428, 'Val/mean hd95_metric': 5.067042827606201} +Epoch [2124/4000] Training [1/16] Loss: 0.00682 +Epoch [2124/4000] Training [2/16] Loss: 0.00538 +Epoch [2124/4000] Training [3/16] Loss: 0.00502 +Epoch [2124/4000] Training [4/16] Loss: 0.00622 +Epoch [2124/4000] Training [5/16] Loss: 0.00400 +Epoch [2124/4000] Training [6/16] Loss: 0.00486 +Epoch [2124/4000] Training [7/16] Loss: 0.00444 +Epoch [2124/4000] Training [8/16] Loss: 0.00564 +Epoch [2124/4000] Training [9/16] Loss: 0.00571 +Epoch [2124/4000] Training [10/16] Loss: 0.00559 +Epoch [2124/4000] Training [11/16] Loss: 0.00440 +Epoch [2124/4000] Training [12/16] Loss: 0.00483 +Epoch [2124/4000] Training [13/16] Loss: 0.00520 +Epoch [2124/4000] Training [14/16] Loss: 0.00441 +Epoch [2124/4000] Training [15/16] Loss: 0.00646 +Epoch [2124/4000] Training [16/16] Loss: 0.00627 +Epoch [2124/4000] Training metric {'Train/mean dice_metric': 0.9963522553443909, 'Train/mean miou_metric': 0.9924584627151489, 'Train/mean f1': 0.9918532967567444, 'Train/mean precision': 0.9870770573616028, 'Train/mean recall': 0.996675968170166, 'Train/mean hd95_metric': 1.0046839714050293} +Epoch [2124/4000] Validation [1/4] Loss: 0.30123 focal_loss 0.23763 dice_loss 0.06360 +Epoch [2124/4000] Validation [2/4] Loss: 0.60560 focal_loss 0.42288 dice_loss 0.18272 +Epoch [2124/4000] Validation [3/4] Loss: 0.35773 focal_loss 0.26639 dice_loss 0.09135 +Epoch [2124/4000] Validation [4/4] Loss: 0.22321 focal_loss 0.14342 dice_loss 0.07979 +Epoch [2124/4000] Validation metric {'Val/mean dice_metric': 0.9739227294921875, 'Val/mean miou_metric': 0.958477795124054, 'Val/mean f1': 0.9754977822303772, 'Val/mean precision': 0.9714479446411133, 'Val/mean recall': 0.9795815348625183, 'Val/mean hd95_metric': 4.899481296539307} +Cheakpoint... +Epoch [2124/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739227294921875, 'Val/mean miou_metric': 0.958477795124054, 'Val/mean f1': 0.9754977822303772, 'Val/mean precision': 0.9714479446411133, 'Val/mean recall': 0.9795815348625183, 'Val/mean hd95_metric': 4.899481296539307} +Epoch [2125/4000] Training [1/16] Loss: 0.00593 +Epoch [2125/4000] Training [2/16] Loss: 0.00587 +Epoch [2125/4000] Training [3/16] Loss: 0.00645 +Epoch [2125/4000] Training [4/16] Loss: 0.00478 +Epoch [2125/4000] Training [5/16] Loss: 0.00556 +Epoch [2125/4000] Training [6/16] Loss: 0.00516 +Epoch [2125/4000] Training [7/16] Loss: 0.00527 +Epoch [2125/4000] Training [8/16] Loss: 0.00617 +Epoch [2125/4000] Training [9/16] Loss: 0.00541 +Epoch [2125/4000] Training [10/16] Loss: 0.00531 +Epoch [2125/4000] Training [11/16] Loss: 0.00933 +Epoch [2125/4000] Training [12/16] Loss: 0.00738 +Epoch [2125/4000] Training [13/16] Loss: 0.00453 +Epoch [2125/4000] Training [14/16] Loss: 0.00499 +Epoch [2125/4000] Training [15/16] Loss: 0.00587 +Epoch [2125/4000] Training [16/16] Loss: 0.00477 +Epoch [2125/4000] Training metric {'Train/mean dice_metric': 0.9962283968925476, 'Train/mean miou_metric': 0.992228090763092, 'Train/mean f1': 0.9919599294662476, 'Train/mean precision': 0.9873660206794739, 'Train/mean recall': 0.9965968132019043, 'Train/mean hd95_metric': 1.0338038206100464} +Epoch [2125/4000] Validation [1/4] Loss: 0.30100 focal_loss 0.23708 dice_loss 0.06393 +Epoch [2125/4000] Validation [2/4] Loss: 0.57576 focal_loss 0.41985 dice_loss 0.15592 +Epoch [2125/4000] Validation [3/4] Loss: 0.21842 focal_loss 0.14199 dice_loss 0.07644 +Epoch [2125/4000] Validation [4/4] Loss: 0.33914 focal_loss 0.21633 dice_loss 0.12281 +Epoch [2125/4000] Validation metric {'Val/mean dice_metric': 0.9735007286071777, 'Val/mean miou_metric': 0.9568365216255188, 'Val/mean f1': 0.9749346971511841, 'Val/mean precision': 0.9703168272972107, 'Val/mean recall': 0.9795967936515808, 'Val/mean hd95_metric': 5.694171905517578} +Cheakpoint... +Epoch [2125/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735007286071777, 'Val/mean miou_metric': 0.9568365216255188, 'Val/mean f1': 0.9749346971511841, 'Val/mean precision': 0.9703168272972107, 'Val/mean recall': 0.9795967936515808, 'Val/mean hd95_metric': 5.694171905517578} +Epoch [2126/4000] Training [1/16] Loss: 0.00421 +Epoch [2126/4000] Training [2/16] Loss: 0.00496 +Epoch [2126/4000] Training [3/16] Loss: 0.00591 +Epoch [2126/4000] Training [4/16] Loss: 0.00469 +Epoch [2126/4000] Training [5/16] Loss: 0.00623 +Epoch [2126/4000] Training [6/16] Loss: 0.00572 +Epoch [2126/4000] Training [7/16] Loss: 0.00821 +Epoch [2126/4000] Training [8/16] Loss: 0.00548 +Epoch [2126/4000] Training [9/16] Loss: 0.00493 +Epoch [2126/4000] Training [10/16] Loss: 0.00606 +Epoch [2126/4000] Training [11/16] Loss: 0.00517 +Epoch [2126/4000] Training [12/16] Loss: 0.00721 +Epoch [2126/4000] Training [13/16] Loss: 0.00852 +Epoch [2126/4000] Training [14/16] Loss: 0.00458 +Epoch [2126/4000] Training [15/16] Loss: 0.00469 +Epoch [2126/4000] Training [16/16] Loss: 0.00471 +Epoch [2126/4000] Training metric {'Train/mean dice_metric': 0.9962296485900879, 'Train/mean miou_metric': 0.9922027587890625, 'Train/mean f1': 0.9913231730461121, 'Train/mean precision': 0.9864105582237244, 'Train/mean recall': 0.9962849617004395, 'Train/mean hd95_metric': 1.012453317642212} +Epoch [2126/4000] Validation [1/4] Loss: 0.33247 focal_loss 0.26581 dice_loss 0.06666 +Epoch [2126/4000] Validation [2/4] Loss: 0.43174 focal_loss 0.27915 dice_loss 0.15259 +Epoch [2126/4000] Validation [3/4] Loss: 0.37765 focal_loss 0.28429 dice_loss 0.09335 +Epoch [2126/4000] Validation [4/4] Loss: 0.23066 focal_loss 0.13642 dice_loss 0.09424 +Epoch [2126/4000] Validation metric {'Val/mean dice_metric': 0.9740577936172485, 'Val/mean miou_metric': 0.9576257467269897, 'Val/mean f1': 0.9737248420715332, 'Val/mean precision': 0.9678268432617188, 'Val/mean recall': 0.979695200920105, 'Val/mean hd95_metric': 5.540131568908691} +Cheakpoint... +Epoch [2126/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740577936172485, 'Val/mean miou_metric': 0.9576257467269897, 'Val/mean f1': 0.9737248420715332, 'Val/mean precision': 0.9678268432617188, 'Val/mean recall': 0.979695200920105, 'Val/mean hd95_metric': 5.540131568908691} +Epoch [2127/4000] Training [1/16] Loss: 0.00397 +Epoch [2127/4000] Training [2/16] Loss: 0.00489 +Epoch [2127/4000] Training [3/16] Loss: 0.00674 +Epoch [2127/4000] Training [4/16] Loss: 0.00473 +Epoch [2127/4000] Training [5/16] Loss: 0.00478 +Epoch [2127/4000] Training [6/16] Loss: 0.00594 +Epoch [2127/4000] Training [7/16] Loss: 0.00538 +Epoch [2127/4000] Training [8/16] Loss: 0.00682 +Epoch [2127/4000] Training [9/16] Loss: 0.00519 +Epoch [2127/4000] Training [10/16] Loss: 0.00520 +Epoch [2127/4000] Training [11/16] Loss: 0.00673 +Epoch [2127/4000] Training [12/16] Loss: 0.00465 +Epoch [2127/4000] Training [13/16] Loss: 0.00686 +Epoch [2127/4000] Training [14/16] Loss: 0.00453 +Epoch [2127/4000] Training [15/16] Loss: 0.00671 +Epoch [2127/4000] Training [16/16] Loss: 0.00553 +Epoch [2127/4000] Training metric {'Train/mean dice_metric': 0.996312141418457, 'Train/mean miou_metric': 0.9923834204673767, 'Train/mean f1': 0.9919683933258057, 'Train/mean precision': 0.9874700903892517, 'Train/mean recall': 0.9965078830718994, 'Train/mean hd95_metric': 1.0833971500396729} +Epoch [2127/4000] Validation [1/4] Loss: 0.25419 focal_loss 0.19106 dice_loss 0.06313 +Epoch [2127/4000] Validation [2/4] Loss: 0.42588 focal_loss 0.30749 dice_loss 0.11838 +Epoch [2127/4000] Validation [3/4] Loss: 0.20346 focal_loss 0.14360 dice_loss 0.05986 +Epoch [2127/4000] Validation [4/4] Loss: 0.31859 focal_loss 0.20539 dice_loss 0.11320 +Epoch [2127/4000] Validation metric {'Val/mean dice_metric': 0.9712745547294617, 'Val/mean miou_metric': 0.9548928141593933, 'Val/mean f1': 0.9741478562355042, 'Val/mean precision': 0.9726089239120483, 'Val/mean recall': 0.9756914973258972, 'Val/mean hd95_metric': 5.559631824493408} +Cheakpoint... +Epoch [2127/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712745547294617, 'Val/mean miou_metric': 0.9548928141593933, 'Val/mean f1': 0.9741478562355042, 'Val/mean precision': 0.9726089239120483, 'Val/mean recall': 0.9756914973258972, 'Val/mean hd95_metric': 5.559631824493408} +Epoch [2128/4000] Training [1/16] Loss: 0.00541 +Epoch [2128/4000] Training [2/16] Loss: 0.00562 +Epoch [2128/4000] Training [3/16] Loss: 0.00863 +Epoch [2128/4000] Training [4/16] Loss: 0.00695 +Epoch [2128/4000] Training [5/16] Loss: 0.00607 +Epoch [2128/4000] Training [6/16] Loss: 0.00556 +Epoch [2128/4000] Training [7/16] Loss: 0.00734 +Epoch [2128/4000] Training [8/16] Loss: 0.00649 +Epoch [2128/4000] Training [9/16] Loss: 0.00807 +Epoch [2128/4000] Training [10/16] Loss: 0.00637 +Epoch [2128/4000] Training [11/16] Loss: 0.00630 +Epoch [2128/4000] Training [12/16] Loss: 0.00495 +Epoch [2128/4000] Training [13/16] Loss: 0.00607 +Epoch [2128/4000] Training [14/16] Loss: 0.00480 +Epoch [2128/4000] Training [15/16] Loss: 0.00650 +Epoch [2128/4000] Training [16/16] Loss: 0.00428 +Epoch [2128/4000] Training metric {'Train/mean dice_metric': 0.9958333969116211, 'Train/mean miou_metric': 0.9914418458938599, 'Train/mean f1': 0.9916897416114807, 'Train/mean precision': 0.9871689677238464, 'Train/mean recall': 0.9962521195411682, 'Train/mean hd95_metric': 1.0013865232467651} +Epoch [2128/4000] Validation [1/4] Loss: 0.31073 focal_loss 0.24223 dice_loss 0.06850 +Epoch [2128/4000] Validation [2/4] Loss: 0.45088 focal_loss 0.29898 dice_loss 0.15190 +Epoch [2128/4000] Validation [3/4] Loss: 0.21316 focal_loss 0.14764 dice_loss 0.06552 +Epoch [2128/4000] Validation [4/4] Loss: 0.25496 focal_loss 0.14161 dice_loss 0.11335 +Epoch [2128/4000] Validation metric {'Val/mean dice_metric': 0.9701796770095825, 'Val/mean miou_metric': 0.9537078738212585, 'Val/mean f1': 0.9746879935264587, 'Val/mean precision': 0.9738641977310181, 'Val/mean recall': 0.9755131602287292, 'Val/mean hd95_metric': 5.064912796020508} +Cheakpoint... +Epoch [2128/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701796770095825, 'Val/mean miou_metric': 0.9537078738212585, 'Val/mean f1': 0.9746879935264587, 'Val/mean precision': 0.9738641977310181, 'Val/mean recall': 0.9755131602287292, 'Val/mean hd95_metric': 5.064912796020508} +Epoch [2129/4000] Training [1/16] Loss: 0.00519 +Epoch [2129/4000] Training [2/16] Loss: 0.00647 +Epoch [2129/4000] Training [3/16] Loss: 0.00485 +Epoch [2129/4000] Training [4/16] Loss: 0.00440 +Epoch [2129/4000] Training [5/16] Loss: 0.00808 +Epoch [2129/4000] Training [6/16] Loss: 0.00479 +Epoch [2129/4000] Training [7/16] Loss: 0.00565 +Epoch [2129/4000] Training [8/16] Loss: 0.00473 +Epoch [2129/4000] Training [9/16] Loss: 0.00580 +Epoch [2129/4000] Training [10/16] Loss: 0.00731 +Epoch [2129/4000] Training [11/16] Loss: 0.00609 +Epoch [2129/4000] Training [12/16] Loss: 0.00631 +Epoch [2129/4000] Training [13/16] Loss: 0.00427 +Epoch [2129/4000] Training [14/16] Loss: 0.00517 +Epoch [2129/4000] Training [15/16] Loss: 0.00637 +Epoch [2129/4000] Training [16/16] Loss: 0.00580 +Epoch [2129/4000] Training metric {'Train/mean dice_metric': 0.9962625503540039, 'Train/mean miou_metric': 0.992295503616333, 'Train/mean f1': 0.9919486045837402, 'Train/mean precision': 0.9874606728553772, 'Train/mean recall': 0.9964775443077087, 'Train/mean hd95_metric': 1.0027893781661987} +Epoch [2129/4000] Validation [1/4] Loss: 0.25407 focal_loss 0.19409 dice_loss 0.05998 +Epoch [2129/4000] Validation [2/4] Loss: 0.67691 focal_loss 0.47922 dice_loss 0.19769 +Epoch [2129/4000] Validation [3/4] Loss: 0.21193 focal_loss 0.14652 dice_loss 0.06541 +Epoch [2129/4000] Validation [4/4] Loss: 0.25943 focal_loss 0.16017 dice_loss 0.09925 +Epoch [2129/4000] Validation metric {'Val/mean dice_metric': 0.9712217450141907, 'Val/mean miou_metric': 0.9551668167114258, 'Val/mean f1': 0.9748623371124268, 'Val/mean precision': 0.974979817867279, 'Val/mean recall': 0.974744975566864, 'Val/mean hd95_metric': 4.728604316711426} +Cheakpoint... +Epoch [2129/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712217450141907, 'Val/mean miou_metric': 0.9551668167114258, 'Val/mean f1': 0.9748623371124268, 'Val/mean precision': 0.974979817867279, 'Val/mean recall': 0.974744975566864, 'Val/mean hd95_metric': 4.728604316711426} +Epoch [2130/4000] Training [1/16] Loss: 0.00488 +Epoch [2130/4000] Training [2/16] Loss: 0.00544 +Epoch [2130/4000] Training [3/16] Loss: 0.00547 +Epoch [2130/4000] Training [4/16] Loss: 0.00536 +Epoch [2130/4000] Training [5/16] Loss: 0.00506 +Epoch [2130/4000] Training [6/16] Loss: 0.00420 +Epoch [2130/4000] Training [7/16] Loss: 0.00634 +Epoch [2130/4000] Training [8/16] Loss: 0.00510 +Epoch [2130/4000] Training [9/16] Loss: 0.00512 +Epoch [2130/4000] Training [10/16] Loss: 0.00423 +Epoch [2130/4000] Training [11/16] Loss: 0.00487 +Epoch [2130/4000] Training [12/16] Loss: 0.00498 +Epoch [2130/4000] Training [13/16] Loss: 0.00413 +Epoch [2130/4000] Training [14/16] Loss: 0.00577 +Epoch [2130/4000] Training [15/16] Loss: 0.00509 +Epoch [2130/4000] Training [16/16] Loss: 0.00489 +Epoch [2130/4000] Training metric {'Train/mean dice_metric': 0.9967013597488403, 'Train/mean miou_metric': 0.9931564331054688, 'Train/mean f1': 0.9921751022338867, 'Train/mean precision': 0.987590491771698, 'Train/mean recall': 0.996802568435669, 'Train/mean hd95_metric': 0.9929543733596802} +Epoch [2130/4000] Validation [1/4] Loss: 0.28037 focal_loss 0.21401 dice_loss 0.06635 +Epoch [2130/4000] Validation [2/4] Loss: 0.39162 focal_loss 0.27696 dice_loss 0.11465 +Epoch [2130/4000] Validation [3/4] Loss: 0.19855 focal_loss 0.13606 dice_loss 0.06249 +Epoch [2130/4000] Validation [4/4] Loss: 0.24329 focal_loss 0.13870 dice_loss 0.10459 +Epoch [2130/4000] Validation metric {'Val/mean dice_metric': 0.9751527905464172, 'Val/mean miou_metric': 0.9590568542480469, 'Val/mean f1': 0.9753504991531372, 'Val/mean precision': 0.9729921817779541, 'Val/mean recall': 0.9777203798294067, 'Val/mean hd95_metric': 4.677420139312744} +Cheakpoint... +Epoch [2130/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751527905464172, 'Val/mean miou_metric': 0.9590568542480469, 'Val/mean f1': 0.9753504991531372, 'Val/mean precision': 0.9729921817779541, 'Val/mean recall': 0.9777203798294067, 'Val/mean hd95_metric': 4.677420139312744} +Epoch [2131/4000] Training [1/16] Loss: 0.00503 +Epoch [2131/4000] Training [2/16] Loss: 0.00589 +Epoch [2131/4000] Training [3/16] Loss: 0.00867 +Epoch [2131/4000] Training [4/16] Loss: 0.00564 +Epoch [2131/4000] Training [5/16] Loss: 0.00446 +Epoch [2131/4000] Training [6/16] Loss: 0.00410 +Epoch [2131/4000] Training [7/16] Loss: 0.00531 +Epoch [2131/4000] Training [8/16] Loss: 0.00462 +Epoch [2131/4000] Training [9/16] Loss: 0.00404 +Epoch [2131/4000] Training [10/16] Loss: 0.00602 +Epoch [2131/4000] Training [11/16] Loss: 0.00689 +Epoch [2131/4000] Training [12/16] Loss: 0.00401 +Epoch [2131/4000] Training [13/16] Loss: 0.00456 +Epoch [2131/4000] Training [14/16] Loss: 0.00456 +Epoch [2131/4000] Training [15/16] Loss: 0.00571 +Epoch [2131/4000] Training [16/16] Loss: 0.00338 +Epoch [2131/4000] Training metric {'Train/mean dice_metric': 0.9965022802352905, 'Train/mean miou_metric': 0.9927284717559814, 'Train/mean f1': 0.9914315342903137, 'Train/mean precision': 0.9862871170043945, 'Train/mean recall': 0.9966298937797546, 'Train/mean hd95_metric': 0.9976181983947754} +Epoch [2131/4000] Validation [1/4] Loss: 0.25299 focal_loss 0.19623 dice_loss 0.05676 +Epoch [2131/4000] Validation [2/4] Loss: 0.40744 focal_loss 0.28728 dice_loss 0.12016 +Epoch [2131/4000] Validation [3/4] Loss: 0.23241 focal_loss 0.16875 dice_loss 0.06366 +Epoch [2131/4000] Validation [4/4] Loss: 0.35928 focal_loss 0.23873 dice_loss 0.12054 +Epoch [2131/4000] Validation metric {'Val/mean dice_metric': 0.9746543765068054, 'Val/mean miou_metric': 0.9584819078445435, 'Val/mean f1': 0.9750522375106812, 'Val/mean precision': 0.9718189239501953, 'Val/mean recall': 0.97830730676651, 'Val/mean hd95_metric': 4.694207191467285} +Cheakpoint... +Epoch [2131/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746543765068054, 'Val/mean miou_metric': 0.9584819078445435, 'Val/mean f1': 0.9750522375106812, 'Val/mean precision': 0.9718189239501953, 'Val/mean recall': 0.97830730676651, 'Val/mean hd95_metric': 4.694207191467285} +Epoch [2132/4000] Training [1/16] Loss: 0.00430 +Epoch [2132/4000] Training [2/16] Loss: 0.00545 +Epoch [2132/4000] Training [3/16] Loss: 0.00562 +Epoch [2132/4000] Training [4/16] Loss: 0.00474 +Epoch [2132/4000] Training [5/16] Loss: 0.00385 +Epoch [2132/4000] Training [6/16] Loss: 0.00467 +Epoch [2132/4000] Training [7/16] Loss: 0.00513 +Epoch [2132/4000] Training [8/16] Loss: 0.00521 +Epoch [2132/4000] Training [9/16] Loss: 0.00424 +Epoch [2132/4000] Training [10/16] Loss: 0.00696 +Epoch [2132/4000] Training [11/16] Loss: 0.00420 +Epoch [2132/4000] Training [12/16] Loss: 0.00573 +Epoch [2132/4000] Training [13/16] Loss: 0.00971 +Epoch [2132/4000] Training [14/16] Loss: 0.00729 +Epoch [2132/4000] Training [15/16] Loss: 0.00903 +Epoch [2132/4000] Training [16/16] Loss: 0.00631 +Epoch [2132/4000] Training metric {'Train/mean dice_metric': 0.9962114095687866, 'Train/mean miou_metric': 0.9921849966049194, 'Train/mean f1': 0.991969883441925, 'Train/mean precision': 0.9874123930931091, 'Train/mean recall': 0.9965695738792419, 'Train/mean hd95_metric': 1.0055049657821655} +Epoch [2132/4000] Validation [1/4] Loss: 0.31425 focal_loss 0.24747 dice_loss 0.06678 +Epoch [2132/4000] Validation [2/4] Loss: 0.37800 focal_loss 0.27219 dice_loss 0.10581 +Epoch [2132/4000] Validation [3/4] Loss: 0.23844 focal_loss 0.17363 dice_loss 0.06480 +Epoch [2132/4000] Validation [4/4] Loss: 0.38316 focal_loss 0.26147 dice_loss 0.12170 +Epoch [2132/4000] Validation metric {'Val/mean dice_metric': 0.9737755060195923, 'Val/mean miou_metric': 0.9571658968925476, 'Val/mean f1': 0.9751399159431458, 'Val/mean precision': 0.9732328057289124, 'Val/mean recall': 0.9770547151565552, 'Val/mean hd95_metric': 4.868330001831055} +Cheakpoint... +Epoch [2132/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737755060195923, 'Val/mean miou_metric': 0.9571658968925476, 'Val/mean f1': 0.9751399159431458, 'Val/mean precision': 0.9732328057289124, 'Val/mean recall': 0.9770547151565552, 'Val/mean hd95_metric': 4.868330001831055} +Epoch [2133/4000] Training [1/16] Loss: 0.00543 +Epoch [2133/4000] Training [2/16] Loss: 0.00447 +Epoch [2133/4000] Training [3/16] Loss: 0.00606 +Epoch [2133/4000] Training [4/16] Loss: 0.00624 +Epoch [2133/4000] Training [5/16] Loss: 0.00875 +Epoch [2133/4000] Training [6/16] Loss: 0.00550 +Epoch [2133/4000] Training [7/16] Loss: 0.00524 +Epoch [2133/4000] Training [8/16] Loss: 0.00614 +Epoch [2133/4000] Training [9/16] Loss: 0.00455 +Epoch [2133/4000] Training [10/16] Loss: 0.00898 +Epoch [2133/4000] Training [11/16] Loss: 0.00410 +Epoch [2133/4000] Training [12/16] Loss: 0.00501 +Epoch [2133/4000] Training [13/16] Loss: 0.00497 +Epoch [2133/4000] Training [14/16] Loss: 0.00565 +Epoch [2133/4000] Training [15/16] Loss: 0.00520 +Epoch [2133/4000] Training [16/16] Loss: 0.00655 +Epoch [2133/4000] Training metric {'Train/mean dice_metric': 0.9961022138595581, 'Train/mean miou_metric': 0.9919817447662354, 'Train/mean f1': 0.9917958378791809, 'Train/mean precision': 0.9872591495513916, 'Train/mean recall': 0.9963744282722473, 'Train/mean hd95_metric': 1.03053879737854} +Epoch [2133/4000] Validation [1/4] Loss: 0.27668 focal_loss 0.20590 dice_loss 0.07078 +Epoch [2133/4000] Validation [2/4] Loss: 0.73450 focal_loss 0.52865 dice_loss 0.20586 +Epoch [2133/4000] Validation [3/4] Loss: 0.22442 focal_loss 0.15424 dice_loss 0.07017 +Epoch [2133/4000] Validation [4/4] Loss: 0.32414 focal_loss 0.21932 dice_loss 0.10482 +Epoch [2133/4000] Validation metric {'Val/mean dice_metric': 0.9717074632644653, 'Val/mean miou_metric': 0.955756664276123, 'Val/mean f1': 0.9744581580162048, 'Val/mean precision': 0.9738823771476746, 'Val/mean recall': 0.975034773349762, 'Val/mean hd95_metric': 5.5720133781433105} +Cheakpoint... +Epoch [2133/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717074632644653, 'Val/mean miou_metric': 0.955756664276123, 'Val/mean f1': 0.9744581580162048, 'Val/mean precision': 0.9738823771476746, 'Val/mean recall': 0.975034773349762, 'Val/mean hd95_metric': 5.5720133781433105} +Epoch [2134/4000] Training [1/16] Loss: 0.00440 +Epoch [2134/4000] Training [2/16] Loss: 0.00443 +Epoch [2134/4000] Training [3/16] Loss: 0.00485 +Epoch [2134/4000] Training [4/16] Loss: 0.00743 +Epoch [2134/4000] Training [5/16] Loss: 0.00502 +Epoch [2134/4000] Training [6/16] Loss: 0.00617 +Epoch [2134/4000] Training [7/16] Loss: 0.00547 +Epoch [2134/4000] Training [8/16] Loss: 0.00542 +Epoch [2134/4000] Training [9/16] Loss: 0.00666 +Epoch [2134/4000] Training [10/16] Loss: 0.00553 +Epoch [2134/4000] Training [11/16] Loss: 0.00566 +Epoch [2134/4000] Training [12/16] Loss: 0.00553 +Epoch [2134/4000] Training [13/16] Loss: 0.00787 +Epoch [2134/4000] Training [14/16] Loss: 0.00544 +Epoch [2134/4000] Training [15/16] Loss: 0.00600 +Epoch [2134/4000] Training [16/16] Loss: 0.00670 +Epoch [2134/4000] Training metric {'Train/mean dice_metric': 0.9962927103042603, 'Train/mean miou_metric': 0.992335319519043, 'Train/mean f1': 0.9918503165245056, 'Train/mean precision': 0.987097442150116, 'Train/mean recall': 0.9966492652893066, 'Train/mean hd95_metric': 0.9899270534515381} +Epoch [2134/4000] Validation [1/4] Loss: 0.44157 focal_loss 0.35280 dice_loss 0.08877 +Epoch [2134/4000] Validation [2/4] Loss: 0.69618 focal_loss 0.50408 dice_loss 0.19210 +Epoch [2134/4000] Validation [3/4] Loss: 0.21271 focal_loss 0.14488 dice_loss 0.06783 +Epoch [2134/4000] Validation [4/4] Loss: 0.29282 focal_loss 0.18572 dice_loss 0.10710 +Epoch [2134/4000] Validation metric {'Val/mean dice_metric': 0.9741657376289368, 'Val/mean miou_metric': 0.9576290845870972, 'Val/mean f1': 0.9745156168937683, 'Val/mean precision': 0.9733356237411499, 'Val/mean recall': 0.9756985306739807, 'Val/mean hd95_metric': 5.108853816986084} +Cheakpoint... +Epoch [2134/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741657376289368, 'Val/mean miou_metric': 0.9576290845870972, 'Val/mean f1': 0.9745156168937683, 'Val/mean precision': 0.9733356237411499, 'Val/mean recall': 0.9756985306739807, 'Val/mean hd95_metric': 5.108853816986084} +Epoch [2135/4000] Training [1/16] Loss: 0.00533 +Epoch [2135/4000] Training [2/16] Loss: 0.00557 +Epoch [2135/4000] Training [3/16] Loss: 0.00819 +Epoch [2135/4000] Training [4/16] Loss: 0.00416 +Epoch [2135/4000] Training [5/16] Loss: 0.01145 +Epoch [2135/4000] Training [6/16] Loss: 0.00576 +Epoch [2135/4000] Training [7/16] Loss: 0.00791 +Epoch [2135/4000] Training [8/16] Loss: 0.00636 +Epoch [2135/4000] Training [9/16] Loss: 0.00560 +Epoch [2135/4000] Training [10/16] Loss: 0.00453 +Epoch [2135/4000] Training [11/16] Loss: 0.00837 +Epoch [2135/4000] Training [12/16] Loss: 0.00545 +Epoch [2135/4000] Training [13/16] Loss: 0.00486 +Epoch [2135/4000] Training [14/16] Loss: 0.00663 +Epoch [2135/4000] Training [15/16] Loss: 0.00558 +Epoch [2135/4000] Training [16/16] Loss: 0.00607 +Epoch [2135/4000] Training metric {'Train/mean dice_metric': 0.9959823489189148, 'Train/mean miou_metric': 0.9917290806770325, 'Train/mean f1': 0.9917134642601013, 'Train/mean precision': 0.9872128963470459, 'Train/mean recall': 0.9962553381919861, 'Train/mean hd95_metric': 1.0084354877471924} +Epoch [2135/4000] Validation [1/4] Loss: 0.33784 focal_loss 0.25214 dice_loss 0.08570 +Epoch [2135/4000] Validation [2/4] Loss: 0.64163 focal_loss 0.45448 dice_loss 0.18715 +Epoch [2135/4000] Validation [3/4] Loss: 0.29502 focal_loss 0.19576 dice_loss 0.09925 +Epoch [2135/4000] Validation [4/4] Loss: 0.36264 focal_loss 0.23513 dice_loss 0.12751 +Epoch [2135/4000] Validation metric {'Val/mean dice_metric': 0.97291100025177, 'Val/mean miou_metric': 0.955988883972168, 'Val/mean f1': 0.9738352298736572, 'Val/mean precision': 0.9732857346534729, 'Val/mean recall': 0.9743852615356445, 'Val/mean hd95_metric': 5.2413330078125} +Cheakpoint... +Epoch [2135/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97291100025177, 'Val/mean miou_metric': 0.955988883972168, 'Val/mean f1': 0.9738352298736572, 'Val/mean precision': 0.9732857346534729, 'Val/mean recall': 0.9743852615356445, 'Val/mean hd95_metric': 5.2413330078125} +Epoch [2136/4000] Training [1/16] Loss: 0.00490 +Epoch [2136/4000] Training [2/16] Loss: 0.00555 +Epoch [2136/4000] Training [3/16] Loss: 0.00654 +Epoch [2136/4000] Training [4/16] Loss: 0.00604 +Epoch [2136/4000] Training [5/16] Loss: 0.00556 +Epoch [2136/4000] Training [6/16] Loss: 0.00524 +Epoch [2136/4000] Training [7/16] Loss: 0.00603 +Epoch [2136/4000] Training [8/16] Loss: 0.00606 +Epoch [2136/4000] Training [9/16] Loss: 0.00572 +Epoch [2136/4000] Training [10/16] Loss: 0.00654 +Epoch [2136/4000] Training [11/16] Loss: 0.00587 +Epoch [2136/4000] Training [12/16] Loss: 0.00541 +Epoch [2136/4000] Training [13/16] Loss: 0.01011 +Epoch [2136/4000] Training [14/16] Loss: 0.00552 +Epoch [2136/4000] Training [15/16] Loss: 0.00697 +Epoch [2136/4000] Training [16/16] Loss: 0.00522 +Epoch [2136/4000] Training metric {'Train/mean dice_metric': 0.9959502220153809, 'Train/mean miou_metric': 0.9916796684265137, 'Train/mean f1': 0.9918677806854248, 'Train/mean precision': 0.9873693585395813, 'Train/mean recall': 0.9964073896408081, 'Train/mean hd95_metric': 1.0391932725906372} +Epoch [2136/4000] Validation [1/4] Loss: 0.22482 focal_loss 0.16742 dice_loss 0.05740 +Epoch [2136/4000] Validation [2/4] Loss: 0.40080 focal_loss 0.27910 dice_loss 0.12170 +Epoch [2136/4000] Validation [3/4] Loss: 0.29084 focal_loss 0.20087 dice_loss 0.08997 +Epoch [2136/4000] Validation [4/4] Loss: 0.24284 focal_loss 0.16006 dice_loss 0.08278 +Epoch [2136/4000] Validation metric {'Val/mean dice_metric': 0.9736455678939819, 'Val/mean miou_metric': 0.9574041366577148, 'Val/mean f1': 0.975216269493103, 'Val/mean precision': 0.9727118611335754, 'Val/mean recall': 0.9777336120605469, 'Val/mean hd95_metric': 5.446252822875977} +Cheakpoint... +Epoch [2136/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736455678939819, 'Val/mean miou_metric': 0.9574041366577148, 'Val/mean f1': 0.975216269493103, 'Val/mean precision': 0.9727118611335754, 'Val/mean recall': 0.9777336120605469, 'Val/mean hd95_metric': 5.446252822875977} +Epoch [2137/4000] Training [1/16] Loss: 0.00492 +Epoch [2137/4000] Training [2/16] Loss: 0.00595 +Epoch [2137/4000] Training [3/16] Loss: 0.00540 +Epoch [2137/4000] Training [4/16] Loss: 0.00486 +Epoch [2137/4000] Training [5/16] Loss: 0.00575 +Epoch [2137/4000] Training [6/16] Loss: 0.00417 +Epoch [2137/4000] Training [7/16] Loss: 0.00497 +Epoch [2137/4000] Training [8/16] Loss: 0.00542 +Epoch [2137/4000] Training [9/16] Loss: 0.00602 +Epoch [2137/4000] Training [10/16] Loss: 0.00592 +Epoch [2137/4000] Training [11/16] Loss: 0.00593 +Epoch [2137/4000] Training [12/16] Loss: 0.00426 +Epoch [2137/4000] Training [13/16] Loss: 0.01067 +Epoch [2137/4000] Training [14/16] Loss: 0.00459 +Epoch [2137/4000] Training [15/16] Loss: 0.00574 +Epoch [2137/4000] Training [16/16] Loss: 0.00542 +Epoch [2137/4000] Training metric {'Train/mean dice_metric': 0.9963521957397461, 'Train/mean miou_metric': 0.9924707412719727, 'Train/mean f1': 0.9920217990875244, 'Train/mean precision': 0.987495481967926, 'Train/mean recall': 0.9965897798538208, 'Train/mean hd95_metric': 1.0029889345169067} +Epoch [2137/4000] Validation [1/4] Loss: 0.25318 focal_loss 0.19511 dice_loss 0.05807 +Epoch [2137/4000] Validation [2/4] Loss: 0.76971 focal_loss 0.53121 dice_loss 0.23850 +Epoch [2137/4000] Validation [3/4] Loss: 0.38338 focal_loss 0.28954 dice_loss 0.09384 +Epoch [2137/4000] Validation [4/4] Loss: 0.27494 focal_loss 0.17368 dice_loss 0.10126 +Epoch [2137/4000] Validation metric {'Val/mean dice_metric': 0.9724507331848145, 'Val/mean miou_metric': 0.9564632177352905, 'Val/mean f1': 0.9745907783508301, 'Val/mean precision': 0.9710890650749207, 'Val/mean recall': 0.9781178832054138, 'Val/mean hd95_metric': 6.110918045043945} +Cheakpoint... +Epoch [2137/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724507331848145, 'Val/mean miou_metric': 0.9564632177352905, 'Val/mean f1': 0.9745907783508301, 'Val/mean precision': 0.9710890650749207, 'Val/mean recall': 0.9781178832054138, 'Val/mean hd95_metric': 6.110918045043945} +Epoch [2138/4000] Training [1/16] Loss: 0.00408 +Epoch [2138/4000] Training [2/16] Loss: 0.00515 +Epoch [2138/4000] Training [3/16] Loss: 0.00598 +Epoch [2138/4000] Training [4/16] Loss: 0.00889 +Epoch [2138/4000] Training [5/16] Loss: 0.00603 +Epoch [2138/4000] Training [6/16] Loss: 0.00437 +Epoch [2138/4000] Training [7/16] Loss: 0.00739 +Epoch [2138/4000] Training [8/16] Loss: 0.00520 +Epoch [2138/4000] Training [9/16] Loss: 0.00500 +Epoch [2138/4000] Training [10/16] Loss: 0.00548 +Epoch [2138/4000] Training [11/16] Loss: 0.00726 +Epoch [2138/4000] Training [12/16] Loss: 0.00529 +Epoch [2138/4000] Training [13/16] Loss: 0.00619 +Epoch [2138/4000] Training [14/16] Loss: 0.00675 +Epoch [2138/4000] Training [15/16] Loss: 0.00714 +Epoch [2138/4000] Training [16/16] Loss: 0.00562 +Epoch [2138/4000] Training metric {'Train/mean dice_metric': 0.9963458180427551, 'Train/mean miou_metric': 0.9924519062042236, 'Train/mean f1': 0.9920996427536011, 'Train/mean precision': 0.9875657558441162, 'Train/mean recall': 0.9966753721237183, 'Train/mean hd95_metric': 0.9998601675033569} +Epoch [2138/4000] Validation [1/4] Loss: 0.26522 focal_loss 0.20215 dice_loss 0.06307 +Epoch [2138/4000] Validation [2/4] Loss: 0.53556 focal_loss 0.34012 dice_loss 0.19544 +Epoch [2138/4000] Validation [3/4] Loss: 0.34598 focal_loss 0.24922 dice_loss 0.09676 +Epoch [2138/4000] Validation [4/4] Loss: 0.34949 focal_loss 0.24701 dice_loss 0.10247 +Epoch [2138/4000] Validation metric {'Val/mean dice_metric': 0.9721983075141907, 'Val/mean miou_metric': 0.9561246037483215, 'Val/mean f1': 0.9740225076675415, 'Val/mean precision': 0.9719395637512207, 'Val/mean recall': 0.9761141538619995, 'Val/mean hd95_metric': 5.769725799560547} +Cheakpoint... +Epoch [2138/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721983075141907, 'Val/mean miou_metric': 0.9561246037483215, 'Val/mean f1': 0.9740225076675415, 'Val/mean precision': 0.9719395637512207, 'Val/mean recall': 0.9761141538619995, 'Val/mean hd95_metric': 5.769725799560547} +Epoch [2139/4000] Training [1/16] Loss: 0.00451 +Epoch [2139/4000] Training [2/16] Loss: 0.00356 +Epoch [2139/4000] Training [3/16] Loss: 0.00533 +Epoch [2139/4000] Training [4/16] Loss: 0.00442 +Epoch [2139/4000] Training [5/16] Loss: 0.00560 +Epoch [2139/4000] Training [6/16] Loss: 0.00492 +Epoch [2139/4000] Training [7/16] Loss: 0.00585 +Epoch [2139/4000] Training [8/16] Loss: 0.00567 +Epoch [2139/4000] Training [9/16] Loss: 0.00557 +Epoch [2139/4000] Training [10/16] Loss: 0.00466 +Epoch [2139/4000] Training [11/16] Loss: 0.00587 +Epoch [2139/4000] Training [12/16] Loss: 0.00653 +Epoch [2139/4000] Training [13/16] Loss: 0.00474 +Epoch [2139/4000] Training [14/16] Loss: 0.00661 +Epoch [2139/4000] Training [15/16] Loss: 0.00680 +Epoch [2139/4000] Training [16/16] Loss: 0.00491 +Epoch [2139/4000] Training metric {'Train/mean dice_metric': 0.9962188005447388, 'Train/mean miou_metric': 0.992181658744812, 'Train/mean f1': 0.9914675951004028, 'Train/mean precision': 0.9864196181297302, 'Train/mean recall': 0.9965674877166748, 'Train/mean hd95_metric': 0.9962751865386963} +Epoch [2139/4000] Validation [1/4] Loss: 0.27312 focal_loss 0.20888 dice_loss 0.06424 +Epoch [2139/4000] Validation [2/4] Loss: 0.43933 focal_loss 0.29437 dice_loss 0.14496 +Epoch [2139/4000] Validation [3/4] Loss: 0.24020 focal_loss 0.15653 dice_loss 0.08367 +Epoch [2139/4000] Validation [4/4] Loss: 0.51278 focal_loss 0.35911 dice_loss 0.15367 +Epoch [2139/4000] Validation metric {'Val/mean dice_metric': 0.9717171788215637, 'Val/mean miou_metric': 0.9545750617980957, 'Val/mean f1': 0.973210871219635, 'Val/mean precision': 0.9716759324073792, 'Val/mean recall': 0.9747506976127625, 'Val/mean hd95_metric': 5.672046661376953} +Cheakpoint... +Epoch [2139/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717171788215637, 'Val/mean miou_metric': 0.9545750617980957, 'Val/mean f1': 0.973210871219635, 'Val/mean precision': 0.9716759324073792, 'Val/mean recall': 0.9747506976127625, 'Val/mean hd95_metric': 5.672046661376953} +Epoch [2140/4000] Training [1/16] Loss: 0.00492 +Epoch [2140/4000] Training [2/16] Loss: 0.00530 +Epoch [2140/4000] Training [3/16] Loss: 0.00426 +Epoch [2140/4000] Training [4/16] Loss: 0.00611 +Epoch [2140/4000] Training [5/16] Loss: 0.00352 +Epoch [2140/4000] Training [6/16] Loss: 0.00590 +Epoch [2140/4000] Training [7/16] Loss: 0.00652 +Epoch [2140/4000] Training [8/16] Loss: 0.00463 +Epoch [2140/4000] Training [9/16] Loss: 0.00436 +Epoch [2140/4000] Training [10/16] Loss: 0.00609 +Epoch [2140/4000] Training [11/16] Loss: 0.00532 +Epoch [2140/4000] Training [12/16] Loss: 0.00844 +Epoch [2140/4000] Training [13/16] Loss: 0.00418 +Epoch [2140/4000] Training [14/16] Loss: 0.00451 +Epoch [2140/4000] Training [15/16] Loss: 0.00577 +Epoch [2140/4000] Training [16/16] Loss: 0.00587 +Epoch [2140/4000] Training metric {'Train/mean dice_metric': 0.9965075254440308, 'Train/mean miou_metric': 0.9927763938903809, 'Train/mean f1': 0.9921697378158569, 'Train/mean precision': 0.9877921938896179, 'Train/mean recall': 0.996586263179779, 'Train/mean hd95_metric': 1.0027344226837158} +Epoch [2140/4000] Validation [1/4] Loss: 0.30901 focal_loss 0.23950 dice_loss 0.06950 +Epoch [2140/4000] Validation [2/4] Loss: 0.58113 focal_loss 0.38961 dice_loss 0.19152 +Epoch [2140/4000] Validation [3/4] Loss: 0.33012 focal_loss 0.23666 dice_loss 0.09346 +Epoch [2140/4000] Validation [4/4] Loss: 0.37794 focal_loss 0.24178 dice_loss 0.13616 +Epoch [2140/4000] Validation metric {'Val/mean dice_metric': 0.97278892993927, 'Val/mean miou_metric': 0.9565435647964478, 'Val/mean f1': 0.9746987223625183, 'Val/mean precision': 0.9728528261184692, 'Val/mean recall': 0.9765515327453613, 'Val/mean hd95_metric': 5.3293986320495605} +Cheakpoint... +Epoch [2140/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97278892993927, 'Val/mean miou_metric': 0.9565435647964478, 'Val/mean f1': 0.9746987223625183, 'Val/mean precision': 0.9728528261184692, 'Val/mean recall': 0.9765515327453613, 'Val/mean hd95_metric': 5.3293986320495605} +Epoch [2141/4000] Training [1/16] Loss: 0.00618 +Epoch [2141/4000] Training [2/16] Loss: 0.00475 +Epoch [2141/4000] Training [3/16] Loss: 0.00371 +Epoch [2141/4000] Training [4/16] Loss: 0.00465 +Epoch [2141/4000] Training [5/16] Loss: 0.00587 +Epoch [2141/4000] Training [6/16] Loss: 0.00523 +Epoch [2141/4000] Training [7/16] Loss: 0.00393 +Epoch [2141/4000] Training [8/16] Loss: 0.00511 +Epoch [2141/4000] Training [9/16] Loss: 0.00447 +Epoch [2141/4000] Training [10/16] Loss: 0.00520 +Epoch [2141/4000] Training [11/16] Loss: 0.00744 +Epoch [2141/4000] Training [12/16] Loss: 0.00557 +Epoch [2141/4000] Training [13/16] Loss: 0.00651 +Epoch [2141/4000] Training [14/16] Loss: 0.00526 +Epoch [2141/4000] Training [15/16] Loss: 0.00682 +Epoch [2141/4000] Training [16/16] Loss: 0.00506 +Epoch [2141/4000] Training metric {'Train/mean dice_metric': 0.9964385628700256, 'Train/mean miou_metric': 0.9926242232322693, 'Train/mean f1': 0.9918197989463806, 'Train/mean precision': 0.9870356917381287, 'Train/mean recall': 0.9966505169868469, 'Train/mean hd95_metric': 1.0046019554138184} +Epoch [2141/4000] Validation [1/4] Loss: 0.33830 focal_loss 0.27017 dice_loss 0.06813 +Epoch [2141/4000] Validation [2/4] Loss: 0.59181 focal_loss 0.40066 dice_loss 0.19115 +Epoch [2141/4000] Validation [3/4] Loss: 0.21239 focal_loss 0.15219 dice_loss 0.06020 +Epoch [2141/4000] Validation [4/4] Loss: 0.28768 focal_loss 0.18537 dice_loss 0.10231 +Epoch [2141/4000] Validation metric {'Val/mean dice_metric': 0.9744470715522766, 'Val/mean miou_metric': 0.9581667184829712, 'Val/mean f1': 0.9749454259872437, 'Val/mean precision': 0.9719860553741455, 'Val/mean recall': 0.9779229164123535, 'Val/mean hd95_metric': 5.3366780281066895} +Cheakpoint... +Epoch [2141/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744470715522766, 'Val/mean miou_metric': 0.9581667184829712, 'Val/mean f1': 0.9749454259872437, 'Val/mean precision': 0.9719860553741455, 'Val/mean recall': 0.9779229164123535, 'Val/mean hd95_metric': 5.3366780281066895} +Epoch [2142/4000] Training [1/16] Loss: 0.00492 +Epoch [2142/4000] Training [2/16] Loss: 0.00553 +Epoch [2142/4000] Training [3/16] Loss: 0.00696 +Epoch [2142/4000] Training [4/16] Loss: 0.00519 +Epoch [2142/4000] Training [5/16] Loss: 0.00548 +Epoch [2142/4000] Training [6/16] Loss: 0.00739 +Epoch [2142/4000] Training [7/16] Loss: 0.00604 +Epoch [2142/4000] Training [8/16] Loss: 0.00553 +Epoch [2142/4000] Training [9/16] Loss: 0.00483 +Epoch [2142/4000] Training [10/16] Loss: 0.00608 +Epoch [2142/4000] Training [11/16] Loss: 0.00392 +Epoch [2142/4000] Training [12/16] Loss: 0.00542 +Epoch [2142/4000] Training [13/16] Loss: 0.00679 +Epoch [2142/4000] Training [14/16] Loss: 0.00381 +Epoch [2142/4000] Training [15/16] Loss: 0.00505 +Epoch [2142/4000] Training [16/16] Loss: 0.00515 +Epoch [2142/4000] Training metric {'Train/mean dice_metric': 0.9962987899780273, 'Train/mean miou_metric': 0.9923659563064575, 'Train/mean f1': 0.9920611381530762, 'Train/mean precision': 0.9876189827919006, 'Train/mean recall': 0.9965434074401855, 'Train/mean hd95_metric': 1.0008248090744019} +Epoch [2142/4000] Validation [1/4] Loss: 0.26739 focal_loss 0.20440 dice_loss 0.06299 +Epoch [2142/4000] Validation [2/4] Loss: 0.39363 focal_loss 0.27390 dice_loss 0.11973 +Epoch [2142/4000] Validation [3/4] Loss: 0.31207 focal_loss 0.21577 dice_loss 0.09631 +Epoch [2142/4000] Validation [4/4] Loss: 0.29150 focal_loss 0.19024 dice_loss 0.10126 +Epoch [2142/4000] Validation metric {'Val/mean dice_metric': 0.971531093120575, 'Val/mean miou_metric': 0.9553925395011902, 'Val/mean f1': 0.974010169506073, 'Val/mean precision': 0.9716590046882629, 'Val/mean recall': 0.9763725996017456, 'Val/mean hd95_metric': 5.746523857116699} +Cheakpoint... +Epoch [2142/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971531093120575, 'Val/mean miou_metric': 0.9553925395011902, 'Val/mean f1': 0.974010169506073, 'Val/mean precision': 0.9716590046882629, 'Val/mean recall': 0.9763725996017456, 'Val/mean hd95_metric': 5.746523857116699} +Epoch [2143/4000] Training [1/16] Loss: 0.00560 +Epoch [2143/4000] Training [2/16] Loss: 0.00553 +Epoch [2143/4000] Training [3/16] Loss: 0.00638 +Epoch [2143/4000] Training [4/16] Loss: 0.00669 +Epoch [2143/4000] Training [5/16] Loss: 0.00445 +Epoch [2143/4000] Training [6/16] Loss: 0.00609 +Epoch [2143/4000] Training [7/16] Loss: 0.00570 +Epoch [2143/4000] Training [8/16] Loss: 0.00501 +Epoch [2143/4000] Training [9/16] Loss: 0.00532 +Epoch [2143/4000] Training [10/16] Loss: 0.00537 +Epoch [2143/4000] Training [11/16] Loss: 0.00416 +Epoch [2143/4000] Training [12/16] Loss: 0.00630 +Epoch [2143/4000] Training [13/16] Loss: 0.00575 +Epoch [2143/4000] Training [14/16] Loss: 0.00646 +Epoch [2143/4000] Training [15/16] Loss: 0.00420 +Epoch [2143/4000] Training [16/16] Loss: 0.00595 +Epoch [2143/4000] Training metric {'Train/mean dice_metric': 0.9964941740036011, 'Train/mean miou_metric': 0.9927393794059753, 'Train/mean f1': 0.9920800924301147, 'Train/mean precision': 0.9874607920646667, 'Train/mean recall': 0.9967427849769592, 'Train/mean hd95_metric': 0.9921032190322876} +Epoch [2143/4000] Validation [1/4] Loss: 0.34613 focal_loss 0.27543 dice_loss 0.07070 +Epoch [2143/4000] Validation [2/4] Loss: 0.40685 focal_loss 0.28087 dice_loss 0.12598 +Epoch [2143/4000] Validation [3/4] Loss: 0.35447 focal_loss 0.26061 dice_loss 0.09386 +Epoch [2143/4000] Validation [4/4] Loss: 0.28346 focal_loss 0.18197 dice_loss 0.10150 +Epoch [2143/4000] Validation metric {'Val/mean dice_metric': 0.9740927815437317, 'Val/mean miou_metric': 0.9578449130058289, 'Val/mean f1': 0.9749253392219543, 'Val/mean precision': 0.9725163578987122, 'Val/mean recall': 0.9773462414741516, 'Val/mean hd95_metric': 5.320208549499512} +Cheakpoint... +Epoch [2143/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740927815437317, 'Val/mean miou_metric': 0.9578449130058289, 'Val/mean f1': 0.9749253392219543, 'Val/mean precision': 0.9725163578987122, 'Val/mean recall': 0.9773462414741516, 'Val/mean hd95_metric': 5.320208549499512} +Epoch [2144/4000] Training [1/16] Loss: 0.00479 +Epoch [2144/4000] Training [2/16] Loss: 0.00418 +Epoch [2144/4000] Training [3/16] Loss: 0.00710 +Epoch [2144/4000] Training [4/16] Loss: 0.00712 +Epoch [2144/4000] Training [5/16] Loss: 0.00538 +Epoch [2144/4000] Training [6/16] Loss: 0.00588 +Epoch [2144/4000] Training [7/16] Loss: 0.00548 +Epoch [2144/4000] Training [8/16] Loss: 0.00707 +Epoch [2144/4000] Training [9/16] Loss: 0.00480 +Epoch [2144/4000] Training [10/16] Loss: 0.00412 +Epoch [2144/4000] Training [11/16] Loss: 0.00490 +Epoch [2144/4000] Training [12/16] Loss: 0.00561 +Epoch [2144/4000] Training [13/16] Loss: 0.00410 +Epoch [2144/4000] Training [14/16] Loss: 0.00620 +Epoch [2144/4000] Training [15/16] Loss: 0.00685 +Epoch [2144/4000] Training [16/16] Loss: 0.00540 +Epoch [2144/4000] Training metric {'Train/mean dice_metric': 0.9964001178741455, 'Train/mean miou_metric': 0.9925558567047119, 'Train/mean f1': 0.9918506741523743, 'Train/mean precision': 0.9871706366539001, 'Train/mean recall': 0.9965754747390747, 'Train/mean hd95_metric': 0.9815788865089417} +Epoch [2144/4000] Validation [1/4] Loss: 0.29277 focal_loss 0.22911 dice_loss 0.06367 +Epoch [2144/4000] Validation [2/4] Loss: 0.39920 focal_loss 0.27697 dice_loss 0.12224 +Epoch [2144/4000] Validation [3/4] Loss: 0.37920 focal_loss 0.28530 dice_loss 0.09390 +Epoch [2144/4000] Validation [4/4] Loss: 0.33711 focal_loss 0.22047 dice_loss 0.11664 +Epoch [2144/4000] Validation metric {'Val/mean dice_metric': 0.9731571078300476, 'Val/mean miou_metric': 0.9568306803703308, 'Val/mean f1': 0.9741681218147278, 'Val/mean precision': 0.9714599847793579, 'Val/mean recall': 0.9768913984298706, 'Val/mean hd95_metric': 5.514817714691162} +Cheakpoint... +Epoch [2144/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731571078300476, 'Val/mean miou_metric': 0.9568306803703308, 'Val/mean f1': 0.9741681218147278, 'Val/mean precision': 0.9714599847793579, 'Val/mean recall': 0.9768913984298706, 'Val/mean hd95_metric': 5.514817714691162} +Epoch [2145/4000] Training [1/16] Loss: 0.00615 +Epoch [2145/4000] Training [2/16] Loss: 0.00617 +Epoch [2145/4000] Training [3/16] Loss: 0.00581 +Epoch [2145/4000] Training [4/16] Loss: 0.00461 +Epoch [2145/4000] Training [5/16] Loss: 0.00677 +Epoch [2145/4000] Training [6/16] Loss: 0.00416 +Epoch [2145/4000] Training [7/16] Loss: 0.00523 +Epoch [2145/4000] Training [8/16] Loss: 0.00526 +Epoch [2145/4000] Training [9/16] Loss: 0.00609 +Epoch [2145/4000] Training [10/16] Loss: 0.00667 +Epoch [2145/4000] Training [11/16] Loss: 0.00638 +Epoch [2145/4000] Training [12/16] Loss: 0.00590 +Epoch [2145/4000] Training [13/16] Loss: 0.00510 +Epoch [2145/4000] Training [14/16] Loss: 0.00449 +Epoch [2145/4000] Training [15/16] Loss: 0.00533 +Epoch [2145/4000] Training [16/16] Loss: 0.00448 +Epoch [2145/4000] Training metric {'Train/mean dice_metric': 0.9963788390159607, 'Train/mean miou_metric': 0.992513120174408, 'Train/mean f1': 0.9919084310531616, 'Train/mean precision': 0.9873109459877014, 'Train/mean recall': 0.9965488910675049, 'Train/mean hd95_metric': 1.0039186477661133} +Epoch [2145/4000] Validation [1/4] Loss: 0.27301 focal_loss 0.21234 dice_loss 0.06068 +Epoch [2145/4000] Validation [2/4] Loss: 0.46279 focal_loss 0.30189 dice_loss 0.16090 +Epoch [2145/4000] Validation [3/4] Loss: 0.19877 focal_loss 0.13679 dice_loss 0.06198 +Epoch [2145/4000] Validation [4/4] Loss: 0.25832 focal_loss 0.16975 dice_loss 0.08857 +Epoch [2145/4000] Validation metric {'Val/mean dice_metric': 0.9731746912002563, 'Val/mean miou_metric': 0.956895649433136, 'Val/mean f1': 0.9749355316162109, 'Val/mean precision': 0.972822368144989, 'Val/mean recall': 0.9770578145980835, 'Val/mean hd95_metric': 5.148313522338867} +Cheakpoint... +Epoch [2145/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731746912002563, 'Val/mean miou_metric': 0.956895649433136, 'Val/mean f1': 0.9749355316162109, 'Val/mean precision': 0.972822368144989, 'Val/mean recall': 0.9770578145980835, 'Val/mean hd95_metric': 5.148313522338867} +Epoch [2146/4000] Training [1/16] Loss: 0.00438 +Epoch [2146/4000] Training [2/16] Loss: 0.00518 +Epoch [2146/4000] Training [3/16] Loss: 0.00456 +Epoch [2146/4000] Training [4/16] Loss: 0.00423 +Epoch [2146/4000] Training [5/16] Loss: 0.00805 +Epoch [2146/4000] Training [6/16] Loss: 0.00432 +Epoch [2146/4000] Training [7/16] Loss: 0.00479 +Epoch [2146/4000] Training [8/16] Loss: 0.00488 +Epoch [2146/4000] Training [9/16] Loss: 0.00508 +Epoch [2146/4000] Training [10/16] Loss: 0.00406 +Epoch [2146/4000] Training [11/16] Loss: 0.00585 +Epoch [2146/4000] Training [12/16] Loss: 0.00709 +Epoch [2146/4000] Training [13/16] Loss: 0.00453 +Epoch [2146/4000] Training [14/16] Loss: 0.00715 +Epoch [2146/4000] Training [15/16] Loss: 0.00478 +Epoch [2146/4000] Training [16/16] Loss: 0.00607 +Epoch [2146/4000] Training metric {'Train/mean dice_metric': 0.9965595602989197, 'Train/mean miou_metric': 0.9928818941116333, 'Train/mean f1': 0.9921228885650635, 'Train/mean precision': 0.9876320362091064, 'Train/mean recall': 0.9966548085212708, 'Train/mean hd95_metric': 1.0857645273208618} +Epoch [2146/4000] Validation [1/4] Loss: 0.25459 focal_loss 0.19815 dice_loss 0.05644 +Epoch [2146/4000] Validation [2/4] Loss: 0.59347 focal_loss 0.40269 dice_loss 0.19078 +Epoch [2146/4000] Validation [3/4] Loss: 0.19975 focal_loss 0.13784 dice_loss 0.06191 +Epoch [2146/4000] Validation [4/4] Loss: 0.23824 focal_loss 0.15149 dice_loss 0.08676 +Epoch [2146/4000] Validation metric {'Val/mean dice_metric': 0.9724006652832031, 'Val/mean miou_metric': 0.9571515917778015, 'Val/mean f1': 0.9758404493331909, 'Val/mean precision': 0.9743048548698425, 'Val/mean recall': 0.9773808717727661, 'Val/mean hd95_metric': 5.363283634185791} +Cheakpoint... +Epoch [2146/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724006652832031, 'Val/mean miou_metric': 0.9571515917778015, 'Val/mean f1': 0.9758404493331909, 'Val/mean precision': 0.9743048548698425, 'Val/mean recall': 0.9773808717727661, 'Val/mean hd95_metric': 5.363283634185791} +Epoch [2147/4000] Training [1/16] Loss: 0.00552 +Epoch [2147/4000] Training [2/16] Loss: 0.00483 +Epoch [2147/4000] Training [3/16] Loss: 0.00582 +Epoch [2147/4000] Training [4/16] Loss: 0.00661 +Epoch [2147/4000] Training [5/16] Loss: 0.00680 +Epoch [2147/4000] Training [6/16] Loss: 0.00477 +Epoch [2147/4000] Training [7/16] Loss: 0.00730 +Epoch [2147/4000] Training [8/16] Loss: 0.00635 +Epoch [2147/4000] Training [9/16] Loss: 0.00605 +Epoch [2147/4000] Training [10/16] Loss: 0.00486 +Epoch [2147/4000] Training [11/16] Loss: 0.00676 +Epoch [2147/4000] Training [12/16] Loss: 0.00985 +Epoch [2147/4000] Training [13/16] Loss: 0.00462 +Epoch [2147/4000] Training [14/16] Loss: 0.00475 +Epoch [2147/4000] Training [15/16] Loss: 0.00501 +Epoch [2147/4000] Training [16/16] Loss: 0.00495 +Epoch [2147/4000] Training metric {'Train/mean dice_metric': 0.9961130023002625, 'Train/mean miou_metric': 0.9919942617416382, 'Train/mean f1': 0.9917835593223572, 'Train/mean precision': 0.9871526956558228, 'Train/mean recall': 0.996458113193512, 'Train/mean hd95_metric': 1.019644021987915} +Epoch [2147/4000] Validation [1/4] Loss: 0.30532 focal_loss 0.23380 dice_loss 0.07152 +Epoch [2147/4000] Validation [2/4] Loss: 0.80534 focal_loss 0.53650 dice_loss 0.26884 +Epoch [2147/4000] Validation [3/4] Loss: 0.38738 focal_loss 0.29230 dice_loss 0.09508 +Epoch [2147/4000] Validation [4/4] Loss: 0.29590 focal_loss 0.18200 dice_loss 0.11389 +Epoch [2147/4000] Validation metric {'Val/mean dice_metric': 0.969720721244812, 'Val/mean miou_metric': 0.9531014561653137, 'Val/mean f1': 0.9736701846122742, 'Val/mean precision': 0.9711788296699524, 'Val/mean recall': 0.9761743545532227, 'Val/mean hd95_metric': 5.901176452636719} +Cheakpoint... +Epoch [2147/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969720721244812, 'Val/mean miou_metric': 0.9531014561653137, 'Val/mean f1': 0.9736701846122742, 'Val/mean precision': 0.9711788296699524, 'Val/mean recall': 0.9761743545532227, 'Val/mean hd95_metric': 5.901176452636719} +Epoch [2148/4000] Training [1/16] Loss: 0.00527 +Epoch [2148/4000] Training [2/16] Loss: 0.00656 +Epoch [2148/4000] Training [3/16] Loss: 0.00550 +Epoch [2148/4000] Training [4/16] Loss: 0.00514 +Epoch [2148/4000] Training [5/16] Loss: 0.00557 +Epoch [2148/4000] Training [6/16] Loss: 0.00572 +Epoch [2148/4000] Training [7/16] Loss: 0.00438 +Epoch [2148/4000] Training [8/16] Loss: 0.00484 +Epoch [2148/4000] Training [9/16] Loss: 0.00485 +Epoch [2148/4000] Training [10/16] Loss: 0.00522 +Epoch [2148/4000] Training [11/16] Loss: 0.00562 +Epoch [2148/4000] Training [12/16] Loss: 0.00465 +Epoch [2148/4000] Training [13/16] Loss: 0.00441 +Epoch [2148/4000] Training [14/16] Loss: 0.00607 +Epoch [2148/4000] Training [15/16] Loss: 0.00603 +Epoch [2148/4000] Training [16/16] Loss: 0.00696 +Epoch [2148/4000] Training metric {'Train/mean dice_metric': 0.9963624477386475, 'Train/mean miou_metric': 0.9924765229225159, 'Train/mean f1': 0.9919804930686951, 'Train/mean precision': 0.9873005747795105, 'Train/mean recall': 0.9967049956321716, 'Train/mean hd95_metric': 0.9957586526870728} +Epoch [2148/4000] Validation [1/4] Loss: 0.25217 focal_loss 0.19689 dice_loss 0.05529 +Epoch [2148/4000] Validation [2/4] Loss: 0.37898 focal_loss 0.25975 dice_loss 0.11923 +Epoch [2148/4000] Validation [3/4] Loss: 0.25959 focal_loss 0.17565 dice_loss 0.08394 +Epoch [2148/4000] Validation [4/4] Loss: 0.37193 focal_loss 0.23218 dice_loss 0.13975 +Epoch [2148/4000] Validation metric {'Val/mean dice_metric': 0.9737785458564758, 'Val/mean miou_metric': 0.9570335149765015, 'Val/mean f1': 0.9739367365837097, 'Val/mean precision': 0.9716517925262451, 'Val/mean recall': 0.9762324690818787, 'Val/mean hd95_metric': 5.652675628662109} +Cheakpoint... +Epoch [2148/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737785458564758, 'Val/mean miou_metric': 0.9570335149765015, 'Val/mean f1': 0.9739367365837097, 'Val/mean precision': 0.9716517925262451, 'Val/mean recall': 0.9762324690818787, 'Val/mean hd95_metric': 5.652675628662109} +Epoch [2149/4000] Training [1/16] Loss: 0.00658 +Epoch [2149/4000] Training [2/16] Loss: 0.00500 +Epoch [2149/4000] Training [3/16] Loss: 0.00497 +Epoch [2149/4000] Training [4/16] Loss: 0.00372 +Epoch [2149/4000] Training [5/16] Loss: 0.00476 +Epoch [2149/4000] Training [6/16] Loss: 0.00707 +Epoch [2149/4000] Training [7/16] Loss: 0.00594 +Epoch [2149/4000] Training [8/16] Loss: 0.00379 +Epoch [2149/4000] Training [9/16] Loss: 0.00610 +Epoch [2149/4000] Training [10/16] Loss: 0.00509 +Epoch [2149/4000] Training [11/16] Loss: 0.00565 +Epoch [2149/4000] Training [12/16] Loss: 0.00512 +Epoch [2149/4000] Training [13/16] Loss: 0.00593 +Epoch [2149/4000] Training [14/16] Loss: 0.00803 +Epoch [2149/4000] Training [15/16] Loss: 0.00504 +Epoch [2149/4000] Training [16/16] Loss: 0.00473 +Epoch [2149/4000] Training metric {'Train/mean dice_metric': 0.996330976486206, 'Train/mean miou_metric': 0.9924298524856567, 'Train/mean f1': 0.9920589327812195, 'Train/mean precision': 0.9875336289405823, 'Train/mean recall': 0.9966258406639099, 'Train/mean hd95_metric': 1.010177731513977} +Epoch [2149/4000] Validation [1/4] Loss: 0.34812 focal_loss 0.28016 dice_loss 0.06796 +Epoch [2149/4000] Validation [2/4] Loss: 0.57030 focal_loss 0.37818 dice_loss 0.19212 +Epoch [2149/4000] Validation [3/4] Loss: 0.33378 focal_loss 0.23773 dice_loss 0.09606 +Epoch [2149/4000] Validation [4/4] Loss: 0.27089 focal_loss 0.18056 dice_loss 0.09032 +Epoch [2149/4000] Validation metric {'Val/mean dice_metric': 0.9732435345649719, 'Val/mean miou_metric': 0.9570249319076538, 'Val/mean f1': 0.9744194149971008, 'Val/mean precision': 0.971798300743103, 'Val/mean recall': 0.9770547151565552, 'Val/mean hd95_metric': 5.703360080718994} +Cheakpoint... +Epoch [2149/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732435345649719, 'Val/mean miou_metric': 0.9570249319076538, 'Val/mean f1': 0.9744194149971008, 'Val/mean precision': 0.971798300743103, 'Val/mean recall': 0.9770547151565552, 'Val/mean hd95_metric': 5.703360080718994} +Epoch [2150/4000] Training [1/16] Loss: 0.00632 +Epoch [2150/4000] Training [2/16] Loss: 0.00472 +Epoch [2150/4000] Training [3/16] Loss: 0.00434 +Epoch [2150/4000] Training [4/16] Loss: 0.00627 +Epoch [2150/4000] Training [5/16] Loss: 0.00528 +Epoch [2150/4000] Training [6/16] Loss: 0.00453 +Epoch [2150/4000] Training [7/16] Loss: 0.00494 +Epoch [2150/4000] Training [8/16] Loss: 0.00700 +Epoch [2150/4000] Training [9/16] Loss: 0.00746 +Epoch [2150/4000] Training [10/16] Loss: 0.00502 +Epoch [2150/4000] Training [11/16] Loss: 0.00403 +Epoch [2150/4000] Training [12/16] Loss: 0.00499 +Epoch [2150/4000] Training [13/16] Loss: 0.00497 +Epoch [2150/4000] Training [14/16] Loss: 0.00575 +Epoch [2150/4000] Training [15/16] Loss: 0.00567 +Epoch [2150/4000] Training [16/16] Loss: 0.00635 +Epoch [2150/4000] Training metric {'Train/mean dice_metric': 0.9963827133178711, 'Train/mean miou_metric': 0.992512047290802, 'Train/mean f1': 0.9919720888137817, 'Train/mean precision': 0.9873912930488586, 'Train/mean recall': 0.9965956211090088, 'Train/mean hd95_metric': 0.9968826174736023} +Epoch [2150/4000] Validation [1/4] Loss: 0.31306 focal_loss 0.25032 dice_loss 0.06274 +Epoch [2150/4000] Validation [2/4] Loss: 0.38810 focal_loss 0.26976 dice_loss 0.11835 +Epoch [2150/4000] Validation [3/4] Loss: 0.24000 focal_loss 0.17527 dice_loss 0.06473 +Epoch [2150/4000] Validation [4/4] Loss: 0.30528 focal_loss 0.18990 dice_loss 0.11538 +Epoch [2150/4000] Validation metric {'Val/mean dice_metric': 0.9740387201309204, 'Val/mean miou_metric': 0.9577550888061523, 'Val/mean f1': 0.9751157164573669, 'Val/mean precision': 0.9722740650177002, 'Val/mean recall': 0.9779740571975708, 'Val/mean hd95_metric': 5.22000789642334} +Cheakpoint... +Epoch [2150/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740387201309204, 'Val/mean miou_metric': 0.9577550888061523, 'Val/mean f1': 0.9751157164573669, 'Val/mean precision': 0.9722740650177002, 'Val/mean recall': 0.9779740571975708, 'Val/mean hd95_metric': 5.22000789642334} +Epoch [2151/4000] Training [1/16] Loss: 0.00630 +Epoch [2151/4000] Training [2/16] Loss: 0.00518 +Epoch [2151/4000] Training [3/16] Loss: 0.00388 +Epoch [2151/4000] Training [4/16] Loss: 0.00506 +Epoch [2151/4000] Training [5/16] Loss: 0.00485 +Epoch [2151/4000] Training [6/16] Loss: 0.00441 +Epoch [2151/4000] Training [7/16] Loss: 0.00541 +Epoch [2151/4000] Training [8/16] Loss: 0.00611 +Epoch [2151/4000] Training [9/16] Loss: 0.00793 +Epoch [2151/4000] Training [10/16] Loss: 0.00437 +Epoch [2151/4000] Training [11/16] Loss: 0.00495 +Epoch [2151/4000] Training [12/16] Loss: 0.00550 +Epoch [2151/4000] Training [13/16] Loss: 0.00518 +Epoch [2151/4000] Training [14/16] Loss: 0.00632 +Epoch [2151/4000] Training [15/16] Loss: 0.00458 +Epoch [2151/4000] Training [16/16] Loss: 0.00628 +Epoch [2151/4000] Training metric {'Train/mean dice_metric': 0.9966573119163513, 'Train/mean miou_metric': 0.9930682182312012, 'Train/mean f1': 0.9923050403594971, 'Train/mean precision': 0.9877757430076599, 'Train/mean recall': 0.9968761205673218, 'Train/mean hd95_metric': 1.0362849235534668} +Epoch [2151/4000] Validation [1/4] Loss: 0.27170 focal_loss 0.20833 dice_loss 0.06338 +Epoch [2151/4000] Validation [2/4] Loss: 0.36712 focal_loss 0.25740 dice_loss 0.10972 +Epoch [2151/4000] Validation [3/4] Loss: 0.34127 focal_loss 0.24810 dice_loss 0.09317 +Epoch [2151/4000] Validation [4/4] Loss: 0.39628 focal_loss 0.29083 dice_loss 0.10545 +Epoch [2151/4000] Validation metric {'Val/mean dice_metric': 0.9727932214736938, 'Val/mean miou_metric': 0.9565664529800415, 'Val/mean f1': 0.9738476872444153, 'Val/mean precision': 0.9675151705741882, 'Val/mean recall': 0.9802635312080383, 'Val/mean hd95_metric': 6.392264366149902} +Cheakpoint... +Epoch [2151/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727932214736938, 'Val/mean miou_metric': 0.9565664529800415, 'Val/mean f1': 0.9738476872444153, 'Val/mean precision': 0.9675151705741882, 'Val/mean recall': 0.9802635312080383, 'Val/mean hd95_metric': 6.392264366149902} +Epoch [2152/4000] Training [1/16] Loss: 0.00574 +Epoch [2152/4000] Training [2/16] Loss: 0.00655 +Epoch [2152/4000] Training [3/16] Loss: 0.00649 +Epoch [2152/4000] Training [4/16] Loss: 0.00475 +Epoch [2152/4000] Training [5/16] Loss: 0.00429 +Epoch [2152/4000] Training [6/16] Loss: 0.00512 +Epoch [2152/4000] Training [7/16] Loss: 0.00403 +Epoch [2152/4000] Training [8/16] Loss: 0.00429 +Epoch [2152/4000] Training [9/16] Loss: 0.00534 +Epoch [2152/4000] Training [10/16] Loss: 0.00795 +Epoch [2152/4000] Training [11/16] Loss: 0.00577 +Epoch [2152/4000] Training [12/16] Loss: 0.00574 +Epoch [2152/4000] Training [13/16] Loss: 0.00632 +Epoch [2152/4000] Training [14/16] Loss: 0.00414 +Epoch [2152/4000] Training [15/16] Loss: 0.00636 +Epoch [2152/4000] Training [16/16] Loss: 0.00406 +Epoch [2152/4000] Training metric {'Train/mean dice_metric': 0.9964343309402466, 'Train/mean miou_metric': 0.992632269859314, 'Train/mean f1': 0.9920855164527893, 'Train/mean precision': 0.9875555634498596, 'Train/mean recall': 0.9966572523117065, 'Train/mean hd95_metric': 1.0367281436920166} +Epoch [2152/4000] Validation [1/4] Loss: 0.28259 focal_loss 0.21982 dice_loss 0.06277 +Epoch [2152/4000] Validation [2/4] Loss: 0.37719 focal_loss 0.26511 dice_loss 0.11208 +Epoch [2152/4000] Validation [3/4] Loss: 0.31282 focal_loss 0.22129 dice_loss 0.09153 +Epoch [2152/4000] Validation [4/4] Loss: 0.44436 focal_loss 0.29962 dice_loss 0.14474 +Epoch [2152/4000] Validation metric {'Val/mean dice_metric': 0.9735800623893738, 'Val/mean miou_metric': 0.9573003053665161, 'Val/mean f1': 0.9746938347816467, 'Val/mean precision': 0.9690005779266357, 'Val/mean recall': 0.9804544448852539, 'Val/mean hd95_metric': 5.763747692108154} +Cheakpoint... +Epoch [2152/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735800623893738, 'Val/mean miou_metric': 0.9573003053665161, 'Val/mean f1': 0.9746938347816467, 'Val/mean precision': 0.9690005779266357, 'Val/mean recall': 0.9804544448852539, 'Val/mean hd95_metric': 5.763747692108154} +Epoch [2153/4000] Training [1/16] Loss: 0.00568 +Epoch [2153/4000] Training [2/16] Loss: 0.00519 +Epoch [2153/4000] Training [3/16] Loss: 0.00543 +Epoch [2153/4000] Training [4/16] Loss: 0.00545 +Epoch [2153/4000] Training [5/16] Loss: 0.00499 +Epoch [2153/4000] Training [6/16] Loss: 0.00709 +Epoch [2153/4000] Training [7/16] Loss: 0.01039 +Epoch [2153/4000] Training [8/16] Loss: 0.00405 +Epoch [2153/4000] Training [9/16] Loss: 0.00603 +Epoch [2153/4000] Training [10/16] Loss: 0.00608 +Epoch [2153/4000] Training [11/16] Loss: 0.00576 +Epoch [2153/4000] Training [12/16] Loss: 0.00495 +Epoch [2153/4000] Training [13/16] Loss: 0.00546 +Epoch [2153/4000] Training [14/16] Loss: 0.00484 +Epoch [2153/4000] Training [15/16] Loss: 0.00605 +Epoch [2153/4000] Training [16/16] Loss: 0.00386 +Epoch [2153/4000] Training metric {'Train/mean dice_metric': 0.9963300824165344, 'Train/mean miou_metric': 0.9924265146255493, 'Train/mean f1': 0.9920549988746643, 'Train/mean precision': 0.9875620007514954, 'Train/mean recall': 0.9965891242027283, 'Train/mean hd95_metric': 1.0044783353805542} +Epoch [2153/4000] Validation [1/4] Loss: 0.27482 focal_loss 0.21471 dice_loss 0.06011 +Epoch [2153/4000] Validation [2/4] Loss: 0.63597 focal_loss 0.47151 dice_loss 0.16447 +Epoch [2153/4000] Validation [3/4] Loss: 0.34250 focal_loss 0.25054 dice_loss 0.09196 +Epoch [2153/4000] Validation [4/4] Loss: 0.33258 focal_loss 0.21290 dice_loss 0.11968 +Epoch [2153/4000] Validation metric {'Val/mean dice_metric': 0.9735736846923828, 'Val/mean miou_metric': 0.9574694633483887, 'Val/mean f1': 0.974973738193512, 'Val/mean precision': 0.9710878133773804, 'Val/mean recall': 0.9788908958435059, 'Val/mean hd95_metric': 5.464232444763184} +Cheakpoint... +Epoch [2153/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735736846923828, 'Val/mean miou_metric': 0.9574694633483887, 'Val/mean f1': 0.974973738193512, 'Val/mean precision': 0.9710878133773804, 'Val/mean recall': 0.9788908958435059, 'Val/mean hd95_metric': 5.464232444763184} +Epoch [2154/4000] Training [1/16] Loss: 0.00486 +Epoch [2154/4000] Training [2/16] Loss: 0.00648 +Epoch [2154/4000] Training [3/16] Loss: 0.00487 +Epoch [2154/4000] Training [4/16] Loss: 0.00545 +Epoch [2154/4000] Training [5/16] Loss: 0.00518 +Epoch [2154/4000] Training [6/16] Loss: 0.00460 +Epoch [2154/4000] Training [7/16] Loss: 0.00511 +Epoch [2154/4000] Training [8/16] Loss: 0.00864 +Epoch [2154/4000] Training [9/16] Loss: 0.00482 +Epoch [2154/4000] Training [10/16] Loss: 0.00603 +Epoch [2154/4000] Training [11/16] Loss: 0.00573 +Epoch [2154/4000] Training [12/16] Loss: 0.00630 +Epoch [2154/4000] Training [13/16] Loss: 0.00839 +Epoch [2154/4000] Training [14/16] Loss: 0.00705 +Epoch [2154/4000] Training [15/16] Loss: 0.00553 +Epoch [2154/4000] Training [16/16] Loss: 0.00579 +Epoch [2154/4000] Training metric {'Train/mean dice_metric': 0.9962374567985535, 'Train/mean miou_metric': 0.9922405481338501, 'Train/mean f1': 0.9920173287391663, 'Train/mean precision': 0.9876200556755066, 'Train/mean recall': 0.9964538812637329, 'Train/mean hd95_metric': 1.0118286609649658} +Epoch [2154/4000] Validation [1/4] Loss: 0.24809 focal_loss 0.18892 dice_loss 0.05917 +Epoch [2154/4000] Validation [2/4] Loss: 0.60493 focal_loss 0.42371 dice_loss 0.18122 +Epoch [2154/4000] Validation [3/4] Loss: 0.22351 focal_loss 0.16188 dice_loss 0.06163 +Epoch [2154/4000] Validation [4/4] Loss: 0.25796 focal_loss 0.15995 dice_loss 0.09800 +Epoch [2154/4000] Validation metric {'Val/mean dice_metric': 0.974513053894043, 'Val/mean miou_metric': 0.9592691659927368, 'Val/mean f1': 0.9759721159934998, 'Val/mean precision': 0.9723715782165527, 'Val/mean recall': 0.9795993566513062, 'Val/mean hd95_metric': 4.881290435791016} +Cheakpoint... +Epoch [2154/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974513053894043, 'Val/mean miou_metric': 0.9592691659927368, 'Val/mean f1': 0.9759721159934998, 'Val/mean precision': 0.9723715782165527, 'Val/mean recall': 0.9795993566513062, 'Val/mean hd95_metric': 4.881290435791016} +Epoch [2155/4000] Training [1/16] Loss: 0.00536 +Epoch [2155/4000] Training [2/16] Loss: 0.00600 +Epoch [2155/4000] Training [3/16] Loss: 0.00464 +Epoch [2155/4000] Training [4/16] Loss: 0.00653 +Epoch [2155/4000] Training [5/16] Loss: 0.00516 +Epoch [2155/4000] Training [6/16] Loss: 0.00592 +Epoch [2155/4000] Training [7/16] Loss: 0.00548 +Epoch [2155/4000] Training [8/16] Loss: 0.00741 +Epoch [2155/4000] Training [9/16] Loss: 0.00776 +Epoch [2155/4000] Training [10/16] Loss: 0.00544 +Epoch [2155/4000] Training [11/16] Loss: 0.00675 +Epoch [2155/4000] Training [12/16] Loss: 0.00440 +Epoch [2155/4000] Training [13/16] Loss: 0.00553 +Epoch [2155/4000] Training [14/16] Loss: 0.00618 +Epoch [2155/4000] Training [15/16] Loss: 0.00563 +Epoch [2155/4000] Training [16/16] Loss: 0.00516 +Epoch [2155/4000] Training metric {'Train/mean dice_metric': 0.9962976574897766, 'Train/mean miou_metric': 0.9923610091209412, 'Train/mean f1': 0.9919660687446594, 'Train/mean precision': 0.9873859882354736, 'Train/mean recall': 0.9965888857841492, 'Train/mean hd95_metric': 0.9939306378364563} +Epoch [2155/4000] Validation [1/4] Loss: 0.26715 focal_loss 0.20024 dice_loss 0.06691 +Epoch [2155/4000] Validation [2/4] Loss: 0.54305 focal_loss 0.35900 dice_loss 0.18406 +Epoch [2155/4000] Validation [3/4] Loss: 0.33671 focal_loss 0.24649 dice_loss 0.09022 +Epoch [2155/4000] Validation [4/4] Loss: 0.30050 focal_loss 0.19589 dice_loss 0.10461 +Epoch [2155/4000] Validation metric {'Val/mean dice_metric': 0.9736906290054321, 'Val/mean miou_metric': 0.9578754305839539, 'Val/mean f1': 0.9750239849090576, 'Val/mean precision': 0.9725971221923828, 'Val/mean recall': 0.9774629473686218, 'Val/mean hd95_metric': 5.595316410064697} +Cheakpoint... +Epoch [2155/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736906290054321, 'Val/mean miou_metric': 0.9578754305839539, 'Val/mean f1': 0.9750239849090576, 'Val/mean precision': 0.9725971221923828, 'Val/mean recall': 0.9774629473686218, 'Val/mean hd95_metric': 5.595316410064697} +Epoch [2156/4000] Training [1/16] Loss: 0.00717 +Epoch [2156/4000] Training [2/16] Loss: 0.00684 +Epoch [2156/4000] Training [3/16] Loss: 0.00454 +Epoch [2156/4000] Training [4/16] Loss: 0.00600 +Epoch [2156/4000] Training [5/16] Loss: 0.00660 +Epoch [2156/4000] Training [6/16] Loss: 0.00487 +Epoch [2156/4000] Training [7/16] Loss: 0.00593 +Epoch [2156/4000] Training [8/16] Loss: 0.00603 +Epoch [2156/4000] Training [9/16] Loss: 0.00509 +Epoch [2156/4000] Training [10/16] Loss: 0.00365 +Epoch [2156/4000] Training [11/16] Loss: 0.00551 +Epoch [2156/4000] Training [12/16] Loss: 0.00448 +Epoch [2156/4000] Training [13/16] Loss: 0.00453 +Epoch [2156/4000] Training [14/16] Loss: 0.00507 +Epoch [2156/4000] Training [15/16] Loss: 0.00543 +Epoch [2156/4000] Training [16/16] Loss: 0.00586 +Epoch [2156/4000] Training metric {'Train/mean dice_metric': 0.9961776733398438, 'Train/mean miou_metric': 0.992149829864502, 'Train/mean f1': 0.9918034076690674, 'Train/mean precision': 0.9872193932533264, 'Train/mean recall': 0.9964302182197571, 'Train/mean hd95_metric': 1.088282823562622} +Epoch [2156/4000] Validation [1/4] Loss: 0.24941 focal_loss 0.18958 dice_loss 0.05983 +Epoch [2156/4000] Validation [2/4] Loss: 0.35948 focal_loss 0.20195 dice_loss 0.15753 +Epoch [2156/4000] Validation [3/4] Loss: 0.20258 focal_loss 0.14518 dice_loss 0.05740 +Epoch [2156/4000] Validation [4/4] Loss: 0.24965 focal_loss 0.15356 dice_loss 0.09609 +Epoch [2156/4000] Validation metric {'Val/mean dice_metric': 0.9733262062072754, 'Val/mean miou_metric': 0.9570599794387817, 'Val/mean f1': 0.9743030667304993, 'Val/mean precision': 0.969840943813324, 'Val/mean recall': 0.9788062572479248, 'Val/mean hd95_metric': 5.466514587402344} +Cheakpoint... +Epoch [2156/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733262062072754, 'Val/mean miou_metric': 0.9570599794387817, 'Val/mean f1': 0.9743030667304993, 'Val/mean precision': 0.969840943813324, 'Val/mean recall': 0.9788062572479248, 'Val/mean hd95_metric': 5.466514587402344} +Epoch [2157/4000] Training [1/16] Loss: 0.00593 +Epoch [2157/4000] Training [2/16] Loss: 0.00417 +Epoch [2157/4000] Training [3/16] Loss: 0.00511 +Epoch [2157/4000] Training [4/16] Loss: 0.00796 +Epoch [2157/4000] Training [5/16] Loss: 0.00590 +Epoch [2157/4000] Training [6/16] Loss: 0.00530 +Epoch [2157/4000] Training [7/16] Loss: 0.00757 +Epoch [2157/4000] Training [8/16] Loss: 0.00460 +Epoch [2157/4000] Training [9/16] Loss: 0.00462 +Epoch [2157/4000] Training [10/16] Loss: 0.00684 +Epoch [2157/4000] Training [11/16] Loss: 0.00506 +Epoch [2157/4000] Training [12/16] Loss: 0.00474 +Epoch [2157/4000] Training [13/16] Loss: 0.00556 +Epoch [2157/4000] Training [14/16] Loss: 0.00443 +Epoch [2157/4000] Training [15/16] Loss: 0.00491 +Epoch [2157/4000] Training [16/16] Loss: 0.00482 +Epoch [2157/4000] Training metric {'Train/mean dice_metric': 0.9963572025299072, 'Train/mean miou_metric': 0.992478609085083, 'Train/mean f1': 0.9920562505722046, 'Train/mean precision': 0.9874933958053589, 'Train/mean recall': 0.9966614842414856, 'Train/mean hd95_metric': 0.9939742684364319} +Epoch [2157/4000] Validation [1/4] Loss: 0.23599 focal_loss 0.18174 dice_loss 0.05425 +Epoch [2157/4000] Validation [2/4] Loss: 0.29334 focal_loss 0.18529 dice_loss 0.10805 +Epoch [2157/4000] Validation [3/4] Loss: 0.40999 focal_loss 0.31477 dice_loss 0.09522 +Epoch [2157/4000] Validation [4/4] Loss: 0.23525 focal_loss 0.14044 dice_loss 0.09481 +Epoch [2157/4000] Validation metric {'Val/mean dice_metric': 0.9740503430366516, 'Val/mean miou_metric': 0.9580933451652527, 'Val/mean f1': 0.973945140838623, 'Val/mean precision': 0.9686747193336487, 'Val/mean recall': 0.9792732000350952, 'Val/mean hd95_metric': 6.150496482849121} +Cheakpoint... +Epoch [2157/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740503430366516, 'Val/mean miou_metric': 0.9580933451652527, 'Val/mean f1': 0.973945140838623, 'Val/mean precision': 0.9686747193336487, 'Val/mean recall': 0.9792732000350952, 'Val/mean hd95_metric': 6.150496482849121} +Epoch [2158/4000] Training [1/16] Loss: 0.00773 +Epoch [2158/4000] Training [2/16] Loss: 0.00642 +Epoch [2158/4000] Training [3/16] Loss: 0.00565 +Epoch [2158/4000] Training [4/16] Loss: 0.00527 +Epoch [2158/4000] Training [5/16] Loss: 0.00548 +Epoch [2158/4000] Training [6/16] Loss: 0.00441 +Epoch [2158/4000] Training [7/16] Loss: 0.00657 +Epoch [2158/4000] Training [8/16] Loss: 0.00364 +Epoch [2158/4000] Training [9/16] Loss: 0.00558 +Epoch [2158/4000] Training [10/16] Loss: 0.00558 +Epoch [2158/4000] Training [11/16] Loss: 0.00511 +Epoch [2158/4000] Training [12/16] Loss: 0.00690 +Epoch [2158/4000] Training [13/16] Loss: 0.00503 +Epoch [2158/4000] Training [14/16] Loss: 0.00550 +Epoch [2158/4000] Training [15/16] Loss: 0.00513 +Epoch [2158/4000] Training [16/16] Loss: 0.00380 +Epoch [2158/4000] Training metric {'Train/mean dice_metric': 0.9958582520484924, 'Train/mean miou_metric': 0.9916331768035889, 'Train/mean f1': 0.9918063282966614, 'Train/mean precision': 0.987349808216095, 'Train/mean recall': 0.9963032007217407, 'Train/mean hd95_metric': 1.042707085609436} +Epoch [2158/4000] Validation [1/4] Loss: 0.30091 focal_loss 0.23673 dice_loss 0.06417 +Epoch [2158/4000] Validation [2/4] Loss: 0.54457 focal_loss 0.39685 dice_loss 0.14772 +Epoch [2158/4000] Validation [3/4] Loss: 0.46357 focal_loss 0.35890 dice_loss 0.10467 +Epoch [2158/4000] Validation [4/4] Loss: 0.36671 focal_loss 0.23313 dice_loss 0.13358 +Epoch [2158/4000] Validation metric {'Val/mean dice_metric': 0.973275363445282, 'Val/mean miou_metric': 0.9567579030990601, 'Val/mean f1': 0.9737323522567749, 'Val/mean precision': 0.9661133885383606, 'Val/mean recall': 0.981472373008728, 'Val/mean hd95_metric': 6.47344970703125} +Cheakpoint... +Epoch [2158/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973275363445282, 'Val/mean miou_metric': 0.9567579030990601, 'Val/mean f1': 0.9737323522567749, 'Val/mean precision': 0.9661133885383606, 'Val/mean recall': 0.981472373008728, 'Val/mean hd95_metric': 6.47344970703125} +Epoch [2159/4000] Training [1/16] Loss: 0.00553 +Epoch [2159/4000] Training [2/16] Loss: 0.00915 +Epoch [2159/4000] Training [3/16] Loss: 0.00516 +Epoch [2159/4000] Training [4/16] Loss: 0.00432 +Epoch [2159/4000] Training [5/16] Loss: 0.00398 +Epoch [2159/4000] Training [6/16] Loss: 0.00421 +Epoch [2159/4000] Training [7/16] Loss: 0.00686 +Epoch [2159/4000] Training [8/16] Loss: 0.00502 +Epoch [2159/4000] Training [9/16] Loss: 0.00599 +Epoch [2159/4000] Training [10/16] Loss: 0.00491 +Epoch [2159/4000] Training [11/16] Loss: 0.00881 +Epoch [2159/4000] Training [12/16] Loss: 0.00532 +Epoch [2159/4000] Training [13/16] Loss: 0.00514 +Epoch [2159/4000] Training [14/16] Loss: 0.00544 +Epoch [2159/4000] Training [15/16] Loss: 0.00599 +Epoch [2159/4000] Training [16/16] Loss: 0.00560 +Epoch [2159/4000] Training metric {'Train/mean dice_metric': 0.9962738752365112, 'Train/mean miou_metric': 0.9923162460327148, 'Train/mean f1': 0.9920030832290649, 'Train/mean precision': 0.9874415397644043, 'Train/mean recall': 0.9966069459915161, 'Train/mean hd95_metric': 0.999370276927948} +Epoch [2159/4000] Validation [1/4] Loss: 0.24798 focal_loss 0.19287 dice_loss 0.05511 +Epoch [2159/4000] Validation [2/4] Loss: 0.52117 focal_loss 0.36691 dice_loss 0.15426 +Epoch [2159/4000] Validation [3/4] Loss: 0.40022 focal_loss 0.30548 dice_loss 0.09474 +Epoch [2159/4000] Validation [4/4] Loss: 0.35335 focal_loss 0.23627 dice_loss 0.11707 +Epoch [2159/4000] Validation metric {'Val/mean dice_metric': 0.9724249839782715, 'Val/mean miou_metric': 0.9554283022880554, 'Val/mean f1': 0.9732035994529724, 'Val/mean precision': 0.9666192531585693, 'Val/mean recall': 0.9798784255981445, 'Val/mean hd95_metric': 6.6207098960876465} +Cheakpoint... +Epoch [2159/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724249839782715, 'Val/mean miou_metric': 0.9554283022880554, 'Val/mean f1': 0.9732035994529724, 'Val/mean precision': 0.9666192531585693, 'Val/mean recall': 0.9798784255981445, 'Val/mean hd95_metric': 6.6207098960876465} +Epoch [2160/4000] Training [1/16] Loss: 0.00557 +Epoch [2160/4000] Training [2/16] Loss: 0.00516 +Epoch [2160/4000] Training [3/16] Loss: 0.00483 +Epoch [2160/4000] Training [4/16] Loss: 0.00589 +Epoch [2160/4000] Training [5/16] Loss: 0.00691 +Epoch [2160/4000] Training [6/16] Loss: 0.00493 +Epoch [2160/4000] Training [7/16] Loss: 0.00621 +Epoch [2160/4000] Training [8/16] Loss: 0.00457 +Epoch [2160/4000] Training [9/16] Loss: 0.00538 +Epoch [2160/4000] Training [10/16] Loss: 0.00519 +Epoch [2160/4000] Training [11/16] Loss: 0.00561 +Epoch [2160/4000] Training [12/16] Loss: 0.00511 +Epoch [2160/4000] Training [13/16] Loss: 0.00460 +Epoch [2160/4000] Training [14/16] Loss: 0.00567 +Epoch [2160/4000] Training [15/16] Loss: 0.00453 +Epoch [2160/4000] Training [16/16] Loss: 0.00561 +Epoch [2160/4000] Training metric {'Train/mean dice_metric': 0.9965468049049377, 'Train/mean miou_metric': 0.9928551316261292, 'Train/mean f1': 0.9921594262123108, 'Train/mean precision': 0.9877285957336426, 'Train/mean recall': 0.9966302514076233, 'Train/mean hd95_metric': 0.9968739748001099} +Epoch [2160/4000] Validation [1/4] Loss: 0.30103 focal_loss 0.22604 dice_loss 0.07498 +Epoch [2160/4000] Validation [2/4] Loss: 0.37689 focal_loss 0.23114 dice_loss 0.14575 +Epoch [2160/4000] Validation [3/4] Loss: 0.39030 focal_loss 0.29812 dice_loss 0.09218 +Epoch [2160/4000] Validation [4/4] Loss: 0.29356 focal_loss 0.18199 dice_loss 0.11157 +Epoch [2160/4000] Validation metric {'Val/mean dice_metric': 0.9718030095100403, 'Val/mean miou_metric': 0.9558219909667969, 'Val/mean f1': 0.9704257845878601, 'Val/mean precision': 0.9602218270301819, 'Val/mean recall': 0.980849027633667, 'Val/mean hd95_metric': 6.900907039642334} +Cheakpoint... +Epoch [2160/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718030095100403, 'Val/mean miou_metric': 0.9558219909667969, 'Val/mean f1': 0.9704257845878601, 'Val/mean precision': 0.9602218270301819, 'Val/mean recall': 0.980849027633667, 'Val/mean hd95_metric': 6.900907039642334} +Epoch [2161/4000] Training [1/16] Loss: 0.00456 +Epoch [2161/4000] Training [2/16] Loss: 0.00699 +Epoch [2161/4000] Training [3/16] Loss: 0.00595 +Epoch [2161/4000] Training [4/16] Loss: 0.00423 +Epoch [2161/4000] Training [5/16] Loss: 0.00486 +Epoch [2161/4000] Training [6/16] Loss: 0.00501 +Epoch [2161/4000] Training [7/16] Loss: 0.00574 +Epoch [2161/4000] Training [8/16] Loss: 0.00519 +Epoch [2161/4000] Training [9/16] Loss: 0.00633 +Epoch [2161/4000] Training [10/16] Loss: 0.00700 +Epoch [2161/4000] Training [11/16] Loss: 0.00928 +Epoch [2161/4000] Training [12/16] Loss: 0.00633 +Epoch [2161/4000] Training [13/16] Loss: 0.00505 +Epoch [2161/4000] Training [14/16] Loss: 0.00527 +Epoch [2161/4000] Training [15/16] Loss: 0.00858 +Epoch [2161/4000] Training [16/16] Loss: 0.00459 +Epoch [2161/4000] Training metric {'Train/mean dice_metric': 0.996119499206543, 'Train/mean miou_metric': 0.9920105934143066, 'Train/mean f1': 0.991793155670166, 'Train/mean precision': 0.9871873259544373, 'Train/mean recall': 0.9964421987533569, 'Train/mean hd95_metric': 1.0167262554168701} +Epoch [2161/4000] Validation [1/4] Loss: 0.28642 focal_loss 0.22726 dice_loss 0.05916 +Epoch [2161/4000] Validation [2/4] Loss: 0.24863 focal_loss 0.15834 dice_loss 0.09029 +Epoch [2161/4000] Validation [3/4] Loss: 0.41304 focal_loss 0.32023 dice_loss 0.09281 +Epoch [2161/4000] Validation [4/4] Loss: 0.21560 focal_loss 0.13816 dice_loss 0.07744 +Epoch [2161/4000] Validation metric {'Val/mean dice_metric': 0.9743779897689819, 'Val/mean miou_metric': 0.958029568195343, 'Val/mean f1': 0.9733108878135681, 'Val/mean precision': 0.9672673344612122, 'Val/mean recall': 0.9794306755065918, 'Val/mean hd95_metric': 6.099370002746582} +Cheakpoint... +Epoch [2161/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743779897689819, 'Val/mean miou_metric': 0.958029568195343, 'Val/mean f1': 0.9733108878135681, 'Val/mean precision': 0.9672673344612122, 'Val/mean recall': 0.9794306755065918, 'Val/mean hd95_metric': 6.099370002746582} +Epoch [2162/4000] Training [1/16] Loss: 0.00428 +Epoch [2162/4000] Training [2/16] Loss: 0.00484 +Epoch [2162/4000] Training [3/16] Loss: 0.00480 +Epoch [2162/4000] Training [4/16] Loss: 0.00696 +Epoch [2162/4000] Training [5/16] Loss: 0.00532 +Epoch [2162/4000] Training [6/16] Loss: 0.00534 +Epoch [2162/4000] Training [7/16] Loss: 0.00671 +Epoch [2162/4000] Training [8/16] Loss: 0.00538 +Epoch [2162/4000] Training [9/16] Loss: 0.00475 +Epoch [2162/4000] Training [10/16] Loss: 0.00692 +Epoch [2162/4000] Training [11/16] Loss: 0.00442 +Epoch [2162/4000] Training [12/16] Loss: 0.00540 +Epoch [2162/4000] Training [13/16] Loss: 0.00441 +Epoch [2162/4000] Training [14/16] Loss: 0.00547 +Epoch [2162/4000] Training [15/16] Loss: 0.00580 +Epoch [2162/4000] Training [16/16] Loss: 0.00610 +Epoch [2162/4000] Training metric {'Train/mean dice_metric': 0.996515691280365, 'Train/mean miou_metric': 0.9927541017532349, 'Train/mean f1': 0.9913730025291443, 'Train/mean precision': 0.9860774874687195, 'Train/mean recall': 0.9967257380485535, 'Train/mean hd95_metric': 0.9906527400016785} +Epoch [2162/4000] Validation [1/4] Loss: 0.27098 focal_loss 0.21351 dice_loss 0.05747 +Epoch [2162/4000] Validation [2/4] Loss: 0.30095 focal_loss 0.18355 dice_loss 0.11740 +Epoch [2162/4000] Validation [3/4] Loss: 0.40378 focal_loss 0.31457 dice_loss 0.08921 +Epoch [2162/4000] Validation [4/4] Loss: 0.26435 focal_loss 0.16721 dice_loss 0.09714 +Epoch [2162/4000] Validation metric {'Val/mean dice_metric': 0.9740056991577148, 'Val/mean miou_metric': 0.9582341313362122, 'Val/mean f1': 0.9725503325462341, 'Val/mean precision': 0.96360844373703, 'Val/mean recall': 0.9816597104072571, 'Val/mean hd95_metric': 6.294149875640869} +Cheakpoint... +Epoch [2162/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740056991577148, 'Val/mean miou_metric': 0.9582341313362122, 'Val/mean f1': 0.9725503325462341, 'Val/mean precision': 0.96360844373703, 'Val/mean recall': 0.9816597104072571, 'Val/mean hd95_metric': 6.294149875640869} +Epoch [2163/4000] Training [1/16] Loss: 0.00463 +Epoch [2163/4000] Training [2/16] Loss: 0.00587 +Epoch [2163/4000] Training [3/16] Loss: 0.00628 +Epoch [2163/4000] Training [4/16] Loss: 0.00515 +Epoch [2163/4000] Training [5/16] Loss: 0.00501 +Epoch [2163/4000] Training [6/16] Loss: 0.00444 +Epoch [2163/4000] Training [7/16] Loss: 0.00419 +Epoch [2163/4000] Training [8/16] Loss: 0.00498 +Epoch [2163/4000] Training [9/16] Loss: 0.00530 +Epoch [2163/4000] Training [10/16] Loss: 0.00655 +Epoch [2163/4000] Training [11/16] Loss: 0.00524 +Epoch [2163/4000] Training [12/16] Loss: 0.00522 +Epoch [2163/4000] Training [13/16] Loss: 0.00520 +Epoch [2163/4000] Training [14/16] Loss: 0.00607 +Epoch [2163/4000] Training [15/16] Loss: 0.00643 +Epoch [2163/4000] Training [16/16] Loss: 0.00423 +Epoch [2163/4000] Training metric {'Train/mean dice_metric': 0.9965069890022278, 'Train/mean miou_metric': 0.9927789568901062, 'Train/mean f1': 0.9921590685844421, 'Train/mean precision': 0.9876797795295715, 'Train/mean recall': 0.9966791272163391, 'Train/mean hd95_metric': 0.9909590482711792} +Epoch [2163/4000] Validation [1/4] Loss: 0.23046 focal_loss 0.17425 dice_loss 0.05620 +Epoch [2163/4000] Validation [2/4] Loss: 0.24328 focal_loss 0.15400 dice_loss 0.08928 +Epoch [2163/4000] Validation [3/4] Loss: 0.33391 focal_loss 0.23879 dice_loss 0.09513 +Epoch [2163/4000] Validation [4/4] Loss: 0.19600 focal_loss 0.12048 dice_loss 0.07553 +Epoch [2163/4000] Validation metric {'Val/mean dice_metric': 0.9740340113639832, 'Val/mean miou_metric': 0.9581327438354492, 'Val/mean f1': 0.9733878374099731, 'Val/mean precision': 0.9661547541618347, 'Val/mean recall': 0.9807301759719849, 'Val/mean hd95_metric': 6.316322326660156} +Cheakpoint... +Epoch [2163/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740340113639832, 'Val/mean miou_metric': 0.9581327438354492, 'Val/mean f1': 0.9733878374099731, 'Val/mean precision': 0.9661547541618347, 'Val/mean recall': 0.9807301759719849, 'Val/mean hd95_metric': 6.316322326660156} +Epoch [2164/4000] Training [1/16] Loss: 0.00412 +Epoch [2164/4000] Training [2/16] Loss: 0.00328 +Epoch [2164/4000] Training [3/16] Loss: 0.00518 +Epoch [2164/4000] Training [4/16] Loss: 0.00459 +Epoch [2164/4000] Training [5/16] Loss: 0.00603 +Epoch [2164/4000] Training [6/16] Loss: 0.00623 +Epoch [2164/4000] Training [7/16] Loss: 0.00547 +Epoch [2164/4000] Training [8/16] Loss: 0.00636 +Epoch [2164/4000] Training [9/16] Loss: 0.00459 +Epoch [2164/4000] Training [10/16] Loss: 0.00508 +Epoch [2164/4000] Training [11/16] Loss: 0.00512 +Epoch [2164/4000] Training [12/16] Loss: 0.00623 +Epoch [2164/4000] Training [13/16] Loss: 0.00843 +Epoch [2164/4000] Training [14/16] Loss: 0.00433 +Epoch [2164/4000] Training [15/16] Loss: 0.00516 +Epoch [2164/4000] Training [16/16] Loss: 0.00543 +Epoch [2164/4000] Training metric {'Train/mean dice_metric': 0.9964920282363892, 'Train/mean miou_metric': 0.9927425384521484, 'Train/mean f1': 0.9921219944953918, 'Train/mean precision': 0.9874363541603088, 'Train/mean recall': 0.9968522787094116, 'Train/mean hd95_metric': 0.9898992776870728} +Epoch [2164/4000] Validation [1/4] Loss: 0.25486 focal_loss 0.19874 dice_loss 0.05612 +Epoch [2164/4000] Validation [2/4] Loss: 0.31119 focal_loss 0.19331 dice_loss 0.11788 +Epoch [2164/4000] Validation [3/4] Loss: 0.42648 focal_loss 0.32734 dice_loss 0.09913 +Epoch [2164/4000] Validation [4/4] Loss: 0.36450 focal_loss 0.24659 dice_loss 0.11791 +Epoch [2164/4000] Validation metric {'Val/mean dice_metric': 0.9730790853500366, 'Val/mean miou_metric': 0.9568178057670593, 'Val/mean f1': 0.9735862612724304, 'Val/mean precision': 0.9668744206428528, 'Val/mean recall': 0.9803920388221741, 'Val/mean hd95_metric': 6.4205121994018555} +Cheakpoint... +Epoch [2164/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730790853500366, 'Val/mean miou_metric': 0.9568178057670593, 'Val/mean f1': 0.9735862612724304, 'Val/mean precision': 0.9668744206428528, 'Val/mean recall': 0.9803920388221741, 'Val/mean hd95_metric': 6.4205121994018555} +Epoch [2165/4000] Training [1/16] Loss: 0.00648 +Epoch [2165/4000] Training [2/16] Loss: 0.00397 +Epoch [2165/4000] Training [3/16] Loss: 0.00486 +Epoch [2165/4000] Training [4/16] Loss: 0.00430 +Epoch [2165/4000] Training [5/16] Loss: 0.00458 +Epoch [2165/4000] Training [6/16] Loss: 0.00576 +Epoch [2165/4000] Training [7/16] Loss: 0.00342 +Epoch [2165/4000] Training [8/16] Loss: 0.00442 +Epoch [2165/4000] Training [9/16] Loss: 0.00856 +Epoch [2165/4000] Training [10/16] Loss: 0.00490 +Epoch [2165/4000] Training [11/16] Loss: 0.00513 +Epoch [2165/4000] Training [12/16] Loss: 0.00783 +Epoch [2165/4000] Training [13/16] Loss: 0.00726 +Epoch [2165/4000] Training [14/16] Loss: 0.00493 +Epoch [2165/4000] Training [15/16] Loss: 0.00488 +Epoch [2165/4000] Training [16/16] Loss: 0.00420 +Epoch [2165/4000] Training metric {'Train/mean dice_metric': 0.9965512752532959, 'Train/mean miou_metric': 0.9928392767906189, 'Train/mean f1': 0.991769552230835, 'Train/mean precision': 0.9869318604469299, 'Train/mean recall': 0.9966549277305603, 'Train/mean hd95_metric': 0.9953130483627319} +Epoch [2165/4000] Validation [1/4] Loss: 0.27452 focal_loss 0.21522 dice_loss 0.05930 +Epoch [2165/4000] Validation [2/4] Loss: 0.52977 focal_loss 0.37326 dice_loss 0.15651 +Epoch [2165/4000] Validation [3/4] Loss: 0.41200 focal_loss 0.31826 dice_loss 0.09374 +Epoch [2165/4000] Validation [4/4] Loss: 0.20402 focal_loss 0.12343 dice_loss 0.08060 +Epoch [2165/4000] Validation metric {'Val/mean dice_metric': 0.9730504155158997, 'Val/mean miou_metric': 0.9566008448600769, 'Val/mean f1': 0.9721242785453796, 'Val/mean precision': 0.9634754657745361, 'Val/mean recall': 0.9809297919273376, 'Val/mean hd95_metric': 7.037152290344238} +Cheakpoint... +Epoch [2165/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730504155158997, 'Val/mean miou_metric': 0.9566008448600769, 'Val/mean f1': 0.9721242785453796, 'Val/mean precision': 0.9634754657745361, 'Val/mean recall': 0.9809297919273376, 'Val/mean hd95_metric': 7.037152290344238} +Epoch [2166/4000] Training [1/16] Loss: 0.00458 +Epoch [2166/4000] Training [2/16] Loss: 0.00578 +Epoch [2166/4000] Training [3/16] Loss: 0.00550 +Epoch [2166/4000] Training [4/16] Loss: 0.00488 +Epoch [2166/4000] Training [5/16] Loss: 0.00459 +Epoch [2166/4000] Training [6/16] Loss: 0.00770 +Epoch [2166/4000] Training [7/16] Loss: 0.00416 +Epoch [2166/4000] Training [8/16] Loss: 0.00544 +Epoch [2166/4000] Training [9/16] Loss: 0.00756 +Epoch [2166/4000] Training [10/16] Loss: 0.00520 +Epoch [2166/4000] Training [11/16] Loss: 0.00541 +Epoch [2166/4000] Training [12/16] Loss: 0.00495 +Epoch [2166/4000] Training [13/16] Loss: 0.00909 +Epoch [2166/4000] Training [14/16] Loss: 0.00619 +Epoch [2166/4000] Training [15/16] Loss: 0.00716 +Epoch [2166/4000] Training [16/16] Loss: 0.00492 +Epoch [2166/4000] Training metric {'Train/mean dice_metric': 0.9952065944671631, 'Train/mean miou_metric': 0.9905345439910889, 'Train/mean f1': 0.9914235472679138, 'Train/mean precision': 0.9866015911102295, 'Train/mean recall': 0.9962928891181946, 'Train/mean hd95_metric': 1.3888652324676514} +Epoch [2166/4000] Validation [1/4] Loss: 0.26018 focal_loss 0.20254 dice_loss 0.05764 +Epoch [2166/4000] Validation [2/4] Loss: 0.25267 focal_loss 0.15790 dice_loss 0.09476 +Epoch [2166/4000] Validation [3/4] Loss: 0.22417 focal_loss 0.15750 dice_loss 0.06668 +Epoch [2166/4000] Validation [4/4] Loss: 0.37317 focal_loss 0.23679 dice_loss 0.13638 +Epoch [2166/4000] Validation metric {'Val/mean dice_metric': 0.9731439352035522, 'Val/mean miou_metric': 0.9564768671989441, 'Val/mean f1': 0.9737973213195801, 'Val/mean precision': 0.9695137739181519, 'Val/mean recall': 0.9781189560890198, 'Val/mean hd95_metric': 6.181642055511475} +Cheakpoint... +Epoch [2166/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731439352035522, 'Val/mean miou_metric': 0.9564768671989441, 'Val/mean f1': 0.9737973213195801, 'Val/mean precision': 0.9695137739181519, 'Val/mean recall': 0.9781189560890198, 'Val/mean hd95_metric': 6.181642055511475} +Epoch [2167/4000] Training [1/16] Loss: 0.00409 +Epoch [2167/4000] Training [2/16] Loss: 0.00631 +Epoch [2167/4000] Training [3/16] Loss: 0.00653 +Epoch [2167/4000] Training [4/16] Loss: 0.00501 +Epoch [2167/4000] Training [5/16] Loss: 0.00423 +Epoch [2167/4000] Training [6/16] Loss: 0.00792 +Epoch [2167/4000] Training [7/16] Loss: 0.00475 +Epoch [2167/4000] Training [8/16] Loss: 0.00485 +Epoch [2167/4000] Training [9/16] Loss: 0.00452 +Epoch [2167/4000] Training [10/16] Loss: 0.00758 +Epoch [2167/4000] Training [11/16] Loss: 0.00643 +Epoch [2167/4000] Training [12/16] Loss: 0.00569 +Epoch [2167/4000] Training [13/16] Loss: 0.00646 +Epoch [2167/4000] Training [14/16] Loss: 0.06702 +Epoch [2167/4000] Training [15/16] Loss: 0.00536 +Epoch [2167/4000] Training [16/16] Loss: 0.00552 +Epoch [2167/4000] Training metric {'Train/mean dice_metric': 0.9953204393386841, 'Train/mean miou_metric': 0.9908934235572815, 'Train/mean f1': 0.9918029308319092, 'Train/mean precision': 0.9874547123908997, 'Train/mean recall': 0.9961895942687988, 'Train/mean hd95_metric': 1.0391209125518799} +Epoch [2167/4000] Validation [1/4] Loss: 0.41908 focal_loss 0.30399 dice_loss 0.11509 +Epoch [2167/4000] Validation [2/4] Loss: 0.30470 focal_loss 0.18655 dice_loss 0.11816 +Epoch [2167/4000] Validation [3/4] Loss: 0.27398 focal_loss 0.20556 dice_loss 0.06842 +Epoch [2167/4000] Validation [4/4] Loss: 0.54888 focal_loss 0.41335 dice_loss 0.13553 +Epoch [2167/4000] Validation metric {'Val/mean dice_metric': 0.9674950838088989, 'Val/mean miou_metric': 0.9503772854804993, 'Val/mean f1': 0.9715620279312134, 'Val/mean precision': 0.9732249975204468, 'Val/mean recall': 0.9699048399925232, 'Val/mean hd95_metric': 6.599440574645996} +Cheakpoint... +Epoch [2167/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9675], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9674950838088989, 'Val/mean miou_metric': 0.9503772854804993, 'Val/mean f1': 0.9715620279312134, 'Val/mean precision': 0.9732249975204468, 'Val/mean recall': 0.9699048399925232, 'Val/mean hd95_metric': 6.599440574645996} +Epoch [2168/4000] Training [1/16] Loss: 0.00557 +Epoch [2168/4000] Training [2/16] Loss: 0.00666 +Epoch [2168/4000] Training [3/16] Loss: 0.00549 +Epoch [2168/4000] Training [4/16] Loss: 0.00570 +Epoch [2168/4000] Training [5/16] Loss: 0.00659 +Epoch [2168/4000] Training [6/16] Loss: 0.00436 +Epoch [2168/4000] Training [7/16] Loss: 0.00683 +Epoch [2168/4000] Training [8/16] Loss: 0.00699 +Epoch [2168/4000] Training [9/16] Loss: 0.00456 +Epoch [2168/4000] Training [10/16] Loss: 0.00462 +Epoch [2168/4000] Training [11/16] Loss: 0.00557 +Epoch [2168/4000] Training [12/16] Loss: 0.00584 +Epoch [2168/4000] Training [13/16] Loss: 0.00675 +Epoch [2168/4000] Training [14/16] Loss: 0.00588 +Epoch [2168/4000] Training [15/16] Loss: 0.00514 +Epoch [2168/4000] Training [16/16] Loss: 0.00465 +Epoch [2168/4000] Training metric {'Train/mean dice_metric': 0.9962315559387207, 'Train/mean miou_metric': 0.9921993613243103, 'Train/mean f1': 0.9912304878234863, 'Train/mean precision': 0.986007571220398, 'Train/mean recall': 0.9965090751647949, 'Train/mean hd95_metric': 1.0033823251724243} +Epoch [2168/4000] Validation [1/4] Loss: 0.39505 focal_loss 0.28289 dice_loss 0.11216 +Epoch [2168/4000] Validation [2/4] Loss: 0.27076 focal_loss 0.16546 dice_loss 0.10529 +Epoch [2168/4000] Validation [3/4] Loss: 0.25025 focal_loss 0.18206 dice_loss 0.06819 +Epoch [2168/4000] Validation [4/4] Loss: 0.58078 focal_loss 0.44174 dice_loss 0.13903 +Epoch [2168/4000] Validation metric {'Val/mean dice_metric': 0.9680724143981934, 'Val/mean miou_metric': 0.9512683153152466, 'Val/mean f1': 0.9719909429550171, 'Val/mean precision': 0.9723090529441833, 'Val/mean recall': 0.9716730713844299, 'Val/mean hd95_metric': 6.179988861083984} +Cheakpoint... +Epoch [2168/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9681], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680724143981934, 'Val/mean miou_metric': 0.9512683153152466, 'Val/mean f1': 0.9719909429550171, 'Val/mean precision': 0.9723090529441833, 'Val/mean recall': 0.9716730713844299, 'Val/mean hd95_metric': 6.179988861083984} +Epoch [2169/4000] Training [1/16] Loss: 0.00472 +Epoch [2169/4000] Training [2/16] Loss: 0.00832 +Epoch [2169/4000] Training [3/16] Loss: 0.00534 +Epoch [2169/4000] Training [4/16] Loss: 0.00443 +Epoch [2169/4000] Training [5/16] Loss: 0.00763 +Epoch [2169/4000] Training [6/16] Loss: 0.00594 +Epoch [2169/4000] Training [7/16] Loss: 0.00505 +Epoch [2169/4000] Training [8/16] Loss: 0.00646 +Epoch [2169/4000] Training [9/16] Loss: 0.00540 +Epoch [2169/4000] Training [10/16] Loss: 0.00626 +Epoch [2169/4000] Training [11/16] Loss: 0.00505 +Epoch [2169/4000] Training [12/16] Loss: 0.00735 +Epoch [2169/4000] Training [13/16] Loss: 0.01202 +Epoch [2169/4000] Training [14/16] Loss: 0.00805 +Epoch [2169/4000] Training [15/16] Loss: 0.00462 +Epoch [2169/4000] Training [16/16] Loss: 0.00414 +Epoch [2169/4000] Training metric {'Train/mean dice_metric': 0.9961013793945312, 'Train/mean miou_metric': 0.9919763803482056, 'Train/mean f1': 0.9919225573539734, 'Train/mean precision': 0.9874929785728455, 'Train/mean recall': 0.9963920712471008, 'Train/mean hd95_metric': 1.011674404144287} +Epoch [2169/4000] Validation [1/4] Loss: 0.38716 focal_loss 0.28180 dice_loss 0.10535 +Epoch [2169/4000] Validation [2/4] Loss: 0.30403 focal_loss 0.18396 dice_loss 0.12006 +Epoch [2169/4000] Validation [3/4] Loss: 0.21578 focal_loss 0.14832 dice_loss 0.06746 +Epoch [2169/4000] Validation [4/4] Loss: 0.56715 focal_loss 0.42619 dice_loss 0.14096 +Epoch [2169/4000] Validation metric {'Val/mean dice_metric': 0.9690062403678894, 'Val/mean miou_metric': 0.9518786668777466, 'Val/mean f1': 0.9719362258911133, 'Val/mean precision': 0.9712243676185608, 'Val/mean recall': 0.9726491570472717, 'Val/mean hd95_metric': 5.6258368492126465} +Cheakpoint... +Epoch [2169/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9690], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9690062403678894, 'Val/mean miou_metric': 0.9518786668777466, 'Val/mean f1': 0.9719362258911133, 'Val/mean precision': 0.9712243676185608, 'Val/mean recall': 0.9726491570472717, 'Val/mean hd95_metric': 5.6258368492126465} +Epoch [2170/4000] Training [1/16] Loss: 0.00465 +Epoch [2170/4000] Training [2/16] Loss: 0.00462 +Epoch [2170/4000] Training [3/16] Loss: 0.00617 +Epoch [2170/4000] Training [4/16] Loss: 0.00382 +Epoch [2170/4000] Training [5/16] Loss: 0.00512 +Epoch [2170/4000] Training [6/16] Loss: 0.00494 +Epoch [2170/4000] Training [7/16] Loss: 0.00581 +Epoch [2170/4000] Training [8/16] Loss: 0.00434 +Epoch [2170/4000] Training [9/16] Loss: 0.00486 +Epoch [2170/4000] Training [10/16] Loss: 0.00520 +Epoch [2170/4000] Training [11/16] Loss: 0.00495 +Epoch [2170/4000] Training [12/16] Loss: 0.00566 +Epoch [2170/4000] Training [13/16] Loss: 0.00504 +Epoch [2170/4000] Training [14/16] Loss: 0.00431 +Epoch [2170/4000] Training [15/16] Loss: 0.00404 +Epoch [2170/4000] Training [16/16] Loss: 0.00476 +Epoch [2170/4000] Training metric {'Train/mean dice_metric': 0.9968087077140808, 'Train/mean miou_metric': 0.9933731555938721, 'Train/mean f1': 0.992375910282135, 'Train/mean precision': 0.9878755211830139, 'Train/mean recall': 0.9969174861907959, 'Train/mean hd95_metric': 0.9834539294242859} +Epoch [2170/4000] Validation [1/4] Loss: 0.39003 focal_loss 0.28887 dice_loss 0.10115 +Epoch [2170/4000] Validation [2/4] Loss: 0.31596 focal_loss 0.19292 dice_loss 0.12304 +Epoch [2170/4000] Validation [3/4] Loss: 0.31569 focal_loss 0.23914 dice_loss 0.07656 +Epoch [2170/4000] Validation [4/4] Loss: 0.57683 focal_loss 0.43150 dice_loss 0.14533 +Epoch [2170/4000] Validation metric {'Val/mean dice_metric': 0.971276581287384, 'Val/mean miou_metric': 0.9546180963516235, 'Val/mean f1': 0.9734302759170532, 'Val/mean precision': 0.9738947153091431, 'Val/mean recall': 0.9729663133621216, 'Val/mean hd95_metric': 6.17578125} +Cheakpoint... +Epoch [2170/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971276581287384, 'Val/mean miou_metric': 0.9546180963516235, 'Val/mean f1': 0.9734302759170532, 'Val/mean precision': 0.9738947153091431, 'Val/mean recall': 0.9729663133621216, 'Val/mean hd95_metric': 6.17578125} +Epoch [2171/4000] Training [1/16] Loss: 0.00488 +Epoch [2171/4000] Training [2/16] Loss: 0.00482 +Epoch [2171/4000] Training [3/16] Loss: 0.00401 +Epoch [2171/4000] Training [4/16] Loss: 0.00396 +Epoch [2171/4000] Training [5/16] Loss: 0.00423 +Epoch [2171/4000] Training [6/16] Loss: 0.00505 +Epoch [2171/4000] Training [7/16] Loss: 0.00393 +Epoch [2171/4000] Training [8/16] Loss: 0.00429 +Epoch [2171/4000] Training [9/16] Loss: 0.00671 +Epoch [2171/4000] Training [10/16] Loss: 0.00493 +Epoch [2171/4000] Training [11/16] Loss: 0.00450 +Epoch [2171/4000] Training [12/16] Loss: 0.00583 +Epoch [2171/4000] Training [13/16] Loss: 0.00512 +Epoch [2171/4000] Training [14/16] Loss: 0.00475 +Epoch [2171/4000] Training [15/16] Loss: 0.00437 +Epoch [2171/4000] Training [16/16] Loss: 0.00646 +Epoch [2171/4000] Training metric {'Train/mean dice_metric': 0.9967033267021179, 'Train/mean miou_metric': 0.993128776550293, 'Train/mean f1': 0.9915339350700378, 'Train/mean precision': 0.9863631129264832, 'Train/mean recall': 0.9967592358589172, 'Train/mean hd95_metric': 0.9825577735900879} +Epoch [2171/4000] Validation [1/4] Loss: 0.34441 focal_loss 0.25684 dice_loss 0.08757 +Epoch [2171/4000] Validation [2/4] Loss: 0.30718 focal_loss 0.18815 dice_loss 0.11903 +Epoch [2171/4000] Validation [3/4] Loss: 0.21421 focal_loss 0.14895 dice_loss 0.06526 +Epoch [2171/4000] Validation [4/4] Loss: 0.32413 focal_loss 0.22025 dice_loss 0.10388 +Epoch [2171/4000] Validation metric {'Val/mean dice_metric': 0.9722935557365417, 'Val/mean miou_metric': 0.9559857249259949, 'Val/mean f1': 0.9742685556411743, 'Val/mean precision': 0.9728650450706482, 'Val/mean recall': 0.9756761193275452, 'Val/mean hd95_metric': 5.645623683929443} +Cheakpoint... +Epoch [2171/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722935557365417, 'Val/mean miou_metric': 0.9559857249259949, 'Val/mean f1': 0.9742685556411743, 'Val/mean precision': 0.9728650450706482, 'Val/mean recall': 0.9756761193275452, 'Val/mean hd95_metric': 5.645623683929443} +Epoch [2172/4000] Training [1/16] Loss: 0.00513 +Epoch [2172/4000] Training [2/16] Loss: 0.00437 +Epoch [2172/4000] Training [3/16] Loss: 0.00559 +Epoch [2172/4000] Training [4/16] Loss: 0.00625 +Epoch [2172/4000] Training [5/16] Loss: 0.00490 +Epoch [2172/4000] Training [6/16] Loss: 0.00386 +Epoch [2172/4000] Training [7/16] Loss: 0.00531 +Epoch [2172/4000] Training [8/16] Loss: 0.00499 +Epoch [2172/4000] Training [9/16] Loss: 0.00413 +Epoch [2172/4000] Training [10/16] Loss: 0.00626 +Epoch [2172/4000] Training [11/16] Loss: 0.00968 +Epoch [2172/4000] Training [12/16] Loss: 0.00402 +Epoch [2172/4000] Training [13/16] Loss: 0.00663 +Epoch [2172/4000] Training [14/16] Loss: 0.00463 +Epoch [2172/4000] Training [15/16] Loss: 0.00735 +Epoch [2172/4000] Training [16/16] Loss: 0.00485 +Epoch [2172/4000] Training metric {'Train/mean dice_metric': 0.9965664148330688, 'Train/mean miou_metric': 0.9928593635559082, 'Train/mean f1': 0.9913293719291687, 'Train/mean precision': 0.9860893487930298, 'Train/mean recall': 0.9966253638267517, 'Train/mean hd95_metric': 0.9901061058044434} +Epoch [2172/4000] Validation [1/4] Loss: 0.31605 focal_loss 0.24726 dice_loss 0.06878 +Epoch [2172/4000] Validation [2/4] Loss: 0.54640 focal_loss 0.38014 dice_loss 0.16625 +Epoch [2172/4000] Validation [3/4] Loss: 0.22222 focal_loss 0.15676 dice_loss 0.06546 +Epoch [2172/4000] Validation [4/4] Loss: 0.24951 focal_loss 0.14503 dice_loss 0.10448 +Epoch [2172/4000] Validation metric {'Val/mean dice_metric': 0.9727823138237, 'Val/mean miou_metric': 0.9565213918685913, 'Val/mean f1': 0.9730210304260254, 'Val/mean precision': 0.9707096815109253, 'Val/mean recall': 0.9753434658050537, 'Val/mean hd95_metric': 5.460288047790527} +Cheakpoint... +Epoch [2172/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727823138237, 'Val/mean miou_metric': 0.9565213918685913, 'Val/mean f1': 0.9730210304260254, 'Val/mean precision': 0.9707096815109253, 'Val/mean recall': 0.9753434658050537, 'Val/mean hd95_metric': 5.460288047790527} +Epoch [2173/4000] Training [1/16] Loss: 0.00331 +Epoch [2173/4000] Training [2/16] Loss: 0.00487 +Epoch [2173/4000] Training [3/16] Loss: 0.00531 +Epoch [2173/4000] Training [4/16] Loss: 0.00410 +Epoch [2173/4000] Training [5/16] Loss: 0.00552 +Epoch [2173/4000] Training [6/16] Loss: 0.00536 +Epoch [2173/4000] Training [7/16] Loss: 0.00400 +Epoch [2173/4000] Training [8/16] Loss: 0.00597 +Epoch [2173/4000] Training [9/16] Loss: 0.00514 +Epoch [2173/4000] Training [10/16] Loss: 0.00530 +Epoch [2173/4000] Training [11/16] Loss: 0.00560 +Epoch [2173/4000] Training [12/16] Loss: 0.00492 +Epoch [2173/4000] Training [13/16] Loss: 0.00702 +Epoch [2173/4000] Training [14/16] Loss: 0.00539 +Epoch [2173/4000] Training [15/16] Loss: 0.00476 +Epoch [2173/4000] Training [16/16] Loss: 0.00451 +Epoch [2173/4000] Training metric {'Train/mean dice_metric': 0.9968980550765991, 'Train/mean miou_metric': 0.9935475587844849, 'Train/mean f1': 0.9923872351646423, 'Train/mean precision': 0.9878594279289246, 'Train/mean recall': 0.9969567060470581, 'Train/mean hd95_metric': 0.9814721345901489} +Epoch [2173/4000] Validation [1/4] Loss: 0.25950 focal_loss 0.19693 dice_loss 0.06258 +Epoch [2173/4000] Validation [2/4] Loss: 0.52547 focal_loss 0.36469 dice_loss 0.16078 +Epoch [2173/4000] Validation [3/4] Loss: 0.21869 focal_loss 0.15619 dice_loss 0.06249 +Epoch [2173/4000] Validation [4/4] Loss: 0.58900 focal_loss 0.43464 dice_loss 0.15436 +Epoch [2173/4000] Validation metric {'Val/mean dice_metric': 0.9724472165107727, 'Val/mean miou_metric': 0.9564725160598755, 'Val/mean f1': 0.9739730954170227, 'Val/mean precision': 0.9716317057609558, 'Val/mean recall': 0.9763258695602417, 'Val/mean hd95_metric': 6.0519304275512695} +Cheakpoint... +Epoch [2173/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724472165107727, 'Val/mean miou_metric': 0.9564725160598755, 'Val/mean f1': 0.9739730954170227, 'Val/mean precision': 0.9716317057609558, 'Val/mean recall': 0.9763258695602417, 'Val/mean hd95_metric': 6.0519304275512695} +Epoch [2174/4000] Training [1/16] Loss: 0.00425 +Epoch [2174/4000] Training [2/16] Loss: 0.00645 +Epoch [2174/4000] Training [3/16] Loss: 0.00442 +Epoch [2174/4000] Training [4/16] Loss: 0.00489 +Epoch [2174/4000] Training [5/16] Loss: 0.00521 +Epoch [2174/4000] Training [6/16] Loss: 0.00449 +Epoch [2174/4000] Training [7/16] Loss: 0.00555 +Epoch [2174/4000] Training [8/16] Loss: 0.00467 +Epoch [2174/4000] Training [9/16] Loss: 0.00510 +Epoch [2174/4000] Training [10/16] Loss: 0.00455 +Epoch [2174/4000] Training [11/16] Loss: 0.00423 +Epoch [2174/4000] Training [12/16] Loss: 0.00479 +Epoch [2174/4000] Training [13/16] Loss: 0.00514 +Epoch [2174/4000] Training [14/16] Loss: 0.00467 +Epoch [2174/4000] Training [15/16] Loss: 0.00426 +Epoch [2174/4000] Training [16/16] Loss: 0.00666 +Epoch [2174/4000] Training metric {'Train/mean dice_metric': 0.9969578385353088, 'Train/mean miou_metric': 0.9936670064926147, 'Train/mean f1': 0.9923164248466492, 'Train/mean precision': 0.9877179265022278, 'Train/mean recall': 0.9969578385353088, 'Train/mean hd95_metric': 0.9860113859176636} +Epoch [2174/4000] Validation [1/4] Loss: 0.27920 focal_loss 0.21438 dice_loss 0.06481 +Epoch [2174/4000] Validation [2/4] Loss: 0.31268 focal_loss 0.19800 dice_loss 0.11469 +Epoch [2174/4000] Validation [3/4] Loss: 0.19053 focal_loss 0.13128 dice_loss 0.05925 +Epoch [2174/4000] Validation [4/4] Loss: 0.31505 focal_loss 0.21736 dice_loss 0.09769 +Epoch [2174/4000] Validation metric {'Val/mean dice_metric': 0.9729766845703125, 'Val/mean miou_metric': 0.9576436877250671, 'Val/mean f1': 0.9742656946182251, 'Val/mean precision': 0.9723942875862122, 'Val/mean recall': 0.9761442542076111, 'Val/mean hd95_metric': 5.5522356033325195} +Cheakpoint... +Epoch [2174/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729766845703125, 'Val/mean miou_metric': 0.9576436877250671, 'Val/mean f1': 0.9742656946182251, 'Val/mean precision': 0.9723942875862122, 'Val/mean recall': 0.9761442542076111, 'Val/mean hd95_metric': 5.5522356033325195} +Epoch [2175/4000] Training [1/16] Loss: 0.00399 +Epoch [2175/4000] Training [2/16] Loss: 0.00518 +Epoch [2175/4000] Training [3/16] Loss: 0.00714 +Epoch [2175/4000] Training [4/16] Loss: 0.07908 +Epoch [2175/4000] Training [5/16] Loss: 0.00495 +Epoch [2175/4000] Training [6/16] Loss: 0.00595 +Epoch [2175/4000] Training [7/16] Loss: 0.00539 +Epoch [2175/4000] Training [8/16] Loss: 0.00456 +Epoch [2175/4000] Training [9/16] Loss: 0.00532 +Epoch [2175/4000] Training [10/16] Loss: 0.00559 +Epoch [2175/4000] Training [11/16] Loss: 0.00511 +Epoch [2175/4000] Training [12/16] Loss: 0.00475 +Epoch [2175/4000] Training [13/16] Loss: 0.00720 +Epoch [2175/4000] Training [14/16] Loss: 0.00505 +Epoch [2175/4000] Training [15/16] Loss: 0.00610 +Epoch [2175/4000] Training [16/16] Loss: 0.00392 +Epoch [2175/4000] Training metric {'Train/mean dice_metric': 0.9958640336990356, 'Train/mean miou_metric': 0.9919633865356445, 'Train/mean f1': 0.9920324087142944, 'Train/mean precision': 0.9874073266983032, 'Train/mean recall': 0.9967010021209717, 'Train/mean hd95_metric': 1.1186408996582031} +Epoch [2175/4000] Validation [1/4] Loss: 0.27986 focal_loss 0.21208 dice_loss 0.06778 +Epoch [2175/4000] Validation [2/4] Loss: 0.35112 focal_loss 0.22496 dice_loss 0.12615 +Epoch [2175/4000] Validation [3/4] Loss: 0.21289 focal_loss 0.15138 dice_loss 0.06150 +Epoch [2175/4000] Validation [4/4] Loss: 0.24793 focal_loss 0.15178 dice_loss 0.09616 +Epoch [2175/4000] Validation metric {'Val/mean dice_metric': 0.9735503196716309, 'Val/mean miou_metric': 0.957420825958252, 'Val/mean f1': 0.9750034213066101, 'Val/mean precision': 0.9737789034843445, 'Val/mean recall': 0.976231038570404, 'Val/mean hd95_metric': 5.598027229309082} +Cheakpoint... +Epoch [2175/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735503196716309, 'Val/mean miou_metric': 0.957420825958252, 'Val/mean f1': 0.9750034213066101, 'Val/mean precision': 0.9737789034843445, 'Val/mean recall': 0.976231038570404, 'Val/mean hd95_metric': 5.598027229309082} +Epoch [2176/4000] Training [1/16] Loss: 0.00553 +Epoch [2176/4000] Training [2/16] Loss: 0.00553 +Epoch [2176/4000] Training [3/16] Loss: 0.00501 +Epoch [2176/4000] Training [4/16] Loss: 0.00676 +Epoch [2176/4000] Training [5/16] Loss: 0.00574 +Epoch [2176/4000] Training [6/16] Loss: 0.00486 +Epoch [2176/4000] Training [7/16] Loss: 0.00404 +Epoch [2176/4000] Training [8/16] Loss: 0.00417 +Epoch [2176/4000] Training [9/16] Loss: 0.00441 +Epoch [2176/4000] Training [10/16] Loss: 0.00478 +Epoch [2176/4000] Training [11/16] Loss: 0.00430 +Epoch [2176/4000] Training [12/16] Loss: 0.00707 +Epoch [2176/4000] Training [13/16] Loss: 0.00743 +Epoch [2176/4000] Training [14/16] Loss: 0.00391 +Epoch [2176/4000] Training [15/16] Loss: 0.00470 +Epoch [2176/4000] Training [16/16] Loss: 0.00527 +Epoch [2176/4000] Training metric {'Train/mean dice_metric': 0.9964742064476013, 'Train/mean miou_metric': 0.9927164316177368, 'Train/mean f1': 0.9921961426734924, 'Train/mean precision': 0.9876687526702881, 'Train/mean recall': 0.9967652559280396, 'Train/mean hd95_metric': 0.9949442148208618} +Epoch [2176/4000] Validation [1/4] Loss: 0.32794 focal_loss 0.25584 dice_loss 0.07210 +Epoch [2176/4000] Validation [2/4] Loss: 0.54357 focal_loss 0.35195 dice_loss 0.19163 +Epoch [2176/4000] Validation [3/4] Loss: 0.27011 focal_loss 0.18960 dice_loss 0.08051 +Epoch [2176/4000] Validation [4/4] Loss: 0.22923 focal_loss 0.13722 dice_loss 0.09201 +Epoch [2176/4000] Validation metric {'Val/mean dice_metric': 0.972608208656311, 'Val/mean miou_metric': 0.9565590023994446, 'Val/mean f1': 0.973701536655426, 'Val/mean precision': 0.9721397161483765, 'Val/mean recall': 0.9752684235572815, 'Val/mean hd95_metric': 5.931639671325684} +Cheakpoint... +Epoch [2176/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972608208656311, 'Val/mean miou_metric': 0.9565590023994446, 'Val/mean f1': 0.973701536655426, 'Val/mean precision': 0.9721397161483765, 'Val/mean recall': 0.9752684235572815, 'Val/mean hd95_metric': 5.931639671325684} +Epoch [2177/4000] Training [1/16] Loss: 0.00530 +Epoch [2177/4000] Training [2/16] Loss: 0.00491 +Epoch [2177/4000] Training [3/16] Loss: 0.00701 +Epoch [2177/4000] Training [4/16] Loss: 0.00482 +Epoch [2177/4000] Training [5/16] Loss: 0.00448 +Epoch [2177/4000] Training [6/16] Loss: 0.00746 +Epoch [2177/4000] Training [7/16] Loss: 0.00428 +Epoch [2177/4000] Training [8/16] Loss: 0.00578 +Epoch [2177/4000] Training [9/16] Loss: 0.00379 +Epoch [2177/4000] Training [10/16] Loss: 0.00466 +Epoch [2177/4000] Training [11/16] Loss: 0.00572 +Epoch [2177/4000] Training [12/16] Loss: 0.00563 +Epoch [2177/4000] Training [13/16] Loss: 0.00602 +Epoch [2177/4000] Training [14/16] Loss: 0.00429 +Epoch [2177/4000] Training [15/16] Loss: 0.00686 +Epoch [2177/4000] Training [16/16] Loss: 0.00524 +Epoch [2177/4000] Training metric {'Train/mean dice_metric': 0.9965807199478149, 'Train/mean miou_metric': 0.9929221868515015, 'Train/mean f1': 0.9921456575393677, 'Train/mean precision': 0.9876989722251892, 'Train/mean recall': 0.99663245677948, 'Train/mean hd95_metric': 0.9885258674621582} +Epoch [2177/4000] Validation [1/4] Loss: 0.35221 focal_loss 0.27651 dice_loss 0.07570 +Epoch [2177/4000] Validation [2/4] Loss: 0.32089 focal_loss 0.18438 dice_loss 0.13651 +Epoch [2177/4000] Validation [3/4] Loss: 0.22944 focal_loss 0.16730 dice_loss 0.06213 +Epoch [2177/4000] Validation [4/4] Loss: 0.25879 focal_loss 0.16524 dice_loss 0.09355 +Epoch [2177/4000] Validation metric {'Val/mean dice_metric': 0.9744724035263062, 'Val/mean miou_metric': 0.9585254788398743, 'Val/mean f1': 0.974361777305603, 'Val/mean precision': 0.9709187746047974, 'Val/mean recall': 0.9778293371200562, 'Val/mean hd95_metric': 5.849775791168213} +Cheakpoint... +Epoch [2177/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744724035263062, 'Val/mean miou_metric': 0.9585254788398743, 'Val/mean f1': 0.974361777305603, 'Val/mean precision': 0.9709187746047974, 'Val/mean recall': 0.9778293371200562, 'Val/mean hd95_metric': 5.849775791168213} +Epoch [2178/4000] Training [1/16] Loss: 0.00653 +Epoch [2178/4000] Training [2/16] Loss: 0.00438 +Epoch [2178/4000] Training [3/16] Loss: 0.00521 +Epoch [2178/4000] Training [4/16] Loss: 0.00483 +Epoch [2178/4000] Training [5/16] Loss: 0.00506 +Epoch [2178/4000] Training [6/16] Loss: 0.00577 +Epoch [2178/4000] Training [7/16] Loss: 0.00563 +Epoch [2178/4000] Training [8/16] Loss: 0.00442 +Epoch [2178/4000] Training [9/16] Loss: 0.00587 +Epoch [2178/4000] Training [10/16] Loss: 0.00408 +Epoch [2178/4000] Training [11/16] Loss: 0.00703 +Epoch [2178/4000] Training [12/16] Loss: 0.00449 +Epoch [2178/4000] Training [13/16] Loss: 0.00433 +Epoch [2178/4000] Training [14/16] Loss: 0.00697 +Epoch [2178/4000] Training [15/16] Loss: 0.00477 +Epoch [2178/4000] Training [16/16] Loss: 0.00443 +Epoch [2178/4000] Training metric {'Train/mean dice_metric': 0.9965764284133911, 'Train/mean miou_metric': 0.9928979277610779, 'Train/mean f1': 0.9920627474784851, 'Train/mean precision': 0.9873825907707214, 'Train/mean recall': 0.9967874884605408, 'Train/mean hd95_metric': 0.9878278970718384} +Epoch [2178/4000] Validation [1/4] Loss: 0.32091 focal_loss 0.25242 dice_loss 0.06848 +Epoch [2178/4000] Validation [2/4] Loss: 0.32765 focal_loss 0.19543 dice_loss 0.13222 +Epoch [2178/4000] Validation [3/4] Loss: 0.25684 focal_loss 0.17456 dice_loss 0.08229 +Epoch [2178/4000] Validation [4/4] Loss: 0.21244 focal_loss 0.13785 dice_loss 0.07459 +Epoch [2178/4000] Validation metric {'Val/mean dice_metric': 0.9743801951408386, 'Val/mean miou_metric': 0.9581683874130249, 'Val/mean f1': 0.974577784538269, 'Val/mean precision': 0.9717714786529541, 'Val/mean recall': 0.9774002432823181, 'Val/mean hd95_metric': 5.712158679962158} +Cheakpoint... +Epoch [2178/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743801951408386, 'Val/mean miou_metric': 0.9581683874130249, 'Val/mean f1': 0.974577784538269, 'Val/mean precision': 0.9717714786529541, 'Val/mean recall': 0.9774002432823181, 'Val/mean hd95_metric': 5.712158679962158} +Epoch [2179/4000] Training [1/16] Loss: 0.00455 +Epoch [2179/4000] Training [2/16] Loss: 0.01252 +Epoch [2179/4000] Training [3/16] Loss: 0.00505 +Epoch [2179/4000] Training [4/16] Loss: 0.00469 +Epoch [2179/4000] Training [5/16] Loss: 0.00472 +Epoch [2179/4000] Training [6/16] Loss: 0.00404 +Epoch [2179/4000] Training [7/16] Loss: 0.00604 +Epoch [2179/4000] Training [8/16] Loss: 0.00586 +Epoch [2179/4000] Training [9/16] Loss: 0.00558 +Epoch [2179/4000] Training [10/16] Loss: 0.00507 +Epoch [2179/4000] Training [11/16] Loss: 0.00611 +Epoch [2179/4000] Training [12/16] Loss: 0.00577 +Epoch [2179/4000] Training [13/16] Loss: 0.00448 +Epoch [2179/4000] Training [14/16] Loss: 0.00721 +Epoch [2179/4000] Training [15/16] Loss: 0.00560 +Epoch [2179/4000] Training [16/16] Loss: 0.00395 +Epoch [2179/4000] Training metric {'Train/mean dice_metric': 0.9963628053665161, 'Train/mean miou_metric': 0.9924918413162231, 'Train/mean f1': 0.9920037388801575, 'Train/mean precision': 0.9875851273536682, 'Train/mean recall': 0.9964619874954224, 'Train/mean hd95_metric': 1.0133039951324463} +Epoch [2179/4000] Validation [1/4] Loss: 0.28098 focal_loss 0.22035 dice_loss 0.06063 +Epoch [2179/4000] Validation [2/4] Loss: 0.50326 focal_loss 0.34770 dice_loss 0.15556 +Epoch [2179/4000] Validation [3/4] Loss: 0.32328 focal_loss 0.22933 dice_loss 0.09395 +Epoch [2179/4000] Validation [4/4] Loss: 0.30487 focal_loss 0.20876 dice_loss 0.09611 +Epoch [2179/4000] Validation metric {'Val/mean dice_metric': 0.9729827642440796, 'Val/mean miou_metric': 0.9569025039672852, 'Val/mean f1': 0.9749844670295715, 'Val/mean precision': 0.972051739692688, 'Val/mean recall': 0.9779349565505981, 'Val/mean hd95_metric': 5.854372024536133} +Cheakpoint... +Epoch [2179/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729827642440796, 'Val/mean miou_metric': 0.9569025039672852, 'Val/mean f1': 0.9749844670295715, 'Val/mean precision': 0.972051739692688, 'Val/mean recall': 0.9779349565505981, 'Val/mean hd95_metric': 5.854372024536133} +Epoch [2180/4000] Training [1/16] Loss: 0.00680 +Epoch [2180/4000] Training [2/16] Loss: 0.00390 +Epoch [2180/4000] Training [3/16] Loss: 0.00513 +Epoch [2180/4000] Training [4/16] Loss: 0.00436 +Epoch [2180/4000] Training [5/16] Loss: 0.00626 +Epoch [2180/4000] Training [6/16] Loss: 0.00753 +Epoch [2180/4000] Training [7/16] Loss: 0.00731 +Epoch [2180/4000] Training [8/16] Loss: 0.00615 +Epoch [2180/4000] Training [9/16] Loss: 0.00560 +Epoch [2180/4000] Training [10/16] Loss: 0.00481 +Epoch [2180/4000] Training [11/16] Loss: 0.00567 +Epoch [2180/4000] Training [12/16] Loss: 0.00684 +Epoch [2180/4000] Training [13/16] Loss: 0.00666 +Epoch [2180/4000] Training [14/16] Loss: 0.00513 +Epoch [2180/4000] Training [15/16] Loss: 0.00554 +Epoch [2180/4000] Training [16/16] Loss: 0.00519 +Epoch [2180/4000] Training metric {'Train/mean dice_metric': 0.9963759183883667, 'Train/mean miou_metric': 0.9924997091293335, 'Train/mean f1': 0.9919715523719788, 'Train/mean precision': 0.9872676134109497, 'Train/mean recall': 0.996720552444458, 'Train/mean hd95_metric': 1.0135968923568726} +Epoch [2180/4000] Validation [1/4] Loss: 0.38864 focal_loss 0.31151 dice_loss 0.07714 +Epoch [2180/4000] Validation [2/4] Loss: 0.30625 focal_loss 0.19438 dice_loss 0.11187 +Epoch [2180/4000] Validation [3/4] Loss: 0.23386 focal_loss 0.16508 dice_loss 0.06878 +Epoch [2180/4000] Validation [4/4] Loss: 0.22191 focal_loss 0.13889 dice_loss 0.08302 +Epoch [2180/4000] Validation metric {'Val/mean dice_metric': 0.9739831686019897, 'Val/mean miou_metric': 0.9578927755355835, 'Val/mean f1': 0.9749176502227783, 'Val/mean precision': 0.9725100994110107, 'Val/mean recall': 0.977337121963501, 'Val/mean hd95_metric': 5.745162010192871} +Cheakpoint... +Epoch [2180/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739831686019897, 'Val/mean miou_metric': 0.9578927755355835, 'Val/mean f1': 0.9749176502227783, 'Val/mean precision': 0.9725100994110107, 'Val/mean recall': 0.977337121963501, 'Val/mean hd95_metric': 5.745162010192871} +Epoch [2181/4000] Training [1/16] Loss: 0.00615 +Epoch [2181/4000] Training [2/16] Loss: 0.00454 +Epoch [2181/4000] Training [3/16] Loss: 0.00541 +Epoch [2181/4000] Training [4/16] Loss: 0.00566 +Epoch [2181/4000] Training [5/16] Loss: 0.00583 +Epoch [2181/4000] Training [6/16] Loss: 0.00516 +Epoch [2181/4000] Training [7/16] Loss: 0.00620 +Epoch [2181/4000] Training [8/16] Loss: 0.00589 +Epoch [2181/4000] Training [9/16] Loss: 0.00540 +Epoch [2181/4000] Training [10/16] Loss: 0.00675 +Epoch [2181/4000] Training [11/16] Loss: 0.00569 +Epoch [2181/4000] Training [12/16] Loss: 0.00494 +Epoch [2181/4000] Training [13/16] Loss: 0.00540 +Epoch [2181/4000] Training [14/16] Loss: 0.00487 +Epoch [2181/4000] Training [15/16] Loss: 0.00664 +Epoch [2181/4000] Training [16/16] Loss: 0.00514 +Epoch [2181/4000] Training metric {'Train/mean dice_metric': 0.9963794946670532, 'Train/mean miou_metric': 0.9925069808959961, 'Train/mean f1': 0.991802990436554, 'Train/mean precision': 0.9870992302894592, 'Train/mean recall': 0.9965517520904541, 'Train/mean hd95_metric': 1.0055793523788452} +Epoch [2181/4000] Validation [1/4] Loss: 0.29288 focal_loss 0.22603 dice_loss 0.06685 +Epoch [2181/4000] Validation [2/4] Loss: 0.58260 focal_loss 0.40196 dice_loss 0.18064 +Epoch [2181/4000] Validation [3/4] Loss: 0.23764 focal_loss 0.16780 dice_loss 0.06984 +Epoch [2181/4000] Validation [4/4] Loss: 0.35694 focal_loss 0.22638 dice_loss 0.13055 +Epoch [2181/4000] Validation metric {'Val/mean dice_metric': 0.9720093607902527, 'Val/mean miou_metric': 0.9554827809333801, 'Val/mean f1': 0.9743484258651733, 'Val/mean precision': 0.9724925756454468, 'Val/mean recall': 0.9762113690376282, 'Val/mean hd95_metric': 5.9367594718933105} +Cheakpoint... +Epoch [2181/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720093607902527, 'Val/mean miou_metric': 0.9554827809333801, 'Val/mean f1': 0.9743484258651733, 'Val/mean precision': 0.9724925756454468, 'Val/mean recall': 0.9762113690376282, 'Val/mean hd95_metric': 5.9367594718933105} +Epoch [2182/4000] Training [1/16] Loss: 0.00407 +Epoch [2182/4000] Training [2/16] Loss: 0.00624 +Epoch [2182/4000] Training [3/16] Loss: 0.00572 +Epoch [2182/4000] Training [4/16] Loss: 0.00402 +Epoch [2182/4000] Training [5/16] Loss: 0.00548 +Epoch [2182/4000] Training [6/16] Loss: 0.00440 +Epoch [2182/4000] Training [7/16] Loss: 0.00563 +Epoch [2182/4000] Training [8/16] Loss: 0.00497 +Epoch [2182/4000] Training [9/16] Loss: 0.00742 +Epoch [2182/4000] Training [10/16] Loss: 0.00422 +Epoch [2182/4000] Training [11/16] Loss: 0.00645 +Epoch [2182/4000] Training [12/16] Loss: 0.00605 +Epoch [2182/4000] Training [13/16] Loss: 0.00635 +Epoch [2182/4000] Training [14/16] Loss: 0.00482 +Epoch [2182/4000] Training [15/16] Loss: 0.00585 +Epoch [2182/4000] Training [16/16] Loss: 0.00477 +Epoch [2182/4000] Training metric {'Train/mean dice_metric': 0.9963936805725098, 'Train/mean miou_metric': 0.9925510883331299, 'Train/mean f1': 0.992119312286377, 'Train/mean precision': 0.9877294301986694, 'Train/mean recall': 0.9965482950210571, 'Train/mean hd95_metric': 0.9947642087936401} +Epoch [2182/4000] Validation [1/4] Loss: 0.37947 focal_loss 0.30312 dice_loss 0.07634 +Epoch [2182/4000] Validation [2/4] Loss: 0.36651 focal_loss 0.24107 dice_loss 0.12544 +Epoch [2182/4000] Validation [3/4] Loss: 0.24937 focal_loss 0.17982 dice_loss 0.06955 +Epoch [2182/4000] Validation [4/4] Loss: 0.40157 focal_loss 0.27403 dice_loss 0.12755 +Epoch [2182/4000] Validation metric {'Val/mean dice_metric': 0.9707908630371094, 'Val/mean miou_metric': 0.9545475244522095, 'Val/mean f1': 0.9740481376647949, 'Val/mean precision': 0.9743718504905701, 'Val/mean recall': 0.9737245440483093, 'Val/mean hd95_metric': 5.511717796325684} +Cheakpoint... +Epoch [2182/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707908630371094, 'Val/mean miou_metric': 0.9545475244522095, 'Val/mean f1': 0.9740481376647949, 'Val/mean precision': 0.9743718504905701, 'Val/mean recall': 0.9737245440483093, 'Val/mean hd95_metric': 5.511717796325684} +Epoch [2183/4000] Training [1/16] Loss: 0.00597 +Epoch [2183/4000] Training [2/16] Loss: 0.00524 +Epoch [2183/4000] Training [3/16] Loss: 0.00554 +Epoch [2183/4000] Training [4/16] Loss: 0.00645 +Epoch [2183/4000] Training [5/16] Loss: 0.00463 +Epoch [2183/4000] Training [6/16] Loss: 0.00511 +Epoch [2183/4000] Training [7/16] Loss: 0.00589 +Epoch [2183/4000] Training [8/16] Loss: 0.00435 +Epoch [2183/4000] Training [9/16] Loss: 0.00559 +Epoch [2183/4000] Training [10/16] Loss: 0.00557 +Epoch [2183/4000] Training [11/16] Loss: 0.00485 +Epoch [2183/4000] Training [12/16] Loss: 0.00398 +Epoch [2183/4000] Training [13/16] Loss: 0.00447 +Epoch [2183/4000] Training [14/16] Loss: 0.00491 +Epoch [2183/4000] Training [15/16] Loss: 0.00494 +Epoch [2183/4000] Training [16/16] Loss: 0.00353 +Epoch [2183/4000] Training metric {'Train/mean dice_metric': 0.9966379404067993, 'Train/mean miou_metric': 0.9929935932159424, 'Train/mean f1': 0.991189181804657, 'Train/mean precision': 0.9857720136642456, 'Train/mean recall': 0.9966662526130676, 'Train/mean hd95_metric': 1.0189929008483887} +Epoch [2183/4000] Validation [1/4] Loss: 0.29438 focal_loss 0.22388 dice_loss 0.07050 +Epoch [2183/4000] Validation [2/4] Loss: 0.58145 focal_loss 0.39387 dice_loss 0.18758 +Epoch [2183/4000] Validation [3/4] Loss: 0.22660 focal_loss 0.14505 dice_loss 0.08154 +Epoch [2183/4000] Validation [4/4] Loss: 0.48889 focal_loss 0.34926 dice_loss 0.13963 +Epoch [2183/4000] Validation metric {'Val/mean dice_metric': 0.9720328450202942, 'Val/mean miou_metric': 0.9557052850723267, 'Val/mean f1': 0.972949206829071, 'Val/mean precision': 0.9717557430267334, 'Val/mean recall': 0.9741455912590027, 'Val/mean hd95_metric': 5.388026237487793} +Cheakpoint... +Epoch [2183/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720328450202942, 'Val/mean miou_metric': 0.9557052850723267, 'Val/mean f1': 0.972949206829071, 'Val/mean precision': 0.9717557430267334, 'Val/mean recall': 0.9741455912590027, 'Val/mean hd95_metric': 5.388026237487793} +Epoch [2184/4000] Training [1/16] Loss: 0.00503 +Epoch [2184/4000] Training [2/16] Loss: 0.00414 +Epoch [2184/4000] Training [3/16] Loss: 0.00393 +Epoch [2184/4000] Training [4/16] Loss: 0.00474 +Epoch [2184/4000] Training [5/16] Loss: 0.00478 +Epoch [2184/4000] Training [6/16] Loss: 0.00617 +Epoch [2184/4000] Training [7/16] Loss: 0.00764 +Epoch [2184/4000] Training [8/16] Loss: 0.00386 +Epoch [2184/4000] Training [9/16] Loss: 0.00436 +Epoch [2184/4000] Training [10/16] Loss: 0.00499 +Epoch [2184/4000] Training [11/16] Loss: 0.00684 +Epoch [2184/4000] Training [12/16] Loss: 0.00367 +Epoch [2184/4000] Training [13/16] Loss: 0.00460 +Epoch [2184/4000] Training [14/16] Loss: 0.00461 +Epoch [2184/4000] Training [15/16] Loss: 0.00579 +Epoch [2184/4000] Training [16/16] Loss: 0.00522 +Epoch [2184/4000] Training metric {'Train/mean dice_metric': 0.9966387152671814, 'Train/mean miou_metric': 0.993016242980957, 'Train/mean f1': 0.991676390171051, 'Train/mean precision': 0.9865386486053467, 'Train/mean recall': 0.9968677759170532, 'Train/mean hd95_metric': 1.475551962852478} +Epoch [2184/4000] Validation [1/4] Loss: 0.40151 focal_loss 0.32316 dice_loss 0.07835 +Epoch [2184/4000] Validation [2/4] Loss: 0.33836 focal_loss 0.22112 dice_loss 0.11724 +Epoch [2184/4000] Validation [3/4] Loss: 0.18666 focal_loss 0.13273 dice_loss 0.05393 +Epoch [2184/4000] Validation [4/4] Loss: 0.43342 focal_loss 0.29181 dice_loss 0.14161 +Epoch [2184/4000] Validation metric {'Val/mean dice_metric': 0.9719529151916504, 'Val/mean miou_metric': 0.9557199478149414, 'Val/mean f1': 0.9738373756408691, 'Val/mean precision': 0.9734513759613037, 'Val/mean recall': 0.9742236137390137, 'Val/mean hd95_metric': 6.158508777618408} +Cheakpoint... +Epoch [2184/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719529151916504, 'Val/mean miou_metric': 0.9557199478149414, 'Val/mean f1': 0.9738373756408691, 'Val/mean precision': 0.9734513759613037, 'Val/mean recall': 0.9742236137390137, 'Val/mean hd95_metric': 6.158508777618408} +Epoch [2185/4000] Training [1/16] Loss: 0.00591 +Epoch [2185/4000] Training [2/16] Loss: 0.00569 +Epoch [2185/4000] Training [3/16] Loss: 0.00412 +Epoch [2185/4000] Training [4/16] Loss: 0.00458 +Epoch [2185/4000] Training [5/16] Loss: 0.00455 +Epoch [2185/4000] Training [6/16] Loss: 0.00718 +Epoch [2185/4000] Training [7/16] Loss: 0.00600 +Epoch [2185/4000] Training [8/16] Loss: 0.00492 +Epoch [2185/4000] Training [9/16] Loss: 0.00472 +Epoch [2185/4000] Training [10/16] Loss: 0.00540 +Epoch [2185/4000] Training [11/16] Loss: 0.00411 +Epoch [2185/4000] Training [12/16] Loss: 0.00582 +Epoch [2185/4000] Training [13/16] Loss: 0.00706 +Epoch [2185/4000] Training [14/16] Loss: 0.00531 +Epoch [2185/4000] Training [15/16] Loss: 0.00370 +Epoch [2185/4000] Training [16/16] Loss: 0.00471 +Epoch [2185/4000] Training metric {'Train/mean dice_metric': 0.9963740110397339, 'Train/mean miou_metric': 0.9925122857093811, 'Train/mean f1': 0.9921039938926697, 'Train/mean precision': 0.9875471591949463, 'Train/mean recall': 0.9967030882835388, 'Train/mean hd95_metric': 1.0007117986679077} +Epoch [2185/4000] Validation [1/4] Loss: 0.27522 focal_loss 0.21650 dice_loss 0.05872 +Epoch [2185/4000] Validation [2/4] Loss: 0.76878 focal_loss 0.52929 dice_loss 0.23949 +Epoch [2185/4000] Validation [3/4] Loss: 0.25970 focal_loss 0.18364 dice_loss 0.07606 +Epoch [2185/4000] Validation [4/4] Loss: 0.32580 focal_loss 0.20971 dice_loss 0.11609 +Epoch [2185/4000] Validation metric {'Val/mean dice_metric': 0.9712123870849609, 'Val/mean miou_metric': 0.9549045562744141, 'Val/mean f1': 0.9744461178779602, 'Val/mean precision': 0.9708387851715088, 'Val/mean recall': 0.9780803322792053, 'Val/mean hd95_metric': 6.809432029724121} +Cheakpoint... +Epoch [2185/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712123870849609, 'Val/mean miou_metric': 0.9549045562744141, 'Val/mean f1': 0.9744461178779602, 'Val/mean precision': 0.9708387851715088, 'Val/mean recall': 0.9780803322792053, 'Val/mean hd95_metric': 6.809432029724121} +Epoch [2186/4000] Training [1/16] Loss: 0.00545 +Epoch [2186/4000] Training [2/16] Loss: 0.00456 +Epoch [2186/4000] Training [3/16] Loss: 0.00463 +Epoch [2186/4000] Training [4/16] Loss: 0.00469 +Epoch [2186/4000] Training [5/16] Loss: 0.00574 +Epoch [2186/4000] Training [6/16] Loss: 0.00441 +Epoch [2186/4000] Training [7/16] Loss: 0.00506 +Epoch [2186/4000] Training [8/16] Loss: 0.00535 +Epoch [2186/4000] Training [9/16] Loss: 0.00877 +Epoch [2186/4000] Training [10/16] Loss: 0.00715 +Epoch [2186/4000] Training [11/16] Loss: 0.00427 +Epoch [2186/4000] Training [12/16] Loss: 0.00411 +Epoch [2186/4000] Training [13/16] Loss: 0.00890 +Epoch [2186/4000] Training [14/16] Loss: 0.00471 +Epoch [2186/4000] Training [15/16] Loss: 0.00518 +Epoch [2186/4000] Training [16/16] Loss: 0.00460 +Epoch [2186/4000] Training metric {'Train/mean dice_metric': 0.9964662790298462, 'Train/mean miou_metric': 0.9926950335502625, 'Train/mean f1': 0.9921451210975647, 'Train/mean precision': 0.9876672625541687, 'Train/mean recall': 0.9966638088226318, 'Train/mean hd95_metric': 1.0452959537506104} +Epoch [2186/4000] Validation [1/4] Loss: 0.29877 focal_loss 0.23339 dice_loss 0.06537 +Epoch [2186/4000] Validation [2/4] Loss: 0.40360 focal_loss 0.26811 dice_loss 0.13549 +Epoch [2186/4000] Validation [3/4] Loss: 0.25675 focal_loss 0.17634 dice_loss 0.08040 +Epoch [2186/4000] Validation [4/4] Loss: 0.30916 focal_loss 0.19958 dice_loss 0.10957 +Epoch [2186/4000] Validation metric {'Val/mean dice_metric': 0.9735217094421387, 'Val/mean miou_metric': 0.9572011828422546, 'Val/mean f1': 0.9750914573669434, 'Val/mean precision': 0.9736352562904358, 'Val/mean recall': 0.9765520691871643, 'Val/mean hd95_metric': 5.748063564300537} +Cheakpoint... +Epoch [2186/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735217094421387, 'Val/mean miou_metric': 0.9572011828422546, 'Val/mean f1': 0.9750914573669434, 'Val/mean precision': 0.9736352562904358, 'Val/mean recall': 0.9765520691871643, 'Val/mean hd95_metric': 5.748063564300537} +Epoch [2187/4000] Training [1/16] Loss: 0.00531 +Epoch [2187/4000] Training [2/16] Loss: 0.00445 +Epoch [2187/4000] Training [3/16] Loss: 0.00516 +Epoch [2187/4000] Training [4/16] Loss: 0.00581 +Epoch [2187/4000] Training [5/16] Loss: 0.00478 +Epoch [2187/4000] Training [6/16] Loss: 0.00530 +Epoch [2187/4000] Training [7/16] Loss: 0.00621 +Epoch [2187/4000] Training [8/16] Loss: 0.00398 +Epoch [2187/4000] Training [9/16] Loss: 0.00484 +Epoch [2187/4000] Training [10/16] Loss: 0.00698 +Epoch [2187/4000] Training [11/16] Loss: 0.00613 +Epoch [2187/4000] Training [12/16] Loss: 0.00612 +Epoch [2187/4000] Training [13/16] Loss: 0.00468 +Epoch [2187/4000] Training [14/16] Loss: 0.00627 +Epoch [2187/4000] Training [15/16] Loss: 0.00596 +Epoch [2187/4000] Training [16/16] Loss: 0.00517 +Epoch [2187/4000] Training metric {'Train/mean dice_metric': 0.9965083599090576, 'Train/mean miou_metric': 0.9927572011947632, 'Train/mean f1': 0.9918241500854492, 'Train/mean precision': 0.9870333075523376, 'Train/mean recall': 0.9966617226600647, 'Train/mean hd95_metric': 1.0710402727127075} +Epoch [2187/4000] Validation [1/4] Loss: 0.27996 focal_loss 0.21855 dice_loss 0.06141 +Epoch [2187/4000] Validation [2/4] Loss: 0.85998 focal_loss 0.62642 dice_loss 0.23356 +Epoch [2187/4000] Validation [3/4] Loss: 0.29544 focal_loss 0.20488 dice_loss 0.09056 +Epoch [2187/4000] Validation [4/4] Loss: 0.25331 focal_loss 0.16012 dice_loss 0.09319 +Epoch [2187/4000] Validation metric {'Val/mean dice_metric': 0.972943902015686, 'Val/mean miou_metric': 0.9574018716812134, 'Val/mean f1': 0.9752823710441589, 'Val/mean precision': 0.9721251726150513, 'Val/mean recall': 0.9784601926803589, 'Val/mean hd95_metric': 5.670711040496826} +Cheakpoint... +Epoch [2187/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972943902015686, 'Val/mean miou_metric': 0.9574018716812134, 'Val/mean f1': 0.9752823710441589, 'Val/mean precision': 0.9721251726150513, 'Val/mean recall': 0.9784601926803589, 'Val/mean hd95_metric': 5.670711040496826} +Epoch [2188/4000] Training [1/16] Loss: 0.00506 +Epoch [2188/4000] Training [2/16] Loss: 0.00568 +Epoch [2188/4000] Training [3/16] Loss: 0.00481 +Epoch [2188/4000] Training [4/16] Loss: 0.00625 +Epoch [2188/4000] Training [5/16] Loss: 0.00723 +Epoch [2188/4000] Training [6/16] Loss: 0.00466 +Epoch [2188/4000] Training [7/16] Loss: 0.00620 +Epoch [2188/4000] Training [8/16] Loss: 0.00453 +Epoch [2188/4000] Training [9/16] Loss: 0.00564 +Epoch [2188/4000] Training [10/16] Loss: 0.00426 +Epoch [2188/4000] Training [11/16] Loss: 0.00479 +Epoch [2188/4000] Training [12/16] Loss: 0.00688 +Epoch [2188/4000] Training [13/16] Loss: 0.00462 +Epoch [2188/4000] Training [14/16] Loss: 0.00716 +Epoch [2188/4000] Training [15/16] Loss: 0.00525 +Epoch [2188/4000] Training [16/16] Loss: 0.00333 +Epoch [2188/4000] Training metric {'Train/mean dice_metric': 0.9964575171470642, 'Train/mean miou_metric': 0.9926787614822388, 'Train/mean f1': 0.9921200275421143, 'Train/mean precision': 0.9875229001045227, 'Train/mean recall': 0.9967602491378784, 'Train/mean hd95_metric': 1.0160210132598877} +Epoch [2188/4000] Validation [1/4] Loss: 0.27819 focal_loss 0.21668 dice_loss 0.06151 +Epoch [2188/4000] Validation [2/4] Loss: 0.33736 focal_loss 0.22885 dice_loss 0.10851 +Epoch [2188/4000] Validation [3/4] Loss: 0.26782 focal_loss 0.18426 dice_loss 0.08356 +Epoch [2188/4000] Validation [4/4] Loss: 0.25318 focal_loss 0.15700 dice_loss 0.09618 +Epoch [2188/4000] Validation metric {'Val/mean dice_metric': 0.9741212725639343, 'Val/mean miou_metric': 0.9580504298210144, 'Val/mean f1': 0.9749646782875061, 'Val/mean precision': 0.9728538990020752, 'Val/mean recall': 0.9770846366882324, 'Val/mean hd95_metric': 5.254083156585693} +Cheakpoint... +Epoch [2188/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741212725639343, 'Val/mean miou_metric': 0.9580504298210144, 'Val/mean f1': 0.9749646782875061, 'Val/mean precision': 0.9728538990020752, 'Val/mean recall': 0.9770846366882324, 'Val/mean hd95_metric': 5.254083156585693} +Epoch [2189/4000] Training [1/16] Loss: 0.00447 +Epoch [2189/4000] Training [2/16] Loss: 0.00717 +Epoch [2189/4000] Training [3/16] Loss: 0.00679 +Epoch [2189/4000] Training [4/16] Loss: 0.00507 +Epoch [2189/4000] Training [5/16] Loss: 0.00616 +Epoch [2189/4000] Training [6/16] Loss: 0.00493 +Epoch [2189/4000] Training [7/16] Loss: 0.00432 +Epoch [2189/4000] Training [8/16] Loss: 0.00909 +Epoch [2189/4000] Training [9/16] Loss: 0.00429 +Epoch [2189/4000] Training [10/16] Loss: 0.00598 +Epoch [2189/4000] Training [11/16] Loss: 0.00748 +Epoch [2189/4000] Training [12/16] Loss: 0.00454 +Epoch [2189/4000] Training [13/16] Loss: 0.00645 +Epoch [2189/4000] Training [14/16] Loss: 0.00444 +Epoch [2189/4000] Training [15/16] Loss: 0.00518 +Epoch [2189/4000] Training [16/16] Loss: 0.00457 +Epoch [2189/4000] Training metric {'Train/mean dice_metric': 0.9961473941802979, 'Train/mean miou_metric': 0.9920535087585449, 'Train/mean f1': 0.9915862679481506, 'Train/mean precision': 0.9868532419204712, 'Train/mean recall': 0.9963648319244385, 'Train/mean hd95_metric': 1.044870376586914} +Epoch [2189/4000] Validation [1/4] Loss: 0.29239 focal_loss 0.22475 dice_loss 0.06764 +Epoch [2189/4000] Validation [2/4] Loss: 0.55454 focal_loss 0.37868 dice_loss 0.17586 +Epoch [2189/4000] Validation [3/4] Loss: 0.38928 focal_loss 0.29710 dice_loss 0.09218 +Epoch [2189/4000] Validation [4/4] Loss: 0.21030 focal_loss 0.12823 dice_loss 0.08206 +Epoch [2189/4000] Validation metric {'Val/mean dice_metric': 0.9735258221626282, 'Val/mean miou_metric': 0.9576911926269531, 'Val/mean f1': 0.9742944836616516, 'Val/mean precision': 0.9694252610206604, 'Val/mean recall': 0.9792128205299377, 'Val/mean hd95_metric': 5.741663455963135} +Cheakpoint... +Epoch [2189/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735258221626282, 'Val/mean miou_metric': 0.9576911926269531, 'Val/mean f1': 0.9742944836616516, 'Val/mean precision': 0.9694252610206604, 'Val/mean recall': 0.9792128205299377, 'Val/mean hd95_metric': 5.741663455963135} +Epoch [2190/4000] Training [1/16] Loss: 0.00521 +Epoch [2190/4000] Training [2/16] Loss: 0.00444 +Epoch [2190/4000] Training [3/16] Loss: 0.00463 +Epoch [2190/4000] Training [4/16] Loss: 0.00514 +Epoch [2190/4000] Training [5/16] Loss: 0.00447 +Epoch [2190/4000] Training [6/16] Loss: 0.00612 +Epoch [2190/4000] Training [7/16] Loss: 0.00491 +Epoch [2190/4000] Training [8/16] Loss: 0.00469 +Epoch [2190/4000] Training [9/16] Loss: 0.00623 +Epoch [2190/4000] Training [10/16] Loss: 0.00623 +Epoch [2190/4000] Training [11/16] Loss: 0.00602 +Epoch [2190/4000] Training [12/16] Loss: 0.00433 +Epoch [2190/4000] Training [13/16] Loss: 0.00402 +Epoch [2190/4000] Training [14/16] Loss: 0.00502 +Epoch [2190/4000] Training [15/16] Loss: 0.00381 +Epoch [2190/4000] Training [16/16] Loss: 0.00535 +Epoch [2190/4000] Training metric {'Train/mean dice_metric': 0.9965765476226807, 'Train/mean miou_metric': 0.9929089546203613, 'Train/mean f1': 0.9921151995658875, 'Train/mean precision': 0.9875516891479492, 'Train/mean recall': 0.9967211484909058, 'Train/mean hd95_metric': 0.9987716674804688} +Epoch [2190/4000] Validation [1/4] Loss: 0.28541 focal_loss 0.22632 dice_loss 0.05909 +Epoch [2190/4000] Validation [2/4] Loss: 0.33293 focal_loss 0.22016 dice_loss 0.11277 +Epoch [2190/4000] Validation [3/4] Loss: 0.21088 focal_loss 0.14948 dice_loss 0.06140 +Epoch [2190/4000] Validation [4/4] Loss: 0.31156 focal_loss 0.19699 dice_loss 0.11457 +Epoch [2190/4000] Validation metric {'Val/mean dice_metric': 0.9721657037734985, 'Val/mean miou_metric': 0.9566333889961243, 'Val/mean f1': 0.974510669708252, 'Val/mean precision': 0.9707892537117004, 'Val/mean recall': 0.9782606363296509, 'Val/mean hd95_metric': 5.770379543304443} +Cheakpoint... +Epoch [2190/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721657037734985, 'Val/mean miou_metric': 0.9566333889961243, 'Val/mean f1': 0.974510669708252, 'Val/mean precision': 0.9707892537117004, 'Val/mean recall': 0.9782606363296509, 'Val/mean hd95_metric': 5.770379543304443} +Epoch [2191/4000] Training [1/16] Loss: 0.00435 +Epoch [2191/4000] Training [2/16] Loss: 0.00397 +Epoch [2191/4000] Training [3/16] Loss: 0.00500 +Epoch [2191/4000] Training [4/16] Loss: 0.00585 +Epoch [2191/4000] Training [5/16] Loss: 0.00567 +Epoch [2191/4000] Training [6/16] Loss: 0.00459 +Epoch [2191/4000] Training [7/16] Loss: 0.00354 +Epoch [2191/4000] Training [8/16] Loss: 0.00535 +Epoch [2191/4000] Training [9/16] Loss: 0.00765 +Epoch [2191/4000] Training [10/16] Loss: 0.00477 +Epoch [2191/4000] Training [11/16] Loss: 0.00586 +Epoch [2191/4000] Training [12/16] Loss: 0.00465 +Epoch [2191/4000] Training [13/16] Loss: 0.00462 +Epoch [2191/4000] Training [14/16] Loss: 0.00424 +Epoch [2191/4000] Training [15/16] Loss: 0.00599 +Epoch [2191/4000] Training [16/16] Loss: 0.00415 +Epoch [2191/4000] Training metric {'Train/mean dice_metric': 0.9964666366577148, 'Train/mean miou_metric': 0.9926953911781311, 'Train/mean f1': 0.9921550750732422, 'Train/mean precision': 0.9876934289932251, 'Train/mean recall': 0.9966571927070618, 'Train/mean hd95_metric': 0.9964449405670166} +Epoch [2191/4000] Validation [1/4] Loss: 0.26851 focal_loss 0.20651 dice_loss 0.06200 +Epoch [2191/4000] Validation [2/4] Loss: 0.32308 focal_loss 0.21422 dice_loss 0.10885 +Epoch [2191/4000] Validation [3/4] Loss: 0.28402 focal_loss 0.19687 dice_loss 0.08715 +Epoch [2191/4000] Validation [4/4] Loss: 0.23551 focal_loss 0.14181 dice_loss 0.09370 +Epoch [2191/4000] Validation metric {'Val/mean dice_metric': 0.9722093343734741, 'Val/mean miou_metric': 0.9562124013900757, 'Val/mean f1': 0.9743537306785583, 'Val/mean precision': 0.9701011180877686, 'Val/mean recall': 0.9786437749862671, 'Val/mean hd95_metric': 5.599114418029785} +Cheakpoint... +Epoch [2191/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722093343734741, 'Val/mean miou_metric': 0.9562124013900757, 'Val/mean f1': 0.9743537306785583, 'Val/mean precision': 0.9701011180877686, 'Val/mean recall': 0.9786437749862671, 'Val/mean hd95_metric': 5.599114418029785} +Epoch [2192/4000] Training [1/16] Loss: 0.00451 +Epoch [2192/4000] Training [2/16] Loss: 0.00574 +Epoch [2192/4000] Training [3/16] Loss: 0.00452 +Epoch [2192/4000] Training [4/16] Loss: 0.00484 +Epoch [2192/4000] Training [5/16] Loss: 0.00407 +Epoch [2192/4000] Training [6/16] Loss: 0.00643 +Epoch [2192/4000] Training [7/16] Loss: 0.00705 +Epoch [2192/4000] Training [8/16] Loss: 0.00513 +Epoch [2192/4000] Training [9/16] Loss: 0.00630 +Epoch [2192/4000] Training [10/16] Loss: 0.00493 +Epoch [2192/4000] Training [11/16] Loss: 0.00446 +Epoch [2192/4000] Training [12/16] Loss: 0.00445 +Epoch [2192/4000] Training [13/16] Loss: 0.00671 +Epoch [2192/4000] Training [14/16] Loss: 0.00595 +Epoch [2192/4000] Training [15/16] Loss: 0.00566 +Epoch [2192/4000] Training [16/16] Loss: 0.00563 +Epoch [2192/4000] Training metric {'Train/mean dice_metric': 0.9964998364448547, 'Train/mean miou_metric': 0.9927512407302856, 'Train/mean f1': 0.991992712020874, 'Train/mean precision': 0.9873947501182556, 'Train/mean recall': 0.9966336488723755, 'Train/mean hd95_metric': 1.0029714107513428} +Epoch [2192/4000] Validation [1/4] Loss: 0.27535 focal_loss 0.21560 dice_loss 0.05975 +Epoch [2192/4000] Validation [2/4] Loss: 0.33938 focal_loss 0.22679 dice_loss 0.11260 +Epoch [2192/4000] Validation [3/4] Loss: 0.31801 focal_loss 0.22876 dice_loss 0.08925 +Epoch [2192/4000] Validation [4/4] Loss: 0.43946 focal_loss 0.31508 dice_loss 0.12438 +Epoch [2192/4000] Validation metric {'Val/mean dice_metric': 0.9731313586235046, 'Val/mean miou_metric': 0.9568331837654114, 'Val/mean f1': 0.9746922850608826, 'Val/mean precision': 0.9723965525627136, 'Val/mean recall': 0.9769989848136902, 'Val/mean hd95_metric': 5.982230186462402} +Cheakpoint... +Epoch [2192/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731313586235046, 'Val/mean miou_metric': 0.9568331837654114, 'Val/mean f1': 0.9746922850608826, 'Val/mean precision': 0.9723965525627136, 'Val/mean recall': 0.9769989848136902, 'Val/mean hd95_metric': 5.982230186462402} +Epoch [2193/4000] Training [1/16] Loss: 0.00507 +Epoch [2193/4000] Training [2/16] Loss: 0.00457 +Epoch [2193/4000] Training [3/16] Loss: 0.00587 +Epoch [2193/4000] Training [4/16] Loss: 0.00649 +Epoch [2193/4000] Training [5/16] Loss: 0.00836 +Epoch [2193/4000] Training [6/16] Loss: 0.00565 +Epoch [2193/4000] Training [7/16] Loss: 0.00678 +Epoch [2193/4000] Training [8/16] Loss: 0.00558 +Epoch [2193/4000] Training [9/16] Loss: 0.00475 +Epoch [2193/4000] Training [10/16] Loss: 0.00337 +Epoch [2193/4000] Training [11/16] Loss: 0.00608 +Epoch [2193/4000] Training [12/16] Loss: 0.00491 +Epoch [2193/4000] Training [13/16] Loss: 0.00431 +Epoch [2193/4000] Training [14/16] Loss: 0.00427 +Epoch [2193/4000] Training [15/16] Loss: 0.00686 +Epoch [2193/4000] Training [16/16] Loss: 0.00744 +Epoch [2193/4000] Training metric {'Train/mean dice_metric': 0.9963569045066833, 'Train/mean miou_metric': 0.9924531579017639, 'Train/mean f1': 0.9916859269142151, 'Train/mean precision': 0.9867745637893677, 'Train/mean recall': 0.9966464638710022, 'Train/mean hd95_metric': 0.9948797225952148} +Epoch [2193/4000] Validation [1/4] Loss: 0.29578 focal_loss 0.22968 dice_loss 0.06609 +Epoch [2193/4000] Validation [2/4] Loss: 0.33775 focal_loss 0.22248 dice_loss 0.11527 +Epoch [2193/4000] Validation [3/4] Loss: 0.20199 focal_loss 0.13943 dice_loss 0.06256 +Epoch [2193/4000] Validation [4/4] Loss: 0.22070 focal_loss 0.13967 dice_loss 0.08103 +Epoch [2193/4000] Validation metric {'Val/mean dice_metric': 0.9727137684822083, 'Val/mean miou_metric': 0.9568220973014832, 'Val/mean f1': 0.9739511013031006, 'Val/mean precision': 0.9709410071372986, 'Val/mean recall': 0.9769798517227173, 'Val/mean hd95_metric': 5.879878520965576} +Cheakpoint... +Epoch [2193/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727137684822083, 'Val/mean miou_metric': 0.9568220973014832, 'Val/mean f1': 0.9739511013031006, 'Val/mean precision': 0.9709410071372986, 'Val/mean recall': 0.9769798517227173, 'Val/mean hd95_metric': 5.879878520965576} +Epoch [2194/4000] Training [1/16] Loss: 0.00473 +Epoch [2194/4000] Training [2/16] Loss: 0.00577 +Epoch [2194/4000] Training [3/16] Loss: 0.00663 +Epoch [2194/4000] Training [4/16] Loss: 0.00652 +Epoch [2194/4000] Training [5/16] Loss: 0.00492 +Epoch [2194/4000] Training [6/16] Loss: 0.00458 +Epoch [2194/4000] Training [7/16] Loss: 0.00675 +Epoch [2194/4000] Training [8/16] Loss: 0.00511 +Epoch [2194/4000] Training [9/16] Loss: 0.00405 +Epoch [2194/4000] Training [10/16] Loss: 0.00644 +Epoch [2194/4000] Training [11/16] Loss: 0.00589 +Epoch [2194/4000] Training [12/16] Loss: 0.00553 +Epoch [2194/4000] Training [13/16] Loss: 0.00817 +Epoch [2194/4000] Training [14/16] Loss: 0.00614 +Epoch [2194/4000] Training [15/16] Loss: 0.00813 +Epoch [2194/4000] Training [16/16] Loss: 0.00535 +Epoch [2194/4000] Training metric {'Train/mean dice_metric': 0.9961672425270081, 'Train/mean miou_metric': 0.9921141862869263, 'Train/mean f1': 0.9920094609260559, 'Train/mean precision': 0.9875085949897766, 'Train/mean recall': 0.9965515732765198, 'Train/mean hd95_metric': 1.0173927545547485} +Epoch [2194/4000] Validation [1/4] Loss: 0.28308 focal_loss 0.21907 dice_loss 0.06401 +Epoch [2194/4000] Validation [2/4] Loss: 0.51016 focal_loss 0.34757 dice_loss 0.16259 +Epoch [2194/4000] Validation [3/4] Loss: 0.21731 focal_loss 0.15048 dice_loss 0.06683 +Epoch [2194/4000] Validation [4/4] Loss: 0.33808 focal_loss 0.22330 dice_loss 0.11477 +Epoch [2194/4000] Validation metric {'Val/mean dice_metric': 0.9746782183647156, 'Val/mean miou_metric': 0.9586417078971863, 'Val/mean f1': 0.9748526215553284, 'Val/mean precision': 0.9716572165489197, 'Val/mean recall': 0.9780691266059875, 'Val/mean hd95_metric': 5.272523880004883} +Cheakpoint... +Epoch [2194/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746782183647156, 'Val/mean miou_metric': 0.9586417078971863, 'Val/mean f1': 0.9748526215553284, 'Val/mean precision': 0.9716572165489197, 'Val/mean recall': 0.9780691266059875, 'Val/mean hd95_metric': 5.272523880004883} +Epoch [2195/4000] Training [1/16] Loss: 0.00602 +Epoch [2195/4000] Training [2/16] Loss: 0.00656 +Epoch [2195/4000] Training [3/16] Loss: 0.00554 +Epoch [2195/4000] Training [4/16] Loss: 0.00649 +Epoch [2195/4000] Training [5/16] Loss: 0.00430 +Epoch [2195/4000] Training [6/16] Loss: 0.00483 +Epoch [2195/4000] Training [7/16] Loss: 0.00551 +Epoch [2195/4000] Training [8/16] Loss: 0.00599 +Epoch [2195/4000] Training [9/16] Loss: 0.00480 +Epoch [2195/4000] Training [10/16] Loss: 0.00433 +Epoch [2195/4000] Training [11/16] Loss: 0.00478 +Epoch [2195/4000] Training [12/16] Loss: 0.00471 +Epoch [2195/4000] Training [13/16] Loss: 0.00612 +Epoch [2195/4000] Training [14/16] Loss: 0.00624 +Epoch [2195/4000] Training [15/16] Loss: 0.00731 +Epoch [2195/4000] Training [16/16] Loss: 0.00515 +Epoch [2195/4000] Training metric {'Train/mean dice_metric': 0.9964091181755066, 'Train/mean miou_metric': 0.9925801157951355, 'Train/mean f1': 0.9921147227287292, 'Train/mean precision': 0.9876834750175476, 'Train/mean recall': 0.9965858459472656, 'Train/mean hd95_metric': 1.018293857574463} +Epoch [2195/4000] Validation [1/4] Loss: 0.28489 focal_loss 0.22175 dice_loss 0.06314 +Epoch [2195/4000] Validation [2/4] Loss: 0.23824 focal_loss 0.15042 dice_loss 0.08781 +Epoch [2195/4000] Validation [3/4] Loss: 0.23440 focal_loss 0.16927 dice_loss 0.06513 +Epoch [2195/4000] Validation [4/4] Loss: 0.26022 focal_loss 0.16541 dice_loss 0.09481 +Epoch [2195/4000] Validation metric {'Val/mean dice_metric': 0.9737926721572876, 'Val/mean miou_metric': 0.9585007429122925, 'Val/mean f1': 0.975386917591095, 'Val/mean precision': 0.9711723923683167, 'Val/mean recall': 0.9796381592750549, 'Val/mean hd95_metric': 5.410674571990967} +Cheakpoint... +Epoch [2195/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737926721572876, 'Val/mean miou_metric': 0.9585007429122925, 'Val/mean f1': 0.975386917591095, 'Val/mean precision': 0.9711723923683167, 'Val/mean recall': 0.9796381592750549, 'Val/mean hd95_metric': 5.410674571990967} +Epoch [2196/4000] Training [1/16] Loss: 0.00668 +Epoch [2196/4000] Training [2/16] Loss: 0.00357 +Epoch [2196/4000] Training [3/16] Loss: 0.00457 +Epoch [2196/4000] Training [4/16] Loss: 0.00755 +Epoch [2196/4000] Training [5/16] Loss: 0.00567 +Epoch [2196/4000] Training [6/16] Loss: 0.00700 +Epoch [2196/4000] Training [7/16] Loss: 0.00471 +Epoch [2196/4000] Training [8/16] Loss: 0.00404 +Epoch [2196/4000] Training [9/16] Loss: 0.00518 +Epoch [2196/4000] Training [10/16] Loss: 0.00421 +Epoch [2196/4000] Training [11/16] Loss: 0.00532 +Epoch [2196/4000] Training [12/16] Loss: 0.00516 +Epoch [2196/4000] Training [13/16] Loss: 0.00430 +Epoch [2196/4000] Training [14/16] Loss: 0.00526 +Epoch [2196/4000] Training [15/16] Loss: 0.00575 +Epoch [2196/4000] Training [16/16] Loss: 0.00594 +Epoch [2196/4000] Training metric {'Train/mean dice_metric': 0.9965871572494507, 'Train/mean miou_metric': 0.9929269552230835, 'Train/mean f1': 0.9920257925987244, 'Train/mean precision': 0.9874154925346375, 'Train/mean recall': 0.996679425239563, 'Train/mean hd95_metric': 0.9954795241355896} +Epoch [2196/4000] Validation [1/4] Loss: 0.23074 focal_loss 0.17137 dice_loss 0.05938 +Epoch [2196/4000] Validation [2/4] Loss: 0.30221 focal_loss 0.20018 dice_loss 0.10203 +Epoch [2196/4000] Validation [3/4] Loss: 0.37842 focal_loss 0.28522 dice_loss 0.09320 +Epoch [2196/4000] Validation [4/4] Loss: 0.58146 focal_loss 0.42522 dice_loss 0.15625 +Epoch [2196/4000] Validation metric {'Val/mean dice_metric': 0.9718786478042603, 'Val/mean miou_metric': 0.9558488726615906, 'Val/mean f1': 0.9738094806671143, 'Val/mean precision': 0.9725850224494934, 'Val/mean recall': 0.9750367999076843, 'Val/mean hd95_metric': 5.7403459548950195} +Cheakpoint... +Epoch [2196/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718786478042603, 'Val/mean miou_metric': 0.9558488726615906, 'Val/mean f1': 0.9738094806671143, 'Val/mean precision': 0.9725850224494934, 'Val/mean recall': 0.9750367999076843, 'Val/mean hd95_metric': 5.7403459548950195} +Epoch [2197/4000] Training [1/16] Loss: 0.00506 +Epoch [2197/4000] Training [2/16] Loss: 0.00426 +Epoch [2197/4000] Training [3/16] Loss: 0.00472 +Epoch [2197/4000] Training [4/16] Loss: 0.00587 +Epoch [2197/4000] Training [5/16] Loss: 0.00647 +Epoch [2197/4000] Training [6/16] Loss: 0.00916 +Epoch [2197/4000] Training [7/16] Loss: 0.00513 +Epoch [2197/4000] Training [8/16] Loss: 0.00459 +Epoch [2197/4000] Training [9/16] Loss: 0.00424 +Epoch [2197/4000] Training [10/16] Loss: 0.00464 +Epoch [2197/4000] Training [11/16] Loss: 0.00352 +Epoch [2197/4000] Training [12/16] Loss: 0.00440 +Epoch [2197/4000] Training [13/16] Loss: 0.00481 +Epoch [2197/4000] Training [14/16] Loss: 0.00760 +Epoch [2197/4000] Training [15/16] Loss: 0.00564 +Epoch [2197/4000] Training [16/16] Loss: 0.00572 +Epoch [2197/4000] Training metric {'Train/mean dice_metric': 0.9964619874954224, 'Train/mean miou_metric': 0.9926875829696655, 'Train/mean f1': 0.9920908808708191, 'Train/mean precision': 0.9876284599304199, 'Train/mean recall': 0.9965937733650208, 'Train/mean hd95_metric': 1.0277113914489746} +Epoch [2197/4000] Validation [1/4] Loss: 0.34576 focal_loss 0.27778 dice_loss 0.06799 +Epoch [2197/4000] Validation [2/4] Loss: 0.57391 focal_loss 0.41508 dice_loss 0.15883 +Epoch [2197/4000] Validation [3/4] Loss: 0.31905 focal_loss 0.22121 dice_loss 0.09784 +Epoch [2197/4000] Validation [4/4] Loss: 0.28738 focal_loss 0.18647 dice_loss 0.10091 +Epoch [2197/4000] Validation metric {'Val/mean dice_metric': 0.9730741381645203, 'Val/mean miou_metric': 0.9573944211006165, 'Val/mean f1': 0.9742114543914795, 'Val/mean precision': 0.9700102210044861, 'Val/mean recall': 0.9784494042396545, 'Val/mean hd95_metric': 5.319754600524902} +Cheakpoint... +Epoch [2197/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730741381645203, 'Val/mean miou_metric': 0.9573944211006165, 'Val/mean f1': 0.9742114543914795, 'Val/mean precision': 0.9700102210044861, 'Val/mean recall': 0.9784494042396545, 'Val/mean hd95_metric': 5.319754600524902} +Epoch [2198/4000] Training [1/16] Loss: 0.00469 +Epoch [2198/4000] Training [2/16] Loss: 0.00440 +Epoch [2198/4000] Training [3/16] Loss: 0.00505 +Epoch [2198/4000] Training [4/16] Loss: 0.00611 +Epoch [2198/4000] Training [5/16] Loss: 0.00490 +Epoch [2198/4000] Training [6/16] Loss: 0.00605 +Epoch [2198/4000] Training [7/16] Loss: 0.00415 +Epoch [2198/4000] Training [8/16] Loss: 0.00566 +Epoch [2198/4000] Training [9/16] Loss: 0.00569 +Epoch [2198/4000] Training [10/16] Loss: 0.00476 +Epoch [2198/4000] Training [11/16] Loss: 0.00475 +Epoch [2198/4000] Training [12/16] Loss: 0.00488 +Epoch [2198/4000] Training [13/16] Loss: 0.00623 +Epoch [2198/4000] Training [14/16] Loss: 0.00578 +Epoch [2198/4000] Training [15/16] Loss: 0.00523 +Epoch [2198/4000] Training [16/16] Loss: 0.00506 +Epoch [2198/4000] Training metric {'Train/mean dice_metric': 0.996619701385498, 'Train/mean miou_metric': 0.9929947853088379, 'Train/mean f1': 0.9921329021453857, 'Train/mean precision': 0.9875544309616089, 'Train/mean recall': 0.996753990650177, 'Train/mean hd95_metric': 0.9914196729660034} +Epoch [2198/4000] Validation [1/4] Loss: 0.26054 focal_loss 0.20366 dice_loss 0.05687 +Epoch [2198/4000] Validation [2/4] Loss: 0.37632 focal_loss 0.25177 dice_loss 0.12456 +Epoch [2198/4000] Validation [3/4] Loss: 0.38754 focal_loss 0.29365 dice_loss 0.09389 +Epoch [2198/4000] Validation [4/4] Loss: 0.37478 focal_loss 0.25133 dice_loss 0.12345 +Epoch [2198/4000] Validation metric {'Val/mean dice_metric': 0.9720872640609741, 'Val/mean miou_metric': 0.9563878774642944, 'Val/mean f1': 0.9750458598136902, 'Val/mean precision': 0.9718670845031738, 'Val/mean recall': 0.9782455563545227, 'Val/mean hd95_metric': 6.216889381408691} +Cheakpoint... +Epoch [2198/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720872640609741, 'Val/mean miou_metric': 0.9563878774642944, 'Val/mean f1': 0.9750458598136902, 'Val/mean precision': 0.9718670845031738, 'Val/mean recall': 0.9782455563545227, 'Val/mean hd95_metric': 6.216889381408691} +Epoch [2199/4000] Training [1/16] Loss: 0.00511 +Epoch [2199/4000] Training [2/16] Loss: 0.00640 +Epoch [2199/4000] Training [3/16] Loss: 0.00704 +Epoch [2199/4000] Training [4/16] Loss: 0.00561 +Epoch [2199/4000] Training [5/16] Loss: 0.00501 +Epoch [2199/4000] Training [6/16] Loss: 0.00568 +Epoch [2199/4000] Training [7/16] Loss: 0.00395 +Epoch [2199/4000] Training [8/16] Loss: 0.00465 +Epoch [2199/4000] Training [9/16] Loss: 0.00556 +Epoch [2199/4000] Training [10/16] Loss: 0.00611 +Epoch [2199/4000] Training [11/16] Loss: 0.00636 +Epoch [2199/4000] Training [12/16] Loss: 0.00510 +Epoch [2199/4000] Training [13/16] Loss: 0.00453 +Epoch [2199/4000] Training [14/16] Loss: 0.00495 +Epoch [2199/4000] Training [15/16] Loss: 0.00410 +Epoch [2199/4000] Training [16/16] Loss: 0.00582 +Epoch [2199/4000] Training metric {'Train/mean dice_metric': 0.9964326620101929, 'Train/mean miou_metric': 0.9926286339759827, 'Train/mean f1': 0.9920947551727295, 'Train/mean precision': 0.9875972867012024, 'Train/mean recall': 0.9966333508491516, 'Train/mean hd95_metric': 1.004045009613037} +Epoch [2199/4000] Validation [1/4] Loss: 0.27455 focal_loss 0.21405 dice_loss 0.06050 +Epoch [2199/4000] Validation [2/4] Loss: 0.37160 focal_loss 0.25846 dice_loss 0.11314 +Epoch [2199/4000] Validation [3/4] Loss: 0.41811 focal_loss 0.32452 dice_loss 0.09359 +Epoch [2199/4000] Validation [4/4] Loss: 0.32244 focal_loss 0.22344 dice_loss 0.09900 +Epoch [2199/4000] Validation metric {'Val/mean dice_metric': 0.9727843999862671, 'Val/mean miou_metric': 0.9568471908569336, 'Val/mean f1': 0.9750648736953735, 'Val/mean precision': 0.9713377952575684, 'Val/mean recall': 0.9788207411766052, 'Val/mean hd95_metric': 5.617255210876465} +Cheakpoint... +Epoch [2199/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727843999862671, 'Val/mean miou_metric': 0.9568471908569336, 'Val/mean f1': 0.9750648736953735, 'Val/mean precision': 0.9713377952575684, 'Val/mean recall': 0.9788207411766052, 'Val/mean hd95_metric': 5.617255210876465} +Epoch [2200/4000] Training [1/16] Loss: 0.00398 +Epoch [2200/4000] Training [2/16] Loss: 0.00683 +Epoch [2200/4000] Training [3/16] Loss: 0.00448 +Epoch [2200/4000] Training [4/16] Loss: 0.00621 +Epoch [2200/4000] Training [5/16] Loss: 0.00510 +Epoch [2200/4000] Training [6/16] Loss: 0.00485 +Epoch [2200/4000] Training [7/16] Loss: 0.00442 +Epoch [2200/4000] Training [8/16] Loss: 0.00434 +Epoch [2200/4000] Training [9/16] Loss: 0.00554 +Epoch [2200/4000] Training [10/16] Loss: 0.00671 +Epoch [2200/4000] Training [11/16] Loss: 0.00557 +Epoch [2200/4000] Training [12/16] Loss: 0.00618 +Epoch [2200/4000] Training [13/16] Loss: 0.00464 +Epoch [2200/4000] Training [14/16] Loss: 0.00591 +Epoch [2200/4000] Training [15/16] Loss: 0.00508 +Epoch [2200/4000] Training [16/16] Loss: 0.00562 +Epoch [2200/4000] Training metric {'Train/mean dice_metric': 0.9964235424995422, 'Train/mean miou_metric': 0.9925855398178101, 'Train/mean f1': 0.9913181662559509, 'Train/mean precision': 0.9861343502998352, 'Train/mean recall': 0.9965566992759705, 'Train/mean hd95_metric': 1.0112007856369019} +Epoch [2200/4000] Validation [1/4] Loss: 0.20656 focal_loss 0.15492 dice_loss 0.05163 +Epoch [2200/4000] Validation [2/4] Loss: 0.61883 focal_loss 0.44792 dice_loss 0.17091 +Epoch [2200/4000] Validation [3/4] Loss: 0.41218 focal_loss 0.31874 dice_loss 0.09344 +Epoch [2200/4000] Validation [4/4] Loss: 0.51249 focal_loss 0.35390 dice_loss 0.15859 +Epoch [2200/4000] Validation metric {'Val/mean dice_metric': 0.9707709550857544, 'Val/mean miou_metric': 0.9548748135566711, 'Val/mean f1': 0.9734296202659607, 'Val/mean precision': 0.9691129922866821, 'Val/mean recall': 0.9777849912643433, 'Val/mean hd95_metric': 6.216442108154297} +Cheakpoint... +Epoch [2200/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707709550857544, 'Val/mean miou_metric': 0.9548748135566711, 'Val/mean f1': 0.9734296202659607, 'Val/mean precision': 0.9691129922866821, 'Val/mean recall': 0.9777849912643433, 'Val/mean hd95_metric': 6.216442108154297} +Epoch [2201/4000] Training [1/16] Loss: 0.00475 +Epoch [2201/4000] Training [2/16] Loss: 0.00482 +Epoch [2201/4000] Training [3/16] Loss: 0.00534 +Epoch [2201/4000] Training [4/16] Loss: 0.00530 +Epoch [2201/4000] Training [5/16] Loss: 0.00589 +Epoch [2201/4000] Training [6/16] Loss: 0.00622 +Epoch [2201/4000] Training [7/16] Loss: 0.00491 +Epoch [2201/4000] Training [8/16] Loss: 0.00691 +Epoch [2201/4000] Training [9/16] Loss: 0.00669 +Epoch [2201/4000] Training [10/16] Loss: 0.00536 +Epoch [2201/4000] Training [11/16] Loss: 0.00604 +Epoch [2201/4000] Training [12/16] Loss: 0.00616 +Epoch [2201/4000] Training [13/16] Loss: 0.00521 +Epoch [2201/4000] Training [14/16] Loss: 0.00554 +Epoch [2201/4000] Training [15/16] Loss: 0.00540 +Epoch [2201/4000] Training [16/16] Loss: 0.00583 +Epoch [2201/4000] Training metric {'Train/mean dice_metric': 0.9961349964141846, 'Train/mean miou_metric': 0.9920403957366943, 'Train/mean f1': 0.9919701218605042, 'Train/mean precision': 0.9875572323799133, 'Train/mean recall': 0.9964225888252258, 'Train/mean hd95_metric': 1.025315284729004} +Epoch [2201/4000] Validation [1/4] Loss: 0.24455 focal_loss 0.18713 dice_loss 0.05742 +Epoch [2201/4000] Validation [2/4] Loss: 0.61699 focal_loss 0.43970 dice_loss 0.17729 +Epoch [2201/4000] Validation [3/4] Loss: 0.37285 focal_loss 0.27859 dice_loss 0.09426 +Epoch [2201/4000] Validation [4/4] Loss: 0.31707 focal_loss 0.21134 dice_loss 0.10573 +Epoch [2201/4000] Validation metric {'Val/mean dice_metric': 0.9722166061401367, 'Val/mean miou_metric': 0.9558847546577454, 'Val/mean f1': 0.9745632410049438, 'Val/mean precision': 0.969258725643158, 'Val/mean recall': 0.9799260497093201, 'Val/mean hd95_metric': 6.642991542816162} +Cheakpoint... +Epoch [2201/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722166061401367, 'Val/mean miou_metric': 0.9558847546577454, 'Val/mean f1': 0.9745632410049438, 'Val/mean precision': 0.969258725643158, 'Val/mean recall': 0.9799260497093201, 'Val/mean hd95_metric': 6.642991542816162} +Epoch [2202/4000] Training [1/16] Loss: 0.00395 +Epoch [2202/4000] Training [2/16] Loss: 0.00443 +Epoch [2202/4000] Training [3/16] Loss: 0.00618 +Epoch [2202/4000] Training [4/16] Loss: 0.00421 +Epoch [2202/4000] Training [5/16] Loss: 0.00624 +Epoch [2202/4000] Training [6/16] Loss: 0.00483 +Epoch [2202/4000] Training [7/16] Loss: 0.00640 +Epoch [2202/4000] Training [8/16] Loss: 0.00504 +Epoch [2202/4000] Training [9/16] Loss: 0.00466 +Epoch [2202/4000] Training [10/16] Loss: 0.00732 +Epoch [2202/4000] Training [11/16] Loss: 0.00392 +Epoch [2202/4000] Training [12/16] Loss: 0.00644 +Epoch [2202/4000] Training [13/16] Loss: 0.00510 +Epoch [2202/4000] Training [14/16] Loss: 0.00465 +Epoch [2202/4000] Training [15/16] Loss: 0.00520 +Epoch [2202/4000] Training [16/16] Loss: 0.00565 +Epoch [2202/4000] Training metric {'Train/mean dice_metric': 0.9966716170310974, 'Train/mean miou_metric': 0.9930955767631531, 'Train/mean f1': 0.9921925067901611, 'Train/mean precision': 0.9875449538230896, 'Train/mean recall': 0.9968840479850769, 'Train/mean hd95_metric': 1.151571273803711} +Epoch [2202/4000] Validation [1/4] Loss: 0.31389 focal_loss 0.24913 dice_loss 0.06476 +Epoch [2202/4000] Validation [2/4] Loss: 0.41139 focal_loss 0.28837 dice_loss 0.12302 +Epoch [2202/4000] Validation [3/4] Loss: 0.22991 focal_loss 0.15495 dice_loss 0.07496 +Epoch [2202/4000] Validation [4/4] Loss: 0.31496 focal_loss 0.20645 dice_loss 0.10851 +Epoch [2202/4000] Validation metric {'Val/mean dice_metric': 0.9749870300292969, 'Val/mean miou_metric': 0.9588149785995483, 'Val/mean f1': 0.9751144051551819, 'Val/mean precision': 0.9727393388748169, 'Val/mean recall': 0.9775010347366333, 'Val/mean hd95_metric': 5.9628119468688965} +Cheakpoint... +Epoch [2202/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749870300292969, 'Val/mean miou_metric': 0.9588149785995483, 'Val/mean f1': 0.9751144051551819, 'Val/mean precision': 0.9727393388748169, 'Val/mean recall': 0.9775010347366333, 'Val/mean hd95_metric': 5.9628119468688965} +Epoch [2203/4000] Training [1/16] Loss: 0.00450 +Epoch [2203/4000] Training [2/16] Loss: 0.00682 +Epoch [2203/4000] Training [3/16] Loss: 0.00547 +Epoch [2203/4000] Training [4/16] Loss: 0.00576 +Epoch [2203/4000] Training [5/16] Loss: 0.00596 +Epoch [2203/4000] Training [6/16] Loss: 0.00471 +Epoch [2203/4000] Training [7/16] Loss: 0.00414 +Epoch [2203/4000] Training [8/16] Loss: 0.00532 +Epoch [2203/4000] Training [9/16] Loss: 0.00725 +Epoch [2203/4000] Training [10/16] Loss: 0.00607 +Epoch [2203/4000] Training [11/16] Loss: 0.00617 +Epoch [2203/4000] Training [12/16] Loss: 0.00432 +Epoch [2203/4000] Training [13/16] Loss: 0.00495 +Epoch [2203/4000] Training [14/16] Loss: 0.00547 +Epoch [2203/4000] Training [15/16] Loss: 0.00630 +Epoch [2203/4000] Training [16/16] Loss: 0.00552 +Epoch [2203/4000] Training metric {'Train/mean dice_metric': 0.9964622259140015, 'Train/mean miou_metric': 0.992682933807373, 'Train/mean f1': 0.992057740688324, 'Train/mean precision': 0.9875319600105286, 'Train/mean recall': 0.9966251850128174, 'Train/mean hd95_metric': 0.9886385202407837} +Epoch [2203/4000] Validation [1/4] Loss: 0.26331 focal_loss 0.20310 dice_loss 0.06021 +Epoch [2203/4000] Validation [2/4] Loss: 0.77148 focal_loss 0.55136 dice_loss 0.22011 +Epoch [2203/4000] Validation [3/4] Loss: 0.34436 focal_loss 0.25110 dice_loss 0.09326 +Epoch [2203/4000] Validation [4/4] Loss: 0.45277 focal_loss 0.30205 dice_loss 0.15072 +Epoch [2203/4000] Validation metric {'Val/mean dice_metric': 0.9701951742172241, 'Val/mean miou_metric': 0.9543010592460632, 'Val/mean f1': 0.9743204712867737, 'Val/mean precision': 0.9713928699493408, 'Val/mean recall': 0.9772658348083496, 'Val/mean hd95_metric': 6.382890224456787} +Cheakpoint... +Epoch [2203/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701951742172241, 'Val/mean miou_metric': 0.9543010592460632, 'Val/mean f1': 0.9743204712867737, 'Val/mean precision': 0.9713928699493408, 'Val/mean recall': 0.9772658348083496, 'Val/mean hd95_metric': 6.382890224456787} +Epoch [2204/4000] Training [1/16] Loss: 0.00496 +Epoch [2204/4000] Training [2/16] Loss: 0.00453 +Epoch [2204/4000] Training [3/16] Loss: 0.00580 +Epoch [2204/4000] Training [4/16] Loss: 0.00572 +Epoch [2204/4000] Training [5/16] Loss: 0.00546 +Epoch [2204/4000] Training [6/16] Loss: 0.00709 +Epoch [2204/4000] Training [7/16] Loss: 0.00650 +Epoch [2204/4000] Training [8/16] Loss: 0.00670 +Epoch [2204/4000] Training [9/16] Loss: 0.00647 +Epoch [2204/4000] Training [10/16] Loss: 0.00535 +Epoch [2204/4000] Training [11/16] Loss: 0.00620 +Epoch [2204/4000] Training [12/16] Loss: 0.00595 +Epoch [2204/4000] Training [13/16] Loss: 0.00339 +Epoch [2204/4000] Training [14/16] Loss: 0.00580 +Epoch [2204/4000] Training [15/16] Loss: 0.00508 +Epoch [2204/4000] Training [16/16] Loss: 0.00815 +Epoch [2204/4000] Training metric {'Train/mean dice_metric': 0.9962530732154846, 'Train/mean miou_metric': 0.9922952055931091, 'Train/mean f1': 0.9921439290046692, 'Train/mean precision': 0.9876199960708618, 'Train/mean recall': 0.9967095851898193, 'Train/mean hd95_metric': 1.0359115600585938} +Epoch [2204/4000] Validation [1/4] Loss: 0.27463 focal_loss 0.21228 dice_loss 0.06236 +Epoch [2204/4000] Validation [2/4] Loss: 0.65797 focal_loss 0.49346 dice_loss 0.16451 +Epoch [2204/4000] Validation [3/4] Loss: 0.34616 focal_loss 0.25245 dice_loss 0.09370 +Epoch [2204/4000] Validation [4/4] Loss: 0.26514 focal_loss 0.18223 dice_loss 0.08290 +Epoch [2204/4000] Validation metric {'Val/mean dice_metric': 0.9726073145866394, 'Val/mean miou_metric': 0.9566642642021179, 'Val/mean f1': 0.9748711585998535, 'Val/mean precision': 0.9715220332145691, 'Val/mean recall': 0.978243350982666, 'Val/mean hd95_metric': 5.825477123260498} +Cheakpoint... +Epoch [2204/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726073145866394, 'Val/mean miou_metric': 0.9566642642021179, 'Val/mean f1': 0.9748711585998535, 'Val/mean precision': 0.9715220332145691, 'Val/mean recall': 0.978243350982666, 'Val/mean hd95_metric': 5.825477123260498} +Epoch [2205/4000] Training [1/16] Loss: 0.00501 +Epoch [2205/4000] Training [2/16] Loss: 0.00512 +Epoch [2205/4000] Training [3/16] Loss: 0.00644 +Epoch [2205/4000] Training [4/16] Loss: 0.00597 +Epoch [2205/4000] Training [5/16] Loss: 0.00490 +Epoch [2205/4000] Training [6/16] Loss: 0.00556 +Epoch [2205/4000] Training [7/16] Loss: 0.00507 +Epoch [2205/4000] Training [8/16] Loss: 0.00567 +Epoch [2205/4000] Training [9/16] Loss: 0.00412 +Epoch [2205/4000] Training [10/16] Loss: 0.00574 +Epoch [2205/4000] Training [11/16] Loss: 0.00648 +Epoch [2205/4000] Training [12/16] Loss: 0.00565 +Epoch [2205/4000] Training [13/16] Loss: 0.00513 +Epoch [2205/4000] Training [14/16] Loss: 0.00453 +Epoch [2205/4000] Training [15/16] Loss: 0.00404 +Epoch [2205/4000] Training [16/16] Loss: 0.00525 +Epoch [2205/4000] Training metric {'Train/mean dice_metric': 0.9964685440063477, 'Train/mean miou_metric': 0.992678701877594, 'Train/mean f1': 0.9919377565383911, 'Train/mean precision': 0.9873252511024475, 'Train/mean recall': 0.9965935349464417, 'Train/mean hd95_metric': 0.9977725148200989} +Epoch [2205/4000] Validation [1/4] Loss: 0.27999 focal_loss 0.21395 dice_loss 0.06604 +Epoch [2205/4000] Validation [2/4] Loss: 0.41990 focal_loss 0.28620 dice_loss 0.13370 +Epoch [2205/4000] Validation [3/4] Loss: 0.20614 focal_loss 0.14382 dice_loss 0.06232 +Epoch [2205/4000] Validation [4/4] Loss: 0.29945 focal_loss 0.19745 dice_loss 0.10199 +Epoch [2205/4000] Validation metric {'Val/mean dice_metric': 0.9724600911140442, 'Val/mean miou_metric': 0.9566359519958496, 'Val/mean f1': 0.9747970700263977, 'Val/mean precision': 0.9729292988777161, 'Val/mean recall': 0.9766718745231628, 'Val/mean hd95_metric': 5.596157073974609} +Cheakpoint... +Epoch [2205/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724600911140442, 'Val/mean miou_metric': 0.9566359519958496, 'Val/mean f1': 0.9747970700263977, 'Val/mean precision': 0.9729292988777161, 'Val/mean recall': 0.9766718745231628, 'Val/mean hd95_metric': 5.596157073974609} +Epoch [2206/4000] Training [1/16] Loss: 0.00424 +Epoch [2206/4000] Training [2/16] Loss: 0.00509 +Epoch [2206/4000] Training [3/16] Loss: 0.00541 +Epoch [2206/4000] Training [4/16] Loss: 0.00468 +Epoch [2206/4000] Training [5/16] Loss: 0.00668 +Epoch [2206/4000] Training [6/16] Loss: 0.00462 +Epoch [2206/4000] Training [7/16] Loss: 0.00696 +Epoch [2206/4000] Training [8/16] Loss: 0.00454 +Epoch [2206/4000] Training [9/16] Loss: 0.00624 +Epoch [2206/4000] Training [10/16] Loss: 0.00552 +Epoch [2206/4000] Training [11/16] Loss: 0.00471 +Epoch [2206/4000] Training [12/16] Loss: 0.00427 +Epoch [2206/4000] Training [13/16] Loss: 0.00538 +Epoch [2206/4000] Training [14/16] Loss: 0.00411 +Epoch [2206/4000] Training [15/16] Loss: 0.00488 +Epoch [2206/4000] Training [16/16] Loss: 0.00436 +Epoch [2206/4000] Training metric {'Train/mean dice_metric': 0.9967406988143921, 'Train/mean miou_metric': 0.9932347536087036, 'Train/mean f1': 0.9922242760658264, 'Train/mean precision': 0.9876391291618347, 'Train/mean recall': 0.9968522191047668, 'Train/mean hd95_metric': 0.9873180389404297} +Epoch [2206/4000] Validation [1/4] Loss: 0.28109 focal_loss 0.22437 dice_loss 0.05672 +Epoch [2206/4000] Validation [2/4] Loss: 0.42499 focal_loss 0.29431 dice_loss 0.13067 +Epoch [2206/4000] Validation [3/4] Loss: 0.23209 focal_loss 0.16029 dice_loss 0.07180 +Epoch [2206/4000] Validation [4/4] Loss: 0.38585 focal_loss 0.25630 dice_loss 0.12955 +Epoch [2206/4000] Validation metric {'Val/mean dice_metric': 0.9729410409927368, 'Val/mean miou_metric': 0.9575767517089844, 'Val/mean f1': 0.9751847386360168, 'Val/mean precision': 0.9732188582420349, 'Val/mean recall': 0.9771585464477539, 'Val/mean hd95_metric': 6.042849063873291} +Cheakpoint... +Epoch [2206/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729410409927368, 'Val/mean miou_metric': 0.9575767517089844, 'Val/mean f1': 0.9751847386360168, 'Val/mean precision': 0.9732188582420349, 'Val/mean recall': 0.9771585464477539, 'Val/mean hd95_metric': 6.042849063873291} +Epoch [2207/4000] Training [1/16] Loss: 0.00575 +Epoch [2207/4000] Training [2/16] Loss: 0.00544 +Epoch [2207/4000] Training [3/16] Loss: 0.00453 +Epoch [2207/4000] Training [4/16] Loss: 0.00690 +Epoch [2207/4000] Training [5/16] Loss: 0.00376 +Epoch [2207/4000] Training [6/16] Loss: 0.00503 +Epoch [2207/4000] Training [7/16] Loss: 0.00504 +Epoch [2207/4000] Training [8/16] Loss: 0.00573 +Epoch [2207/4000] Training [9/16] Loss: 0.00529 +Epoch [2207/4000] Training [10/16] Loss: 0.00602 +Epoch [2207/4000] Training [11/16] Loss: 0.00445 +Epoch [2207/4000] Training [12/16] Loss: 0.00939 +Epoch [2207/4000] Training [13/16] Loss: 0.00594 +Epoch [2207/4000] Training [14/16] Loss: 0.00634 +Epoch [2207/4000] Training [15/16] Loss: 0.00401 +Epoch [2207/4000] Training [16/16] Loss: 0.00488 +Epoch [2207/4000] Training metric {'Train/mean dice_metric': 0.9966078400611877, 'Train/mean miou_metric': 0.992956280708313, 'Train/mean f1': 0.9919096231460571, 'Train/mean precision': 0.9871588349342346, 'Train/mean recall': 0.9967064261436462, 'Train/mean hd95_metric': 0.9985446929931641} +Epoch [2207/4000] Validation [1/4] Loss: 0.29813 focal_loss 0.23203 dice_loss 0.06610 +Epoch [2207/4000] Validation [2/4] Loss: 0.42345 focal_loss 0.27924 dice_loss 0.14421 +Epoch [2207/4000] Validation [3/4] Loss: 0.22054 focal_loss 0.15286 dice_loss 0.06769 +Epoch [2207/4000] Validation [4/4] Loss: 0.54398 focal_loss 0.40712 dice_loss 0.13687 +Epoch [2207/4000] Validation metric {'Val/mean dice_metric': 0.9719328880310059, 'Val/mean miou_metric': 0.9558650851249695, 'Val/mean f1': 0.9749844670295715, 'Val/mean precision': 0.9728500247001648, 'Val/mean recall': 0.977128267288208, 'Val/mean hd95_metric': 5.9858503341674805} +Cheakpoint... +Epoch [2207/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719328880310059, 'Val/mean miou_metric': 0.9558650851249695, 'Val/mean f1': 0.9749844670295715, 'Val/mean precision': 0.9728500247001648, 'Val/mean recall': 0.977128267288208, 'Val/mean hd95_metric': 5.9858503341674805} +Epoch [2208/4000] Training [1/16] Loss: 0.00361 +Epoch [2208/4000] Training [2/16] Loss: 0.00492 +Epoch [2208/4000] Training [3/16] Loss: 0.00414 +Epoch [2208/4000] Training [4/16] Loss: 0.00541 +Epoch [2208/4000] Training [5/16] Loss: 0.00559 +Epoch [2208/4000] Training [6/16] Loss: 0.00642 +Epoch [2208/4000] Training [7/16] Loss: 0.00681 +Epoch [2208/4000] Training [8/16] Loss: 0.00472 +Epoch [2208/4000] Training [9/16] Loss: 0.00491 +Epoch [2208/4000] Training [10/16] Loss: 0.00632 +Epoch [2208/4000] Training [11/16] Loss: 0.00429 +Epoch [2208/4000] Training [12/16] Loss: 0.00501 +Epoch [2208/4000] Training [13/16] Loss: 0.00744 +Epoch [2208/4000] Training [14/16] Loss: 0.00486 +Epoch [2208/4000] Training [15/16] Loss: 0.00565 +Epoch [2208/4000] Training [16/16] Loss: 0.00422 +Epoch [2208/4000] Training metric {'Train/mean dice_metric': 0.9966109991073608, 'Train/mean miou_metric': 0.9929769039154053, 'Train/mean f1': 0.9921708106994629, 'Train/mean precision': 0.9875925183296204, 'Train/mean recall': 0.9967917203903198, 'Train/mean hd95_metric': 1.000364065170288} +Epoch [2208/4000] Validation [1/4] Loss: 0.30826 focal_loss 0.23972 dice_loss 0.06855 +Epoch [2208/4000] Validation [2/4] Loss: 0.84409 focal_loss 0.60933 dice_loss 0.23476 +Epoch [2208/4000] Validation [3/4] Loss: 0.28632 focal_loss 0.19900 dice_loss 0.08731 +Epoch [2208/4000] Validation [4/4] Loss: 0.27869 focal_loss 0.18802 dice_loss 0.09067 +Epoch [2208/4000] Validation metric {'Val/mean dice_metric': 0.9707450866699219, 'Val/mean miou_metric': 0.9551141858100891, 'Val/mean f1': 0.9742680788040161, 'Val/mean precision': 0.9727298617362976, 'Val/mean recall': 0.9758111834526062, 'Val/mean hd95_metric': 6.139532566070557} +Cheakpoint... +Epoch [2208/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707450866699219, 'Val/mean miou_metric': 0.9551141858100891, 'Val/mean f1': 0.9742680788040161, 'Val/mean precision': 0.9727298617362976, 'Val/mean recall': 0.9758111834526062, 'Val/mean hd95_metric': 6.139532566070557} +Epoch [2209/4000] Training [1/16] Loss: 0.00440 +Epoch [2209/4000] Training [2/16] Loss: 0.00601 +Epoch [2209/4000] Training [3/16] Loss: 0.00382 +Epoch [2209/4000] Training [4/16] Loss: 0.00557 +Epoch [2209/4000] Training [5/16] Loss: 0.00399 +Epoch [2209/4000] Training [6/16] Loss: 0.00503 +Epoch [2209/4000] Training [7/16] Loss: 0.00550 +Epoch [2209/4000] Training [8/16] Loss: 0.00438 +Epoch [2209/4000] Training [9/16] Loss: 0.00375 +Epoch [2209/4000] Training [10/16] Loss: 0.00579 +Epoch [2209/4000] Training [11/16] Loss: 0.00362 +Epoch [2209/4000] Training [12/16] Loss: 0.00587 +Epoch [2209/4000] Training [13/16] Loss: 0.00505 +Epoch [2209/4000] Training [14/16] Loss: 0.00745 +Epoch [2209/4000] Training [15/16] Loss: 0.00401 +Epoch [2209/4000] Training [16/16] Loss: 0.00519 +Epoch [2209/4000] Training metric {'Train/mean dice_metric': 0.9969018697738647, 'Train/mean miou_metric': 0.9935561418533325, 'Train/mean f1': 0.9923524856567383, 'Train/mean precision': 0.9878817796707153, 'Train/mean recall': 0.996863842010498, 'Train/mean hd95_metric': 0.9774136543273926} +Epoch [2209/4000] Validation [1/4] Loss: 0.31887 focal_loss 0.25234 dice_loss 0.06653 +Epoch [2209/4000] Validation [2/4] Loss: 0.39657 focal_loss 0.26654 dice_loss 0.13003 +Epoch [2209/4000] Validation [3/4] Loss: 0.36299 focal_loss 0.27063 dice_loss 0.09236 +Epoch [2209/4000] Validation [4/4] Loss: 0.21293 focal_loss 0.13619 dice_loss 0.07674 +Epoch [2209/4000] Validation metric {'Val/mean dice_metric': 0.971892237663269, 'Val/mean miou_metric': 0.9564164876937866, 'Val/mean f1': 0.9741150140762329, 'Val/mean precision': 0.9705386757850647, 'Val/mean recall': 0.9777178764343262, 'Val/mean hd95_metric': 5.681483745574951} +Cheakpoint... +Epoch [2209/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971892237663269, 'Val/mean miou_metric': 0.9564164876937866, 'Val/mean f1': 0.9741150140762329, 'Val/mean precision': 0.9705386757850647, 'Val/mean recall': 0.9777178764343262, 'Val/mean hd95_metric': 5.681483745574951} +Epoch [2210/4000] Training [1/16] Loss: 0.00419 +Epoch [2210/4000] Training [2/16] Loss: 0.00565 +Epoch [2210/4000] Training [3/16] Loss: 0.00532 +Epoch [2210/4000] Training [4/16] Loss: 0.00519 +Epoch [2210/4000] Training [5/16] Loss: 0.00668 +Epoch [2210/4000] Training [6/16] Loss: 0.00552 +Epoch [2210/4000] Training [7/16] Loss: 0.00501 +Epoch [2210/4000] Training [8/16] Loss: 0.00506 +Epoch [2210/4000] Training [9/16] Loss: 0.00518 +Epoch [2210/4000] Training [10/16] Loss: 0.00617 +Epoch [2210/4000] Training [11/16] Loss: 0.00626 +Epoch [2210/4000] Training [12/16] Loss: 0.00470 +Epoch [2210/4000] Training [13/16] Loss: 0.00554 +Epoch [2210/4000] Training [14/16] Loss: 0.00385 +Epoch [2210/4000] Training [15/16] Loss: 0.00449 +Epoch [2210/4000] Training [16/16] Loss: 0.00500 +Epoch [2210/4000] Training metric {'Train/mean dice_metric': 0.9965951442718506, 'Train/mean miou_metric': 0.9929444789886475, 'Train/mean f1': 0.992137610912323, 'Train/mean precision': 0.9874700903892517, 'Train/mean recall': 0.9968494772911072, 'Train/mean hd95_metric': 0.9824364185333252} +Epoch [2210/4000] Validation [1/4] Loss: 0.24494 focal_loss 0.18804 dice_loss 0.05691 +Epoch [2210/4000] Validation [2/4] Loss: 0.42917 focal_loss 0.27571 dice_loss 0.15347 +Epoch [2210/4000] Validation [3/4] Loss: 0.30624 focal_loss 0.21305 dice_loss 0.09319 +Epoch [2210/4000] Validation [4/4] Loss: 0.33345 focal_loss 0.21209 dice_loss 0.12136 +Epoch [2210/4000] Validation metric {'Val/mean dice_metric': 0.9750467538833618, 'Val/mean miou_metric': 0.9592593908309937, 'Val/mean f1': 0.9758378863334656, 'Val/mean precision': 0.9726563096046448, 'Val/mean recall': 0.9790403246879578, 'Val/mean hd95_metric': 5.514657020568848} +Cheakpoint... +Epoch [2210/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750467538833618, 'Val/mean miou_metric': 0.9592593908309937, 'Val/mean f1': 0.9758378863334656, 'Val/mean precision': 0.9726563096046448, 'Val/mean recall': 0.9790403246879578, 'Val/mean hd95_metric': 5.514657020568848} +Epoch [2211/4000] Training [1/16] Loss: 0.00499 +Epoch [2211/4000] Training [2/16] Loss: 0.00654 +Epoch [2211/4000] Training [3/16] Loss: 0.00415 +Epoch [2211/4000] Training [4/16] Loss: 0.00417 +Epoch [2211/4000] Training [5/16] Loss: 0.00640 +Epoch [2211/4000] Training [6/16] Loss: 0.00460 +Epoch [2211/4000] Training [7/16] Loss: 0.01056 +Epoch [2211/4000] Training [8/16] Loss: 0.00404 +Epoch [2211/4000] Training [9/16] Loss: 0.00526 +Epoch [2211/4000] Training [10/16] Loss: 0.00538 +Epoch [2211/4000] Training [11/16] Loss: 0.00630 +Epoch [2211/4000] Training [12/16] Loss: 0.00684 +Epoch [2211/4000] Training [13/16] Loss: 0.00630 +Epoch [2211/4000] Training [14/16] Loss: 0.00418 +Epoch [2211/4000] Training [15/16] Loss: 0.00623 +Epoch [2211/4000] Training [16/16] Loss: 0.00421 +Epoch [2211/4000] Training metric {'Train/mean dice_metric': 0.9964461326599121, 'Train/mean miou_metric': 0.9926625490188599, 'Train/mean f1': 0.9923074841499329, 'Train/mean precision': 0.9878648519515991, 'Train/mean recall': 0.9967902898788452, 'Train/mean hd95_metric': 0.9934704303741455} +Epoch [2211/4000] Validation [1/4] Loss: 0.27919 focal_loss 0.21522 dice_loss 0.06397 +Epoch [2211/4000] Validation [2/4] Loss: 0.35038 focal_loss 0.23517 dice_loss 0.11522 +Epoch [2211/4000] Validation [3/4] Loss: 0.31538 focal_loss 0.22439 dice_loss 0.09098 +Epoch [2211/4000] Validation [4/4] Loss: 0.53030 focal_loss 0.38214 dice_loss 0.14816 +Epoch [2211/4000] Validation metric {'Val/mean dice_metric': 0.9728735089302063, 'Val/mean miou_metric': 0.9569988250732422, 'Val/mean f1': 0.9744423627853394, 'Val/mean precision': 0.9714916348457336, 'Val/mean recall': 0.977411150932312, 'Val/mean hd95_metric': 6.102418899536133} +Cheakpoint... +Epoch [2211/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728735089302063, 'Val/mean miou_metric': 0.9569988250732422, 'Val/mean f1': 0.9744423627853394, 'Val/mean precision': 0.9714916348457336, 'Val/mean recall': 0.977411150932312, 'Val/mean hd95_metric': 6.102418899536133} +Epoch [2212/4000] Training [1/16] Loss: 0.00586 +Epoch [2212/4000] Training [2/16] Loss: 0.00478 +Epoch [2212/4000] Training [3/16] Loss: 0.00393 +Epoch [2212/4000] Training [4/16] Loss: 0.00697 +Epoch [2212/4000] Training [5/16] Loss: 0.00423 +Epoch [2212/4000] Training [6/16] Loss: 0.00614 +Epoch [2212/4000] Training [7/16] Loss: 0.00516 +Epoch [2212/4000] Training [8/16] Loss: 0.00524 +Epoch [2212/4000] Training [9/16] Loss: 0.00647 +Epoch [2212/4000] Training [10/16] Loss: 0.00464 +Epoch [2212/4000] Training [11/16] Loss: 0.00625 +Epoch [2212/4000] Training [12/16] Loss: 0.00596 +Epoch [2212/4000] Training [13/16] Loss: 0.00495 +Epoch [2212/4000] Training [14/16] Loss: 0.00591 +Epoch [2212/4000] Training [15/16] Loss: 0.00558 +Epoch [2212/4000] Training [16/16] Loss: 0.00434 +Epoch [2212/4000] Training metric {'Train/mean dice_metric': 0.9964872598648071, 'Train/mean miou_metric': 0.9927370548248291, 'Train/mean f1': 0.9920960068702698, 'Train/mean precision': 0.9875128269195557, 'Train/mean recall': 0.9967219233512878, 'Train/mean hd95_metric': 0.9962053298950195} +Epoch [2212/4000] Validation [1/4] Loss: 0.27705 focal_loss 0.21629 dice_loss 0.06076 +Epoch [2212/4000] Validation [2/4] Loss: 0.38123 focal_loss 0.26110 dice_loss 0.12013 +Epoch [2212/4000] Validation [3/4] Loss: 0.34569 focal_loss 0.25657 dice_loss 0.08912 +Epoch [2212/4000] Validation [4/4] Loss: 0.30313 focal_loss 0.19879 dice_loss 0.10435 +Epoch [2212/4000] Validation metric {'Val/mean dice_metric': 0.973973274230957, 'Val/mean miou_metric': 0.958159327507019, 'Val/mean f1': 0.9752442836761475, 'Val/mean precision': 0.9728053212165833, 'Val/mean recall': 0.9776953458786011, 'Val/mean hd95_metric': 5.060375213623047} +Cheakpoint... +Epoch [2212/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973973274230957, 'Val/mean miou_metric': 0.958159327507019, 'Val/mean f1': 0.9752442836761475, 'Val/mean precision': 0.9728053212165833, 'Val/mean recall': 0.9776953458786011, 'Val/mean hd95_metric': 5.060375213623047} +Epoch [2213/4000] Training [1/16] Loss: 0.00607 +Epoch [2213/4000] Training [2/16] Loss: 0.00532 +Epoch [2213/4000] Training [3/16] Loss: 0.00505 +Epoch [2213/4000] Training [4/16] Loss: 0.00488 +Epoch [2213/4000] Training [5/16] Loss: 0.00736 +Epoch [2213/4000] Training [6/16] Loss: 0.00919 +Epoch [2213/4000] Training [7/16] Loss: 0.00578 +Epoch [2213/4000] Training [8/16] Loss: 0.00616 +Epoch [2213/4000] Training [9/16] Loss: 0.00419 +Epoch [2213/4000] Training [10/16] Loss: 0.00450 +Epoch [2213/4000] Training [11/16] Loss: 0.00838 +Epoch [2213/4000] Training [12/16] Loss: 0.00501 +Epoch [2213/4000] Training [13/16] Loss: 0.00617 +Epoch [2213/4000] Training [14/16] Loss: 0.00540 +Epoch [2213/4000] Training [15/16] Loss: 0.00435 +Epoch [2213/4000] Training [16/16] Loss: 0.00467 +Epoch [2213/4000] Training metric {'Train/mean dice_metric': 0.9964997172355652, 'Train/mean miou_metric': 0.9927557706832886, 'Train/mean f1': 0.9918050169944763, 'Train/mean precision': 0.9871363043785095, 'Train/mean recall': 0.996518075466156, 'Train/mean hd95_metric': 1.031644344329834} +Epoch [2213/4000] Validation [1/4] Loss: 0.36974 focal_loss 0.29747 dice_loss 0.07227 +Epoch [2213/4000] Validation [2/4] Loss: 0.35324 focal_loss 0.21672 dice_loss 0.13652 +Epoch [2213/4000] Validation [3/4] Loss: 0.33879 focal_loss 0.24694 dice_loss 0.09185 +Epoch [2213/4000] Validation [4/4] Loss: 0.27156 focal_loss 0.16910 dice_loss 0.10245 +Epoch [2213/4000] Validation metric {'Val/mean dice_metric': 0.9736582040786743, 'Val/mean miou_metric': 0.957619845867157, 'Val/mean f1': 0.9747058749198914, 'Val/mean precision': 0.9730698466300964, 'Val/mean recall': 0.9763475060462952, 'Val/mean hd95_metric': 5.280722618103027} +Cheakpoint... +Epoch [2213/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736582040786743, 'Val/mean miou_metric': 0.957619845867157, 'Val/mean f1': 0.9747058749198914, 'Val/mean precision': 0.9730698466300964, 'Val/mean recall': 0.9763475060462952, 'Val/mean hd95_metric': 5.280722618103027} +Epoch [2214/4000] Training [1/16] Loss: 0.00654 +Epoch [2214/4000] Training [2/16] Loss: 0.00605 +Epoch [2214/4000] Training [3/16] Loss: 0.00566 +Epoch [2214/4000] Training [4/16] Loss: 0.00563 +Epoch [2214/4000] Training [5/16] Loss: 0.00484 +Epoch [2214/4000] Training [6/16] Loss: 0.00529 +Epoch [2214/4000] Training [7/16] Loss: 0.00473 +Epoch [2214/4000] Training [8/16] Loss: 0.00853 +Epoch [2214/4000] Training [9/16] Loss: 0.00562 +Epoch [2214/4000] Training [10/16] Loss: 0.00423 +Epoch [2214/4000] Training [11/16] Loss: 0.00832 +Epoch [2214/4000] Training [12/16] Loss: 0.00685 +Epoch [2214/4000] Training [13/16] Loss: 0.00855 +Epoch [2214/4000] Training [14/16] Loss: 0.00566 +Epoch [2214/4000] Training [15/16] Loss: 0.00567 +Epoch [2214/4000] Training [16/16] Loss: 0.00622 +Epoch [2214/4000] Training metric {'Train/mean dice_metric': 0.996251106262207, 'Train/mean miou_metric': 0.9922502040863037, 'Train/mean f1': 0.9915899038314819, 'Train/mean precision': 0.986659824848175, 'Train/mean recall': 0.9965694546699524, 'Train/mean hd95_metric': 1.0316996574401855} +Epoch [2214/4000] Validation [1/4] Loss: 0.30934 focal_loss 0.24346 dice_loss 0.06588 +Epoch [2214/4000] Validation [2/4] Loss: 0.32508 focal_loss 0.20856 dice_loss 0.11651 +Epoch [2214/4000] Validation [3/4] Loss: 0.38030 focal_loss 0.28672 dice_loss 0.09359 +Epoch [2214/4000] Validation [4/4] Loss: 0.40413 focal_loss 0.28177 dice_loss 0.12235 +Epoch [2214/4000] Validation metric {'Val/mean dice_metric': 0.9725639224052429, 'Val/mean miou_metric': 0.9560283422470093, 'Val/mean f1': 0.9740570187568665, 'Val/mean precision': 0.9724906086921692, 'Val/mean recall': 0.9756284356117249, 'Val/mean hd95_metric': 5.62598991394043} +Cheakpoint... +Epoch [2214/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725639224052429, 'Val/mean miou_metric': 0.9560283422470093, 'Val/mean f1': 0.9740570187568665, 'Val/mean precision': 0.9724906086921692, 'Val/mean recall': 0.9756284356117249, 'Val/mean hd95_metric': 5.62598991394043} +Epoch [2215/4000] Training [1/16] Loss: 0.00429 +Epoch [2215/4000] Training [2/16] Loss: 0.00427 +Epoch [2215/4000] Training [3/16] Loss: 0.00481 +Epoch [2215/4000] Training [4/16] Loss: 0.00639 +Epoch [2215/4000] Training [5/16] Loss: 0.00493 +Epoch [2215/4000] Training [6/16] Loss: 0.00783 +Epoch [2215/4000] Training [7/16] Loss: 0.00544 +Epoch [2215/4000] Training [8/16] Loss: 0.00504 +Epoch [2215/4000] Training [9/16] Loss: 0.00452 +Epoch [2215/4000] Training [10/16] Loss: 0.00515 +Epoch [2215/4000] Training [11/16] Loss: 0.00647 +Epoch [2215/4000] Training [12/16] Loss: 0.00436 +Epoch [2215/4000] Training [13/16] Loss: 0.00729 +Epoch [2215/4000] Training [14/16] Loss: 0.00468 +Epoch [2215/4000] Training [15/16] Loss: 0.00497 +Epoch [2215/4000] Training [16/16] Loss: 0.00588 +Epoch [2215/4000] Training metric {'Train/mean dice_metric': 0.9966448545455933, 'Train/mean miou_metric': 0.9930123090744019, 'Train/mean f1': 0.991322934627533, 'Train/mean precision': 0.9860185384750366, 'Train/mean recall': 0.996684730052948, 'Train/mean hd95_metric': 1.0092051029205322} +Epoch [2215/4000] Validation [1/4] Loss: 0.27872 focal_loss 0.21619 dice_loss 0.06253 +Epoch [2215/4000] Validation [2/4] Loss: 0.44533 focal_loss 0.29867 dice_loss 0.14666 +Epoch [2215/4000] Validation [3/4] Loss: 0.31829 focal_loss 0.22637 dice_loss 0.09192 +Epoch [2215/4000] Validation [4/4] Loss: 0.43268 focal_loss 0.30099 dice_loss 0.13169 +Epoch [2215/4000] Validation metric {'Val/mean dice_metric': 0.9718731045722961, 'Val/mean miou_metric': 0.9560529589653015, 'Val/mean f1': 0.9733986258506775, 'Val/mean precision': 0.9709540605545044, 'Val/mean recall': 0.9758555889129639, 'Val/mean hd95_metric': 5.733155727386475} +Cheakpoint... +Epoch [2215/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718731045722961, 'Val/mean miou_metric': 0.9560529589653015, 'Val/mean f1': 0.9733986258506775, 'Val/mean precision': 0.9709540605545044, 'Val/mean recall': 0.9758555889129639, 'Val/mean hd95_metric': 5.733155727386475} +Epoch [2216/4000] Training [1/16] Loss: 0.00477 +Epoch [2216/4000] Training [2/16] Loss: 0.00722 +Epoch [2216/4000] Training [3/16] Loss: 0.00501 +Epoch [2216/4000] Training [4/16] Loss: 0.00519 +Epoch [2216/4000] Training [5/16] Loss: 0.00441 +Epoch [2216/4000] Training [6/16] Loss: 0.00475 +Epoch [2216/4000] Training [7/16] Loss: 0.00570 +Epoch [2216/4000] Training [8/16] Loss: 0.00579 +Epoch [2216/4000] Training [9/16] Loss: 0.00534 +Epoch [2216/4000] Training [10/16] Loss: 0.00457 +Epoch [2216/4000] Training [11/16] Loss: 0.00546 +Epoch [2216/4000] Training [12/16] Loss: 0.00432 +Epoch [2216/4000] Training [13/16] Loss: 0.00545 +Epoch [2216/4000] Training [14/16] Loss: 0.00588 +Epoch [2216/4000] Training [15/16] Loss: 0.00383 +Epoch [2216/4000] Training [16/16] Loss: 0.00461 +Epoch [2216/4000] Training metric {'Train/mean dice_metric': 0.9966077208518982, 'Train/mean miou_metric': 0.9929527044296265, 'Train/mean f1': 0.9916058778762817, 'Train/mean precision': 0.9865074157714844, 'Train/mean recall': 0.9967573285102844, 'Train/mean hd95_metric': 0.9873682856559753} +Epoch [2216/4000] Validation [1/4] Loss: 0.28252 focal_loss 0.21816 dice_loss 0.06436 +Epoch [2216/4000] Validation [2/4] Loss: 0.40941 focal_loss 0.27029 dice_loss 0.13912 +Epoch [2216/4000] Validation [3/4] Loss: 0.28092 focal_loss 0.18985 dice_loss 0.09106 +Epoch [2216/4000] Validation [4/4] Loss: 0.26334 focal_loss 0.16387 dice_loss 0.09947 +Epoch [2216/4000] Validation metric {'Val/mean dice_metric': 0.9726325869560242, 'Val/mean miou_metric': 0.9566934704780579, 'Val/mean f1': 0.9747851490974426, 'Val/mean precision': 0.9728543162345886, 'Val/mean recall': 0.9767237901687622, 'Val/mean hd95_metric': 5.637722492218018} +Cheakpoint... +Epoch [2216/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726325869560242, 'Val/mean miou_metric': 0.9566934704780579, 'Val/mean f1': 0.9747851490974426, 'Val/mean precision': 0.9728543162345886, 'Val/mean recall': 0.9767237901687622, 'Val/mean hd95_metric': 5.637722492218018} +Epoch [2217/4000] Training [1/16] Loss: 0.00508 +Epoch [2217/4000] Training [2/16] Loss: 0.00402 +Epoch [2217/4000] Training [3/16] Loss: 0.00423 +Epoch [2217/4000] Training [4/16] Loss: 0.00522 +Epoch [2217/4000] Training [5/16] Loss: 0.00636 +Epoch [2217/4000] Training [6/16] Loss: 0.00470 +Epoch [2217/4000] Training [7/16] Loss: 0.00433 +Epoch [2217/4000] Training [8/16] Loss: 0.00539 +Epoch [2217/4000] Training [9/16] Loss: 0.00676 +Epoch [2217/4000] Training [10/16] Loss: 0.00556 +Epoch [2217/4000] Training [11/16] Loss: 0.00663 +Epoch [2217/4000] Training [12/16] Loss: 0.00473 +Epoch [2217/4000] Training [13/16] Loss: 0.00533 +Epoch [2217/4000] Training [14/16] Loss: 0.00667 +Epoch [2217/4000] Training [15/16] Loss: 0.00506 +Epoch [2217/4000] Training [16/16] Loss: 0.00476 +Epoch [2217/4000] Training metric {'Train/mean dice_metric': 0.9965335130691528, 'Train/mean miou_metric': 0.9928275942802429, 'Train/mean f1': 0.9921311140060425, 'Train/mean precision': 0.9875850081443787, 'Train/mean recall': 0.996719241142273, 'Train/mean hd95_metric': 0.9978927373886108} +Epoch [2217/4000] Validation [1/4] Loss: 0.27854 focal_loss 0.21643 dice_loss 0.06211 +Epoch [2217/4000] Validation [2/4] Loss: 0.32943 focal_loss 0.21306 dice_loss 0.11638 +Epoch [2217/4000] Validation [3/4] Loss: 0.42885 focal_loss 0.34362 dice_loss 0.08523 +Epoch [2217/4000] Validation [4/4] Loss: 0.43737 focal_loss 0.31204 dice_loss 0.12533 +Epoch [2217/4000] Validation metric {'Val/mean dice_metric': 0.9728330373764038, 'Val/mean miou_metric': 0.9567028880119324, 'Val/mean f1': 0.9735813140869141, 'Val/mean precision': 0.9729546904563904, 'Val/mean recall': 0.9742087125778198, 'Val/mean hd95_metric': 5.464531421661377} +Cheakpoint... +Epoch [2217/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728330373764038, 'Val/mean miou_metric': 0.9567028880119324, 'Val/mean f1': 0.9735813140869141, 'Val/mean precision': 0.9729546904563904, 'Val/mean recall': 0.9742087125778198, 'Val/mean hd95_metric': 5.464531421661377} +Epoch [2218/4000] Training [1/16] Loss: 0.00522 +Epoch [2218/4000] Training [2/16] Loss: 0.00430 +Epoch [2218/4000] Training [3/16] Loss: 0.00448 +Epoch [2218/4000] Training [4/16] Loss: 0.00589 +Epoch [2218/4000] Training [5/16] Loss: 0.00758 +Epoch [2218/4000] Training [6/16] Loss: 0.00473 +Epoch [2218/4000] Training [7/16] Loss: 0.00382 +Epoch [2218/4000] Training [8/16] Loss: 0.00667 +Epoch [2218/4000] Training [9/16] Loss: 0.00527 +Epoch [2218/4000] Training [10/16] Loss: 0.00846 +Epoch [2218/4000] Training [11/16] Loss: 0.00448 +Epoch [2218/4000] Training [12/16] Loss: 0.00639 +Epoch [2218/4000] Training [13/16] Loss: 0.00453 +Epoch [2218/4000] Training [14/16] Loss: 0.00516 +Epoch [2218/4000] Training [15/16] Loss: 0.00637 +Epoch [2218/4000] Training [16/16] Loss: 0.00823 +Epoch [2218/4000] Training metric {'Train/mean dice_metric': 0.9962944984436035, 'Train/mean miou_metric': 0.9923131465911865, 'Train/mean f1': 0.9909456968307495, 'Train/mean precision': 0.9855397939682007, 'Train/mean recall': 0.9964112639427185, 'Train/mean hd95_metric': 1.0168509483337402} +Epoch [2218/4000] Validation [1/4] Loss: 0.27754 focal_loss 0.21427 dice_loss 0.06327 +Epoch [2218/4000] Validation [2/4] Loss: 0.92701 focal_loss 0.63098 dice_loss 0.29603 +Epoch [2218/4000] Validation [3/4] Loss: 0.19177 focal_loss 0.13188 dice_loss 0.05989 +Epoch [2218/4000] Validation [4/4] Loss: 0.27391 focal_loss 0.17579 dice_loss 0.09811 +Epoch [2218/4000] Validation metric {'Val/mean dice_metric': 0.9713295102119446, 'Val/mean miou_metric': 0.9559568166732788, 'Val/mean f1': 0.9738900661468506, 'Val/mean precision': 0.9704898595809937, 'Val/mean recall': 0.9773142337799072, 'Val/mean hd95_metric': 5.3721394538879395} +Cheakpoint... +Epoch [2218/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713295102119446, 'Val/mean miou_metric': 0.9559568166732788, 'Val/mean f1': 0.9738900661468506, 'Val/mean precision': 0.9704898595809937, 'Val/mean recall': 0.9773142337799072, 'Val/mean hd95_metric': 5.3721394538879395} +Epoch [2219/4000] Training [1/16] Loss: 0.00497 +Epoch [2219/4000] Training [2/16] Loss: 0.00556 +Epoch [2219/4000] Training [3/16] Loss: 0.00346 +Epoch [2219/4000] Training [4/16] Loss: 0.00631 +Epoch [2219/4000] Training [5/16] Loss: 0.00482 +Epoch [2219/4000] Training [6/16] Loss: 0.00394 +Epoch [2219/4000] Training [7/16] Loss: 0.00618 +Epoch [2219/4000] Training [8/16] Loss: 0.00500 +Epoch [2219/4000] Training [9/16] Loss: 0.00392 +Epoch [2219/4000] Training [10/16] Loss: 0.00536 +Epoch [2219/4000] Training [11/16] Loss: 0.00584 +Epoch [2219/4000] Training [12/16] Loss: 0.00594 +Epoch [2219/4000] Training [13/16] Loss: 0.00542 +Epoch [2219/4000] Training [14/16] Loss: 0.00621 +Epoch [2219/4000] Training [15/16] Loss: 0.00548 +Epoch [2219/4000] Training [16/16] Loss: 0.00650 +Epoch [2219/4000] Training metric {'Train/mean dice_metric': 0.9966907501220703, 'Train/mean miou_metric': 0.9931405782699585, 'Train/mean f1': 0.9922215938568115, 'Train/mean precision': 0.9876261353492737, 'Train/mean recall': 0.9968600273132324, 'Train/mean hd95_metric': 0.9932695031166077} +Epoch [2219/4000] Validation [1/4] Loss: 0.26205 focal_loss 0.20172 dice_loss 0.06033 +Epoch [2219/4000] Validation [2/4] Loss: 0.29943 focal_loss 0.19516 dice_loss 0.10427 +Epoch [2219/4000] Validation [3/4] Loss: 0.40451 focal_loss 0.31055 dice_loss 0.09397 +Epoch [2219/4000] Validation [4/4] Loss: 0.27788 focal_loss 0.16518 dice_loss 0.11270 +Epoch [2219/4000] Validation metric {'Val/mean dice_metric': 0.9745422601699829, 'Val/mean miou_metric': 0.9588211178779602, 'Val/mean f1': 0.9746858477592468, 'Val/mean precision': 0.9701282978057861, 'Val/mean recall': 0.979286253452301, 'Val/mean hd95_metric': 5.690934181213379} +Cheakpoint... +Epoch [2219/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745422601699829, 'Val/mean miou_metric': 0.9588211178779602, 'Val/mean f1': 0.9746858477592468, 'Val/mean precision': 0.9701282978057861, 'Val/mean recall': 0.979286253452301, 'Val/mean hd95_metric': 5.690934181213379} +Epoch [2220/4000] Training [1/16] Loss: 0.00359 +Epoch [2220/4000] Training [2/16] Loss: 0.00615 +Epoch [2220/4000] Training [3/16] Loss: 0.00457 +Epoch [2220/4000] Training [4/16] Loss: 0.00556 +Epoch [2220/4000] Training [5/16] Loss: 0.00505 +Epoch [2220/4000] Training [6/16] Loss: 0.00560 +Epoch [2220/4000] Training [7/16] Loss: 0.00446 +Epoch [2220/4000] Training [8/16] Loss: 0.00399 +Epoch [2220/4000] Training [9/16] Loss: 0.00476 +Epoch [2220/4000] Training [10/16] Loss: 0.00435 +Epoch [2220/4000] Training [11/16] Loss: 0.00339 +Epoch [2220/4000] Training [12/16] Loss: 0.00590 +Epoch [2220/4000] Training [13/16] Loss: 0.00518 +Epoch [2220/4000] Training [14/16] Loss: 0.00411 +Epoch [2220/4000] Training [15/16] Loss: 0.00577 +Epoch [2220/4000] Training [16/16] Loss: 0.00497 +Epoch [2220/4000] Training metric {'Train/mean dice_metric': 0.9967067241668701, 'Train/mean miou_metric': 0.9931545257568359, 'Train/mean f1': 0.9921582341194153, 'Train/mean precision': 0.9875952005386353, 'Train/mean recall': 0.9967636466026306, 'Train/mean hd95_metric': 1.04337477684021} +Epoch [2220/4000] Validation [1/4] Loss: 0.30947 focal_loss 0.24486 dice_loss 0.06461 +Epoch [2220/4000] Validation [2/4] Loss: 0.32740 focal_loss 0.21214 dice_loss 0.11526 +Epoch [2220/4000] Validation [3/4] Loss: 0.41475 focal_loss 0.31711 dice_loss 0.09764 +Epoch [2220/4000] Validation [4/4] Loss: 0.35442 focal_loss 0.25324 dice_loss 0.10118 +Epoch [2220/4000] Validation metric {'Val/mean dice_metric': 0.972039520740509, 'Val/mean miou_metric': 0.9563238024711609, 'Val/mean f1': 0.9747406840324402, 'Val/mean precision': 0.9739072322845459, 'Val/mean recall': 0.9755755662918091, 'Val/mean hd95_metric': 5.840268135070801} +Cheakpoint... +Epoch [2220/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972039520740509, 'Val/mean miou_metric': 0.9563238024711609, 'Val/mean f1': 0.9747406840324402, 'Val/mean precision': 0.9739072322845459, 'Val/mean recall': 0.9755755662918091, 'Val/mean hd95_metric': 5.840268135070801} +Epoch [2221/4000] Training [1/16] Loss: 0.00574 +Epoch [2221/4000] Training [2/16] Loss: 0.00385 +Epoch [2221/4000] Training [3/16] Loss: 0.00511 +Epoch [2221/4000] Training [4/16] Loss: 0.00517 +Epoch [2221/4000] Training [5/16] Loss: 0.00560 +Epoch [2221/4000] Training [6/16] Loss: 0.00415 +Epoch [2221/4000] Training [7/16] Loss: 0.00451 +Epoch [2221/4000] Training [8/16] Loss: 0.00458 +Epoch [2221/4000] Training [9/16] Loss: 0.00641 +Epoch [2221/4000] Training [10/16] Loss: 0.00464 +Epoch [2221/4000] Training [11/16] Loss: 0.00636 +Epoch [2221/4000] Training [12/16] Loss: 0.00454 +Epoch [2221/4000] Training [13/16] Loss: 0.00325 +Epoch [2221/4000] Training [14/16] Loss: 0.00548 +Epoch [2221/4000] Training [15/16] Loss: 0.00457 +Epoch [2221/4000] Training [16/16] Loss: 0.00508 +Epoch [2221/4000] Training metric {'Train/mean dice_metric': 0.9968003034591675, 'Train/mean miou_metric': 0.9933465719223022, 'Train/mean f1': 0.9922250509262085, 'Train/mean precision': 0.9876989722251892, 'Train/mean recall': 0.996792733669281, 'Train/mean hd95_metric': 0.9779250025749207} +Epoch [2221/4000] Validation [1/4] Loss: 0.24130 focal_loss 0.18037 dice_loss 0.06093 +Epoch [2221/4000] Validation [2/4] Loss: 0.32032 focal_loss 0.20526 dice_loss 0.11506 +Epoch [2221/4000] Validation [3/4] Loss: 0.41359 focal_loss 0.32008 dice_loss 0.09350 +Epoch [2221/4000] Validation [4/4] Loss: 0.23655 focal_loss 0.16135 dice_loss 0.07520 +Epoch [2221/4000] Validation metric {'Val/mean dice_metric': 0.9740787744522095, 'Val/mean miou_metric': 0.9583288431167603, 'Val/mean f1': 0.9750339984893799, 'Val/mean precision': 0.9702739715576172, 'Val/mean recall': 0.9798410534858704, 'Val/mean hd95_metric': 5.932946681976318} +Cheakpoint... +Epoch [2221/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740787744522095, 'Val/mean miou_metric': 0.9583288431167603, 'Val/mean f1': 0.9750339984893799, 'Val/mean precision': 0.9702739715576172, 'Val/mean recall': 0.9798410534858704, 'Val/mean hd95_metric': 5.932946681976318} +Epoch [2222/4000] Training [1/16] Loss: 0.00486 +Epoch [2222/4000] Training [2/16] Loss: 0.00440 +Epoch [2222/4000] Training [3/16] Loss: 0.00503 +Epoch [2222/4000] Training [4/16] Loss: 0.00485 +Epoch [2222/4000] Training [5/16] Loss: 0.00437 +Epoch [2222/4000] Training [6/16] Loss: 0.00803 +Epoch [2222/4000] Training [7/16] Loss: 0.00442 +Epoch [2222/4000] Training [8/16] Loss: 0.00475 +Epoch [2222/4000] Training [9/16] Loss: 0.00435 +Epoch [2222/4000] Training [10/16] Loss: 0.00615 +Epoch [2222/4000] Training [11/16] Loss: 0.00475 +Epoch [2222/4000] Training [12/16] Loss: 0.00443 +Epoch [2222/4000] Training [13/16] Loss: 0.00457 +Epoch [2222/4000] Training [14/16] Loss: 0.00385 +Epoch [2222/4000] Training [15/16] Loss: 0.00457 +Epoch [2222/4000] Training [16/16] Loss: 0.00400 +Epoch [2222/4000] Training metric {'Train/mean dice_metric': 0.9968953132629395, 'Train/mean miou_metric': 0.9935019612312317, 'Train/mean f1': 0.9914699196815491, 'Train/mean precision': 0.9860987663269043, 'Train/mean recall': 0.9968999028205872, 'Train/mean hd95_metric': 0.9922007918357849} +Epoch [2222/4000] Validation [1/4] Loss: 0.30317 focal_loss 0.23837 dice_loss 0.06480 +Epoch [2222/4000] Validation [2/4] Loss: 0.25934 focal_loss 0.16201 dice_loss 0.09733 +Epoch [2222/4000] Validation [3/4] Loss: 0.42341 focal_loss 0.33061 dice_loss 0.09280 +Epoch [2222/4000] Validation [4/4] Loss: 0.28130 focal_loss 0.18374 dice_loss 0.09756 +Epoch [2222/4000] Validation metric {'Val/mean dice_metric': 0.9743644595146179, 'Val/mean miou_metric': 0.9586340188980103, 'Val/mean f1': 0.9749951362609863, 'Val/mean precision': 0.9702171683311462, 'Val/mean recall': 0.9798205494880676, 'Val/mean hd95_metric': 5.797883987426758} +Cheakpoint... +Epoch [2222/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743644595146179, 'Val/mean miou_metric': 0.9586340188980103, 'Val/mean f1': 0.9749951362609863, 'Val/mean precision': 0.9702171683311462, 'Val/mean recall': 0.9798205494880676, 'Val/mean hd95_metric': 5.797883987426758} +Epoch [2223/4000] Training [1/16] Loss: 0.00653 +Epoch [2223/4000] Training [2/16] Loss: 0.00367 +Epoch [2223/4000] Training [3/16] Loss: 0.00801 +Epoch [2223/4000] Training [4/16] Loss: 0.00446 +Epoch [2223/4000] Training [5/16] Loss: 0.00526 +Epoch [2223/4000] Training [6/16] Loss: 0.00503 +Epoch [2223/4000] Training [7/16] Loss: 0.00596 +Epoch [2223/4000] Training [8/16] Loss: 0.00432 +Epoch [2223/4000] Training [9/16] Loss: 0.00520 +Epoch [2223/4000] Training [10/16] Loss: 0.00501 +Epoch [2223/4000] Training [11/16] Loss: 0.00526 +Epoch [2223/4000] Training [12/16] Loss: 0.00453 +Epoch [2223/4000] Training [13/16] Loss: 0.00584 +Epoch [2223/4000] Training [14/16] Loss: 0.00476 +Epoch [2223/4000] Training [15/16] Loss: 0.00430 +Epoch [2223/4000] Training [16/16] Loss: 0.00472 +Epoch [2223/4000] Training metric {'Train/mean dice_metric': 0.996695876121521, 'Train/mean miou_metric': 0.9931122660636902, 'Train/mean f1': 0.9916074872016907, 'Train/mean precision': 0.9864553213119507, 'Train/mean recall': 0.9968137741088867, 'Train/mean hd95_metric': 0.9961585402488708} +Epoch [2223/4000] Validation [1/4] Loss: 0.27533 focal_loss 0.21610 dice_loss 0.05923 +Epoch [2223/4000] Validation [2/4] Loss: 0.66270 focal_loss 0.44517 dice_loss 0.21752 +Epoch [2223/4000] Validation [3/4] Loss: 0.24325 focal_loss 0.17152 dice_loss 0.07173 +Epoch [2223/4000] Validation [4/4] Loss: 0.28920 focal_loss 0.18704 dice_loss 0.10216 +Epoch [2223/4000] Validation metric {'Val/mean dice_metric': 0.9727576971054077, 'Val/mean miou_metric': 0.9574779272079468, 'Val/mean f1': 0.9730373620986938, 'Val/mean precision': 0.9681976437568665, 'Val/mean recall': 0.977925717830658, 'Val/mean hd95_metric': 6.082253456115723} +Cheakpoint... +Epoch [2223/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727576971054077, 'Val/mean miou_metric': 0.9574779272079468, 'Val/mean f1': 0.9730373620986938, 'Val/mean precision': 0.9681976437568665, 'Val/mean recall': 0.977925717830658, 'Val/mean hd95_metric': 6.082253456115723} +Epoch [2224/4000] Training [1/16] Loss: 0.00631 +Epoch [2224/4000] Training [2/16] Loss: 0.00536 +Epoch [2224/4000] Training [3/16] Loss: 0.00534 +Epoch [2224/4000] Training [4/16] Loss: 0.00444 +Epoch [2224/4000] Training [5/16] Loss: 0.00512 +Epoch [2224/4000] Training [6/16] Loss: 0.00441 +Epoch [2224/4000] Training [7/16] Loss: 0.00559 +Epoch [2224/4000] Training [8/16] Loss: 0.00597 +Epoch [2224/4000] Training [9/16] Loss: 0.00492 +Epoch [2224/4000] Training [10/16] Loss: 0.00681 +Epoch [2224/4000] Training [11/16] Loss: 0.00416 +Epoch [2224/4000] Training [12/16] Loss: 0.00682 +Epoch [2224/4000] Training [13/16] Loss: 0.00490 +Epoch [2224/4000] Training [14/16] Loss: 0.00463 +Epoch [2224/4000] Training [15/16] Loss: 0.00562 +Epoch [2224/4000] Training [16/16] Loss: 0.00415 +Epoch [2224/4000] Training metric {'Train/mean dice_metric': 0.9965366125106812, 'Train/mean miou_metric': 0.9928350448608398, 'Train/mean f1': 0.9921829104423523, 'Train/mean precision': 0.9876229763031006, 'Train/mean recall': 0.9967851638793945, 'Train/mean hd95_metric': 0.9892018437385559} +Epoch [2224/4000] Validation [1/4] Loss: 0.26945 focal_loss 0.21112 dice_loss 0.05833 +Epoch [2224/4000] Validation [2/4] Loss: 0.32030 focal_loss 0.20331 dice_loss 0.11700 +Epoch [2224/4000] Validation [3/4] Loss: 0.44783 focal_loss 0.34358 dice_loss 0.10424 +Epoch [2224/4000] Validation [4/4] Loss: 0.30318 focal_loss 0.20318 dice_loss 0.10000 +Epoch [2224/4000] Validation metric {'Val/mean dice_metric': 0.9730526208877563, 'Val/mean miou_metric': 0.9572708010673523, 'Val/mean f1': 0.9738250374794006, 'Val/mean precision': 0.9693068861961365, 'Val/mean recall': 0.9783855676651001, 'Val/mean hd95_metric': 6.154547214508057} +Cheakpoint... +Epoch [2224/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730526208877563, 'Val/mean miou_metric': 0.9572708010673523, 'Val/mean f1': 0.9738250374794006, 'Val/mean precision': 0.9693068861961365, 'Val/mean recall': 0.9783855676651001, 'Val/mean hd95_metric': 6.154547214508057} +Epoch [2225/4000] Training [1/16] Loss: 0.00388 +Epoch [2225/4000] Training [2/16] Loss: 0.00460 +Epoch [2225/4000] Training [3/16] Loss: 0.00444 +Epoch [2225/4000] Training [4/16] Loss: 0.00632 +Epoch [2225/4000] Training [5/16] Loss: 0.00466 +Epoch [2225/4000] Training [6/16] Loss: 0.00462 +Epoch [2225/4000] Training [7/16] Loss: 0.00405 +Epoch [2225/4000] Training [8/16] Loss: 0.00656 +Epoch [2225/4000] Training [9/16] Loss: 0.00479 +Epoch [2225/4000] Training [10/16] Loss: 0.00619 +Epoch [2225/4000] Training [11/16] Loss: 0.00593 +Epoch [2225/4000] Training [12/16] Loss: 0.01036 +Epoch [2225/4000] Training [13/16] Loss: 0.00519 +Epoch [2225/4000] Training [14/16] Loss: 0.00601 +Epoch [2225/4000] Training [15/16] Loss: 0.00538 +Epoch [2225/4000] Training [16/16] Loss: 0.00437 +Epoch [2225/4000] Training metric {'Train/mean dice_metric': 0.996590793132782, 'Train/mean miou_metric': 0.992939829826355, 'Train/mean f1': 0.9922923445701599, 'Train/mean precision': 0.9877859950065613, 'Train/mean recall': 0.9968399405479431, 'Train/mean hd95_metric': 1.0448886156082153} +Epoch [2225/4000] Validation [1/4] Loss: 0.35315 focal_loss 0.28648 dice_loss 0.06667 +Epoch [2225/4000] Validation [2/4] Loss: 0.58842 focal_loss 0.39373 dice_loss 0.19469 +Epoch [2225/4000] Validation [3/4] Loss: 0.46465 focal_loss 0.36236 dice_loss 0.10228 +Epoch [2225/4000] Validation [4/4] Loss: 0.29987 focal_loss 0.20852 dice_loss 0.09135 +Epoch [2225/4000] Validation metric {'Val/mean dice_metric': 0.9709668159484863, 'Val/mean miou_metric': 0.9554159045219421, 'Val/mean f1': 0.9737217426300049, 'Val/mean precision': 0.969395637512207, 'Val/mean recall': 0.9780865907669067, 'Val/mean hd95_metric': 6.016185283660889} +Cheakpoint... +Epoch [2225/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709668159484863, 'Val/mean miou_metric': 0.9554159045219421, 'Val/mean f1': 0.9737217426300049, 'Val/mean precision': 0.969395637512207, 'Val/mean recall': 0.9780865907669067, 'Val/mean hd95_metric': 6.016185283660889} +Epoch [2226/4000] Training [1/16] Loss: 0.00397 +Epoch [2226/4000] Training [2/16] Loss: 0.00958 +Epoch [2226/4000] Training [3/16] Loss: 0.00549 +Epoch [2226/4000] Training [4/16] Loss: 0.00637 +Epoch [2226/4000] Training [5/16] Loss: 0.00599 +Epoch [2226/4000] Training [6/16] Loss: 0.00563 +Epoch [2226/4000] Training [7/16] Loss: 0.00520 +Epoch [2226/4000] Training [8/16] Loss: 0.00611 +Epoch [2226/4000] Training [9/16] Loss: 0.00684 +Epoch [2226/4000] Training [10/16] Loss: 0.00436 +Epoch [2226/4000] Training [11/16] Loss: 0.00379 +Epoch [2226/4000] Training [12/16] Loss: 0.00590 +Epoch [2226/4000] Training [13/16] Loss: 0.00462 +Epoch [2226/4000] Training [14/16] Loss: 0.00465 +Epoch [2226/4000] Training [15/16] Loss: 0.00602 +Epoch [2226/4000] Training [16/16] Loss: 0.00524 +Epoch [2226/4000] Training metric {'Train/mean dice_metric': 0.9963235855102539, 'Train/mean miou_metric': 0.9924182891845703, 'Train/mean f1': 0.9920568466186523, 'Train/mean precision': 0.9875065684318542, 'Train/mean recall': 0.9966492652893066, 'Train/mean hd95_metric': 1.2088558673858643} +Epoch [2226/4000] Validation [1/4] Loss: 0.33574 focal_loss 0.26573 dice_loss 0.07001 +Epoch [2226/4000] Validation [2/4] Loss: 0.29798 focal_loss 0.19166 dice_loss 0.10632 +Epoch [2226/4000] Validation [3/4] Loss: 0.40484 focal_loss 0.30991 dice_loss 0.09493 +Epoch [2226/4000] Validation [4/4] Loss: 0.33967 focal_loss 0.22978 dice_loss 0.10988 +Epoch [2226/4000] Validation metric {'Val/mean dice_metric': 0.9746776819229126, 'Val/mean miou_metric': 0.958347499370575, 'Val/mean f1': 0.9754562377929688, 'Val/mean precision': 0.9726581573486328, 'Val/mean recall': 0.9782706499099731, 'Val/mean hd95_metric': 5.671872138977051} +Cheakpoint... +Epoch [2226/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746776819229126, 'Val/mean miou_metric': 0.958347499370575, 'Val/mean f1': 0.9754562377929688, 'Val/mean precision': 0.9726581573486328, 'Val/mean recall': 0.9782706499099731, 'Val/mean hd95_metric': 5.671872138977051} +Epoch [2227/4000] Training [1/16] Loss: 0.00519 +Epoch [2227/4000] Training [2/16] Loss: 0.00572 +Epoch [2227/4000] Training [3/16] Loss: 0.00694 +Epoch [2227/4000] Training [4/16] Loss: 0.00526 +Epoch [2227/4000] Training [5/16] Loss: 0.00499 +Epoch [2227/4000] Training [6/16] Loss: 0.00615 +Epoch [2227/4000] Training [7/16] Loss: 0.00734 +Epoch [2227/4000] Training [8/16] Loss: 0.00502 +Epoch [2227/4000] Training [9/16] Loss: 0.00499 +Epoch [2227/4000] Training [10/16] Loss: 0.00548 +Epoch [2227/4000] Training [11/16] Loss: 0.00435 +Epoch [2227/4000] Training [12/16] Loss: 0.00648 +Epoch [2227/4000] Training [13/16] Loss: 0.00620 +Epoch [2227/4000] Training [14/16] Loss: 0.00487 +Epoch [2227/4000] Training [15/16] Loss: 0.00423 +Epoch [2227/4000] Training [16/16] Loss: 0.00629 +Epoch [2227/4000] Training metric {'Train/mean dice_metric': 0.9963334202766418, 'Train/mean miou_metric': 0.9924168586730957, 'Train/mean f1': 0.9918492436408997, 'Train/mean precision': 0.9872284531593323, 'Train/mean recall': 0.9965134263038635, 'Train/mean hd95_metric': 1.0013654232025146} +Epoch [2227/4000] Validation [1/4] Loss: 0.27878 focal_loss 0.21656 dice_loss 0.06222 +Epoch [2227/4000] Validation [2/4] Loss: 0.73313 focal_loss 0.54144 dice_loss 0.19169 +Epoch [2227/4000] Validation [3/4] Loss: 0.30321 focal_loss 0.21544 dice_loss 0.08777 +Epoch [2227/4000] Validation [4/4] Loss: 0.29995 focal_loss 0.19335 dice_loss 0.10660 +Epoch [2227/4000] Validation metric {'Val/mean dice_metric': 0.972996711730957, 'Val/mean miou_metric': 0.9573561549186707, 'Val/mean f1': 0.9745842814445496, 'Val/mean precision': 0.9713274240493774, 'Val/mean recall': 0.9778631329536438, 'Val/mean hd95_metric': 5.559075355529785} +Cheakpoint... +Epoch [2227/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972996711730957, 'Val/mean miou_metric': 0.9573561549186707, 'Val/mean f1': 0.9745842814445496, 'Val/mean precision': 0.9713274240493774, 'Val/mean recall': 0.9778631329536438, 'Val/mean hd95_metric': 5.559075355529785} +Epoch [2228/4000] Training [1/16] Loss: 0.00676 +Epoch [2228/4000] Training [2/16] Loss: 0.00462 +Epoch [2228/4000] Training [3/16] Loss: 0.00415 +Epoch [2228/4000] Training [4/16] Loss: 0.00683 +Epoch [2228/4000] Training [5/16] Loss: 0.00902 +Epoch [2228/4000] Training [6/16] Loss: 0.00460 +Epoch [2228/4000] Training [7/16] Loss: 0.00609 +Epoch [2228/4000] Training [8/16] Loss: 0.00517 +Epoch [2228/4000] Training [9/16] Loss: 0.00466 +Epoch [2228/4000] Training [10/16] Loss: 0.00404 +Epoch [2228/4000] Training [11/16] Loss: 0.00453 +Epoch [2228/4000] Training [12/16] Loss: 0.00644 +Epoch [2228/4000] Training [13/16] Loss: 0.00623 +Epoch [2228/4000] Training [14/16] Loss: 0.00418 +Epoch [2228/4000] Training [15/16] Loss: 0.00495 +Epoch [2228/4000] Training [16/16] Loss: 0.00788 +Epoch [2228/4000] Training metric {'Train/mean dice_metric': 0.9965952634811401, 'Train/mean miou_metric': 0.9929220080375671, 'Train/mean f1': 0.9916903376579285, 'Train/mean precision': 0.9868385195732117, 'Train/mean recall': 0.9965901374816895, 'Train/mean hd95_metric': 1.1631405353546143} +Epoch [2228/4000] Validation [1/4] Loss: 0.28057 focal_loss 0.21931 dice_loss 0.06126 +Epoch [2228/4000] Validation [2/4] Loss: 0.53004 focal_loss 0.33560 dice_loss 0.19444 +Epoch [2228/4000] Validation [3/4] Loss: 0.29253 focal_loss 0.20470 dice_loss 0.08783 +Epoch [2228/4000] Validation [4/4] Loss: 0.22426 focal_loss 0.14982 dice_loss 0.07444 +Epoch [2228/4000] Validation metric {'Val/mean dice_metric': 0.971282958984375, 'Val/mean miou_metric': 0.9556578397750854, 'Val/mean f1': 0.9744265079498291, 'Val/mean precision': 0.9736708402633667, 'Val/mean recall': 0.9751834273338318, 'Val/mean hd95_metric': 5.318653106689453} +Cheakpoint... +Epoch [2228/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971282958984375, 'Val/mean miou_metric': 0.9556578397750854, 'Val/mean f1': 0.9744265079498291, 'Val/mean precision': 0.9736708402633667, 'Val/mean recall': 0.9751834273338318, 'Val/mean hd95_metric': 5.318653106689453} +Epoch [2229/4000] Training [1/16] Loss: 0.00434 +Epoch [2229/4000] Training [2/16] Loss: 0.00465 +Epoch [2229/4000] Training [3/16] Loss: 0.00648 +Epoch [2229/4000] Training [4/16] Loss: 0.00701 +Epoch [2229/4000] Training [5/16] Loss: 0.00452 +Epoch [2229/4000] Training [6/16] Loss: 0.00559 +Epoch [2229/4000] Training [7/16] Loss: 0.00515 +Epoch [2229/4000] Training [8/16] Loss: 0.00602 +Epoch [2229/4000] Training [9/16] Loss: 0.00629 +Epoch [2229/4000] Training [10/16] Loss: 0.00649 +Epoch [2229/4000] Training [11/16] Loss: 0.00357 +Epoch [2229/4000] Training [12/16] Loss: 0.00573 +Epoch [2229/4000] Training [13/16] Loss: 0.00542 +Epoch [2229/4000] Training [14/16] Loss: 0.00573 +Epoch [2229/4000] Training [15/16] Loss: 0.00521 +Epoch [2229/4000] Training [16/16] Loss: 0.00556 +Epoch [2229/4000] Training metric {'Train/mean dice_metric': 0.996547281742096, 'Train/mean miou_metric': 0.9928560256958008, 'Train/mean f1': 0.9921597242355347, 'Train/mean precision': 0.9875321984291077, 'Train/mean recall': 0.9968308210372925, 'Train/mean hd95_metric': 0.9900076389312744} +Epoch [2229/4000] Validation [1/4] Loss: 0.29182 focal_loss 0.23044 dice_loss 0.06138 +Epoch [2229/4000] Validation [2/4] Loss: 0.51468 focal_loss 0.35253 dice_loss 0.16215 +Epoch [2229/4000] Validation [3/4] Loss: 0.58498 focal_loss 0.46353 dice_loss 0.12146 +Epoch [2229/4000] Validation [4/4] Loss: 0.36507 focal_loss 0.25161 dice_loss 0.11345 +Epoch [2229/4000] Validation metric {'Val/mean dice_metric': 0.9719488024711609, 'Val/mean miou_metric': 0.9560966491699219, 'Val/mean f1': 0.9742280840873718, 'Val/mean precision': 0.9723801612854004, 'Val/mean recall': 0.9760831594467163, 'Val/mean hd95_metric': 5.895547389984131} +Cheakpoint... +Epoch [2229/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719488024711609, 'Val/mean miou_metric': 0.9560966491699219, 'Val/mean f1': 0.9742280840873718, 'Val/mean precision': 0.9723801612854004, 'Val/mean recall': 0.9760831594467163, 'Val/mean hd95_metric': 5.895547389984131} +Epoch [2230/4000] Training [1/16] Loss: 0.00819 +Epoch [2230/4000] Training [2/16] Loss: 0.00568 +Epoch [2230/4000] Training [3/16] Loss: 0.00631 +Epoch [2230/4000] Training [4/16] Loss: 0.00479 +Epoch [2230/4000] Training [5/16] Loss: 0.00641 +Epoch [2230/4000] Training [6/16] Loss: 0.00722 +Epoch [2230/4000] Training [7/16] Loss: 0.00464 +Epoch [2230/4000] Training [8/16] Loss: 0.00671 +Epoch [2230/4000] Training [9/16] Loss: 0.00650 +Epoch [2230/4000] Training [10/16] Loss: 0.00480 +Epoch [2230/4000] Training [11/16] Loss: 0.00507 +Epoch [2230/4000] Training [12/16] Loss: 0.00543 +Epoch [2230/4000] Training [13/16] Loss: 0.00542 +Epoch [2230/4000] Training [14/16] Loss: 0.00498 +Epoch [2230/4000] Training [15/16] Loss: 0.00519 +Epoch [2230/4000] Training [16/16] Loss: 0.00487 +Epoch [2230/4000] Training metric {'Train/mean dice_metric': 0.9961811304092407, 'Train/mean miou_metric': 0.9921073913574219, 'Train/mean f1': 0.9911817312240601, 'Train/mean precision': 0.9860841631889343, 'Train/mean recall': 0.9963322877883911, 'Train/mean hd95_metric': 1.0556614398956299} +Epoch [2230/4000] Validation [1/4] Loss: 0.33589 focal_loss 0.26309 dice_loss 0.07279 +Epoch [2230/4000] Validation [2/4] Loss: 0.53244 focal_loss 0.33464 dice_loss 0.19780 +Epoch [2230/4000] Validation [3/4] Loss: 0.25938 focal_loss 0.17888 dice_loss 0.08050 +Epoch [2230/4000] Validation [4/4] Loss: 0.60651 focal_loss 0.46623 dice_loss 0.14028 +Epoch [2230/4000] Validation metric {'Val/mean dice_metric': 0.9705613851547241, 'Val/mean miou_metric': 0.9541948437690735, 'Val/mean f1': 0.9728479981422424, 'Val/mean precision': 0.9731255173683167, 'Val/mean recall': 0.9725704789161682, 'Val/mean hd95_metric': 5.605462074279785} +Cheakpoint... +Epoch [2230/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705613851547241, 'Val/mean miou_metric': 0.9541948437690735, 'Val/mean f1': 0.9728479981422424, 'Val/mean precision': 0.9731255173683167, 'Val/mean recall': 0.9725704789161682, 'Val/mean hd95_metric': 5.605462074279785} +Epoch [2231/4000] Training [1/16] Loss: 0.00517 +Epoch [2231/4000] Training [2/16] Loss: 0.00670 +Epoch [2231/4000] Training [3/16] Loss: 0.00338 +Epoch [2231/4000] Training [4/16] Loss: 0.00430 +Epoch [2231/4000] Training [5/16] Loss: 0.00504 +Epoch [2231/4000] Training [6/16] Loss: 0.00708 +Epoch [2231/4000] Training [7/16] Loss: 0.00504 +Epoch [2231/4000] Training [8/16] Loss: 0.00375 +Epoch [2231/4000] Training [9/16] Loss: 0.00424 +Epoch [2231/4000] Training [10/16] Loss: 0.00381 +Epoch [2231/4000] Training [11/16] Loss: 0.00634 +Epoch [2231/4000] Training [12/16] Loss: 0.00434 +Epoch [2231/4000] Training [13/16] Loss: 0.00790 +Epoch [2231/4000] Training [14/16] Loss: 0.00591 +Epoch [2231/4000] Training [15/16] Loss: 0.00613 +Epoch [2231/4000] Training [16/16] Loss: 0.00422 +Epoch [2231/4000] Training metric {'Train/mean dice_metric': 0.9966287612915039, 'Train/mean miou_metric': 0.9930016994476318, 'Train/mean f1': 0.9921057820320129, 'Train/mean precision': 0.9875084161758423, 'Train/mean recall': 0.9967461824417114, 'Train/mean hd95_metric': 1.0023571252822876} +Epoch [2231/4000] Validation [1/4] Loss: 0.32408 focal_loss 0.25720 dice_loss 0.06689 +Epoch [2231/4000] Validation [2/4] Loss: 0.31517 focal_loss 0.19728 dice_loss 0.11790 +Epoch [2231/4000] Validation [3/4] Loss: 0.38103 focal_loss 0.28866 dice_loss 0.09237 +Epoch [2231/4000] Validation [4/4] Loss: 0.25038 focal_loss 0.16432 dice_loss 0.08606 +Epoch [2231/4000] Validation metric {'Val/mean dice_metric': 0.9715738296508789, 'Val/mean miou_metric': 0.9561256170272827, 'Val/mean f1': 0.9747459292411804, 'Val/mean precision': 0.9726502895355225, 'Val/mean recall': 0.976850688457489, 'Val/mean hd95_metric': 5.1859130859375} +Cheakpoint... +Epoch [2231/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715738296508789, 'Val/mean miou_metric': 0.9561256170272827, 'Val/mean f1': 0.9747459292411804, 'Val/mean precision': 0.9726502895355225, 'Val/mean recall': 0.976850688457489, 'Val/mean hd95_metric': 5.1859130859375} +Epoch [2232/4000] Training [1/16] Loss: 0.00486 +Epoch [2232/4000] Training [2/16] Loss: 0.00758 +Epoch [2232/4000] Training [3/16] Loss: 0.00720 +Epoch [2232/4000] Training [4/16] Loss: 0.00532 +Epoch [2232/4000] Training [5/16] Loss: 0.00452 +Epoch [2232/4000] Training [6/16] Loss: 0.00444 +Epoch [2232/4000] Training [7/16] Loss: 0.00437 +Epoch [2232/4000] Training [8/16] Loss: 0.00404 +Epoch [2232/4000] Training [9/16] Loss: 0.00445 +Epoch [2232/4000] Training [10/16] Loss: 0.00554 +Epoch [2232/4000] Training [11/16] Loss: 0.00707 +Epoch [2232/4000] Training [12/16] Loss: 0.00668 +Epoch [2232/4000] Training [13/16] Loss: 0.00690 +Epoch [2232/4000] Training [14/16] Loss: 0.00643 +Epoch [2232/4000] Training [15/16] Loss: 0.00449 +Epoch [2232/4000] Training [16/16] Loss: 0.00418 +Epoch [2232/4000] Training metric {'Train/mean dice_metric': 0.9966427087783813, 'Train/mean miou_metric': 0.9930188059806824, 'Train/mean f1': 0.9918060302734375, 'Train/mean precision': 0.9869704842567444, 'Train/mean recall': 0.9966891407966614, 'Train/mean hd95_metric': 1.0015175342559814} +Epoch [2232/4000] Validation [1/4] Loss: 0.27622 focal_loss 0.21179 dice_loss 0.06443 +Epoch [2232/4000] Validation [2/4] Loss: 1.00581 focal_loss 0.76307 dice_loss 0.24274 +Epoch [2232/4000] Validation [3/4] Loss: 0.35926 focal_loss 0.25847 dice_loss 0.10079 +Epoch [2232/4000] Validation [4/4] Loss: 0.30230 focal_loss 0.20462 dice_loss 0.09768 +Epoch [2232/4000] Validation metric {'Val/mean dice_metric': 0.9713791608810425, 'Val/mean miou_metric': 0.9555796384811401, 'Val/mean f1': 0.9742091298103333, 'Val/mean precision': 0.9716657400131226, 'Val/mean recall': 0.9767659306526184, 'Val/mean hd95_metric': 5.520389556884766} +Cheakpoint... +Epoch [2232/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713791608810425, 'Val/mean miou_metric': 0.9555796384811401, 'Val/mean f1': 0.9742091298103333, 'Val/mean precision': 0.9716657400131226, 'Val/mean recall': 0.9767659306526184, 'Val/mean hd95_metric': 5.520389556884766} +Epoch [2233/4000] Training [1/16] Loss: 0.00579 +Epoch [2233/4000] Training [2/16] Loss: 0.00461 +Epoch [2233/4000] Training [3/16] Loss: 0.00742 +Epoch [2233/4000] Training [4/16] Loss: 0.00437 +Epoch [2233/4000] Training [5/16] Loss: 0.00513 +Epoch [2233/4000] Training [6/16] Loss: 0.00619 +Epoch [2233/4000] Training [7/16] Loss: 0.00529 +Epoch [2233/4000] Training [8/16] Loss: 0.00382 +Epoch [2233/4000] Training [9/16] Loss: 0.00520 +Epoch [2233/4000] Training [10/16] Loss: 0.00499 +Epoch [2233/4000] Training [11/16] Loss: 0.00378 +Epoch [2233/4000] Training [12/16] Loss: 0.00496 +Epoch [2233/4000] Training [13/16] Loss: 0.00449 +Epoch [2233/4000] Training [14/16] Loss: 0.00634 +Epoch [2233/4000] Training [15/16] Loss: 0.00619 +Epoch [2233/4000] Training [16/16] Loss: 0.00465 +Epoch [2233/4000] Training metric {'Train/mean dice_metric': 0.9966086745262146, 'Train/mean miou_metric': 0.9929803609848022, 'Train/mean f1': 0.9922972321510315, 'Train/mean precision': 0.9877400994300842, 'Train/mean recall': 0.9968966245651245, 'Train/mean hd95_metric': 0.995646595954895} +Epoch [2233/4000] Validation [1/4] Loss: 0.31432 focal_loss 0.25103 dice_loss 0.06329 +Epoch [2233/4000] Validation [2/4] Loss: 0.42446 focal_loss 0.28444 dice_loss 0.14002 +Epoch [2233/4000] Validation [3/4] Loss: 0.43169 focal_loss 0.33612 dice_loss 0.09558 +Epoch [2233/4000] Validation [4/4] Loss: 0.49324 focal_loss 0.37328 dice_loss 0.11997 +Epoch [2233/4000] Validation metric {'Val/mean dice_metric': 0.9735309481620789, 'Val/mean miou_metric': 0.9575954675674438, 'Val/mean f1': 0.9745073914527893, 'Val/mean precision': 0.9722151756286621, 'Val/mean recall': 0.9768105149269104, 'Val/mean hd95_metric': 5.424992084503174} +Cheakpoint... +Epoch [2233/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735309481620789, 'Val/mean miou_metric': 0.9575954675674438, 'Val/mean f1': 0.9745073914527893, 'Val/mean precision': 0.9722151756286621, 'Val/mean recall': 0.9768105149269104, 'Val/mean hd95_metric': 5.424992084503174} +Epoch [2234/4000] Training [1/16] Loss: 0.00468 +Epoch [2234/4000] Training [2/16] Loss: 0.00553 +Epoch [2234/4000] Training [3/16] Loss: 0.00394 +Epoch [2234/4000] Training [4/16] Loss: 0.00421 +Epoch [2234/4000] Training [5/16] Loss: 0.00497 +Epoch [2234/4000] Training [6/16] Loss: 0.00617 +Epoch [2234/4000] Training [7/16] Loss: 0.00354 +Epoch [2234/4000] Training [8/16] Loss: 0.00422 +Epoch [2234/4000] Training [9/16] Loss: 0.00505 +Epoch [2234/4000] Training [10/16] Loss: 0.00603 +Epoch [2234/4000] Training [11/16] Loss: 0.00495 +Epoch [2234/4000] Training [12/16] Loss: 0.00633 +Epoch [2234/4000] Training [13/16] Loss: 0.00395 +Epoch [2234/4000] Training [14/16] Loss: 0.00686 +Epoch [2234/4000] Training [15/16] Loss: 0.00433 +Epoch [2234/4000] Training [16/16] Loss: 0.00575 +Epoch [2234/4000] Training metric {'Train/mean dice_metric': 0.9965671896934509, 'Train/mean miou_metric': 0.9928954839706421, 'Train/mean f1': 0.992305338382721, 'Train/mean precision': 0.9878314137458801, 'Train/mean recall': 0.9968200325965881, 'Train/mean hd95_metric': 0.9992029666900635} +Epoch [2234/4000] Validation [1/4] Loss: 0.28919 focal_loss 0.22638 dice_loss 0.06281 +Epoch [2234/4000] Validation [2/4] Loss: 0.38763 focal_loss 0.24996 dice_loss 0.13767 +Epoch [2234/4000] Validation [3/4] Loss: 0.40844 focal_loss 0.31353 dice_loss 0.09491 +Epoch [2234/4000] Validation [4/4] Loss: 0.36046 focal_loss 0.23881 dice_loss 0.12165 +Epoch [2234/4000] Validation metric {'Val/mean dice_metric': 0.9737738370895386, 'Val/mean miou_metric': 0.9579607248306274, 'Val/mean f1': 0.9752993583679199, 'Val/mean precision': 0.9727476239204407, 'Val/mean recall': 0.9778645038604736, 'Val/mean hd95_metric': 5.721777439117432} +Cheakpoint... +Epoch [2234/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737738370895386, 'Val/mean miou_metric': 0.9579607248306274, 'Val/mean f1': 0.9752993583679199, 'Val/mean precision': 0.9727476239204407, 'Val/mean recall': 0.9778645038604736, 'Val/mean hd95_metric': 5.721777439117432} +Epoch [2235/4000] Training [1/16] Loss: 0.00348 +Epoch [2235/4000] Training [2/16] Loss: 0.00374 +Epoch [2235/4000] Training [3/16] Loss: 0.00545 +Epoch [2235/4000] Training [4/16] Loss: 0.00964 +Epoch [2235/4000] Training [5/16] Loss: 0.00515 +Epoch [2235/4000] Training [6/16] Loss: 0.00390 +Epoch [2235/4000] Training [7/16] Loss: 0.00604 +Epoch [2235/4000] Training [8/16] Loss: 0.00436 +Epoch [2235/4000] Training [9/16] Loss: 0.00493 +Epoch [2235/4000] Training [10/16] Loss: 0.00747 +Epoch [2235/4000] Training [11/16] Loss: 0.00538 +Epoch [2235/4000] Training [12/16] Loss: 0.00742 +Epoch [2235/4000] Training [13/16] Loss: 0.00446 +Epoch [2235/4000] Training [14/16] Loss: 0.00787 +Epoch [2235/4000] Training [15/16] Loss: 0.00435 +Epoch [2235/4000] Training [16/16] Loss: 0.00455 +Epoch [2235/4000] Training metric {'Train/mean dice_metric': 0.9965572357177734, 'Train/mean miou_metric': 0.9928492307662964, 'Train/mean f1': 0.9915512800216675, 'Train/mean precision': 0.9864723682403564, 'Train/mean recall': 0.9966827630996704, 'Train/mean hd95_metric': 1.002328872680664} +Epoch [2235/4000] Validation [1/4] Loss: 0.25919 focal_loss 0.19807 dice_loss 0.06112 +Epoch [2235/4000] Validation [2/4] Loss: 0.27972 focal_loss 0.17638 dice_loss 0.10335 +Epoch [2235/4000] Validation [3/4] Loss: 0.44894 focal_loss 0.35503 dice_loss 0.09391 +Epoch [2235/4000] Validation [4/4] Loss: 0.34383 focal_loss 0.23271 dice_loss 0.11112 +Epoch [2235/4000] Validation metric {'Val/mean dice_metric': 0.972643256187439, 'Val/mean miou_metric': 0.9567114114761353, 'Val/mean f1': 0.9743254780769348, 'Val/mean precision': 0.971339225769043, 'Val/mean recall': 0.977330207824707, 'Val/mean hd95_metric': 5.36791467666626} +Cheakpoint... +Epoch [2235/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972643256187439, 'Val/mean miou_metric': 0.9567114114761353, 'Val/mean f1': 0.9743254780769348, 'Val/mean precision': 0.971339225769043, 'Val/mean recall': 0.977330207824707, 'Val/mean hd95_metric': 5.36791467666626} +Epoch [2236/4000] Training [1/16] Loss: 0.00500 +Epoch [2236/4000] Training [2/16] Loss: 0.00582 +Epoch [2236/4000] Training [3/16] Loss: 0.00537 +Epoch [2236/4000] Training [4/16] Loss: 0.00621 +Epoch [2236/4000] Training [5/16] Loss: 0.00361 +Epoch [2236/4000] Training [6/16] Loss: 0.00415 +Epoch [2236/4000] Training [7/16] Loss: 0.00378 +Epoch [2236/4000] Training [8/16] Loss: 0.00582 +Epoch [2236/4000] Training [9/16] Loss: 0.00443 +Epoch [2236/4000] Training [10/16] Loss: 0.00624 +Epoch [2236/4000] Training [11/16] Loss: 0.00733 +Epoch [2236/4000] Training [12/16] Loss: 0.00470 +Epoch [2236/4000] Training [13/16] Loss: 0.00785 +Epoch [2236/4000] Training [14/16] Loss: 0.00489 +Epoch [2236/4000] Training [15/16] Loss: 0.00468 +Epoch [2236/4000] Training [16/16] Loss: 0.00578 +Epoch [2236/4000] Training metric {'Train/mean dice_metric': 0.9964596033096313, 'Train/mean miou_metric': 0.9926934242248535, 'Train/mean f1': 0.9921776056289673, 'Train/mean precision': 0.9876722097396851, 'Train/mean recall': 0.9967243075370789, 'Train/mean hd95_metric': 1.0006985664367676} +Epoch [2236/4000] Validation [1/4] Loss: 0.30518 focal_loss 0.24269 dice_loss 0.06249 +Epoch [2236/4000] Validation [2/4] Loss: 0.30683 focal_loss 0.19170 dice_loss 0.11513 +Epoch [2236/4000] Validation [3/4] Loss: 0.42392 focal_loss 0.33320 dice_loss 0.09073 +Epoch [2236/4000] Validation [4/4] Loss: 0.30543 focal_loss 0.20669 dice_loss 0.09874 +Epoch [2236/4000] Validation metric {'Val/mean dice_metric': 0.9733670949935913, 'Val/mean miou_metric': 0.9573968052864075, 'Val/mean f1': 0.9750796556472778, 'Val/mean precision': 0.9715508222579956, 'Val/mean recall': 0.9786340594291687, 'Val/mean hd95_metric': 5.67331075668335} +Cheakpoint... +Epoch [2236/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733670949935913, 'Val/mean miou_metric': 0.9573968052864075, 'Val/mean f1': 0.9750796556472778, 'Val/mean precision': 0.9715508222579956, 'Val/mean recall': 0.9786340594291687, 'Val/mean hd95_metric': 5.67331075668335} +Epoch [2237/4000] Training [1/16] Loss: 0.00676 +Epoch [2237/4000] Training [2/16] Loss: 0.00472 +Epoch [2237/4000] Training [3/16] Loss: 0.00462 +Epoch [2237/4000] Training [4/16] Loss: 0.00368 +Epoch [2237/4000] Training [5/16] Loss: 0.00521 +Epoch [2237/4000] Training [6/16] Loss: 0.00527 +Epoch [2237/4000] Training [7/16] Loss: 0.00578 +Epoch [2237/4000] Training [8/16] Loss: 0.00387 +Epoch [2237/4000] Training [9/16] Loss: 0.00547 +Epoch [2237/4000] Training [10/16] Loss: 0.00513 +Epoch [2237/4000] Training [11/16] Loss: 0.00357 +Epoch [2237/4000] Training [12/16] Loss: 0.00595 +Epoch [2237/4000] Training [13/16] Loss: 0.00604 +Epoch [2237/4000] Training [14/16] Loss: 0.00488 +Epoch [2237/4000] Training [15/16] Loss: 0.00423 +Epoch [2237/4000] Training [16/16] Loss: 0.00566 +Epoch [2237/4000] Training metric {'Train/mean dice_metric': 0.9966917037963867, 'Train/mean miou_metric': 0.9931368827819824, 'Train/mean f1': 0.992254912853241, 'Train/mean precision': 0.9877243041992188, 'Train/mean recall': 0.9968271851539612, 'Train/mean hd95_metric': 0.9932756423950195} +Epoch [2237/4000] Validation [1/4] Loss: 0.32005 focal_loss 0.25347 dice_loss 0.06658 +Epoch [2237/4000] Validation [2/4] Loss: 0.26351 focal_loss 0.16175 dice_loss 0.10176 +Epoch [2237/4000] Validation [3/4] Loss: 0.36593 focal_loss 0.26618 dice_loss 0.09975 +Epoch [2237/4000] Validation [4/4] Loss: 0.33071 focal_loss 0.22031 dice_loss 0.11041 +Epoch [2237/4000] Validation metric {'Val/mean dice_metric': 0.9732751846313477, 'Val/mean miou_metric': 0.9572194814682007, 'Val/mean f1': 0.9757586717605591, 'Val/mean precision': 0.9723507165908813, 'Val/mean recall': 0.9791905879974365, 'Val/mean hd95_metric': 5.6845197677612305} +Cheakpoint... +Epoch [2237/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732751846313477, 'Val/mean miou_metric': 0.9572194814682007, 'Val/mean f1': 0.9757586717605591, 'Val/mean precision': 0.9723507165908813, 'Val/mean recall': 0.9791905879974365, 'Val/mean hd95_metric': 5.6845197677612305} +Epoch [2238/4000] Training [1/16] Loss: 0.00697 +Epoch [2238/4000] Training [2/16] Loss: 0.00581 +Epoch [2238/4000] Training [3/16] Loss: 0.00435 +Epoch [2238/4000] Training [4/16] Loss: 0.00585 +Epoch [2238/4000] Training [5/16] Loss: 0.00580 +Epoch [2238/4000] Training [6/16] Loss: 0.00410 +Epoch [2238/4000] Training [7/16] Loss: 0.00541 +Epoch [2238/4000] Training [8/16] Loss: 0.00445 +Epoch [2238/4000] Training [9/16] Loss: 0.00426 +Epoch [2238/4000] Training [10/16] Loss: 0.00494 +Epoch [2238/4000] Training [11/16] Loss: 0.00688 +Epoch [2238/4000] Training [12/16] Loss: 0.00404 +Epoch [2238/4000] Training [13/16] Loss: 0.00447 +Epoch [2238/4000] Training [14/16] Loss: 0.00574 +Epoch [2238/4000] Training [15/16] Loss: 0.00538 +Epoch [2238/4000] Training [16/16] Loss: 0.00528 +Epoch [2238/4000] Training metric {'Train/mean dice_metric': 0.996475100517273, 'Train/mean miou_metric': 0.9927141666412354, 'Train/mean f1': 0.9920535683631897, 'Train/mean precision': 0.9875187277793884, 'Train/mean recall': 0.9966302514076233, 'Train/mean hd95_metric': 1.027571439743042} +Epoch [2238/4000] Validation [1/4] Loss: 0.34841 focal_loss 0.28108 dice_loss 0.06733 +Epoch [2238/4000] Validation [2/4] Loss: 0.24692 focal_loss 0.15319 dice_loss 0.09373 +Epoch [2238/4000] Validation [3/4] Loss: 0.40251 focal_loss 0.31241 dice_loss 0.09010 +Epoch [2238/4000] Validation [4/4] Loss: 0.24537 focal_loss 0.16845 dice_loss 0.07692 +Epoch [2238/4000] Validation metric {'Val/mean dice_metric': 0.974024772644043, 'Val/mean miou_metric': 0.9580057263374329, 'Val/mean f1': 0.9748668074607849, 'Val/mean precision': 0.9706465601921082, 'Val/mean recall': 0.9791237711906433, 'Val/mean hd95_metric': 5.839418888092041} +Cheakpoint... +Epoch [2238/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974024772644043, 'Val/mean miou_metric': 0.9580057263374329, 'Val/mean f1': 0.9748668074607849, 'Val/mean precision': 0.9706465601921082, 'Val/mean recall': 0.9791237711906433, 'Val/mean hd95_metric': 5.839418888092041} +Epoch [2239/4000] Training [1/16] Loss: 0.00517 +Epoch [2239/4000] Training [2/16] Loss: 0.00537 +Epoch [2239/4000] Training [3/16] Loss: 0.00380 +Epoch [2239/4000] Training [4/16] Loss: 0.00402 +Epoch [2239/4000] Training [5/16] Loss: 0.00622 +Epoch [2239/4000] Training [6/16] Loss: 0.00749 +Epoch [2239/4000] Training [7/16] Loss: 0.00498 +Epoch [2239/4000] Training [8/16] Loss: 0.00407 +Epoch [2239/4000] Training [9/16] Loss: 0.00520 +Epoch [2239/4000] Training [10/16] Loss: 0.00685 +Epoch [2239/4000] Training [11/16] Loss: 0.00619 +Epoch [2239/4000] Training [12/16] Loss: 0.00522 +Epoch [2239/4000] Training [13/16] Loss: 0.00464 +Epoch [2239/4000] Training [14/16] Loss: 0.00724 +Epoch [2239/4000] Training [15/16] Loss: 0.00410 +Epoch [2239/4000] Training [16/16] Loss: 0.00496 +Epoch [2239/4000] Training metric {'Train/mean dice_metric': 0.9965347647666931, 'Train/mean miou_metric': 0.9928293824195862, 'Train/mean f1': 0.9920185804367065, 'Train/mean precision': 0.9874070286750793, 'Train/mean recall': 0.9966734051704407, 'Train/mean hd95_metric': 1.0320024490356445} +Epoch [2239/4000] Validation [1/4] Loss: 0.26904 focal_loss 0.20671 dice_loss 0.06233 +Epoch [2239/4000] Validation [2/4] Loss: 0.24982 focal_loss 0.14836 dice_loss 0.10146 +Epoch [2239/4000] Validation [3/4] Loss: 0.39291 focal_loss 0.29783 dice_loss 0.09509 +Epoch [2239/4000] Validation [4/4] Loss: 0.22082 focal_loss 0.13863 dice_loss 0.08219 +Epoch [2239/4000] Validation metric {'Val/mean dice_metric': 0.9734451174736023, 'Val/mean miou_metric': 0.9575873613357544, 'Val/mean f1': 0.9753137826919556, 'Val/mean precision': 0.9699751138687134, 'Val/mean recall': 0.9807115793228149, 'Val/mean hd95_metric': 5.688082695007324} +Cheakpoint... +Epoch [2239/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734451174736023, 'Val/mean miou_metric': 0.9575873613357544, 'Val/mean f1': 0.9753137826919556, 'Val/mean precision': 0.9699751138687134, 'Val/mean recall': 0.9807115793228149, 'Val/mean hd95_metric': 5.688082695007324} +Epoch [2240/4000] Training [1/16] Loss: 0.00867 +Epoch [2240/4000] Training [2/16] Loss: 0.00541 +Epoch [2240/4000] Training [3/16] Loss: 0.00464 +Epoch [2240/4000] Training [4/16] Loss: 0.00454 +Epoch [2240/4000] Training [5/16] Loss: 0.00558 +Epoch [2240/4000] Training [6/16] Loss: 0.00534 +Epoch [2240/4000] Training [7/16] Loss: 0.00601 +Epoch [2240/4000] Training [8/16] Loss: 0.00448 +Epoch [2240/4000] Training [9/16] Loss: 0.00611 +Epoch [2240/4000] Training [10/16] Loss: 0.00408 +Epoch [2240/4000] Training [11/16] Loss: 0.00468 +Epoch [2240/4000] Training [12/16] Loss: 0.00592 +Epoch [2240/4000] Training [13/16] Loss: 0.00611 +Epoch [2240/4000] Training [14/16] Loss: 0.00652 +Epoch [2240/4000] Training [15/16] Loss: 0.00488 +Epoch [2240/4000] Training [16/16] Loss: 0.00484 +Epoch [2240/4000] Training metric {'Train/mean dice_metric': 0.9964781999588013, 'Train/mean miou_metric': 0.992719292640686, 'Train/mean f1': 0.9921045899391174, 'Train/mean precision': 0.9876012206077576, 'Train/mean recall': 0.9966491460800171, 'Train/mean hd95_metric': 1.0001640319824219} +Epoch [2240/4000] Validation [1/4] Loss: 0.33397 focal_loss 0.26890 dice_loss 0.06506 +Epoch [2240/4000] Validation [2/4] Loss: 0.67574 focal_loss 0.49065 dice_loss 0.18509 +Epoch [2240/4000] Validation [3/4] Loss: 0.40390 focal_loss 0.31074 dice_loss 0.09316 +Epoch [2240/4000] Validation [4/4] Loss: 0.48185 focal_loss 0.33191 dice_loss 0.14994 +Epoch [2240/4000] Validation metric {'Val/mean dice_metric': 0.9713690876960754, 'Val/mean miou_metric': 0.9554241895675659, 'Val/mean f1': 0.9733368754386902, 'Val/mean precision': 0.9698666334152222, 'Val/mean recall': 0.9768319725990295, 'Val/mean hd95_metric': 6.192075729370117} +Cheakpoint... +Epoch [2240/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713690876960754, 'Val/mean miou_metric': 0.9554241895675659, 'Val/mean f1': 0.9733368754386902, 'Val/mean precision': 0.9698666334152222, 'Val/mean recall': 0.9768319725990295, 'Val/mean hd95_metric': 6.192075729370117} +Epoch [2241/4000] Training [1/16] Loss: 0.00916 +Epoch [2241/4000] Training [2/16] Loss: 0.00470 +Epoch [2241/4000] Training [3/16] Loss: 0.00509 +Epoch [2241/4000] Training [4/16] Loss: 0.00674 +Epoch [2241/4000] Training [5/16] Loss: 0.00621 +Epoch [2241/4000] Training [6/16] Loss: 0.00414 +Epoch [2241/4000] Training [7/16] Loss: 0.00605 +Epoch [2241/4000] Training [8/16] Loss: 0.00556 +Epoch [2241/4000] Training [9/16] Loss: 0.00461 +Epoch [2241/4000] Training [10/16] Loss: 0.00761 +Epoch [2241/4000] Training [11/16] Loss: 0.00549 +Epoch [2241/4000] Training [12/16] Loss: 0.00842 +Epoch [2241/4000] Training [13/16] Loss: 0.00673 +Epoch [2241/4000] Training [14/16] Loss: 0.00391 +Epoch [2241/4000] Training [15/16] Loss: 0.00541 +Epoch [2241/4000] Training [16/16] Loss: 0.00374 +Epoch [2241/4000] Training metric {'Train/mean dice_metric': 0.9963027238845825, 'Train/mean miou_metric': 0.9923678636550903, 'Train/mean f1': 0.9916337132453918, 'Train/mean precision': 0.9868687391281128, 'Train/mean recall': 0.9964450001716614, 'Train/mean hd95_metric': 1.087376594543457} +Epoch [2241/4000] Validation [1/4] Loss: 0.31604 focal_loss 0.25123 dice_loss 0.06481 +Epoch [2241/4000] Validation [2/4] Loss: 0.60664 focal_loss 0.42413 dice_loss 0.18251 +Epoch [2241/4000] Validation [3/4] Loss: 0.20294 focal_loss 0.13422 dice_loss 0.06872 +Epoch [2241/4000] Validation [4/4] Loss: 0.25707 focal_loss 0.17330 dice_loss 0.08377 +Epoch [2241/4000] Validation metric {'Val/mean dice_metric': 0.9735586047172546, 'Val/mean miou_metric': 0.9581681489944458, 'Val/mean f1': 0.9756850004196167, 'Val/mean precision': 0.9715116024017334, 'Val/mean recall': 0.9798944592475891, 'Val/mean hd95_metric': 5.605533123016357} +Cheakpoint... +Epoch [2241/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735586047172546, 'Val/mean miou_metric': 0.9581681489944458, 'Val/mean f1': 0.9756850004196167, 'Val/mean precision': 0.9715116024017334, 'Val/mean recall': 0.9798944592475891, 'Val/mean hd95_metric': 5.605533123016357} +Epoch [2242/4000] Training [1/16] Loss: 0.00433 +Epoch [2242/4000] Training [2/16] Loss: 0.00791 +Epoch [2242/4000] Training [3/16] Loss: 0.00495 +Epoch [2242/4000] Training [4/16] Loss: 0.00682 +Epoch [2242/4000] Training [5/16] Loss: 0.00428 +Epoch [2242/4000] Training [6/16] Loss: 0.00493 +Epoch [2242/4000] Training [7/16] Loss: 0.00376 +Epoch [2242/4000] Training [8/16] Loss: 0.00449 +Epoch [2242/4000] Training [9/16] Loss: 0.00484 +Epoch [2242/4000] Training [10/16] Loss: 0.00978 +Epoch [2242/4000] Training [11/16] Loss: 0.00447 +Epoch [2242/4000] Training [12/16] Loss: 0.00417 +Epoch [2242/4000] Training [13/16] Loss: 0.00405 +Epoch [2242/4000] Training [14/16] Loss: 0.00528 +Epoch [2242/4000] Training [15/16] Loss: 0.00568 +Epoch [2242/4000] Training [16/16] Loss: 0.00456 +Epoch [2242/4000] Training metric {'Train/mean dice_metric': 0.9967797994613647, 'Train/mean miou_metric': 0.9933127164840698, 'Train/mean f1': 0.992221474647522, 'Train/mean precision': 0.9876296520233154, 'Train/mean recall': 0.9968562126159668, 'Train/mean hd95_metric': 1.02919602394104} +Epoch [2242/4000] Validation [1/4] Loss: 0.36791 focal_loss 0.29357 dice_loss 0.07434 +Epoch [2242/4000] Validation [2/4] Loss: 0.21476 focal_loss 0.13341 dice_loss 0.08135 +Epoch [2242/4000] Validation [3/4] Loss: 0.31580 focal_loss 0.22202 dice_loss 0.09378 +Epoch [2242/4000] Validation [4/4] Loss: 0.25439 focal_loss 0.15646 dice_loss 0.09793 +Epoch [2242/4000] Validation metric {'Val/mean dice_metric': 0.9730037450790405, 'Val/mean miou_metric': 0.9569042325019836, 'Val/mean f1': 0.9741989374160767, 'Val/mean precision': 0.9712098836898804, 'Val/mean recall': 0.9772065877914429, 'Val/mean hd95_metric': 5.9553303718566895} +Cheakpoint... +Epoch [2242/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730037450790405, 'Val/mean miou_metric': 0.9569042325019836, 'Val/mean f1': 0.9741989374160767, 'Val/mean precision': 0.9712098836898804, 'Val/mean recall': 0.9772065877914429, 'Val/mean hd95_metric': 5.9553303718566895} +Epoch [2243/4000] Training [1/16] Loss: 0.00477 +Epoch [2243/4000] Training [2/16] Loss: 0.00658 +Epoch [2243/4000] Training [3/16] Loss: 0.00422 +Epoch [2243/4000] Training [4/16] Loss: 0.00414 +Epoch [2243/4000] Training [5/16] Loss: 0.00620 +Epoch [2243/4000] Training [6/16] Loss: 0.00351 +Epoch [2243/4000] Training [7/16] Loss: 0.00624 +Epoch [2243/4000] Training [8/16] Loss: 0.00494 +Epoch [2243/4000] Training [9/16] Loss: 0.00650 +Epoch [2243/4000] Training [10/16] Loss: 0.00433 +Epoch [2243/4000] Training [11/16] Loss: 0.00488 +Epoch [2243/4000] Training [12/16] Loss: 0.00547 +Epoch [2243/4000] Training [13/16] Loss: 0.00457 +Epoch [2243/4000] Training [14/16] Loss: 0.00520 +Epoch [2243/4000] Training [15/16] Loss: 0.00419 +Epoch [2243/4000] Training [16/16] Loss: 0.00509 +Epoch [2243/4000] Training metric {'Train/mean dice_metric': 0.996788501739502, 'Train/mean miou_metric': 0.9933315515518188, 'Train/mean f1': 0.992233395576477, 'Train/mean precision': 0.9876259565353394, 'Train/mean recall': 0.9968839883804321, 'Train/mean hd95_metric': 0.9813888072967529} +Epoch [2243/4000] Validation [1/4] Loss: 0.35547 focal_loss 0.28296 dice_loss 0.07251 +Epoch [2243/4000] Validation [2/4] Loss: 0.32764 focal_loss 0.21090 dice_loss 0.11674 +Epoch [2243/4000] Validation [3/4] Loss: 0.42243 focal_loss 0.33182 dice_loss 0.09061 +Epoch [2243/4000] Validation [4/4] Loss: 0.22910 focal_loss 0.14815 dice_loss 0.08095 +Epoch [2243/4000] Validation metric {'Val/mean dice_metric': 0.9754934310913086, 'Val/mean miou_metric': 0.9593329429626465, 'Val/mean f1': 0.975053071975708, 'Val/mean precision': 0.9725708365440369, 'Val/mean recall': 0.9775481224060059, 'Val/mean hd95_metric': 6.138239860534668} +Cheakpoint... +Epoch [2243/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754934310913086, 'Val/mean miou_metric': 0.9593329429626465, 'Val/mean f1': 0.975053071975708, 'Val/mean precision': 0.9725708365440369, 'Val/mean recall': 0.9775481224060059, 'Val/mean hd95_metric': 6.138239860534668} +Epoch [2244/4000] Training [1/16] Loss: 0.00506 +Epoch [2244/4000] Training [2/16] Loss: 0.00499 +Epoch [2244/4000] Training [3/16] Loss: 0.00541 +Epoch [2244/4000] Training [4/16] Loss: 0.00562 +Epoch [2244/4000] Training [5/16] Loss: 0.00536 +Epoch [2244/4000] Training [6/16] Loss: 0.00515 +Epoch [2244/4000] Training [7/16] Loss: 0.00623 +Epoch [2244/4000] Training [8/16] Loss: 0.00419 +Epoch [2244/4000] Training [9/16] Loss: 0.00588 +Epoch [2244/4000] Training [10/16] Loss: 0.00568 +Epoch [2244/4000] Training [11/16] Loss: 0.00585 +Epoch [2244/4000] Training [12/16] Loss: 0.00385 +Epoch [2244/4000] Training [13/16] Loss: 0.00420 +Epoch [2244/4000] Training [14/16] Loss: 0.00707 +Epoch [2244/4000] Training [15/16] Loss: 0.00553 +Epoch [2244/4000] Training [16/16] Loss: 0.00427 +Epoch [2244/4000] Training metric {'Train/mean dice_metric': 0.9966869950294495, 'Train/mean miou_metric': 0.9931274056434631, 'Train/mean f1': 0.9922106266021729, 'Train/mean precision': 0.9877241849899292, 'Train/mean recall': 0.9967380166053772, 'Train/mean hd95_metric': 1.027901530265808} +Epoch [2244/4000] Validation [1/4] Loss: 0.29093 focal_loss 0.22933 dice_loss 0.06160 +Epoch [2244/4000] Validation [2/4] Loss: 0.20141 focal_loss 0.12410 dice_loss 0.07731 +Epoch [2244/4000] Validation [3/4] Loss: 0.41737 focal_loss 0.32667 dice_loss 0.09070 +Epoch [2244/4000] Validation [4/4] Loss: 0.32440 focal_loss 0.22374 dice_loss 0.10065 +Epoch [2244/4000] Validation metric {'Val/mean dice_metric': 0.9746208190917969, 'Val/mean miou_metric': 0.9585955739021301, 'Val/mean f1': 0.974344789981842, 'Val/mean precision': 0.9701477885246277, 'Val/mean recall': 0.9785783886909485, 'Val/mean hd95_metric': 5.898634910583496} +Cheakpoint... +Epoch [2244/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746208190917969, 'Val/mean miou_metric': 0.9585955739021301, 'Val/mean f1': 0.974344789981842, 'Val/mean precision': 0.9701477885246277, 'Val/mean recall': 0.9785783886909485, 'Val/mean hd95_metric': 5.898634910583496} +Epoch [2245/4000] Training [1/16] Loss: 0.00560 +Epoch [2245/4000] Training [2/16] Loss: 0.00536 +Epoch [2245/4000] Training [3/16] Loss: 0.00572 +Epoch [2245/4000] Training [4/16] Loss: 0.00569 +Epoch [2245/4000] Training [5/16] Loss: 0.00510 +Epoch [2245/4000] Training [6/16] Loss: 0.00464 +Epoch [2245/4000] Training [7/16] Loss: 0.01006 +Epoch [2245/4000] Training [8/16] Loss: 0.00395 +Epoch [2245/4000] Training [9/16] Loss: 0.00546 +Epoch [2245/4000] Training [10/16] Loss: 0.00415 +Epoch [2245/4000] Training [11/16] Loss: 0.00485 +Epoch [2245/4000] Training [12/16] Loss: 0.00545 +Epoch [2245/4000] Training [13/16] Loss: 0.00583 +Epoch [2245/4000] Training [14/16] Loss: 0.00443 +Epoch [2245/4000] Training [15/16] Loss: 0.00694 +Epoch [2245/4000] Training [16/16] Loss: 0.00457 +Epoch [2245/4000] Training metric {'Train/mean dice_metric': 0.9966168403625488, 'Train/mean miou_metric': 0.9929919838905334, 'Train/mean f1': 0.9921692609786987, 'Train/mean precision': 0.9876591563224792, 'Train/mean recall': 0.9967207312583923, 'Train/mean hd95_metric': 1.0047707557678223} +Epoch [2245/4000] Validation [1/4] Loss: 0.30619 focal_loss 0.24266 dice_loss 0.06354 +Epoch [2245/4000] Validation [2/4] Loss: 0.29772 focal_loss 0.18726 dice_loss 0.11047 +Epoch [2245/4000] Validation [3/4] Loss: 0.44347 focal_loss 0.34787 dice_loss 0.09559 +Epoch [2245/4000] Validation [4/4] Loss: 0.31761 focal_loss 0.21841 dice_loss 0.09920 +Epoch [2245/4000] Validation metric {'Val/mean dice_metric': 0.9742637872695923, 'Val/mean miou_metric': 0.958155632019043, 'Val/mean f1': 0.9744356274604797, 'Val/mean precision': 0.9699159264564514, 'Val/mean recall': 0.9789976477622986, 'Val/mean hd95_metric': 6.003110408782959} +Cheakpoint... +Epoch [2245/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742637872695923, 'Val/mean miou_metric': 0.958155632019043, 'Val/mean f1': 0.9744356274604797, 'Val/mean precision': 0.9699159264564514, 'Val/mean recall': 0.9789976477622986, 'Val/mean hd95_metric': 6.003110408782959} +Epoch [2246/4000] Training [1/16] Loss: 0.00548 +Epoch [2246/4000] Training [2/16] Loss: 0.00622 +Epoch [2246/4000] Training [3/16] Loss: 0.00540 +Epoch [2246/4000] Training [4/16] Loss: 0.00456 +Epoch [2246/4000] Training [5/16] Loss: 0.00432 +Epoch [2246/4000] Training [6/16] Loss: 0.00534 +Epoch [2246/4000] Training [7/16] Loss: 0.00572 +Epoch [2246/4000] Training [8/16] Loss: 0.00393 +Epoch [2246/4000] Training [9/16] Loss: 0.00411 +Epoch [2246/4000] Training [10/16] Loss: 0.00448 +Epoch [2246/4000] Training [11/16] Loss: 0.00596 +Epoch [2246/4000] Training [12/16] Loss: 0.00579 +Epoch [2246/4000] Training [13/16] Loss: 0.00356 +Epoch [2246/4000] Training [14/16] Loss: 0.00635 +Epoch [2246/4000] Training [15/16] Loss: 0.00457 +Epoch [2246/4000] Training [16/16] Loss: 0.00339 +Epoch [2246/4000] Training metric {'Train/mean dice_metric': 0.9965251088142395, 'Train/mean miou_metric': 0.9928106069564819, 'Train/mean f1': 0.9920893311500549, 'Train/mean precision': 0.9874259233474731, 'Train/mean recall': 0.9967969655990601, 'Train/mean hd95_metric': 1.1972066164016724} +Epoch [2246/4000] Validation [1/4] Loss: 0.35901 focal_loss 0.28709 dice_loss 0.07192 +Epoch [2246/4000] Validation [2/4] Loss: 0.34043 focal_loss 0.21810 dice_loss 0.12233 +Epoch [2246/4000] Validation [3/4] Loss: 0.22345 focal_loss 0.15700 dice_loss 0.06645 +Epoch [2246/4000] Validation [4/4] Loss: 0.32139 focal_loss 0.21804 dice_loss 0.10335 +Epoch [2246/4000] Validation metric {'Val/mean dice_metric': 0.9737607836723328, 'Val/mean miou_metric': 0.9572615623474121, 'Val/mean f1': 0.9746843576431274, 'Val/mean precision': 0.9719326496124268, 'Val/mean recall': 0.977451503276825, 'Val/mean hd95_metric': 5.702110767364502} +Cheakpoint... +Epoch [2246/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737607836723328, 'Val/mean miou_metric': 0.9572615623474121, 'Val/mean f1': 0.9746843576431274, 'Val/mean precision': 0.9719326496124268, 'Val/mean recall': 0.977451503276825, 'Val/mean hd95_metric': 5.702110767364502} +Epoch [2247/4000] Training [1/16] Loss: 0.00381 +Epoch [2247/4000] Training [2/16] Loss: 0.00414 +Epoch [2247/4000] Training [3/16] Loss: 0.00419 +Epoch [2247/4000] Training [4/16] Loss: 0.00465 +Epoch [2247/4000] Training [5/16] Loss: 0.00513 +Epoch [2247/4000] Training [6/16] Loss: 0.00416 +Epoch [2247/4000] Training [7/16] Loss: 0.00356 +Epoch [2247/4000] Training [8/16] Loss: 0.00466 +Epoch [2247/4000] Training [9/16] Loss: 0.00354 +Epoch [2247/4000] Training [10/16] Loss: 0.00632 +Epoch [2247/4000] Training [11/16] Loss: 0.00528 +Epoch [2247/4000] Training [12/16] Loss: 0.00386 +Epoch [2247/4000] Training [13/16] Loss: 0.00667 +Epoch [2247/4000] Training [14/16] Loss: 0.00528 +Epoch [2247/4000] Training [15/16] Loss: 0.00594 +Epoch [2247/4000] Training [16/16] Loss: 0.00469 +Epoch [2247/4000] Training metric {'Train/mean dice_metric': 0.9968385696411133, 'Train/mean miou_metric': 0.9933673143386841, 'Train/mean f1': 0.990950345993042, 'Train/mean precision': 0.9851512312889099, 'Train/mean recall': 0.9968181848526001, 'Train/mean hd95_metric': 0.9911959171295166} +Epoch [2247/4000] Validation [1/4] Loss: 0.42537 focal_loss 0.31376 dice_loss 0.11161 +Epoch [2247/4000] Validation [2/4] Loss: 0.61820 focal_loss 0.43287 dice_loss 0.18532 +Epoch [2247/4000] Validation [3/4] Loss: 0.38241 focal_loss 0.29271 dice_loss 0.08969 +Epoch [2247/4000] Validation [4/4] Loss: 0.23697 focal_loss 0.15790 dice_loss 0.07907 +Epoch [2247/4000] Validation metric {'Val/mean dice_metric': 0.9712556600570679, 'Val/mean miou_metric': 0.9559625387191772, 'Val/mean f1': 0.9731427431106567, 'Val/mean precision': 0.9706706404685974, 'Val/mean recall': 0.9756274223327637, 'Val/mean hd95_metric': 5.734172344207764} +Cheakpoint... +Epoch [2247/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712556600570679, 'Val/mean miou_metric': 0.9559625387191772, 'Val/mean f1': 0.9731427431106567, 'Val/mean precision': 0.9706706404685974, 'Val/mean recall': 0.9756274223327637, 'Val/mean hd95_metric': 5.734172344207764} +Epoch [2248/4000] Training [1/16] Loss: 0.00502 +Epoch [2248/4000] Training [2/16] Loss: 0.00474 +Epoch [2248/4000] Training [3/16] Loss: 0.00591 +Epoch [2248/4000] Training [4/16] Loss: 0.00633 +Epoch [2248/4000] Training [5/16] Loss: 0.00458 +Epoch [2248/4000] Training [6/16] Loss: 0.00434 +Epoch [2248/4000] Training [7/16] Loss: 0.00573 +Epoch [2248/4000] Training [8/16] Loss: 0.00446 +Epoch [2248/4000] Training [9/16] Loss: 0.00367 +Epoch [2248/4000] Training [10/16] Loss: 0.00500 +Epoch [2248/4000] Training [11/16] Loss: 0.00543 +Epoch [2248/4000] Training [12/16] Loss: 0.00689 +Epoch [2248/4000] Training [13/16] Loss: 0.00488 +Epoch [2248/4000] Training [14/16] Loss: 0.00499 +Epoch [2248/4000] Training [15/16] Loss: 0.00615 +Epoch [2248/4000] Training [16/16] Loss: 0.00531 +Epoch [2248/4000] Training metric {'Train/mean dice_metric': 0.9964441657066345, 'Train/mean miou_metric': 0.9926501512527466, 'Train/mean f1': 0.9920340776443481, 'Train/mean precision': 0.987419068813324, 'Train/mean recall': 0.9966924786567688, 'Train/mean hd95_metric': 0.9980013370513916} +Epoch [2248/4000] Validation [1/4] Loss: 0.31312 focal_loss 0.24241 dice_loss 0.07072 +Epoch [2248/4000] Validation [2/4] Loss: 0.47062 focal_loss 0.29569 dice_loss 0.17493 +Epoch [2248/4000] Validation [3/4] Loss: 0.41901 focal_loss 0.32336 dice_loss 0.09565 +Epoch [2248/4000] Validation [4/4] Loss: 0.24701 focal_loss 0.15646 dice_loss 0.09055 +Epoch [2248/4000] Validation metric {'Val/mean dice_metric': 0.9709420204162598, 'Val/mean miou_metric': 0.9547564387321472, 'Val/mean f1': 0.973964512348175, 'Val/mean precision': 0.9725379347801208, 'Val/mean recall': 0.9753953814506531, 'Val/mean hd95_metric': 5.363447189331055} +Cheakpoint... +Epoch [2248/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709420204162598, 'Val/mean miou_metric': 0.9547564387321472, 'Val/mean f1': 0.973964512348175, 'Val/mean precision': 0.9725379347801208, 'Val/mean recall': 0.9753953814506531, 'Val/mean hd95_metric': 5.363447189331055} +Epoch [2249/4000] Training [1/16] Loss: 0.00518 +Epoch [2249/4000] Training [2/16] Loss: 0.00345 +Epoch [2249/4000] Training [3/16] Loss: 0.00474 +Epoch [2249/4000] Training [4/16] Loss: 0.00499 +Epoch [2249/4000] Training [5/16] Loss: 0.00645 +Epoch [2249/4000] Training [6/16] Loss: 0.00582 +Epoch [2249/4000] Training [7/16] Loss: 0.00479 +Epoch [2249/4000] Training [8/16] Loss: 0.00448 +Epoch [2249/4000] Training [9/16] Loss: 0.00603 +Epoch [2249/4000] Training [10/16] Loss: 0.00530 +Epoch [2249/4000] Training [11/16] Loss: 0.00409 +Epoch [2249/4000] Training [12/16] Loss: 0.00465 +Epoch [2249/4000] Training [13/16] Loss: 0.00684 +Epoch [2249/4000] Training [14/16] Loss: 0.00550 +Epoch [2249/4000] Training [15/16] Loss: 0.00339 +Epoch [2249/4000] Training [16/16] Loss: 0.00450 +Epoch [2249/4000] Training metric {'Train/mean dice_metric': 0.9966930150985718, 'Train/mean miou_metric': 0.993125855922699, 'Train/mean f1': 0.9920176863670349, 'Train/mean precision': 0.987339973449707, 'Train/mean recall': 0.9967399835586548, 'Train/mean hd95_metric': 0.9847512245178223} +Epoch [2249/4000] Validation [1/4] Loss: 0.38325 focal_loss 0.29256 dice_loss 0.09069 +Epoch [2249/4000] Validation [2/4] Loss: 0.29519 focal_loss 0.18686 dice_loss 0.10833 +Epoch [2249/4000] Validation [3/4] Loss: 0.25223 focal_loss 0.16328 dice_loss 0.08896 +Epoch [2249/4000] Validation [4/4] Loss: 0.33620 focal_loss 0.22547 dice_loss 0.11072 +Epoch [2249/4000] Validation metric {'Val/mean dice_metric': 0.9730022549629211, 'Val/mean miou_metric': 0.9569160342216492, 'Val/mean f1': 0.9749398231506348, 'Val/mean precision': 0.9724127650260925, 'Val/mean recall': 0.9774799942970276, 'Val/mean hd95_metric': 5.295703887939453} +Cheakpoint... +Epoch [2249/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730022549629211, 'Val/mean miou_metric': 0.9569160342216492, 'Val/mean f1': 0.9749398231506348, 'Val/mean precision': 0.9724127650260925, 'Val/mean recall': 0.9774799942970276, 'Val/mean hd95_metric': 5.295703887939453} +Epoch [2250/4000] Training [1/16] Loss: 0.00366 +Epoch [2250/4000] Training [2/16] Loss: 0.00597 +Epoch [2250/4000] Training [3/16] Loss: 0.00551 +Epoch [2250/4000] Training [4/16] Loss: 0.00663 +Epoch [2250/4000] Training [5/16] Loss: 0.00491 +Epoch [2250/4000] Training [6/16] Loss: 0.00481 +Epoch [2250/4000] Training [7/16] Loss: 0.00510 +Epoch [2250/4000] Training [8/16] Loss: 0.00439 +Epoch [2250/4000] Training [9/16] Loss: 0.00454 +Epoch [2250/4000] Training [10/16] Loss: 0.00574 +Epoch [2250/4000] Training [11/16] Loss: 0.00508 +Epoch [2250/4000] Training [12/16] Loss: 0.00340 +Epoch [2250/4000] Training [13/16] Loss: 0.00814 +Epoch [2250/4000] Training [14/16] Loss: 0.00850 +Epoch [2250/4000] Training [15/16] Loss: 0.00574 +Epoch [2250/4000] Training [16/16] Loss: 0.00505 +Epoch [2250/4000] Training metric {'Train/mean dice_metric': 0.9964950084686279, 'Train/mean miou_metric': 0.9927526712417603, 'Train/mean f1': 0.9919853210449219, 'Train/mean precision': 0.9871917963027954, 'Train/mean recall': 0.9968256950378418, 'Train/mean hd95_metric': 1.0339957475662231} +Epoch [2250/4000] Validation [1/4] Loss: 0.28480 focal_loss 0.22374 dice_loss 0.06106 +Epoch [2250/4000] Validation [2/4] Loss: 0.76866 focal_loss 0.58381 dice_loss 0.18485 +Epoch [2250/4000] Validation [3/4] Loss: 0.18538 focal_loss 0.13085 dice_loss 0.05453 +Epoch [2250/4000] Validation [4/4] Loss: 0.34333 focal_loss 0.23182 dice_loss 0.11151 +Epoch [2250/4000] Validation metric {'Val/mean dice_metric': 0.9729150533676147, 'Val/mean miou_metric': 0.9571483731269836, 'Val/mean f1': 0.974596381187439, 'Val/mean precision': 0.9732811450958252, 'Val/mean recall': 0.9759150147438049, 'Val/mean hd95_metric': 5.216814994812012} +Cheakpoint... +Epoch [2250/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729150533676147, 'Val/mean miou_metric': 0.9571483731269836, 'Val/mean f1': 0.974596381187439, 'Val/mean precision': 0.9732811450958252, 'Val/mean recall': 0.9759150147438049, 'Val/mean hd95_metric': 5.216814994812012} +Epoch [2251/4000] Training [1/16] Loss: 0.00334 +Epoch [2251/4000] Training [2/16] Loss: 0.00461 +Epoch [2251/4000] Training [3/16] Loss: 0.00563 +Epoch [2251/4000] Training [4/16] Loss: 0.00401 +Epoch [2251/4000] Training [5/16] Loss: 0.00683 +Epoch [2251/4000] Training [6/16] Loss: 0.00508 +Epoch [2251/4000] Training [7/16] Loss: 0.00610 +Epoch [2251/4000] Training [8/16] Loss: 0.00602 +Epoch [2251/4000] Training [9/16] Loss: 0.00429 +Epoch [2251/4000] Training [10/16] Loss: 0.00567 +Epoch [2251/4000] Training [11/16] Loss: 0.00572 +Epoch [2251/4000] Training [12/16] Loss: 0.00399 +Epoch [2251/4000] Training [13/16] Loss: 0.00477 +Epoch [2251/4000] Training [14/16] Loss: 0.00526 +Epoch [2251/4000] Training [15/16] Loss: 0.00363 +Epoch [2251/4000] Training [16/16] Loss: 0.00442 +Epoch [2251/4000] Training metric {'Train/mean dice_metric': 0.9967786073684692, 'Train/mean miou_metric': 0.9933124780654907, 'Train/mean f1': 0.9923690557479858, 'Train/mean precision': 0.9878493547439575, 'Train/mean recall': 0.9969303607940674, 'Train/mean hd95_metric': 0.9869830012321472} +Epoch [2251/4000] Validation [1/4] Loss: 0.28821 focal_loss 0.22646 dice_loss 0.06175 +Epoch [2251/4000] Validation [2/4] Loss: 0.30574 focal_loss 0.18844 dice_loss 0.11730 +Epoch [2251/4000] Validation [3/4] Loss: 0.24631 focal_loss 0.18077 dice_loss 0.06553 +Epoch [2251/4000] Validation [4/4] Loss: 0.44473 focal_loss 0.32304 dice_loss 0.12169 +Epoch [2251/4000] Validation metric {'Val/mean dice_metric': 0.9737650156021118, 'Val/mean miou_metric': 0.9577957987785339, 'Val/mean f1': 0.9752892851829529, 'Val/mean precision': 0.9729577302932739, 'Val/mean recall': 0.9776320457458496, 'Val/mean hd95_metric': 4.831060886383057} +Cheakpoint... +Epoch [2251/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737650156021118, 'Val/mean miou_metric': 0.9577957987785339, 'Val/mean f1': 0.9752892851829529, 'Val/mean precision': 0.9729577302932739, 'Val/mean recall': 0.9776320457458496, 'Val/mean hd95_metric': 4.831060886383057} +Epoch [2252/4000] Training [1/16] Loss: 0.00474 +Epoch [2252/4000] Training [2/16] Loss: 0.00470 +Epoch [2252/4000] Training [3/16] Loss: 0.00807 +Epoch [2252/4000] Training [4/16] Loss: 0.00368 +Epoch [2252/4000] Training [5/16] Loss: 0.00409 +Epoch [2252/4000] Training [6/16] Loss: 0.00458 +Epoch [2252/4000] Training [7/16] Loss: 0.00541 +Epoch [2252/4000] Training [8/16] Loss: 0.00492 +Epoch [2252/4000] Training [9/16] Loss: 0.00505 +Epoch [2252/4000] Training [10/16] Loss: 0.00406 +Epoch [2252/4000] Training [11/16] Loss: 0.00376 +Epoch [2252/4000] Training [12/16] Loss: 0.00541 +Epoch [2252/4000] Training [13/16] Loss: 0.00469 +Epoch [2252/4000] Training [14/16] Loss: 0.00689 +Epoch [2252/4000] Training [15/16] Loss: 0.00500 +Epoch [2252/4000] Training [16/16] Loss: 0.00488 +Epoch [2252/4000] Training metric {'Train/mean dice_metric': 0.9967108964920044, 'Train/mean miou_metric': 0.993137001991272, 'Train/mean f1': 0.9914512634277344, 'Train/mean precision': 0.9862281084060669, 'Train/mean recall': 0.9967299699783325, 'Train/mean hd95_metric': 0.9906661510467529} +Epoch [2252/4000] Validation [1/4] Loss: 0.28683 focal_loss 0.22170 dice_loss 0.06513 +Epoch [2252/4000] Validation [2/4] Loss: 0.66536 focal_loss 0.46261 dice_loss 0.20275 +Epoch [2252/4000] Validation [3/4] Loss: 0.37498 focal_loss 0.28686 dice_loss 0.08812 +Epoch [2252/4000] Validation [4/4] Loss: 0.42148 focal_loss 0.29908 dice_loss 0.12240 +Epoch [2252/4000] Validation metric {'Val/mean dice_metric': 0.9704698324203491, 'Val/mean miou_metric': 0.9547489881515503, 'Val/mean f1': 0.9742901921272278, 'Val/mean precision': 0.9716429114341736, 'Val/mean recall': 0.976952075958252, 'Val/mean hd95_metric': 5.642871856689453} +Cheakpoint... +Epoch [2252/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704698324203491, 'Val/mean miou_metric': 0.9547489881515503, 'Val/mean f1': 0.9742901921272278, 'Val/mean precision': 0.9716429114341736, 'Val/mean recall': 0.976952075958252, 'Val/mean hd95_metric': 5.642871856689453} +Epoch [2253/4000] Training [1/16] Loss: 0.00529 +Epoch [2253/4000] Training [2/16] Loss: 0.00598 +Epoch [2253/4000] Training [3/16] Loss: 0.00538 +Epoch [2253/4000] Training [4/16] Loss: 0.00443 +Epoch [2253/4000] Training [5/16] Loss: 0.01062 +Epoch [2253/4000] Training [6/16] Loss: 0.00633 +Epoch [2253/4000] Training [7/16] Loss: 0.00423 +Epoch [2253/4000] Training [8/16] Loss: 0.00488 +Epoch [2253/4000] Training [9/16] Loss: 0.00335 +Epoch [2253/4000] Training [10/16] Loss: 0.00460 +Epoch [2253/4000] Training [11/16] Loss: 0.00539 +Epoch [2253/4000] Training [12/16] Loss: 0.00538 +Epoch [2253/4000] Training [13/16] Loss: 0.00663 +Epoch [2253/4000] Training [14/16] Loss: 0.00585 +Epoch [2253/4000] Training [15/16] Loss: 0.00524 +Epoch [2253/4000] Training [16/16] Loss: 0.00706 +Epoch [2253/4000] Training metric {'Train/mean dice_metric': 0.9964885711669922, 'Train/mean miou_metric': 0.9927499890327454, 'Train/mean f1': 0.9921743869781494, 'Train/mean precision': 0.9875938296318054, 'Train/mean recall': 0.9967978596687317, 'Train/mean hd95_metric': 1.0621522665023804} +Epoch [2253/4000] Validation [1/4] Loss: 0.26276 focal_loss 0.20066 dice_loss 0.06209 +Epoch [2253/4000] Validation [2/4] Loss: 0.35793 focal_loss 0.22509 dice_loss 0.13284 +Epoch [2253/4000] Validation [3/4] Loss: 0.19428 focal_loss 0.13194 dice_loss 0.06234 +Epoch [2253/4000] Validation [4/4] Loss: 0.36238 focal_loss 0.24005 dice_loss 0.12233 +Epoch [2253/4000] Validation metric {'Val/mean dice_metric': 0.9713643789291382, 'Val/mean miou_metric': 0.955974280834198, 'Val/mean f1': 0.9751296639442444, 'Val/mean precision': 0.9721541404724121, 'Val/mean recall': 0.9781234860420227, 'Val/mean hd95_metric': 5.729331016540527} +Cheakpoint... +Epoch [2253/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713643789291382, 'Val/mean miou_metric': 0.955974280834198, 'Val/mean f1': 0.9751296639442444, 'Val/mean precision': 0.9721541404724121, 'Val/mean recall': 0.9781234860420227, 'Val/mean hd95_metric': 5.729331016540527} +Epoch [2254/4000] Training [1/16] Loss: 0.00432 +Epoch [2254/4000] Training [2/16] Loss: 0.00423 +Epoch [2254/4000] Training [3/16] Loss: 0.00480 +Epoch [2254/4000] Training [4/16] Loss: 0.00539 +Epoch [2254/4000] Training [5/16] Loss: 0.00803 +Epoch [2254/4000] Training [6/16] Loss: 0.00786 +Epoch [2254/4000] Training [7/16] Loss: 0.00670 +Epoch [2254/4000] Training [8/16] Loss: 0.00392 +Epoch [2254/4000] Training [9/16] Loss: 0.00387 +Epoch [2254/4000] Training [10/16] Loss: 0.00509 +Epoch [2254/4000] Training [11/16] Loss: 0.00438 +Epoch [2254/4000] Training [12/16] Loss: 0.00558 +Epoch [2254/4000] Training [13/16] Loss: 0.00410 +Epoch [2254/4000] Training [14/16] Loss: 0.00482 +Epoch [2254/4000] Training [15/16] Loss: 0.00519 +Epoch [2254/4000] Training [16/16] Loss: 0.00408 +Epoch [2254/4000] Training metric {'Train/mean dice_metric': 0.9966747760772705, 'Train/mean miou_metric': 0.9931122064590454, 'Train/mean f1': 0.992348313331604, 'Train/mean precision': 0.9879062175750732, 'Train/mean recall': 0.9968305230140686, 'Train/mean hd95_metric': 0.9936800599098206} +Epoch [2254/4000] Validation [1/4] Loss: 0.30728 focal_loss 0.24417 dice_loss 0.06312 +Epoch [2254/4000] Validation [2/4] Loss: 0.38470 focal_loss 0.24773 dice_loss 0.13696 +Epoch [2254/4000] Validation [3/4] Loss: 0.39231 focal_loss 0.29893 dice_loss 0.09338 +Epoch [2254/4000] Validation [4/4] Loss: 0.30172 focal_loss 0.20480 dice_loss 0.09692 +Epoch [2254/4000] Validation metric {'Val/mean dice_metric': 0.9745254516601562, 'Val/mean miou_metric': 0.9585152864456177, 'Val/mean f1': 0.9746873378753662, 'Val/mean precision': 0.9703765511512756, 'Val/mean recall': 0.9790363907814026, 'Val/mean hd95_metric': 5.598267555236816} +Cheakpoint... +Epoch [2254/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745254516601562, 'Val/mean miou_metric': 0.9585152864456177, 'Val/mean f1': 0.9746873378753662, 'Val/mean precision': 0.9703765511512756, 'Val/mean recall': 0.9790363907814026, 'Val/mean hd95_metric': 5.598267555236816} +Epoch [2255/4000] Training [1/16] Loss: 0.00490 +Epoch [2255/4000] Training [2/16] Loss: 0.00852 +Epoch [2255/4000] Training [3/16] Loss: 0.00567 +Epoch [2255/4000] Training [4/16] Loss: 0.00495 +Epoch [2255/4000] Training [5/16] Loss: 0.00468 +Epoch [2255/4000] Training [6/16] Loss: 0.00558 +Epoch [2255/4000] Training [7/16] Loss: 0.00451 +Epoch [2255/4000] Training [8/16] Loss: 0.00405 +Epoch [2255/4000] Training [9/16] Loss: 0.00431 +Epoch [2255/4000] Training [10/16] Loss: 0.00437 +Epoch [2255/4000] Training [11/16] Loss: 0.00547 +Epoch [2255/4000] Training [12/16] Loss: 0.00571 +Epoch [2255/4000] Training [13/16] Loss: 0.00545 +Epoch [2255/4000] Training [14/16] Loss: 0.00671 +Epoch [2255/4000] Training [15/16] Loss: 0.00582 +Epoch [2255/4000] Training [16/16] Loss: 0.00552 +Epoch [2255/4000] Training metric {'Train/mean dice_metric': 0.9966577291488647, 'Train/mean miou_metric': 0.9930739998817444, 'Train/mean f1': 0.9921709895133972, 'Train/mean precision': 0.9877110123634338, 'Train/mean recall': 0.9966714978218079, 'Train/mean hd95_metric': 1.0250229835510254} +Epoch [2255/4000] Validation [1/4] Loss: 0.27982 focal_loss 0.22075 dice_loss 0.05906 +Epoch [2255/4000] Validation [2/4] Loss: 0.32370 focal_loss 0.20778 dice_loss 0.11592 +Epoch [2255/4000] Validation [3/4] Loss: 0.58165 focal_loss 0.46361 dice_loss 0.11804 +Epoch [2255/4000] Validation [4/4] Loss: 0.63332 focal_loss 0.50107 dice_loss 0.13224 +Epoch [2255/4000] Validation metric {'Val/mean dice_metric': 0.973515510559082, 'Val/mean miou_metric': 0.9572361707687378, 'Val/mean f1': 0.9741460084915161, 'Val/mean precision': 0.9720401167869568, 'Val/mean recall': 0.9762609004974365, 'Val/mean hd95_metric': 5.895698547363281} +Cheakpoint... +Epoch [2255/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973515510559082, 'Val/mean miou_metric': 0.9572361707687378, 'Val/mean f1': 0.9741460084915161, 'Val/mean precision': 0.9720401167869568, 'Val/mean recall': 0.9762609004974365, 'Val/mean hd95_metric': 5.895698547363281} +Epoch [2256/4000] Training [1/16] Loss: 0.00526 +Epoch [2256/4000] Training [2/16] Loss: 0.00881 +Epoch [2256/4000] Training [3/16] Loss: 0.00415 +Epoch [2256/4000] Training [4/16] Loss: 0.00513 +Epoch [2256/4000] Training [5/16] Loss: 0.00545 +Epoch [2256/4000] Training [6/16] Loss: 0.00404 +Epoch [2256/4000] Training [7/16] Loss: 0.00473 +Epoch [2256/4000] Training [8/16] Loss: 0.00640 +Epoch [2256/4000] Training [9/16] Loss: 0.00457 +Epoch [2256/4000] Training [10/16] Loss: 0.00491 +Epoch [2256/4000] Training [11/16] Loss: 0.00527 +Epoch [2256/4000] Training [12/16] Loss: 0.00510 +Epoch [2256/4000] Training [13/16] Loss: 0.00339 +Epoch [2256/4000] Training [14/16] Loss: 0.00517 +Epoch [2256/4000] Training [15/16] Loss: 0.00443 +Epoch [2256/4000] Training [16/16] Loss: 0.00513 +Epoch [2256/4000] Training metric {'Train/mean dice_metric': 0.9966776371002197, 'Train/mean miou_metric': 0.9931150078773499, 'Train/mean f1': 0.9923555850982666, 'Train/mean precision': 0.9877695441246033, 'Train/mean recall': 0.9969843626022339, 'Train/mean hd95_metric': 0.9986739754676819} +Epoch [2256/4000] Validation [1/4] Loss: 0.28629 focal_loss 0.22446 dice_loss 0.06183 +Epoch [2256/4000] Validation [2/4] Loss: 0.32168 focal_loss 0.20416 dice_loss 0.11751 +Epoch [2256/4000] Validation [3/4] Loss: 0.39986 focal_loss 0.30181 dice_loss 0.09805 +Epoch [2256/4000] Validation [4/4] Loss: 0.34960 focal_loss 0.24438 dice_loss 0.10521 +Epoch [2256/4000] Validation metric {'Val/mean dice_metric': 0.9742682576179504, 'Val/mean miou_metric': 0.9585077166557312, 'Val/mean f1': 0.9760570526123047, 'Val/mean precision': 0.9740495681762695, 'Val/mean recall': 0.9780727028846741, 'Val/mean hd95_metric': 5.259882926940918} +Cheakpoint... +Epoch [2256/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742682576179504, 'Val/mean miou_metric': 0.9585077166557312, 'Val/mean f1': 0.9760570526123047, 'Val/mean precision': 0.9740495681762695, 'Val/mean recall': 0.9780727028846741, 'Val/mean hd95_metric': 5.259882926940918} +Epoch [2257/4000] Training [1/16] Loss: 0.00659 +Epoch [2257/4000] Training [2/16] Loss: 0.00524 +Epoch [2257/4000] Training [3/16] Loss: 0.00543 +Epoch [2257/4000] Training [4/16] Loss: 0.00581 +Epoch [2257/4000] Training [5/16] Loss: 0.00555 +Epoch [2257/4000] Training [6/16] Loss: 0.00561 +Epoch [2257/4000] Training [7/16] Loss: 0.00454 +Epoch [2257/4000] Training [8/16] Loss: 0.00656 +Epoch [2257/4000] Training [9/16] Loss: 0.00549 +Epoch [2257/4000] Training [10/16] Loss: 0.00513 +Epoch [2257/4000] Training [11/16] Loss: 0.00409 +Epoch [2257/4000] Training [12/16] Loss: 0.00517 +Epoch [2257/4000] Training [13/16] Loss: 0.00554 +Epoch [2257/4000] Training [14/16] Loss: 0.00456 +Epoch [2257/4000] Training [15/16] Loss: 0.00587 +Epoch [2257/4000] Training [16/16] Loss: 0.00384 +Epoch [2257/4000] Training metric {'Train/mean dice_metric': 0.9967536926269531, 'Train/mean miou_metric': 0.9932401180267334, 'Train/mean f1': 0.9918633699417114, 'Train/mean precision': 0.9869493246078491, 'Train/mean recall': 0.9968266487121582, 'Train/mean hd95_metric': 0.9953156113624573} +Epoch [2257/4000] Validation [1/4] Loss: 0.27478 focal_loss 0.21001 dice_loss 0.06477 +Epoch [2257/4000] Validation [2/4] Loss: 0.65419 focal_loss 0.44101 dice_loss 0.21317 +Epoch [2257/4000] Validation [3/4] Loss: 0.38349 focal_loss 0.28669 dice_loss 0.09680 +Epoch [2257/4000] Validation [4/4] Loss: 0.43144 focal_loss 0.29948 dice_loss 0.13195 +Epoch [2257/4000] Validation metric {'Val/mean dice_metric': 0.972326397895813, 'Val/mean miou_metric': 0.9561457633972168, 'Val/mean f1': 0.9745655059814453, 'Val/mean precision': 0.9724754691123962, 'Val/mean recall': 0.976664662361145, 'Val/mean hd95_metric': 5.197141170501709} +Cheakpoint... +Epoch [2257/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972326397895813, 'Val/mean miou_metric': 0.9561457633972168, 'Val/mean f1': 0.9745655059814453, 'Val/mean precision': 0.9724754691123962, 'Val/mean recall': 0.976664662361145, 'Val/mean hd95_metric': 5.197141170501709} +Epoch [2258/4000] Training [1/16] Loss: 0.00622 +Epoch [2258/4000] Training [2/16] Loss: 0.00512 +Epoch [2258/4000] Training [3/16] Loss: 0.00390 +Epoch [2258/4000] Training [4/16] Loss: 0.00552 +Epoch [2258/4000] Training [5/16] Loss: 0.00471 +Epoch [2258/4000] Training [6/16] Loss: 0.00509 +Epoch [2258/4000] Training [7/16] Loss: 0.00491 +Epoch [2258/4000] Training [8/16] Loss: 0.00449 +Epoch [2258/4000] Training [9/16] Loss: 0.00508 +Epoch [2258/4000] Training [10/16] Loss: 0.00528 +Epoch [2258/4000] Training [11/16] Loss: 0.00536 +Epoch [2258/4000] Training [12/16] Loss: 0.00506 +Epoch [2258/4000] Training [13/16] Loss: 0.00630 +Epoch [2258/4000] Training [14/16] Loss: 0.00385 +Epoch [2258/4000] Training [15/16] Loss: 0.00426 +Epoch [2258/4000] Training [16/16] Loss: 0.00493 +Epoch [2258/4000] Training metric {'Train/mean dice_metric': 0.9967441558837891, 'Train/mean miou_metric': 0.9932175874710083, 'Train/mean f1': 0.9921180009841919, 'Train/mean precision': 0.9874187111854553, 'Train/mean recall': 0.9968621730804443, 'Train/mean hd95_metric': 0.9909722805023193} +Epoch [2258/4000] Validation [1/4] Loss: 0.31363 focal_loss 0.24461 dice_loss 0.06902 +Epoch [2258/4000] Validation [2/4] Loss: 0.29800 focal_loss 0.18680 dice_loss 0.11119 +Epoch [2258/4000] Validation [3/4] Loss: 0.39045 focal_loss 0.29462 dice_loss 0.09583 +Epoch [2258/4000] Validation [4/4] Loss: 0.27703 focal_loss 0.17985 dice_loss 0.09719 +Epoch [2258/4000] Validation metric {'Val/mean dice_metric': 0.9742096662521362, 'Val/mean miou_metric': 0.9586885571479797, 'Val/mean f1': 0.975355327129364, 'Val/mean precision': 0.9722403883934021, 'Val/mean recall': 0.9784901142120361, 'Val/mean hd95_metric': 5.561829566955566} +Cheakpoint... +Epoch [2258/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742096662521362, 'Val/mean miou_metric': 0.9586885571479797, 'Val/mean f1': 0.975355327129364, 'Val/mean precision': 0.9722403883934021, 'Val/mean recall': 0.9784901142120361, 'Val/mean hd95_metric': 5.561829566955566} +Epoch [2259/4000] Training [1/16] Loss: 0.00473 +Epoch [2259/4000] Training [2/16] Loss: 0.00735 +Epoch [2259/4000] Training [3/16] Loss: 0.00491 +Epoch [2259/4000] Training [4/16] Loss: 0.00568 +Epoch [2259/4000] Training [5/16] Loss: 0.00531 +Epoch [2259/4000] Training [6/16] Loss: 0.00495 +Epoch [2259/4000] Training [7/16] Loss: 0.00449 +Epoch [2259/4000] Training [8/16] Loss: 0.00595 +Epoch [2259/4000] Training [9/16] Loss: 0.00447 +Epoch [2259/4000] Training [10/16] Loss: 0.00462 +Epoch [2259/4000] Training [11/16] Loss: 0.00455 +Epoch [2259/4000] Training [12/16] Loss: 0.00438 +Epoch [2259/4000] Training [13/16] Loss: 0.00564 +Epoch [2259/4000] Training [14/16] Loss: 0.00393 +Epoch [2259/4000] Training [15/16] Loss: 0.00431 +Epoch [2259/4000] Training [16/16] Loss: 0.00472 +Epoch [2259/4000] Training metric {'Train/mean dice_metric': 0.9968476891517639, 'Train/mean miou_metric': 0.9934388399124146, 'Train/mean f1': 0.9923194646835327, 'Train/mean precision': 0.9877215623855591, 'Train/mean recall': 0.9969603419303894, 'Train/mean hd95_metric': 0.9876809120178223} +Epoch [2259/4000] Validation [1/4] Loss: 0.30949 focal_loss 0.24403 dice_loss 0.06546 +Epoch [2259/4000] Validation [2/4] Loss: 0.31123 focal_loss 0.20411 dice_loss 0.10712 +Epoch [2259/4000] Validation [3/4] Loss: 0.24059 focal_loss 0.16492 dice_loss 0.07567 +Epoch [2259/4000] Validation [4/4] Loss: 0.69534 focal_loss 0.53269 dice_loss 0.16265 +Epoch [2259/4000] Validation metric {'Val/mean dice_metric': 0.9722369909286499, 'Val/mean miou_metric': 0.9564811587333679, 'Val/mean f1': 0.9739610552787781, 'Val/mean precision': 0.971468985080719, 'Val/mean recall': 0.9764660596847534, 'Val/mean hd95_metric': 5.925502777099609} +Cheakpoint... +Epoch [2259/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722369909286499, 'Val/mean miou_metric': 0.9564811587333679, 'Val/mean f1': 0.9739610552787781, 'Val/mean precision': 0.971468985080719, 'Val/mean recall': 0.9764660596847534, 'Val/mean hd95_metric': 5.925502777099609} +Epoch [2260/4000] Training [1/16] Loss: 0.00417 +Epoch [2260/4000] Training [2/16] Loss: 0.00588 +Epoch [2260/4000] Training [3/16] Loss: 0.00473 +Epoch [2260/4000] Training [4/16] Loss: 0.00654 +Epoch [2260/4000] Training [5/16] Loss: 0.00425 +Epoch [2260/4000] Training [6/16] Loss: 0.00433 +Epoch [2260/4000] Training [7/16] Loss: 0.00439 +Epoch [2260/4000] Training [8/16] Loss: 0.00529 +Epoch [2260/4000] Training [9/16] Loss: 0.00496 +Epoch [2260/4000] Training [10/16] Loss: 0.00427 +Epoch [2260/4000] Training [11/16] Loss: 0.00572 +Epoch [2260/4000] Training [12/16] Loss: 0.00591 +Epoch [2260/4000] Training [13/16] Loss: 0.00588 +Epoch [2260/4000] Training [14/16] Loss: 0.01063 +Epoch [2260/4000] Training [15/16] Loss: 0.00535 +Epoch [2260/4000] Training [16/16] Loss: 0.00687 +Epoch [2260/4000] Training metric {'Train/mean dice_metric': 0.9959206581115723, 'Train/mean miou_metric': 0.9918766021728516, 'Train/mean f1': 0.9911665916442871, 'Train/mean precision': 0.9859238266944885, 'Train/mean recall': 0.9964654445648193, 'Train/mean hd95_metric': 1.3417507410049438} +Epoch [2260/4000] Validation [1/4] Loss: 0.35833 focal_loss 0.28132 dice_loss 0.07701 +Epoch [2260/4000] Validation [2/4] Loss: 0.54094 focal_loss 0.39042 dice_loss 0.15052 +Epoch [2260/4000] Validation [3/4] Loss: 0.39529 focal_loss 0.29990 dice_loss 0.09539 +Epoch [2260/4000] Validation [4/4] Loss: 0.39590 focal_loss 0.27994 dice_loss 0.11597 +Epoch [2260/4000] Validation metric {'Val/mean dice_metric': 0.9717084765434265, 'Val/mean miou_metric': 0.9552881121635437, 'Val/mean f1': 0.9739267826080322, 'Val/mean precision': 0.9718711376190186, 'Val/mean recall': 0.9759910106658936, 'Val/mean hd95_metric': 5.5347819328308105} +Cheakpoint... +Epoch [2260/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717084765434265, 'Val/mean miou_metric': 0.9552881121635437, 'Val/mean f1': 0.9739267826080322, 'Val/mean precision': 0.9718711376190186, 'Val/mean recall': 0.9759910106658936, 'Val/mean hd95_metric': 5.5347819328308105} +Epoch [2261/4000] Training [1/16] Loss: 0.00526 +Epoch [2261/4000] Training [2/16] Loss: 0.00732 +Epoch [2261/4000] Training [3/16] Loss: 0.00561 +Epoch [2261/4000] Training [4/16] Loss: 0.00458 +Epoch [2261/4000] Training [5/16] Loss: 0.00673 +Epoch [2261/4000] Training [6/16] Loss: 0.00441 +Epoch [2261/4000] Training [7/16] Loss: 0.00633 +Epoch [2261/4000] Training [8/16] Loss: 0.00536 +Epoch [2261/4000] Training [9/16] Loss: 0.00581 +Epoch [2261/4000] Training [10/16] Loss: 0.00368 +Epoch [2261/4000] Training [11/16] Loss: 0.00671 +Epoch [2261/4000] Training [12/16] Loss: 0.00624 +Epoch [2261/4000] Training [13/16] Loss: 0.00453 +Epoch [2261/4000] Training [14/16] Loss: 0.00610 +Epoch [2261/4000] Training [15/16] Loss: 0.00587 +Epoch [2261/4000] Training [16/16] Loss: 0.00494 +Epoch [2261/4000] Training metric {'Train/mean dice_metric': 0.9965252876281738, 'Train/mean miou_metric': 0.9927819967269897, 'Train/mean f1': 0.991500198841095, 'Train/mean precision': 0.9866569638252258, 'Train/mean recall': 0.9963912963867188, 'Train/mean hd95_metric': 1.0005300045013428} +Epoch [2261/4000] Validation [1/4] Loss: 0.51302 focal_loss 0.39848 dice_loss 0.11454 +Epoch [2261/4000] Validation [2/4] Loss: 0.29531 focal_loss 0.18717 dice_loss 0.10814 +Epoch [2261/4000] Validation [3/4] Loss: 0.30372 focal_loss 0.20054 dice_loss 0.10317 +Epoch [2261/4000] Validation [4/4] Loss: 0.65612 focal_loss 0.50278 dice_loss 0.15334 +Epoch [2261/4000] Validation metric {'Val/mean dice_metric': 0.9708271026611328, 'Val/mean miou_metric': 0.95405513048172, 'Val/mean f1': 0.9724764227867126, 'Val/mean precision': 0.9738679528236389, 'Val/mean recall': 0.9710889458656311, 'Val/mean hd95_metric': 5.816235065460205} +Cheakpoint... +Epoch [2261/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708271026611328, 'Val/mean miou_metric': 0.95405513048172, 'Val/mean f1': 0.9724764227867126, 'Val/mean precision': 0.9738679528236389, 'Val/mean recall': 0.9710889458656311, 'Val/mean hd95_metric': 5.816235065460205} +Epoch [2262/4000] Training [1/16] Loss: 0.00525 +Epoch [2262/4000] Training [2/16] Loss: 0.00505 +Epoch [2262/4000] Training [3/16] Loss: 0.00574 +Epoch [2262/4000] Training [4/16] Loss: 0.00482 +Epoch [2262/4000] Training [5/16] Loss: 0.00551 +Epoch [2262/4000] Training [6/16] Loss: 0.00517 +Epoch [2262/4000] Training [7/16] Loss: 0.00487 +Epoch [2262/4000] Training [8/16] Loss: 0.00810 +Epoch [2262/4000] Training [9/16] Loss: 0.00485 +Epoch [2262/4000] Training [10/16] Loss: 0.00586 +Epoch [2262/4000] Training [11/16] Loss: 0.00577 +Epoch [2262/4000] Training [12/16] Loss: 0.00453 +Epoch [2262/4000] Training [13/16] Loss: 0.00571 +Epoch [2262/4000] Training [14/16] Loss: 0.00431 +Epoch [2262/4000] Training [15/16] Loss: 0.00790 +Epoch [2262/4000] Training [16/16] Loss: 0.00624 +Epoch [2262/4000] Training metric {'Train/mean dice_metric': 0.9963664412498474, 'Train/mean miou_metric': 0.9924994707107544, 'Train/mean f1': 0.992057204246521, 'Train/mean precision': 0.9874707460403442, 'Train/mean recall': 0.9966865181922913, 'Train/mean hd95_metric': 0.9883096218109131} +Epoch [2262/4000] Validation [1/4] Loss: 0.40266 focal_loss 0.31081 dice_loss 0.09185 +Epoch [2262/4000] Validation [2/4] Loss: 0.59942 focal_loss 0.40037 dice_loss 0.19905 +Epoch [2262/4000] Validation [3/4] Loss: 0.22187 focal_loss 0.14588 dice_loss 0.07599 +Epoch [2262/4000] Validation [4/4] Loss: 0.31242 focal_loss 0.20720 dice_loss 0.10522 +Epoch [2262/4000] Validation metric {'Val/mean dice_metric': 0.9713712930679321, 'Val/mean miou_metric': 0.9554258584976196, 'Val/mean f1': 0.9743314385414124, 'Val/mean precision': 0.974608838558197, 'Val/mean recall': 0.9740540385246277, 'Val/mean hd95_metric': 5.021816730499268} +Cheakpoint... +Epoch [2262/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713712930679321, 'Val/mean miou_metric': 0.9554258584976196, 'Val/mean f1': 0.9743314385414124, 'Val/mean precision': 0.974608838558197, 'Val/mean recall': 0.9740540385246277, 'Val/mean hd95_metric': 5.021816730499268} +Epoch [2263/4000] Training [1/16] Loss: 0.00513 +Epoch [2263/4000] Training [2/16] Loss: 0.00417 +Epoch [2263/4000] Training [3/16] Loss: 0.00464 +Epoch [2263/4000] Training [4/16] Loss: 0.00441 +Epoch [2263/4000] Training [5/16] Loss: 0.00496 +Epoch [2263/4000] Training [6/16] Loss: 0.00499 +Epoch [2263/4000] Training [7/16] Loss: 0.00463 +Epoch [2263/4000] Training [8/16] Loss: 0.00413 +Epoch [2263/4000] Training [9/16] Loss: 0.00596 +Epoch [2263/4000] Training [10/16] Loss: 0.00449 +Epoch [2263/4000] Training [11/16] Loss: 0.00446 +Epoch [2263/4000] Training [12/16] Loss: 0.00591 +Epoch [2263/4000] Training [13/16] Loss: 0.00524 +Epoch [2263/4000] Training [14/16] Loss: 0.00627 +Epoch [2263/4000] Training [15/16] Loss: 0.00604 +Epoch [2263/4000] Training [16/16] Loss: 0.00494 +Epoch [2263/4000] Training metric {'Train/mean dice_metric': 0.9966695308685303, 'Train/mean miou_metric': 0.9930917024612427, 'Train/mean f1': 0.9921072721481323, 'Train/mean precision': 0.9875578284263611, 'Train/mean recall': 0.996698796749115, 'Train/mean hd95_metric': 1.2481262683868408} +Epoch [2263/4000] Validation [1/4] Loss: 0.26013 focal_loss 0.19450 dice_loss 0.06562 +Epoch [2263/4000] Validation [2/4] Loss: 0.31805 focal_loss 0.20127 dice_loss 0.11678 +Epoch [2263/4000] Validation [3/4] Loss: 0.20959 focal_loss 0.14552 dice_loss 0.06407 +Epoch [2263/4000] Validation [4/4] Loss: 0.35337 focal_loss 0.23547 dice_loss 0.11790 +Epoch [2263/4000] Validation metric {'Val/mean dice_metric': 0.9723666906356812, 'Val/mean miou_metric': 0.9569343328475952, 'Val/mean f1': 0.9757532477378845, 'Val/mean precision': 0.9751856923103333, 'Val/mean recall': 0.9763213396072388, 'Val/mean hd95_metric': 4.8986358642578125} +Cheakpoint... +Epoch [2263/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723666906356812, 'Val/mean miou_metric': 0.9569343328475952, 'Val/mean f1': 0.9757532477378845, 'Val/mean precision': 0.9751856923103333, 'Val/mean recall': 0.9763213396072388, 'Val/mean hd95_metric': 4.8986358642578125} +Epoch [2264/4000] Training [1/16] Loss: 0.00535 +Epoch [2264/4000] Training [2/16] Loss: 0.00622 +Epoch [2264/4000] Training [3/16] Loss: 0.00489 +Epoch [2264/4000] Training [4/16] Loss: 0.00539 +Epoch [2264/4000] Training [5/16] Loss: 0.00502 +Epoch [2264/4000] Training [6/16] Loss: 0.00538 +Epoch [2264/4000] Training [7/16] Loss: 0.00452 +Epoch [2264/4000] Training [8/16] Loss: 0.00646 +Epoch [2264/4000] Training [9/16] Loss: 0.00393 +Epoch [2264/4000] Training [10/16] Loss: 0.00484 +Epoch [2264/4000] Training [11/16] Loss: 0.00452 +Epoch [2264/4000] Training [12/16] Loss: 0.00456 +Epoch [2264/4000] Training [13/16] Loss: 0.00465 +Epoch [2264/4000] Training [14/16] Loss: 0.00508 +Epoch [2264/4000] Training [15/16] Loss: 0.00423 +Epoch [2264/4000] Training [16/16] Loss: 0.00460 +Epoch [2264/4000] Training metric {'Train/mean dice_metric': 0.9969422221183777, 'Train/mean miou_metric': 0.9936362504959106, 'Train/mean f1': 0.9924505949020386, 'Train/mean precision': 0.9878151416778564, 'Train/mean recall': 0.9971299171447754, 'Train/mean hd95_metric': 0.9763250350952148} +Epoch [2264/4000] Validation [1/4] Loss: 0.48000 focal_loss 0.37355 dice_loss 0.10645 +Epoch [2264/4000] Validation [2/4] Loss: 0.31596 focal_loss 0.20467 dice_loss 0.11129 +Epoch [2264/4000] Validation [3/4] Loss: 0.32077 focal_loss 0.23409 dice_loss 0.08668 +Epoch [2264/4000] Validation [4/4] Loss: 0.48305 focal_loss 0.35198 dice_loss 0.13107 +Epoch [2264/4000] Validation metric {'Val/mean dice_metric': 0.9728676080703735, 'Val/mean miou_metric': 0.9571818113327026, 'Val/mean f1': 0.9754180908203125, 'Val/mean precision': 0.9737632870674133, 'Val/mean recall': 0.9770785570144653, 'Val/mean hd95_metric': 5.661593437194824} +Cheakpoint... +Epoch [2264/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728676080703735, 'Val/mean miou_metric': 0.9571818113327026, 'Val/mean f1': 0.9754180908203125, 'Val/mean precision': 0.9737632870674133, 'Val/mean recall': 0.9770785570144653, 'Val/mean hd95_metric': 5.661593437194824} +Epoch [2265/4000] Training [1/16] Loss: 0.00437 +Epoch [2265/4000] Training [2/16] Loss: 0.00481 +Epoch [2265/4000] Training [3/16] Loss: 0.00488 +Epoch [2265/4000] Training [4/16] Loss: 0.00525 +Epoch [2265/4000] Training [5/16] Loss: 0.00626 +Epoch [2265/4000] Training [6/16] Loss: 0.00411 +Epoch [2265/4000] Training [7/16] Loss: 0.00307 +Epoch [2265/4000] Training [8/16] Loss: 0.00314 +Epoch [2265/4000] Training [9/16] Loss: 0.00469 +Epoch [2265/4000] Training [10/16] Loss: 0.00615 +Epoch [2265/4000] Training [11/16] Loss: 0.00407 +Epoch [2265/4000] Training [12/16] Loss: 0.00361 +Epoch [2265/4000] Training [13/16] Loss: 0.00368 +Epoch [2265/4000] Training [14/16] Loss: 0.00498 +Epoch [2265/4000] Training [15/16] Loss: 0.00566 +Epoch [2265/4000] Training [16/16] Loss: 0.00494 +Epoch [2265/4000] Training metric {'Train/mean dice_metric': 0.9969347715377808, 'Train/mean miou_metric': 0.9936532974243164, 'Train/mean f1': 0.992576539516449, 'Train/mean precision': 0.9880372881889343, 'Train/mean recall': 0.997157633304596, 'Train/mean hd95_metric': 1.0106875896453857} +Epoch [2265/4000] Validation [1/4] Loss: 0.39192 focal_loss 0.29651 dice_loss 0.09541 +Epoch [2265/4000] Validation [2/4] Loss: 0.31182 focal_loss 0.19825 dice_loss 0.11356 +Epoch [2265/4000] Validation [3/4] Loss: 0.36802 focal_loss 0.27229 dice_loss 0.09574 +Epoch [2265/4000] Validation [4/4] Loss: 0.26093 focal_loss 0.17860 dice_loss 0.08233 +Epoch [2265/4000] Validation metric {'Val/mean dice_metric': 0.9734467267990112, 'Val/mean miou_metric': 0.9578240513801575, 'Val/mean f1': 0.9747187495231628, 'Val/mean precision': 0.9729304909706116, 'Val/mean recall': 0.976513683795929, 'Val/mean hd95_metric': 5.731823444366455} +Cheakpoint... +Epoch [2265/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734467267990112, 'Val/mean miou_metric': 0.9578240513801575, 'Val/mean f1': 0.9747187495231628, 'Val/mean precision': 0.9729304909706116, 'Val/mean recall': 0.976513683795929, 'Val/mean hd95_metric': 5.731823444366455} +Epoch [2266/4000] Training [1/16] Loss: 0.00413 +Epoch [2266/4000] Training [2/16] Loss: 0.00610 +Epoch [2266/4000] Training [3/16] Loss: 0.00594 +Epoch [2266/4000] Training [4/16] Loss: 0.00381 +Epoch [2266/4000] Training [5/16] Loss: 0.00628 +Epoch [2266/4000] Training [6/16] Loss: 0.00502 +Epoch [2266/4000] Training [7/16] Loss: 0.00384 +Epoch [2266/4000] Training [8/16] Loss: 0.00383 +Epoch [2266/4000] Training [9/16] Loss: 0.00417 +Epoch [2266/4000] Training [10/16] Loss: 0.00547 +Epoch [2266/4000] Training [11/16] Loss: 0.00471 +Epoch [2266/4000] Training [12/16] Loss: 0.00626 +Epoch [2266/4000] Training [13/16] Loss: 0.00586 +Epoch [2266/4000] Training [14/16] Loss: 0.00485 +Epoch [2266/4000] Training [15/16] Loss: 0.00518 +Epoch [2266/4000] Training [16/16] Loss: 0.00693 +Epoch [2266/4000] Training metric {'Train/mean dice_metric': 0.9965144395828247, 'Train/mean miou_metric': 0.9927718639373779, 'Train/mean f1': 0.99180668592453, 'Train/mean precision': 0.9869945645332336, 'Train/mean recall': 0.9966659545898438, 'Train/mean hd95_metric': 0.9870949387550354} +Epoch [2266/4000] Validation [1/4] Loss: 0.39176 focal_loss 0.30546 dice_loss 0.08630 +Epoch [2266/4000] Validation [2/4] Loss: 0.44157 focal_loss 0.28224 dice_loss 0.15933 +Epoch [2266/4000] Validation [3/4] Loss: 0.34966 focal_loss 0.25254 dice_loss 0.09712 +Epoch [2266/4000] Validation [4/4] Loss: 0.35989 focal_loss 0.23369 dice_loss 0.12621 +Epoch [2266/4000] Validation metric {'Val/mean dice_metric': 0.9732041358947754, 'Val/mean miou_metric': 0.9564726948738098, 'Val/mean f1': 0.9748741984367371, 'Val/mean precision': 0.9731472730636597, 'Val/mean recall': 0.9766072630882263, 'Val/mean hd95_metric': 5.27407693862915} +Cheakpoint... +Epoch [2266/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732041358947754, 'Val/mean miou_metric': 0.9564726948738098, 'Val/mean f1': 0.9748741984367371, 'Val/mean precision': 0.9731472730636597, 'Val/mean recall': 0.9766072630882263, 'Val/mean hd95_metric': 5.27407693862915} +Epoch [2267/4000] Training [1/16] Loss: 0.00426 +Epoch [2267/4000] Training [2/16] Loss: 0.00393 +Epoch [2267/4000] Training [3/16] Loss: 0.00586 +Epoch [2267/4000] Training [4/16] Loss: 0.00416 +Epoch [2267/4000] Training [5/16] Loss: 0.00477 +Epoch [2267/4000] Training [6/16] Loss: 0.00416 +Epoch [2267/4000] Training [7/16] Loss: 0.00456 +Epoch [2267/4000] Training [8/16] Loss: 0.00522 +Epoch [2267/4000] Training [9/16] Loss: 0.00462 +Epoch [2267/4000] Training [10/16] Loss: 0.00362 +Epoch [2267/4000] Training [11/16] Loss: 0.00472 +Epoch [2267/4000] Training [12/16] Loss: 0.00457 +Epoch [2267/4000] Training [13/16] Loss: 0.00747 +Epoch [2267/4000] Training [14/16] Loss: 0.00384 +Epoch [2267/4000] Training [15/16] Loss: 0.00545 +Epoch [2267/4000] Training [16/16] Loss: 0.00408 +Epoch [2267/4000] Training metric {'Train/mean dice_metric': 0.9969589710235596, 'Train/mean miou_metric': 0.9936711192131042, 'Train/mean f1': 0.9924973845481873, 'Train/mean precision': 0.9879075288772583, 'Train/mean recall': 0.9971300959587097, 'Train/mean hd95_metric': 0.9835516214370728} +Epoch [2267/4000] Validation [1/4] Loss: 0.34936 focal_loss 0.27285 dice_loss 0.07651 +Epoch [2267/4000] Validation [2/4] Loss: 0.35341 focal_loss 0.23063 dice_loss 0.12278 +Epoch [2267/4000] Validation [3/4] Loss: 0.21084 focal_loss 0.15346 dice_loss 0.05738 +Epoch [2267/4000] Validation [4/4] Loss: 0.28958 focal_loss 0.18989 dice_loss 0.09969 +Epoch [2267/4000] Validation metric {'Val/mean dice_metric': 0.9752195477485657, 'Val/mean miou_metric': 0.9596958160400391, 'Val/mean f1': 0.9758694171905518, 'Val/mean precision': 0.9733762145042419, 'Val/mean recall': 0.9783754348754883, 'Val/mean hd95_metric': 5.046138286590576} +Cheakpoint... +Epoch [2267/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752195477485657, 'Val/mean miou_metric': 0.9596958160400391, 'Val/mean f1': 0.9758694171905518, 'Val/mean precision': 0.9733762145042419, 'Val/mean recall': 0.9783754348754883, 'Val/mean hd95_metric': 5.046138286590576} +Epoch [2268/4000] Training [1/16] Loss: 0.00440 +Epoch [2268/4000] Training [2/16] Loss: 0.00573 +Epoch [2268/4000] Training [3/16] Loss: 0.00494 +Epoch [2268/4000] Training [4/16] Loss: 0.00410 +Epoch [2268/4000] Training [5/16] Loss: 0.00670 +Epoch [2268/4000] Training [6/16] Loss: 0.00588 +Epoch [2268/4000] Training [7/16] Loss: 0.00482 +Epoch [2268/4000] Training [8/16] Loss: 0.00339 +Epoch [2268/4000] Training [9/16] Loss: 0.00529 +Epoch [2268/4000] Training [10/16] Loss: 0.00643 +Epoch [2268/4000] Training [11/16] Loss: 0.00354 +Epoch [2268/4000] Training [12/16] Loss: 0.00447 +Epoch [2268/4000] Training [13/16] Loss: 0.00463 +Epoch [2268/4000] Training [14/16] Loss: 0.00534 +Epoch [2268/4000] Training [15/16] Loss: 0.00392 +Epoch [2268/4000] Training [16/16] Loss: 0.00445 +Epoch [2268/4000] Training metric {'Train/mean dice_metric': 0.9969947338104248, 'Train/mean miou_metric': 0.9937338829040527, 'Train/mean f1': 0.9924460053443909, 'Train/mean precision': 0.9879403710365295, 'Train/mean recall': 0.9969929456710815, 'Train/mean hd95_metric': 0.9993327856063843} +Epoch [2268/4000] Validation [1/4] Loss: 0.33755 focal_loss 0.26992 dice_loss 0.06763 +Epoch [2268/4000] Validation [2/4] Loss: 0.63890 focal_loss 0.44282 dice_loss 0.19608 +Epoch [2268/4000] Validation [3/4] Loss: 0.38154 focal_loss 0.28618 dice_loss 0.09536 +Epoch [2268/4000] Validation [4/4] Loss: 0.31789 focal_loss 0.20630 dice_loss 0.11159 +Epoch [2268/4000] Validation metric {'Val/mean dice_metric': 0.9725755453109741, 'Val/mean miou_metric': 0.9572958946228027, 'Val/mean f1': 0.9755553603172302, 'Val/mean precision': 0.9722158312797546, 'Val/mean recall': 0.9789179563522339, 'Val/mean hd95_metric': 5.7736382484436035} +Cheakpoint... +Epoch [2268/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725755453109741, 'Val/mean miou_metric': 0.9572958946228027, 'Val/mean f1': 0.9755553603172302, 'Val/mean precision': 0.9722158312797546, 'Val/mean recall': 0.9789179563522339, 'Val/mean hd95_metric': 5.7736382484436035} +Epoch [2269/4000] Training [1/16] Loss: 0.00456 +Epoch [2269/4000] Training [2/16] Loss: 0.00443 +Epoch [2269/4000] Training [3/16] Loss: 0.00440 +Epoch [2269/4000] Training [4/16] Loss: 0.00503 +Epoch [2269/4000] Training [5/16] Loss: 0.00440 +Epoch [2269/4000] Training [6/16] Loss: 0.00628 +Epoch [2269/4000] Training [7/16] Loss: 0.00695 +Epoch [2269/4000] Training [8/16] Loss: 0.00536 +Epoch [2269/4000] Training [9/16] Loss: 0.00537 +Epoch [2269/4000] Training [10/16] Loss: 0.00423 +Epoch [2269/4000] Training [11/16] Loss: 0.00572 +Epoch [2269/4000] Training [12/16] Loss: 0.00427 +Epoch [2269/4000] Training [13/16] Loss: 0.00505 +Epoch [2269/4000] Training [14/16] Loss: 0.00432 +Epoch [2269/4000] Training [15/16] Loss: 0.00664 +Epoch [2269/4000] Training [16/16] Loss: 0.00471 +Epoch [2269/4000] Training metric {'Train/mean dice_metric': 0.9968010783195496, 'Train/mean miou_metric': 0.9933575391769409, 'Train/mean f1': 0.9923015832901001, 'Train/mean precision': 0.9877546429634094, 'Train/mean recall': 0.996890664100647, 'Train/mean hd95_metric': 0.980914831161499} +Epoch [2269/4000] Validation [1/4] Loss: 0.29263 focal_loss 0.22149 dice_loss 0.07114 +Epoch [2269/4000] Validation [2/4] Loss: 0.53773 focal_loss 0.38319 dice_loss 0.15454 +Epoch [2269/4000] Validation [3/4] Loss: 0.18360 focal_loss 0.12953 dice_loss 0.05408 +Epoch [2269/4000] Validation [4/4] Loss: 0.32219 focal_loss 0.21483 dice_loss 0.10736 +Epoch [2269/4000] Validation metric {'Val/mean dice_metric': 0.9743644595146179, 'Val/mean miou_metric': 0.9583421945571899, 'Val/mean f1': 0.9757488965988159, 'Val/mean precision': 0.9737793803215027, 'Val/mean recall': 0.9777262806892395, 'Val/mean hd95_metric': 4.812702178955078} +Cheakpoint... +Epoch [2269/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743644595146179, 'Val/mean miou_metric': 0.9583421945571899, 'Val/mean f1': 0.9757488965988159, 'Val/mean precision': 0.9737793803215027, 'Val/mean recall': 0.9777262806892395, 'Val/mean hd95_metric': 4.812702178955078} +Epoch [2270/4000] Training [1/16] Loss: 0.00449 +Epoch [2270/4000] Training [2/16] Loss: 0.00485 +Epoch [2270/4000] Training [3/16] Loss: 0.00377 +Epoch [2270/4000] Training [4/16] Loss: 0.00475 +Epoch [2270/4000] Training [5/16] Loss: 0.00341 +Epoch [2270/4000] Training [6/16] Loss: 0.00412 +Epoch [2270/4000] Training [7/16] Loss: 0.00456 +Epoch [2270/4000] Training [8/16] Loss: 0.00536 +Epoch [2270/4000] Training [9/16] Loss: 0.00471 +Epoch [2270/4000] Training [10/16] Loss: 0.00526 +Epoch [2270/4000] Training [11/16] Loss: 0.00614 +Epoch [2270/4000] Training [12/16] Loss: 0.00428 +Epoch [2270/4000] Training [13/16] Loss: 0.00485 +Epoch [2270/4000] Training [14/16] Loss: 0.00499 +Epoch [2270/4000] Training [15/16] Loss: 0.00435 +Epoch [2270/4000] Training [16/16] Loss: 0.00494 +Epoch [2270/4000] Training metric {'Train/mean dice_metric': 0.9969724416732788, 'Train/mean miou_metric': 0.993694543838501, 'Train/mean f1': 0.9924235939979553, 'Train/mean precision': 0.9878223538398743, 'Train/mean recall': 0.997067928314209, 'Train/mean hd95_metric': 0.9902424812316895} +Epoch [2270/4000] Validation [1/4] Loss: 0.34892 focal_loss 0.26393 dice_loss 0.08500 +Epoch [2270/4000] Validation [2/4] Loss: 0.63524 focal_loss 0.43701 dice_loss 0.19822 +Epoch [2270/4000] Validation [3/4] Loss: 0.20351 focal_loss 0.14380 dice_loss 0.05971 +Epoch [2270/4000] Validation [4/4] Loss: 0.32717 focal_loss 0.22232 dice_loss 0.10486 +Epoch [2270/4000] Validation metric {'Val/mean dice_metric': 0.9727025032043457, 'Val/mean miou_metric': 0.9574187994003296, 'Val/mean f1': 0.9752817153930664, 'Val/mean precision': 0.9740162491798401, 'Val/mean recall': 0.9765505194664001, 'Val/mean hd95_metric': 4.934050559997559} +Cheakpoint... +Epoch [2270/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727025032043457, 'Val/mean miou_metric': 0.9574187994003296, 'Val/mean f1': 0.9752817153930664, 'Val/mean precision': 0.9740162491798401, 'Val/mean recall': 0.9765505194664001, 'Val/mean hd95_metric': 4.934050559997559} +Epoch [2271/4000] Training [1/16] Loss: 0.00648 +Epoch [2271/4000] Training [2/16] Loss: 0.00511 +Epoch [2271/4000] Training [3/16] Loss: 0.00454 +Epoch [2271/4000] Training [4/16] Loss: 0.00672 +Epoch [2271/4000] Training [5/16] Loss: 0.00431 +Epoch [2271/4000] Training [6/16] Loss: 0.00513 +Epoch [2271/4000] Training [7/16] Loss: 0.00415 +Epoch [2271/4000] Training [8/16] Loss: 0.00549 +Epoch [2271/4000] Training [9/16] Loss: 0.00746 +Epoch [2271/4000] Training [10/16] Loss: 0.00534 +Epoch [2271/4000] Training [11/16] Loss: 0.00504 +Epoch [2271/4000] Training [12/16] Loss: 0.00776 +Epoch [2271/4000] Training [13/16] Loss: 0.00717 +Epoch [2271/4000] Training [14/16] Loss: 0.01374 +Epoch [2271/4000] Training [15/16] Loss: 0.00722 +Epoch [2271/4000] Training [16/16] Loss: 0.00492 +Epoch [2271/4000] Training metric {'Train/mean dice_metric': 0.9961777925491333, 'Train/mean miou_metric': 0.9921233654022217, 'Train/mean f1': 0.991828203201294, 'Train/mean precision': 0.9871658086776733, 'Train/mean recall': 0.9965348243713379, 'Train/mean hd95_metric': 1.0219731330871582} +Epoch [2271/4000] Validation [1/4] Loss: 0.28328 focal_loss 0.21595 dice_loss 0.06733 +Epoch [2271/4000] Validation [2/4] Loss: 0.28313 focal_loss 0.17750 dice_loss 0.10564 +Epoch [2271/4000] Validation [3/4] Loss: 0.40190 focal_loss 0.30899 dice_loss 0.09291 +Epoch [2271/4000] Validation [4/4] Loss: 0.45714 focal_loss 0.32040 dice_loss 0.13674 +Epoch [2271/4000] Validation metric {'Val/mean dice_metric': 0.9729925394058228, 'Val/mean miou_metric': 0.9568489193916321, 'Val/mean f1': 0.9751160740852356, 'Val/mean precision': 0.9728395342826843, 'Val/mean recall': 0.9774032831192017, 'Val/mean hd95_metric': 5.082987308502197} +Cheakpoint... +Epoch [2271/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729925394058228, 'Val/mean miou_metric': 0.9568489193916321, 'Val/mean f1': 0.9751160740852356, 'Val/mean precision': 0.9728395342826843, 'Val/mean recall': 0.9774032831192017, 'Val/mean hd95_metric': 5.082987308502197} +Epoch [2272/4000] Training [1/16] Loss: 0.00439 +Epoch [2272/4000] Training [2/16] Loss: 0.00464 +Epoch [2272/4000] Training [3/16] Loss: 0.00434 +Epoch [2272/4000] Training [4/16] Loss: 0.00580 +Epoch [2272/4000] Training [5/16] Loss: 0.00364 +Epoch [2272/4000] Training [6/16] Loss: 0.00422 +Epoch [2272/4000] Training [7/16] Loss: 0.00466 +Epoch [2272/4000] Training [8/16] Loss: 0.00402 +Epoch [2272/4000] Training [9/16] Loss: 0.00582 +Epoch [2272/4000] Training [10/16] Loss: 0.00527 +Epoch [2272/4000] Training [11/16] Loss: 0.00418 +Epoch [2272/4000] Training [12/16] Loss: 0.00544 +Epoch [2272/4000] Training [13/16] Loss: 0.00445 +Epoch [2272/4000] Training [14/16] Loss: 0.00435 +Epoch [2272/4000] Training [15/16] Loss: 0.00405 +Epoch [2272/4000] Training [16/16] Loss: 0.00463 +Epoch [2272/4000] Training metric {'Train/mean dice_metric': 0.997063398361206, 'Train/mean miou_metric': 0.9938720464706421, 'Train/mean f1': 0.9924978613853455, 'Train/mean precision': 0.9879686832427979, 'Train/mean recall': 0.9970688223838806, 'Train/mean hd95_metric': 0.9891457557678223} +Epoch [2272/4000] Validation [1/4] Loss: 0.32554 focal_loss 0.25603 dice_loss 0.06951 +Epoch [2272/4000] Validation [2/4] Loss: 0.26937 focal_loss 0.16956 dice_loss 0.09981 +Epoch [2272/4000] Validation [3/4] Loss: 0.37626 focal_loss 0.28159 dice_loss 0.09467 +Epoch [2272/4000] Validation [4/4] Loss: 0.70131 focal_loss 0.53176 dice_loss 0.16955 +Epoch [2272/4000] Validation metric {'Val/mean dice_metric': 0.9725959897041321, 'Val/mean miou_metric': 0.9567278027534485, 'Val/mean f1': 0.9746817946434021, 'Val/mean precision': 0.9723350405693054, 'Val/mean recall': 0.9770398736000061, 'Val/mean hd95_metric': 5.406918048858643} +Cheakpoint... +Epoch [2272/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725959897041321, 'Val/mean miou_metric': 0.9567278027534485, 'Val/mean f1': 0.9746817946434021, 'Val/mean precision': 0.9723350405693054, 'Val/mean recall': 0.9770398736000061, 'Val/mean hd95_metric': 5.406918048858643} +Epoch [2273/4000] Training [1/16] Loss: 0.00554 +Epoch [2273/4000] Training [2/16] Loss: 0.00413 +Epoch [2273/4000] Training [3/16] Loss: 0.00317 +Epoch [2273/4000] Training [4/16] Loss: 0.00558 +Epoch [2273/4000] Training [5/16] Loss: 0.00486 +Epoch [2273/4000] Training [6/16] Loss: 0.00468 +Epoch [2273/4000] Training [7/16] Loss: 0.00408 +Epoch [2273/4000] Training [8/16] Loss: 0.00618 +Epoch [2273/4000] Training [9/16] Loss: 0.00510 +Epoch [2273/4000] Training [10/16] Loss: 0.00450 +Epoch [2273/4000] Training [11/16] Loss: 0.00485 +Epoch [2273/4000] Training [12/16] Loss: 0.00579 +Epoch [2273/4000] Training [13/16] Loss: 0.00457 +Epoch [2273/4000] Training [14/16] Loss: 0.00577 +Epoch [2273/4000] Training [15/16] Loss: 0.00612 +Epoch [2273/4000] Training [16/16] Loss: 0.00701 +Epoch [2273/4000] Training metric {'Train/mean dice_metric': 0.9966152906417847, 'Train/mean miou_metric': 0.9929877519607544, 'Train/mean f1': 0.9920753240585327, 'Train/mean precision': 0.9874134659767151, 'Train/mean recall': 0.9967812895774841, 'Train/mean hd95_metric': 0.987205982208252} +Epoch [2273/4000] Validation [1/4] Loss: 0.37678 focal_loss 0.29969 dice_loss 0.07709 +Epoch [2273/4000] Validation [2/4] Loss: 0.30330 focal_loss 0.19856 dice_loss 0.10475 +Epoch [2273/4000] Validation [3/4] Loss: 0.39657 focal_loss 0.30651 dice_loss 0.09006 +Epoch [2273/4000] Validation [4/4] Loss: 0.33930 focal_loss 0.20902 dice_loss 0.13028 +Epoch [2273/4000] Validation metric {'Val/mean dice_metric': 0.9735525846481323, 'Val/mean miou_metric': 0.9575166702270508, 'Val/mean f1': 0.9755988121032715, 'Val/mean precision': 0.9723695516586304, 'Val/mean recall': 0.9788495302200317, 'Val/mean hd95_metric': 5.124279022216797} +Cheakpoint... +Epoch [2273/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735525846481323, 'Val/mean miou_metric': 0.9575166702270508, 'Val/mean f1': 0.9755988121032715, 'Val/mean precision': 0.9723695516586304, 'Val/mean recall': 0.9788495302200317, 'Val/mean hd95_metric': 5.124279022216797} +Epoch [2274/4000] Training [1/16] Loss: 0.00589 +Epoch [2274/4000] Training [2/16] Loss: 0.00872 +Epoch [2274/4000] Training [3/16] Loss: 0.00344 +Epoch [2274/4000] Training [4/16] Loss: 0.00681 +Epoch [2274/4000] Training [5/16] Loss: 0.00484 +Epoch [2274/4000] Training [6/16] Loss: 0.00407 +Epoch [2274/4000] Training [7/16] Loss: 0.00477 +Epoch [2274/4000] Training [8/16] Loss: 0.00537 +Epoch [2274/4000] Training [9/16] Loss: 0.00640 +Epoch [2274/4000] Training [10/16] Loss: 0.00522 +Epoch [2274/4000] Training [11/16] Loss: 0.00472 +Epoch [2274/4000] Training [12/16] Loss: 0.00400 +Epoch [2274/4000] Training [13/16] Loss: 0.00657 +Epoch [2274/4000] Training [14/16] Loss: 0.00510 +Epoch [2274/4000] Training [15/16] Loss: 0.00395 +Epoch [2274/4000] Training [16/16] Loss: 0.00598 +Epoch [2274/4000] Training metric {'Train/mean dice_metric': 0.9964902400970459, 'Train/mean miou_metric': 0.9927427172660828, 'Train/mean f1': 0.9921210408210754, 'Train/mean precision': 0.9876642823219299, 'Train/mean recall': 0.9966180920600891, 'Train/mean hd95_metric': 1.0041704177856445} +Epoch [2274/4000] Validation [1/4] Loss: 0.28295 focal_loss 0.21977 dice_loss 0.06318 +Epoch [2274/4000] Validation [2/4] Loss: 0.28698 focal_loss 0.17834 dice_loss 0.10864 +Epoch [2274/4000] Validation [3/4] Loss: 0.19342 focal_loss 0.13403 dice_loss 0.05939 +Epoch [2274/4000] Validation [4/4] Loss: 0.37665 focal_loss 0.24534 dice_loss 0.13131 +Epoch [2274/4000] Validation metric {'Val/mean dice_metric': 0.9735980033874512, 'Val/mean miou_metric': 0.9579488039016724, 'Val/mean f1': 0.975949227809906, 'Val/mean precision': 0.9728520512580872, 'Val/mean recall': 0.9790661931037903, 'Val/mean hd95_metric': 5.069991588592529} +Cheakpoint... +Epoch [2274/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735980033874512, 'Val/mean miou_metric': 0.9579488039016724, 'Val/mean f1': 0.975949227809906, 'Val/mean precision': 0.9728520512580872, 'Val/mean recall': 0.9790661931037903, 'Val/mean hd95_metric': 5.069991588592529} +Epoch [2275/4000] Training [1/16] Loss: 0.00415 +Epoch [2275/4000] Training [2/16] Loss: 0.00580 +Epoch [2275/4000] Training [3/16] Loss: 0.00396 +Epoch [2275/4000] Training [4/16] Loss: 0.00493 +Epoch [2275/4000] Training [5/16] Loss: 0.00508 +Epoch [2275/4000] Training [6/16] Loss: 0.00483 +Epoch [2275/4000] Training [7/16] Loss: 0.00393 +Epoch [2275/4000] Training [8/16] Loss: 0.00454 +Epoch [2275/4000] Training [9/16] Loss: 0.00545 +Epoch [2275/4000] Training [10/16] Loss: 0.00700 +Epoch [2275/4000] Training [11/16] Loss: 0.00547 +Epoch [2275/4000] Training [12/16] Loss: 0.00487 +Epoch [2275/4000] Training [13/16] Loss: 0.00686 +Epoch [2275/4000] Training [14/16] Loss: 0.00446 +Epoch [2275/4000] Training [15/16] Loss: 0.00552 +Epoch [2275/4000] Training [16/16] Loss: 0.00441 +Epoch [2275/4000] Training metric {'Train/mean dice_metric': 0.9966706037521362, 'Train/mean miou_metric': 0.9930977821350098, 'Train/mean f1': 0.992155909538269, 'Train/mean precision': 0.9874815344810486, 'Train/mean recall': 0.9968747496604919, 'Train/mean hd95_metric': 0.9974237680435181} +Epoch [2275/4000] Validation [1/4] Loss: 0.36993 focal_loss 0.29552 dice_loss 0.07441 +Epoch [2275/4000] Validation [2/4] Loss: 0.28638 focal_loss 0.18212 dice_loss 0.10425 +Epoch [2275/4000] Validation [3/4] Loss: 0.24885 focal_loss 0.18261 dice_loss 0.06624 +Epoch [2275/4000] Validation [4/4] Loss: 0.36380 focal_loss 0.25812 dice_loss 0.10569 +Epoch [2275/4000] Validation metric {'Val/mean dice_metric': 0.9722094535827637, 'Val/mean miou_metric': 0.9563727378845215, 'Val/mean f1': 0.9746086597442627, 'Val/mean precision': 0.9734445214271545, 'Val/mean recall': 0.9757756590843201, 'Val/mean hd95_metric': 4.975037574768066} +Cheakpoint... +Epoch [2275/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722094535827637, 'Val/mean miou_metric': 0.9563727378845215, 'Val/mean f1': 0.9746086597442627, 'Val/mean precision': 0.9734445214271545, 'Val/mean recall': 0.9757756590843201, 'Val/mean hd95_metric': 4.975037574768066} +Epoch [2276/4000] Training [1/16] Loss: 0.00372 +Epoch [2276/4000] Training [2/16] Loss: 0.00451 +Epoch [2276/4000] Training [3/16] Loss: 0.00461 +Epoch [2276/4000] Training [4/16] Loss: 0.00529 +Epoch [2276/4000] Training [5/16] Loss: 0.00522 +Epoch [2276/4000] Training [6/16] Loss: 0.00604 +Epoch [2276/4000] Training [7/16] Loss: 0.00555 +Epoch [2276/4000] Training [8/16] Loss: 0.00514 +Epoch [2276/4000] Training [9/16] Loss: 0.00501 +Epoch [2276/4000] Training [10/16] Loss: 0.00500 +Epoch [2276/4000] Training [11/16] Loss: 0.00573 +Epoch [2276/4000] Training [12/16] Loss: 0.00438 +Epoch [2276/4000] Training [13/16] Loss: 0.00485 +Epoch [2276/4000] Training [14/16] Loss: 0.00497 +Epoch [2276/4000] Training [15/16] Loss: 0.00452 +Epoch [2276/4000] Training [16/16] Loss: 0.00468 +Epoch [2276/4000] Training metric {'Train/mean dice_metric': 0.9967941045761108, 'Train/mean miou_metric': 0.9933332204818726, 'Train/mean f1': 0.9922764301300049, 'Train/mean precision': 0.9876746535301208, 'Train/mean recall': 0.9969212412834167, 'Train/mean hd95_metric': 0.9888776540756226} +Epoch [2276/4000] Validation [1/4] Loss: 0.42815 focal_loss 0.33322 dice_loss 0.09493 +Epoch [2276/4000] Validation [2/4] Loss: 0.74248 focal_loss 0.54607 dice_loss 0.19641 +Epoch [2276/4000] Validation [3/4] Loss: 0.39550 focal_loss 0.30585 dice_loss 0.08965 +Epoch [2276/4000] Validation [4/4] Loss: 0.32861 focal_loss 0.20204 dice_loss 0.12658 +Epoch [2276/4000] Validation metric {'Val/mean dice_metric': 0.9710401296615601, 'Val/mean miou_metric': 0.9551178216934204, 'Val/mean f1': 0.974427342414856, 'Val/mean precision': 0.9735941290855408, 'Val/mean recall': 0.9752620458602905, 'Val/mean hd95_metric': 5.185101509094238} +Cheakpoint... +Epoch [2276/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710401296615601, 'Val/mean miou_metric': 0.9551178216934204, 'Val/mean f1': 0.974427342414856, 'Val/mean precision': 0.9735941290855408, 'Val/mean recall': 0.9752620458602905, 'Val/mean hd95_metric': 5.185101509094238} +Epoch [2277/4000] Training [1/16] Loss: 0.00526 +Epoch [2277/4000] Training [2/16] Loss: 0.00457 +Epoch [2277/4000] Training [3/16] Loss: 0.00365 +Epoch [2277/4000] Training [4/16] Loss: 0.00380 +Epoch [2277/4000] Training [5/16] Loss: 0.00460 +Epoch [2277/4000] Training [6/16] Loss: 0.00503 +Epoch [2277/4000] Training [7/16] Loss: 0.00464 +Epoch [2277/4000] Training [8/16] Loss: 0.00411 +Epoch [2277/4000] Training [9/16] Loss: 0.00585 +Epoch [2277/4000] Training [10/16] Loss: 0.00458 +Epoch [2277/4000] Training [11/16] Loss: 0.00676 +Epoch [2277/4000] Training [12/16] Loss: 0.00470 +Epoch [2277/4000] Training [13/16] Loss: 0.00441 +Epoch [2277/4000] Training [14/16] Loss: 0.00430 +Epoch [2277/4000] Training [15/16] Loss: 0.00453 +Epoch [2277/4000] Training [16/16] Loss: 0.00537 +Epoch [2277/4000] Training metric {'Train/mean dice_metric': 0.9967954754829407, 'Train/mean miou_metric': 0.9933387041091919, 'Train/mean f1': 0.9920229315757751, 'Train/mean precision': 0.9873001575469971, 'Train/mean recall': 0.9967911243438721, 'Train/mean hd95_metric': 0.9949584007263184} +Epoch [2277/4000] Validation [1/4] Loss: 0.37404 focal_loss 0.28200 dice_loss 0.09204 +Epoch [2277/4000] Validation [2/4] Loss: 0.80813 focal_loss 0.61342 dice_loss 0.19471 +Epoch [2277/4000] Validation [3/4] Loss: 0.37302 focal_loss 0.28170 dice_loss 0.09133 +Epoch [2277/4000] Validation [4/4] Loss: 0.42289 focal_loss 0.29438 dice_loss 0.12851 +Epoch [2277/4000] Validation metric {'Val/mean dice_metric': 0.9722315073013306, 'Val/mean miou_metric': 0.956402599811554, 'Val/mean f1': 0.9746308922767639, 'Val/mean precision': 0.9728676676750183, 'Val/mean recall': 0.9764004945755005, 'Val/mean hd95_metric': 4.955052852630615} +Cheakpoint... +Epoch [2277/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722315073013306, 'Val/mean miou_metric': 0.956402599811554, 'Val/mean f1': 0.9746308922767639, 'Val/mean precision': 0.9728676676750183, 'Val/mean recall': 0.9764004945755005, 'Val/mean hd95_metric': 4.955052852630615} +Epoch [2278/4000] Training [1/16] Loss: 0.00470 +Epoch [2278/4000] Training [2/16] Loss: 0.00421 +Epoch [2278/4000] Training [3/16] Loss: 0.00432 +Epoch [2278/4000] Training [4/16] Loss: 0.00499 +Epoch [2278/4000] Training [5/16] Loss: 0.00495 +Epoch [2278/4000] Training [6/16] Loss: 0.00476 +Epoch [2278/4000] Training [7/16] Loss: 0.00493 +Epoch [2278/4000] Training [8/16] Loss: 0.00439 +Epoch [2278/4000] Training [9/16] Loss: 0.00520 +Epoch [2278/4000] Training [10/16] Loss: 0.00402 +Epoch [2278/4000] Training [11/16] Loss: 0.00369 +Epoch [2278/4000] Training [12/16] Loss: 0.00414 +Epoch [2278/4000] Training [13/16] Loss: 0.00496 +Epoch [2278/4000] Training [14/16] Loss: 0.00480 +Epoch [2278/4000] Training [15/16] Loss: 0.00407 +Epoch [2278/4000] Training [16/16] Loss: 0.00888 +Epoch [2278/4000] Training metric {'Train/mean dice_metric': 0.996743381023407, 'Train/mean miou_metric': 0.9932463765144348, 'Train/mean f1': 0.9923702478408813, 'Train/mean precision': 0.987932026386261, 'Train/mean recall': 0.9968485236167908, 'Train/mean hd95_metric': 1.0149039030075073} +Epoch [2278/4000] Validation [1/4] Loss: 0.45062 focal_loss 0.33180 dice_loss 0.11882 +Epoch [2278/4000] Validation [2/4] Loss: 0.71311 focal_loss 0.52230 dice_loss 0.19081 +Epoch [2278/4000] Validation [3/4] Loss: 0.21305 focal_loss 0.15393 dice_loss 0.05912 +Epoch [2278/4000] Validation [4/4] Loss: 0.41174 focal_loss 0.29826 dice_loss 0.11348 +Epoch [2278/4000] Validation metric {'Val/mean dice_metric': 0.9696645736694336, 'Val/mean miou_metric': 0.9536997079849243, 'Val/mean f1': 0.972284197807312, 'Val/mean precision': 0.9743005037307739, 'Val/mean recall': 0.9702762365341187, 'Val/mean hd95_metric': 5.161764621734619} +Cheakpoint... +Epoch [2278/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696645736694336, 'Val/mean miou_metric': 0.9536997079849243, 'Val/mean f1': 0.972284197807312, 'Val/mean precision': 0.9743005037307739, 'Val/mean recall': 0.9702762365341187, 'Val/mean hd95_metric': 5.161764621734619} +Epoch [2279/4000] Training [1/16] Loss: 0.00494 +Epoch [2279/4000] Training [2/16] Loss: 0.00497 +Epoch [2279/4000] Training [3/16] Loss: 0.00501 +Epoch [2279/4000] Training [4/16] Loss: 0.00499 +Epoch [2279/4000] Training [5/16] Loss: 0.00447 +Epoch [2279/4000] Training [6/16] Loss: 0.00475 +Epoch [2279/4000] Training [7/16] Loss: 0.00460 +Epoch [2279/4000] Training [8/16] Loss: 0.00376 +Epoch [2279/4000] Training [9/16] Loss: 0.00399 +Epoch [2279/4000] Training [10/16] Loss: 0.00565 +Epoch [2279/4000] Training [11/16] Loss: 0.00311 +Epoch [2279/4000] Training [12/16] Loss: 0.00363 +Epoch [2279/4000] Training [13/16] Loss: 0.00437 +Epoch [2279/4000] Training [14/16] Loss: 0.00416 +Epoch [2279/4000] Training [15/16] Loss: 0.00398 +Epoch [2279/4000] Training [16/16] Loss: 0.00440 +Epoch [2279/4000] Training metric {'Train/mean dice_metric': 0.9969366192817688, 'Train/mean miou_metric': 0.9936268329620361, 'Train/mean f1': 0.9924253225326538, 'Train/mean precision': 0.9878112077713013, 'Train/mean recall': 0.9970827698707581, 'Train/mean hd95_metric': 0.984533429145813} +Epoch [2279/4000] Validation [1/4] Loss: 0.42530 focal_loss 0.32291 dice_loss 0.10239 +Epoch [2279/4000] Validation [2/4] Loss: 0.56234 focal_loss 0.40455 dice_loss 0.15778 +Epoch [2279/4000] Validation [3/4] Loss: 0.35283 focal_loss 0.26333 dice_loss 0.08950 +Epoch [2279/4000] Validation [4/4] Loss: 0.25194 focal_loss 0.15570 dice_loss 0.09624 +Epoch [2279/4000] Validation metric {'Val/mean dice_metric': 0.9748605489730835, 'Val/mean miou_metric': 0.9586618542671204, 'Val/mean f1': 0.9755685925483704, 'Val/mean precision': 0.9727649092674255, 'Val/mean recall': 0.9783885478973389, 'Val/mean hd95_metric': 5.2053141593933105} +Cheakpoint... +Epoch [2279/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748605489730835, 'Val/mean miou_metric': 0.9586618542671204, 'Val/mean f1': 0.9755685925483704, 'Val/mean precision': 0.9727649092674255, 'Val/mean recall': 0.9783885478973389, 'Val/mean hd95_metric': 5.2053141593933105} +Epoch [2280/4000] Training [1/16] Loss: 0.00831 +Epoch [2280/4000] Training [2/16] Loss: 0.00409 +Epoch [2280/4000] Training [3/16] Loss: 0.00507 +Epoch [2280/4000] Training [4/16] Loss: 0.00645 +Epoch [2280/4000] Training [5/16] Loss: 0.00482 +Epoch [2280/4000] Training [6/16] Loss: 0.00521 +Epoch [2280/4000] Training [7/16] Loss: 0.00637 +Epoch [2280/4000] Training [8/16] Loss: 0.00524 +Epoch [2280/4000] Training [9/16] Loss: 0.00498 +Epoch [2280/4000] Training [10/16] Loss: 0.00669 +Epoch [2280/4000] Training [11/16] Loss: 0.00344 +Epoch [2280/4000] Training [12/16] Loss: 0.00381 +Epoch [2280/4000] Training [13/16] Loss: 0.00484 +Epoch [2280/4000] Training [14/16] Loss: 0.00415 +Epoch [2280/4000] Training [15/16] Loss: 0.00545 +Epoch [2280/4000] Training [16/16] Loss: 0.00550 +Epoch [2280/4000] Training metric {'Train/mean dice_metric': 0.9966062307357788, 'Train/mean miou_metric': 0.9929581880569458, 'Train/mean f1': 0.9920058846473694, 'Train/mean precision': 0.9873728156089783, 'Train/mean recall': 0.9966826438903809, 'Train/mean hd95_metric': 0.9929469227790833} +Epoch [2280/4000] Validation [1/4] Loss: 0.30755 focal_loss 0.23404 dice_loss 0.07351 +Epoch [2280/4000] Validation [2/4] Loss: 0.68548 focal_loss 0.48897 dice_loss 0.19651 +Epoch [2280/4000] Validation [3/4] Loss: 0.37656 focal_loss 0.28292 dice_loss 0.09364 +Epoch [2280/4000] Validation [4/4] Loss: 0.35483 focal_loss 0.24089 dice_loss 0.11394 +Epoch [2280/4000] Validation metric {'Val/mean dice_metric': 0.9719667434692383, 'Val/mean miou_metric': 0.9561467170715332, 'Val/mean f1': 0.9751465916633606, 'Val/mean precision': 0.973613440990448, 'Val/mean recall': 0.9766844511032104, 'Val/mean hd95_metric': 5.1860809326171875} +Cheakpoint... +Epoch [2280/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719667434692383, 'Val/mean miou_metric': 0.9561467170715332, 'Val/mean f1': 0.9751465916633606, 'Val/mean precision': 0.973613440990448, 'Val/mean recall': 0.9766844511032104, 'Val/mean hd95_metric': 5.1860809326171875} +Epoch [2281/4000] Training [1/16] Loss: 0.00445 +Epoch [2281/4000] Training [2/16] Loss: 0.00510 +Epoch [2281/4000] Training [3/16] Loss: 0.00503 +Epoch [2281/4000] Training [4/16] Loss: 0.00534 +Epoch [2281/4000] Training [5/16] Loss: 0.00870 +Epoch [2281/4000] Training [6/16] Loss: 0.00463 +Epoch [2281/4000] Training [7/16] Loss: 0.00641 +Epoch [2281/4000] Training [8/16] Loss: 0.00479 +Epoch [2281/4000] Training [9/16] Loss: 0.00386 +Epoch [2281/4000] Training [10/16] Loss: 0.00385 +Epoch [2281/4000] Training [11/16] Loss: 0.00534 +Epoch [2281/4000] Training [12/16] Loss: 0.00765 +Epoch [2281/4000] Training [13/16] Loss: 0.00494 +Epoch [2281/4000] Training [14/16] Loss: 0.00387 +Epoch [2281/4000] Training [15/16] Loss: 0.00499 +Epoch [2281/4000] Training [16/16] Loss: 0.00599 +Epoch [2281/4000] Training metric {'Train/mean dice_metric': 0.9966374635696411, 'Train/mean miou_metric': 0.9930341243743896, 'Train/mean f1': 0.9922942519187927, 'Train/mean precision': 0.9877620935440063, 'Train/mean recall': 0.9968681931495667, 'Train/mean hd95_metric': 0.9873660802841187} +Epoch [2281/4000] Validation [1/4] Loss: 0.29828 focal_loss 0.22319 dice_loss 0.07510 +Epoch [2281/4000] Validation [2/4] Loss: 0.66479 focal_loss 0.46985 dice_loss 0.19493 +Epoch [2281/4000] Validation [3/4] Loss: 0.39090 focal_loss 0.29588 dice_loss 0.09502 +Epoch [2281/4000] Validation [4/4] Loss: 0.35129 focal_loss 0.22726 dice_loss 0.12403 +Epoch [2281/4000] Validation metric {'Val/mean dice_metric': 0.9728175401687622, 'Val/mean miou_metric': 0.957072913646698, 'Val/mean f1': 0.9747656583786011, 'Val/mean precision': 0.9719787240028381, 'Val/mean recall': 0.9775686860084534, 'Val/mean hd95_metric': 4.994866371154785} +Cheakpoint... +Epoch [2281/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728175401687622, 'Val/mean miou_metric': 0.957072913646698, 'Val/mean f1': 0.9747656583786011, 'Val/mean precision': 0.9719787240028381, 'Val/mean recall': 0.9775686860084534, 'Val/mean hd95_metric': 4.994866371154785} +Epoch [2282/4000] Training [1/16] Loss: 0.00527 +Epoch [2282/4000] Training [2/16] Loss: 0.00364 +Epoch [2282/4000] Training [3/16] Loss: 0.00425 +Epoch [2282/4000] Training [4/16] Loss: 0.00488 +Epoch [2282/4000] Training [5/16] Loss: 0.00437 +Epoch [2282/4000] Training [6/16] Loss: 0.00520 +Epoch [2282/4000] Training [7/16] Loss: 0.00579 +Epoch [2282/4000] Training [8/16] Loss: 0.00427 +Epoch [2282/4000] Training [9/16] Loss: 0.00442 +Epoch [2282/4000] Training [10/16] Loss: 0.00413 +Epoch [2282/4000] Training [11/16] Loss: 0.00643 +Epoch [2282/4000] Training [12/16] Loss: 0.00447 +Epoch [2282/4000] Training [13/16] Loss: 0.00367 +Epoch [2282/4000] Training [14/16] Loss: 0.00420 +Epoch [2282/4000] Training [15/16] Loss: 0.00491 +Epoch [2282/4000] Training [16/16] Loss: 0.00556 +Epoch [2282/4000] Training metric {'Train/mean dice_metric': 0.9968981146812439, 'Train/mean miou_metric': 0.9935187101364136, 'Train/mean f1': 0.9920564293861389, 'Train/mean precision': 0.9872245788574219, 'Train/mean recall': 0.9969358444213867, 'Train/mean hd95_metric': 0.9876110553741455} +Epoch [2282/4000] Validation [1/4] Loss: 0.33474 focal_loss 0.26788 dice_loss 0.06686 +Epoch [2282/4000] Validation [2/4] Loss: 0.30582 focal_loss 0.20202 dice_loss 0.10380 +Epoch [2282/4000] Validation [3/4] Loss: 0.37351 focal_loss 0.28457 dice_loss 0.08894 +Epoch [2282/4000] Validation [4/4] Loss: 0.29305 focal_loss 0.19580 dice_loss 0.09725 +Epoch [2282/4000] Validation metric {'Val/mean dice_metric': 0.973889946937561, 'Val/mean miou_metric': 0.9579204320907593, 'Val/mean f1': 0.9745442867279053, 'Val/mean precision': 0.972183346748352, 'Val/mean recall': 0.9769166707992554, 'Val/mean hd95_metric': 5.674487590789795} +Cheakpoint... +Epoch [2282/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973889946937561, 'Val/mean miou_metric': 0.9579204320907593, 'Val/mean f1': 0.9745442867279053, 'Val/mean precision': 0.972183346748352, 'Val/mean recall': 0.9769166707992554, 'Val/mean hd95_metric': 5.674487590789795} +Epoch [2283/4000] Training [1/16] Loss: 0.00547 +Epoch [2283/4000] Training [2/16] Loss: 0.00419 +Epoch [2283/4000] Training [3/16] Loss: 0.00637 +Epoch [2283/4000] Training [4/16] Loss: 0.00446 +Epoch [2283/4000] Training [5/16] Loss: 0.00666 +Epoch [2283/4000] Training [6/16] Loss: 0.00429 +Epoch [2283/4000] Training [7/16] Loss: 0.00491 +Epoch [2283/4000] Training [8/16] Loss: 0.00440 +Epoch [2283/4000] Training [9/16] Loss: 0.00601 +Epoch [2283/4000] Training [10/16] Loss: 0.00516 +Epoch [2283/4000] Training [11/16] Loss: 0.00541 +Epoch [2283/4000] Training [12/16] Loss: 0.00435 +Epoch [2283/4000] Training [13/16] Loss: 0.00389 +Epoch [2283/4000] Training [14/16] Loss: 0.00443 +Epoch [2283/4000] Training [15/16] Loss: 0.00508 +Epoch [2283/4000] Training [16/16] Loss: 0.00568 +Epoch [2283/4000] Training metric {'Train/mean dice_metric': 0.9967635869979858, 'Train/mean miou_metric': 0.9932746887207031, 'Train/mean f1': 0.9922775030136108, 'Train/mean precision': 0.9876445531845093, 'Train/mean recall': 0.996954083442688, 'Train/mean hd95_metric': 0.9940712451934814} +Epoch [2283/4000] Validation [1/4] Loss: 0.33278 focal_loss 0.25627 dice_loss 0.07651 +Epoch [2283/4000] Validation [2/4] Loss: 0.32529 focal_loss 0.22059 dice_loss 0.10470 +Epoch [2283/4000] Validation [3/4] Loss: 0.40125 focal_loss 0.30192 dice_loss 0.09933 +Epoch [2283/4000] Validation [4/4] Loss: 0.36946 focal_loss 0.24437 dice_loss 0.12508 +Epoch [2283/4000] Validation metric {'Val/mean dice_metric': 0.9735199809074402, 'Val/mean miou_metric': 0.9575239419937134, 'Val/mean f1': 0.97552090883255, 'Val/mean precision': 0.9729753136634827, 'Val/mean recall': 0.9780799746513367, 'Val/mean hd95_metric': 5.733668327331543} +Cheakpoint... +Epoch [2283/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735199809074402, 'Val/mean miou_metric': 0.9575239419937134, 'Val/mean f1': 0.97552090883255, 'Val/mean precision': 0.9729753136634827, 'Val/mean recall': 0.9780799746513367, 'Val/mean hd95_metric': 5.733668327331543} +Epoch [2284/4000] Training [1/16] Loss: 0.00503 +Epoch [2284/4000] Training [2/16] Loss: 0.00647 +Epoch [2284/4000] Training [3/16] Loss: 0.00444 +Epoch [2284/4000] Training [4/16] Loss: 0.00502 +Epoch [2284/4000] Training [5/16] Loss: 0.00530 +Epoch [2284/4000] Training [6/16] Loss: 0.00484 +Epoch [2284/4000] Training [7/16] Loss: 0.00371 +Epoch [2284/4000] Training [8/16] Loss: 0.00593 +Epoch [2284/4000] Training [9/16] Loss: 0.00759 +Epoch [2284/4000] Training [10/16] Loss: 0.00635 +Epoch [2284/4000] Training [11/16] Loss: 0.00491 +Epoch [2284/4000] Training [12/16] Loss: 0.00454 +Epoch [2284/4000] Training [13/16] Loss: 0.00454 +Epoch [2284/4000] Training [14/16] Loss: 0.00407 +Epoch [2284/4000] Training [15/16] Loss: 0.00464 +Epoch [2284/4000] Training [16/16] Loss: 0.00552 +Epoch [2284/4000] Training metric {'Train/mean dice_metric': 0.9967900514602661, 'Train/mean miou_metric': 0.9933292865753174, 'Train/mean f1': 0.9922361969947815, 'Train/mean precision': 0.9876028895378113, 'Train/mean recall': 0.9969131946563721, 'Train/mean hd95_metric': 0.9866765737533569} +Epoch [2284/4000] Validation [1/4] Loss: 0.30919 focal_loss 0.23938 dice_loss 0.06981 +Epoch [2284/4000] Validation [2/4] Loss: 0.51760 focal_loss 0.37419 dice_loss 0.14341 +Epoch [2284/4000] Validation [3/4] Loss: 0.38506 focal_loss 0.29648 dice_loss 0.08858 +Epoch [2284/4000] Validation [4/4] Loss: 0.25848 focal_loss 0.16068 dice_loss 0.09780 +Epoch [2284/4000] Validation metric {'Val/mean dice_metric': 0.9743175506591797, 'Val/mean miou_metric': 0.9581006765365601, 'Val/mean f1': 0.9754185080528259, 'Val/mean precision': 0.9715744256973267, 'Val/mean recall': 0.9792931079864502, 'Val/mean hd95_metric': 5.34790563583374} +Cheakpoint... +Epoch [2284/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743175506591797, 'Val/mean miou_metric': 0.9581006765365601, 'Val/mean f1': 0.9754185080528259, 'Val/mean precision': 0.9715744256973267, 'Val/mean recall': 0.9792931079864502, 'Val/mean hd95_metric': 5.34790563583374} +Epoch [2285/4000] Training [1/16] Loss: 0.00493 +Epoch [2285/4000] Training [2/16] Loss: 0.00494 +Epoch [2285/4000] Training [3/16] Loss: 0.00530 +Epoch [2285/4000] Training [4/16] Loss: 0.00394 +Epoch [2285/4000] Training [5/16] Loss: 0.00694 +Epoch [2285/4000] Training [6/16] Loss: 0.00462 +Epoch [2285/4000] Training [7/16] Loss: 0.00335 +Epoch [2285/4000] Training [8/16] Loss: 0.00349 +Epoch [2285/4000] Training [9/16] Loss: 0.00485 +Epoch [2285/4000] Training [10/16] Loss: 0.00482 +Epoch [2285/4000] Training [11/16] Loss: 0.00904 +Epoch [2285/4000] Training [12/16] Loss: 0.00431 +Epoch [2285/4000] Training [13/16] Loss: 0.00499 +Epoch [2285/4000] Training [14/16] Loss: 0.00373 +Epoch [2285/4000] Training [15/16] Loss: 0.00430 +Epoch [2285/4000] Training [16/16] Loss: 0.00573 +Epoch [2285/4000] Training metric {'Train/mean dice_metric': 0.9969639778137207, 'Train/mean miou_metric': 0.9936662912368774, 'Train/mean f1': 0.9923627972602844, 'Train/mean precision': 0.987742006778717, 'Train/mean recall': 0.9970270395278931, 'Train/mean hd95_metric': 0.9860109090805054} +Epoch [2285/4000] Validation [1/4] Loss: 0.34942 focal_loss 0.28112 dice_loss 0.06830 +Epoch [2285/4000] Validation [2/4] Loss: 0.58552 focal_loss 0.38631 dice_loss 0.19921 +Epoch [2285/4000] Validation [3/4] Loss: 0.38410 focal_loss 0.29713 dice_loss 0.08697 +Epoch [2285/4000] Validation [4/4] Loss: 0.28308 focal_loss 0.18477 dice_loss 0.09831 +Epoch [2285/4000] Validation metric {'Val/mean dice_metric': 0.9751390218734741, 'Val/mean miou_metric': 0.9598882794380188, 'Val/mean f1': 0.975529670715332, 'Val/mean precision': 0.9711847305297852, 'Val/mean recall': 0.9799135327339172, 'Val/mean hd95_metric': 5.209593296051025} +Cheakpoint... +Epoch [2285/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751390218734741, 'Val/mean miou_metric': 0.9598882794380188, 'Val/mean f1': 0.975529670715332, 'Val/mean precision': 0.9711847305297852, 'Val/mean recall': 0.9799135327339172, 'Val/mean hd95_metric': 5.209593296051025} +Epoch [2286/4000] Training [1/16] Loss: 0.00372 +Epoch [2286/4000] Training [2/16] Loss: 0.00542 +Epoch [2286/4000] Training [3/16] Loss: 0.00635 +Epoch [2286/4000] Training [4/16] Loss: 0.00315 +Epoch [2286/4000] Training [5/16] Loss: 0.00486 +Epoch [2286/4000] Training [6/16] Loss: 0.00541 +Epoch [2286/4000] Training [7/16] Loss: 0.00405 +Epoch [2286/4000] Training [8/16] Loss: 0.00562 +Epoch [2286/4000] Training [9/16] Loss: 0.00588 +Epoch [2286/4000] Training [10/16] Loss: 0.00341 +Epoch [2286/4000] Training [11/16] Loss: 0.00472 +Epoch [2286/4000] Training [12/16] Loss: 0.00625 +Epoch [2286/4000] Training [13/16] Loss: 0.00546 +Epoch [2286/4000] Training [14/16] Loss: 0.00493 +Epoch [2286/4000] Training [15/16] Loss: 0.00569 +Epoch [2286/4000] Training [16/16] Loss: 0.00553 +Epoch [2286/4000] Training metric {'Train/mean dice_metric': 0.996726393699646, 'Train/mean miou_metric': 0.9932132363319397, 'Train/mean f1': 0.9923413991928101, 'Train/mean precision': 0.9879364967346191, 'Train/mean recall': 0.9967857003211975, 'Train/mean hd95_metric': 0.9777482748031616} +Epoch [2286/4000] Validation [1/4] Loss: 0.29154 focal_loss 0.22941 dice_loss 0.06212 +Epoch [2286/4000] Validation [2/4] Loss: 0.34283 focal_loss 0.22631 dice_loss 0.11652 +Epoch [2286/4000] Validation [3/4] Loss: 0.42748 focal_loss 0.32928 dice_loss 0.09821 +Epoch [2286/4000] Validation [4/4] Loss: 0.33438 focal_loss 0.22578 dice_loss 0.10860 +Epoch [2286/4000] Validation metric {'Val/mean dice_metric': 0.9730556607246399, 'Val/mean miou_metric': 0.9574307203292847, 'Val/mean f1': 0.9755564332008362, 'Val/mean precision': 0.9722132682800293, 'Val/mean recall': 0.9789225459098816, 'Val/mean hd95_metric': 5.738622188568115} +Cheakpoint... +Epoch [2286/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730556607246399, 'Val/mean miou_metric': 0.9574307203292847, 'Val/mean f1': 0.9755564332008362, 'Val/mean precision': 0.9722132682800293, 'Val/mean recall': 0.9789225459098816, 'Val/mean hd95_metric': 5.738622188568115} +Epoch [2287/4000] Training [1/16] Loss: 0.00606 +Epoch [2287/4000] Training [2/16] Loss: 0.00532 +Epoch [2287/4000] Training [3/16] Loss: 0.00599 +Epoch [2287/4000] Training [4/16] Loss: 0.00456 +Epoch [2287/4000] Training [5/16] Loss: 0.00563 +Epoch [2287/4000] Training [6/16] Loss: 0.00516 +Epoch [2287/4000] Training [7/16] Loss: 0.00557 +Epoch [2287/4000] Training [8/16] Loss: 0.00703 +Epoch [2287/4000] Training [9/16] Loss: 0.00458 +Epoch [2287/4000] Training [10/16] Loss: 0.00808 +Epoch [2287/4000] Training [11/16] Loss: 0.00398 +Epoch [2287/4000] Training [12/16] Loss: 0.00545 +Epoch [2287/4000] Training [13/16] Loss: 0.00392 +Epoch [2287/4000] Training [14/16] Loss: 0.00584 +Epoch [2287/4000] Training [15/16] Loss: 0.00486 +Epoch [2287/4000] Training [16/16] Loss: 0.00479 +Epoch [2287/4000] Training metric {'Train/mean dice_metric': 0.9966527223587036, 'Train/mean miou_metric': 0.9930458068847656, 'Train/mean f1': 0.9919982552528381, 'Train/mean precision': 0.9872951507568359, 'Train/mean recall': 0.9967464208602905, 'Train/mean hd95_metric': 0.9913923740386963} +Epoch [2287/4000] Validation [1/4] Loss: 0.28720 focal_loss 0.22206 dice_loss 0.06514 +Epoch [2287/4000] Validation [2/4] Loss: 0.30094 focal_loss 0.19515 dice_loss 0.10579 +Epoch [2287/4000] Validation [3/4] Loss: 0.36824 focal_loss 0.27908 dice_loss 0.08915 +Epoch [2287/4000] Validation [4/4] Loss: 0.27273 focal_loss 0.17628 dice_loss 0.09645 +Epoch [2287/4000] Validation metric {'Val/mean dice_metric': 0.9752958416938782, 'Val/mean miou_metric': 0.9591243863105774, 'Val/mean f1': 0.9750075340270996, 'Val/mean precision': 0.972910463809967, 'Val/mean recall': 0.9771136045455933, 'Val/mean hd95_metric': 5.3081374168396} +Cheakpoint... +Epoch [2287/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752958416938782, 'Val/mean miou_metric': 0.9591243863105774, 'Val/mean f1': 0.9750075340270996, 'Val/mean precision': 0.972910463809967, 'Val/mean recall': 0.9771136045455933, 'Val/mean hd95_metric': 5.3081374168396} +Epoch [2288/4000] Training [1/16] Loss: 0.00444 +Epoch [2288/4000] Training [2/16] Loss: 0.00524 +Epoch [2288/4000] Training [3/16] Loss: 0.00504 +Epoch [2288/4000] Training [4/16] Loss: 0.00484 +Epoch [2288/4000] Training [5/16] Loss: 0.00386 +Epoch [2288/4000] Training [6/16] Loss: 0.00385 +Epoch [2288/4000] Training [7/16] Loss: 0.00509 +Epoch [2288/4000] Training [8/16] Loss: 0.00572 +Epoch [2288/4000] Training [9/16] Loss: 0.00457 +Epoch [2288/4000] Training [10/16] Loss: 0.00515 +Epoch [2288/4000] Training [11/16] Loss: 0.00796 +Epoch [2288/4000] Training [12/16] Loss: 0.00747 +Epoch [2288/4000] Training [13/16] Loss: 0.00651 +Epoch [2288/4000] Training [14/16] Loss: 0.00525 +Epoch [2288/4000] Training [15/16] Loss: 0.00499 +Epoch [2288/4000] Training [16/16] Loss: 0.00657 +Epoch [2288/4000] Training metric {'Train/mean dice_metric': 0.9964271187782288, 'Train/mean miou_metric': 0.9926319718360901, 'Train/mean f1': 0.9918568134307861, 'Train/mean precision': 0.9875329732894897, 'Train/mean recall': 0.9962188601493835, 'Train/mean hd95_metric': 1.0560952425003052} +Epoch [2288/4000] Validation [1/4] Loss: 0.31618 focal_loss 0.25334 dice_loss 0.06284 +Epoch [2288/4000] Validation [2/4] Loss: 0.28566 focal_loss 0.17871 dice_loss 0.10695 +Epoch [2288/4000] Validation [3/4] Loss: 0.38571 focal_loss 0.29374 dice_loss 0.09197 +Epoch [2288/4000] Validation [4/4] Loss: 0.40673 focal_loss 0.27710 dice_loss 0.12963 +Epoch [2288/4000] Validation metric {'Val/mean dice_metric': 0.9743574261665344, 'Val/mean miou_metric': 0.9580421447753906, 'Val/mean f1': 0.9755187630653381, 'Val/mean precision': 0.9701254367828369, 'Val/mean recall': 0.980972409248352, 'Val/mean hd95_metric': 5.920012950897217} +Cheakpoint... +Epoch [2288/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743574261665344, 'Val/mean miou_metric': 0.9580421447753906, 'Val/mean f1': 0.9755187630653381, 'Val/mean precision': 0.9701254367828369, 'Val/mean recall': 0.980972409248352, 'Val/mean hd95_metric': 5.920012950897217} +Epoch [2289/4000] Training [1/16] Loss: 0.00453 +Epoch [2289/4000] Training [2/16] Loss: 0.00450 +Epoch [2289/4000] Training [3/16] Loss: 0.00540 +Epoch [2289/4000] Training [4/16] Loss: 0.00494 +Epoch [2289/4000] Training [5/16] Loss: 0.00898 +Epoch [2289/4000] Training [6/16] Loss: 0.00517 +Epoch [2289/4000] Training [7/16] Loss: 0.00368 +Epoch [2289/4000] Training [8/16] Loss: 0.00460 +Epoch [2289/4000] Training [9/16] Loss: 0.00504 +Epoch [2289/4000] Training [10/16] Loss: 0.00473 +Epoch [2289/4000] Training [11/16] Loss: 0.00576 +Epoch [2289/4000] Training [12/16] Loss: 0.00586 +Epoch [2289/4000] Training [13/16] Loss: 0.00571 +Epoch [2289/4000] Training [14/16] Loss: 0.00412 +Epoch [2289/4000] Training [15/16] Loss: 0.00547 +Epoch [2289/4000] Training [16/16] Loss: 0.00432 +Epoch [2289/4000] Training metric {'Train/mean dice_metric': 0.9967910051345825, 'Train/mean miou_metric': 0.9933193922042847, 'Train/mean f1': 0.9920268058776855, 'Train/mean precision': 0.9873209595680237, 'Train/mean recall': 0.9967777132987976, 'Train/mean hd95_metric': 1.0337519645690918} +Epoch [2289/4000] Validation [1/4] Loss: 0.26688 focal_loss 0.20620 dice_loss 0.06068 +Epoch [2289/4000] Validation [2/4] Loss: 0.29214 focal_loss 0.18295 dice_loss 0.10919 +Epoch [2289/4000] Validation [3/4] Loss: 0.23422 focal_loss 0.16119 dice_loss 0.07303 +Epoch [2289/4000] Validation [4/4] Loss: 0.32219 focal_loss 0.20343 dice_loss 0.11875 +Epoch [2289/4000] Validation metric {'Val/mean dice_metric': 0.9733295440673828, 'Val/mean miou_metric': 0.9577722549438477, 'Val/mean f1': 0.9751322865486145, 'Val/mean precision': 0.970523476600647, 'Val/mean recall': 0.979785144329071, 'Val/mean hd95_metric': 6.091308116912842} +Cheakpoint... +Epoch [2289/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733295440673828, 'Val/mean miou_metric': 0.9577722549438477, 'Val/mean f1': 0.9751322865486145, 'Val/mean precision': 0.970523476600647, 'Val/mean recall': 0.979785144329071, 'Val/mean hd95_metric': 6.091308116912842} +Epoch [2290/4000] Training [1/16] Loss: 0.00606 +Epoch [2290/4000] Training [2/16] Loss: 0.00484 +Epoch [2290/4000] Training [3/16] Loss: 0.00587 +Epoch [2290/4000] Training [4/16] Loss: 0.00498 +Epoch [2290/4000] Training [5/16] Loss: 0.00394 +Epoch [2290/4000] Training [6/16] Loss: 0.00558 +Epoch [2290/4000] Training [7/16] Loss: 0.01482 +Epoch [2290/4000] Training [8/16] Loss: 0.00546 +Epoch [2290/4000] Training [9/16] Loss: 0.00807 +Epoch [2290/4000] Training [10/16] Loss: 0.00498 +Epoch [2290/4000] Training [11/16] Loss: 0.00365 +Epoch [2290/4000] Training [12/16] Loss: 0.00702 +Epoch [2290/4000] Training [13/16] Loss: 0.00561 +Epoch [2290/4000] Training [14/16] Loss: 0.00534 +Epoch [2290/4000] Training [15/16] Loss: 0.00544 +Epoch [2290/4000] Training [16/16] Loss: 0.00611 +Epoch [2290/4000] Training metric {'Train/mean dice_metric': 0.9963536262512207, 'Train/mean miou_metric': 0.9924814701080322, 'Train/mean f1': 0.991538405418396, 'Train/mean precision': 0.9866633415222168, 'Train/mean recall': 0.9964618682861328, 'Train/mean hd95_metric': 1.1344375610351562} +Epoch [2290/4000] Validation [1/4] Loss: 0.26955 focal_loss 0.20404 dice_loss 0.06551 +Epoch [2290/4000] Validation [2/4] Loss: 0.32001 focal_loss 0.20505 dice_loss 0.11496 +Epoch [2290/4000] Validation [3/4] Loss: 0.17624 focal_loss 0.12247 dice_loss 0.05377 +Epoch [2290/4000] Validation [4/4] Loss: 0.24842 focal_loss 0.16354 dice_loss 0.08487 +Epoch [2290/4000] Validation metric {'Val/mean dice_metric': 0.9733213186264038, 'Val/mean miou_metric': 0.9575549364089966, 'Val/mean f1': 0.975092351436615, 'Val/mean precision': 0.9737913012504578, 'Val/mean recall': 0.976396918296814, 'Val/mean hd95_metric': 5.132172584533691} +Cheakpoint... +Epoch [2290/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733213186264038, 'Val/mean miou_metric': 0.9575549364089966, 'Val/mean f1': 0.975092351436615, 'Val/mean precision': 0.9737913012504578, 'Val/mean recall': 0.976396918296814, 'Val/mean hd95_metric': 5.132172584533691} +Epoch [2291/4000] Training [1/16] Loss: 0.00528 +Epoch [2291/4000] Training [2/16] Loss: 0.00411 +Epoch [2291/4000] Training [3/16] Loss: 0.00581 +Epoch [2291/4000] Training [4/16] Loss: 0.00492 +Epoch [2291/4000] Training [5/16] Loss: 0.00567 +Epoch [2291/4000] Training [6/16] Loss: 0.00382 +Epoch [2291/4000] Training [7/16] Loss: 0.00670 +Epoch [2291/4000] Training [8/16] Loss: 0.00506 +Epoch [2291/4000] Training [9/16] Loss: 0.00432 +Epoch [2291/4000] Training [10/16] Loss: 0.00355 +Epoch [2291/4000] Training [11/16] Loss: 0.00749 +Epoch [2291/4000] Training [12/16] Loss: 0.00567 +Epoch [2291/4000] Training [13/16] Loss: 0.00477 +Epoch [2291/4000] Training [14/16] Loss: 0.00652 +Epoch [2291/4000] Training [15/16] Loss: 0.00717 +Epoch [2291/4000] Training [16/16] Loss: 0.00473 +Epoch [2291/4000] Training metric {'Train/mean dice_metric': 0.9966630339622498, 'Train/mean miou_metric': 0.9930633306503296, 'Train/mean f1': 0.9919136762619019, 'Train/mean precision': 0.9870402216911316, 'Train/mean recall': 0.9968355298042297, 'Train/mean hd95_metric': 0.9896694421768188} +Epoch [2291/4000] Validation [1/4] Loss: 0.24783 focal_loss 0.18555 dice_loss 0.06228 +Epoch [2291/4000] Validation [2/4] Loss: 0.31912 focal_loss 0.19815 dice_loss 0.12098 +Epoch [2291/4000] Validation [3/4] Loss: 0.19500 focal_loss 0.13793 dice_loss 0.05707 +Epoch [2291/4000] Validation [4/4] Loss: 0.26657 focal_loss 0.17483 dice_loss 0.09174 +Epoch [2291/4000] Validation metric {'Val/mean dice_metric': 0.9728981852531433, 'Val/mean miou_metric': 0.9571323394775391, 'Val/mean f1': 0.9747220873832703, 'Val/mean precision': 0.9742089509963989, 'Val/mean recall': 0.9752358198165894, 'Val/mean hd95_metric': 4.99536657333374} +Cheakpoint... +Epoch [2291/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728981852531433, 'Val/mean miou_metric': 0.9571323394775391, 'Val/mean f1': 0.9747220873832703, 'Val/mean precision': 0.9742089509963989, 'Val/mean recall': 0.9752358198165894, 'Val/mean hd95_metric': 4.99536657333374} +Epoch [2292/4000] Training [1/16] Loss: 0.00388 +Epoch [2292/4000] Training [2/16] Loss: 0.00397 +Epoch [2292/4000] Training [3/16] Loss: 0.00556 +Epoch [2292/4000] Training [4/16] Loss: 0.00634 +Epoch [2292/4000] Training [5/16] Loss: 0.00656 +Epoch [2292/4000] Training [6/16] Loss: 0.00559 +Epoch [2292/4000] Training [7/16] Loss: 0.00654 +Epoch [2292/4000] Training [8/16] Loss: 0.00382 +Epoch [2292/4000] Training [9/16] Loss: 0.00445 +Epoch [2292/4000] Training [10/16] Loss: 0.00518 +Epoch [2292/4000] Training [11/16] Loss: 0.00380 +Epoch [2292/4000] Training [12/16] Loss: 0.00422 +Epoch [2292/4000] Training [13/16] Loss: 0.00497 +Epoch [2292/4000] Training [14/16] Loss: 0.00534 +Epoch [2292/4000] Training [15/16] Loss: 0.00383 +Epoch [2292/4000] Training [16/16] Loss: 0.00493 +Epoch [2292/4000] Training metric {'Train/mean dice_metric': 0.9968467354774475, 'Train/mean miou_metric': 0.9934300780296326, 'Train/mean f1': 0.9921305775642395, 'Train/mean precision': 0.987447202205658, 'Train/mean recall': 0.996858537197113, 'Train/mean hd95_metric': 0.9966525435447693} +Epoch [2292/4000] Validation [1/4] Loss: 0.29931 focal_loss 0.23452 dice_loss 0.06479 +Epoch [2292/4000] Validation [2/4] Loss: 0.80710 focal_loss 0.61454 dice_loss 0.19256 +Epoch [2292/4000] Validation [3/4] Loss: 0.37113 focal_loss 0.27697 dice_loss 0.09416 +Epoch [2292/4000] Validation [4/4] Loss: 0.26544 focal_loss 0.16044 dice_loss 0.10501 +Epoch [2292/4000] Validation metric {'Val/mean dice_metric': 0.9725418090820312, 'Val/mean miou_metric': 0.9567548036575317, 'Val/mean f1': 0.9749962091445923, 'Val/mean precision': 0.9728689193725586, 'Val/mean recall': 0.9771327376365662, 'Val/mean hd95_metric': 5.143707275390625} +Cheakpoint... +Epoch [2292/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725418090820312, 'Val/mean miou_metric': 0.9567548036575317, 'Val/mean f1': 0.9749962091445923, 'Val/mean precision': 0.9728689193725586, 'Val/mean recall': 0.9771327376365662, 'Val/mean hd95_metric': 5.143707275390625} +Epoch [2293/4000] Training [1/16] Loss: 0.00509 +Epoch [2293/4000] Training [2/16] Loss: 0.00487 +Epoch [2293/4000] Training [3/16] Loss: 0.00403 +Epoch [2293/4000] Training [4/16] Loss: 0.00441 +Epoch [2293/4000] Training [5/16] Loss: 0.00474 +Epoch [2293/4000] Training [6/16] Loss: 0.00502 +Epoch [2293/4000] Training [7/16] Loss: 0.00408 +Epoch [2293/4000] Training [8/16] Loss: 0.00591 +Epoch [2293/4000] Training [9/16] Loss: 0.00543 +Epoch [2293/4000] Training [10/16] Loss: 0.00363 +Epoch [2293/4000] Training [11/16] Loss: 0.00616 +Epoch [2293/4000] Training [12/16] Loss: 0.00492 +Epoch [2293/4000] Training [13/16] Loss: 0.00399 +Epoch [2293/4000] Training [14/16] Loss: 0.00604 +Epoch [2293/4000] Training [15/16] Loss: 0.00374 +Epoch [2293/4000] Training [16/16] Loss: 0.00450 +Epoch [2293/4000] Training metric {'Train/mean dice_metric': 0.9967894554138184, 'Train/mean miou_metric': 0.9933327436447144, 'Train/mean f1': 0.9922766089439392, 'Train/mean precision': 0.9876964688301086, 'Train/mean recall': 0.9968993663787842, 'Train/mean hd95_metric': 0.9747589826583862} +Epoch [2293/4000] Validation [1/4] Loss: 0.32349 focal_loss 0.25722 dice_loss 0.06627 +Epoch [2293/4000] Validation [2/4] Loss: 0.83695 focal_loss 0.63477 dice_loss 0.20218 +Epoch [2293/4000] Validation [3/4] Loss: 0.39215 focal_loss 0.29932 dice_loss 0.09283 +Epoch [2293/4000] Validation [4/4] Loss: 0.26690 focal_loss 0.18433 dice_loss 0.08257 +Epoch [2293/4000] Validation metric {'Val/mean dice_metric': 0.9737281799316406, 'Val/mean miou_metric': 0.9582535028457642, 'Val/mean f1': 0.9755578637123108, 'Val/mean precision': 0.972109854221344, 'Val/mean recall': 0.9790304899215698, 'Val/mean hd95_metric': 5.35744047164917} +Cheakpoint... +Epoch [2293/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737281799316406, 'Val/mean miou_metric': 0.9582535028457642, 'Val/mean f1': 0.9755578637123108, 'Val/mean precision': 0.972109854221344, 'Val/mean recall': 0.9790304899215698, 'Val/mean hd95_metric': 5.35744047164917} +Epoch [2294/4000] Training [1/16] Loss: 0.00669 +Epoch [2294/4000] Training [2/16] Loss: 0.00600 +Epoch [2294/4000] Training [3/16] Loss: 0.00575 +Epoch [2294/4000] Training [4/16] Loss: 0.00511 +Epoch [2294/4000] Training [5/16] Loss: 0.00364 +Epoch [2294/4000] Training [6/16] Loss: 0.00515 +Epoch [2294/4000] Training [7/16] Loss: 0.00392 +Epoch [2294/4000] Training [8/16] Loss: 0.00548 +Epoch [2294/4000] Training [9/16] Loss: 0.00440 +Epoch [2294/4000] Training [10/16] Loss: 0.00520 +Epoch [2294/4000] Training [11/16] Loss: 0.00522 +Epoch [2294/4000] Training [12/16] Loss: 0.00582 +Epoch [2294/4000] Training [13/16] Loss: 0.00521 +Epoch [2294/4000] Training [14/16] Loss: 0.00419 +Epoch [2294/4000] Training [15/16] Loss: 0.00526 +Epoch [2294/4000] Training [16/16] Loss: 0.00389 +Epoch [2294/4000] Training metric {'Train/mean dice_metric': 0.9968060255050659, 'Train/mean miou_metric': 0.9933664798736572, 'Train/mean f1': 0.992469072341919, 'Train/mean precision': 0.9879242181777954, 'Train/mean recall': 0.9970559477806091, 'Train/mean hd95_metric': 0.9908597469329834} +Epoch [2294/4000] Validation [1/4] Loss: 0.39648 focal_loss 0.29563 dice_loss 0.10085 +Epoch [2294/4000] Validation [2/4] Loss: 0.36386 focal_loss 0.23940 dice_loss 0.12445 +Epoch [2294/4000] Validation [3/4] Loss: 0.39812 focal_loss 0.30459 dice_loss 0.09352 +Epoch [2294/4000] Validation [4/4] Loss: 0.42778 focal_loss 0.29921 dice_loss 0.12857 +Epoch [2294/4000] Validation metric {'Val/mean dice_metric': 0.9721202850341797, 'Val/mean miou_metric': 0.955734133720398, 'Val/mean f1': 0.9743446111679077, 'Val/mean precision': 0.9733434319496155, 'Val/mean recall': 0.9753478765487671, 'Val/mean hd95_metric': 5.751251220703125} +Cheakpoint... +Epoch [2294/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721202850341797, 'Val/mean miou_metric': 0.955734133720398, 'Val/mean f1': 0.9743446111679077, 'Val/mean precision': 0.9733434319496155, 'Val/mean recall': 0.9753478765487671, 'Val/mean hd95_metric': 5.751251220703125} +Epoch [2295/4000] Training [1/16] Loss: 0.00402 +Epoch [2295/4000] Training [2/16] Loss: 0.00469 +Epoch [2295/4000] Training [3/16] Loss: 0.00438 +Epoch [2295/4000] Training [4/16] Loss: 0.00569 +Epoch [2295/4000] Training [5/16] Loss: 0.00499 +Epoch [2295/4000] Training [6/16] Loss: 0.00522 +Epoch [2295/4000] Training [7/16] Loss: 0.00403 +Epoch [2295/4000] Training [8/16] Loss: 0.00663 +Epoch [2295/4000] Training [9/16] Loss: 0.00492 +Epoch [2295/4000] Training [10/16] Loss: 0.00565 +Epoch [2295/4000] Training [11/16] Loss: 0.00521 +Epoch [2295/4000] Training [12/16] Loss: 0.00391 +Epoch [2295/4000] Training [13/16] Loss: 0.00465 +Epoch [2295/4000] Training [14/16] Loss: 0.00422 +Epoch [2295/4000] Training [15/16] Loss: 0.00419 +Epoch [2295/4000] Training [16/16] Loss: 0.00458 +Epoch [2295/4000] Training metric {'Train/mean dice_metric': 0.9968725442886353, 'Train/mean miou_metric': 0.993495523929596, 'Train/mean f1': 0.9923837780952454, 'Train/mean precision': 0.9878283739089966, 'Train/mean recall': 0.9969813823699951, 'Train/mean hd95_metric': 0.9835002422332764} +Epoch [2295/4000] Validation [1/4] Loss: 0.30182 focal_loss 0.23676 dice_loss 0.06506 +Epoch [2295/4000] Validation [2/4] Loss: 0.30540 focal_loss 0.19322 dice_loss 0.11218 +Epoch [2295/4000] Validation [3/4] Loss: 0.40777 focal_loss 0.31631 dice_loss 0.09147 +Epoch [2295/4000] Validation [4/4] Loss: 0.24892 focal_loss 0.15600 dice_loss 0.09292 +Epoch [2295/4000] Validation metric {'Val/mean dice_metric': 0.9710386395454407, 'Val/mean miou_metric': 0.9552332162857056, 'Val/mean f1': 0.9737681746482849, 'Val/mean precision': 0.9719659090042114, 'Val/mean recall': 0.9755770564079285, 'Val/mean hd95_metric': 6.046797275543213} +Cheakpoint... +Epoch [2295/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710386395454407, 'Val/mean miou_metric': 0.9552332162857056, 'Val/mean f1': 0.9737681746482849, 'Val/mean precision': 0.9719659090042114, 'Val/mean recall': 0.9755770564079285, 'Val/mean hd95_metric': 6.046797275543213} +Epoch [2296/4000] Training [1/16] Loss: 0.00610 +Epoch [2296/4000] Training [2/16] Loss: 0.00445 +Epoch [2296/4000] Training [3/16] Loss: 0.00578 +Epoch [2296/4000] Training [4/16] Loss: 0.00518 +Epoch [2296/4000] Training [5/16] Loss: 0.00440 +Epoch [2296/4000] Training [6/16] Loss: 0.00410 +Epoch [2296/4000] Training [7/16] Loss: 0.00486 +Epoch [2296/4000] Training [8/16] Loss: 0.00391 +Epoch [2296/4000] Training [9/16] Loss: 0.00397 +Epoch [2296/4000] Training [10/16] Loss: 0.00489 +Epoch [2296/4000] Training [11/16] Loss: 0.00566 +Epoch [2296/4000] Training [12/16] Loss: 0.00419 +Epoch [2296/4000] Training [13/16] Loss: 0.00422 +Epoch [2296/4000] Training [14/16] Loss: 0.00640 +Epoch [2296/4000] Training [15/16] Loss: 0.00454 +Epoch [2296/4000] Training [16/16] Loss: 0.00416 +Epoch [2296/4000] Training metric {'Train/mean dice_metric': 0.9969421625137329, 'Train/mean miou_metric': 0.9936255812644958, 'Train/mean f1': 0.9923993349075317, 'Train/mean precision': 0.9879200458526611, 'Train/mean recall': 0.9969194531440735, 'Train/mean hd95_metric': 0.9739812612533569} +Epoch [2296/4000] Validation [1/4] Loss: 0.26055 focal_loss 0.19926 dice_loss 0.06130 +Epoch [2296/4000] Validation [2/4] Loss: 0.80633 focal_loss 0.60040 dice_loss 0.20593 +Epoch [2296/4000] Validation [3/4] Loss: 0.36627 focal_loss 0.27388 dice_loss 0.09239 +Epoch [2296/4000] Validation [4/4] Loss: 0.24459 focal_loss 0.15879 dice_loss 0.08581 +Epoch [2296/4000] Validation metric {'Val/mean dice_metric': 0.973369300365448, 'Val/mean miou_metric': 0.9577590227127075, 'Val/mean f1': 0.9752324819564819, 'Val/mean precision': 0.9736327528953552, 'Val/mean recall': 0.9768376350402832, 'Val/mean hd95_metric': 5.06770658493042} +Cheakpoint... +Epoch [2296/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973369300365448, 'Val/mean miou_metric': 0.9577590227127075, 'Val/mean f1': 0.9752324819564819, 'Val/mean precision': 0.9736327528953552, 'Val/mean recall': 0.9768376350402832, 'Val/mean hd95_metric': 5.06770658493042} +Epoch [2297/4000] Training [1/16] Loss: 0.00352 +Epoch [2297/4000] Training [2/16] Loss: 0.00578 +Epoch [2297/4000] Training [3/16] Loss: 0.00563 +Epoch [2297/4000] Training [4/16] Loss: 0.00506 +Epoch [2297/4000] Training [5/16] Loss: 0.00442 +Epoch [2297/4000] Training [6/16] Loss: 0.00663 +Epoch [2297/4000] Training [7/16] Loss: 0.00477 +Epoch [2297/4000] Training [8/16] Loss: 0.00609 +Epoch [2297/4000] Training [9/16] Loss: 0.00423 +Epoch [2297/4000] Training [10/16] Loss: 0.00534 +Epoch [2297/4000] Training [11/16] Loss: 0.00497 +Epoch [2297/4000] Training [12/16] Loss: 0.00579 +Epoch [2297/4000] Training [13/16] Loss: 0.00527 +Epoch [2297/4000] Training [14/16] Loss: 0.00434 +Epoch [2297/4000] Training [15/16] Loss: 0.00506 +Epoch [2297/4000] Training [16/16] Loss: 0.00532 +Epoch [2297/4000] Training metric {'Train/mean dice_metric': 0.9968037605285645, 'Train/mean miou_metric': 0.9933615326881409, 'Train/mean f1': 0.9923443794250488, 'Train/mean precision': 0.9877694845199585, 'Train/mean recall': 0.9969618916511536, 'Train/mean hd95_metric': 0.9879461526870728} +Epoch [2297/4000] Validation [1/4] Loss: 0.31229 focal_loss 0.24827 dice_loss 0.06401 +Epoch [2297/4000] Validation [2/4] Loss: 0.66736 focal_loss 0.46993 dice_loss 0.19743 +Epoch [2297/4000] Validation [3/4] Loss: 0.38438 focal_loss 0.29049 dice_loss 0.09389 +Epoch [2297/4000] Validation [4/4] Loss: 0.34328 focal_loss 0.21974 dice_loss 0.12354 +Epoch [2297/4000] Validation metric {'Val/mean dice_metric': 0.9716078042984009, 'Val/mean miou_metric': 0.9559696316719055, 'Val/mean f1': 0.9743441343307495, 'Val/mean precision': 0.9711514115333557, 'Val/mean recall': 0.977557897567749, 'Val/mean hd95_metric': 5.5840044021606445} +Cheakpoint... +Epoch [2297/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716078042984009, 'Val/mean miou_metric': 0.9559696316719055, 'Val/mean f1': 0.9743441343307495, 'Val/mean precision': 0.9711514115333557, 'Val/mean recall': 0.977557897567749, 'Val/mean hd95_metric': 5.5840044021606445} +Epoch [2298/4000] Training [1/16] Loss: 0.00357 +Epoch [2298/4000] Training [2/16] Loss: 0.00449 +Epoch [2298/4000] Training [3/16] Loss: 0.00435 +Epoch [2298/4000] Training [4/16] Loss: 0.00389 +Epoch [2298/4000] Training [5/16] Loss: 0.00524 +Epoch [2298/4000] Training [6/16] Loss: 0.00378 +Epoch [2298/4000] Training [7/16] Loss: 0.00562 +Epoch [2298/4000] Training [8/16] Loss: 0.00422 +Epoch [2298/4000] Training [9/16] Loss: 0.00489 +Epoch [2298/4000] Training [10/16] Loss: 0.00576 +Epoch [2298/4000] Training [11/16] Loss: 0.00557 +Epoch [2298/4000] Training [12/16] Loss: 0.00457 +Epoch [2298/4000] Training [13/16] Loss: 0.00518 +Epoch [2298/4000] Training [14/16] Loss: 0.00468 +Epoch [2298/4000] Training [15/16] Loss: 0.00675 +Epoch [2298/4000] Training [16/16] Loss: 0.00439 +Epoch [2298/4000] Training metric {'Train/mean dice_metric': 0.9966195821762085, 'Train/mean miou_metric': 0.9930022954940796, 'Train/mean f1': 0.9922794103622437, 'Train/mean precision': 0.9876676797866821, 'Train/mean recall': 0.9969344139099121, 'Train/mean hd95_metric': 0.997820258140564} +Epoch [2298/4000] Validation [1/4] Loss: 0.36471 focal_loss 0.29300 dice_loss 0.07172 +Epoch [2298/4000] Validation [2/4] Loss: 0.35794 focal_loss 0.22055 dice_loss 0.13739 +Epoch [2298/4000] Validation [3/4] Loss: 0.39590 focal_loss 0.30227 dice_loss 0.09363 +Epoch [2298/4000] Validation [4/4] Loss: 0.27059 focal_loss 0.17990 dice_loss 0.09069 +Epoch [2298/4000] Validation metric {'Val/mean dice_metric': 0.9730285406112671, 'Val/mean miou_metric': 0.9567872285842896, 'Val/mean f1': 0.9743724465370178, 'Val/mean precision': 0.9728786945343018, 'Val/mean recall': 0.9758708477020264, 'Val/mean hd95_metric': 5.326927661895752} +Cheakpoint... +Epoch [2298/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730285406112671, 'Val/mean miou_metric': 0.9567872285842896, 'Val/mean f1': 0.9743724465370178, 'Val/mean precision': 0.9728786945343018, 'Val/mean recall': 0.9758708477020264, 'Val/mean hd95_metric': 5.326927661895752} +Epoch [2299/4000] Training [1/16] Loss: 0.00490 +Epoch [2299/4000] Training [2/16] Loss: 0.00402 +Epoch [2299/4000] Training [3/16] Loss: 0.00464 +Epoch [2299/4000] Training [4/16] Loss: 0.00501 +Epoch [2299/4000] Training [5/16] Loss: 0.00476 +Epoch [2299/4000] Training [6/16] Loss: 0.00675 +Epoch [2299/4000] Training [7/16] Loss: 0.00597 +Epoch [2299/4000] Training [8/16] Loss: 0.00422 +Epoch [2299/4000] Training [9/16] Loss: 0.00528 +Epoch [2299/4000] Training [10/16] Loss: 0.00344 +Epoch [2299/4000] Training [11/16] Loss: 0.00328 +Epoch [2299/4000] Training [12/16] Loss: 0.00588 +Epoch [2299/4000] Training [13/16] Loss: 0.00645 +Epoch [2299/4000] Training [14/16] Loss: 0.00528 +Epoch [2299/4000] Training [15/16] Loss: 0.00439 +Epoch [2299/4000] Training [16/16] Loss: 0.00562 +Epoch [2299/4000] Training metric {'Train/mean dice_metric': 0.9968366026878357, 'Train/mean miou_metric': 0.9934002757072449, 'Train/mean f1': 0.991618812084198, 'Train/mean precision': 0.9865524768829346, 'Train/mean recall': 0.9967374205589294, 'Train/mean hd95_metric': 0.9798540472984314} +Epoch [2299/4000] Validation [1/4] Loss: 0.29214 focal_loss 0.22477 dice_loss 0.06737 +Epoch [2299/4000] Validation [2/4] Loss: 0.37585 focal_loss 0.24533 dice_loss 0.13053 +Epoch [2299/4000] Validation [3/4] Loss: 0.38078 focal_loss 0.29349 dice_loss 0.08729 +Epoch [2299/4000] Validation [4/4] Loss: 0.28742 focal_loss 0.18457 dice_loss 0.10285 +Epoch [2299/4000] Validation metric {'Val/mean dice_metric': 0.9733275175094604, 'Val/mean miou_metric': 0.9576318860054016, 'Val/mean f1': 0.9747287034988403, 'Val/mean precision': 0.9715296030044556, 'Val/mean recall': 0.9779489636421204, 'Val/mean hd95_metric': 5.1105875968933105} +Cheakpoint... +Epoch [2299/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733275175094604, 'Val/mean miou_metric': 0.9576318860054016, 'Val/mean f1': 0.9747287034988403, 'Val/mean precision': 0.9715296030044556, 'Val/mean recall': 0.9779489636421204, 'Val/mean hd95_metric': 5.1105875968933105} +Epoch [2300/4000] Training [1/16] Loss: 0.00680 +Epoch [2300/4000] Training [2/16] Loss: 0.00537 +Epoch [2300/4000] Training [3/16] Loss: 0.00405 +Epoch [2300/4000] Training [4/16] Loss: 0.00469 +Epoch [2300/4000] Training [5/16] Loss: 0.00501 +Epoch [2300/4000] Training [6/16] Loss: 0.00417 +Epoch [2300/4000] Training [7/16] Loss: 0.00552 +Epoch [2300/4000] Training [8/16] Loss: 0.00980 +Epoch [2300/4000] Training [9/16] Loss: 0.00408 +Epoch [2300/4000] Training [10/16] Loss: 0.00555 +Epoch [2300/4000] Training [11/16] Loss: 0.00463 +Epoch [2300/4000] Training [12/16] Loss: 0.00586 +Epoch [2300/4000] Training [13/16] Loss: 0.00374 +Epoch [2300/4000] Training [14/16] Loss: 0.00531 +Epoch [2300/4000] Training [15/16] Loss: 0.00439 +Epoch [2300/4000] Training [16/16] Loss: 0.00646 +Epoch [2300/4000] Training metric {'Train/mean dice_metric': 0.996640145778656, 'Train/mean miou_metric': 0.9930147528648376, 'Train/mean f1': 0.9918964505195618, 'Train/mean precision': 0.9870367050170898, 'Train/mean recall': 0.9968045353889465, 'Train/mean hd95_metric': 1.000282883644104} +Epoch [2300/4000] Validation [1/4] Loss: 0.32195 focal_loss 0.24210 dice_loss 0.07985 +Epoch [2300/4000] Validation [2/4] Loss: 0.31995 focal_loss 0.20140 dice_loss 0.11855 +Epoch [2300/4000] Validation [3/4] Loss: 0.40000 focal_loss 0.30834 dice_loss 0.09166 +Epoch [2300/4000] Validation [4/4] Loss: 0.30561 focal_loss 0.19531 dice_loss 0.11030 +Epoch [2300/4000] Validation metric {'Val/mean dice_metric': 0.974770724773407, 'Val/mean miou_metric': 0.9585787057876587, 'Val/mean f1': 0.9751706123352051, 'Val/mean precision': 0.9708678722381592, 'Val/mean recall': 0.9795117974281311, 'Val/mean hd95_metric': 5.84177303314209} +Cheakpoint... +Epoch [2300/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974770724773407, 'Val/mean miou_metric': 0.9585787057876587, 'Val/mean f1': 0.9751706123352051, 'Val/mean precision': 0.9708678722381592, 'Val/mean recall': 0.9795117974281311, 'Val/mean hd95_metric': 5.84177303314209} +Epoch [2301/4000] Training [1/16] Loss: 0.00454 +Epoch [2301/4000] Training [2/16] Loss: 0.00506 +Epoch [2301/4000] Training [3/16] Loss: 0.00446 +Epoch [2301/4000] Training [4/16] Loss: 0.00588 +Epoch [2301/4000] Training [5/16] Loss: 0.00652 +Epoch [2301/4000] Training [6/16] Loss: 0.00619 +Epoch [2301/4000] Training [7/16] Loss: 0.00444 +Epoch [2301/4000] Training [8/16] Loss: 0.00454 +Epoch [2301/4000] Training [9/16] Loss: 0.00423 +Epoch [2301/4000] Training [10/16] Loss: 0.00391 +Epoch [2301/4000] Training [11/16] Loss: 0.00704 +Epoch [2301/4000] Training [12/16] Loss: 0.00433 +Epoch [2301/4000] Training [13/16] Loss: 0.00419 +Epoch [2301/4000] Training [14/16] Loss: 0.00480 +Epoch [2301/4000] Training [15/16] Loss: 0.00383 +Epoch [2301/4000] Training [16/16] Loss: 0.00449 +Epoch [2301/4000] Training metric {'Train/mean dice_metric': 0.9967358112335205, 'Train/mean miou_metric': 0.9932281970977783, 'Train/mean f1': 0.9923622608184814, 'Train/mean precision': 0.987779438495636, 'Train/mean recall': 0.9969878792762756, 'Train/mean hd95_metric': 1.0200458765029907} +Epoch [2301/4000] Validation [1/4] Loss: 0.33091 focal_loss 0.26444 dice_loss 0.06646 +Epoch [2301/4000] Validation [2/4] Loss: 0.77225 focal_loss 0.57629 dice_loss 0.19596 +Epoch [2301/4000] Validation [3/4] Loss: 0.42302 focal_loss 0.32388 dice_loss 0.09914 +Epoch [2301/4000] Validation [4/4] Loss: 0.28443 focal_loss 0.18816 dice_loss 0.09627 +Epoch [2301/4000] Validation metric {'Val/mean dice_metric': 0.9712702035903931, 'Val/mean miou_metric': 0.9556159973144531, 'Val/mean f1': 0.9742189049720764, 'Val/mean precision': 0.9717146754264832, 'Val/mean recall': 0.9767360687255859, 'Val/mean hd95_metric': 5.245577335357666} +Cheakpoint... +Epoch [2301/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712702035903931, 'Val/mean miou_metric': 0.9556159973144531, 'Val/mean f1': 0.9742189049720764, 'Val/mean precision': 0.9717146754264832, 'Val/mean recall': 0.9767360687255859, 'Val/mean hd95_metric': 5.245577335357666} +Epoch [2302/4000] Training [1/16] Loss: 0.00392 +Epoch [2302/4000] Training [2/16] Loss: 0.00386 +Epoch [2302/4000] Training [3/16] Loss: 0.00455 +Epoch [2302/4000] Training [4/16] Loss: 0.00445 +Epoch [2302/4000] Training [5/16] Loss: 0.00514 +Epoch [2302/4000] Training [6/16] Loss: 0.00535 +Epoch [2302/4000] Training [7/16] Loss: 0.00401 +Epoch [2302/4000] Training [8/16] Loss: 0.00509 +Epoch [2302/4000] Training [9/16] Loss: 0.00576 +Epoch [2302/4000] Training [10/16] Loss: 0.00482 +Epoch [2302/4000] Training [11/16] Loss: 0.00487 +Epoch [2302/4000] Training [12/16] Loss: 0.00470 +Epoch [2302/4000] Training [13/16] Loss: 0.00443 +Epoch [2302/4000] Training [14/16] Loss: 0.00452 +Epoch [2302/4000] Training [15/16] Loss: 0.00486 +Epoch [2302/4000] Training [16/16] Loss: 0.00479 +Epoch [2302/4000] Training metric {'Train/mean dice_metric': 0.9969805479049683, 'Train/mean miou_metric': 0.9937138557434082, 'Train/mean f1': 0.9924860000610352, 'Train/mean precision': 0.9879806637763977, 'Train/mean recall': 0.9970325827598572, 'Train/mean hd95_metric': 0.9684715270996094} +Epoch [2302/4000] Validation [1/4] Loss: 0.52203 focal_loss 0.41132 dice_loss 0.11072 +Epoch [2302/4000] Validation [2/4] Loss: 0.53217 focal_loss 0.33867 dice_loss 0.19350 +Epoch [2302/4000] Validation [3/4] Loss: 0.41704 focal_loss 0.32301 dice_loss 0.09403 +Epoch [2302/4000] Validation [4/4] Loss: 0.30564 focal_loss 0.19940 dice_loss 0.10624 +Epoch [2302/4000] Validation metric {'Val/mean dice_metric': 0.9727610349655151, 'Val/mean miou_metric': 0.9570123553276062, 'Val/mean f1': 0.9751999974250793, 'Val/mean precision': 0.9729495048522949, 'Val/mean recall': 0.9774609208106995, 'Val/mean hd95_metric': 5.739433765411377} +Cheakpoint... +Epoch [2302/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727610349655151, 'Val/mean miou_metric': 0.9570123553276062, 'Val/mean f1': 0.9751999974250793, 'Val/mean precision': 0.9729495048522949, 'Val/mean recall': 0.9774609208106995, 'Val/mean hd95_metric': 5.739433765411377} +Epoch [2303/4000] Training [1/16] Loss: 0.00594 +Epoch [2303/4000] Training [2/16] Loss: 0.00527 +Epoch [2303/4000] Training [3/16] Loss: 0.00572 +Epoch [2303/4000] Training [4/16] Loss: 0.00566 +Epoch [2303/4000] Training [5/16] Loss: 0.00494 +Epoch [2303/4000] Training [6/16] Loss: 0.00471 +Epoch [2303/4000] Training [7/16] Loss: 0.00511 +Epoch [2303/4000] Training [8/16] Loss: 0.00295 +Epoch [2303/4000] Training [9/16] Loss: 0.00435 +Epoch [2303/4000] Training [10/16] Loss: 0.00482 +Epoch [2303/4000] Training [11/16] Loss: 0.00725 +Epoch [2303/4000] Training [12/16] Loss: 0.00596 +Epoch [2303/4000] Training [13/16] Loss: 0.00372 +Epoch [2303/4000] Training [14/16] Loss: 0.00544 +Epoch [2303/4000] Training [15/16] Loss: 0.00598 +Epoch [2303/4000] Training [16/16] Loss: 0.00592 +Epoch [2303/4000] Training metric {'Train/mean dice_metric': 0.9968526363372803, 'Train/mean miou_metric': 0.993450403213501, 'Train/mean f1': 0.992335855960846, 'Train/mean precision': 0.9877423048019409, 'Train/mean recall': 0.9969722628593445, 'Train/mean hd95_metric': 0.9796730279922485} +Epoch [2303/4000] Validation [1/4] Loss: 0.32644 focal_loss 0.25931 dice_loss 0.06714 +Epoch [2303/4000] Validation [2/4] Loss: 0.37145 focal_loss 0.24912 dice_loss 0.12232 +Epoch [2303/4000] Validation [3/4] Loss: 0.44902 focal_loss 0.35319 dice_loss 0.09583 +Epoch [2303/4000] Validation [4/4] Loss: 0.20718 focal_loss 0.12946 dice_loss 0.07773 +Epoch [2303/4000] Validation metric {'Val/mean dice_metric': 0.9744974374771118, 'Val/mean miou_metric': 0.9589086771011353, 'Val/mean f1': 0.9756121635437012, 'Val/mean precision': 0.9729344248771667, 'Val/mean recall': 0.978304922580719, 'Val/mean hd95_metric': 5.2512006759643555} +Cheakpoint... +Epoch [2303/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744974374771118, 'Val/mean miou_metric': 0.9589086771011353, 'Val/mean f1': 0.9756121635437012, 'Val/mean precision': 0.9729344248771667, 'Val/mean recall': 0.978304922580719, 'Val/mean hd95_metric': 5.2512006759643555} +Epoch [2304/4000] Training [1/16] Loss: 0.00603 +Epoch [2304/4000] Training [2/16] Loss: 0.00433 +Epoch [2304/4000] Training [3/16] Loss: 0.00468 +Epoch [2304/4000] Training [4/16] Loss: 0.00450 +Epoch [2304/4000] Training [5/16] Loss: 0.00607 +Epoch [2304/4000] Training [6/16] Loss: 0.00451 +Epoch [2304/4000] Training [7/16] Loss: 0.00452 +Epoch [2304/4000] Training [8/16] Loss: 0.00428 +Epoch [2304/4000] Training [9/16] Loss: 0.00599 +Epoch [2304/4000] Training [10/16] Loss: 0.00357 +Epoch [2304/4000] Training [11/16] Loss: 0.00431 +Epoch [2304/4000] Training [12/16] Loss: 0.00453 +Epoch [2304/4000] Training [13/16] Loss: 0.00389 +Epoch [2304/4000] Training [14/16] Loss: 0.00371 +Epoch [2304/4000] Training [15/16] Loss: 0.00469 +Epoch [2304/4000] Training [16/16] Loss: 0.00373 +Epoch [2304/4000] Training metric {'Train/mean dice_metric': 0.9970120191574097, 'Train/mean miou_metric': 0.9937378764152527, 'Train/mean f1': 0.9917893409729004, 'Train/mean precision': 0.9865900278091431, 'Train/mean recall': 0.997043788433075, 'Train/mean hd95_metric': 0.976415753364563} +Epoch [2304/4000] Validation [1/4] Loss: 0.35529 focal_loss 0.28340 dice_loss 0.07189 +Epoch [2304/4000] Validation [2/4] Loss: 0.82278 focal_loss 0.61323 dice_loss 0.20955 +Epoch [2304/4000] Validation [3/4] Loss: 0.37680 focal_loss 0.28922 dice_loss 0.08758 +Epoch [2304/4000] Validation [4/4] Loss: 0.22128 focal_loss 0.13061 dice_loss 0.09067 +Epoch [2304/4000] Validation metric {'Val/mean dice_metric': 0.9731118083000183, 'Val/mean miou_metric': 0.9576019048690796, 'Val/mean f1': 0.9750515818595886, 'Val/mean precision': 0.9725974202156067, 'Val/mean recall': 0.9775179624557495, 'Val/mean hd95_metric': 5.247802257537842} +Cheakpoint... +Epoch [2304/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731118083000183, 'Val/mean miou_metric': 0.9576019048690796, 'Val/mean f1': 0.9750515818595886, 'Val/mean precision': 0.9725974202156067, 'Val/mean recall': 0.9775179624557495, 'Val/mean hd95_metric': 5.247802257537842} +Epoch [2305/4000] Training [1/16] Loss: 0.00446 +Epoch [2305/4000] Training [2/16] Loss: 0.00392 +Epoch [2305/4000] Training [3/16] Loss: 0.00360 +Epoch [2305/4000] Training [4/16] Loss: 0.00473 +Epoch [2305/4000] Training [5/16] Loss: 0.00394 +Epoch [2305/4000] Training [6/16] Loss: 0.00570 +Epoch [2305/4000] Training [7/16] Loss: 0.00829 +Epoch [2305/4000] Training [8/16] Loss: 0.00606 +Epoch [2305/4000] Training [9/16] Loss: 0.00569 +Epoch [2305/4000] Training [10/16] Loss: 0.00460 +Epoch [2305/4000] Training [11/16] Loss: 0.00428 +Epoch [2305/4000] Training [12/16] Loss: 0.00567 +Epoch [2305/4000] Training [13/16] Loss: 0.00521 +Epoch [2305/4000] Training [14/16] Loss: 0.00591 +Epoch [2305/4000] Training [15/16] Loss: 0.00634 +Epoch [2305/4000] Training [16/16] Loss: 0.00453 +Epoch [2305/4000] Training metric {'Train/mean dice_metric': 0.9966579675674438, 'Train/mean miou_metric': 0.9930763244628906, 'Train/mean f1': 0.9921614527702332, 'Train/mean precision': 0.9876622557640076, 'Train/mean recall': 0.9967017769813538, 'Train/mean hd95_metric': 0.999821126461029} +Epoch [2305/4000] Validation [1/4] Loss: 0.29387 focal_loss 0.22691 dice_loss 0.06696 +Epoch [2305/4000] Validation [2/4] Loss: 0.33570 focal_loss 0.22365 dice_loss 0.11204 +Epoch [2305/4000] Validation [3/4] Loss: 0.40039 focal_loss 0.30917 dice_loss 0.09122 +Epoch [2305/4000] Validation [4/4] Loss: 0.28797 focal_loss 0.18327 dice_loss 0.10469 +Epoch [2305/4000] Validation metric {'Val/mean dice_metric': 0.9735740423202515, 'Val/mean miou_metric': 0.9577302932739258, 'Val/mean f1': 0.9751150608062744, 'Val/mean precision': 0.9717578291893005, 'Val/mean recall': 0.9784956574440002, 'Val/mean hd95_metric': 5.542719841003418} +Cheakpoint... +Epoch [2305/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735740423202515, 'Val/mean miou_metric': 0.9577302932739258, 'Val/mean f1': 0.9751150608062744, 'Val/mean precision': 0.9717578291893005, 'Val/mean recall': 0.9784956574440002, 'Val/mean hd95_metric': 5.542719841003418} +Epoch [2306/4000] Training [1/16] Loss: 0.00545 +Epoch [2306/4000] Training [2/16] Loss: 0.00394 +Epoch [2306/4000] Training [3/16] Loss: 0.00691 +Epoch [2306/4000] Training [4/16] Loss: 0.00482 +Epoch [2306/4000] Training [5/16] Loss: 0.00476 +Epoch [2306/4000] Training [6/16] Loss: 0.00612 +Epoch [2306/4000] Training [7/16] Loss: 0.00441 +Epoch [2306/4000] Training [8/16] Loss: 0.00690 +Epoch [2306/4000] Training [9/16] Loss: 0.00365 +Epoch [2306/4000] Training [10/16] Loss: 0.00424 +Epoch [2306/4000] Training [11/16] Loss: 0.00552 +Epoch [2306/4000] Training [12/16] Loss: 0.00519 +Epoch [2306/4000] Training [13/16] Loss: 0.00499 +Epoch [2306/4000] Training [14/16] Loss: 0.00556 +Epoch [2306/4000] Training [15/16] Loss: 0.00399 +Epoch [2306/4000] Training [16/16] Loss: 0.00553 +Epoch [2306/4000] Training metric {'Train/mean dice_metric': 0.9968201518058777, 'Train/mean miou_metric': 0.9933950304985046, 'Train/mean f1': 0.9923929572105408, 'Train/mean precision': 0.9879202246665955, 'Train/mean recall': 0.9969063401222229, 'Train/mean hd95_metric': 0.9932056665420532} +Epoch [2306/4000] Validation [1/4] Loss: 0.31970 focal_loss 0.24916 dice_loss 0.07054 +Epoch [2306/4000] Validation [2/4] Loss: 0.31493 focal_loss 0.20716 dice_loss 0.10777 +Epoch [2306/4000] Validation [3/4] Loss: 0.41104 focal_loss 0.32163 dice_loss 0.08941 +Epoch [2306/4000] Validation [4/4] Loss: 0.64980 focal_loss 0.48971 dice_loss 0.16009 +Epoch [2306/4000] Validation metric {'Val/mean dice_metric': 0.9740816950798035, 'Val/mean miou_metric': 0.9577186703681946, 'Val/mean f1': 0.9747136831283569, 'Val/mean precision': 0.9715311527252197, 'Val/mean recall': 0.9779170155525208, 'Val/mean hd95_metric': 5.803165912628174} +Cheakpoint... +Epoch [2306/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740816950798035, 'Val/mean miou_metric': 0.9577186703681946, 'Val/mean f1': 0.9747136831283569, 'Val/mean precision': 0.9715311527252197, 'Val/mean recall': 0.9779170155525208, 'Val/mean hd95_metric': 5.803165912628174} +Epoch [2307/4000] Training [1/16] Loss: 0.00436 +Epoch [2307/4000] Training [2/16] Loss: 0.00453 +Epoch [2307/4000] Training [3/16] Loss: 0.00526 +Epoch [2307/4000] Training [4/16] Loss: 0.00346 +Epoch [2307/4000] Training [5/16] Loss: 0.00565 +Epoch [2307/4000] Training [6/16] Loss: 0.00555 +Epoch [2307/4000] Training [7/16] Loss: 0.00548 +Epoch [2307/4000] Training [8/16] Loss: 0.00359 +Epoch [2307/4000] Training [9/16] Loss: 0.00389 +Epoch [2307/4000] Training [10/16] Loss: 0.00889 +Epoch [2307/4000] Training [11/16] Loss: 0.00506 +Epoch [2307/4000] Training [12/16] Loss: 0.00843 +Epoch [2307/4000] Training [13/16] Loss: 0.00616 +Epoch [2307/4000] Training [14/16] Loss: 0.00538 +Epoch [2307/4000] Training [15/16] Loss: 0.00472 +Epoch [2307/4000] Training [16/16] Loss: 0.00427 +Epoch [2307/4000] Training metric {'Train/mean dice_metric': 0.996650218963623, 'Train/mean miou_metric': 0.9930539131164551, 'Train/mean f1': 0.9921439290046692, 'Train/mean precision': 0.9876402616500854, 'Train/mean recall': 0.9966888427734375, 'Train/mean hd95_metric': 0.9832719564437866} +Epoch [2307/4000] Validation [1/4] Loss: 0.28349 focal_loss 0.22356 dice_loss 0.05993 +Epoch [2307/4000] Validation [2/4] Loss: 0.33873 focal_loss 0.22199 dice_loss 0.11674 +Epoch [2307/4000] Validation [3/4] Loss: 0.43503 focal_loss 0.33889 dice_loss 0.09614 +Epoch [2307/4000] Validation [4/4] Loss: 0.46224 focal_loss 0.32709 dice_loss 0.13514 +Epoch [2307/4000] Validation metric {'Val/mean dice_metric': 0.9732965230941772, 'Val/mean miou_metric': 0.9574676752090454, 'Val/mean f1': 0.9752657413482666, 'Val/mean precision': 0.9723649621009827, 'Val/mean recall': 0.9781839847564697, 'Val/mean hd95_metric': 5.620223045349121} +Cheakpoint... +Epoch [2307/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732965230941772, 'Val/mean miou_metric': 0.9574676752090454, 'Val/mean f1': 0.9752657413482666, 'Val/mean precision': 0.9723649621009827, 'Val/mean recall': 0.9781839847564697, 'Val/mean hd95_metric': 5.620223045349121} +Epoch [2308/4000] Training [1/16] Loss: 0.00620 +Epoch [2308/4000] Training [2/16] Loss: 0.00472 +Epoch [2308/4000] Training [3/16] Loss: 0.00461 +Epoch [2308/4000] Training [4/16] Loss: 0.00436 +Epoch [2308/4000] Training [5/16] Loss: 0.00428 +Epoch [2308/4000] Training [6/16] Loss: 0.00433 +Epoch [2308/4000] Training [7/16] Loss: 0.00365 +Epoch [2308/4000] Training [8/16] Loss: 0.00562 +Epoch [2308/4000] Training [9/16] Loss: 0.00353 +Epoch [2308/4000] Training [10/16] Loss: 0.00576 +Epoch [2308/4000] Training [11/16] Loss: 0.00474 +Epoch [2308/4000] Training [12/16] Loss: 0.00474 +Epoch [2308/4000] Training [13/16] Loss: 0.00518 +Epoch [2308/4000] Training [14/16] Loss: 0.00520 +Epoch [2308/4000] Training [15/16] Loss: 0.00628 +Epoch [2308/4000] Training [16/16] Loss: 0.00682 +Epoch [2308/4000] Training metric {'Train/mean dice_metric': 0.9969500303268433, 'Train/mean miou_metric': 0.9936479330062866, 'Train/mean f1': 0.99242103099823, 'Train/mean precision': 0.9878219366073608, 'Train/mean recall': 0.9970631003379822, 'Train/mean hd95_metric': 1.226000428199768} +Epoch [2308/4000] Validation [1/4] Loss: 0.31053 focal_loss 0.24522 dice_loss 0.06531 +Epoch [2308/4000] Validation [2/4] Loss: 0.57967 focal_loss 0.42163 dice_loss 0.15804 +Epoch [2308/4000] Validation [3/4] Loss: 0.42629 focal_loss 0.33583 dice_loss 0.09046 +Epoch [2308/4000] Validation [4/4] Loss: 0.27975 focal_loss 0.18198 dice_loss 0.09777 +Epoch [2308/4000] Validation metric {'Val/mean dice_metric': 0.9739965200424194, 'Val/mean miou_metric': 0.958098292350769, 'Val/mean f1': 0.9754219651222229, 'Val/mean precision': 0.9716678857803345, 'Val/mean recall': 0.9792051911354065, 'Val/mean hd95_metric': 5.789759635925293} +Cheakpoint... +Epoch [2308/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739965200424194, 'Val/mean miou_metric': 0.958098292350769, 'Val/mean f1': 0.9754219651222229, 'Val/mean precision': 0.9716678857803345, 'Val/mean recall': 0.9792051911354065, 'Val/mean hd95_metric': 5.789759635925293} +Epoch [2309/4000] Training [1/16] Loss: 0.00443 +Epoch [2309/4000] Training [2/16] Loss: 0.00424 +Epoch [2309/4000] Training [3/16] Loss: 0.00481 +Epoch [2309/4000] Training [4/16] Loss: 0.00450 +Epoch [2309/4000] Training [5/16] Loss: 0.00474 +Epoch [2309/4000] Training [6/16] Loss: 0.00496 +Epoch [2309/4000] Training [7/16] Loss: 0.00419 +Epoch [2309/4000] Training [8/16] Loss: 0.00678 +Epoch [2309/4000] Training [9/16] Loss: 0.00669 +Epoch [2309/4000] Training [10/16] Loss: 0.00575 +Epoch [2309/4000] Training [11/16] Loss: 0.00565 +Epoch [2309/4000] Training [12/16] Loss: 0.00494 +Epoch [2309/4000] Training [13/16] Loss: 0.00490 +Epoch [2309/4000] Training [14/16] Loss: 0.00482 +Epoch [2309/4000] Training [15/16] Loss: 0.00429 +Epoch [2309/4000] Training [16/16] Loss: 0.00654 +Epoch [2309/4000] Training metric {'Train/mean dice_metric': 0.9967061281204224, 'Train/mean miou_metric': 0.9931551218032837, 'Train/mean f1': 0.9922426342964172, 'Train/mean precision': 0.9877280592918396, 'Train/mean recall': 0.9967986345291138, 'Train/mean hd95_metric': 0.980394721031189} +Epoch [2309/4000] Validation [1/4] Loss: 0.29700 focal_loss 0.23293 dice_loss 0.06407 +Epoch [2309/4000] Validation [2/4] Loss: 0.34236 focal_loss 0.23099 dice_loss 0.11137 +Epoch [2309/4000] Validation [3/4] Loss: 0.48872 focal_loss 0.38532 dice_loss 0.10340 +Epoch [2309/4000] Validation [4/4] Loss: 0.35219 focal_loss 0.23595 dice_loss 0.11624 +Epoch [2309/4000] Validation metric {'Val/mean dice_metric': 0.9730783700942993, 'Val/mean miou_metric': 0.956804096698761, 'Val/mean f1': 0.9744220972061157, 'Val/mean precision': 0.9716015458106995, 'Val/mean recall': 0.9772590398788452, 'Val/mean hd95_metric': 5.801732063293457} +Cheakpoint... +Epoch [2309/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730783700942993, 'Val/mean miou_metric': 0.956804096698761, 'Val/mean f1': 0.9744220972061157, 'Val/mean precision': 0.9716015458106995, 'Val/mean recall': 0.9772590398788452, 'Val/mean hd95_metric': 5.801732063293457} +Epoch [2310/4000] Training [1/16] Loss: 0.00637 +Epoch [2310/4000] Training [2/16] Loss: 0.00648 +Epoch [2310/4000] Training [3/16] Loss: 0.00420 +Epoch [2310/4000] Training [4/16] Loss: 0.00500 +Epoch [2310/4000] Training [5/16] Loss: 0.00506 +Epoch [2310/4000] Training [6/16] Loss: 0.00533 +Epoch [2310/4000] Training [7/16] Loss: 0.00443 +Epoch [2310/4000] Training [8/16] Loss: 0.00478 +Epoch [2310/4000] Training [9/16] Loss: 0.00492 +Epoch [2310/4000] Training [10/16] Loss: 0.00500 +Epoch [2310/4000] Training [11/16] Loss: 0.00366 +Epoch [2310/4000] Training [12/16] Loss: 0.00525 +Epoch [2310/4000] Training [13/16] Loss: 0.00538 +Epoch [2310/4000] Training [14/16] Loss: 0.00596 +Epoch [2310/4000] Training [15/16] Loss: 0.00415 +Epoch [2310/4000] Training [16/16] Loss: 0.00461 +Epoch [2310/4000] Training metric {'Train/mean dice_metric': 0.9967988729476929, 'Train/mean miou_metric': 0.993348240852356, 'Train/mean f1': 0.9924277067184448, 'Train/mean precision': 0.9878371953964233, 'Train/mean recall': 0.9970611333847046, 'Train/mean hd95_metric': 1.1934343576431274} +Epoch [2310/4000] Validation [1/4] Loss: 0.27766 focal_loss 0.20955 dice_loss 0.06812 +Epoch [2310/4000] Validation [2/4] Loss: 0.34336 focal_loss 0.23268 dice_loss 0.11068 +Epoch [2310/4000] Validation [3/4] Loss: 0.23506 focal_loss 0.17241 dice_loss 0.06265 +Epoch [2310/4000] Validation [4/4] Loss: 0.33362 focal_loss 0.21217 dice_loss 0.12144 +Epoch [2310/4000] Validation metric {'Val/mean dice_metric': 0.9724880456924438, 'Val/mean miou_metric': 0.9571163058280945, 'Val/mean f1': 0.9750083684921265, 'Val/mean precision': 0.972303032875061, 'Val/mean recall': 0.9777287840843201, 'Val/mean hd95_metric': 5.49388313293457} +Cheakpoint... +Epoch [2310/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724880456924438, 'Val/mean miou_metric': 0.9571163058280945, 'Val/mean f1': 0.9750083684921265, 'Val/mean precision': 0.972303032875061, 'Val/mean recall': 0.9777287840843201, 'Val/mean hd95_metric': 5.49388313293457} +Epoch [2311/4000] Training [1/16] Loss: 0.00726 +Epoch [2311/4000] Training [2/16] Loss: 0.00537 +Epoch [2311/4000] Training [3/16] Loss: 0.00404 +Epoch [2311/4000] Training [4/16] Loss: 0.00469 +Epoch [2311/4000] Training [5/16] Loss: 0.00650 +Epoch [2311/4000] Training [6/16] Loss: 0.00403 +Epoch [2311/4000] Training [7/16] Loss: 0.00606 +Epoch [2311/4000] Training [8/16] Loss: 0.00502 +Epoch [2311/4000] Training [9/16] Loss: 0.00505 +Epoch [2311/4000] Training [10/16] Loss: 0.00563 +Epoch [2311/4000] Training [11/16] Loss: 0.00475 +Epoch [2311/4000] Training [12/16] Loss: 0.00389 +Epoch [2311/4000] Training [13/16] Loss: 0.00525 +Epoch [2311/4000] Training [14/16] Loss: 0.00510 +Epoch [2311/4000] Training [15/16] Loss: 0.00588 +Epoch [2311/4000] Training [16/16] Loss: 0.00378 +Epoch [2311/4000] Training metric {'Train/mean dice_metric': 0.9968988299369812, 'Train/mean miou_metric': 0.9935364723205566, 'Train/mean f1': 0.9922701716423035, 'Train/mean precision': 0.9876996874809265, 'Train/mean recall': 0.9968831539154053, 'Train/mean hd95_metric': 0.9774236679077148} +Epoch [2311/4000] Validation [1/4] Loss: 0.33140 focal_loss 0.26271 dice_loss 0.06869 +Epoch [2311/4000] Validation [2/4] Loss: 0.31800 focal_loss 0.20599 dice_loss 0.11202 +Epoch [2311/4000] Validation [3/4] Loss: 0.44732 focal_loss 0.35124 dice_loss 0.09608 +Epoch [2311/4000] Validation [4/4] Loss: 0.20219 focal_loss 0.12459 dice_loss 0.07760 +Epoch [2311/4000] Validation metric {'Val/mean dice_metric': 0.9744027853012085, 'Val/mean miou_metric': 0.9586307406425476, 'Val/mean f1': 0.9751641750335693, 'Val/mean precision': 0.9708328247070312, 'Val/mean recall': 0.9795344471931458, 'Val/mean hd95_metric': 5.709750175476074} +Cheakpoint... +Epoch [2311/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744027853012085, 'Val/mean miou_metric': 0.9586307406425476, 'Val/mean f1': 0.9751641750335693, 'Val/mean precision': 0.9708328247070312, 'Val/mean recall': 0.9795344471931458, 'Val/mean hd95_metric': 5.709750175476074} +Epoch [2312/4000] Training [1/16] Loss: 0.00599 +Epoch [2312/4000] Training [2/16] Loss: 0.00479 +Epoch [2312/4000] Training [3/16] Loss: 0.00447 +Epoch [2312/4000] Training [4/16] Loss: 0.00704 +Epoch [2312/4000] Training [5/16] Loss: 0.00424 +Epoch [2312/4000] Training [6/16] Loss: 0.00459 +Epoch [2312/4000] Training [7/16] Loss: 0.00564 +Epoch [2312/4000] Training [8/16] Loss: 0.00458 +Epoch [2312/4000] Training [9/16] Loss: 0.00420 +Epoch [2312/4000] Training [10/16] Loss: 0.00407 +Epoch [2312/4000] Training [11/16] Loss: 0.00441 +Epoch [2312/4000] Training [12/16] Loss: 0.00482 +Epoch [2312/4000] Training [13/16] Loss: 0.00470 +Epoch [2312/4000] Training [14/16] Loss: 0.00533 +Epoch [2312/4000] Training [15/16] Loss: 0.00433 +Epoch [2312/4000] Training [16/16] Loss: 0.00445 +Epoch [2312/4000] Training metric {'Train/mean dice_metric': 0.9967822432518005, 'Train/mean miou_metric': 0.9932938814163208, 'Train/mean f1': 0.9916269779205322, 'Train/mean precision': 0.9865188598632812, 'Train/mean recall': 0.9967883229255676, 'Train/mean hd95_metric': 0.980734646320343} +Epoch [2312/4000] Validation [1/4] Loss: 0.33889 focal_loss 0.27112 dice_loss 0.06777 +Epoch [2312/4000] Validation [2/4] Loss: 0.34499 focal_loss 0.23010 dice_loss 0.11489 +Epoch [2312/4000] Validation [3/4] Loss: 0.40759 focal_loss 0.31984 dice_loss 0.08775 +Epoch [2312/4000] Validation [4/4] Loss: 0.28682 focal_loss 0.18534 dice_loss 0.10148 +Epoch [2312/4000] Validation metric {'Val/mean dice_metric': 0.9736608266830444, 'Val/mean miou_metric': 0.9580078125, 'Val/mean f1': 0.9754130244255066, 'Val/mean precision': 0.9716467261314392, 'Val/mean recall': 0.979208767414093, 'Val/mean hd95_metric': 5.3885674476623535} +Cheakpoint... +Epoch [2312/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736608266830444, 'Val/mean miou_metric': 0.9580078125, 'Val/mean f1': 0.9754130244255066, 'Val/mean precision': 0.9716467261314392, 'Val/mean recall': 0.979208767414093, 'Val/mean hd95_metric': 5.3885674476623535} +Epoch [2313/4000] Training [1/16] Loss: 0.00594 +Epoch [2313/4000] Training [2/16] Loss: 0.00578 +Epoch [2313/4000] Training [3/16] Loss: 0.00529 +Epoch [2313/4000] Training [4/16] Loss: 0.00464 +Epoch [2313/4000] Training [5/16] Loss: 0.00848 +Epoch [2313/4000] Training [6/16] Loss: 0.00298 +Epoch [2313/4000] Training [7/16] Loss: 0.00364 +Epoch [2313/4000] Training [8/16] Loss: 0.00439 +Epoch [2313/4000] Training [9/16] Loss: 0.00475 +Epoch [2313/4000] Training [10/16] Loss: 0.00438 +Epoch [2313/4000] Training [11/16] Loss: 0.00577 +Epoch [2313/4000] Training [12/16] Loss: 0.00443 +Epoch [2313/4000] Training [13/16] Loss: 0.00603 +Epoch [2313/4000] Training [14/16] Loss: 0.00477 +Epoch [2313/4000] Training [15/16] Loss: 0.00506 +Epoch [2313/4000] Training [16/16] Loss: 0.00471 +Epoch [2313/4000] Training metric {'Train/mean dice_metric': 0.9967775344848633, 'Train/mean miou_metric': 0.9932922124862671, 'Train/mean f1': 0.9918349981307983, 'Train/mean precision': 0.9867502450942993, 'Train/mean recall': 0.9969724416732788, 'Train/mean hd95_metric': 0.9826305508613586} +Epoch [2313/4000] Validation [1/4] Loss: 0.34689 focal_loss 0.27637 dice_loss 0.07052 +Epoch [2313/4000] Validation [2/4] Loss: 0.36211 focal_loss 0.23895 dice_loss 0.12315 +Epoch [2313/4000] Validation [3/4] Loss: 0.39765 focal_loss 0.30471 dice_loss 0.09295 +Epoch [2313/4000] Validation [4/4] Loss: 0.24954 focal_loss 0.16650 dice_loss 0.08304 +Epoch [2313/4000] Validation metric {'Val/mean dice_metric': 0.9747241735458374, 'Val/mean miou_metric': 0.9587251543998718, 'Val/mean f1': 0.9756689071655273, 'Val/mean precision': 0.972427487373352, 'Val/mean recall': 0.9789319038391113, 'Val/mean hd95_metric': 5.506072044372559} +Cheakpoint... +Epoch [2313/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747241735458374, 'Val/mean miou_metric': 0.9587251543998718, 'Val/mean f1': 0.9756689071655273, 'Val/mean precision': 0.972427487373352, 'Val/mean recall': 0.9789319038391113, 'Val/mean hd95_metric': 5.506072044372559} +Epoch [2314/4000] Training [1/16] Loss: 0.00513 +Epoch [2314/4000] Training [2/16] Loss: 0.00420 +Epoch [2314/4000] Training [3/16] Loss: 0.00428 +Epoch [2314/4000] Training [4/16] Loss: 0.00473 +Epoch [2314/4000] Training [5/16] Loss: 0.00481 +Epoch [2314/4000] Training [6/16] Loss: 0.00594 +Epoch [2314/4000] Training [7/16] Loss: 0.00451 +Epoch [2314/4000] Training [8/16] Loss: 0.00556 +Epoch [2314/4000] Training [9/16] Loss: 0.00597 +Epoch [2314/4000] Training [10/16] Loss: 0.00541 +Epoch [2314/4000] Training [11/16] Loss: 0.00699 +Epoch [2314/4000] Training [12/16] Loss: 0.00468 +Epoch [2314/4000] Training [13/16] Loss: 0.00427 +Epoch [2314/4000] Training [14/16] Loss: 0.00441 +Epoch [2314/4000] Training [15/16] Loss: 0.00348 +Epoch [2314/4000] Training [16/16] Loss: 0.00401 +Epoch [2314/4000] Training metric {'Train/mean dice_metric': 0.9967557787895203, 'Train/mean miou_metric': 0.993266761302948, 'Train/mean f1': 0.9922819137573242, 'Train/mean precision': 0.9877520203590393, 'Train/mean recall': 0.9968535304069519, 'Train/mean hd95_metric': 0.9882444143295288} +Epoch [2314/4000] Validation [1/4] Loss: 0.30532 focal_loss 0.23761 dice_loss 0.06771 +Epoch [2314/4000] Validation [2/4] Loss: 0.77038 focal_loss 0.56623 dice_loss 0.20415 +Epoch [2314/4000] Validation [3/4] Loss: 0.42596 focal_loss 0.32794 dice_loss 0.09802 +Epoch [2314/4000] Validation [4/4] Loss: 0.30986 focal_loss 0.20552 dice_loss 0.10434 +Epoch [2314/4000] Validation metric {'Val/mean dice_metric': 0.9716814160346985, 'Val/mean miou_metric': 0.955938458442688, 'Val/mean f1': 0.974746823310852, 'Val/mean precision': 0.9722115993499756, 'Val/mean recall': 0.9772952198982239, 'Val/mean hd95_metric': 5.747869968414307} +Cheakpoint... +Epoch [2314/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716814160346985, 'Val/mean miou_metric': 0.955938458442688, 'Val/mean f1': 0.974746823310852, 'Val/mean precision': 0.9722115993499756, 'Val/mean recall': 0.9772952198982239, 'Val/mean hd95_metric': 5.747869968414307} +Epoch [2315/4000] Training [1/16] Loss: 0.00470 +Epoch [2315/4000] Training [2/16] Loss: 0.00452 +Epoch [2315/4000] Training [3/16] Loss: 0.00450 +Epoch [2315/4000] Training [4/16] Loss: 0.00536 +Epoch [2315/4000] Training [5/16] Loss: 0.00413 +Epoch [2315/4000] Training [6/16] Loss: 0.00539 +Epoch [2315/4000] Training [7/16] Loss: 0.00496 +Epoch [2315/4000] Training [8/16] Loss: 0.00723 +Epoch [2315/4000] Training [9/16] Loss: 0.00502 +Epoch [2315/4000] Training [10/16] Loss: 0.00522 +Epoch [2315/4000] Training [11/16] Loss: 0.00488 +Epoch [2315/4000] Training [12/16] Loss: 0.00448 +Epoch [2315/4000] Training [13/16] Loss: 0.00676 +Epoch [2315/4000] Training [14/16] Loss: 0.00643 +Epoch [2315/4000] Training [15/16] Loss: 0.00497 +Epoch [2315/4000] Training [16/16] Loss: 0.00602 +Epoch [2315/4000] Training metric {'Train/mean dice_metric': 0.9966752529144287, 'Train/mean miou_metric': 0.9931086301803589, 'Train/mean f1': 0.992257833480835, 'Train/mean precision': 0.9877541661262512, 'Train/mean recall': 0.9968026876449585, 'Train/mean hd95_metric': 0.9890562295913696} +Epoch [2315/4000] Validation [1/4] Loss: 0.29238 focal_loss 0.22489 dice_loss 0.06749 +Epoch [2315/4000] Validation [2/4] Loss: 0.34471 focal_loss 0.23105 dice_loss 0.11366 +Epoch [2315/4000] Validation [3/4] Loss: 0.43424 focal_loss 0.33512 dice_loss 0.09912 +Epoch [2315/4000] Validation [4/4] Loss: 0.24764 focal_loss 0.15578 dice_loss 0.09186 +Epoch [2315/4000] Validation metric {'Val/mean dice_metric': 0.9729498028755188, 'Val/mean miou_metric': 0.9575834274291992, 'Val/mean f1': 0.9749585390090942, 'Val/mean precision': 0.971511960029602, 'Val/mean recall': 0.9784295558929443, 'Val/mean hd95_metric': 6.002168655395508} +Cheakpoint... +Epoch [2315/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729498028755188, 'Val/mean miou_metric': 0.9575834274291992, 'Val/mean f1': 0.9749585390090942, 'Val/mean precision': 0.971511960029602, 'Val/mean recall': 0.9784295558929443, 'Val/mean hd95_metric': 6.002168655395508} +Epoch [2316/4000] Training [1/16] Loss: 0.00452 +Epoch [2316/4000] Training [2/16] Loss: 0.00473 +Epoch [2316/4000] Training [3/16] Loss: 0.00378 +Epoch [2316/4000] Training [4/16] Loss: 0.00466 +Epoch [2316/4000] Training [5/16] Loss: 0.00804 +Epoch [2316/4000] Training [6/16] Loss: 0.00396 +Epoch [2316/4000] Training [7/16] Loss: 0.00388 +Epoch [2316/4000] Training [8/16] Loss: 0.00466 +Epoch [2316/4000] Training [9/16] Loss: 0.00447 +Epoch [2316/4000] Training [10/16] Loss: 0.00589 +Epoch [2316/4000] Training [11/16] Loss: 0.00418 +Epoch [2316/4000] Training [12/16] Loss: 0.00551 +Epoch [2316/4000] Training [13/16] Loss: 0.00462 +Epoch [2316/4000] Training [14/16] Loss: 0.00716 +Epoch [2316/4000] Training [15/16] Loss: 0.00457 +Epoch [2316/4000] Training [16/16] Loss: 0.00379 +Epoch [2316/4000] Training metric {'Train/mean dice_metric': 0.996963381767273, 'Train/mean miou_metric': 0.9936803579330444, 'Train/mean f1': 0.9925757050514221, 'Train/mean precision': 0.9880685806274414, 'Train/mean recall': 0.9971241354942322, 'Train/mean hd95_metric': 0.9732879400253296} +Epoch [2316/4000] Validation [1/4] Loss: 0.26328 focal_loss 0.20238 dice_loss 0.06090 +Epoch [2316/4000] Validation [2/4] Loss: 0.60073 focal_loss 0.42617 dice_loss 0.17456 +Epoch [2316/4000] Validation [3/4] Loss: 0.43164 focal_loss 0.33555 dice_loss 0.09609 +Epoch [2316/4000] Validation [4/4] Loss: 0.27078 focal_loss 0.17239 dice_loss 0.09839 +Epoch [2316/4000] Validation metric {'Val/mean dice_metric': 0.9742699861526489, 'Val/mean miou_metric': 0.9584337472915649, 'Val/mean f1': 0.975712239742279, 'Val/mean precision': 0.9730690121650696, 'Val/mean recall': 0.9783698916435242, 'Val/mean hd95_metric': 5.373884201049805} +Cheakpoint... +Epoch [2316/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742699861526489, 'Val/mean miou_metric': 0.9584337472915649, 'Val/mean f1': 0.975712239742279, 'Val/mean precision': 0.9730690121650696, 'Val/mean recall': 0.9783698916435242, 'Val/mean hd95_metric': 5.373884201049805} +Epoch [2317/4000] Training [1/16] Loss: 0.00506 +Epoch [2317/4000] Training [2/16] Loss: 0.00408 +Epoch [2317/4000] Training [3/16] Loss: 0.00667 +Epoch [2317/4000] Training [4/16] Loss: 0.00372 +Epoch [2317/4000] Training [5/16] Loss: 0.00577 +Epoch [2317/4000] Training [6/16] Loss: 0.00638 +Epoch [2317/4000] Training [7/16] Loss: 0.00454 +Epoch [2317/4000] Training [8/16] Loss: 0.00569 +Epoch [2317/4000] Training [9/16] Loss: 0.00494 +Epoch [2317/4000] Training [10/16] Loss: 0.00602 +Epoch [2317/4000] Training [11/16] Loss: 0.00474 +Epoch [2317/4000] Training [12/16] Loss: 0.00444 +Epoch [2317/4000] Training [13/16] Loss: 0.00680 +Epoch [2317/4000] Training [14/16] Loss: 0.00519 +Epoch [2317/4000] Training [15/16] Loss: 0.00392 +Epoch [2317/4000] Training [16/16] Loss: 0.00466 +Epoch [2317/4000] Training metric {'Train/mean dice_metric': 0.9967982769012451, 'Train/mean miou_metric': 0.9933451414108276, 'Train/mean f1': 0.9923402070999146, 'Train/mean precision': 0.9878440499305725, 'Train/mean recall': 0.9968774914741516, 'Train/mean hd95_metric': 0.9891377687454224} +Epoch [2317/4000] Validation [1/4] Loss: 0.30248 focal_loss 0.23607 dice_loss 0.06641 +Epoch [2317/4000] Validation [2/4] Loss: 0.61875 focal_loss 0.44008 dice_loss 0.17866 +Epoch [2317/4000] Validation [3/4] Loss: 0.20409 focal_loss 0.14198 dice_loss 0.06211 +Epoch [2317/4000] Validation [4/4] Loss: 0.32093 focal_loss 0.20550 dice_loss 0.11544 +Epoch [2317/4000] Validation metric {'Val/mean dice_metric': 0.972278892993927, 'Val/mean miou_metric': 0.9563918113708496, 'Val/mean f1': 0.9744155406951904, 'Val/mean precision': 0.9726511240005493, 'Val/mean recall': 0.9761862754821777, 'Val/mean hd95_metric': 5.462330341339111} +Cheakpoint... +Epoch [2317/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972278892993927, 'Val/mean miou_metric': 0.9563918113708496, 'Val/mean f1': 0.9744155406951904, 'Val/mean precision': 0.9726511240005493, 'Val/mean recall': 0.9761862754821777, 'Val/mean hd95_metric': 5.462330341339111} +Epoch [2318/4000] Training [1/16] Loss: 0.00526 +Epoch [2318/4000] Training [2/16] Loss: 0.00415 +Epoch [2318/4000] Training [3/16] Loss: 0.00494 +Epoch [2318/4000] Training [4/16] Loss: 0.00634 +Epoch [2318/4000] Training [5/16] Loss: 0.00578 +Epoch [2318/4000] Training [6/16] Loss: 0.00434 +Epoch [2318/4000] Training [7/16] Loss: 0.00415 +Epoch [2318/4000] Training [8/16] Loss: 0.00382 +Epoch [2318/4000] Training [9/16] Loss: 0.00535 +Epoch [2318/4000] Training [10/16] Loss: 0.00590 +Epoch [2318/4000] Training [11/16] Loss: 0.00454 +Epoch [2318/4000] Training [12/16] Loss: 0.00492 +Epoch [2318/4000] Training [13/16] Loss: 0.00375 +Epoch [2318/4000] Training [14/16] Loss: 0.00498 +Epoch [2318/4000] Training [15/16] Loss: 0.00424 +Epoch [2318/4000] Training [16/16] Loss: 0.00389 +Epoch [2318/4000] Training metric {'Train/mean dice_metric': 0.9968855381011963, 'Train/mean miou_metric': 0.9935250282287598, 'Train/mean f1': 0.992491602897644, 'Train/mean precision': 0.9878818392753601, 'Train/mean recall': 0.9971445798873901, 'Train/mean hd95_metric': 0.986698567867279} +Epoch [2318/4000] Validation [1/4] Loss: 0.36824 focal_loss 0.29376 dice_loss 0.07448 +Epoch [2318/4000] Validation [2/4] Loss: 0.42840 focal_loss 0.27559 dice_loss 0.15281 +Epoch [2318/4000] Validation [3/4] Loss: 0.37195 focal_loss 0.28431 dice_loss 0.08764 +Epoch [2318/4000] Validation [4/4] Loss: 0.37549 focal_loss 0.25841 dice_loss 0.11709 +Epoch [2318/4000] Validation metric {'Val/mean dice_metric': 0.9714368581771851, 'Val/mean miou_metric': 0.9556528925895691, 'Val/mean f1': 0.9747349619865417, 'Val/mean precision': 0.9757640361785889, 'Val/mean recall': 0.973707914352417, 'Val/mean hd95_metric': 5.415592193603516} +Cheakpoint... +Epoch [2318/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714368581771851, 'Val/mean miou_metric': 0.9556528925895691, 'Val/mean f1': 0.9747349619865417, 'Val/mean precision': 0.9757640361785889, 'Val/mean recall': 0.973707914352417, 'Val/mean hd95_metric': 5.415592193603516} +Epoch [2319/4000] Training [1/16] Loss: 0.00411 +Epoch [2319/4000] Training [2/16] Loss: 0.00313 +Epoch [2319/4000] Training [3/16] Loss: 0.00401 +Epoch [2319/4000] Training [4/16] Loss: 0.00641 +Epoch [2319/4000] Training [5/16] Loss: 0.00480 +Epoch [2319/4000] Training [6/16] Loss: 0.00584 +Epoch [2319/4000] Training [7/16] Loss: 0.00746 +Epoch [2319/4000] Training [8/16] Loss: 0.00587 +Epoch [2319/4000] Training [9/16] Loss: 0.00452 +Epoch [2319/4000] Training [10/16] Loss: 0.00596 +Epoch [2319/4000] Training [11/16] Loss: 0.00477 +Epoch [2319/4000] Training [12/16] Loss: 0.00513 +Epoch [2319/4000] Training [13/16] Loss: 0.00444 +Epoch [2319/4000] Training [14/16] Loss: 0.00397 +Epoch [2319/4000] Training [15/16] Loss: 0.00620 +Epoch [2319/4000] Training [16/16] Loss: 0.00476 +Epoch [2319/4000] Training metric {'Train/mean dice_metric': 0.9966270923614502, 'Train/mean miou_metric': 0.9930459260940552, 'Train/mean f1': 0.9921671748161316, 'Train/mean precision': 0.987455427646637, 'Train/mean recall': 0.9969241619110107, 'Train/mean hd95_metric': 1.0999516248703003} +Epoch [2319/4000] Validation [1/4] Loss: 0.34797 focal_loss 0.27873 dice_loss 0.06924 +Epoch [2319/4000] Validation [2/4] Loss: 0.71397 focal_loss 0.50714 dice_loss 0.20683 +Epoch [2319/4000] Validation [3/4] Loss: 0.41803 focal_loss 0.32853 dice_loss 0.08950 +Epoch [2319/4000] Validation [4/4] Loss: 0.36934 focal_loss 0.24457 dice_loss 0.12476 +Epoch [2319/4000] Validation metric {'Val/mean dice_metric': 0.9736733436584473, 'Val/mean miou_metric': 0.9578550457954407, 'Val/mean f1': 0.9752187132835388, 'Val/mean precision': 0.9712822437286377, 'Val/mean recall': 0.9791873693466187, 'Val/mean hd95_metric': 5.754826545715332} +Cheakpoint... +Epoch [2319/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736733436584473, 'Val/mean miou_metric': 0.9578550457954407, 'Val/mean f1': 0.9752187132835388, 'Val/mean precision': 0.9712822437286377, 'Val/mean recall': 0.9791873693466187, 'Val/mean hd95_metric': 5.754826545715332} +Epoch [2320/4000] Training [1/16] Loss: 0.00540 +Epoch [2320/4000] Training [2/16] Loss: 0.00505 +Epoch [2320/4000] Training [3/16] Loss: 0.00504 +Epoch [2320/4000] Training [4/16] Loss: 0.00456 +Epoch [2320/4000] Training [5/16] Loss: 0.00488 +Epoch [2320/4000] Training [6/16] Loss: 0.00432 +Epoch [2320/4000] Training [7/16] Loss: 0.00335 +Epoch [2320/4000] Training [8/16] Loss: 0.00455 +Epoch [2320/4000] Training [9/16] Loss: 0.00355 +Epoch [2320/4000] Training [10/16] Loss: 0.00398 +Epoch [2320/4000] Training [11/16] Loss: 0.00401 +Epoch [2320/4000] Training [12/16] Loss: 0.00585 +Epoch [2320/4000] Training [13/16] Loss: 0.00607 +Epoch [2320/4000] Training [14/16] Loss: 0.00486 +Epoch [2320/4000] Training [15/16] Loss: 0.00492 +Epoch [2320/4000] Training [16/16] Loss: 0.00693 +Epoch [2320/4000] Training metric {'Train/mean dice_metric': 0.9969342947006226, 'Train/mean miou_metric': 0.9935867786407471, 'Train/mean f1': 0.9920632243156433, 'Train/mean precision': 0.9872658252716064, 'Train/mean recall': 0.9969074726104736, 'Train/mean hd95_metric': 0.9836626052856445} +Epoch [2320/4000] Validation [1/4] Loss: 0.29506 focal_loss 0.23055 dice_loss 0.06451 +Epoch [2320/4000] Validation [2/4] Loss: 0.55954 focal_loss 0.39353 dice_loss 0.16602 +Epoch [2320/4000] Validation [3/4] Loss: 0.20917 focal_loss 0.15077 dice_loss 0.05840 +Epoch [2320/4000] Validation [4/4] Loss: 0.36597 focal_loss 0.23748 dice_loss 0.12849 +Epoch [2320/4000] Validation metric {'Val/mean dice_metric': 0.9749141931533813, 'Val/mean miou_metric': 0.9592776298522949, 'Val/mean f1': 0.9762737154960632, 'Val/mean precision': 0.972230851650238, 'Val/mean recall': 0.9803502559661865, 'Val/mean hd95_metric': 5.120222091674805} +Cheakpoint... +Epoch [2320/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749141931533813, 'Val/mean miou_metric': 0.9592776298522949, 'Val/mean f1': 0.9762737154960632, 'Val/mean precision': 0.972230851650238, 'Val/mean recall': 0.9803502559661865, 'Val/mean hd95_metric': 5.120222091674805} +Epoch [2321/4000] Training [1/16] Loss: 0.00627 +Epoch [2321/4000] Training [2/16] Loss: 0.00588 +Epoch [2321/4000] Training [3/16] Loss: 0.00697 +Epoch [2321/4000] Training [4/16] Loss: 0.00567 +Epoch [2321/4000] Training [5/16] Loss: 0.00367 +Epoch [2321/4000] Training [6/16] Loss: 0.00332 +Epoch [2321/4000] Training [7/16] Loss: 0.00553 +Epoch [2321/4000] Training [8/16] Loss: 0.01275 +Epoch [2321/4000] Training [9/16] Loss: 0.00536 +Epoch [2321/4000] Training [10/16] Loss: 0.00444 +Epoch [2321/4000] Training [11/16] Loss: 0.00494 +Epoch [2321/4000] Training [12/16] Loss: 0.00551 +Epoch [2321/4000] Training [13/16] Loss: 0.00485 +Epoch [2321/4000] Training [14/16] Loss: 0.00445 +Epoch [2321/4000] Training [15/16] Loss: 0.00408 +Epoch [2321/4000] Training [16/16] Loss: 0.00372 +Epoch [2321/4000] Training metric {'Train/mean dice_metric': 0.9967663884162903, 'Train/mean miou_metric': 0.993285596370697, 'Train/mean f1': 0.9922611713409424, 'Train/mean precision': 0.9877421855926514, 'Train/mean recall': 0.9968217015266418, 'Train/mean hd95_metric': 1.0147148370742798} +Epoch [2321/4000] Validation [1/4] Loss: 0.30400 focal_loss 0.23540 dice_loss 0.06860 +Epoch [2321/4000] Validation [2/4] Loss: 0.42605 focal_loss 0.27196 dice_loss 0.15409 +Epoch [2321/4000] Validation [3/4] Loss: 0.36069 focal_loss 0.27048 dice_loss 0.09021 +Epoch [2321/4000] Validation [4/4] Loss: 0.43491 focal_loss 0.29621 dice_loss 0.13870 +Epoch [2321/4000] Validation metric {'Val/mean dice_metric': 0.9729338884353638, 'Val/mean miou_metric': 0.9571259617805481, 'Val/mean f1': 0.9757007956504822, 'Val/mean precision': 0.9743558168411255, 'Val/mean recall': 0.9770496487617493, 'Val/mean hd95_metric': 5.128396511077881} +Cheakpoint... +Epoch [2321/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729338884353638, 'Val/mean miou_metric': 0.9571259617805481, 'Val/mean f1': 0.9757007956504822, 'Val/mean precision': 0.9743558168411255, 'Val/mean recall': 0.9770496487617493, 'Val/mean hd95_metric': 5.128396511077881} +Epoch [2322/4000] Training [1/16] Loss: 0.00439 +Epoch [2322/4000] Training [2/16] Loss: 0.00360 +Epoch [2322/4000] Training [3/16] Loss: 0.00395 +Epoch [2322/4000] Training [4/16] Loss: 0.00596 +Epoch [2322/4000] Training [5/16] Loss: 0.00347 +Epoch [2322/4000] Training [6/16] Loss: 0.00556 +Epoch [2322/4000] Training [7/16] Loss: 0.00555 +Epoch [2322/4000] Training [8/16] Loss: 0.00758 +Epoch [2322/4000] Training [9/16] Loss: 0.00369 +Epoch [2322/4000] Training [10/16] Loss: 0.00624 +Epoch [2322/4000] Training [11/16] Loss: 0.00471 +Epoch [2322/4000] Training [12/16] Loss: 0.00469 +Epoch [2322/4000] Training [13/16] Loss: 0.00683 +Epoch [2322/4000] Training [14/16] Loss: 0.00489 +Epoch [2322/4000] Training [15/16] Loss: 0.00492 +Epoch [2322/4000] Training [16/16] Loss: 0.00484 +Epoch [2322/4000] Training metric {'Train/mean dice_metric': 0.9967479109764099, 'Train/mean miou_metric': 0.9932447671890259, 'Train/mean f1': 0.9922022223472595, 'Train/mean precision': 0.9875482320785522, 'Train/mean recall': 0.9969002604484558, 'Train/mean hd95_metric': 0.9819161891937256} +Epoch [2322/4000] Validation [1/4] Loss: 0.37774 focal_loss 0.30634 dice_loss 0.07140 +Epoch [2322/4000] Validation [2/4] Loss: 0.40170 focal_loss 0.26227 dice_loss 0.13943 +Epoch [2322/4000] Validation [3/4] Loss: 0.37917 focal_loss 0.28970 dice_loss 0.08946 +Epoch [2322/4000] Validation [4/4] Loss: 0.28791 focal_loss 0.18677 dice_loss 0.10114 +Epoch [2322/4000] Validation metric {'Val/mean dice_metric': 0.9732241630554199, 'Val/mean miou_metric': 0.9575799703598022, 'Val/mean f1': 0.9754437208175659, 'Val/mean precision': 0.9729461669921875, 'Val/mean recall': 0.9779539704322815, 'Val/mean hd95_metric': 5.641749382019043} +Cheakpoint... +Epoch [2322/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732241630554199, 'Val/mean miou_metric': 0.9575799703598022, 'Val/mean f1': 0.9754437208175659, 'Val/mean precision': 0.9729461669921875, 'Val/mean recall': 0.9779539704322815, 'Val/mean hd95_metric': 5.641749382019043} +Epoch [2323/4000] Training [1/16] Loss: 0.00384 +Epoch [2323/4000] Training [2/16] Loss: 0.00589 +Epoch [2323/4000] Training [3/16] Loss: 0.00354 +Epoch [2323/4000] Training [4/16] Loss: 0.00472 +Epoch [2323/4000] Training [5/16] Loss: 0.00413 +Epoch [2323/4000] Training [6/16] Loss: 0.00542 +Epoch [2323/4000] Training [7/16] Loss: 0.00602 +Epoch [2323/4000] Training [8/16] Loss: 0.00474 +Epoch [2323/4000] Training [9/16] Loss: 0.00478 +Epoch [2323/4000] Training [10/16] Loss: 0.00404 +Epoch [2323/4000] Training [11/16] Loss: 0.00371 +Epoch [2323/4000] Training [12/16] Loss: 0.00444 +Epoch [2323/4000] Training [13/16] Loss: 0.00384 +Epoch [2323/4000] Training [14/16] Loss: 0.00497 +Epoch [2323/4000] Training [15/16] Loss: 0.00503 +Epoch [2323/4000] Training [16/16] Loss: 0.00541 +Epoch [2323/4000] Training metric {'Train/mean dice_metric': 0.9971523284912109, 'Train/mean miou_metric': 0.9939964413642883, 'Train/mean f1': 0.9918577671051025, 'Train/mean precision': 0.986646294593811, 'Train/mean recall': 0.9971245527267456, 'Train/mean hd95_metric': 0.9762370586395264} +Epoch [2323/4000] Validation [1/4] Loss: 0.29930 focal_loss 0.23702 dice_loss 0.06227 +Epoch [2323/4000] Validation [2/4] Loss: 0.32673 focal_loss 0.20521 dice_loss 0.12152 +Epoch [2323/4000] Validation [3/4] Loss: 0.40107 focal_loss 0.30734 dice_loss 0.09374 +Epoch [2323/4000] Validation [4/4] Loss: 0.44897 focal_loss 0.31505 dice_loss 0.13392 +Epoch [2323/4000] Validation metric {'Val/mean dice_metric': 0.9740545153617859, 'Val/mean miou_metric': 0.9581621289253235, 'Val/mean f1': 0.9752153158187866, 'Val/mean precision': 0.9719332456588745, 'Val/mean recall': 0.9785197377204895, 'Val/mean hd95_metric': 5.465144634246826} +Cheakpoint... +Epoch [2323/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740545153617859, 'Val/mean miou_metric': 0.9581621289253235, 'Val/mean f1': 0.9752153158187866, 'Val/mean precision': 0.9719332456588745, 'Val/mean recall': 0.9785197377204895, 'Val/mean hd95_metric': 5.465144634246826} +Epoch [2324/4000] Training [1/16] Loss: 0.00373 +Epoch [2324/4000] Training [2/16] Loss: 0.00415 +Epoch [2324/4000] Training [3/16] Loss: 0.00560 +Epoch [2324/4000] Training [4/16] Loss: 0.00410 +Epoch [2324/4000] Training [5/16] Loss: 0.00382 +Epoch [2324/4000] Training [6/16] Loss: 0.00414 +Epoch [2324/4000] Training [7/16] Loss: 0.00498 +Epoch [2324/4000] Training [8/16] Loss: 0.00381 +Epoch [2324/4000] Training [9/16] Loss: 0.00625 +Epoch [2324/4000] Training [10/16] Loss: 0.00475 +Epoch [2324/4000] Training [11/16] Loss: 0.00364 +Epoch [2324/4000] Training [12/16] Loss: 0.00565 +Epoch [2324/4000] Training [13/16] Loss: 0.00648 +Epoch [2324/4000] Training [14/16] Loss: 0.00409 +Epoch [2324/4000] Training [15/16] Loss: 0.00457 +Epoch [2324/4000] Training [16/16] Loss: 0.00469 +Epoch [2324/4000] Training metric {'Train/mean dice_metric': 0.9970933198928833, 'Train/mean miou_metric': 0.993934154510498, 'Train/mean f1': 0.992595374584198, 'Train/mean precision': 0.9881464838981628, 'Train/mean recall': 0.9970845580101013, 'Train/mean hd95_metric': 0.970094621181488} +Epoch [2324/4000] Validation [1/4] Loss: 0.32761 focal_loss 0.26101 dice_loss 0.06659 +Epoch [2324/4000] Validation [2/4] Loss: 0.69154 focal_loss 0.49635 dice_loss 0.19519 +Epoch [2324/4000] Validation [3/4] Loss: 0.39777 focal_loss 0.30750 dice_loss 0.09028 +Epoch [2324/4000] Validation [4/4] Loss: 0.30141 focal_loss 0.19682 dice_loss 0.10459 +Epoch [2324/4000] Validation metric {'Val/mean dice_metric': 0.9728919863700867, 'Val/mean miou_metric': 0.9581847190856934, 'Val/mean f1': 0.9758163094520569, 'Val/mean precision': 0.9733638763427734, 'Val/mean recall': 0.9782810807228088, 'Val/mean hd95_metric': 5.772052764892578} +Cheakpoint... +Epoch [2324/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728919863700867, 'Val/mean miou_metric': 0.9581847190856934, 'Val/mean f1': 0.9758163094520569, 'Val/mean precision': 0.9733638763427734, 'Val/mean recall': 0.9782810807228088, 'Val/mean hd95_metric': 5.772052764892578} +Epoch [2325/4000] Training [1/16] Loss: 0.00566 +Epoch [2325/4000] Training [2/16] Loss: 0.00425 +Epoch [2325/4000] Training [3/16] Loss: 0.00516 +Epoch [2325/4000] Training [4/16] Loss: 0.00458 +Epoch [2325/4000] Training [5/16] Loss: 0.00346 +Epoch [2325/4000] Training [6/16] Loss: 0.00572 +Epoch [2325/4000] Training [7/16] Loss: 0.00449 +Epoch [2325/4000] Training [8/16] Loss: 0.00372 +Epoch [2325/4000] Training [9/16] Loss: 0.00787 +Epoch [2325/4000] Training [10/16] Loss: 0.00890 +Epoch [2325/4000] Training [11/16] Loss: 0.00493 +Epoch [2325/4000] Training [12/16] Loss: 0.00452 +Epoch [2325/4000] Training [13/16] Loss: 0.00505 +Epoch [2325/4000] Training [14/16] Loss: 0.00406 +Epoch [2325/4000] Training [15/16] Loss: 0.00672 +Epoch [2325/4000] Training [16/16] Loss: 0.00407 +Epoch [2325/4000] Training metric {'Train/mean dice_metric': 0.9969356656074524, 'Train/mean miou_metric': 0.9935991764068604, 'Train/mean f1': 0.9918843507766724, 'Train/mean precision': 0.9867725968360901, 'Train/mean recall': 0.9970493912696838, 'Train/mean hd95_metric': 0.9699486494064331} +Epoch [2325/4000] Validation [1/4] Loss: 0.35421 focal_loss 0.28439 dice_loss 0.06982 +Epoch [2325/4000] Validation [2/4] Loss: 0.73127 focal_loss 0.52813 dice_loss 0.20314 +Epoch [2325/4000] Validation [3/4] Loss: 0.42893 focal_loss 0.33481 dice_loss 0.09412 +Epoch [2325/4000] Validation [4/4] Loss: 0.26994 focal_loss 0.16685 dice_loss 0.10309 +Epoch [2325/4000] Validation metric {'Val/mean dice_metric': 0.9727692604064941, 'Val/mean miou_metric': 0.9577746391296387, 'Val/mean f1': 0.9750735759735107, 'Val/mean precision': 0.9728960394859314, 'Val/mean recall': 0.9772610068321228, 'Val/mean hd95_metric': 5.280859470367432} +Cheakpoint... +Epoch [2325/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727692604064941, 'Val/mean miou_metric': 0.9577746391296387, 'Val/mean f1': 0.9750735759735107, 'Val/mean precision': 0.9728960394859314, 'Val/mean recall': 0.9772610068321228, 'Val/mean hd95_metric': 5.280859470367432} +Epoch [2326/4000] Training [1/16] Loss: 0.00665 +Epoch [2326/4000] Training [2/16] Loss: 0.00386 +Epoch [2326/4000] Training [3/16] Loss: 0.00433 +Epoch [2326/4000] Training [4/16] Loss: 0.00539 +Epoch [2326/4000] Training [5/16] Loss: 0.00534 +Epoch [2326/4000] Training [6/16] Loss: 0.00343 +Epoch [2326/4000] Training [7/16] Loss: 0.00491 +Epoch [2326/4000] Training [8/16] Loss: 0.00304 +Epoch [2326/4000] Training [9/16] Loss: 0.00631 +Epoch [2326/4000] Training [10/16] Loss: 0.00399 +Epoch [2326/4000] Training [11/16] Loss: 0.00505 +Epoch [2326/4000] Training [12/16] Loss: 0.00465 +Epoch [2326/4000] Training [13/16] Loss: 0.00579 +Epoch [2326/4000] Training [14/16] Loss: 0.00402 +Epoch [2326/4000] Training [15/16] Loss: 0.00510 +Epoch [2326/4000] Training [16/16] Loss: 0.00427 +Epoch [2326/4000] Training metric {'Train/mean dice_metric': 0.9969989061355591, 'Train/mean miou_metric': 0.9937498569488525, 'Train/mean f1': 0.9924880266189575, 'Train/mean precision': 0.9879492521286011, 'Train/mean recall': 0.9970687627792358, 'Train/mean hd95_metric': 0.9672707319259644} +Epoch [2326/4000] Validation [1/4] Loss: 0.31539 focal_loss 0.24995 dice_loss 0.06544 +Epoch [2326/4000] Validation [2/4] Loss: 0.31688 focal_loss 0.19301 dice_loss 0.12387 +Epoch [2326/4000] Validation [3/4] Loss: 0.42038 focal_loss 0.32234 dice_loss 0.09804 +Epoch [2326/4000] Validation [4/4] Loss: 0.35187 focal_loss 0.23521 dice_loss 0.11666 +Epoch [2326/4000] Validation metric {'Val/mean dice_metric': 0.9730249643325806, 'Val/mean miou_metric': 0.9574803113937378, 'Val/mean f1': 0.9755852222442627, 'Val/mean precision': 0.9745954871177673, 'Val/mean recall': 0.9765770435333252, 'Val/mean hd95_metric': 5.507737159729004} +Cheakpoint... +Epoch [2326/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730249643325806, 'Val/mean miou_metric': 0.9574803113937378, 'Val/mean f1': 0.9755852222442627, 'Val/mean precision': 0.9745954871177673, 'Val/mean recall': 0.9765770435333252, 'Val/mean hd95_metric': 5.507737159729004} +Epoch [2327/4000] Training [1/16] Loss: 0.00463 +Epoch [2327/4000] Training [2/16] Loss: 0.00446 +Epoch [2327/4000] Training [3/16] Loss: 0.00489 +Epoch [2327/4000] Training [4/16] Loss: 0.00326 +Epoch [2327/4000] Training [5/16] Loss: 0.00342 +Epoch [2327/4000] Training [6/16] Loss: 0.00411 +Epoch [2327/4000] Training [7/16] Loss: 0.00496 +Epoch [2327/4000] Training [8/16] Loss: 0.00328 +Epoch [2327/4000] Training [9/16] Loss: 0.00574 +Epoch [2327/4000] Training [10/16] Loss: 0.00358 +Epoch [2327/4000] Training [11/16] Loss: 0.00445 +Epoch [2327/4000] Training [12/16] Loss: 0.00567 +Epoch [2327/4000] Training [13/16] Loss: 0.00373 +Epoch [2327/4000] Training [14/16] Loss: 0.00509 +Epoch [2327/4000] Training [15/16] Loss: 0.00633 +Epoch [2327/4000] Training [16/16] Loss: 0.00615 +Epoch [2327/4000] Training metric {'Train/mean dice_metric': 0.9970622062683105, 'Train/mean miou_metric': 0.9938478469848633, 'Train/mean f1': 0.9919114708900452, 'Train/mean precision': 0.9867767095565796, 'Train/mean recall': 0.9970999360084534, 'Train/mean hd95_metric': 1.2779459953308105} +Epoch [2327/4000] Validation [1/4] Loss: 0.33684 focal_loss 0.26827 dice_loss 0.06857 +Epoch [2327/4000] Validation [2/4] Loss: 0.29160 focal_loss 0.18123 dice_loss 0.11037 +Epoch [2327/4000] Validation [3/4] Loss: 0.41020 focal_loss 0.31961 dice_loss 0.09058 +Epoch [2327/4000] Validation [4/4] Loss: 0.31856 focal_loss 0.21079 dice_loss 0.10777 +Epoch [2327/4000] Validation metric {'Val/mean dice_metric': 0.9745334386825562, 'Val/mean miou_metric': 0.9589374661445618, 'Val/mean f1': 0.9755327105522156, 'Val/mean precision': 0.9721602201461792, 'Val/mean recall': 0.9789286851882935, 'Val/mean hd95_metric': 5.49260950088501} +Cheakpoint... +Epoch [2327/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745334386825562, 'Val/mean miou_metric': 0.9589374661445618, 'Val/mean f1': 0.9755327105522156, 'Val/mean precision': 0.9721602201461792, 'Val/mean recall': 0.9789286851882935, 'Val/mean hd95_metric': 5.49260950088501} +Epoch [2328/4000] Training [1/16] Loss: 0.00457 +Epoch [2328/4000] Training [2/16] Loss: 0.00552 +Epoch [2328/4000] Training [3/16] Loss: 0.00516 +Epoch [2328/4000] Training [4/16] Loss: 0.00432 +Epoch [2328/4000] Training [5/16] Loss: 0.00363 +Epoch [2328/4000] Training [6/16] Loss: 0.00591 +Epoch [2328/4000] Training [7/16] Loss: 0.00627 +Epoch [2328/4000] Training [8/16] Loss: 0.00463 +Epoch [2328/4000] Training [9/16] Loss: 0.00595 +Epoch [2328/4000] Training [10/16] Loss: 0.00375 +Epoch [2328/4000] Training [11/16] Loss: 0.00402 +Epoch [2328/4000] Training [12/16] Loss: 0.00477 +Epoch [2328/4000] Training [13/16] Loss: 0.00430 +Epoch [2328/4000] Training [14/16] Loss: 0.00509 +Epoch [2328/4000] Training [15/16] Loss: 0.00356 +Epoch [2328/4000] Training [16/16] Loss: 0.00563 +Epoch [2328/4000] Training metric {'Train/mean dice_metric': 0.9969443082809448, 'Train/mean miou_metric': 0.9936078786849976, 'Train/mean f1': 0.9917545318603516, 'Train/mean precision': 0.9865713119506836, 'Train/mean recall': 0.9969925284385681, 'Train/mean hd95_metric': 0.9900299310684204} +Epoch [2328/4000] Validation [1/4] Loss: 0.35717 focal_loss 0.28842 dice_loss 0.06875 +Epoch [2328/4000] Validation [2/4] Loss: 0.32806 focal_loss 0.20919 dice_loss 0.11887 +Epoch [2328/4000] Validation [3/4] Loss: 0.43641 focal_loss 0.33867 dice_loss 0.09774 +Epoch [2328/4000] Validation [4/4] Loss: 0.24400 focal_loss 0.16391 dice_loss 0.08008 +Epoch [2328/4000] Validation metric {'Val/mean dice_metric': 0.9748897552490234, 'Val/mean miou_metric': 0.9593082666397095, 'Val/mean f1': 0.9753711223602295, 'Val/mean precision': 0.9717101454734802, 'Val/mean recall': 0.9790598154067993, 'Val/mean hd95_metric': 5.314955711364746} +Cheakpoint... +Epoch [2328/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748897552490234, 'Val/mean miou_metric': 0.9593082666397095, 'Val/mean f1': 0.9753711223602295, 'Val/mean precision': 0.9717101454734802, 'Val/mean recall': 0.9790598154067993, 'Val/mean hd95_metric': 5.314955711364746} +Epoch [2329/4000] Training [1/16] Loss: 0.00415 +Epoch [2329/4000] Training [2/16] Loss: 0.00503 +Epoch [2329/4000] Training [3/16] Loss: 0.00663 +Epoch [2329/4000] Training [4/16] Loss: 0.00416 +Epoch [2329/4000] Training [5/16] Loss: 0.00497 +Epoch [2329/4000] Training [6/16] Loss: 0.00495 +Epoch [2329/4000] Training [7/16] Loss: 0.00480 +Epoch [2329/4000] Training [8/16] Loss: 0.00454 +Epoch [2329/4000] Training [9/16] Loss: 0.00511 +Epoch [2329/4000] Training [10/16] Loss: 0.00783 +Epoch [2329/4000] Training [11/16] Loss: 0.00455 +Epoch [2329/4000] Training [12/16] Loss: 0.00580 +Epoch [2329/4000] Training [13/16] Loss: 0.00612 +Epoch [2329/4000] Training [14/16] Loss: 0.00399 +Epoch [2329/4000] Training [15/16] Loss: 0.00494 +Epoch [2329/4000] Training [16/16] Loss: 0.00613 +Epoch [2329/4000] Training metric {'Train/mean dice_metric': 0.9966379404067993, 'Train/mean miou_metric': 0.9930015802383423, 'Train/mean f1': 0.9914163947105408, 'Train/mean precision': 0.9862443804740906, 'Train/mean recall': 0.9966428875923157, 'Train/mean hd95_metric': 0.9920189380645752} +Epoch [2329/4000] Validation [1/4] Loss: 0.33757 focal_loss 0.26938 dice_loss 0.06819 +Epoch [2329/4000] Validation [2/4] Loss: 0.40457 focal_loss 0.23588 dice_loss 0.16869 +Epoch [2329/4000] Validation [3/4] Loss: 0.40659 focal_loss 0.31694 dice_loss 0.08965 +Epoch [2329/4000] Validation [4/4] Loss: 0.44603 focal_loss 0.31086 dice_loss 0.13517 +Epoch [2329/4000] Validation metric {'Val/mean dice_metric': 0.9727987051010132, 'Val/mean miou_metric': 0.9567106366157532, 'Val/mean f1': 0.9742774367332458, 'Val/mean precision': 0.9707397818565369, 'Val/mean recall': 0.9778410196304321, 'Val/mean hd95_metric': 5.68360710144043} +Cheakpoint... +Epoch [2329/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727987051010132, 'Val/mean miou_metric': 0.9567106366157532, 'Val/mean f1': 0.9742774367332458, 'Val/mean precision': 0.9707397818565369, 'Val/mean recall': 0.9778410196304321, 'Val/mean hd95_metric': 5.68360710144043} +Epoch [2330/4000] Training [1/16] Loss: 0.00566 +Epoch [2330/4000] Training [2/16] Loss: 0.00448 +Epoch [2330/4000] Training [3/16] Loss: 0.00406 +Epoch [2330/4000] Training [4/16] Loss: 0.00516 +Epoch [2330/4000] Training [5/16] Loss: 0.00431 +Epoch [2330/4000] Training [6/16] Loss: 0.00511 +Epoch [2330/4000] Training [7/16] Loss: 0.00553 +Epoch [2330/4000] Training [8/16] Loss: 0.00445 +Epoch [2330/4000] Training [9/16] Loss: 0.00420 +Epoch [2330/4000] Training [10/16] Loss: 0.00621 +Epoch [2330/4000] Training [11/16] Loss: 0.00466 +Epoch [2330/4000] Training [12/16] Loss: 0.00554 +Epoch [2330/4000] Training [13/16] Loss: 0.00497 +Epoch [2330/4000] Training [14/16] Loss: 0.00408 +Epoch [2330/4000] Training [15/16] Loss: 0.00527 +Epoch [2330/4000] Training [16/16] Loss: 0.00404 +Epoch [2330/4000] Training metric {'Train/mean dice_metric': 0.9969034194946289, 'Train/mean miou_metric': 0.9935511946678162, 'Train/mean f1': 0.9923040270805359, 'Train/mean precision': 0.987687349319458, 'Train/mean recall': 0.9969640374183655, 'Train/mean hd95_metric': 0.9784734845161438} +Epoch [2330/4000] Validation [1/4] Loss: 0.33209 focal_loss 0.26286 dice_loss 0.06922 +Epoch [2330/4000] Validation [2/4] Loss: 0.38490 focal_loss 0.23732 dice_loss 0.14758 +Epoch [2330/4000] Validation [3/4] Loss: 0.18954 focal_loss 0.13247 dice_loss 0.05707 +Epoch [2330/4000] Validation [4/4] Loss: 0.36552 focal_loss 0.26033 dice_loss 0.10519 +Epoch [2330/4000] Validation metric {'Val/mean dice_metric': 0.9741052389144897, 'Val/mean miou_metric': 0.9585803747177124, 'Val/mean f1': 0.9757596850395203, 'Val/mean precision': 0.9736021757125854, 'Val/mean recall': 0.9779266119003296, 'Val/mean hd95_metric': 5.268770694732666} +Cheakpoint... +Epoch [2330/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741052389144897, 'Val/mean miou_metric': 0.9585803747177124, 'Val/mean f1': 0.9757596850395203, 'Val/mean precision': 0.9736021757125854, 'Val/mean recall': 0.9779266119003296, 'Val/mean hd95_metric': 5.268770694732666} +Epoch [2331/4000] Training [1/16] Loss: 0.00486 +Epoch [2331/4000] Training [2/16] Loss: 0.00463 +Epoch [2331/4000] Training [3/16] Loss: 0.00364 +Epoch [2331/4000] Training [4/16] Loss: 0.00706 +Epoch [2331/4000] Training [5/16] Loss: 0.00682 +Epoch [2331/4000] Training [6/16] Loss: 0.00543 +Epoch [2331/4000] Training [7/16] Loss: 0.00409 +Epoch [2331/4000] Training [8/16] Loss: 0.00511 +Epoch [2331/4000] Training [9/16] Loss: 0.00474 +Epoch [2331/4000] Training [10/16] Loss: 0.00464 +Epoch [2331/4000] Training [11/16] Loss: 0.00498 +Epoch [2331/4000] Training [12/16] Loss: 0.00545 +Epoch [2331/4000] Training [13/16] Loss: 0.00814 +Epoch [2331/4000] Training [14/16] Loss: 0.00431 +Epoch [2331/4000] Training [15/16] Loss: 0.00511 +Epoch [2331/4000] Training [16/16] Loss: 0.00436 +Epoch [2331/4000] Training metric {'Train/mean dice_metric': 0.9966081976890564, 'Train/mean miou_metric': 0.9929501414299011, 'Train/mean f1': 0.9916257262229919, 'Train/mean precision': 0.9865482449531555, 'Train/mean recall': 0.9967557191848755, 'Train/mean hd95_metric': 0.9841525554656982} +Epoch [2331/4000] Validation [1/4] Loss: 0.30269 focal_loss 0.23776 dice_loss 0.06493 +Epoch [2331/4000] Validation [2/4] Loss: 0.75784 focal_loss 0.55655 dice_loss 0.20129 +Epoch [2331/4000] Validation [3/4] Loss: 0.37139 focal_loss 0.27986 dice_loss 0.09152 +Epoch [2331/4000] Validation [4/4] Loss: 0.35587 focal_loss 0.24248 dice_loss 0.11339 +Epoch [2331/4000] Validation metric {'Val/mean dice_metric': 0.9732634425163269, 'Val/mean miou_metric': 0.9578237533569336, 'Val/mean f1': 0.9745992422103882, 'Val/mean precision': 0.9710724949836731, 'Val/mean recall': 0.978151798248291, 'Val/mean hd95_metric': 5.11021089553833} +Cheakpoint... +Epoch [2331/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732634425163269, 'Val/mean miou_metric': 0.9578237533569336, 'Val/mean f1': 0.9745992422103882, 'Val/mean precision': 0.9710724949836731, 'Val/mean recall': 0.978151798248291, 'Val/mean hd95_metric': 5.11021089553833} +Epoch [2332/4000] Training [1/16] Loss: 0.00576 +Epoch [2332/4000] Training [2/16] Loss: 0.00450 +Epoch [2332/4000] Training [3/16] Loss: 0.00447 +Epoch [2332/4000] Training [4/16] Loss: 0.00558 +Epoch [2332/4000] Training [5/16] Loss: 0.00535 +Epoch [2332/4000] Training [6/16] Loss: 0.00451 +Epoch [2332/4000] Training [7/16] Loss: 0.00435 +Epoch [2332/4000] Training [8/16] Loss: 0.00651 +Epoch [2332/4000] Training [9/16] Loss: 0.00499 +Epoch [2332/4000] Training [10/16] Loss: 0.00397 +Epoch [2332/4000] Training [11/16] Loss: 0.00622 +Epoch [2332/4000] Training [12/16] Loss: 0.00543 +Epoch [2332/4000] Training [13/16] Loss: 0.00427 +Epoch [2332/4000] Training [14/16] Loss: 0.00459 +Epoch [2332/4000] Training [15/16] Loss: 0.00433 +Epoch [2332/4000] Training [16/16] Loss: 0.00550 +Epoch [2332/4000] Training metric {'Train/mean dice_metric': 0.9967888593673706, 'Train/mean miou_metric': 0.9933297038078308, 'Train/mean f1': 0.9923742413520813, 'Train/mean precision': 0.9877888560295105, 'Train/mean recall': 0.997002363204956, 'Train/mean hd95_metric': 0.9830211400985718} +Epoch [2332/4000] Validation [1/4] Loss: 0.33673 focal_loss 0.26856 dice_loss 0.06817 +Epoch [2332/4000] Validation [2/4] Loss: 0.38307 focal_loss 0.24740 dice_loss 0.13566 +Epoch [2332/4000] Validation [3/4] Loss: 0.30363 focal_loss 0.21300 dice_loss 0.09062 +Epoch [2332/4000] Validation [4/4] Loss: 0.60612 focal_loss 0.43614 dice_loss 0.16998 +Epoch [2332/4000] Validation metric {'Val/mean dice_metric': 0.9735673666000366, 'Val/mean miou_metric': 0.9573978185653687, 'Val/mean f1': 0.9749271869659424, 'Val/mean precision': 0.9731755256652832, 'Val/mean recall': 0.9766852259635925, 'Val/mean hd95_metric': 5.427034854888916} +Cheakpoint... +Epoch [2332/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735673666000366, 'Val/mean miou_metric': 0.9573978185653687, 'Val/mean f1': 0.9749271869659424, 'Val/mean precision': 0.9731755256652832, 'Val/mean recall': 0.9766852259635925, 'Val/mean hd95_metric': 5.427034854888916} +Epoch [2333/4000] Training [1/16] Loss: 0.00420 +Epoch [2333/4000] Training [2/16] Loss: 0.00421 +Epoch [2333/4000] Training [3/16] Loss: 0.00645 +Epoch [2333/4000] Training [4/16] Loss: 0.00672 +Epoch [2333/4000] Training [5/16] Loss: 0.00396 +Epoch [2333/4000] Training [6/16] Loss: 0.00461 +Epoch [2333/4000] Training [7/16] Loss: 0.00502 +Epoch [2333/4000] Training [8/16] Loss: 0.00750 +Epoch [2333/4000] Training [9/16] Loss: 0.00466 +Epoch [2333/4000] Training [10/16] Loss: 0.00542 +Epoch [2333/4000] Training [11/16] Loss: 0.00427 +Epoch [2333/4000] Training [12/16] Loss: 0.00515 +Epoch [2333/4000] Training [13/16] Loss: 0.00572 +Epoch [2333/4000] Training [14/16] Loss: 0.00515 +Epoch [2333/4000] Training [15/16] Loss: 0.00510 +Epoch [2333/4000] Training [16/16] Loss: 0.00549 +Epoch [2333/4000] Training metric {'Train/mean dice_metric': 0.9965252876281738, 'Train/mean miou_metric': 0.992798924446106, 'Train/mean f1': 0.9921569228172302, 'Train/mean precision': 0.9874877333641052, 'Train/mean recall': 0.9968705773353577, 'Train/mean hd95_metric': 1.0008337497711182} +Epoch [2333/4000] Validation [1/4] Loss: 0.33529 focal_loss 0.26865 dice_loss 0.06664 +Epoch [2333/4000] Validation [2/4] Loss: 0.35534 focal_loss 0.23230 dice_loss 0.12304 +Epoch [2333/4000] Validation [3/4] Loss: 0.42386 focal_loss 0.33260 dice_loss 0.09126 +Epoch [2333/4000] Validation [4/4] Loss: 0.28382 focal_loss 0.18236 dice_loss 0.10146 +Epoch [2333/4000] Validation metric {'Val/mean dice_metric': 0.9739471673965454, 'Val/mean miou_metric': 0.957965075969696, 'Val/mean f1': 0.9759172797203064, 'Val/mean precision': 0.9716460704803467, 'Val/mean recall': 0.9802262783050537, 'Val/mean hd95_metric': 5.35305118560791} +Cheakpoint... +Epoch [2333/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739471673965454, 'Val/mean miou_metric': 0.957965075969696, 'Val/mean f1': 0.9759172797203064, 'Val/mean precision': 0.9716460704803467, 'Val/mean recall': 0.9802262783050537, 'Val/mean hd95_metric': 5.35305118560791} +Epoch [2334/4000] Training [1/16] Loss: 0.00602 +Epoch [2334/4000] Training [2/16] Loss: 0.00488 +Epoch [2334/4000] Training [3/16] Loss: 0.00426 +Epoch [2334/4000] Training [4/16] Loss: 0.00751 +Epoch [2334/4000] Training [5/16] Loss: 0.00560 +Epoch [2334/4000] Training [6/16] Loss: 0.00531 +Epoch [2334/4000] Training [7/16] Loss: 0.00385 +Epoch [2334/4000] Training [8/16] Loss: 0.00465 +Epoch [2334/4000] Training [9/16] Loss: 0.00401 +Epoch [2334/4000] Training [10/16] Loss: 0.00492 +Epoch [2334/4000] Training [11/16] Loss: 0.00610 +Epoch [2334/4000] Training [12/16] Loss: 0.00526 +Epoch [2334/4000] Training [13/16] Loss: 0.00435 +Epoch [2334/4000] Training [14/16] Loss: 0.00491 +Epoch [2334/4000] Training [15/16] Loss: 0.00527 +Epoch [2334/4000] Training [16/16] Loss: 0.00427 +Epoch [2334/4000] Training metric {'Train/mean dice_metric': 0.9967404007911682, 'Train/mean miou_metric': 0.9932003021240234, 'Train/mean f1': 0.9915822148323059, 'Train/mean precision': 0.9863498210906982, 'Train/mean recall': 0.9968703985214233, 'Train/mean hd95_metric': 0.9879872798919678} +Epoch [2334/4000] Validation [1/4] Loss: 0.33518 focal_loss 0.26904 dice_loss 0.06614 +Epoch [2334/4000] Validation [2/4] Loss: 0.35533 focal_loss 0.22834 dice_loss 0.12699 +Epoch [2334/4000] Validation [3/4] Loss: 0.20211 focal_loss 0.14809 dice_loss 0.05401 +Epoch [2334/4000] Validation [4/4] Loss: 0.37002 focal_loss 0.24654 dice_loss 0.12348 +Epoch [2334/4000] Validation metric {'Val/mean dice_metric': 0.9749574661254883, 'Val/mean miou_metric': 0.9589883685112, 'Val/mean f1': 0.9756978154182434, 'Val/mean precision': 0.9703527092933655, 'Val/mean recall': 0.9811021685600281, 'Val/mean hd95_metric': 5.454437732696533} +Cheakpoint... +Epoch [2334/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749574661254883, 'Val/mean miou_metric': 0.9589883685112, 'Val/mean f1': 0.9756978154182434, 'Val/mean precision': 0.9703527092933655, 'Val/mean recall': 0.9811021685600281, 'Val/mean hd95_metric': 5.454437732696533} +Epoch [2335/4000] Training [1/16] Loss: 0.00511 +Epoch [2335/4000] Training [2/16] Loss: 0.00490 +Epoch [2335/4000] Training [3/16] Loss: 0.00431 +Epoch [2335/4000] Training [4/16] Loss: 0.00641 +Epoch [2335/4000] Training [5/16] Loss: 0.00583 +Epoch [2335/4000] Training [6/16] Loss: 0.00428 +Epoch [2335/4000] Training [7/16] Loss: 0.00443 +Epoch [2335/4000] Training [8/16] Loss: 0.00407 +Epoch [2335/4000] Training [9/16] Loss: 0.00471 +Epoch [2335/4000] Training [10/16] Loss: 0.00641 +Epoch [2335/4000] Training [11/16] Loss: 0.00397 +Epoch [2335/4000] Training [12/16] Loss: 0.00660 +Epoch [2335/4000] Training [13/16] Loss: 0.00534 +Epoch [2335/4000] Training [14/16] Loss: 0.00453 +Epoch [2335/4000] Training [15/16] Loss: 0.00344 +Epoch [2335/4000] Training [16/16] Loss: 0.00385 +Epoch [2335/4000] Training metric {'Train/mean dice_metric': 0.9969317317008972, 'Train/mean miou_metric': 0.9936099052429199, 'Train/mean f1': 0.9924313426017761, 'Train/mean precision': 0.987891435623169, 'Train/mean recall': 0.9970132112503052, 'Train/mean hd95_metric': 0.9813863635063171} +Epoch [2335/4000] Validation [1/4] Loss: 0.30624 focal_loss 0.23482 dice_loss 0.07142 +Epoch [2335/4000] Validation [2/4] Loss: 0.33467 focal_loss 0.20884 dice_loss 0.12583 +Epoch [2335/4000] Validation [3/4] Loss: 0.40111 focal_loss 0.30925 dice_loss 0.09186 +Epoch [2335/4000] Validation [4/4] Loss: 0.25523 focal_loss 0.16141 dice_loss 0.09381 +Epoch [2335/4000] Validation metric {'Val/mean dice_metric': 0.9752050638198853, 'Val/mean miou_metric': 0.9593383073806763, 'Val/mean f1': 0.9760112166404724, 'Val/mean precision': 0.9722514748573303, 'Val/mean recall': 0.9798002243041992, 'Val/mean hd95_metric': 5.431829452514648} +Cheakpoint... +Epoch [2335/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752050638198853, 'Val/mean miou_metric': 0.9593383073806763, 'Val/mean f1': 0.9760112166404724, 'Val/mean precision': 0.9722514748573303, 'Val/mean recall': 0.9798002243041992, 'Val/mean hd95_metric': 5.431829452514648} +Epoch [2336/4000] Training [1/16] Loss: 0.00496 +Epoch [2336/4000] Training [2/16] Loss: 0.00440 +Epoch [2336/4000] Training [3/16] Loss: 0.00523 +Epoch [2336/4000] Training [4/16] Loss: 0.00471 +Epoch [2336/4000] Training [5/16] Loss: 0.00501 +Epoch [2336/4000] Training [6/16] Loss: 0.00713 +Epoch [2336/4000] Training [7/16] Loss: 0.00508 +Epoch [2336/4000] Training [8/16] Loss: 0.00443 +Epoch [2336/4000] Training [9/16] Loss: 0.00421 +Epoch [2336/4000] Training [10/16] Loss: 0.00423 +Epoch [2336/4000] Training [11/16] Loss: 0.00342 +Epoch [2336/4000] Training [12/16] Loss: 0.00728 +Epoch [2336/4000] Training [13/16] Loss: 0.00526 +Epoch [2336/4000] Training [14/16] Loss: 0.00903 +Epoch [2336/4000] Training [15/16] Loss: 0.00514 +Epoch [2336/4000] Training [16/16] Loss: 0.00480 +Epoch [2336/4000] Training metric {'Train/mean dice_metric': 0.9965206384658813, 'Train/mean miou_metric': 0.9928146600723267, 'Train/mean f1': 0.992188572883606, 'Train/mean precision': 0.987801194190979, 'Train/mean recall': 0.9966151714324951, 'Train/mean hd95_metric': 1.0424628257751465} +Epoch [2336/4000] Validation [1/4] Loss: 0.36044 focal_loss 0.28963 dice_loss 0.07081 +Epoch [2336/4000] Validation [2/4] Loss: 0.27653 focal_loss 0.17306 dice_loss 0.10347 +Epoch [2336/4000] Validation [3/4] Loss: 0.42288 focal_loss 0.32832 dice_loss 0.09457 +Epoch [2336/4000] Validation [4/4] Loss: 0.36352 focal_loss 0.25341 dice_loss 0.11011 +Epoch [2336/4000] Validation metric {'Val/mean dice_metric': 0.9712591171264648, 'Val/mean miou_metric': 0.9554616212844849, 'Val/mean f1': 0.9745005369186401, 'Val/mean precision': 0.9693019986152649, 'Val/mean recall': 0.9797549843788147, 'Val/mean hd95_metric': 5.945378303527832} +Cheakpoint... +Epoch [2336/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712591171264648, 'Val/mean miou_metric': 0.9554616212844849, 'Val/mean f1': 0.9745005369186401, 'Val/mean precision': 0.9693019986152649, 'Val/mean recall': 0.9797549843788147, 'Val/mean hd95_metric': 5.945378303527832} +Epoch [2337/4000] Training [1/16] Loss: 0.00496 +Epoch [2337/4000] Training [2/16] Loss: 0.00459 +Epoch [2337/4000] Training [3/16] Loss: 0.00455 +Epoch [2337/4000] Training [4/16] Loss: 0.00557 +Epoch [2337/4000] Training [5/16] Loss: 0.00407 +Epoch [2337/4000] Training [6/16] Loss: 0.00475 +Epoch [2337/4000] Training [7/16] Loss: 0.00663 +Epoch [2337/4000] Training [8/16] Loss: 0.00524 +Epoch [2337/4000] Training [9/16] Loss: 0.00403 +Epoch [2337/4000] Training [10/16] Loss: 0.00601 +Epoch [2337/4000] Training [11/16] Loss: 0.00660 +Epoch [2337/4000] Training [12/16] Loss: 0.00489 +Epoch [2337/4000] Training [13/16] Loss: 0.00435 +Epoch [2337/4000] Training [14/16] Loss: 0.00400 +Epoch [2337/4000] Training [15/16] Loss: 0.00463 +Epoch [2337/4000] Training [16/16] Loss: 0.00604 +Epoch [2337/4000] Training metric {'Train/mean dice_metric': 0.9967004060745239, 'Train/mean miou_metric': 0.9931584000587463, 'Train/mean f1': 0.9923051595687866, 'Train/mean precision': 0.9877787828445435, 'Train/mean recall': 0.996873140335083, 'Train/mean hd95_metric': 0.9815366268157959} +Epoch [2337/4000] Validation [1/4] Loss: 0.37967 focal_loss 0.31143 dice_loss 0.06824 +Epoch [2337/4000] Validation [2/4] Loss: 0.35276 focal_loss 0.23704 dice_loss 0.11572 +Epoch [2337/4000] Validation [3/4] Loss: 0.19841 focal_loss 0.14588 dice_loss 0.05253 +Epoch [2337/4000] Validation [4/4] Loss: 0.24533 focal_loss 0.15631 dice_loss 0.08902 +Epoch [2337/4000] Validation metric {'Val/mean dice_metric': 0.9741759300231934, 'Val/mean miou_metric': 0.9586588144302368, 'Val/mean f1': 0.9759021401405334, 'Val/mean precision': 0.9718522429466248, 'Val/mean recall': 0.979985773563385, 'Val/mean hd95_metric': 5.389960289001465} +Cheakpoint... +Epoch [2337/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741759300231934, 'Val/mean miou_metric': 0.9586588144302368, 'Val/mean f1': 0.9759021401405334, 'Val/mean precision': 0.9718522429466248, 'Val/mean recall': 0.979985773563385, 'Val/mean hd95_metric': 5.389960289001465} +Epoch [2338/4000] Training [1/16] Loss: 0.00595 +Epoch [2338/4000] Training [2/16] Loss: 0.00607 +Epoch [2338/4000] Training [3/16] Loss: 0.00665 +Epoch [2338/4000] Training [4/16] Loss: 0.00446 +Epoch [2338/4000] Training [5/16] Loss: 0.00386 +Epoch [2338/4000] Training [6/16] Loss: 0.00393 +Epoch [2338/4000] Training [7/16] Loss: 0.00403 +Epoch [2338/4000] Training [8/16] Loss: 0.00347 +Epoch [2338/4000] Training [9/16] Loss: 0.00558 +Epoch [2338/4000] Training [10/16] Loss: 0.00461 +Epoch [2338/4000] Training [11/16] Loss: 0.00505 +Epoch [2338/4000] Training [12/16] Loss: 0.00488 +Epoch [2338/4000] Training [13/16] Loss: 0.00418 +Epoch [2338/4000] Training [14/16] Loss: 0.00802 +Epoch [2338/4000] Training [15/16] Loss: 0.00615 +Epoch [2338/4000] Training [16/16] Loss: 0.00447 +Epoch [2338/4000] Training metric {'Train/mean dice_metric': 0.9968201518058777, 'Train/mean miou_metric': 0.9933748245239258, 'Train/mean f1': 0.9921231865882874, 'Train/mean precision': 0.9873433709144592, 'Train/mean recall': 0.9969495534896851, 'Train/mean hd95_metric': 0.9837594628334045} +Epoch [2338/4000] Validation [1/4] Loss: 0.36811 focal_loss 0.29416 dice_loss 0.07395 +Epoch [2338/4000] Validation [2/4] Loss: 0.31954 focal_loss 0.20506 dice_loss 0.11448 +Epoch [2338/4000] Validation [3/4] Loss: 0.43699 focal_loss 0.34472 dice_loss 0.09227 +Epoch [2338/4000] Validation [4/4] Loss: 0.24829 focal_loss 0.15892 dice_loss 0.08937 +Epoch [2338/4000] Validation metric {'Val/mean dice_metric': 0.9736143350601196, 'Val/mean miou_metric': 0.9576389193534851, 'Val/mean f1': 0.9747929573059082, 'Val/mean precision': 0.9720562696456909, 'Val/mean recall': 0.9775452017784119, 'Val/mean hd95_metric': 5.887350559234619} +Cheakpoint... +Epoch [2338/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736143350601196, 'Val/mean miou_metric': 0.9576389193534851, 'Val/mean f1': 0.9747929573059082, 'Val/mean precision': 0.9720562696456909, 'Val/mean recall': 0.9775452017784119, 'Val/mean hd95_metric': 5.887350559234619} +Epoch [2339/4000] Training [1/16] Loss: 0.00477 +Epoch [2339/4000] Training [2/16] Loss: 0.00676 +Epoch [2339/4000] Training [3/16] Loss: 0.00656 +Epoch [2339/4000] Training [4/16] Loss: 0.00669 +Epoch [2339/4000] Training [5/16] Loss: 0.00505 +Epoch [2339/4000] Training [6/16] Loss: 0.00461 +Epoch [2339/4000] Training [7/16] Loss: 0.00429 +Epoch [2339/4000] Training [8/16] Loss: 0.00367 +Epoch [2339/4000] Training [9/16] Loss: 0.00424 +Epoch [2339/4000] Training [10/16] Loss: 0.00510 +Epoch [2339/4000] Training [11/16] Loss: 0.00599 +Epoch [2339/4000] Training [12/16] Loss: 0.00414 +Epoch [2339/4000] Training [13/16] Loss: 0.00549 +Epoch [2339/4000] Training [14/16] Loss: 0.00415 +Epoch [2339/4000] Training [15/16] Loss: 0.00466 +Epoch [2339/4000] Training [16/16] Loss: 0.00392 +Epoch [2339/4000] Training metric {'Train/mean dice_metric': 0.9970161318778992, 'Train/mean miou_metric': 0.9937830567359924, 'Train/mean f1': 0.9925304651260376, 'Train/mean precision': 0.9880436062812805, 'Train/mean recall': 0.9970582127571106, 'Train/mean hd95_metric': 0.9764469265937805} +Epoch [2339/4000] Validation [1/4] Loss: 0.35183 focal_loss 0.28555 dice_loss 0.06628 +Epoch [2339/4000] Validation [2/4] Loss: 0.53502 focal_loss 0.37265 dice_loss 0.16236 +Epoch [2339/4000] Validation [3/4] Loss: 0.45828 focal_loss 0.35724 dice_loss 0.10105 +Epoch [2339/4000] Validation [4/4] Loss: 0.25982 focal_loss 0.16649 dice_loss 0.09333 +Epoch [2339/4000] Validation metric {'Val/mean dice_metric': 0.974407970905304, 'Val/mean miou_metric': 0.9589633941650391, 'Val/mean f1': 0.9751787781715393, 'Val/mean precision': 0.9710644483566284, 'Val/mean recall': 0.9793280959129333, 'Val/mean hd95_metric': 5.383737564086914} +Cheakpoint... +Epoch [2339/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974407970905304, 'Val/mean miou_metric': 0.9589633941650391, 'Val/mean f1': 0.9751787781715393, 'Val/mean precision': 0.9710644483566284, 'Val/mean recall': 0.9793280959129333, 'Val/mean hd95_metric': 5.383737564086914} +Epoch [2340/4000] Training [1/16] Loss: 0.00701 +Epoch [2340/4000] Training [2/16] Loss: 0.00485 +Epoch [2340/4000] Training [3/16] Loss: 0.00360 +Epoch [2340/4000] Training [4/16] Loss: 0.00472 +Epoch [2340/4000] Training [5/16] Loss: 0.00498 +Epoch [2340/4000] Training [6/16] Loss: 0.00539 +Epoch [2340/4000] Training [7/16] Loss: 0.00461 +Epoch [2340/4000] Training [8/16] Loss: 0.00513 +Epoch [2340/4000] Training [9/16] Loss: 0.00403 +Epoch [2340/4000] Training [10/16] Loss: 0.00470 +Epoch [2340/4000] Training [11/16] Loss: 0.00386 +Epoch [2340/4000] Training [12/16] Loss: 0.00420 +Epoch [2340/4000] Training [13/16] Loss: 0.00487 +Epoch [2340/4000] Training [14/16] Loss: 0.00427 +Epoch [2340/4000] Training [15/16] Loss: 0.00502 +Epoch [2340/4000] Training [16/16] Loss: 0.00438 +Epoch [2340/4000] Training metric {'Train/mean dice_metric': 0.9967819452285767, 'Train/mean miou_metric': 0.9933134913444519, 'Train/mean f1': 0.9921921491622925, 'Train/mean precision': 0.9874452948570251, 'Train/mean recall': 0.9969849586486816, 'Train/mean hd95_metric': 0.9814693927764893} +Epoch [2340/4000] Validation [1/4] Loss: 0.27978 focal_loss 0.21562 dice_loss 0.06416 +Epoch [2340/4000] Validation [2/4] Loss: 0.36447 focal_loss 0.22779 dice_loss 0.13668 +Epoch [2340/4000] Validation [3/4] Loss: 0.38550 focal_loss 0.29956 dice_loss 0.08594 +Epoch [2340/4000] Validation [4/4] Loss: 0.27162 focal_loss 0.17624 dice_loss 0.09538 +Epoch [2340/4000] Validation metric {'Val/mean dice_metric': 0.9744077920913696, 'Val/mean miou_metric': 0.9587455987930298, 'Val/mean f1': 0.9751367568969727, 'Val/mean precision': 0.9719234704971313, 'Val/mean recall': 0.9783713221549988, 'Val/mean hd95_metric': 5.181676387786865} +Cheakpoint... +Epoch [2340/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744077920913696, 'Val/mean miou_metric': 0.9587455987930298, 'Val/mean f1': 0.9751367568969727, 'Val/mean precision': 0.9719234704971313, 'Val/mean recall': 0.9783713221549988, 'Val/mean hd95_metric': 5.181676387786865} +Epoch [2341/4000] Training [1/16] Loss: 0.00513 +Epoch [2341/4000] Training [2/16] Loss: 0.00537 +Epoch [2341/4000] Training [3/16] Loss: 0.00443 +Epoch [2341/4000] Training [4/16] Loss: 0.00576 +Epoch [2341/4000] Training [5/16] Loss: 0.00540 +Epoch [2341/4000] Training [6/16] Loss: 0.00442 +Epoch [2341/4000] Training [7/16] Loss: 0.00451 +Epoch [2341/4000] Training [8/16] Loss: 0.00527 +Epoch [2341/4000] Training [9/16] Loss: 0.00490 +Epoch [2341/4000] Training [10/16] Loss: 0.00484 +Epoch [2341/4000] Training [11/16] Loss: 0.00397 +Epoch [2341/4000] Training [12/16] Loss: 0.00446 +Epoch [2341/4000] Training [13/16] Loss: 0.00465 +Epoch [2341/4000] Training [14/16] Loss: 0.00580 +Epoch [2341/4000] Training [15/16] Loss: 0.00404 +Epoch [2341/4000] Training [16/16] Loss: 0.00535 +Epoch [2341/4000] Training metric {'Train/mean dice_metric': 0.9968103766441345, 'Train/mean miou_metric': 0.9933741688728333, 'Train/mean f1': 0.9923684597015381, 'Train/mean precision': 0.9878341555595398, 'Train/mean recall': 0.9969446063041687, 'Train/mean hd95_metric': 0.9848067760467529} +Epoch [2341/4000] Validation [1/4] Loss: 0.35119 focal_loss 0.28435 dice_loss 0.06685 +Epoch [2341/4000] Validation [2/4] Loss: 0.78198 focal_loss 0.58450 dice_loss 0.19748 +Epoch [2341/4000] Validation [3/4] Loss: 0.40263 focal_loss 0.31404 dice_loss 0.08859 +Epoch [2341/4000] Validation [4/4] Loss: 0.22786 focal_loss 0.13478 dice_loss 0.09307 +Epoch [2341/4000] Validation metric {'Val/mean dice_metric': 0.9743804931640625, 'Val/mean miou_metric': 0.959104061126709, 'Val/mean f1': 0.9756179451942444, 'Val/mean precision': 0.9719654321670532, 'Val/mean recall': 0.9792980551719666, 'Val/mean hd95_metric': 5.569136619567871} +Cheakpoint... +Epoch [2341/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743804931640625, 'Val/mean miou_metric': 0.959104061126709, 'Val/mean f1': 0.9756179451942444, 'Val/mean precision': 0.9719654321670532, 'Val/mean recall': 0.9792980551719666, 'Val/mean hd95_metric': 5.569136619567871} +Epoch [2342/4000] Training [1/16] Loss: 0.00464 +Epoch [2342/4000] Training [2/16] Loss: 0.00479 +Epoch [2342/4000] Training [3/16] Loss: 0.00585 +Epoch [2342/4000] Training [4/16] Loss: 0.00415 +Epoch [2342/4000] Training [5/16] Loss: 0.00471 +Epoch [2342/4000] Training [6/16] Loss: 0.00502 +Epoch [2342/4000] Training [7/16] Loss: 0.00334 +Epoch [2342/4000] Training [8/16] Loss: 0.00379 +Epoch [2342/4000] Training [9/16] Loss: 0.00511 +Epoch [2342/4000] Training [10/16] Loss: 0.00511 +Epoch [2342/4000] Training [11/16] Loss: 0.00492 +Epoch [2342/4000] Training [12/16] Loss: 0.00341 +Epoch [2342/4000] Training [13/16] Loss: 0.00391 +Epoch [2342/4000] Training [14/16] Loss: 0.00523 +Epoch [2342/4000] Training [15/16] Loss: 0.00433 +Epoch [2342/4000] Training [16/16] Loss: 0.00357 +Epoch [2342/4000] Training metric {'Train/mean dice_metric': 0.9968992471694946, 'Train/mean miou_metric': 0.9935531616210938, 'Train/mean f1': 0.992523193359375, 'Train/mean precision': 0.9880067110061646, 'Train/mean recall': 0.9970811009407043, 'Train/mean hd95_metric': 0.9890481233596802} +Epoch [2342/4000] Validation [1/4] Loss: 0.36275 focal_loss 0.29303 dice_loss 0.06972 +Epoch [2342/4000] Validation [2/4] Loss: 0.30727 focal_loss 0.19196 dice_loss 0.11531 +Epoch [2342/4000] Validation [3/4] Loss: 0.42582 focal_loss 0.32654 dice_loss 0.09928 +Epoch [2342/4000] Validation [4/4] Loss: 0.50986 focal_loss 0.36502 dice_loss 0.14484 +Epoch [2342/4000] Validation metric {'Val/mean dice_metric': 0.9743421673774719, 'Val/mean miou_metric': 0.9584152102470398, 'Val/mean f1': 0.9754197597503662, 'Val/mean precision': 0.9730177521705627, 'Val/mean recall': 0.9778335690498352, 'Val/mean hd95_metric': 5.3939948081970215} +Cheakpoint... +Epoch [2342/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743421673774719, 'Val/mean miou_metric': 0.9584152102470398, 'Val/mean f1': 0.9754197597503662, 'Val/mean precision': 0.9730177521705627, 'Val/mean recall': 0.9778335690498352, 'Val/mean hd95_metric': 5.3939948081970215} +Epoch [2343/4000] Training [1/16] Loss: 0.00517 +Epoch [2343/4000] Training [2/16] Loss: 0.00753 +Epoch [2343/4000] Training [3/16] Loss: 0.00490 +Epoch [2343/4000] Training [4/16] Loss: 0.00361 +Epoch [2343/4000] Training [5/16] Loss: 0.00724 +Epoch [2343/4000] Training [6/16] Loss: 0.00494 +Epoch [2343/4000] Training [7/16] Loss: 0.00507 +Epoch [2343/4000] Training [8/16] Loss: 0.00340 +Epoch [2343/4000] Training [9/16] Loss: 0.00447 +Epoch [2343/4000] Training [10/16] Loss: 0.00476 +Epoch [2343/4000] Training [11/16] Loss: 0.00419 +Epoch [2343/4000] Training [12/16] Loss: 0.00493 +Epoch [2343/4000] Training [13/16] Loss: 0.00484 +Epoch [2343/4000] Training [14/16] Loss: 0.00364 +Epoch [2343/4000] Training [15/16] Loss: 0.00657 +Epoch [2343/4000] Training [16/16] Loss: 0.00381 +Epoch [2343/4000] Training metric {'Train/mean dice_metric': 0.9969133138656616, 'Train/mean miou_metric': 0.9935690760612488, 'Train/mean f1': 0.9922832250595093, 'Train/mean precision': 0.9877079129219055, 'Train/mean recall': 0.9969010949134827, 'Train/mean hd95_metric': 0.9892162084579468} +Epoch [2343/4000] Validation [1/4] Loss: 0.33014 focal_loss 0.26118 dice_loss 0.06896 +Epoch [2343/4000] Validation [2/4] Loss: 0.55708 focal_loss 0.39852 dice_loss 0.15856 +Epoch [2343/4000] Validation [3/4] Loss: 0.42609 focal_loss 0.33449 dice_loss 0.09160 +Epoch [2343/4000] Validation [4/4] Loss: 0.27276 focal_loss 0.17762 dice_loss 0.09514 +Epoch [2343/4000] Validation metric {'Val/mean dice_metric': 0.9734116792678833, 'Val/mean miou_metric': 0.9577083587646484, 'Val/mean f1': 0.975525975227356, 'Val/mean precision': 0.9720525741577148, 'Val/mean recall': 0.9790245294570923, 'Val/mean hd95_metric': 5.665706634521484} +Cheakpoint... +Epoch [2343/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734116792678833, 'Val/mean miou_metric': 0.9577083587646484, 'Val/mean f1': 0.975525975227356, 'Val/mean precision': 0.9720525741577148, 'Val/mean recall': 0.9790245294570923, 'Val/mean hd95_metric': 5.665706634521484} +Epoch [2344/4000] Training [1/16] Loss: 0.00631 +Epoch [2344/4000] Training [2/16] Loss: 0.00447 +Epoch [2344/4000] Training [3/16] Loss: 0.00474 +Epoch [2344/4000] Training [4/16] Loss: 0.00610 +Epoch [2344/4000] Training [5/16] Loss: 0.00679 +Epoch [2344/4000] Training [6/16] Loss: 0.00500 +Epoch [2344/4000] Training [7/16] Loss: 0.00819 +Epoch [2344/4000] Training [8/16] Loss: 0.00387 +Epoch [2344/4000] Training [9/16] Loss: 0.00383 +Epoch [2344/4000] Training [10/16] Loss: 0.00560 +Epoch [2344/4000] Training [11/16] Loss: 0.00481 +Epoch [2344/4000] Training [12/16] Loss: 0.00380 +Epoch [2344/4000] Training [13/16] Loss: 0.00414 +Epoch [2344/4000] Training [14/16] Loss: 0.00493 +Epoch [2344/4000] Training [15/16] Loss: 0.00623 +Epoch [2344/4000] Training [16/16] Loss: 0.00594 +Epoch [2344/4000] Training metric {'Train/mean dice_metric': 0.99648517370224, 'Train/mean miou_metric': 0.9927300214767456, 'Train/mean f1': 0.991874635219574, 'Train/mean precision': 0.9870445728302002, 'Train/mean recall': 0.9967522025108337, 'Train/mean hd95_metric': 1.0410637855529785} +Epoch [2344/4000] Validation [1/4] Loss: 0.33562 focal_loss 0.26480 dice_loss 0.07082 +Epoch [2344/4000] Validation [2/4] Loss: 0.32600 focal_loss 0.21032 dice_loss 0.11568 +Epoch [2344/4000] Validation [3/4] Loss: 0.42269 focal_loss 0.33040 dice_loss 0.09229 +Epoch [2344/4000] Validation [4/4] Loss: 0.24323 focal_loss 0.16506 dice_loss 0.07818 +Epoch [2344/4000] Validation metric {'Val/mean dice_metric': 0.9737957119941711, 'Val/mean miou_metric': 0.9577867388725281, 'Val/mean f1': 0.975095272064209, 'Val/mean precision': 0.9723936915397644, 'Val/mean recall': 0.9778118133544922, 'Val/mean hd95_metric': 5.421229362487793} +Cheakpoint... +Epoch [2344/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737957119941711, 'Val/mean miou_metric': 0.9577867388725281, 'Val/mean f1': 0.975095272064209, 'Val/mean precision': 0.9723936915397644, 'Val/mean recall': 0.9778118133544922, 'Val/mean hd95_metric': 5.421229362487793} +Epoch [2345/4000] Training [1/16] Loss: 0.00558 +Epoch [2345/4000] Training [2/16] Loss: 0.00469 +Epoch [2345/4000] Training [3/16] Loss: 0.00398 +Epoch [2345/4000] Training [4/16] Loss: 0.00353 +Epoch [2345/4000] Training [5/16] Loss: 0.00604 +Epoch [2345/4000] Training [6/16] Loss: 0.00487 +Epoch [2345/4000] Training [7/16] Loss: 0.00417 +Epoch [2345/4000] Training [8/16] Loss: 0.00585 +Epoch [2345/4000] Training [9/16] Loss: 0.00604 +Epoch [2345/4000] Training [10/16] Loss: 0.00419 +Epoch [2345/4000] Training [11/16] Loss: 0.00641 +Epoch [2345/4000] Training [12/16] Loss: 0.00361 +Epoch [2345/4000] Training [13/16] Loss: 0.00570 +Epoch [2345/4000] Training [14/16] Loss: 0.00426 +Epoch [2345/4000] Training [15/16] Loss: 0.00555 +Epoch [2345/4000] Training [16/16] Loss: 0.00597 +Epoch [2345/4000] Training metric {'Train/mean dice_metric': 0.9966864585876465, 'Train/mean miou_metric': 0.9931305646896362, 'Train/mean f1': 0.9923454523086548, 'Train/mean precision': 0.9878904223442078, 'Train/mean recall': 0.9968408346176147, 'Train/mean hd95_metric': 0.9813113212585449} +Epoch [2345/4000] Validation [1/4] Loss: 0.32909 focal_loss 0.25806 dice_loss 0.07104 +Epoch [2345/4000] Validation [2/4] Loss: 0.77776 focal_loss 0.57797 dice_loss 0.19978 +Epoch [2345/4000] Validation [3/4] Loss: 0.39343 focal_loss 0.29235 dice_loss 0.10108 +Epoch [2345/4000] Validation [4/4] Loss: 0.32915 focal_loss 0.22485 dice_loss 0.10430 +Epoch [2345/4000] Validation metric {'Val/mean dice_metric': 0.9719266891479492, 'Val/mean miou_metric': 0.9564935564994812, 'Val/mean f1': 0.9752664566040039, 'Val/mean precision': 0.9748409986495972, 'Val/mean recall': 0.9756922125816345, 'Val/mean hd95_metric': 5.345795154571533} +Cheakpoint... +Epoch [2345/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719266891479492, 'Val/mean miou_metric': 0.9564935564994812, 'Val/mean f1': 0.9752664566040039, 'Val/mean precision': 0.9748409986495972, 'Val/mean recall': 0.9756922125816345, 'Val/mean hd95_metric': 5.345795154571533} +Epoch [2346/4000] Training [1/16] Loss: 0.00475 +Epoch [2346/4000] Training [2/16] Loss: 0.00462 +Epoch [2346/4000] Training [3/16] Loss: 0.00435 +Epoch [2346/4000] Training [4/16] Loss: 0.00488 +Epoch [2346/4000] Training [5/16] Loss: 0.00715 +Epoch [2346/4000] Training [6/16] Loss: 0.00554 +Epoch [2346/4000] Training [7/16] Loss: 0.00469 +Epoch [2346/4000] Training [8/16] Loss: 0.00517 +Epoch [2346/4000] Training [9/16] Loss: 0.00648 +Epoch [2346/4000] Training [10/16] Loss: 0.00429 +Epoch [2346/4000] Training [11/16] Loss: 0.00555 +Epoch [2346/4000] Training [12/16] Loss: 0.00620 +Epoch [2346/4000] Training [13/16] Loss: 0.00504 +Epoch [2346/4000] Training [14/16] Loss: 0.00455 +Epoch [2346/4000] Training [15/16] Loss: 0.00465 +Epoch [2346/4000] Training [16/16] Loss: 0.00465 +Epoch [2346/4000] Training metric {'Train/mean dice_metric': 0.9968634843826294, 'Train/mean miou_metric': 0.993480920791626, 'Train/mean f1': 0.9923580884933472, 'Train/mean precision': 0.987704873085022, 'Train/mean recall': 0.9970554113388062, 'Train/mean hd95_metric': 0.9888498783111572} +Epoch [2346/4000] Validation [1/4] Loss: 0.39037 focal_loss 0.31052 dice_loss 0.07984 +Epoch [2346/4000] Validation [2/4] Loss: 0.37132 focal_loss 0.24420 dice_loss 0.12712 +Epoch [2346/4000] Validation [3/4] Loss: 0.41872 focal_loss 0.32191 dice_loss 0.09681 +Epoch [2346/4000] Validation [4/4] Loss: 0.52339 focal_loss 0.39431 dice_loss 0.12908 +Epoch [2346/4000] Validation metric {'Val/mean dice_metric': 0.9751491546630859, 'Val/mean miou_metric': 0.9587970972061157, 'Val/mean f1': 0.9744945168495178, 'Val/mean precision': 0.9744263291358948, 'Val/mean recall': 0.9745627045631409, 'Val/mean hd95_metric': 5.546193599700928} +Cheakpoint... +Epoch [2346/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751491546630859, 'Val/mean miou_metric': 0.9587970972061157, 'Val/mean f1': 0.9744945168495178, 'Val/mean precision': 0.9744263291358948, 'Val/mean recall': 0.9745627045631409, 'Val/mean hd95_metric': 5.546193599700928} +Epoch [2347/4000] Training [1/16] Loss: 0.00409 +Epoch [2347/4000] Training [2/16] Loss: 0.00542 +Epoch [2347/4000] Training [3/16] Loss: 0.00561 +Epoch [2347/4000] Training [4/16] Loss: 0.00504 +Epoch [2347/4000] Training [5/16] Loss: 0.00399 +Epoch [2347/4000] Training [6/16] Loss: 0.00368 +Epoch [2347/4000] Training [7/16] Loss: 0.00674 +Epoch [2347/4000] Training [8/16] Loss: 0.00651 +Epoch [2347/4000] Training [9/16] Loss: 0.00485 +Epoch [2347/4000] Training [10/16] Loss: 0.00563 +Epoch [2347/4000] Training [11/16] Loss: 0.00477 +Epoch [2347/4000] Training [12/16] Loss: 0.00558 +Epoch [2347/4000] Training [13/16] Loss: 0.00502 +Epoch [2347/4000] Training [14/16] Loss: 0.00449 +Epoch [2347/4000] Training [15/16] Loss: 0.00333 +Epoch [2347/4000] Training [16/16] Loss: 0.00727 +Epoch [2347/4000] Training metric {'Train/mean dice_metric': 0.9966200590133667, 'Train/mean miou_metric': 0.9930009841918945, 'Train/mean f1': 0.9923413991928101, 'Train/mean precision': 0.9879157543182373, 'Train/mean recall': 0.996806800365448, 'Train/mean hd95_metric': 0.9942377805709839} +Epoch [2347/4000] Validation [1/4] Loss: 0.31945 focal_loss 0.25139 dice_loss 0.06805 +Epoch [2347/4000] Validation [2/4] Loss: 0.58573 focal_loss 0.41141 dice_loss 0.17433 +Epoch [2347/4000] Validation [3/4] Loss: 0.41814 focal_loss 0.32811 dice_loss 0.09003 +Epoch [2347/4000] Validation [4/4] Loss: 0.52378 focal_loss 0.40026 dice_loss 0.12352 +Epoch [2347/4000] Validation metric {'Val/mean dice_metric': 0.9733638763427734, 'Val/mean miou_metric': 0.9571801424026489, 'Val/mean f1': 0.9750096797943115, 'Val/mean precision': 0.9741772413253784, 'Val/mean recall': 0.9758434295654297, 'Val/mean hd95_metric': 5.338240146636963} +Cheakpoint... +Epoch [2347/4000] best acc:tensor([0.9759], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733638763427734, 'Val/mean miou_metric': 0.9571801424026489, 'Val/mean f1': 0.9750096797943115, 'Val/mean precision': 0.9741772413253784, 'Val/mean recall': 0.9758434295654297, 'Val/mean hd95_metric': 5.338240146636963} +Epoch [2348/4000] Training [1/16] Loss: 0.00547 +Epoch [2348/4000] Training [2/16] Loss: 0.00518 +Epoch [2348/4000] Training [3/16] Loss: 0.00527 +Epoch [2348/4000] Training [4/16] Loss: 0.00731 +Epoch [2348/4000] Training [5/16] Loss: 0.00459 +Epoch [2348/4000] Training [6/16] Loss: 0.00432 +Epoch [2348/4000] Training [7/16] Loss: 0.00464 +Epoch [2348/4000] Training [8/16] Loss: 0.00400 +Epoch [2348/4000] Training [9/16] Loss: 0.00471 +Epoch [2348/4000] Training [10/16] Loss: 0.00553 +Epoch [2348/4000] Training [11/16] Loss: 0.00375 +Epoch [2348/4000] Training [12/16] Loss: 0.00539 +Epoch [2348/4000] Training [13/16] Loss: 0.00479 +Epoch [2348/4000] Training [14/16] Loss: 0.00498 +Epoch [2348/4000] Training [15/16] Loss: 0.00373 +Epoch [2348/4000] Training [16/16] Loss: 0.00628 +Epoch [2348/4000] Training metric {'Train/mean dice_metric': 0.9969966411590576, 'Train/mean miou_metric': 0.9936875104904175, 'Train/mean f1': 0.9910315275192261, 'Train/mean precision': 0.9852333068847656, 'Train/mean recall': 0.996898353099823, 'Train/mean hd95_metric': 0.9809327721595764} +Epoch [2348/4000] Validation [1/4] Loss: 0.33684 focal_loss 0.26819 dice_loss 0.06865 +Epoch [2348/4000] Validation [2/4] Loss: 0.35900 focal_loss 0.23300 dice_loss 0.12600 +Epoch [2348/4000] Validation [3/4] Loss: 0.19784 focal_loss 0.14097 dice_loss 0.05687 +Epoch [2348/4000] Validation [4/4] Loss: 0.26434 focal_loss 0.17142 dice_loss 0.09291 +Epoch [2348/4000] Validation metric {'Val/mean dice_metric': 0.9760611653327942, 'Val/mean miou_metric': 0.9603551626205444, 'Val/mean f1': 0.9746298789978027, 'Val/mean precision': 0.9714074730873108, 'Val/mean recall': 0.977873682975769, 'Val/mean hd95_metric': 5.337923526763916} +Cheakpoint... +Epoch [2348/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9761], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9760611653327942, 'Val/mean miou_metric': 0.9603551626205444, 'Val/mean f1': 0.9746298789978027, 'Val/mean precision': 0.9714074730873108, 'Val/mean recall': 0.977873682975769, 'Val/mean hd95_metric': 5.337923526763916} +Epoch [2349/4000] Training [1/16] Loss: 0.00480 +Epoch [2349/4000] Training [2/16] Loss: 0.00433 +Epoch [2349/4000] Training [3/16] Loss: 0.00462 +Epoch [2349/4000] Training [4/16] Loss: 0.00549 +Epoch [2349/4000] Training [5/16] Loss: 0.00454 +Epoch [2349/4000] Training [6/16] Loss: 0.00379 +Epoch [2349/4000] Training [7/16] Loss: 0.00400 +Epoch [2349/4000] Training [8/16] Loss: 0.00573 +Epoch [2349/4000] Training [9/16] Loss: 0.00484 +Epoch [2349/4000] Training [10/16] Loss: 0.00671 +Epoch [2349/4000] Training [11/16] Loss: 0.00452 +Epoch [2349/4000] Training [12/16] Loss: 0.00496 +Epoch [2349/4000] Training [13/16] Loss: 0.00472 +Epoch [2349/4000] Training [14/16] Loss: 0.00529 +Epoch [2349/4000] Training [15/16] Loss: 0.00535 +Epoch [2349/4000] Training [16/16] Loss: 0.00514 +Epoch [2349/4000] Training metric {'Train/mean dice_metric': 0.9969573020935059, 'Train/mean miou_metric': 0.9936655759811401, 'Train/mean f1': 0.9924939870834351, 'Train/mean precision': 0.9880056381225586, 'Train/mean recall': 0.997023344039917, 'Train/mean hd95_metric': 0.9675359725952148} +Epoch [2349/4000] Validation [1/4] Loss: 0.34894 focal_loss 0.27955 dice_loss 0.06939 +Epoch [2349/4000] Validation [2/4] Loss: 0.37283 focal_loss 0.24676 dice_loss 0.12607 +Epoch [2349/4000] Validation [3/4] Loss: 0.41557 focal_loss 0.32436 dice_loss 0.09121 +Epoch [2349/4000] Validation [4/4] Loss: 0.48709 focal_loss 0.35167 dice_loss 0.13543 +Epoch [2349/4000] Validation metric {'Val/mean dice_metric': 0.9733003377914429, 'Val/mean miou_metric': 0.9572162628173828, 'Val/mean f1': 0.9752426743507385, 'Val/mean precision': 0.9738262295722961, 'Val/mean recall': 0.97666335105896, 'Val/mean hd95_metric': 5.679387092590332} +Cheakpoint... +Epoch [2349/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733003377914429, 'Val/mean miou_metric': 0.9572162628173828, 'Val/mean f1': 0.9752426743507385, 'Val/mean precision': 0.9738262295722961, 'Val/mean recall': 0.97666335105896, 'Val/mean hd95_metric': 5.679387092590332} +Epoch [2350/4000] Training [1/16] Loss: 0.00541 +Epoch [2350/4000] Training [2/16] Loss: 0.00451 +Epoch [2350/4000] Training [3/16] Loss: 0.00428 +Epoch [2350/4000] Training [4/16] Loss: 0.00540 +Epoch [2350/4000] Training [5/16] Loss: 0.00737 +Epoch [2350/4000] Training [6/16] Loss: 0.00432 +Epoch [2350/4000] Training [7/16] Loss: 0.00619 +Epoch [2350/4000] Training [8/16] Loss: 0.00413 +Epoch [2350/4000] Training [9/16] Loss: 0.00428 +Epoch [2350/4000] Training [10/16] Loss: 0.00449 +Epoch [2350/4000] Training [11/16] Loss: 0.00704 +Epoch [2350/4000] Training [12/16] Loss: 0.00402 +Epoch [2350/4000] Training [13/16] Loss: 0.00475 +Epoch [2350/4000] Training [14/16] Loss: 0.00457 +Epoch [2350/4000] Training [15/16] Loss: 0.00525 +Epoch [2350/4000] Training [16/16] Loss: 0.00400 +Epoch [2350/4000] Training metric {'Train/mean dice_metric': 0.9968266487121582, 'Train/mean miou_metric': 0.9934070706367493, 'Train/mean f1': 0.9923338294029236, 'Train/mean precision': 0.9878199696540833, 'Train/mean recall': 0.9968891739845276, 'Train/mean hd95_metric': 0.9818775653839111} +Epoch [2350/4000] Validation [1/4] Loss: 0.34562 focal_loss 0.27702 dice_loss 0.06860 +Epoch [2350/4000] Validation [2/4] Loss: 0.37482 focal_loss 0.24516 dice_loss 0.12966 +Epoch [2350/4000] Validation [3/4] Loss: 0.21016 focal_loss 0.15315 dice_loss 0.05701 +Epoch [2350/4000] Validation [4/4] Loss: 0.33732 focal_loss 0.23309 dice_loss 0.10423 +Epoch [2350/4000] Validation metric {'Val/mean dice_metric': 0.9740031361579895, 'Val/mean miou_metric': 0.958416759967804, 'Val/mean f1': 0.9751657843589783, 'Val/mean precision': 0.9726503491401672, 'Val/mean recall': 0.9776943922042847, 'Val/mean hd95_metric': 5.257802486419678} +Cheakpoint... +Epoch [2350/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740031361579895, 'Val/mean miou_metric': 0.958416759967804, 'Val/mean f1': 0.9751657843589783, 'Val/mean precision': 0.9726503491401672, 'Val/mean recall': 0.9776943922042847, 'Val/mean hd95_metric': 5.257802486419678} +Epoch [2351/4000] Training [1/16] Loss: 0.00750 +Epoch [2351/4000] Training [2/16] Loss: 0.00914 +Epoch [2351/4000] Training [3/16] Loss: 0.00382 +Epoch [2351/4000] Training [4/16] Loss: 0.00430 +Epoch [2351/4000] Training [5/16] Loss: 0.00611 +Epoch [2351/4000] Training [6/16] Loss: 0.00648 +Epoch [2351/4000] Training [7/16] Loss: 0.00592 +Epoch [2351/4000] Training [8/16] Loss: 0.00358 +Epoch [2351/4000] Training [9/16] Loss: 0.00448 +Epoch [2351/4000] Training [10/16] Loss: 0.00399 +Epoch [2351/4000] Training [11/16] Loss: 0.00493 +Epoch [2351/4000] Training [12/16] Loss: 0.00414 +Epoch [2351/4000] Training [13/16] Loss: 0.00518 +Epoch [2351/4000] Training [14/16] Loss: 0.00432 +Epoch [2351/4000] Training [15/16] Loss: 0.00415 +Epoch [2351/4000] Training [16/16] Loss: 0.00401 +Epoch [2351/4000] Training metric {'Train/mean dice_metric': 0.9968410730361938, 'Train/mean miou_metric': 0.9933910369873047, 'Train/mean f1': 0.9915328621864319, 'Train/mean precision': 0.9862386584281921, 'Train/mean recall': 0.9968841671943665, 'Train/mean hd95_metric': 0.9703050255775452} +Epoch [2351/4000] Validation [1/4] Loss: 0.37788 focal_loss 0.30595 dice_loss 0.07193 +Epoch [2351/4000] Validation [2/4] Loss: 0.39800 focal_loss 0.26113 dice_loss 0.13686 +Epoch [2351/4000] Validation [3/4] Loss: 0.39023 focal_loss 0.29948 dice_loss 0.09075 +Epoch [2351/4000] Validation [4/4] Loss: 0.27988 focal_loss 0.18925 dice_loss 0.09063 +Epoch [2351/4000] Validation metric {'Val/mean dice_metric': 0.9743908643722534, 'Val/mean miou_metric': 0.9584387540817261, 'Val/mean f1': 0.9740003347396851, 'Val/mean precision': 0.9700955152511597, 'Val/mean recall': 0.977936863899231, 'Val/mean hd95_metric': 5.617565155029297} +Cheakpoint... +Epoch [2351/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743908643722534, 'Val/mean miou_metric': 0.9584387540817261, 'Val/mean f1': 0.9740003347396851, 'Val/mean precision': 0.9700955152511597, 'Val/mean recall': 0.977936863899231, 'Val/mean hd95_metric': 5.617565155029297} +Epoch [2352/4000] Training [1/16] Loss: 0.00602 +Epoch [2352/4000] Training [2/16] Loss: 0.00425 +Epoch [2352/4000] Training [3/16] Loss: 0.00417 +Epoch [2352/4000] Training [4/16] Loss: 0.00641 +Epoch [2352/4000] Training [5/16] Loss: 0.00384 +Epoch [2352/4000] Training [6/16] Loss: 0.00452 +Epoch [2352/4000] Training [7/16] Loss: 0.00417 +Epoch [2352/4000] Training [8/16] Loss: 0.00374 +Epoch [2352/4000] Training [9/16] Loss: 0.00389 +Epoch [2352/4000] Training [10/16] Loss: 0.00424 +Epoch [2352/4000] Training [11/16] Loss: 0.00511 +Epoch [2352/4000] Training [12/16] Loss: 0.00544 +Epoch [2352/4000] Training [13/16] Loss: 0.00536 +Epoch [2352/4000] Training [14/16] Loss: 0.00442 +Epoch [2352/4000] Training [15/16] Loss: 0.00510 +Epoch [2352/4000] Training [16/16] Loss: 0.00482 +Epoch [2352/4000] Training metric {'Train/mean dice_metric': 0.9969695210456848, 'Train/mean miou_metric': 0.9936917424201965, 'Train/mean f1': 0.9925207495689392, 'Train/mean precision': 0.9879693984985352, 'Train/mean recall': 0.9971143007278442, 'Train/mean hd95_metric': 0.9813748598098755} +Epoch [2352/4000] Validation [1/4] Loss: 0.29801 focal_loss 0.23171 dice_loss 0.06630 +Epoch [2352/4000] Validation [2/4] Loss: 0.31861 focal_loss 0.20340 dice_loss 0.11521 +Epoch [2352/4000] Validation [3/4] Loss: 0.43480 focal_loss 0.34291 dice_loss 0.09189 +Epoch [2352/4000] Validation [4/4] Loss: 0.22968 focal_loss 0.14543 dice_loss 0.08425 +Epoch [2352/4000] Validation metric {'Val/mean dice_metric': 0.9747399091720581, 'Val/mean miou_metric': 0.9591256380081177, 'Val/mean f1': 0.9753794074058533, 'Val/mean precision': 0.9716852307319641, 'Val/mean recall': 0.979101836681366, 'Val/mean hd95_metric': 5.8451385498046875} +Cheakpoint... +Epoch [2352/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747399091720581, 'Val/mean miou_metric': 0.9591256380081177, 'Val/mean f1': 0.9753794074058533, 'Val/mean precision': 0.9716852307319641, 'Val/mean recall': 0.979101836681366, 'Val/mean hd95_metric': 5.8451385498046875} +Epoch [2353/4000] Training [1/16] Loss: 0.00507 +Epoch [2353/4000] Training [2/16] Loss: 0.00333 +Epoch [2353/4000] Training [3/16] Loss: 0.00402 +Epoch [2353/4000] Training [4/16] Loss: 0.00516 +Epoch [2353/4000] Training [5/16] Loss: 0.00434 +Epoch [2353/4000] Training [6/16] Loss: 0.00579 +Epoch [2353/4000] Training [7/16] Loss: 0.00520 +Epoch [2353/4000] Training [8/16] Loss: 0.00480 +Epoch [2353/4000] Training [9/16] Loss: 0.00443 +Epoch [2353/4000] Training [10/16] Loss: 0.00405 +Epoch [2353/4000] Training [11/16] Loss: 0.00434 +Epoch [2353/4000] Training [12/16] Loss: 0.00490 +Epoch [2353/4000] Training [13/16] Loss: 0.00344 +Epoch [2353/4000] Training [14/16] Loss: 0.00607 +Epoch [2353/4000] Training [15/16] Loss: 0.00543 +Epoch [2353/4000] Training [16/16] Loss: 0.00418 +Epoch [2353/4000] Training metric {'Train/mean dice_metric': 0.9968816041946411, 'Train/mean miou_metric': 0.993522047996521, 'Train/mean f1': 0.9924967288970947, 'Train/mean precision': 0.988038957118988, 'Train/mean recall': 0.9969949722290039, 'Train/mean hd95_metric': 1.0002070665359497} +Epoch [2353/4000] Validation [1/4] Loss: 0.30345 focal_loss 0.24073 dice_loss 0.06273 +Epoch [2353/4000] Validation [2/4] Loss: 0.39521 focal_loss 0.25886 dice_loss 0.13635 +Epoch [2353/4000] Validation [3/4] Loss: 0.42262 focal_loss 0.33214 dice_loss 0.09048 +Epoch [2353/4000] Validation [4/4] Loss: 0.40648 focal_loss 0.28644 dice_loss 0.12004 +Epoch [2353/4000] Validation metric {'Val/mean dice_metric': 0.9726110696792603, 'Val/mean miou_metric': 0.9568730592727661, 'Val/mean f1': 0.9748681783676147, 'Val/mean precision': 0.9720979928970337, 'Val/mean recall': 0.977654218673706, 'Val/mean hd95_metric': 6.062958240509033} +Cheakpoint... +Epoch [2353/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726110696792603, 'Val/mean miou_metric': 0.9568730592727661, 'Val/mean f1': 0.9748681783676147, 'Val/mean precision': 0.9720979928970337, 'Val/mean recall': 0.977654218673706, 'Val/mean hd95_metric': 6.062958240509033} +Epoch [2354/4000] Training [1/16] Loss: 0.00415 +Epoch [2354/4000] Training [2/16] Loss: 0.00360 +Epoch [2354/4000] Training [3/16] Loss: 0.00479 +Epoch [2354/4000] Training [4/16] Loss: 0.00443 +Epoch [2354/4000] Training [5/16] Loss: 0.00675 +Epoch [2354/4000] Training [6/16] Loss: 0.00430 +Epoch [2354/4000] Training [7/16] Loss: 0.00388 +Epoch [2354/4000] Training [8/16] Loss: 0.00437 +Epoch [2354/4000] Training [9/16] Loss: 0.00392 +Epoch [2354/4000] Training [10/16] Loss: 0.00419 +Epoch [2354/4000] Training [11/16] Loss: 0.00437 +Epoch [2354/4000] Training [12/16] Loss: 0.00471 +Epoch [2354/4000] Training [13/16] Loss: 0.00405 +Epoch [2354/4000] Training [14/16] Loss: 0.00590 +Epoch [2354/4000] Training [15/16] Loss: 0.00630 +Epoch [2354/4000] Training [16/16] Loss: 0.00397 +Epoch [2354/4000] Training metric {'Train/mean dice_metric': 0.9969173073768616, 'Train/mean miou_metric': 0.9935811161994934, 'Train/mean f1': 0.9923776984214783, 'Train/mean precision': 0.9877519607543945, 'Train/mean recall': 0.997046947479248, 'Train/mean hd95_metric': 0.973102331161499} +Epoch [2354/4000] Validation [1/4] Loss: 0.28393 focal_loss 0.22192 dice_loss 0.06201 +Epoch [2354/4000] Validation [2/4] Loss: 0.33040 focal_loss 0.21393 dice_loss 0.11647 +Epoch [2354/4000] Validation [3/4] Loss: 0.44204 focal_loss 0.34807 dice_loss 0.09396 +Epoch [2354/4000] Validation [4/4] Loss: 0.39904 focal_loss 0.28506 dice_loss 0.11397 +Epoch [2354/4000] Validation metric {'Val/mean dice_metric': 0.9740106463432312, 'Val/mean miou_metric': 0.9581464529037476, 'Val/mean f1': 0.9748385548591614, 'Val/mean precision': 0.9706599116325378, 'Val/mean recall': 0.979053258895874, 'Val/mean hd95_metric': 5.62042760848999} +Cheakpoint... +Epoch [2354/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740106463432312, 'Val/mean miou_metric': 0.9581464529037476, 'Val/mean f1': 0.9748385548591614, 'Val/mean precision': 0.9706599116325378, 'Val/mean recall': 0.979053258895874, 'Val/mean hd95_metric': 5.62042760848999} +Epoch [2355/4000] Training [1/16] Loss: 0.00415 +Epoch [2355/4000] Training [2/16] Loss: 0.00671 +Epoch [2355/4000] Training [3/16] Loss: 0.00605 +Epoch [2355/4000] Training [4/16] Loss: 0.00533 +Epoch [2355/4000] Training [5/16] Loss: 0.00441 +Epoch [2355/4000] Training [6/16] Loss: 0.00405 +Epoch [2355/4000] Training [7/16] Loss: 0.00501 +Epoch [2355/4000] Training [8/16] Loss: 0.00361 +Epoch [2355/4000] Training [9/16] Loss: 0.00471 +Epoch [2355/4000] Training [10/16] Loss: 0.00522 +Epoch [2355/4000] Training [11/16] Loss: 0.00371 +Epoch [2355/4000] Training [12/16] Loss: 0.00665 +Epoch [2355/4000] Training [13/16] Loss: 0.00491 +Epoch [2355/4000] Training [14/16] Loss: 0.00461 +Epoch [2355/4000] Training [15/16] Loss: 0.00419 +Epoch [2355/4000] Training [16/16] Loss: 0.00486 +Epoch [2355/4000] Training metric {'Train/mean dice_metric': 0.9969402551651001, 'Train/mean miou_metric': 0.9936121702194214, 'Train/mean f1': 0.9922547340393066, 'Train/mean precision': 0.9876287579536438, 'Train/mean recall': 0.9969242811203003, 'Train/mean hd95_metric': 0.9806455969810486} +Epoch [2355/4000] Validation [1/4] Loss: 0.32568 focal_loss 0.25707 dice_loss 0.06862 +Epoch [2355/4000] Validation [2/4] Loss: 0.34882 focal_loss 0.23215 dice_loss 0.11666 +Epoch [2355/4000] Validation [3/4] Loss: 0.22900 focal_loss 0.16853 dice_loss 0.06047 +Epoch [2355/4000] Validation [4/4] Loss: 0.28240 focal_loss 0.17727 dice_loss 0.10513 +Epoch [2355/4000] Validation metric {'Val/mean dice_metric': 0.9728439450263977, 'Val/mean miou_metric': 0.9574923515319824, 'Val/mean f1': 0.9740729331970215, 'Val/mean precision': 0.9697377681732178, 'Val/mean recall': 0.9784470796585083, 'Val/mean hd95_metric': 6.072339057922363} +Cheakpoint... +Epoch [2355/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728439450263977, 'Val/mean miou_metric': 0.9574923515319824, 'Val/mean f1': 0.9740729331970215, 'Val/mean precision': 0.9697377681732178, 'Val/mean recall': 0.9784470796585083, 'Val/mean hd95_metric': 6.072339057922363} +Epoch [2356/4000] Training [1/16] Loss: 0.00375 +Epoch [2356/4000] Training [2/16] Loss: 0.00445 +Epoch [2356/4000] Training [3/16] Loss: 0.00666 +Epoch [2356/4000] Training [4/16] Loss: 0.00560 +Epoch [2356/4000] Training [5/16] Loss: 0.00590 +Epoch [2356/4000] Training [6/16] Loss: 0.00579 +Epoch [2356/4000] Training [7/16] Loss: 0.00340 +Epoch [2356/4000] Training [8/16] Loss: 0.00391 +Epoch [2356/4000] Training [9/16] Loss: 0.00462 +Epoch [2356/4000] Training [10/16] Loss: 0.00558 +Epoch [2356/4000] Training [11/16] Loss: 0.00529 +Epoch [2356/4000] Training [12/16] Loss: 0.00441 +Epoch [2356/4000] Training [13/16] Loss: 0.00531 +Epoch [2356/4000] Training [14/16] Loss: 0.00393 +Epoch [2356/4000] Training [15/16] Loss: 0.00460 +Epoch [2356/4000] Training [16/16] Loss: 0.00457 +Epoch [2356/4000] Training metric {'Train/mean dice_metric': 0.9969667196273804, 'Train/mean miou_metric': 0.9936730861663818, 'Train/mean f1': 0.9922874569892883, 'Train/mean precision': 0.9874082207679749, 'Train/mean recall': 0.997215211391449, 'Train/mean hd95_metric': 0.9898848533630371} +Epoch [2356/4000] Validation [1/4] Loss: 0.36148 focal_loss 0.29196 dice_loss 0.06953 +Epoch [2356/4000] Validation [2/4] Loss: 0.58852 focal_loss 0.41899 dice_loss 0.16953 +Epoch [2356/4000] Validation [3/4] Loss: 0.40556 focal_loss 0.31488 dice_loss 0.09068 +Epoch [2356/4000] Validation [4/4] Loss: 0.29850 focal_loss 0.20854 dice_loss 0.08996 +Epoch [2356/4000] Validation metric {'Val/mean dice_metric': 0.9733505249023438, 'Val/mean miou_metric': 0.9576429128646851, 'Val/mean f1': 0.9747095704078674, 'Val/mean precision': 0.9713817834854126, 'Val/mean recall': 0.978060245513916, 'Val/mean hd95_metric': 5.842254638671875} +Cheakpoint... +Epoch [2356/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733505249023438, 'Val/mean miou_metric': 0.9576429128646851, 'Val/mean f1': 0.9747095704078674, 'Val/mean precision': 0.9713817834854126, 'Val/mean recall': 0.978060245513916, 'Val/mean hd95_metric': 5.842254638671875} +Epoch [2357/4000] Training [1/16] Loss: 0.00449 +Epoch [2357/4000] Training [2/16] Loss: 0.00400 +Epoch [2357/4000] Training [3/16] Loss: 0.00523 +Epoch [2357/4000] Training [4/16] Loss: 0.00405 +Epoch [2357/4000] Training [5/16] Loss: 0.00426 +Epoch [2357/4000] Training [6/16] Loss: 0.00312 +Epoch [2357/4000] Training [7/16] Loss: 0.00603 +Epoch [2357/4000] Training [8/16] Loss: 0.00335 +Epoch [2357/4000] Training [9/16] Loss: 0.00377 +Epoch [2357/4000] Training [10/16] Loss: 0.00412 +Epoch [2357/4000] Training [11/16] Loss: 0.00606 +Epoch [2357/4000] Training [12/16] Loss: 0.00390 +Epoch [2357/4000] Training [13/16] Loss: 0.00508 +Epoch [2357/4000] Training [14/16] Loss: 0.00377 +Epoch [2357/4000] Training [15/16] Loss: 0.00574 +Epoch [2357/4000] Training [16/16] Loss: 0.00722 +Epoch [2357/4000] Training metric {'Train/mean dice_metric': 0.9970126748085022, 'Train/mean miou_metric': 0.9937792420387268, 'Train/mean f1': 0.9925883412361145, 'Train/mean precision': 0.9881182909011841, 'Train/mean recall': 0.997098982334137, 'Train/mean hd95_metric': 0.9830355644226074} +Epoch [2357/4000] Validation [1/4] Loss: 0.30942 focal_loss 0.24372 dice_loss 0.06571 +Epoch [2357/4000] Validation [2/4] Loss: 0.38246 focal_loss 0.25217 dice_loss 0.13028 +Epoch [2357/4000] Validation [3/4] Loss: 0.39338 focal_loss 0.30292 dice_loss 0.09046 +Epoch [2357/4000] Validation [4/4] Loss: 0.61695 focal_loss 0.47586 dice_loss 0.14109 +Epoch [2357/4000] Validation metric {'Val/mean dice_metric': 0.9733196496963501, 'Val/mean miou_metric': 0.956965446472168, 'Val/mean f1': 0.9744107723236084, 'Val/mean precision': 0.9734305739402771, 'Val/mean recall': 0.9753929376602173, 'Val/mean hd95_metric': 5.740433692932129} +Cheakpoint... +Epoch [2357/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733196496963501, 'Val/mean miou_metric': 0.956965446472168, 'Val/mean f1': 0.9744107723236084, 'Val/mean precision': 0.9734305739402771, 'Val/mean recall': 0.9753929376602173, 'Val/mean hd95_metric': 5.740433692932129} +Epoch [2358/4000] Training [1/16] Loss: 0.00520 +Epoch [2358/4000] Training [2/16] Loss: 0.00370 +Epoch [2358/4000] Training [3/16] Loss: 0.00426 +Epoch [2358/4000] Training [4/16] Loss: 0.00597 +Epoch [2358/4000] Training [5/16] Loss: 0.00464 +Epoch [2358/4000] Training [6/16] Loss: 0.00432 +Epoch [2358/4000] Training [7/16] Loss: 0.00420 +Epoch [2358/4000] Training [8/16] Loss: 0.00462 +Epoch [2358/4000] Training [9/16] Loss: 0.00351 +Epoch [2358/4000] Training [10/16] Loss: 0.00555 +Epoch [2358/4000] Training [11/16] Loss: 0.00403 +Epoch [2358/4000] Training [12/16] Loss: 0.00378 +Epoch [2358/4000] Training [13/16] Loss: 0.00660 +Epoch [2358/4000] Training [14/16] Loss: 0.00562 +Epoch [2358/4000] Training [15/16] Loss: 0.00451 +Epoch [2358/4000] Training [16/16] Loss: 0.00410 +Epoch [2358/4000] Training metric {'Train/mean dice_metric': 0.9970368146896362, 'Train/mean miou_metric': 0.9937747120857239, 'Train/mean f1': 0.9915053844451904, 'Train/mean precision': 0.9859739542007446, 'Train/mean recall': 0.9970991611480713, 'Train/mean hd95_metric': 0.972125768661499} +Epoch [2358/4000] Validation [1/4] Loss: 0.36864 focal_loss 0.29859 dice_loss 0.07005 +Epoch [2358/4000] Validation [2/4] Loss: 0.36941 focal_loss 0.24423 dice_loss 0.12517 +Epoch [2358/4000] Validation [3/4] Loss: 0.42575 focal_loss 0.33195 dice_loss 0.09380 +Epoch [2358/4000] Validation [4/4] Loss: 0.27802 focal_loss 0.19702 dice_loss 0.08100 +Epoch [2358/4000] Validation metric {'Val/mean dice_metric': 0.9746036529541016, 'Val/mean miou_metric': 0.9588724970817566, 'Val/mean f1': 0.9746014475822449, 'Val/mean precision': 0.9707697033882141, 'Val/mean recall': 0.9784636497497559, 'Val/mean hd95_metric': 5.588025093078613} +Cheakpoint... +Epoch [2358/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746036529541016, 'Val/mean miou_metric': 0.9588724970817566, 'Val/mean f1': 0.9746014475822449, 'Val/mean precision': 0.9707697033882141, 'Val/mean recall': 0.9784636497497559, 'Val/mean hd95_metric': 5.588025093078613} +Epoch [2359/4000] Training [1/16] Loss: 0.00366 +Epoch [2359/4000] Training [2/16] Loss: 0.00447 +Epoch [2359/4000] Training [3/16] Loss: 0.00404 +Epoch [2359/4000] Training [4/16] Loss: 0.00589 +Epoch [2359/4000] Training [5/16] Loss: 0.00550 +Epoch [2359/4000] Training [6/16] Loss: 0.00629 +Epoch [2359/4000] Training [7/16] Loss: 0.00504 +Epoch [2359/4000] Training [8/16] Loss: 0.00361 +Epoch [2359/4000] Training [9/16] Loss: 0.00458 +Epoch [2359/4000] Training [10/16] Loss: 0.00605 +Epoch [2359/4000] Training [11/16] Loss: 0.00565 +Epoch [2359/4000] Training [12/16] Loss: 0.00342 +Epoch [2359/4000] Training [13/16] Loss: 0.00480 +Epoch [2359/4000] Training [14/16] Loss: 0.00387 +Epoch [2359/4000] Training [15/16] Loss: 0.00513 +Epoch [2359/4000] Training [16/16] Loss: 0.00509 +Epoch [2359/4000] Training metric {'Train/mean dice_metric': 0.9970475435256958, 'Train/mean miou_metric': 0.9938434362411499, 'Train/mean f1': 0.9924193024635315, 'Train/mean precision': 0.9878315329551697, 'Train/mean recall': 0.9970499277114868, 'Train/mean hd95_metric': 0.968417227268219} +Epoch [2359/4000] Validation [1/4] Loss: 0.33668 focal_loss 0.26968 dice_loss 0.06700 +Epoch [2359/4000] Validation [2/4] Loss: 0.31341 focal_loss 0.19945 dice_loss 0.11397 +Epoch [2359/4000] Validation [3/4] Loss: 0.39764 focal_loss 0.31007 dice_loss 0.08757 +Epoch [2359/4000] Validation [4/4] Loss: 0.37764 focal_loss 0.24682 dice_loss 0.13082 +Epoch [2359/4000] Validation metric {'Val/mean dice_metric': 0.9745464324951172, 'Val/mean miou_metric': 0.9586326479911804, 'Val/mean f1': 0.9753440618515015, 'Val/mean precision': 0.9718571901321411, 'Val/mean recall': 0.9788560271263123, 'Val/mean hd95_metric': 5.932696342468262} +Cheakpoint... +Epoch [2359/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745464324951172, 'Val/mean miou_metric': 0.9586326479911804, 'Val/mean f1': 0.9753440618515015, 'Val/mean precision': 0.9718571901321411, 'Val/mean recall': 0.9788560271263123, 'Val/mean hd95_metric': 5.932696342468262} +Epoch [2360/4000] Training [1/16] Loss: 0.00430 +Epoch [2360/4000] Training [2/16] Loss: 0.00549 +Epoch [2360/4000] Training [3/16] Loss: 0.00407 +Epoch [2360/4000] Training [4/16] Loss: 0.00509 +Epoch [2360/4000] Training [5/16] Loss: 0.00576 +Epoch [2360/4000] Training [6/16] Loss: 0.00510 +Epoch [2360/4000] Training [7/16] Loss: 0.00504 +Epoch [2360/4000] Training [8/16] Loss: 0.00465 +Epoch [2360/4000] Training [9/16] Loss: 0.00518 +Epoch [2360/4000] Training [10/16] Loss: 0.00506 +Epoch [2360/4000] Training [11/16] Loss: 0.00333 +Epoch [2360/4000] Training [12/16] Loss: 0.00539 +Epoch [2360/4000] Training [13/16] Loss: 0.00420 +Epoch [2360/4000] Training [14/16] Loss: 0.00477 +Epoch [2360/4000] Training [15/16] Loss: 0.00470 +Epoch [2360/4000] Training [16/16] Loss: 0.00470 +Epoch [2360/4000] Training metric {'Train/mean dice_metric': 0.9969505071640015, 'Train/mean miou_metric': 0.9936485886573792, 'Train/mean f1': 0.9924933314323425, 'Train/mean precision': 0.9879263043403625, 'Train/mean recall': 0.9971027970314026, 'Train/mean hd95_metric': 0.9764504432678223} +Epoch [2360/4000] Validation [1/4] Loss: 0.38694 focal_loss 0.31622 dice_loss 0.07072 +Epoch [2360/4000] Validation [2/4] Loss: 0.32260 focal_loss 0.20101 dice_loss 0.12159 +Epoch [2360/4000] Validation [3/4] Loss: 0.41657 focal_loss 0.32530 dice_loss 0.09127 +Epoch [2360/4000] Validation [4/4] Loss: 0.27128 focal_loss 0.17794 dice_loss 0.09334 +Epoch [2360/4000] Validation metric {'Val/mean dice_metric': 0.9737017750740051, 'Val/mean miou_metric': 0.9577761888504028, 'Val/mean f1': 0.9749393463134766, 'Val/mean precision': 0.972527265548706, 'Val/mean recall': 0.9773634076118469, 'Val/mean hd95_metric': 5.875871181488037} +Cheakpoint... +Epoch [2360/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737017750740051, 'Val/mean miou_metric': 0.9577761888504028, 'Val/mean f1': 0.9749393463134766, 'Val/mean precision': 0.972527265548706, 'Val/mean recall': 0.9773634076118469, 'Val/mean hd95_metric': 5.875871181488037} +Epoch [2361/4000] Training [1/16] Loss: 0.00522 +Epoch [2361/4000] Training [2/16] Loss: 0.00430 +Epoch [2361/4000] Training [3/16] Loss: 0.00485 +Epoch [2361/4000] Training [4/16] Loss: 0.00435 +Epoch [2361/4000] Training [5/16] Loss: 0.00405 +Epoch [2361/4000] Training [6/16] Loss: 0.00413 +Epoch [2361/4000] Training [7/16] Loss: 0.00451 +Epoch [2361/4000] Training [8/16] Loss: 0.00445 +Epoch [2361/4000] Training [9/16] Loss: 0.00398 +Epoch [2361/4000] Training [10/16] Loss: 0.00422 +Epoch [2361/4000] Training [11/16] Loss: 0.00473 +Epoch [2361/4000] Training [12/16] Loss: 0.00675 +Epoch [2361/4000] Training [13/16] Loss: 0.01063 +Epoch [2361/4000] Training [14/16] Loss: 0.00429 +Epoch [2361/4000] Training [15/16] Loss: 0.00495 +Epoch [2361/4000] Training [16/16] Loss: 0.00558 +Epoch [2361/4000] Training metric {'Train/mean dice_metric': 0.9968421459197998, 'Train/mean miou_metric': 0.9934180974960327, 'Train/mean f1': 0.9921539425849915, 'Train/mean precision': 0.9874523282051086, 'Train/mean recall': 0.9969004988670349, 'Train/mean hd95_metric': 0.9928575754165649} +Epoch [2361/4000] Validation [1/4] Loss: 0.35523 focal_loss 0.28149 dice_loss 0.07374 +Epoch [2361/4000] Validation [2/4] Loss: 0.69453 focal_loss 0.48746 dice_loss 0.20707 +Epoch [2361/4000] Validation [3/4] Loss: 0.39980 focal_loss 0.31116 dice_loss 0.08864 +Epoch [2361/4000] Validation [4/4] Loss: 0.44270 focal_loss 0.31873 dice_loss 0.12397 +Epoch [2361/4000] Validation metric {'Val/mean dice_metric': 0.9727042317390442, 'Val/mean miou_metric': 0.9569453001022339, 'Val/mean f1': 0.9747042059898376, 'Val/mean precision': 0.9728924036026001, 'Val/mean recall': 0.9765227437019348, 'Val/mean hd95_metric': 5.794104099273682} +Cheakpoint... +Epoch [2361/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727042317390442, 'Val/mean miou_metric': 0.9569453001022339, 'Val/mean f1': 0.9747042059898376, 'Val/mean precision': 0.9728924036026001, 'Val/mean recall': 0.9765227437019348, 'Val/mean hd95_metric': 5.794104099273682} +Epoch [2362/4000] Training [1/16] Loss: 0.00461 +Epoch [2362/4000] Training [2/16] Loss: 0.00522 +Epoch [2362/4000] Training [3/16] Loss: 0.00540 +Epoch [2362/4000] Training [4/16] Loss: 0.00456 +Epoch [2362/4000] Training [5/16] Loss: 0.00480 +Epoch [2362/4000] Training [6/16] Loss: 0.00346 +Epoch [2362/4000] Training [7/16] Loss: 0.00378 +Epoch [2362/4000] Training [8/16] Loss: 0.00487 +Epoch [2362/4000] Training [9/16] Loss: 0.00362 +Epoch [2362/4000] Training [10/16] Loss: 0.00419 +Epoch [2362/4000] Training [11/16] Loss: 0.00716 +Epoch [2362/4000] Training [12/16] Loss: 0.00446 +Epoch [2362/4000] Training [13/16] Loss: 0.00493 +Epoch [2362/4000] Training [14/16] Loss: 0.00437 +Epoch [2362/4000] Training [15/16] Loss: 0.00489 +Epoch [2362/4000] Training [16/16] Loss: 0.00480 +Epoch [2362/4000] Training metric {'Train/mean dice_metric': 0.9969050884246826, 'Train/mean miou_metric': 0.9935594797134399, 'Train/mean f1': 0.9924001097679138, 'Train/mean precision': 0.9878485798835754, 'Train/mean recall': 0.9969937801361084, 'Train/mean hd95_metric': 0.9935947060585022} +Epoch [2362/4000] Validation [1/4] Loss: 0.37202 focal_loss 0.29763 dice_loss 0.07439 +Epoch [2362/4000] Validation [2/4] Loss: 0.34046 focal_loss 0.21944 dice_loss 0.12102 +Epoch [2362/4000] Validation [3/4] Loss: 0.40075 focal_loss 0.30493 dice_loss 0.09582 +Epoch [2362/4000] Validation [4/4] Loss: 0.53210 focal_loss 0.38646 dice_loss 0.14563 +Epoch [2362/4000] Validation metric {'Val/mean dice_metric': 0.9723507761955261, 'Val/mean miou_metric': 0.9564592242240906, 'Val/mean f1': 0.9743133783340454, 'Val/mean precision': 0.9722671508789062, 'Val/mean recall': 0.976368248462677, 'Val/mean hd95_metric': 6.156347274780273} +Cheakpoint... +Epoch [2362/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723507761955261, 'Val/mean miou_metric': 0.9564592242240906, 'Val/mean f1': 0.9743133783340454, 'Val/mean precision': 0.9722671508789062, 'Val/mean recall': 0.976368248462677, 'Val/mean hd95_metric': 6.156347274780273} +Epoch [2363/4000] Training [1/16] Loss: 0.00685 +Epoch [2363/4000] Training [2/16] Loss: 0.00540 +Epoch [2363/4000] Training [3/16] Loss: 0.00455 +Epoch [2363/4000] Training [4/16] Loss: 0.00699 +Epoch [2363/4000] Training [5/16] Loss: 0.00363 +Epoch [2363/4000] Training [6/16] Loss: 0.00418 +Epoch [2363/4000] Training [7/16] Loss: 0.00627 +Epoch [2363/4000] Training [8/16] Loss: 0.00524 +Epoch [2363/4000] Training [9/16] Loss: 0.00381 +Epoch [2363/4000] Training [10/16] Loss: 0.00406 +Epoch [2363/4000] Training [11/16] Loss: 0.00543 +Epoch [2363/4000] Training [12/16] Loss: 0.00455 +Epoch [2363/4000] Training [13/16] Loss: 0.00443 +Epoch [2363/4000] Training [14/16] Loss: 0.00411 +Epoch [2363/4000] Training [15/16] Loss: 0.00403 +Epoch [2363/4000] Training [16/16] Loss: 0.00421 +Epoch [2363/4000] Training metric {'Train/mean dice_metric': 0.9967995285987854, 'Train/mean miou_metric': 0.9933269023895264, 'Train/mean f1': 0.9917906522750854, 'Train/mean precision': 0.9867700934410095, 'Train/mean recall': 0.9968624711036682, 'Train/mean hd95_metric': 0.9890758991241455} +Epoch [2363/4000] Validation [1/4] Loss: 0.33651 focal_loss 0.26938 dice_loss 0.06713 +Epoch [2363/4000] Validation [2/4] Loss: 0.87269 focal_loss 0.62110 dice_loss 0.25158 +Epoch [2363/4000] Validation [3/4] Loss: 0.40715 focal_loss 0.31202 dice_loss 0.09513 +Epoch [2363/4000] Validation [4/4] Loss: 0.32841 focal_loss 0.21254 dice_loss 0.11586 +Epoch [2363/4000] Validation metric {'Val/mean dice_metric': 0.9720824956893921, 'Val/mean miou_metric': 0.9564222097396851, 'Val/mean f1': 0.973773717880249, 'Val/mean precision': 0.9711046814918518, 'Val/mean recall': 0.9764574766159058, 'Val/mean hd95_metric': 5.841367244720459} +Cheakpoint... +Epoch [2363/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720824956893921, 'Val/mean miou_metric': 0.9564222097396851, 'Val/mean f1': 0.973773717880249, 'Val/mean precision': 0.9711046814918518, 'Val/mean recall': 0.9764574766159058, 'Val/mean hd95_metric': 5.841367244720459} +Epoch [2364/4000] Training [1/16] Loss: 0.00678 +Epoch [2364/4000] Training [2/16] Loss: 0.00407 +Epoch [2364/4000] Training [3/16] Loss: 0.00363 +Epoch [2364/4000] Training [4/16] Loss: 0.00440 +Epoch [2364/4000] Training [5/16] Loss: 0.00337 +Epoch [2364/4000] Training [6/16] Loss: 0.00421 +Epoch [2364/4000] Training [7/16] Loss: 0.00489 +Epoch [2364/4000] Training [8/16] Loss: 0.00572 +Epoch [2364/4000] Training [9/16] Loss: 0.00386 +Epoch [2364/4000] Training [10/16] Loss: 0.00520 +Epoch [2364/4000] Training [11/16] Loss: 0.00476 +Epoch [2364/4000] Training [12/16] Loss: 0.00502 +Epoch [2364/4000] Training [13/16] Loss: 0.00393 +Epoch [2364/4000] Training [14/16] Loss: 0.00539 +Epoch [2364/4000] Training [15/16] Loss: 0.00623 +Epoch [2364/4000] Training [16/16] Loss: 0.00408 +Epoch [2364/4000] Training metric {'Train/mean dice_metric': 0.9970620274543762, 'Train/mean miou_metric': 0.9938406348228455, 'Train/mean f1': 0.9917709827423096, 'Train/mean precision': 0.9866787195205688, 'Train/mean recall': 0.9969160556793213, 'Train/mean hd95_metric': 1.0123307704925537} +Epoch [2364/4000] Validation [1/4] Loss: 0.30401 focal_loss 0.23990 dice_loss 0.06411 +Epoch [2364/4000] Validation [2/4] Loss: 0.30673 focal_loss 0.19381 dice_loss 0.11292 +Epoch [2364/4000] Validation [3/4] Loss: 0.39481 focal_loss 0.30234 dice_loss 0.09247 +Epoch [2364/4000] Validation [4/4] Loss: 0.23854 focal_loss 0.15061 dice_loss 0.08794 +Epoch [2364/4000] Validation metric {'Val/mean dice_metric': 0.9744065999984741, 'Val/mean miou_metric': 0.9588541984558105, 'Val/mean f1': 0.9748637676239014, 'Val/mean precision': 0.9718350172042847, 'Val/mean recall': 0.9779114127159119, 'Val/mean hd95_metric': 5.611720085144043} +Cheakpoint... +Epoch [2364/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744065999984741, 'Val/mean miou_metric': 0.9588541984558105, 'Val/mean f1': 0.9748637676239014, 'Val/mean precision': 0.9718350172042847, 'Val/mean recall': 0.9779114127159119, 'Val/mean hd95_metric': 5.611720085144043} +Epoch [2365/4000] Training [1/16] Loss: 0.00414 +Epoch [2365/4000] Training [2/16] Loss: 0.00380 +Epoch [2365/4000] Training [3/16] Loss: 0.00370 +Epoch [2365/4000] Training [4/16] Loss: 0.00767 +Epoch [2365/4000] Training [5/16] Loss: 0.00459 +Epoch [2365/4000] Training [6/16] Loss: 0.00416 +Epoch [2365/4000] Training [7/16] Loss: 0.00642 +Epoch [2365/4000] Training [8/16] Loss: 0.00553 +Epoch [2365/4000] Training [9/16] Loss: 0.00523 +Epoch [2365/4000] Training [10/16] Loss: 0.00448 +Epoch [2365/4000] Training [11/16] Loss: 0.00604 +Epoch [2365/4000] Training [12/16] Loss: 0.00659 +Epoch [2365/4000] Training [13/16] Loss: 0.00449 +Epoch [2365/4000] Training [14/16] Loss: 0.00411 +Epoch [2365/4000] Training [15/16] Loss: 0.00454 +Epoch [2365/4000] Training [16/16] Loss: 0.00478 +Epoch [2365/4000] Training metric {'Train/mean dice_metric': 0.9968854188919067, 'Train/mean miou_metric': 0.993513822555542, 'Train/mean f1': 0.9922803044319153, 'Train/mean precision': 0.9875100255012512, 'Train/mean recall': 0.9970968961715698, 'Train/mean hd95_metric': 1.0009279251098633} +Epoch [2365/4000] Validation [1/4] Loss: 0.30804 focal_loss 0.24618 dice_loss 0.06186 +Epoch [2365/4000] Validation [2/4] Loss: 0.29497 focal_loss 0.18245 dice_loss 0.11252 +Epoch [2365/4000] Validation [3/4] Loss: 0.43450 focal_loss 0.33473 dice_loss 0.09977 +Epoch [2365/4000] Validation [4/4] Loss: 0.29343 focal_loss 0.19757 dice_loss 0.09586 +Epoch [2365/4000] Validation metric {'Val/mean dice_metric': 0.9738408923149109, 'Val/mean miou_metric': 0.9579809308052063, 'Val/mean f1': 0.9752321839332581, 'Val/mean precision': 0.9720793962478638, 'Val/mean recall': 0.9784054756164551, 'Val/mean hd95_metric': 5.897506237030029} +Cheakpoint... +Epoch [2365/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738408923149109, 'Val/mean miou_metric': 0.9579809308052063, 'Val/mean f1': 0.9752321839332581, 'Val/mean precision': 0.9720793962478638, 'Val/mean recall': 0.9784054756164551, 'Val/mean hd95_metric': 5.897506237030029} +Epoch [2366/4000] Training [1/16] Loss: 0.00465 +Epoch [2366/4000] Training [2/16] Loss: 0.00498 +Epoch [2366/4000] Training [3/16] Loss: 0.00458 +Epoch [2366/4000] Training [4/16] Loss: 0.00363 +Epoch [2366/4000] Training [5/16] Loss: 0.00407 +Epoch [2366/4000] Training [6/16] Loss: 0.00456 +Epoch [2366/4000] Training [7/16] Loss: 0.00416 +Epoch [2366/4000] Training [8/16] Loss: 0.00407 +Epoch [2366/4000] Training [9/16] Loss: 0.00400 +Epoch [2366/4000] Training [10/16] Loss: 0.00499 +Epoch [2366/4000] Training [11/16] Loss: 0.00467 +Epoch [2366/4000] Training [12/16] Loss: 0.00455 +Epoch [2366/4000] Training [13/16] Loss: 0.00532 +Epoch [2366/4000] Training [14/16] Loss: 0.00631 +Epoch [2366/4000] Training [15/16] Loss: 0.00437 +Epoch [2366/4000] Training [16/16] Loss: 0.00382 +Epoch [2366/4000] Training metric {'Train/mean dice_metric': 0.997051477432251, 'Train/mean miou_metric': 0.9938241243362427, 'Train/mean f1': 0.991852879524231, 'Train/mean precision': 0.9866988658905029, 'Train/mean recall': 0.997061014175415, 'Train/mean hd95_metric': 0.9844551682472229} +Epoch [2366/4000] Validation [1/4] Loss: 0.33071 focal_loss 0.26495 dice_loss 0.06576 +Epoch [2366/4000] Validation [2/4] Loss: 0.42584 focal_loss 0.25161 dice_loss 0.17424 +Epoch [2366/4000] Validation [3/4] Loss: 0.21109 focal_loss 0.15397 dice_loss 0.05711 +Epoch [2366/4000] Validation [4/4] Loss: 0.22991 focal_loss 0.14609 dice_loss 0.08382 +Epoch [2366/4000] Validation metric {'Val/mean dice_metric': 0.9741719961166382, 'Val/mean miou_metric': 0.9593308568000793, 'Val/mean f1': 0.9743579626083374, 'Val/mean precision': 0.9702950119972229, 'Val/mean recall': 0.9784550070762634, 'Val/mean hd95_metric': 5.579257965087891} +Cheakpoint... +Epoch [2366/4000] best acc:tensor([0.9761], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741719961166382, 'Val/mean miou_metric': 0.9593308568000793, 'Val/mean f1': 0.9743579626083374, 'Val/mean precision': 0.9702950119972229, 'Val/mean recall': 0.9784550070762634, 'Val/mean hd95_metric': 5.579257965087891} +Epoch [2367/4000] Training [1/16] Loss: 0.00381 +Epoch [2367/4000] Training [2/16] Loss: 0.00553 +Epoch [2367/4000] Training [3/16] Loss: 0.00438 +Epoch [2367/4000] Training [4/16] Loss: 0.00391 +Epoch [2367/4000] Training [5/16] Loss: 0.00390 +Epoch [2367/4000] Training [6/16] Loss: 0.00379 +Epoch [2367/4000] Training [7/16] Loss: 0.00449 +Epoch [2367/4000] Training [8/16] Loss: 0.00446 +Epoch [2367/4000] Training [9/16] Loss: 0.00648 +Epoch [2367/4000] Training [10/16] Loss: 0.00410 +Epoch [2367/4000] Training [11/16] Loss: 0.00519 +Epoch [2367/4000] Training [12/16] Loss: 0.00550 +Epoch [2367/4000] Training [13/16] Loss: 0.00565 +Epoch [2367/4000] Training [14/16] Loss: 0.00519 +Epoch [2367/4000] Training [15/16] Loss: 0.00363 +Epoch [2367/4000] Training [16/16] Loss: 0.00393 +Epoch [2367/4000] Training metric {'Train/mean dice_metric': 0.9970812797546387, 'Train/mean miou_metric': 0.9938994646072388, 'Train/mean f1': 0.9922630786895752, 'Train/mean precision': 0.9875887036323547, 'Train/mean recall': 0.9969819188117981, 'Train/mean hd95_metric': 0.9738414287567139} +Epoch [2367/4000] Validation [1/4] Loss: 0.32140 focal_loss 0.25655 dice_loss 0.06486 +Epoch [2367/4000] Validation [2/4] Loss: 0.30985 focal_loss 0.20258 dice_loss 0.10728 +Epoch [2367/4000] Validation [3/4] Loss: 0.41769 focal_loss 0.32849 dice_loss 0.08919 +Epoch [2367/4000] Validation [4/4] Loss: 0.27408 focal_loss 0.18882 dice_loss 0.08526 +Epoch [2367/4000] Validation metric {'Val/mean dice_metric': 0.9762137532234192, 'Val/mean miou_metric': 0.9606276750564575, 'Val/mean f1': 0.9758467674255371, 'Val/mean precision': 0.9720349311828613, 'Val/mean recall': 0.9796885848045349, 'Val/mean hd95_metric': 5.570890426635742} +Cheakpoint... +Epoch [2367/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9762137532234192, 'Val/mean miou_metric': 0.9606276750564575, 'Val/mean f1': 0.9758467674255371, 'Val/mean precision': 0.9720349311828613, 'Val/mean recall': 0.9796885848045349, 'Val/mean hd95_metric': 5.570890426635742} +Epoch [2368/4000] Training [1/16] Loss: 0.00463 +Epoch [2368/4000] Training [2/16] Loss: 0.00582 +Epoch [2368/4000] Training [3/16] Loss: 0.00522 +Epoch [2368/4000] Training [4/16] Loss: 0.00439 +Epoch [2368/4000] Training [5/16] Loss: 0.00406 +Epoch [2368/4000] Training [6/16] Loss: 0.01038 +Epoch [2368/4000] Training [7/16] Loss: 0.00599 +Epoch [2368/4000] Training [8/16] Loss: 0.00438 +Epoch [2368/4000] Training [9/16] Loss: 0.00462 +Epoch [2368/4000] Training [10/16] Loss: 0.00464 +Epoch [2368/4000] Training [11/16] Loss: 0.00385 +Epoch [2368/4000] Training [12/16] Loss: 0.00467 +Epoch [2368/4000] Training [13/16] Loss: 0.00557 +Epoch [2368/4000] Training [14/16] Loss: 0.00459 +Epoch [2368/4000] Training [15/16] Loss: 0.00308 +Epoch [2368/4000] Training [16/16] Loss: 0.00517 +Epoch [2368/4000] Training metric {'Train/mean dice_metric': 0.9969363212585449, 'Train/mean miou_metric': 0.9936289191246033, 'Train/mean f1': 0.9924825429916382, 'Train/mean precision': 0.9880121350288391, 'Train/mean recall': 0.9969935417175293, 'Train/mean hd95_metric': 0.9825161695480347} +Epoch [2368/4000] Validation [1/4] Loss: 0.37333 focal_loss 0.30602 dice_loss 0.06730 +Epoch [2368/4000] Validation [2/4] Loss: 0.28654 focal_loss 0.18420 dice_loss 0.10233 +Epoch [2368/4000] Validation [3/4] Loss: 0.19859 focal_loss 0.14391 dice_loss 0.05468 +Epoch [2368/4000] Validation [4/4] Loss: 0.27755 focal_loss 0.18722 dice_loss 0.09033 +Epoch [2368/4000] Validation metric {'Val/mean dice_metric': 0.9761737585067749, 'Val/mean miou_metric': 0.960818886756897, 'Val/mean f1': 0.9767012596130371, 'Val/mean precision': 0.9733524322509766, 'Val/mean recall': 0.9800732135772705, 'Val/mean hd95_metric': 5.409744739532471} +Cheakpoint... +Epoch [2368/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9761737585067749, 'Val/mean miou_metric': 0.960818886756897, 'Val/mean f1': 0.9767012596130371, 'Val/mean precision': 0.9733524322509766, 'Val/mean recall': 0.9800732135772705, 'Val/mean hd95_metric': 5.409744739532471} +Epoch [2369/4000] Training [1/16] Loss: 0.00530 +Epoch [2369/4000] Training [2/16] Loss: 0.00443 +Epoch [2369/4000] Training [3/16] Loss: 0.00379 +Epoch [2369/4000] Training [4/16] Loss: 0.00423 +Epoch [2369/4000] Training [5/16] Loss: 0.00491 +Epoch [2369/4000] Training [6/16] Loss: 0.00580 +Epoch [2369/4000] Training [7/16] Loss: 0.00635 +Epoch [2369/4000] Training [8/16] Loss: 0.00528 +Epoch [2369/4000] Training [9/16] Loss: 0.00527 +Epoch [2369/4000] Training [10/16] Loss: 0.00348 +Epoch [2369/4000] Training [11/16] Loss: 0.00546 +Epoch [2369/4000] Training [12/16] Loss: 0.00407 +Epoch [2369/4000] Training [13/16] Loss: 0.00490 +Epoch [2369/4000] Training [14/16] Loss: 0.00580 +Epoch [2369/4000] Training [15/16] Loss: 0.00415 +Epoch [2369/4000] Training [16/16] Loss: 0.00507 +Epoch [2369/4000] Training metric {'Train/mean dice_metric': 0.9970037341117859, 'Train/mean miou_metric': 0.9937447309494019, 'Train/mean f1': 0.9924052357673645, 'Train/mean precision': 0.9878168106079102, 'Train/mean recall': 0.9970365762710571, 'Train/mean hd95_metric': 0.9850867986679077} +Epoch [2369/4000] Validation [1/4] Loss: 0.30971 focal_loss 0.24544 dice_loss 0.06427 +Epoch [2369/4000] Validation [2/4] Loss: 0.26901 focal_loss 0.16937 dice_loss 0.09964 +Epoch [2369/4000] Validation [3/4] Loss: 0.21028 focal_loss 0.15537 dice_loss 0.05491 +Epoch [2369/4000] Validation [4/4] Loss: 0.28315 focal_loss 0.19409 dice_loss 0.08906 +Epoch [2369/4000] Validation metric {'Val/mean dice_metric': 0.9754902124404907, 'Val/mean miou_metric': 0.959903359413147, 'Val/mean f1': 0.9761991500854492, 'Val/mean precision': 0.9734590649604797, 'Val/mean recall': 0.9789547324180603, 'Val/mean hd95_metric': 4.9742584228515625} +Cheakpoint... +Epoch [2369/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754902124404907, 'Val/mean miou_metric': 0.959903359413147, 'Val/mean f1': 0.9761991500854492, 'Val/mean precision': 0.9734590649604797, 'Val/mean recall': 0.9789547324180603, 'Val/mean hd95_metric': 4.9742584228515625} +Epoch [2370/4000] Training [1/16] Loss: 0.00476 +Epoch [2370/4000] Training [2/16] Loss: 0.00416 +Epoch [2370/4000] Training [3/16] Loss: 0.00443 +Epoch [2370/4000] Training [4/16] Loss: 0.00420 +Epoch [2370/4000] Training [5/16] Loss: 0.00370 +Epoch [2370/4000] Training [6/16] Loss: 0.00467 +Epoch [2370/4000] Training [7/16] Loss: 0.00392 +Epoch [2370/4000] Training [8/16] Loss: 0.00715 +Epoch [2370/4000] Training [9/16] Loss: 0.00564 +Epoch [2370/4000] Training [10/16] Loss: 0.00402 +Epoch [2370/4000] Training [11/16] Loss: 0.00874 +Epoch [2370/4000] Training [12/16] Loss: 0.00489 +Epoch [2370/4000] Training [13/16] Loss: 0.00402 +Epoch [2370/4000] Training [14/16] Loss: 0.00393 +Epoch [2370/4000] Training [15/16] Loss: 0.00405 +Epoch [2370/4000] Training [16/16] Loss: 0.00444 +Epoch [2370/4000] Training metric {'Train/mean dice_metric': 0.9970095753669739, 'Train/mean miou_metric': 0.9937760829925537, 'Train/mean f1': 0.9925304055213928, 'Train/mean precision': 0.9880117177963257, 'Train/mean recall': 0.9970905780792236, 'Train/mean hd95_metric': 0.9808194637298584} +Epoch [2370/4000] Validation [1/4] Loss: 0.35873 focal_loss 0.29155 dice_loss 0.06718 +Epoch [2370/4000] Validation [2/4] Loss: 0.34320 focal_loss 0.23203 dice_loss 0.11116 +Epoch [2370/4000] Validation [3/4] Loss: 0.37316 focal_loss 0.27950 dice_loss 0.09365 +Epoch [2370/4000] Validation [4/4] Loss: 0.27449 focal_loss 0.18459 dice_loss 0.08991 +Epoch [2370/4000] Validation metric {'Val/mean dice_metric': 0.9743071794509888, 'Val/mean miou_metric': 0.9587424993515015, 'Val/mean f1': 0.9750844240188599, 'Val/mean precision': 0.9699897766113281, 'Val/mean recall': 0.980232834815979, 'Val/mean hd95_metric': 5.5272746086120605} +Cheakpoint... +Epoch [2370/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743071794509888, 'Val/mean miou_metric': 0.9587424993515015, 'Val/mean f1': 0.9750844240188599, 'Val/mean precision': 0.9699897766113281, 'Val/mean recall': 0.980232834815979, 'Val/mean hd95_metric': 5.5272746086120605} +Epoch [2371/4000] Training [1/16] Loss: 0.00343 +Epoch [2371/4000] Training [2/16] Loss: 0.00470 +Epoch [2371/4000] Training [3/16] Loss: 0.00343 +Epoch [2371/4000] Training [4/16] Loss: 0.00529 +Epoch [2371/4000] Training [5/16] Loss: 0.00496 +Epoch [2371/4000] Training [6/16] Loss: 0.00443 +Epoch [2371/4000] Training [7/16] Loss: 0.00407 +Epoch [2371/4000] Training [8/16] Loss: 0.00323 +Epoch [2371/4000] Training [9/16] Loss: 0.00453 +Epoch [2371/4000] Training [10/16] Loss: 0.00542 +Epoch [2371/4000] Training [11/16] Loss: 0.00462 +Epoch [2371/4000] Training [12/16] Loss: 0.00288 +Epoch [2371/4000] Training [13/16] Loss: 0.00417 +Epoch [2371/4000] Training [14/16] Loss: 0.00525 +Epoch [2371/4000] Training [15/16] Loss: 0.00559 +Epoch [2371/4000] Training [16/16] Loss: 0.00544 +Epoch [2371/4000] Training metric {'Train/mean dice_metric': 0.9971358776092529, 'Train/mean miou_metric': 0.9940164089202881, 'Train/mean f1': 0.9925757050514221, 'Train/mean precision': 0.9879635572433472, 'Train/mean recall': 0.9972310662269592, 'Train/mean hd95_metric': 0.9646761417388916} +Epoch [2371/4000] Validation [1/4] Loss: 0.31658 focal_loss 0.25373 dice_loss 0.06286 +Epoch [2371/4000] Validation [2/4] Loss: 0.33599 focal_loss 0.22197 dice_loss 0.11403 +Epoch [2371/4000] Validation [3/4] Loss: 0.41700 focal_loss 0.32806 dice_loss 0.08895 +Epoch [2371/4000] Validation [4/4] Loss: 0.25438 focal_loss 0.17647 dice_loss 0.07791 +Epoch [2371/4000] Validation metric {'Val/mean dice_metric': 0.974572479724884, 'Val/mean miou_metric': 0.9588316082954407, 'Val/mean f1': 0.9750800728797913, 'Val/mean precision': 0.970771312713623, 'Val/mean recall': 0.9794273972511292, 'Val/mean hd95_metric': 5.934165000915527} +Cheakpoint... +Epoch [2371/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974572479724884, 'Val/mean miou_metric': 0.9588316082954407, 'Val/mean f1': 0.9750800728797913, 'Val/mean precision': 0.970771312713623, 'Val/mean recall': 0.9794273972511292, 'Val/mean hd95_metric': 5.934165000915527} +Epoch [2372/4000] Training [1/16] Loss: 0.00382 +Epoch [2372/4000] Training [2/16] Loss: 0.00336 +Epoch [2372/4000] Training [3/16] Loss: 0.00420 +Epoch [2372/4000] Training [4/16] Loss: 0.00521 +Epoch [2372/4000] Training [5/16] Loss: 0.00368 +Epoch [2372/4000] Training [6/16] Loss: 0.00347 +Epoch [2372/4000] Training [7/16] Loss: 0.00442 +Epoch [2372/4000] Training [8/16] Loss: 0.00528 +Epoch [2372/4000] Training [9/16] Loss: 0.00385 +Epoch [2372/4000] Training [10/16] Loss: 0.00611 +Epoch [2372/4000] Training [11/16] Loss: 0.00466 +Epoch [2372/4000] Training [12/16] Loss: 0.00694 +Epoch [2372/4000] Training [13/16] Loss: 0.00458 +Epoch [2372/4000] Training [14/16] Loss: 0.00425 +Epoch [2372/4000] Training [15/16] Loss: 0.00509 +Epoch [2372/4000] Training [16/16] Loss: 0.00576 +Epoch [2372/4000] Training metric {'Train/mean dice_metric': 0.9969578981399536, 'Train/mean miou_metric': 0.9936618804931641, 'Train/mean f1': 0.992396354675293, 'Train/mean precision': 0.9877797961235046, 'Train/mean recall': 0.997056245803833, 'Train/mean hd95_metric': 0.9736629724502563} +Epoch [2372/4000] Validation [1/4] Loss: 0.32353 focal_loss 0.25731 dice_loss 0.06622 +Epoch [2372/4000] Validation [2/4] Loss: 0.62016 focal_loss 0.42106 dice_loss 0.19909 +Epoch [2372/4000] Validation [3/4] Loss: 0.42107 focal_loss 0.33038 dice_loss 0.09070 +Epoch [2372/4000] Validation [4/4] Loss: 0.27929 focal_loss 0.19128 dice_loss 0.08802 +Epoch [2372/4000] Validation metric {'Val/mean dice_metric': 0.973553478717804, 'Val/mean miou_metric': 0.9579871892929077, 'Val/mean f1': 0.9755235910415649, 'Val/mean precision': 0.9722395539283752, 'Val/mean recall': 0.9788298606872559, 'Val/mean hd95_metric': 6.078855514526367} +Cheakpoint... +Epoch [2372/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973553478717804, 'Val/mean miou_metric': 0.9579871892929077, 'Val/mean f1': 0.9755235910415649, 'Val/mean precision': 0.9722395539283752, 'Val/mean recall': 0.9788298606872559, 'Val/mean hd95_metric': 6.078855514526367} +Epoch [2373/4000] Training [1/16] Loss: 0.00698 +Epoch [2373/4000] Training [2/16] Loss: 0.00926 +Epoch [2373/4000] Training [3/16] Loss: 0.00530 +Epoch [2373/4000] Training [4/16] Loss: 0.00387 +Epoch [2373/4000] Training [5/16] Loss: 0.00446 +Epoch [2373/4000] Training [6/16] Loss: 0.00346 +Epoch [2373/4000] Training [7/16] Loss: 0.00425 +Epoch [2373/4000] Training [8/16] Loss: 0.00554 +Epoch [2373/4000] Training [9/16] Loss: 0.00492 +Epoch [2373/4000] Training [10/16] Loss: 0.00689 +Epoch [2373/4000] Training [11/16] Loss: 0.00569 +Epoch [2373/4000] Training [12/16] Loss: 0.00366 +Epoch [2373/4000] Training [13/16] Loss: 0.00407 +Epoch [2373/4000] Training [14/16] Loss: 0.00587 +Epoch [2373/4000] Training [15/16] Loss: 0.00451 +Epoch [2373/4000] Training [16/16] Loss: 0.00343 +Epoch [2373/4000] Training metric {'Train/mean dice_metric': 0.9968457221984863, 'Train/mean miou_metric': 0.9934462904930115, 'Train/mean f1': 0.9922671914100647, 'Train/mean precision': 0.9876812696456909, 'Train/mean recall': 0.9968959093093872, 'Train/mean hd95_metric': 0.9737721681594849} +Epoch [2373/4000] Validation [1/4] Loss: 0.28423 focal_loss 0.21818 dice_loss 0.06605 +Epoch [2373/4000] Validation [2/4] Loss: 0.28084 focal_loss 0.17514 dice_loss 0.10571 +Epoch [2373/4000] Validation [3/4] Loss: 0.41965 focal_loss 0.32762 dice_loss 0.09203 +Epoch [2373/4000] Validation [4/4] Loss: 0.28646 focal_loss 0.18884 dice_loss 0.09762 +Epoch [2373/4000] Validation metric {'Val/mean dice_metric': 0.9756120443344116, 'Val/mean miou_metric': 0.9594483375549316, 'Val/mean f1': 0.97505122423172, 'Val/mean precision': 0.9707064628601074, 'Val/mean recall': 0.9794349670410156, 'Val/mean hd95_metric': 5.576679229736328} +Cheakpoint... +Epoch [2373/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756120443344116, 'Val/mean miou_metric': 0.9594483375549316, 'Val/mean f1': 0.97505122423172, 'Val/mean precision': 0.9707064628601074, 'Val/mean recall': 0.9794349670410156, 'Val/mean hd95_metric': 5.576679229736328} +Epoch [2374/4000] Training [1/16] Loss: 0.00485 +Epoch [2374/4000] Training [2/16] Loss: 0.00549 +Epoch [2374/4000] Training [3/16] Loss: 0.00580 +Epoch [2374/4000] Training [4/16] Loss: 0.00597 +Epoch [2374/4000] Training [5/16] Loss: 0.00427 +Epoch [2374/4000] Training [6/16] Loss: 0.00433 +Epoch [2374/4000] Training [7/16] Loss: 0.00492 +Epoch [2374/4000] Training [8/16] Loss: 0.00398 +Epoch [2374/4000] Training [9/16] Loss: 0.00409 +Epoch [2374/4000] Training [10/16] Loss: 0.00565 +Epoch [2374/4000] Training [11/16] Loss: 0.00406 +Epoch [2374/4000] Training [12/16] Loss: 0.00491 +Epoch [2374/4000] Training [13/16] Loss: 0.00685 +Epoch [2374/4000] Training [14/16] Loss: 0.00511 +Epoch [2374/4000] Training [15/16] Loss: 0.00626 +Epoch [2374/4000] Training [16/16] Loss: 0.00359 +Epoch [2374/4000] Training metric {'Train/mean dice_metric': 0.9968886375427246, 'Train/mean miou_metric': 0.9935282468795776, 'Train/mean f1': 0.9924123287200928, 'Train/mean precision': 0.9878849983215332, 'Train/mean recall': 0.9969813823699951, 'Train/mean hd95_metric': 0.9701796770095825} +Epoch [2374/4000] Validation [1/4] Loss: 0.32356 focal_loss 0.25627 dice_loss 0.06729 +Epoch [2374/4000] Validation [2/4] Loss: 0.54447 focal_loss 0.38614 dice_loss 0.15833 +Epoch [2374/4000] Validation [3/4] Loss: 0.44387 focal_loss 0.35010 dice_loss 0.09377 +Epoch [2374/4000] Validation [4/4] Loss: 0.28974 focal_loss 0.19666 dice_loss 0.09308 +Epoch [2374/4000] Validation metric {'Val/mean dice_metric': 0.9743316769599915, 'Val/mean miou_metric': 0.9585056304931641, 'Val/mean f1': 0.9752796292304993, 'Val/mean precision': 0.9708278179168701, 'Val/mean recall': 0.9797724485397339, 'Val/mean hd95_metric': 5.885441780090332} +Cheakpoint... +Epoch [2374/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743316769599915, 'Val/mean miou_metric': 0.9585056304931641, 'Val/mean f1': 0.9752796292304993, 'Val/mean precision': 0.9708278179168701, 'Val/mean recall': 0.9797724485397339, 'Val/mean hd95_metric': 5.885441780090332} +Epoch [2375/4000] Training [1/16] Loss: 0.00391 +Epoch [2375/4000] Training [2/16] Loss: 0.00450 +Epoch [2375/4000] Training [3/16] Loss: 0.00699 +Epoch [2375/4000] Training [4/16] Loss: 0.00482 +Epoch [2375/4000] Training [5/16] Loss: 0.00437 +Epoch [2375/4000] Training [6/16] Loss: 0.00529 +Epoch [2375/4000] Training [7/16] Loss: 0.00527 +Epoch [2375/4000] Training [8/16] Loss: 0.00553 +Epoch [2375/4000] Training [9/16] Loss: 0.00315 +Epoch [2375/4000] Training [10/16] Loss: 0.00389 +Epoch [2375/4000] Training [11/16] Loss: 0.00381 +Epoch [2375/4000] Training [12/16] Loss: 0.00713 +Epoch [2375/4000] Training [13/16] Loss: 0.00424 +Epoch [2375/4000] Training [14/16] Loss: 0.01050 +Epoch [2375/4000] Training [15/16] Loss: 0.00347 +Epoch [2375/4000] Training [16/16] Loss: 0.00442 +Epoch [2375/4000] Training metric {'Train/mean dice_metric': 0.996745765209198, 'Train/mean miou_metric': 0.9932519197463989, 'Train/mean f1': 0.9923149943351746, 'Train/mean precision': 0.9876714944839478, 'Train/mean recall': 0.9970023036003113, 'Train/mean hd95_metric': 0.9844682216644287} +Epoch [2375/4000] Validation [1/4] Loss: 0.28256 focal_loss 0.21851 dice_loss 0.06405 +Epoch [2375/4000] Validation [2/4] Loss: 0.55295 focal_loss 0.35458 dice_loss 0.19837 +Epoch [2375/4000] Validation [3/4] Loss: 0.43106 focal_loss 0.33857 dice_loss 0.09248 +Epoch [2375/4000] Validation [4/4] Loss: 0.33726 focal_loss 0.22808 dice_loss 0.10919 +Epoch [2375/4000] Validation metric {'Val/mean dice_metric': 0.9723631143569946, 'Val/mean miou_metric': 0.9566411972045898, 'Val/mean f1': 0.9748721122741699, 'Val/mean precision': 0.9725219011306763, 'Val/mean recall': 0.9772338271141052, 'Val/mean hd95_metric': 5.647454261779785} +Cheakpoint... +Epoch [2375/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723631143569946, 'Val/mean miou_metric': 0.9566411972045898, 'Val/mean f1': 0.9748721122741699, 'Val/mean precision': 0.9725219011306763, 'Val/mean recall': 0.9772338271141052, 'Val/mean hd95_metric': 5.647454261779785} +Epoch [2376/4000] Training [1/16] Loss: 0.00432 +Epoch [2376/4000] Training [2/16] Loss: 0.00547 +Epoch [2376/4000] Training [3/16] Loss: 0.00368 +Epoch [2376/4000] Training [4/16] Loss: 0.00346 +Epoch [2376/4000] Training [5/16] Loss: 0.00378 +Epoch [2376/4000] Training [6/16] Loss: 0.00328 +Epoch [2376/4000] Training [7/16] Loss: 0.00522 +Epoch [2376/4000] Training [8/16] Loss: 0.00426 +Epoch [2376/4000] Training [9/16] Loss: 0.00458 +Epoch [2376/4000] Training [10/16] Loss: 0.00368 +Epoch [2376/4000] Training [11/16] Loss: 0.00478 +Epoch [2376/4000] Training [12/16] Loss: 0.00594 +Epoch [2376/4000] Training [13/16] Loss: 0.00422 +Epoch [2376/4000] Training [14/16] Loss: 0.00404 +Epoch [2376/4000] Training [15/16] Loss: 0.00450 +Epoch [2376/4000] Training [16/16] Loss: 0.00462 +Epoch [2376/4000] Training metric {'Train/mean dice_metric': 0.997214674949646, 'Train/mean miou_metric': 0.9941783547401428, 'Train/mean f1': 0.9927329421043396, 'Train/mean precision': 0.9881606101989746, 'Train/mean recall': 0.9973477721214294, 'Train/mean hd95_metric': 0.9691683650016785} +Epoch [2376/4000] Validation [1/4] Loss: 0.31322 focal_loss 0.24596 dice_loss 0.06726 +Epoch [2376/4000] Validation [2/4] Loss: 0.32554 focal_loss 0.21022 dice_loss 0.11531 +Epoch [2376/4000] Validation [3/4] Loss: 0.45244 focal_loss 0.36053 dice_loss 0.09191 +Epoch [2376/4000] Validation [4/4] Loss: 0.58267 focal_loss 0.45035 dice_loss 0.13232 +Epoch [2376/4000] Validation metric {'Val/mean dice_metric': 0.9734797477722168, 'Val/mean miou_metric': 0.9574295282363892, 'Val/mean f1': 0.9742212295532227, 'Val/mean precision': 0.971093475818634, 'Val/mean recall': 0.9773690104484558, 'Val/mean hd95_metric': 6.462760925292969} +Cheakpoint... +Epoch [2376/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734797477722168, 'Val/mean miou_metric': 0.9574295282363892, 'Val/mean f1': 0.9742212295532227, 'Val/mean precision': 0.971093475818634, 'Val/mean recall': 0.9773690104484558, 'Val/mean hd95_metric': 6.462760925292969} +Epoch [2377/4000] Training [1/16] Loss: 0.00450 +Epoch [2377/4000] Training [2/16] Loss: 0.00377 +Epoch [2377/4000] Training [3/16] Loss: 0.00594 +Epoch [2377/4000] Training [4/16] Loss: 0.00366 +Epoch [2377/4000] Training [5/16] Loss: 0.00449 +Epoch [2377/4000] Training [6/16] Loss: 0.00621 +Epoch [2377/4000] Training [7/16] Loss: 0.00493 +Epoch [2377/4000] Training [8/16] Loss: 0.00414 +Epoch [2377/4000] Training [9/16] Loss: 0.00444 +Epoch [2377/4000] Training [10/16] Loss: 0.00398 +Epoch [2377/4000] Training [11/16] Loss: 0.00365 +Epoch [2377/4000] Training [12/16] Loss: 0.00342 +Epoch [2377/4000] Training [13/16] Loss: 0.00341 +Epoch [2377/4000] Training [14/16] Loss: 0.00435 +Epoch [2377/4000] Training [15/16] Loss: 0.00567 +Epoch [2377/4000] Training [16/16] Loss: 0.00454 +Epoch [2377/4000] Training metric {'Train/mean dice_metric': 0.9970294833183289, 'Train/mean miou_metric': 0.9938068389892578, 'Train/mean f1': 0.9922937154769897, 'Train/mean precision': 0.9876960515975952, 'Train/mean recall': 0.9969342350959778, 'Train/mean hd95_metric': 1.104950189590454} +Epoch [2377/4000] Validation [1/4] Loss: 0.33644 focal_loss 0.26741 dice_loss 0.06904 +Epoch [2377/4000] Validation [2/4] Loss: 0.76630 focal_loss 0.53499 dice_loss 0.23130 +Epoch [2377/4000] Validation [3/4] Loss: 0.41862 focal_loss 0.33014 dice_loss 0.08848 +Epoch [2377/4000] Validation [4/4] Loss: 0.77499 focal_loss 0.60173 dice_loss 0.17326 +Epoch [2377/4000] Validation metric {'Val/mean dice_metric': 0.9721065759658813, 'Val/mean miou_metric': 0.9559192657470703, 'Val/mean f1': 0.9745284914970398, 'Val/mean precision': 0.9722135663032532, 'Val/mean recall': 0.9768546223640442, 'Val/mean hd95_metric': 6.363703727722168} +Cheakpoint... +Epoch [2377/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721065759658813, 'Val/mean miou_metric': 0.9559192657470703, 'Val/mean f1': 0.9745284914970398, 'Val/mean precision': 0.9722135663032532, 'Val/mean recall': 0.9768546223640442, 'Val/mean hd95_metric': 6.363703727722168} +Epoch [2378/4000] Training [1/16] Loss: 0.00557 +Epoch [2378/4000] Training [2/16] Loss: 0.00367 +Epoch [2378/4000] Training [3/16] Loss: 0.00490 +Epoch [2378/4000] Training [4/16] Loss: 0.00391 +Epoch [2378/4000] Training [5/16] Loss: 0.00472 +Epoch [2378/4000] Training [6/16] Loss: 0.00337 +Epoch [2378/4000] Training [7/16] Loss: 0.00404 +Epoch [2378/4000] Training [8/16] Loss: 0.00373 +Epoch [2378/4000] Training [9/16] Loss: 0.00479 +Epoch [2378/4000] Training [10/16] Loss: 0.00620 +Epoch [2378/4000] Training [11/16] Loss: 0.00574 +Epoch [2378/4000] Training [12/16] Loss: 0.00925 +Epoch [2378/4000] Training [13/16] Loss: 0.00464 +Epoch [2378/4000] Training [14/16] Loss: 0.00457 +Epoch [2378/4000] Training [15/16] Loss: 0.00438 +Epoch [2378/4000] Training [16/16] Loss: 0.00454 +Epoch [2378/4000] Training metric {'Train/mean dice_metric': 0.9968786835670471, 'Train/mean miou_metric': 0.9935141801834106, 'Train/mean f1': 0.9924373626708984, 'Train/mean precision': 0.9879153370857239, 'Train/mean recall': 0.9970011115074158, 'Train/mean hd95_metric': 0.9795986413955688} +Epoch [2378/4000] Validation [1/4] Loss: 0.28258 focal_loss 0.22233 dice_loss 0.06025 +Epoch [2378/4000] Validation [2/4] Loss: 0.44993 focal_loss 0.28744 dice_loss 0.16249 +Epoch [2378/4000] Validation [3/4] Loss: 0.19016 focal_loss 0.13553 dice_loss 0.05463 +Epoch [2378/4000] Validation [4/4] Loss: 0.78011 focal_loss 0.58565 dice_loss 0.19447 +Epoch [2378/4000] Validation metric {'Val/mean dice_metric': 0.9741790890693665, 'Val/mean miou_metric': 0.9580995440483093, 'Val/mean f1': 0.9750524759292603, 'Val/mean precision': 0.9732267260551453, 'Val/mean recall': 0.9768850803375244, 'Val/mean hd95_metric': 5.320683002471924} +Cheakpoint... +Epoch [2378/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741790890693665, 'Val/mean miou_metric': 0.9580995440483093, 'Val/mean f1': 0.9750524759292603, 'Val/mean precision': 0.9732267260551453, 'Val/mean recall': 0.9768850803375244, 'Val/mean hd95_metric': 5.320683002471924} +Epoch [2379/4000] Training [1/16] Loss: 0.00557 +Epoch [2379/4000] Training [2/16] Loss: 0.00365 +Epoch [2379/4000] Training [3/16] Loss: 0.00578 +Epoch [2379/4000] Training [4/16] Loss: 0.00337 +Epoch [2379/4000] Training [5/16] Loss: 0.00403 +Epoch [2379/4000] Training [6/16] Loss: 0.00386 +Epoch [2379/4000] Training [7/16] Loss: 0.00351 +Epoch [2379/4000] Training [8/16] Loss: 0.00403 +Epoch [2379/4000] Training [9/16] Loss: 0.00437 +Epoch [2379/4000] Training [10/16] Loss: 0.00561 +Epoch [2379/4000] Training [11/16] Loss: 0.00325 +Epoch [2379/4000] Training [12/16] Loss: 0.00509 +Epoch [2379/4000] Training [13/16] Loss: 0.00353 +Epoch [2379/4000] Training [14/16] Loss: 0.00456 +Epoch [2379/4000] Training [15/16] Loss: 0.00501 +Epoch [2379/4000] Training [16/16] Loss: 0.00372 +Epoch [2379/4000] Training metric {'Train/mean dice_metric': 0.9972215890884399, 'Train/mean miou_metric': 0.9941846132278442, 'Train/mean f1': 0.9925211071968079, 'Train/mean precision': 0.9878868460655212, 'Train/mean recall': 0.9971990585327148, 'Train/mean hd95_metric': 0.9668523073196411} +Epoch [2379/4000] Validation [1/4] Loss: 0.36462 focal_loss 0.29416 dice_loss 0.07047 +Epoch [2379/4000] Validation [2/4] Loss: 0.82415 focal_loss 0.58036 dice_loss 0.24379 +Epoch [2379/4000] Validation [3/4] Loss: 0.38487 focal_loss 0.29831 dice_loss 0.08656 +Epoch [2379/4000] Validation [4/4] Loss: 0.31682 focal_loss 0.20363 dice_loss 0.11319 +Epoch [2379/4000] Validation metric {'Val/mean dice_metric': 0.9729586839675903, 'Val/mean miou_metric': 0.9576666951179504, 'Val/mean f1': 0.9748215675354004, 'Val/mean precision': 0.9715521335601807, 'Val/mean recall': 0.978113055229187, 'Val/mean hd95_metric': 5.660305023193359} +Cheakpoint... +Epoch [2379/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729586839675903, 'Val/mean miou_metric': 0.9576666951179504, 'Val/mean f1': 0.9748215675354004, 'Val/mean precision': 0.9715521335601807, 'Val/mean recall': 0.978113055229187, 'Val/mean hd95_metric': 5.660305023193359} +Epoch [2380/4000] Training [1/16] Loss: 0.00345 +Epoch [2380/4000] Training [2/16] Loss: 0.00572 +Epoch [2380/4000] Training [3/16] Loss: 0.00457 +Epoch [2380/4000] Training [4/16] Loss: 0.00359 +Epoch [2380/4000] Training [5/16] Loss: 0.00351 +Epoch [2380/4000] Training [6/16] Loss: 0.00613 +Epoch [2380/4000] Training [7/16] Loss: 0.00433 +Epoch [2380/4000] Training [8/16] Loss: 0.00536 +Epoch [2380/4000] Training [9/16] Loss: 0.00524 +Epoch [2380/4000] Training [10/16] Loss: 0.00493 +Epoch [2380/4000] Training [11/16] Loss: 0.00366 +Epoch [2380/4000] Training [12/16] Loss: 0.00433 +Epoch [2380/4000] Training [13/16] Loss: 0.00504 +Epoch [2380/4000] Training [14/16] Loss: 0.00385 +Epoch [2380/4000] Training [15/16] Loss: 0.00518 +Epoch [2380/4000] Training [16/16] Loss: 0.00386 +Epoch [2380/4000] Training metric {'Train/mean dice_metric': 0.9972077012062073, 'Train/mean miou_metric': 0.9941458702087402, 'Train/mean f1': 0.992508053779602, 'Train/mean precision': 0.987838864326477, 'Train/mean recall': 0.9972215294837952, 'Train/mean hd95_metric': 0.9525060653686523} +Epoch [2380/4000] Validation [1/4] Loss: 0.32878 focal_loss 0.25995 dice_loss 0.06883 +Epoch [2380/4000] Validation [2/4] Loss: 1.05009 focal_loss 0.75573 dice_loss 0.29436 +Epoch [2380/4000] Validation [3/4] Loss: 0.28075 focal_loss 0.19709 dice_loss 0.08367 +Epoch [2380/4000] Validation [4/4] Loss: 0.30188 focal_loss 0.19856 dice_loss 0.10331 +Epoch [2380/4000] Validation metric {'Val/mean dice_metric': 0.9702812433242798, 'Val/mean miou_metric': 0.9554392695426941, 'Val/mean f1': 0.9743698239326477, 'Val/mean precision': 0.9738555550575256, 'Val/mean recall': 0.974884569644928, 'Val/mean hd95_metric': 5.569377422332764} +Cheakpoint... +Epoch [2380/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702812433242798, 'Val/mean miou_metric': 0.9554392695426941, 'Val/mean f1': 0.9743698239326477, 'Val/mean precision': 0.9738555550575256, 'Val/mean recall': 0.974884569644928, 'Val/mean hd95_metric': 5.569377422332764} +Epoch [2381/4000] Training [1/16] Loss: 0.00449 +Epoch [2381/4000] Training [2/16] Loss: 0.00367 +Epoch [2381/4000] Training [3/16] Loss: 0.00497 +Epoch [2381/4000] Training [4/16] Loss: 0.00648 +Epoch [2381/4000] Training [5/16] Loss: 0.00344 +Epoch [2381/4000] Training [6/16] Loss: 0.00379 +Epoch [2381/4000] Training [7/16] Loss: 0.00474 +Epoch [2381/4000] Training [8/16] Loss: 0.00635 +Epoch [2381/4000] Training [9/16] Loss: 0.00588 +Epoch [2381/4000] Training [10/16] Loss: 0.00428 +Epoch [2381/4000] Training [11/16] Loss: 0.00530 +Epoch [2381/4000] Training [12/16] Loss: 0.00387 +Epoch [2381/4000] Training [13/16] Loss: 0.00790 +Epoch [2381/4000] Training [14/16] Loss: 0.00342 +Epoch [2381/4000] Training [15/16] Loss: 0.00444 +Epoch [2381/4000] Training [16/16] Loss: 0.00409 +Epoch [2381/4000] Training metric {'Train/mean dice_metric': 0.9970747232437134, 'Train/mean miou_metric': 0.9938952922821045, 'Train/mean f1': 0.9924480319023132, 'Train/mean precision': 0.9878474473953247, 'Train/mean recall': 0.9970916509628296, 'Train/mean hd95_metric': 0.9734172821044922} +Epoch [2381/4000] Validation [1/4] Loss: 0.31298 focal_loss 0.24817 dice_loss 0.06481 +Epoch [2381/4000] Validation [2/4] Loss: 0.79214 focal_loss 0.54375 dice_loss 0.24840 +Epoch [2381/4000] Validation [3/4] Loss: 0.38044 focal_loss 0.29441 dice_loss 0.08604 +Epoch [2381/4000] Validation [4/4] Loss: 0.35898 focal_loss 0.24199 dice_loss 0.11699 +Epoch [2381/4000] Validation metric {'Val/mean dice_metric': 0.9726917147636414, 'Val/mean miou_metric': 0.9572173357009888, 'Val/mean f1': 0.9752039313316345, 'Val/mean precision': 0.9735260009765625, 'Val/mean recall': 0.976887583732605, 'Val/mean hd95_metric': 5.8754682540893555} +Cheakpoint... +Epoch [2381/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726917147636414, 'Val/mean miou_metric': 0.9572173357009888, 'Val/mean f1': 0.9752039313316345, 'Val/mean precision': 0.9735260009765625, 'Val/mean recall': 0.976887583732605, 'Val/mean hd95_metric': 5.8754682540893555} +Epoch [2382/4000] Training [1/16] Loss: 0.00458 +Epoch [2382/4000] Training [2/16] Loss: 0.00347 +Epoch [2382/4000] Training [3/16] Loss: 0.00491 +Epoch [2382/4000] Training [4/16] Loss: 0.00563 +Epoch [2382/4000] Training [5/16] Loss: 0.00599 +Epoch [2382/4000] Training [6/16] Loss: 0.00428 +Epoch [2382/4000] Training [7/16] Loss: 0.00555 +Epoch [2382/4000] Training [8/16] Loss: 0.00504 +Epoch [2382/4000] Training [9/16] Loss: 0.00332 +Epoch [2382/4000] Training [10/16] Loss: 0.00385 +Epoch [2382/4000] Training [11/16] Loss: 0.00312 +Epoch [2382/4000] Training [12/16] Loss: 0.00396 +Epoch [2382/4000] Training [13/16] Loss: 0.00363 +Epoch [2382/4000] Training [14/16] Loss: 0.00447 +Epoch [2382/4000] Training [15/16] Loss: 0.00590 +Epoch [2382/4000] Training [16/16] Loss: 0.00604 +Epoch [2382/4000] Training metric {'Train/mean dice_metric': 0.9970807433128357, 'Train/mean miou_metric': 0.9939031600952148, 'Train/mean f1': 0.9924290180206299, 'Train/mean precision': 0.9877651929855347, 'Train/mean recall': 0.9971370697021484, 'Train/mean hd95_metric': 0.9567932486534119} +Epoch [2382/4000] Validation [1/4] Loss: 0.30146 focal_loss 0.23557 dice_loss 0.06590 +Epoch [2382/4000] Validation [2/4] Loss: 1.00517 focal_loss 0.71270 dice_loss 0.29247 +Epoch [2382/4000] Validation [3/4] Loss: 0.20663 focal_loss 0.15058 dice_loss 0.05605 +Epoch [2382/4000] Validation [4/4] Loss: 0.37198 focal_loss 0.26273 dice_loss 0.10925 +Epoch [2382/4000] Validation metric {'Val/mean dice_metric': 0.972569465637207, 'Val/mean miou_metric': 0.9576732516288757, 'Val/mean f1': 0.9749622344970703, 'Val/mean precision': 0.9722241163253784, 'Val/mean recall': 0.977715790271759, 'Val/mean hd95_metric': 5.415932655334473} +Cheakpoint... +Epoch [2382/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972569465637207, 'Val/mean miou_metric': 0.9576732516288757, 'Val/mean f1': 0.9749622344970703, 'Val/mean precision': 0.9722241163253784, 'Val/mean recall': 0.977715790271759, 'Val/mean hd95_metric': 5.415932655334473} +Epoch [2383/4000] Training [1/16] Loss: 0.00444 +Epoch [2383/4000] Training [2/16] Loss: 0.00440 +Epoch [2383/4000] Training [3/16] Loss: 0.00608 +Epoch [2383/4000] Training [4/16] Loss: 0.00357 +Epoch [2383/4000] Training [5/16] Loss: 0.00381 +Epoch [2383/4000] Training [6/16] Loss: 0.00414 +Epoch [2383/4000] Training [7/16] Loss: 0.00459 +Epoch [2383/4000] Training [8/16] Loss: 0.00667 +Epoch [2383/4000] Training [9/16] Loss: 0.00570 +Epoch [2383/4000] Training [10/16] Loss: 0.00402 +Epoch [2383/4000] Training [11/16] Loss: 0.00434 +Epoch [2383/4000] Training [12/16] Loss: 0.00486 +Epoch [2383/4000] Training [13/16] Loss: 0.00372 +Epoch [2383/4000] Training [14/16] Loss: 0.00357 +Epoch [2383/4000] Training [15/16] Loss: 0.00563 +Epoch [2383/4000] Training [16/16] Loss: 0.00732 +Epoch [2383/4000] Training metric {'Train/mean dice_metric': 0.9968669414520264, 'Train/mean miou_metric': 0.9934712648391724, 'Train/mean f1': 0.9919872283935547, 'Train/mean precision': 0.9871731400489807, 'Train/mean recall': 0.9968485236167908, 'Train/mean hd95_metric': 1.052464485168457} +Epoch [2383/4000] Validation [1/4] Loss: 0.29309 focal_loss 0.23006 dice_loss 0.06303 +Epoch [2383/4000] Validation [2/4] Loss: 0.46151 focal_loss 0.31223 dice_loss 0.14928 +Epoch [2383/4000] Validation [3/4] Loss: 0.43024 focal_loss 0.33462 dice_loss 0.09562 +Epoch [2383/4000] Validation [4/4] Loss: 0.36903 focal_loss 0.24104 dice_loss 0.12800 +Epoch [2383/4000] Validation metric {'Val/mean dice_metric': 0.9731433987617493, 'Val/mean miou_metric': 0.9574629068374634, 'Val/mean f1': 0.9744086265563965, 'Val/mean precision': 0.9702363610267639, 'Val/mean recall': 0.9786170721054077, 'Val/mean hd95_metric': 5.8038811683654785} +Cheakpoint... +Epoch [2383/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731433987617493, 'Val/mean miou_metric': 0.9574629068374634, 'Val/mean f1': 0.9744086265563965, 'Val/mean precision': 0.9702363610267639, 'Val/mean recall': 0.9786170721054077, 'Val/mean hd95_metric': 5.8038811683654785} +Epoch [2384/4000] Training [1/16] Loss: 0.00429 +Epoch [2384/4000] Training [2/16] Loss: 0.00505 +Epoch [2384/4000] Training [3/16] Loss: 0.00403 +Epoch [2384/4000] Training [4/16] Loss: 0.00416 +Epoch [2384/4000] Training [5/16] Loss: 0.00502 +Epoch [2384/4000] Training [6/16] Loss: 0.00593 +Epoch [2384/4000] Training [7/16] Loss: 0.00485 +Epoch [2384/4000] Training [8/16] Loss: 0.00620 +Epoch [2384/4000] Training [9/16] Loss: 0.00502 +Epoch [2384/4000] Training [10/16] Loss: 0.00365 +Epoch [2384/4000] Training [11/16] Loss: 0.00511 +Epoch [2384/4000] Training [12/16] Loss: 0.00307 +Epoch [2384/4000] Training [13/16] Loss: 0.00508 +Epoch [2384/4000] Training [14/16] Loss: 0.00418 +Epoch [2384/4000] Training [15/16] Loss: 0.00450 +Epoch [2384/4000] Training [16/16] Loss: 0.00500 +Epoch [2384/4000] Training metric {'Train/mean dice_metric': 0.9970588088035583, 'Train/mean miou_metric': 0.9938669204711914, 'Train/mean f1': 0.9925601482391357, 'Train/mean precision': 0.9880818128585815, 'Train/mean recall': 0.9970792531967163, 'Train/mean hd95_metric': 0.9735207557678223} +Epoch [2384/4000] Validation [1/4] Loss: 0.29163 focal_loss 0.22957 dice_loss 0.06206 +Epoch [2384/4000] Validation [2/4] Loss: 0.58529 focal_loss 0.40753 dice_loss 0.17777 +Epoch [2384/4000] Validation [3/4] Loss: 0.41460 focal_loss 0.32582 dice_loss 0.08878 +Epoch [2384/4000] Validation [4/4] Loss: 0.25425 focal_loss 0.17085 dice_loss 0.08340 +Epoch [2384/4000] Validation metric {'Val/mean dice_metric': 0.9750229120254517, 'Val/mean miou_metric': 0.9599687457084656, 'Val/mean f1': 0.9764149785041809, 'Val/mean precision': 0.9726808071136475, 'Val/mean recall': 0.9801779389381409, 'Val/mean hd95_metric': 5.496027946472168} +Cheakpoint... +Epoch [2384/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750229120254517, 'Val/mean miou_metric': 0.9599687457084656, 'Val/mean f1': 0.9764149785041809, 'Val/mean precision': 0.9726808071136475, 'Val/mean recall': 0.9801779389381409, 'Val/mean hd95_metric': 5.496027946472168} +Epoch [2385/4000] Training [1/16] Loss: 0.00423 +Epoch [2385/4000] Training [2/16] Loss: 0.00413 +Epoch [2385/4000] Training [3/16] Loss: 0.00621 +Epoch [2385/4000] Training [4/16] Loss: 0.00440 +Epoch [2385/4000] Training [5/16] Loss: 0.00519 +Epoch [2385/4000] Training [6/16] Loss: 0.00345 +Epoch [2385/4000] Training [7/16] Loss: 0.00703 +Epoch [2385/4000] Training [8/16] Loss: 0.00467 +Epoch [2385/4000] Training [9/16] Loss: 0.00332 +Epoch [2385/4000] Training [10/16] Loss: 0.00456 +Epoch [2385/4000] Training [11/16] Loss: 0.00443 +Epoch [2385/4000] Training [12/16] Loss: 0.00478 +Epoch [2385/4000] Training [13/16] Loss: 0.00356 +Epoch [2385/4000] Training [14/16] Loss: 0.00412 +Epoch [2385/4000] Training [15/16] Loss: 0.00314 +Epoch [2385/4000] Training [16/16] Loss: 0.00464 +Epoch [2385/4000] Training metric {'Train/mean dice_metric': 0.9970483183860779, 'Train/mean miou_metric': 0.9938466548919678, 'Train/mean f1': 0.9925950765609741, 'Train/mean precision': 0.9880967736244202, 'Train/mean recall': 0.9971345067024231, 'Train/mean hd95_metric': 0.978752076625824} +Epoch [2385/4000] Validation [1/4] Loss: 0.27168 focal_loss 0.21090 dice_loss 0.06078 +Epoch [2385/4000] Validation [2/4] Loss: 0.60700 focal_loss 0.42666 dice_loss 0.18034 +Epoch [2385/4000] Validation [3/4] Loss: 0.38143 focal_loss 0.29400 dice_loss 0.08744 +Epoch [2385/4000] Validation [4/4] Loss: 0.32659 focal_loss 0.22063 dice_loss 0.10596 +Epoch [2385/4000] Validation metric {'Val/mean dice_metric': 0.9737436175346375, 'Val/mean miou_metric': 0.9582439661026001, 'Val/mean f1': 0.9758188724517822, 'Val/mean precision': 0.9726482629776001, 'Val/mean recall': 0.9790102243423462, 'Val/mean hd95_metric': 5.518383026123047} +Cheakpoint... +Epoch [2385/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737436175346375, 'Val/mean miou_metric': 0.9582439661026001, 'Val/mean f1': 0.9758188724517822, 'Val/mean precision': 0.9726482629776001, 'Val/mean recall': 0.9790102243423462, 'Val/mean hd95_metric': 5.518383026123047} +Epoch [2386/4000] Training [1/16] Loss: 0.00451 +Epoch [2386/4000] Training [2/16] Loss: 0.00425 +Epoch [2386/4000] Training [3/16] Loss: 0.00396 +Epoch [2386/4000] Training [4/16] Loss: 0.00537 +Epoch [2386/4000] Training [5/16] Loss: 0.00397 +Epoch [2386/4000] Training [6/16] Loss: 0.00553 +Epoch [2386/4000] Training [7/16] Loss: 0.00497 +Epoch [2386/4000] Training [8/16] Loss: 0.00352 +Epoch [2386/4000] Training [9/16] Loss: 0.00552 +Epoch [2386/4000] Training [10/16] Loss: 0.00536 +Epoch [2386/4000] Training [11/16] Loss: 0.00368 +Epoch [2386/4000] Training [12/16] Loss: 0.00376 +Epoch [2386/4000] Training [13/16] Loss: 0.00382 +Epoch [2386/4000] Training [14/16] Loss: 0.00420 +Epoch [2386/4000] Training [15/16] Loss: 0.00482 +Epoch [2386/4000] Training [16/16] Loss: 0.00365 +Epoch [2386/4000] Training metric {'Train/mean dice_metric': 0.9972020387649536, 'Train/mean miou_metric': 0.9941021203994751, 'Train/mean f1': 0.9921246767044067, 'Train/mean precision': 0.9871897101402283, 'Train/mean recall': 0.9971092939376831, 'Train/mean hd95_metric': 0.9756495952606201} +Epoch [2386/4000] Validation [1/4] Loss: 0.27862 focal_loss 0.21810 dice_loss 0.06051 +Epoch [2386/4000] Validation [2/4] Loss: 0.32982 focal_loss 0.22118 dice_loss 0.10864 +Epoch [2386/4000] Validation [3/4] Loss: 0.50163 focal_loss 0.39863 dice_loss 0.10300 +Epoch [2386/4000] Validation [4/4] Loss: 0.28352 focal_loss 0.19482 dice_loss 0.08869 +Epoch [2386/4000] Validation metric {'Val/mean dice_metric': 0.9732845425605774, 'Val/mean miou_metric': 0.957767128944397, 'Val/mean f1': 0.9752605557441711, 'Val/mean precision': 0.9720913767814636, 'Val/mean recall': 0.97845059633255, 'Val/mean hd95_metric': 5.793931007385254} +Cheakpoint... +Epoch [2386/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732845425605774, 'Val/mean miou_metric': 0.957767128944397, 'Val/mean f1': 0.9752605557441711, 'Val/mean precision': 0.9720913767814636, 'Val/mean recall': 0.97845059633255, 'Val/mean hd95_metric': 5.793931007385254} +Epoch [2387/4000] Training [1/16] Loss: 0.00401 +Epoch [2387/4000] Training [2/16] Loss: 0.00438 +Epoch [2387/4000] Training [3/16] Loss: 0.00332 +Epoch [2387/4000] Training [4/16] Loss: 0.00438 +Epoch [2387/4000] Training [5/16] Loss: 0.00458 +Epoch [2387/4000] Training [6/16] Loss: 0.00363 +Epoch [2387/4000] Training [7/16] Loss: 0.00408 +Epoch [2387/4000] Training [8/16] Loss: 0.00374 +Epoch [2387/4000] Training [9/16] Loss: 0.00371 +Epoch [2387/4000] Training [10/16] Loss: 0.00492 +Epoch [2387/4000] Training [11/16] Loss: 0.00547 +Epoch [2387/4000] Training [12/16] Loss: 0.00740 +Epoch [2387/4000] Training [13/16] Loss: 0.00694 +Epoch [2387/4000] Training [14/16] Loss: 0.00420 +Epoch [2387/4000] Training [15/16] Loss: 0.00411 +Epoch [2387/4000] Training [16/16] Loss: 0.00485 +Epoch [2387/4000] Training metric {'Train/mean dice_metric': 0.9970754384994507, 'Train/mean miou_metric': 0.9939014315605164, 'Train/mean f1': 0.9925763010978699, 'Train/mean precision': 0.9880547523498535, 'Train/mean recall': 0.9971393942832947, 'Train/mean hd95_metric': 0.969496488571167} +Epoch [2387/4000] Validation [1/4] Loss: 0.29905 focal_loss 0.23492 dice_loss 0.06412 +Epoch [2387/4000] Validation [2/4] Loss: 0.35226 focal_loss 0.23227 dice_loss 0.11998 +Epoch [2387/4000] Validation [3/4] Loss: 0.41988 focal_loss 0.33011 dice_loss 0.08977 +Epoch [2387/4000] Validation [4/4] Loss: 0.43489 focal_loss 0.30880 dice_loss 0.12609 +Epoch [2387/4000] Validation metric {'Val/mean dice_metric': 0.9743154644966125, 'Val/mean miou_metric': 0.9589317440986633, 'Val/mean f1': 0.9758102297782898, 'Val/mean precision': 0.9721889495849609, 'Val/mean recall': 0.9794585704803467, 'Val/mean hd95_metric': 5.804155349731445} +Cheakpoint... +Epoch [2387/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743154644966125, 'Val/mean miou_metric': 0.9589317440986633, 'Val/mean f1': 0.9758102297782898, 'Val/mean precision': 0.9721889495849609, 'Val/mean recall': 0.9794585704803467, 'Val/mean hd95_metric': 5.804155349731445} +Epoch [2388/4000] Training [1/16] Loss: 0.00497 +Epoch [2388/4000] Training [2/16] Loss: 0.00702 +Epoch [2388/4000] Training [3/16] Loss: 0.00366 +Epoch [2388/4000] Training [4/16] Loss: 0.00812 +Epoch [2388/4000] Training [5/16] Loss: 0.00336 +Epoch [2388/4000] Training [6/16] Loss: 0.00342 +Epoch [2388/4000] Training [7/16] Loss: 0.00545 +Epoch [2388/4000] Training [8/16] Loss: 0.00384 +Epoch [2388/4000] Training [9/16] Loss: 0.00334 +Epoch [2388/4000] Training [10/16] Loss: 0.00411 +Epoch [2388/4000] Training [11/16] Loss: 0.00457 +Epoch [2388/4000] Training [12/16] Loss: 0.00293 +Epoch [2388/4000] Training [13/16] Loss: 0.00568 +Epoch [2388/4000] Training [14/16] Loss: 0.00631 +Epoch [2388/4000] Training [15/16] Loss: 0.00447 +Epoch [2388/4000] Training [16/16] Loss: 0.00510 +Epoch [2388/4000] Training metric {'Train/mean dice_metric': 0.9970813989639282, 'Train/mean miou_metric': 0.9938908815383911, 'Train/mean f1': 0.9921251535415649, 'Train/mean precision': 0.9873310923576355, 'Train/mean recall': 0.9969660043716431, 'Train/mean hd95_metric': 0.9889335632324219} +Epoch [2388/4000] Validation [1/4] Loss: 0.31600 focal_loss 0.24591 dice_loss 0.07009 +Epoch [2388/4000] Validation [2/4] Loss: 0.37291 focal_loss 0.24542 dice_loss 0.12749 +Epoch [2388/4000] Validation [3/4] Loss: 0.36364 focal_loss 0.27793 dice_loss 0.08571 +Epoch [2388/4000] Validation [4/4] Loss: 0.41316 focal_loss 0.29364 dice_loss 0.11951 +Epoch [2388/4000] Validation metric {'Val/mean dice_metric': 0.9726186990737915, 'Val/mean miou_metric': 0.9565693140029907, 'Val/mean f1': 0.9751046299934387, 'Val/mean precision': 0.9738689661026001, 'Val/mean recall': 0.97634357213974, 'Val/mean hd95_metric': 5.2779436111450195} +Cheakpoint... +Epoch [2388/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726186990737915, 'Val/mean miou_metric': 0.9565693140029907, 'Val/mean f1': 0.9751046299934387, 'Val/mean precision': 0.9738689661026001, 'Val/mean recall': 0.97634357213974, 'Val/mean hd95_metric': 5.2779436111450195} +Epoch [2389/4000] Training [1/16] Loss: 0.00415 +Epoch [2389/4000] Training [2/16] Loss: 0.00468 +Epoch [2389/4000] Training [3/16] Loss: 0.00345 +Epoch [2389/4000] Training [4/16] Loss: 0.00539 +Epoch [2389/4000] Training [5/16] Loss: 0.00609 +Epoch [2389/4000] Training [6/16] Loss: 0.00481 +Epoch [2389/4000] Training [7/16] Loss: 0.00584 +Epoch [2389/4000] Training [8/16] Loss: 0.00470 +Epoch [2389/4000] Training [9/16] Loss: 0.00460 +Epoch [2389/4000] Training [10/16] Loss: 0.00444 +Epoch [2389/4000] Training [11/16] Loss: 0.00413 +Epoch [2389/4000] Training [12/16] Loss: 0.00382 +Epoch [2389/4000] Training [13/16] Loss: 0.00339 +Epoch [2389/4000] Training [14/16] Loss: 0.00394 +Epoch [2389/4000] Training [15/16] Loss: 0.00477 +Epoch [2389/4000] Training [16/16] Loss: 0.00367 +Epoch [2389/4000] Training metric {'Train/mean dice_metric': 0.9971848726272583, 'Train/mean miou_metric': 0.9941155910491943, 'Train/mean f1': 0.9926043152809143, 'Train/mean precision': 0.9880911111831665, 'Train/mean recall': 0.997158944606781, 'Train/mean hd95_metric': 0.9675215482711792} +Epoch [2389/4000] Validation [1/4] Loss: 0.26689 focal_loss 0.20652 dice_loss 0.06038 +Epoch [2389/4000] Validation [2/4] Loss: 0.52074 focal_loss 0.36036 dice_loss 0.16038 +Epoch [2389/4000] Validation [3/4] Loss: 0.20431 focal_loss 0.14650 dice_loss 0.05781 +Epoch [2389/4000] Validation [4/4] Loss: 0.28717 focal_loss 0.18877 dice_loss 0.09840 +Epoch [2389/4000] Validation metric {'Val/mean dice_metric': 0.9725404977798462, 'Val/mean miou_metric': 0.9575725793838501, 'Val/mean f1': 0.9750568270683289, 'Val/mean precision': 0.9716534614562988, 'Val/mean recall': 0.9784840941429138, 'Val/mean hd95_metric': 5.232621669769287} +Cheakpoint... +Epoch [2389/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725404977798462, 'Val/mean miou_metric': 0.9575725793838501, 'Val/mean f1': 0.9750568270683289, 'Val/mean precision': 0.9716534614562988, 'Val/mean recall': 0.9784840941429138, 'Val/mean hd95_metric': 5.232621669769287} +Epoch [2390/4000] Training [1/16] Loss: 0.00413 +Epoch [2390/4000] Training [2/16] Loss: 0.00764 +Epoch [2390/4000] Training [3/16] Loss: 0.00486 +Epoch [2390/4000] Training [4/16] Loss: 0.00546 +Epoch [2390/4000] Training [5/16] Loss: 0.00475 +Epoch [2390/4000] Training [6/16] Loss: 0.00465 +Epoch [2390/4000] Training [7/16] Loss: 0.00554 +Epoch [2390/4000] Training [8/16] Loss: 0.00457 +Epoch [2390/4000] Training [9/16] Loss: 0.00507 +Epoch [2390/4000] Training [10/16] Loss: 0.00404 +Epoch [2390/4000] Training [11/16] Loss: 0.00735 +Epoch [2390/4000] Training [12/16] Loss: 0.00442 +Epoch [2390/4000] Training [13/16] Loss: 0.00601 +Epoch [2390/4000] Training [14/16] Loss: 0.00398 +Epoch [2390/4000] Training [15/16] Loss: 0.00337 +Epoch [2390/4000] Training [16/16] Loss: 0.00492 +Epoch [2390/4000] Training metric {'Train/mean dice_metric': 0.9968757033348083, 'Train/mean miou_metric': 0.9935076236724854, 'Train/mean f1': 0.9922850728034973, 'Train/mean precision': 0.9876964092254639, 'Train/mean recall': 0.9969165921211243, 'Train/mean hd95_metric': 0.9793469905853271} +Epoch [2390/4000] Validation [1/4] Loss: 0.28708 focal_loss 0.22463 dice_loss 0.06245 +Epoch [2390/4000] Validation [2/4] Loss: 0.69400 focal_loss 0.49951 dice_loss 0.19449 +Epoch [2390/4000] Validation [3/4] Loss: 0.39615 focal_loss 0.30525 dice_loss 0.09090 +Epoch [2390/4000] Validation [4/4] Loss: 0.26231 focal_loss 0.18252 dice_loss 0.07979 +Epoch [2390/4000] Validation metric {'Val/mean dice_metric': 0.9728274345397949, 'Val/mean miou_metric': 0.9580146670341492, 'Val/mean f1': 0.975435733795166, 'Val/mean precision': 0.9732243418693542, 'Val/mean recall': 0.9776570796966553, 'Val/mean hd95_metric': 5.520993709564209} +Cheakpoint... +Epoch [2390/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728274345397949, 'Val/mean miou_metric': 0.9580146670341492, 'Val/mean f1': 0.975435733795166, 'Val/mean precision': 0.9732243418693542, 'Val/mean recall': 0.9776570796966553, 'Val/mean hd95_metric': 5.520993709564209} +Epoch [2391/4000] Training [1/16] Loss: 0.00415 +Epoch [2391/4000] Training [2/16] Loss: 0.00465 +Epoch [2391/4000] Training [3/16] Loss: 0.00359 +Epoch [2391/4000] Training [4/16] Loss: 0.00471 +Epoch [2391/4000] Training [5/16] Loss: 0.00321 +Epoch [2391/4000] Training [6/16] Loss: 0.00527 +Epoch [2391/4000] Training [7/16] Loss: 0.00476 +Epoch [2391/4000] Training [8/16] Loss: 0.00394 +Epoch [2391/4000] Training [9/16] Loss: 0.00370 +Epoch [2391/4000] Training [10/16] Loss: 0.00595 +Epoch [2391/4000] Training [11/16] Loss: 0.00487 +Epoch [2391/4000] Training [12/16] Loss: 0.00489 +Epoch [2391/4000] Training [13/16] Loss: 0.00448 +Epoch [2391/4000] Training [14/16] Loss: 0.00446 +Epoch [2391/4000] Training [15/16] Loss: 0.00404 +Epoch [2391/4000] Training [16/16] Loss: 0.00479 +Epoch [2391/4000] Training metric {'Train/mean dice_metric': 0.9971376061439514, 'Train/mean miou_metric': 0.9940224885940552, 'Train/mean f1': 0.9925951957702637, 'Train/mean precision': 0.9880809783935547, 'Train/mean recall': 0.9971508383750916, 'Train/mean hd95_metric': 0.9654974341392517} +Epoch [2391/4000] Validation [1/4] Loss: 0.33197 focal_loss 0.26477 dice_loss 0.06720 +Epoch [2391/4000] Validation [2/4] Loss: 0.35932 focal_loss 0.24235 dice_loss 0.11697 +Epoch [2391/4000] Validation [3/4] Loss: 0.21010 focal_loss 0.15276 dice_loss 0.05734 +Epoch [2391/4000] Validation [4/4] Loss: 0.56655 focal_loss 0.44626 dice_loss 0.12029 +Epoch [2391/4000] Validation metric {'Val/mean dice_metric': 0.974787712097168, 'Val/mean miou_metric': 0.9596845507621765, 'Val/mean f1': 0.9758990406990051, 'Val/mean precision': 0.9740371704101562, 'Val/mean recall': 0.9777680039405823, 'Val/mean hd95_metric': 5.192243576049805} +Cheakpoint... +Epoch [2391/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974787712097168, 'Val/mean miou_metric': 0.9596845507621765, 'Val/mean f1': 0.9758990406990051, 'Val/mean precision': 0.9740371704101562, 'Val/mean recall': 0.9777680039405823, 'Val/mean hd95_metric': 5.192243576049805} +Epoch [2392/4000] Training [1/16] Loss: 0.00357 +Epoch [2392/4000] Training [2/16] Loss: 0.00353 +Epoch [2392/4000] Training [3/16] Loss: 0.00517 +Epoch [2392/4000] Training [4/16] Loss: 0.00556 +Epoch [2392/4000] Training [5/16] Loss: 0.00462 +Epoch [2392/4000] Training [6/16] Loss: 0.00471 +Epoch [2392/4000] Training [7/16] Loss: 0.00364 +Epoch [2392/4000] Training [8/16] Loss: 0.00469 +Epoch [2392/4000] Training [9/16] Loss: 0.00528 +Epoch [2392/4000] Training [10/16] Loss: 0.00424 +Epoch [2392/4000] Training [11/16] Loss: 0.00460 +Epoch [2392/4000] Training [12/16] Loss: 0.00449 +Epoch [2392/4000] Training [13/16] Loss: 0.00592 +Epoch [2392/4000] Training [14/16] Loss: 0.00463 +Epoch [2392/4000] Training [15/16] Loss: 0.00521 +Epoch [2392/4000] Training [16/16] Loss: 0.00626 +Epoch [2392/4000] Training metric {'Train/mean dice_metric': 0.9970644116401672, 'Train/mean miou_metric': 0.9938777685165405, 'Train/mean f1': 0.9925392866134644, 'Train/mean precision': 0.9880039691925049, 'Train/mean recall': 0.9971164464950562, 'Train/mean hd95_metric': 0.9760516881942749} +Epoch [2392/4000] Validation [1/4] Loss: 0.33375 focal_loss 0.26771 dice_loss 0.06604 +Epoch [2392/4000] Validation [2/4] Loss: 0.33784 focal_loss 0.23180 dice_loss 0.10605 +Epoch [2392/4000] Validation [3/4] Loss: 0.40983 focal_loss 0.32007 dice_loss 0.08977 +Epoch [2392/4000] Validation [4/4] Loss: 0.65886 focal_loss 0.49840 dice_loss 0.16046 +Epoch [2392/4000] Validation metric {'Val/mean dice_metric': 0.9747060537338257, 'Val/mean miou_metric': 0.9590603709220886, 'Val/mean f1': 0.9749278426170349, 'Val/mean precision': 0.971406102180481, 'Val/mean recall': 0.9784751534461975, 'Val/mean hd95_metric': 5.273342132568359} +Cheakpoint... +Epoch [2392/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747060537338257, 'Val/mean miou_metric': 0.9590603709220886, 'Val/mean f1': 0.9749278426170349, 'Val/mean precision': 0.971406102180481, 'Val/mean recall': 0.9784751534461975, 'Val/mean hd95_metric': 5.273342132568359} +Epoch [2393/4000] Training [1/16] Loss: 0.00438 +Epoch [2393/4000] Training [2/16] Loss: 0.00491 +Epoch [2393/4000] Training [3/16] Loss: 0.00582 +Epoch [2393/4000] Training [4/16] Loss: 0.00405 +Epoch [2393/4000] Training [5/16] Loss: 0.00354 +Epoch [2393/4000] Training [6/16] Loss: 0.00399 +Epoch [2393/4000] Training [7/16] Loss: 0.00514 +Epoch [2393/4000] Training [8/16] Loss: 0.00532 +Epoch [2393/4000] Training [9/16] Loss: 0.00532 +Epoch [2393/4000] Training [10/16] Loss: 0.00384 +Epoch [2393/4000] Training [11/16] Loss: 0.00415 +Epoch [2393/4000] Training [12/16] Loss: 0.00537 +Epoch [2393/4000] Training [13/16] Loss: 0.00364 +Epoch [2393/4000] Training [14/16] Loss: 0.00392 +Epoch [2393/4000] Training [15/16] Loss: 0.00402 +Epoch [2393/4000] Training [16/16] Loss: 0.00480 +Epoch [2393/4000] Training metric {'Train/mean dice_metric': 0.9971798658370972, 'Train/mean miou_metric': 0.9941069483757019, 'Train/mean f1': 0.9926290512084961, 'Train/mean precision': 0.9881178736686707, 'Train/mean recall': 0.9971816539764404, 'Train/mean hd95_metric': 0.9599465131759644} +Epoch [2393/4000] Validation [1/4] Loss: 0.30767 focal_loss 0.24252 dice_loss 0.06516 +Epoch [2393/4000] Validation [2/4] Loss: 0.32576 focal_loss 0.21890 dice_loss 0.10686 +Epoch [2393/4000] Validation [3/4] Loss: 0.43184 focal_loss 0.34158 dice_loss 0.09027 +Epoch [2393/4000] Validation [4/4] Loss: 0.30182 focal_loss 0.20625 dice_loss 0.09556 +Epoch [2393/4000] Validation metric {'Val/mean dice_metric': 0.973698616027832, 'Val/mean miou_metric': 0.9587663412094116, 'Val/mean f1': 0.9761234521865845, 'Val/mean precision': 0.9728716015815735, 'Val/mean recall': 0.9793971180915833, 'Val/mean hd95_metric': 5.588934421539307} +Cheakpoint... +Epoch [2393/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973698616027832, 'Val/mean miou_metric': 0.9587663412094116, 'Val/mean f1': 0.9761234521865845, 'Val/mean precision': 0.9728716015815735, 'Val/mean recall': 0.9793971180915833, 'Val/mean hd95_metric': 5.588934421539307} +Epoch [2394/4000] Training [1/16] Loss: 0.00475 +Epoch [2394/4000] Training [2/16] Loss: 0.00479 +Epoch [2394/4000] Training [3/16] Loss: 0.00350 +Epoch [2394/4000] Training [4/16] Loss: 0.00438 +Epoch [2394/4000] Training [5/16] Loss: 0.00433 +Epoch [2394/4000] Training [6/16] Loss: 0.00694 +Epoch [2394/4000] Training [7/16] Loss: 0.00375 +Epoch [2394/4000] Training [8/16] Loss: 0.00425 +Epoch [2394/4000] Training [9/16] Loss: 0.00530 +Epoch [2394/4000] Training [10/16] Loss: 0.00493 +Epoch [2394/4000] Training [11/16] Loss: 0.00369 +Epoch [2394/4000] Training [12/16] Loss: 0.00547 +Epoch [2394/4000] Training [13/16] Loss: 0.00473 +Epoch [2394/4000] Training [14/16] Loss: 0.00313 +Epoch [2394/4000] Training [15/16] Loss: 0.00497 +Epoch [2394/4000] Training [16/16] Loss: 0.00749 +Epoch [2394/4000] Training metric {'Train/mean dice_metric': 0.9971041679382324, 'Train/mean miou_metric': 0.9939500093460083, 'Train/mean f1': 0.9924976229667664, 'Train/mean precision': 0.9878683090209961, 'Train/mean recall': 0.9971705079078674, 'Train/mean hd95_metric': 0.9631593823432922} +Epoch [2394/4000] Validation [1/4] Loss: 0.37038 focal_loss 0.30193 dice_loss 0.06845 +Epoch [2394/4000] Validation [2/4] Loss: 0.42363 focal_loss 0.25223 dice_loss 0.17140 +Epoch [2394/4000] Validation [3/4] Loss: 0.35961 focal_loss 0.26460 dice_loss 0.09501 +Epoch [2394/4000] Validation [4/4] Loss: 0.30699 focal_loss 0.20460 dice_loss 0.10240 +Epoch [2394/4000] Validation metric {'Val/mean dice_metric': 0.9725397229194641, 'Val/mean miou_metric': 0.956956684589386, 'Val/mean f1': 0.9755940437316895, 'Val/mean precision': 0.9727754592895508, 'Val/mean recall': 0.9784291386604309, 'Val/mean hd95_metric': 5.334316730499268} +Cheakpoint... +Epoch [2394/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725397229194641, 'Val/mean miou_metric': 0.956956684589386, 'Val/mean f1': 0.9755940437316895, 'Val/mean precision': 0.9727754592895508, 'Val/mean recall': 0.9784291386604309, 'Val/mean hd95_metric': 5.334316730499268} +Epoch [2395/4000] Training [1/16] Loss: 0.00427 +Epoch [2395/4000] Training [2/16] Loss: 0.00410 +Epoch [2395/4000] Training [3/16] Loss: 0.00627 +Epoch [2395/4000] Training [4/16] Loss: 0.00390 +Epoch [2395/4000] Training [5/16] Loss: 0.00463 +Epoch [2395/4000] Training [6/16] Loss: 0.00614 +Epoch [2395/4000] Training [7/16] Loss: 0.00434 +Epoch [2395/4000] Training [8/16] Loss: 0.00337 +Epoch [2395/4000] Training [9/16] Loss: 0.00424 +Epoch [2395/4000] Training [10/16] Loss: 0.00387 +Epoch [2395/4000] Training [11/16] Loss: 0.00489 +Epoch [2395/4000] Training [12/16] Loss: 0.00482 +Epoch [2395/4000] Training [13/16] Loss: 0.00488 +Epoch [2395/4000] Training [14/16] Loss: 0.00507 +Epoch [2395/4000] Training [15/16] Loss: 0.00608 +Epoch [2395/4000] Training [16/16] Loss: 0.00656 +Epoch [2395/4000] Training metric {'Train/mean dice_metric': 0.9969143867492676, 'Train/mean miou_metric': 0.9935910701751709, 'Train/mean f1': 0.9925052523612976, 'Train/mean precision': 0.9880096912384033, 'Train/mean recall': 0.9970419406890869, 'Train/mean hd95_metric': 0.9857000112533569} +Epoch [2395/4000] Validation [1/4] Loss: 0.33116 focal_loss 0.26379 dice_loss 0.06737 +Epoch [2395/4000] Validation [2/4] Loss: 0.33138 focal_loss 0.22285 dice_loss 0.10853 +Epoch [2395/4000] Validation [3/4] Loss: 0.40930 focal_loss 0.31993 dice_loss 0.08938 +Epoch [2395/4000] Validation [4/4] Loss: 0.52927 focal_loss 0.39134 dice_loss 0.13793 +Epoch [2395/4000] Validation metric {'Val/mean dice_metric': 0.9735119938850403, 'Val/mean miou_metric': 0.9576774835586548, 'Val/mean f1': 0.9750574231147766, 'Val/mean precision': 0.9711859226226807, 'Val/mean recall': 0.9789599776268005, 'Val/mean hd95_metric': 5.707241058349609} +Cheakpoint... +Epoch [2395/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735119938850403, 'Val/mean miou_metric': 0.9576774835586548, 'Val/mean f1': 0.9750574231147766, 'Val/mean precision': 0.9711859226226807, 'Val/mean recall': 0.9789599776268005, 'Val/mean hd95_metric': 5.707241058349609} +Epoch [2396/4000] Training [1/16] Loss: 0.01670 +Epoch [2396/4000] Training [2/16] Loss: 0.00515 +Epoch [2396/4000] Training [3/16] Loss: 0.00579 +Epoch [2396/4000] Training [4/16] Loss: 0.00319 +Epoch [2396/4000] Training [5/16] Loss: 0.00359 +Epoch [2396/4000] Training [6/16] Loss: 0.00544 +Epoch [2396/4000] Training [7/16] Loss: 0.00521 +Epoch [2396/4000] Training [8/16] Loss: 0.00410 +Epoch [2396/4000] Training [9/16] Loss: 0.00459 +Epoch [2396/4000] Training [10/16] Loss: 0.00479 +Epoch [2396/4000] Training [11/16] Loss: 0.00687 +Epoch [2396/4000] Training [12/16] Loss: 0.00392 +Epoch [2396/4000] Training [13/16] Loss: 0.00572 +Epoch [2396/4000] Training [14/16] Loss: 0.00464 +Epoch [2396/4000] Training [15/16] Loss: 0.00386 +Epoch [2396/4000] Training [16/16] Loss: 0.00492 +Epoch [2396/4000] Training metric {'Train/mean dice_metric': 0.9968664050102234, 'Train/mean miou_metric': 0.9934859275817871, 'Train/mean f1': 0.9923914074897766, 'Train/mean precision': 0.9879753589630127, 'Train/mean recall': 0.9968470335006714, 'Train/mean hd95_metric': 1.0829505920410156} +Epoch [2396/4000] Validation [1/4] Loss: 0.30412 focal_loss 0.24092 dice_loss 0.06320 +Epoch [2396/4000] Validation [2/4] Loss: 0.31520 focal_loss 0.20870 dice_loss 0.10650 +Epoch [2396/4000] Validation [3/4] Loss: 0.36636 focal_loss 0.27874 dice_loss 0.08762 +Epoch [2396/4000] Validation [4/4] Loss: 0.28187 focal_loss 0.18369 dice_loss 0.09818 +Epoch [2396/4000] Validation metric {'Val/mean dice_metric': 0.9758265614509583, 'Val/mean miou_metric': 0.9601251482963562, 'Val/mean f1': 0.9762585163116455, 'Val/mean precision': 0.9703761339187622, 'Val/mean recall': 0.9822126626968384, 'Val/mean hd95_metric': 5.595954895019531} +Cheakpoint... +Epoch [2396/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758265614509583, 'Val/mean miou_metric': 0.9601251482963562, 'Val/mean f1': 0.9762585163116455, 'Val/mean precision': 0.9703761339187622, 'Val/mean recall': 0.9822126626968384, 'Val/mean hd95_metric': 5.595954895019531} +Epoch [2397/4000] Training [1/16] Loss: 0.00556 +Epoch [2397/4000] Training [2/16] Loss: 0.00474 +Epoch [2397/4000] Training [3/16] Loss: 0.00467 +Epoch [2397/4000] Training [4/16] Loss: 0.00311 +Epoch [2397/4000] Training [5/16] Loss: 0.00480 +Epoch [2397/4000] Training [6/16] Loss: 0.00590 +Epoch [2397/4000] Training [7/16] Loss: 0.00406 +Epoch [2397/4000] Training [8/16] Loss: 0.00459 +Epoch [2397/4000] Training [9/16] Loss: 0.00424 +Epoch [2397/4000] Training [10/16] Loss: 0.00462 +Epoch [2397/4000] Training [11/16] Loss: 0.00468 +Epoch [2397/4000] Training [12/16] Loss: 0.00426 +Epoch [2397/4000] Training [13/16] Loss: 0.00342 +Epoch [2397/4000] Training [14/16] Loss: 0.00486 +Epoch [2397/4000] Training [15/16] Loss: 0.00494 +Epoch [2397/4000] Training [16/16] Loss: 0.00579 +Epoch [2397/4000] Training metric {'Train/mean dice_metric': 0.9969170093536377, 'Train/mean miou_metric': 0.9935862421989441, 'Train/mean f1': 0.9923682808876038, 'Train/mean precision': 0.9878829717636108, 'Train/mean recall': 0.9968944787979126, 'Train/mean hd95_metric': 0.9830478429794312} +Epoch [2397/4000] Validation [1/4] Loss: 0.26373 focal_loss 0.20312 dice_loss 0.06061 +Epoch [2397/4000] Validation [2/4] Loss: 0.38986 focal_loss 0.25683 dice_loss 0.13303 +Epoch [2397/4000] Validation [3/4] Loss: 0.34707 focal_loss 0.25805 dice_loss 0.08902 +Epoch [2397/4000] Validation [4/4] Loss: 0.41528 focal_loss 0.28637 dice_loss 0.12892 +Epoch [2397/4000] Validation metric {'Val/mean dice_metric': 0.9739450216293335, 'Val/mean miou_metric': 0.9577156901359558, 'Val/mean f1': 0.9755734801292419, 'Val/mean precision': 0.9723896384239197, 'Val/mean recall': 0.9787781834602356, 'Val/mean hd95_metric': 5.321292877197266} +Cheakpoint... +Epoch [2397/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739450216293335, 'Val/mean miou_metric': 0.9577156901359558, 'Val/mean f1': 0.9755734801292419, 'Val/mean precision': 0.9723896384239197, 'Val/mean recall': 0.9787781834602356, 'Val/mean hd95_metric': 5.321292877197266} +Epoch [2398/4000] Training [1/16] Loss: 0.00568 +Epoch [2398/4000] Training [2/16] Loss: 0.00585 +Epoch [2398/4000] Training [3/16] Loss: 0.00373 +Epoch [2398/4000] Training [4/16] Loss: 0.00537 +Epoch [2398/4000] Training [5/16] Loss: 0.00554 +Epoch [2398/4000] Training [6/16] Loss: 0.00345 +Epoch [2398/4000] Training [7/16] Loss: 0.00545 +Epoch [2398/4000] Training [8/16] Loss: 0.00442 +Epoch [2398/4000] Training [9/16] Loss: 0.00507 +Epoch [2398/4000] Training [10/16] Loss: 0.00664 +Epoch [2398/4000] Training [11/16] Loss: 0.00349 +Epoch [2398/4000] Training [12/16] Loss: 0.00366 +Epoch [2398/4000] Training [13/16] Loss: 0.00449 +Epoch [2398/4000] Training [14/16] Loss: 0.00636 +Epoch [2398/4000] Training [15/16] Loss: 0.00478 +Epoch [2398/4000] Training [16/16] Loss: 0.00467 +Epoch [2398/4000] Training metric {'Train/mean dice_metric': 0.9967948198318481, 'Train/mean miou_metric': 0.9933466911315918, 'Train/mean f1': 0.9923200607299805, 'Train/mean precision': 0.9877210259437561, 'Train/mean recall': 0.9969619512557983, 'Train/mean hd95_metric': 0.9776779413223267} +Epoch [2398/4000] Validation [1/4] Loss: 0.37251 focal_loss 0.30800 dice_loss 0.06451 +Epoch [2398/4000] Validation [2/4] Loss: 0.49091 focal_loss 0.35284 dice_loss 0.13807 +Epoch [2398/4000] Validation [3/4] Loss: 0.44890 focal_loss 0.34309 dice_loss 0.10581 +Epoch [2398/4000] Validation [4/4] Loss: 0.29799 focal_loss 0.19965 dice_loss 0.09834 +Epoch [2398/4000] Validation metric {'Val/mean dice_metric': 0.9734306335449219, 'Val/mean miou_metric': 0.9575145840644836, 'Val/mean f1': 0.9751525521278381, 'Val/mean precision': 0.9706483483314514, 'Val/mean recall': 0.9796987771987915, 'Val/mean hd95_metric': 5.679062843322754} +Cheakpoint... +Epoch [2398/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734306335449219, 'Val/mean miou_metric': 0.9575145840644836, 'Val/mean f1': 0.9751525521278381, 'Val/mean precision': 0.9706483483314514, 'Val/mean recall': 0.9796987771987915, 'Val/mean hd95_metric': 5.679062843322754} +Epoch [2399/4000] Training [1/16] Loss: 0.00416 +Epoch [2399/4000] Training [2/16] Loss: 0.00518 +Epoch [2399/4000] Training [3/16] Loss: 0.00342 +Epoch [2399/4000] Training [4/16] Loss: 0.00408 +Epoch [2399/4000] Training [5/16] Loss: 0.00414 +Epoch [2399/4000] Training [6/16] Loss: 0.00420 +Epoch [2399/4000] Training [7/16] Loss: 0.00347 +Epoch [2399/4000] Training [8/16] Loss: 0.00317 +Epoch [2399/4000] Training [9/16] Loss: 0.00375 +Epoch [2399/4000] Training [10/16] Loss: 0.00409 +Epoch [2399/4000] Training [11/16] Loss: 0.00435 +Epoch [2399/4000] Training [12/16] Loss: 0.00359 +Epoch [2399/4000] Training [13/16] Loss: 0.00367 +Epoch [2399/4000] Training [14/16] Loss: 0.00665 +Epoch [2399/4000] Training [15/16] Loss: 0.00440 +Epoch [2399/4000] Training [16/16] Loss: 0.00459 +Epoch [2399/4000] Training metric {'Train/mean dice_metric': 0.9973609447479248, 'Train/mean miou_metric': 0.9944396018981934, 'Train/mean f1': 0.9923120141029358, 'Train/mean precision': 0.987486720085144, 'Train/mean recall': 0.997184693813324, 'Train/mean hd95_metric': 0.9619972705841064} +Epoch [2399/4000] Validation [1/4] Loss: 0.28784 focal_loss 0.22334 dice_loss 0.06450 +Epoch [2399/4000] Validation [2/4] Loss: 0.75363 focal_loss 0.54788 dice_loss 0.20576 +Epoch [2399/4000] Validation [3/4] Loss: 0.37939 focal_loss 0.29302 dice_loss 0.08637 +Epoch [2399/4000] Validation [4/4] Loss: 0.28092 focal_loss 0.18708 dice_loss 0.09384 +Epoch [2399/4000] Validation metric {'Val/mean dice_metric': 0.9735845327377319, 'Val/mean miou_metric': 0.9588232040405273, 'Val/mean f1': 0.9758629202842712, 'Val/mean precision': 0.9714816212654114, 'Val/mean recall': 0.9802840948104858, 'Val/mean hd95_metric': 5.4580512046813965} +Cheakpoint... +Epoch [2399/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735845327377319, 'Val/mean miou_metric': 0.9588232040405273, 'Val/mean f1': 0.9758629202842712, 'Val/mean precision': 0.9714816212654114, 'Val/mean recall': 0.9802840948104858, 'Val/mean hd95_metric': 5.4580512046813965} +Epoch [2400/4000] Training [1/16] Loss: 0.00628 +Epoch [2400/4000] Training [2/16] Loss: 0.00455 +Epoch [2400/4000] Training [3/16] Loss: 0.00447 +Epoch [2400/4000] Training [4/16] Loss: 0.00368 +Epoch [2400/4000] Training [5/16] Loss: 0.00518 +Epoch [2400/4000] Training [6/16] Loss: 0.00292 +Epoch [2400/4000] Training [7/16] Loss: 0.00418 +Epoch [2400/4000] Training [8/16] Loss: 0.00548 +Epoch [2400/4000] Training [9/16] Loss: 0.00502 +Epoch [2400/4000] Training [10/16] Loss: 0.00483 +Epoch [2400/4000] Training [11/16] Loss: 0.00421 +Epoch [2400/4000] Training [12/16] Loss: 0.00405 +Epoch [2400/4000] Training [13/16] Loss: 0.00410 +Epoch [2400/4000] Training [14/16] Loss: 0.00500 +Epoch [2400/4000] Training [15/16] Loss: 0.00641 +Epoch [2400/4000] Training [16/16] Loss: 0.00617 +Epoch [2400/4000] Training metric {'Train/mean dice_metric': 0.997146487236023, 'Train/mean miou_metric': 0.9940416812896729, 'Train/mean f1': 0.9926407337188721, 'Train/mean precision': 0.9880882501602173, 'Train/mean recall': 0.9972352981567383, 'Train/mean hd95_metric': 0.9598153829574585} +Epoch [2400/4000] Validation [1/4] Loss: 0.27532 focal_loss 0.21207 dice_loss 0.06326 +Epoch [2400/4000] Validation [2/4] Loss: 0.81856 focal_loss 0.61205 dice_loss 0.20650 +Epoch [2400/4000] Validation [3/4] Loss: 0.38149 focal_loss 0.28483 dice_loss 0.09665 +Epoch [2400/4000] Validation [4/4] Loss: 0.27486 focal_loss 0.18269 dice_loss 0.09217 +Epoch [2400/4000] Validation metric {'Val/mean dice_metric': 0.9743220210075378, 'Val/mean miou_metric': 0.9592251777648926, 'Val/mean f1': 0.9757915735244751, 'Val/mean precision': 0.9716917872428894, 'Val/mean recall': 0.9799260497093201, 'Val/mean hd95_metric': 4.9321675300598145} +Cheakpoint... +Epoch [2400/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743220210075378, 'Val/mean miou_metric': 0.9592251777648926, 'Val/mean f1': 0.9757915735244751, 'Val/mean precision': 0.9716917872428894, 'Val/mean recall': 0.9799260497093201, 'Val/mean hd95_metric': 4.9321675300598145} +Epoch [2401/4000] Training [1/16] Loss: 0.00535 +Epoch [2401/4000] Training [2/16] Loss: 0.00423 +Epoch [2401/4000] Training [3/16] Loss: 0.00449 +Epoch [2401/4000] Training [4/16] Loss: 0.00354 +Epoch [2401/4000] Training [5/16] Loss: 0.00291 +Epoch [2401/4000] Training [6/16] Loss: 0.00700 +Epoch [2401/4000] Training [7/16] Loss: 0.00513 +Epoch [2401/4000] Training [8/16] Loss: 0.00411 +Epoch [2401/4000] Training [9/16] Loss: 0.00447 +Epoch [2401/4000] Training [10/16] Loss: 0.00548 +Epoch [2401/4000] Training [11/16] Loss: 0.00378 +Epoch [2401/4000] Training [12/16] Loss: 0.00867 +Epoch [2401/4000] Training [13/16] Loss: 0.00445 +Epoch [2401/4000] Training [14/16] Loss: 0.00361 +Epoch [2401/4000] Training [15/16] Loss: 0.00328 +Epoch [2401/4000] Training [16/16] Loss: 0.00439 +Epoch [2401/4000] Training metric {'Train/mean dice_metric': 0.9970614910125732, 'Train/mean miou_metric': 0.993877649307251, 'Train/mean f1': 0.9925468564033508, 'Train/mean precision': 0.9880830645561218, 'Train/mean recall': 0.9970511794090271, 'Train/mean hd95_metric': 0.9663923978805542} +Epoch [2401/4000] Validation [1/4] Loss: 0.28575 focal_loss 0.22293 dice_loss 0.06282 +Epoch [2401/4000] Validation [2/4] Loss: 0.33268 focal_loss 0.22114 dice_loss 0.11154 +Epoch [2401/4000] Validation [3/4] Loss: 0.36848 focal_loss 0.27111 dice_loss 0.09737 +Epoch [2401/4000] Validation [4/4] Loss: 0.24885 focal_loss 0.16210 dice_loss 0.08674 +Epoch [2401/4000] Validation metric {'Val/mean dice_metric': 0.9752298593521118, 'Val/mean miou_metric': 0.9597188234329224, 'Val/mean f1': 0.9756909012794495, 'Val/mean precision': 0.9731860756874084, 'Val/mean recall': 0.9782086610794067, 'Val/mean hd95_metric': 4.822426795959473} +Cheakpoint... +Epoch [2401/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752298593521118, 'Val/mean miou_metric': 0.9597188234329224, 'Val/mean f1': 0.9756909012794495, 'Val/mean precision': 0.9731860756874084, 'Val/mean recall': 0.9782086610794067, 'Val/mean hd95_metric': 4.822426795959473} +Epoch [2402/4000] Training [1/16] Loss: 0.00347 +Epoch [2402/4000] Training [2/16] Loss: 0.00329 +Epoch [2402/4000] Training [3/16] Loss: 0.00500 +Epoch [2402/4000] Training [4/16] Loss: 0.00428 +Epoch [2402/4000] Training [5/16] Loss: 0.00481 +Epoch [2402/4000] Training [6/16] Loss: 0.00432 +Epoch [2402/4000] Training [7/16] Loss: 0.00409 +Epoch [2402/4000] Training [8/16] Loss: 0.00379 +Epoch [2402/4000] Training [9/16] Loss: 0.00353 +Epoch [2402/4000] Training [10/16] Loss: 0.00484 +Epoch [2402/4000] Training [11/16] Loss: 0.00597 +Epoch [2402/4000] Training [12/16] Loss: 0.00593 +Epoch [2402/4000] Training [13/16] Loss: 0.00392 +Epoch [2402/4000] Training [14/16] Loss: 0.00636 +Epoch [2402/4000] Training [15/16] Loss: 0.00528 +Epoch [2402/4000] Training [16/16] Loss: 0.00405 +Epoch [2402/4000] Training metric {'Train/mean dice_metric': 0.9972004294395447, 'Train/mean miou_metric': 0.994146466255188, 'Train/mean f1': 0.9925841689109802, 'Train/mean precision': 0.988053023815155, 'Train/mean recall': 0.997157096862793, 'Train/mean hd95_metric': 0.9706887602806091} +Epoch [2402/4000] Validation [1/4] Loss: 0.31238 focal_loss 0.24713 dice_loss 0.06525 +Epoch [2402/4000] Validation [2/4] Loss: 0.35848 focal_loss 0.23713 dice_loss 0.12135 +Epoch [2402/4000] Validation [3/4] Loss: 0.40128 focal_loss 0.31152 dice_loss 0.08976 +Epoch [2402/4000] Validation [4/4] Loss: 0.60996 focal_loss 0.47161 dice_loss 0.13835 +Epoch [2402/4000] Validation metric {'Val/mean dice_metric': 0.9732373952865601, 'Val/mean miou_metric': 0.9576547741889954, 'Val/mean f1': 0.9747729301452637, 'Val/mean precision': 0.9720714688301086, 'Val/mean recall': 0.9774894118309021, 'Val/mean hd95_metric': 5.674663543701172} +Cheakpoint... +Epoch [2402/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732373952865601, 'Val/mean miou_metric': 0.9576547741889954, 'Val/mean f1': 0.9747729301452637, 'Val/mean precision': 0.9720714688301086, 'Val/mean recall': 0.9774894118309021, 'Val/mean hd95_metric': 5.674663543701172} +Epoch [2403/4000] Training [1/16] Loss: 0.00737 +Epoch [2403/4000] Training [2/16] Loss: 0.00555 +Epoch [2403/4000] Training [3/16] Loss: 0.00444 +Epoch [2403/4000] Training [4/16] Loss: 0.00468 +Epoch [2403/4000] Training [5/16] Loss: 0.00510 +Epoch [2403/4000] Training [6/16] Loss: 0.00718 +Epoch [2403/4000] Training [7/16] Loss: 0.00514 +Epoch [2403/4000] Training [8/16] Loss: 0.00528 +Epoch [2403/4000] Training [9/16] Loss: 0.00547 +Epoch [2403/4000] Training [10/16] Loss: 0.00425 +Epoch [2403/4000] Training [11/16] Loss: 0.00583 +Epoch [2403/4000] Training [12/16] Loss: 0.00419 +Epoch [2403/4000] Training [13/16] Loss: 0.00400 +Epoch [2403/4000] Training [14/16] Loss: 0.00547 +Epoch [2403/4000] Training [15/16] Loss: 0.00416 +Epoch [2403/4000] Training [16/16] Loss: 0.00520 +Epoch [2403/4000] Training metric {'Train/mean dice_metric': 0.9968047738075256, 'Train/mean miou_metric': 0.9933463931083679, 'Train/mean f1': 0.992110013961792, 'Train/mean precision': 0.9873406887054443, 'Train/mean recall': 0.9969256520271301, 'Train/mean hd95_metric': 0.9817943572998047} +Epoch [2403/4000] Validation [1/4] Loss: 0.31671 focal_loss 0.24783 dice_loss 0.06887 +Epoch [2403/4000] Validation [2/4] Loss: 0.68807 focal_loss 0.49293 dice_loss 0.19514 +Epoch [2403/4000] Validation [3/4] Loss: 0.61057 focal_loss 0.49589 dice_loss 0.11467 +Epoch [2403/4000] Validation [4/4] Loss: 0.28805 focal_loss 0.19338 dice_loss 0.09468 +Epoch [2403/4000] Validation metric {'Val/mean dice_metric': 0.9723148345947266, 'Val/mean miou_metric': 0.9565668106079102, 'Val/mean f1': 0.9746190905570984, 'Val/mean precision': 0.9727063775062561, 'Val/mean recall': 0.9765392541885376, 'Val/mean hd95_metric': 5.096796989440918} +Cheakpoint... +Epoch [2403/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723148345947266, 'Val/mean miou_metric': 0.9565668106079102, 'Val/mean f1': 0.9746190905570984, 'Val/mean precision': 0.9727063775062561, 'Val/mean recall': 0.9765392541885376, 'Val/mean hd95_metric': 5.096796989440918} +Epoch [2404/4000] Training [1/16] Loss: 0.00413 +Epoch [2404/4000] Training [2/16] Loss: 0.00541 +Epoch [2404/4000] Training [3/16] Loss: 0.00525 +Epoch [2404/4000] Training [4/16] Loss: 0.00426 +Epoch [2404/4000] Training [5/16] Loss: 0.00447 +Epoch [2404/4000] Training [6/16] Loss: 0.00380 +Epoch [2404/4000] Training [7/16] Loss: 0.00641 +Epoch [2404/4000] Training [8/16] Loss: 0.00317 +Epoch [2404/4000] Training [9/16] Loss: 0.00535 +Epoch [2404/4000] Training [10/16] Loss: 0.00516 +Epoch [2404/4000] Training [11/16] Loss: 0.00405 +Epoch [2404/4000] Training [12/16] Loss: 0.00463 +Epoch [2404/4000] Training [13/16] Loss: 0.00447 +Epoch [2404/4000] Training [14/16] Loss: 0.00653 +Epoch [2404/4000] Training [15/16] Loss: 0.00607 +Epoch [2404/4000] Training [16/16] Loss: 0.00466 +Epoch [2404/4000] Training metric {'Train/mean dice_metric': 0.996985673904419, 'Train/mean miou_metric': 0.9937188625335693, 'Train/mean f1': 0.9923605918884277, 'Train/mean precision': 0.9878005981445312, 'Train/mean recall': 0.99696284532547, 'Train/mean hd95_metric': 0.9723488688468933} +Epoch [2404/4000] Validation [1/4] Loss: 0.27607 focal_loss 0.21326 dice_loss 0.06281 +Epoch [2404/4000] Validation [2/4] Loss: 0.33842 focal_loss 0.22572 dice_loss 0.11270 +Epoch [2404/4000] Validation [3/4] Loss: 0.34046 focal_loss 0.24685 dice_loss 0.09362 +Epoch [2404/4000] Validation [4/4] Loss: 0.27083 focal_loss 0.17573 dice_loss 0.09510 +Epoch [2404/4000] Validation metric {'Val/mean dice_metric': 0.9736284017562866, 'Val/mean miou_metric': 0.9581969380378723, 'Val/mean f1': 0.9756107330322266, 'Val/mean precision': 0.9734393954277039, 'Val/mean recall': 0.9777916669845581, 'Val/mean hd95_metric': 5.726212501525879} +Cheakpoint... +Epoch [2404/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736284017562866, 'Val/mean miou_metric': 0.9581969380378723, 'Val/mean f1': 0.9756107330322266, 'Val/mean precision': 0.9734393954277039, 'Val/mean recall': 0.9777916669845581, 'Val/mean hd95_metric': 5.726212501525879} +Epoch [2405/4000] Training [1/16] Loss: 0.00505 +Epoch [2405/4000] Training [2/16] Loss: 0.00354 +Epoch [2405/4000] Training [3/16] Loss: 0.00388 +Epoch [2405/4000] Training [4/16] Loss: 0.00382 +Epoch [2405/4000] Training [5/16] Loss: 0.00462 +Epoch [2405/4000] Training [6/16] Loss: 0.00494 +Epoch [2405/4000] Training [7/16] Loss: 0.00584 +Epoch [2405/4000] Training [8/16] Loss: 0.00355 +Epoch [2405/4000] Training [9/16] Loss: 0.00436 +Epoch [2405/4000] Training [10/16] Loss: 0.00697 +Epoch [2405/4000] Training [11/16] Loss: 0.00518 +Epoch [2405/4000] Training [12/16] Loss: 0.00492 +Epoch [2405/4000] Training [13/16] Loss: 0.00382 +Epoch [2405/4000] Training [14/16] Loss: 0.00433 +Epoch [2405/4000] Training [15/16] Loss: 0.00600 +Epoch [2405/4000] Training [16/16] Loss: 0.00548 +Epoch [2405/4000] Training metric {'Train/mean dice_metric': 0.996986448764801, 'Train/mean miou_metric': 0.9937241673469543, 'Train/mean f1': 0.9924609661102295, 'Train/mean precision': 0.9879093170166016, 'Train/mean recall': 0.9970546960830688, 'Train/mean hd95_metric': 1.0054320096969604} +Epoch [2405/4000] Validation [1/4] Loss: 0.33316 focal_loss 0.26624 dice_loss 0.06692 +Epoch [2405/4000] Validation [2/4] Loss: 0.76153 focal_loss 0.56389 dice_loss 0.19764 +Epoch [2405/4000] Validation [3/4] Loss: 0.22842 focal_loss 0.16659 dice_loss 0.06183 +Epoch [2405/4000] Validation [4/4] Loss: 0.47383 focal_loss 0.33166 dice_loss 0.14217 +Epoch [2405/4000] Validation metric {'Val/mean dice_metric': 0.9717642068862915, 'Val/mean miou_metric': 0.9564114809036255, 'Val/mean f1': 0.9752126336097717, 'Val/mean precision': 0.9726576805114746, 'Val/mean recall': 0.9777809977531433, 'Val/mean hd95_metric': 5.30086088180542} +Cheakpoint... +Epoch [2405/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717642068862915, 'Val/mean miou_metric': 0.9564114809036255, 'Val/mean f1': 0.9752126336097717, 'Val/mean precision': 0.9726576805114746, 'Val/mean recall': 0.9777809977531433, 'Val/mean hd95_metric': 5.30086088180542} +Epoch [2406/4000] Training [1/16] Loss: 0.00732 +Epoch [2406/4000] Training [2/16] Loss: 0.00599 +Epoch [2406/4000] Training [3/16] Loss: 0.00359 +Epoch [2406/4000] Training [4/16] Loss: 0.00473 +Epoch [2406/4000] Training [5/16] Loss: 0.00444 +Epoch [2406/4000] Training [6/16] Loss: 0.00461 +Epoch [2406/4000] Training [7/16] Loss: 0.00430 +Epoch [2406/4000] Training [8/16] Loss: 0.00422 +Epoch [2406/4000] Training [9/16] Loss: 0.00432 +Epoch [2406/4000] Training [10/16] Loss: 0.00380 +Epoch [2406/4000] Training [11/16] Loss: 0.00591 +Epoch [2406/4000] Training [12/16] Loss: 0.00462 +Epoch [2406/4000] Training [13/16] Loss: 0.00473 +Epoch [2406/4000] Training [14/16] Loss: 0.00572 +Epoch [2406/4000] Training [15/16] Loss: 0.00425 +Epoch [2406/4000] Training [16/16] Loss: 0.00441 +Epoch [2406/4000] Training metric {'Train/mean dice_metric': 0.9970381855964661, 'Train/mean miou_metric': 0.9937956929206848, 'Train/mean f1': 0.9918457269668579, 'Train/mean precision': 0.9867739081382751, 'Train/mean recall': 0.9969698786735535, 'Train/mean hd95_metric': 0.9905470609664917} +Epoch [2406/4000] Validation [1/4] Loss: 0.34324 focal_loss 0.27516 dice_loss 0.06808 +Epoch [2406/4000] Validation [2/4] Loss: 0.31517 focal_loss 0.20333 dice_loss 0.11184 +Epoch [2406/4000] Validation [3/4] Loss: 0.39600 focal_loss 0.30444 dice_loss 0.09156 +Epoch [2406/4000] Validation [4/4] Loss: 0.32917 focal_loss 0.22289 dice_loss 0.10628 +Epoch [2406/4000] Validation metric {'Val/mean dice_metric': 0.9729423522949219, 'Val/mean miou_metric': 0.9575268030166626, 'Val/mean f1': 0.9747141599655151, 'Val/mean precision': 0.9720293879508972, 'Val/mean recall': 0.9774138331413269, 'Val/mean hd95_metric': 5.380459308624268} +Cheakpoint... +Epoch [2406/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729423522949219, 'Val/mean miou_metric': 0.9575268030166626, 'Val/mean f1': 0.9747141599655151, 'Val/mean precision': 0.9720293879508972, 'Val/mean recall': 0.9774138331413269, 'Val/mean hd95_metric': 5.380459308624268} +Epoch [2407/4000] Training [1/16] Loss: 0.00517 +Epoch [2407/4000] Training [2/16] Loss: 0.00511 +Epoch [2407/4000] Training [3/16] Loss: 0.00403 +Epoch [2407/4000] Training [4/16] Loss: 0.00472 +Epoch [2407/4000] Training [5/16] Loss: 0.00592 +Epoch [2407/4000] Training [6/16] Loss: 0.00492 +Epoch [2407/4000] Training [7/16] Loss: 0.00584 +Epoch [2407/4000] Training [8/16] Loss: 0.00404 +Epoch [2407/4000] Training [9/16] Loss: 0.00383 +Epoch [2407/4000] Training [10/16] Loss: 0.00477 +Epoch [2407/4000] Training [11/16] Loss: 0.00419 +Epoch [2407/4000] Training [12/16] Loss: 0.00513 +Epoch [2407/4000] Training [13/16] Loss: 0.00493 +Epoch [2407/4000] Training [14/16] Loss: 0.00437 +Epoch [2407/4000] Training [15/16] Loss: 0.00423 +Epoch [2407/4000] Training [16/16] Loss: 0.00382 +Epoch [2407/4000] Training metric {'Train/mean dice_metric': 0.9970158934593201, 'Train/mean miou_metric': 0.9937684535980225, 'Train/mean f1': 0.9923309087753296, 'Train/mean precision': 0.9876473546028137, 'Train/mean recall': 0.9970590472221375, 'Train/mean hd95_metric': 0.9646472930908203} +Epoch [2407/4000] Validation [1/4] Loss: 0.32347 focal_loss 0.25804 dice_loss 0.06544 +Epoch [2407/4000] Validation [2/4] Loss: 0.54543 focal_loss 0.39649 dice_loss 0.14893 +Epoch [2407/4000] Validation [3/4] Loss: 0.39017 focal_loss 0.29665 dice_loss 0.09351 +Epoch [2407/4000] Validation [4/4] Loss: 0.54590 focal_loss 0.40247 dice_loss 0.14344 +Epoch [2407/4000] Validation metric {'Val/mean dice_metric': 0.9727670550346375, 'Val/mean miou_metric': 0.9568595886230469, 'Val/mean f1': 0.9749829173088074, 'Val/mean precision': 0.9718304872512817, 'Val/mean recall': 0.9781556725502014, 'Val/mean hd95_metric': 5.5123491287231445} +Cheakpoint... +Epoch [2407/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727670550346375, 'Val/mean miou_metric': 0.9568595886230469, 'Val/mean f1': 0.9749829173088074, 'Val/mean precision': 0.9718304872512817, 'Val/mean recall': 0.9781556725502014, 'Val/mean hd95_metric': 5.5123491287231445} +Epoch [2408/4000] Training [1/16] Loss: 0.00421 +Epoch [2408/4000] Training [2/16] Loss: 0.00519 +Epoch [2408/4000] Training [3/16] Loss: 0.00648 +Epoch [2408/4000] Training [4/16] Loss: 0.00432 +Epoch [2408/4000] Training [5/16] Loss: 0.00396 +Epoch [2408/4000] Training [6/16] Loss: 0.00596 +Epoch [2408/4000] Training [7/16] Loss: 0.00476 +Epoch [2408/4000] Training [8/16] Loss: 0.00539 +Epoch [2408/4000] Training [9/16] Loss: 0.00345 +Epoch [2408/4000] Training [10/16] Loss: 0.00658 +Epoch [2408/4000] Training [11/16] Loss: 0.00501 +Epoch [2408/4000] Training [12/16] Loss: 0.00382 +Epoch [2408/4000] Training [13/16] Loss: 0.00414 +Epoch [2408/4000] Training [14/16] Loss: 0.00456 +Epoch [2408/4000] Training [15/16] Loss: 0.00557 +Epoch [2408/4000] Training [16/16] Loss: 0.00402 +Epoch [2408/4000] Training metric {'Train/mean dice_metric': 0.9971932172775269, 'Train/mean miou_metric': 0.9941197037696838, 'Train/mean f1': 0.9925840497016907, 'Train/mean precision': 0.9880560636520386, 'Train/mean recall': 0.9971536993980408, 'Train/mean hd95_metric': 0.9639226198196411} +Epoch [2408/4000] Validation [1/4] Loss: 0.35431 focal_loss 0.28900 dice_loss 0.06531 +Epoch [2408/4000] Validation [2/4] Loss: 0.31358 focal_loss 0.20635 dice_loss 0.10723 +Epoch [2408/4000] Validation [3/4] Loss: 0.20970 focal_loss 0.15254 dice_loss 0.05716 +Epoch [2408/4000] Validation [4/4] Loss: 0.22527 focal_loss 0.14167 dice_loss 0.08360 +Epoch [2408/4000] Validation metric {'Val/mean dice_metric': 0.9732734560966492, 'Val/mean miou_metric': 0.9586537480354309, 'Val/mean f1': 0.9764336347579956, 'Val/mean precision': 0.973871111869812, 'Val/mean recall': 0.9790096282958984, 'Val/mean hd95_metric': 5.643255710601807} +Cheakpoint... +Epoch [2408/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732734560966492, 'Val/mean miou_metric': 0.9586537480354309, 'Val/mean f1': 0.9764336347579956, 'Val/mean precision': 0.973871111869812, 'Val/mean recall': 0.9790096282958984, 'Val/mean hd95_metric': 5.643255710601807} +Epoch [2409/4000] Training [1/16] Loss: 0.00492 +Epoch [2409/4000] Training [2/16] Loss: 0.00430 +Epoch [2409/4000] Training [3/16] Loss: 0.00372 +Epoch [2409/4000] Training [4/16] Loss: 0.00441 +Epoch [2409/4000] Training [5/16] Loss: 0.00368 +Epoch [2409/4000] Training [6/16] Loss: 0.00482 +Epoch [2409/4000] Training [7/16] Loss: 0.00336 +Epoch [2409/4000] Training [8/16] Loss: 0.00588 +Epoch [2409/4000] Training [9/16] Loss: 0.00480 +Epoch [2409/4000] Training [10/16] Loss: 0.00432 +Epoch [2409/4000] Training [11/16] Loss: 0.00551 +Epoch [2409/4000] Training [12/16] Loss: 0.00375 +Epoch [2409/4000] Training [13/16] Loss: 0.00522 +Epoch [2409/4000] Training [14/16] Loss: 0.00322 +Epoch [2409/4000] Training [15/16] Loss: 0.00368 +Epoch [2409/4000] Training [16/16] Loss: 0.00383 +Epoch [2409/4000] Training metric {'Train/mean dice_metric': 0.9971835613250732, 'Train/mean miou_metric': 0.994114875793457, 'Train/mean f1': 0.9926819205284119, 'Train/mean precision': 0.9881469011306763, 'Train/mean recall': 0.9972588419914246, 'Train/mean hd95_metric': 0.9666848182678223} +Epoch [2409/4000] Validation [1/4] Loss: 0.33061 focal_loss 0.26495 dice_loss 0.06566 +Epoch [2409/4000] Validation [2/4] Loss: 0.52224 focal_loss 0.38055 dice_loss 0.14169 +Epoch [2409/4000] Validation [3/4] Loss: 0.40870 focal_loss 0.32045 dice_loss 0.08824 +Epoch [2409/4000] Validation [4/4] Loss: 0.40432 focal_loss 0.28441 dice_loss 0.11991 +Epoch [2409/4000] Validation metric {'Val/mean dice_metric': 0.9736993908882141, 'Val/mean miou_metric': 0.958043098449707, 'Val/mean f1': 0.975554883480072, 'Val/mean precision': 0.9725239872932434, 'Val/mean recall': 0.9786046147346497, 'Val/mean hd95_metric': 5.4889936447143555} +Cheakpoint... +Epoch [2409/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736993908882141, 'Val/mean miou_metric': 0.958043098449707, 'Val/mean f1': 0.975554883480072, 'Val/mean precision': 0.9725239872932434, 'Val/mean recall': 0.9786046147346497, 'Val/mean hd95_metric': 5.4889936447143555} +Epoch [2410/4000] Training [1/16] Loss: 0.00431 +Epoch [2410/4000] Training [2/16] Loss: 0.00456 +Epoch [2410/4000] Training [3/16] Loss: 0.00430 +Epoch [2410/4000] Training [4/16] Loss: 0.00379 +Epoch [2410/4000] Training [5/16] Loss: 0.00691 +Epoch [2410/4000] Training [6/16] Loss: 0.00488 +Epoch [2410/4000] Training [7/16] Loss: 0.00596 +Epoch [2410/4000] Training [8/16] Loss: 0.00334 +Epoch [2410/4000] Training [9/16] Loss: 0.00623 +Epoch [2410/4000] Training [10/16] Loss: 0.00455 +Epoch [2410/4000] Training [11/16] Loss: 0.00456 +Epoch [2410/4000] Training [12/16] Loss: 0.00349 +Epoch [2410/4000] Training [13/16] Loss: 0.00632 +Epoch [2410/4000] Training [14/16] Loss: 0.00484 +Epoch [2410/4000] Training [15/16] Loss: 0.00460 +Epoch [2410/4000] Training [16/16] Loss: 0.00501 +Epoch [2410/4000] Training metric {'Train/mean dice_metric': 0.9969731569290161, 'Train/mean miou_metric': 0.9936975240707397, 'Train/mean f1': 0.9924708008766174, 'Train/mean precision': 0.9878778457641602, 'Train/mean recall': 0.9971066117286682, 'Train/mean hd95_metric': 0.9994367361068726} +Epoch [2410/4000] Validation [1/4] Loss: 0.32658 focal_loss 0.25656 dice_loss 0.07001 +Epoch [2410/4000] Validation [2/4] Loss: 0.60257 focal_loss 0.42933 dice_loss 0.17324 +Epoch [2410/4000] Validation [3/4] Loss: 0.30517 focal_loss 0.21314 dice_loss 0.09203 +Epoch [2410/4000] Validation [4/4] Loss: 0.29319 focal_loss 0.19729 dice_loss 0.09590 +Epoch [2410/4000] Validation metric {'Val/mean dice_metric': 0.9696676135063171, 'Val/mean miou_metric': 0.9547640681266785, 'Val/mean f1': 0.9749725461006165, 'Val/mean precision': 0.9735721945762634, 'Val/mean recall': 0.9763768911361694, 'Val/mean hd95_metric': 5.71270751953125} +Cheakpoint... +Epoch [2410/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696676135063171, 'Val/mean miou_metric': 0.9547640681266785, 'Val/mean f1': 0.9749725461006165, 'Val/mean precision': 0.9735721945762634, 'Val/mean recall': 0.9763768911361694, 'Val/mean hd95_metric': 5.71270751953125} +Epoch [2411/4000] Training [1/16] Loss: 0.00447 +Epoch [2411/4000] Training [2/16] Loss: 0.00506 +Epoch [2411/4000] Training [3/16] Loss: 0.00453 +Epoch [2411/4000] Training [4/16] Loss: 0.00396 +Epoch [2411/4000] Training [5/16] Loss: 0.00349 +Epoch [2411/4000] Training [6/16] Loss: 0.00412 +Epoch [2411/4000] Training [7/16] Loss: 0.00630 +Epoch [2411/4000] Training [8/16] Loss: 0.00536 +Epoch [2411/4000] Training [9/16] Loss: 0.00387 +Epoch [2411/4000] Training [10/16] Loss: 0.00438 +Epoch [2411/4000] Training [11/16] Loss: 0.00660 +Epoch [2411/4000] Training [12/16] Loss: 0.00405 +Epoch [2411/4000] Training [13/16] Loss: 0.00627 +Epoch [2411/4000] Training [14/16] Loss: 0.00478 +Epoch [2411/4000] Training [15/16] Loss: 0.00522 +Epoch [2411/4000] Training [16/16] Loss: 0.00641 +Epoch [2411/4000] Training metric {'Train/mean dice_metric': 0.9968322515487671, 'Train/mean miou_metric': 0.9934329986572266, 'Train/mean f1': 0.9922347068786621, 'Train/mean precision': 0.9876073598861694, 'Train/mean recall': 0.9969056248664856, 'Train/mean hd95_metric': 1.0234837532043457} +Epoch [2411/4000] Validation [1/4] Loss: 0.36251 focal_loss 0.29585 dice_loss 0.06666 +Epoch [2411/4000] Validation [2/4] Loss: 0.27385 focal_loss 0.17569 dice_loss 0.09816 +Epoch [2411/4000] Validation [3/4] Loss: 0.34162 focal_loss 0.24484 dice_loss 0.09678 +Epoch [2411/4000] Validation [4/4] Loss: 0.26816 focal_loss 0.17949 dice_loss 0.08867 +Epoch [2411/4000] Validation metric {'Val/mean dice_metric': 0.9733017086982727, 'Val/mean miou_metric': 0.9581111669540405, 'Val/mean f1': 0.9757421612739563, 'Val/mean precision': 0.971836507320404, 'Val/mean recall': 0.9796793460845947, 'Val/mean hd95_metric': 5.182387351989746} +Cheakpoint... +Epoch [2411/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733017086982727, 'Val/mean miou_metric': 0.9581111669540405, 'Val/mean f1': 0.9757421612739563, 'Val/mean precision': 0.971836507320404, 'Val/mean recall': 0.9796793460845947, 'Val/mean hd95_metric': 5.182387351989746} +Epoch [2412/4000] Training [1/16] Loss: 0.00413 +Epoch [2412/4000] Training [2/16] Loss: 0.00527 +Epoch [2412/4000] Training [3/16] Loss: 0.00358 +Epoch [2412/4000] Training [4/16] Loss: 0.00348 +Epoch [2412/4000] Training [5/16] Loss: 0.00546 +Epoch [2412/4000] Training [6/16] Loss: 0.00364 +Epoch [2412/4000] Training [7/16] Loss: 0.00429 +Epoch [2412/4000] Training [8/16] Loss: 0.00437 +Epoch [2412/4000] Training [9/16] Loss: 0.00454 +Epoch [2412/4000] Training [10/16] Loss: 0.00379 +Epoch [2412/4000] Training [11/16] Loss: 0.00429 +Epoch [2412/4000] Training [12/16] Loss: 0.00515 +Epoch [2412/4000] Training [13/16] Loss: 0.00533 +Epoch [2412/4000] Training [14/16] Loss: 0.00336 +Epoch [2412/4000] Training [15/16] Loss: 0.00508 +Epoch [2412/4000] Training [16/16] Loss: 0.00449 +Epoch [2412/4000] Training metric {'Train/mean dice_metric': 0.9971575736999512, 'Train/mean miou_metric': 0.9940499067306519, 'Train/mean f1': 0.9925191402435303, 'Train/mean precision': 0.9879483580589294, 'Train/mean recall': 0.9971323609352112, 'Train/mean hd95_metric': 0.9654574394226074} +Epoch [2412/4000] Validation [1/4] Loss: 0.32790 focal_loss 0.25966 dice_loss 0.06824 +Epoch [2412/4000] Validation [2/4] Loss: 0.32213 focal_loss 0.21600 dice_loss 0.10613 +Epoch [2412/4000] Validation [3/4] Loss: 0.40029 focal_loss 0.31215 dice_loss 0.08814 +Epoch [2412/4000] Validation [4/4] Loss: 0.53737 focal_loss 0.40074 dice_loss 0.13662 +Epoch [2412/4000] Validation metric {'Val/mean dice_metric': 0.973802387714386, 'Val/mean miou_metric': 0.9580730199813843, 'Val/mean f1': 0.9750754237174988, 'Val/mean precision': 0.970568060874939, 'Val/mean recall': 0.9796249866485596, 'Val/mean hd95_metric': 5.550909519195557} +Cheakpoint... +Epoch [2412/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973802387714386, 'Val/mean miou_metric': 0.9580730199813843, 'Val/mean f1': 0.9750754237174988, 'Val/mean precision': 0.970568060874939, 'Val/mean recall': 0.9796249866485596, 'Val/mean hd95_metric': 5.550909519195557} +Epoch [2413/4000] Training [1/16] Loss: 0.00469 +Epoch [2413/4000] Training [2/16] Loss: 0.00393 +Epoch [2413/4000] Training [3/16] Loss: 0.00393 +Epoch [2413/4000] Training [4/16] Loss: 0.00500 +Epoch [2413/4000] Training [5/16] Loss: 0.00389 +Epoch [2413/4000] Training [6/16] Loss: 0.00461 +Epoch [2413/4000] Training [7/16] Loss: 0.00438 +Epoch [2413/4000] Training [8/16] Loss: 0.00532 +Epoch [2413/4000] Training [9/16] Loss: 0.00448 +Epoch [2413/4000] Training [10/16] Loss: 0.00442 +Epoch [2413/4000] Training [11/16] Loss: 0.00387 +Epoch [2413/4000] Training [12/16] Loss: 0.00431 +Epoch [2413/4000] Training [13/16] Loss: 0.00543 +Epoch [2413/4000] Training [14/16] Loss: 0.00585 +Epoch [2413/4000] Training [15/16] Loss: 0.00551 +Epoch [2413/4000] Training [16/16] Loss: 0.00392 +Epoch [2413/4000] Training metric {'Train/mean dice_metric': 0.9970717430114746, 'Train/mean miou_metric': 0.993872880935669, 'Train/mean f1': 0.9922035932540894, 'Train/mean precision': 0.987417459487915, 'Train/mean recall': 0.997036337852478, 'Train/mean hd95_metric': 0.9686673283576965} +Epoch [2413/4000] Validation [1/4] Loss: 0.37272 focal_loss 0.30076 dice_loss 0.07196 +Epoch [2413/4000] Validation [2/4] Loss: 0.59047 focal_loss 0.41528 dice_loss 0.17519 +Epoch [2413/4000] Validation [3/4] Loss: 0.37726 focal_loss 0.28222 dice_loss 0.09504 +Epoch [2413/4000] Validation [4/4] Loss: 0.58882 focal_loss 0.45759 dice_loss 0.13122 +Epoch [2413/4000] Validation metric {'Val/mean dice_metric': 0.9740017056465149, 'Val/mean miou_metric': 0.9584325551986694, 'Val/mean f1': 0.9743285179138184, 'Val/mean precision': 0.9716372489929199, 'Val/mean recall': 0.9770346879959106, 'Val/mean hd95_metric': 5.844250679016113} +Cheakpoint... +Epoch [2413/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740017056465149, 'Val/mean miou_metric': 0.9584325551986694, 'Val/mean f1': 0.9743285179138184, 'Val/mean precision': 0.9716372489929199, 'Val/mean recall': 0.9770346879959106, 'Val/mean hd95_metric': 5.844250679016113} +Epoch [2414/4000] Training [1/16] Loss: 0.00437 +Epoch [2414/4000] Training [2/16] Loss: 0.00509 +Epoch [2414/4000] Training [3/16] Loss: 0.00487 +Epoch [2414/4000] Training [4/16] Loss: 0.00379 +Epoch [2414/4000] Training [5/16] Loss: 0.00572 +Epoch [2414/4000] Training [6/16] Loss: 0.00562 +Epoch [2414/4000] Training [7/16] Loss: 0.00324 +Epoch [2414/4000] Training [8/16] Loss: 0.00387 +Epoch [2414/4000] Training [9/16] Loss: 0.00501 +Epoch [2414/4000] Training [10/16] Loss: 0.00517 +Epoch [2414/4000] Training [11/16] Loss: 0.00353 +Epoch [2414/4000] Training [12/16] Loss: 0.00658 +Epoch [2414/4000] Training [13/16] Loss: 0.00350 +Epoch [2414/4000] Training [14/16] Loss: 0.00470 +Epoch [2414/4000] Training [15/16] Loss: 0.00416 +Epoch [2414/4000] Training [16/16] Loss: 0.00526 +Epoch [2414/4000] Training metric {'Train/mean dice_metric': 0.9970437288284302, 'Train/mean miou_metric': 0.9938297271728516, 'Train/mean f1': 0.9924324750900269, 'Train/mean precision': 0.9878120422363281, 'Train/mean recall': 0.9970963001251221, 'Train/mean hd95_metric': 0.9703471660614014} +Epoch [2414/4000] Validation [1/4] Loss: 0.32381 focal_loss 0.25671 dice_loss 0.06711 +Epoch [2414/4000] Validation [2/4] Loss: 0.29168 focal_loss 0.18924 dice_loss 0.10244 +Epoch [2414/4000] Validation [3/4] Loss: 0.38454 focal_loss 0.29244 dice_loss 0.09210 +Epoch [2414/4000] Validation [4/4] Loss: 0.59746 focal_loss 0.46785 dice_loss 0.12961 +Epoch [2414/4000] Validation metric {'Val/mean dice_metric': 0.9722906351089478, 'Val/mean miou_metric': 0.9569019079208374, 'Val/mean f1': 0.973562479019165, 'Val/mean precision': 0.970285952091217, 'Val/mean recall': 0.9768612384796143, 'Val/mean hd95_metric': 5.839927673339844} +Cheakpoint... +Epoch [2414/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722906351089478, 'Val/mean miou_metric': 0.9569019079208374, 'Val/mean f1': 0.973562479019165, 'Val/mean precision': 0.970285952091217, 'Val/mean recall': 0.9768612384796143, 'Val/mean hd95_metric': 5.839927673339844} +Epoch [2415/4000] Training [1/16] Loss: 0.00416 +Epoch [2415/4000] Training [2/16] Loss: 0.00475 +Epoch [2415/4000] Training [3/16] Loss: 0.00397 +Epoch [2415/4000] Training [4/16] Loss: 0.00649 +Epoch [2415/4000] Training [5/16] Loss: 0.00465 +Epoch [2415/4000] Training [6/16] Loss: 0.00316 +Epoch [2415/4000] Training [7/16] Loss: 0.00459 +Epoch [2415/4000] Training [8/16] Loss: 0.00454 +Epoch [2415/4000] Training [9/16] Loss: 0.00479 +Epoch [2415/4000] Training [10/16] Loss: 0.00539 +Epoch [2415/4000] Training [11/16] Loss: 0.00624 +Epoch [2415/4000] Training [12/16] Loss: 0.00494 +Epoch [2415/4000] Training [13/16] Loss: 0.00427 +Epoch [2415/4000] Training [14/16] Loss: 0.00405 +Epoch [2415/4000] Training [15/16] Loss: 0.00395 +Epoch [2415/4000] Training [16/16] Loss: 0.00364 +Epoch [2415/4000] Training metric {'Train/mean dice_metric': 0.9972472190856934, 'Train/mean miou_metric': 0.9942407011985779, 'Train/mean f1': 0.9926921129226685, 'Train/mean precision': 0.9881349802017212, 'Train/mean recall': 0.9972915053367615, 'Train/mean hd95_metric': 0.9615788459777832} +Epoch [2415/4000] Validation [1/4] Loss: 0.28840 focal_loss 0.22615 dice_loss 0.06224 +Epoch [2415/4000] Validation [2/4] Loss: 0.32784 focal_loss 0.21805 dice_loss 0.10979 +Epoch [2415/4000] Validation [3/4] Loss: 0.36678 focal_loss 0.27583 dice_loss 0.09095 +Epoch [2415/4000] Validation [4/4] Loss: 0.31494 focal_loss 0.21600 dice_loss 0.09894 +Epoch [2415/4000] Validation metric {'Val/mean dice_metric': 0.9754177927970886, 'Val/mean miou_metric': 0.9599208831787109, 'Val/mean f1': 0.9758928418159485, 'Val/mean precision': 0.9715409278869629, 'Val/mean recall': 0.9802839756011963, 'Val/mean hd95_metric': 5.329391956329346} +Cheakpoint... +Epoch [2415/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754177927970886, 'Val/mean miou_metric': 0.9599208831787109, 'Val/mean f1': 0.9758928418159485, 'Val/mean precision': 0.9715409278869629, 'Val/mean recall': 0.9802839756011963, 'Val/mean hd95_metric': 5.329391956329346} +Epoch [2416/4000] Training [1/16] Loss: 0.00443 +Epoch [2416/4000] Training [2/16] Loss: 0.00376 +Epoch [2416/4000] Training [3/16] Loss: 0.00609 +Epoch [2416/4000] Training [4/16] Loss: 0.01108 +Epoch [2416/4000] Training [5/16] Loss: 0.00301 +Epoch [2416/4000] Training [6/16] Loss: 0.00376 +Epoch [2416/4000] Training [7/16] Loss: 0.00414 +Epoch [2416/4000] Training [8/16] Loss: 0.00490 +Epoch [2416/4000] Training [9/16] Loss: 0.00419 +Epoch [2416/4000] Training [10/16] Loss: 0.00449 +Epoch [2416/4000] Training [11/16] Loss: 0.00546 +Epoch [2416/4000] Training [12/16] Loss: 0.00444 +Epoch [2416/4000] Training [13/16] Loss: 0.00433 +Epoch [2416/4000] Training [14/16] Loss: 0.00469 +Epoch [2416/4000] Training [15/16] Loss: 0.00419 +Epoch [2416/4000] Training [16/16] Loss: 0.00544 +Epoch [2416/4000] Training metric {'Train/mean dice_metric': 0.9970827102661133, 'Train/mean miou_metric': 0.9939263463020325, 'Train/mean f1': 0.9926446080207825, 'Train/mean precision': 0.9881999492645264, 'Train/mean recall': 0.9971293807029724, 'Train/mean hd95_metric': 1.0006738901138306} +Epoch [2416/4000] Validation [1/4] Loss: 0.32029 focal_loss 0.25426 dice_loss 0.06603 +Epoch [2416/4000] Validation [2/4] Loss: 0.35327 focal_loss 0.23982 dice_loss 0.11346 +Epoch [2416/4000] Validation [3/4] Loss: 0.40864 focal_loss 0.32026 dice_loss 0.08838 +Epoch [2416/4000] Validation [4/4] Loss: 0.54072 focal_loss 0.42204 dice_loss 0.11868 +Epoch [2416/4000] Validation metric {'Val/mean dice_metric': 0.9735172986984253, 'Val/mean miou_metric': 0.9577215313911438, 'Val/mean f1': 0.9752514958381653, 'Val/mean precision': 0.9724533557891846, 'Val/mean recall': 0.9780657291412354, 'Val/mean hd95_metric': 5.693984031677246} +Cheakpoint... +Epoch [2416/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735172986984253, 'Val/mean miou_metric': 0.9577215313911438, 'Val/mean f1': 0.9752514958381653, 'Val/mean precision': 0.9724533557891846, 'Val/mean recall': 0.9780657291412354, 'Val/mean hd95_metric': 5.693984031677246} +Epoch [2417/4000] Training [1/16] Loss: 0.00420 +Epoch [2417/4000] Training [2/16] Loss: 0.00412 +Epoch [2417/4000] Training [3/16] Loss: 0.00475 +Epoch [2417/4000] Training [4/16] Loss: 0.00554 +Epoch [2417/4000] Training [5/16] Loss: 0.00505 +Epoch [2417/4000] Training [6/16] Loss: 0.00495 +Epoch [2417/4000] Training [7/16] Loss: 0.00590 +Epoch [2417/4000] Training [8/16] Loss: 0.00496 +Epoch [2417/4000] Training [9/16] Loss: 0.00389 +Epoch [2417/4000] Training [10/16] Loss: 0.00493 +Epoch [2417/4000] Training [11/16] Loss: 0.00547 +Epoch [2417/4000] Training [12/16] Loss: 0.00389 +Epoch [2417/4000] Training [13/16] Loss: 0.00381 +Epoch [2417/4000] Training [14/16] Loss: 0.00504 +Epoch [2417/4000] Training [15/16] Loss: 0.00408 +Epoch [2417/4000] Training [16/16] Loss: 0.00361 +Epoch [2417/4000] Training metric {'Train/mean dice_metric': 0.9971243739128113, 'Train/mean miou_metric': 0.9939959049224854, 'Train/mean f1': 0.9925140738487244, 'Train/mean precision': 0.987956702709198, 'Train/mean recall': 0.9971136450767517, 'Train/mean hd95_metric': 0.9620949029922485} +Epoch [2417/4000] Validation [1/4] Loss: 0.30664 focal_loss 0.24040 dice_loss 0.06624 +Epoch [2417/4000] Validation [2/4] Loss: 0.36493 focal_loss 0.24981 dice_loss 0.11512 +Epoch [2417/4000] Validation [3/4] Loss: 0.37706 focal_loss 0.28470 dice_loss 0.09236 +Epoch [2417/4000] Validation [4/4] Loss: 0.39336 focal_loss 0.28155 dice_loss 0.11181 +Epoch [2417/4000] Validation metric {'Val/mean dice_metric': 0.9726215600967407, 'Val/mean miou_metric': 0.957497775554657, 'Val/mean f1': 0.9747394919395447, 'Val/mean precision': 0.9717211723327637, 'Val/mean recall': 0.9777767658233643, 'Val/mean hd95_metric': 5.430132865905762} +Cheakpoint... +Epoch [2417/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726215600967407, 'Val/mean miou_metric': 0.957497775554657, 'Val/mean f1': 0.9747394919395447, 'Val/mean precision': 0.9717211723327637, 'Val/mean recall': 0.9777767658233643, 'Val/mean hd95_metric': 5.430132865905762} +Epoch [2418/4000] Training [1/16] Loss: 0.00469 +Epoch [2418/4000] Training [2/16] Loss: 0.00385 +Epoch [2418/4000] Training [3/16] Loss: 0.00345 +Epoch [2418/4000] Training [4/16] Loss: 0.00619 +Epoch [2418/4000] Training [5/16] Loss: 0.00391 +Epoch [2418/4000] Training [6/16] Loss: 0.00483 +Epoch [2418/4000] Training [7/16] Loss: 0.00402 +Epoch [2418/4000] Training [8/16] Loss: 0.00406 +Epoch [2418/4000] Training [9/16] Loss: 0.00351 +Epoch [2418/4000] Training [10/16] Loss: 0.00454 +Epoch [2418/4000] Training [11/16] Loss: 0.00431 +Epoch [2418/4000] Training [12/16] Loss: 0.00406 +Epoch [2418/4000] Training [13/16] Loss: 0.00608 +Epoch [2418/4000] Training [14/16] Loss: 0.00380 +Epoch [2418/4000] Training [15/16] Loss: 0.00516 +Epoch [2418/4000] Training [16/16] Loss: 0.00561 +Epoch [2418/4000] Training metric {'Train/mean dice_metric': 0.9971262216567993, 'Train/mean miou_metric': 0.9939658641815186, 'Train/mean f1': 0.991741955280304, 'Train/mean precision': 0.9864475727081299, 'Train/mean recall': 0.9970934987068176, 'Train/mean hd95_metric': 0.9759621620178223} +Epoch [2418/4000] Validation [1/4] Loss: 0.30842 focal_loss 0.24043 dice_loss 0.06800 +Epoch [2418/4000] Validation [2/4] Loss: 0.59732 focal_loss 0.43787 dice_loss 0.15945 +Epoch [2418/4000] Validation [3/4] Loss: 0.40383 focal_loss 0.31287 dice_loss 0.09095 +Epoch [2418/4000] Validation [4/4] Loss: 0.28790 focal_loss 0.19756 dice_loss 0.09034 +Epoch [2418/4000] Validation metric {'Val/mean dice_metric': 0.9740899801254272, 'Val/mean miou_metric': 0.9586084485054016, 'Val/mean f1': 0.9748113751411438, 'Val/mean precision': 0.9709213376045227, 'Val/mean recall': 0.9787325263023376, 'Val/mean hd95_metric': 5.606117248535156} +Cheakpoint... +Epoch [2418/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740899801254272, 'Val/mean miou_metric': 0.9586084485054016, 'Val/mean f1': 0.9748113751411438, 'Val/mean precision': 0.9709213376045227, 'Val/mean recall': 0.9787325263023376, 'Val/mean hd95_metric': 5.606117248535156} +Epoch [2419/4000] Training [1/16] Loss: 0.00511 +Epoch [2419/4000] Training [2/16] Loss: 0.00424 +Epoch [2419/4000] Training [3/16] Loss: 0.00607 +Epoch [2419/4000] Training [4/16] Loss: 0.00359 +Epoch [2419/4000] Training [5/16] Loss: 0.00365 +Epoch [2419/4000] Training [6/16] Loss: 0.00367 +Epoch [2419/4000] Training [7/16] Loss: 0.00449 +Epoch [2419/4000] Training [8/16] Loss: 0.00409 +Epoch [2419/4000] Training [9/16] Loss: 0.00408 +Epoch [2419/4000] Training [10/16] Loss: 0.00410 +Epoch [2419/4000] Training [11/16] Loss: 0.00416 +Epoch [2419/4000] Training [12/16] Loss: 0.00582 +Epoch [2419/4000] Training [13/16] Loss: 0.00432 +Epoch [2419/4000] Training [14/16] Loss: 0.00498 +Epoch [2419/4000] Training [15/16] Loss: 0.00576 +Epoch [2419/4000] Training [16/16] Loss: 0.00517 +Epoch [2419/4000] Training metric {'Train/mean dice_metric': 0.9969599843025208, 'Train/mean miou_metric': 0.9936732053756714, 'Train/mean f1': 0.9925432801246643, 'Train/mean precision': 0.9880077838897705, 'Train/mean recall': 0.9971206784248352, 'Train/mean hd95_metric': 1.266737937927246} +Epoch [2419/4000] Validation [1/4] Loss: 0.25012 focal_loss 0.18994 dice_loss 0.06017 +Epoch [2419/4000] Validation [2/4] Loss: 0.69684 focal_loss 0.50444 dice_loss 0.19239 +Epoch [2419/4000] Validation [3/4] Loss: 0.44452 focal_loss 0.34766 dice_loss 0.09686 +Epoch [2419/4000] Validation [4/4] Loss: 0.24879 focal_loss 0.16800 dice_loss 0.08078 +Epoch [2419/4000] Validation metric {'Val/mean dice_metric': 0.9729827642440796, 'Val/mean miou_metric': 0.9580268859863281, 'Val/mean f1': 0.9750346541404724, 'Val/mean precision': 0.9712873697280884, 'Val/mean recall': 0.9788110256195068, 'Val/mean hd95_metric': 5.954923629760742} +Cheakpoint... +Epoch [2419/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729827642440796, 'Val/mean miou_metric': 0.9580268859863281, 'Val/mean f1': 0.9750346541404724, 'Val/mean precision': 0.9712873697280884, 'Val/mean recall': 0.9788110256195068, 'Val/mean hd95_metric': 5.954923629760742} +Epoch [2420/4000] Training [1/16] Loss: 0.00396 +Epoch [2420/4000] Training [2/16] Loss: 0.00616 +Epoch [2420/4000] Training [3/16] Loss: 0.00409 +Epoch [2420/4000] Training [4/16] Loss: 0.00332 +Epoch [2420/4000] Training [5/16] Loss: 0.00405 +Epoch [2420/4000] Training [6/16] Loss: 0.00518 +Epoch [2420/4000] Training [7/16] Loss: 0.00453 +Epoch [2420/4000] Training [8/16] Loss: 0.00487 +Epoch [2420/4000] Training [9/16] Loss: 0.00451 +Epoch [2420/4000] Training [10/16] Loss: 0.00481 +Epoch [2420/4000] Training [11/16] Loss: 0.00506 +Epoch [2420/4000] Training [12/16] Loss: 0.00413 +Epoch [2420/4000] Training [13/16] Loss: 0.00406 +Epoch [2420/4000] Training [14/16] Loss: 0.00439 +Epoch [2420/4000] Training [15/16] Loss: 0.00643 +Epoch [2420/4000] Training [16/16] Loss: 0.00500 +Epoch [2420/4000] Training metric {'Train/mean dice_metric': 0.9971073865890503, 'Train/mean miou_metric': 0.9939640760421753, 'Train/mean f1': 0.9926342964172363, 'Train/mean precision': 0.9882006645202637, 'Train/mean recall': 0.9971079230308533, 'Train/mean hd95_metric': 0.992537796497345} +Epoch [2420/4000] Validation [1/4] Loss: 0.31073 focal_loss 0.24738 dice_loss 0.06335 +Epoch [2420/4000] Validation [2/4] Loss: 0.34411 focal_loss 0.22830 dice_loss 0.11582 +Epoch [2420/4000] Validation [3/4] Loss: 0.42338 focal_loss 0.33143 dice_loss 0.09195 +Epoch [2420/4000] Validation [4/4] Loss: 0.26398 focal_loss 0.17945 dice_loss 0.08453 +Epoch [2420/4000] Validation metric {'Val/mean dice_metric': 0.973844051361084, 'Val/mean miou_metric': 0.9583436846733093, 'Val/mean f1': 0.9759584069252014, 'Val/mean precision': 0.9724180698394775, 'Val/mean recall': 0.9795246124267578, 'Val/mean hd95_metric': 6.007449150085449} +Cheakpoint... +Epoch [2420/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973844051361084, 'Val/mean miou_metric': 0.9583436846733093, 'Val/mean f1': 0.9759584069252014, 'Val/mean precision': 0.9724180698394775, 'Val/mean recall': 0.9795246124267578, 'Val/mean hd95_metric': 6.007449150085449} +Epoch [2421/4000] Training [1/16] Loss: 0.00429 +Epoch [2421/4000] Training [2/16] Loss: 0.00636 +Epoch [2421/4000] Training [3/16] Loss: 0.00354 +Epoch [2421/4000] Training [4/16] Loss: 0.00583 +Epoch [2421/4000] Training [5/16] Loss: 0.00456 +Epoch [2421/4000] Training [6/16] Loss: 0.00667 +Epoch [2421/4000] Training [7/16] Loss: 0.00436 +Epoch [2421/4000] Training [8/16] Loss: 0.00421 +Epoch [2421/4000] Training [9/16] Loss: 0.00390 +Epoch [2421/4000] Training [10/16] Loss: 0.00774 +Epoch [2421/4000] Training [11/16] Loss: 0.00590 +Epoch [2421/4000] Training [12/16] Loss: 0.00311 +Epoch [2421/4000] Training [13/16] Loss: 0.00520 +Epoch [2421/4000] Training [14/16] Loss: 0.00548 +Epoch [2421/4000] Training [15/16] Loss: 0.00363 +Epoch [2421/4000] Training [16/16] Loss: 0.00413 +Epoch [2421/4000] Training metric {'Train/mean dice_metric': 0.9969258308410645, 'Train/mean miou_metric': 0.9936084747314453, 'Train/mean f1': 0.99250727891922, 'Train/mean precision': 0.9879623651504517, 'Train/mean recall': 0.9970941543579102, 'Train/mean hd95_metric': 0.9838318824768066} +Epoch [2421/4000] Validation [1/4] Loss: 0.28204 focal_loss 0.22120 dice_loss 0.06084 +Epoch [2421/4000] Validation [2/4] Loss: 0.34256 focal_loss 0.22388 dice_loss 0.11868 +Epoch [2421/4000] Validation [3/4] Loss: 0.38451 focal_loss 0.30068 dice_loss 0.08383 +Epoch [2421/4000] Validation [4/4] Loss: 0.51348 focal_loss 0.38306 dice_loss 0.13042 +Epoch [2421/4000] Validation metric {'Val/mean dice_metric': 0.9737588763237, 'Val/mean miou_metric': 0.9582041501998901, 'Val/mean f1': 0.9754055142402649, 'Val/mean precision': 0.9732313752174377, 'Val/mean recall': 0.9775895476341248, 'Val/mean hd95_metric': 5.364099025726318} +Cheakpoint... +Epoch [2421/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737588763237, 'Val/mean miou_metric': 0.9582041501998901, 'Val/mean f1': 0.9754055142402649, 'Val/mean precision': 0.9732313752174377, 'Val/mean recall': 0.9775895476341248, 'Val/mean hd95_metric': 5.364099025726318} +Epoch [2422/4000] Training [1/16] Loss: 0.00446 +Epoch [2422/4000] Training [2/16] Loss: 0.00391 +Epoch [2422/4000] Training [3/16] Loss: 0.00430 +Epoch [2422/4000] Training [4/16] Loss: 0.00381 +Epoch [2422/4000] Training [5/16] Loss: 0.00421 +Epoch [2422/4000] Training [6/16] Loss: 0.00377 +Epoch [2422/4000] Training [7/16] Loss: 0.00417 +Epoch [2422/4000] Training [8/16] Loss: 0.00638 +Epoch [2422/4000] Training [9/16] Loss: 0.00520 +Epoch [2422/4000] Training [10/16] Loss: 0.00512 +Epoch [2422/4000] Training [11/16] Loss: 0.00563 +Epoch [2422/4000] Training [12/16] Loss: 0.00426 +Epoch [2422/4000] Training [13/16] Loss: 0.00440 +Epoch [2422/4000] Training [14/16] Loss: 0.00506 +Epoch [2422/4000] Training [15/16] Loss: 0.00341 +Epoch [2422/4000] Training [16/16] Loss: 0.00378 +Epoch [2422/4000] Training metric {'Train/mean dice_metric': 0.9971023797988892, 'Train/mean miou_metric': 0.9939464330673218, 'Train/mean f1': 0.9924070239067078, 'Train/mean precision': 0.9877504110336304, 'Train/mean recall': 0.997107744216919, 'Train/mean hd95_metric': 0.963685154914856} +Epoch [2422/4000] Validation [1/4] Loss: 0.32400 focal_loss 0.25968 dice_loss 0.06432 +Epoch [2422/4000] Validation [2/4] Loss: 0.33638 focal_loss 0.21916 dice_loss 0.11721 +Epoch [2422/4000] Validation [3/4] Loss: 0.38988 focal_loss 0.29876 dice_loss 0.09112 +Epoch [2422/4000] Validation [4/4] Loss: 0.38968 focal_loss 0.28475 dice_loss 0.10493 +Epoch [2422/4000] Validation metric {'Val/mean dice_metric': 0.9744684100151062, 'Val/mean miou_metric': 0.9591692090034485, 'Val/mean f1': 0.9752576947212219, 'Val/mean precision': 0.9709739089012146, 'Val/mean recall': 0.9795794486999512, 'Val/mean hd95_metric': 5.545182704925537} +Cheakpoint... +Epoch [2422/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744684100151062, 'Val/mean miou_metric': 0.9591692090034485, 'Val/mean f1': 0.9752576947212219, 'Val/mean precision': 0.9709739089012146, 'Val/mean recall': 0.9795794486999512, 'Val/mean hd95_metric': 5.545182704925537} +Epoch [2423/4000] Training [1/16] Loss: 0.00397 +Epoch [2423/4000] Training [2/16] Loss: 0.00362 +Epoch [2423/4000] Training [3/16] Loss: 0.00380 +Epoch [2423/4000] Training [4/16] Loss: 0.00483 +Epoch [2423/4000] Training [5/16] Loss: 0.00487 +Epoch [2423/4000] Training [6/16] Loss: 0.00297 +Epoch [2423/4000] Training [7/16] Loss: 0.00495 +Epoch [2423/4000] Training [8/16] Loss: 0.00674 +Epoch [2423/4000] Training [9/16] Loss: 0.00385 +Epoch [2423/4000] Training [10/16] Loss: 0.00533 +Epoch [2423/4000] Training [11/16] Loss: 0.00611 +Epoch [2423/4000] Training [12/16] Loss: 0.00401 +Epoch [2423/4000] Training [13/16] Loss: 0.00458 +Epoch [2423/4000] Training [14/16] Loss: 0.00449 +Epoch [2423/4000] Training [15/16] Loss: 0.00472 +Epoch [2423/4000] Training [16/16] Loss: 0.00516 +Epoch [2423/4000] Training metric {'Train/mean dice_metric': 0.9970133304595947, 'Train/mean miou_metric': 0.9937772750854492, 'Train/mean f1': 0.9923439621925354, 'Train/mean precision': 0.9876496195793152, 'Train/mean recall': 0.9970830082893372, 'Train/mean hd95_metric': 0.9696844816207886} +Epoch [2423/4000] Validation [1/4] Loss: 0.33241 focal_loss 0.26584 dice_loss 0.06657 +Epoch [2423/4000] Validation [2/4] Loss: 0.38456 focal_loss 0.25901 dice_loss 0.12555 +Epoch [2423/4000] Validation [3/4] Loss: 0.42003 focal_loss 0.32867 dice_loss 0.09135 +Epoch [2423/4000] Validation [4/4] Loss: 0.24229 focal_loss 0.15663 dice_loss 0.08566 +Epoch [2423/4000] Validation metric {'Val/mean dice_metric': 0.9747932553291321, 'Val/mean miou_metric': 0.9593738317489624, 'Val/mean f1': 0.9759458899497986, 'Val/mean precision': 0.9728209972381592, 'Val/mean recall': 0.9790909886360168, 'Val/mean hd95_metric': 5.281325340270996} +Cheakpoint... +Epoch [2423/4000] best acc:tensor([0.9762], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747932553291321, 'Val/mean miou_metric': 0.9593738317489624, 'Val/mean f1': 0.9759458899497986, 'Val/mean precision': 0.9728209972381592, 'Val/mean recall': 0.9790909886360168, 'Val/mean hd95_metric': 5.281325340270996} +Epoch [2424/4000] Training [1/16] Loss: 0.00400 +Epoch [2424/4000] Training [2/16] Loss: 0.00421 +Epoch [2424/4000] Training [3/16] Loss: 0.00499 +Epoch [2424/4000] Training [4/16] Loss: 0.00336 +Epoch [2424/4000] Training [5/16] Loss: 0.00639 +Epoch [2424/4000] Training [6/16] Loss: 0.00516 +Epoch [2424/4000] Training [7/16] Loss: 0.00423 +Epoch [2424/4000] Training [8/16] Loss: 0.00641 +Epoch [2424/4000] Training [9/16] Loss: 0.00386 +Epoch [2424/4000] Training [10/16] Loss: 0.00602 +Epoch [2424/4000] Training [11/16] Loss: 0.00445 +Epoch [2424/4000] Training [12/16] Loss: 0.00378 +Epoch [2424/4000] Training [13/16] Loss: 0.00412 +Epoch [2424/4000] Training [14/16] Loss: 0.00483 +Epoch [2424/4000] Training [15/16] Loss: 0.00342 +Epoch [2424/4000] Training [16/16] Loss: 0.00401 +Epoch [2424/4000] Training metric {'Train/mean dice_metric': 0.9972902536392212, 'Train/mean miou_metric': 0.9943096041679382, 'Train/mean f1': 0.9925956130027771, 'Train/mean precision': 0.9879055619239807, 'Train/mean recall': 0.9973304271697998, 'Train/mean hd95_metric': 0.9553999304771423} +Epoch [2424/4000] Validation [1/4] Loss: 0.38410 focal_loss 0.31346 dice_loss 0.07064 +Epoch [2424/4000] Validation [2/4] Loss: 0.35755 focal_loss 0.23682 dice_loss 0.12073 +Epoch [2424/4000] Validation [3/4] Loss: 0.39723 focal_loss 0.31108 dice_loss 0.08615 +Epoch [2424/4000] Validation [4/4] Loss: 0.29404 focal_loss 0.19675 dice_loss 0.09729 +Epoch [2424/4000] Validation metric {'Val/mean dice_metric': 0.976292610168457, 'Val/mean miou_metric': 0.9607661366462708, 'Val/mean f1': 0.9755778312683105, 'Val/mean precision': 0.9725966453552246, 'Val/mean recall': 0.9785772562026978, 'Val/mean hd95_metric': 5.060739040374756} +Cheakpoint... +Epoch [2424/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9763], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.976292610168457, 'Val/mean miou_metric': 0.9607661366462708, 'Val/mean f1': 0.9755778312683105, 'Val/mean precision': 0.9725966453552246, 'Val/mean recall': 0.9785772562026978, 'Val/mean hd95_metric': 5.060739040374756} +Epoch [2425/4000] Training [1/16] Loss: 0.00522 +Epoch [2425/4000] Training [2/16] Loss: 0.00377 +Epoch [2425/4000] Training [3/16] Loss: 0.00459 +Epoch [2425/4000] Training [4/16] Loss: 0.00439 +Epoch [2425/4000] Training [5/16] Loss: 0.00486 +Epoch [2425/4000] Training [6/16] Loss: 0.00602 +Epoch [2425/4000] Training [7/16] Loss: 0.00511 +Epoch [2425/4000] Training [8/16] Loss: 0.00581 +Epoch [2425/4000] Training [9/16] Loss: 0.00514 +Epoch [2425/4000] Training [10/16] Loss: 0.00462 +Epoch [2425/4000] Training [11/16] Loss: 0.00431 +Epoch [2425/4000] Training [12/16] Loss: 0.00415 +Epoch [2425/4000] Training [13/16] Loss: 0.00646 +Epoch [2425/4000] Training [14/16] Loss: 0.00499 +Epoch [2425/4000] Training [15/16] Loss: 0.00489 +Epoch [2425/4000] Training [16/16] Loss: 0.00420 +Epoch [2425/4000] Training metric {'Train/mean dice_metric': 0.9970357418060303, 'Train/mean miou_metric': 0.9938259124755859, 'Train/mean f1': 0.992546021938324, 'Train/mean precision': 0.9881150126457214, 'Train/mean recall': 0.997016966342926, 'Train/mean hd95_metric': 0.9668240547180176} +Epoch [2425/4000] Validation [1/4] Loss: 0.33131 focal_loss 0.26666 dice_loss 0.06465 +Epoch [2425/4000] Validation [2/4] Loss: 0.34468 focal_loss 0.22586 dice_loss 0.11882 +Epoch [2425/4000] Validation [3/4] Loss: 0.22137 focal_loss 0.16107 dice_loss 0.06030 +Epoch [2425/4000] Validation [4/4] Loss: 0.42110 focal_loss 0.30121 dice_loss 0.11989 +Epoch [2425/4000] Validation metric {'Val/mean dice_metric': 0.9738659858703613, 'Val/mean miou_metric': 0.9585302472114563, 'Val/mean f1': 0.9751423001289368, 'Val/mean precision': 0.9726808667182922, 'Val/mean recall': 0.9776163101196289, 'Val/mean hd95_metric': 5.250093936920166} +Cheakpoint... +Epoch [2425/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738659858703613, 'Val/mean miou_metric': 0.9585302472114563, 'Val/mean f1': 0.9751423001289368, 'Val/mean precision': 0.9726808667182922, 'Val/mean recall': 0.9776163101196289, 'Val/mean hd95_metric': 5.250093936920166} +Epoch [2426/4000] Training [1/16] Loss: 0.00371 +Epoch [2426/4000] Training [2/16] Loss: 0.00392 +Epoch [2426/4000] Training [3/16] Loss: 0.00390 +Epoch [2426/4000] Training [4/16] Loss: 0.00481 +Epoch [2426/4000] Training [5/16] Loss: 0.00399 +Epoch [2426/4000] Training [6/16] Loss: 0.00498 +Epoch [2426/4000] Training [7/16] Loss: 0.00325 +Epoch [2426/4000] Training [8/16] Loss: 0.00377 +Epoch [2426/4000] Training [9/16] Loss: 0.00424 +Epoch [2426/4000] Training [10/16] Loss: 0.00533 +Epoch [2426/4000] Training [11/16] Loss: 0.00503 +Epoch [2426/4000] Training [12/16] Loss: 0.00447 +Epoch [2426/4000] Training [13/16] Loss: 0.00639 +Epoch [2426/4000] Training [14/16] Loss: 0.00441 +Epoch [2426/4000] Training [15/16] Loss: 0.00399 +Epoch [2426/4000] Training [16/16] Loss: 0.00472 +Epoch [2426/4000] Training metric {'Train/mean dice_metric': 0.99736088514328, 'Train/mean miou_metric': 0.9944397807121277, 'Train/mean f1': 0.9921501874923706, 'Train/mean precision': 0.9870761632919312, 'Train/mean recall': 0.9972766041755676, 'Train/mean hd95_metric': 0.9637972712516785} +Epoch [2426/4000] Validation [1/4] Loss: 0.28976 focal_loss 0.22643 dice_loss 0.06333 +Epoch [2426/4000] Validation [2/4] Loss: 0.59601 focal_loss 0.39466 dice_loss 0.20135 +Epoch [2426/4000] Validation [3/4] Loss: 0.32977 focal_loss 0.23931 dice_loss 0.09047 +Epoch [2426/4000] Validation [4/4] Loss: 0.36728 focal_loss 0.24341 dice_loss 0.12388 +Epoch [2426/4000] Validation metric {'Val/mean dice_metric': 0.9721639752388, 'Val/mean miou_metric': 0.9570762515068054, 'Val/mean f1': 0.9739335179328918, 'Val/mean precision': 0.9706785678863525, 'Val/mean recall': 0.977210521697998, 'Val/mean hd95_metric': 5.758450984954834} +Cheakpoint... +Epoch [2426/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721639752388, 'Val/mean miou_metric': 0.9570762515068054, 'Val/mean f1': 0.9739335179328918, 'Val/mean precision': 0.9706785678863525, 'Val/mean recall': 0.977210521697998, 'Val/mean hd95_metric': 5.758450984954834} +Epoch [2427/4000] Training [1/16] Loss: 0.00364 +Epoch [2427/4000] Training [2/16] Loss: 0.00455 +Epoch [2427/4000] Training [3/16] Loss: 0.00475 +Epoch [2427/4000] Training [4/16] Loss: 0.00395 +Epoch [2427/4000] Training [5/16] Loss: 0.00525 +Epoch [2427/4000] Training [6/16] Loss: 0.00908 +Epoch [2427/4000] Training [7/16] Loss: 0.00510 +Epoch [2427/4000] Training [8/16] Loss: 0.00388 +Epoch [2427/4000] Training [9/16] Loss: 0.00389 +Epoch [2427/4000] Training [10/16] Loss: 0.00459 +Epoch [2427/4000] Training [11/16] Loss: 0.00436 +Epoch [2427/4000] Training [12/16] Loss: 0.00379 +Epoch [2427/4000] Training [13/16] Loss: 0.00442 +Epoch [2427/4000] Training [14/16] Loss: 0.00274 +Epoch [2427/4000] Training [15/16] Loss: 0.00507 +Epoch [2427/4000] Training [16/16] Loss: 0.00339 +Epoch [2427/4000] Training metric {'Train/mean dice_metric': 0.9971185922622681, 'Train/mean miou_metric': 0.9939814805984497, 'Train/mean f1': 0.9923828840255737, 'Train/mean precision': 0.9877519011497498, 'Train/mean recall': 0.9970574378967285, 'Train/mean hd95_metric': 1.0236068964004517} +Epoch [2427/4000] Validation [1/4] Loss: 0.33747 focal_loss 0.26687 dice_loss 0.07060 +Epoch [2427/4000] Validation [2/4] Loss: 0.53690 focal_loss 0.38847 dice_loss 0.14843 +Epoch [2427/4000] Validation [3/4] Loss: 0.56613 focal_loss 0.45423 dice_loss 0.11189 +Epoch [2427/4000] Validation [4/4] Loss: 0.67159 focal_loss 0.51880 dice_loss 0.15279 +Epoch [2427/4000] Validation metric {'Val/mean dice_metric': 0.9721540212631226, 'Val/mean miou_metric': 0.9556371569633484, 'Val/mean f1': 0.9728422164916992, 'Val/mean precision': 0.9707785248756409, 'Val/mean recall': 0.9749146699905396, 'Val/mean hd95_metric': 5.879380226135254} +Cheakpoint... +Epoch [2427/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721540212631226, 'Val/mean miou_metric': 0.9556371569633484, 'Val/mean f1': 0.9728422164916992, 'Val/mean precision': 0.9707785248756409, 'Val/mean recall': 0.9749146699905396, 'Val/mean hd95_metric': 5.879380226135254} +Epoch [2428/4000] Training [1/16] Loss: 0.00418 +Epoch [2428/4000] Training [2/16] Loss: 0.00366 +Epoch [2428/4000] Training [3/16] Loss: 0.00400 +Epoch [2428/4000] Training [4/16] Loss: 0.00340 +Epoch [2428/4000] Training [5/16] Loss: 0.00467 +Epoch [2428/4000] Training [6/16] Loss: 0.00394 +Epoch [2428/4000] Training [7/16] Loss: 0.00480 +Epoch [2428/4000] Training [8/16] Loss: 0.00436 +Epoch [2428/4000] Training [9/16] Loss: 0.00441 +Epoch [2428/4000] Training [10/16] Loss: 0.00936 +Epoch [2428/4000] Training [11/16] Loss: 0.00549 +Epoch [2428/4000] Training [12/16] Loss: 0.00515 +Epoch [2428/4000] Training [13/16] Loss: 0.00440 +Epoch [2428/4000] Training [14/16] Loss: 0.00619 +Epoch [2428/4000] Training [15/16] Loss: 0.00376 +Epoch [2428/4000] Training [16/16] Loss: 0.00563 +Epoch [2428/4000] Training metric {'Train/mean dice_metric': 0.9969477653503418, 'Train/mean miou_metric': 0.9936550855636597, 'Train/mean f1': 0.9925454258918762, 'Train/mean precision': 0.9880366325378418, 'Train/mean recall': 0.9970955848693848, 'Train/mean hd95_metric': 0.9964736700057983} +Epoch [2428/4000] Validation [1/4] Loss: 0.32727 focal_loss 0.26407 dice_loss 0.06320 +Epoch [2428/4000] Validation [2/4] Loss: 0.45259 focal_loss 0.28336 dice_loss 0.16923 +Epoch [2428/4000] Validation [3/4] Loss: 0.42461 focal_loss 0.33377 dice_loss 0.09084 +Epoch [2428/4000] Validation [4/4] Loss: 0.27061 focal_loss 0.19250 dice_loss 0.07810 +Epoch [2428/4000] Validation metric {'Val/mean dice_metric': 0.9734989404678345, 'Val/mean miou_metric': 0.9576019048690796, 'Val/mean f1': 0.9747833013534546, 'Val/mean precision': 0.9714276194572449, 'Val/mean recall': 0.9781621098518372, 'Val/mean hd95_metric': 5.882772445678711} +Cheakpoint... +Epoch [2428/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734989404678345, 'Val/mean miou_metric': 0.9576019048690796, 'Val/mean f1': 0.9747833013534546, 'Val/mean precision': 0.9714276194572449, 'Val/mean recall': 0.9781621098518372, 'Val/mean hd95_metric': 5.882772445678711} +Epoch [2429/4000] Training [1/16] Loss: 0.00442 +Epoch [2429/4000] Training [2/16] Loss: 0.00409 +Epoch [2429/4000] Training [3/16] Loss: 0.00427 +Epoch [2429/4000] Training [4/16] Loss: 0.00353 +Epoch [2429/4000] Training [5/16] Loss: 0.00653 +Epoch [2429/4000] Training [6/16] Loss: 0.00466 +Epoch [2429/4000] Training [7/16] Loss: 0.00466 +Epoch [2429/4000] Training [8/16] Loss: 0.00411 +Epoch [2429/4000] Training [9/16] Loss: 0.00374 +Epoch [2429/4000] Training [10/16] Loss: 0.00495 +Epoch [2429/4000] Training [11/16] Loss: 0.00484 +Epoch [2429/4000] Training [12/16] Loss: 0.00361 +Epoch [2429/4000] Training [13/16] Loss: 0.00493 +Epoch [2429/4000] Training [14/16] Loss: 0.00546 +Epoch [2429/4000] Training [15/16] Loss: 0.00712 +Epoch [2429/4000] Training [16/16] Loss: 0.00533 +Epoch [2429/4000] Training metric {'Train/mean dice_metric': 0.9969743490219116, 'Train/mean miou_metric': 0.9936954975128174, 'Train/mean f1': 0.9924830794334412, 'Train/mean precision': 0.9879364967346191, 'Train/mean recall': 0.9970717430114746, 'Train/mean hd95_metric': 0.9660993814468384} +Epoch [2429/4000] Validation [1/4] Loss: 0.30550 focal_loss 0.23876 dice_loss 0.06674 +Epoch [2429/4000] Validation [2/4] Loss: 0.31301 focal_loss 0.20453 dice_loss 0.10848 +Epoch [2429/4000] Validation [3/4] Loss: 0.37902 focal_loss 0.29219 dice_loss 0.08684 +Epoch [2429/4000] Validation [4/4] Loss: 0.61348 focal_loss 0.48597 dice_loss 0.12751 +Epoch [2429/4000] Validation metric {'Val/mean dice_metric': 0.9729297757148743, 'Val/mean miou_metric': 0.9572485089302063, 'Val/mean f1': 0.9742961525917053, 'Val/mean precision': 0.9714910984039307, 'Val/mean recall': 0.9771174788475037, 'Val/mean hd95_metric': 5.6960344314575195} +Cheakpoint... +Epoch [2429/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729297757148743, 'Val/mean miou_metric': 0.9572485089302063, 'Val/mean f1': 0.9742961525917053, 'Val/mean precision': 0.9714910984039307, 'Val/mean recall': 0.9771174788475037, 'Val/mean hd95_metric': 5.6960344314575195} +Epoch [2430/4000] Training [1/16] Loss: 0.00406 +Epoch [2430/4000] Training [2/16] Loss: 0.00324 +Epoch [2430/4000] Training [3/16] Loss: 0.00346 +Epoch [2430/4000] Training [4/16] Loss: 0.00470 +Epoch [2430/4000] Training [5/16] Loss: 0.00345 +Epoch [2430/4000] Training [6/16] Loss: 0.00601 +Epoch [2430/4000] Training [7/16] Loss: 0.00639 +Epoch [2430/4000] Training [8/16] Loss: 0.00365 +Epoch [2430/4000] Training [9/16] Loss: 0.00518 +Epoch [2430/4000] Training [10/16] Loss: 0.00614 +Epoch [2430/4000] Training [11/16] Loss: 0.00496 +Epoch [2430/4000] Training [12/16] Loss: 0.00432 +Epoch [2430/4000] Training [13/16] Loss: 0.00472 +Epoch [2430/4000] Training [14/16] Loss: 0.00397 +Epoch [2430/4000] Training [15/16] Loss: 0.00399 +Epoch [2430/4000] Training [16/16] Loss: 0.00591 +Epoch [2430/4000] Training metric {'Train/mean dice_metric': 0.9970623850822449, 'Train/mean miou_metric': 0.9938784241676331, 'Train/mean f1': 0.9926401376724243, 'Train/mean precision': 0.9881844520568848, 'Train/mean recall': 0.9971362352371216, 'Train/mean hd95_metric': 0.9704512357711792} +Epoch [2430/4000] Validation [1/4] Loss: 0.31591 focal_loss 0.24927 dice_loss 0.06664 +Epoch [2430/4000] Validation [2/4] Loss: 0.32769 focal_loss 0.21577 dice_loss 0.11192 +Epoch [2430/4000] Validation [3/4] Loss: 0.41691 focal_loss 0.32331 dice_loss 0.09359 +Epoch [2430/4000] Validation [4/4] Loss: 0.30578 focal_loss 0.21300 dice_loss 0.09277 +Epoch [2430/4000] Validation metric {'Val/mean dice_metric': 0.9733784794807434, 'Val/mean miou_metric': 0.9580416679382324, 'Val/mean f1': 0.9747692346572876, 'Val/mean precision': 0.9714512825012207, 'Val/mean recall': 0.9781100749969482, 'Val/mean hd95_metric': 5.591159820556641} +Cheakpoint... +Epoch [2430/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733784794807434, 'Val/mean miou_metric': 0.9580416679382324, 'Val/mean f1': 0.9747692346572876, 'Val/mean precision': 0.9714512825012207, 'Val/mean recall': 0.9781100749969482, 'Val/mean hd95_metric': 5.591159820556641} +Epoch [2431/4000] Training [1/16] Loss: 0.00362 +Epoch [2431/4000] Training [2/16] Loss: 0.00600 +Epoch [2431/4000] Training [3/16] Loss: 0.00374 +Epoch [2431/4000] Training [4/16] Loss: 0.00386 +Epoch [2431/4000] Training [5/16] Loss: 0.00587 +Epoch [2431/4000] Training [6/16] Loss: 0.00472 +Epoch [2431/4000] Training [7/16] Loss: 0.00505 +Epoch [2431/4000] Training [8/16] Loss: 0.00584 +Epoch [2431/4000] Training [9/16] Loss: 0.00288 +Epoch [2431/4000] Training [10/16] Loss: 0.00333 +Epoch [2431/4000] Training [11/16] Loss: 0.00413 +Epoch [2431/4000] Training [12/16] Loss: 0.00725 +Epoch [2431/4000] Training [13/16] Loss: 0.00322 +Epoch [2431/4000] Training [14/16] Loss: 0.00490 +Epoch [2431/4000] Training [15/16] Loss: 0.00432 +Epoch [2431/4000] Training [16/16] Loss: 0.00502 +Epoch [2431/4000] Training metric {'Train/mean dice_metric': 0.9969249963760376, 'Train/mean miou_metric': 0.993605375289917, 'Train/mean f1': 0.9923886060714722, 'Train/mean precision': 0.9879530668258667, 'Train/mean recall': 0.9968641996383667, 'Train/mean hd95_metric': 0.9798669815063477} +Epoch [2431/4000] Validation [1/4] Loss: 0.40610 focal_loss 0.33331 dice_loss 0.07279 +Epoch [2431/4000] Validation [2/4] Loss: 0.59101 focal_loss 0.43669 dice_loss 0.15432 +Epoch [2431/4000] Validation [3/4] Loss: 0.35603 focal_loss 0.27220 dice_loss 0.08383 +Epoch [2431/4000] Validation [4/4] Loss: 0.34442 focal_loss 0.23459 dice_loss 0.10983 +Epoch [2431/4000] Validation metric {'Val/mean dice_metric': 0.9729471206665039, 'Val/mean miou_metric': 0.9571670293807983, 'Val/mean f1': 0.9740631580352783, 'Val/mean precision': 0.9704721570014954, 'Val/mean recall': 0.9776808619499207, 'Val/mean hd95_metric': 5.733869552612305} +Cheakpoint... +Epoch [2431/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729471206665039, 'Val/mean miou_metric': 0.9571670293807983, 'Val/mean f1': 0.9740631580352783, 'Val/mean precision': 0.9704721570014954, 'Val/mean recall': 0.9776808619499207, 'Val/mean hd95_metric': 5.733869552612305} +Epoch [2432/4000] Training [1/16] Loss: 0.00460 +Epoch [2432/4000] Training [2/16] Loss: 0.00389 +Epoch [2432/4000] Training [3/16] Loss: 0.00447 +Epoch [2432/4000] Training [4/16] Loss: 0.00465 +Epoch [2432/4000] Training [5/16] Loss: 0.00431 +Epoch [2432/4000] Training [6/16] Loss: 0.00505 +Epoch [2432/4000] Training [7/16] Loss: 0.00421 +Epoch [2432/4000] Training [8/16] Loss: 0.00634 +Epoch [2432/4000] Training [9/16] Loss: 0.00433 +Epoch [2432/4000] Training [10/16] Loss: 0.00563 +Epoch [2432/4000] Training [11/16] Loss: 0.00405 +Epoch [2432/4000] Training [12/16] Loss: 0.00477 +Epoch [2432/4000] Training [13/16] Loss: 0.00475 +Epoch [2432/4000] Training [14/16] Loss: 0.00532 +Epoch [2432/4000] Training [15/16] Loss: 0.00443 +Epoch [2432/4000] Training [16/16] Loss: 0.00436 +Epoch [2432/4000] Training metric {'Train/mean dice_metric': 0.9971100687980652, 'Train/mean miou_metric': 0.9939642548561096, 'Train/mean f1': 0.9925004839897156, 'Train/mean precision': 0.9879072904586792, 'Train/mean recall': 0.997136652469635, 'Train/mean hd95_metric': 0.9649425148963928} +Epoch [2432/4000] Validation [1/4] Loss: 0.35165 focal_loss 0.28062 dice_loss 0.07103 +Epoch [2432/4000] Validation [2/4] Loss: 0.63604 focal_loss 0.43843 dice_loss 0.19760 +Epoch [2432/4000] Validation [3/4] Loss: 0.20629 focal_loss 0.15254 dice_loss 0.05375 +Epoch [2432/4000] Validation [4/4] Loss: 0.27204 focal_loss 0.18863 dice_loss 0.08341 +Epoch [2432/4000] Validation metric {'Val/mean dice_metric': 0.9735181927680969, 'Val/mean miou_metric': 0.9586366415023804, 'Val/mean f1': 0.9747067093849182, 'Val/mean precision': 0.9716759920120239, 'Val/mean recall': 0.9777563214302063, 'Val/mean hd95_metric': 5.324568271636963} +Cheakpoint... +Epoch [2432/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735181927680969, 'Val/mean miou_metric': 0.9586366415023804, 'Val/mean f1': 0.9747067093849182, 'Val/mean precision': 0.9716759920120239, 'Val/mean recall': 0.9777563214302063, 'Val/mean hd95_metric': 5.324568271636963} +Epoch [2433/4000] Training [1/16] Loss: 0.00441 +Epoch [2433/4000] Training [2/16] Loss: 0.00381 +Epoch [2433/4000] Training [3/16] Loss: 0.00528 +Epoch [2433/4000] Training [4/16] Loss: 0.00416 +Epoch [2433/4000] Training [5/16] Loss: 0.00567 +Epoch [2433/4000] Training [6/16] Loss: 0.00594 +Epoch [2433/4000] Training [7/16] Loss: 0.00443 +Epoch [2433/4000] Training [8/16] Loss: 0.00543 +Epoch [2433/4000] Training [9/16] Loss: 0.00428 +Epoch [2433/4000] Training [10/16] Loss: 0.00385 +Epoch [2433/4000] Training [11/16] Loss: 0.00468 +Epoch [2433/4000] Training [12/16] Loss: 0.00354 +Epoch [2433/4000] Training [13/16] Loss: 0.00459 +Epoch [2433/4000] Training [14/16] Loss: 0.00403 +Epoch [2433/4000] Training [15/16] Loss: 0.00440 +Epoch [2433/4000] Training [16/16] Loss: 0.00483 +Epoch [2433/4000] Training metric {'Train/mean dice_metric': 0.9971693158149719, 'Train/mean miou_metric': 0.9940862655639648, 'Train/mean f1': 0.9926155209541321, 'Train/mean precision': 0.9881469011306763, 'Train/mean recall': 0.9971247315406799, 'Train/mean hd95_metric': 0.9502507448196411} +Epoch [2433/4000] Validation [1/4] Loss: 0.33311 focal_loss 0.26557 dice_loss 0.06754 +Epoch [2433/4000] Validation [2/4] Loss: 0.28946 focal_loss 0.19084 dice_loss 0.09863 +Epoch [2433/4000] Validation [3/4] Loss: 0.40381 focal_loss 0.31335 dice_loss 0.09046 +Epoch [2433/4000] Validation [4/4] Loss: 0.64457 focal_loss 0.51551 dice_loss 0.12905 +Epoch [2433/4000] Validation metric {'Val/mean dice_metric': 0.9742803573608398, 'Val/mean miou_metric': 0.9587098360061646, 'Val/mean f1': 0.974890947341919, 'Val/mean precision': 0.9723037481307983, 'Val/mean recall': 0.9774919748306274, 'Val/mean hd95_metric': 5.649241924285889} +Cheakpoint... +Epoch [2433/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742803573608398, 'Val/mean miou_metric': 0.9587098360061646, 'Val/mean f1': 0.974890947341919, 'Val/mean precision': 0.9723037481307983, 'Val/mean recall': 0.9774919748306274, 'Val/mean hd95_metric': 5.649241924285889} +Epoch [2434/4000] Training [1/16] Loss: 0.00527 +Epoch [2434/4000] Training [2/16] Loss: 0.00378 +Epoch [2434/4000] Training [3/16] Loss: 0.00469 +Epoch [2434/4000] Training [4/16] Loss: 0.00702 +Epoch [2434/4000] Training [5/16] Loss: 0.00656 +Epoch [2434/4000] Training [6/16] Loss: 0.00460 +Epoch [2434/4000] Training [7/16] Loss: 0.00421 +Epoch [2434/4000] Training [8/16] Loss: 0.00391 +Epoch [2434/4000] Training [9/16] Loss: 0.00460 +Epoch [2434/4000] Training [10/16] Loss: 0.00464 +Epoch [2434/4000] Training [11/16] Loss: 0.00571 +Epoch [2434/4000] Training [12/16] Loss: 0.00401 +Epoch [2434/4000] Training [13/16] Loss: 0.00484 +Epoch [2434/4000] Training [14/16] Loss: 0.00408 +Epoch [2434/4000] Training [15/16] Loss: 0.00336 +Epoch [2434/4000] Training [16/16] Loss: 0.00505 +Epoch [2434/4000] Training metric {'Train/mean dice_metric': 0.9970929622650146, 'Train/mean miou_metric': 0.9939218163490295, 'Train/mean f1': 0.9925163984298706, 'Train/mean precision': 0.9879012107849121, 'Train/mean recall': 0.9971749186515808, 'Train/mean hd95_metric': 0.9608951807022095} +Epoch [2434/4000] Validation [1/4] Loss: 0.34820 focal_loss 0.27839 dice_loss 0.06981 +Epoch [2434/4000] Validation [2/4] Loss: 0.30033 focal_loss 0.19882 dice_loss 0.10152 +Epoch [2434/4000] Validation [3/4] Loss: 0.21450 focal_loss 0.15081 dice_loss 0.06369 +Epoch [2434/4000] Validation [4/4] Loss: 0.21505 focal_loss 0.14158 dice_loss 0.07348 +Epoch [2434/4000] Validation metric {'Val/mean dice_metric': 0.9758499264717102, 'Val/mean miou_metric': 0.9607839584350586, 'Val/mean f1': 0.9755975008010864, 'Val/mean precision': 0.9714658260345459, 'Val/mean recall': 0.9797644019126892, 'Val/mean hd95_metric': 5.255505561828613} +Cheakpoint... +Epoch [2434/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758499264717102, 'Val/mean miou_metric': 0.9607839584350586, 'Val/mean f1': 0.9755975008010864, 'Val/mean precision': 0.9714658260345459, 'Val/mean recall': 0.9797644019126892, 'Val/mean hd95_metric': 5.255505561828613} +Epoch [2435/4000] Training [1/16] Loss: 0.00669 +Epoch [2435/4000] Training [2/16] Loss: 0.00457 +Epoch [2435/4000] Training [3/16] Loss: 0.00434 +Epoch [2435/4000] Training [4/16] Loss: 0.00326 +Epoch [2435/4000] Training [5/16] Loss: 0.00416 +Epoch [2435/4000] Training [6/16] Loss: 0.00457 +Epoch [2435/4000] Training [7/16] Loss: 0.00501 +Epoch [2435/4000] Training [8/16] Loss: 0.00484 +Epoch [2435/4000] Training [9/16] Loss: 0.00463 +Epoch [2435/4000] Training [10/16] Loss: 0.00417 +Epoch [2435/4000] Training [11/16] Loss: 0.00436 +Epoch [2435/4000] Training [12/16] Loss: 0.00584 +Epoch [2435/4000] Training [13/16] Loss: 0.00554 +Epoch [2435/4000] Training [14/16] Loss: 0.00392 +Epoch [2435/4000] Training [15/16] Loss: 0.00382 +Epoch [2435/4000] Training [16/16] Loss: 0.00348 +Epoch [2435/4000] Training metric {'Train/mean dice_metric': 0.997094452381134, 'Train/mean miou_metric': 0.9939212203025818, 'Train/mean f1': 0.9922611117362976, 'Train/mean precision': 0.9875002503395081, 'Train/mean recall': 0.9970681667327881, 'Train/mean hd95_metric': 0.9747902154922485} +Epoch [2435/4000] Validation [1/4] Loss: 0.31996 focal_loss 0.25387 dice_loss 0.06609 +Epoch [2435/4000] Validation [2/4] Loss: 0.29829 focal_loss 0.19591 dice_loss 0.10238 +Epoch [2435/4000] Validation [3/4] Loss: 0.40784 focal_loss 0.31827 dice_loss 0.08957 +Epoch [2435/4000] Validation [4/4] Loss: 0.64280 focal_loss 0.51778 dice_loss 0.12502 +Epoch [2435/4000] Validation metric {'Val/mean dice_metric': 0.9738729596138, 'Val/mean miou_metric': 0.9582967758178711, 'Val/mean f1': 0.974339485168457, 'Val/mean precision': 0.9710677862167358, 'Val/mean recall': 0.9776333570480347, 'Val/mean hd95_metric': 5.947523593902588} +Cheakpoint... +Epoch [2435/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738729596138, 'Val/mean miou_metric': 0.9582967758178711, 'Val/mean f1': 0.974339485168457, 'Val/mean precision': 0.9710677862167358, 'Val/mean recall': 0.9776333570480347, 'Val/mean hd95_metric': 5.947523593902588} +Epoch [2436/4000] Training [1/16] Loss: 0.00923 +Epoch [2436/4000] Training [2/16] Loss: 0.00436 +Epoch [2436/4000] Training [3/16] Loss: 0.00442 +Epoch [2436/4000] Training [4/16] Loss: 0.00371 +Epoch [2436/4000] Training [5/16] Loss: 0.00435 +Epoch [2436/4000] Training [6/16] Loss: 0.00504 +Epoch [2436/4000] Training [7/16] Loss: 0.00439 +Epoch [2436/4000] Training [8/16] Loss: 0.00531 +Epoch [2436/4000] Training [9/16] Loss: 0.00490 +Epoch [2436/4000] Training [10/16] Loss: 0.00443 +Epoch [2436/4000] Training [11/16] Loss: 0.00720 +Epoch [2436/4000] Training [12/16] Loss: 0.00588 +Epoch [2436/4000] Training [13/16] Loss: 0.00541 +Epoch [2436/4000] Training [14/16] Loss: 0.00449 +Epoch [2436/4000] Training [15/16] Loss: 0.00360 +Epoch [2436/4000] Training [16/16] Loss: 0.00346 +Epoch [2436/4000] Training metric {'Train/mean dice_metric': 0.996767520904541, 'Train/mean miou_metric': 0.9933096170425415, 'Train/mean f1': 0.9919913411140442, 'Train/mean precision': 0.9873284101486206, 'Train/mean recall': 0.9966984391212463, 'Train/mean hd95_metric': 1.0645891427993774} +Epoch [2436/4000] Validation [1/4] Loss: 0.31255 focal_loss 0.24720 dice_loss 0.06535 +Epoch [2436/4000] Validation [2/4] Loss: 0.31639 focal_loss 0.21200 dice_loss 0.10439 +Epoch [2436/4000] Validation [3/4] Loss: 0.37107 focal_loss 0.28169 dice_loss 0.08939 +Epoch [2436/4000] Validation [4/4] Loss: 0.62761 focal_loss 0.48468 dice_loss 0.14293 +Epoch [2436/4000] Validation metric {'Val/mean dice_metric': 0.9729675054550171, 'Val/mean miou_metric': 0.9567279815673828, 'Val/mean f1': 0.9747139811515808, 'Val/mean precision': 0.9704098701477051, 'Val/mean recall': 0.9790564775466919, 'Val/mean hd95_metric': 5.87600040435791} +Cheakpoint... +Epoch [2436/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729675054550171, 'Val/mean miou_metric': 0.9567279815673828, 'Val/mean f1': 0.9747139811515808, 'Val/mean precision': 0.9704098701477051, 'Val/mean recall': 0.9790564775466919, 'Val/mean hd95_metric': 5.87600040435791} +Epoch [2437/4000] Training [1/16] Loss: 0.00491 +Epoch [2437/4000] Training [2/16] Loss: 0.00350 +Epoch [2437/4000] Training [3/16] Loss: 0.00452 +Epoch [2437/4000] Training [4/16] Loss: 0.00643 +Epoch [2437/4000] Training [5/16] Loss: 0.00449 +Epoch [2437/4000] Training [6/16] Loss: 0.00542 +Epoch [2437/4000] Training [7/16] Loss: 0.00479 +Epoch [2437/4000] Training [8/16] Loss: 0.00405 +Epoch [2437/4000] Training [9/16] Loss: 0.00405 +Epoch [2437/4000] Training [10/16] Loss: 0.00617 +Epoch [2437/4000] Training [11/16] Loss: 0.00502 +Epoch [2437/4000] Training [12/16] Loss: 0.00373 +Epoch [2437/4000] Training [13/16] Loss: 0.00462 +Epoch [2437/4000] Training [14/16] Loss: 0.00475 +Epoch [2437/4000] Training [15/16] Loss: 0.00376 +Epoch [2437/4000] Training [16/16] Loss: 0.00547 +Epoch [2437/4000] Training metric {'Train/mean dice_metric': 0.9969557523727417, 'Train/mean miou_metric': 0.9936577677726746, 'Train/mean f1': 0.992309033870697, 'Train/mean precision': 0.987643837928772, 'Train/mean recall': 0.9970184564590454, 'Train/mean hd95_metric': 0.9744274020195007} +Epoch [2437/4000] Validation [1/4] Loss: 0.26974 focal_loss 0.21357 dice_loss 0.05616 +Epoch [2437/4000] Validation [2/4] Loss: 0.41252 focal_loss 0.28260 dice_loss 0.12992 +Epoch [2437/4000] Validation [3/4] Loss: 0.44039 focal_loss 0.34261 dice_loss 0.09779 +Epoch [2437/4000] Validation [4/4] Loss: 0.46837 focal_loss 0.33735 dice_loss 0.13102 +Epoch [2437/4000] Validation metric {'Val/mean dice_metric': 0.9732368588447571, 'Val/mean miou_metric': 0.9573214650154114, 'Val/mean f1': 0.9744152426719666, 'Val/mean precision': 0.9695456027984619, 'Val/mean recall': 0.9793339371681213, 'Val/mean hd95_metric': 5.644509315490723} +Cheakpoint... +Epoch [2437/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732368588447571, 'Val/mean miou_metric': 0.9573214650154114, 'Val/mean f1': 0.9744152426719666, 'Val/mean precision': 0.9695456027984619, 'Val/mean recall': 0.9793339371681213, 'Val/mean hd95_metric': 5.644509315490723} +Epoch [2438/4000] Training [1/16] Loss: 0.00486 +Epoch [2438/4000] Training [2/16] Loss: 0.00458 +Epoch [2438/4000] Training [3/16] Loss: 0.00357 +Epoch [2438/4000] Training [4/16] Loss: 0.00484 +Epoch [2438/4000] Training [5/16] Loss: 0.00450 +Epoch [2438/4000] Training [6/16] Loss: 0.00458 +Epoch [2438/4000] Training [7/16] Loss: 0.00731 +Epoch [2438/4000] Training [8/16] Loss: 0.00516 +Epoch [2438/4000] Training [9/16] Loss: 0.00475 +Epoch [2438/4000] Training [10/16] Loss: 0.00321 +Epoch [2438/4000] Training [11/16] Loss: 0.00503 +Epoch [2438/4000] Training [12/16] Loss: 0.00489 +Epoch [2438/4000] Training [13/16] Loss: 0.00466 +Epoch [2438/4000] Training [14/16] Loss: 0.00452 +Epoch [2438/4000] Training [15/16] Loss: 0.00439 +Epoch [2438/4000] Training [16/16] Loss: 0.00373 +Epoch [2438/4000] Training metric {'Train/mean dice_metric': 0.9971197843551636, 'Train/mean miou_metric': 0.9939887523651123, 'Train/mean f1': 0.9924915432929993, 'Train/mean precision': 0.9880080223083496, 'Train/mean recall': 0.9970158934593201, 'Train/mean hd95_metric': 0.9697256088256836} +Epoch [2438/4000] Validation [1/4] Loss: 0.27608 focal_loss 0.21849 dice_loss 0.05759 +Epoch [2438/4000] Validation [2/4] Loss: 0.30934 focal_loss 0.21024 dice_loss 0.09910 +Epoch [2438/4000] Validation [3/4] Loss: 0.44066 focal_loss 0.34665 dice_loss 0.09401 +Epoch [2438/4000] Validation [4/4] Loss: 0.29582 focal_loss 0.19509 dice_loss 0.10073 +Epoch [2438/4000] Validation metric {'Val/mean dice_metric': 0.9729625582695007, 'Val/mean miou_metric': 0.9576592445373535, 'Val/mean f1': 0.9748353958129883, 'Val/mean precision': 0.9711914658546448, 'Val/mean recall': 0.9785067439079285, 'Val/mean hd95_metric': 5.686106204986572} +Cheakpoint... +Epoch [2438/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729625582695007, 'Val/mean miou_metric': 0.9576592445373535, 'Val/mean f1': 0.9748353958129883, 'Val/mean precision': 0.9711914658546448, 'Val/mean recall': 0.9785067439079285, 'Val/mean hd95_metric': 5.686106204986572} +Epoch [2439/4000] Training [1/16] Loss: 0.00403 +Epoch [2439/4000] Training [2/16] Loss: 0.00446 +Epoch [2439/4000] Training [3/16] Loss: 0.00403 +Epoch [2439/4000] Training [4/16] Loss: 0.00489 +Epoch [2439/4000] Training [5/16] Loss: 0.00557 +Epoch [2439/4000] Training [6/16] Loss: 0.00501 +Epoch [2439/4000] Training [7/16] Loss: 0.00455 +Epoch [2439/4000] Training [8/16] Loss: 0.00381 +Epoch [2439/4000] Training [9/16] Loss: 0.00462 +Epoch [2439/4000] Training [10/16] Loss: 0.00443 +Epoch [2439/4000] Training [11/16] Loss: 0.00497 +Epoch [2439/4000] Training [12/16] Loss: 0.00382 +Epoch [2439/4000] Training [13/16] Loss: 0.00365 +Epoch [2439/4000] Training [14/16] Loss: 0.00454 +Epoch [2439/4000] Training [15/16] Loss: 0.00556 +Epoch [2439/4000] Training [16/16] Loss: 0.00558 +Epoch [2439/4000] Training metric {'Train/mean dice_metric': 0.9971327781677246, 'Train/mean miou_metric': 0.9939993619918823, 'Train/mean f1': 0.9925398826599121, 'Train/mean precision': 0.9879664182662964, 'Train/mean recall': 0.9971559047698975, 'Train/mean hd95_metric': 0.9739530086517334} +Epoch [2439/4000] Validation [1/4] Loss: 0.28007 focal_loss 0.22109 dice_loss 0.05898 +Epoch [2439/4000] Validation [2/4] Loss: 0.71807 focal_loss 0.52184 dice_loss 0.19623 +Epoch [2439/4000] Validation [3/4] Loss: 0.38021 focal_loss 0.28802 dice_loss 0.09218 +Epoch [2439/4000] Validation [4/4] Loss: 0.25570 focal_loss 0.17460 dice_loss 0.08109 +Epoch [2439/4000] Validation metric {'Val/mean dice_metric': 0.9730709195137024, 'Val/mean miou_metric': 0.9579429626464844, 'Val/mean f1': 0.9747323393821716, 'Val/mean precision': 0.970984935760498, 'Val/mean recall': 0.9785088896751404, 'Val/mean hd95_metric': 5.470143795013428} +Cheakpoint... +Epoch [2439/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730709195137024, 'Val/mean miou_metric': 0.9579429626464844, 'Val/mean f1': 0.9747323393821716, 'Val/mean precision': 0.970984935760498, 'Val/mean recall': 0.9785088896751404, 'Val/mean hd95_metric': 5.470143795013428} +Epoch [2440/4000] Training [1/16] Loss: 0.00431 +Epoch [2440/4000] Training [2/16] Loss: 0.00469 +Epoch [2440/4000] Training [3/16] Loss: 0.00376 +Epoch [2440/4000] Training [4/16] Loss: 0.00402 +Epoch [2440/4000] Training [5/16] Loss: 0.00437 +Epoch [2440/4000] Training [6/16] Loss: 0.00332 +Epoch [2440/4000] Training [7/16] Loss: 0.00592 +Epoch [2440/4000] Training [8/16] Loss: 0.00574 +Epoch [2440/4000] Training [9/16] Loss: 0.00623 +Epoch [2440/4000] Training [10/16] Loss: 0.00392 +Epoch [2440/4000] Training [11/16] Loss: 0.00445 +Epoch [2440/4000] Training [12/16] Loss: 0.00637 +Epoch [2440/4000] Training [13/16] Loss: 0.00478 +Epoch [2440/4000] Training [14/16] Loss: 0.00440 +Epoch [2440/4000] Training [15/16] Loss: 0.00606 +Epoch [2440/4000] Training [16/16] Loss: 0.00561 +Epoch [2440/4000] Training metric {'Train/mean dice_metric': 0.9969322681427002, 'Train/mean miou_metric': 0.9936171770095825, 'Train/mean f1': 0.9923720955848694, 'Train/mean precision': 0.9878606200218201, 'Train/mean recall': 0.9969249963760376, 'Train/mean hd95_metric': 0.9726777076721191} +Epoch [2440/4000] Validation [1/4] Loss: 0.28172 focal_loss 0.21935 dice_loss 0.06237 +Epoch [2440/4000] Validation [2/4] Loss: 0.33824 focal_loss 0.23036 dice_loss 0.10788 +Epoch [2440/4000] Validation [3/4] Loss: 0.35355 focal_loss 0.26337 dice_loss 0.09018 +Epoch [2440/4000] Validation [4/4] Loss: 0.49014 focal_loss 0.35720 dice_loss 0.13294 +Epoch [2440/4000] Validation metric {'Val/mean dice_metric': 0.9737470746040344, 'Val/mean miou_metric': 0.9579189419746399, 'Val/mean f1': 0.9755140542984009, 'Val/mean precision': 0.9725987315177917, 'Val/mean recall': 0.978446900844574, 'Val/mean hd95_metric': 5.5801591873168945} +Cheakpoint... +Epoch [2440/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737470746040344, 'Val/mean miou_metric': 0.9579189419746399, 'Val/mean f1': 0.9755140542984009, 'Val/mean precision': 0.9725987315177917, 'Val/mean recall': 0.978446900844574, 'Val/mean hd95_metric': 5.5801591873168945} +Epoch [2441/4000] Training [1/16] Loss: 0.00547 +Epoch [2441/4000] Training [2/16] Loss: 0.00414 +Epoch [2441/4000] Training [3/16] Loss: 0.00310 +Epoch [2441/4000] Training [4/16] Loss: 0.00522 +Epoch [2441/4000] Training [5/16] Loss: 0.00432 +Epoch [2441/4000] Training [6/16] Loss: 0.00333 +Epoch [2441/4000] Training [7/16] Loss: 0.00564 +Epoch [2441/4000] Training [8/16] Loss: 0.00496 +Epoch [2441/4000] Training [9/16] Loss: 0.00470 +Epoch [2441/4000] Training [10/16] Loss: 0.00365 +Epoch [2441/4000] Training [11/16] Loss: 0.00453 +Epoch [2441/4000] Training [12/16] Loss: 0.00421 +Epoch [2441/4000] Training [13/16] Loss: 0.00393 +Epoch [2441/4000] Training [14/16] Loss: 0.00350 +Epoch [2441/4000] Training [15/16] Loss: 0.00460 +Epoch [2441/4000] Training [16/16] Loss: 0.00422 +Epoch [2441/4000] Training metric {'Train/mean dice_metric': 0.9972681999206543, 'Train/mean miou_metric': 0.9942725896835327, 'Train/mean f1': 0.9925422072410583, 'Train/mean precision': 0.9879235029220581, 'Train/mean recall': 0.9972043037414551, 'Train/mean hd95_metric': 0.9541570544242859} +Epoch [2441/4000] Validation [1/4] Loss: 0.30979 focal_loss 0.24505 dice_loss 0.06473 +Epoch [2441/4000] Validation [2/4] Loss: 0.58672 focal_loss 0.42348 dice_loss 0.16324 +Epoch [2441/4000] Validation [3/4] Loss: 0.40273 focal_loss 0.30971 dice_loss 0.09302 +Epoch [2441/4000] Validation [4/4] Loss: 0.44897 focal_loss 0.31959 dice_loss 0.12938 +Epoch [2441/4000] Validation metric {'Val/mean dice_metric': 0.9705661535263062, 'Val/mean miou_metric': 0.9553365707397461, 'Val/mean f1': 0.9746537208557129, 'Val/mean precision': 0.9729806184768677, 'Val/mean recall': 0.9763325452804565, 'Val/mean hd95_metric': 5.574133396148682} +Cheakpoint... +Epoch [2441/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705661535263062, 'Val/mean miou_metric': 0.9553365707397461, 'Val/mean f1': 0.9746537208557129, 'Val/mean precision': 0.9729806184768677, 'Val/mean recall': 0.9763325452804565, 'Val/mean hd95_metric': 5.574133396148682} +Epoch [2442/4000] Training [1/16] Loss: 0.00475 +Epoch [2442/4000] Training [2/16] Loss: 0.00525 +Epoch [2442/4000] Training [3/16] Loss: 0.00499 +Epoch [2442/4000] Training [4/16] Loss: 0.00396 +Epoch [2442/4000] Training [5/16] Loss: 0.00323 +Epoch [2442/4000] Training [6/16] Loss: 0.00382 +Epoch [2442/4000] Training [7/16] Loss: 0.00394 +Epoch [2442/4000] Training [8/16] Loss: 0.00549 +Epoch [2442/4000] Training [9/16] Loss: 0.00542 +Epoch [2442/4000] Training [10/16] Loss: 0.00624 +Epoch [2442/4000] Training [11/16] Loss: 0.00411 +Epoch [2442/4000] Training [12/16] Loss: 0.00437 +Epoch [2442/4000] Training [13/16] Loss: 0.00458 +Epoch [2442/4000] Training [14/16] Loss: 0.00468 +Epoch [2442/4000] Training [15/16] Loss: 0.00478 +Epoch [2442/4000] Training [16/16] Loss: 0.00346 +Epoch [2442/4000] Training metric {'Train/mean dice_metric': 0.9971334934234619, 'Train/mean miou_metric': 0.9940003752708435, 'Train/mean f1': 0.9923382997512817, 'Train/mean precision': 0.9876373410224915, 'Train/mean recall': 0.9970842599868774, 'Train/mean hd95_metric': 0.9611802101135254} +Epoch [2442/4000] Validation [1/4] Loss: 0.30298 focal_loss 0.23671 dice_loss 0.06626 +Epoch [2442/4000] Validation [2/4] Loss: 0.96915 focal_loss 0.70556 dice_loss 0.26359 +Epoch [2442/4000] Validation [3/4] Loss: 0.41417 focal_loss 0.31744 dice_loss 0.09673 +Epoch [2442/4000] Validation [4/4] Loss: 0.57073 focal_loss 0.45218 dice_loss 0.11855 +Epoch [2442/4000] Validation metric {'Val/mean dice_metric': 0.9720619916915894, 'Val/mean miou_metric': 0.9567515254020691, 'Val/mean f1': 0.9737892150878906, 'Val/mean precision': 0.971875786781311, 'Val/mean recall': 0.9757100343704224, 'Val/mean hd95_metric': 5.7719011306762695} +Cheakpoint... +Epoch [2442/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720619916915894, 'Val/mean miou_metric': 0.9567515254020691, 'Val/mean f1': 0.9737892150878906, 'Val/mean precision': 0.971875786781311, 'Val/mean recall': 0.9757100343704224, 'Val/mean hd95_metric': 5.7719011306762695} +Epoch [2443/4000] Training [1/16] Loss: 0.00491 +Epoch [2443/4000] Training [2/16] Loss: 0.00478 +Epoch [2443/4000] Training [3/16] Loss: 0.00385 +Epoch [2443/4000] Training [4/16] Loss: 0.00360 +Epoch [2443/4000] Training [5/16] Loss: 0.00355 +Epoch [2443/4000] Training [6/16] Loss: 0.00473 +Epoch [2443/4000] Training [7/16] Loss: 0.00454 +Epoch [2443/4000] Training [8/16] Loss: 0.00546 +Epoch [2443/4000] Training [9/16] Loss: 0.00458 +Epoch [2443/4000] Training [10/16] Loss: 0.00472 +Epoch [2443/4000] Training [11/16] Loss: 0.00447 +Epoch [2443/4000] Training [12/16] Loss: 0.00747 +Epoch [2443/4000] Training [13/16] Loss: 0.00297 +Epoch [2443/4000] Training [14/16] Loss: 0.00439 +Epoch [2443/4000] Training [15/16] Loss: 0.00576 +Epoch [2443/4000] Training [16/16] Loss: 0.00381 +Epoch [2443/4000] Training metric {'Train/mean dice_metric': 0.9972153902053833, 'Train/mean miou_metric': 0.9941509366035461, 'Train/mean f1': 0.9920002222061157, 'Train/mean precision': 0.986871063709259, 'Train/mean recall': 0.9971829652786255, 'Train/mean hd95_metric': 0.9521340131759644} +Epoch [2443/4000] Validation [1/4] Loss: 0.30206 focal_loss 0.23925 dice_loss 0.06281 +Epoch [2443/4000] Validation [2/4] Loss: 0.28526 focal_loss 0.18291 dice_loss 0.10235 +Epoch [2443/4000] Validation [3/4] Loss: 0.44520 focal_loss 0.34750 dice_loss 0.09770 +Epoch [2443/4000] Validation [4/4] Loss: 0.39703 focal_loss 0.28989 dice_loss 0.10714 +Epoch [2443/4000] Validation metric {'Val/mean dice_metric': 0.9741191864013672, 'Val/mean miou_metric': 0.9589767456054688, 'Val/mean f1': 0.9744665622711182, 'Val/mean precision': 0.9704344868659973, 'Val/mean recall': 0.9785323143005371, 'Val/mean hd95_metric': 5.661136627197266} +Cheakpoint... +Epoch [2443/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741191864013672, 'Val/mean miou_metric': 0.9589767456054688, 'Val/mean f1': 0.9744665622711182, 'Val/mean precision': 0.9704344868659973, 'Val/mean recall': 0.9785323143005371, 'Val/mean hd95_metric': 5.661136627197266} +Epoch [2444/4000] Training [1/16] Loss: 0.00357 +Epoch [2444/4000] Training [2/16] Loss: 0.00313 +Epoch [2444/4000] Training [3/16] Loss: 0.00557 +Epoch [2444/4000] Training [4/16] Loss: 0.00442 +Epoch [2444/4000] Training [5/16] Loss: 0.00486 +Epoch [2444/4000] Training [6/16] Loss: 0.00400 +Epoch [2444/4000] Training [7/16] Loss: 0.00682 +Epoch [2444/4000] Training [8/16] Loss: 0.00356 +Epoch [2444/4000] Training [9/16] Loss: 0.00389 +Epoch [2444/4000] Training [10/16] Loss: 0.00452 +Epoch [2444/4000] Training [11/16] Loss: 0.00394 +Epoch [2444/4000] Training [12/16] Loss: 0.00376 +Epoch [2444/4000] Training [13/16] Loss: 0.00415 +Epoch [2444/4000] Training [14/16] Loss: 0.00382 +Epoch [2444/4000] Training [15/16] Loss: 0.00572 +Epoch [2444/4000] Training [16/16] Loss: 0.00414 +Epoch [2444/4000] Training metric {'Train/mean dice_metric': 0.9972820281982422, 'Train/mean miou_metric': 0.9943091869354248, 'Train/mean f1': 0.9927191734313965, 'Train/mean precision': 0.9882240891456604, 'Train/mean recall': 0.9972553849220276, 'Train/mean hd95_metric': 0.9639225602149963} +Epoch [2444/4000] Validation [1/4] Loss: 0.37596 focal_loss 0.30577 dice_loss 0.07019 +Epoch [2444/4000] Validation [2/4] Loss: 0.59253 focal_loss 0.42475 dice_loss 0.16778 +Epoch [2444/4000] Validation [3/4] Loss: 0.37896 focal_loss 0.28809 dice_loss 0.09087 +Epoch [2444/4000] Validation [4/4] Loss: 0.41984 focal_loss 0.30959 dice_loss 0.11025 +Epoch [2444/4000] Validation metric {'Val/mean dice_metric': 0.973166823387146, 'Val/mean miou_metric': 0.9578034281730652, 'Val/mean f1': 0.9746037721633911, 'Val/mean precision': 0.970953106880188, 'Val/mean recall': 0.9782819747924805, 'Val/mean hd95_metric': 5.483540058135986} +Cheakpoint... +Epoch [2444/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973166823387146, 'Val/mean miou_metric': 0.9578034281730652, 'Val/mean f1': 0.9746037721633911, 'Val/mean precision': 0.970953106880188, 'Val/mean recall': 0.9782819747924805, 'Val/mean hd95_metric': 5.483540058135986} +Epoch [2445/4000] Training [1/16] Loss: 0.00493 +Epoch [2445/4000] Training [2/16] Loss: 0.00413 +Epoch [2445/4000] Training [3/16] Loss: 0.00493 +Epoch [2445/4000] Training [4/16] Loss: 0.00550 +Epoch [2445/4000] Training [5/16] Loss: 0.00479 +Epoch [2445/4000] Training [6/16] Loss: 0.00429 +Epoch [2445/4000] Training [7/16] Loss: 0.00310 +Epoch [2445/4000] Training [8/16] Loss: 0.00395 +Epoch [2445/4000] Training [9/16] Loss: 0.00656 +Epoch [2445/4000] Training [10/16] Loss: 0.00466 +Epoch [2445/4000] Training [11/16] Loss: 0.00375 +Epoch [2445/4000] Training [12/16] Loss: 0.00359 +Epoch [2445/4000] Training [13/16] Loss: 0.00369 +Epoch [2445/4000] Training [14/16] Loss: 0.00402 +Epoch [2445/4000] Training [15/16] Loss: 0.00515 +Epoch [2445/4000] Training [16/16] Loss: 0.00595 +Epoch [2445/4000] Training metric {'Train/mean dice_metric': 0.9970133900642395, 'Train/mean miou_metric': 0.993778645992279, 'Train/mean f1': 0.9925462603569031, 'Train/mean precision': 0.9879366159439087, 'Train/mean recall': 0.9971991777420044, 'Train/mean hd95_metric': 0.9955732822418213} +Epoch [2445/4000] Validation [1/4] Loss: 0.27946 focal_loss 0.21745 dice_loss 0.06201 +Epoch [2445/4000] Validation [2/4] Loss: 0.30131 focal_loss 0.19596 dice_loss 0.10534 +Epoch [2445/4000] Validation [3/4] Loss: 0.46783 focal_loss 0.36679 dice_loss 0.10103 +Epoch [2445/4000] Validation [4/4] Loss: 0.36203 focal_loss 0.24882 dice_loss 0.11321 +Epoch [2445/4000] Validation metric {'Val/mean dice_metric': 0.9739646911621094, 'Val/mean miou_metric': 0.958480715751648, 'Val/mean f1': 0.9751358032226562, 'Val/mean precision': 0.9720709323883057, 'Val/mean recall': 0.9782202243804932, 'Val/mean hd95_metric': 5.257808208465576} +Cheakpoint... +Epoch [2445/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739646911621094, 'Val/mean miou_metric': 0.958480715751648, 'Val/mean f1': 0.9751358032226562, 'Val/mean precision': 0.9720709323883057, 'Val/mean recall': 0.9782202243804932, 'Val/mean hd95_metric': 5.257808208465576} +Epoch [2446/4000] Training [1/16] Loss: 0.00517 +Epoch [2446/4000] Training [2/16] Loss: 0.00351 +Epoch [2446/4000] Training [3/16] Loss: 0.00400 +Epoch [2446/4000] Training [4/16] Loss: 0.00434 +Epoch [2446/4000] Training [5/16] Loss: 0.00411 +Epoch [2446/4000] Training [6/16] Loss: 0.00531 +Epoch [2446/4000] Training [7/16] Loss: 0.00441 +Epoch [2446/4000] Training [8/16] Loss: 0.00388 +Epoch [2446/4000] Training [9/16] Loss: 0.00544 +Epoch [2446/4000] Training [10/16] Loss: 0.00425 +Epoch [2446/4000] Training [11/16] Loss: 0.00412 +Epoch [2446/4000] Training [12/16] Loss: 0.00415 +Epoch [2446/4000] Training [13/16] Loss: 0.00594 +Epoch [2446/4000] Training [14/16] Loss: 0.00554 +Epoch [2446/4000] Training [15/16] Loss: 0.00424 +Epoch [2446/4000] Training [16/16] Loss: 0.00520 +Epoch [2446/4000] Training metric {'Train/mean dice_metric': 0.996925950050354, 'Train/mean miou_metric': 0.9936025142669678, 'Train/mean f1': 0.9923802018165588, 'Train/mean precision': 0.9878248572349548, 'Train/mean recall': 0.996977686882019, 'Train/mean hd95_metric': 0.9833958148956299} +Epoch [2446/4000] Validation [1/4] Loss: 0.30050 focal_loss 0.23890 dice_loss 0.06160 +Epoch [2446/4000] Validation [2/4] Loss: 0.23990 focal_loss 0.14766 dice_loss 0.09224 +Epoch [2446/4000] Validation [3/4] Loss: 0.29965 focal_loss 0.21639 dice_loss 0.08326 +Epoch [2446/4000] Validation [4/4] Loss: 0.33197 focal_loss 0.23266 dice_loss 0.09932 +Epoch [2446/4000] Validation metric {'Val/mean dice_metric': 0.9749976992607117, 'Val/mean miou_metric': 0.959527850151062, 'Val/mean f1': 0.9760147333145142, 'Val/mean precision': 0.9734703302383423, 'Val/mean recall': 0.9785726070404053, 'Val/mean hd95_metric': 5.229715347290039} +Cheakpoint... +Epoch [2446/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749976992607117, 'Val/mean miou_metric': 0.959527850151062, 'Val/mean f1': 0.9760147333145142, 'Val/mean precision': 0.9734703302383423, 'Val/mean recall': 0.9785726070404053, 'Val/mean hd95_metric': 5.229715347290039} +Epoch [2447/4000] Training [1/16] Loss: 0.00570 +Epoch [2447/4000] Training [2/16] Loss: 0.00596 +Epoch [2447/4000] Training [3/16] Loss: 0.00407 +Epoch [2447/4000] Training [4/16] Loss: 0.00688 +Epoch [2447/4000] Training [5/16] Loss: 0.00499 +Epoch [2447/4000] Training [6/16] Loss: 0.00389 +Epoch [2447/4000] Training [7/16] Loss: 0.00554 +Epoch [2447/4000] Training [8/16] Loss: 0.00348 +Epoch [2447/4000] Training [9/16] Loss: 0.00429 +Epoch [2447/4000] Training [10/16] Loss: 0.00411 +Epoch [2447/4000] Training [11/16] Loss: 0.00515 +Epoch [2447/4000] Training [12/16] Loss: 0.00494 +Epoch [2447/4000] Training [13/16] Loss: 0.00456 +Epoch [2447/4000] Training [14/16] Loss: 0.00463 +Epoch [2447/4000] Training [15/16] Loss: 0.00545 +Epoch [2447/4000] Training [16/16] Loss: 0.00363 +Epoch [2447/4000] Training metric {'Train/mean dice_metric': 0.99693763256073, 'Train/mean miou_metric': 0.9936302304267883, 'Train/mean f1': 0.9924761652946472, 'Train/mean precision': 0.9879290461540222, 'Train/mean recall': 0.9970653057098389, 'Train/mean hd95_metric': 0.9752786159515381} +Epoch [2447/4000] Validation [1/4] Loss: 0.33641 focal_loss 0.26531 dice_loss 0.07110 +Epoch [2447/4000] Validation [2/4] Loss: 0.38376 focal_loss 0.22305 dice_loss 0.16071 +Epoch [2447/4000] Validation [3/4] Loss: 0.22165 focal_loss 0.16146 dice_loss 0.06019 +Epoch [2447/4000] Validation [4/4] Loss: 0.36340 focal_loss 0.24022 dice_loss 0.12319 +Epoch [2447/4000] Validation metric {'Val/mean dice_metric': 0.9736444354057312, 'Val/mean miou_metric': 0.9580936431884766, 'Val/mean f1': 0.9755107760429382, 'Val/mean precision': 0.9740931391716003, 'Val/mean recall': 0.9769325256347656, 'Val/mean hd95_metric': 5.380847930908203} +Cheakpoint... +Epoch [2447/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736444354057312, 'Val/mean miou_metric': 0.9580936431884766, 'Val/mean f1': 0.9755107760429382, 'Val/mean precision': 0.9740931391716003, 'Val/mean recall': 0.9769325256347656, 'Val/mean hd95_metric': 5.380847930908203} +Epoch [2448/4000] Training [1/16] Loss: 0.00551 +Epoch [2448/4000] Training [2/16] Loss: 0.00422 +Epoch [2448/4000] Training [3/16] Loss: 0.00673 +Epoch [2448/4000] Training [4/16] Loss: 0.00396 +Epoch [2448/4000] Training [5/16] Loss: 0.00536 +Epoch [2448/4000] Training [6/16] Loss: 0.00472 +Epoch [2448/4000] Training [7/16] Loss: 0.00561 +Epoch [2448/4000] Training [8/16] Loss: 0.00910 +Epoch [2448/4000] Training [9/16] Loss: 0.00420 +Epoch [2448/4000] Training [10/16] Loss: 0.00590 +Epoch [2448/4000] Training [11/16] Loss: 0.00506 +Epoch [2448/4000] Training [12/16] Loss: 0.00443 +Epoch [2448/4000] Training [13/16] Loss: 0.00454 +Epoch [2448/4000] Training [14/16] Loss: 0.00509 +Epoch [2448/4000] Training [15/16] Loss: 0.00383 +Epoch [2448/4000] Training [16/16] Loss: 0.00384 +Epoch [2448/4000] Training metric {'Train/mean dice_metric': 0.9967131018638611, 'Train/mean miou_metric': 0.9931642413139343, 'Train/mean f1': 0.9917378425598145, 'Train/mean precision': 0.9867650270462036, 'Train/mean recall': 0.9967610836029053, 'Train/mean hd95_metric': 1.0976594686508179} +Epoch [2448/4000] Validation [1/4] Loss: 0.29077 focal_loss 0.23163 dice_loss 0.05914 +Epoch [2448/4000] Validation [2/4] Loss: 0.30356 focal_loss 0.18629 dice_loss 0.11728 +Epoch [2448/4000] Validation [3/4] Loss: 0.35355 focal_loss 0.26411 dice_loss 0.08944 +Epoch [2448/4000] Validation [4/4] Loss: 0.39166 focal_loss 0.28114 dice_loss 0.11052 +Epoch [2448/4000] Validation metric {'Val/mean dice_metric': 0.9739378094673157, 'Val/mean miou_metric': 0.9577199220657349, 'Val/mean f1': 0.9746519923210144, 'Val/mean precision': 0.9715979695320129, 'Val/mean recall': 0.9777253866195679, 'Val/mean hd95_metric': 5.455809593200684} +Cheakpoint... +Epoch [2448/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739378094673157, 'Val/mean miou_metric': 0.9577199220657349, 'Val/mean f1': 0.9746519923210144, 'Val/mean precision': 0.9715979695320129, 'Val/mean recall': 0.9777253866195679, 'Val/mean hd95_metric': 5.455809593200684} +Epoch [2449/4000] Training [1/16] Loss: 0.00473 +Epoch [2449/4000] Training [2/16] Loss: 0.00425 +Epoch [2449/4000] Training [3/16] Loss: 0.00395 +Epoch [2449/4000] Training [4/16] Loss: 0.00698 +Epoch [2449/4000] Training [5/16] Loss: 0.00467 +Epoch [2449/4000] Training [6/16] Loss: 0.00812 +Epoch [2449/4000] Training [7/16] Loss: 0.00426 +Epoch [2449/4000] Training [8/16] Loss: 0.00556 +Epoch [2449/4000] Training [9/16] Loss: 0.00472 +Epoch [2449/4000] Training [10/16] Loss: 0.00429 +Epoch [2449/4000] Training [11/16] Loss: 0.00382 +Epoch [2449/4000] Training [12/16] Loss: 0.00465 +Epoch [2449/4000] Training [13/16] Loss: 0.00456 +Epoch [2449/4000] Training [14/16] Loss: 0.00456 +Epoch [2449/4000] Training [15/16] Loss: 0.00370 +Epoch [2449/4000] Training [16/16] Loss: 0.00494 +Epoch [2449/4000] Training metric {'Train/mean dice_metric': 0.9969983100891113, 'Train/mean miou_metric': 0.9937183856964111, 'Train/mean f1': 0.9921345114707947, 'Train/mean precision': 0.9872948527336121, 'Train/mean recall': 0.9970218539237976, 'Train/mean hd95_metric': 0.9929717183113098} +Epoch [2449/4000] Validation [1/4] Loss: 0.30861 focal_loss 0.24321 dice_loss 0.06541 +Epoch [2449/4000] Validation [2/4] Loss: 0.31321 focal_loss 0.19959 dice_loss 0.11362 +Epoch [2449/4000] Validation [3/4] Loss: 0.33459 focal_loss 0.24472 dice_loss 0.08988 +Epoch [2449/4000] Validation [4/4] Loss: 0.39827 focal_loss 0.27150 dice_loss 0.12677 +Epoch [2449/4000] Validation metric {'Val/mean dice_metric': 0.9727334976196289, 'Val/mean miou_metric': 0.9571945071220398, 'Val/mean f1': 0.9748111963272095, 'Val/mean precision': 0.9710612893104553, 'Val/mean recall': 0.9785901308059692, 'Val/mean hd95_metric': 6.1186933517456055} +Cheakpoint... +Epoch [2449/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727334976196289, 'Val/mean miou_metric': 0.9571945071220398, 'Val/mean f1': 0.9748111963272095, 'Val/mean precision': 0.9710612893104553, 'Val/mean recall': 0.9785901308059692, 'Val/mean hd95_metric': 6.1186933517456055} +Epoch [2450/4000] Training [1/16] Loss: 0.00490 +Epoch [2450/4000] Training [2/16] Loss: 0.00301 +Epoch [2450/4000] Training [3/16] Loss: 0.00491 +Epoch [2450/4000] Training [4/16] Loss: 0.00398 +Epoch [2450/4000] Training [5/16] Loss: 0.00556 +Epoch [2450/4000] Training [6/16] Loss: 0.00409 +Epoch [2450/4000] Training [7/16] Loss: 0.00527 +Epoch [2450/4000] Training [8/16] Loss: 0.00375 +Epoch [2450/4000] Training [9/16] Loss: 0.00423 +Epoch [2450/4000] Training [10/16] Loss: 0.00398 +Epoch [2450/4000] Training [11/16] Loss: 0.00335 +Epoch [2450/4000] Training [12/16] Loss: 0.00429 +Epoch [2450/4000] Training [13/16] Loss: 0.00456 +Epoch [2450/4000] Training [14/16] Loss: 0.00421 +Epoch [2450/4000] Training [15/16] Loss: 0.00404 +Epoch [2450/4000] Training [16/16] Loss: 0.00499 +Epoch [2450/4000] Training metric {'Train/mean dice_metric': 0.9970356822013855, 'Train/mean miou_metric': 0.9938383102416992, 'Train/mean f1': 0.9927008748054504, 'Train/mean precision': 0.9883039593696594, 'Train/mean recall': 0.9971370697021484, 'Train/mean hd95_metric': 0.9772346019744873} +Epoch [2450/4000] Validation [1/4] Loss: 0.41128 focal_loss 0.34217 dice_loss 0.06911 +Epoch [2450/4000] Validation [2/4] Loss: 0.55196 focal_loss 0.40174 dice_loss 0.15022 +Epoch [2450/4000] Validation [3/4] Loss: 0.37171 focal_loss 0.28258 dice_loss 0.08913 +Epoch [2450/4000] Validation [4/4] Loss: 0.24844 focal_loss 0.16563 dice_loss 0.08281 +Epoch [2450/4000] Validation metric {'Val/mean dice_metric': 0.973655104637146, 'Val/mean miou_metric': 0.9583126306533813, 'Val/mean f1': 0.9753024578094482, 'Val/mean precision': 0.9709389805793762, 'Val/mean recall': 0.9797051548957825, 'Val/mean hd95_metric': 5.5605363845825195} +Cheakpoint... +Epoch [2450/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973655104637146, 'Val/mean miou_metric': 0.9583126306533813, 'Val/mean f1': 0.9753024578094482, 'Val/mean precision': 0.9709389805793762, 'Val/mean recall': 0.9797051548957825, 'Val/mean hd95_metric': 5.5605363845825195} +Epoch [2451/4000] Training [1/16] Loss: 0.00321 +Epoch [2451/4000] Training [2/16] Loss: 0.00591 +Epoch [2451/4000] Training [3/16] Loss: 0.00472 +Epoch [2451/4000] Training [4/16] Loss: 0.00488 +Epoch [2451/4000] Training [5/16] Loss: 0.00467 +Epoch [2451/4000] Training [6/16] Loss: 0.00524 +Epoch [2451/4000] Training [7/16] Loss: 0.00579 +Epoch [2451/4000] Training [8/16] Loss: 0.00511 +Epoch [2451/4000] Training [9/16] Loss: 0.00356 +Epoch [2451/4000] Training [10/16] Loss: 0.00741 +Epoch [2451/4000] Training [11/16] Loss: 0.00380 +Epoch [2451/4000] Training [12/16] Loss: 0.00519 +Epoch [2451/4000] Training [13/16] Loss: 0.00467 +Epoch [2451/4000] Training [14/16] Loss: 0.00376 +Epoch [2451/4000] Training [15/16] Loss: 0.00504 +Epoch [2451/4000] Training [16/16] Loss: 0.00528 +Epoch [2451/4000] Training metric {'Train/mean dice_metric': 0.9969134330749512, 'Train/mean miou_metric': 0.9935657978057861, 'Train/mean f1': 0.992243766784668, 'Train/mean precision': 0.9875040054321289, 'Train/mean recall': 0.9970292448997498, 'Train/mean hd95_metric': 0.964661717414856} +Epoch [2451/4000] Validation [1/4] Loss: 0.27771 focal_loss 0.21804 dice_loss 0.05967 +Epoch [2451/4000] Validation [2/4] Loss: 0.28700 focal_loss 0.18569 dice_loss 0.10131 +Epoch [2451/4000] Validation [3/4] Loss: 0.35804 focal_loss 0.25775 dice_loss 0.10029 +Epoch [2451/4000] Validation [4/4] Loss: 0.37156 focal_loss 0.26061 dice_loss 0.11095 +Epoch [2451/4000] Validation metric {'Val/mean dice_metric': 0.9733633995056152, 'Val/mean miou_metric': 0.9578520059585571, 'Val/mean f1': 0.9753478169441223, 'Val/mean precision': 0.9723423719406128, 'Val/mean recall': 0.9783720374107361, 'Val/mean hd95_metric': 5.313775539398193} +Cheakpoint... +Epoch [2451/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733633995056152, 'Val/mean miou_metric': 0.9578520059585571, 'Val/mean f1': 0.9753478169441223, 'Val/mean precision': 0.9723423719406128, 'Val/mean recall': 0.9783720374107361, 'Val/mean hd95_metric': 5.313775539398193} +Epoch [2452/4000] Training [1/16] Loss: 0.00327 +Epoch [2452/4000] Training [2/16] Loss: 0.00526 +Epoch [2452/4000] Training [3/16] Loss: 0.00400 +Epoch [2452/4000] Training [4/16] Loss: 0.00376 +Epoch [2452/4000] Training [5/16] Loss: 0.00436 +Epoch [2452/4000] Training [6/16] Loss: 0.00440 +Epoch [2452/4000] Training [7/16] Loss: 0.00292 +Epoch [2452/4000] Training [8/16] Loss: 0.00595 +Epoch [2452/4000] Training [9/16] Loss: 0.00436 +Epoch [2452/4000] Training [10/16] Loss: 0.00576 +Epoch [2452/4000] Training [11/16] Loss: 0.00391 +Epoch [2452/4000] Training [12/16] Loss: 0.00656 +Epoch [2452/4000] Training [13/16] Loss: 0.00480 +Epoch [2452/4000] Training [14/16] Loss: 0.00437 +Epoch [2452/4000] Training [15/16] Loss: 0.00403 +Epoch [2452/4000] Training [16/16] Loss: 0.00575 +Epoch [2452/4000] Training metric {'Train/mean dice_metric': 0.9971137046813965, 'Train/mean miou_metric': 0.9939836263656616, 'Train/mean f1': 0.9925429224967957, 'Train/mean precision': 0.988008975982666, 'Train/mean recall': 0.9971186518669128, 'Train/mean hd95_metric': 0.9712642431259155} +Epoch [2452/4000] Validation [1/4] Loss: 0.55223 focal_loss 0.44564 dice_loss 0.10659 +Epoch [2452/4000] Validation [2/4] Loss: 0.57546 focal_loss 0.41989 dice_loss 0.15556 +Epoch [2452/4000] Validation [3/4] Loss: 0.42947 focal_loss 0.33352 dice_loss 0.09594 +Epoch [2452/4000] Validation [4/4] Loss: 0.30910 focal_loss 0.20741 dice_loss 0.10169 +Epoch [2452/4000] Validation metric {'Val/mean dice_metric': 0.9731300473213196, 'Val/mean miou_metric': 0.9568396806716919, 'Val/mean f1': 0.9744519591331482, 'Val/mean precision': 0.972732424736023, 'Val/mean recall': 0.9761775732040405, 'Val/mean hd95_metric': 5.677621364593506} +Cheakpoint... +Epoch [2452/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731300473213196, 'Val/mean miou_metric': 0.9568396806716919, 'Val/mean f1': 0.9744519591331482, 'Val/mean precision': 0.972732424736023, 'Val/mean recall': 0.9761775732040405, 'Val/mean hd95_metric': 5.677621364593506} +Epoch [2453/4000] Training [1/16] Loss: 0.00359 +Epoch [2453/4000] Training [2/16] Loss: 0.00359 +Epoch [2453/4000] Training [3/16] Loss: 0.00611 +Epoch [2453/4000] Training [4/16] Loss: 0.00371 +Epoch [2453/4000] Training [5/16] Loss: 0.00599 +Epoch [2453/4000] Training [6/16] Loss: 0.00410 +Epoch [2453/4000] Training [7/16] Loss: 0.00341 +Epoch [2453/4000] Training [8/16] Loss: 0.00385 +Epoch [2453/4000] Training [9/16] Loss: 0.00472 +Epoch [2453/4000] Training [10/16] Loss: 0.00405 +Epoch [2453/4000] Training [11/16] Loss: 0.00457 +Epoch [2453/4000] Training [12/16] Loss: 0.00367 +Epoch [2453/4000] Training [13/16] Loss: 0.00376 +Epoch [2453/4000] Training [14/16] Loss: 0.00420 +Epoch [2453/4000] Training [15/16] Loss: 0.00425 +Epoch [2453/4000] Training [16/16] Loss: 0.00322 +Epoch [2453/4000] Training metric {'Train/mean dice_metric': 0.9973593354225159, 'Train/mean miou_metric': 0.9944521188735962, 'Train/mean f1': 0.9926660656929016, 'Train/mean precision': 0.9880071878433228, 'Train/mean recall': 0.997369110584259, 'Train/mean hd95_metric': 0.9534105062484741} +Epoch [2453/4000] Validation [1/4] Loss: 0.28450 focal_loss 0.22437 dice_loss 0.06013 +Epoch [2453/4000] Validation [2/4] Loss: 0.26167 focal_loss 0.16348 dice_loss 0.09819 +Epoch [2453/4000] Validation [3/4] Loss: 0.36598 focal_loss 0.27548 dice_loss 0.09050 +Epoch [2453/4000] Validation [4/4] Loss: 0.26105 focal_loss 0.17794 dice_loss 0.08311 +Epoch [2453/4000] Validation metric {'Val/mean dice_metric': 0.9737035632133484, 'Val/mean miou_metric': 0.9584630727767944, 'Val/mean f1': 0.9757490158081055, 'Val/mean precision': 0.9727688431739807, 'Val/mean recall': 0.978747546672821, 'Val/mean hd95_metric': 5.897258281707764} +Cheakpoint... +Epoch [2453/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737035632133484, 'Val/mean miou_metric': 0.9584630727767944, 'Val/mean f1': 0.9757490158081055, 'Val/mean precision': 0.9727688431739807, 'Val/mean recall': 0.978747546672821, 'Val/mean hd95_metric': 5.897258281707764} +Epoch [2454/4000] Training [1/16] Loss: 0.00355 +Epoch [2454/4000] Training [2/16] Loss: 0.00383 +Epoch [2454/4000] Training [3/16] Loss: 0.00389 +Epoch [2454/4000] Training [4/16] Loss: 0.00331 +Epoch [2454/4000] Training [5/16] Loss: 0.00406 +Epoch [2454/4000] Training [6/16] Loss: 0.00410 +Epoch [2454/4000] Training [7/16] Loss: 0.00400 +Epoch [2454/4000] Training [8/16] Loss: 0.00453 +Epoch [2454/4000] Training [9/16] Loss: 0.00436 +Epoch [2454/4000] Training [10/16] Loss: 0.00429 +Epoch [2454/4000] Training [11/16] Loss: 0.00510 +Epoch [2454/4000] Training [12/16] Loss: 0.00458 +Epoch [2454/4000] Training [13/16] Loss: 0.00443 +Epoch [2454/4000] Training [14/16] Loss: 0.00403 +Epoch [2454/4000] Training [15/16] Loss: 0.00478 +Epoch [2454/4000] Training [16/16] Loss: 0.00370 +Epoch [2454/4000] Training metric {'Train/mean dice_metric': 0.9974006414413452, 'Train/mean miou_metric': 0.9945381879806519, 'Train/mean f1': 0.9927366971969604, 'Train/mean precision': 0.988195538520813, 'Train/mean recall': 0.9973199367523193, 'Train/mean hd95_metric': 0.9506136178970337} +Epoch [2454/4000] Validation [1/4] Loss: 0.31820 focal_loss 0.25536 dice_loss 0.06284 +Epoch [2454/4000] Validation [2/4] Loss: 0.31510 focal_loss 0.20994 dice_loss 0.10516 +Epoch [2454/4000] Validation [3/4] Loss: 0.29142 focal_loss 0.20225 dice_loss 0.08917 +Epoch [2454/4000] Validation [4/4] Loss: 0.21613 focal_loss 0.14408 dice_loss 0.07205 +Epoch [2454/4000] Validation metric {'Val/mean dice_metric': 0.9745725393295288, 'Val/mean miou_metric': 0.9597717523574829, 'Val/mean f1': 0.975841224193573, 'Val/mean precision': 0.9727755784988403, 'Val/mean recall': 0.9789263010025024, 'Val/mean hd95_metric': 5.550783157348633} +Cheakpoint... +Epoch [2454/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745725393295288, 'Val/mean miou_metric': 0.9597717523574829, 'Val/mean f1': 0.975841224193573, 'Val/mean precision': 0.9727755784988403, 'Val/mean recall': 0.9789263010025024, 'Val/mean hd95_metric': 5.550783157348633} +Epoch [2455/4000] Training [1/16] Loss: 0.00424 +Epoch [2455/4000] Training [2/16] Loss: 0.00437 +Epoch [2455/4000] Training [3/16] Loss: 0.00357 +Epoch [2455/4000] Training [4/16] Loss: 0.00446 +Epoch [2455/4000] Training [5/16] Loss: 0.00379 +Epoch [2455/4000] Training [6/16] Loss: 0.00537 +Epoch [2455/4000] Training [7/16] Loss: 0.00413 +Epoch [2455/4000] Training [8/16] Loss: 0.00481 +Epoch [2455/4000] Training [9/16] Loss: 0.00444 +Epoch [2455/4000] Training [10/16] Loss: 0.00308 +Epoch [2455/4000] Training [11/16] Loss: 0.00348 +Epoch [2455/4000] Training [12/16] Loss: 0.00432 +Epoch [2455/4000] Training [13/16] Loss: 0.00394 +Epoch [2455/4000] Training [14/16] Loss: 0.00568 +Epoch [2455/4000] Training [15/16] Loss: 0.00412 +Epoch [2455/4000] Training [16/16] Loss: 0.00356 +Epoch [2455/4000] Training metric {'Train/mean dice_metric': 0.9973152875900269, 'Train/mean miou_metric': 0.9943768978118896, 'Train/mean f1': 0.9927839636802673, 'Train/mean precision': 0.988304615020752, 'Train/mean recall': 0.9973041415214539, 'Train/mean hd95_metric': 1.1264129877090454} +Epoch [2455/4000] Validation [1/4] Loss: 0.29522 focal_loss 0.23292 dice_loss 0.06230 +Epoch [2455/4000] Validation [2/4] Loss: 0.29364 focal_loss 0.19182 dice_loss 0.10182 +Epoch [2455/4000] Validation [3/4] Loss: 0.40399 focal_loss 0.31118 dice_loss 0.09281 +Epoch [2455/4000] Validation [4/4] Loss: 0.22446 focal_loss 0.14573 dice_loss 0.07873 +Epoch [2455/4000] Validation metric {'Val/mean dice_metric': 0.9739614725112915, 'Val/mean miou_metric': 0.9584776163101196, 'Val/mean f1': 0.9751801490783691, 'Val/mean precision': 0.9721869230270386, 'Val/mean recall': 0.9781918525695801, 'Val/mean hd95_metric': 6.335127830505371} +Cheakpoint... +Epoch [2455/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739614725112915, 'Val/mean miou_metric': 0.9584776163101196, 'Val/mean f1': 0.9751801490783691, 'Val/mean precision': 0.9721869230270386, 'Val/mean recall': 0.9781918525695801, 'Val/mean hd95_metric': 6.335127830505371} +Epoch [2456/4000] Training [1/16] Loss: 0.00311 +Epoch [2456/4000] Training [2/16] Loss: 0.01716 +Epoch [2456/4000] Training [3/16] Loss: 0.00362 +Epoch [2456/4000] Training [4/16] Loss: 0.00547 +Epoch [2456/4000] Training [5/16] Loss: 0.00750 +Epoch [2456/4000] Training [6/16] Loss: 0.00521 +Epoch [2456/4000] Training [7/16] Loss: 0.00769 +Epoch [2456/4000] Training [8/16] Loss: 0.00382 +Epoch [2456/4000] Training [9/16] Loss: 0.00630 +Epoch [2456/4000] Training [10/16] Loss: 0.00404 +Epoch [2456/4000] Training [11/16] Loss: 0.00354 +Epoch [2456/4000] Training [12/16] Loss: 0.00437 +Epoch [2456/4000] Training [13/16] Loss: 0.00391 +Epoch [2456/4000] Training [14/16] Loss: 0.00452 +Epoch [2456/4000] Training [15/16] Loss: 0.00447 +Epoch [2456/4000] Training [16/16] Loss: 0.00417 +Epoch [2456/4000] Training metric {'Train/mean dice_metric': 0.996825098991394, 'Train/mean miou_metric': 0.9934245944023132, 'Train/mean f1': 0.9923379421234131, 'Train/mean precision': 0.9877513647079468, 'Train/mean recall': 0.9969672560691833, 'Train/mean hd95_metric': 1.0441336631774902} +Epoch [2456/4000] Validation [1/4] Loss: 0.30063 focal_loss 0.23870 dice_loss 0.06193 +Epoch [2456/4000] Validation [2/4] Loss: 0.30210 focal_loss 0.18628 dice_loss 0.11582 +Epoch [2456/4000] Validation [3/4] Loss: 0.26392 focal_loss 0.18358 dice_loss 0.08034 +Epoch [2456/4000] Validation [4/4] Loss: 0.24913 focal_loss 0.16999 dice_loss 0.07914 +Epoch [2456/4000] Validation metric {'Val/mean dice_metric': 0.9730445146560669, 'Val/mean miou_metric': 0.9578641057014465, 'Val/mean f1': 0.9750558733940125, 'Val/mean precision': 0.9718398451805115, 'Val/mean recall': 0.978293240070343, 'Val/mean hd95_metric': 6.071135997772217} +Cheakpoint... +Epoch [2456/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730445146560669, 'Val/mean miou_metric': 0.9578641057014465, 'Val/mean f1': 0.9750558733940125, 'Val/mean precision': 0.9718398451805115, 'Val/mean recall': 0.978293240070343, 'Val/mean hd95_metric': 6.071135997772217} +Epoch [2457/4000] Training [1/16] Loss: 0.00426 +Epoch [2457/4000] Training [2/16] Loss: 0.00361 +Epoch [2457/4000] Training [3/16] Loss: 0.00597 +Epoch [2457/4000] Training [4/16] Loss: 0.00316 +Epoch [2457/4000] Training [5/16] Loss: 0.00426 +Epoch [2457/4000] Training [6/16] Loss: 0.00455 +Epoch [2457/4000] Training [7/16] Loss: 0.00504 +Epoch [2457/4000] Training [8/16] Loss: 0.00393 +Epoch [2457/4000] Training [9/16] Loss: 0.00478 +Epoch [2457/4000] Training [10/16] Loss: 0.00536 +Epoch [2457/4000] Training [11/16] Loss: 0.00354 +Epoch [2457/4000] Training [12/16] Loss: 0.00341 +Epoch [2457/4000] Training [13/16] Loss: 0.00364 +Epoch [2457/4000] Training [14/16] Loss: 0.00348 +Epoch [2457/4000] Training [15/16] Loss: 0.00367 +Epoch [2457/4000] Training [16/16] Loss: 0.00299 +Epoch [2457/4000] Training metric {'Train/mean dice_metric': 0.9974441528320312, 'Train/mean miou_metric': 0.9946069717407227, 'Train/mean f1': 0.9925348162651062, 'Train/mean precision': 0.9878345727920532, 'Train/mean recall': 0.997279942035675, 'Train/mean hd95_metric': 0.9466403722763062} +Epoch [2457/4000] Validation [1/4] Loss: 0.30592 focal_loss 0.24057 dice_loss 0.06535 +Epoch [2457/4000] Validation [2/4] Loss: 0.30687 focal_loss 0.19434 dice_loss 0.11254 +Epoch [2457/4000] Validation [3/4] Loss: 0.36416 focal_loss 0.27570 dice_loss 0.08846 +Epoch [2457/4000] Validation [4/4] Loss: 0.23524 focal_loss 0.14923 dice_loss 0.08602 +Epoch [2457/4000] Validation metric {'Val/mean dice_metric': 0.9746778607368469, 'Val/mean miou_metric': 0.959119975566864, 'Val/mean f1': 0.9746063351631165, 'Val/mean precision': 0.9700498580932617, 'Val/mean recall': 0.9792057871818542, 'Val/mean hd95_metric': 5.650259971618652} +Cheakpoint... +Epoch [2457/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746778607368469, 'Val/mean miou_metric': 0.959119975566864, 'Val/mean f1': 0.9746063351631165, 'Val/mean precision': 0.9700498580932617, 'Val/mean recall': 0.9792057871818542, 'Val/mean hd95_metric': 5.650259971618652} +Epoch [2458/4000] Training [1/16] Loss: 0.00430 +Epoch [2458/4000] Training [2/16] Loss: 0.00391 +Epoch [2458/4000] Training [3/16] Loss: 0.00481 +Epoch [2458/4000] Training [4/16] Loss: 0.00377 +Epoch [2458/4000] Training [5/16] Loss: 0.00335 +Epoch [2458/4000] Training [6/16] Loss: 0.00371 +Epoch [2458/4000] Training [7/16] Loss: 0.00379 +Epoch [2458/4000] Training [8/16] Loss: 0.00573 +Epoch [2458/4000] Training [9/16] Loss: 0.00500 +Epoch [2458/4000] Training [10/16] Loss: 0.00479 +Epoch [2458/4000] Training [11/16] Loss: 0.00612 +Epoch [2458/4000] Training [12/16] Loss: 0.00471 +Epoch [2458/4000] Training [13/16] Loss: 0.00430 +Epoch [2458/4000] Training [14/16] Loss: 0.00426 +Epoch [2458/4000] Training [15/16] Loss: 0.00477 +Epoch [2458/4000] Training [16/16] Loss: 0.00474 +Epoch [2458/4000] Training metric {'Train/mean dice_metric': 0.997266411781311, 'Train/mean miou_metric': 0.9942430257797241, 'Train/mean f1': 0.9919050335884094, 'Train/mean precision': 0.9866846799850464, 'Train/mean recall': 0.9971808791160583, 'Train/mean hd95_metric': 0.9634621143341064} +Epoch [2458/4000] Validation [1/4] Loss: 0.27839 focal_loss 0.21889 dice_loss 0.05950 +Epoch [2458/4000] Validation [2/4] Loss: 0.34253 focal_loss 0.22339 dice_loss 0.11913 +Epoch [2458/4000] Validation [3/4] Loss: 0.45049 focal_loss 0.35612 dice_loss 0.09437 +Epoch [2458/4000] Validation [4/4] Loss: 0.24876 focal_loss 0.17085 dice_loss 0.07791 +Epoch [2458/4000] Validation metric {'Val/mean dice_metric': 0.9739497303962708, 'Val/mean miou_metric': 0.9586494565010071, 'Val/mean f1': 0.9739355444908142, 'Val/mean precision': 0.9688735008239746, 'Val/mean recall': 0.9790506958961487, 'Val/mean hd95_metric': 5.915230751037598} +Cheakpoint... +Epoch [2458/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739497303962708, 'Val/mean miou_metric': 0.9586494565010071, 'Val/mean f1': 0.9739355444908142, 'Val/mean precision': 0.9688735008239746, 'Val/mean recall': 0.9790506958961487, 'Val/mean hd95_metric': 5.915230751037598} +Epoch [2459/4000] Training [1/16] Loss: 0.00449 +Epoch [2459/4000] Training [2/16] Loss: 0.00532 +Epoch [2459/4000] Training [3/16] Loss: 0.00550 +Epoch [2459/4000] Training [4/16] Loss: 0.00434 +Epoch [2459/4000] Training [5/16] Loss: 0.00363 +Epoch [2459/4000] Training [6/16] Loss: 0.00502 +Epoch [2459/4000] Training [7/16] Loss: 0.00518 +Epoch [2459/4000] Training [8/16] Loss: 0.00443 +Epoch [2459/4000] Training [9/16] Loss: 0.00508 +Epoch [2459/4000] Training [10/16] Loss: 0.00451 +Epoch [2459/4000] Training [11/16] Loss: 0.00362 +Epoch [2459/4000] Training [12/16] Loss: 0.00474 +Epoch [2459/4000] Training [13/16] Loss: 0.00494 +Epoch [2459/4000] Training [14/16] Loss: 0.00376 +Epoch [2459/4000] Training [15/16] Loss: 0.00498 +Epoch [2459/4000] Training [16/16] Loss: 0.00419 +Epoch [2459/4000] Training metric {'Train/mean dice_metric': 0.9972487688064575, 'Train/mean miou_metric': 0.9942367076873779, 'Train/mean f1': 0.9926035404205322, 'Train/mean precision': 0.9880157709121704, 'Train/mean recall': 0.9972341656684875, 'Train/mean hd95_metric': 0.9436657428741455} +Epoch [2459/4000] Validation [1/4] Loss: 0.27302 focal_loss 0.21118 dice_loss 0.06184 +Epoch [2459/4000] Validation [2/4] Loss: 0.40631 focal_loss 0.24168 dice_loss 0.16463 +Epoch [2459/4000] Validation [3/4] Loss: 0.31592 focal_loss 0.22934 dice_loss 0.08658 +Epoch [2459/4000] Validation [4/4] Loss: 0.26309 focal_loss 0.18317 dice_loss 0.07991 +Epoch [2459/4000] Validation metric {'Val/mean dice_metric': 0.9731941223144531, 'Val/mean miou_metric': 0.9580144882202148, 'Val/mean f1': 0.9747211933135986, 'Val/mean precision': 0.9711722731590271, 'Val/mean recall': 0.9782962203025818, 'Val/mean hd95_metric': 5.7737016677856445} +Cheakpoint... +Epoch [2459/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731941223144531, 'Val/mean miou_metric': 0.9580144882202148, 'Val/mean f1': 0.9747211933135986, 'Val/mean precision': 0.9711722731590271, 'Val/mean recall': 0.9782962203025818, 'Val/mean hd95_metric': 5.7737016677856445} +Epoch [2460/4000] Training [1/16] Loss: 0.00390 +Epoch [2460/4000] Training [2/16] Loss: 0.00388 +Epoch [2460/4000] Training [3/16] Loss: 0.00396 +Epoch [2460/4000] Training [4/16] Loss: 0.00349 +Epoch [2460/4000] Training [5/16] Loss: 0.00338 +Epoch [2460/4000] Training [6/16] Loss: 0.00339 +Epoch [2460/4000] Training [7/16] Loss: 0.00407 +Epoch [2460/4000] Training [8/16] Loss: 0.00421 +Epoch [2460/4000] Training [9/16] Loss: 0.00468 +Epoch [2460/4000] Training [10/16] Loss: 0.00338 +Epoch [2460/4000] Training [11/16] Loss: 0.00475 +Epoch [2460/4000] Training [12/16] Loss: 0.00517 +Epoch [2460/4000] Training [13/16] Loss: 0.00558 +Epoch [2460/4000] Training [14/16] Loss: 0.00522 +Epoch [2460/4000] Training [15/16] Loss: 0.00359 +Epoch [2460/4000] Training [16/16] Loss: 0.00562 +Epoch [2460/4000] Training metric {'Train/mean dice_metric': 0.9972482919692993, 'Train/mean miou_metric': 0.9942189455032349, 'Train/mean f1': 0.9919525384902954, 'Train/mean precision': 0.9868487119674683, 'Train/mean recall': 0.9971094727516174, 'Train/mean hd95_metric': 0.9517711400985718} +Epoch [2460/4000] Validation [1/4] Loss: 0.25385 focal_loss 0.19699 dice_loss 0.05687 +Epoch [2460/4000] Validation [2/4] Loss: 0.67156 focal_loss 0.46286 dice_loss 0.20870 +Epoch [2460/4000] Validation [3/4] Loss: 0.31168 focal_loss 0.22403 dice_loss 0.08765 +Epoch [2460/4000] Validation [4/4] Loss: 0.28135 focal_loss 0.19573 dice_loss 0.08562 +Epoch [2460/4000] Validation metric {'Val/mean dice_metric': 0.9735719561576843, 'Val/mean miou_metric': 0.9582786560058594, 'Val/mean f1': 0.9746310710906982, 'Val/mean precision': 0.9711950421333313, 'Val/mean recall': 0.9780916571617126, 'Val/mean hd95_metric': 6.046195030212402} +Cheakpoint... +Epoch [2460/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735719561576843, 'Val/mean miou_metric': 0.9582786560058594, 'Val/mean f1': 0.9746310710906982, 'Val/mean precision': 0.9711950421333313, 'Val/mean recall': 0.9780916571617126, 'Val/mean hd95_metric': 6.046195030212402} +Epoch [2461/4000] Training [1/16] Loss: 0.00460 +Epoch [2461/4000] Training [2/16] Loss: 0.00460 +Epoch [2461/4000] Training [3/16] Loss: 0.00351 +Epoch [2461/4000] Training [4/16] Loss: 0.00341 +Epoch [2461/4000] Training [5/16] Loss: 0.00454 +Epoch [2461/4000] Training [6/16] Loss: 0.00357 +Epoch [2461/4000] Training [7/16] Loss: 0.00525 +Epoch [2461/4000] Training [8/16] Loss: 0.00338 +Epoch [2461/4000] Training [9/16] Loss: 0.00331 +Epoch [2461/4000] Training [10/16] Loss: 0.00482 +Epoch [2461/4000] Training [11/16] Loss: 0.00410 +Epoch [2461/4000] Training [12/16] Loss: 0.00715 +Epoch [2461/4000] Training [13/16] Loss: 0.00334 +Epoch [2461/4000] Training [14/16] Loss: 0.00322 +Epoch [2461/4000] Training [15/16] Loss: 0.00469 +Epoch [2461/4000] Training [16/16] Loss: 0.00521 +Epoch [2461/4000] Training metric {'Train/mean dice_metric': 0.9973833560943604, 'Train/mean miou_metric': 0.9945123195648193, 'Train/mean f1': 0.9927342534065247, 'Train/mean precision': 0.9881780743598938, 'Train/mean recall': 0.9973326921463013, 'Train/mean hd95_metric': 0.9506592750549316} +Epoch [2461/4000] Validation [1/4] Loss: 0.28627 focal_loss 0.22214 dice_loss 0.06413 +Epoch [2461/4000] Validation [2/4] Loss: 0.33447 focal_loss 0.21391 dice_loss 0.12056 +Epoch [2461/4000] Validation [3/4] Loss: 0.20842 focal_loss 0.15625 dice_loss 0.05217 +Epoch [2461/4000] Validation [4/4] Loss: 0.36257 focal_loss 0.25152 dice_loss 0.11105 +Epoch [2461/4000] Validation metric {'Val/mean dice_metric': 0.972999095916748, 'Val/mean miou_metric': 0.9580854177474976, 'Val/mean f1': 0.9746570587158203, 'Val/mean precision': 0.9723412990570068, 'Val/mean recall': 0.976983904838562, 'Val/mean hd95_metric': 5.888295650482178} +Cheakpoint... +Epoch [2461/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972999095916748, 'Val/mean miou_metric': 0.9580854177474976, 'Val/mean f1': 0.9746570587158203, 'Val/mean precision': 0.9723412990570068, 'Val/mean recall': 0.976983904838562, 'Val/mean hd95_metric': 5.888295650482178} +Epoch [2462/4000] Training [1/16] Loss: 0.00340 +Epoch [2462/4000] Training [2/16] Loss: 0.00408 +Epoch [2462/4000] Training [3/16] Loss: 0.00312 +Epoch [2462/4000] Training [4/16] Loss: 0.00471 +Epoch [2462/4000] Training [5/16] Loss: 0.00492 +Epoch [2462/4000] Training [6/16] Loss: 0.00544 +Epoch [2462/4000] Training [7/16] Loss: 0.00538 +Epoch [2462/4000] Training [8/16] Loss: 0.00665 +Epoch [2462/4000] Training [9/16] Loss: 0.00355 +Epoch [2462/4000] Training [10/16] Loss: 0.00397 +Epoch [2462/4000] Training [11/16] Loss: 0.00583 +Epoch [2462/4000] Training [12/16] Loss: 0.00420 +Epoch [2462/4000] Training [13/16] Loss: 0.00425 +Epoch [2462/4000] Training [14/16] Loss: 0.00388 +Epoch [2462/4000] Training [15/16] Loss: 0.00411 +Epoch [2462/4000] Training [16/16] Loss: 0.00386 +Epoch [2462/4000] Training metric {'Train/mean dice_metric': 0.997162401676178, 'Train/mean miou_metric': 0.9940474033355713, 'Train/mean f1': 0.9925155639648438, 'Train/mean precision': 0.9877991080284119, 'Train/mean recall': 0.9972773194313049, 'Train/mean hd95_metric': 0.9945745468139648} +Epoch [2462/4000] Validation [1/4] Loss: 0.37329 focal_loss 0.30369 dice_loss 0.06960 +Epoch [2462/4000] Validation [2/4] Loss: 0.65682 focal_loss 0.45768 dice_loss 0.19914 +Epoch [2462/4000] Validation [3/4] Loss: 0.44665 focal_loss 0.35144 dice_loss 0.09521 +Epoch [2462/4000] Validation [4/4] Loss: 0.27744 focal_loss 0.19066 dice_loss 0.08678 +Epoch [2462/4000] Validation metric {'Val/mean dice_metric': 0.9736398458480835, 'Val/mean miou_metric': 0.9582573175430298, 'Val/mean f1': 0.9746915102005005, 'Val/mean precision': 0.9720155000686646, 'Val/mean recall': 0.977382242679596, 'Val/mean hd95_metric': 5.77788782119751} +Cheakpoint... +Epoch [2462/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736398458480835, 'Val/mean miou_metric': 0.9582573175430298, 'Val/mean f1': 0.9746915102005005, 'Val/mean precision': 0.9720155000686646, 'Val/mean recall': 0.977382242679596, 'Val/mean hd95_metric': 5.77788782119751} +Epoch [2463/4000] Training [1/16] Loss: 0.00401 +Epoch [2463/4000] Training [2/16] Loss: 0.00424 +Epoch [2463/4000] Training [3/16] Loss: 0.00380 +Epoch [2463/4000] Training [4/16] Loss: 0.00431 +Epoch [2463/4000] Training [5/16] Loss: 0.00416 +Epoch [2463/4000] Training [6/16] Loss: 0.00511 +Epoch [2463/4000] Training [7/16] Loss: 0.00394 +Epoch [2463/4000] Training [8/16] Loss: 0.00453 +Epoch [2463/4000] Training [9/16] Loss: 0.00381 +Epoch [2463/4000] Training [10/16] Loss: 0.00322 +Epoch [2463/4000] Training [11/16] Loss: 0.00419 +Epoch [2463/4000] Training [12/16] Loss: 0.00402 +Epoch [2463/4000] Training [13/16] Loss: 0.00441 +Epoch [2463/4000] Training [14/16] Loss: 0.00658 +Epoch [2463/4000] Training [15/16] Loss: 0.00379 +Epoch [2463/4000] Training [16/16] Loss: 0.00452 +Epoch [2463/4000] Training metric {'Train/mean dice_metric': 0.9972913265228271, 'Train/mean miou_metric': 0.9943007230758667, 'Train/mean f1': 0.9921042323112488, 'Train/mean precision': 0.9871640801429749, 'Train/mean recall': 0.9970940351486206, 'Train/mean hd95_metric': 1.0152318477630615} +Epoch [2463/4000] Validation [1/4] Loss: 0.31052 focal_loss 0.24791 dice_loss 0.06261 +Epoch [2463/4000] Validation [2/4] Loss: 0.31817 focal_loss 0.20422 dice_loss 0.11394 +Epoch [2463/4000] Validation [3/4] Loss: 0.30081 focal_loss 0.21454 dice_loss 0.08627 +Epoch [2463/4000] Validation [4/4] Loss: 0.48298 focal_loss 0.35717 dice_loss 0.12581 +Epoch [2463/4000] Validation metric {'Val/mean dice_metric': 0.9734051823616028, 'Val/mean miou_metric': 0.9580039978027344, 'Val/mean f1': 0.97356778383255, 'Val/mean precision': 0.9702256321907043, 'Val/mean recall': 0.9769330024719238, 'Val/mean hd95_metric': 5.49051570892334} +Cheakpoint... +Epoch [2463/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734051823616028, 'Val/mean miou_metric': 0.9580039978027344, 'Val/mean f1': 0.97356778383255, 'Val/mean precision': 0.9702256321907043, 'Val/mean recall': 0.9769330024719238, 'Val/mean hd95_metric': 5.49051570892334} +Epoch [2464/4000] Training [1/16] Loss: 0.00423 +Epoch [2464/4000] Training [2/16] Loss: 0.00386 +Epoch [2464/4000] Training [3/16] Loss: 0.00390 +Epoch [2464/4000] Training [4/16] Loss: 0.00487 +Epoch [2464/4000] Training [5/16] Loss: 0.00381 +Epoch [2464/4000] Training [6/16] Loss: 0.00542 +Epoch [2464/4000] Training [7/16] Loss: 0.00446 +Epoch [2464/4000] Training [8/16] Loss: 0.00555 +Epoch [2464/4000] Training [9/16] Loss: 0.00419 +Epoch [2464/4000] Training [10/16] Loss: 0.00543 +Epoch [2464/4000] Training [11/16] Loss: 0.00359 +Epoch [2464/4000] Training [12/16] Loss: 0.00469 +Epoch [2464/4000] Training [13/16] Loss: 0.00533 +Epoch [2464/4000] Training [14/16] Loss: 0.00447 +Epoch [2464/4000] Training [15/16] Loss: 0.00328 +Epoch [2464/4000] Training [16/16] Loss: 0.00463 +Epoch [2464/4000] Training metric {'Train/mean dice_metric': 0.997438371181488, 'Train/mean miou_metric': 0.9945984482765198, 'Train/mean f1': 0.9922383427619934, 'Train/mean precision': 0.9871380925178528, 'Train/mean recall': 0.9973915815353394, 'Train/mean hd95_metric': 0.9478793144226074} +Epoch [2464/4000] Validation [1/4] Loss: 0.33117 focal_loss 0.26659 dice_loss 0.06458 +Epoch [2464/4000] Validation [2/4] Loss: 0.55972 focal_loss 0.41131 dice_loss 0.14841 +Epoch [2464/4000] Validation [3/4] Loss: 0.40064 focal_loss 0.30910 dice_loss 0.09154 +Epoch [2464/4000] Validation [4/4] Loss: 0.32103 focal_loss 0.22178 dice_loss 0.09925 +Epoch [2464/4000] Validation metric {'Val/mean dice_metric': 0.9744027853012085, 'Val/mean miou_metric': 0.9591339230537415, 'Val/mean f1': 0.9748206734657288, 'Val/mean precision': 0.9698440432548523, 'Val/mean recall': 0.9798486828804016, 'Val/mean hd95_metric': 5.866305828094482} +Cheakpoint... +Epoch [2464/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744027853012085, 'Val/mean miou_metric': 0.9591339230537415, 'Val/mean f1': 0.9748206734657288, 'Val/mean precision': 0.9698440432548523, 'Val/mean recall': 0.9798486828804016, 'Val/mean hd95_metric': 5.866305828094482} +Epoch [2465/4000] Training [1/16] Loss: 0.00358 +Epoch [2465/4000] Training [2/16] Loss: 0.00372 +Epoch [2465/4000] Training [3/16] Loss: 0.00392 +Epoch [2465/4000] Training [4/16] Loss: 0.00392 +Epoch [2465/4000] Training [5/16] Loss: 0.00369 +Epoch [2465/4000] Training [6/16] Loss: 0.00436 +Epoch [2465/4000] Training [7/16] Loss: 0.00321 +Epoch [2465/4000] Training [8/16] Loss: 0.00440 +Epoch [2465/4000] Training [9/16] Loss: 0.00409 +Epoch [2465/4000] Training [10/16] Loss: 0.00408 +Epoch [2465/4000] Training [11/16] Loss: 0.00440 +Epoch [2465/4000] Training [12/16] Loss: 0.00644 +Epoch [2465/4000] Training [13/16] Loss: 0.00371 +Epoch [2465/4000] Training [14/16] Loss: 0.00466 +Epoch [2465/4000] Training [15/16] Loss: 0.00487 +Epoch [2465/4000] Training [16/16] Loss: 0.00372 +Epoch [2465/4000] Training metric {'Train/mean dice_metric': 0.9974127411842346, 'Train/mean miou_metric': 0.9945659637451172, 'Train/mean f1': 0.992720901966095, 'Train/mean precision': 0.9880560040473938, 'Train/mean recall': 0.9974300265312195, 'Train/mean hd95_metric': 0.9407082200050354} +Epoch [2465/4000] Validation [1/4] Loss: 0.40509 focal_loss 0.33374 dice_loss 0.07135 +Epoch [2465/4000] Validation [2/4] Loss: 0.62136 focal_loss 0.43337 dice_loss 0.18799 +Epoch [2465/4000] Validation [3/4] Loss: 0.45152 focal_loss 0.35749 dice_loss 0.09403 +Epoch [2465/4000] Validation [4/4] Loss: 0.43889 focal_loss 0.29659 dice_loss 0.14230 +Epoch [2465/4000] Validation metric {'Val/mean dice_metric': 0.9739240407943726, 'Val/mean miou_metric': 0.9586623907089233, 'Val/mean f1': 0.9748290777206421, 'Val/mean precision': 0.9715935587882996, 'Val/mean recall': 0.9780861139297485, 'Val/mean hd95_metric': 5.6375322341918945} +Cheakpoint... +Epoch [2465/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739240407943726, 'Val/mean miou_metric': 0.9586623907089233, 'Val/mean f1': 0.9748290777206421, 'Val/mean precision': 0.9715935587882996, 'Val/mean recall': 0.9780861139297485, 'Val/mean hd95_metric': 5.6375322341918945} +Epoch [2466/4000] Training [1/16] Loss: 0.00492 +Epoch [2466/4000] Training [2/16] Loss: 0.00512 +Epoch [2466/4000] Training [3/16] Loss: 0.00327 +Epoch [2466/4000] Training [4/16] Loss: 0.00806 +Epoch [2466/4000] Training [5/16] Loss: 0.00492 +Epoch [2466/4000] Training [6/16] Loss: 0.00636 +Epoch [2466/4000] Training [7/16] Loss: 0.00382 +Epoch [2466/4000] Training [8/16] Loss: 0.00381 +Epoch [2466/4000] Training [9/16] Loss: 0.00467 +Epoch [2466/4000] Training [10/16] Loss: 0.00594 +Epoch [2466/4000] Training [11/16] Loss: 0.00468 +Epoch [2466/4000] Training [12/16] Loss: 0.00432 +Epoch [2466/4000] Training [13/16] Loss: 0.00695 +Epoch [2466/4000] Training [14/16] Loss: 0.00365 +Epoch [2466/4000] Training [15/16] Loss: 0.00393 +Epoch [2466/4000] Training [16/16] Loss: 0.00376 +Epoch [2466/4000] Training metric {'Train/mean dice_metric': 0.9970261454582214, 'Train/mean miou_metric': 0.9937934875488281, 'Train/mean f1': 0.9922075271606445, 'Train/mean precision': 0.9874346852302551, 'Train/mean recall': 0.997026801109314, 'Train/mean hd95_metric': 0.9722776412963867} +Epoch [2466/4000] Validation [1/4] Loss: 0.33834 focal_loss 0.27308 dice_loss 0.06526 +Epoch [2466/4000] Validation [2/4] Loss: 0.92234 focal_loss 0.69196 dice_loss 0.23038 +Epoch [2466/4000] Validation [3/4] Loss: 0.36334 focal_loss 0.26991 dice_loss 0.09343 +Epoch [2466/4000] Validation [4/4] Loss: 0.34943 focal_loss 0.24117 dice_loss 0.10826 +Epoch [2466/4000] Validation metric {'Val/mean dice_metric': 0.9732178449630737, 'Val/mean miou_metric': 0.9573078155517578, 'Val/mean f1': 0.9745535850524902, 'Val/mean precision': 0.9716631770133972, 'Val/mean recall': 0.9774612784385681, 'Val/mean hd95_metric': 5.958005905151367} +Cheakpoint... +Epoch [2466/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732178449630737, 'Val/mean miou_metric': 0.9573078155517578, 'Val/mean f1': 0.9745535850524902, 'Val/mean precision': 0.9716631770133972, 'Val/mean recall': 0.9774612784385681, 'Val/mean hd95_metric': 5.958005905151367} +Epoch [2467/4000] Training [1/16] Loss: 0.00646 +Epoch [2467/4000] Training [2/16] Loss: 0.00376 +Epoch [2467/4000] Training [3/16] Loss: 0.00359 +Epoch [2467/4000] Training [4/16] Loss: 0.00447 +Epoch [2467/4000] Training [5/16] Loss: 0.00637 +Epoch [2467/4000] Training [6/16] Loss: 0.00465 +Epoch [2467/4000] Training [7/16] Loss: 0.00299 +Epoch [2467/4000] Training [8/16] Loss: 0.00579 +Epoch [2467/4000] Training [9/16] Loss: 0.00857 +Epoch [2467/4000] Training [10/16] Loss: 0.00387 +Epoch [2467/4000] Training [11/16] Loss: 0.00379 +Epoch [2467/4000] Training [12/16] Loss: 0.00456 +Epoch [2467/4000] Training [13/16] Loss: 0.00469 +Epoch [2467/4000] Training [14/16] Loss: 0.00701 +Epoch [2467/4000] Training [15/16] Loss: 0.00392 +Epoch [2467/4000] Training [16/16] Loss: 0.00527 +Epoch [2467/4000] Training metric {'Train/mean dice_metric': 0.9968286752700806, 'Train/mean miou_metric': 0.9934194087982178, 'Train/mean f1': 0.992469310760498, 'Train/mean precision': 0.9879823923110962, 'Train/mean recall': 0.9969971179962158, 'Train/mean hd95_metric': 0.9854385852813721} +Epoch [2467/4000] Validation [1/4] Loss: 0.29918 focal_loss 0.23815 dice_loss 0.06102 +Epoch [2467/4000] Validation [2/4] Loss: 0.62311 focal_loss 0.45931 dice_loss 0.16379 +Epoch [2467/4000] Validation [3/4] Loss: 0.42152 focal_loss 0.32803 dice_loss 0.09349 +Epoch [2467/4000] Validation [4/4] Loss: 0.33636 focal_loss 0.23734 dice_loss 0.09902 +Epoch [2467/4000] Validation metric {'Val/mean dice_metric': 0.9735819101333618, 'Val/mean miou_metric': 0.9575783014297485, 'Val/mean f1': 0.9744948744773865, 'Val/mean precision': 0.9714382886886597, 'Val/mean recall': 0.9775707721710205, 'Val/mean hd95_metric': 5.785841464996338} +Cheakpoint... +Epoch [2467/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735819101333618, 'Val/mean miou_metric': 0.9575783014297485, 'Val/mean f1': 0.9744948744773865, 'Val/mean precision': 0.9714382886886597, 'Val/mean recall': 0.9775707721710205, 'Val/mean hd95_metric': 5.785841464996338} +Epoch [2468/4000] Training [1/16] Loss: 0.00517 +Epoch [2468/4000] Training [2/16] Loss: 0.00514 +Epoch [2468/4000] Training [3/16] Loss: 0.00383 +Epoch [2468/4000] Training [4/16] Loss: 0.00349 +Epoch [2468/4000] Training [5/16] Loss: 0.00535 +Epoch [2468/4000] Training [6/16] Loss: 0.00558 +Epoch [2468/4000] Training [7/16] Loss: 0.00443 +Epoch [2468/4000] Training [8/16] Loss: 0.00386 +Epoch [2468/4000] Training [9/16] Loss: 0.00389 +Epoch [2468/4000] Training [10/16] Loss: 0.00369 +Epoch [2468/4000] Training [11/16] Loss: 0.00350 +Epoch [2468/4000] Training [12/16] Loss: 0.00491 +Epoch [2468/4000] Training [13/16] Loss: 0.00337 +Epoch [2468/4000] Training [14/16] Loss: 0.00516 +Epoch [2468/4000] Training [15/16] Loss: 0.00302 +Epoch [2468/4000] Training [16/16] Loss: 0.00428 +Epoch [2468/4000] Training metric {'Train/mean dice_metric': 0.9972848296165466, 'Train/mean miou_metric': 0.9942933320999146, 'Train/mean f1': 0.9922969341278076, 'Train/mean precision': 0.9874402284622192, 'Train/mean recall': 0.997201681137085, 'Train/mean hd95_metric': 0.9509343504905701} +Epoch [2468/4000] Validation [1/4] Loss: 0.37986 focal_loss 0.31035 dice_loss 0.06951 +Epoch [2468/4000] Validation [2/4] Loss: 0.29095 focal_loss 0.18336 dice_loss 0.10759 +Epoch [2468/4000] Validation [3/4] Loss: 0.39241 focal_loss 0.29890 dice_loss 0.09351 +Epoch [2468/4000] Validation [4/4] Loss: 0.35781 focal_loss 0.24227 dice_loss 0.11554 +Epoch [2468/4000] Validation metric {'Val/mean dice_metric': 0.974737823009491, 'Val/mean miou_metric': 0.9590173959732056, 'Val/mean f1': 0.9747198224067688, 'Val/mean precision': 0.9715627431869507, 'Val/mean recall': 0.977897584438324, 'Val/mean hd95_metric': 5.870794773101807} +Cheakpoint... +Epoch [2468/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974737823009491, 'Val/mean miou_metric': 0.9590173959732056, 'Val/mean f1': 0.9747198224067688, 'Val/mean precision': 0.9715627431869507, 'Val/mean recall': 0.977897584438324, 'Val/mean hd95_metric': 5.870794773101807} +Epoch [2469/4000] Training [1/16] Loss: 0.00631 +Epoch [2469/4000] Training [2/16] Loss: 0.00435 +Epoch [2469/4000] Training [3/16] Loss: 0.00311 +Epoch [2469/4000] Training [4/16] Loss: 0.00559 +Epoch [2469/4000] Training [5/16] Loss: 0.00351 +Epoch [2469/4000] Training [6/16] Loss: 0.00375 +Epoch [2469/4000] Training [7/16] Loss: 0.00595 +Epoch [2469/4000] Training [8/16] Loss: 0.00454 +Epoch [2469/4000] Training [9/16] Loss: 0.00351 +Epoch [2469/4000] Training [10/16] Loss: 0.00332 +Epoch [2469/4000] Training [11/16] Loss: 0.00395 +Epoch [2469/4000] Training [12/16] Loss: 0.00392 +Epoch [2469/4000] Training [13/16] Loss: 0.00454 +Epoch [2469/4000] Training [14/16] Loss: 0.00454 +Epoch [2469/4000] Training [15/16] Loss: 0.00347 +Epoch [2469/4000] Training [16/16] Loss: 0.00553 +Epoch [2469/4000] Training metric {'Train/mean dice_metric': 0.9972807168960571, 'Train/mean miou_metric': 0.994271457195282, 'Train/mean f1': 0.9918966889381409, 'Train/mean precision': 0.9866389632225037, 'Train/mean recall': 0.9972108006477356, 'Train/mean hd95_metric': 0.9638948440551758} +Epoch [2469/4000] Validation [1/4] Loss: 0.28676 focal_loss 0.22633 dice_loss 0.06042 +Epoch [2469/4000] Validation [2/4] Loss: 0.26598 focal_loss 0.16689 dice_loss 0.09910 +Epoch [2469/4000] Validation [3/4] Loss: 0.40002 focal_loss 0.30746 dice_loss 0.09256 +Epoch [2469/4000] Validation [4/4] Loss: 0.58764 focal_loss 0.45339 dice_loss 0.13425 +Epoch [2469/4000] Validation metric {'Val/mean dice_metric': 0.9735574722290039, 'Val/mean miou_metric': 0.9581056833267212, 'Val/mean f1': 0.9735857844352722, 'Val/mean precision': 0.9693891406059265, 'Val/mean recall': 0.9778189659118652, 'Val/mean hd95_metric': 6.054276466369629} +Cheakpoint... +Epoch [2469/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735574722290039, 'Val/mean miou_metric': 0.9581056833267212, 'Val/mean f1': 0.9735857844352722, 'Val/mean precision': 0.9693891406059265, 'Val/mean recall': 0.9778189659118652, 'Val/mean hd95_metric': 6.054276466369629} +Epoch [2470/4000] Training [1/16] Loss: 0.00417 +Epoch [2470/4000] Training [2/16] Loss: 0.00508 +Epoch [2470/4000] Training [3/16] Loss: 0.00541 +Epoch [2470/4000] Training [4/16] Loss: 0.00446 +Epoch [2470/4000] Training [5/16] Loss: 0.00416 +Epoch [2470/4000] Training [6/16] Loss: 0.00505 +Epoch [2470/4000] Training [7/16] Loss: 0.00406 +Epoch [2470/4000] Training [8/16] Loss: 0.00446 +Epoch [2470/4000] Training [9/16] Loss: 0.00683 +Epoch [2470/4000] Training [10/16] Loss: 0.00497 +Epoch [2470/4000] Training [11/16] Loss: 0.00351 +Epoch [2470/4000] Training [12/16] Loss: 0.00780 +Epoch [2470/4000] Training [13/16] Loss: 0.00478 +Epoch [2470/4000] Training [14/16] Loss: 0.00407 +Epoch [2470/4000] Training [15/16] Loss: 0.00354 +Epoch [2470/4000] Training [16/16] Loss: 0.00433 +Epoch [2470/4000] Training metric {'Train/mean dice_metric': 0.9970371127128601, 'Train/mean miou_metric': 0.9938049912452698, 'Train/mean f1': 0.9923519492149353, 'Train/mean precision': 0.9876787066459656, 'Train/mean recall': 0.9970696568489075, 'Train/mean hd95_metric': 0.9714574217796326} +Epoch [2470/4000] Validation [1/4] Loss: 0.33598 focal_loss 0.27130 dice_loss 0.06468 +Epoch [2470/4000] Validation [2/4] Loss: 0.24761 focal_loss 0.16174 dice_loss 0.08587 +Epoch [2470/4000] Validation [3/4] Loss: 0.44374 focal_loss 0.34981 dice_loss 0.09392 +Epoch [2470/4000] Validation [4/4] Loss: 0.31659 focal_loss 0.21531 dice_loss 0.10128 +Epoch [2470/4000] Validation metric {'Val/mean dice_metric': 0.9758962392807007, 'Val/mean miou_metric': 0.9606391787528992, 'Val/mean f1': 0.9755687117576599, 'Val/mean precision': 0.9704257249832153, 'Val/mean recall': 0.9807665348052979, 'Val/mean hd95_metric': 5.4256768226623535} +Cheakpoint... +Epoch [2470/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758962392807007, 'Val/mean miou_metric': 0.9606391787528992, 'Val/mean f1': 0.9755687117576599, 'Val/mean precision': 0.9704257249832153, 'Val/mean recall': 0.9807665348052979, 'Val/mean hd95_metric': 5.4256768226623535} +Epoch [2471/4000] Training [1/16] Loss: 0.00360 +Epoch [2471/4000] Training [2/16] Loss: 0.00484 +Epoch [2471/4000] Training [3/16] Loss: 0.00378 +Epoch [2471/4000] Training [4/16] Loss: 0.00266 +Epoch [2471/4000] Training [5/16] Loss: 0.00363 +Epoch [2471/4000] Training [6/16] Loss: 0.00414 +Epoch [2471/4000] Training [7/16] Loss: 0.00414 +Epoch [2471/4000] Training [8/16] Loss: 0.00404 +Epoch [2471/4000] Training [9/16] Loss: 0.00479 +Epoch [2471/4000] Training [10/16] Loss: 0.00366 +Epoch [2471/4000] Training [11/16] Loss: 0.00463 +Epoch [2471/4000] Training [12/16] Loss: 0.00834 +Epoch [2471/4000] Training [13/16] Loss: 0.00482 +Epoch [2471/4000] Training [14/16] Loss: 0.00342 +Epoch [2471/4000] Training [15/16] Loss: 0.00499 +Epoch [2471/4000] Training [16/16] Loss: 0.00398 +Epoch [2471/4000] Training metric {'Train/mean dice_metric': 0.9973430633544922, 'Train/mean miou_metric': 0.994428277015686, 'Train/mean f1': 0.9927601218223572, 'Train/mean precision': 0.9882141947746277, 'Train/mean recall': 0.9973480701446533, 'Train/mean hd95_metric': 0.9623323678970337} +Epoch [2471/4000] Validation [1/4] Loss: 0.33377 focal_loss 0.27230 dice_loss 0.06147 +Epoch [2471/4000] Validation [2/4] Loss: 0.69423 focal_loss 0.50620 dice_loss 0.18803 +Epoch [2471/4000] Validation [3/4] Loss: 0.41000 focal_loss 0.30926 dice_loss 0.10074 +Epoch [2471/4000] Validation [4/4] Loss: 0.32347 focal_loss 0.22034 dice_loss 0.10314 +Epoch [2471/4000] Validation metric {'Val/mean dice_metric': 0.9759612083435059, 'Val/mean miou_metric': 0.9608672857284546, 'Val/mean f1': 0.9758986234664917, 'Val/mean precision': 0.9705180525779724, 'Val/mean recall': 0.9813392162322998, 'Val/mean hd95_metric': 5.356725692749023} +Cheakpoint... +Epoch [2471/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759612083435059, 'Val/mean miou_metric': 0.9608672857284546, 'Val/mean f1': 0.9758986234664917, 'Val/mean precision': 0.9705180525779724, 'Val/mean recall': 0.9813392162322998, 'Val/mean hd95_metric': 5.356725692749023} +Epoch [2472/4000] Training [1/16] Loss: 0.00391 +Epoch [2472/4000] Training [2/16] Loss: 0.00466 +Epoch [2472/4000] Training [3/16] Loss: 0.00295 +Epoch [2472/4000] Training [4/16] Loss: 0.00410 +Epoch [2472/4000] Training [5/16] Loss: 0.00508 +Epoch [2472/4000] Training [6/16] Loss: 0.00539 +Epoch [2472/4000] Training [7/16] Loss: 0.00358 +Epoch [2472/4000] Training [8/16] Loss: 0.00404 +Epoch [2472/4000] Training [9/16] Loss: 0.00553 +Epoch [2472/4000] Training [10/16] Loss: 0.00379 +Epoch [2472/4000] Training [11/16] Loss: 0.00455 +Epoch [2472/4000] Training [12/16] Loss: 0.00448 +Epoch [2472/4000] Training [13/16] Loss: 0.00493 +Epoch [2472/4000] Training [14/16] Loss: 0.00564 +Epoch [2472/4000] Training [15/16] Loss: 0.00433 +Epoch [2472/4000] Training [16/16] Loss: 0.00489 +Epoch [2472/4000] Training metric {'Train/mean dice_metric': 0.9972152709960938, 'Train/mean miou_metric': 0.9941752552986145, 'Train/mean f1': 0.992689311504364, 'Train/mean precision': 0.9881753921508789, 'Train/mean recall': 0.9972445964813232, 'Train/mean hd95_metric': 0.9509609937667847} +Epoch [2472/4000] Validation [1/4] Loss: 0.32900 focal_loss 0.26708 dice_loss 0.06191 +Epoch [2472/4000] Validation [2/4] Loss: 0.30563 focal_loss 0.20192 dice_loss 0.10371 +Epoch [2472/4000] Validation [3/4] Loss: 0.40475 focal_loss 0.31623 dice_loss 0.08851 +Epoch [2472/4000] Validation [4/4] Loss: 0.35019 focal_loss 0.23568 dice_loss 0.11451 +Epoch [2472/4000] Validation metric {'Val/mean dice_metric': 0.9747223854064941, 'Val/mean miou_metric': 0.959301769733429, 'Val/mean f1': 0.9749779105186462, 'Val/mean precision': 0.969696581363678, 'Val/mean recall': 0.9803169965744019, 'Val/mean hd95_metric': 5.6443986892700195} +Cheakpoint... +Epoch [2472/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747223854064941, 'Val/mean miou_metric': 0.959301769733429, 'Val/mean f1': 0.9749779105186462, 'Val/mean precision': 0.969696581363678, 'Val/mean recall': 0.9803169965744019, 'Val/mean hd95_metric': 5.6443986892700195} +Epoch [2473/4000] Training [1/16] Loss: 0.00297 +Epoch [2473/4000] Training [2/16] Loss: 0.00471 +Epoch [2473/4000] Training [3/16] Loss: 0.00474 +Epoch [2473/4000] Training [4/16] Loss: 0.00399 +Epoch [2473/4000] Training [5/16] Loss: 0.00486 +Epoch [2473/4000] Training [6/16] Loss: 0.01613 +Epoch [2473/4000] Training [7/16] Loss: 0.00570 +Epoch [2473/4000] Training [8/16] Loss: 0.00555 +Epoch [2473/4000] Training [9/16] Loss: 0.00445 +Epoch [2473/4000] Training [10/16] Loss: 0.00339 +Epoch [2473/4000] Training [11/16] Loss: 0.00431 +Epoch [2473/4000] Training [12/16] Loss: 0.00374 +Epoch [2473/4000] Training [13/16] Loss: 0.00471 +Epoch [2473/4000] Training [14/16] Loss: 0.00399 +Epoch [2473/4000] Training [15/16] Loss: 0.00417 +Epoch [2473/4000] Training [16/16] Loss: 0.00400 +Epoch [2473/4000] Training metric {'Train/mean dice_metric': 0.9970111846923828, 'Train/mean miou_metric': 0.9937623739242554, 'Train/mean f1': 0.9917054772377014, 'Train/mean precision': 0.9863887429237366, 'Train/mean recall': 0.9970798492431641, 'Train/mean hd95_metric': 1.008744478225708} +Epoch [2473/4000] Validation [1/4] Loss: 0.29733 focal_loss 0.23728 dice_loss 0.06005 +Epoch [2473/4000] Validation [2/4] Loss: 0.73543 focal_loss 0.53744 dice_loss 0.19798 +Epoch [2473/4000] Validation [3/4] Loss: 0.47106 focal_loss 0.36818 dice_loss 0.10288 +Epoch [2473/4000] Validation [4/4] Loss: 0.32881 focal_loss 0.23307 dice_loss 0.09574 +Epoch [2473/4000] Validation metric {'Val/mean dice_metric': 0.9726508855819702, 'Val/mean miou_metric': 0.9577630758285522, 'Val/mean f1': 0.9746745824813843, 'Val/mean precision': 0.9714720249176025, 'Val/mean recall': 0.9778981804847717, 'Val/mean hd95_metric': 5.81047248840332} +Cheakpoint... +Epoch [2473/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726508855819702, 'Val/mean miou_metric': 0.9577630758285522, 'Val/mean f1': 0.9746745824813843, 'Val/mean precision': 0.9714720249176025, 'Val/mean recall': 0.9778981804847717, 'Val/mean hd95_metric': 5.81047248840332} +Epoch [2474/4000] Training [1/16] Loss: 0.00341 +Epoch [2474/4000] Training [2/16] Loss: 0.00451 +Epoch [2474/4000] Training [3/16] Loss: 0.00291 +Epoch [2474/4000] Training [4/16] Loss: 0.00569 +Epoch [2474/4000] Training [5/16] Loss: 0.00345 +Epoch [2474/4000] Training [6/16] Loss: 0.00603 +Epoch [2474/4000] Training [7/16] Loss: 0.00411 +Epoch [2474/4000] Training [8/16] Loss: 0.00509 +Epoch [2474/4000] Training [9/16] Loss: 0.00452 +Epoch [2474/4000] Training [10/16] Loss: 0.00410 +Epoch [2474/4000] Training [11/16] Loss: 0.00638 +Epoch [2474/4000] Training [12/16] Loss: 0.00309 +Epoch [2474/4000] Training [13/16] Loss: 0.00378 +Epoch [2474/4000] Training [14/16] Loss: 0.00435 +Epoch [2474/4000] Training [15/16] Loss: 0.00484 +Epoch [2474/4000] Training [16/16] Loss: 0.00828 +Epoch [2474/4000] Training metric {'Train/mean dice_metric': 0.9969406127929688, 'Train/mean miou_metric': 0.9936530590057373, 'Train/mean f1': 0.9924176931381226, 'Train/mean precision': 0.9877514243125916, 'Train/mean recall': 0.9971283078193665, 'Train/mean hd95_metric': 1.0445361137390137} +Epoch [2474/4000] Validation [1/4] Loss: 0.40098 focal_loss 0.33288 dice_loss 0.06810 +Epoch [2474/4000] Validation [2/4] Loss: 0.63591 focal_loss 0.40823 dice_loss 0.22768 +Epoch [2474/4000] Validation [3/4] Loss: 0.44602 focal_loss 0.34960 dice_loss 0.09642 +Epoch [2474/4000] Validation [4/4] Loss: 0.36659 focal_loss 0.25647 dice_loss 0.11011 +Epoch [2474/4000] Validation metric {'Val/mean dice_metric': 0.9729498624801636, 'Val/mean miou_metric': 0.9576162099838257, 'Val/mean f1': 0.9749308228492737, 'Val/mean precision': 0.9719168543815613, 'Val/mean recall': 0.9779634475708008, 'Val/mean hd95_metric': 5.009870529174805} +Cheakpoint... +Epoch [2474/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729498624801636, 'Val/mean miou_metric': 0.9576162099838257, 'Val/mean f1': 0.9749308228492737, 'Val/mean precision': 0.9719168543815613, 'Val/mean recall': 0.9779634475708008, 'Val/mean hd95_metric': 5.009870529174805} +Epoch [2475/4000] Training [1/16] Loss: 0.00551 +Epoch [2475/4000] Training [2/16] Loss: 0.00439 +Epoch [2475/4000] Training [3/16] Loss: 0.00507 +Epoch [2475/4000] Training [4/16] Loss: 0.00503 +Epoch [2475/4000] Training [5/16] Loss: 0.00407 +Epoch [2475/4000] Training [6/16] Loss: 0.00661 +Epoch [2475/4000] Training [7/16] Loss: 0.00458 +Epoch [2475/4000] Training [8/16] Loss: 0.00413 +Epoch [2475/4000] Training [9/16] Loss: 0.00316 +Epoch [2475/4000] Training [10/16] Loss: 0.00491 +Epoch [2475/4000] Training [11/16] Loss: 0.00530 +Epoch [2475/4000] Training [12/16] Loss: 0.00462 +Epoch [2475/4000] Training [13/16] Loss: 0.00364 +Epoch [2475/4000] Training [14/16] Loss: 0.00349 +Epoch [2475/4000] Training [15/16] Loss: 0.00487 +Epoch [2475/4000] Training [16/16] Loss: 0.00450 +Epoch [2475/4000] Training metric {'Train/mean dice_metric': 0.9970784187316895, 'Train/mean miou_metric': 0.9939076900482178, 'Train/mean f1': 0.9926161766052246, 'Train/mean precision': 0.9881749749183655, 'Train/mean recall': 0.9970974326133728, 'Train/mean hd95_metric': 0.9722239971160889} +Epoch [2475/4000] Validation [1/4] Loss: 0.28109 focal_loss 0.22430 dice_loss 0.05679 +Epoch [2475/4000] Validation [2/4] Loss: 0.76991 focal_loss 0.56959 dice_loss 0.20031 +Epoch [2475/4000] Validation [3/4] Loss: 0.44690 focal_loss 0.34858 dice_loss 0.09832 +Epoch [2475/4000] Validation [4/4] Loss: 0.35217 focal_loss 0.24849 dice_loss 0.10368 +Epoch [2475/4000] Validation metric {'Val/mean dice_metric': 0.9709740877151489, 'Val/mean miou_metric': 0.9558649063110352, 'Val/mean f1': 0.9749706387519836, 'Val/mean precision': 0.973301887512207, 'Val/mean recall': 0.9766451120376587, 'Val/mean hd95_metric': 4.844589710235596} +Cheakpoint... +Epoch [2475/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709740877151489, 'Val/mean miou_metric': 0.9558649063110352, 'Val/mean f1': 0.9749706387519836, 'Val/mean precision': 0.973301887512207, 'Val/mean recall': 0.9766451120376587, 'Val/mean hd95_metric': 4.844589710235596} +Epoch [2476/4000] Training [1/16] Loss: 0.00398 +Epoch [2476/4000] Training [2/16] Loss: 0.00277 +Epoch [2476/4000] Training [3/16] Loss: 0.00422 +Epoch [2476/4000] Training [4/16] Loss: 0.00424 +Epoch [2476/4000] Training [5/16] Loss: 0.00521 +Epoch [2476/4000] Training [6/16] Loss: 0.00366 +Epoch [2476/4000] Training [7/16] Loss: 0.00740 +Epoch [2476/4000] Training [8/16] Loss: 0.00480 +Epoch [2476/4000] Training [9/16] Loss: 0.00697 +Epoch [2476/4000] Training [10/16] Loss: 0.00406 +Epoch [2476/4000] Training [11/16] Loss: 0.00583 +Epoch [2476/4000] Training [12/16] Loss: 0.00500 +Epoch [2476/4000] Training [13/16] Loss: 0.00365 +Epoch [2476/4000] Training [14/16] Loss: 0.00501 +Epoch [2476/4000] Training [15/16] Loss: 0.00343 +Epoch [2476/4000] Training [16/16] Loss: 0.00401 +Epoch [2476/4000] Training metric {'Train/mean dice_metric': 0.9971542954444885, 'Train/mean miou_metric': 0.9940333962440491, 'Train/mean f1': 0.9920070767402649, 'Train/mean precision': 0.986835241317749, 'Train/mean recall': 0.9972332715988159, 'Train/mean hd95_metric': 0.9771632552146912} +Epoch [2476/4000] Validation [1/4] Loss: 0.31923 focal_loss 0.25315 dice_loss 0.06608 +Epoch [2476/4000] Validation [2/4] Loss: 0.46185 focal_loss 0.31295 dice_loss 0.14889 +Epoch [2476/4000] Validation [3/4] Loss: 0.28991 focal_loss 0.20159 dice_loss 0.08832 +Epoch [2476/4000] Validation [4/4] Loss: 0.29337 focal_loss 0.20126 dice_loss 0.09211 +Epoch [2476/4000] Validation metric {'Val/mean dice_metric': 0.973924994468689, 'Val/mean miou_metric': 0.9583591222763062, 'Val/mean f1': 0.9755885004997253, 'Val/mean precision': 0.973656952381134, 'Val/mean recall': 0.9775277376174927, 'Val/mean hd95_metric': 4.654220104217529} +Cheakpoint... +Epoch [2476/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973924994468689, 'Val/mean miou_metric': 0.9583591222763062, 'Val/mean f1': 0.9755885004997253, 'Val/mean precision': 0.973656952381134, 'Val/mean recall': 0.9775277376174927, 'Val/mean hd95_metric': 4.654220104217529} +Epoch [2477/4000] Training [1/16] Loss: 0.00451 +Epoch [2477/4000] Training [2/16] Loss: 0.00345 +Epoch [2477/4000] Training [3/16] Loss: 0.00387 +Epoch [2477/4000] Training [4/16] Loss: 0.00480 +Epoch [2477/4000] Training [5/16] Loss: 0.00346 +Epoch [2477/4000] Training [6/16] Loss: 0.00566 +Epoch [2477/4000] Training [7/16] Loss: 0.00477 +Epoch [2477/4000] Training [8/16] Loss: 0.00426 +Epoch [2477/4000] Training [9/16] Loss: 0.00316 +Epoch [2477/4000] Training [10/16] Loss: 0.00303 +Epoch [2477/4000] Training [11/16] Loss: 0.00431 +Epoch [2477/4000] Training [12/16] Loss: 0.00554 +Epoch [2477/4000] Training [13/16] Loss: 0.00537 +Epoch [2477/4000] Training [14/16] Loss: 0.00438 +Epoch [2477/4000] Training [15/16] Loss: 0.00386 +Epoch [2477/4000] Training [16/16] Loss: 0.00295 +Epoch [2477/4000] Training metric {'Train/mean dice_metric': 0.9974178671836853, 'Train/mean miou_metric': 0.9945828318595886, 'Train/mean f1': 0.9927577972412109, 'Train/mean precision': 0.9882254600524902, 'Train/mean recall': 0.9973319172859192, 'Train/mean hd95_metric': 0.9339085817337036} +Epoch [2477/4000] Validation [1/4] Loss: 0.36076 focal_loss 0.28924 dice_loss 0.07152 +Epoch [2477/4000] Validation [2/4] Loss: 0.42861 focal_loss 0.29356 dice_loss 0.13505 +Epoch [2477/4000] Validation [3/4] Loss: 0.40806 focal_loss 0.32082 dice_loss 0.08724 +Epoch [2477/4000] Validation [4/4] Loss: 0.28834 focal_loss 0.20119 dice_loss 0.08715 +Epoch [2477/4000] Validation metric {'Val/mean dice_metric': 0.973637580871582, 'Val/mean miou_metric': 0.9585517048835754, 'Val/mean f1': 0.9752427339553833, 'Val/mean precision': 0.9736467003822327, 'Val/mean recall': 0.9768438935279846, 'Val/mean hd95_metric': 5.128387451171875} +Cheakpoint... +Epoch [2477/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973637580871582, 'Val/mean miou_metric': 0.9585517048835754, 'Val/mean f1': 0.9752427339553833, 'Val/mean precision': 0.9736467003822327, 'Val/mean recall': 0.9768438935279846, 'Val/mean hd95_metric': 5.128387451171875} +Epoch [2478/4000] Training [1/16] Loss: 0.00405 +Epoch [2478/4000] Training [2/16] Loss: 0.00422 +Epoch [2478/4000] Training [3/16] Loss: 0.00338 +Epoch [2478/4000] Training [4/16] Loss: 0.00462 +Epoch [2478/4000] Training [5/16] Loss: 0.00477 +Epoch [2478/4000] Training [6/16] Loss: 0.00428 +Epoch [2478/4000] Training [7/16] Loss: 0.00519 +Epoch [2478/4000] Training [8/16] Loss: 0.00345 +Epoch [2478/4000] Training [9/16] Loss: 0.00449 +Epoch [2478/4000] Training [10/16] Loss: 0.00401 +Epoch [2478/4000] Training [11/16] Loss: 0.00446 +Epoch [2478/4000] Training [12/16] Loss: 0.00505 +Epoch [2478/4000] Training [13/16] Loss: 0.00616 +Epoch [2478/4000] Training [14/16] Loss: 0.00375 +Epoch [2478/4000] Training [15/16] Loss: 0.00412 +Epoch [2478/4000] Training [16/16] Loss: 0.00414 +Epoch [2478/4000] Training metric {'Train/mean dice_metric': 0.9972518682479858, 'Train/mean miou_metric': 0.9942531585693359, 'Train/mean f1': 0.9926376938819885, 'Train/mean precision': 0.9881410002708435, 'Train/mean recall': 0.9971754550933838, 'Train/mean hd95_metric': 0.970145583152771} +Epoch [2478/4000] Validation [1/4] Loss: 0.33187 focal_loss 0.26630 dice_loss 0.06557 +Epoch [2478/4000] Validation [2/4] Loss: 0.45842 focal_loss 0.31163 dice_loss 0.14679 +Epoch [2478/4000] Validation [3/4] Loss: 0.31347 focal_loss 0.22332 dice_loss 0.09015 +Epoch [2478/4000] Validation [4/4] Loss: 0.25951 focal_loss 0.17952 dice_loss 0.07999 +Epoch [2478/4000] Validation metric {'Val/mean dice_metric': 0.9745357632637024, 'Val/mean miou_metric': 0.9594709277153015, 'Val/mean f1': 0.9762687087059021, 'Val/mean precision': 0.9732636213302612, 'Val/mean recall': 0.9792923927307129, 'Val/mean hd95_metric': 4.844258785247803} +Cheakpoint... +Epoch [2478/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745357632637024, 'Val/mean miou_metric': 0.9594709277153015, 'Val/mean f1': 0.9762687087059021, 'Val/mean precision': 0.9732636213302612, 'Val/mean recall': 0.9792923927307129, 'Val/mean hd95_metric': 4.844258785247803} +Epoch [2479/4000] Training [1/16] Loss: 0.00374 +Epoch [2479/4000] Training [2/16] Loss: 0.00587 +Epoch [2479/4000] Training [3/16] Loss: 0.00443 +Epoch [2479/4000] Training [4/16] Loss: 0.00472 +Epoch [2479/4000] Training [5/16] Loss: 0.00345 +Epoch [2479/4000] Training [6/16] Loss: 0.00463 +Epoch [2479/4000] Training [7/16] Loss: 0.00556 +Epoch [2479/4000] Training [8/16] Loss: 0.00532 +Epoch [2479/4000] Training [9/16] Loss: 0.00534 +Epoch [2479/4000] Training [10/16] Loss: 0.00408 +Epoch [2479/4000] Training [11/16] Loss: 0.00534 +Epoch [2479/4000] Training [12/16] Loss: 0.00487 +Epoch [2479/4000] Training [13/16] Loss: 0.00420 +Epoch [2479/4000] Training [14/16] Loss: 0.00502 +Epoch [2479/4000] Training [15/16] Loss: 0.00502 +Epoch [2479/4000] Training [16/16] Loss: 0.00377 +Epoch [2479/4000] Training metric {'Train/mean dice_metric': 0.9972092509269714, 'Train/mean miou_metric': 0.9941586256027222, 'Train/mean f1': 0.9925739765167236, 'Train/mean precision': 0.9879888892173767, 'Train/mean recall': 0.9972018599510193, 'Train/mean hd95_metric': 0.9574271440505981} +Epoch [2479/4000] Validation [1/4] Loss: 0.34931 focal_loss 0.28343 dice_loss 0.06587 +Epoch [2479/4000] Validation [2/4] Loss: 0.40522 focal_loss 0.27182 dice_loss 0.13340 +Epoch [2479/4000] Validation [3/4] Loss: 0.42748 focal_loss 0.33106 dice_loss 0.09642 +Epoch [2479/4000] Validation [4/4] Loss: 0.28967 focal_loss 0.19822 dice_loss 0.09145 +Epoch [2479/4000] Validation metric {'Val/mean dice_metric': 0.9727174639701843, 'Val/mean miou_metric': 0.9571617245674133, 'Val/mean f1': 0.975762128829956, 'Val/mean precision': 0.9737372994422913, 'Val/mean recall': 0.9777952432632446, 'Val/mean hd95_metric': 5.157118797302246} +Cheakpoint... +Epoch [2479/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727174639701843, 'Val/mean miou_metric': 0.9571617245674133, 'Val/mean f1': 0.975762128829956, 'Val/mean precision': 0.9737372994422913, 'Val/mean recall': 0.9777952432632446, 'Val/mean hd95_metric': 5.157118797302246} +Epoch [2480/4000] Training [1/16] Loss: 0.00434 +Epoch [2480/4000] Training [2/16] Loss: 0.00344 +Epoch [2480/4000] Training [3/16] Loss: 0.00472 +Epoch [2480/4000] Training [4/16] Loss: 0.00483 +Epoch [2480/4000] Training [5/16] Loss: 0.00502 +Epoch [2480/4000] Training [6/16] Loss: 0.00409 +Epoch [2480/4000] Training [7/16] Loss: 0.00368 +Epoch [2480/4000] Training [8/16] Loss: 0.00398 +Epoch [2480/4000] Training [9/16] Loss: 0.00343 +Epoch [2480/4000] Training [10/16] Loss: 0.00293 +Epoch [2480/4000] Training [11/16] Loss: 0.00363 +Epoch [2480/4000] Training [12/16] Loss: 0.00471 +Epoch [2480/4000] Training [13/16] Loss: 0.00288 +Epoch [2480/4000] Training [14/16] Loss: 0.00506 +Epoch [2480/4000] Training [15/16] Loss: 0.00489 +Epoch [2480/4000] Training [16/16] Loss: 0.00421 +Epoch [2480/4000] Training metric {'Train/mean dice_metric': 0.9974137544631958, 'Train/mean miou_metric': 0.9945712089538574, 'Train/mean f1': 0.9927549958229065, 'Train/mean precision': 0.988201379776001, 'Train/mean recall': 0.9973506331443787, 'Train/mean hd95_metric': 0.9522738456726074} +Epoch [2480/4000] Validation [1/4] Loss: 0.31070 focal_loss 0.24492 dice_loss 0.06578 +Epoch [2480/4000] Validation [2/4] Loss: 0.43568 focal_loss 0.29281 dice_loss 0.14287 +Epoch [2480/4000] Validation [3/4] Loss: 0.44825 focal_loss 0.35408 dice_loss 0.09417 +Epoch [2480/4000] Validation [4/4] Loss: 0.27851 focal_loss 0.19532 dice_loss 0.08319 +Epoch [2480/4000] Validation metric {'Val/mean dice_metric': 0.9733600616455078, 'Val/mean miou_metric': 0.958104133605957, 'Val/mean f1': 0.9755435585975647, 'Val/mean precision': 0.9736596941947937, 'Val/mean recall': 0.9774348735809326, 'Val/mean hd95_metric': 4.967642307281494} +Cheakpoint... +Epoch [2480/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733600616455078, 'Val/mean miou_metric': 0.958104133605957, 'Val/mean f1': 0.9755435585975647, 'Val/mean precision': 0.9736596941947937, 'Val/mean recall': 0.9774348735809326, 'Val/mean hd95_metric': 4.967642307281494} +Epoch [2481/4000] Training [1/16] Loss: 0.00644 +Epoch [2481/4000] Training [2/16] Loss: 0.00422 +Epoch [2481/4000] Training [3/16] Loss: 0.00397 +Epoch [2481/4000] Training [4/16] Loss: 0.00446 +Epoch [2481/4000] Training [5/16] Loss: 0.00540 +Epoch [2481/4000] Training [6/16] Loss: 0.00381 +Epoch [2481/4000] Training [7/16] Loss: 0.00487 +Epoch [2481/4000] Training [8/16] Loss: 0.00465 +Epoch [2481/4000] Training [9/16] Loss: 0.00390 +Epoch [2481/4000] Training [10/16] Loss: 0.00339 +Epoch [2481/4000] Training [11/16] Loss: 0.00374 +Epoch [2481/4000] Training [12/16] Loss: 0.00596 +Epoch [2481/4000] Training [13/16] Loss: 0.00445 +Epoch [2481/4000] Training [14/16] Loss: 0.00461 +Epoch [2481/4000] Training [15/16] Loss: 0.00447 +Epoch [2481/4000] Training [16/16] Loss: 0.00380 +Epoch [2481/4000] Training metric {'Train/mean dice_metric': 0.9971584677696228, 'Train/mean miou_metric': 0.9940599799156189, 'Train/mean f1': 0.9925936460494995, 'Train/mean precision': 0.9880011677742004, 'Train/mean recall': 0.9972290396690369, 'Train/mean hd95_metric': 0.9538365602493286} +Epoch [2481/4000] Validation [1/4] Loss: 0.37903 focal_loss 0.31324 dice_loss 0.06579 +Epoch [2481/4000] Validation [2/4] Loss: 0.40164 focal_loss 0.26619 dice_loss 0.13545 +Epoch [2481/4000] Validation [3/4] Loss: 0.43447 focal_loss 0.34257 dice_loss 0.09190 +Epoch [2481/4000] Validation [4/4] Loss: 0.31431 focal_loss 0.23078 dice_loss 0.08353 +Epoch [2481/4000] Validation metric {'Val/mean dice_metric': 0.9740198254585266, 'Val/mean miou_metric': 0.9584553837776184, 'Val/mean f1': 0.9752411842346191, 'Val/mean precision': 0.9732521176338196, 'Val/mean recall': 0.9772383570671082, 'Val/mean hd95_metric': 5.102968692779541} +Cheakpoint... +Epoch [2481/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740198254585266, 'Val/mean miou_metric': 0.9584553837776184, 'Val/mean f1': 0.9752411842346191, 'Val/mean precision': 0.9732521176338196, 'Val/mean recall': 0.9772383570671082, 'Val/mean hd95_metric': 5.102968692779541} +Epoch [2482/4000] Training [1/16] Loss: 0.00362 +Epoch [2482/4000] Training [2/16] Loss: 0.00367 +Epoch [2482/4000] Training [3/16] Loss: 0.00345 +Epoch [2482/4000] Training [4/16] Loss: 0.00532 +Epoch [2482/4000] Training [5/16] Loss: 0.00386 +Epoch [2482/4000] Training [6/16] Loss: 0.00396 +Epoch [2482/4000] Training [7/16] Loss: 0.00495 +Epoch [2482/4000] Training [8/16] Loss: 0.00476 +Epoch [2482/4000] Training [9/16] Loss: 0.00366 +Epoch [2482/4000] Training [10/16] Loss: 0.00477 +Epoch [2482/4000] Training [11/16] Loss: 0.00587 +Epoch [2482/4000] Training [12/16] Loss: 0.00329 +Epoch [2482/4000] Training [13/16] Loss: 0.00439 +Epoch [2482/4000] Training [14/16] Loss: 0.00356 +Epoch [2482/4000] Training [15/16] Loss: 0.00405 +Epoch [2482/4000] Training [16/16] Loss: 0.00435 +Epoch [2482/4000] Training metric {'Train/mean dice_metric': 0.9974198341369629, 'Train/mean miou_metric': 0.9945436716079712, 'Train/mean f1': 0.9919905066490173, 'Train/mean precision': 0.986751914024353, 'Train/mean recall': 0.9972849488258362, 'Train/mean hd95_metric': 0.939899206161499} +Epoch [2482/4000] Validation [1/4] Loss: 0.32250 focal_loss 0.25629 dice_loss 0.06621 +Epoch [2482/4000] Validation [2/4] Loss: 0.40918 focal_loss 0.27246 dice_loss 0.13672 +Epoch [2482/4000] Validation [3/4] Loss: 0.41390 focal_loss 0.32473 dice_loss 0.08917 +Epoch [2482/4000] Validation [4/4] Loss: 0.31418 focal_loss 0.22518 dice_loss 0.08899 +Epoch [2482/4000] Validation metric {'Val/mean dice_metric': 0.9723374247550964, 'Val/mean miou_metric': 0.9571577906608582, 'Val/mean f1': 0.974413275718689, 'Val/mean precision': 0.9728187918663025, 'Val/mean recall': 0.97601318359375, 'Val/mean hd95_metric': 5.110327243804932} +Cheakpoint... +Epoch [2482/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723374247550964, 'Val/mean miou_metric': 0.9571577906608582, 'Val/mean f1': 0.974413275718689, 'Val/mean precision': 0.9728187918663025, 'Val/mean recall': 0.97601318359375, 'Val/mean hd95_metric': 5.110327243804932} +Epoch [2483/4000] Training [1/16] Loss: 0.00324 +Epoch [2483/4000] Training [2/16] Loss: 0.00382 +Epoch [2483/4000] Training [3/16] Loss: 0.00408 +Epoch [2483/4000] Training [4/16] Loss: 0.00387 +Epoch [2483/4000] Training [5/16] Loss: 0.00514 +Epoch [2483/4000] Training [6/16] Loss: 0.00439 +Epoch [2483/4000] Training [7/16] Loss: 0.00426 +Epoch [2483/4000] Training [8/16] Loss: 0.00382 +Epoch [2483/4000] Training [9/16] Loss: 0.00420 +Epoch [2483/4000] Training [10/16] Loss: 0.00359 +Epoch [2483/4000] Training [11/16] Loss: 0.00458 +Epoch [2483/4000] Training [12/16] Loss: 0.00481 +Epoch [2483/4000] Training [13/16] Loss: 0.00531 +Epoch [2483/4000] Training [14/16] Loss: 0.00465 +Epoch [2483/4000] Training [15/16] Loss: 0.00524 +Epoch [2483/4000] Training [16/16] Loss: 0.00455 +Epoch [2483/4000] Training metric {'Train/mean dice_metric': 0.9974380731582642, 'Train/mean miou_metric': 0.9946218729019165, 'Train/mean f1': 0.9928315281867981, 'Train/mean precision': 0.9883219003677368, 'Train/mean recall': 0.9973824620246887, 'Train/mean hd95_metric': 0.9527333974838257} +Epoch [2483/4000] Validation [1/4] Loss: 0.34248 focal_loss 0.27211 dice_loss 0.07037 +Epoch [2483/4000] Validation [2/4] Loss: 0.32471 focal_loss 0.21212 dice_loss 0.11259 +Epoch [2483/4000] Validation [3/4] Loss: 0.40675 focal_loss 0.31338 dice_loss 0.09338 +Epoch [2483/4000] Validation [4/4] Loss: 0.25513 focal_loss 0.16548 dice_loss 0.08965 +Epoch [2483/4000] Validation metric {'Val/mean dice_metric': 0.9722196459770203, 'Val/mean miou_metric': 0.9572027921676636, 'Val/mean f1': 0.9752330183982849, 'Val/mean precision': 0.9732381701469421, 'Val/mean recall': 0.9772360920906067, 'Val/mean hd95_metric': 5.450907230377197} +Cheakpoint... +Epoch [2483/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722196459770203, 'Val/mean miou_metric': 0.9572027921676636, 'Val/mean f1': 0.9752330183982849, 'Val/mean precision': 0.9732381701469421, 'Val/mean recall': 0.9772360920906067, 'Val/mean hd95_metric': 5.450907230377197} +Epoch [2484/4000] Training [1/16] Loss: 0.00490 +Epoch [2484/4000] Training [2/16] Loss: 0.00413 +Epoch [2484/4000] Training [3/16] Loss: 0.00374 +Epoch [2484/4000] Training [4/16] Loss: 0.00394 +Epoch [2484/4000] Training [5/16] Loss: 0.00323 +Epoch [2484/4000] Training [6/16] Loss: 0.00441 +Epoch [2484/4000] Training [7/16] Loss: 0.00341 +Epoch [2484/4000] Training [8/16] Loss: 0.00396 +Epoch [2484/4000] Training [9/16] Loss: 0.00447 +Epoch [2484/4000] Training [10/16] Loss: 0.00478 +Epoch [2484/4000] Training [11/16] Loss: 0.00291 +Epoch [2484/4000] Training [12/16] Loss: 0.00602 +Epoch [2484/4000] Training [13/16] Loss: 0.00357 +Epoch [2484/4000] Training [14/16] Loss: 0.00407 +Epoch [2484/4000] Training [15/16] Loss: 0.00406 +Epoch [2484/4000] Training [16/16] Loss: 0.00313 +Epoch [2484/4000] Training metric {'Train/mean dice_metric': 0.9974411725997925, 'Train/mean miou_metric': 0.9946218729019165, 'Train/mean f1': 0.9926097393035889, 'Train/mean precision': 0.9880051016807556, 'Train/mean recall': 0.9972575306892395, 'Train/mean hd95_metric': 0.9497347474098206} +Epoch [2484/4000] Validation [1/4] Loss: 0.29845 focal_loss 0.23959 dice_loss 0.05886 +Epoch [2484/4000] Validation [2/4] Loss: 0.36604 focal_loss 0.24673 dice_loss 0.11931 +Epoch [2484/4000] Validation [3/4] Loss: 0.23194 focal_loss 0.16543 dice_loss 0.06651 +Epoch [2484/4000] Validation [4/4] Loss: 0.34712 focal_loss 0.24112 dice_loss 0.10600 +Epoch [2484/4000] Validation metric {'Val/mean dice_metric': 0.9748436212539673, 'Val/mean miou_metric': 0.9595749974250793, 'Val/mean f1': 0.9754554629325867, 'Val/mean precision': 0.9732650518417358, 'Val/mean recall': 0.9776557087898254, 'Val/mean hd95_metric': 5.3087687492370605} +Cheakpoint... +Epoch [2484/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748436212539673, 'Val/mean miou_metric': 0.9595749974250793, 'Val/mean f1': 0.9754554629325867, 'Val/mean precision': 0.9732650518417358, 'Val/mean recall': 0.9776557087898254, 'Val/mean hd95_metric': 5.3087687492370605} +Epoch [2485/4000] Training [1/16] Loss: 0.00561 +Epoch [2485/4000] Training [2/16] Loss: 0.00384 +Epoch [2485/4000] Training [3/16] Loss: 0.00489 +Epoch [2485/4000] Training [4/16] Loss: 0.00495 +Epoch [2485/4000] Training [5/16] Loss: 0.00440 +Epoch [2485/4000] Training [6/16] Loss: 0.00388 +Epoch [2485/4000] Training [7/16] Loss: 0.00797 +Epoch [2485/4000] Training [8/16] Loss: 0.00845 +Epoch [2485/4000] Training [9/16] Loss: 0.00365 +Epoch [2485/4000] Training [10/16] Loss: 0.00441 +Epoch [2485/4000] Training [11/16] Loss: 0.00479 +Epoch [2485/4000] Training [12/16] Loss: 0.00362 +Epoch [2485/4000] Training [13/16] Loss: 0.00582 +Epoch [2485/4000] Training [14/16] Loss: 0.00309 +Epoch [2485/4000] Training [15/16] Loss: 0.00477 +Epoch [2485/4000] Training [16/16] Loss: 0.00488 +Epoch [2485/4000] Training metric {'Train/mean dice_metric': 0.9968034029006958, 'Train/mean miou_metric': 0.9933856725692749, 'Train/mean f1': 0.9915976524353027, 'Train/mean precision': 0.9863367676734924, 'Train/mean recall': 0.9969149827957153, 'Train/mean hd95_metric': 1.1744451522827148} +Epoch [2485/4000] Validation [1/4] Loss: 0.83560 focal_loss 0.68431 dice_loss 0.15129 +Epoch [2485/4000] Validation [2/4] Loss: 0.58226 focal_loss 0.40015 dice_loss 0.18211 +Epoch [2485/4000] Validation [3/4] Loss: 0.32356 focal_loss 0.23783 dice_loss 0.08573 +Epoch [2485/4000] Validation [4/4] Loss: 0.52502 focal_loss 0.41374 dice_loss 0.11128 +Epoch [2485/4000] Validation metric {'Val/mean dice_metric': 0.9687187075614929, 'Val/mean miou_metric': 0.9521558880805969, 'Val/mean f1': 0.9701016545295715, 'Val/mean precision': 0.9749614000320435, 'Val/mean recall': 0.9652901291847229, 'Val/mean hd95_metric': 6.005276203155518} +Cheakpoint... +Epoch [2485/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687187075614929, 'Val/mean miou_metric': 0.9521558880805969, 'Val/mean f1': 0.9701016545295715, 'Val/mean precision': 0.9749614000320435, 'Val/mean recall': 0.9652901291847229, 'Val/mean hd95_metric': 6.005276203155518} +Epoch [2486/4000] Training [1/16] Loss: 0.00545 +Epoch [2486/4000] Training [2/16] Loss: 0.00512 +Epoch [2486/4000] Training [3/16] Loss: 0.00487 +Epoch [2486/4000] Training [4/16] Loss: 0.00382 +Epoch [2486/4000] Training [5/16] Loss: 0.00411 +Epoch [2486/4000] Training [6/16] Loss: 0.00390 +Epoch [2486/4000] Training [7/16] Loss: 0.00427 +Epoch [2486/4000] Training [8/16] Loss: 0.00425 +Epoch [2486/4000] Training [9/16] Loss: 0.00543 +Epoch [2486/4000] Training [10/16] Loss: 0.00448 +Epoch [2486/4000] Training [11/16] Loss: 0.00401 +Epoch [2486/4000] Training [12/16] Loss: 0.00347 +Epoch [2486/4000] Training [13/16] Loss: 0.00404 +Epoch [2486/4000] Training [14/16] Loss: 0.00521 +Epoch [2486/4000] Training [15/16] Loss: 0.00553 +Epoch [2486/4000] Training [16/16] Loss: 0.00427 +Epoch [2486/4000] Training metric {'Train/mean dice_metric': 0.9971266388893127, 'Train/mean miou_metric': 0.9939848184585571, 'Train/mean f1': 0.9922606945037842, 'Train/mean precision': 0.9875790476799011, 'Train/mean recall': 0.996986985206604, 'Train/mean hd95_metric': 0.978103756904602} +Epoch [2486/4000] Validation [1/4] Loss: 1.17339 focal_loss 0.99467 dice_loss 0.17873 +Epoch [2486/4000] Validation [2/4] Loss: 0.98591 focal_loss 0.80141 dice_loss 0.18449 +Epoch [2486/4000] Validation [3/4] Loss: 0.32304 focal_loss 0.23095 dice_loss 0.09210 +Epoch [2486/4000] Validation [4/4] Loss: 0.67820 focal_loss 0.53784 dice_loss 0.14036 +Epoch [2486/4000] Validation metric {'Val/mean dice_metric': 0.9649775624275208, 'Val/mean miou_metric': 0.9488770365715027, 'Val/mean f1': 0.9689365029335022, 'Val/mean precision': 0.976413905620575, 'Val/mean recall': 0.9615727663040161, 'Val/mean hd95_metric': 5.705512046813965} +Cheakpoint... +Epoch [2486/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9650], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9649775624275208, 'Val/mean miou_metric': 0.9488770365715027, 'Val/mean f1': 0.9689365029335022, 'Val/mean precision': 0.976413905620575, 'Val/mean recall': 0.9615727663040161, 'Val/mean hd95_metric': 5.705512046813965} +Epoch [2487/4000] Training [1/16] Loss: 0.00551 +Epoch [2487/4000] Training [2/16] Loss: 0.00351 +Epoch [2487/4000] Training [3/16] Loss: 0.00402 +Epoch [2487/4000] Training [4/16] Loss: 0.00467 +Epoch [2487/4000] Training [5/16] Loss: 0.00353 +Epoch [2487/4000] Training [6/16] Loss: 0.00492 +Epoch [2487/4000] Training [7/16] Loss: 0.00423 +Epoch [2487/4000] Training [8/16] Loss: 0.00412 +Epoch [2487/4000] Training [9/16] Loss: 0.00382 +Epoch [2487/4000] Training [10/16] Loss: 0.00391 +Epoch [2487/4000] Training [11/16] Loss: 0.00484 +Epoch [2487/4000] Training [12/16] Loss: 0.00486 +Epoch [2487/4000] Training [13/16] Loss: 0.00437 +Epoch [2487/4000] Training [14/16] Loss: 0.00451 +Epoch [2487/4000] Training [15/16] Loss: 0.00539 +Epoch [2487/4000] Training [16/16] Loss: 0.00475 +Epoch [2487/4000] Training metric {'Train/mean dice_metric': 0.9972611665725708, 'Train/mean miou_metric': 0.9942389130592346, 'Train/mean f1': 0.992012619972229, 'Train/mean precision': 0.9869872331619263, 'Train/mean recall': 0.9970895051956177, 'Train/mean hd95_metric': 0.9590120911598206} +Epoch [2487/4000] Validation [1/4] Loss: 0.73171 focal_loss 0.58627 dice_loss 0.14544 +Epoch [2487/4000] Validation [2/4] Loss: 0.77158 focal_loss 0.58654 dice_loss 0.18504 +Epoch [2487/4000] Validation [3/4] Loss: 0.32132 focal_loss 0.22349 dice_loss 0.09783 +Epoch [2487/4000] Validation [4/4] Loss: 0.45363 focal_loss 0.33406 dice_loss 0.11958 +Epoch [2487/4000] Validation metric {'Val/mean dice_metric': 0.9673224687576294, 'Val/mean miou_metric': 0.9513359069824219, 'Val/mean f1': 0.971476674079895, 'Val/mean precision': 0.9759413599967957, 'Val/mean recall': 0.9670526385307312, 'Val/mean hd95_metric': 5.437809467315674} +Cheakpoint... +Epoch [2487/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9673], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9673224687576294, 'Val/mean miou_metric': 0.9513359069824219, 'Val/mean f1': 0.971476674079895, 'Val/mean precision': 0.9759413599967957, 'Val/mean recall': 0.9670526385307312, 'Val/mean hd95_metric': 5.437809467315674} +Epoch [2488/4000] Training [1/16] Loss: 0.00458 +Epoch [2488/4000] Training [2/16] Loss: 0.00445 +Epoch [2488/4000] Training [3/16] Loss: 0.00592 +Epoch [2488/4000] Training [4/16] Loss: 0.00373 +Epoch [2488/4000] Training [5/16] Loss: 0.00674 +Epoch [2488/4000] Training [6/16] Loss: 0.00382 +Epoch [2488/4000] Training [7/16] Loss: 0.00473 +Epoch [2488/4000] Training [8/16] Loss: 0.00359 +Epoch [2488/4000] Training [9/16] Loss: 0.00417 +Epoch [2488/4000] Training [10/16] Loss: 0.00411 +Epoch [2488/4000] Training [11/16] Loss: 0.00333 +Epoch [2488/4000] Training [12/16] Loss: 0.00231 +Epoch [2488/4000] Training [13/16] Loss: 0.00465 +Epoch [2488/4000] Training [14/16] Loss: 0.00455 +Epoch [2488/4000] Training [15/16] Loss: 0.00507 +Epoch [2488/4000] Training [16/16] Loss: 0.00605 +Epoch [2488/4000] Training metric {'Train/mean dice_metric': 0.9973821640014648, 'Train/mean miou_metric': 0.9945005178451538, 'Train/mean f1': 0.9926464557647705, 'Train/mean precision': 0.9880504608154297, 'Train/mean recall': 0.9972854256629944, 'Train/mean hd95_metric': 0.944141149520874} +Epoch [2488/4000] Validation [1/4] Loss: 0.62759 focal_loss 0.49521 dice_loss 0.13237 +Epoch [2488/4000] Validation [2/4] Loss: 0.64722 focal_loss 0.46368 dice_loss 0.18354 +Epoch [2488/4000] Validation [3/4] Loss: 0.37135 focal_loss 0.27329 dice_loss 0.09806 +Epoch [2488/4000] Validation [4/4] Loss: 0.38068 focal_loss 0.27643 dice_loss 0.10425 +Epoch [2488/4000] Validation metric {'Val/mean dice_metric': 0.9692633748054504, 'Val/mean miou_metric': 0.9538871645927429, 'Val/mean f1': 0.9728516936302185, 'Val/mean precision': 0.9763216376304626, 'Val/mean recall': 0.9694064259529114, 'Val/mean hd95_metric': 5.560876846313477} +Cheakpoint... +Epoch [2488/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9693], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692633748054504, 'Val/mean miou_metric': 0.9538871645927429, 'Val/mean f1': 0.9728516936302185, 'Val/mean precision': 0.9763216376304626, 'Val/mean recall': 0.9694064259529114, 'Val/mean hd95_metric': 5.560876846313477} +Epoch [2489/4000] Training [1/16] Loss: 0.00489 +Epoch [2489/4000] Training [2/16] Loss: 0.00952 +Epoch [2489/4000] Training [3/16] Loss: 0.00314 +Epoch [2489/4000] Training [4/16] Loss: 0.00534 +Epoch [2489/4000] Training [5/16] Loss: 0.00442 +Epoch [2489/4000] Training [6/16] Loss: 0.00387 +Epoch [2489/4000] Training [7/16] Loss: 0.00444 +Epoch [2489/4000] Training [8/16] Loss: 0.00640 +Epoch [2489/4000] Training [9/16] Loss: 0.00416 +Epoch [2489/4000] Training [10/16] Loss: 0.00441 +Epoch [2489/4000] Training [11/16] Loss: 0.00502 +Epoch [2489/4000] Training [12/16] Loss: 0.00405 +Epoch [2489/4000] Training [13/16] Loss: 0.00425 +Epoch [2489/4000] Training [14/16] Loss: 0.00479 +Epoch [2489/4000] Training [15/16] Loss: 0.00411 +Epoch [2489/4000] Training [16/16] Loss: 0.00336 +Epoch [2489/4000] Training metric {'Train/mean dice_metric': 0.9968656897544861, 'Train/mean miou_metric': 0.9934608936309814, 'Train/mean f1': 0.9917442798614502, 'Train/mean precision': 0.9870833158493042, 'Train/mean recall': 0.9964494705200195, 'Train/mean hd95_metric': 1.0882837772369385} +Epoch [2489/4000] Validation [1/4] Loss: 0.28789 focal_loss 0.22623 dice_loss 0.06166 +Epoch [2489/4000] Validation [2/4] Loss: 0.40227 focal_loss 0.27070 dice_loss 0.13157 +Epoch [2489/4000] Validation [3/4] Loss: 0.44843 focal_loss 0.35615 dice_loss 0.09228 +Epoch [2489/4000] Validation [4/4] Loss: 0.28019 focal_loss 0.18029 dice_loss 0.09989 +Epoch [2489/4000] Validation metric {'Val/mean dice_metric': 0.9733338356018066, 'Val/mean miou_metric': 0.9579461216926575, 'Val/mean f1': 0.9751257300376892, 'Val/mean precision': 0.9711026549339294, 'Val/mean recall': 0.9791823029518127, 'Val/mean hd95_metric': 5.684709072113037} +Cheakpoint... +Epoch [2489/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733338356018066, 'Val/mean miou_metric': 0.9579461216926575, 'Val/mean f1': 0.9751257300376892, 'Val/mean precision': 0.9711026549339294, 'Val/mean recall': 0.9791823029518127, 'Val/mean hd95_metric': 5.684709072113037} +Epoch [2490/4000] Training [1/16] Loss: 0.00522 +Epoch [2490/4000] Training [2/16] Loss: 0.00481 +Epoch [2490/4000] Training [3/16] Loss: 0.00452 +Epoch [2490/4000] Training [4/16] Loss: 0.00403 +Epoch [2490/4000] Training [5/16] Loss: 0.00541 +Epoch [2490/4000] Training [6/16] Loss: 0.00471 +Epoch [2490/4000] Training [7/16] Loss: 0.00466 +Epoch [2490/4000] Training [8/16] Loss: 0.00477 +Epoch [2490/4000] Training [9/16] Loss: 0.00391 +Epoch [2490/4000] Training [10/16] Loss: 0.00330 +Epoch [2490/4000] Training [11/16] Loss: 0.00489 +Epoch [2490/4000] Training [12/16] Loss: 0.00438 +Epoch [2490/4000] Training [13/16] Loss: 0.00309 +Epoch [2490/4000] Training [14/16] Loss: 0.00421 +Epoch [2490/4000] Training [15/16] Loss: 0.00317 +Epoch [2490/4000] Training [16/16] Loss: 0.00554 +Epoch [2490/4000] Training metric {'Train/mean dice_metric': 0.9973193407058716, 'Train/mean miou_metric': 0.9943793416023254, 'Train/mean f1': 0.9924430251121521, 'Train/mean precision': 0.987797200679779, 'Train/mean recall': 0.9971327781677246, 'Train/mean hd95_metric': 1.1645606756210327} +Epoch [2490/4000] Validation [1/4] Loss: 0.37982 focal_loss 0.30978 dice_loss 0.07004 +Epoch [2490/4000] Validation [2/4] Loss: 0.86234 focal_loss 0.62348 dice_loss 0.23886 +Epoch [2490/4000] Validation [3/4] Loss: 0.44186 focal_loss 0.34668 dice_loss 0.09518 +Epoch [2490/4000] Validation [4/4] Loss: 0.28389 focal_loss 0.19551 dice_loss 0.08838 +Epoch [2490/4000] Validation metric {'Val/mean dice_metric': 0.9710367918014526, 'Val/mean miou_metric': 0.9557892084121704, 'Val/mean f1': 0.9744433760643005, 'Val/mean precision': 0.9724293947219849, 'Val/mean recall': 0.9764658808708191, 'Val/mean hd95_metric': 5.661021709442139} +Cheakpoint... +Epoch [2490/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710367918014526, 'Val/mean miou_metric': 0.9557892084121704, 'Val/mean f1': 0.9744433760643005, 'Val/mean precision': 0.9724293947219849, 'Val/mean recall': 0.9764658808708191, 'Val/mean hd95_metric': 5.661021709442139} +Epoch [2491/4000] Training [1/16] Loss: 0.00313 +Epoch [2491/4000] Training [2/16] Loss: 0.00359 +Epoch [2491/4000] Training [3/16] Loss: 0.00472 +Epoch [2491/4000] Training [4/16] Loss: 0.00425 +Epoch [2491/4000] Training [5/16] Loss: 0.00351 +Epoch [2491/4000] Training [6/16] Loss: 0.00371 +Epoch [2491/4000] Training [7/16] Loss: 0.00401 +Epoch [2491/4000] Training [8/16] Loss: 0.00325 +Epoch [2491/4000] Training [9/16] Loss: 0.00501 +Epoch [2491/4000] Training [10/16] Loss: 0.00492 +Epoch [2491/4000] Training [11/16] Loss: 0.00631 +Epoch [2491/4000] Training [12/16] Loss: 0.00726 +Epoch [2491/4000] Training [13/16] Loss: 0.00660 +Epoch [2491/4000] Training [14/16] Loss: 0.00417 +Epoch [2491/4000] Training [15/16] Loss: 0.00490 +Epoch [2491/4000] Training [16/16] Loss: 0.00331 +Epoch [2491/4000] Training metric {'Train/mean dice_metric': 0.9971790909767151, 'Train/mean miou_metric': 0.9940963387489319, 'Train/mean f1': 0.9923254251480103, 'Train/mean precision': 0.9876671433448792, 'Train/mean recall': 0.9970278143882751, 'Train/mean hd95_metric': 0.9617875814437866} +Epoch [2491/4000] Validation [1/4] Loss: 0.35427 focal_loss 0.27701 dice_loss 0.07727 +Epoch [2491/4000] Validation [2/4] Loss: 0.99900 focal_loss 0.77014 dice_loss 0.22886 +Epoch [2491/4000] Validation [3/4] Loss: 0.46841 focal_loss 0.36503 dice_loss 0.10337 +Epoch [2491/4000] Validation [4/4] Loss: 0.33954 focal_loss 0.22675 dice_loss 0.11279 +Epoch [2491/4000] Validation metric {'Val/mean dice_metric': 0.9710530042648315, 'Val/mean miou_metric': 0.9554643630981445, 'Val/mean f1': 0.9737527966499329, 'Val/mean precision': 0.9713661074638367, 'Val/mean recall': 0.9761513471603394, 'Val/mean hd95_metric': 5.465267181396484} +Cheakpoint... +Epoch [2491/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710530042648315, 'Val/mean miou_metric': 0.9554643630981445, 'Val/mean f1': 0.9737527966499329, 'Val/mean precision': 0.9713661074638367, 'Val/mean recall': 0.9761513471603394, 'Val/mean hd95_metric': 5.465267181396484} +Epoch [2492/4000] Training [1/16] Loss: 0.00366 +Epoch [2492/4000] Training [2/16] Loss: 0.00383 +Epoch [2492/4000] Training [3/16] Loss: 0.00363 +Epoch [2492/4000] Training [4/16] Loss: 0.00452 +Epoch [2492/4000] Training [5/16] Loss: 0.00297 +Epoch [2492/4000] Training [6/16] Loss: 0.00495 +Epoch [2492/4000] Training [7/16] Loss: 0.00459 +Epoch [2492/4000] Training [8/16] Loss: 0.00393 +Epoch [2492/4000] Training [9/16] Loss: 0.00304 +Epoch [2492/4000] Training [10/16] Loss: 0.00440 +Epoch [2492/4000] Training [11/16] Loss: 0.00483 +Epoch [2492/4000] Training [12/16] Loss: 0.00386 +Epoch [2492/4000] Training [13/16] Loss: 0.00479 +Epoch [2492/4000] Training [14/16] Loss: 0.00622 +Epoch [2492/4000] Training [15/16] Loss: 0.00385 +Epoch [2492/4000] Training [16/16] Loss: 0.00367 +Epoch [2492/4000] Training metric {'Train/mean dice_metric': 0.9974124431610107, 'Train/mean miou_metric': 0.9945344924926758, 'Train/mean f1': 0.9919673204421997, 'Train/mean precision': 0.9867333173751831, 'Train/mean recall': 0.9972571730613708, 'Train/mean hd95_metric': 1.3005919456481934} +Epoch [2492/4000] Validation [1/4] Loss: 0.31259 focal_loss 0.24334 dice_loss 0.06925 +Epoch [2492/4000] Validation [2/4] Loss: 0.78351 focal_loss 0.57096 dice_loss 0.21255 +Epoch [2492/4000] Validation [3/4] Loss: 0.41431 focal_loss 0.31991 dice_loss 0.09440 +Epoch [2492/4000] Validation [4/4] Loss: 0.31994 focal_loss 0.21137 dice_loss 0.10856 +Epoch [2492/4000] Validation metric {'Val/mean dice_metric': 0.9718502163887024, 'Val/mean miou_metric': 0.9570907354354858, 'Val/mean f1': 0.9750552773475647, 'Val/mean precision': 0.9726682901382446, 'Val/mean recall': 0.9774540066719055, 'Val/mean hd95_metric': 5.410625457763672} +Cheakpoint... +Epoch [2492/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718502163887024, 'Val/mean miou_metric': 0.9570907354354858, 'Val/mean f1': 0.9750552773475647, 'Val/mean precision': 0.9726682901382446, 'Val/mean recall': 0.9774540066719055, 'Val/mean hd95_metric': 5.410625457763672} +Epoch [2493/4000] Training [1/16] Loss: 0.00409 +Epoch [2493/4000] Training [2/16] Loss: 0.00380 +Epoch [2493/4000] Training [3/16] Loss: 0.00466 +Epoch [2493/4000] Training [4/16] Loss: 0.00369 +Epoch [2493/4000] Training [5/16] Loss: 0.00752 +Epoch [2493/4000] Training [6/16] Loss: 0.00534 +Epoch [2493/4000] Training [7/16] Loss: 0.00398 +Epoch [2493/4000] Training [8/16] Loss: 0.00533 +Epoch [2493/4000] Training [9/16] Loss: 0.00550 +Epoch [2493/4000] Training [10/16] Loss: 0.00553 +Epoch [2493/4000] Training [11/16] Loss: 0.00396 +Epoch [2493/4000] Training [12/16] Loss: 0.00372 +Epoch [2493/4000] Training [13/16] Loss: 0.00399 +Epoch [2493/4000] Training [14/16] Loss: 0.00404 +Epoch [2493/4000] Training [15/16] Loss: 0.00474 +Epoch [2493/4000] Training [16/16] Loss: 0.00421 +Epoch [2493/4000] Training metric {'Train/mean dice_metric': 0.9972870945930481, 'Train/mean miou_metric': 0.9943112134933472, 'Train/mean f1': 0.992445707321167, 'Train/mean precision': 0.9876745343208313, 'Train/mean recall': 0.9972632527351379, 'Train/mean hd95_metric': 0.9477543830871582} +Epoch [2493/4000] Validation [1/4] Loss: 0.34744 focal_loss 0.28350 dice_loss 0.06394 +Epoch [2493/4000] Validation [2/4] Loss: 0.68978 focal_loss 0.51822 dice_loss 0.17156 +Epoch [2493/4000] Validation [3/4] Loss: 0.46016 focal_loss 0.36436 dice_loss 0.09581 +Epoch [2493/4000] Validation [4/4] Loss: 0.29799 focal_loss 0.20260 dice_loss 0.09539 +Epoch [2493/4000] Validation metric {'Val/mean dice_metric': 0.9737480282783508, 'Val/mean miou_metric': 0.9584105610847473, 'Val/mean f1': 0.9754956364631653, 'Val/mean precision': 0.9725990295410156, 'Val/mean recall': 0.9784095883369446, 'Val/mean hd95_metric': 5.300100326538086} +Cheakpoint... +Epoch [2493/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737480282783508, 'Val/mean miou_metric': 0.9584105610847473, 'Val/mean f1': 0.9754956364631653, 'Val/mean precision': 0.9725990295410156, 'Val/mean recall': 0.9784095883369446, 'Val/mean hd95_metric': 5.300100326538086} +Epoch [2494/4000] Training [1/16] Loss: 0.00375 +Epoch [2494/4000] Training [2/16] Loss: 0.00416 +Epoch [2494/4000] Training [3/16] Loss: 0.00498 +Epoch [2494/4000] Training [4/16] Loss: 0.00532 +Epoch [2494/4000] Training [5/16] Loss: 0.00364 +Epoch [2494/4000] Training [6/16] Loss: 0.00412 +Epoch [2494/4000] Training [7/16] Loss: 0.00372 +Epoch [2494/4000] Training [8/16] Loss: 0.00406 +Epoch [2494/4000] Training [9/16] Loss: 0.00412 +Epoch [2494/4000] Training [10/16] Loss: 0.00324 +Epoch [2494/4000] Training [11/16] Loss: 0.00454 +Epoch [2494/4000] Training [12/16] Loss: 0.00404 +Epoch [2494/4000] Training [13/16] Loss: 0.00406 +Epoch [2494/4000] Training [14/16] Loss: 0.00433 +Epoch [2494/4000] Training [15/16] Loss: 0.00435 +Epoch [2494/4000] Training [16/16] Loss: 0.00456 +Epoch [2494/4000] Training metric {'Train/mean dice_metric': 0.9974390864372253, 'Train/mean miou_metric': 0.9946169853210449, 'Train/mean f1': 0.9926891326904297, 'Train/mean precision': 0.9880301356315613, 'Train/mean recall': 0.9973922371864319, 'Train/mean hd95_metric': 0.9310123920440674} +Epoch [2494/4000] Validation [1/4] Loss: 0.32939 focal_loss 0.26055 dice_loss 0.06884 +Epoch [2494/4000] Validation [2/4] Loss: 1.14802 focal_loss 0.84924 dice_loss 0.29877 +Epoch [2494/4000] Validation [3/4] Loss: 0.46361 focal_loss 0.36745 dice_loss 0.09616 +Epoch [2494/4000] Validation [4/4] Loss: 0.28016 focal_loss 0.18763 dice_loss 0.09252 +Epoch [2494/4000] Validation metric {'Val/mean dice_metric': 0.9722232818603516, 'Val/mean miou_metric': 0.957402229309082, 'Val/mean f1': 0.9747662544250488, 'Val/mean precision': 0.9706284999847412, 'Val/mean recall': 0.9789394736289978, 'Val/mean hd95_metric': 5.6236138343811035} +Cheakpoint... +Epoch [2494/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722232818603516, 'Val/mean miou_metric': 0.957402229309082, 'Val/mean f1': 0.9747662544250488, 'Val/mean precision': 0.9706284999847412, 'Val/mean recall': 0.9789394736289978, 'Val/mean hd95_metric': 5.6236138343811035} +Epoch [2495/4000] Training [1/16] Loss: 0.00315 +Epoch [2495/4000] Training [2/16] Loss: 0.00424 +Epoch [2495/4000] Training [3/16] Loss: 0.00368 +Epoch [2495/4000] Training [4/16] Loss: 0.00525 +Epoch [2495/4000] Training [5/16] Loss: 0.00329 +Epoch [2495/4000] Training [6/16] Loss: 0.00452 +Epoch [2495/4000] Training [7/16] Loss: 0.00366 +Epoch [2495/4000] Training [8/16] Loss: 0.00346 +Epoch [2495/4000] Training [9/16] Loss: 0.00338 +Epoch [2495/4000] Training [10/16] Loss: 0.00467 +Epoch [2495/4000] Training [11/16] Loss: 0.00364 +Epoch [2495/4000] Training [12/16] Loss: 0.00378 +Epoch [2495/4000] Training [13/16] Loss: 0.00412 +Epoch [2495/4000] Training [14/16] Loss: 0.00585 +Epoch [2495/4000] Training [15/16] Loss: 0.00613 +Epoch [2495/4000] Training [16/16] Loss: 0.00549 +Epoch [2495/4000] Training metric {'Train/mean dice_metric': 0.9975429773330688, 'Train/mean miou_metric': 0.994827151298523, 'Train/mean f1': 0.9928831458091736, 'Train/mean precision': 0.988420844078064, 'Train/mean recall': 0.9973859786987305, 'Train/mean hd95_metric': 0.9225163459777832} +Epoch [2495/4000] Validation [1/4] Loss: 0.36002 focal_loss 0.29417 dice_loss 0.06585 +Epoch [2495/4000] Validation [2/4] Loss: 0.44943 focal_loss 0.31597 dice_loss 0.13347 +Epoch [2495/4000] Validation [3/4] Loss: 0.45530 focal_loss 0.36249 dice_loss 0.09281 +Epoch [2495/4000] Validation [4/4] Loss: 0.53450 focal_loss 0.39379 dice_loss 0.14070 +Epoch [2495/4000] Validation metric {'Val/mean dice_metric': 0.9720775485038757, 'Val/mean miou_metric': 0.9571610689163208, 'Val/mean f1': 0.975437343120575, 'Val/mean precision': 0.9727036356925964, 'Val/mean recall': 0.978186309337616, 'Val/mean hd95_metric': 5.637176990509033} +Cheakpoint... +Epoch [2495/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720775485038757, 'Val/mean miou_metric': 0.9571610689163208, 'Val/mean f1': 0.975437343120575, 'Val/mean precision': 0.9727036356925964, 'Val/mean recall': 0.978186309337616, 'Val/mean hd95_metric': 5.637176990509033} +Epoch [2496/4000] Training [1/16] Loss: 0.00419 +Epoch [2496/4000] Training [2/16] Loss: 0.00419 +Epoch [2496/4000] Training [3/16] Loss: 0.00669 +Epoch [2496/4000] Training [4/16] Loss: 0.00366 +Epoch [2496/4000] Training [5/16] Loss: 0.00345 +Epoch [2496/4000] Training [6/16] Loss: 0.00357 +Epoch [2496/4000] Training [7/16] Loss: 0.00408 +Epoch [2496/4000] Training [8/16] Loss: 0.00420 +Epoch [2496/4000] Training [9/16] Loss: 0.00547 +Epoch [2496/4000] Training [10/16] Loss: 0.00329 +Epoch [2496/4000] Training [11/16] Loss: 0.00433 +Epoch [2496/4000] Training [12/16] Loss: 0.00462 +Epoch [2496/4000] Training [13/16] Loss: 0.00480 +Epoch [2496/4000] Training [14/16] Loss: 0.00455 +Epoch [2496/4000] Training [15/16] Loss: 0.00358 +Epoch [2496/4000] Training [16/16] Loss: 0.00400 +Epoch [2496/4000] Training metric {'Train/mean dice_metric': 0.9972937107086182, 'Train/mean miou_metric': 0.9943315982818604, 'Train/mean f1': 0.9925931692123413, 'Train/mean precision': 0.9880028367042542, 'Train/mean recall': 0.997226357460022, 'Train/mean hd95_metric': 1.0231431722640991} +Epoch [2496/4000] Validation [1/4] Loss: 0.35009 focal_loss 0.27278 dice_loss 0.07732 +Epoch [2496/4000] Validation [2/4] Loss: 0.93776 focal_loss 0.67523 dice_loss 0.26253 +Epoch [2496/4000] Validation [3/4] Loss: 0.40168 focal_loss 0.30425 dice_loss 0.09743 +Epoch [2496/4000] Validation [4/4] Loss: 0.39327 focal_loss 0.26697 dice_loss 0.12630 +Epoch [2496/4000] Validation metric {'Val/mean dice_metric': 0.96942538022995, 'Val/mean miou_metric': 0.9543043971061707, 'Val/mean f1': 0.9742782115936279, 'Val/mean precision': 0.9732754826545715, 'Val/mean recall': 0.9752830266952515, 'Val/mean hd95_metric': 5.842778205871582} +Cheakpoint... +Epoch [2496/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96942538022995, 'Val/mean miou_metric': 0.9543043971061707, 'Val/mean f1': 0.9742782115936279, 'Val/mean precision': 0.9732754826545715, 'Val/mean recall': 0.9752830266952515, 'Val/mean hd95_metric': 5.842778205871582} +Epoch [2497/4000] Training [1/16] Loss: 0.00418 +Epoch [2497/4000] Training [2/16] Loss: 0.00400 +Epoch [2497/4000] Training [3/16] Loss: 0.00414 +Epoch [2497/4000] Training [4/16] Loss: 0.00561 +Epoch [2497/4000] Training [5/16] Loss: 0.00394 +Epoch [2497/4000] Training [6/16] Loss: 0.00456 +Epoch [2497/4000] Training [7/16] Loss: 0.00439 +Epoch [2497/4000] Training [8/16] Loss: 0.00333 +Epoch [2497/4000] Training [9/16] Loss: 0.00322 +Epoch [2497/4000] Training [10/16] Loss: 0.00357 +Epoch [2497/4000] Training [11/16] Loss: 0.00589 +Epoch [2497/4000] Training [12/16] Loss: 0.00448 +Epoch [2497/4000] Training [13/16] Loss: 0.00412 +Epoch [2497/4000] Training [14/16] Loss: 0.00360 +Epoch [2497/4000] Training [15/16] Loss: 0.00623 +Epoch [2497/4000] Training [16/16] Loss: 0.00495 +Epoch [2497/4000] Training metric {'Train/mean dice_metric': 0.9972043037414551, 'Train/mean miou_metric': 0.9941573143005371, 'Train/mean f1': 0.9927364587783813, 'Train/mean precision': 0.9883182048797607, 'Train/mean recall': 0.9971944093704224, 'Train/mean hd95_metric': 0.957923412322998} +Epoch [2497/4000] Validation [1/4] Loss: 0.31419 focal_loss 0.25028 dice_loss 0.06392 +Epoch [2497/4000] Validation [2/4] Loss: 0.78612 focal_loss 0.60120 dice_loss 0.18492 +Epoch [2497/4000] Validation [3/4] Loss: 0.40152 focal_loss 0.30758 dice_loss 0.09394 +Epoch [2497/4000] Validation [4/4] Loss: 0.28986 focal_loss 0.20107 dice_loss 0.08880 +Epoch [2497/4000] Validation metric {'Val/mean dice_metric': 0.9723523855209351, 'Val/mean miou_metric': 0.9574459195137024, 'Val/mean f1': 0.975773274898529, 'Val/mean precision': 0.9753950834274292, 'Val/mean recall': 0.976151704788208, 'Val/mean hd95_metric': 5.310141563415527} +Cheakpoint... +Epoch [2497/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723523855209351, 'Val/mean miou_metric': 0.9574459195137024, 'Val/mean f1': 0.975773274898529, 'Val/mean precision': 0.9753950834274292, 'Val/mean recall': 0.976151704788208, 'Val/mean hd95_metric': 5.310141563415527} +Epoch [2498/4000] Training [1/16] Loss: 0.00422 +Epoch [2498/4000] Training [2/16] Loss: 0.00302 +Epoch [2498/4000] Training [3/16] Loss: 0.00332 +Epoch [2498/4000] Training [4/16] Loss: 0.00503 +Epoch [2498/4000] Training [5/16] Loss: 0.00351 +Epoch [2498/4000] Training [6/16] Loss: 0.00317 +Epoch [2498/4000] Training [7/16] Loss: 0.00397 +Epoch [2498/4000] Training [8/16] Loss: 0.00499 +Epoch [2498/4000] Training [9/16] Loss: 0.00394 +Epoch [2498/4000] Training [10/16] Loss: 0.00439 +Epoch [2498/4000] Training [11/16] Loss: 0.00382 +Epoch [2498/4000] Training [12/16] Loss: 0.00324 +Epoch [2498/4000] Training [13/16] Loss: 0.00403 +Epoch [2498/4000] Training [14/16] Loss: 0.00390 +Epoch [2498/4000] Training [15/16] Loss: 0.00472 +Epoch [2498/4000] Training [16/16] Loss: 0.00317 +Epoch [2498/4000] Training metric {'Train/mean dice_metric': 0.9975806474685669, 'Train/mean miou_metric': 0.9949018955230713, 'Train/mean f1': 0.992919921875, 'Train/mean precision': 0.9883239269256592, 'Train/mean recall': 0.9975588321685791, 'Train/mean hd95_metric': 1.1919430494308472} +Epoch [2498/4000] Validation [1/4] Loss: 0.35994 focal_loss 0.29491 dice_loss 0.06504 +Epoch [2498/4000] Validation [2/4] Loss: 0.79581 focal_loss 0.61480 dice_loss 0.18100 +Epoch [2498/4000] Validation [3/4] Loss: 0.38464 focal_loss 0.29382 dice_loss 0.09082 +Epoch [2498/4000] Validation [4/4] Loss: 0.21665 focal_loss 0.13420 dice_loss 0.08245 +Epoch [2498/4000] Validation metric {'Val/mean dice_metric': 0.9717835187911987, 'Val/mean miou_metric': 0.9572259783744812, 'Val/mean f1': 0.9754754304885864, 'Val/mean precision': 0.9743437767028809, 'Val/mean recall': 0.9766096472740173, 'Val/mean hd95_metric': 5.601695537567139} +Cheakpoint... +Epoch [2498/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717835187911987, 'Val/mean miou_metric': 0.9572259783744812, 'Val/mean f1': 0.9754754304885864, 'Val/mean precision': 0.9743437767028809, 'Val/mean recall': 0.9766096472740173, 'Val/mean hd95_metric': 5.601695537567139} +Epoch [2499/4000] Training [1/16] Loss: 0.00312 +Epoch [2499/4000] Training [2/16] Loss: 0.00504 +Epoch [2499/4000] Training [3/16] Loss: 0.00448 +Epoch [2499/4000] Training [4/16] Loss: 0.00628 +Epoch [2499/4000] Training [5/16] Loss: 0.00355 +Epoch [2499/4000] Training [6/16] Loss: 0.00482 +Epoch [2499/4000] Training [7/16] Loss: 0.00376 +Epoch [2499/4000] Training [8/16] Loss: 0.00352 +Epoch [2499/4000] Training [9/16] Loss: 0.00434 +Epoch [2499/4000] Training [10/16] Loss: 0.00339 +Epoch [2499/4000] Training [11/16] Loss: 0.00300 +Epoch [2499/4000] Training [12/16] Loss: 0.00284 +Epoch [2499/4000] Training [13/16] Loss: 0.00347 +Epoch [2499/4000] Training [14/16] Loss: 0.00419 +Epoch [2499/4000] Training [15/16] Loss: 0.00579 +Epoch [2499/4000] Training [16/16] Loss: 0.00586 +Epoch [2499/4000] Training metric {'Train/mean dice_metric': 0.9974030256271362, 'Train/mean miou_metric': 0.9945416450500488, 'Train/mean f1': 0.9927153587341309, 'Train/mean precision': 0.988098680973053, 'Train/mean recall': 0.9973753690719604, 'Train/mean hd95_metric': 0.958160936832428} +Epoch [2499/4000] Validation [1/4] Loss: 0.38510 focal_loss 0.30342 dice_loss 0.08168 +Epoch [2499/4000] Validation [2/4] Loss: 0.43294 focal_loss 0.30487 dice_loss 0.12808 +Epoch [2499/4000] Validation [3/4] Loss: 0.39831 focal_loss 0.30459 dice_loss 0.09372 +Epoch [2499/4000] Validation [4/4] Loss: 0.25960 focal_loss 0.17366 dice_loss 0.08594 +Epoch [2499/4000] Validation metric {'Val/mean dice_metric': 0.972469687461853, 'Val/mean miou_metric': 0.9570934176445007, 'Val/mean f1': 0.9746731519699097, 'Val/mean precision': 0.973131000995636, 'Val/mean recall': 0.9762203097343445, 'Val/mean hd95_metric': 5.286471843719482} +Cheakpoint... +Epoch [2499/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972469687461853, 'Val/mean miou_metric': 0.9570934176445007, 'Val/mean f1': 0.9746731519699097, 'Val/mean precision': 0.973131000995636, 'Val/mean recall': 0.9762203097343445, 'Val/mean hd95_metric': 5.286471843719482} +Epoch [2500/4000] Training [1/16] Loss: 0.00460 +Epoch [2500/4000] Training [2/16] Loss: 0.00630 +Epoch [2500/4000] Training [3/16] Loss: 0.00361 +Epoch [2500/4000] Training [4/16] Loss: 0.00369 +Epoch [2500/4000] Training [5/16] Loss: 0.00322 +Epoch [2500/4000] Training [6/16] Loss: 0.00367 +Epoch [2500/4000] Training [7/16] Loss: 0.00473 +Epoch [2500/4000] Training [8/16] Loss: 0.00328 +Epoch [2500/4000] Training [9/16] Loss: 0.00505 +Epoch [2500/4000] Training [10/16] Loss: 0.00397 +Epoch [2500/4000] Training [11/16] Loss: 0.00493 +Epoch [2500/4000] Training [12/16] Loss: 0.00532 +Epoch [2500/4000] Training [13/16] Loss: 0.00428 +Epoch [2500/4000] Training [14/16] Loss: 0.00351 +Epoch [2500/4000] Training [15/16] Loss: 0.00455 +Epoch [2500/4000] Training [16/16] Loss: 0.00404 +Epoch [2500/4000] Training metric {'Train/mean dice_metric': 0.9973049163818359, 'Train/mean miou_metric': 0.9943480491638184, 'Train/mean f1': 0.9925492405891418, 'Train/mean precision': 0.987960934638977, 'Train/mean recall': 0.9971803426742554, 'Train/mean hd95_metric': 0.9594026803970337} +Epoch [2500/4000] Validation [1/4] Loss: 0.34477 focal_loss 0.27748 dice_loss 0.06729 +Epoch [2500/4000] Validation [2/4] Loss: 0.41518 focal_loss 0.29090 dice_loss 0.12428 +Epoch [2500/4000] Validation [3/4] Loss: 0.44704 focal_loss 0.35001 dice_loss 0.09703 +Epoch [2500/4000] Validation [4/4] Loss: 0.29905 focal_loss 0.20548 dice_loss 0.09357 +Epoch [2500/4000] Validation metric {'Val/mean dice_metric': 0.9725974798202515, 'Val/mean miou_metric': 0.9578114748001099, 'Val/mean f1': 0.9754742383956909, 'Val/mean precision': 0.974267303943634, 'Val/mean recall': 0.9766842126846313, 'Val/mean hd95_metric': 5.490874290466309} +Cheakpoint... +Epoch [2500/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725974798202515, 'Val/mean miou_metric': 0.9578114748001099, 'Val/mean f1': 0.9754742383956909, 'Val/mean precision': 0.974267303943634, 'Val/mean recall': 0.9766842126846313, 'Val/mean hd95_metric': 5.490874290466309} +Epoch [2501/4000] Training [1/16] Loss: 0.00377 +Epoch [2501/4000] Training [2/16] Loss: 0.00378 +Epoch [2501/4000] Training [3/16] Loss: 0.00561 +Epoch [2501/4000] Training [4/16] Loss: 0.00452 +Epoch [2501/4000] Training [5/16] Loss: 0.00501 +Epoch [2501/4000] Training [6/16] Loss: 0.00502 +Epoch [2501/4000] Training [7/16] Loss: 0.00562 +Epoch [2501/4000] Training [8/16] Loss: 0.00391 +Epoch [2501/4000] Training [9/16] Loss: 0.00496 +Epoch [2501/4000] Training [10/16] Loss: 0.00405 +Epoch [2501/4000] Training [11/16] Loss: 0.00397 +Epoch [2501/4000] Training [12/16] Loss: 0.00349 +Epoch [2501/4000] Training [13/16] Loss: 0.00415 +Epoch [2501/4000] Training [14/16] Loss: 0.00369 +Epoch [2501/4000] Training [15/16] Loss: 0.00320 +Epoch [2501/4000] Training [16/16] Loss: 0.00394 +Epoch [2501/4000] Training metric {'Train/mean dice_metric': 0.9973755478858948, 'Train/mean miou_metric': 0.9944926500320435, 'Train/mean f1': 0.9928001165390015, 'Train/mean precision': 0.9883259534835815, 'Train/mean recall': 0.997314989566803, 'Train/mean hd95_metric': 0.951617956161499} +Epoch [2501/4000] Validation [1/4] Loss: 0.30722 focal_loss 0.23685 dice_loss 0.07037 +Epoch [2501/4000] Validation [2/4] Loss: 0.82294 focal_loss 0.58291 dice_loss 0.24003 +Epoch [2501/4000] Validation [3/4] Loss: 0.40666 focal_loss 0.31316 dice_loss 0.09350 +Epoch [2501/4000] Validation [4/4] Loss: 0.33521 focal_loss 0.22829 dice_loss 0.10691 +Epoch [2501/4000] Validation metric {'Val/mean dice_metric': 0.970681369304657, 'Val/mean miou_metric': 0.9558701515197754, 'Val/mean f1': 0.9753562808036804, 'Val/mean precision': 0.9752146005630493, 'Val/mean recall': 0.9754980206489563, 'Val/mean hd95_metric': 5.705540180206299} +Cheakpoint... +Epoch [2501/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970681369304657, 'Val/mean miou_metric': 0.9558701515197754, 'Val/mean f1': 0.9753562808036804, 'Val/mean precision': 0.9752146005630493, 'Val/mean recall': 0.9754980206489563, 'Val/mean hd95_metric': 5.705540180206299} +Epoch [2502/4000] Training [1/16] Loss: 0.00358 +Epoch [2502/4000] Training [2/16] Loss: 0.00430 +Epoch [2502/4000] Training [3/16] Loss: 0.00368 +Epoch [2502/4000] Training [4/16] Loss: 0.00524 +Epoch [2502/4000] Training [5/16] Loss: 0.00489 +Epoch [2502/4000] Training [6/16] Loss: 0.00459 +Epoch [2502/4000] Training [7/16] Loss: 0.00643 +Epoch [2502/4000] Training [8/16] Loss: 0.00398 +Epoch [2502/4000] Training [9/16] Loss: 0.00401 +Epoch [2502/4000] Training [10/16] Loss: 0.00420 +Epoch [2502/4000] Training [11/16] Loss: 0.00431 +Epoch [2502/4000] Training [12/16] Loss: 0.00379 +Epoch [2502/4000] Training [13/16] Loss: 0.00358 +Epoch [2502/4000] Training [14/16] Loss: 0.00486 +Epoch [2502/4000] Training [15/16] Loss: 0.00541 +Epoch [2502/4000] Training [16/16] Loss: 0.00327 +Epoch [2502/4000] Training metric {'Train/mean dice_metric': 0.9972549676895142, 'Train/mean miou_metric': 0.9942524433135986, 'Train/mean f1': 0.9926276206970215, 'Train/mean precision': 0.9880144000053406, 'Train/mean recall': 0.9972841143608093, 'Train/mean hd95_metric': 0.9477394819259644} +Epoch [2502/4000] Validation [1/4] Loss: 0.37889 focal_loss 0.30063 dice_loss 0.07826 +Epoch [2502/4000] Validation [2/4] Loss: 0.42086 focal_loss 0.28803 dice_loss 0.13284 +Epoch [2502/4000] Validation [3/4] Loss: 0.47665 focal_loss 0.37575 dice_loss 0.10090 +Epoch [2502/4000] Validation [4/4] Loss: 0.42514 focal_loss 0.31265 dice_loss 0.11249 +Epoch [2502/4000] Validation metric {'Val/mean dice_metric': 0.9734352231025696, 'Val/mean miou_metric': 0.9577974081039429, 'Val/mean f1': 0.9753687381744385, 'Val/mean precision': 0.9743745923042297, 'Val/mean recall': 0.9763649702072144, 'Val/mean hd95_metric': 5.110785007476807} +Cheakpoint... +Epoch [2502/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734352231025696, 'Val/mean miou_metric': 0.9577974081039429, 'Val/mean f1': 0.9753687381744385, 'Val/mean precision': 0.9743745923042297, 'Val/mean recall': 0.9763649702072144, 'Val/mean hd95_metric': 5.110785007476807} +Epoch [2503/4000] Training [1/16] Loss: 0.00399 +Epoch [2503/4000] Training [2/16] Loss: 0.00576 +Epoch [2503/4000] Training [3/16] Loss: 0.00487 +Epoch [2503/4000] Training [4/16] Loss: 0.00424 +Epoch [2503/4000] Training [5/16] Loss: 0.00341 +Epoch [2503/4000] Training [6/16] Loss: 0.00267 +Epoch [2503/4000] Training [7/16] Loss: 0.00325 +Epoch [2503/4000] Training [8/16] Loss: 0.00367 +Epoch [2503/4000] Training [9/16] Loss: 0.00450 +Epoch [2503/4000] Training [10/16] Loss: 0.00429 +Epoch [2503/4000] Training [11/16] Loss: 0.00381 +Epoch [2503/4000] Training [12/16] Loss: 0.00479 +Epoch [2503/4000] Training [13/16] Loss: 0.00439 +Epoch [2503/4000] Training [14/16] Loss: 0.00444 +Epoch [2503/4000] Training [15/16] Loss: 0.00306 +Epoch [2503/4000] Training [16/16] Loss: 0.00472 +Epoch [2503/4000] Training metric {'Train/mean dice_metric': 0.9974255561828613, 'Train/mean miou_metric': 0.9945582151412964, 'Train/mean f1': 0.9920215010643005, 'Train/mean precision': 0.9867988228797913, 'Train/mean recall': 0.9972997903823853, 'Train/mean hd95_metric': 0.9484652280807495} +Epoch [2503/4000] Validation [1/4] Loss: 0.38649 focal_loss 0.31975 dice_loss 0.06674 +Epoch [2503/4000] Validation [2/4] Loss: 0.42894 focal_loss 0.28892 dice_loss 0.14002 +Epoch [2503/4000] Validation [3/4] Loss: 0.43380 focal_loss 0.33431 dice_loss 0.09948 +Epoch [2503/4000] Validation [4/4] Loss: 0.28586 focal_loss 0.19383 dice_loss 0.09203 +Epoch [2503/4000] Validation metric {'Val/mean dice_metric': 0.9728468060493469, 'Val/mean miou_metric': 0.9577943682670593, 'Val/mean f1': 0.975043535232544, 'Val/mean precision': 0.9729803204536438, 'Val/mean recall': 0.9771153926849365, 'Val/mean hd95_metric': 5.0586256980896} +Cheakpoint... +Epoch [2503/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728468060493469, 'Val/mean miou_metric': 0.9577943682670593, 'Val/mean f1': 0.975043535232544, 'Val/mean precision': 0.9729803204536438, 'Val/mean recall': 0.9771153926849365, 'Val/mean hd95_metric': 5.0586256980896} +Epoch [2504/4000] Training [1/16] Loss: 0.00691 +Epoch [2504/4000] Training [2/16] Loss: 0.00415 +Epoch [2504/4000] Training [3/16] Loss: 0.00394 +Epoch [2504/4000] Training [4/16] Loss: 0.00489 +Epoch [2504/4000] Training [5/16] Loss: 0.00504 +Epoch [2504/4000] Training [6/16] Loss: 0.00430 +Epoch [2504/4000] Training [7/16] Loss: 0.00398 +Epoch [2504/4000] Training [8/16] Loss: 0.00575 +Epoch [2504/4000] Training [9/16] Loss: 0.00395 +Epoch [2504/4000] Training [10/16] Loss: 0.00452 +Epoch [2504/4000] Training [11/16] Loss: 0.00463 +Epoch [2504/4000] Training [12/16] Loss: 0.00379 +Epoch [2504/4000] Training [13/16] Loss: 0.00515 +Epoch [2504/4000] Training [14/16] Loss: 0.00427 +Epoch [2504/4000] Training [15/16] Loss: 0.00419 +Epoch [2504/4000] Training [16/16] Loss: 0.00412 +Epoch [2504/4000] Training metric {'Train/mean dice_metric': 0.997146487236023, 'Train/mean miou_metric': 0.9940436482429504, 'Train/mean f1': 0.9926487803459167, 'Train/mean precision': 0.9881356954574585, 'Train/mean recall': 0.9972032904624939, 'Train/mean hd95_metric': 0.9661675691604614} +Epoch [2504/4000] Validation [1/4] Loss: 0.32692 focal_loss 0.25779 dice_loss 0.06913 +Epoch [2504/4000] Validation [2/4] Loss: 0.70565 focal_loss 0.50248 dice_loss 0.20317 +Epoch [2504/4000] Validation [3/4] Loss: 0.42246 focal_loss 0.32580 dice_loss 0.09665 +Epoch [2504/4000] Validation [4/4] Loss: 0.46178 focal_loss 0.32343 dice_loss 0.13835 +Epoch [2504/4000] Validation metric {'Val/mean dice_metric': 0.9714420437812805, 'Val/mean miou_metric': 0.9557317495346069, 'Val/mean f1': 0.9739729166030884, 'Val/mean precision': 0.9716874957084656, 'Val/mean recall': 0.9762690663337708, 'Val/mean hd95_metric': 5.530035972595215} +Cheakpoint... +Epoch [2504/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714420437812805, 'Val/mean miou_metric': 0.9557317495346069, 'Val/mean f1': 0.9739729166030884, 'Val/mean precision': 0.9716874957084656, 'Val/mean recall': 0.9762690663337708, 'Val/mean hd95_metric': 5.530035972595215} +Epoch [2505/4000] Training [1/16] Loss: 0.00406 +Epoch [2505/4000] Training [2/16] Loss: 0.00370 +Epoch [2505/4000] Training [3/16] Loss: 0.00568 +Epoch [2505/4000] Training [4/16] Loss: 0.00296 +Epoch [2505/4000] Training [5/16] Loss: 0.00508 +Epoch [2505/4000] Training [6/16] Loss: 0.00488 +Epoch [2505/4000] Training [7/16] Loss: 0.00316 +Epoch [2505/4000] Training [8/16] Loss: 0.00375 +Epoch [2505/4000] Training [9/16] Loss: 0.00473 +Epoch [2505/4000] Training [10/16] Loss: 0.00498 +Epoch [2505/4000] Training [11/16] Loss: 0.00518 +Epoch [2505/4000] Training [12/16] Loss: 0.00551 +Epoch [2505/4000] Training [13/16] Loss: 0.00348 +Epoch [2505/4000] Training [14/16] Loss: 0.00408 +Epoch [2505/4000] Training [15/16] Loss: 0.00509 +Epoch [2505/4000] Training [16/16] Loss: 0.00416 +Epoch [2505/4000] Training metric {'Train/mean dice_metric': 0.9972231388092041, 'Train/mean miou_metric': 0.9941913485527039, 'Train/mean f1': 0.9926855564117432, 'Train/mean precision': 0.9881716966629028, 'Train/mean recall': 0.9972408413887024, 'Train/mean hd95_metric': 0.9577425718307495} +Epoch [2505/4000] Validation [1/4] Loss: 0.29110 focal_loss 0.22780 dice_loss 0.06330 +Epoch [2505/4000] Validation [2/4] Loss: 0.66984 focal_loss 0.48487 dice_loss 0.18498 +Epoch [2505/4000] Validation [3/4] Loss: 0.40441 focal_loss 0.31011 dice_loss 0.09430 +Epoch [2505/4000] Validation [4/4] Loss: 0.24953 focal_loss 0.16856 dice_loss 0.08097 +Epoch [2505/4000] Validation metric {'Val/mean dice_metric': 0.9703875780105591, 'Val/mean miou_metric': 0.955386757850647, 'Val/mean f1': 0.9751118421554565, 'Val/mean precision': 0.973148763179779, 'Val/mean recall': 0.9770828485488892, 'Val/mean hd95_metric': 5.8225417137146} +Cheakpoint... +Epoch [2505/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703875780105591, 'Val/mean miou_metric': 0.955386757850647, 'Val/mean f1': 0.9751118421554565, 'Val/mean precision': 0.973148763179779, 'Val/mean recall': 0.9770828485488892, 'Val/mean hd95_metric': 5.8225417137146} +Epoch [2506/4000] Training [1/16] Loss: 0.00372 +Epoch [2506/4000] Training [2/16] Loss: 0.00319 +Epoch [2506/4000] Training [3/16] Loss: 0.00398 +Epoch [2506/4000] Training [4/16] Loss: 0.00312 +Epoch [2506/4000] Training [5/16] Loss: 0.00397 +Epoch [2506/4000] Training [6/16] Loss: 0.00345 +Epoch [2506/4000] Training [7/16] Loss: 0.00420 +Epoch [2506/4000] Training [8/16] Loss: 0.00485 +Epoch [2506/4000] Training [9/16] Loss: 0.00295 +Epoch [2506/4000] Training [10/16] Loss: 0.00382 +Epoch [2506/4000] Training [11/16] Loss: 0.00358 +Epoch [2506/4000] Training [12/16] Loss: 0.00490 +Epoch [2506/4000] Training [13/16] Loss: 0.00544 +Epoch [2506/4000] Training [14/16] Loss: 0.00454 +Epoch [2506/4000] Training [15/16] Loss: 0.00558 +Epoch [2506/4000] Training [16/16] Loss: 0.00348 +Epoch [2506/4000] Training metric {'Train/mean dice_metric': 0.9973548650741577, 'Train/mean miou_metric': 0.9944455623626709, 'Train/mean f1': 0.9925967454910278, 'Train/mean precision': 0.9879555702209473, 'Train/mean recall': 0.9972817301750183, 'Train/mean hd95_metric': 0.9560824036598206} +Epoch [2506/4000] Validation [1/4] Loss: 0.39164 focal_loss 0.32320 dice_loss 0.06843 +Epoch [2506/4000] Validation [2/4] Loss: 0.70890 focal_loss 0.51483 dice_loss 0.19407 +Epoch [2506/4000] Validation [3/4] Loss: 0.52869 focal_loss 0.41721 dice_loss 0.11148 +Epoch [2506/4000] Validation [4/4] Loss: 0.39159 focal_loss 0.26015 dice_loss 0.13144 +Epoch [2506/4000] Validation metric {'Val/mean dice_metric': 0.9712623357772827, 'Val/mean miou_metric': 0.955600380897522, 'Val/mean f1': 0.9742374420166016, 'Val/mean precision': 0.9744749665260315, 'Val/mean recall': 0.9740000367164612, 'Val/mean hd95_metric': 5.573931694030762} +Cheakpoint... +Epoch [2506/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712623357772827, 'Val/mean miou_metric': 0.955600380897522, 'Val/mean f1': 0.9742374420166016, 'Val/mean precision': 0.9744749665260315, 'Val/mean recall': 0.9740000367164612, 'Val/mean hd95_metric': 5.573931694030762} +Epoch [2507/4000] Training [1/16] Loss: 0.00551 +Epoch [2507/4000] Training [2/16] Loss: 0.00366 +Epoch [2507/4000] Training [3/16] Loss: 0.00459 +Epoch [2507/4000] Training [4/16] Loss: 0.00642 +Epoch [2507/4000] Training [5/16] Loss: 0.00322 +Epoch [2507/4000] Training [6/16] Loss: 0.00384 +Epoch [2507/4000] Training [7/16] Loss: 0.00385 +Epoch [2507/4000] Training [8/16] Loss: 0.00568 +Epoch [2507/4000] Training [9/16] Loss: 0.00345 +Epoch [2507/4000] Training [10/16] Loss: 0.00528 +Epoch [2507/4000] Training [11/16] Loss: 0.00398 +Epoch [2507/4000] Training [12/16] Loss: 0.00436 +Epoch [2507/4000] Training [13/16] Loss: 0.00375 +Epoch [2507/4000] Training [14/16] Loss: 0.00389 +Epoch [2507/4000] Training [15/16] Loss: 0.00384 +Epoch [2507/4000] Training [16/16] Loss: 0.00416 +Epoch [2507/4000] Training metric {'Train/mean dice_metric': 0.9972389936447144, 'Train/mean miou_metric': 0.9942222237586975, 'Train/mean f1': 0.9926020503044128, 'Train/mean precision': 0.9879836440086365, 'Train/mean recall': 0.9972637891769409, 'Train/mean hd95_metric': 0.9645837545394897} +Epoch [2507/4000] Validation [1/4] Loss: 0.29416 focal_loss 0.23411 dice_loss 0.06005 +Epoch [2507/4000] Validation [2/4] Loss: 0.74666 focal_loss 0.55682 dice_loss 0.18984 +Epoch [2507/4000] Validation [3/4] Loss: 0.38199 focal_loss 0.28833 dice_loss 0.09367 +Epoch [2507/4000] Validation [4/4] Loss: 0.37015 focal_loss 0.25704 dice_loss 0.11311 +Epoch [2507/4000] Validation metric {'Val/mean dice_metric': 0.9714053869247437, 'Val/mean miou_metric': 0.9562585949897766, 'Val/mean f1': 0.974377453327179, 'Val/mean precision': 0.9722620248794556, 'Val/mean recall': 0.9765021800994873, 'Val/mean hd95_metric': 5.916828632354736} +Cheakpoint... +Epoch [2507/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714053869247437, 'Val/mean miou_metric': 0.9562585949897766, 'Val/mean f1': 0.974377453327179, 'Val/mean precision': 0.9722620248794556, 'Val/mean recall': 0.9765021800994873, 'Val/mean hd95_metric': 5.916828632354736} +Epoch [2508/4000] Training [1/16] Loss: 0.00451 +Epoch [2508/4000] Training [2/16] Loss: 0.00410 +Epoch [2508/4000] Training [3/16] Loss: 0.00369 +Epoch [2508/4000] Training [4/16] Loss: 0.00368 +Epoch [2508/4000] Training [5/16] Loss: 0.00350 +Epoch [2508/4000] Training [6/16] Loss: 0.00348 +Epoch [2508/4000] Training [7/16] Loss: 0.00447 +Epoch [2508/4000] Training [8/16] Loss: 0.00499 +Epoch [2508/4000] Training [9/16] Loss: 0.00418 +Epoch [2508/4000] Training [10/16] Loss: 0.00321 +Epoch [2508/4000] Training [11/16] Loss: 0.00390 +Epoch [2508/4000] Training [12/16] Loss: 0.00494 +Epoch [2508/4000] Training [13/16] Loss: 0.00510 +Epoch [2508/4000] Training [14/16] Loss: 0.00370 +Epoch [2508/4000] Training [15/16] Loss: 0.00336 +Epoch [2508/4000] Training [16/16] Loss: 0.00380 +Epoch [2508/4000] Training metric {'Train/mean dice_metric': 0.9973500370979309, 'Train/mean miou_metric': 0.9944469928741455, 'Train/mean f1': 0.9927967190742493, 'Train/mean precision': 0.9882869720458984, 'Train/mean recall': 0.9973477721214294, 'Train/mean hd95_metric': 0.9566260576248169} +Epoch [2508/4000] Validation [1/4] Loss: 0.32953 focal_loss 0.26147 dice_loss 0.06806 +Epoch [2508/4000] Validation [2/4] Loss: 0.36110 focal_loss 0.23982 dice_loss 0.12128 +Epoch [2508/4000] Validation [3/4] Loss: 0.39399 focal_loss 0.30032 dice_loss 0.09366 +Epoch [2508/4000] Validation [4/4] Loss: 0.27643 focal_loss 0.17607 dice_loss 0.10036 +Epoch [2508/4000] Validation metric {'Val/mean dice_metric': 0.974972128868103, 'Val/mean miou_metric': 0.9596366882324219, 'Val/mean f1': 0.9762634038925171, 'Val/mean precision': 0.9738761782646179, 'Val/mean recall': 0.9786624312400818, 'Val/mean hd95_metric': 4.918643951416016} +Cheakpoint... +Epoch [2508/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974972128868103, 'Val/mean miou_metric': 0.9596366882324219, 'Val/mean f1': 0.9762634038925171, 'Val/mean precision': 0.9738761782646179, 'Val/mean recall': 0.9786624312400818, 'Val/mean hd95_metric': 4.918643951416016} +Epoch [2509/4000] Training [1/16] Loss: 0.00398 +Epoch [2509/4000] Training [2/16] Loss: 0.00379 +Epoch [2509/4000] Training [3/16] Loss: 0.00372 +Epoch [2509/4000] Training [4/16] Loss: 0.00479 +Epoch [2509/4000] Training [5/16] Loss: 0.00356 +Epoch [2509/4000] Training [6/16] Loss: 0.00541 +Epoch [2509/4000] Training [7/16] Loss: 0.00347 +Epoch [2509/4000] Training [8/16] Loss: 0.00466 +Epoch [2509/4000] Training [9/16] Loss: 0.00572 +Epoch [2509/4000] Training [10/16] Loss: 0.00402 +Epoch [2509/4000] Training [11/16] Loss: 0.00360 +Epoch [2509/4000] Training [12/16] Loss: 0.00474 +Epoch [2509/4000] Training [13/16] Loss: 0.00356 +Epoch [2509/4000] Training [14/16] Loss: 0.00608 +Epoch [2509/4000] Training [15/16] Loss: 0.00691 +Epoch [2509/4000] Training [16/16] Loss: 0.00510 +Epoch [2509/4000] Training metric {'Train/mean dice_metric': 0.99713134765625, 'Train/mean miou_metric': 0.9940148591995239, 'Train/mean f1': 0.9925983548164368, 'Train/mean precision': 0.9879649877548218, 'Train/mean recall': 0.9972753524780273, 'Train/mean hd95_metric': 0.9605602025985718} +Epoch [2509/4000] Validation [1/4] Loss: 0.30617 focal_loss 0.24140 dice_loss 0.06477 +Epoch [2509/4000] Validation [2/4] Loss: 0.38360 focal_loss 0.26318 dice_loss 0.12042 +Epoch [2509/4000] Validation [3/4] Loss: 0.45583 focal_loss 0.35942 dice_loss 0.09641 +Epoch [2509/4000] Validation [4/4] Loss: 0.28413 focal_loss 0.19307 dice_loss 0.09106 +Epoch [2509/4000] Validation metric {'Val/mean dice_metric': 0.9724529385566711, 'Val/mean miou_metric': 0.9572288393974304, 'Val/mean f1': 0.9747885465621948, 'Val/mean precision': 0.9719511270523071, 'Val/mean recall': 0.9776425361633301, 'Val/mean hd95_metric': 5.371979236602783} +Cheakpoint... +Epoch [2509/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724529385566711, 'Val/mean miou_metric': 0.9572288393974304, 'Val/mean f1': 0.9747885465621948, 'Val/mean precision': 0.9719511270523071, 'Val/mean recall': 0.9776425361633301, 'Val/mean hd95_metric': 5.371979236602783} +Epoch [2510/4000] Training [1/16] Loss: 0.00325 +Epoch [2510/4000] Training [2/16] Loss: 0.00339 +Epoch [2510/4000] Training [3/16] Loss: 0.00407 +Epoch [2510/4000] Training [4/16] Loss: 0.00393 +Epoch [2510/4000] Training [5/16] Loss: 0.00384 +Epoch [2510/4000] Training [6/16] Loss: 0.00434 +Epoch [2510/4000] Training [7/16] Loss: 0.00400 +Epoch [2510/4000] Training [8/16] Loss: 0.00426 +Epoch [2510/4000] Training [9/16] Loss: 0.00471 +Epoch [2510/4000] Training [10/16] Loss: 0.00438 +Epoch [2510/4000] Training [11/16] Loss: 0.00553 +Epoch [2510/4000] Training [12/16] Loss: 0.00481 +Epoch [2510/4000] Training [13/16] Loss: 0.00332 +Epoch [2510/4000] Training [14/16] Loss: 0.00542 +Epoch [2510/4000] Training [15/16] Loss: 0.00425 +Epoch [2510/4000] Training [16/16] Loss: 0.00326 +Epoch [2510/4000] Training metric {'Train/mean dice_metric': 0.997329592704773, 'Train/mean miou_metric': 0.9943971633911133, 'Train/mean f1': 0.9926909804344177, 'Train/mean precision': 0.9881511926651001, 'Train/mean recall': 0.9972726702690125, 'Train/mean hd95_metric': 0.9482699036598206} +Epoch [2510/4000] Validation [1/4] Loss: 0.31922 focal_loss 0.25219 dice_loss 0.06703 +Epoch [2510/4000] Validation [2/4] Loss: 0.42215 focal_loss 0.28735 dice_loss 0.13480 +Epoch [2510/4000] Validation [3/4] Loss: 0.42785 focal_loss 0.33355 dice_loss 0.09429 +Epoch [2510/4000] Validation [4/4] Loss: 0.37927 focal_loss 0.25975 dice_loss 0.11952 +Epoch [2510/4000] Validation metric {'Val/mean dice_metric': 0.9728191494941711, 'Val/mean miou_metric': 0.9572509527206421, 'Val/mean f1': 0.9756459593772888, 'Val/mean precision': 0.9732470512390137, 'Val/mean recall': 0.9780567288398743, 'Val/mean hd95_metric': 5.76692533493042} +Cheakpoint... +Epoch [2510/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728191494941711, 'Val/mean miou_metric': 0.9572509527206421, 'Val/mean f1': 0.9756459593772888, 'Val/mean precision': 0.9732470512390137, 'Val/mean recall': 0.9780567288398743, 'Val/mean hd95_metric': 5.76692533493042} +Epoch [2511/4000] Training [1/16] Loss: 0.00363 +Epoch [2511/4000] Training [2/16] Loss: 0.00613 +Epoch [2511/4000] Training [3/16] Loss: 0.00630 +Epoch [2511/4000] Training [4/16] Loss: 0.00358 +Epoch [2511/4000] Training [5/16] Loss: 0.00599 +Epoch [2511/4000] Training [6/16] Loss: 0.00567 +Epoch [2511/4000] Training [7/16] Loss: 0.00392 +Epoch [2511/4000] Training [8/16] Loss: 0.00495 +Epoch [2511/4000] Training [9/16] Loss: 0.00429 +Epoch [2511/4000] Training [10/16] Loss: 0.00386 +Epoch [2511/4000] Training [11/16] Loss: 0.00367 +Epoch [2511/4000] Training [12/16] Loss: 0.00508 +Epoch [2511/4000] Training [13/16] Loss: 0.00471 +Epoch [2511/4000] Training [14/16] Loss: 0.00466 +Epoch [2511/4000] Training [15/16] Loss: 0.00391 +Epoch [2511/4000] Training [16/16] Loss: 0.00401 +Epoch [2511/4000] Training metric {'Train/mean dice_metric': 0.997065544128418, 'Train/mean miou_metric': 0.9938820600509644, 'Train/mean f1': 0.992631196975708, 'Train/mean precision': 0.9881766438484192, 'Train/mean recall': 0.997126042842865, 'Train/mean hd95_metric': 0.9592350721359253} +Epoch [2511/4000] Validation [1/4] Loss: 0.40929 focal_loss 0.33446 dice_loss 0.07484 +Epoch [2511/4000] Validation [2/4] Loss: 0.88585 focal_loss 0.69532 dice_loss 0.19053 +Epoch [2511/4000] Validation [3/4] Loss: 0.45936 focal_loss 0.35428 dice_loss 0.10508 +Epoch [2511/4000] Validation [4/4] Loss: 0.30397 focal_loss 0.20874 dice_loss 0.09523 +Epoch [2511/4000] Validation metric {'Val/mean dice_metric': 0.9713279604911804, 'Val/mean miou_metric': 0.9563772082328796, 'Val/mean f1': 0.9751356244087219, 'Val/mean precision': 0.9738081097602844, 'Val/mean recall': 0.9764666557312012, 'Val/mean hd95_metric': 5.437893390655518} +Cheakpoint... +Epoch [2511/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713279604911804, 'Val/mean miou_metric': 0.9563772082328796, 'Val/mean f1': 0.9751356244087219, 'Val/mean precision': 0.9738081097602844, 'Val/mean recall': 0.9764666557312012, 'Val/mean hd95_metric': 5.437893390655518} +Epoch [2512/4000] Training [1/16] Loss: 0.00550 +Epoch [2512/4000] Training [2/16] Loss: 0.00493 +Epoch [2512/4000] Training [3/16] Loss: 0.00377 +Epoch [2512/4000] Training [4/16] Loss: 0.00458 +Epoch [2512/4000] Training [5/16] Loss: 0.00447 +Epoch [2512/4000] Training [6/16] Loss: 0.00445 +Epoch [2512/4000] Training [7/16] Loss: 0.00534 +Epoch [2512/4000] Training [8/16] Loss: 0.00550 +Epoch [2512/4000] Training [9/16] Loss: 0.00318 +Epoch [2512/4000] Training [10/16] Loss: 0.00342 +Epoch [2512/4000] Training [11/16] Loss: 0.00534 +Epoch [2512/4000] Training [12/16] Loss: 0.00418 +Epoch [2512/4000] Training [13/16] Loss: 0.00644 +Epoch [2512/4000] Training [14/16] Loss: 0.00517 +Epoch [2512/4000] Training [15/16] Loss: 0.00408 +Epoch [2512/4000] Training [16/16] Loss: 0.00405 +Epoch [2512/4000] Training metric {'Train/mean dice_metric': 0.9970659017562866, 'Train/mean miou_metric': 0.9938769340515137, 'Train/mean f1': 0.9923719763755798, 'Train/mean precision': 0.9876448512077332, 'Train/mean recall': 0.9971445798873901, 'Train/mean hd95_metric': 0.9748601913452148} +Epoch [2512/4000] Validation [1/4] Loss: 0.31798 focal_loss 0.25324 dice_loss 0.06474 +Epoch [2512/4000] Validation [2/4] Loss: 0.79266 focal_loss 0.49575 dice_loss 0.29691 +Epoch [2512/4000] Validation [3/4] Loss: 0.42960 focal_loss 0.32747 dice_loss 0.10214 +Epoch [2512/4000] Validation [4/4] Loss: 0.40597 focal_loss 0.28242 dice_loss 0.12355 +Epoch [2512/4000] Validation metric {'Val/mean dice_metric': 0.9702008962631226, 'Val/mean miou_metric': 0.9550122022628784, 'Val/mean f1': 0.97420734167099, 'Val/mean precision': 0.9735522866249084, 'Val/mean recall': 0.9748631715774536, 'Val/mean hd95_metric': 5.395330905914307} +Cheakpoint... +Epoch [2512/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702008962631226, 'Val/mean miou_metric': 0.9550122022628784, 'Val/mean f1': 0.97420734167099, 'Val/mean precision': 0.9735522866249084, 'Val/mean recall': 0.9748631715774536, 'Val/mean hd95_metric': 5.395330905914307} +Epoch [2513/4000] Training [1/16] Loss: 0.00614 +Epoch [2513/4000] Training [2/16] Loss: 0.00348 +Epoch [2513/4000] Training [3/16] Loss: 0.00384 +Epoch [2513/4000] Training [4/16] Loss: 0.00451 +Epoch [2513/4000] Training [5/16] Loss: 0.00556 +Epoch [2513/4000] Training [6/16] Loss: 0.00408 +Epoch [2513/4000] Training [7/16] Loss: 0.00416 +Epoch [2513/4000] Training [8/16] Loss: 0.00306 +Epoch [2513/4000] Training [9/16] Loss: 0.00463 +Epoch [2513/4000] Training [10/16] Loss: 0.00516 +Epoch [2513/4000] Training [11/16] Loss: 0.00465 +Epoch [2513/4000] Training [12/16] Loss: 0.00400 +Epoch [2513/4000] Training [13/16] Loss: 0.00608 +Epoch [2513/4000] Training [14/16] Loss: 0.00368 +Epoch [2513/4000] Training [15/16] Loss: 0.00437 +Epoch [2513/4000] Training [16/16] Loss: 0.00328 +Epoch [2513/4000] Training metric {'Train/mean dice_metric': 0.9973124861717224, 'Train/mean miou_metric': 0.9943708181381226, 'Train/mean f1': 0.9927105903625488, 'Train/mean precision': 0.9881666302680969, 'Train/mean recall': 0.9972965717315674, 'Train/mean hd95_metric': 0.9398996829986572} +Epoch [2513/4000] Validation [1/4] Loss: 0.34784 focal_loss 0.27225 dice_loss 0.07559 +Epoch [2513/4000] Validation [2/4] Loss: 0.86717 focal_loss 0.66676 dice_loss 0.20041 +Epoch [2513/4000] Validation [3/4] Loss: 0.42056 focal_loss 0.33132 dice_loss 0.08924 +Epoch [2513/4000] Validation [4/4] Loss: 0.42045 focal_loss 0.29913 dice_loss 0.12132 +Epoch [2513/4000] Validation metric {'Val/mean dice_metric': 0.9713765978813171, 'Val/mean miou_metric': 0.9560467004776001, 'Val/mean f1': 0.9750286340713501, 'Val/mean precision': 0.9748011827468872, 'Val/mean recall': 0.9752562046051025, 'Val/mean hd95_metric': 5.128314971923828} +Cheakpoint... +Epoch [2513/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713765978813171, 'Val/mean miou_metric': 0.9560467004776001, 'Val/mean f1': 0.9750286340713501, 'Val/mean precision': 0.9748011827468872, 'Val/mean recall': 0.9752562046051025, 'Val/mean hd95_metric': 5.128314971923828} +Epoch [2514/4000] Training [1/16] Loss: 0.00311 +Epoch [2514/4000] Training [2/16] Loss: 0.00424 +Epoch [2514/4000] Training [3/16] Loss: 0.00310 +Epoch [2514/4000] Training [4/16] Loss: 0.00589 +Epoch [2514/4000] Training [5/16] Loss: 0.00427 +Epoch [2514/4000] Training [6/16] Loss: 0.00396 +Epoch [2514/4000] Training [7/16] Loss: 0.00274 +Epoch [2514/4000] Training [8/16] Loss: 0.00490 +Epoch [2514/4000] Training [9/16] Loss: 0.00535 +Epoch [2514/4000] Training [10/16] Loss: 0.00362 +Epoch [2514/4000] Training [11/16] Loss: 0.00377 +Epoch [2514/4000] Training [12/16] Loss: 0.00378 +Epoch [2514/4000] Training [13/16] Loss: 0.00376 +Epoch [2514/4000] Training [14/16] Loss: 0.00375 +Epoch [2514/4000] Training [15/16] Loss: 0.00378 +Epoch [2514/4000] Training [16/16] Loss: 0.00523 +Epoch [2514/4000] Training metric {'Train/mean dice_metric': 0.9974926710128784, 'Train/mean miou_metric': 0.9947275519371033, 'Train/mean f1': 0.9927850961685181, 'Train/mean precision': 0.9883019924163818, 'Train/mean recall': 0.9973090291023254, 'Train/mean hd95_metric': 0.9417668581008911} +Epoch [2514/4000] Validation [1/4] Loss: 0.32147 focal_loss 0.25581 dice_loss 0.06566 +Epoch [2514/4000] Validation [2/4] Loss: 0.61794 focal_loss 0.40870 dice_loss 0.20925 +Epoch [2514/4000] Validation [3/4] Loss: 0.41182 focal_loss 0.32207 dice_loss 0.08975 +Epoch [2514/4000] Validation [4/4] Loss: 0.49495 focal_loss 0.36358 dice_loss 0.13137 +Epoch [2514/4000] Validation metric {'Val/mean dice_metric': 0.9714096784591675, 'Val/mean miou_metric': 0.956291675567627, 'Val/mean f1': 0.9742936491966248, 'Val/mean precision': 0.9740616083145142, 'Val/mean recall': 0.9745256900787354, 'Val/mean hd95_metric': 5.428952217102051} +Cheakpoint... +Epoch [2514/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714096784591675, 'Val/mean miou_metric': 0.956291675567627, 'Val/mean f1': 0.9742936491966248, 'Val/mean precision': 0.9740616083145142, 'Val/mean recall': 0.9745256900787354, 'Val/mean hd95_metric': 5.428952217102051} +Epoch [2515/4000] Training [1/16] Loss: 0.00489 +Epoch [2515/4000] Training [2/16] Loss: 0.00522 +Epoch [2515/4000] Training [3/16] Loss: 0.00356 +Epoch [2515/4000] Training [4/16] Loss: 0.00500 +Epoch [2515/4000] Training [5/16] Loss: 0.00505 +Epoch [2515/4000] Training [6/16] Loss: 0.00409 +Epoch [2515/4000] Training [7/16] Loss: 0.00656 +Epoch [2515/4000] Training [8/16] Loss: 0.00433 +Epoch [2515/4000] Training [9/16] Loss: 0.00379 +Epoch [2515/4000] Training [10/16] Loss: 0.00471 +Epoch [2515/4000] Training [11/16] Loss: 0.00469 +Epoch [2515/4000] Training [12/16] Loss: 0.00747 +Epoch [2515/4000] Training [13/16] Loss: 0.00555 +Epoch [2515/4000] Training [14/16] Loss: 0.00533 +Epoch [2515/4000] Training [15/16] Loss: 0.00751 +Epoch [2515/4000] Training [16/16] Loss: 0.00405 +Epoch [2515/4000] Training metric {'Train/mean dice_metric': 0.9969210624694824, 'Train/mean miou_metric': 0.9935928583145142, 'Train/mean f1': 0.9924883842468262, 'Train/mean precision': 0.9879940748214722, 'Train/mean recall': 0.9970237612724304, 'Train/mean hd95_metric': 1.0241365432739258} +Epoch [2515/4000] Validation [1/4] Loss: 0.33873 focal_loss 0.27121 dice_loss 0.06752 +Epoch [2515/4000] Validation [2/4] Loss: 0.44042 focal_loss 0.29094 dice_loss 0.14948 +Epoch [2515/4000] Validation [3/4] Loss: 0.46229 focal_loss 0.36488 dice_loss 0.09741 +Epoch [2515/4000] Validation [4/4] Loss: 0.48909 focal_loss 0.36532 dice_loss 0.12376 +Epoch [2515/4000] Validation metric {'Val/mean dice_metric': 0.9717332720756531, 'Val/mean miou_metric': 0.9559572339057922, 'Val/mean f1': 0.9745091795921326, 'Val/mean precision': 0.9733951687812805, 'Val/mean recall': 0.97562575340271, 'Val/mean hd95_metric': 5.19276762008667} +Cheakpoint... +Epoch [2515/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717332720756531, 'Val/mean miou_metric': 0.9559572339057922, 'Val/mean f1': 0.9745091795921326, 'Val/mean precision': 0.9733951687812805, 'Val/mean recall': 0.97562575340271, 'Val/mean hd95_metric': 5.19276762008667} +Epoch [2516/4000] Training [1/16] Loss: 0.00600 +Epoch [2516/4000] Training [2/16] Loss: 0.00342 +Epoch [2516/4000] Training [3/16] Loss: 0.00386 +Epoch [2516/4000] Training [4/16] Loss: 0.00359 +Epoch [2516/4000] Training [5/16] Loss: 0.00572 +Epoch [2516/4000] Training [6/16] Loss: 0.00387 +Epoch [2516/4000] Training [7/16] Loss: 0.00351 +Epoch [2516/4000] Training [8/16] Loss: 0.00485 +Epoch [2516/4000] Training [9/16] Loss: 0.00360 +Epoch [2516/4000] Training [10/16] Loss: 0.00462 +Epoch [2516/4000] Training [11/16] Loss: 0.00474 +Epoch [2516/4000] Training [12/16] Loss: 0.00449 +Epoch [2516/4000] Training [13/16] Loss: 0.00382 +Epoch [2516/4000] Training [14/16] Loss: 0.00656 +Epoch [2516/4000] Training [15/16] Loss: 0.00368 +Epoch [2516/4000] Training [16/16] Loss: 0.00401 +Epoch [2516/4000] Training metric {'Train/mean dice_metric': 0.9972349405288696, 'Train/mean miou_metric': 0.9942128658294678, 'Train/mean f1': 0.9926063418388367, 'Train/mean precision': 0.9879315495491028, 'Train/mean recall': 0.997325599193573, 'Train/mean hd95_metric': 1.0551385879516602} +Epoch [2516/4000] Validation [1/4] Loss: 0.37744 focal_loss 0.30651 dice_loss 0.07093 +Epoch [2516/4000] Validation [2/4] Loss: 0.41267 focal_loss 0.27883 dice_loss 0.13383 +Epoch [2516/4000] Validation [3/4] Loss: 0.42153 focal_loss 0.32839 dice_loss 0.09313 +Epoch [2516/4000] Validation [4/4] Loss: 0.28184 focal_loss 0.19720 dice_loss 0.08464 +Epoch [2516/4000] Validation metric {'Val/mean dice_metric': 0.9709622263908386, 'Val/mean miou_metric': 0.955582320690155, 'Val/mean f1': 0.9741615653038025, 'Val/mean precision': 0.9716049432754517, 'Val/mean recall': 0.9767317175865173, 'Val/mean hd95_metric': 5.672857284545898} +Cheakpoint... +Epoch [2516/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709622263908386, 'Val/mean miou_metric': 0.955582320690155, 'Val/mean f1': 0.9741615653038025, 'Val/mean precision': 0.9716049432754517, 'Val/mean recall': 0.9767317175865173, 'Val/mean hd95_metric': 5.672857284545898} +Epoch [2517/4000] Training [1/16] Loss: 0.00472 +Epoch [2517/4000] Training [2/16] Loss: 0.00321 +Epoch [2517/4000] Training [3/16] Loss: 0.00426 +Epoch [2517/4000] Training [4/16] Loss: 0.00375 +Epoch [2517/4000] Training [5/16] Loss: 0.00397 +Epoch [2517/4000] Training [6/16] Loss: 0.00517 +Epoch [2517/4000] Training [7/16] Loss: 0.00400 +Epoch [2517/4000] Training [8/16] Loss: 0.00501 +Epoch [2517/4000] Training [9/16] Loss: 0.00472 +Epoch [2517/4000] Training [10/16] Loss: 0.01065 +Epoch [2517/4000] Training [11/16] Loss: 0.00490 +Epoch [2517/4000] Training [12/16] Loss: 0.00499 +Epoch [2517/4000] Training [13/16] Loss: 0.00364 +Epoch [2517/4000] Training [14/16] Loss: 0.00434 +Epoch [2517/4000] Training [15/16] Loss: 0.00347 +Epoch [2517/4000] Training [16/16] Loss: 0.00483 +Epoch [2517/4000] Training metric {'Train/mean dice_metric': 0.9971292018890381, 'Train/mean miou_metric': 0.9939857721328735, 'Train/mean f1': 0.992063045501709, 'Train/mean precision': 0.9870859384536743, 'Train/mean recall': 0.9970905780792236, 'Train/mean hd95_metric': 1.0062735080718994} +Epoch [2517/4000] Validation [1/4] Loss: 0.31010 focal_loss 0.24572 dice_loss 0.06439 +Epoch [2517/4000] Validation [2/4] Loss: 0.65137 focal_loss 0.45025 dice_loss 0.20112 +Epoch [2517/4000] Validation [3/4] Loss: 0.24084 focal_loss 0.17681 dice_loss 0.06403 +Epoch [2517/4000] Validation [4/4] Loss: 0.27946 focal_loss 0.19188 dice_loss 0.08757 +Epoch [2517/4000] Validation metric {'Val/mean dice_metric': 0.9713435173034668, 'Val/mean miou_metric': 0.9566084742546082, 'Val/mean f1': 0.9748508930206299, 'Val/mean precision': 0.9743192195892334, 'Val/mean recall': 0.9753832221031189, 'Val/mean hd95_metric': 5.207538604736328} +Cheakpoint... +Epoch [2517/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713435173034668, 'Val/mean miou_metric': 0.9566084742546082, 'Val/mean f1': 0.9748508930206299, 'Val/mean precision': 0.9743192195892334, 'Val/mean recall': 0.9753832221031189, 'Val/mean hd95_metric': 5.207538604736328} +Epoch [2518/4000] Training [1/16] Loss: 0.00435 +Epoch [2518/4000] Training [2/16] Loss: 0.00397 +Epoch [2518/4000] Training [3/16] Loss: 0.00436 +Epoch [2518/4000] Training [4/16] Loss: 0.00342 +Epoch [2518/4000] Training [5/16] Loss: 0.00519 +Epoch [2518/4000] Training [6/16] Loss: 0.00566 +Epoch [2518/4000] Training [7/16] Loss: 0.00577 +Epoch [2518/4000] Training [8/16] Loss: 0.00540 +Epoch [2518/4000] Training [9/16] Loss: 0.00562 +Epoch [2518/4000] Training [10/16] Loss: 0.00293 +Epoch [2518/4000] Training [11/16] Loss: 0.00363 +Epoch [2518/4000] Training [12/16] Loss: 0.00374 +Epoch [2518/4000] Training [13/16] Loss: 0.00797 +Epoch [2518/4000] Training [14/16] Loss: 0.00430 +Epoch [2518/4000] Training [15/16] Loss: 0.00411 +Epoch [2518/4000] Training [16/16] Loss: 0.00377 +Epoch [2518/4000] Training metric {'Train/mean dice_metric': 0.9971851110458374, 'Train/mean miou_metric': 0.9941166639328003, 'Train/mean f1': 0.9927194118499756, 'Train/mean precision': 0.9883219599723816, 'Train/mean recall': 0.9971562027931213, 'Train/mean hd95_metric': 0.9594534039497375} +Epoch [2518/4000] Validation [1/4] Loss: 0.30998 focal_loss 0.24675 dice_loss 0.06323 +Epoch [2518/4000] Validation [2/4] Loss: 0.57004 focal_loss 0.39783 dice_loss 0.17222 +Epoch [2518/4000] Validation [3/4] Loss: 0.44880 focal_loss 0.35622 dice_loss 0.09258 +Epoch [2518/4000] Validation [4/4] Loss: 0.60223 focal_loss 0.43927 dice_loss 0.16296 +Epoch [2518/4000] Validation metric {'Val/mean dice_metric': 0.970492959022522, 'Val/mean miou_metric': 0.9547693133354187, 'Val/mean f1': 0.9742599725723267, 'Val/mean precision': 0.9741489291191101, 'Val/mean recall': 0.9743711352348328, 'Val/mean hd95_metric': 5.603553771972656} +Cheakpoint... +Epoch [2518/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970492959022522, 'Val/mean miou_metric': 0.9547693133354187, 'Val/mean f1': 0.9742599725723267, 'Val/mean precision': 0.9741489291191101, 'Val/mean recall': 0.9743711352348328, 'Val/mean hd95_metric': 5.603553771972656} +Epoch [2519/4000] Training [1/16] Loss: 0.00528 +Epoch [2519/4000] Training [2/16] Loss: 0.00377 +Epoch [2519/4000] Training [3/16] Loss: 0.00598 +Epoch [2519/4000] Training [4/16] Loss: 0.00321 +Epoch [2519/4000] Training [5/16] Loss: 0.00502 +Epoch [2519/4000] Training [6/16] Loss: 0.00348 +Epoch [2519/4000] Training [7/16] Loss: 0.00310 +Epoch [2519/4000] Training [8/16] Loss: 0.00334 +Epoch [2519/4000] Training [9/16] Loss: 0.00559 +Epoch [2519/4000] Training [10/16] Loss: 0.00569 +Epoch [2519/4000] Training [11/16] Loss: 0.00381 +Epoch [2519/4000] Training [12/16] Loss: 0.00283 +Epoch [2519/4000] Training [13/16] Loss: 0.00507 +Epoch [2519/4000] Training [14/16] Loss: 0.00471 +Epoch [2519/4000] Training [15/16] Loss: 0.00416 +Epoch [2519/4000] Training [16/16] Loss: 0.00577 +Epoch [2519/4000] Training metric {'Train/mean dice_metric': 0.9972226619720459, 'Train/mean miou_metric': 0.9941778779029846, 'Train/mean f1': 0.9924604892730713, 'Train/mean precision': 0.9877176880836487, 'Train/mean recall': 0.9972490072250366, 'Train/mean hd95_metric': 0.9568220376968384} +Epoch [2519/4000] Validation [1/4] Loss: 0.33923 focal_loss 0.26958 dice_loss 0.06965 +Epoch [2519/4000] Validation [2/4] Loss: 0.45612 focal_loss 0.31126 dice_loss 0.14487 +Epoch [2519/4000] Validation [3/4] Loss: 0.49539 focal_loss 0.39438 dice_loss 0.10101 +Epoch [2519/4000] Validation [4/4] Loss: 0.46301 focal_loss 0.32702 dice_loss 0.13599 +Epoch [2519/4000] Validation metric {'Val/mean dice_metric': 0.9728859663009644, 'Val/mean miou_metric': 0.9567773938179016, 'Val/mean f1': 0.9745758771896362, 'Val/mean precision': 0.9731115102767944, 'Val/mean recall': 0.9760445952415466, 'Val/mean hd95_metric': 5.2801313400268555} +Cheakpoint... +Epoch [2519/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728859663009644, 'Val/mean miou_metric': 0.9567773938179016, 'Val/mean f1': 0.9745758771896362, 'Val/mean precision': 0.9731115102767944, 'Val/mean recall': 0.9760445952415466, 'Val/mean hd95_metric': 5.2801313400268555} +Epoch [2520/4000] Training [1/16] Loss: 0.00575 +Epoch [2520/4000] Training [2/16] Loss: 0.00490 +Epoch [2520/4000] Training [3/16] Loss: 0.00388 +Epoch [2520/4000] Training [4/16] Loss: 0.00566 +Epoch [2520/4000] Training [5/16] Loss: 0.00340 +Epoch [2520/4000] Training [6/16] Loss: 0.00440 +Epoch [2520/4000] Training [7/16] Loss: 0.00640 +Epoch [2520/4000] Training [8/16] Loss: 0.00608 +Epoch [2520/4000] Training [9/16] Loss: 0.00493 +Epoch [2520/4000] Training [10/16] Loss: 0.00366 +Epoch [2520/4000] Training [11/16] Loss: 0.00419 +Epoch [2520/4000] Training [12/16] Loss: 0.00365 +Epoch [2520/4000] Training [13/16] Loss: 0.00351 +Epoch [2520/4000] Training [14/16] Loss: 0.00498 +Epoch [2520/4000] Training [15/16] Loss: 0.00430 +Epoch [2520/4000] Training [16/16] Loss: 0.00411 +Epoch [2520/4000] Training metric {'Train/mean dice_metric': 0.9970226287841797, 'Train/mean miou_metric': 0.9937917590141296, 'Train/mean f1': 0.9924086928367615, 'Train/mean precision': 0.987847626209259, 'Train/mean recall': 0.9970120191574097, 'Train/mean hd95_metric': 1.3154040575027466} +Epoch [2520/4000] Validation [1/4] Loss: 0.27517 focal_loss 0.21846 dice_loss 0.05671 +Epoch [2520/4000] Validation [2/4] Loss: 0.32080 focal_loss 0.21726 dice_loss 0.10354 +Epoch [2520/4000] Validation [3/4] Loss: 0.28552 focal_loss 0.20681 dice_loss 0.07870 +Epoch [2520/4000] Validation [4/4] Loss: 0.41581 focal_loss 0.31111 dice_loss 0.10470 +Epoch [2520/4000] Validation metric {'Val/mean dice_metric': 0.9733883142471313, 'Val/mean miou_metric': 0.9578390121459961, 'Val/mean f1': 0.9754528403282166, 'Val/mean precision': 0.974583089351654, 'Val/mean recall': 0.9763240218162537, 'Val/mean hd95_metric': 5.094762325286865} +Cheakpoint... +Epoch [2520/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733883142471313, 'Val/mean miou_metric': 0.9578390121459961, 'Val/mean f1': 0.9754528403282166, 'Val/mean precision': 0.974583089351654, 'Val/mean recall': 0.9763240218162537, 'Val/mean hd95_metric': 5.094762325286865} +Epoch [2521/4000] Training [1/16] Loss: 0.00452 +Epoch [2521/4000] Training [2/16] Loss: 0.00374 +Epoch [2521/4000] Training [3/16] Loss: 0.00435 +Epoch [2521/4000] Training [4/16] Loss: 0.00305 +Epoch [2521/4000] Training [5/16] Loss: 0.00483 +Epoch [2521/4000] Training [6/16] Loss: 0.00550 +Epoch [2521/4000] Training [7/16] Loss: 0.00350 +Epoch [2521/4000] Training [8/16] Loss: 0.00855 +Epoch [2521/4000] Training [9/16] Loss: 0.01023 +Epoch [2521/4000] Training [10/16] Loss: 0.00575 +Epoch [2521/4000] Training [11/16] Loss: 0.00415 +Epoch [2521/4000] Training [12/16] Loss: 0.00383 +Epoch [2521/4000] Training [13/16] Loss: 0.00341 +Epoch [2521/4000] Training [14/16] Loss: 0.00325 +Epoch [2521/4000] Training [15/16] Loss: 0.00445 +Epoch [2521/4000] Training [16/16] Loss: 0.00458 +Epoch [2521/4000] Training metric {'Train/mean dice_metric': 0.9973249435424805, 'Train/mean miou_metric': 0.9943938255310059, 'Train/mean f1': 0.9926016926765442, 'Train/mean precision': 0.9880081415176392, 'Train/mean recall': 0.9972381591796875, 'Train/mean hd95_metric': 1.0063985586166382} +Epoch [2521/4000] Validation [1/4] Loss: 0.28289 focal_loss 0.22606 dice_loss 0.05683 +Epoch [2521/4000] Validation [2/4] Loss: 0.36867 focal_loss 0.25354 dice_loss 0.11513 +Epoch [2521/4000] Validation [3/4] Loss: 0.40855 focal_loss 0.31006 dice_loss 0.09849 +Epoch [2521/4000] Validation [4/4] Loss: 0.37542 focal_loss 0.28345 dice_loss 0.09196 +Epoch [2521/4000] Validation metric {'Val/mean dice_metric': 0.9718208312988281, 'Val/mean miou_metric': 0.9559947848320007, 'Val/mean f1': 0.973585844039917, 'Val/mean precision': 0.9742001295089722, 'Val/mean recall': 0.9729723334312439, 'Val/mean hd95_metric': 5.271600246429443} +Cheakpoint... +Epoch [2521/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718208312988281, 'Val/mean miou_metric': 0.9559947848320007, 'Val/mean f1': 0.973585844039917, 'Val/mean precision': 0.9742001295089722, 'Val/mean recall': 0.9729723334312439, 'Val/mean hd95_metric': 5.271600246429443} +Epoch [2522/4000] Training [1/16] Loss: 0.00521 +Epoch [2522/4000] Training [2/16] Loss: 0.00479 +Epoch [2522/4000] Training [3/16] Loss: 0.00280 +Epoch [2522/4000] Training [4/16] Loss: 0.00397 +Epoch [2522/4000] Training [5/16] Loss: 0.00319 +Epoch [2522/4000] Training [6/16] Loss: 0.00503 +Epoch [2522/4000] Training [7/16] Loss: 0.00362 +Epoch [2522/4000] Training [8/16] Loss: 0.00597 +Epoch [2522/4000] Training [9/16] Loss: 0.00469 +Epoch [2522/4000] Training [10/16] Loss: 0.00496 +Epoch [2522/4000] Training [11/16] Loss: 0.00380 +Epoch [2522/4000] Training [12/16] Loss: 0.00407 +Epoch [2522/4000] Training [13/16] Loss: 0.00600 +Epoch [2522/4000] Training [14/16] Loss: 0.00406 +Epoch [2522/4000] Training [15/16] Loss: 0.00478 +Epoch [2522/4000] Training [16/16] Loss: 0.00315 +Epoch [2522/4000] Training metric {'Train/mean dice_metric': 0.9971907138824463, 'Train/mean miou_metric': 0.9941034317016602, 'Train/mean f1': 0.9919257760047913, 'Train/mean precision': 0.9868590235710144, 'Train/mean recall': 0.9970448017120361, 'Train/mean hd95_metric': 0.9345835447311401} +Epoch [2522/4000] Validation [1/4] Loss: 0.28096 focal_loss 0.22460 dice_loss 0.05636 +Epoch [2522/4000] Validation [2/4] Loss: 0.43052 focal_loss 0.29829 dice_loss 0.13223 +Epoch [2522/4000] Validation [3/4] Loss: 0.26500 focal_loss 0.19587 dice_loss 0.06913 +Epoch [2522/4000] Validation [4/4] Loss: 0.35380 focal_loss 0.25420 dice_loss 0.09960 +Epoch [2522/4000] Validation metric {'Val/mean dice_metric': 0.9720603227615356, 'Val/mean miou_metric': 0.9569149017333984, 'Val/mean f1': 0.9749390482902527, 'Val/mean precision': 0.9730949401855469, 'Val/mean recall': 0.9767902493476868, 'Val/mean hd95_metric': 5.538102149963379} +Cheakpoint... +Epoch [2522/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720603227615356, 'Val/mean miou_metric': 0.9569149017333984, 'Val/mean f1': 0.9749390482902527, 'Val/mean precision': 0.9730949401855469, 'Val/mean recall': 0.9767902493476868, 'Val/mean hd95_metric': 5.538102149963379} +Epoch [2523/4000] Training [1/16] Loss: 0.00327 +Epoch [2523/4000] Training [2/16] Loss: 0.00464 +Epoch [2523/4000] Training [3/16] Loss: 0.00663 +Epoch [2523/4000] Training [4/16] Loss: 0.00384 +Epoch [2523/4000] Training [5/16] Loss: 0.00428 +Epoch [2523/4000] Training [6/16] Loss: 0.00395 +Epoch [2523/4000] Training [7/16] Loss: 0.00309 +Epoch [2523/4000] Training [8/16] Loss: 0.00592 +Epoch [2523/4000] Training [9/16] Loss: 0.00395 +Epoch [2523/4000] Training [10/16] Loss: 0.00537 +Epoch [2523/4000] Training [11/16] Loss: 0.00490 +Epoch [2523/4000] Training [12/16] Loss: 0.00467 +Epoch [2523/4000] Training [13/16] Loss: 0.00338 +Epoch [2523/4000] Training [14/16] Loss: 0.00445 +Epoch [2523/4000] Training [15/16] Loss: 0.00427 +Epoch [2523/4000] Training [16/16] Loss: 0.00394 +Epoch [2523/4000] Training metric {'Train/mean dice_metric': 0.9973810911178589, 'Train/mean miou_metric': 0.994509220123291, 'Train/mean f1': 0.9927403330802917, 'Train/mean precision': 0.9881601333618164, 'Train/mean recall': 0.997363269329071, 'Train/mean hd95_metric': 0.9421452879905701} +Epoch [2523/4000] Validation [1/4] Loss: 0.28170 focal_loss 0.22390 dice_loss 0.05780 +Epoch [2523/4000] Validation [2/4] Loss: 0.95397 focal_loss 0.76112 dice_loss 0.19285 +Epoch [2523/4000] Validation [3/4] Loss: 0.38383 focal_loss 0.28745 dice_loss 0.09638 +Epoch [2523/4000] Validation [4/4] Loss: 0.48256 focal_loss 0.34098 dice_loss 0.14158 +Epoch [2523/4000] Validation metric {'Val/mean dice_metric': 0.9698264002799988, 'Val/mean miou_metric': 0.954452633857727, 'Val/mean f1': 0.9734008312225342, 'Val/mean precision': 0.9737975597381592, 'Val/mean recall': 0.9730044603347778, 'Val/mean hd95_metric': 5.697716236114502} +Cheakpoint... +Epoch [2523/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9698], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698264002799988, 'Val/mean miou_metric': 0.954452633857727, 'Val/mean f1': 0.9734008312225342, 'Val/mean precision': 0.9737975597381592, 'Val/mean recall': 0.9730044603347778, 'Val/mean hd95_metric': 5.697716236114502} +Epoch [2524/4000] Training [1/16] Loss: 0.00471 +Epoch [2524/4000] Training [2/16] Loss: 0.00435 +Epoch [2524/4000] Training [3/16] Loss: 0.00473 +Epoch [2524/4000] Training [4/16] Loss: 0.00448 +Epoch [2524/4000] Training [5/16] Loss: 0.00386 +Epoch [2524/4000] Training [6/16] Loss: 0.00405 +Epoch [2524/4000] Training [7/16] Loss: 0.00357 +Epoch [2524/4000] Training [8/16] Loss: 0.00398 +Epoch [2524/4000] Training [9/16] Loss: 0.00436 +Epoch [2524/4000] Training [10/16] Loss: 0.00372 +Epoch [2524/4000] Training [11/16] Loss: 0.00385 +Epoch [2524/4000] Training [12/16] Loss: 0.00388 +Epoch [2524/4000] Training [13/16] Loss: 0.00545 +Epoch [2524/4000] Training [14/16] Loss: 0.00477 +Epoch [2524/4000] Training [15/16] Loss: 0.00458 +Epoch [2524/4000] Training [16/16] Loss: 0.00413 +Epoch [2524/4000] Training metric {'Train/mean dice_metric': 0.9973341226577759, 'Train/mean miou_metric': 0.9943810701370239, 'Train/mean f1': 0.9919770359992981, 'Train/mean precision': 0.986844003200531, 'Train/mean recall': 0.997163712978363, 'Train/mean hd95_metric': 0.9451252222061157} +Epoch [2524/4000] Validation [1/4] Loss: 0.36738 focal_loss 0.30041 dice_loss 0.06696 +Epoch [2524/4000] Validation [2/4] Loss: 0.42869 focal_loss 0.30136 dice_loss 0.12733 +Epoch [2524/4000] Validation [3/4] Loss: 0.39551 focal_loss 0.30312 dice_loss 0.09239 +Epoch [2524/4000] Validation [4/4] Loss: 0.49960 focal_loss 0.36841 dice_loss 0.13119 +Epoch [2524/4000] Validation metric {'Val/mean dice_metric': 0.9727401733398438, 'Val/mean miou_metric': 0.9569290280342102, 'Val/mean f1': 0.9745298624038696, 'Val/mean precision': 0.97329181432724, 'Val/mean recall': 0.9757710099220276, 'Val/mean hd95_metric': 5.043339252471924} +Cheakpoint... +Epoch [2524/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727401733398438, 'Val/mean miou_metric': 0.9569290280342102, 'Val/mean f1': 0.9745298624038696, 'Val/mean precision': 0.97329181432724, 'Val/mean recall': 0.9757710099220276, 'Val/mean hd95_metric': 5.043339252471924} +Epoch [2525/4000] Training [1/16] Loss: 0.00407 +Epoch [2525/4000] Training [2/16] Loss: 0.00481 +Epoch [2525/4000] Training [3/16] Loss: 0.00354 +Epoch [2525/4000] Training [4/16] Loss: 0.00573 +Epoch [2525/4000] Training [5/16] Loss: 0.00514 +Epoch [2525/4000] Training [6/16] Loss: 0.00309 +Epoch [2525/4000] Training [7/16] Loss: 0.00418 +Epoch [2525/4000] Training [8/16] Loss: 0.00329 +Epoch [2525/4000] Training [9/16] Loss: 0.00504 +Epoch [2525/4000] Training [10/16] Loss: 0.00416 +Epoch [2525/4000] Training [11/16] Loss: 0.00597 +Epoch [2525/4000] Training [12/16] Loss: 0.00481 +Epoch [2525/4000] Training [13/16] Loss: 0.00509 +Epoch [2525/4000] Training [14/16] Loss: 0.00390 +Epoch [2525/4000] Training [15/16] Loss: 0.00551 +Epoch [2525/4000] Training [16/16] Loss: 0.00557 +Epoch [2525/4000] Training metric {'Train/mean dice_metric': 0.9972846508026123, 'Train/mean miou_metric': 0.9943128824234009, 'Train/mean f1': 0.9926668405532837, 'Train/mean precision': 0.9881399869918823, 'Train/mean recall': 0.9972354173660278, 'Train/mean hd95_metric': 0.9574688673019409} +Epoch [2525/4000] Validation [1/4] Loss: 0.37480 focal_loss 0.28964 dice_loss 0.08516 +Epoch [2525/4000] Validation [2/4] Loss: 0.97192 focal_loss 0.77286 dice_loss 0.19906 +Epoch [2525/4000] Validation [3/4] Loss: 0.41847 focal_loss 0.32626 dice_loss 0.09222 +Epoch [2525/4000] Validation [4/4] Loss: 0.24407 focal_loss 0.16142 dice_loss 0.08265 +Epoch [2525/4000] Validation metric {'Val/mean dice_metric': 0.9717909693717957, 'Val/mean miou_metric': 0.9567365646362305, 'Val/mean f1': 0.974972128868103, 'Val/mean precision': 0.9740872383117676, 'Val/mean recall': 0.975858747959137, 'Val/mean hd95_metric': 5.235129356384277} +Cheakpoint... +Epoch [2525/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717909693717957, 'Val/mean miou_metric': 0.9567365646362305, 'Val/mean f1': 0.974972128868103, 'Val/mean precision': 0.9740872383117676, 'Val/mean recall': 0.975858747959137, 'Val/mean hd95_metric': 5.235129356384277} +Epoch [2526/4000] Training [1/16] Loss: 0.00419 +Epoch [2526/4000] Training [2/16] Loss: 0.00295 +Epoch [2526/4000] Training [3/16] Loss: 0.00601 +Epoch [2526/4000] Training [4/16] Loss: 0.00356 +Epoch [2526/4000] Training [5/16] Loss: 0.00403 +Epoch [2526/4000] Training [6/16] Loss: 0.00505 +Epoch [2526/4000] Training [7/16] Loss: 0.00560 +Epoch [2526/4000] Training [8/16] Loss: 0.00490 +Epoch [2526/4000] Training [9/16] Loss: 0.01265 +Epoch [2526/4000] Training [10/16] Loss: 0.00371 +Epoch [2526/4000] Training [11/16] Loss: 0.00387 +Epoch [2526/4000] Training [12/16] Loss: 0.00355 +Epoch [2526/4000] Training [13/16] Loss: 0.00424 +Epoch [2526/4000] Training [14/16] Loss: 0.00395 +Epoch [2526/4000] Training [15/16] Loss: 0.00433 +Epoch [2526/4000] Training [16/16] Loss: 0.00412 +Epoch [2526/4000] Training metric {'Train/mean dice_metric': 0.9971805810928345, 'Train/mean miou_metric': 0.9941043853759766, 'Train/mean f1': 0.9924975037574768, 'Train/mean precision': 0.9879631996154785, 'Train/mean recall': 0.9970735907554626, 'Train/mean hd95_metric': 0.9540183544158936} +Epoch [2526/4000] Validation [1/4] Loss: 0.36635 focal_loss 0.28752 dice_loss 0.07883 +Epoch [2526/4000] Validation [2/4] Loss: 0.43957 focal_loss 0.30626 dice_loss 0.13331 +Epoch [2526/4000] Validation [3/4] Loss: 0.40179 focal_loss 0.30839 dice_loss 0.09339 +Epoch [2526/4000] Validation [4/4] Loss: 0.31717 focal_loss 0.23114 dice_loss 0.08602 +Epoch [2526/4000] Validation metric {'Val/mean dice_metric': 0.972857654094696, 'Val/mean miou_metric': 0.9575660824775696, 'Val/mean f1': 0.9755339622497559, 'Val/mean precision': 0.9743513464927673, 'Val/mean recall': 0.976719319820404, 'Val/mean hd95_metric': 4.83030366897583} +Cheakpoint... +Epoch [2526/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972857654094696, 'Val/mean miou_metric': 0.9575660824775696, 'Val/mean f1': 0.9755339622497559, 'Val/mean precision': 0.9743513464927673, 'Val/mean recall': 0.976719319820404, 'Val/mean hd95_metric': 4.83030366897583} +Epoch [2527/4000] Training [1/16] Loss: 0.00528 +Epoch [2527/4000] Training [2/16] Loss: 0.00292 +Epoch [2527/4000] Training [3/16] Loss: 0.00545 +Epoch [2527/4000] Training [4/16] Loss: 0.00405 +Epoch [2527/4000] Training [5/16] Loss: 0.00429 +Epoch [2527/4000] Training [6/16] Loss: 0.00415 +Epoch [2527/4000] Training [7/16] Loss: 0.00339 +Epoch [2527/4000] Training [8/16] Loss: 0.00374 +Epoch [2527/4000] Training [9/16] Loss: 0.00464 +Epoch [2527/4000] Training [10/16] Loss: 0.00372 +Epoch [2527/4000] Training [11/16] Loss: 0.00350 +Epoch [2527/4000] Training [12/16] Loss: 0.00317 +Epoch [2527/4000] Training [13/16] Loss: 0.00304 +Epoch [2527/4000] Training [14/16] Loss: 0.00432 +Epoch [2527/4000] Training [15/16] Loss: 0.00397 +Epoch [2527/4000] Training [16/16] Loss: 0.00387 +Epoch [2527/4000] Training metric {'Train/mean dice_metric': 0.9975699782371521, 'Train/mean miou_metric': 0.9948476552963257, 'Train/mean f1': 0.9925647974014282, 'Train/mean precision': 0.9876622557640076, 'Train/mean recall': 0.9975162148475647, 'Train/mean hd95_metric': 0.9317350387573242} +Epoch [2527/4000] Validation [1/4] Loss: 0.35880 focal_loss 0.27495 dice_loss 0.08385 +Epoch [2527/4000] Validation [2/4] Loss: 0.42886 focal_loss 0.30599 dice_loss 0.12287 +Epoch [2527/4000] Validation [3/4] Loss: 0.23394 focal_loss 0.17550 dice_loss 0.05844 +Epoch [2527/4000] Validation [4/4] Loss: 0.29527 focal_loss 0.19812 dice_loss 0.09715 +Epoch [2527/4000] Validation metric {'Val/mean dice_metric': 0.9740495681762695, 'Val/mean miou_metric': 0.9592709541320801, 'Val/mean f1': 0.9759502410888672, 'Val/mean precision': 0.9740045666694641, 'Val/mean recall': 0.9779036641120911, 'Val/mean hd95_metric': 4.704674243927002} +Cheakpoint... +Epoch [2527/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740495681762695, 'Val/mean miou_metric': 0.9592709541320801, 'Val/mean f1': 0.9759502410888672, 'Val/mean precision': 0.9740045666694641, 'Val/mean recall': 0.9779036641120911, 'Val/mean hd95_metric': 4.704674243927002} +Epoch [2528/4000] Training [1/16] Loss: 0.00353 +Epoch [2528/4000] Training [2/16] Loss: 0.00450 +Epoch [2528/4000] Training [3/16] Loss: 0.00440 +Epoch [2528/4000] Training [4/16] Loss: 0.00448 +Epoch [2528/4000] Training [5/16] Loss: 0.00334 +Epoch [2528/4000] Training [6/16] Loss: 0.00415 +Epoch [2528/4000] Training [7/16] Loss: 0.00508 +Epoch [2528/4000] Training [8/16] Loss: 0.00364 +Epoch [2528/4000] Training [9/16] Loss: 0.00341 +Epoch [2528/4000] Training [10/16] Loss: 0.00438 +Epoch [2528/4000] Training [11/16] Loss: 0.00527 +Epoch [2528/4000] Training [12/16] Loss: 0.00302 +Epoch [2528/4000] Training [13/16] Loss: 0.00504 +Epoch [2528/4000] Training [14/16] Loss: 0.00433 +Epoch [2528/4000] Training [15/16] Loss: 0.00577 +Epoch [2528/4000] Training [16/16] Loss: 0.00419 +Epoch [2528/4000] Training metric {'Train/mean dice_metric': 0.9972759485244751, 'Train/mean miou_metric': 0.9942615628242493, 'Train/mean f1': 0.9920420050621033, 'Train/mean precision': 0.987052321434021, 'Train/mean recall': 0.9970824122428894, 'Train/mean hd95_metric': 0.9493575096130371} +Epoch [2528/4000] Validation [1/4] Loss: 0.30394 focal_loss 0.23596 dice_loss 0.06798 +Epoch [2528/4000] Validation [2/4] Loss: 0.45561 focal_loss 0.32479 dice_loss 0.13081 +Epoch [2528/4000] Validation [3/4] Loss: 0.38575 focal_loss 0.29149 dice_loss 0.09426 +Epoch [2528/4000] Validation [4/4] Loss: 0.32567 focal_loss 0.23365 dice_loss 0.09201 +Epoch [2528/4000] Validation metric {'Val/mean dice_metric': 0.9741793870925903, 'Val/mean miou_metric': 0.9589122533798218, 'Val/mean f1': 0.9751549959182739, 'Val/mean precision': 0.9732595682144165, 'Val/mean recall': 0.9770579934120178, 'Val/mean hd95_metric': 4.8353590965271} +Cheakpoint... +Epoch [2528/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741793870925903, 'Val/mean miou_metric': 0.9589122533798218, 'Val/mean f1': 0.9751549959182739, 'Val/mean precision': 0.9732595682144165, 'Val/mean recall': 0.9770579934120178, 'Val/mean hd95_metric': 4.8353590965271} +Epoch [2529/4000] Training [1/16] Loss: 0.00746 +Epoch [2529/4000] Training [2/16] Loss: 0.00259 +Epoch [2529/4000] Training [3/16] Loss: 0.00392 +Epoch [2529/4000] Training [4/16] Loss: 0.00268 +Epoch [2529/4000] Training [5/16] Loss: 0.00542 +Epoch [2529/4000] Training [6/16] Loss: 0.00534 +Epoch [2529/4000] Training [7/16] Loss: 0.00335 +Epoch [2529/4000] Training [8/16] Loss: 0.00505 +Epoch [2529/4000] Training [9/16] Loss: 0.00359 +Epoch [2529/4000] Training [10/16] Loss: 0.00432 +Epoch [2529/4000] Training [11/16] Loss: 0.00433 +Epoch [2529/4000] Training [12/16] Loss: 0.00427 +Epoch [2529/4000] Training [13/16] Loss: 0.00377 +Epoch [2529/4000] Training [14/16] Loss: 0.00382 +Epoch [2529/4000] Training [15/16] Loss: 0.00307 +Epoch [2529/4000] Training [16/16] Loss: 0.00487 +Epoch [2529/4000] Training metric {'Train/mean dice_metric': 0.9973496198654175, 'Train/mean miou_metric': 0.9944216012954712, 'Train/mean f1': 0.9922910332679749, 'Train/mean precision': 0.9872879981994629, 'Train/mean recall': 0.9973449110984802, 'Train/mean hd95_metric': 0.9473344087600708} +Epoch [2529/4000] Validation [1/4] Loss: 0.37387 focal_loss 0.28238 dice_loss 0.09149 +Epoch [2529/4000] Validation [2/4] Loss: 0.40384 focal_loss 0.28007 dice_loss 0.12377 +Epoch [2529/4000] Validation [3/4] Loss: 0.38407 focal_loss 0.29504 dice_loss 0.08903 +Epoch [2529/4000] Validation [4/4] Loss: 0.29624 focal_loss 0.20688 dice_loss 0.08936 +Epoch [2529/4000] Validation metric {'Val/mean dice_metric': 0.9710108041763306, 'Val/mean miou_metric': 0.9560726284980774, 'Val/mean f1': 0.9744317531585693, 'Val/mean precision': 0.9727392196655273, 'Val/mean recall': 0.9761302471160889, 'Val/mean hd95_metric': 4.954726696014404} +Cheakpoint... +Epoch [2529/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710108041763306, 'Val/mean miou_metric': 0.9560726284980774, 'Val/mean f1': 0.9744317531585693, 'Val/mean precision': 0.9727392196655273, 'Val/mean recall': 0.9761302471160889, 'Val/mean hd95_metric': 4.954726696014404} +Epoch [2530/4000] Training [1/16] Loss: 0.00376 +Epoch [2530/4000] Training [2/16] Loss: 0.00552 +Epoch [2530/4000] Training [3/16] Loss: 0.00338 +Epoch [2530/4000] Training [4/16] Loss: 0.00539 +Epoch [2530/4000] Training [5/16] Loss: 0.00503 +Epoch [2530/4000] Training [6/16] Loss: 0.00415 +Epoch [2530/4000] Training [7/16] Loss: 0.00395 +Epoch [2530/4000] Training [8/16] Loss: 0.00434 +Epoch [2530/4000] Training [9/16] Loss: 0.00344 +Epoch [2530/4000] Training [10/16] Loss: 0.00441 +Epoch [2530/4000] Training [11/16] Loss: 0.00320 +Epoch [2530/4000] Training [12/16] Loss: 0.00375 +Epoch [2530/4000] Training [13/16] Loss: 0.00465 +Epoch [2530/4000] Training [14/16] Loss: 0.00388 +Epoch [2530/4000] Training [15/16] Loss: 0.00398 +Epoch [2530/4000] Training [16/16] Loss: 0.00553 +Epoch [2530/4000] Training metric {'Train/mean dice_metric': 0.9974051713943481, 'Train/mean miou_metric': 0.9945448637008667, 'Train/mean f1': 0.9925670623779297, 'Train/mean precision': 0.98787522315979, 'Train/mean recall': 0.9973037838935852, 'Train/mean hd95_metric': 0.9584847688674927} +Epoch [2530/4000] Validation [1/4] Loss: 0.41265 focal_loss 0.31995 dice_loss 0.09270 +Epoch [2530/4000] Validation [2/4] Loss: 0.44780 focal_loss 0.30095 dice_loss 0.14686 +Epoch [2530/4000] Validation [3/4] Loss: 0.38138 focal_loss 0.28995 dice_loss 0.09143 +Epoch [2530/4000] Validation [4/4] Loss: 0.59324 focal_loss 0.46452 dice_loss 0.12872 +Epoch [2530/4000] Validation metric {'Val/mean dice_metric': 0.9724475741386414, 'Val/mean miou_metric': 0.9568525552749634, 'Val/mean f1': 0.9743101596832275, 'Val/mean precision': 0.9735082983970642, 'Val/mean recall': 0.9751133322715759, 'Val/mean hd95_metric': 5.133119106292725} +Cheakpoint... +Epoch [2530/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724475741386414, 'Val/mean miou_metric': 0.9568525552749634, 'Val/mean f1': 0.9743101596832275, 'Val/mean precision': 0.9735082983970642, 'Val/mean recall': 0.9751133322715759, 'Val/mean hd95_metric': 5.133119106292725} +Epoch [2531/4000] Training [1/16] Loss: 0.00362 +Epoch [2531/4000] Training [2/16] Loss: 0.00436 +Epoch [2531/4000] Training [3/16] Loss: 0.00285 +Epoch [2531/4000] Training [4/16] Loss: 0.00414 +Epoch [2531/4000] Training [5/16] Loss: 0.00639 +Epoch [2531/4000] Training [6/16] Loss: 0.00306 +Epoch [2531/4000] Training [7/16] Loss: 0.00612 +Epoch [2531/4000] Training [8/16] Loss: 0.00536 +Epoch [2531/4000] Training [9/16] Loss: 0.00530 +Epoch [2531/4000] Training [10/16] Loss: 0.00480 +Epoch [2531/4000] Training [11/16] Loss: 0.00434 +Epoch [2531/4000] Training [12/16] Loss: 0.00360 +Epoch [2531/4000] Training [13/16] Loss: 0.00367 +Epoch [2531/4000] Training [14/16] Loss: 0.00625 +Epoch [2531/4000] Training [15/16] Loss: 0.00509 +Epoch [2531/4000] Training [16/16] Loss: 0.00555 +Epoch [2531/4000] Training metric {'Train/mean dice_metric': 0.9971398711204529, 'Train/mean miou_metric': 0.9940307140350342, 'Train/mean f1': 0.9925091862678528, 'Train/mean precision': 0.987886369228363, 'Train/mean recall': 0.9971754550933838, 'Train/mean hd95_metric': 1.0116902589797974} +Epoch [2531/4000] Validation [1/4] Loss: 0.50722 focal_loss 0.39705 dice_loss 0.11017 +Epoch [2531/4000] Validation [2/4] Loss: 0.47741 focal_loss 0.34271 dice_loss 0.13470 +Epoch [2531/4000] Validation [3/4] Loss: 0.43647 focal_loss 0.34126 dice_loss 0.09521 +Epoch [2531/4000] Validation [4/4] Loss: 0.47987 focal_loss 0.33670 dice_loss 0.14317 +Epoch [2531/4000] Validation metric {'Val/mean dice_metric': 0.9691886901855469, 'Val/mean miou_metric': 0.9533027410507202, 'Val/mean f1': 0.9735622406005859, 'Val/mean precision': 0.9752743244171143, 'Val/mean recall': 0.9718561172485352, 'Val/mean hd95_metric': 5.712414264678955} +Cheakpoint... +Epoch [2531/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691886901855469, 'Val/mean miou_metric': 0.9533027410507202, 'Val/mean f1': 0.9735622406005859, 'Val/mean precision': 0.9752743244171143, 'Val/mean recall': 0.9718561172485352, 'Val/mean hd95_metric': 5.712414264678955} +Epoch [2532/4000] Training [1/16] Loss: 0.00304 +Epoch [2532/4000] Training [2/16] Loss: 0.00512 +Epoch [2532/4000] Training [3/16] Loss: 0.00400 +Epoch [2532/4000] Training [4/16] Loss: 0.00367 +Epoch [2532/4000] Training [5/16] Loss: 0.00314 +Epoch [2532/4000] Training [6/16] Loss: 0.00379 +Epoch [2532/4000] Training [7/16] Loss: 0.00480 +Epoch [2532/4000] Training [8/16] Loss: 0.00528 +Epoch [2532/4000] Training [9/16] Loss: 0.00500 +Epoch [2532/4000] Training [10/16] Loss: 0.00460 +Epoch [2532/4000] Training [11/16] Loss: 0.00503 +Epoch [2532/4000] Training [12/16] Loss: 0.00382 +Epoch [2532/4000] Training [13/16] Loss: 0.00421 +Epoch [2532/4000] Training [14/16] Loss: 0.00334 +Epoch [2532/4000] Training [15/16] Loss: 0.00446 +Epoch [2532/4000] Training [16/16] Loss: 0.00427 +Epoch [2532/4000] Training metric {'Train/mean dice_metric': 0.9974479675292969, 'Train/mean miou_metric': 0.9946367740631104, 'Train/mean f1': 0.9927847981452942, 'Train/mean precision': 0.988319456577301, 'Train/mean recall': 0.9972906708717346, 'Train/mean hd95_metric': 0.9538639783859253} +Epoch [2532/4000] Validation [1/4] Loss: 0.42234 focal_loss 0.32097 dice_loss 0.10137 +Epoch [2532/4000] Validation [2/4] Loss: 0.94544 focal_loss 0.75335 dice_loss 0.19209 +Epoch [2532/4000] Validation [3/4] Loss: 0.27715 focal_loss 0.19465 dice_loss 0.08250 +Epoch [2532/4000] Validation [4/4] Loss: 0.35199 focal_loss 0.24753 dice_loss 0.10446 +Epoch [2532/4000] Validation metric {'Val/mean dice_metric': 0.9691481590270996, 'Val/mean miou_metric': 0.9538496732711792, 'Val/mean f1': 0.9734458327293396, 'Val/mean precision': 0.976052463054657, 'Val/mean recall': 0.9708529710769653, 'Val/mean hd95_metric': 5.345170021057129} +Cheakpoint... +Epoch [2532/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691481590270996, 'Val/mean miou_metric': 0.9538496732711792, 'Val/mean f1': 0.9734458327293396, 'Val/mean precision': 0.976052463054657, 'Val/mean recall': 0.9708529710769653, 'Val/mean hd95_metric': 5.345170021057129} +Epoch [2533/4000] Training [1/16] Loss: 0.00453 +Epoch [2533/4000] Training [2/16] Loss: 0.00381 +Epoch [2533/4000] Training [3/16] Loss: 0.00495 +Epoch [2533/4000] Training [4/16] Loss: 0.00484 +Epoch [2533/4000] Training [5/16] Loss: 0.00368 +Epoch [2533/4000] Training [6/16] Loss: 0.00425 +Epoch [2533/4000] Training [7/16] Loss: 0.00441 +Epoch [2533/4000] Training [8/16] Loss: 0.00410 +Epoch [2533/4000] Training [9/16] Loss: 0.00469 +Epoch [2533/4000] Training [10/16] Loss: 0.00365 +Epoch [2533/4000] Training [11/16] Loss: 0.00508 +Epoch [2533/4000] Training [12/16] Loss: 0.00390 +Epoch [2533/4000] Training [13/16] Loss: 0.00437 +Epoch [2533/4000] Training [14/16] Loss: 0.00437 +Epoch [2533/4000] Training [15/16] Loss: 0.00425 +Epoch [2533/4000] Training [16/16] Loss: 0.00490 +Epoch [2533/4000] Training metric {'Train/mean dice_metric': 0.9972405433654785, 'Train/mean miou_metric': 0.9942030906677246, 'Train/mean f1': 0.9924027919769287, 'Train/mean precision': 0.9876052737236023, 'Train/mean recall': 0.9972471594810486, 'Train/mean hd95_metric': 0.9570016860961914} +Epoch [2533/4000] Validation [1/4] Loss: 0.52602 focal_loss 0.41761 dice_loss 0.10841 +Epoch [2533/4000] Validation [2/4] Loss: 0.82485 focal_loss 0.61951 dice_loss 0.20534 +Epoch [2533/4000] Validation [3/4] Loss: 0.38671 focal_loss 0.28254 dice_loss 0.10417 +Epoch [2533/4000] Validation [4/4] Loss: 0.63053 focal_loss 0.49340 dice_loss 0.13713 +Epoch [2533/4000] Validation metric {'Val/mean dice_metric': 0.9680112600326538, 'Val/mean miou_metric': 0.9526654481887817, 'Val/mean f1': 0.9729518294334412, 'Val/mean precision': 0.9750291109085083, 'Val/mean recall': 0.9708834290504456, 'Val/mean hd95_metric': 5.837887287139893} +Cheakpoint... +Epoch [2533/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9680], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9680112600326538, 'Val/mean miou_metric': 0.9526654481887817, 'Val/mean f1': 0.9729518294334412, 'Val/mean precision': 0.9750291109085083, 'Val/mean recall': 0.9708834290504456, 'Val/mean hd95_metric': 5.837887287139893} +Epoch [2534/4000] Training [1/16] Loss: 0.00418 +Epoch [2534/4000] Training [2/16] Loss: 0.00473 +Epoch [2534/4000] Training [3/16] Loss: 0.00554 +Epoch [2534/4000] Training [4/16] Loss: 0.00418 +Epoch [2534/4000] Training [5/16] Loss: 0.00530 +Epoch [2534/4000] Training [6/16] Loss: 0.00394 +Epoch [2534/4000] Training [7/16] Loss: 0.00365 +Epoch [2534/4000] Training [8/16] Loss: 0.00308 +Epoch [2534/4000] Training [9/16] Loss: 0.00407 +Epoch [2534/4000] Training [10/16] Loss: 0.00429 +Epoch [2534/4000] Training [11/16] Loss: 0.00421 +Epoch [2534/4000] Training [12/16] Loss: 0.00857 +Epoch [2534/4000] Training [13/16] Loss: 0.00354 +Epoch [2534/4000] Training [14/16] Loss: 0.00348 +Epoch [2534/4000] Training [15/16] Loss: 0.00521 +Epoch [2534/4000] Training [16/16] Loss: 0.00302 +Epoch [2534/4000] Training metric {'Train/mean dice_metric': 0.997469425201416, 'Train/mean miou_metric': 0.9946755170822144, 'Train/mean f1': 0.9927715063095093, 'Train/mean precision': 0.9880651235580444, 'Train/mean recall': 0.9975230097770691, 'Train/mean hd95_metric': 0.9509724378585815} +Epoch [2534/4000] Validation [1/4] Loss: 0.26165 focal_loss 0.20494 dice_loss 0.05672 +Epoch [2534/4000] Validation [2/4] Loss: 0.54262 focal_loss 0.39729 dice_loss 0.14533 +Epoch [2534/4000] Validation [3/4] Loss: 0.36907 focal_loss 0.26442 dice_loss 0.10464 +Epoch [2534/4000] Validation [4/4] Loss: 0.34195 focal_loss 0.23999 dice_loss 0.10196 +Epoch [2534/4000] Validation metric {'Val/mean dice_metric': 0.9713412523269653, 'Val/mean miou_metric': 0.9558076858520508, 'Val/mean f1': 0.9740188121795654, 'Val/mean precision': 0.9747071862220764, 'Val/mean recall': 0.9733313322067261, 'Val/mean hd95_metric': 5.1981706619262695} +Cheakpoint... +Epoch [2534/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713412523269653, 'Val/mean miou_metric': 0.9558076858520508, 'Val/mean f1': 0.9740188121795654, 'Val/mean precision': 0.9747071862220764, 'Val/mean recall': 0.9733313322067261, 'Val/mean hd95_metric': 5.1981706619262695} +Epoch [2535/4000] Training [1/16] Loss: 0.00322 +Epoch [2535/4000] Training [2/16] Loss: 0.00438 +Epoch [2535/4000] Training [3/16] Loss: 0.00384 +Epoch [2535/4000] Training [4/16] Loss: 0.00329 +Epoch [2535/4000] Training [5/16] Loss: 0.00453 +Epoch [2535/4000] Training [6/16] Loss: 0.00447 +Epoch [2535/4000] Training [7/16] Loss: 0.00507 +Epoch [2535/4000] Training [8/16] Loss: 0.00444 +Epoch [2535/4000] Training [9/16] Loss: 0.00382 +Epoch [2535/4000] Training [10/16] Loss: 0.00434 +Epoch [2535/4000] Training [11/16] Loss: 0.00316 +Epoch [2535/4000] Training [12/16] Loss: 0.00471 +Epoch [2535/4000] Training [13/16] Loss: 0.00349 +Epoch [2535/4000] Training [14/16] Loss: 0.00382 +Epoch [2535/4000] Training [15/16] Loss: 0.00544 +Epoch [2535/4000] Training [16/16] Loss: 0.00271 +Epoch [2535/4000] Training metric {'Train/mean dice_metric': 0.9974595308303833, 'Train/mean miou_metric': 0.9946618676185608, 'Train/mean f1': 0.99285489320755, 'Train/mean precision': 0.9883430600166321, 'Train/mean recall': 0.9974080920219421, 'Train/mean hd95_metric': 0.9402897953987122} +Epoch [2535/4000] Validation [1/4] Loss: 0.41958 focal_loss 0.32182 dice_loss 0.09776 +Epoch [2535/4000] Validation [2/4] Loss: 0.99215 focal_loss 0.78559 dice_loss 0.20656 +Epoch [2535/4000] Validation [3/4] Loss: 0.29410 focal_loss 0.20526 dice_loss 0.08884 +Epoch [2535/4000] Validation [4/4] Loss: 0.39051 focal_loss 0.27817 dice_loss 0.11234 +Epoch [2535/4000] Validation metric {'Val/mean dice_metric': 0.9691116213798523, 'Val/mean miou_metric': 0.9542890787124634, 'Val/mean f1': 0.973778486251831, 'Val/mean precision': 0.9750190377235413, 'Val/mean recall': 0.9725408554077148, 'Val/mean hd95_metric': 5.504688739776611} +Cheakpoint... +Epoch [2535/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9691], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691116213798523, 'Val/mean miou_metric': 0.9542890787124634, 'Val/mean f1': 0.973778486251831, 'Val/mean precision': 0.9750190377235413, 'Val/mean recall': 0.9725408554077148, 'Val/mean hd95_metric': 5.504688739776611} +Epoch [2536/4000] Training [1/16] Loss: 0.00530 +Epoch [2536/4000] Training [2/16] Loss: 0.00304 +Epoch [2536/4000] Training [3/16] Loss: 0.00414 +Epoch [2536/4000] Training [4/16] Loss: 0.00287 +Epoch [2536/4000] Training [5/16] Loss: 0.00395 +Epoch [2536/4000] Training [6/16] Loss: 0.00412 +Epoch [2536/4000] Training [7/16] Loss: 0.00485 +Epoch [2536/4000] Training [8/16] Loss: 0.00297 +Epoch [2536/4000] Training [9/16] Loss: 0.00219 +Epoch [2536/4000] Training [10/16] Loss: 0.00466 +Epoch [2536/4000] Training [11/16] Loss: 0.00454 +Epoch [2536/4000] Training [12/16] Loss: 0.00630 +Epoch [2536/4000] Training [13/16] Loss: 0.00594 +Epoch [2536/4000] Training [14/16] Loss: 0.00310 +Epoch [2536/4000] Training [15/16] Loss: 0.00562 +Epoch [2536/4000] Training [16/16] Loss: 0.00416 +Epoch [2536/4000] Training metric {'Train/mean dice_metric': 0.9973993897438049, 'Train/mean miou_metric': 0.9945338368415833, 'Train/mean f1': 0.99278324842453, 'Train/mean precision': 0.9882876873016357, 'Train/mean recall': 0.9973198771476746, 'Train/mean hd95_metric': 0.933021068572998} +Epoch [2536/4000] Validation [1/4] Loss: 0.51670 focal_loss 0.41031 dice_loss 0.10640 +Epoch [2536/4000] Validation [2/4] Loss: 0.65530 focal_loss 0.47131 dice_loss 0.18399 +Epoch [2536/4000] Validation [3/4] Loss: 0.31914 focal_loss 0.23541 dice_loss 0.08373 +Epoch [2536/4000] Validation [4/4] Loss: 0.57201 focal_loss 0.43124 dice_loss 0.14077 +Epoch [2536/4000] Validation metric {'Val/mean dice_metric': 0.970240592956543, 'Val/mean miou_metric': 0.9545574188232422, 'Val/mean f1': 0.9735853672027588, 'Val/mean precision': 0.9744303226470947, 'Val/mean recall': 0.9727417826652527, 'Val/mean hd95_metric': 5.509985446929932} +Cheakpoint... +Epoch [2536/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970240592956543, 'Val/mean miou_metric': 0.9545574188232422, 'Val/mean f1': 0.9735853672027588, 'Val/mean precision': 0.9744303226470947, 'Val/mean recall': 0.9727417826652527, 'Val/mean hd95_metric': 5.509985446929932} +Epoch [2537/4000] Training [1/16] Loss: 0.00521 +Epoch [2537/4000] Training [2/16] Loss: 0.00357 +Epoch [2537/4000] Training [3/16] Loss: 0.00426 +Epoch [2537/4000] Training [4/16] Loss: 0.00350 +Epoch [2537/4000] Training [5/16] Loss: 0.00406 +Epoch [2537/4000] Training [6/16] Loss: 0.00477 +Epoch [2537/4000] Training [7/16] Loss: 0.00313 +Epoch [2537/4000] Training [8/16] Loss: 0.00402 +Epoch [2537/4000] Training [9/16] Loss: 0.00463 +Epoch [2537/4000] Training [10/16] Loss: 0.00413 +Epoch [2537/4000] Training [11/16] Loss: 0.00486 +Epoch [2537/4000] Training [12/16] Loss: 0.00452 +Epoch [2537/4000] Training [13/16] Loss: 0.00382 +Epoch [2537/4000] Training [14/16] Loss: 0.00393 +Epoch [2537/4000] Training [15/16] Loss: 0.00425 +Epoch [2537/4000] Training [16/16] Loss: 0.00595 +Epoch [2537/4000] Training metric {'Train/mean dice_metric': 0.9972748160362244, 'Train/mean miou_metric': 0.9942533373832703, 'Train/mean f1': 0.9920423626899719, 'Train/mean precision': 0.9869527220726013, 'Train/mean recall': 0.997184693813324, 'Train/mean hd95_metric': 0.9608028531074524} +Epoch [2537/4000] Validation [1/4] Loss: 0.37505 focal_loss 0.31109 dice_loss 0.06396 +Epoch [2537/4000] Validation [2/4] Loss: 0.88385 focal_loss 0.68750 dice_loss 0.19635 +Epoch [2537/4000] Validation [3/4] Loss: 0.24302 focal_loss 0.18356 dice_loss 0.05946 +Epoch [2537/4000] Validation [4/4] Loss: 0.30653 focal_loss 0.21915 dice_loss 0.08737 +Epoch [2537/4000] Validation metric {'Val/mean dice_metric': 0.9718039631843567, 'Val/mean miou_metric': 0.9573335647583008, 'Val/mean f1': 0.9753242135047913, 'Val/mean precision': 0.9738548398017883, 'Val/mean recall': 0.9767981767654419, 'Val/mean hd95_metric': 4.791413307189941} +Cheakpoint... +Epoch [2537/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718039631843567, 'Val/mean miou_metric': 0.9573335647583008, 'Val/mean f1': 0.9753242135047913, 'Val/mean precision': 0.9738548398017883, 'Val/mean recall': 0.9767981767654419, 'Val/mean hd95_metric': 4.791413307189941} +Epoch [2538/4000] Training [1/16] Loss: 0.00418 +Epoch [2538/4000] Training [2/16] Loss: 0.00448 +Epoch [2538/4000] Training [3/16] Loss: 0.00314 +Epoch [2538/4000] Training [4/16] Loss: 0.00463 +Epoch [2538/4000] Training [5/16] Loss: 0.00733 +Epoch [2538/4000] Training [6/16] Loss: 0.00374 +Epoch [2538/4000] Training [7/16] Loss: 0.00340 +Epoch [2538/4000] Training [8/16] Loss: 0.00399 +Epoch [2538/4000] Training [9/16] Loss: 0.00359 +Epoch [2538/4000] Training [10/16] Loss: 0.00397 +Epoch [2538/4000] Training [11/16] Loss: 0.00426 +Epoch [2538/4000] Training [12/16] Loss: 0.00376 +Epoch [2538/4000] Training [13/16] Loss: 0.00384 +Epoch [2538/4000] Training [14/16] Loss: 0.00325 +Epoch [2538/4000] Training [15/16] Loss: 0.00716 +Epoch [2538/4000] Training [16/16] Loss: 0.00425 +Epoch [2538/4000] Training metric {'Train/mean dice_metric': 0.9973639249801636, 'Train/mean miou_metric': 0.9944629669189453, 'Train/mean f1': 0.9926345944404602, 'Train/mean precision': 0.987977147102356, 'Train/mean recall': 0.9973360896110535, 'Train/mean hd95_metric': 0.9531105160713196} +Epoch [2538/4000] Validation [1/4] Loss: 0.37183 focal_loss 0.28853 dice_loss 0.08330 +Epoch [2538/4000] Validation [2/4] Loss: 0.43611 focal_loss 0.31595 dice_loss 0.12016 +Epoch [2538/4000] Validation [3/4] Loss: 0.37609 focal_loss 0.27813 dice_loss 0.09796 +Epoch [2538/4000] Validation [4/4] Loss: 0.65394 focal_loss 0.52618 dice_loss 0.12776 +Epoch [2538/4000] Validation metric {'Val/mean dice_metric': 0.9723633527755737, 'Val/mean miou_metric': 0.9568341374397278, 'Val/mean f1': 0.9746237993240356, 'Val/mean precision': 0.9752287864685059, 'Val/mean recall': 0.9740196466445923, 'Val/mean hd95_metric': 5.613414287567139} +Cheakpoint... +Epoch [2538/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723633527755737, 'Val/mean miou_metric': 0.9568341374397278, 'Val/mean f1': 0.9746237993240356, 'Val/mean precision': 0.9752287864685059, 'Val/mean recall': 0.9740196466445923, 'Val/mean hd95_metric': 5.613414287567139} +Epoch [2539/4000] Training [1/16] Loss: 0.00567 +Epoch [2539/4000] Training [2/16] Loss: 0.00351 +Epoch [2539/4000] Training [3/16] Loss: 0.00339 +Epoch [2539/4000] Training [4/16] Loss: 0.00441 +Epoch [2539/4000] Training [5/16] Loss: 0.00520 +Epoch [2539/4000] Training [6/16] Loss: 0.00524 +Epoch [2539/4000] Training [7/16] Loss: 0.00368 +Epoch [2539/4000] Training [8/16] Loss: 0.00313 +Epoch [2539/4000] Training [9/16] Loss: 0.00294 +Epoch [2539/4000] Training [10/16] Loss: 0.00444 +Epoch [2539/4000] Training [11/16] Loss: 0.00411 +Epoch [2539/4000] Training [12/16] Loss: 0.00490 +Epoch [2539/4000] Training [13/16] Loss: 0.00510 +Epoch [2539/4000] Training [14/16] Loss: 0.00378 +Epoch [2539/4000] Training [15/16] Loss: 0.00524 +Epoch [2539/4000] Training [16/16] Loss: 0.00452 +Epoch [2539/4000] Training metric {'Train/mean dice_metric': 0.9974079132080078, 'Train/mean miou_metric': 0.9945586919784546, 'Train/mean f1': 0.9928253293037415, 'Train/mean precision': 0.9882436394691467, 'Train/mean recall': 0.9974496960639954, 'Train/mean hd95_metric': 0.9475297331809998} +Epoch [2539/4000] Validation [1/4] Loss: 0.40120 focal_loss 0.31214 dice_loss 0.08906 +Epoch [2539/4000] Validation [2/4] Loss: 0.70231 focal_loss 0.52695 dice_loss 0.17536 +Epoch [2539/4000] Validation [3/4] Loss: 0.38813 focal_loss 0.29943 dice_loss 0.08870 +Epoch [2539/4000] Validation [4/4] Loss: 0.76114 focal_loss 0.60310 dice_loss 0.15804 +Epoch [2539/4000] Validation metric {'Val/mean dice_metric': 0.9710451364517212, 'Val/mean miou_metric': 0.9554244875907898, 'Val/mean f1': 0.9739994406700134, 'Val/mean precision': 0.9741603136062622, 'Val/mean recall': 0.9738385081291199, 'Val/mean hd95_metric': 5.92614221572876} +Cheakpoint... +Epoch [2539/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710451364517212, 'Val/mean miou_metric': 0.9554244875907898, 'Val/mean f1': 0.9739994406700134, 'Val/mean precision': 0.9741603136062622, 'Val/mean recall': 0.9738385081291199, 'Val/mean hd95_metric': 5.92614221572876} +Epoch [2540/4000] Training [1/16] Loss: 0.00425 +Epoch [2540/4000] Training [2/16] Loss: 0.00394 +Epoch [2540/4000] Training [3/16] Loss: 0.00422 +Epoch [2540/4000] Training [4/16] Loss: 0.00426 +Epoch [2540/4000] Training [5/16] Loss: 0.00341 +Epoch [2540/4000] Training [6/16] Loss: 0.00499 +Epoch [2540/4000] Training [7/16] Loss: 0.00406 +Epoch [2540/4000] Training [8/16] Loss: 0.00469 +Epoch [2540/4000] Training [9/16] Loss: 0.00582 +Epoch [2540/4000] Training [10/16] Loss: 0.00353 +Epoch [2540/4000] Training [11/16] Loss: 0.00388 +Epoch [2540/4000] Training [12/16] Loss: 0.00373 +Epoch [2540/4000] Training [13/16] Loss: 0.00447 +Epoch [2540/4000] Training [14/16] Loss: 0.00405 +Epoch [2540/4000] Training [15/16] Loss: 0.00399 +Epoch [2540/4000] Training [16/16] Loss: 0.00318 +Epoch [2540/4000] Training metric {'Train/mean dice_metric': 0.9972496628761292, 'Train/mean miou_metric': 0.9942479133605957, 'Train/mean f1': 0.9926958680152893, 'Train/mean precision': 0.9881454110145569, 'Train/mean recall': 0.9972884654998779, 'Train/mean hd95_metric': 0.9503568410873413} +Epoch [2540/4000] Validation [1/4] Loss: 0.38446 focal_loss 0.29642 dice_loss 0.08804 +Epoch [2540/4000] Validation [2/4] Loss: 0.78666 focal_loss 0.60003 dice_loss 0.18663 +Epoch [2540/4000] Validation [3/4] Loss: 0.41923 focal_loss 0.32612 dice_loss 0.09310 +Epoch [2540/4000] Validation [4/4] Loss: 0.31950 focal_loss 0.22130 dice_loss 0.09820 +Epoch [2540/4000] Validation metric {'Val/mean dice_metric': 0.9709471464157104, 'Val/mean miou_metric': 0.9560664296150208, 'Val/mean f1': 0.9743737578392029, 'Val/mean precision': 0.9733253121376038, 'Val/mean recall': 0.9754244089126587, 'Val/mean hd95_metric': 5.258317470550537} +Cheakpoint... +Epoch [2540/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709471464157104, 'Val/mean miou_metric': 0.9560664296150208, 'Val/mean f1': 0.9743737578392029, 'Val/mean precision': 0.9733253121376038, 'Val/mean recall': 0.9754244089126587, 'Val/mean hd95_metric': 5.258317470550537} +Epoch [2541/4000] Training [1/16] Loss: 0.00415 +Epoch [2541/4000] Training [2/16] Loss: 0.00415 +Epoch [2541/4000] Training [3/16] Loss: 0.00366 +Epoch [2541/4000] Training [4/16] Loss: 0.00284 +Epoch [2541/4000] Training [5/16] Loss: 0.00473 +Epoch [2541/4000] Training [6/16] Loss: 0.00424 +Epoch [2541/4000] Training [7/16] Loss: 0.00375 +Epoch [2541/4000] Training [8/16] Loss: 0.00346 +Epoch [2541/4000] Training [9/16] Loss: 0.00438 +Epoch [2541/4000] Training [10/16] Loss: 0.00410 +Epoch [2541/4000] Training [11/16] Loss: 0.00559 +Epoch [2541/4000] Training [12/16] Loss: 0.00452 +Epoch [2541/4000] Training [13/16] Loss: 0.00513 +Epoch [2541/4000] Training [14/16] Loss: 0.00530 +Epoch [2541/4000] Training [15/16] Loss: 0.00409 +Epoch [2541/4000] Training [16/16] Loss: 0.00295 +Epoch [2541/4000] Training metric {'Train/mean dice_metric': 0.9972808361053467, 'Train/mean miou_metric': 0.9943097829818726, 'Train/mean f1': 0.9927172660827637, 'Train/mean precision': 0.9881691336631775, 'Train/mean recall': 0.9973074197769165, 'Train/mean hd95_metric': 0.9382246732711792} +Epoch [2541/4000] Validation [1/4] Loss: 0.42739 focal_loss 0.34101 dice_loss 0.08637 +Epoch [2541/4000] Validation [2/4] Loss: 0.37133 focal_loss 0.26038 dice_loss 0.11095 +Epoch [2541/4000] Validation [3/4] Loss: 0.35704 focal_loss 0.26951 dice_loss 0.08753 +Epoch [2541/4000] Validation [4/4] Loss: 0.64755 focal_loss 0.50529 dice_loss 0.14226 +Epoch [2541/4000] Validation metric {'Val/mean dice_metric': 0.9706009030342102, 'Val/mean miou_metric': 0.955033004283905, 'Val/mean f1': 0.9739022850990295, 'Val/mean precision': 0.9741266369819641, 'Val/mean recall': 0.973677933216095, 'Val/mean hd95_metric': 5.536736488342285} +Cheakpoint... +Epoch [2541/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706009030342102, 'Val/mean miou_metric': 0.955033004283905, 'Val/mean f1': 0.9739022850990295, 'Val/mean precision': 0.9741266369819641, 'Val/mean recall': 0.973677933216095, 'Val/mean hd95_metric': 5.536736488342285} +Epoch [2542/4000] Training [1/16] Loss: 0.00443 +Epoch [2542/4000] Training [2/16] Loss: 0.00313 +Epoch [2542/4000] Training [3/16] Loss: 0.00476 +Epoch [2542/4000] Training [4/16] Loss: 0.00334 +Epoch [2542/4000] Training [5/16] Loss: 0.00608 +Epoch [2542/4000] Training [6/16] Loss: 0.00318 +Epoch [2542/4000] Training [7/16] Loss: 0.00473 +Epoch [2542/4000] Training [8/16] Loss: 0.00350 +Epoch [2542/4000] Training [9/16] Loss: 0.00474 +Epoch [2542/4000] Training [10/16] Loss: 0.00359 +Epoch [2542/4000] Training [11/16] Loss: 0.00445 +Epoch [2542/4000] Training [12/16] Loss: 0.00301 +Epoch [2542/4000] Training [13/16] Loss: 0.00533 +Epoch [2542/4000] Training [14/16] Loss: 0.00365 +Epoch [2542/4000] Training [15/16] Loss: 0.00364 +Epoch [2542/4000] Training [16/16] Loss: 0.00345 +Epoch [2542/4000] Training metric {'Train/mean dice_metric': 0.9970209002494812, 'Train/mean miou_metric': 0.9938278198242188, 'Train/mean f1': 0.9926198720932007, 'Train/mean precision': 0.9881742000579834, 'Train/mean recall': 0.9971057176589966, 'Train/mean hd95_metric': 0.9642218947410583} +Epoch [2542/4000] Validation [1/4] Loss: 0.35419 focal_loss 0.28692 dice_loss 0.06727 +Epoch [2542/4000] Validation [2/4] Loss: 0.52167 focal_loss 0.37015 dice_loss 0.15152 +Epoch [2542/4000] Validation [3/4] Loss: 0.34841 focal_loss 0.25290 dice_loss 0.09551 +Epoch [2542/4000] Validation [4/4] Loss: 0.28382 focal_loss 0.18506 dice_loss 0.09876 +Epoch [2542/4000] Validation metric {'Val/mean dice_metric': 0.9706840515136719, 'Val/mean miou_metric': 0.9549905061721802, 'Val/mean f1': 0.9743085503578186, 'Val/mean precision': 0.9726496934890747, 'Val/mean recall': 0.9759732484817505, 'Val/mean hd95_metric': 5.802989959716797} +Cheakpoint... +Epoch [2542/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706840515136719, 'Val/mean miou_metric': 0.9549905061721802, 'Val/mean f1': 0.9743085503578186, 'Val/mean precision': 0.9726496934890747, 'Val/mean recall': 0.9759732484817505, 'Val/mean hd95_metric': 5.802989959716797} +Epoch [2543/4000] Training [1/16] Loss: 0.00547 +Epoch [2543/4000] Training [2/16] Loss: 0.00407 +Epoch [2543/4000] Training [3/16] Loss: 0.00397 +Epoch [2543/4000] Training [4/16] Loss: 0.00419 +Epoch [2543/4000] Training [5/16] Loss: 0.00397 +Epoch [2543/4000] Training [6/16] Loss: 0.00652 +Epoch [2543/4000] Training [7/16] Loss: 0.00348 +Epoch [2543/4000] Training [8/16] Loss: 0.00362 +Epoch [2543/4000] Training [9/16] Loss: 0.00378 +Epoch [2543/4000] Training [10/16] Loss: 0.00398 +Epoch [2543/4000] Training [11/16] Loss: 0.00834 +Epoch [2543/4000] Training [12/16] Loss: 0.00420 +Epoch [2543/4000] Training [13/16] Loss: 0.00535 +Epoch [2543/4000] Training [14/16] Loss: 0.00391 +Epoch [2543/4000] Training [15/16] Loss: 0.00472 +Epoch [2543/4000] Training [16/16] Loss: 0.00619 +Epoch [2543/4000] Training metric {'Train/mean dice_metric': 0.9970968961715698, 'Train/mean miou_metric': 0.9939374327659607, 'Train/mean f1': 0.9923512935638428, 'Train/mean precision': 0.9875720143318176, 'Train/mean recall': 0.997177004814148, 'Train/mean hd95_metric': 0.9825276732444763} +Epoch [2543/4000] Validation [1/4] Loss: 0.37677 focal_loss 0.29063 dice_loss 0.08614 +Epoch [2543/4000] Validation [2/4] Loss: 0.49151 focal_loss 0.34798 dice_loss 0.14353 +Epoch [2543/4000] Validation [3/4] Loss: 0.34677 focal_loss 0.25515 dice_loss 0.09162 +Epoch [2543/4000] Validation [4/4] Loss: 0.30687 focal_loss 0.21766 dice_loss 0.08921 +Epoch [2543/4000] Validation metric {'Val/mean dice_metric': 0.9720481634140015, 'Val/mean miou_metric': 0.9566816091537476, 'Val/mean f1': 0.974896252155304, 'Val/mean precision': 0.9733384251594543, 'Val/mean recall': 0.9764591455459595, 'Val/mean hd95_metric': 5.002284049987793} +Cheakpoint... +Epoch [2543/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720481634140015, 'Val/mean miou_metric': 0.9566816091537476, 'Val/mean f1': 0.974896252155304, 'Val/mean precision': 0.9733384251594543, 'Val/mean recall': 0.9764591455459595, 'Val/mean hd95_metric': 5.002284049987793} +Epoch [2544/4000] Training [1/16] Loss: 0.00590 +Epoch [2544/4000] Training [2/16] Loss: 0.00491 +Epoch [2544/4000] Training [3/16] Loss: 0.00436 +Epoch [2544/4000] Training [4/16] Loss: 0.00456 +Epoch [2544/4000] Training [5/16] Loss: 0.00414 +Epoch [2544/4000] Training [6/16] Loss: 0.00354 +Epoch [2544/4000] Training [7/16] Loss: 0.00697 +Epoch [2544/4000] Training [8/16] Loss: 0.00293 +Epoch [2544/4000] Training [9/16] Loss: 0.00441 +Epoch [2544/4000] Training [10/16] Loss: 0.00483 +Epoch [2544/4000] Training [11/16] Loss: 0.00434 +Epoch [2544/4000] Training [12/16] Loss: 0.00387 +Epoch [2544/4000] Training [13/16] Loss: 0.00366 +Epoch [2544/4000] Training [14/16] Loss: 0.00401 +Epoch [2544/4000] Training [15/16] Loss: 0.00445 +Epoch [2544/4000] Training [16/16] Loss: 0.00368 +Epoch [2544/4000] Training metric {'Train/mean dice_metric': 0.997175931930542, 'Train/mean miou_metric': 0.9940512180328369, 'Train/mean f1': 0.9916979670524597, 'Train/mean precision': 0.9863647818565369, 'Train/mean recall': 0.997089147567749, 'Train/mean hd95_metric': 0.9525552988052368} +Epoch [2544/4000] Validation [1/4] Loss: 0.38745 focal_loss 0.30989 dice_loss 0.07756 +Epoch [2544/4000] Validation [2/4] Loss: 0.43175 focal_loss 0.30966 dice_loss 0.12210 +Epoch [2544/4000] Validation [3/4] Loss: 0.24077 focal_loss 0.17685 dice_loss 0.06392 +Epoch [2544/4000] Validation [4/4] Loss: 0.44569 focal_loss 0.30840 dice_loss 0.13729 +Epoch [2544/4000] Validation metric {'Val/mean dice_metric': 0.9712285995483398, 'Val/mean miou_metric': 0.9558221697807312, 'Val/mean f1': 0.9740195274353027, 'Val/mean precision': 0.9726718068122864, 'Val/mean recall': 0.9753708243370056, 'Val/mean hd95_metric': 5.448868751525879} +Cheakpoint... +Epoch [2544/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712285995483398, 'Val/mean miou_metric': 0.9558221697807312, 'Val/mean f1': 0.9740195274353027, 'Val/mean precision': 0.9726718068122864, 'Val/mean recall': 0.9753708243370056, 'Val/mean hd95_metric': 5.448868751525879} +Epoch [2545/4000] Training [1/16] Loss: 0.00372 +Epoch [2545/4000] Training [2/16] Loss: 0.00341 +Epoch [2545/4000] Training [3/16] Loss: 0.00378 +Epoch [2545/4000] Training [4/16] Loss: 0.00331 +Epoch [2545/4000] Training [5/16] Loss: 0.00380 +Epoch [2545/4000] Training [6/16] Loss: 0.00422 +Epoch [2545/4000] Training [7/16] Loss: 0.00379 +Epoch [2545/4000] Training [8/16] Loss: 0.00352 +Epoch [2545/4000] Training [9/16] Loss: 0.00441 +Epoch [2545/4000] Training [10/16] Loss: 0.00372 +Epoch [2545/4000] Training [11/16] Loss: 0.00393 +Epoch [2545/4000] Training [12/16] Loss: 0.00420 +Epoch [2545/4000] Training [13/16] Loss: 0.00292 +Epoch [2545/4000] Training [14/16] Loss: 0.00432 +Epoch [2545/4000] Training [15/16] Loss: 0.00418 +Epoch [2545/4000] Training [16/16] Loss: 0.00623 +Epoch [2545/4000] Training metric {'Train/mean dice_metric': 0.997467041015625, 'Train/mean miou_metric': 0.994675874710083, 'Train/mean f1': 0.9928104281425476, 'Train/mean precision': 0.9882661700248718, 'Train/mean recall': 0.99739670753479, 'Train/mean hd95_metric': 0.9529851078987122} +Epoch [2545/4000] Validation [1/4] Loss: 0.37635 focal_loss 0.30414 dice_loss 0.07221 +Epoch [2545/4000] Validation [2/4] Loss: 0.37291 focal_loss 0.26285 dice_loss 0.11006 +Epoch [2545/4000] Validation [3/4] Loss: 0.45808 focal_loss 0.36027 dice_loss 0.09782 +Epoch [2545/4000] Validation [4/4] Loss: 0.44614 focal_loss 0.30878 dice_loss 0.13736 +Epoch [2545/4000] Validation metric {'Val/mean dice_metric': 0.9713324308395386, 'Val/mean miou_metric': 0.9565040469169617, 'Val/mean f1': 0.9746417999267578, 'Val/mean precision': 0.9732254147529602, 'Val/mean recall': 0.9760621786117554, 'Val/mean hd95_metric': 5.454163074493408} +Cheakpoint... +Epoch [2545/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713324308395386, 'Val/mean miou_metric': 0.9565040469169617, 'Val/mean f1': 0.9746417999267578, 'Val/mean precision': 0.9732254147529602, 'Val/mean recall': 0.9760621786117554, 'Val/mean hd95_metric': 5.454163074493408} +Epoch [2546/4000] Training [1/16] Loss: 0.00591 +Epoch [2546/4000] Training [2/16] Loss: 0.00443 +Epoch [2546/4000] Training [3/16] Loss: 0.00414 +Epoch [2546/4000] Training [4/16] Loss: 0.00452 +Epoch [2546/4000] Training [5/16] Loss: 0.00488 +Epoch [2546/4000] Training [6/16] Loss: 0.00561 +Epoch [2546/4000] Training [7/16] Loss: 0.00541 +Epoch [2546/4000] Training [8/16] Loss: 0.00355 +Epoch [2546/4000] Training [9/16] Loss: 0.00357 +Epoch [2546/4000] Training [10/16] Loss: 0.00384 +Epoch [2546/4000] Training [11/16] Loss: 0.00527 +Epoch [2546/4000] Training [12/16] Loss: 0.00427 +Epoch [2546/4000] Training [13/16] Loss: 0.00415 +Epoch [2546/4000] Training [14/16] Loss: 0.00419 +Epoch [2546/4000] Training [15/16] Loss: 0.00397 +Epoch [2546/4000] Training [16/16] Loss: 0.00591 +Epoch [2546/4000] Training metric {'Train/mean dice_metric': 0.9970398545265198, 'Train/mean miou_metric': 0.993822455406189, 'Train/mean f1': 0.9923539161682129, 'Train/mean precision': 0.9877890348434448, 'Train/mean recall': 0.9969611763954163, 'Train/mean hd95_metric': 0.9729540348052979} +Epoch [2546/4000] Validation [1/4] Loss: 0.40673 focal_loss 0.33683 dice_loss 0.06989 +Epoch [2546/4000] Validation [2/4] Loss: 0.43962 focal_loss 0.31220 dice_loss 0.12742 +Epoch [2546/4000] Validation [3/4] Loss: 0.43584 focal_loss 0.33916 dice_loss 0.09668 +Epoch [2546/4000] Validation [4/4] Loss: 0.32129 focal_loss 0.22914 dice_loss 0.09215 +Epoch [2546/4000] Validation metric {'Val/mean dice_metric': 0.9728052020072937, 'Val/mean miou_metric': 0.9571714401245117, 'Val/mean f1': 0.974731981754303, 'Val/mean precision': 0.9733563661575317, 'Val/mean recall': 0.9761113524436951, 'Val/mean hd95_metric': 5.183415412902832} +Cheakpoint... +Epoch [2546/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728052020072937, 'Val/mean miou_metric': 0.9571714401245117, 'Val/mean f1': 0.974731981754303, 'Val/mean precision': 0.9733563661575317, 'Val/mean recall': 0.9761113524436951, 'Val/mean hd95_metric': 5.183415412902832} +Epoch [2547/4000] Training [1/16] Loss: 0.00329 +Epoch [2547/4000] Training [2/16] Loss: 0.00457 +Epoch [2547/4000] Training [3/16] Loss: 0.00237 +Epoch [2547/4000] Training [4/16] Loss: 0.00376 +Epoch [2547/4000] Training [5/16] Loss: 0.00418 +Epoch [2547/4000] Training [6/16] Loss: 0.00433 +Epoch [2547/4000] Training [7/16] Loss: 0.00368 +Epoch [2547/4000] Training [8/16] Loss: 0.00551 +Epoch [2547/4000] Training [9/16] Loss: 0.00519 +Epoch [2547/4000] Training [10/16] Loss: 0.00360 +Epoch [2547/4000] Training [11/16] Loss: 0.00318 +Epoch [2547/4000] Training [12/16] Loss: 0.00479 +Epoch [2547/4000] Training [13/16] Loss: 0.00336 +Epoch [2547/4000] Training [14/16] Loss: 0.00409 +Epoch [2547/4000] Training [15/16] Loss: 0.00405 +Epoch [2547/4000] Training [16/16] Loss: 0.00389 +Epoch [2547/4000] Training metric {'Train/mean dice_metric': 0.9974420666694641, 'Train/mean miou_metric': 0.9946212768554688, 'Train/mean f1': 0.9926613569259644, 'Train/mean precision': 0.9879439473152161, 'Train/mean recall': 0.9974240064620972, 'Train/mean hd95_metric': 0.933063268661499} +Epoch [2547/4000] Validation [1/4] Loss: 0.42382 focal_loss 0.32811 dice_loss 0.09571 +Epoch [2547/4000] Validation [2/4] Loss: 0.94893 focal_loss 0.76430 dice_loss 0.18462 +Epoch [2547/4000] Validation [3/4] Loss: 0.40320 focal_loss 0.31335 dice_loss 0.08986 +Epoch [2547/4000] Validation [4/4] Loss: 0.43678 focal_loss 0.30322 dice_loss 0.13356 +Epoch [2547/4000] Validation metric {'Val/mean dice_metric': 0.9718896746635437, 'Val/mean miou_metric': 0.9568848609924316, 'Val/mean f1': 0.974103569984436, 'Val/mean precision': 0.9719635248184204, 'Val/mean recall': 0.9762530326843262, 'Val/mean hd95_metric': 5.329936981201172} +Cheakpoint... +Epoch [2547/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718896746635437, 'Val/mean miou_metric': 0.9568848609924316, 'Val/mean f1': 0.974103569984436, 'Val/mean precision': 0.9719635248184204, 'Val/mean recall': 0.9762530326843262, 'Val/mean hd95_metric': 5.329936981201172} +Epoch [2548/4000] Training [1/16] Loss: 0.00494 +Epoch [2548/4000] Training [2/16] Loss: 0.00429 +Epoch [2548/4000] Training [3/16] Loss: 0.00383 +Epoch [2548/4000] Training [4/16] Loss: 0.00249 +Epoch [2548/4000] Training [5/16] Loss: 0.00474 +Epoch [2548/4000] Training [6/16] Loss: 0.00366 +Epoch [2548/4000] Training [7/16] Loss: 0.00299 +Epoch [2548/4000] Training [8/16] Loss: 0.00421 +Epoch [2548/4000] Training [9/16] Loss: 0.00403 +Epoch [2548/4000] Training [10/16] Loss: 0.00372 +Epoch [2548/4000] Training [11/16] Loss: 0.00417 +Epoch [2548/4000] Training [12/16] Loss: 0.00395 +Epoch [2548/4000] Training [13/16] Loss: 0.00327 +Epoch [2548/4000] Training [14/16] Loss: 0.00294 +Epoch [2548/4000] Training [15/16] Loss: 0.00616 +Epoch [2548/4000] Training [16/16] Loss: 0.00496 +Epoch [2548/4000] Training metric {'Train/mean dice_metric': 0.997360348701477, 'Train/mean miou_metric': 0.9944276809692383, 'Train/mean f1': 0.9916462302207947, 'Train/mean precision': 0.9861702919006348, 'Train/mean recall': 0.9971832633018494, 'Train/mean hd95_metric': 0.9882063269615173} +Epoch [2548/4000] Validation [1/4] Loss: 0.40752 focal_loss 0.31672 dice_loss 0.09080 +Epoch [2548/4000] Validation [2/4] Loss: 0.46380 focal_loss 0.33112 dice_loss 0.13268 +Epoch [2548/4000] Validation [3/4] Loss: 0.42924 focal_loss 0.33992 dice_loss 0.08932 +Epoch [2548/4000] Validation [4/4] Loss: 0.28517 focal_loss 0.19856 dice_loss 0.08662 +Epoch [2548/4000] Validation metric {'Val/mean dice_metric': 0.9732658267021179, 'Val/mean miou_metric': 0.9580690264701843, 'Val/mean f1': 0.9747077226638794, 'Val/mean precision': 0.9726515412330627, 'Val/mean recall': 0.9767725467681885, 'Val/mean hd95_metric': 5.23381233215332} +Cheakpoint... +Epoch [2548/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732658267021179, 'Val/mean miou_metric': 0.9580690264701843, 'Val/mean f1': 0.9747077226638794, 'Val/mean precision': 0.9726515412330627, 'Val/mean recall': 0.9767725467681885, 'Val/mean hd95_metric': 5.23381233215332} +Epoch [2549/4000] Training [1/16] Loss: 0.00445 +Epoch [2549/4000] Training [2/16] Loss: 0.00484 +Epoch [2549/4000] Training [3/16] Loss: 0.00358 +Epoch [2549/4000] Training [4/16] Loss: 0.00339 +Epoch [2549/4000] Training [5/16] Loss: 0.00468 +Epoch [2549/4000] Training [6/16] Loss: 0.00392 +Epoch [2549/4000] Training [7/16] Loss: 0.00352 +Epoch [2549/4000] Training [8/16] Loss: 0.00411 +Epoch [2549/4000] Training [9/16] Loss: 0.00530 +Epoch [2549/4000] Training [10/16] Loss: 0.00372 +Epoch [2549/4000] Training [11/16] Loss: 0.00436 +Epoch [2549/4000] Training [12/16] Loss: 0.00731 +Epoch [2549/4000] Training [13/16] Loss: 0.00396 +Epoch [2549/4000] Training [14/16] Loss: 0.00357 +Epoch [2549/4000] Training [15/16] Loss: 0.00367 +Epoch [2549/4000] Training [16/16] Loss: 0.00440 +Epoch [2549/4000] Training metric {'Train/mean dice_metric': 0.997359573841095, 'Train/mean miou_metric': 0.9944621324539185, 'Train/mean f1': 0.992777943611145, 'Train/mean precision': 0.9883706569671631, 'Train/mean recall': 0.997224748134613, 'Train/mean hd95_metric': 1.0016392469406128} +Epoch [2549/4000] Validation [1/4] Loss: 0.37794 focal_loss 0.29523 dice_loss 0.08271 +Epoch [2549/4000] Validation [2/4] Loss: 0.58488 focal_loss 0.42772 dice_loss 0.15716 +Epoch [2549/4000] Validation [3/4] Loss: 0.39292 focal_loss 0.30203 dice_loss 0.09089 +Epoch [2549/4000] Validation [4/4] Loss: 0.37707 focal_loss 0.25951 dice_loss 0.11756 +Epoch [2549/4000] Validation metric {'Val/mean dice_metric': 0.971401035785675, 'Val/mean miou_metric': 0.9562630653381348, 'Val/mean f1': 0.974605143070221, 'Val/mean precision': 0.9738598465919495, 'Val/mean recall': 0.9753516316413879, 'Val/mean hd95_metric': 5.511135101318359} +Cheakpoint... +Epoch [2549/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971401035785675, 'Val/mean miou_metric': 0.9562630653381348, 'Val/mean f1': 0.974605143070221, 'Val/mean precision': 0.9738598465919495, 'Val/mean recall': 0.9753516316413879, 'Val/mean hd95_metric': 5.511135101318359} +Epoch [2550/4000] Training [1/16] Loss: 0.00340 +Epoch [2550/4000] Training [2/16] Loss: 0.00370 +Epoch [2550/4000] Training [3/16] Loss: 0.00488 +Epoch [2550/4000] Training [4/16] Loss: 0.00318 +Epoch [2550/4000] Training [5/16] Loss: 0.00515 +Epoch [2550/4000] Training [6/16] Loss: 0.00463 +Epoch [2550/4000] Training [7/16] Loss: 0.00417 +Epoch [2550/4000] Training [8/16] Loss: 0.00439 +Epoch [2550/4000] Training [9/16] Loss: 0.00357 +Epoch [2550/4000] Training [10/16] Loss: 0.00495 +Epoch [2550/4000] Training [11/16] Loss: 0.00440 +Epoch [2550/4000] Training [12/16] Loss: 0.00412 +Epoch [2550/4000] Training [13/16] Loss: 0.00470 +Epoch [2550/4000] Training [14/16] Loss: 0.00460 +Epoch [2550/4000] Training [15/16] Loss: 0.00377 +Epoch [2550/4000] Training [16/16] Loss: 0.00466 +Epoch [2550/4000] Training metric {'Train/mean dice_metric': 0.9973611235618591, 'Train/mean miou_metric': 0.9944548606872559, 'Train/mean f1': 0.9925224781036377, 'Train/mean precision': 0.9878021478652954, 'Train/mean recall': 0.9972880482673645, 'Train/mean hd95_metric': 0.9537761807441711} +Epoch [2550/4000] Validation [1/4] Loss: 0.33998 focal_loss 0.27413 dice_loss 0.06584 +Epoch [2550/4000] Validation [2/4] Loss: 0.67595 focal_loss 0.50002 dice_loss 0.17593 +Epoch [2550/4000] Validation [3/4] Loss: 0.36159 focal_loss 0.26654 dice_loss 0.09505 +Epoch [2550/4000] Validation [4/4] Loss: 0.29467 focal_loss 0.20414 dice_loss 0.09053 +Epoch [2550/4000] Validation metric {'Val/mean dice_metric': 0.9692357778549194, 'Val/mean miou_metric': 0.9537175297737122, 'Val/mean f1': 0.9729921817779541, 'Val/mean precision': 0.9741023182868958, 'Val/mean recall': 0.9718846678733826, 'Val/mean hd95_metric': 5.550723552703857} +Cheakpoint... +Epoch [2550/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9692357778549194, 'Val/mean miou_metric': 0.9537175297737122, 'Val/mean f1': 0.9729921817779541, 'Val/mean precision': 0.9741023182868958, 'Val/mean recall': 0.9718846678733826, 'Val/mean hd95_metric': 5.550723552703857} +Epoch [2551/4000] Training [1/16] Loss: 0.00351 +Epoch [2551/4000] Training [2/16] Loss: 0.00453 +Epoch [2551/4000] Training [3/16] Loss: 0.00345 +Epoch [2551/4000] Training [4/16] Loss: 0.00446 +Epoch [2551/4000] Training [5/16] Loss: 0.00407 +Epoch [2551/4000] Training [6/16] Loss: 0.00654 +Epoch [2551/4000] Training [7/16] Loss: 0.00573 +Epoch [2551/4000] Training [8/16] Loss: 0.00376 +Epoch [2551/4000] Training [9/16] Loss: 0.00404 +Epoch [2551/4000] Training [10/16] Loss: 0.00375 +Epoch [2551/4000] Training [11/16] Loss: 0.00315 +Epoch [2551/4000] Training [12/16] Loss: 0.00594 +Epoch [2551/4000] Training [13/16] Loss: 0.00422 +Epoch [2551/4000] Training [14/16] Loss: 0.00454 +Epoch [2551/4000] Training [15/16] Loss: 0.00459 +Epoch [2551/4000] Training [16/16] Loss: 0.00387 +Epoch [2551/4000] Training metric {'Train/mean dice_metric': 0.9974207878112793, 'Train/mean miou_metric': 0.9945868253707886, 'Train/mean f1': 0.9928066730499268, 'Train/mean precision': 0.9882568717002869, 'Train/mean recall': 0.9973985552787781, 'Train/mean hd95_metric': 0.9323795437812805} +Epoch [2551/4000] Validation [1/4] Loss: 0.45746 focal_loss 0.35063 dice_loss 0.10682 +Epoch [2551/4000] Validation [2/4] Loss: 0.54647 focal_loss 0.40204 dice_loss 0.14443 +Epoch [2551/4000] Validation [3/4] Loss: 0.29791 focal_loss 0.21696 dice_loss 0.08095 +Epoch [2551/4000] Validation [4/4] Loss: 0.42630 focal_loss 0.28826 dice_loss 0.13804 +Epoch [2551/4000] Validation metric {'Val/mean dice_metric': 0.9702007174491882, 'Val/mean miou_metric': 0.9550067186355591, 'Val/mean f1': 0.9746006727218628, 'Val/mean precision': 0.9744731783866882, 'Val/mean recall': 0.9747282862663269, 'Val/mean hd95_metric': 5.467948913574219} +Cheakpoint... +Epoch [2551/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702007174491882, 'Val/mean miou_metric': 0.9550067186355591, 'Val/mean f1': 0.9746006727218628, 'Val/mean precision': 0.9744731783866882, 'Val/mean recall': 0.9747282862663269, 'Val/mean hd95_metric': 5.467948913574219} +Epoch [2552/4000] Training [1/16] Loss: 0.00337 +Epoch [2552/4000] Training [2/16] Loss: 0.00359 +Epoch [2552/4000] Training [3/16] Loss: 0.00330 +Epoch [2552/4000] Training [4/16] Loss: 0.00295 +Epoch [2552/4000] Training [5/16] Loss: 0.00406 +Epoch [2552/4000] Training [6/16] Loss: 0.00503 +Epoch [2552/4000] Training [7/16] Loss: 0.00334 +Epoch [2552/4000] Training [8/16] Loss: 0.00465 +Epoch [2552/4000] Training [9/16] Loss: 0.00480 +Epoch [2552/4000] Training [10/16] Loss: 0.00326 +Epoch [2552/4000] Training [11/16] Loss: 0.00405 +Epoch [2552/4000] Training [12/16] Loss: 0.00348 +Epoch [2552/4000] Training [13/16] Loss: 0.00322 +Epoch [2552/4000] Training [14/16] Loss: 0.00424 +Epoch [2552/4000] Training [15/16] Loss: 0.00551 +Epoch [2552/4000] Training [16/16] Loss: 0.00436 +Epoch [2552/4000] Training metric {'Train/mean dice_metric': 0.9975471496582031, 'Train/mean miou_metric': 0.9948257207870483, 'Train/mean f1': 0.9928917288780212, 'Train/mean precision': 0.9882590174674988, 'Train/mean recall': 0.9975681304931641, 'Train/mean hd95_metric': 0.9599114656448364} +Epoch [2552/4000] Validation [1/4] Loss: 0.50218 focal_loss 0.38861 dice_loss 0.11357 +Epoch [2552/4000] Validation [2/4] Loss: 0.47245 focal_loss 0.34355 dice_loss 0.12890 +Epoch [2552/4000] Validation [3/4] Loss: 0.32090 focal_loss 0.23136 dice_loss 0.08954 +Epoch [2552/4000] Validation [4/4] Loss: 0.39124 focal_loss 0.27808 dice_loss 0.11317 +Epoch [2552/4000] Validation metric {'Val/mean dice_metric': 0.9711440205574036, 'Val/mean miou_metric': 0.9558555483818054, 'Val/mean f1': 0.9745215773582458, 'Val/mean precision': 0.9744406938552856, 'Val/mean recall': 0.9746025204658508, 'Val/mean hd95_metric': 5.076958656311035} +Cheakpoint... +Epoch [2552/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711440205574036, 'Val/mean miou_metric': 0.9558555483818054, 'Val/mean f1': 0.9745215773582458, 'Val/mean precision': 0.9744406938552856, 'Val/mean recall': 0.9746025204658508, 'Val/mean hd95_metric': 5.076958656311035} +Epoch [2553/4000] Training [1/16] Loss: 0.00469 +Epoch [2553/4000] Training [2/16] Loss: 0.00321 +Epoch [2553/4000] Training [3/16] Loss: 0.00364 +Epoch [2553/4000] Training [4/16] Loss: 0.00400 +Epoch [2553/4000] Training [5/16] Loss: 0.00580 +Epoch [2553/4000] Training [6/16] Loss: 0.00502 +Epoch [2553/4000] Training [7/16] Loss: 0.00452 +Epoch [2553/4000] Training [8/16] Loss: 0.00484 +Epoch [2553/4000] Training [9/16] Loss: 0.00463 +Epoch [2553/4000] Training [10/16] Loss: 0.00307 +Epoch [2553/4000] Training [11/16] Loss: 0.00412 +Epoch [2553/4000] Training [12/16] Loss: 0.00381 +Epoch [2553/4000] Training [13/16] Loss: 0.00522 +Epoch [2553/4000] Training [14/16] Loss: 0.00285 +Epoch [2553/4000] Training [15/16] Loss: 0.00546 +Epoch [2553/4000] Training [16/16] Loss: 0.00399 +Epoch [2553/4000] Training metric {'Train/mean dice_metric': 0.9975290298461914, 'Train/mean miou_metric': 0.9947991371154785, 'Train/mean f1': 0.9928581714630127, 'Train/mean precision': 0.988308310508728, 'Train/mean recall': 0.9974501132965088, 'Train/mean hd95_metric': 0.9346534013748169} +Epoch [2553/4000] Validation [1/4] Loss: 0.47103 focal_loss 0.36710 dice_loss 0.10393 +Epoch [2553/4000] Validation [2/4] Loss: 0.49858 focal_loss 0.35305 dice_loss 0.14553 +Epoch [2553/4000] Validation [3/4] Loss: 0.35999 focal_loss 0.26802 dice_loss 0.09196 +Epoch [2553/4000] Validation [4/4] Loss: 0.51831 focal_loss 0.39318 dice_loss 0.12514 +Epoch [2553/4000] Validation metric {'Val/mean dice_metric': 0.9727781414985657, 'Val/mean miou_metric': 0.9572650790214539, 'Val/mean f1': 0.974109411239624, 'Val/mean precision': 0.9734862446784973, 'Val/mean recall': 0.9747334122657776, 'Val/mean hd95_metric': 5.0461225509643555} +Cheakpoint... +Epoch [2553/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727781414985657, 'Val/mean miou_metric': 0.9572650790214539, 'Val/mean f1': 0.974109411239624, 'Val/mean precision': 0.9734862446784973, 'Val/mean recall': 0.9747334122657776, 'Val/mean hd95_metric': 5.0461225509643555} +Epoch [2554/4000] Training [1/16] Loss: 0.00342 +Epoch [2554/4000] Training [2/16] Loss: 0.00370 +Epoch [2554/4000] Training [3/16] Loss: 0.00298 +Epoch [2554/4000] Training [4/16] Loss: 0.00409 +Epoch [2554/4000] Training [5/16] Loss: 0.00402 +Epoch [2554/4000] Training [6/16] Loss: 0.00330 +Epoch [2554/4000] Training [7/16] Loss: 0.00346 +Epoch [2554/4000] Training [8/16] Loss: 0.00376 +Epoch [2554/4000] Training [9/16] Loss: 0.00359 +Epoch [2554/4000] Training [10/16] Loss: 0.00432 +Epoch [2554/4000] Training [11/16] Loss: 0.00306 +Epoch [2554/4000] Training [12/16] Loss: 0.00570 +Epoch [2554/4000] Training [13/16] Loss: 0.00379 +Epoch [2554/4000] Training [14/16] Loss: 0.00468 +Epoch [2554/4000] Training [15/16] Loss: 0.00381 +Epoch [2554/4000] Training [16/16] Loss: 0.00493 +Epoch [2554/4000] Training metric {'Train/mean dice_metric': 0.9975746870040894, 'Train/mean miou_metric': 0.9948840141296387, 'Train/mean f1': 0.9928004145622253, 'Train/mean precision': 0.9882100224494934, 'Train/mean recall': 0.9974336624145508, 'Train/mean hd95_metric': 0.9354070425033569} +Epoch [2554/4000] Validation [1/4] Loss: 0.37145 focal_loss 0.28100 dice_loss 0.09044 +Epoch [2554/4000] Validation [2/4] Loss: 0.86279 focal_loss 0.60966 dice_loss 0.25313 +Epoch [2554/4000] Validation [3/4] Loss: 0.28571 focal_loss 0.20299 dice_loss 0.08272 +Epoch [2554/4000] Validation [4/4] Loss: 0.36532 focal_loss 0.24250 dice_loss 0.12282 +Epoch [2554/4000] Validation metric {'Val/mean dice_metric': 0.96917325258255, 'Val/mean miou_metric': 0.9542838335037231, 'Val/mean f1': 0.9743067026138306, 'Val/mean precision': 0.9737264513969421, 'Val/mean recall': 0.9748876690864563, 'Val/mean hd95_metric': 5.1934309005737305} +Cheakpoint... +Epoch [2554/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.96917325258255, 'Val/mean miou_metric': 0.9542838335037231, 'Val/mean f1': 0.9743067026138306, 'Val/mean precision': 0.9737264513969421, 'Val/mean recall': 0.9748876690864563, 'Val/mean hd95_metric': 5.1934309005737305} +Epoch [2555/4000] Training [1/16] Loss: 0.00600 +Epoch [2555/4000] Training [2/16] Loss: 0.00413 +Epoch [2555/4000] Training [3/16] Loss: 0.00426 +Epoch [2555/4000] Training [4/16] Loss: 0.00462 +Epoch [2555/4000] Training [5/16] Loss: 0.00407 +Epoch [2555/4000] Training [6/16] Loss: 0.00527 +Epoch [2555/4000] Training [7/16] Loss: 0.00461 +Epoch [2555/4000] Training [8/16] Loss: 0.00381 +Epoch [2555/4000] Training [9/16] Loss: 0.00424 +Epoch [2555/4000] Training [10/16] Loss: 0.00369 +Epoch [2555/4000] Training [11/16] Loss: 0.00438 +Epoch [2555/4000] Training [12/16] Loss: 0.00654 +Epoch [2555/4000] Training [13/16] Loss: 0.00449 +Epoch [2555/4000] Training [14/16] Loss: 0.00407 +Epoch [2555/4000] Training [15/16] Loss: 0.00267 +Epoch [2555/4000] Training [16/16] Loss: 0.00356 +Epoch [2555/4000] Training metric {'Train/mean dice_metric': 0.9971991777420044, 'Train/mean miou_metric': 0.9941461086273193, 'Train/mean f1': 0.992530345916748, 'Train/mean precision': 0.9879270195960999, 'Train/mean recall': 0.9971767067909241, 'Train/mean hd95_metric': 0.9570446014404297} +Epoch [2555/4000] Validation [1/4] Loss: 0.41037 focal_loss 0.33666 dice_loss 0.07370 +Epoch [2555/4000] Validation [2/4] Loss: 0.48451 focal_loss 0.35198 dice_loss 0.13253 +Epoch [2555/4000] Validation [3/4] Loss: 0.25135 focal_loss 0.18405 dice_loss 0.06731 +Epoch [2555/4000] Validation [4/4] Loss: 0.28898 focal_loss 0.19014 dice_loss 0.09884 +Epoch [2555/4000] Validation metric {'Val/mean dice_metric': 0.9722396731376648, 'Val/mean miou_metric': 0.9567626714706421, 'Val/mean f1': 0.9743541479110718, 'Val/mean precision': 0.9715970754623413, 'Val/mean recall': 0.9771268963813782, 'Val/mean hd95_metric': 5.291327476501465} +Cheakpoint... +Epoch [2555/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722396731376648, 'Val/mean miou_metric': 0.9567626714706421, 'Val/mean f1': 0.9743541479110718, 'Val/mean precision': 0.9715970754623413, 'Val/mean recall': 0.9771268963813782, 'Val/mean hd95_metric': 5.291327476501465} +Epoch [2556/4000] Training [1/16] Loss: 0.00458 +Epoch [2556/4000] Training [2/16] Loss: 0.00397 +Epoch [2556/4000] Training [3/16] Loss: 0.00423 +Epoch [2556/4000] Training [4/16] Loss: 0.00318 +Epoch [2556/4000] Training [5/16] Loss: 0.00348 +Epoch [2556/4000] Training [6/16] Loss: 0.00543 +Epoch [2556/4000] Training [7/16] Loss: 0.00344 +Epoch [2556/4000] Training [8/16] Loss: 0.00316 +Epoch [2556/4000] Training [9/16] Loss: 0.00422 +Epoch [2556/4000] Training [10/16] Loss: 0.00375 +Epoch [2556/4000] Training [11/16] Loss: 0.00526 +Epoch [2556/4000] Training [12/16] Loss: 0.00385 +Epoch [2556/4000] Training [13/16] Loss: 0.00463 +Epoch [2556/4000] Training [14/16] Loss: 0.00429 +Epoch [2556/4000] Training [15/16] Loss: 0.00423 +Epoch [2556/4000] Training [16/16] Loss: 0.00393 +Epoch [2556/4000] Training metric {'Train/mean dice_metric': 0.9973848462104797, 'Train/mean miou_metric': 0.9945156574249268, 'Train/mean f1': 0.9927348494529724, 'Train/mean precision': 0.9882183074951172, 'Train/mean recall': 0.9972930550575256, 'Train/mean hd95_metric': 0.9603849649429321} +Epoch [2556/4000] Validation [1/4] Loss: 0.38549 focal_loss 0.30545 dice_loss 0.08003 +Epoch [2556/4000] Validation [2/4] Loss: 0.77895 focal_loss 0.58825 dice_loss 0.19071 +Epoch [2556/4000] Validation [3/4] Loss: 0.40986 focal_loss 0.31482 dice_loss 0.09503 +Epoch [2556/4000] Validation [4/4] Loss: 0.37026 focal_loss 0.25589 dice_loss 0.11437 +Epoch [2556/4000] Validation metric {'Val/mean dice_metric': 0.970526397228241, 'Val/mean miou_metric': 0.9554889798164368, 'Val/mean f1': 0.9741902947425842, 'Val/mean precision': 0.9722216129302979, 'Val/mean recall': 0.9761670827865601, 'Val/mean hd95_metric': 5.040007591247559} +Cheakpoint... +Epoch [2556/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970526397228241, 'Val/mean miou_metric': 0.9554889798164368, 'Val/mean f1': 0.9741902947425842, 'Val/mean precision': 0.9722216129302979, 'Val/mean recall': 0.9761670827865601, 'Val/mean hd95_metric': 5.040007591247559} +Epoch [2557/4000] Training [1/16] Loss: 0.00472 +Epoch [2557/4000] Training [2/16] Loss: 0.00315 +Epoch [2557/4000] Training [3/16] Loss: 0.00467 +Epoch [2557/4000] Training [4/16] Loss: 0.00424 +Epoch [2557/4000] Training [5/16] Loss: 0.00431 +Epoch [2557/4000] Training [6/16] Loss: 0.00419 +Epoch [2557/4000] Training [7/16] Loss: 0.00348 +Epoch [2557/4000] Training [8/16] Loss: 0.00336 +Epoch [2557/4000] Training [9/16] Loss: 0.00340 +Epoch [2557/4000] Training [10/16] Loss: 0.00297 +Epoch [2557/4000] Training [11/16] Loss: 0.00467 +Epoch [2557/4000] Training [12/16] Loss: 0.00498 +Epoch [2557/4000] Training [13/16] Loss: 0.00681 +Epoch [2557/4000] Training [14/16] Loss: 0.00425 +Epoch [2557/4000] Training [15/16] Loss: 0.00564 +Epoch [2557/4000] Training [16/16] Loss: 0.00394 +Epoch [2557/4000] Training metric {'Train/mean dice_metric': 0.9972956776618958, 'Train/mean miou_metric': 0.9943362474441528, 'Train/mean f1': 0.9926894903182983, 'Train/mean precision': 0.9880926012992859, 'Train/mean recall': 0.9973292946815491, 'Train/mean hd95_metric': 0.942828893661499} +Epoch [2557/4000] Validation [1/4] Loss: 0.42166 focal_loss 0.33674 dice_loss 0.08492 +Epoch [2557/4000] Validation [2/4] Loss: 0.46066 focal_loss 0.33144 dice_loss 0.12922 +Epoch [2557/4000] Validation [3/4] Loss: 0.35651 focal_loss 0.26832 dice_loss 0.08820 +Epoch [2557/4000] Validation [4/4] Loss: 0.30756 focal_loss 0.20603 dice_loss 0.10153 +Epoch [2557/4000] Validation metric {'Val/mean dice_metric': 0.972202479839325, 'Val/mean miou_metric': 0.9562538266181946, 'Val/mean f1': 0.9744433760643005, 'Val/mean precision': 0.9718354344367981, 'Val/mean recall': 0.9770653247833252, 'Val/mean hd95_metric': 5.140079975128174} +Cheakpoint... +Epoch [2557/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972202479839325, 'Val/mean miou_metric': 0.9562538266181946, 'Val/mean f1': 0.9744433760643005, 'Val/mean precision': 0.9718354344367981, 'Val/mean recall': 0.9770653247833252, 'Val/mean hd95_metric': 5.140079975128174} +Epoch [2558/4000] Training [1/16] Loss: 0.00357 +Epoch [2558/4000] Training [2/16] Loss: 0.00312 +Epoch [2558/4000] Training [3/16] Loss: 0.00447 +Epoch [2558/4000] Training [4/16] Loss: 0.00411 +Epoch [2558/4000] Training [5/16] Loss: 0.00486 +Epoch [2558/4000] Training [6/16] Loss: 0.00646 +Epoch [2558/4000] Training [7/16] Loss: 0.00396 +Epoch [2558/4000] Training [8/16] Loss: 0.00376 +Epoch [2558/4000] Training [9/16] Loss: 0.00512 +Epoch [2558/4000] Training [10/16] Loss: 0.00341 +Epoch [2558/4000] Training [11/16] Loss: 0.00464 +Epoch [2558/4000] Training [12/16] Loss: 0.00421 +Epoch [2558/4000] Training [13/16] Loss: 0.00388 +Epoch [2558/4000] Training [14/16] Loss: 0.00322 +Epoch [2558/4000] Training [15/16] Loss: 0.00497 +Epoch [2558/4000] Training [16/16] Loss: 0.00413 +Epoch [2558/4000] Training metric {'Train/mean dice_metric': 0.9974231719970703, 'Train/mean miou_metric': 0.9945923089981079, 'Train/mean f1': 0.9927343130111694, 'Train/mean precision': 0.9882444739341736, 'Train/mean recall': 0.9972650408744812, 'Train/mean hd95_metric': 0.9456887245178223} +Epoch [2558/4000] Validation [1/4] Loss: 0.40480 focal_loss 0.32109 dice_loss 0.08371 +Epoch [2558/4000] Validation [2/4] Loss: 0.49143 focal_loss 0.36047 dice_loss 0.13097 +Epoch [2558/4000] Validation [3/4] Loss: 0.35202 focal_loss 0.25827 dice_loss 0.09376 +Epoch [2558/4000] Validation [4/4] Loss: 0.77022 focal_loss 0.60250 dice_loss 0.16772 +Epoch [2558/4000] Validation metric {'Val/mean dice_metric': 0.9703426361083984, 'Val/mean miou_metric': 0.9547541737556458, 'Val/mean f1': 0.9736180305480957, 'Val/mean precision': 0.9739974737167358, 'Val/mean recall': 0.973239004611969, 'Val/mean hd95_metric': 5.165664196014404} +Cheakpoint... +Epoch [2558/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703426361083984, 'Val/mean miou_metric': 0.9547541737556458, 'Val/mean f1': 0.9736180305480957, 'Val/mean precision': 0.9739974737167358, 'Val/mean recall': 0.973239004611969, 'Val/mean hd95_metric': 5.165664196014404} +Epoch [2559/4000] Training [1/16] Loss: 0.00384 +Epoch [2559/4000] Training [2/16] Loss: 0.00382 +Epoch [2559/4000] Training [3/16] Loss: 0.00488 +Epoch [2559/4000] Training [4/16] Loss: 0.00337 +Epoch [2559/4000] Training [5/16] Loss: 0.00412 +Epoch [2559/4000] Training [6/16] Loss: 0.00488 +Epoch [2559/4000] Training [7/16] Loss: 0.00554 +Epoch [2559/4000] Training [8/16] Loss: 0.00427 +Epoch [2559/4000] Training [9/16] Loss: 0.00584 +Epoch [2559/4000] Training [10/16] Loss: 0.00382 +Epoch [2559/4000] Training [11/16] Loss: 0.00496 +Epoch [2559/4000] Training [12/16] Loss: 0.00375 +Epoch [2559/4000] Training [13/16] Loss: 0.00507 +Epoch [2559/4000] Training [14/16] Loss: 0.00462 +Epoch [2559/4000] Training [15/16] Loss: 0.00369 +Epoch [2559/4000] Training [16/16] Loss: 0.00523 +Epoch [2559/4000] Training metric {'Train/mean dice_metric': 0.997028112411499, 'Train/mean miou_metric': 0.9938322901725769, 'Train/mean f1': 0.9926548004150391, 'Train/mean precision': 0.9882141947746277, 'Train/mean recall': 0.9971354603767395, 'Train/mean hd95_metric': 0.9536324739456177} +Epoch [2559/4000] Validation [1/4] Loss: 0.36969 focal_loss 0.30137 dice_loss 0.06831 +Epoch [2559/4000] Validation [2/4] Loss: 1.31399 focal_loss 1.06188 dice_loss 0.25211 +Epoch [2559/4000] Validation [3/4] Loss: 0.33809 focal_loss 0.24850 dice_loss 0.08959 +Epoch [2559/4000] Validation [4/4] Loss: 0.57362 focal_loss 0.42128 dice_loss 0.15234 +Epoch [2559/4000] Validation metric {'Val/mean dice_metric': 0.9691885113716125, 'Val/mean miou_metric': 0.9536498785018921, 'Val/mean f1': 0.9734160304069519, 'Val/mean precision': 0.9719377756118774, 'Val/mean recall': 0.9748987555503845, 'Val/mean hd95_metric': 5.550751209259033} +Cheakpoint... +Epoch [2559/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691885113716125, 'Val/mean miou_metric': 0.9536498785018921, 'Val/mean f1': 0.9734160304069519, 'Val/mean precision': 0.9719377756118774, 'Val/mean recall': 0.9748987555503845, 'Val/mean hd95_metric': 5.550751209259033} +Epoch [2560/4000] Training [1/16] Loss: 0.00403 +Epoch [2560/4000] Training [2/16] Loss: 0.00539 +Epoch [2560/4000] Training [3/16] Loss: 0.00515 +Epoch [2560/4000] Training [4/16] Loss: 0.00304 +Epoch [2560/4000] Training [5/16] Loss: 0.00342 +Epoch [2560/4000] Training [6/16] Loss: 0.00391 +Epoch [2560/4000] Training [7/16] Loss: 0.00462 +Epoch [2560/4000] Training [8/16] Loss: 0.00466 +Epoch [2560/4000] Training [9/16] Loss: 0.00347 +Epoch [2560/4000] Training [10/16] Loss: 0.00326 +Epoch [2560/4000] Training [11/16] Loss: 0.00391 +Epoch [2560/4000] Training [12/16] Loss: 0.00547 +Epoch [2560/4000] Training [13/16] Loss: 0.00408 +Epoch [2560/4000] Training [14/16] Loss: 0.00409 +Epoch [2560/4000] Training [15/16] Loss: 0.00551 +Epoch [2560/4000] Training [16/16] Loss: 0.00316 +Epoch [2560/4000] Training metric {'Train/mean dice_metric': 0.9974228143692017, 'Train/mean miou_metric': 0.9945895671844482, 'Train/mean f1': 0.9928305745124817, 'Train/mean precision': 0.9883158802986145, 'Train/mean recall': 0.9973867535591125, 'Train/mean hd95_metric': 0.9359137415885925} +Epoch [2560/4000] Validation [1/4] Loss: 0.31474 focal_loss 0.25450 dice_loss 0.06024 +Epoch [2560/4000] Validation [2/4] Loss: 0.60293 focal_loss 0.41381 dice_loss 0.18911 +Epoch [2560/4000] Validation [3/4] Loss: 0.36347 focal_loss 0.27040 dice_loss 0.09307 +Epoch [2560/4000] Validation [4/4] Loss: 0.26530 focal_loss 0.17859 dice_loss 0.08671 +Epoch [2560/4000] Validation metric {'Val/mean dice_metric': 0.9727615118026733, 'Val/mean miou_metric': 0.9579847455024719, 'Val/mean f1': 0.9752910733222961, 'Val/mean precision': 0.9740497469902039, 'Val/mean recall': 0.9765357375144958, 'Val/mean hd95_metric': 5.313440322875977} +Cheakpoint... +Epoch [2560/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727615118026733, 'Val/mean miou_metric': 0.9579847455024719, 'Val/mean f1': 0.9752910733222961, 'Val/mean precision': 0.9740497469902039, 'Val/mean recall': 0.9765357375144958, 'Val/mean hd95_metric': 5.313440322875977} +Epoch [2561/4000] Training [1/16] Loss: 0.00452 +Epoch [2561/4000] Training [2/16] Loss: 0.00402 +Epoch [2561/4000] Training [3/16] Loss: 0.00340 +Epoch [2561/4000] Training [4/16] Loss: 0.00446 +Epoch [2561/4000] Training [5/16] Loss: 0.00449 +Epoch [2561/4000] Training [6/16] Loss: 0.00427 +Epoch [2561/4000] Training [7/16] Loss: 0.00484 +Epoch [2561/4000] Training [8/16] Loss: 0.00389 +Epoch [2561/4000] Training [9/16] Loss: 0.00336 +Epoch [2561/4000] Training [10/16] Loss: 0.00402 +Epoch [2561/4000] Training [11/16] Loss: 0.00511 +Epoch [2561/4000] Training [12/16] Loss: 0.00412 +Epoch [2561/4000] Training [13/16] Loss: 0.00443 +Epoch [2561/4000] Training [14/16] Loss: 0.00355 +Epoch [2561/4000] Training [15/16] Loss: 0.00361 +Epoch [2561/4000] Training [16/16] Loss: 0.00440 +Epoch [2561/4000] Training metric {'Train/mean dice_metric': 0.9973795413970947, 'Train/mean miou_metric': 0.9944663643836975, 'Train/mean f1': 0.9923758506774902, 'Train/mean precision': 0.9873605966567993, 'Train/mean recall': 0.997442364692688, 'Train/mean hd95_metric': 0.9484380483627319} +Epoch [2561/4000] Validation [1/4] Loss: 0.40909 focal_loss 0.33795 dice_loss 0.07114 +Epoch [2561/4000] Validation [2/4] Loss: 0.45293 focal_loss 0.28648 dice_loss 0.16645 +Epoch [2561/4000] Validation [3/4] Loss: 0.32348 focal_loss 0.23693 dice_loss 0.08655 +Epoch [2561/4000] Validation [4/4] Loss: 0.28839 focal_loss 0.19666 dice_loss 0.09173 +Epoch [2561/4000] Validation metric {'Val/mean dice_metric': 0.9714400172233582, 'Val/mean miou_metric': 0.956102728843689, 'Val/mean f1': 0.9739434123039246, 'Val/mean precision': 0.9722970128059387, 'Val/mean recall': 0.9755953550338745, 'Val/mean hd95_metric': 5.03281831741333} +Cheakpoint... +Epoch [2561/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714400172233582, 'Val/mean miou_metric': 0.956102728843689, 'Val/mean f1': 0.9739434123039246, 'Val/mean precision': 0.9722970128059387, 'Val/mean recall': 0.9755953550338745, 'Val/mean hd95_metric': 5.03281831741333} +Epoch [2562/4000] Training [1/16] Loss: 0.00434 +Epoch [2562/4000] Training [2/16] Loss: 0.00385 +Epoch [2562/4000] Training [3/16] Loss: 0.00362 +Epoch [2562/4000] Training [4/16] Loss: 0.00305 +Epoch [2562/4000] Training [5/16] Loss: 0.00456 +Epoch [2562/4000] Training [6/16] Loss: 0.00482 +Epoch [2562/4000] Training [7/16] Loss: 0.00496 +Epoch [2562/4000] Training [8/16] Loss: 0.00371 +Epoch [2562/4000] Training [9/16] Loss: 0.00369 +Epoch [2562/4000] Training [10/16] Loss: 0.00371 +Epoch [2562/4000] Training [11/16] Loss: 0.00437 +Epoch [2562/4000] Training [12/16] Loss: 0.00619 +Epoch [2562/4000] Training [13/16] Loss: 0.00424 +Epoch [2562/4000] Training [14/16] Loss: 0.00306 +Epoch [2562/4000] Training [15/16] Loss: 0.00442 +Epoch [2562/4000] Training [16/16] Loss: 0.00407 +Epoch [2562/4000] Training metric {'Train/mean dice_metric': 0.9974931478500366, 'Train/mean miou_metric': 0.9947121143341064, 'Train/mean f1': 0.9925836324691772, 'Train/mean precision': 0.987783670425415, 'Train/mean recall': 0.9974303841590881, 'Train/mean hd95_metric': 0.9498051404953003} +Epoch [2562/4000] Validation [1/4] Loss: 0.35006 focal_loss 0.28328 dice_loss 0.06678 +Epoch [2562/4000] Validation [2/4] Loss: 0.39845 focal_loss 0.28684 dice_loss 0.11161 +Epoch [2562/4000] Validation [3/4] Loss: 0.34659 focal_loss 0.25834 dice_loss 0.08825 +Epoch [2562/4000] Validation [4/4] Loss: 0.26450 focal_loss 0.17006 dice_loss 0.09443 +Epoch [2562/4000] Validation metric {'Val/mean dice_metric': 0.9744199514389038, 'Val/mean miou_metric': 0.9590358734130859, 'Val/mean f1': 0.975066065788269, 'Val/mean precision': 0.971851110458374, 'Val/mean recall': 0.9783023595809937, 'Val/mean hd95_metric': 4.920252323150635} +Cheakpoint... +Epoch [2562/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744199514389038, 'Val/mean miou_metric': 0.9590358734130859, 'Val/mean f1': 0.975066065788269, 'Val/mean precision': 0.971851110458374, 'Val/mean recall': 0.9783023595809937, 'Val/mean hd95_metric': 4.920252323150635} +Epoch [2563/4000] Training [1/16] Loss: 0.00407 +Epoch [2563/4000] Training [2/16] Loss: 0.00556 +Epoch [2563/4000] Training [3/16] Loss: 0.00397 +Epoch [2563/4000] Training [4/16] Loss: 0.00384 +Epoch [2563/4000] Training [5/16] Loss: 0.00483 +Epoch [2563/4000] Training [6/16] Loss: 0.00491 +Epoch [2563/4000] Training [7/16] Loss: 0.00479 +Epoch [2563/4000] Training [8/16] Loss: 0.00397 +Epoch [2563/4000] Training [9/16] Loss: 0.00457 +Epoch [2563/4000] Training [10/16] Loss: 0.00489 +Epoch [2563/4000] Training [11/16] Loss: 0.00455 +Epoch [2563/4000] Training [12/16] Loss: 0.00403 +Epoch [2563/4000] Training [13/16] Loss: 0.00614 +Epoch [2563/4000] Training [14/16] Loss: 0.00364 +Epoch [2563/4000] Training [15/16] Loss: 0.00442 +Epoch [2563/4000] Training [16/16] Loss: 0.00626 +Epoch [2563/4000] Training metric {'Train/mean dice_metric': 0.9970086812973022, 'Train/mean miou_metric': 0.9937708973884583, 'Train/mean f1': 0.9924548268318176, 'Train/mean precision': 0.9879269599914551, 'Train/mean recall': 0.997024416923523, 'Train/mean hd95_metric': 0.953330397605896} +Epoch [2563/4000] Validation [1/4] Loss: 0.30679 focal_loss 0.24284 dice_loss 0.06395 +Epoch [2563/4000] Validation [2/4] Loss: 0.54957 focal_loss 0.39587 dice_loss 0.15370 +Epoch [2563/4000] Validation [3/4] Loss: 0.40114 focal_loss 0.31024 dice_loss 0.09090 +Epoch [2563/4000] Validation [4/4] Loss: 0.32109 focal_loss 0.21674 dice_loss 0.10435 +Epoch [2563/4000] Validation metric {'Val/mean dice_metric': 0.9747340083122253, 'Val/mean miou_metric': 0.959530234336853, 'Val/mean f1': 0.9758439660072327, 'Val/mean precision': 0.9717609286308289, 'Val/mean recall': 0.9799615144729614, 'Val/mean hd95_metric': 4.952991485595703} +Cheakpoint... +Epoch [2563/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747340083122253, 'Val/mean miou_metric': 0.959530234336853, 'Val/mean f1': 0.9758439660072327, 'Val/mean precision': 0.9717609286308289, 'Val/mean recall': 0.9799615144729614, 'Val/mean hd95_metric': 4.952991485595703} +Epoch [2564/4000] Training [1/16] Loss: 0.00497 +Epoch [2564/4000] Training [2/16] Loss: 0.00432 +Epoch [2564/4000] Training [3/16] Loss: 0.00421 +Epoch [2564/4000] Training [4/16] Loss: 0.00399 +Epoch [2564/4000] Training [5/16] Loss: 0.00481 +Epoch [2564/4000] Training [6/16] Loss: 0.00438 +Epoch [2564/4000] Training [7/16] Loss: 0.00400 +Epoch [2564/4000] Training [8/16] Loss: 0.00382 +Epoch [2564/4000] Training [9/16] Loss: 0.00404 +Epoch [2564/4000] Training [10/16] Loss: 0.00389 +Epoch [2564/4000] Training [11/16] Loss: 0.00340 +Epoch [2564/4000] Training [12/16] Loss: 0.00400 +Epoch [2564/4000] Training [13/16] Loss: 0.00585 +Epoch [2564/4000] Training [14/16] Loss: 0.00375 +Epoch [2564/4000] Training [15/16] Loss: 0.00317 +Epoch [2564/4000] Training [16/16] Loss: 0.00336 +Epoch [2564/4000] Training metric {'Train/mean dice_metric': 0.9973009824752808, 'Train/mean miou_metric': 0.994330883026123, 'Train/mean f1': 0.9923689961433411, 'Train/mean precision': 0.9876320958137512, 'Train/mean recall': 0.9971515536308289, 'Train/mean hd95_metric': 0.9661320447921753} +Epoch [2564/4000] Validation [1/4] Loss: 0.30425 focal_loss 0.23961 dice_loss 0.06464 +Epoch [2564/4000] Validation [2/4] Loss: 0.39828 focal_loss 0.29014 dice_loss 0.10813 +Epoch [2564/4000] Validation [3/4] Loss: 0.41948 focal_loss 0.32799 dice_loss 0.09149 +Epoch [2564/4000] Validation [4/4] Loss: 0.33539 focal_loss 0.21811 dice_loss 0.11728 +Epoch [2564/4000] Validation metric {'Val/mean dice_metric': 0.9734841585159302, 'Val/mean miou_metric': 0.9582660794258118, 'Val/mean f1': 0.9749046564102173, 'Val/mean precision': 0.9720034003257751, 'Val/mean recall': 0.9778233170509338, 'Val/mean hd95_metric': 5.423543453216553} +Cheakpoint... +Epoch [2564/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734841585159302, 'Val/mean miou_metric': 0.9582660794258118, 'Val/mean f1': 0.9749046564102173, 'Val/mean precision': 0.9720034003257751, 'Val/mean recall': 0.9778233170509338, 'Val/mean hd95_metric': 5.423543453216553} +Epoch [2565/4000] Training [1/16] Loss: 0.00357 +Epoch [2565/4000] Training [2/16] Loss: 0.00445 +Epoch [2565/4000] Training [3/16] Loss: 0.00466 +Epoch [2565/4000] Training [4/16] Loss: 0.00408 +Epoch [2565/4000] Training [5/16] Loss: 0.00351 +Epoch [2565/4000] Training [6/16] Loss: 0.00436 +Epoch [2565/4000] Training [7/16] Loss: 0.00497 +Epoch [2565/4000] Training [8/16] Loss: 0.00408 +Epoch [2565/4000] Training [9/16] Loss: 0.00447 +Epoch [2565/4000] Training [10/16] Loss: 0.00345 +Epoch [2565/4000] Training [11/16] Loss: 0.00365 +Epoch [2565/4000] Training [12/16] Loss: 0.00398 +Epoch [2565/4000] Training [13/16] Loss: 0.00488 +Epoch [2565/4000] Training [14/16] Loss: 0.00445 +Epoch [2565/4000] Training [15/16] Loss: 0.00322 +Epoch [2565/4000] Training [16/16] Loss: 0.00450 +Epoch [2565/4000] Training metric {'Train/mean dice_metric': 0.9973359107971191, 'Train/mean miou_metric': 0.994391679763794, 'Train/mean f1': 0.9925176501274109, 'Train/mean precision': 0.9877628087997437, 'Train/mean recall': 0.9973185062408447, 'Train/mean hd95_metric': 0.9701326489448547} +Epoch [2565/4000] Validation [1/4] Loss: 0.41358 focal_loss 0.34180 dice_loss 0.07178 +Epoch [2565/4000] Validation [2/4] Loss: 0.90846 focal_loss 0.72289 dice_loss 0.18557 +Epoch [2565/4000] Validation [3/4] Loss: 0.35861 focal_loss 0.26757 dice_loss 0.09105 +Epoch [2565/4000] Validation [4/4] Loss: 0.40950 focal_loss 0.28088 dice_loss 0.12861 +Epoch [2565/4000] Validation metric {'Val/mean dice_metric': 0.9739755392074585, 'Val/mean miou_metric': 0.958357036113739, 'Val/mean f1': 0.9752327799797058, 'Val/mean precision': 0.9734705090522766, 'Val/mean recall': 0.9770015478134155, 'Val/mean hd95_metric': 5.617154121398926} +Cheakpoint... +Epoch [2565/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739755392074585, 'Val/mean miou_metric': 0.958357036113739, 'Val/mean f1': 0.9752327799797058, 'Val/mean precision': 0.9734705090522766, 'Val/mean recall': 0.9770015478134155, 'Val/mean hd95_metric': 5.617154121398926} +Epoch [2566/4000] Training [1/16] Loss: 0.00337 +Epoch [2566/4000] Training [2/16] Loss: 0.00498 +Epoch [2566/4000] Training [3/16] Loss: 0.00450 +Epoch [2566/4000] Training [4/16] Loss: 0.00499 +Epoch [2566/4000] Training [5/16] Loss: 0.00424 +Epoch [2566/4000] Training [6/16] Loss: 0.00422 +Epoch [2566/4000] Training [7/16] Loss: 0.00470 +Epoch [2566/4000] Training [8/16] Loss: 0.00371 +Epoch [2566/4000] Training [9/16] Loss: 0.00390 +Epoch [2566/4000] Training [10/16] Loss: 0.00311 +Epoch [2566/4000] Training [11/16] Loss: 0.00347 +Epoch [2566/4000] Training [12/16] Loss: 0.00546 +Epoch [2566/4000] Training [13/16] Loss: 0.00341 +Epoch [2566/4000] Training [14/16] Loss: 0.00494 +Epoch [2566/4000] Training [15/16] Loss: 0.00378 +Epoch [2566/4000] Training [16/16] Loss: 0.00424 +Epoch [2566/4000] Training metric {'Train/mean dice_metric': 0.9973827600479126, 'Train/mean miou_metric': 0.9945034384727478, 'Train/mean f1': 0.9927536249160767, 'Train/mean precision': 0.988247811794281, 'Train/mean recall': 0.9973007440567017, 'Train/mean hd95_metric': 0.9468605518341064} +Epoch [2566/4000] Validation [1/4] Loss: 0.37140 focal_loss 0.30227 dice_loss 0.06913 +Epoch [2566/4000] Validation [2/4] Loss: 0.35266 focal_loss 0.24882 dice_loss 0.10383 +Epoch [2566/4000] Validation [3/4] Loss: 0.26307 focal_loss 0.18936 dice_loss 0.07371 +Epoch [2566/4000] Validation [4/4] Loss: 0.40003 focal_loss 0.29148 dice_loss 0.10855 +Epoch [2566/4000] Validation metric {'Val/mean dice_metric': 0.9741237759590149, 'Val/mean miou_metric': 0.9589158892631531, 'Val/mean f1': 0.975786566734314, 'Val/mean precision': 0.9730345010757446, 'Val/mean recall': 0.9785541296005249, 'Val/mean hd95_metric': 5.313830375671387} +Cheakpoint... +Epoch [2566/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741237759590149, 'Val/mean miou_metric': 0.9589158892631531, 'Val/mean f1': 0.975786566734314, 'Val/mean precision': 0.9730345010757446, 'Val/mean recall': 0.9785541296005249, 'Val/mean hd95_metric': 5.313830375671387} +Epoch [2567/4000] Training [1/16] Loss: 0.00424 +Epoch [2567/4000] Training [2/16] Loss: 0.00304 +Epoch [2567/4000] Training [3/16] Loss: 0.00360 +Epoch [2567/4000] Training [4/16] Loss: 0.00451 +Epoch [2567/4000] Training [5/16] Loss: 0.00419 +Epoch [2567/4000] Training [6/16] Loss: 0.00356 +Epoch [2567/4000] Training [7/16] Loss: 0.00378 +Epoch [2567/4000] Training [8/16] Loss: 0.00479 +Epoch [2567/4000] Training [9/16] Loss: 0.00431 +Epoch [2567/4000] Training [10/16] Loss: 0.00347 +Epoch [2567/4000] Training [11/16] Loss: 0.00352 +Epoch [2567/4000] Training [12/16] Loss: 0.00326 +Epoch [2567/4000] Training [13/16] Loss: 0.00375 +Epoch [2567/4000] Training [14/16] Loss: 0.00375 +Epoch [2567/4000] Training [15/16] Loss: 0.00632 +Epoch [2567/4000] Training [16/16] Loss: 0.00403 +Epoch [2567/4000] Training metric {'Train/mean dice_metric': 0.9975115656852722, 'Train/mean miou_metric': 0.9947599172592163, 'Train/mean f1': 0.9928305149078369, 'Train/mean precision': 0.9882464408874512, 'Train/mean recall': 0.9974573850631714, 'Train/mean hd95_metric': 0.9344309568405151} +Epoch [2567/4000] Validation [1/4] Loss: 0.34288 focal_loss 0.27685 dice_loss 0.06602 +Epoch [2567/4000] Validation [2/4] Loss: 0.33637 focal_loss 0.23191 dice_loss 0.10446 +Epoch [2567/4000] Validation [3/4] Loss: 0.40062 focal_loss 0.31107 dice_loss 0.08955 +Epoch [2567/4000] Validation [4/4] Loss: 0.35609 focal_loss 0.24319 dice_loss 0.11291 +Epoch [2567/4000] Validation metric {'Val/mean dice_metric': 0.9752505421638489, 'Val/mean miou_metric': 0.9600067138671875, 'Val/mean f1': 0.9759297966957092, 'Val/mean precision': 0.9718295931816101, 'Val/mean recall': 0.9800648093223572, 'Val/mean hd95_metric': 5.179670333862305} +Cheakpoint... +Epoch [2567/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752505421638489, 'Val/mean miou_metric': 0.9600067138671875, 'Val/mean f1': 0.9759297966957092, 'Val/mean precision': 0.9718295931816101, 'Val/mean recall': 0.9800648093223572, 'Val/mean hd95_metric': 5.179670333862305} +Epoch [2568/4000] Training [1/16] Loss: 0.00321 +Epoch [2568/4000] Training [2/16] Loss: 0.00321 +Epoch [2568/4000] Training [3/16] Loss: 0.00462 +Epoch [2568/4000] Training [4/16] Loss: 0.00319 +Epoch [2568/4000] Training [5/16] Loss: 0.00313 +Epoch [2568/4000] Training [6/16] Loss: 0.00281 +Epoch [2568/4000] Training [7/16] Loss: 0.00448 +Epoch [2568/4000] Training [8/16] Loss: 0.00351 +Epoch [2568/4000] Training [9/16] Loss: 0.00455 +Epoch [2568/4000] Training [10/16] Loss: 0.00481 +Epoch [2568/4000] Training [11/16] Loss: 0.00423 +Epoch [2568/4000] Training [12/16] Loss: 0.00400 +Epoch [2568/4000] Training [13/16] Loss: 0.00555 +Epoch [2568/4000] Training [14/16] Loss: 0.00452 +Epoch [2568/4000] Training [15/16] Loss: 0.00407 +Epoch [2568/4000] Training [16/16] Loss: 0.00384 +Epoch [2568/4000] Training metric {'Train/mean dice_metric': 0.9975854158401489, 'Train/mean miou_metric': 0.9948937296867371, 'Train/mean f1': 0.9927794933319092, 'Train/mean precision': 0.9881221652030945, 'Train/mean recall': 0.9974809288978577, 'Train/mean hd95_metric': 0.934528112411499} +Epoch [2568/4000] Validation [1/4] Loss: 0.34803 focal_loss 0.28486 dice_loss 0.06317 +Epoch [2568/4000] Validation [2/4] Loss: 0.33486 focal_loss 0.23337 dice_loss 0.10149 +Epoch [2568/4000] Validation [3/4] Loss: 0.31041 focal_loss 0.22367 dice_loss 0.08674 +Epoch [2568/4000] Validation [4/4] Loss: 0.26401 focal_loss 0.16740 dice_loss 0.09661 +Epoch [2568/4000] Validation metric {'Val/mean dice_metric': 0.9759537577629089, 'Val/mean miou_metric': 0.9609476327896118, 'Val/mean f1': 0.9764284491539001, 'Val/mean precision': 0.9725141525268555, 'Val/mean recall': 0.9803743362426758, 'Val/mean hd95_metric': 5.212413311004639} +Cheakpoint... +Epoch [2568/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759537577629089, 'Val/mean miou_metric': 0.9609476327896118, 'Val/mean f1': 0.9764284491539001, 'Val/mean precision': 0.9725141525268555, 'Val/mean recall': 0.9803743362426758, 'Val/mean hd95_metric': 5.212413311004639} +Epoch [2569/4000] Training [1/16] Loss: 0.00545 +Epoch [2569/4000] Training [2/16] Loss: 0.00477 +Epoch [2569/4000] Training [3/16] Loss: 0.00359 +Epoch [2569/4000] Training [4/16] Loss: 0.00421 +Epoch [2569/4000] Training [5/16] Loss: 0.00384 +Epoch [2569/4000] Training [6/16] Loss: 0.00535 +Epoch [2569/4000] Training [7/16] Loss: 0.00389 +Epoch [2569/4000] Training [8/16] Loss: 0.00534 +Epoch [2569/4000] Training [9/16] Loss: 0.00384 +Epoch [2569/4000] Training [10/16] Loss: 0.00335 +Epoch [2569/4000] Training [11/16] Loss: 0.00617 +Epoch [2569/4000] Training [12/16] Loss: 0.00411 +Epoch [2569/4000] Training [13/16] Loss: 0.00485 +Epoch [2569/4000] Training [14/16] Loss: 0.00338 +Epoch [2569/4000] Training [15/16] Loss: 0.00349 +Epoch [2569/4000] Training [16/16] Loss: 0.00340 +Epoch [2569/4000] Training metric {'Train/mean dice_metric': 0.9972566366195679, 'Train/mean miou_metric': 0.9942536354064941, 'Train/mean f1': 0.9924968481063843, 'Train/mean precision': 0.9878328442573547, 'Train/mean recall': 0.9972050786018372, 'Train/mean hd95_metric': 0.9438707828521729} +Epoch [2569/4000] Validation [1/4] Loss: 0.33096 focal_loss 0.26771 dice_loss 0.06325 +Epoch [2569/4000] Validation [2/4] Loss: 0.87298 focal_loss 0.69006 dice_loss 0.18292 +Epoch [2569/4000] Validation [3/4] Loss: 0.44066 focal_loss 0.34814 dice_loss 0.09252 +Epoch [2569/4000] Validation [4/4] Loss: 0.43658 focal_loss 0.32045 dice_loss 0.11613 +Epoch [2569/4000] Validation metric {'Val/mean dice_metric': 0.9733380079269409, 'Val/mean miou_metric': 0.9580410122871399, 'Val/mean f1': 0.9751662611961365, 'Val/mean precision': 0.9717196226119995, 'Val/mean recall': 0.9786374568939209, 'Val/mean hd95_metric': 5.349615573883057} +Cheakpoint... +Epoch [2569/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733380079269409, 'Val/mean miou_metric': 0.9580410122871399, 'Val/mean f1': 0.9751662611961365, 'Val/mean precision': 0.9717196226119995, 'Val/mean recall': 0.9786374568939209, 'Val/mean hd95_metric': 5.349615573883057} +Epoch [2570/4000] Training [1/16] Loss: 0.00363 +Epoch [2570/4000] Training [2/16] Loss: 0.00431 +Epoch [2570/4000] Training [3/16] Loss: 0.00588 +Epoch [2570/4000] Training [4/16] Loss: 0.00330 +Epoch [2570/4000] Training [5/16] Loss: 0.00376 +Epoch [2570/4000] Training [6/16] Loss: 0.00383 +Epoch [2570/4000] Training [7/16] Loss: 0.00443 +Epoch [2570/4000] Training [8/16] Loss: 0.00497 +Epoch [2570/4000] Training [9/16] Loss: 0.00359 +Epoch [2570/4000] Training [10/16] Loss: 0.00382 +Epoch [2570/4000] Training [11/16] Loss: 0.00471 +Epoch [2570/4000] Training [12/16] Loss: 0.00430 +Epoch [2570/4000] Training [13/16] Loss: 0.00413 +Epoch [2570/4000] Training [14/16] Loss: 0.00535 +Epoch [2570/4000] Training [15/16] Loss: 0.00362 +Epoch [2570/4000] Training [16/16] Loss: 0.00493 +Epoch [2570/4000] Training metric {'Train/mean dice_metric': 0.9973827600479126, 'Train/mean miou_metric': 0.9944995641708374, 'Train/mean f1': 0.9927086234092712, 'Train/mean precision': 0.9881523251533508, 'Train/mean recall': 0.9973070621490479, 'Train/mean hd95_metric': 0.9427034258842468} +Epoch [2570/4000] Validation [1/4] Loss: 0.35779 focal_loss 0.29361 dice_loss 0.06418 +Epoch [2570/4000] Validation [2/4] Loss: 0.43788 focal_loss 0.30010 dice_loss 0.13778 +Epoch [2570/4000] Validation [3/4] Loss: 0.42708 focal_loss 0.33915 dice_loss 0.08793 +Epoch [2570/4000] Validation [4/4] Loss: 0.32817 focal_loss 0.21898 dice_loss 0.10919 +Epoch [2570/4000] Validation metric {'Val/mean dice_metric': 0.9747816324234009, 'Val/mean miou_metric': 0.959269642829895, 'Val/mean f1': 0.9754706025123596, 'Val/mean precision': 0.971091091632843, 'Val/mean recall': 0.9798897504806519, 'Val/mean hd95_metric': 5.684313774108887} +Cheakpoint... +Epoch [2570/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747816324234009, 'Val/mean miou_metric': 0.959269642829895, 'Val/mean f1': 0.9754706025123596, 'Val/mean precision': 0.971091091632843, 'Val/mean recall': 0.9798897504806519, 'Val/mean hd95_metric': 5.684313774108887} +Epoch [2571/4000] Training [1/16] Loss: 0.00459 +Epoch [2571/4000] Training [2/16] Loss: 0.00293 +Epoch [2571/4000] Training [3/16] Loss: 0.00438 +Epoch [2571/4000] Training [4/16] Loss: 0.00689 +Epoch [2571/4000] Training [5/16] Loss: 0.00354 +Epoch [2571/4000] Training [6/16] Loss: 0.00342 +Epoch [2571/4000] Training [7/16] Loss: 0.00436 +Epoch [2571/4000] Training [8/16] Loss: 0.00410 +Epoch [2571/4000] Training [9/16] Loss: 0.00470 +Epoch [2571/4000] Training [10/16] Loss: 0.00443 +Epoch [2571/4000] Training [11/16] Loss: 0.00379 +Epoch [2571/4000] Training [12/16] Loss: 0.00314 +Epoch [2571/4000] Training [13/16] Loss: 0.00506 +Epoch [2571/4000] Training [14/16] Loss: 0.00396 +Epoch [2571/4000] Training [15/16] Loss: 0.00414 +Epoch [2571/4000] Training [16/16] Loss: 0.00469 +Epoch [2571/4000] Training metric {'Train/mean dice_metric': 0.9974075555801392, 'Train/mean miou_metric': 0.9945520162582397, 'Train/mean f1': 0.9925669431686401, 'Train/mean precision': 0.9877591133117676, 'Train/mean recall': 0.9974217414855957, 'Train/mean hd95_metric': 0.9323797225952148} +Epoch [2571/4000] Validation [1/4] Loss: 0.34966 focal_loss 0.28221 dice_loss 0.06745 +Epoch [2571/4000] Validation [2/4] Loss: 0.38623 focal_loss 0.25082 dice_loss 0.13541 +Epoch [2571/4000] Validation [3/4] Loss: 0.41955 focal_loss 0.32973 dice_loss 0.08983 +Epoch [2571/4000] Validation [4/4] Loss: 0.34441 focal_loss 0.23556 dice_loss 0.10885 +Epoch [2571/4000] Validation metric {'Val/mean dice_metric': 0.9744651913642883, 'Val/mean miou_metric': 0.9589060544967651, 'Val/mean f1': 0.974917471408844, 'Val/mean precision': 0.9715215563774109, 'Val/mean recall': 0.9783373475074768, 'Val/mean hd95_metric': 5.309287071228027} +Cheakpoint... +Epoch [2571/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744651913642883, 'Val/mean miou_metric': 0.9589060544967651, 'Val/mean f1': 0.974917471408844, 'Val/mean precision': 0.9715215563774109, 'Val/mean recall': 0.9783373475074768, 'Val/mean hd95_metric': 5.309287071228027} +Epoch [2572/4000] Training [1/16] Loss: 0.00340 +Epoch [2572/4000] Training [2/16] Loss: 0.00398 +Epoch [2572/4000] Training [3/16] Loss: 0.00481 +Epoch [2572/4000] Training [4/16] Loss: 0.00290 +Epoch [2572/4000] Training [5/16] Loss: 0.00543 +Epoch [2572/4000] Training [6/16] Loss: 0.00438 +Epoch [2572/4000] Training [7/16] Loss: 0.00448 +Epoch [2572/4000] Training [8/16] Loss: 0.00731 +Epoch [2572/4000] Training [9/16] Loss: 0.00316 +Epoch [2572/4000] Training [10/16] Loss: 0.00397 +Epoch [2572/4000] Training [11/16] Loss: 0.00401 +Epoch [2572/4000] Training [12/16] Loss: 0.00511 +Epoch [2572/4000] Training [13/16] Loss: 0.00282 +Epoch [2572/4000] Training [14/16] Loss: 0.00338 +Epoch [2572/4000] Training [15/16] Loss: 0.00395 +Epoch [2572/4000] Training [16/16] Loss: 0.00412 +Epoch [2572/4000] Training metric {'Train/mean dice_metric': 0.9973552227020264, 'Train/mean miou_metric': 0.9944616556167603, 'Train/mean f1': 0.9927152395248413, 'Train/mean precision': 0.9881439208984375, 'Train/mean recall': 0.99732905626297, 'Train/mean hd95_metric': 1.0290292501449585} +Epoch [2572/4000] Validation [1/4] Loss: 0.33406 focal_loss 0.26898 dice_loss 0.06508 +Epoch [2572/4000] Validation [2/4] Loss: 0.88583 focal_loss 0.69679 dice_loss 0.18904 +Epoch [2572/4000] Validation [3/4] Loss: 0.40581 focal_loss 0.31094 dice_loss 0.09487 +Epoch [2572/4000] Validation [4/4] Loss: 0.33234 focal_loss 0.23045 dice_loss 0.10189 +Epoch [2572/4000] Validation metric {'Val/mean dice_metric': 0.9731408953666687, 'Val/mean miou_metric': 0.9576619863510132, 'Val/mean f1': 0.9748357534408569, 'Val/mean precision': 0.9734283685684204, 'Val/mean recall': 0.976247251033783, 'Val/mean hd95_metric': 5.542919158935547} +Cheakpoint... +Epoch [2572/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731408953666687, 'Val/mean miou_metric': 0.9576619863510132, 'Val/mean f1': 0.9748357534408569, 'Val/mean precision': 0.9734283685684204, 'Val/mean recall': 0.976247251033783, 'Val/mean hd95_metric': 5.542919158935547} +Epoch [2573/4000] Training [1/16] Loss: 0.00346 +Epoch [2573/4000] Training [2/16] Loss: 0.00430 +Epoch [2573/4000] Training [3/16] Loss: 0.00598 +Epoch [2573/4000] Training [4/16] Loss: 0.00383 +Epoch [2573/4000] Training [5/16] Loss: 0.00452 +Epoch [2573/4000] Training [6/16] Loss: 0.00475 +Epoch [2573/4000] Training [7/16] Loss: 0.00345 +Epoch [2573/4000] Training [8/16] Loss: 0.00478 +Epoch [2573/4000] Training [9/16] Loss: 0.00347 +Epoch [2573/4000] Training [10/16] Loss: 0.00515 +Epoch [2573/4000] Training [11/16] Loss: 0.00360 +Epoch [2573/4000] Training [12/16] Loss: 0.00384 +Epoch [2573/4000] Training [13/16] Loss: 0.00410 +Epoch [2573/4000] Training [14/16] Loss: 0.00411 +Epoch [2573/4000] Training [15/16] Loss: 0.00428 +Epoch [2573/4000] Training [16/16] Loss: 0.00370 +Epoch [2573/4000] Training metric {'Train/mean dice_metric': 0.9973471760749817, 'Train/mean miou_metric': 0.994436502456665, 'Train/mean f1': 0.9926851391792297, 'Train/mean precision': 0.9881457090377808, 'Train/mean recall': 0.9972665309906006, 'Train/mean hd95_metric': 0.9388105869293213} +Epoch [2573/4000] Validation [1/4] Loss: 0.36312 focal_loss 0.29530 dice_loss 0.06782 +Epoch [2573/4000] Validation [2/4] Loss: 0.46089 focal_loss 0.32839 dice_loss 0.13250 +Epoch [2573/4000] Validation [3/4] Loss: 0.39906 focal_loss 0.30129 dice_loss 0.09777 +Epoch [2573/4000] Validation [4/4] Loss: 0.32839 focal_loss 0.22491 dice_loss 0.10348 +Epoch [2573/4000] Validation metric {'Val/mean dice_metric': 0.9743434190750122, 'Val/mean miou_metric': 0.959115207195282, 'Val/mean f1': 0.9753422737121582, 'Val/mean precision': 0.9733616709709167, 'Val/mean recall': 0.9773308634757996, 'Val/mean hd95_metric': 5.254575252532959} +Cheakpoint... +Epoch [2573/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743434190750122, 'Val/mean miou_metric': 0.959115207195282, 'Val/mean f1': 0.9753422737121582, 'Val/mean precision': 0.9733616709709167, 'Val/mean recall': 0.9773308634757996, 'Val/mean hd95_metric': 5.254575252532959} +Epoch [2574/4000] Training [1/16] Loss: 0.00290 +Epoch [2574/4000] Training [2/16] Loss: 0.00480 +Epoch [2574/4000] Training [3/16] Loss: 0.00438 +Epoch [2574/4000] Training [4/16] Loss: 0.00369 +Epoch [2574/4000] Training [5/16] Loss: 0.00398 +Epoch [2574/4000] Training [6/16] Loss: 0.00423 +Epoch [2574/4000] Training [7/16] Loss: 0.00556 +Epoch [2574/4000] Training [8/16] Loss: 0.00672 +Epoch [2574/4000] Training [9/16] Loss: 0.00439 +Epoch [2574/4000] Training [10/16] Loss: 0.00267 +Epoch [2574/4000] Training [11/16] Loss: 0.00319 +Epoch [2574/4000] Training [12/16] Loss: 0.00332 +Epoch [2574/4000] Training [13/16] Loss: 0.00411 +Epoch [2574/4000] Training [14/16] Loss: 0.00456 +Epoch [2574/4000] Training [15/16] Loss: 0.00423 +Epoch [2574/4000] Training [16/16] Loss: 0.00472 +Epoch [2574/4000] Training metric {'Train/mean dice_metric': 0.9973964095115662, 'Train/mean miou_metric': 0.9945361614227295, 'Train/mean f1': 0.9927818179130554, 'Train/mean precision': 0.9882935285568237, 'Train/mean recall': 0.9973110556602478, 'Train/mean hd95_metric': 0.923150897026062} +Epoch [2574/4000] Validation [1/4] Loss: 0.33511 focal_loss 0.27010 dice_loss 0.06501 +Epoch [2574/4000] Validation [2/4] Loss: 0.76815 focal_loss 0.57960 dice_loss 0.18856 +Epoch [2574/4000] Validation [3/4] Loss: 0.43087 focal_loss 0.33569 dice_loss 0.09519 +Epoch [2574/4000] Validation [4/4] Loss: 0.35352 focal_loss 0.23863 dice_loss 0.11489 +Epoch [2574/4000] Validation metric {'Val/mean dice_metric': 0.9736937284469604, 'Val/mean miou_metric': 0.9586389660835266, 'Val/mean f1': 0.9754180312156677, 'Val/mean precision': 0.972213089466095, 'Val/mean recall': 0.9786442518234253, 'Val/mean hd95_metric': 5.3116021156311035} +Cheakpoint... +Epoch [2574/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736937284469604, 'Val/mean miou_metric': 0.9586389660835266, 'Val/mean f1': 0.9754180312156677, 'Val/mean precision': 0.972213089466095, 'Val/mean recall': 0.9786442518234253, 'Val/mean hd95_metric': 5.3116021156311035} +Epoch [2575/4000] Training [1/16] Loss: 0.00545 +Epoch [2575/4000] Training [2/16] Loss: 0.00488 +Epoch [2575/4000] Training [3/16] Loss: 0.00474 +Epoch [2575/4000] Training [4/16] Loss: 0.00525 +Epoch [2575/4000] Training [5/16] Loss: 0.00333 +Epoch [2575/4000] Training [6/16] Loss: 0.00376 +Epoch [2575/4000] Training [7/16] Loss: 0.00282 +Epoch [2575/4000] Training [8/16] Loss: 0.00482 +Epoch [2575/4000] Training [9/16] Loss: 0.00416 +Epoch [2575/4000] Training [10/16] Loss: 0.00547 +Epoch [2575/4000] Training [11/16] Loss: 0.00521 +Epoch [2575/4000] Training [12/16] Loss: 0.00331 +Epoch [2575/4000] Training [13/16] Loss: 0.00362 +Epoch [2575/4000] Training [14/16] Loss: 0.00347 +Epoch [2575/4000] Training [15/16] Loss: 0.00289 +Epoch [2575/4000] Training [16/16] Loss: 0.00426 +Epoch [2575/4000] Training metric {'Train/mean dice_metric': 0.9975931644439697, 'Train/mean miou_metric': 0.9948921799659729, 'Train/mean f1': 0.9920835494995117, 'Train/mean precision': 0.9867987036705017, 'Train/mean recall': 0.9974252581596375, 'Train/mean hd95_metric': 0.9342458844184875} +Epoch [2575/4000] Validation [1/4] Loss: 0.33399 focal_loss 0.26863 dice_loss 0.06536 +Epoch [2575/4000] Validation [2/4] Loss: 0.66623 focal_loss 0.48959 dice_loss 0.17664 +Epoch [2575/4000] Validation [3/4] Loss: 0.39256 focal_loss 0.30011 dice_loss 0.09246 +Epoch [2575/4000] Validation [4/4] Loss: 0.30925 focal_loss 0.20665 dice_loss 0.10260 +Epoch [2575/4000] Validation metric {'Val/mean dice_metric': 0.9748861193656921, 'Val/mean miou_metric': 0.9596349596977234, 'Val/mean f1': 0.9749935865402222, 'Val/mean precision': 0.9710037112236023, 'Val/mean recall': 0.9790164232254028, 'Val/mean hd95_metric': 5.556506156921387} +Cheakpoint... +Epoch [2575/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748861193656921, 'Val/mean miou_metric': 0.9596349596977234, 'Val/mean f1': 0.9749935865402222, 'Val/mean precision': 0.9710037112236023, 'Val/mean recall': 0.9790164232254028, 'Val/mean hd95_metric': 5.556506156921387} +Epoch [2576/4000] Training [1/16] Loss: 0.00328 +Epoch [2576/4000] Training [2/16] Loss: 0.00357 +Epoch [2576/4000] Training [3/16] Loss: 0.00392 +Epoch [2576/4000] Training [4/16] Loss: 0.00314 +Epoch [2576/4000] Training [5/16] Loss: 0.00305 +Epoch [2576/4000] Training [6/16] Loss: 0.00309 +Epoch [2576/4000] Training [7/16] Loss: 0.00396 +Epoch [2576/4000] Training [8/16] Loss: 0.00387 +Epoch [2576/4000] Training [9/16] Loss: 0.00301 +Epoch [2576/4000] Training [10/16] Loss: 0.00364 +Epoch [2576/4000] Training [11/16] Loss: 0.00606 +Epoch [2576/4000] Training [12/16] Loss: 0.00489 +Epoch [2576/4000] Training [13/16] Loss: 0.00467 +Epoch [2576/4000] Training [14/16] Loss: 0.00528 +Epoch [2576/4000] Training [15/16] Loss: 0.00377 +Epoch [2576/4000] Training [16/16] Loss: 0.00589 +Epoch [2576/4000] Training metric {'Train/mean dice_metric': 0.9975334405899048, 'Train/mean miou_metric': 0.9948122501373291, 'Train/mean f1': 0.99295973777771, 'Train/mean precision': 0.9884480237960815, 'Train/mean recall': 0.9975128173828125, 'Train/mean hd95_metric': 0.9077436923980713} +Epoch [2576/4000] Validation [1/4] Loss: 0.34033 focal_loss 0.27375 dice_loss 0.06658 +Epoch [2576/4000] Validation [2/4] Loss: 0.41965 focal_loss 0.29445 dice_loss 0.12519 +Epoch [2576/4000] Validation [3/4] Loss: 0.42824 focal_loss 0.32798 dice_loss 0.10026 +Epoch [2576/4000] Validation [4/4] Loss: 0.39323 focal_loss 0.27378 dice_loss 0.11945 +Epoch [2576/4000] Validation metric {'Val/mean dice_metric': 0.974664032459259, 'Val/mean miou_metric': 0.9592158198356628, 'Val/mean f1': 0.9762482047080994, 'Val/mean precision': 0.9737095236778259, 'Val/mean recall': 0.9788002371788025, 'Val/mean hd95_metric': 5.368569374084473} +Cheakpoint... +Epoch [2576/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974664032459259, 'Val/mean miou_metric': 0.9592158198356628, 'Val/mean f1': 0.9762482047080994, 'Val/mean precision': 0.9737095236778259, 'Val/mean recall': 0.9788002371788025, 'Val/mean hd95_metric': 5.368569374084473} +Epoch [2577/4000] Training [1/16] Loss: 0.00422 +Epoch [2577/4000] Training [2/16] Loss: 0.00475 +Epoch [2577/4000] Training [3/16] Loss: 0.00441 +Epoch [2577/4000] Training [4/16] Loss: 0.00355 +Epoch [2577/4000] Training [5/16] Loss: 0.00432 +Epoch [2577/4000] Training [6/16] Loss: 0.00380 +Epoch [2577/4000] Training [7/16] Loss: 0.00355 +Epoch [2577/4000] Training [8/16] Loss: 0.00468 +Epoch [2577/4000] Training [9/16] Loss: 0.00359 +Epoch [2577/4000] Training [10/16] Loss: 0.00353 +Epoch [2577/4000] Training [11/16] Loss: 0.00584 +Epoch [2577/4000] Training [12/16] Loss: 0.00339 +Epoch [2577/4000] Training [13/16] Loss: 0.00523 +Epoch [2577/4000] Training [14/16] Loss: 0.00334 +Epoch [2577/4000] Training [15/16] Loss: 0.00587 +Epoch [2577/4000] Training [16/16] Loss: 0.00447 +Epoch [2577/4000] Training metric {'Train/mean dice_metric': 0.9973242282867432, 'Train/mean miou_metric': 0.9943751096725464, 'Train/mean f1': 0.9925925135612488, 'Train/mean precision': 0.9879909753799438, 'Train/mean recall': 0.9972371459007263, 'Train/mean hd95_metric': 0.9335237741470337} +Epoch [2577/4000] Validation [1/4] Loss: 0.43574 focal_loss 0.36609 dice_loss 0.06965 +Epoch [2577/4000] Validation [2/4] Loss: 0.40486 focal_loss 0.28462 dice_loss 0.12024 +Epoch [2577/4000] Validation [3/4] Loss: 0.41730 focal_loss 0.33031 dice_loss 0.08699 +Epoch [2577/4000] Validation [4/4] Loss: 0.29700 focal_loss 0.19085 dice_loss 0.10614 +Epoch [2577/4000] Validation metric {'Val/mean dice_metric': 0.9759595990180969, 'Val/mean miou_metric': 0.9599297642707825, 'Val/mean f1': 0.9760010242462158, 'Val/mean precision': 0.9725838899612427, 'Val/mean recall': 0.9794421195983887, 'Val/mean hd95_metric': 5.354390621185303} +Cheakpoint... +Epoch [2577/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759595990180969, 'Val/mean miou_metric': 0.9599297642707825, 'Val/mean f1': 0.9760010242462158, 'Val/mean precision': 0.9725838899612427, 'Val/mean recall': 0.9794421195983887, 'Val/mean hd95_metric': 5.354390621185303} +Epoch [2578/4000] Training [1/16] Loss: 0.00459 +Epoch [2578/4000] Training [2/16] Loss: 0.00392 +Epoch [2578/4000] Training [3/16] Loss: 0.00454 +Epoch [2578/4000] Training [4/16] Loss: 0.00378 +Epoch [2578/4000] Training [5/16] Loss: 0.00360 +Epoch [2578/4000] Training [6/16] Loss: 0.00370 +Epoch [2578/4000] Training [7/16] Loss: 0.00530 +Epoch [2578/4000] Training [8/16] Loss: 0.00369 +Epoch [2578/4000] Training [9/16] Loss: 0.00465 +Epoch [2578/4000] Training [10/16] Loss: 0.00315 +Epoch [2578/4000] Training [11/16] Loss: 0.00431 +Epoch [2578/4000] Training [12/16] Loss: 0.00416 +Epoch [2578/4000] Training [13/16] Loss: 0.00249 +Epoch [2578/4000] Training [14/16] Loss: 0.00450 +Epoch [2578/4000] Training [15/16] Loss: 0.00309 +Epoch [2578/4000] Training [16/16] Loss: 0.00470 +Epoch [2578/4000] Training metric {'Train/mean dice_metric': 0.9974579215049744, 'Train/mean miou_metric': 0.9946267008781433, 'Train/mean f1': 0.9923754930496216, 'Train/mean precision': 0.9874374270439148, 'Train/mean recall': 0.9973632097244263, 'Train/mean hd95_metric': 0.9278597831726074} +Epoch [2578/4000] Validation [1/4] Loss: 0.35477 focal_loss 0.29145 dice_loss 0.06332 +Epoch [2578/4000] Validation [2/4] Loss: 0.85514 focal_loss 0.67447 dice_loss 0.18067 +Epoch [2578/4000] Validation [3/4] Loss: 0.42037 focal_loss 0.32146 dice_loss 0.09891 +Epoch [2578/4000] Validation [4/4] Loss: 0.39251 focal_loss 0.26951 dice_loss 0.12300 +Epoch [2578/4000] Validation metric {'Val/mean dice_metric': 0.9732704162597656, 'Val/mean miou_metric': 0.9580437541007996, 'Val/mean f1': 0.9751765131950378, 'Val/mean precision': 0.9716018438339233, 'Val/mean recall': 0.9787776470184326, 'Val/mean hd95_metric': 5.314156532287598} +Cheakpoint... +Epoch [2578/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732704162597656, 'Val/mean miou_metric': 0.9580437541007996, 'Val/mean f1': 0.9751765131950378, 'Val/mean precision': 0.9716018438339233, 'Val/mean recall': 0.9787776470184326, 'Val/mean hd95_metric': 5.314156532287598} +Epoch [2579/4000] Training [1/16] Loss: 0.00437 +Epoch [2579/4000] Training [2/16] Loss: 0.00304 +Epoch [2579/4000] Training [3/16] Loss: 0.00514 +Epoch [2579/4000] Training [4/16] Loss: 0.00434 +Epoch [2579/4000] Training [5/16] Loss: 0.00339 +Epoch [2579/4000] Training [6/16] Loss: 0.00420 +Epoch [2579/4000] Training [7/16] Loss: 0.00328 +Epoch [2579/4000] Training [8/16] Loss: 0.00347 +Epoch [2579/4000] Training [9/16] Loss: 0.00273 +Epoch [2579/4000] Training [10/16] Loss: 0.00398 +Epoch [2579/4000] Training [11/16] Loss: 0.00330 +Epoch [2579/4000] Training [12/16] Loss: 0.00410 +Epoch [2579/4000] Training [13/16] Loss: 0.00448 +Epoch [2579/4000] Training [14/16] Loss: 0.00541 +Epoch [2579/4000] Training [15/16] Loss: 0.00491 +Epoch [2579/4000] Training [16/16] Loss: 0.00412 +Epoch [2579/4000] Training metric {'Train/mean dice_metric': 0.9975409507751465, 'Train/mean miou_metric': 0.9948215484619141, 'Train/mean f1': 0.9929473996162415, 'Train/mean precision': 0.9883648753166199, 'Train/mean recall': 0.997572660446167, 'Train/mean hd95_metric': 0.9539617300033569} +Epoch [2579/4000] Validation [1/4] Loss: 0.39781 focal_loss 0.33034 dice_loss 0.06747 +Epoch [2579/4000] Validation [2/4] Loss: 1.17997 focal_loss 0.93101 dice_loss 0.24896 +Epoch [2579/4000] Validation [3/4] Loss: 0.30033 focal_loss 0.21520 dice_loss 0.08513 +Epoch [2579/4000] Validation [4/4] Loss: 0.28386 focal_loss 0.18986 dice_loss 0.09400 +Epoch [2579/4000] Validation metric {'Val/mean dice_metric': 0.972393810749054, 'Val/mean miou_metric': 0.9577109217643738, 'Val/mean f1': 0.9753955602645874, 'Val/mean precision': 0.9726278185844421, 'Val/mean recall': 0.9781792759895325, 'Val/mean hd95_metric': 5.476015090942383} +Cheakpoint... +Epoch [2579/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972393810749054, 'Val/mean miou_metric': 0.9577109217643738, 'Val/mean f1': 0.9753955602645874, 'Val/mean precision': 0.9726278185844421, 'Val/mean recall': 0.9781792759895325, 'Val/mean hd95_metric': 5.476015090942383} +Epoch [2580/4000] Training [1/16] Loss: 0.00467 +Epoch [2580/4000] Training [2/16] Loss: 0.00466 +Epoch [2580/4000] Training [3/16] Loss: 0.00377 +Epoch [2580/4000] Training [4/16] Loss: 0.00433 +Epoch [2580/4000] Training [5/16] Loss: 0.00505 +Epoch [2580/4000] Training [6/16] Loss: 0.00487 +Epoch [2580/4000] Training [7/16] Loss: 0.00379 +Epoch [2580/4000] Training [8/16] Loss: 0.00435 +Epoch [2580/4000] Training [9/16] Loss: 0.00343 +Epoch [2580/4000] Training [10/16] Loss: 0.00379 +Epoch [2580/4000] Training [11/16] Loss: 0.00522 +Epoch [2580/4000] Training [12/16] Loss: 0.00387 +Epoch [2580/4000] Training [13/16] Loss: 0.00382 +Epoch [2580/4000] Training [14/16] Loss: 0.00435 +Epoch [2580/4000] Training [15/16] Loss: 0.00327 +Epoch [2580/4000] Training [16/16] Loss: 0.00502 +Epoch [2580/4000] Training metric {'Train/mean dice_metric': 0.9973440170288086, 'Train/mean miou_metric': 0.9944266080856323, 'Train/mean f1': 0.992609441280365, 'Train/mean precision': 0.9879790544509888, 'Train/mean recall': 0.997283399105072, 'Train/mean hd95_metric': 0.97318434715271} +Epoch [2580/4000] Validation [1/4] Loss: 0.33527 focal_loss 0.26970 dice_loss 0.06556 +Epoch [2580/4000] Validation [2/4] Loss: 0.42116 focal_loss 0.30486 dice_loss 0.11629 +Epoch [2580/4000] Validation [3/4] Loss: 0.37312 focal_loss 0.27994 dice_loss 0.09318 +Epoch [2580/4000] Validation [4/4] Loss: 0.28832 focal_loss 0.18933 dice_loss 0.09899 +Epoch [2580/4000] Validation metric {'Val/mean dice_metric': 0.9711576700210571, 'Val/mean miou_metric': 0.9564231634140015, 'Val/mean f1': 0.9748941659927368, 'Val/mean precision': 0.9728217124938965, 'Val/mean recall': 0.9769754409790039, 'Val/mean hd95_metric': 5.561853408813477} +Cheakpoint... +Epoch [2580/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711576700210571, 'Val/mean miou_metric': 0.9564231634140015, 'Val/mean f1': 0.9748941659927368, 'Val/mean precision': 0.9728217124938965, 'Val/mean recall': 0.9769754409790039, 'Val/mean hd95_metric': 5.561853408813477} +Epoch [2581/4000] Training [1/16] Loss: 0.00510 +Epoch [2581/4000] Training [2/16] Loss: 0.00318 +Epoch [2581/4000] Training [3/16] Loss: 0.00425 +Epoch [2581/4000] Training [4/16] Loss: 0.00474 +Epoch [2581/4000] Training [5/16] Loss: 0.00298 +Epoch [2581/4000] Training [6/16] Loss: 0.00330 +Epoch [2581/4000] Training [7/16] Loss: 0.00511 +Epoch [2581/4000] Training [8/16] Loss: 0.00409 +Epoch [2581/4000] Training [9/16] Loss: 0.00484 +Epoch [2581/4000] Training [10/16] Loss: 0.00473 +Epoch [2581/4000] Training [11/16] Loss: 0.00742 +Epoch [2581/4000] Training [12/16] Loss: 0.00572 +Epoch [2581/4000] Training [13/16] Loss: 0.00558 +Epoch [2581/4000] Training [14/16] Loss: 0.00532 +Epoch [2581/4000] Training [15/16] Loss: 0.00329 +Epoch [2581/4000] Training [16/16] Loss: 0.00594 +Epoch [2581/4000] Training metric {'Train/mean dice_metric': 0.9972156882286072, 'Train/mean miou_metric': 0.9941819906234741, 'Train/mean f1': 0.9926745891571045, 'Train/mean precision': 0.9881014227867126, 'Train/mean recall': 0.9972901344299316, 'Train/mean hd95_metric': 0.9816539287567139} +Epoch [2581/4000] Validation [1/4] Loss: 0.34335 focal_loss 0.27805 dice_loss 0.06530 +Epoch [2581/4000] Validation [2/4] Loss: 0.83742 focal_loss 0.65445 dice_loss 0.18297 +Epoch [2581/4000] Validation [3/4] Loss: 0.24835 focal_loss 0.17710 dice_loss 0.07125 +Epoch [2581/4000] Validation [4/4] Loss: 0.28273 focal_loss 0.19702 dice_loss 0.08571 +Epoch [2581/4000] Validation metric {'Val/mean dice_metric': 0.9729403257369995, 'Val/mean miou_metric': 0.9580492973327637, 'Val/mean f1': 0.9757752418518066, 'Val/mean precision': 0.9736117124557495, 'Val/mean recall': 0.9779483675956726, 'Val/mean hd95_metric': 4.9168548583984375} +Cheakpoint... +Epoch [2581/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729403257369995, 'Val/mean miou_metric': 0.9580492973327637, 'Val/mean f1': 0.9757752418518066, 'Val/mean precision': 0.9736117124557495, 'Val/mean recall': 0.9779483675956726, 'Val/mean hd95_metric': 4.9168548583984375} +Epoch [2582/4000] Training [1/16] Loss: 0.00284 +Epoch [2582/4000] Training [2/16] Loss: 0.00416 +Epoch [2582/4000] Training [3/16] Loss: 0.00313 +Epoch [2582/4000] Training [4/16] Loss: 0.00679 +Epoch [2582/4000] Training [5/16] Loss: 0.00339 +Epoch [2582/4000] Training [6/16] Loss: 0.00380 +Epoch [2582/4000] Training [7/16] Loss: 0.00415 +Epoch [2582/4000] Training [8/16] Loss: 0.00338 +Epoch [2582/4000] Training [9/16] Loss: 0.00346 +Epoch [2582/4000] Training [10/16] Loss: 0.00495 +Epoch [2582/4000] Training [11/16] Loss: 0.00371 +Epoch [2582/4000] Training [12/16] Loss: 0.00533 +Epoch [2582/4000] Training [13/16] Loss: 0.00325 +Epoch [2582/4000] Training [14/16] Loss: 0.00400 +Epoch [2582/4000] Training [15/16] Loss: 0.00452 +Epoch [2582/4000] Training [16/16] Loss: 0.00379 +Epoch [2582/4000] Training metric {'Train/mean dice_metric': 0.997343122959137, 'Train/mean miou_metric': 0.9944066405296326, 'Train/mean f1': 0.9922378063201904, 'Train/mean precision': 0.9872944951057434, 'Train/mean recall': 0.9972309470176697, 'Train/mean hd95_metric': 0.9440706372261047} +Epoch [2582/4000] Validation [1/4] Loss: 0.37471 focal_loss 0.30585 dice_loss 0.06886 +Epoch [2582/4000] Validation [2/4] Loss: 0.80344 focal_loss 0.61582 dice_loss 0.18762 +Epoch [2582/4000] Validation [3/4] Loss: 0.40898 focal_loss 0.31716 dice_loss 0.09182 +Epoch [2582/4000] Validation [4/4] Loss: 0.27601 focal_loss 0.17774 dice_loss 0.09827 +Epoch [2582/4000] Validation metric {'Val/mean dice_metric': 0.9723831415176392, 'Val/mean miou_metric': 0.9571149945259094, 'Val/mean f1': 0.9745139479637146, 'Val/mean precision': 0.9712129235267639, 'Val/mean recall': 0.9778375029563904, 'Val/mean hd95_metric': 5.280872344970703} +Cheakpoint... +Epoch [2582/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723831415176392, 'Val/mean miou_metric': 0.9571149945259094, 'Val/mean f1': 0.9745139479637146, 'Val/mean precision': 0.9712129235267639, 'Val/mean recall': 0.9778375029563904, 'Val/mean hd95_metric': 5.280872344970703} +Epoch [2583/4000] Training [1/16] Loss: 0.00399 +Epoch [2583/4000] Training [2/16] Loss: 0.00447 +Epoch [2583/4000] Training [3/16] Loss: 0.00340 +Epoch [2583/4000] Training [4/16] Loss: 0.00294 +Epoch [2583/4000] Training [5/16] Loss: 0.00582 +Epoch [2583/4000] Training [6/16] Loss: 0.00384 +Epoch [2583/4000] Training [7/16] Loss: 0.00389 +Epoch [2583/4000] Training [8/16] Loss: 0.00376 +Epoch [2583/4000] Training [9/16] Loss: 0.00394 +Epoch [2583/4000] Training [10/16] Loss: 0.00328 +Epoch [2583/4000] Training [11/16] Loss: 0.00420 +Epoch [2583/4000] Training [12/16] Loss: 0.00546 +Epoch [2583/4000] Training [13/16] Loss: 0.00589 +Epoch [2583/4000] Training [14/16] Loss: 0.00358 +Epoch [2583/4000] Training [15/16] Loss: 0.00526 +Epoch [2583/4000] Training [16/16] Loss: 0.00473 +Epoch [2583/4000] Training metric {'Train/mean dice_metric': 0.9974254369735718, 'Train/mean miou_metric': 0.9945951104164124, 'Train/mean f1': 0.992824137210846, 'Train/mean precision': 0.9882717132568359, 'Train/mean recall': 0.9974187612533569, 'Train/mean hd95_metric': 0.9624496102333069} +Epoch [2583/4000] Validation [1/4] Loss: 0.34613 focal_loss 0.27928 dice_loss 0.06684 +Epoch [2583/4000] Validation [2/4] Loss: 0.42515 focal_loss 0.30458 dice_loss 0.12057 +Epoch [2583/4000] Validation [3/4] Loss: 0.35143 focal_loss 0.25524 dice_loss 0.09619 +Epoch [2583/4000] Validation [4/4] Loss: 0.32611 focal_loss 0.21177 dice_loss 0.11434 +Epoch [2583/4000] Validation metric {'Val/mean dice_metric': 0.9756399393081665, 'Val/mean miou_metric': 0.9600122570991516, 'Val/mean f1': 0.9755891561508179, 'Val/mean precision': 0.9727062582969666, 'Val/mean recall': 0.978489339351654, 'Val/mean hd95_metric': 4.9622979164123535} +Cheakpoint... +Epoch [2583/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756399393081665, 'Val/mean miou_metric': 0.9600122570991516, 'Val/mean f1': 0.9755891561508179, 'Val/mean precision': 0.9727062582969666, 'Val/mean recall': 0.978489339351654, 'Val/mean hd95_metric': 4.9622979164123535} +Epoch [2584/4000] Training [1/16] Loss: 0.00381 +Epoch [2584/4000] Training [2/16] Loss: 0.00327 +Epoch [2584/4000] Training [3/16] Loss: 0.00800 +Epoch [2584/4000] Training [4/16] Loss: 0.00318 +Epoch [2584/4000] Training [5/16] Loss: 0.00511 +Epoch [2584/4000] Training [6/16] Loss: 0.00542 +Epoch [2584/4000] Training [7/16] Loss: 0.00492 +Epoch [2584/4000] Training [8/16] Loss: 0.00599 +Epoch [2584/4000] Training [9/16] Loss: 0.00471 +Epoch [2584/4000] Training [10/16] Loss: 0.00342 +Epoch [2584/4000] Training [11/16] Loss: 0.00360 +Epoch [2584/4000] Training [12/16] Loss: 0.00491 +Epoch [2584/4000] Training [13/16] Loss: 0.00369 +Epoch [2584/4000] Training [14/16] Loss: 0.00435 +Epoch [2584/4000] Training [15/16] Loss: 0.00332 +Epoch [2584/4000] Training [16/16] Loss: 0.00337 +Epoch [2584/4000] Training metric {'Train/mean dice_metric': 0.997331440448761, 'Train/mean miou_metric': 0.9944102168083191, 'Train/mean f1': 0.9927849173545837, 'Train/mean precision': 0.9882698655128479, 'Train/mean recall': 0.9973414540290833, 'Train/mean hd95_metric': 1.2038867473602295} +Epoch [2584/4000] Validation [1/4] Loss: 0.34868 focal_loss 0.28033 dice_loss 0.06835 +Epoch [2584/4000] Validation [2/4] Loss: 1.00418 focal_loss 0.77299 dice_loss 0.23119 +Epoch [2584/4000] Validation [3/4] Loss: 0.42921 focal_loss 0.33116 dice_loss 0.09805 +Epoch [2584/4000] Validation [4/4] Loss: 0.30296 focal_loss 0.19793 dice_loss 0.10503 +Epoch [2584/4000] Validation metric {'Val/mean dice_metric': 0.9715023040771484, 'Val/mean miou_metric': 0.9567732810974121, 'Val/mean f1': 0.9750087857246399, 'Val/mean precision': 0.971809983253479, 'Val/mean recall': 0.978228747844696, 'Val/mean hd95_metric': 5.661208629608154} +Cheakpoint... +Epoch [2584/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715023040771484, 'Val/mean miou_metric': 0.9567732810974121, 'Val/mean f1': 0.9750087857246399, 'Val/mean precision': 0.971809983253479, 'Val/mean recall': 0.978228747844696, 'Val/mean hd95_metric': 5.661208629608154} +Epoch [2585/4000] Training [1/16] Loss: 0.00501 +Epoch [2585/4000] Training [2/16] Loss: 0.00341 +Epoch [2585/4000] Training [3/16] Loss: 0.00402 +Epoch [2585/4000] Training [4/16] Loss: 0.00473 +Epoch [2585/4000] Training [5/16] Loss: 0.00457 +Epoch [2585/4000] Training [6/16] Loss: 0.00407 +Epoch [2585/4000] Training [7/16] Loss: 0.00356 +Epoch [2585/4000] Training [8/16] Loss: 0.00411 +Epoch [2585/4000] Training [9/16] Loss: 0.00413 +Epoch [2585/4000] Training [10/16] Loss: 0.00357 +Epoch [2585/4000] Training [11/16] Loss: 0.00525 +Epoch [2585/4000] Training [12/16] Loss: 0.00373 +Epoch [2585/4000] Training [13/16] Loss: 0.00447 +Epoch [2585/4000] Training [14/16] Loss: 0.00412 +Epoch [2585/4000] Training [15/16] Loss: 0.00670 +Epoch [2585/4000] Training [16/16] Loss: 0.00545 +Epoch [2585/4000] Training metric {'Train/mean dice_metric': 0.9973376393318176, 'Train/mean miou_metric': 0.9944221377372742, 'Train/mean f1': 0.9926847815513611, 'Train/mean precision': 0.9881690740585327, 'Train/mean recall': 0.9972419142723083, 'Train/mean hd95_metric': 0.9466230869293213} +Epoch [2585/4000] Validation [1/4] Loss: 0.38679 focal_loss 0.31906 dice_loss 0.06772 +Epoch [2585/4000] Validation [2/4] Loss: 0.47757 focal_loss 0.35055 dice_loss 0.12702 +Epoch [2585/4000] Validation [3/4] Loss: 0.33759 focal_loss 0.24493 dice_loss 0.09266 +Epoch [2585/4000] Validation [4/4] Loss: 0.29764 focal_loss 0.20173 dice_loss 0.09591 +Epoch [2585/4000] Validation metric {'Val/mean dice_metric': 0.972795844078064, 'Val/mean miou_metric': 0.9574480056762695, 'Val/mean f1': 0.9746837019920349, 'Val/mean precision': 0.9716482758522034, 'Val/mean recall': 0.9777381420135498, 'Val/mean hd95_metric': 4.808966636657715} +Cheakpoint... +Epoch [2585/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972795844078064, 'Val/mean miou_metric': 0.9574480056762695, 'Val/mean f1': 0.9746837019920349, 'Val/mean precision': 0.9716482758522034, 'Val/mean recall': 0.9777381420135498, 'Val/mean hd95_metric': 4.808966636657715} +Epoch [2586/4000] Training [1/16] Loss: 0.00440 +Epoch [2586/4000] Training [2/16] Loss: 0.00471 +Epoch [2586/4000] Training [3/16] Loss: 0.00487 +Epoch [2586/4000] Training [4/16] Loss: 0.00377 +Epoch [2586/4000] Training [5/16] Loss: 0.00430 +Epoch [2586/4000] Training [6/16] Loss: 0.00359 +Epoch [2586/4000] Training [7/16] Loss: 0.00345 +Epoch [2586/4000] Training [8/16] Loss: 0.00342 +Epoch [2586/4000] Training [9/16] Loss: 0.00336 +Epoch [2586/4000] Training [10/16] Loss: 0.00530 +Epoch [2586/4000] Training [11/16] Loss: 0.00816 +Epoch [2586/4000] Training [12/16] Loss: 0.00446 +Epoch [2586/4000] Training [13/16] Loss: 0.00339 +Epoch [2586/4000] Training [14/16] Loss: 0.00361 +Epoch [2586/4000] Training [15/16] Loss: 0.00459 +Epoch [2586/4000] Training [16/16] Loss: 0.00444 +Epoch [2586/4000] Training metric {'Train/mean dice_metric': 0.9973795413970947, 'Train/mean miou_metric': 0.994491457939148, 'Train/mean f1': 0.9926449060440063, 'Train/mean precision': 0.9880664944648743, 'Train/mean recall': 0.9972658157348633, 'Train/mean hd95_metric': 0.953925609588623} +Epoch [2586/4000] Validation [1/4] Loss: 0.37420 focal_loss 0.30270 dice_loss 0.07150 +Epoch [2586/4000] Validation [2/4] Loss: 0.86034 focal_loss 0.65479 dice_loss 0.20555 +Epoch [2586/4000] Validation [3/4] Loss: 0.29561 focal_loss 0.21256 dice_loss 0.08305 +Epoch [2586/4000] Validation [4/4] Loss: 0.33292 focal_loss 0.22824 dice_loss 0.10468 +Epoch [2586/4000] Validation metric {'Val/mean dice_metric': 0.9729623794555664, 'Val/mean miou_metric': 0.9578708410263062, 'Val/mean f1': 0.9749246835708618, 'Val/mean precision': 0.9716742038726807, 'Val/mean recall': 0.9781967997550964, 'Val/mean hd95_metric': 5.566498756408691} +Cheakpoint... +Epoch [2586/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729623794555664, 'Val/mean miou_metric': 0.9578708410263062, 'Val/mean f1': 0.9749246835708618, 'Val/mean precision': 0.9716742038726807, 'Val/mean recall': 0.9781967997550964, 'Val/mean hd95_metric': 5.566498756408691} +Epoch [2587/4000] Training [1/16] Loss: 0.00404 +Epoch [2587/4000] Training [2/16] Loss: 0.00408 +Epoch [2587/4000] Training [3/16] Loss: 0.00432 +Epoch [2587/4000] Training [4/16] Loss: 0.00520 +Epoch [2587/4000] Training [5/16] Loss: 0.00553 +Epoch [2587/4000] Training [6/16] Loss: 0.00588 +Epoch [2587/4000] Training [7/16] Loss: 0.00504 +Epoch [2587/4000] Training [8/16] Loss: 0.00351 +Epoch [2587/4000] Training [9/16] Loss: 0.00347 +Epoch [2587/4000] Training [10/16] Loss: 0.00286 +Epoch [2587/4000] Training [11/16] Loss: 0.00316 +Epoch [2587/4000] Training [12/16] Loss: 0.00522 +Epoch [2587/4000] Training [13/16] Loss: 0.00270 +Epoch [2587/4000] Training [14/16] Loss: 0.00400 +Epoch [2587/4000] Training [15/16] Loss: 0.00437 +Epoch [2587/4000] Training [16/16] Loss: 0.00394 +Epoch [2587/4000] Training metric {'Train/mean dice_metric': 0.9972192645072937, 'Train/mean miou_metric': 0.9941746592521667, 'Train/mean f1': 0.9922018051147461, 'Train/mean precision': 0.9873227477073669, 'Train/mean recall': 0.9971293210983276, 'Train/mean hd95_metric': 0.9717719554901123} +Epoch [2587/4000] Validation [1/4] Loss: 0.31167 focal_loss 0.24814 dice_loss 0.06353 +Epoch [2587/4000] Validation [2/4] Loss: 0.46364 focal_loss 0.32660 dice_loss 0.13704 +Epoch [2587/4000] Validation [3/4] Loss: 0.23846 focal_loss 0.16981 dice_loss 0.06865 +Epoch [2587/4000] Validation [4/4] Loss: 0.44888 focal_loss 0.31832 dice_loss 0.13057 +Epoch [2587/4000] Validation metric {'Val/mean dice_metric': 0.9733741879463196, 'Val/mean miou_metric': 0.9576648473739624, 'Val/mean f1': 0.9743717908859253, 'Val/mean precision': 0.9693302512168884, 'Val/mean recall': 0.9794660806655884, 'Val/mean hd95_metric': 5.4791436195373535} +Cheakpoint... +Epoch [2587/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733741879463196, 'Val/mean miou_metric': 0.9576648473739624, 'Val/mean f1': 0.9743717908859253, 'Val/mean precision': 0.9693302512168884, 'Val/mean recall': 0.9794660806655884, 'Val/mean hd95_metric': 5.4791436195373535} +Epoch [2588/4000] Training [1/16] Loss: 0.00431 +Epoch [2588/4000] Training [2/16] Loss: 0.00310 +Epoch [2588/4000] Training [3/16] Loss: 0.00436 +Epoch [2588/4000] Training [4/16] Loss: 0.00472 +Epoch [2588/4000] Training [5/16] Loss: 0.00560 +Epoch [2588/4000] Training [6/16] Loss: 0.00362 +Epoch [2588/4000] Training [7/16] Loss: 0.00382 +Epoch [2588/4000] Training [8/16] Loss: 0.00488 +Epoch [2588/4000] Training [9/16] Loss: 0.00315 +Epoch [2588/4000] Training [10/16] Loss: 0.00346 +Epoch [2588/4000] Training [11/16] Loss: 0.00310 +Epoch [2588/4000] Training [12/16] Loss: 0.00647 +Epoch [2588/4000] Training [13/16] Loss: 0.00397 +Epoch [2588/4000] Training [14/16] Loss: 0.00339 +Epoch [2588/4000] Training [15/16] Loss: 0.00302 +Epoch [2588/4000] Training [16/16] Loss: 0.00559 +Epoch [2588/4000] Training metric {'Train/mean dice_metric': 0.9974076151847839, 'Train/mean miou_metric': 0.9945297837257385, 'Train/mean f1': 0.991996705532074, 'Train/mean precision': 0.986788272857666, 'Train/mean recall': 0.9972602725028992, 'Train/mean hd95_metric': 0.9331609010696411} +Epoch [2588/4000] Validation [1/4] Loss: 0.38156 focal_loss 0.31058 dice_loss 0.07098 +Epoch [2588/4000] Validation [2/4] Loss: 1.08667 focal_loss 0.88975 dice_loss 0.19692 +Epoch [2588/4000] Validation [3/4] Loss: 0.35380 focal_loss 0.25460 dice_loss 0.09921 +Epoch [2588/4000] Validation [4/4] Loss: 0.36143 focal_loss 0.25291 dice_loss 0.10852 +Epoch [2588/4000] Validation metric {'Val/mean dice_metric': 0.9729887843132019, 'Val/mean miou_metric': 0.9575555920600891, 'Val/mean f1': 0.9749895334243774, 'Val/mean precision': 0.9716532826423645, 'Val/mean recall': 0.9783486127853394, 'Val/mean hd95_metric': 4.9574503898620605} +Cheakpoint... +Epoch [2588/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729887843132019, 'Val/mean miou_metric': 0.9575555920600891, 'Val/mean f1': 0.9749895334243774, 'Val/mean precision': 0.9716532826423645, 'Val/mean recall': 0.9783486127853394, 'Val/mean hd95_metric': 4.9574503898620605} +Epoch [2589/4000] Training [1/16] Loss: 0.00426 +Epoch [2589/4000] Training [2/16] Loss: 0.00319 +Epoch [2589/4000] Training [3/16] Loss: 0.00335 +Epoch [2589/4000] Training [4/16] Loss: 0.00424 +Epoch [2589/4000] Training [5/16] Loss: 0.00541 +Epoch [2589/4000] Training [6/16] Loss: 0.00331 +Epoch [2589/4000] Training [7/16] Loss: 0.00344 +Epoch [2589/4000] Training [8/16] Loss: 0.00388 +Epoch [2589/4000] Training [9/16] Loss: 0.00284 +Epoch [2589/4000] Training [10/16] Loss: 0.00308 +Epoch [2589/4000] Training [11/16] Loss: 0.00387 +Epoch [2589/4000] Training [12/16] Loss: 0.00510 +Epoch [2589/4000] Training [13/16] Loss: 0.00329 +Epoch [2589/4000] Training [14/16] Loss: 0.00361 +Epoch [2589/4000] Training [15/16] Loss: 0.00319 +Epoch [2589/4000] Training [16/16] Loss: 0.00614 +Epoch [2589/4000] Training metric {'Train/mean dice_metric': 0.9976280927658081, 'Train/mean miou_metric': 0.9949966669082642, 'Train/mean f1': 0.9930169582366943, 'Train/mean precision': 0.9885895252227783, 'Train/mean recall': 0.9974842667579651, 'Train/mean hd95_metric': 0.9206331372261047} +Epoch [2589/4000] Validation [1/4] Loss: 0.35948 focal_loss 0.28527 dice_loss 0.07421 +Epoch [2589/4000] Validation [2/4] Loss: 0.86244 focal_loss 0.67320 dice_loss 0.18924 +Epoch [2589/4000] Validation [3/4] Loss: 0.44339 focal_loss 0.34827 dice_loss 0.09512 +Epoch [2589/4000] Validation [4/4] Loss: 0.38812 focal_loss 0.28099 dice_loss 0.10713 +Epoch [2589/4000] Validation metric {'Val/mean dice_metric': 0.9721207618713379, 'Val/mean miou_metric': 0.9576284289360046, 'Val/mean f1': 0.9758813977241516, 'Val/mean precision': 0.9738333821296692, 'Val/mean recall': 0.9779380559921265, 'Val/mean hd95_metric': 4.871872425079346} +Cheakpoint... +Epoch [2589/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721207618713379, 'Val/mean miou_metric': 0.9576284289360046, 'Val/mean f1': 0.9758813977241516, 'Val/mean precision': 0.9738333821296692, 'Val/mean recall': 0.9779380559921265, 'Val/mean hd95_metric': 4.871872425079346} +Epoch [2590/4000] Training [1/16] Loss: 0.00423 +Epoch [2590/4000] Training [2/16] Loss: 0.00396 +Epoch [2590/4000] Training [3/16] Loss: 0.00539 +Epoch [2590/4000] Training [4/16] Loss: 0.00322 +Epoch [2590/4000] Training [5/16] Loss: 0.00462 +Epoch [2590/4000] Training [6/16] Loss: 0.00327 +Epoch [2590/4000] Training [7/16] Loss: 0.00370 +Epoch [2590/4000] Training [8/16] Loss: 0.00341 +Epoch [2590/4000] Training [9/16] Loss: 0.00496 +Epoch [2590/4000] Training [10/16] Loss: 0.00258 +Epoch [2590/4000] Training [11/16] Loss: 0.00331 +Epoch [2590/4000] Training [12/16] Loss: 0.00497 +Epoch [2590/4000] Training [13/16] Loss: 0.00424 +Epoch [2590/4000] Training [14/16] Loss: 0.00483 +Epoch [2590/4000] Training [15/16] Loss: 0.00291 +Epoch [2590/4000] Training [16/16] Loss: 0.00348 +Epoch [2590/4000] Training metric {'Train/mean dice_metric': 0.9975563883781433, 'Train/mean miou_metric': 0.9948405623435974, 'Train/mean f1': 0.9926563501358032, 'Train/mean precision': 0.9879712462425232, 'Train/mean recall': 0.99738609790802, 'Train/mean hd95_metric': 0.9220558404922485} +Epoch [2590/4000] Validation [1/4] Loss: 0.38025 focal_loss 0.30849 dice_loss 0.07176 +Epoch [2590/4000] Validation [2/4] Loss: 0.86178 focal_loss 0.67164 dice_loss 0.19013 +Epoch [2590/4000] Validation [3/4] Loss: 0.30491 focal_loss 0.22217 dice_loss 0.08274 +Epoch [2590/4000] Validation [4/4] Loss: 0.37072 focal_loss 0.25912 dice_loss 0.11160 +Epoch [2590/4000] Validation metric {'Val/mean dice_metric': 0.973899245262146, 'Val/mean miou_metric': 0.9590547680854797, 'Val/mean f1': 0.9756291508674622, 'Val/mean precision': 0.9738154411315918, 'Val/mean recall': 0.9774496555328369, 'Val/mean hd95_metric': 4.755392074584961} +Cheakpoint... +Epoch [2590/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973899245262146, 'Val/mean miou_metric': 0.9590547680854797, 'Val/mean f1': 0.9756291508674622, 'Val/mean precision': 0.9738154411315918, 'Val/mean recall': 0.9774496555328369, 'Val/mean hd95_metric': 4.755392074584961} +Epoch [2591/4000] Training [1/16] Loss: 0.00610 +Epoch [2591/4000] Training [2/16] Loss: 0.00517 +Epoch [2591/4000] Training [3/16] Loss: 0.00628 +Epoch [2591/4000] Training [4/16] Loss: 0.00359 +Epoch [2591/4000] Training [5/16] Loss: 0.00404 +Epoch [2591/4000] Training [6/16] Loss: 0.00344 +Epoch [2591/4000] Training [7/16] Loss: 0.00395 +Epoch [2591/4000] Training [8/16] Loss: 0.00359 +Epoch [2591/4000] Training [9/16] Loss: 0.00325 +Epoch [2591/4000] Training [10/16] Loss: 0.00264 +Epoch [2591/4000] Training [11/16] Loss: 0.00338 +Epoch [2591/4000] Training [12/16] Loss: 0.00242 +Epoch [2591/4000] Training [13/16] Loss: 0.00419 +Epoch [2591/4000] Training [14/16] Loss: 0.00436 +Epoch [2591/4000] Training [15/16] Loss: 0.00439 +Epoch [2591/4000] Training [16/16] Loss: 0.00514 +Epoch [2591/4000] Training metric {'Train/mean dice_metric': 0.997622549533844, 'Train/mean miou_metric': 0.9949601888656616, 'Train/mean f1': 0.9924077987670898, 'Train/mean precision': 0.9873601794242859, 'Train/mean recall': 0.9975072145462036, 'Train/mean hd95_metric': 0.9277619123458862} +Epoch [2591/4000] Validation [1/4] Loss: 0.34596 focal_loss 0.27610 dice_loss 0.06987 +Epoch [2591/4000] Validation [2/4] Loss: 1.11688 focal_loss 0.92524 dice_loss 0.19164 +Epoch [2591/4000] Validation [3/4] Loss: 0.37448 focal_loss 0.27433 dice_loss 0.10014 +Epoch [2591/4000] Validation [4/4] Loss: 0.43628 focal_loss 0.30607 dice_loss 0.13021 +Epoch [2591/4000] Validation metric {'Val/mean dice_metric': 0.9725152850151062, 'Val/mean miou_metric': 0.9569204449653625, 'Val/mean f1': 0.9746075868606567, 'Val/mean precision': 0.9724618792533875, 'Val/mean recall': 0.9767627120018005, 'Val/mean hd95_metric': 5.341989517211914} +Cheakpoint... +Epoch [2591/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725152850151062, 'Val/mean miou_metric': 0.9569204449653625, 'Val/mean f1': 0.9746075868606567, 'Val/mean precision': 0.9724618792533875, 'Val/mean recall': 0.9767627120018005, 'Val/mean hd95_metric': 5.341989517211914} +Epoch [2592/4000] Training [1/16] Loss: 0.00354 +Epoch [2592/4000] Training [2/16] Loss: 0.00391 +Epoch [2592/4000] Training [3/16] Loss: 0.00323 +Epoch [2592/4000] Training [4/16] Loss: 0.00348 +Epoch [2592/4000] Training [5/16] Loss: 0.00528 +Epoch [2592/4000] Training [6/16] Loss: 0.00609 +Epoch [2592/4000] Training [7/16] Loss: 0.00410 +Epoch [2592/4000] Training [8/16] Loss: 0.00389 +Epoch [2592/4000] Training [9/16] Loss: 0.00373 +Epoch [2592/4000] Training [10/16] Loss: 0.00427 +Epoch [2592/4000] Training [11/16] Loss: 0.00344 +Epoch [2592/4000] Training [12/16] Loss: 0.00457 +Epoch [2592/4000] Training [13/16] Loss: 0.00335 +Epoch [2592/4000] Training [14/16] Loss: 0.00399 +Epoch [2592/4000] Training [15/16] Loss: 0.00415 +Epoch [2592/4000] Training [16/16] Loss: 0.00411 +Epoch [2592/4000] Training metric {'Train/mean dice_metric': 0.997529149055481, 'Train/mean miou_metric': 0.9947628974914551, 'Train/mean f1': 0.9921248555183411, 'Train/mean precision': 0.9869955778121948, 'Train/mean recall': 0.9973077774047852, 'Train/mean hd95_metric': 0.9198571443557739} +Epoch [2592/4000] Validation [1/4] Loss: 0.43065 focal_loss 0.35682 dice_loss 0.07383 +Epoch [2592/4000] Validation [2/4] Loss: 0.47131 focal_loss 0.34324 dice_loss 0.12807 +Epoch [2592/4000] Validation [3/4] Loss: 0.47286 focal_loss 0.37047 dice_loss 0.10238 +Epoch [2592/4000] Validation [4/4] Loss: 0.37968 focal_loss 0.27043 dice_loss 0.10925 +Epoch [2592/4000] Validation metric {'Val/mean dice_metric': 0.9720737338066101, 'Val/mean miou_metric': 0.956647515296936, 'Val/mean f1': 0.9747048020362854, 'Val/mean precision': 0.9723345041275024, 'Val/mean recall': 0.9770866632461548, 'Val/mean hd95_metric': 5.338887691497803} +Cheakpoint... +Epoch [2592/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720737338066101, 'Val/mean miou_metric': 0.956647515296936, 'Val/mean f1': 0.9747048020362854, 'Val/mean precision': 0.9723345041275024, 'Val/mean recall': 0.9770866632461548, 'Val/mean hd95_metric': 5.338887691497803} +Epoch [2593/4000] Training [1/16] Loss: 0.00396 +Epoch [2593/4000] Training [2/16] Loss: 0.00331 +Epoch [2593/4000] Training [3/16] Loss: 0.00400 +Epoch [2593/4000] Training [4/16] Loss: 0.00439 +Epoch [2593/4000] Training [5/16] Loss: 0.00358 +Epoch [2593/4000] Training [6/16] Loss: 0.00550 +Epoch [2593/4000] Training [7/16] Loss: 0.00476 +Epoch [2593/4000] Training [8/16] Loss: 0.00335 +Epoch [2593/4000] Training [9/16] Loss: 0.00354 +Epoch [2593/4000] Training [10/16] Loss: 0.00356 +Epoch [2593/4000] Training [11/16] Loss: 0.00471 +Epoch [2593/4000] Training [12/16] Loss: 0.00434 +Epoch [2593/4000] Training [13/16] Loss: 0.00347 +Epoch [2593/4000] Training [14/16] Loss: 0.00579 +Epoch [2593/4000] Training [15/16] Loss: 0.00348 +Epoch [2593/4000] Training [16/16] Loss: 0.00365 +Epoch [2593/4000] Training metric {'Train/mean dice_metric': 0.9975148439407349, 'Train/mean miou_metric': 0.9947712421417236, 'Train/mean f1': 0.9928901195526123, 'Train/mean precision': 0.988411545753479, 'Train/mean recall': 0.997409462928772, 'Train/mean hd95_metric': 0.9284231066703796} +Epoch [2593/4000] Validation [1/4] Loss: 0.34725 focal_loss 0.27966 dice_loss 0.06759 +Epoch [2593/4000] Validation [2/4] Loss: 0.89372 focal_loss 0.70462 dice_loss 0.18910 +Epoch [2593/4000] Validation [3/4] Loss: 0.38007 focal_loss 0.28477 dice_loss 0.09531 +Epoch [2593/4000] Validation [4/4] Loss: 0.39051 focal_loss 0.26568 dice_loss 0.12483 +Epoch [2593/4000] Validation metric {'Val/mean dice_metric': 0.9718793630599976, 'Val/mean miou_metric': 0.9571167826652527, 'Val/mean f1': 0.9754502773284912, 'Val/mean precision': 0.9726526141166687, 'Val/mean recall': 0.9782640337944031, 'Val/mean hd95_metric': 5.217520713806152} +Cheakpoint... +Epoch [2593/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718793630599976, 'Val/mean miou_metric': 0.9571167826652527, 'Val/mean f1': 0.9754502773284912, 'Val/mean precision': 0.9726526141166687, 'Val/mean recall': 0.9782640337944031, 'Val/mean hd95_metric': 5.217520713806152} +Epoch [2594/4000] Training [1/16] Loss: 0.00312 +Epoch [2594/4000] Training [2/16] Loss: 0.00418 +Epoch [2594/4000] Training [3/16] Loss: 0.00327 +Epoch [2594/4000] Training [4/16] Loss: 0.00281 +Epoch [2594/4000] Training [5/16] Loss: 0.00392 +Epoch [2594/4000] Training [6/16] Loss: 0.00449 +Epoch [2594/4000] Training [7/16] Loss: 0.00382 +Epoch [2594/4000] Training [8/16] Loss: 0.00374 +Epoch [2594/4000] Training [9/16] Loss: 0.00307 +Epoch [2594/4000] Training [10/16] Loss: 0.00705 +Epoch [2594/4000] Training [11/16] Loss: 0.00393 +Epoch [2594/4000] Training [12/16] Loss: 0.00472 +Epoch [2594/4000] Training [13/16] Loss: 0.00439 +Epoch [2594/4000] Training [14/16] Loss: 0.00460 +Epoch [2594/4000] Training [15/16] Loss: 0.00377 +Epoch [2594/4000] Training [16/16] Loss: 0.00532 +Epoch [2594/4000] Training metric {'Train/mean dice_metric': 0.9975263476371765, 'Train/mean miou_metric': 0.9947836399078369, 'Train/mean f1': 0.9928780198097229, 'Train/mean precision': 0.9883233904838562, 'Train/mean recall': 0.9974747896194458, 'Train/mean hd95_metric': 0.9340120553970337} +Epoch [2594/4000] Validation [1/4] Loss: 0.38543 focal_loss 0.31944 dice_loss 0.06599 +Epoch [2594/4000] Validation [2/4] Loss: 0.45822 focal_loss 0.32996 dice_loss 0.12826 +Epoch [2594/4000] Validation [3/4] Loss: 0.30359 focal_loss 0.21949 dice_loss 0.08409 +Epoch [2594/4000] Validation [4/4] Loss: 0.26720 focal_loss 0.17135 dice_loss 0.09585 +Epoch [2594/4000] Validation metric {'Val/mean dice_metric': 0.9741280674934387, 'Val/mean miou_metric': 0.9590851068496704, 'Val/mean f1': 0.9758491516113281, 'Val/mean precision': 0.9725006222724915, 'Val/mean recall': 0.9792208671569824, 'Val/mean hd95_metric': 5.11378812789917} +Cheakpoint... +Epoch [2594/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741280674934387, 'Val/mean miou_metric': 0.9590851068496704, 'Val/mean f1': 0.9758491516113281, 'Val/mean precision': 0.9725006222724915, 'Val/mean recall': 0.9792208671569824, 'Val/mean hd95_metric': 5.11378812789917} +Epoch [2595/4000] Training [1/16] Loss: 0.00331 +Epoch [2595/4000] Training [2/16] Loss: 0.00574 +Epoch [2595/4000] Training [3/16] Loss: 0.00270 +Epoch [2595/4000] Training [4/16] Loss: 0.00376 +Epoch [2595/4000] Training [5/16] Loss: 0.00402 +Epoch [2595/4000] Training [6/16] Loss: 0.00540 +Epoch [2595/4000] Training [7/16] Loss: 0.00345 +Epoch [2595/4000] Training [8/16] Loss: 0.00464 +Epoch [2595/4000] Training [9/16] Loss: 0.00340 +Epoch [2595/4000] Training [10/16] Loss: 0.00399 +Epoch [2595/4000] Training [11/16] Loss: 0.00327 +Epoch [2595/4000] Training [12/16] Loss: 0.00453 +Epoch [2595/4000] Training [13/16] Loss: 0.00515 +Epoch [2595/4000] Training [14/16] Loss: 0.00317 +Epoch [2595/4000] Training [15/16] Loss: 0.00331 +Epoch [2595/4000] Training [16/16] Loss: 0.00564 +Epoch [2595/4000] Training metric {'Train/mean dice_metric': 0.9975402355194092, 'Train/mean miou_metric': 0.9948226809501648, 'Train/mean f1': 0.9928876161575317, 'Train/mean precision': 0.9883293509483337, 'Train/mean recall': 0.9974880814552307, 'Train/mean hd95_metric': 0.9324073791503906} +Epoch [2595/4000] Validation [1/4] Loss: 0.39753 focal_loss 0.32439 dice_loss 0.07314 +Epoch [2595/4000] Validation [2/4] Loss: 1.22853 focal_loss 0.97867 dice_loss 0.24987 +Epoch [2595/4000] Validation [3/4] Loss: 0.41398 focal_loss 0.31804 dice_loss 0.09594 +Epoch [2595/4000] Validation [4/4] Loss: 0.28793 focal_loss 0.18472 dice_loss 0.10321 +Epoch [2595/4000] Validation metric {'Val/mean dice_metric': 0.9722323417663574, 'Val/mean miou_metric': 0.9573566317558289, 'Val/mean f1': 0.9754584431648254, 'Val/mean precision': 0.9728165864944458, 'Val/mean recall': 0.978114664554596, 'Val/mean hd95_metric': 4.967910289764404} +Cheakpoint... +Epoch [2595/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722323417663574, 'Val/mean miou_metric': 0.9573566317558289, 'Val/mean f1': 0.9754584431648254, 'Val/mean precision': 0.9728165864944458, 'Val/mean recall': 0.978114664554596, 'Val/mean hd95_metric': 4.967910289764404} +Epoch [2596/4000] Training [1/16] Loss: 0.00427 +Epoch [2596/4000] Training [2/16] Loss: 0.00304 +Epoch [2596/4000] Training [3/16] Loss: 0.00470 +Epoch [2596/4000] Training [4/16] Loss: 0.00512 +Epoch [2596/4000] Training [5/16] Loss: 0.00378 +Epoch [2596/4000] Training [6/16] Loss: 0.00488 +Epoch [2596/4000] Training [7/16] Loss: 0.00370 +Epoch [2596/4000] Training [8/16] Loss: 0.00439 +Epoch [2596/4000] Training [9/16] Loss: 0.00295 +Epoch [2596/4000] Training [10/16] Loss: 0.00557 +Epoch [2596/4000] Training [11/16] Loss: 0.00423 +Epoch [2596/4000] Training [12/16] Loss: 0.00432 +Epoch [2596/4000] Training [13/16] Loss: 0.00344 +Epoch [2596/4000] Training [14/16] Loss: 0.00451 +Epoch [2596/4000] Training [15/16] Loss: 0.00410 +Epoch [2596/4000] Training [16/16] Loss: 0.00341 +Epoch [2596/4000] Training metric {'Train/mean dice_metric': 0.9975447654724121, 'Train/mean miou_metric': 0.9948060512542725, 'Train/mean f1': 0.9924485683441162, 'Train/mean precision': 0.9874867796897888, 'Train/mean recall': 0.9974604249000549, 'Train/mean hd95_metric': 0.9277620315551758} +Epoch [2596/4000] Validation [1/4] Loss: 0.33055 focal_loss 0.26625 dice_loss 0.06431 +Epoch [2596/4000] Validation [2/4] Loss: 0.41381 focal_loss 0.29554 dice_loss 0.11827 +Epoch [2596/4000] Validation [3/4] Loss: 0.33241 focal_loss 0.24446 dice_loss 0.08794 +Epoch [2596/4000] Validation [4/4] Loss: 0.37878 focal_loss 0.25141 dice_loss 0.12738 +Epoch [2596/4000] Validation metric {'Val/mean dice_metric': 0.9727004170417786, 'Val/mean miou_metric': 0.9574316143989563, 'Val/mean f1': 0.9756661653518677, 'Val/mean precision': 0.9738560318946838, 'Val/mean recall': 0.9774831533432007, 'Val/mean hd95_metric': 5.258565902709961} +Cheakpoint... +Epoch [2596/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727004170417786, 'Val/mean miou_metric': 0.9574316143989563, 'Val/mean f1': 0.9756661653518677, 'Val/mean precision': 0.9738560318946838, 'Val/mean recall': 0.9774831533432007, 'Val/mean hd95_metric': 5.258565902709961} +Epoch [2597/4000] Training [1/16] Loss: 0.00384 +Epoch [2597/4000] Training [2/16] Loss: 0.00488 +Epoch [2597/4000] Training [3/16] Loss: 0.00539 +Epoch [2597/4000] Training [4/16] Loss: 0.00426 +Epoch [2597/4000] Training [5/16] Loss: 0.00637 +Epoch [2597/4000] Training [6/16] Loss: 0.00324 +Epoch [2597/4000] Training [7/16] Loss: 0.00474 +Epoch [2597/4000] Training [8/16] Loss: 0.00438 +Epoch [2597/4000] Training [9/16] Loss: 0.00335 +Epoch [2597/4000] Training [10/16] Loss: 0.00522 +Epoch [2597/4000] Training [11/16] Loss: 0.00446 +Epoch [2597/4000] Training [12/16] Loss: 0.00447 +Epoch [2597/4000] Training [13/16] Loss: 0.00362 +Epoch [2597/4000] Training [14/16] Loss: 0.00340 +Epoch [2597/4000] Training [15/16] Loss: 0.00367 +Epoch [2597/4000] Training [16/16] Loss: 0.00449 +Epoch [2597/4000] Training metric {'Train/mean dice_metric': 0.9973740577697754, 'Train/mean miou_metric': 0.9944847822189331, 'Train/mean f1': 0.9926143884658813, 'Train/mean precision': 0.9879415035247803, 'Train/mean recall': 0.9973317384719849, 'Train/mean hd95_metric': 0.934235155582428} +Epoch [2597/4000] Validation [1/4] Loss: 0.39896 focal_loss 0.32571 dice_loss 0.07324 +Epoch [2597/4000] Validation [2/4] Loss: 1.13549 focal_loss 0.94343 dice_loss 0.19206 +Epoch [2597/4000] Validation [3/4] Loss: 0.23983 focal_loss 0.17359 dice_loss 0.06624 +Epoch [2597/4000] Validation [4/4] Loss: 0.28810 focal_loss 0.19626 dice_loss 0.09184 +Epoch [2597/4000] Validation metric {'Val/mean dice_metric': 0.9711571931838989, 'Val/mean miou_metric': 0.9559938311576843, 'Val/mean f1': 0.9747010469436646, 'Val/mean precision': 0.973894476890564, 'Val/mean recall': 0.9755088686943054, 'Val/mean hd95_metric': 5.276999473571777} +Cheakpoint... +Epoch [2597/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711571931838989, 'Val/mean miou_metric': 0.9559938311576843, 'Val/mean f1': 0.9747010469436646, 'Val/mean precision': 0.973894476890564, 'Val/mean recall': 0.9755088686943054, 'Val/mean hd95_metric': 5.276999473571777} +Epoch [2598/4000] Training [1/16] Loss: 0.01834 +Epoch [2598/4000] Training [2/16] Loss: 0.00571 +Epoch [2598/4000] Training [3/16] Loss: 0.00442 +Epoch [2598/4000] Training [4/16] Loss: 0.00385 +Epoch [2598/4000] Training [5/16] Loss: 0.00343 +Epoch [2598/4000] Training [6/16] Loss: 0.00361 +Epoch [2598/4000] Training [7/16] Loss: 0.00355 +Epoch [2598/4000] Training [8/16] Loss: 0.00436 +Epoch [2598/4000] Training [9/16] Loss: 0.00585 +Epoch [2598/4000] Training [10/16] Loss: 0.00395 +Epoch [2598/4000] Training [11/16] Loss: 0.00416 +Epoch [2598/4000] Training [12/16] Loss: 0.00552 +Epoch [2598/4000] Training [13/16] Loss: 0.00453 +Epoch [2598/4000] Training [14/16] Loss: 0.00498 +Epoch [2598/4000] Training [15/16] Loss: 0.00594 +Epoch [2598/4000] Training [16/16] Loss: 0.00381 +Epoch [2598/4000] Training metric {'Train/mean dice_metric': 0.9971963167190552, 'Train/mean miou_metric': 0.9941415190696716, 'Train/mean f1': 0.9923869371414185, 'Train/mean precision': 0.9879270195960999, 'Train/mean recall': 0.9968873262405396, 'Train/mean hd95_metric': 1.0433499813079834} +Epoch [2598/4000] Validation [1/4] Loss: 0.39194 focal_loss 0.32424 dice_loss 0.06770 +Epoch [2598/4000] Validation [2/4] Loss: 0.92735 focal_loss 0.72986 dice_loss 0.19748 +Epoch [2598/4000] Validation [3/4] Loss: 0.41441 focal_loss 0.32259 dice_loss 0.09182 +Epoch [2598/4000] Validation [4/4] Loss: 0.28978 focal_loss 0.18973 dice_loss 0.10005 +Epoch [2598/4000] Validation metric {'Val/mean dice_metric': 0.9720613360404968, 'Val/mean miou_metric': 0.956579327583313, 'Val/mean f1': 0.974831223487854, 'Val/mean precision': 0.9685434699058533, 'Val/mean recall': 0.981201171875, 'Val/mean hd95_metric': 6.375457763671875} +Cheakpoint... +Epoch [2598/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720613360404968, 'Val/mean miou_metric': 0.956579327583313, 'Val/mean f1': 0.974831223487854, 'Val/mean precision': 0.9685434699058533, 'Val/mean recall': 0.981201171875, 'Val/mean hd95_metric': 6.375457763671875} +Epoch [2599/4000] Training [1/16] Loss: 0.00330 +Epoch [2599/4000] Training [2/16] Loss: 0.00334 +Epoch [2599/4000] Training [3/16] Loss: 0.00370 +Epoch [2599/4000] Training [4/16] Loss: 0.00447 +Epoch [2599/4000] Training [5/16] Loss: 0.00468 +Epoch [2599/4000] Training [6/16] Loss: 0.00333 +Epoch [2599/4000] Training [7/16] Loss: 0.00343 +Epoch [2599/4000] Training [8/16] Loss: 0.00450 +Epoch [2599/4000] Training [9/16] Loss: 0.00422 +Epoch [2599/4000] Training [10/16] Loss: 0.00780 +Epoch [2599/4000] Training [11/16] Loss: 0.00369 +Epoch [2599/4000] Training [12/16] Loss: 0.00466 +Epoch [2599/4000] Training [13/16] Loss: 0.00404 +Epoch [2599/4000] Training [14/16] Loss: 0.00460 +Epoch [2599/4000] Training [15/16] Loss: 0.00342 +Epoch [2599/4000] Training [16/16] Loss: 0.00361 +Epoch [2599/4000] Training metric {'Train/mean dice_metric': 0.9969233274459839, 'Train/mean miou_metric': 0.9937347769737244, 'Train/mean f1': 0.991504430770874, 'Train/mean precision': 0.9858565926551819, 'Train/mean recall': 0.9972172975540161, 'Train/mean hd95_metric': 1.3326278924942017} +Epoch [2599/4000] Validation [1/4] Loss: 0.36586 focal_loss 0.29551 dice_loss 0.07035 +Epoch [2599/4000] Validation [2/4] Loss: 0.56063 focal_loss 0.41524 dice_loss 0.14539 +Epoch [2599/4000] Validation [3/4] Loss: 0.37917 focal_loss 0.29280 dice_loss 0.08637 +Epoch [2599/4000] Validation [4/4] Loss: 0.34377 focal_loss 0.23088 dice_loss 0.11288 +Epoch [2599/4000] Validation metric {'Val/mean dice_metric': 0.9735573530197144, 'Val/mean miou_metric': 0.957663893699646, 'Val/mean f1': 0.9746036529541016, 'Val/mean precision': 0.9698782563209534, 'Val/mean recall': 0.9793753027915955, 'Val/mean hd95_metric': 5.670032024383545} +Cheakpoint... +Epoch [2599/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735573530197144, 'Val/mean miou_metric': 0.957663893699646, 'Val/mean f1': 0.9746036529541016, 'Val/mean precision': 0.9698782563209534, 'Val/mean recall': 0.9793753027915955, 'Val/mean hd95_metric': 5.670032024383545} +Epoch [2600/4000] Training [1/16] Loss: 0.00491 +Epoch [2600/4000] Training [2/16] Loss: 0.00370 +Epoch [2600/4000] Training [3/16] Loss: 0.00406 +Epoch [2600/4000] Training [4/16] Loss: 0.00510 +Epoch [2600/4000] Training [5/16] Loss: 0.00478 +Epoch [2600/4000] Training [6/16] Loss: 0.00661 +Epoch [2600/4000] Training [7/16] Loss: 0.00520 +Epoch [2600/4000] Training [8/16] Loss: 0.00454 +Epoch [2600/4000] Training [9/16] Loss: 0.00446 +Epoch [2600/4000] Training [10/16] Loss: 0.00374 +Epoch [2600/4000] Training [11/16] Loss: 0.00320 +Epoch [2600/4000] Training [12/16] Loss: 0.00326 +Epoch [2600/4000] Training [13/16] Loss: 0.00571 +Epoch [2600/4000] Training [14/16] Loss: 0.00490 +Epoch [2600/4000] Training [15/16] Loss: 0.00368 +Epoch [2600/4000] Training [16/16] Loss: 0.00414 +Epoch [2600/4000] Training metric {'Train/mean dice_metric': 0.9973136186599731, 'Train/mean miou_metric': 0.9943704605102539, 'Train/mean f1': 0.9926900863647461, 'Train/mean precision': 0.9884673953056335, 'Train/mean recall': 0.9969489574432373, 'Train/mean hd95_metric': 1.285902976989746} +Epoch [2600/4000] Validation [1/4] Loss: 0.38064 focal_loss 0.30958 dice_loss 0.07106 +Epoch [2600/4000] Validation [2/4] Loss: 0.35321 focal_loss 0.24436 dice_loss 0.10885 +Epoch [2600/4000] Validation [3/4] Loss: 0.26428 focal_loss 0.18729 dice_loss 0.07698 +Epoch [2600/4000] Validation [4/4] Loss: 0.33238 focal_loss 0.23843 dice_loss 0.09396 +Epoch [2600/4000] Validation metric {'Val/mean dice_metric': 0.9709585309028625, 'Val/mean miou_metric': 0.9551239013671875, 'Val/mean f1': 0.9737867116928101, 'Val/mean precision': 0.9767172336578369, 'Val/mean recall': 0.9708736538887024, 'Val/mean hd95_metric': 6.0192975997924805} +Cheakpoint... +Epoch [2600/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709585309028625, 'Val/mean miou_metric': 0.9551239013671875, 'Val/mean f1': 0.9737867116928101, 'Val/mean precision': 0.9767172336578369, 'Val/mean recall': 0.9708736538887024, 'Val/mean hd95_metric': 6.0192975997924805} +Epoch [2601/4000] Training [1/16] Loss: 0.00405 +Epoch [2601/4000] Training [2/16] Loss: 0.00365 +Epoch [2601/4000] Training [3/16] Loss: 0.00419 +Epoch [2601/4000] Training [4/16] Loss: 0.00517 +Epoch [2601/4000] Training [5/16] Loss: 0.00499 +Epoch [2601/4000] Training [6/16] Loss: 0.00344 +Epoch [2601/4000] Training [7/16] Loss: 0.00555 +Epoch [2601/4000] Training [8/16] Loss: 0.00547 +Epoch [2601/4000] Training [9/16] Loss: 0.00573 +Epoch [2601/4000] Training [10/16] Loss: 0.00416 +Epoch [2601/4000] Training [11/16] Loss: 0.00446 +Epoch [2601/4000] Training [12/16] Loss: 0.00478 +Epoch [2601/4000] Training [13/16] Loss: 0.00403 +Epoch [2601/4000] Training [14/16] Loss: 0.00464 +Epoch [2601/4000] Training [15/16] Loss: 0.00287 +Epoch [2601/4000] Training [16/16] Loss: 0.00286 +Epoch [2601/4000] Training metric {'Train/mean dice_metric': 0.9971990585327148, 'Train/mean miou_metric': 0.9941102266311646, 'Train/mean f1': 0.9916862845420837, 'Train/mean precision': 0.9864198565483093, 'Train/mean recall': 0.99700927734375, 'Train/mean hd95_metric': 1.1225084066390991} +Epoch [2601/4000] Validation [1/4] Loss: 0.31511 focal_loss 0.24471 dice_loss 0.07040 +Epoch [2601/4000] Validation [2/4] Loss: 0.35249 focal_loss 0.24560 dice_loss 0.10689 +Epoch [2601/4000] Validation [3/4] Loss: 0.30879 focal_loss 0.23969 dice_loss 0.06910 +Epoch [2601/4000] Validation [4/4] Loss: 0.32950 focal_loss 0.22411 dice_loss 0.10539 +Epoch [2601/4000] Validation metric {'Val/mean dice_metric': 0.9710911512374878, 'Val/mean miou_metric': 0.9550878405570984, 'Val/mean f1': 0.9723076820373535, 'Val/mean precision': 0.9731245636940002, 'Val/mean recall': 0.9714920520782471, 'Val/mean hd95_metric': 5.886283874511719} +Cheakpoint... +Epoch [2601/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710911512374878, 'Val/mean miou_metric': 0.9550878405570984, 'Val/mean f1': 0.9723076820373535, 'Val/mean precision': 0.9731245636940002, 'Val/mean recall': 0.9714920520782471, 'Val/mean hd95_metric': 5.886283874511719} +Epoch [2602/4000] Training [1/16] Loss: 0.00320 +Epoch [2602/4000] Training [2/16] Loss: 0.00857 +Epoch [2602/4000] Training [3/16] Loss: 0.00382 +Epoch [2602/4000] Training [4/16] Loss: 0.00391 +Epoch [2602/4000] Training [5/16] Loss: 0.00436 +Epoch [2602/4000] Training [6/16] Loss: 0.00386 +Epoch [2602/4000] Training [7/16] Loss: 0.00407 +Epoch [2602/4000] Training [8/16] Loss: 0.00380 +Epoch [2602/4000] Training [9/16] Loss: 0.00322 +Epoch [2602/4000] Training [10/16] Loss: 0.00398 +Epoch [2602/4000] Training [11/16] Loss: 0.00362 +Epoch [2602/4000] Training [12/16] Loss: 0.00492 +Epoch [2602/4000] Training [13/16] Loss: 0.00466 +Epoch [2602/4000] Training [14/16] Loss: 0.00591 +Epoch [2602/4000] Training [15/16] Loss: 0.00320 +Epoch [2602/4000] Training [16/16] Loss: 0.00418 +Epoch [2602/4000] Training metric {'Train/mean dice_metric': 0.9974459409713745, 'Train/mean miou_metric': 0.9946267604827881, 'Train/mean f1': 0.9926226139068604, 'Train/mean precision': 0.9880901575088501, 'Train/mean recall': 0.9971968531608582, 'Train/mean hd95_metric': 1.248457670211792} +Epoch [2602/4000] Validation [1/4] Loss: 0.26314 focal_loss 0.20506 dice_loss 0.05808 +Epoch [2602/4000] Validation [2/4] Loss: 0.79188 focal_loss 0.60468 dice_loss 0.18720 +Epoch [2602/4000] Validation [3/4] Loss: 0.27210 focal_loss 0.19982 dice_loss 0.07228 +Epoch [2602/4000] Validation [4/4] Loss: 0.35821 focal_loss 0.25165 dice_loss 0.10656 +Epoch [2602/4000] Validation metric {'Val/mean dice_metric': 0.9728962182998657, 'Val/mean miou_metric': 0.9578092694282532, 'Val/mean f1': 0.974848747253418, 'Val/mean precision': 0.9747907519340515, 'Val/mean recall': 0.9749067425727844, 'Val/mean hd95_metric': 5.0008649826049805} +Cheakpoint... +Epoch [2602/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728962182998657, 'Val/mean miou_metric': 0.9578092694282532, 'Val/mean f1': 0.974848747253418, 'Val/mean precision': 0.9747907519340515, 'Val/mean recall': 0.9749067425727844, 'Val/mean hd95_metric': 5.0008649826049805} +Epoch [2603/4000] Training [1/16] Loss: 0.00362 +Epoch [2603/4000] Training [2/16] Loss: 0.00524 +Epoch [2603/4000] Training [3/16] Loss: 0.01889 +Epoch [2603/4000] Training [4/16] Loss: 0.00390 +Epoch [2603/4000] Training [5/16] Loss: 0.00473 +Epoch [2603/4000] Training [6/16] Loss: 0.00292 +Epoch [2603/4000] Training [7/16] Loss: 0.00397 +Epoch [2603/4000] Training [8/16] Loss: 0.00516 +Epoch [2603/4000] Training [9/16] Loss: 0.14891 +Epoch [2603/4000] Training [10/16] Loss: 0.00453 +Epoch [2603/4000] Training [11/16] Loss: 0.00368 +Epoch [2603/4000] Training [12/16] Loss: 0.00541 +Epoch [2603/4000] Training [13/16] Loss: 0.00685 +Epoch [2603/4000] Training [14/16] Loss: 0.00411 +Epoch [2603/4000] Training [15/16] Loss: 0.00446 +Epoch [2603/4000] Training [16/16] Loss: 0.00393 +Epoch [2603/4000] Training metric {'Train/mean dice_metric': 0.9964921474456787, 'Train/mean miou_metric': 0.992987871170044, 'Train/mean f1': 0.9912678003311157, 'Train/mean precision': 0.9859387278556824, 'Train/mean recall': 0.996654748916626, 'Train/mean hd95_metric': 1.5022532939910889} +Epoch [2603/4000] Validation [1/4] Loss: 0.61267 focal_loss 0.49599 dice_loss 0.11667 +Epoch [2603/4000] Validation [2/4] Loss: 0.68764 focal_loss 0.50472 dice_loss 0.18293 +Epoch [2603/4000] Validation [3/4] Loss: 0.62692 focal_loss 0.49572 dice_loss 0.13120 +Epoch [2603/4000] Validation [4/4] Loss: 0.71442 focal_loss 0.56058 dice_loss 0.15384 +Epoch [2603/4000] Validation metric {'Val/mean dice_metric': 0.9670022130012512, 'Val/mean miou_metric': 0.9502536654472351, 'Val/mean f1': 0.9697641134262085, 'Val/mean precision': 0.9748919010162354, 'Val/mean recall': 0.9646897315979004, 'Val/mean hd95_metric': 5.891049861907959} +Cheakpoint... +Epoch [2603/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9670], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9670022130012512, 'Val/mean miou_metric': 0.9502536654472351, 'Val/mean f1': 0.9697641134262085, 'Val/mean precision': 0.9748919010162354, 'Val/mean recall': 0.9646897315979004, 'Val/mean hd95_metric': 5.891049861907959} +Epoch [2604/4000] Training [1/16] Loss: 0.00492 +Epoch [2604/4000] Training [2/16] Loss: 0.00331 +Epoch [2604/4000] Training [3/16] Loss: 0.00303 +Epoch [2604/4000] Training [4/16] Loss: 0.00395 +Epoch [2604/4000] Training [5/16] Loss: 0.00817 +Epoch [2604/4000] Training [6/16] Loss: 0.00475 +Epoch [2604/4000] Training [7/16] Loss: 0.00436 +Epoch [2604/4000] Training [8/16] Loss: 0.00457 +Epoch [2604/4000] Training [9/16] Loss: 0.00408 +Epoch [2604/4000] Training [10/16] Loss: 0.00399 +Epoch [2604/4000] Training [11/16] Loss: 0.00387 +Epoch [2604/4000] Training [12/16] Loss: 0.00372 +Epoch [2604/4000] Training [13/16] Loss: 0.00469 +Epoch [2604/4000] Training [14/16] Loss: 0.00400 +Epoch [2604/4000] Training [15/16] Loss: 0.00599 +Epoch [2604/4000] Training [16/16] Loss: 0.00481 +Epoch [2604/4000] Training metric {'Train/mean dice_metric': 0.9970867037773132, 'Train/mean miou_metric': 0.9939131736755371, 'Train/mean f1': 0.9913865327835083, 'Train/mean precision': 0.9866599440574646, 'Train/mean recall': 0.9961585998535156, 'Train/mean hd95_metric': 1.154310703277588} +Epoch [2604/4000] Validation [1/4] Loss: 0.46391 focal_loss 0.38277 dice_loss 0.08114 +Epoch [2604/4000] Validation [2/4] Loss: 0.34094 focal_loss 0.23235 dice_loss 0.10859 +Epoch [2604/4000] Validation [3/4] Loss: 0.46685 focal_loss 0.35971 dice_loss 0.10713 +Epoch [2604/4000] Validation [4/4] Loss: 0.77354 focal_loss 0.61836 dice_loss 0.15518 +Epoch [2604/4000] Validation metric {'Val/mean dice_metric': 0.9676752090454102, 'Val/mean miou_metric': 0.951707661151886, 'Val/mean f1': 0.9703155755996704, 'Val/mean precision': 0.9727534055709839, 'Val/mean recall': 0.9678897857666016, 'Val/mean hd95_metric': 5.827434539794922} +Cheakpoint... +Epoch [2604/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9676752090454102, 'Val/mean miou_metric': 0.951707661151886, 'Val/mean f1': 0.9703155755996704, 'Val/mean precision': 0.9727534055709839, 'Val/mean recall': 0.9678897857666016, 'Val/mean hd95_metric': 5.827434539794922} +Epoch [2605/4000] Training [1/16] Loss: 0.00508 +Epoch [2605/4000] Training [2/16] Loss: 0.00380 +Epoch [2605/4000] Training [3/16] Loss: 0.00518 +Epoch [2605/4000] Training [4/16] Loss: 0.00427 +Epoch [2605/4000] Training [5/16] Loss: 0.00530 +Epoch [2605/4000] Training [6/16] Loss: 0.00337 +Epoch [2605/4000] Training [7/16] Loss: 0.00413 +Epoch [2605/4000] Training [8/16] Loss: 0.00410 +Epoch [2605/4000] Training [9/16] Loss: 0.00423 +Epoch [2605/4000] Training [10/16] Loss: 0.00397 +Epoch [2605/4000] Training [11/16] Loss: 0.00509 +Epoch [2605/4000] Training [12/16] Loss: 0.00432 +Epoch [2605/4000] Training [13/16] Loss: 0.00334 +Epoch [2605/4000] Training [14/16] Loss: 0.00559 +Epoch [2605/4000] Training [15/16] Loss: 0.00336 +Epoch [2605/4000] Training [16/16] Loss: 0.00322 +Epoch [2605/4000] Training metric {'Train/mean dice_metric': 0.9973328709602356, 'Train/mean miou_metric': 0.9944117069244385, 'Train/mean f1': 0.9926345944404602, 'Train/mean precision': 0.9880958795547485, 'Train/mean recall': 0.997215211391449, 'Train/mean hd95_metric': 0.948157787322998} +Epoch [2605/4000] Validation [1/4] Loss: 0.46894 focal_loss 0.39257 dice_loss 0.07637 +Epoch [2605/4000] Validation [2/4] Loss: 0.40416 focal_loss 0.26312 dice_loss 0.14104 +Epoch [2605/4000] Validation [3/4] Loss: 0.24435 focal_loss 0.18157 dice_loss 0.06278 +Epoch [2605/4000] Validation [4/4] Loss: 0.34277 focal_loss 0.22697 dice_loss 0.11580 +Epoch [2605/4000] Validation metric {'Val/mean dice_metric': 0.9721773862838745, 'Val/mean miou_metric': 0.9565050005912781, 'Val/mean f1': 0.9734308123588562, 'Val/mean precision': 0.9736148118972778, 'Val/mean recall': 0.9732469320297241, 'Val/mean hd95_metric': 5.231557369232178} +Cheakpoint... +Epoch [2605/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721773862838745, 'Val/mean miou_metric': 0.9565050005912781, 'Val/mean f1': 0.9734308123588562, 'Val/mean precision': 0.9736148118972778, 'Val/mean recall': 0.9732469320297241, 'Val/mean hd95_metric': 5.231557369232178} +Epoch [2606/4000] Training [1/16] Loss: 0.00466 +Epoch [2606/4000] Training [2/16] Loss: 0.00482 +Epoch [2606/4000] Training [3/16] Loss: 0.00446 +Epoch [2606/4000] Training [4/16] Loss: 0.00691 +Epoch [2606/4000] Training [5/16] Loss: 0.00544 +Epoch [2606/4000] Training [6/16] Loss: 0.00522 +Epoch [2606/4000] Training [7/16] Loss: 0.00378 +Epoch [2606/4000] Training [8/16] Loss: 0.00365 +Epoch [2606/4000] Training [9/16] Loss: 0.00362 +Epoch [2606/4000] Training [10/16] Loss: 0.00368 +Epoch [2606/4000] Training [11/16] Loss: 0.00333 +Epoch [2606/4000] Training [12/16] Loss: 0.00331 +Epoch [2606/4000] Training [13/16] Loss: 0.00511 +Epoch [2606/4000] Training [14/16] Loss: 0.00383 +Epoch [2606/4000] Training [15/16] Loss: 0.00527 +Epoch [2606/4000] Training [16/16] Loss: 0.00432 +Epoch [2606/4000] Training metric {'Train/mean dice_metric': 0.9973625540733337, 'Train/mean miou_metric': 0.9944400787353516, 'Train/mean f1': 0.9917155504226685, 'Train/mean precision': 0.9864525198936462, 'Train/mean recall': 0.997035026550293, 'Train/mean hd95_metric': 0.9313052296638489} +Epoch [2606/4000] Validation [1/4] Loss: 0.43477 focal_loss 0.33777 dice_loss 0.09700 +Epoch [2606/4000] Validation [2/4] Loss: 1.46579 focal_loss 1.16244 dice_loss 0.30335 +Epoch [2606/4000] Validation [3/4] Loss: 0.51297 focal_loss 0.41057 dice_loss 0.10240 +Epoch [2606/4000] Validation [4/4] Loss: 0.32885 focal_loss 0.22597 dice_loss 0.10288 +Epoch [2606/4000] Validation metric {'Val/mean dice_metric': 0.9672277569770813, 'Val/mean miou_metric': 0.9522789120674133, 'Val/mean f1': 0.9724183082580566, 'Val/mean precision': 0.9717724919319153, 'Val/mean recall': 0.9730648398399353, 'Val/mean hd95_metric': 5.609821319580078} +Cheakpoint... +Epoch [2606/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9672], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9672277569770813, 'Val/mean miou_metric': 0.9522789120674133, 'Val/mean f1': 0.9724183082580566, 'Val/mean precision': 0.9717724919319153, 'Val/mean recall': 0.9730648398399353, 'Val/mean hd95_metric': 5.609821319580078} +Epoch [2607/4000] Training [1/16] Loss: 0.00444 +Epoch [2607/4000] Training [2/16] Loss: 0.00646 +Epoch [2607/4000] Training [3/16] Loss: 0.00422 +Epoch [2607/4000] Training [4/16] Loss: 0.00454 +Epoch [2607/4000] Training [5/16] Loss: 0.00418 +Epoch [2607/4000] Training [6/16] Loss: 0.00556 +Epoch [2607/4000] Training [7/16] Loss: 0.00639 +Epoch [2607/4000] Training [8/16] Loss: 0.00537 +Epoch [2607/4000] Training [9/16] Loss: 0.00479 +Epoch [2607/4000] Training [10/16] Loss: 0.00320 +Epoch [2607/4000] Training [11/16] Loss: 0.00392 +Epoch [2607/4000] Training [12/16] Loss: 0.00302 +Epoch [2607/4000] Training [13/16] Loss: 0.00385 +Epoch [2607/4000] Training [14/16] Loss: 0.00426 +Epoch [2607/4000] Training [15/16] Loss: 0.00441 +Epoch [2607/4000] Training [16/16] Loss: 0.00355 +Epoch [2607/4000] Training metric {'Train/mean dice_metric': 0.9974873661994934, 'Train/mean miou_metric': 0.9947142004966736, 'Train/mean f1': 0.9927351474761963, 'Train/mean precision': 0.9882698655128479, 'Train/mean recall': 0.9972409605979919, 'Train/mean hd95_metric': 0.9926110506057739} +Epoch [2607/4000] Validation [1/4] Loss: 0.39698 focal_loss 0.31126 dice_loss 0.08573 +Epoch [2607/4000] Validation [2/4] Loss: 0.31068 focal_loss 0.21166 dice_loss 0.09902 +Epoch [2607/4000] Validation [3/4] Loss: 0.50242 focal_loss 0.39358 dice_loss 0.10884 +Epoch [2607/4000] Validation [4/4] Loss: 0.34445 focal_loss 0.22917 dice_loss 0.11527 +Epoch [2607/4000] Validation metric {'Val/mean dice_metric': 0.9703631401062012, 'Val/mean miou_metric': 0.9556291699409485, 'Val/mean f1': 0.9756540060043335, 'Val/mean precision': 0.9735199213027954, 'Val/mean recall': 0.9777974486351013, 'Val/mean hd95_metric': 5.627468585968018} +Cheakpoint... +Epoch [2607/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703631401062012, 'Val/mean miou_metric': 0.9556291699409485, 'Val/mean f1': 0.9756540060043335, 'Val/mean precision': 0.9735199213027954, 'Val/mean recall': 0.9777974486351013, 'Val/mean hd95_metric': 5.627468585968018} +Epoch [2608/4000] Training [1/16] Loss: 0.00429 +Epoch [2608/4000] Training [2/16] Loss: 0.00323 +Epoch [2608/4000] Training [3/16] Loss: 0.00514 +Epoch [2608/4000] Training [4/16] Loss: 0.00618 +Epoch [2608/4000] Training [5/16] Loss: 0.00519 +Epoch [2608/4000] Training [6/16] Loss: 0.00355 +Epoch [2608/4000] Training [7/16] Loss: 0.00312 +Epoch [2608/4000] Training [8/16] Loss: 0.00397 +Epoch [2608/4000] Training [9/16] Loss: 0.00373 +Epoch [2608/4000] Training [10/16] Loss: 0.00437 +Epoch [2608/4000] Training [11/16] Loss: 0.00347 +Epoch [2608/4000] Training [12/16] Loss: 0.00444 +Epoch [2608/4000] Training [13/16] Loss: 0.00355 +Epoch [2608/4000] Training [14/16] Loss: 0.00351 +Epoch [2608/4000] Training [15/16] Loss: 0.00478 +Epoch [2608/4000] Training [16/16] Loss: 0.00340 +Epoch [2608/4000] Training metric {'Train/mean dice_metric': 0.9975115060806274, 'Train/mean miou_metric': 0.9947693943977356, 'Train/mean f1': 0.9928326606750488, 'Train/mean precision': 0.9883324503898621, 'Train/mean recall': 0.9973738789558411, 'Train/mean hd95_metric': 0.9115089178085327} +Epoch [2608/4000] Validation [1/4] Loss: 0.40269 focal_loss 0.31547 dice_loss 0.08722 +Epoch [2608/4000] Validation [2/4] Loss: 0.68955 focal_loss 0.48315 dice_loss 0.20640 +Epoch [2608/4000] Validation [3/4] Loss: 0.45605 focal_loss 0.36008 dice_loss 0.09598 +Epoch [2608/4000] Validation [4/4] Loss: 0.43768 focal_loss 0.31437 dice_loss 0.12331 +Epoch [2608/4000] Validation metric {'Val/mean dice_metric': 0.9687078595161438, 'Val/mean miou_metric': 0.9533449411392212, 'Val/mean f1': 0.9731158018112183, 'Val/mean precision': 0.973556637763977, 'Val/mean recall': 0.9726753830909729, 'Val/mean hd95_metric': 5.426921367645264} +Cheakpoint... +Epoch [2608/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9687], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9687078595161438, 'Val/mean miou_metric': 0.9533449411392212, 'Val/mean f1': 0.9731158018112183, 'Val/mean precision': 0.973556637763977, 'Val/mean recall': 0.9726753830909729, 'Val/mean hd95_metric': 5.426921367645264} +Epoch [2609/4000] Training [1/16] Loss: 0.00382 +Epoch [2609/4000] Training [2/16] Loss: 0.00242 +Epoch [2609/4000] Training [3/16] Loss: 0.00482 +Epoch [2609/4000] Training [4/16] Loss: 0.00343 +Epoch [2609/4000] Training [5/16] Loss: 0.00426 +Epoch [2609/4000] Training [6/16] Loss: 0.00414 +Epoch [2609/4000] Training [7/16] Loss: 0.00584 +Epoch [2609/4000] Training [8/16] Loss: 0.00295 +Epoch [2609/4000] Training [9/16] Loss: 0.00346 +Epoch [2609/4000] Training [10/16] Loss: 0.00449 +Epoch [2609/4000] Training [11/16] Loss: 0.00368 +Epoch [2609/4000] Training [12/16] Loss: 0.00308 +Epoch [2609/4000] Training [13/16] Loss: 0.00334 +Epoch [2609/4000] Training [14/16] Loss: 0.00310 +Epoch [2609/4000] Training [15/16] Loss: 0.00727 +Epoch [2609/4000] Training [16/16] Loss: 0.00369 +Epoch [2609/4000] Training metric {'Train/mean dice_metric': 0.9975730776786804, 'Train/mean miou_metric': 0.9948908090591431, 'Train/mean f1': 0.9928262233734131, 'Train/mean precision': 0.9883233904838562, 'Train/mean recall': 0.9973703026771545, 'Train/mean hd95_metric': 0.9240072965621948} +Epoch [2609/4000] Validation [1/4] Loss: 0.40446 focal_loss 0.32745 dice_loss 0.07702 +Epoch [2609/4000] Validation [2/4] Loss: 0.34114 focal_loss 0.23439 dice_loss 0.10674 +Epoch [2609/4000] Validation [3/4] Loss: 0.47864 focal_loss 0.37968 dice_loss 0.09896 +Epoch [2609/4000] Validation [4/4] Loss: 0.62369 focal_loss 0.47616 dice_loss 0.14752 +Epoch [2609/4000] Validation metric {'Val/mean dice_metric': 0.9695842862129211, 'Val/mean miou_metric': 0.9543277621269226, 'Val/mean f1': 0.9735051989555359, 'Val/mean precision': 0.9744966626167297, 'Val/mean recall': 0.972515881061554, 'Val/mean hd95_metric': 5.308544158935547} +Cheakpoint... +Epoch [2609/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9695842862129211, 'Val/mean miou_metric': 0.9543277621269226, 'Val/mean f1': 0.9735051989555359, 'Val/mean precision': 0.9744966626167297, 'Val/mean recall': 0.972515881061554, 'Val/mean hd95_metric': 5.308544158935547} +Epoch [2610/4000] Training [1/16] Loss: 0.00350 +Epoch [2610/4000] Training [2/16] Loss: 0.00302 +Epoch [2610/4000] Training [3/16] Loss: 0.00501 +Epoch [2610/4000] Training [4/16] Loss: 0.00456 +Epoch [2610/4000] Training [5/16] Loss: 0.00370 +Epoch [2610/4000] Training [6/16] Loss: 0.00333 +Epoch [2610/4000] Training [7/16] Loss: 0.00494 +Epoch [2610/4000] Training [8/16] Loss: 0.00481 +Epoch [2610/4000] Training [9/16] Loss: 0.00416 +Epoch [2610/4000] Training [10/16] Loss: 0.00429 +Epoch [2610/4000] Training [11/16] Loss: 0.00367 +Epoch [2610/4000] Training [12/16] Loss: 0.00389 +Epoch [2610/4000] Training [13/16] Loss: 0.00289 +Epoch [2610/4000] Training [14/16] Loss: 0.00349 +Epoch [2610/4000] Training [15/16] Loss: 0.00316 +Epoch [2610/4000] Training [16/16] Loss: 0.00404 +Epoch [2610/4000] Training metric {'Train/mean dice_metric': 0.9976807832717896, 'Train/mean miou_metric': 0.995096743106842, 'Train/mean f1': 0.9928812384605408, 'Train/mean precision': 0.9883012771606445, 'Train/mean recall': 0.9975038766860962, 'Train/mean hd95_metric': 0.9104069471359253} +Epoch [2610/4000] Validation [1/4] Loss: 0.33781 focal_loss 0.27182 dice_loss 0.06599 +Epoch [2610/4000] Validation [2/4] Loss: 1.00192 focal_loss 0.81682 dice_loss 0.18510 +Epoch [2610/4000] Validation [3/4] Loss: 0.45037 focal_loss 0.35296 dice_loss 0.09741 +Epoch [2610/4000] Validation [4/4] Loss: 0.39039 focal_loss 0.27653 dice_loss 0.11387 +Epoch [2610/4000] Validation metric {'Val/mean dice_metric': 0.9705206751823425, 'Val/mean miou_metric': 0.9560761451721191, 'Val/mean f1': 0.9749711155891418, 'Val/mean precision': 0.9726487994194031, 'Val/mean recall': 0.9773046970367432, 'Val/mean hd95_metric': 5.272307395935059} +Cheakpoint... +Epoch [2610/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705206751823425, 'Val/mean miou_metric': 0.9560761451721191, 'Val/mean f1': 0.9749711155891418, 'Val/mean precision': 0.9726487994194031, 'Val/mean recall': 0.9773046970367432, 'Val/mean hd95_metric': 5.272307395935059} +Epoch [2611/4000] Training [1/16] Loss: 0.00378 +Epoch [2611/4000] Training [2/16] Loss: 0.00458 +Epoch [2611/4000] Training [3/16] Loss: 0.00352 +Epoch [2611/4000] Training [4/16] Loss: 0.00377 +Epoch [2611/4000] Training [5/16] Loss: 0.00346 +Epoch [2611/4000] Training [6/16] Loss: 0.00460 +Epoch [2611/4000] Training [7/16] Loss: 0.00381 +Epoch [2611/4000] Training [8/16] Loss: 0.00425 +Epoch [2611/4000] Training [9/16] Loss: 0.00271 +Epoch [2611/4000] Training [10/16] Loss: 0.00343 +Epoch [2611/4000] Training [11/16] Loss: 0.00347 +Epoch [2611/4000] Training [12/16] Loss: 0.00325 +Epoch [2611/4000] Training [13/16] Loss: 0.00318 +Epoch [2611/4000] Training [14/16] Loss: 0.00313 +Epoch [2611/4000] Training [15/16] Loss: 0.00426 +Epoch [2611/4000] Training [16/16] Loss: 0.00360 +Epoch [2611/4000] Training metric {'Train/mean dice_metric': 0.9976869821548462, 'Train/mean miou_metric': 0.9951180219650269, 'Train/mean f1': 0.9929642081260681, 'Train/mean precision': 0.9884771108627319, 'Train/mean recall': 0.997492253780365, 'Train/mean hd95_metric': 0.9155645966529846} +Epoch [2611/4000] Validation [1/4] Loss: 0.36301 focal_loss 0.29636 dice_loss 0.06665 +Epoch [2611/4000] Validation [2/4] Loss: 0.28746 focal_loss 0.19411 dice_loss 0.09335 +Epoch [2611/4000] Validation [3/4] Loss: 0.43803 focal_loss 0.34195 dice_loss 0.09608 +Epoch [2611/4000] Validation [4/4] Loss: 0.22029 focal_loss 0.13576 dice_loss 0.08453 +Epoch [2611/4000] Validation metric {'Val/mean dice_metric': 0.9722183346748352, 'Val/mean miou_metric': 0.9577315449714661, 'Val/mean f1': 0.9757114052772522, 'Val/mean precision': 0.9736401438713074, 'Val/mean recall': 0.9777913689613342, 'Val/mean hd95_metric': 5.028693199157715} +Cheakpoint... +Epoch [2611/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722183346748352, 'Val/mean miou_metric': 0.9577315449714661, 'Val/mean f1': 0.9757114052772522, 'Val/mean precision': 0.9736401438713074, 'Val/mean recall': 0.9777913689613342, 'Val/mean hd95_metric': 5.028693199157715} +Epoch [2612/4000] Training [1/16] Loss: 0.00475 +Epoch [2612/4000] Training [2/16] Loss: 0.00430 +Epoch [2612/4000] Training [3/16] Loss: 0.00309 +Epoch [2612/4000] Training [4/16] Loss: 0.00347 +Epoch [2612/4000] Training [5/16] Loss: 0.00357 +Epoch [2612/4000] Training [6/16] Loss: 0.00443 +Epoch [2612/4000] Training [7/16] Loss: 0.00425 +Epoch [2612/4000] Training [8/16] Loss: 0.00326 +Epoch [2612/4000] Training [9/16] Loss: 0.00495 +Epoch [2612/4000] Training [10/16] Loss: 0.00331 +Epoch [2612/4000] Training [11/16] Loss: 0.00415 +Epoch [2612/4000] Training [12/16] Loss: 0.00394 +Epoch [2612/4000] Training [13/16] Loss: 0.00326 +Epoch [2612/4000] Training [14/16] Loss: 0.00408 +Epoch [2612/4000] Training [15/16] Loss: 0.00373 +Epoch [2612/4000] Training [16/16] Loss: 0.00447 +Epoch [2612/4000] Training metric {'Train/mean dice_metric': 0.9974714517593384, 'Train/mean miou_metric': 0.9946672320365906, 'Train/mean f1': 0.9918797612190247, 'Train/mean precision': 0.986514151096344, 'Train/mean recall': 0.9973040819168091, 'Train/mean hd95_metric': 0.9286603927612305} +Epoch [2612/4000] Validation [1/4] Loss: 0.33130 focal_loss 0.26386 dice_loss 0.06744 +Epoch [2612/4000] Validation [2/4] Loss: 0.36254 focal_loss 0.24463 dice_loss 0.11791 +Epoch [2612/4000] Validation [3/4] Loss: 0.47673 focal_loss 0.38089 dice_loss 0.09584 +Epoch [2612/4000] Validation [4/4] Loss: 0.28761 focal_loss 0.19193 dice_loss 0.09568 +Epoch [2612/4000] Validation metric {'Val/mean dice_metric': 0.9722606539726257, 'Val/mean miou_metric': 0.9574642181396484, 'Val/mean f1': 0.9752908945083618, 'Val/mean precision': 0.972294807434082, 'Val/mean recall': 0.9783055186271667, 'Val/mean hd95_metric': 4.929938316345215} +Cheakpoint... +Epoch [2612/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722606539726257, 'Val/mean miou_metric': 0.9574642181396484, 'Val/mean f1': 0.9752908945083618, 'Val/mean precision': 0.972294807434082, 'Val/mean recall': 0.9783055186271667, 'Val/mean hd95_metric': 4.929938316345215} +Epoch [2613/4000] Training [1/16] Loss: 0.00377 +Epoch [2613/4000] Training [2/16] Loss: 0.00300 +Epoch [2613/4000] Training [3/16] Loss: 0.00333 +Epoch [2613/4000] Training [4/16] Loss: 0.00338 +Epoch [2613/4000] Training [5/16] Loss: 0.00445 +Epoch [2613/4000] Training [6/16] Loss: 0.00504 +Epoch [2613/4000] Training [7/16] Loss: 0.00496 +Epoch [2613/4000] Training [8/16] Loss: 0.00431 +Epoch [2613/4000] Training [9/16] Loss: 0.00294 +Epoch [2613/4000] Training [10/16] Loss: 0.00381 +Epoch [2613/4000] Training [11/16] Loss: 0.00401 +Epoch [2613/4000] Training [12/16] Loss: 0.00261 +Epoch [2613/4000] Training [13/16] Loss: 0.00347 +Epoch [2613/4000] Training [14/16] Loss: 0.00441 +Epoch [2613/4000] Training [15/16] Loss: 0.00378 +Epoch [2613/4000] Training [16/16] Loss: 0.00362 +Epoch [2613/4000] Training metric {'Train/mean dice_metric': 0.9977540969848633, 'Train/mean miou_metric': 0.9952333569526672, 'Train/mean f1': 0.9929523468017578, 'Train/mean precision': 0.9883614182472229, 'Train/mean recall': 0.997586190700531, 'Train/mean hd95_metric': 0.9097235202789307} +Epoch [2613/4000] Validation [1/4] Loss: 0.34071 focal_loss 0.27033 dice_loss 0.07038 +Epoch [2613/4000] Validation [2/4] Loss: 1.13270 focal_loss 0.94626 dice_loss 0.18644 +Epoch [2613/4000] Validation [3/4] Loss: 0.21441 focal_loss 0.15388 dice_loss 0.06054 +Epoch [2613/4000] Validation [4/4] Loss: 0.27072 focal_loss 0.18316 dice_loss 0.08755 +Epoch [2613/4000] Validation metric {'Val/mean dice_metric': 0.9729622006416321, 'Val/mean miou_metric': 0.9586025476455688, 'Val/mean f1': 0.9755363464355469, 'Val/mean precision': 0.9749181866645813, 'Val/mean recall': 0.976155161857605, 'Val/mean hd95_metric': 4.676680564880371} +Cheakpoint... +Epoch [2613/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729622006416321, 'Val/mean miou_metric': 0.9586025476455688, 'Val/mean f1': 0.9755363464355469, 'Val/mean precision': 0.9749181866645813, 'Val/mean recall': 0.976155161857605, 'Val/mean hd95_metric': 4.676680564880371} +Epoch [2614/4000] Training [1/16] Loss: 0.00432 +Epoch [2614/4000] Training [2/16] Loss: 0.00472 +Epoch [2614/4000] Training [3/16] Loss: 0.00383 +Epoch [2614/4000] Training [4/16] Loss: 0.00493 +Epoch [2614/4000] Training [5/16] Loss: 0.00379 +Epoch [2614/4000] Training [6/16] Loss: 0.00435 +Epoch [2614/4000] Training [7/16] Loss: 0.00415 +Epoch [2614/4000] Training [8/16] Loss: 0.00407 +Epoch [2614/4000] Training [9/16] Loss: 0.00347 +Epoch [2614/4000] Training [10/16] Loss: 0.00425 +Epoch [2614/4000] Training [11/16] Loss: 0.00412 +Epoch [2614/4000] Training [12/16] Loss: 0.00297 +Epoch [2614/4000] Training [13/16] Loss: 0.00696 +Epoch [2614/4000] Training [14/16] Loss: 0.00260 +Epoch [2614/4000] Training [15/16] Loss: 0.00336 +Epoch [2614/4000] Training [16/16] Loss: 0.00338 +Epoch [2614/4000] Training metric {'Train/mean dice_metric': 0.9973796606063843, 'Train/mean miou_metric': 0.9945018291473389, 'Train/mean f1': 0.9927164912223816, 'Train/mean precision': 0.9882295727729797, 'Train/mean recall': 0.9972443580627441, 'Train/mean hd95_metric': 0.9253345131874084} +Epoch [2614/4000] Validation [1/4] Loss: 0.35424 focal_loss 0.28330 dice_loss 0.07094 +Epoch [2614/4000] Validation [2/4] Loss: 0.43289 focal_loss 0.30053 dice_loss 0.13236 +Epoch [2614/4000] Validation [3/4] Loss: 0.43958 focal_loss 0.34754 dice_loss 0.09203 +Epoch [2614/4000] Validation [4/4] Loss: 0.26513 focal_loss 0.17526 dice_loss 0.08986 +Epoch [2614/4000] Validation metric {'Val/mean dice_metric': 0.9741794466972351, 'Val/mean miou_metric': 0.959067702293396, 'Val/mean f1': 0.9762921929359436, 'Val/mean precision': 0.9742954969406128, 'Val/mean recall': 0.9782971143722534, 'Val/mean hd95_metric': 4.833270072937012} +Cheakpoint... +Epoch [2614/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741794466972351, 'Val/mean miou_metric': 0.959067702293396, 'Val/mean f1': 0.9762921929359436, 'Val/mean precision': 0.9742954969406128, 'Val/mean recall': 0.9782971143722534, 'Val/mean hd95_metric': 4.833270072937012} +Epoch [2615/4000] Training [1/16] Loss: 0.00354 +Epoch [2615/4000] Training [2/16] Loss: 0.00448 +Epoch [2615/4000] Training [3/16] Loss: 0.00736 +Epoch [2615/4000] Training [4/16] Loss: 0.00316 +Epoch [2615/4000] Training [5/16] Loss: 0.00304 +Epoch [2615/4000] Training [6/16] Loss: 0.00370 +Epoch [2615/4000] Training [7/16] Loss: 0.00394 +Epoch [2615/4000] Training [8/16] Loss: 0.00325 +Epoch [2615/4000] Training [9/16] Loss: 0.00421 +Epoch [2615/4000] Training [10/16] Loss: 0.00386 +Epoch [2615/4000] Training [11/16] Loss: 0.00379 +Epoch [2615/4000] Training [12/16] Loss: 0.00368 +Epoch [2615/4000] Training [13/16] Loss: 0.00411 +Epoch [2615/4000] Training [14/16] Loss: 0.00313 +Epoch [2615/4000] Training [15/16] Loss: 0.00339 +Epoch [2615/4000] Training [16/16] Loss: 0.00435 +Epoch [2615/4000] Training metric {'Train/mean dice_metric': 0.9975831508636475, 'Train/mean miou_metric': 0.9949069023132324, 'Train/mean f1': 0.9929226636886597, 'Train/mean precision': 0.9883536100387573, 'Train/mean recall': 0.9975341558456421, 'Train/mean hd95_metric': 0.9206331372261047} +Epoch [2615/4000] Validation [1/4] Loss: 0.32991 focal_loss 0.26160 dice_loss 0.06831 +Epoch [2615/4000] Validation [2/4] Loss: 0.82597 focal_loss 0.64263 dice_loss 0.18334 +Epoch [2615/4000] Validation [3/4] Loss: 0.43017 focal_loss 0.33574 dice_loss 0.09443 +Epoch [2615/4000] Validation [4/4] Loss: 0.28335 focal_loss 0.19187 dice_loss 0.09148 +Epoch [2615/4000] Validation metric {'Val/mean dice_metric': 0.9726285934448242, 'Val/mean miou_metric': 0.9584289789199829, 'Val/mean f1': 0.9762963652610779, 'Val/mean precision': 0.9740691184997559, 'Val/mean recall': 0.9785339832305908, 'Val/mean hd95_metric': 4.845112323760986} +Cheakpoint... +Epoch [2615/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726285934448242, 'Val/mean miou_metric': 0.9584289789199829, 'Val/mean f1': 0.9762963652610779, 'Val/mean precision': 0.9740691184997559, 'Val/mean recall': 0.9785339832305908, 'Val/mean hd95_metric': 4.845112323760986} +Epoch [2616/4000] Training [1/16] Loss: 0.00311 +Epoch [2616/4000] Training [2/16] Loss: 0.00406 +Epoch [2616/4000] Training [3/16] Loss: 0.00549 +Epoch [2616/4000] Training [4/16] Loss: 0.00474 +Epoch [2616/4000] Training [5/16] Loss: 0.00531 +Epoch [2616/4000] Training [6/16] Loss: 0.00474 +Epoch [2616/4000] Training [7/16] Loss: 0.00330 +Epoch [2616/4000] Training [8/16] Loss: 0.00290 +Epoch [2616/4000] Training [9/16] Loss: 0.00304 +Epoch [2616/4000] Training [10/16] Loss: 0.00467 +Epoch [2616/4000] Training [11/16] Loss: 0.00522 +Epoch [2616/4000] Training [12/16] Loss: 0.00535 +Epoch [2616/4000] Training [13/16] Loss: 0.00382 +Epoch [2616/4000] Training [14/16] Loss: 0.00424 +Epoch [2616/4000] Training [15/16] Loss: 0.00394 +Epoch [2616/4000] Training [16/16] Loss: 0.00327 +Epoch [2616/4000] Training metric {'Train/mean dice_metric': 0.9975073933601379, 'Train/mean miou_metric': 0.9947574138641357, 'Train/mean f1': 0.9928560853004456, 'Train/mean precision': 0.9882846474647522, 'Train/mean recall': 0.9974700212478638, 'Train/mean hd95_metric': 0.9223487973213196} +Epoch [2616/4000] Validation [1/4] Loss: 0.31559 focal_loss 0.24863 dice_loss 0.06696 +Epoch [2616/4000] Validation [2/4] Loss: 0.66694 focal_loss 0.49829 dice_loss 0.16865 +Epoch [2616/4000] Validation [3/4] Loss: 0.47141 focal_loss 0.37467 dice_loss 0.09675 +Epoch [2616/4000] Validation [4/4] Loss: 0.38780 focal_loss 0.27928 dice_loss 0.10852 +Epoch [2616/4000] Validation metric {'Val/mean dice_metric': 0.9731870889663696, 'Val/mean miou_metric': 0.9576307535171509, 'Val/mean f1': 0.9751542210578918, 'Val/mean precision': 0.9732905626296997, 'Val/mean recall': 0.977025032043457, 'Val/mean hd95_metric': 5.202673435211182} +Cheakpoint... +Epoch [2616/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731870889663696, 'Val/mean miou_metric': 0.9576307535171509, 'Val/mean f1': 0.9751542210578918, 'Val/mean precision': 0.9732905626296997, 'Val/mean recall': 0.977025032043457, 'Val/mean hd95_metric': 5.202673435211182} +Epoch [2617/4000] Training [1/16] Loss: 0.00436 +Epoch [2617/4000] Training [2/16] Loss: 0.00374 +Epoch [2617/4000] Training [3/16] Loss: 0.00381 +Epoch [2617/4000] Training [4/16] Loss: 0.00296 +Epoch [2617/4000] Training [5/16] Loss: 0.00296 +Epoch [2617/4000] Training [6/16] Loss: 0.00390 +Epoch [2617/4000] Training [7/16] Loss: 0.00540 +Epoch [2617/4000] Training [8/16] Loss: 0.00438 +Epoch [2617/4000] Training [9/16] Loss: 0.00315 +Epoch [2617/4000] Training [10/16] Loss: 0.00379 +Epoch [2617/4000] Training [11/16] Loss: 0.00389 +Epoch [2617/4000] Training [12/16] Loss: 0.00511 +Epoch [2617/4000] Training [13/16] Loss: 0.00416 +Epoch [2617/4000] Training [14/16] Loss: 0.00731 +Epoch [2617/4000] Training [15/16] Loss: 0.00407 +Epoch [2617/4000] Training [16/16] Loss: 0.00303 +Epoch [2617/4000] Training metric {'Train/mean dice_metric': 0.9975512027740479, 'Train/mean miou_metric': 0.9948038458824158, 'Train/mean f1': 0.9920899868011475, 'Train/mean precision': 0.9869336485862732, 'Train/mean recall': 0.9973004460334778, 'Train/mean hd95_metric': 0.9415315985679626} +Epoch [2617/4000] Validation [1/4] Loss: 0.34305 focal_loss 0.27296 dice_loss 0.07009 +Epoch [2617/4000] Validation [2/4] Loss: 0.37693 focal_loss 0.26466 dice_loss 0.11228 +Epoch [2617/4000] Validation [3/4] Loss: 0.45926 focal_loss 0.36255 dice_loss 0.09671 +Epoch [2617/4000] Validation [4/4] Loss: 0.62076 focal_loss 0.48452 dice_loss 0.13624 +Epoch [2617/4000] Validation metric {'Val/mean dice_metric': 0.9737313985824585, 'Val/mean miou_metric': 0.9584172964096069, 'Val/mean f1': 0.974700927734375, 'Val/mean precision': 0.9723559021949768, 'Val/mean recall': 0.9770573973655701, 'Val/mean hd95_metric': 5.463018417358398} +Cheakpoint... +Epoch [2617/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737313985824585, 'Val/mean miou_metric': 0.9584172964096069, 'Val/mean f1': 0.974700927734375, 'Val/mean precision': 0.9723559021949768, 'Val/mean recall': 0.9770573973655701, 'Val/mean hd95_metric': 5.463018417358398} +Epoch [2618/4000] Training [1/16] Loss: 0.00485 +Epoch [2618/4000] Training [2/16] Loss: 0.00411 +Epoch [2618/4000] Training [3/16] Loss: 0.00289 +Epoch [2618/4000] Training [4/16] Loss: 0.00465 +Epoch [2618/4000] Training [5/16] Loss: 0.00441 +Epoch [2618/4000] Training [6/16] Loss: 0.00391 +Epoch [2618/4000] Training [7/16] Loss: 0.00373 +Epoch [2618/4000] Training [8/16] Loss: 0.00335 +Epoch [2618/4000] Training [9/16] Loss: 0.00404 +Epoch [2618/4000] Training [10/16] Loss: 0.00365 +Epoch [2618/4000] Training [11/16] Loss: 0.00301 +Epoch [2618/4000] Training [12/16] Loss: 0.00502 +Epoch [2618/4000] Training [13/16] Loss: 0.00440 +Epoch [2618/4000] Training [14/16] Loss: 0.00366 +Epoch [2618/4000] Training [15/16] Loss: 0.00282 +Epoch [2618/4000] Training [16/16] Loss: 0.00446 +Epoch [2618/4000] Training metric {'Train/mean dice_metric': 0.9976211786270142, 'Train/mean miou_metric': 0.9949657917022705, 'Train/mean f1': 0.9927013516426086, 'Train/mean precision': 0.9879520535469055, 'Train/mean recall': 0.997496485710144, 'Train/mean hd95_metric': 0.9316683411598206} +Epoch [2618/4000] Validation [1/4] Loss: 0.31906 focal_loss 0.25694 dice_loss 0.06212 +Epoch [2618/4000] Validation [2/4] Loss: 0.82113 focal_loss 0.63723 dice_loss 0.18390 +Epoch [2618/4000] Validation [3/4] Loss: 0.41464 focal_loss 0.32434 dice_loss 0.09030 +Epoch [2618/4000] Validation [4/4] Loss: 0.31694 focal_loss 0.21053 dice_loss 0.10641 +Epoch [2618/4000] Validation metric {'Val/mean dice_metric': 0.974081814289093, 'Val/mean miou_metric': 0.9595762491226196, 'Val/mean f1': 0.9759354591369629, 'Val/mean precision': 0.9735262989997864, 'Val/mean recall': 0.9783565402030945, 'Val/mean hd95_metric': 5.078466892242432} +Cheakpoint... +Epoch [2618/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974081814289093, 'Val/mean miou_metric': 0.9595762491226196, 'Val/mean f1': 0.9759354591369629, 'Val/mean precision': 0.9735262989997864, 'Val/mean recall': 0.9783565402030945, 'Val/mean hd95_metric': 5.078466892242432} +Epoch [2619/4000] Training [1/16] Loss: 0.00281 +Epoch [2619/4000] Training [2/16] Loss: 0.00406 +Epoch [2619/4000] Training [3/16] Loss: 0.00407 +Epoch [2619/4000] Training [4/16] Loss: 0.00324 +Epoch [2619/4000] Training [5/16] Loss: 0.00436 +Epoch [2619/4000] Training [6/16] Loss: 0.00329 +Epoch [2619/4000] Training [7/16] Loss: 0.00564 +Epoch [2619/4000] Training [8/16] Loss: 0.00403 +Epoch [2619/4000] Training [9/16] Loss: 0.00599 +Epoch [2619/4000] Training [10/16] Loss: 0.00380 +Epoch [2619/4000] Training [11/16] Loss: 0.00342 +Epoch [2619/4000] Training [12/16] Loss: 0.00432 +Epoch [2619/4000] Training [13/16] Loss: 0.00402 +Epoch [2619/4000] Training [14/16] Loss: 0.00435 +Epoch [2619/4000] Training [15/16] Loss: 0.00522 +Epoch [2619/4000] Training [16/16] Loss: 0.00512 +Epoch [2619/4000] Training metric {'Train/mean dice_metric': 0.9974410533905029, 'Train/mean miou_metric': 0.9946128129959106, 'Train/mean f1': 0.9926246404647827, 'Train/mean precision': 0.9879730939865112, 'Train/mean recall': 0.9973201155662537, 'Train/mean hd95_metric': 0.9294776916503906} +Epoch [2619/4000] Validation [1/4] Loss: 0.39486 focal_loss 0.30664 dice_loss 0.08822 +Epoch [2619/4000] Validation [2/4] Loss: 0.38800 focal_loss 0.27031 dice_loss 0.11769 +Epoch [2619/4000] Validation [3/4] Loss: 0.44524 focal_loss 0.34845 dice_loss 0.09678 +Epoch [2619/4000] Validation [4/4] Loss: 0.34313 focal_loss 0.23530 dice_loss 0.10783 +Epoch [2619/4000] Validation metric {'Val/mean dice_metric': 0.9718273282051086, 'Val/mean miou_metric': 0.9566150903701782, 'Val/mean f1': 0.9745665788650513, 'Val/mean precision': 0.9735102653503418, 'Val/mean recall': 0.9756251573562622, 'Val/mean hd95_metric': 5.423827171325684} +Cheakpoint... +Epoch [2619/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718273282051086, 'Val/mean miou_metric': 0.9566150903701782, 'Val/mean f1': 0.9745665788650513, 'Val/mean precision': 0.9735102653503418, 'Val/mean recall': 0.9756251573562622, 'Val/mean hd95_metric': 5.423827171325684} +Epoch [2620/4000] Training [1/16] Loss: 0.00430 +Epoch [2620/4000] Training [2/16] Loss: 0.00299 +Epoch [2620/4000] Training [3/16] Loss: 0.00369 +Epoch [2620/4000] Training [4/16] Loss: 0.00312 +Epoch [2620/4000] Training [5/16] Loss: 0.00371 +Epoch [2620/4000] Training [6/16] Loss: 0.00447 +Epoch [2620/4000] Training [7/16] Loss: 0.00320 +Epoch [2620/4000] Training [8/16] Loss: 0.00452 +Epoch [2620/4000] Training [9/16] Loss: 0.00291 +Epoch [2620/4000] Training [10/16] Loss: 0.00491 +Epoch [2620/4000] Training [11/16] Loss: 0.00415 +Epoch [2620/4000] Training [12/16] Loss: 0.00366 +Epoch [2620/4000] Training [13/16] Loss: 0.00396 +Epoch [2620/4000] Training [14/16] Loss: 0.00407 +Epoch [2620/4000] Training [15/16] Loss: 0.00351 +Epoch [2620/4000] Training [16/16] Loss: 0.00376 +Epoch [2620/4000] Training metric {'Train/mean dice_metric': 0.9976843595504761, 'Train/mean miou_metric': 0.9951006174087524, 'Train/mean f1': 0.9929895997047424, 'Train/mean precision': 0.9883887767791748, 'Train/mean recall': 0.9976335167884827, 'Train/mean hd95_metric': 0.9273014664649963} +Epoch [2620/4000] Validation [1/4] Loss: 0.35763 focal_loss 0.28830 dice_loss 0.06932 +Epoch [2620/4000] Validation [2/4] Loss: 0.36594 focal_loss 0.25316 dice_loss 0.11278 +Epoch [2620/4000] Validation [3/4] Loss: 0.43190 focal_loss 0.33303 dice_loss 0.09888 +Epoch [2620/4000] Validation [4/4] Loss: 0.55851 focal_loss 0.40703 dice_loss 0.15148 +Epoch [2620/4000] Validation metric {'Val/mean dice_metric': 0.9703727960586548, 'Val/mean miou_metric': 0.9556835889816284, 'Val/mean f1': 0.974715530872345, 'Val/mean precision': 0.974351167678833, 'Val/mean recall': 0.975080132484436, 'Val/mean hd95_metric': 5.2088494300842285} +Cheakpoint... +Epoch [2620/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703727960586548, 'Val/mean miou_metric': 0.9556835889816284, 'Val/mean f1': 0.974715530872345, 'Val/mean precision': 0.974351167678833, 'Val/mean recall': 0.975080132484436, 'Val/mean hd95_metric': 5.2088494300842285} +Epoch [2621/4000] Training [1/16] Loss: 0.00433 +Epoch [2621/4000] Training [2/16] Loss: 0.00463 +Epoch [2621/4000] Training [3/16] Loss: 0.00446 +Epoch [2621/4000] Training [4/16] Loss: 0.00518 +Epoch [2621/4000] Training [5/16] Loss: 0.00402 +Epoch [2621/4000] Training [6/16] Loss: 0.00384 +Epoch [2621/4000] Training [7/16] Loss: 0.00509 +Epoch [2621/4000] Training [8/16] Loss: 0.00555 +Epoch [2621/4000] Training [9/16] Loss: 0.00486 +Epoch [2621/4000] Training [10/16] Loss: 0.00315 +Epoch [2621/4000] Training [11/16] Loss: 0.00493 +Epoch [2621/4000] Training [12/16] Loss: 0.00341 +Epoch [2621/4000] Training [13/16] Loss: 0.00361 +Epoch [2621/4000] Training [14/16] Loss: 0.00443 +Epoch [2621/4000] Training [15/16] Loss: 0.00429 +Epoch [2621/4000] Training [16/16] Loss: 0.00385 +Epoch [2621/4000] Training metric {'Train/mean dice_metric': 0.9974155426025391, 'Train/mean miou_metric': 0.9945769906044006, 'Train/mean f1': 0.9927526712417603, 'Train/mean precision': 0.9882965087890625, 'Train/mean recall': 0.997249186038971, 'Train/mean hd95_metric': 0.9497700929641724} +Epoch [2621/4000] Validation [1/4] Loss: 0.24629 focal_loss 0.18865 dice_loss 0.05764 +Epoch [2621/4000] Validation [2/4] Loss: 0.72908 focal_loss 0.50519 dice_loss 0.22390 +Epoch [2621/4000] Validation [3/4] Loss: 0.26742 focal_loss 0.19915 dice_loss 0.06827 +Epoch [2621/4000] Validation [4/4] Loss: 0.26900 focal_loss 0.18769 dice_loss 0.08130 +Epoch [2621/4000] Validation metric {'Val/mean dice_metric': 0.9722046852111816, 'Val/mean miou_metric': 0.9569964408874512, 'Val/mean f1': 0.9753792881965637, 'Val/mean precision': 0.9739016890525818, 'Val/mean recall': 0.9768615365028381, 'Val/mean hd95_metric': 5.190295219421387} +Cheakpoint... +Epoch [2621/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722046852111816, 'Val/mean miou_metric': 0.9569964408874512, 'Val/mean f1': 0.9753792881965637, 'Val/mean precision': 0.9739016890525818, 'Val/mean recall': 0.9768615365028381, 'Val/mean hd95_metric': 5.190295219421387} +Epoch [2622/4000] Training [1/16] Loss: 0.00430 +Epoch [2622/4000] Training [2/16] Loss: 0.00599 +Epoch [2622/4000] Training [3/16] Loss: 0.00346 +Epoch [2622/4000] Training [4/16] Loss: 0.00363 +Epoch [2622/4000] Training [5/16] Loss: 0.00385 +Epoch [2622/4000] Training [6/16] Loss: 0.00483 +Epoch [2622/4000] Training [7/16] Loss: 0.00409 +Epoch [2622/4000] Training [8/16] Loss: 0.00335 +Epoch [2622/4000] Training [9/16] Loss: 0.00334 +Epoch [2622/4000] Training [10/16] Loss: 0.00328 +Epoch [2622/4000] Training [11/16] Loss: 0.00350 +Epoch [2622/4000] Training [12/16] Loss: 0.00469 +Epoch [2622/4000] Training [13/16] Loss: 0.00394 +Epoch [2622/4000] Training [14/16] Loss: 0.00501 +Epoch [2622/4000] Training [15/16] Loss: 0.00574 +Epoch [2622/4000] Training [16/16] Loss: 0.00311 +Epoch [2622/4000] Training metric {'Train/mean dice_metric': 0.9974926710128784, 'Train/mean miou_metric': 0.9947311878204346, 'Train/mean f1': 0.9928799271583557, 'Train/mean precision': 0.9883831739425659, 'Train/mean recall': 0.9974178075790405, 'Train/mean hd95_metric': 0.9229347705841064} +Epoch [2622/4000] Validation [1/4] Loss: 0.34656 focal_loss 0.27858 dice_loss 0.06798 +Epoch [2622/4000] Validation [2/4] Loss: 0.74371 focal_loss 0.54074 dice_loss 0.20297 +Epoch [2622/4000] Validation [3/4] Loss: 0.44362 focal_loss 0.35115 dice_loss 0.09247 +Epoch [2622/4000] Validation [4/4] Loss: 0.43857 focal_loss 0.29460 dice_loss 0.14397 +Epoch [2622/4000] Validation metric {'Val/mean dice_metric': 0.971954345703125, 'Val/mean miou_metric': 0.9562162160873413, 'Val/mean f1': 0.975090742111206, 'Val/mean precision': 0.974051833152771, 'Val/mean recall': 0.976131796836853, 'Val/mean hd95_metric': 5.146290302276611} +Cheakpoint... +Epoch [2622/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971954345703125, 'Val/mean miou_metric': 0.9562162160873413, 'Val/mean f1': 0.975090742111206, 'Val/mean precision': 0.974051833152771, 'Val/mean recall': 0.976131796836853, 'Val/mean hd95_metric': 5.146290302276611} +Epoch [2623/4000] Training [1/16] Loss: 0.00386 +Epoch [2623/4000] Training [2/16] Loss: 0.00324 +Epoch [2623/4000] Training [3/16] Loss: 0.00538 +Epoch [2623/4000] Training [4/16] Loss: 0.00304 +Epoch [2623/4000] Training [5/16] Loss: 0.00394 +Epoch [2623/4000] Training [6/16] Loss: 0.00334 +Epoch [2623/4000] Training [7/16] Loss: 0.00492 +Epoch [2623/4000] Training [8/16] Loss: 0.00367 +Epoch [2623/4000] Training [9/16] Loss: 0.00450 +Epoch [2623/4000] Training [10/16] Loss: 0.00445 +Epoch [2623/4000] Training [11/16] Loss: 0.00363 +Epoch [2623/4000] Training [12/16] Loss: 0.00551 +Epoch [2623/4000] Training [13/16] Loss: 0.00406 +Epoch [2623/4000] Training [14/16] Loss: 0.00483 +Epoch [2623/4000] Training [15/16] Loss: 0.00287 +Epoch [2623/4000] Training [16/16] Loss: 0.00414 +Epoch [2623/4000] Training metric {'Train/mean dice_metric': 0.9975012540817261, 'Train/mean miou_metric': 0.9947430491447449, 'Train/mean f1': 0.9928253293037415, 'Train/mean precision': 0.9882683753967285, 'Train/mean recall': 0.9974244832992554, 'Train/mean hd95_metric': 0.927050769329071} +Epoch [2623/4000] Validation [1/4] Loss: 0.35635 focal_loss 0.28778 dice_loss 0.06858 +Epoch [2623/4000] Validation [2/4] Loss: 0.36089 focal_loss 0.24967 dice_loss 0.11122 +Epoch [2623/4000] Validation [3/4] Loss: 0.45781 focal_loss 0.35956 dice_loss 0.09825 +Epoch [2623/4000] Validation [4/4] Loss: 0.42574 focal_loss 0.30845 dice_loss 0.11729 +Epoch [2623/4000] Validation metric {'Val/mean dice_metric': 0.972779393196106, 'Val/mean miou_metric': 0.9571396112442017, 'Val/mean f1': 0.9753813147544861, 'Val/mean precision': 0.9739601016044617, 'Val/mean recall': 0.9768068194389343, 'Val/mean hd95_metric': 5.0378875732421875} +Cheakpoint... +Epoch [2623/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972779393196106, 'Val/mean miou_metric': 0.9571396112442017, 'Val/mean f1': 0.9753813147544861, 'Val/mean precision': 0.9739601016044617, 'Val/mean recall': 0.9768068194389343, 'Val/mean hd95_metric': 5.0378875732421875} +Epoch [2624/4000] Training [1/16] Loss: 0.00452 +Epoch [2624/4000] Training [2/16] Loss: 0.00482 +Epoch [2624/4000] Training [3/16] Loss: 0.00307 +Epoch [2624/4000] Training [4/16] Loss: 0.00434 +Epoch [2624/4000] Training [5/16] Loss: 0.00530 +Epoch [2624/4000] Training [6/16] Loss: 0.00381 +Epoch [2624/4000] Training [7/16] Loss: 0.00406 +Epoch [2624/4000] Training [8/16] Loss: 0.00409 +Epoch [2624/4000] Training [9/16] Loss: 0.00403 +Epoch [2624/4000] Training [10/16] Loss: 0.00345 +Epoch [2624/4000] Training [11/16] Loss: 0.00384 +Epoch [2624/4000] Training [12/16] Loss: 0.00425 +Epoch [2624/4000] Training [13/16] Loss: 0.00284 +Epoch [2624/4000] Training [14/16] Loss: 0.00370 +Epoch [2624/4000] Training [15/16] Loss: 0.00432 +Epoch [2624/4000] Training [16/16] Loss: 0.00455 +Epoch [2624/4000] Training metric {'Train/mean dice_metric': 0.9974280595779419, 'Train/mean miou_metric': 0.9945711493492126, 'Train/mean f1': 0.992279052734375, 'Train/mean precision': 0.9872704744338989, 'Train/mean recall': 0.9973386526107788, 'Train/mean hd95_metric': 0.9407780170440674} +Epoch [2624/4000] Validation [1/4] Loss: 0.36274 focal_loss 0.29382 dice_loss 0.06892 +Epoch [2624/4000] Validation [2/4] Loss: 0.37353 focal_loss 0.26205 dice_loss 0.11148 +Epoch [2624/4000] Validation [3/4] Loss: 0.45075 focal_loss 0.35587 dice_loss 0.09488 +Epoch [2624/4000] Validation [4/4] Loss: 0.28101 focal_loss 0.18982 dice_loss 0.09119 +Epoch [2624/4000] Validation metric {'Val/mean dice_metric': 0.9749781489372253, 'Val/mean miou_metric': 0.959577202796936, 'Val/mean f1': 0.9760788083076477, 'Val/mean precision': 0.9727631211280823, 'Val/mean recall': 0.9794172048568726, 'Val/mean hd95_metric': 5.138330459594727} +Cheakpoint... +Epoch [2624/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749781489372253, 'Val/mean miou_metric': 0.959577202796936, 'Val/mean f1': 0.9760788083076477, 'Val/mean precision': 0.9727631211280823, 'Val/mean recall': 0.9794172048568726, 'Val/mean hd95_metric': 5.138330459594727} +Epoch [2625/4000] Training [1/16] Loss: 0.00322 +Epoch [2625/4000] Training [2/16] Loss: 0.00395 +Epoch [2625/4000] Training [3/16] Loss: 0.00496 +Epoch [2625/4000] Training [4/16] Loss: 0.00394 +Epoch [2625/4000] Training [5/16] Loss: 0.00377 +Epoch [2625/4000] Training [6/16] Loss: 0.00380 +Epoch [2625/4000] Training [7/16] Loss: 0.00488 +Epoch [2625/4000] Training [8/16] Loss: 0.00493 +Epoch [2625/4000] Training [9/16] Loss: 0.00479 +Epoch [2625/4000] Training [10/16] Loss: 0.00329 +Epoch [2625/4000] Training [11/16] Loss: 0.00408 +Epoch [2625/4000] Training [12/16] Loss: 0.00355 +Epoch [2625/4000] Training [13/16] Loss: 0.00420 +Epoch [2625/4000] Training [14/16] Loss: 0.00381 +Epoch [2625/4000] Training [15/16] Loss: 0.00319 +Epoch [2625/4000] Training [16/16] Loss: 0.00399 +Epoch [2625/4000] Training metric {'Train/mean dice_metric': 0.9974201917648315, 'Train/mean miou_metric': 0.994575023651123, 'Train/mean f1': 0.9927226305007935, 'Train/mean precision': 0.9881219863891602, 'Train/mean recall': 0.9973662495613098, 'Train/mean hd95_metric': 0.9473655819892883} +Epoch [2625/4000] Validation [1/4] Loss: 0.35017 focal_loss 0.28398 dice_loss 0.06619 +Epoch [2625/4000] Validation [2/4] Loss: 0.36844 focal_loss 0.25517 dice_loss 0.11326 +Epoch [2625/4000] Validation [3/4] Loss: 0.43824 focal_loss 0.34660 dice_loss 0.09164 +Epoch [2625/4000] Validation [4/4] Loss: 0.66281 focal_loss 0.51634 dice_loss 0.14646 +Epoch [2625/4000] Validation metric {'Val/mean dice_metric': 0.9734119176864624, 'Val/mean miou_metric': 0.9582316279411316, 'Val/mean f1': 0.9755649566650391, 'Val/mean precision': 0.972762942314148, 'Val/mean recall': 0.9783831238746643, 'Val/mean hd95_metric': 5.131360054016113} +Cheakpoint... +Epoch [2625/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734119176864624, 'Val/mean miou_metric': 0.9582316279411316, 'Val/mean f1': 0.9755649566650391, 'Val/mean precision': 0.972762942314148, 'Val/mean recall': 0.9783831238746643, 'Val/mean hd95_metric': 5.131360054016113} +Epoch [2626/4000] Training [1/16] Loss: 0.00417 +Epoch [2626/4000] Training [2/16] Loss: 0.00404 +Epoch [2626/4000] Training [3/16] Loss: 0.00308 +Epoch [2626/4000] Training [4/16] Loss: 0.00397 +Epoch [2626/4000] Training [5/16] Loss: 0.00334 +Epoch [2626/4000] Training [6/16] Loss: 0.00508 +Epoch [2626/4000] Training [7/16] Loss: 0.00439 +Epoch [2626/4000] Training [8/16] Loss: 0.00340 +Epoch [2626/4000] Training [9/16] Loss: 0.00448 +Epoch [2626/4000] Training [10/16] Loss: 0.00341 +Epoch [2626/4000] Training [11/16] Loss: 0.00398 +Epoch [2626/4000] Training [12/16] Loss: 0.00502 +Epoch [2626/4000] Training [13/16] Loss: 0.00290 +Epoch [2626/4000] Training [14/16] Loss: 0.00388 +Epoch [2626/4000] Training [15/16] Loss: 0.00356 +Epoch [2626/4000] Training [16/16] Loss: 0.00338 +Epoch [2626/4000] Training metric {'Train/mean dice_metric': 0.9976105690002441, 'Train/mean miou_metric': 0.9949544668197632, 'Train/mean f1': 0.9927992224693298, 'Train/mean precision': 0.98805832862854, 'Train/mean recall': 0.9975857734680176, 'Train/mean hd95_metric': 0.9184848070144653} +Epoch [2626/4000] Validation [1/4] Loss: 0.35844 focal_loss 0.29120 dice_loss 0.06724 +Epoch [2626/4000] Validation [2/4] Loss: 0.70097 focal_loss 0.48326 dice_loss 0.21771 +Epoch [2626/4000] Validation [3/4] Loss: 0.27676 focal_loss 0.20024 dice_loss 0.07651 +Epoch [2626/4000] Validation [4/4] Loss: 0.28350 focal_loss 0.19832 dice_loss 0.08519 +Epoch [2626/4000] Validation metric {'Val/mean dice_metric': 0.9740821719169617, 'Val/mean miou_metric': 0.9596750140190125, 'Val/mean f1': 0.975979208946228, 'Val/mean precision': 0.9724332094192505, 'Val/mean recall': 0.9795511960983276, 'Val/mean hd95_metric': 4.8933539390563965} +Cheakpoint... +Epoch [2626/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740821719169617, 'Val/mean miou_metric': 0.9596750140190125, 'Val/mean f1': 0.975979208946228, 'Val/mean precision': 0.9724332094192505, 'Val/mean recall': 0.9795511960983276, 'Val/mean hd95_metric': 4.8933539390563965} +Epoch [2627/4000] Training [1/16] Loss: 0.00306 +Epoch [2627/4000] Training [2/16] Loss: 0.00511 +Epoch [2627/4000] Training [3/16] Loss: 0.00432 +Epoch [2627/4000] Training [4/16] Loss: 0.00332 +Epoch [2627/4000] Training [5/16] Loss: 0.00482 +Epoch [2627/4000] Training [6/16] Loss: 0.00402 +Epoch [2627/4000] Training [7/16] Loss: 0.00381 +Epoch [2627/4000] Training [8/16] Loss: 0.00384 +Epoch [2627/4000] Training [9/16] Loss: 0.00361 +Epoch [2627/4000] Training [10/16] Loss: 0.00346 +Epoch [2627/4000] Training [11/16] Loss: 0.00472 +Epoch [2627/4000] Training [12/16] Loss: 0.00415 +Epoch [2627/4000] Training [13/16] Loss: 0.00388 +Epoch [2627/4000] Training [14/16] Loss: 0.00369 +Epoch [2627/4000] Training [15/16] Loss: 0.00675 +Epoch [2627/4000] Training [16/16] Loss: 0.00375 +Epoch [2627/4000] Training metric {'Train/mean dice_metric': 0.9972615838050842, 'Train/mean miou_metric': 0.9943551421165466, 'Train/mean f1': 0.9930039644241333, 'Train/mean precision': 0.9886330366134644, 'Train/mean recall': 0.997413694858551, 'Train/mean hd95_metric': 0.9674485921859741} +Epoch [2627/4000] Validation [1/4] Loss: 0.33300 focal_loss 0.26693 dice_loss 0.06607 +Epoch [2627/4000] Validation [2/4] Loss: 0.79356 focal_loss 0.58135 dice_loss 0.21221 +Epoch [2627/4000] Validation [3/4] Loss: 0.44094 focal_loss 0.34629 dice_loss 0.09465 +Epoch [2627/4000] Validation [4/4] Loss: 0.31437 focal_loss 0.21127 dice_loss 0.10310 +Epoch [2627/4000] Validation metric {'Val/mean dice_metric': 0.9727338552474976, 'Val/mean miou_metric': 0.9575783014297485, 'Val/mean f1': 0.9759028553962708, 'Val/mean precision': 0.9725115895271301, 'Val/mean recall': 0.9793179035186768, 'Val/mean hd95_metric': 5.5903849601745605} +Cheakpoint... +Epoch [2627/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727338552474976, 'Val/mean miou_metric': 0.9575783014297485, 'Val/mean f1': 0.9759028553962708, 'Val/mean precision': 0.9725115895271301, 'Val/mean recall': 0.9793179035186768, 'Val/mean hd95_metric': 5.5903849601745605} +Epoch [2628/4000] Training [1/16] Loss: 0.00396 +Epoch [2628/4000] Training [2/16] Loss: 0.00318 +Epoch [2628/4000] Training [3/16] Loss: 0.00329 +Epoch [2628/4000] Training [4/16] Loss: 0.00405 +Epoch [2628/4000] Training [5/16] Loss: 0.00321 +Epoch [2628/4000] Training [6/16] Loss: 0.00321 +Epoch [2628/4000] Training [7/16] Loss: 0.00407 +Epoch [2628/4000] Training [8/16] Loss: 0.00499 +Epoch [2628/4000] Training [9/16] Loss: 0.00299 +Epoch [2628/4000] Training [10/16] Loss: 0.00500 +Epoch [2628/4000] Training [11/16] Loss: 0.00484 +Epoch [2628/4000] Training [12/16] Loss: 0.00333 +Epoch [2628/4000] Training [13/16] Loss: 0.00372 +Epoch [2628/4000] Training [14/16] Loss: 0.00260 +Epoch [2628/4000] Training [15/16] Loss: 0.00400 +Epoch [2628/4000] Training [16/16] Loss: 0.00444 +Epoch [2628/4000] Training metric {'Train/mean dice_metric': 0.9976596236228943, 'Train/mean miou_metric': 0.9950568675994873, 'Train/mean f1': 0.9929381608963013, 'Train/mean precision': 0.9884277582168579, 'Train/mean recall': 0.997489869594574, 'Train/mean hd95_metric': 0.910476803779602} +Epoch [2628/4000] Validation [1/4] Loss: 0.34966 focal_loss 0.28666 dice_loss 0.06300 +Epoch [2628/4000] Validation [2/4] Loss: 0.33085 focal_loss 0.23256 dice_loss 0.09830 +Epoch [2628/4000] Validation [3/4] Loss: 0.49421 focal_loss 0.39430 dice_loss 0.09991 +Epoch [2628/4000] Validation [4/4] Loss: 0.44458 focal_loss 0.31624 dice_loss 0.12835 +Epoch [2628/4000] Validation metric {'Val/mean dice_metric': 0.9737951159477234, 'Val/mean miou_metric': 0.9591771364212036, 'Val/mean f1': 0.975843071937561, 'Val/mean precision': 0.9720322489738464, 'Val/mean recall': 0.9796839952468872, 'Val/mean hd95_metric': 5.357191562652588} +Cheakpoint... +Epoch [2628/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737951159477234, 'Val/mean miou_metric': 0.9591771364212036, 'Val/mean f1': 0.975843071937561, 'Val/mean precision': 0.9720322489738464, 'Val/mean recall': 0.9796839952468872, 'Val/mean hd95_metric': 5.357191562652588} +Epoch [2629/4000] Training [1/16] Loss: 0.00426 +Epoch [2629/4000] Training [2/16] Loss: 0.00378 +Epoch [2629/4000] Training [3/16] Loss: 0.00349 +Epoch [2629/4000] Training [4/16] Loss: 0.00389 +Epoch [2629/4000] Training [5/16] Loss: 0.00376 +Epoch [2629/4000] Training [6/16] Loss: 0.00407 +Epoch [2629/4000] Training [7/16] Loss: 0.00374 +Epoch [2629/4000] Training [8/16] Loss: 0.00407 +Epoch [2629/4000] Training [9/16] Loss: 0.00393 +Epoch [2629/4000] Training [10/16] Loss: 0.00332 +Epoch [2629/4000] Training [11/16] Loss: 0.00279 +Epoch [2629/4000] Training [12/16] Loss: 0.00379 +Epoch [2629/4000] Training [13/16] Loss: 0.00537 +Epoch [2629/4000] Training [14/16] Loss: 0.00314 +Epoch [2629/4000] Training [15/16] Loss: 0.00470 +Epoch [2629/4000] Training [16/16] Loss: 0.00406 +Epoch [2629/4000] Training metric {'Train/mean dice_metric': 0.9975162744522095, 'Train/mean miou_metric': 0.9947730302810669, 'Train/mean f1': 0.9928492903709412, 'Train/mean precision': 0.988341748714447, 'Train/mean recall': 0.9973981380462646, 'Train/mean hd95_metric': 0.9408479928970337} +Epoch [2629/4000] Validation [1/4] Loss: 0.26831 focal_loss 0.21258 dice_loss 0.05573 +Epoch [2629/4000] Validation [2/4] Loss: 0.33963 focal_loss 0.23732 dice_loss 0.10231 +Epoch [2629/4000] Validation [3/4] Loss: 0.45586 focal_loss 0.36325 dice_loss 0.09260 +Epoch [2629/4000] Validation [4/4] Loss: 0.38341 focal_loss 0.26295 dice_loss 0.12046 +Epoch [2629/4000] Validation metric {'Val/mean dice_metric': 0.9739837646484375, 'Val/mean miou_metric': 0.9590840339660645, 'Val/mean f1': 0.9767715334892273, 'Val/mean precision': 0.9734184741973877, 'Val/mean recall': 0.980147659778595, 'Val/mean hd95_metric': 5.36061954498291} +Cheakpoint... +Epoch [2629/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739837646484375, 'Val/mean miou_metric': 0.9590840339660645, 'Val/mean f1': 0.9767715334892273, 'Val/mean precision': 0.9734184741973877, 'Val/mean recall': 0.980147659778595, 'Val/mean hd95_metric': 5.36061954498291} +Epoch [2630/4000] Training [1/16] Loss: 0.00424 +Epoch [2630/4000] Training [2/16] Loss: 0.00293 +Epoch [2630/4000] Training [3/16] Loss: 0.00251 +Epoch [2630/4000] Training [4/16] Loss: 0.00433 +Epoch [2630/4000] Training [5/16] Loss: 0.00345 +Epoch [2630/4000] Training [6/16] Loss: 0.00287 +Epoch [2630/4000] Training [7/16] Loss: 0.00458 +Epoch [2630/4000] Training [8/16] Loss: 0.00555 +Epoch [2630/4000] Training [9/16] Loss: 0.00456 +Epoch [2630/4000] Training [10/16] Loss: 0.00277 +Epoch [2630/4000] Training [11/16] Loss: 0.00366 +Epoch [2630/4000] Training [12/16] Loss: 0.00423 +Epoch [2630/4000] Training [13/16] Loss: 0.00332 +Epoch [2630/4000] Training [14/16] Loss: 0.00356 +Epoch [2630/4000] Training [15/16] Loss: 0.00307 +Epoch [2630/4000] Training [16/16] Loss: 0.00346 +Epoch [2630/4000] Training metric {'Train/mean dice_metric': 0.9976300001144409, 'Train/mean miou_metric': 0.9949845671653748, 'Train/mean f1': 0.9928269982337952, 'Train/mean precision': 0.9881761074066162, 'Train/mean recall': 0.9975218176841736, 'Train/mean hd95_metric': 0.9268831014633179} +Epoch [2630/4000] Validation [1/4] Loss: 0.39998 focal_loss 0.33110 dice_loss 0.06889 +Epoch [2630/4000] Validation [2/4] Loss: 0.81223 focal_loss 0.62904 dice_loss 0.18319 +Epoch [2630/4000] Validation [3/4] Loss: 0.25433 focal_loss 0.18484 dice_loss 0.06949 +Epoch [2630/4000] Validation [4/4] Loss: 0.31608 focal_loss 0.21891 dice_loss 0.09717 +Epoch [2630/4000] Validation metric {'Val/mean dice_metric': 0.9730088114738464, 'Val/mean miou_metric': 0.9588001370429993, 'Val/mean f1': 0.975619912147522, 'Val/mean precision': 0.9732906222343445, 'Val/mean recall': 0.9779602885246277, 'Val/mean hd95_metric': 5.411973476409912} +Cheakpoint... +Epoch [2630/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730088114738464, 'Val/mean miou_metric': 0.9588001370429993, 'Val/mean f1': 0.975619912147522, 'Val/mean precision': 0.9732906222343445, 'Val/mean recall': 0.9779602885246277, 'Val/mean hd95_metric': 5.411973476409912} +Epoch [2631/4000] Training [1/16] Loss: 0.00297 +Epoch [2631/4000] Training [2/16] Loss: 0.00326 +Epoch [2631/4000] Training [3/16] Loss: 0.00480 +Epoch [2631/4000] Training [4/16] Loss: 0.00348 +Epoch [2631/4000] Training [5/16] Loss: 0.00388 +Epoch [2631/4000] Training [6/16] Loss: 0.00432 +Epoch [2631/4000] Training [7/16] Loss: 0.00467 +Epoch [2631/4000] Training [8/16] Loss: 0.00344 +Epoch [2631/4000] Training [9/16] Loss: 0.03234 +Epoch [2631/4000] Training [10/16] Loss: 0.00368 +Epoch [2631/4000] Training [11/16] Loss: 0.00679 +Epoch [2631/4000] Training [12/16] Loss: 0.00307 +Epoch [2631/4000] Training [13/16] Loss: 0.00320 +Epoch [2631/4000] Training [14/16] Loss: 0.00358 +Epoch [2631/4000] Training [15/16] Loss: 0.00405 +Epoch [2631/4000] Training [16/16] Loss: 0.00388 +Epoch [2631/4000] Training metric {'Train/mean dice_metric': 0.9970170259475708, 'Train/mean miou_metric': 0.9938560724258423, 'Train/mean f1': 0.9925344586372375, 'Train/mean precision': 0.9879835247993469, 'Train/mean recall': 0.9971275329589844, 'Train/mean hd95_metric': 1.008773684501648} +Epoch [2631/4000] Validation [1/4] Loss: 0.32438 focal_loss 0.26146 dice_loss 0.06292 +Epoch [2631/4000] Validation [2/4] Loss: 0.85484 focal_loss 0.64047 dice_loss 0.21436 +Epoch [2631/4000] Validation [3/4] Loss: 0.26424 focal_loss 0.19516 dice_loss 0.06908 +Epoch [2631/4000] Validation [4/4] Loss: 0.41729 focal_loss 0.29344 dice_loss 0.12385 +Epoch [2631/4000] Validation metric {'Val/mean dice_metric': 0.9717744588851929, 'Val/mean miou_metric': 0.9568759799003601, 'Val/mean f1': 0.9748621582984924, 'Val/mean precision': 0.969735860824585, 'Val/mean recall': 0.9800428748130798, 'Val/mean hd95_metric': 5.417749404907227} +Cheakpoint... +Epoch [2631/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717744588851929, 'Val/mean miou_metric': 0.9568759799003601, 'Val/mean f1': 0.9748621582984924, 'Val/mean precision': 0.969735860824585, 'Val/mean recall': 0.9800428748130798, 'Val/mean hd95_metric': 5.417749404907227} +Epoch [2632/4000] Training [1/16] Loss: 0.00372 +Epoch [2632/4000] Training [2/16] Loss: 0.00337 +Epoch [2632/4000] Training [3/16] Loss: 0.00400 +Epoch [2632/4000] Training [4/16] Loss: 0.00444 +Epoch [2632/4000] Training [5/16] Loss: 0.00354 +Epoch [2632/4000] Training [6/16] Loss: 0.00379 +Epoch [2632/4000] Training [7/16] Loss: 0.00403 +Epoch [2632/4000] Training [8/16] Loss: 0.00360 +Epoch [2632/4000] Training [9/16] Loss: 0.00305 +Epoch [2632/4000] Training [10/16] Loss: 0.00385 +Epoch [2632/4000] Training [11/16] Loss: 0.00395 +Epoch [2632/4000] Training [12/16] Loss: 0.00435 +Epoch [2632/4000] Training [13/16] Loss: 0.00642 +Epoch [2632/4000] Training [14/16] Loss: 0.00384 +Epoch [2632/4000] Training [15/16] Loss: 0.00407 +Epoch [2632/4000] Training [16/16] Loss: 0.00498 +Epoch [2632/4000] Training metric {'Train/mean dice_metric': 0.9974464178085327, 'Train/mean miou_metric': 0.9946302175521851, 'Train/mean f1': 0.9927669167518616, 'Train/mean precision': 0.9881762862205505, 'Train/mean recall': 0.9974004030227661, 'Train/mean hd95_metric': 0.9132112860679626} +Epoch [2632/4000] Validation [1/4] Loss: 0.30672 focal_loss 0.24239 dice_loss 0.06434 +Epoch [2632/4000] Validation [2/4] Loss: 0.37108 focal_loss 0.26337 dice_loss 0.10771 +Epoch [2632/4000] Validation [3/4] Loss: 0.25697 focal_loss 0.18946 dice_loss 0.06750 +Epoch [2632/4000] Validation [4/4] Loss: 0.40648 focal_loss 0.28502 dice_loss 0.12145 +Epoch [2632/4000] Validation metric {'Val/mean dice_metric': 0.9755876660346985, 'Val/mean miou_metric': 0.960307240486145, 'Val/mean f1': 0.9764216542243958, 'Val/mean precision': 0.9707717299461365, 'Val/mean recall': 0.9821377396583557, 'Val/mean hd95_metric': 5.697485446929932} +Cheakpoint... +Epoch [2632/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755876660346985, 'Val/mean miou_metric': 0.960307240486145, 'Val/mean f1': 0.9764216542243958, 'Val/mean precision': 0.9707717299461365, 'Val/mean recall': 0.9821377396583557, 'Val/mean hd95_metric': 5.697485446929932} +Epoch [2633/4000] Training [1/16] Loss: 0.00371 +Epoch [2633/4000] Training [2/16] Loss: 0.00402 +Epoch [2633/4000] Training [3/16] Loss: 0.00298 +Epoch [2633/4000] Training [4/16] Loss: 0.00443 +Epoch [2633/4000] Training [5/16] Loss: 0.00334 +Epoch [2633/4000] Training [6/16] Loss: 0.00422 +Epoch [2633/4000] Training [7/16] Loss: 0.00348 +Epoch [2633/4000] Training [8/16] Loss: 0.00426 +Epoch [2633/4000] Training [9/16] Loss: 0.00445 +Epoch [2633/4000] Training [10/16] Loss: 0.00288 +Epoch [2633/4000] Training [11/16] Loss: 0.00308 +Epoch [2633/4000] Training [12/16] Loss: 0.00390 +Epoch [2633/4000] Training [13/16] Loss: 0.00288 +Epoch [2633/4000] Training [14/16] Loss: 0.00276 +Epoch [2633/4000] Training [15/16] Loss: 0.00528 +Epoch [2633/4000] Training [16/16] Loss: 0.00339 +Epoch [2633/4000] Training metric {'Train/mean dice_metric': 0.9977822303771973, 'Train/mean miou_metric': 0.9952858686447144, 'Train/mean f1': 0.9929395914077759, 'Train/mean precision': 0.988329291343689, 'Train/mean recall': 0.997593104839325, 'Train/mean hd95_metric': 0.9032503366470337} +Epoch [2633/4000] Validation [1/4] Loss: 0.32792 focal_loss 0.26432 dice_loss 0.06360 +Epoch [2633/4000] Validation [2/4] Loss: 0.38109 focal_loss 0.27093 dice_loss 0.11016 +Epoch [2633/4000] Validation [3/4] Loss: 0.47841 focal_loss 0.38540 dice_loss 0.09301 +Epoch [2633/4000] Validation [4/4] Loss: 0.32497 focal_loss 0.21953 dice_loss 0.10543 +Epoch [2633/4000] Validation metric {'Val/mean dice_metric': 0.9735703468322754, 'Val/mean miou_metric': 0.9589313268661499, 'Val/mean f1': 0.976093053817749, 'Val/mean precision': 0.9716629385948181, 'Val/mean recall': 0.980563759803772, 'Val/mean hd95_metric': 6.073872089385986} +Cheakpoint... +Epoch [2633/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735703468322754, 'Val/mean miou_metric': 0.9589313268661499, 'Val/mean f1': 0.976093053817749, 'Val/mean precision': 0.9716629385948181, 'Val/mean recall': 0.980563759803772, 'Val/mean hd95_metric': 6.073872089385986} +Epoch [2634/4000] Training [1/16] Loss: 0.00405 +Epoch [2634/4000] Training [2/16] Loss: 0.00319 +Epoch [2634/4000] Training [3/16] Loss: 0.00326 +Epoch [2634/4000] Training [4/16] Loss: 0.00433 +Epoch [2634/4000] Training [5/16] Loss: 0.00315 +Epoch [2634/4000] Training [6/16] Loss: 0.00531 +Epoch [2634/4000] Training [7/16] Loss: 0.00730 +Epoch [2634/4000] Training [8/16] Loss: 0.00503 +Epoch [2634/4000] Training [9/16] Loss: 0.00381 +Epoch [2634/4000] Training [10/16] Loss: 0.00372 +Epoch [2634/4000] Training [11/16] Loss: 0.00400 +Epoch [2634/4000] Training [12/16] Loss: 0.00372 +Epoch [2634/4000] Training [13/16] Loss: 0.00449 +Epoch [2634/4000] Training [14/16] Loss: 0.00333 +Epoch [2634/4000] Training [15/16] Loss: 0.00319 +Epoch [2634/4000] Training [16/16] Loss: 0.00472 +Epoch [2634/4000] Training metric {'Train/mean dice_metric': 0.9975327253341675, 'Train/mean miou_metric': 0.9947524070739746, 'Train/mean f1': 0.9915350079536438, 'Train/mean precision': 0.9857291579246521, 'Train/mean recall': 0.9974097013473511, 'Train/mean hd95_metric': 0.9589219093322754} +Epoch [2634/4000] Validation [1/4] Loss: 0.33175 focal_loss 0.26717 dice_loss 0.06458 +Epoch [2634/4000] Validation [2/4] Loss: 0.66476 focal_loss 0.50157 dice_loss 0.16319 +Epoch [2634/4000] Validation [3/4] Loss: 0.47502 focal_loss 0.37961 dice_loss 0.09541 +Epoch [2634/4000] Validation [4/4] Loss: 0.50384 focal_loss 0.36584 dice_loss 0.13800 +Epoch [2634/4000] Validation metric {'Val/mean dice_metric': 0.9715490341186523, 'Val/mean miou_metric': 0.9565898180007935, 'Val/mean f1': 0.9738325476646423, 'Val/mean precision': 0.9693238139152527, 'Val/mean recall': 0.9783833622932434, 'Val/mean hd95_metric': 5.830207824707031} +Cheakpoint... +Epoch [2634/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715490341186523, 'Val/mean miou_metric': 0.9565898180007935, 'Val/mean f1': 0.9738325476646423, 'Val/mean precision': 0.9693238139152527, 'Val/mean recall': 0.9783833622932434, 'Val/mean hd95_metric': 5.830207824707031} +Epoch [2635/4000] Training [1/16] Loss: 0.00440 +Epoch [2635/4000] Training [2/16] Loss: 0.00469 +Epoch [2635/4000] Training [3/16] Loss: 0.00368 +Epoch [2635/4000] Training [4/16] Loss: 0.00372 +Epoch [2635/4000] Training [5/16] Loss: 0.00507 +Epoch [2635/4000] Training [6/16] Loss: 0.00387 +Epoch [2635/4000] Training [7/16] Loss: 0.00439 +Epoch [2635/4000] Training [8/16] Loss: 0.00404 +Epoch [2635/4000] Training [9/16] Loss: 0.00442 +Epoch [2635/4000] Training [10/16] Loss: 0.00377 +Epoch [2635/4000] Training [11/16] Loss: 0.00387 +Epoch [2635/4000] Training [12/16] Loss: 0.00352 +Epoch [2635/4000] Training [13/16] Loss: 0.00366 +Epoch [2635/4000] Training [14/16] Loss: 0.00275 +Epoch [2635/4000] Training [15/16] Loss: 0.00290 +Epoch [2635/4000] Training [16/16] Loss: 0.00463 +Epoch [2635/4000] Training metric {'Train/mean dice_metric': 0.9974442720413208, 'Train/mean miou_metric': 0.9946185946464539, 'Train/mean f1': 0.9925822019577026, 'Train/mean precision': 0.9877630472183228, 'Train/mean recall': 0.9974486231803894, 'Train/mean hd95_metric': 0.9215397238731384} +Epoch [2635/4000] Validation [1/4] Loss: 0.31516 focal_loss 0.25056 dice_loss 0.06460 +Epoch [2635/4000] Validation [2/4] Loss: 0.85152 focal_loss 0.65275 dice_loss 0.19877 +Epoch [2635/4000] Validation [3/4] Loss: 0.46166 focal_loss 0.36570 dice_loss 0.09596 +Epoch [2635/4000] Validation [4/4] Loss: 0.26900 focal_loss 0.17215 dice_loss 0.09685 +Epoch [2635/4000] Validation metric {'Val/mean dice_metric': 0.9741052389144897, 'Val/mean miou_metric': 0.9590790867805481, 'Val/mean f1': 0.9754946231842041, 'Val/mean precision': 0.9725801944732666, 'Val/mean recall': 0.9784265756607056, 'Val/mean hd95_metric': 5.691641807556152} +Cheakpoint... +Epoch [2635/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741052389144897, 'Val/mean miou_metric': 0.9590790867805481, 'Val/mean f1': 0.9754946231842041, 'Val/mean precision': 0.9725801944732666, 'Val/mean recall': 0.9784265756607056, 'Val/mean hd95_metric': 5.691641807556152} +Epoch [2636/4000] Training [1/16] Loss: 0.00350 +Epoch [2636/4000] Training [2/16] Loss: 0.00329 +Epoch [2636/4000] Training [3/16] Loss: 0.00365 +Epoch [2636/4000] Training [4/16] Loss: 0.00421 +Epoch [2636/4000] Training [5/16] Loss: 0.00467 +Epoch [2636/4000] Training [6/16] Loss: 0.00293 +Epoch [2636/4000] Training [7/16] Loss: 0.00357 +Epoch [2636/4000] Training [8/16] Loss: 0.00518 +Epoch [2636/4000] Training [9/16] Loss: 0.00362 +Epoch [2636/4000] Training [10/16] Loss: 0.00332 +Epoch [2636/4000] Training [11/16] Loss: 0.00492 +Epoch [2636/4000] Training [12/16] Loss: 0.00432 +Epoch [2636/4000] Training [13/16] Loss: 0.00345 +Epoch [2636/4000] Training [14/16] Loss: 0.00416 +Epoch [2636/4000] Training [15/16] Loss: 0.00360 +Epoch [2636/4000] Training [16/16] Loss: 0.00355 +Epoch [2636/4000] Training metric {'Train/mean dice_metric': 0.9977745413780212, 'Train/mean miou_metric': 0.995286226272583, 'Train/mean f1': 0.9930227994918823, 'Train/mean precision': 0.9885267615318298, 'Train/mean recall': 0.9975599050521851, 'Train/mean hd95_metric': 0.9040315747261047} +Epoch [2636/4000] Validation [1/4] Loss: 0.34994 focal_loss 0.28252 dice_loss 0.06741 +Epoch [2636/4000] Validation [2/4] Loss: 0.39035 focal_loss 0.27635 dice_loss 0.11400 +Epoch [2636/4000] Validation [3/4] Loss: 0.47372 focal_loss 0.37878 dice_loss 0.09495 +Epoch [2636/4000] Validation [4/4] Loss: 0.31749 focal_loss 0.22768 dice_loss 0.08981 +Epoch [2636/4000] Validation metric {'Val/mean dice_metric': 0.9743888974189758, 'Val/mean miou_metric': 0.9596184492111206, 'Val/mean f1': 0.9755227565765381, 'Val/mean precision': 0.9724723696708679, 'Val/mean recall': 0.9785923361778259, 'Val/mean hd95_metric': 5.34852933883667} +Cheakpoint... +Epoch [2636/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743888974189758, 'Val/mean miou_metric': 0.9596184492111206, 'Val/mean f1': 0.9755227565765381, 'Val/mean precision': 0.9724723696708679, 'Val/mean recall': 0.9785923361778259, 'Val/mean hd95_metric': 5.34852933883667} +Epoch [2637/4000] Training [1/16] Loss: 0.00365 +Epoch [2637/4000] Training [2/16] Loss: 0.00330 +Epoch [2637/4000] Training [3/16] Loss: 0.00430 +Epoch [2637/4000] Training [4/16] Loss: 0.00470 +Epoch [2637/4000] Training [5/16] Loss: 0.00365 +Epoch [2637/4000] Training [6/16] Loss: 0.00350 +Epoch [2637/4000] Training [7/16] Loss: 0.00386 +Epoch [2637/4000] Training [8/16] Loss: 0.00378 +Epoch [2637/4000] Training [9/16] Loss: 0.00318 +Epoch [2637/4000] Training [10/16] Loss: 0.00366 +Epoch [2637/4000] Training [11/16] Loss: 0.00401 +Epoch [2637/4000] Training [12/16] Loss: 0.00354 +Epoch [2637/4000] Training [13/16] Loss: 0.00424 +Epoch [2637/4000] Training [14/16] Loss: 0.00392 +Epoch [2637/4000] Training [15/16] Loss: 0.00418 +Epoch [2637/4000] Training [16/16] Loss: 0.00350 +Epoch [2637/4000] Training metric {'Train/mean dice_metric': 0.9976800680160522, 'Train/mean miou_metric': 0.9950964450836182, 'Train/mean f1': 0.9930176734924316, 'Train/mean precision': 0.988508403301239, 'Train/mean recall': 0.9975682497024536, 'Train/mean hd95_metric': 0.8975862264633179} +Epoch [2637/4000] Validation [1/4] Loss: 0.28723 focal_loss 0.22671 dice_loss 0.06053 +Epoch [2637/4000] Validation [2/4] Loss: 0.37017 focal_loss 0.26263 dice_loss 0.10754 +Epoch [2637/4000] Validation [3/4] Loss: 0.45978 focal_loss 0.36825 dice_loss 0.09153 +Epoch [2637/4000] Validation [4/4] Loss: 0.34250 focal_loss 0.23869 dice_loss 0.10381 +Epoch [2637/4000] Validation metric {'Val/mean dice_metric': 0.9738208651542664, 'Val/mean miou_metric': 0.9591922760009766, 'Val/mean f1': 0.9757672548294067, 'Val/mean precision': 0.9725788235664368, 'Val/mean recall': 0.9789765477180481, 'Val/mean hd95_metric': 5.518885612487793} +Cheakpoint... +Epoch [2637/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738208651542664, 'Val/mean miou_metric': 0.9591922760009766, 'Val/mean f1': 0.9757672548294067, 'Val/mean precision': 0.9725788235664368, 'Val/mean recall': 0.9789765477180481, 'Val/mean hd95_metric': 5.518885612487793} +Epoch [2638/4000] Training [1/16] Loss: 0.00362 +Epoch [2638/4000] Training [2/16] Loss: 0.00408 +Epoch [2638/4000] Training [3/16] Loss: 0.00478 +Epoch [2638/4000] Training [4/16] Loss: 0.00411 +Epoch [2638/4000] Training [5/16] Loss: 0.00360 +Epoch [2638/4000] Training [6/16] Loss: 0.00272 +Epoch [2638/4000] Training [7/16] Loss: 0.00291 +Epoch [2638/4000] Training [8/16] Loss: 0.00453 +Epoch [2638/4000] Training [9/16] Loss: 0.00750 +Epoch [2638/4000] Training [10/16] Loss: 0.00575 +Epoch [2638/4000] Training [11/16] Loss: 0.00422 +Epoch [2638/4000] Training [12/16] Loss: 0.00294 +Epoch [2638/4000] Training [13/16] Loss: 0.00390 +Epoch [2638/4000] Training [14/16] Loss: 0.00439 +Epoch [2638/4000] Training [15/16] Loss: 0.00487 +Epoch [2638/4000] Training [16/16] Loss: 0.00452 +Epoch [2638/4000] Training metric {'Train/mean dice_metric': 0.9974527359008789, 'Train/mean miou_metric': 0.9946426153182983, 'Train/mean f1': 0.9927839040756226, 'Train/mean precision': 0.9881753921508789, 'Train/mean recall': 0.9974355697631836, 'Train/mean hd95_metric': 1.1620535850524902} +Epoch [2638/4000] Validation [1/4] Loss: 0.32327 focal_loss 0.25857 dice_loss 0.06470 +Epoch [2638/4000] Validation [2/4] Loss: 0.87129 focal_loss 0.68256 dice_loss 0.18873 +Epoch [2638/4000] Validation [3/4] Loss: 0.42859 focal_loss 0.33107 dice_loss 0.09752 +Epoch [2638/4000] Validation [4/4] Loss: 0.41650 focal_loss 0.28417 dice_loss 0.13233 +Epoch [2638/4000] Validation metric {'Val/mean dice_metric': 0.9738672971725464, 'Val/mean miou_metric': 0.9584587216377258, 'Val/mean f1': 0.9755544662475586, 'Val/mean precision': 0.9736913442611694, 'Val/mean recall': 0.977424681186676, 'Val/mean hd95_metric': 5.486382961273193} +Cheakpoint... +Epoch [2638/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738672971725464, 'Val/mean miou_metric': 0.9584587216377258, 'Val/mean f1': 0.9755544662475586, 'Val/mean precision': 0.9736913442611694, 'Val/mean recall': 0.977424681186676, 'Val/mean hd95_metric': 5.486382961273193} +Epoch [2639/4000] Training [1/16] Loss: 0.00412 +Epoch [2639/4000] Training [2/16] Loss: 0.00353 +Epoch [2639/4000] Training [3/16] Loss: 0.00341 +Epoch [2639/4000] Training [4/16] Loss: 0.00445 +Epoch [2639/4000] Training [5/16] Loss: 0.00695 +Epoch [2639/4000] Training [6/16] Loss: 0.00340 +Epoch [2639/4000] Training [7/16] Loss: 0.00410 +Epoch [2639/4000] Training [8/16] Loss: 0.00308 +Epoch [2639/4000] Training [9/16] Loss: 0.00440 +Epoch [2639/4000] Training [10/16] Loss: 0.00354 +Epoch [2639/4000] Training [11/16] Loss: 0.00327 +Epoch [2639/4000] Training [12/16] Loss: 0.00365 +Epoch [2639/4000] Training [13/16] Loss: 0.00309 +Epoch [2639/4000] Training [14/16] Loss: 0.00316 +Epoch [2639/4000] Training [15/16] Loss: 0.00440 +Epoch [2639/4000] Training [16/16] Loss: 0.00654 +Epoch [2639/4000] Training metric {'Train/mean dice_metric': 0.9974852800369263, 'Train/mean miou_metric': 0.994694709777832, 'Train/mean f1': 0.9925361275672913, 'Train/mean precision': 0.9877876043319702, 'Train/mean recall': 0.9973304867744446, 'Train/mean hd95_metric': 0.9307471513748169} +Epoch [2639/4000] Validation [1/4] Loss: 0.34003 focal_loss 0.27373 dice_loss 0.06630 +Epoch [2639/4000] Validation [2/4] Loss: 0.39890 focal_loss 0.28461 dice_loss 0.11429 +Epoch [2639/4000] Validation [3/4] Loss: 0.37671 focal_loss 0.28745 dice_loss 0.08926 +Epoch [2639/4000] Validation [4/4] Loss: 0.39537 focal_loss 0.28538 dice_loss 0.10999 +Epoch [2639/4000] Validation metric {'Val/mean dice_metric': 0.9719792604446411, 'Val/mean miou_metric': 0.9570290446281433, 'Val/mean f1': 0.9753226041793823, 'Val/mean precision': 0.9724766612052917, 'Val/mean recall': 0.9781851172447205, 'Val/mean hd95_metric': 5.433784008026123} +Cheakpoint... +Epoch [2639/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719792604446411, 'Val/mean miou_metric': 0.9570290446281433, 'Val/mean f1': 0.9753226041793823, 'Val/mean precision': 0.9724766612052917, 'Val/mean recall': 0.9781851172447205, 'Val/mean hd95_metric': 5.433784008026123} +Epoch [2640/4000] Training [1/16] Loss: 0.00384 +Epoch [2640/4000] Training [2/16] Loss: 0.00518 +Epoch [2640/4000] Training [3/16] Loss: 0.00393 +Epoch [2640/4000] Training [4/16] Loss: 0.00309 +Epoch [2640/4000] Training [5/16] Loss: 0.00437 +Epoch [2640/4000] Training [6/16] Loss: 0.00318 +Epoch [2640/4000] Training [7/16] Loss: 0.00285 +Epoch [2640/4000] Training [8/16] Loss: 0.00478 +Epoch [2640/4000] Training [9/16] Loss: 0.00474 +Epoch [2640/4000] Training [10/16] Loss: 0.00440 +Epoch [2640/4000] Training [11/16] Loss: 0.00449 +Epoch [2640/4000] Training [12/16] Loss: 0.00364 +Epoch [2640/4000] Training [13/16] Loss: 0.00477 +Epoch [2640/4000] Training [14/16] Loss: 0.00361 +Epoch [2640/4000] Training [15/16] Loss: 0.00430 +Epoch [2640/4000] Training [16/16] Loss: 0.00319 +Epoch [2640/4000] Training metric {'Train/mean dice_metric': 0.9975282549858093, 'Train/mean miou_metric': 0.9947877526283264, 'Train/mean f1': 0.9926842451095581, 'Train/mean precision': 0.987984836101532, 'Train/mean recall': 0.9974285960197449, 'Train/mean hd95_metric': 0.9259037375450134} +Epoch [2640/4000] Validation [1/4] Loss: 0.37812 focal_loss 0.31375 dice_loss 0.06437 +Epoch [2640/4000] Validation [2/4] Loss: 0.73124 focal_loss 0.53431 dice_loss 0.19693 +Epoch [2640/4000] Validation [3/4] Loss: 0.47746 focal_loss 0.37611 dice_loss 0.10135 +Epoch [2640/4000] Validation [4/4] Loss: 0.29391 focal_loss 0.19557 dice_loss 0.09834 +Epoch [2640/4000] Validation metric {'Val/mean dice_metric': 0.9739206433296204, 'Val/mean miou_metric': 0.9586321711540222, 'Val/mean f1': 0.9753446578979492, 'Val/mean precision': 0.9726592898368835, 'Val/mean recall': 0.9780450463294983, 'Val/mean hd95_metric': 5.3400678634643555} +Cheakpoint... +Epoch [2640/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739206433296204, 'Val/mean miou_metric': 0.9586321711540222, 'Val/mean f1': 0.9753446578979492, 'Val/mean precision': 0.9726592898368835, 'Val/mean recall': 0.9780450463294983, 'Val/mean hd95_metric': 5.3400678634643555} +Epoch [2641/4000] Training [1/16] Loss: 0.00460 +Epoch [2641/4000] Training [2/16] Loss: 0.00390 +Epoch [2641/4000] Training [3/16] Loss: 0.00332 +Epoch [2641/4000] Training [4/16] Loss: 0.00286 +Epoch [2641/4000] Training [5/16] Loss: 0.00436 +Epoch [2641/4000] Training [6/16] Loss: 0.00357 +Epoch [2641/4000] Training [7/16] Loss: 0.00347 +Epoch [2641/4000] Training [8/16] Loss: 0.00319 +Epoch [2641/4000] Training [9/16] Loss: 0.00290 +Epoch [2641/4000] Training [10/16] Loss: 0.00293 +Epoch [2641/4000] Training [11/16] Loss: 0.00499 +Epoch [2641/4000] Training [12/16] Loss: 0.00237 +Epoch [2641/4000] Training [13/16] Loss: 0.00344 +Epoch [2641/4000] Training [14/16] Loss: 0.00312 +Epoch [2641/4000] Training [15/16] Loss: 0.00362 +Epoch [2641/4000] Training [16/16] Loss: 0.00433 +Epoch [2641/4000] Training metric {'Train/mean dice_metric': 0.9977927803993225, 'Train/mean miou_metric': 0.9953193068504333, 'Train/mean f1': 0.9929777979850769, 'Train/mean precision': 0.9883588552474976, 'Train/mean recall': 0.9976401329040527, 'Train/mean hd95_metric': 0.8884066343307495} +Epoch [2641/4000] Validation [1/4] Loss: 0.33580 focal_loss 0.26951 dice_loss 0.06630 +Epoch [2641/4000] Validation [2/4] Loss: 0.63226 focal_loss 0.43870 dice_loss 0.19355 +Epoch [2641/4000] Validation [3/4] Loss: 0.49328 focal_loss 0.39125 dice_loss 0.10203 +Epoch [2641/4000] Validation [4/4] Loss: 0.30215 focal_loss 0.21699 dice_loss 0.08515 +Epoch [2641/4000] Validation metric {'Val/mean dice_metric': 0.9737974405288696, 'Val/mean miou_metric': 0.9587377309799194, 'Val/mean f1': 0.9745469689369202, 'Val/mean precision': 0.9718284010887146, 'Val/mean recall': 0.977280855178833, 'Val/mean hd95_metric': 5.407927513122559} +Cheakpoint... +Epoch [2641/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737974405288696, 'Val/mean miou_metric': 0.9587377309799194, 'Val/mean f1': 0.9745469689369202, 'Val/mean precision': 0.9718284010887146, 'Val/mean recall': 0.977280855178833, 'Val/mean hd95_metric': 5.407927513122559} +Epoch [2642/4000] Training [1/16] Loss: 0.00436 +Epoch [2642/4000] Training [2/16] Loss: 0.00277 +Epoch [2642/4000] Training [3/16] Loss: 0.00422 +Epoch [2642/4000] Training [4/16] Loss: 0.00362 +Epoch [2642/4000] Training [5/16] Loss: 0.00568 +Epoch [2642/4000] Training [6/16] Loss: 0.00382 +Epoch [2642/4000] Training [7/16] Loss: 0.00537 +Epoch [2642/4000] Training [8/16] Loss: 0.00278 +Epoch [2642/4000] Training [9/16] Loss: 0.00247 +Epoch [2642/4000] Training [10/16] Loss: 0.00442 +Epoch [2642/4000] Training [11/16] Loss: 0.00541 +Epoch [2642/4000] Training [12/16] Loss: 0.00526 +Epoch [2642/4000] Training [13/16] Loss: 0.00448 +Epoch [2642/4000] Training [14/16] Loss: 0.00314 +Epoch [2642/4000] Training [15/16] Loss: 0.00375 +Epoch [2642/4000] Training [16/16] Loss: 0.00418 +Epoch [2642/4000] Training metric {'Train/mean dice_metric': 0.9974349737167358, 'Train/mean miou_metric': 0.9946169853210449, 'Train/mean f1': 0.992851972579956, 'Train/mean precision': 0.9882635474205017, 'Train/mean recall': 0.9974831938743591, 'Train/mean hd95_metric': 0.9336491823196411} +Epoch [2642/4000] Validation [1/4] Loss: 0.31753 focal_loss 0.25297 dice_loss 0.06456 +Epoch [2642/4000] Validation [2/4] Loss: 0.81602 focal_loss 0.62587 dice_loss 0.19015 +Epoch [2642/4000] Validation [3/4] Loss: 0.43543 focal_loss 0.33784 dice_loss 0.09759 +Epoch [2642/4000] Validation [4/4] Loss: 0.30335 focal_loss 0.21389 dice_loss 0.08947 +Epoch [2642/4000] Validation metric {'Val/mean dice_metric': 0.9723283052444458, 'Val/mean miou_metric': 0.9578874707221985, 'Val/mean f1': 0.9757953882217407, 'Val/mean precision': 0.9740058183670044, 'Val/mean recall': 0.9775914549827576, 'Val/mean hd95_metric': 5.880885601043701} +Cheakpoint... +Epoch [2642/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723283052444458, 'Val/mean miou_metric': 0.9578874707221985, 'Val/mean f1': 0.9757953882217407, 'Val/mean precision': 0.9740058183670044, 'Val/mean recall': 0.9775914549827576, 'Val/mean hd95_metric': 5.880885601043701} +Epoch [2643/4000] Training [1/16] Loss: 0.00550 +Epoch [2643/4000] Training [2/16] Loss: 0.00385 +Epoch [2643/4000] Training [3/16] Loss: 0.00310 +Epoch [2643/4000] Training [4/16] Loss: 0.00288 +Epoch [2643/4000] Training [5/16] Loss: 0.00287 +Epoch [2643/4000] Training [6/16] Loss: 0.00275 +Epoch [2643/4000] Training [7/16] Loss: 0.00439 +Epoch [2643/4000] Training [8/16] Loss: 0.00493 +Epoch [2643/4000] Training [9/16] Loss: 0.00428 +Epoch [2643/4000] Training [10/16] Loss: 0.00487 +Epoch [2643/4000] Training [11/16] Loss: 0.00340 +Epoch [2643/4000] Training [12/16] Loss: 0.00275 +Epoch [2643/4000] Training [13/16] Loss: 0.00386 +Epoch [2643/4000] Training [14/16] Loss: 0.00466 +Epoch [2643/4000] Training [15/16] Loss: 0.00382 +Epoch [2643/4000] Training [16/16] Loss: 0.00392 +Epoch [2643/4000] Training metric {'Train/mean dice_metric': 0.9975197911262512, 'Train/mean miou_metric': 0.9947759509086609, 'Train/mean f1': 0.9928545355796814, 'Train/mean precision': 0.9883241057395935, 'Train/mean recall': 0.9974268674850464, 'Train/mean hd95_metric': 0.9081465601921082} +Epoch [2643/4000] Validation [1/4] Loss: 0.36239 focal_loss 0.29647 dice_loss 0.06592 +Epoch [2643/4000] Validation [2/4] Loss: 0.38491 focal_loss 0.26899 dice_loss 0.11593 +Epoch [2643/4000] Validation [3/4] Loss: 0.23382 focal_loss 0.16685 dice_loss 0.06697 +Epoch [2643/4000] Validation [4/4] Loss: 0.35857 focal_loss 0.25207 dice_loss 0.10651 +Epoch [2643/4000] Validation metric {'Val/mean dice_metric': 0.9733175039291382, 'Val/mean miou_metric': 0.9585837125778198, 'Val/mean f1': 0.9762024879455566, 'Val/mean precision': 0.9738687872886658, 'Val/mean recall': 0.9785474538803101, 'Val/mean hd95_metric': 5.011641502380371} +Cheakpoint... +Epoch [2643/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733175039291382, 'Val/mean miou_metric': 0.9585837125778198, 'Val/mean f1': 0.9762024879455566, 'Val/mean precision': 0.9738687872886658, 'Val/mean recall': 0.9785474538803101, 'Val/mean hd95_metric': 5.011641502380371} +Epoch [2644/4000] Training [1/16] Loss: 0.00343 +Epoch [2644/4000] Training [2/16] Loss: 0.00331 +Epoch [2644/4000] Training [3/16] Loss: 0.00434 +Epoch [2644/4000] Training [4/16] Loss: 0.00351 +Epoch [2644/4000] Training [5/16] Loss: 0.00530 +Epoch [2644/4000] Training [6/16] Loss: 0.00352 +Epoch [2644/4000] Training [7/16] Loss: 0.00296 +Epoch [2644/4000] Training [8/16] Loss: 0.00424 +Epoch [2644/4000] Training [9/16] Loss: 0.00367 +Epoch [2644/4000] Training [10/16] Loss: 0.00396 +Epoch [2644/4000] Training [11/16] Loss: 0.00491 +Epoch [2644/4000] Training [12/16] Loss: 0.00396 +Epoch [2644/4000] Training [13/16] Loss: 0.00466 +Epoch [2644/4000] Training [14/16] Loss: 0.00444 +Epoch [2644/4000] Training [15/16] Loss: 0.00513 +Epoch [2644/4000] Training [16/16] Loss: 0.00321 +Epoch [2644/4000] Training metric {'Train/mean dice_metric': 0.9976311922073364, 'Train/mean miou_metric': 0.9949922561645508, 'Train/mean f1': 0.9928414225578308, 'Train/mean precision': 0.9881616830825806, 'Train/mean recall': 0.997565746307373, 'Train/mean hd95_metric': 0.9160710573196411} +Epoch [2644/4000] Validation [1/4] Loss: 0.30084 focal_loss 0.23847 dice_loss 0.06236 +Epoch [2644/4000] Validation [2/4] Loss: 0.39635 focal_loss 0.28055 dice_loss 0.11580 +Epoch [2644/4000] Validation [3/4] Loss: 0.39743 focal_loss 0.30718 dice_loss 0.09025 +Epoch [2644/4000] Validation [4/4] Loss: 0.32764 focal_loss 0.21394 dice_loss 0.11370 +Epoch [2644/4000] Validation metric {'Val/mean dice_metric': 0.9742735028266907, 'Val/mean miou_metric': 0.9592853784561157, 'Val/mean f1': 0.9759564399719238, 'Val/mean precision': 0.9737775325775146, 'Val/mean recall': 0.9781451225280762, 'Val/mean hd95_metric': 5.167773723602295} +Cheakpoint... +Epoch [2644/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742735028266907, 'Val/mean miou_metric': 0.9592853784561157, 'Val/mean f1': 0.9759564399719238, 'Val/mean precision': 0.9737775325775146, 'Val/mean recall': 0.9781451225280762, 'Val/mean hd95_metric': 5.167773723602295} +Epoch [2645/4000] Training [1/16] Loss: 0.00523 +Epoch [2645/4000] Training [2/16] Loss: 0.00299 +Epoch [2645/4000] Training [3/16] Loss: 0.00397 +Epoch [2645/4000] Training [4/16] Loss: 0.00337 +Epoch [2645/4000] Training [5/16] Loss: 0.00386 +Epoch [2645/4000] Training [6/16] Loss: 0.00399 +Epoch [2645/4000] Training [7/16] Loss: 0.00283 +Epoch [2645/4000] Training [8/16] Loss: 0.00378 +Epoch [2645/4000] Training [9/16] Loss: 0.00498 +Epoch [2645/4000] Training [10/16] Loss: 0.00474 +Epoch [2645/4000] Training [11/16] Loss: 0.00393 +Epoch [2645/4000] Training [12/16] Loss: 0.00351 +Epoch [2645/4000] Training [13/16] Loss: 0.00512 +Epoch [2645/4000] Training [14/16] Loss: 0.00395 +Epoch [2645/4000] Training [15/16] Loss: 0.00556 +Epoch [2645/4000] Training [16/16] Loss: 0.00413 +Epoch [2645/4000] Training metric {'Train/mean dice_metric': 0.9973785877227783, 'Train/mean miou_metric': 0.9945120811462402, 'Train/mean f1': 0.9928736686706543, 'Train/mean precision': 0.98839271068573, 'Train/mean recall': 0.9973954558372498, 'Train/mean hd95_metric': 0.9623905420303345} +Epoch [2645/4000] Validation [1/4] Loss: 0.30124 focal_loss 0.24128 dice_loss 0.05996 +Epoch [2645/4000] Validation [2/4] Loss: 0.38486 focal_loss 0.27280 dice_loss 0.11205 +Epoch [2645/4000] Validation [3/4] Loss: 0.44378 focal_loss 0.35172 dice_loss 0.09207 +Epoch [2645/4000] Validation [4/4] Loss: 0.48809 focal_loss 0.34866 dice_loss 0.13943 +Epoch [2645/4000] Validation metric {'Val/mean dice_metric': 0.9734228253364563, 'Val/mean miou_metric': 0.9586437344551086, 'Val/mean f1': 0.9765323400497437, 'Val/mean precision': 0.9732567667961121, 'Val/mean recall': 0.9798299074172974, 'Val/mean hd95_metric': 5.131755352020264} +Cheakpoint... +Epoch [2645/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734228253364563, 'Val/mean miou_metric': 0.9586437344551086, 'Val/mean f1': 0.9765323400497437, 'Val/mean precision': 0.9732567667961121, 'Val/mean recall': 0.9798299074172974, 'Val/mean hd95_metric': 5.131755352020264} +Epoch [2646/4000] Training [1/16] Loss: 0.00361 +Epoch [2646/4000] Training [2/16] Loss: 0.00440 +Epoch [2646/4000] Training [3/16] Loss: 0.00336 +Epoch [2646/4000] Training [4/16] Loss: 0.00325 +Epoch [2646/4000] Training [5/16] Loss: 0.00390 +Epoch [2646/4000] Training [6/16] Loss: 0.00271 +Epoch [2646/4000] Training [7/16] Loss: 0.00283 +Epoch [2646/4000] Training [8/16] Loss: 0.00508 +Epoch [2646/4000] Training [9/16] Loss: 0.00425 +Epoch [2646/4000] Training [10/16] Loss: 0.00500 +Epoch [2646/4000] Training [11/16] Loss: 0.00354 +Epoch [2646/4000] Training [12/16] Loss: 0.00302 +Epoch [2646/4000] Training [13/16] Loss: 0.00425 +Epoch [2646/4000] Training [14/16] Loss: 0.00493 +Epoch [2646/4000] Training [15/16] Loss: 0.00325 +Epoch [2646/4000] Training [16/16] Loss: 0.00380 +Epoch [2646/4000] Training metric {'Train/mean dice_metric': 0.9976050853729248, 'Train/mean miou_metric': 0.994949221611023, 'Train/mean f1': 0.9929430484771729, 'Train/mean precision': 0.9883959889411926, 'Train/mean recall': 0.997532069683075, 'Train/mean hd95_metric': 0.936816930770874} +Epoch [2646/4000] Validation [1/4] Loss: 0.33306 focal_loss 0.27088 dice_loss 0.06218 +Epoch [2646/4000] Validation [2/4] Loss: 0.65464 focal_loss 0.49432 dice_loss 0.16033 +Epoch [2646/4000] Validation [3/4] Loss: 0.43773 focal_loss 0.34041 dice_loss 0.09732 +Epoch [2646/4000] Validation [4/4] Loss: 0.23643 focal_loss 0.15811 dice_loss 0.07831 +Epoch [2646/4000] Validation metric {'Val/mean dice_metric': 0.9728072881698608, 'Val/mean miou_metric': 0.9581203460693359, 'Val/mean f1': 0.9755480289459229, 'Val/mean precision': 0.9726313352584839, 'Val/mean recall': 0.9784823060035706, 'Val/mean hd95_metric': 5.120729446411133} +Cheakpoint... +Epoch [2646/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728072881698608, 'Val/mean miou_metric': 0.9581203460693359, 'Val/mean f1': 0.9755480289459229, 'Val/mean precision': 0.9726313352584839, 'Val/mean recall': 0.9784823060035706, 'Val/mean hd95_metric': 5.120729446411133} +Epoch [2647/4000] Training [1/16] Loss: 0.00428 +Epoch [2647/4000] Training [2/16] Loss: 0.00364 +Epoch [2647/4000] Training [3/16] Loss: 0.00391 +Epoch [2647/4000] Training [4/16] Loss: 0.00263 +Epoch [2647/4000] Training [5/16] Loss: 0.00586 +Epoch [2647/4000] Training [6/16] Loss: 0.00396 +Epoch [2647/4000] Training [7/16] Loss: 0.00375 +Epoch [2647/4000] Training [8/16] Loss: 0.00408 +Epoch [2647/4000] Training [9/16] Loss: 0.00434 +Epoch [2647/4000] Training [10/16] Loss: 0.00292 +Epoch [2647/4000] Training [11/16] Loss: 0.00404 +Epoch [2647/4000] Training [12/16] Loss: 0.00301 +Epoch [2647/4000] Training [13/16] Loss: 0.00302 +Epoch [2647/4000] Training [14/16] Loss: 0.00343 +Epoch [2647/4000] Training [15/16] Loss: 0.00368 +Epoch [2647/4000] Training [16/16] Loss: 0.00321 +Epoch [2647/4000] Training metric {'Train/mean dice_metric': 0.9977835416793823, 'Train/mean miou_metric': 0.9953036308288574, 'Train/mean f1': 0.9930335879325867, 'Train/mean precision': 0.9885455965995789, 'Train/mean recall': 0.9975625872612, 'Train/mean hd95_metric': 0.9106721878051758} +Epoch [2647/4000] Validation [1/4] Loss: 0.35932 focal_loss 0.29569 dice_loss 0.06363 +Epoch [2647/4000] Validation [2/4] Loss: 1.23831 focal_loss 0.99778 dice_loss 0.24053 +Epoch [2647/4000] Validation [3/4] Loss: 0.46419 focal_loss 0.36904 dice_loss 0.09515 +Epoch [2647/4000] Validation [4/4] Loss: 0.33304 focal_loss 0.22564 dice_loss 0.10740 +Epoch [2647/4000] Validation metric {'Val/mean dice_metric': 0.973858654499054, 'Val/mean miou_metric': 0.9587059020996094, 'Val/mean f1': 0.9757850170135498, 'Val/mean precision': 0.9735163450241089, 'Val/mean recall': 0.9780643582344055, 'Val/mean hd95_metric': 5.079688549041748} +Cheakpoint... +Epoch [2647/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973858654499054, 'Val/mean miou_metric': 0.9587059020996094, 'Val/mean f1': 0.9757850170135498, 'Val/mean precision': 0.9735163450241089, 'Val/mean recall': 0.9780643582344055, 'Val/mean hd95_metric': 5.079688549041748} +Epoch [2648/4000] Training [1/16] Loss: 0.00297 +Epoch [2648/4000] Training [2/16] Loss: 0.00452 +Epoch [2648/4000] Training [3/16] Loss: 0.00511 +Epoch [2648/4000] Training [4/16] Loss: 0.00338 +Epoch [2648/4000] Training [5/16] Loss: 0.00381 +Epoch [2648/4000] Training [6/16] Loss: 0.00502 +Epoch [2648/4000] Training [7/16] Loss: 0.00451 +Epoch [2648/4000] Training [8/16] Loss: 0.00284 +Epoch [2648/4000] Training [9/16] Loss: 0.00444 +Epoch [2648/4000] Training [10/16] Loss: 0.00389 +Epoch [2648/4000] Training [11/16] Loss: 0.00301 +Epoch [2648/4000] Training [12/16] Loss: 0.00393 +Epoch [2648/4000] Training [13/16] Loss: 0.00389 +Epoch [2648/4000] Training [14/16] Loss: 0.00409 +Epoch [2648/4000] Training [15/16] Loss: 0.00417 +Epoch [2648/4000] Training [16/16] Loss: 0.00327 +Epoch [2648/4000] Training metric {'Train/mean dice_metric': 0.9975484609603882, 'Train/mean miou_metric': 0.9948302507400513, 'Train/mean f1': 0.992872953414917, 'Train/mean precision': 0.9883394837379456, 'Train/mean recall': 0.9974481463432312, 'Train/mean hd95_metric': 0.9163362979888916} +Epoch [2648/4000] Validation [1/4] Loss: 0.35416 focal_loss 0.28785 dice_loss 0.06631 +Epoch [2648/4000] Validation [2/4] Loss: 0.62158 focal_loss 0.46269 dice_loss 0.15890 +Epoch [2648/4000] Validation [3/4] Loss: 0.45494 focal_loss 0.35514 dice_loss 0.09981 +Epoch [2648/4000] Validation [4/4] Loss: 0.34531 focal_loss 0.23366 dice_loss 0.11165 +Epoch [2648/4000] Validation metric {'Val/mean dice_metric': 0.9720269441604614, 'Val/mean miou_metric': 0.9571592211723328, 'Val/mean f1': 0.9759555459022522, 'Val/mean precision': 0.9735012054443359, 'Val/mean recall': 0.9784222841262817, 'Val/mean hd95_metric': 4.967907428741455} +Cheakpoint... +Epoch [2648/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720269441604614, 'Val/mean miou_metric': 0.9571592211723328, 'Val/mean f1': 0.9759555459022522, 'Val/mean precision': 0.9735012054443359, 'Val/mean recall': 0.9784222841262817, 'Val/mean hd95_metric': 4.967907428741455} +Epoch [2649/4000] Training [1/16] Loss: 0.00357 +Epoch [2649/4000] Training [2/16] Loss: 0.00455 +Epoch [2649/4000] Training [3/16] Loss: 0.00315 +Epoch [2649/4000] Training [4/16] Loss: 0.00375 +Epoch [2649/4000] Training [5/16] Loss: 0.00412 +Epoch [2649/4000] Training [6/16] Loss: 0.00548 +Epoch [2649/4000] Training [7/16] Loss: 0.00380 +Epoch [2649/4000] Training [8/16] Loss: 0.00636 +Epoch [2649/4000] Training [9/16] Loss: 0.00396 +Epoch [2649/4000] Training [10/16] Loss: 0.00382 +Epoch [2649/4000] Training [11/16] Loss: 0.00545 +Epoch [2649/4000] Training [12/16] Loss: 0.00532 +Epoch [2649/4000] Training [13/16] Loss: 0.00402 +Epoch [2649/4000] Training [14/16] Loss: 0.00370 +Epoch [2649/4000] Training [15/16] Loss: 0.00364 +Epoch [2649/4000] Training [16/16] Loss: 0.00704 +Epoch [2649/4000] Training metric {'Train/mean dice_metric': 0.9972655773162842, 'Train/mean miou_metric': 0.9942598938941956, 'Train/mean f1': 0.9924256205558777, 'Train/mean precision': 0.9876059293746948, 'Train/mean recall': 0.9972928166389465, 'Train/mean hd95_metric': 0.925361692905426} +Epoch [2649/4000] Validation [1/4] Loss: 0.31886 focal_loss 0.25757 dice_loss 0.06129 +Epoch [2649/4000] Validation [2/4] Loss: 0.90015 focal_loss 0.70373 dice_loss 0.19643 +Epoch [2649/4000] Validation [3/4] Loss: 0.42218 focal_loss 0.33184 dice_loss 0.09034 +Epoch [2649/4000] Validation [4/4] Loss: 0.27077 focal_loss 0.17528 dice_loss 0.09549 +Epoch [2649/4000] Validation metric {'Val/mean dice_metric': 0.9736646413803101, 'Val/mean miou_metric': 0.9591989517211914, 'Val/mean f1': 0.976429283618927, 'Val/mean precision': 0.9724888205528259, 'Val/mean recall': 0.9804018139839172, 'Val/mean hd95_metric': 5.030032634735107} +Cheakpoint... +Epoch [2649/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736646413803101, 'Val/mean miou_metric': 0.9591989517211914, 'Val/mean f1': 0.976429283618927, 'Val/mean precision': 0.9724888205528259, 'Val/mean recall': 0.9804018139839172, 'Val/mean hd95_metric': 5.030032634735107} +Epoch [2650/4000] Training [1/16] Loss: 0.00302 +Epoch [2650/4000] Training [2/16] Loss: 0.00402 +Epoch [2650/4000] Training [3/16] Loss: 0.00368 +Epoch [2650/4000] Training [4/16] Loss: 0.00449 +Epoch [2650/4000] Training [5/16] Loss: 0.00473 +Epoch [2650/4000] Training [6/16] Loss: 0.00757 +Epoch [2650/4000] Training [7/16] Loss: 0.00479 +Epoch [2650/4000] Training [8/16] Loss: 0.00350 +Epoch [2650/4000] Training [9/16] Loss: 0.00389 +Epoch [2650/4000] Training [10/16] Loss: 0.00429 +Epoch [2650/4000] Training [11/16] Loss: 0.00359 +Epoch [2650/4000] Training [12/16] Loss: 0.00363 +Epoch [2650/4000] Training [13/16] Loss: 0.00354 +Epoch [2650/4000] Training [14/16] Loss: 0.00409 +Epoch [2650/4000] Training [15/16] Loss: 0.00395 +Epoch [2650/4000] Training [16/16] Loss: 0.00445 +Epoch [2650/4000] Training metric {'Train/mean dice_metric': 0.9973410367965698, 'Train/mean miou_metric': 0.9944319725036621, 'Train/mean f1': 0.9927915334701538, 'Train/mean precision': 0.9882931113243103, 'Train/mean recall': 0.9973310828208923, 'Train/mean hd95_metric': 0.9666600227355957} +Epoch [2650/4000] Validation [1/4] Loss: 0.40872 focal_loss 0.34133 dice_loss 0.06739 +Epoch [2650/4000] Validation [2/4] Loss: 0.83196 focal_loss 0.64300 dice_loss 0.18897 +Epoch [2650/4000] Validation [3/4] Loss: 0.41308 focal_loss 0.31632 dice_loss 0.09676 +Epoch [2650/4000] Validation [4/4] Loss: 0.31067 focal_loss 0.21122 dice_loss 0.09944 +Epoch [2650/4000] Validation metric {'Val/mean dice_metric': 0.9730765223503113, 'Val/mean miou_metric': 0.9580146670341492, 'Val/mean f1': 0.9757486581802368, 'Val/mean precision': 0.9731282591819763, 'Val/mean recall': 0.9783831834793091, 'Val/mean hd95_metric': 5.3883280754089355} +Cheakpoint... +Epoch [2650/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730765223503113, 'Val/mean miou_metric': 0.9580146670341492, 'Val/mean f1': 0.9757486581802368, 'Val/mean precision': 0.9731282591819763, 'Val/mean recall': 0.9783831834793091, 'Val/mean hd95_metric': 5.3883280754089355} +Epoch [2651/4000] Training [1/16] Loss: 0.00437 +Epoch [2651/4000] Training [2/16] Loss: 0.00366 +Epoch [2651/4000] Training [3/16] Loss: 0.00356 +Epoch [2651/4000] Training [4/16] Loss: 0.00309 +Epoch [2651/4000] Training [5/16] Loss: 0.00412 +Epoch [2651/4000] Training [6/16] Loss: 0.00492 +Epoch [2651/4000] Training [7/16] Loss: 0.00321 +Epoch [2651/4000] Training [8/16] Loss: 0.00554 +Epoch [2651/4000] Training [9/16] Loss: 0.00445 +Epoch [2651/4000] Training [10/16] Loss: 0.00540 +Epoch [2651/4000] Training [11/16] Loss: 0.00357 +Epoch [2651/4000] Training [12/16] Loss: 0.00356 +Epoch [2651/4000] Training [13/16] Loss: 0.00364 +Epoch [2651/4000] Training [14/16] Loss: 0.00313 +Epoch [2651/4000] Training [15/16] Loss: 0.00324 +Epoch [2651/4000] Training [16/16] Loss: 0.00357 +Epoch [2651/4000] Training metric {'Train/mean dice_metric': 0.9975869655609131, 'Train/mean miou_metric': 0.9949103593826294, 'Train/mean f1': 0.992884635925293, 'Train/mean precision': 0.9883385896682739, 'Train/mean recall': 0.9974727034568787, 'Train/mean hd95_metric': 0.9338167905807495} +Epoch [2651/4000] Validation [1/4] Loss: 0.33421 focal_loss 0.27032 dice_loss 0.06389 +Epoch [2651/4000] Validation [2/4] Loss: 0.34173 focal_loss 0.23620 dice_loss 0.10554 +Epoch [2651/4000] Validation [3/4] Loss: 0.38903 focal_loss 0.29069 dice_loss 0.09835 +Epoch [2651/4000] Validation [4/4] Loss: 0.29338 focal_loss 0.19213 dice_loss 0.10125 +Epoch [2651/4000] Validation metric {'Val/mean dice_metric': 0.9734334945678711, 'Val/mean miou_metric': 0.9588702321052551, 'Val/mean f1': 0.9766415357589722, 'Val/mean precision': 0.9739528298377991, 'Val/mean recall': 0.9793452620506287, 'Val/mean hd95_metric': 5.1772236824035645} +Cheakpoint... +Epoch [2651/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734334945678711, 'Val/mean miou_metric': 0.9588702321052551, 'Val/mean f1': 0.9766415357589722, 'Val/mean precision': 0.9739528298377991, 'Val/mean recall': 0.9793452620506287, 'Val/mean hd95_metric': 5.1772236824035645} +Epoch [2652/4000] Training [1/16] Loss: 0.00366 +Epoch [2652/4000] Training [2/16] Loss: 0.00387 +Epoch [2652/4000] Training [3/16] Loss: 0.00264 +Epoch [2652/4000] Training [4/16] Loss: 0.00360 +Epoch [2652/4000] Training [5/16] Loss: 0.00338 +Epoch [2652/4000] Training [6/16] Loss: 0.00384 +Epoch [2652/4000] Training [7/16] Loss: 0.00362 +Epoch [2652/4000] Training [8/16] Loss: 0.00492 +Epoch [2652/4000] Training [9/16] Loss: 0.00435 +Epoch [2652/4000] Training [10/16] Loss: 0.00460 +Epoch [2652/4000] Training [11/16] Loss: 0.00550 +Epoch [2652/4000] Training [12/16] Loss: 0.00515 +Epoch [2652/4000] Training [13/16] Loss: 0.00429 +Epoch [2652/4000] Training [14/16] Loss: 0.00374 +Epoch [2652/4000] Training [15/16] Loss: 0.00475 +Epoch [2652/4000] Training [16/16] Loss: 0.00380 +Epoch [2652/4000] Training metric {'Train/mean dice_metric': 0.9974983930587769, 'Train/mean miou_metric': 0.9947372674942017, 'Train/mean f1': 0.9928170442581177, 'Train/mean precision': 0.9882643222808838, 'Train/mean recall': 0.9974119067192078, 'Train/mean hd95_metric': 0.9279879927635193} +Epoch [2652/4000] Validation [1/4] Loss: 0.34949 focal_loss 0.28377 dice_loss 0.06572 +Epoch [2652/4000] Validation [2/4] Loss: 0.55396 focal_loss 0.38876 dice_loss 0.16520 +Epoch [2652/4000] Validation [3/4] Loss: 0.44351 focal_loss 0.33463 dice_loss 0.10888 +Epoch [2652/4000] Validation [4/4] Loss: 0.30722 focal_loss 0.20828 dice_loss 0.09895 +Epoch [2652/4000] Validation metric {'Val/mean dice_metric': 0.9714905023574829, 'Val/mean miou_metric': 0.95665043592453, 'Val/mean f1': 0.9753679037094116, 'Val/mean precision': 0.9730204343795776, 'Val/mean recall': 0.9777266383171082, 'Val/mean hd95_metric': 5.462615966796875} +Cheakpoint... +Epoch [2652/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714905023574829, 'Val/mean miou_metric': 0.95665043592453, 'Val/mean f1': 0.9753679037094116, 'Val/mean precision': 0.9730204343795776, 'Val/mean recall': 0.9777266383171082, 'Val/mean hd95_metric': 5.462615966796875} +Epoch [2653/4000] Training [1/16] Loss: 0.00570 +Epoch [2653/4000] Training [2/16] Loss: 0.00268 +Epoch [2653/4000] Training [3/16] Loss: 0.00375 +Epoch [2653/4000] Training [4/16] Loss: 0.00413 +Epoch [2653/4000] Training [5/16] Loss: 0.00378 +Epoch [2653/4000] Training [6/16] Loss: 0.00398 +Epoch [2653/4000] Training [7/16] Loss: 0.00408 +Epoch [2653/4000] Training [8/16] Loss: 0.00599 +Epoch [2653/4000] Training [9/16] Loss: 0.00427 +Epoch [2653/4000] Training [10/16] Loss: 0.00403 +Epoch [2653/4000] Training [11/16] Loss: 0.00416 +Epoch [2653/4000] Training [12/16] Loss: 0.00524 +Epoch [2653/4000] Training [13/16] Loss: 0.00297 +Epoch [2653/4000] Training [14/16] Loss: 0.00426 +Epoch [2653/4000] Training [15/16] Loss: 0.00432 +Epoch [2653/4000] Training [16/16] Loss: 0.00394 +Epoch [2653/4000] Training metric {'Train/mean dice_metric': 0.9974875450134277, 'Train/mean miou_metric': 0.9946850538253784, 'Train/mean f1': 0.9920263290405273, 'Train/mean precision': 0.9867680072784424, 'Train/mean recall': 0.9973410367965698, 'Train/mean hd95_metric': 0.9188331961631775} +Epoch [2653/4000] Validation [1/4] Loss: 0.34254 focal_loss 0.27923 dice_loss 0.06331 +Epoch [2653/4000] Validation [2/4] Loss: 1.22806 focal_loss 0.99506 dice_loss 0.23300 +Epoch [2653/4000] Validation [3/4] Loss: 0.41045 focal_loss 0.31074 dice_loss 0.09971 +Epoch [2653/4000] Validation [4/4] Loss: 0.34786 focal_loss 0.23886 dice_loss 0.10899 +Epoch [2653/4000] Validation metric {'Val/mean dice_metric': 0.9720240831375122, 'Val/mean miou_metric': 0.9571245312690735, 'Val/mean f1': 0.9744261503219604, 'Val/mean precision': 0.9720003008842468, 'Val/mean recall': 0.9768641591072083, 'Val/mean hd95_metric': 5.346896648406982} +Cheakpoint... +Epoch [2653/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720240831375122, 'Val/mean miou_metric': 0.9571245312690735, 'Val/mean f1': 0.9744261503219604, 'Val/mean precision': 0.9720003008842468, 'Val/mean recall': 0.9768641591072083, 'Val/mean hd95_metric': 5.346896648406982} +Epoch [2654/4000] Training [1/16] Loss: 0.00457 +Epoch [2654/4000] Training [2/16] Loss: 0.00412 +Epoch [2654/4000] Training [3/16] Loss: 0.00327 +Epoch [2654/4000] Training [4/16] Loss: 0.00298 +Epoch [2654/4000] Training [5/16] Loss: 0.00425 +Epoch [2654/4000] Training [6/16] Loss: 0.00483 +Epoch [2654/4000] Training [7/16] Loss: 0.00375 +Epoch [2654/4000] Training [8/16] Loss: 0.00380 +Epoch [2654/4000] Training [9/16] Loss: 0.00392 +Epoch [2654/4000] Training [10/16] Loss: 0.00481 +Epoch [2654/4000] Training [11/16] Loss: 0.00432 +Epoch [2654/4000] Training [12/16] Loss: 0.00326 +Epoch [2654/4000] Training [13/16] Loss: 0.00364 +Epoch [2654/4000] Training [14/16] Loss: 0.00335 +Epoch [2654/4000] Training [15/16] Loss: 0.00401 +Epoch [2654/4000] Training [16/16] Loss: 0.00503 +Epoch [2654/4000] Training metric {'Train/mean dice_metric': 0.9975321292877197, 'Train/mean miou_metric': 0.9948014616966248, 'Train/mean f1': 0.9926933646202087, 'Train/mean precision': 0.9880122542381287, 'Train/mean recall': 0.997418999671936, 'Train/mean hd95_metric': 0.9187355041503906} +Epoch [2654/4000] Validation [1/4] Loss: 0.30933 focal_loss 0.24636 dice_loss 0.06297 +Epoch [2654/4000] Validation [2/4] Loss: 0.67600 focal_loss 0.49980 dice_loss 0.17620 +Epoch [2654/4000] Validation [3/4] Loss: 0.45091 focal_loss 0.35173 dice_loss 0.09919 +Epoch [2654/4000] Validation [4/4] Loss: 0.27717 focal_loss 0.18090 dice_loss 0.09628 +Epoch [2654/4000] Validation metric {'Val/mean dice_metric': 0.9712119102478027, 'Val/mean miou_metric': 0.9563179016113281, 'Val/mean f1': 0.9751542806625366, 'Val/mean precision': 0.9735313057899475, 'Val/mean recall': 0.9767827391624451, 'Val/mean hd95_metric': 5.223310947418213} +Cheakpoint... +Epoch [2654/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712119102478027, 'Val/mean miou_metric': 0.9563179016113281, 'Val/mean f1': 0.9751542806625366, 'Val/mean precision': 0.9735313057899475, 'Val/mean recall': 0.9767827391624451, 'Val/mean hd95_metric': 5.223310947418213} +Epoch [2655/4000] Training [1/16] Loss: 0.00488 +Epoch [2655/4000] Training [2/16] Loss: 0.00344 +Epoch [2655/4000] Training [3/16] Loss: 0.00338 +Epoch [2655/4000] Training [4/16] Loss: 0.00380 +Epoch [2655/4000] Training [5/16] Loss: 0.00427 +Epoch [2655/4000] Training [6/16] Loss: 0.00566 +Epoch [2655/4000] Training [7/16] Loss: 0.00476 +Epoch [2655/4000] Training [8/16] Loss: 0.00411 +Epoch [2655/4000] Training [9/16] Loss: 0.00267 +Epoch [2655/4000] Training [10/16] Loss: 0.00465 +Epoch [2655/4000] Training [11/16] Loss: 0.00308 +Epoch [2655/4000] Training [12/16] Loss: 0.00460 +Epoch [2655/4000] Training [13/16] Loss: 0.00533 +Epoch [2655/4000] Training [14/16] Loss: 0.00340 +Epoch [2655/4000] Training [15/16] Loss: 0.00449 +Epoch [2655/4000] Training [16/16] Loss: 0.00318 +Epoch [2655/4000] Training metric {'Train/mean dice_metric': 0.9973512887954712, 'Train/mean miou_metric': 0.9944372773170471, 'Train/mean f1': 0.9925321340560913, 'Train/mean precision': 0.9877433776855469, 'Train/mean recall': 0.9973675608634949, 'Train/mean hd95_metric': 0.9243296384811401} +Epoch [2655/4000] Validation [1/4] Loss: 0.38221 focal_loss 0.31797 dice_loss 0.06424 +Epoch [2655/4000] Validation [2/4] Loss: 0.42480 focal_loss 0.30624 dice_loss 0.11856 +Epoch [2655/4000] Validation [3/4] Loss: 0.43702 focal_loss 0.34257 dice_loss 0.09445 +Epoch [2655/4000] Validation [4/4] Loss: 0.29674 focal_loss 0.19790 dice_loss 0.09884 +Epoch [2655/4000] Validation metric {'Val/mean dice_metric': 0.9740810394287109, 'Val/mean miou_metric': 0.9586527943611145, 'Val/mean f1': 0.975522518157959, 'Val/mean precision': 0.9745641350746155, 'Val/mean recall': 0.9764826893806458, 'Val/mean hd95_metric': 5.027442455291748} +Cheakpoint... +Epoch [2655/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740810394287109, 'Val/mean miou_metric': 0.9586527943611145, 'Val/mean f1': 0.975522518157959, 'Val/mean precision': 0.9745641350746155, 'Val/mean recall': 0.9764826893806458, 'Val/mean hd95_metric': 5.027442455291748} +Epoch [2656/4000] Training [1/16] Loss: 0.00422 +Epoch [2656/4000] Training [2/16] Loss: 0.00528 +Epoch [2656/4000] Training [3/16] Loss: 0.00465 +Epoch [2656/4000] Training [4/16] Loss: 0.00357 +Epoch [2656/4000] Training [5/16] Loss: 0.00422 +Epoch [2656/4000] Training [6/16] Loss: 0.00402 +Epoch [2656/4000] Training [7/16] Loss: 0.00352 +Epoch [2656/4000] Training [8/16] Loss: 0.00405 +Epoch [2656/4000] Training [9/16] Loss: 0.00398 +Epoch [2656/4000] Training [10/16] Loss: 0.00363 +Epoch [2656/4000] Training [11/16] Loss: 0.00440 +Epoch [2656/4000] Training [12/16] Loss: 0.00582 +Epoch [2656/4000] Training [13/16] Loss: 0.00338 +Epoch [2656/4000] Training [14/16] Loss: 0.00426 +Epoch [2656/4000] Training [15/16] Loss: 0.00347 +Epoch [2656/4000] Training [16/16] Loss: 0.00327 +Epoch [2656/4000] Training metric {'Train/mean dice_metric': 0.9974979758262634, 'Train/mean miou_metric': 0.9947423338890076, 'Train/mean f1': 0.992844820022583, 'Train/mean precision': 0.9882758855819702, 'Train/mean recall': 0.9974561929702759, 'Train/mean hd95_metric': 0.9162364602088928} +Epoch [2656/4000] Validation [1/4] Loss: 0.31646 focal_loss 0.25478 dice_loss 0.06168 +Epoch [2656/4000] Validation [2/4] Loss: 0.41726 focal_loss 0.30074 dice_loss 0.11652 +Epoch [2656/4000] Validation [3/4] Loss: 0.33602 focal_loss 0.24640 dice_loss 0.08962 +Epoch [2656/4000] Validation [4/4] Loss: 0.31381 focal_loss 0.22578 dice_loss 0.08803 +Epoch [2656/4000] Validation metric {'Val/mean dice_metric': 0.9728231430053711, 'Val/mean miou_metric': 0.9581249356269836, 'Val/mean f1': 0.9756579995155334, 'Val/mean precision': 0.974515974521637, 'Val/mean recall': 0.9768027663230896, 'Val/mean hd95_metric': 5.2559661865234375} +Cheakpoint... +Epoch [2656/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728231430053711, 'Val/mean miou_metric': 0.9581249356269836, 'Val/mean f1': 0.9756579995155334, 'Val/mean precision': 0.974515974521637, 'Val/mean recall': 0.9768027663230896, 'Val/mean hd95_metric': 5.2559661865234375} +Epoch [2657/4000] Training [1/16] Loss: 0.00432 +Epoch [2657/4000] Training [2/16] Loss: 0.02595 +Epoch [2657/4000] Training [3/16] Loss: 0.00387 +Epoch [2657/4000] Training [4/16] Loss: 0.00359 +Epoch [2657/4000] Training [5/16] Loss: 0.00356 +Epoch [2657/4000] Training [6/16] Loss: 0.00259 +Epoch [2657/4000] Training [7/16] Loss: 0.00402 +Epoch [2657/4000] Training [8/16] Loss: 0.00462 +Epoch [2657/4000] Training [9/16] Loss: 0.00319 +Epoch [2657/4000] Training [10/16] Loss: 0.00422 +Epoch [2657/4000] Training [11/16] Loss: 0.00464 +Epoch [2657/4000] Training [12/16] Loss: 0.00391 +Epoch [2657/4000] Training [13/16] Loss: 0.00448 +Epoch [2657/4000] Training [14/16] Loss: 0.00393 +Epoch [2657/4000] Training [15/16] Loss: 0.00261 +Epoch [2657/4000] Training [16/16] Loss: 0.00428 +Epoch [2657/4000] Training metric {'Train/mean dice_metric': 0.9975345730781555, 'Train/mean miou_metric': 0.9948228001594543, 'Train/mean f1': 0.9927732348442078, 'Train/mean precision': 0.988129198551178, 'Train/mean recall': 0.997461199760437, 'Train/mean hd95_metric': 0.945557713508606} +Epoch [2657/4000] Validation [1/4] Loss: 0.38339 focal_loss 0.31740 dice_loss 0.06599 +Epoch [2657/4000] Validation [2/4] Loss: 0.41846 focal_loss 0.28808 dice_loss 0.13038 +Epoch [2657/4000] Validation [3/4] Loss: 0.26054 focal_loss 0.18518 dice_loss 0.07535 +Epoch [2657/4000] Validation [4/4] Loss: 0.28498 focal_loss 0.19664 dice_loss 0.08834 +Epoch [2657/4000] Validation metric {'Val/mean dice_metric': 0.9725597500801086, 'Val/mean miou_metric': 0.9575898051261902, 'Val/mean f1': 0.9751993417739868, 'Val/mean precision': 0.9747188687324524, 'Val/mean recall': 0.9756803512573242, 'Val/mean hd95_metric': 4.847040176391602} +Cheakpoint... +Epoch [2657/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725597500801086, 'Val/mean miou_metric': 0.9575898051261902, 'Val/mean f1': 0.9751993417739868, 'Val/mean precision': 0.9747188687324524, 'Val/mean recall': 0.9756803512573242, 'Val/mean hd95_metric': 4.847040176391602} +Epoch [2658/4000] Training [1/16] Loss: 0.00299 +Epoch [2658/4000] Training [2/16] Loss: 0.00302 +Epoch [2658/4000] Training [3/16] Loss: 0.00340 +Epoch [2658/4000] Training [4/16] Loss: 0.00319 +Epoch [2658/4000] Training [5/16] Loss: 0.00362 +Epoch [2658/4000] Training [6/16] Loss: 0.00500 +Epoch [2658/4000] Training [7/16] Loss: 0.00492 +Epoch [2658/4000] Training [8/16] Loss: 0.00364 +Epoch [2658/4000] Training [9/16] Loss: 0.00383 +Epoch [2658/4000] Training [10/16] Loss: 0.00491 +Epoch [2658/4000] Training [11/16] Loss: 0.00315 +Epoch [2658/4000] Training [12/16] Loss: 0.00458 +Epoch [2658/4000] Training [13/16] Loss: 0.00348 +Epoch [2658/4000] Training [14/16] Loss: 0.00367 +Epoch [2658/4000] Training [15/16] Loss: 0.00414 +Epoch [2658/4000] Training [16/16] Loss: 0.00399 +Epoch [2658/4000] Training metric {'Train/mean dice_metric': 0.9975981712341309, 'Train/mean miou_metric': 0.9949242472648621, 'Train/mean f1': 0.9928402900695801, 'Train/mean precision': 0.9882527589797974, 'Train/mean recall': 0.9974706172943115, 'Train/mean hd95_metric': 0.8994972109794617} +Epoch [2658/4000] Validation [1/4] Loss: 0.34914 focal_loss 0.28226 dice_loss 0.06688 +Epoch [2658/4000] Validation [2/4] Loss: 0.80442 focal_loss 0.61591 dice_loss 0.18851 +Epoch [2658/4000] Validation [3/4] Loss: 0.22610 focal_loss 0.16770 dice_loss 0.05840 +Epoch [2658/4000] Validation [4/4] Loss: 0.30095 focal_loss 0.20482 dice_loss 0.09613 +Epoch [2658/4000] Validation metric {'Val/mean dice_metric': 0.9724395871162415, 'Val/mean miou_metric': 0.9579446911811829, 'Val/mean f1': 0.9758493304252625, 'Val/mean precision': 0.9757435917854309, 'Val/mean recall': 0.9759552478790283, 'Val/mean hd95_metric': 4.906961441040039} +Cheakpoint... +Epoch [2658/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724395871162415, 'Val/mean miou_metric': 0.9579446911811829, 'Val/mean f1': 0.9758493304252625, 'Val/mean precision': 0.9757435917854309, 'Val/mean recall': 0.9759552478790283, 'Val/mean hd95_metric': 4.906961441040039} +Epoch [2659/4000] Training [1/16] Loss: 0.00434 +Epoch [2659/4000] Training [2/16] Loss: 0.00439 +Epoch [2659/4000] Training [3/16] Loss: 0.00367 +Epoch [2659/4000] Training [4/16] Loss: 0.00364 +Epoch [2659/4000] Training [5/16] Loss: 0.00342 +Epoch [2659/4000] Training [6/16] Loss: 0.00499 +Epoch [2659/4000] Training [7/16] Loss: 0.00325 +Epoch [2659/4000] Training [8/16] Loss: 0.00388 +Epoch [2659/4000] Training [9/16] Loss: 0.00363 +Epoch [2659/4000] Training [10/16] Loss: 0.00394 +Epoch [2659/4000] Training [11/16] Loss: 0.00466 +Epoch [2659/4000] Training [12/16] Loss: 0.00321 +Epoch [2659/4000] Training [13/16] Loss: 0.00475 +Epoch [2659/4000] Training [14/16] Loss: 0.00329 +Epoch [2659/4000] Training [15/16] Loss: 0.00496 +Epoch [2659/4000] Training [16/16] Loss: 0.00394 +Epoch [2659/4000] Training metric {'Train/mean dice_metric': 0.9975884556770325, 'Train/mean miou_metric': 0.994916558265686, 'Train/mean f1': 0.9928346872329712, 'Train/mean precision': 0.9882053136825562, 'Train/mean recall': 0.9975076913833618, 'Train/mean hd95_metric': 0.8885042667388916} +Epoch [2659/4000] Validation [1/4] Loss: 0.35682 focal_loss 0.28996 dice_loss 0.06686 +Epoch [2659/4000] Validation [2/4] Loss: 1.03549 focal_loss 0.85470 dice_loss 0.18079 +Epoch [2659/4000] Validation [3/4] Loss: 0.29701 focal_loss 0.21495 dice_loss 0.08206 +Epoch [2659/4000] Validation [4/4] Loss: 0.57858 focal_loss 0.44799 dice_loss 0.13058 +Epoch [2659/4000] Validation metric {'Val/mean dice_metric': 0.9705911874771118, 'Val/mean miou_metric': 0.955974280834198, 'Val/mean f1': 0.9746035933494568, 'Val/mean precision': 0.9746788740158081, 'Val/mean recall': 0.974528431892395, 'Val/mean hd95_metric': 5.4286723136901855} +Cheakpoint... +Epoch [2659/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705911874771118, 'Val/mean miou_metric': 0.955974280834198, 'Val/mean f1': 0.9746035933494568, 'Val/mean precision': 0.9746788740158081, 'Val/mean recall': 0.974528431892395, 'Val/mean hd95_metric': 5.4286723136901855} +Epoch [2660/4000] Training [1/16] Loss: 0.00280 +Epoch [2660/4000] Training [2/16] Loss: 0.00484 +Epoch [2660/4000] Training [3/16] Loss: 0.00500 +Epoch [2660/4000] Training [4/16] Loss: 0.00253 +Epoch [2660/4000] Training [5/16] Loss: 0.00454 +Epoch [2660/4000] Training [6/16] Loss: 0.00414 +Epoch [2660/4000] Training [7/16] Loss: 0.00254 +Epoch [2660/4000] Training [8/16] Loss: 0.00644 +Epoch [2660/4000] Training [9/16] Loss: 0.00514 +Epoch [2660/4000] Training [10/16] Loss: 0.00490 +Epoch [2660/4000] Training [11/16] Loss: 0.00374 +Epoch [2660/4000] Training [12/16] Loss: 0.00386 +Epoch [2660/4000] Training [13/16] Loss: 0.00278 +Epoch [2660/4000] Training [14/16] Loss: 0.00421 +Epoch [2660/4000] Training [15/16] Loss: 0.00272 +Epoch [2660/4000] Training [16/16] Loss: 0.00328 +Epoch [2660/4000] Training metric {'Train/mean dice_metric': 0.9977951049804688, 'Train/mean miou_metric': 0.9953230619430542, 'Train/mean f1': 0.9930345416069031, 'Train/mean precision': 0.9885208606719971, 'Train/mean recall': 0.997589647769928, 'Train/mean hd95_metric': 0.8729767799377441} +Epoch [2660/4000] Validation [1/4] Loss: 0.46924 focal_loss 0.38954 dice_loss 0.07970 +Epoch [2660/4000] Validation [2/4] Loss: 1.02595 focal_loss 0.84909 dice_loss 0.17685 +Epoch [2660/4000] Validation [3/4] Loss: 0.28506 focal_loss 0.20569 dice_loss 0.07937 +Epoch [2660/4000] Validation [4/4] Loss: 0.45704 focal_loss 0.31939 dice_loss 0.13764 +Epoch [2660/4000] Validation metric {'Val/mean dice_metric': 0.9713722467422485, 'Val/mean miou_metric': 0.9570876359939575, 'Val/mean f1': 0.9750145077705383, 'Val/mean precision': 0.974277138710022, 'Val/mean recall': 0.9757529497146606, 'Val/mean hd95_metric': 5.035012722015381} +Cheakpoint... +Epoch [2660/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713722467422485, 'Val/mean miou_metric': 0.9570876359939575, 'Val/mean f1': 0.9750145077705383, 'Val/mean precision': 0.974277138710022, 'Val/mean recall': 0.9757529497146606, 'Val/mean hd95_metric': 5.035012722015381} +Epoch [2661/4000] Training [1/16] Loss: 0.00283 +Epoch [2661/4000] Training [2/16] Loss: 0.00341 +Epoch [2661/4000] Training [3/16] Loss: 0.00517 +Epoch [2661/4000] Training [4/16] Loss: 0.05816 +Epoch [2661/4000] Training [5/16] Loss: 0.00292 +Epoch [2661/4000] Training [6/16] Loss: 0.00384 +Epoch [2661/4000] Training [7/16] Loss: 0.00456 +Epoch [2661/4000] Training [8/16] Loss: 0.00381 +Epoch [2661/4000] Training [9/16] Loss: 0.00394 +Epoch [2661/4000] Training [10/16] Loss: 0.00431 +Epoch [2661/4000] Training [11/16] Loss: 0.00355 +Epoch [2661/4000] Training [12/16] Loss: 0.00343 +Epoch [2661/4000] Training [13/16] Loss: 0.00389 +Epoch [2661/4000] Training [14/16] Loss: 0.00425 +Epoch [2661/4000] Training [15/16] Loss: 0.00396 +Epoch [2661/4000] Training [16/16] Loss: 0.00385 +Epoch [2661/4000] Training metric {'Train/mean dice_metric': 0.9971767067909241, 'Train/mean miou_metric': 0.9941843152046204, 'Train/mean f1': 0.9926208257675171, 'Train/mean precision': 0.9882141947746277, 'Train/mean recall': 0.9970669150352478, 'Train/mean hd95_metric': 0.9622707366943359} +Epoch [2661/4000] Validation [1/4] Loss: 0.36212 focal_loss 0.29386 dice_loss 0.06825 +Epoch [2661/4000] Validation [2/4] Loss: 0.74003 focal_loss 0.55869 dice_loss 0.18135 +Epoch [2661/4000] Validation [3/4] Loss: 0.43132 focal_loss 0.32566 dice_loss 0.10566 +Epoch [2661/4000] Validation [4/4] Loss: 0.30956 focal_loss 0.21179 dice_loss 0.09777 +Epoch [2661/4000] Validation metric {'Val/mean dice_metric': 0.9724165797233582, 'Val/mean miou_metric': 0.9570229649543762, 'Val/mean f1': 0.9750779867172241, 'Val/mean precision': 0.9720525741577148, 'Val/mean recall': 0.9781221747398376, 'Val/mean hd95_metric': 5.534947872161865} +Cheakpoint... +Epoch [2661/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724165797233582, 'Val/mean miou_metric': 0.9570229649543762, 'Val/mean f1': 0.9750779867172241, 'Val/mean precision': 0.9720525741577148, 'Val/mean recall': 0.9781221747398376, 'Val/mean hd95_metric': 5.534947872161865} +Epoch [2662/4000] Training [1/16] Loss: 0.00411 +Epoch [2662/4000] Training [2/16] Loss: 0.00315 +Epoch [2662/4000] Training [3/16] Loss: 0.00428 +Epoch [2662/4000] Training [4/16] Loss: 0.00374 +Epoch [2662/4000] Training [5/16] Loss: 0.00376 +Epoch [2662/4000] Training [6/16] Loss: 0.00492 +Epoch [2662/4000] Training [7/16] Loss: 0.00292 +Epoch [2662/4000] Training [8/16] Loss: 0.00342 +Epoch [2662/4000] Training [9/16] Loss: 0.00284 +Epoch [2662/4000] Training [10/16] Loss: 0.00416 +Epoch [2662/4000] Training [11/16] Loss: 0.00362 +Epoch [2662/4000] Training [12/16] Loss: 0.00409 +Epoch [2662/4000] Training [13/16] Loss: 0.00298 +Epoch [2662/4000] Training [14/16] Loss: 0.00404 +Epoch [2662/4000] Training [15/16] Loss: 0.00419 +Epoch [2662/4000] Training [16/16] Loss: 0.00320 +Epoch [2662/4000] Training metric {'Train/mean dice_metric': 0.997650146484375, 'Train/mean miou_metric': 0.9950395822525024, 'Train/mean f1': 0.992915153503418, 'Train/mean precision': 0.9883489608764648, 'Train/mean recall': 0.9975236654281616, 'Train/mean hd95_metric': 0.8869694471359253} +Epoch [2662/4000] Validation [1/4] Loss: 0.32413 focal_loss 0.26153 dice_loss 0.06260 +Epoch [2662/4000] Validation [2/4] Loss: 0.51109 focal_loss 0.35902 dice_loss 0.15207 +Epoch [2662/4000] Validation [3/4] Loss: 0.47839 focal_loss 0.37622 dice_loss 0.10217 +Epoch [2662/4000] Validation [4/4] Loss: 0.36947 focal_loss 0.24457 dice_loss 0.12490 +Epoch [2662/4000] Validation metric {'Val/mean dice_metric': 0.971902072429657, 'Val/mean miou_metric': 0.9565368890762329, 'Val/mean f1': 0.9739890694618225, 'Val/mean precision': 0.9691656231880188, 'Val/mean recall': 0.97886061668396, 'Val/mean hd95_metric': 6.053942680358887} +Cheakpoint... +Epoch [2662/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971902072429657, 'Val/mean miou_metric': 0.9565368890762329, 'Val/mean f1': 0.9739890694618225, 'Val/mean precision': 0.9691656231880188, 'Val/mean recall': 0.97886061668396, 'Val/mean hd95_metric': 6.053942680358887} +Epoch [2663/4000] Training [1/16] Loss: 0.00302 +Epoch [2663/4000] Training [2/16] Loss: 0.00375 +Epoch [2663/4000] Training [3/16] Loss: 0.00336 +Epoch [2663/4000] Training [4/16] Loss: 0.00375 +Epoch [2663/4000] Training [5/16] Loss: 0.00455 +Epoch [2663/4000] Training [6/16] Loss: 0.00367 +Epoch [2663/4000] Training [7/16] Loss: 0.00336 +Epoch [2663/4000] Training [8/16] Loss: 0.00518 +Epoch [2663/4000] Training [9/16] Loss: 0.00461 +Epoch [2663/4000] Training [10/16] Loss: 0.00255 +Epoch [2663/4000] Training [11/16] Loss: 0.00351 +Epoch [2663/4000] Training [12/16] Loss: 0.00263 +Epoch [2663/4000] Training [13/16] Loss: 0.00516 +Epoch [2663/4000] Training [14/16] Loss: 0.00467 +Epoch [2663/4000] Training [15/16] Loss: 0.00348 +Epoch [2663/4000] Training [16/16] Loss: 0.00343 +Epoch [2663/4000] Training metric {'Train/mean dice_metric': 0.9977101683616638, 'Train/mean miou_metric': 0.9951373338699341, 'Train/mean f1': 0.9923362731933594, 'Train/mean precision': 0.9872154593467712, 'Train/mean recall': 0.9975104928016663, 'Train/mean hd95_metric': 0.8972346782684326} +Epoch [2663/4000] Validation [1/4] Loss: 0.34140 focal_loss 0.27572 dice_loss 0.06568 +Epoch [2663/4000] Validation [2/4] Loss: 0.52340 focal_loss 0.35479 dice_loss 0.16862 +Epoch [2663/4000] Validation [3/4] Loss: 0.36563 focal_loss 0.26589 dice_loss 0.09974 +Epoch [2663/4000] Validation [4/4] Loss: 0.34513 focal_loss 0.23145 dice_loss 0.11368 +Epoch [2663/4000] Validation metric {'Val/mean dice_metric': 0.9751429557800293, 'Val/mean miou_metric': 0.959671676158905, 'Val/mean f1': 0.9750362038612366, 'Val/mean precision': 0.9689815044403076, 'Val/mean recall': 0.9811670780181885, 'Val/mean hd95_metric': 5.509365081787109} +Cheakpoint... +Epoch [2663/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751429557800293, 'Val/mean miou_metric': 0.959671676158905, 'Val/mean f1': 0.9750362038612366, 'Val/mean precision': 0.9689815044403076, 'Val/mean recall': 0.9811670780181885, 'Val/mean hd95_metric': 5.509365081787109} +Epoch [2664/4000] Training [1/16] Loss: 0.00640 +Epoch [2664/4000] Training [2/16] Loss: 0.00644 +Epoch [2664/4000] Training [3/16] Loss: 0.00301 +Epoch [2664/4000] Training [4/16] Loss: 0.00477 +Epoch [2664/4000] Training [5/16] Loss: 0.00402 +Epoch [2664/4000] Training [6/16] Loss: 0.00320 +Epoch [2664/4000] Training [7/16] Loss: 0.00453 +Epoch [2664/4000] Training [8/16] Loss: 0.00353 +Epoch [2664/4000] Training [9/16] Loss: 0.00283 +Epoch [2664/4000] Training [10/16] Loss: 0.00402 +Epoch [2664/4000] Training [11/16] Loss: 0.00362 +Epoch [2664/4000] Training [12/16] Loss: 0.00356 +Epoch [2664/4000] Training [13/16] Loss: 0.00324 +Epoch [2664/4000] Training [14/16] Loss: 0.00294 +Epoch [2664/4000] Training [15/16] Loss: 0.00471 +Epoch [2664/4000] Training [16/16] Loss: 0.00400 +Epoch [2664/4000] Training metric {'Train/mean dice_metric': 0.9975862503051758, 'Train/mean miou_metric': 0.9949160814285278, 'Train/mean f1': 0.9928834438323975, 'Train/mean precision': 0.9883018732070923, 'Train/mean recall': 0.9975076913833618, 'Train/mean hd95_metric': 0.9696313738822937} +Epoch [2664/4000] Validation [1/4] Loss: 0.46297 focal_loss 0.38510 dice_loss 0.07786 +Epoch [2664/4000] Validation [2/4] Loss: 0.47297 focal_loss 0.33423 dice_loss 0.13874 +Epoch [2664/4000] Validation [3/4] Loss: 0.34396 focal_loss 0.24681 dice_loss 0.09715 +Epoch [2664/4000] Validation [4/4] Loss: 0.26629 focal_loss 0.16972 dice_loss 0.09657 +Epoch [2664/4000] Validation metric {'Val/mean dice_metric': 0.9713484048843384, 'Val/mean miou_metric': 0.9563885927200317, 'Val/mean f1': 0.974338173866272, 'Val/mean precision': 0.9724166393280029, 'Val/mean recall': 0.9762672185897827, 'Val/mean hd95_metric': 5.751683235168457} +Cheakpoint... +Epoch [2664/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713484048843384, 'Val/mean miou_metric': 0.9563885927200317, 'Val/mean f1': 0.974338173866272, 'Val/mean precision': 0.9724166393280029, 'Val/mean recall': 0.9762672185897827, 'Val/mean hd95_metric': 5.751683235168457} +Epoch [2665/4000] Training [1/16] Loss: 0.00292 +Epoch [2665/4000] Training [2/16] Loss: 0.00284 +Epoch [2665/4000] Training [3/16] Loss: 0.00467 +Epoch [2665/4000] Training [4/16] Loss: 0.00442 +Epoch [2665/4000] Training [5/16] Loss: 0.00399 +Epoch [2665/4000] Training [6/16] Loss: 0.00286 +Epoch [2665/4000] Training [7/16] Loss: 0.00314 +Epoch [2665/4000] Training [8/16] Loss: 0.00307 +Epoch [2665/4000] Training [9/16] Loss: 0.00426 +Epoch [2665/4000] Training [10/16] Loss: 0.00415 +Epoch [2665/4000] Training [11/16] Loss: 0.00349 +Epoch [2665/4000] Training [12/16] Loss: 0.00583 +Epoch [2665/4000] Training [13/16] Loss: 0.00495 +Epoch [2665/4000] Training [14/16] Loss: 0.00297 +Epoch [2665/4000] Training [15/16] Loss: 0.00477 +Epoch [2665/4000] Training [16/16] Loss: 0.00637 +Epoch [2665/4000] Training metric {'Train/mean dice_metric': 0.9977471232414246, 'Train/mean miou_metric': 0.9952036142349243, 'Train/mean f1': 0.9926661252975464, 'Train/mean precision': 0.9878520369529724, 'Train/mean recall': 0.9975273013114929, 'Train/mean hd95_metric': 0.8799017071723938} +Epoch [2665/4000] Validation [1/4] Loss: 0.36070 focal_loss 0.29112 dice_loss 0.06958 +Epoch [2665/4000] Validation [2/4] Loss: 0.45623 focal_loss 0.32471 dice_loss 0.13153 +Epoch [2665/4000] Validation [3/4] Loss: 0.27698 focal_loss 0.19636 dice_loss 0.08062 +Epoch [2665/4000] Validation [4/4] Loss: 0.30627 focal_loss 0.20950 dice_loss 0.09677 +Epoch [2665/4000] Validation metric {'Val/mean dice_metric': 0.974448561668396, 'Val/mean miou_metric': 0.9596126675605774, 'Val/mean f1': 0.9755902290344238, 'Val/mean precision': 0.9726248383522034, 'Val/mean recall': 0.9785736203193665, 'Val/mean hd95_metric': 5.468209266662598} +Cheakpoint... +Epoch [2665/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974448561668396, 'Val/mean miou_metric': 0.9596126675605774, 'Val/mean f1': 0.9755902290344238, 'Val/mean precision': 0.9726248383522034, 'Val/mean recall': 0.9785736203193665, 'Val/mean hd95_metric': 5.468209266662598} +Epoch [2666/4000] Training [1/16] Loss: 0.00323 +Epoch [2666/4000] Training [2/16] Loss: 0.00403 +Epoch [2666/4000] Training [3/16] Loss: 0.00418 +Epoch [2666/4000] Training [4/16] Loss: 0.00283 +Epoch [2666/4000] Training [5/16] Loss: 0.00500 +Epoch [2666/4000] Training [6/16] Loss: 0.00282 +Epoch [2666/4000] Training [7/16] Loss: 0.00409 +Epoch [2666/4000] Training [8/16] Loss: 0.00344 +Epoch [2666/4000] Training [9/16] Loss: 0.00274 +Epoch [2666/4000] Training [10/16] Loss: 0.00375 +Epoch [2666/4000] Training [11/16] Loss: 0.00271 +Epoch [2666/4000] Training [12/16] Loss: 0.00325 +Epoch [2666/4000] Training [13/16] Loss: 0.00236 +Epoch [2666/4000] Training [14/16] Loss: 0.00310 +Epoch [2666/4000] Training [15/16] Loss: 0.00558 +Epoch [2666/4000] Training [16/16] Loss: 0.00330 +Epoch [2666/4000] Training metric {'Train/mean dice_metric': 0.9978436231613159, 'Train/mean miou_metric': 0.9954259395599365, 'Train/mean f1': 0.9931737184524536, 'Train/mean precision': 0.9886547327041626, 'Train/mean recall': 0.9977341294288635, 'Train/mean hd95_metric': 0.8641259670257568} +Epoch [2666/4000] Validation [1/4] Loss: 0.30571 focal_loss 0.24304 dice_loss 0.06267 +Epoch [2666/4000] Validation [2/4] Loss: 0.90561 focal_loss 0.67542 dice_loss 0.23019 +Epoch [2666/4000] Validation [3/4] Loss: 0.41482 focal_loss 0.32342 dice_loss 0.09139 +Epoch [2666/4000] Validation [4/4] Loss: 0.39481 focal_loss 0.27200 dice_loss 0.12282 +Epoch [2666/4000] Validation metric {'Val/mean dice_metric': 0.973196804523468, 'Val/mean miou_metric': 0.9585887789726257, 'Val/mean f1': 0.9757333993911743, 'Val/mean precision': 0.9715310335159302, 'Val/mean recall': 0.9799721240997314, 'Val/mean hd95_metric': 5.045895576477051} +Cheakpoint... +Epoch [2666/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973196804523468, 'Val/mean miou_metric': 0.9585887789726257, 'Val/mean f1': 0.9757333993911743, 'Val/mean precision': 0.9715310335159302, 'Val/mean recall': 0.9799721240997314, 'Val/mean hd95_metric': 5.045895576477051} +Epoch [2667/4000] Training [1/16] Loss: 0.00301 +Epoch [2667/4000] Training [2/16] Loss: 0.00296 +Epoch [2667/4000] Training [3/16] Loss: 0.00304 +Epoch [2667/4000] Training [4/16] Loss: 0.00389 +Epoch [2667/4000] Training [5/16] Loss: 0.00378 +Epoch [2667/4000] Training [6/16] Loss: 0.00364 +Epoch [2667/4000] Training [7/16] Loss: 0.00298 +Epoch [2667/4000] Training [8/16] Loss: 0.00335 +Epoch [2667/4000] Training [9/16] Loss: 0.00500 +Epoch [2667/4000] Training [10/16] Loss: 0.00449 +Epoch [2667/4000] Training [11/16] Loss: 0.00261 +Epoch [2667/4000] Training [12/16] Loss: 0.00462 +Epoch [2667/4000] Training [13/16] Loss: 0.00287 +Epoch [2667/4000] Training [14/16] Loss: 0.00487 +Epoch [2667/4000] Training [15/16] Loss: 0.00366 +Epoch [2667/4000] Training [16/16] Loss: 0.00426 +Epoch [2667/4000] Training metric {'Train/mean dice_metric': 0.9978973269462585, 'Train/mean miou_metric': 0.9955281019210815, 'Train/mean f1': 0.993035078048706, 'Train/mean precision': 0.9884548783302307, 'Train/mean recall': 0.9976579546928406, 'Train/mean hd95_metric': 0.8879038095474243} +Epoch [2667/4000] Validation [1/4] Loss: 0.34006 focal_loss 0.27333 dice_loss 0.06673 +Epoch [2667/4000] Validation [2/4] Loss: 0.75111 focal_loss 0.57009 dice_loss 0.18102 +Epoch [2667/4000] Validation [3/4] Loss: 0.39683 focal_loss 0.30112 dice_loss 0.09571 +Epoch [2667/4000] Validation [4/4] Loss: 0.26177 focal_loss 0.16904 dice_loss 0.09273 +Epoch [2667/4000] Validation metric {'Val/mean dice_metric': 0.9738553762435913, 'Val/mean miou_metric': 0.9596384167671204, 'Val/mean f1': 0.9764382243156433, 'Val/mean precision': 0.9728882908821106, 'Val/mean recall': 0.9800141453742981, 'Val/mean hd95_metric': 5.170592784881592} +Cheakpoint... +Epoch [2667/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738553762435913, 'Val/mean miou_metric': 0.9596384167671204, 'Val/mean f1': 0.9764382243156433, 'Val/mean precision': 0.9728882908821106, 'Val/mean recall': 0.9800141453742981, 'Val/mean hd95_metric': 5.170592784881592} +Epoch [2668/4000] Training [1/16] Loss: 0.01185 +Epoch [2668/4000] Training [2/16] Loss: 0.00404 +Epoch [2668/4000] Training [3/16] Loss: 0.00574 +Epoch [2668/4000] Training [4/16] Loss: 0.00447 +Epoch [2668/4000] Training [5/16] Loss: 0.00342 +Epoch [2668/4000] Training [6/16] Loss: 0.00381 +Epoch [2668/4000] Training [7/16] Loss: 0.00323 +Epoch [2668/4000] Training [8/16] Loss: 0.00506 +Epoch [2668/4000] Training [9/16] Loss: 0.00348 +Epoch [2668/4000] Training [10/16] Loss: 0.00429 +Epoch [2668/4000] Training [11/16] Loss: 0.00335 +Epoch [2668/4000] Training [12/16] Loss: 0.00379 +Epoch [2668/4000] Training [13/16] Loss: 0.00505 +Epoch [2668/4000] Training [14/16] Loss: 0.01615 +Epoch [2668/4000] Training [15/16] Loss: 0.00388 +Epoch [2668/4000] Training [16/16] Loss: 0.00353 +Epoch [2668/4000] Training metric {'Train/mean dice_metric': 0.9974466562271118, 'Train/mean miou_metric': 0.9946600198745728, 'Train/mean f1': 0.9928141236305237, 'Train/mean precision': 0.98824542760849, 'Train/mean recall': 0.9974252581596375, 'Train/mean hd95_metric': 1.1938426494598389} +Epoch [2668/4000] Validation [1/4] Loss: 0.33087 focal_loss 0.26189 dice_loss 0.06898 +Epoch [2668/4000] Validation [2/4] Loss: 0.97221 focal_loss 0.71293 dice_loss 0.25928 +Epoch [2668/4000] Validation [3/4] Loss: 0.22663 focal_loss 0.16807 dice_loss 0.05857 +Epoch [2668/4000] Validation [4/4] Loss: 0.50442 focal_loss 0.38335 dice_loss 0.12107 +Epoch [2668/4000] Validation metric {'Val/mean dice_metric': 0.9731546640396118, 'Val/mean miou_metric': 0.9577668905258179, 'Val/mean f1': 0.9746267199516296, 'Val/mean precision': 0.9736278057098389, 'Val/mean recall': 0.9756277203559875, 'Val/mean hd95_metric': 5.693495750427246} +Cheakpoint... +Epoch [2668/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731546640396118, 'Val/mean miou_metric': 0.9577668905258179, 'Val/mean f1': 0.9746267199516296, 'Val/mean precision': 0.9736278057098389, 'Val/mean recall': 0.9756277203559875, 'Val/mean hd95_metric': 5.693495750427246} +Epoch [2669/4000] Training [1/16] Loss: 0.00368 +Epoch [2669/4000] Training [2/16] Loss: 0.00435 +Epoch [2669/4000] Training [3/16] Loss: 0.00277 +Epoch [2669/4000] Training [4/16] Loss: 0.00649 +Epoch [2669/4000] Training [5/16] Loss: 0.00264 +Epoch [2669/4000] Training [6/16] Loss: 0.00492 +Epoch [2669/4000] Training [7/16] Loss: 0.00494 +Epoch [2669/4000] Training [8/16] Loss: 0.00341 +Epoch [2669/4000] Training [9/16] Loss: 0.00299 +Epoch [2669/4000] Training [10/16] Loss: 0.00487 +Epoch [2669/4000] Training [11/16] Loss: 0.00357 +Epoch [2669/4000] Training [12/16] Loss: 0.00457 +Epoch [2669/4000] Training [13/16] Loss: 0.00591 +Epoch [2669/4000] Training [14/16] Loss: 0.00306 +Epoch [2669/4000] Training [15/16] Loss: 0.00382 +Epoch [2669/4000] Training [16/16] Loss: 0.00353 +Epoch [2669/4000] Training metric {'Train/mean dice_metric': 0.9977233409881592, 'Train/mean miou_metric': 0.9951595067977905, 'Train/mean f1': 0.9924473166465759, 'Train/mean precision': 0.9874879717826843, 'Train/mean recall': 0.9974567294120789, 'Train/mean hd95_metric': 0.9054542183876038} +Epoch [2669/4000] Validation [1/4] Loss: 0.45516 focal_loss 0.37820 dice_loss 0.07695 +Epoch [2669/4000] Validation [2/4] Loss: 1.07136 focal_loss 0.86949 dice_loss 0.20187 +Epoch [2669/4000] Validation [3/4] Loss: 0.34867 focal_loss 0.25084 dice_loss 0.09783 +Epoch [2669/4000] Validation [4/4] Loss: 0.30067 focal_loss 0.20762 dice_loss 0.09305 +Epoch [2669/4000] Validation metric {'Val/mean dice_metric': 0.9709709882736206, 'Val/mean miou_metric': 0.9561207890510559, 'Val/mean f1': 0.9738317728042603, 'Val/mean precision': 0.9734669923782349, 'Val/mean recall': 0.9741970300674438, 'Val/mean hd95_metric': 5.0559844970703125} +Cheakpoint... +Epoch [2669/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709709882736206, 'Val/mean miou_metric': 0.9561207890510559, 'Val/mean f1': 0.9738317728042603, 'Val/mean precision': 0.9734669923782349, 'Val/mean recall': 0.9741970300674438, 'Val/mean hd95_metric': 5.0559844970703125} +Epoch [2670/4000] Training [1/16] Loss: 0.00299 +Epoch [2670/4000] Training [2/16] Loss: 0.00422 +Epoch [2670/4000] Training [3/16] Loss: 0.00410 +Epoch [2670/4000] Training [4/16] Loss: 0.00343 +Epoch [2670/4000] Training [5/16] Loss: 0.00289 +Epoch [2670/4000] Training [6/16] Loss: 0.00367 +Epoch [2670/4000] Training [7/16] Loss: 0.00369 +Epoch [2670/4000] Training [8/16] Loss: 0.00275 +Epoch [2670/4000] Training [9/16] Loss: 0.00513 +Epoch [2670/4000] Training [10/16] Loss: 0.00306 +Epoch [2670/4000] Training [11/16] Loss: 0.00563 +Epoch [2670/4000] Training [12/16] Loss: 0.00309 +Epoch [2670/4000] Training [13/16] Loss: 0.00412 +Epoch [2670/4000] Training [14/16] Loss: 0.00396 +Epoch [2670/4000] Training [15/16] Loss: 0.00298 +Epoch [2670/4000] Training [16/16] Loss: 0.00426 +Epoch [2670/4000] Training metric {'Train/mean dice_metric': 0.9977765083312988, 'Train/mean miou_metric': 0.9952853322029114, 'Train/mean f1': 0.992971658706665, 'Train/mean precision': 0.9883933663368225, 'Train/mean recall': 0.997592568397522, 'Train/mean hd95_metric': 0.8791996240615845} +Epoch [2670/4000] Validation [1/4] Loss: 0.64204 focal_loss 0.54803 dice_loss 0.09401 +Epoch [2670/4000] Validation [2/4] Loss: 0.79862 focal_loss 0.62272 dice_loss 0.17590 +Epoch [2670/4000] Validation [3/4] Loss: 0.36956 focal_loss 0.28014 dice_loss 0.08942 +Epoch [2670/4000] Validation [4/4] Loss: 0.37159 focal_loss 0.25224 dice_loss 0.11935 +Epoch [2670/4000] Validation metric {'Val/mean dice_metric': 0.9711382985115051, 'Val/mean miou_metric': 0.9559376835823059, 'Val/mean f1': 0.9741572737693787, 'Val/mean precision': 0.9747657775878906, 'Val/mean recall': 0.9735493659973145, 'Val/mean hd95_metric': 5.0535688400268555} +Cheakpoint... +Epoch [2670/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711382985115051, 'Val/mean miou_metric': 0.9559376835823059, 'Val/mean f1': 0.9741572737693787, 'Val/mean precision': 0.9747657775878906, 'Val/mean recall': 0.9735493659973145, 'Val/mean hd95_metric': 5.0535688400268555} +Epoch [2671/4000] Training [1/16] Loss: 0.00349 +Epoch [2671/4000] Training [2/16] Loss: 0.00401 +Epoch [2671/4000] Training [3/16] Loss: 0.00360 +Epoch [2671/4000] Training [4/16] Loss: 0.00403 +Epoch [2671/4000] Training [5/16] Loss: 0.00388 +Epoch [2671/4000] Training [6/16] Loss: 0.00429 +Epoch [2671/4000] Training [7/16] Loss: 0.00342 +Epoch [2671/4000] Training [8/16] Loss: 0.00427 +Epoch [2671/4000] Training [9/16] Loss: 0.00523 +Epoch [2671/4000] Training [10/16] Loss: 0.00415 +Epoch [2671/4000] Training [11/16] Loss: 0.00314 +Epoch [2671/4000] Training [12/16] Loss: 0.00338 +Epoch [2671/4000] Training [13/16] Loss: 0.00416 +Epoch [2671/4000] Training [14/16] Loss: 0.00518 +Epoch [2671/4000] Training [15/16] Loss: 0.00424 +Epoch [2671/4000] Training [16/16] Loss: 0.00328 +Epoch [2671/4000] Training metric {'Train/mean dice_metric': 0.9977374076843262, 'Train/mean miou_metric': 0.9951984882354736, 'Train/mean f1': 0.9928504228591919, 'Train/mean precision': 0.9881631731987, 'Train/mean recall': 0.9975823760032654, 'Train/mean hd95_metric': 0.8950472474098206} +Epoch [2671/4000] Validation [1/4] Loss: 0.53510 focal_loss 0.45574 dice_loss 0.07936 +Epoch [2671/4000] Validation [2/4] Loss: 1.63463 focal_loss 1.33456 dice_loss 0.30007 +Epoch [2671/4000] Validation [3/4] Loss: 0.34537 focal_loss 0.25429 dice_loss 0.09108 +Epoch [2671/4000] Validation [4/4] Loss: 0.39687 focal_loss 0.28281 dice_loss 0.11406 +Epoch [2671/4000] Validation metric {'Val/mean dice_metric': 0.9696561694145203, 'Val/mean miou_metric': 0.9548753499984741, 'Val/mean f1': 0.974041223526001, 'Val/mean precision': 0.9744131565093994, 'Val/mean recall': 0.9736695885658264, 'Val/mean hd95_metric': 5.5888895988464355} +Cheakpoint... +Epoch [2671/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9696561694145203, 'Val/mean miou_metric': 0.9548753499984741, 'Val/mean f1': 0.974041223526001, 'Val/mean precision': 0.9744131565093994, 'Val/mean recall': 0.9736695885658264, 'Val/mean hd95_metric': 5.5888895988464355} +Epoch [2672/4000] Training [1/16] Loss: 0.00357 +Epoch [2672/4000] Training [2/16] Loss: 0.00436 +Epoch [2672/4000] Training [3/16] Loss: 0.00318 +Epoch [2672/4000] Training [4/16] Loss: 0.00371 +Epoch [2672/4000] Training [5/16] Loss: 0.00330 +Epoch [2672/4000] Training [6/16] Loss: 0.00315 +Epoch [2672/4000] Training [7/16] Loss: 0.00352 +Epoch [2672/4000] Training [8/16] Loss: 0.00309 +Epoch [2672/4000] Training [9/16] Loss: 0.00336 +Epoch [2672/4000] Training [10/16] Loss: 0.00364 +Epoch [2672/4000] Training [11/16] Loss: 0.00447 +Epoch [2672/4000] Training [12/16] Loss: 0.00333 +Epoch [2672/4000] Training [13/16] Loss: 0.00546 +Epoch [2672/4000] Training [14/16] Loss: 0.00276 +Epoch [2672/4000] Training [15/16] Loss: 0.00315 +Epoch [2672/4000] Training [16/16] Loss: 0.00299 +Epoch [2672/4000] Training metric {'Train/mean dice_metric': 0.9977844953536987, 'Train/mean miou_metric': 0.9953069090843201, 'Train/mean f1': 0.9930684566497803, 'Train/mean precision': 0.9885406494140625, 'Train/mean recall': 0.9976378679275513, 'Train/mean hd95_metric': 0.8908756971359253} +Epoch [2672/4000] Validation [1/4] Loss: 0.61159 focal_loss 0.52018 dice_loss 0.09141 +Epoch [2672/4000] Validation [2/4] Loss: 0.77111 focal_loss 0.59907 dice_loss 0.17204 +Epoch [2672/4000] Validation [3/4] Loss: 0.38296 focal_loss 0.28629 dice_loss 0.09666 +Epoch [2672/4000] Validation [4/4] Loss: 0.40496 focal_loss 0.29071 dice_loss 0.11425 +Epoch [2672/4000] Validation metric {'Val/mean dice_metric': 0.9708808660507202, 'Val/mean miou_metric': 0.9562534093856812, 'Val/mean f1': 0.9744216203689575, 'Val/mean precision': 0.9748613834381104, 'Val/mean recall': 0.9739822745323181, 'Val/mean hd95_metric': 5.191993236541748} +Cheakpoint... +Epoch [2672/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708808660507202, 'Val/mean miou_metric': 0.9562534093856812, 'Val/mean f1': 0.9744216203689575, 'Val/mean precision': 0.9748613834381104, 'Val/mean recall': 0.9739822745323181, 'Val/mean hd95_metric': 5.191993236541748} +Epoch [2673/4000] Training [1/16] Loss: 0.00264 +Epoch [2673/4000] Training [2/16] Loss: 0.00551 +Epoch [2673/4000] Training [3/16] Loss: 0.00338 +Epoch [2673/4000] Training [4/16] Loss: 0.00374 +Epoch [2673/4000] Training [5/16] Loss: 0.00386 +Epoch [2673/4000] Training [6/16] Loss: 0.00325 +Epoch [2673/4000] Training [7/16] Loss: 0.00353 +Epoch [2673/4000] Training [8/16] Loss: 0.00433 +Epoch [2673/4000] Training [9/16] Loss: 0.00416 +Epoch [2673/4000] Training [10/16] Loss: 0.00393 +Epoch [2673/4000] Training [11/16] Loss: 0.00380 +Epoch [2673/4000] Training [12/16] Loss: 0.00585 +Epoch [2673/4000] Training [13/16] Loss: 0.00359 +Epoch [2673/4000] Training [14/16] Loss: 0.00284 +Epoch [2673/4000] Training [15/16] Loss: 0.00411 +Epoch [2673/4000] Training [16/16] Loss: 0.00473 +Epoch [2673/4000] Training metric {'Train/mean dice_metric': 0.9976608157157898, 'Train/mean miou_metric': 0.995058536529541, 'Train/mean f1': 0.9930332899093628, 'Train/mean precision': 0.9885594844818115, 'Train/mean recall': 0.9975477457046509, 'Train/mean hd95_metric': 0.9042881727218628} +Epoch [2673/4000] Validation [1/4] Loss: 0.54673 focal_loss 0.43902 dice_loss 0.10770 +Epoch [2673/4000] Validation [2/4] Loss: 1.14749 focal_loss 0.86852 dice_loss 0.27897 +Epoch [2673/4000] Validation [3/4] Loss: 0.27731 focal_loss 0.19289 dice_loss 0.08442 +Epoch [2673/4000] Validation [4/4] Loss: 0.41442 focal_loss 0.28234 dice_loss 0.13209 +Epoch [2673/4000] Validation metric {'Val/mean dice_metric': 0.9678298830986023, 'Val/mean miou_metric': 0.9525457620620728, 'Val/mean f1': 0.9734190702438354, 'Val/mean precision': 0.9743027091026306, 'Val/mean recall': 0.9725371599197388, 'Val/mean hd95_metric': 5.448755741119385} +Cheakpoint... +Epoch [2673/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9678], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9678298830986023, 'Val/mean miou_metric': 0.9525457620620728, 'Val/mean f1': 0.9734190702438354, 'Val/mean precision': 0.9743027091026306, 'Val/mean recall': 0.9725371599197388, 'Val/mean hd95_metric': 5.448755741119385} +Epoch [2674/4000] Training [1/16] Loss: 0.00420 +Epoch [2674/4000] Training [2/16] Loss: 0.00305 +Epoch [2674/4000] Training [3/16] Loss: 0.00372 +Epoch [2674/4000] Training [4/16] Loss: 0.00400 +Epoch [2674/4000] Training [5/16] Loss: 0.00329 +Epoch [2674/4000] Training [6/16] Loss: 0.00312 +Epoch [2674/4000] Training [7/16] Loss: 0.00387 +Epoch [2674/4000] Training [8/16] Loss: 0.00435 +Epoch [2674/4000] Training [9/16] Loss: 0.00331 +Epoch [2674/4000] Training [10/16] Loss: 0.00311 +Epoch [2674/4000] Training [11/16] Loss: 0.00347 +Epoch [2674/4000] Training [12/16] Loss: 0.00289 +Epoch [2674/4000] Training [13/16] Loss: 0.00455 +Epoch [2674/4000] Training [14/16] Loss: 0.00424 +Epoch [2674/4000] Training [15/16] Loss: 0.00382 +Epoch [2674/4000] Training [16/16] Loss: 0.00338 +Epoch [2674/4000] Training metric {'Train/mean dice_metric': 0.9977662563323975, 'Train/mean miou_metric': 0.9952222108840942, 'Train/mean f1': 0.992001473903656, 'Train/mean precision': 0.9864627122879028, 'Train/mean recall': 0.9976027607917786, 'Train/mean hd95_metric': 0.9004431962966919} +Epoch [2674/4000] Validation [1/4] Loss: 0.35127 focal_loss 0.28285 dice_loss 0.06842 +Epoch [2674/4000] Validation [2/4] Loss: 1.22219 focal_loss 1.03491 dice_loss 0.18728 +Epoch [2674/4000] Validation [3/4] Loss: 0.30539 focal_loss 0.22236 dice_loss 0.08303 +Epoch [2674/4000] Validation [4/4] Loss: 0.41194 focal_loss 0.29257 dice_loss 0.11937 +Epoch [2674/4000] Validation metric {'Val/mean dice_metric': 0.9708177447319031, 'Val/mean miou_metric': 0.9561091661453247, 'Val/mean f1': 0.9740555286407471, 'Val/mean precision': 0.9729971289634705, 'Val/mean recall': 0.9751160740852356, 'Val/mean hd95_metric': 5.369926452636719} +Cheakpoint... +Epoch [2674/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708177447319031, 'Val/mean miou_metric': 0.9561091661453247, 'Val/mean f1': 0.9740555286407471, 'Val/mean precision': 0.9729971289634705, 'Val/mean recall': 0.9751160740852356, 'Val/mean hd95_metric': 5.369926452636719} +Epoch [2675/4000] Training [1/16] Loss: 0.00435 +Epoch [2675/4000] Training [2/16] Loss: 0.00443 +Epoch [2675/4000] Training [3/16] Loss: 0.00537 +Epoch [2675/4000] Training [4/16] Loss: 0.00389 +Epoch [2675/4000] Training [5/16] Loss: 0.00353 +Epoch [2675/4000] Training [6/16] Loss: 0.00531 +Epoch [2675/4000] Training [7/16] Loss: 0.00433 +Epoch [2675/4000] Training [8/16] Loss: 0.00617 +Epoch [2675/4000] Training [9/16] Loss: 0.00339 +Epoch [2675/4000] Training [10/16] Loss: 0.00364 +Epoch [2675/4000] Training [11/16] Loss: 0.00328 +Epoch [2675/4000] Training [12/16] Loss: 0.00299 +Epoch [2675/4000] Training [13/16] Loss: 0.00619 +Epoch [2675/4000] Training [14/16] Loss: 0.00392 +Epoch [2675/4000] Training [15/16] Loss: 0.00303 +Epoch [2675/4000] Training [16/16] Loss: 0.00473 +Epoch [2675/4000] Training metric {'Train/mean dice_metric': 0.9973421692848206, 'Train/mean miou_metric': 0.994425356388092, 'Train/mean f1': 0.9924143552780151, 'Train/mean precision': 0.9876387119293213, 'Train/mean recall': 0.9972364902496338, 'Train/mean hd95_metric': 0.9421688914299011} +Epoch [2675/4000] Validation [1/4] Loss: 0.38967 focal_loss 0.32352 dice_loss 0.06616 +Epoch [2675/4000] Validation [2/4] Loss: 0.98424 focal_loss 0.71453 dice_loss 0.26971 +Epoch [2675/4000] Validation [3/4] Loss: 0.37411 focal_loss 0.28121 dice_loss 0.09290 +Epoch [2675/4000] Validation [4/4] Loss: 0.42107 focal_loss 0.30059 dice_loss 0.12048 +Epoch [2675/4000] Validation metric {'Val/mean dice_metric': 0.9691600799560547, 'Val/mean miou_metric': 0.9540818929672241, 'Val/mean f1': 0.9736209511756897, 'Val/mean precision': 0.9730968475341797, 'Val/mean recall': 0.9741455912590027, 'Val/mean hd95_metric': 5.323145389556885} +Cheakpoint... +Epoch [2675/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9692], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9691600799560547, 'Val/mean miou_metric': 0.9540818929672241, 'Val/mean f1': 0.9736209511756897, 'Val/mean precision': 0.9730968475341797, 'Val/mean recall': 0.9741455912590027, 'Val/mean hd95_metric': 5.323145389556885} +Epoch [2676/4000] Training [1/16] Loss: 0.00410 +Epoch [2676/4000] Training [2/16] Loss: 0.00286 +Epoch [2676/4000] Training [3/16] Loss: 0.00288 +Epoch [2676/4000] Training [4/16] Loss: 0.00288 +Epoch [2676/4000] Training [5/16] Loss: 0.00453 +Epoch [2676/4000] Training [6/16] Loss: 0.00332 +Epoch [2676/4000] Training [7/16] Loss: 0.00534 +Epoch [2676/4000] Training [8/16] Loss: 0.00375 +Epoch [2676/4000] Training [9/16] Loss: 0.00397 +Epoch [2676/4000] Training [10/16] Loss: 0.00321 +Epoch [2676/4000] Training [11/16] Loss: 0.00356 +Epoch [2676/4000] Training [12/16] Loss: 0.00489 +Epoch [2676/4000] Training [13/16] Loss: 0.00324 +Epoch [2676/4000] Training [14/16] Loss: 0.00419 +Epoch [2676/4000] Training [15/16] Loss: 0.00339 +Epoch [2676/4000] Training [16/16] Loss: 0.00366 +Epoch [2676/4000] Training metric {'Train/mean dice_metric': 0.9976236820220947, 'Train/mean miou_metric': 0.994983971118927, 'Train/mean f1': 0.9929550290107727, 'Train/mean precision': 0.9884217977523804, 'Train/mean recall': 0.9975299835205078, 'Train/mean hd95_metric': 0.8989031314849854} +Epoch [2676/4000] Validation [1/4] Loss: 0.39494 focal_loss 0.32172 dice_loss 0.07322 +Epoch [2676/4000] Validation [2/4] Loss: 0.70495 focal_loss 0.53646 dice_loss 0.16849 +Epoch [2676/4000] Validation [3/4] Loss: 0.35694 focal_loss 0.26748 dice_loss 0.08946 +Epoch [2676/4000] Validation [4/4] Loss: 0.30250 focal_loss 0.21212 dice_loss 0.09038 +Epoch [2676/4000] Validation metric {'Val/mean dice_metric': 0.9724971055984497, 'Val/mean miou_metric': 0.9575437307357788, 'Val/mean f1': 0.9754500985145569, 'Val/mean precision': 0.9746293425559998, 'Val/mean recall': 0.9762722253799438, 'Val/mean hd95_metric': 5.014153003692627} +Cheakpoint... +Epoch [2676/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724971055984497, 'Val/mean miou_metric': 0.9575437307357788, 'Val/mean f1': 0.9754500985145569, 'Val/mean precision': 0.9746293425559998, 'Val/mean recall': 0.9762722253799438, 'Val/mean hd95_metric': 5.014153003692627} +Epoch [2677/4000] Training [1/16] Loss: 0.00402 +Epoch [2677/4000] Training [2/16] Loss: 0.00308 +Epoch [2677/4000] Training [3/16] Loss: 0.00448 +Epoch [2677/4000] Training [4/16] Loss: 0.00295 +Epoch [2677/4000] Training [5/16] Loss: 0.00346 +Epoch [2677/4000] Training [6/16] Loss: 0.00347 +Epoch [2677/4000] Training [7/16] Loss: 0.00436 +Epoch [2677/4000] Training [8/16] Loss: 0.00409 +Epoch [2677/4000] Training [9/16] Loss: 0.00372 +Epoch [2677/4000] Training [10/16] Loss: 0.00386 +Epoch [2677/4000] Training [11/16] Loss: 0.00471 +Epoch [2677/4000] Training [12/16] Loss: 0.00237 +Epoch [2677/4000] Training [13/16] Loss: 0.00388 +Epoch [2677/4000] Training [14/16] Loss: 0.00384 +Epoch [2677/4000] Training [15/16] Loss: 0.00361 +Epoch [2677/4000] Training [16/16] Loss: 0.00363 +Epoch [2677/4000] Training metric {'Train/mean dice_metric': 0.9976094961166382, 'Train/mean miou_metric': 0.9949495196342468, 'Train/mean f1': 0.9927600026130676, 'Train/mean precision': 0.9880789518356323, 'Train/mean recall': 0.9974856376647949, 'Train/mean hd95_metric': 0.8973211050033569} +Epoch [2677/4000] Validation [1/4] Loss: 0.38735 focal_loss 0.30690 dice_loss 0.08045 +Epoch [2677/4000] Validation [2/4] Loss: 0.97926 focal_loss 0.79248 dice_loss 0.18678 +Epoch [2677/4000] Validation [3/4] Loss: 0.35662 focal_loss 0.26499 dice_loss 0.09163 +Epoch [2677/4000] Validation [4/4] Loss: 0.33618 focal_loss 0.22720 dice_loss 0.10898 +Epoch [2677/4000] Validation metric {'Val/mean dice_metric': 0.9715543985366821, 'Val/mean miou_metric': 0.9565948247909546, 'Val/mean f1': 0.9752318859100342, 'Val/mean precision': 0.9741859436035156, 'Val/mean recall': 0.9762800931930542, 'Val/mean hd95_metric': 5.043448448181152} +Cheakpoint... +Epoch [2677/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715543985366821, 'Val/mean miou_metric': 0.9565948247909546, 'Val/mean f1': 0.9752318859100342, 'Val/mean precision': 0.9741859436035156, 'Val/mean recall': 0.9762800931930542, 'Val/mean hd95_metric': 5.043448448181152} +Epoch [2678/4000] Training [1/16] Loss: 0.00420 +Epoch [2678/4000] Training [2/16] Loss: 0.00345 +Epoch [2678/4000] Training [3/16] Loss: 0.00325 +Epoch [2678/4000] Training [4/16] Loss: 0.00308 +Epoch [2678/4000] Training [5/16] Loss: 0.00314 +Epoch [2678/4000] Training [6/16] Loss: 0.00462 +Epoch [2678/4000] Training [7/16] Loss: 0.00472 +Epoch [2678/4000] Training [8/16] Loss: 0.00350 +Epoch [2678/4000] Training [9/16] Loss: 0.00407 +Epoch [2678/4000] Training [10/16] Loss: 0.00312 +Epoch [2678/4000] Training [11/16] Loss: 0.00425 +Epoch [2678/4000] Training [12/16] Loss: 0.00424 +Epoch [2678/4000] Training [13/16] Loss: 0.00361 +Epoch [2678/4000] Training [14/16] Loss: 0.00368 +Epoch [2678/4000] Training [15/16] Loss: 0.00349 +Epoch [2678/4000] Training [16/16] Loss: 0.00373 +Epoch [2678/4000] Training metric {'Train/mean dice_metric': 0.9977636933326721, 'Train/mean miou_metric': 0.9952654838562012, 'Train/mean f1': 0.9929655194282532, 'Train/mean precision': 0.9883451461791992, 'Train/mean recall': 0.9976292848587036, 'Train/mean hd95_metric': 0.886551022529602} +Epoch [2678/4000] Validation [1/4] Loss: 0.38707 focal_loss 0.31438 dice_loss 0.07269 +Epoch [2678/4000] Validation [2/4] Loss: 0.59527 focal_loss 0.45667 dice_loss 0.13859 +Epoch [2678/4000] Validation [3/4] Loss: 0.35913 focal_loss 0.26201 dice_loss 0.09713 +Epoch [2678/4000] Validation [4/4] Loss: 0.27222 focal_loss 0.18197 dice_loss 0.09025 +Epoch [2678/4000] Validation metric {'Val/mean dice_metric': 0.9722272753715515, 'Val/mean miou_metric': 0.9573495984077454, 'Val/mean f1': 0.9746649265289307, 'Val/mean precision': 0.9740175604820251, 'Val/mean recall': 0.975313127040863, 'Val/mean hd95_metric': 5.0761494636535645} +Cheakpoint... +Epoch [2678/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722272753715515, 'Val/mean miou_metric': 0.9573495984077454, 'Val/mean f1': 0.9746649265289307, 'Val/mean precision': 0.9740175604820251, 'Val/mean recall': 0.975313127040863, 'Val/mean hd95_metric': 5.0761494636535645} +Epoch [2679/4000] Training [1/16] Loss: 0.00308 +Epoch [2679/4000] Training [2/16] Loss: 0.00254 +Epoch [2679/4000] Training [3/16] Loss: 0.00439 +Epoch [2679/4000] Training [4/16] Loss: 0.00449 +Epoch [2679/4000] Training [5/16] Loss: 0.00353 +Epoch [2679/4000] Training [6/16] Loss: 0.00359 +Epoch [2679/4000] Training [7/16] Loss: 0.00588 +Epoch [2679/4000] Training [8/16] Loss: 0.00537 +Epoch [2679/4000] Training [9/16] Loss: 0.00497 +Epoch [2679/4000] Training [10/16] Loss: 0.00469 +Epoch [2679/4000] Training [11/16] Loss: 0.00295 +Epoch [2679/4000] Training [12/16] Loss: 0.00309 +Epoch [2679/4000] Training [13/16] Loss: 0.00405 +Epoch [2679/4000] Training [14/16] Loss: 0.00387 +Epoch [2679/4000] Training [15/16] Loss: 0.00259 +Epoch [2679/4000] Training [16/16] Loss: 0.00269 +Epoch [2679/4000] Training metric {'Train/mean dice_metric': 0.997663676738739, 'Train/mean miou_metric': 0.9950646162033081, 'Train/mean f1': 0.9929823875427246, 'Train/mean precision': 0.9884241819381714, 'Train/mean recall': 0.9975827932357788, 'Train/mean hd95_metric': 1.1740307807922363} +Epoch [2679/4000] Validation [1/4] Loss: 0.49187 focal_loss 0.40445 dice_loss 0.08742 +Epoch [2679/4000] Validation [2/4] Loss: 0.82372 focal_loss 0.63241 dice_loss 0.19130 +Epoch [2679/4000] Validation [3/4] Loss: 0.34541 focal_loss 0.25595 dice_loss 0.08947 +Epoch [2679/4000] Validation [4/4] Loss: 0.26905 focal_loss 0.18695 dice_loss 0.08209 +Epoch [2679/4000] Validation metric {'Val/mean dice_metric': 0.9718236923217773, 'Val/mean miou_metric': 0.956628143787384, 'Val/mean f1': 0.9749879240989685, 'Val/mean precision': 0.9744051694869995, 'Val/mean recall': 0.9755714535713196, 'Val/mean hd95_metric': 5.762382984161377} +Cheakpoint... +Epoch [2679/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718236923217773, 'Val/mean miou_metric': 0.956628143787384, 'Val/mean f1': 0.9749879240989685, 'Val/mean precision': 0.9744051694869995, 'Val/mean recall': 0.9755714535713196, 'Val/mean hd95_metric': 5.762382984161377} +Epoch [2680/4000] Training [1/16] Loss: 0.00335 +Epoch [2680/4000] Training [2/16] Loss: 0.00258 +Epoch [2680/4000] Training [3/16] Loss: 0.00369 +Epoch [2680/4000] Training [4/16] Loss: 0.00361 +Epoch [2680/4000] Training [5/16] Loss: 0.00366 +Epoch [2680/4000] Training [6/16] Loss: 0.00337 +Epoch [2680/4000] Training [7/16] Loss: 0.00338 +Epoch [2680/4000] Training [8/16] Loss: 0.00388 +Epoch [2680/4000] Training [9/16] Loss: 0.00372 +Epoch [2680/4000] Training [10/16] Loss: 0.00362 +Epoch [2680/4000] Training [11/16] Loss: 0.00336 +Epoch [2680/4000] Training [12/16] Loss: 0.00303 +Epoch [2680/4000] Training [13/16] Loss: 0.00368 +Epoch [2680/4000] Training [14/16] Loss: 0.00352 +Epoch [2680/4000] Training [15/16] Loss: 0.00374 +Epoch [2680/4000] Training [16/16] Loss: 0.00398 +Epoch [2680/4000] Training metric {'Train/mean dice_metric': 0.9978315830230713, 'Train/mean miou_metric': 0.9953995943069458, 'Train/mean f1': 0.9931499361991882, 'Train/mean precision': 0.9887274503707886, 'Train/mean recall': 0.9976122379302979, 'Train/mean hd95_metric': 0.88791823387146} +Epoch [2680/4000] Validation [1/4] Loss: 0.46973 focal_loss 0.38749 dice_loss 0.08224 +Epoch [2680/4000] Validation [2/4] Loss: 0.49589 focal_loss 0.36819 dice_loss 0.12770 +Epoch [2680/4000] Validation [3/4] Loss: 0.41092 focal_loss 0.30774 dice_loss 0.10318 +Epoch [2680/4000] Validation [4/4] Loss: 0.24950 focal_loss 0.15978 dice_loss 0.08972 +Epoch [2680/4000] Validation metric {'Val/mean dice_metric': 0.9730842709541321, 'Val/mean miou_metric': 0.9580581784248352, 'Val/mean f1': 0.9755871295928955, 'Val/mean precision': 0.9739381074905396, 'Val/mean recall': 0.9772415161132812, 'Val/mean hd95_metric': 5.1107354164123535} +Cheakpoint... +Epoch [2680/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730842709541321, 'Val/mean miou_metric': 0.9580581784248352, 'Val/mean f1': 0.9755871295928955, 'Val/mean precision': 0.9739381074905396, 'Val/mean recall': 0.9772415161132812, 'Val/mean hd95_metric': 5.1107354164123535} +Epoch [2681/4000] Training [1/16] Loss: 0.00461 +Epoch [2681/4000] Training [2/16] Loss: 0.00247 +Epoch [2681/4000] Training [3/16] Loss: 0.00400 +Epoch [2681/4000] Training [4/16] Loss: 0.00353 +Epoch [2681/4000] Training [5/16] Loss: 0.00438 +Epoch [2681/4000] Training [6/16] Loss: 0.00418 +Epoch [2681/4000] Training [7/16] Loss: 0.00303 +Epoch [2681/4000] Training [8/16] Loss: 0.00443 +Epoch [2681/4000] Training [9/16] Loss: 0.00484 +Epoch [2681/4000] Training [10/16] Loss: 0.00852 +Epoch [2681/4000] Training [11/16] Loss: 0.00384 +Epoch [2681/4000] Training [12/16] Loss: 0.00505 +Epoch [2681/4000] Training [13/16] Loss: 0.00411 +Epoch [2681/4000] Training [14/16] Loss: 0.00526 +Epoch [2681/4000] Training [15/16] Loss: 0.01914 +Epoch [2681/4000] Training [16/16] Loss: 0.00289 +Epoch [2681/4000] Training metric {'Train/mean dice_metric': 0.9971045255661011, 'Train/mean miou_metric': 0.993982195854187, 'Train/mean f1': 0.9926910996437073, 'Train/mean precision': 0.9880725145339966, 'Train/mean recall': 0.9973530769348145, 'Train/mean hd95_metric': 0.9765338897705078} +Epoch [2681/4000] Validation [1/4] Loss: 0.59273 focal_loss 0.47772 dice_loss 0.11500 +Epoch [2681/4000] Validation [2/4] Loss: 0.50532 focal_loss 0.37118 dice_loss 0.13414 +Epoch [2681/4000] Validation [3/4] Loss: 0.25486 focal_loss 0.18582 dice_loss 0.06904 +Epoch [2681/4000] Validation [4/4] Loss: 0.30467 focal_loss 0.21415 dice_loss 0.09052 +Epoch [2681/4000] Validation metric {'Val/mean dice_metric': 0.9711917638778687, 'Val/mean miou_metric': 0.9554521441459656, 'Val/mean f1': 0.9743282794952393, 'Val/mean precision': 0.9741625785827637, 'Val/mean recall': 0.9744938611984253, 'Val/mean hd95_metric': 5.7572832107543945} +Cheakpoint... +Epoch [2681/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711917638778687, 'Val/mean miou_metric': 0.9554521441459656, 'Val/mean f1': 0.9743282794952393, 'Val/mean precision': 0.9741625785827637, 'Val/mean recall': 0.9744938611984253, 'Val/mean hd95_metric': 5.7572832107543945} +Epoch [2682/4000] Training [1/16] Loss: 0.00380 +Epoch [2682/4000] Training [2/16] Loss: 0.00303 +Epoch [2682/4000] Training [3/16] Loss: 0.00303 +Epoch [2682/4000] Training [4/16] Loss: 0.00319 +Epoch [2682/4000] Training [5/16] Loss: 0.00415 +Epoch [2682/4000] Training [6/16] Loss: 0.00360 +Epoch [2682/4000] Training [7/16] Loss: 0.00527 +Epoch [2682/4000] Training [8/16] Loss: 0.00387 +Epoch [2682/4000] Training [9/16] Loss: 0.00411 +Epoch [2682/4000] Training [10/16] Loss: 0.00459 +Epoch [2682/4000] Training [11/16] Loss: 0.00328 +Epoch [2682/4000] Training [12/16] Loss: 0.00248 +Epoch [2682/4000] Training [13/16] Loss: 0.00526 +Epoch [2682/4000] Training [14/16] Loss: 0.00381 +Epoch [2682/4000] Training [15/16] Loss: 0.00319 +Epoch [2682/4000] Training [16/16] Loss: 0.00434 +Epoch [2682/4000] Training metric {'Train/mean dice_metric': 0.9978252649307251, 'Train/mean miou_metric': 0.9953850507736206, 'Train/mean f1': 0.9930683374404907, 'Train/mean precision': 0.9885917901992798, 'Train/mean recall': 0.9975855946540833, 'Train/mean hd95_metric': 0.9032082557678223} +Epoch [2682/4000] Validation [1/4] Loss: 0.53383 focal_loss 0.44597 dice_loss 0.08786 +Epoch [2682/4000] Validation [2/4] Loss: 1.30587 focal_loss 1.11342 dice_loss 0.19245 +Epoch [2682/4000] Validation [3/4] Loss: 0.43851 focal_loss 0.33913 dice_loss 0.09939 +Epoch [2682/4000] Validation [4/4] Loss: 0.46082 focal_loss 0.32946 dice_loss 0.13137 +Epoch [2682/4000] Validation metric {'Val/mean dice_metric': 0.9688243865966797, 'Val/mean miou_metric': 0.9537670016288757, 'Val/mean f1': 0.9735535383224487, 'Val/mean precision': 0.9747158288955688, 'Val/mean recall': 0.972393810749054, 'Val/mean hd95_metric': 4.888556957244873} +Cheakpoint... +Epoch [2682/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9688], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9688243865966797, 'Val/mean miou_metric': 0.9537670016288757, 'Val/mean f1': 0.9735535383224487, 'Val/mean precision': 0.9747158288955688, 'Val/mean recall': 0.972393810749054, 'Val/mean hd95_metric': 4.888556957244873} +Epoch [2683/4000] Training [1/16] Loss: 0.00366 +Epoch [2683/4000] Training [2/16] Loss: 0.00497 +Epoch [2683/4000] Training [3/16] Loss: 0.00305 +Epoch [2683/4000] Training [4/16] Loss: 0.00319 +Epoch [2683/4000] Training [5/16] Loss: 0.00506 +Epoch [2683/4000] Training [6/16] Loss: 0.00323 +Epoch [2683/4000] Training [7/16] Loss: 0.00358 +Epoch [2683/4000] Training [8/16] Loss: 0.00337 +Epoch [2683/4000] Training [9/16] Loss: 0.00504 +Epoch [2683/4000] Training [10/16] Loss: 0.00322 +Epoch [2683/4000] Training [11/16] Loss: 0.00374 +Epoch [2683/4000] Training [12/16] Loss: 0.00417 +Epoch [2683/4000] Training [13/16] Loss: 0.00351 +Epoch [2683/4000] Training [14/16] Loss: 0.00445 +Epoch [2683/4000] Training [15/16] Loss: 0.00445 +Epoch [2683/4000] Training [16/16] Loss: 0.00439 +Epoch [2683/4000] Training metric {'Train/mean dice_metric': 0.9975939989089966, 'Train/mean miou_metric': 0.9948901534080505, 'Train/mean f1': 0.9920452237129211, 'Train/mean precision': 0.9867873191833496, 'Train/mean recall': 0.9973594546318054, 'Train/mean hd95_metric': 0.9102815985679626} +Epoch [2683/4000] Validation [1/4] Loss: 0.45399 focal_loss 0.37115 dice_loss 0.08284 +Epoch [2683/4000] Validation [2/4] Loss: 0.65083 focal_loss 0.48459 dice_loss 0.16623 +Epoch [2683/4000] Validation [3/4] Loss: 0.34308 focal_loss 0.25119 dice_loss 0.09189 +Epoch [2683/4000] Validation [4/4] Loss: 0.37749 focal_loss 0.26466 dice_loss 0.11283 +Epoch [2683/4000] Validation metric {'Val/mean dice_metric': 0.9706413149833679, 'Val/mean miou_metric': 0.9552749395370483, 'Val/mean f1': 0.9732346534729004, 'Val/mean precision': 0.9732954502105713, 'Val/mean recall': 0.9731738567352295, 'Val/mean hd95_metric': 4.789218425750732} +Cheakpoint... +Epoch [2683/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706413149833679, 'Val/mean miou_metric': 0.9552749395370483, 'Val/mean f1': 0.9732346534729004, 'Val/mean precision': 0.9732954502105713, 'Val/mean recall': 0.9731738567352295, 'Val/mean hd95_metric': 4.789218425750732} +Epoch [2684/4000] Training [1/16] Loss: 0.00378 +Epoch [2684/4000] Training [2/16] Loss: 0.00365 +Epoch [2684/4000] Training [3/16] Loss: 0.00361 +Epoch [2684/4000] Training [4/16] Loss: 0.00348 +Epoch [2684/4000] Training [5/16] Loss: 0.00416 +Epoch [2684/4000] Training [6/16] Loss: 0.00451 +Epoch [2684/4000] Training [7/16] Loss: 0.00375 +Epoch [2684/4000] Training [8/16] Loss: 0.00342 +Epoch [2684/4000] Training [9/16] Loss: 0.00422 +Epoch [2684/4000] Training [10/16] Loss: 0.00375 +Epoch [2684/4000] Training [11/16] Loss: 0.00386 +Epoch [2684/4000] Training [12/16] Loss: 0.00350 +Epoch [2684/4000] Training [13/16] Loss: 0.00327 +Epoch [2684/4000] Training [14/16] Loss: 0.00471 +Epoch [2684/4000] Training [15/16] Loss: 0.00362 +Epoch [2684/4000] Training [16/16] Loss: 0.00363 +Epoch [2684/4000] Training metric {'Train/mean dice_metric': 0.9976625442504883, 'Train/mean miou_metric': 0.99505215883255, 'Train/mean f1': 0.9927231073379517, 'Train/mean precision': 0.9879498481750488, 'Train/mean recall': 0.9975427389144897, 'Train/mean hd95_metric': 0.8911686539649963} +Epoch [2684/4000] Validation [1/4] Loss: 0.43599 focal_loss 0.36103 dice_loss 0.07496 +Epoch [2684/4000] Validation [2/4] Loss: 0.64143 focal_loss 0.47175 dice_loss 0.16968 +Epoch [2684/4000] Validation [3/4] Loss: 0.30589 focal_loss 0.21324 dice_loss 0.09264 +Epoch [2684/4000] Validation [4/4] Loss: 0.47198 focal_loss 0.34744 dice_loss 0.12453 +Epoch [2684/4000] Validation metric {'Val/mean dice_metric': 0.9702900052070618, 'Val/mean miou_metric': 0.9547247886657715, 'Val/mean f1': 0.9735631346702576, 'Val/mean precision': 0.9746200442314148, 'Val/mean recall': 0.9725084900856018, 'Val/mean hd95_metric': 5.065245628356934} +Cheakpoint... +Epoch [2684/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702900052070618, 'Val/mean miou_metric': 0.9547247886657715, 'Val/mean f1': 0.9735631346702576, 'Val/mean precision': 0.9746200442314148, 'Val/mean recall': 0.9725084900856018, 'Val/mean hd95_metric': 5.065245628356934} +Epoch [2685/4000] Training [1/16] Loss: 0.00318 +Epoch [2685/4000] Training [2/16] Loss: 0.00480 +Epoch [2685/4000] Training [3/16] Loss: 0.00436 +Epoch [2685/4000] Training [4/16] Loss: 0.00349 +Epoch [2685/4000] Training [5/16] Loss: 0.00454 +Epoch [2685/4000] Training [6/16] Loss: 0.00375 +Epoch [2685/4000] Training [7/16] Loss: 0.00462 +Epoch [2685/4000] Training [8/16] Loss: 0.00683 +Epoch [2685/4000] Training [9/16] Loss: 0.00369 +Epoch [2685/4000] Training [10/16] Loss: 0.00495 +Epoch [2685/4000] Training [11/16] Loss: 0.00328 +Epoch [2685/4000] Training [12/16] Loss: 0.00431 +Epoch [2685/4000] Training [13/16] Loss: 0.00546 +Epoch [2685/4000] Training [14/16] Loss: 0.00460 +Epoch [2685/4000] Training [15/16] Loss: 0.00366 +Epoch [2685/4000] Training [16/16] Loss: 0.00295 +Epoch [2685/4000] Training metric {'Train/mean dice_metric': 0.9969115257263184, 'Train/mean miou_metric': 0.9937325716018677, 'Train/mean f1': 0.9926160573959351, 'Train/mean precision': 0.9879734516143799, 'Train/mean recall': 0.9973025321960449, 'Train/mean hd95_metric': 1.0177727937698364} +Epoch [2685/4000] Validation [1/4] Loss: 0.66936 focal_loss 0.57325 dice_loss 0.09611 +Epoch [2685/4000] Validation [2/4] Loss: 0.87534 focal_loss 0.67833 dice_loss 0.19701 +Epoch [2685/4000] Validation [3/4] Loss: 0.27745 focal_loss 0.19434 dice_loss 0.08311 +Epoch [2685/4000] Validation [4/4] Loss: 0.65715 focal_loss 0.50505 dice_loss 0.15210 +Epoch [2685/4000] Validation metric {'Val/mean dice_metric': 0.9677330851554871, 'Val/mean miou_metric': 0.9514504671096802, 'Val/mean f1': 0.972436785697937, 'Val/mean precision': 0.9745940566062927, 'Val/mean recall': 0.9702890515327454, 'Val/mean hd95_metric': 5.394740104675293} +Cheakpoint... +Epoch [2685/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9677], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9677330851554871, 'Val/mean miou_metric': 0.9514504671096802, 'Val/mean f1': 0.972436785697937, 'Val/mean precision': 0.9745940566062927, 'Val/mean recall': 0.9702890515327454, 'Val/mean hd95_metric': 5.394740104675293} +Epoch [2686/4000] Training [1/16] Loss: 0.00488 +Epoch [2686/4000] Training [2/16] Loss: 0.00305 +Epoch [2686/4000] Training [3/16] Loss: 0.00395 +Epoch [2686/4000] Training [4/16] Loss: 0.00429 +Epoch [2686/4000] Training [5/16] Loss: 0.00460 +Epoch [2686/4000] Training [6/16] Loss: 0.00384 +Epoch [2686/4000] Training [7/16] Loss: 0.00351 +Epoch [2686/4000] Training [8/16] Loss: 0.00279 +Epoch [2686/4000] Training [9/16] Loss: 0.00475 +Epoch [2686/4000] Training [10/16] Loss: 0.00372 +Epoch [2686/4000] Training [11/16] Loss: 0.00397 +Epoch [2686/4000] Training [12/16] Loss: 0.00433 +Epoch [2686/4000] Training [13/16] Loss: 0.00337 +Epoch [2686/4000] Training [14/16] Loss: 0.00451 +Epoch [2686/4000] Training [15/16] Loss: 0.00320 +Epoch [2686/4000] Training [16/16] Loss: 0.00337 +Epoch [2686/4000] Training metric {'Train/mean dice_metric': 0.9976656436920166, 'Train/mean miou_metric': 0.995060384273529, 'Train/mean f1': 0.9927551746368408, 'Train/mean precision': 0.9880900382995605, 'Train/mean recall': 0.9974645376205444, 'Train/mean hd95_metric': 0.8979347944259644} +Epoch [2686/4000] Validation [1/4] Loss: 0.39547 focal_loss 0.31607 dice_loss 0.07940 +Epoch [2686/4000] Validation [2/4] Loss: 0.97197 focal_loss 0.69851 dice_loss 0.27346 +Epoch [2686/4000] Validation [3/4] Loss: 0.30037 focal_loss 0.21519 dice_loss 0.08518 +Epoch [2686/4000] Validation [4/4] Loss: 0.28029 focal_loss 0.19794 dice_loss 0.08235 +Epoch [2686/4000] Validation metric {'Val/mean dice_metric': 0.9706363677978516, 'Val/mean miou_metric': 0.9559468030929565, 'Val/mean f1': 0.9748400449752808, 'Val/mean precision': 0.9747302532196045, 'Val/mean recall': 0.9749497771263123, 'Val/mean hd95_metric': 4.9556803703308105} +Cheakpoint... +Epoch [2686/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9706], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9706363677978516, 'Val/mean miou_metric': 0.9559468030929565, 'Val/mean f1': 0.9748400449752808, 'Val/mean precision': 0.9747302532196045, 'Val/mean recall': 0.9749497771263123, 'Val/mean hd95_metric': 4.9556803703308105} +Epoch [2687/4000] Training [1/16] Loss: 0.00417 +Epoch [2687/4000] Training [2/16] Loss: 0.00476 +Epoch [2687/4000] Training [3/16] Loss: 0.00264 +Epoch [2687/4000] Training [4/16] Loss: 0.00346 +Epoch [2687/4000] Training [5/16] Loss: 0.00449 +Epoch [2687/4000] Training [6/16] Loss: 0.00391 +Epoch [2687/4000] Training [7/16] Loss: 0.00405 +Epoch [2687/4000] Training [8/16] Loss: 0.00482 +Epoch [2687/4000] Training [9/16] Loss: 0.00354 +Epoch [2687/4000] Training [10/16] Loss: 0.00495 +Epoch [2687/4000] Training [11/16] Loss: 0.00391 +Epoch [2687/4000] Training [12/16] Loss: 0.00311 +Epoch [2687/4000] Training [13/16] Loss: 0.00386 +Epoch [2687/4000] Training [14/16] Loss: 0.00344 +Epoch [2687/4000] Training [15/16] Loss: 0.00292 +Epoch [2687/4000] Training [16/16] Loss: 0.00336 +Epoch [2687/4000] Training metric {'Train/mean dice_metric': 0.9978379011154175, 'Train/mean miou_metric': 0.995414137840271, 'Train/mean f1': 0.9930687546730042, 'Train/mean precision': 0.9884804487228394, 'Train/mean recall': 0.9976998567581177, 'Train/mean hd95_metric': 0.8620948791503906} +Epoch [2687/4000] Validation [1/4] Loss: 0.39341 focal_loss 0.31481 dice_loss 0.07860 +Epoch [2687/4000] Validation [2/4] Loss: 0.77680 focal_loss 0.59020 dice_loss 0.18660 +Epoch [2687/4000] Validation [3/4] Loss: 0.21467 focal_loss 0.15942 dice_loss 0.05525 +Epoch [2687/4000] Validation [4/4] Loss: 0.38006 focal_loss 0.27480 dice_loss 0.10525 +Epoch [2687/4000] Validation metric {'Val/mean dice_metric': 0.9704713821411133, 'Val/mean miou_metric': 0.9554654955863953, 'Val/mean f1': 0.9742334485054016, 'Val/mean precision': 0.9752351641654968, 'Val/mean recall': 0.9732336401939392, 'Val/mean hd95_metric': 4.8316144943237305} +Cheakpoint... +Epoch [2687/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704713821411133, 'Val/mean miou_metric': 0.9554654955863953, 'Val/mean f1': 0.9742334485054016, 'Val/mean precision': 0.9752351641654968, 'Val/mean recall': 0.9732336401939392, 'Val/mean hd95_metric': 4.8316144943237305} +Epoch [2688/4000] Training [1/16] Loss: 0.00419 +Epoch [2688/4000] Training [2/16] Loss: 0.00417 +Epoch [2688/4000] Training [3/16] Loss: 0.00370 +Epoch [2688/4000] Training [4/16] Loss: 0.00419 +Epoch [2688/4000] Training [5/16] Loss: 0.00429 +Epoch [2688/4000] Training [6/16] Loss: 0.00399 +Epoch [2688/4000] Training [7/16] Loss: 0.00301 +Epoch [2688/4000] Training [8/16] Loss: 0.00344 +Epoch [2688/4000] Training [9/16] Loss: 0.00392 +Epoch [2688/4000] Training [10/16] Loss: 0.00461 +Epoch [2688/4000] Training [11/16] Loss: 0.00357 +Epoch [2688/4000] Training [12/16] Loss: 0.00245 +Epoch [2688/4000] Training [13/16] Loss: 0.00451 +Epoch [2688/4000] Training [14/16] Loss: 0.00371 +Epoch [2688/4000] Training [15/16] Loss: 0.00370 +Epoch [2688/4000] Training [16/16] Loss: 0.00384 +Epoch [2688/4000] Training metric {'Train/mean dice_metric': 0.997698187828064, 'Train/mean miou_metric': 0.9951143860816956, 'Train/mean f1': 0.9927867650985718, 'Train/mean precision': 0.9880675673484802, 'Train/mean recall': 0.9975513219833374, 'Train/mean hd95_metric': 0.8902620077133179} +Epoch [2688/4000] Validation [1/4] Loss: 0.42407 focal_loss 0.34168 dice_loss 0.08239 +Epoch [2688/4000] Validation [2/4] Loss: 1.07436 focal_loss 0.88459 dice_loss 0.18977 +Epoch [2688/4000] Validation [3/4] Loss: 0.23283 focal_loss 0.17342 dice_loss 0.05941 +Epoch [2688/4000] Validation [4/4] Loss: 0.46508 focal_loss 0.33344 dice_loss 0.13164 +Epoch [2688/4000] Validation metric {'Val/mean dice_metric': 0.9701582193374634, 'Val/mean miou_metric': 0.9556359052658081, 'Val/mean f1': 0.974751353263855, 'Val/mean precision': 0.9751079082489014, 'Val/mean recall': 0.9743950366973877, 'Val/mean hd95_metric': 4.7567243576049805} +Cheakpoint... +Epoch [2688/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701582193374634, 'Val/mean miou_metric': 0.9556359052658081, 'Val/mean f1': 0.974751353263855, 'Val/mean precision': 0.9751079082489014, 'Val/mean recall': 0.9743950366973877, 'Val/mean hd95_metric': 4.7567243576049805} +Epoch [2689/4000] Training [1/16] Loss: 0.00462 +Epoch [2689/4000] Training [2/16] Loss: 0.00301 +Epoch [2689/4000] Training [3/16] Loss: 0.00264 +Epoch [2689/4000] Training [4/16] Loss: 0.00433 +Epoch [2689/4000] Training [5/16] Loss: 0.00371 +Epoch [2689/4000] Training [6/16] Loss: 0.00379 +Epoch [2689/4000] Training [7/16] Loss: 0.00325 +Epoch [2689/4000] Training [8/16] Loss: 0.00460 +Epoch [2689/4000] Training [9/16] Loss: 0.00394 +Epoch [2689/4000] Training [10/16] Loss: 0.00371 +Epoch [2689/4000] Training [11/16] Loss: 0.00376 +Epoch [2689/4000] Training [12/16] Loss: 0.00237 +Epoch [2689/4000] Training [13/16] Loss: 0.00329 +Epoch [2689/4000] Training [14/16] Loss: 0.00352 +Epoch [2689/4000] Training [15/16] Loss: 0.00308 +Epoch [2689/4000] Training [16/16] Loss: 0.00305 +Epoch [2689/4000] Training metric {'Train/mean dice_metric': 0.9978498220443726, 'Train/mean miou_metric': 0.9954268336296082, 'Train/mean f1': 0.9929827451705933, 'Train/mean precision': 0.9883248805999756, 'Train/mean recall': 0.9976846575737, 'Train/mean hd95_metric': 0.8835791945457458} +Epoch [2689/4000] Validation [1/4] Loss: 0.36940 focal_loss 0.29567 dice_loss 0.07373 +Epoch [2689/4000] Validation [2/4] Loss: 1.29726 focal_loss 1.10618 dice_loss 0.19108 +Epoch [2689/4000] Validation [3/4] Loss: 0.40005 focal_loss 0.29884 dice_loss 0.10121 +Epoch [2689/4000] Validation [4/4] Loss: 0.41269 focal_loss 0.29781 dice_loss 0.11488 +Epoch [2689/4000] Validation metric {'Val/mean dice_metric': 0.9711869955062866, 'Val/mean miou_metric': 0.9562435150146484, 'Val/mean f1': 0.974729597568512, 'Val/mean precision': 0.9747104048728943, 'Val/mean recall': 0.9747487306594849, 'Val/mean hd95_metric': 4.934628486633301} +Cheakpoint... +Epoch [2689/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711869955062866, 'Val/mean miou_metric': 0.9562435150146484, 'Val/mean f1': 0.974729597568512, 'Val/mean precision': 0.9747104048728943, 'Val/mean recall': 0.9747487306594849, 'Val/mean hd95_metric': 4.934628486633301} +Epoch [2690/4000] Training [1/16] Loss: 0.00360 +Epoch [2690/4000] Training [2/16] Loss: 0.00293 +Epoch [2690/4000] Training [3/16] Loss: 0.00269 +Epoch [2690/4000] Training [4/16] Loss: 0.00375 +Epoch [2690/4000] Training [5/16] Loss: 0.00324 +Epoch [2690/4000] Training [6/16] Loss: 0.00490 +Epoch [2690/4000] Training [7/16] Loss: 0.00658 +Epoch [2690/4000] Training [8/16] Loss: 0.00401 +Epoch [2690/4000] Training [9/16] Loss: 0.00235 +Epoch [2690/4000] Training [10/16] Loss: 0.00419 +Epoch [2690/4000] Training [11/16] Loss: 0.00366 +Epoch [2690/4000] Training [12/16] Loss: 0.00480 +Epoch [2690/4000] Training [13/16] Loss: 0.00427 +Epoch [2690/4000] Training [14/16] Loss: 0.00426 +Epoch [2690/4000] Training [15/16] Loss: 0.00580 +Epoch [2690/4000] Training [16/16] Loss: 0.00343 +Epoch [2690/4000] Training metric {'Train/mean dice_metric': 0.9976559281349182, 'Train/mean miou_metric': 0.9950548410415649, 'Train/mean f1': 0.9929515719413757, 'Train/mean precision': 0.9883943200111389, 'Train/mean recall': 0.9975510835647583, 'Train/mean hd95_metric': 0.8779903650283813} +Epoch [2690/4000] Validation [1/4] Loss: 0.51863 focal_loss 0.43185 dice_loss 0.08678 +Epoch [2690/4000] Validation [2/4] Loss: 1.08474 focal_loss 0.81396 dice_loss 0.27078 +Epoch [2690/4000] Validation [3/4] Loss: 0.41505 focal_loss 0.32265 dice_loss 0.09240 +Epoch [2690/4000] Validation [4/4] Loss: 0.26691 focal_loss 0.17479 dice_loss 0.09213 +Epoch [2690/4000] Validation metric {'Val/mean dice_metric': 0.9693998098373413, 'Val/mean miou_metric': 0.9543710947036743, 'Val/mean f1': 0.9739539623260498, 'Val/mean precision': 0.9741936326026917, 'Val/mean recall': 0.9737144112586975, 'Val/mean hd95_metric': 5.280183792114258} +Cheakpoint... +Epoch [2690/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9694], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9693998098373413, 'Val/mean miou_metric': 0.9543710947036743, 'Val/mean f1': 0.9739539623260498, 'Val/mean precision': 0.9741936326026917, 'Val/mean recall': 0.9737144112586975, 'Val/mean hd95_metric': 5.280183792114258} +Epoch [2691/4000] Training [1/16] Loss: 0.00271 +Epoch [2691/4000] Training [2/16] Loss: 0.00439 +Epoch [2691/4000] Training [3/16] Loss: 0.00279 +Epoch [2691/4000] Training [4/16] Loss: 0.00461 +Epoch [2691/4000] Training [5/16] Loss: 0.00265 +Epoch [2691/4000] Training [6/16] Loss: 0.00547 +Epoch [2691/4000] Training [7/16] Loss: 0.00309 +Epoch [2691/4000] Training [8/16] Loss: 0.00251 +Epoch [2691/4000] Training [9/16] Loss: 0.00426 +Epoch [2691/4000] Training [10/16] Loss: 0.00340 +Epoch [2691/4000] Training [11/16] Loss: 0.00443 +Epoch [2691/4000] Training [12/16] Loss: 0.00345 +Epoch [2691/4000] Training [13/16] Loss: 0.00367 +Epoch [2691/4000] Training [14/16] Loss: 0.00371 +Epoch [2691/4000] Training [15/16] Loss: 0.00421 +Epoch [2691/4000] Training [16/16] Loss: 0.00398 +Epoch [2691/4000] Training metric {'Train/mean dice_metric': 0.997481107711792, 'Train/mean miou_metric': 0.9947226047515869, 'Train/mean f1': 0.9928975701332092, 'Train/mean precision': 0.9884083271026611, 'Train/mean recall': 0.997427761554718, 'Train/mean hd95_metric': 0.9594818949699402} +Epoch [2691/4000] Validation [1/4] Loss: 0.37894 focal_loss 0.30883 dice_loss 0.07011 +Epoch [2691/4000] Validation [2/4] Loss: 0.91633 focal_loss 0.72569 dice_loss 0.19064 +Epoch [2691/4000] Validation [3/4] Loss: 0.47495 focal_loss 0.38042 dice_loss 0.09453 +Epoch [2691/4000] Validation [4/4] Loss: 0.34334 focal_loss 0.23498 dice_loss 0.10836 +Epoch [2691/4000] Validation metric {'Val/mean dice_metric': 0.9729024767875671, 'Val/mean miou_metric': 0.9582897424697876, 'Val/mean f1': 0.9757872223854065, 'Val/mean precision': 0.9738700985908508, 'Val/mean recall': 0.9777120351791382, 'Val/mean hd95_metric': 4.861888408660889} +Cheakpoint... +Epoch [2691/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729024767875671, 'Val/mean miou_metric': 0.9582897424697876, 'Val/mean f1': 0.9757872223854065, 'Val/mean precision': 0.9738700985908508, 'Val/mean recall': 0.9777120351791382, 'Val/mean hd95_metric': 4.861888408660889} +Epoch [2692/4000] Training [1/16] Loss: 0.00474 +Epoch [2692/4000] Training [2/16] Loss: 0.00345 +Epoch [2692/4000] Training [3/16] Loss: 0.00402 +Epoch [2692/4000] Training [4/16] Loss: 0.00237 +Epoch [2692/4000] Training [5/16] Loss: 0.00481 +Epoch [2692/4000] Training [6/16] Loss: 0.00325 +Epoch [2692/4000] Training [7/16] Loss: 0.00277 +Epoch [2692/4000] Training [8/16] Loss: 0.00471 +Epoch [2692/4000] Training [9/16] Loss: 0.00329 +Epoch [2692/4000] Training [10/16] Loss: 0.00503 +Epoch [2692/4000] Training [11/16] Loss: 0.00355 +Epoch [2692/4000] Training [12/16] Loss: 0.00348 +Epoch [2692/4000] Training [13/16] Loss: 0.00369 +Epoch [2692/4000] Training [14/16] Loss: 0.00312 +Epoch [2692/4000] Training [15/16] Loss: 0.00398 +Epoch [2692/4000] Training [16/16] Loss: 0.00409 +Epoch [2692/4000] Training metric {'Train/mean dice_metric': 0.9976665377616882, 'Train/mean miou_metric': 0.9950293302536011, 'Train/mean f1': 0.9924867749214172, 'Train/mean precision': 0.9875890612602234, 'Train/mean recall': 0.9974333047866821, 'Train/mean hd95_metric': 0.9212035536766052} +Epoch [2692/4000] Validation [1/4] Loss: 0.37075 focal_loss 0.30227 dice_loss 0.06848 +Epoch [2692/4000] Validation [2/4] Loss: 0.40936 focal_loss 0.29660 dice_loss 0.11276 +Epoch [2692/4000] Validation [3/4] Loss: 0.46507 focal_loss 0.36311 dice_loss 0.10196 +Epoch [2692/4000] Validation [4/4] Loss: 0.28853 focal_loss 0.20014 dice_loss 0.08839 +Epoch [2692/4000] Validation metric {'Val/mean dice_metric': 0.9744073748588562, 'Val/mean miou_metric': 0.9595152139663696, 'Val/mean f1': 0.9757798314094543, 'Val/mean precision': 0.9727303385734558, 'Val/mean recall': 0.978848397731781, 'Val/mean hd95_metric': 5.022384166717529} +Cheakpoint... +Epoch [2692/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744073748588562, 'Val/mean miou_metric': 0.9595152139663696, 'Val/mean f1': 0.9757798314094543, 'Val/mean precision': 0.9727303385734558, 'Val/mean recall': 0.978848397731781, 'Val/mean hd95_metric': 5.022384166717529} +Epoch [2693/4000] Training [1/16] Loss: 0.00402 +Epoch [2693/4000] Training [2/16] Loss: 0.00403 +Epoch [2693/4000] Training [3/16] Loss: 0.00468 +Epoch [2693/4000] Training [4/16] Loss: 0.00460 +Epoch [2693/4000] Training [5/16] Loss: 0.00477 +Epoch [2693/4000] Training [6/16] Loss: 0.00368 +Epoch [2693/4000] Training [7/16] Loss: 0.00414 +Epoch [2693/4000] Training [8/16] Loss: 0.00355 +Epoch [2693/4000] Training [9/16] Loss: 0.00335 +Epoch [2693/4000] Training [10/16] Loss: 0.00264 +Epoch [2693/4000] Training [11/16] Loss: 0.00411 +Epoch [2693/4000] Training [12/16] Loss: 0.00390 +Epoch [2693/4000] Training [13/16] Loss: 0.00404 +Epoch [2693/4000] Training [14/16] Loss: 0.00558 +Epoch [2693/4000] Training [15/16] Loss: 0.00456 +Epoch [2693/4000] Training [16/16] Loss: 0.00411 +Epoch [2693/4000] Training metric {'Train/mean dice_metric': 0.9975358247756958, 'Train/mean miou_metric': 0.9948122501373291, 'Train/mean f1': 0.9928086400032043, 'Train/mean precision': 0.9881951212882996, 'Train/mean recall': 0.9974654316902161, 'Train/mean hd95_metric': 0.9051879048347473} +Epoch [2693/4000] Validation [1/4] Loss: 0.37785 focal_loss 0.31009 dice_loss 0.06776 +Epoch [2693/4000] Validation [2/4] Loss: 0.39777 focal_loss 0.27887 dice_loss 0.11890 +Epoch [2693/4000] Validation [3/4] Loss: 0.43837 focal_loss 0.34833 dice_loss 0.09004 +Epoch [2693/4000] Validation [4/4] Loss: 0.32747 focal_loss 0.22221 dice_loss 0.10526 +Epoch [2693/4000] Validation metric {'Val/mean dice_metric': 0.9733379483222961, 'Val/mean miou_metric': 0.9582992792129517, 'Val/mean f1': 0.9754756093025208, 'Val/mean precision': 0.9716865420341492, 'Val/mean recall': 0.9792944192886353, 'Val/mean hd95_metric': 5.250974655151367} +Cheakpoint... +Epoch [2693/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733379483222961, 'Val/mean miou_metric': 0.9582992792129517, 'Val/mean f1': 0.9754756093025208, 'Val/mean precision': 0.9716865420341492, 'Val/mean recall': 0.9792944192886353, 'Val/mean hd95_metric': 5.250974655151367} +Epoch [2694/4000] Training [1/16] Loss: 0.00300 +Epoch [2694/4000] Training [2/16] Loss: 0.00379 +Epoch [2694/4000] Training [3/16] Loss: 0.00360 +Epoch [2694/4000] Training [4/16] Loss: 0.00473 +Epoch [2694/4000] Training [5/16] Loss: 0.00371 +Epoch [2694/4000] Training [6/16] Loss: 0.00346 +Epoch [2694/4000] Training [7/16] Loss: 0.00267 +Epoch [2694/4000] Training [8/16] Loss: 0.00329 +Epoch [2694/4000] Training [9/16] Loss: 0.00332 +Epoch [2694/4000] Training [10/16] Loss: 0.00441 +Epoch [2694/4000] Training [11/16] Loss: 0.00300 +Epoch [2694/4000] Training [12/16] Loss: 0.00331 +Epoch [2694/4000] Training [13/16] Loss: 0.00425 +Epoch [2694/4000] Training [14/16] Loss: 0.00268 +Epoch [2694/4000] Training [15/16] Loss: 0.00330 +Epoch [2694/4000] Training [16/16] Loss: 0.00404 +Epoch [2694/4000] Training metric {'Train/mean dice_metric': 0.9978929758071899, 'Train/mean miou_metric': 0.9955211877822876, 'Train/mean f1': 0.9932245016098022, 'Train/mean precision': 0.9887350797653198, 'Train/mean recall': 0.9977548718452454, 'Train/mean hd95_metric': 0.88498854637146} +Epoch [2694/4000] Validation [1/4] Loss: 0.37333 focal_loss 0.30391 dice_loss 0.06942 +Epoch [2694/4000] Validation [2/4] Loss: 1.01707 focal_loss 0.78161 dice_loss 0.23546 +Epoch [2694/4000] Validation [3/4] Loss: 0.44341 focal_loss 0.34903 dice_loss 0.09439 +Epoch [2694/4000] Validation [4/4] Loss: 0.37374 focal_loss 0.25672 dice_loss 0.11702 +Epoch [2694/4000] Validation metric {'Val/mean dice_metric': 0.9714452624320984, 'Val/mean miou_metric': 0.9565030932426453, 'Val/mean f1': 0.9750745296478271, 'Val/mean precision': 0.9728229641914368, 'Val/mean recall': 0.9773364663124084, 'Val/mean hd95_metric': 5.237088680267334} +Cheakpoint... +Epoch [2694/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714452624320984, 'Val/mean miou_metric': 0.9565030932426453, 'Val/mean f1': 0.9750745296478271, 'Val/mean precision': 0.9728229641914368, 'Val/mean recall': 0.9773364663124084, 'Val/mean hd95_metric': 5.237088680267334} +Epoch [2695/4000] Training [1/16] Loss: 0.00377 +Epoch [2695/4000] Training [2/16] Loss: 0.00303 +Epoch [2695/4000] Training [3/16] Loss: 0.00335 +Epoch [2695/4000] Training [4/16] Loss: 0.00315 +Epoch [2695/4000] Training [5/16] Loss: 0.00343 +Epoch [2695/4000] Training [6/16] Loss: 0.00309 +Epoch [2695/4000] Training [7/16] Loss: 0.00567 +Epoch [2695/4000] Training [8/16] Loss: 0.00440 +Epoch [2695/4000] Training [9/16] Loss: 0.00438 +Epoch [2695/4000] Training [10/16] Loss: 0.00297 +Epoch [2695/4000] Training [11/16] Loss: 0.00470 +Epoch [2695/4000] Training [12/16] Loss: 0.00399 +Epoch [2695/4000] Training [13/16] Loss: 0.00301 +Epoch [2695/4000] Training [14/16] Loss: 0.00507 +Epoch [2695/4000] Training [15/16] Loss: 0.00253 +Epoch [2695/4000] Training [16/16] Loss: 0.00496 +Epoch [2695/4000] Training metric {'Train/mean dice_metric': 0.9977309703826904, 'Train/mean miou_metric': 0.9951927065849304, 'Train/mean f1': 0.9928666949272156, 'Train/mean precision': 0.9882753491401672, 'Train/mean recall': 0.9975009560585022, 'Train/mean hd95_metric': 0.89847332239151} +Epoch [2695/4000] Validation [1/4] Loss: 0.35554 focal_loss 0.28940 dice_loss 0.06614 +Epoch [2695/4000] Validation [2/4] Loss: 0.36930 focal_loss 0.26519 dice_loss 0.10411 +Epoch [2695/4000] Validation [3/4] Loss: 0.45774 focal_loss 0.36334 dice_loss 0.09440 +Epoch [2695/4000] Validation [4/4] Loss: 0.34181 focal_loss 0.23876 dice_loss 0.10306 +Epoch [2695/4000] Validation metric {'Val/mean dice_metric': 0.9734552502632141, 'Val/mean miou_metric': 0.9586801528930664, 'Val/mean f1': 0.9754879474639893, 'Val/mean precision': 0.9732808470726013, 'Val/mean recall': 0.9777051210403442, 'Val/mean hd95_metric': 5.236141681671143} +Cheakpoint... +Epoch [2695/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734552502632141, 'Val/mean miou_metric': 0.9586801528930664, 'Val/mean f1': 0.9754879474639893, 'Val/mean precision': 0.9732808470726013, 'Val/mean recall': 0.9777051210403442, 'Val/mean hd95_metric': 5.236141681671143} +Epoch [2696/4000] Training [1/16] Loss: 0.00286 +Epoch [2696/4000] Training [2/16] Loss: 0.00447 +Epoch [2696/4000] Training [3/16] Loss: 0.00345 +Epoch [2696/4000] Training [4/16] Loss: 0.00512 +Epoch [2696/4000] Training [5/16] Loss: 0.00353 +Epoch [2696/4000] Training [6/16] Loss: 0.00375 +Epoch [2696/4000] Training [7/16] Loss: 0.00349 +Epoch [2696/4000] Training [8/16] Loss: 0.00392 +Epoch [2696/4000] Training [9/16] Loss: 0.00471 +Epoch [2696/4000] Training [10/16] Loss: 0.00378 +Epoch [2696/4000] Training [11/16] Loss: 0.00475 +Epoch [2696/4000] Training [12/16] Loss: 0.00365 +Epoch [2696/4000] Training [13/16] Loss: 0.00459 +Epoch [2696/4000] Training [14/16] Loss: 0.00332 +Epoch [2696/4000] Training [15/16] Loss: 0.00482 +Epoch [2696/4000] Training [16/16] Loss: 0.00493 +Epoch [2696/4000] Training metric {'Train/mean dice_metric': 0.9975825548171997, 'Train/mean miou_metric': 0.9949069023132324, 'Train/mean f1': 0.9930108189582825, 'Train/mean precision': 0.9884887337684631, 'Train/mean recall': 0.9975743889808655, 'Train/mean hd95_metric': 0.9025245904922485} +Epoch [2696/4000] Validation [1/4] Loss: 0.41799 focal_loss 0.34728 dice_loss 0.07070 +Epoch [2696/4000] Validation [2/4] Loss: 0.32208 focal_loss 0.23085 dice_loss 0.09123 +Epoch [2696/4000] Validation [3/4] Loss: 0.46623 focal_loss 0.36647 dice_loss 0.09977 +Epoch [2696/4000] Validation [4/4] Loss: 0.26363 focal_loss 0.17810 dice_loss 0.08553 +Epoch [2696/4000] Validation metric {'Val/mean dice_metric': 0.9741438031196594, 'Val/mean miou_metric': 0.9591309428215027, 'Val/mean f1': 0.9760617613792419, 'Val/mean precision': 0.9740588068962097, 'Val/mean recall': 0.978073000907898, 'Val/mean hd95_metric': 4.972325801849365} +Cheakpoint... +Epoch [2696/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741438031196594, 'Val/mean miou_metric': 0.9591309428215027, 'Val/mean f1': 0.9760617613792419, 'Val/mean precision': 0.9740588068962097, 'Val/mean recall': 0.978073000907898, 'Val/mean hd95_metric': 4.972325801849365} +Epoch [2697/4000] Training [1/16] Loss: 0.00290 +Epoch [2697/4000] Training [2/16] Loss: 0.00399 +Epoch [2697/4000] Training [3/16] Loss: 0.00402 +Epoch [2697/4000] Training [4/16] Loss: 0.00528 +Epoch [2697/4000] Training [5/16] Loss: 0.00333 +Epoch [2697/4000] Training [6/16] Loss: 0.00302 +Epoch [2697/4000] Training [7/16] Loss: 0.00254 +Epoch [2697/4000] Training [8/16] Loss: 0.00604 +Epoch [2697/4000] Training [9/16] Loss: 0.00426 +Epoch [2697/4000] Training [10/16] Loss: 0.00405 +Epoch [2697/4000] Training [11/16] Loss: 0.00379 +Epoch [2697/4000] Training [12/16] Loss: 0.00411 +Epoch [2697/4000] Training [13/16] Loss: 0.00383 +Epoch [2697/4000] Training [14/16] Loss: 0.00392 +Epoch [2697/4000] Training [15/16] Loss: 0.00322 +Epoch [2697/4000] Training [16/16] Loss: 0.00276 +Epoch [2697/4000] Training metric {'Train/mean dice_metric': 0.9975687265396118, 'Train/mean miou_metric': 0.9948827028274536, 'Train/mean f1': 0.9929041266441345, 'Train/mean precision': 0.9883974194526672, 'Train/mean recall': 0.9974520802497864, 'Train/mean hd95_metric': 0.9042015075683594} +Epoch [2697/4000] Validation [1/4] Loss: 0.38906 focal_loss 0.32420 dice_loss 0.06486 +Epoch [2697/4000] Validation [2/4] Loss: 0.32496 focal_loss 0.23082 dice_loss 0.09413 +Epoch [2697/4000] Validation [3/4] Loss: 0.46084 focal_loss 0.36156 dice_loss 0.09928 +Epoch [2697/4000] Validation [4/4] Loss: 0.29958 focal_loss 0.21098 dice_loss 0.08859 +Epoch [2697/4000] Validation metric {'Val/mean dice_metric': 0.9733512997627258, 'Val/mean miou_metric': 0.9584996104240417, 'Val/mean f1': 0.9755370616912842, 'Val/mean precision': 0.9729478359222412, 'Val/mean recall': 0.978140115737915, 'Val/mean hd95_metric': 5.270291328430176} +Cheakpoint... +Epoch [2697/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733512997627258, 'Val/mean miou_metric': 0.9584996104240417, 'Val/mean f1': 0.9755370616912842, 'Val/mean precision': 0.9729478359222412, 'Val/mean recall': 0.978140115737915, 'Val/mean hd95_metric': 5.270291328430176} +Epoch [2698/4000] Training [1/16] Loss: 0.00390 +Epoch [2698/4000] Training [2/16] Loss: 0.00299 +Epoch [2698/4000] Training [3/16] Loss: 0.00425 +Epoch [2698/4000] Training [4/16] Loss: 0.00329 +Epoch [2698/4000] Training [5/16] Loss: 0.00349 +Epoch [2698/4000] Training [6/16] Loss: 0.00311 +Epoch [2698/4000] Training [7/16] Loss: 0.00413 +Epoch [2698/4000] Training [8/16] Loss: 0.00466 +Epoch [2698/4000] Training [9/16] Loss: 0.00275 +Epoch [2698/4000] Training [10/16] Loss: 0.00556 +Epoch [2698/4000] Training [11/16] Loss: 0.00325 +Epoch [2698/4000] Training [12/16] Loss: 0.00615 +Epoch [2698/4000] Training [13/16] Loss: 0.00345 +Epoch [2698/4000] Training [14/16] Loss: 0.00319 +Epoch [2698/4000] Training [15/16] Loss: 0.00399 +Epoch [2698/4000] Training [16/16] Loss: 0.00520 +Epoch [2698/4000] Training metric {'Train/mean dice_metric': 0.9976260662078857, 'Train/mean miou_metric': 0.9949902296066284, 'Train/mean f1': 0.9929167032241821, 'Train/mean precision': 0.9882949590682983, 'Train/mean recall': 0.9975818991661072, 'Train/mean hd95_metric': 0.8809728622436523} +Epoch [2698/4000] Validation [1/4] Loss: 0.34320 focal_loss 0.28024 dice_loss 0.06297 +Epoch [2698/4000] Validation [2/4] Loss: 0.32049 focal_loss 0.22845 dice_loss 0.09204 +Epoch [2698/4000] Validation [3/4] Loss: 0.42519 focal_loss 0.32785 dice_loss 0.09734 +Epoch [2698/4000] Validation [4/4] Loss: 0.54954 focal_loss 0.39724 dice_loss 0.15230 +Epoch [2698/4000] Validation metric {'Val/mean dice_metric': 0.9738453030586243, 'Val/mean miou_metric': 0.9580771327018738, 'Val/mean f1': 0.9751171469688416, 'Val/mean precision': 0.9723393321037292, 'Val/mean recall': 0.9779108166694641, 'Val/mean hd95_metric': 5.193728923797607} +Cheakpoint... +Epoch [2698/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738453030586243, 'Val/mean miou_metric': 0.9580771327018738, 'Val/mean f1': 0.9751171469688416, 'Val/mean precision': 0.9723393321037292, 'Val/mean recall': 0.9779108166694641, 'Val/mean hd95_metric': 5.193728923797607} +Epoch [2699/4000] Training [1/16] Loss: 0.00370 +Epoch [2699/4000] Training [2/16] Loss: 0.00291 +Epoch [2699/4000] Training [3/16] Loss: 0.00368 +Epoch [2699/4000] Training [4/16] Loss: 0.00275 +Epoch [2699/4000] Training [5/16] Loss: 0.00343 +Epoch [2699/4000] Training [6/16] Loss: 0.00429 +Epoch [2699/4000] Training [7/16] Loss: 0.00420 +Epoch [2699/4000] Training [8/16] Loss: 0.00391 +Epoch [2699/4000] Training [9/16] Loss: 0.00301 +Epoch [2699/4000] Training [10/16] Loss: 0.00554 +Epoch [2699/4000] Training [11/16] Loss: 0.00345 +Epoch [2699/4000] Training [12/16] Loss: 0.00318 +Epoch [2699/4000] Training [13/16] Loss: 0.00421 +Epoch [2699/4000] Training [14/16] Loss: 0.00406 +Epoch [2699/4000] Training [15/16] Loss: 0.00444 +Epoch [2699/4000] Training [16/16] Loss: 0.00570 +Epoch [2699/4000] Training metric {'Train/mean dice_metric': 0.9977266788482666, 'Train/mean miou_metric': 0.995179295539856, 'Train/mean f1': 0.9929981827735901, 'Train/mean precision': 0.9884753227233887, 'Train/mean recall': 0.9975626468658447, 'Train/mean hd95_metric': 0.9019807577133179} +Epoch [2699/4000] Validation [1/4] Loss: 0.37002 focal_loss 0.30221 dice_loss 0.06781 +Epoch [2699/4000] Validation [2/4] Loss: 0.32749 focal_loss 0.23030 dice_loss 0.09719 +Epoch [2699/4000] Validation [3/4] Loss: 0.21322 focal_loss 0.15803 dice_loss 0.05519 +Epoch [2699/4000] Validation [4/4] Loss: 0.33894 focal_loss 0.23959 dice_loss 0.09935 +Epoch [2699/4000] Validation metric {'Val/mean dice_metric': 0.9729883074760437, 'Val/mean miou_metric': 0.9588363766670227, 'Val/mean f1': 0.9760861396789551, 'Val/mean precision': 0.974997878074646, 'Val/mean recall': 0.9771767258644104, 'Val/mean hd95_metric': 5.037037372589111} +Cheakpoint... +Epoch [2699/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729883074760437, 'Val/mean miou_metric': 0.9588363766670227, 'Val/mean f1': 0.9760861396789551, 'Val/mean precision': 0.974997878074646, 'Val/mean recall': 0.9771767258644104, 'Val/mean hd95_metric': 5.037037372589111} +Epoch [2700/4000] Training [1/16] Loss: 0.00331 +Epoch [2700/4000] Training [2/16] Loss: 0.00275 +Epoch [2700/4000] Training [3/16] Loss: 0.00318 +Epoch [2700/4000] Training [4/16] Loss: 0.00360 +Epoch [2700/4000] Training [5/16] Loss: 0.00306 +Epoch [2700/4000] Training [6/16] Loss: 0.00443 +Epoch [2700/4000] Training [7/16] Loss: 0.00338 +Epoch [2700/4000] Training [8/16] Loss: 0.00292 +Epoch [2700/4000] Training [9/16] Loss: 0.00429 +Epoch [2700/4000] Training [10/16] Loss: 0.00475 +Epoch [2700/4000] Training [11/16] Loss: 0.00416 +Epoch [2700/4000] Training [12/16] Loss: 0.00343 +Epoch [2700/4000] Training [13/16] Loss: 0.00370 +Epoch [2700/4000] Training [14/16] Loss: 0.00344 +Epoch [2700/4000] Training [15/16] Loss: 0.00354 +Epoch [2700/4000] Training [16/16] Loss: 0.00336 +Epoch [2700/4000] Training metric {'Train/mean dice_metric': 0.9976711869239807, 'Train/mean miou_metric': 0.9950808882713318, 'Train/mean f1': 0.993046224117279, 'Train/mean precision': 0.9885665774345398, 'Train/mean recall': 0.9975665807723999, 'Train/mean hd95_metric': 0.8877229690551758} +Epoch [2700/4000] Validation [1/4] Loss: 0.42265 focal_loss 0.34644 dice_loss 0.07621 +Epoch [2700/4000] Validation [2/4] Loss: 0.80419 focal_loss 0.59076 dice_loss 0.21343 +Epoch [2700/4000] Validation [3/4] Loss: 0.23960 focal_loss 0.17691 dice_loss 0.06269 +Epoch [2700/4000] Validation [4/4] Loss: 0.31886 focal_loss 0.22883 dice_loss 0.09003 +Epoch [2700/4000] Validation metric {'Val/mean dice_metric': 0.9719645380973816, 'Val/mean miou_metric': 0.9571453332901001, 'Val/mean f1': 0.9749722480773926, 'Val/mean precision': 0.9743544459342957, 'Val/mean recall': 0.9755907654762268, 'Val/mean hd95_metric': 5.590334415435791} +Cheakpoint... +Epoch [2700/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719645380973816, 'Val/mean miou_metric': 0.9571453332901001, 'Val/mean f1': 0.9749722480773926, 'Val/mean precision': 0.9743544459342957, 'Val/mean recall': 0.9755907654762268, 'Val/mean hd95_metric': 5.590334415435791} +Epoch [2701/4000] Training [1/16] Loss: 0.00377 +Epoch [2701/4000] Training [2/16] Loss: 0.00389 +Epoch [2701/4000] Training [3/16] Loss: 0.00305 +Epoch [2701/4000] Training [4/16] Loss: 0.00338 +Epoch [2701/4000] Training [5/16] Loss: 0.00312 +Epoch [2701/4000] Training [6/16] Loss: 0.00294 +Epoch [2701/4000] Training [7/16] Loss: 0.00456 +Epoch [2701/4000] Training [8/16] Loss: 0.00349 +Epoch [2701/4000] Training [9/16] Loss: 0.00311 +Epoch [2701/4000] Training [10/16] Loss: 0.00297 +Epoch [2701/4000] Training [11/16] Loss: 0.00577 +Epoch [2701/4000] Training [12/16] Loss: 0.00431 +Epoch [2701/4000] Training [13/16] Loss: 0.00424 +Epoch [2701/4000] Training [14/16] Loss: 0.00325 +Epoch [2701/4000] Training [15/16] Loss: 0.00391 +Epoch [2701/4000] Training [16/16] Loss: 0.00389 +Epoch [2701/4000] Training metric {'Train/mean dice_metric': 0.997802734375, 'Train/mean miou_metric': 0.9953382015228271, 'Train/mean f1': 0.9930198788642883, 'Train/mean precision': 0.9884112477302551, 'Train/mean recall': 0.9976716637611389, 'Train/mean hd95_metric': 0.88254714012146} +Epoch [2701/4000] Validation [1/4] Loss: 0.34788 focal_loss 0.27916 dice_loss 0.06872 +Epoch [2701/4000] Validation [2/4] Loss: 0.37358 focal_loss 0.25722 dice_loss 0.11636 +Epoch [2701/4000] Validation [3/4] Loss: 0.44056 focal_loss 0.34804 dice_loss 0.09252 +Epoch [2701/4000] Validation [4/4] Loss: 0.37376 focal_loss 0.25862 dice_loss 0.11514 +Epoch [2701/4000] Validation metric {'Val/mean dice_metric': 0.9736669659614563, 'Val/mean miou_metric': 0.9584099650382996, 'Val/mean f1': 0.9753605723381042, 'Val/mean precision': 0.9728838801383972, 'Val/mean recall': 0.9778500199317932, 'Val/mean hd95_metric': 4.78798246383667} +Cheakpoint... +Epoch [2701/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736669659614563, 'Val/mean miou_metric': 0.9584099650382996, 'Val/mean f1': 0.9753605723381042, 'Val/mean precision': 0.9728838801383972, 'Val/mean recall': 0.9778500199317932, 'Val/mean hd95_metric': 4.78798246383667} +Epoch [2702/4000] Training [1/16] Loss: 0.00294 +Epoch [2702/4000] Training [2/16] Loss: 0.00510 +Epoch [2702/4000] Training [3/16] Loss: 0.00276 +Epoch [2702/4000] Training [4/16] Loss: 0.00417 +Epoch [2702/4000] Training [5/16] Loss: 0.00316 +Epoch [2702/4000] Training [6/16] Loss: 0.00488 +Epoch [2702/4000] Training [7/16] Loss: 0.00383 +Epoch [2702/4000] Training [8/16] Loss: 0.00506 +Epoch [2702/4000] Training [9/16] Loss: 0.00363 +Epoch [2702/4000] Training [10/16] Loss: 0.00283 +Epoch [2702/4000] Training [11/16] Loss: 0.00337 +Epoch [2702/4000] Training [12/16] Loss: 0.00333 +Epoch [2702/4000] Training [13/16] Loss: 0.00584 +Epoch [2702/4000] Training [14/16] Loss: 0.00527 +Epoch [2702/4000] Training [15/16] Loss: 0.00344 +Epoch [2702/4000] Training [16/16] Loss: 0.00321 +Epoch [2702/4000] Training metric {'Train/mean dice_metric': 0.9976450204849243, 'Train/mean miou_metric': 0.9950315952301025, 'Train/mean f1': 0.9929350018501282, 'Train/mean precision': 0.9884337186813354, 'Train/mean recall': 0.9974774122238159, 'Train/mean hd95_metric': 0.9014925360679626} +Epoch [2702/4000] Validation [1/4] Loss: 0.31820 focal_loss 0.25632 dice_loss 0.06187 +Epoch [2702/4000] Validation [2/4] Loss: 0.94152 focal_loss 0.70953 dice_loss 0.23199 +Epoch [2702/4000] Validation [3/4] Loss: 0.42008 focal_loss 0.32965 dice_loss 0.09043 +Epoch [2702/4000] Validation [4/4] Loss: 0.30907 focal_loss 0.21381 dice_loss 0.09527 +Epoch [2702/4000] Validation metric {'Val/mean dice_metric': 0.9737838506698608, 'Val/mean miou_metric': 0.9588965177536011, 'Val/mean f1': 0.9757679104804993, 'Val/mean precision': 0.9733973145484924, 'Val/mean recall': 0.9781500101089478, 'Val/mean hd95_metric': 5.060235977172852} +Cheakpoint... +Epoch [2702/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737838506698608, 'Val/mean miou_metric': 0.9588965177536011, 'Val/mean f1': 0.9757679104804993, 'Val/mean precision': 0.9733973145484924, 'Val/mean recall': 0.9781500101089478, 'Val/mean hd95_metric': 5.060235977172852} +Epoch [2703/4000] Training [1/16] Loss: 0.00359 +Epoch [2703/4000] Training [2/16] Loss: 0.00376 +Epoch [2703/4000] Training [3/16] Loss: 0.00295 +Epoch [2703/4000] Training [4/16] Loss: 0.00415 +Epoch [2703/4000] Training [5/16] Loss: 0.00446 +Epoch [2703/4000] Training [6/16] Loss: 0.00366 +Epoch [2703/4000] Training [7/16] Loss: 0.00340 +Epoch [2703/4000] Training [8/16] Loss: 0.00372 +Epoch [2703/4000] Training [9/16] Loss: 0.00377 +Epoch [2703/4000] Training [10/16] Loss: 0.00466 +Epoch [2703/4000] Training [11/16] Loss: 0.00266 +Epoch [2703/4000] Training [12/16] Loss: 0.00351 +Epoch [2703/4000] Training [13/16] Loss: 0.00354 +Epoch [2703/4000] Training [14/16] Loss: 0.00450 +Epoch [2703/4000] Training [15/16] Loss: 0.00477 +Epoch [2703/4000] Training [16/16] Loss: 0.00472 +Epoch [2703/4000] Training metric {'Train/mean dice_metric': 0.9976723194122314, 'Train/mean miou_metric': 0.9950821399688721, 'Train/mean f1': 0.9929527044296265, 'Train/mean precision': 0.9883392453193665, 'Train/mean recall': 0.9976094961166382, 'Train/mean hd95_metric': 0.9017854928970337} +Epoch [2703/4000] Validation [1/4] Loss: 0.39980 focal_loss 0.33437 dice_loss 0.06543 +Epoch [2703/4000] Validation [2/4] Loss: 0.87893 focal_loss 0.69489 dice_loss 0.18404 +Epoch [2703/4000] Validation [3/4] Loss: 0.27167 focal_loss 0.19732 dice_loss 0.07436 +Epoch [2703/4000] Validation [4/4] Loss: 0.32916 focal_loss 0.22994 dice_loss 0.09922 +Epoch [2703/4000] Validation metric {'Val/mean dice_metric': 0.9716612100601196, 'Val/mean miou_metric': 0.9573192596435547, 'Val/mean f1': 0.9755988121032715, 'Val/mean precision': 0.973676860332489, 'Val/mean recall': 0.97752845287323, 'Val/mean hd95_metric': 5.15158224105835} +Cheakpoint... +Epoch [2703/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716612100601196, 'Val/mean miou_metric': 0.9573192596435547, 'Val/mean f1': 0.9755988121032715, 'Val/mean precision': 0.973676860332489, 'Val/mean recall': 0.97752845287323, 'Val/mean hd95_metric': 5.15158224105835} +Epoch [2704/4000] Training [1/16] Loss: 0.00312 +Epoch [2704/4000] Training [2/16] Loss: 0.00335 +Epoch [2704/4000] Training [3/16] Loss: 0.00560 +Epoch [2704/4000] Training [4/16] Loss: 0.00548 +Epoch [2704/4000] Training [5/16] Loss: 0.00284 +Epoch [2704/4000] Training [6/16] Loss: 0.00309 +Epoch [2704/4000] Training [7/16] Loss: 0.00508 +Epoch [2704/4000] Training [8/16] Loss: 0.00327 +Epoch [2704/4000] Training [9/16] Loss: 0.00411 +Epoch [2704/4000] Training [10/16] Loss: 0.00756 +Epoch [2704/4000] Training [11/16] Loss: 0.00394 +Epoch [2704/4000] Training [12/16] Loss: 0.00416 +Epoch [2704/4000] Training [13/16] Loss: 0.00442 +Epoch [2704/4000] Training [14/16] Loss: 0.00361 +Epoch [2704/4000] Training [15/16] Loss: 0.00417 +Epoch [2704/4000] Training [16/16] Loss: 0.00673 +Epoch [2704/4000] Training metric {'Train/mean dice_metric': 0.9974520206451416, 'Train/mean miou_metric': 0.9946563243865967, 'Train/mean f1': 0.9927939176559448, 'Train/mean precision': 0.9882597923278809, 'Train/mean recall': 0.9973697066307068, 'Train/mean hd95_metric': 0.9458572268486023} +Epoch [2704/4000] Validation [1/4] Loss: 0.46366 focal_loss 0.38334 dice_loss 0.08032 +Epoch [2704/4000] Validation [2/4] Loss: 0.47891 focal_loss 0.33472 dice_loss 0.14419 +Epoch [2704/4000] Validation [3/4] Loss: 0.49094 focal_loss 0.38762 dice_loss 0.10332 +Epoch [2704/4000] Validation [4/4] Loss: 0.31403 focal_loss 0.22089 dice_loss 0.09313 +Epoch [2704/4000] Validation metric {'Val/mean dice_metric': 0.9712093472480774, 'Val/mean miou_metric': 0.9560340642929077, 'Val/mean f1': 0.9744090437889099, 'Val/mean precision': 0.974271833896637, 'Val/mean recall': 0.9745463728904724, 'Val/mean hd95_metric': 5.27583122253418} +Cheakpoint... +Epoch [2704/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712093472480774, 'Val/mean miou_metric': 0.9560340642929077, 'Val/mean f1': 0.9744090437889099, 'Val/mean precision': 0.974271833896637, 'Val/mean recall': 0.9745463728904724, 'Val/mean hd95_metric': 5.27583122253418} +Epoch [2705/4000] Training [1/16] Loss: 0.00351 +Epoch [2705/4000] Training [2/16] Loss: 0.00526 +Epoch [2705/4000] Training [3/16] Loss: 0.00364 +Epoch [2705/4000] Training [4/16] Loss: 0.00530 +Epoch [2705/4000] Training [5/16] Loss: 0.00270 +Epoch [2705/4000] Training [6/16] Loss: 0.00366 +Epoch [2705/4000] Training [7/16] Loss: 0.00295 +Epoch [2705/4000] Training [8/16] Loss: 0.00330 +Epoch [2705/4000] Training [9/16] Loss: 0.00626 +Epoch [2705/4000] Training [10/16] Loss: 0.10164 +Epoch [2705/4000] Training [11/16] Loss: 0.00389 +Epoch [2705/4000] Training [12/16] Loss: 0.00403 +Epoch [2705/4000] Training [13/16] Loss: 0.00380 +Epoch [2705/4000] Training [14/16] Loss: 0.00331 +Epoch [2705/4000] Training [15/16] Loss: 0.00332 +Epoch [2705/4000] Training [16/16] Loss: 0.00342 +Epoch [2705/4000] Training metric {'Train/mean dice_metric': 0.9964789748191833, 'Train/mean miou_metric': 0.9935807585716248, 'Train/mean f1': 0.9927881360054016, 'Train/mean precision': 0.9883544445037842, 'Train/mean recall': 0.9972617030143738, 'Train/mean hd95_metric': 0.9235098958015442} +Epoch [2705/4000] Validation [1/4] Loss: 0.37588 focal_loss 0.30853 dice_loss 0.06734 +Epoch [2705/4000] Validation [2/4] Loss: 0.35092 focal_loss 0.25075 dice_loss 0.10017 +Epoch [2705/4000] Validation [3/4] Loss: 0.43104 focal_loss 0.33898 dice_loss 0.09207 +Epoch [2705/4000] Validation [4/4] Loss: 0.38895 focal_loss 0.27408 dice_loss 0.11488 +Epoch [2705/4000] Validation metric {'Val/mean dice_metric': 0.9728389978408813, 'Val/mean miou_metric': 0.9573667645454407, 'Val/mean f1': 0.9748867154121399, 'Val/mean precision': 0.9740240573883057, 'Val/mean recall': 0.9757509827613831, 'Val/mean hd95_metric': 5.099797248840332} +Cheakpoint... +Epoch [2705/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728389978408813, 'Val/mean miou_metric': 0.9573667645454407, 'Val/mean f1': 0.9748867154121399, 'Val/mean precision': 0.9740240573883057, 'Val/mean recall': 0.9757509827613831, 'Val/mean hd95_metric': 5.099797248840332} +Epoch [2706/4000] Training [1/16] Loss: 0.00380 +Epoch [2706/4000] Training [2/16] Loss: 0.00318 +Epoch [2706/4000] Training [3/16] Loss: 0.00477 +Epoch [2706/4000] Training [4/16] Loss: 0.00404 +Epoch [2706/4000] Training [5/16] Loss: 0.00454 +Epoch [2706/4000] Training [6/16] Loss: 0.00379 +Epoch [2706/4000] Training [7/16] Loss: 0.00376 +Epoch [2706/4000] Training [8/16] Loss: 0.00401 +Epoch [2706/4000] Training [9/16] Loss: 0.00616 +Epoch [2706/4000] Training [10/16] Loss: 0.00359 +Epoch [2706/4000] Training [11/16] Loss: 0.00404 +Epoch [2706/4000] Training [12/16] Loss: 0.00304 +Epoch [2706/4000] Training [13/16] Loss: 0.00321 +Epoch [2706/4000] Training [14/16] Loss: 0.00633 +Epoch [2706/4000] Training [15/16] Loss: 0.00396 +Epoch [2706/4000] Training [16/16] Loss: 0.00387 +Epoch [2706/4000] Training metric {'Train/mean dice_metric': 0.997246503829956, 'Train/mean miou_metric': 0.9942419528961182, 'Train/mean f1': 0.9926767349243164, 'Train/mean precision': 0.9881169199943542, 'Train/mean recall': 0.9972787499427795, 'Train/mean hd95_metric': 0.9296730160713196} +Epoch [2706/4000] Validation [1/4] Loss: 0.37806 focal_loss 0.31292 dice_loss 0.06514 +Epoch [2706/4000] Validation [2/4] Loss: 0.84205 focal_loss 0.67355 dice_loss 0.16850 +Epoch [2706/4000] Validation [3/4] Loss: 0.44399 focal_loss 0.35517 dice_loss 0.08882 +Epoch [2706/4000] Validation [4/4] Loss: 0.29347 focal_loss 0.21164 dice_loss 0.08183 +Epoch [2706/4000] Validation metric {'Val/mean dice_metric': 0.9722839593887329, 'Val/mean miou_metric': 0.9575067758560181, 'Val/mean f1': 0.974809467792511, 'Val/mean precision': 0.9721519947052002, 'Val/mean recall': 0.9774815440177917, 'Val/mean hd95_metric': 5.450162410736084} +Cheakpoint... +Epoch [2706/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722839593887329, 'Val/mean miou_metric': 0.9575067758560181, 'Val/mean f1': 0.974809467792511, 'Val/mean precision': 0.9721519947052002, 'Val/mean recall': 0.9774815440177917, 'Val/mean hd95_metric': 5.450162410736084} +Epoch [2707/4000] Training [1/16] Loss: 0.00304 +Epoch [2707/4000] Training [2/16] Loss: 0.00298 +Epoch [2707/4000] Training [3/16] Loss: 0.00362 +Epoch [2707/4000] Training [4/16] Loss: 0.00552 +Epoch [2707/4000] Training [5/16] Loss: 0.00561 +Epoch [2707/4000] Training [6/16] Loss: 0.00352 +Epoch [2707/4000] Training [7/16] Loss: 0.00437 +Epoch [2707/4000] Training [8/16] Loss: 0.00357 +Epoch [2707/4000] Training [9/16] Loss: 0.00563 +Epoch [2707/4000] Training [10/16] Loss: 0.00502 +Epoch [2707/4000] Training [11/16] Loss: 0.00254 +Epoch [2707/4000] Training [12/16] Loss: 0.00357 +Epoch [2707/4000] Training [13/16] Loss: 0.00376 +Epoch [2707/4000] Training [14/16] Loss: 0.00446 +Epoch [2707/4000] Training [15/16] Loss: 0.00289 +Epoch [2707/4000] Training [16/16] Loss: 0.00372 +Epoch [2707/4000] Training metric {'Train/mean dice_metric': 0.9976279735565186, 'Train/mean miou_metric': 0.9949995875358582, 'Train/mean f1': 0.9929764866828918, 'Train/mean precision': 0.9884718656539917, 'Train/mean recall': 0.9975223541259766, 'Train/mean hd95_metric': 0.8782082796096802} +Epoch [2707/4000] Validation [1/4] Loss: 0.37471 focal_loss 0.30819 dice_loss 0.06652 +Epoch [2707/4000] Validation [2/4] Loss: 0.62179 focal_loss 0.47057 dice_loss 0.15122 +Epoch [2707/4000] Validation [3/4] Loss: 0.48310 focal_loss 0.38935 dice_loss 0.09375 +Epoch [2707/4000] Validation [4/4] Loss: 0.29797 focal_loss 0.20824 dice_loss 0.08973 +Epoch [2707/4000] Validation metric {'Val/mean dice_metric': 0.9725960493087769, 'Val/mean miou_metric': 0.9576395750045776, 'Val/mean f1': 0.9752229452133179, 'Val/mean precision': 0.9722795486450195, 'Val/mean recall': 0.9781842231750488, 'Val/mean hd95_metric': 5.269097805023193} +Cheakpoint... +Epoch [2707/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725960493087769, 'Val/mean miou_metric': 0.9576395750045776, 'Val/mean f1': 0.9752229452133179, 'Val/mean precision': 0.9722795486450195, 'Val/mean recall': 0.9781842231750488, 'Val/mean hd95_metric': 5.269097805023193} +Epoch [2708/4000] Training [1/16] Loss: 0.00376 +Epoch [2708/4000] Training [2/16] Loss: 0.00371 +Epoch [2708/4000] Training [3/16] Loss: 0.00405 +Epoch [2708/4000] Training [4/16] Loss: 0.00515 +Epoch [2708/4000] Training [5/16] Loss: 0.00361 +Epoch [2708/4000] Training [6/16] Loss: 0.00311 +Epoch [2708/4000] Training [7/16] Loss: 0.00362 +Epoch [2708/4000] Training [8/16] Loss: 0.00345 +Epoch [2708/4000] Training [9/16] Loss: 0.00231 +Epoch [2708/4000] Training [10/16] Loss: 0.00327 +Epoch [2708/4000] Training [11/16] Loss: 0.00467 +Epoch [2708/4000] Training [12/16] Loss: 0.00408 +Epoch [2708/4000] Training [13/16] Loss: 0.00464 +Epoch [2708/4000] Training [14/16] Loss: 0.00413 +Epoch [2708/4000] Training [15/16] Loss: 0.00331 +Epoch [2708/4000] Training [16/16] Loss: 0.00378 +Epoch [2708/4000] Training metric {'Train/mean dice_metric': 0.9970852136611938, 'Train/mean miou_metric': 0.9940659403800964, 'Train/mean f1': 0.99241703748703, 'Train/mean precision': 0.9875974059104919, 'Train/mean recall': 0.997283935546875, 'Train/mean hd95_metric': 1.0850669145584106} +Epoch [2708/4000] Validation [1/4] Loss: 0.36997 focal_loss 0.30499 dice_loss 0.06498 +Epoch [2708/4000] Validation [2/4] Loss: 0.79513 focal_loss 0.60399 dice_loss 0.19115 +Epoch [2708/4000] Validation [3/4] Loss: 0.43230 focal_loss 0.33500 dice_loss 0.09730 +Epoch [2708/4000] Validation [4/4] Loss: 0.31547 focal_loss 0.22052 dice_loss 0.09494 +Epoch [2708/4000] Validation metric {'Val/mean dice_metric': 0.9702121615409851, 'Val/mean miou_metric': 0.9553958177566528, 'Val/mean f1': 0.9743059277534485, 'Val/mean precision': 0.9734854102134705, 'Val/mean recall': 0.9751278162002563, 'Val/mean hd95_metric': 5.45311164855957} +Cheakpoint... +Epoch [2708/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9702], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702121615409851, 'Val/mean miou_metric': 0.9553958177566528, 'Val/mean f1': 0.9743059277534485, 'Val/mean precision': 0.9734854102134705, 'Val/mean recall': 0.9751278162002563, 'Val/mean hd95_metric': 5.45311164855957} +Epoch [2709/4000] Training [1/16] Loss: 0.00321 +Epoch [2709/4000] Training [2/16] Loss: 0.00314 +Epoch [2709/4000] Training [3/16] Loss: 0.00381 +Epoch [2709/4000] Training [4/16] Loss: 0.00407 +Epoch [2709/4000] Training [5/16] Loss: 0.00454 +Epoch [2709/4000] Training [6/16] Loss: 0.00500 +Epoch [2709/4000] Training [7/16] Loss: 0.00360 +Epoch [2709/4000] Training [8/16] Loss: 0.00449 +Epoch [2709/4000] Training [9/16] Loss: 0.00328 +Epoch [2709/4000] Training [10/16] Loss: 0.00453 +Epoch [2709/4000] Training [11/16] Loss: 0.00299 +Epoch [2709/4000] Training [12/16] Loss: 0.00520 +Epoch [2709/4000] Training [13/16] Loss: 0.00334 +Epoch [2709/4000] Training [14/16] Loss: 0.00405 +Epoch [2709/4000] Training [15/16] Loss: 0.00406 +Epoch [2709/4000] Training [16/16] Loss: 0.00365 +Epoch [2709/4000] Training metric {'Train/mean dice_metric': 0.997628927230835, 'Train/mean miou_metric': 0.9949965476989746, 'Train/mean f1': 0.9929261803627014, 'Train/mean precision': 0.9884974956512451, 'Train/mean recall': 0.9973946809768677, 'Train/mean hd95_metric': 0.9038640260696411} +Epoch [2709/4000] Validation [1/4] Loss: 0.35040 focal_loss 0.28542 dice_loss 0.06498 +Epoch [2709/4000] Validation [2/4] Loss: 0.84401 focal_loss 0.65424 dice_loss 0.18976 +Epoch [2709/4000] Validation [3/4] Loss: 0.43135 focal_loss 0.33039 dice_loss 0.10096 +Epoch [2709/4000] Validation [4/4] Loss: 0.49155 focal_loss 0.35185 dice_loss 0.13970 +Epoch [2709/4000] Validation metric {'Val/mean dice_metric': 0.9730764627456665, 'Val/mean miou_metric': 0.9581424593925476, 'Val/mean f1': 0.9756684303283691, 'Val/mean precision': 0.9747301936149597, 'Val/mean recall': 0.9766083359718323, 'Val/mean hd95_metric': 5.068112373352051} +Cheakpoint... +Epoch [2709/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730764627456665, 'Val/mean miou_metric': 0.9581424593925476, 'Val/mean f1': 0.9756684303283691, 'Val/mean precision': 0.9747301936149597, 'Val/mean recall': 0.9766083359718323, 'Val/mean hd95_metric': 5.068112373352051} +Epoch [2710/4000] Training [1/16] Loss: 0.00310 +Epoch [2710/4000] Training [2/16] Loss: 0.00275 +Epoch [2710/4000] Training [3/16] Loss: 0.00323 +Epoch [2710/4000] Training [4/16] Loss: 0.00366 +Epoch [2710/4000] Training [5/16] Loss: 0.00336 +Epoch [2710/4000] Training [6/16] Loss: 0.00315 +Epoch [2710/4000] Training [7/16] Loss: 0.00298 +Epoch [2710/4000] Training [8/16] Loss: 0.00289 +Epoch [2710/4000] Training [9/16] Loss: 0.00360 +Epoch [2710/4000] Training [10/16] Loss: 0.00581 +Epoch [2710/4000] Training [11/16] Loss: 0.00395 +Epoch [2710/4000] Training [12/16] Loss: 0.00375 +Epoch [2710/4000] Training [13/16] Loss: 0.00440 +Epoch [2710/4000] Training [14/16] Loss: 0.00348 +Epoch [2710/4000] Training [15/16] Loss: 0.00263 +Epoch [2710/4000] Training [16/16] Loss: 0.00354 +Epoch [2710/4000] Training metric {'Train/mean dice_metric': 0.9978258609771729, 'Train/mean miou_metric': 0.9953819513320923, 'Train/mean f1': 0.9929932951927185, 'Train/mean precision': 0.9883039593696594, 'Train/mean recall': 0.9977273941040039, 'Train/mean hd95_metric': 0.873004674911499} +Epoch [2710/4000] Validation [1/4] Loss: 0.32883 focal_loss 0.26799 dice_loss 0.06084 +Epoch [2710/4000] Validation [2/4] Loss: 0.63636 focal_loss 0.47353 dice_loss 0.16283 +Epoch [2710/4000] Validation [3/4] Loss: 0.41201 focal_loss 0.31511 dice_loss 0.09690 +Epoch [2710/4000] Validation [4/4] Loss: 0.31043 focal_loss 0.21855 dice_loss 0.09188 +Epoch [2710/4000] Validation metric {'Val/mean dice_metric': 0.9736608266830444, 'Val/mean miou_metric': 0.9586231112480164, 'Val/mean f1': 0.9757693409919739, 'Val/mean precision': 0.9748360514640808, 'Val/mean recall': 0.9767043590545654, 'Val/mean hd95_metric': 5.415616989135742} +Cheakpoint... +Epoch [2710/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736608266830444, 'Val/mean miou_metric': 0.9586231112480164, 'Val/mean f1': 0.9757693409919739, 'Val/mean precision': 0.9748360514640808, 'Val/mean recall': 0.9767043590545654, 'Val/mean hd95_metric': 5.415616989135742} +Epoch [2711/4000] Training [1/16] Loss: 0.00245 +Epoch [2711/4000] Training [2/16] Loss: 0.00374 +Epoch [2711/4000] Training [3/16] Loss: 0.00297 +Epoch [2711/4000] Training [4/16] Loss: 0.00356 +Epoch [2711/4000] Training [5/16] Loss: 0.00362 +Epoch [2711/4000] Training [6/16] Loss: 0.00416 +Epoch [2711/4000] Training [7/16] Loss: 0.00323 +Epoch [2711/4000] Training [8/16] Loss: 0.00433 +Epoch [2711/4000] Training [9/16] Loss: 0.00422 +Epoch [2711/4000] Training [10/16] Loss: 0.00342 +Epoch [2711/4000] Training [11/16] Loss: 0.00477 +Epoch [2711/4000] Training [12/16] Loss: 0.00264 +Epoch [2711/4000] Training [13/16] Loss: 0.00359 +Epoch [2711/4000] Training [14/16] Loss: 0.00217 +Epoch [2711/4000] Training [15/16] Loss: 0.00354 +Epoch [2711/4000] Training [16/16] Loss: 0.00296 +Epoch [2711/4000] Training metric {'Train/mean dice_metric': 0.9980549812316895, 'Train/mean miou_metric': 0.9958386421203613, 'Train/mean f1': 0.9930336475372314, 'Train/mean precision': 0.9884033799171448, 'Train/mean recall': 0.9977074861526489, 'Train/mean hd95_metric': 1.0538434982299805} +Epoch [2711/4000] Validation [1/4] Loss: 0.36953 focal_loss 0.30447 dice_loss 0.06506 +Epoch [2711/4000] Validation [2/4] Loss: 0.33701 focal_loss 0.23866 dice_loss 0.09835 +Epoch [2711/4000] Validation [3/4] Loss: 0.41988 focal_loss 0.31934 dice_loss 0.10054 +Epoch [2711/4000] Validation [4/4] Loss: 0.32959 focal_loss 0.22410 dice_loss 0.10549 +Epoch [2711/4000] Validation metric {'Val/mean dice_metric': 0.9736690521240234, 'Val/mean miou_metric': 0.9583066701889038, 'Val/mean f1': 0.9753112196922302, 'Val/mean precision': 0.9746561646461487, 'Val/mean recall': 0.9759671688079834, 'Val/mean hd95_metric': 5.060454845428467} +Cheakpoint... +Epoch [2711/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736690521240234, 'Val/mean miou_metric': 0.9583066701889038, 'Val/mean f1': 0.9753112196922302, 'Val/mean precision': 0.9746561646461487, 'Val/mean recall': 0.9759671688079834, 'Val/mean hd95_metric': 5.060454845428467} +Epoch [2712/4000] Training [1/16] Loss: 0.00315 +Epoch [2712/4000] Training [2/16] Loss: 0.00396 +Epoch [2712/4000] Training [3/16] Loss: 0.00327 +Epoch [2712/4000] Training [4/16] Loss: 0.00508 +Epoch [2712/4000] Training [5/16] Loss: 0.00310 +Epoch [2712/4000] Training [6/16] Loss: 0.00288 +Epoch [2712/4000] Training [7/16] Loss: 0.00418 +Epoch [2712/4000] Training [8/16] Loss: 0.00340 +Epoch [2712/4000] Training [9/16] Loss: 0.00410 +Epoch [2712/4000] Training [10/16] Loss: 0.00367 +Epoch [2712/4000] Training [11/16] Loss: 0.00284 +Epoch [2712/4000] Training [12/16] Loss: 0.00284 +Epoch [2712/4000] Training [13/16] Loss: 0.00701 +Epoch [2712/4000] Training [14/16] Loss: 0.00422 +Epoch [2712/4000] Training [15/16] Loss: 0.00378 +Epoch [2712/4000] Training [16/16] Loss: 0.00307 +Epoch [2712/4000] Training metric {'Train/mean dice_metric': 0.9977798461914062, 'Train/mean miou_metric': 0.9952884912490845, 'Train/mean f1': 0.9929108619689941, 'Train/mean precision': 0.9883458614349365, 'Train/mean recall': 0.9975182414054871, 'Train/mean hd95_metric': 0.8986842632293701} +Epoch [2712/4000] Validation [1/4] Loss: 0.32850 focal_loss 0.26790 dice_loss 0.06060 +Epoch [2712/4000] Validation [2/4] Loss: 0.41338 focal_loss 0.29088 dice_loss 0.12250 +Epoch [2712/4000] Validation [3/4] Loss: 0.44149 focal_loss 0.33939 dice_loss 0.10210 +Epoch [2712/4000] Validation [4/4] Loss: 0.39699 focal_loss 0.28219 dice_loss 0.11481 +Epoch [2712/4000] Validation metric {'Val/mean dice_metric': 0.9736202359199524, 'Val/mean miou_metric': 0.9582287073135376, 'Val/mean f1': 0.9757483005523682, 'Val/mean precision': 0.9748835563659668, 'Val/mean recall': 0.9766144752502441, 'Val/mean hd95_metric': 5.058779716491699} +Cheakpoint... +Epoch [2712/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736202359199524, 'Val/mean miou_metric': 0.9582287073135376, 'Val/mean f1': 0.9757483005523682, 'Val/mean precision': 0.9748835563659668, 'Val/mean recall': 0.9766144752502441, 'Val/mean hd95_metric': 5.058779716491699} +Epoch [2713/4000] Training [1/16] Loss: 0.00357 +Epoch [2713/4000] Training [2/16] Loss: 0.00365 +Epoch [2713/4000] Training [3/16] Loss: 0.00272 +Epoch [2713/4000] Training [4/16] Loss: 0.00403 +Epoch [2713/4000] Training [5/16] Loss: 0.00387 +Epoch [2713/4000] Training [6/16] Loss: 0.00509 +Epoch [2713/4000] Training [7/16] Loss: 0.00528 +Epoch [2713/4000] Training [8/16] Loss: 0.00322 +Epoch [2713/4000] Training [9/16] Loss: 0.00267 +Epoch [2713/4000] Training [10/16] Loss: 0.00483 +Epoch [2713/4000] Training [11/16] Loss: 0.00253 +Epoch [2713/4000] Training [12/16] Loss: 0.00311 +Epoch [2713/4000] Training [13/16] Loss: 0.00330 +Epoch [2713/4000] Training [14/16] Loss: 0.00323 +Epoch [2713/4000] Training [15/16] Loss: 0.00348 +Epoch [2713/4000] Training [16/16] Loss: 0.00261 +Epoch [2713/4000] Training metric {'Train/mean dice_metric': 0.9979220628738403, 'Train/mean miou_metric': 0.9955786466598511, 'Train/mean f1': 0.993085503578186, 'Train/mean precision': 0.9885104298591614, 'Train/mean recall': 0.9977031350135803, 'Train/mean hd95_metric': 0.8720055818557739} +Epoch [2713/4000] Validation [1/4] Loss: 0.41846 focal_loss 0.34429 dice_loss 0.07417 +Epoch [2713/4000] Validation [2/4] Loss: 1.18320 focal_loss 0.92224 dice_loss 0.26096 +Epoch [2713/4000] Validation [3/4] Loss: 0.43290 focal_loss 0.33710 dice_loss 0.09580 +Epoch [2713/4000] Validation [4/4] Loss: 0.29738 focal_loss 0.21249 dice_loss 0.08489 +Epoch [2713/4000] Validation metric {'Val/mean dice_metric': 0.9705333709716797, 'Val/mean miou_metric': 0.9558830261230469, 'Val/mean f1': 0.9749207496643066, 'Val/mean precision': 0.9749393463134766, 'Val/mean recall': 0.9749021530151367, 'Val/mean hd95_metric': 5.077384948730469} +Cheakpoint... +Epoch [2713/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705333709716797, 'Val/mean miou_metric': 0.9558830261230469, 'Val/mean f1': 0.9749207496643066, 'Val/mean precision': 0.9749393463134766, 'Val/mean recall': 0.9749021530151367, 'Val/mean hd95_metric': 5.077384948730469} +Epoch [2714/4000] Training [1/16] Loss: 0.00355 +Epoch [2714/4000] Training [2/16] Loss: 0.00493 +Epoch [2714/4000] Training [3/16] Loss: 0.00404 +Epoch [2714/4000] Training [4/16] Loss: 0.00511 +Epoch [2714/4000] Training [5/16] Loss: 0.00428 +Epoch [2714/4000] Training [6/16] Loss: 0.00394 +Epoch [2714/4000] Training [7/16] Loss: 0.00464 +Epoch [2714/4000] Training [8/16] Loss: 0.00354 +Epoch [2714/4000] Training [9/16] Loss: 0.00331 +Epoch [2714/4000] Training [10/16] Loss: 0.00345 +Epoch [2714/4000] Training [11/16] Loss: 0.00622 +Epoch [2714/4000] Training [12/16] Loss: 0.00305 +Epoch [2714/4000] Training [13/16] Loss: 0.00304 +Epoch [2714/4000] Training [14/16] Loss: 0.00530 +Epoch [2714/4000] Training [15/16] Loss: 0.00283 +Epoch [2714/4000] Training [16/16] Loss: 0.00335 +Epoch [2714/4000] Training metric {'Train/mean dice_metric': 0.997732400894165, 'Train/mean miou_metric': 0.9951941967010498, 'Train/mean f1': 0.9930716156959534, 'Train/mean precision': 0.9885478615760803, 'Train/mean recall': 0.9976369738578796, 'Train/mean hd95_metric': 0.8862148523330688} +Epoch [2714/4000] Validation [1/4] Loss: 0.34448 focal_loss 0.27919 dice_loss 0.06529 +Epoch [2714/4000] Validation [2/4] Loss: 0.33577 focal_loss 0.23698 dice_loss 0.09879 +Epoch [2714/4000] Validation [3/4] Loss: 0.50394 focal_loss 0.39458 dice_loss 0.10936 +Epoch [2714/4000] Validation [4/4] Loss: 0.61320 focal_loss 0.47295 dice_loss 0.14024 +Epoch [2714/4000] Validation metric {'Val/mean dice_metric': 0.9744865298271179, 'Val/mean miou_metric': 0.9587656855583191, 'Val/mean f1': 0.975495457649231, 'Val/mean precision': 0.975392758846283, 'Val/mean recall': 0.9755982160568237, 'Val/mean hd95_metric': 5.53721809387207} +Cheakpoint... +Epoch [2714/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744865298271179, 'Val/mean miou_metric': 0.9587656855583191, 'Val/mean f1': 0.975495457649231, 'Val/mean precision': 0.975392758846283, 'Val/mean recall': 0.9755982160568237, 'Val/mean hd95_metric': 5.53721809387207} +Epoch [2715/4000] Training [1/16] Loss: 0.00365 +Epoch [2715/4000] Training [2/16] Loss: 0.00324 +Epoch [2715/4000] Training [3/16] Loss: 0.00355 +Epoch [2715/4000] Training [4/16] Loss: 0.00400 +Epoch [2715/4000] Training [5/16] Loss: 0.00277 +Epoch [2715/4000] Training [6/16] Loss: 0.00737 +Epoch [2715/4000] Training [7/16] Loss: 0.00313 +Epoch [2715/4000] Training [8/16] Loss: 0.00300 +Epoch [2715/4000] Training [9/16] Loss: 0.00339 +Epoch [2715/4000] Training [10/16] Loss: 0.00329 +Epoch [2715/4000] Training [11/16] Loss: 0.00409 +Epoch [2715/4000] Training [12/16] Loss: 0.00275 +Epoch [2715/4000] Training [13/16] Loss: 0.00613 +Epoch [2715/4000] Training [14/16] Loss: 0.00362 +Epoch [2715/4000] Training [15/16] Loss: 0.00439 +Epoch [2715/4000] Training [16/16] Loss: 0.00404 +Epoch [2715/4000] Training metric {'Train/mean dice_metric': 0.9978111982345581, 'Train/mean miou_metric': 0.9953557252883911, 'Train/mean f1': 0.9930661916732788, 'Train/mean precision': 0.9885108470916748, 'Train/mean recall': 0.9976637959480286, 'Train/mean hd95_metric': 0.8611882925033569} +Epoch [2715/4000] Validation [1/4] Loss: 0.56518 focal_loss 0.45396 dice_loss 0.11122 +Epoch [2715/4000] Validation [2/4] Loss: 0.75278 focal_loss 0.57179 dice_loss 0.18099 +Epoch [2715/4000] Validation [3/4] Loss: 0.23685 focal_loss 0.17084 dice_loss 0.06601 +Epoch [2715/4000] Validation [4/4] Loss: 0.28280 focal_loss 0.19775 dice_loss 0.08505 +Epoch [2715/4000] Validation metric {'Val/mean dice_metric': 0.972785472869873, 'Val/mean miou_metric': 0.9580279588699341, 'Val/mean f1': 0.9755246639251709, 'Val/mean precision': 0.9754483103752136, 'Val/mean recall': 0.9756010174751282, 'Val/mean hd95_metric': 5.054559230804443} +Cheakpoint... +Epoch [2715/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972785472869873, 'Val/mean miou_metric': 0.9580279588699341, 'Val/mean f1': 0.9755246639251709, 'Val/mean precision': 0.9754483103752136, 'Val/mean recall': 0.9756010174751282, 'Val/mean hd95_metric': 5.054559230804443} +Epoch [2716/4000] Training [1/16] Loss: 0.00379 +Epoch [2716/4000] Training [2/16] Loss: 0.00346 +Epoch [2716/4000] Training [3/16] Loss: 0.00362 +Epoch [2716/4000] Training [4/16] Loss: 0.00529 +Epoch [2716/4000] Training [5/16] Loss: 0.00309 +Epoch [2716/4000] Training [6/16] Loss: 0.00342 +Epoch [2716/4000] Training [7/16] Loss: 0.00292 +Epoch [2716/4000] Training [8/16] Loss: 0.00355 +Epoch [2716/4000] Training [9/16] Loss: 0.00335 +Epoch [2716/4000] Training [10/16] Loss: 0.00320 +Epoch [2716/4000] Training [11/16] Loss: 0.00518 +Epoch [2716/4000] Training [12/16] Loss: 0.00305 +Epoch [2716/4000] Training [13/16] Loss: 0.00371 +Epoch [2716/4000] Training [14/16] Loss: 0.00432 +Epoch [2716/4000] Training [15/16] Loss: 0.00438 +Epoch [2716/4000] Training [16/16] Loss: 0.00335 +Epoch [2716/4000] Training metric {'Train/mean dice_metric': 0.9977414011955261, 'Train/mean miou_metric': 0.9952247738838196, 'Train/mean f1': 0.9931604266166687, 'Train/mean precision': 0.988726794719696, 'Train/mean recall': 0.99763423204422, 'Train/mean hd95_metric': 0.88791823387146} +Epoch [2716/4000] Validation [1/4] Loss: 0.42366 focal_loss 0.34949 dice_loss 0.07418 +Epoch [2716/4000] Validation [2/4] Loss: 0.68429 focal_loss 0.51282 dice_loss 0.17147 +Epoch [2716/4000] Validation [3/4] Loss: 0.27541 focal_loss 0.19813 dice_loss 0.07728 +Epoch [2716/4000] Validation [4/4] Loss: 0.30268 focal_loss 0.21351 dice_loss 0.08917 +Epoch [2716/4000] Validation metric {'Val/mean dice_metric': 0.9719734191894531, 'Val/mean miou_metric': 0.9569185376167297, 'Val/mean f1': 0.9752506017684937, 'Val/mean precision': 0.9747791886329651, 'Val/mean recall': 0.9757224321365356, 'Val/mean hd95_metric': 5.452978610992432} +Cheakpoint... +Epoch [2716/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719734191894531, 'Val/mean miou_metric': 0.9569185376167297, 'Val/mean f1': 0.9752506017684937, 'Val/mean precision': 0.9747791886329651, 'Val/mean recall': 0.9757224321365356, 'Val/mean hd95_metric': 5.452978610992432} +Epoch [2717/4000] Training [1/16] Loss: 0.00330 +Epoch [2717/4000] Training [2/16] Loss: 0.00417 +Epoch [2717/4000] Training [3/16] Loss: 0.00360 +Epoch [2717/4000] Training [4/16] Loss: 0.00302 +Epoch [2717/4000] Training [5/16] Loss: 0.00332 +Epoch [2717/4000] Training [6/16] Loss: 0.00411 +Epoch [2717/4000] Training [7/16] Loss: 0.00419 +Epoch [2717/4000] Training [8/16] Loss: 0.00471 +Epoch [2717/4000] Training [9/16] Loss: 0.00369 +Epoch [2717/4000] Training [10/16] Loss: 0.00324 +Epoch [2717/4000] Training [11/16] Loss: 0.00322 +Epoch [2717/4000] Training [12/16] Loss: 0.00297 +Epoch [2717/4000] Training [13/16] Loss: 0.00500 +Epoch [2717/4000] Training [14/16] Loss: 0.00631 +Epoch [2717/4000] Training [15/16] Loss: 0.00314 +Epoch [2717/4000] Training [16/16] Loss: 0.00476 +Epoch [2717/4000] Training metric {'Train/mean dice_metric': 0.9976879358291626, 'Train/mean miou_metric': 0.995112419128418, 'Train/mean f1': 0.9929344058036804, 'Train/mean precision': 0.9884063601493835, 'Train/mean recall': 0.9975041747093201, 'Train/mean hd95_metric': 0.8878483772277832} +Epoch [2717/4000] Validation [1/4] Loss: 0.37394 focal_loss 0.29366 dice_loss 0.08028 +Epoch [2717/4000] Validation [2/4] Loss: 0.36114 focal_loss 0.26295 dice_loss 0.09819 +Epoch [2717/4000] Validation [3/4] Loss: 0.40743 focal_loss 0.31416 dice_loss 0.09327 +Epoch [2717/4000] Validation [4/4] Loss: 0.37554 focal_loss 0.27303 dice_loss 0.10252 +Epoch [2717/4000] Validation metric {'Val/mean dice_metric': 0.9734379053115845, 'Val/mean miou_metric': 0.9578256607055664, 'Val/mean f1': 0.9753474593162537, 'Val/mean precision': 0.9744101166725159, 'Val/mean recall': 0.9762865304946899, 'Val/mean hd95_metric': 4.921133518218994} +Cheakpoint... +Epoch [2717/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734379053115845, 'Val/mean miou_metric': 0.9578256607055664, 'Val/mean f1': 0.9753474593162537, 'Val/mean precision': 0.9744101166725159, 'Val/mean recall': 0.9762865304946899, 'Val/mean hd95_metric': 4.921133518218994} +Epoch [2718/4000] Training [1/16] Loss: 0.00353 +Epoch [2718/4000] Training [2/16] Loss: 0.00374 +Epoch [2718/4000] Training [3/16] Loss: 0.00319 +Epoch [2718/4000] Training [4/16] Loss: 0.00320 +Epoch [2718/4000] Training [5/16] Loss: 0.00490 +Epoch [2718/4000] Training [6/16] Loss: 0.00446 +Epoch [2718/4000] Training [7/16] Loss: 0.00373 +Epoch [2718/4000] Training [8/16] Loss: 0.00533 +Epoch [2718/4000] Training [9/16] Loss: 0.00239 +Epoch [2718/4000] Training [10/16] Loss: 0.00568 +Epoch [2718/4000] Training [11/16] Loss: 0.00335 +Epoch [2718/4000] Training [12/16] Loss: 0.00369 +Epoch [2718/4000] Training [13/16] Loss: 0.00522 +Epoch [2718/4000] Training [14/16] Loss: 0.00513 +Epoch [2718/4000] Training [15/16] Loss: 0.00310 +Epoch [2718/4000] Training [16/16] Loss: 0.00316 +Epoch [2718/4000] Training metric {'Train/mean dice_metric': 0.9976701140403748, 'Train/mean miou_metric': 0.9950611591339111, 'Train/mean f1': 0.9928399920463562, 'Train/mean precision': 0.9881520867347717, 'Train/mean recall': 0.9975725412368774, 'Train/mean hd95_metric': 1.0045796632766724} +Epoch [2718/4000] Validation [1/4] Loss: 0.37932 focal_loss 0.30547 dice_loss 0.07384 +Epoch [2718/4000] Validation [2/4] Loss: 0.38078 focal_loss 0.27820 dice_loss 0.10258 +Epoch [2718/4000] Validation [3/4] Loss: 0.41720 focal_loss 0.32145 dice_loss 0.09576 +Epoch [2718/4000] Validation [4/4] Loss: 0.31841 focal_loss 0.22576 dice_loss 0.09265 +Epoch [2718/4000] Validation metric {'Val/mean dice_metric': 0.9734188318252563, 'Val/mean miou_metric': 0.957924485206604, 'Val/mean f1': 0.9745050072669983, 'Val/mean precision': 0.9732755422592163, 'Val/mean recall': 0.9757375717163086, 'Val/mean hd95_metric': 5.477862358093262} +Cheakpoint... +Epoch [2718/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734188318252563, 'Val/mean miou_metric': 0.957924485206604, 'Val/mean f1': 0.9745050072669983, 'Val/mean precision': 0.9732755422592163, 'Val/mean recall': 0.9757375717163086, 'Val/mean hd95_metric': 5.477862358093262} +Epoch [2719/4000] Training [1/16] Loss: 0.00487 +Epoch [2719/4000] Training [2/16] Loss: 0.00288 +Epoch [2719/4000] Training [3/16] Loss: 0.00349 +Epoch [2719/4000] Training [4/16] Loss: 0.00501 +Epoch [2719/4000] Training [5/16] Loss: 0.00300 +Epoch [2719/4000] Training [6/16] Loss: 0.00315 +Epoch [2719/4000] Training [7/16] Loss: 0.00397 +Epoch [2719/4000] Training [8/16] Loss: 0.00421 +Epoch [2719/4000] Training [9/16] Loss: 0.00292 +Epoch [2719/4000] Training [10/16] Loss: 0.00343 +Epoch [2719/4000] Training [11/16] Loss: 0.00346 +Epoch [2719/4000] Training [12/16] Loss: 0.00371 +Epoch [2719/4000] Training [13/16] Loss: 0.00254 +Epoch [2719/4000] Training [14/16] Loss: 0.00541 +Epoch [2719/4000] Training [15/16] Loss: 0.00401 +Epoch [2719/4000] Training [16/16] Loss: 0.00683 +Epoch [2719/4000] Training metric {'Train/mean dice_metric': 0.9977392554283142, 'Train/mean miou_metric': 0.9952194094657898, 'Train/mean f1': 0.9929639101028442, 'Train/mean precision': 0.9884658455848694, 'Train/mean recall': 0.9975031614303589, 'Train/mean hd95_metric': 0.9069733619689941} +Epoch [2719/4000] Validation [1/4] Loss: 0.39746 focal_loss 0.31788 dice_loss 0.07958 +Epoch [2719/4000] Validation [2/4] Loss: 0.41540 focal_loss 0.30596 dice_loss 0.10943 +Epoch [2719/4000] Validation [3/4] Loss: 0.35106 focal_loss 0.26127 dice_loss 0.08979 +Epoch [2719/4000] Validation [4/4] Loss: 0.67151 focal_loss 0.51617 dice_loss 0.15533 +Epoch [2719/4000] Validation metric {'Val/mean dice_metric': 0.972040057182312, 'Val/mean miou_metric': 0.9563921093940735, 'Val/mean f1': 0.9745455384254456, 'Val/mean precision': 0.9747363328933716, 'Val/mean recall': 0.9743549227714539, 'Val/mean hd95_metric': 5.166993618011475} +Cheakpoint... +Epoch [2719/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972040057182312, 'Val/mean miou_metric': 0.9563921093940735, 'Val/mean f1': 0.9745455384254456, 'Val/mean precision': 0.9747363328933716, 'Val/mean recall': 0.9743549227714539, 'Val/mean hd95_metric': 5.166993618011475} +Epoch [2720/4000] Training [1/16] Loss: 0.00419 +Epoch [2720/4000] Training [2/16] Loss: 0.00459 +Epoch [2720/4000] Training [3/16] Loss: 0.00611 +Epoch [2720/4000] Training [4/16] Loss: 0.00305 +Epoch [2720/4000] Training [5/16] Loss: 0.00354 +Epoch [2720/4000] Training [6/16] Loss: 0.00356 +Epoch [2720/4000] Training [7/16] Loss: 0.00393 +Epoch [2720/4000] Training [8/16] Loss: 0.00361 +Epoch [2720/4000] Training [9/16] Loss: 0.00300 +Epoch [2720/4000] Training [10/16] Loss: 0.00373 +Epoch [2720/4000] Training [11/16] Loss: 0.00413 +Epoch [2720/4000] Training [12/16] Loss: 0.00410 +Epoch [2720/4000] Training [13/16] Loss: 0.00375 +Epoch [2720/4000] Training [14/16] Loss: 0.00303 +Epoch [2720/4000] Training [15/16] Loss: 0.00305 +Epoch [2720/4000] Training [16/16] Loss: 0.00447 +Epoch [2720/4000] Training metric {'Train/mean dice_metric': 0.9976400136947632, 'Train/mean miou_metric': 0.9950225353240967, 'Train/mean f1': 0.99298095703125, 'Train/mean precision': 0.9884459972381592, 'Train/mean recall': 0.9975576996803284, 'Train/mean hd95_metric': 0.9100915193557739} +Epoch [2720/4000] Validation [1/4] Loss: 0.32998 focal_loss 0.26737 dice_loss 0.06261 +Epoch [2720/4000] Validation [2/4] Loss: 0.84347 focal_loss 0.67034 dice_loss 0.17313 +Epoch [2720/4000] Validation [3/4] Loss: 0.25393 focal_loss 0.18437 dice_loss 0.06956 +Epoch [2720/4000] Validation [4/4] Loss: 0.60493 focal_loss 0.45088 dice_loss 0.15405 +Epoch [2720/4000] Validation metric {'Val/mean dice_metric': 0.9730566143989563, 'Val/mean miou_metric': 0.9573569297790527, 'Val/mean f1': 0.9744444489479065, 'Val/mean precision': 0.9744974374771118, 'Val/mean recall': 0.9743914604187012, 'Val/mean hd95_metric': 5.746802806854248} +Cheakpoint... +Epoch [2720/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730566143989563, 'Val/mean miou_metric': 0.9573569297790527, 'Val/mean f1': 0.9744444489479065, 'Val/mean precision': 0.9744974374771118, 'Val/mean recall': 0.9743914604187012, 'Val/mean hd95_metric': 5.746802806854248} +Epoch [2721/4000] Training [1/16] Loss: 0.00538 +Epoch [2721/4000] Training [2/16] Loss: 0.00334 +Epoch [2721/4000] Training [3/16] Loss: 0.00738 +Epoch [2721/4000] Training [4/16] Loss: 0.00373 +Epoch [2721/4000] Training [5/16] Loss: 0.00351 +Epoch [2721/4000] Training [6/16] Loss: 0.00438 +Epoch [2721/4000] Training [7/16] Loss: 0.00408 +Epoch [2721/4000] Training [8/16] Loss: 0.00278 +Epoch [2721/4000] Training [9/16] Loss: 0.00501 +Epoch [2721/4000] Training [10/16] Loss: 0.00412 +Epoch [2721/4000] Training [11/16] Loss: 0.00366 +Epoch [2721/4000] Training [12/16] Loss: 0.00319 +Epoch [2721/4000] Training [13/16] Loss: 0.00440 +Epoch [2721/4000] Training [14/16] Loss: 0.00424 +Epoch [2721/4000] Training [15/16] Loss: 0.00326 +Epoch [2721/4000] Training [16/16] Loss: 0.00346 +Epoch [2721/4000] Training metric {'Train/mean dice_metric': 0.9975974559783936, 'Train/mean miou_metric': 0.9949392080307007, 'Train/mean f1': 0.992897629737854, 'Train/mean precision': 0.9882923364639282, 'Train/mean recall': 0.9975460171699524, 'Train/mean hd95_metric': 0.8857555389404297} +Epoch [2721/4000] Validation [1/4] Loss: 0.35831 focal_loss 0.29380 dice_loss 0.06451 +Epoch [2721/4000] Validation [2/4] Loss: 0.82883 focal_loss 0.64276 dice_loss 0.18607 +Epoch [2721/4000] Validation [3/4] Loss: 0.25758 focal_loss 0.18947 dice_loss 0.06811 +Epoch [2721/4000] Validation [4/4] Loss: 0.30627 focal_loss 0.22010 dice_loss 0.08617 +Epoch [2721/4000] Validation metric {'Val/mean dice_metric': 0.9728572964668274, 'Val/mean miou_metric': 0.9585021734237671, 'Val/mean f1': 0.9751324653625488, 'Val/mean precision': 0.9734732508659363, 'Val/mean recall': 0.9767972826957703, 'Val/mean hd95_metric': 5.3932905197143555} +Cheakpoint... +Epoch [2721/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728572964668274, 'Val/mean miou_metric': 0.9585021734237671, 'Val/mean f1': 0.9751324653625488, 'Val/mean precision': 0.9734732508659363, 'Val/mean recall': 0.9767972826957703, 'Val/mean hd95_metric': 5.3932905197143555} +Epoch [2722/4000] Training [1/16] Loss: 0.00381 +Epoch [2722/4000] Training [2/16] Loss: 0.00265 +Epoch [2722/4000] Training [3/16] Loss: 0.00412 +Epoch [2722/4000] Training [4/16] Loss: 0.00454 +Epoch [2722/4000] Training [5/16] Loss: 0.00439 +Epoch [2722/4000] Training [6/16] Loss: 0.00432 +Epoch [2722/4000] Training [7/16] Loss: 0.00419 +Epoch [2722/4000] Training [8/16] Loss: 0.00353 +Epoch [2722/4000] Training [9/16] Loss: 0.00304 +Epoch [2722/4000] Training [10/16] Loss: 0.00410 +Epoch [2722/4000] Training [11/16] Loss: 0.00266 +Epoch [2722/4000] Training [12/16] Loss: 0.00396 +Epoch [2722/4000] Training [13/16] Loss: 0.00600 +Epoch [2722/4000] Training [14/16] Loss: 0.00403 +Epoch [2722/4000] Training [15/16] Loss: 0.00275 +Epoch [2722/4000] Training [16/16] Loss: 0.00460 +Epoch [2722/4000] Training metric {'Train/mean dice_metric': 0.9977514743804932, 'Train/mean miou_metric': 0.9952445030212402, 'Train/mean f1': 0.9930940270423889, 'Train/mean precision': 0.9885865449905396, 'Train/mean recall': 0.9976428747177124, 'Train/mean hd95_metric': 0.8839598894119263} +Epoch [2722/4000] Validation [1/4] Loss: 0.34610 focal_loss 0.27818 dice_loss 0.06792 +Epoch [2722/4000] Validation [2/4] Loss: 0.88588 focal_loss 0.67383 dice_loss 0.21205 +Epoch [2722/4000] Validation [3/4] Loss: 0.45109 focal_loss 0.35489 dice_loss 0.09621 +Epoch [2722/4000] Validation [4/4] Loss: 0.37685 focal_loss 0.26523 dice_loss 0.11162 +Epoch [2722/4000] Validation metric {'Val/mean dice_metric': 0.9709529876708984, 'Val/mean miou_metric': 0.9559659957885742, 'Val/mean f1': 0.9746646285057068, 'Val/mean precision': 0.9739758372306824, 'Val/mean recall': 0.9753543734550476, 'Val/mean hd95_metric': 5.406940937042236} +Cheakpoint... +Epoch [2722/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709529876708984, 'Val/mean miou_metric': 0.9559659957885742, 'Val/mean f1': 0.9746646285057068, 'Val/mean precision': 0.9739758372306824, 'Val/mean recall': 0.9753543734550476, 'Val/mean hd95_metric': 5.406940937042236} +Epoch [2723/4000] Training [1/16] Loss: 0.00374 +Epoch [2723/4000] Training [2/16] Loss: 0.00392 +Epoch [2723/4000] Training [3/16] Loss: 0.00403 +Epoch [2723/4000] Training [4/16] Loss: 0.00299 +Epoch [2723/4000] Training [5/16] Loss: 0.00380 +Epoch [2723/4000] Training [6/16] Loss: 0.00357 +Epoch [2723/4000] Training [7/16] Loss: 0.00302 +Epoch [2723/4000] Training [8/16] Loss: 0.00346 +Epoch [2723/4000] Training [9/16] Loss: 0.00429 +Epoch [2723/4000] Training [10/16] Loss: 0.00446 +Epoch [2723/4000] Training [11/16] Loss: 0.00392 +Epoch [2723/4000] Training [12/16] Loss: 0.00442 +Epoch [2723/4000] Training [13/16] Loss: 0.00472 +Epoch [2723/4000] Training [14/16] Loss: 0.00359 +Epoch [2723/4000] Training [15/16] Loss: 0.00297 +Epoch [2723/4000] Training [16/16] Loss: 0.00488 +Epoch [2723/4000] Training metric {'Train/mean dice_metric': 0.9975206255912781, 'Train/mean miou_metric': 0.994787871837616, 'Train/mean f1': 0.9928897023200989, 'Train/mean precision': 0.9884375929832458, 'Train/mean recall': 0.9973821640014648, 'Train/mean hd95_metric': 0.8991765379905701} +Epoch [2723/4000] Validation [1/4] Loss: 0.34193 focal_loss 0.27835 dice_loss 0.06358 +Epoch [2723/4000] Validation [2/4] Loss: 0.64350 focal_loss 0.46392 dice_loss 0.17958 +Epoch [2723/4000] Validation [3/4] Loss: 0.42997 focal_loss 0.32854 dice_loss 0.10143 +Epoch [2723/4000] Validation [4/4] Loss: 0.40159 focal_loss 0.29404 dice_loss 0.10755 +Epoch [2723/4000] Validation metric {'Val/mean dice_metric': 0.971532940864563, 'Val/mean miou_metric': 0.9568517804145813, 'Val/mean f1': 0.9749718308448792, 'Val/mean precision': 0.9738612771034241, 'Val/mean recall': 0.9760848879814148, 'Val/mean hd95_metric': 5.445116996765137} +Cheakpoint... +Epoch [2723/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971532940864563, 'Val/mean miou_metric': 0.9568517804145813, 'Val/mean f1': 0.9749718308448792, 'Val/mean precision': 0.9738612771034241, 'Val/mean recall': 0.9760848879814148, 'Val/mean hd95_metric': 5.445116996765137} +Epoch [2724/4000] Training [1/16] Loss: 0.00334 +Epoch [2724/4000] Training [2/16] Loss: 0.00335 +Epoch [2724/4000] Training [3/16] Loss: 0.00382 +Epoch [2724/4000] Training [4/16] Loss: 0.00343 +Epoch [2724/4000] Training [5/16] Loss: 0.00426 +Epoch [2724/4000] Training [6/16] Loss: 0.00383 +Epoch [2724/4000] Training [7/16] Loss: 0.00300 +Epoch [2724/4000] Training [8/16] Loss: 0.00364 +Epoch [2724/4000] Training [9/16] Loss: 0.00491 +Epoch [2724/4000] Training [10/16] Loss: 0.00393 +Epoch [2724/4000] Training [11/16] Loss: 0.00308 +Epoch [2724/4000] Training [12/16] Loss: 0.00385 +Epoch [2724/4000] Training [13/16] Loss: 0.00423 +Epoch [2724/4000] Training [14/16] Loss: 0.00376 +Epoch [2724/4000] Training [15/16] Loss: 0.00316 +Epoch [2724/4000] Training [16/16] Loss: 0.00448 +Epoch [2724/4000] Training metric {'Train/mean dice_metric': 0.9977020621299744, 'Train/mean miou_metric': 0.9951403141021729, 'Train/mean f1': 0.9930258989334106, 'Train/mean precision': 0.9885302186012268, 'Train/mean recall': 0.9975625872612, 'Train/mean hd95_metric': 0.9072540998458862} +Epoch [2724/4000] Validation [1/4] Loss: 0.37735 focal_loss 0.30746 dice_loss 0.06989 +Epoch [2724/4000] Validation [2/4] Loss: 0.35123 focal_loss 0.24831 dice_loss 0.10292 +Epoch [2724/4000] Validation [3/4] Loss: 0.41869 focal_loss 0.32914 dice_loss 0.08955 +Epoch [2724/4000] Validation [4/4] Loss: 0.27287 focal_loss 0.20129 dice_loss 0.07158 +Epoch [2724/4000] Validation metric {'Val/mean dice_metric': 0.973776638507843, 'Val/mean miou_metric': 0.9591766595840454, 'Val/mean f1': 0.9757224917411804, 'Val/mean precision': 0.9732718467712402, 'Val/mean recall': 0.9781853556632996, 'Val/mean hd95_metric': 5.419707775115967} +Cheakpoint... +Epoch [2724/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973776638507843, 'Val/mean miou_metric': 0.9591766595840454, 'Val/mean f1': 0.9757224917411804, 'Val/mean precision': 0.9732718467712402, 'Val/mean recall': 0.9781853556632996, 'Val/mean hd95_metric': 5.419707775115967} +Epoch [2725/4000] Training [1/16] Loss: 0.00461 +Epoch [2725/4000] Training [2/16] Loss: 0.00460 +Epoch [2725/4000] Training [3/16] Loss: 0.00334 +Epoch [2725/4000] Training [4/16] Loss: 0.00440 +Epoch [2725/4000] Training [5/16] Loss: 0.00329 +Epoch [2725/4000] Training [6/16] Loss: 0.00381 +Epoch [2725/4000] Training [7/16] Loss: 0.00307 +Epoch [2725/4000] Training [8/16] Loss: 0.00405 +Epoch [2725/4000] Training [9/16] Loss: 0.00323 +Epoch [2725/4000] Training [10/16] Loss: 0.00372 +Epoch [2725/4000] Training [11/16] Loss: 0.00355 +Epoch [2725/4000] Training [12/16] Loss: 0.00357 +Epoch [2725/4000] Training [13/16] Loss: 0.00320 +Epoch [2725/4000] Training [14/16] Loss: 0.00516 +Epoch [2725/4000] Training [15/16] Loss: 0.00390 +Epoch [2725/4000] Training [16/16] Loss: 0.00430 +Epoch [2725/4000] Training metric {'Train/mean dice_metric': 0.997724175453186, 'Train/mean miou_metric': 0.9951710104942322, 'Train/mean f1': 0.9927061200141907, 'Train/mean precision': 0.9879053235054016, 'Train/mean recall': 0.997553825378418, 'Train/mean hd95_metric': 0.8704376816749573} +Epoch [2725/4000] Validation [1/4] Loss: 0.51649 focal_loss 0.41414 dice_loss 0.10235 +Epoch [2725/4000] Validation [2/4] Loss: 0.97687 focal_loss 0.74292 dice_loss 0.23395 +Epoch [2725/4000] Validation [3/4] Loss: 0.40139 focal_loss 0.30887 dice_loss 0.09251 +Epoch [2725/4000] Validation [4/4] Loss: 0.41843 focal_loss 0.29521 dice_loss 0.12321 +Epoch [2725/4000] Validation metric {'Val/mean dice_metric': 0.9704629778862, 'Val/mean miou_metric': 0.954736590385437, 'Val/mean f1': 0.9738450050354004, 'Val/mean precision': 0.973685085773468, 'Val/mean recall': 0.9740050435066223, 'Val/mean hd95_metric': 5.381108283996582} +Cheakpoint... +Epoch [2725/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704629778862, 'Val/mean miou_metric': 0.954736590385437, 'Val/mean f1': 0.9738450050354004, 'Val/mean precision': 0.973685085773468, 'Val/mean recall': 0.9740050435066223, 'Val/mean hd95_metric': 5.381108283996582} +Epoch [2726/4000] Training [1/16] Loss: 0.00310 +Epoch [2726/4000] Training [2/16] Loss: 0.00365 +Epoch [2726/4000] Training [3/16] Loss: 0.00246 +Epoch [2726/4000] Training [4/16] Loss: 0.00326 +Epoch [2726/4000] Training [5/16] Loss: 0.00379 +Epoch [2726/4000] Training [6/16] Loss: 0.00368 +Epoch [2726/4000] Training [7/16] Loss: 0.00319 +Epoch [2726/4000] Training [8/16] Loss: 0.00257 +Epoch [2726/4000] Training [9/16] Loss: 0.00395 +Epoch [2726/4000] Training [10/16] Loss: 0.00270 +Epoch [2726/4000] Training [11/16] Loss: 0.00382 +Epoch [2726/4000] Training [12/16] Loss: 0.00259 +Epoch [2726/4000] Training [13/16] Loss: 0.00462 +Epoch [2726/4000] Training [14/16] Loss: 0.00408 +Epoch [2726/4000] Training [15/16] Loss: 0.00383 +Epoch [2726/4000] Training [16/16] Loss: 0.00315 +Epoch [2726/4000] Training metric {'Train/mean dice_metric': 0.9979442358016968, 'Train/mean miou_metric': 0.9956139326095581, 'Train/mean f1': 0.9930562973022461, 'Train/mean precision': 0.9883771538734436, 'Train/mean recall': 0.9977799654006958, 'Train/mean hd95_metric': 0.8927310705184937} +Epoch [2726/4000] Validation [1/4] Loss: 0.42001 focal_loss 0.34852 dice_loss 0.07149 +Epoch [2726/4000] Validation [2/4] Loss: 0.38561 focal_loss 0.27813 dice_loss 0.10748 +Epoch [2726/4000] Validation [3/4] Loss: 0.47925 focal_loss 0.38222 dice_loss 0.09702 +Epoch [2726/4000] Validation [4/4] Loss: 0.31720 focal_loss 0.22167 dice_loss 0.09553 +Epoch [2726/4000] Validation metric {'Val/mean dice_metric': 0.9739300012588501, 'Val/mean miou_metric': 0.9590862989425659, 'Val/mean f1': 0.9754462242126465, 'Val/mean precision': 0.9725413918495178, 'Val/mean recall': 0.9783685207366943, 'Val/mean hd95_metric': 5.5766801834106445} +Cheakpoint... +Epoch [2726/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739300012588501, 'Val/mean miou_metric': 0.9590862989425659, 'Val/mean f1': 0.9754462242126465, 'Val/mean precision': 0.9725413918495178, 'Val/mean recall': 0.9783685207366943, 'Val/mean hd95_metric': 5.5766801834106445} +Epoch [2727/4000] Training [1/16] Loss: 0.00448 +Epoch [2727/4000] Training [2/16] Loss: 0.00338 +Epoch [2727/4000] Training [3/16] Loss: 0.00386 +Epoch [2727/4000] Training [4/16] Loss: 0.00323 +Epoch [2727/4000] Training [5/16] Loss: 0.00394 +Epoch [2727/4000] Training [6/16] Loss: 0.00333 +Epoch [2727/4000] Training [7/16] Loss: 0.00323 +Epoch [2727/4000] Training [8/16] Loss: 0.00380 +Epoch [2727/4000] Training [9/16] Loss: 0.00325 +Epoch [2727/4000] Training [10/16] Loss: 0.00437 +Epoch [2727/4000] Training [11/16] Loss: 0.00290 +Epoch [2727/4000] Training [12/16] Loss: 0.00412 +Epoch [2727/4000] Training [13/16] Loss: 0.00323 +Epoch [2727/4000] Training [14/16] Loss: 0.00340 +Epoch [2727/4000] Training [15/16] Loss: 0.00275 +Epoch [2727/4000] Training [16/16] Loss: 0.00426 +Epoch [2727/4000] Training metric {'Train/mean dice_metric': 0.9978534579277039, 'Train/mean miou_metric': 0.9954297542572021, 'Train/mean f1': 0.9928747415542603, 'Train/mean precision': 0.9880913496017456, 'Train/mean recall': 0.9977046251296997, 'Train/mean hd95_metric': 0.886258065700531} +Epoch [2727/4000] Validation [1/4] Loss: 0.35911 focal_loss 0.29229 dice_loss 0.06683 +Epoch [2727/4000] Validation [2/4] Loss: 0.98709 focal_loss 0.72229 dice_loss 0.26479 +Epoch [2727/4000] Validation [3/4] Loss: 0.26575 focal_loss 0.18644 dice_loss 0.07931 +Epoch [2727/4000] Validation [4/4] Loss: 0.28470 focal_loss 0.20166 dice_loss 0.08304 +Epoch [2727/4000] Validation metric {'Val/mean dice_metric': 0.9710756540298462, 'Val/mean miou_metric': 0.9571730494499207, 'Val/mean f1': 0.9747740030288696, 'Val/mean precision': 0.9725341200828552, 'Val/mean recall': 0.9770243763923645, 'Val/mean hd95_metric': 5.4560441970825195} +Cheakpoint... +Epoch [2727/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710756540298462, 'Val/mean miou_metric': 0.9571730494499207, 'Val/mean f1': 0.9747740030288696, 'Val/mean precision': 0.9725341200828552, 'Val/mean recall': 0.9770243763923645, 'Val/mean hd95_metric': 5.4560441970825195} +Epoch [2728/4000] Training [1/16] Loss: 0.00301 +Epoch [2728/4000] Training [2/16] Loss: 0.00257 +Epoch [2728/4000] Training [3/16] Loss: 0.00334 +Epoch [2728/4000] Training [4/16] Loss: 0.00308 +Epoch [2728/4000] Training [5/16] Loss: 0.00366 +Epoch [2728/4000] Training [6/16] Loss: 0.00303 +Epoch [2728/4000] Training [7/16] Loss: 0.00266 +Epoch [2728/4000] Training [8/16] Loss: 0.00323 +Epoch [2728/4000] Training [9/16] Loss: 0.00334 +Epoch [2728/4000] Training [10/16] Loss: 0.00404 +Epoch [2728/4000] Training [11/16] Loss: 0.00444 +Epoch [2728/4000] Training [12/16] Loss: 0.00336 +Epoch [2728/4000] Training [13/16] Loss: 0.00448 +Epoch [2728/4000] Training [14/16] Loss: 0.00304 +Epoch [2728/4000] Training [15/16] Loss: 0.00428 +Epoch [2728/4000] Training [16/16] Loss: 0.00351 +Epoch [2728/4000] Training metric {'Train/mean dice_metric': 0.9979263544082642, 'Train/mean miou_metric': 0.9955905675888062, 'Train/mean f1': 0.9931952357292175, 'Train/mean precision': 0.9886561632156372, 'Train/mean recall': 0.9977761507034302, 'Train/mean hd95_metric': 0.8802311420440674} +Epoch [2728/4000] Validation [1/4] Loss: 0.37268 focal_loss 0.30417 dice_loss 0.06851 +Epoch [2728/4000] Validation [2/4] Loss: 0.38908 focal_loss 0.27748 dice_loss 0.11160 +Epoch [2728/4000] Validation [3/4] Loss: 0.46331 focal_loss 0.36737 dice_loss 0.09594 +Epoch [2728/4000] Validation [4/4] Loss: 0.29778 focal_loss 0.21215 dice_loss 0.08563 +Epoch [2728/4000] Validation metric {'Val/mean dice_metric': 0.9738889932632446, 'Val/mean miou_metric': 0.9590730667114258, 'Val/mean f1': 0.9753589034080505, 'Val/mean precision': 0.9733748435974121, 'Val/mean recall': 0.9773510694503784, 'Val/mean hd95_metric': 5.065103530883789} +Cheakpoint... +Epoch [2728/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738889932632446, 'Val/mean miou_metric': 0.9590730667114258, 'Val/mean f1': 0.9753589034080505, 'Val/mean precision': 0.9733748435974121, 'Val/mean recall': 0.9773510694503784, 'Val/mean hd95_metric': 5.065103530883789} +Epoch [2729/4000] Training [1/16] Loss: 0.00442 +Epoch [2729/4000] Training [2/16] Loss: 0.00373 +Epoch [2729/4000] Training [3/16] Loss: 0.00324 +Epoch [2729/4000] Training [4/16] Loss: 0.00411 +Epoch [2729/4000] Training [5/16] Loss: 0.00361 +Epoch [2729/4000] Training [6/16] Loss: 0.00471 +Epoch [2729/4000] Training [7/16] Loss: 0.00347 +Epoch [2729/4000] Training [8/16] Loss: 0.00443 +Epoch [2729/4000] Training [9/16] Loss: 0.00372 +Epoch [2729/4000] Training [10/16] Loss: 0.00409 +Epoch [2729/4000] Training [11/16] Loss: 0.00278 +Epoch [2729/4000] Training [12/16] Loss: 0.00344 +Epoch [2729/4000] Training [13/16] Loss: 0.00393 +Epoch [2729/4000] Training [14/16] Loss: 0.00315 +Epoch [2729/4000] Training [15/16] Loss: 0.00355 +Epoch [2729/4000] Training [16/16] Loss: 0.00271 +Epoch [2729/4000] Training metric {'Train/mean dice_metric': 0.9978493452072144, 'Train/mean miou_metric': 0.9954226613044739, 'Train/mean f1': 0.9928500056266785, 'Train/mean precision': 0.9880949854850769, 'Train/mean recall': 0.9976510405540466, 'Train/mean hd95_metric': 0.8916813135147095} +Epoch [2729/4000] Validation [1/4] Loss: 0.37773 focal_loss 0.30887 dice_loss 0.06885 +Epoch [2729/4000] Validation [2/4] Loss: 0.82699 focal_loss 0.64533 dice_loss 0.18165 +Epoch [2729/4000] Validation [3/4] Loss: 0.43506 focal_loss 0.34514 dice_loss 0.08992 +Epoch [2729/4000] Validation [4/4] Loss: 0.34665 focal_loss 0.23686 dice_loss 0.10980 +Epoch [2729/4000] Validation metric {'Val/mean dice_metric': 0.973219096660614, 'Val/mean miou_metric': 0.9587590098381042, 'Val/mean f1': 0.9754924178123474, 'Val/mean precision': 0.9731456637382507, 'Val/mean recall': 0.9778504967689514, 'Val/mean hd95_metric': 5.06520938873291} +Cheakpoint... +Epoch [2729/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973219096660614, 'Val/mean miou_metric': 0.9587590098381042, 'Val/mean f1': 0.9754924178123474, 'Val/mean precision': 0.9731456637382507, 'Val/mean recall': 0.9778504967689514, 'Val/mean hd95_metric': 5.06520938873291} +Epoch [2730/4000] Training [1/16] Loss: 0.00309 +Epoch [2730/4000] Training [2/16] Loss: 0.00341 +Epoch [2730/4000] Training [3/16] Loss: 0.00378 +Epoch [2730/4000] Training [4/16] Loss: 0.00357 +Epoch [2730/4000] Training [5/16] Loss: 0.00372 +Epoch [2730/4000] Training [6/16] Loss: 0.00315 +Epoch [2730/4000] Training [7/16] Loss: 0.00516 +Epoch [2730/4000] Training [8/16] Loss: 0.00477 +Epoch [2730/4000] Training [9/16] Loss: 0.00437 +Epoch [2730/4000] Training [10/16] Loss: 0.00312 +Epoch [2730/4000] Training [11/16] Loss: 0.00410 +Epoch [2730/4000] Training [12/16] Loss: 0.00542 +Epoch [2730/4000] Training [13/16] Loss: 0.00392 +Epoch [2730/4000] Training [14/16] Loss: 0.00227 +Epoch [2730/4000] Training [15/16] Loss: 0.00455 +Epoch [2730/4000] Training [16/16] Loss: 0.00372 +Epoch [2730/4000] Training metric {'Train/mean dice_metric': 0.9976685047149658, 'Train/mean miou_metric': 0.9950726628303528, 'Train/mean f1': 0.9927699565887451, 'Train/mean precision': 0.988060712814331, 'Train/mean recall': 0.9975243210792542, 'Train/mean hd95_metric': 0.9211353063583374} +Epoch [2730/4000] Validation [1/4] Loss: 0.37936 focal_loss 0.31121 dice_loss 0.06816 +Epoch [2730/4000] Validation [2/4] Loss: 0.70938 focal_loss 0.52200 dice_loss 0.18738 +Epoch [2730/4000] Validation [3/4] Loss: 0.48023 focal_loss 0.37867 dice_loss 0.10157 +Epoch [2730/4000] Validation [4/4] Loss: 0.33373 focal_loss 0.24354 dice_loss 0.09019 +Epoch [2730/4000] Validation metric {'Val/mean dice_metric': 0.9724583625793457, 'Val/mean miou_metric': 0.9573122262954712, 'Val/mean f1': 0.9747292399406433, 'Val/mean precision': 0.9725253582000732, 'Val/mean recall': 0.9769431948661804, 'Val/mean hd95_metric': 5.687520980834961} +Cheakpoint... +Epoch [2730/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724583625793457, 'Val/mean miou_metric': 0.9573122262954712, 'Val/mean f1': 0.9747292399406433, 'Val/mean precision': 0.9725253582000732, 'Val/mean recall': 0.9769431948661804, 'Val/mean hd95_metric': 5.687520980834961} +Epoch [2731/4000] Training [1/16] Loss: 0.00320 +Epoch [2731/4000] Training [2/16] Loss: 0.00475 +Epoch [2731/4000] Training [3/16] Loss: 0.00419 +Epoch [2731/4000] Training [4/16] Loss: 0.00382 +Epoch [2731/4000] Training [5/16] Loss: 0.00389 +Epoch [2731/4000] Training [6/16] Loss: 0.00405 +Epoch [2731/4000] Training [7/16] Loss: 0.00460 +Epoch [2731/4000] Training [8/16] Loss: 0.00372 +Epoch [2731/4000] Training [9/16] Loss: 0.00385 +Epoch [2731/4000] Training [10/16] Loss: 0.00381 +Epoch [2731/4000] Training [11/16] Loss: 0.00337 +Epoch [2731/4000] Training [12/16] Loss: 0.00372 +Epoch [2731/4000] Training [13/16] Loss: 0.00415 +Epoch [2731/4000] Training [14/16] Loss: 0.00315 +Epoch [2731/4000] Training [15/16] Loss: 0.00460 +Epoch [2731/4000] Training [16/16] Loss: 0.00353 +Epoch [2731/4000] Training metric {'Train/mean dice_metric': 0.9974790811538696, 'Train/mean miou_metric': 0.9946984052658081, 'Train/mean f1': 0.9926965236663818, 'Train/mean precision': 0.9881806969642639, 'Train/mean recall': 0.9972537755966187, 'Train/mean hd95_metric': 1.0550940036773682} +Epoch [2731/4000] Validation [1/4] Loss: 0.44864 focal_loss 0.37360 dice_loss 0.07504 +Epoch [2731/4000] Validation [2/4] Loss: 0.63083 focal_loss 0.45069 dice_loss 0.18014 +Epoch [2731/4000] Validation [3/4] Loss: 0.26440 focal_loss 0.19276 dice_loss 0.07164 +Epoch [2731/4000] Validation [4/4] Loss: 0.32310 focal_loss 0.23164 dice_loss 0.09146 +Epoch [2731/4000] Validation metric {'Val/mean dice_metric': 0.9715210199356079, 'Val/mean miou_metric': 0.9563583135604858, 'Val/mean f1': 0.9742444157600403, 'Val/mean precision': 0.975492000579834, 'Val/mean recall': 0.973000168800354, 'Val/mean hd95_metric': 5.673866271972656} +Cheakpoint... +Epoch [2731/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715210199356079, 'Val/mean miou_metric': 0.9563583135604858, 'Val/mean f1': 0.9742444157600403, 'Val/mean precision': 0.975492000579834, 'Val/mean recall': 0.973000168800354, 'Val/mean hd95_metric': 5.673866271972656} +Epoch [2732/4000] Training [1/16] Loss: 0.00599 +Epoch [2732/4000] Training [2/16] Loss: 0.00318 +Epoch [2732/4000] Training [3/16] Loss: 0.00355 +Epoch [2732/4000] Training [4/16] Loss: 0.00349 +Epoch [2732/4000] Training [5/16] Loss: 0.00426 +Epoch [2732/4000] Training [6/16] Loss: 0.00545 +Epoch [2732/4000] Training [7/16] Loss: 0.00499 +Epoch [2732/4000] Training [8/16] Loss: 0.00426 +Epoch [2732/4000] Training [9/16] Loss: 0.00309 +Epoch [2732/4000] Training [10/16] Loss: 0.00496 +Epoch [2732/4000] Training [11/16] Loss: 0.00433 +Epoch [2732/4000] Training [12/16] Loss: 0.00271 +Epoch [2732/4000] Training [13/16] Loss: 0.00434 +Epoch [2732/4000] Training [14/16] Loss: 0.00302 +Epoch [2732/4000] Training [15/16] Loss: 0.00247 +Epoch [2732/4000] Training [16/16] Loss: 0.00277 +Epoch [2732/4000] Training metric {'Train/mean dice_metric': 0.9976174831390381, 'Train/mean miou_metric': 0.9949508905410767, 'Train/mean f1': 0.9923259019851685, 'Train/mean precision': 0.9873297810554504, 'Train/mean recall': 0.9973728060722351, 'Train/mean hd95_metric': 0.9335231781005859} +Epoch [2732/4000] Validation [1/4] Loss: 0.33691 focal_loss 0.27289 dice_loss 0.06402 +Epoch [2732/4000] Validation [2/4] Loss: 0.76189 focal_loss 0.58078 dice_loss 0.18111 +Epoch [2732/4000] Validation [3/4] Loss: 0.24562 focal_loss 0.18150 dice_loss 0.06412 +Epoch [2732/4000] Validation [4/4] Loss: 0.38231 focal_loss 0.25610 dice_loss 0.12620 +Epoch [2732/4000] Validation metric {'Val/mean dice_metric': 0.9697054028511047, 'Val/mean miou_metric': 0.9552878141403198, 'Val/mean f1': 0.9744693636894226, 'Val/mean precision': 0.9746962189674377, 'Val/mean recall': 0.9742425084114075, 'Val/mean hd95_metric': 5.4371771812438965} +Cheakpoint... +Epoch [2732/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9697], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9697054028511047, 'Val/mean miou_metric': 0.9552878141403198, 'Val/mean f1': 0.9744693636894226, 'Val/mean precision': 0.9746962189674377, 'Val/mean recall': 0.9742425084114075, 'Val/mean hd95_metric': 5.4371771812438965} +Epoch [2733/4000] Training [1/16] Loss: 0.00327 +Epoch [2733/4000] Training [2/16] Loss: 0.00523 +Epoch [2733/4000] Training [3/16] Loss: 0.00555 +Epoch [2733/4000] Training [4/16] Loss: 0.00327 +Epoch [2733/4000] Training [5/16] Loss: 0.00274 +Epoch [2733/4000] Training [6/16] Loss: 0.00315 +Epoch [2733/4000] Training [7/16] Loss: 0.00424 +Epoch [2733/4000] Training [8/16] Loss: 0.00406 +Epoch [2733/4000] Training [9/16] Loss: 0.00342 +Epoch [2733/4000] Training [10/16] Loss: 0.00446 +Epoch [2733/4000] Training [11/16] Loss: 0.00375 +Epoch [2733/4000] Training [12/16] Loss: 0.00385 +Epoch [2733/4000] Training [13/16] Loss: 0.00259 +Epoch [2733/4000] Training [14/16] Loss: 0.00350 +Epoch [2733/4000] Training [15/16] Loss: 0.00334 +Epoch [2733/4000] Training [16/16] Loss: 0.00324 +Epoch [2733/4000] Training metric {'Train/mean dice_metric': 0.99769127368927, 'Train/mean miou_metric': 0.9951239824295044, 'Train/mean f1': 0.9930095076560974, 'Train/mean precision': 0.988510012626648, 'Train/mean recall': 0.9975501894950867, 'Train/mean hd95_metric': 0.9006384611129761} +Epoch [2733/4000] Validation [1/4] Loss: 0.37702 focal_loss 0.31199 dice_loss 0.06503 +Epoch [2733/4000] Validation [2/4] Loss: 0.76348 focal_loss 0.58672 dice_loss 0.17676 +Epoch [2733/4000] Validation [3/4] Loss: 0.43638 focal_loss 0.34833 dice_loss 0.08805 +Epoch [2733/4000] Validation [4/4] Loss: 0.27383 focal_loss 0.18390 dice_loss 0.08993 +Epoch [2733/4000] Validation metric {'Val/mean dice_metric': 0.9720985293388367, 'Val/mean miou_metric': 0.9579029083251953, 'Val/mean f1': 0.9755384922027588, 'Val/mean precision': 0.9736358523368835, 'Val/mean recall': 0.9774485230445862, 'Val/mean hd95_metric': 5.545196056365967} +Cheakpoint... +Epoch [2733/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720985293388367, 'Val/mean miou_metric': 0.9579029083251953, 'Val/mean f1': 0.9755384922027588, 'Val/mean precision': 0.9736358523368835, 'Val/mean recall': 0.9774485230445862, 'Val/mean hd95_metric': 5.545196056365967} +Epoch [2734/4000] Training [1/16] Loss: 0.00485 +Epoch [2734/4000] Training [2/16] Loss: 0.00571 +Epoch [2734/4000] Training [3/16] Loss: 0.00502 +Epoch [2734/4000] Training [4/16] Loss: 0.00363 +Epoch [2734/4000] Training [5/16] Loss: 0.00425 +Epoch [2734/4000] Training [6/16] Loss: 0.00450 +Epoch [2734/4000] Training [7/16] Loss: 0.00390 +Epoch [2734/4000] Training [8/16] Loss: 0.00338 +Epoch [2734/4000] Training [9/16] Loss: 0.00300 +Epoch [2734/4000] Training [10/16] Loss: 0.00571 +Epoch [2734/4000] Training [11/16] Loss: 0.00412 +Epoch [2734/4000] Training [12/16] Loss: 0.00377 +Epoch [2734/4000] Training [13/16] Loss: 0.00273 +Epoch [2734/4000] Training [14/16] Loss: 0.00500 +Epoch [2734/4000] Training [15/16] Loss: 0.00399 +Epoch [2734/4000] Training [16/16] Loss: 0.00410 +Epoch [2734/4000] Training metric {'Train/mean dice_metric': 0.99741530418396, 'Train/mean miou_metric': 0.9945323467254639, 'Train/mean f1': 0.9920313358306885, 'Train/mean precision': 0.9868043065071106, 'Train/mean recall': 0.9973140358924866, 'Train/mean hd95_metric': 0.9523894786834717} +Epoch [2734/4000] Validation [1/4] Loss: 0.41952 focal_loss 0.35044 dice_loss 0.06908 +Epoch [2734/4000] Validation [2/4] Loss: 0.60468 focal_loss 0.44432 dice_loss 0.16036 +Epoch [2734/4000] Validation [3/4] Loss: 0.27864 focal_loss 0.20717 dice_loss 0.07147 +Epoch [2734/4000] Validation [4/4] Loss: 0.27404 focal_loss 0.18641 dice_loss 0.08763 +Epoch [2734/4000] Validation metric {'Val/mean dice_metric': 0.972303032875061, 'Val/mean miou_metric': 0.9576187133789062, 'Val/mean f1': 0.9746447205543518, 'Val/mean precision': 0.9733086228370667, 'Val/mean recall': 0.9759845733642578, 'Val/mean hd95_metric': 5.247256278991699} +Cheakpoint... +Epoch [2734/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972303032875061, 'Val/mean miou_metric': 0.9576187133789062, 'Val/mean f1': 0.9746447205543518, 'Val/mean precision': 0.9733086228370667, 'Val/mean recall': 0.9759845733642578, 'Val/mean hd95_metric': 5.247256278991699} +Epoch [2735/4000] Training [1/16] Loss: 0.00488 +Epoch [2735/4000] Training [2/16] Loss: 0.00318 +Epoch [2735/4000] Training [3/16] Loss: 0.00314 +Epoch [2735/4000] Training [4/16] Loss: 0.00316 +Epoch [2735/4000] Training [5/16] Loss: 0.00301 +Epoch [2735/4000] Training [6/16] Loss: 0.00359 +Epoch [2735/4000] Training [7/16] Loss: 0.00306 +Epoch [2735/4000] Training [8/16] Loss: 0.00405 +Epoch [2735/4000] Training [9/16] Loss: 0.00374 +Epoch [2735/4000] Training [10/16] Loss: 0.00388 +Epoch [2735/4000] Training [11/16] Loss: 0.00331 +Epoch [2735/4000] Training [12/16] Loss: 0.00558 +Epoch [2735/4000] Training [13/16] Loss: 0.00361 +Epoch [2735/4000] Training [14/16] Loss: 0.00386 +Epoch [2735/4000] Training [15/16] Loss: 0.00380 +Epoch [2735/4000] Training [16/16] Loss: 0.00312 +Epoch [2735/4000] Training metric {'Train/mean dice_metric': 0.9979124069213867, 'Train/mean miou_metric': 0.9955627918243408, 'Train/mean f1': 0.9931283593177795, 'Train/mean precision': 0.9886404275894165, 'Train/mean recall': 0.9976572394371033, 'Train/mean hd95_metric': 0.87815260887146} +Epoch [2735/4000] Validation [1/4] Loss: 0.40651 focal_loss 0.33537 dice_loss 0.07114 +Epoch [2735/4000] Validation [2/4] Loss: 0.82593 focal_loss 0.60938 dice_loss 0.21655 +Epoch [2735/4000] Validation [3/4] Loss: 0.42456 focal_loss 0.33390 dice_loss 0.09066 +Epoch [2735/4000] Validation [4/4] Loss: 0.31593 focal_loss 0.22796 dice_loss 0.08797 +Epoch [2735/4000] Validation metric {'Val/mean dice_metric': 0.9708442687988281, 'Val/mean miou_metric': 0.9560154676437378, 'Val/mean f1': 0.9743703007698059, 'Val/mean precision': 0.9730774760246277, 'Val/mean recall': 0.9756664037704468, 'Val/mean hd95_metric': 5.97659158706665} +Cheakpoint... +Epoch [2735/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708442687988281, 'Val/mean miou_metric': 0.9560154676437378, 'Val/mean f1': 0.9743703007698059, 'Val/mean precision': 0.9730774760246277, 'Val/mean recall': 0.9756664037704468, 'Val/mean hd95_metric': 5.97659158706665} +Epoch [2736/4000] Training [1/16] Loss: 0.00311 +Epoch [2736/4000] Training [2/16] Loss: 0.00304 +Epoch [2736/4000] Training [3/16] Loss: 0.00354 +Epoch [2736/4000] Training [4/16] Loss: 0.00403 +Epoch [2736/4000] Training [5/16] Loss: 0.00289 +Epoch [2736/4000] Training [6/16] Loss: 0.00357 +Epoch [2736/4000] Training [7/16] Loss: 0.00331 +Epoch [2736/4000] Training [8/16] Loss: 0.00398 +Epoch [2736/4000] Training [9/16] Loss: 0.00308 +Epoch [2736/4000] Training [10/16] Loss: 0.00312 +Epoch [2736/4000] Training [11/16] Loss: 0.00366 +Epoch [2736/4000] Training [12/16] Loss: 0.00375 +Epoch [2736/4000] Training [13/16] Loss: 0.00367 +Epoch [2736/4000] Training [14/16] Loss: 0.00244 +Epoch [2736/4000] Training [15/16] Loss: 0.00316 +Epoch [2736/4000] Training [16/16] Loss: 0.00343 +Epoch [2736/4000] Training metric {'Train/mean dice_metric': 0.9979523420333862, 'Train/mean miou_metric': 0.995642364025116, 'Train/mean f1': 0.9931403994560242, 'Train/mean precision': 0.9886190295219421, 'Train/mean recall': 0.9977033138275146, 'Train/mean hd95_metric': 0.8511995077133179} +Epoch [2736/4000] Validation [1/4] Loss: 0.36628 focal_loss 0.30050 dice_loss 0.06578 +Epoch [2736/4000] Validation [2/4] Loss: 0.68494 focal_loss 0.50673 dice_loss 0.17822 +Epoch [2736/4000] Validation [3/4] Loss: 0.45965 focal_loss 0.36728 dice_loss 0.09237 +Epoch [2736/4000] Validation [4/4] Loss: 0.36128 focal_loss 0.25673 dice_loss 0.10455 +Epoch [2736/4000] Validation metric {'Val/mean dice_metric': 0.9721639752388, 'Val/mean miou_metric': 0.957440197467804, 'Val/mean f1': 0.974499523639679, 'Val/mean precision': 0.9736571907997131, 'Val/mean recall': 0.9753432273864746, 'Val/mean hd95_metric': 5.194416522979736} +Cheakpoint... +Epoch [2736/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721639752388, 'Val/mean miou_metric': 0.957440197467804, 'Val/mean f1': 0.974499523639679, 'Val/mean precision': 0.9736571907997131, 'Val/mean recall': 0.9753432273864746, 'Val/mean hd95_metric': 5.194416522979736} +Epoch [2737/4000] Training [1/16] Loss: 0.00404 +Epoch [2737/4000] Training [2/16] Loss: 0.00308 +Epoch [2737/4000] Training [3/16] Loss: 0.00333 +Epoch [2737/4000] Training [4/16] Loss: 0.00346 +Epoch [2737/4000] Training [5/16] Loss: 0.00322 +Epoch [2737/4000] Training [6/16] Loss: 0.00300 +Epoch [2737/4000] Training [7/16] Loss: 0.00287 +Epoch [2737/4000] Training [8/16] Loss: 0.00339 +Epoch [2737/4000] Training [9/16] Loss: 0.00427 +Epoch [2737/4000] Training [10/16] Loss: 0.00240 +Epoch [2737/4000] Training [11/16] Loss: 0.00649 +Epoch [2737/4000] Training [12/16] Loss: 0.00313 +Epoch [2737/4000] Training [13/16] Loss: 0.00341 +Epoch [2737/4000] Training [14/16] Loss: 0.00308 +Epoch [2737/4000] Training [15/16] Loss: 0.00319 +Epoch [2737/4000] Training [16/16] Loss: 0.00303 +Epoch [2737/4000] Training metric {'Train/mean dice_metric': 0.9980034232139587, 'Train/mean miou_metric': 0.995715856552124, 'Train/mean f1': 0.9926287531852722, 'Train/mean precision': 0.9875349998474121, 'Train/mean recall': 0.9977753758430481, 'Train/mean hd95_metric': 0.8568645715713501} +Epoch [2737/4000] Validation [1/4] Loss: 0.37071 focal_loss 0.30146 dice_loss 0.06925 +Epoch [2737/4000] Validation [2/4] Loss: 0.46057 focal_loss 0.33282 dice_loss 0.12774 +Epoch [2737/4000] Validation [3/4] Loss: 0.44227 focal_loss 0.35282 dice_loss 0.08944 +Epoch [2737/4000] Validation [4/4] Loss: 0.36616 focal_loss 0.25350 dice_loss 0.11267 +Epoch [2737/4000] Validation metric {'Val/mean dice_metric': 0.9724515080451965, 'Val/mean miou_metric': 0.9579111337661743, 'Val/mean f1': 0.9751502275466919, 'Val/mean precision': 0.973097562789917, 'Val/mean recall': 0.9772113561630249, 'Val/mean hd95_metric': 5.116325855255127} +Cheakpoint... +Epoch [2737/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724515080451965, 'Val/mean miou_metric': 0.9579111337661743, 'Val/mean f1': 0.9751502275466919, 'Val/mean precision': 0.973097562789917, 'Val/mean recall': 0.9772113561630249, 'Val/mean hd95_metric': 5.116325855255127} +Epoch [2738/4000] Training [1/16] Loss: 0.00446 +Epoch [2738/4000] Training [2/16] Loss: 0.00314 +Epoch [2738/4000] Training [3/16] Loss: 0.00499 +Epoch [2738/4000] Training [4/16] Loss: 0.00292 +Epoch [2738/4000] Training [5/16] Loss: 0.00252 +Epoch [2738/4000] Training [6/16] Loss: 0.00424 +Epoch [2738/4000] Training [7/16] Loss: 0.00324 +Epoch [2738/4000] Training [8/16] Loss: 0.00397 +Epoch [2738/4000] Training [9/16] Loss: 0.00583 +Epoch [2738/4000] Training [10/16] Loss: 0.00384 +Epoch [2738/4000] Training [11/16] Loss: 0.00231 +Epoch [2738/4000] Training [12/16] Loss: 0.00366 +Epoch [2738/4000] Training [13/16] Loss: 0.00403 +Epoch [2738/4000] Training [14/16] Loss: 0.00307 +Epoch [2738/4000] Training [15/16] Loss: 0.00318 +Epoch [2738/4000] Training [16/16] Loss: 0.00323 +Epoch [2738/4000] Training metric {'Train/mean dice_metric': 0.9977419376373291, 'Train/mean miou_metric': 0.9952244758605957, 'Train/mean f1': 0.9930907487869263, 'Train/mean precision': 0.9885610938072205, 'Train/mean recall': 0.9976621270179749, 'Train/mean hd95_metric': 0.8608952760696411} +Epoch [2738/4000] Validation [1/4] Loss: 0.37420 focal_loss 0.30930 dice_loss 0.06491 +Epoch [2738/4000] Validation [2/4] Loss: 0.46498 focal_loss 0.33465 dice_loss 0.13032 +Epoch [2738/4000] Validation [3/4] Loss: 0.23895 focal_loss 0.17422 dice_loss 0.06473 +Epoch [2738/4000] Validation [4/4] Loss: 0.29792 focal_loss 0.21643 dice_loss 0.08149 +Epoch [2738/4000] Validation metric {'Val/mean dice_metric': 0.9745439291000366, 'Val/mean miou_metric': 0.9596568942070007, 'Val/mean f1': 0.9761275053024292, 'Val/mean precision': 0.9738364815711975, 'Val/mean recall': 0.9784291982650757, 'Val/mean hd95_metric': 5.064082622528076} +Cheakpoint... +Epoch [2738/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745439291000366, 'Val/mean miou_metric': 0.9596568942070007, 'Val/mean f1': 0.9761275053024292, 'Val/mean precision': 0.9738364815711975, 'Val/mean recall': 0.9784291982650757, 'Val/mean hd95_metric': 5.064082622528076} +Epoch [2739/4000] Training [1/16] Loss: 0.00372 +Epoch [2739/4000] Training [2/16] Loss: 0.00293 +Epoch [2739/4000] Training [3/16] Loss: 0.00429 +Epoch [2739/4000] Training [4/16] Loss: 0.00356 +Epoch [2739/4000] Training [5/16] Loss: 0.00342 +Epoch [2739/4000] Training [6/16] Loss: 0.00454 +Epoch [2739/4000] Training [7/16] Loss: 0.00506 +Epoch [2739/4000] Training [8/16] Loss: 0.00440 +Epoch [2739/4000] Training [9/16] Loss: 0.00262 +Epoch [2739/4000] Training [10/16] Loss: 0.00438 +Epoch [2739/4000] Training [11/16] Loss: 0.00366 +Epoch [2739/4000] Training [12/16] Loss: 0.00394 +Epoch [2739/4000] Training [13/16] Loss: 0.00386 +Epoch [2739/4000] Training [14/16] Loss: 0.00700 +Epoch [2739/4000] Training [15/16] Loss: 0.00340 +Epoch [2739/4000] Training [16/16] Loss: 0.00311 +Epoch [2739/4000] Training metric {'Train/mean dice_metric': 0.9977352023124695, 'Train/mean miou_metric': 0.9951896667480469, 'Train/mean f1': 0.9927761554718018, 'Train/mean precision': 0.9881501793861389, 'Train/mean recall': 0.9974457025527954, 'Train/mean hd95_metric': 0.9025575518608093} +Epoch [2739/4000] Validation [1/4] Loss: 0.35787 focal_loss 0.29316 dice_loss 0.06472 +Epoch [2739/4000] Validation [2/4] Loss: 0.59202 focal_loss 0.41942 dice_loss 0.17260 +Epoch [2739/4000] Validation [3/4] Loss: 0.44858 focal_loss 0.36261 dice_loss 0.08597 +Epoch [2739/4000] Validation [4/4] Loss: 0.35380 focal_loss 0.23882 dice_loss 0.11497 +Epoch [2739/4000] Validation metric {'Val/mean dice_metric': 0.974107563495636, 'Val/mean miou_metric': 0.9587754011154175, 'Val/mean f1': 0.9746987819671631, 'Val/mean precision': 0.9702616930007935, 'Val/mean recall': 0.9791767597198486, 'Val/mean hd95_metric': 5.784802436828613} +Cheakpoint... +Epoch [2739/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974107563495636, 'Val/mean miou_metric': 0.9587754011154175, 'Val/mean f1': 0.9746987819671631, 'Val/mean precision': 0.9702616930007935, 'Val/mean recall': 0.9791767597198486, 'Val/mean hd95_metric': 5.784802436828613} +Epoch [2740/4000] Training [1/16] Loss: 0.00333 +Epoch [2740/4000] Training [2/16] Loss: 0.00380 +Epoch [2740/4000] Training [3/16] Loss: 0.00436 +Epoch [2740/4000] Training [4/16] Loss: 0.00261 +Epoch [2740/4000] Training [5/16] Loss: 0.00291 +Epoch [2740/4000] Training [6/16] Loss: 0.00416 +Epoch [2740/4000] Training [7/16] Loss: 0.00334 +Epoch [2740/4000] Training [8/16] Loss: 0.00274 +Epoch [2740/4000] Training [9/16] Loss: 0.00284 +Epoch [2740/4000] Training [10/16] Loss: 0.00447 +Epoch [2740/4000] Training [11/16] Loss: 0.00312 +Epoch [2740/4000] Training [12/16] Loss: 0.00307 +Epoch [2740/4000] Training [13/16] Loss: 0.00296 +Epoch [2740/4000] Training [14/16] Loss: 0.00382 +Epoch [2740/4000] Training [15/16] Loss: 0.00298 +Epoch [2740/4000] Training [16/16] Loss: 0.00471 +Epoch [2740/4000] Training metric {'Train/mean dice_metric': 0.9980214238166809, 'Train/mean miou_metric': 0.9957654476165771, 'Train/mean f1': 0.9930480122566223, 'Train/mean precision': 0.9884065389633179, 'Train/mean recall': 0.9977332949638367, 'Train/mean hd95_metric': 0.8524690866470337} +Epoch [2740/4000] Validation [1/4] Loss: 0.33708 focal_loss 0.27553 dice_loss 0.06155 +Epoch [2740/4000] Validation [2/4] Loss: 0.45837 focal_loss 0.33009 dice_loss 0.12828 +Epoch [2740/4000] Validation [3/4] Loss: 0.49122 focal_loss 0.39154 dice_loss 0.09968 +Epoch [2740/4000] Validation [4/4] Loss: 0.36413 focal_loss 0.25610 dice_loss 0.10803 +Epoch [2740/4000] Validation metric {'Val/mean dice_metric': 0.9727686047554016, 'Val/mean miou_metric': 0.9580693244934082, 'Val/mean f1': 0.9755300283432007, 'Val/mean precision': 0.972704291343689, 'Val/mean recall': 0.9783722758293152, 'Val/mean hd95_metric': 5.598929405212402} +Cheakpoint... +Epoch [2740/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727686047554016, 'Val/mean miou_metric': 0.9580693244934082, 'Val/mean f1': 0.9755300283432007, 'Val/mean precision': 0.972704291343689, 'Val/mean recall': 0.9783722758293152, 'Val/mean hd95_metric': 5.598929405212402} +Epoch [2741/4000] Training [1/16] Loss: 0.00339 +Epoch [2741/4000] Training [2/16] Loss: 0.00381 +Epoch [2741/4000] Training [3/16] Loss: 0.00279 +Epoch [2741/4000] Training [4/16] Loss: 0.00267 +Epoch [2741/4000] Training [5/16] Loss: 0.00480 +Epoch [2741/4000] Training [6/16] Loss: 0.00422 +Epoch [2741/4000] Training [7/16] Loss: 0.00319 +Epoch [2741/4000] Training [8/16] Loss: 0.00428 +Epoch [2741/4000] Training [9/16] Loss: 0.00234 +Epoch [2741/4000] Training [10/16] Loss: 0.00343 +Epoch [2741/4000] Training [11/16] Loss: 0.04265 +Epoch [2741/4000] Training [12/16] Loss: 0.00345 +Epoch [2741/4000] Training [13/16] Loss: 0.00416 +Epoch [2741/4000] Training [14/16] Loss: 0.00235 +Epoch [2741/4000] Training [15/16] Loss: 0.00522 +Epoch [2741/4000] Training [16/16] Loss: 0.00409 +Epoch [2741/4000] Training metric {'Train/mean dice_metric': 0.9969316720962524, 'Train/mean miou_metric': 0.9938538074493408, 'Train/mean f1': 0.9919748306274414, 'Train/mean precision': 0.9869852066040039, 'Train/mean recall': 0.9970152378082275, 'Train/mean hd95_metric': 1.069959044456482} +Epoch [2741/4000] Validation [1/4] Loss: 0.41074 focal_loss 0.34603 dice_loss 0.06471 +Epoch [2741/4000] Validation [2/4] Loss: 0.67215 focal_loss 0.48310 dice_loss 0.18905 +Epoch [2741/4000] Validation [3/4] Loss: 0.33641 focal_loss 0.24960 dice_loss 0.08681 +Epoch [2741/4000] Validation [4/4] Loss: 0.30424 focal_loss 0.21774 dice_loss 0.08651 +Epoch [2741/4000] Validation metric {'Val/mean dice_metric': 0.973401665687561, 'Val/mean miou_metric': 0.9575108289718628, 'Val/mean f1': 0.9745615124702454, 'Val/mean precision': 0.9723649024963379, 'Val/mean recall': 0.9767681360244751, 'Val/mean hd95_metric': 5.578361988067627} +Cheakpoint... +Epoch [2741/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973401665687561, 'Val/mean miou_metric': 0.9575108289718628, 'Val/mean f1': 0.9745615124702454, 'Val/mean precision': 0.9723649024963379, 'Val/mean recall': 0.9767681360244751, 'Val/mean hd95_metric': 5.578361988067627} +Epoch [2742/4000] Training [1/16] Loss: 0.00442 +Epoch [2742/4000] Training [2/16] Loss: 0.00391 +Epoch [2742/4000] Training [3/16] Loss: 0.00395 +Epoch [2742/4000] Training [4/16] Loss: 0.00336 +Epoch [2742/4000] Training [5/16] Loss: 0.00326 +Epoch [2742/4000] Training [6/16] Loss: 0.00399 +Epoch [2742/4000] Training [7/16] Loss: 0.00239 +Epoch [2742/4000] Training [8/16] Loss: 0.00277 +Epoch [2742/4000] Training [9/16] Loss: 0.00446 +Epoch [2742/4000] Training [10/16] Loss: 0.00359 +Epoch [2742/4000] Training [11/16] Loss: 0.00413 +Epoch [2742/4000] Training [12/16] Loss: 0.00348 +Epoch [2742/4000] Training [13/16] Loss: 0.00479 +Epoch [2742/4000] Training [14/16] Loss: 0.00282 +Epoch [2742/4000] Training [15/16] Loss: 0.00457 +Epoch [2742/4000] Training [16/16] Loss: 0.00473 +Epoch [2742/4000] Training metric {'Train/mean dice_metric': 0.9978188276290894, 'Train/mean miou_metric': 0.9953771829605103, 'Train/mean f1': 0.99302077293396, 'Train/mean precision': 0.9885898232460022, 'Train/mean recall': 0.9974915981292725, 'Train/mean hd95_metric': 0.8710236549377441} +Epoch [2742/4000] Validation [1/4] Loss: 0.37473 focal_loss 0.30577 dice_loss 0.06896 +Epoch [2742/4000] Validation [2/4] Loss: 0.84110 focal_loss 0.66345 dice_loss 0.17765 +Epoch [2742/4000] Validation [3/4] Loss: 0.33720 focal_loss 0.24179 dice_loss 0.09542 +Epoch [2742/4000] Validation [4/4] Loss: 0.35569 focal_loss 0.24144 dice_loss 0.11424 +Epoch [2742/4000] Validation metric {'Val/mean dice_metric': 0.9723159670829773, 'Val/mean miou_metric': 0.9571729898452759, 'Val/mean f1': 0.9747476577758789, 'Val/mean precision': 0.974808394908905, 'Val/mean recall': 0.9746870398521423, 'Val/mean hd95_metric': 5.637687683105469} +Cheakpoint... +Epoch [2742/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723159670829773, 'Val/mean miou_metric': 0.9571729898452759, 'Val/mean f1': 0.9747476577758789, 'Val/mean precision': 0.974808394908905, 'Val/mean recall': 0.9746870398521423, 'Val/mean hd95_metric': 5.637687683105469} +Epoch [2743/4000] Training [1/16] Loss: 0.00376 +Epoch [2743/4000] Training [2/16] Loss: 0.00367 +Epoch [2743/4000] Training [3/16] Loss: 0.00419 +Epoch [2743/4000] Training [4/16] Loss: 0.00309 +Epoch [2743/4000] Training [5/16] Loss: 0.00351 +Epoch [2743/4000] Training [6/16] Loss: 0.00469 +Epoch [2743/4000] Training [7/16] Loss: 0.00303 +Epoch [2743/4000] Training [8/16] Loss: 0.00459 +Epoch [2743/4000] Training [9/16] Loss: 0.00415 +Epoch [2743/4000] Training [10/16] Loss: 0.00518 +Epoch [2743/4000] Training [11/16] Loss: 0.00484 +Epoch [2743/4000] Training [12/16] Loss: 0.00522 +Epoch [2743/4000] Training [13/16] Loss: 0.00311 +Epoch [2743/4000] Training [14/16] Loss: 0.00362 +Epoch [2743/4000] Training [15/16] Loss: 0.00387 +Epoch [2743/4000] Training [16/16] Loss: 0.00284 +Epoch [2743/4000] Training metric {'Train/mean dice_metric': 0.9974864721298218, 'Train/mean miou_metric': 0.9947608709335327, 'Train/mean f1': 0.9927107691764832, 'Train/mean precision': 0.9883817434310913, 'Train/mean recall': 0.9970778822898865, 'Train/mean hd95_metric': 0.9858279228210449} +Epoch [2743/4000] Validation [1/4] Loss: 0.34894 focal_loss 0.28559 dice_loss 0.06334 +Epoch [2743/4000] Validation [2/4] Loss: 1.11196 focal_loss 0.87188 dice_loss 0.24009 +Epoch [2743/4000] Validation [3/4] Loss: 0.30337 focal_loss 0.22838 dice_loss 0.07498 +Epoch [2743/4000] Validation [4/4] Loss: 0.28580 focal_loss 0.20590 dice_loss 0.07990 +Epoch [2743/4000] Validation metric {'Val/mean dice_metric': 0.9716711044311523, 'Val/mean miou_metric': 0.9566706418991089, 'Val/mean f1': 0.9743951559066772, 'Val/mean precision': 0.9725162982940674, 'Val/mean recall': 0.9762812852859497, 'Val/mean hd95_metric': 6.2129621505737305} +Cheakpoint... +Epoch [2743/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716711044311523, 'Val/mean miou_metric': 0.9566706418991089, 'Val/mean f1': 0.9743951559066772, 'Val/mean precision': 0.9725162982940674, 'Val/mean recall': 0.9762812852859497, 'Val/mean hd95_metric': 6.2129621505737305} +Epoch [2744/4000] Training [1/16] Loss: 0.00389 +Epoch [2744/4000] Training [2/16] Loss: 0.00376 +Epoch [2744/4000] Training [3/16] Loss: 0.00341 +Epoch [2744/4000] Training [4/16] Loss: 0.00350 +Epoch [2744/4000] Training [5/16] Loss: 0.00549 +Epoch [2744/4000] Training [6/16] Loss: 0.00383 +Epoch [2744/4000] Training [7/16] Loss: 0.00410 +Epoch [2744/4000] Training [8/16] Loss: 0.00428 +Epoch [2744/4000] Training [9/16] Loss: 0.00660 +Epoch [2744/4000] Training [10/16] Loss: 0.00358 +Epoch [2744/4000] Training [11/16] Loss: 0.00226 +Epoch [2744/4000] Training [12/16] Loss: 0.00522 +Epoch [2744/4000] Training [13/16] Loss: 0.00427 +Epoch [2744/4000] Training [14/16] Loss: 0.00384 +Epoch [2744/4000] Training [15/16] Loss: 0.00318 +Epoch [2744/4000] Training [16/16] Loss: 0.00306 +Epoch [2744/4000] Training metric {'Train/mean dice_metric': 0.9975376129150391, 'Train/mean miou_metric': 0.9947969317436218, 'Train/mean f1': 0.9926266074180603, 'Train/mean precision': 0.9878294467926025, 'Train/mean recall': 0.9974705576896667, 'Train/mean hd95_metric': 0.9324186444282532} +Epoch [2744/4000] Validation [1/4] Loss: 0.34347 focal_loss 0.27944 dice_loss 0.06403 +Epoch [2744/4000] Validation [2/4] Loss: 0.80467 focal_loss 0.54292 dice_loss 0.26175 +Epoch [2744/4000] Validation [3/4] Loss: 0.47808 focal_loss 0.38169 dice_loss 0.09639 +Epoch [2744/4000] Validation [4/4] Loss: 0.36379 focal_loss 0.25888 dice_loss 0.10491 +Epoch [2744/4000] Validation metric {'Val/mean dice_metric': 0.9714080691337585, 'Val/mean miou_metric': 0.9557770490646362, 'Val/mean f1': 0.973842442035675, 'Val/mean precision': 0.9703947305679321, 'Val/mean recall': 0.977314829826355, 'Val/mean hd95_metric': 6.334596157073975} +Cheakpoint... +Epoch [2744/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714080691337585, 'Val/mean miou_metric': 0.9557770490646362, 'Val/mean f1': 0.973842442035675, 'Val/mean precision': 0.9703947305679321, 'Val/mean recall': 0.977314829826355, 'Val/mean hd95_metric': 6.334596157073975} +Epoch [2745/4000] Training [1/16] Loss: 0.00471 +Epoch [2745/4000] Training [2/16] Loss: 0.00231 +Epoch [2745/4000] Training [3/16] Loss: 0.00373 +Epoch [2745/4000] Training [4/16] Loss: 0.00435 +Epoch [2745/4000] Training [5/16] Loss: 0.00391 +Epoch [2745/4000] Training [6/16] Loss: 0.00414 +Epoch [2745/4000] Training [7/16] Loss: 0.00600 +Epoch [2745/4000] Training [8/16] Loss: 0.00369 +Epoch [2745/4000] Training [9/16] Loss: 0.00474 +Epoch [2745/4000] Training [10/16] Loss: 0.00664 +Epoch [2745/4000] Training [11/16] Loss: 0.00255 +Epoch [2745/4000] Training [12/16] Loss: 0.00440 +Epoch [2745/4000] Training [13/16] Loss: 0.00336 +Epoch [2745/4000] Training [14/16] Loss: 0.00412 +Epoch [2745/4000] Training [15/16] Loss: 0.00293 +Epoch [2745/4000] Training [16/16] Loss: 0.00427 +Epoch [2745/4000] Training metric {'Train/mean dice_metric': 0.9977627396583557, 'Train/mean miou_metric': 0.9952468872070312, 'Train/mean f1': 0.9927360415458679, 'Train/mean precision': 0.9878993630409241, 'Train/mean recall': 0.9976202249526978, 'Train/mean hd95_metric': 0.8722540140151978} +Epoch [2745/4000] Validation [1/4] Loss: 0.40106 focal_loss 0.33535 dice_loss 0.06571 +Epoch [2745/4000] Validation [2/4] Loss: 0.54351 focal_loss 0.38567 dice_loss 0.15784 +Epoch [2745/4000] Validation [3/4] Loss: 0.46268 focal_loss 0.36865 dice_loss 0.09403 +Epoch [2745/4000] Validation [4/4] Loss: 0.42280 focal_loss 0.30860 dice_loss 0.11420 +Epoch [2745/4000] Validation metric {'Val/mean dice_metric': 0.9722091555595398, 'Val/mean miou_metric': 0.9575279951095581, 'Val/mean f1': 0.9746192693710327, 'Val/mean precision': 0.9711588025093079, 'Val/mean recall': 0.9781044721603394, 'Val/mean hd95_metric': 5.765753746032715} +Cheakpoint... +Epoch [2745/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722091555595398, 'Val/mean miou_metric': 0.9575279951095581, 'Val/mean f1': 0.9746192693710327, 'Val/mean precision': 0.9711588025093079, 'Val/mean recall': 0.9781044721603394, 'Val/mean hd95_metric': 5.765753746032715} +Epoch [2746/4000] Training [1/16] Loss: 0.00268 +Epoch [2746/4000] Training [2/16] Loss: 0.00447 +Epoch [2746/4000] Training [3/16] Loss: 0.00516 +Epoch [2746/4000] Training [4/16] Loss: 0.00351 +Epoch [2746/4000] Training [5/16] Loss: 0.00262 +Epoch [2746/4000] Training [6/16] Loss: 0.00612 +Epoch [2746/4000] Training [7/16] Loss: 0.00236 +Epoch [2746/4000] Training [8/16] Loss: 0.00802 +Epoch [2746/4000] Training [9/16] Loss: 0.00236 +Epoch [2746/4000] Training [10/16] Loss: 0.00283 +Epoch [2746/4000] Training [11/16] Loss: 0.00337 +Epoch [2746/4000] Training [12/16] Loss: 0.00369 +Epoch [2746/4000] Training [13/16] Loss: 0.00395 +Epoch [2746/4000] Training [14/16] Loss: 0.00467 +Epoch [2746/4000] Training [15/16] Loss: 0.00439 +Epoch [2746/4000] Training [16/16] Loss: 0.00256 +Epoch [2746/4000] Training metric {'Train/mean dice_metric': 0.9972919821739197, 'Train/mean miou_metric': 0.994407057762146, 'Train/mean f1': 0.9924299716949463, 'Train/mean precision': 0.9882820844650269, 'Train/mean recall': 0.9966128468513489, 'Train/mean hd95_metric': 1.0039348602294922} +Epoch [2746/4000] Validation [1/4] Loss: 0.36508 focal_loss 0.30270 dice_loss 0.06238 +Epoch [2746/4000] Validation [2/4] Loss: 0.46794 focal_loss 0.32783 dice_loss 0.14012 +Epoch [2746/4000] Validation [3/4] Loss: 0.43984 focal_loss 0.34942 dice_loss 0.09042 +Epoch [2746/4000] Validation [4/4] Loss: 0.36222 focal_loss 0.26326 dice_loss 0.09896 +Epoch [2746/4000] Validation metric {'Val/mean dice_metric': 0.9724868535995483, 'Val/mean miou_metric': 0.9578207731246948, 'Val/mean f1': 0.9751601219177246, 'Val/mean precision': 0.9720861315727234, 'Val/mean recall': 0.9782536625862122, 'Val/mean hd95_metric': 5.929774284362793} +Cheakpoint... +Epoch [2746/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724868535995483, 'Val/mean miou_metric': 0.9578207731246948, 'Val/mean f1': 0.9751601219177246, 'Val/mean precision': 0.9720861315727234, 'Val/mean recall': 0.9782536625862122, 'Val/mean hd95_metric': 5.929774284362793} +Epoch [2747/4000] Training [1/16] Loss: 0.00540 +Epoch [2747/4000] Training [2/16] Loss: 0.00371 +Epoch [2747/4000] Training [3/16] Loss: 0.00444 +Epoch [2747/4000] Training [4/16] Loss: 0.00273 +Epoch [2747/4000] Training [5/16] Loss: 0.00259 +Epoch [2747/4000] Training [6/16] Loss: 0.00459 +Epoch [2747/4000] Training [7/16] Loss: 0.00446 +Epoch [2747/4000] Training [8/16] Loss: 0.00378 +Epoch [2747/4000] Training [9/16] Loss: 0.00287 +Epoch [2747/4000] Training [10/16] Loss: 0.00318 +Epoch [2747/4000] Training [11/16] Loss: 0.00337 +Epoch [2747/4000] Training [12/16] Loss: 0.00356 +Epoch [2747/4000] Training [13/16] Loss: 0.00311 +Epoch [2747/4000] Training [14/16] Loss: 0.00263 +Epoch [2747/4000] Training [15/16] Loss: 0.00366 +Epoch [2747/4000] Training [16/16] Loss: 0.00261 +Epoch [2747/4000] Training metric {'Train/mean dice_metric': 0.9978271722793579, 'Train/mean miou_metric': 0.9953821897506714, 'Train/mean f1': 0.9929607510566711, 'Train/mean precision': 0.9882559180259705, 'Train/mean recall': 0.997710645198822, 'Train/mean hd95_metric': 0.8962478637695312} +Epoch [2747/4000] Validation [1/4] Loss: 0.36403 focal_loss 0.30005 dice_loss 0.06398 +Epoch [2747/4000] Validation [2/4] Loss: 0.69679 focal_loss 0.51378 dice_loss 0.18301 +Epoch [2747/4000] Validation [3/4] Loss: 0.46059 focal_loss 0.36086 dice_loss 0.09973 +Epoch [2747/4000] Validation [4/4] Loss: 0.37917 focal_loss 0.27816 dice_loss 0.10101 +Epoch [2747/4000] Validation metric {'Val/mean dice_metric': 0.9703838229179382, 'Val/mean miou_metric': 0.9555737376213074, 'Val/mean f1': 0.9740896224975586, 'Val/mean precision': 0.9704529643058777, 'Val/mean recall': 0.9777536392211914, 'Val/mean hd95_metric': 6.135001182556152} +Cheakpoint... +Epoch [2747/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703838229179382, 'Val/mean miou_metric': 0.9555737376213074, 'Val/mean f1': 0.9740896224975586, 'Val/mean precision': 0.9704529643058777, 'Val/mean recall': 0.9777536392211914, 'Val/mean hd95_metric': 6.135001182556152} +Epoch [2748/4000] Training [1/16] Loss: 0.00318 +Epoch [2748/4000] Training [2/16] Loss: 0.00323 +Epoch [2748/4000] Training [3/16] Loss: 0.00463 +Epoch [2748/4000] Training [4/16] Loss: 0.00328 +Epoch [2748/4000] Training [5/16] Loss: 0.00340 +Epoch [2748/4000] Training [6/16] Loss: 0.00278 +Epoch [2748/4000] Training [7/16] Loss: 0.00346 +Epoch [2748/4000] Training [8/16] Loss: 0.00330 +Epoch [2748/4000] Training [9/16] Loss: 0.00402 +Epoch [2748/4000] Training [10/16] Loss: 0.00428 +Epoch [2748/4000] Training [11/16] Loss: 0.00313 +Epoch [2748/4000] Training [12/16] Loss: 0.00350 +Epoch [2748/4000] Training [13/16] Loss: 0.00281 +Epoch [2748/4000] Training [14/16] Loss: 0.00294 +Epoch [2748/4000] Training [15/16] Loss: 0.00473 +Epoch [2748/4000] Training [16/16] Loss: 0.00355 +Epoch [2748/4000] Training metric {'Train/mean dice_metric': 0.9978811740875244, 'Train/mean miou_metric': 0.9954774379730225, 'Train/mean f1': 0.9924933314323425, 'Train/mean precision': 0.9874141812324524, 'Train/mean recall': 0.9976249933242798, 'Train/mean hd95_metric': 0.8585515022277832} +Epoch [2748/4000] Validation [1/4] Loss: 0.39956 focal_loss 0.33549 dice_loss 0.06406 +Epoch [2748/4000] Validation [2/4] Loss: 0.72394 focal_loss 0.52852 dice_loss 0.19542 +Epoch [2748/4000] Validation [3/4] Loss: 0.46644 focal_loss 0.36974 dice_loss 0.09670 +Epoch [2748/4000] Validation [4/4] Loss: 0.50430 focal_loss 0.37719 dice_loss 0.12711 +Epoch [2748/4000] Validation metric {'Val/mean dice_metric': 0.9707565307617188, 'Val/mean miou_metric': 0.9563742876052856, 'Val/mean f1': 0.9741407036781311, 'Val/mean precision': 0.9716363549232483, 'Val/mean recall': 0.976658046245575, 'Val/mean hd95_metric': 5.961964130401611} +Cheakpoint... +Epoch [2748/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707565307617188, 'Val/mean miou_metric': 0.9563742876052856, 'Val/mean f1': 0.9741407036781311, 'Val/mean precision': 0.9716363549232483, 'Val/mean recall': 0.976658046245575, 'Val/mean hd95_metric': 5.961964130401611} +Epoch [2749/4000] Training [1/16] Loss: 0.00299 +Epoch [2749/4000] Training [2/16] Loss: 0.00426 +Epoch [2749/4000] Training [3/16] Loss: 0.00298 +Epoch [2749/4000] Training [4/16] Loss: 0.00421 +Epoch [2749/4000] Training [5/16] Loss: 0.00484 +Epoch [2749/4000] Training [6/16] Loss: 0.00407 +Epoch [2749/4000] Training [7/16] Loss: 0.00503 +Epoch [2749/4000] Training [8/16] Loss: 0.00255 +Epoch [2749/4000] Training [9/16] Loss: 0.00321 +Epoch [2749/4000] Training [10/16] Loss: 0.00316 +Epoch [2749/4000] Training [11/16] Loss: 0.00282 +Epoch [2749/4000] Training [12/16] Loss: 0.00312 +Epoch [2749/4000] Training [13/16] Loss: 0.00397 +Epoch [2749/4000] Training [14/16] Loss: 0.00693 +Epoch [2749/4000] Training [15/16] Loss: 0.00511 +Epoch [2749/4000] Training [16/16] Loss: 0.00303 +Epoch [2749/4000] Training metric {'Train/mean dice_metric': 0.9978818893432617, 'Train/mean miou_metric': 0.9955064058303833, 'Train/mean f1': 0.9930492043495178, 'Train/mean precision': 0.9884302020072937, 'Train/mean recall': 0.9977115392684937, 'Train/mean hd95_metric': 0.8706292510032654} +Epoch [2749/4000] Validation [1/4] Loss: 0.35901 focal_loss 0.29406 dice_loss 0.06496 +Epoch [2749/4000] Validation [2/4] Loss: 0.67547 focal_loss 0.49813 dice_loss 0.17734 +Epoch [2749/4000] Validation [3/4] Loss: 0.40829 focal_loss 0.32361 dice_loss 0.08468 +Epoch [2749/4000] Validation [4/4] Loss: 0.38951 focal_loss 0.27055 dice_loss 0.11896 +Epoch [2749/4000] Validation metric {'Val/mean dice_metric': 0.9720834493637085, 'Val/mean miou_metric': 0.9575647115707397, 'Val/mean f1': 0.9754089713096619, 'Val/mean precision': 0.9728822112083435, 'Val/mean recall': 0.9779489040374756, 'Val/mean hd95_metric': 5.4714884757995605} +Cheakpoint... +Epoch [2749/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720834493637085, 'Val/mean miou_metric': 0.9575647115707397, 'Val/mean f1': 0.9754089713096619, 'Val/mean precision': 0.9728822112083435, 'Val/mean recall': 0.9779489040374756, 'Val/mean hd95_metric': 5.4714884757995605} +Epoch [2750/4000] Training [1/16] Loss: 0.00419 +Epoch [2750/4000] Training [2/16] Loss: 0.00406 +Epoch [2750/4000] Training [3/16] Loss: 0.00300 +Epoch [2750/4000] Training [4/16] Loss: 0.00295 +Epoch [2750/4000] Training [5/16] Loss: 0.00305 +Epoch [2750/4000] Training [6/16] Loss: 0.00312 +Epoch [2750/4000] Training [7/16] Loss: 0.00416 +Epoch [2750/4000] Training [8/16] Loss: 0.00356 +Epoch [2750/4000] Training [9/16] Loss: 0.00262 +Epoch [2750/4000] Training [10/16] Loss: 0.00226 +Epoch [2750/4000] Training [11/16] Loss: 0.00364 +Epoch [2750/4000] Training [12/16] Loss: 0.00402 +Epoch [2750/4000] Training [13/16] Loss: 0.00291 +Epoch [2750/4000] Training [14/16] Loss: 0.00557 +Epoch [2750/4000] Training [15/16] Loss: 0.00471 +Epoch [2750/4000] Training [16/16] Loss: 0.00348 +Epoch [2750/4000] Training metric {'Train/mean dice_metric': 0.9979245662689209, 'Train/mean miou_metric': 0.9955835938453674, 'Train/mean f1': 0.9931560158729553, 'Train/mean precision': 0.9886835813522339, 'Train/mean recall': 0.9976690411567688, 'Train/mean hd95_metric': 0.9716050624847412} +Epoch [2750/4000] Validation [1/4] Loss: 0.38634 focal_loss 0.32043 dice_loss 0.06591 +Epoch [2750/4000] Validation [2/4] Loss: 0.83551 focal_loss 0.63352 dice_loss 0.20199 +Epoch [2750/4000] Validation [3/4] Loss: 0.38608 focal_loss 0.28857 dice_loss 0.09751 +Epoch [2750/4000] Validation [4/4] Loss: 0.43087 focal_loss 0.32721 dice_loss 0.10365 +Epoch [2750/4000] Validation metric {'Val/mean dice_metric': 0.971208930015564, 'Val/mean miou_metric': 0.956904411315918, 'Val/mean f1': 0.9745809435844421, 'Val/mean precision': 0.9734630584716797, 'Val/mean recall': 0.9757013916969299, 'Val/mean hd95_metric': 5.66951322555542} +Cheakpoint... +Epoch [2750/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971208930015564, 'Val/mean miou_metric': 0.956904411315918, 'Val/mean f1': 0.9745809435844421, 'Val/mean precision': 0.9734630584716797, 'Val/mean recall': 0.9757013916969299, 'Val/mean hd95_metric': 5.66951322555542} +Epoch [2751/4000] Training [1/16] Loss: 0.00381 +Epoch [2751/4000] Training [2/16] Loss: 0.00447 +Epoch [2751/4000] Training [3/16] Loss: 0.00356 +Epoch [2751/4000] Training [4/16] Loss: 0.00426 +Epoch [2751/4000] Training [5/16] Loss: 0.00413 +Epoch [2751/4000] Training [6/16] Loss: 0.00301 +Epoch [2751/4000] Training [7/16] Loss: 0.00365 +Epoch [2751/4000] Training [8/16] Loss: 0.00282 +Epoch [2751/4000] Training [9/16] Loss: 0.00306 +Epoch [2751/4000] Training [10/16] Loss: 0.00306 +Epoch [2751/4000] Training [11/16] Loss: 0.00370 +Epoch [2751/4000] Training [12/16] Loss: 0.00303 +Epoch [2751/4000] Training [13/16] Loss: 0.00422 +Epoch [2751/4000] Training [14/16] Loss: 0.00528 +Epoch [2751/4000] Training [15/16] Loss: 0.00315 +Epoch [2751/4000] Training [16/16] Loss: 0.00252 +Epoch [2751/4000] Training metric {'Train/mean dice_metric': 0.9978988170623779, 'Train/mean miou_metric': 0.9955339431762695, 'Train/mean f1': 0.9931091666221619, 'Train/mean precision': 0.9885308742523193, 'Train/mean recall': 0.9977300763130188, 'Train/mean hd95_metric': 0.8725319504737854} +Epoch [2751/4000] Validation [1/4] Loss: 0.36859 focal_loss 0.30138 dice_loss 0.06721 +Epoch [2751/4000] Validation [2/4] Loss: 0.84594 focal_loss 0.65121 dice_loss 0.19473 +Epoch [2751/4000] Validation [3/4] Loss: 0.38566 focal_loss 0.29448 dice_loss 0.09118 +Epoch [2751/4000] Validation [4/4] Loss: 0.37054 focal_loss 0.25612 dice_loss 0.11442 +Epoch [2751/4000] Validation metric {'Val/mean dice_metric': 0.9717329144477844, 'Val/mean miou_metric': 0.9572442770004272, 'Val/mean f1': 0.975159764289856, 'Val/mean precision': 0.9740051031112671, 'Val/mean recall': 0.9763171076774597, 'Val/mean hd95_metric': 5.517023086547852} +Cheakpoint... +Epoch [2751/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717329144477844, 'Val/mean miou_metric': 0.9572442770004272, 'Val/mean f1': 0.975159764289856, 'Val/mean precision': 0.9740051031112671, 'Val/mean recall': 0.9763171076774597, 'Val/mean hd95_metric': 5.517023086547852} +Epoch [2752/4000] Training [1/16] Loss: 0.00398 +Epoch [2752/4000] Training [2/16] Loss: 0.00234 +Epoch [2752/4000] Training [3/16] Loss: 0.00420 +Epoch [2752/4000] Training [4/16] Loss: 0.00278 +Epoch [2752/4000] Training [5/16] Loss: 0.00277 +Epoch [2752/4000] Training [6/16] Loss: 0.00318 +Epoch [2752/4000] Training [7/16] Loss: 0.00396 +Epoch [2752/4000] Training [8/16] Loss: 0.00481 +Epoch [2752/4000] Training [9/16] Loss: 0.00435 +Epoch [2752/4000] Training [10/16] Loss: 0.00360 +Epoch [2752/4000] Training [11/16] Loss: 0.00326 +Epoch [2752/4000] Training [12/16] Loss: 0.00331 +Epoch [2752/4000] Training [13/16] Loss: 0.00475 +Epoch [2752/4000] Training [14/16] Loss: 0.00328 +Epoch [2752/4000] Training [15/16] Loss: 0.00311 +Epoch [2752/4000] Training [16/16] Loss: 0.00329 +Epoch [2752/4000] Training metric {'Train/mean dice_metric': 0.9979882836341858, 'Train/mean miou_metric': 0.9957031011581421, 'Train/mean f1': 0.9930988550186157, 'Train/mean precision': 0.9884616136550903, 'Train/mean recall': 0.9977797865867615, 'Train/mean hd95_metric': 0.8356720209121704} +Epoch [2752/4000] Validation [1/4] Loss: 0.44049 focal_loss 0.35263 dice_loss 0.08785 +Epoch [2752/4000] Validation [2/4] Loss: 0.78174 focal_loss 0.56189 dice_loss 0.21985 +Epoch [2752/4000] Validation [3/4] Loss: 0.27567 focal_loss 0.19315 dice_loss 0.08252 +Epoch [2752/4000] Validation [4/4] Loss: 0.34487 focal_loss 0.25130 dice_loss 0.09357 +Epoch [2752/4000] Validation metric {'Val/mean dice_metric': 0.9714384078979492, 'Val/mean miou_metric': 0.9565935134887695, 'Val/mean f1': 0.9747788310050964, 'Val/mean precision': 0.9735907912254333, 'Val/mean recall': 0.9759698510169983, 'Val/mean hd95_metric': 5.4712700843811035} +Cheakpoint... +Epoch [2752/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714384078979492, 'Val/mean miou_metric': 0.9565935134887695, 'Val/mean f1': 0.9747788310050964, 'Val/mean precision': 0.9735907912254333, 'Val/mean recall': 0.9759698510169983, 'Val/mean hd95_metric': 5.4712700843811035} +Epoch [2753/4000] Training [1/16] Loss: 0.00375 +Epoch [2753/4000] Training [2/16] Loss: 0.00334 +Epoch [2753/4000] Training [3/16] Loss: 0.00379 +Epoch [2753/4000] Training [4/16] Loss: 0.00307 +Epoch [2753/4000] Training [5/16] Loss: 0.00525 +Epoch [2753/4000] Training [6/16] Loss: 0.00287 +Epoch [2753/4000] Training [7/16] Loss: 0.01103 +Epoch [2753/4000] Training [8/16] Loss: 0.00426 +Epoch [2753/4000] Training [9/16] Loss: 0.00303 +Epoch [2753/4000] Training [10/16] Loss: 0.00355 +Epoch [2753/4000] Training [11/16] Loss: 0.00290 +Epoch [2753/4000] Training [12/16] Loss: 0.00292 +Epoch [2753/4000] Training [13/16] Loss: 0.00263 +Epoch [2753/4000] Training [14/16] Loss: 0.00356 +Epoch [2753/4000] Training [15/16] Loss: 0.00360 +Epoch [2753/4000] Training [16/16] Loss: 0.00497 +Epoch [2753/4000] Training metric {'Train/mean dice_metric': 0.997785210609436, 'Train/mean miou_metric': 0.9953108429908752, 'Train/mean f1': 0.9929705858230591, 'Train/mean precision': 0.9884634613990784, 'Train/mean recall': 0.9975190162658691, 'Train/mean hd95_metric': 0.8900983929634094} +Epoch [2753/4000] Validation [1/4] Loss: 0.51167 focal_loss 0.41527 dice_loss 0.09641 +Epoch [2753/4000] Validation [2/4] Loss: 0.82672 focal_loss 0.64140 dice_loss 0.18532 +Epoch [2753/4000] Validation [3/4] Loss: 0.43188 focal_loss 0.33294 dice_loss 0.09895 +Epoch [2753/4000] Validation [4/4] Loss: 0.36862 focal_loss 0.22773 dice_loss 0.14088 +Epoch [2753/4000] Validation metric {'Val/mean dice_metric': 0.9718077778816223, 'Val/mean miou_metric': 0.9568444490432739, 'Val/mean f1': 0.9743576049804688, 'Val/mean precision': 0.9727944731712341, 'Val/mean recall': 0.9759258031845093, 'Val/mean hd95_metric': 5.560007572174072} +Cheakpoint... +Epoch [2753/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718077778816223, 'Val/mean miou_metric': 0.9568444490432739, 'Val/mean f1': 0.9743576049804688, 'Val/mean precision': 0.9727944731712341, 'Val/mean recall': 0.9759258031845093, 'Val/mean hd95_metric': 5.560007572174072} +Epoch [2754/4000] Training [1/16] Loss: 0.00315 +Epoch [2754/4000] Training [2/16] Loss: 0.00475 +Epoch [2754/4000] Training [3/16] Loss: 0.00391 +Epoch [2754/4000] Training [4/16] Loss: 0.00327 +Epoch [2754/4000] Training [5/16] Loss: 0.00279 +Epoch [2754/4000] Training [6/16] Loss: 0.00311 +Epoch [2754/4000] Training [7/16] Loss: 0.00524 +Epoch [2754/4000] Training [8/16] Loss: 0.00325 +Epoch [2754/4000] Training [9/16] Loss: 0.00378 +Epoch [2754/4000] Training [10/16] Loss: 0.00362 +Epoch [2754/4000] Training [11/16] Loss: 0.00316 +Epoch [2754/4000] Training [12/16] Loss: 0.00558 +Epoch [2754/4000] Training [13/16] Loss: 0.00327 +Epoch [2754/4000] Training [14/16] Loss: 0.00466 +Epoch [2754/4000] Training [15/16] Loss: 0.00411 +Epoch [2754/4000] Training [16/16] Loss: 0.00390 +Epoch [2754/4000] Training metric {'Train/mean dice_metric': 0.9976966381072998, 'Train/mean miou_metric': 0.9951159358024597, 'Train/mean f1': 0.9927290081977844, 'Train/mean precision': 0.9879747629165649, 'Train/mean recall': 0.9975292682647705, 'Train/mean hd95_metric': 0.8888821601867676} +Epoch [2754/4000] Validation [1/4] Loss: 0.38294 focal_loss 0.31580 dice_loss 0.06714 +Epoch [2754/4000] Validation [2/4] Loss: 0.62039 focal_loss 0.44987 dice_loss 0.17052 +Epoch [2754/4000] Validation [3/4] Loss: 0.22599 focal_loss 0.16655 dice_loss 0.05944 +Epoch [2754/4000] Validation [4/4] Loss: 0.31481 focal_loss 0.22768 dice_loss 0.08713 +Epoch [2754/4000] Validation metric {'Val/mean dice_metric': 0.9728660583496094, 'Val/mean miou_metric': 0.95838862657547, 'Val/mean f1': 0.9754796028137207, 'Val/mean precision': 0.9743146300315857, 'Val/mean recall': 0.9766472578048706, 'Val/mean hd95_metric': 5.116315841674805} +Cheakpoint... +Epoch [2754/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728660583496094, 'Val/mean miou_metric': 0.95838862657547, 'Val/mean f1': 0.9754796028137207, 'Val/mean precision': 0.9743146300315857, 'Val/mean recall': 0.9766472578048706, 'Val/mean hd95_metric': 5.116315841674805} +Epoch [2755/4000] Training [1/16] Loss: 0.00377 +Epoch [2755/4000] Training [2/16] Loss: 0.00342 +Epoch [2755/4000] Training [3/16] Loss: 0.01275 +Epoch [2755/4000] Training [4/16] Loss: 0.00312 +Epoch [2755/4000] Training [5/16] Loss: 0.00359 +Epoch [2755/4000] Training [6/16] Loss: 0.00390 +Epoch [2755/4000] Training [7/16] Loss: 0.00389 +Epoch [2755/4000] Training [8/16] Loss: 0.00302 +Epoch [2755/4000] Training [9/16] Loss: 0.00360 +Epoch [2755/4000] Training [10/16] Loss: 0.00462 +Epoch [2755/4000] Training [11/16] Loss: 0.00507 +Epoch [2755/4000] Training [12/16] Loss: 0.00318 +Epoch [2755/4000] Training [13/16] Loss: 0.00414 +Epoch [2755/4000] Training [14/16] Loss: 0.00243 +Epoch [2755/4000] Training [15/16] Loss: 0.00320 +Epoch [2755/4000] Training [16/16] Loss: 0.00531 +Epoch [2755/4000] Training metric {'Train/mean dice_metric': 0.9976433515548706, 'Train/mean miou_metric': 0.995032548904419, 'Train/mean f1': 0.992921769618988, 'Train/mean precision': 0.9884799122810364, 'Train/mean recall': 0.9974038004875183, 'Train/mean hd95_metric': 0.9472376108169556} +Epoch [2755/4000] Validation [1/4] Loss: 0.35104 focal_loss 0.28963 dice_loss 0.06142 +Epoch [2755/4000] Validation [2/4] Loss: 0.65939 focal_loss 0.48467 dice_loss 0.17472 +Epoch [2755/4000] Validation [3/4] Loss: 0.44701 focal_loss 0.35785 dice_loss 0.08915 +Epoch [2755/4000] Validation [4/4] Loss: 0.34517 focal_loss 0.24836 dice_loss 0.09681 +Epoch [2755/4000] Validation metric {'Val/mean dice_metric': 0.9731242060661316, 'Val/mean miou_metric': 0.9576921463012695, 'Val/mean f1': 0.9748557806015015, 'Val/mean precision': 0.971131443977356, 'Val/mean recall': 0.9786087870597839, 'Val/mean hd95_metric': 5.649476051330566} +Cheakpoint... +Epoch [2755/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731242060661316, 'Val/mean miou_metric': 0.9576921463012695, 'Val/mean f1': 0.9748557806015015, 'Val/mean precision': 0.971131443977356, 'Val/mean recall': 0.9786087870597839, 'Val/mean hd95_metric': 5.649476051330566} +Epoch [2756/4000] Training [1/16] Loss: 0.00377 +Epoch [2756/4000] Training [2/16] Loss: 0.00380 +Epoch [2756/4000] Training [3/16] Loss: 0.00415 +Epoch [2756/4000] Training [4/16] Loss: 0.00331 +Epoch [2756/4000] Training [5/16] Loss: 0.00324 +Epoch [2756/4000] Training [6/16] Loss: 0.00370 +Epoch [2756/4000] Training [7/16] Loss: 0.00512 +Epoch [2756/4000] Training [8/16] Loss: 0.00311 +Epoch [2756/4000] Training [9/16] Loss: 0.00369 +Epoch [2756/4000] Training [10/16] Loss: 0.00426 +Epoch [2756/4000] Training [11/16] Loss: 0.00443 +Epoch [2756/4000] Training [12/16] Loss: 0.00303 +Epoch [2756/4000] Training [13/16] Loss: 0.00364 +Epoch [2756/4000] Training [14/16] Loss: 0.00384 +Epoch [2756/4000] Training [15/16] Loss: 0.00253 +Epoch [2756/4000] Training [16/16] Loss: 0.00395 +Epoch [2756/4000] Training metric {'Train/mean dice_metric': 0.9976798892021179, 'Train/mean miou_metric': 0.9950844049453735, 'Train/mean f1': 0.992735743522644, 'Train/mean precision': 0.9879878163337708, 'Train/mean recall': 0.9975295662879944, 'Train/mean hd95_metric': 0.9152166843414307} +Epoch [2756/4000] Validation [1/4] Loss: 0.33090 focal_loss 0.26744 dice_loss 0.06346 +Epoch [2756/4000] Validation [2/4] Loss: 0.38560 focal_loss 0.27041 dice_loss 0.11518 +Epoch [2756/4000] Validation [3/4] Loss: 0.47335 focal_loss 0.37967 dice_loss 0.09368 +Epoch [2756/4000] Validation [4/4] Loss: 0.35381 focal_loss 0.24970 dice_loss 0.10411 +Epoch [2756/4000] Validation metric {'Val/mean dice_metric': 0.9736671447753906, 'Val/mean miou_metric': 0.9583961367607117, 'Val/mean f1': 0.9754645228385925, 'Val/mean precision': 0.9718165397644043, 'Val/mean recall': 0.9791399240493774, 'Val/mean hd95_metric': 5.689558506011963} +Cheakpoint... +Epoch [2756/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736671447753906, 'Val/mean miou_metric': 0.9583961367607117, 'Val/mean f1': 0.9754645228385925, 'Val/mean precision': 0.9718165397644043, 'Val/mean recall': 0.9791399240493774, 'Val/mean hd95_metric': 5.689558506011963} +Epoch [2757/4000] Training [1/16] Loss: 0.00429 +Epoch [2757/4000] Training [2/16] Loss: 0.00415 +Epoch [2757/4000] Training [3/16] Loss: 0.00402 +Epoch [2757/4000] Training [4/16] Loss: 0.00374 +Epoch [2757/4000] Training [5/16] Loss: 0.00325 +Epoch [2757/4000] Training [6/16] Loss: 0.00322 +Epoch [2757/4000] Training [7/16] Loss: 0.00414 +Epoch [2757/4000] Training [8/16] Loss: 0.00388 +Epoch [2757/4000] Training [9/16] Loss: 0.00281 +Epoch [2757/4000] Training [10/16] Loss: 0.00512 +Epoch [2757/4000] Training [11/16] Loss: 0.00242 +Epoch [2757/4000] Training [12/16] Loss: 0.00543 +Epoch [2757/4000] Training [13/16] Loss: 0.00500 +Epoch [2757/4000] Training [14/16] Loss: 0.00451 +Epoch [2757/4000] Training [15/16] Loss: 0.00385 +Epoch [2757/4000] Training [16/16] Loss: 0.00500 +Epoch [2757/4000] Training metric {'Train/mean dice_metric': 0.9976211786270142, 'Train/mean miou_metric': 0.9949768781661987, 'Train/mean f1': 0.9927754402160645, 'Train/mean precision': 0.9881691336631775, 'Train/mean recall': 0.9974247813224792, 'Train/mean hd95_metric': 0.8937505483627319} +Epoch [2757/4000] Validation [1/4] Loss: 0.37870 focal_loss 0.31341 dice_loss 0.06529 +Epoch [2757/4000] Validation [2/4] Loss: 0.41188 focal_loss 0.29154 dice_loss 0.12034 +Epoch [2757/4000] Validation [3/4] Loss: 0.23363 focal_loss 0.17127 dice_loss 0.06236 +Epoch [2757/4000] Validation [4/4] Loss: 0.34487 focal_loss 0.24174 dice_loss 0.10312 +Epoch [2757/4000] Validation metric {'Val/mean dice_metric': 0.9741500616073608, 'Val/mean miou_metric': 0.9594360589981079, 'Val/mean f1': 0.9758809208869934, 'Val/mean precision': 0.9723621606826782, 'Val/mean recall': 0.979425311088562, 'Val/mean hd95_metric': 5.375929355621338} +Cheakpoint... +Epoch [2757/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741500616073608, 'Val/mean miou_metric': 0.9594360589981079, 'Val/mean f1': 0.9758809208869934, 'Val/mean precision': 0.9723621606826782, 'Val/mean recall': 0.979425311088562, 'Val/mean hd95_metric': 5.375929355621338} +Epoch [2758/4000] Training [1/16] Loss: 0.00287 +Epoch [2758/4000] Training [2/16] Loss: 0.00355 +Epoch [2758/4000] Training [3/16] Loss: 0.00348 +Epoch [2758/4000] Training [4/16] Loss: 0.00276 +Epoch [2758/4000] Training [5/16] Loss: 0.00295 +Epoch [2758/4000] Training [6/16] Loss: 0.00472 +Epoch [2758/4000] Training [7/16] Loss: 0.00296 +Epoch [2758/4000] Training [8/16] Loss: 0.00408 +Epoch [2758/4000] Training [9/16] Loss: 0.00436 +Epoch [2758/4000] Training [10/16] Loss: 0.00673 +Epoch [2758/4000] Training [11/16] Loss: 0.00370 +Epoch [2758/4000] Training [12/16] Loss: 0.00318 +Epoch [2758/4000] Training [13/16] Loss: 0.00491 +Epoch [2758/4000] Training [14/16] Loss: 0.00375 +Epoch [2758/4000] Training [15/16] Loss: 0.00360 +Epoch [2758/4000] Training [16/16] Loss: 0.00301 +Epoch [2758/4000] Training metric {'Train/mean dice_metric': 0.9977920055389404, 'Train/mean miou_metric': 0.9953119158744812, 'Train/mean f1': 0.99275803565979, 'Train/mean precision': 0.9880112409591675, 'Train/mean recall': 0.9975506067276001, 'Train/mean hd95_metric': 0.8706351518630981} +Epoch [2758/4000] Validation [1/4] Loss: 0.36406 focal_loss 0.29854 dice_loss 0.06551 +Epoch [2758/4000] Validation [2/4] Loss: 0.82065 focal_loss 0.62560 dice_loss 0.19505 +Epoch [2758/4000] Validation [3/4] Loss: 0.24321 focal_loss 0.18069 dice_loss 0.06252 +Epoch [2758/4000] Validation [4/4] Loss: 0.34397 focal_loss 0.24330 dice_loss 0.10067 +Epoch [2758/4000] Validation metric {'Val/mean dice_metric': 0.9730235934257507, 'Val/mean miou_metric': 0.958426296710968, 'Val/mean f1': 0.9754576086997986, 'Val/mean precision': 0.9730568528175354, 'Val/mean recall': 0.9778702855110168, 'Val/mean hd95_metric': 5.487009525299072} +Cheakpoint... +Epoch [2758/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730235934257507, 'Val/mean miou_metric': 0.958426296710968, 'Val/mean f1': 0.9754576086997986, 'Val/mean precision': 0.9730568528175354, 'Val/mean recall': 0.9778702855110168, 'Val/mean hd95_metric': 5.487009525299072} +Epoch [2759/4000] Training [1/16] Loss: 0.00349 +Epoch [2759/4000] Training [2/16] Loss: 0.00325 +Epoch [2759/4000] Training [3/16] Loss: 0.00266 +Epoch [2759/4000] Training [4/16] Loss: 0.00403 +Epoch [2759/4000] Training [5/16] Loss: 0.00339 +Epoch [2759/4000] Training [6/16] Loss: 0.00301 +Epoch [2759/4000] Training [7/16] Loss: 0.00388 +Epoch [2759/4000] Training [8/16] Loss: 0.00268 +Epoch [2759/4000] Training [9/16] Loss: 0.00411 +Epoch [2759/4000] Training [10/16] Loss: 0.00414 +Epoch [2759/4000] Training [11/16] Loss: 0.00383 +Epoch [2759/4000] Training [12/16] Loss: 0.00390 +Epoch [2759/4000] Training [13/16] Loss: 0.00248 +Epoch [2759/4000] Training [14/16] Loss: 0.00275 +Epoch [2759/4000] Training [15/16] Loss: 0.00308 +Epoch [2759/4000] Training [16/16] Loss: 0.00401 +Epoch [2759/4000] Training metric {'Train/mean dice_metric': 0.9979748725891113, 'Train/mean miou_metric': 0.9956828355789185, 'Train/mean f1': 0.9931844472885132, 'Train/mean precision': 0.9886360168457031, 'Train/mean recall': 0.9977748990058899, 'Train/mean hd95_metric': 0.8505436778068542} +Epoch [2759/4000] Validation [1/4] Loss: 0.35685 focal_loss 0.29492 dice_loss 0.06193 +Epoch [2759/4000] Validation [2/4] Loss: 0.49091 focal_loss 0.34697 dice_loss 0.14394 +Epoch [2759/4000] Validation [3/4] Loss: 0.45215 focal_loss 0.35934 dice_loss 0.09281 +Epoch [2759/4000] Validation [4/4] Loss: 0.28811 focal_loss 0.20350 dice_loss 0.08461 +Epoch [2759/4000] Validation metric {'Val/mean dice_metric': 0.9730203747749329, 'Val/mean miou_metric': 0.958604633808136, 'Val/mean f1': 0.9756528735160828, 'Val/mean precision': 0.9732826352119446, 'Val/mean recall': 0.9780347347259521, 'Val/mean hd95_metric': 5.588895797729492} +Cheakpoint... +Epoch [2759/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730203747749329, 'Val/mean miou_metric': 0.958604633808136, 'Val/mean f1': 0.9756528735160828, 'Val/mean precision': 0.9732826352119446, 'Val/mean recall': 0.9780347347259521, 'Val/mean hd95_metric': 5.588895797729492} +Epoch [2760/4000] Training [1/16] Loss: 0.00370 +Epoch [2760/4000] Training [2/16] Loss: 0.00280 +Epoch [2760/4000] Training [3/16] Loss: 0.00427 +Epoch [2760/4000] Training [4/16] Loss: 0.00467 +Epoch [2760/4000] Training [5/16] Loss: 0.00418 +Epoch [2760/4000] Training [6/16] Loss: 0.00313 +Epoch [2760/4000] Training [7/16] Loss: 0.00323 +Epoch [2760/4000] Training [8/16] Loss: 0.00326 +Epoch [2760/4000] Training [9/16] Loss: 0.00413 +Epoch [2760/4000] Training [10/16] Loss: 0.00434 +Epoch [2760/4000] Training [11/16] Loss: 0.00338 +Epoch [2760/4000] Training [12/16] Loss: 0.00367 +Epoch [2760/4000] Training [13/16] Loss: 0.00343 +Epoch [2760/4000] Training [14/16] Loss: 0.00323 +Epoch [2760/4000] Training [15/16] Loss: 0.00437 +Epoch [2760/4000] Training [16/16] Loss: 0.00428 +Epoch [2760/4000] Training metric {'Train/mean dice_metric': 0.9977701902389526, 'Train/mean miou_metric': 0.995272159576416, 'Train/mean f1': 0.9929327368736267, 'Train/mean precision': 0.9883073568344116, 'Train/mean recall': 0.9976015686988831, 'Train/mean hd95_metric': 0.8814728856086731} +Epoch [2760/4000] Validation [1/4] Loss: 0.38854 focal_loss 0.32198 dice_loss 0.06656 +Epoch [2760/4000] Validation [2/4] Loss: 0.77842 focal_loss 0.57099 dice_loss 0.20743 +Epoch [2760/4000] Validation [3/4] Loss: 0.45018 focal_loss 0.35917 dice_loss 0.09101 +Epoch [2760/4000] Validation [4/4] Loss: 0.33888 focal_loss 0.23512 dice_loss 0.10376 +Epoch [2760/4000] Validation metric {'Val/mean dice_metric': 0.9735652804374695, 'Val/mean miou_metric': 0.9583236575126648, 'Val/mean f1': 0.9748889207839966, 'Val/mean precision': 0.9715361595153809, 'Val/mean recall': 0.9782649874687195, 'Val/mean hd95_metric': 5.210416316986084} +Cheakpoint... +Epoch [2760/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735652804374695, 'Val/mean miou_metric': 0.9583236575126648, 'Val/mean f1': 0.9748889207839966, 'Val/mean precision': 0.9715361595153809, 'Val/mean recall': 0.9782649874687195, 'Val/mean hd95_metric': 5.210416316986084} +Epoch [2761/4000] Training [1/16] Loss: 0.00414 +Epoch [2761/4000] Training [2/16] Loss: 0.00291 +Epoch [2761/4000] Training [3/16] Loss: 0.00321 +Epoch [2761/4000] Training [4/16] Loss: 0.00331 +Epoch [2761/4000] Training [5/16] Loss: 0.00301 +Epoch [2761/4000] Training [6/16] Loss: 0.00299 +Epoch [2761/4000] Training [7/16] Loss: 0.00352 +Epoch [2761/4000] Training [8/16] Loss: 0.00540 +Epoch [2761/4000] Training [9/16] Loss: 0.00532 +Epoch [2761/4000] Training [10/16] Loss: 0.00403 +Epoch [2761/4000] Training [11/16] Loss: 0.00456 +Epoch [2761/4000] Training [12/16] Loss: 0.00373 +Epoch [2761/4000] Training [13/16] Loss: 0.00416 +Epoch [2761/4000] Training [14/16] Loss: 0.00365 +Epoch [2761/4000] Training [15/16] Loss: 0.00293 +Epoch [2761/4000] Training [16/16] Loss: 0.00468 +Epoch [2761/4000] Training metric {'Train/mean dice_metric': 0.9977792501449585, 'Train/mean miou_metric': 0.9952709674835205, 'Train/mean f1': 0.9926620721817017, 'Train/mean precision': 0.9878023862838745, 'Train/mean recall': 0.997569739818573, 'Train/mean hd95_metric': 0.8706245422363281} +Epoch [2761/4000] Validation [1/4] Loss: 0.40875 focal_loss 0.34234 dice_loss 0.06641 +Epoch [2761/4000] Validation [2/4] Loss: 0.79680 focal_loss 0.61227 dice_loss 0.18454 +Epoch [2761/4000] Validation [3/4] Loss: 0.23562 focal_loss 0.17011 dice_loss 0.06551 +Epoch [2761/4000] Validation [4/4] Loss: 0.58763 focal_loss 0.44098 dice_loss 0.14665 +Epoch [2761/4000] Validation metric {'Val/mean dice_metric': 0.9722277522087097, 'Val/mean miou_metric': 0.9575384259223938, 'Val/mean f1': 0.9742070436477661, 'Val/mean precision': 0.9717327952384949, 'Val/mean recall': 0.9766940474510193, 'Val/mean hd95_metric': 6.131728172302246} +Cheakpoint... +Epoch [2761/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722277522087097, 'Val/mean miou_metric': 0.9575384259223938, 'Val/mean f1': 0.9742070436477661, 'Val/mean precision': 0.9717327952384949, 'Val/mean recall': 0.9766940474510193, 'Val/mean hd95_metric': 6.131728172302246} +Epoch [2762/4000] Training [1/16] Loss: 0.00417 +Epoch [2762/4000] Training [2/16] Loss: 0.00310 +Epoch [2762/4000] Training [3/16] Loss: 0.00436 +Epoch [2762/4000] Training [4/16] Loss: 0.00351 +Epoch [2762/4000] Training [5/16] Loss: 0.00291 +Epoch [2762/4000] Training [6/16] Loss: 0.00420 +Epoch [2762/4000] Training [7/16] Loss: 0.00470 +Epoch [2762/4000] Training [8/16] Loss: 0.00487 +Epoch [2762/4000] Training [9/16] Loss: 0.00374 +Epoch [2762/4000] Training [10/16] Loss: 0.00347 +Epoch [2762/4000] Training [11/16] Loss: 0.00264 +Epoch [2762/4000] Training [12/16] Loss: 0.00372 +Epoch [2762/4000] Training [13/16] Loss: 0.00425 +Epoch [2762/4000] Training [14/16] Loss: 0.00421 +Epoch [2762/4000] Training [15/16] Loss: 0.00283 +Epoch [2762/4000] Training [16/16] Loss: 0.00447 +Epoch [2762/4000] Training metric {'Train/mean dice_metric': 0.9976494908332825, 'Train/mean miou_metric': 0.9950399398803711, 'Train/mean f1': 0.9930319786071777, 'Train/mean precision': 0.9885483980178833, 'Train/mean recall': 0.9975564479827881, 'Train/mean hd95_metric': 0.9270923137664795} +Epoch [2762/4000] Validation [1/4] Loss: 0.41955 focal_loss 0.34808 dice_loss 0.07147 +Epoch [2762/4000] Validation [2/4] Loss: 0.81794 focal_loss 0.63458 dice_loss 0.18337 +Epoch [2762/4000] Validation [3/4] Loss: 0.46942 focal_loss 0.36699 dice_loss 0.10243 +Epoch [2762/4000] Validation [4/4] Loss: 0.27826 focal_loss 0.19671 dice_loss 0.08155 +Epoch [2762/4000] Validation metric {'Val/mean dice_metric': 0.9744532704353333, 'Val/mean miou_metric': 0.9597018361091614, 'Val/mean f1': 0.9755839109420776, 'Val/mean precision': 0.9724401235580444, 'Val/mean recall': 0.9787482023239136, 'Val/mean hd95_metric': 4.815851211547852} +Cheakpoint... +Epoch [2762/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744532704353333, 'Val/mean miou_metric': 0.9597018361091614, 'Val/mean f1': 0.9755839109420776, 'Val/mean precision': 0.9724401235580444, 'Val/mean recall': 0.9787482023239136, 'Val/mean hd95_metric': 4.815851211547852} +Epoch [2763/4000] Training [1/16] Loss: 0.00374 +Epoch [2763/4000] Training [2/16] Loss: 0.00305 +Epoch [2763/4000] Training [3/16] Loss: 0.00305 +Epoch [2763/4000] Training [4/16] Loss: 0.00314 +Epoch [2763/4000] Training [5/16] Loss: 0.00514 +Epoch [2763/4000] Training [6/16] Loss: 0.00296 +Epoch [2763/4000] Training [7/16] Loss: 0.00297 +Epoch [2763/4000] Training [8/16] Loss: 0.00400 +Epoch [2763/4000] Training [9/16] Loss: 0.00285 +Epoch [2763/4000] Training [10/16] Loss: 0.00317 +Epoch [2763/4000] Training [11/16] Loss: 0.00386 +Epoch [2763/4000] Training [12/16] Loss: 0.00253 +Epoch [2763/4000] Training [13/16] Loss: 0.00480 +Epoch [2763/4000] Training [14/16] Loss: 0.00268 +Epoch [2763/4000] Training [15/16] Loss: 0.00363 +Epoch [2763/4000] Training [16/16] Loss: 0.00407 +Epoch [2763/4000] Training metric {'Train/mean dice_metric': 0.9978517293930054, 'Train/mean miou_metric': 0.9954415559768677, 'Train/mean f1': 0.9930437207221985, 'Train/mean precision': 0.9884749054908752, 'Train/mean recall': 0.9976549744606018, 'Train/mean hd95_metric': 1.2562898397445679} +Epoch [2763/4000] Validation [1/4] Loss: 0.37782 focal_loss 0.31190 dice_loss 0.06592 +Epoch [2763/4000] Validation [2/4] Loss: 0.55170 focal_loss 0.39354 dice_loss 0.15816 +Epoch [2763/4000] Validation [3/4] Loss: 0.44767 focal_loss 0.35803 dice_loss 0.08964 +Epoch [2763/4000] Validation [4/4] Loss: 0.25938 focal_loss 0.17210 dice_loss 0.08728 +Epoch [2763/4000] Validation metric {'Val/mean dice_metric': 0.9735379219055176, 'Val/mean miou_metric': 0.9590520858764648, 'Val/mean f1': 0.9755704402923584, 'Val/mean precision': 0.9728919267654419, 'Val/mean recall': 0.9782636761665344, 'Val/mean hd95_metric': 5.447052955627441} +Cheakpoint... +Epoch [2763/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735379219055176, 'Val/mean miou_metric': 0.9590520858764648, 'Val/mean f1': 0.9755704402923584, 'Val/mean precision': 0.9728919267654419, 'Val/mean recall': 0.9782636761665344, 'Val/mean hd95_metric': 5.447052955627441} +Epoch [2764/4000] Training [1/16] Loss: 0.00372 +Epoch [2764/4000] Training [2/16] Loss: 0.00403 +Epoch [2764/4000] Training [3/16] Loss: 0.00348 +Epoch [2764/4000] Training [4/16] Loss: 0.00315 +Epoch [2764/4000] Training [5/16] Loss: 0.00350 +Epoch [2764/4000] Training [6/16] Loss: 0.00359 +Epoch [2764/4000] Training [7/16] Loss: 0.00297 +Epoch [2764/4000] Training [8/16] Loss: 0.00372 +Epoch [2764/4000] Training [9/16] Loss: 0.00529 +Epoch [2764/4000] Training [10/16] Loss: 0.00335 +Epoch [2764/4000] Training [11/16] Loss: 0.00267 +Epoch [2764/4000] Training [12/16] Loss: 0.00436 +Epoch [2764/4000] Training [13/16] Loss: 0.00485 +Epoch [2764/4000] Training [14/16] Loss: 0.00414 +Epoch [2764/4000] Training [15/16] Loss: 0.00395 +Epoch [2764/4000] Training [16/16] Loss: 0.00449 +Epoch [2764/4000] Training metric {'Train/mean dice_metric': 0.9978144764900208, 'Train/mean miou_metric': 0.9953495264053345, 'Train/mean f1': 0.9928988218307495, 'Train/mean precision': 0.9881754517555237, 'Train/mean recall': 0.9976675510406494, 'Train/mean hd95_metric': 0.8725863695144653} +Epoch [2764/4000] Validation [1/4] Loss: 0.32795 focal_loss 0.26649 dice_loss 0.06146 +Epoch [2764/4000] Validation [2/4] Loss: 0.81867 focal_loss 0.58808 dice_loss 0.23060 +Epoch [2764/4000] Validation [3/4] Loss: 0.29732 focal_loss 0.21095 dice_loss 0.08637 +Epoch [2764/4000] Validation [4/4] Loss: 0.44101 focal_loss 0.31988 dice_loss 0.12114 +Epoch [2764/4000] Validation metric {'Val/mean dice_metric': 0.9709820747375488, 'Val/mean miou_metric': 0.9561691284179688, 'Val/mean f1': 0.9749414324760437, 'Val/mean precision': 0.9736530780792236, 'Val/mean recall': 0.976233184337616, 'Val/mean hd95_metric': 5.561178207397461} +Cheakpoint... +Epoch [2764/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709820747375488, 'Val/mean miou_metric': 0.9561691284179688, 'Val/mean f1': 0.9749414324760437, 'Val/mean precision': 0.9736530780792236, 'Val/mean recall': 0.976233184337616, 'Val/mean hd95_metric': 5.561178207397461} +Epoch [2765/4000] Training [1/16] Loss: 0.00484 +Epoch [2765/4000] Training [2/16] Loss: 0.00294 +Epoch [2765/4000] Training [3/16] Loss: 0.00321 +Epoch [2765/4000] Training [4/16] Loss: 0.00296 +Epoch [2765/4000] Training [5/16] Loss: 0.00370 +Epoch [2765/4000] Training [6/16] Loss: 0.00407 +Epoch [2765/4000] Training [7/16] Loss: 0.00310 +Epoch [2765/4000] Training [8/16] Loss: 0.00426 +Epoch [2765/4000] Training [9/16] Loss: 0.00303 +Epoch [2765/4000] Training [10/16] Loss: 0.00348 +Epoch [2765/4000] Training [11/16] Loss: 0.00285 +Epoch [2765/4000] Training [12/16] Loss: 0.00346 +Epoch [2765/4000] Training [13/16] Loss: 0.00333 +Epoch [2765/4000] Training [14/16] Loss: 0.00379 +Epoch [2765/4000] Training [15/16] Loss: 0.00298 +Epoch [2765/4000] Training [16/16] Loss: 0.00586 +Epoch [2765/4000] Training metric {'Train/mean dice_metric': 0.9978374242782593, 'Train/mean miou_metric': 0.9954098463058472, 'Train/mean f1': 0.993007481098175, 'Train/mean precision': 0.9885227084159851, 'Train/mean recall': 0.9975331425666809, 'Train/mean hd95_metric': 1.0848278999328613} +Epoch [2765/4000] Validation [1/4] Loss: 0.33561 focal_loss 0.27088 dice_loss 0.06473 +Epoch [2765/4000] Validation [2/4] Loss: 1.06811 focal_loss 0.88412 dice_loss 0.18399 +Epoch [2765/4000] Validation [3/4] Loss: 0.20595 focal_loss 0.15342 dice_loss 0.05253 +Epoch [2765/4000] Validation [4/4] Loss: 0.32377 focal_loss 0.22520 dice_loss 0.09857 +Epoch [2765/4000] Validation metric {'Val/mean dice_metric': 0.9722798466682434, 'Val/mean miou_metric': 0.9581276178359985, 'Val/mean f1': 0.9757964015007019, 'Val/mean precision': 0.9738438725471497, 'Val/mean recall': 0.9777567386627197, 'Val/mean hd95_metric': 5.13347053527832} +Cheakpoint... +Epoch [2765/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722798466682434, 'Val/mean miou_metric': 0.9581276178359985, 'Val/mean f1': 0.9757964015007019, 'Val/mean precision': 0.9738438725471497, 'Val/mean recall': 0.9777567386627197, 'Val/mean hd95_metric': 5.13347053527832} +Epoch [2766/4000] Training [1/16] Loss: 0.00319 +Epoch [2766/4000] Training [2/16] Loss: 0.00339 +Epoch [2766/4000] Training [3/16] Loss: 0.00423 +Epoch [2766/4000] Training [4/16] Loss: 0.00339 +Epoch [2766/4000] Training [5/16] Loss: 0.00364 +Epoch [2766/4000] Training [6/16] Loss: 0.00314 +Epoch [2766/4000] Training [7/16] Loss: 0.00319 +Epoch [2766/4000] Training [8/16] Loss: 0.00266 +Epoch [2766/4000] Training [9/16] Loss: 0.00505 +Epoch [2766/4000] Training [10/16] Loss: 0.00515 +Epoch [2766/4000] Training [11/16] Loss: 0.00392 +Epoch [2766/4000] Training [12/16] Loss: 0.00453 +Epoch [2766/4000] Training [13/16] Loss: 0.00436 +Epoch [2766/4000] Training [14/16] Loss: 0.00441 +Epoch [2766/4000] Training [15/16] Loss: 0.00361 +Epoch [2766/4000] Training [16/16] Loss: 0.00349 +Epoch [2766/4000] Training metric {'Train/mean dice_metric': 0.9977455139160156, 'Train/mean miou_metric': 0.9952306151390076, 'Train/mean f1': 0.9930311441421509, 'Train/mean precision': 0.9885352253913879, 'Train/mean recall': 0.9975681304931641, 'Train/mean hd95_metric': 0.9373587965965271} +Epoch [2766/4000] Validation [1/4] Loss: 0.31292 focal_loss 0.25042 dice_loss 0.06250 +Epoch [2766/4000] Validation [2/4] Loss: 1.03525 focal_loss 0.84579 dice_loss 0.18946 +Epoch [2766/4000] Validation [3/4] Loss: 0.45279 focal_loss 0.36060 dice_loss 0.09219 +Epoch [2766/4000] Validation [4/4] Loss: 0.26814 focal_loss 0.18274 dice_loss 0.08539 +Epoch [2766/4000] Validation metric {'Val/mean dice_metric': 0.9712620973587036, 'Val/mean miou_metric': 0.9574772119522095, 'Val/mean f1': 0.975838840007782, 'Val/mean precision': 0.9735802412033081, 'Val/mean recall': 0.9781079888343811, 'Val/mean hd95_metric': 4.998401641845703} +Cheakpoint... +Epoch [2766/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712620973587036, 'Val/mean miou_metric': 0.9574772119522095, 'Val/mean f1': 0.975838840007782, 'Val/mean precision': 0.9735802412033081, 'Val/mean recall': 0.9781079888343811, 'Val/mean hd95_metric': 4.998401641845703} +Epoch [2767/4000] Training [1/16] Loss: 0.00395 +Epoch [2767/4000] Training [2/16] Loss: 0.00374 +Epoch [2767/4000] Training [3/16] Loss: 0.00356 +Epoch [2767/4000] Training [4/16] Loss: 0.00438 +Epoch [2767/4000] Training [5/16] Loss: 0.00253 +Epoch [2767/4000] Training [6/16] Loss: 0.00306 +Epoch [2767/4000] Training [7/16] Loss: 0.00420 +Epoch [2767/4000] Training [8/16] Loss: 0.00396 +Epoch [2767/4000] Training [9/16] Loss: 0.00462 +Epoch [2767/4000] Training [10/16] Loss: 0.00393 +Epoch [2767/4000] Training [11/16] Loss: 0.00393 +Epoch [2767/4000] Training [12/16] Loss: 0.00377 +Epoch [2767/4000] Training [13/16] Loss: 0.00450 +Epoch [2767/4000] Training [14/16] Loss: 0.00298 +Epoch [2767/4000] Training [15/16] Loss: 0.00314 +Epoch [2767/4000] Training [16/16] Loss: 0.00293 +Epoch [2767/4000] Training metric {'Train/mean dice_metric': 0.9976872205734253, 'Train/mean miou_metric': 0.9951168298721313, 'Train/mean f1': 0.9930686950683594, 'Train/mean precision': 0.9885388016700745, 'Train/mean recall': 0.9976403117179871, 'Train/mean hd95_metric': 0.8717077970504761} +Epoch [2767/4000] Validation [1/4] Loss: 0.36704 focal_loss 0.29925 dice_loss 0.06779 +Epoch [2767/4000] Validation [2/4] Loss: 1.06050 focal_loss 0.86576 dice_loss 0.19474 +Epoch [2767/4000] Validation [3/4] Loss: 0.46603 focal_loss 0.37085 dice_loss 0.09517 +Epoch [2767/4000] Validation [4/4] Loss: 0.31631 focal_loss 0.21632 dice_loss 0.09998 +Epoch [2767/4000] Validation metric {'Val/mean dice_metric': 0.9702770113945007, 'Val/mean miou_metric': 0.9558348655700684, 'Val/mean f1': 0.9750560522079468, 'Val/mean precision': 0.9741240739822388, 'Val/mean recall': 0.9759898781776428, 'Val/mean hd95_metric': 5.320008277893066} +Cheakpoint... +Epoch [2767/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9703], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9702770113945007, 'Val/mean miou_metric': 0.9558348655700684, 'Val/mean f1': 0.9750560522079468, 'Val/mean precision': 0.9741240739822388, 'Val/mean recall': 0.9759898781776428, 'Val/mean hd95_metric': 5.320008277893066} +Epoch [2768/4000] Training [1/16] Loss: 0.00457 +Epoch [2768/4000] Training [2/16] Loss: 0.00371 +Epoch [2768/4000] Training [3/16] Loss: 0.00300 +Epoch [2768/4000] Training [4/16] Loss: 0.00297 +Epoch [2768/4000] Training [5/16] Loss: 0.00401 +Epoch [2768/4000] Training [6/16] Loss: 0.00523 +Epoch [2768/4000] Training [7/16] Loss: 0.00459 +Epoch [2768/4000] Training [8/16] Loss: 0.00273 +Epoch [2768/4000] Training [9/16] Loss: 0.00291 +Epoch [2768/4000] Training [10/16] Loss: 0.00300 +Epoch [2768/4000] Training [11/16] Loss: 0.00334 +Epoch [2768/4000] Training [12/16] Loss: 0.00328 +Epoch [2768/4000] Training [13/16] Loss: 0.00560 +Epoch [2768/4000] Training [14/16] Loss: 0.00300 +Epoch [2768/4000] Training [15/16] Loss: 0.00486 +Epoch [2768/4000] Training [16/16] Loss: 0.00409 +Epoch [2768/4000] Training metric {'Train/mean dice_metric': 0.9977015256881714, 'Train/mean miou_metric': 0.9951314330101013, 'Train/mean f1': 0.9928547739982605, 'Train/mean precision': 0.9881986975669861, 'Train/mean recall': 0.9975549578666687, 'Train/mean hd95_metric': 0.886383593082428} +Epoch [2768/4000] Validation [1/4] Loss: 0.32425 focal_loss 0.25944 dice_loss 0.06481 +Epoch [2768/4000] Validation [2/4] Loss: 1.23768 focal_loss 1.05563 dice_loss 0.18205 +Epoch [2768/4000] Validation [3/4] Loss: 0.44115 focal_loss 0.34894 dice_loss 0.09220 +Epoch [2768/4000] Validation [4/4] Loss: 0.45360 focal_loss 0.32409 dice_loss 0.12952 +Epoch [2768/4000] Validation metric {'Val/mean dice_metric': 0.9720882177352905, 'Val/mean miou_metric': 0.9577210545539856, 'Val/mean f1': 0.9755823016166687, 'Val/mean precision': 0.9741717576980591, 'Val/mean recall': 0.9769969582557678, 'Val/mean hd95_metric': 5.090047359466553} +Cheakpoint... +Epoch [2768/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720882177352905, 'Val/mean miou_metric': 0.9577210545539856, 'Val/mean f1': 0.9755823016166687, 'Val/mean precision': 0.9741717576980591, 'Val/mean recall': 0.9769969582557678, 'Val/mean hd95_metric': 5.090047359466553} +Epoch [2769/4000] Training [1/16] Loss: 0.00297 +Epoch [2769/4000] Training [2/16] Loss: 0.00302 +Epoch [2769/4000] Training [3/16] Loss: 0.00368 +Epoch [2769/4000] Training [4/16] Loss: 0.00405 +Epoch [2769/4000] Training [5/16] Loss: 0.00420 +Epoch [2769/4000] Training [6/16] Loss: 0.00226 +Epoch [2769/4000] Training [7/16] Loss: 0.00489 +Epoch [2769/4000] Training [8/16] Loss: 0.00510 +Epoch [2769/4000] Training [9/16] Loss: 0.00319 +Epoch [2769/4000] Training [10/16] Loss: 0.00422 +Epoch [2769/4000] Training [11/16] Loss: 0.00288 +Epoch [2769/4000] Training [12/16] Loss: 0.00403 +Epoch [2769/4000] Training [13/16] Loss: 0.00258 +Epoch [2769/4000] Training [14/16] Loss: 0.00405 +Epoch [2769/4000] Training [15/16] Loss: 0.00501 +Epoch [2769/4000] Training [16/16] Loss: 0.00319 +Epoch [2769/4000] Training metric {'Train/mean dice_metric': 0.9978906512260437, 'Train/mean miou_metric': 0.9955178499221802, 'Train/mean f1': 0.9930946230888367, 'Train/mean precision': 0.988565981388092, 'Train/mean recall': 0.9976648688316345, 'Train/mean hd95_metric': 0.8913362622261047} +Epoch [2769/4000] Validation [1/4] Loss: 0.39250 focal_loss 0.32555 dice_loss 0.06695 +Epoch [2769/4000] Validation [2/4] Loss: 0.45658 focal_loss 0.32764 dice_loss 0.12894 +Epoch [2769/4000] Validation [3/4] Loss: 0.44376 focal_loss 0.35710 dice_loss 0.08666 +Epoch [2769/4000] Validation [4/4] Loss: 0.42409 focal_loss 0.30318 dice_loss 0.12091 +Epoch [2769/4000] Validation metric {'Val/mean dice_metric': 0.9716261625289917, 'Val/mean miou_metric': 0.9574075937271118, 'Val/mean f1': 0.9749246835708618, 'Val/mean precision': 0.9727330207824707, 'Val/mean recall': 0.9771260619163513, 'Val/mean hd95_metric': 5.369429111480713} +Cheakpoint... +Epoch [2769/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716261625289917, 'Val/mean miou_metric': 0.9574075937271118, 'Val/mean f1': 0.9749246835708618, 'Val/mean precision': 0.9727330207824707, 'Val/mean recall': 0.9771260619163513, 'Val/mean hd95_metric': 5.369429111480713} +Epoch [2770/4000] Training [1/16] Loss: 0.00308 +Epoch [2770/4000] Training [2/16] Loss: 0.00371 +Epoch [2770/4000] Training [3/16] Loss: 0.00307 +Epoch [2770/4000] Training [4/16] Loss: 0.00371 +Epoch [2770/4000] Training [5/16] Loss: 0.00361 +Epoch [2770/4000] Training [6/16] Loss: 0.00427 +Epoch [2770/4000] Training [7/16] Loss: 0.00421 +Epoch [2770/4000] Training [8/16] Loss: 0.00368 +Epoch [2770/4000] Training [9/16] Loss: 0.00380 +Epoch [2770/4000] Training [10/16] Loss: 0.00426 +Epoch [2770/4000] Training [11/16] Loss: 0.00278 +Epoch [2770/4000] Training [12/16] Loss: 0.00345 +Epoch [2770/4000] Training [13/16] Loss: 0.00344 +Epoch [2770/4000] Training [14/16] Loss: 0.00287 +Epoch [2770/4000] Training [15/16] Loss: 0.00456 +Epoch [2770/4000] Training [16/16] Loss: 0.00398 +Epoch [2770/4000] Training metric {'Train/mean dice_metric': 0.9976643919944763, 'Train/mean miou_metric': 0.995053768157959, 'Train/mean f1': 0.9928412437438965, 'Train/mean precision': 0.9881954789161682, 'Train/mean recall': 0.9975308775901794, 'Train/mean hd95_metric': 0.891292929649353} +Epoch [2770/4000] Validation [1/4] Loss: 0.34219 focal_loss 0.28024 dice_loss 0.06196 +Epoch [2770/4000] Validation [2/4] Loss: 0.43861 focal_loss 0.31714 dice_loss 0.12146 +Epoch [2770/4000] Validation [3/4] Loss: 0.46445 focal_loss 0.37796 dice_loss 0.08649 +Epoch [2770/4000] Validation [4/4] Loss: 0.28998 focal_loss 0.21160 dice_loss 0.07839 +Epoch [2770/4000] Validation metric {'Val/mean dice_metric': 0.97210693359375, 'Val/mean miou_metric': 0.9580476880073547, 'Val/mean f1': 0.9758047461509705, 'Val/mean precision': 0.974087119102478, 'Val/mean recall': 0.97752845287323, 'Val/mean hd95_metric': 4.967008113861084} +Cheakpoint... +Epoch [2770/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97210693359375, 'Val/mean miou_metric': 0.9580476880073547, 'Val/mean f1': 0.9758047461509705, 'Val/mean precision': 0.974087119102478, 'Val/mean recall': 0.97752845287323, 'Val/mean hd95_metric': 4.967008113861084} +Epoch [2771/4000] Training [1/16] Loss: 0.00509 +Epoch [2771/4000] Training [2/16] Loss: 0.00337 +Epoch [2771/4000] Training [3/16] Loss: 0.00276 +Epoch [2771/4000] Training [4/16] Loss: 0.00330 +Epoch [2771/4000] Training [5/16] Loss: 0.00309 +Epoch [2771/4000] Training [6/16] Loss: 0.00345 +Epoch [2771/4000] Training [7/16] Loss: 0.00557 +Epoch [2771/4000] Training [8/16] Loss: 0.00315 +Epoch [2771/4000] Training [9/16] Loss: 0.00340 +Epoch [2771/4000] Training [10/16] Loss: 0.00381 +Epoch [2771/4000] Training [11/16] Loss: 0.00621 +Epoch [2771/4000] Training [12/16] Loss: 0.00392 +Epoch [2771/4000] Training [13/16] Loss: 0.00363 +Epoch [2771/4000] Training [14/16] Loss: 0.00329 +Epoch [2771/4000] Training [15/16] Loss: 0.00320 +Epoch [2771/4000] Training [16/16] Loss: 0.00392 +Epoch [2771/4000] Training metric {'Train/mean dice_metric': 0.9977131485939026, 'Train/mean miou_metric': 0.9951651692390442, 'Train/mean f1': 0.9930305480957031, 'Train/mean precision': 0.9884843230247498, 'Train/mean recall': 0.9976187348365784, 'Train/mean hd95_metric': 0.8855323791503906} +Epoch [2771/4000] Validation [1/4] Loss: 0.35118 focal_loss 0.28928 dice_loss 0.06190 +Epoch [2771/4000] Validation [2/4] Loss: 0.78330 focal_loss 0.55932 dice_loss 0.22398 +Epoch [2771/4000] Validation [3/4] Loss: 0.42369 focal_loss 0.33939 dice_loss 0.08430 +Epoch [2771/4000] Validation [4/4] Loss: 0.30664 focal_loss 0.21830 dice_loss 0.08834 +Epoch [2771/4000] Validation metric {'Val/mean dice_metric': 0.9730552434921265, 'Val/mean miou_metric': 0.9584614634513855, 'Val/mean f1': 0.9758438467979431, 'Val/mean precision': 0.9733080267906189, 'Val/mean recall': 0.9783927798271179, 'Val/mean hd95_metric': 4.914659023284912} +Cheakpoint... +Epoch [2771/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730552434921265, 'Val/mean miou_metric': 0.9584614634513855, 'Val/mean f1': 0.9758438467979431, 'Val/mean precision': 0.9733080267906189, 'Val/mean recall': 0.9783927798271179, 'Val/mean hd95_metric': 4.914659023284912} +Epoch [2772/4000] Training [1/16] Loss: 0.00569 +Epoch [2772/4000] Training [2/16] Loss: 0.00344 +Epoch [2772/4000] Training [3/16] Loss: 0.00454 +Epoch [2772/4000] Training [4/16] Loss: 0.00413 +Epoch [2772/4000] Training [5/16] Loss: 0.00289 +Epoch [2772/4000] Training [6/16] Loss: 0.00299 +Epoch [2772/4000] Training [7/16] Loss: 0.00500 +Epoch [2772/4000] Training [8/16] Loss: 0.00361 +Epoch [2772/4000] Training [9/16] Loss: 0.00427 +Epoch [2772/4000] Training [10/16] Loss: 0.00386 +Epoch [2772/4000] Training [11/16] Loss: 0.00418 +Epoch [2772/4000] Training [12/16] Loss: 0.00305 +Epoch [2772/4000] Training [13/16] Loss: 0.00266 +Epoch [2772/4000] Training [14/16] Loss: 0.00271 +Epoch [2772/4000] Training [15/16] Loss: 0.00274 +Epoch [2772/4000] Training [16/16] Loss: 0.00310 +Epoch [2772/4000] Training metric {'Train/mean dice_metric': 0.9978526830673218, 'Train/mean miou_metric': 0.9954202175140381, 'Train/mean f1': 0.9927423596382141, 'Train/mean precision': 0.9879738092422485, 'Train/mean recall': 0.9975572228431702, 'Train/mean hd95_metric': 0.8311753273010254} +Epoch [2772/4000] Validation [1/4] Loss: 0.40839 focal_loss 0.33805 dice_loss 0.07034 +Epoch [2772/4000] Validation [2/4] Loss: 1.02136 focal_loss 0.83085 dice_loss 0.19051 +Epoch [2772/4000] Validation [3/4] Loss: 0.43085 focal_loss 0.34582 dice_loss 0.08503 +Epoch [2772/4000] Validation [4/4] Loss: 0.25575 focal_loss 0.16490 dice_loss 0.09085 +Epoch [2772/4000] Validation metric {'Val/mean dice_metric': 0.9728851318359375, 'Val/mean miou_metric': 0.9586435556411743, 'Val/mean f1': 0.9754949808120728, 'Val/mean precision': 0.9733243584632874, 'Val/mean recall': 0.9776752591133118, 'Val/mean hd95_metric': 4.822000980377197} +Cheakpoint... +Epoch [2772/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728851318359375, 'Val/mean miou_metric': 0.9586435556411743, 'Val/mean f1': 0.9754949808120728, 'Val/mean precision': 0.9733243584632874, 'Val/mean recall': 0.9776752591133118, 'Val/mean hd95_metric': 4.822000980377197} +Epoch [2773/4000] Training [1/16] Loss: 0.00366 +Epoch [2773/4000] Training [2/16] Loss: 0.00363 +Epoch [2773/4000] Training [3/16] Loss: 0.00524 +Epoch [2773/4000] Training [4/16] Loss: 0.00229 +Epoch [2773/4000] Training [5/16] Loss: 0.00278 +Epoch [2773/4000] Training [6/16] Loss: 0.00432 +Epoch [2773/4000] Training [7/16] Loss: 0.00336 +Epoch [2773/4000] Training [8/16] Loss: 0.00312 +Epoch [2773/4000] Training [9/16] Loss: 0.00466 +Epoch [2773/4000] Training [10/16] Loss: 0.00439 +Epoch [2773/4000] Training [11/16] Loss: 0.00321 +Epoch [2773/4000] Training [12/16] Loss: 0.00241 +Epoch [2773/4000] Training [13/16] Loss: 0.00380 +Epoch [2773/4000] Training [14/16] Loss: 0.00363 +Epoch [2773/4000] Training [15/16] Loss: 0.00438 +Epoch [2773/4000] Training [16/16] Loss: 0.00384 +Epoch [2773/4000] Training metric {'Train/mean dice_metric': 0.9977831840515137, 'Train/mean miou_metric': 0.9952906370162964, 'Train/mean f1': 0.9927400350570679, 'Train/mean precision': 0.9879191517829895, 'Train/mean recall': 0.9976082444190979, 'Train/mean hd95_metric': 0.8701447248458862} +Epoch [2773/4000] Validation [1/4] Loss: 0.33193 focal_loss 0.27193 dice_loss 0.06000 +Epoch [2773/4000] Validation [2/4] Loss: 0.47689 focal_loss 0.34968 dice_loss 0.12721 +Epoch [2773/4000] Validation [3/4] Loss: 0.21403 focal_loss 0.15497 dice_loss 0.05906 +Epoch [2773/4000] Validation [4/4] Loss: 0.31251 focal_loss 0.21488 dice_loss 0.09763 +Epoch [2773/4000] Validation metric {'Val/mean dice_metric': 0.974258303642273, 'Val/mean miou_metric': 0.9597233533859253, 'Val/mean f1': 0.9764379858970642, 'Val/mean precision': 0.9738038182258606, 'Val/mean recall': 0.9790865778923035, 'Val/mean hd95_metric': 4.641829967498779} +Cheakpoint... +Epoch [2773/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974258303642273, 'Val/mean miou_metric': 0.9597233533859253, 'Val/mean f1': 0.9764379858970642, 'Val/mean precision': 0.9738038182258606, 'Val/mean recall': 0.9790865778923035, 'Val/mean hd95_metric': 4.641829967498779} +Epoch [2774/4000] Training [1/16] Loss: 0.00354 +Epoch [2774/4000] Training [2/16] Loss: 0.00352 +Epoch [2774/4000] Training [3/16] Loss: 0.00318 +Epoch [2774/4000] Training [4/16] Loss: 0.00325 +Epoch [2774/4000] Training [5/16] Loss: 0.00261 +Epoch [2774/4000] Training [6/16] Loss: 0.00339 +Epoch [2774/4000] Training [7/16] Loss: 0.00340 +Epoch [2774/4000] Training [8/16] Loss: 0.00306 +Epoch [2774/4000] Training [9/16] Loss: 0.00418 +Epoch [2774/4000] Training [10/16] Loss: 0.00340 +Epoch [2774/4000] Training [11/16] Loss: 0.00325 +Epoch [2774/4000] Training [12/16] Loss: 0.00288 +Epoch [2774/4000] Training [13/16] Loss: 0.00339 +Epoch [2774/4000] Training [14/16] Loss: 0.00303 +Epoch [2774/4000] Training [15/16] Loss: 0.00404 +Epoch [2774/4000] Training [16/16] Loss: 0.00383 +Epoch [2774/4000] Training metric {'Train/mean dice_metric': 0.9979509115219116, 'Train/mean miou_metric': 0.9956355690956116, 'Train/mean f1': 0.9931856393814087, 'Train/mean precision': 0.9886488914489746, 'Train/mean recall': 0.9977642893791199, 'Train/mean hd95_metric': 0.8548406362533569} +Epoch [2774/4000] Validation [1/4] Loss: 0.31503 focal_loss 0.25387 dice_loss 0.06117 +Epoch [2774/4000] Validation [2/4] Loss: 0.51017 focal_loss 0.38188 dice_loss 0.12830 +Epoch [2774/4000] Validation [3/4] Loss: 0.42717 focal_loss 0.33844 dice_loss 0.08873 +Epoch [2774/4000] Validation [4/4] Loss: 0.23704 focal_loss 0.15700 dice_loss 0.08004 +Epoch [2774/4000] Validation metric {'Val/mean dice_metric': 0.9739478826522827, 'Val/mean miou_metric': 0.9595993757247925, 'Val/mean f1': 0.9762511253356934, 'Val/mean precision': 0.9741888046264648, 'Val/mean recall': 0.9783223271369934, 'Val/mean hd95_metric': 4.687778472900391} +Cheakpoint... +Epoch [2774/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739478826522827, 'Val/mean miou_metric': 0.9595993757247925, 'Val/mean f1': 0.9762511253356934, 'Val/mean precision': 0.9741888046264648, 'Val/mean recall': 0.9783223271369934, 'Val/mean hd95_metric': 4.687778472900391} +Epoch [2775/4000] Training [1/16] Loss: 0.00429 +Epoch [2775/4000] Training [2/16] Loss: 0.00303 +Epoch [2775/4000] Training [3/16] Loss: 0.00341 +Epoch [2775/4000] Training [4/16] Loss: 0.00359 +Epoch [2775/4000] Training [5/16] Loss: 0.00334 +Epoch [2775/4000] Training [6/16] Loss: 0.00375 +Epoch [2775/4000] Training [7/16] Loss: 0.00502 +Epoch [2775/4000] Training [8/16] Loss: 0.00309 +Epoch [2775/4000] Training [9/16] Loss: 0.00436 +Epoch [2775/4000] Training [10/16] Loss: 0.00264 +Epoch [2775/4000] Training [11/16] Loss: 0.00274 +Epoch [2775/4000] Training [12/16] Loss: 0.00309 +Epoch [2775/4000] Training [13/16] Loss: 0.00497 +Epoch [2775/4000] Training [14/16] Loss: 0.00403 +Epoch [2775/4000] Training [15/16] Loss: 0.00417 +Epoch [2775/4000] Training [16/16] Loss: 0.00296 +Epoch [2775/4000] Training metric {'Train/mean dice_metric': 0.9978320598602295, 'Train/mean miou_metric': 0.995376706123352, 'Train/mean f1': 0.9923987984657288, 'Train/mean precision': 0.9872948527336121, 'Train/mean recall': 0.9975557923316956, 'Train/mean hd95_metric': 0.8866493105888367} +Epoch [2775/4000] Validation [1/4] Loss: 0.31979 focal_loss 0.25787 dice_loss 0.06192 +Epoch [2775/4000] Validation [2/4] Loss: 0.45850 focal_loss 0.34299 dice_loss 0.11552 +Epoch [2775/4000] Validation [3/4] Loss: 0.42074 focal_loss 0.32958 dice_loss 0.09116 +Epoch [2775/4000] Validation [4/4] Loss: 0.28902 focal_loss 0.20544 dice_loss 0.08358 +Epoch [2775/4000] Validation metric {'Val/mean dice_metric': 0.9729671478271484, 'Val/mean miou_metric': 0.9580984115600586, 'Val/mean f1': 0.9746458530426025, 'Val/mean precision': 0.9721651077270508, 'Val/mean recall': 0.9771394729614258, 'Val/mean hd95_metric': 5.369824409484863} +Cheakpoint... +Epoch [2775/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729671478271484, 'Val/mean miou_metric': 0.9580984115600586, 'Val/mean f1': 0.9746458530426025, 'Val/mean precision': 0.9721651077270508, 'Val/mean recall': 0.9771394729614258, 'Val/mean hd95_metric': 5.369824409484863} +Epoch [2776/4000] Training [1/16] Loss: 0.00303 +Epoch [2776/4000] Training [2/16] Loss: 0.00254 +Epoch [2776/4000] Training [3/16] Loss: 0.00358 +Epoch [2776/4000] Training [4/16] Loss: 0.00339 +Epoch [2776/4000] Training [5/16] Loss: 0.00282 +Epoch [2776/4000] Training [6/16] Loss: 0.00356 +Epoch [2776/4000] Training [7/16] Loss: 0.00358 +Epoch [2776/4000] Training [8/16] Loss: 0.00399 +Epoch [2776/4000] Training [9/16] Loss: 0.00354 +Epoch [2776/4000] Training [10/16] Loss: 0.00293 +Epoch [2776/4000] Training [11/16] Loss: 0.00290 +Epoch [2776/4000] Training [12/16] Loss: 0.00325 +Epoch [2776/4000] Training [13/16] Loss: 0.00375 +Epoch [2776/4000] Training [14/16] Loss: 0.00272 +Epoch [2776/4000] Training [15/16] Loss: 0.00351 +Epoch [2776/4000] Training [16/16] Loss: 0.00335 +Epoch [2776/4000] Training metric {'Train/mean dice_metric': 0.9980282783508301, 'Train/mean miou_metric': 0.9957668781280518, 'Train/mean f1': 0.9929623007774353, 'Train/mean precision': 0.9881849884986877, 'Train/mean recall': 0.9977861046791077, 'Train/mean hd95_metric': 0.8614112138748169} +Epoch [2776/4000] Validation [1/4] Loss: 0.41386 focal_loss 0.34650 dice_loss 0.06736 +Epoch [2776/4000] Validation [2/4] Loss: 1.09703 focal_loss 0.90683 dice_loss 0.19020 +Epoch [2776/4000] Validation [3/4] Loss: 0.40880 focal_loss 0.32219 dice_loss 0.08660 +Epoch [2776/4000] Validation [4/4] Loss: 0.31429 focal_loss 0.21429 dice_loss 0.10000 +Epoch [2776/4000] Validation metric {'Val/mean dice_metric': 0.9733864665031433, 'Val/mean miou_metric': 0.9588367342948914, 'Val/mean f1': 0.9756515026092529, 'Val/mean precision': 0.9736985564231873, 'Val/mean recall': 0.9776122570037842, 'Val/mean hd95_metric': 4.61215877532959} +Cheakpoint... +Epoch [2776/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733864665031433, 'Val/mean miou_metric': 0.9588367342948914, 'Val/mean f1': 0.9756515026092529, 'Val/mean precision': 0.9736985564231873, 'Val/mean recall': 0.9776122570037842, 'Val/mean hd95_metric': 4.61215877532959} +Epoch [2777/4000] Training [1/16] Loss: 0.00298 +Epoch [2777/4000] Training [2/16] Loss: 0.00585 +Epoch [2777/4000] Training [3/16] Loss: 0.00382 +Epoch [2777/4000] Training [4/16] Loss: 0.00289 +Epoch [2777/4000] Training [5/16] Loss: 0.00548 +Epoch [2777/4000] Training [6/16] Loss: 0.00456 +Epoch [2777/4000] Training [7/16] Loss: 0.00474 +Epoch [2777/4000] Training [8/16] Loss: 0.00352 +Epoch [2777/4000] Training [9/16] Loss: 0.00352 +Epoch [2777/4000] Training [10/16] Loss: 0.00336 +Epoch [2777/4000] Training [11/16] Loss: 0.00315 +Epoch [2777/4000] Training [12/16] Loss: 0.00406 +Epoch [2777/4000] Training [13/16] Loss: 0.00317 +Epoch [2777/4000] Training [14/16] Loss: 0.00316 +Epoch [2777/4000] Training [15/16] Loss: 0.00468 +Epoch [2777/4000] Training [16/16] Loss: 0.00273 +Epoch [2777/4000] Training metric {'Train/mean dice_metric': 0.9977688193321228, 'Train/mean miou_metric': 0.995275616645813, 'Train/mean f1': 0.9930704236030579, 'Train/mean precision': 0.9885302186012268, 'Train/mean recall': 0.9976524710655212, 'Train/mean hd95_metric': 0.8772737383842468} +Epoch [2777/4000] Validation [1/4] Loss: 0.40116 focal_loss 0.31926 dice_loss 0.08189 +Epoch [2777/4000] Validation [2/4] Loss: 1.07453 focal_loss 0.88694 dice_loss 0.18759 +Epoch [2777/4000] Validation [3/4] Loss: 0.41458 focal_loss 0.32526 dice_loss 0.08932 +Epoch [2777/4000] Validation [4/4] Loss: 0.27902 focal_loss 0.19059 dice_loss 0.08844 +Epoch [2777/4000] Validation metric {'Val/mean dice_metric': 0.974134087562561, 'Val/mean miou_metric': 0.9592782855033875, 'Val/mean f1': 0.9756765365600586, 'Val/mean precision': 0.9743471741676331, 'Val/mean recall': 0.9770095348358154, 'Val/mean hd95_metric': 4.669461727142334} +Cheakpoint... +Epoch [2777/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974134087562561, 'Val/mean miou_metric': 0.9592782855033875, 'Val/mean f1': 0.9756765365600586, 'Val/mean precision': 0.9743471741676331, 'Val/mean recall': 0.9770095348358154, 'Val/mean hd95_metric': 4.669461727142334} +Epoch [2778/4000] Training [1/16] Loss: 0.00536 +Epoch [2778/4000] Training [2/16] Loss: 0.00416 +Epoch [2778/4000] Training [3/16] Loss: 0.00443 +Epoch [2778/4000] Training [4/16] Loss: 0.00380 +Epoch [2778/4000] Training [5/16] Loss: 0.00330 +Epoch [2778/4000] Training [6/16] Loss: 0.00361 +Epoch [2778/4000] Training [7/16] Loss: 0.00407 +Epoch [2778/4000] Training [8/16] Loss: 0.00363 +Epoch [2778/4000] Training [9/16] Loss: 0.00335 +Epoch [2778/4000] Training [10/16] Loss: 0.00306 +Epoch [2778/4000] Training [11/16] Loss: 0.00402 +Epoch [2778/4000] Training [12/16] Loss: 0.00365 +Epoch [2778/4000] Training [13/16] Loss: 0.00259 +Epoch [2778/4000] Training [14/16] Loss: 0.00393 +Epoch [2778/4000] Training [15/16] Loss: 0.00265 +Epoch [2778/4000] Training [16/16] Loss: 0.00398 +Epoch [2778/4000] Training metric {'Train/mean dice_metric': 0.997722864151001, 'Train/mean miou_metric': 0.9951889514923096, 'Train/mean f1': 0.9929986000061035, 'Train/mean precision': 0.988514244556427, 'Train/mean recall': 0.9975237846374512, 'Train/mean hd95_metric': 0.8988673686981201} +Epoch [2778/4000] Validation [1/4] Loss: 0.37385 focal_loss 0.30791 dice_loss 0.06594 +Epoch [2778/4000] Validation [2/4] Loss: 1.03090 focal_loss 0.84447 dice_loss 0.18643 +Epoch [2778/4000] Validation [3/4] Loss: 0.40269 focal_loss 0.31550 dice_loss 0.08718 +Epoch [2778/4000] Validation [4/4] Loss: 0.30082 focal_loss 0.21155 dice_loss 0.08927 +Epoch [2778/4000] Validation metric {'Val/mean dice_metric': 0.9725416302680969, 'Val/mean miou_metric': 0.9579795002937317, 'Val/mean f1': 0.9756225347518921, 'Val/mean precision': 0.9739019870758057, 'Val/mean recall': 0.9773491621017456, 'Val/mean hd95_metric': 4.95942497253418} +Cheakpoint... +Epoch [2778/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725416302680969, 'Val/mean miou_metric': 0.9579795002937317, 'Val/mean f1': 0.9756225347518921, 'Val/mean precision': 0.9739019870758057, 'Val/mean recall': 0.9773491621017456, 'Val/mean hd95_metric': 4.95942497253418} +Epoch [2779/4000] Training [1/16] Loss: 0.00483 +Epoch [2779/4000] Training [2/16] Loss: 0.00269 +Epoch [2779/4000] Training [3/16] Loss: 0.00392 +Epoch [2779/4000] Training [4/16] Loss: 0.00271 +Epoch [2779/4000] Training [5/16] Loss: 0.00596 +Epoch [2779/4000] Training [6/16] Loss: 0.00394 +Epoch [2779/4000] Training [7/16] Loss: 0.00431 +Epoch [2779/4000] Training [8/16] Loss: 0.00530 +Epoch [2779/4000] Training [9/16] Loss: 0.00359 +Epoch [2779/4000] Training [10/16] Loss: 0.00275 +Epoch [2779/4000] Training [11/16] Loss: 0.00325 +Epoch [2779/4000] Training [12/16] Loss: 0.00335 +Epoch [2779/4000] Training [13/16] Loss: 0.00256 +Epoch [2779/4000] Training [14/16] Loss: 0.00371 +Epoch [2779/4000] Training [15/16] Loss: 0.00316 +Epoch [2779/4000] Training [16/16] Loss: 0.00503 +Epoch [2779/4000] Training metric {'Train/mean dice_metric': 0.9975870847702026, 'Train/mean miou_metric': 0.9948734045028687, 'Train/mean f1': 0.992294192314148, 'Train/mean precision': 0.9871562123298645, 'Train/mean recall': 0.997485876083374, 'Train/mean hd95_metric': 0.9025834202766418} +Epoch [2779/4000] Validation [1/4] Loss: 0.32645 focal_loss 0.26542 dice_loss 0.06103 +Epoch [2779/4000] Validation [2/4] Loss: 0.91192 focal_loss 0.72114 dice_loss 0.19078 +Epoch [2779/4000] Validation [3/4] Loss: 0.44129 focal_loss 0.34871 dice_loss 0.09257 +Epoch [2779/4000] Validation [4/4] Loss: 0.37399 focal_loss 0.25670 dice_loss 0.11729 +Epoch [2779/4000] Validation metric {'Val/mean dice_metric': 0.9721725583076477, 'Val/mean miou_metric': 0.9578604698181152, 'Val/mean f1': 0.9745326042175293, 'Val/mean precision': 0.9704557657241821, 'Val/mean recall': 0.9786438941955566, 'Val/mean hd95_metric': 5.262930393218994} +Cheakpoint... +Epoch [2779/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721725583076477, 'Val/mean miou_metric': 0.9578604698181152, 'Val/mean f1': 0.9745326042175293, 'Val/mean precision': 0.9704557657241821, 'Val/mean recall': 0.9786438941955566, 'Val/mean hd95_metric': 5.262930393218994} +Epoch [2780/4000] Training [1/16] Loss: 0.00333 +Epoch [2780/4000] Training [2/16] Loss: 0.00468 +Epoch [2780/4000] Training [3/16] Loss: 0.00311 +Epoch [2780/4000] Training [4/16] Loss: 0.00350 +Epoch [2780/4000] Training [5/16] Loss: 0.00423 +Epoch [2780/4000] Training [6/16] Loss: 0.00403 +Epoch [2780/4000] Training [7/16] Loss: 0.00268 +Epoch [2780/4000] Training [8/16] Loss: 0.00298 +Epoch [2780/4000] Training [9/16] Loss: 0.00334 +Epoch [2780/4000] Training [10/16] Loss: 0.00520 +Epoch [2780/4000] Training [11/16] Loss: 0.00299 +Epoch [2780/4000] Training [12/16] Loss: 0.00297 +Epoch [2780/4000] Training [13/16] Loss: 0.00326 +Epoch [2780/4000] Training [14/16] Loss: 0.00337 +Epoch [2780/4000] Training [15/16] Loss: 0.00385 +Epoch [2780/4000] Training [16/16] Loss: 0.00361 +Epoch [2780/4000] Training metric {'Train/mean dice_metric': 0.9977520704269409, 'Train/mean miou_metric': 0.9952459931373596, 'Train/mean f1': 0.9930676817893982, 'Train/mean precision': 0.988578736782074, 'Train/mean recall': 0.9975975155830383, 'Train/mean hd95_metric': 0.8680241107940674} +Epoch [2780/4000] Validation [1/4] Loss: 0.36640 focal_loss 0.30103 dice_loss 0.06537 +Epoch [2780/4000] Validation [2/4] Loss: 0.42857 focal_loss 0.31228 dice_loss 0.11628 +Epoch [2780/4000] Validation [3/4] Loss: 0.43589 focal_loss 0.34537 dice_loss 0.09052 +Epoch [2780/4000] Validation [4/4] Loss: 0.26925 focal_loss 0.19206 dice_loss 0.07719 +Epoch [2780/4000] Validation metric {'Val/mean dice_metric': 0.9742450714111328, 'Val/mean miou_metric': 0.959943413734436, 'Val/mean f1': 0.976012647151947, 'Val/mean precision': 0.9736771583557129, 'Val/mean recall': 0.9783594012260437, 'Val/mean hd95_metric': 4.962357521057129} +Cheakpoint... +Epoch [2780/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742450714111328, 'Val/mean miou_metric': 0.959943413734436, 'Val/mean f1': 0.976012647151947, 'Val/mean precision': 0.9736771583557129, 'Val/mean recall': 0.9783594012260437, 'Val/mean hd95_metric': 4.962357521057129} +Epoch [2781/4000] Training [1/16] Loss: 0.00391 +Epoch [2781/4000] Training [2/16] Loss: 0.00343 +Epoch [2781/4000] Training [3/16] Loss: 0.00282 +Epoch [2781/4000] Training [4/16] Loss: 0.00355 +Epoch [2781/4000] Training [5/16] Loss: 0.00270 +Epoch [2781/4000] Training [6/16] Loss: 0.00351 +Epoch [2781/4000] Training [7/16] Loss: 0.00296 +Epoch [2781/4000] Training [8/16] Loss: 0.00354 +Epoch [2781/4000] Training [9/16] Loss: 0.00353 +Epoch [2781/4000] Training [10/16] Loss: 0.00392 +Epoch [2781/4000] Training [11/16] Loss: 0.00303 +Epoch [2781/4000] Training [12/16] Loss: 0.00297 +Epoch [2781/4000] Training [13/16] Loss: 0.00345 +Epoch [2781/4000] Training [14/16] Loss: 0.00327 +Epoch [2781/4000] Training [15/16] Loss: 0.00316 +Epoch [2781/4000] Training [16/16] Loss: 0.00349 +Epoch [2781/4000] Training metric {'Train/mean dice_metric': 0.9978526830673218, 'Train/mean miou_metric': 0.9954420328140259, 'Train/mean f1': 0.9931346774101257, 'Train/mean precision': 0.9886288046836853, 'Train/mean recall': 0.9976817965507507, 'Train/mean hd95_metric': 0.8636995553970337} +Epoch [2781/4000] Validation [1/4] Loss: 0.36984 focal_loss 0.30184 dice_loss 0.06801 +Epoch [2781/4000] Validation [2/4] Loss: 0.40931 focal_loss 0.29567 dice_loss 0.11364 +Epoch [2781/4000] Validation [3/4] Loss: 0.43885 focal_loss 0.35169 dice_loss 0.08716 +Epoch [2781/4000] Validation [4/4] Loss: 0.28958 focal_loss 0.20117 dice_loss 0.08841 +Epoch [2781/4000] Validation metric {'Val/mean dice_metric': 0.9736669659614563, 'Val/mean miou_metric': 0.958916187286377, 'Val/mean f1': 0.9748762249946594, 'Val/mean precision': 0.9715520143508911, 'Val/mean recall': 0.9782230257987976, 'Val/mean hd95_metric': 5.479487419128418} +Cheakpoint... +Epoch [2781/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736669659614563, 'Val/mean miou_metric': 0.958916187286377, 'Val/mean f1': 0.9748762249946594, 'Val/mean precision': 0.9715520143508911, 'Val/mean recall': 0.9782230257987976, 'Val/mean hd95_metric': 5.479487419128418} +Epoch [2782/4000] Training [1/16] Loss: 0.00467 +Epoch [2782/4000] Training [2/16] Loss: 0.00413 +Epoch [2782/4000] Training [3/16] Loss: 0.00303 +Epoch [2782/4000] Training [4/16] Loss: 0.00344 +Epoch [2782/4000] Training [5/16] Loss: 0.00377 +Epoch [2782/4000] Training [6/16] Loss: 0.00426 +Epoch [2782/4000] Training [7/16] Loss: 0.00404 +Epoch [2782/4000] Training [8/16] Loss: 0.00535 +Epoch [2782/4000] Training [9/16] Loss: 0.00356 +Epoch [2782/4000] Training [10/16] Loss: 0.00395 +Epoch [2782/4000] Training [11/16] Loss: 0.00472 +Epoch [2782/4000] Training [12/16] Loss: 0.00278 +Epoch [2782/4000] Training [13/16] Loss: 0.00388 +Epoch [2782/4000] Training [14/16] Loss: 0.00361 +Epoch [2782/4000] Training [15/16] Loss: 0.00367 +Epoch [2782/4000] Training [16/16] Loss: 0.00378 +Epoch [2782/4000] Training metric {'Train/mean dice_metric': 0.9977200031280518, 'Train/mean miou_metric': 0.9951839447021484, 'Train/mean f1': 0.9930841326713562, 'Train/mean precision': 0.9885393381118774, 'Train/mean recall': 0.9976709485054016, 'Train/mean hd95_metric': 0.8732554912567139} +Epoch [2782/4000] Validation [1/4] Loss: 0.34124 focal_loss 0.27710 dice_loss 0.06414 +Epoch [2782/4000] Validation [2/4] Loss: 0.92642 focal_loss 0.73251 dice_loss 0.19391 +Epoch [2782/4000] Validation [3/4] Loss: 0.43806 focal_loss 0.34480 dice_loss 0.09326 +Epoch [2782/4000] Validation [4/4] Loss: 0.33866 focal_loss 0.23588 dice_loss 0.10278 +Epoch [2782/4000] Validation metric {'Val/mean dice_metric': 0.9730409383773804, 'Val/mean miou_metric': 0.9589124917984009, 'Val/mean f1': 0.9760465025901794, 'Val/mean precision': 0.9733009934425354, 'Val/mean recall': 0.9788076877593994, 'Val/mean hd95_metric': 5.249056816101074} +Cheakpoint... +Epoch [2782/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730409383773804, 'Val/mean miou_metric': 0.9589124917984009, 'Val/mean f1': 0.9760465025901794, 'Val/mean precision': 0.9733009934425354, 'Val/mean recall': 0.9788076877593994, 'Val/mean hd95_metric': 5.249056816101074} +Epoch [2783/4000] Training [1/16] Loss: 0.00407 +Epoch [2783/4000] Training [2/16] Loss: 0.00456 +Epoch [2783/4000] Training [3/16] Loss: 0.00375 +Epoch [2783/4000] Training [4/16] Loss: 0.00342 +Epoch [2783/4000] Training [5/16] Loss: 0.00498 +Epoch [2783/4000] Training [6/16] Loss: 0.00388 +Epoch [2783/4000] Training [7/16] Loss: 0.00275 +Epoch [2783/4000] Training [8/16] Loss: 0.00264 +Epoch [2783/4000] Training [9/16] Loss: 0.00498 +Epoch [2783/4000] Training [10/16] Loss: 0.00291 +Epoch [2783/4000] Training [11/16] Loss: 0.00337 +Epoch [2783/4000] Training [12/16] Loss: 0.00351 +Epoch [2783/4000] Training [13/16] Loss: 0.00315 +Epoch [2783/4000] Training [14/16] Loss: 0.00394 +Epoch [2783/4000] Training [15/16] Loss: 0.00343 +Epoch [2783/4000] Training [16/16] Loss: 0.00293 +Epoch [2783/4000] Training metric {'Train/mean dice_metric': 0.9977914690971375, 'Train/mean miou_metric': 0.9953180551528931, 'Train/mean f1': 0.9929437041282654, 'Train/mean precision': 0.9883111119270325, 'Train/mean recall': 0.9976199269294739, 'Train/mean hd95_metric': 0.8797428607940674} +Epoch [2783/4000] Validation [1/4] Loss: 0.35887 focal_loss 0.29435 dice_loss 0.06453 +Epoch [2783/4000] Validation [2/4] Loss: 0.90146 focal_loss 0.71056 dice_loss 0.19090 +Epoch [2783/4000] Validation [3/4] Loss: 0.44117 focal_loss 0.35213 dice_loss 0.08904 +Epoch [2783/4000] Validation [4/4] Loss: 0.24635 focal_loss 0.15894 dice_loss 0.08741 +Epoch [2783/4000] Validation metric {'Val/mean dice_metric': 0.9730450510978699, 'Val/mean miou_metric': 0.9593428373336792, 'Val/mean f1': 0.9757120609283447, 'Val/mean precision': 0.9724695682525635, 'Val/mean recall': 0.9789761304855347, 'Val/mean hd95_metric': 5.110924243927002} +Cheakpoint... +Epoch [2783/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730450510978699, 'Val/mean miou_metric': 0.9593428373336792, 'Val/mean f1': 0.9757120609283447, 'Val/mean precision': 0.9724695682525635, 'Val/mean recall': 0.9789761304855347, 'Val/mean hd95_metric': 5.110924243927002} +Epoch [2784/4000] Training [1/16] Loss: 0.00308 +Epoch [2784/4000] Training [2/16] Loss: 0.00404 +Epoch [2784/4000] Training [3/16] Loss: 0.00304 +Epoch [2784/4000] Training [4/16] Loss: 0.00527 +Epoch [2784/4000] Training [5/16] Loss: 0.00295 +Epoch [2784/4000] Training [6/16] Loss: 0.00411 +Epoch [2784/4000] Training [7/16] Loss: 0.00391 +Epoch [2784/4000] Training [8/16] Loss: 0.00261 +Epoch [2784/4000] Training [9/16] Loss: 0.00265 +Epoch [2784/4000] Training [10/16] Loss: 0.00358 +Epoch [2784/4000] Training [11/16] Loss: 0.00455 +Epoch [2784/4000] Training [12/16] Loss: 0.00590 +Epoch [2784/4000] Training [13/16] Loss: 0.00338 +Epoch [2784/4000] Training [14/16] Loss: 0.00457 +Epoch [2784/4000] Training [15/16] Loss: 0.00406 +Epoch [2784/4000] Training [16/16] Loss: 0.00551 +Epoch [2784/4000] Training metric {'Train/mean dice_metric': 0.9977350831031799, 'Train/mean miou_metric': 0.9951921701431274, 'Train/mean f1': 0.992813229560852, 'Train/mean precision': 0.9881409406661987, 'Train/mean recall': 0.997529923915863, 'Train/mean hd95_metric': 0.8927311897277832} +Epoch [2784/4000] Validation [1/4] Loss: 0.38426 focal_loss 0.32002 dice_loss 0.06425 +Epoch [2784/4000] Validation [2/4] Loss: 0.70424 focal_loss 0.51710 dice_loss 0.18714 +Epoch [2784/4000] Validation [3/4] Loss: 0.43417 focal_loss 0.34182 dice_loss 0.09235 +Epoch [2784/4000] Validation [4/4] Loss: 0.47807 focal_loss 0.34713 dice_loss 0.13094 +Epoch [2784/4000] Validation metric {'Val/mean dice_metric': 0.9722394943237305, 'Val/mean miou_metric': 0.9569745063781738, 'Val/mean f1': 0.9746261835098267, 'Val/mean precision': 0.9719595909118652, 'Val/mean recall': 0.9773075580596924, 'Val/mean hd95_metric': 5.5744500160217285} +Cheakpoint... +Epoch [2784/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722394943237305, 'Val/mean miou_metric': 0.9569745063781738, 'Val/mean f1': 0.9746261835098267, 'Val/mean precision': 0.9719595909118652, 'Val/mean recall': 0.9773075580596924, 'Val/mean hd95_metric': 5.5744500160217285} +Epoch [2785/4000] Training [1/16] Loss: 0.00473 +Epoch [2785/4000] Training [2/16] Loss: 0.00447 +Epoch [2785/4000] Training [3/16] Loss: 0.02036 +Epoch [2785/4000] Training [4/16] Loss: 0.00353 +Epoch [2785/4000] Training [5/16] Loss: 0.00318 +Epoch [2785/4000] Training [6/16] Loss: 0.00363 +Epoch [2785/4000] Training [7/16] Loss: 0.00432 +Epoch [2785/4000] Training [8/16] Loss: 0.00369 +Epoch [2785/4000] Training [9/16] Loss: 0.00467 +Epoch [2785/4000] Training [10/16] Loss: 0.00337 +Epoch [2785/4000] Training [11/16] Loss: 0.00307 +Epoch [2785/4000] Training [12/16] Loss: 0.00353 +Epoch [2785/4000] Training [13/16] Loss: 0.00278 +Epoch [2785/4000] Training [14/16] Loss: 0.00318 +Epoch [2785/4000] Training [15/16] Loss: 0.00322 +Epoch [2785/4000] Training [16/16] Loss: 0.00386 +Epoch [2785/4000] Training metric {'Train/mean dice_metric': 0.9976857900619507, 'Train/mean miou_metric': 0.9951321482658386, 'Train/mean f1': 0.9930206537246704, 'Train/mean precision': 0.9886083006858826, 'Train/mean recall': 0.9974725246429443, 'Train/mean hd95_metric': 0.8795159459114075} +Epoch [2785/4000] Validation [1/4] Loss: 0.34301 focal_loss 0.27812 dice_loss 0.06489 +Epoch [2785/4000] Validation [2/4] Loss: 0.33364 focal_loss 0.23287 dice_loss 0.10077 +Epoch [2785/4000] Validation [3/4] Loss: 0.45776 focal_loss 0.36962 dice_loss 0.08814 +Epoch [2785/4000] Validation [4/4] Loss: 0.34675 focal_loss 0.23939 dice_loss 0.10737 +Epoch [2785/4000] Validation metric {'Val/mean dice_metric': 0.9736565351486206, 'Val/mean miou_metric': 0.9590174555778503, 'Val/mean f1': 0.975976288318634, 'Val/mean precision': 0.973324179649353, 'Val/mean recall': 0.978643000125885, 'Val/mean hd95_metric': 5.046588897705078} +Cheakpoint... +Epoch [2785/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736565351486206, 'Val/mean miou_metric': 0.9590174555778503, 'Val/mean f1': 0.975976288318634, 'Val/mean precision': 0.973324179649353, 'Val/mean recall': 0.978643000125885, 'Val/mean hd95_metric': 5.046588897705078} +Epoch [2786/4000] Training [1/16] Loss: 0.00419 +Epoch [2786/4000] Training [2/16] Loss: 0.00561 +Epoch [2786/4000] Training [3/16] Loss: 0.00337 +Epoch [2786/4000] Training [4/16] Loss: 0.00301 +Epoch [2786/4000] Training [5/16] Loss: 0.00434 +Epoch [2786/4000] Training [6/16] Loss: 0.00298 +Epoch [2786/4000] Training [7/16] Loss: 0.00520 +Epoch [2786/4000] Training [8/16] Loss: 0.00326 +Epoch [2786/4000] Training [9/16] Loss: 0.00402 +Epoch [2786/4000] Training [10/16] Loss: 0.00294 +Epoch [2786/4000] Training [11/16] Loss: 0.00287 +Epoch [2786/4000] Training [12/16] Loss: 0.00347 +Epoch [2786/4000] Training [13/16] Loss: 0.00288 +Epoch [2786/4000] Training [14/16] Loss: 0.00266 +Epoch [2786/4000] Training [15/16] Loss: 0.00335 +Epoch [2786/4000] Training [16/16] Loss: 0.00269 +Epoch [2786/4000] Training metric {'Train/mean dice_metric': 0.9978976249694824, 'Train/mean miou_metric': 0.9955295920372009, 'Train/mean f1': 0.9931699633598328, 'Train/mean precision': 0.988624632358551, 'Train/mean recall': 0.9977573156356812, 'Train/mean hd95_metric': 0.8583353757858276} +Epoch [2786/4000] Validation [1/4] Loss: 0.35497 focal_loss 0.28929 dice_loss 0.06568 +Epoch [2786/4000] Validation [2/4] Loss: 0.38091 focal_loss 0.27056 dice_loss 0.11035 +Epoch [2786/4000] Validation [3/4] Loss: 0.44834 focal_loss 0.35998 dice_loss 0.08836 +Epoch [2786/4000] Validation [4/4] Loss: 0.28460 focal_loss 0.19925 dice_loss 0.08536 +Epoch [2786/4000] Validation metric {'Val/mean dice_metric': 0.9739991426467896, 'Val/mean miou_metric': 0.9595503807067871, 'Val/mean f1': 0.9761947393417358, 'Val/mean precision': 0.9735742211341858, 'Val/mean recall': 0.9788295030593872, 'Val/mean hd95_metric': 4.906483173370361} +Cheakpoint... +Epoch [2786/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739991426467896, 'Val/mean miou_metric': 0.9595503807067871, 'Val/mean f1': 0.9761947393417358, 'Val/mean precision': 0.9735742211341858, 'Val/mean recall': 0.9788295030593872, 'Val/mean hd95_metric': 4.906483173370361} +Epoch [2787/4000] Training [1/16] Loss: 0.00372 +Epoch [2787/4000] Training [2/16] Loss: 0.00492 +Epoch [2787/4000] Training [3/16] Loss: 0.00369 +Epoch [2787/4000] Training [4/16] Loss: 0.00285 +Epoch [2787/4000] Training [5/16] Loss: 0.00312 +Epoch [2787/4000] Training [6/16] Loss: 0.00253 +Epoch [2787/4000] Training [7/16] Loss: 0.00439 +Epoch [2787/4000] Training [8/16] Loss: 0.00457 +Epoch [2787/4000] Training [9/16] Loss: 0.00376 +Epoch [2787/4000] Training [10/16] Loss: 0.00270 +Epoch [2787/4000] Training [11/16] Loss: 0.00328 +Epoch [2787/4000] Training [12/16] Loss: 0.00312 +Epoch [2787/4000] Training [13/16] Loss: 0.00362 +Epoch [2787/4000] Training [14/16] Loss: 0.00343 +Epoch [2787/4000] Training [15/16] Loss: 0.00377 +Epoch [2787/4000] Training [16/16] Loss: 0.00410 +Epoch [2787/4000] Training metric {'Train/mean dice_metric': 0.9979220628738403, 'Train/mean miou_metric': 0.9955621957778931, 'Train/mean f1': 0.9927768111228943, 'Train/mean precision': 0.9878314137458801, 'Train/mean recall': 0.9977719783782959, 'Train/mean hd95_metric': 0.8914297223091125} +Epoch [2787/4000] Validation [1/4] Loss: 0.33920 focal_loss 0.27405 dice_loss 0.06515 +Epoch [2787/4000] Validation [2/4] Loss: 0.40556 focal_loss 0.28890 dice_loss 0.11665 +Epoch [2787/4000] Validation [3/4] Loss: 0.42892 focal_loss 0.33365 dice_loss 0.09526 +Epoch [2787/4000] Validation [4/4] Loss: 0.38775 focal_loss 0.28102 dice_loss 0.10673 +Epoch [2787/4000] Validation metric {'Val/mean dice_metric': 0.9728866815567017, 'Val/mean miou_metric': 0.9581722021102905, 'Val/mean f1': 0.975436806678772, 'Val/mean precision': 0.9724966287612915, 'Val/mean recall': 0.9783948659896851, 'Val/mean hd95_metric': 5.134429454803467} +Cheakpoint... +Epoch [2787/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728866815567017, 'Val/mean miou_metric': 0.9581722021102905, 'Val/mean f1': 0.975436806678772, 'Val/mean precision': 0.9724966287612915, 'Val/mean recall': 0.9783948659896851, 'Val/mean hd95_metric': 5.134429454803467} +Epoch [2788/4000] Training [1/16] Loss: 0.00316 +Epoch [2788/4000] Training [2/16] Loss: 0.00419 +Epoch [2788/4000] Training [3/16] Loss: 0.00302 +Epoch [2788/4000] Training [4/16] Loss: 0.00472 +Epoch [2788/4000] Training [5/16] Loss: 0.00280 +Epoch [2788/4000] Training [6/16] Loss: 0.00511 +Epoch [2788/4000] Training [7/16] Loss: 0.00515 +Epoch [2788/4000] Training [8/16] Loss: 0.00459 +Epoch [2788/4000] Training [9/16] Loss: 0.00550 +Epoch [2788/4000] Training [10/16] Loss: 0.00303 +Epoch [2788/4000] Training [11/16] Loss: 0.00371 +Epoch [2788/4000] Training [12/16] Loss: 0.00460 +Epoch [2788/4000] Training [13/16] Loss: 0.00276 +Epoch [2788/4000] Training [14/16] Loss: 0.00343 +Epoch [2788/4000] Training [15/16] Loss: 0.00434 +Epoch [2788/4000] Training [16/16] Loss: 0.00363 +Epoch [2788/4000] Training metric {'Train/mean dice_metric': 0.9976320266723633, 'Train/mean miou_metric': 0.995001494884491, 'Train/mean f1': 0.9930559992790222, 'Train/mean precision': 0.9885332584381104, 'Train/mean recall': 0.9976202845573425, 'Train/mean hd95_metric': 0.880203366279602} +Epoch [2788/4000] Validation [1/4] Loss: 0.35370 focal_loss 0.28950 dice_loss 0.06420 +Epoch [2788/4000] Validation [2/4] Loss: 1.38806 focal_loss 1.12031 dice_loss 0.26775 +Epoch [2788/4000] Validation [3/4] Loss: 0.32867 focal_loss 0.23957 dice_loss 0.08910 +Epoch [2788/4000] Validation [4/4] Loss: 0.38773 focal_loss 0.27883 dice_loss 0.10890 +Epoch [2788/4000] Validation metric {'Val/mean dice_metric': 0.9713302850723267, 'Val/mean miou_metric': 0.9565191268920898, 'Val/mean f1': 0.9752453565597534, 'Val/mean precision': 0.9727915525436401, 'Val/mean recall': 0.97771155834198, 'Val/mean hd95_metric': 4.970455169677734} +Cheakpoint... +Epoch [2788/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713302850723267, 'Val/mean miou_metric': 0.9565191268920898, 'Val/mean f1': 0.9752453565597534, 'Val/mean precision': 0.9727915525436401, 'Val/mean recall': 0.97771155834198, 'Val/mean hd95_metric': 4.970455169677734} +Epoch [2789/4000] Training [1/16] Loss: 0.00407 +Epoch [2789/4000] Training [2/16] Loss: 0.00308 +Epoch [2789/4000] Training [3/16] Loss: 0.00545 +Epoch [2789/4000] Training [4/16] Loss: 0.00378 +Epoch [2789/4000] Training [5/16] Loss: 0.00329 +Epoch [2789/4000] Training [6/16] Loss: 0.00452 +Epoch [2789/4000] Training [7/16] Loss: 0.00377 +Epoch [2789/4000] Training [8/16] Loss: 0.00506 +Epoch [2789/4000] Training [9/16] Loss: 0.00439 +Epoch [2789/4000] Training [10/16] Loss: 0.00386 +Epoch [2789/4000] Training [11/16] Loss: 0.00314 +Epoch [2789/4000] Training [12/16] Loss: 0.00390 +Epoch [2789/4000] Training [13/16] Loss: 0.00295 +Epoch [2789/4000] Training [14/16] Loss: 0.00309 +Epoch [2789/4000] Training [15/16] Loss: 0.00323 +Epoch [2789/4000] Training [16/16] Loss: 0.00326 +Epoch [2789/4000] Training metric {'Train/mean dice_metric': 0.9977805614471436, 'Train/mean miou_metric': 0.995283842086792, 'Train/mean f1': 0.9928019642829895, 'Train/mean precision': 0.9880607724189758, 'Train/mean recall': 0.9975888729095459, 'Train/mean hd95_metric': 0.8643132448196411} +Epoch [2789/4000] Validation [1/4] Loss: 0.35986 focal_loss 0.29368 dice_loss 0.06619 +Epoch [2789/4000] Validation [2/4] Loss: 0.41302 focal_loss 0.29637 dice_loss 0.11665 +Epoch [2789/4000] Validation [3/4] Loss: 0.44701 focal_loss 0.35623 dice_loss 0.09077 +Epoch [2789/4000] Validation [4/4] Loss: 0.29173 focal_loss 0.20451 dice_loss 0.08723 +Epoch [2789/4000] Validation metric {'Val/mean dice_metric': 0.9734498262405396, 'Val/mean miou_metric': 0.9586647152900696, 'Val/mean f1': 0.9754375219345093, 'Val/mean precision': 0.9731078147888184, 'Val/mean recall': 0.9777782559394836, 'Val/mean hd95_metric': 5.177323818206787} +Cheakpoint... +Epoch [2789/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734498262405396, 'Val/mean miou_metric': 0.9586647152900696, 'Val/mean f1': 0.9754375219345093, 'Val/mean precision': 0.9731078147888184, 'Val/mean recall': 0.9777782559394836, 'Val/mean hd95_metric': 5.177323818206787} +Epoch [2790/4000] Training [1/16] Loss: 0.00322 +Epoch [2790/4000] Training [2/16] Loss: 0.00269 +Epoch [2790/4000] Training [3/16] Loss: 0.00338 +Epoch [2790/4000] Training [4/16] Loss: 0.00236 +Epoch [2790/4000] Training [5/16] Loss: 0.00410 +Epoch [2790/4000] Training [6/16] Loss: 0.00420 +Epoch [2790/4000] Training [7/16] Loss: 0.00332 +Epoch [2790/4000] Training [8/16] Loss: 0.00310 +Epoch [2790/4000] Training [9/16] Loss: 0.00293 +Epoch [2790/4000] Training [10/16] Loss: 0.00202 +Epoch [2790/4000] Training [11/16] Loss: 0.00284 +Epoch [2790/4000] Training [12/16] Loss: 0.00576 +Epoch [2790/4000] Training [13/16] Loss: 0.00333 +Epoch [2790/4000] Training [14/16] Loss: 0.00443 +Epoch [2790/4000] Training [15/16] Loss: 0.00391 +Epoch [2790/4000] Training [16/16] Loss: 0.00294 +Epoch [2790/4000] Training metric {'Train/mean dice_metric': 0.9978739619255066, 'Train/mean miou_metric': 0.9954869747161865, 'Train/mean f1': 0.9932679533958435, 'Train/mean precision': 0.9887824058532715, 'Train/mean recall': 0.9977943897247314, 'Train/mean hd95_metric': 0.8708561658859253} +Epoch [2790/4000] Validation [1/4] Loss: 0.33725 focal_loss 0.27500 dice_loss 0.06225 +Epoch [2790/4000] Validation [2/4] Loss: 0.39690 focal_loss 0.28441 dice_loss 0.11249 +Epoch [2790/4000] Validation [3/4] Loss: 0.42709 focal_loss 0.33381 dice_loss 0.09328 +Epoch [2790/4000] Validation [4/4] Loss: 0.25241 focal_loss 0.17524 dice_loss 0.07717 +Epoch [2790/4000] Validation metric {'Val/mean dice_metric': 0.9737323522567749, 'Val/mean miou_metric': 0.9593837857246399, 'Val/mean f1': 0.9763772487640381, 'Val/mean precision': 0.9741441607475281, 'Val/mean recall': 0.978620707988739, 'Val/mean hd95_metric': 5.12583589553833} +Cheakpoint... +Epoch [2790/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737323522567749, 'Val/mean miou_metric': 0.9593837857246399, 'Val/mean f1': 0.9763772487640381, 'Val/mean precision': 0.9741441607475281, 'Val/mean recall': 0.978620707988739, 'Val/mean hd95_metric': 5.12583589553833} +Epoch [2791/4000] Training [1/16] Loss: 0.00475 +Epoch [2791/4000] Training [2/16] Loss: 0.00270 +Epoch [2791/4000] Training [3/16] Loss: 0.00327 +Epoch [2791/4000] Training [4/16] Loss: 0.00366 +Epoch [2791/4000] Training [5/16] Loss: 0.00472 +Epoch [2791/4000] Training [6/16] Loss: 0.00531 +Epoch [2791/4000] Training [7/16] Loss: 0.00297 +Epoch [2791/4000] Training [8/16] Loss: 0.00231 +Epoch [2791/4000] Training [9/16] Loss: 0.00305 +Epoch [2791/4000] Training [10/16] Loss: 0.00480 +Epoch [2791/4000] Training [11/16] Loss: 0.00329 +Epoch [2791/4000] Training [12/16] Loss: 0.00305 +Epoch [2791/4000] Training [13/16] Loss: 0.00255 +Epoch [2791/4000] Training [14/16] Loss: 0.00456 +Epoch [2791/4000] Training [15/16] Loss: 0.00315 +Epoch [2791/4000] Training [16/16] Loss: 0.00396 +Epoch [2791/4000] Training metric {'Train/mean dice_metric': 0.9978345632553101, 'Train/mean miou_metric': 0.9953852891921997, 'Train/mean f1': 0.9928178191184998, 'Train/mean precision': 0.9880508780479431, 'Train/mean recall': 0.9976309537887573, 'Train/mean hd95_metric': 0.8856722116470337} +Epoch [2791/4000] Validation [1/4] Loss: 0.29394 focal_loss 0.23421 dice_loss 0.05973 +Epoch [2791/4000] Validation [2/4] Loss: 0.73270 focal_loss 0.51611 dice_loss 0.21659 +Epoch [2791/4000] Validation [3/4] Loss: 0.24864 focal_loss 0.19002 dice_loss 0.05862 +Epoch [2791/4000] Validation [4/4] Loss: 0.42982 focal_loss 0.31207 dice_loss 0.11775 +Epoch [2791/4000] Validation metric {'Val/mean dice_metric': 0.9721225500106812, 'Val/mean miou_metric': 0.9574908018112183, 'Val/mean f1': 0.9745744466781616, 'Val/mean precision': 0.9715895652770996, 'Val/mean recall': 0.9775777459144592, 'Val/mean hd95_metric': 4.97553014755249} +Cheakpoint... +Epoch [2791/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721225500106812, 'Val/mean miou_metric': 0.9574908018112183, 'Val/mean f1': 0.9745744466781616, 'Val/mean precision': 0.9715895652770996, 'Val/mean recall': 0.9775777459144592, 'Val/mean hd95_metric': 4.97553014755249} +Epoch [2792/4000] Training [1/16] Loss: 0.00406 +Epoch [2792/4000] Training [2/16] Loss: 0.00336 +Epoch [2792/4000] Training [3/16] Loss: 0.00253 +Epoch [2792/4000] Training [4/16] Loss: 0.00459 +Epoch [2792/4000] Training [5/16] Loss: 0.00335 +Epoch [2792/4000] Training [6/16] Loss: 0.00253 +Epoch [2792/4000] Training [7/16] Loss: 0.00279 +Epoch [2792/4000] Training [8/16] Loss: 0.00343 +Epoch [2792/4000] Training [9/16] Loss: 0.00265 +Epoch [2792/4000] Training [10/16] Loss: 0.00342 +Epoch [2792/4000] Training [11/16] Loss: 0.00401 +Epoch [2792/4000] Training [12/16] Loss: 0.00372 +Epoch [2792/4000] Training [13/16] Loss: 0.00250 +Epoch [2792/4000] Training [14/16] Loss: 0.00401 +Epoch [2792/4000] Training [15/16] Loss: 0.00370 +Epoch [2792/4000] Training [16/16] Loss: 0.00420 +Epoch [2792/4000] Training metric {'Train/mean dice_metric': 0.9979454874992371, 'Train/mean miou_metric': 0.9956021904945374, 'Train/mean f1': 0.9925865530967712, 'Train/mean precision': 0.987479031085968, 'Train/mean recall': 0.9977472424507141, 'Train/mean hd95_metric': 0.8816683292388916} +Epoch [2792/4000] Validation [1/4] Loss: 0.30726 focal_loss 0.24799 dice_loss 0.05927 +Epoch [2792/4000] Validation [2/4] Loss: 0.34649 focal_loss 0.24285 dice_loss 0.10364 +Epoch [2792/4000] Validation [3/4] Loss: 0.22275 focal_loss 0.16681 dice_loss 0.05595 +Epoch [2792/4000] Validation [4/4] Loss: 0.48209 focal_loss 0.33380 dice_loss 0.14829 +Epoch [2792/4000] Validation metric {'Val/mean dice_metric': 0.9742057919502258, 'Val/mean miou_metric': 0.9594858884811401, 'Val/mean f1': 0.9758760929107666, 'Val/mean precision': 0.9728140830993652, 'Val/mean recall': 0.9789573550224304, 'Val/mean hd95_metric': 4.56358003616333} +Cheakpoint... +Epoch [2792/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742057919502258, 'Val/mean miou_metric': 0.9594858884811401, 'Val/mean f1': 0.9758760929107666, 'Val/mean precision': 0.9728140830993652, 'Val/mean recall': 0.9789573550224304, 'Val/mean hd95_metric': 4.56358003616333} +Epoch [2793/4000] Training [1/16] Loss: 0.00340 +Epoch [2793/4000] Training [2/16] Loss: 0.00386 +Epoch [2793/4000] Training [3/16] Loss: 0.00436 +Epoch [2793/4000] Training [4/16] Loss: 0.00535 +Epoch [2793/4000] Training [5/16] Loss: 0.00394 +Epoch [2793/4000] Training [6/16] Loss: 0.00313 +Epoch [2793/4000] Training [7/16] Loss: 0.00254 +Epoch [2793/4000] Training [8/16] Loss: 0.00352 +Epoch [2793/4000] Training [9/16] Loss: 0.00350 +Epoch [2793/4000] Training [10/16] Loss: 0.00328 +Epoch [2793/4000] Training [11/16] Loss: 0.00310 +Epoch [2793/4000] Training [12/16] Loss: 0.00333 +Epoch [2793/4000] Training [13/16] Loss: 0.00382 +Epoch [2793/4000] Training [14/16] Loss: 0.00330 +Epoch [2793/4000] Training [15/16] Loss: 0.00288 +Epoch [2793/4000] Training [16/16] Loss: 0.00348 +Epoch [2793/4000] Training metric {'Train/mean dice_metric': 0.9979038238525391, 'Train/mean miou_metric': 0.9955241084098816, 'Train/mean f1': 0.9930185079574585, 'Train/mean precision': 0.9883901476860046, 'Train/mean recall': 0.9976903796195984, 'Train/mean hd95_metric': 0.8643131256103516} +Epoch [2793/4000] Validation [1/4] Loss: 0.37712 focal_loss 0.30968 dice_loss 0.06744 +Epoch [2793/4000] Validation [2/4] Loss: 0.61112 focal_loss 0.45037 dice_loss 0.16075 +Epoch [2793/4000] Validation [3/4] Loss: 0.38746 focal_loss 0.29953 dice_loss 0.08792 +Epoch [2793/4000] Validation [4/4] Loss: 0.45622 focal_loss 0.32530 dice_loss 0.13092 +Epoch [2793/4000] Validation metric {'Val/mean dice_metric': 0.9725243449211121, 'Val/mean miou_metric': 0.9575210809707642, 'Val/mean f1': 0.9754452109336853, 'Val/mean precision': 0.9714939594268799, 'Val/mean recall': 0.9794286489486694, 'Val/mean hd95_metric': 5.175350189208984} +Cheakpoint... +Epoch [2793/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725243449211121, 'Val/mean miou_metric': 0.9575210809707642, 'Val/mean f1': 0.9754452109336853, 'Val/mean precision': 0.9714939594268799, 'Val/mean recall': 0.9794286489486694, 'Val/mean hd95_metric': 5.175350189208984} +Epoch [2794/4000] Training [1/16] Loss: 0.00275 +Epoch [2794/4000] Training [2/16] Loss: 0.00431 +Epoch [2794/4000] Training [3/16] Loss: 0.00415 +Epoch [2794/4000] Training [4/16] Loss: 0.00455 +Epoch [2794/4000] Training [5/16] Loss: 0.00287 +Epoch [2794/4000] Training [6/16] Loss: 0.00257 +Epoch [2794/4000] Training [7/16] Loss: 0.00509 +Epoch [2794/4000] Training [8/16] Loss: 0.00320 +Epoch [2794/4000] Training [9/16] Loss: 0.00303 +Epoch [2794/4000] Training [10/16] Loss: 0.00268 +Epoch [2794/4000] Training [11/16] Loss: 0.00326 +Epoch [2794/4000] Training [12/16] Loss: 0.00482 +Epoch [2794/4000] Training [13/16] Loss: 0.00363 +Epoch [2794/4000] Training [14/16] Loss: 0.00345 +Epoch [2794/4000] Training [15/16] Loss: 0.00350 +Epoch [2794/4000] Training [16/16] Loss: 0.00391 +Epoch [2794/4000] Training metric {'Train/mean dice_metric': 0.9978336691856384, 'Train/mean miou_metric': 0.9953929781913757, 'Train/mean f1': 0.9929523468017578, 'Train/mean precision': 0.9882411956787109, 'Train/mean recall': 0.9977086186408997, 'Train/mean hd95_metric': 0.8607000112533569} +Epoch [2794/4000] Validation [1/4] Loss: 0.31445 focal_loss 0.25294 dice_loss 0.06151 +Epoch [2794/4000] Validation [2/4] Loss: 0.33427 focal_loss 0.23309 dice_loss 0.10119 +Epoch [2794/4000] Validation [3/4] Loss: 0.22316 focal_loss 0.16810 dice_loss 0.05506 +Epoch [2794/4000] Validation [4/4] Loss: 0.24362 focal_loss 0.15869 dice_loss 0.08493 +Epoch [2794/4000] Validation metric {'Val/mean dice_metric': 0.975037693977356, 'Val/mean miou_metric': 0.9607017636299133, 'Val/mean f1': 0.9767618179321289, 'Val/mean precision': 0.9735082387924194, 'Val/mean recall': 0.9800371527671814, 'Val/mean hd95_metric': 4.724329471588135} +Cheakpoint... +Epoch [2794/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975037693977356, 'Val/mean miou_metric': 0.9607017636299133, 'Val/mean f1': 0.9767618179321289, 'Val/mean precision': 0.9735082387924194, 'Val/mean recall': 0.9800371527671814, 'Val/mean hd95_metric': 4.724329471588135} +Epoch [2795/4000] Training [1/16] Loss: 0.00377 +Epoch [2795/4000] Training [2/16] Loss: 0.00474 +Epoch [2795/4000] Training [3/16] Loss: 0.00400 +Epoch [2795/4000] Training [4/16] Loss: 0.00332 +Epoch [2795/4000] Training [5/16] Loss: 0.00421 +Epoch [2795/4000] Training [6/16] Loss: 0.00268 +Epoch [2795/4000] Training [7/16] Loss: 0.00424 +Epoch [2795/4000] Training [8/16] Loss: 0.00348 +Epoch [2795/4000] Training [9/16] Loss: 0.00362 +Epoch [2795/4000] Training [10/16] Loss: 0.00386 +Epoch [2795/4000] Training [11/16] Loss: 0.00447 +Epoch [2795/4000] Training [12/16] Loss: 0.00294 +Epoch [2795/4000] Training [13/16] Loss: 0.00354 +Epoch [2795/4000] Training [14/16] Loss: 0.00280 +Epoch [2795/4000] Training [15/16] Loss: 0.00327 +Epoch [2795/4000] Training [16/16] Loss: 0.00413 +Epoch [2795/4000] Training metric {'Train/mean dice_metric': 0.9976579546928406, 'Train/mean miou_metric': 0.9950425624847412, 'Train/mean f1': 0.9928376078605652, 'Train/mean precision': 0.9881542921066284, 'Train/mean recall': 0.9975654482841492, 'Train/mean hd95_metric': 0.9006609916687012} +Epoch [2795/4000] Validation [1/4] Loss: 0.35545 focal_loss 0.29044 dice_loss 0.06501 +Epoch [2795/4000] Validation [2/4] Loss: 0.90462 focal_loss 0.71644 dice_loss 0.18818 +Epoch [2795/4000] Validation [3/4] Loss: 0.21796 focal_loss 0.16284 dice_loss 0.05512 +Epoch [2795/4000] Validation [4/4] Loss: 0.57894 focal_loss 0.45358 dice_loss 0.12537 +Epoch [2795/4000] Validation metric {'Val/mean dice_metric': 0.9725629687309265, 'Val/mean miou_metric': 0.9579679369926453, 'Val/mean f1': 0.9754027724266052, 'Val/mean precision': 0.9736154675483704, 'Val/mean recall': 0.9771968722343445, 'Val/mean hd95_metric': 5.021003246307373} +Cheakpoint... +Epoch [2795/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725629687309265, 'Val/mean miou_metric': 0.9579679369926453, 'Val/mean f1': 0.9754027724266052, 'Val/mean precision': 0.9736154675483704, 'Val/mean recall': 0.9771968722343445, 'Val/mean hd95_metric': 5.021003246307373} +Epoch [2796/4000] Training [1/16] Loss: 0.00425 +Epoch [2796/4000] Training [2/16] Loss: 0.00315 +Epoch [2796/4000] Training [3/16] Loss: 0.00595 +Epoch [2796/4000] Training [4/16] Loss: 0.00365 +Epoch [2796/4000] Training [5/16] Loss: 0.00344 +Epoch [2796/4000] Training [6/16] Loss: 0.00324 +Epoch [2796/4000] Training [7/16] Loss: 0.00371 +Epoch [2796/4000] Training [8/16] Loss: 0.00368 +Epoch [2796/4000] Training [9/16] Loss: 0.00337 +Epoch [2796/4000] Training [10/16] Loss: 0.00374 +Epoch [2796/4000] Training [11/16] Loss: 0.00239 +Epoch [2796/4000] Training [12/16] Loss: 0.00421 +Epoch [2796/4000] Training [13/16] Loss: 0.00350 +Epoch [2796/4000] Training [14/16] Loss: 0.00458 +Epoch [2796/4000] Training [15/16] Loss: 0.00406 +Epoch [2796/4000] Training [16/16] Loss: 0.00564 +Epoch [2796/4000] Training metric {'Train/mean dice_metric': 0.9976456761360168, 'Train/mean miou_metric': 0.9950311779975891, 'Train/mean f1': 0.9930247664451599, 'Train/mean precision': 0.9885080456733704, 'Train/mean recall': 0.9975829720497131, 'Train/mean hd95_metric': 0.8786767721176147} +Epoch [2796/4000] Validation [1/4] Loss: 0.33383 focal_loss 0.27184 dice_loss 0.06198 +Epoch [2796/4000] Validation [2/4] Loss: 0.99687 focal_loss 0.80258 dice_loss 0.19429 +Epoch [2796/4000] Validation [3/4] Loss: 0.41001 focal_loss 0.32308 dice_loss 0.08693 +Epoch [2796/4000] Validation [4/4] Loss: 0.32444 focal_loss 0.22770 dice_loss 0.09674 +Epoch [2796/4000] Validation metric {'Val/mean dice_metric': 0.9729923009872437, 'Val/mean miou_metric': 0.9586520195007324, 'Val/mean f1': 0.9756023287773132, 'Val/mean precision': 0.9722857475280762, 'Val/mean recall': 0.9789416790008545, 'Val/mean hd95_metric': 5.266870975494385} +Cheakpoint... +Epoch [2796/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729923009872437, 'Val/mean miou_metric': 0.9586520195007324, 'Val/mean f1': 0.9756023287773132, 'Val/mean precision': 0.9722857475280762, 'Val/mean recall': 0.9789416790008545, 'Val/mean hd95_metric': 5.266870975494385} +Epoch [2797/4000] Training [1/16] Loss: 0.00258 +Epoch [2797/4000] Training [2/16] Loss: 0.00317 +Epoch [2797/4000] Training [3/16] Loss: 0.00383 +Epoch [2797/4000] Training [4/16] Loss: 0.00324 +Epoch [2797/4000] Training [5/16] Loss: 0.00312 +Epoch [2797/4000] Training [6/16] Loss: 0.00429 +Epoch [2797/4000] Training [7/16] Loss: 0.00361 +Epoch [2797/4000] Training [8/16] Loss: 0.00481 +Epoch [2797/4000] Training [9/16] Loss: 0.00590 +Epoch [2797/4000] Training [10/16] Loss: 0.00322 +Epoch [2797/4000] Training [11/16] Loss: 0.00310 +Epoch [2797/4000] Training [12/16] Loss: 0.00594 +Epoch [2797/4000] Training [13/16] Loss: 0.00485 +Epoch [2797/4000] Training [14/16] Loss: 0.00442 +Epoch [2797/4000] Training [15/16] Loss: 0.00411 +Epoch [2797/4000] Training [16/16] Loss: 0.00413 +Epoch [2797/4000] Training metric {'Train/mean dice_metric': 0.9977470636367798, 'Train/mean miou_metric': 0.9952083230018616, 'Train/mean f1': 0.9924262762069702, 'Train/mean precision': 0.9874659776687622, 'Train/mean recall': 0.9974366426467896, 'Train/mean hd95_metric': 0.8999302387237549} +Epoch [2797/4000] Validation [1/4] Loss: 0.31248 focal_loss 0.25332 dice_loss 0.05915 +Epoch [2797/4000] Validation [2/4] Loss: 1.22060 focal_loss 0.96760 dice_loss 0.25300 +Epoch [2797/4000] Validation [3/4] Loss: 0.41077 focal_loss 0.31557 dice_loss 0.09520 +Epoch [2797/4000] Validation [4/4] Loss: 0.32466 focal_loss 0.21948 dice_loss 0.10519 +Epoch [2797/4000] Validation metric {'Val/mean dice_metric': 0.9716953039169312, 'Val/mean miou_metric': 0.9572828412055969, 'Val/mean f1': 0.9745963215827942, 'Val/mean precision': 0.971747100353241, 'Val/mean recall': 0.9774624109268188, 'Val/mean hd95_metric': 5.115682125091553} +Cheakpoint... +Epoch [2797/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716953039169312, 'Val/mean miou_metric': 0.9572828412055969, 'Val/mean f1': 0.9745963215827942, 'Val/mean precision': 0.971747100353241, 'Val/mean recall': 0.9774624109268188, 'Val/mean hd95_metric': 5.115682125091553} +Epoch [2798/4000] Training [1/16] Loss: 0.00537 +Epoch [2798/4000] Training [2/16] Loss: 0.00423 +Epoch [2798/4000] Training [3/16] Loss: 0.00462 +Epoch [2798/4000] Training [4/16] Loss: 0.00375 +Epoch [2798/4000] Training [5/16] Loss: 0.00372 +Epoch [2798/4000] Training [6/16] Loss: 0.00363 +Epoch [2798/4000] Training [7/16] Loss: 0.00353 +Epoch [2798/4000] Training [8/16] Loss: 0.00554 +Epoch [2798/4000] Training [9/16] Loss: 0.00390 +Epoch [2798/4000] Training [10/16] Loss: 0.00452 +Epoch [2798/4000] Training [11/16] Loss: 0.00390 +Epoch [2798/4000] Training [12/16] Loss: 0.00285 +Epoch [2798/4000] Training [13/16] Loss: 0.00430 +Epoch [2798/4000] Training [14/16] Loss: 0.00318 +Epoch [2798/4000] Training [15/16] Loss: 0.00374 +Epoch [2798/4000] Training [16/16] Loss: 0.00350 +Epoch [2798/4000] Training metric {'Train/mean dice_metric': 0.9975640773773193, 'Train/mean miou_metric': 0.9948645234107971, 'Train/mean f1': 0.9928763508796692, 'Train/mean precision': 0.9883272051811218, 'Train/mean recall': 0.9974676370620728, 'Train/mean hd95_metric': 0.9179685115814209} +Epoch [2798/4000] Validation [1/4] Loss: 0.33171 focal_loss 0.27031 dice_loss 0.06140 +Epoch [2798/4000] Validation [2/4] Loss: 0.65270 focal_loss 0.47124 dice_loss 0.18147 +Epoch [2798/4000] Validation [3/4] Loss: 0.43841 focal_loss 0.33925 dice_loss 0.09916 +Epoch [2798/4000] Validation [4/4] Loss: 0.38189 focal_loss 0.27103 dice_loss 0.11086 +Epoch [2798/4000] Validation metric {'Val/mean dice_metric': 0.972464919090271, 'Val/mean miou_metric': 0.9573241472244263, 'Val/mean f1': 0.9753612279891968, 'Val/mean precision': 0.9729474782943726, 'Val/mean recall': 0.9777868390083313, 'Val/mean hd95_metric': 5.16859769821167} +Cheakpoint... +Epoch [2798/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972464919090271, 'Val/mean miou_metric': 0.9573241472244263, 'Val/mean f1': 0.9753612279891968, 'Val/mean precision': 0.9729474782943726, 'Val/mean recall': 0.9777868390083313, 'Val/mean hd95_metric': 5.16859769821167} +Epoch [2799/4000] Training [1/16] Loss: 0.00360 +Epoch [2799/4000] Training [2/16] Loss: 0.00273 +Epoch [2799/4000] Training [3/16] Loss: 0.00425 +Epoch [2799/4000] Training [4/16] Loss: 0.00289 +Epoch [2799/4000] Training [5/16] Loss: 0.00271 +Epoch [2799/4000] Training [6/16] Loss: 0.00469 +Epoch [2799/4000] Training [7/16] Loss: 0.00450 +Epoch [2799/4000] Training [8/16] Loss: 0.00340 +Epoch [2799/4000] Training [9/16] Loss: 0.00492 +Epoch [2799/4000] Training [10/16] Loss: 0.00407 +Epoch [2799/4000] Training [11/16] Loss: 0.00385 +Epoch [2799/4000] Training [12/16] Loss: 0.00437 +Epoch [2799/4000] Training [13/16] Loss: 0.00377 +Epoch [2799/4000] Training [14/16] Loss: 0.00381 +Epoch [2799/4000] Training [15/16] Loss: 0.00347 +Epoch [2799/4000] Training [16/16] Loss: 0.00463 +Epoch [2799/4000] Training metric {'Train/mean dice_metric': 0.9976657629013062, 'Train/mean miou_metric': 0.9950642585754395, 'Train/mean f1': 0.9928328990936279, 'Train/mean precision': 0.9881773591041565, 'Train/mean recall': 0.9975325465202332, 'Train/mean hd95_metric': 0.8896760940551758} +Epoch [2799/4000] Validation [1/4] Loss: 0.32806 focal_loss 0.26407 dice_loss 0.06399 +Epoch [2799/4000] Validation [2/4] Loss: 0.36634 focal_loss 0.25913 dice_loss 0.10721 +Epoch [2799/4000] Validation [3/4] Loss: 0.25156 focal_loss 0.18910 dice_loss 0.06247 +Epoch [2799/4000] Validation [4/4] Loss: 0.46222 focal_loss 0.33465 dice_loss 0.12757 +Epoch [2799/4000] Validation metric {'Val/mean dice_metric': 0.9721317291259766, 'Val/mean miou_metric': 0.9573653936386108, 'Val/mean f1': 0.9753025770187378, 'Val/mean precision': 0.9726707339286804, 'Val/mean recall': 0.9779487252235413, 'Val/mean hd95_metric': 5.2970685958862305} +Cheakpoint... +Epoch [2799/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721317291259766, 'Val/mean miou_metric': 0.9573653936386108, 'Val/mean f1': 0.9753025770187378, 'Val/mean precision': 0.9726707339286804, 'Val/mean recall': 0.9779487252235413, 'Val/mean hd95_metric': 5.2970685958862305} +Epoch [2800/4000] Training [1/16] Loss: 0.00331 +Epoch [2800/4000] Training [2/16] Loss: 0.00297 +Epoch [2800/4000] Training [3/16] Loss: 0.00307 +Epoch [2800/4000] Training [4/16] Loss: 0.00377 +Epoch [2800/4000] Training [5/16] Loss: 0.00251 +Epoch [2800/4000] Training [6/16] Loss: 0.00286 +Epoch [2800/4000] Training [7/16] Loss: 0.00275 +Epoch [2800/4000] Training [8/16] Loss: 0.00376 +Epoch [2800/4000] Training [9/16] Loss: 0.00386 +Epoch [2800/4000] Training [10/16] Loss: 0.00329 +Epoch [2800/4000] Training [11/16] Loss: 0.00517 +Epoch [2800/4000] Training [12/16] Loss: 0.00405 +Epoch [2800/4000] Training [13/16] Loss: 0.00320 +Epoch [2800/4000] Training [14/16] Loss: 0.00383 +Epoch [2800/4000] Training [15/16] Loss: 0.00381 +Epoch [2800/4000] Training [16/16] Loss: 0.00400 +Epoch [2800/4000] Training metric {'Train/mean dice_metric': 0.9979398250579834, 'Train/mean miou_metric': 0.9956167936325073, 'Train/mean f1': 0.9932103157043457, 'Train/mean precision': 0.9887678623199463, 'Train/mean recall': 0.997692883014679, 'Train/mean hd95_metric': 0.8763947486877441} +Epoch [2800/4000] Validation [1/4] Loss: 0.29548 focal_loss 0.23664 dice_loss 0.05884 +Epoch [2800/4000] Validation [2/4] Loss: 0.48055 focal_loss 0.29626 dice_loss 0.18428 +Epoch [2800/4000] Validation [3/4] Loss: 0.38575 focal_loss 0.29856 dice_loss 0.08719 +Epoch [2800/4000] Validation [4/4] Loss: 0.43013 focal_loss 0.30850 dice_loss 0.12163 +Epoch [2800/4000] Validation metric {'Val/mean dice_metric': 0.9725269079208374, 'Val/mean miou_metric': 0.9575885534286499, 'Val/mean f1': 0.9754834175109863, 'Val/mean precision': 0.9733756184577942, 'Val/mean recall': 0.9776002764701843, 'Val/mean hd95_metric': 5.027341365814209} +Cheakpoint... +Epoch [2800/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725269079208374, 'Val/mean miou_metric': 0.9575885534286499, 'Val/mean f1': 0.9754834175109863, 'Val/mean precision': 0.9733756184577942, 'Val/mean recall': 0.9776002764701843, 'Val/mean hd95_metric': 5.027341365814209} +Epoch [2801/4000] Training [1/16] Loss: 0.00323 +Epoch [2801/4000] Training [2/16] Loss: 0.00347 +Epoch [2801/4000] Training [3/16] Loss: 0.00337 +Epoch [2801/4000] Training [4/16] Loss: 0.00458 +Epoch [2801/4000] Training [5/16] Loss: 0.00315 +Epoch [2801/4000] Training [6/16] Loss: 0.00463 +Epoch [2801/4000] Training [7/16] Loss: 0.00342 +Epoch [2801/4000] Training [8/16] Loss: 0.00446 +Epoch [2801/4000] Training [9/16] Loss: 0.00367 +Epoch [2801/4000] Training [10/16] Loss: 0.00405 +Epoch [2801/4000] Training [11/16] Loss: 0.00427 +Epoch [2801/4000] Training [12/16] Loss: 0.00333 +Epoch [2801/4000] Training [13/16] Loss: 0.00432 +Epoch [2801/4000] Training [14/16] Loss: 0.00295 +Epoch [2801/4000] Training [15/16] Loss: 0.00399 +Epoch [2801/4000] Training [16/16] Loss: 0.00361 +Epoch [2801/4000] Training metric {'Train/mean dice_metric': 0.9978590607643127, 'Train/mean miou_metric': 0.9954360723495483, 'Train/mean f1': 0.9928224086761475, 'Train/mean precision': 0.988093912601471, 'Train/mean recall': 0.9975964426994324, 'Train/mean hd95_metric': 0.8755438327789307} +Epoch [2801/4000] Validation [1/4] Loss: 0.35165 focal_loss 0.28673 dice_loss 0.06492 +Epoch [2801/4000] Validation [2/4] Loss: 0.36210 focal_loss 0.25473 dice_loss 0.10736 +Epoch [2801/4000] Validation [3/4] Loss: 0.37629 focal_loss 0.28800 dice_loss 0.08828 +Epoch [2801/4000] Validation [4/4] Loss: 0.26061 focal_loss 0.18031 dice_loss 0.08030 +Epoch [2801/4000] Validation metric {'Val/mean dice_metric': 0.974700927734375, 'Val/mean miou_metric': 0.960030198097229, 'Val/mean f1': 0.9759868383407593, 'Val/mean precision': 0.9726622104644775, 'Val/mean recall': 0.97933429479599, 'Val/mean hd95_metric': 5.1622490882873535} +Cheakpoint... +Epoch [2801/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974700927734375, 'Val/mean miou_metric': 0.960030198097229, 'Val/mean f1': 0.9759868383407593, 'Val/mean precision': 0.9726622104644775, 'Val/mean recall': 0.97933429479599, 'Val/mean hd95_metric': 5.1622490882873535} +Epoch [2802/4000] Training [1/16] Loss: 0.00343 +Epoch [2802/4000] Training [2/16] Loss: 0.00223 +Epoch [2802/4000] Training [3/16] Loss: 0.00739 +Epoch [2802/4000] Training [4/16] Loss: 0.00343 +Epoch [2802/4000] Training [5/16] Loss: 0.00320 +Epoch [2802/4000] Training [6/16] Loss: 0.00404 +Epoch [2802/4000] Training [7/16] Loss: 0.00438 +Epoch [2802/4000] Training [8/16] Loss: 0.00376 +Epoch [2802/4000] Training [9/16] Loss: 0.00288 +Epoch [2802/4000] Training [10/16] Loss: 0.00439 +Epoch [2802/4000] Training [11/16] Loss: 0.00437 +Epoch [2802/4000] Training [12/16] Loss: 0.00335 +Epoch [2802/4000] Training [13/16] Loss: 0.00386 +Epoch [2802/4000] Training [14/16] Loss: 0.00295 +Epoch [2802/4000] Training [15/16] Loss: 0.00396 +Epoch [2802/4000] Training [16/16] Loss: 0.00389 +Epoch [2802/4000] Training metric {'Train/mean dice_metric': 0.9977285265922546, 'Train/mean miou_metric': 0.9951968193054199, 'Train/mean f1': 0.9930552244186401, 'Train/mean precision': 0.9885692596435547, 'Train/mean recall': 0.9975821375846863, 'Train/mean hd95_metric': 0.8618441820144653} +Epoch [2802/4000] Validation [1/4] Loss: 0.32424 focal_loss 0.26345 dice_loss 0.06079 +Epoch [2802/4000] Validation [2/4] Loss: 0.35599 focal_loss 0.25435 dice_loss 0.10163 +Epoch [2802/4000] Validation [3/4] Loss: 0.45690 focal_loss 0.36451 dice_loss 0.09239 +Epoch [2802/4000] Validation [4/4] Loss: 0.23459 focal_loss 0.15294 dice_loss 0.08165 +Epoch [2802/4000] Validation metric {'Val/mean dice_metric': 0.9747648239135742, 'Val/mean miou_metric': 0.9604116678237915, 'Val/mean f1': 0.9767231345176697, 'Val/mean precision': 0.9736084938049316, 'Val/mean recall': 0.9798577427864075, 'Val/mean hd95_metric': 4.8474321365356445} +Cheakpoint... +Epoch [2802/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747648239135742, 'Val/mean miou_metric': 0.9604116678237915, 'Val/mean f1': 0.9767231345176697, 'Val/mean precision': 0.9736084938049316, 'Val/mean recall': 0.9798577427864075, 'Val/mean hd95_metric': 4.8474321365356445} +Epoch [2803/4000] Training [1/16] Loss: 0.00324 +Epoch [2803/4000] Training [2/16] Loss: 0.00247 +Epoch [2803/4000] Training [3/16] Loss: 0.00310 +Epoch [2803/4000] Training [4/16] Loss: 0.00340 +Epoch [2803/4000] Training [5/16] Loss: 0.00314 +Epoch [2803/4000] Training [6/16] Loss: 0.00461 +Epoch [2803/4000] Training [7/16] Loss: 0.00401 +Epoch [2803/4000] Training [8/16] Loss: 0.00286 +Epoch [2803/4000] Training [9/16] Loss: 0.00263 +Epoch [2803/4000] Training [10/16] Loss: 0.00298 +Epoch [2803/4000] Training [11/16] Loss: 0.00327 +Epoch [2803/4000] Training [12/16] Loss: 0.00316 +Epoch [2803/4000] Training [13/16] Loss: 0.00330 +Epoch [2803/4000] Training [14/16] Loss: 0.00418 +Epoch [2803/4000] Training [15/16] Loss: 0.00367 +Epoch [2803/4000] Training [16/16] Loss: 0.00431 +Epoch [2803/4000] Training metric {'Train/mean dice_metric': 0.9978455305099487, 'Train/mean miou_metric': 0.9954274892807007, 'Train/mean f1': 0.9930564761161804, 'Train/mean precision': 0.9885109663009644, 'Train/mean recall': 0.9976440072059631, 'Train/mean hd95_metric': 0.8619707226753235} +Epoch [2803/4000] Validation [1/4] Loss: 0.36458 focal_loss 0.30063 dice_loss 0.06395 +Epoch [2803/4000] Validation [2/4] Loss: 0.85600 focal_loss 0.66196 dice_loss 0.19404 +Epoch [2803/4000] Validation [3/4] Loss: 0.40926 focal_loss 0.31379 dice_loss 0.09546 +Epoch [2803/4000] Validation [4/4] Loss: 0.34899 focal_loss 0.24068 dice_loss 0.10830 +Epoch [2803/4000] Validation metric {'Val/mean dice_metric': 0.9744337201118469, 'Val/mean miou_metric': 0.9600604176521301, 'Val/mean f1': 0.9756872057914734, 'Val/mean precision': 0.9721437692642212, 'Val/mean recall': 0.9792566299438477, 'Val/mean hd95_metric': 5.583222389221191} +Cheakpoint... +Epoch [2803/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744337201118469, 'Val/mean miou_metric': 0.9600604176521301, 'Val/mean f1': 0.9756872057914734, 'Val/mean precision': 0.9721437692642212, 'Val/mean recall': 0.9792566299438477, 'Val/mean hd95_metric': 5.583222389221191} +Epoch [2804/4000] Training [1/16] Loss: 0.00343 +Epoch [2804/4000] Training [2/16] Loss: 0.00334 +Epoch [2804/4000] Training [3/16] Loss: 0.00412 +Epoch [2804/4000] Training [4/16] Loss: 0.00345 +Epoch [2804/4000] Training [5/16] Loss: 0.00435 +Epoch [2804/4000] Training [6/16] Loss: 0.00317 +Epoch [2804/4000] Training [7/16] Loss: 0.00324 +Epoch [2804/4000] Training [8/16] Loss: 0.00359 +Epoch [2804/4000] Training [9/16] Loss: 0.00372 +Epoch [2804/4000] Training [10/16] Loss: 0.00386 +Epoch [2804/4000] Training [11/16] Loss: 0.00352 +Epoch [2804/4000] Training [12/16] Loss: 0.00486 +Epoch [2804/4000] Training [13/16] Loss: 0.00418 +Epoch [2804/4000] Training [14/16] Loss: 0.00291 +Epoch [2804/4000] Training [15/16] Loss: 0.00381 +Epoch [2804/4000] Training [16/16] Loss: 0.00449 +Epoch [2804/4000] Training metric {'Train/mean dice_metric': 0.9977409839630127, 'Train/mean miou_metric': 0.9952211380004883, 'Train/mean f1': 0.9930354356765747, 'Train/mean precision': 0.9884824752807617, 'Train/mean recall': 0.9976305961608887, 'Train/mean hd95_metric': 0.8985207080841064} +Epoch [2804/4000] Validation [1/4] Loss: 0.31755 focal_loss 0.26011 dice_loss 0.05744 +Epoch [2804/4000] Validation [2/4] Loss: 0.84062 focal_loss 0.65710 dice_loss 0.18352 +Epoch [2804/4000] Validation [3/4] Loss: 0.42756 focal_loss 0.33814 dice_loss 0.08942 +Epoch [2804/4000] Validation [4/4] Loss: 0.31748 focal_loss 0.21369 dice_loss 0.10379 +Epoch [2804/4000] Validation metric {'Val/mean dice_metric': 0.9729215502738953, 'Val/mean miou_metric': 0.958203911781311, 'Val/mean f1': 0.9756513833999634, 'Val/mean precision': 0.9724587202072144, 'Val/mean recall': 0.9788649678230286, 'Val/mean hd95_metric': 5.11087703704834} +Cheakpoint... +Epoch [2804/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729215502738953, 'Val/mean miou_metric': 0.958203911781311, 'Val/mean f1': 0.9756513833999634, 'Val/mean precision': 0.9724587202072144, 'Val/mean recall': 0.9788649678230286, 'Val/mean hd95_metric': 5.11087703704834} +Epoch [2805/4000] Training [1/16] Loss: 0.00375 +Epoch [2805/4000] Training [2/16] Loss: 0.00441 +Epoch [2805/4000] Training [3/16] Loss: 0.00389 +Epoch [2805/4000] Training [4/16] Loss: 0.00428 +Epoch [2805/4000] Training [5/16] Loss: 0.00446 +Epoch [2805/4000] Training [6/16] Loss: 0.00413 +Epoch [2805/4000] Training [7/16] Loss: 0.00336 +Epoch [2805/4000] Training [8/16] Loss: 0.00542 +Epoch [2805/4000] Training [9/16] Loss: 0.00324 +Epoch [2805/4000] Training [10/16] Loss: 0.00318 +Epoch [2805/4000] Training [11/16] Loss: 0.00433 +Epoch [2805/4000] Training [12/16] Loss: 0.00352 +Epoch [2805/4000] Training [13/16] Loss: 0.00400 +Epoch [2805/4000] Training [14/16] Loss: 0.00248 +Epoch [2805/4000] Training [15/16] Loss: 0.00343 +Epoch [2805/4000] Training [16/16] Loss: 0.00376 +Epoch [2805/4000] Training metric {'Train/mean dice_metric': 0.9977108240127563, 'Train/mean miou_metric': 0.9951620101928711, 'Train/mean f1': 0.9930698871612549, 'Train/mean precision': 0.9885507225990295, 'Train/mean recall': 0.9976306557655334, 'Train/mean hd95_metric': 0.889313280582428} +Epoch [2805/4000] Validation [1/4] Loss: 0.30696 focal_loss 0.24875 dice_loss 0.05821 +Epoch [2805/4000] Validation [2/4] Loss: 0.33466 focal_loss 0.23853 dice_loss 0.09613 +Epoch [2805/4000] Validation [3/4] Loss: 0.22517 focal_loss 0.16681 dice_loss 0.05836 +Epoch [2805/4000] Validation [4/4] Loss: 0.34421 focal_loss 0.22904 dice_loss 0.11517 +Epoch [2805/4000] Validation metric {'Val/mean dice_metric': 0.9743238687515259, 'Val/mean miou_metric': 0.9594934582710266, 'Val/mean f1': 0.9764572381973267, 'Val/mean precision': 0.9733486175537109, 'Val/mean recall': 0.9795858263969421, 'Val/mean hd95_metric': 5.003281593322754} +Cheakpoint... +Epoch [2805/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743238687515259, 'Val/mean miou_metric': 0.9594934582710266, 'Val/mean f1': 0.9764572381973267, 'Val/mean precision': 0.9733486175537109, 'Val/mean recall': 0.9795858263969421, 'Val/mean hd95_metric': 5.003281593322754} +Epoch [2806/4000] Training [1/16] Loss: 0.00399 +Epoch [2806/4000] Training [2/16] Loss: 0.00409 +Epoch [2806/4000] Training [3/16] Loss: 0.00396 +Epoch [2806/4000] Training [4/16] Loss: 0.00346 +Epoch [2806/4000] Training [5/16] Loss: 0.01346 +Epoch [2806/4000] Training [6/16] Loss: 0.00272 +Epoch [2806/4000] Training [7/16] Loss: 0.00298 +Epoch [2806/4000] Training [8/16] Loss: 0.00280 +Epoch [2806/4000] Training [9/16] Loss: 0.00353 +Epoch [2806/4000] Training [10/16] Loss: 0.00438 +Epoch [2806/4000] Training [11/16] Loss: 0.00275 +Epoch [2806/4000] Training [12/16] Loss: 0.00299 +Epoch [2806/4000] Training [13/16] Loss: 0.00382 +Epoch [2806/4000] Training [14/16] Loss: 0.00306 +Epoch [2806/4000] Training [15/16] Loss: 0.00306 +Epoch [2806/4000] Training [16/16] Loss: 0.00347 +Epoch [2806/4000] Training metric {'Train/mean dice_metric': 0.9976996183395386, 'Train/mean miou_metric': 0.9951493740081787, 'Train/mean f1': 0.993098258972168, 'Train/mean precision': 0.9885600805282593, 'Train/mean recall': 0.997678279876709, 'Train/mean hd95_metric': 0.9078648090362549} +Epoch [2806/4000] Validation [1/4] Loss: 0.33852 focal_loss 0.27654 dice_loss 0.06198 +Epoch [2806/4000] Validation [2/4] Loss: 0.40027 focal_loss 0.28361 dice_loss 0.11666 +Epoch [2806/4000] Validation [3/4] Loss: 0.38555 focal_loss 0.29434 dice_loss 0.09122 +Epoch [2806/4000] Validation [4/4] Loss: 0.48494 focal_loss 0.35967 dice_loss 0.12528 +Epoch [2806/4000] Validation metric {'Val/mean dice_metric': 0.9733991622924805, 'Val/mean miou_metric': 0.9580642580986023, 'Val/mean f1': 0.9750993847846985, 'Val/mean precision': 0.9731390476226807, 'Val/mean recall': 0.9770677089691162, 'Val/mean hd95_metric': 5.279182434082031} +Cheakpoint... +Epoch [2806/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733991622924805, 'Val/mean miou_metric': 0.9580642580986023, 'Val/mean f1': 0.9750993847846985, 'Val/mean precision': 0.9731390476226807, 'Val/mean recall': 0.9770677089691162, 'Val/mean hd95_metric': 5.279182434082031} +Epoch [2807/4000] Training [1/16] Loss: 0.00370 +Epoch [2807/4000] Training [2/16] Loss: 0.00455 +Epoch [2807/4000] Training [3/16] Loss: 0.00347 +Epoch [2807/4000] Training [4/16] Loss: 0.00336 +Epoch [2807/4000] Training [5/16] Loss: 0.00381 +Epoch [2807/4000] Training [6/16] Loss: 0.00346 +Epoch [2807/4000] Training [7/16] Loss: 0.00333 +Epoch [2807/4000] Training [8/16] Loss: 0.00382 +Epoch [2807/4000] Training [9/16] Loss: 0.00461 +Epoch [2807/4000] Training [10/16] Loss: 0.00399 +Epoch [2807/4000] Training [11/16] Loss: 0.00439 +Epoch [2807/4000] Training [12/16] Loss: 0.00343 +Epoch [2807/4000] Training [13/16] Loss: 0.00427 +Epoch [2807/4000] Training [14/16] Loss: 0.00281 +Epoch [2807/4000] Training [15/16] Loss: 0.00286 +Epoch [2807/4000] Training [16/16] Loss: 0.00358 +Epoch [2807/4000] Training metric {'Train/mean dice_metric': 0.9976347088813782, 'Train/mean miou_metric': 0.9950087666511536, 'Train/mean f1': 0.9929708242416382, 'Train/mean precision': 0.9883948564529419, 'Train/mean recall': 0.9975893497467041, 'Train/mean hd95_metric': 0.898084282875061} +Epoch [2807/4000] Validation [1/4] Loss: 0.33913 focal_loss 0.27734 dice_loss 0.06179 +Epoch [2807/4000] Validation [2/4] Loss: 0.69727 focal_loss 0.50963 dice_loss 0.18764 +Epoch [2807/4000] Validation [3/4] Loss: 0.19641 focal_loss 0.14784 dice_loss 0.04857 +Epoch [2807/4000] Validation [4/4] Loss: 0.35713 focal_loss 0.24758 dice_loss 0.10955 +Epoch [2807/4000] Validation metric {'Val/mean dice_metric': 0.9735192060470581, 'Val/mean miou_metric': 0.9588119387626648, 'Val/mean f1': 0.9759256839752197, 'Val/mean precision': 0.9731971621513367, 'Val/mean recall': 0.9786696434020996, 'Val/mean hd95_metric': 5.081260681152344} +Cheakpoint... +Epoch [2807/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735192060470581, 'Val/mean miou_metric': 0.9588119387626648, 'Val/mean f1': 0.9759256839752197, 'Val/mean precision': 0.9731971621513367, 'Val/mean recall': 0.9786696434020996, 'Val/mean hd95_metric': 5.081260681152344} +Epoch [2808/4000] Training [1/16] Loss: 0.00340 +Epoch [2808/4000] Training [2/16] Loss: 0.00382 +Epoch [2808/4000] Training [3/16] Loss: 0.00405 +Epoch [2808/4000] Training [4/16] Loss: 0.00355 +Epoch [2808/4000] Training [5/16] Loss: 0.00318 +Epoch [2808/4000] Training [6/16] Loss: 0.00331 +Epoch [2808/4000] Training [7/16] Loss: 0.00307 +Epoch [2808/4000] Training [8/16] Loss: 0.00326 +Epoch [2808/4000] Training [9/16] Loss: 0.00390 +Epoch [2808/4000] Training [10/16] Loss: 0.00403 +Epoch [2808/4000] Training [11/16] Loss: 0.00353 +Epoch [2808/4000] Training [12/16] Loss: 0.00655 +Epoch [2808/4000] Training [13/16] Loss: 0.00277 +Epoch [2808/4000] Training [14/16] Loss: 0.00324 +Epoch [2808/4000] Training [15/16] Loss: 0.00331 +Epoch [2808/4000] Training [16/16] Loss: 0.00273 +Epoch [2808/4000] Training metric {'Train/mean dice_metric': 0.9978187084197998, 'Train/mean miou_metric': 0.9953476190567017, 'Train/mean f1': 0.9927448034286499, 'Train/mean precision': 0.9879593849182129, 'Train/mean recall': 0.9975767731666565, 'Train/mean hd95_metric': 0.86496901512146} +Epoch [2808/4000] Validation [1/4] Loss: 0.35516 focal_loss 0.29180 dice_loss 0.06336 +Epoch [2808/4000] Validation [2/4] Loss: 0.35789 focal_loss 0.25287 dice_loss 0.10502 +Epoch [2808/4000] Validation [3/4] Loss: 0.40721 focal_loss 0.32113 dice_loss 0.08607 +Epoch [2808/4000] Validation [4/4] Loss: 0.33228 focal_loss 0.23060 dice_loss 0.10168 +Epoch [2808/4000] Validation metric {'Val/mean dice_metric': 0.9743757247924805, 'Val/mean miou_metric': 0.9596306085586548, 'Val/mean f1': 0.9759538173675537, 'Val/mean precision': 0.9728224277496338, 'Val/mean recall': 0.9791054129600525, 'Val/mean hd95_metric': 5.141909599304199} +Cheakpoint... +Epoch [2808/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743757247924805, 'Val/mean miou_metric': 0.9596306085586548, 'Val/mean f1': 0.9759538173675537, 'Val/mean precision': 0.9728224277496338, 'Val/mean recall': 0.9791054129600525, 'Val/mean hd95_metric': 5.141909599304199} +Epoch [2809/4000] Training [1/16] Loss: 0.00407 +Epoch [2809/4000] Training [2/16] Loss: 0.00484 +Epoch [2809/4000] Training [3/16] Loss: 0.00373 +Epoch [2809/4000] Training [4/16] Loss: 0.00290 +Epoch [2809/4000] Training [5/16] Loss: 0.00423 +Epoch [2809/4000] Training [6/16] Loss: 0.00331 +Epoch [2809/4000] Training [7/16] Loss: 0.00283 +Epoch [2809/4000] Training [8/16] Loss: 0.00383 +Epoch [2809/4000] Training [9/16] Loss: 0.00371 +Epoch [2809/4000] Training [10/16] Loss: 0.00330 +Epoch [2809/4000] Training [11/16] Loss: 0.00338 +Epoch [2809/4000] Training [12/16] Loss: 0.00357 +Epoch [2809/4000] Training [13/16] Loss: 0.00343 +Epoch [2809/4000] Training [14/16] Loss: 0.00335 +Epoch [2809/4000] Training [15/16] Loss: 0.00499 +Epoch [2809/4000] Training [16/16] Loss: 0.00319 +Epoch [2809/4000] Training metric {'Train/mean dice_metric': 0.9978991746902466, 'Train/mean miou_metric': 0.9955130219459534, 'Train/mean f1': 0.9929161071777344, 'Train/mean precision': 0.9881746172904968, 'Train/mean recall': 0.9977033734321594, 'Train/mean hd95_metric': 0.8720003366470337} +Epoch [2809/4000] Validation [1/4] Loss: 0.31852 focal_loss 0.26019 dice_loss 0.05833 +Epoch [2809/4000] Validation [2/4] Loss: 0.38590 focal_loss 0.27660 dice_loss 0.10931 +Epoch [2809/4000] Validation [3/4] Loss: 0.42688 focal_loss 0.33514 dice_loss 0.09174 +Epoch [2809/4000] Validation [4/4] Loss: 0.31694 focal_loss 0.21891 dice_loss 0.09802 +Epoch [2809/4000] Validation metric {'Val/mean dice_metric': 0.9745984077453613, 'Val/mean miou_metric': 0.9602119326591492, 'Val/mean f1': 0.9763520956039429, 'Val/mean precision': 0.9732664823532104, 'Val/mean recall': 0.9794571995735168, 'Val/mean hd95_metric': 5.001669406890869} +Cheakpoint... +Epoch [2809/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745984077453613, 'Val/mean miou_metric': 0.9602119326591492, 'Val/mean f1': 0.9763520956039429, 'Val/mean precision': 0.9732664823532104, 'Val/mean recall': 0.9794571995735168, 'Val/mean hd95_metric': 5.001669406890869} +Epoch [2810/4000] Training [1/16] Loss: 0.00406 +Epoch [2810/4000] Training [2/16] Loss: 0.00437 +Epoch [2810/4000] Training [3/16] Loss: 0.00360 +Epoch [2810/4000] Training [4/16] Loss: 0.00315 +Epoch [2810/4000] Training [5/16] Loss: 0.00419 +Epoch [2810/4000] Training [6/16] Loss: 0.00426 +Epoch [2810/4000] Training [7/16] Loss: 0.00453 +Epoch [2810/4000] Training [8/16] Loss: 0.00320 +Epoch [2810/4000] Training [9/16] Loss: 0.00320 +Epoch [2810/4000] Training [10/16] Loss: 0.00370 +Epoch [2810/4000] Training [11/16] Loss: 0.00257 +Epoch [2810/4000] Training [12/16] Loss: 0.00366 +Epoch [2810/4000] Training [13/16] Loss: 0.00312 +Epoch [2810/4000] Training [14/16] Loss: 0.00346 +Epoch [2810/4000] Training [15/16] Loss: 0.00283 +Epoch [2810/4000] Training [16/16] Loss: 0.00304 +Epoch [2810/4000] Training metric {'Train/mean dice_metric': 0.9978733658790588, 'Train/mean miou_metric': 0.9954502582550049, 'Train/mean f1': 0.9924951791763306, 'Train/mean precision': 0.9874190092086792, 'Train/mean recall': 0.9976239204406738, 'Train/mean hd95_metric': 0.856765866279602} +Epoch [2810/4000] Validation [1/4] Loss: 0.34128 focal_loss 0.27779 dice_loss 0.06349 +Epoch [2810/4000] Validation [2/4] Loss: 0.42761 focal_loss 0.31084 dice_loss 0.11677 +Epoch [2810/4000] Validation [3/4] Loss: 0.41274 focal_loss 0.32545 dice_loss 0.08729 +Epoch [2810/4000] Validation [4/4] Loss: 0.35632 focal_loss 0.23514 dice_loss 0.12118 +Epoch [2810/4000] Validation metric {'Val/mean dice_metric': 0.9761195182800293, 'Val/mean miou_metric': 0.9607806205749512, 'Val/mean f1': 0.975749135017395, 'Val/mean precision': 0.973035454750061, 'Val/mean recall': 0.978477954864502, 'Val/mean hd95_metric': 4.941030025482178} +Cheakpoint... +Epoch [2810/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9761], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9761195182800293, 'Val/mean miou_metric': 0.9607806205749512, 'Val/mean f1': 0.975749135017395, 'Val/mean precision': 0.973035454750061, 'Val/mean recall': 0.978477954864502, 'Val/mean hd95_metric': 4.941030025482178} +Epoch [2811/4000] Training [1/16] Loss: 0.00608 +Epoch [2811/4000] Training [2/16] Loss: 0.00336 +Epoch [2811/4000] Training [3/16] Loss: 0.00460 +Epoch [2811/4000] Training [4/16] Loss: 0.00341 +Epoch [2811/4000] Training [5/16] Loss: 0.00227 +Epoch [2811/4000] Training [6/16] Loss: 0.00361 +Epoch [2811/4000] Training [7/16] Loss: 0.00359 +Epoch [2811/4000] Training [8/16] Loss: 0.00394 +Epoch [2811/4000] Training [9/16] Loss: 0.00329 +Epoch [2811/4000] Training [10/16] Loss: 0.00420 +Epoch [2811/4000] Training [11/16] Loss: 0.00355 +Epoch [2811/4000] Training [12/16] Loss: 0.00330 +Epoch [2811/4000] Training [13/16] Loss: 0.00381 +Epoch [2811/4000] Training [14/16] Loss: 0.00409 +Epoch [2811/4000] Training [15/16] Loss: 0.00311 +Epoch [2811/4000] Training [16/16] Loss: 0.00292 +Epoch [2811/4000] Training metric {'Train/mean dice_metric': 0.9978204965591431, 'Train/mean miou_metric': 0.9953827857971191, 'Train/mean f1': 0.9931711554527283, 'Train/mean precision': 0.9886560440063477, 'Train/mean recall': 0.9977276921272278, 'Train/mean hd95_metric': 0.8726104497909546} +Epoch [2811/4000] Validation [1/4] Loss: 0.32909 focal_loss 0.26606 dice_loss 0.06303 +Epoch [2811/4000] Validation [2/4] Loss: 0.39677 focal_loss 0.27830 dice_loss 0.11847 +Epoch [2811/4000] Validation [3/4] Loss: 0.40444 focal_loss 0.31476 dice_loss 0.08968 +Epoch [2811/4000] Validation [4/4] Loss: 0.35176 focal_loss 0.24194 dice_loss 0.10981 +Epoch [2811/4000] Validation metric {'Val/mean dice_metric': 0.9731948971748352, 'Val/mean miou_metric': 0.9585021734237671, 'Val/mean f1': 0.9758838415145874, 'Val/mean precision': 0.9732781648635864, 'Val/mean recall': 0.9785035252571106, 'Val/mean hd95_metric': 5.197367191314697} +Cheakpoint... +Epoch [2811/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731948971748352, 'Val/mean miou_metric': 0.9585021734237671, 'Val/mean f1': 0.9758838415145874, 'Val/mean precision': 0.9732781648635864, 'Val/mean recall': 0.9785035252571106, 'Val/mean hd95_metric': 5.197367191314697} +Epoch [2812/4000] Training [1/16] Loss: 0.00392 +Epoch [2812/4000] Training [2/16] Loss: 0.00455 +Epoch [2812/4000] Training [3/16] Loss: 0.00382 +Epoch [2812/4000] Training [4/16] Loss: 0.00318 +Epoch [2812/4000] Training [5/16] Loss: 0.00267 +Epoch [2812/4000] Training [6/16] Loss: 0.00270 +Epoch [2812/4000] Training [7/16] Loss: 0.00329 +Epoch [2812/4000] Training [8/16] Loss: 0.00475 +Epoch [2812/4000] Training [9/16] Loss: 0.00416 +Epoch [2812/4000] Training [10/16] Loss: 0.00360 +Epoch [2812/4000] Training [11/16] Loss: 0.00317 +Epoch [2812/4000] Training [12/16] Loss: 0.00391 +Epoch [2812/4000] Training [13/16] Loss: 0.00331 +Epoch [2812/4000] Training [14/16] Loss: 0.00533 +Epoch [2812/4000] Training [15/16] Loss: 0.00352 +Epoch [2812/4000] Training [16/16] Loss: 0.00373 +Epoch [2812/4000] Training metric {'Train/mean dice_metric': 0.997844934463501, 'Train/mean miou_metric': 0.9953975677490234, 'Train/mean f1': 0.9925006031990051, 'Train/mean precision': 0.9874411821365356, 'Train/mean recall': 0.9976121783256531, 'Train/mean hd95_metric': 0.8575193881988525} +Epoch [2812/4000] Validation [1/4] Loss: 0.32450 focal_loss 0.26205 dice_loss 0.06245 +Epoch [2812/4000] Validation [2/4] Loss: 0.39769 focal_loss 0.28300 dice_loss 0.11469 +Epoch [2812/4000] Validation [3/4] Loss: 0.49175 focal_loss 0.39006 dice_loss 0.10169 +Epoch [2812/4000] Validation [4/4] Loss: 0.40743 focal_loss 0.29925 dice_loss 0.10819 +Epoch [2812/4000] Validation metric {'Val/mean dice_metric': 0.9750105142593384, 'Val/mean miou_metric': 0.9599960446357727, 'Val/mean f1': 0.975384533405304, 'Val/mean precision': 0.9722426533699036, 'Val/mean recall': 0.9785469174385071, 'Val/mean hd95_metric': 4.884062767028809} +Cheakpoint... +Epoch [2812/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750105142593384, 'Val/mean miou_metric': 0.9599960446357727, 'Val/mean f1': 0.975384533405304, 'Val/mean precision': 0.9722426533699036, 'Val/mean recall': 0.9785469174385071, 'Val/mean hd95_metric': 4.884062767028809} +Epoch [2813/4000] Training [1/16] Loss: 0.00432 +Epoch [2813/4000] Training [2/16] Loss: 0.00359 +Epoch [2813/4000] Training [3/16] Loss: 0.00406 +Epoch [2813/4000] Training [4/16] Loss: 0.00455 +Epoch [2813/4000] Training [5/16] Loss: 0.00500 +Epoch [2813/4000] Training [6/16] Loss: 0.00367 +Epoch [2813/4000] Training [7/16] Loss: 0.00389 +Epoch [2813/4000] Training [8/16] Loss: 0.00293 +Epoch [2813/4000] Training [9/16] Loss: 0.00297 +Epoch [2813/4000] Training [10/16] Loss: 0.00416 +Epoch [2813/4000] Training [11/16] Loss: 0.00411 +Epoch [2813/4000] Training [12/16] Loss: 0.00240 +Epoch [2813/4000] Training [13/16] Loss: 0.00298 +Epoch [2813/4000] Training [14/16] Loss: 0.00338 +Epoch [2813/4000] Training [15/16] Loss: 0.00401 +Epoch [2813/4000] Training [16/16] Loss: 0.00366 +Epoch [2813/4000] Training metric {'Train/mean dice_metric': 0.9977057576179504, 'Train/mean miou_metric': 0.9951397180557251, 'Train/mean f1': 0.9926910400390625, 'Train/mean precision': 0.9878987073898315, 'Train/mean recall': 0.9975300431251526, 'Train/mean hd95_metric': 0.890094518661499} +Epoch [2813/4000] Validation [1/4] Loss: 0.30581 focal_loss 0.24556 dice_loss 0.06024 +Epoch [2813/4000] Validation [2/4] Loss: 0.38742 focal_loss 0.27681 dice_loss 0.11060 +Epoch [2813/4000] Validation [3/4] Loss: 0.41131 focal_loss 0.32175 dice_loss 0.08956 +Epoch [2813/4000] Validation [4/4] Loss: 0.50844 focal_loss 0.37791 dice_loss 0.13053 +Epoch [2813/4000] Validation metric {'Val/mean dice_metric': 0.9733721613883972, 'Val/mean miou_metric': 0.9582653045654297, 'Val/mean f1': 0.9748984575271606, 'Val/mean precision': 0.9724839329719543, 'Val/mean recall': 0.9773250222206116, 'Val/mean hd95_metric': 4.734914779663086} +Cheakpoint... +Epoch [2813/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733721613883972, 'Val/mean miou_metric': 0.9582653045654297, 'Val/mean f1': 0.9748984575271606, 'Val/mean precision': 0.9724839329719543, 'Val/mean recall': 0.9773250222206116, 'Val/mean hd95_metric': 4.734914779663086} +Epoch [2814/4000] Training [1/16] Loss: 0.00300 +Epoch [2814/4000] Training [2/16] Loss: 0.00547 +Epoch [2814/4000] Training [3/16] Loss: 0.00393 +Epoch [2814/4000] Training [4/16] Loss: 0.00339 +Epoch [2814/4000] Training [5/16] Loss: 0.00359 +Epoch [2814/4000] Training [6/16] Loss: 0.00303 +Epoch [2814/4000] Training [7/16] Loss: 0.00398 +Epoch [2814/4000] Training [8/16] Loss: 0.00237 +Epoch [2814/4000] Training [9/16] Loss: 0.00413 +Epoch [2814/4000] Training [10/16] Loss: 0.00315 +Epoch [2814/4000] Training [11/16] Loss: 0.00429 +Epoch [2814/4000] Training [12/16] Loss: 0.00379 +Epoch [2814/4000] Training [13/16] Loss: 0.00390 +Epoch [2814/4000] Training [14/16] Loss: 0.00418 +Epoch [2814/4000] Training [15/16] Loss: 0.00379 +Epoch [2814/4000] Training [16/16] Loss: 0.00278 +Epoch [2814/4000] Training metric {'Train/mean dice_metric': 0.9978395700454712, 'Train/mean miou_metric': 0.9954180121421814, 'Train/mean f1': 0.9929721355438232, 'Train/mean precision': 0.9884369373321533, 'Train/mean recall': 0.9975492358207703, 'Train/mean hd95_metric': 0.8609006404876709} +Epoch [2814/4000] Validation [1/4] Loss: 0.34054 focal_loss 0.27742 dice_loss 0.06312 +Epoch [2814/4000] Validation [2/4] Loss: 0.37545 focal_loss 0.26751 dice_loss 0.10794 +Epoch [2814/4000] Validation [3/4] Loss: 0.45376 focal_loss 0.35848 dice_loss 0.09528 +Epoch [2814/4000] Validation [4/4] Loss: 0.52703 focal_loss 0.37856 dice_loss 0.14847 +Epoch [2814/4000] Validation metric {'Val/mean dice_metric': 0.9728814959526062, 'Val/mean miou_metric': 0.9578021764755249, 'Val/mean f1': 0.9748551845550537, 'Val/mean precision': 0.9716511368751526, 'Val/mean recall': 0.9780803918838501, 'Val/mean hd95_metric': 5.212929725646973} +Cheakpoint... +Epoch [2814/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728814959526062, 'Val/mean miou_metric': 0.9578021764755249, 'Val/mean f1': 0.9748551845550537, 'Val/mean precision': 0.9716511368751526, 'Val/mean recall': 0.9780803918838501, 'Val/mean hd95_metric': 5.212929725646973} +Epoch [2815/4000] Training [1/16] Loss: 0.00396 +Epoch [2815/4000] Training [2/16] Loss: 0.00358 +Epoch [2815/4000] Training [3/16] Loss: 0.00384 +Epoch [2815/4000] Training [4/16] Loss: 0.00320 +Epoch [2815/4000] Training [5/16] Loss: 0.00321 +Epoch [2815/4000] Training [6/16] Loss: 0.00261 +Epoch [2815/4000] Training [7/16] Loss: 0.00422 +Epoch [2815/4000] Training [8/16] Loss: 0.00576 +Epoch [2815/4000] Training [9/16] Loss: 0.00335 +Epoch [2815/4000] Training [10/16] Loss: 0.00316 +Epoch [2815/4000] Training [11/16] Loss: 0.00256 +Epoch [2815/4000] Training [12/16] Loss: 0.00313 +Epoch [2815/4000] Training [13/16] Loss: 0.00321 +Epoch [2815/4000] Training [14/16] Loss: 0.00315 +Epoch [2815/4000] Training [15/16] Loss: 0.00312 +Epoch [2815/4000] Training [16/16] Loss: 0.00350 +Epoch [2815/4000] Training metric {'Train/mean dice_metric': 0.9980385899543762, 'Train/mean miou_metric': 0.9957953691482544, 'Train/mean f1': 0.9931684732437134, 'Train/mean precision': 0.9885647892951965, 'Train/mean recall': 0.9978151917457581, 'Train/mean hd95_metric': 0.8474888801574707} +Epoch [2815/4000] Validation [1/4] Loss: 0.28518 focal_loss 0.22851 dice_loss 0.05667 +Epoch [2815/4000] Validation [2/4] Loss: 0.68775 focal_loss 0.50122 dice_loss 0.18654 +Epoch [2815/4000] Validation [3/4] Loss: 0.41080 focal_loss 0.31537 dice_loss 0.09544 +Epoch [2815/4000] Validation [4/4] Loss: 0.50182 focal_loss 0.38554 dice_loss 0.11629 +Epoch [2815/4000] Validation metric {'Val/mean dice_metric': 0.972974956035614, 'Val/mean miou_metric': 0.9581656455993652, 'Val/mean f1': 0.9757768511772156, 'Val/mean precision': 0.9730057120323181, 'Val/mean recall': 0.9785639047622681, 'Val/mean hd95_metric': 5.573869705200195} +Cheakpoint... +Epoch [2815/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972974956035614, 'Val/mean miou_metric': 0.9581656455993652, 'Val/mean f1': 0.9757768511772156, 'Val/mean precision': 0.9730057120323181, 'Val/mean recall': 0.9785639047622681, 'Val/mean hd95_metric': 5.573869705200195} +Epoch [2816/4000] Training [1/16] Loss: 0.00319 +Epoch [2816/4000] Training [2/16] Loss: 0.00416 +Epoch [2816/4000] Training [3/16] Loss: 0.00245 +Epoch [2816/4000] Training [4/16] Loss: 0.00250 +Epoch [2816/4000] Training [5/16] Loss: 0.00405 +Epoch [2816/4000] Training [6/16] Loss: 0.00319 +Epoch [2816/4000] Training [7/16] Loss: 0.00399 +Epoch [2816/4000] Training [8/16] Loss: 0.00447 +Epoch [2816/4000] Training [9/16] Loss: 0.00316 +Epoch [2816/4000] Training [10/16] Loss: 0.00314 +Epoch [2816/4000] Training [11/16] Loss: 0.00332 +Epoch [2816/4000] Training [12/16] Loss: 0.00487 +Epoch [2816/4000] Training [13/16] Loss: 0.00238 +Epoch [2816/4000] Training [14/16] Loss: 0.00371 +Epoch [2816/4000] Training [15/16] Loss: 0.00308 +Epoch [2816/4000] Training [16/16] Loss: 0.00354 +Epoch [2816/4000] Training metric {'Train/mean dice_metric': 0.9979391098022461, 'Train/mean miou_metric': 0.9956094622612, 'Train/mean f1': 0.9930821657180786, 'Train/mean precision': 0.9884520173072815, 'Train/mean recall': 0.9977559447288513, 'Train/mean hd95_metric': 0.8208562135696411} +Epoch [2816/4000] Validation [1/4] Loss: 0.31360 focal_loss 0.25372 dice_loss 0.05988 +Epoch [2816/4000] Validation [2/4] Loss: 0.42036 focal_loss 0.30377 dice_loss 0.11659 +Epoch [2816/4000] Validation [3/4] Loss: 0.37675 focal_loss 0.28706 dice_loss 0.08969 +Epoch [2816/4000] Validation [4/4] Loss: 0.33022 focal_loss 0.21765 dice_loss 0.11257 +Epoch [2816/4000] Validation metric {'Val/mean dice_metric': 0.9733318090438843, 'Val/mean miou_metric': 0.9588750004768372, 'Val/mean f1': 0.9758325815200806, 'Val/mean precision': 0.9742708802223206, 'Val/mean recall': 0.9773992896080017, 'Val/mean hd95_metric': 4.990172386169434} +Cheakpoint... +Epoch [2816/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733318090438843, 'Val/mean miou_metric': 0.9588750004768372, 'Val/mean f1': 0.9758325815200806, 'Val/mean precision': 0.9742708802223206, 'Val/mean recall': 0.9773992896080017, 'Val/mean hd95_metric': 4.990172386169434} +Epoch [2817/4000] Training [1/16] Loss: 0.00347 +Epoch [2817/4000] Training [2/16] Loss: 0.00289 +Epoch [2817/4000] Training [3/16] Loss: 0.00321 +Epoch [2817/4000] Training [4/16] Loss: 0.00380 +Epoch [2817/4000] Training [5/16] Loss: 0.00274 +Epoch [2817/4000] Training [6/16] Loss: 0.00427 +Epoch [2817/4000] Training [7/16] Loss: 0.00419 +Epoch [2817/4000] Training [8/16] Loss: 0.00321 +Epoch [2817/4000] Training [9/16] Loss: 0.00494 +Epoch [2817/4000] Training [10/16] Loss: 0.00362 +Epoch [2817/4000] Training [11/16] Loss: 0.00311 +Epoch [2817/4000] Training [12/16] Loss: 0.00346 +Epoch [2817/4000] Training [13/16] Loss: 0.00360 +Epoch [2817/4000] Training [14/16] Loss: 0.00352 +Epoch [2817/4000] Training [15/16] Loss: 0.00378 +Epoch [2817/4000] Training [16/16] Loss: 0.00350 +Epoch [2817/4000] Training metric {'Train/mean dice_metric': 0.9978464841842651, 'Train/mean miou_metric': 0.9954091906547546, 'Train/mean f1': 0.9929970502853394, 'Train/mean precision': 0.9883553981781006, 'Train/mean recall': 0.997682511806488, 'Train/mean hd95_metric': 0.8696565628051758} +Epoch [2817/4000] Validation [1/4] Loss: 0.29931 focal_loss 0.24197 dice_loss 0.05733 +Epoch [2817/4000] Validation [2/4] Loss: 0.45249 focal_loss 0.33189 dice_loss 0.12060 +Epoch [2817/4000] Validation [3/4] Loss: 0.39418 focal_loss 0.30593 dice_loss 0.08825 +Epoch [2817/4000] Validation [4/4] Loss: 0.36142 focal_loss 0.26267 dice_loss 0.09874 +Epoch [2817/4000] Validation metric {'Val/mean dice_metric': 0.9756956100463867, 'Val/mean miou_metric': 0.9606069326400757, 'Val/mean f1': 0.9763080477714539, 'Val/mean precision': 0.9742116332054138, 'Val/mean recall': 0.978413462638855, 'Val/mean hd95_metric': 4.918409824371338} +Cheakpoint... +Epoch [2817/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756956100463867, 'Val/mean miou_metric': 0.9606069326400757, 'Val/mean f1': 0.9763080477714539, 'Val/mean precision': 0.9742116332054138, 'Val/mean recall': 0.978413462638855, 'Val/mean hd95_metric': 4.918409824371338} +Epoch [2818/4000] Training [1/16] Loss: 0.00347 +Epoch [2818/4000] Training [2/16] Loss: 0.00452 +Epoch [2818/4000] Training [3/16] Loss: 0.00367 +Epoch [2818/4000] Training [4/16] Loss: 0.00337 +Epoch [2818/4000] Training [5/16] Loss: 0.00461 +Epoch [2818/4000] Training [6/16] Loss: 0.00325 +Epoch [2818/4000] Training [7/16] Loss: 0.00361 +Epoch [2818/4000] Training [8/16] Loss: 0.00381 +Epoch [2818/4000] Training [9/16] Loss: 0.00306 +Epoch [2818/4000] Training [10/16] Loss: 0.00379 +Epoch [2818/4000] Training [11/16] Loss: 0.00370 +Epoch [2818/4000] Training [12/16] Loss: 0.00439 +Epoch [2818/4000] Training [13/16] Loss: 0.00348 +Epoch [2818/4000] Training [14/16] Loss: 0.00452 +Epoch [2818/4000] Training [15/16] Loss: 0.00338 +Epoch [2818/4000] Training [16/16] Loss: 0.00566 +Epoch [2818/4000] Training metric {'Train/mean dice_metric': 0.9977679252624512, 'Train/mean miou_metric': 0.9952724575996399, 'Train/mean f1': 0.9929924607276917, 'Train/mean precision': 0.9884200096130371, 'Train/mean recall': 0.9976074695587158, 'Train/mean hd95_metric': 0.8559845685958862} +Epoch [2818/4000] Validation [1/4] Loss: 0.30936 focal_loss 0.24793 dice_loss 0.06143 +Epoch [2818/4000] Validation [2/4] Loss: 0.82357 focal_loss 0.62871 dice_loss 0.19486 +Epoch [2818/4000] Validation [3/4] Loss: 0.45329 focal_loss 0.35520 dice_loss 0.09809 +Epoch [2818/4000] Validation [4/4] Loss: 0.36367 focal_loss 0.24214 dice_loss 0.12152 +Epoch [2818/4000] Validation metric {'Val/mean dice_metric': 0.9715970158576965, 'Val/mean miou_metric': 0.9572189450263977, 'Val/mean f1': 0.9750328660011292, 'Val/mean precision': 0.9732916355133057, 'Val/mean recall': 0.976780354976654, 'Val/mean hd95_metric': 5.220943450927734} +Cheakpoint... +Epoch [2818/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715970158576965, 'Val/mean miou_metric': 0.9572189450263977, 'Val/mean f1': 0.9750328660011292, 'Val/mean precision': 0.9732916355133057, 'Val/mean recall': 0.976780354976654, 'Val/mean hd95_metric': 5.220943450927734} +Epoch [2819/4000] Training [1/16] Loss: 0.00427 +Epoch [2819/4000] Training [2/16] Loss: 0.00374 +Epoch [2819/4000] Training [3/16] Loss: 0.00529 +Epoch [2819/4000] Training [4/16] Loss: 0.00273 +Epoch [2819/4000] Training [5/16] Loss: 0.00380 +Epoch [2819/4000] Training [6/16] Loss: 0.00462 +Epoch [2819/4000] Training [7/16] Loss: 0.00553 +Epoch [2819/4000] Training [8/16] Loss: 0.00342 +Epoch [2819/4000] Training [9/16] Loss: 0.00319 +Epoch [2819/4000] Training [10/16] Loss: 0.00315 +Epoch [2819/4000] Training [11/16] Loss: 0.00306 +Epoch [2819/4000] Training [12/16] Loss: 0.00683 +Epoch [2819/4000] Training [13/16] Loss: 0.00283 +Epoch [2819/4000] Training [14/16] Loss: 0.00317 +Epoch [2819/4000] Training [15/16] Loss: 0.00481 +Epoch [2819/4000] Training [16/16] Loss: 0.00442 +Epoch [2819/4000] Training metric {'Train/mean dice_metric': 0.9975955486297607, 'Train/mean miou_metric': 0.9949332475662231, 'Train/mean f1': 0.993022084236145, 'Train/mean precision': 0.9885227084159851, 'Train/mean recall': 0.9975625872612, 'Train/mean hd95_metric': 0.8862859606742859} +Epoch [2819/4000] Validation [1/4] Loss: 0.40712 focal_loss 0.33883 dice_loss 0.06828 +Epoch [2819/4000] Validation [2/4] Loss: 1.15234 focal_loss 0.89780 dice_loss 0.25454 +Epoch [2819/4000] Validation [3/4] Loss: 0.40687 focal_loss 0.31266 dice_loss 0.09422 +Epoch [2819/4000] Validation [4/4] Loss: 0.23694 focal_loss 0.15745 dice_loss 0.07949 +Epoch [2819/4000] Validation metric {'Val/mean dice_metric': 0.97254878282547, 'Val/mean miou_metric': 0.957989513874054, 'Val/mean f1': 0.9756844639778137, 'Val/mean precision': 0.9729006290435791, 'Val/mean recall': 0.9784842729568481, 'Val/mean hd95_metric': 5.310353755950928} +Cheakpoint... +Epoch [2819/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97254878282547, 'Val/mean miou_metric': 0.957989513874054, 'Val/mean f1': 0.9756844639778137, 'Val/mean precision': 0.9729006290435791, 'Val/mean recall': 0.9784842729568481, 'Val/mean hd95_metric': 5.310353755950928} +Epoch [2820/4000] Training [1/16] Loss: 0.00396 +Epoch [2820/4000] Training [2/16] Loss: 0.00436 +Epoch [2820/4000] Training [3/16] Loss: 0.00585 +Epoch [2820/4000] Training [4/16] Loss: 0.00456 +Epoch [2820/4000] Training [5/16] Loss: 0.00317 +Epoch [2820/4000] Training [6/16] Loss: 0.00410 +Epoch [2820/4000] Training [7/16] Loss: 0.00386 +Epoch [2820/4000] Training [8/16] Loss: 0.00427 +Epoch [2820/4000] Training [9/16] Loss: 0.00419 +Epoch [2820/4000] Training [10/16] Loss: 0.00315 +Epoch [2820/4000] Training [11/16] Loss: 0.00403 +Epoch [2820/4000] Training [12/16] Loss: 0.00484 +Epoch [2820/4000] Training [13/16] Loss: 0.00461 +Epoch [2820/4000] Training [14/16] Loss: 0.00391 +Epoch [2820/4000] Training [15/16] Loss: 0.00264 +Epoch [2820/4000] Training [16/16] Loss: 0.00343 +Epoch [2820/4000] Training metric {'Train/mean dice_metric': 0.9976053237915039, 'Train/mean miou_metric': 0.9949215054512024, 'Train/mean f1': 0.9923031330108643, 'Train/mean precision': 0.987187385559082, 'Train/mean recall': 0.9974721074104309, 'Train/mean hd95_metric': 0.9108953475952148} +Epoch [2820/4000] Validation [1/4] Loss: 0.34005 focal_loss 0.27884 dice_loss 0.06120 +Epoch [2820/4000] Validation [2/4] Loss: 0.44529 focal_loss 0.32382 dice_loss 0.12147 +Epoch [2820/4000] Validation [3/4] Loss: 0.41771 focal_loss 0.32396 dice_loss 0.09375 +Epoch [2820/4000] Validation [4/4] Loss: 0.46189 focal_loss 0.33112 dice_loss 0.13077 +Epoch [2820/4000] Validation metric {'Val/mean dice_metric': 0.9739447832107544, 'Val/mean miou_metric': 0.9592449069023132, 'Val/mean f1': 0.9756664633750916, 'Val/mean precision': 0.9719151854515076, 'Val/mean recall': 0.9794469475746155, 'Val/mean hd95_metric': 5.065718173980713} +Cheakpoint... +Epoch [2820/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739447832107544, 'Val/mean miou_metric': 0.9592449069023132, 'Val/mean f1': 0.9756664633750916, 'Val/mean precision': 0.9719151854515076, 'Val/mean recall': 0.9794469475746155, 'Val/mean hd95_metric': 5.065718173980713} +Epoch [2821/4000] Training [1/16] Loss: 0.00310 +Epoch [2821/4000] Training [2/16] Loss: 0.00479 +Epoch [2821/4000] Training [3/16] Loss: 0.00333 +Epoch [2821/4000] Training [4/16] Loss: 0.00286 +Epoch [2821/4000] Training [5/16] Loss: 0.00345 +Epoch [2821/4000] Training [6/16] Loss: 0.00368 +Epoch [2821/4000] Training [7/16] Loss: 0.00452 +Epoch [2821/4000] Training [8/16] Loss: 0.00299 +Epoch [2821/4000] Training [9/16] Loss: 0.00365 +Epoch [2821/4000] Training [10/16] Loss: 0.00431 +Epoch [2821/4000] Training [11/16] Loss: 0.00270 +Epoch [2821/4000] Training [12/16] Loss: 0.00355 +Epoch [2821/4000] Training [13/16] Loss: 0.00265 +Epoch [2821/4000] Training [14/16] Loss: 0.00310 +Epoch [2821/4000] Training [15/16] Loss: 0.00478 +Epoch [2821/4000] Training [16/16] Loss: 0.00265 +Epoch [2821/4000] Training metric {'Train/mean dice_metric': 0.9978848695755005, 'Train/mean miou_metric': 0.9954926371574402, 'Train/mean f1': 0.9931193590164185, 'Train/mean precision': 0.9885257482528687, 'Train/mean recall': 0.9977558255195618, 'Train/mean hd95_metric': 0.8633562922477722} +Epoch [2821/4000] Validation [1/4] Loss: 0.35801 focal_loss 0.29439 dice_loss 0.06362 +Epoch [2821/4000] Validation [2/4] Loss: 0.42835 focal_loss 0.30966 dice_loss 0.11869 +Epoch [2821/4000] Validation [3/4] Loss: 0.39845 focal_loss 0.30202 dice_loss 0.09643 +Epoch [2821/4000] Validation [4/4] Loss: 0.46838 focal_loss 0.34631 dice_loss 0.12207 +Epoch [2821/4000] Validation metric {'Val/mean dice_metric': 0.9736671447753906, 'Val/mean miou_metric': 0.9588038325309753, 'Val/mean f1': 0.9756713509559631, 'Val/mean precision': 0.9722046256065369, 'Val/mean recall': 0.9791629910469055, 'Val/mean hd95_metric': 5.310434341430664} +Cheakpoint... +Epoch [2821/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736671447753906, 'Val/mean miou_metric': 0.9588038325309753, 'Val/mean f1': 0.9756713509559631, 'Val/mean precision': 0.9722046256065369, 'Val/mean recall': 0.9791629910469055, 'Val/mean hd95_metric': 5.310434341430664} +Epoch [2822/4000] Training [1/16] Loss: 0.00270 +Epoch [2822/4000] Training [2/16] Loss: 0.00385 +Epoch [2822/4000] Training [3/16] Loss: 0.00302 +Epoch [2822/4000] Training [4/16] Loss: 0.00283 +Epoch [2822/4000] Training [5/16] Loss: 0.00293 +Epoch [2822/4000] Training [6/16] Loss: 0.00352 +Epoch [2822/4000] Training [7/16] Loss: 0.00495 +Epoch [2822/4000] Training [8/16] Loss: 0.00448 +Epoch [2822/4000] Training [9/16] Loss: 0.00588 +Epoch [2822/4000] Training [10/16] Loss: 0.00304 +Epoch [2822/4000] Training [11/16] Loss: 0.00507 +Epoch [2822/4000] Training [12/16] Loss: 0.00291 +Epoch [2822/4000] Training [13/16] Loss: 0.00236 +Epoch [2822/4000] Training [14/16] Loss: 0.00320 +Epoch [2822/4000] Training [15/16] Loss: 0.00345 +Epoch [2822/4000] Training [16/16] Loss: 0.00311 +Epoch [2822/4000] Training metric {'Train/mean dice_metric': 0.9977561831474304, 'Train/mean miou_metric': 0.9952549934387207, 'Train/mean f1': 0.9930850267410278, 'Train/mean precision': 0.9885444641113281, 'Train/mean recall': 0.9976674318313599, 'Train/mean hd95_metric': 0.8829459547996521} +Epoch [2822/4000] Validation [1/4] Loss: 0.36019 focal_loss 0.29695 dice_loss 0.06324 +Epoch [2822/4000] Validation [2/4] Loss: 0.44406 focal_loss 0.32178 dice_loss 0.12227 +Epoch [2822/4000] Validation [3/4] Loss: 0.46012 focal_loss 0.36526 dice_loss 0.09486 +Epoch [2822/4000] Validation [4/4] Loss: 0.45562 focal_loss 0.32882 dice_loss 0.12680 +Epoch [2822/4000] Validation metric {'Val/mean dice_metric': 0.9739680290222168, 'Val/mean miou_metric': 0.959119975566864, 'Val/mean f1': 0.975555956363678, 'Val/mean precision': 0.9717504382133484, 'Val/mean recall': 0.9793913960456848, 'Val/mean hd95_metric': 5.246568202972412} +Cheakpoint... +Epoch [2822/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739680290222168, 'Val/mean miou_metric': 0.959119975566864, 'Val/mean f1': 0.975555956363678, 'Val/mean precision': 0.9717504382133484, 'Val/mean recall': 0.9793913960456848, 'Val/mean hd95_metric': 5.246568202972412} +Epoch [2823/4000] Training [1/16] Loss: 0.00248 +Epoch [2823/4000] Training [2/16] Loss: 0.00271 +Epoch [2823/4000] Training [3/16] Loss: 0.00328 +Epoch [2823/4000] Training [4/16] Loss: 0.00272 +Epoch [2823/4000] Training [5/16] Loss: 0.00258 +Epoch [2823/4000] Training [6/16] Loss: 0.00384 +Epoch [2823/4000] Training [7/16] Loss: 0.00310 +Epoch [2823/4000] Training [8/16] Loss: 0.00481 +Epoch [2823/4000] Training [9/16] Loss: 0.00330 +Epoch [2823/4000] Training [10/16] Loss: 0.00261 +Epoch [2823/4000] Training [11/16] Loss: 0.00235 +Epoch [2823/4000] Training [12/16] Loss: 0.00281 +Epoch [2823/4000] Training [13/16] Loss: 0.00275 +Epoch [2823/4000] Training [14/16] Loss: 0.00265 +Epoch [2823/4000] Training [15/16] Loss: 0.00466 +Epoch [2823/4000] Training [16/16] Loss: 0.00342 +Epoch [2823/4000] Training metric {'Train/mean dice_metric': 0.9980475902557373, 'Train/mean miou_metric': 0.9958195686340332, 'Train/mean f1': 0.9931215047836304, 'Train/mean precision': 0.9884256720542908, 'Train/mean recall': 0.9978621602058411, 'Train/mean hd95_metric': 0.8297151327133179} +Epoch [2823/4000] Validation [1/4] Loss: 0.33634 focal_loss 0.27490 dice_loss 0.06143 +Epoch [2823/4000] Validation [2/4] Loss: 0.45233 focal_loss 0.32891 dice_loss 0.12342 +Epoch [2823/4000] Validation [3/4] Loss: 0.39944 focal_loss 0.30750 dice_loss 0.09193 +Epoch [2823/4000] Validation [4/4] Loss: 0.32414 focal_loss 0.21847 dice_loss 0.10568 +Epoch [2823/4000] Validation metric {'Val/mean dice_metric': 0.9734466671943665, 'Val/mean miou_metric': 0.9590983390808105, 'Val/mean f1': 0.9757435321807861, 'Val/mean precision': 0.9732192754745483, 'Val/mean recall': 0.978280782699585, 'Val/mean hd95_metric': 5.250826835632324} +Cheakpoint... +Epoch [2823/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734466671943665, 'Val/mean miou_metric': 0.9590983390808105, 'Val/mean f1': 0.9757435321807861, 'Val/mean precision': 0.9732192754745483, 'Val/mean recall': 0.978280782699585, 'Val/mean hd95_metric': 5.250826835632324} +Epoch [2824/4000] Training [1/16] Loss: 0.00469 +Epoch [2824/4000] Training [2/16] Loss: 0.00385 +Epoch [2824/4000] Training [3/16] Loss: 0.00323 +Epoch [2824/4000] Training [4/16] Loss: 0.00399 +Epoch [2824/4000] Training [5/16] Loss: 0.00365 +Epoch [2824/4000] Training [6/16] Loss: 0.00526 +Epoch [2824/4000] Training [7/16] Loss: 0.00305 +Epoch [2824/4000] Training [8/16] Loss: 0.00442 +Epoch [2824/4000] Training [9/16] Loss: 0.00512 +Epoch [2824/4000] Training [10/16] Loss: 0.00342 +Epoch [2824/4000] Training [11/16] Loss: 0.00367 +Epoch [2824/4000] Training [12/16] Loss: 0.00295 +Epoch [2824/4000] Training [13/16] Loss: 0.00269 +Epoch [2824/4000] Training [14/16] Loss: 0.00243 +Epoch [2824/4000] Training [15/16] Loss: 0.00295 +Epoch [2824/4000] Training [16/16] Loss: 0.00388 +Epoch [2824/4000] Training metric {'Train/mean dice_metric': 0.9978225231170654, 'Train/mean miou_metric': 0.9953603148460388, 'Train/mean f1': 0.9927968382835388, 'Train/mean precision': 0.9879347681999207, 'Train/mean recall': 0.9977070093154907, 'Train/mean hd95_metric': 0.8756413459777832} +Epoch [2824/4000] Validation [1/4] Loss: 0.36883 focal_loss 0.30364 dice_loss 0.06519 +Epoch [2824/4000] Validation [2/4] Loss: 0.47010 focal_loss 0.34150 dice_loss 0.12860 +Epoch [2824/4000] Validation [3/4] Loss: 0.35537 focal_loss 0.27012 dice_loss 0.08525 +Epoch [2824/4000] Validation [4/4] Loss: 0.32647 focal_loss 0.22682 dice_loss 0.09965 +Epoch [2824/4000] Validation metric {'Val/mean dice_metric': 0.9741159677505493, 'Val/mean miou_metric': 0.9593240022659302, 'Val/mean f1': 0.9758752584457397, 'Val/mean precision': 0.9735100269317627, 'Val/mean recall': 0.9782520532608032, 'Val/mean hd95_metric': 4.866459846496582} +Cheakpoint... +Epoch [2824/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741159677505493, 'Val/mean miou_metric': 0.9593240022659302, 'Val/mean f1': 0.9758752584457397, 'Val/mean precision': 0.9735100269317627, 'Val/mean recall': 0.9782520532608032, 'Val/mean hd95_metric': 4.866459846496582} +Epoch [2825/4000] Training [1/16] Loss: 0.00397 +Epoch [2825/4000] Training [2/16] Loss: 0.00420 +Epoch [2825/4000] Training [3/16] Loss: 0.00385 +Epoch [2825/4000] Training [4/16] Loss: 0.00335 +Epoch [2825/4000] Training [5/16] Loss: 0.00407 +Epoch [2825/4000] Training [6/16] Loss: 0.00361 +Epoch [2825/4000] Training [7/16] Loss: 0.00428 +Epoch [2825/4000] Training [8/16] Loss: 0.00342 +Epoch [2825/4000] Training [9/16] Loss: 0.00328 +Epoch [2825/4000] Training [10/16] Loss: 0.00277 +Epoch [2825/4000] Training [11/16] Loss: 0.00278 +Epoch [2825/4000] Training [12/16] Loss: 0.00432 +Epoch [2825/4000] Training [13/16] Loss: 0.00266 +Epoch [2825/4000] Training [14/16] Loss: 0.00290 +Epoch [2825/4000] Training [15/16] Loss: 0.00456 +Epoch [2825/4000] Training [16/16] Loss: 0.00231 +Epoch [2825/4000] Training metric {'Train/mean dice_metric': 0.9980442523956299, 'Train/mean miou_metric': 0.9958115220069885, 'Train/mean f1': 0.9930589199066162, 'Train/mean precision': 0.9884078502655029, 'Train/mean recall': 0.9977539777755737, 'Train/mean hd95_metric': 0.8229768872261047} +Epoch [2825/4000] Validation [1/4] Loss: 0.38652 focal_loss 0.32103 dice_loss 0.06550 +Epoch [2825/4000] Validation [2/4] Loss: 0.83839 focal_loss 0.64998 dice_loss 0.18841 +Epoch [2825/4000] Validation [3/4] Loss: 0.23798 focal_loss 0.17671 dice_loss 0.06127 +Epoch [2825/4000] Validation [4/4] Loss: 0.36360 focal_loss 0.25624 dice_loss 0.10736 +Epoch [2825/4000] Validation metric {'Val/mean dice_metric': 0.9749132394790649, 'Val/mean miou_metric': 0.9604053497314453, 'Val/mean f1': 0.9755045771598816, 'Val/mean precision': 0.9720336198806763, 'Val/mean recall': 0.9790005683898926, 'Val/mean hd95_metric': 5.349233627319336} +Cheakpoint... +Epoch [2825/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749132394790649, 'Val/mean miou_metric': 0.9604053497314453, 'Val/mean f1': 0.9755045771598816, 'Val/mean precision': 0.9720336198806763, 'Val/mean recall': 0.9790005683898926, 'Val/mean hd95_metric': 5.349233627319336} +Epoch [2826/4000] Training [1/16] Loss: 0.00376 +Epoch [2826/4000] Training [2/16] Loss: 0.00284 +Epoch [2826/4000] Training [3/16] Loss: 0.00335 +Epoch [2826/4000] Training [4/16] Loss: 0.00350 +Epoch [2826/4000] Training [5/16] Loss: 0.00399 +Epoch [2826/4000] Training [6/16] Loss: 0.00454 +Epoch [2826/4000] Training [7/16] Loss: 0.00443 +Epoch [2826/4000] Training [8/16] Loss: 0.00315 +Epoch [2826/4000] Training [9/16] Loss: 0.00326 +Epoch [2826/4000] Training [10/16] Loss: 0.00253 +Epoch [2826/4000] Training [11/16] Loss: 0.00308 +Epoch [2826/4000] Training [12/16] Loss: 0.00391 +Epoch [2826/4000] Training [13/16] Loss: 0.00465 +Epoch [2826/4000] Training [14/16] Loss: 0.00574 +Epoch [2826/4000] Training [15/16] Loss: 0.00382 +Epoch [2826/4000] Training [16/16] Loss: 0.00335 +Epoch [2826/4000] Training metric {'Train/mean dice_metric': 0.9978762865066528, 'Train/mean miou_metric': 0.9954656958580017, 'Train/mean f1': 0.9929502010345459, 'Train/mean precision': 0.9882252216339111, 'Train/mean recall': 0.9977205395698547, 'Train/mean hd95_metric': 0.8849993944168091} +Epoch [2826/4000] Validation [1/4] Loss: 0.33771 focal_loss 0.27647 dice_loss 0.06124 +Epoch [2826/4000] Validation [2/4] Loss: 0.71674 focal_loss 0.52079 dice_loss 0.19595 +Epoch [2826/4000] Validation [3/4] Loss: 0.40143 focal_loss 0.31023 dice_loss 0.09120 +Epoch [2826/4000] Validation [4/4] Loss: 0.54727 focal_loss 0.39278 dice_loss 0.15449 +Epoch [2826/4000] Validation metric {'Val/mean dice_metric': 0.9723164439201355, 'Val/mean miou_metric': 0.9576818346977234, 'Val/mean f1': 0.9753586053848267, 'Val/mean precision': 0.974102795124054, 'Val/mean recall': 0.9766178727149963, 'Val/mean hd95_metric': 5.287801742553711} +Cheakpoint... +Epoch [2826/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723164439201355, 'Val/mean miou_metric': 0.9576818346977234, 'Val/mean f1': 0.9753586053848267, 'Val/mean precision': 0.974102795124054, 'Val/mean recall': 0.9766178727149963, 'Val/mean hd95_metric': 5.287801742553711} +Epoch [2827/4000] Training [1/16] Loss: 0.00275 +Epoch [2827/4000] Training [2/16] Loss: 0.00345 +Epoch [2827/4000] Training [3/16] Loss: 0.00414 +Epoch [2827/4000] Training [4/16] Loss: 0.00268 +Epoch [2827/4000] Training [5/16] Loss: 0.00395 +Epoch [2827/4000] Training [6/16] Loss: 0.00414 +Epoch [2827/4000] Training [7/16] Loss: 0.00305 +Epoch [2827/4000] Training [8/16] Loss: 0.00481 +Epoch [2827/4000] Training [9/16] Loss: 0.00412 +Epoch [2827/4000] Training [10/16] Loss: 0.00325 +Epoch [2827/4000] Training [11/16] Loss: 0.00352 +Epoch [2827/4000] Training [12/16] Loss: 0.00358 +Epoch [2827/4000] Training [13/16] Loss: 0.00498 +Epoch [2827/4000] Training [14/16] Loss: 0.00339 +Epoch [2827/4000] Training [15/16] Loss: 0.00331 +Epoch [2827/4000] Training [16/16] Loss: 0.00265 +Epoch [2827/4000] Training metric {'Train/mean dice_metric': 0.9979305267333984, 'Train/mean miou_metric': 0.9955993890762329, 'Train/mean f1': 0.9932162165641785, 'Train/mean precision': 0.9886744618415833, 'Train/mean recall': 0.9977998733520508, 'Train/mean hd95_metric': 0.8439728021621704} +Epoch [2827/4000] Validation [1/4] Loss: 0.29017 focal_loss 0.23182 dice_loss 0.05835 +Epoch [2827/4000] Validation [2/4] Loss: 0.43181 focal_loss 0.31274 dice_loss 0.11906 +Epoch [2827/4000] Validation [3/4] Loss: 0.39685 focal_loss 0.30197 dice_loss 0.09488 +Epoch [2827/4000] Validation [4/4] Loss: 0.26027 focal_loss 0.17555 dice_loss 0.08472 +Epoch [2827/4000] Validation metric {'Val/mean dice_metric': 0.9747999310493469, 'Val/mean miou_metric': 0.9603255987167358, 'Val/mean f1': 0.9760870933532715, 'Val/mean precision': 0.9726765751838684, 'Val/mean recall': 0.9795216917991638, 'Val/mean hd95_metric': 4.884206295013428} +Cheakpoint... +Epoch [2827/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747999310493469, 'Val/mean miou_metric': 0.9603255987167358, 'Val/mean f1': 0.9760870933532715, 'Val/mean precision': 0.9726765751838684, 'Val/mean recall': 0.9795216917991638, 'Val/mean hd95_metric': 4.884206295013428} +Epoch [2828/4000] Training [1/16] Loss: 0.00390 +Epoch [2828/4000] Training [2/16] Loss: 0.00274 +Epoch [2828/4000] Training [3/16] Loss: 0.00351 +Epoch [2828/4000] Training [4/16] Loss: 0.00467 +Epoch [2828/4000] Training [5/16] Loss: 0.00504 +Epoch [2828/4000] Training [6/16] Loss: 0.00573 +Epoch [2828/4000] Training [7/16] Loss: 0.00351 +Epoch [2828/4000] Training [8/16] Loss: 0.00316 +Epoch [2828/4000] Training [9/16] Loss: 0.00351 +Epoch [2828/4000] Training [10/16] Loss: 0.00303 +Epoch [2828/4000] Training [11/16] Loss: 0.00344 +Epoch [2828/4000] Training [12/16] Loss: 0.00305 +Epoch [2828/4000] Training [13/16] Loss: 0.00322 +Epoch [2828/4000] Training [14/16] Loss: 0.00330 +Epoch [2828/4000] Training [15/16] Loss: 0.00382 +Epoch [2828/4000] Training [16/16] Loss: 0.00330 +Epoch [2828/4000] Training metric {'Train/mean dice_metric': 0.9979144334793091, 'Train/mean miou_metric': 0.9955664873123169, 'Train/mean f1': 0.9931194186210632, 'Train/mean precision': 0.9885563254356384, 'Train/mean recall': 0.9977248311042786, 'Train/mean hd95_metric': 0.8468753695487976} +Epoch [2828/4000] Validation [1/4] Loss: 0.35449 focal_loss 0.29212 dice_loss 0.06236 +Epoch [2828/4000] Validation [2/4] Loss: 1.23664 focal_loss 0.94518 dice_loss 0.29146 +Epoch [2828/4000] Validation [3/4] Loss: 0.47041 focal_loss 0.37543 dice_loss 0.09498 +Epoch [2828/4000] Validation [4/4] Loss: 0.27625 focal_loss 0.19452 dice_loss 0.08173 +Epoch [2828/4000] Validation metric {'Val/mean dice_metric': 0.9718211889266968, 'Val/mean miou_metric': 0.9575923681259155, 'Val/mean f1': 0.9749078154563904, 'Val/mean precision': 0.9721901416778564, 'Val/mean recall': 0.9776407480239868, 'Val/mean hd95_metric': 5.109792232513428} +Cheakpoint... +Epoch [2828/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718211889266968, 'Val/mean miou_metric': 0.9575923681259155, 'Val/mean f1': 0.9749078154563904, 'Val/mean precision': 0.9721901416778564, 'Val/mean recall': 0.9776407480239868, 'Val/mean hd95_metric': 5.109792232513428} +Epoch [2829/4000] Training [1/16] Loss: 0.00306 +Epoch [2829/4000] Training [2/16] Loss: 0.00272 +Epoch [2829/4000] Training [3/16] Loss: 0.00320 +Epoch [2829/4000] Training [4/16] Loss: 0.00412 +Epoch [2829/4000] Training [5/16] Loss: 0.00405 +Epoch [2829/4000] Training [6/16] Loss: 0.00353 +Epoch [2829/4000] Training [7/16] Loss: 0.00461 +Epoch [2829/4000] Training [8/16] Loss: 0.00314 +Epoch [2829/4000] Training [9/16] Loss: 0.00364 +Epoch [2829/4000] Training [10/16] Loss: 0.00292 +Epoch [2829/4000] Training [11/16] Loss: 0.00303 +Epoch [2829/4000] Training [12/16] Loss: 0.00472 +Epoch [2829/4000] Training [13/16] Loss: 0.00524 +Epoch [2829/4000] Training [14/16] Loss: 0.00288 +Epoch [2829/4000] Training [15/16] Loss: 0.00290 +Epoch [2829/4000] Training [16/16] Loss: 0.00381 +Epoch [2829/4000] Training metric {'Train/mean dice_metric': 0.9979220628738403, 'Train/mean miou_metric': 0.9955710172653198, 'Train/mean f1': 0.9930562973022461, 'Train/mean precision': 0.9884805679321289, 'Train/mean recall': 0.9976745843887329, 'Train/mean hd95_metric': 0.8970763683319092} +Epoch [2829/4000] Validation [1/4] Loss: 0.38921 focal_loss 0.32579 dice_loss 0.06342 +Epoch [2829/4000] Validation [2/4] Loss: 0.85987 focal_loss 0.66712 dice_loss 0.19275 +Epoch [2829/4000] Validation [3/4] Loss: 0.41203 focal_loss 0.32326 dice_loss 0.08877 +Epoch [2829/4000] Validation [4/4] Loss: 0.29855 focal_loss 0.20196 dice_loss 0.09659 +Epoch [2829/4000] Validation metric {'Val/mean dice_metric': 0.9732521176338196, 'Val/mean miou_metric': 0.9590091705322266, 'Val/mean f1': 0.9759181141853333, 'Val/mean precision': 0.9744269847869873, 'Val/mean recall': 0.9774137735366821, 'Val/mean hd95_metric': 4.797528266906738} +Cheakpoint... +Epoch [2829/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732521176338196, 'Val/mean miou_metric': 0.9590091705322266, 'Val/mean f1': 0.9759181141853333, 'Val/mean precision': 0.9744269847869873, 'Val/mean recall': 0.9774137735366821, 'Val/mean hd95_metric': 4.797528266906738} +Epoch [2830/4000] Training [1/16] Loss: 0.00419 +Epoch [2830/4000] Training [2/16] Loss: 0.00386 +Epoch [2830/4000] Training [3/16] Loss: 0.00463 +Epoch [2830/4000] Training [4/16] Loss: 0.00347 +Epoch [2830/4000] Training [5/16] Loss: 0.00278 +Epoch [2830/4000] Training [6/16] Loss: 0.00452 +Epoch [2830/4000] Training [7/16] Loss: 0.00354 +Epoch [2830/4000] Training [8/16] Loss: 0.00286 +Epoch [2830/4000] Training [9/16] Loss: 0.00278 +Epoch [2830/4000] Training [10/16] Loss: 0.00351 +Epoch [2830/4000] Training [11/16] Loss: 0.00273 +Epoch [2830/4000] Training [12/16] Loss: 0.00526 +Epoch [2830/4000] Training [13/16] Loss: 0.00276 +Epoch [2830/4000] Training [14/16] Loss: 0.00413 +Epoch [2830/4000] Training [15/16] Loss: 0.00307 +Epoch [2830/4000] Training [16/16] Loss: 0.00412 +Epoch [2830/4000] Training metric {'Train/mean dice_metric': 0.9978688955307007, 'Train/mean miou_metric': 0.9954644441604614, 'Train/mean f1': 0.9928902387619019, 'Train/mean precision': 0.9881625771522522, 'Train/mean recall': 0.9976633787155151, 'Train/mean hd95_metric': 0.8633366227149963} +Epoch [2830/4000] Validation [1/4] Loss: 0.38872 focal_loss 0.32545 dice_loss 0.06326 +Epoch [2830/4000] Validation [2/4] Loss: 0.45702 focal_loss 0.33618 dice_loss 0.12084 +Epoch [2830/4000] Validation [3/4] Loss: 0.25421 focal_loss 0.19692 dice_loss 0.05728 +Epoch [2830/4000] Validation [4/4] Loss: 0.48207 focal_loss 0.35838 dice_loss 0.12369 +Epoch [2830/4000] Validation metric {'Val/mean dice_metric': 0.9726226925849915, 'Val/mean miou_metric': 0.9583393931388855, 'Val/mean f1': 0.9757886528968811, 'Val/mean precision': 0.9745493531227112, 'Val/mean recall': 0.9770311117172241, 'Val/mean hd95_metric': 5.02341890335083} +Cheakpoint... +Epoch [2830/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726226925849915, 'Val/mean miou_metric': 0.9583393931388855, 'Val/mean f1': 0.9757886528968811, 'Val/mean precision': 0.9745493531227112, 'Val/mean recall': 0.9770311117172241, 'Val/mean hd95_metric': 5.02341890335083} +Epoch [2831/4000] Training [1/16] Loss: 0.00308 +Epoch [2831/4000] Training [2/16] Loss: 0.00348 +Epoch [2831/4000] Training [3/16] Loss: 0.00318 +Epoch [2831/4000] Training [4/16] Loss: 0.00576 +Epoch [2831/4000] Training [5/16] Loss: 0.00352 +Epoch [2831/4000] Training [6/16] Loss: 0.00297 +Epoch [2831/4000] Training [7/16] Loss: 0.00380 +Epoch [2831/4000] Training [8/16] Loss: 0.00335 +Epoch [2831/4000] Training [9/16] Loss: 0.00364 +Epoch [2831/4000] Training [10/16] Loss: 0.00276 +Epoch [2831/4000] Training [11/16] Loss: 0.00320 +Epoch [2831/4000] Training [12/16] Loss: 0.00260 +Epoch [2831/4000] Training [13/16] Loss: 0.00524 +Epoch [2831/4000] Training [14/16] Loss: 0.00349 +Epoch [2831/4000] Training [15/16] Loss: 0.00240 +Epoch [2831/4000] Training [16/16] Loss: 0.00318 +Epoch [2831/4000] Training metric {'Train/mean dice_metric': 0.9977571964263916, 'Train/mean miou_metric': 0.9952521324157715, 'Train/mean f1': 0.9927307367324829, 'Train/mean precision': 0.9878705739974976, 'Train/mean recall': 0.9976389408111572, 'Train/mean hd95_metric': 0.8736377954483032} +Epoch [2831/4000] Validation [1/4] Loss: 0.32367 focal_loss 0.26476 dice_loss 0.05891 +Epoch [2831/4000] Validation [2/4] Loss: 0.83875 focal_loss 0.64832 dice_loss 0.19042 +Epoch [2831/4000] Validation [3/4] Loss: 0.22246 focal_loss 0.16695 dice_loss 0.05550 +Epoch [2831/4000] Validation [4/4] Loss: 0.28280 focal_loss 0.19719 dice_loss 0.08561 +Epoch [2831/4000] Validation metric {'Val/mean dice_metric': 0.9723572731018066, 'Val/mean miou_metric': 0.958609938621521, 'Val/mean f1': 0.9759913682937622, 'Val/mean precision': 0.973469078540802, 'Val/mean recall': 0.9785268902778625, 'Val/mean hd95_metric': 4.637040615081787} +Cheakpoint... +Epoch [2831/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723572731018066, 'Val/mean miou_metric': 0.958609938621521, 'Val/mean f1': 0.9759913682937622, 'Val/mean precision': 0.973469078540802, 'Val/mean recall': 0.9785268902778625, 'Val/mean hd95_metric': 4.637040615081787} +Epoch [2832/4000] Training [1/16] Loss: 0.00364 +Epoch [2832/4000] Training [2/16] Loss: 0.00402 +Epoch [2832/4000] Training [3/16] Loss: 0.00268 +Epoch [2832/4000] Training [4/16] Loss: 0.00268 +Epoch [2832/4000] Training [5/16] Loss: 0.00333 +Epoch [2832/4000] Training [6/16] Loss: 0.00387 +Epoch [2832/4000] Training [7/16] Loss: 0.00360 +Epoch [2832/4000] Training [8/16] Loss: 0.00308 +Epoch [2832/4000] Training [9/16] Loss: 0.00219 +Epoch [2832/4000] Training [10/16] Loss: 0.00391 +Epoch [2832/4000] Training [11/16] Loss: 0.00391 +Epoch [2832/4000] Training [12/16] Loss: 0.00336 +Epoch [2832/4000] Training [13/16] Loss: 0.00379 +Epoch [2832/4000] Training [14/16] Loss: 0.00449 +Epoch [2832/4000] Training [15/16] Loss: 0.00212 +Epoch [2832/4000] Training [16/16] Loss: 0.00476 +Epoch [2832/4000] Training metric {'Train/mean dice_metric': 0.9979400634765625, 'Train/mean miou_metric': 0.9956120252609253, 'Train/mean f1': 0.9930872917175293, 'Train/mean precision': 0.9884915947914124, 'Train/mean recall': 0.9977259635925293, 'Train/mean hd95_metric': 0.8363836407661438} +Epoch [2832/4000] Validation [1/4] Loss: 0.35678 focal_loss 0.29269 dice_loss 0.06409 +Epoch [2832/4000] Validation [2/4] Loss: 0.41440 focal_loss 0.30057 dice_loss 0.11382 +Epoch [2832/4000] Validation [3/4] Loss: 0.40772 focal_loss 0.31796 dice_loss 0.08975 +Epoch [2832/4000] Validation [4/4] Loss: 0.47068 focal_loss 0.34270 dice_loss 0.12798 +Epoch [2832/4000] Validation metric {'Val/mean dice_metric': 0.9728978872299194, 'Val/mean miou_metric': 0.9581714868545532, 'Val/mean f1': 0.9753280282020569, 'Val/mean precision': 0.9742317795753479, 'Val/mean recall': 0.9764265418052673, 'Val/mean hd95_metric': 4.998218536376953} +Cheakpoint... +Epoch [2832/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728978872299194, 'Val/mean miou_metric': 0.9581714868545532, 'Val/mean f1': 0.9753280282020569, 'Val/mean precision': 0.9742317795753479, 'Val/mean recall': 0.9764265418052673, 'Val/mean hd95_metric': 4.998218536376953} +Epoch [2833/4000] Training [1/16] Loss: 0.00366 +Epoch [2833/4000] Training [2/16] Loss: 0.00335 +Epoch [2833/4000] Training [3/16] Loss: 0.00351 +Epoch [2833/4000] Training [4/16] Loss: 0.00354 +Epoch [2833/4000] Training [5/16] Loss: 0.00259 +Epoch [2833/4000] Training [6/16] Loss: 0.00287 +Epoch [2833/4000] Training [7/16] Loss: 0.00257 +Epoch [2833/4000] Training [8/16] Loss: 0.00283 +Epoch [2833/4000] Training [9/16] Loss: 0.00367 +Epoch [2833/4000] Training [10/16] Loss: 0.00413 +Epoch [2833/4000] Training [11/16] Loss: 0.00234 +Epoch [2833/4000] Training [12/16] Loss: 0.00443 +Epoch [2833/4000] Training [13/16] Loss: 0.00337 +Epoch [2833/4000] Training [14/16] Loss: 0.00317 +Epoch [2833/4000] Training [15/16] Loss: 0.00236 +Epoch [2833/4000] Training [16/16] Loss: 0.00353 +Epoch [2833/4000] Training metric {'Train/mean dice_metric': 0.9980922341346741, 'Train/mean miou_metric': 0.9959131479263306, 'Train/mean f1': 0.9931493401527405, 'Train/mean precision': 0.988568127155304, 'Train/mean recall': 0.9977732300758362, 'Train/mean hd95_metric': 0.8088445067405701} +Epoch [2833/4000] Validation [1/4] Loss: 0.35989 focal_loss 0.29831 dice_loss 0.06158 +Epoch [2833/4000] Validation [2/4] Loss: 0.77661 focal_loss 0.57097 dice_loss 0.20564 +Epoch [2833/4000] Validation [3/4] Loss: 0.43267 focal_loss 0.34064 dice_loss 0.09203 +Epoch [2833/4000] Validation [4/4] Loss: 0.44024 focal_loss 0.31896 dice_loss 0.12128 +Epoch [2833/4000] Validation metric {'Val/mean dice_metric': 0.9726869463920593, 'Val/mean miou_metric': 0.9578495025634766, 'Val/mean f1': 0.9756394028663635, 'Val/mean precision': 0.9734638929367065, 'Val/mean recall': 0.9778245091438293, 'Val/mean hd95_metric': 5.53502082824707} +Cheakpoint... +Epoch [2833/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726869463920593, 'Val/mean miou_metric': 0.9578495025634766, 'Val/mean f1': 0.9756394028663635, 'Val/mean precision': 0.9734638929367065, 'Val/mean recall': 0.9778245091438293, 'Val/mean hd95_metric': 5.53502082824707} +Epoch [2834/4000] Training [1/16] Loss: 0.00340 +Epoch [2834/4000] Training [2/16] Loss: 0.00352 +Epoch [2834/4000] Training [3/16] Loss: 0.00362 +Epoch [2834/4000] Training [4/16] Loss: 0.00360 +Epoch [2834/4000] Training [5/16] Loss: 0.00341 +Epoch [2834/4000] Training [6/16] Loss: 0.00439 +Epoch [2834/4000] Training [7/16] Loss: 0.00285 +Epoch [2834/4000] Training [8/16] Loss: 0.00282 +Epoch [2834/4000] Training [9/16] Loss: 0.00427 +Epoch [2834/4000] Training [10/16] Loss: 0.00311 +Epoch [2834/4000] Training [11/16] Loss: 0.00268 +Epoch [2834/4000] Training [12/16] Loss: 0.00375 +Epoch [2834/4000] Training [13/16] Loss: 0.00338 +Epoch [2834/4000] Training [14/16] Loss: 0.00385 +Epoch [2834/4000] Training [15/16] Loss: 0.00316 +Epoch [2834/4000] Training [16/16] Loss: 0.00292 +Epoch [2834/4000] Training metric {'Train/mean dice_metric': 0.9978416562080383, 'Train/mean miou_metric': 0.9954190254211426, 'Train/mean f1': 0.9930816292762756, 'Train/mean precision': 0.9885379672050476, 'Train/mean recall': 0.9976672530174255, 'Train/mean hd95_metric': 0.8668949604034424} +Epoch [2834/4000] Validation [1/4] Loss: 0.37912 focal_loss 0.31635 dice_loss 0.06277 +Epoch [2834/4000] Validation [2/4] Loss: 0.97726 focal_loss 0.79018 dice_loss 0.18708 +Epoch [2834/4000] Validation [3/4] Loss: 0.44888 focal_loss 0.35930 dice_loss 0.08958 +Epoch [2834/4000] Validation [4/4] Loss: 0.40057 focal_loss 0.28794 dice_loss 0.11262 +Epoch [2834/4000] Validation metric {'Val/mean dice_metric': 0.9719921350479126, 'Val/mean miou_metric': 0.9578668475151062, 'Val/mean f1': 0.9758495688438416, 'Val/mean precision': 0.9745532870292664, 'Val/mean recall': 0.9771493077278137, 'Val/mean hd95_metric': 5.216316223144531} +Cheakpoint... +Epoch [2834/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719921350479126, 'Val/mean miou_metric': 0.9578668475151062, 'Val/mean f1': 0.9758495688438416, 'Val/mean precision': 0.9745532870292664, 'Val/mean recall': 0.9771493077278137, 'Val/mean hd95_metric': 5.216316223144531} +Epoch [2835/4000] Training [1/16] Loss: 0.00241 +Epoch [2835/4000] Training [2/16] Loss: 0.00281 +Epoch [2835/4000] Training [3/16] Loss: 0.00298 +Epoch [2835/4000] Training [4/16] Loss: 0.00606 +Epoch [2835/4000] Training [5/16] Loss: 0.00397 +Epoch [2835/4000] Training [6/16] Loss: 0.00274 +Epoch [2835/4000] Training [7/16] Loss: 0.00433 +Epoch [2835/4000] Training [8/16] Loss: 0.00449 +Epoch [2835/4000] Training [9/16] Loss: 0.00381 +Epoch [2835/4000] Training [10/16] Loss: 0.00381 +Epoch [2835/4000] Training [11/16] Loss: 0.00253 +Epoch [2835/4000] Training [12/16] Loss: 0.00368 +Epoch [2835/4000] Training [13/16] Loss: 0.00338 +Epoch [2835/4000] Training [14/16] Loss: 0.00291 +Epoch [2835/4000] Training [15/16] Loss: 0.00289 +Epoch [2835/4000] Training [16/16] Loss: 0.00298 +Epoch [2835/4000] Training metric {'Train/mean dice_metric': 0.9978947639465332, 'Train/mean miou_metric': 0.9955064058303833, 'Train/mean f1': 0.9928956031799316, 'Train/mean precision': 0.9881756901741028, 'Train/mean recall': 0.997660756111145, 'Train/mean hd95_metric': 0.859890878200531} +Epoch [2835/4000] Validation [1/4] Loss: 0.36115 focal_loss 0.29936 dice_loss 0.06179 +Epoch [2835/4000] Validation [2/4] Loss: 0.69495 focal_loss 0.47240 dice_loss 0.22255 +Epoch [2835/4000] Validation [3/4] Loss: 0.23870 focal_loss 0.18039 dice_loss 0.05831 +Epoch [2835/4000] Validation [4/4] Loss: 0.43304 focal_loss 0.31608 dice_loss 0.11697 +Epoch [2835/4000] Validation metric {'Val/mean dice_metric': 0.9747874140739441, 'Val/mean miou_metric': 0.9598973989486694, 'Val/mean f1': 0.9758133292198181, 'Val/mean precision': 0.9738100171089172, 'Val/mean recall': 0.977824866771698, 'Val/mean hd95_metric': 4.876393795013428} +Cheakpoint... +Epoch [2835/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747874140739441, 'Val/mean miou_metric': 0.9598973989486694, 'Val/mean f1': 0.9758133292198181, 'Val/mean precision': 0.9738100171089172, 'Val/mean recall': 0.977824866771698, 'Val/mean hd95_metric': 4.876393795013428} +Epoch [2836/4000] Training [1/16] Loss: 0.00332 +Epoch [2836/4000] Training [2/16] Loss: 0.00296 +Epoch [2836/4000] Training [3/16] Loss: 0.00496 +Epoch [2836/4000] Training [4/16] Loss: 0.00366 +Epoch [2836/4000] Training [5/16] Loss: 0.00349 +Epoch [2836/4000] Training [6/16] Loss: 0.00272 +Epoch [2836/4000] Training [7/16] Loss: 0.00406 +Epoch [2836/4000] Training [8/16] Loss: 0.00259 +Epoch [2836/4000] Training [9/16] Loss: 0.00281 +Epoch [2836/4000] Training [10/16] Loss: 0.00548 +Epoch [2836/4000] Training [11/16] Loss: 0.00291 +Epoch [2836/4000] Training [12/16] Loss: 0.00368 +Epoch [2836/4000] Training [13/16] Loss: 0.00391 +Epoch [2836/4000] Training [14/16] Loss: 0.00279 +Epoch [2836/4000] Training [15/16] Loss: 0.00327 +Epoch [2836/4000] Training [16/16] Loss: 0.00317 +Epoch [2836/4000] Training metric {'Train/mean dice_metric': 0.9979428052902222, 'Train/mean miou_metric': 0.9956200122833252, 'Train/mean f1': 0.9932209849357605, 'Train/mean precision': 0.9886778593063354, 'Train/mean recall': 0.9978058934211731, 'Train/mean hd95_metric': 0.8509065508842468} +Epoch [2836/4000] Validation [1/4] Loss: 0.35258 focal_loss 0.28991 dice_loss 0.06268 +Epoch [2836/4000] Validation [2/4] Loss: 1.27719 focal_loss 0.99836 dice_loss 0.27883 +Epoch [2836/4000] Validation [3/4] Loss: 0.42536 focal_loss 0.33532 dice_loss 0.09004 +Epoch [2836/4000] Validation [4/4] Loss: 0.32197 focal_loss 0.21494 dice_loss 0.10703 +Epoch [2836/4000] Validation metric {'Val/mean dice_metric': 0.9698748588562012, 'Val/mean miou_metric': 0.955924391746521, 'Val/mean f1': 0.9750627279281616, 'Val/mean precision': 0.9743975400924683, 'Val/mean recall': 0.9757288694381714, 'Val/mean hd95_metric': 5.236788272857666} +Cheakpoint... +Epoch [2836/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9699], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9698748588562012, 'Val/mean miou_metric': 0.955924391746521, 'Val/mean f1': 0.9750627279281616, 'Val/mean precision': 0.9743975400924683, 'Val/mean recall': 0.9757288694381714, 'Val/mean hd95_metric': 5.236788272857666} +Epoch [2837/4000] Training [1/16] Loss: 0.00427 +Epoch [2837/4000] Training [2/16] Loss: 0.00209 +Epoch [2837/4000] Training [3/16] Loss: 0.00301 +Epoch [2837/4000] Training [4/16] Loss: 0.00351 +Epoch [2837/4000] Training [5/16] Loss: 0.00302 +Epoch [2837/4000] Training [6/16] Loss: 0.00390 +Epoch [2837/4000] Training [7/16] Loss: 0.00425 +Epoch [2837/4000] Training [8/16] Loss: 0.00354 +Epoch [2837/4000] Training [9/16] Loss: 0.00534 +Epoch [2837/4000] Training [10/16] Loss: 0.00280 +Epoch [2837/4000] Training [11/16] Loss: 0.00328 +Epoch [2837/4000] Training [12/16] Loss: 0.00293 +Epoch [2837/4000] Training [13/16] Loss: 0.00446 +Epoch [2837/4000] Training [14/16] Loss: 0.00336 +Epoch [2837/4000] Training [15/16] Loss: 0.00398 +Epoch [2837/4000] Training [16/16] Loss: 0.00287 +Epoch [2837/4000] Training metric {'Train/mean dice_metric': 0.9980373978614807, 'Train/mean miou_metric': 0.9958077669143677, 'Train/mean f1': 0.9932869076728821, 'Train/mean precision': 0.9887496829032898, 'Train/mean recall': 0.9978660345077515, 'Train/mean hd95_metric': 0.8453679084777832} +Epoch [2837/4000] Validation [1/4] Loss: 0.40587 focal_loss 0.33970 dice_loss 0.06617 +Epoch [2837/4000] Validation [2/4] Loss: 0.51686 focal_loss 0.39117 dice_loss 0.12569 +Epoch [2837/4000] Validation [3/4] Loss: 0.43162 focal_loss 0.34375 dice_loss 0.08787 +Epoch [2837/4000] Validation [4/4] Loss: 0.45861 focal_loss 0.32050 dice_loss 0.13812 +Epoch [2837/4000] Validation metric {'Val/mean dice_metric': 0.9718053936958313, 'Val/mean miou_metric': 0.9573860168457031, 'Val/mean f1': 0.9750969409942627, 'Val/mean precision': 0.9736793041229248, 'Val/mean recall': 0.9765185117721558, 'Val/mean hd95_metric': 5.465210914611816} +Cheakpoint... +Epoch [2837/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718053936958313, 'Val/mean miou_metric': 0.9573860168457031, 'Val/mean f1': 0.9750969409942627, 'Val/mean precision': 0.9736793041229248, 'Val/mean recall': 0.9765185117721558, 'Val/mean hd95_metric': 5.465210914611816} +Epoch [2838/4000] Training [1/16] Loss: 0.00380 +Epoch [2838/4000] Training [2/16] Loss: 0.00433 +Epoch [2838/4000] Training [3/16] Loss: 0.00287 +Epoch [2838/4000] Training [4/16] Loss: 0.00302 +Epoch [2838/4000] Training [5/16] Loss: 0.00389 +Epoch [2838/4000] Training [6/16] Loss: 0.00484 +Epoch [2838/4000] Training [7/16] Loss: 0.00282 +Epoch [2838/4000] Training [8/16] Loss: 0.00233 +Epoch [2838/4000] Training [9/16] Loss: 0.00371 +Epoch [2838/4000] Training [10/16] Loss: 0.00354 +Epoch [2838/4000] Training [11/16] Loss: 0.00333 +Epoch [2838/4000] Training [12/16] Loss: 0.00378 +Epoch [2838/4000] Training [13/16] Loss: 0.00309 +Epoch [2838/4000] Training [14/16] Loss: 0.00382 +Epoch [2838/4000] Training [15/16] Loss: 0.00462 +Epoch [2838/4000] Training [16/16] Loss: 0.00285 +Epoch [2838/4000] Training metric {'Train/mean dice_metric': 0.9978095889091492, 'Train/mean miou_metric': 0.9953577518463135, 'Train/mean f1': 0.993043839931488, 'Train/mean precision': 0.9884911179542542, 'Train/mean recall': 0.9976386427879333, 'Train/mean hd95_metric': 0.8610986471176147} +Epoch [2838/4000] Validation [1/4] Loss: 0.32863 focal_loss 0.26837 dice_loss 0.06026 +Epoch [2838/4000] Validation [2/4] Loss: 0.51507 focal_loss 0.38990 dice_loss 0.12518 +Epoch [2838/4000] Validation [3/4] Loss: 0.41719 focal_loss 0.32066 dice_loss 0.09653 +Epoch [2838/4000] Validation [4/4] Loss: 0.42569 focal_loss 0.30120 dice_loss 0.12449 +Epoch [2838/4000] Validation metric {'Val/mean dice_metric': 0.9735497236251831, 'Val/mean miou_metric': 0.9588448405265808, 'Val/mean f1': 0.9760019183158875, 'Val/mean precision': 0.9742186069488525, 'Val/mean recall': 0.9777919054031372, 'Val/mean hd95_metric': 5.383048057556152} +Cheakpoint... +Epoch [2838/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735497236251831, 'Val/mean miou_metric': 0.9588448405265808, 'Val/mean f1': 0.9760019183158875, 'Val/mean precision': 0.9742186069488525, 'Val/mean recall': 0.9777919054031372, 'Val/mean hd95_metric': 5.383048057556152} +Epoch [2839/4000] Training [1/16] Loss: 0.00442 +Epoch [2839/4000] Training [2/16] Loss: 0.00294 +Epoch [2839/4000] Training [3/16] Loss: 0.00551 +Epoch [2839/4000] Training [4/16] Loss: 0.00395 +Epoch [2839/4000] Training [5/16] Loss: 0.00292 +Epoch [2839/4000] Training [6/16] Loss: 0.00342 +Epoch [2839/4000] Training [7/16] Loss: 0.00272 +Epoch [2839/4000] Training [8/16] Loss: 0.00442 +Epoch [2839/4000] Training [9/16] Loss: 0.00449 +Epoch [2839/4000] Training [10/16] Loss: 0.00441 +Epoch [2839/4000] Training [11/16] Loss: 0.00465 +Epoch [2839/4000] Training [12/16] Loss: 0.00351 +Epoch [2839/4000] Training [13/16] Loss: 0.00390 +Epoch [2839/4000] Training [14/16] Loss: 0.00362 +Epoch [2839/4000] Training [15/16] Loss: 0.00258 +Epoch [2839/4000] Training [16/16] Loss: 0.00267 +Epoch [2839/4000] Training metric {'Train/mean dice_metric': 0.9978156685829163, 'Train/mean miou_metric': 0.9953417181968689, 'Train/mean f1': 0.992609441280365, 'Train/mean precision': 0.9876009821891785, 'Train/mean recall': 0.9976690411567688, 'Train/mean hd95_metric': 0.8684135675430298} +Epoch [2839/4000] Validation [1/4] Loss: 0.33037 focal_loss 0.27161 dice_loss 0.05876 +Epoch [2839/4000] Validation [2/4] Loss: 0.49536 focal_loss 0.37487 dice_loss 0.12049 +Epoch [2839/4000] Validation [3/4] Loss: 0.24205 focal_loss 0.18351 dice_loss 0.05854 +Epoch [2839/4000] Validation [4/4] Loss: 0.27076 focal_loss 0.18750 dice_loss 0.08326 +Epoch [2839/4000] Validation metric {'Val/mean dice_metric': 0.973537802696228, 'Val/mean miou_metric': 0.9596745371818542, 'Val/mean f1': 0.9760518670082092, 'Val/mean precision': 0.9734358191490173, 'Val/mean recall': 0.9786820411682129, 'Val/mean hd95_metric': 4.691258430480957} +Cheakpoint... +Epoch [2839/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973537802696228, 'Val/mean miou_metric': 0.9596745371818542, 'Val/mean f1': 0.9760518670082092, 'Val/mean precision': 0.9734358191490173, 'Val/mean recall': 0.9786820411682129, 'Val/mean hd95_metric': 4.691258430480957} +Epoch [2840/4000] Training [1/16] Loss: 0.00409 +Epoch [2840/4000] Training [2/16] Loss: 0.00248 +Epoch [2840/4000] Training [3/16] Loss: 0.00401 +Epoch [2840/4000] Training [4/16] Loss: 0.00312 +Epoch [2840/4000] Training [5/16] Loss: 0.00313 +Epoch [2840/4000] Training [6/16] Loss: 0.00346 +Epoch [2840/4000] Training [7/16] Loss: 0.00461 +Epoch [2840/4000] Training [8/16] Loss: 0.00324 +Epoch [2840/4000] Training [9/16] Loss: 0.00776 +Epoch [2840/4000] Training [10/16] Loss: 0.00301 +Epoch [2840/4000] Training [11/16] Loss: 0.00440 +Epoch [2840/4000] Training [12/16] Loss: 0.00412 +Epoch [2840/4000] Training [13/16] Loss: 0.00325 +Epoch [2840/4000] Training [14/16] Loss: 0.00428 +Epoch [2840/4000] Training [15/16] Loss: 0.00321 +Epoch [2840/4000] Training [16/16] Loss: 0.00336 +Epoch [2840/4000] Training metric {'Train/mean dice_metric': 0.9978491067886353, 'Train/mean miou_metric': 0.9954365491867065, 'Train/mean f1': 0.9931047558784485, 'Train/mean precision': 0.9885507822036743, 'Train/mean recall': 0.9977008104324341, 'Train/mean hd95_metric': 0.8440989255905151} +Epoch [2840/4000] Validation [1/4] Loss: 0.46045 focal_loss 0.37287 dice_loss 0.08758 +Epoch [2840/4000] Validation [2/4] Loss: 0.53984 focal_loss 0.41164 dice_loss 0.12820 +Epoch [2840/4000] Validation [3/4] Loss: 0.44545 focal_loss 0.35738 dice_loss 0.08808 +Epoch [2840/4000] Validation [4/4] Loss: 0.33105 focal_loss 0.23594 dice_loss 0.09511 +Epoch [2840/4000] Validation metric {'Val/mean dice_metric': 0.9719164967536926, 'Val/mean miou_metric': 0.9574413299560547, 'Val/mean f1': 0.9754577875137329, 'Val/mean precision': 0.9742890000343323, 'Val/mean recall': 0.9766293168067932, 'Val/mean hd95_metric': 5.439924716949463} +Cheakpoint... +Epoch [2840/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719164967536926, 'Val/mean miou_metric': 0.9574413299560547, 'Val/mean f1': 0.9754577875137329, 'Val/mean precision': 0.9742890000343323, 'Val/mean recall': 0.9766293168067932, 'Val/mean hd95_metric': 5.439924716949463} +Epoch [2841/4000] Training [1/16] Loss: 0.00222 +Epoch [2841/4000] Training [2/16] Loss: 0.00417 +Epoch [2841/4000] Training [3/16] Loss: 0.00582 +Epoch [2841/4000] Training [4/16] Loss: 0.00381 +Epoch [2841/4000] Training [5/16] Loss: 0.00418 +Epoch [2841/4000] Training [6/16] Loss: 0.00305 +Epoch [2841/4000] Training [7/16] Loss: 0.00292 +Epoch [2841/4000] Training [8/16] Loss: 0.00405 +Epoch [2841/4000] Training [9/16] Loss: 0.00467 +Epoch [2841/4000] Training [10/16] Loss: 0.00313 +Epoch [2841/4000] Training [11/16] Loss: 0.00341 +Epoch [2841/4000] Training [12/16] Loss: 0.00339 +Epoch [2841/4000] Training [13/16] Loss: 0.00401 +Epoch [2841/4000] Training [14/16] Loss: 0.00361 +Epoch [2841/4000] Training [15/16] Loss: 0.00443 +Epoch [2841/4000] Training [16/16] Loss: 0.00332 +Epoch [2841/4000] Training metric {'Train/mean dice_metric': 0.9976696372032166, 'Train/mean miou_metric': 0.9950743913650513, 'Train/mean f1': 0.9929671287536621, 'Train/mean precision': 0.9884273409843445, 'Train/mean recall': 0.9975488185882568, 'Train/mean hd95_metric': 0.8830209970474243} +Epoch [2841/4000] Validation [1/4] Loss: 0.37323 focal_loss 0.30874 dice_loss 0.06449 +Epoch [2841/4000] Validation [2/4] Loss: 0.55410 focal_loss 0.42627 dice_loss 0.12782 +Epoch [2841/4000] Validation [3/4] Loss: 0.25461 focal_loss 0.19499 dice_loss 0.05962 +Epoch [2841/4000] Validation [4/4] Loss: 0.31188 focal_loss 0.22250 dice_loss 0.08938 +Epoch [2841/4000] Validation metric {'Val/mean dice_metric': 0.9729821085929871, 'Val/mean miou_metric': 0.9583839178085327, 'Val/mean f1': 0.9752317667007446, 'Val/mean precision': 0.9733908772468567, 'Val/mean recall': 0.9770795702934265, 'Val/mean hd95_metric': 5.215387344360352} +Cheakpoint... +Epoch [2841/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729821085929871, 'Val/mean miou_metric': 0.9583839178085327, 'Val/mean f1': 0.9752317667007446, 'Val/mean precision': 0.9733908772468567, 'Val/mean recall': 0.9770795702934265, 'Val/mean hd95_metric': 5.215387344360352} +Epoch [2842/4000] Training [1/16] Loss: 0.00472 +Epoch [2842/4000] Training [2/16] Loss: 0.00296 +Epoch [2842/4000] Training [3/16] Loss: 0.00386 +Epoch [2842/4000] Training [4/16] Loss: 0.00387 +Epoch [2842/4000] Training [5/16] Loss: 0.00428 +Epoch [2842/4000] Training [6/16] Loss: 0.00280 +Epoch [2842/4000] Training [7/16] Loss: 0.00367 +Epoch [2842/4000] Training [8/16] Loss: 0.00408 +Epoch [2842/4000] Training [9/16] Loss: 0.00290 +Epoch [2842/4000] Training [10/16] Loss: 0.00416 +Epoch [2842/4000] Training [11/16] Loss: 0.00248 +Epoch [2842/4000] Training [12/16] Loss: 0.00384 +Epoch [2842/4000] Training [13/16] Loss: 0.00275 +Epoch [2842/4000] Training [14/16] Loss: 0.00445 +Epoch [2842/4000] Training [15/16] Loss: 0.00361 +Epoch [2842/4000] Training [16/16] Loss: 0.00404 +Epoch [2842/4000] Training metric {'Train/mean dice_metric': 0.9977731704711914, 'Train/mean miou_metric': 0.9952675700187683, 'Train/mean f1': 0.9928116798400879, 'Train/mean precision': 0.9880356788635254, 'Train/mean recall': 0.9976341128349304, 'Train/mean hd95_metric': 0.834918737411499} +Epoch [2842/4000] Validation [1/4] Loss: 0.31046 focal_loss 0.25295 dice_loss 0.05752 +Epoch [2842/4000] Validation [2/4] Loss: 0.56134 focal_loss 0.43232 dice_loss 0.12903 +Epoch [2842/4000] Validation [3/4] Loss: 0.47298 focal_loss 0.37734 dice_loss 0.09565 +Epoch [2842/4000] Validation [4/4] Loss: 0.27654 focal_loss 0.19629 dice_loss 0.08025 +Epoch [2842/4000] Validation metric {'Val/mean dice_metric': 0.9727848172187805, 'Val/mean miou_metric': 0.9586588144302368, 'Val/mean f1': 0.9757647514343262, 'Val/mean precision': 0.9734587669372559, 'Val/mean recall': 0.9780817627906799, 'Val/mean hd95_metric': 5.2849650382995605} +Cheakpoint... +Epoch [2842/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727848172187805, 'Val/mean miou_metric': 0.9586588144302368, 'Val/mean f1': 0.9757647514343262, 'Val/mean precision': 0.9734587669372559, 'Val/mean recall': 0.9780817627906799, 'Val/mean hd95_metric': 5.2849650382995605} +Epoch [2843/4000] Training [1/16] Loss: 0.00618 +Epoch [2843/4000] Training [2/16] Loss: 0.00402 +Epoch [2843/4000] Training [3/16] Loss: 0.00304 +Epoch [2843/4000] Training [4/16] Loss: 0.00664 +Epoch [2843/4000] Training [5/16] Loss: 0.00443 +Epoch [2843/4000] Training [6/16] Loss: 0.00338 +Epoch [2843/4000] Training [7/16] Loss: 0.00247 +Epoch [2843/4000] Training [8/16] Loss: 0.00358 +Epoch [2843/4000] Training [9/16] Loss: 0.00251 +Epoch [2843/4000] Training [10/16] Loss: 0.00394 +Epoch [2843/4000] Training [11/16] Loss: 0.00310 +Epoch [2843/4000] Training [12/16] Loss: 0.00293 +Epoch [2843/4000] Training [13/16] Loss: 0.00330 +Epoch [2843/4000] Training [14/16] Loss: 0.00231 +Epoch [2843/4000] Training [15/16] Loss: 0.00321 +Epoch [2843/4000] Training [16/16] Loss: 0.00297 +Epoch [2843/4000] Training metric {'Train/mean dice_metric': 0.9978041648864746, 'Train/mean miou_metric': 0.9953410029411316, 'Train/mean f1': 0.99303138256073, 'Train/mean precision': 0.9884651303291321, 'Train/mean recall': 0.9976400136947632, 'Train/mean hd95_metric': 0.8543379306793213} +Epoch [2843/4000] Validation [1/4] Loss: 0.32591 focal_loss 0.26538 dice_loss 0.06053 +Epoch [2843/4000] Validation [2/4] Loss: 0.50155 focal_loss 0.37218 dice_loss 0.12937 +Epoch [2843/4000] Validation [3/4] Loss: 0.24308 focal_loss 0.18537 dice_loss 0.05771 +Epoch [2843/4000] Validation [4/4] Loss: 0.38007 focal_loss 0.27844 dice_loss 0.10163 +Epoch [2843/4000] Validation metric {'Val/mean dice_metric': 0.972751259803772, 'Val/mean miou_metric': 0.958544135093689, 'Val/mean f1': 0.9762940406799316, 'Val/mean precision': 0.9752377867698669, 'Val/mean recall': 0.9773526787757874, 'Val/mean hd95_metric': 4.735602378845215} +Cheakpoint... +Epoch [2843/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972751259803772, 'Val/mean miou_metric': 0.958544135093689, 'Val/mean f1': 0.9762940406799316, 'Val/mean precision': 0.9752377867698669, 'Val/mean recall': 0.9773526787757874, 'Val/mean hd95_metric': 4.735602378845215} +Epoch [2844/4000] Training [1/16] Loss: 0.00390 +Epoch [2844/4000] Training [2/16] Loss: 0.00305 +Epoch [2844/4000] Training [3/16] Loss: 0.00351 +Epoch [2844/4000] Training [4/16] Loss: 0.00249 +Epoch [2844/4000] Training [5/16] Loss: 0.00287 +Epoch [2844/4000] Training [6/16] Loss: 0.00258 +Epoch [2844/4000] Training [7/16] Loss: 0.00377 +Epoch [2844/4000] Training [8/16] Loss: 0.00360 +Epoch [2844/4000] Training [9/16] Loss: 0.00299 +Epoch [2844/4000] Training [10/16] Loss: 0.00301 +Epoch [2844/4000] Training [11/16] Loss: 0.00364 +Epoch [2844/4000] Training [12/16] Loss: 0.00334 +Epoch [2844/4000] Training [13/16] Loss: 0.00417 +Epoch [2844/4000] Training [14/16] Loss: 0.00308 +Epoch [2844/4000] Training [15/16] Loss: 0.00297 +Epoch [2844/4000] Training [16/16] Loss: 0.00452 +Epoch [2844/4000] Training metric {'Train/mean dice_metric': 0.9979255199432373, 'Train/mean miou_metric': 0.995569109916687, 'Train/mean f1': 0.9929746985435486, 'Train/mean precision': 0.9882241487503052, 'Train/mean recall': 0.997771143913269, 'Train/mean hd95_metric': 0.8418245911598206} +Epoch [2844/4000] Validation [1/4] Loss: 0.33544 focal_loss 0.27188 dice_loss 0.06356 +Epoch [2844/4000] Validation [2/4] Loss: 0.49095 focal_loss 0.36941 dice_loss 0.12155 +Epoch [2844/4000] Validation [3/4] Loss: 0.48221 focal_loss 0.37982 dice_loss 0.10239 +Epoch [2844/4000] Validation [4/4] Loss: 0.25455 focal_loss 0.16999 dice_loss 0.08456 +Epoch [2844/4000] Validation metric {'Val/mean dice_metric': 0.9719290733337402, 'Val/mean miou_metric': 0.9574733972549438, 'Val/mean f1': 0.9748876690864563, 'Val/mean precision': 0.9735029935836792, 'Val/mean recall': 0.9762762188911438, 'Val/mean hd95_metric': 5.137976169586182} +Cheakpoint... +Epoch [2844/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719290733337402, 'Val/mean miou_metric': 0.9574733972549438, 'Val/mean f1': 0.9748876690864563, 'Val/mean precision': 0.9735029935836792, 'Val/mean recall': 0.9762762188911438, 'Val/mean hd95_metric': 5.137976169586182} +Epoch [2845/4000] Training [1/16] Loss: 0.00303 +Epoch [2845/4000] Training [2/16] Loss: 0.00343 +Epoch [2845/4000] Training [3/16] Loss: 0.00278 +Epoch [2845/4000] Training [4/16] Loss: 0.00518 +Epoch [2845/4000] Training [5/16] Loss: 0.00373 +Epoch [2845/4000] Training [6/16] Loss: 0.00445 +Epoch [2845/4000] Training [7/16] Loss: 0.00369 +Epoch [2845/4000] Training [8/16] Loss: 0.00390 +Epoch [2845/4000] Training [9/16] Loss: 0.00421 +Epoch [2845/4000] Training [10/16] Loss: 0.00313 +Epoch [2845/4000] Training [11/16] Loss: 0.00333 +Epoch [2845/4000] Training [12/16] Loss: 0.01721 +Epoch [2845/4000] Training [13/16] Loss: 0.00314 +Epoch [2845/4000] Training [14/16] Loss: 0.00328 +Epoch [2845/4000] Training [15/16] Loss: 0.00303 +Epoch [2845/4000] Training [16/16] Loss: 0.00310 +Epoch [2845/4000] Training metric {'Train/mean dice_metric': 0.9978033900260925, 'Train/mean miou_metric': 0.9953517913818359, 'Train/mean f1': 0.993100106716156, 'Train/mean precision': 0.9886173009872437, 'Train/mean recall': 0.9976236820220947, 'Train/mean hd95_metric': 0.8793133497238159} +Epoch [2845/4000] Validation [1/4] Loss: 0.33269 focal_loss 0.27283 dice_loss 0.05986 +Epoch [2845/4000] Validation [2/4] Loss: 0.47980 focal_loss 0.35543 dice_loss 0.12437 +Epoch [2845/4000] Validation [3/4] Loss: 0.50311 focal_loss 0.40739 dice_loss 0.09572 +Epoch [2845/4000] Validation [4/4] Loss: 0.27848 focal_loss 0.19930 dice_loss 0.07918 +Epoch [2845/4000] Validation metric {'Val/mean dice_metric': 0.9734350442886353, 'Val/mean miou_metric': 0.9589172601699829, 'Val/mean f1': 0.9759330749511719, 'Val/mean precision': 0.9732949733734131, 'Val/mean recall': 0.9785854816436768, 'Val/mean hd95_metric': 5.162732124328613} +Cheakpoint... +Epoch [2845/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734350442886353, 'Val/mean miou_metric': 0.9589172601699829, 'Val/mean f1': 0.9759330749511719, 'Val/mean precision': 0.9732949733734131, 'Val/mean recall': 0.9785854816436768, 'Val/mean hd95_metric': 5.162732124328613} +Epoch [2846/4000] Training [1/16] Loss: 0.00459 +Epoch [2846/4000] Training [2/16] Loss: 0.00295 +Epoch [2846/4000] Training [3/16] Loss: 0.00365 +Epoch [2846/4000] Training [4/16] Loss: 0.00459 +Epoch [2846/4000] Training [5/16] Loss: 0.00244 +Epoch [2846/4000] Training [6/16] Loss: 0.00446 +Epoch [2846/4000] Training [7/16] Loss: 0.00322 +Epoch [2846/4000] Training [8/16] Loss: 0.00399 +Epoch [2846/4000] Training [9/16] Loss: 0.00331 +Epoch [2846/4000] Training [10/16] Loss: 0.00284 +Epoch [2846/4000] Training [11/16] Loss: 0.00429 +Epoch [2846/4000] Training [12/16] Loss: 0.00335 +Epoch [2846/4000] Training [13/16] Loss: 0.00424 +Epoch [2846/4000] Training [14/16] Loss: 0.00243 +Epoch [2846/4000] Training [15/16] Loss: 0.00281 +Epoch [2846/4000] Training [16/16] Loss: 0.00330 +Epoch [2846/4000] Training metric {'Train/mean dice_metric': 0.9979978203773499, 'Train/mean miou_metric': 0.9957255125045776, 'Train/mean f1': 0.9931641817092896, 'Train/mean precision': 0.9886019229888916, 'Train/mean recall': 0.9977689385414124, 'Train/mean hd95_metric': 0.82737135887146} +Epoch [2846/4000] Validation [1/4] Loss: 0.38127 focal_loss 0.32059 dice_loss 0.06068 +Epoch [2846/4000] Validation [2/4] Loss: 0.40490 focal_loss 0.29468 dice_loss 0.11023 +Epoch [2846/4000] Validation [3/4] Loss: 0.48734 focal_loss 0.39621 dice_loss 0.09113 +Epoch [2846/4000] Validation [4/4] Loss: 0.39260 focal_loss 0.28000 dice_loss 0.11260 +Epoch [2846/4000] Validation metric {'Val/mean dice_metric': 0.9738607406616211, 'Val/mean miou_metric': 0.959153950214386, 'Val/mean f1': 0.9763336181640625, 'Val/mean precision': 0.9728505611419678, 'Val/mean recall': 0.9798418283462524, 'Val/mean hd95_metric': 5.014042854309082} +Cheakpoint... +Epoch [2846/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738607406616211, 'Val/mean miou_metric': 0.959153950214386, 'Val/mean f1': 0.9763336181640625, 'Val/mean precision': 0.9728505611419678, 'Val/mean recall': 0.9798418283462524, 'Val/mean hd95_metric': 5.014042854309082} +Epoch [2847/4000] Training [1/16] Loss: 0.00355 +Epoch [2847/4000] Training [2/16] Loss: 0.00374 +Epoch [2847/4000] Training [3/16] Loss: 0.00296 +Epoch [2847/4000] Training [4/16] Loss: 0.00322 +Epoch [2847/4000] Training [5/16] Loss: 0.00376 +Epoch [2847/4000] Training [6/16] Loss: 0.00459 +Epoch [2847/4000] Training [7/16] Loss: 0.00274 +Epoch [2847/4000] Training [8/16] Loss: 0.00324 +Epoch [2847/4000] Training [9/16] Loss: 0.00209 +Epoch [2847/4000] Training [10/16] Loss: 0.00363 +Epoch [2847/4000] Training [11/16] Loss: 0.00398 +Epoch [2847/4000] Training [12/16] Loss: 0.00301 +Epoch [2847/4000] Training [13/16] Loss: 0.00360 +Epoch [2847/4000] Training [14/16] Loss: 0.00339 +Epoch [2847/4000] Training [15/16] Loss: 0.00297 +Epoch [2847/4000] Training [16/16] Loss: 0.00362 +Epoch [2847/4000] Training metric {'Train/mean dice_metric': 0.9980218410491943, 'Train/mean miou_metric': 0.9957692623138428, 'Train/mean f1': 0.9931491613388062, 'Train/mean precision': 0.9885570406913757, 'Train/mean recall': 0.9977841377258301, 'Train/mean hd95_metric': 0.8240788578987122} +Epoch [2847/4000] Validation [1/4] Loss: 0.41775 focal_loss 0.35134 dice_loss 0.06642 +Epoch [2847/4000] Validation [2/4] Loss: 0.43318 focal_loss 0.31911 dice_loss 0.11407 +Epoch [2847/4000] Validation [3/4] Loss: 0.25109 focal_loss 0.18960 dice_loss 0.06149 +Epoch [2847/4000] Validation [4/4] Loss: 0.34007 focal_loss 0.23383 dice_loss 0.10624 +Epoch [2847/4000] Validation metric {'Val/mean dice_metric': 0.9727622866630554, 'Val/mean miou_metric': 0.9587833285331726, 'Val/mean f1': 0.9759364128112793, 'Val/mean precision': 0.9728745818138123, 'Val/mean recall': 0.9790176749229431, 'Val/mean hd95_metric': 4.9873223304748535} +Cheakpoint... +Epoch [2847/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727622866630554, 'Val/mean miou_metric': 0.9587833285331726, 'Val/mean f1': 0.9759364128112793, 'Val/mean precision': 0.9728745818138123, 'Val/mean recall': 0.9790176749229431, 'Val/mean hd95_metric': 4.9873223304748535} +Epoch [2848/4000] Training [1/16] Loss: 0.00354 +Epoch [2848/4000] Training [2/16] Loss: 0.00517 +Epoch [2848/4000] Training [3/16] Loss: 0.00431 +Epoch [2848/4000] Training [4/16] Loss: 0.00368 +Epoch [2848/4000] Training [5/16] Loss: 0.00516 +Epoch [2848/4000] Training [6/16] Loss: 0.00403 +Epoch [2848/4000] Training [7/16] Loss: 0.00308 +Epoch [2848/4000] Training [8/16] Loss: 0.00307 +Epoch [2848/4000] Training [9/16] Loss: 0.00246 +Epoch [2848/4000] Training [10/16] Loss: 0.00328 +Epoch [2848/4000] Training [11/16] Loss: 0.00299 +Epoch [2848/4000] Training [12/16] Loss: 0.00280 +Epoch [2848/4000] Training [13/16] Loss: 0.00317 +Epoch [2848/4000] Training [14/16] Loss: 0.00259 +Epoch [2848/4000] Training [15/16] Loss: 0.00328 +Epoch [2848/4000] Training [16/16] Loss: 0.00463 +Epoch [2848/4000] Training metric {'Train/mean dice_metric': 0.9978547096252441, 'Train/mean miou_metric': 0.9954168796539307, 'Train/mean f1': 0.9929187297821045, 'Train/mean precision': 0.9882062077522278, 'Train/mean recall': 0.997676432132721, 'Train/mean hd95_metric': 0.8413916230201721} +Epoch [2848/4000] Validation [1/4] Loss: 0.40647 focal_loss 0.34226 dice_loss 0.06420 +Epoch [2848/4000] Validation [2/4] Loss: 0.68385 focal_loss 0.50544 dice_loss 0.17841 +Epoch [2848/4000] Validation [3/4] Loss: 0.49725 focal_loss 0.40062 dice_loss 0.09663 +Epoch [2848/4000] Validation [4/4] Loss: 0.43680 focal_loss 0.30541 dice_loss 0.13139 +Epoch [2848/4000] Validation metric {'Val/mean dice_metric': 0.9727588891983032, 'Val/mean miou_metric': 0.9581385850906372, 'Val/mean f1': 0.9751322865486145, 'Val/mean precision': 0.9733659625053406, 'Val/mean recall': 0.9769049882888794, 'Val/mean hd95_metric': 5.421113014221191} +Cheakpoint... +Epoch [2848/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727588891983032, 'Val/mean miou_metric': 0.9581385850906372, 'Val/mean f1': 0.9751322865486145, 'Val/mean precision': 0.9733659625053406, 'Val/mean recall': 0.9769049882888794, 'Val/mean hd95_metric': 5.421113014221191} +Epoch [2849/4000] Training [1/16] Loss: 0.00452 +Epoch [2849/4000] Training [2/16] Loss: 0.00412 +Epoch [2849/4000] Training [3/16] Loss: 0.00312 +Epoch [2849/4000] Training [4/16] Loss: 0.00428 +Epoch [2849/4000] Training [5/16] Loss: 0.00282 +Epoch [2849/4000] Training [6/16] Loss: 0.00361 +Epoch [2849/4000] Training [7/16] Loss: 0.00291 +Epoch [2849/4000] Training [8/16] Loss: 0.00314 +Epoch [2849/4000] Training [9/16] Loss: 0.00491 +Epoch [2849/4000] Training [10/16] Loss: 0.00402 +Epoch [2849/4000] Training [11/16] Loss: 0.00263 +Epoch [2849/4000] Training [12/16] Loss: 0.00413 +Epoch [2849/4000] Training [13/16] Loss: 0.00399 +Epoch [2849/4000] Training [14/16] Loss: 0.00520 +Epoch [2849/4000] Training [15/16] Loss: 0.00207 +Epoch [2849/4000] Training [16/16] Loss: 0.00405 +Epoch [2849/4000] Training metric {'Train/mean dice_metric': 0.9979193210601807, 'Train/mean miou_metric': 0.9955724477767944, 'Train/mean f1': 0.9931191802024841, 'Train/mean precision': 0.9885174632072449, 'Train/mean recall': 0.9977639317512512, 'Train/mean hd95_metric': 0.8421651124954224} +Epoch [2849/4000] Validation [1/4] Loss: 0.32695 focal_loss 0.26896 dice_loss 0.05799 +Epoch [2849/4000] Validation [2/4] Loss: 0.58522 focal_loss 0.44820 dice_loss 0.13702 +Epoch [2849/4000] Validation [3/4] Loss: 0.23183 focal_loss 0.17809 dice_loss 0.05375 +Epoch [2849/4000] Validation [4/4] Loss: 0.27571 focal_loss 0.19548 dice_loss 0.08023 +Epoch [2849/4000] Validation metric {'Val/mean dice_metric': 0.9762055277824402, 'Val/mean miou_metric': 0.9616525769233704, 'Val/mean f1': 0.976619303226471, 'Val/mean precision': 0.9737992882728577, 'Val/mean recall': 0.9794555306434631, 'Val/mean hd95_metric': 4.864092826843262} +Cheakpoint... +Epoch [2849/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9762055277824402, 'Val/mean miou_metric': 0.9616525769233704, 'Val/mean f1': 0.976619303226471, 'Val/mean precision': 0.9737992882728577, 'Val/mean recall': 0.9794555306434631, 'Val/mean hd95_metric': 4.864092826843262} +Epoch [2850/4000] Training [1/16] Loss: 0.00336 +Epoch [2850/4000] Training [2/16] Loss: 0.00309 +Epoch [2850/4000] Training [3/16] Loss: 0.00317 +Epoch [2850/4000] Training [4/16] Loss: 0.00432 +Epoch [2850/4000] Training [5/16] Loss: 0.00379 +Epoch [2850/4000] Training [6/16] Loss: 0.00256 +Epoch [2850/4000] Training [7/16] Loss: 0.00404 +Epoch [2850/4000] Training [8/16] Loss: 0.00373 +Epoch [2850/4000] Training [9/16] Loss: 0.00305 +Epoch [2850/4000] Training [10/16] Loss: 0.00337 +Epoch [2850/4000] Training [11/16] Loss: 0.00320 +Epoch [2850/4000] Training [12/16] Loss: 0.00281 +Epoch [2850/4000] Training [13/16] Loss: 0.00367 +Epoch [2850/4000] Training [14/16] Loss: 0.00236 +Epoch [2850/4000] Training [15/16] Loss: 0.00445 +Epoch [2850/4000] Training [16/16] Loss: 0.00213 +Epoch [2850/4000] Training metric {'Train/mean dice_metric': 0.9981004595756531, 'Train/mean miou_metric': 0.9959276914596558, 'Train/mean f1': 0.9931780099868774, 'Train/mean precision': 0.9885598421096802, 'Train/mean recall': 0.9978395104408264, 'Train/mean hd95_metric': 0.8006413578987122} +Epoch [2850/4000] Validation [1/4] Loss: 0.33582 focal_loss 0.27380 dice_loss 0.06202 +Epoch [2850/4000] Validation [2/4] Loss: 0.86326 focal_loss 0.66473 dice_loss 0.19853 +Epoch [2850/4000] Validation [3/4] Loss: 0.44182 focal_loss 0.35552 dice_loss 0.08630 +Epoch [2850/4000] Validation [4/4] Loss: 0.29720 focal_loss 0.20618 dice_loss 0.09102 +Epoch [2850/4000] Validation metric {'Val/mean dice_metric': 0.9731656908988953, 'Val/mean miou_metric': 0.9590563774108887, 'Val/mean f1': 0.9754871726036072, 'Val/mean precision': 0.9724258780479431, 'Val/mean recall': 0.978567898273468, 'Val/mean hd95_metric': 5.242819309234619} +Cheakpoint... +Epoch [2850/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731656908988953, 'Val/mean miou_metric': 0.9590563774108887, 'Val/mean f1': 0.9754871726036072, 'Val/mean precision': 0.9724258780479431, 'Val/mean recall': 0.978567898273468, 'Val/mean hd95_metric': 5.242819309234619} +Epoch [2851/4000] Training [1/16] Loss: 0.00298 +Epoch [2851/4000] Training [2/16] Loss: 0.00242 +Epoch [2851/4000] Training [3/16] Loss: 0.00310 +Epoch [2851/4000] Training [4/16] Loss: 0.00231 +Epoch [2851/4000] Training [5/16] Loss: 0.00380 +Epoch [2851/4000] Training [6/16] Loss: 0.00392 +Epoch [2851/4000] Training [7/16] Loss: 0.00322 +Epoch [2851/4000] Training [8/16] Loss: 0.00402 +Epoch [2851/4000] Training [9/16] Loss: 0.00379 +Epoch [2851/4000] Training [10/16] Loss: 0.00333 +Epoch [2851/4000] Training [11/16] Loss: 0.00324 +Epoch [2851/4000] Training [12/16] Loss: 0.00277 +Epoch [2851/4000] Training [13/16] Loss: 0.00327 +Epoch [2851/4000] Training [14/16] Loss: 0.00316 +Epoch [2851/4000] Training [15/16] Loss: 0.00271 +Epoch [2851/4000] Training [16/16] Loss: 0.00330 +Epoch [2851/4000] Training metric {'Train/mean dice_metric': 0.9980258941650391, 'Train/mean miou_metric': 0.9957865476608276, 'Train/mean f1': 0.9932693839073181, 'Train/mean precision': 0.988699734210968, 'Train/mean recall': 0.9978814125061035, 'Train/mean hd95_metric': 0.81076979637146} +Epoch [2851/4000] Validation [1/4] Loss: 0.32496 focal_loss 0.26258 dice_loss 0.06238 +Epoch [2851/4000] Validation [2/4] Loss: 0.60675 focal_loss 0.47491 dice_loss 0.13184 +Epoch [2851/4000] Validation [3/4] Loss: 0.45553 focal_loss 0.36503 dice_loss 0.09050 +Epoch [2851/4000] Validation [4/4] Loss: 0.33955 focal_loss 0.23402 dice_loss 0.10553 +Epoch [2851/4000] Validation metric {'Val/mean dice_metric': 0.9727751016616821, 'Val/mean miou_metric': 0.9586044549942017, 'Val/mean f1': 0.9761452078819275, 'Val/mean precision': 0.9746752381324768, 'Val/mean recall': 0.9776197075843811, 'Val/mean hd95_metric': 5.2651495933532715} +Cheakpoint... +Epoch [2851/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727751016616821, 'Val/mean miou_metric': 0.9586044549942017, 'Val/mean f1': 0.9761452078819275, 'Val/mean precision': 0.9746752381324768, 'Val/mean recall': 0.9776197075843811, 'Val/mean hd95_metric': 5.2651495933532715} +Epoch [2852/4000] Training [1/16] Loss: 0.00354 +Epoch [2852/4000] Training [2/16] Loss: 0.00449 +Epoch [2852/4000] Training [3/16] Loss: 0.00334 +Epoch [2852/4000] Training [4/16] Loss: 0.00306 +Epoch [2852/4000] Training [5/16] Loss: 0.00263 +Epoch [2852/4000] Training [6/16] Loss: 0.00377 +Epoch [2852/4000] Training [7/16] Loss: 0.00252 +Epoch [2852/4000] Training [8/16] Loss: 0.00470 +Epoch [2852/4000] Training [9/16] Loss: 0.00318 +Epoch [2852/4000] Training [10/16] Loss: 0.00233 +Epoch [2852/4000] Training [11/16] Loss: 0.00382 +Epoch [2852/4000] Training [12/16] Loss: 0.00352 +Epoch [2852/4000] Training [13/16] Loss: 0.00427 +Epoch [2852/4000] Training [14/16] Loss: 0.00304 +Epoch [2852/4000] Training [15/16] Loss: 0.00289 +Epoch [2852/4000] Training [16/16] Loss: 0.00393 +Epoch [2852/4000] Training metric {'Train/mean dice_metric': 0.9979391694068909, 'Train/mean miou_metric': 0.9956099390983582, 'Train/mean f1': 0.9932316541671753, 'Train/mean precision': 0.9886816740036011, 'Train/mean recall': 0.9978236556053162, 'Train/mean hd95_metric': 0.8411409854888916} +Epoch [2852/4000] Validation [1/4] Loss: 0.32599 focal_loss 0.26566 dice_loss 0.06032 +Epoch [2852/4000] Validation [2/4] Loss: 0.84473 focal_loss 0.65670 dice_loss 0.18804 +Epoch [2852/4000] Validation [3/4] Loss: 0.24447 focal_loss 0.18450 dice_loss 0.05997 +Epoch [2852/4000] Validation [4/4] Loss: 0.28595 focal_loss 0.20097 dice_loss 0.08498 +Epoch [2852/4000] Validation metric {'Val/mean dice_metric': 0.9729225039482117, 'Val/mean miou_metric': 0.9592592120170593, 'Val/mean f1': 0.9768146872520447, 'Val/mean precision': 0.9751509428024292, 'Val/mean recall': 0.9784840941429138, 'Val/mean hd95_metric': 4.833749771118164} +Cheakpoint... +Epoch [2852/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729225039482117, 'Val/mean miou_metric': 0.9592592120170593, 'Val/mean f1': 0.9768146872520447, 'Val/mean precision': 0.9751509428024292, 'Val/mean recall': 0.9784840941429138, 'Val/mean hd95_metric': 4.833749771118164} +Epoch [2853/4000] Training [1/16] Loss: 0.00400 +Epoch [2853/4000] Training [2/16] Loss: 0.00340 +Epoch [2853/4000] Training [3/16] Loss: 0.00561 +Epoch [2853/4000] Training [4/16] Loss: 0.00341 +Epoch [2853/4000] Training [5/16] Loss: 0.00286 +Epoch [2853/4000] Training [6/16] Loss: 0.00276 +Epoch [2853/4000] Training [7/16] Loss: 0.00258 +Epoch [2853/4000] Training [8/16] Loss: 0.00451 +Epoch [2853/4000] Training [9/16] Loss: 0.00480 +Epoch [2853/4000] Training [10/16] Loss: 0.00390 +Epoch [2853/4000] Training [11/16] Loss: 0.00382 +Epoch [2853/4000] Training [12/16] Loss: 0.00281 +Epoch [2853/4000] Training [13/16] Loss: 0.00356 +Epoch [2853/4000] Training [14/16] Loss: 0.00342 +Epoch [2853/4000] Training [15/16] Loss: 0.00313 +Epoch [2853/4000] Training [16/16] Loss: 0.00259 +Epoch [2853/4000] Training metric {'Train/mean dice_metric': 0.997943639755249, 'Train/mean miou_metric': 0.9956209659576416, 'Train/mean f1': 0.9930877089500427, 'Train/mean precision': 0.9885130524635315, 'Train/mean recall': 0.9977049231529236, 'Train/mean hd95_metric': 0.8691428899765015} +Epoch [2853/4000] Validation [1/4] Loss: 0.35202 focal_loss 0.28626 dice_loss 0.06577 +Epoch [2853/4000] Validation [2/4] Loss: 0.49457 focal_loss 0.36758 dice_loss 0.12699 +Epoch [2853/4000] Validation [3/4] Loss: 0.41536 focal_loss 0.32326 dice_loss 0.09211 +Epoch [2853/4000] Validation [4/4] Loss: 0.29177 focal_loss 0.19567 dice_loss 0.09610 +Epoch [2853/4000] Validation metric {'Val/mean dice_metric': 0.9738122820854187, 'Val/mean miou_metric': 0.9592379331588745, 'Val/mean f1': 0.9762762188911438, 'Val/mean precision': 0.9750048518180847, 'Val/mean recall': 0.9775509238243103, 'Val/mean hd95_metric': 4.827667236328125} +Cheakpoint... +Epoch [2853/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738122820854187, 'Val/mean miou_metric': 0.9592379331588745, 'Val/mean f1': 0.9762762188911438, 'Val/mean precision': 0.9750048518180847, 'Val/mean recall': 0.9775509238243103, 'Val/mean hd95_metric': 4.827667236328125} +Epoch [2854/4000] Training [1/16] Loss: 0.00329 +Epoch [2854/4000] Training [2/16] Loss: 0.00329 +Epoch [2854/4000] Training [3/16] Loss: 0.00244 +Epoch [2854/4000] Training [4/16] Loss: 0.00398 +Epoch [2854/4000] Training [5/16] Loss: 0.00331 +Epoch [2854/4000] Training [6/16] Loss: 0.00632 +Epoch [2854/4000] Training [7/16] Loss: 0.00298 +Epoch [2854/4000] Training [8/16] Loss: 0.00280 +Epoch [2854/4000] Training [9/16] Loss: 0.00281 +Epoch [2854/4000] Training [10/16] Loss: 0.00306 +Epoch [2854/4000] Training [11/16] Loss: 0.00319 +Epoch [2854/4000] Training [12/16] Loss: 0.00380 +Epoch [2854/4000] Training [13/16] Loss: 0.00322 +Epoch [2854/4000] Training [14/16] Loss: 0.00408 +Epoch [2854/4000] Training [15/16] Loss: 0.00437 +Epoch [2854/4000] Training [16/16] Loss: 0.00343 +Epoch [2854/4000] Training metric {'Train/mean dice_metric': 0.9978829622268677, 'Train/mean miou_metric': 0.9954919219017029, 'Train/mean f1': 0.9928655028343201, 'Train/mean precision': 0.9881284236907959, 'Train/mean recall': 0.9976482391357422, 'Train/mean hd95_metric': 0.8475162982940674} +Epoch [2854/4000] Validation [1/4] Loss: 0.32324 focal_loss 0.26502 dice_loss 0.05822 +Epoch [2854/4000] Validation [2/4] Loss: 0.96202 focal_loss 0.76181 dice_loss 0.20020 +Epoch [2854/4000] Validation [3/4] Loss: 0.24738 focal_loss 0.18969 dice_loss 0.05769 +Epoch [2854/4000] Validation [4/4] Loss: 0.30870 focal_loss 0.21721 dice_loss 0.09149 +Epoch [2854/4000] Validation metric {'Val/mean dice_metric': 0.9732905626296997, 'Val/mean miou_metric': 0.9589020013809204, 'Val/mean f1': 0.9761490225791931, 'Val/mean precision': 0.9749714732170105, 'Val/mean recall': 0.977329432964325, 'Val/mean hd95_metric': 4.539279460906982} +Cheakpoint... +Epoch [2854/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732905626296997, 'Val/mean miou_metric': 0.9589020013809204, 'Val/mean f1': 0.9761490225791931, 'Val/mean precision': 0.9749714732170105, 'Val/mean recall': 0.977329432964325, 'Val/mean hd95_metric': 4.539279460906982} +Epoch [2855/4000] Training [1/16] Loss: 0.00277 +Epoch [2855/4000] Training [2/16] Loss: 0.00295 +Epoch [2855/4000] Training [3/16] Loss: 0.00338 +Epoch [2855/4000] Training [4/16] Loss: 0.00273 +Epoch [2855/4000] Training [5/16] Loss: 0.00325 +Epoch [2855/4000] Training [6/16] Loss: 0.00315 +Epoch [2855/4000] Training [7/16] Loss: 0.00364 +Epoch [2855/4000] Training [8/16] Loss: 0.00337 +Epoch [2855/4000] Training [9/16] Loss: 0.00298 +Epoch [2855/4000] Training [10/16] Loss: 0.00368 +Epoch [2855/4000] Training [11/16] Loss: 0.00483 +Epoch [2855/4000] Training [12/16] Loss: 0.00301 +Epoch [2855/4000] Training [13/16] Loss: 0.00430 +Epoch [2855/4000] Training [14/16] Loss: 0.00292 +Epoch [2855/4000] Training [15/16] Loss: 0.00324 +Epoch [2855/4000] Training [16/16] Loss: 0.00240 +Epoch [2855/4000] Training metric {'Train/mean dice_metric': 0.9980760812759399, 'Train/mean miou_metric': 0.9958598017692566, 'Train/mean f1': 0.9927164316177368, 'Train/mean precision': 0.9877266883850098, 'Train/mean recall': 0.997756838798523, 'Train/mean hd95_metric': 0.84201979637146} +Epoch [2855/4000] Validation [1/4] Loss: 0.35907 focal_loss 0.29707 dice_loss 0.06200 +Epoch [2855/4000] Validation [2/4] Loss: 0.53634 focal_loss 0.40249 dice_loss 0.13385 +Epoch [2855/4000] Validation [3/4] Loss: 0.48548 focal_loss 0.38466 dice_loss 0.10081 +Epoch [2855/4000] Validation [4/4] Loss: 0.38117 focal_loss 0.26791 dice_loss 0.11326 +Epoch [2855/4000] Validation metric {'Val/mean dice_metric': 0.974084198474884, 'Val/mean miou_metric': 0.9590668678283691, 'Val/mean f1': 0.9754964113235474, 'Val/mean precision': 0.9733421206474304, 'Val/mean recall': 0.9776601195335388, 'Val/mean hd95_metric': 4.8649749755859375} +Cheakpoint... +Epoch [2855/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974084198474884, 'Val/mean miou_metric': 0.9590668678283691, 'Val/mean f1': 0.9754964113235474, 'Val/mean precision': 0.9733421206474304, 'Val/mean recall': 0.9776601195335388, 'Val/mean hd95_metric': 4.8649749755859375} +Epoch [2856/4000] Training [1/16] Loss: 0.00449 +Epoch [2856/4000] Training [2/16] Loss: 0.00358 +Epoch [2856/4000] Training [3/16] Loss: 0.00349 +Epoch [2856/4000] Training [4/16] Loss: 0.00541 +Epoch [2856/4000] Training [5/16] Loss: 0.00272 +Epoch [2856/4000] Training [6/16] Loss: 0.00299 +Epoch [2856/4000] Training [7/16] Loss: 0.00352 +Epoch [2856/4000] Training [8/16] Loss: 0.00453 +Epoch [2856/4000] Training [9/16] Loss: 0.00253 +Epoch [2856/4000] Training [10/16] Loss: 0.00459 +Epoch [2856/4000] Training [11/16] Loss: 0.00272 +Epoch [2856/4000] Training [12/16] Loss: 0.00237 +Epoch [2856/4000] Training [13/16] Loss: 0.00453 +Epoch [2856/4000] Training [14/16] Loss: 0.00402 +Epoch [2856/4000] Training [15/16] Loss: 0.00383 +Epoch [2856/4000] Training [16/16] Loss: 0.00369 +Epoch [2856/4000] Training metric {'Train/mean dice_metric': 0.9978617429733276, 'Train/mean miou_metric': 0.9954438209533691, 'Train/mean f1': 0.992849588394165, 'Train/mean precision': 0.9880402088165283, 'Train/mean recall': 0.9977060556411743, 'Train/mean hd95_metric': 0.8337745070457458} +Epoch [2856/4000] Validation [1/4] Loss: 0.38897 focal_loss 0.32476 dice_loss 0.06421 +Epoch [2856/4000] Validation [2/4] Loss: 0.54232 focal_loss 0.40790 dice_loss 0.13442 +Epoch [2856/4000] Validation [3/4] Loss: 0.41290 focal_loss 0.32134 dice_loss 0.09156 +Epoch [2856/4000] Validation [4/4] Loss: 0.31173 focal_loss 0.22296 dice_loss 0.08877 +Epoch [2856/4000] Validation metric {'Val/mean dice_metric': 0.973088264465332, 'Val/mean miou_metric': 0.9584605097770691, 'Val/mean f1': 0.9755855798721313, 'Val/mean precision': 0.9743812680244446, 'Val/mean recall': 0.9767930507659912, 'Val/mean hd95_metric': 4.827176570892334} +Cheakpoint... +Epoch [2856/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973088264465332, 'Val/mean miou_metric': 0.9584605097770691, 'Val/mean f1': 0.9755855798721313, 'Val/mean precision': 0.9743812680244446, 'Val/mean recall': 0.9767930507659912, 'Val/mean hd95_metric': 4.827176570892334} +Epoch [2857/4000] Training [1/16] Loss: 0.00279 +Epoch [2857/4000] Training [2/16] Loss: 0.00401 +Epoch [2857/4000] Training [3/16] Loss: 0.00355 +Epoch [2857/4000] Training [4/16] Loss: 0.00311 +Epoch [2857/4000] Training [5/16] Loss: 0.00299 +Epoch [2857/4000] Training [6/16] Loss: 0.00273 +Epoch [2857/4000] Training [7/16] Loss: 0.00452 +Epoch [2857/4000] Training [8/16] Loss: 0.00249 +Epoch [2857/4000] Training [9/16] Loss: 0.00379 +Epoch [2857/4000] Training [10/16] Loss: 0.00429 +Epoch [2857/4000] Training [11/16] Loss: 0.00553 +Epoch [2857/4000] Training [12/16] Loss: 0.00367 +Epoch [2857/4000] Training [13/16] Loss: 0.00363 +Epoch [2857/4000] Training [14/16] Loss: 0.00316 +Epoch [2857/4000] Training [15/16] Loss: 0.00306 +Epoch [2857/4000] Training [16/16] Loss: 0.00391 +Epoch [2857/4000] Training metric {'Train/mean dice_metric': 0.9978716969490051, 'Train/mean miou_metric': 0.9954774379730225, 'Train/mean f1': 0.9930919408798218, 'Train/mean precision': 0.9885900020599365, 'Train/mean recall': 0.997635006904602, 'Train/mean hd95_metric': 0.84787917137146} +Epoch [2857/4000] Validation [1/4] Loss: 0.32775 focal_loss 0.26926 dice_loss 0.05849 +Epoch [2857/4000] Validation [2/4] Loss: 0.96275 focal_loss 0.77726 dice_loss 0.18549 +Epoch [2857/4000] Validation [3/4] Loss: 0.45230 focal_loss 0.36223 dice_loss 0.09007 +Epoch [2857/4000] Validation [4/4] Loss: 0.29448 focal_loss 0.19952 dice_loss 0.09496 +Epoch [2857/4000] Validation metric {'Val/mean dice_metric': 0.9721657037734985, 'Val/mean miou_metric': 0.9582340121269226, 'Val/mean f1': 0.9757804274559021, 'Val/mean precision': 0.9736383557319641, 'Val/mean recall': 0.9779319167137146, 'Val/mean hd95_metric': 5.4874958992004395} +Cheakpoint... +Epoch [2857/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721657037734985, 'Val/mean miou_metric': 0.9582340121269226, 'Val/mean f1': 0.9757804274559021, 'Val/mean precision': 0.9736383557319641, 'Val/mean recall': 0.9779319167137146, 'Val/mean hd95_metric': 5.4874958992004395} +Epoch [2858/4000] Training [1/16] Loss: 0.00295 +Epoch [2858/4000] Training [2/16] Loss: 0.00239 +Epoch [2858/4000] Training [3/16] Loss: 0.00378 +Epoch [2858/4000] Training [4/16] Loss: 0.00418 +Epoch [2858/4000] Training [5/16] Loss: 0.00309 +Epoch [2858/4000] Training [6/16] Loss: 0.00424 +Epoch [2858/4000] Training [7/16] Loss: 0.00360 +Epoch [2858/4000] Training [8/16] Loss: 0.00437 +Epoch [2858/4000] Training [9/16] Loss: 0.00304 +Epoch [2858/4000] Training [10/16] Loss: 0.00273 +Epoch [2858/4000] Training [11/16] Loss: 0.00313 +Epoch [2858/4000] Training [12/16] Loss: 0.00410 +Epoch [2858/4000] Training [13/16] Loss: 0.00410 +Epoch [2858/4000] Training [14/16] Loss: 0.00348 +Epoch [2858/4000] Training [15/16] Loss: 0.00348 +Epoch [2858/4000] Training [16/16] Loss: 0.00325 +Epoch [2858/4000] Training metric {'Train/mean dice_metric': 0.9979204535484314, 'Train/mean miou_metric': 0.9955737590789795, 'Train/mean f1': 0.9929176568984985, 'Train/mean precision': 0.988207995891571, 'Train/mean recall': 0.997672438621521, 'Train/mean hd95_metric': 0.8534954190254211} +Epoch [2858/4000] Validation [1/4] Loss: 0.35259 focal_loss 0.28747 dice_loss 0.06512 +Epoch [2858/4000] Validation [2/4] Loss: 0.52033 focal_loss 0.38922 dice_loss 0.13111 +Epoch [2858/4000] Validation [3/4] Loss: 0.43883 focal_loss 0.34830 dice_loss 0.09053 +Epoch [2858/4000] Validation [4/4] Loss: 0.31861 focal_loss 0.22496 dice_loss 0.09366 +Epoch [2858/4000] Validation metric {'Val/mean dice_metric': 0.9739080667495728, 'Val/mean miou_metric': 0.9589661359786987, 'Val/mean f1': 0.9753746390342712, 'Val/mean precision': 0.9741630554199219, 'Val/mean recall': 0.9765893220901489, 'Val/mean hd95_metric': 4.97314977645874} +Cheakpoint... +Epoch [2858/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739080667495728, 'Val/mean miou_metric': 0.9589661359786987, 'Val/mean f1': 0.9753746390342712, 'Val/mean precision': 0.9741630554199219, 'Val/mean recall': 0.9765893220901489, 'Val/mean hd95_metric': 4.97314977645874} +Epoch [2859/4000] Training [1/16] Loss: 0.00356 +Epoch [2859/4000] Training [2/16] Loss: 0.00520 +Epoch [2859/4000] Training [3/16] Loss: 0.00367 +Epoch [2859/4000] Training [4/16] Loss: 0.00401 +Epoch [2859/4000] Training [5/16] Loss: 0.00319 +Epoch [2859/4000] Training [6/16] Loss: 0.00395 +Epoch [2859/4000] Training [7/16] Loss: 0.00467 +Epoch [2859/4000] Training [8/16] Loss: 0.00322 +Epoch [2859/4000] Training [9/16] Loss: 0.00392 +Epoch [2859/4000] Training [10/16] Loss: 0.00315 +Epoch [2859/4000] Training [11/16] Loss: 0.00361 +Epoch [2859/4000] Training [12/16] Loss: 0.00364 +Epoch [2859/4000] Training [13/16] Loss: 0.00403 +Epoch [2859/4000] Training [14/16] Loss: 0.00455 +Epoch [2859/4000] Training [15/16] Loss: 0.00253 +Epoch [2859/4000] Training [16/16] Loss: 0.00404 +Epoch [2859/4000] Training metric {'Train/mean dice_metric': 0.9978245496749878, 'Train/mean miou_metric': 0.9953487515449524, 'Train/mean f1': 0.9923697710037231, 'Train/mean precision': 0.987253725528717, 'Train/mean recall': 0.9975391030311584, 'Train/mean hd95_metric': 0.8338167071342468} +Epoch [2859/4000] Validation [1/4] Loss: 0.33555 focal_loss 0.27305 dice_loss 0.06250 +Epoch [2859/4000] Validation [2/4] Loss: 0.52727 focal_loss 0.39822 dice_loss 0.12905 +Epoch [2859/4000] Validation [3/4] Loss: 0.40192 focal_loss 0.31241 dice_loss 0.08951 +Epoch [2859/4000] Validation [4/4] Loss: 0.48884 focal_loss 0.35818 dice_loss 0.13066 +Epoch [2859/4000] Validation metric {'Val/mean dice_metric': 0.9723120927810669, 'Val/mean miou_metric': 0.9572128057479858, 'Val/mean f1': 0.975130021572113, 'Val/mean precision': 0.9738222360610962, 'Val/mean recall': 0.9764412641525269, 'Val/mean hd95_metric': 5.003187656402588} +Cheakpoint... +Epoch [2859/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723120927810669, 'Val/mean miou_metric': 0.9572128057479858, 'Val/mean f1': 0.975130021572113, 'Val/mean precision': 0.9738222360610962, 'Val/mean recall': 0.9764412641525269, 'Val/mean hd95_metric': 5.003187656402588} +Epoch [2860/4000] Training [1/16] Loss: 0.00542 +Epoch [2860/4000] Training [2/16] Loss: 0.00447 +Epoch [2860/4000] Training [3/16] Loss: 0.00367 +Epoch [2860/4000] Training [4/16] Loss: 0.00433 +Epoch [2860/4000] Training [5/16] Loss: 0.00321 +Epoch [2860/4000] Training [6/16] Loss: 0.00278 +Epoch [2860/4000] Training [7/16] Loss: 0.00295 +Epoch [2860/4000] Training [8/16] Loss: 0.00278 +Epoch [2860/4000] Training [9/16] Loss: 0.00367 +Epoch [2860/4000] Training [10/16] Loss: 0.00343 +Epoch [2860/4000] Training [11/16] Loss: 0.00366 +Epoch [2860/4000] Training [12/16] Loss: 0.00284 +Epoch [2860/4000] Training [13/16] Loss: 0.00380 +Epoch [2860/4000] Training [14/16] Loss: 0.00354 +Epoch [2860/4000] Training [15/16] Loss: 0.00323 +Epoch [2860/4000] Training [16/16] Loss: 0.00338 +Epoch [2860/4000] Training metric {'Train/mean dice_metric': 0.9978859424591064, 'Train/mean miou_metric': 0.9954893589019775, 'Train/mean f1': 0.9928634762763977, 'Train/mean precision': 0.9880502820014954, 'Train/mean recall': 0.9977238178253174, 'Train/mean hd95_metric': 0.8516179323196411} +Epoch [2860/4000] Validation [1/4] Loss: 0.35987 focal_loss 0.29704 dice_loss 0.06283 +Epoch [2860/4000] Validation [2/4] Loss: 0.52236 focal_loss 0.39217 dice_loss 0.13020 +Epoch [2860/4000] Validation [3/4] Loss: 0.45769 focal_loss 0.36664 dice_loss 0.09105 +Epoch [2860/4000] Validation [4/4] Loss: 0.48707 focal_loss 0.34983 dice_loss 0.13724 +Epoch [2860/4000] Validation metric {'Val/mean dice_metric': 0.9726778268814087, 'Val/mean miou_metric': 0.9578521847724915, 'Val/mean f1': 0.9756385684013367, 'Val/mean precision': 0.9744305610656738, 'Val/mean recall': 0.9768494963645935, 'Val/mean hd95_metric': 5.02553129196167} +Cheakpoint... +Epoch [2860/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726778268814087, 'Val/mean miou_metric': 0.9578521847724915, 'Val/mean f1': 0.9756385684013367, 'Val/mean precision': 0.9744305610656738, 'Val/mean recall': 0.9768494963645935, 'Val/mean hd95_metric': 5.02553129196167} +Epoch [2861/4000] Training [1/16] Loss: 0.00343 +Epoch [2861/4000] Training [2/16] Loss: 0.00290 +Epoch [2861/4000] Training [3/16] Loss: 0.00374 +Epoch [2861/4000] Training [4/16] Loss: 0.00464 +Epoch [2861/4000] Training [5/16] Loss: 0.00380 +Epoch [2861/4000] Training [6/16] Loss: 0.00289 +Epoch [2861/4000] Training [7/16] Loss: 0.00384 +Epoch [2861/4000] Training [8/16] Loss: 0.00404 +Epoch [2861/4000] Training [9/16] Loss: 0.00444 +Epoch [2861/4000] Training [10/16] Loss: 0.00327 +Epoch [2861/4000] Training [11/16] Loss: 0.00393 +Epoch [2861/4000] Training [12/16] Loss: 0.00344 +Epoch [2861/4000] Training [13/16] Loss: 0.00407 +Epoch [2861/4000] Training [14/16] Loss: 0.00253 +Epoch [2861/4000] Training [15/16] Loss: 0.00483 +Epoch [2861/4000] Training [16/16] Loss: 0.00393 +Epoch [2861/4000] Training metric {'Train/mean dice_metric': 0.9977787733078003, 'Train/mean miou_metric': 0.9952977299690247, 'Train/mean f1': 0.9930635690689087, 'Train/mean precision': 0.988452136516571, 'Train/mean recall': 0.9977181553840637, 'Train/mean hd95_metric': 0.8741704225540161} +Epoch [2861/4000] Validation [1/4] Loss: 0.36272 focal_loss 0.29920 dice_loss 0.06352 +Epoch [2861/4000] Validation [2/4] Loss: 0.73590 focal_loss 0.50098 dice_loss 0.23492 +Epoch [2861/4000] Validation [3/4] Loss: 0.45009 focal_loss 0.36183 dice_loss 0.08827 +Epoch [2861/4000] Validation [4/4] Loss: 0.29029 focal_loss 0.20294 dice_loss 0.08735 +Epoch [2861/4000] Validation metric {'Val/mean dice_metric': 0.9723501205444336, 'Val/mean miou_metric': 0.9578015208244324, 'Val/mean f1': 0.9755131006240845, 'Val/mean precision': 0.9734898805618286, 'Val/mean recall': 0.9775446653366089, 'Val/mean hd95_metric': 5.101339340209961} +Cheakpoint... +Epoch [2861/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723501205444336, 'Val/mean miou_metric': 0.9578015208244324, 'Val/mean f1': 0.9755131006240845, 'Val/mean precision': 0.9734898805618286, 'Val/mean recall': 0.9775446653366089, 'Val/mean hd95_metric': 5.101339340209961} +Epoch [2862/4000] Training [1/16] Loss: 0.00297 +Epoch [2862/4000] Training [2/16] Loss: 0.00381 +Epoch [2862/4000] Training [3/16] Loss: 0.00291 +Epoch [2862/4000] Training [4/16] Loss: 0.00354 +Epoch [2862/4000] Training [5/16] Loss: 0.00290 +Epoch [2862/4000] Training [6/16] Loss: 0.00399 +Epoch [2862/4000] Training [7/16] Loss: 0.00854 +Epoch [2862/4000] Training [8/16] Loss: 0.00421 +Epoch [2862/4000] Training [9/16] Loss: 0.00443 +Epoch [2862/4000] Training [10/16] Loss: 0.00363 +Epoch [2862/4000] Training [11/16] Loss: 0.00306 +Epoch [2862/4000] Training [12/16] Loss: 0.00451 +Epoch [2862/4000] Training [13/16] Loss: 0.00315 +Epoch [2862/4000] Training [14/16] Loss: 0.00329 +Epoch [2862/4000] Training [15/16] Loss: 0.00377 +Epoch [2862/4000] Training [16/16] Loss: 0.00306 +Epoch [2862/4000] Training metric {'Train/mean dice_metric': 0.9977129697799683, 'Train/mean miou_metric': 0.9951603412628174, 'Train/mean f1': 0.9928350448608398, 'Train/mean precision': 0.9884676337242126, 'Train/mean recall': 0.997241199016571, 'Train/mean hd95_metric': 0.9169168472290039} +Epoch [2862/4000] Validation [1/4] Loss: 0.32743 focal_loss 0.26686 dice_loss 0.06057 +Epoch [2862/4000] Validation [2/4] Loss: 0.92186 focal_loss 0.72574 dice_loss 0.19613 +Epoch [2862/4000] Validation [3/4] Loss: 0.46294 focal_loss 0.36278 dice_loss 0.10016 +Epoch [2862/4000] Validation [4/4] Loss: 0.40506 focal_loss 0.28025 dice_loss 0.12481 +Epoch [2862/4000] Validation metric {'Val/mean dice_metric': 0.9731037020683289, 'Val/mean miou_metric': 0.9584659337997437, 'Val/mean f1': 0.9759106636047363, 'Val/mean precision': 0.9728166460990906, 'Val/mean recall': 0.9790244698524475, 'Val/mean hd95_metric': 5.122500896453857} +Cheakpoint... +Epoch [2862/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731037020683289, 'Val/mean miou_metric': 0.9584659337997437, 'Val/mean f1': 0.9759106636047363, 'Val/mean precision': 0.9728166460990906, 'Val/mean recall': 0.9790244698524475, 'Val/mean hd95_metric': 5.122500896453857} +Epoch [2863/4000] Training [1/16] Loss: 0.00462 +Epoch [2863/4000] Training [2/16] Loss: 0.00300 +Epoch [2863/4000] Training [3/16] Loss: 0.00422 +Epoch [2863/4000] Training [4/16] Loss: 0.00482 +Epoch [2863/4000] Training [5/16] Loss: 0.00510 +Epoch [2863/4000] Training [6/16] Loss: 0.00294 +Epoch [2863/4000] Training [7/16] Loss: 0.00271 +Epoch [2863/4000] Training [8/16] Loss: 0.00338 +Epoch [2863/4000] Training [9/16] Loss: 0.00324 +Epoch [2863/4000] Training [10/16] Loss: 0.00283 +Epoch [2863/4000] Training [11/16] Loss: 0.00362 +Epoch [2863/4000] Training [12/16] Loss: 0.00383 +Epoch [2863/4000] Training [13/16] Loss: 0.00270 +Epoch [2863/4000] Training [14/16] Loss: 0.00407 +Epoch [2863/4000] Training [15/16] Loss: 0.00425 +Epoch [2863/4000] Training [16/16] Loss: 0.00311 +Epoch [2863/4000] Training metric {'Train/mean dice_metric': 0.9977290034294128, 'Train/mean miou_metric': 0.995154619216919, 'Train/mean f1': 0.9922971129417419, 'Train/mean precision': 0.9870901703834534, 'Train/mean recall': 0.9975593686103821, 'Train/mean hd95_metric': 0.8571571111679077} +Epoch [2863/4000] Validation [1/4] Loss: 0.34690 focal_loss 0.28531 dice_loss 0.06158 +Epoch [2863/4000] Validation [2/4] Loss: 0.53581 focal_loss 0.40530 dice_loss 0.13051 +Epoch [2863/4000] Validation [3/4] Loss: 0.46447 focal_loss 0.37338 dice_loss 0.09109 +Epoch [2863/4000] Validation [4/4] Loss: 0.33365 focal_loss 0.22287 dice_loss 0.11078 +Epoch [2863/4000] Validation metric {'Val/mean dice_metric': 0.9732056856155396, 'Val/mean miou_metric': 0.9586876034736633, 'Val/mean f1': 0.9756476283073425, 'Val/mean precision': 0.9716901183128357, 'Val/mean recall': 0.9796373844146729, 'Val/mean hd95_metric': 4.789884090423584} +Cheakpoint... +Epoch [2863/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732056856155396, 'Val/mean miou_metric': 0.9586876034736633, 'Val/mean f1': 0.9756476283073425, 'Val/mean precision': 0.9716901183128357, 'Val/mean recall': 0.9796373844146729, 'Val/mean hd95_metric': 4.789884090423584} +Epoch [2864/4000] Training [1/16] Loss: 0.00327 +Epoch [2864/4000] Training [2/16] Loss: 0.00310 +Epoch [2864/4000] Training [3/16] Loss: 0.00420 +Epoch [2864/4000] Training [4/16] Loss: 0.00402 +Epoch [2864/4000] Training [5/16] Loss: 0.00313 +Epoch [2864/4000] Training [6/16] Loss: 0.00544 +Epoch [2864/4000] Training [7/16] Loss: 0.00249 +Epoch [2864/4000] Training [8/16] Loss: 0.00390 +Epoch [2864/4000] Training [9/16] Loss: 0.00362 +Epoch [2864/4000] Training [10/16] Loss: 0.00309 +Epoch [2864/4000] Training [11/16] Loss: 0.00351 +Epoch [2864/4000] Training [12/16] Loss: 0.00395 +Epoch [2864/4000] Training [13/16] Loss: 0.00357 +Epoch [2864/4000] Training [14/16] Loss: 0.00375 +Epoch [2864/4000] Training [15/16] Loss: 0.00323 +Epoch [2864/4000] Training [16/16] Loss: 0.00365 +Epoch [2864/4000] Training metric {'Train/mean dice_metric': 0.9978615045547485, 'Train/mean miou_metric': 0.9954601526260376, 'Train/mean f1': 0.9931437373161316, 'Train/mean precision': 0.9886707067489624, 'Train/mean recall': 0.9976574182510376, 'Train/mean hd95_metric': 0.8683871030807495} +Epoch [2864/4000] Validation [1/4] Loss: 0.35675 focal_loss 0.29593 dice_loss 0.06083 +Epoch [2864/4000] Validation [2/4] Loss: 0.94549 focal_loss 0.74874 dice_loss 0.19676 +Epoch [2864/4000] Validation [3/4] Loss: 0.47133 focal_loss 0.37287 dice_loss 0.09845 +Epoch [2864/4000] Validation [4/4] Loss: 0.32778 focal_loss 0.23358 dice_loss 0.09420 +Epoch [2864/4000] Validation metric {'Val/mean dice_metric': 0.9729906320571899, 'Val/mean miou_metric': 0.9582818746566772, 'Val/mean f1': 0.9759718179702759, 'Val/mean precision': 0.9735035300254822, 'Val/mean recall': 0.9784526824951172, 'Val/mean hd95_metric': 5.261661529541016} +Cheakpoint... +Epoch [2864/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729906320571899, 'Val/mean miou_metric': 0.9582818746566772, 'Val/mean f1': 0.9759718179702759, 'Val/mean precision': 0.9735035300254822, 'Val/mean recall': 0.9784526824951172, 'Val/mean hd95_metric': 5.261661529541016} +Epoch [2865/4000] Training [1/16] Loss: 0.00341 +Epoch [2865/4000] Training [2/16] Loss: 0.00348 +Epoch [2865/4000] Training [3/16] Loss: 0.00373 +Epoch [2865/4000] Training [4/16] Loss: 0.00335 +Epoch [2865/4000] Training [5/16] Loss: 0.00323 +Epoch [2865/4000] Training [6/16] Loss: 0.00349 +Epoch [2865/4000] Training [7/16] Loss: 0.00462 +Epoch [2865/4000] Training [8/16] Loss: 0.00466 +Epoch [2865/4000] Training [9/16] Loss: 0.00317 +Epoch [2865/4000] Training [10/16] Loss: 0.00366 +Epoch [2865/4000] Training [11/16] Loss: 0.00314 +Epoch [2865/4000] Training [12/16] Loss: 0.00298 +Epoch [2865/4000] Training [13/16] Loss: 0.00277 +Epoch [2865/4000] Training [14/16] Loss: 0.00461 +Epoch [2865/4000] Training [15/16] Loss: 0.00512 +Epoch [2865/4000] Training [16/16] Loss: 0.00269 +Epoch [2865/4000] Training metric {'Train/mean dice_metric': 0.9979998469352722, 'Train/mean miou_metric': 0.9957260489463806, 'Train/mean f1': 0.9931296110153198, 'Train/mean precision': 0.9885125160217285, 'Train/mean recall': 0.9977900981903076, 'Train/mean hd95_metric': 0.8409456014633179} +Epoch [2865/4000] Validation [1/4] Loss: 0.36631 focal_loss 0.30250 dice_loss 0.06381 +Epoch [2865/4000] Validation [2/4] Loss: 0.50214 focal_loss 0.37730 dice_loss 0.12485 +Epoch [2865/4000] Validation [3/4] Loss: 0.46395 focal_loss 0.37525 dice_loss 0.08870 +Epoch [2865/4000] Validation [4/4] Loss: 0.24798 focal_loss 0.16121 dice_loss 0.08678 +Epoch [2865/4000] Validation metric {'Val/mean dice_metric': 0.9755973815917969, 'Val/mean miou_metric': 0.9612768292427063, 'Val/mean f1': 0.9770162105560303, 'Val/mean precision': 0.9738484621047974, 'Val/mean recall': 0.980204701423645, 'Val/mean hd95_metric': 4.970656871795654} +Cheakpoint... +Epoch [2865/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755973815917969, 'Val/mean miou_metric': 0.9612768292427063, 'Val/mean f1': 0.9770162105560303, 'Val/mean precision': 0.9738484621047974, 'Val/mean recall': 0.980204701423645, 'Val/mean hd95_metric': 4.970656871795654} +Epoch [2866/4000] Training [1/16] Loss: 0.00232 +Epoch [2866/4000] Training [2/16] Loss: 0.00271 +Epoch [2866/4000] Training [3/16] Loss: 0.00340 +Epoch [2866/4000] Training [4/16] Loss: 0.00331 +Epoch [2866/4000] Training [5/16] Loss: 0.00405 +Epoch [2866/4000] Training [6/16] Loss: 0.00272 +Epoch [2866/4000] Training [7/16] Loss: 0.00396 +Epoch [2866/4000] Training [8/16] Loss: 0.00283 +Epoch [2866/4000] Training [9/16] Loss: 0.00464 +Epoch [2866/4000] Training [10/16] Loss: 0.00533 +Epoch [2866/4000] Training [11/16] Loss: 0.00304 +Epoch [2866/4000] Training [12/16] Loss: 0.00305 +Epoch [2866/4000] Training [13/16] Loss: 0.00331 +Epoch [2866/4000] Training [14/16] Loss: 0.00295 +Epoch [2866/4000] Training [15/16] Loss: 0.00269 +Epoch [2866/4000] Training [16/16] Loss: 0.00274 +Epoch [2866/4000] Training metric {'Train/mean dice_metric': 0.9981245398521423, 'Train/mean miou_metric': 0.9959806799888611, 'Train/mean f1': 0.9933112859725952, 'Train/mean precision': 0.9887056350708008, 'Train/mean recall': 0.9979600310325623, 'Train/mean hd95_metric': 0.8111604452133179} +Epoch [2866/4000] Validation [1/4] Loss: 0.36357 focal_loss 0.29093 dice_loss 0.07263 +Epoch [2866/4000] Validation [2/4] Loss: 0.52625 focal_loss 0.39179 dice_loss 0.13445 +Epoch [2866/4000] Validation [3/4] Loss: 0.48604 focal_loss 0.38537 dice_loss 0.10067 +Epoch [2866/4000] Validation [4/4] Loss: 0.38182 focal_loss 0.28116 dice_loss 0.10066 +Epoch [2866/4000] Validation metric {'Val/mean dice_metric': 0.9749269485473633, 'Val/mean miou_metric': 0.9601355791091919, 'Val/mean f1': 0.976142942905426, 'Val/mean precision': 0.9729225635528564, 'Val/mean recall': 0.9793846607208252, 'Val/mean hd95_metric': 5.313513278961182} +Cheakpoint... +Epoch [2866/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749269485473633, 'Val/mean miou_metric': 0.9601355791091919, 'Val/mean f1': 0.976142942905426, 'Val/mean precision': 0.9729225635528564, 'Val/mean recall': 0.9793846607208252, 'Val/mean hd95_metric': 5.313513278961182} +Epoch [2867/4000] Training [1/16] Loss: 0.00489 +Epoch [2867/4000] Training [2/16] Loss: 0.00621 +Epoch [2867/4000] Training [3/16] Loss: 0.00296 +Epoch [2867/4000] Training [4/16] Loss: 0.00328 +Epoch [2867/4000] Training [5/16] Loss: 0.00304 +Epoch [2867/4000] Training [6/16] Loss: 0.00326 +Epoch [2867/4000] Training [7/16] Loss: 0.00307 +Epoch [2867/4000] Training [8/16] Loss: 0.00295 +Epoch [2867/4000] Training [9/16] Loss: 0.00318 +Epoch [2867/4000] Training [10/16] Loss: 0.00288 +Epoch [2867/4000] Training [11/16] Loss: 0.00305 +Epoch [2867/4000] Training [12/16] Loss: 0.00430 +Epoch [2867/4000] Training [13/16] Loss: 0.00298 +Epoch [2867/4000] Training [14/16] Loss: 0.00343 +Epoch [2867/4000] Training [15/16] Loss: 0.00456 +Epoch [2867/4000] Training [16/16] Loss: 0.00328 +Epoch [2867/4000] Training metric {'Train/mean dice_metric': 0.9978450536727905, 'Train/mean miou_metric': 0.9954041838645935, 'Train/mean f1': 0.9924265146255493, 'Train/mean precision': 0.9873502850532532, 'Train/mean recall': 0.9975551962852478, 'Train/mean hd95_metric': 0.8568070530891418} +Epoch [2867/4000] Validation [1/4] Loss: 0.31701 focal_loss 0.26073 dice_loss 0.05628 +Epoch [2867/4000] Validation [2/4] Loss: 0.55639 focal_loss 0.41999 dice_loss 0.13640 +Epoch [2867/4000] Validation [3/4] Loss: 0.47843 focal_loss 0.38732 dice_loss 0.09111 +Epoch [2867/4000] Validation [4/4] Loss: 0.42173 focal_loss 0.30137 dice_loss 0.12036 +Epoch [2867/4000] Validation metric {'Val/mean dice_metric': 0.9747991561889648, 'Val/mean miou_metric': 0.9599058032035828, 'Val/mean f1': 0.97542405128479, 'Val/mean precision': 0.9719433188438416, 'Val/mean recall': 0.9789297580718994, 'Val/mean hd95_metric': 5.260358810424805} +Cheakpoint... +Epoch [2867/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747991561889648, 'Val/mean miou_metric': 0.9599058032035828, 'Val/mean f1': 0.97542405128479, 'Val/mean precision': 0.9719433188438416, 'Val/mean recall': 0.9789297580718994, 'Val/mean hd95_metric': 5.260358810424805} +Epoch [2868/4000] Training [1/16] Loss: 0.00288 +Epoch [2868/4000] Training [2/16] Loss: 0.00320 +Epoch [2868/4000] Training [3/16] Loss: 0.00365 +Epoch [2868/4000] Training [4/16] Loss: 0.00334 +Epoch [2868/4000] Training [5/16] Loss: 0.00457 +Epoch [2868/4000] Training [6/16] Loss: 0.00376 +Epoch [2868/4000] Training [7/16] Loss: 0.00299 +Epoch [2868/4000] Training [8/16] Loss: 0.00343 +Epoch [2868/4000] Training [9/16] Loss: 0.00291 +Epoch [2868/4000] Training [10/16] Loss: 0.00247 +Epoch [2868/4000] Training [11/16] Loss: 0.00499 +Epoch [2868/4000] Training [12/16] Loss: 0.00302 +Epoch [2868/4000] Training [13/16] Loss: 0.00344 +Epoch [2868/4000] Training [14/16] Loss: 0.00320 +Epoch [2868/4000] Training [15/16] Loss: 0.00356 +Epoch [2868/4000] Training [16/16] Loss: 0.00332 +Epoch [2868/4000] Training metric {'Train/mean dice_metric': 0.9980145692825317, 'Train/mean miou_metric': 0.9957640767097473, 'Train/mean f1': 0.9932225942611694, 'Train/mean precision': 0.9886593222618103, 'Train/mean recall': 0.9978281855583191, 'Train/mean hd95_metric': 0.83616042137146} +Epoch [2868/4000] Validation [1/4] Loss: 0.31671 focal_loss 0.25780 dice_loss 0.05890 +Epoch [2868/4000] Validation [2/4] Loss: 0.47103 focal_loss 0.35219 dice_loss 0.11884 +Epoch [2868/4000] Validation [3/4] Loss: 0.45681 focal_loss 0.36638 dice_loss 0.09043 +Epoch [2868/4000] Validation [4/4] Loss: 0.36045 focal_loss 0.25645 dice_loss 0.10400 +Epoch [2868/4000] Validation metric {'Val/mean dice_metric': 0.9729192852973938, 'Val/mean miou_metric': 0.9585810899734497, 'Val/mean f1': 0.9759400486946106, 'Val/mean precision': 0.9747684001922607, 'Val/mean recall': 0.9771145582199097, 'Val/mean hd95_metric': 4.91301155090332} +Cheakpoint... +Epoch [2868/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729192852973938, 'Val/mean miou_metric': 0.9585810899734497, 'Val/mean f1': 0.9759400486946106, 'Val/mean precision': 0.9747684001922607, 'Val/mean recall': 0.9771145582199097, 'Val/mean hd95_metric': 4.91301155090332} +Epoch [2869/4000] Training [1/16] Loss: 0.00238 +Epoch [2869/4000] Training [2/16] Loss: 0.00354 +Epoch [2869/4000] Training [3/16] Loss: 0.00297 +Epoch [2869/4000] Training [4/16] Loss: 0.00302 +Epoch [2869/4000] Training [5/16] Loss: 0.00255 +Epoch [2869/4000] Training [6/16] Loss: 0.00513 +Epoch [2869/4000] Training [7/16] Loss: 0.00319 +Epoch [2869/4000] Training [8/16] Loss: 0.00393 +Epoch [2869/4000] Training [9/16] Loss: 0.00466 +Epoch [2869/4000] Training [10/16] Loss: 0.00421 +Epoch [2869/4000] Training [11/16] Loss: 0.00307 +Epoch [2869/4000] Training [12/16] Loss: 0.00368 +Epoch [2869/4000] Training [13/16] Loss: 0.00522 +Epoch [2869/4000] Training [14/16] Loss: 0.00359 +Epoch [2869/4000] Training [15/16] Loss: 0.00380 +Epoch [2869/4000] Training [16/16] Loss: 0.01134 +Epoch [2869/4000] Training metric {'Train/mean dice_metric': 0.9977917671203613, 'Train/mean miou_metric': 0.9953259825706482, 'Train/mean f1': 0.9929826259613037, 'Train/mean precision': 0.988357424736023, 'Train/mean recall': 0.9976513385772705, 'Train/mean hd95_metric': 0.8422142267227173} +Epoch [2869/4000] Validation [1/4] Loss: 0.40315 focal_loss 0.33804 dice_loss 0.06511 +Epoch [2869/4000] Validation [2/4] Loss: 0.43107 focal_loss 0.31902 dice_loss 0.11205 +Epoch [2869/4000] Validation [3/4] Loss: 0.46581 focal_loss 0.37246 dice_loss 0.09335 +Epoch [2869/4000] Validation [4/4] Loss: 0.60137 focal_loss 0.47195 dice_loss 0.12941 +Epoch [2869/4000] Validation metric {'Val/mean dice_metric': 0.9725707173347473, 'Val/mean miou_metric': 0.9574705362319946, 'Val/mean f1': 0.9741166234016418, 'Val/mean precision': 0.9716615080833435, 'Val/mean recall': 0.976584255695343, 'Val/mean hd95_metric': 5.48240852355957} +Cheakpoint... +Epoch [2869/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725707173347473, 'Val/mean miou_metric': 0.9574705362319946, 'Val/mean f1': 0.9741166234016418, 'Val/mean precision': 0.9716615080833435, 'Val/mean recall': 0.976584255695343, 'Val/mean hd95_metric': 5.48240852355957} +Epoch [2870/4000] Training [1/16] Loss: 0.00261 +Epoch [2870/4000] Training [2/16] Loss: 0.00517 +Epoch [2870/4000] Training [3/16] Loss: 0.00308 +Epoch [2870/4000] Training [4/16] Loss: 0.00260 +Epoch [2870/4000] Training [5/16] Loss: 0.00347 +Epoch [2870/4000] Training [6/16] Loss: 0.00550 +Epoch [2870/4000] Training [7/16] Loss: 0.00483 +Epoch [2870/4000] Training [8/16] Loss: 0.00384 +Epoch [2870/4000] Training [9/16] Loss: 0.00332 +Epoch [2870/4000] Training [10/16] Loss: 0.00319 +Epoch [2870/4000] Training [11/16] Loss: 0.00375 +Epoch [2870/4000] Training [12/16] Loss: 0.00270 +Epoch [2870/4000] Training [13/16] Loss: 0.00583 +Epoch [2870/4000] Training [14/16] Loss: 0.00347 +Epoch [2870/4000] Training [15/16] Loss: 0.00429 +Epoch [2870/4000] Training [16/16] Loss: 0.00345 +Epoch [2870/4000] Training metric {'Train/mean dice_metric': 0.9978174567222595, 'Train/mean miou_metric': 0.9953696727752686, 'Train/mean f1': 0.9928743839263916, 'Train/mean precision': 0.9884160161018372, 'Train/mean recall': 0.9973732233047485, 'Train/mean hd95_metric': 0.859974205493927} +Epoch [2870/4000] Validation [1/4] Loss: 0.32609 focal_loss 0.26624 dice_loss 0.05985 +Epoch [2870/4000] Validation [2/4] Loss: 0.40499 focal_loss 0.29777 dice_loss 0.10722 +Epoch [2870/4000] Validation [3/4] Loss: 0.48835 focal_loss 0.38879 dice_loss 0.09955 +Epoch [2870/4000] Validation [4/4] Loss: 0.28150 focal_loss 0.19952 dice_loss 0.08199 +Epoch [2870/4000] Validation metric {'Val/mean dice_metric': 0.9731130599975586, 'Val/mean miou_metric': 0.9586693644523621, 'Val/mean f1': 0.9759177565574646, 'Val/mean precision': 0.9740326404571533, 'Val/mean recall': 0.977810263633728, 'Val/mean hd95_metric': 4.912304401397705} +Cheakpoint... +Epoch [2870/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731130599975586, 'Val/mean miou_metric': 0.9586693644523621, 'Val/mean f1': 0.9759177565574646, 'Val/mean precision': 0.9740326404571533, 'Val/mean recall': 0.977810263633728, 'Val/mean hd95_metric': 4.912304401397705} +Epoch [2871/4000] Training [1/16] Loss: 0.00283 +Epoch [2871/4000] Training [2/16] Loss: 0.00281 +Epoch [2871/4000] Training [3/16] Loss: 0.00308 +Epoch [2871/4000] Training [4/16] Loss: 0.00210 +Epoch [2871/4000] Training [5/16] Loss: 0.00322 +Epoch [2871/4000] Training [6/16] Loss: 0.00332 +Epoch [2871/4000] Training [7/16] Loss: 0.00310 +Epoch [2871/4000] Training [8/16] Loss: 0.00413 +Epoch [2871/4000] Training [9/16] Loss: 0.00276 +Epoch [2871/4000] Training [10/16] Loss: 0.00362 +Epoch [2871/4000] Training [11/16] Loss: 0.00406 +Epoch [2871/4000] Training [12/16] Loss: 0.00323 +Epoch [2871/4000] Training [13/16] Loss: 0.00361 +Epoch [2871/4000] Training [14/16] Loss: 0.00418 +Epoch [2871/4000] Training [15/16] Loss: 0.00360 +Epoch [2871/4000] Training [16/16] Loss: 0.00283 +Epoch [2871/4000] Training metric {'Train/mean dice_metric': 0.9980574250221252, 'Train/mean miou_metric': 0.9958495497703552, 'Train/mean f1': 0.9932047724723816, 'Train/mean precision': 0.988677978515625, 'Train/mean recall': 0.9977731108665466, 'Train/mean hd95_metric': 0.8151838779449463} +Epoch [2871/4000] Validation [1/4] Loss: 0.34097 focal_loss 0.27969 dice_loss 0.06127 +Epoch [2871/4000] Validation [2/4] Loss: 0.41519 focal_loss 0.30516 dice_loss 0.11003 +Epoch [2871/4000] Validation [3/4] Loss: 0.48558 focal_loss 0.39239 dice_loss 0.09319 +Epoch [2871/4000] Validation [4/4] Loss: 0.22629 focal_loss 0.15146 dice_loss 0.07483 +Epoch [2871/4000] Validation metric {'Val/mean dice_metric': 0.9732959866523743, 'Val/mean miou_metric': 0.959276020526886, 'Val/mean f1': 0.976658046245575, 'Val/mean precision': 0.974537193775177, 'Val/mean recall': 0.9787881374359131, 'Val/mean hd95_metric': 4.879458904266357} +Cheakpoint... +Epoch [2871/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732959866523743, 'Val/mean miou_metric': 0.959276020526886, 'Val/mean f1': 0.976658046245575, 'Val/mean precision': 0.974537193775177, 'Val/mean recall': 0.9787881374359131, 'Val/mean hd95_metric': 4.879458904266357} +Epoch [2872/4000] Training [1/16] Loss: 0.00353 +Epoch [2872/4000] Training [2/16] Loss: 0.00378 +Epoch [2872/4000] Training [3/16] Loss: 0.00291 +Epoch [2872/4000] Training [4/16] Loss: 0.00317 +Epoch [2872/4000] Training [5/16] Loss: 0.00494 +Epoch [2872/4000] Training [6/16] Loss: 0.00260 +Epoch [2872/4000] Training [7/16] Loss: 0.00380 +Epoch [2872/4000] Training [8/16] Loss: 0.00311 +Epoch [2872/4000] Training [9/16] Loss: 0.00348 +Epoch [2872/4000] Training [10/16] Loss: 0.00260 +Epoch [2872/4000] Training [11/16] Loss: 0.00560 +Epoch [2872/4000] Training [12/16] Loss: 0.00381 +Epoch [2872/4000] Training [13/16] Loss: 0.00279 +Epoch [2872/4000] Training [14/16] Loss: 0.00317 +Epoch [2872/4000] Training [15/16] Loss: 0.00300 +Epoch [2872/4000] Training [16/16] Loss: 0.00256 +Epoch [2872/4000] Training metric {'Train/mean dice_metric': 0.9979424476623535, 'Train/mean miou_metric': 0.9956233501434326, 'Train/mean f1': 0.9931820034980774, 'Train/mean precision': 0.9886179566383362, 'Train/mean recall': 0.9977883696556091, 'Train/mean hd95_metric': 0.8284733295440674} +Epoch [2872/4000] Validation [1/4] Loss: 0.35285 focal_loss 0.29055 dice_loss 0.06230 +Epoch [2872/4000] Validation [2/4] Loss: 0.83643 focal_loss 0.63942 dice_loss 0.19701 +Epoch [2872/4000] Validation [3/4] Loss: 0.24233 focal_loss 0.18277 dice_loss 0.05956 +Epoch [2872/4000] Validation [4/4] Loss: 0.53234 focal_loss 0.38564 dice_loss 0.14669 +Epoch [2872/4000] Validation metric {'Val/mean dice_metric': 0.9724953770637512, 'Val/mean miou_metric': 0.9584862589836121, 'Val/mean f1': 0.9756543040275574, 'Val/mean precision': 0.9740301966667175, 'Val/mean recall': 0.9772839546203613, 'Val/mean hd95_metric': 4.633440017700195} +Cheakpoint... +Epoch [2872/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724953770637512, 'Val/mean miou_metric': 0.9584862589836121, 'Val/mean f1': 0.9756543040275574, 'Val/mean precision': 0.9740301966667175, 'Val/mean recall': 0.9772839546203613, 'Val/mean hd95_metric': 4.633440017700195} +Epoch [2873/4000] Training [1/16] Loss: 0.00286 +Epoch [2873/4000] Training [2/16] Loss: 0.00325 +Epoch [2873/4000] Training [3/16] Loss: 0.00263 +Epoch [2873/4000] Training [4/16] Loss: 0.00351 +Epoch [2873/4000] Training [5/16] Loss: 0.00252 +Epoch [2873/4000] Training [6/16] Loss: 0.00293 +Epoch [2873/4000] Training [7/16] Loss: 0.00493 +Epoch [2873/4000] Training [8/16] Loss: 0.00295 +Epoch [2873/4000] Training [9/16] Loss: 0.00559 +Epoch [2873/4000] Training [10/16] Loss: 0.00325 +Epoch [2873/4000] Training [11/16] Loss: 0.00377 +Epoch [2873/4000] Training [12/16] Loss: 0.00522 +Epoch [2873/4000] Training [13/16] Loss: 0.00297 +Epoch [2873/4000] Training [14/16] Loss: 0.00332 +Epoch [2873/4000] Training [15/16] Loss: 0.00324 +Epoch [2873/4000] Training [16/16] Loss: 0.00254 +Epoch [2873/4000] Training metric {'Train/mean dice_metric': 0.9980166554450989, 'Train/mean miou_metric': 0.9957612156867981, 'Train/mean f1': 0.9931764006614685, 'Train/mean precision': 0.9885405898094177, 'Train/mean recall': 0.9978559613227844, 'Train/mean hd95_metric': 0.818679928779602} +Epoch [2873/4000] Validation [1/4] Loss: 0.36957 focal_loss 0.30472 dice_loss 0.06485 +Epoch [2873/4000] Validation [2/4] Loss: 0.40783 focal_loss 0.30102 dice_loss 0.10681 +Epoch [2873/4000] Validation [3/4] Loss: 0.47011 focal_loss 0.37930 dice_loss 0.09081 +Epoch [2873/4000] Validation [4/4] Loss: 0.33585 focal_loss 0.23205 dice_loss 0.10380 +Epoch [2873/4000] Validation metric {'Val/mean dice_metric': 0.9740505218505859, 'Val/mean miou_metric': 0.9595783352851868, 'Val/mean f1': 0.9763062596321106, 'Val/mean precision': 0.9738912582397461, 'Val/mean recall': 0.9787333011627197, 'Val/mean hd95_metric': 4.943460941314697} +Cheakpoint... +Epoch [2873/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740505218505859, 'Val/mean miou_metric': 0.9595783352851868, 'Val/mean f1': 0.9763062596321106, 'Val/mean precision': 0.9738912582397461, 'Val/mean recall': 0.9787333011627197, 'Val/mean hd95_metric': 4.943460941314697} +Epoch [2874/4000] Training [1/16] Loss: 0.00256 +Epoch [2874/4000] Training [2/16] Loss: 0.00273 +Epoch [2874/4000] Training [3/16] Loss: 0.00287 +Epoch [2874/4000] Training [4/16] Loss: 0.00244 +Epoch [2874/4000] Training [5/16] Loss: 0.00364 +Epoch [2874/4000] Training [6/16] Loss: 0.00371 +Epoch [2874/4000] Training [7/16] Loss: 0.00458 +Epoch [2874/4000] Training [8/16] Loss: 0.00330 +Epoch [2874/4000] Training [9/16] Loss: 0.00317 +Epoch [2874/4000] Training [10/16] Loss: 0.00386 +Epoch [2874/4000] Training [11/16] Loss: 0.00401 +Epoch [2874/4000] Training [12/16] Loss: 0.00294 +Epoch [2874/4000] Training [13/16] Loss: 0.00298 +Epoch [2874/4000] Training [14/16] Loss: 0.00336 +Epoch [2874/4000] Training [15/16] Loss: 0.00362 +Epoch [2874/4000] Training [16/16] Loss: 0.00392 +Epoch [2874/4000] Training metric {'Train/mean dice_metric': 0.9979836344718933, 'Train/mean miou_metric': 0.9957042932510376, 'Train/mean f1': 0.993222177028656, 'Train/mean precision': 0.9887189269065857, 'Train/mean recall': 0.9977666139602661, 'Train/mean hd95_metric': 0.8374577760696411} +Epoch [2874/4000] Validation [1/4] Loss: 0.31501 focal_loss 0.25685 dice_loss 0.05817 +Epoch [2874/4000] Validation [2/4] Loss: 0.74386 focal_loss 0.54538 dice_loss 0.19848 +Epoch [2874/4000] Validation [3/4] Loss: 0.46198 focal_loss 0.37038 dice_loss 0.09161 +Epoch [2874/4000] Validation [4/4] Loss: 0.41830 focal_loss 0.31442 dice_loss 0.10389 +Epoch [2874/4000] Validation metric {'Val/mean dice_metric': 0.9728511571884155, 'Val/mean miou_metric': 0.9584211111068726, 'Val/mean f1': 0.975700318813324, 'Val/mean precision': 0.972807765007019, 'Val/mean recall': 0.9786099195480347, 'Val/mean hd95_metric': 5.264410972595215} +Cheakpoint... +Epoch [2874/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728511571884155, 'Val/mean miou_metric': 0.9584211111068726, 'Val/mean f1': 0.975700318813324, 'Val/mean precision': 0.972807765007019, 'Val/mean recall': 0.9786099195480347, 'Val/mean hd95_metric': 5.264410972595215} +Epoch [2875/4000] Training [1/16] Loss: 0.00360 +Epoch [2875/4000] Training [2/16] Loss: 0.00614 +Epoch [2875/4000] Training [3/16] Loss: 0.00250 +Epoch [2875/4000] Training [4/16] Loss: 0.00256 +Epoch [2875/4000] Training [5/16] Loss: 0.00290 +Epoch [2875/4000] Training [6/16] Loss: 0.00329 +Epoch [2875/4000] Training [7/16] Loss: 0.00310 +Epoch [2875/4000] Training [8/16] Loss: 0.00471 +Epoch [2875/4000] Training [9/16] Loss: 0.00464 +Epoch [2875/4000] Training [10/16] Loss: 0.00332 +Epoch [2875/4000] Training [11/16] Loss: 0.00297 +Epoch [2875/4000] Training [12/16] Loss: 0.00304 +Epoch [2875/4000] Training [13/16] Loss: 0.00304 +Epoch [2875/4000] Training [14/16] Loss: 0.00387 +Epoch [2875/4000] Training [15/16] Loss: 0.00339 +Epoch [2875/4000] Training [16/16] Loss: 0.00408 +Epoch [2875/4000] Training metric {'Train/mean dice_metric': 0.9978545904159546, 'Train/mean miou_metric': 0.9954354763031006, 'Train/mean f1': 0.99283367395401, 'Train/mean precision': 0.98812335729599, 'Train/mean recall': 0.9975891709327698, 'Train/mean hd95_metric': 0.8481454849243164} +Epoch [2875/4000] Validation [1/4] Loss: 0.32121 focal_loss 0.26261 dice_loss 0.05859 +Epoch [2875/4000] Validation [2/4] Loss: 0.39588 focal_loss 0.28980 dice_loss 0.10608 +Epoch [2875/4000] Validation [3/4] Loss: 0.46703 focal_loss 0.37765 dice_loss 0.08938 +Epoch [2875/4000] Validation [4/4] Loss: 0.36395 focal_loss 0.25743 dice_loss 0.10653 +Epoch [2875/4000] Validation metric {'Val/mean dice_metric': 0.9744521379470825, 'Val/mean miou_metric': 0.9596863985061646, 'Val/mean f1': 0.9761161208152771, 'Val/mean precision': 0.9733428359031677, 'Val/mean recall': 0.9789050817489624, 'Val/mean hd95_metric': 4.891005516052246} +Cheakpoint... +Epoch [2875/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744521379470825, 'Val/mean miou_metric': 0.9596863985061646, 'Val/mean f1': 0.9761161208152771, 'Val/mean precision': 0.9733428359031677, 'Val/mean recall': 0.9789050817489624, 'Val/mean hd95_metric': 4.891005516052246} +Epoch [2876/4000] Training [1/16] Loss: 0.00309 +Epoch [2876/4000] Training [2/16] Loss: 0.00310 +Epoch [2876/4000] Training [3/16] Loss: 0.00406 +Epoch [2876/4000] Training [4/16] Loss: 0.00280 +Epoch [2876/4000] Training [5/16] Loss: 0.00514 +Epoch [2876/4000] Training [6/16] Loss: 0.00338 +Epoch [2876/4000] Training [7/16] Loss: 0.00262 +Epoch [2876/4000] Training [8/16] Loss: 0.00385 +Epoch [2876/4000] Training [9/16] Loss: 0.00236 +Epoch [2876/4000] Training [10/16] Loss: 0.00275 +Epoch [2876/4000] Training [11/16] Loss: 0.00377 +Epoch [2876/4000] Training [12/16] Loss: 0.00327 +Epoch [2876/4000] Training [13/16] Loss: 0.00382 +Epoch [2876/4000] Training [14/16] Loss: 0.00440 +Epoch [2876/4000] Training [15/16] Loss: 0.00256 +Epoch [2876/4000] Training [16/16] Loss: 0.00308 +Epoch [2876/4000] Training metric {'Train/mean dice_metric': 0.9981275796890259, 'Train/mean miou_metric': 0.9959800243377686, 'Train/mean f1': 0.9932226538658142, 'Train/mean precision': 0.9886304140090942, 'Train/mean recall': 0.9978578090667725, 'Train/mean hd95_metric': 0.82248854637146} +Epoch [2876/4000] Validation [1/4] Loss: 0.32570 focal_loss 0.26526 dice_loss 0.06044 +Epoch [2876/4000] Validation [2/4] Loss: 0.39615 focal_loss 0.29062 dice_loss 0.10553 +Epoch [2876/4000] Validation [3/4] Loss: 0.50412 focal_loss 0.41038 dice_loss 0.09374 +Epoch [2876/4000] Validation [4/4] Loss: 0.35601 focal_loss 0.25802 dice_loss 0.09799 +Epoch [2876/4000] Validation metric {'Val/mean dice_metric': 0.9752376675605774, 'Val/mean miou_metric': 0.960570216178894, 'Val/mean f1': 0.9761918187141418, 'Val/mean precision': 0.9733960628509521, 'Val/mean recall': 0.9790037870407104, 'Val/mean hd95_metric': 5.190547943115234} +Cheakpoint... +Epoch [2876/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752376675605774, 'Val/mean miou_metric': 0.960570216178894, 'Val/mean f1': 0.9761918187141418, 'Val/mean precision': 0.9733960628509521, 'Val/mean recall': 0.9790037870407104, 'Val/mean hd95_metric': 5.190547943115234} +Epoch [2877/4000] Training [1/16] Loss: 0.00296 +Epoch [2877/4000] Training [2/16] Loss: 0.00301 +Epoch [2877/4000] Training [3/16] Loss: 0.00421 +Epoch [2877/4000] Training [4/16] Loss: 0.00316 +Epoch [2877/4000] Training [5/16] Loss: 0.00359 +Epoch [2877/4000] Training [6/16] Loss: 0.00326 +Epoch [2877/4000] Training [7/16] Loss: 0.00383 +Epoch [2877/4000] Training [8/16] Loss: 0.00221 +Epoch [2877/4000] Training [9/16] Loss: 0.00316 +Epoch [2877/4000] Training [10/16] Loss: 0.00454 +Epoch [2877/4000] Training [11/16] Loss: 0.00330 +Epoch [2877/4000] Training [12/16] Loss: 0.00280 +Epoch [2877/4000] Training [13/16] Loss: 0.00291 +Epoch [2877/4000] Training [14/16] Loss: 0.00339 +Epoch [2877/4000] Training [15/16] Loss: 0.00392 +Epoch [2877/4000] Training [16/16] Loss: 0.00353 +Epoch [2877/4000] Training metric {'Train/mean dice_metric': 0.998069703578949, 'Train/mean miou_metric': 0.9958629608154297, 'Train/mean f1': 0.9931349754333496, 'Train/mean precision': 0.9884442687034607, 'Train/mean recall': 0.9978703856468201, 'Train/mean hd95_metric': 0.8262971043586731} +Epoch [2877/4000] Validation [1/4] Loss: 0.41366 focal_loss 0.34764 dice_loss 0.06602 +Epoch [2877/4000] Validation [2/4] Loss: 0.76850 focal_loss 0.57104 dice_loss 0.19746 +Epoch [2877/4000] Validation [3/4] Loss: 0.23939 focal_loss 0.18047 dice_loss 0.05892 +Epoch [2877/4000] Validation [4/4] Loss: 0.28728 focal_loss 0.20628 dice_loss 0.08100 +Epoch [2877/4000] Validation metric {'Val/mean dice_metric': 0.9735864400863647, 'Val/mean miou_metric': 0.9587938189506531, 'Val/mean f1': 0.9757474660873413, 'Val/mean precision': 0.9734414219856262, 'Val/mean recall': 0.9780643582344055, 'Val/mean hd95_metric': 5.064803600311279} +Cheakpoint... +Epoch [2877/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735864400863647, 'Val/mean miou_metric': 0.9587938189506531, 'Val/mean f1': 0.9757474660873413, 'Val/mean precision': 0.9734414219856262, 'Val/mean recall': 0.9780643582344055, 'Val/mean hd95_metric': 5.064803600311279} +Epoch [2878/4000] Training [1/16] Loss: 0.00326 +Epoch [2878/4000] Training [2/16] Loss: 0.00358 +Epoch [2878/4000] Training [3/16] Loss: 0.00377 +Epoch [2878/4000] Training [4/16] Loss: 0.00310 +Epoch [2878/4000] Training [5/16] Loss: 0.00250 +Epoch [2878/4000] Training [6/16] Loss: 0.00573 +Epoch [2878/4000] Training [7/16] Loss: 0.00379 +Epoch [2878/4000] Training [8/16] Loss: 0.00404 +Epoch [2878/4000] Training [9/16] Loss: 0.00341 +Epoch [2878/4000] Training [10/16] Loss: 0.00312 +Epoch [2878/4000] Training [11/16] Loss: 0.00303 +Epoch [2878/4000] Training [12/16] Loss: 0.00396 +Epoch [2878/4000] Training [13/16] Loss: 0.00310 +Epoch [2878/4000] Training [14/16] Loss: 0.00316 +Epoch [2878/4000] Training [15/16] Loss: 0.00296 +Epoch [2878/4000] Training [16/16] Loss: 0.00291 +Epoch [2878/4000] Training metric {'Train/mean dice_metric': 0.9978690147399902, 'Train/mean miou_metric': 0.9954783320426941, 'Train/mean f1': 0.9930691719055176, 'Train/mean precision': 0.9885309338569641, 'Train/mean recall': 0.9976493120193481, 'Train/mean hd95_metric': 0.8862709999084473} +Epoch [2878/4000] Validation [1/4] Loss: 0.31956 focal_loss 0.26245 dice_loss 0.05711 +Epoch [2878/4000] Validation [2/4] Loss: 0.83282 focal_loss 0.64574 dice_loss 0.18709 +Epoch [2878/4000] Validation [3/4] Loss: 0.25832 focal_loss 0.19372 dice_loss 0.06460 +Epoch [2878/4000] Validation [4/4] Loss: 0.29739 focal_loss 0.20586 dice_loss 0.09153 +Epoch [2878/4000] Validation metric {'Val/mean dice_metric': 0.9749475717544556, 'Val/mean miou_metric': 0.9609823226928711, 'Val/mean f1': 0.9760156273841858, 'Val/mean precision': 0.9723998308181763, 'Val/mean recall': 0.9796582460403442, 'Val/mean hd95_metric': 5.648176193237305} +Cheakpoint... +Epoch [2878/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749475717544556, 'Val/mean miou_metric': 0.9609823226928711, 'Val/mean f1': 0.9760156273841858, 'Val/mean precision': 0.9723998308181763, 'Val/mean recall': 0.9796582460403442, 'Val/mean hd95_metric': 5.648176193237305} +Epoch [2879/4000] Training [1/16] Loss: 0.00299 +Epoch [2879/4000] Training [2/16] Loss: 0.00414 +Epoch [2879/4000] Training [3/16] Loss: 0.00291 +Epoch [2879/4000] Training [4/16] Loss: 0.00466 +Epoch [2879/4000] Training [5/16] Loss: 0.00369 +Epoch [2879/4000] Training [6/16] Loss: 0.00285 +Epoch [2879/4000] Training [7/16] Loss: 0.00303 +Epoch [2879/4000] Training [8/16] Loss: 0.00384 +Epoch [2879/4000] Training [9/16] Loss: 0.00251 +Epoch [2879/4000] Training [10/16] Loss: 0.00267 +Epoch [2879/4000] Training [11/16] Loss: 0.00285 +Epoch [2879/4000] Training [12/16] Loss: 0.00487 +Epoch [2879/4000] Training [13/16] Loss: 0.00355 +Epoch [2879/4000] Training [14/16] Loss: 0.00345 +Epoch [2879/4000] Training [15/16] Loss: 0.00282 +Epoch [2879/4000] Training [16/16] Loss: 0.00266 +Epoch [2879/4000] Training metric {'Train/mean dice_metric': 0.9980343580245972, 'Train/mean miou_metric': 0.9957940578460693, 'Train/mean f1': 0.9931043386459351, 'Train/mean precision': 0.9884602427482605, 'Train/mean recall': 0.9977923035621643, 'Train/mean hd95_metric': 0.8580354452133179} +Epoch [2879/4000] Validation [1/4] Loss: 0.29996 focal_loss 0.24415 dice_loss 0.05581 +Epoch [2879/4000] Validation [2/4] Loss: 0.48425 focal_loss 0.35684 dice_loss 0.12741 +Epoch [2879/4000] Validation [3/4] Loss: 0.48953 focal_loss 0.39976 dice_loss 0.08977 +Epoch [2879/4000] Validation [4/4] Loss: 0.28331 focal_loss 0.19720 dice_loss 0.08610 +Epoch [2879/4000] Validation metric {'Val/mean dice_metric': 0.9748103022575378, 'Val/mean miou_metric': 0.9603919982910156, 'Val/mean f1': 0.9763885736465454, 'Val/mean precision': 0.9730829000473022, 'Val/mean recall': 0.979716956615448, 'Val/mean hd95_metric': 5.193613052368164} +Cheakpoint... +Epoch [2879/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748103022575378, 'Val/mean miou_metric': 0.9603919982910156, 'Val/mean f1': 0.9763885736465454, 'Val/mean precision': 0.9730829000473022, 'Val/mean recall': 0.979716956615448, 'Val/mean hd95_metric': 5.193613052368164} +Epoch [2880/4000] Training [1/16] Loss: 0.00339 +Epoch [2880/4000] Training [2/16] Loss: 0.00343 +Epoch [2880/4000] Training [3/16] Loss: 0.00458 +Epoch [2880/4000] Training [4/16] Loss: 0.00310 +Epoch [2880/4000] Training [5/16] Loss: 0.00313 +Epoch [2880/4000] Training [6/16] Loss: 0.00275 +Epoch [2880/4000] Training [7/16] Loss: 0.00464 +Epoch [2880/4000] Training [8/16] Loss: 0.00390 +Epoch [2880/4000] Training [9/16] Loss: 0.00713 +Epoch [2880/4000] Training [10/16] Loss: 0.00378 +Epoch [2880/4000] Training [11/16] Loss: 0.00385 +Epoch [2880/4000] Training [12/16] Loss: 0.00445 +Epoch [2880/4000] Training [13/16] Loss: 0.00292 +Epoch [2880/4000] Training [14/16] Loss: 0.00521 +Epoch [2880/4000] Training [15/16] Loss: 0.00294 +Epoch [2880/4000] Training [16/16] Loss: 0.00352 +Epoch [2880/4000] Training metric {'Train/mean dice_metric': 0.9977840185165405, 'Train/mean miou_metric': 0.9953137636184692, 'Train/mean f1': 0.9930123090744019, 'Train/mean precision': 0.9885547161102295, 'Train/mean recall': 0.9975103139877319, 'Train/mean hd95_metric': 0.8483331203460693} +Epoch [2880/4000] Validation [1/4] Loss: 0.48976 focal_loss 0.39965 dice_loss 0.09011 +Epoch [2880/4000] Validation [2/4] Loss: 0.42727 focal_loss 0.31311 dice_loss 0.11417 +Epoch [2880/4000] Validation [3/4] Loss: 0.49735 focal_loss 0.40322 dice_loss 0.09413 +Epoch [2880/4000] Validation [4/4] Loss: 0.27914 focal_loss 0.19410 dice_loss 0.08504 +Epoch [2880/4000] Validation metric {'Val/mean dice_metric': 0.9756795763969421, 'Val/mean miou_metric': 0.9606077075004578, 'Val/mean f1': 0.9762648940086365, 'Val/mean precision': 0.9733750820159912, 'Val/mean recall': 0.9791719317436218, 'Val/mean hd95_metric': 4.881814002990723} +Cheakpoint... +Epoch [2880/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756795763969421, 'Val/mean miou_metric': 0.9606077075004578, 'Val/mean f1': 0.9762648940086365, 'Val/mean precision': 0.9733750820159912, 'Val/mean recall': 0.9791719317436218, 'Val/mean hd95_metric': 4.881814002990723} +Epoch [2881/4000] Training [1/16] Loss: 0.00279 +Epoch [2881/4000] Training [2/16] Loss: 0.00319 +Epoch [2881/4000] Training [3/16] Loss: 0.00252 +Epoch [2881/4000] Training [4/16] Loss: 0.00314 +Epoch [2881/4000] Training [5/16] Loss: 0.00493 +Epoch [2881/4000] Training [6/16] Loss: 0.00327 +Epoch [2881/4000] Training [7/16] Loss: 0.00293 +Epoch [2881/4000] Training [8/16] Loss: 0.00355 +Epoch [2881/4000] Training [9/16] Loss: 0.00460 +Epoch [2881/4000] Training [10/16] Loss: 0.00294 +Epoch [2881/4000] Training [11/16] Loss: 0.00413 +Epoch [2881/4000] Training [12/16] Loss: 0.00344 +Epoch [2881/4000] Training [13/16] Loss: 0.00340 +Epoch [2881/4000] Training [14/16] Loss: 0.00335 +Epoch [2881/4000] Training [15/16] Loss: 0.00404 +Epoch [2881/4000] Training [16/16] Loss: 0.00274 +Epoch [2881/4000] Training metric {'Train/mean dice_metric': 0.9979305267333984, 'Train/mean miou_metric': 0.9955971240997314, 'Train/mean f1': 0.9931211471557617, 'Train/mean precision': 0.9885441660881042, 'Train/mean recall': 0.997740626335144, 'Train/mean hd95_metric': 0.8441261053085327} +Epoch [2881/4000] Validation [1/4] Loss: 0.36365 focal_loss 0.30142 dice_loss 0.06223 +Epoch [2881/4000] Validation [2/4] Loss: 0.44255 focal_loss 0.32599 dice_loss 0.11656 +Epoch [2881/4000] Validation [3/4] Loss: 0.27419 focal_loss 0.20525 dice_loss 0.06894 +Epoch [2881/4000] Validation [4/4] Loss: 0.32241 focal_loss 0.21947 dice_loss 0.10294 +Epoch [2881/4000] Validation metric {'Val/mean dice_metric': 0.9756790399551392, 'Val/mean miou_metric': 0.9607589840888977, 'Val/mean f1': 0.9760802984237671, 'Val/mean precision': 0.9730262160301208, 'Val/mean recall': 0.9791536927223206, 'Val/mean hd95_metric': 4.85748291015625} +Cheakpoint... +Epoch [2881/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756790399551392, 'Val/mean miou_metric': 0.9607589840888977, 'Val/mean f1': 0.9760802984237671, 'Val/mean precision': 0.9730262160301208, 'Val/mean recall': 0.9791536927223206, 'Val/mean hd95_metric': 4.85748291015625} +Epoch [2882/4000] Training [1/16] Loss: 0.00403 +Epoch [2882/4000] Training [2/16] Loss: 0.00285 +Epoch [2882/4000] Training [3/16] Loss: 0.00286 +Epoch [2882/4000] Training [4/16] Loss: 0.00461 +Epoch [2882/4000] Training [5/16] Loss: 0.00409 +Epoch [2882/4000] Training [6/16] Loss: 0.00402 +Epoch [2882/4000] Training [7/16] Loss: 0.00341 +Epoch [2882/4000] Training [8/16] Loss: 0.00337 +Epoch [2882/4000] Training [9/16] Loss: 0.00470 +Epoch [2882/4000] Training [10/16] Loss: 0.00285 +Epoch [2882/4000] Training [11/16] Loss: 0.00277 +Epoch [2882/4000] Training [12/16] Loss: 0.00251 +Epoch [2882/4000] Training [13/16] Loss: 0.00310 +Epoch [2882/4000] Training [14/16] Loss: 0.00478 +Epoch [2882/4000] Training [15/16] Loss: 0.00678 +Epoch [2882/4000] Training [16/16] Loss: 0.00423 +Epoch [2882/4000] Training metric {'Train/mean dice_metric': 0.9979344606399536, 'Train/mean miou_metric': 0.995600700378418, 'Train/mean f1': 0.9929839372634888, 'Train/mean precision': 0.9883663654327393, 'Train/mean recall': 0.99764484167099, 'Train/mean hd95_metric': 0.833942174911499} +Epoch [2882/4000] Validation [1/4] Loss: 0.33571 focal_loss 0.27628 dice_loss 0.05943 +Epoch [2882/4000] Validation [2/4] Loss: 0.42506 focal_loss 0.31356 dice_loss 0.11149 +Epoch [2882/4000] Validation [3/4] Loss: 0.50150 focal_loss 0.41167 dice_loss 0.08983 +Epoch [2882/4000] Validation [4/4] Loss: 0.57169 focal_loss 0.42312 dice_loss 0.14858 +Epoch [2882/4000] Validation metric {'Val/mean dice_metric': 0.9749507904052734, 'Val/mean miou_metric': 0.95989990234375, 'Val/mean f1': 0.9757205247879028, 'Val/mean precision': 0.9730249047279358, 'Val/mean recall': 0.9784312844276428, 'Val/mean hd95_metric': 5.087675094604492} +Cheakpoint... +Epoch [2882/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749507904052734, 'Val/mean miou_metric': 0.95989990234375, 'Val/mean f1': 0.9757205247879028, 'Val/mean precision': 0.9730249047279358, 'Val/mean recall': 0.9784312844276428, 'Val/mean hd95_metric': 5.087675094604492} +Epoch [2883/4000] Training [1/16] Loss: 0.00312 +Epoch [2883/4000] Training [2/16] Loss: 0.00413 +Epoch [2883/4000] Training [3/16] Loss: 0.00427 +Epoch [2883/4000] Training [4/16] Loss: 0.00358 +Epoch [2883/4000] Training [5/16] Loss: 0.00388 +Epoch [2883/4000] Training [6/16] Loss: 0.00297 +Epoch [2883/4000] Training [7/16] Loss: 0.00321 +Epoch [2883/4000] Training [8/16] Loss: 0.00403 +Epoch [2883/4000] Training [9/16] Loss: 0.00212 +Epoch [2883/4000] Training [10/16] Loss: 0.00244 +Epoch [2883/4000] Training [11/16] Loss: 0.00403 +Epoch [2883/4000] Training [12/16] Loss: 0.00297 +Epoch [2883/4000] Training [13/16] Loss: 0.00372 +Epoch [2883/4000] Training [14/16] Loss: 0.00358 +Epoch [2883/4000] Training [15/16] Loss: 0.00232 +Epoch [2883/4000] Training [16/16] Loss: 0.00357 +Epoch [2883/4000] Training metric {'Train/mean dice_metric': 0.9980049133300781, 'Train/mean miou_metric': 0.9957454204559326, 'Train/mean f1': 0.9931873083114624, 'Train/mean precision': 0.9886627197265625, 'Train/mean recall': 0.9977535009384155, 'Train/mean hd95_metric': 0.8365440368652344} +Epoch [2883/4000] Validation [1/4] Loss: 0.30943 focal_loss 0.25346 dice_loss 0.05597 +Epoch [2883/4000] Validation [2/4] Loss: 0.46572 focal_loss 0.34159 dice_loss 0.12414 +Epoch [2883/4000] Validation [3/4] Loss: 0.24834 focal_loss 0.18446 dice_loss 0.06387 +Epoch [2883/4000] Validation [4/4] Loss: 0.48347 focal_loss 0.35248 dice_loss 0.13099 +Epoch [2883/4000] Validation metric {'Val/mean dice_metric': 0.9740487933158875, 'Val/mean miou_metric': 0.9592808485031128, 'Val/mean f1': 0.9754935503005981, 'Val/mean precision': 0.9720706939697266, 'Val/mean recall': 0.9789406061172485, 'Val/mean hd95_metric': 5.289386749267578} +Cheakpoint... +Epoch [2883/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740487933158875, 'Val/mean miou_metric': 0.9592808485031128, 'Val/mean f1': 0.9754935503005981, 'Val/mean precision': 0.9720706939697266, 'Val/mean recall': 0.9789406061172485, 'Val/mean hd95_metric': 5.289386749267578} +Epoch [2884/4000] Training [1/16] Loss: 0.00233 +Epoch [2884/4000] Training [2/16] Loss: 0.00348 +Epoch [2884/4000] Training [3/16] Loss: 0.00362 +Epoch [2884/4000] Training [4/16] Loss: 0.00485 +Epoch [2884/4000] Training [5/16] Loss: 0.00255 +Epoch [2884/4000] Training [6/16] Loss: 0.00425 +Epoch [2884/4000] Training [7/16] Loss: 0.00298 +Epoch [2884/4000] Training [8/16] Loss: 0.00337 +Epoch [2884/4000] Training [9/16] Loss: 0.00447 +Epoch [2884/4000] Training [10/16] Loss: 0.00322 +Epoch [2884/4000] Training [11/16] Loss: 0.00309 +Epoch [2884/4000] Training [12/16] Loss: 0.00553 +Epoch [2884/4000] Training [13/16] Loss: 0.00310 +Epoch [2884/4000] Training [14/16] Loss: 0.00241 +Epoch [2884/4000] Training [15/16] Loss: 0.00383 +Epoch [2884/4000] Training [16/16] Loss: 0.00422 +Epoch [2884/4000] Training metric {'Train/mean dice_metric': 0.9979491233825684, 'Train/mean miou_metric': 0.9956355690956116, 'Train/mean f1': 0.9932183027267456, 'Train/mean precision': 0.9887375831604004, 'Train/mean recall': 0.997739851474762, 'Train/mean hd95_metric': 0.8549648523330688} +Epoch [2884/4000] Validation [1/4] Loss: 0.37973 focal_loss 0.31595 dice_loss 0.06378 +Epoch [2884/4000] Validation [2/4] Loss: 0.77917 focal_loss 0.58890 dice_loss 0.19026 +Epoch [2884/4000] Validation [3/4] Loss: 0.25088 focal_loss 0.18239 dice_loss 0.06849 +Epoch [2884/4000] Validation [4/4] Loss: 0.46199 focal_loss 0.33977 dice_loss 0.12222 +Epoch [2884/4000] Validation metric {'Val/mean dice_metric': 0.9737812280654907, 'Val/mean miou_metric': 0.9594858288764954, 'Val/mean f1': 0.975683867931366, 'Val/mean precision': 0.9724513292312622, 'Val/mean recall': 0.9789378046989441, 'Val/mean hd95_metric': 5.425168037414551} +Cheakpoint... +Epoch [2884/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737812280654907, 'Val/mean miou_metric': 0.9594858288764954, 'Val/mean f1': 0.975683867931366, 'Val/mean precision': 0.9724513292312622, 'Val/mean recall': 0.9789378046989441, 'Val/mean hd95_metric': 5.425168037414551} +Epoch [2885/4000] Training [1/16] Loss: 0.00321 +Epoch [2885/4000] Training [2/16] Loss: 0.00444 +Epoch [2885/4000] Training [3/16] Loss: 0.00410 +Epoch [2885/4000] Training [4/16] Loss: 0.00482 +Epoch [2885/4000] Training [5/16] Loss: 0.00474 +Epoch [2885/4000] Training [6/16] Loss: 0.00392 +Epoch [2885/4000] Training [7/16] Loss: 0.00323 +Epoch [2885/4000] Training [8/16] Loss: 0.00346 +Epoch [2885/4000] Training [9/16] Loss: 0.00270 +Epoch [2885/4000] Training [10/16] Loss: 0.00330 +Epoch [2885/4000] Training [11/16] Loss: 0.00423 +Epoch [2885/4000] Training [12/16] Loss: 0.00366 +Epoch [2885/4000] Training [13/16] Loss: 0.00220 +Epoch [2885/4000] Training [14/16] Loss: 0.00286 +Epoch [2885/4000] Training [15/16] Loss: 0.00457 +Epoch [2885/4000] Training [16/16] Loss: 0.00366 +Epoch [2885/4000] Training metric {'Train/mean dice_metric': 0.9978073835372925, 'Train/mean miou_metric': 0.9953062534332275, 'Train/mean f1': 0.9922438859939575, 'Train/mean precision': 0.9869270324707031, 'Train/mean recall': 0.9976183176040649, 'Train/mean hd95_metric': 0.8656526803970337} +Epoch [2885/4000] Validation [1/4] Loss: 0.34147 focal_loss 0.27892 dice_loss 0.06255 +Epoch [2885/4000] Validation [2/4] Loss: 1.19950 focal_loss 0.90925 dice_loss 0.29024 +Epoch [2885/4000] Validation [3/4] Loss: 0.24602 focal_loss 0.18281 dice_loss 0.06321 +Epoch [2885/4000] Validation [4/4] Loss: 0.30305 focal_loss 0.21851 dice_loss 0.08454 +Epoch [2885/4000] Validation metric {'Val/mean dice_metric': 0.971713662147522, 'Val/mean miou_metric': 0.9572332501411438, 'Val/mean f1': 0.9751664996147156, 'Val/mean precision': 0.9728067517280579, 'Val/mean recall': 0.9775376915931702, 'Val/mean hd95_metric': 5.565013885498047} +Cheakpoint... +Epoch [2885/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971713662147522, 'Val/mean miou_metric': 0.9572332501411438, 'Val/mean f1': 0.9751664996147156, 'Val/mean precision': 0.9728067517280579, 'Val/mean recall': 0.9775376915931702, 'Val/mean hd95_metric': 5.565013885498047} +Epoch [2886/4000] Training [1/16] Loss: 0.00354 +Epoch [2886/4000] Training [2/16] Loss: 0.00388 +Epoch [2886/4000] Training [3/16] Loss: 0.00357 +Epoch [2886/4000] Training [4/16] Loss: 0.00307 +Epoch [2886/4000] Training [5/16] Loss: 0.00376 +Epoch [2886/4000] Training [6/16] Loss: 0.00279 +Epoch [2886/4000] Training [7/16] Loss: 0.00300 +Epoch [2886/4000] Training [8/16] Loss: 0.00288 +Epoch [2886/4000] Training [9/16] Loss: 0.00279 +Epoch [2886/4000] Training [10/16] Loss: 0.00409 +Epoch [2886/4000] Training [11/16] Loss: 0.00267 +Epoch [2886/4000] Training [12/16] Loss: 0.00322 +Epoch [2886/4000] Training [13/16] Loss: 0.00350 +Epoch [2886/4000] Training [14/16] Loss: 0.00342 +Epoch [2886/4000] Training [15/16] Loss: 0.00365 +Epoch [2886/4000] Training [16/16] Loss: 0.00314 +Epoch [2886/4000] Training metric {'Train/mean dice_metric': 0.9980502128601074, 'Train/mean miou_metric': 0.9958361387252808, 'Train/mean f1': 0.9933342933654785, 'Train/mean precision': 0.9888046979904175, 'Train/mean recall': 0.9979055523872375, 'Train/mean hd95_metric': 0.8428987264633179} +Epoch [2886/4000] Validation [1/4] Loss: 0.30374 focal_loss 0.24512 dice_loss 0.05862 +Epoch [2886/4000] Validation [2/4] Loss: 0.84057 focal_loss 0.64931 dice_loss 0.19125 +Epoch [2886/4000] Validation [3/4] Loss: 0.50596 focal_loss 0.40628 dice_loss 0.09968 +Epoch [2886/4000] Validation [4/4] Loss: 0.28585 focal_loss 0.20472 dice_loss 0.08113 +Epoch [2886/4000] Validation metric {'Val/mean dice_metric': 0.9741509556770325, 'Val/mean miou_metric': 0.9601554870605469, 'Val/mean f1': 0.9765932559967041, 'Val/mean precision': 0.9741143584251404, 'Val/mean recall': 0.9790849089622498, 'Val/mean hd95_metric': 4.902817726135254} +Cheakpoint... +Epoch [2886/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741509556770325, 'Val/mean miou_metric': 0.9601554870605469, 'Val/mean f1': 0.9765932559967041, 'Val/mean precision': 0.9741143584251404, 'Val/mean recall': 0.9790849089622498, 'Val/mean hd95_metric': 4.902817726135254} +Epoch [2887/4000] Training [1/16] Loss: 0.00279 +Epoch [2887/4000] Training [2/16] Loss: 0.00351 +Epoch [2887/4000] Training [3/16] Loss: 0.00453 +Epoch [2887/4000] Training [4/16] Loss: 0.00237 +Epoch [2887/4000] Training [5/16] Loss: 0.00411 +Epoch [2887/4000] Training [6/16] Loss: 0.00279 +Epoch [2887/4000] Training [7/16] Loss: 0.00376 +Epoch [2887/4000] Training [8/16] Loss: 0.00323 +Epoch [2887/4000] Training [9/16] Loss: 0.00318 +Epoch [2887/4000] Training [10/16] Loss: 0.00349 +Epoch [2887/4000] Training [11/16] Loss: 0.00294 +Epoch [2887/4000] Training [12/16] Loss: 0.00269 +Epoch [2887/4000] Training [13/16] Loss: 0.00304 +Epoch [2887/4000] Training [14/16] Loss: 0.00566 +Epoch [2887/4000] Training [15/16] Loss: 0.00254 +Epoch [2887/4000] Training [16/16] Loss: 0.00343 +Epoch [2887/4000] Training metric {'Train/mean dice_metric': 0.9979666471481323, 'Train/mean miou_metric': 0.9956673383712769, 'Train/mean f1': 0.9932335615158081, 'Train/mean precision': 0.9887199997901917, 'Train/mean recall': 0.9977884888648987, 'Train/mean hd95_metric': 0.8287663459777832} +Epoch [2887/4000] Validation [1/4] Loss: 0.38840 focal_loss 0.32398 dice_loss 0.06442 +Epoch [2887/4000] Validation [2/4] Loss: 0.83320 focal_loss 0.61937 dice_loss 0.21382 +Epoch [2887/4000] Validation [3/4] Loss: 0.47931 focal_loss 0.38579 dice_loss 0.09351 +Epoch [2887/4000] Validation [4/4] Loss: 0.29134 focal_loss 0.20795 dice_loss 0.08339 +Epoch [2887/4000] Validation metric {'Val/mean dice_metric': 0.9709814786911011, 'Val/mean miou_metric': 0.9566470980644226, 'Val/mean f1': 0.9748910665512085, 'Val/mean precision': 0.9725567698478699, 'Val/mean recall': 0.9772366285324097, 'Val/mean hd95_metric': 5.430952072143555} +Cheakpoint... +Epoch [2887/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709814786911011, 'Val/mean miou_metric': 0.9566470980644226, 'Val/mean f1': 0.9748910665512085, 'Val/mean precision': 0.9725567698478699, 'Val/mean recall': 0.9772366285324097, 'Val/mean hd95_metric': 5.430952072143555} +Epoch [2888/4000] Training [1/16] Loss: 0.00468 +Epoch [2888/4000] Training [2/16] Loss: 0.00311 +Epoch [2888/4000] Training [3/16] Loss: 0.00281 +Epoch [2888/4000] Training [4/16] Loss: 0.00282 +Epoch [2888/4000] Training [5/16] Loss: 0.00270 +Epoch [2888/4000] Training [6/16] Loss: 0.00513 +Epoch [2888/4000] Training [7/16] Loss: 0.00320 +Epoch [2888/4000] Training [8/16] Loss: 0.00313 +Epoch [2888/4000] Training [9/16] Loss: 0.00277 +Epoch [2888/4000] Training [10/16] Loss: 0.00410 +Epoch [2888/4000] Training [11/16] Loss: 0.00346 +Epoch [2888/4000] Training [12/16] Loss: 0.00319 +Epoch [2888/4000] Training [13/16] Loss: 0.00420 +Epoch [2888/4000] Training [14/16] Loss: 0.00373 +Epoch [2888/4000] Training [15/16] Loss: 0.00282 +Epoch [2888/4000] Training [16/16] Loss: 0.00539 +Epoch [2888/4000] Training metric {'Train/mean dice_metric': 0.997869610786438, 'Train/mean miou_metric': 0.995448112487793, 'Train/mean f1': 0.9925181269645691, 'Train/mean precision': 0.9874361753463745, 'Train/mean recall': 0.9976526498794556, 'Train/mean hd95_metric': 0.8146857619285583} +Epoch [2888/4000] Validation [1/4] Loss: 0.33985 focal_loss 0.27975 dice_loss 0.06011 +Epoch [2888/4000] Validation [2/4] Loss: 0.41197 focal_loss 0.30074 dice_loss 0.11123 +Epoch [2888/4000] Validation [3/4] Loss: 0.50599 focal_loss 0.41212 dice_loss 0.09387 +Epoch [2888/4000] Validation [4/4] Loss: 0.56995 focal_loss 0.42592 dice_loss 0.14403 +Epoch [2888/4000] Validation metric {'Val/mean dice_metric': 0.9725849032402039, 'Val/mean miou_metric': 0.9576331377029419, 'Val/mean f1': 0.9747984409332275, 'Val/mean precision': 0.9724245071411133, 'Val/mean recall': 0.9771838188171387, 'Val/mean hd95_metric': 5.160708904266357} +Cheakpoint... +Epoch [2888/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725849032402039, 'Val/mean miou_metric': 0.9576331377029419, 'Val/mean f1': 0.9747984409332275, 'Val/mean precision': 0.9724245071411133, 'Val/mean recall': 0.9771838188171387, 'Val/mean hd95_metric': 5.160708904266357} +Epoch [2889/4000] Training [1/16] Loss: 0.00304 +Epoch [2889/4000] Training [2/16] Loss: 0.00272 +Epoch [2889/4000] Training [3/16] Loss: 0.00256 +Epoch [2889/4000] Training [4/16] Loss: 0.00401 +Epoch [2889/4000] Training [5/16] Loss: 0.00320 +Epoch [2889/4000] Training [6/16] Loss: 0.00253 +Epoch [2889/4000] Training [7/16] Loss: 0.00365 +Epoch [2889/4000] Training [8/16] Loss: 0.00301 +Epoch [2889/4000] Training [9/16] Loss: 0.00312 +Epoch [2889/4000] Training [10/16] Loss: 0.00311 +Epoch [2889/4000] Training [11/16] Loss: 0.00463 +Epoch [2889/4000] Training [12/16] Loss: 0.00372 +Epoch [2889/4000] Training [13/16] Loss: 0.00332 +Epoch [2889/4000] Training [14/16] Loss: 0.00316 +Epoch [2889/4000] Training [15/16] Loss: 0.00390 +Epoch [2889/4000] Training [16/16] Loss: 0.00406 +Epoch [2889/4000] Training metric {'Train/mean dice_metric': 0.9980724453926086, 'Train/mean miou_metric': 0.995881199836731, 'Train/mean f1': 0.9933300614356995, 'Train/mean precision': 0.9888297319412231, 'Train/mean recall': 0.9978715181350708, 'Train/mean hd95_metric': 0.81321120262146} +Epoch [2889/4000] Validation [1/4] Loss: 0.37643 focal_loss 0.30952 dice_loss 0.06691 +Epoch [2889/4000] Validation [2/4] Loss: 0.40774 focal_loss 0.29324 dice_loss 0.11450 +Epoch [2889/4000] Validation [3/4] Loss: 0.31941 focal_loss 0.24096 dice_loss 0.07844 +Epoch [2889/4000] Validation [4/4] Loss: 0.28862 focal_loss 0.19355 dice_loss 0.09507 +Epoch [2889/4000] Validation metric {'Val/mean dice_metric': 0.9728334546089172, 'Val/mean miou_metric': 0.9579986333847046, 'Val/mean f1': 0.9756404161453247, 'Val/mean precision': 0.9730979800224304, 'Val/mean recall': 0.9781962037086487, 'Val/mean hd95_metric': 5.688990116119385} +Cheakpoint... +Epoch [2889/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728334546089172, 'Val/mean miou_metric': 0.9579986333847046, 'Val/mean f1': 0.9756404161453247, 'Val/mean precision': 0.9730979800224304, 'Val/mean recall': 0.9781962037086487, 'Val/mean hd95_metric': 5.688990116119385} +Epoch [2890/4000] Training [1/16] Loss: 0.00264 +Epoch [2890/4000] Training [2/16] Loss: 0.00340 +Epoch [2890/4000] Training [3/16] Loss: 0.00312 +Epoch [2890/4000] Training [4/16] Loss: 0.00300 +Epoch [2890/4000] Training [5/16] Loss: 0.00368 +Epoch [2890/4000] Training [6/16] Loss: 0.00258 +Epoch [2890/4000] Training [7/16] Loss: 0.00344 +Epoch [2890/4000] Training [8/16] Loss: 0.00327 +Epoch [2890/4000] Training [9/16] Loss: 0.00260 +Epoch [2890/4000] Training [10/16] Loss: 0.00465 +Epoch [2890/4000] Training [11/16] Loss: 0.00287 +Epoch [2890/4000] Training [12/16] Loss: 0.00348 +Epoch [2890/4000] Training [13/16] Loss: 0.00348 +Epoch [2890/4000] Training [14/16] Loss: 0.00338 +Epoch [2890/4000] Training [15/16] Loss: 0.00372 +Epoch [2890/4000] Training [16/16] Loss: 0.00293 +Epoch [2890/4000] Training metric {'Train/mean dice_metric': 0.9980406165122986, 'Train/mean miou_metric': 0.9958156943321228, 'Train/mean f1': 0.9932501912117004, 'Train/mean precision': 0.988713800907135, 'Train/mean recall': 0.9978284239768982, 'Train/mean hd95_metric': 0.8201454877853394} +Epoch [2890/4000] Validation [1/4] Loss: 0.37462 focal_loss 0.31318 dice_loss 0.06143 +Epoch [2890/4000] Validation [2/4] Loss: 0.38324 focal_loss 0.27602 dice_loss 0.10722 +Epoch [2890/4000] Validation [3/4] Loss: 0.48789 focal_loss 0.39682 dice_loss 0.09107 +Epoch [2890/4000] Validation [4/4] Loss: 0.34277 focal_loss 0.24740 dice_loss 0.09537 +Epoch [2890/4000] Validation metric {'Val/mean dice_metric': 0.9745470285415649, 'Val/mean miou_metric': 0.959996223449707, 'Val/mean f1': 0.9755212068557739, 'Val/mean precision': 0.9725184440612793, 'Val/mean recall': 0.9785426259040833, 'Val/mean hd95_metric': 5.299690246582031} +Cheakpoint... +Epoch [2890/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745470285415649, 'Val/mean miou_metric': 0.959996223449707, 'Val/mean f1': 0.9755212068557739, 'Val/mean precision': 0.9725184440612793, 'Val/mean recall': 0.9785426259040833, 'Val/mean hd95_metric': 5.299690246582031} +Epoch [2891/4000] Training [1/16] Loss: 0.00319 +Epoch [2891/4000] Training [2/16] Loss: 0.00256 +Epoch [2891/4000] Training [3/16] Loss: 0.00437 +Epoch [2891/4000] Training [4/16] Loss: 0.00447 +Epoch [2891/4000] Training [5/16] Loss: 0.00461 +Epoch [2891/4000] Training [6/16] Loss: 0.00323 +Epoch [2891/4000] Training [7/16] Loss: 0.00305 +Epoch [2891/4000] Training [8/16] Loss: 0.00363 +Epoch [2891/4000] Training [9/16] Loss: 0.00341 +Epoch [2891/4000] Training [10/16] Loss: 0.00486 +Epoch [2891/4000] Training [11/16] Loss: 0.00336 +Epoch [2891/4000] Training [12/16] Loss: 0.00413 +Epoch [2891/4000] Training [13/16] Loss: 0.00367 +Epoch [2891/4000] Training [14/16] Loss: 0.00257 +Epoch [2891/4000] Training [15/16] Loss: 0.00390 +Epoch [2891/4000] Training [16/16] Loss: 0.00398 +Epoch [2891/4000] Training metric {'Train/mean dice_metric': 0.9978889226913452, 'Train/mean miou_metric': 0.9955309629440308, 'Train/mean f1': 0.993235170841217, 'Train/mean precision': 0.9886987805366516, 'Train/mean recall': 0.99781334400177, 'Train/mean hd95_metric': 0.847957968711853} +Epoch [2891/4000] Validation [1/4] Loss: 0.33092 focal_loss 0.27066 dice_loss 0.06026 +Epoch [2891/4000] Validation [2/4] Loss: 0.39615 focal_loss 0.28398 dice_loss 0.11218 +Epoch [2891/4000] Validation [3/4] Loss: 0.51136 focal_loss 0.42044 dice_loss 0.09092 +Epoch [2891/4000] Validation [4/4] Loss: 0.43141 focal_loss 0.31020 dice_loss 0.12121 +Epoch [2891/4000] Validation metric {'Val/mean dice_metric': 0.9734053611755371, 'Val/mean miou_metric': 0.9583314657211304, 'Val/mean f1': 0.9756994247436523, 'Val/mean precision': 0.9729676842689514, 'Val/mean recall': 0.9784465432167053, 'Val/mean hd95_metric': 5.598817825317383} +Cheakpoint... +Epoch [2891/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734053611755371, 'Val/mean miou_metric': 0.9583314657211304, 'Val/mean f1': 0.9756994247436523, 'Val/mean precision': 0.9729676842689514, 'Val/mean recall': 0.9784465432167053, 'Val/mean hd95_metric': 5.598817825317383} +Epoch [2892/4000] Training [1/16] Loss: 0.00457 +Epoch [2892/4000] Training [2/16] Loss: 0.00288 +Epoch [2892/4000] Training [3/16] Loss: 0.00230 +Epoch [2892/4000] Training [4/16] Loss: 0.00285 +Epoch [2892/4000] Training [5/16] Loss: 0.00273 +Epoch [2892/4000] Training [6/16] Loss: 0.00442 +Epoch [2892/4000] Training [7/16] Loss: 0.00886 +Epoch [2892/4000] Training [8/16] Loss: 0.00226 +Epoch [2892/4000] Training [9/16] Loss: 0.00288 +Epoch [2892/4000] Training [10/16] Loss: 0.00378 +Epoch [2892/4000] Training [11/16] Loss: 0.00434 +Epoch [2892/4000] Training [12/16] Loss: 0.00369 +Epoch [2892/4000] Training [13/16] Loss: 0.00413 +Epoch [2892/4000] Training [14/16] Loss: 0.00362 +Epoch [2892/4000] Training [15/16] Loss: 0.00511 +Epoch [2892/4000] Training [16/16] Loss: 0.00442 +Epoch [2892/4000] Training metric {'Train/mean dice_metric': 0.9978263974189758, 'Train/mean miou_metric': 0.9953482151031494, 'Train/mean f1': 0.9921811819076538, 'Train/mean precision': 0.9868049621582031, 'Train/mean recall': 0.9976163506507874, 'Train/mean hd95_metric': 0.8502184748649597} +Epoch [2892/4000] Validation [1/4] Loss: 0.33408 focal_loss 0.27229 dice_loss 0.06179 +Epoch [2892/4000] Validation [2/4] Loss: 0.40151 focal_loss 0.28920 dice_loss 0.11231 +Epoch [2892/4000] Validation [3/4] Loss: 0.48171 focal_loss 0.39449 dice_loss 0.08722 +Epoch [2892/4000] Validation [4/4] Loss: 0.38681 focal_loss 0.25738 dice_loss 0.12942 +Epoch [2892/4000] Validation metric {'Val/mean dice_metric': 0.9716876745223999, 'Val/mean miou_metric': 0.9572793245315552, 'Val/mean f1': 0.9748628735542297, 'Val/mean precision': 0.9719260931015015, 'Val/mean recall': 0.9778174161911011, 'Val/mean hd95_metric': 6.034670352935791} +Cheakpoint... +Epoch [2892/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716876745223999, 'Val/mean miou_metric': 0.9572793245315552, 'Val/mean f1': 0.9748628735542297, 'Val/mean precision': 0.9719260931015015, 'Val/mean recall': 0.9778174161911011, 'Val/mean hd95_metric': 6.034670352935791} +Epoch [2893/4000] Training [1/16] Loss: 0.00265 +Epoch [2893/4000] Training [2/16] Loss: 0.00425 +Epoch [2893/4000] Training [3/16] Loss: 0.00384 +Epoch [2893/4000] Training [4/16] Loss: 0.00396 +Epoch [2893/4000] Training [5/16] Loss: 0.00388 +Epoch [2893/4000] Training [6/16] Loss: 0.00496 +Epoch [2893/4000] Training [7/16] Loss: 0.00263 +Epoch [2893/4000] Training [8/16] Loss: 0.00364 +Epoch [2893/4000] Training [9/16] Loss: 0.00350 +Epoch [2893/4000] Training [10/16] Loss: 0.00360 +Epoch [2893/4000] Training [11/16] Loss: 0.00257 +Epoch [2893/4000] Training [12/16] Loss: 0.00357 +Epoch [2893/4000] Training [13/16] Loss: 0.00323 +Epoch [2893/4000] Training [14/16] Loss: 0.00316 +Epoch [2893/4000] Training [15/16] Loss: 0.00346 +Epoch [2893/4000] Training [16/16] Loss: 0.00455 +Epoch [2893/4000] Training metric {'Train/mean dice_metric': 0.9979586601257324, 'Train/mean miou_metric': 0.9955926537513733, 'Train/mean f1': 0.9917482733726501, 'Train/mean precision': 0.985849142074585, 'Train/mean recall': 0.9977184534072876, 'Train/mean hd95_metric': 0.8478372097015381} +Epoch [2893/4000] Validation [1/4] Loss: 0.33729 focal_loss 0.27709 dice_loss 0.06020 +Epoch [2893/4000] Validation [2/4] Loss: 0.38469 focal_loss 0.28016 dice_loss 0.10454 +Epoch [2893/4000] Validation [3/4] Loss: 0.51847 focal_loss 0.42326 dice_loss 0.09521 +Epoch [2893/4000] Validation [4/4] Loss: 0.37478 focal_loss 0.26313 dice_loss 0.11164 +Epoch [2893/4000] Validation metric {'Val/mean dice_metric': 0.9735652208328247, 'Val/mean miou_metric': 0.9591631889343262, 'Val/mean f1': 0.9748793244361877, 'Val/mean precision': 0.970816433429718, 'Val/mean recall': 0.978976309299469, 'Val/mean hd95_metric': 5.2652387619018555} +Cheakpoint... +Epoch [2893/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735652208328247, 'Val/mean miou_metric': 0.9591631889343262, 'Val/mean f1': 0.9748793244361877, 'Val/mean precision': 0.970816433429718, 'Val/mean recall': 0.978976309299469, 'Val/mean hd95_metric': 5.2652387619018555} +Epoch [2894/4000] Training [1/16] Loss: 0.00375 +Epoch [2894/4000] Training [2/16] Loss: 0.00330 +Epoch [2894/4000] Training [3/16] Loss: 0.00447 +Epoch [2894/4000] Training [4/16] Loss: 0.00297 +Epoch [2894/4000] Training [5/16] Loss: 0.00311 +Epoch [2894/4000] Training [6/16] Loss: 0.00299 +Epoch [2894/4000] Training [7/16] Loss: 0.00372 +Epoch [2894/4000] Training [8/16] Loss: 0.00315 +Epoch [2894/4000] Training [9/16] Loss: 0.00373 +Epoch [2894/4000] Training [10/16] Loss: 0.00260 +Epoch [2894/4000] Training [11/16] Loss: 0.00309 +Epoch [2894/4000] Training [12/16] Loss: 0.00319 +Epoch [2894/4000] Training [13/16] Loss: 0.00632 +Epoch [2894/4000] Training [14/16] Loss: 0.00267 +Epoch [2894/4000] Training [15/16] Loss: 0.00434 +Epoch [2894/4000] Training [16/16] Loss: 0.00427 +Epoch [2894/4000] Training metric {'Train/mean dice_metric': 0.9979763031005859, 'Train/mean miou_metric': 0.9956617951393127, 'Train/mean f1': 0.992624819278717, 'Train/mean precision': 0.9875552654266357, 'Train/mean recall': 0.9977467060089111, 'Train/mean hd95_metric': 0.8624855279922485} +Epoch [2894/4000] Validation [1/4] Loss: 0.33317 focal_loss 0.27233 dice_loss 0.06083 +Epoch [2894/4000] Validation [2/4] Loss: 0.81201 focal_loss 0.62124 dice_loss 0.19077 +Epoch [2894/4000] Validation [3/4] Loss: 0.51571 focal_loss 0.42347 dice_loss 0.09224 +Epoch [2894/4000] Validation [4/4] Loss: 0.52016 focal_loss 0.38297 dice_loss 0.13718 +Epoch [2894/4000] Validation metric {'Val/mean dice_metric': 0.9705365896224976, 'Val/mean miou_metric': 0.9565064311027527, 'Val/mean f1': 0.9742872714996338, 'Val/mean precision': 0.9732286334037781, 'Val/mean recall': 0.9753482937812805, 'Val/mean hd95_metric': 5.830992221832275} +Cheakpoint... +Epoch [2894/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9705], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9705365896224976, 'Val/mean miou_metric': 0.9565064311027527, 'Val/mean f1': 0.9742872714996338, 'Val/mean precision': 0.9732286334037781, 'Val/mean recall': 0.9753482937812805, 'Val/mean hd95_metric': 5.830992221832275} +Epoch [2895/4000] Training [1/16] Loss: 0.00322 +Epoch [2895/4000] Training [2/16] Loss: 0.00376 +Epoch [2895/4000] Training [3/16] Loss: 0.00279 +Epoch [2895/4000] Training [4/16] Loss: 0.00289 +Epoch [2895/4000] Training [5/16] Loss: 0.00330 +Epoch [2895/4000] Training [6/16] Loss: 0.00261 +Epoch [2895/4000] Training [7/16] Loss: 0.00306 +Epoch [2895/4000] Training [8/16] Loss: 0.00399 +Epoch [2895/4000] Training [9/16] Loss: 0.00305 +Epoch [2895/4000] Training [10/16] Loss: 0.00295 +Epoch [2895/4000] Training [11/16] Loss: 0.00314 +Epoch [2895/4000] Training [12/16] Loss: 0.00383 +Epoch [2895/4000] Training [13/16] Loss: 0.00288 +Epoch [2895/4000] Training [14/16] Loss: 0.00319 +Epoch [2895/4000] Training [15/16] Loss: 0.00308 +Epoch [2895/4000] Training [16/16] Loss: 0.00285 +Epoch [2895/4000] Training metric {'Train/mean dice_metric': 0.9981160163879395, 'Train/mean miou_metric': 0.9959617853164673, 'Train/mean f1': 0.9932637810707092, 'Train/mean precision': 0.9887118339538574, 'Train/mean recall': 0.9978578686714172, 'Train/mean hd95_metric': 0.8380159735679626} +Epoch [2895/4000] Validation [1/4] Loss: 0.32208 focal_loss 0.26238 dice_loss 0.05970 +Epoch [2895/4000] Validation [2/4] Loss: 0.61957 focal_loss 0.41775 dice_loss 0.20182 +Epoch [2895/4000] Validation [3/4] Loss: 0.28264 focal_loss 0.21376 dice_loss 0.06887 +Epoch [2895/4000] Validation [4/4] Loss: 0.40583 focal_loss 0.29216 dice_loss 0.11367 +Epoch [2895/4000] Validation metric {'Val/mean dice_metric': 0.9723998308181763, 'Val/mean miou_metric': 0.95787113904953, 'Val/mean f1': 0.9756672382354736, 'Val/mean precision': 0.9734622240066528, 'Val/mean recall': 0.9778822064399719, 'Val/mean hd95_metric': 5.124889850616455} +Cheakpoint... +Epoch [2895/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723998308181763, 'Val/mean miou_metric': 0.95787113904953, 'Val/mean f1': 0.9756672382354736, 'Val/mean precision': 0.9734622240066528, 'Val/mean recall': 0.9778822064399719, 'Val/mean hd95_metric': 5.124889850616455} +Epoch [2896/4000] Training [1/16] Loss: 0.00362 +Epoch [2896/4000] Training [2/16] Loss: 0.00301 +Epoch [2896/4000] Training [3/16] Loss: 0.00208 +Epoch [2896/4000] Training [4/16] Loss: 0.00349 +Epoch [2896/4000] Training [5/16] Loss: 0.00389 +Epoch [2896/4000] Training [6/16] Loss: 0.00374 +Epoch [2896/4000] Training [7/16] Loss: 0.00259 +Epoch [2896/4000] Training [8/16] Loss: 0.00428 +Epoch [2896/4000] Training [9/16] Loss: 0.00437 +Epoch [2896/4000] Training [10/16] Loss: 0.00226 +Epoch [2896/4000] Training [11/16] Loss: 0.00295 +Epoch [2896/4000] Training [12/16] Loss: 0.00267 +Epoch [2896/4000] Training [13/16] Loss: 0.00440 +Epoch [2896/4000] Training [14/16] Loss: 0.00427 +Epoch [2896/4000] Training [15/16] Loss: 0.00218 +Epoch [2896/4000] Training [16/16] Loss: 0.00247 +Epoch [2896/4000] Training metric {'Train/mean dice_metric': 0.9982030391693115, 'Train/mean miou_metric': 0.9961273670196533, 'Train/mean f1': 0.9930633306503296, 'Train/mean precision': 0.9882774949073792, 'Train/mean recall': 0.9978957176208496, 'Train/mean hd95_metric': 0.7893130779266357} +Epoch [2896/4000] Validation [1/4] Loss: 0.32567 focal_loss 0.26687 dice_loss 0.05880 +Epoch [2896/4000] Validation [2/4] Loss: 0.76982 focal_loss 0.56503 dice_loss 0.20478 +Epoch [2896/4000] Validation [3/4] Loss: 0.46881 focal_loss 0.37980 dice_loss 0.08901 +Epoch [2896/4000] Validation [4/4] Loss: 0.27068 focal_loss 0.18882 dice_loss 0.08186 +Epoch [2896/4000] Validation metric {'Val/mean dice_metric': 0.9731847047805786, 'Val/mean miou_metric': 0.9590383768081665, 'Val/mean f1': 0.9758300185203552, 'Val/mean precision': 0.9734561443328857, 'Val/mean recall': 0.9782156348228455, 'Val/mean hd95_metric': 5.029098033905029} +Cheakpoint... +Epoch [2896/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731847047805786, 'Val/mean miou_metric': 0.9590383768081665, 'Val/mean f1': 0.9758300185203552, 'Val/mean precision': 0.9734561443328857, 'Val/mean recall': 0.9782156348228455, 'Val/mean hd95_metric': 5.029098033905029} +Epoch [2897/4000] Training [1/16] Loss: 0.00328 +Epoch [2897/4000] Training [2/16] Loss: 0.00356 +Epoch [2897/4000] Training [3/16] Loss: 0.00335 +Epoch [2897/4000] Training [4/16] Loss: 0.00309 +Epoch [2897/4000] Training [5/16] Loss: 0.00288 +Epoch [2897/4000] Training [6/16] Loss: 0.00362 +Epoch [2897/4000] Training [7/16] Loss: 0.00580 +Epoch [2897/4000] Training [8/16] Loss: 0.00485 +Epoch [2897/4000] Training [9/16] Loss: 0.00361 +Epoch [2897/4000] Training [10/16] Loss: 0.00260 +Epoch [2897/4000] Training [11/16] Loss: 0.00322 +Epoch [2897/4000] Training [12/16] Loss: 0.00420 +Epoch [2897/4000] Training [13/16] Loss: 0.00397 +Epoch [2897/4000] Training [14/16] Loss: 0.00494 +Epoch [2897/4000] Training [15/16] Loss: 0.00319 +Epoch [2897/4000] Training [16/16] Loss: 0.00310 +Epoch [2897/4000] Training metric {'Train/mean dice_metric': 0.9978587627410889, 'Train/mean miou_metric': 0.9954577088356018, 'Train/mean f1': 0.9931828379631042, 'Train/mean precision': 0.9886818528175354, 'Train/mean recall': 0.9977249503135681, 'Train/mean hd95_metric': 0.8425636291503906} +Epoch [2897/4000] Validation [1/4] Loss: 0.35546 focal_loss 0.29340 dice_loss 0.06206 +Epoch [2897/4000] Validation [2/4] Loss: 0.86278 focal_loss 0.66880 dice_loss 0.19397 +Epoch [2897/4000] Validation [3/4] Loss: 0.46226 focal_loss 0.36347 dice_loss 0.09879 +Epoch [2897/4000] Validation [4/4] Loss: 0.44275 focal_loss 0.33269 dice_loss 0.11006 +Epoch [2897/4000] Validation metric {'Val/mean dice_metric': 0.9720918536186218, 'Val/mean miou_metric': 0.9574733972549438, 'Val/mean f1': 0.9756863713264465, 'Val/mean precision': 0.9742313623428345, 'Val/mean recall': 0.9771458506584167, 'Val/mean hd95_metric': 4.916098594665527} +Cheakpoint... +Epoch [2897/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720918536186218, 'Val/mean miou_metric': 0.9574733972549438, 'Val/mean f1': 0.9756863713264465, 'Val/mean precision': 0.9742313623428345, 'Val/mean recall': 0.9771458506584167, 'Val/mean hd95_metric': 4.916098594665527} +Epoch [2898/4000] Training [1/16] Loss: 0.00455 +Epoch [2898/4000] Training [2/16] Loss: 0.00897 +Epoch [2898/4000] Training [3/16] Loss: 0.00326 +Epoch [2898/4000] Training [4/16] Loss: 0.00356 +Epoch [2898/4000] Training [5/16] Loss: 0.00376 +Epoch [2898/4000] Training [6/16] Loss: 0.00291 +Epoch [2898/4000] Training [7/16] Loss: 0.00393 +Epoch [2898/4000] Training [8/16] Loss: 0.00326 +Epoch [2898/4000] Training [9/16] Loss: 0.00332 +Epoch [2898/4000] Training [10/16] Loss: 0.00372 +Epoch [2898/4000] Training [11/16] Loss: 0.00359 +Epoch [2898/4000] Training [12/16] Loss: 0.00334 +Epoch [2898/4000] Training [13/16] Loss: 0.00313 +Epoch [2898/4000] Training [14/16] Loss: 0.00285 +Epoch [2898/4000] Training [15/16] Loss: 0.00316 +Epoch [2898/4000] Training [16/16] Loss: 0.00264 +Epoch [2898/4000] Training metric {'Train/mean dice_metric': 0.9979884624481201, 'Train/mean miou_metric': 0.9956749677658081, 'Train/mean f1': 0.9921547770500183, 'Train/mean precision': 0.9868243932723999, 'Train/mean recall': 0.9975430965423584, 'Train/mean hd95_metric': 0.8632348775863647} +Epoch [2898/4000] Validation [1/4] Loss: 0.31947 focal_loss 0.26060 dice_loss 0.05887 +Epoch [2898/4000] Validation [2/4] Loss: 0.42373 focal_loss 0.30820 dice_loss 0.11553 +Epoch [2898/4000] Validation [3/4] Loss: 0.47758 focal_loss 0.37374 dice_loss 0.10383 +Epoch [2898/4000] Validation [4/4] Loss: 0.35373 focal_loss 0.25240 dice_loss 0.10133 +Epoch [2898/4000] Validation metric {'Val/mean dice_metric': 0.9744242429733276, 'Val/mean miou_metric': 0.9598028063774109, 'Val/mean f1': 0.9754664301872253, 'Val/mean precision': 0.9719248414039612, 'Val/mean recall': 0.979033887386322, 'Val/mean hd95_metric': 4.9058661460876465} +Cheakpoint... +Epoch [2898/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744242429733276, 'Val/mean miou_metric': 0.9598028063774109, 'Val/mean f1': 0.9754664301872253, 'Val/mean precision': 0.9719248414039612, 'Val/mean recall': 0.979033887386322, 'Val/mean hd95_metric': 4.9058661460876465} +Epoch [2899/4000] Training [1/16] Loss: 0.00297 +Epoch [2899/4000] Training [2/16] Loss: 0.00303 +Epoch [2899/4000] Training [3/16] Loss: 0.00412 +Epoch [2899/4000] Training [4/16] Loss: 0.00359 +Epoch [2899/4000] Training [5/16] Loss: 0.00240 +Epoch [2899/4000] Training [6/16] Loss: 0.00512 +Epoch [2899/4000] Training [7/16] Loss: 0.00323 +Epoch [2899/4000] Training [8/16] Loss: 0.00280 +Epoch [2899/4000] Training [9/16] Loss: 0.00392 +Epoch [2899/4000] Training [10/16] Loss: 0.00450 +Epoch [2899/4000] Training [11/16] Loss: 0.00402 +Epoch [2899/4000] Training [12/16] Loss: 0.00347 +Epoch [2899/4000] Training [13/16] Loss: 0.00203 +Epoch [2899/4000] Training [14/16] Loss: 0.00271 +Epoch [2899/4000] Training [15/16] Loss: 0.00268 +Epoch [2899/4000] Training [16/16] Loss: 0.00224 +Epoch [2899/4000] Training metric {'Train/mean dice_metric': 0.9977844953536987, 'Train/mean miou_metric': 0.9953153133392334, 'Train/mean f1': 0.9927681088447571, 'Train/mean precision': 0.9879364967346191, 'Train/mean recall': 0.997647225856781, 'Train/mean hd95_metric': 0.8518054485321045} +Epoch [2899/4000] Validation [1/4] Loss: 0.35647 focal_loss 0.29131 dice_loss 0.06516 +Epoch [2899/4000] Validation [2/4] Loss: 0.39732 focal_loss 0.28767 dice_loss 0.10965 +Epoch [2899/4000] Validation [3/4] Loss: 0.49173 focal_loss 0.39183 dice_loss 0.09990 +Epoch [2899/4000] Validation [4/4] Loss: 0.41594 focal_loss 0.30167 dice_loss 0.11427 +Epoch [2899/4000] Validation metric {'Val/mean dice_metric': 0.9731501340866089, 'Val/mean miou_metric': 0.958264946937561, 'Val/mean f1': 0.9752041101455688, 'Val/mean precision': 0.973054826259613, 'Val/mean recall': 0.9773629903793335, 'Val/mean hd95_metric': 5.012430191040039} +Cheakpoint... +Epoch [2899/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731501340866089, 'Val/mean miou_metric': 0.958264946937561, 'Val/mean f1': 0.9752041101455688, 'Val/mean precision': 0.973054826259613, 'Val/mean recall': 0.9773629903793335, 'Val/mean hd95_metric': 5.012430191040039} +Epoch [2900/4000] Training [1/16] Loss: 0.00239 +Epoch [2900/4000] Training [2/16] Loss: 0.00297 +Epoch [2900/4000] Training [3/16] Loss: 0.00284 +Epoch [2900/4000] Training [4/16] Loss: 0.00401 +Epoch [2900/4000] Training [5/16] Loss: 0.00269 +Epoch [2900/4000] Training [6/16] Loss: 0.00380 +Epoch [2900/4000] Training [7/16] Loss: 0.00360 +Epoch [2900/4000] Training [8/16] Loss: 0.00393 +Epoch [2900/4000] Training [9/16] Loss: 0.00311 +Epoch [2900/4000] Training [10/16] Loss: 0.00337 +Epoch [2900/4000] Training [11/16] Loss: 0.00318 +Epoch [2900/4000] Training [12/16] Loss: 0.00315 +Epoch [2900/4000] Training [13/16] Loss: 0.00280 +Epoch [2900/4000] Training [14/16] Loss: 0.00430 +Epoch [2900/4000] Training [15/16] Loss: 0.00255 +Epoch [2900/4000] Training [16/16] Loss: 0.00317 +Epoch [2900/4000] Training metric {'Train/mean dice_metric': 0.9979701042175293, 'Train/mean miou_metric': 0.9956543445587158, 'Train/mean f1': 0.9929208159446716, 'Train/mean precision': 0.9880834221839905, 'Train/mean recall': 0.9978058934211731, 'Train/mean hd95_metric': 0.818651556968689} +Epoch [2900/4000] Validation [1/4] Loss: 0.45638 focal_loss 0.36820 dice_loss 0.08817 +Epoch [2900/4000] Validation [2/4] Loss: 0.39645 focal_loss 0.28318 dice_loss 0.11327 +Epoch [2900/4000] Validation [3/4] Loss: 0.48739 focal_loss 0.39307 dice_loss 0.09432 +Epoch [2900/4000] Validation [4/4] Loss: 0.44114 focal_loss 0.33373 dice_loss 0.10741 +Epoch [2900/4000] Validation metric {'Val/mean dice_metric': 0.9740341305732727, 'Val/mean miou_metric': 0.9587745666503906, 'Val/mean f1': 0.975547730922699, 'Val/mean precision': 0.9738665223121643, 'Val/mean recall': 0.9772347807884216, 'Val/mean hd95_metric': 5.346484184265137} +Cheakpoint... +Epoch [2900/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740341305732727, 'Val/mean miou_metric': 0.9587745666503906, 'Val/mean f1': 0.975547730922699, 'Val/mean precision': 0.9738665223121643, 'Val/mean recall': 0.9772347807884216, 'Val/mean hd95_metric': 5.346484184265137} +Epoch [2901/4000] Training [1/16] Loss: 0.00383 +Epoch [2901/4000] Training [2/16] Loss: 0.00298 +Epoch [2901/4000] Training [3/16] Loss: 0.00298 +Epoch [2901/4000] Training [4/16] Loss: 0.00397 +Epoch [2901/4000] Training [5/16] Loss: 0.00315 +Epoch [2901/4000] Training [6/16] Loss: 0.00234 +Epoch [2901/4000] Training [7/16] Loss: 0.00263 +Epoch [2901/4000] Training [8/16] Loss: 0.00258 +Epoch [2901/4000] Training [9/16] Loss: 0.00414 +Epoch [2901/4000] Training [10/16] Loss: 0.00502 +Epoch [2901/4000] Training [11/16] Loss: 0.00281 +Epoch [2901/4000] Training [12/16] Loss: 0.00370 +Epoch [2901/4000] Training [13/16] Loss: 0.00241 +Epoch [2901/4000] Training [14/16] Loss: 0.00283 +Epoch [2901/4000] Training [15/16] Loss: 0.00320 +Epoch [2901/4000] Training [16/16] Loss: 0.00350 +Epoch [2901/4000] Training metric {'Train/mean dice_metric': 0.9981622695922852, 'Train/mean miou_metric': 0.9960571527481079, 'Train/mean f1': 0.9933880567550659, 'Train/mean precision': 0.988900363445282, 'Train/mean recall': 0.9979166388511658, 'Train/mean hd95_metric': 0.8179265260696411} +Epoch [2901/4000] Validation [1/4] Loss: 0.35329 focal_loss 0.29129 dice_loss 0.06200 +Epoch [2901/4000] Validation [2/4] Loss: 0.97362 focal_loss 0.77012 dice_loss 0.20350 +Epoch [2901/4000] Validation [3/4] Loss: 0.49754 focal_loss 0.40621 dice_loss 0.09133 +Epoch [2901/4000] Validation [4/4] Loss: 0.30727 focal_loss 0.22106 dice_loss 0.08621 +Epoch [2901/4000] Validation metric {'Val/mean dice_metric': 0.972618579864502, 'Val/mean miou_metric': 0.9586696624755859, 'Val/mean f1': 0.9760069251060486, 'Val/mean precision': 0.9742860198020935, 'Val/mean recall': 0.9777340888977051, 'Val/mean hd95_metric': 5.168530464172363} +Cheakpoint... +Epoch [2901/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972618579864502, 'Val/mean miou_metric': 0.9586696624755859, 'Val/mean f1': 0.9760069251060486, 'Val/mean precision': 0.9742860198020935, 'Val/mean recall': 0.9777340888977051, 'Val/mean hd95_metric': 5.168530464172363} +Epoch [2902/4000] Training [1/16] Loss: 0.00335 +Epoch [2902/4000] Training [2/16] Loss: 0.00426 +Epoch [2902/4000] Training [3/16] Loss: 0.00398 +Epoch [2902/4000] Training [4/16] Loss: 0.00342 +Epoch [2902/4000] Training [5/16] Loss: 0.00298 +Epoch [2902/4000] Training [6/16] Loss: 0.00295 +Epoch [2902/4000] Training [7/16] Loss: 0.00285 +Epoch [2902/4000] Training [8/16] Loss: 0.00355 +Epoch [2902/4000] Training [9/16] Loss: 0.00516 +Epoch [2902/4000] Training [10/16] Loss: 0.00260 +Epoch [2902/4000] Training [11/16] Loss: 0.00372 +Epoch [2902/4000] Training [12/16] Loss: 0.00383 +Epoch [2902/4000] Training [13/16] Loss: 0.00304 +Epoch [2902/4000] Training [14/16] Loss: 0.00498 +Epoch [2902/4000] Training [15/16] Loss: 0.00285 +Epoch [2902/4000] Training [16/16] Loss: 0.00369 +Epoch [2902/4000] Training metric {'Train/mean dice_metric': 0.9978833794593811, 'Train/mean miou_metric': 0.9954779148101807, 'Train/mean f1': 0.9926483631134033, 'Train/mean precision': 0.9876272082328796, 'Train/mean recall': 0.9977208971977234, 'Train/mean hd95_metric': 0.8440481424331665} +Epoch [2902/4000] Validation [1/4] Loss: 0.49376 focal_loss 0.40085 dice_loss 0.09291 +Epoch [2902/4000] Validation [2/4] Loss: 0.89955 focal_loss 0.71418 dice_loss 0.18537 +Epoch [2902/4000] Validation [3/4] Loss: 0.50146 focal_loss 0.41047 dice_loss 0.09099 +Epoch [2902/4000] Validation [4/4] Loss: 0.37324 focal_loss 0.26915 dice_loss 0.10409 +Epoch [2902/4000] Validation metric {'Val/mean dice_metric': 0.9728047251701355, 'Val/mean miou_metric': 0.9583684802055359, 'Val/mean f1': 0.9751958250999451, 'Val/mean precision': 0.9735451340675354, 'Val/mean recall': 0.9768521189689636, 'Val/mean hd95_metric': 5.336532115936279} +Cheakpoint... +Epoch [2902/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728047251701355, 'Val/mean miou_metric': 0.9583684802055359, 'Val/mean f1': 0.9751958250999451, 'Val/mean precision': 0.9735451340675354, 'Val/mean recall': 0.9768521189689636, 'Val/mean hd95_metric': 5.336532115936279} +Epoch [2903/4000] Training [1/16] Loss: 0.00347 +Epoch [2903/4000] Training [2/16] Loss: 0.00466 +Epoch [2903/4000] Training [3/16] Loss: 0.00432 +Epoch [2903/4000] Training [4/16] Loss: 0.00517 +Epoch [2903/4000] Training [5/16] Loss: 0.00284 +Epoch [2903/4000] Training [6/16] Loss: 0.00358 +Epoch [2903/4000] Training [7/16] Loss: 0.00398 +Epoch [2903/4000] Training [8/16] Loss: 0.00320 +Epoch [2903/4000] Training [9/16] Loss: 0.00592 +Epoch [2903/4000] Training [10/16] Loss: 0.00530 +Epoch [2903/4000] Training [11/16] Loss: 0.00396 +Epoch [2903/4000] Training [12/16] Loss: 0.00390 +Epoch [2903/4000] Training [13/16] Loss: 0.00316 +Epoch [2903/4000] Training [14/16] Loss: 0.00346 +Epoch [2903/4000] Training [15/16] Loss: 0.00302 +Epoch [2903/4000] Training [16/16] Loss: 0.00255 +Epoch [2903/4000] Training metric {'Train/mean dice_metric': 0.997728705406189, 'Train/mean miou_metric': 0.9951846599578857, 'Train/mean f1': 0.9928016662597656, 'Train/mean precision': 0.9880223870277405, 'Train/mean recall': 0.9976274371147156, 'Train/mean hd95_metric': 0.8397741913795471} +Epoch [2903/4000] Validation [1/4] Loss: 0.34206 focal_loss 0.28146 dice_loss 0.06060 +Epoch [2903/4000] Validation [2/4] Loss: 0.41273 focal_loss 0.30198 dice_loss 0.11076 +Epoch [2903/4000] Validation [3/4] Loss: 0.47564 focal_loss 0.38647 dice_loss 0.08917 +Epoch [2903/4000] Validation [4/4] Loss: 0.41179 focal_loss 0.29790 dice_loss 0.11389 +Epoch [2903/4000] Validation metric {'Val/mean dice_metric': 0.9737032055854797, 'Val/mean miou_metric': 0.9587446451187134, 'Val/mean f1': 0.9759702682495117, 'Val/mean precision': 0.9743188619613647, 'Val/mean recall': 0.9776274561882019, 'Val/mean hd95_metric': 4.8114118576049805} +Cheakpoint... +Epoch [2903/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737032055854797, 'Val/mean miou_metric': 0.9587446451187134, 'Val/mean f1': 0.9759702682495117, 'Val/mean precision': 0.9743188619613647, 'Val/mean recall': 0.9776274561882019, 'Val/mean hd95_metric': 4.8114118576049805} +Epoch [2904/4000] Training [1/16] Loss: 0.00308 +Epoch [2904/4000] Training [2/16] Loss: 0.00291 +Epoch [2904/4000] Training [3/16] Loss: 0.00348 +Epoch [2904/4000] Training [4/16] Loss: 0.00395 +Epoch [2904/4000] Training [5/16] Loss: 0.00292 +Epoch [2904/4000] Training [6/16] Loss: 0.00250 +Epoch [2904/4000] Training [7/16] Loss: 0.00272 +Epoch [2904/4000] Training [8/16] Loss: 0.00288 +Epoch [2904/4000] Training [9/16] Loss: 0.00290 +Epoch [2904/4000] Training [10/16] Loss: 0.00471 +Epoch [2904/4000] Training [11/16] Loss: 0.00429 +Epoch [2904/4000] Training [12/16] Loss: 0.00305 +Epoch [2904/4000] Training [13/16] Loss: 0.00334 +Epoch [2904/4000] Training [14/16] Loss: 0.00387 +Epoch [2904/4000] Training [15/16] Loss: 0.00278 +Epoch [2904/4000] Training [16/16] Loss: 0.00338 +Epoch [2904/4000] Training metric {'Train/mean dice_metric': 0.9981051683425903, 'Train/mean miou_metric': 0.9959453344345093, 'Train/mean f1': 0.9932399988174438, 'Train/mean precision': 0.9887470602989197, 'Train/mean recall': 0.9977740049362183, 'Train/mean hd95_metric': 0.8087663650512695} +Epoch [2904/4000] Validation [1/4] Loss: 0.41076 focal_loss 0.34562 dice_loss 0.06515 +Epoch [2904/4000] Validation [2/4] Loss: 0.40703 focal_loss 0.29459 dice_loss 0.11244 +Epoch [2904/4000] Validation [3/4] Loss: 0.47181 focal_loss 0.38310 dice_loss 0.08871 +Epoch [2904/4000] Validation [4/4] Loss: 0.32425 focal_loss 0.23097 dice_loss 0.09328 +Epoch [2904/4000] Validation metric {'Val/mean dice_metric': 0.9741886258125305, 'Val/mean miou_metric': 0.9596738815307617, 'Val/mean f1': 0.9759989976882935, 'Val/mean precision': 0.9742331504821777, 'Val/mean recall': 0.9777711629867554, 'Val/mean hd95_metric': 4.916313648223877} +Cheakpoint... +Epoch [2904/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741886258125305, 'Val/mean miou_metric': 0.9596738815307617, 'Val/mean f1': 0.9759989976882935, 'Val/mean precision': 0.9742331504821777, 'Val/mean recall': 0.9777711629867554, 'Val/mean hd95_metric': 4.916313648223877} +Epoch [2905/4000] Training [1/16] Loss: 0.00335 +Epoch [2905/4000] Training [2/16] Loss: 0.00482 +Epoch [2905/4000] Training [3/16] Loss: 0.00202 +Epoch [2905/4000] Training [4/16] Loss: 0.00266 +Epoch [2905/4000] Training [5/16] Loss: 0.00259 +Epoch [2905/4000] Training [6/16] Loss: 0.00328 +Epoch [2905/4000] Training [7/16] Loss: 0.00256 +Epoch [2905/4000] Training [8/16] Loss: 0.00267 +Epoch [2905/4000] Training [9/16] Loss: 0.00396 +Epoch [2905/4000] Training [10/16] Loss: 0.00324 +Epoch [2905/4000] Training [11/16] Loss: 0.00555 +Epoch [2905/4000] Training [12/16] Loss: 0.00439 +Epoch [2905/4000] Training [13/16] Loss: 0.00340 +Epoch [2905/4000] Training [14/16] Loss: 0.00282 +Epoch [2905/4000] Training [15/16] Loss: 0.00278 +Epoch [2905/4000] Training [16/16] Loss: 0.00537 +Epoch [2905/4000] Training metric {'Train/mean dice_metric': 0.9980342388153076, 'Train/mean miou_metric': 0.9958037734031677, 'Train/mean f1': 0.9932196140289307, 'Train/mean precision': 0.988649845123291, 'Train/mean recall': 0.9978318214416504, 'Train/mean hd95_metric': 0.8318214416503906} +Epoch [2905/4000] Validation [1/4] Loss: 0.35076 focal_loss 0.28808 dice_loss 0.06267 +Epoch [2905/4000] Validation [2/4] Loss: 0.82139 focal_loss 0.60767 dice_loss 0.21372 +Epoch [2905/4000] Validation [3/4] Loss: 0.45663 focal_loss 0.36895 dice_loss 0.08768 +Epoch [2905/4000] Validation [4/4] Loss: 0.48482 focal_loss 0.34890 dice_loss 0.13593 +Epoch [2905/4000] Validation metric {'Val/mean dice_metric': 0.969618022441864, 'Val/mean miou_metric': 0.9549867510795593, 'Val/mean f1': 0.9741668701171875, 'Val/mean precision': 0.97307950258255, 'Val/mean recall': 0.9752567410469055, 'Val/mean hd95_metric': 5.373574733734131} +Cheakpoint... +Epoch [2905/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9696], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.969618022441864, 'Val/mean miou_metric': 0.9549867510795593, 'Val/mean f1': 0.9741668701171875, 'Val/mean precision': 0.97307950258255, 'Val/mean recall': 0.9752567410469055, 'Val/mean hd95_metric': 5.373574733734131} +Epoch [2906/4000] Training [1/16] Loss: 0.00401 +Epoch [2906/4000] Training [2/16] Loss: 0.00471 +Epoch [2906/4000] Training [3/16] Loss: 0.00274 +Epoch [2906/4000] Training [4/16] Loss: 0.00344 +Epoch [2906/4000] Training [5/16] Loss: 0.00405 +Epoch [2906/4000] Training [6/16] Loss: 0.00337 +Epoch [2906/4000] Training [7/16] Loss: 0.00479 +Epoch [2906/4000] Training [8/16] Loss: 0.00326 +Epoch [2906/4000] Training [9/16] Loss: 0.00310 +Epoch [2906/4000] Training [10/16] Loss: 0.00688 +Epoch [2906/4000] Training [11/16] Loss: 0.00340 +Epoch [2906/4000] Training [12/16] Loss: 0.00341 +Epoch [2906/4000] Training [13/16] Loss: 0.00286 +Epoch [2906/4000] Training [14/16] Loss: 0.00302 +Epoch [2906/4000] Training [15/16] Loss: 0.00337 +Epoch [2906/4000] Training [16/16] Loss: 0.00396 +Epoch [2906/4000] Training metric {'Train/mean dice_metric': 0.9978401064872742, 'Train/mean miou_metric': 0.9954206943511963, 'Train/mean f1': 0.9931097626686096, 'Train/mean precision': 0.9885067939758301, 'Train/mean recall': 0.9977558255195618, 'Train/mean hd95_metric': 0.8227815628051758} +Epoch [2906/4000] Validation [1/4] Loss: 0.32284 focal_loss 0.26303 dice_loss 0.05981 +Epoch [2906/4000] Validation [2/4] Loss: 0.71856 focal_loss 0.53369 dice_loss 0.18487 +Epoch [2906/4000] Validation [3/4] Loss: 0.50730 focal_loss 0.40798 dice_loss 0.09932 +Epoch [2906/4000] Validation [4/4] Loss: 0.35108 focal_loss 0.23391 dice_loss 0.11717 +Epoch [2906/4000] Validation metric {'Val/mean dice_metric': 0.9735145568847656, 'Val/mean miou_metric': 0.9588254690170288, 'Val/mean f1': 0.9751121401786804, 'Val/mean precision': 0.9713588356971741, 'Val/mean recall': 0.9788944721221924, 'Val/mean hd95_metric': 5.542624473571777} +Cheakpoint... +Epoch [2906/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735145568847656, 'Val/mean miou_metric': 0.9588254690170288, 'Val/mean f1': 0.9751121401786804, 'Val/mean precision': 0.9713588356971741, 'Val/mean recall': 0.9788944721221924, 'Val/mean hd95_metric': 5.542624473571777} +Epoch [2907/4000] Training [1/16] Loss: 0.00333 +Epoch [2907/4000] Training [2/16] Loss: 0.00306 +Epoch [2907/4000] Training [3/16] Loss: 0.00310 +Epoch [2907/4000] Training [4/16] Loss: 0.00244 +Epoch [2907/4000] Training [5/16] Loss: 0.00415 +Epoch [2907/4000] Training [6/16] Loss: 0.00401 +Epoch [2907/4000] Training [7/16] Loss: 0.00253 +Epoch [2907/4000] Training [8/16] Loss: 0.00326 +Epoch [2907/4000] Training [9/16] Loss: 0.00281 +Epoch [2907/4000] Training [10/16] Loss: 0.00336 +Epoch [2907/4000] Training [11/16] Loss: 0.00344 +Epoch [2907/4000] Training [12/16] Loss: 0.00532 +Epoch [2907/4000] Training [13/16] Loss: 0.00374 +Epoch [2907/4000] Training [14/16] Loss: 0.00336 +Epoch [2907/4000] Training [15/16] Loss: 0.00310 +Epoch [2907/4000] Training [16/16] Loss: 0.00295 +Epoch [2907/4000] Training metric {'Train/mean dice_metric': 0.9979800581932068, 'Train/mean miou_metric': 0.9956932067871094, 'Train/mean f1': 0.9931919574737549, 'Train/mean precision': 0.9886395931243896, 'Train/mean recall': 0.9977864623069763, 'Train/mean hd95_metric': 0.8206608295440674} +Epoch [2907/4000] Validation [1/4] Loss: 0.31849 focal_loss 0.26131 dice_loss 0.05719 +Epoch [2907/4000] Validation [2/4] Loss: 0.35486 focal_loss 0.26001 dice_loss 0.09485 +Epoch [2907/4000] Validation [3/4] Loss: 0.49293 focal_loss 0.40282 dice_loss 0.09011 +Epoch [2907/4000] Validation [4/4] Loss: 0.44592 focal_loss 0.32021 dice_loss 0.12572 +Epoch [2907/4000] Validation metric {'Val/mean dice_metric': 0.974011242389679, 'Val/mean miou_metric': 0.959129810333252, 'Val/mean f1': 0.9759941101074219, 'Val/mean precision': 0.9736073017120361, 'Val/mean recall': 0.9783926010131836, 'Val/mean hd95_metric': 5.101605415344238} +Cheakpoint... +Epoch [2907/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974011242389679, 'Val/mean miou_metric': 0.959129810333252, 'Val/mean f1': 0.9759941101074219, 'Val/mean precision': 0.9736073017120361, 'Val/mean recall': 0.9783926010131836, 'Val/mean hd95_metric': 5.101605415344238} +Epoch [2908/4000] Training [1/16] Loss: 0.00265 +Epoch [2908/4000] Training [2/16] Loss: 0.00415 +Epoch [2908/4000] Training [3/16] Loss: 0.00270 +Epoch [2908/4000] Training [4/16] Loss: 0.00264 +Epoch [2908/4000] Training [5/16] Loss: 0.00304 +Epoch [2908/4000] Training [6/16] Loss: 0.00334 +Epoch [2908/4000] Training [7/16] Loss: 0.00389 +Epoch [2908/4000] Training [8/16] Loss: 0.00323 +Epoch [2908/4000] Training [9/16] Loss: 0.00383 +Epoch [2908/4000] Training [10/16] Loss: 0.00344 +Epoch [2908/4000] Training [11/16] Loss: 0.00263 +Epoch [2908/4000] Training [12/16] Loss: 0.00428 +Epoch [2908/4000] Training [13/16] Loss: 0.00428 +Epoch [2908/4000] Training [14/16] Loss: 0.00481 +Epoch [2908/4000] Training [15/16] Loss: 0.00257 +Epoch [2908/4000] Training [16/16] Loss: 0.00343 +Epoch [2908/4000] Training metric {'Train/mean dice_metric': 0.9978923797607422, 'Train/mean miou_metric': 0.9955077171325684, 'Train/mean f1': 0.9929574728012085, 'Train/mean precision': 0.9882335066795349, 'Train/mean recall': 0.9977267980575562, 'Train/mean hd95_metric': 0.8415676355361938} +Epoch [2908/4000] Validation [1/4] Loss: 0.37372 focal_loss 0.30760 dice_loss 0.06611 +Epoch [2908/4000] Validation [2/4] Loss: 0.84082 focal_loss 0.64981 dice_loss 0.19101 +Epoch [2908/4000] Validation [3/4] Loss: 0.40971 focal_loss 0.31668 dice_loss 0.09302 +Epoch [2908/4000] Validation [4/4] Loss: 0.40762 focal_loss 0.28892 dice_loss 0.11870 +Epoch [2908/4000] Validation metric {'Val/mean dice_metric': 0.9707218408584595, 'Val/mean miou_metric': 0.9564355611801147, 'Val/mean f1': 0.9749677181243896, 'Val/mean precision': 0.9736531972885132, 'Val/mean recall': 0.9762858152389526, 'Val/mean hd95_metric': 5.206727027893066} +Cheakpoint... +Epoch [2908/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707218408584595, 'Val/mean miou_metric': 0.9564355611801147, 'Val/mean f1': 0.9749677181243896, 'Val/mean precision': 0.9736531972885132, 'Val/mean recall': 0.9762858152389526, 'Val/mean hd95_metric': 5.206727027893066} +Epoch [2909/4000] Training [1/16] Loss: 0.00273 +Epoch [2909/4000] Training [2/16] Loss: 0.00394 +Epoch [2909/4000] Training [3/16] Loss: 0.00423 +Epoch [2909/4000] Training [4/16] Loss: 0.00392 +Epoch [2909/4000] Training [5/16] Loss: 0.00273 +Epoch [2909/4000] Training [6/16] Loss: 0.00303 +Epoch [2909/4000] Training [7/16] Loss: 0.00303 +Epoch [2909/4000] Training [8/16] Loss: 0.00366 +Epoch [2909/4000] Training [9/16] Loss: 0.00283 +Epoch [2909/4000] Training [10/16] Loss: 0.00321 +Epoch [2909/4000] Training [11/16] Loss: 0.00336 +Epoch [2909/4000] Training [12/16] Loss: 0.00313 +Epoch [2909/4000] Training [13/16] Loss: 0.00429 +Epoch [2909/4000] Training [14/16] Loss: 0.00248 +Epoch [2909/4000] Training [15/16] Loss: 0.00314 +Epoch [2909/4000] Training [16/16] Loss: 0.00462 +Epoch [2909/4000] Training metric {'Train/mean dice_metric': 0.9979839324951172, 'Train/mean miou_metric': 0.9956945180892944, 'Train/mean f1': 0.9930854439735413, 'Train/mean precision': 0.9884087443351746, 'Train/mean recall': 0.9978066086769104, 'Train/mean hd95_metric': 0.831012487411499} +Epoch [2909/4000] Validation [1/4] Loss: 0.35903 focal_loss 0.29651 dice_loss 0.06252 +Epoch [2909/4000] Validation [2/4] Loss: 0.90592 focal_loss 0.71534 dice_loss 0.19058 +Epoch [2909/4000] Validation [3/4] Loss: 0.46409 focal_loss 0.37531 dice_loss 0.08878 +Epoch [2909/4000] Validation [4/4] Loss: 0.41790 focal_loss 0.29867 dice_loss 0.11924 +Epoch [2909/4000] Validation metric {'Val/mean dice_metric': 0.9721218943595886, 'Val/mean miou_metric': 0.9578058123588562, 'Val/mean f1': 0.9754130244255066, 'Val/mean precision': 0.9744851589202881, 'Val/mean recall': 0.9763427376747131, 'Val/mean hd95_metric': 5.527388572692871} +Cheakpoint... +Epoch [2909/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721218943595886, 'Val/mean miou_metric': 0.9578058123588562, 'Val/mean f1': 0.9754130244255066, 'Val/mean precision': 0.9744851589202881, 'Val/mean recall': 0.9763427376747131, 'Val/mean hd95_metric': 5.527388572692871} +Epoch [2910/4000] Training [1/16] Loss: 0.00497 +Epoch [2910/4000] Training [2/16] Loss: 0.00317 +Epoch [2910/4000] Training [3/16] Loss: 0.00305 +Epoch [2910/4000] Training [4/16] Loss: 0.00360 +Epoch [2910/4000] Training [5/16] Loss: 0.00310 +Epoch [2910/4000] Training [6/16] Loss: 0.00600 +Epoch [2910/4000] Training [7/16] Loss: 0.00362 +Epoch [2910/4000] Training [8/16] Loss: 0.00480 +Epoch [2910/4000] Training [9/16] Loss: 0.00365 +Epoch [2910/4000] Training [10/16] Loss: 0.00357 +Epoch [2910/4000] Training [11/16] Loss: 0.00248 +Epoch [2910/4000] Training [12/16] Loss: 0.00258 +Epoch [2910/4000] Training [13/16] Loss: 0.00460 +Epoch [2910/4000] Training [14/16] Loss: 0.00323 +Epoch [2910/4000] Training [15/16] Loss: 0.00320 +Epoch [2910/4000] Training [16/16] Loss: 0.00395 +Epoch [2910/4000] Training metric {'Train/mean dice_metric': 0.997877299785614, 'Train/mean miou_metric': 0.9954710006713867, 'Train/mean f1': 0.9928156733512878, 'Train/mean precision': 0.9880625009536743, 'Train/mean recall': 0.9976147413253784, 'Train/mean hd95_metric': 0.8494102954864502} +Epoch [2910/4000] Validation [1/4] Loss: 0.40612 focal_loss 0.34006 dice_loss 0.06606 +Epoch [2910/4000] Validation [2/4] Loss: 0.83423 focal_loss 0.64310 dice_loss 0.19113 +Epoch [2910/4000] Validation [3/4] Loss: 0.45310 focal_loss 0.36497 dice_loss 0.08813 +Epoch [2910/4000] Validation [4/4] Loss: 0.50918 focal_loss 0.39203 dice_loss 0.11716 +Epoch [2910/4000] Validation metric {'Val/mean dice_metric': 0.9722382426261902, 'Val/mean miou_metric': 0.9578977823257446, 'Val/mean f1': 0.9751304388046265, 'Val/mean precision': 0.9745668768882751, 'Val/mean recall': 0.9756947159767151, 'Val/mean hd95_metric': 5.082029819488525} +Cheakpoint... +Epoch [2910/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722382426261902, 'Val/mean miou_metric': 0.9578977823257446, 'Val/mean f1': 0.9751304388046265, 'Val/mean precision': 0.9745668768882751, 'Val/mean recall': 0.9756947159767151, 'Val/mean hd95_metric': 5.082029819488525} +Epoch [2911/4000] Training [1/16] Loss: 0.00368 +Epoch [2911/4000] Training [2/16] Loss: 0.00245 +Epoch [2911/4000] Training [3/16] Loss: 0.00287 +Epoch [2911/4000] Training [4/16] Loss: 0.00319 +Epoch [2911/4000] Training [5/16] Loss: 0.00424 +Epoch [2911/4000] Training [6/16] Loss: 0.00326 +Epoch [2911/4000] Training [7/16] Loss: 0.00215 +Epoch [2911/4000] Training [8/16] Loss: 0.00454 +Epoch [2911/4000] Training [9/16] Loss: 0.00325 +Epoch [2911/4000] Training [10/16] Loss: 0.00332 +Epoch [2911/4000] Training [11/16] Loss: 0.00271 +Epoch [2911/4000] Training [12/16] Loss: 0.00313 +Epoch [2911/4000] Training [13/16] Loss: 0.00303 +Epoch [2911/4000] Training [14/16] Loss: 0.00344 +Epoch [2911/4000] Training [15/16] Loss: 0.00398 +Epoch [2911/4000] Training [16/16] Loss: 0.00302 +Epoch [2911/4000] Training metric {'Train/mean dice_metric': 0.9980098009109497, 'Train/mean miou_metric': 0.9957292079925537, 'Train/mean f1': 0.9926548004150391, 'Train/mean precision': 0.9876099228858948, 'Train/mean recall': 0.9977515339851379, 'Train/mean hd95_metric': 0.8079379200935364} +Epoch [2911/4000] Validation [1/4] Loss: 0.32250 focal_loss 0.26271 dice_loss 0.05979 +Epoch [2911/4000] Validation [2/4] Loss: 0.39083 focal_loss 0.27939 dice_loss 0.11144 +Epoch [2911/4000] Validation [3/4] Loss: 0.47699 focal_loss 0.38675 dice_loss 0.09024 +Epoch [2911/4000] Validation [4/4] Loss: 0.42944 focal_loss 0.31596 dice_loss 0.11348 +Epoch [2911/4000] Validation metric {'Val/mean dice_metric': 0.9727388620376587, 'Val/mean miou_metric': 0.9582692980766296, 'Val/mean f1': 0.9756386876106262, 'Val/mean precision': 0.9737442135810852, 'Val/mean recall': 0.9775406122207642, 'Val/mean hd95_metric': 4.971545219421387} +Cheakpoint... +Epoch [2911/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727388620376587, 'Val/mean miou_metric': 0.9582692980766296, 'Val/mean f1': 0.9756386876106262, 'Val/mean precision': 0.9737442135810852, 'Val/mean recall': 0.9775406122207642, 'Val/mean hd95_metric': 4.971545219421387} +Epoch [2912/4000] Training [1/16] Loss: 0.00278 +Epoch [2912/4000] Training [2/16] Loss: 0.00258 +Epoch [2912/4000] Training [3/16] Loss: 0.00308 +Epoch [2912/4000] Training [4/16] Loss: 0.00448 +Epoch [2912/4000] Training [5/16] Loss: 0.00232 +Epoch [2912/4000] Training [6/16] Loss: 0.00211 +Epoch [2912/4000] Training [7/16] Loss: 0.00278 +Epoch [2912/4000] Training [8/16] Loss: 0.00396 +Epoch [2912/4000] Training [9/16] Loss: 0.00291 +Epoch [2912/4000] Training [10/16] Loss: 0.00448 +Epoch [2912/4000] Training [11/16] Loss: 0.00254 +Epoch [2912/4000] Training [12/16] Loss: 0.00319 +Epoch [2912/4000] Training [13/16] Loss: 0.00337 +Epoch [2912/4000] Training [14/16] Loss: 0.00312 +Epoch [2912/4000] Training [15/16] Loss: 0.00318 +Epoch [2912/4000] Training [16/16] Loss: 0.00356 +Epoch [2912/4000] Training metric {'Train/mean dice_metric': 0.9982542395591736, 'Train/mean miou_metric': 0.9962289333343506, 'Train/mean f1': 0.9933432340621948, 'Train/mean precision': 0.9887943267822266, 'Train/mean recall': 0.9979342222213745, 'Train/mean hd95_metric': 0.8061522841453552} +Epoch [2912/4000] Validation [1/4] Loss: 0.42518 focal_loss 0.35787 dice_loss 0.06731 +Epoch [2912/4000] Validation [2/4] Loss: 0.39407 focal_loss 0.28498 dice_loss 0.10909 +Epoch [2912/4000] Validation [3/4] Loss: 0.50357 focal_loss 0.40492 dice_loss 0.09865 +Epoch [2912/4000] Validation [4/4] Loss: 0.40505 focal_loss 0.28813 dice_loss 0.11693 +Epoch [2912/4000] Validation metric {'Val/mean dice_metric': 0.9720596075057983, 'Val/mean miou_metric': 0.9579151272773743, 'Val/mean f1': 0.9754812717437744, 'Val/mean precision': 0.9736058712005615, 'Val/mean recall': 0.9773638248443604, 'Val/mean hd95_metric': 5.629207134246826} +Cheakpoint... +Epoch [2912/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720596075057983, 'Val/mean miou_metric': 0.9579151272773743, 'Val/mean f1': 0.9754812717437744, 'Val/mean precision': 0.9736058712005615, 'Val/mean recall': 0.9773638248443604, 'Val/mean hd95_metric': 5.629207134246826} +Epoch [2913/4000] Training [1/16] Loss: 0.00247 +Epoch [2913/4000] Training [2/16] Loss: 0.00411 +Epoch [2913/4000] Training [3/16] Loss: 0.00358 +Epoch [2913/4000] Training [4/16] Loss: 0.00317 +Epoch [2913/4000] Training [5/16] Loss: 0.00352 +Epoch [2913/4000] Training [6/16] Loss: 0.00372 +Epoch [2913/4000] Training [7/16] Loss: 0.00320 +Epoch [2913/4000] Training [8/16] Loss: 0.00216 +Epoch [2913/4000] Training [9/16] Loss: 0.00311 +Epoch [2913/4000] Training [10/16] Loss: 0.00219 +Epoch [2913/4000] Training [11/16] Loss: 0.00301 +Epoch [2913/4000] Training [12/16] Loss: 0.00495 +Epoch [2913/4000] Training [13/16] Loss: 0.00347 +Epoch [2913/4000] Training [14/16] Loss: 0.00265 +Epoch [2913/4000] Training [15/16] Loss: 0.00318 +Epoch [2913/4000] Training [16/16] Loss: 0.00383 +Epoch [2913/4000] Training metric {'Train/mean dice_metric': 0.9980349540710449, 'Train/mean miou_metric': 0.9957995414733887, 'Train/mean f1': 0.993157684803009, 'Train/mean precision': 0.9885076284408569, 'Train/mean recall': 0.9978516101837158, 'Train/mean hd95_metric': 0.8184846639633179} +Epoch [2913/4000] Validation [1/4] Loss: 0.32735 focal_loss 0.26933 dice_loss 0.05801 +Epoch [2913/4000] Validation [2/4] Loss: 1.13360 focal_loss 0.86870 dice_loss 0.26490 +Epoch [2913/4000] Validation [3/4] Loss: 0.48263 focal_loss 0.39037 dice_loss 0.09226 +Epoch [2913/4000] Validation [4/4] Loss: 0.41105 focal_loss 0.28303 dice_loss 0.12803 +Epoch [2913/4000] Validation metric {'Val/mean dice_metric': 0.9710825085639954, 'Val/mean miou_metric': 0.9570214152336121, 'Val/mean f1': 0.9751795530319214, 'Val/mean precision': 0.9740340709686279, 'Val/mean recall': 0.9763277769088745, 'Val/mean hd95_metric': 4.89520263671875} +Cheakpoint... +Epoch [2913/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710825085639954, 'Val/mean miou_metric': 0.9570214152336121, 'Val/mean f1': 0.9751795530319214, 'Val/mean precision': 0.9740340709686279, 'Val/mean recall': 0.9763277769088745, 'Val/mean hd95_metric': 4.89520263671875} +Epoch [2914/4000] Training [1/16] Loss: 0.00287 +Epoch [2914/4000] Training [2/16] Loss: 0.00269 +Epoch [2914/4000] Training [3/16] Loss: 0.00528 +Epoch [2914/4000] Training [4/16] Loss: 0.00330 +Epoch [2914/4000] Training [5/16] Loss: 0.00432 +Epoch [2914/4000] Training [6/16] Loss: 0.00325 +Epoch [2914/4000] Training [7/16] Loss: 0.00269 +Epoch [2914/4000] Training [8/16] Loss: 0.00475 +Epoch [2914/4000] Training [9/16] Loss: 0.00264 +Epoch [2914/4000] Training [10/16] Loss: 0.00486 +Epoch [2914/4000] Training [11/16] Loss: 0.00306 +Epoch [2914/4000] Training [12/16] Loss: 0.00347 +Epoch [2914/4000] Training [13/16] Loss: 0.00269 +Epoch [2914/4000] Training [14/16] Loss: 0.00379 +Epoch [2914/4000] Training [15/16] Loss: 0.00368 +Epoch [2914/4000] Training [16/16] Loss: 0.00403 +Epoch [2914/4000] Training metric {'Train/mean dice_metric': 0.9979326725006104, 'Train/mean miou_metric': 0.9955968856811523, 'Train/mean f1': 0.9931012392044067, 'Train/mean precision': 0.9885249137878418, 'Train/mean recall': 0.9977201223373413, 'Train/mean hd95_metric': 0.8327702283859253} +Epoch [2914/4000] Validation [1/4] Loss: 0.33297 focal_loss 0.27506 dice_loss 0.05791 +Epoch [2914/4000] Validation [2/4] Loss: 0.90667 focal_loss 0.71185 dice_loss 0.19482 +Epoch [2914/4000] Validation [3/4] Loss: 0.47208 focal_loss 0.38393 dice_loss 0.08816 +Epoch [2914/4000] Validation [4/4] Loss: 0.36081 focal_loss 0.24397 dice_loss 0.11684 +Epoch [2914/4000] Validation metric {'Val/mean dice_metric': 0.9716796875, 'Val/mean miou_metric': 0.9576553106307983, 'Val/mean f1': 0.9757033586502075, 'Val/mean precision': 0.9743992686271667, 'Val/mean recall': 0.97701096534729, 'Val/mean hd95_metric': 5.277953147888184} +Cheakpoint... +Epoch [2914/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716796875, 'Val/mean miou_metric': 0.9576553106307983, 'Val/mean f1': 0.9757033586502075, 'Val/mean precision': 0.9743992686271667, 'Val/mean recall': 0.97701096534729, 'Val/mean hd95_metric': 5.277953147888184} +Epoch [2915/4000] Training [1/16] Loss: 0.00290 +Epoch [2915/4000] Training [2/16] Loss: 0.00321 +Epoch [2915/4000] Training [3/16] Loss: 0.00273 +Epoch [2915/4000] Training [4/16] Loss: 0.00388 +Epoch [2915/4000] Training [5/16] Loss: 0.00336 +Epoch [2915/4000] Training [6/16] Loss: 0.00305 +Epoch [2915/4000] Training [7/16] Loss: 0.00341 +Epoch [2915/4000] Training [8/16] Loss: 0.00299 +Epoch [2915/4000] Training [9/16] Loss: 0.00409 +Epoch [2915/4000] Training [10/16] Loss: 0.00376 +Epoch [2915/4000] Training [11/16] Loss: 0.00376 +Epoch [2915/4000] Training [12/16] Loss: 0.00418 +Epoch [2915/4000] Training [13/16] Loss: 0.00420 +Epoch [2915/4000] Training [14/16] Loss: 0.00333 +Epoch [2915/4000] Training [15/16] Loss: 0.00396 +Epoch [2915/4000] Training [16/16] Loss: 0.00368 +Epoch [2915/4000] Training metric {'Train/mean dice_metric': 0.9979977607727051, 'Train/mean miou_metric': 0.9957294464111328, 'Train/mean f1': 0.9931442141532898, 'Train/mean precision': 0.9885743260383606, 'Train/mean recall': 0.9977566003799438, 'Train/mean hd95_metric': 0.8404574394226074} +Epoch [2915/4000] Validation [1/4] Loss: 0.42247 focal_loss 0.35694 dice_loss 0.06553 +Epoch [2915/4000] Validation [2/4] Loss: 1.02183 focal_loss 0.82489 dice_loss 0.19694 +Epoch [2915/4000] Validation [3/4] Loss: 0.49431 focal_loss 0.39624 dice_loss 0.09807 +Epoch [2915/4000] Validation [4/4] Loss: 0.34313 focal_loss 0.24206 dice_loss 0.10108 +Epoch [2915/4000] Validation metric {'Val/mean dice_metric': 0.9722250699996948, 'Val/mean miou_metric': 0.9577956199645996, 'Val/mean f1': 0.975293755531311, 'Val/mean precision': 0.9743538498878479, 'Val/mean recall': 0.9762356877326965, 'Val/mean hd95_metric': 5.0049285888671875} +Cheakpoint... +Epoch [2915/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722250699996948, 'Val/mean miou_metric': 0.9577956199645996, 'Val/mean f1': 0.975293755531311, 'Val/mean precision': 0.9743538498878479, 'Val/mean recall': 0.9762356877326965, 'Val/mean hd95_metric': 5.0049285888671875} +Epoch [2916/4000] Training [1/16] Loss: 0.00280 +Epoch [2916/4000] Training [2/16] Loss: 0.00334 +Epoch [2916/4000] Training [3/16] Loss: 0.00526 +Epoch [2916/4000] Training [4/16] Loss: 0.00326 +Epoch [2916/4000] Training [5/16] Loss: 0.00314 +Epoch [2916/4000] Training [6/16] Loss: 0.00348 +Epoch [2916/4000] Training [7/16] Loss: 0.00296 +Epoch [2916/4000] Training [8/16] Loss: 0.00315 +Epoch [2916/4000] Training [9/16] Loss: 0.00324 +Epoch [2916/4000] Training [10/16] Loss: 0.00295 +Epoch [2916/4000] Training [11/16] Loss: 0.00365 +Epoch [2916/4000] Training [12/16] Loss: 0.00374 +Epoch [2916/4000] Training [13/16] Loss: 0.00333 +Epoch [2916/4000] Training [14/16] Loss: 0.00485 +Epoch [2916/4000] Training [15/16] Loss: 0.00374 +Epoch [2916/4000] Training [16/16] Loss: 0.00278 +Epoch [2916/4000] Training metric {'Train/mean dice_metric': 0.9978538155555725, 'Train/mean miou_metric': 0.995436429977417, 'Train/mean f1': 0.9930140376091003, 'Train/mean precision': 0.9883639812469482, 'Train/mean recall': 0.9977080225944519, 'Train/mean hd95_metric': 0.8251808285713196} +Epoch [2916/4000] Validation [1/4] Loss: 0.31035 focal_loss 0.25023 dice_loss 0.06012 +Epoch [2916/4000] Validation [2/4] Loss: 0.46456 focal_loss 0.34871 dice_loss 0.11585 +Epoch [2916/4000] Validation [3/4] Loss: 0.47606 focal_loss 0.38583 dice_loss 0.09023 +Epoch [2916/4000] Validation [4/4] Loss: 0.51263 focal_loss 0.37230 dice_loss 0.14033 +Epoch [2916/4000] Validation metric {'Val/mean dice_metric': 0.9726430773735046, 'Val/mean miou_metric': 0.9576305150985718, 'Val/mean f1': 0.9750775694847107, 'Val/mean precision': 0.9739445447921753, 'Val/mean recall': 0.9762132167816162, 'Val/mean hd95_metric': 5.207285404205322} +Cheakpoint... +Epoch [2916/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726430773735046, 'Val/mean miou_metric': 0.9576305150985718, 'Val/mean f1': 0.9750775694847107, 'Val/mean precision': 0.9739445447921753, 'Val/mean recall': 0.9762132167816162, 'Val/mean hd95_metric': 5.207285404205322} +Epoch [2917/4000] Training [1/16] Loss: 0.00372 +Epoch [2917/4000] Training [2/16] Loss: 0.00333 +Epoch [2917/4000] Training [3/16] Loss: 0.00365 +Epoch [2917/4000] Training [4/16] Loss: 0.00325 +Epoch [2917/4000] Training [5/16] Loss: 0.00315 +Epoch [2917/4000] Training [6/16] Loss: 0.00321 +Epoch [2917/4000] Training [7/16] Loss: 0.00333 +Epoch [2917/4000] Training [8/16] Loss: 0.00356 +Epoch [2917/4000] Training [9/16] Loss: 0.00407 +Epoch [2917/4000] Training [10/16] Loss: 0.00303 +Epoch [2917/4000] Training [11/16] Loss: 0.00408 +Epoch [2917/4000] Training [12/16] Loss: 0.00340 +Epoch [2917/4000] Training [13/16] Loss: 0.00259 +Epoch [2917/4000] Training [14/16] Loss: 0.00406 +Epoch [2917/4000] Training [15/16] Loss: 0.00254 +Epoch [2917/4000] Training [16/16] Loss: 0.00424 +Epoch [2917/4000] Training metric {'Train/mean dice_metric': 0.9980540871620178, 'Train/mean miou_metric': 0.995815098285675, 'Train/mean f1': 0.9927548170089722, 'Train/mean precision': 0.9877781271934509, 'Train/mean recall': 0.9977818727493286, 'Train/mean hd95_metric': 0.8278313279151917} +Epoch [2917/4000] Validation [1/4] Loss: 0.36147 focal_loss 0.29857 dice_loss 0.06289 +Epoch [2917/4000] Validation [2/4] Loss: 0.45429 focal_loss 0.33802 dice_loss 0.11627 +Epoch [2917/4000] Validation [3/4] Loss: 0.45211 focal_loss 0.35553 dice_loss 0.09657 +Epoch [2917/4000] Validation [4/4] Loss: 0.46560 focal_loss 0.34380 dice_loss 0.12180 +Epoch [2917/4000] Validation metric {'Val/mean dice_metric': 0.9742510914802551, 'Val/mean miou_metric': 0.9592145681381226, 'Val/mean f1': 0.9751878380775452, 'Val/mean precision': 0.973072350025177, 'Val/mean recall': 0.9773126244544983, 'Val/mean hd95_metric': 5.0159502029418945} +Cheakpoint... +Epoch [2917/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742510914802551, 'Val/mean miou_metric': 0.9592145681381226, 'Val/mean f1': 0.9751878380775452, 'Val/mean precision': 0.973072350025177, 'Val/mean recall': 0.9773126244544983, 'Val/mean hd95_metric': 5.0159502029418945} +Epoch [2918/4000] Training [1/16] Loss: 0.00494 +Epoch [2918/4000] Training [2/16] Loss: 0.00249 +Epoch [2918/4000] Training [3/16] Loss: 0.00350 +Epoch [2918/4000] Training [4/16] Loss: 0.00272 +Epoch [2918/4000] Training [5/16] Loss: 0.00251 +Epoch [2918/4000] Training [6/16] Loss: 0.00278 +Epoch [2918/4000] Training [7/16] Loss: 0.00340 +Epoch [2918/4000] Training [8/16] Loss: 0.00437 +Epoch [2918/4000] Training [9/16] Loss: 0.00400 +Epoch [2918/4000] Training [10/16] Loss: 0.00356 +Epoch [2918/4000] Training [11/16] Loss: 0.00307 +Epoch [2918/4000] Training [12/16] Loss: 0.00317 +Epoch [2918/4000] Training [13/16] Loss: 0.00306 +Epoch [2918/4000] Training [14/16] Loss: 0.00340 +Epoch [2918/4000] Training [15/16] Loss: 0.00346 +Epoch [2918/4000] Training [16/16] Loss: 0.00339 +Epoch [2918/4000] Training metric {'Train/mean dice_metric': 0.998027503490448, 'Train/mean miou_metric': 0.9957702159881592, 'Train/mean f1': 0.9930692315101624, 'Train/mean precision': 0.9883983135223389, 'Train/mean recall': 0.997784435749054, 'Train/mean hd95_metric': 0.7856721878051758} +Epoch [2918/4000] Validation [1/4] Loss: 0.34346 focal_loss 0.28163 dice_loss 0.06183 +Epoch [2918/4000] Validation [2/4] Loss: 0.42697 focal_loss 0.31564 dice_loss 0.11133 +Epoch [2918/4000] Validation [3/4] Loss: 0.45583 focal_loss 0.36088 dice_loss 0.09496 +Epoch [2918/4000] Validation [4/4] Loss: 0.45582 focal_loss 0.33548 dice_loss 0.12033 +Epoch [2918/4000] Validation metric {'Val/mean dice_metric': 0.9744846224784851, 'Val/mean miou_metric': 0.9597259759902954, 'Val/mean f1': 0.9753439426422119, 'Val/mean precision': 0.9721916317939758, 'Val/mean recall': 0.9785168170928955, 'Val/mean hd95_metric': 5.5446343421936035} +Cheakpoint... +Epoch [2918/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744846224784851, 'Val/mean miou_metric': 0.9597259759902954, 'Val/mean f1': 0.9753439426422119, 'Val/mean precision': 0.9721916317939758, 'Val/mean recall': 0.9785168170928955, 'Val/mean hd95_metric': 5.5446343421936035} +Epoch [2919/4000] Training [1/16] Loss: 0.00304 +Epoch [2919/4000] Training [2/16] Loss: 0.00278 +Epoch [2919/4000] Training [3/16] Loss: 0.00369 +Epoch [2919/4000] Training [4/16] Loss: 0.00487 +Epoch [2919/4000] Training [5/16] Loss: 0.00283 +Epoch [2919/4000] Training [6/16] Loss: 0.00288 +Epoch [2919/4000] Training [7/16] Loss: 0.00257 +Epoch [2919/4000] Training [8/16] Loss: 0.00326 +Epoch [2919/4000] Training [9/16] Loss: 0.00381 +Epoch [2919/4000] Training [10/16] Loss: 0.00212 +Epoch [2919/4000] Training [11/16] Loss: 0.00375 +Epoch [2919/4000] Training [12/16] Loss: 0.00288 +Epoch [2919/4000] Training [13/16] Loss: 0.00414 +Epoch [2919/4000] Training [14/16] Loss: 0.00240 +Epoch [2919/4000] Training [15/16] Loss: 0.00421 +Epoch [2919/4000] Training [16/16] Loss: 0.00435 +Epoch [2919/4000] Training metric {'Train/mean dice_metric': 0.9980248808860779, 'Train/mean miou_metric': 0.9957877397537231, 'Train/mean f1': 0.9932292103767395, 'Train/mean precision': 0.9886834621429443, 'Train/mean recall': 0.9978169798851013, 'Train/mean hd95_metric': 0.8043633103370667} +Epoch [2919/4000] Validation [1/4] Loss: 0.31227 focal_loss 0.25277 dice_loss 0.05950 +Epoch [2919/4000] Validation [2/4] Loss: 0.44500 focal_loss 0.33187 dice_loss 0.11313 +Epoch [2919/4000] Validation [3/4] Loss: 0.47201 focal_loss 0.38061 dice_loss 0.09140 +Epoch [2919/4000] Validation [4/4] Loss: 0.33693 focal_loss 0.24431 dice_loss 0.09263 +Epoch [2919/4000] Validation metric {'Val/mean dice_metric': 0.9742597341537476, 'Val/mean miou_metric': 0.9598473310470581, 'Val/mean f1': 0.9762803912162781, 'Val/mean precision': 0.9739217758178711, 'Val/mean recall': 0.9786503314971924, 'Val/mean hd95_metric': 4.851941108703613} +Cheakpoint... +Epoch [2919/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742597341537476, 'Val/mean miou_metric': 0.9598473310470581, 'Val/mean f1': 0.9762803912162781, 'Val/mean precision': 0.9739217758178711, 'Val/mean recall': 0.9786503314971924, 'Val/mean hd95_metric': 4.851941108703613} +Epoch [2920/4000] Training [1/16] Loss: 0.00303 +Epoch [2920/4000] Training [2/16] Loss: 0.00437 +Epoch [2920/4000] Training [3/16] Loss: 0.00344 +Epoch [2920/4000] Training [4/16] Loss: 0.00360 +Epoch [2920/4000] Training [5/16] Loss: 0.00257 +Epoch [2920/4000] Training [6/16] Loss: 0.00290 +Epoch [2920/4000] Training [7/16] Loss: 0.00281 +Epoch [2920/4000] Training [8/16] Loss: 0.00325 +Epoch [2920/4000] Training [9/16] Loss: 0.00569 +Epoch [2920/4000] Training [10/16] Loss: 0.00522 +Epoch [2920/4000] Training [11/16] Loss: 0.00312 +Epoch [2920/4000] Training [12/16] Loss: 0.00259 +Epoch [2920/4000] Training [13/16] Loss: 0.00268 +Epoch [2920/4000] Training [14/16] Loss: 0.00447 +Epoch [2920/4000] Training [15/16] Loss: 0.00289 +Epoch [2920/4000] Training [16/16] Loss: 0.00389 +Epoch [2920/4000] Training metric {'Train/mean dice_metric': 0.997981071472168, 'Train/mean miou_metric': 0.9956883788108826, 'Train/mean f1': 0.9930253028869629, 'Train/mean precision': 0.988247275352478, 'Train/mean recall': 0.9978498220443726, 'Train/mean hd95_metric': 0.8219586610794067} +Epoch [2920/4000] Validation [1/4] Loss: 0.33388 focal_loss 0.27357 dice_loss 0.06031 +Epoch [2920/4000] Validation [2/4] Loss: 0.43836 focal_loss 0.32790 dice_loss 0.11046 +Epoch [2920/4000] Validation [3/4] Loss: 0.48013 focal_loss 0.38314 dice_loss 0.09699 +Epoch [2920/4000] Validation [4/4] Loss: 0.32536 focal_loss 0.23158 dice_loss 0.09378 +Epoch [2920/4000] Validation metric {'Val/mean dice_metric': 0.9744774103164673, 'Val/mean miou_metric': 0.9595653414726257, 'Val/mean f1': 0.976464569568634, 'Val/mean precision': 0.9744319915771484, 'Val/mean recall': 0.9785056114196777, 'Val/mean hd95_metric': 5.11391019821167} +Cheakpoint... +Epoch [2920/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744774103164673, 'Val/mean miou_metric': 0.9595653414726257, 'Val/mean f1': 0.976464569568634, 'Val/mean precision': 0.9744319915771484, 'Val/mean recall': 0.9785056114196777, 'Val/mean hd95_metric': 5.11391019821167} +Epoch [2921/4000] Training [1/16] Loss: 0.00302 +Epoch [2921/4000] Training [2/16] Loss: 0.00550 +Epoch [2921/4000] Training [3/16] Loss: 0.00335 +Epoch [2921/4000] Training [4/16] Loss: 0.00413 +Epoch [2921/4000] Training [5/16] Loss: 0.00353 +Epoch [2921/4000] Training [6/16] Loss: 0.00383 +Epoch [2921/4000] Training [7/16] Loss: 0.00367 +Epoch [2921/4000] Training [8/16] Loss: 0.00397 +Epoch [2921/4000] Training [9/16] Loss: 0.00331 +Epoch [2921/4000] Training [10/16] Loss: 0.00246 +Epoch [2921/4000] Training [11/16] Loss: 0.00388 +Epoch [2921/4000] Training [12/16] Loss: 0.00243 +Epoch [2921/4000] Training [13/16] Loss: 0.00375 +Epoch [2921/4000] Training [14/16] Loss: 0.00381 +Epoch [2921/4000] Training [15/16] Loss: 0.00300 +Epoch [2921/4000] Training [16/16] Loss: 0.00321 +Epoch [2921/4000] Training metric {'Train/mean dice_metric': 0.9979897141456604, 'Train/mean miou_metric': 0.9957142472267151, 'Train/mean f1': 0.9932920336723328, 'Train/mean precision': 0.9888438582420349, 'Train/mean recall': 0.9977803826332092, 'Train/mean hd95_metric': 0.836941659450531} +Epoch [2921/4000] Validation [1/4] Loss: 0.33628 focal_loss 0.27556 dice_loss 0.06071 +Epoch [2921/4000] Validation [2/4] Loss: 0.42524 focal_loss 0.31553 dice_loss 0.10971 +Epoch [2921/4000] Validation [3/4] Loss: 0.47954 focal_loss 0.39151 dice_loss 0.08803 +Epoch [2921/4000] Validation [4/4] Loss: 0.34913 focal_loss 0.23193 dice_loss 0.11720 +Epoch [2921/4000] Validation metric {'Val/mean dice_metric': 0.9750312566757202, 'Val/mean miou_metric': 0.9605256915092468, 'Val/mean f1': 0.9761680364608765, 'Val/mean precision': 0.9733714461326599, 'Val/mean recall': 0.9789807200431824, 'Val/mean hd95_metric': 4.972825527191162} +Cheakpoint... +Epoch [2921/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750312566757202, 'Val/mean miou_metric': 0.9605256915092468, 'Val/mean f1': 0.9761680364608765, 'Val/mean precision': 0.9733714461326599, 'Val/mean recall': 0.9789807200431824, 'Val/mean hd95_metric': 4.972825527191162} +Epoch [2922/4000] Training [1/16] Loss: 0.00354 +Epoch [2922/4000] Training [2/16] Loss: 0.00271 +Epoch [2922/4000] Training [3/16] Loss: 0.00421 +Epoch [2922/4000] Training [4/16] Loss: 0.00247 +Epoch [2922/4000] Training [5/16] Loss: 0.00244 +Epoch [2922/4000] Training [6/16] Loss: 0.00330 +Epoch [2922/4000] Training [7/16] Loss: 0.00243 +Epoch [2922/4000] Training [8/16] Loss: 0.00292 +Epoch [2922/4000] Training [9/16] Loss: 0.00370 +Epoch [2922/4000] Training [10/16] Loss: 0.00287 +Epoch [2922/4000] Training [11/16] Loss: 0.00401 +Epoch [2922/4000] Training [12/16] Loss: 0.00371 +Epoch [2922/4000] Training [13/16] Loss: 0.00240 +Epoch [2922/4000] Training [14/16] Loss: 0.00267 +Epoch [2922/4000] Training [15/16] Loss: 0.00371 +Epoch [2922/4000] Training [16/16] Loss: 0.00291 +Epoch [2922/4000] Training metric {'Train/mean dice_metric': 0.9980900287628174, 'Train/mean miou_metric': 0.9958839416503906, 'Train/mean f1': 0.9931111931800842, 'Train/mean precision': 0.9883880019187927, 'Train/mean recall': 0.997879683971405, 'Train/mean hd95_metric': 0.8219026327133179} +Epoch [2922/4000] Validation [1/4] Loss: 0.36192 focal_loss 0.29972 dice_loss 0.06220 +Epoch [2922/4000] Validation [2/4] Loss: 0.41571 focal_loss 0.30671 dice_loss 0.10900 +Epoch [2922/4000] Validation [3/4] Loss: 0.48853 focal_loss 0.39155 dice_loss 0.09698 +Epoch [2922/4000] Validation [4/4] Loss: 0.40833 focal_loss 0.28250 dice_loss 0.12583 +Epoch [2922/4000] Validation metric {'Val/mean dice_metric': 0.9744418263435364, 'Val/mean miou_metric': 0.9593895077705383, 'Val/mean f1': 0.9757860898971558, 'Val/mean precision': 0.9737354516983032, 'Val/mean recall': 0.9778453707695007, 'Val/mean hd95_metric': 4.865667343139648} +Cheakpoint... +Epoch [2922/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744418263435364, 'Val/mean miou_metric': 0.9593895077705383, 'Val/mean f1': 0.9757860898971558, 'Val/mean precision': 0.9737354516983032, 'Val/mean recall': 0.9778453707695007, 'Val/mean hd95_metric': 4.865667343139648} +Epoch [2923/4000] Training [1/16] Loss: 0.00353 +Epoch [2923/4000] Training [2/16] Loss: 0.00220 +Epoch [2923/4000] Training [3/16] Loss: 0.00308 +Epoch [2923/4000] Training [4/16] Loss: 0.00326 +Epoch [2923/4000] Training [5/16] Loss: 0.00235 +Epoch [2923/4000] Training [6/16] Loss: 0.00457 +Epoch [2923/4000] Training [7/16] Loss: 0.00387 +Epoch [2923/4000] Training [8/16] Loss: 0.00346 +Epoch [2923/4000] Training [9/16] Loss: 0.00277 +Epoch [2923/4000] Training [10/16] Loss: 0.00324 +Epoch [2923/4000] Training [11/16] Loss: 0.00371 +Epoch [2923/4000] Training [12/16] Loss: 0.00271 +Epoch [2923/4000] Training [13/16] Loss: 0.00303 +Epoch [2923/4000] Training [14/16] Loss: 0.00301 +Epoch [2923/4000] Training [15/16] Loss: 0.00303 +Epoch [2923/4000] Training [16/16] Loss: 0.00283 +Epoch [2923/4000] Training metric {'Train/mean dice_metric': 0.9981122016906738, 'Train/mean miou_metric': 0.9959567189216614, 'Train/mean f1': 0.9931811690330505, 'Train/mean precision': 0.9885441064834595, 'Train/mean recall': 0.9978619813919067, 'Train/mean hd95_metric': 0.7787384986877441} +Epoch [2923/4000] Validation [1/4] Loss: 0.36588 focal_loss 0.30236 dice_loss 0.06352 +Epoch [2923/4000] Validation [2/4] Loss: 0.84395 focal_loss 0.66225 dice_loss 0.18169 +Epoch [2923/4000] Validation [3/4] Loss: 0.49688 focal_loss 0.40117 dice_loss 0.09572 +Epoch [2923/4000] Validation [4/4] Loss: 0.43148 focal_loss 0.30622 dice_loss 0.12526 +Epoch [2923/4000] Validation metric {'Val/mean dice_metric': 0.9733127355575562, 'Val/mean miou_metric': 0.9588451385498047, 'Val/mean f1': 0.9758456945419312, 'Val/mean precision': 0.9740047454833984, 'Val/mean recall': 0.9776936173439026, 'Val/mean hd95_metric': 4.923377990722656} +Cheakpoint... +Epoch [2923/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733127355575562, 'Val/mean miou_metric': 0.9588451385498047, 'Val/mean f1': 0.9758456945419312, 'Val/mean precision': 0.9740047454833984, 'Val/mean recall': 0.9776936173439026, 'Val/mean hd95_metric': 4.923377990722656} +Epoch [2924/4000] Training [1/16] Loss: 0.00502 +Epoch [2924/4000] Training [2/16] Loss: 0.00313 +Epoch [2924/4000] Training [3/16] Loss: 0.00271 +Epoch [2924/4000] Training [4/16] Loss: 0.00457 +Epoch [2924/4000] Training [5/16] Loss: 0.00312 +Epoch [2924/4000] Training [6/16] Loss: 0.00215 +Epoch [2924/4000] Training [7/16] Loss: 0.00287 +Epoch [2924/4000] Training [8/16] Loss: 0.00224 +Epoch [2924/4000] Training [9/16] Loss: 0.00427 +Epoch [2924/4000] Training [10/16] Loss: 0.00265 +Epoch [2924/4000] Training [11/16] Loss: 0.00306 +Epoch [2924/4000] Training [12/16] Loss: 0.00533 +Epoch [2924/4000] Training [13/16] Loss: 0.00288 +Epoch [2924/4000] Training [14/16] Loss: 0.00331 +Epoch [2924/4000] Training [15/16] Loss: 0.00437 +Epoch [2924/4000] Training [16/16] Loss: 0.00284 +Epoch [2924/4000] Training metric {'Train/mean dice_metric': 0.9980578422546387, 'Train/mean miou_metric': 0.9958475828170776, 'Train/mean f1': 0.9932631850242615, 'Train/mean precision': 0.9887216687202454, 'Train/mean recall': 0.9978465437889099, 'Train/mean hd95_metric': 0.7910711169242859} +Epoch [2924/4000] Validation [1/4] Loss: 0.36971 focal_loss 0.30557 dice_loss 0.06414 +Epoch [2924/4000] Validation [2/4] Loss: 0.87682 focal_loss 0.68985 dice_loss 0.18697 +Epoch [2924/4000] Validation [3/4] Loss: 0.46462 focal_loss 0.36959 dice_loss 0.09503 +Epoch [2924/4000] Validation [4/4] Loss: 0.32532 focal_loss 0.23357 dice_loss 0.09174 +Epoch [2924/4000] Validation metric {'Val/mean dice_metric': 0.973857581615448, 'Val/mean miou_metric': 0.9594791531562805, 'Val/mean f1': 0.976360559463501, 'Val/mean precision': 0.9744477868080139, 'Val/mean recall': 0.9782807230949402, 'Val/mean hd95_metric': 4.990443229675293} +Cheakpoint... +Epoch [2924/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973857581615448, 'Val/mean miou_metric': 0.9594791531562805, 'Val/mean f1': 0.976360559463501, 'Val/mean precision': 0.9744477868080139, 'Val/mean recall': 0.9782807230949402, 'Val/mean hd95_metric': 4.990443229675293} +Epoch [2925/4000] Training [1/16] Loss: 0.00376 +Epoch [2925/4000] Training [2/16] Loss: 0.00406 +Epoch [2925/4000] Training [3/16] Loss: 0.00298 +Epoch [2925/4000] Training [4/16] Loss: 0.00386 +Epoch [2925/4000] Training [5/16] Loss: 0.00255 +Epoch [2925/4000] Training [6/16] Loss: 0.00413 +Epoch [2925/4000] Training [7/16] Loss: 0.00362 +Epoch [2925/4000] Training [8/16] Loss: 0.00221 +Epoch [2925/4000] Training [9/16] Loss: 0.00443 +Epoch [2925/4000] Training [10/16] Loss: 0.00416 +Epoch [2925/4000] Training [11/16] Loss: 0.00373 +Epoch [2925/4000] Training [12/16] Loss: 0.00420 +Epoch [2925/4000] Training [13/16] Loss: 0.00343 +Epoch [2925/4000] Training [14/16] Loss: 0.00260 +Epoch [2925/4000] Training [15/16] Loss: 0.00260 +Epoch [2925/4000] Training [16/16] Loss: 0.00185 +Epoch [2925/4000] Training metric {'Train/mean dice_metric': 0.9980774521827698, 'Train/mean miou_metric': 0.9958760738372803, 'Train/mean f1': 0.9931117296218872, 'Train/mean precision': 0.9884371161460876, 'Train/mean recall': 0.9978308081626892, 'Train/mean hd95_metric': 0.8296451568603516} +Epoch [2925/4000] Validation [1/4] Loss: 0.34866 focal_loss 0.28504 dice_loss 0.06362 +Epoch [2925/4000] Validation [2/4] Loss: 0.41262 focal_loss 0.30279 dice_loss 0.10983 +Epoch [2925/4000] Validation [3/4] Loss: 0.49637 focal_loss 0.40261 dice_loss 0.09376 +Epoch [2925/4000] Validation [4/4] Loss: 0.37560 focal_loss 0.26309 dice_loss 0.11251 +Epoch [2925/4000] Validation metric {'Val/mean dice_metric': 0.9753972887992859, 'Val/mean miou_metric': 0.9606928825378418, 'Val/mean f1': 0.9757556915283203, 'Val/mean precision': 0.973274827003479, 'Val/mean recall': 0.9782492518424988, 'Val/mean hd95_metric': 4.990660190582275} +Cheakpoint... +Epoch [2925/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753972887992859, 'Val/mean miou_metric': 0.9606928825378418, 'Val/mean f1': 0.9757556915283203, 'Val/mean precision': 0.973274827003479, 'Val/mean recall': 0.9782492518424988, 'Val/mean hd95_metric': 4.990660190582275} +Epoch [2926/4000] Training [1/16] Loss: 0.00292 +Epoch [2926/4000] Training [2/16] Loss: 0.00207 +Epoch [2926/4000] Training [3/16] Loss: 0.00340 +Epoch [2926/4000] Training [4/16] Loss: 0.00329 +Epoch [2926/4000] Training [5/16] Loss: 0.00425 +Epoch [2926/4000] Training [6/16] Loss: 0.00241 +Epoch [2926/4000] Training [7/16] Loss: 0.00293 +Epoch [2926/4000] Training [8/16] Loss: 0.00396 +Epoch [2926/4000] Training [9/16] Loss: 0.00263 +Epoch [2926/4000] Training [10/16] Loss: 0.00284 +Epoch [2926/4000] Training [11/16] Loss: 0.00331 +Epoch [2926/4000] Training [12/16] Loss: 0.00435 +Epoch [2926/4000] Training [13/16] Loss: 0.00343 +Epoch [2926/4000] Training [14/16] Loss: 0.00374 +Epoch [2926/4000] Training [15/16] Loss: 0.00341 +Epoch [2926/4000] Training [16/16] Loss: 0.00295 +Epoch [2926/4000] Training metric {'Train/mean dice_metric': 0.9981734752655029, 'Train/mean miou_metric': 0.9960663318634033, 'Train/mean f1': 0.9932984113693237, 'Train/mean precision': 0.9887158870697021, 'Train/mean recall': 0.9979235529899597, 'Train/mean hd95_metric': 0.8009763956069946} +Epoch [2926/4000] Validation [1/4] Loss: 0.31924 focal_loss 0.26092 dice_loss 0.05831 +Epoch [2926/4000] Validation [2/4] Loss: 0.86564 focal_loss 0.67576 dice_loss 0.18988 +Epoch [2926/4000] Validation [3/4] Loss: 0.43040 focal_loss 0.33173 dice_loss 0.09867 +Epoch [2926/4000] Validation [4/4] Loss: 0.28764 focal_loss 0.20879 dice_loss 0.07885 +Epoch [2926/4000] Validation metric {'Val/mean dice_metric': 0.9737836122512817, 'Val/mean miou_metric': 0.959935188293457, 'Val/mean f1': 0.9762637615203857, 'Val/mean precision': 0.9741519093513489, 'Val/mean recall': 0.978384792804718, 'Val/mean hd95_metric': 4.731678009033203} +Cheakpoint... +Epoch [2926/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737836122512817, 'Val/mean miou_metric': 0.959935188293457, 'Val/mean f1': 0.9762637615203857, 'Val/mean precision': 0.9741519093513489, 'Val/mean recall': 0.978384792804718, 'Val/mean hd95_metric': 4.731678009033203} +Epoch [2927/4000] Training [1/16] Loss: 0.00384 +Epoch [2927/4000] Training [2/16] Loss: 0.00382 +Epoch [2927/4000] Training [3/16] Loss: 0.00261 +Epoch [2927/4000] Training [4/16] Loss: 0.00266 +Epoch [2927/4000] Training [5/16] Loss: 0.00322 +Epoch [2927/4000] Training [6/16] Loss: 0.00606 +Epoch [2927/4000] Training [7/16] Loss: 0.00732 +Epoch [2927/4000] Training [8/16] Loss: 0.00378 +Epoch [2927/4000] Training [9/16] Loss: 0.00298 +Epoch [2927/4000] Training [10/16] Loss: 0.00259 +Epoch [2927/4000] Training [11/16] Loss: 0.00343 +Epoch [2927/4000] Training [12/16] Loss: 0.00409 +Epoch [2927/4000] Training [13/16] Loss: 0.00360 +Epoch [2927/4000] Training [14/16] Loss: 0.00332 +Epoch [2927/4000] Training [15/16] Loss: 0.00288 +Epoch [2927/4000] Training [16/16] Loss: 0.00257 +Epoch [2927/4000] Training metric {'Train/mean dice_metric': 0.9979563355445862, 'Train/mean miou_metric': 0.9956371784210205, 'Train/mean f1': 0.9930794835090637, 'Train/mean precision': 0.9883614182472229, 'Train/mean recall': 0.9978428483009338, 'Train/mean hd95_metric': 0.8133366107940674} +Epoch [2927/4000] Validation [1/4] Loss: 0.36609 focal_loss 0.30244 dice_loss 0.06364 +Epoch [2927/4000] Validation [2/4] Loss: 0.85123 focal_loss 0.65813 dice_loss 0.19310 +Epoch [2927/4000] Validation [3/4] Loss: 0.47011 focal_loss 0.38010 dice_loss 0.09000 +Epoch [2927/4000] Validation [4/4] Loss: 0.50680 focal_loss 0.38426 dice_loss 0.12254 +Epoch [2927/4000] Validation metric {'Val/mean dice_metric': 0.9726089239120483, 'Val/mean miou_metric': 0.958361029624939, 'Val/mean f1': 0.9755104780197144, 'Val/mean precision': 0.9745766520500183, 'Val/mean recall': 0.9764460325241089, 'Val/mean hd95_metric': 5.032731056213379} +Cheakpoint... +Epoch [2927/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726089239120483, 'Val/mean miou_metric': 0.958361029624939, 'Val/mean f1': 0.9755104780197144, 'Val/mean precision': 0.9745766520500183, 'Val/mean recall': 0.9764460325241089, 'Val/mean hd95_metric': 5.032731056213379} +Epoch [2928/4000] Training [1/16] Loss: 0.00395 +Epoch [2928/4000] Training [2/16] Loss: 0.00345 +Epoch [2928/4000] Training [3/16] Loss: 0.00384 +Epoch [2928/4000] Training [4/16] Loss: 0.00294 +Epoch [2928/4000] Training [5/16] Loss: 0.00204 +Epoch [2928/4000] Training [6/16] Loss: 0.00373 +Epoch [2928/4000] Training [7/16] Loss: 0.00321 +Epoch [2928/4000] Training [8/16] Loss: 0.00318 +Epoch [2928/4000] Training [9/16] Loss: 0.00201 +Epoch [2928/4000] Training [10/16] Loss: 0.00233 +Epoch [2928/4000] Training [11/16] Loss: 0.00376 +Epoch [2928/4000] Training [12/16] Loss: 0.00402 +Epoch [2928/4000] Training [13/16] Loss: 0.00304 +Epoch [2928/4000] Training [14/16] Loss: 0.00442 +Epoch [2928/4000] Training [15/16] Loss: 0.00319 +Epoch [2928/4000] Training [16/16] Loss: 0.00324 +Epoch [2928/4000] Training metric {'Train/mean dice_metric': 0.9981077909469604, 'Train/mean miou_metric': 0.995924174785614, 'Train/mean f1': 0.9928887486457825, 'Train/mean precision': 0.9880073070526123, 'Train/mean recall': 0.997818648815155, 'Train/mean hd95_metric': 0.814448356628418} +Epoch [2928/4000] Validation [1/4] Loss: 0.34043 focal_loss 0.28081 dice_loss 0.05962 +Epoch [2928/4000] Validation [2/4] Loss: 0.85484 focal_loss 0.66339 dice_loss 0.19144 +Epoch [2928/4000] Validation [3/4] Loss: 0.46979 focal_loss 0.38066 dice_loss 0.08913 +Epoch [2928/4000] Validation [4/4] Loss: 0.39509 focal_loss 0.28498 dice_loss 0.11011 +Epoch [2928/4000] Validation metric {'Val/mean dice_metric': 0.9746650457382202, 'Val/mean miou_metric': 0.9605236053466797, 'Val/mean f1': 0.9757543206214905, 'Val/mean precision': 0.9734940528869629, 'Val/mean recall': 0.9780250787734985, 'Val/mean hd95_metric': 5.017228126525879} +Cheakpoint... +Epoch [2928/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746650457382202, 'Val/mean miou_metric': 0.9605236053466797, 'Val/mean f1': 0.9757543206214905, 'Val/mean precision': 0.9734940528869629, 'Val/mean recall': 0.9780250787734985, 'Val/mean hd95_metric': 5.017228126525879} +Epoch [2929/4000] Training [1/16] Loss: 0.00283 +Epoch [2929/4000] Training [2/16] Loss: 0.00312 +Epoch [2929/4000] Training [3/16] Loss: 0.00404 +Epoch [2929/4000] Training [4/16] Loss: 0.00259 +Epoch [2929/4000] Training [5/16] Loss: 0.00249 +Epoch [2929/4000] Training [6/16] Loss: 0.00235 +Epoch [2929/4000] Training [7/16] Loss: 0.00308 +Epoch [2929/4000] Training [8/16] Loss: 0.00357 +Epoch [2929/4000] Training [9/16] Loss: 0.00356 +Epoch [2929/4000] Training [10/16] Loss: 0.00302 +Epoch [2929/4000] Training [11/16] Loss: 0.00330 +Epoch [2929/4000] Training [12/16] Loss: 0.00621 +Epoch [2929/4000] Training [13/16] Loss: 0.00328 +Epoch [2929/4000] Training [14/16] Loss: 0.00352 +Epoch [2929/4000] Training [15/16] Loss: 0.00213 +Epoch [2929/4000] Training [16/16] Loss: 0.00271 +Epoch [2929/4000] Training metric {'Train/mean dice_metric': 0.9980936050415039, 'Train/mean miou_metric': 0.9958840012550354, 'Train/mean f1': 0.9925382137298584, 'Train/mean precision': 0.9872828722000122, 'Train/mean recall': 0.9978497624397278, 'Train/mean hd95_metric': 0.8173127174377441} +Epoch [2929/4000] Validation [1/4] Loss: 0.38827 focal_loss 0.32454 dice_loss 0.06373 +Epoch [2929/4000] Validation [2/4] Loss: 1.34657 focal_loss 1.04235 dice_loss 0.30422 +Epoch [2929/4000] Validation [3/4] Loss: 0.52522 focal_loss 0.43111 dice_loss 0.09412 +Epoch [2929/4000] Validation [4/4] Loss: 0.32053 focal_loss 0.22642 dice_loss 0.09412 +Epoch [2929/4000] Validation metric {'Val/mean dice_metric': 0.9718748331069946, 'Val/mean miou_metric': 0.9577207565307617, 'Val/mean f1': 0.9747598767280579, 'Val/mean precision': 0.9718250036239624, 'Val/mean recall': 0.9777126312255859, 'Val/mean hd95_metric': 5.322037220001221} +Cheakpoint... +Epoch [2929/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718748331069946, 'Val/mean miou_metric': 0.9577207565307617, 'Val/mean f1': 0.9747598767280579, 'Val/mean precision': 0.9718250036239624, 'Val/mean recall': 0.9777126312255859, 'Val/mean hd95_metric': 5.322037220001221} +Epoch [2930/4000] Training [1/16] Loss: 0.00270 +Epoch [2930/4000] Training [2/16] Loss: 0.00291 +Epoch [2930/4000] Training [3/16] Loss: 0.00347 +Epoch [2930/4000] Training [4/16] Loss: 0.00257 +Epoch [2930/4000] Training [5/16] Loss: 0.00310 +Epoch [2930/4000] Training [6/16] Loss: 0.00399 +Epoch [2930/4000] Training [7/16] Loss: 0.00338 +Epoch [2930/4000] Training [8/16] Loss: 0.00493 +Epoch [2930/4000] Training [9/16] Loss: 0.00288 +Epoch [2930/4000] Training [10/16] Loss: 0.00386 +Epoch [2930/4000] Training [11/16] Loss: 0.00260 +Epoch [2930/4000] Training [12/16] Loss: 0.00385 +Epoch [2930/4000] Training [13/16] Loss: 0.00309 +Epoch [2930/4000] Training [14/16] Loss: 0.00383 +Epoch [2930/4000] Training [15/16] Loss: 0.00333 +Epoch [2930/4000] Training [16/16] Loss: 0.00655 +Epoch [2930/4000] Training metric {'Train/mean dice_metric': 0.9979135990142822, 'Train/mean miou_metric': 0.9955717921257019, 'Train/mean f1': 0.993179202079773, 'Train/mean precision': 0.9886379837989807, 'Train/mean recall': 0.9977623820304871, 'Train/mean hd95_metric': 0.8606209754943848} +Epoch [2930/4000] Validation [1/4] Loss: 0.38471 focal_loss 0.32172 dice_loss 0.06298 +Epoch [2930/4000] Validation [2/4] Loss: 0.85071 focal_loss 0.65045 dice_loss 0.20025 +Epoch [2930/4000] Validation [3/4] Loss: 0.53979 focal_loss 0.44479 dice_loss 0.09500 +Epoch [2930/4000] Validation [4/4] Loss: 0.29521 focal_loss 0.19827 dice_loss 0.09694 +Epoch [2930/4000] Validation metric {'Val/mean dice_metric': 0.9742509722709656, 'Val/mean miou_metric': 0.9599189758300781, 'Val/mean f1': 0.9757224321365356, 'Val/mean precision': 0.9720858931541443, 'Val/mean recall': 0.9793863296508789, 'Val/mean hd95_metric': 5.359159469604492} +Cheakpoint... +Epoch [2930/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742509722709656, 'Val/mean miou_metric': 0.9599189758300781, 'Val/mean f1': 0.9757224321365356, 'Val/mean precision': 0.9720858931541443, 'Val/mean recall': 0.9793863296508789, 'Val/mean hd95_metric': 5.359159469604492} +Epoch [2931/4000] Training [1/16] Loss: 0.00283 +Epoch [2931/4000] Training [2/16] Loss: 0.00372 +Epoch [2931/4000] Training [3/16] Loss: 0.00261 +Epoch [2931/4000] Training [4/16] Loss: 0.00319 +Epoch [2931/4000] Training [5/16] Loss: 0.00316 +Epoch [2931/4000] Training [6/16] Loss: 0.00337 +Epoch [2931/4000] Training [7/16] Loss: 0.00322 +Epoch [2931/4000] Training [8/16] Loss: 0.00432 +Epoch [2931/4000] Training [9/16] Loss: 0.00286 +Epoch [2931/4000] Training [10/16] Loss: 0.00391 +Epoch [2931/4000] Training [11/16] Loss: 0.00281 +Epoch [2931/4000] Training [12/16] Loss: 0.00309 +Epoch [2931/4000] Training [13/16] Loss: 0.00293 +Epoch [2931/4000] Training [14/16] Loss: 0.00372 +Epoch [2931/4000] Training [15/16] Loss: 0.00278 +Epoch [2931/4000] Training [16/16] Loss: 0.00308 +Epoch [2931/4000] Training metric {'Train/mean dice_metric': 0.9981018304824829, 'Train/mean miou_metric': 0.9959052801132202, 'Train/mean f1': 0.9929400682449341, 'Train/mean precision': 0.9881501197814941, 'Train/mean recall': 0.9977767467498779, 'Train/mean hd95_metric': 0.829129159450531} +Epoch [2931/4000] Validation [1/4] Loss: 0.34714 focal_loss 0.28453 dice_loss 0.06261 +Epoch [2931/4000] Validation [2/4] Loss: 0.52661 focal_loss 0.38702 dice_loss 0.13959 +Epoch [2931/4000] Validation [3/4] Loss: 0.50597 focal_loss 0.41671 dice_loss 0.08926 +Epoch [2931/4000] Validation [4/4] Loss: 0.36437 focal_loss 0.24670 dice_loss 0.11767 +Epoch [2931/4000] Validation metric {'Val/mean dice_metric': 0.9742819666862488, 'Val/mean miou_metric': 0.9592603445053101, 'Val/mean f1': 0.9752339124679565, 'Val/mean precision': 0.9715968370437622, 'Val/mean recall': 0.9788982272148132, 'Val/mean hd95_metric': 5.431903839111328} +Cheakpoint... +Epoch [2931/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742819666862488, 'Val/mean miou_metric': 0.9592603445053101, 'Val/mean f1': 0.9752339124679565, 'Val/mean precision': 0.9715968370437622, 'Val/mean recall': 0.9788982272148132, 'Val/mean hd95_metric': 5.431903839111328} +Epoch [2932/4000] Training [1/16] Loss: 0.00366 +Epoch [2932/4000] Training [2/16] Loss: 0.00316 +Epoch [2932/4000] Training [3/16] Loss: 0.00272 +Epoch [2932/4000] Training [4/16] Loss: 0.00246 +Epoch [2932/4000] Training [5/16] Loss: 0.00316 +Epoch [2932/4000] Training [6/16] Loss: 0.00294 +Epoch [2932/4000] Training [7/16] Loss: 0.00300 +Epoch [2932/4000] Training [8/16] Loss: 0.00276 +Epoch [2932/4000] Training [9/16] Loss: 0.00233 +Epoch [2932/4000] Training [10/16] Loss: 0.00308 +Epoch [2932/4000] Training [11/16] Loss: 0.00345 +Epoch [2932/4000] Training [12/16] Loss: 0.00254 +Epoch [2932/4000] Training [13/16] Loss: 0.00561 +Epoch [2932/4000] Training [14/16] Loss: 0.00297 +Epoch [2932/4000] Training [15/16] Loss: 0.00316 +Epoch [2932/4000] Training [16/16] Loss: 0.00325 +Epoch [2932/4000] Training metric {'Train/mean dice_metric': 0.9981659650802612, 'Train/mean miou_metric': 0.9960434436798096, 'Train/mean f1': 0.9926947951316833, 'Train/mean precision': 0.9875519871711731, 'Train/mean recall': 0.9978914260864258, 'Train/mean hd95_metric': 0.7825471758842468} +Epoch [2932/4000] Validation [1/4] Loss: 0.35534 focal_loss 0.29293 dice_loss 0.06240 +Epoch [2932/4000] Validation [2/4] Loss: 0.48179 focal_loss 0.36469 dice_loss 0.11710 +Epoch [2932/4000] Validation [3/4] Loss: 0.53047 focal_loss 0.43237 dice_loss 0.09810 +Epoch [2932/4000] Validation [4/4] Loss: 0.43645 focal_loss 0.31191 dice_loss 0.12454 +Epoch [2932/4000] Validation metric {'Val/mean dice_metric': 0.9733285903930664, 'Val/mean miou_metric': 0.9583708047866821, 'Val/mean f1': 0.9750127196311951, 'Val/mean precision': 0.9720386266708374, 'Val/mean recall': 0.9780051708221436, 'Val/mean hd95_metric': 5.50605583190918} +Cheakpoint... +Epoch [2932/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733285903930664, 'Val/mean miou_metric': 0.9583708047866821, 'Val/mean f1': 0.9750127196311951, 'Val/mean precision': 0.9720386266708374, 'Val/mean recall': 0.9780051708221436, 'Val/mean hd95_metric': 5.50605583190918} +Epoch [2933/4000] Training [1/16] Loss: 0.00310 +Epoch [2933/4000] Training [2/16] Loss: 0.00294 +Epoch [2933/4000] Training [3/16] Loss: 0.00320 +Epoch [2933/4000] Training [4/16] Loss: 0.00475 +Epoch [2933/4000] Training [5/16] Loss: 0.00313 +Epoch [2933/4000] Training [6/16] Loss: 0.00377 +Epoch [2933/4000] Training [7/16] Loss: 0.00309 +Epoch [2933/4000] Training [8/16] Loss: 0.00425 +Epoch [2933/4000] Training [9/16] Loss: 0.00382 +Epoch [2933/4000] Training [10/16] Loss: 0.00204 +Epoch [2933/4000] Training [11/16] Loss: 0.00297 +Epoch [2933/4000] Training [12/16] Loss: 0.00293 +Epoch [2933/4000] Training [13/16] Loss: 0.00331 +Epoch [2933/4000] Training [14/16] Loss: 0.00297 +Epoch [2933/4000] Training [15/16] Loss: 0.00443 +Epoch [2933/4000] Training [16/16] Loss: 0.00380 +Epoch [2933/4000] Training metric {'Train/mean dice_metric': 0.9981554746627808, 'Train/mean miou_metric': 0.9960372447967529, 'Train/mean f1': 0.9934208989143372, 'Train/mean precision': 0.9889218211174011, 'Train/mean recall': 0.9979611039161682, 'Train/mean hd95_metric': 0.8345003128051758} +Epoch [2933/4000] Validation [1/4] Loss: 0.35054 focal_loss 0.28766 dice_loss 0.06288 +Epoch [2933/4000] Validation [2/4] Loss: 0.88006 focal_loss 0.66070 dice_loss 0.21936 +Epoch [2933/4000] Validation [3/4] Loss: 0.50334 focal_loss 0.41181 dice_loss 0.09153 +Epoch [2933/4000] Validation [4/4] Loss: 0.25557 focal_loss 0.17500 dice_loss 0.08057 +Epoch [2933/4000] Validation metric {'Val/mean dice_metric': 0.9718382954597473, 'Val/mean miou_metric': 0.9577833414077759, 'Val/mean f1': 0.9761220812797546, 'Val/mean precision': 0.9741812348365784, 'Val/mean recall': 0.9780706763267517, 'Val/mean hd95_metric': 5.298250198364258} +Cheakpoint... +Epoch [2933/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718382954597473, 'Val/mean miou_metric': 0.9577833414077759, 'Val/mean f1': 0.9761220812797546, 'Val/mean precision': 0.9741812348365784, 'Val/mean recall': 0.9780706763267517, 'Val/mean hd95_metric': 5.298250198364258} +Epoch [2934/4000] Training [1/16] Loss: 0.00452 +Epoch [2934/4000] Training [2/16] Loss: 0.00355 +Epoch [2934/4000] Training [3/16] Loss: 0.00325 +Epoch [2934/4000] Training [4/16] Loss: 0.00296 +Epoch [2934/4000] Training [5/16] Loss: 0.00291 +Epoch [2934/4000] Training [6/16] Loss: 0.00341 +Epoch [2934/4000] Training [7/16] Loss: 0.00558 +Epoch [2934/4000] Training [8/16] Loss: 0.00247 +Epoch [2934/4000] Training [9/16] Loss: 0.00252 +Epoch [2934/4000] Training [10/16] Loss: 0.00297 +Epoch [2934/4000] Training [11/16] Loss: 0.00295 +Epoch [2934/4000] Training [12/16] Loss: 0.00291 +Epoch [2934/4000] Training [13/16] Loss: 0.00396 +Epoch [2934/4000] Training [14/16] Loss: 0.00371 +Epoch [2934/4000] Training [15/16] Loss: 0.00312 +Epoch [2934/4000] Training [16/16] Loss: 0.00300 +Epoch [2934/4000] Training metric {'Train/mean dice_metric': 0.9980344772338867, 'Train/mean miou_metric': 0.9957830905914307, 'Train/mean f1': 0.9928919672966003, 'Train/mean precision': 0.9880595803260803, 'Train/mean recall': 0.9977717995643616, 'Train/mean hd95_metric': 0.8210792541503906} +Epoch [2934/4000] Validation [1/4] Loss: 0.37346 focal_loss 0.30881 dice_loss 0.06465 +Epoch [2934/4000] Validation [2/4] Loss: 0.85687 focal_loss 0.66371 dice_loss 0.19315 +Epoch [2934/4000] Validation [3/4] Loss: 0.28332 focal_loss 0.21309 dice_loss 0.07023 +Epoch [2934/4000] Validation [4/4] Loss: 0.36692 focal_loss 0.26101 dice_loss 0.10591 +Epoch [2934/4000] Validation metric {'Val/mean dice_metric': 0.9737190008163452, 'Val/mean miou_metric': 0.9593232274055481, 'Val/mean f1': 0.9756781458854675, 'Val/mean precision': 0.9727747440338135, 'Val/mean recall': 0.9785991311073303, 'Val/mean hd95_metric': 5.1545090675354} +Cheakpoint... +Epoch [2934/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737190008163452, 'Val/mean miou_metric': 0.9593232274055481, 'Val/mean f1': 0.9756781458854675, 'Val/mean precision': 0.9727747440338135, 'Val/mean recall': 0.9785991311073303, 'Val/mean hd95_metric': 5.1545090675354} +Epoch [2935/4000] Training [1/16] Loss: 0.00370 +Epoch [2935/4000] Training [2/16] Loss: 0.00415 +Epoch [2935/4000] Training [3/16] Loss: 0.00293 +Epoch [2935/4000] Training [4/16] Loss: 0.00310 +Epoch [2935/4000] Training [5/16] Loss: 0.00286 +Epoch [2935/4000] Training [6/16] Loss: 0.00657 +Epoch [2935/4000] Training [7/16] Loss: 0.00334 +Epoch [2935/4000] Training [8/16] Loss: 0.00522 +Epoch [2935/4000] Training [9/16] Loss: 0.00358 +Epoch [2935/4000] Training [10/16] Loss: 0.00411 +Epoch [2935/4000] Training [11/16] Loss: 0.00275 +Epoch [2935/4000] Training [12/16] Loss: 0.00272 +Epoch [2935/4000] Training [13/16] Loss: 0.00237 +Epoch [2935/4000] Training [14/16] Loss: 0.00302 +Epoch [2935/4000] Training [15/16] Loss: 0.00281 +Epoch [2935/4000] Training [16/16] Loss: 0.00313 +Epoch [2935/4000] Training metric {'Train/mean dice_metric': 0.998132586479187, 'Train/mean miou_metric': 0.9959826469421387, 'Train/mean f1': 0.9931002855300903, 'Train/mean precision': 0.9884175658226013, 'Train/mean recall': 0.9978275895118713, 'Train/mean hd95_metric': 0.7953704595565796} +Epoch [2935/4000] Validation [1/4] Loss: 0.36744 focal_loss 0.30344 dice_loss 0.06399 +Epoch [2935/4000] Validation [2/4] Loss: 0.45489 focal_loss 0.34381 dice_loss 0.11109 +Epoch [2935/4000] Validation [3/4] Loss: 0.53136 focal_loss 0.43021 dice_loss 0.10115 +Epoch [2935/4000] Validation [4/4] Loss: 0.43453 focal_loss 0.32188 dice_loss 0.11264 +Epoch [2935/4000] Validation metric {'Val/mean dice_metric': 0.9742155075073242, 'Val/mean miou_metric': 0.9591464996337891, 'Val/mean f1': 0.9757922887802124, 'Val/mean precision': 0.9728547930717468, 'Val/mean recall': 0.9787473678588867, 'Val/mean hd95_metric': 5.059970378875732} +Cheakpoint... +Epoch [2935/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742155075073242, 'Val/mean miou_metric': 0.9591464996337891, 'Val/mean f1': 0.9757922887802124, 'Val/mean precision': 0.9728547930717468, 'Val/mean recall': 0.9787473678588867, 'Val/mean hd95_metric': 5.059970378875732} +Epoch [2936/4000] Training [1/16] Loss: 0.00566 +Epoch [2936/4000] Training [2/16] Loss: 0.00311 +Epoch [2936/4000] Training [3/16] Loss: 0.00266 +Epoch [2936/4000] Training [4/16] Loss: 0.00298 +Epoch [2936/4000] Training [5/16] Loss: 0.00315 +Epoch [2936/4000] Training [6/16] Loss: 0.00376 +Epoch [2936/4000] Training [7/16] Loss: 0.00264 +Epoch [2936/4000] Training [8/16] Loss: 0.00358 +Epoch [2936/4000] Training [9/16] Loss: 0.00232 +Epoch [2936/4000] Training [10/16] Loss: 0.00399 +Epoch [2936/4000] Training [11/16] Loss: 0.00259 +Epoch [2936/4000] Training [12/16] Loss: 0.00328 +Epoch [2936/4000] Training [13/16] Loss: 0.00384 +Epoch [2936/4000] Training [14/16] Loss: 0.00474 +Epoch [2936/4000] Training [15/16] Loss: 0.00347 +Epoch [2936/4000] Training [16/16] Loss: 0.00362 +Epoch [2936/4000] Training metric {'Train/mean dice_metric': 0.9980224967002869, 'Train/mean miou_metric': 0.995780885219574, 'Train/mean f1': 0.9931371808052063, 'Train/mean precision': 0.9886353611946106, 'Train/mean recall': 0.9976801872253418, 'Train/mean hd95_metric': 0.7892433404922485} +Epoch [2936/4000] Validation [1/4] Loss: 0.35703 focal_loss 0.29385 dice_loss 0.06319 +Epoch [2936/4000] Validation [2/4] Loss: 0.42087 focal_loss 0.31470 dice_loss 0.10616 +Epoch [2936/4000] Validation [3/4] Loss: 0.52871 focal_loss 0.43419 dice_loss 0.09452 +Epoch [2936/4000] Validation [4/4] Loss: 0.42059 focal_loss 0.29837 dice_loss 0.12222 +Epoch [2936/4000] Validation metric {'Val/mean dice_metric': 0.9753156900405884, 'Val/mean miou_metric': 0.9603880047798157, 'Val/mean f1': 0.9756304621696472, 'Val/mean precision': 0.9733182787895203, 'Val/mean recall': 0.9779536128044128, 'Val/mean hd95_metric': 4.979167461395264} +Cheakpoint... +Epoch [2936/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753156900405884, 'Val/mean miou_metric': 0.9603880047798157, 'Val/mean f1': 0.9756304621696472, 'Val/mean precision': 0.9733182787895203, 'Val/mean recall': 0.9779536128044128, 'Val/mean hd95_metric': 4.979167461395264} +Epoch [2937/4000] Training [1/16] Loss: 0.00308 +Epoch [2937/4000] Training [2/16] Loss: 0.00339 +Epoch [2937/4000] Training [3/16] Loss: 0.00347 +Epoch [2937/4000] Training [4/16] Loss: 0.00523 +Epoch [2937/4000] Training [5/16] Loss: 0.00278 +Epoch [2937/4000] Training [6/16] Loss: 0.00229 +Epoch [2937/4000] Training [7/16] Loss: 0.00367 +Epoch [2937/4000] Training [8/16] Loss: 0.00280 +Epoch [2937/4000] Training [9/16] Loss: 0.00321 +Epoch [2937/4000] Training [10/16] Loss: 0.00333 +Epoch [2937/4000] Training [11/16] Loss: 0.00298 +Epoch [2937/4000] Training [12/16] Loss: 0.00290 +Epoch [2937/4000] Training [13/16] Loss: 0.00320 +Epoch [2937/4000] Training [14/16] Loss: 0.00292 +Epoch [2937/4000] Training [15/16] Loss: 0.00389 +Epoch [2937/4000] Training [16/16] Loss: 0.00295 +Epoch [2937/4000] Training metric {'Train/mean dice_metric': 0.998131513595581, 'Train/mean miou_metric': 0.9959959983825684, 'Train/mean f1': 0.9932563304901123, 'Train/mean precision': 0.9886890649795532, 'Train/mean recall': 0.9978660345077515, 'Train/mean hd95_metric': 0.7928218841552734} +Epoch [2937/4000] Validation [1/4] Loss: 0.33045 focal_loss 0.27172 dice_loss 0.05873 +Epoch [2937/4000] Validation [2/4] Loss: 0.58138 focal_loss 0.42223 dice_loss 0.15915 +Epoch [2937/4000] Validation [3/4] Loss: 0.49765 focal_loss 0.39688 dice_loss 0.10077 +Epoch [2937/4000] Validation [4/4] Loss: 0.40439 focal_loss 0.28137 dice_loss 0.12302 +Epoch [2937/4000] Validation metric {'Val/mean dice_metric': 0.9740662574768066, 'Val/mean miou_metric': 0.9593535661697388, 'Val/mean f1': 0.9760940670967102, 'Val/mean precision': 0.9726591110229492, 'Val/mean recall': 0.9795532822608948, 'Val/mean hd95_metric': 4.865717887878418} +Cheakpoint... +Epoch [2937/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740662574768066, 'Val/mean miou_metric': 0.9593535661697388, 'Val/mean f1': 0.9760940670967102, 'Val/mean precision': 0.9726591110229492, 'Val/mean recall': 0.9795532822608948, 'Val/mean hd95_metric': 4.865717887878418} +Epoch [2938/4000] Training [1/16] Loss: 0.00379 +Epoch [2938/4000] Training [2/16] Loss: 0.00309 +Epoch [2938/4000] Training [3/16] Loss: 0.00325 +Epoch [2938/4000] Training [4/16] Loss: 0.00409 +Epoch [2938/4000] Training [5/16] Loss: 0.00300 +Epoch [2938/4000] Training [6/16] Loss: 0.00340 +Epoch [2938/4000] Training [7/16] Loss: 0.00347 +Epoch [2938/4000] Training [8/16] Loss: 0.00356 +Epoch [2938/4000] Training [9/16] Loss: 0.00401 +Epoch [2938/4000] Training [10/16] Loss: 0.00275 +Epoch [2938/4000] Training [11/16] Loss: 0.00353 +Epoch [2938/4000] Training [12/16] Loss: 0.00384 +Epoch [2938/4000] Training [13/16] Loss: 0.00384 +Epoch [2938/4000] Training [14/16] Loss: 0.00431 +Epoch [2938/4000] Training [15/16] Loss: 0.00331 +Epoch [2938/4000] Training [16/16] Loss: 0.00282 +Epoch [2938/4000] Training metric {'Train/mean dice_metric': 0.997994065284729, 'Train/mean miou_metric': 0.9957156181335449, 'Train/mean f1': 0.9931293725967407, 'Train/mean precision': 0.9885224103927612, 'Train/mean recall': 0.9977794289588928, 'Train/mean hd95_metric': 0.7890201807022095} +Epoch [2938/4000] Validation [1/4] Loss: 0.36779 focal_loss 0.30565 dice_loss 0.06214 +Epoch [2938/4000] Validation [2/4] Loss: 0.48750 focal_loss 0.37384 dice_loss 0.11366 +Epoch [2938/4000] Validation [3/4] Loss: 0.42013 focal_loss 0.32596 dice_loss 0.09417 +Epoch [2938/4000] Validation [4/4] Loss: 0.42692 focal_loss 0.31125 dice_loss 0.11567 +Epoch [2938/4000] Validation metric {'Val/mean dice_metric': 0.9744197726249695, 'Val/mean miou_metric': 0.9598401784896851, 'Val/mean f1': 0.9757992029190063, 'Val/mean precision': 0.9739173650741577, 'Val/mean recall': 0.9776883721351624, 'Val/mean hd95_metric': 4.928238868713379} +Cheakpoint... +Epoch [2938/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744197726249695, 'Val/mean miou_metric': 0.9598401784896851, 'Val/mean f1': 0.9757992029190063, 'Val/mean precision': 0.9739173650741577, 'Val/mean recall': 0.9776883721351624, 'Val/mean hd95_metric': 4.928238868713379} +Epoch [2939/4000] Training [1/16] Loss: 0.00284 +Epoch [2939/4000] Training [2/16] Loss: 0.00440 +Epoch [2939/4000] Training [3/16] Loss: 0.00254 +Epoch [2939/4000] Training [4/16] Loss: 0.00313 +Epoch [2939/4000] Training [5/16] Loss: 0.00475 +Epoch [2939/4000] Training [6/16] Loss: 0.00278 +Epoch [2939/4000] Training [7/16] Loss: 0.00301 +Epoch [2939/4000] Training [8/16] Loss: 0.00335 +Epoch [2939/4000] Training [9/16] Loss: 0.00252 +Epoch [2939/4000] Training [10/16] Loss: 0.00613 +Epoch [2939/4000] Training [11/16] Loss: 0.00264 +Epoch [2939/4000] Training [12/16] Loss: 0.00333 +Epoch [2939/4000] Training [13/16] Loss: 0.00454 +Epoch [2939/4000] Training [14/16] Loss: 0.00460 +Epoch [2939/4000] Training [15/16] Loss: 0.00342 +Epoch [2939/4000] Training [16/16] Loss: 0.00325 +Epoch [2939/4000] Training metric {'Train/mean dice_metric': 0.9980124235153198, 'Train/mean miou_metric': 0.9957560300827026, 'Train/mean f1': 0.9932462573051453, 'Train/mean precision': 0.9887795448303223, 'Train/mean recall': 0.9977534413337708, 'Train/mean hd95_metric': 0.8162940740585327} +Epoch [2939/4000] Validation [1/4] Loss: 0.38309 focal_loss 0.31865 dice_loss 0.06444 +Epoch [2939/4000] Validation [2/4] Loss: 0.92617 focal_loss 0.73793 dice_loss 0.18824 +Epoch [2939/4000] Validation [3/4] Loss: 0.50529 focal_loss 0.41262 dice_loss 0.09267 +Epoch [2939/4000] Validation [4/4] Loss: 0.31556 focal_loss 0.23128 dice_loss 0.08428 +Epoch [2939/4000] Validation metric {'Val/mean dice_metric': 0.9716297388076782, 'Val/mean miou_metric': 0.9579149484634399, 'Val/mean f1': 0.9757229685783386, 'Val/mean precision': 0.9744077920913696, 'Val/mean recall': 0.9770417809486389, 'Val/mean hd95_metric': 5.452888011932373} +Cheakpoint... +Epoch [2939/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716297388076782, 'Val/mean miou_metric': 0.9579149484634399, 'Val/mean f1': 0.9757229685783386, 'Val/mean precision': 0.9744077920913696, 'Val/mean recall': 0.9770417809486389, 'Val/mean hd95_metric': 5.452888011932373} +Epoch [2940/4000] Training [1/16] Loss: 0.00319 +Epoch [2940/4000] Training [2/16] Loss: 0.00237 +Epoch [2940/4000] Training [3/16] Loss: 0.00299 +Epoch [2940/4000] Training [4/16] Loss: 0.00316 +Epoch [2940/4000] Training [5/16] Loss: 0.00258 +Epoch [2940/4000] Training [6/16] Loss: 0.00308 +Epoch [2940/4000] Training [7/16] Loss: 0.00390 +Epoch [2940/4000] Training [8/16] Loss: 0.00397 +Epoch [2940/4000] Training [9/16] Loss: 0.00391 +Epoch [2940/4000] Training [10/16] Loss: 0.00340 +Epoch [2940/4000] Training [11/16] Loss: 0.00242 +Epoch [2940/4000] Training [12/16] Loss: 0.00342 +Epoch [2940/4000] Training [13/16] Loss: 0.00313 +Epoch [2940/4000] Training [14/16] Loss: 0.00301 +Epoch [2940/4000] Training [15/16] Loss: 0.00395 +Epoch [2940/4000] Training [16/16] Loss: 0.00372 +Epoch [2940/4000] Training metric {'Train/mean dice_metric': 0.9979978203773499, 'Train/mean miou_metric': 0.9957027435302734, 'Train/mean f1': 0.9929839968681335, 'Train/mean precision': 0.9882409572601318, 'Train/mean recall': 0.9977728128433228, 'Train/mean hd95_metric': 0.8081331253051758} +Epoch [2940/4000] Validation [1/4] Loss: 0.36504 focal_loss 0.30082 dice_loss 0.06422 +Epoch [2940/4000] Validation [2/4] Loss: 0.98584 focal_loss 0.75774 dice_loss 0.22810 +Epoch [2940/4000] Validation [3/4] Loss: 0.48203 focal_loss 0.39175 dice_loss 0.09027 +Epoch [2940/4000] Validation [4/4] Loss: 0.47011 focal_loss 0.34321 dice_loss 0.12690 +Epoch [2940/4000] Validation metric {'Val/mean dice_metric': 0.971426784992218, 'Val/mean miou_metric': 0.9567403793334961, 'Val/mean f1': 0.9746745228767395, 'Val/mean precision': 0.9732288122177124, 'Val/mean recall': 0.9761245846748352, 'Val/mean hd95_metric': 5.259603023529053} +Cheakpoint... +Epoch [2940/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971426784992218, 'Val/mean miou_metric': 0.9567403793334961, 'Val/mean f1': 0.9746745228767395, 'Val/mean precision': 0.9732288122177124, 'Val/mean recall': 0.9761245846748352, 'Val/mean hd95_metric': 5.259603023529053} +Epoch [2941/4000] Training [1/16] Loss: 0.00372 +Epoch [2941/4000] Training [2/16] Loss: 0.00319 +Epoch [2941/4000] Training [3/16] Loss: 0.00236 +Epoch [2941/4000] Training [4/16] Loss: 0.00391 +Epoch [2941/4000] Training [5/16] Loss: 0.00302 +Epoch [2941/4000] Training [6/16] Loss: 0.00369 +Epoch [2941/4000] Training [7/16] Loss: 0.00299 +Epoch [2941/4000] Training [8/16] Loss: 0.00305 +Epoch [2941/4000] Training [9/16] Loss: 0.00310 +Epoch [2941/4000] Training [10/16] Loss: 0.00376 +Epoch [2941/4000] Training [11/16] Loss: 0.00265 +Epoch [2941/4000] Training [12/16] Loss: 0.00274 +Epoch [2941/4000] Training [13/16] Loss: 0.00369 +Epoch [2941/4000] Training [14/16] Loss: 0.00280 +Epoch [2941/4000] Training [15/16] Loss: 0.00327 +Epoch [2941/4000] Training [16/16] Loss: 0.00317 +Epoch [2941/4000] Training metric {'Train/mean dice_metric': 0.9981198310852051, 'Train/mean miou_metric': 0.9959701895713806, 'Train/mean f1': 0.9931973218917847, 'Train/mean precision': 0.9885703921318054, 'Train/mean recall': 0.9978677034378052, 'Train/mean hd95_metric': 0.8050079941749573} +Epoch [2941/4000] Validation [1/4] Loss: 0.31445 focal_loss 0.25426 dice_loss 0.06019 +Epoch [2941/4000] Validation [2/4] Loss: 1.32305 focal_loss 1.02164 dice_loss 0.30141 +Epoch [2941/4000] Validation [3/4] Loss: 0.48699 focal_loss 0.38541 dice_loss 0.10157 +Epoch [2941/4000] Validation [4/4] Loss: 0.29748 focal_loss 0.21579 dice_loss 0.08169 +Epoch [2941/4000] Validation metric {'Val/mean dice_metric': 0.9723153114318848, 'Val/mean miou_metric': 0.9581086039543152, 'Val/mean f1': 0.9757601022720337, 'Val/mean precision': 0.9733346104621887, 'Val/mean recall': 0.9781978130340576, 'Val/mean hd95_metric': 5.405954360961914} +Cheakpoint... +Epoch [2941/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723153114318848, 'Val/mean miou_metric': 0.9581086039543152, 'Val/mean f1': 0.9757601022720337, 'Val/mean precision': 0.9733346104621887, 'Val/mean recall': 0.9781978130340576, 'Val/mean hd95_metric': 5.405954360961914} +Epoch [2942/4000] Training [1/16] Loss: 0.00256 +Epoch [2942/4000] Training [2/16] Loss: 0.00455 +Epoch [2942/4000] Training [3/16] Loss: 0.00587 +Epoch [2942/4000] Training [4/16] Loss: 0.00365 +Epoch [2942/4000] Training [5/16] Loss: 0.00280 +Epoch [2942/4000] Training [6/16] Loss: 0.00340 +Epoch [2942/4000] Training [7/16] Loss: 0.00281 +Epoch [2942/4000] Training [8/16] Loss: 0.00441 +Epoch [2942/4000] Training [9/16] Loss: 0.00270 +Epoch [2942/4000] Training [10/16] Loss: 0.00312 +Epoch [2942/4000] Training [11/16] Loss: 0.00372 +Epoch [2942/4000] Training [12/16] Loss: 0.00390 +Epoch [2942/4000] Training [13/16] Loss: 0.00421 +Epoch [2942/4000] Training [14/16] Loss: 0.00246 +Epoch [2942/4000] Training [15/16] Loss: 0.00310 +Epoch [2942/4000] Training [16/16] Loss: 0.00245 +Epoch [2942/4000] Training metric {'Train/mean dice_metric': 0.998158872127533, 'Train/mean miou_metric': 0.9960443377494812, 'Train/mean f1': 0.9931995272636414, 'Train/mean precision': 0.9885950088500977, 'Train/mean recall': 0.9978470802307129, 'Train/mean hd95_metric': 0.8009897470474243} +Epoch [2942/4000] Validation [1/4] Loss: 0.36435 focal_loss 0.29814 dice_loss 0.06622 +Epoch [2942/4000] Validation [2/4] Loss: 0.48685 focal_loss 0.36436 dice_loss 0.12248 +Epoch [2942/4000] Validation [3/4] Loss: 0.49598 focal_loss 0.40374 dice_loss 0.09225 +Epoch [2942/4000] Validation [4/4] Loss: 0.49318 focal_loss 0.35821 dice_loss 0.13497 +Epoch [2942/4000] Validation metric {'Val/mean dice_metric': 0.9723219871520996, 'Val/mean miou_metric': 0.9575163125991821, 'Val/mean f1': 0.975505530834198, 'Val/mean precision': 0.9739046096801758, 'Val/mean recall': 0.9771116971969604, 'Val/mean hd95_metric': 5.3339056968688965} +Cheakpoint... +Epoch [2942/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723219871520996, 'Val/mean miou_metric': 0.9575163125991821, 'Val/mean f1': 0.975505530834198, 'Val/mean precision': 0.9739046096801758, 'Val/mean recall': 0.9771116971969604, 'Val/mean hd95_metric': 5.3339056968688965} +Epoch [2943/4000] Training [1/16] Loss: 0.00291 +Epoch [2943/4000] Training [2/16] Loss: 0.00359 +Epoch [2943/4000] Training [3/16] Loss: 0.00269 +Epoch [2943/4000] Training [4/16] Loss: 0.00373 +Epoch [2943/4000] Training [5/16] Loss: 0.00276 +Epoch [2943/4000] Training [6/16] Loss: 0.00364 +Epoch [2943/4000] Training [7/16] Loss: 0.00343 +Epoch [2943/4000] Training [8/16] Loss: 0.00276 +Epoch [2943/4000] Training [9/16] Loss: 0.00268 +Epoch [2943/4000] Training [10/16] Loss: 0.00301 +Epoch [2943/4000] Training [11/16] Loss: 0.00237 +Epoch [2943/4000] Training [12/16] Loss: 0.00322 +Epoch [2943/4000] Training [13/16] Loss: 0.00363 +Epoch [2943/4000] Training [14/16] Loss: 0.00317 +Epoch [2943/4000] Training [15/16] Loss: 0.00287 +Epoch [2943/4000] Training [16/16] Loss: 0.00202 +Epoch [2943/4000] Training metric {'Train/mean dice_metric': 0.9982757568359375, 'Train/mean miou_metric': 0.996279776096344, 'Train/mean f1': 0.9934617280960083, 'Train/mean precision': 0.9889931678771973, 'Train/mean recall': 0.9979708194732666, 'Train/mean hd95_metric': 0.7868441343307495} +Epoch [2943/4000] Validation [1/4] Loss: 0.35859 focal_loss 0.29535 dice_loss 0.06325 +Epoch [2943/4000] Validation [2/4] Loss: 0.47134 focal_loss 0.35602 dice_loss 0.11533 +Epoch [2943/4000] Validation [3/4] Loss: 0.49869 focal_loss 0.40283 dice_loss 0.09586 +Epoch [2943/4000] Validation [4/4] Loss: 0.31252 focal_loss 0.21877 dice_loss 0.09374 +Epoch [2943/4000] Validation metric {'Val/mean dice_metric': 0.9746354818344116, 'Val/mean miou_metric': 0.9602135419845581, 'Val/mean f1': 0.9765301942825317, 'Val/mean precision': 0.9739360213279724, 'Val/mean recall': 0.979138195514679, 'Val/mean hd95_metric': 5.464544296264648} +Cheakpoint... +Epoch [2943/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746354818344116, 'Val/mean miou_metric': 0.9602135419845581, 'Val/mean f1': 0.9765301942825317, 'Val/mean precision': 0.9739360213279724, 'Val/mean recall': 0.979138195514679, 'Val/mean hd95_metric': 5.464544296264648} +Epoch [2944/4000] Training [1/16] Loss: 0.00270 +Epoch [2944/4000] Training [2/16] Loss: 0.00425 +Epoch [2944/4000] Training [3/16] Loss: 0.00353 +Epoch [2944/4000] Training [4/16] Loss: 0.00358 +Epoch [2944/4000] Training [5/16] Loss: 0.00412 +Epoch [2944/4000] Training [6/16] Loss: 0.00343 +Epoch [2944/4000] Training [7/16] Loss: 0.00389 +Epoch [2944/4000] Training [8/16] Loss: 0.00244 +Epoch [2944/4000] Training [9/16] Loss: 0.00302 +Epoch [2944/4000] Training [10/16] Loss: 0.00263 +Epoch [2944/4000] Training [11/16] Loss: 0.00369 +Epoch [2944/4000] Training [12/16] Loss: 0.00267 +Epoch [2944/4000] Training [13/16] Loss: 0.00364 +Epoch [2944/4000] Training [14/16] Loss: 0.00376 +Epoch [2944/4000] Training [15/16] Loss: 0.00413 +Epoch [2944/4000] Training [16/16] Loss: 0.00625 +Epoch [2944/4000] Training metric {'Train/mean dice_metric': 0.9979566335678101, 'Train/mean miou_metric': 0.995632529258728, 'Train/mean f1': 0.9930083751678467, 'Train/mean precision': 0.9882926940917969, 'Train/mean recall': 0.9977692365646362, 'Train/mean hd95_metric': 0.8172706365585327} +Epoch [2944/4000] Validation [1/4] Loss: 0.37159 focal_loss 0.30919 dice_loss 0.06240 +Epoch [2944/4000] Validation [2/4] Loss: 0.91837 focal_loss 0.69486 dice_loss 0.22351 +Epoch [2944/4000] Validation [3/4] Loss: 0.49849 focal_loss 0.40801 dice_loss 0.09048 +Epoch [2944/4000] Validation [4/4] Loss: 0.43330 focal_loss 0.31768 dice_loss 0.11561 +Epoch [2944/4000] Validation metric {'Val/mean dice_metric': 0.9739965200424194, 'Val/mean miou_metric': 0.9591422080993652, 'Val/mean f1': 0.9759595394134521, 'Val/mean precision': 0.972724199295044, 'Val/mean recall': 0.9792165756225586, 'Val/mean hd95_metric': 4.814053058624268} +Cheakpoint... +Epoch [2944/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739965200424194, 'Val/mean miou_metric': 0.9591422080993652, 'Val/mean f1': 0.9759595394134521, 'Val/mean precision': 0.972724199295044, 'Val/mean recall': 0.9792165756225586, 'Val/mean hd95_metric': 4.814053058624268} +Epoch [2945/4000] Training [1/16] Loss: 0.00444 +Epoch [2945/4000] Training [2/16] Loss: 0.00264 +Epoch [2945/4000] Training [3/16] Loss: 0.00300 +Epoch [2945/4000] Training [4/16] Loss: 0.00396 +Epoch [2945/4000] Training [5/16] Loss: 0.00255 +Epoch [2945/4000] Training [6/16] Loss: 0.00280 +Epoch [2945/4000] Training [7/16] Loss: 0.00235 +Epoch [2945/4000] Training [8/16] Loss: 0.00377 +Epoch [2945/4000] Training [9/16] Loss: 0.00356 +Epoch [2945/4000] Training [10/16] Loss: 0.00407 +Epoch [2945/4000] Training [11/16] Loss: 0.00321 +Epoch [2945/4000] Training [12/16] Loss: 0.00377 +Epoch [2945/4000] Training [13/16] Loss: 0.00350 +Epoch [2945/4000] Training [14/16] Loss: 0.00294 +Epoch [2945/4000] Training [15/16] Loss: 0.00240 +Epoch [2945/4000] Training [16/16] Loss: 0.00288 +Epoch [2945/4000] Training metric {'Train/mean dice_metric': 0.9981337785720825, 'Train/mean miou_metric': 0.9959982633590698, 'Train/mean f1': 0.9933416247367859, 'Train/mean precision': 0.9887856841087341, 'Train/mean recall': 0.9979397058486938, 'Train/mean hd95_metric': 0.8000274896621704} +Epoch [2945/4000] Validation [1/4] Loss: 0.38395 focal_loss 0.31925 dice_loss 0.06470 +Epoch [2945/4000] Validation [2/4] Loss: 0.45715 focal_loss 0.34178 dice_loss 0.11537 +Epoch [2945/4000] Validation [3/4] Loss: 0.49111 focal_loss 0.39446 dice_loss 0.09665 +Epoch [2945/4000] Validation [4/4] Loss: 0.33785 focal_loss 0.24679 dice_loss 0.09107 +Epoch [2945/4000] Validation metric {'Val/mean dice_metric': 0.9752710461616516, 'Val/mean miou_metric': 0.9606853723526001, 'Val/mean f1': 0.9762277603149414, 'Val/mean precision': 0.9739705920219421, 'Val/mean recall': 0.9784955382347107, 'Val/mean hd95_metric': 5.068765640258789} +Cheakpoint... +Epoch [2945/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752710461616516, 'Val/mean miou_metric': 0.9606853723526001, 'Val/mean f1': 0.9762277603149414, 'Val/mean precision': 0.9739705920219421, 'Val/mean recall': 0.9784955382347107, 'Val/mean hd95_metric': 5.068765640258789} +Epoch [2946/4000] Training [1/16] Loss: 0.00326 +Epoch [2946/4000] Training [2/16] Loss: 0.00256 +Epoch [2946/4000] Training [3/16] Loss: 0.00303 +Epoch [2946/4000] Training [4/16] Loss: 0.00369 +Epoch [2946/4000] Training [5/16] Loss: 0.00345 +Epoch [2946/4000] Training [6/16] Loss: 0.00244 +Epoch [2946/4000] Training [7/16] Loss: 0.00274 +Epoch [2946/4000] Training [8/16] Loss: 0.00435 +Epoch [2946/4000] Training [9/16] Loss: 0.00461 +Epoch [2946/4000] Training [10/16] Loss: 0.00299 +Epoch [2946/4000] Training [11/16] Loss: 0.00255 +Epoch [2946/4000] Training [12/16] Loss: 0.00558 +Epoch [2946/4000] Training [13/16] Loss: 0.00267 +Epoch [2946/4000] Training [14/16] Loss: 0.00341 +Epoch [2946/4000] Training [15/16] Loss: 0.00337 +Epoch [2946/4000] Training [16/16] Loss: 0.00438 +Epoch [2946/4000] Training metric {'Train/mean dice_metric': 0.998045802116394, 'Train/mean miou_metric': 0.9958118200302124, 'Train/mean f1': 0.9931490421295166, 'Train/mean precision': 0.9885257482528687, 'Train/mean recall': 0.997815728187561, 'Train/mean hd95_metric': 0.7681217193603516} +Epoch [2946/4000] Validation [1/4] Loss: 0.38014 focal_loss 0.31534 dice_loss 0.06480 +Epoch [2946/4000] Validation [2/4] Loss: 1.26623 focal_loss 0.96786 dice_loss 0.29836 +Epoch [2946/4000] Validation [3/4] Loss: 0.24798 focal_loss 0.18402 dice_loss 0.06396 +Epoch [2946/4000] Validation [4/4] Loss: 0.37583 focal_loss 0.27089 dice_loss 0.10494 +Epoch [2946/4000] Validation metric {'Val/mean dice_metric': 0.9725022315979004, 'Val/mean miou_metric': 0.9585628509521484, 'Val/mean f1': 0.9757238626480103, 'Val/mean precision': 0.973624587059021, 'Val/mean recall': 0.9778323769569397, 'Val/mean hd95_metric': 5.021249294281006} +Cheakpoint... +Epoch [2946/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725022315979004, 'Val/mean miou_metric': 0.9585628509521484, 'Val/mean f1': 0.9757238626480103, 'Val/mean precision': 0.973624587059021, 'Val/mean recall': 0.9778323769569397, 'Val/mean hd95_metric': 5.021249294281006} +Epoch [2947/4000] Training [1/16] Loss: 0.00345 +Epoch [2947/4000] Training [2/16] Loss: 0.00337 +Epoch [2947/4000] Training [3/16] Loss: 0.00277 +Epoch [2947/4000] Training [4/16] Loss: 0.00245 +Epoch [2947/4000] Training [5/16] Loss: 0.00421 +Epoch [2947/4000] Training [6/16] Loss: 0.00290 +Epoch [2947/4000] Training [7/16] Loss: 0.00369 +Epoch [2947/4000] Training [8/16] Loss: 0.00335 +Epoch [2947/4000] Training [9/16] Loss: 0.00452 +Epoch [2947/4000] Training [10/16] Loss: 0.00270 +Epoch [2947/4000] Training [11/16] Loss: 0.00414 +Epoch [2947/4000] Training [12/16] Loss: 0.00240 +Epoch [2947/4000] Training [13/16] Loss: 0.00281 +Epoch [2947/4000] Training [14/16] Loss: 0.00328 +Epoch [2947/4000] Training [15/16] Loss: 0.00460 +Epoch [2947/4000] Training [16/16] Loss: 0.00211 +Epoch [2947/4000] Training metric {'Train/mean dice_metric': 0.9981547594070435, 'Train/mean miou_metric': 0.9960411787033081, 'Train/mean f1': 0.9932664632797241, 'Train/mean precision': 0.9886747598648071, 'Train/mean recall': 0.9979010224342346, 'Train/mean hd95_metric': 0.7985904812812805} +Epoch [2947/4000] Validation [1/4] Loss: 0.37517 focal_loss 0.31107 dice_loss 0.06410 +Epoch [2947/4000] Validation [2/4] Loss: 0.79730 focal_loss 0.60931 dice_loss 0.18799 +Epoch [2947/4000] Validation [3/4] Loss: 0.44599 focal_loss 0.35089 dice_loss 0.09510 +Epoch [2947/4000] Validation [4/4] Loss: 0.39472 focal_loss 0.28939 dice_loss 0.10532 +Epoch [2947/4000] Validation metric {'Val/mean dice_metric': 0.9730979800224304, 'Val/mean miou_metric': 0.9588989019393921, 'Val/mean f1': 0.9754809737205505, 'Val/mean precision': 0.9730995297431946, 'Val/mean recall': 0.9778741598129272, 'Val/mean hd95_metric': 5.025360584259033} +Cheakpoint... +Epoch [2947/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730979800224304, 'Val/mean miou_metric': 0.9588989019393921, 'Val/mean f1': 0.9754809737205505, 'Val/mean precision': 0.9730995297431946, 'Val/mean recall': 0.9778741598129272, 'Val/mean hd95_metric': 5.025360584259033} +Epoch [2948/4000] Training [1/16] Loss: 0.00203 +Epoch [2948/4000] Training [2/16] Loss: 0.00356 +Epoch [2948/4000] Training [3/16] Loss: 0.00295 +Epoch [2948/4000] Training [4/16] Loss: 0.00351 +Epoch [2948/4000] Training [5/16] Loss: 0.00301 +Epoch [2948/4000] Training [6/16] Loss: 0.00303 +Epoch [2948/4000] Training [7/16] Loss: 0.00371 +Epoch [2948/4000] Training [8/16] Loss: 0.00309 +Epoch [2948/4000] Training [9/16] Loss: 0.00296 +Epoch [2948/4000] Training [10/16] Loss: 0.00547 +Epoch [2948/4000] Training [11/16] Loss: 0.00271 +Epoch [2948/4000] Training [12/16] Loss: 0.00448 +Epoch [2948/4000] Training [13/16] Loss: 0.00457 +Epoch [2948/4000] Training [14/16] Loss: 0.00219 +Epoch [2948/4000] Training [15/16] Loss: 0.00368 +Epoch [2948/4000] Training [16/16] Loss: 0.00366 +Epoch [2948/4000] Training metric {'Train/mean dice_metric': 0.9981496930122375, 'Train/mean miou_metric': 0.9960324764251709, 'Train/mean f1': 0.9933686852455139, 'Train/mean precision': 0.9889367818832397, 'Train/mean recall': 0.9978405237197876, 'Train/mean hd95_metric': 0.7926333546638489} +Epoch [2948/4000] Validation [1/4] Loss: 0.40023 focal_loss 0.33545 dice_loss 0.06478 +Epoch [2948/4000] Validation [2/4] Loss: 0.47540 focal_loss 0.35445 dice_loss 0.12094 +Epoch [2948/4000] Validation [3/4] Loss: 0.48628 focal_loss 0.39831 dice_loss 0.08797 +Epoch [2948/4000] Validation [4/4] Loss: 0.36991 focal_loss 0.25835 dice_loss 0.11157 +Epoch [2948/4000] Validation metric {'Val/mean dice_metric': 0.9744903445243835, 'Val/mean miou_metric': 0.9598852396011353, 'Val/mean f1': 0.9765577912330627, 'Val/mean precision': 0.9735215306282043, 'Val/mean recall': 0.979613184928894, 'Val/mean hd95_metric': 4.976237773895264} +Cheakpoint... +Epoch [2948/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744903445243835, 'Val/mean miou_metric': 0.9598852396011353, 'Val/mean f1': 0.9765577912330627, 'Val/mean precision': 0.9735215306282043, 'Val/mean recall': 0.979613184928894, 'Val/mean hd95_metric': 4.976237773895264} +Epoch [2949/4000] Training [1/16] Loss: 0.00448 +Epoch [2949/4000] Training [2/16] Loss: 0.00391 +Epoch [2949/4000] Training [3/16] Loss: 0.00309 +Epoch [2949/4000] Training [4/16] Loss: 0.00510 +Epoch [2949/4000] Training [5/16] Loss: 0.00387 +Epoch [2949/4000] Training [6/16] Loss: 0.00246 +Epoch [2949/4000] Training [7/16] Loss: 0.00247 +Epoch [2949/4000] Training [8/16] Loss: 0.00356 +Epoch [2949/4000] Training [9/16] Loss: 0.00392 +Epoch [2949/4000] Training [10/16] Loss: 0.00244 +Epoch [2949/4000] Training [11/16] Loss: 0.00409 +Epoch [2949/4000] Training [12/16] Loss: 0.00367 +Epoch [2949/4000] Training [13/16] Loss: 0.00454 +Epoch [2949/4000] Training [14/16] Loss: 0.00358 +Epoch [2949/4000] Training [15/16] Loss: 0.00287 +Epoch [2949/4000] Training [16/16] Loss: 0.00340 +Epoch [2949/4000] Training metric {'Train/mean dice_metric': 0.9980112314224243, 'Train/mean miou_metric': 0.9957478642463684, 'Train/mean f1': 0.9931609034538269, 'Train/mean precision': 0.9884798526763916, 'Train/mean recall': 0.9978864192962646, 'Train/mean hd95_metric': 0.8025718331336975} +Epoch [2949/4000] Validation [1/4] Loss: 0.38464 focal_loss 0.32020 dice_loss 0.06444 +Epoch [2949/4000] Validation [2/4] Loss: 0.76727 focal_loss 0.59553 dice_loss 0.17173 +Epoch [2949/4000] Validation [3/4] Loss: 0.49154 focal_loss 0.39678 dice_loss 0.09476 +Epoch [2949/4000] Validation [4/4] Loss: 0.36293 focal_loss 0.25413 dice_loss 0.10880 +Epoch [2949/4000] Validation metric {'Val/mean dice_metric': 0.9726960062980652, 'Val/mean miou_metric': 0.9580842852592468, 'Val/mean f1': 0.9753095507621765, 'Val/mean precision': 0.9728870391845703, 'Val/mean recall': 0.9777441620826721, 'Val/mean hd95_metric': 5.755664825439453} +Cheakpoint... +Epoch [2949/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726960062980652, 'Val/mean miou_metric': 0.9580842852592468, 'Val/mean f1': 0.9753095507621765, 'Val/mean precision': 0.9728870391845703, 'Val/mean recall': 0.9777441620826721, 'Val/mean hd95_metric': 5.755664825439453} +Epoch [2950/4000] Training [1/16] Loss: 0.00286 +Epoch [2950/4000] Training [2/16] Loss: 0.00445 +Epoch [2950/4000] Training [3/16] Loss: 0.00339 +Epoch [2950/4000] Training [4/16] Loss: 0.00299 +Epoch [2950/4000] Training [5/16] Loss: 0.00314 +Epoch [2950/4000] Training [6/16] Loss: 0.00259 +Epoch [2950/4000] Training [7/16] Loss: 0.00420 +Epoch [2950/4000] Training [8/16] Loss: 0.00359 +Epoch [2950/4000] Training [9/16] Loss: 0.00218 +Epoch [2950/4000] Training [10/16] Loss: 0.00292 +Epoch [2950/4000] Training [11/16] Loss: 0.00347 +Epoch [2950/4000] Training [12/16] Loss: 0.00337 +Epoch [2950/4000] Training [13/16] Loss: 0.00314 +Epoch [2950/4000] Training [14/16] Loss: 0.00258 +Epoch [2950/4000] Training [15/16] Loss: 0.00413 +Epoch [2950/4000] Training [16/16] Loss: 0.00260 +Epoch [2950/4000] Training metric {'Train/mean dice_metric': 0.9981242418289185, 'Train/mean miou_metric': 0.9959831237792969, 'Train/mean f1': 0.9933539032936096, 'Train/mean precision': 0.9888511896133423, 'Train/mean recall': 0.9978978037834167, 'Train/mean hd95_metric': 0.7883366346359253} +Epoch [2950/4000] Validation [1/4] Loss: 0.37055 focal_loss 0.30589 dice_loss 0.06466 +Epoch [2950/4000] Validation [2/4] Loss: 0.46585 focal_loss 0.35255 dice_loss 0.11330 +Epoch [2950/4000] Validation [3/4] Loss: 0.45529 focal_loss 0.36967 dice_loss 0.08562 +Epoch [2950/4000] Validation [4/4] Loss: 0.47323 focal_loss 0.34642 dice_loss 0.12681 +Epoch [2950/4000] Validation metric {'Val/mean dice_metric': 0.9748243093490601, 'Val/mean miou_metric': 0.9600366353988647, 'Val/mean f1': 0.9763166904449463, 'Val/mean precision': 0.9739421010017395, 'Val/mean recall': 0.978702962398529, 'Val/mean hd95_metric': 5.016559600830078} +Cheakpoint... +Epoch [2950/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748243093490601, 'Val/mean miou_metric': 0.9600366353988647, 'Val/mean f1': 0.9763166904449463, 'Val/mean precision': 0.9739421010017395, 'Val/mean recall': 0.978702962398529, 'Val/mean hd95_metric': 5.016559600830078} +Epoch [2951/4000] Training [1/16] Loss: 0.00361 +Epoch [2951/4000] Training [2/16] Loss: 0.00308 +Epoch [2951/4000] Training [3/16] Loss: 0.00253 +Epoch [2951/4000] Training [4/16] Loss: 0.00449 +Epoch [2951/4000] Training [5/16] Loss: 0.00532 +Epoch [2951/4000] Training [6/16] Loss: 0.00246 +Epoch [2951/4000] Training [7/16] Loss: 0.00368 +Epoch [2951/4000] Training [8/16] Loss: 0.00376 +Epoch [2951/4000] Training [9/16] Loss: 0.00352 +Epoch [2951/4000] Training [10/16] Loss: 0.00287 +Epoch [2951/4000] Training [11/16] Loss: 0.00388 +Epoch [2951/4000] Training [12/16] Loss: 0.00527 +Epoch [2951/4000] Training [13/16] Loss: 0.00426 +Epoch [2951/4000] Training [14/16] Loss: 0.00371 +Epoch [2951/4000] Training [15/16] Loss: 0.00310 +Epoch [2951/4000] Training [16/16] Loss: 0.00350 +Epoch [2951/4000] Training metric {'Train/mean dice_metric': 0.9978904724121094, 'Train/mean miou_metric': 0.9955011010169983, 'Train/mean f1': 0.9929651021957397, 'Train/mean precision': 0.9883438944816589, 'Train/mean recall': 0.9976298213005066, 'Train/mean hd95_metric': 0.8398569822311401} +Epoch [2951/4000] Validation [1/4] Loss: 0.35323 focal_loss 0.29193 dice_loss 0.06130 +Epoch [2951/4000] Validation [2/4] Loss: 0.47101 focal_loss 0.35498 dice_loss 0.11603 +Epoch [2951/4000] Validation [3/4] Loss: 0.48534 focal_loss 0.39741 dice_loss 0.08793 +Epoch [2951/4000] Validation [4/4] Loss: 0.31844 focal_loss 0.23406 dice_loss 0.08438 +Epoch [2951/4000] Validation metric {'Val/mean dice_metric': 0.9758428335189819, 'Val/mean miou_metric': 0.9607057571411133, 'Val/mean f1': 0.9762013554573059, 'Val/mean precision': 0.974163293838501, 'Val/mean recall': 0.9782480001449585, 'Val/mean hd95_metric': 5.002361297607422} +Cheakpoint... +Epoch [2951/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758428335189819, 'Val/mean miou_metric': 0.9607057571411133, 'Val/mean f1': 0.9762013554573059, 'Val/mean precision': 0.974163293838501, 'Val/mean recall': 0.9782480001449585, 'Val/mean hd95_metric': 5.002361297607422} +Epoch [2952/4000] Training [1/16] Loss: 0.00346 +Epoch [2952/4000] Training [2/16] Loss: 0.00360 +Epoch [2952/4000] Training [3/16] Loss: 0.00397 +Epoch [2952/4000] Training [4/16] Loss: 0.00333 +Epoch [2952/4000] Training [5/16] Loss: 0.00311 +Epoch [2952/4000] Training [6/16] Loss: 0.00277 +Epoch [2952/4000] Training [7/16] Loss: 0.00246 +Epoch [2952/4000] Training [8/16] Loss: 0.00376 +Epoch [2952/4000] Training [9/16] Loss: 0.00306 +Epoch [2952/4000] Training [10/16] Loss: 0.00278 +Epoch [2952/4000] Training [11/16] Loss: 0.00264 +Epoch [2952/4000] Training [12/16] Loss: 0.00374 +Epoch [2952/4000] Training [13/16] Loss: 0.00415 +Epoch [2952/4000] Training [14/16] Loss: 0.00226 +Epoch [2952/4000] Training [15/16] Loss: 0.00310 +Epoch [2952/4000] Training [16/16] Loss: 0.00258 +Epoch [2952/4000] Training metric {'Train/mean dice_metric': 0.998139500617981, 'Train/mean miou_metric': 0.9960128664970398, 'Train/mean f1': 0.9933744668960571, 'Train/mean precision': 0.9887980818748474, 'Train/mean recall': 0.997993528842926, 'Train/mean hd95_metric': 0.785601019859314} +Epoch [2952/4000] Validation [1/4] Loss: 0.33809 focal_loss 0.27637 dice_loss 0.06172 +Epoch [2952/4000] Validation [2/4] Loss: 0.86946 focal_loss 0.66903 dice_loss 0.20043 +Epoch [2952/4000] Validation [3/4] Loss: 0.23612 focal_loss 0.17420 dice_loss 0.06192 +Epoch [2952/4000] Validation [4/4] Loss: 0.36198 focal_loss 0.25728 dice_loss 0.10469 +Epoch [2952/4000] Validation metric {'Val/mean dice_metric': 0.9722563028335571, 'Val/mean miou_metric': 0.9581567645072937, 'Val/mean f1': 0.9761192798614502, 'Val/mean precision': 0.9747620224952698, 'Val/mean recall': 0.9774803519248962, 'Val/mean hd95_metric': 5.449954032897949} +Cheakpoint... +Epoch [2952/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722563028335571, 'Val/mean miou_metric': 0.9581567645072937, 'Val/mean f1': 0.9761192798614502, 'Val/mean precision': 0.9747620224952698, 'Val/mean recall': 0.9774803519248962, 'Val/mean hd95_metric': 5.449954032897949} +Epoch [2953/4000] Training [1/16] Loss: 0.00446 +Epoch [2953/4000] Training [2/16] Loss: 0.00289 +Epoch [2953/4000] Training [3/16] Loss: 0.00413 +Epoch [2953/4000] Training [4/16] Loss: 0.00313 +Epoch [2953/4000] Training [5/16] Loss: 0.00356 +Epoch [2953/4000] Training [6/16] Loss: 0.00343 +Epoch [2953/4000] Training [7/16] Loss: 0.00514 +Epoch [2953/4000] Training [8/16] Loss: 0.00378 +Epoch [2953/4000] Training [9/16] Loss: 0.00399 +Epoch [2953/4000] Training [10/16] Loss: 0.00309 +Epoch [2953/4000] Training [11/16] Loss: 0.00235 +Epoch [2953/4000] Training [12/16] Loss: 0.00272 +Epoch [2953/4000] Training [13/16] Loss: 0.00276 +Epoch [2953/4000] Training [14/16] Loss: 0.00404 +Epoch [2953/4000] Training [15/16] Loss: 0.00372 +Epoch [2953/4000] Training [16/16] Loss: 0.00337 +Epoch [2953/4000] Training metric {'Train/mean dice_metric': 0.9979238510131836, 'Train/mean miou_metric': 0.9955832958221436, 'Train/mean f1': 0.9931389093399048, 'Train/mean precision': 0.9885784387588501, 'Train/mean recall': 0.99774169921875, 'Train/mean hd95_metric': 0.8383643627166748} +Epoch [2953/4000] Validation [1/4] Loss: 0.39915 focal_loss 0.33656 dice_loss 0.06259 +Epoch [2953/4000] Validation [2/4] Loss: 0.94175 focal_loss 0.74927 dice_loss 0.19248 +Epoch [2953/4000] Validation [3/4] Loss: 0.48107 focal_loss 0.39312 dice_loss 0.08795 +Epoch [2953/4000] Validation [4/4] Loss: 0.32220 focal_loss 0.23855 dice_loss 0.08365 +Epoch [2953/4000] Validation metric {'Val/mean dice_metric': 0.9730124473571777, 'Val/mean miou_metric': 0.9587224721908569, 'Val/mean f1': 0.9755637645721436, 'Val/mean precision': 0.974029004573822, 'Val/mean recall': 0.9771034121513367, 'Val/mean hd95_metric': 5.072563171386719} +Cheakpoint... +Epoch [2953/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730124473571777, 'Val/mean miou_metric': 0.9587224721908569, 'Val/mean f1': 0.9755637645721436, 'Val/mean precision': 0.974029004573822, 'Val/mean recall': 0.9771034121513367, 'Val/mean hd95_metric': 5.072563171386719} +Epoch [2954/4000] Training [1/16] Loss: 0.00315 +Epoch [2954/4000] Training [2/16] Loss: 0.00395 +Epoch [2954/4000] Training [3/16] Loss: 0.00356 +Epoch [2954/4000] Training [4/16] Loss: 0.00403 +Epoch [2954/4000] Training [5/16] Loss: 0.00452 +Epoch [2954/4000] Training [6/16] Loss: 0.00282 +Epoch [2954/4000] Training [7/16] Loss: 0.00226 +Epoch [2954/4000] Training [8/16] Loss: 0.00266 +Epoch [2954/4000] Training [9/16] Loss: 0.00278 +Epoch [2954/4000] Training [10/16] Loss: 0.00381 +Epoch [2954/4000] Training [11/16] Loss: 0.00377 +Epoch [2954/4000] Training [12/16] Loss: 0.00423 +Epoch [2954/4000] Training [13/16] Loss: 0.00428 +Epoch [2954/4000] Training [14/16] Loss: 0.00484 +Epoch [2954/4000] Training [15/16] Loss: 0.00428 +Epoch [2954/4000] Training [16/16] Loss: 0.00431 +Epoch [2954/4000] Training metric {'Train/mean dice_metric': 0.9978941082954407, 'Train/mean miou_metric': 0.9955188632011414, 'Train/mean f1': 0.9930166602134705, 'Train/mean precision': 0.9884236454963684, 'Train/mean recall': 0.9976525902748108, 'Train/mean hd95_metric': 0.855008065700531} +Epoch [2954/4000] Validation [1/4] Loss: 0.38815 focal_loss 0.32428 dice_loss 0.06388 +Epoch [2954/4000] Validation [2/4] Loss: 0.49937 focal_loss 0.37596 dice_loss 0.12341 +Epoch [2954/4000] Validation [3/4] Loss: 0.49778 focal_loss 0.40605 dice_loss 0.09172 +Epoch [2954/4000] Validation [4/4] Loss: 0.36991 focal_loss 0.26635 dice_loss 0.10356 +Epoch [2954/4000] Validation metric {'Val/mean dice_metric': 0.9734713435173035, 'Val/mean miou_metric': 0.9586665034294128, 'Val/mean f1': 0.9751100540161133, 'Val/mean precision': 0.9726431369781494, 'Val/mean recall': 0.9775895476341248, 'Val/mean hd95_metric': 5.322856903076172} +Cheakpoint... +Epoch [2954/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734713435173035, 'Val/mean miou_metric': 0.9586665034294128, 'Val/mean f1': 0.9751100540161133, 'Val/mean precision': 0.9726431369781494, 'Val/mean recall': 0.9775895476341248, 'Val/mean hd95_metric': 5.322856903076172} +Epoch [2955/4000] Training [1/16] Loss: 0.00320 +Epoch [2955/4000] Training [2/16] Loss: 0.00322 +Epoch [2955/4000] Training [3/16] Loss: 0.00332 +Epoch [2955/4000] Training [4/16] Loss: 0.00272 +Epoch [2955/4000] Training [5/16] Loss: 0.00339 +Epoch [2955/4000] Training [6/16] Loss: 0.00326 +Epoch [2955/4000] Training [7/16] Loss: 0.00446 +Epoch [2955/4000] Training [8/16] Loss: 0.00303 +Epoch [2955/4000] Training [9/16] Loss: 0.00370 +Epoch [2955/4000] Training [10/16] Loss: 0.00507 +Epoch [2955/4000] Training [11/16] Loss: 0.00461 +Epoch [2955/4000] Training [12/16] Loss: 0.00265 +Epoch [2955/4000] Training [13/16] Loss: 0.00306 +Epoch [2955/4000] Training [14/16] Loss: 0.00418 +Epoch [2955/4000] Training [15/16] Loss: 0.00282 +Epoch [2955/4000] Training [16/16] Loss: 0.00304 +Epoch [2955/4000] Training metric {'Train/mean dice_metric': 0.9979972839355469, 'Train/mean miou_metric': 0.9957307577133179, 'Train/mean f1': 0.9932509660720825, 'Train/mean precision': 0.9887387156486511, 'Train/mean recall': 0.9978045225143433, 'Train/mean hd95_metric': 0.8131967782974243} +Epoch [2955/4000] Validation [1/4] Loss: 0.33451 focal_loss 0.27128 dice_loss 0.06324 +Epoch [2955/4000] Validation [2/4] Loss: 0.46825 focal_loss 0.35375 dice_loss 0.11449 +Epoch [2955/4000] Validation [3/4] Loss: 0.50100 focal_loss 0.40637 dice_loss 0.09463 +Epoch [2955/4000] Validation [4/4] Loss: 0.27410 focal_loss 0.19588 dice_loss 0.07822 +Epoch [2955/4000] Validation metric {'Val/mean dice_metric': 0.9758492708206177, 'Val/mean miou_metric': 0.9614583849906921, 'Val/mean f1': 0.976503312587738, 'Val/mean precision': 0.9730371832847595, 'Val/mean recall': 0.9799941778182983, 'Val/mean hd95_metric': 5.254828453063965} +Cheakpoint... +Epoch [2955/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758492708206177, 'Val/mean miou_metric': 0.9614583849906921, 'Val/mean f1': 0.976503312587738, 'Val/mean precision': 0.9730371832847595, 'Val/mean recall': 0.9799941778182983, 'Val/mean hd95_metric': 5.254828453063965} +Epoch [2956/4000] Training [1/16] Loss: 0.00494 +Epoch [2956/4000] Training [2/16] Loss: 0.00345 +Epoch [2956/4000] Training [3/16] Loss: 0.00258 +Epoch [2956/4000] Training [4/16] Loss: 0.00245 +Epoch [2956/4000] Training [5/16] Loss: 0.00326 +Epoch [2956/4000] Training [6/16] Loss: 0.00471 +Epoch [2956/4000] Training [7/16] Loss: 0.00310 +Epoch [2956/4000] Training [8/16] Loss: 0.00271 +Epoch [2956/4000] Training [9/16] Loss: 0.00441 +Epoch [2956/4000] Training [10/16] Loss: 0.00387 +Epoch [2956/4000] Training [11/16] Loss: 0.00275 +Epoch [2956/4000] Training [12/16] Loss: 0.00396 +Epoch [2956/4000] Training [13/16] Loss: 0.00306 +Epoch [2956/4000] Training [14/16] Loss: 0.00324 +Epoch [2956/4000] Training [15/16] Loss: 0.00517 +Epoch [2956/4000] Training [16/16] Loss: 0.00384 +Epoch [2956/4000] Training metric {'Train/mean dice_metric': 0.9980039596557617, 'Train/mean miou_metric': 0.9957362413406372, 'Train/mean f1': 0.9931184649467468, 'Train/mean precision': 0.9884994029998779, 'Train/mean recall': 0.9977807998657227, 'Train/mean hd95_metric': 0.8277896642684937} +Epoch [2956/4000] Validation [1/4] Loss: 0.32734 focal_loss 0.26449 dice_loss 0.06284 +Epoch [2956/4000] Validation [2/4] Loss: 0.46969 focal_loss 0.35144 dice_loss 0.11826 +Epoch [2956/4000] Validation [3/4] Loss: 0.48572 focal_loss 0.38622 dice_loss 0.09950 +Epoch [2956/4000] Validation [4/4] Loss: 0.33711 focal_loss 0.24165 dice_loss 0.09545 +Epoch [2956/4000] Validation metric {'Val/mean dice_metric': 0.9749462008476257, 'Val/mean miou_metric': 0.95989590883255, 'Val/mean f1': 0.9758404493331909, 'Val/mean precision': 0.9733123779296875, 'Val/mean recall': 0.9783816933631897, 'Val/mean hd95_metric': 5.007258415222168} +Cheakpoint... +Epoch [2956/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749462008476257, 'Val/mean miou_metric': 0.95989590883255, 'Val/mean f1': 0.9758404493331909, 'Val/mean precision': 0.9733123779296875, 'Val/mean recall': 0.9783816933631897, 'Val/mean hd95_metric': 5.007258415222168} +Epoch [2957/4000] Training [1/16] Loss: 0.00291 +Epoch [2957/4000] Training [2/16] Loss: 0.00230 +Epoch [2957/4000] Training [3/16] Loss: 0.00335 +Epoch [2957/4000] Training [4/16] Loss: 0.00259 +Epoch [2957/4000] Training [5/16] Loss: 0.00361 +Epoch [2957/4000] Training [6/16] Loss: 0.00504 +Epoch [2957/4000] Training [7/16] Loss: 0.00411 +Epoch [2957/4000] Training [8/16] Loss: 0.00259 +Epoch [2957/4000] Training [9/16] Loss: 0.00220 +Epoch [2957/4000] Training [10/16] Loss: 0.00342 +Epoch [2957/4000] Training [11/16] Loss: 0.00392 +Epoch [2957/4000] Training [12/16] Loss: 0.00400 +Epoch [2957/4000] Training [13/16] Loss: 0.00244 +Epoch [2957/4000] Training [14/16] Loss: 0.00381 +Epoch [2957/4000] Training [15/16] Loss: 0.00292 +Epoch [2957/4000] Training [16/16] Loss: 0.00342 +Epoch [2957/4000] Training metric {'Train/mean dice_metric': 0.9980796575546265, 'Train/mean miou_metric': 0.9958799481391907, 'Train/mean f1': 0.9931014776229858, 'Train/mean precision': 0.9883965253829956, 'Train/mean recall': 0.9978514909744263, 'Train/mean hd95_metric': 0.7889646291732788} +Epoch [2957/4000] Validation [1/4] Loss: 0.37118 focal_loss 0.30447 dice_loss 0.06672 +Epoch [2957/4000] Validation [2/4] Loss: 0.90928 focal_loss 0.72015 dice_loss 0.18913 +Epoch [2957/4000] Validation [3/4] Loss: 0.50472 focal_loss 0.41146 dice_loss 0.09326 +Epoch [2957/4000] Validation [4/4] Loss: 0.25684 focal_loss 0.17411 dice_loss 0.08273 +Epoch [2957/4000] Validation metric {'Val/mean dice_metric': 0.97247314453125, 'Val/mean miou_metric': 0.9586095809936523, 'Val/mean f1': 0.9754802584648132, 'Val/mean precision': 0.9738224744796753, 'Val/mean recall': 0.9771437644958496, 'Val/mean hd95_metric': 5.11873197555542} +Cheakpoint... +Epoch [2957/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97247314453125, 'Val/mean miou_metric': 0.9586095809936523, 'Val/mean f1': 0.9754802584648132, 'Val/mean precision': 0.9738224744796753, 'Val/mean recall': 0.9771437644958496, 'Val/mean hd95_metric': 5.11873197555542} +Epoch [2958/4000] Training [1/16] Loss: 0.00398 +Epoch [2958/4000] Training [2/16] Loss: 0.00283 +Epoch [2958/4000] Training [3/16] Loss: 0.00322 +Epoch [2958/4000] Training [4/16] Loss: 0.00394 +Epoch [2958/4000] Training [5/16] Loss: 0.00357 +Epoch [2958/4000] Training [6/16] Loss: 0.00386 +Epoch [2958/4000] Training [7/16] Loss: 0.00346 +Epoch [2958/4000] Training [8/16] Loss: 0.00196 +Epoch [2958/4000] Training [9/16] Loss: 0.00277 +Epoch [2958/4000] Training [10/16] Loss: 0.00328 +Epoch [2958/4000] Training [11/16] Loss: 0.00459 +Epoch [2958/4000] Training [12/16] Loss: 0.00410 +Epoch [2958/4000] Training [13/16] Loss: 0.00348 +Epoch [2958/4000] Training [14/16] Loss: 0.00242 +Epoch [2958/4000] Training [15/16] Loss: 0.00448 +Epoch [2958/4000] Training [16/16] Loss: 0.00264 +Epoch [2958/4000] Training metric {'Train/mean dice_metric': 0.9980378150939941, 'Train/mean miou_metric': 0.9957945346832275, 'Train/mean f1': 0.9929748177528381, 'Train/mean precision': 0.9881971478462219, 'Train/mean recall': 0.9977989196777344, 'Train/mean hd95_metric': 0.7540316581726074} +Epoch [2958/4000] Validation [1/4] Loss: 0.38617 focal_loss 0.32360 dice_loss 0.06257 +Epoch [2958/4000] Validation [2/4] Loss: 0.44136 focal_loss 0.33182 dice_loss 0.10954 +Epoch [2958/4000] Validation [3/4] Loss: 0.50027 focal_loss 0.41147 dice_loss 0.08880 +Epoch [2958/4000] Validation [4/4] Loss: 0.38820 focal_loss 0.28138 dice_loss 0.10681 +Epoch [2958/4000] Validation metric {'Val/mean dice_metric': 0.97406405210495, 'Val/mean miou_metric': 0.9594688415527344, 'Val/mean f1': 0.9755737781524658, 'Val/mean precision': 0.9738194346427917, 'Val/mean recall': 0.9773344397544861, 'Val/mean hd95_metric': 4.796029090881348} +Cheakpoint... +Epoch [2958/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97406405210495, 'Val/mean miou_metric': 0.9594688415527344, 'Val/mean f1': 0.9755737781524658, 'Val/mean precision': 0.9738194346427917, 'Val/mean recall': 0.9773344397544861, 'Val/mean hd95_metric': 4.796029090881348} +Epoch [2959/4000] Training [1/16] Loss: 0.00310 +Epoch [2959/4000] Training [2/16] Loss: 0.00376 +Epoch [2959/4000] Training [3/16] Loss: 0.00294 +Epoch [2959/4000] Training [4/16] Loss: 0.00583 +Epoch [2959/4000] Training [5/16] Loss: 0.00381 +Epoch [2959/4000] Training [6/16] Loss: 0.00372 +Epoch [2959/4000] Training [7/16] Loss: 0.00225 +Epoch [2959/4000] Training [8/16] Loss: 0.00407 +Epoch [2959/4000] Training [9/16] Loss: 0.00444 +Epoch [2959/4000] Training [10/16] Loss: 0.00370 +Epoch [2959/4000] Training [11/16] Loss: 0.00375 +Epoch [2959/4000] Training [12/16] Loss: 0.00415 +Epoch [2959/4000] Training [13/16] Loss: 0.00242 +Epoch [2959/4000] Training [14/16] Loss: 0.00452 +Epoch [2959/4000] Training [15/16] Loss: 0.00406 +Epoch [2959/4000] Training [16/16] Loss: 0.00335 +Epoch [2959/4000] Training metric {'Train/mean dice_metric': 0.9978231191635132, 'Train/mean miou_metric': 0.9953376054763794, 'Train/mean f1': 0.9922500252723694, 'Train/mean precision': 0.986941397190094, 'Train/mean recall': 0.9976161122322083, 'Train/mean hd95_metric': 0.8290870785713196} +Epoch [2959/4000] Validation [1/4] Loss: 0.39382 focal_loss 0.32994 dice_loss 0.06388 +Epoch [2959/4000] Validation [2/4] Loss: 0.87018 focal_loss 0.67962 dice_loss 0.19055 +Epoch [2959/4000] Validation [3/4] Loss: 0.21308 focal_loss 0.16139 dice_loss 0.05168 +Epoch [2959/4000] Validation [4/4] Loss: 0.33640 focal_loss 0.24913 dice_loss 0.08727 +Epoch [2959/4000] Validation metric {'Val/mean dice_metric': 0.9728790521621704, 'Val/mean miou_metric': 0.9588906168937683, 'Val/mean f1': 0.9754217267036438, 'Val/mean precision': 0.9733996987342834, 'Val/mean recall': 0.977452278137207, 'Val/mean hd95_metric': 4.87841796875} +Cheakpoint... +Epoch [2959/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728790521621704, 'Val/mean miou_metric': 0.9588906168937683, 'Val/mean f1': 0.9754217267036438, 'Val/mean precision': 0.9733996987342834, 'Val/mean recall': 0.977452278137207, 'Val/mean hd95_metric': 4.87841796875} +Epoch [2960/4000] Training [1/16] Loss: 0.00265 +Epoch [2960/4000] Training [2/16] Loss: 0.00263 +Epoch [2960/4000] Training [3/16] Loss: 0.00383 +Epoch [2960/4000] Training [4/16] Loss: 0.00273 +Epoch [2960/4000] Training [5/16] Loss: 0.00239 +Epoch [2960/4000] Training [6/16] Loss: 0.00325 +Epoch [2960/4000] Training [7/16] Loss: 0.00406 +Epoch [2960/4000] Training [8/16] Loss: 0.00333 +Epoch [2960/4000] Training [9/16] Loss: 0.00298 +Epoch [2960/4000] Training [10/16] Loss: 0.00374 +Epoch [2960/4000] Training [11/16] Loss: 0.00254 +Epoch [2960/4000] Training [12/16] Loss: 0.00398 +Epoch [2960/4000] Training [13/16] Loss: 0.00405 +Epoch [2960/4000] Training [14/16] Loss: 0.00310 +Epoch [2960/4000] Training [15/16] Loss: 0.00235 +Epoch [2960/4000] Training [16/16] Loss: 0.00345 +Epoch [2960/4000] Training metric {'Train/mean dice_metric': 0.9982564449310303, 'Train/mean miou_metric': 0.9962455630302429, 'Train/mean f1': 0.9933859705924988, 'Train/mean precision': 0.9888386130332947, 'Train/mean recall': 0.9979753494262695, 'Train/mean hd95_metric': 0.7984651923179626} +Epoch [2960/4000] Validation [1/4] Loss: 0.52536 focal_loss 0.43389 dice_loss 0.09147 +Epoch [2960/4000] Validation [2/4] Loss: 0.50550 focal_loss 0.38493 dice_loss 0.12057 +Epoch [2960/4000] Validation [3/4] Loss: 0.47315 focal_loss 0.38152 dice_loss 0.09162 +Epoch [2960/4000] Validation [4/4] Loss: 0.34604 focal_loss 0.24758 dice_loss 0.09846 +Epoch [2960/4000] Validation metric {'Val/mean dice_metric': 0.9728288650512695, 'Val/mean miou_metric': 0.957994282245636, 'Val/mean f1': 0.9744255542755127, 'Val/mean precision': 0.9729661345481873, 'Val/mean recall': 0.9758892059326172, 'Val/mean hd95_metric': 5.387904644012451} +Cheakpoint... +Epoch [2960/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728288650512695, 'Val/mean miou_metric': 0.957994282245636, 'Val/mean f1': 0.9744255542755127, 'Val/mean precision': 0.9729661345481873, 'Val/mean recall': 0.9758892059326172, 'Val/mean hd95_metric': 5.387904644012451} +Epoch [2961/4000] Training [1/16] Loss: 0.00248 +Epoch [2961/4000] Training [2/16] Loss: 0.00311 +Epoch [2961/4000] Training [3/16] Loss: 0.00272 +Epoch [2961/4000] Training [4/16] Loss: 0.00294 +Epoch [2961/4000] Training [5/16] Loss: 0.00268 +Epoch [2961/4000] Training [6/16] Loss: 0.00280 +Epoch [2961/4000] Training [7/16] Loss: 0.00400 +Epoch [2961/4000] Training [8/16] Loss: 0.00325 +Epoch [2961/4000] Training [9/16] Loss: 0.00272 +Epoch [2961/4000] Training [10/16] Loss: 0.00368 +Epoch [2961/4000] Training [11/16] Loss: 0.00283 +Epoch [2961/4000] Training [12/16] Loss: 0.00332 +Epoch [2961/4000] Training [13/16] Loss: 0.00295 +Epoch [2961/4000] Training [14/16] Loss: 0.00262 +Epoch [2961/4000] Training [15/16] Loss: 0.00384 +Epoch [2961/4000] Training [16/16] Loss: 0.00304 +Epoch [2961/4000] Training metric {'Train/mean dice_metric': 0.9982684850692749, 'Train/mean miou_metric': 0.9962531924247742, 'Train/mean f1': 0.9932245016098022, 'Train/mean precision': 0.9884952902793884, 'Train/mean recall': 0.9979991316795349, 'Train/mean hd95_metric': 0.7723209857940674} +Epoch [2961/4000] Validation [1/4] Loss: 0.37856 focal_loss 0.31569 dice_loss 0.06287 +Epoch [2961/4000] Validation [2/4] Loss: 0.66215 focal_loss 0.48394 dice_loss 0.17821 +Epoch [2961/4000] Validation [3/4] Loss: 0.47604 focal_loss 0.38725 dice_loss 0.08879 +Epoch [2961/4000] Validation [4/4] Loss: 0.41172 focal_loss 0.29166 dice_loss 0.12006 +Epoch [2961/4000] Validation metric {'Val/mean dice_metric': 0.9722572565078735, 'Val/mean miou_metric': 0.9573975801467896, 'Val/mean f1': 0.9749044179916382, 'Val/mean precision': 0.9735859036445618, 'Val/mean recall': 0.9762265086174011, 'Val/mean hd95_metric': 4.962936878204346} +Cheakpoint... +Epoch [2961/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722572565078735, 'Val/mean miou_metric': 0.9573975801467896, 'Val/mean f1': 0.9749044179916382, 'Val/mean precision': 0.9735859036445618, 'Val/mean recall': 0.9762265086174011, 'Val/mean hd95_metric': 4.962936878204346} +Epoch [2962/4000] Training [1/16] Loss: 0.00321 +Epoch [2962/4000] Training [2/16] Loss: 0.00247 +Epoch [2962/4000] Training [3/16] Loss: 0.00356 +Epoch [2962/4000] Training [4/16] Loss: 0.00277 +Epoch [2962/4000] Training [5/16] Loss: 0.00286 +Epoch [2962/4000] Training [6/16] Loss: 0.00277 +Epoch [2962/4000] Training [7/16] Loss: 0.00258 +Epoch [2962/4000] Training [8/16] Loss: 0.00221 +Epoch [2962/4000] Training [9/16] Loss: 0.00365 +Epoch [2962/4000] Training [10/16] Loss: 0.00363 +Epoch [2962/4000] Training [11/16] Loss: 0.00310 +Epoch [2962/4000] Training [12/16] Loss: 0.00276 +Epoch [2962/4000] Training [13/16] Loss: 0.00292 +Epoch [2962/4000] Training [14/16] Loss: 0.00274 +Epoch [2962/4000] Training [15/16] Loss: 0.00253 +Epoch [2962/4000] Training [16/16] Loss: 0.00263 +Epoch [2962/4000] Training metric {'Train/mean dice_metric': 0.9983437657356262, 'Train/mean miou_metric': 0.9964001178741455, 'Train/mean f1': 0.9932010173797607, 'Train/mean precision': 0.9884535670280457, 'Train/mean recall': 0.9979943037033081, 'Train/mean hd95_metric': 0.7680939435958862} +Epoch [2962/4000] Validation [1/4] Loss: 0.39187 focal_loss 0.32712 dice_loss 0.06475 +Epoch [2962/4000] Validation [2/4] Loss: 0.51011 focal_loss 0.38302 dice_loss 0.12709 +Epoch [2962/4000] Validation [3/4] Loss: 0.49039 focal_loss 0.39816 dice_loss 0.09222 +Epoch [2962/4000] Validation [4/4] Loss: 0.32317 focal_loss 0.23735 dice_loss 0.08582 +Epoch [2962/4000] Validation metric {'Val/mean dice_metric': 0.9738225936889648, 'Val/mean miou_metric': 0.9595974087715149, 'Val/mean f1': 0.9762142896652222, 'Val/mean precision': 0.9740729331970215, 'Val/mean recall': 0.9783650636672974, 'Val/mean hd95_metric': 4.837514400482178} +Cheakpoint... +Epoch [2962/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738225936889648, 'Val/mean miou_metric': 0.9595974087715149, 'Val/mean f1': 0.9762142896652222, 'Val/mean precision': 0.9740729331970215, 'Val/mean recall': 0.9783650636672974, 'Val/mean hd95_metric': 4.837514400482178} +Epoch [2963/4000] Training [1/16] Loss: 0.00388 +Epoch [2963/4000] Training [2/16] Loss: 0.00465 +Epoch [2963/4000] Training [3/16] Loss: 0.00332 +Epoch [2963/4000] Training [4/16] Loss: 0.00350 +Epoch [2963/4000] Training [5/16] Loss: 0.00208 +Epoch [2963/4000] Training [6/16] Loss: 0.00359 +Epoch [2963/4000] Training [7/16] Loss: 0.00217 +Epoch [2963/4000] Training [8/16] Loss: 0.00236 +Epoch [2963/4000] Training [9/16] Loss: 0.00410 +Epoch [2963/4000] Training [10/16] Loss: 0.00223 +Epoch [2963/4000] Training [11/16] Loss: 0.00247 +Epoch [2963/4000] Training [12/16] Loss: 0.00443 +Epoch [2963/4000] Training [13/16] Loss: 0.00500 +Epoch [2963/4000] Training [14/16] Loss: 0.00255 +Epoch [2963/4000] Training [15/16] Loss: 0.00290 +Epoch [2963/4000] Training [16/16] Loss: 0.00270 +Epoch [2963/4000] Training metric {'Train/mean dice_metric': 0.9982025623321533, 'Train/mean miou_metric': 0.9961361885070801, 'Train/mean f1': 0.9933387637138367, 'Train/mean precision': 0.9887707829475403, 'Train/mean recall': 0.9979491829872131, 'Train/mean hd95_metric': 0.7801755666732788} +Epoch [2963/4000] Validation [1/4] Loss: 0.39737 focal_loss 0.33145 dice_loss 0.06592 +Epoch [2963/4000] Validation [2/4] Loss: 0.85994 focal_loss 0.66729 dice_loss 0.19265 +Epoch [2963/4000] Validation [3/4] Loss: 0.47814 focal_loss 0.39218 dice_loss 0.08596 +Epoch [2963/4000] Validation [4/4] Loss: 0.30852 focal_loss 0.22357 dice_loss 0.08495 +Epoch [2963/4000] Validation metric {'Val/mean dice_metric': 0.9747481346130371, 'Val/mean miou_metric': 0.9606308937072754, 'Val/mean f1': 0.9763514995574951, 'Val/mean precision': 0.9743305444717407, 'Val/mean recall': 0.9783809781074524, 'Val/mean hd95_metric': 4.741163730621338} +Cheakpoint... +Epoch [2963/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747481346130371, 'Val/mean miou_metric': 0.9606308937072754, 'Val/mean f1': 0.9763514995574951, 'Val/mean precision': 0.9743305444717407, 'Val/mean recall': 0.9783809781074524, 'Val/mean hd95_metric': 4.741163730621338} +Epoch [2964/4000] Training [1/16] Loss: 0.00321 +Epoch [2964/4000] Training [2/16] Loss: 0.00305 +Epoch [2964/4000] Training [3/16] Loss: 0.00329 +Epoch [2964/4000] Training [4/16] Loss: 0.00249 +Epoch [2964/4000] Training [5/16] Loss: 0.00340 +Epoch [2964/4000] Training [6/16] Loss: 0.00254 +Epoch [2964/4000] Training [7/16] Loss: 0.00374 +Epoch [2964/4000] Training [8/16] Loss: 0.00288 +Epoch [2964/4000] Training [9/16] Loss: 0.00218 +Epoch [2964/4000] Training [10/16] Loss: 0.00328 +Epoch [2964/4000] Training [11/16] Loss: 0.00344 +Epoch [2964/4000] Training [12/16] Loss: 0.00352 +Epoch [2964/4000] Training [13/16] Loss: 0.00280 +Epoch [2964/4000] Training [14/16] Loss: 0.00443 +Epoch [2964/4000] Training [15/16] Loss: 0.00444 +Epoch [2964/4000] Training [16/16] Loss: 0.00268 +Epoch [2964/4000] Training metric {'Train/mean dice_metric': 0.9981859922409058, 'Train/mean miou_metric': 0.9961069822311401, 'Train/mean f1': 0.9934278726577759, 'Train/mean precision': 0.9889183640480042, 'Train/mean recall': 0.9979787468910217, 'Train/mean hd95_metric': 0.786941647529602} +Epoch [2964/4000] Validation [1/4] Loss: 0.37172 focal_loss 0.30985 dice_loss 0.06187 +Epoch [2964/4000] Validation [2/4] Loss: 0.74708 focal_loss 0.55440 dice_loss 0.19268 +Epoch [2964/4000] Validation [3/4] Loss: 0.41793 focal_loss 0.32324 dice_loss 0.09470 +Epoch [2964/4000] Validation [4/4] Loss: 0.39703 focal_loss 0.29412 dice_loss 0.10292 +Epoch [2964/4000] Validation metric {'Val/mean dice_metric': 0.9731538891792297, 'Val/mean miou_metric': 0.9590765237808228, 'Val/mean f1': 0.9756159782409668, 'Val/mean precision': 0.9728547930717468, 'Val/mean recall': 0.9783927202224731, 'Val/mean hd95_metric': 5.299934387207031} +Cheakpoint... +Epoch [2964/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731538891792297, 'Val/mean miou_metric': 0.9590765237808228, 'Val/mean f1': 0.9756159782409668, 'Val/mean precision': 0.9728547930717468, 'Val/mean recall': 0.9783927202224731, 'Val/mean hd95_metric': 5.299934387207031} +Epoch [2965/4000] Training [1/16] Loss: 0.00390 +Epoch [2965/4000] Training [2/16] Loss: 0.00215 +Epoch [2965/4000] Training [3/16] Loss: 0.00249 +Epoch [2965/4000] Training [4/16] Loss: 0.00255 +Epoch [2965/4000] Training [5/16] Loss: 0.00270 +Epoch [2965/4000] Training [6/16] Loss: 0.00456 +Epoch [2965/4000] Training [7/16] Loss: 0.00353 +Epoch [2965/4000] Training [8/16] Loss: 0.00329 +Epoch [2965/4000] Training [9/16] Loss: 0.00371 +Epoch [2965/4000] Training [10/16] Loss: 0.00259 +Epoch [2965/4000] Training [11/16] Loss: 0.00279 +Epoch [2965/4000] Training [12/16] Loss: 0.00235 +Epoch [2965/4000] Training [13/16] Loss: 0.00306 +Epoch [2965/4000] Training [14/16] Loss: 0.00482 +Epoch [2965/4000] Training [15/16] Loss: 0.00445 +Epoch [2965/4000] Training [16/16] Loss: 0.00348 +Epoch [2965/4000] Training metric {'Train/mean dice_metric': 0.9980707168579102, 'Train/mean miou_metric': 0.995861291885376, 'Train/mean f1': 0.9931862354278564, 'Train/mean precision': 0.9885703921318054, 'Train/mean recall': 0.9978454113006592, 'Train/mean hd95_metric': 0.828528881072998} +Epoch [2965/4000] Validation [1/4] Loss: 0.37009 focal_loss 0.30812 dice_loss 0.06197 +Epoch [2965/4000] Validation [2/4] Loss: 0.83075 focal_loss 0.63687 dice_loss 0.19388 +Epoch [2965/4000] Validation [3/4] Loss: 0.52087 focal_loss 0.42895 dice_loss 0.09191 +Epoch [2965/4000] Validation [4/4] Loss: 0.30524 focal_loss 0.22437 dice_loss 0.08086 +Epoch [2965/4000] Validation metric {'Val/mean dice_metric': 0.9736896753311157, 'Val/mean miou_metric': 0.9596418142318726, 'Val/mean f1': 0.9758515954017639, 'Val/mean precision': 0.9732010364532471, 'Val/mean recall': 0.9785165786743164, 'Val/mean hd95_metric': 5.282917022705078} +Cheakpoint... +Epoch [2965/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736896753311157, 'Val/mean miou_metric': 0.9596418142318726, 'Val/mean f1': 0.9758515954017639, 'Val/mean precision': 0.9732010364532471, 'Val/mean recall': 0.9785165786743164, 'Val/mean hd95_metric': 5.282917022705078} +Epoch [2966/4000] Training [1/16] Loss: 0.00312 +Epoch [2966/4000] Training [2/16] Loss: 0.00229 +Epoch [2966/4000] Training [3/16] Loss: 0.00312 +Epoch [2966/4000] Training [4/16] Loss: 0.00305 +Epoch [2966/4000] Training [5/16] Loss: 0.00325 +Epoch [2966/4000] Training [6/16] Loss: 0.00295 +Epoch [2966/4000] Training [7/16] Loss: 0.00244 +Epoch [2966/4000] Training [8/16] Loss: 0.00280 +Epoch [2966/4000] Training [9/16] Loss: 0.00312 +Epoch [2966/4000] Training [10/16] Loss: 0.00251 +Epoch [2966/4000] Training [11/16] Loss: 0.00368 +Epoch [2966/4000] Training [12/16] Loss: 0.00349 +Epoch [2966/4000] Training [13/16] Loss: 0.00339 +Epoch [2966/4000] Training [14/16] Loss: 0.00324 +Epoch [2966/4000] Training [15/16] Loss: 0.00413 +Epoch [2966/4000] Training [16/16] Loss: 0.00340 +Epoch [2966/4000] Training metric {'Train/mean dice_metric': 0.998115062713623, 'Train/mean miou_metric': 0.9959019422531128, 'Train/mean f1': 0.9921011328697205, 'Train/mean precision': 0.986504077911377, 'Train/mean recall': 0.9977620840072632, 'Train/mean hd95_metric': 0.810086190700531} +Epoch [2966/4000] Validation [1/4] Loss: 0.40012 focal_loss 0.33413 dice_loss 0.06599 +Epoch [2966/4000] Validation [2/4] Loss: 0.56404 focal_loss 0.43039 dice_loss 0.13365 +Epoch [2966/4000] Validation [3/4] Loss: 0.23824 focal_loss 0.18035 dice_loss 0.05789 +Epoch [2966/4000] Validation [4/4] Loss: 0.59222 focal_loss 0.45014 dice_loss 0.14207 +Epoch [2966/4000] Validation metric {'Val/mean dice_metric': 0.9725631475448608, 'Val/mean miou_metric': 0.9578205347061157, 'Val/mean f1': 0.9745248556137085, 'Val/mean precision': 0.9730714559555054, 'Val/mean recall': 0.9759824872016907, 'Val/mean hd95_metric': 4.938451290130615} +Cheakpoint... +Epoch [2966/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725631475448608, 'Val/mean miou_metric': 0.9578205347061157, 'Val/mean f1': 0.9745248556137085, 'Val/mean precision': 0.9730714559555054, 'Val/mean recall': 0.9759824872016907, 'Val/mean hd95_metric': 4.938451290130615} +Epoch [2967/4000] Training [1/16] Loss: 0.00437 +Epoch [2967/4000] Training [2/16] Loss: 0.00326 +Epoch [2967/4000] Training [3/16] Loss: 0.00454 +Epoch [2967/4000] Training [4/16] Loss: 0.00293 +Epoch [2967/4000] Training [5/16] Loss: 0.00274 +Epoch [2967/4000] Training [6/16] Loss: 0.00332 +Epoch [2967/4000] Training [7/16] Loss: 0.00331 +Epoch [2967/4000] Training [8/16] Loss: 0.01316 +Epoch [2967/4000] Training [9/16] Loss: 0.00340 +Epoch [2967/4000] Training [10/16] Loss: 0.00298 +Epoch [2967/4000] Training [11/16] Loss: 0.00236 +Epoch [2967/4000] Training [12/16] Loss: 0.00287 +Epoch [2967/4000] Training [13/16] Loss: 0.00216 +Epoch [2967/4000] Training [14/16] Loss: 0.00444 +Epoch [2967/4000] Training [15/16] Loss: 0.00306 +Epoch [2967/4000] Training [16/16] Loss: 0.00405 +Epoch [2967/4000] Training metric {'Train/mean dice_metric': 0.9979900121688843, 'Train/mean miou_metric': 0.9956799149513245, 'Train/mean f1': 0.9923344850540161, 'Train/mean precision': 0.9869393110275269, 'Train/mean recall': 0.9977889657020569, 'Train/mean hd95_metric': 0.8256210088729858} +Epoch [2967/4000] Validation [1/4] Loss: 0.36307 focal_loss 0.29939 dice_loss 0.06368 +Epoch [2967/4000] Validation [2/4] Loss: 0.49659 focal_loss 0.38017 dice_loss 0.11642 +Epoch [2967/4000] Validation [3/4] Loss: 0.49322 focal_loss 0.40451 dice_loss 0.08871 +Epoch [2967/4000] Validation [4/4] Loss: 0.28672 focal_loss 0.20720 dice_loss 0.07952 +Epoch [2967/4000] Validation metric {'Val/mean dice_metric': 0.974946141242981, 'Val/mean miou_metric': 0.9604603052139282, 'Val/mean f1': 0.9754308462142944, 'Val/mean precision': 0.973010778427124, 'Val/mean recall': 0.9778629541397095, 'Val/mean hd95_metric': 4.962541580200195} +Cheakpoint... +Epoch [2967/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974946141242981, 'Val/mean miou_metric': 0.9604603052139282, 'Val/mean f1': 0.9754308462142944, 'Val/mean precision': 0.973010778427124, 'Val/mean recall': 0.9778629541397095, 'Val/mean hd95_metric': 4.962541580200195} +Epoch [2968/4000] Training [1/16] Loss: 0.00367 +Epoch [2968/4000] Training [2/16] Loss: 0.00311 +Epoch [2968/4000] Training [3/16] Loss: 0.00287 +Epoch [2968/4000] Training [4/16] Loss: 0.00349 +Epoch [2968/4000] Training [5/16] Loss: 0.00347 +Epoch [2968/4000] Training [6/16] Loss: 0.00263 +Epoch [2968/4000] Training [7/16] Loss: 0.00325 +Epoch [2968/4000] Training [8/16] Loss: 0.00349 +Epoch [2968/4000] Training [9/16] Loss: 0.00299 +Epoch [2968/4000] Training [10/16] Loss: 0.00268 +Epoch [2968/4000] Training [11/16] Loss: 0.00288 +Epoch [2968/4000] Training [12/16] Loss: 0.00425 +Epoch [2968/4000] Training [13/16] Loss: 0.00355 +Epoch [2968/4000] Training [14/16] Loss: 0.00335 +Epoch [2968/4000] Training [15/16] Loss: 0.00358 +Epoch [2968/4000] Training [16/16] Loss: 0.00258 +Epoch [2968/4000] Training metric {'Train/mean dice_metric': 0.9980937242507935, 'Train/mean miou_metric': 0.9959185123443604, 'Train/mean f1': 0.9932538270950317, 'Train/mean precision': 0.988741397857666, 'Train/mean recall': 0.9978075623512268, 'Train/mean hd95_metric': 1.0030434131622314} +Epoch [2968/4000] Validation [1/4] Loss: 0.63601 focal_loss 0.52618 dice_loss 0.10983 +Epoch [2968/4000] Validation [2/4] Loss: 0.99169 focal_loss 0.80732 dice_loss 0.18437 +Epoch [2968/4000] Validation [3/4] Loss: 0.27497 focal_loss 0.21155 dice_loss 0.06342 +Epoch [2968/4000] Validation [4/4] Loss: 0.30572 focal_loss 0.22276 dice_loss 0.08297 +Epoch [2968/4000] Validation metric {'Val/mean dice_metric': 0.9718843698501587, 'Val/mean miou_metric': 0.9575226902961731, 'Val/mean f1': 0.9751269221305847, 'Val/mean precision': 0.9755129814147949, 'Val/mean recall': 0.9747413396835327, 'Val/mean hd95_metric': 5.052689075469971} +Cheakpoint... +Epoch [2968/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718843698501587, 'Val/mean miou_metric': 0.9575226902961731, 'Val/mean f1': 0.9751269221305847, 'Val/mean precision': 0.9755129814147949, 'Val/mean recall': 0.9747413396835327, 'Val/mean hd95_metric': 5.052689075469971} +Epoch [2969/4000] Training [1/16] Loss: 0.00410 +Epoch [2969/4000] Training [2/16] Loss: 0.00344 +Epoch [2969/4000] Training [3/16] Loss: 0.00351 +Epoch [2969/4000] Training [4/16] Loss: 0.00308 +Epoch [2969/4000] Training [5/16] Loss: 0.00255 +Epoch [2969/4000] Training [6/16] Loss: 0.00305 +Epoch [2969/4000] Training [7/16] Loss: 0.00284 +Epoch [2969/4000] Training [8/16] Loss: 0.00391 +Epoch [2969/4000] Training [9/16] Loss: 0.00309 +Epoch [2969/4000] Training [10/16] Loss: 0.00362 +Epoch [2969/4000] Training [11/16] Loss: 0.00217 +Epoch [2969/4000] Training [12/16] Loss: 0.00222 +Epoch [2969/4000] Training [13/16] Loss: 0.00415 +Epoch [2969/4000] Training [14/16] Loss: 0.00292 +Epoch [2969/4000] Training [15/16] Loss: 0.00298 +Epoch [2969/4000] Training [16/16] Loss: 0.00252 +Epoch [2969/4000] Training metric {'Train/mean dice_metric': 0.9982796907424927, 'Train/mean miou_metric': 0.9962495565414429, 'Train/mean f1': 0.9925228953361511, 'Train/mean precision': 0.9871917963027954, 'Train/mean recall': 0.9979118704795837, 'Train/mean hd95_metric': 0.7554464340209961} +Epoch [2969/4000] Validation [1/4] Loss: 0.37018 focal_loss 0.30305 dice_loss 0.06713 +Epoch [2969/4000] Validation [2/4] Loss: 1.43309 focal_loss 1.13293 dice_loss 0.30016 +Epoch [2969/4000] Validation [3/4] Loss: 0.46494 focal_loss 0.36911 dice_loss 0.09583 +Epoch [2969/4000] Validation [4/4] Loss: 0.37535 focal_loss 0.27040 dice_loss 0.10495 +Epoch [2969/4000] Validation metric {'Val/mean dice_metric': 0.9714719653129578, 'Val/mean miou_metric': 0.9570596814155579, 'Val/mean f1': 0.9745315909385681, 'Val/mean precision': 0.973763108253479, 'Val/mean recall': 0.9753010869026184, 'Val/mean hd95_metric': 4.820898056030273} +Cheakpoint... +Epoch [2969/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714719653129578, 'Val/mean miou_metric': 0.9570596814155579, 'Val/mean f1': 0.9745315909385681, 'Val/mean precision': 0.973763108253479, 'Val/mean recall': 0.9753010869026184, 'Val/mean hd95_metric': 4.820898056030273} +Epoch [2970/4000] Training [1/16] Loss: 0.00219 +Epoch [2970/4000] Training [2/16] Loss: 0.00387 +Epoch [2970/4000] Training [3/16] Loss: 0.00538 +Epoch [2970/4000] Training [4/16] Loss: 0.00206 +Epoch [2970/4000] Training [5/16] Loss: 0.00549 +Epoch [2970/4000] Training [6/16] Loss: 0.00372 +Epoch [2970/4000] Training [7/16] Loss: 0.00241 +Epoch [2970/4000] Training [8/16] Loss: 0.00437 +Epoch [2970/4000] Training [9/16] Loss: 0.00233 +Epoch [2970/4000] Training [10/16] Loss: 0.00309 +Epoch [2970/4000] Training [11/16] Loss: 0.00277 +Epoch [2970/4000] Training [12/16] Loss: 0.00448 +Epoch [2970/4000] Training [13/16] Loss: 0.00286 +Epoch [2970/4000] Training [14/16] Loss: 0.00293 +Epoch [2970/4000] Training [15/16] Loss: 0.00310 +Epoch [2970/4000] Training [16/16] Loss: 0.00236 +Epoch [2970/4000] Training metric {'Train/mean dice_metric': 0.9980803728103638, 'Train/mean miou_metric': 0.9959011077880859, 'Train/mean f1': 0.9933680891990662, 'Train/mean precision': 0.9888896942138672, 'Train/mean recall': 0.9978871941566467, 'Train/mean hd95_metric': 0.7819890379905701} +Epoch [2970/4000] Validation [1/4] Loss: 0.41021 focal_loss 0.34033 dice_loss 0.06988 +Epoch [2970/4000] Validation [2/4] Loss: 0.53538 focal_loss 0.41426 dice_loss 0.12112 +Epoch [2970/4000] Validation [3/4] Loss: 0.49175 focal_loss 0.39963 dice_loss 0.09212 +Epoch [2970/4000] Validation [4/4] Loss: 0.24792 focal_loss 0.16887 dice_loss 0.07905 +Epoch [2970/4000] Validation metric {'Val/mean dice_metric': 0.9730249643325806, 'Val/mean miou_metric': 0.958660900592804, 'Val/mean f1': 0.9759555459022522, 'Val/mean precision': 0.9745016098022461, 'Val/mean recall': 0.9774137735366821, 'Val/mean hd95_metric': 5.435476779937744} +Cheakpoint... +Epoch [2970/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730249643325806, 'Val/mean miou_metric': 0.958660900592804, 'Val/mean f1': 0.9759555459022522, 'Val/mean precision': 0.9745016098022461, 'Val/mean recall': 0.9774137735366821, 'Val/mean hd95_metric': 5.435476779937744} +Epoch [2971/4000] Training [1/16] Loss: 0.00255 +Epoch [2971/4000] Training [2/16] Loss: 0.00286 +Epoch [2971/4000] Training [3/16] Loss: 0.00374 +Epoch [2971/4000] Training [4/16] Loss: 0.00374 +Epoch [2971/4000] Training [5/16] Loss: 0.00254 +Epoch [2971/4000] Training [6/16] Loss: 0.00342 +Epoch [2971/4000] Training [7/16] Loss: 0.00337 +Epoch [2971/4000] Training [8/16] Loss: 0.00282 +Epoch [2971/4000] Training [9/16] Loss: 0.00271 +Epoch [2971/4000] Training [10/16] Loss: 0.00354 +Epoch [2971/4000] Training [11/16] Loss: 0.00255 +Epoch [2971/4000] Training [12/16] Loss: 0.00323 +Epoch [2971/4000] Training [13/16] Loss: 0.00261 +Epoch [2971/4000] Training [14/16] Loss: 0.00305 +Epoch [2971/4000] Training [15/16] Loss: 0.00318 +Epoch [2971/4000] Training [16/16] Loss: 0.00321 +Epoch [2971/4000] Training metric {'Train/mean dice_metric': 0.9983565211296082, 'Train/mean miou_metric': 0.9964450597763062, 'Train/mean f1': 0.9934985041618347, 'Train/mean precision': 0.988997220993042, 'Train/mean recall': 0.9980408549308777, 'Train/mean hd95_metric': 0.74387526512146} +Epoch [2971/4000] Validation [1/4] Loss: 0.37557 focal_loss 0.30895 dice_loss 0.06662 +Epoch [2971/4000] Validation [2/4] Loss: 1.56397 focal_loss 1.25623 dice_loss 0.30774 +Epoch [2971/4000] Validation [3/4] Loss: 0.50026 focal_loss 0.40879 dice_loss 0.09147 +Epoch [2971/4000] Validation [4/4] Loss: 0.38057 focal_loss 0.27489 dice_loss 0.10568 +Epoch [2971/4000] Validation metric {'Val/mean dice_metric': 0.9701221585273743, 'Val/mean miou_metric': 0.9562042355537415, 'Val/mean f1': 0.9751700162887573, 'Val/mean precision': 0.9745780229568481, 'Val/mean recall': 0.9757627248764038, 'Val/mean hd95_metric': 4.999283790588379} +Cheakpoint... +Epoch [2971/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9701221585273743, 'Val/mean miou_metric': 0.9562042355537415, 'Val/mean f1': 0.9751700162887573, 'Val/mean precision': 0.9745780229568481, 'Val/mean recall': 0.9757627248764038, 'Val/mean hd95_metric': 4.999283790588379} +Epoch [2972/4000] Training [1/16] Loss: 0.00342 +Epoch [2972/4000] Training [2/16] Loss: 0.00282 +Epoch [2972/4000] Training [3/16] Loss: 0.00314 +Epoch [2972/4000] Training [4/16] Loss: 0.00321 +Epoch [2972/4000] Training [5/16] Loss: 0.00462 +Epoch [2972/4000] Training [6/16] Loss: 0.00298 +Epoch [2972/4000] Training [7/16] Loss: 0.00301 +Epoch [2972/4000] Training [8/16] Loss: 0.00344 +Epoch [2972/4000] Training [9/16] Loss: 0.00272 +Epoch [2972/4000] Training [10/16] Loss: 0.00246 +Epoch [2972/4000] Training [11/16] Loss: 0.00442 +Epoch [2972/4000] Training [12/16] Loss: 0.00361 +Epoch [2972/4000] Training [13/16] Loss: 0.00365 +Epoch [2972/4000] Training [14/16] Loss: 0.00246 +Epoch [2972/4000] Training [15/16] Loss: 0.00206 +Epoch [2972/4000] Training [16/16] Loss: 0.00317 +Epoch [2972/4000] Training metric {'Train/mean dice_metric': 0.9981483817100525, 'Train/mean miou_metric': 0.9960222244262695, 'Train/mean f1': 0.9931509494781494, 'Train/mean precision': 0.988457202911377, 'Train/mean recall': 0.997889518737793, 'Train/mean hd95_metric': 0.772781491279602} +Epoch [2972/4000] Validation [1/4] Loss: 0.46836 focal_loss 0.39566 dice_loss 0.07270 +Epoch [2972/4000] Validation [2/4] Loss: 1.04778 focal_loss 0.80858 dice_loss 0.23920 +Epoch [2972/4000] Validation [3/4] Loss: 0.51288 focal_loss 0.41292 dice_loss 0.09996 +Epoch [2972/4000] Validation [4/4] Loss: 0.32720 focal_loss 0.24250 dice_loss 0.08470 +Epoch [2972/4000] Validation metric {'Val/mean dice_metric': 0.9699857831001282, 'Val/mean miou_metric': 0.9551898837089539, 'Val/mean f1': 0.9739965796470642, 'Val/mean precision': 0.9743414521217346, 'Val/mean recall': 0.9736518263816833, 'Val/mean hd95_metric': 5.408054828643799} +Cheakpoint... +Epoch [2972/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9700], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9699857831001282, 'Val/mean miou_metric': 0.9551898837089539, 'Val/mean f1': 0.9739965796470642, 'Val/mean precision': 0.9743414521217346, 'Val/mean recall': 0.9736518263816833, 'Val/mean hd95_metric': 5.408054828643799} +Epoch [2973/4000] Training [1/16] Loss: 0.00346 +Epoch [2973/4000] Training [2/16] Loss: 0.00428 +Epoch [2973/4000] Training [3/16] Loss: 0.00352 +Epoch [2973/4000] Training [4/16] Loss: 0.00380 +Epoch [2973/4000] Training [5/16] Loss: 0.00202 +Epoch [2973/4000] Training [6/16] Loss: 0.00288 +Epoch [2973/4000] Training [7/16] Loss: 0.00400 +Epoch [2973/4000] Training [8/16] Loss: 0.00425 +Epoch [2973/4000] Training [9/16] Loss: 0.00397 +Epoch [2973/4000] Training [10/16] Loss: 0.00320 +Epoch [2973/4000] Training [11/16] Loss: 0.00268 +Epoch [2973/4000] Training [12/16] Loss: 0.00264 +Epoch [2973/4000] Training [13/16] Loss: 0.00384 +Epoch [2973/4000] Training [14/16] Loss: 0.00306 +Epoch [2973/4000] Training [15/16] Loss: 0.00238 +Epoch [2973/4000] Training [16/16] Loss: 0.00406 +Epoch [2973/4000] Training metric {'Train/mean dice_metric': 0.997952401638031, 'Train/mean miou_metric': 0.9956001043319702, 'Train/mean f1': 0.992205798625946, 'Train/mean precision': 0.986845076084137, 'Train/mean recall': 0.9976250529289246, 'Train/mean hd95_metric': 0.8051334619522095} +Epoch [2973/4000] Validation [1/4] Loss: 0.35852 focal_loss 0.29239 dice_loss 0.06613 +Epoch [2973/4000] Validation [2/4] Loss: 0.56929 focal_loss 0.44308 dice_loss 0.12621 +Epoch [2973/4000] Validation [3/4] Loss: 0.49358 focal_loss 0.39902 dice_loss 0.09456 +Epoch [2973/4000] Validation [4/4] Loss: 0.45482 focal_loss 0.33848 dice_loss 0.11634 +Epoch [2973/4000] Validation metric {'Val/mean dice_metric': 0.9729819297790527, 'Val/mean miou_metric': 0.9579248428344727, 'Val/mean f1': 0.9747734069824219, 'Val/mean precision': 0.9735910892486572, 'Val/mean recall': 0.9759586453437805, 'Val/mean hd95_metric': 5.048468112945557} +Cheakpoint... +Epoch [2973/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729819297790527, 'Val/mean miou_metric': 0.9579248428344727, 'Val/mean f1': 0.9747734069824219, 'Val/mean precision': 0.9735910892486572, 'Val/mean recall': 0.9759586453437805, 'Val/mean hd95_metric': 5.048468112945557} +Epoch [2974/4000] Training [1/16] Loss: 0.00299 +Epoch [2974/4000] Training [2/16] Loss: 0.00328 +Epoch [2974/4000] Training [3/16] Loss: 0.00327 +Epoch [2974/4000] Training [4/16] Loss: 0.00281 +Epoch [2974/4000] Training [5/16] Loss: 0.00297 +Epoch [2974/4000] Training [6/16] Loss: 0.00264 +Epoch [2974/4000] Training [7/16] Loss: 0.00323 +Epoch [2974/4000] Training [8/16] Loss: 0.00348 +Epoch [2974/4000] Training [9/16] Loss: 0.00224 +Epoch [2974/4000] Training [10/16] Loss: 0.00252 +Epoch [2974/4000] Training [11/16] Loss: 0.00200 +Epoch [2974/4000] Training [12/16] Loss: 0.00249 +Epoch [2974/4000] Training [13/16] Loss: 0.00425 +Epoch [2974/4000] Training [14/16] Loss: 0.00263 +Epoch [2974/4000] Training [15/16] Loss: 0.00355 +Epoch [2974/4000] Training [16/16] Loss: 0.00393 +Epoch [2974/4000] Training metric {'Train/mean dice_metric': 0.9982700943946838, 'Train/mean miou_metric': 0.9962701797485352, 'Train/mean f1': 0.993333637714386, 'Train/mean precision': 0.9887740015983582, 'Train/mean recall': 0.9979355335235596, 'Train/mean hd95_metric': 0.7402199506759644} +Epoch [2974/4000] Validation [1/4] Loss: 0.40241 focal_loss 0.33223 dice_loss 0.07018 +Epoch [2974/4000] Validation [2/4] Loss: 1.18441 focal_loss 0.99609 dice_loss 0.18833 +Epoch [2974/4000] Validation [3/4] Loss: 0.51616 focal_loss 0.41166 dice_loss 0.10450 +Epoch [2974/4000] Validation [4/4] Loss: 0.61851 focal_loss 0.47462 dice_loss 0.14389 +Epoch [2974/4000] Validation metric {'Val/mean dice_metric': 0.9723488092422485, 'Val/mean miou_metric': 0.9577277898788452, 'Val/mean f1': 0.9743444323539734, 'Val/mean precision': 0.9741529226303101, 'Val/mean recall': 0.9745360016822815, 'Val/mean hd95_metric': 4.895417213439941} +Cheakpoint... +Epoch [2974/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723488092422485, 'Val/mean miou_metric': 0.9577277898788452, 'Val/mean f1': 0.9743444323539734, 'Val/mean precision': 0.9741529226303101, 'Val/mean recall': 0.9745360016822815, 'Val/mean hd95_metric': 4.895417213439941} +Epoch [2975/4000] Training [1/16] Loss: 0.00254 +Epoch [2975/4000] Training [2/16] Loss: 0.00399 +Epoch [2975/4000] Training [3/16] Loss: 0.00280 +Epoch [2975/4000] Training [4/16] Loss: 0.00415 +Epoch [2975/4000] Training [5/16] Loss: 0.00314 +Epoch [2975/4000] Training [6/16] Loss: 0.00434 +Epoch [2975/4000] Training [7/16] Loss: 0.00275 +Epoch [2975/4000] Training [8/16] Loss: 0.00299 +Epoch [2975/4000] Training [9/16] Loss: 0.00345 +Epoch [2975/4000] Training [10/16] Loss: 0.00317 +Epoch [2975/4000] Training [11/16] Loss: 0.00289 +Epoch [2975/4000] Training [12/16] Loss: 0.00339 +Epoch [2975/4000] Training [13/16] Loss: 0.00354 +Epoch [2975/4000] Training [14/16] Loss: 0.00344 +Epoch [2975/4000] Training [15/16] Loss: 0.00292 +Epoch [2975/4000] Training [16/16] Loss: 0.00355 +Epoch [2975/4000] Training metric {'Train/mean dice_metric': 0.9981324672698975, 'Train/mean miou_metric': 0.9960014820098877, 'Train/mean f1': 0.9933368563652039, 'Train/mean precision': 0.9888488054275513, 'Train/mean recall': 0.9978657960891724, 'Train/mean hd95_metric': 0.7727115750312805} +Epoch [2975/4000] Validation [1/4] Loss: 0.45331 focal_loss 0.38151 dice_loss 0.07180 +Epoch [2975/4000] Validation [2/4] Loss: 1.06959 focal_loss 0.87576 dice_loss 0.19383 +Epoch [2975/4000] Validation [3/4] Loss: 0.55135 focal_loss 0.44940 dice_loss 0.10195 +Epoch [2975/4000] Validation [4/4] Loss: 0.33693 focal_loss 0.24236 dice_loss 0.09456 +Epoch [2975/4000] Validation metric {'Val/mean dice_metric': 0.9712793231010437, 'Val/mean miou_metric': 0.9567937850952148, 'Val/mean f1': 0.9747650027275085, 'Val/mean precision': 0.9753233790397644, 'Val/mean recall': 0.97420734167099, 'Val/mean hd95_metric': 4.683077335357666} +Cheakpoint... +Epoch [2975/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712793231010437, 'Val/mean miou_metric': 0.9567937850952148, 'Val/mean f1': 0.9747650027275085, 'Val/mean precision': 0.9753233790397644, 'Val/mean recall': 0.97420734167099, 'Val/mean hd95_metric': 4.683077335357666} +Epoch [2976/4000] Training [1/16] Loss: 0.00335 +Epoch [2976/4000] Training [2/16] Loss: 0.00326 +Epoch [2976/4000] Training [3/16] Loss: 0.00201 +Epoch [2976/4000] Training [4/16] Loss: 0.00316 +Epoch [2976/4000] Training [5/16] Loss: 0.00243 +Epoch [2976/4000] Training [6/16] Loss: 0.00283 +Epoch [2976/4000] Training [7/16] Loss: 0.00445 +Epoch [2976/4000] Training [8/16] Loss: 0.00243 +Epoch [2976/4000] Training [9/16] Loss: 0.00297 +Epoch [2976/4000] Training [10/16] Loss: 0.00369 +Epoch [2976/4000] Training [11/16] Loss: 0.00259 +Epoch [2976/4000] Training [12/16] Loss: 0.00351 +Epoch [2976/4000] Training [13/16] Loss: 0.00240 +Epoch [2976/4000] Training [14/16] Loss: 0.00397 +Epoch [2976/4000] Training [15/16] Loss: 0.00298 +Epoch [2976/4000] Training [16/16] Loss: 0.00270 +Epoch [2976/4000] Training metric {'Train/mean dice_metric': 0.9982864856719971, 'Train/mean miou_metric': 0.9962869882583618, 'Train/mean f1': 0.993191123008728, 'Train/mean precision': 0.9884082078933716, 'Train/mean recall': 0.9980205297470093, 'Train/mean hd95_metric': 0.7914339900016785} +Epoch [2976/4000] Validation [1/4] Loss: 0.34714 focal_loss 0.28132 dice_loss 0.06582 +Epoch [2976/4000] Validation [2/4] Loss: 1.06313 focal_loss 0.82821 dice_loss 0.23492 +Epoch [2976/4000] Validation [3/4] Loss: 0.52450 focal_loss 0.42416 dice_loss 0.10034 +Epoch [2976/4000] Validation [4/4] Loss: 0.31456 focal_loss 0.22693 dice_loss 0.08763 +Epoch [2976/4000] Validation metric {'Val/mean dice_metric': 0.9724920988082886, 'Val/mean miou_metric': 0.9580442309379578, 'Val/mean f1': 0.9748963117599487, 'Val/mean precision': 0.9740700125694275, 'Val/mean recall': 0.9757241606712341, 'Val/mean hd95_metric': 5.5617995262146} +Cheakpoint... +Epoch [2976/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724920988082886, 'Val/mean miou_metric': 0.9580442309379578, 'Val/mean f1': 0.9748963117599487, 'Val/mean precision': 0.9740700125694275, 'Val/mean recall': 0.9757241606712341, 'Val/mean hd95_metric': 5.5617995262146} +Epoch [2977/4000] Training [1/16] Loss: 0.00309 +Epoch [2977/4000] Training [2/16] Loss: 0.00219 +Epoch [2977/4000] Training [3/16] Loss: 0.00269 +Epoch [2977/4000] Training [4/16] Loss: 0.00529 +Epoch [2977/4000] Training [5/16] Loss: 0.00296 +Epoch [2977/4000] Training [6/16] Loss: 0.00257 +Epoch [2977/4000] Training [7/16] Loss: 0.00442 +Epoch [2977/4000] Training [8/16] Loss: 0.00344 +Epoch [2977/4000] Training [9/16] Loss: 0.00301 +Epoch [2977/4000] Training [10/16] Loss: 0.00215 +Epoch [2977/4000] Training [11/16] Loss: 0.00368 +Epoch [2977/4000] Training [12/16] Loss: 0.00335 +Epoch [2977/4000] Training [13/16] Loss: 0.00316 +Epoch [2977/4000] Training [14/16] Loss: 0.00450 +Epoch [2977/4000] Training [15/16] Loss: 0.00293 +Epoch [2977/4000] Training [16/16] Loss: 0.00339 +Epoch [2977/4000] Training metric {'Train/mean dice_metric': 0.9981279373168945, 'Train/mean miou_metric': 0.9959601163864136, 'Train/mean f1': 0.9929237365722656, 'Train/mean precision': 0.9880044460296631, 'Train/mean recall': 0.9978922009468079, 'Train/mean hd95_metric': 0.7940705418586731} +Epoch [2977/4000] Validation [1/4] Loss: 0.36573 focal_loss 0.30247 dice_loss 0.06327 +Epoch [2977/4000] Validation [2/4] Loss: 1.16648 focal_loss 0.95982 dice_loss 0.20666 +Epoch [2977/4000] Validation [3/4] Loss: 0.46897 focal_loss 0.37292 dice_loss 0.09604 +Epoch [2977/4000] Validation [4/4] Loss: 0.72585 focal_loss 0.58273 dice_loss 0.14311 +Epoch [2977/4000] Validation metric {'Val/mean dice_metric': 0.9707685708999634, 'Val/mean miou_metric': 0.9562797546386719, 'Val/mean f1': 0.9745626449584961, 'Val/mean precision': 0.9741672873497009, 'Val/mean recall': 0.9749583005905151, 'Val/mean hd95_metric': 4.704737186431885} +Cheakpoint... +Epoch [2977/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707685708999634, 'Val/mean miou_metric': 0.9562797546386719, 'Val/mean f1': 0.9745626449584961, 'Val/mean precision': 0.9741672873497009, 'Val/mean recall': 0.9749583005905151, 'Val/mean hd95_metric': 4.704737186431885} +Epoch [2978/4000] Training [1/16] Loss: 0.00357 +Epoch [2978/4000] Training [2/16] Loss: 0.00529 +Epoch [2978/4000] Training [3/16] Loss: 0.00210 +Epoch [2978/4000] Training [4/16] Loss: 0.00297 +Epoch [2978/4000] Training [5/16] Loss: 0.00323 +Epoch [2978/4000] Training [6/16] Loss: 0.00275 +Epoch [2978/4000] Training [7/16] Loss: 0.00289 +Epoch [2978/4000] Training [8/16] Loss: 0.00335 +Epoch [2978/4000] Training [9/16] Loss: 0.00390 +Epoch [2978/4000] Training [10/16] Loss: 0.00294 +Epoch [2978/4000] Training [11/16] Loss: 0.00327 +Epoch [2978/4000] Training [12/16] Loss: 0.00283 +Epoch [2978/4000] Training [13/16] Loss: 0.00286 +Epoch [2978/4000] Training [14/16] Loss: 0.00229 +Epoch [2978/4000] Training [15/16] Loss: 0.00331 +Epoch [2978/4000] Training [16/16] Loss: 0.00340 +Epoch [2978/4000] Training metric {'Train/mean dice_metric': 0.9981346726417542, 'Train/mean miou_metric': 0.9960054159164429, 'Train/mean f1': 0.9934258460998535, 'Train/mean precision': 0.9889113306999207, 'Train/mean recall': 0.9979817271232605, 'Train/mean hd95_metric': 0.7768408060073853} +Epoch [2978/4000] Validation [1/4] Loss: 0.37512 focal_loss 0.30935 dice_loss 0.06577 +Epoch [2978/4000] Validation [2/4] Loss: 1.01790 focal_loss 0.82243 dice_loss 0.19547 +Epoch [2978/4000] Validation [3/4] Loss: 0.52446 focal_loss 0.42758 dice_loss 0.09688 +Epoch [2978/4000] Validation [4/4] Loss: 0.61977 focal_loss 0.49706 dice_loss 0.12271 +Epoch [2978/4000] Validation metric {'Val/mean dice_metric': 0.971717357635498, 'Val/mean miou_metric': 0.9571828842163086, 'Val/mean f1': 0.974644124507904, 'Val/mean precision': 0.9754158854484558, 'Val/mean recall': 0.9738734364509583, 'Val/mean hd95_metric': 5.167444229125977} +Cheakpoint... +Epoch [2978/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971717357635498, 'Val/mean miou_metric': 0.9571828842163086, 'Val/mean f1': 0.974644124507904, 'Val/mean precision': 0.9754158854484558, 'Val/mean recall': 0.9738734364509583, 'Val/mean hd95_metric': 5.167444229125977} +Epoch [2979/4000] Training [1/16] Loss: 0.00299 +Epoch [2979/4000] Training [2/16] Loss: 0.00462 +Epoch [2979/4000] Training [3/16] Loss: 0.00377 +Epoch [2979/4000] Training [4/16] Loss: 0.00240 +Epoch [2979/4000] Training [5/16] Loss: 0.00272 +Epoch [2979/4000] Training [6/16] Loss: 0.00373 +Epoch [2979/4000] Training [7/16] Loss: 0.00310 +Epoch [2979/4000] Training [8/16] Loss: 0.00285 +Epoch [2979/4000] Training [9/16] Loss: 0.00250 +Epoch [2979/4000] Training [10/16] Loss: 0.00328 +Epoch [2979/4000] Training [11/16] Loss: 0.00265 +Epoch [2979/4000] Training [12/16] Loss: 0.00417 +Epoch [2979/4000] Training [13/16] Loss: 0.00321 +Epoch [2979/4000] Training [14/16] Loss: 0.00409 +Epoch [2979/4000] Training [15/16] Loss: 0.00300 +Epoch [2979/4000] Training [16/16] Loss: 0.00346 +Epoch [2979/4000] Training metric {'Train/mean dice_metric': 0.9981180429458618, 'Train/mean miou_metric': 0.9959630966186523, 'Train/mean f1': 0.9932356476783752, 'Train/mean precision': 0.9886118769645691, 'Train/mean recall': 0.9979028105735779, 'Train/mean hd95_metric': 0.8057193756103516} +Epoch [2979/4000] Validation [1/4] Loss: 0.42895 focal_loss 0.35353 dice_loss 0.07542 +Epoch [2979/4000] Validation [2/4] Loss: 0.54915 focal_loss 0.42129 dice_loss 0.12786 +Epoch [2979/4000] Validation [3/4] Loss: 0.45285 focal_loss 0.36186 dice_loss 0.09099 +Epoch [2979/4000] Validation [4/4] Loss: 0.62319 focal_loss 0.49787 dice_loss 0.12532 +Epoch [2979/4000] Validation metric {'Val/mean dice_metric': 0.9720321893692017, 'Val/mean miou_metric': 0.9571123123168945, 'Val/mean f1': 0.9747307896614075, 'Val/mean precision': 0.9747655391693115, 'Val/mean recall': 0.9746959805488586, 'Val/mean hd95_metric': 5.121973037719727} +Cheakpoint... +Epoch [2979/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720321893692017, 'Val/mean miou_metric': 0.9571123123168945, 'Val/mean f1': 0.9747307896614075, 'Val/mean precision': 0.9747655391693115, 'Val/mean recall': 0.9746959805488586, 'Val/mean hd95_metric': 5.121973037719727} +Epoch [2980/4000] Training [1/16] Loss: 0.00298 +Epoch [2980/4000] Training [2/16] Loss: 0.00315 +Epoch [2980/4000] Training [3/16] Loss: 0.00305 +Epoch [2980/4000] Training [4/16] Loss: 0.00296 +Epoch [2980/4000] Training [5/16] Loss: 0.00342 +Epoch [2980/4000] Training [6/16] Loss: 0.00403 +Epoch [2980/4000] Training [7/16] Loss: 0.00246 +Epoch [2980/4000] Training [8/16] Loss: 0.00287 +Epoch [2980/4000] Training [9/16] Loss: 0.00271 +Epoch [2980/4000] Training [10/16] Loss: 0.00310 +Epoch [2980/4000] Training [11/16] Loss: 0.00306 +Epoch [2980/4000] Training [12/16] Loss: 0.00215 +Epoch [2980/4000] Training [13/16] Loss: 0.00367 +Epoch [2980/4000] Training [14/16] Loss: 0.00431 +Epoch [2980/4000] Training [15/16] Loss: 0.00372 +Epoch [2980/4000] Training [16/16] Loss: 0.00362 +Epoch [2980/4000] Training metric {'Train/mean dice_metric': 0.99814373254776, 'Train/mean miou_metric': 0.9960182309150696, 'Train/mean f1': 0.9933732151985168, 'Train/mean precision': 0.9888606071472168, 'Train/mean recall': 0.997927188873291, 'Train/mean hd95_metric': 0.8136296272277832} +Epoch [2980/4000] Validation [1/4] Loss: 0.41277 focal_loss 0.34553 dice_loss 0.06724 +Epoch [2980/4000] Validation [2/4] Loss: 0.54765 focal_loss 0.41880 dice_loss 0.12885 +Epoch [2980/4000] Validation [3/4] Loss: 0.44252 focal_loss 0.35493 dice_loss 0.08758 +Epoch [2980/4000] Validation [4/4] Loss: 0.29461 focal_loss 0.21500 dice_loss 0.07961 +Epoch [2980/4000] Validation metric {'Val/mean dice_metric': 0.973464846611023, 'Val/mean miou_metric': 0.959228515625, 'Val/mean f1': 0.9762195348739624, 'Val/mean precision': 0.9752436280250549, 'Val/mean recall': 0.9771972298622131, 'Val/mean hd95_metric': 4.869100093841553} +Cheakpoint... +Epoch [2980/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973464846611023, 'Val/mean miou_metric': 0.959228515625, 'Val/mean f1': 0.9762195348739624, 'Val/mean precision': 0.9752436280250549, 'Val/mean recall': 0.9771972298622131, 'Val/mean hd95_metric': 4.869100093841553} +Epoch [2981/4000] Training [1/16] Loss: 0.00267 +Epoch [2981/4000] Training [2/16] Loss: 0.00285 +Epoch [2981/4000] Training [3/16] Loss: 0.00287 +Epoch [2981/4000] Training [4/16] Loss: 0.00315 +Epoch [2981/4000] Training [5/16] Loss: 0.00234 +Epoch [2981/4000] Training [6/16] Loss: 0.00356 +Epoch [2981/4000] Training [7/16] Loss: 0.00327 +Epoch [2981/4000] Training [8/16] Loss: 0.00382 +Epoch [2981/4000] Training [9/16] Loss: 0.00316 +Epoch [2981/4000] Training [10/16] Loss: 0.00434 +Epoch [2981/4000] Training [11/16] Loss: 0.00411 +Epoch [2981/4000] Training [12/16] Loss: 0.00424 +Epoch [2981/4000] Training [13/16] Loss: 0.00303 +Epoch [2981/4000] Training [14/16] Loss: 0.00356 +Epoch [2981/4000] Training [15/16] Loss: 0.00368 +Epoch [2981/4000] Training [16/16] Loss: 0.00220 +Epoch [2981/4000] Training metric {'Train/mean dice_metric': 0.9981628060340881, 'Train/mean miou_metric': 0.9960588216781616, 'Train/mean f1': 0.9933702349662781, 'Train/mean precision': 0.9888803362846375, 'Train/mean recall': 0.9979011416435242, 'Train/mean hd95_metric': 0.7903319597244263} +Epoch [2981/4000] Validation [1/4] Loss: 0.46316 focal_loss 0.39292 dice_loss 0.07023 +Epoch [2981/4000] Validation [2/4] Loss: 1.08252 focal_loss 0.87474 dice_loss 0.20778 +Epoch [2981/4000] Validation [3/4] Loss: 0.44455 focal_loss 0.35413 dice_loss 0.09042 +Epoch [2981/4000] Validation [4/4] Loss: 0.38599 focal_loss 0.27999 dice_loss 0.10600 +Epoch [2981/4000] Validation metric {'Val/mean dice_metric': 0.9720064997673035, 'Val/mean miou_metric': 0.9576144218444824, 'Val/mean f1': 0.9750186800956726, 'Val/mean precision': 0.9752728939056396, 'Val/mean recall': 0.9747647047042847, 'Val/mean hd95_metric': 5.055581092834473} +Cheakpoint... +Epoch [2981/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720064997673035, 'Val/mean miou_metric': 0.9576144218444824, 'Val/mean f1': 0.9750186800956726, 'Val/mean precision': 0.9752728939056396, 'Val/mean recall': 0.9747647047042847, 'Val/mean hd95_metric': 5.055581092834473} +Epoch [2982/4000] Training [1/16] Loss: 0.00484 +Epoch [2982/4000] Training [2/16] Loss: 0.00279 +Epoch [2982/4000] Training [3/16] Loss: 0.00372 +Epoch [2982/4000] Training [4/16] Loss: 0.00316 +Epoch [2982/4000] Training [5/16] Loss: 0.00265 +Epoch [2982/4000] Training [6/16] Loss: 0.00304 +Epoch [2982/4000] Training [7/16] Loss: 0.00263 +Epoch [2982/4000] Training [8/16] Loss: 0.00220 +Epoch [2982/4000] Training [9/16] Loss: 0.00290 +Epoch [2982/4000] Training [10/16] Loss: 0.00412 +Epoch [2982/4000] Training [11/16] Loss: 0.00538 +Epoch [2982/4000] Training [12/16] Loss: 0.00253 +Epoch [2982/4000] Training [13/16] Loss: 0.00310 +Epoch [2982/4000] Training [14/16] Loss: 0.00512 +Epoch [2982/4000] Training [15/16] Loss: 0.00348 +Epoch [2982/4000] Training [16/16] Loss: 0.00347 +Epoch [2982/4000] Training metric {'Train/mean dice_metric': 0.9979758262634277, 'Train/mean miou_metric': 0.99565589427948, 'Train/mean f1': 0.9924249649047852, 'Train/mean precision': 0.9871786832809448, 'Train/mean recall': 0.9977273344993591, 'Train/mean hd95_metric': 0.7850902080535889} +Epoch [2982/4000] Validation [1/4] Loss: 0.41513 focal_loss 0.34511 dice_loss 0.07002 +Epoch [2982/4000] Validation [2/4] Loss: 0.52587 focal_loss 0.39765 dice_loss 0.12822 +Epoch [2982/4000] Validation [3/4] Loss: 0.47634 focal_loss 0.38445 dice_loss 0.09189 +Epoch [2982/4000] Validation [4/4] Loss: 0.52742 focal_loss 0.39227 dice_loss 0.13515 +Epoch [2982/4000] Validation metric {'Val/mean dice_metric': 0.9715434908866882, 'Val/mean miou_metric': 0.9564290046691895, 'Val/mean f1': 0.9738999009132385, 'Val/mean precision': 0.9729630947113037, 'Val/mean recall': 0.9748384356498718, 'Val/mean hd95_metric': 5.17146635055542} +Cheakpoint... +Epoch [2982/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715434908866882, 'Val/mean miou_metric': 0.9564290046691895, 'Val/mean f1': 0.9738999009132385, 'Val/mean precision': 0.9729630947113037, 'Val/mean recall': 0.9748384356498718, 'Val/mean hd95_metric': 5.17146635055542} +Epoch [2983/4000] Training [1/16] Loss: 0.00247 +Epoch [2983/4000] Training [2/16] Loss: 0.00203 +Epoch [2983/4000] Training [3/16] Loss: 0.00302 +Epoch [2983/4000] Training [4/16] Loss: 0.00273 +Epoch [2983/4000] Training [5/16] Loss: 0.00240 +Epoch [2983/4000] Training [6/16] Loss: 0.00271 +Epoch [2983/4000] Training [7/16] Loss: 0.00314 +Epoch [2983/4000] Training [8/16] Loss: 0.00404 +Epoch [2983/4000] Training [9/16] Loss: 0.00318 +Epoch [2983/4000] Training [10/16] Loss: 0.00386 +Epoch [2983/4000] Training [11/16] Loss: 0.00290 +Epoch [2983/4000] Training [12/16] Loss: 0.00263 +Epoch [2983/4000] Training [13/16] Loss: 0.00353 +Epoch [2983/4000] Training [14/16] Loss: 0.00392 +Epoch [2983/4000] Training [15/16] Loss: 0.00369 +Epoch [2983/4000] Training [16/16] Loss: 0.00378 +Epoch [2983/4000] Training metric {'Train/mean dice_metric': 0.9981098175048828, 'Train/mean miou_metric': 0.9959510564804077, 'Train/mean f1': 0.9932109713554382, 'Train/mean precision': 0.9886311888694763, 'Train/mean recall': 0.9978333711624146, 'Train/mean hd95_metric': 0.788894772529602} +Epoch [2983/4000] Validation [1/4] Loss: 0.40945 focal_loss 0.33873 dice_loss 0.07071 +Epoch [2983/4000] Validation [2/4] Loss: 0.58631 focal_loss 0.44502 dice_loss 0.14129 +Epoch [2983/4000] Validation [3/4] Loss: 0.24007 focal_loss 0.18428 dice_loss 0.05580 +Epoch [2983/4000] Validation [4/4] Loss: 0.35145 focal_loss 0.25016 dice_loss 0.10130 +Epoch [2983/4000] Validation metric {'Val/mean dice_metric': 0.9714568853378296, 'Val/mean miou_metric': 0.9571771621704102, 'Val/mean f1': 0.9753063917160034, 'Val/mean precision': 0.9755643606185913, 'Val/mean recall': 0.9750486016273499, 'Val/mean hd95_metric': 4.428422451019287} +Cheakpoint... +Epoch [2983/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714568853378296, 'Val/mean miou_metric': 0.9571771621704102, 'Val/mean f1': 0.9753063917160034, 'Val/mean precision': 0.9755643606185913, 'Val/mean recall': 0.9750486016273499, 'Val/mean hd95_metric': 4.428422451019287} +Epoch [2984/4000] Training [1/16] Loss: 0.00297 +Epoch [2984/4000] Training [2/16] Loss: 0.00334 +Epoch [2984/4000] Training [3/16] Loss: 0.00330 +Epoch [2984/4000] Training [4/16] Loss: 0.00500 +Epoch [2984/4000] Training [5/16] Loss: 0.00344 +Epoch [2984/4000] Training [6/16] Loss: 0.00450 +Epoch [2984/4000] Training [7/16] Loss: 0.00229 +Epoch [2984/4000] Training [8/16] Loss: 0.00322 +Epoch [2984/4000] Training [9/16] Loss: 0.00306 +Epoch [2984/4000] Training [10/16] Loss: 0.00297 +Epoch [2984/4000] Training [11/16] Loss: 0.00301 +Epoch [2984/4000] Training [12/16] Loss: 0.00374 +Epoch [2984/4000] Training [13/16] Loss: 0.00343 +Epoch [2984/4000] Training [14/16] Loss: 0.00293 +Epoch [2984/4000] Training [15/16] Loss: 0.00249 +Epoch [2984/4000] Training [16/16] Loss: 0.00383 +Epoch [2984/4000] Training metric {'Train/mean dice_metric': 0.9980790019035339, 'Train/mean miou_metric': 0.9958720207214355, 'Train/mean f1': 0.9929198026657104, 'Train/mean precision': 0.9881762266159058, 'Train/mean recall': 0.9977090954780579, 'Train/mean hd95_metric': 0.8069895505905151} +Epoch [2984/4000] Validation [1/4] Loss: 0.39060 focal_loss 0.32468 dice_loss 0.06592 +Epoch [2984/4000] Validation [2/4] Loss: 0.49097 focal_loss 0.36780 dice_loss 0.12317 +Epoch [2984/4000] Validation [3/4] Loss: 0.49642 focal_loss 0.40588 dice_loss 0.09054 +Epoch [2984/4000] Validation [4/4] Loss: 0.39794 focal_loss 0.28616 dice_loss 0.11178 +Epoch [2984/4000] Validation metric {'Val/mean dice_metric': 0.9722181558609009, 'Val/mean miou_metric': 0.957645058631897, 'Val/mean f1': 0.9751419425010681, 'Val/mean precision': 0.9730968475341797, 'Val/mean recall': 0.977195680141449, 'Val/mean hd95_metric': 5.189689636230469} +Cheakpoint... +Epoch [2984/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722181558609009, 'Val/mean miou_metric': 0.957645058631897, 'Val/mean f1': 0.9751419425010681, 'Val/mean precision': 0.9730968475341797, 'Val/mean recall': 0.977195680141449, 'Val/mean hd95_metric': 5.189689636230469} +Epoch [2985/4000] Training [1/16] Loss: 0.00276 +Epoch [2985/4000] Training [2/16] Loss: 0.00389 +Epoch [2985/4000] Training [3/16] Loss: 0.00334 +Epoch [2985/4000] Training [4/16] Loss: 0.00352 +Epoch [2985/4000] Training [5/16] Loss: 0.00256 +Epoch [2985/4000] Training [6/16] Loss: 0.00394 +Epoch [2985/4000] Training [7/16] Loss: 0.00331 +Epoch [2985/4000] Training [8/16] Loss: 0.00235 +Epoch [2985/4000] Training [9/16] Loss: 0.00393 +Epoch [2985/4000] Training [10/16] Loss: 0.00292 +Epoch [2985/4000] Training [11/16] Loss: 0.00253 +Epoch [2985/4000] Training [12/16] Loss: 0.00340 +Epoch [2985/4000] Training [13/16] Loss: 0.00261 +Epoch [2985/4000] Training [14/16] Loss: 0.00334 +Epoch [2985/4000] Training [15/16] Loss: 0.00454 +Epoch [2985/4000] Training [16/16] Loss: 0.00326 +Epoch [2985/4000] Training metric {'Train/mean dice_metric': 0.9980540871620178, 'Train/mean miou_metric': 0.99580979347229, 'Train/mean f1': 0.993040144443512, 'Train/mean precision': 0.9882287383079529, 'Train/mean recall': 0.9978986382484436, 'Train/mean hd95_metric': 0.8077424168586731} +Epoch [2985/4000] Validation [1/4] Loss: 0.48428 focal_loss 0.41282 dice_loss 0.07146 +Epoch [2985/4000] Validation [2/4] Loss: 0.47891 focal_loss 0.36365 dice_loss 0.11526 +Epoch [2985/4000] Validation [3/4] Loss: 0.49851 focal_loss 0.40243 dice_loss 0.09608 +Epoch [2985/4000] Validation [4/4] Loss: 0.40953 focal_loss 0.28764 dice_loss 0.12189 +Epoch [2985/4000] Validation metric {'Val/mean dice_metric': 0.9719845652580261, 'Val/mean miou_metric': 0.9570642709732056, 'Val/mean f1': 0.9748339056968689, 'Val/mean precision': 0.9741775989532471, 'Val/mean recall': 0.9754911661148071, 'Val/mean hd95_metric': 5.481200218200684} +Cheakpoint... +Epoch [2985/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719845652580261, 'Val/mean miou_metric': 0.9570642709732056, 'Val/mean f1': 0.9748339056968689, 'Val/mean precision': 0.9741775989532471, 'Val/mean recall': 0.9754911661148071, 'Val/mean hd95_metric': 5.481200218200684} +Epoch [2986/4000] Training [1/16] Loss: 0.00372 +Epoch [2986/4000] Training [2/16] Loss: 0.00351 +Epoch [2986/4000] Training [3/16] Loss: 0.00233 +Epoch [2986/4000] Training [4/16] Loss: 0.00362 +Epoch [2986/4000] Training [5/16] Loss: 0.00258 +Epoch [2986/4000] Training [6/16] Loss: 0.00270 +Epoch [2986/4000] Training [7/16] Loss: 0.00271 +Epoch [2986/4000] Training [8/16] Loss: 0.00375 +Epoch [2986/4000] Training [9/16] Loss: 0.00400 +Epoch [2986/4000] Training [10/16] Loss: 0.00328 +Epoch [2986/4000] Training [11/16] Loss: 0.00414 +Epoch [2986/4000] Training [12/16] Loss: 0.00352 +Epoch [2986/4000] Training [13/16] Loss: 0.00360 +Epoch [2986/4000] Training [14/16] Loss: 0.00356 +Epoch [2986/4000] Training [15/16] Loss: 0.00325 +Epoch [2986/4000] Training [16/16] Loss: 0.00497 +Epoch [2986/4000] Training metric {'Train/mean dice_metric': 0.9981608986854553, 'Train/mean miou_metric': 0.9960572123527527, 'Train/mean f1': 0.9934021830558777, 'Train/mean precision': 0.9889017939567566, 'Train/mean recall': 0.9979436993598938, 'Train/mean hd95_metric': 0.806179940700531} +Epoch [2986/4000] Validation [1/4] Loss: 0.42397 focal_loss 0.34997 dice_loss 0.07400 +Epoch [2986/4000] Validation [2/4] Loss: 1.01511 focal_loss 0.78164 dice_loss 0.23346 +Epoch [2986/4000] Validation [3/4] Loss: 0.50211 focal_loss 0.40801 dice_loss 0.09410 +Epoch [2986/4000] Validation [4/4] Loss: 0.42123 focal_loss 0.30529 dice_loss 0.11594 +Epoch [2986/4000] Validation metric {'Val/mean dice_metric': 0.9713218808174133, 'Val/mean miou_metric': 0.9563207626342773, 'Val/mean f1': 0.9748184084892273, 'Val/mean precision': 0.9744307398796082, 'Val/mean recall': 0.9752063751220703, 'Val/mean hd95_metric': 5.059609889984131} +Cheakpoint... +Epoch [2986/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713218808174133, 'Val/mean miou_metric': 0.9563207626342773, 'Val/mean f1': 0.9748184084892273, 'Val/mean precision': 0.9744307398796082, 'Val/mean recall': 0.9752063751220703, 'Val/mean hd95_metric': 5.059609889984131} +Epoch [2987/4000] Training [1/16] Loss: 0.00350 +Epoch [2987/4000] Training [2/16] Loss: 0.00447 +Epoch [2987/4000] Training [3/16] Loss: 0.00326 +Epoch [2987/4000] Training [4/16] Loss: 0.00264 +Epoch [2987/4000] Training [5/16] Loss: 0.00267 +Epoch [2987/4000] Training [6/16] Loss: 0.00464 +Epoch [2987/4000] Training [7/16] Loss: 0.00280 +Epoch [2987/4000] Training [8/16] Loss: 0.00273 +Epoch [2987/4000] Training [9/16] Loss: 0.00444 +Epoch [2987/4000] Training [10/16] Loss: 0.00336 +Epoch [2987/4000] Training [11/16] Loss: 0.00580 +Epoch [2987/4000] Training [12/16] Loss: 0.00350 +Epoch [2987/4000] Training [13/16] Loss: 0.00361 +Epoch [2987/4000] Training [14/16] Loss: 0.00364 +Epoch [2987/4000] Training [15/16] Loss: 0.00373 +Epoch [2987/4000] Training [16/16] Loss: 0.00371 +Epoch [2987/4000] Training metric {'Train/mean dice_metric': 0.9979551434516907, 'Train/mean miou_metric': 0.9956235885620117, 'Train/mean f1': 0.9928908348083496, 'Train/mean precision': 0.9881578087806702, 'Train/mean recall': 0.9976694583892822, 'Train/mean hd95_metric': 0.801910936832428} +Epoch [2987/4000] Validation [1/4] Loss: 0.37681 focal_loss 0.31163 dice_loss 0.06517 +Epoch [2987/4000] Validation [2/4] Loss: 0.52192 focal_loss 0.39727 dice_loss 0.12466 +Epoch [2987/4000] Validation [3/4] Loss: 0.48087 focal_loss 0.39203 dice_loss 0.08885 +Epoch [2987/4000] Validation [4/4] Loss: 0.27078 focal_loss 0.18433 dice_loss 0.08645 +Epoch [2987/4000] Validation metric {'Val/mean dice_metric': 0.9723553657531738, 'Val/mean miou_metric': 0.9575794339179993, 'Val/mean f1': 0.9752841591835022, 'Val/mean precision': 0.9747361540794373, 'Val/mean recall': 0.9758329391479492, 'Val/mean hd95_metric': 4.617313861846924} +Cheakpoint... +Epoch [2987/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723553657531738, 'Val/mean miou_metric': 0.9575794339179993, 'Val/mean f1': 0.9752841591835022, 'Val/mean precision': 0.9747361540794373, 'Val/mean recall': 0.9758329391479492, 'Val/mean hd95_metric': 4.617313861846924} +Epoch [2988/4000] Training [1/16] Loss: 0.00364 +Epoch [2988/4000] Training [2/16] Loss: 0.00415 +Epoch [2988/4000] Training [3/16] Loss: 0.00255 +Epoch [2988/4000] Training [4/16] Loss: 0.00373 +Epoch [2988/4000] Training [5/16] Loss: 0.00324 +Epoch [2988/4000] Training [6/16] Loss: 0.00267 +Epoch [2988/4000] Training [7/16] Loss: 0.00383 +Epoch [2988/4000] Training [8/16] Loss: 0.00197 +Epoch [2988/4000] Training [9/16] Loss: 0.00422 +Epoch [2988/4000] Training [10/16] Loss: 0.00278 +Epoch [2988/4000] Training [11/16] Loss: 0.00492 +Epoch [2988/4000] Training [12/16] Loss: 0.00432 +Epoch [2988/4000] Training [13/16] Loss: 0.00382 +Epoch [2988/4000] Training [14/16] Loss: 0.00246 +Epoch [2988/4000] Training [15/16] Loss: 0.00373 +Epoch [2988/4000] Training [16/16] Loss: 0.00384 +Epoch [2988/4000] Training metric {'Train/mean dice_metric': 0.9980920553207397, 'Train/mean miou_metric': 0.9959092736244202, 'Train/mean f1': 0.9931716322898865, 'Train/mean precision': 0.9885343909263611, 'Train/mean recall': 0.997852623462677, 'Train/mean hd95_metric': 0.7912662029266357} +Epoch [2988/4000] Validation [1/4] Loss: 0.42921 focal_loss 0.35811 dice_loss 0.07109 +Epoch [2988/4000] Validation [2/4] Loss: 0.97895 focal_loss 0.75130 dice_loss 0.22765 +Epoch [2988/4000] Validation [3/4] Loss: 0.56765 focal_loss 0.46641 dice_loss 0.10125 +Epoch [2988/4000] Validation [4/4] Loss: 0.36306 focal_loss 0.25918 dice_loss 0.10388 +Epoch [2988/4000] Validation metric {'Val/mean dice_metric': 0.9707385301589966, 'Val/mean miou_metric': 0.9555457234382629, 'Val/mean f1': 0.9743767380714417, 'Val/mean precision': 0.9740036725997925, 'Val/mean recall': 0.9747500419616699, 'Val/mean hd95_metric': 5.479928016662598} +Cheakpoint... +Epoch [2988/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707385301589966, 'Val/mean miou_metric': 0.9555457234382629, 'Val/mean f1': 0.9743767380714417, 'Val/mean precision': 0.9740036725997925, 'Val/mean recall': 0.9747500419616699, 'Val/mean hd95_metric': 5.479928016662598} +Epoch [2989/4000] Training [1/16] Loss: 0.00297 +Epoch [2989/4000] Training [2/16] Loss: 0.00398 +Epoch [2989/4000] Training [3/16] Loss: 0.00270 +Epoch [2989/4000] Training [4/16] Loss: 0.00395 +Epoch [2989/4000] Training [5/16] Loss: 0.00422 +Epoch [2989/4000] Training [6/16] Loss: 0.00275 +Epoch [2989/4000] Training [7/16] Loss: 0.00262 +Epoch [2989/4000] Training [8/16] Loss: 0.00261 +Epoch [2989/4000] Training [9/16] Loss: 0.00300 +Epoch [2989/4000] Training [10/16] Loss: 0.00323 +Epoch [2989/4000] Training [11/16] Loss: 0.00336 +Epoch [2989/4000] Training [12/16] Loss: 0.00238 +Epoch [2989/4000] Training [13/16] Loss: 0.00256 +Epoch [2989/4000] Training [14/16] Loss: 0.00205 +Epoch [2989/4000] Training [15/16] Loss: 0.00374 +Epoch [2989/4000] Training [16/16] Loss: 0.00252 +Epoch [2989/4000] Training metric {'Train/mean dice_metric': 0.9981833696365356, 'Train/mean miou_metric': 0.9960846900939941, 'Train/mean f1': 0.993072509765625, 'Train/mean precision': 0.9882614612579346, 'Train/mean recall': 0.9979305267333984, 'Train/mean hd95_metric': 0.7968326807022095} +Epoch [2989/4000] Validation [1/4] Loss: 0.40853 focal_loss 0.34198 dice_loss 0.06654 +Epoch [2989/4000] Validation [2/4] Loss: 0.56654 focal_loss 0.42999 dice_loss 0.13655 +Epoch [2989/4000] Validation [3/4] Loss: 0.25421 focal_loss 0.19549 dice_loss 0.05871 +Epoch [2989/4000] Validation [4/4] Loss: 0.31952 focal_loss 0.23795 dice_loss 0.08157 +Epoch [2989/4000] Validation metric {'Val/mean dice_metric': 0.973467230796814, 'Val/mean miou_metric': 0.9591911435127258, 'Val/mean f1': 0.9759641289710999, 'Val/mean precision': 0.9748934507369995, 'Val/mean recall': 0.9770374298095703, 'Val/mean hd95_metric': 4.902309417724609} +Cheakpoint... +Epoch [2989/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973467230796814, 'Val/mean miou_metric': 0.9591911435127258, 'Val/mean f1': 0.9759641289710999, 'Val/mean precision': 0.9748934507369995, 'Val/mean recall': 0.9770374298095703, 'Val/mean hd95_metric': 4.902309417724609} +Epoch [2990/4000] Training [1/16] Loss: 0.00419 +Epoch [2990/4000] Training [2/16] Loss: 0.00278 +Epoch [2990/4000] Training [3/16] Loss: 0.00234 +Epoch [2990/4000] Training [4/16] Loss: 0.00368 +Epoch [2990/4000] Training [5/16] Loss: 0.00285 +Epoch [2990/4000] Training [6/16] Loss: 0.00294 +Epoch [2990/4000] Training [7/16] Loss: 0.00331 +Epoch [2990/4000] Training [8/16] Loss: 0.00345 +Epoch [2990/4000] Training [9/16] Loss: 0.00367 +Epoch [2990/4000] Training [10/16] Loss: 0.00299 +Epoch [2990/4000] Training [11/16] Loss: 0.00198 +Epoch [2990/4000] Training [12/16] Loss: 0.00468 +Epoch [2990/4000] Training [13/16] Loss: 0.00306 +Epoch [2990/4000] Training [14/16] Loss: 0.00405 +Epoch [2990/4000] Training [15/16] Loss: 0.00270 +Epoch [2990/4000] Training [16/16] Loss: 0.00495 +Epoch [2990/4000] Training metric {'Train/mean dice_metric': 0.9981799125671387, 'Train/mean miou_metric': 0.9960641860961914, 'Train/mean f1': 0.9931998252868652, 'Train/mean precision': 0.9885079264640808, 'Train/mean recall': 0.997936487197876, 'Train/mean hd95_metric': 0.784500241279602} +Epoch [2990/4000] Validation [1/4] Loss: 0.42398 focal_loss 0.35263 dice_loss 0.07135 +Epoch [2990/4000] Validation [2/4] Loss: 0.61309 focal_loss 0.47109 dice_loss 0.14200 +Epoch [2990/4000] Validation [3/4] Loss: 0.47412 focal_loss 0.38482 dice_loss 0.08930 +Epoch [2990/4000] Validation [4/4] Loss: 0.31775 focal_loss 0.23407 dice_loss 0.08368 +Epoch [2990/4000] Validation metric {'Val/mean dice_metric': 0.9723367691040039, 'Val/mean miou_metric': 0.957563579082489, 'Val/mean f1': 0.9752886295318604, 'Val/mean precision': 0.9749859571456909, 'Val/mean recall': 0.9755914807319641, 'Val/mean hd95_metric': 4.941594123840332} +Cheakpoint... +Epoch [2990/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723367691040039, 'Val/mean miou_metric': 0.957563579082489, 'Val/mean f1': 0.9752886295318604, 'Val/mean precision': 0.9749859571456909, 'Val/mean recall': 0.9755914807319641, 'Val/mean hd95_metric': 4.941594123840332} +Epoch [2991/4000] Training [1/16] Loss: 0.00471 +Epoch [2991/4000] Training [2/16] Loss: 0.00316 +Epoch [2991/4000] Training [3/16] Loss: 0.00284 +Epoch [2991/4000] Training [4/16] Loss: 0.00327 +Epoch [2991/4000] Training [5/16] Loss: 0.00277 +Epoch [2991/4000] Training [6/16] Loss: 0.00308 +Epoch [2991/4000] Training [7/16] Loss: 0.00309 +Epoch [2991/4000] Training [8/16] Loss: 0.00316 +Epoch [2991/4000] Training [9/16] Loss: 0.00280 +Epoch [2991/4000] Training [10/16] Loss: 0.00332 +Epoch [2991/4000] Training [11/16] Loss: 0.00251 +Epoch [2991/4000] Training [12/16] Loss: 0.00423 +Epoch [2991/4000] Training [13/16] Loss: 0.00279 +Epoch [2991/4000] Training [14/16] Loss: 0.00338 +Epoch [2991/4000] Training [15/16] Loss: 0.00341 +Epoch [2991/4000] Training [16/16] Loss: 0.00238 +Epoch [2991/4000] Training metric {'Train/mean dice_metric': 0.9981558322906494, 'Train/mean miou_metric': 0.9959934949874878, 'Train/mean f1': 0.9924005270004272, 'Train/mean precision': 0.9869990348815918, 'Train/mean recall': 0.9978615045547485, 'Train/mean hd95_metric': 0.7985905408859253} +Epoch [2991/4000] Validation [1/4] Loss: 0.40148 focal_loss 0.33458 dice_loss 0.06691 +Epoch [2991/4000] Validation [2/4] Loss: 1.49583 focal_loss 1.20207 dice_loss 0.29375 +Epoch [2991/4000] Validation [3/4] Loss: 0.49116 focal_loss 0.39539 dice_loss 0.09578 +Epoch [2991/4000] Validation [4/4] Loss: 0.29232 focal_loss 0.19998 dice_loss 0.09233 +Epoch [2991/4000] Validation metric {'Val/mean dice_metric': 0.9710033535957336, 'Val/mean miou_metric': 0.9571243524551392, 'Val/mean f1': 0.974407970905304, 'Val/mean precision': 0.9723958373069763, 'Val/mean recall': 0.9764284491539001, 'Val/mean hd95_metric': 5.147981643676758} +Cheakpoint... +Epoch [2991/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9710], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9710033535957336, 'Val/mean miou_metric': 0.9571243524551392, 'Val/mean f1': 0.974407970905304, 'Val/mean precision': 0.9723958373069763, 'Val/mean recall': 0.9764284491539001, 'Val/mean hd95_metric': 5.147981643676758} +Epoch [2992/4000] Training [1/16] Loss: 0.00301 +Epoch [2992/4000] Training [2/16] Loss: 0.00323 +Epoch [2992/4000] Training [3/16] Loss: 0.00397 +Epoch [2992/4000] Training [4/16] Loss: 0.00303 +Epoch [2992/4000] Training [5/16] Loss: 0.00314 +Epoch [2992/4000] Training [6/16] Loss: 0.00386 +Epoch [2992/4000] Training [7/16] Loss: 0.00273 +Epoch [2992/4000] Training [8/16] Loss: 0.00281 +Epoch [2992/4000] Training [9/16] Loss: 0.00268 +Epoch [2992/4000] Training [10/16] Loss: 0.00445 +Epoch [2992/4000] Training [11/16] Loss: 0.00301 +Epoch [2992/4000] Training [12/16] Loss: 0.00344 +Epoch [2992/4000] Training [13/16] Loss: 0.00337 +Epoch [2992/4000] Training [14/16] Loss: 0.00336 +Epoch [2992/4000] Training [15/16] Loss: 0.00313 +Epoch [2992/4000] Training [16/16] Loss: 0.00346 +Epoch [2992/4000] Training metric {'Train/mean dice_metric': 0.9980543851852417, 'Train/mean miou_metric': 0.9958356022834778, 'Train/mean f1': 0.9932038187980652, 'Train/mean precision': 0.9886564016342163, 'Train/mean recall': 0.9977933168411255, 'Train/mean hd95_metric': 0.8009837865829468} +Epoch [2992/4000] Validation [1/4] Loss: 0.37693 focal_loss 0.30914 dice_loss 0.06779 +Epoch [2992/4000] Validation [2/4] Loss: 0.53404 focal_loss 0.40317 dice_loss 0.13087 +Epoch [2992/4000] Validation [3/4] Loss: 0.50967 focal_loss 0.41287 dice_loss 0.09680 +Epoch [2992/4000] Validation [4/4] Loss: 0.58101 focal_loss 0.45919 dice_loss 0.12181 +Epoch [2992/4000] Validation metric {'Val/mean dice_metric': 0.9731518626213074, 'Val/mean miou_metric': 0.9582395553588867, 'Val/mean f1': 0.9752511978149414, 'Val/mean precision': 0.9743685126304626, 'Val/mean recall': 0.9761354923248291, 'Val/mean hd95_metric': 4.904524326324463} +Cheakpoint... +Epoch [2992/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731518626213074, 'Val/mean miou_metric': 0.9582395553588867, 'Val/mean f1': 0.9752511978149414, 'Val/mean precision': 0.9743685126304626, 'Val/mean recall': 0.9761354923248291, 'Val/mean hd95_metric': 4.904524326324463} +Epoch [2993/4000] Training [1/16] Loss: 0.00318 +Epoch [2993/4000] Training [2/16] Loss: 0.00400 +Epoch [2993/4000] Training [3/16] Loss: 0.00296 +Epoch [2993/4000] Training [4/16] Loss: 0.00341 +Epoch [2993/4000] Training [5/16] Loss: 0.00285 +Epoch [2993/4000] Training [6/16] Loss: 0.00273 +Epoch [2993/4000] Training [7/16] Loss: 0.00436 +Epoch [2993/4000] Training [8/16] Loss: 0.00262 +Epoch [2993/4000] Training [9/16] Loss: 0.00477 +Epoch [2993/4000] Training [10/16] Loss: 0.00281 +Epoch [2993/4000] Training [11/16] Loss: 0.00375 +Epoch [2993/4000] Training [12/16] Loss: 0.00352 +Epoch [2993/4000] Training [13/16] Loss: 0.00239 +Epoch [2993/4000] Training [14/16] Loss: 0.00288 +Epoch [2993/4000] Training [15/16] Loss: 0.00453 +Epoch [2993/4000] Training [16/16] Loss: 0.00398 +Epoch [2993/4000] Training metric {'Train/mean dice_metric': 0.9980837106704712, 'Train/mean miou_metric': 0.9958997964859009, 'Train/mean f1': 0.9932777881622314, 'Train/mean precision': 0.988750159740448, 'Train/mean recall': 0.9978470802307129, 'Train/mean hd95_metric': 0.7764924168586731} +Epoch [2993/4000] Validation [1/4] Loss: 0.39959 focal_loss 0.33526 dice_loss 0.06433 +Epoch [2993/4000] Validation [2/4] Loss: 0.47369 focal_loss 0.35502 dice_loss 0.11867 +Epoch [2993/4000] Validation [3/4] Loss: 0.49132 focal_loss 0.39867 dice_loss 0.09266 +Epoch [2993/4000] Validation [4/4] Loss: 0.45153 focal_loss 0.31901 dice_loss 0.13252 +Epoch [2993/4000] Validation metric {'Val/mean dice_metric': 0.9732868075370789, 'Val/mean miou_metric': 0.9585062265396118, 'Val/mean f1': 0.9756181836128235, 'Val/mean precision': 0.9732669591903687, 'Val/mean recall': 0.9779808521270752, 'Val/mean hd95_metric': 5.322338104248047} +Cheakpoint... +Epoch [2993/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732868075370789, 'Val/mean miou_metric': 0.9585062265396118, 'Val/mean f1': 0.9756181836128235, 'Val/mean precision': 0.9732669591903687, 'Val/mean recall': 0.9779808521270752, 'Val/mean hd95_metric': 5.322338104248047} +Epoch [2994/4000] Training [1/16] Loss: 0.00410 +Epoch [2994/4000] Training [2/16] Loss: 0.00353 +Epoch [2994/4000] Training [3/16] Loss: 0.00416 +Epoch [2994/4000] Training [4/16] Loss: 0.00375 +Epoch [2994/4000] Training [5/16] Loss: 0.00432 +Epoch [2994/4000] Training [6/16] Loss: 0.00257 +Epoch [2994/4000] Training [7/16] Loss: 0.00258 +Epoch [2994/4000] Training [8/16] Loss: 0.00230 +Epoch [2994/4000] Training [9/16] Loss: 0.00318 +Epoch [2994/4000] Training [10/16] Loss: 0.00329 +Epoch [2994/4000] Training [11/16] Loss: 0.00349 +Epoch [2994/4000] Training [12/16] Loss: 0.00366 +Epoch [2994/4000] Training [13/16] Loss: 0.00316 +Epoch [2994/4000] Training [14/16] Loss: 0.00276 +Epoch [2994/4000] Training [15/16] Loss: 0.00313 +Epoch [2994/4000] Training [16/16] Loss: 0.00282 +Epoch [2994/4000] Training metric {'Train/mean dice_metric': 0.9982143044471741, 'Train/mean miou_metric': 0.9961576461791992, 'Train/mean f1': 0.993229329586029, 'Train/mean precision': 0.9884929656982422, 'Train/mean recall': 0.9980113506317139, 'Train/mean hd95_metric': 0.7809845805168152} +Epoch [2994/4000] Validation [1/4] Loss: 0.45134 focal_loss 0.38458 dice_loss 0.06675 +Epoch [2994/4000] Validation [2/4] Loss: 0.45856 focal_loss 0.34164 dice_loss 0.11693 +Epoch [2994/4000] Validation [3/4] Loss: 0.49818 focal_loss 0.40275 dice_loss 0.09542 +Epoch [2994/4000] Validation [4/4] Loss: 0.24532 focal_loss 0.16737 dice_loss 0.07796 +Epoch [2994/4000] Validation metric {'Val/mean dice_metric': 0.9739049673080444, 'Val/mean miou_metric': 0.9593003988265991, 'Val/mean f1': 0.9757311344146729, 'Val/mean precision': 0.9739839434623718, 'Val/mean recall': 0.9774847030639648, 'Val/mean hd95_metric': 5.316676616668701} +Cheakpoint... +Epoch [2994/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739049673080444, 'Val/mean miou_metric': 0.9593003988265991, 'Val/mean f1': 0.9757311344146729, 'Val/mean precision': 0.9739839434623718, 'Val/mean recall': 0.9774847030639648, 'Val/mean hd95_metric': 5.316676616668701} +Epoch [2995/4000] Training [1/16] Loss: 0.00302 +Epoch [2995/4000] Training [2/16] Loss: 0.00328 +Epoch [2995/4000] Training [3/16] Loss: 0.00307 +Epoch [2995/4000] Training [4/16] Loss: 0.00305 +Epoch [2995/4000] Training [5/16] Loss: 0.00461 +Epoch [2995/4000] Training [6/16] Loss: 0.00309 +Epoch [2995/4000] Training [7/16] Loss: 0.00268 +Epoch [2995/4000] Training [8/16] Loss: 0.00276 +Epoch [2995/4000] Training [9/16] Loss: 0.00229 +Epoch [2995/4000] Training [10/16] Loss: 0.00303 +Epoch [2995/4000] Training [11/16] Loss: 0.00358 +Epoch [2995/4000] Training [12/16] Loss: 0.00283 +Epoch [2995/4000] Training [13/16] Loss: 0.00239 +Epoch [2995/4000] Training [14/16] Loss: 0.00245 +Epoch [2995/4000] Training [15/16] Loss: 0.00304 +Epoch [2995/4000] Training [16/16] Loss: 0.00239 +Epoch [2995/4000] Training metric {'Train/mean dice_metric': 0.9982538223266602, 'Train/mean miou_metric': 0.9962413311004639, 'Train/mean f1': 0.9934390187263489, 'Train/mean precision': 0.9889258146286011, 'Train/mean recall': 0.9979936480522156, 'Train/mean hd95_metric': 0.7707584500312805} +Epoch [2995/4000] Validation [1/4] Loss: 0.39849 focal_loss 0.33503 dice_loss 0.06345 +Epoch [2995/4000] Validation [2/4] Loss: 0.48172 focal_loss 0.36031 dice_loss 0.12141 +Epoch [2995/4000] Validation [3/4] Loss: 0.47586 focal_loss 0.38599 dice_loss 0.08987 +Epoch [2995/4000] Validation [4/4] Loss: 0.54446 focal_loss 0.41540 dice_loss 0.12906 +Epoch [2995/4000] Validation metric {'Val/mean dice_metric': 0.972094714641571, 'Val/mean miou_metric': 0.957345187664032, 'Val/mean f1': 0.974703311920166, 'Val/mean precision': 0.9744048118591309, 'Val/mean recall': 0.9750019907951355, 'Val/mean hd95_metric': 5.196116924285889} +Cheakpoint... +Epoch [2995/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972094714641571, 'Val/mean miou_metric': 0.957345187664032, 'Val/mean f1': 0.974703311920166, 'Val/mean precision': 0.9744048118591309, 'Val/mean recall': 0.9750019907951355, 'Val/mean hd95_metric': 5.196116924285889} +Epoch [2996/4000] Training [1/16] Loss: 0.00333 +Epoch [2996/4000] Training [2/16] Loss: 0.00280 +Epoch [2996/4000] Training [3/16] Loss: 0.00286 +Epoch [2996/4000] Training [4/16] Loss: 0.00304 +Epoch [2996/4000] Training [5/16] Loss: 0.00440 +Epoch [2996/4000] Training [6/16] Loss: 0.00281 +Epoch [2996/4000] Training [7/16] Loss: 0.00325 +Epoch [2996/4000] Training [8/16] Loss: 0.00349 +Epoch [2996/4000] Training [9/16] Loss: 0.00265 +Epoch [2996/4000] Training [10/16] Loss: 0.00329 +Epoch [2996/4000] Training [11/16] Loss: 0.00265 +Epoch [2996/4000] Training [12/16] Loss: 0.00332 +Epoch [2996/4000] Training [13/16] Loss: 0.00332 +Epoch [2996/4000] Training [14/16] Loss: 0.00319 +Epoch [2996/4000] Training [15/16] Loss: 0.00367 +Epoch [2996/4000] Training [16/16] Loss: 0.00325 +Epoch [2996/4000] Training metric {'Train/mean dice_metric': 0.9981247186660767, 'Train/mean miou_metric': 0.9959853887557983, 'Train/mean f1': 0.9932969808578491, 'Train/mean precision': 0.9888055324554443, 'Train/mean recall': 0.9978294372558594, 'Train/mean hd95_metric': 0.7716508507728577} +Epoch [2996/4000] Validation [1/4] Loss: 0.45267 focal_loss 0.36323 dice_loss 0.08944 +Epoch [2996/4000] Validation [2/4] Loss: 0.48062 focal_loss 0.36086 dice_loss 0.11975 +Epoch [2996/4000] Validation [3/4] Loss: 0.52339 focal_loss 0.42635 dice_loss 0.09704 +Epoch [2996/4000] Validation [4/4] Loss: 0.35614 focal_loss 0.25755 dice_loss 0.09859 +Epoch [2996/4000] Validation metric {'Val/mean dice_metric': 0.9748172760009766, 'Val/mean miou_metric': 0.9598913192749023, 'Val/mean f1': 0.9760143160820007, 'Val/mean precision': 0.9734683036804199, 'Val/mean recall': 0.9785736203193665, 'Val/mean hd95_metric': 5.015664577484131} +Cheakpoint... +Epoch [2996/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748172760009766, 'Val/mean miou_metric': 0.9598913192749023, 'Val/mean f1': 0.9760143160820007, 'Val/mean precision': 0.9734683036804199, 'Val/mean recall': 0.9785736203193665, 'Val/mean hd95_metric': 5.015664577484131} +Epoch [2997/4000] Training [1/16] Loss: 0.00342 +Epoch [2997/4000] Training [2/16] Loss: 0.00364 +Epoch [2997/4000] Training [3/16] Loss: 0.00320 +Epoch [2997/4000] Training [4/16] Loss: 0.00430 +Epoch [2997/4000] Training [5/16] Loss: 0.00235 +Epoch [2997/4000] Training [6/16] Loss: 0.00282 +Epoch [2997/4000] Training [7/16] Loss: 0.00242 +Epoch [2997/4000] Training [8/16] Loss: 0.00375 +Epoch [2997/4000] Training [9/16] Loss: 0.00251 +Epoch [2997/4000] Training [10/16] Loss: 0.00394 +Epoch [2997/4000] Training [11/16] Loss: 0.00312 +Epoch [2997/4000] Training [12/16] Loss: 0.00392 +Epoch [2997/4000] Training [13/16] Loss: 0.00356 +Epoch [2997/4000] Training [14/16] Loss: 0.00410 +Epoch [2997/4000] Training [15/16] Loss: 0.00234 +Epoch [2997/4000] Training [16/16] Loss: 0.00318 +Epoch [2997/4000] Training metric {'Train/mean dice_metric': 0.9982554316520691, 'Train/mean miou_metric': 0.9962400197982788, 'Train/mean f1': 0.9934481978416443, 'Train/mean precision': 0.9889180660247803, 'Train/mean recall': 0.9980200529098511, 'Train/mean hd95_metric': 0.7517853379249573} +Epoch [2997/4000] Validation [1/4] Loss: 0.36334 focal_loss 0.29936 dice_loss 0.06398 +Epoch [2997/4000] Validation [2/4] Loss: 0.97160 focal_loss 0.77701 dice_loss 0.19459 +Epoch [2997/4000] Validation [3/4] Loss: 0.51508 focal_loss 0.41931 dice_loss 0.09577 +Epoch [2997/4000] Validation [4/4] Loss: 0.31589 focal_loss 0.23269 dice_loss 0.08321 +Epoch [2997/4000] Validation metric {'Val/mean dice_metric': 0.9718759655952454, 'Val/mean miou_metric': 0.9578048586845398, 'Val/mean f1': 0.9754051566123962, 'Val/mean precision': 0.9746364951133728, 'Val/mean recall': 0.9761750102043152, 'Val/mean hd95_metric': 4.890347003936768} +Cheakpoint... +Epoch [2997/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718759655952454, 'Val/mean miou_metric': 0.9578048586845398, 'Val/mean f1': 0.9754051566123962, 'Val/mean precision': 0.9746364951133728, 'Val/mean recall': 0.9761750102043152, 'Val/mean hd95_metric': 4.890347003936768} +Epoch [2998/4000] Training [1/16] Loss: 0.00576 +Epoch [2998/4000] Training [2/16] Loss: 0.00376 +Epoch [2998/4000] Training [3/16] Loss: 0.00308 +Epoch [2998/4000] Training [4/16] Loss: 0.00275 +Epoch [2998/4000] Training [5/16] Loss: 0.00236 +Epoch [2998/4000] Training [6/16] Loss: 0.00297 +Epoch [2998/4000] Training [7/16] Loss: 0.00281 +Epoch [2998/4000] Training [8/16] Loss: 0.00328 +Epoch [2998/4000] Training [9/16] Loss: 0.00249 +Epoch [2998/4000] Training [10/16] Loss: 0.00452 +Epoch [2998/4000] Training [11/16] Loss: 0.00254 +Epoch [2998/4000] Training [12/16] Loss: 0.00295 +Epoch [2998/4000] Training [13/16] Loss: 0.00195 +Epoch [2998/4000] Training [14/16] Loss: 0.00357 +Epoch [2998/4000] Training [15/16] Loss: 0.00234 +Epoch [2998/4000] Training [16/16] Loss: 0.00408 +Epoch [2998/4000] Training metric {'Train/mean dice_metric': 0.9981756210327148, 'Train/mean miou_metric': 0.996070384979248, 'Train/mean f1': 0.993178129196167, 'Train/mean precision': 0.9884993433952332, 'Train/mean recall': 0.9979013800621033, 'Train/mean hd95_metric': 0.7476838231086731} +Epoch [2998/4000] Validation [1/4] Loss: 0.35535 focal_loss 0.29184 dice_loss 0.06351 +Epoch [2998/4000] Validation [2/4] Loss: 0.53118 focal_loss 0.40178 dice_loss 0.12940 +Epoch [2998/4000] Validation [3/4] Loss: 0.24423 focal_loss 0.18537 dice_loss 0.05886 +Epoch [2998/4000] Validation [4/4] Loss: 0.51054 focal_loss 0.37326 dice_loss 0.13729 +Epoch [2998/4000] Validation metric {'Val/mean dice_metric': 0.9727548360824585, 'Val/mean miou_metric': 0.9582729339599609, 'Val/mean f1': 0.9757178425788879, 'Val/mean precision': 0.9753509759902954, 'Val/mean recall': 0.9760848879814148, 'Val/mean hd95_metric': 4.814876079559326} +Cheakpoint... +Epoch [2998/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727548360824585, 'Val/mean miou_metric': 0.9582729339599609, 'Val/mean f1': 0.9757178425788879, 'Val/mean precision': 0.9753509759902954, 'Val/mean recall': 0.9760848879814148, 'Val/mean hd95_metric': 4.814876079559326} +Epoch [2999/4000] Training [1/16] Loss: 0.00408 +Epoch [2999/4000] Training [2/16] Loss: 0.00360 +Epoch [2999/4000] Training [3/16] Loss: 0.00205 +Epoch [2999/4000] Training [4/16] Loss: 0.00394 +Epoch [2999/4000] Training [5/16] Loss: 0.00296 +Epoch [2999/4000] Training [6/16] Loss: 0.00271 +Epoch [2999/4000] Training [7/16] Loss: 0.00277 +Epoch [2999/4000] Training [8/16] Loss: 0.00252 +Epoch [2999/4000] Training [9/16] Loss: 0.00389 +Epoch [2999/4000] Training [10/16] Loss: 0.00222 +Epoch [2999/4000] Training [11/16] Loss: 0.00288 +Epoch [2999/4000] Training [12/16] Loss: 0.00293 +Epoch [2999/4000] Training [13/16] Loss: 0.00280 +Epoch [2999/4000] Training [14/16] Loss: 0.00281 +Epoch [2999/4000] Training [15/16] Loss: 0.00477 +Epoch [2999/4000] Training [16/16] Loss: 0.00336 +Epoch [2999/4000] Training metric {'Train/mean dice_metric': 0.9981904625892639, 'Train/mean miou_metric': 0.9961117506027222, 'Train/mean f1': 0.9933530688285828, 'Train/mean precision': 0.9887902736663818, 'Train/mean recall': 0.9979583024978638, 'Train/mean hd95_metric': 0.7640202045440674} +Epoch [2999/4000] Validation [1/4] Loss: 0.37814 focal_loss 0.31615 dice_loss 0.06199 +Epoch [2999/4000] Validation [2/4] Loss: 1.03505 focal_loss 0.84540 dice_loss 0.18965 +Epoch [2999/4000] Validation [3/4] Loss: 0.24420 focal_loss 0.18426 dice_loss 0.05994 +Epoch [2999/4000] Validation [4/4] Loss: 0.31650 focal_loss 0.23068 dice_loss 0.08583 +Epoch [2999/4000] Validation metric {'Val/mean dice_metric': 0.9725227355957031, 'Val/mean miou_metric': 0.9591943621635437, 'Val/mean f1': 0.9757199883460999, 'Val/mean precision': 0.9744921326637268, 'Val/mean recall': 0.9769509434700012, 'Val/mean hd95_metric': 4.995049476623535} +Cheakpoint... +Epoch [2999/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725227355957031, 'Val/mean miou_metric': 0.9591943621635437, 'Val/mean f1': 0.9757199883460999, 'Val/mean precision': 0.9744921326637268, 'Val/mean recall': 0.9769509434700012, 'Val/mean hd95_metric': 4.995049476623535} +Epoch [3000/4000] Training [1/16] Loss: 0.00210 +Epoch [3000/4000] Training [2/16] Loss: 0.00330 +Epoch [3000/4000] Training [3/16] Loss: 0.00333 +Epoch [3000/4000] Training [4/16] Loss: 0.00283 +Epoch [3000/4000] Training [5/16] Loss: 0.00289 +Epoch [3000/4000] Training [6/16] Loss: 0.00281 +Epoch [3000/4000] Training [7/16] Loss: 0.00361 +Epoch [3000/4000] Training [8/16] Loss: 0.00441 +Epoch [3000/4000] Training [9/16] Loss: 0.00290 +Epoch [3000/4000] Training [10/16] Loss: 0.00409 +Epoch [3000/4000] Training [11/16] Loss: 0.00237 +Epoch [3000/4000] Training [12/16] Loss: 0.00380 +Epoch [3000/4000] Training [13/16] Loss: 0.00396 +Epoch [3000/4000] Training [14/16] Loss: 0.00464 +Epoch [3000/4000] Training [15/16] Loss: 0.00356 +Epoch [3000/4000] Training [16/16] Loss: 0.00374 +Epoch [3000/4000] Training metric {'Train/mean dice_metric': 0.9981790781021118, 'Train/mean miou_metric': 0.9960926175117493, 'Train/mean f1': 0.9934574365615845, 'Train/mean precision': 0.9889882802963257, 'Train/mean recall': 0.9979671835899353, 'Train/mean hd95_metric': 0.7730652689933777} +Epoch [3000/4000] Validation [1/4] Loss: 0.36979 focal_loss 0.30669 dice_loss 0.06310 +Epoch [3000/4000] Validation [2/4] Loss: 0.87286 focal_loss 0.68070 dice_loss 0.19217 +Epoch [3000/4000] Validation [3/4] Loss: 0.53594 focal_loss 0.44337 dice_loss 0.09257 +Epoch [3000/4000] Validation [4/4] Loss: 0.24652 focal_loss 0.16699 dice_loss 0.07952 +Epoch [3000/4000] Validation metric {'Val/mean dice_metric': 0.9743289947509766, 'Val/mean miou_metric': 0.9596433639526367, 'Val/mean f1': 0.9757371544837952, 'Val/mean precision': 0.9742364883422852, 'Val/mean recall': 0.9772423505783081, 'Val/mean hd95_metric': 5.223867893218994} +Cheakpoint... +Epoch [3000/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743289947509766, 'Val/mean miou_metric': 0.9596433639526367, 'Val/mean f1': 0.9757371544837952, 'Val/mean precision': 0.9742364883422852, 'Val/mean recall': 0.9772423505783081, 'Val/mean hd95_metric': 5.223867893218994} +Epoch [3001/4000] Training [1/16] Loss: 0.00271 +Epoch [3001/4000] Training [2/16] Loss: 0.00342 +Epoch [3001/4000] Training [3/16] Loss: 0.00310 +Epoch [3001/4000] Training [4/16] Loss: 0.00307 +Epoch [3001/4000] Training [5/16] Loss: 0.00200 +Epoch [3001/4000] Training [6/16] Loss: 0.00347 +Epoch [3001/4000] Training [7/16] Loss: 0.00426 +Epoch [3001/4000] Training [8/16] Loss: 0.00241 +Epoch [3001/4000] Training [9/16] Loss: 0.00246 +Epoch [3001/4000] Training [10/16] Loss: 0.00440 +Epoch [3001/4000] Training [11/16] Loss: 0.00419 +Epoch [3001/4000] Training [12/16] Loss: 0.00242 +Epoch [3001/4000] Training [13/16] Loss: 0.00305 +Epoch [3001/4000] Training [14/16] Loss: 0.00234 +Epoch [3001/4000] Training [15/16] Loss: 0.00233 +Epoch [3001/4000] Training [16/16] Loss: 0.00341 +Epoch [3001/4000] Training metric {'Train/mean dice_metric': 0.9982666969299316, 'Train/mean miou_metric': 0.996230959892273, 'Train/mean f1': 0.9926518797874451, 'Train/mean precision': 0.9874072074890137, 'Train/mean recall': 0.9979525804519653, 'Train/mean hd95_metric': 0.760281503200531} +Epoch [3001/4000] Validation [1/4] Loss: 0.35544 focal_loss 0.29269 dice_loss 0.06274 +Epoch [3001/4000] Validation [2/4] Loss: 0.98624 focal_loss 0.80052 dice_loss 0.18572 +Epoch [3001/4000] Validation [3/4] Loss: 0.51082 focal_loss 0.41460 dice_loss 0.09622 +Epoch [3001/4000] Validation [4/4] Loss: 0.31878 focal_loss 0.23182 dice_loss 0.08697 +Epoch [3001/4000] Validation metric {'Val/mean dice_metric': 0.973366379737854, 'Val/mean miou_metric': 0.9593570828437805, 'Val/mean f1': 0.9753130674362183, 'Val/mean precision': 0.9731640815734863, 'Val/mean recall': 0.9774717092514038, 'Val/mean hd95_metric': 5.366258144378662} +Cheakpoint... +Epoch [3001/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973366379737854, 'Val/mean miou_metric': 0.9593570828437805, 'Val/mean f1': 0.9753130674362183, 'Val/mean precision': 0.9731640815734863, 'Val/mean recall': 0.9774717092514038, 'Val/mean hd95_metric': 5.366258144378662} +Epoch [3002/4000] Training [1/16] Loss: 0.00350 +Epoch [3002/4000] Training [2/16] Loss: 0.00388 +Epoch [3002/4000] Training [3/16] Loss: 0.00295 +Epoch [3002/4000] Training [4/16] Loss: 0.00378 +Epoch [3002/4000] Training [5/16] Loss: 0.00303 +Epoch [3002/4000] Training [6/16] Loss: 0.00283 +Epoch [3002/4000] Training [7/16] Loss: 0.00448 +Epoch [3002/4000] Training [8/16] Loss: 0.00295 +Epoch [3002/4000] Training [9/16] Loss: 0.00289 +Epoch [3002/4000] Training [10/16] Loss: 0.00330 +Epoch [3002/4000] Training [11/16] Loss: 0.00479 +Epoch [3002/4000] Training [12/16] Loss: 0.00245 +Epoch [3002/4000] Training [13/16] Loss: 0.00402 +Epoch [3002/4000] Training [14/16] Loss: 0.00296 +Epoch [3002/4000] Training [15/16] Loss: 0.00434 +Epoch [3002/4000] Training [16/16] Loss: 0.00354 +Epoch [3002/4000] Training metric {'Train/mean dice_metric': 0.9979485273361206, 'Train/mean miou_metric': 0.995620846748352, 'Train/mean f1': 0.9929799437522888, 'Train/mean precision': 0.9883025884628296, 'Train/mean recall': 0.9977018237113953, 'Train/mean hd95_metric': 0.9669643640518188} +Epoch [3002/4000] Validation [1/4] Loss: 0.32752 focal_loss 0.26817 dice_loss 0.05935 +Epoch [3002/4000] Validation [2/4] Loss: 0.53618 focal_loss 0.40723 dice_loss 0.12895 +Epoch [3002/4000] Validation [3/4] Loss: 0.50853 focal_loss 0.41194 dice_loss 0.09660 +Epoch [3002/4000] Validation [4/4] Loss: 0.30849 focal_loss 0.22155 dice_loss 0.08694 +Epoch [3002/4000] Validation metric {'Val/mean dice_metric': 0.9725314974784851, 'Val/mean miou_metric': 0.958135724067688, 'Val/mean f1': 0.9757459163665771, 'Val/mean precision': 0.973909854888916, 'Val/mean recall': 0.9775887727737427, 'Val/mean hd95_metric': 5.034398078918457} +Cheakpoint... +Epoch [3002/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725314974784851, 'Val/mean miou_metric': 0.958135724067688, 'Val/mean f1': 0.9757459163665771, 'Val/mean precision': 0.973909854888916, 'Val/mean recall': 0.9775887727737427, 'Val/mean hd95_metric': 5.034398078918457} +Epoch [3003/4000] Training [1/16] Loss: 0.00311 +Epoch [3003/4000] Training [2/16] Loss: 0.00256 +Epoch [3003/4000] Training [3/16] Loss: 0.00335 +Epoch [3003/4000] Training [4/16] Loss: 0.00365 +Epoch [3003/4000] Training [5/16] Loss: 0.00248 +Epoch [3003/4000] Training [6/16] Loss: 0.00525 +Epoch [3003/4000] Training [7/16] Loss: 0.00320 +Epoch [3003/4000] Training [8/16] Loss: 0.00310 +Epoch [3003/4000] Training [9/16] Loss: 0.00277 +Epoch [3003/4000] Training [10/16] Loss: 0.00399 +Epoch [3003/4000] Training [11/16] Loss: 0.00319 +Epoch [3003/4000] Training [12/16] Loss: 0.00277 +Epoch [3003/4000] Training [13/16] Loss: 0.00270 +Epoch [3003/4000] Training [14/16] Loss: 0.00368 +Epoch [3003/4000] Training [15/16] Loss: 0.00420 +Epoch [3003/4000] Training [16/16] Loss: 0.00351 +Epoch [3003/4000] Training metric {'Train/mean dice_metric': 0.9981233477592468, 'Train/mean miou_metric': 0.9959736466407776, 'Train/mean f1': 0.9932200312614441, 'Train/mean precision': 0.9885506629943848, 'Train/mean recall': 0.9979337453842163, 'Train/mean hd95_metric': 0.7866486310958862} +Epoch [3003/4000] Validation [1/4] Loss: 0.37334 focal_loss 0.31124 dice_loss 0.06210 +Epoch [3003/4000] Validation [2/4] Loss: 0.88489 focal_loss 0.69300 dice_loss 0.19189 +Epoch [3003/4000] Validation [3/4] Loss: 0.49105 focal_loss 0.40463 dice_loss 0.08642 +Epoch [3003/4000] Validation [4/4] Loss: 0.45863 focal_loss 0.34134 dice_loss 0.11729 +Epoch [3003/4000] Validation metric {'Val/mean dice_metric': 0.9723184704780579, 'Val/mean miou_metric': 0.9580499529838562, 'Val/mean f1': 0.9753877520561218, 'Val/mean precision': 0.9734905958175659, 'Val/mean recall': 0.9772923588752747, 'Val/mean hd95_metric': 5.245918273925781} +Cheakpoint... +Epoch [3003/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723184704780579, 'Val/mean miou_metric': 0.9580499529838562, 'Val/mean f1': 0.9753877520561218, 'Val/mean precision': 0.9734905958175659, 'Val/mean recall': 0.9772923588752747, 'Val/mean hd95_metric': 5.245918273925781} +Epoch [3004/4000] Training [1/16] Loss: 0.00266 +Epoch [3004/4000] Training [2/16] Loss: 0.00288 +Epoch [3004/4000] Training [3/16] Loss: 0.00397 +Epoch [3004/4000] Training [4/16] Loss: 0.00234 +Epoch [3004/4000] Training [5/16] Loss: 0.00327 +Epoch [3004/4000] Training [6/16] Loss: 0.00354 +Epoch [3004/4000] Training [7/16] Loss: 0.00375 +Epoch [3004/4000] Training [8/16] Loss: 0.00273 +Epoch [3004/4000] Training [9/16] Loss: 0.00267 +Epoch [3004/4000] Training [10/16] Loss: 0.00336 +Epoch [3004/4000] Training [11/16] Loss: 0.00314 +Epoch [3004/4000] Training [12/16] Loss: 0.00298 +Epoch [3004/4000] Training [13/16] Loss: 0.00525 +Epoch [3004/4000] Training [14/16] Loss: 0.00403 +Epoch [3004/4000] Training [15/16] Loss: 0.00295 +Epoch [3004/4000] Training [16/16] Loss: 0.00280 +Epoch [3004/4000] Training metric {'Train/mean dice_metric': 0.9981381893157959, 'Train/mean miou_metric': 0.9959931373596191, 'Train/mean f1': 0.9932017922401428, 'Train/mean precision': 0.9885447025299072, 'Train/mean recall': 0.9979029893875122, 'Train/mean hd95_metric': 0.79612135887146} +Epoch [3004/4000] Validation [1/4] Loss: 0.41311 focal_loss 0.34613 dice_loss 0.06698 +Epoch [3004/4000] Validation [2/4] Loss: 0.55179 focal_loss 0.42463 dice_loss 0.12716 +Epoch [3004/4000] Validation [3/4] Loss: 0.51277 focal_loss 0.41715 dice_loss 0.09562 +Epoch [3004/4000] Validation [4/4] Loss: 0.33748 focal_loss 0.24244 dice_loss 0.09505 +Epoch [3004/4000] Validation metric {'Val/mean dice_metric': 0.9725505113601685, 'Val/mean miou_metric': 0.9579456448554993, 'Val/mean f1': 0.9757149815559387, 'Val/mean precision': 0.9739858508110046, 'Val/mean recall': 0.9774502515792847, 'Val/mean hd95_metric': 4.845178127288818} +Cheakpoint... +Epoch [3004/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725505113601685, 'Val/mean miou_metric': 0.9579456448554993, 'Val/mean f1': 0.9757149815559387, 'Val/mean precision': 0.9739858508110046, 'Val/mean recall': 0.9774502515792847, 'Val/mean hd95_metric': 4.845178127288818} +Epoch [3005/4000] Training [1/16] Loss: 0.00281 +Epoch [3005/4000] Training [2/16] Loss: 0.00392 +Epoch [3005/4000] Training [3/16] Loss: 0.00254 +Epoch [3005/4000] Training [4/16] Loss: 0.00580 +Epoch [3005/4000] Training [5/16] Loss: 0.00373 +Epoch [3005/4000] Training [6/16] Loss: 0.00190 +Epoch [3005/4000] Training [7/16] Loss: 0.00242 +Epoch [3005/4000] Training [8/16] Loss: 0.00269 +Epoch [3005/4000] Training [9/16] Loss: 0.00215 +Epoch [3005/4000] Training [10/16] Loss: 0.00247 +Epoch [3005/4000] Training [11/16] Loss: 0.00422 +Epoch [3005/4000] Training [12/16] Loss: 0.00342 +Epoch [3005/4000] Training [13/16] Loss: 0.00346 +Epoch [3005/4000] Training [14/16] Loss: 0.00306 +Epoch [3005/4000] Training [15/16] Loss: 0.00270 +Epoch [3005/4000] Training [16/16] Loss: 0.00323 +Epoch [3005/4000] Training metric {'Train/mean dice_metric': 0.9982511401176453, 'Train/mean miou_metric': 0.9962182641029358, 'Train/mean f1': 0.9933218359947205, 'Train/mean precision': 0.9887053370475769, 'Train/mean recall': 0.997981607913971, 'Train/mean hd95_metric': 0.7545474171638489} +Epoch [3005/4000] Validation [1/4] Loss: 0.34959 focal_loss 0.28778 dice_loss 0.06181 +Epoch [3005/4000] Validation [2/4] Loss: 1.07934 focal_loss 0.89493 dice_loss 0.18441 +Epoch [3005/4000] Validation [3/4] Loss: 0.54200 focal_loss 0.44462 dice_loss 0.09739 +Epoch [3005/4000] Validation [4/4] Loss: 0.28422 focal_loss 0.19635 dice_loss 0.08787 +Epoch [3005/4000] Validation metric {'Val/mean dice_metric': 0.971572995185852, 'Val/mean miou_metric': 0.9578931927680969, 'Val/mean f1': 0.9760538935661316, 'Val/mean precision': 0.9744225740432739, 'Val/mean recall': 0.9776907563209534, 'Val/mean hd95_metric': 4.987037658691406} +Cheakpoint... +Epoch [3005/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971572995185852, 'Val/mean miou_metric': 0.9578931927680969, 'Val/mean f1': 0.9760538935661316, 'Val/mean precision': 0.9744225740432739, 'Val/mean recall': 0.9776907563209534, 'Val/mean hd95_metric': 4.987037658691406} +Epoch [3006/4000] Training [1/16] Loss: 0.00393 +Epoch [3006/4000] Training [2/16] Loss: 0.00417 +Epoch [3006/4000] Training [3/16] Loss: 0.00362 +Epoch [3006/4000] Training [4/16] Loss: 0.00267 +Epoch [3006/4000] Training [5/16] Loss: 0.00278 +Epoch [3006/4000] Training [6/16] Loss: 0.00281 +Epoch [3006/4000] Training [7/16] Loss: 0.00313 +Epoch [3006/4000] Training [8/16] Loss: 0.00243 +Epoch [3006/4000] Training [9/16] Loss: 0.00271 +Epoch [3006/4000] Training [10/16] Loss: 0.00350 +Epoch [3006/4000] Training [11/16] Loss: 0.00263 +Epoch [3006/4000] Training [12/16] Loss: 0.00245 +Epoch [3006/4000] Training [13/16] Loss: 0.00299 +Epoch [3006/4000] Training [14/16] Loss: 0.00370 +Epoch [3006/4000] Training [15/16] Loss: 0.00225 +Epoch [3006/4000] Training [16/16] Loss: 0.00351 +Epoch [3006/4000] Training metric {'Train/mean dice_metric': 0.9981591701507568, 'Train/mean miou_metric': 0.9960508346557617, 'Train/mean f1': 0.9933281540870667, 'Train/mean precision': 0.9887918829917908, 'Train/mean recall': 0.9979062080383301, 'Train/mean hd95_metric': 0.7570866942405701} +Epoch [3006/4000] Validation [1/4] Loss: 0.39439 focal_loss 0.33082 dice_loss 0.06357 +Epoch [3006/4000] Validation [2/4] Loss: 0.56249 focal_loss 0.43420 dice_loss 0.12829 +Epoch [3006/4000] Validation [3/4] Loss: 0.51775 focal_loss 0.42009 dice_loss 0.09766 +Epoch [3006/4000] Validation [4/4] Loss: 0.31136 focal_loss 0.22948 dice_loss 0.08188 +Epoch [3006/4000] Validation metric {'Val/mean dice_metric': 0.9749695658683777, 'Val/mean miou_metric': 0.9604297876358032, 'Val/mean f1': 0.9758580327033997, 'Val/mean precision': 0.97337406873703, 'Val/mean recall': 0.9783546924591064, 'Val/mean hd95_metric': 5.200967311859131} +Cheakpoint... +Epoch [3006/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749695658683777, 'Val/mean miou_metric': 0.9604297876358032, 'Val/mean f1': 0.9758580327033997, 'Val/mean precision': 0.97337406873703, 'Val/mean recall': 0.9783546924591064, 'Val/mean hd95_metric': 5.200967311859131} +Epoch [3007/4000] Training [1/16] Loss: 0.00410 +Epoch [3007/4000] Training [2/16] Loss: 0.00540 +Epoch [3007/4000] Training [3/16] Loss: 0.00357 +Epoch [3007/4000] Training [4/16] Loss: 0.00252 +Epoch [3007/4000] Training [5/16] Loss: 0.00287 +Epoch [3007/4000] Training [6/16] Loss: 0.01058 +Epoch [3007/4000] Training [7/16] Loss: 0.00404 +Epoch [3007/4000] Training [8/16] Loss: 0.00362 +Epoch [3007/4000] Training [9/16] Loss: 0.00306 +Epoch [3007/4000] Training [10/16] Loss: 0.00342 +Epoch [3007/4000] Training [11/16] Loss: 0.00358 +Epoch [3007/4000] Training [12/16] Loss: 0.00331 +Epoch [3007/4000] Training [13/16] Loss: 0.00239 +Epoch [3007/4000] Training [14/16] Loss: 0.00453 +Epoch [3007/4000] Training [15/16] Loss: 0.00283 +Epoch [3007/4000] Training [16/16] Loss: 0.00354 +Epoch [3007/4000] Training metric {'Train/mean dice_metric': 0.9979228973388672, 'Train/mean miou_metric': 0.9955752491950989, 'Train/mean f1': 0.9931091666221619, 'Train/mean precision': 0.9885016083717346, 'Train/mean recall': 0.9977598786354065, 'Train/mean hd95_metric': 0.7820594310760498} +Epoch [3007/4000] Validation [1/4] Loss: 0.33605 focal_loss 0.27467 dice_loss 0.06138 +Epoch [3007/4000] Validation [2/4] Loss: 0.53071 focal_loss 0.41113 dice_loss 0.11958 +Epoch [3007/4000] Validation [3/4] Loss: 0.45927 focal_loss 0.35995 dice_loss 0.09932 +Epoch [3007/4000] Validation [4/4] Loss: 0.35244 focal_loss 0.26126 dice_loss 0.09118 +Epoch [3007/4000] Validation metric {'Val/mean dice_metric': 0.9730033874511719, 'Val/mean miou_metric': 0.9583781957626343, 'Val/mean f1': 0.9755925536155701, 'Val/mean precision': 0.9743198752403259, 'Val/mean recall': 0.9768684506416321, 'Val/mean hd95_metric': 4.905806064605713} +Cheakpoint... +Epoch [3007/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730033874511719, 'Val/mean miou_metric': 0.9583781957626343, 'Val/mean f1': 0.9755925536155701, 'Val/mean precision': 0.9743198752403259, 'Val/mean recall': 0.9768684506416321, 'Val/mean hd95_metric': 4.905806064605713} +Epoch [3008/4000] Training [1/16] Loss: 0.00327 +Epoch [3008/4000] Training [2/16] Loss: 0.00242 +Epoch [3008/4000] Training [3/16] Loss: 0.00246 +Epoch [3008/4000] Training [4/16] Loss: 0.00351 +Epoch [3008/4000] Training [5/16] Loss: 0.00326 +Epoch [3008/4000] Training [6/16] Loss: 0.00539 +Epoch [3008/4000] Training [7/16] Loss: 0.00247 +Epoch [3008/4000] Training [8/16] Loss: 0.00288 +Epoch [3008/4000] Training [9/16] Loss: 0.00285 +Epoch [3008/4000] Training [10/16] Loss: 0.00342 +Epoch [3008/4000] Training [11/16] Loss: 0.00276 +Epoch [3008/4000] Training [12/16] Loss: 0.00282 +Epoch [3008/4000] Training [13/16] Loss: 0.00253 +Epoch [3008/4000] Training [14/16] Loss: 0.00308 +Epoch [3008/4000] Training [15/16] Loss: 0.00231 +Epoch [3008/4000] Training [16/16] Loss: 0.00328 +Epoch [3008/4000] Training metric {'Train/mean dice_metric': 0.998356282711029, 'Train/mean miou_metric': 0.9964348077774048, 'Train/mean f1': 0.9932788014411926, 'Train/mean precision': 0.9885953664779663, 'Train/mean recall': 0.9980067610740662, 'Train/mean hd95_metric': 0.7520783543586731} +Epoch [3008/4000] Validation [1/4] Loss: 0.36910 focal_loss 0.30707 dice_loss 0.06204 +Epoch [3008/4000] Validation [2/4] Loss: 1.40766 focal_loss 1.15827 dice_loss 0.24939 +Epoch [3008/4000] Validation [3/4] Loss: 0.26469 focal_loss 0.20580 dice_loss 0.05889 +Epoch [3008/4000] Validation [4/4] Loss: 0.24824 focal_loss 0.16674 dice_loss 0.08151 +Epoch [3008/4000] Validation metric {'Val/mean dice_metric': 0.9743234515190125, 'Val/mean miou_metric': 0.9601091146469116, 'Val/mean f1': 0.9756375551223755, 'Val/mean precision': 0.9739729166030884, 'Val/mean recall': 0.9773077964782715, 'Val/mean hd95_metric': 4.879739284515381} +Cheakpoint... +Epoch [3008/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743234515190125, 'Val/mean miou_metric': 0.9601091146469116, 'Val/mean f1': 0.9756375551223755, 'Val/mean precision': 0.9739729166030884, 'Val/mean recall': 0.9773077964782715, 'Val/mean hd95_metric': 4.879739284515381} +Epoch [3009/4000] Training [1/16] Loss: 0.00310 +Epoch [3009/4000] Training [2/16] Loss: 0.00240 +Epoch [3009/4000] Training [3/16] Loss: 0.00325 +Epoch [3009/4000] Training [4/16] Loss: 0.00312 +Epoch [3009/4000] Training [5/16] Loss: 0.00482 +Epoch [3009/4000] Training [6/16] Loss: 0.00322 +Epoch [3009/4000] Training [7/16] Loss: 0.00306 +Epoch [3009/4000] Training [8/16] Loss: 0.00345 +Epoch [3009/4000] Training [9/16] Loss: 0.00467 +Epoch [3009/4000] Training [10/16] Loss: 0.00274 +Epoch [3009/4000] Training [11/16] Loss: 0.00304 +Epoch [3009/4000] Training [12/16] Loss: 0.00339 +Epoch [3009/4000] Training [13/16] Loss: 0.00281 +Epoch [3009/4000] Training [14/16] Loss: 0.00256 +Epoch [3009/4000] Training [15/16] Loss: 0.00278 +Epoch [3009/4000] Training [16/16] Loss: 0.00384 +Epoch [3009/4000] Training metric {'Train/mean dice_metric': 0.9983031153678894, 'Train/mean miou_metric': 0.9963387250900269, 'Train/mean f1': 0.9935391545295715, 'Train/mean precision': 0.9890527725219727, 'Train/mean recall': 0.9980664253234863, 'Train/mean hd95_metric': 0.7657887935638428} +Epoch [3009/4000] Validation [1/4] Loss: 0.38914 focal_loss 0.31711 dice_loss 0.07203 +Epoch [3009/4000] Validation [2/4] Loss: 0.47715 focal_loss 0.35940 dice_loss 0.11776 +Epoch [3009/4000] Validation [3/4] Loss: 0.53178 focal_loss 0.44261 dice_loss 0.08917 +Epoch [3009/4000] Validation [4/4] Loss: 0.34810 focal_loss 0.24486 dice_loss 0.10324 +Epoch [3009/4000] Validation metric {'Val/mean dice_metric': 0.9737638235092163, 'Val/mean miou_metric': 0.959170937538147, 'Val/mean f1': 0.9760988354682922, 'Val/mean precision': 0.9737384915351868, 'Val/mean recall': 0.9784707427024841, 'Val/mean hd95_metric': 4.985440254211426} +Cheakpoint... +Epoch [3009/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737638235092163, 'Val/mean miou_metric': 0.959170937538147, 'Val/mean f1': 0.9760988354682922, 'Val/mean precision': 0.9737384915351868, 'Val/mean recall': 0.9784707427024841, 'Val/mean hd95_metric': 4.985440254211426} +Epoch [3010/4000] Training [1/16] Loss: 0.00369 +Epoch [3010/4000] Training [2/16] Loss: 0.00309 +Epoch [3010/4000] Training [3/16] Loss: 0.00231 +Epoch [3010/4000] Training [4/16] Loss: 0.00343 +Epoch [3010/4000] Training [5/16] Loss: 0.00257 +Epoch [3010/4000] Training [6/16] Loss: 0.00364 +Epoch [3010/4000] Training [7/16] Loss: 0.00250 +Epoch [3010/4000] Training [8/16] Loss: 0.00296 +Epoch [3010/4000] Training [9/16] Loss: 0.00272 +Epoch [3010/4000] Training [10/16] Loss: 0.00210 +Epoch [3010/4000] Training [11/16] Loss: 0.00263 +Epoch [3010/4000] Training [12/16] Loss: 0.00255 +Epoch [3010/4000] Training [13/16] Loss: 0.00402 +Epoch [3010/4000] Training [14/16] Loss: 0.00337 +Epoch [3010/4000] Training [15/16] Loss: 0.00293 +Epoch [3010/4000] Training [16/16] Loss: 0.00256 +Epoch [3010/4000] Training metric {'Train/mean dice_metric': 0.9982457160949707, 'Train/mean miou_metric': 0.9962245225906372, 'Train/mean f1': 0.9934662580490112, 'Train/mean precision': 0.9889835715293884, 'Train/mean recall': 0.9979897737503052, 'Train/mean hd95_metric': 0.7312497496604919} +Epoch [3010/4000] Validation [1/4] Loss: 0.35046 focal_loss 0.28961 dice_loss 0.06085 +Epoch [3010/4000] Validation [2/4] Loss: 0.84839 focal_loss 0.65567 dice_loss 0.19272 +Epoch [3010/4000] Validation [3/4] Loss: 0.47796 focal_loss 0.38074 dice_loss 0.09722 +Epoch [3010/4000] Validation [4/4] Loss: 0.32715 focal_loss 0.23288 dice_loss 0.09427 +Epoch [3010/4000] Validation metric {'Val/mean dice_metric': 0.972760796546936, 'Val/mean miou_metric': 0.958476722240448, 'Val/mean f1': 0.9758650660514832, 'Val/mean precision': 0.9736292958259583, 'Val/mean recall': 0.9781111478805542, 'Val/mean hd95_metric': 4.763430595397949} +Cheakpoint... +Epoch [3010/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972760796546936, 'Val/mean miou_metric': 0.958476722240448, 'Val/mean f1': 0.9758650660514832, 'Val/mean precision': 0.9736292958259583, 'Val/mean recall': 0.9781111478805542, 'Val/mean hd95_metric': 4.763430595397949} +Epoch [3011/4000] Training [1/16] Loss: 0.00465 +Epoch [3011/4000] Training [2/16] Loss: 0.00557 +Epoch [3011/4000] Training [3/16] Loss: 0.00248 +Epoch [3011/4000] Training [4/16] Loss: 0.00408 +Epoch [3011/4000] Training [5/16] Loss: 0.00418 +Epoch [3011/4000] Training [6/16] Loss: 0.00258 +Epoch [3011/4000] Training [7/16] Loss: 0.00322 +Epoch [3011/4000] Training [8/16] Loss: 0.00267 +Epoch [3011/4000] Training [9/16] Loss: 0.00241 +Epoch [3011/4000] Training [10/16] Loss: 0.00359 +Epoch [3011/4000] Training [11/16] Loss: 0.00316 +Epoch [3011/4000] Training [12/16] Loss: 0.00332 +Epoch [3011/4000] Training [13/16] Loss: 0.00223 +Epoch [3011/4000] Training [14/16] Loss: 0.00298 +Epoch [3011/4000] Training [15/16] Loss: 0.00306 +Epoch [3011/4000] Training [16/16] Loss: 0.00394 +Epoch [3011/4000] Training metric {'Train/mean dice_metric': 0.9980690479278564, 'Train/mean miou_metric': 0.9958679676055908, 'Train/mean f1': 0.9932810068130493, 'Train/mean precision': 0.9887757301330566, 'Train/mean recall': 0.9978275299072266, 'Train/mean hd95_metric': 0.8120670914649963} +Epoch [3011/4000] Validation [1/4] Loss: 0.38257 focal_loss 0.31297 dice_loss 0.06961 +Epoch [3011/4000] Validation [2/4] Loss: 0.58169 focal_loss 0.44385 dice_loss 0.13785 +Epoch [3011/4000] Validation [3/4] Loss: 0.26723 focal_loss 0.20664 dice_loss 0.06060 +Epoch [3011/4000] Validation [4/4] Loss: 0.33809 focal_loss 0.24666 dice_loss 0.09143 +Epoch [3011/4000] Validation metric {'Val/mean dice_metric': 0.9736356735229492, 'Val/mean miou_metric': 0.958753228187561, 'Val/mean f1': 0.9761489033699036, 'Val/mean precision': 0.9743924140930176, 'Val/mean recall': 0.977911651134491, 'Val/mean hd95_metric': 4.627569198608398} +Cheakpoint... +Epoch [3011/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736356735229492, 'Val/mean miou_metric': 0.958753228187561, 'Val/mean f1': 0.9761489033699036, 'Val/mean precision': 0.9743924140930176, 'Val/mean recall': 0.977911651134491, 'Val/mean hd95_metric': 4.627569198608398} +Epoch [3012/4000] Training [1/16] Loss: 0.00279 +Epoch [3012/4000] Training [2/16] Loss: 0.00356 +Epoch [3012/4000] Training [3/16] Loss: 0.00277 +Epoch [3012/4000] Training [4/16] Loss: 0.00252 +Epoch [3012/4000] Training [5/16] Loss: 0.00360 +Epoch [3012/4000] Training [6/16] Loss: 0.00326 +Epoch [3012/4000] Training [7/16] Loss: 0.00346 +Epoch [3012/4000] Training [8/16] Loss: 0.00235 +Epoch [3012/4000] Training [9/16] Loss: 0.00494 +Epoch [3012/4000] Training [10/16] Loss: 0.00255 +Epoch [3012/4000] Training [11/16] Loss: 0.00286 +Epoch [3012/4000] Training [12/16] Loss: 0.00362 +Epoch [3012/4000] Training [13/16] Loss: 0.00354 +Epoch [3012/4000] Training [14/16] Loss: 0.00235 +Epoch [3012/4000] Training [15/16] Loss: 0.00687 +Epoch [3012/4000] Training [16/16] Loss: 0.00273 +Epoch [3012/4000] Training metric {'Train/mean dice_metric': 0.998150110244751, 'Train/mean miou_metric': 0.9960354566574097, 'Train/mean f1': 0.9933249950408936, 'Train/mean precision': 0.9887600541114807, 'Train/mean recall': 0.9979322552680969, 'Train/mean hd95_metric': 0.7702425122261047} +Epoch [3012/4000] Validation [1/4] Loss: 0.45513 focal_loss 0.38784 dice_loss 0.06728 +Epoch [3012/4000] Validation [2/4] Loss: 1.10032 focal_loss 0.90876 dice_loss 0.19156 +Epoch [3012/4000] Validation [3/4] Loss: 0.50215 focal_loss 0.41061 dice_loss 0.09154 +Epoch [3012/4000] Validation [4/4] Loss: 0.36699 focal_loss 0.26682 dice_loss 0.10017 +Epoch [3012/4000] Validation metric {'Val/mean dice_metric': 0.9723206758499146, 'Val/mean miou_metric': 0.9580482244491577, 'Val/mean f1': 0.9754817485809326, 'Val/mean precision': 0.9746885299682617, 'Val/mean recall': 0.976276159286499, 'Val/mean hd95_metric': 5.075234889984131} +Cheakpoint... +Epoch [3012/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723206758499146, 'Val/mean miou_metric': 0.9580482244491577, 'Val/mean f1': 0.9754817485809326, 'Val/mean precision': 0.9746885299682617, 'Val/mean recall': 0.976276159286499, 'Val/mean hd95_metric': 5.075234889984131} +Epoch [3013/4000] Training [1/16] Loss: 0.00236 +Epoch [3013/4000] Training [2/16] Loss: 0.00312 +Epoch [3013/4000] Training [3/16] Loss: 0.00350 +Epoch [3013/4000] Training [4/16] Loss: 0.00306 +Epoch [3013/4000] Training [5/16] Loss: 0.00311 +Epoch [3013/4000] Training [6/16] Loss: 0.00368 +Epoch [3013/4000] Training [7/16] Loss: 0.00226 +Epoch [3013/4000] Training [8/16] Loss: 0.00388 +Epoch [3013/4000] Training [9/16] Loss: 0.00293 +Epoch [3013/4000] Training [10/16] Loss: 0.00286 +Epoch [3013/4000] Training [11/16] Loss: 0.00225 +Epoch [3013/4000] Training [12/16] Loss: 0.00246 +Epoch [3013/4000] Training [13/16] Loss: 0.00375 +Epoch [3013/4000] Training [14/16] Loss: 0.00260 +Epoch [3013/4000] Training [15/16] Loss: 0.00364 +Epoch [3013/4000] Training [16/16] Loss: 0.00303 +Epoch [3013/4000] Training metric {'Train/mean dice_metric': 0.9983165264129639, 'Train/mean miou_metric': 0.996361494064331, 'Train/mean f1': 0.9935054183006287, 'Train/mean precision': 0.9890047311782837, 'Train/mean recall': 0.9980471730232239, 'Train/mean hd95_metric': 0.7783479690551758} +Epoch [3013/4000] Validation [1/4] Loss: 0.36800 focal_loss 0.30557 dice_loss 0.06243 +Epoch [3013/4000] Validation [2/4] Loss: 0.53097 focal_loss 0.40118 dice_loss 0.12979 +Epoch [3013/4000] Validation [3/4] Loss: 0.49923 focal_loss 0.40552 dice_loss 0.09371 +Epoch [3013/4000] Validation [4/4] Loss: 0.31764 focal_loss 0.23187 dice_loss 0.08578 +Epoch [3013/4000] Validation metric {'Val/mean dice_metric': 0.9741371273994446, 'Val/mean miou_metric': 0.9598283767700195, 'Val/mean f1': 0.9761329889297485, 'Val/mean precision': 0.9736272096633911, 'Val/mean recall': 0.9786515235900879, 'Val/mean hd95_metric': 4.908346176147461} +Cheakpoint... +Epoch [3013/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741371273994446, 'Val/mean miou_metric': 0.9598283767700195, 'Val/mean f1': 0.9761329889297485, 'Val/mean precision': 0.9736272096633911, 'Val/mean recall': 0.9786515235900879, 'Val/mean hd95_metric': 4.908346176147461} +Epoch [3014/4000] Training [1/16] Loss: 0.00317 +Epoch [3014/4000] Training [2/16] Loss: 0.00396 +Epoch [3014/4000] Training [3/16] Loss: 0.00352 +Epoch [3014/4000] Training [4/16] Loss: 0.00248 +Epoch [3014/4000] Training [5/16] Loss: 0.00221 +Epoch [3014/4000] Training [6/16] Loss: 0.00309 +Epoch [3014/4000] Training [7/16] Loss: 0.00297 +Epoch [3014/4000] Training [8/16] Loss: 0.00346 +Epoch [3014/4000] Training [9/16] Loss: 0.00243 +Epoch [3014/4000] Training [10/16] Loss: 0.00304 +Epoch [3014/4000] Training [11/16] Loss: 0.00297 +Epoch [3014/4000] Training [12/16] Loss: 0.00277 +Epoch [3014/4000] Training [13/16] Loss: 0.00251 +Epoch [3014/4000] Training [14/16] Loss: 0.00311 +Epoch [3014/4000] Training [15/16] Loss: 0.00244 +Epoch [3014/4000] Training [16/16] Loss: 0.00437 +Epoch [3014/4000] Training metric {'Train/mean dice_metric': 0.9982423782348633, 'Train/mean miou_metric': 0.9961665868759155, 'Train/mean f1': 0.9925379157066345, 'Train/mean precision': 0.987184464931488, 'Train/mean recall': 0.9979498386383057, 'Train/mean hd95_metric': 0.7659453749656677} +Epoch [3014/4000] Validation [1/4] Loss: 0.38339 focal_loss 0.32099 dice_loss 0.06240 +Epoch [3014/4000] Validation [2/4] Loss: 0.55178 focal_loss 0.42276 dice_loss 0.12901 +Epoch [3014/4000] Validation [3/4] Loss: 0.50743 focal_loss 0.41602 dice_loss 0.09142 +Epoch [3014/4000] Validation [4/4] Loss: 0.40792 focal_loss 0.29457 dice_loss 0.11334 +Epoch [3014/4000] Validation metric {'Val/mean dice_metric': 0.9732486009597778, 'Val/mean miou_metric': 0.9590069651603699, 'Val/mean f1': 0.9755317568778992, 'Val/mean precision': 0.9734326004981995, 'Val/mean recall': 0.9776398539543152, 'Val/mean hd95_metric': 5.017638683319092} +Cheakpoint... +Epoch [3014/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732486009597778, 'Val/mean miou_metric': 0.9590069651603699, 'Val/mean f1': 0.9755317568778992, 'Val/mean precision': 0.9734326004981995, 'Val/mean recall': 0.9776398539543152, 'Val/mean hd95_metric': 5.017638683319092} +Epoch [3015/4000] Training [1/16] Loss: 0.00417 +Epoch [3015/4000] Training [2/16] Loss: 0.00306 +Epoch [3015/4000] Training [3/16] Loss: 0.00426 +Epoch [3015/4000] Training [4/16] Loss: 0.00421 +Epoch [3015/4000] Training [5/16] Loss: 0.00284 +Epoch [3015/4000] Training [6/16] Loss: 0.00230 +Epoch [3015/4000] Training [7/16] Loss: 0.00301 +Epoch [3015/4000] Training [8/16] Loss: 0.00340 +Epoch [3015/4000] Training [9/16] Loss: 0.00423 +Epoch [3015/4000] Training [10/16] Loss: 0.00287 +Epoch [3015/4000] Training [11/16] Loss: 0.00293 +Epoch [3015/4000] Training [12/16] Loss: 0.00256 +Epoch [3015/4000] Training [13/16] Loss: 0.00424 +Epoch [3015/4000] Training [14/16] Loss: 0.00404 +Epoch [3015/4000] Training [15/16] Loss: 0.00338 +Epoch [3015/4000] Training [16/16] Loss: 0.00223 +Epoch [3015/4000] Training metric {'Train/mean dice_metric': 0.9980998039245605, 'Train/mean miou_metric': 0.9959208965301514, 'Train/mean f1': 0.9932824373245239, 'Train/mean precision': 0.9887349605560303, 'Train/mean recall': 0.9978719353675842, 'Train/mean hd95_metric': 0.7812499403953552} +Epoch [3015/4000] Validation [1/4] Loss: 0.37986 focal_loss 0.31682 dice_loss 0.06304 +Epoch [3015/4000] Validation [2/4] Loss: 0.51276 focal_loss 0.39273 dice_loss 0.12004 +Epoch [3015/4000] Validation [3/4] Loss: 0.50062 focal_loss 0.40766 dice_loss 0.09296 +Epoch [3015/4000] Validation [4/4] Loss: 0.35512 focal_loss 0.24186 dice_loss 0.11326 +Epoch [3015/4000] Validation metric {'Val/mean dice_metric': 0.9727728962898254, 'Val/mean miou_metric': 0.9587470889091492, 'Val/mean f1': 0.9759734272956848, 'Val/mean precision': 0.9741794466972351, 'Val/mean recall': 0.9777738451957703, 'Val/mean hd95_metric': 5.084125995635986} +Cheakpoint... +Epoch [3015/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727728962898254, 'Val/mean miou_metric': 0.9587470889091492, 'Val/mean f1': 0.9759734272956848, 'Val/mean precision': 0.9741794466972351, 'Val/mean recall': 0.9777738451957703, 'Val/mean hd95_metric': 5.084125995635986} +Epoch [3016/4000] Training [1/16] Loss: 0.00224 +Epoch [3016/4000] Training [2/16] Loss: 0.00227 +Epoch [3016/4000] Training [3/16] Loss: 0.00348 +Epoch [3016/4000] Training [4/16] Loss: 0.00277 +Epoch [3016/4000] Training [5/16] Loss: 0.00375 +Epoch [3016/4000] Training [6/16] Loss: 0.00214 +Epoch [3016/4000] Training [7/16] Loss: 0.00365 +Epoch [3016/4000] Training [8/16] Loss: 0.00326 +Epoch [3016/4000] Training [9/16] Loss: 0.00325 +Epoch [3016/4000] Training [10/16] Loss: 0.00193 +Epoch [3016/4000] Training [11/16] Loss: 0.00507 +Epoch [3016/4000] Training [12/16] Loss: 0.00425 +Epoch [3016/4000] Training [13/16] Loss: 0.00318 +Epoch [3016/4000] Training [14/16] Loss: 0.00418 +Epoch [3016/4000] Training [15/16] Loss: 0.00232 +Epoch [3016/4000] Training [16/16] Loss: 0.00285 +Epoch [3016/4000] Training metric {'Train/mean dice_metric': 0.9982811212539673, 'Train/mean miou_metric': 0.9962890148162842, 'Train/mean f1': 0.9934017658233643, 'Train/mean precision': 0.9888061285018921, 'Train/mean recall': 0.9980403184890747, 'Train/mean hd95_metric': 0.781570553779602} +Epoch [3016/4000] Validation [1/4] Loss: 0.38618 focal_loss 0.32156 dice_loss 0.06462 +Epoch [3016/4000] Validation [2/4] Loss: 0.56181 focal_loss 0.43114 dice_loss 0.13066 +Epoch [3016/4000] Validation [3/4] Loss: 0.51915 focal_loss 0.41819 dice_loss 0.10095 +Epoch [3016/4000] Validation [4/4] Loss: 0.37385 focal_loss 0.27037 dice_loss 0.10347 +Epoch [3016/4000] Validation metric {'Val/mean dice_metric': 0.9727083444595337, 'Val/mean miou_metric': 0.9582821726799011, 'Val/mean f1': 0.975729763507843, 'Val/mean precision': 0.9743421077728271, 'Val/mean recall': 0.9771215319633484, 'Val/mean hd95_metric': 5.271656036376953} +Cheakpoint... +Epoch [3016/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727083444595337, 'Val/mean miou_metric': 0.9582821726799011, 'Val/mean f1': 0.975729763507843, 'Val/mean precision': 0.9743421077728271, 'Val/mean recall': 0.9771215319633484, 'Val/mean hd95_metric': 5.271656036376953} +Epoch [3017/4000] Training [1/16] Loss: 0.00227 +Epoch [3017/4000] Training [2/16] Loss: 0.00380 +Epoch [3017/4000] Training [3/16] Loss: 0.00293 +Epoch [3017/4000] Training [4/16] Loss: 0.00233 +Epoch [3017/4000] Training [5/16] Loss: 0.00271 +Epoch [3017/4000] Training [6/16] Loss: 0.00280 +Epoch [3017/4000] Training [7/16] Loss: 0.00299 +Epoch [3017/4000] Training [8/16] Loss: 0.00312 +Epoch [3017/4000] Training [9/16] Loss: 0.00375 +Epoch [3017/4000] Training [10/16] Loss: 0.00286 +Epoch [3017/4000] Training [11/16] Loss: 0.00416 +Epoch [3017/4000] Training [12/16] Loss: 0.00281 +Epoch [3017/4000] Training [13/16] Loss: 0.00341 +Epoch [3017/4000] Training [14/16] Loss: 0.00309 +Epoch [3017/4000] Training [15/16] Loss: 0.00272 +Epoch [3017/4000] Training [16/16] Loss: 0.00256 +Epoch [3017/4000] Training metric {'Train/mean dice_metric': 0.9983358383178711, 'Train/mean miou_metric': 0.9964026212692261, 'Train/mean f1': 0.9935716986656189, 'Train/mean precision': 0.9890719056129456, 'Train/mean recall': 0.998112678527832, 'Train/mean hd95_metric': 0.7534453868865967} +Epoch [3017/4000] Validation [1/4] Loss: 0.33323 focal_loss 0.27474 dice_loss 0.05849 +Epoch [3017/4000] Validation [2/4] Loss: 0.53450 focal_loss 0.40999 dice_loss 0.12452 +Epoch [3017/4000] Validation [3/4] Loss: 0.52394 focal_loss 0.42858 dice_loss 0.09536 +Epoch [3017/4000] Validation [4/4] Loss: 0.26810 focal_loss 0.18553 dice_loss 0.08256 +Epoch [3017/4000] Validation metric {'Val/mean dice_metric': 0.9749467968940735, 'Val/mean miou_metric': 0.960779070854187, 'Val/mean f1': 0.9764957427978516, 'Val/mean precision': 0.9748618006706238, 'Val/mean recall': 0.9781351685523987, 'Val/mean hd95_metric': 5.0221476554870605} +Cheakpoint... +Epoch [3017/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749467968940735, 'Val/mean miou_metric': 0.960779070854187, 'Val/mean f1': 0.9764957427978516, 'Val/mean precision': 0.9748618006706238, 'Val/mean recall': 0.9781351685523987, 'Val/mean hd95_metric': 5.0221476554870605} +Epoch [3018/4000] Training [1/16] Loss: 0.00472 +Epoch [3018/4000] Training [2/16] Loss: 0.00260 +Epoch [3018/4000] Training [3/16] Loss: 0.00346 +Epoch [3018/4000] Training [4/16] Loss: 0.00225 +Epoch [3018/4000] Training [5/16] Loss: 0.00291 +Epoch [3018/4000] Training [6/16] Loss: 0.00385 +Epoch [3018/4000] Training [7/16] Loss: 0.00347 +Epoch [3018/4000] Training [8/16] Loss: 0.00292 +Epoch [3018/4000] Training [9/16] Loss: 0.00372 +Epoch [3018/4000] Training [10/16] Loss: 0.00265 +Epoch [3018/4000] Training [11/16] Loss: 0.00332 +Epoch [3018/4000] Training [12/16] Loss: 0.00409 +Epoch [3018/4000] Training [13/16] Loss: 0.00457 +Epoch [3018/4000] Training [14/16] Loss: 0.00362 +Epoch [3018/4000] Training [15/16] Loss: 0.00429 +Epoch [3018/4000] Training [16/16] Loss: 0.00324 +Epoch [3018/4000] Training metric {'Train/mean dice_metric': 0.998120903968811, 'Train/mean miou_metric': 0.9959388971328735, 'Train/mean f1': 0.9925248622894287, 'Train/mean precision': 0.9873607754707336, 'Train/mean recall': 0.9977432489395142, 'Train/mean hd95_metric': 0.7977756857872009} +Epoch [3018/4000] Validation [1/4] Loss: 0.40953 focal_loss 0.34693 dice_loss 0.06261 +Epoch [3018/4000] Validation [2/4] Loss: 0.55519 focal_loss 0.42249 dice_loss 0.13270 +Epoch [3018/4000] Validation [3/4] Loss: 0.56004 focal_loss 0.46423 dice_loss 0.09581 +Epoch [3018/4000] Validation [4/4] Loss: 0.32199 focal_loss 0.23692 dice_loss 0.08507 +Epoch [3018/4000] Validation metric {'Val/mean dice_metric': 0.9749444127082825, 'Val/mean miou_metric': 0.9604217410087585, 'Val/mean f1': 0.9757559895515442, 'Val/mean precision': 0.9730069041252136, 'Val/mean recall': 0.9785205125808716, 'Val/mean hd95_metric': 5.17125940322876} +Cheakpoint... +Epoch [3018/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749444127082825, 'Val/mean miou_metric': 0.9604217410087585, 'Val/mean f1': 0.9757559895515442, 'Val/mean precision': 0.9730069041252136, 'Val/mean recall': 0.9785205125808716, 'Val/mean hd95_metric': 5.17125940322876} +Epoch [3019/4000] Training [1/16] Loss: 0.00256 +Epoch [3019/4000] Training [2/16] Loss: 0.00395 +Epoch [3019/4000] Training [3/16] Loss: 0.00287 +Epoch [3019/4000] Training [4/16] Loss: 0.00435 +Epoch [3019/4000] Training [5/16] Loss: 0.00479 +Epoch [3019/4000] Training [6/16] Loss: 0.00367 +Epoch [3019/4000] Training [7/16] Loss: 0.00354 +Epoch [3019/4000] Training [8/16] Loss: 0.00361 +Epoch [3019/4000] Training [9/16] Loss: 0.00279 +Epoch [3019/4000] Training [10/16] Loss: 0.00319 +Epoch [3019/4000] Training [11/16] Loss: 0.00211 +Epoch [3019/4000] Training [12/16] Loss: 0.00280 +Epoch [3019/4000] Training [13/16] Loss: 0.00255 +Epoch [3019/4000] Training [14/16] Loss: 0.00321 +Epoch [3019/4000] Training [15/16] Loss: 0.00307 +Epoch [3019/4000] Training [16/16] Loss: 0.00325 +Epoch [3019/4000] Training metric {'Train/mean dice_metric': 0.9983224272727966, 'Train/mean miou_metric': 0.9963766932487488, 'Train/mean f1': 0.9934544563293457, 'Train/mean precision': 0.988968551158905, 'Train/mean recall': 0.9979812502861023, 'Train/mean hd95_metric': 0.7367740869522095} +Epoch [3019/4000] Validation [1/4] Loss: 0.35321 focal_loss 0.29047 dice_loss 0.06274 +Epoch [3019/4000] Validation [2/4] Loss: 1.48880 focal_loss 1.22342 dice_loss 0.26539 +Epoch [3019/4000] Validation [3/4] Loss: 0.25957 focal_loss 0.20057 dice_loss 0.05900 +Epoch [3019/4000] Validation [4/4] Loss: 0.33924 focal_loss 0.22236 dice_loss 0.11687 +Epoch [3019/4000] Validation metric {'Val/mean dice_metric': 0.9722540974617004, 'Val/mean miou_metric': 0.9586118459701538, 'Val/mean f1': 0.9758656024932861, 'Val/mean precision': 0.9734116792678833, 'Val/mean recall': 0.9783316850662231, 'Val/mean hd95_metric': 4.791611671447754} +Cheakpoint... +Epoch [3019/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722540974617004, 'Val/mean miou_metric': 0.9586118459701538, 'Val/mean f1': 0.9758656024932861, 'Val/mean precision': 0.9734116792678833, 'Val/mean recall': 0.9783316850662231, 'Val/mean hd95_metric': 4.791611671447754} +Epoch [3020/4000] Training [1/16] Loss: 0.00327 +Epoch [3020/4000] Training [2/16] Loss: 0.00225 +Epoch [3020/4000] Training [3/16] Loss: 0.00270 +Epoch [3020/4000] Training [4/16] Loss: 0.00328 +Epoch [3020/4000] Training [5/16] Loss: 0.00331 +Epoch [3020/4000] Training [6/16] Loss: 0.00356 +Epoch [3020/4000] Training [7/16] Loss: 0.00352 +Epoch [3020/4000] Training [8/16] Loss: 0.00239 +Epoch [3020/4000] Training [9/16] Loss: 0.00328 +Epoch [3020/4000] Training [10/16] Loss: 0.00316 +Epoch [3020/4000] Training [11/16] Loss: 0.00360 +Epoch [3020/4000] Training [12/16] Loss: 0.00193 +Epoch [3020/4000] Training [13/16] Loss: 0.00210 +Epoch [3020/4000] Training [14/16] Loss: 0.00242 +Epoch [3020/4000] Training [15/16] Loss: 0.00316 +Epoch [3020/4000] Training [16/16] Loss: 0.00251 +Epoch [3020/4000] Training metric {'Train/mean dice_metric': 0.9983182549476624, 'Train/mean miou_metric': 0.9963626861572266, 'Train/mean f1': 0.993337869644165, 'Train/mean precision': 0.9886645078659058, 'Train/mean recall': 0.998055636882782, 'Train/mean hd95_metric': 0.7347933053970337} +Epoch [3020/4000] Validation [1/4] Loss: 0.42330 focal_loss 0.35580 dice_loss 0.06751 +Epoch [3020/4000] Validation [2/4] Loss: 0.87631 focal_loss 0.68887 dice_loss 0.18744 +Epoch [3020/4000] Validation [3/4] Loss: 0.28308 focal_loss 0.20860 dice_loss 0.07447 +Epoch [3020/4000] Validation [4/4] Loss: 0.31647 focal_loss 0.23184 dice_loss 0.08463 +Epoch [3020/4000] Validation metric {'Val/mean dice_metric': 0.9723132848739624, 'Val/mean miou_metric': 0.9579393267631531, 'Val/mean f1': 0.9750192761421204, 'Val/mean precision': 0.9729816317558289, 'Val/mean recall': 0.9770653247833252, 'Val/mean hd95_metric': 5.381871700286865} +Cheakpoint... +Epoch [3020/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723132848739624, 'Val/mean miou_metric': 0.9579393267631531, 'Val/mean f1': 0.9750192761421204, 'Val/mean precision': 0.9729816317558289, 'Val/mean recall': 0.9770653247833252, 'Val/mean hd95_metric': 5.381871700286865} +Epoch [3021/4000] Training [1/16] Loss: 0.00322 +Epoch [3021/4000] Training [2/16] Loss: 0.00295 +Epoch [3021/4000] Training [3/16] Loss: 0.00419 +Epoch [3021/4000] Training [4/16] Loss: 0.00329 +Epoch [3021/4000] Training [5/16] Loss: 0.00262 +Epoch [3021/4000] Training [6/16] Loss: 0.00297 +Epoch [3021/4000] Training [7/16] Loss: 0.00316 +Epoch [3021/4000] Training [8/16] Loss: 0.00332 +Epoch [3021/4000] Training [9/16] Loss: 0.00375 +Epoch [3021/4000] Training [10/16] Loss: 0.00415 +Epoch [3021/4000] Training [11/16] Loss: 0.00338 +Epoch [3021/4000] Training [12/16] Loss: 0.00295 +Epoch [3021/4000] Training [13/16] Loss: 0.00251 +Epoch [3021/4000] Training [14/16] Loss: 0.00329 +Epoch [3021/4000] Training [15/16] Loss: 0.00308 +Epoch [3021/4000] Training [16/16] Loss: 0.00280 +Epoch [3021/4000] Training metric {'Train/mean dice_metric': 0.99814772605896, 'Train/mean miou_metric': 0.9960306882858276, 'Train/mean f1': 0.993366539478302, 'Train/mean precision': 0.9888175129890442, 'Train/mean recall': 0.9979575872421265, 'Train/mean hd95_metric': 0.7933988571166992} +Epoch [3021/4000] Validation [1/4] Loss: 0.40227 focal_loss 0.33671 dice_loss 0.06556 +Epoch [3021/4000] Validation [2/4] Loss: 0.57254 focal_loss 0.43741 dice_loss 0.13513 +Epoch [3021/4000] Validation [3/4] Loss: 0.29033 focal_loss 0.22365 dice_loss 0.06668 +Epoch [3021/4000] Validation [4/4] Loss: 0.43583 focal_loss 0.32898 dice_loss 0.10685 +Epoch [3021/4000] Validation metric {'Val/mean dice_metric': 0.9732152223587036, 'Val/mean miou_metric': 0.9589126706123352, 'Val/mean f1': 0.9754879474639893, 'Val/mean precision': 0.9743980169296265, 'Val/mean recall': 0.9765802621841431, 'Val/mean hd95_metric': 5.019602298736572} +Cheakpoint... +Epoch [3021/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732152223587036, 'Val/mean miou_metric': 0.9589126706123352, 'Val/mean f1': 0.9754879474639893, 'Val/mean precision': 0.9743980169296265, 'Val/mean recall': 0.9765802621841431, 'Val/mean hd95_metric': 5.019602298736572} +Epoch [3022/4000] Training [1/16] Loss: 0.00271 +Epoch [3022/4000] Training [2/16] Loss: 0.00212 +Epoch [3022/4000] Training [3/16] Loss: 0.00504 +Epoch [3022/4000] Training [4/16] Loss: 0.00514 +Epoch [3022/4000] Training [5/16] Loss: 0.00212 +Epoch [3022/4000] Training [6/16] Loss: 0.00266 +Epoch [3022/4000] Training [7/16] Loss: 0.00324 +Epoch [3022/4000] Training [8/16] Loss: 0.00369 +Epoch [3022/4000] Training [9/16] Loss: 0.00262 +Epoch [3022/4000] Training [10/16] Loss: 0.00286 +Epoch [3022/4000] Training [11/16] Loss: 0.00322 +Epoch [3022/4000] Training [12/16] Loss: 0.00320 +Epoch [3022/4000] Training [13/16] Loss: 0.00318 +Epoch [3022/4000] Training [14/16] Loss: 0.00310 +Epoch [3022/4000] Training [15/16] Loss: 0.00236 +Epoch [3022/4000] Training [16/16] Loss: 0.00335 +Epoch [3022/4000] Training metric {'Train/mean dice_metric': 0.9982028603553772, 'Train/mean miou_metric': 0.9961405992507935, 'Train/mean f1': 0.9934064149856567, 'Train/mean precision': 0.9889618754386902, 'Train/mean recall': 0.9978910684585571, 'Train/mean hd95_metric': 0.7441682815551758} +Epoch [3022/4000] Validation [1/4] Loss: 0.40347 focal_loss 0.33356 dice_loss 0.06991 +Epoch [3022/4000] Validation [2/4] Loss: 1.11945 focal_loss 0.92822 dice_loss 0.19124 +Epoch [3022/4000] Validation [3/4] Loss: 0.49732 focal_loss 0.40071 dice_loss 0.09661 +Epoch [3022/4000] Validation [4/4] Loss: 0.42944 focal_loss 0.31162 dice_loss 0.11782 +Epoch [3022/4000] Validation metric {'Val/mean dice_metric': 0.9703952074050903, 'Val/mean miou_metric': 0.9567391276359558, 'Val/mean f1': 0.9751275181770325, 'Val/mean precision': 0.9746485948562622, 'Val/mean recall': 0.9756069183349609, 'Val/mean hd95_metric': 4.983057975769043} +Cheakpoint... +Epoch [3022/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9703952074050903, 'Val/mean miou_metric': 0.9567391276359558, 'Val/mean f1': 0.9751275181770325, 'Val/mean precision': 0.9746485948562622, 'Val/mean recall': 0.9756069183349609, 'Val/mean hd95_metric': 4.983057975769043} +Epoch [3023/4000] Training [1/16] Loss: 0.00291 +Epoch [3023/4000] Training [2/16] Loss: 0.00322 +Epoch [3023/4000] Training [3/16] Loss: 0.00320 +Epoch [3023/4000] Training [4/16] Loss: 0.00268 +Epoch [3023/4000] Training [5/16] Loss: 0.00278 +Epoch [3023/4000] Training [6/16] Loss: 0.00383 +Epoch [3023/4000] Training [7/16] Loss: 0.00209 +Epoch [3023/4000] Training [8/16] Loss: 0.00245 +Epoch [3023/4000] Training [9/16] Loss: 0.00250 +Epoch [3023/4000] Training [10/16] Loss: 0.00320 +Epoch [3023/4000] Training [11/16] Loss: 0.00294 +Epoch [3023/4000] Training [12/16] Loss: 0.00477 +Epoch [3023/4000] Training [13/16] Loss: 0.00289 +Epoch [3023/4000] Training [14/16] Loss: 0.00406 +Epoch [3023/4000] Training [15/16] Loss: 0.00278 +Epoch [3023/4000] Training [16/16] Loss: 0.00299 +Epoch [3023/4000] Training metric {'Train/mean dice_metric': 0.998267650604248, 'Train/mean miou_metric': 0.9962667226791382, 'Train/mean f1': 0.993364155292511, 'Train/mean precision': 0.988827109336853, 'Train/mean recall': 0.9979430437088013, 'Train/mean hd95_metric': 0.7247068881988525} +Epoch [3023/4000] Validation [1/4] Loss: 0.42240 focal_loss 0.35415 dice_loss 0.06825 +Epoch [3023/4000] Validation [2/4] Loss: 0.53426 focal_loss 0.40579 dice_loss 0.12847 +Epoch [3023/4000] Validation [3/4] Loss: 0.50387 focal_loss 0.41244 dice_loss 0.09143 +Epoch [3023/4000] Validation [4/4] Loss: 0.31472 focal_loss 0.22958 dice_loss 0.08514 +Epoch [3023/4000] Validation metric {'Val/mean dice_metric': 0.9733244776725769, 'Val/mean miou_metric': 0.9591938257217407, 'Val/mean f1': 0.9759558439254761, 'Val/mean precision': 0.9739537239074707, 'Val/mean recall': 0.9779661893844604, 'Val/mean hd95_metric': 4.855252265930176} +Cheakpoint... +Epoch [3023/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733244776725769, 'Val/mean miou_metric': 0.9591938257217407, 'Val/mean f1': 0.9759558439254761, 'Val/mean precision': 0.9739537239074707, 'Val/mean recall': 0.9779661893844604, 'Val/mean hd95_metric': 4.855252265930176} +Epoch [3024/4000] Training [1/16] Loss: 0.00276 +Epoch [3024/4000] Training [2/16] Loss: 0.00235 +Epoch [3024/4000] Training [3/16] Loss: 0.00220 +Epoch [3024/4000] Training [4/16] Loss: 0.00282 +Epoch [3024/4000] Training [5/16] Loss: 0.00257 +Epoch [3024/4000] Training [6/16] Loss: 0.00328 +Epoch [3024/4000] Training [7/16] Loss: 0.00426 +Epoch [3024/4000] Training [8/16] Loss: 0.00316 +Epoch [3024/4000] Training [9/16] Loss: 0.00350 +Epoch [3024/4000] Training [10/16] Loss: 0.00278 +Epoch [3024/4000] Training [11/16] Loss: 0.00290 +Epoch [3024/4000] Training [12/16] Loss: 0.00305 +Epoch [3024/4000] Training [13/16] Loss: 0.00371 +Epoch [3024/4000] Training [14/16] Loss: 0.00406 +Epoch [3024/4000] Training [15/16] Loss: 0.00272 +Epoch [3024/4000] Training [16/16] Loss: 0.00249 +Epoch [3024/4000] Training metric {'Train/mean dice_metric': 0.9982718229293823, 'Train/mean miou_metric': 0.9962739944458008, 'Train/mean f1': 0.993401050567627, 'Train/mean precision': 0.9888405203819275, 'Train/mean recall': 0.9980037808418274, 'Train/mean hd95_metric': 0.7538917064666748} +Epoch [3024/4000] Validation [1/4] Loss: 0.39927 focal_loss 0.33402 dice_loss 0.06525 +Epoch [3024/4000] Validation [2/4] Loss: 0.92920 focal_loss 0.70284 dice_loss 0.22636 +Epoch [3024/4000] Validation [3/4] Loss: 0.25066 focal_loss 0.18887 dice_loss 0.06179 +Epoch [3024/4000] Validation [4/4] Loss: 0.30398 focal_loss 0.21841 dice_loss 0.08557 +Epoch [3024/4000] Validation metric {'Val/mean dice_metric': 0.9740371704101562, 'Val/mean miou_metric': 0.9600151777267456, 'Val/mean f1': 0.9760037660598755, 'Val/mean precision': 0.9742217063903809, 'Val/mean recall': 0.9777924418449402, 'Val/mean hd95_metric': 5.019350528717041} +Cheakpoint... +Epoch [3024/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740371704101562, 'Val/mean miou_metric': 0.9600151777267456, 'Val/mean f1': 0.9760037660598755, 'Val/mean precision': 0.9742217063903809, 'Val/mean recall': 0.9777924418449402, 'Val/mean hd95_metric': 5.019350528717041} +Epoch [3025/4000] Training [1/16] Loss: 0.00229 +Epoch [3025/4000] Training [2/16] Loss: 0.00428 +Epoch [3025/4000] Training [3/16] Loss: 0.00329 +Epoch [3025/4000] Training [4/16] Loss: 0.00359 +Epoch [3025/4000] Training [5/16] Loss: 0.00300 +Epoch [3025/4000] Training [6/16] Loss: 0.00360 +Epoch [3025/4000] Training [7/16] Loss: 0.00205 +Epoch [3025/4000] Training [8/16] Loss: 0.00215 +Epoch [3025/4000] Training [9/16] Loss: 0.00422 +Epoch [3025/4000] Training [10/16] Loss: 0.00291 +Epoch [3025/4000] Training [11/16] Loss: 0.00258 +Epoch [3025/4000] Training [12/16] Loss: 0.00417 +Epoch [3025/4000] Training [13/16] Loss: 0.00387 +Epoch [3025/4000] Training [14/16] Loss: 0.00297 +Epoch [3025/4000] Training [15/16] Loss: 0.00257 +Epoch [3025/4000] Training [16/16] Loss: 0.00306 +Epoch [3025/4000] Training metric {'Train/mean dice_metric': 0.9982547760009766, 'Train/mean miou_metric': 0.99624103307724, 'Train/mean f1': 0.9934545755386353, 'Train/mean precision': 0.9888845682144165, 'Train/mean recall': 0.9980669617652893, 'Train/mean hd95_metric': 0.7589840888977051} +Epoch [3025/4000] Validation [1/4] Loss: 0.41516 focal_loss 0.34901 dice_loss 0.06616 +Epoch [3025/4000] Validation [2/4] Loss: 1.08928 focal_loss 0.89189 dice_loss 0.19739 +Epoch [3025/4000] Validation [3/4] Loss: 0.47267 focal_loss 0.37447 dice_loss 0.09821 +Epoch [3025/4000] Validation [4/4] Loss: 0.30711 focal_loss 0.21217 dice_loss 0.09494 +Epoch [3025/4000] Validation metric {'Val/mean dice_metric': 0.9724999666213989, 'Val/mean miou_metric': 0.9587261080741882, 'Val/mean f1': 0.9759538769721985, 'Val/mean precision': 0.973917543888092, 'Val/mean recall': 0.977998673915863, 'Val/mean hd95_metric': 4.901778221130371} +Cheakpoint... +Epoch [3025/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724999666213989, 'Val/mean miou_metric': 0.9587261080741882, 'Val/mean f1': 0.9759538769721985, 'Val/mean precision': 0.973917543888092, 'Val/mean recall': 0.977998673915863, 'Val/mean hd95_metric': 4.901778221130371} +Epoch [3026/4000] Training [1/16] Loss: 0.00328 +Epoch [3026/4000] Training [2/16] Loss: 0.00420 +Epoch [3026/4000] Training [3/16] Loss: 0.00268 +Epoch [3026/4000] Training [4/16] Loss: 0.00283 +Epoch [3026/4000] Training [5/16] Loss: 0.00244 +Epoch [3026/4000] Training [6/16] Loss: 0.00285 +Epoch [3026/4000] Training [7/16] Loss: 0.00489 +Epoch [3026/4000] Training [8/16] Loss: 0.00616 +Epoch [3026/4000] Training [9/16] Loss: 0.00450 +Epoch [3026/4000] Training [10/16] Loss: 0.00354 +Epoch [3026/4000] Training [11/16] Loss: 0.00446 +Epoch [3026/4000] Training [12/16] Loss: 0.00397 +Epoch [3026/4000] Training [13/16] Loss: 0.00281 +Epoch [3026/4000] Training [14/16] Loss: 0.00208 +Epoch [3026/4000] Training [15/16] Loss: 0.00291 +Epoch [3026/4000] Training [16/16] Loss: 0.00281 +Epoch [3026/4000] Training metric {'Train/mean dice_metric': 0.9981537461280823, 'Train/mean miou_metric': 0.9960161447525024, 'Train/mean f1': 0.99308842420578, 'Train/mean precision': 0.9883896112442017, 'Train/mean recall': 0.9978320598602295, 'Train/mean hd95_metric': 0.7622067332267761} +Epoch [3026/4000] Validation [1/4] Loss: 0.44234 focal_loss 0.37605 dice_loss 0.06629 +Epoch [3026/4000] Validation [2/4] Loss: 0.91954 focal_loss 0.69516 dice_loss 0.22438 +Epoch [3026/4000] Validation [3/4] Loss: 0.49116 focal_loss 0.40200 dice_loss 0.08916 +Epoch [3026/4000] Validation [4/4] Loss: 0.33924 focal_loss 0.24311 dice_loss 0.09613 +Epoch [3026/4000] Validation metric {'Val/mean dice_metric': 0.9712444543838501, 'Val/mean miou_metric': 0.9572309255599976, 'Val/mean f1': 0.9751716256141663, 'Val/mean precision': 0.9739221334457397, 'Val/mean recall': 0.9764242172241211, 'Val/mean hd95_metric': 5.410348892211914} +Cheakpoint... +Epoch [3026/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712444543838501, 'Val/mean miou_metric': 0.9572309255599976, 'Val/mean f1': 0.9751716256141663, 'Val/mean precision': 0.9739221334457397, 'Val/mean recall': 0.9764242172241211, 'Val/mean hd95_metric': 5.410348892211914} +Epoch [3027/4000] Training [1/16] Loss: 0.00326 +Epoch [3027/4000] Training [2/16] Loss: 0.00305 +Epoch [3027/4000] Training [3/16] Loss: 0.00643 +Epoch [3027/4000] Training [4/16] Loss: 0.00286 +Epoch [3027/4000] Training [5/16] Loss: 0.00227 +Epoch [3027/4000] Training [6/16] Loss: 0.00460 +Epoch [3027/4000] Training [7/16] Loss: 0.00332 +Epoch [3027/4000] Training [8/16] Loss: 0.00268 +Epoch [3027/4000] Training [9/16] Loss: 0.00243 +Epoch [3027/4000] Training [10/16] Loss: 0.00513 +Epoch [3027/4000] Training [11/16] Loss: 0.00204 +Epoch [3027/4000] Training [12/16] Loss: 0.00248 +Epoch [3027/4000] Training [13/16] Loss: 0.00267 +Epoch [3027/4000] Training [14/16] Loss: 0.00408 +Epoch [3027/4000] Training [15/16] Loss: 0.00352 +Epoch [3027/4000] Training [16/16] Loss: 0.00396 +Epoch [3027/4000] Training metric {'Train/mean dice_metric': 0.9980024099349976, 'Train/mean miou_metric': 0.9957385659217834, 'Train/mean f1': 0.9931964874267578, 'Train/mean precision': 0.9885225892066956, 'Train/mean recall': 0.9979147911071777, 'Train/mean hd95_metric': 0.7700749635696411} +Epoch [3027/4000] Validation [1/4] Loss: 0.38484 focal_loss 0.32021 dice_loss 0.06464 +Epoch [3027/4000] Validation [2/4] Loss: 0.49770 focal_loss 0.37515 dice_loss 0.12255 +Epoch [3027/4000] Validation [3/4] Loss: 0.53812 focal_loss 0.44205 dice_loss 0.09607 +Epoch [3027/4000] Validation [4/4] Loss: 0.47929 focal_loss 0.36057 dice_loss 0.11871 +Epoch [3027/4000] Validation metric {'Val/mean dice_metric': 0.9729348421096802, 'Val/mean miou_metric': 0.9584556818008423, 'Val/mean f1': 0.9751087427139282, 'Val/mean precision': 0.9732863903045654, 'Val/mean recall': 0.9769380688667297, 'Val/mean hd95_metric': 5.391272068023682} +Cheakpoint... +Epoch [3027/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729348421096802, 'Val/mean miou_metric': 0.9584556818008423, 'Val/mean f1': 0.9751087427139282, 'Val/mean precision': 0.9732863903045654, 'Val/mean recall': 0.9769380688667297, 'Val/mean hd95_metric': 5.391272068023682} +Epoch [3028/4000] Training [1/16] Loss: 0.00338 +Epoch [3028/4000] Training [2/16] Loss: 0.00305 +Epoch [3028/4000] Training [3/16] Loss: 0.00437 +Epoch [3028/4000] Training [4/16] Loss: 0.00286 +Epoch [3028/4000] Training [5/16] Loss: 0.00278 +Epoch [3028/4000] Training [6/16] Loss: 0.00206 +Epoch [3028/4000] Training [7/16] Loss: 0.00421 +Epoch [3028/4000] Training [8/16] Loss: 0.00289 +Epoch [3028/4000] Training [9/16] Loss: 0.00333 +Epoch [3028/4000] Training [10/16] Loss: 0.00354 +Epoch [3028/4000] Training [11/16] Loss: 0.00343 +Epoch [3028/4000] Training [12/16] Loss: 0.00312 +Epoch [3028/4000] Training [13/16] Loss: 0.00347 +Epoch [3028/4000] Training [14/16] Loss: 0.00287 +Epoch [3028/4000] Training [15/16] Loss: 0.00329 +Epoch [3028/4000] Training [16/16] Loss: 0.00434 +Epoch [3028/4000] Training metric {'Train/mean dice_metric': 0.9981981515884399, 'Train/mean miou_metric': 0.996128499507904, 'Train/mean f1': 0.9933550953865051, 'Train/mean precision': 0.9888401627540588, 'Train/mean recall': 0.9979113936424255, 'Train/mean hd95_metric': 0.75657057762146} +Epoch [3028/4000] Validation [1/4] Loss: 0.41431 focal_loss 0.34928 dice_loss 0.06504 +Epoch [3028/4000] Validation [2/4] Loss: 0.48306 focal_loss 0.36474 dice_loss 0.11832 +Epoch [3028/4000] Validation [3/4] Loss: 0.49917 focal_loss 0.40866 dice_loss 0.09051 +Epoch [3028/4000] Validation [4/4] Loss: 0.34466 focal_loss 0.24595 dice_loss 0.09871 +Epoch [3028/4000] Validation metric {'Val/mean dice_metric': 0.9736081957817078, 'Val/mean miou_metric': 0.959420382976532, 'Val/mean f1': 0.9761040210723877, 'Val/mean precision': 0.9743949770927429, 'Val/mean recall': 0.9778189659118652, 'Val/mean hd95_metric': 4.887476921081543} +Cheakpoint... +Epoch [3028/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736081957817078, 'Val/mean miou_metric': 0.959420382976532, 'Val/mean f1': 0.9761040210723877, 'Val/mean precision': 0.9743949770927429, 'Val/mean recall': 0.9778189659118652, 'Val/mean hd95_metric': 4.887476921081543} +Epoch [3029/4000] Training [1/16] Loss: 0.00537 +Epoch [3029/4000] Training [2/16] Loss: 0.00347 +Epoch [3029/4000] Training [3/16] Loss: 0.00311 +Epoch [3029/4000] Training [4/16] Loss: 0.00565 +Epoch [3029/4000] Training [5/16] Loss: 0.00381 +Epoch [3029/4000] Training [6/16] Loss: 0.00268 +Epoch [3029/4000] Training [7/16] Loss: 0.00462 +Epoch [3029/4000] Training [8/16] Loss: 0.00326 +Epoch [3029/4000] Training [9/16] Loss: 0.00321 +Epoch [3029/4000] Training [10/16] Loss: 0.00297 +Epoch [3029/4000] Training [11/16] Loss: 0.00350 +Epoch [3029/4000] Training [12/16] Loss: 0.00221 +Epoch [3029/4000] Training [13/16] Loss: 0.00347 +Epoch [3029/4000] Training [14/16] Loss: 0.00291 +Epoch [3029/4000] Training [15/16] Loss: 0.00255 +Epoch [3029/4000] Training [16/16] Loss: 0.00257 +Epoch [3029/4000] Training metric {'Train/mean dice_metric': 0.9981144070625305, 'Train/mean miou_metric': 0.9959267973899841, 'Train/mean f1': 0.9929683208465576, 'Train/mean precision': 0.9881671071052551, 'Train/mean recall': 0.9978164434432983, 'Train/mean hd95_metric': 0.7880159616470337} +Epoch [3029/4000] Validation [1/4] Loss: 0.41522 focal_loss 0.34570 dice_loss 0.06951 +Epoch [3029/4000] Validation [2/4] Loss: 1.14170 focal_loss 0.95002 dice_loss 0.19168 +Epoch [3029/4000] Validation [3/4] Loss: 0.52510 focal_loss 0.43000 dice_loss 0.09509 +Epoch [3029/4000] Validation [4/4] Loss: 0.39455 focal_loss 0.28782 dice_loss 0.10672 +Epoch [3029/4000] Validation metric {'Val/mean dice_metric': 0.9721590280532837, 'Val/mean miou_metric': 0.9579179883003235, 'Val/mean f1': 0.975579023361206, 'Val/mean precision': 0.9742205739021301, 'Val/mean recall': 0.9769411683082581, 'Val/mean hd95_metric': 5.456209659576416} +Cheakpoint... +Epoch [3029/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721590280532837, 'Val/mean miou_metric': 0.9579179883003235, 'Val/mean f1': 0.975579023361206, 'Val/mean precision': 0.9742205739021301, 'Val/mean recall': 0.9769411683082581, 'Val/mean hd95_metric': 5.456209659576416} +Epoch [3030/4000] Training [1/16] Loss: 0.00223 +Epoch [3030/4000] Training [2/16] Loss: 0.00292 +Epoch [3030/4000] Training [3/16] Loss: 0.00409 +Epoch [3030/4000] Training [4/16] Loss: 0.00296 +Epoch [3030/4000] Training [5/16] Loss: 0.00355 +Epoch [3030/4000] Training [6/16] Loss: 0.00380 +Epoch [3030/4000] Training [7/16] Loss: 0.00285 +Epoch [3030/4000] Training [8/16] Loss: 0.00304 +Epoch [3030/4000] Training [9/16] Loss: 0.00396 +Epoch [3030/4000] Training [10/16] Loss: 0.00282 +Epoch [3030/4000] Training [11/16] Loss: 0.00329 +Epoch [3030/4000] Training [12/16] Loss: 0.00263 +Epoch [3030/4000] Training [13/16] Loss: 0.00207 +Epoch [3030/4000] Training [14/16] Loss: 0.00337 +Epoch [3030/4000] Training [15/16] Loss: 0.00274 +Epoch [3030/4000] Training [16/16] Loss: 0.00299 +Epoch [3030/4000] Training metric {'Train/mean dice_metric': 0.9981355667114258, 'Train/mean miou_metric': 0.9959982633590698, 'Train/mean f1': 0.9931426048278809, 'Train/mean precision': 0.9884759187698364, 'Train/mean recall': 0.9978535175323486, 'Train/mean hd95_metric': 0.7639224529266357} +Epoch [3030/4000] Validation [1/4] Loss: 0.40367 focal_loss 0.33867 dice_loss 0.06500 +Epoch [3030/4000] Validation [2/4] Loss: 0.54692 focal_loss 0.41405 dice_loss 0.13287 +Epoch [3030/4000] Validation [3/4] Loss: 0.45729 focal_loss 0.36353 dice_loss 0.09376 +Epoch [3030/4000] Validation [4/4] Loss: 0.31484 focal_loss 0.23092 dice_loss 0.08392 +Epoch [3030/4000] Validation metric {'Val/mean dice_metric': 0.9735886454582214, 'Val/mean miou_metric': 0.9593709707260132, 'Val/mean f1': 0.9758926033973694, 'Val/mean precision': 0.9738949537277222, 'Val/mean recall': 0.9778985381126404, 'Val/mean hd95_metric': 4.886534690856934} +Cheakpoint... +Epoch [3030/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735886454582214, 'Val/mean miou_metric': 0.9593709707260132, 'Val/mean f1': 0.9758926033973694, 'Val/mean precision': 0.9738949537277222, 'Val/mean recall': 0.9778985381126404, 'Val/mean hd95_metric': 4.886534690856934} +Epoch [3031/4000] Training [1/16] Loss: 0.00272 +Epoch [3031/4000] Training [2/16] Loss: 0.00300 +Epoch [3031/4000] Training [3/16] Loss: 0.00301 +Epoch [3031/4000] Training [4/16] Loss: 0.00459 +Epoch [3031/4000] Training [5/16] Loss: 0.00279 +Epoch [3031/4000] Training [6/16] Loss: 0.00418 +Epoch [3031/4000] Training [7/16] Loss: 0.00369 +Epoch [3031/4000] Training [8/16] Loss: 0.00345 +Epoch [3031/4000] Training [9/16] Loss: 0.00240 +Epoch [3031/4000] Training [10/16] Loss: 0.00343 +Epoch [3031/4000] Training [11/16] Loss: 0.00243 +Epoch [3031/4000] Training [12/16] Loss: 0.00183 +Epoch [3031/4000] Training [13/16] Loss: 0.00254 +Epoch [3031/4000] Training [14/16] Loss: 0.00292 +Epoch [3031/4000] Training [15/16] Loss: 0.00363 +Epoch [3031/4000] Training [16/16] Loss: 0.00331 +Epoch [3031/4000] Training metric {'Train/mean dice_metric': 0.9982581734657288, 'Train/mean miou_metric': 0.9962480068206787, 'Train/mean f1': 0.993442952632904, 'Train/mean precision': 0.988934338092804, 'Train/mean recall': 0.9979929327964783, 'Train/mean hd95_metric': 0.7671648263931274} +Epoch [3031/4000] Validation [1/4] Loss: 0.44997 focal_loss 0.38304 dice_loss 0.06693 +Epoch [3031/4000] Validation [2/4] Loss: 0.53529 focal_loss 0.40426 dice_loss 0.13103 +Epoch [3031/4000] Validation [3/4] Loss: 0.52981 focal_loss 0.43555 dice_loss 0.09426 +Epoch [3031/4000] Validation [4/4] Loss: 0.31437 focal_loss 0.22593 dice_loss 0.08845 +Epoch [3031/4000] Validation metric {'Val/mean dice_metric': 0.9726904034614563, 'Val/mean miou_metric': 0.9579870104789734, 'Val/mean f1': 0.9755674004554749, 'Val/mean precision': 0.9739647507667542, 'Val/mean recall': 0.9771754145622253, 'Val/mean hd95_metric': 5.5582194328308105} +Cheakpoint... +Epoch [3031/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726904034614563, 'Val/mean miou_metric': 0.9579870104789734, 'Val/mean f1': 0.9755674004554749, 'Val/mean precision': 0.9739647507667542, 'Val/mean recall': 0.9771754145622253, 'Val/mean hd95_metric': 5.5582194328308105} +Epoch [3032/4000] Training [1/16] Loss: 0.00302 +Epoch [3032/4000] Training [2/16] Loss: 0.00298 +Epoch [3032/4000] Training [3/16] Loss: 0.00258 +Epoch [3032/4000] Training [4/16] Loss: 0.00281 +Epoch [3032/4000] Training [5/16] Loss: 0.00247 +Epoch [3032/4000] Training [6/16] Loss: 0.00324 +Epoch [3032/4000] Training [7/16] Loss: 0.00425 +Epoch [3032/4000] Training [8/16] Loss: 0.00284 +Epoch [3032/4000] Training [9/16] Loss: 0.00230 +Epoch [3032/4000] Training [10/16] Loss: 0.00279 +Epoch [3032/4000] Training [11/16] Loss: 0.00253 +Epoch [3032/4000] Training [12/16] Loss: 0.00327 +Epoch [3032/4000] Training [13/16] Loss: 0.00276 +Epoch [3032/4000] Training [14/16] Loss: 0.00291 +Epoch [3032/4000] Training [15/16] Loss: 0.00379 +Epoch [3032/4000] Training [16/16] Loss: 0.00380 +Epoch [3032/4000] Training metric {'Train/mean dice_metric': 0.9983235597610474, 'Train/mean miou_metric': 0.9963663220405579, 'Train/mean f1': 0.9934486746788025, 'Train/mean precision': 0.9888942837715149, 'Train/mean recall': 0.9980452656745911, 'Train/mean hd95_metric': 0.741043210029602} +Epoch [3032/4000] Validation [1/4] Loss: 0.39595 focal_loss 0.33267 dice_loss 0.06328 +Epoch [3032/4000] Validation [2/4] Loss: 1.20205 focal_loss 1.00502 dice_loss 0.19703 +Epoch [3032/4000] Validation [3/4] Loss: 0.54480 focal_loss 0.44807 dice_loss 0.09672 +Epoch [3032/4000] Validation [4/4] Loss: 0.33573 focal_loss 0.24487 dice_loss 0.09086 +Epoch [3032/4000] Validation metric {'Val/mean dice_metric': 0.973300576210022, 'Val/mean miou_metric': 0.9591060876846313, 'Val/mean f1': 0.9758702516555786, 'Val/mean precision': 0.9743874669075012, 'Val/mean recall': 0.9773575663566589, 'Val/mean hd95_metric': 4.975249767303467} +Cheakpoint... +Epoch [3032/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973300576210022, 'Val/mean miou_metric': 0.9591060876846313, 'Val/mean f1': 0.9758702516555786, 'Val/mean precision': 0.9743874669075012, 'Val/mean recall': 0.9773575663566589, 'Val/mean hd95_metric': 4.975249767303467} +Epoch [3033/4000] Training [1/16] Loss: 0.00280 +Epoch [3033/4000] Training [2/16] Loss: 0.00264 +Epoch [3033/4000] Training [3/16] Loss: 0.00325 +Epoch [3033/4000] Training [4/16] Loss: 0.00526 +Epoch [3033/4000] Training [5/16] Loss: 0.00274 +Epoch [3033/4000] Training [6/16] Loss: 0.00280 +Epoch [3033/4000] Training [7/16] Loss: 0.00313 +Epoch [3033/4000] Training [8/16] Loss: 0.00286 +Epoch [3033/4000] Training [9/16] Loss: 0.00283 +Epoch [3033/4000] Training [10/16] Loss: 0.00241 +Epoch [3033/4000] Training [11/16] Loss: 0.00279 +Epoch [3033/4000] Training [12/16] Loss: 0.00254 +Epoch [3033/4000] Training [13/16] Loss: 0.00258 +Epoch [3033/4000] Training [14/16] Loss: 0.00344 +Epoch [3033/4000] Training [15/16] Loss: 0.00379 +Epoch [3033/4000] Training [16/16] Loss: 0.00205 +Epoch [3033/4000] Training metric {'Train/mean dice_metric': 0.9982388019561768, 'Train/mean miou_metric': 0.9962028861045837, 'Train/mean f1': 0.9932718276977539, 'Train/mean precision': 0.9885822534561157, 'Train/mean recall': 0.9980061054229736, 'Train/mean hd95_metric': 0.7480398416519165} +Epoch [3033/4000] Validation [1/4] Loss: 0.39312 focal_loss 0.32879 dice_loss 0.06433 +Epoch [3033/4000] Validation [2/4] Loss: 0.48550 focal_loss 0.36719 dice_loss 0.11831 +Epoch [3033/4000] Validation [3/4] Loss: 0.45314 focal_loss 0.35503 dice_loss 0.09810 +Epoch [3033/4000] Validation [4/4] Loss: 0.33682 focal_loss 0.24482 dice_loss 0.09200 +Epoch [3033/4000] Validation metric {'Val/mean dice_metric': 0.9732085466384888, 'Val/mean miou_metric': 0.9590669870376587, 'Val/mean f1': 0.9757489562034607, 'Val/mean precision': 0.9739294648170471, 'Val/mean recall': 0.9775751829147339, 'Val/mean hd95_metric': 4.993514537811279} +Cheakpoint... +Epoch [3033/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732085466384888, 'Val/mean miou_metric': 0.9590669870376587, 'Val/mean f1': 0.9757489562034607, 'Val/mean precision': 0.9739294648170471, 'Val/mean recall': 0.9775751829147339, 'Val/mean hd95_metric': 4.993514537811279} +Epoch [3034/4000] Training [1/16] Loss: 0.00237 +Epoch [3034/4000] Training [2/16] Loss: 0.00339 +Epoch [3034/4000] Training [3/16] Loss: 0.00236 +Epoch [3034/4000] Training [4/16] Loss: 0.00197 +Epoch [3034/4000] Training [5/16] Loss: 0.00307 +Epoch [3034/4000] Training [6/16] Loss: 0.00373 +Epoch [3034/4000] Training [7/16] Loss: 0.00319 +Epoch [3034/4000] Training [8/16] Loss: 0.00290 +Epoch [3034/4000] Training [9/16] Loss: 0.00336 +Epoch [3034/4000] Training [10/16] Loss: 0.00331 +Epoch [3034/4000] Training [11/16] Loss: 0.00283 +Epoch [3034/4000] Training [12/16] Loss: 0.00436 +Epoch [3034/4000] Training [13/16] Loss: 0.00295 +Epoch [3034/4000] Training [14/16] Loss: 0.00276 +Epoch [3034/4000] Training [15/16] Loss: 0.00306 +Epoch [3034/4000] Training [16/16] Loss: 0.00367 +Epoch [3034/4000] Training metric {'Train/mean dice_metric': 0.9982377290725708, 'Train/mean miou_metric': 0.9962038993835449, 'Train/mean f1': 0.9934159517288208, 'Train/mean precision': 0.9889101982116699, 'Train/mean recall': 0.9979629516601562, 'Train/mean hd95_metric': 0.7634106278419495} +Epoch [3034/4000] Validation [1/4] Loss: 0.37453 focal_loss 0.31224 dice_loss 0.06229 +Epoch [3034/4000] Validation [2/4] Loss: 1.33587 focal_loss 1.07825 dice_loss 0.25762 +Epoch [3034/4000] Validation [3/4] Loss: 0.50283 focal_loss 0.41224 dice_loss 0.09059 +Epoch [3034/4000] Validation [4/4] Loss: 0.58661 focal_loss 0.43914 dice_loss 0.14748 +Epoch [3034/4000] Validation metric {'Val/mean dice_metric': 0.9725240468978882, 'Val/mean miou_metric': 0.9579825401306152, 'Val/mean f1': 0.9754911661148071, 'Val/mean precision': 0.9730777144432068, 'Val/mean recall': 0.9779167175292969, 'Val/mean hd95_metric': 5.234872341156006} +Cheakpoint... +Epoch [3034/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725240468978882, 'Val/mean miou_metric': 0.9579825401306152, 'Val/mean f1': 0.9754911661148071, 'Val/mean precision': 0.9730777144432068, 'Val/mean recall': 0.9779167175292969, 'Val/mean hd95_metric': 5.234872341156006} +Epoch [3035/4000] Training [1/16] Loss: 0.00435 +Epoch [3035/4000] Training [2/16] Loss: 0.00347 +Epoch [3035/4000] Training [3/16] Loss: 0.00375 +Epoch [3035/4000] Training [4/16] Loss: 0.00281 +Epoch [3035/4000] Training [5/16] Loss: 0.00289 +Epoch [3035/4000] Training [6/16] Loss: 0.00275 +Epoch [3035/4000] Training [7/16] Loss: 0.00253 +Epoch [3035/4000] Training [8/16] Loss: 0.00391 +Epoch [3035/4000] Training [9/16] Loss: 0.00334 +Epoch [3035/4000] Training [10/16] Loss: 0.00301 +Epoch [3035/4000] Training [11/16] Loss: 0.00335 +Epoch [3035/4000] Training [12/16] Loss: 0.00342 +Epoch [3035/4000] Training [13/16] Loss: 0.00323 +Epoch [3035/4000] Training [14/16] Loss: 0.00287 +Epoch [3035/4000] Training [15/16] Loss: 0.00300 +Epoch [3035/4000] Training [16/16] Loss: 0.00361 +Epoch [3035/4000] Training metric {'Train/mean dice_metric': 0.9982326030731201, 'Train/mean miou_metric': 0.9961780905723572, 'Train/mean f1': 0.9931920766830444, 'Train/mean precision': 0.9885092973709106, 'Train/mean recall': 0.9979194402694702, 'Train/mean hd95_metric': 0.7647736072540283} +Epoch [3035/4000] Validation [1/4] Loss: 0.36631 focal_loss 0.30192 dice_loss 0.06439 +Epoch [3035/4000] Validation [2/4] Loss: 1.02232 focal_loss 0.83030 dice_loss 0.19202 +Epoch [3035/4000] Validation [3/4] Loss: 0.44484 focal_loss 0.35157 dice_loss 0.09326 +Epoch [3035/4000] Validation [4/4] Loss: 0.31162 focal_loss 0.22441 dice_loss 0.08721 +Epoch [3035/4000] Validation metric {'Val/mean dice_metric': 0.9734214544296265, 'Val/mean miou_metric': 0.9596264958381653, 'Val/mean f1': 0.9759442210197449, 'Val/mean precision': 0.9734518527984619, 'Val/mean recall': 0.9784493446350098, 'Val/mean hd95_metric': 4.880038261413574} +Cheakpoint... +Epoch [3035/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734214544296265, 'Val/mean miou_metric': 0.9596264958381653, 'Val/mean f1': 0.9759442210197449, 'Val/mean precision': 0.9734518527984619, 'Val/mean recall': 0.9784493446350098, 'Val/mean hd95_metric': 4.880038261413574} +Epoch [3036/4000] Training [1/16] Loss: 0.00376 +Epoch [3036/4000] Training [2/16] Loss: 0.00245 +Epoch [3036/4000] Training [3/16] Loss: 0.00255 +Epoch [3036/4000] Training [4/16] Loss: 0.00373 +Epoch [3036/4000] Training [5/16] Loss: 0.00353 +Epoch [3036/4000] Training [6/16] Loss: 0.00286 +Epoch [3036/4000] Training [7/16] Loss: 0.00265 +Epoch [3036/4000] Training [8/16] Loss: 0.00224 +Epoch [3036/4000] Training [9/16] Loss: 0.00374 +Epoch [3036/4000] Training [10/16] Loss: 0.00234 +Epoch [3036/4000] Training [11/16] Loss: 0.00302 +Epoch [3036/4000] Training [12/16] Loss: 0.00380 +Epoch [3036/4000] Training [13/16] Loss: 0.00490 +Epoch [3036/4000] Training [14/16] Loss: 0.00183 +Epoch [3036/4000] Training [15/16] Loss: 0.00273 +Epoch [3036/4000] Training [16/16] Loss: 0.00268 +Epoch [3036/4000] Training metric {'Train/mean dice_metric': 0.9981260299682617, 'Train/mean miou_metric': 0.9959681630134583, 'Train/mean f1': 0.9929837584495544, 'Train/mean precision': 0.9881713390350342, 'Train/mean recall': 0.997843325138092, 'Train/mean hd95_metric': 0.7976456880569458} +Epoch [3036/4000] Validation [1/4] Loss: 0.39312 focal_loss 0.33086 dice_loss 0.06226 +Epoch [3036/4000] Validation [2/4] Loss: 0.46116 focal_loss 0.34802 dice_loss 0.11314 +Epoch [3036/4000] Validation [3/4] Loss: 0.49489 focal_loss 0.40492 dice_loss 0.08997 +Epoch [3036/4000] Validation [4/4] Loss: 0.30447 focal_loss 0.22239 dice_loss 0.08207 +Epoch [3036/4000] Validation metric {'Val/mean dice_metric': 0.9735521078109741, 'Val/mean miou_metric': 0.9593290090560913, 'Val/mean f1': 0.9755904078483582, 'Val/mean precision': 0.9728394746780396, 'Val/mean recall': 0.9783571362495422, 'Val/mean hd95_metric': 5.050686359405518} +Cheakpoint... +Epoch [3036/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735521078109741, 'Val/mean miou_metric': 0.9593290090560913, 'Val/mean f1': 0.9755904078483582, 'Val/mean precision': 0.9728394746780396, 'Val/mean recall': 0.9783571362495422, 'Val/mean hd95_metric': 5.050686359405518} +Epoch [3037/4000] Training [1/16] Loss: 0.00369 +Epoch [3037/4000] Training [2/16] Loss: 0.00285 +Epoch [3037/4000] Training [3/16] Loss: 0.00410 +Epoch [3037/4000] Training [4/16] Loss: 0.00351 +Epoch [3037/4000] Training [5/16] Loss: 0.00252 +Epoch [3037/4000] Training [6/16] Loss: 0.00417 +Epoch [3037/4000] Training [7/16] Loss: 0.00274 +Epoch [3037/4000] Training [8/16] Loss: 0.00307 +Epoch [3037/4000] Training [9/16] Loss: 0.00229 +Epoch [3037/4000] Training [10/16] Loss: 0.00255 +Epoch [3037/4000] Training [11/16] Loss: 0.00243 +Epoch [3037/4000] Training [12/16] Loss: 0.00412 +Epoch [3037/4000] Training [13/16] Loss: 0.00226 +Epoch [3037/4000] Training [14/16] Loss: 0.00259 +Epoch [3037/4000] Training [15/16] Loss: 0.00489 +Epoch [3037/4000] Training [16/16] Loss: 0.00275 +Epoch [3037/4000] Training metric {'Train/mean dice_metric': 0.9982522130012512, 'Train/mean miou_metric': 0.9962351322174072, 'Train/mean f1': 0.9934496879577637, 'Train/mean precision': 0.9889233708381653, 'Train/mean recall': 0.9980176687240601, 'Train/mean hd95_metric': 0.7400944828987122} +Epoch [3037/4000] Validation [1/4] Loss: 0.39551 focal_loss 0.33231 dice_loss 0.06320 +Epoch [3037/4000] Validation [2/4] Loss: 0.52838 focal_loss 0.40005 dice_loss 0.12833 +Epoch [3037/4000] Validation [3/4] Loss: 0.51752 focal_loss 0.42524 dice_loss 0.09227 +Epoch [3037/4000] Validation [4/4] Loss: 0.32408 focal_loss 0.23435 dice_loss 0.08974 +Epoch [3037/4000] Validation metric {'Val/mean dice_metric': 0.973541259765625, 'Val/mean miou_metric': 0.9590957760810852, 'Val/mean f1': 0.9760173559188843, 'Val/mean precision': 0.9742096662521362, 'Val/mean recall': 0.9778319597244263, 'Val/mean hd95_metric': 5.058442115783691} +Cheakpoint... +Epoch [3037/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973541259765625, 'Val/mean miou_metric': 0.9590957760810852, 'Val/mean f1': 0.9760173559188843, 'Val/mean precision': 0.9742096662521362, 'Val/mean recall': 0.9778319597244263, 'Val/mean hd95_metric': 5.058442115783691} +Epoch [3038/4000] Training [1/16] Loss: 0.00301 +Epoch [3038/4000] Training [2/16] Loss: 0.00269 +Epoch [3038/4000] Training [3/16] Loss: 0.00292 +Epoch [3038/4000] Training [4/16] Loss: 0.00295 +Epoch [3038/4000] Training [5/16] Loss: 0.00307 +Epoch [3038/4000] Training [6/16] Loss: 0.00420 +Epoch [3038/4000] Training [7/16] Loss: 0.00276 +Epoch [3038/4000] Training [8/16] Loss: 0.00212 +Epoch [3038/4000] Training [9/16] Loss: 0.00377 +Epoch [3038/4000] Training [10/16] Loss: 0.00295 +Epoch [3038/4000] Training [11/16] Loss: 0.00344 +Epoch [3038/4000] Training [12/16] Loss: 0.00366 +Epoch [3038/4000] Training [13/16] Loss: 0.00346 +Epoch [3038/4000] Training [14/16] Loss: 0.00256 +Epoch [3038/4000] Training [15/16] Loss: 0.00340 +Epoch [3038/4000] Training [16/16] Loss: 0.00292 +Epoch [3038/4000] Training metric {'Train/mean dice_metric': 0.9983282089233398, 'Train/mean miou_metric': 0.9963869452476501, 'Train/mean f1': 0.9934206604957581, 'Train/mean precision': 0.988843560218811, 'Train/mean recall': 0.9980403780937195, 'Train/mean hd95_metric': 0.7431495189666748} +Epoch [3038/4000] Validation [1/4] Loss: 0.38247 focal_loss 0.31753 dice_loss 0.06494 +Epoch [3038/4000] Validation [2/4] Loss: 0.48293 focal_loss 0.36766 dice_loss 0.11526 +Epoch [3038/4000] Validation [3/4] Loss: 0.53517 focal_loss 0.43753 dice_loss 0.09764 +Epoch [3038/4000] Validation [4/4] Loss: 0.33246 focal_loss 0.24141 dice_loss 0.09104 +Epoch [3038/4000] Validation metric {'Val/mean dice_metric': 0.9731817245483398, 'Val/mean miou_metric': 0.9589133262634277, 'Val/mean f1': 0.9755851626396179, 'Val/mean precision': 0.9733842015266418, 'Val/mean recall': 0.9777961373329163, 'Val/mean hd95_metric': 5.216371536254883} +Cheakpoint... +Epoch [3038/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731817245483398, 'Val/mean miou_metric': 0.9589133262634277, 'Val/mean f1': 0.9755851626396179, 'Val/mean precision': 0.9733842015266418, 'Val/mean recall': 0.9777961373329163, 'Val/mean hd95_metric': 5.216371536254883} +Epoch [3039/4000] Training [1/16] Loss: 0.00320 +Epoch [3039/4000] Training [2/16] Loss: 0.00270 +Epoch [3039/4000] Training [3/16] Loss: 0.00224 +Epoch [3039/4000] Training [4/16] Loss: 0.00381 +Epoch [3039/4000] Training [5/16] Loss: 0.00531 +Epoch [3039/4000] Training [6/16] Loss: 0.00268 +Epoch [3039/4000] Training [7/16] Loss: 0.00526 +Epoch [3039/4000] Training [8/16] Loss: 0.00264 +Epoch [3039/4000] Training [9/16] Loss: 0.00462 +Epoch [3039/4000] Training [10/16] Loss: 0.00244 +Epoch [3039/4000] Training [11/16] Loss: 0.00286 +Epoch [3039/4000] Training [12/16] Loss: 0.00342 +Epoch [3039/4000] Training [13/16] Loss: 0.00297 +Epoch [3039/4000] Training [14/16] Loss: 0.00251 +Epoch [3039/4000] Training [15/16] Loss: 0.00235 +Epoch [3039/4000] Training [16/16] Loss: 0.00438 +Epoch [3039/4000] Training metric {'Train/mean dice_metric': 0.9981693029403687, 'Train/mean miou_metric': 0.996066153049469, 'Train/mean f1': 0.9932524561882019, 'Train/mean precision': 0.9886824488639832, 'Train/mean recall': 0.9978649616241455, 'Train/mean hd95_metric': 0.7643547058105469} +Epoch [3039/4000] Validation [1/4] Loss: 0.38022 focal_loss 0.31843 dice_loss 0.06178 +Epoch [3039/4000] Validation [2/4] Loss: 0.49127 focal_loss 0.37244 dice_loss 0.11883 +Epoch [3039/4000] Validation [3/4] Loss: 0.51148 focal_loss 0.41775 dice_loss 0.09373 +Epoch [3039/4000] Validation [4/4] Loss: 0.51171 focal_loss 0.38311 dice_loss 0.12861 +Epoch [3039/4000] Validation metric {'Val/mean dice_metric': 0.9731189012527466, 'Val/mean miou_metric': 0.9587718844413757, 'Val/mean f1': 0.9758968949317932, 'Val/mean precision': 0.9743531942367554, 'Val/mean recall': 0.9774453639984131, 'Val/mean hd95_metric': 4.861533164978027} +Cheakpoint... +Epoch [3039/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731189012527466, 'Val/mean miou_metric': 0.9587718844413757, 'Val/mean f1': 0.9758968949317932, 'Val/mean precision': 0.9743531942367554, 'Val/mean recall': 0.9774453639984131, 'Val/mean hd95_metric': 4.861533164978027} +Epoch [3040/4000] Training [1/16] Loss: 0.00238 +Epoch [3040/4000] Training [2/16] Loss: 0.00410 +Epoch [3040/4000] Training [3/16] Loss: 0.00246 +Epoch [3040/4000] Training [4/16] Loss: 0.00264 +Epoch [3040/4000] Training [5/16] Loss: 0.00211 +Epoch [3040/4000] Training [6/16] Loss: 0.00380 +Epoch [3040/4000] Training [7/16] Loss: 0.00289 +Epoch [3040/4000] Training [8/16] Loss: 0.00273 +Epoch [3040/4000] Training [9/16] Loss: 0.00248 +Epoch [3040/4000] Training [10/16] Loss: 0.00244 +Epoch [3040/4000] Training [11/16] Loss: 0.00266 +Epoch [3040/4000] Training [12/16] Loss: 0.00350 +Epoch [3040/4000] Training [13/16] Loss: 0.00354 +Epoch [3040/4000] Training [14/16] Loss: 0.00358 +Epoch [3040/4000] Training [15/16] Loss: 0.00534 +Epoch [3040/4000] Training [16/16] Loss: 0.00366 +Epoch [3040/4000] Training metric {'Train/mean dice_metric': 0.9982550144195557, 'Train/mean miou_metric': 0.9962313175201416, 'Train/mean f1': 0.9932697415351868, 'Train/mean precision': 0.9886353015899658, 'Train/mean recall': 0.9979478120803833, 'Train/mean hd95_metric': 0.7506551742553711} +Epoch [3040/4000] Validation [1/4] Loss: 0.36028 focal_loss 0.29588 dice_loss 0.06440 +Epoch [3040/4000] Validation [2/4] Loss: 0.90683 focal_loss 0.69476 dice_loss 0.21207 +Epoch [3040/4000] Validation [3/4] Loss: 0.52319 focal_loss 0.42675 dice_loss 0.09644 +Epoch [3040/4000] Validation [4/4] Loss: 0.59709 focal_loss 0.45453 dice_loss 0.14256 +Epoch [3040/4000] Validation metric {'Val/mean dice_metric': 0.9712725877761841, 'Val/mean miou_metric': 0.9567853808403015, 'Val/mean f1': 0.9745973944664001, 'Val/mean precision': 0.973533570766449, 'Val/mean recall': 0.9756635427474976, 'Val/mean hd95_metric': 5.16656494140625} +Cheakpoint... +Epoch [3040/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712725877761841, 'Val/mean miou_metric': 0.9567853808403015, 'Val/mean f1': 0.9745973944664001, 'Val/mean precision': 0.973533570766449, 'Val/mean recall': 0.9756635427474976, 'Val/mean hd95_metric': 5.16656494140625} +Epoch [3041/4000] Training [1/16] Loss: 0.00267 +Epoch [3041/4000] Training [2/16] Loss: 0.00345 +Epoch [3041/4000] Training [3/16] Loss: 0.00361 +Epoch [3041/4000] Training [4/16] Loss: 0.00257 +Epoch [3041/4000] Training [5/16] Loss: 0.00277 +Epoch [3041/4000] Training [6/16] Loss: 0.00335 +Epoch [3041/4000] Training [7/16] Loss: 0.00392 +Epoch [3041/4000] Training [8/16] Loss: 0.00261 +Epoch [3041/4000] Training [9/16] Loss: 0.00281 +Epoch [3041/4000] Training [10/16] Loss: 0.00265 +Epoch [3041/4000] Training [11/16] Loss: 0.00343 +Epoch [3041/4000] Training [12/16] Loss: 0.00229 +Epoch [3041/4000] Training [13/16] Loss: 0.00306 +Epoch [3041/4000] Training [14/16] Loss: 0.00283 +Epoch [3041/4000] Training [15/16] Loss: 0.00305 +Epoch [3041/4000] Training [16/16] Loss: 0.00396 +Epoch [3041/4000] Training metric {'Train/mean dice_metric': 0.9982483386993408, 'Train/mean miou_metric': 0.9962311387062073, 'Train/mean f1': 0.9934971332550049, 'Train/mean precision': 0.9889676570892334, 'Train/mean recall': 0.9980683326721191, 'Train/mean hd95_metric': 0.7461822032928467} +Epoch [3041/4000] Validation [1/4] Loss: 0.44134 focal_loss 0.37172 dice_loss 0.06962 +Epoch [3041/4000] Validation [2/4] Loss: 0.53563 focal_loss 0.40757 dice_loss 0.12805 +Epoch [3041/4000] Validation [3/4] Loss: 0.48413 focal_loss 0.39495 dice_loss 0.08918 +Epoch [3041/4000] Validation [4/4] Loss: 0.32446 focal_loss 0.23245 dice_loss 0.09200 +Epoch [3041/4000] Validation metric {'Val/mean dice_metric': 0.9733737111091614, 'Val/mean miou_metric': 0.9589647054672241, 'Val/mean f1': 0.9757732152938843, 'Val/mean precision': 0.9744133353233337, 'Val/mean recall': 0.9771368503570557, 'Val/mean hd95_metric': 5.033719062805176} +Cheakpoint... +Epoch [3041/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733737111091614, 'Val/mean miou_metric': 0.9589647054672241, 'Val/mean f1': 0.9757732152938843, 'Val/mean precision': 0.9744133353233337, 'Val/mean recall': 0.9771368503570557, 'Val/mean hd95_metric': 5.033719062805176} +Epoch [3042/4000] Training [1/16] Loss: 0.00239 +Epoch [3042/4000] Training [2/16] Loss: 0.00369 +Epoch [3042/4000] Training [3/16] Loss: 0.00294 +Epoch [3042/4000] Training [4/16] Loss: 0.00338 +Epoch [3042/4000] Training [5/16] Loss: 0.00315 +Epoch [3042/4000] Training [6/16] Loss: 0.00295 +Epoch [3042/4000] Training [7/16] Loss: 0.00271 +Epoch [3042/4000] Training [8/16] Loss: 0.00275 +Epoch [3042/4000] Training [9/16] Loss: 0.00409 +Epoch [3042/4000] Training [10/16] Loss: 0.00278 +Epoch [3042/4000] Training [11/16] Loss: 0.00243 +Epoch [3042/4000] Training [12/16] Loss: 0.00433 +Epoch [3042/4000] Training [13/16] Loss: 0.00516 +Epoch [3042/4000] Training [14/16] Loss: 0.00219 +Epoch [3042/4000] Training [15/16] Loss: 0.00322 +Epoch [3042/4000] Training [16/16] Loss: 0.00222 +Epoch [3042/4000] Training metric {'Train/mean dice_metric': 0.9982467889785767, 'Train/mean miou_metric': 0.9961891174316406, 'Train/mean f1': 0.9925190210342407, 'Train/mean precision': 0.9871920943260193, 'Train/mean recall': 0.9979037642478943, 'Train/mean hd95_metric': 0.7348476648330688} +Epoch [3042/4000] Validation [1/4] Loss: 0.34042 focal_loss 0.28227 dice_loss 0.05816 +Epoch [3042/4000] Validation [2/4] Loss: 0.56124 focal_loss 0.43024 dice_loss 0.13100 +Epoch [3042/4000] Validation [3/4] Loss: 0.48552 focal_loss 0.39735 dice_loss 0.08816 +Epoch [3042/4000] Validation [4/4] Loss: 0.33069 focal_loss 0.24102 dice_loss 0.08968 +Epoch [3042/4000] Validation metric {'Val/mean dice_metric': 0.974709153175354, 'Val/mean miou_metric': 0.9605444073677063, 'Val/mean f1': 0.9759351015090942, 'Val/mean precision': 0.9725937247276306, 'Val/mean recall': 0.9792994856834412, 'Val/mean hd95_metric': 4.932710647583008} +Cheakpoint... +Epoch [3042/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974709153175354, 'Val/mean miou_metric': 0.9605444073677063, 'Val/mean f1': 0.9759351015090942, 'Val/mean precision': 0.9725937247276306, 'Val/mean recall': 0.9792994856834412, 'Val/mean hd95_metric': 4.932710647583008} +Epoch [3043/4000] Training [1/16] Loss: 0.00307 +Epoch [3043/4000] Training [2/16] Loss: 0.00381 +Epoch [3043/4000] Training [3/16] Loss: 0.00298 +Epoch [3043/4000] Training [4/16] Loss: 0.00313 +Epoch [3043/4000] Training [5/16] Loss: 0.00265 +Epoch [3043/4000] Training [6/16] Loss: 0.00239 +Epoch [3043/4000] Training [7/16] Loss: 0.00360 +Epoch [3043/4000] Training [8/16] Loss: 0.00260 +Epoch [3043/4000] Training [9/16] Loss: 0.00308 +Epoch [3043/4000] Training [10/16] Loss: 0.00223 +Epoch [3043/4000] Training [11/16] Loss: 0.00305 +Epoch [3043/4000] Training [12/16] Loss: 0.00290 +Epoch [3043/4000] Training [13/16] Loss: 0.00278 +Epoch [3043/4000] Training [14/16] Loss: 0.00213 +Epoch [3043/4000] Training [15/16] Loss: 0.00354 +Epoch [3043/4000] Training [16/16] Loss: 0.00226 +Epoch [3043/4000] Training metric {'Train/mean dice_metric': 0.9983152151107788, 'Train/mean miou_metric': 0.9963449835777283, 'Train/mean f1': 0.9932820200920105, 'Train/mean precision': 0.9886624813079834, 'Train/mean recall': 0.9979448318481445, 'Train/mean hd95_metric': 0.721947431564331} +Epoch [3043/4000] Validation [1/4] Loss: 0.38489 focal_loss 0.32096 dice_loss 0.06393 +Epoch [3043/4000] Validation [2/4] Loss: 1.01250 focal_loss 0.81853 dice_loss 0.19397 +Epoch [3043/4000] Validation [3/4] Loss: 0.50328 focal_loss 0.41362 dice_loss 0.08966 +Epoch [3043/4000] Validation [4/4] Loss: 0.31947 focal_loss 0.23310 dice_loss 0.08637 +Epoch [3043/4000] Validation metric {'Val/mean dice_metric': 0.9739280939102173, 'Val/mean miou_metric': 0.9600370526313782, 'Val/mean f1': 0.9760773777961731, 'Val/mean precision': 0.9731549620628357, 'Val/mean recall': 0.9790173172950745, 'Val/mean hd95_metric': 4.962563991546631} +Cheakpoint... +Epoch [3043/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739280939102173, 'Val/mean miou_metric': 0.9600370526313782, 'Val/mean f1': 0.9760773777961731, 'Val/mean precision': 0.9731549620628357, 'Val/mean recall': 0.9790173172950745, 'Val/mean hd95_metric': 4.962563991546631} +Epoch [3044/4000] Training [1/16] Loss: 0.00258 +Epoch [3044/4000] Training [2/16] Loss: 0.00382 +Epoch [3044/4000] Training [3/16] Loss: 0.00387 +Epoch [3044/4000] Training [4/16] Loss: 0.00274 +Epoch [3044/4000] Training [5/16] Loss: 0.00281 +Epoch [3044/4000] Training [6/16] Loss: 0.00199 +Epoch [3044/4000] Training [7/16] Loss: 0.00317 +Epoch [3044/4000] Training [8/16] Loss: 0.00288 +Epoch [3044/4000] Training [9/16] Loss: 0.00470 +Epoch [3044/4000] Training [10/16] Loss: 0.00347 +Epoch [3044/4000] Training [11/16] Loss: 0.00322 +Epoch [3044/4000] Training [12/16] Loss: 0.00307 +Epoch [3044/4000] Training [13/16] Loss: 0.00166 +Epoch [3044/4000] Training [14/16] Loss: 0.00245 +Epoch [3044/4000] Training [15/16] Loss: 0.00317 +Epoch [3044/4000] Training [16/16] Loss: 0.00333 +Epoch [3044/4000] Training metric {'Train/mean dice_metric': 0.9982689619064331, 'Train/mean miou_metric': 0.9962727427482605, 'Train/mean f1': 0.9934448599815369, 'Train/mean precision': 0.9889376163482666, 'Train/mean recall': 0.9979933500289917, 'Train/mean hd95_metric': 0.7255158424377441} +Epoch [3044/4000] Validation [1/4] Loss: 0.42954 focal_loss 0.36454 dice_loss 0.06500 +Epoch [3044/4000] Validation [2/4] Loss: 0.75167 focal_loss 0.53774 dice_loss 0.21394 +Epoch [3044/4000] Validation [3/4] Loss: 0.51198 focal_loss 0.42165 dice_loss 0.09033 +Epoch [3044/4000] Validation [4/4] Loss: 0.34019 focal_loss 0.24378 dice_loss 0.09641 +Epoch [3044/4000] Validation metric {'Val/mean dice_metric': 0.9731677770614624, 'Val/mean miou_metric': 0.9587489366531372, 'Val/mean f1': 0.9759072065353394, 'Val/mean precision': 0.9738339781761169, 'Val/mean recall': 0.9779892563819885, 'Val/mean hd95_metric': 4.775552272796631} +Cheakpoint... +Epoch [3044/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731677770614624, 'Val/mean miou_metric': 0.9587489366531372, 'Val/mean f1': 0.9759072065353394, 'Val/mean precision': 0.9738339781761169, 'Val/mean recall': 0.9779892563819885, 'Val/mean hd95_metric': 4.775552272796631} +Epoch [3045/4000] Training [1/16] Loss: 0.00331 +Epoch [3045/4000] Training [2/16] Loss: 0.00287 +Epoch [3045/4000] Training [3/16] Loss: 0.00242 +Epoch [3045/4000] Training [4/16] Loss: 0.00358 +Epoch [3045/4000] Training [5/16] Loss: 0.00256 +Epoch [3045/4000] Training [6/16] Loss: 0.00204 +Epoch [3045/4000] Training [7/16] Loss: 0.00311 +Epoch [3045/4000] Training [8/16] Loss: 0.00327 +Epoch [3045/4000] Training [9/16] Loss: 0.00263 +Epoch [3045/4000] Training [10/16] Loss: 0.00316 +Epoch [3045/4000] Training [11/16] Loss: 0.00328 +Epoch [3045/4000] Training [12/16] Loss: 0.00497 +Epoch [3045/4000] Training [13/16] Loss: 0.00339 +Epoch [3045/4000] Training [14/16] Loss: 0.00316 +Epoch [3045/4000] Training [15/16] Loss: 0.00348 +Epoch [3045/4000] Training [16/16] Loss: 0.00233 +Epoch [3045/4000] Training metric {'Train/mean dice_metric': 0.9982814788818359, 'Train/mean miou_metric': 0.9962888956069946, 'Train/mean f1': 0.9934713244438171, 'Train/mean precision': 0.9889866709709167, 'Train/mean recall': 0.9979968070983887, 'Train/mean hd95_metric': 0.7424381971359253} +Epoch [3045/4000] Validation [1/4] Loss: 0.37190 focal_loss 0.31073 dice_loss 0.06117 +Epoch [3045/4000] Validation [2/4] Loss: 0.51181 focal_loss 0.39140 dice_loss 0.12041 +Epoch [3045/4000] Validation [3/4] Loss: 0.51277 focal_loss 0.42035 dice_loss 0.09242 +Epoch [3045/4000] Validation [4/4] Loss: 0.37826 focal_loss 0.27901 dice_loss 0.09925 +Epoch [3045/4000] Validation metric {'Val/mean dice_metric': 0.9742833971977234, 'Val/mean miou_metric': 0.959873378276825, 'Val/mean f1': 0.9763631224632263, 'Val/mean precision': 0.9738726615905762, 'Val/mean recall': 0.9788663387298584, 'Val/mean hd95_metric': 4.926462173461914} +Cheakpoint... +Epoch [3045/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742833971977234, 'Val/mean miou_metric': 0.959873378276825, 'Val/mean f1': 0.9763631224632263, 'Val/mean precision': 0.9738726615905762, 'Val/mean recall': 0.9788663387298584, 'Val/mean hd95_metric': 4.926462173461914} +Epoch [3046/4000] Training [1/16] Loss: 0.00361 +Epoch [3046/4000] Training [2/16] Loss: 0.00453 +Epoch [3046/4000] Training [3/16] Loss: 0.00313 +Epoch [3046/4000] Training [4/16] Loss: 0.00335 +Epoch [3046/4000] Training [5/16] Loss: 0.00385 +Epoch [3046/4000] Training [6/16] Loss: 0.00275 +Epoch [3046/4000] Training [7/16] Loss: 0.00474 +Epoch [3046/4000] Training [8/16] Loss: 0.00475 +Epoch [3046/4000] Training [9/16] Loss: 0.00428 +Epoch [3046/4000] Training [10/16] Loss: 0.00272 +Epoch [3046/4000] Training [11/16] Loss: 0.00398 +Epoch [3046/4000] Training [12/16] Loss: 0.00271 +Epoch [3046/4000] Training [13/16] Loss: 0.00191 +Epoch [3046/4000] Training [14/16] Loss: 0.00243 +Epoch [3046/4000] Training [15/16] Loss: 0.00393 +Epoch [3046/4000] Training [16/16] Loss: 0.00273 +Epoch [3046/4000] Training metric {'Train/mean dice_metric': 0.9980945587158203, 'Train/mean miou_metric': 0.9959229230880737, 'Train/mean f1': 0.9933976531028748, 'Train/mean precision': 0.988917887210846, 'Train/mean recall': 0.9979182481765747, 'Train/mean hd95_metric': 0.7637273073196411} +Epoch [3046/4000] Validation [1/4] Loss: 0.40980 focal_loss 0.34625 dice_loss 0.06356 +Epoch [3046/4000] Validation [2/4] Loss: 0.50546 focal_loss 0.38615 dice_loss 0.11931 +Epoch [3046/4000] Validation [3/4] Loss: 0.50096 focal_loss 0.41086 dice_loss 0.09010 +Epoch [3046/4000] Validation [4/4] Loss: 0.30027 focal_loss 0.20744 dice_loss 0.09283 +Epoch [3046/4000] Validation metric {'Val/mean dice_metric': 0.9733666181564331, 'Val/mean miou_metric': 0.9590247273445129, 'Val/mean f1': 0.9760153889656067, 'Val/mean precision': 0.9743967056274414, 'Val/mean recall': 0.9776393175125122, 'Val/mean hd95_metric': 5.080435752868652} +Cheakpoint... +Epoch [3046/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733666181564331, 'Val/mean miou_metric': 0.9590247273445129, 'Val/mean f1': 0.9760153889656067, 'Val/mean precision': 0.9743967056274414, 'Val/mean recall': 0.9776393175125122, 'Val/mean hd95_metric': 5.080435752868652} +Epoch [3047/4000] Training [1/16] Loss: 0.00349 +Epoch [3047/4000] Training [2/16] Loss: 0.00372 +Epoch [3047/4000] Training [3/16] Loss: 0.00243 +Epoch [3047/4000] Training [4/16] Loss: 0.00406 +Epoch [3047/4000] Training [5/16] Loss: 0.00268 +Epoch [3047/4000] Training [6/16] Loss: 0.00279 +Epoch [3047/4000] Training [7/16] Loss: 0.00459 +Epoch [3047/4000] Training [8/16] Loss: 0.00268 +Epoch [3047/4000] Training [9/16] Loss: 0.00945 +Epoch [3047/4000] Training [10/16] Loss: 0.00327 +Epoch [3047/4000] Training [11/16] Loss: 0.00265 +Epoch [3047/4000] Training [12/16] Loss: 0.00320 +Epoch [3047/4000] Training [13/16] Loss: 0.00274 +Epoch [3047/4000] Training [14/16] Loss: 0.00313 +Epoch [3047/4000] Training [15/16] Loss: 0.00424 +Epoch [3047/4000] Training [16/16] Loss: 0.00310 +Epoch [3047/4000] Training metric {'Train/mean dice_metric': 0.9980916976928711, 'Train/mean miou_metric': 0.995919942855835, 'Train/mean f1': 0.9933642148971558, 'Train/mean precision': 0.988876223564148, 'Train/mean recall': 0.9978930950164795, 'Train/mean hd95_metric': 0.8019543886184692} +Epoch [3047/4000] Validation [1/4] Loss: 0.29864 focal_loss 0.24303 dice_loss 0.05561 +Epoch [3047/4000] Validation [2/4] Loss: 0.88828 focal_loss 0.68561 dice_loss 0.20267 +Epoch [3047/4000] Validation [3/4] Loss: 0.52330 focal_loss 0.42901 dice_loss 0.09429 +Epoch [3047/4000] Validation [4/4] Loss: 0.38970 focal_loss 0.27762 dice_loss 0.11208 +Epoch [3047/4000] Validation metric {'Val/mean dice_metric': 0.9720498919487, 'Val/mean miou_metric': 0.9574533700942993, 'Val/mean f1': 0.9754261374473572, 'Val/mean precision': 0.9731543660163879, 'Val/mean recall': 0.9777084589004517, 'Val/mean hd95_metric': 5.5948662757873535} +Cheakpoint... +Epoch [3047/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720498919487, 'Val/mean miou_metric': 0.9574533700942993, 'Val/mean f1': 0.9754261374473572, 'Val/mean precision': 0.9731543660163879, 'Val/mean recall': 0.9777084589004517, 'Val/mean hd95_metric': 5.5948662757873535} +Epoch [3048/4000] Training [1/16] Loss: 0.00432 +Epoch [3048/4000] Training [2/16] Loss: 0.00461 +Epoch [3048/4000] Training [3/16] Loss: 0.00278 +Epoch [3048/4000] Training [4/16] Loss: 0.00412 +Epoch [3048/4000] Training [5/16] Loss: 0.00324 +Epoch [3048/4000] Training [6/16] Loss: 0.00353 +Epoch [3048/4000] Training [7/16] Loss: 0.00329 +Epoch [3048/4000] Training [8/16] Loss: 0.00260 +Epoch [3048/4000] Training [9/16] Loss: 0.00347 +Epoch [3048/4000] Training [10/16] Loss: 0.00250 +Epoch [3048/4000] Training [11/16] Loss: 0.00444 +Epoch [3048/4000] Training [12/16] Loss: 0.00291 +Epoch [3048/4000] Training [13/16] Loss: 0.00407 +Epoch [3048/4000] Training [14/16] Loss: 0.00256 +Epoch [3048/4000] Training [15/16] Loss: 0.00470 +Epoch [3048/4000] Training [16/16] Loss: 0.00244 +Epoch [3048/4000] Training metric {'Train/mean dice_metric': 0.9980142116546631, 'Train/mean miou_metric': 0.9957597255706787, 'Train/mean f1': 0.9930214881896973, 'Train/mean precision': 0.9883788228034973, 'Train/mean recall': 0.9977079629898071, 'Train/mean hd95_metric': 0.7727116346359253} +Epoch [3048/4000] Validation [1/4] Loss: 0.43903 focal_loss 0.37453 dice_loss 0.06450 +Epoch [3048/4000] Validation [2/4] Loss: 0.90713 focal_loss 0.72088 dice_loss 0.18626 +Epoch [3048/4000] Validation [3/4] Loss: 0.50542 focal_loss 0.41407 dice_loss 0.09135 +Epoch [3048/4000] Validation [4/4] Loss: 0.33846 focal_loss 0.23108 dice_loss 0.10738 +Epoch [3048/4000] Validation metric {'Val/mean dice_metric': 0.9751850366592407, 'Val/mean miou_metric': 0.9607855081558228, 'Val/mean f1': 0.9762158989906311, 'Val/mean precision': 0.9730468392372131, 'Val/mean recall': 0.9794055819511414, 'Val/mean hd95_metric': 4.927696704864502} +Cheakpoint... +Epoch [3048/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751850366592407, 'Val/mean miou_metric': 0.9607855081558228, 'Val/mean f1': 0.9762158989906311, 'Val/mean precision': 0.9730468392372131, 'Val/mean recall': 0.9794055819511414, 'Val/mean hd95_metric': 4.927696704864502} +Epoch [3049/4000] Training [1/16] Loss: 0.00304 +Epoch [3049/4000] Training [2/16] Loss: 0.00252 +Epoch [3049/4000] Training [3/16] Loss: 0.00308 +Epoch [3049/4000] Training [4/16] Loss: 0.00315 +Epoch [3049/4000] Training [5/16] Loss: 0.00272 +Epoch [3049/4000] Training [6/16] Loss: 0.00306 +Epoch [3049/4000] Training [7/16] Loss: 0.00407 +Epoch [3049/4000] Training [8/16] Loss: 0.00308 +Epoch [3049/4000] Training [9/16] Loss: 0.00419 +Epoch [3049/4000] Training [10/16] Loss: 0.00319 +Epoch [3049/4000] Training [11/16] Loss: 0.00332 +Epoch [3049/4000] Training [12/16] Loss: 0.00504 +Epoch [3049/4000] Training [13/16] Loss: 0.00342 +Epoch [3049/4000] Training [14/16] Loss: 0.00233 +Epoch [3049/4000] Training [15/16] Loss: 0.00275 +Epoch [3049/4000] Training [16/16] Loss: 0.00392 +Epoch [3049/4000] Training metric {'Train/mean dice_metric': 0.9980497360229492, 'Train/mean miou_metric': 0.9958356618881226, 'Train/mean f1': 0.9932583570480347, 'Train/mean precision': 0.9887306690216064, 'Train/mean recall': 0.9978276491165161, 'Train/mean hd95_metric': 0.8102757930755615} +Epoch [3049/4000] Validation [1/4] Loss: 0.41004 focal_loss 0.34495 dice_loss 0.06509 +Epoch [3049/4000] Validation [2/4] Loss: 0.51673 focal_loss 0.39889 dice_loss 0.11784 +Epoch [3049/4000] Validation [3/4] Loss: 0.52252 focal_loss 0.43117 dice_loss 0.09136 +Epoch [3049/4000] Validation [4/4] Loss: 0.32413 focal_loss 0.23469 dice_loss 0.08944 +Epoch [3049/4000] Validation metric {'Val/mean dice_metric': 0.9736018180847168, 'Val/mean miou_metric': 0.9589492678642273, 'Val/mean f1': 0.9755493402481079, 'Val/mean precision': 0.9722150564193726, 'Val/mean recall': 0.978906512260437, 'Val/mean hd95_metric': 5.3742899894714355} +Cheakpoint... +Epoch [3049/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736018180847168, 'Val/mean miou_metric': 0.9589492678642273, 'Val/mean f1': 0.9755493402481079, 'Val/mean precision': 0.9722150564193726, 'Val/mean recall': 0.978906512260437, 'Val/mean hd95_metric': 5.3742899894714355} +Epoch [3050/4000] Training [1/16] Loss: 0.00327 +Epoch [3050/4000] Training [2/16] Loss: 0.00316 +Epoch [3050/4000] Training [3/16] Loss: 0.00341 +Epoch [3050/4000] Training [4/16] Loss: 0.00258 +Epoch [3050/4000] Training [5/16] Loss: 0.00231 +Epoch [3050/4000] Training [6/16] Loss: 0.00254 +Epoch [3050/4000] Training [7/16] Loss: 0.00271 +Epoch [3050/4000] Training [8/16] Loss: 0.00286 +Epoch [3050/4000] Training [9/16] Loss: 0.00497 +Epoch [3050/4000] Training [10/16] Loss: 0.00373 +Epoch [3050/4000] Training [11/16] Loss: 0.00307 +Epoch [3050/4000] Training [12/16] Loss: 0.00305 +Epoch [3050/4000] Training [13/16] Loss: 0.00317 +Epoch [3050/4000] Training [14/16] Loss: 0.00268 +Epoch [3050/4000] Training [15/16] Loss: 0.00255 +Epoch [3050/4000] Training [16/16] Loss: 0.00278 +Epoch [3050/4000] Training metric {'Train/mean dice_metric': 0.9982601404190063, 'Train/mean miou_metric': 0.9962474703788757, 'Train/mean f1': 0.993363082408905, 'Train/mean precision': 0.9887840151786804, 'Train/mean recall': 0.997984766960144, 'Train/mean hd95_metric': 0.7729768753051758} +Epoch [3050/4000] Validation [1/4] Loss: 0.34484 focal_loss 0.28709 dice_loss 0.05775 +Epoch [3050/4000] Validation [2/4] Loss: 1.17244 focal_loss 0.97029 dice_loss 0.20215 +Epoch [3050/4000] Validation [3/4] Loss: 0.53454 focal_loss 0.44120 dice_loss 0.09333 +Epoch [3050/4000] Validation [4/4] Loss: 0.37805 focal_loss 0.27165 dice_loss 0.10640 +Epoch [3050/4000] Validation metric {'Val/mean dice_metric': 0.9720665216445923, 'Val/mean miou_metric': 0.9579998254776001, 'Val/mean f1': 0.9758285880088806, 'Val/mean precision': 0.9733302593231201, 'Val/mean recall': 0.9783399701118469, 'Val/mean hd95_metric': 5.202887058258057} +Cheakpoint... +Epoch [3050/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720665216445923, 'Val/mean miou_metric': 0.9579998254776001, 'Val/mean f1': 0.9758285880088806, 'Val/mean precision': 0.9733302593231201, 'Val/mean recall': 0.9783399701118469, 'Val/mean hd95_metric': 5.202887058258057} +Epoch [3051/4000] Training [1/16] Loss: 0.00194 +Epoch [3051/4000] Training [2/16] Loss: 0.00285 +Epoch [3051/4000] Training [3/16] Loss: 0.00267 +Epoch [3051/4000] Training [4/16] Loss: 0.00235 +Epoch [3051/4000] Training [5/16] Loss: 0.00274 +Epoch [3051/4000] Training [6/16] Loss: 0.00328 +Epoch [3051/4000] Training [7/16] Loss: 0.00260 +Epoch [3051/4000] Training [8/16] Loss: 0.00340 +Epoch [3051/4000] Training [9/16] Loss: 0.00286 +Epoch [3051/4000] Training [10/16] Loss: 0.00295 +Epoch [3051/4000] Training [11/16] Loss: 0.00335 +Epoch [3051/4000] Training [12/16] Loss: 0.00246 +Epoch [3051/4000] Training [13/16] Loss: 0.00323 +Epoch [3051/4000] Training [14/16] Loss: 0.00384 +Epoch [3051/4000] Training [15/16] Loss: 0.00333 +Epoch [3051/4000] Training [16/16] Loss: 0.00497 +Epoch [3051/4000] Training metric {'Train/mean dice_metric': 0.9983171224594116, 'Train/mean miou_metric': 0.9963403940200806, 'Train/mean f1': 0.9929293990135193, 'Train/mean precision': 0.9878901839256287, 'Train/mean recall': 0.9980202317237854, 'Train/mean hd95_metric': 0.7294498682022095} +Epoch [3051/4000] Validation [1/4] Loss: 0.34283 focal_loss 0.28632 dice_loss 0.05652 +Epoch [3051/4000] Validation [2/4] Loss: 0.54896 focal_loss 0.42481 dice_loss 0.12414 +Epoch [3051/4000] Validation [3/4] Loss: 0.46586 focal_loss 0.36779 dice_loss 0.09807 +Epoch [3051/4000] Validation [4/4] Loss: 0.41687 focal_loss 0.31284 dice_loss 0.10403 +Epoch [3051/4000] Validation metric {'Val/mean dice_metric': 0.9741951823234558, 'Val/mean miou_metric': 0.9603727459907532, 'Val/mean f1': 0.9757754802703857, 'Val/mean precision': 0.9735122919082642, 'Val/mean recall': 0.9780492782592773, 'Val/mean hd95_metric': 5.018399715423584} +Cheakpoint... +Epoch [3051/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741951823234558, 'Val/mean miou_metric': 0.9603727459907532, 'Val/mean f1': 0.9757754802703857, 'Val/mean precision': 0.9735122919082642, 'Val/mean recall': 0.9780492782592773, 'Val/mean hd95_metric': 5.018399715423584} +Epoch [3052/4000] Training [1/16] Loss: 0.00303 +Epoch [3052/4000] Training [2/16] Loss: 0.00233 +Epoch [3052/4000] Training [3/16] Loss: 0.00228 +Epoch [3052/4000] Training [4/16] Loss: 0.00209 +Epoch [3052/4000] Training [5/16] Loss: 0.00265 +Epoch [3052/4000] Training [6/16] Loss: 0.00319 +Epoch [3052/4000] Training [7/16] Loss: 0.00337 +Epoch [3052/4000] Training [8/16] Loss: 0.00312 +Epoch [3052/4000] Training [9/16] Loss: 0.00328 +Epoch [3052/4000] Training [10/16] Loss: 0.00223 +Epoch [3052/4000] Training [11/16] Loss: 0.00327 +Epoch [3052/4000] Training [12/16] Loss: 0.00263 +Epoch [3052/4000] Training [13/16] Loss: 0.00345 +Epoch [3052/4000] Training [14/16] Loss: 0.00386 +Epoch [3052/4000] Training [15/16] Loss: 0.00415 +Epoch [3052/4000] Training [16/16] Loss: 0.00306 +Epoch [3052/4000] Training metric {'Train/mean dice_metric': 0.9981658458709717, 'Train/mean miou_metric': 0.9960571527481079, 'Train/mean f1': 0.9930800199508667, 'Train/mean precision': 0.988286018371582, 'Train/mean recall': 0.9979208111763, 'Train/mean hd95_metric': 0.7446221709251404} +Epoch [3052/4000] Validation [1/4] Loss: 0.41321 focal_loss 0.34801 dice_loss 0.06520 +Epoch [3052/4000] Validation [2/4] Loss: 1.19462 focal_loss 0.99602 dice_loss 0.19860 +Epoch [3052/4000] Validation [3/4] Loss: 0.52729 focal_loss 0.43475 dice_loss 0.09254 +Epoch [3052/4000] Validation [4/4] Loss: 0.37537 focal_loss 0.26486 dice_loss 0.11051 +Epoch [3052/4000] Validation metric {'Val/mean dice_metric': 0.9729025959968567, 'Val/mean miou_metric': 0.9582155346870422, 'Val/mean f1': 0.975177526473999, 'Val/mean precision': 0.9735032320022583, 'Val/mean recall': 0.9768575429916382, 'Val/mean hd95_metric': 5.109082221984863} +Cheakpoint... +Epoch [3052/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729025959968567, 'Val/mean miou_metric': 0.9582155346870422, 'Val/mean f1': 0.975177526473999, 'Val/mean precision': 0.9735032320022583, 'Val/mean recall': 0.9768575429916382, 'Val/mean hd95_metric': 5.109082221984863} +Epoch [3053/4000] Training [1/16] Loss: 0.00262 +Epoch [3053/4000] Training [2/16] Loss: 0.00363 +Epoch [3053/4000] Training [3/16] Loss: 0.00301 +Epoch [3053/4000] Training [4/16] Loss: 0.00205 +Epoch [3053/4000] Training [5/16] Loss: 0.00303 +Epoch [3053/4000] Training [6/16] Loss: 0.00376 +Epoch [3053/4000] Training [7/16] Loss: 0.00385 +Epoch [3053/4000] Training [8/16] Loss: 0.00226 +Epoch [3053/4000] Training [9/16] Loss: 0.00324 +Epoch [3053/4000] Training [10/16] Loss: 0.00389 +Epoch [3053/4000] Training [11/16] Loss: 0.00271 +Epoch [3053/4000] Training [12/16] Loss: 0.00353 +Epoch [3053/4000] Training [13/16] Loss: 0.00192 +Epoch [3053/4000] Training [14/16] Loss: 0.00363 +Epoch [3053/4000] Training [15/16] Loss: 0.00275 +Epoch [3053/4000] Training [16/16] Loss: 0.00341 +Epoch [3053/4000] Training metric {'Train/mean dice_metric': 0.9983224868774414, 'Train/mean miou_metric': 0.9963638782501221, 'Train/mean f1': 0.9932329058647156, 'Train/mean precision': 0.9885302782058716, 'Train/mean recall': 0.9979804158210754, 'Train/mean hd95_metric': 0.7830354571342468} +Epoch [3053/4000] Validation [1/4] Loss: 0.38108 focal_loss 0.31976 dice_loss 0.06133 +Epoch [3053/4000] Validation [2/4] Loss: 1.08471 focal_loss 0.89218 dice_loss 0.19254 +Epoch [3053/4000] Validation [3/4] Loss: 0.53535 focal_loss 0.44126 dice_loss 0.09409 +Epoch [3053/4000] Validation [4/4] Loss: 0.35885 focal_loss 0.25326 dice_loss 0.10559 +Epoch [3053/4000] Validation metric {'Val/mean dice_metric': 0.9719337224960327, 'Val/mean miou_metric': 0.958260715007782, 'Val/mean f1': 0.9753481149673462, 'Val/mean precision': 0.9742752313613892, 'Val/mean recall': 0.9764232635498047, 'Val/mean hd95_metric': 5.130025386810303} +Cheakpoint... +Epoch [3053/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719337224960327, 'Val/mean miou_metric': 0.958260715007782, 'Val/mean f1': 0.9753481149673462, 'Val/mean precision': 0.9742752313613892, 'Val/mean recall': 0.9764232635498047, 'Val/mean hd95_metric': 5.130025386810303} +Epoch [3054/4000] Training [1/16] Loss: 0.00203 +Epoch [3054/4000] Training [2/16] Loss: 0.00353 +Epoch [3054/4000] Training [3/16] Loss: 0.00280 +Epoch [3054/4000] Training [4/16] Loss: 0.00288 +Epoch [3054/4000] Training [5/16] Loss: 0.00349 +Epoch [3054/4000] Training [6/16] Loss: 0.00413 +Epoch [3054/4000] Training [7/16] Loss: 0.00266 +Epoch [3054/4000] Training [8/16] Loss: 0.00291 +Epoch [3054/4000] Training [9/16] Loss: 0.00373 +Epoch [3054/4000] Training [10/16] Loss: 0.00304 +Epoch [3054/4000] Training [11/16] Loss: 0.00346 +Epoch [3054/4000] Training [12/16] Loss: 0.00240 +Epoch [3054/4000] Training [13/16] Loss: 0.00291 +Epoch [3054/4000] Training [14/16] Loss: 0.00253 +Epoch [3054/4000] Training [15/16] Loss: 0.00264 +Epoch [3054/4000] Training [16/16] Loss: 0.00451 +Epoch [3054/4000] Training metric {'Train/mean dice_metric': 0.9982742667198181, 'Train/mean miou_metric': 0.9962800145149231, 'Train/mean f1': 0.9934664964675903, 'Train/mean precision': 0.9889457821846008, 'Train/mean recall': 0.9980286955833435, 'Train/mean hd95_metric': 0.7442657947540283} +Epoch [3054/4000] Validation [1/4] Loss: 0.42291 focal_loss 0.35281 dice_loss 0.07010 +Epoch [3054/4000] Validation [2/4] Loss: 1.05243 focal_loss 0.86338 dice_loss 0.18905 +Epoch [3054/4000] Validation [3/4] Loss: 0.27216 focal_loss 0.21041 dice_loss 0.06175 +Epoch [3054/4000] Validation [4/4] Loss: 0.32628 focal_loss 0.23639 dice_loss 0.08989 +Epoch [3054/4000] Validation metric {'Val/mean dice_metric': 0.9733362197875977, 'Val/mean miou_metric': 0.9594511985778809, 'Val/mean f1': 0.9760205149650574, 'Val/mean precision': 0.9749512672424316, 'Val/mean recall': 0.9770920872688293, 'Val/mean hd95_metric': 4.78873348236084} +Cheakpoint... +Epoch [3054/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733362197875977, 'Val/mean miou_metric': 0.9594511985778809, 'Val/mean f1': 0.9760205149650574, 'Val/mean precision': 0.9749512672424316, 'Val/mean recall': 0.9770920872688293, 'Val/mean hd95_metric': 4.78873348236084} +Epoch [3055/4000] Training [1/16] Loss: 0.00258 +Epoch [3055/4000] Training [2/16] Loss: 0.00536 +Epoch [3055/4000] Training [3/16] Loss: 0.00366 +Epoch [3055/4000] Training [4/16] Loss: 0.00355 +Epoch [3055/4000] Training [5/16] Loss: 0.00333 +Epoch [3055/4000] Training [6/16] Loss: 0.00332 +Epoch [3055/4000] Training [7/16] Loss: 0.00281 +Epoch [3055/4000] Training [8/16] Loss: 0.00312 +Epoch [3055/4000] Training [9/16] Loss: 0.00246 +Epoch [3055/4000] Training [10/16] Loss: 0.00358 +Epoch [3055/4000] Training [11/16] Loss: 0.00307 +Epoch [3055/4000] Training [12/16] Loss: 0.00267 +Epoch [3055/4000] Training [13/16] Loss: 0.00310 +Epoch [3055/4000] Training [14/16] Loss: 0.00330 +Epoch [3055/4000] Training [15/16] Loss: 0.00274 +Epoch [3055/4000] Training [16/16] Loss: 0.00380 +Epoch [3055/4000] Training metric {'Train/mean dice_metric': 0.998180091381073, 'Train/mean miou_metric': 0.9960918426513672, 'Train/mean f1': 0.9933961033821106, 'Train/mean precision': 0.988902747631073, 'Train/mean recall': 0.9979304671287537, 'Train/mean hd95_metric': 0.7702279090881348} +Epoch [3055/4000] Validation [1/4] Loss: 0.32512 focal_loss 0.26528 dice_loss 0.05983 +Epoch [3055/4000] Validation [2/4] Loss: 0.52243 focal_loss 0.39904 dice_loss 0.12339 +Epoch [3055/4000] Validation [3/4] Loss: 0.50896 focal_loss 0.41454 dice_loss 0.09442 +Epoch [3055/4000] Validation [4/4] Loss: 0.50118 focal_loss 0.37082 dice_loss 0.13036 +Epoch [3055/4000] Validation metric {'Val/mean dice_metric': 0.9740961194038391, 'Val/mean miou_metric': 0.9593189358711243, 'Val/mean f1': 0.9758186936378479, 'Val/mean precision': 0.9741286635398865, 'Val/mean recall': 0.9775145649909973, 'Val/mean hd95_metric': 5.132067680358887} +Cheakpoint... +Epoch [3055/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740961194038391, 'Val/mean miou_metric': 0.9593189358711243, 'Val/mean f1': 0.9758186936378479, 'Val/mean precision': 0.9741286635398865, 'Val/mean recall': 0.9775145649909973, 'Val/mean hd95_metric': 5.132067680358887} +Epoch [3056/4000] Training [1/16] Loss: 0.00205 +Epoch [3056/4000] Training [2/16] Loss: 0.00243 +Epoch [3056/4000] Training [3/16] Loss: 0.00290 +Epoch [3056/4000] Training [4/16] Loss: 0.00536 +Epoch [3056/4000] Training [5/16] Loss: 0.00289 +Epoch [3056/4000] Training [6/16] Loss: 0.00592 +Epoch [3056/4000] Training [7/16] Loss: 0.00286 +Epoch [3056/4000] Training [8/16] Loss: 0.00285 +Epoch [3056/4000] Training [9/16] Loss: 0.00208 +Epoch [3056/4000] Training [10/16] Loss: 0.00252 +Epoch [3056/4000] Training [11/16] Loss: 0.00407 +Epoch [3056/4000] Training [12/16] Loss: 0.00304 +Epoch [3056/4000] Training [13/16] Loss: 0.00252 +Epoch [3056/4000] Training [14/16] Loss: 0.00274 +Epoch [3056/4000] Training [15/16] Loss: 0.00250 +Epoch [3056/4000] Training [16/16] Loss: 0.00223 +Epoch [3056/4000] Training metric {'Train/mean dice_metric': 0.9982811212539673, 'Train/mean miou_metric': 0.9962942600250244, 'Train/mean f1': 0.9934861063957214, 'Train/mean precision': 0.9889469742774963, 'Train/mean recall': 0.9980670213699341, 'Train/mean hd95_metric': 0.748688280582428} +Epoch [3056/4000] Validation [1/4] Loss: 0.38427 focal_loss 0.32003 dice_loss 0.06424 +Epoch [3056/4000] Validation [2/4] Loss: 0.53306 focal_loss 0.40881 dice_loss 0.12425 +Epoch [3056/4000] Validation [3/4] Loss: 0.50113 focal_loss 0.41077 dice_loss 0.09036 +Epoch [3056/4000] Validation [4/4] Loss: 0.34315 focal_loss 0.23873 dice_loss 0.10441 +Epoch [3056/4000] Validation metric {'Val/mean dice_metric': 0.9722358584403992, 'Val/mean miou_metric': 0.9581701159477234, 'Val/mean f1': 0.9758149981498718, 'Val/mean precision': 0.9744592308998108, 'Val/mean recall': 0.9771745800971985, 'Val/mean hd95_metric': 5.219786167144775} +Cheakpoint... +Epoch [3056/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722358584403992, 'Val/mean miou_metric': 0.9581701159477234, 'Val/mean f1': 0.9758149981498718, 'Val/mean precision': 0.9744592308998108, 'Val/mean recall': 0.9771745800971985, 'Val/mean hd95_metric': 5.219786167144775} +Epoch [3057/4000] Training [1/16] Loss: 0.00427 +Epoch [3057/4000] Training [2/16] Loss: 0.00397 +Epoch [3057/4000] Training [3/16] Loss: 0.00289 +Epoch [3057/4000] Training [4/16] Loss: 0.00340 +Epoch [3057/4000] Training [5/16] Loss: 0.00237 +Epoch [3057/4000] Training [6/16] Loss: 0.00328 +Epoch [3057/4000] Training [7/16] Loss: 0.00345 +Epoch [3057/4000] Training [8/16] Loss: 0.00348 +Epoch [3057/4000] Training [9/16] Loss: 0.00259 +Epoch [3057/4000] Training [10/16] Loss: 0.00438 +Epoch [3057/4000] Training [11/16] Loss: 0.00289 +Epoch [3057/4000] Training [12/16] Loss: 0.00276 +Epoch [3057/4000] Training [13/16] Loss: 0.00287 +Epoch [3057/4000] Training [14/16] Loss: 0.00495 +Epoch [3057/4000] Training [15/16] Loss: 0.00268 +Epoch [3057/4000] Training [16/16] Loss: 0.00350 +Epoch [3057/4000] Training metric {'Train/mean dice_metric': 0.9981690049171448, 'Train/mean miou_metric': 0.9960366487503052, 'Train/mean f1': 0.9925174713134766, 'Train/mean precision': 0.9872060418128967, 'Train/mean recall': 0.9978863596916199, 'Train/mean hd95_metric': 0.7514923810958862} +Epoch [3057/4000] Validation [1/4] Loss: 0.41510 focal_loss 0.35094 dice_loss 0.06416 +Epoch [3057/4000] Validation [2/4] Loss: 0.51889 focal_loss 0.40080 dice_loss 0.11808 +Epoch [3057/4000] Validation [3/4] Loss: 0.52522 focal_loss 0.42749 dice_loss 0.09773 +Epoch [3057/4000] Validation [4/4] Loss: 0.33372 focal_loss 0.23985 dice_loss 0.09387 +Epoch [3057/4000] Validation metric {'Val/mean dice_metric': 0.9747337102890015, 'Val/mean miou_metric': 0.9599091410636902, 'Val/mean f1': 0.9752379059791565, 'Val/mean precision': 0.9725000858306885, 'Val/mean recall': 0.9779912233352661, 'Val/mean hd95_metric': 4.833471298217773} +Cheakpoint... +Epoch [3057/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747337102890015, 'Val/mean miou_metric': 0.9599091410636902, 'Val/mean f1': 0.9752379059791565, 'Val/mean precision': 0.9725000858306885, 'Val/mean recall': 0.9779912233352661, 'Val/mean hd95_metric': 4.833471298217773} +Epoch [3058/4000] Training [1/16] Loss: 0.00298 +Epoch [3058/4000] Training [2/16] Loss: 0.00239 +Epoch [3058/4000] Training [3/16] Loss: 0.00305 +Epoch [3058/4000] Training [4/16] Loss: 0.00207 +Epoch [3058/4000] Training [5/16] Loss: 0.00337 +Epoch [3058/4000] Training [6/16] Loss: 0.00280 +Epoch [3058/4000] Training [7/16] Loss: 0.00371 +Epoch [3058/4000] Training [8/16] Loss: 0.00289 +Epoch [3058/4000] Training [9/16] Loss: 0.00229 +Epoch [3058/4000] Training [10/16] Loss: 0.00308 +Epoch [3058/4000] Training [11/16] Loss: 0.00286 +Epoch [3058/4000] Training [12/16] Loss: 0.00255 +Epoch [3058/4000] Training [13/16] Loss: 0.00255 +Epoch [3058/4000] Training [14/16] Loss: 0.00247 +Epoch [3058/4000] Training [15/16] Loss: 0.00262 +Epoch [3058/4000] Training [16/16] Loss: 0.00381 +Epoch [3058/4000] Training metric {'Train/mean dice_metric': 0.9983850717544556, 'Train/mean miou_metric': 0.996479332447052, 'Train/mean f1': 0.9932421445846558, 'Train/mean precision': 0.9884383082389832, 'Train/mean recall': 0.9980928301811218, 'Train/mean hd95_metric': 0.7679964303970337} +Epoch [3058/4000] Validation [1/4] Loss: 0.41532 focal_loss 0.35022 dice_loss 0.06509 +Epoch [3058/4000] Validation [2/4] Loss: 0.50901 focal_loss 0.38890 dice_loss 0.12011 +Epoch [3058/4000] Validation [3/4] Loss: 0.27264 focal_loss 0.19981 dice_loss 0.07283 +Epoch [3058/4000] Validation [4/4] Loss: 0.39148 focal_loss 0.28817 dice_loss 0.10332 +Epoch [3058/4000] Validation metric {'Val/mean dice_metric': 0.9746420979499817, 'Val/mean miou_metric': 0.9603345990180969, 'Val/mean f1': 0.976254940032959, 'Val/mean precision': 0.9743466377258301, 'Val/mean recall': 0.97817063331604, 'Val/mean hd95_metric': 4.9407243728637695} +Cheakpoint... +Epoch [3058/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746420979499817, 'Val/mean miou_metric': 0.9603345990180969, 'Val/mean f1': 0.976254940032959, 'Val/mean precision': 0.9743466377258301, 'Val/mean recall': 0.97817063331604, 'Val/mean hd95_metric': 4.9407243728637695} +Epoch [3059/4000] Training [1/16] Loss: 0.00309 +Epoch [3059/4000] Training [2/16] Loss: 0.00440 +Epoch [3059/4000] Training [3/16] Loss: 0.00367 +Epoch [3059/4000] Training [4/16] Loss: 0.00279 +Epoch [3059/4000] Training [5/16] Loss: 0.00359 +Epoch [3059/4000] Training [6/16] Loss: 0.00308 +Epoch [3059/4000] Training [7/16] Loss: 0.00288 +Epoch [3059/4000] Training [8/16] Loss: 0.00258 +Epoch [3059/4000] Training [9/16] Loss: 0.00299 +Epoch [3059/4000] Training [10/16] Loss: 0.00416 +Epoch [3059/4000] Training [11/16] Loss: 0.00340 +Epoch [3059/4000] Training [12/16] Loss: 0.00210 +Epoch [3059/4000] Training [13/16] Loss: 0.00223 +Epoch [3059/4000] Training [14/16] Loss: 0.00458 +Epoch [3059/4000] Training [15/16] Loss: 0.00307 +Epoch [3059/4000] Training [16/16] Loss: 0.00302 +Epoch [3059/4000] Training metric {'Train/mean dice_metric': 0.9982203245162964, 'Train/mean miou_metric': 0.9961736798286438, 'Train/mean f1': 0.9933999180793762, 'Train/mean precision': 0.9888224005699158, 'Train/mean recall': 0.9980199933052063, 'Train/mean hd95_metric': 0.7521061301231384} +Epoch [3059/4000] Validation [1/4] Loss: 0.40856 focal_loss 0.34384 dice_loss 0.06472 +Epoch [3059/4000] Validation [2/4] Loss: 1.03547 focal_loss 0.80467 dice_loss 0.23080 +Epoch [3059/4000] Validation [3/4] Loss: 0.48554 focal_loss 0.40044 dice_loss 0.08510 +Epoch [3059/4000] Validation [4/4] Loss: 0.35340 focal_loss 0.25478 dice_loss 0.09862 +Epoch [3059/4000] Validation metric {'Val/mean dice_metric': 0.9721380472183228, 'Val/mean miou_metric': 0.9581111669540405, 'Val/mean f1': 0.9756761789321899, 'Val/mean precision': 0.9738842248916626, 'Val/mean recall': 0.9774746894836426, 'Val/mean hd95_metric': 4.988364219665527} +Cheakpoint... +Epoch [3059/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721380472183228, 'Val/mean miou_metric': 0.9581111669540405, 'Val/mean f1': 0.9756761789321899, 'Val/mean precision': 0.9738842248916626, 'Val/mean recall': 0.9774746894836426, 'Val/mean hd95_metric': 4.988364219665527} +Epoch [3060/4000] Training [1/16] Loss: 0.00279 +Epoch [3060/4000] Training [2/16] Loss: 0.00273 +Epoch [3060/4000] Training [3/16] Loss: 0.00327 +Epoch [3060/4000] Training [4/16] Loss: 0.00338 +Epoch [3060/4000] Training [5/16] Loss: 0.00230 +Epoch [3060/4000] Training [6/16] Loss: 0.00308 +Epoch [3060/4000] Training [7/16] Loss: 0.00376 +Epoch [3060/4000] Training [8/16] Loss: 0.00321 +Epoch [3060/4000] Training [9/16] Loss: 0.00261 +Epoch [3060/4000] Training [10/16] Loss: 0.00264 +Epoch [3060/4000] Training [11/16] Loss: 0.00322 +Epoch [3060/4000] Training [12/16] Loss: 0.00286 +Epoch [3060/4000] Training [13/16] Loss: 0.00249 +Epoch [3060/4000] Training [14/16] Loss: 0.00245 +Epoch [3060/4000] Training [15/16] Loss: 0.00287 +Epoch [3060/4000] Training [16/16] Loss: 0.00257 +Epoch [3060/4000] Training metric {'Train/mean dice_metric': 0.9984105825424194, 'Train/mean miou_metric': 0.996526837348938, 'Train/mean f1': 0.9929154515266418, 'Train/mean precision': 0.9878223538398743, 'Train/mean recall': 0.9980613589286804, 'Train/mean hd95_metric': 0.7598909735679626} +Epoch [3060/4000] Validation [1/4] Loss: 0.40175 focal_loss 0.33661 dice_loss 0.06515 +Epoch [3060/4000] Validation [2/4] Loss: 1.43297 focal_loss 1.14905 dice_loss 0.28392 +Epoch [3060/4000] Validation [3/4] Loss: 0.29746 focal_loss 0.22687 dice_loss 0.07059 +Epoch [3060/4000] Validation [4/4] Loss: 0.58615 focal_loss 0.44315 dice_loss 0.14301 +Epoch [3060/4000] Validation metric {'Val/mean dice_metric': 0.9704355001449585, 'Val/mean miou_metric': 0.9561273455619812, 'Val/mean f1': 0.9740661382675171, 'Val/mean precision': 0.9728388786315918, 'Val/mean recall': 0.9752964973449707, 'Val/mean hd95_metric': 5.315140724182129} +Cheakpoint... +Epoch [3060/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9704], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9704355001449585, 'Val/mean miou_metric': 0.9561273455619812, 'Val/mean f1': 0.9740661382675171, 'Val/mean precision': 0.9728388786315918, 'Val/mean recall': 0.9752964973449707, 'Val/mean hd95_metric': 5.315140724182129} +Epoch [3061/4000] Training [1/16] Loss: 0.00302 +Epoch [3061/4000] Training [2/16] Loss: 0.00353 +Epoch [3061/4000] Training [3/16] Loss: 0.00350 +Epoch [3061/4000] Training [4/16] Loss: 0.00291 +Epoch [3061/4000] Training [5/16] Loss: 0.00375 +Epoch [3061/4000] Training [6/16] Loss: 0.00307 +Epoch [3061/4000] Training [7/16] Loss: 0.00314 +Epoch [3061/4000] Training [8/16] Loss: 0.00432 +Epoch [3061/4000] Training [9/16] Loss: 0.00219 +Epoch [3061/4000] Training [10/16] Loss: 0.00340 +Epoch [3061/4000] Training [11/16] Loss: 0.00304 +Epoch [3061/4000] Training [12/16] Loss: 0.00320 +Epoch [3061/4000] Training [13/16] Loss: 0.00212 +Epoch [3061/4000] Training [14/16] Loss: 0.00194 +Epoch [3061/4000] Training [15/16] Loss: 0.00344 +Epoch [3061/4000] Training [16/16] Loss: 0.00315 +Epoch [3061/4000] Training metric {'Train/mean dice_metric': 0.998198926448822, 'Train/mean miou_metric': 0.9961320161819458, 'Train/mean f1': 0.9934343099594116, 'Train/mean precision': 0.9890064001083374, 'Train/mean recall': 0.9979020357131958, 'Train/mean hd95_metric': 0.7866500616073608} +Epoch [3061/4000] Validation [1/4] Loss: 0.38933 focal_loss 0.32371 dice_loss 0.06562 +Epoch [3061/4000] Validation [2/4] Loss: 0.53388 focal_loss 0.41060 dice_loss 0.12328 +Epoch [3061/4000] Validation [3/4] Loss: 0.50228 focal_loss 0.40970 dice_loss 0.09258 +Epoch [3061/4000] Validation [4/4] Loss: 0.25025 focal_loss 0.16893 dice_loss 0.08133 +Epoch [3061/4000] Validation metric {'Val/mean dice_metric': 0.9732040166854858, 'Val/mean miou_metric': 0.9587545394897461, 'Val/mean f1': 0.9754418134689331, 'Val/mean precision': 0.9730108976364136, 'Val/mean recall': 0.9778848886489868, 'Val/mean hd95_metric': 5.244439125061035} +Cheakpoint... +Epoch [3061/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732040166854858, 'Val/mean miou_metric': 0.9587545394897461, 'Val/mean f1': 0.9754418134689331, 'Val/mean precision': 0.9730108976364136, 'Val/mean recall': 0.9778848886489868, 'Val/mean hd95_metric': 5.244439125061035} +Epoch [3062/4000] Training [1/16] Loss: 0.00267 +Epoch [3062/4000] Training [2/16] Loss: 0.00197 +Epoch [3062/4000] Training [3/16] Loss: 0.00375 +Epoch [3062/4000] Training [4/16] Loss: 0.00357 +Epoch [3062/4000] Training [5/16] Loss: 0.00327 +Epoch [3062/4000] Training [6/16] Loss: 0.00322 +Epoch [3062/4000] Training [7/16] Loss: 0.00344 +Epoch [3062/4000] Training [8/16] Loss: 0.00333 +Epoch [3062/4000] Training [9/16] Loss: 0.00262 +Epoch [3062/4000] Training [10/16] Loss: 0.00242 +Epoch [3062/4000] Training [11/16] Loss: 0.00246 +Epoch [3062/4000] Training [12/16] Loss: 0.00274 +Epoch [3062/4000] Training [13/16] Loss: 0.00304 +Epoch [3062/4000] Training [14/16] Loss: 0.00398 +Epoch [3062/4000] Training [15/16] Loss: 0.00323 +Epoch [3062/4000] Training [16/16] Loss: 0.00420 +Epoch [3062/4000] Training metric {'Train/mean dice_metric': 0.9982108473777771, 'Train/mean miou_metric': 0.9961549043655396, 'Train/mean f1': 0.9933946132659912, 'Train/mean precision': 0.9888080358505249, 'Train/mean recall': 0.9980239272117615, 'Train/mean hd95_metric': 0.7448518872261047} +Epoch [3062/4000] Validation [1/4] Loss: 0.40327 focal_loss 0.33735 dice_loss 0.06593 +Epoch [3062/4000] Validation [2/4] Loss: 0.57384 focal_loss 0.44315 dice_loss 0.13069 +Epoch [3062/4000] Validation [3/4] Loss: 0.32153 focal_loss 0.24678 dice_loss 0.07475 +Epoch [3062/4000] Validation [4/4] Loss: 0.33568 focal_loss 0.23332 dice_loss 0.10236 +Epoch [3062/4000] Validation metric {'Val/mean dice_metric': 0.9726682901382446, 'Val/mean miou_metric': 0.9583044052124023, 'Val/mean f1': 0.9755117893218994, 'Val/mean precision': 0.9745647311210632, 'Val/mean recall': 0.9764607548713684, 'Val/mean hd95_metric': 5.235489368438721} +Cheakpoint... +Epoch [3062/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726682901382446, 'Val/mean miou_metric': 0.9583044052124023, 'Val/mean f1': 0.9755117893218994, 'Val/mean precision': 0.9745647311210632, 'Val/mean recall': 0.9764607548713684, 'Val/mean hd95_metric': 5.235489368438721} +Epoch [3063/4000] Training [1/16] Loss: 0.00315 +Epoch [3063/4000] Training [2/16] Loss: 0.00323 +Epoch [3063/4000] Training [3/16] Loss: 0.00229 +Epoch [3063/4000] Training [4/16] Loss: 0.00367 +Epoch [3063/4000] Training [5/16] Loss: 0.00497 +Epoch [3063/4000] Training [6/16] Loss: 0.00415 +Epoch [3063/4000] Training [7/16] Loss: 0.00225 +Epoch [3063/4000] Training [8/16] Loss: 0.00217 +Epoch [3063/4000] Training [9/16] Loss: 0.00238 +Epoch [3063/4000] Training [10/16] Loss: 0.00232 +Epoch [3063/4000] Training [11/16] Loss: 0.00248 +Epoch [3063/4000] Training [12/16] Loss: 0.00212 +Epoch [3063/4000] Training [13/16] Loss: 0.00249 +Epoch [3063/4000] Training [14/16] Loss: 0.00293 +Epoch [3063/4000] Training [15/16] Loss: 0.00222 +Epoch [3063/4000] Training [16/16] Loss: 0.00485 +Epoch [3063/4000] Training metric {'Train/mean dice_metric': 0.9983173608779907, 'Train/mean miou_metric': 0.9963600635528564, 'Train/mean f1': 0.9934148192405701, 'Train/mean precision': 0.988842248916626, 'Train/mean recall': 0.998029887676239, 'Train/mean hd95_metric': 0.7249298691749573} +Epoch [3063/4000] Validation [1/4] Loss: 0.43510 focal_loss 0.36898 dice_loss 0.06612 +Epoch [3063/4000] Validation [2/4] Loss: 1.01280 focal_loss 0.82731 dice_loss 0.18549 +Epoch [3063/4000] Validation [3/4] Loss: 0.53847 focal_loss 0.44276 dice_loss 0.09571 +Epoch [3063/4000] Validation [4/4] Loss: 0.33113 focal_loss 0.24401 dice_loss 0.08713 +Epoch [3063/4000] Validation metric {'Val/mean dice_metric': 0.9728768467903137, 'Val/mean miou_metric': 0.9590345621109009, 'Val/mean f1': 0.9758662581443787, 'Val/mean precision': 0.974719762802124, 'Val/mean recall': 0.9770154356956482, 'Val/mean hd95_metric': 4.936698913574219} +Cheakpoint... +Epoch [3063/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728768467903137, 'Val/mean miou_metric': 0.9590345621109009, 'Val/mean f1': 0.9758662581443787, 'Val/mean precision': 0.974719762802124, 'Val/mean recall': 0.9770154356956482, 'Val/mean hd95_metric': 4.936698913574219} +Epoch [3064/4000] Training [1/16] Loss: 0.00373 +Epoch [3064/4000] Training [2/16] Loss: 0.00254 +Epoch [3064/4000] Training [3/16] Loss: 0.00465 +Epoch [3064/4000] Training [4/16] Loss: 0.00351 +Epoch [3064/4000] Training [5/16] Loss: 0.00330 +Epoch [3064/4000] Training [6/16] Loss: 0.00544 +Epoch [3064/4000] Training [7/16] Loss: 0.00368 +Epoch [3064/4000] Training [8/16] Loss: 0.00417 +Epoch [3064/4000] Training [9/16] Loss: 0.00518 +Epoch [3064/4000] Training [10/16] Loss: 0.00319 +Epoch [3064/4000] Training [11/16] Loss: 0.00295 +Epoch [3064/4000] Training [12/16] Loss: 0.00388 +Epoch [3064/4000] Training [13/16] Loss: 0.00388 +Epoch [3064/4000] Training [14/16] Loss: 0.00422 +Epoch [3064/4000] Training [15/16] Loss: 0.00318 +Epoch [3064/4000] Training [16/16] Loss: 0.00368 +Epoch [3064/4000] Training metric {'Train/mean dice_metric': 0.9980126619338989, 'Train/mean miou_metric': 0.9957605600357056, 'Train/mean f1': 0.993151843547821, 'Train/mean precision': 0.9886288642883301, 'Train/mean recall': 0.9977164268493652, 'Train/mean hd95_metric': 0.7950049638748169} +Epoch [3064/4000] Validation [1/4] Loss: 0.36948 focal_loss 0.30718 dice_loss 0.06230 +Epoch [3064/4000] Validation [2/4] Loss: 0.52473 focal_loss 0.40427 dice_loss 0.12046 +Epoch [3064/4000] Validation [3/4] Loss: 0.51196 focal_loss 0.41908 dice_loss 0.09288 +Epoch [3064/4000] Validation [4/4] Loss: 0.32551 focal_loss 0.22464 dice_loss 0.10087 +Epoch [3064/4000] Validation metric {'Val/mean dice_metric': 0.9734512567520142, 'Val/mean miou_metric': 0.9586569666862488, 'Val/mean f1': 0.9755880236625671, 'Val/mean precision': 0.9739405512809753, 'Val/mean recall': 0.977241039276123, 'Val/mean hd95_metric': 4.880314826965332} +Cheakpoint... +Epoch [3064/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734512567520142, 'Val/mean miou_metric': 0.9586569666862488, 'Val/mean f1': 0.9755880236625671, 'Val/mean precision': 0.9739405512809753, 'Val/mean recall': 0.977241039276123, 'Val/mean hd95_metric': 4.880314826965332} +Epoch [3065/4000] Training [1/16] Loss: 0.00348 +Epoch [3065/4000] Training [2/16] Loss: 0.00285 +Epoch [3065/4000] Training [3/16] Loss: 0.00264 +Epoch [3065/4000] Training [4/16] Loss: 0.00262 +Epoch [3065/4000] Training [5/16] Loss: 0.00431 +Epoch [3065/4000] Training [6/16] Loss: 0.00313 +Epoch [3065/4000] Training [7/16] Loss: 0.00275 +Epoch [3065/4000] Training [8/16] Loss: 0.00573 +Epoch [3065/4000] Training [9/16] Loss: 0.00431 +Epoch [3065/4000] Training [10/16] Loss: 0.00291 +Epoch [3065/4000] Training [11/16] Loss: 0.00248 +Epoch [3065/4000] Training [12/16] Loss: 0.00291 +Epoch [3065/4000] Training [13/16] Loss: 0.00320 +Epoch [3065/4000] Training [14/16] Loss: 0.00350 +Epoch [3065/4000] Training [15/16] Loss: 0.00239 +Epoch [3065/4000] Training [16/16] Loss: 0.00365 +Epoch [3065/4000] Training metric {'Train/mean dice_metric': 0.9981150031089783, 'Train/mean miou_metric': 0.9959512948989868, 'Train/mean f1': 0.9930068254470825, 'Train/mean precision': 0.9882346391677856, 'Train/mean recall': 0.9978253245353699, 'Train/mean hd95_metric': 0.8201459646224976} +Epoch [3065/4000] Validation [1/4] Loss: 0.39386 focal_loss 0.33054 dice_loss 0.06332 +Epoch [3065/4000] Validation [2/4] Loss: 0.51103 focal_loss 0.39327 dice_loss 0.11775 +Epoch [3065/4000] Validation [3/4] Loss: 0.51467 focal_loss 0.42179 dice_loss 0.09288 +Epoch [3065/4000] Validation [4/4] Loss: 0.34330 focal_loss 0.24879 dice_loss 0.09451 +Epoch [3065/4000] Validation metric {'Val/mean dice_metric': 0.9744378924369812, 'Val/mean miou_metric': 0.9600634574890137, 'Val/mean f1': 0.9759642481803894, 'Val/mean precision': 0.9732492566108704, 'Val/mean recall': 0.9786944389343262, 'Val/mean hd95_metric': 4.8941779136657715} +Cheakpoint... +Epoch [3065/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744378924369812, 'Val/mean miou_metric': 0.9600634574890137, 'Val/mean f1': 0.9759642481803894, 'Val/mean precision': 0.9732492566108704, 'Val/mean recall': 0.9786944389343262, 'Val/mean hd95_metric': 4.8941779136657715} +Epoch [3066/4000] Training [1/16] Loss: 0.00246 +Epoch [3066/4000] Training [2/16] Loss: 0.00251 +Epoch [3066/4000] Training [3/16] Loss: 0.00260 +Epoch [3066/4000] Training [4/16] Loss: 0.00261 +Epoch [3066/4000] Training [5/16] Loss: 0.00322 +Epoch [3066/4000] Training [6/16] Loss: 0.00314 +Epoch [3066/4000] Training [7/16] Loss: 0.00653 +Epoch [3066/4000] Training [8/16] Loss: 0.00332 +Epoch [3066/4000] Training [9/16] Loss: 0.00334 +Epoch [3066/4000] Training [10/16] Loss: 0.00309 +Epoch [3066/4000] Training [11/16] Loss: 0.00250 +Epoch [3066/4000] Training [12/16] Loss: 0.00391 +Epoch [3066/4000] Training [13/16] Loss: 0.00356 +Epoch [3066/4000] Training [14/16] Loss: 0.00248 +Epoch [3066/4000] Training [15/16] Loss: 0.00292 +Epoch [3066/4000] Training [16/16] Loss: 0.00287 +Epoch [3066/4000] Training metric {'Train/mean dice_metric': 0.9982815980911255, 'Train/mean miou_metric': 0.9962856769561768, 'Train/mean f1': 0.9934713244438171, 'Train/mean precision': 0.9888925552368164, 'Train/mean recall': 0.9980927109718323, 'Train/mean hd95_metric': 0.738797664642334} +Epoch [3066/4000] Validation [1/4] Loss: 0.42514 focal_loss 0.36131 dice_loss 0.06383 +Epoch [3066/4000] Validation [2/4] Loss: 1.07237 focal_loss 0.88679 dice_loss 0.18558 +Epoch [3066/4000] Validation [3/4] Loss: 0.54499 focal_loss 0.45032 dice_loss 0.09467 +Epoch [3066/4000] Validation [4/4] Loss: 0.40420 focal_loss 0.28231 dice_loss 0.12189 +Epoch [3066/4000] Validation metric {'Val/mean dice_metric': 0.972250759601593, 'Val/mean miou_metric': 0.957981288433075, 'Val/mean f1': 0.975710391998291, 'Val/mean precision': 0.9743158221244812, 'Val/mean recall': 0.9771090149879456, 'Val/mean hd95_metric': 5.139205455780029} +Cheakpoint... +Epoch [3066/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972250759601593, 'Val/mean miou_metric': 0.957981288433075, 'Val/mean f1': 0.975710391998291, 'Val/mean precision': 0.9743158221244812, 'Val/mean recall': 0.9771090149879456, 'Val/mean hd95_metric': 5.139205455780029} +Epoch [3067/4000] Training [1/16] Loss: 0.00271 +Epoch [3067/4000] Training [2/16] Loss: 0.00322 +Epoch [3067/4000] Training [3/16] Loss: 0.00351 +Epoch [3067/4000] Training [4/16] Loss: 0.00289 +Epoch [3067/4000] Training [5/16] Loss: 0.00303 +Epoch [3067/4000] Training [6/16] Loss: 0.00221 +Epoch [3067/4000] Training [7/16] Loss: 0.00265 +Epoch [3067/4000] Training [8/16] Loss: 0.00321 +Epoch [3067/4000] Training [9/16] Loss: 0.00309 +Epoch [3067/4000] Training [10/16] Loss: 0.00238 +Epoch [3067/4000] Training [11/16] Loss: 0.00288 +Epoch [3067/4000] Training [12/16] Loss: 0.00472 +Epoch [3067/4000] Training [13/16] Loss: 0.00194 +Epoch [3067/4000] Training [14/16] Loss: 0.00249 +Epoch [3067/4000] Training [15/16] Loss: 0.00425 +Epoch [3067/4000] Training [16/16] Loss: 0.00228 +Epoch [3067/4000] Training metric {'Train/mean dice_metric': 0.998397946357727, 'Train/mean miou_metric': 0.9965206384658813, 'Train/mean f1': 0.9934103488922119, 'Train/mean precision': 0.9887980818748474, 'Train/mean recall': 0.9980658888816833, 'Train/mean hd95_metric': 0.7190706729888916} +Epoch [3067/4000] Validation [1/4] Loss: 0.40009 focal_loss 0.33641 dice_loss 0.06368 +Epoch [3067/4000] Validation [2/4] Loss: 0.51280 focal_loss 0.39136 dice_loss 0.12144 +Epoch [3067/4000] Validation [3/4] Loss: 0.50661 focal_loss 0.41637 dice_loss 0.09024 +Epoch [3067/4000] Validation [4/4] Loss: 0.34715 focal_loss 0.24778 dice_loss 0.09937 +Epoch [3067/4000] Validation metric {'Val/mean dice_metric': 0.9731238484382629, 'Val/mean miou_metric': 0.9592134356498718, 'Val/mean f1': 0.9757125377655029, 'Val/mean precision': 0.9737088084220886, 'Val/mean recall': 0.9777244329452515, 'Val/mean hd95_metric': 5.283117294311523} +Cheakpoint... +Epoch [3067/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731238484382629, 'Val/mean miou_metric': 0.9592134356498718, 'Val/mean f1': 0.9757125377655029, 'Val/mean precision': 0.9737088084220886, 'Val/mean recall': 0.9777244329452515, 'Val/mean hd95_metric': 5.283117294311523} +Epoch [3068/4000] Training [1/16] Loss: 0.00258 +Epoch [3068/4000] Training [2/16] Loss: 0.00233 +Epoch [3068/4000] Training [3/16] Loss: 0.00270 +Epoch [3068/4000] Training [4/16] Loss: 0.00307 +Epoch [3068/4000] Training [5/16] Loss: 0.00471 +Epoch [3068/4000] Training [6/16] Loss: 0.00321 +Epoch [3068/4000] Training [7/16] Loss: 0.00306 +Epoch [3068/4000] Training [8/16] Loss: 0.00252 +Epoch [3068/4000] Training [9/16] Loss: 0.00286 +Epoch [3068/4000] Training [10/16] Loss: 0.00369 +Epoch [3068/4000] Training [11/16] Loss: 0.00287 +Epoch [3068/4000] Training [12/16] Loss: 0.00424 +Epoch [3068/4000] Training [13/16] Loss: 0.00265 +Epoch [3068/4000] Training [14/16] Loss: 0.00266 +Epoch [3068/4000] Training [15/16] Loss: 0.00328 +Epoch [3068/4000] Training [16/16] Loss: 0.00237 +Epoch [3068/4000] Training metric {'Train/mean dice_metric': 0.9982674717903137, 'Train/mean miou_metric': 0.9962506890296936, 'Train/mean f1': 0.9932872653007507, 'Train/mean precision': 0.9886077046394348, 'Train/mean recall': 0.9980114102363586, 'Train/mean hd95_metric': 0.773269772529602} +Epoch [3068/4000] Validation [1/4] Loss: 0.42209 focal_loss 0.35680 dice_loss 0.06529 +Epoch [3068/4000] Validation [2/4] Loss: 1.28821 focal_loss 1.04915 dice_loss 0.23906 +Epoch [3068/4000] Validation [3/4] Loss: 0.27784 focal_loss 0.21005 dice_loss 0.06780 +Epoch [3068/4000] Validation [4/4] Loss: 0.33308 focal_loss 0.23410 dice_loss 0.09897 +Epoch [3068/4000] Validation metric {'Val/mean dice_metric': 0.9726375341415405, 'Val/mean miou_metric': 0.9588967561721802, 'Val/mean f1': 0.9755924940109253, 'Val/mean precision': 0.9726740121841431, 'Val/mean recall': 0.9785284996032715, 'Val/mean hd95_metric': 4.832956790924072} +Cheakpoint... +Epoch [3068/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726375341415405, 'Val/mean miou_metric': 0.9588967561721802, 'Val/mean f1': 0.9755924940109253, 'Val/mean precision': 0.9726740121841431, 'Val/mean recall': 0.9785284996032715, 'Val/mean hd95_metric': 4.832956790924072} +Epoch [3069/4000] Training [1/16] Loss: 0.00332 +Epoch [3069/4000] Training [2/16] Loss: 0.00308 +Epoch [3069/4000] Training [3/16] Loss: 0.00231 +Epoch [3069/4000] Training [4/16] Loss: 0.00319 +Epoch [3069/4000] Training [5/16] Loss: 0.00315 +Epoch [3069/4000] Training [6/16] Loss: 0.00266 +Epoch [3069/4000] Training [7/16] Loss: 0.00270 +Epoch [3069/4000] Training [8/16] Loss: 0.00231 +Epoch [3069/4000] Training [9/16] Loss: 0.00216 +Epoch [3069/4000] Training [10/16] Loss: 0.00368 +Epoch [3069/4000] Training [11/16] Loss: 0.00248 +Epoch [3069/4000] Training [12/16] Loss: 0.00725 +Epoch [3069/4000] Training [13/16] Loss: 0.00336 +Epoch [3069/4000] Training [14/16] Loss: 0.00306 +Epoch [3069/4000] Training [15/16] Loss: 0.00246 +Epoch [3069/4000] Training [16/16] Loss: 0.00371 +Epoch [3069/4000] Training metric {'Train/mean dice_metric': 0.9982445240020752, 'Train/mean miou_metric': 0.9962190985679626, 'Train/mean f1': 0.9933090806007385, 'Train/mean precision': 0.988701343536377, 'Train/mean recall': 0.9979599118232727, 'Train/mean hd95_metric': 0.7657501697540283} +Epoch [3069/4000] Validation [1/4] Loss: 0.44860 focal_loss 0.37744 dice_loss 0.07115 +Epoch [3069/4000] Validation [2/4] Loss: 1.11825 focal_loss 0.92898 dice_loss 0.18927 +Epoch [3069/4000] Validation [3/4] Loss: 0.50863 focal_loss 0.41733 dice_loss 0.09129 +Epoch [3069/4000] Validation [4/4] Loss: 0.54449 focal_loss 0.40237 dice_loss 0.14213 +Epoch [3069/4000] Validation metric {'Val/mean dice_metric': 0.9717227220535278, 'Val/mean miou_metric': 0.9573208093643188, 'Val/mean f1': 0.9747060537338257, 'Val/mean precision': 0.9737140536308289, 'Val/mean recall': 0.9757001399993896, 'Val/mean hd95_metric': 4.885102272033691} +Cheakpoint... +Epoch [3069/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717227220535278, 'Val/mean miou_metric': 0.9573208093643188, 'Val/mean f1': 0.9747060537338257, 'Val/mean precision': 0.9737140536308289, 'Val/mean recall': 0.9757001399993896, 'Val/mean hd95_metric': 4.885102272033691} +Epoch [3070/4000] Training [1/16] Loss: 0.00292 +Epoch [3070/4000] Training [2/16] Loss: 0.00214 +Epoch [3070/4000] Training [3/16] Loss: 0.00345 +Epoch [3070/4000] Training [4/16] Loss: 0.00262 +Epoch [3070/4000] Training [5/16] Loss: 0.00335 +Epoch [3070/4000] Training [6/16] Loss: 0.00252 +Epoch [3070/4000] Training [7/16] Loss: 0.00339 +Epoch [3070/4000] Training [8/16] Loss: 0.00349 +Epoch [3070/4000] Training [9/16] Loss: 0.00257 +Epoch [3070/4000] Training [10/16] Loss: 0.00277 +Epoch [3070/4000] Training [11/16] Loss: 0.00246 +Epoch [3070/4000] Training [12/16] Loss: 0.00304 +Epoch [3070/4000] Training [13/16] Loss: 0.00277 +Epoch [3070/4000] Training [14/16] Loss: 0.00380 +Epoch [3070/4000] Training [15/16] Loss: 0.00319 +Epoch [3070/4000] Training [16/16] Loss: 0.00240 +Epoch [3070/4000] Training metric {'Train/mean dice_metric': 0.9983310699462891, 'Train/mean miou_metric': 0.9963593482971191, 'Train/mean f1': 0.9930758476257324, 'Train/mean precision': 0.9882464408874512, 'Train/mean recall': 0.9979526400566101, 'Train/mean hd95_metric': 0.6998153924942017} +Epoch [3070/4000] Validation [1/4] Loss: 0.47165 focal_loss 0.40192 dice_loss 0.06973 +Epoch [3070/4000] Validation [2/4] Loss: 0.51542 focal_loss 0.39202 dice_loss 0.12340 +Epoch [3070/4000] Validation [3/4] Loss: 0.54871 focal_loss 0.45053 dice_loss 0.09819 +Epoch [3070/4000] Validation [4/4] Loss: 0.58099 focal_loss 0.45284 dice_loss 0.12815 +Epoch [3070/4000] Validation metric {'Val/mean dice_metric': 0.9735589027404785, 'Val/mean miou_metric': 0.9585415720939636, 'Val/mean f1': 0.9747537970542908, 'Val/mean precision': 0.9738166928291321, 'Val/mean recall': 0.9756928086280823, 'Val/mean hd95_metric': 5.087472915649414} +Cheakpoint... +Epoch [3070/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735589027404785, 'Val/mean miou_metric': 0.9585415720939636, 'Val/mean f1': 0.9747537970542908, 'Val/mean precision': 0.9738166928291321, 'Val/mean recall': 0.9756928086280823, 'Val/mean hd95_metric': 5.087472915649414} +Epoch [3071/4000] Training [1/16] Loss: 0.00252 +Epoch [3071/4000] Training [2/16] Loss: 0.00268 +Epoch [3071/4000] Training [3/16] Loss: 0.00302 +Epoch [3071/4000] Training [4/16] Loss: 0.00223 +Epoch [3071/4000] Training [5/16] Loss: 0.00245 +Epoch [3071/4000] Training [6/16] Loss: 0.00334 +Epoch [3071/4000] Training [7/16] Loss: 0.00374 +Epoch [3071/4000] Training [8/16] Loss: 0.00267 +Epoch [3071/4000] Training [9/16] Loss: 0.00442 +Epoch [3071/4000] Training [10/16] Loss: 0.00285 +Epoch [3071/4000] Training [11/16] Loss: 0.00277 +Epoch [3071/4000] Training [12/16] Loss: 0.00466 +Epoch [3071/4000] Training [13/16] Loss: 0.00299 +Epoch [3071/4000] Training [14/16] Loss: 0.00342 +Epoch [3071/4000] Training [15/16] Loss: 0.00479 +Epoch [3071/4000] Training [16/16] Loss: 0.00340 +Epoch [3071/4000] Training metric {'Train/mean dice_metric': 0.9980891346931458, 'Train/mean miou_metric': 0.9959057569503784, 'Train/mean f1': 0.9931665658950806, 'Train/mean precision': 0.9885432720184326, 'Train/mean recall': 0.9978333711624146, 'Train/mean hd95_metric': 0.7427732944488525} +Epoch [3071/4000] Validation [1/4] Loss: 0.39296 focal_loss 0.32966 dice_loss 0.06331 +Epoch [3071/4000] Validation [2/4] Loss: 0.52863 focal_loss 0.40358 dice_loss 0.12504 +Epoch [3071/4000] Validation [3/4] Loss: 0.50615 focal_loss 0.41566 dice_loss 0.09049 +Epoch [3071/4000] Validation [4/4] Loss: 0.50037 focal_loss 0.36729 dice_loss 0.13309 +Epoch [3071/4000] Validation metric {'Val/mean dice_metric': 0.9724372625350952, 'Val/mean miou_metric': 0.9578868746757507, 'Val/mean f1': 0.9748743176460266, 'Val/mean precision': 0.9727331399917603, 'Val/mean recall': 0.9770251512527466, 'Val/mean hd95_metric': 5.512619495391846} +Cheakpoint... +Epoch [3071/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724372625350952, 'Val/mean miou_metric': 0.9578868746757507, 'Val/mean f1': 0.9748743176460266, 'Val/mean precision': 0.9727331399917603, 'Val/mean recall': 0.9770251512527466, 'Val/mean hd95_metric': 5.512619495391846} +Epoch [3072/4000] Training [1/16] Loss: 0.00361 +Epoch [3072/4000] Training [2/16] Loss: 0.00377 +Epoch [3072/4000] Training [3/16] Loss: 0.00345 +Epoch [3072/4000] Training [4/16] Loss: 0.00276 +Epoch [3072/4000] Training [5/16] Loss: 0.00412 +Epoch [3072/4000] Training [6/16] Loss: 0.00229 +Epoch [3072/4000] Training [7/16] Loss: 0.00370 +Epoch [3072/4000] Training [8/16] Loss: 0.00345 +Epoch [3072/4000] Training [9/16] Loss: 0.00230 +Epoch [3072/4000] Training [10/16] Loss: 0.00426 +Epoch [3072/4000] Training [11/16] Loss: 0.00298 +Epoch [3072/4000] Training [12/16] Loss: 0.00285 +Epoch [3072/4000] Training [13/16] Loss: 0.00276 +Epoch [3072/4000] Training [14/16] Loss: 0.00260 +Epoch [3072/4000] Training [15/16] Loss: 0.00277 +Epoch [3072/4000] Training [16/16] Loss: 0.00302 +Epoch [3072/4000] Training metric {'Train/mean dice_metric': 0.998142659664154, 'Train/mean miou_metric': 0.9960153698921204, 'Train/mean f1': 0.9931873083114624, 'Train/mean precision': 0.9885478019714355, 'Train/mean recall': 0.9978705644607544, 'Train/mean hd95_metric': 0.7544776797294617} +Epoch [3072/4000] Validation [1/4] Loss: 0.40783 focal_loss 0.34121 dice_loss 0.06661 +Epoch [3072/4000] Validation [2/4] Loss: 1.16868 focal_loss 0.98155 dice_loss 0.18713 +Epoch [3072/4000] Validation [3/4] Loss: 0.50895 focal_loss 0.41889 dice_loss 0.09006 +Epoch [3072/4000] Validation [4/4] Loss: 0.35550 focal_loss 0.25767 dice_loss 0.09783 +Epoch [3072/4000] Validation metric {'Val/mean dice_metric': 0.9720403552055359, 'Val/mean miou_metric': 0.9579719305038452, 'Val/mean f1': 0.9752005934715271, 'Val/mean precision': 0.9732592105865479, 'Val/mean recall': 0.9771495461463928, 'Val/mean hd95_metric': 5.045739650726318} +Cheakpoint... +Epoch [3072/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720403552055359, 'Val/mean miou_metric': 0.9579719305038452, 'Val/mean f1': 0.9752005934715271, 'Val/mean precision': 0.9732592105865479, 'Val/mean recall': 0.9771495461463928, 'Val/mean hd95_metric': 5.045739650726318} +Epoch [3073/4000] Training [1/16] Loss: 0.00238 +Epoch [3073/4000] Training [2/16] Loss: 0.00365 +Epoch [3073/4000] Training [3/16] Loss: 0.00593 +Epoch [3073/4000] Training [4/16] Loss: 0.00281 +Epoch [3073/4000] Training [5/16] Loss: 0.00288 +Epoch [3073/4000] Training [6/16] Loss: 0.00267 +Epoch [3073/4000] Training [7/16] Loss: 0.00239 +Epoch [3073/4000] Training [8/16] Loss: 0.00321 +Epoch [3073/4000] Training [9/16] Loss: 0.00227 +Epoch [3073/4000] Training [10/16] Loss: 0.00318 +Epoch [3073/4000] Training [11/16] Loss: 0.00246 +Epoch [3073/4000] Training [12/16] Loss: 0.00324 +Epoch [3073/4000] Training [13/16] Loss: 0.00374 +Epoch [3073/4000] Training [14/16] Loss: 0.00357 +Epoch [3073/4000] Training [15/16] Loss: 0.00296 +Epoch [3073/4000] Training [16/16] Loss: 0.00370 +Epoch [3073/4000] Training metric {'Train/mean dice_metric': 0.9982925057411194, 'Train/mean miou_metric': 0.9962933659553528, 'Train/mean f1': 0.9927999377250671, 'Train/mean precision': 0.9875989556312561, 'Train/mean recall': 0.9980559349060059, 'Train/mean hd95_metric': 0.7367464303970337} +Epoch [3073/4000] Validation [1/4] Loss: 0.38913 focal_loss 0.32488 dice_loss 0.06425 +Epoch [3073/4000] Validation [2/4] Loss: 0.53061 focal_loss 0.40754 dice_loss 0.12307 +Epoch [3073/4000] Validation [3/4] Loss: 0.51847 focal_loss 0.42704 dice_loss 0.09143 +Epoch [3073/4000] Validation [4/4] Loss: 0.42993 focal_loss 0.31703 dice_loss 0.11290 +Epoch [3073/4000] Validation metric {'Val/mean dice_metric': 0.9724302291870117, 'Val/mean miou_metric': 0.9581868052482605, 'Val/mean f1': 0.9752484560012817, 'Val/mean precision': 0.9736494421958923, 'Val/mean recall': 0.9768527150154114, 'Val/mean hd95_metric': 5.246030330657959} +Cheakpoint... +Epoch [3073/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724302291870117, 'Val/mean miou_metric': 0.9581868052482605, 'Val/mean f1': 0.9752484560012817, 'Val/mean precision': 0.9736494421958923, 'Val/mean recall': 0.9768527150154114, 'Val/mean hd95_metric': 5.246030330657959} +Epoch [3074/4000] Training [1/16] Loss: 0.00408 +Epoch [3074/4000] Training [2/16] Loss: 0.00228 +Epoch [3074/4000] Training [3/16] Loss: 0.00428 +Epoch [3074/4000] Training [4/16] Loss: 0.00283 +Epoch [3074/4000] Training [5/16] Loss: 0.00253 +Epoch [3074/4000] Training [6/16] Loss: 0.00388 +Epoch [3074/4000] Training [7/16] Loss: 0.00338 +Epoch [3074/4000] Training [8/16] Loss: 0.00295 +Epoch [3074/4000] Training [9/16] Loss: 0.00177 +Epoch [3074/4000] Training [10/16] Loss: 0.00333 +Epoch [3074/4000] Training [11/16] Loss: 0.00381 +Epoch [3074/4000] Training [12/16] Loss: 0.00396 +Epoch [3074/4000] Training [13/16] Loss: 0.00275 +Epoch [3074/4000] Training [14/16] Loss: 0.00247 +Epoch [3074/4000] Training [15/16] Loss: 0.00221 +Epoch [3074/4000] Training [16/16] Loss: 0.00367 +Epoch [3074/4000] Training metric {'Train/mean dice_metric': 0.9981979131698608, 'Train/mean miou_metric': 0.9961121082305908, 'Train/mean f1': 0.9931854009628296, 'Train/mean precision': 0.9885708093643188, 'Train/mean recall': 0.997843325138092, 'Train/mean hd95_metric': 0.7327980399131775} +Epoch [3074/4000] Validation [1/4] Loss: 0.40653 focal_loss 0.34105 dice_loss 0.06548 +Epoch [3074/4000] Validation [2/4] Loss: 1.20419 focal_loss 1.00762 dice_loss 0.19657 +Epoch [3074/4000] Validation [3/4] Loss: 0.55559 focal_loss 0.45391 dice_loss 0.10168 +Epoch [3074/4000] Validation [4/4] Loss: 0.31377 focal_loss 0.22593 dice_loss 0.08783 +Epoch [3074/4000] Validation metric {'Val/mean dice_metric': 0.9720527529716492, 'Val/mean miou_metric': 0.9577964544296265, 'Val/mean f1': 0.9752113223075867, 'Val/mean precision': 0.9741032123565674, 'Val/mean recall': 0.976321816444397, 'Val/mean hd95_metric': 4.790058135986328} +Cheakpoint... +Epoch [3074/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720527529716492, 'Val/mean miou_metric': 0.9577964544296265, 'Val/mean f1': 0.9752113223075867, 'Val/mean precision': 0.9741032123565674, 'Val/mean recall': 0.976321816444397, 'Val/mean hd95_metric': 4.790058135986328} +Epoch [3075/4000] Training [1/16] Loss: 0.00337 +Epoch [3075/4000] Training [2/16] Loss: 0.00366 +Epoch [3075/4000] Training [3/16] Loss: 0.00260 +Epoch [3075/4000] Training [4/16] Loss: 0.00252 +Epoch [3075/4000] Training [5/16] Loss: 0.00207 +Epoch [3075/4000] Training [6/16] Loss: 0.00350 +Epoch [3075/4000] Training [7/16] Loss: 0.00368 +Epoch [3075/4000] Training [8/16] Loss: 0.00338 +Epoch [3075/4000] Training [9/16] Loss: 0.00458 +Epoch [3075/4000] Training [10/16] Loss: 0.00268 +Epoch [3075/4000] Training [11/16] Loss: 0.00496 +Epoch [3075/4000] Training [12/16] Loss: 0.00352 +Epoch [3075/4000] Training [13/16] Loss: 0.00315 +Epoch [3075/4000] Training [14/16] Loss: 0.00226 +Epoch [3075/4000] Training [15/16] Loss: 0.00319 +Epoch [3075/4000] Training [16/16] Loss: 0.00241 +Epoch [3075/4000] Training metric {'Train/mean dice_metric': 0.9982664585113525, 'Train/mean miou_metric': 0.9962625503540039, 'Train/mean f1': 0.9934327602386475, 'Train/mean precision': 0.9889358878135681, 'Train/mean recall': 0.997970700263977, 'Train/mean hd95_metric': 0.7475862503051758} +Epoch [3075/4000] Validation [1/4] Loss: 0.39141 focal_loss 0.32746 dice_loss 0.06396 +Epoch [3075/4000] Validation [2/4] Loss: 0.52665 focal_loss 0.39636 dice_loss 0.13030 +Epoch [3075/4000] Validation [3/4] Loss: 0.49524 focal_loss 0.40563 dice_loss 0.08961 +Epoch [3075/4000] Validation [4/4] Loss: 0.31488 focal_loss 0.22330 dice_loss 0.09158 +Epoch [3075/4000] Validation metric {'Val/mean dice_metric': 0.9752804636955261, 'Val/mean miou_metric': 0.96051424741745, 'Val/mean f1': 0.976357638835907, 'Val/mean precision': 0.9738162159919739, 'Val/mean recall': 0.9789122343063354, 'Val/mean hd95_metric': 4.766785144805908} +Cheakpoint... +Epoch [3075/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752804636955261, 'Val/mean miou_metric': 0.96051424741745, 'Val/mean f1': 0.976357638835907, 'Val/mean precision': 0.9738162159919739, 'Val/mean recall': 0.9789122343063354, 'Val/mean hd95_metric': 4.766785144805908} +Epoch [3076/4000] Training [1/16] Loss: 0.00300 +Epoch [3076/4000] Training [2/16] Loss: 0.00381 +Epoch [3076/4000] Training [3/16] Loss: 0.00285 +Epoch [3076/4000] Training [4/16] Loss: 0.00509 +Epoch [3076/4000] Training [5/16] Loss: 0.00381 +Epoch [3076/4000] Training [6/16] Loss: 0.00219 +Epoch [3076/4000] Training [7/16] Loss: 0.00260 +Epoch [3076/4000] Training [8/16] Loss: 0.00544 +Epoch [3076/4000] Training [9/16] Loss: 0.00263 +Epoch [3076/4000] Training [10/16] Loss: 0.00356 +Epoch [3076/4000] Training [11/16] Loss: 0.00320 +Epoch [3076/4000] Training [12/16] Loss: 0.00397 +Epoch [3076/4000] Training [13/16] Loss: 0.00317 +Epoch [3076/4000] Training [14/16] Loss: 0.00303 +Epoch [3076/4000] Training [15/16] Loss: 0.00232 +Epoch [3076/4000] Training [16/16] Loss: 0.00317 +Epoch [3076/4000] Training metric {'Train/mean dice_metric': 0.9981706738471985, 'Train/mean miou_metric': 0.9960757493972778, 'Train/mean f1': 0.9933608770370483, 'Train/mean precision': 0.98876953125, 'Train/mean recall': 0.9979950785636902, 'Train/mean hd95_metric': 0.7243717908859253} +Epoch [3076/4000] Validation [1/4] Loss: 0.40467 focal_loss 0.34103 dice_loss 0.06364 +Epoch [3076/4000] Validation [2/4] Loss: 0.48946 focal_loss 0.37277 dice_loss 0.11670 +Epoch [3076/4000] Validation [3/4] Loss: 0.51808 focal_loss 0.42207 dice_loss 0.09601 +Epoch [3076/4000] Validation [4/4] Loss: 0.34737 focal_loss 0.24919 dice_loss 0.09818 +Epoch [3076/4000] Validation metric {'Val/mean dice_metric': 0.9730859994888306, 'Val/mean miou_metric': 0.9589549899101257, 'Val/mean f1': 0.9757742881774902, 'Val/mean precision': 0.9737252593040466, 'Val/mean recall': 0.9778319597244263, 'Val/mean hd95_metric': 4.973415374755859} +Cheakpoint... +Epoch [3076/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730859994888306, 'Val/mean miou_metric': 0.9589549899101257, 'Val/mean f1': 0.9757742881774902, 'Val/mean precision': 0.9737252593040466, 'Val/mean recall': 0.9778319597244263, 'Val/mean hd95_metric': 4.973415374755859} +Epoch [3077/4000] Training [1/16] Loss: 0.00217 +Epoch [3077/4000] Training [2/16] Loss: 0.00218 +Epoch [3077/4000] Training [3/16] Loss: 0.00263 +Epoch [3077/4000] Training [4/16] Loss: 0.00288 +Epoch [3077/4000] Training [5/16] Loss: 0.00213 +Epoch [3077/4000] Training [6/16] Loss: 0.00235 +Epoch [3077/4000] Training [7/16] Loss: 0.00331 +Epoch [3077/4000] Training [8/16] Loss: 0.00352 +Epoch [3077/4000] Training [9/16] Loss: 0.00281 +Epoch [3077/4000] Training [10/16] Loss: 0.00254 +Epoch [3077/4000] Training [11/16] Loss: 0.00225 +Epoch [3077/4000] Training [12/16] Loss: 0.00312 +Epoch [3077/4000] Training [13/16] Loss: 0.00356 +Epoch [3077/4000] Training [14/16] Loss: 0.00430 +Epoch [3077/4000] Training [15/16] Loss: 0.00314 +Epoch [3077/4000] Training [16/16] Loss: 0.00314 +Epoch [3077/4000] Training metric {'Train/mean dice_metric': 0.9984562397003174, 'Train/mean miou_metric': 0.9966403245925903, 'Train/mean f1': 0.9936428666114807, 'Train/mean precision': 0.9891899824142456, 'Train/mean recall': 0.9981359839439392, 'Train/mean hd95_metric': 0.7198517918586731} +Epoch [3077/4000] Validation [1/4] Loss: 0.41126 focal_loss 0.34630 dice_loss 0.06495 +Epoch [3077/4000] Validation [2/4] Loss: 1.14255 focal_loss 0.95026 dice_loss 0.19230 +Epoch [3077/4000] Validation [3/4] Loss: 0.51724 focal_loss 0.42275 dice_loss 0.09449 +Epoch [3077/4000] Validation [4/4] Loss: 0.37102 focal_loss 0.26014 dice_loss 0.11088 +Epoch [3077/4000] Validation metric {'Val/mean dice_metric': 0.9720567464828491, 'Val/mean miou_metric': 0.9582589864730835, 'Val/mean f1': 0.975598931312561, 'Val/mean precision': 0.9739652872085571, 'Val/mean recall': 0.9772379398345947, 'Val/mean hd95_metric': 4.997143745422363} +Cheakpoint... +Epoch [3077/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720567464828491, 'Val/mean miou_metric': 0.9582589864730835, 'Val/mean f1': 0.975598931312561, 'Val/mean precision': 0.9739652872085571, 'Val/mean recall': 0.9772379398345947, 'Val/mean hd95_metric': 4.997143745422363} +Epoch [3078/4000] Training [1/16] Loss: 0.00302 +Epoch [3078/4000] Training [2/16] Loss: 0.00299 +Epoch [3078/4000] Training [3/16] Loss: 0.00249 +Epoch [3078/4000] Training [4/16] Loss: 0.00238 +Epoch [3078/4000] Training [5/16] Loss: 0.00302 +Epoch [3078/4000] Training [6/16] Loss: 0.00399 +Epoch [3078/4000] Training [7/16] Loss: 0.00273 +Epoch [3078/4000] Training [8/16] Loss: 0.00224 +Epoch [3078/4000] Training [9/16] Loss: 0.00338 +Epoch [3078/4000] Training [10/16] Loss: 0.00372 +Epoch [3078/4000] Training [11/16] Loss: 0.00357 +Epoch [3078/4000] Training [12/16] Loss: 0.00324 +Epoch [3078/4000] Training [13/16] Loss: 0.00345 +Epoch [3078/4000] Training [14/16] Loss: 0.00333 +Epoch [3078/4000] Training [15/16] Loss: 0.00299 +Epoch [3078/4000] Training [16/16] Loss: 0.00290 +Epoch [3078/4000] Training metric {'Train/mean dice_metric': 0.9982750415802002, 'Train/mean miou_metric': 0.9962667226791382, 'Train/mean f1': 0.9933092594146729, 'Train/mean precision': 0.9887299537658691, 'Train/mean recall': 0.9979311227798462, 'Train/mean hd95_metric': 0.7655550241470337} +Epoch [3078/4000] Validation [1/4] Loss: 0.42020 focal_loss 0.35385 dice_loss 0.06636 +Epoch [3078/4000] Validation [2/4] Loss: 0.50192 focal_loss 0.37805 dice_loss 0.12387 +Epoch [3078/4000] Validation [3/4] Loss: 0.51342 focal_loss 0.42263 dice_loss 0.09079 +Epoch [3078/4000] Validation [4/4] Loss: 0.31870 focal_loss 0.23448 dice_loss 0.08423 +Epoch [3078/4000] Validation metric {'Val/mean dice_metric': 0.9733589291572571, 'Val/mean miou_metric': 0.9591097831726074, 'Val/mean f1': 0.9756574630737305, 'Val/mean precision': 0.9741089344024658, 'Val/mean recall': 0.9772109985351562, 'Val/mean hd95_metric': 4.91120719909668} +Cheakpoint... +Epoch [3078/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733589291572571, 'Val/mean miou_metric': 0.9591097831726074, 'Val/mean f1': 0.9756574630737305, 'Val/mean precision': 0.9741089344024658, 'Val/mean recall': 0.9772109985351562, 'Val/mean hd95_metric': 4.91120719909668} +Epoch [3079/4000] Training [1/16] Loss: 0.00337 +Epoch [3079/4000] Training [2/16] Loss: 0.00355 +Epoch [3079/4000] Training [3/16] Loss: 0.00241 +Epoch [3079/4000] Training [4/16] Loss: 0.00331 +Epoch [3079/4000] Training [5/16] Loss: 0.00316 +Epoch [3079/4000] Training [6/16] Loss: 0.00304 +Epoch [3079/4000] Training [7/16] Loss: 0.00274 +Epoch [3079/4000] Training [8/16] Loss: 0.00421 +Epoch [3079/4000] Training [9/16] Loss: 0.00368 +Epoch [3079/4000] Training [10/16] Loss: 0.00247 +Epoch [3079/4000] Training [11/16] Loss: 0.00342 +Epoch [3079/4000] Training [12/16] Loss: 0.00294 +Epoch [3079/4000] Training [13/16] Loss: 0.00373 +Epoch [3079/4000] Training [14/16] Loss: 0.00256 +Epoch [3079/4000] Training [15/16] Loss: 0.00205 +Epoch [3079/4000] Training [16/16] Loss: 0.00210 +Epoch [3079/4000] Training metric {'Train/mean dice_metric': 0.9983271956443787, 'Train/mean miou_metric': 0.9963865876197815, 'Train/mean f1': 0.993409276008606, 'Train/mean precision': 0.9888808131217957, 'Train/mean recall': 0.9979793429374695, 'Train/mean hd95_metric': 0.7114810943603516} +Epoch [3079/4000] Validation [1/4] Loss: 0.35434 focal_loss 0.29438 dice_loss 0.05997 +Epoch [3079/4000] Validation [2/4] Loss: 0.48414 focal_loss 0.36675 dice_loss 0.11740 +Epoch [3079/4000] Validation [3/4] Loss: 0.49331 focal_loss 0.39489 dice_loss 0.09841 +Epoch [3079/4000] Validation [4/4] Loss: 0.37444 focal_loss 0.27472 dice_loss 0.09973 +Epoch [3079/4000] Validation metric {'Val/mean dice_metric': 0.9735487103462219, 'Val/mean miou_metric': 0.959485650062561, 'Val/mean f1': 0.9763506054878235, 'Val/mean precision': 0.9746885299682617, 'Val/mean recall': 0.9780182838439941, 'Val/mean hd95_metric': 4.722780227661133} +Cheakpoint... +Epoch [3079/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735487103462219, 'Val/mean miou_metric': 0.959485650062561, 'Val/mean f1': 0.9763506054878235, 'Val/mean precision': 0.9746885299682617, 'Val/mean recall': 0.9780182838439941, 'Val/mean hd95_metric': 4.722780227661133} +Epoch [3080/4000] Training [1/16] Loss: 0.00340 +Epoch [3080/4000] Training [2/16] Loss: 0.00306 +Epoch [3080/4000] Training [3/16] Loss: 0.00367 +Epoch [3080/4000] Training [4/16] Loss: 0.00290 +Epoch [3080/4000] Training [5/16] Loss: 0.00363 +Epoch [3080/4000] Training [6/16] Loss: 0.00373 +Epoch [3080/4000] Training [7/16] Loss: 0.00219 +Epoch [3080/4000] Training [8/16] Loss: 0.00209 +Epoch [3080/4000] Training [9/16] Loss: 0.00247 +Epoch [3080/4000] Training [10/16] Loss: 0.00271 +Epoch [3080/4000] Training [11/16] Loss: 0.00279 +Epoch [3080/4000] Training [12/16] Loss: 0.00423 +Epoch [3080/4000] Training [13/16] Loss: 0.00270 +Epoch [3080/4000] Training [14/16] Loss: 0.00298 +Epoch [3080/4000] Training [15/16] Loss: 0.00300 +Epoch [3080/4000] Training [16/16] Loss: 0.00317 +Epoch [3080/4000] Training metric {'Train/mean dice_metric': 0.9982326030731201, 'Train/mean miou_metric': 0.9961684942245483, 'Train/mean f1': 0.9928555488586426, 'Train/mean precision': 0.987790048122406, 'Train/mean recall': 0.9979732036590576, 'Train/mean hd95_metric': 0.7478792071342468} +Epoch [3080/4000] Validation [1/4] Loss: 0.38104 focal_loss 0.31580 dice_loss 0.06524 +Epoch [3080/4000] Validation [2/4] Loss: 1.11300 focal_loss 0.92651 dice_loss 0.18649 +Epoch [3080/4000] Validation [3/4] Loss: 0.52053 focal_loss 0.42814 dice_loss 0.09239 +Epoch [3080/4000] Validation [4/4] Loss: 0.32681 focal_loss 0.23499 dice_loss 0.09182 +Epoch [3080/4000] Validation metric {'Val/mean dice_metric': 0.9728137850761414, 'Val/mean miou_metric': 0.9588481783866882, 'Val/mean f1': 0.9753862619400024, 'Val/mean precision': 0.9731502532958984, 'Val/mean recall': 0.9776327013969421, 'Val/mean hd95_metric': 4.907433986663818} +Cheakpoint... +Epoch [3080/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728137850761414, 'Val/mean miou_metric': 0.9588481783866882, 'Val/mean f1': 0.9753862619400024, 'Val/mean precision': 0.9731502532958984, 'Val/mean recall': 0.9776327013969421, 'Val/mean hd95_metric': 4.907433986663818} +Epoch [3081/4000] Training [1/16] Loss: 0.00327 +Epoch [3081/4000] Training [2/16] Loss: 0.00206 +Epoch [3081/4000] Training [3/16] Loss: 0.00256 +Epoch [3081/4000] Training [4/16] Loss: 0.00587 +Epoch [3081/4000] Training [5/16] Loss: 0.00226 +Epoch [3081/4000] Training [6/16] Loss: 0.00363 +Epoch [3081/4000] Training [7/16] Loss: 0.00245 +Epoch [3081/4000] Training [8/16] Loss: 0.00379 +Epoch [3081/4000] Training [9/16] Loss: 0.00474 +Epoch [3081/4000] Training [10/16] Loss: 0.00175 +Epoch [3081/4000] Training [11/16] Loss: 0.00334 +Epoch [3081/4000] Training [12/16] Loss: 0.00338 +Epoch [3081/4000] Training [13/16] Loss: 0.00382 +Epoch [3081/4000] Training [14/16] Loss: 0.00389 +Epoch [3081/4000] Training [15/16] Loss: 0.00290 +Epoch [3081/4000] Training [16/16] Loss: 0.00379 +Epoch [3081/4000] Training metric {'Train/mean dice_metric': 0.9982782602310181, 'Train/mean miou_metric': 0.996266782283783, 'Train/mean f1': 0.9931180477142334, 'Train/mean precision': 0.9882410168647766, 'Train/mean recall': 0.9980434775352478, 'Train/mean hd95_metric': 0.7411408424377441} +Epoch [3081/4000] Validation [1/4] Loss: 0.41808 focal_loss 0.35222 dice_loss 0.06586 +Epoch [3081/4000] Validation [2/4] Loss: 0.49166 focal_loss 0.37199 dice_loss 0.11967 +Epoch [3081/4000] Validation [3/4] Loss: 0.53014 focal_loss 0.43323 dice_loss 0.09692 +Epoch [3081/4000] Validation [4/4] Loss: 0.28021 focal_loss 0.18846 dice_loss 0.09174 +Epoch [3081/4000] Validation metric {'Val/mean dice_metric': 0.9735937118530273, 'Val/mean miou_metric': 0.959260106086731, 'Val/mean f1': 0.9758053421974182, 'Val/mean precision': 0.9739804863929749, 'Val/mean recall': 0.9776371121406555, 'Val/mean hd95_metric': 4.965351104736328} +Cheakpoint... +Epoch [3081/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735937118530273, 'Val/mean miou_metric': 0.959260106086731, 'Val/mean f1': 0.9758053421974182, 'Val/mean precision': 0.9739804863929749, 'Val/mean recall': 0.9776371121406555, 'Val/mean hd95_metric': 4.965351104736328} +Epoch [3082/4000] Training [1/16] Loss: 0.00432 +Epoch [3082/4000] Training [2/16] Loss: 0.00367 +Epoch [3082/4000] Training [3/16] Loss: 0.00198 +Epoch [3082/4000] Training [4/16] Loss: 0.00367 +Epoch [3082/4000] Training [5/16] Loss: 0.00316 +Epoch [3082/4000] Training [6/16] Loss: 0.00297 +Epoch [3082/4000] Training [7/16] Loss: 0.00345 +Epoch [3082/4000] Training [8/16] Loss: 0.00251 +Epoch [3082/4000] Training [9/16] Loss: 0.00579 +Epoch [3082/4000] Training [10/16] Loss: 0.00284 +Epoch [3082/4000] Training [11/16] Loss: 0.00344 +Epoch [3082/4000] Training [12/16] Loss: 0.00231 +Epoch [3082/4000] Training [13/16] Loss: 0.00304 +Epoch [3082/4000] Training [14/16] Loss: 0.00388 +Epoch [3082/4000] Training [15/16] Loss: 0.00256 +Epoch [3082/4000] Training [16/16] Loss: 0.00189 +Epoch [3082/4000] Training metric {'Train/mean dice_metric': 0.9982284903526306, 'Train/mean miou_metric': 0.9961888790130615, 'Train/mean f1': 0.9934303760528564, 'Train/mean precision': 0.9889140129089355, 'Train/mean recall': 0.9979881644248962, 'Train/mean hd95_metric': 0.7289894223213196} +Epoch [3082/4000] Validation [1/4] Loss: 0.38761 focal_loss 0.32258 dice_loss 0.06504 +Epoch [3082/4000] Validation [2/4] Loss: 0.93035 focal_loss 0.71868 dice_loss 0.21167 +Epoch [3082/4000] Validation [3/4] Loss: 0.53506 focal_loss 0.43254 dice_loss 0.10252 +Epoch [3082/4000] Validation [4/4] Loss: 0.39695 focal_loss 0.28998 dice_loss 0.10697 +Epoch [3082/4000] Validation metric {'Val/mean dice_metric': 0.9725604057312012, 'Val/mean miou_metric': 0.9577262997627258, 'Val/mean f1': 0.9752498269081116, 'Val/mean precision': 0.9744455814361572, 'Val/mean recall': 0.9760554432868958, 'Val/mean hd95_metric': 5.090953350067139} +Cheakpoint... +Epoch [3082/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725604057312012, 'Val/mean miou_metric': 0.9577262997627258, 'Val/mean f1': 0.9752498269081116, 'Val/mean precision': 0.9744455814361572, 'Val/mean recall': 0.9760554432868958, 'Val/mean hd95_metric': 5.090953350067139} +Epoch [3083/4000] Training [1/16] Loss: 0.00229 +Epoch [3083/4000] Training [2/16] Loss: 0.00300 +Epoch [3083/4000] Training [3/16] Loss: 0.00438 +Epoch [3083/4000] Training [4/16] Loss: 0.00352 +Epoch [3083/4000] Training [5/16] Loss: 0.00414 +Epoch [3083/4000] Training [6/16] Loss: 0.00238 +Epoch [3083/4000] Training [7/16] Loss: 0.00236 +Epoch [3083/4000] Training [8/16] Loss: 0.00337 +Epoch [3083/4000] Training [9/16] Loss: 0.00323 +Epoch [3083/4000] Training [10/16] Loss: 0.00307 +Epoch [3083/4000] Training [11/16] Loss: 0.00388 +Epoch [3083/4000] Training [12/16] Loss: 0.00293 +Epoch [3083/4000] Training [13/16] Loss: 0.00280 +Epoch [3083/4000] Training [14/16] Loss: 0.00276 +Epoch [3083/4000] Training [15/16] Loss: 0.00324 +Epoch [3083/4000] Training [16/16] Loss: 0.00270 +Epoch [3083/4000] Training metric {'Train/mean dice_metric': 0.9983667135238647, 'Train/mean miou_metric': 0.9964554309844971, 'Train/mean f1': 0.9933421611785889, 'Train/mean precision': 0.9887215495109558, 'Train/mean recall': 0.9980061650276184, 'Train/mean hd95_metric': 0.75608229637146} +Epoch [3083/4000] Validation [1/4] Loss: 0.33989 focal_loss 0.28162 dice_loss 0.05827 +Epoch [3083/4000] Validation [2/4] Loss: 1.08975 focal_loss 0.90381 dice_loss 0.18594 +Epoch [3083/4000] Validation [3/4] Loss: 0.52255 focal_loss 0.42773 dice_loss 0.09482 +Epoch [3083/4000] Validation [4/4] Loss: 0.33943 focal_loss 0.25337 dice_loss 0.08606 +Epoch [3083/4000] Validation metric {'Val/mean dice_metric': 0.9729217290878296, 'Val/mean miou_metric': 0.9592453241348267, 'Val/mean f1': 0.9756793975830078, 'Val/mean precision': 0.9740912914276123, 'Val/mean recall': 0.977272629737854, 'Val/mean hd95_metric': 5.459555625915527} +Cheakpoint... +Epoch [3083/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729217290878296, 'Val/mean miou_metric': 0.9592453241348267, 'Val/mean f1': 0.9756793975830078, 'Val/mean precision': 0.9740912914276123, 'Val/mean recall': 0.977272629737854, 'Val/mean hd95_metric': 5.459555625915527} +Epoch [3084/4000] Training [1/16] Loss: 0.00218 +Epoch [3084/4000] Training [2/16] Loss: 0.00239 +Epoch [3084/4000] Training [3/16] Loss: 0.00282 +Epoch [3084/4000] Training [4/16] Loss: 0.00221 +Epoch [3084/4000] Training [5/16] Loss: 0.00470 +Epoch [3084/4000] Training [6/16] Loss: 0.00238 +Epoch [3084/4000] Training [7/16] Loss: 0.00198 +Epoch [3084/4000] Training [8/16] Loss: 0.00301 +Epoch [3084/4000] Training [9/16] Loss: 0.00251 +Epoch [3084/4000] Training [10/16] Loss: 0.00353 +Epoch [3084/4000] Training [11/16] Loss: 0.00272 +Epoch [3084/4000] Training [12/16] Loss: 0.00348 +Epoch [3084/4000] Training [13/16] Loss: 0.00280 +Epoch [3084/4000] Training [14/16] Loss: 0.00391 +Epoch [3084/4000] Training [15/16] Loss: 0.00405 +Epoch [3084/4000] Training [16/16] Loss: 0.00303 +Epoch [3084/4000] Training metric {'Train/mean dice_metric': 0.9982069730758667, 'Train/mean miou_metric': 0.9961456656455994, 'Train/mean f1': 0.9933865070343018, 'Train/mean precision': 0.9888063073158264, 'Train/mean recall': 0.998009443283081, 'Train/mean hd95_metric': 0.7593055963516235} +Epoch [3084/4000] Validation [1/4] Loss: 0.36101 focal_loss 0.29668 dice_loss 0.06433 +Epoch [3084/4000] Validation [2/4] Loss: 0.90734 focal_loss 0.68994 dice_loss 0.21739 +Epoch [3084/4000] Validation [3/4] Loss: 0.29631 focal_loss 0.23279 dice_loss 0.06352 +Epoch [3084/4000] Validation [4/4] Loss: 0.36772 focal_loss 0.26508 dice_loss 0.10263 +Epoch [3084/4000] Validation metric {'Val/mean dice_metric': 0.9713481664657593, 'Val/mean miou_metric': 0.9566978216171265, 'Val/mean f1': 0.974745512008667, 'Val/mean precision': 0.9728962779045105, 'Val/mean recall': 0.9766017198562622, 'Val/mean hd95_metric': 5.315168857574463} +Cheakpoint... +Epoch [3084/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713481664657593, 'Val/mean miou_metric': 0.9566978216171265, 'Val/mean f1': 0.974745512008667, 'Val/mean precision': 0.9728962779045105, 'Val/mean recall': 0.9766017198562622, 'Val/mean hd95_metric': 5.315168857574463} +Epoch [3085/4000] Training [1/16] Loss: 0.00318 +Epoch [3085/4000] Training [2/16] Loss: 0.00355 +Epoch [3085/4000] Training [3/16] Loss: 0.00241 +Epoch [3085/4000] Training [4/16] Loss: 0.00375 +Epoch [3085/4000] Training [5/16] Loss: 0.00389 +Epoch [3085/4000] Training [6/16] Loss: 0.00388 +Epoch [3085/4000] Training [7/16] Loss: 0.00404 +Epoch [3085/4000] Training [8/16] Loss: 0.00392 +Epoch [3085/4000] Training [9/16] Loss: 0.00282 +Epoch [3085/4000] Training [10/16] Loss: 0.00326 +Epoch [3085/4000] Training [11/16] Loss: 0.00276 +Epoch [3085/4000] Training [12/16] Loss: 0.00190 +Epoch [3085/4000] Training [13/16] Loss: 0.00239 +Epoch [3085/4000] Training [14/16] Loss: 0.00260 +Epoch [3085/4000] Training [15/16] Loss: 0.00483 +Epoch [3085/4000] Training [16/16] Loss: 0.00294 +Epoch [3085/4000] Training metric {'Train/mean dice_metric': 0.998224139213562, 'Train/mean miou_metric': 0.9961791038513184, 'Train/mean f1': 0.9933431148529053, 'Train/mean precision': 0.9887791872024536, 'Train/mean recall': 0.9979494214057922, 'Train/mean hd95_metric': 0.7722232937812805} +Epoch [3085/4000] Validation [1/4] Loss: 0.38763 focal_loss 0.32269 dice_loss 0.06494 +Epoch [3085/4000] Validation [2/4] Loss: 0.64210 focal_loss 0.46192 dice_loss 0.18018 +Epoch [3085/4000] Validation [3/4] Loss: 0.25910 focal_loss 0.19055 dice_loss 0.06855 +Epoch [3085/4000] Validation [4/4] Loss: 0.34138 focal_loss 0.24446 dice_loss 0.09692 +Epoch [3085/4000] Validation metric {'Val/mean dice_metric': 0.9735120534896851, 'Val/mean miou_metric': 0.9589685201644897, 'Val/mean f1': 0.9757009744644165, 'Val/mean precision': 0.9722719192504883, 'Val/mean recall': 0.9791544079780579, 'Val/mean hd95_metric': 4.9317946434021} +Cheakpoint... +Epoch [3085/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735120534896851, 'Val/mean miou_metric': 0.9589685201644897, 'Val/mean f1': 0.9757009744644165, 'Val/mean precision': 0.9722719192504883, 'Val/mean recall': 0.9791544079780579, 'Val/mean hd95_metric': 4.9317946434021} +Epoch [3086/4000] Training [1/16] Loss: 0.00415 +Epoch [3086/4000] Training [2/16] Loss: 0.00240 +Epoch [3086/4000] Training [3/16] Loss: 0.00323 +Epoch [3086/4000] Training [4/16] Loss: 0.00240 +Epoch [3086/4000] Training [5/16] Loss: 0.00268 +Epoch [3086/4000] Training [6/16] Loss: 0.00304 +Epoch [3086/4000] Training [7/16] Loss: 0.00263 +Epoch [3086/4000] Training [8/16] Loss: 0.00442 +Epoch [3086/4000] Training [9/16] Loss: 0.00225 +Epoch [3086/4000] Training [10/16] Loss: 0.00187 +Epoch [3086/4000] Training [11/16] Loss: 0.00329 +Epoch [3086/4000] Training [12/16] Loss: 0.00230 +Epoch [3086/4000] Training [13/16] Loss: 0.00427 +Epoch [3086/4000] Training [14/16] Loss: 0.00280 +Epoch [3086/4000] Training [15/16] Loss: 0.00231 +Epoch [3086/4000] Training [16/16] Loss: 0.00189 +Epoch [3086/4000] Training metric {'Train/mean dice_metric': 0.9984005689620972, 'Train/mean miou_metric': 0.996522843837738, 'Train/mean f1': 0.9933516979217529, 'Train/mean precision': 0.9886594414710999, 'Train/mean recall': 0.9980887174606323, 'Train/mean hd95_metric': 0.7413639426231384} +Epoch [3086/4000] Validation [1/4] Loss: 0.38794 focal_loss 0.32396 dice_loss 0.06398 +Epoch [3086/4000] Validation [2/4] Loss: 0.43397 focal_loss 0.32092 dice_loss 0.11305 +Epoch [3086/4000] Validation [3/4] Loss: 0.32420 focal_loss 0.25040 dice_loss 0.07379 +Epoch [3086/4000] Validation [4/4] Loss: 0.44423 focal_loss 0.33379 dice_loss 0.11044 +Epoch [3086/4000] Validation metric {'Val/mean dice_metric': 0.9740459322929382, 'Val/mean miou_metric': 0.9597949981689453, 'Val/mean f1': 0.975908637046814, 'Val/mean precision': 0.9728266000747681, 'Val/mean recall': 0.9790103435516357, 'Val/mean hd95_metric': 5.1277174949646} +Cheakpoint... +Epoch [3086/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740459322929382, 'Val/mean miou_metric': 0.9597949981689453, 'Val/mean f1': 0.975908637046814, 'Val/mean precision': 0.9728266000747681, 'Val/mean recall': 0.9790103435516357, 'Val/mean hd95_metric': 5.1277174949646} +Epoch [3087/4000] Training [1/16] Loss: 0.00242 +Epoch [3087/4000] Training [2/16] Loss: 0.00229 +Epoch [3087/4000] Training [3/16] Loss: 0.00288 +Epoch [3087/4000] Training [4/16] Loss: 0.00358 +Epoch [3087/4000] Training [5/16] Loss: 0.00317 +Epoch [3087/4000] Training [6/16] Loss: 0.00223 +Epoch [3087/4000] Training [7/16] Loss: 0.00281 +Epoch [3087/4000] Training [8/16] Loss: 0.00350 +Epoch [3087/4000] Training [9/16] Loss: 0.00297 +Epoch [3087/4000] Training [10/16] Loss: 0.00212 +Epoch [3087/4000] Training [11/16] Loss: 0.00277 +Epoch [3087/4000] Training [12/16] Loss: 0.00245 +Epoch [3087/4000] Training [13/16] Loss: 0.00434 +Epoch [3087/4000] Training [14/16] Loss: 0.00341 +Epoch [3087/4000] Training [15/16] Loss: 0.00406 +Epoch [3087/4000] Training [16/16] Loss: 0.00251 +Epoch [3087/4000] Training metric {'Train/mean dice_metric': 0.9983955025672913, 'Train/mean miou_metric': 0.9965234398841858, 'Train/mean f1': 0.9935099482536316, 'Train/mean precision': 0.9890120029449463, 'Train/mean recall': 0.9980489611625671, 'Train/mean hd95_metric': 0.7190006971359253} +Epoch [3087/4000] Validation [1/4] Loss: 0.40644 focal_loss 0.34252 dice_loss 0.06392 +Epoch [3087/4000] Validation [2/4] Loss: 0.46707 focal_loss 0.34726 dice_loss 0.11981 +Epoch [3087/4000] Validation [3/4] Loss: 0.51587 focal_loss 0.41901 dice_loss 0.09685 +Epoch [3087/4000] Validation [4/4] Loss: 0.31709 focal_loss 0.22910 dice_loss 0.08799 +Epoch [3087/4000] Validation metric {'Val/mean dice_metric': 0.9738775491714478, 'Val/mean miou_metric': 0.9594218134880066, 'Val/mean f1': 0.97573322057724, 'Val/mean precision': 0.9729514122009277, 'Val/mean recall': 0.978531002998352, 'Val/mean hd95_metric': 5.112747669219971} +Cheakpoint... +Epoch [3087/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738775491714478, 'Val/mean miou_metric': 0.9594218134880066, 'Val/mean f1': 0.97573322057724, 'Val/mean precision': 0.9729514122009277, 'Val/mean recall': 0.978531002998352, 'Val/mean hd95_metric': 5.112747669219971} +Epoch [3088/4000] Training [1/16] Loss: 0.00371 +Epoch [3088/4000] Training [2/16] Loss: 0.00388 +Epoch [3088/4000] Training [3/16] Loss: 0.00349 +Epoch [3088/4000] Training [4/16] Loss: 0.00301 +Epoch [3088/4000] Training [5/16] Loss: 0.00263 +Epoch [3088/4000] Training [6/16] Loss: 0.00277 +Epoch [3088/4000] Training [7/16] Loss: 0.00343 +Epoch [3088/4000] Training [8/16] Loss: 0.00242 +Epoch [3088/4000] Training [9/16] Loss: 0.00249 +Epoch [3088/4000] Training [10/16] Loss: 0.00311 +Epoch [3088/4000] Training [11/16] Loss: 0.00363 +Epoch [3088/4000] Training [12/16] Loss: 0.00244 +Epoch [3088/4000] Training [13/16] Loss: 0.00230 +Epoch [3088/4000] Training [14/16] Loss: 0.00277 +Epoch [3088/4000] Training [15/16] Loss: 0.00365 +Epoch [3088/4000] Training [16/16] Loss: 0.00298 +Epoch [3088/4000] Training metric {'Train/mean dice_metric': 0.9981651306152344, 'Train/mean miou_metric': 0.9960525035858154, 'Train/mean f1': 0.9931393265724182, 'Train/mean precision': 0.9884665012359619, 'Train/mean recall': 0.9978565573692322, 'Train/mean hd95_metric': 0.7644177675247192} +Epoch [3088/4000] Validation [1/4] Loss: 0.36186 focal_loss 0.30123 dice_loss 0.06063 +Epoch [3088/4000] Validation [2/4] Loss: 0.88626 focal_loss 0.69467 dice_loss 0.19159 +Epoch [3088/4000] Validation [3/4] Loss: 0.50344 focal_loss 0.41378 dice_loss 0.08966 +Epoch [3088/4000] Validation [4/4] Loss: 0.45662 focal_loss 0.33584 dice_loss 0.12077 +Epoch [3088/4000] Validation metric {'Val/mean dice_metric': 0.972241997718811, 'Val/mean miou_metric': 0.9581406712532043, 'Val/mean f1': 0.975326657295227, 'Val/mean precision': 0.973193883895874, 'Val/mean recall': 0.9774688482284546, 'Val/mean hd95_metric': 4.910059452056885} +Cheakpoint... +Epoch [3088/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972241997718811, 'Val/mean miou_metric': 0.9581406712532043, 'Val/mean f1': 0.975326657295227, 'Val/mean precision': 0.973193883895874, 'Val/mean recall': 0.9774688482284546, 'Val/mean hd95_metric': 4.910059452056885} +Epoch [3089/4000] Training [1/16] Loss: 0.00242 +Epoch [3089/4000] Training [2/16] Loss: 0.00254 +Epoch [3089/4000] Training [3/16] Loss: 0.00240 +Epoch [3089/4000] Training [4/16] Loss: 0.00331 +Epoch [3089/4000] Training [5/16] Loss: 0.00327 +Epoch [3089/4000] Training [6/16] Loss: 0.00338 +Epoch [3089/4000] Training [7/16] Loss: 0.00494 +Epoch [3089/4000] Training [8/16] Loss: 0.00257 +Epoch [3089/4000] Training [9/16] Loss: 0.00441 +Epoch [3089/4000] Training [10/16] Loss: 0.00190 +Epoch [3089/4000] Training [11/16] Loss: 0.00320 +Epoch [3089/4000] Training [12/16] Loss: 0.00508 +Epoch [3089/4000] Training [13/16] Loss: 0.00246 +Epoch [3089/4000] Training [14/16] Loss: 0.00255 +Epoch [3089/4000] Training [15/16] Loss: 0.00253 +Epoch [3089/4000] Training [16/16] Loss: 0.00310 +Epoch [3089/4000] Training metric {'Train/mean dice_metric': 0.9982313513755798, 'Train/mean miou_metric': 0.9961761236190796, 'Train/mean f1': 0.9933041930198669, 'Train/mean precision': 0.9886553883552551, 'Train/mean recall': 0.9979968667030334, 'Train/mean hd95_metric': 0.73948073387146} +Epoch [3089/4000] Validation [1/4] Loss: 0.41976 focal_loss 0.35322 dice_loss 0.06654 +Epoch [3089/4000] Validation [2/4] Loss: 0.46736 focal_loss 0.34787 dice_loss 0.11949 +Epoch [3089/4000] Validation [3/4] Loss: 0.52356 focal_loss 0.43004 dice_loss 0.09352 +Epoch [3089/4000] Validation [4/4] Loss: 0.35625 focal_loss 0.26408 dice_loss 0.09218 +Epoch [3089/4000] Validation metric {'Val/mean dice_metric': 0.9741361737251282, 'Val/mean miou_metric': 0.9596160650253296, 'Val/mean f1': 0.9759503602981567, 'Val/mean precision': 0.9735798239707947, 'Val/mean recall': 0.9783322811126709, 'Val/mean hd95_metric': 4.981103897094727} +Cheakpoint... +Epoch [3089/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741361737251282, 'Val/mean miou_metric': 0.9596160650253296, 'Val/mean f1': 0.9759503602981567, 'Val/mean precision': 0.9735798239707947, 'Val/mean recall': 0.9783322811126709, 'Val/mean hd95_metric': 4.981103897094727} +Epoch [3090/4000] Training [1/16] Loss: 0.00324 +Epoch [3090/4000] Training [2/16] Loss: 0.00206 +Epoch [3090/4000] Training [3/16] Loss: 0.00193 +Epoch [3090/4000] Training [4/16] Loss: 0.00334 +Epoch [3090/4000] Training [5/16] Loss: 0.00426 +Epoch [3090/4000] Training [6/16] Loss: 0.00223 +Epoch [3090/4000] Training [7/16] Loss: 0.00342 +Epoch [3090/4000] Training [8/16] Loss: 0.00280 +Epoch [3090/4000] Training [9/16] Loss: 0.00311 +Epoch [3090/4000] Training [10/16] Loss: 0.00396 +Epoch [3090/4000] Training [11/16] Loss: 0.00201 +Epoch [3090/4000] Training [12/16] Loss: 0.00296 +Epoch [3090/4000] Training [13/16] Loss: 0.00292 +Epoch [3090/4000] Training [14/16] Loss: 0.00399 +Epoch [3090/4000] Training [15/16] Loss: 0.00264 +Epoch [3090/4000] Training [16/16] Loss: 0.00328 +Epoch [3090/4000] Training metric {'Train/mean dice_metric': 0.9984170794487, 'Train/mean miou_metric': 0.9965642690658569, 'Train/mean f1': 0.9935712218284607, 'Train/mean precision': 0.9890660047531128, 'Train/mean recall': 0.9981178045272827, 'Train/mean hd95_metric': 0.7161687016487122} +Epoch [3090/4000] Validation [1/4] Loss: 0.39066 focal_loss 0.32726 dice_loss 0.06340 +Epoch [3090/4000] Validation [2/4] Loss: 0.44290 focal_loss 0.32708 dice_loss 0.11582 +Epoch [3090/4000] Validation [3/4] Loss: 0.53560 focal_loss 0.44129 dice_loss 0.09431 +Epoch [3090/4000] Validation [4/4] Loss: 0.43561 focal_loss 0.32801 dice_loss 0.10760 +Epoch [3090/4000] Validation metric {'Val/mean dice_metric': 0.9756180047988892, 'Val/mean miou_metric': 0.9610563516616821, 'Val/mean f1': 0.9764869809150696, 'Val/mean precision': 0.9748947620391846, 'Val/mean recall': 0.9780844449996948, 'Val/mean hd95_metric': 4.977791786193848} +Cheakpoint... +Epoch [3090/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756180047988892, 'Val/mean miou_metric': 0.9610563516616821, 'Val/mean f1': 0.9764869809150696, 'Val/mean precision': 0.9748947620391846, 'Val/mean recall': 0.9780844449996948, 'Val/mean hd95_metric': 4.977791786193848} +Epoch [3091/4000] Training [1/16] Loss: 0.00293 +Epoch [3091/4000] Training [2/16] Loss: 0.00253 +Epoch [3091/4000] Training [3/16] Loss: 0.00348 +Epoch [3091/4000] Training [4/16] Loss: 0.00332 +Epoch [3091/4000] Training [5/16] Loss: 0.00295 +Epoch [3091/4000] Training [6/16] Loss: 0.00270 +Epoch [3091/4000] Training [7/16] Loss: 0.00346 +Epoch [3091/4000] Training [8/16] Loss: 0.00383 +Epoch [3091/4000] Training [9/16] Loss: 0.00248 +Epoch [3091/4000] Training [10/16] Loss: 0.00306 +Epoch [3091/4000] Training [11/16] Loss: 0.00255 +Epoch [3091/4000] Training [12/16] Loss: 0.00247 +Epoch [3091/4000] Training [13/16] Loss: 0.00329 +Epoch [3091/4000] Training [14/16] Loss: 0.00408 +Epoch [3091/4000] Training [15/16] Loss: 0.00384 +Epoch [3091/4000] Training [16/16] Loss: 0.00284 +Epoch [3091/4000] Training metric {'Train/mean dice_metric': 0.9981712698936462, 'Train/mean miou_metric': 0.9960755109786987, 'Train/mean f1': 0.9932680726051331, 'Train/mean precision': 0.9886939525604248, 'Train/mean recall': 0.9978847503662109, 'Train/mean hd95_metric': 0.7353579998016357} +Epoch [3091/4000] Validation [1/4] Loss: 0.43322 focal_loss 0.36639 dice_loss 0.06682 +Epoch [3091/4000] Validation [2/4] Loss: 0.46751 focal_loss 0.34781 dice_loss 0.11970 +Epoch [3091/4000] Validation [3/4] Loss: 0.50816 focal_loss 0.41752 dice_loss 0.09064 +Epoch [3091/4000] Validation [4/4] Loss: 0.36069 focal_loss 0.26748 dice_loss 0.09322 +Epoch [3091/4000] Validation metric {'Val/mean dice_metric': 0.9733112454414368, 'Val/mean miou_metric': 0.9588955044746399, 'Val/mean f1': 0.9756469130516052, 'Val/mean precision': 0.9742994904518127, 'Val/mean recall': 0.9769979119300842, 'Val/mean hd95_metric': 4.9487080574035645} +Cheakpoint... +Epoch [3091/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733112454414368, 'Val/mean miou_metric': 0.9588955044746399, 'Val/mean f1': 0.9756469130516052, 'Val/mean precision': 0.9742994904518127, 'Val/mean recall': 0.9769979119300842, 'Val/mean hd95_metric': 4.9487080574035645} +Epoch [3092/4000] Training [1/16] Loss: 0.00470 +Epoch [3092/4000] Training [2/16] Loss: 0.00298 +Epoch [3092/4000] Training [3/16] Loss: 0.00380 +Epoch [3092/4000] Training [4/16] Loss: 0.00270 +Epoch [3092/4000] Training [5/16] Loss: 0.00254 +Epoch [3092/4000] Training [6/16] Loss: 0.00266 +Epoch [3092/4000] Training [7/16] Loss: 0.00297 +Epoch [3092/4000] Training [8/16] Loss: 0.00319 +Epoch [3092/4000] Training [9/16] Loss: 0.00233 +Epoch [3092/4000] Training [10/16] Loss: 0.00280 +Epoch [3092/4000] Training [11/16] Loss: 0.00303 +Epoch [3092/4000] Training [12/16] Loss: 0.00340 +Epoch [3092/4000] Training [13/16] Loss: 0.00275 +Epoch [3092/4000] Training [14/16] Loss: 0.00407 +Epoch [3092/4000] Training [15/16] Loss: 0.00424 +Epoch [3092/4000] Training [16/16] Loss: 0.00313 +Epoch [3092/4000] Training metric {'Train/mean dice_metric': 0.998215913772583, 'Train/mean miou_metric': 0.9961374998092651, 'Train/mean f1': 0.9928556084632874, 'Train/mean precision': 0.9879249334335327, 'Train/mean recall': 0.9978358149528503, 'Train/mean hd95_metric': 0.7471954822540283} +Epoch [3092/4000] Validation [1/4] Loss: 0.39232 focal_loss 0.32671 dice_loss 0.06562 +Epoch [3092/4000] Validation [2/4] Loss: 1.10129 focal_loss 0.90375 dice_loss 0.19754 +Epoch [3092/4000] Validation [3/4] Loss: 0.51983 focal_loss 0.42792 dice_loss 0.09191 +Epoch [3092/4000] Validation [4/4] Loss: 0.43095 focal_loss 0.30688 dice_loss 0.12408 +Epoch [3092/4000] Validation metric {'Val/mean dice_metric': 0.9715389013290405, 'Val/mean miou_metric': 0.9570661783218384, 'Val/mean f1': 0.9749931693077087, 'Val/mean precision': 0.9733492732048035, 'Val/mean recall': 0.9766426682472229, 'Val/mean hd95_metric': 5.176328659057617} +Cheakpoint... +Epoch [3092/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715389013290405, 'Val/mean miou_metric': 0.9570661783218384, 'Val/mean f1': 0.9749931693077087, 'Val/mean precision': 0.9733492732048035, 'Val/mean recall': 0.9766426682472229, 'Val/mean hd95_metric': 5.176328659057617} +Epoch [3093/4000] Training [1/16] Loss: 0.00273 +Epoch [3093/4000] Training [2/16] Loss: 0.00293 +Epoch [3093/4000] Training [3/16] Loss: 0.00325 +Epoch [3093/4000] Training [4/16] Loss: 0.00268 +Epoch [3093/4000] Training [5/16] Loss: 0.00428 +Epoch [3093/4000] Training [6/16] Loss: 0.00294 +Epoch [3093/4000] Training [7/16] Loss: 0.00267 +Epoch [3093/4000] Training [8/16] Loss: 0.00225 +Epoch [3093/4000] Training [9/16] Loss: 0.00868 +Epoch [3093/4000] Training [10/16] Loss: 0.00258 +Epoch [3093/4000] Training [11/16] Loss: 0.00270 +Epoch [3093/4000] Training [12/16] Loss: 0.00241 +Epoch [3093/4000] Training [13/16] Loss: 0.00383 +Epoch [3093/4000] Training [14/16] Loss: 0.00283 +Epoch [3093/4000] Training [15/16] Loss: 0.00286 +Epoch [3093/4000] Training [16/16] Loss: 0.00282 +Epoch [3093/4000] Training metric {'Train/mean dice_metric': 0.9981430768966675, 'Train/mean miou_metric': 0.9960259199142456, 'Train/mean f1': 0.9933426380157471, 'Train/mean precision': 0.988743245601654, 'Train/mean recall': 0.9979850053787231, 'Train/mean hd95_metric': 0.784398078918457} +Epoch [3093/4000] Validation [1/4] Loss: 0.43809 focal_loss 0.37206 dice_loss 0.06604 +Epoch [3093/4000] Validation [2/4] Loss: 0.90409 focal_loss 0.68802 dice_loss 0.21608 +Epoch [3093/4000] Validation [3/4] Loss: 0.46275 focal_loss 0.37808 dice_loss 0.08467 +Epoch [3093/4000] Validation [4/4] Loss: 0.37714 focal_loss 0.27077 dice_loss 0.10636 +Epoch [3093/4000] Validation metric {'Val/mean dice_metric': 0.9713783264160156, 'Val/mean miou_metric': 0.957220196723938, 'Val/mean f1': 0.9749990701675415, 'Val/mean precision': 0.9730959534645081, 'Val/mean recall': 0.9769095182418823, 'Val/mean hd95_metric': 5.524064540863037} +Cheakpoint... +Epoch [3093/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9714], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713783264160156, 'Val/mean miou_metric': 0.957220196723938, 'Val/mean f1': 0.9749990701675415, 'Val/mean precision': 0.9730959534645081, 'Val/mean recall': 0.9769095182418823, 'Val/mean hd95_metric': 5.524064540863037} +Epoch [3094/4000] Training [1/16] Loss: 0.00271 +Epoch [3094/4000] Training [2/16] Loss: 0.00217 +Epoch [3094/4000] Training [3/16] Loss: 0.00335 +Epoch [3094/4000] Training [4/16] Loss: 0.00413 +Epoch [3094/4000] Training [5/16] Loss: 0.00365 +Epoch [3094/4000] Training [6/16] Loss: 0.00451 +Epoch [3094/4000] Training [7/16] Loss: 0.00282 +Epoch [3094/4000] Training [8/16] Loss: 0.01061 +Epoch [3094/4000] Training [9/16] Loss: 0.00397 +Epoch [3094/4000] Training [10/16] Loss: 0.00271 +Epoch [3094/4000] Training [11/16] Loss: 0.00324 +Epoch [3094/4000] Training [12/16] Loss: 0.00190 +Epoch [3094/4000] Training [13/16] Loss: 0.00501 +Epoch [3094/4000] Training [14/16] Loss: 0.00292 +Epoch [3094/4000] Training [15/16] Loss: 0.00324 +Epoch [3094/4000] Training [16/16] Loss: 0.00415 +Epoch [3094/4000] Training metric {'Train/mean dice_metric': 0.9980034232139587, 'Train/mean miou_metric': 0.9957476854324341, 'Train/mean f1': 0.9933273792266846, 'Train/mean precision': 0.9888449311256409, 'Train/mean recall': 0.9978505969047546, 'Train/mean hd95_metric': 0.7866936922073364} +Epoch [3094/4000] Validation [1/4] Loss: 0.38936 focal_loss 0.32480 dice_loss 0.06456 +Epoch [3094/4000] Validation [2/4] Loss: 0.98169 focal_loss 0.78981 dice_loss 0.19188 +Epoch [3094/4000] Validation [3/4] Loss: 0.49260 focal_loss 0.39795 dice_loss 0.09465 +Epoch [3094/4000] Validation [4/4] Loss: 0.35338 focal_loss 0.25128 dice_loss 0.10210 +Epoch [3094/4000] Validation metric {'Val/mean dice_metric': 0.9723696708679199, 'Val/mean miou_metric': 0.9580438733100891, 'Val/mean f1': 0.9757899641990662, 'Val/mean precision': 0.9742009043693542, 'Val/mean recall': 0.9773842096328735, 'Val/mean hd95_metric': 4.9612860679626465} +Cheakpoint... +Epoch [3094/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723696708679199, 'Val/mean miou_metric': 0.9580438733100891, 'Val/mean f1': 0.9757899641990662, 'Val/mean precision': 0.9742009043693542, 'Val/mean recall': 0.9773842096328735, 'Val/mean hd95_metric': 4.9612860679626465} +Epoch [3095/4000] Training [1/16] Loss: 0.00254 +Epoch [3095/4000] Training [2/16] Loss: 0.00351 +Epoch [3095/4000] Training [3/16] Loss: 0.00243 +Epoch [3095/4000] Training [4/16] Loss: 0.00361 +Epoch [3095/4000] Training [5/16] Loss: 0.00328 +Epoch [3095/4000] Training [6/16] Loss: 0.00299 +Epoch [3095/4000] Training [7/16] Loss: 0.00235 +Epoch [3095/4000] Training [8/16] Loss: 0.00295 +Epoch [3095/4000] Training [9/16] Loss: 0.00305 +Epoch [3095/4000] Training [10/16] Loss: 0.00200 +Epoch [3095/4000] Training [11/16] Loss: 0.00779 +Epoch [3095/4000] Training [12/16] Loss: 0.00374 +Epoch [3095/4000] Training [13/16] Loss: 0.00319 +Epoch [3095/4000] Training [14/16] Loss: 0.00257 +Epoch [3095/4000] Training [15/16] Loss: 0.00317 +Epoch [3095/4000] Training [16/16] Loss: 0.00293 +Epoch [3095/4000] Training metric {'Train/mean dice_metric': 0.9981824159622192, 'Train/mean miou_metric': 0.9961004257202148, 'Train/mean f1': 0.9934404492378235, 'Train/mean precision': 0.9889974594116211, 'Train/mean recall': 0.9979234337806702, 'Train/mean hd95_metric': 0.8041894435882568} +Epoch [3095/4000] Validation [1/4] Loss: 0.40186 focal_loss 0.33939 dice_loss 0.06247 +Epoch [3095/4000] Validation [2/4] Loss: 0.85712 focal_loss 0.64963 dice_loss 0.20749 +Epoch [3095/4000] Validation [3/4] Loss: 0.46129 focal_loss 0.36611 dice_loss 0.09519 +Epoch [3095/4000] Validation [4/4] Loss: 0.30907 focal_loss 0.22425 dice_loss 0.08482 +Epoch [3095/4000] Validation metric {'Val/mean dice_metric': 0.9728099703788757, 'Val/mean miou_metric': 0.9586156010627747, 'Val/mean f1': 0.9762941598892212, 'Val/mean precision': 0.9735230207443237, 'Val/mean recall': 0.9790811538696289, 'Val/mean hd95_metric': 4.9501543045043945} +Cheakpoint... +Epoch [3095/4000] best acc:tensor([0.9763], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728099703788757, 'Val/mean miou_metric': 0.9586156010627747, 'Val/mean f1': 0.9762941598892212, 'Val/mean precision': 0.9735230207443237, 'Val/mean recall': 0.9790811538696289, 'Val/mean hd95_metric': 4.9501543045043945} +Epoch [3096/4000] Training [1/16] Loss: 0.00278 +Epoch [3096/4000] Training [2/16] Loss: 0.00266 +Epoch [3096/4000] Training [3/16] Loss: 0.00251 +Epoch [3096/4000] Training [4/16] Loss: 0.00315 +Epoch [3096/4000] Training [5/16] Loss: 0.00296 +Epoch [3096/4000] Training [6/16] Loss: 0.00291 +Epoch [3096/4000] Training [7/16] Loss: 0.00375 +Epoch [3096/4000] Training [8/16] Loss: 0.00288 +Epoch [3096/4000] Training [9/16] Loss: 0.00267 +Epoch [3096/4000] Training [10/16] Loss: 0.00329 +Epoch [3096/4000] Training [11/16] Loss: 0.00268 +Epoch [3096/4000] Training [12/16] Loss: 0.00197 +Epoch [3096/4000] Training [13/16] Loss: 0.00425 +Epoch [3096/4000] Training [14/16] Loss: 0.00252 +Epoch [3096/4000] Training [15/16] Loss: 0.00225 +Epoch [3096/4000] Training [16/16] Loss: 0.00426 +Epoch [3096/4000] Training metric {'Train/mean dice_metric': 0.9983055591583252, 'Train/mean miou_metric': 0.9963414669036865, 'Train/mean f1': 0.9934329986572266, 'Train/mean precision': 0.9888713955879211, 'Train/mean recall': 0.9980369210243225, 'Train/mean hd95_metric': 0.7506413459777832} +Epoch [3096/4000] Validation [1/4] Loss: 0.38207 focal_loss 0.31984 dice_loss 0.06224 +Epoch [3096/4000] Validation [2/4] Loss: 0.44393 focal_loss 0.33255 dice_loss 0.11138 +Epoch [3096/4000] Validation [3/4] Loss: 0.26957 focal_loss 0.20356 dice_loss 0.06601 +Epoch [3096/4000] Validation [4/4] Loss: 0.30301 focal_loss 0.21835 dice_loss 0.08466 +Epoch [3096/4000] Validation metric {'Val/mean dice_metric': 0.9766683578491211, 'Val/mean miou_metric': 0.9627512693405151, 'Val/mean f1': 0.9770849943161011, 'Val/mean precision': 0.9734519124031067, 'Val/mean recall': 0.9807453155517578, 'Val/mean hd95_metric': 4.8563127517700195} +Cheakpoint... +Epoch [3096/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9767], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9766683578491211, 'Val/mean miou_metric': 0.9627512693405151, 'Val/mean f1': 0.9770849943161011, 'Val/mean precision': 0.9734519124031067, 'Val/mean recall': 0.9807453155517578, 'Val/mean hd95_metric': 4.8563127517700195} +Epoch [3097/4000] Training [1/16] Loss: 0.00336 +Epoch [3097/4000] Training [2/16] Loss: 0.00438 +Epoch [3097/4000] Training [3/16] Loss: 0.00277 +Epoch [3097/4000] Training [4/16] Loss: 0.00248 +Epoch [3097/4000] Training [5/16] Loss: 0.00307 +Epoch [3097/4000] Training [6/16] Loss: 0.00194 +Epoch [3097/4000] Training [7/16] Loss: 0.00238 +Epoch [3097/4000] Training [8/16] Loss: 0.00221 +Epoch [3097/4000] Training [9/16] Loss: 0.00374 +Epoch [3097/4000] Training [10/16] Loss: 0.00280 +Epoch [3097/4000] Training [11/16] Loss: 0.00467 +Epoch [3097/4000] Training [12/16] Loss: 0.00205 +Epoch [3097/4000] Training [13/16] Loss: 0.00283 +Epoch [3097/4000] Training [14/16] Loss: 0.00303 +Epoch [3097/4000] Training [15/16] Loss: 0.00232 +Epoch [3097/4000] Training [16/16] Loss: 0.00313 +Epoch [3097/4000] Training metric {'Train/mean dice_metric': 0.9982312917709351, 'Train/mean miou_metric': 0.9961675405502319, 'Train/mean f1': 0.9928202629089355, 'Train/mean precision': 0.9878465533256531, 'Train/mean recall': 0.9978442788124084, 'Train/mean hd95_metric': 0.7314735054969788} +Epoch [3097/4000] Validation [1/4] Loss: 0.38830 focal_loss 0.32502 dice_loss 0.06328 +Epoch [3097/4000] Validation [2/4] Loss: 0.91504 focal_loss 0.69896 dice_loss 0.21608 +Epoch [3097/4000] Validation [3/4] Loss: 0.50188 focal_loss 0.41164 dice_loss 0.09024 +Epoch [3097/4000] Validation [4/4] Loss: 0.44519 focal_loss 0.32768 dice_loss 0.11751 +Epoch [3097/4000] Validation metric {'Val/mean dice_metric': 0.972265899181366, 'Val/mean miou_metric': 0.9579157829284668, 'Val/mean f1': 0.975261390209198, 'Val/mean precision': 0.972272515296936, 'Val/mean recall': 0.9782686829566956, 'Val/mean hd95_metric': 5.027864933013916} +Cheakpoint... +Epoch [3097/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972265899181366, 'Val/mean miou_metric': 0.9579157829284668, 'Val/mean f1': 0.975261390209198, 'Val/mean precision': 0.972272515296936, 'Val/mean recall': 0.9782686829566956, 'Val/mean hd95_metric': 5.027864933013916} +Epoch [3098/4000] Training [1/16] Loss: 0.00309 +Epoch [3098/4000] Training [2/16] Loss: 0.00259 +Epoch [3098/4000] Training [3/16] Loss: 0.00372 +Epoch [3098/4000] Training [4/16] Loss: 0.00269 +Epoch [3098/4000] Training [5/16] Loss: 0.00337 +Epoch [3098/4000] Training [6/16] Loss: 0.00411 +Epoch [3098/4000] Training [7/16] Loss: 0.00229 +Epoch [3098/4000] Training [8/16] Loss: 0.00421 +Epoch [3098/4000] Training [9/16] Loss: 0.00174 +Epoch [3098/4000] Training [10/16] Loss: 0.00268 +Epoch [3098/4000] Training [11/16] Loss: 0.00384 +Epoch [3098/4000] Training [12/16] Loss: 0.00390 +Epoch [3098/4000] Training [13/16] Loss: 0.00383 +Epoch [3098/4000] Training [14/16] Loss: 0.00329 +Epoch [3098/4000] Training [15/16] Loss: 0.00302 +Epoch [3098/4000] Training [16/16] Loss: 0.00238 +Epoch [3098/4000] Training metric {'Train/mean dice_metric': 0.9982774257659912, 'Train/mean miou_metric': 0.9962722063064575, 'Train/mean f1': 0.9934405088424683, 'Train/mean precision': 0.9889072775840759, 'Train/mean recall': 0.9980154633522034, 'Train/mean hd95_metric': 0.7477813959121704} +Epoch [3098/4000] Validation [1/4] Loss: 0.40062 focal_loss 0.33699 dice_loss 0.06364 +Epoch [3098/4000] Validation [2/4] Loss: 0.47829 focal_loss 0.36443 dice_loss 0.11386 +Epoch [3098/4000] Validation [3/4] Loss: 0.51864 focal_loss 0.42173 dice_loss 0.09690 +Epoch [3098/4000] Validation [4/4] Loss: 0.33333 focal_loss 0.24170 dice_loss 0.09163 +Epoch [3098/4000] Validation metric {'Val/mean dice_metric': 0.9738434553146362, 'Val/mean miou_metric': 0.9597765803337097, 'Val/mean f1': 0.9763654470443726, 'Val/mean precision': 0.9750045537948608, 'Val/mean recall': 0.9777301549911499, 'Val/mean hd95_metric': 4.965045928955078} +Cheakpoint... +Epoch [3098/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738434553146362, 'Val/mean miou_metric': 0.9597765803337097, 'Val/mean f1': 0.9763654470443726, 'Val/mean precision': 0.9750045537948608, 'Val/mean recall': 0.9777301549911499, 'Val/mean hd95_metric': 4.965045928955078} +Epoch [3099/4000] Training [1/16] Loss: 0.00232 +Epoch [3099/4000] Training [2/16] Loss: 0.00455 +Epoch [3099/4000] Training [3/16] Loss: 0.00316 +Epoch [3099/4000] Training [4/16] Loss: 0.00421 +Epoch [3099/4000] Training [5/16] Loss: 0.00411 +Epoch [3099/4000] Training [6/16] Loss: 0.00323 +Epoch [3099/4000] Training [7/16] Loss: 0.00335 +Epoch [3099/4000] Training [8/16] Loss: 0.00480 +Epoch [3099/4000] Training [9/16] Loss: 0.00218 +Epoch [3099/4000] Training [10/16] Loss: 0.00235 +Epoch [3099/4000] Training [11/16] Loss: 0.00210 +Epoch [3099/4000] Training [12/16] Loss: 0.00244 +Epoch [3099/4000] Training [13/16] Loss: 0.00393 +Epoch [3099/4000] Training [14/16] Loss: 0.00318 +Epoch [3099/4000] Training [15/16] Loss: 0.00319 +Epoch [3099/4000] Training [16/16] Loss: 0.00181 +Epoch [3099/4000] Training metric {'Train/mean dice_metric': 0.9982819557189941, 'Train/mean miou_metric': 0.9962887167930603, 'Train/mean f1': 0.9934185743331909, 'Train/mean precision': 0.9888269901275635, 'Train/mean recall': 0.9980530738830566, 'Train/mean hd95_metric': 0.6962190270423889} +Epoch [3099/4000] Validation [1/4] Loss: 0.38207 focal_loss 0.31764 dice_loss 0.06443 +Epoch [3099/4000] Validation [2/4] Loss: 0.51158 focal_loss 0.38679 dice_loss 0.12479 +Epoch [3099/4000] Validation [3/4] Loss: 0.51101 focal_loss 0.41566 dice_loss 0.09535 +Epoch [3099/4000] Validation [4/4] Loss: 0.46697 focal_loss 0.34204 dice_loss 0.12494 +Epoch [3099/4000] Validation metric {'Val/mean dice_metric': 0.9720060229301453, 'Val/mean miou_metric': 0.9575021862983704, 'Val/mean f1': 0.9758685231208801, 'Val/mean precision': 0.9747807383537292, 'Val/mean recall': 0.976958692073822, 'Val/mean hd95_metric': 5.000523567199707} +Cheakpoint... +Epoch [3099/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720060229301453, 'Val/mean miou_metric': 0.9575021862983704, 'Val/mean f1': 0.9758685231208801, 'Val/mean precision': 0.9747807383537292, 'Val/mean recall': 0.976958692073822, 'Val/mean hd95_metric': 5.000523567199707} +Epoch [3100/4000] Training [1/16] Loss: 0.00254 +Epoch [3100/4000] Training [2/16] Loss: 0.00255 +Epoch [3100/4000] Training [3/16] Loss: 0.00208 +Epoch [3100/4000] Training [4/16] Loss: 0.00462 +Epoch [3100/4000] Training [5/16] Loss: 0.00262 +Epoch [3100/4000] Training [6/16] Loss: 0.00292 +Epoch [3100/4000] Training [7/16] Loss: 0.00242 +Epoch [3100/4000] Training [8/16] Loss: 0.00242 +Epoch [3100/4000] Training [9/16] Loss: 0.00343 +Epoch [3100/4000] Training [10/16] Loss: 0.00388 +Epoch [3100/4000] Training [11/16] Loss: 0.00206 +Epoch [3100/4000] Training [12/16] Loss: 0.00297 +Epoch [3100/4000] Training [13/16] Loss: 0.00260 +Epoch [3100/4000] Training [14/16] Loss: 0.00262 +Epoch [3100/4000] Training [15/16] Loss: 0.00365 +Epoch [3100/4000] Training [16/16] Loss: 0.00224 +Epoch [3100/4000] Training metric {'Train/mean dice_metric': 0.9985259771347046, 'Train/mean miou_metric': 0.996773362159729, 'Train/mean f1': 0.9934298396110535, 'Train/mean precision': 0.9887550473213196, 'Train/mean recall': 0.998149037361145, 'Train/mean hd95_metric': 0.6819609999656677} +Epoch [3100/4000] Validation [1/4] Loss: 0.40487 focal_loss 0.34091 dice_loss 0.06396 +Epoch [3100/4000] Validation [2/4] Loss: 0.70894 focal_loss 0.50803 dice_loss 0.20091 +Epoch [3100/4000] Validation [3/4] Loss: 0.51342 focal_loss 0.41597 dice_loss 0.09746 +Epoch [3100/4000] Validation [4/4] Loss: 0.35307 focal_loss 0.24254 dice_loss 0.11053 +Epoch [3100/4000] Validation metric {'Val/mean dice_metric': 0.9726244807243347, 'Val/mean miou_metric': 0.958521842956543, 'Val/mean f1': 0.9758034348487854, 'Val/mean precision': 0.9738000631332397, 'Val/mean recall': 0.9778152704238892, 'Val/mean hd95_metric': 4.803054332733154} +Cheakpoint... +Epoch [3100/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726244807243347, 'Val/mean miou_metric': 0.958521842956543, 'Val/mean f1': 0.9758034348487854, 'Val/mean precision': 0.9738000631332397, 'Val/mean recall': 0.9778152704238892, 'Val/mean hd95_metric': 4.803054332733154} +Epoch [3101/4000] Training [1/16] Loss: 0.00294 +Epoch [3101/4000] Training [2/16] Loss: 0.00286 +Epoch [3101/4000] Training [3/16] Loss: 0.00314 +Epoch [3101/4000] Training [4/16] Loss: 0.00199 +Epoch [3101/4000] Training [5/16] Loss: 0.00377 +Epoch [3101/4000] Training [6/16] Loss: 0.00401 +Epoch [3101/4000] Training [7/16] Loss: 0.00229 +Epoch [3101/4000] Training [8/16] Loss: 0.00412 +Epoch [3101/4000] Training [9/16] Loss: 0.00189 +Epoch [3101/4000] Training [10/16] Loss: 0.00200 +Epoch [3101/4000] Training [11/16] Loss: 0.00262 +Epoch [3101/4000] Training [12/16] Loss: 0.00259 +Epoch [3101/4000] Training [13/16] Loss: 0.00312 +Epoch [3101/4000] Training [14/16] Loss: 0.00288 +Epoch [3101/4000] Training [15/16] Loss: 0.00292 +Epoch [3101/4000] Training [16/16] Loss: 0.00236 +Epoch [3101/4000] Training metric {'Train/mean dice_metric': 0.9983768463134766, 'Train/mean miou_metric': 0.9964832067489624, 'Train/mean f1': 0.9934338927268982, 'Train/mean precision': 0.9888289570808411, 'Train/mean recall': 0.9980818629264832, 'Train/mean hd95_metric': 0.6900672912597656} +Epoch [3101/4000] Validation [1/4] Loss: 0.38629 focal_loss 0.32181 dice_loss 0.06448 +Epoch [3101/4000] Validation [2/4] Loss: 0.89009 focal_loss 0.67097 dice_loss 0.21913 +Epoch [3101/4000] Validation [3/4] Loss: 0.49962 focal_loss 0.40377 dice_loss 0.09585 +Epoch [3101/4000] Validation [4/4] Loss: 0.35397 focal_loss 0.25312 dice_loss 0.10086 +Epoch [3101/4000] Validation metric {'Val/mean dice_metric': 0.9731176495552063, 'Val/mean miou_metric': 0.9589527249336243, 'Val/mean f1': 0.9756187796592712, 'Val/mean precision': 0.9729647636413574, 'Val/mean recall': 0.9782872796058655, 'Val/mean hd95_metric': 4.809180736541748} +Cheakpoint... +Epoch [3101/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731176495552063, 'Val/mean miou_metric': 0.9589527249336243, 'Val/mean f1': 0.9756187796592712, 'Val/mean precision': 0.9729647636413574, 'Val/mean recall': 0.9782872796058655, 'Val/mean hd95_metric': 4.809180736541748} +Epoch [3102/4000] Training [1/16] Loss: 0.00303 +Epoch [3102/4000] Training [2/16] Loss: 0.00305 +Epoch [3102/4000] Training [3/16] Loss: 0.00437 +Epoch [3102/4000] Training [4/16] Loss: 0.00286 +Epoch [3102/4000] Training [5/16] Loss: 0.00335 +Epoch [3102/4000] Training [6/16] Loss: 0.00316 +Epoch [3102/4000] Training [7/16] Loss: 0.00310 +Epoch [3102/4000] Training [8/16] Loss: 0.00286 +Epoch [3102/4000] Training [9/16] Loss: 0.00257 +Epoch [3102/4000] Training [10/16] Loss: 0.00394 +Epoch [3102/4000] Training [11/16] Loss: 0.00259 +Epoch [3102/4000] Training [12/16] Loss: 0.00318 +Epoch [3102/4000] Training [13/16] Loss: 0.00283 +Epoch [3102/4000] Training [14/16] Loss: 0.00307 +Epoch [3102/4000] Training [15/16] Loss: 0.00308 +Epoch [3102/4000] Training [16/16] Loss: 0.00408 +Epoch [3102/4000] Training metric {'Train/mean dice_metric': 0.9982109069824219, 'Train/mean miou_metric': 0.9961539506912231, 'Train/mean f1': 0.9934750199317932, 'Train/mean precision': 0.9890007972717285, 'Train/mean recall': 0.9979899525642395, 'Train/mean hd95_metric': 0.7373600006103516} +Epoch [3102/4000] Validation [1/4] Loss: 0.37540 focal_loss 0.31180 dice_loss 0.06360 +Epoch [3102/4000] Validation [2/4] Loss: 0.97348 focal_loss 0.77842 dice_loss 0.19506 +Epoch [3102/4000] Validation [3/4] Loss: 0.52838 focal_loss 0.43463 dice_loss 0.09374 +Epoch [3102/4000] Validation [4/4] Loss: 0.32655 focal_loss 0.23550 dice_loss 0.09105 +Epoch [3102/4000] Validation metric {'Val/mean dice_metric': 0.9737103581428528, 'Val/mean miou_metric': 0.9594907760620117, 'Val/mean f1': 0.9762225151062012, 'Val/mean precision': 0.9740948677062988, 'Val/mean recall': 0.9783594012260437, 'Val/mean hd95_metric': 5.13289213180542} +Cheakpoint... +Epoch [3102/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737103581428528, 'Val/mean miou_metric': 0.9594907760620117, 'Val/mean f1': 0.9762225151062012, 'Val/mean precision': 0.9740948677062988, 'Val/mean recall': 0.9783594012260437, 'Val/mean hd95_metric': 5.13289213180542} +Epoch [3103/4000] Training [1/16] Loss: 0.00248 +Epoch [3103/4000] Training [2/16] Loss: 0.00308 +Epoch [3103/4000] Training [3/16] Loss: 0.00333 +Epoch [3103/4000] Training [4/16] Loss: 0.00333 +Epoch [3103/4000] Training [5/16] Loss: 0.00265 +Epoch [3103/4000] Training [6/16] Loss: 0.00192 +Epoch [3103/4000] Training [7/16] Loss: 0.00264 +Epoch [3103/4000] Training [8/16] Loss: 0.00319 +Epoch [3103/4000] Training [9/16] Loss: 0.00211 +Epoch [3103/4000] Training [10/16] Loss: 0.00265 +Epoch [3103/4000] Training [11/16] Loss: 0.00275 +Epoch [3103/4000] Training [12/16] Loss: 0.00306 +Epoch [3103/4000] Training [13/16] Loss: 0.00369 +Epoch [3103/4000] Training [14/16] Loss: 0.00297 +Epoch [3103/4000] Training [15/16] Loss: 0.00268 +Epoch [3103/4000] Training [16/16] Loss: 0.00319 +Epoch [3103/4000] Training metric {'Train/mean dice_metric': 0.9983997344970703, 'Train/mean miou_metric': 0.996493399143219, 'Train/mean f1': 0.9927554726600647, 'Train/mean precision': 0.9875690937042236, 'Train/mean recall': 0.9979966282844543, 'Train/mean hd95_metric': 0.7070866227149963} +Epoch [3103/4000] Validation [1/4] Loss: 0.37297 focal_loss 0.31150 dice_loss 0.06147 +Epoch [3103/4000] Validation [2/4] Loss: 0.45915 focal_loss 0.34350 dice_loss 0.11565 +Epoch [3103/4000] Validation [3/4] Loss: 0.50180 focal_loss 0.40632 dice_loss 0.09549 +Epoch [3103/4000] Validation [4/4] Loss: 0.34849 focal_loss 0.25566 dice_loss 0.09283 +Epoch [3103/4000] Validation metric {'Val/mean dice_metric': 0.9743286371231079, 'Val/mean miou_metric': 0.9599283337593079, 'Val/mean f1': 0.975610613822937, 'Val/mean precision': 0.9728168845176697, 'Val/mean recall': 0.9784203767776489, 'Val/mean hd95_metric': 4.936156749725342} +Cheakpoint... +Epoch [3103/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743286371231079, 'Val/mean miou_metric': 0.9599283337593079, 'Val/mean f1': 0.975610613822937, 'Val/mean precision': 0.9728168845176697, 'Val/mean recall': 0.9784203767776489, 'Val/mean hd95_metric': 4.936156749725342} +Epoch [3104/4000] Training [1/16] Loss: 0.00219 +Epoch [3104/4000] Training [2/16] Loss: 0.00239 +Epoch [3104/4000] Training [3/16] Loss: 0.00311 +Epoch [3104/4000] Training [4/16] Loss: 0.00379 +Epoch [3104/4000] Training [5/16] Loss: 0.00260 +Epoch [3104/4000] Training [6/16] Loss: 0.00238 +Epoch [3104/4000] Training [7/16] Loss: 0.00306 +Epoch [3104/4000] Training [8/16] Loss: 0.00291 +Epoch [3104/4000] Training [9/16] Loss: 0.00505 +Epoch [3104/4000] Training [10/16] Loss: 0.00364 +Epoch [3104/4000] Training [11/16] Loss: 0.00389 +Epoch [3104/4000] Training [12/16] Loss: 0.00173 +Epoch [3104/4000] Training [13/16] Loss: 0.00383 +Epoch [3104/4000] Training [14/16] Loss: 0.00236 +Epoch [3104/4000] Training [15/16] Loss: 0.00250 +Epoch [3104/4000] Training [16/16] Loss: 0.00285 +Epoch [3104/4000] Training metric {'Train/mean dice_metric': 0.9982741475105286, 'Train/mean miou_metric': 0.9962756633758545, 'Train/mean f1': 0.9933408498764038, 'Train/mean precision': 0.9887065887451172, 'Train/mean recall': 0.998018741607666, 'Train/mean hd95_metric': 0.725769579410553} +Epoch [3104/4000] Validation [1/4] Loss: 0.40114 focal_loss 0.33754 dice_loss 0.06359 +Epoch [3104/4000] Validation [2/4] Loss: 0.77957 focal_loss 0.58883 dice_loss 0.19075 +Epoch [3104/4000] Validation [3/4] Loss: 0.51159 focal_loss 0.41958 dice_loss 0.09200 +Epoch [3104/4000] Validation [4/4] Loss: 0.35912 focal_loss 0.26190 dice_loss 0.09722 +Epoch [3104/4000] Validation metric {'Val/mean dice_metric': 0.9719089269638062, 'Val/mean miou_metric': 0.9577539563179016, 'Val/mean f1': 0.9753528237342834, 'Val/mean precision': 0.9724740982055664, 'Val/mean recall': 0.9782487154006958, 'Val/mean hd95_metric': 4.830496788024902} +Cheakpoint... +Epoch [3104/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719089269638062, 'Val/mean miou_metric': 0.9577539563179016, 'Val/mean f1': 0.9753528237342834, 'Val/mean precision': 0.9724740982055664, 'Val/mean recall': 0.9782487154006958, 'Val/mean hd95_metric': 4.830496788024902} +Epoch [3105/4000] Training [1/16] Loss: 0.00414 +Epoch [3105/4000] Training [2/16] Loss: 0.00245 +Epoch [3105/4000] Training [3/16] Loss: 0.00249 +Epoch [3105/4000] Training [4/16] Loss: 0.00238 +Epoch [3105/4000] Training [5/16] Loss: 0.00298 +Epoch [3105/4000] Training [6/16] Loss: 0.00339 +Epoch [3105/4000] Training [7/16] Loss: 0.00306 +Epoch [3105/4000] Training [8/16] Loss: 0.00445 +Epoch [3105/4000] Training [9/16] Loss: 0.00315 +Epoch [3105/4000] Training [10/16] Loss: 0.00351 +Epoch [3105/4000] Training [11/16] Loss: 0.00260 +Epoch [3105/4000] Training [12/16] Loss: 0.00358 +Epoch [3105/4000] Training [13/16] Loss: 0.00320 +Epoch [3105/4000] Training [14/16] Loss: 0.00462 +Epoch [3105/4000] Training [15/16] Loss: 0.00239 +Epoch [3105/4000] Training [16/16] Loss: 0.00317 +Epoch [3105/4000] Training metric {'Train/mean dice_metric': 0.9981766939163208, 'Train/mean miou_metric': 0.9960881471633911, 'Train/mean f1': 0.9934074878692627, 'Train/mean precision': 0.9888719320297241, 'Train/mean recall': 0.9979848265647888, 'Train/mean hd95_metric': 0.7192156314849854} +Epoch [3105/4000] Validation [1/4] Loss: 0.45835 focal_loss 0.38867 dice_loss 0.06968 +Epoch [3105/4000] Validation [2/4] Loss: 0.45020 focal_loss 0.33422 dice_loss 0.11598 +Epoch [3105/4000] Validation [3/4] Loss: 0.56129 focal_loss 0.46250 dice_loss 0.09880 +Epoch [3105/4000] Validation [4/4] Loss: 0.32059 focal_loss 0.22003 dice_loss 0.10056 +Epoch [3105/4000] Validation metric {'Val/mean dice_metric': 0.9739590883255005, 'Val/mean miou_metric': 0.9593942761421204, 'Val/mean f1': 0.9757037162780762, 'Val/mean precision': 0.9712923765182495, 'Val/mean recall': 0.9801551103591919, 'Val/mean hd95_metric': 5.577253818511963} +Cheakpoint... +Epoch [3105/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739590883255005, 'Val/mean miou_metric': 0.9593942761421204, 'Val/mean f1': 0.9757037162780762, 'Val/mean precision': 0.9712923765182495, 'Val/mean recall': 0.9801551103591919, 'Val/mean hd95_metric': 5.577253818511963} +Epoch [3106/4000] Training [1/16] Loss: 0.00219 +Epoch [3106/4000] Training [2/16] Loss: 0.00300 +Epoch [3106/4000] Training [3/16] Loss: 0.00219 +Epoch [3106/4000] Training [4/16] Loss: 0.00261 +Epoch [3106/4000] Training [5/16] Loss: 0.00414 +Epoch [3106/4000] Training [6/16] Loss: 0.00217 +Epoch [3106/4000] Training [7/16] Loss: 0.00302 +Epoch [3106/4000] Training [8/16] Loss: 0.00193 +Epoch [3106/4000] Training [9/16] Loss: 0.00216 +Epoch [3106/4000] Training [10/16] Loss: 0.00295 +Epoch [3106/4000] Training [11/16] Loss: 0.00308 +Epoch [3106/4000] Training [12/16] Loss: 0.00411 +Epoch [3106/4000] Training [13/16] Loss: 0.00218 +Epoch [3106/4000] Training [14/16] Loss: 0.00423 +Epoch [3106/4000] Training [15/16] Loss: 0.00290 +Epoch [3106/4000] Training [16/16] Loss: 0.00378 +Epoch [3106/4000] Training metric {'Train/mean dice_metric': 0.9983465671539307, 'Train/mean miou_metric': 0.996415913105011, 'Train/mean f1': 0.9933528304100037, 'Train/mean precision': 0.9886777997016907, 'Train/mean recall': 0.9980722069740295, 'Train/mean hd95_metric': 0.7250009775161743} +Epoch [3106/4000] Validation [1/4] Loss: 0.42766 focal_loss 0.36472 dice_loss 0.06293 +Epoch [3106/4000] Validation [2/4] Loss: 0.53265 focal_loss 0.40184 dice_loss 0.13081 +Epoch [3106/4000] Validation [3/4] Loss: 0.35404 focal_loss 0.27296 dice_loss 0.08108 +Epoch [3106/4000] Validation [4/4] Loss: 0.35974 focal_loss 0.25227 dice_loss 0.10747 +Epoch [3106/4000] Validation metric {'Val/mean dice_metric': 0.9749500155448914, 'Val/mean miou_metric': 0.960285484790802, 'Val/mean f1': 0.9763367772102356, 'Val/mean precision': 0.9713165760040283, 'Val/mean recall': 0.9814091920852661, 'Val/mean hd95_metric': 5.349240779876709} +Cheakpoint... +Epoch [3106/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749500155448914, 'Val/mean miou_metric': 0.960285484790802, 'Val/mean f1': 0.9763367772102356, 'Val/mean precision': 0.9713165760040283, 'Val/mean recall': 0.9814091920852661, 'Val/mean hd95_metric': 5.349240779876709} +Epoch [3107/4000] Training [1/16] Loss: 0.00283 +Epoch [3107/4000] Training [2/16] Loss: 0.00188 +Epoch [3107/4000] Training [3/16] Loss: 0.00299 +Epoch [3107/4000] Training [4/16] Loss: 0.00240 +Epoch [3107/4000] Training [5/16] Loss: 0.00374 +Epoch [3107/4000] Training [6/16] Loss: 0.00279 +Epoch [3107/4000] Training [7/16] Loss: 0.00591 +Epoch [3107/4000] Training [8/16] Loss: 0.00263 +Epoch [3107/4000] Training [9/16] Loss: 0.00365 +Epoch [3107/4000] Training [10/16] Loss: 0.00390 +Epoch [3107/4000] Training [11/16] Loss: 0.00185 +Epoch [3107/4000] Training [12/16] Loss: 0.00466 +Epoch [3107/4000] Training [13/16] Loss: 0.00303 +Epoch [3107/4000] Training [14/16] Loss: 0.00304 +Epoch [3107/4000] Training [15/16] Loss: 0.00207 +Epoch [3107/4000] Training [16/16] Loss: 0.00383 +Epoch [3107/4000] Training metric {'Train/mean dice_metric': 0.9982309341430664, 'Train/mean miou_metric': 0.9961915016174316, 'Train/mean f1': 0.9933085441589355, 'Train/mean precision': 0.9886816740036011, 'Train/mean recall': 0.997978925704956, 'Train/mean hd95_metric': 0.7303448915481567} +Epoch [3107/4000] Validation [1/4] Loss: 0.43765 focal_loss 0.37087 dice_loss 0.06679 +Epoch [3107/4000] Validation [2/4] Loss: 0.35260 focal_loss 0.25320 dice_loss 0.09940 +Epoch [3107/4000] Validation [3/4] Loss: 0.28865 focal_loss 0.21650 dice_loss 0.07215 +Epoch [3107/4000] Validation [4/4] Loss: 0.33963 focal_loss 0.24141 dice_loss 0.09823 +Epoch [3107/4000] Validation metric {'Val/mean dice_metric': 0.9746068716049194, 'Val/mean miou_metric': 0.9600647687911987, 'Val/mean f1': 0.9762881398200989, 'Val/mean precision': 0.9722291827201843, 'Val/mean recall': 0.980381190776825, 'Val/mean hd95_metric': 4.897812366485596} +Cheakpoint... +Epoch [3107/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746068716049194, 'Val/mean miou_metric': 0.9600647687911987, 'Val/mean f1': 0.9762881398200989, 'Val/mean precision': 0.9722291827201843, 'Val/mean recall': 0.980381190776825, 'Val/mean hd95_metric': 4.897812366485596} +Epoch [3108/4000] Training [1/16] Loss: 0.00446 +Epoch [3108/4000] Training [2/16] Loss: 0.00257 +Epoch [3108/4000] Training [3/16] Loss: 0.00413 +Epoch [3108/4000] Training [4/16] Loss: 0.00370 +Epoch [3108/4000] Training [5/16] Loss: 0.00279 +Epoch [3108/4000] Training [6/16] Loss: 0.00270 +Epoch [3108/4000] Training [7/16] Loss: 0.00321 +Epoch [3108/4000] Training [8/16] Loss: 0.00316 +Epoch [3108/4000] Training [9/16] Loss: 0.00201 +Epoch [3108/4000] Training [10/16] Loss: 0.00201 +Epoch [3108/4000] Training [11/16] Loss: 0.00319 +Epoch [3108/4000] Training [12/16] Loss: 0.00312 +Epoch [3108/4000] Training [13/16] Loss: 0.00369 +Epoch [3108/4000] Training [14/16] Loss: 0.00254 +Epoch [3108/4000] Training [15/16] Loss: 0.00220 +Epoch [3108/4000] Training [16/16] Loss: 0.00188 +Epoch [3108/4000] Training metric {'Train/mean dice_metric': 0.9984387755393982, 'Train/mean miou_metric': 0.9965465068817139, 'Train/mean f1': 0.9923582673072815, 'Train/mean precision': 0.9867815375328064, 'Train/mean recall': 0.9979983568191528, 'Train/mean hd95_metric': 0.7060823440551758} +Epoch [3108/4000] Validation [1/4] Loss: 0.38383 focal_loss 0.31946 dice_loss 0.06437 +Epoch [3108/4000] Validation [2/4] Loss: 0.33165 focal_loss 0.23635 dice_loss 0.09530 +Epoch [3108/4000] Validation [3/4] Loss: 0.26693 focal_loss 0.19690 dice_loss 0.07003 +Epoch [3108/4000] Validation [4/4] Loss: 0.34542 focal_loss 0.24705 dice_loss 0.09837 +Epoch [3108/4000] Validation metric {'Val/mean dice_metric': 0.9751510620117188, 'Val/mean miou_metric': 0.9611071348190308, 'Val/mean f1': 0.9758278131484985, 'Val/mean precision': 0.9716296195983887, 'Val/mean recall': 0.9800624847412109, 'Val/mean hd95_metric': 4.793454170227051} +Cheakpoint... +Epoch [3108/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751510620117188, 'Val/mean miou_metric': 0.9611071348190308, 'Val/mean f1': 0.9758278131484985, 'Val/mean precision': 0.9716296195983887, 'Val/mean recall': 0.9800624847412109, 'Val/mean hd95_metric': 4.793454170227051} +Epoch [3109/4000] Training [1/16] Loss: 0.00350 +Epoch [3109/4000] Training [2/16] Loss: 0.00448 +Epoch [3109/4000] Training [3/16] Loss: 0.00264 +Epoch [3109/4000] Training [4/16] Loss: 0.00211 +Epoch [3109/4000] Training [5/16] Loss: 0.00233 +Epoch [3109/4000] Training [6/16] Loss: 0.00335 +Epoch [3109/4000] Training [7/16] Loss: 0.00418 +Epoch [3109/4000] Training [8/16] Loss: 0.00292 +Epoch [3109/4000] Training [9/16] Loss: 0.00301 +Epoch [3109/4000] Training [10/16] Loss: 0.00261 +Epoch [3109/4000] Training [11/16] Loss: 0.00303 +Epoch [3109/4000] Training [12/16] Loss: 0.00364 +Epoch [3109/4000] Training [13/16] Loss: 0.00241 +Epoch [3109/4000] Training [14/16] Loss: 0.00266 +Epoch [3109/4000] Training [15/16] Loss: 0.00266 +Epoch [3109/4000] Training [16/16] Loss: 0.00359 +Epoch [3109/4000] Training metric {'Train/mean dice_metric': 0.9982702732086182, 'Train/mean miou_metric': 0.9962565898895264, 'Train/mean f1': 0.9932098388671875, 'Train/mean precision': 0.9884878993034363, 'Train/mean recall': 0.9979771375656128, 'Train/mean hd95_metric': 0.7823673486709595} +Epoch [3109/4000] Validation [1/4] Loss: 0.40724 focal_loss 0.34396 dice_loss 0.06328 +Epoch [3109/4000] Validation [2/4] Loss: 0.34340 focal_loss 0.24789 dice_loss 0.09551 +Epoch [3109/4000] Validation [3/4] Loss: 0.55118 focal_loss 0.45264 dice_loss 0.09855 +Epoch [3109/4000] Validation [4/4] Loss: 0.33694 focal_loss 0.23883 dice_loss 0.09811 +Epoch [3109/4000] Validation metric {'Val/mean dice_metric': 0.9748836755752563, 'Val/mean miou_metric': 0.9603412747383118, 'Val/mean f1': 0.976717472076416, 'Val/mean precision': 0.9723117351531982, 'Val/mean recall': 0.9811632037162781, 'Val/mean hd95_metric': 5.197188854217529} +Cheakpoint... +Epoch [3109/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748836755752563, 'Val/mean miou_metric': 0.9603412747383118, 'Val/mean f1': 0.976717472076416, 'Val/mean precision': 0.9723117351531982, 'Val/mean recall': 0.9811632037162781, 'Val/mean hd95_metric': 5.197188854217529} +Epoch [3110/4000] Training [1/16] Loss: 0.00330 +Epoch [3110/4000] Training [2/16] Loss: 0.00308 +Epoch [3110/4000] Training [3/16] Loss: 0.00238 +Epoch [3110/4000] Training [4/16] Loss: 0.00355 +Epoch [3110/4000] Training [5/16] Loss: 0.00191 +Epoch [3110/4000] Training [6/16] Loss: 0.00242 +Epoch [3110/4000] Training [7/16] Loss: 0.00267 +Epoch [3110/4000] Training [8/16] Loss: 0.00247 +Epoch [3110/4000] Training [9/16] Loss: 0.00272 +Epoch [3110/4000] Training [10/16] Loss: 0.00447 +Epoch [3110/4000] Training [11/16] Loss: 0.00282 +Epoch [3110/4000] Training [12/16] Loss: 0.00326 +Epoch [3110/4000] Training [13/16] Loss: 0.00388 +Epoch [3110/4000] Training [14/16] Loss: 0.00237 +Epoch [3110/4000] Training [15/16] Loss: 0.00326 +Epoch [3110/4000] Training [16/16] Loss: 0.00222 +Epoch [3110/4000] Training metric {'Train/mean dice_metric': 0.998367965221405, 'Train/mean miou_metric': 0.9964659214019775, 'Train/mean f1': 0.9934954047203064, 'Train/mean precision': 0.9889629483222961, 'Train/mean recall': 0.9980695247650146, 'Train/mean hd95_metric': 0.6998680830001831} +Epoch [3110/4000] Validation [1/4] Loss: 0.41142 focal_loss 0.34647 dice_loss 0.06495 +Epoch [3110/4000] Validation [2/4] Loss: 0.47128 focal_loss 0.34269 dice_loss 0.12859 +Epoch [3110/4000] Validation [3/4] Loss: 0.52589 focal_loss 0.42724 dice_loss 0.09865 +Epoch [3110/4000] Validation [4/4] Loss: 0.29253 focal_loss 0.20313 dice_loss 0.08939 +Epoch [3110/4000] Validation metric {'Val/mean dice_metric': 0.9737939834594727, 'Val/mean miou_metric': 0.959642767906189, 'Val/mean f1': 0.9757391810417175, 'Val/mean precision': 0.9708673357963562, 'Val/mean recall': 0.9806602597236633, 'Val/mean hd95_metric': 5.201137542724609} +Cheakpoint... +Epoch [3110/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737939834594727, 'Val/mean miou_metric': 0.959642767906189, 'Val/mean f1': 0.9757391810417175, 'Val/mean precision': 0.9708673357963562, 'Val/mean recall': 0.9806602597236633, 'Val/mean hd95_metric': 5.201137542724609} +Epoch [3111/4000] Training [1/16] Loss: 0.00243 +Epoch [3111/4000] Training [2/16] Loss: 0.00195 +Epoch [3111/4000] Training [3/16] Loss: 0.00270 +Epoch [3111/4000] Training [4/16] Loss: 0.00497 +Epoch [3111/4000] Training [5/16] Loss: 0.00329 +Epoch [3111/4000] Training [6/16] Loss: 0.00435 +Epoch [3111/4000] Training [7/16] Loss: 0.00359 +Epoch [3111/4000] Training [8/16] Loss: 0.00278 +Epoch [3111/4000] Training [9/16] Loss: 0.00343 +Epoch [3111/4000] Training [10/16] Loss: 0.00309 +Epoch [3111/4000] Training [11/16] Loss: 0.00237 +Epoch [3111/4000] Training [12/16] Loss: 0.00288 +Epoch [3111/4000] Training [13/16] Loss: 0.00362 +Epoch [3111/4000] Training [14/16] Loss: 0.00297 +Epoch [3111/4000] Training [15/16] Loss: 0.00362 +Epoch [3111/4000] Training [16/16] Loss: 0.00228 +Epoch [3111/4000] Training metric {'Train/mean dice_metric': 0.998244047164917, 'Train/mean miou_metric': 0.9962131381034851, 'Train/mean f1': 0.9932655692100525, 'Train/mean precision': 0.9886273145675659, 'Train/mean recall': 0.9979475140571594, 'Train/mean hd95_metric': 0.7197542190551758} +Epoch [3111/4000] Validation [1/4] Loss: 0.38457 focal_loss 0.32209 dice_loss 0.06247 +Epoch [3111/4000] Validation [2/4] Loss: 0.33849 focal_loss 0.24657 dice_loss 0.09192 +Epoch [3111/4000] Validation [3/4] Loss: 0.51717 focal_loss 0.42249 dice_loss 0.09468 +Epoch [3111/4000] Validation [4/4] Loss: 0.35041 focal_loss 0.24801 dice_loss 0.10240 +Epoch [3111/4000] Validation metric {'Val/mean dice_metric': 0.9739450216293335, 'Val/mean miou_metric': 0.959423840045929, 'Val/mean f1': 0.9756237864494324, 'Val/mean precision': 0.9715134501457214, 'Val/mean recall': 0.9797689914703369, 'Val/mean hd95_metric': 5.201977252960205} +Cheakpoint... +Epoch [3111/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739450216293335, 'Val/mean miou_metric': 0.959423840045929, 'Val/mean f1': 0.9756237864494324, 'Val/mean precision': 0.9715134501457214, 'Val/mean recall': 0.9797689914703369, 'Val/mean hd95_metric': 5.201977252960205} +Epoch [3112/4000] Training [1/16] Loss: 0.00294 +Epoch [3112/4000] Training [2/16] Loss: 0.00338 +Epoch [3112/4000] Training [3/16] Loss: 0.00274 +Epoch [3112/4000] Training [4/16] Loss: 0.00289 +Epoch [3112/4000] Training [5/16] Loss: 0.00252 +Epoch [3112/4000] Training [6/16] Loss: 0.00245 +Epoch [3112/4000] Training [7/16] Loss: 0.00275 +Epoch [3112/4000] Training [8/16] Loss: 0.00305 +Epoch [3112/4000] Training [9/16] Loss: 0.00430 +Epoch [3112/4000] Training [10/16] Loss: 0.00259 +Epoch [3112/4000] Training [11/16] Loss: 0.00271 +Epoch [3112/4000] Training [12/16] Loss: 0.00254 +Epoch [3112/4000] Training [13/16] Loss: 0.00351 +Epoch [3112/4000] Training [14/16] Loss: 0.01309 +Epoch [3112/4000] Training [15/16] Loss: 0.00340 +Epoch [3112/4000] Training [16/16] Loss: 0.00272 +Epoch [3112/4000] Training metric {'Train/mean dice_metric': 0.9983000755310059, 'Train/mean miou_metric': 0.9963284730911255, 'Train/mean f1': 0.9932422637939453, 'Train/mean precision': 0.9885523915290833, 'Train/mean recall': 0.9979768395423889, 'Train/mean hd95_metric': 0.8149852752685547} +Epoch [3112/4000] Validation [1/4] Loss: 0.40502 focal_loss 0.34048 dice_loss 0.06454 +Epoch [3112/4000] Validation [2/4] Loss: 0.37830 focal_loss 0.27257 dice_loss 0.10573 +Epoch [3112/4000] Validation [3/4] Loss: 0.55569 focal_loss 0.45667 dice_loss 0.09901 +Epoch [3112/4000] Validation [4/4] Loss: 0.31533 focal_loss 0.22839 dice_loss 0.08694 +Epoch [3112/4000] Validation metric {'Val/mean dice_metric': 0.9749168157577515, 'Val/mean miou_metric': 0.9605892300605774, 'Val/mean f1': 0.9763287305831909, 'Val/mean precision': 0.9727874994277954, 'Val/mean recall': 0.9798957705497742, 'Val/mean hd95_metric': 4.969442844390869} +Cheakpoint... +Epoch [3112/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749168157577515, 'Val/mean miou_metric': 0.9605892300605774, 'Val/mean f1': 0.9763287305831909, 'Val/mean precision': 0.9727874994277954, 'Val/mean recall': 0.9798957705497742, 'Val/mean hd95_metric': 4.969442844390869} +Epoch [3113/4000] Training [1/16] Loss: 0.00308 +Epoch [3113/4000] Training [2/16] Loss: 0.00441 +Epoch [3113/4000] Training [3/16] Loss: 0.00303 +Epoch [3113/4000] Training [4/16] Loss: 0.00268 +Epoch [3113/4000] Training [5/16] Loss: 0.00340 +Epoch [3113/4000] Training [6/16] Loss: 0.00329 +Epoch [3113/4000] Training [7/16] Loss: 0.00294 +Epoch [3113/4000] Training [8/16] Loss: 0.00233 +Epoch [3113/4000] Training [9/16] Loss: 0.00414 +Epoch [3113/4000] Training [10/16] Loss: 0.00292 +Epoch [3113/4000] Training [11/16] Loss: 0.00330 +Epoch [3113/4000] Training [12/16] Loss: 0.00276 +Epoch [3113/4000] Training [13/16] Loss: 0.00358 +Epoch [3113/4000] Training [14/16] Loss: 0.00311 +Epoch [3113/4000] Training [15/16] Loss: 0.00389 +Epoch [3113/4000] Training [16/16] Loss: 0.00285 +Epoch [3113/4000] Training metric {'Train/mean dice_metric': 0.9982480406761169, 'Train/mean miou_metric': 0.996185839176178, 'Train/mean f1': 0.9925774931907654, 'Train/mean precision': 0.9872921705245972, 'Train/mean recall': 0.9979196786880493, 'Train/mean hd95_metric': 0.7539337873458862} +Epoch [3113/4000] Validation [1/4] Loss: 0.38855 focal_loss 0.32267 dice_loss 0.06588 +Epoch [3113/4000] Validation [2/4] Loss: 0.38347 focal_loss 0.28184 dice_loss 0.10164 +Epoch [3113/4000] Validation [3/4] Loss: 0.50858 focal_loss 0.41409 dice_loss 0.09449 +Epoch [3113/4000] Validation [4/4] Loss: 0.35478 focal_loss 0.24202 dice_loss 0.11276 +Epoch [3113/4000] Validation metric {'Val/mean dice_metric': 0.9741409420967102, 'Val/mean miou_metric': 0.9594713449478149, 'Val/mean f1': 0.9752069115638733, 'Val/mean precision': 0.9721381664276123, 'Val/mean recall': 0.978295087814331, 'Val/mean hd95_metric': 4.894297122955322} +Cheakpoint... +Epoch [3113/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741409420967102, 'Val/mean miou_metric': 0.9594713449478149, 'Val/mean f1': 0.9752069115638733, 'Val/mean precision': 0.9721381664276123, 'Val/mean recall': 0.978295087814331, 'Val/mean hd95_metric': 4.894297122955322} +Epoch [3114/4000] Training [1/16] Loss: 0.00277 +Epoch [3114/4000] Training [2/16] Loss: 0.00290 +Epoch [3114/4000] Training [3/16] Loss: 0.00270 +Epoch [3114/4000] Training [4/16] Loss: 0.00365 +Epoch [3114/4000] Training [5/16] Loss: 0.00339 +Epoch [3114/4000] Training [6/16] Loss: 0.00422 +Epoch [3114/4000] Training [7/16] Loss: 0.00306 +Epoch [3114/4000] Training [8/16] Loss: 0.00335 +Epoch [3114/4000] Training [9/16] Loss: 0.00212 +Epoch [3114/4000] Training [10/16] Loss: 0.00286 +Epoch [3114/4000] Training [11/16] Loss: 0.00176 +Epoch [3114/4000] Training [12/16] Loss: 0.00239 +Epoch [3114/4000] Training [13/16] Loss: 0.00245 +Epoch [3114/4000] Training [14/16] Loss: 0.00370 +Epoch [3114/4000] Training [15/16] Loss: 0.00410 +Epoch [3114/4000] Training [16/16] Loss: 0.00211 +Epoch [3114/4000] Training metric {'Train/mean dice_metric': 0.9983693361282349, 'Train/mean miou_metric': 0.9964536428451538, 'Train/mean f1': 0.993303120136261, 'Train/mean precision': 0.9886589646339417, 'Train/mean recall': 0.9979910850524902, 'Train/mean hd95_metric': 0.7075823545455933} +Epoch [3114/4000] Validation [1/4] Loss: 0.36926 focal_loss 0.30593 dice_loss 0.06333 +Epoch [3114/4000] Validation [2/4] Loss: 0.41899 focal_loss 0.31334 dice_loss 0.10566 +Epoch [3114/4000] Validation [3/4] Loss: 0.47812 focal_loss 0.38419 dice_loss 0.09393 +Epoch [3114/4000] Validation [4/4] Loss: 0.40544 focal_loss 0.29950 dice_loss 0.10593 +Epoch [3114/4000] Validation metric {'Val/mean dice_metric': 0.973122239112854, 'Val/mean miou_metric': 0.9588860273361206, 'Val/mean f1': 0.9759756326675415, 'Val/mean precision': 0.9745243787765503, 'Val/mean recall': 0.977431058883667, 'Val/mean hd95_metric': 4.498671054840088} +Cheakpoint... +Epoch [3114/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973122239112854, 'Val/mean miou_metric': 0.9588860273361206, 'Val/mean f1': 0.9759756326675415, 'Val/mean precision': 0.9745243787765503, 'Val/mean recall': 0.977431058883667, 'Val/mean hd95_metric': 4.498671054840088} +Epoch [3115/4000] Training [1/16] Loss: 0.00311 +Epoch [3115/4000] Training [2/16] Loss: 0.00294 +Epoch [3115/4000] Training [3/16] Loss: 0.00251 +Epoch [3115/4000] Training [4/16] Loss: 0.00258 +Epoch [3115/4000] Training [5/16] Loss: 0.00244 +Epoch [3115/4000] Training [6/16] Loss: 0.00217 +Epoch [3115/4000] Training [7/16] Loss: 0.00468 +Epoch [3115/4000] Training [8/16] Loss: 0.00344 +Epoch [3115/4000] Training [9/16] Loss: 0.00261 +Epoch [3115/4000] Training [10/16] Loss: 0.00218 +Epoch [3115/4000] Training [11/16] Loss: 0.00414 +Epoch [3115/4000] Training [12/16] Loss: 0.00244 +Epoch [3115/4000] Training [13/16] Loss: 0.00249 +Epoch [3115/4000] Training [14/16] Loss: 0.00541 +Epoch [3115/4000] Training [15/16] Loss: 0.00419 +Epoch [3115/4000] Training [16/16] Loss: 0.00393 +Epoch [3115/4000] Training metric {'Train/mean dice_metric': 0.9982135891914368, 'Train/mean miou_metric': 0.996104896068573, 'Train/mean f1': 0.9923361539840698, 'Train/mean precision': 0.9868578910827637, 'Train/mean recall': 0.9978755712509155, 'Train/mean hd95_metric': 0.724441647529602} +Epoch [3115/4000] Validation [1/4] Loss: 0.40300 focal_loss 0.33721 dice_loss 0.06579 +Epoch [3115/4000] Validation [2/4] Loss: 0.42255 focal_loss 0.31363 dice_loss 0.10892 +Epoch [3115/4000] Validation [3/4] Loss: 0.55037 focal_loss 0.45221 dice_loss 0.09817 +Epoch [3115/4000] Validation [4/4] Loss: 0.50992 focal_loss 0.38232 dice_loss 0.12760 +Epoch [3115/4000] Validation metric {'Val/mean dice_metric': 0.9740501642227173, 'Val/mean miou_metric': 0.9591468572616577, 'Val/mean f1': 0.974837601184845, 'Val/mean precision': 0.972514808177948, 'Val/mean recall': 0.9771715998649597, 'Val/mean hd95_metric': 4.694336414337158} +Cheakpoint... +Epoch [3115/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740501642227173, 'Val/mean miou_metric': 0.9591468572616577, 'Val/mean f1': 0.974837601184845, 'Val/mean precision': 0.972514808177948, 'Val/mean recall': 0.9771715998649597, 'Val/mean hd95_metric': 4.694336414337158} +Epoch [3116/4000] Training [1/16] Loss: 0.00318 +Epoch [3116/4000] Training [2/16] Loss: 0.00277 +Epoch [3116/4000] Training [3/16] Loss: 0.00278 +Epoch [3116/4000] Training [4/16] Loss: 0.00263 +Epoch [3116/4000] Training [5/16] Loss: 0.00314 +Epoch [3116/4000] Training [6/16] Loss: 0.00311 +Epoch [3116/4000] Training [7/16] Loss: 0.00308 +Epoch [3116/4000] Training [8/16] Loss: 0.00345 +Epoch [3116/4000] Training [9/16] Loss: 0.00328 +Epoch [3116/4000] Training [10/16] Loss: 0.00209 +Epoch [3116/4000] Training [11/16] Loss: 0.00312 +Epoch [3116/4000] Training [12/16] Loss: 0.00285 +Epoch [3116/4000] Training [13/16] Loss: 0.00326 +Epoch [3116/4000] Training [14/16] Loss: 0.00288 +Epoch [3116/4000] Training [15/16] Loss: 0.00294 +Epoch [3116/4000] Training [16/16] Loss: 0.00290 +Epoch [3116/4000] Training metric {'Train/mean dice_metric': 0.9983696937561035, 'Train/mean miou_metric': 0.9964709281921387, 'Train/mean f1': 0.9934129118919373, 'Train/mean precision': 0.9888886213302612, 'Train/mean recall': 0.9979788064956665, 'Train/mean hd95_metric': 0.6943172812461853} +Epoch [3116/4000] Validation [1/4] Loss: 0.35133 focal_loss 0.29057 dice_loss 0.06076 +Epoch [3116/4000] Validation [2/4] Loss: 1.03716 focal_loss 0.77059 dice_loss 0.26657 +Epoch [3116/4000] Validation [3/4] Loss: 0.52037 focal_loss 0.42001 dice_loss 0.10036 +Epoch [3116/4000] Validation [4/4] Loss: 0.34361 focal_loss 0.23494 dice_loss 0.10867 +Epoch [3116/4000] Validation metric {'Val/mean dice_metric': 0.9723488092422485, 'Val/mean miou_metric': 0.9579618573188782, 'Val/mean f1': 0.97529536485672, 'Val/mean precision': 0.9725921154022217, 'Val/mean recall': 0.9780136346817017, 'Val/mean hd95_metric': 5.072024345397949} +Cheakpoint... +Epoch [3116/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723488092422485, 'Val/mean miou_metric': 0.9579618573188782, 'Val/mean f1': 0.97529536485672, 'Val/mean precision': 0.9725921154022217, 'Val/mean recall': 0.9780136346817017, 'Val/mean hd95_metric': 5.072024345397949} +Epoch [3117/4000] Training [1/16] Loss: 0.00466 +Epoch [3117/4000] Training [2/16] Loss: 0.00159 +Epoch [3117/4000] Training [3/16] Loss: 0.00293 +Epoch [3117/4000] Training [4/16] Loss: 0.00252 +Epoch [3117/4000] Training [5/16] Loss: 0.00258 +Epoch [3117/4000] Training [6/16] Loss: 0.00342 +Epoch [3117/4000] Training [7/16] Loss: 0.00330 +Epoch [3117/4000] Training [8/16] Loss: 0.00423 +Epoch [3117/4000] Training [9/16] Loss: 0.00329 +Epoch [3117/4000] Training [10/16] Loss: 0.00190 +Epoch [3117/4000] Training [11/16] Loss: 0.00268 +Epoch [3117/4000] Training [12/16] Loss: 0.00277 +Epoch [3117/4000] Training [13/16] Loss: 0.00337 +Epoch [3117/4000] Training [14/16] Loss: 0.00308 +Epoch [3117/4000] Training [15/16] Loss: 0.00276 +Epoch [3117/4000] Training [16/16] Loss: 0.00433 +Epoch [3117/4000] Training metric {'Train/mean dice_metric': 0.9983524680137634, 'Train/mean miou_metric': 0.9964353442192078, 'Train/mean f1': 0.9934175610542297, 'Train/mean precision': 0.9888625741004944, 'Train/mean recall': 0.9980146288871765, 'Train/mean hd95_metric': 0.712722897529602} +Epoch [3117/4000] Validation [1/4] Loss: 0.38848 focal_loss 0.32467 dice_loss 0.06381 +Epoch [3117/4000] Validation [2/4] Loss: 0.41405 focal_loss 0.30614 dice_loss 0.10791 +Epoch [3117/4000] Validation [3/4] Loss: 0.53935 focal_loss 0.44327 dice_loss 0.09608 +Epoch [3117/4000] Validation [4/4] Loss: 0.33630 focal_loss 0.24527 dice_loss 0.09102 +Epoch [3117/4000] Validation metric {'Val/mean dice_metric': 0.9732829928398132, 'Val/mean miou_metric': 0.9590455889701843, 'Val/mean f1': 0.9757771492004395, 'Val/mean precision': 0.9734399914741516, 'Val/mean recall': 0.9781255125999451, 'Val/mean hd95_metric': 5.519012451171875} +Cheakpoint... +Epoch [3117/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732829928398132, 'Val/mean miou_metric': 0.9590455889701843, 'Val/mean f1': 0.9757771492004395, 'Val/mean precision': 0.9734399914741516, 'Val/mean recall': 0.9781255125999451, 'Val/mean hd95_metric': 5.519012451171875} +Epoch [3118/4000] Training [1/16] Loss: 0.00322 +Epoch [3118/4000] Training [2/16] Loss: 0.00323 +Epoch [3118/4000] Training [3/16] Loss: 0.00228 +Epoch [3118/4000] Training [4/16] Loss: 0.00210 +Epoch [3118/4000] Training [5/16] Loss: 0.00301 +Epoch [3118/4000] Training [6/16] Loss: 0.00327 +Epoch [3118/4000] Training [7/16] Loss: 0.00305 +Epoch [3118/4000] Training [8/16] Loss: 0.00249 +Epoch [3118/4000] Training [9/16] Loss: 0.00272 +Epoch [3118/4000] Training [10/16] Loss: 0.00293 +Epoch [3118/4000] Training [11/16] Loss: 0.00323 +Epoch [3118/4000] Training [12/16] Loss: 0.00478 +Epoch [3118/4000] Training [13/16] Loss: 0.00359 +Epoch [3118/4000] Training [14/16] Loss: 0.00400 +Epoch [3118/4000] Training [15/16] Loss: 0.00309 +Epoch [3118/4000] Training [16/16] Loss: 0.00245 +Epoch [3118/4000] Training metric {'Train/mean dice_metric': 0.9983352422714233, 'Train/mean miou_metric': 0.9963756799697876, 'Train/mean f1': 0.9929624199867249, 'Train/mean precision': 0.9879484176635742, 'Train/mean recall': 0.9980275630950928, 'Train/mean hd95_metric': 0.6896759867668152} +Epoch [3118/4000] Validation [1/4] Loss: 0.42725 focal_loss 0.35969 dice_loss 0.06757 +Epoch [3118/4000] Validation [2/4] Loss: 0.47236 focal_loss 0.35511 dice_loss 0.11725 +Epoch [3118/4000] Validation [3/4] Loss: 0.50446 focal_loss 0.41413 dice_loss 0.09033 +Epoch [3118/4000] Validation [4/4] Loss: 0.33336 focal_loss 0.24788 dice_loss 0.08548 +Epoch [3118/4000] Validation metric {'Val/mean dice_metric': 0.9745994806289673, 'Val/mean miou_metric': 0.959992527961731, 'Val/mean f1': 0.975853681564331, 'Val/mean precision': 0.9733695983886719, 'Val/mean recall': 0.9783504009246826, 'Val/mean hd95_metric': 4.773386001586914} +Cheakpoint... +Epoch [3118/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745994806289673, 'Val/mean miou_metric': 0.959992527961731, 'Val/mean f1': 0.975853681564331, 'Val/mean precision': 0.9733695983886719, 'Val/mean recall': 0.9783504009246826, 'Val/mean hd95_metric': 4.773386001586914} +Epoch [3119/4000] Training [1/16] Loss: 0.00306 +Epoch [3119/4000] Training [2/16] Loss: 0.00212 +Epoch [3119/4000] Training [3/16] Loss: 0.00322 +Epoch [3119/4000] Training [4/16] Loss: 0.00265 +Epoch [3119/4000] Training [5/16] Loss: 0.00303 +Epoch [3119/4000] Training [6/16] Loss: 0.00313 +Epoch [3119/4000] Training [7/16] Loss: 0.00346 +Epoch [3119/4000] Training [8/16] Loss: 0.00269 +Epoch [3119/4000] Training [9/16] Loss: 0.00186 +Epoch [3119/4000] Training [10/16] Loss: 0.00326 +Epoch [3119/4000] Training [11/16] Loss: 0.00262 +Epoch [3119/4000] Training [12/16] Loss: 0.00335 +Epoch [3119/4000] Training [13/16] Loss: 0.00327 +Epoch [3119/4000] Training [14/16] Loss: 0.00277 +Epoch [3119/4000] Training [15/16] Loss: 0.00364 +Epoch [3119/4000] Training [16/16] Loss: 0.00280 +Epoch [3119/4000] Training metric {'Train/mean dice_metric': 0.9981707334518433, 'Train/mean miou_metric': 0.9960684776306152, 'Train/mean f1': 0.9933384656906128, 'Train/mean precision': 0.9887449145317078, 'Train/mean recall': 0.9979748129844666, 'Train/mean hd95_metric': 0.7196565270423889} +Epoch [3119/4000] Validation [1/4] Loss: 0.37652 focal_loss 0.31084 dice_loss 0.06568 +Epoch [3119/4000] Validation [2/4] Loss: 0.41647 focal_loss 0.30859 dice_loss 0.10788 +Epoch [3119/4000] Validation [3/4] Loss: 0.49214 focal_loss 0.39813 dice_loss 0.09401 +Epoch [3119/4000] Validation [4/4] Loss: 0.44819 focal_loss 0.33216 dice_loss 0.11603 +Epoch [3119/4000] Validation metric {'Val/mean dice_metric': 0.9748414754867554, 'Val/mean miou_metric': 0.9597815275192261, 'Val/mean f1': 0.9755260348320007, 'Val/mean precision': 0.973867654800415, 'Val/mean recall': 0.9771900773048401, 'Val/mean hd95_metric': 4.8069844245910645} +Cheakpoint... +Epoch [3119/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748414754867554, 'Val/mean miou_metric': 0.9597815275192261, 'Val/mean f1': 0.9755260348320007, 'Val/mean precision': 0.973867654800415, 'Val/mean recall': 0.9771900773048401, 'Val/mean hd95_metric': 4.8069844245910645} +Epoch [3120/4000] Training [1/16] Loss: 0.00252 +Epoch [3120/4000] Training [2/16] Loss: 0.00286 +Epoch [3120/4000] Training [3/16] Loss: 0.00227 +Epoch [3120/4000] Training [4/16] Loss: 0.00239 +Epoch [3120/4000] Training [5/16] Loss: 0.00275 +Epoch [3120/4000] Training [6/16] Loss: 0.00288 +Epoch [3120/4000] Training [7/16] Loss: 0.00258 +Epoch [3120/4000] Training [8/16] Loss: 0.00333 +Epoch [3120/4000] Training [9/16] Loss: 0.00396 +Epoch [3120/4000] Training [10/16] Loss: 0.00262 +Epoch [3120/4000] Training [11/16] Loss: 0.00306 +Epoch [3120/4000] Training [12/16] Loss: 0.00381 +Epoch [3120/4000] Training [13/16] Loss: 0.00265 +Epoch [3120/4000] Training [14/16] Loss: 0.00285 +Epoch [3120/4000] Training [15/16] Loss: 0.00194 +Epoch [3120/4000] Training [16/16] Loss: 0.00279 +Epoch [3120/4000] Training metric {'Train/mean dice_metric': 0.9984992146492004, 'Train/mean miou_metric': 0.9967254996299744, 'Train/mean f1': 0.9935696125030518, 'Train/mean precision': 0.9890658855438232, 'Train/mean recall': 0.9981144666671753, 'Train/mean hd95_metric': 0.7039337158203125} +Epoch [3120/4000] Validation [1/4] Loss: 0.46952 focal_loss 0.38925 dice_loss 0.08027 +Epoch [3120/4000] Validation [2/4] Loss: 0.60115 focal_loss 0.44139 dice_loss 0.15976 +Epoch [3120/4000] Validation [3/4] Loss: 0.27808 focal_loss 0.20771 dice_loss 0.07037 +Epoch [3120/4000] Validation [4/4] Loss: 0.31434 focal_loss 0.23126 dice_loss 0.08308 +Epoch [3120/4000] Validation metric {'Val/mean dice_metric': 0.9742075204849243, 'Val/mean miou_metric': 0.9599688649177551, 'Val/mean f1': 0.9760916233062744, 'Val/mean precision': 0.9739589691162109, 'Val/mean recall': 0.9782335162162781, 'Val/mean hd95_metric': 5.002476215362549} +Cheakpoint... +Epoch [3120/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742075204849243, 'Val/mean miou_metric': 0.9599688649177551, 'Val/mean f1': 0.9760916233062744, 'Val/mean precision': 0.9739589691162109, 'Val/mean recall': 0.9782335162162781, 'Val/mean hd95_metric': 5.002476215362549} +Epoch [3121/4000] Training [1/16] Loss: 0.00343 +Epoch [3121/4000] Training [2/16] Loss: 0.00478 +Epoch [3121/4000] Training [3/16] Loss: 0.00205 +Epoch [3121/4000] Training [4/16] Loss: 0.00304 +Epoch [3121/4000] Training [5/16] Loss: 0.00259 +Epoch [3121/4000] Training [6/16] Loss: 0.00221 +Epoch [3121/4000] Training [7/16] Loss: 0.00314 +Epoch [3121/4000] Training [8/16] Loss: 0.00216 +Epoch [3121/4000] Training [9/16] Loss: 0.00311 +Epoch [3121/4000] Training [10/16] Loss: 0.00291 +Epoch [3121/4000] Training [11/16] Loss: 0.00374 +Epoch [3121/4000] Training [12/16] Loss: 0.00220 +Epoch [3121/4000] Training [13/16] Loss: 0.00280 +Epoch [3121/4000] Training [14/16] Loss: 0.00282 +Epoch [3121/4000] Training [15/16] Loss: 0.00546 +Epoch [3121/4000] Training [16/16] Loss: 0.00254 +Epoch [3121/4000] Training metric {'Train/mean dice_metric': 0.9982024431228638, 'Train/mean miou_metric': 0.9961042404174805, 'Train/mean f1': 0.9924734830856323, 'Train/mean precision': 0.9871088266372681, 'Train/mean recall': 0.9978968501091003, 'Train/mean hd95_metric': 0.7547008395195007} +Epoch [3121/4000] Validation [1/4] Loss: 0.39327 focal_loss 0.32799 dice_loss 0.06528 +Epoch [3121/4000] Validation [2/4] Loss: 0.37417 focal_loss 0.27204 dice_loss 0.10213 +Epoch [3121/4000] Validation [3/4] Loss: 0.57394 focal_loss 0.47411 dice_loss 0.09983 +Epoch [3121/4000] Validation [4/4] Loss: 0.52604 focal_loss 0.39557 dice_loss 0.13047 +Epoch [3121/4000] Validation metric {'Val/mean dice_metric': 0.9735005497932434, 'Val/mean miou_metric': 0.958389401435852, 'Val/mean f1': 0.9748530983924866, 'Val/mean precision': 0.9724653363227844, 'Val/mean recall': 0.9772524833679199, 'Val/mean hd95_metric': 4.943970680236816} +Cheakpoint... +Epoch [3121/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735005497932434, 'Val/mean miou_metric': 0.958389401435852, 'Val/mean f1': 0.9748530983924866, 'Val/mean precision': 0.9724653363227844, 'Val/mean recall': 0.9772524833679199, 'Val/mean hd95_metric': 4.943970680236816} +Epoch [3122/4000] Training [1/16] Loss: 0.00255 +Epoch [3122/4000] Training [2/16] Loss: 0.00251 +Epoch [3122/4000] Training [3/16] Loss: 0.00240 +Epoch [3122/4000] Training [4/16] Loss: 0.00228 +Epoch [3122/4000] Training [5/16] Loss: 0.00245 +Epoch [3122/4000] Training [6/16] Loss: 0.00277 +Epoch [3122/4000] Training [7/16] Loss: 0.00234 +Epoch [3122/4000] Training [8/16] Loss: 0.00286 +Epoch [3122/4000] Training [9/16] Loss: 0.00436 +Epoch [3122/4000] Training [10/16] Loss: 0.00199 +Epoch [3122/4000] Training [11/16] Loss: 0.00319 +Epoch [3122/4000] Training [12/16] Loss: 0.00322 +Epoch [3122/4000] Training [13/16] Loss: 0.00283 +Epoch [3122/4000] Training [14/16] Loss: 0.00261 +Epoch [3122/4000] Training [15/16] Loss: 0.00371 +Epoch [3122/4000] Training [16/16] Loss: 0.00246 +Epoch [3122/4000] Training metric {'Train/mean dice_metric': 0.9984993934631348, 'Train/mean miou_metric': 0.9967232346534729, 'Train/mean f1': 0.9935606122016907, 'Train/mean precision': 0.9889772534370422, 'Train/mean recall': 0.9981865882873535, 'Train/mean hd95_metric': 0.6699771881103516} +Epoch [3122/4000] Validation [1/4] Loss: 0.33851 focal_loss 0.27781 dice_loss 0.06071 +Epoch [3122/4000] Validation [2/4] Loss: 0.38911 focal_loss 0.28700 dice_loss 0.10210 +Epoch [3122/4000] Validation [3/4] Loss: 0.53331 focal_loss 0.43611 dice_loss 0.09720 +Epoch [3122/4000] Validation [4/4] Loss: 0.34648 focal_loss 0.24094 dice_loss 0.10553 +Epoch [3122/4000] Validation metric {'Val/mean dice_metric': 0.9751685857772827, 'Val/mean miou_metric': 0.9610656499862671, 'Val/mean f1': 0.976885974407196, 'Val/mean precision': 0.9733676314353943, 'Val/mean recall': 0.980430006980896, 'Val/mean hd95_metric': 4.843987464904785} +Cheakpoint... +Epoch [3122/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751685857772827, 'Val/mean miou_metric': 0.9610656499862671, 'Val/mean f1': 0.976885974407196, 'Val/mean precision': 0.9733676314353943, 'Val/mean recall': 0.980430006980896, 'Val/mean hd95_metric': 4.843987464904785} +Epoch [3123/4000] Training [1/16] Loss: 0.00386 +Epoch [3123/4000] Training [2/16] Loss: 0.00338 +Epoch [3123/4000] Training [3/16] Loss: 0.00287 +Epoch [3123/4000] Training [4/16] Loss: 0.00234 +Epoch [3123/4000] Training [5/16] Loss: 0.00363 +Epoch [3123/4000] Training [6/16] Loss: 0.00214 +Epoch [3123/4000] Training [7/16] Loss: 0.00285 +Epoch [3123/4000] Training [8/16] Loss: 0.00347 +Epoch [3123/4000] Training [9/16] Loss: 0.00301 +Epoch [3123/4000] Training [10/16] Loss: 0.00225 +Epoch [3123/4000] Training [11/16] Loss: 0.00409 +Epoch [3123/4000] Training [12/16] Loss: 0.00234 +Epoch [3123/4000] Training [13/16] Loss: 0.00258 +Epoch [3123/4000] Training [14/16] Loss: 0.00250 +Epoch [3123/4000] Training [15/16] Loss: 0.00309 +Epoch [3123/4000] Training [16/16] Loss: 0.00304 +Epoch [3123/4000] Training metric {'Train/mean dice_metric': 0.9983141422271729, 'Train/mean miou_metric': 0.9963487982749939, 'Train/mean f1': 0.9932976961135864, 'Train/mean precision': 0.98868727684021, 'Train/mean recall': 0.9979512691497803, 'Train/mean hd95_metric': 0.7344303131103516} +Epoch [3123/4000] Validation [1/4] Loss: 0.36866 focal_loss 0.30522 dice_loss 0.06344 +Epoch [3123/4000] Validation [2/4] Loss: 0.40654 focal_loss 0.30197 dice_loss 0.10456 +Epoch [3123/4000] Validation [3/4] Loss: 0.52205 focal_loss 0.42867 dice_loss 0.09338 +Epoch [3123/4000] Validation [4/4] Loss: 0.31086 focal_loss 0.22384 dice_loss 0.08702 +Epoch [3123/4000] Validation metric {'Val/mean dice_metric': 0.9751224517822266, 'Val/mean miou_metric': 0.9608603715896606, 'Val/mean f1': 0.9765397310256958, 'Val/mean precision': 0.9733026623725891, 'Val/mean recall': 0.9797982573509216, 'Val/mean hd95_metric': 4.837536811828613} +Cheakpoint... +Epoch [3123/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751224517822266, 'Val/mean miou_metric': 0.9608603715896606, 'Val/mean f1': 0.9765397310256958, 'Val/mean precision': 0.9733026623725891, 'Val/mean recall': 0.9797982573509216, 'Val/mean hd95_metric': 4.837536811828613} +Epoch [3124/4000] Training [1/16] Loss: 0.00373 +Epoch [3124/4000] Training [2/16] Loss: 0.00270 +Epoch [3124/4000] Training [3/16] Loss: 0.00277 +Epoch [3124/4000] Training [4/16] Loss: 0.00277 +Epoch [3124/4000] Training [5/16] Loss: 0.00320 +Epoch [3124/4000] Training [6/16] Loss: 0.00291 +Epoch [3124/4000] Training [7/16] Loss: 0.00438 +Epoch [3124/4000] Training [8/16] Loss: 0.00218 +Epoch [3124/4000] Training [9/16] Loss: 0.00238 +Epoch [3124/4000] Training [10/16] Loss: 0.00209 +Epoch [3124/4000] Training [11/16] Loss: 0.00246 +Epoch [3124/4000] Training [12/16] Loss: 0.00330 +Epoch [3124/4000] Training [13/16] Loss: 0.00388 +Epoch [3124/4000] Training [14/16] Loss: 0.00341 +Epoch [3124/4000] Training [15/16] Loss: 0.00307 +Epoch [3124/4000] Training [16/16] Loss: 0.00305 +Epoch [3124/4000] Training metric {'Train/mean dice_metric': 0.9983046650886536, 'Train/mean miou_metric': 0.9963408708572388, 'Train/mean f1': 0.9934229850769043, 'Train/mean precision': 0.9888806939125061, 'Train/mean recall': 0.99800705909729, 'Train/mean hd95_metric': 0.72336745262146} +Epoch [3124/4000] Validation [1/4] Loss: 0.43981 focal_loss 0.37359 dice_loss 0.06622 +Epoch [3124/4000] Validation [2/4] Loss: 0.41551 focal_loss 0.30909 dice_loss 0.10642 +Epoch [3124/4000] Validation [3/4] Loss: 0.52942 focal_loss 0.43623 dice_loss 0.09319 +Epoch [3124/4000] Validation [4/4] Loss: 0.26968 focal_loss 0.18445 dice_loss 0.08523 +Epoch [3124/4000] Validation metric {'Val/mean dice_metric': 0.9760515093803406, 'Val/mean miou_metric': 0.9615013003349304, 'Val/mean f1': 0.9765459299087524, 'Val/mean precision': 0.9731484651565552, 'Val/mean recall': 0.9799671769142151, 'Val/mean hd95_metric': 4.910441875457764} +Cheakpoint... +Epoch [3124/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9761], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9760515093803406, 'Val/mean miou_metric': 0.9615013003349304, 'Val/mean f1': 0.9765459299087524, 'Val/mean precision': 0.9731484651565552, 'Val/mean recall': 0.9799671769142151, 'Val/mean hd95_metric': 4.910441875457764} +Epoch [3125/4000] Training [1/16] Loss: 0.00274 +Epoch [3125/4000] Training [2/16] Loss: 0.00325 +Epoch [3125/4000] Training [3/16] Loss: 0.00284 +Epoch [3125/4000] Training [4/16] Loss: 0.00356 +Epoch [3125/4000] Training [5/16] Loss: 0.00332 +Epoch [3125/4000] Training [6/16] Loss: 0.00316 +Epoch [3125/4000] Training [7/16] Loss: 0.00268 +Epoch [3125/4000] Training [8/16] Loss: 0.00315 +Epoch [3125/4000] Training [9/16] Loss: 0.00311 +Epoch [3125/4000] Training [10/16] Loss: 0.00214 +Epoch [3125/4000] Training [11/16] Loss: 0.00308 +Epoch [3125/4000] Training [12/16] Loss: 0.00284 +Epoch [3125/4000] Training [13/16] Loss: 0.00310 +Epoch [3125/4000] Training [14/16] Loss: 0.00283 +Epoch [3125/4000] Training [15/16] Loss: 0.00249 +Epoch [3125/4000] Training [16/16] Loss: 0.00334 +Epoch [3125/4000] Training metric {'Train/mean dice_metric': 0.9982584714889526, 'Train/mean miou_metric': 0.9962407946586609, 'Train/mean f1': 0.9933753609657288, 'Train/mean precision': 0.9888444542884827, 'Train/mean recall': 0.9979479908943176, 'Train/mean hd95_metric': 0.7445587515830994} +Epoch [3125/4000] Validation [1/4] Loss: 0.41093 focal_loss 0.34616 dice_loss 0.06477 +Epoch [3125/4000] Validation [2/4] Loss: 1.37365 focal_loss 1.08552 dice_loss 0.28814 +Epoch [3125/4000] Validation [3/4] Loss: 0.53022 focal_loss 0.43409 dice_loss 0.09613 +Epoch [3125/4000] Validation [4/4] Loss: 0.33135 focal_loss 0.24248 dice_loss 0.08887 +Epoch [3125/4000] Validation metric {'Val/mean dice_metric': 0.9730812311172485, 'Val/mean miou_metric': 0.9589260220527649, 'Val/mean f1': 0.9757546186447144, 'Val/mean precision': 0.9727658033370972, 'Val/mean recall': 0.9787617921829224, 'Val/mean hd95_metric': 5.09528923034668} +Cheakpoint... +Epoch [3125/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730812311172485, 'Val/mean miou_metric': 0.9589260220527649, 'Val/mean f1': 0.9757546186447144, 'Val/mean precision': 0.9727658033370972, 'Val/mean recall': 0.9787617921829224, 'Val/mean hd95_metric': 5.09528923034668} +Epoch [3126/4000] Training [1/16] Loss: 0.00253 +Epoch [3126/4000] Training [2/16] Loss: 0.00266 +Epoch [3126/4000] Training [3/16] Loss: 0.00364 +Epoch [3126/4000] Training [4/16] Loss: 0.00467 +Epoch [3126/4000] Training [5/16] Loss: 0.00313 +Epoch [3126/4000] Training [6/16] Loss: 0.00273 +Epoch [3126/4000] Training [7/16] Loss: 0.00230 +Epoch [3126/4000] Training [8/16] Loss: 0.00221 +Epoch [3126/4000] Training [9/16] Loss: 0.00376 +Epoch [3126/4000] Training [10/16] Loss: 0.00296 +Epoch [3126/4000] Training [11/16] Loss: 0.00337 +Epoch [3126/4000] Training [12/16] Loss: 0.00515 +Epoch [3126/4000] Training [13/16] Loss: 0.00354 +Epoch [3126/4000] Training [14/16] Loss: 0.00421 +Epoch [3126/4000] Training [15/16] Loss: 0.00233 +Epoch [3126/4000] Training [16/16] Loss: 0.00415 +Epoch [3126/4000] Training metric {'Train/mean dice_metric': 0.9982428550720215, 'Train/mean miou_metric': 0.9961946606636047, 'Train/mean f1': 0.9931527972221375, 'Train/mean precision': 0.9884290099143982, 'Train/mean recall': 0.9979220032691956, 'Train/mean hd95_metric': 0.7009524703025818} +Epoch [3126/4000] Validation [1/4] Loss: 0.34719 focal_loss 0.28596 dice_loss 0.06122 +Epoch [3126/4000] Validation [2/4] Loss: 0.83868 focal_loss 0.62901 dice_loss 0.20967 +Epoch [3126/4000] Validation [3/4] Loss: 0.26234 focal_loss 0.19838 dice_loss 0.06396 +Epoch [3126/4000] Validation [4/4] Loss: 0.43143 focal_loss 0.32330 dice_loss 0.10813 +Epoch [3126/4000] Validation metric {'Val/mean dice_metric': 0.9711191058158875, 'Val/mean miou_metric': 0.9572982788085938, 'Val/mean f1': 0.975429892539978, 'Val/mean precision': 0.9727715849876404, 'Val/mean recall': 0.97810298204422, 'Val/mean hd95_metric': 5.318487167358398} +Cheakpoint... +Epoch [3126/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711191058158875, 'Val/mean miou_metric': 0.9572982788085938, 'Val/mean f1': 0.975429892539978, 'Val/mean precision': 0.9727715849876404, 'Val/mean recall': 0.97810298204422, 'Val/mean hd95_metric': 5.318487167358398} +Epoch [3127/4000] Training [1/16] Loss: 0.00368 +Epoch [3127/4000] Training [2/16] Loss: 0.00212 +Epoch [3127/4000] Training [3/16] Loss: 0.00279 +Epoch [3127/4000] Training [4/16] Loss: 0.00320 +Epoch [3127/4000] Training [5/16] Loss: 0.00374 +Epoch [3127/4000] Training [6/16] Loss: 0.00253 +Epoch [3127/4000] Training [7/16] Loss: 0.00217 +Epoch [3127/4000] Training [8/16] Loss: 0.00464 +Epoch [3127/4000] Training [9/16] Loss: 0.00258 +Epoch [3127/4000] Training [10/16] Loss: 0.00257 +Epoch [3127/4000] Training [11/16] Loss: 0.00326 +Epoch [3127/4000] Training [12/16] Loss: 0.00279 +Epoch [3127/4000] Training [13/16] Loss: 0.00358 +Epoch [3127/4000] Training [14/16] Loss: 0.00337 +Epoch [3127/4000] Training [15/16] Loss: 0.00277 +Epoch [3127/4000] Training [16/16] Loss: 0.00266 +Epoch [3127/4000] Training metric {'Train/mean dice_metric': 0.9983490109443665, 'Train/mean miou_metric': 0.996406078338623, 'Train/mean f1': 0.9933170676231384, 'Train/mean precision': 0.9886301159858704, 'Train/mean recall': 0.9980486035346985, 'Train/mean hd95_metric': 0.7271325588226318} +Epoch [3127/4000] Validation [1/4] Loss: 0.34192 focal_loss 0.28103 dice_loss 0.06090 +Epoch [3127/4000] Validation [2/4] Loss: 0.44678 focal_loss 0.33171 dice_loss 0.11507 +Epoch [3127/4000] Validation [3/4] Loss: 0.51714 focal_loss 0.42270 dice_loss 0.09444 +Epoch [3127/4000] Validation [4/4] Loss: 0.48531 focal_loss 0.36481 dice_loss 0.12050 +Epoch [3127/4000] Validation metric {'Val/mean dice_metric': 0.9750528335571289, 'Val/mean miou_metric': 0.9605109095573425, 'Val/mean f1': 0.9762377738952637, 'Val/mean precision': 0.9735238552093506, 'Val/mean recall': 0.9789668917655945, 'Val/mean hd95_metric': 4.940820217132568} +Cheakpoint... +Epoch [3127/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750528335571289, 'Val/mean miou_metric': 0.9605109095573425, 'Val/mean f1': 0.9762377738952637, 'Val/mean precision': 0.9735238552093506, 'Val/mean recall': 0.9789668917655945, 'Val/mean hd95_metric': 4.940820217132568} +Epoch [3128/4000] Training [1/16] Loss: 0.00457 +Epoch [3128/4000] Training [2/16] Loss: 0.00292 +Epoch [3128/4000] Training [3/16] Loss: 0.00358 +Epoch [3128/4000] Training [4/16] Loss: 0.00286 +Epoch [3128/4000] Training [5/16] Loss: 0.00295 +Epoch [3128/4000] Training [6/16] Loss: 0.00210 +Epoch [3128/4000] Training [7/16] Loss: 0.00200 +Epoch [3128/4000] Training [8/16] Loss: 0.00305 +Epoch [3128/4000] Training [9/16] Loss: 0.00250 +Epoch [3128/4000] Training [10/16] Loss: 0.00271 +Epoch [3128/4000] Training [11/16] Loss: 0.00264 +Epoch [3128/4000] Training [12/16] Loss: 0.00336 +Epoch [3128/4000] Training [13/16] Loss: 0.00429 +Epoch [3128/4000] Training [14/16] Loss: 0.00447 +Epoch [3128/4000] Training [15/16] Loss: 0.00262 +Epoch [3128/4000] Training [16/16] Loss: 0.00374 +Epoch [3128/4000] Training metric {'Train/mean dice_metric': 0.9982115030288696, 'Train/mean miou_metric': 0.9961202144622803, 'Train/mean f1': 0.9925645589828491, 'Train/mean precision': 0.9873551726341248, 'Train/mean recall': 0.9978294372558594, 'Train/mean hd95_metric': 0.7526641488075256} +Epoch [3128/4000] Validation [1/4] Loss: 0.42411 focal_loss 0.35921 dice_loss 0.06490 +Epoch [3128/4000] Validation [2/4] Loss: 0.40087 focal_loss 0.29797 dice_loss 0.10290 +Epoch [3128/4000] Validation [3/4] Loss: 0.49261 focal_loss 0.39677 dice_loss 0.09584 +Epoch [3128/4000] Validation [4/4] Loss: 0.29304 focal_loss 0.20168 dice_loss 0.09136 +Epoch [3128/4000] Validation metric {'Val/mean dice_metric': 0.9747241139411926, 'Val/mean miou_metric': 0.9603878259658813, 'Val/mean f1': 0.9761810898780823, 'Val/mean precision': 0.9722165465354919, 'Val/mean recall': 0.9801780581474304, 'Val/mean hd95_metric': 4.952885627746582} +Cheakpoint... +Epoch [3128/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747241139411926, 'Val/mean miou_metric': 0.9603878259658813, 'Val/mean f1': 0.9761810898780823, 'Val/mean precision': 0.9722165465354919, 'Val/mean recall': 0.9801780581474304, 'Val/mean hd95_metric': 4.952885627746582} +Epoch [3129/4000] Training [1/16] Loss: 0.00215 +Epoch [3129/4000] Training [2/16] Loss: 0.00317 +Epoch [3129/4000] Training [3/16] Loss: 0.00376 +Epoch [3129/4000] Training [4/16] Loss: 0.00267 +Epoch [3129/4000] Training [5/16] Loss: 0.00263 +Epoch [3129/4000] Training [6/16] Loss: 0.00247 +Epoch [3129/4000] Training [7/16] Loss: 0.00361 +Epoch [3129/4000] Training [8/16] Loss: 0.00281 +Epoch [3129/4000] Training [9/16] Loss: 0.00310 +Epoch [3129/4000] Training [10/16] Loss: 0.00257 +Epoch [3129/4000] Training [11/16] Loss: 0.00250 +Epoch [3129/4000] Training [12/16] Loss: 0.00236 +Epoch [3129/4000] Training [13/16] Loss: 0.00236 +Epoch [3129/4000] Training [14/16] Loss: 0.00230 +Epoch [3129/4000] Training [15/16] Loss: 0.00266 +Epoch [3129/4000] Training [16/16] Loss: 0.00350 +Epoch [3129/4000] Training metric {'Train/mean dice_metric': 0.9984468221664429, 'Train/mean miou_metric': 0.9965903162956238, 'Train/mean f1': 0.9928765892982483, 'Train/mean precision': 0.9877506494522095, 'Train/mean recall': 0.9980559945106506, 'Train/mean hd95_metric': 0.7266876697540283} +Epoch [3129/4000] Validation [1/4] Loss: 0.42258 focal_loss 0.35558 dice_loss 0.06700 +Epoch [3129/4000] Validation [2/4] Loss: 0.39548 focal_loss 0.29205 dice_loss 0.10343 +Epoch [3129/4000] Validation [3/4] Loss: 0.51427 focal_loss 0.41993 dice_loss 0.09434 +Epoch [3129/4000] Validation [4/4] Loss: 0.30183 focal_loss 0.21343 dice_loss 0.08840 +Epoch [3129/4000] Validation metric {'Val/mean dice_metric': 0.9752079844474792, 'Val/mean miou_metric': 0.9608338475227356, 'Val/mean f1': 0.9755853414535522, 'Val/mean precision': 0.972230076789856, 'Val/mean recall': 0.9789638519287109, 'Val/mean hd95_metric': 4.99212121963501} +Cheakpoint... +Epoch [3129/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752079844474792, 'Val/mean miou_metric': 0.9608338475227356, 'Val/mean f1': 0.9755853414535522, 'Val/mean precision': 0.972230076789856, 'Val/mean recall': 0.9789638519287109, 'Val/mean hd95_metric': 4.99212121963501} +Epoch [3130/4000] Training [1/16] Loss: 0.00328 +Epoch [3130/4000] Training [2/16] Loss: 0.00195 +Epoch [3130/4000] Training [3/16] Loss: 0.00297 +Epoch [3130/4000] Training [4/16] Loss: 0.00318 +Epoch [3130/4000] Training [5/16] Loss: 0.00392 +Epoch [3130/4000] Training [6/16] Loss: 0.00247 +Epoch [3130/4000] Training [7/16] Loss: 0.00285 +Epoch [3130/4000] Training [8/16] Loss: 0.00331 +Epoch [3130/4000] Training [9/16] Loss: 0.00235 +Epoch [3130/4000] Training [10/16] Loss: 0.00148 +Epoch [3130/4000] Training [11/16] Loss: 0.00316 +Epoch [3130/4000] Training [12/16] Loss: 0.00232 +Epoch [3130/4000] Training [13/16] Loss: 0.00234 +Epoch [3130/4000] Training [14/16] Loss: 0.00298 +Epoch [3130/4000] Training [15/16] Loss: 0.00381 +Epoch [3130/4000] Training [16/16] Loss: 0.00317 +Epoch [3130/4000] Training metric {'Train/mean dice_metric': 0.9984108805656433, 'Train/mean miou_metric': 0.9965528845787048, 'Train/mean f1': 0.9936202764511108, 'Train/mean precision': 0.9891064763069153, 'Train/mean recall': 0.9981754422187805, 'Train/mean hd95_metric': 0.6940202116966248} +Epoch [3130/4000] Validation [1/4] Loss: 0.34266 focal_loss 0.27847 dice_loss 0.06420 +Epoch [3130/4000] Validation [2/4] Loss: 0.38858 focal_loss 0.28653 dice_loss 0.10205 +Epoch [3130/4000] Validation [3/4] Loss: 0.51570 focal_loss 0.41918 dice_loss 0.09651 +Epoch [3130/4000] Validation [4/4] Loss: 0.41768 focal_loss 0.30761 dice_loss 0.11007 +Epoch [3130/4000] Validation metric {'Val/mean dice_metric': 0.9745284914970398, 'Val/mean miou_metric': 0.9598718881607056, 'Val/mean f1': 0.9763451814651489, 'Val/mean precision': 0.9741454720497131, 'Val/mean recall': 0.9785549640655518, 'Val/mean hd95_metric': 4.710536956787109} +Cheakpoint... +Epoch [3130/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745284914970398, 'Val/mean miou_metric': 0.9598718881607056, 'Val/mean f1': 0.9763451814651489, 'Val/mean precision': 0.9741454720497131, 'Val/mean recall': 0.9785549640655518, 'Val/mean hd95_metric': 4.710536956787109} +Epoch [3131/4000] Training [1/16] Loss: 0.00280 +Epoch [3131/4000] Training [2/16] Loss: 0.00273 +Epoch [3131/4000] Training [3/16] Loss: 0.00329 +Epoch [3131/4000] Training [4/16] Loss: 0.00353 +Epoch [3131/4000] Training [5/16] Loss: 0.00330 +Epoch [3131/4000] Training [6/16] Loss: 0.00236 +Epoch [3131/4000] Training [7/16] Loss: 0.00294 +Epoch [3131/4000] Training [8/16] Loss: 0.00344 +Epoch [3131/4000] Training [9/16] Loss: 0.00217 +Epoch [3131/4000] Training [10/16] Loss: 0.00304 +Epoch [3131/4000] Training [11/16] Loss: 0.00474 +Epoch [3131/4000] Training [12/16] Loss: 0.00294 +Epoch [3131/4000] Training [13/16] Loss: 0.00261 +Epoch [3131/4000] Training [14/16] Loss: 0.00276 +Epoch [3131/4000] Training [15/16] Loss: 0.00243 +Epoch [3131/4000] Training [16/16] Loss: 0.00291 +Epoch [3131/4000] Training metric {'Train/mean dice_metric': 0.9983631372451782, 'Train/mean miou_metric': 0.9964587688446045, 'Train/mean f1': 0.9934853315353394, 'Train/mean precision': 0.9889179468154907, 'Train/mean recall': 0.9980950951576233, 'Train/mean hd95_metric': 0.709282398223877} +Epoch [3131/4000] Validation [1/4] Loss: 0.36296 focal_loss 0.30284 dice_loss 0.06011 +Epoch [3131/4000] Validation [2/4] Loss: 0.39592 focal_loss 0.29168 dice_loss 0.10424 +Epoch [3131/4000] Validation [3/4] Loss: 0.47632 focal_loss 0.38960 dice_loss 0.08672 +Epoch [3131/4000] Validation [4/4] Loss: 0.33327 focal_loss 0.23901 dice_loss 0.09426 +Epoch [3131/4000] Validation metric {'Val/mean dice_metric': 0.9746366739273071, 'Val/mean miou_metric': 0.9607979655265808, 'Val/mean f1': 0.9764770865440369, 'Val/mean precision': 0.9742742776870728, 'Val/mean recall': 0.9786900877952576, 'Val/mean hd95_metric': 5.294673919677734} +Cheakpoint... +Epoch [3131/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746366739273071, 'Val/mean miou_metric': 0.9607979655265808, 'Val/mean f1': 0.9764770865440369, 'Val/mean precision': 0.9742742776870728, 'Val/mean recall': 0.9786900877952576, 'Val/mean hd95_metric': 5.294673919677734} +Epoch [3132/4000] Training [1/16] Loss: 0.00293 +Epoch [3132/4000] Training [2/16] Loss: 0.00291 +Epoch [3132/4000] Training [3/16] Loss: 0.00265 +Epoch [3132/4000] Training [4/16] Loss: 0.00247 +Epoch [3132/4000] Training [5/16] Loss: 0.00276 +Epoch [3132/4000] Training [6/16] Loss: 0.00313 +Epoch [3132/4000] Training [7/16] Loss: 0.00323 +Epoch [3132/4000] Training [8/16] Loss: 0.00498 +Epoch [3132/4000] Training [9/16] Loss: 0.00311 +Epoch [3132/4000] Training [10/16] Loss: 0.00293 +Epoch [3132/4000] Training [11/16] Loss: 0.00887 +Epoch [3132/4000] Training [12/16] Loss: 0.00219 +Epoch [3132/4000] Training [13/16] Loss: 0.00328 +Epoch [3132/4000] Training [14/16] Loss: 0.00250 +Epoch [3132/4000] Training [15/16] Loss: 0.00262 +Epoch [3132/4000] Training [16/16] Loss: 0.00374 +Epoch [3132/4000] Training metric {'Train/mean dice_metric': 0.998221755027771, 'Train/mean miou_metric': 0.9961521625518799, 'Train/mean f1': 0.9931472539901733, 'Train/mean precision': 0.9883520603179932, 'Train/mean recall': 0.9979892373085022, 'Train/mean hd95_metric': 0.7660104036331177} +Epoch [3132/4000] Validation [1/4] Loss: 0.40633 focal_loss 0.34097 dice_loss 0.06537 +Epoch [3132/4000] Validation [2/4] Loss: 0.49684 focal_loss 0.35345 dice_loss 0.14339 +Epoch [3132/4000] Validation [3/4] Loss: 0.49702 focal_loss 0.40828 dice_loss 0.08874 +Epoch [3132/4000] Validation [4/4] Loss: 0.44289 focal_loss 0.33218 dice_loss 0.11070 +Epoch [3132/4000] Validation metric {'Val/mean dice_metric': 0.9723049998283386, 'Val/mean miou_metric': 0.9583365321159363, 'Val/mean f1': 0.9756816625595093, 'Val/mean precision': 0.9731541872024536, 'Val/mean recall': 0.9782223105430603, 'Val/mean hd95_metric': 5.562223434448242} +Cheakpoint... +Epoch [3132/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723049998283386, 'Val/mean miou_metric': 0.9583365321159363, 'Val/mean f1': 0.9756816625595093, 'Val/mean precision': 0.9731541872024536, 'Val/mean recall': 0.9782223105430603, 'Val/mean hd95_metric': 5.562223434448242} +Epoch [3133/4000] Training [1/16] Loss: 0.00326 +Epoch [3133/4000] Training [2/16] Loss: 0.00315 +Epoch [3133/4000] Training [3/16] Loss: 0.00276 +Epoch [3133/4000] Training [4/16] Loss: 0.00248 +Epoch [3133/4000] Training [5/16] Loss: 0.00254 +Epoch [3133/4000] Training [6/16] Loss: 0.00329 +Epoch [3133/4000] Training [7/16] Loss: 0.00291 +Epoch [3133/4000] Training [8/16] Loss: 0.00295 +Epoch [3133/4000] Training [9/16] Loss: 0.00326 +Epoch [3133/4000] Training [10/16] Loss: 0.00334 +Epoch [3133/4000] Training [11/16] Loss: 0.00298 +Epoch [3133/4000] Training [12/16] Loss: 0.00265 +Epoch [3133/4000] Training [13/16] Loss: 0.00289 +Epoch [3133/4000] Training [14/16] Loss: 0.00292 +Epoch [3133/4000] Training [15/16] Loss: 0.00323 +Epoch [3133/4000] Training [16/16] Loss: 0.00265 +Epoch [3133/4000] Training metric {'Train/mean dice_metric': 0.9981967210769653, 'Train/mean miou_metric': 0.9961237907409668, 'Train/mean f1': 0.9933076500892639, 'Train/mean precision': 0.988785445690155, 'Train/mean recall': 0.9978713989257812, 'Train/mean hd95_metric': 0.7600163221359253} +Epoch [3133/4000] Validation [1/4] Loss: 0.38601 focal_loss 0.32074 dice_loss 0.06527 +Epoch [3133/4000] Validation [2/4] Loss: 0.50877 focal_loss 0.36712 dice_loss 0.14164 +Epoch [3133/4000] Validation [3/4] Loss: 0.50632 focal_loss 0.41529 dice_loss 0.09103 +Epoch [3133/4000] Validation [4/4] Loss: 0.32251 focal_loss 0.23583 dice_loss 0.08668 +Epoch [3133/4000] Validation metric {'Val/mean dice_metric': 0.9744779467582703, 'Val/mean miou_metric': 0.9598075151443481, 'Val/mean f1': 0.9757822751998901, 'Val/mean precision': 0.9729101061820984, 'Val/mean recall': 0.9786714911460876, 'Val/mean hd95_metric': 5.3033447265625} +Cheakpoint... +Epoch [3133/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744779467582703, 'Val/mean miou_metric': 0.9598075151443481, 'Val/mean f1': 0.9757822751998901, 'Val/mean precision': 0.9729101061820984, 'Val/mean recall': 0.9786714911460876, 'Val/mean hd95_metric': 5.3033447265625} +Epoch [3134/4000] Training [1/16] Loss: 0.00292 +Epoch [3134/4000] Training [2/16] Loss: 0.00290 +Epoch [3134/4000] Training [3/16] Loss: 0.00275 +Epoch [3134/4000] Training [4/16] Loss: 0.00271 +Epoch [3134/4000] Training [5/16] Loss: 0.00215 +Epoch [3134/4000] Training [6/16] Loss: 0.00235 +Epoch [3134/4000] Training [7/16] Loss: 0.00335 +Epoch [3134/4000] Training [8/16] Loss: 0.00280 +Epoch [3134/4000] Training [9/16] Loss: 0.00373 +Epoch [3134/4000] Training [10/16] Loss: 0.00299 +Epoch [3134/4000] Training [11/16] Loss: 0.00373 +Epoch [3134/4000] Training [12/16] Loss: 0.00329 +Epoch [3134/4000] Training [13/16] Loss: 0.00249 +Epoch [3134/4000] Training [14/16] Loss: 0.00327 +Epoch [3134/4000] Training [15/16] Loss: 0.00476 +Epoch [3134/4000] Training [16/16] Loss: 0.00307 +Epoch [3134/4000] Training metric {'Train/mean dice_metric': 0.9982516169548035, 'Train/mean miou_metric': 0.9962361454963684, 'Train/mean f1': 0.9934155941009521, 'Train/mean precision': 0.9889088869094849, 'Train/mean recall': 0.9979634881019592, 'Train/mean hd95_metric': 0.7511296272277832} +Epoch [3134/4000] Validation [1/4] Loss: 0.39348 focal_loss 0.32826 dice_loss 0.06522 +Epoch [3134/4000] Validation [2/4] Loss: 0.40664 focal_loss 0.30203 dice_loss 0.10461 +Epoch [3134/4000] Validation [3/4] Loss: 0.27071 focal_loss 0.20561 dice_loss 0.06510 +Epoch [3134/4000] Validation [4/4] Loss: 0.31068 focal_loss 0.22816 dice_loss 0.08251 +Epoch [3134/4000] Validation metric {'Val/mean dice_metric': 0.9750040769577026, 'Val/mean miou_metric': 0.9608402252197266, 'Val/mean f1': 0.9765726327896118, 'Val/mean precision': 0.974879264831543, 'Val/mean recall': 0.9782718420028687, 'Val/mean hd95_metric': 4.778100490570068} +Cheakpoint... +Epoch [3134/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750040769577026, 'Val/mean miou_metric': 0.9608402252197266, 'Val/mean f1': 0.9765726327896118, 'Val/mean precision': 0.974879264831543, 'Val/mean recall': 0.9782718420028687, 'Val/mean hd95_metric': 4.778100490570068} +Epoch [3135/4000] Training [1/16] Loss: 0.00347 +Epoch [3135/4000] Training [2/16] Loss: 0.00215 +Epoch [3135/4000] Training [3/16] Loss: 0.00198 +Epoch [3135/4000] Training [4/16] Loss: 0.00381 +Epoch [3135/4000] Training [5/16] Loss: 0.00269 +Epoch [3135/4000] Training [6/16] Loss: 0.00208 +Epoch [3135/4000] Training [7/16] Loss: 0.00260 +Epoch [3135/4000] Training [8/16] Loss: 0.00201 +Epoch [3135/4000] Training [9/16] Loss: 0.00287 +Epoch [3135/4000] Training [10/16] Loss: 0.00324 +Epoch [3135/4000] Training [11/16] Loss: 0.00385 +Epoch [3135/4000] Training [12/16] Loss: 0.00367 +Epoch [3135/4000] Training [13/16] Loss: 0.00203 +Epoch [3135/4000] Training [14/16] Loss: 0.00315 +Epoch [3135/4000] Training [15/16] Loss: 0.00436 +Epoch [3135/4000] Training [16/16] Loss: 0.00234 +Epoch [3135/4000] Training metric {'Train/mean dice_metric': 0.9984253644943237, 'Train/mean miou_metric': 0.9965662956237793, 'Train/mean f1': 0.9933724999427795, 'Train/mean precision': 0.9886190295219421, 'Train/mean recall': 0.9981718063354492, 'Train/mean hd95_metric': 0.6678010821342468} +Epoch [3135/4000] Validation [1/4] Loss: 0.36882 focal_loss 0.30592 dice_loss 0.06289 +Epoch [3135/4000] Validation [2/4] Loss: 0.88786 focal_loss 0.69573 dice_loss 0.19213 +Epoch [3135/4000] Validation [3/4] Loss: 0.51668 focal_loss 0.41830 dice_loss 0.09839 +Epoch [3135/4000] Validation [4/4] Loss: 0.54418 focal_loss 0.41685 dice_loss 0.12732 +Epoch [3135/4000] Validation metric {'Val/mean dice_metric': 0.973059356212616, 'Val/mean miou_metric': 0.9590578079223633, 'Val/mean f1': 0.9754695892333984, 'Val/mean precision': 0.9735780954360962, 'Val/mean recall': 0.9773685932159424, 'Val/mean hd95_metric': 5.133694648742676} +Cheakpoint... +Epoch [3135/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973059356212616, 'Val/mean miou_metric': 0.9590578079223633, 'Val/mean f1': 0.9754695892333984, 'Val/mean precision': 0.9735780954360962, 'Val/mean recall': 0.9773685932159424, 'Val/mean hd95_metric': 5.133694648742676} +Epoch [3136/4000] Training [1/16] Loss: 0.00323 +Epoch [3136/4000] Training [2/16] Loss: 0.00379 +Epoch [3136/4000] Training [3/16] Loss: 0.00274 +Epoch [3136/4000] Training [4/16] Loss: 0.00181 +Epoch [3136/4000] Training [5/16] Loss: 0.00222 +Epoch [3136/4000] Training [6/16] Loss: 0.00271 +Epoch [3136/4000] Training [7/16] Loss: 0.00228 +Epoch [3136/4000] Training [8/16] Loss: 0.00299 +Epoch [3136/4000] Training [9/16] Loss: 0.00258 +Epoch [3136/4000] Training [10/16] Loss: 0.00276 +Epoch [3136/4000] Training [11/16] Loss: 0.00260 +Epoch [3136/4000] Training [12/16] Loss: 0.00316 +Epoch [3136/4000] Training [13/16] Loss: 0.00316 +Epoch [3136/4000] Training [14/16] Loss: 0.00364 +Epoch [3136/4000] Training [15/16] Loss: 0.00334 +Epoch [3136/4000] Training [16/16] Loss: 0.00328 +Epoch [3136/4000] Training metric {'Train/mean dice_metric': 0.9983838796615601, 'Train/mean miou_metric': 0.9964905381202698, 'Train/mean f1': 0.9932781457901001, 'Train/mean precision': 0.9886564016342163, 'Train/mean recall': 0.9979432821273804, 'Train/mean hd95_metric': 0.680984616279602} +Epoch [3136/4000] Validation [1/4] Loss: 0.41853 focal_loss 0.35018 dice_loss 0.06835 +Epoch [3136/4000] Validation [2/4] Loss: 0.41471 focal_loss 0.30437 dice_loss 0.11034 +Epoch [3136/4000] Validation [3/4] Loss: 0.30747 focal_loss 0.23855 dice_loss 0.06892 +Epoch [3136/4000] Validation [4/4] Loss: 0.25142 focal_loss 0.17277 dice_loss 0.07865 +Epoch [3136/4000] Validation metric {'Val/mean dice_metric': 0.9738547205924988, 'Val/mean miou_metric': 0.9598825573921204, 'Val/mean f1': 0.9756501317024231, 'Val/mean precision': 0.974362850189209, 'Val/mean recall': 0.9769407510757446, 'Val/mean hd95_metric': 5.044813632965088} +Cheakpoint... +Epoch [3136/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738547205924988, 'Val/mean miou_metric': 0.9598825573921204, 'Val/mean f1': 0.9756501317024231, 'Val/mean precision': 0.974362850189209, 'Val/mean recall': 0.9769407510757446, 'Val/mean hd95_metric': 5.044813632965088} +Epoch [3137/4000] Training [1/16] Loss: 0.00520 +Epoch [3137/4000] Training [2/16] Loss: 0.00364 +Epoch [3137/4000] Training [3/16] Loss: 0.00278 +Epoch [3137/4000] Training [4/16] Loss: 0.00249 +Epoch [3137/4000] Training [5/16] Loss: 0.00290 +Epoch [3137/4000] Training [6/16] Loss: 0.00199 +Epoch [3137/4000] Training [7/16] Loss: 0.00336 +Epoch [3137/4000] Training [8/16] Loss: 0.00241 +Epoch [3137/4000] Training [9/16] Loss: 0.00274 +Epoch [3137/4000] Training [10/16] Loss: 0.00264 +Epoch [3137/4000] Training [11/16] Loss: 0.00291 +Epoch [3137/4000] Training [12/16] Loss: 0.00400 +Epoch [3137/4000] Training [13/16] Loss: 0.00326 +Epoch [3137/4000] Training [14/16] Loss: 0.00342 +Epoch [3137/4000] Training [15/16] Loss: 0.00293 +Epoch [3137/4000] Training [16/16] Loss: 0.00333 +Epoch [3137/4000] Training metric {'Train/mean dice_metric': 0.9983544945716858, 'Train/mean miou_metric': 0.9964320659637451, 'Train/mean f1': 0.9933426976203918, 'Train/mean precision': 0.9887130260467529, 'Train/mean recall': 0.9980159997940063, 'Train/mean hd95_metric': 0.7101140022277832} +Epoch [3137/4000] Validation [1/4] Loss: 0.40396 focal_loss 0.33837 dice_loss 0.06559 +Epoch [3137/4000] Validation [2/4] Loss: 0.94072 focal_loss 0.74516 dice_loss 0.19556 +Epoch [3137/4000] Validation [3/4] Loss: 0.55322 focal_loss 0.45147 dice_loss 0.10175 +Epoch [3137/4000] Validation [4/4] Loss: 0.30853 focal_loss 0.21076 dice_loss 0.09776 +Epoch [3137/4000] Validation metric {'Val/mean dice_metric': 0.9737766981124878, 'Val/mean miou_metric': 0.9594437479972839, 'Val/mean f1': 0.9759025573730469, 'Val/mean precision': 0.9743451476097107, 'Val/mean recall': 0.9774649739265442, 'Val/mean hd95_metric': 4.799938678741455} +Cheakpoint... +Epoch [3137/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737766981124878, 'Val/mean miou_metric': 0.9594437479972839, 'Val/mean f1': 0.9759025573730469, 'Val/mean precision': 0.9743451476097107, 'Val/mean recall': 0.9774649739265442, 'Val/mean hd95_metric': 4.799938678741455} +Epoch [3138/4000] Training [1/16] Loss: 0.00221 +Epoch [3138/4000] Training [2/16] Loss: 0.00352 +Epoch [3138/4000] Training [3/16] Loss: 0.00224 +Epoch [3138/4000] Training [4/16] Loss: 0.00305 +Epoch [3138/4000] Training [5/16] Loss: 0.00339 +Epoch [3138/4000] Training [6/16] Loss: 0.00296 +Epoch [3138/4000] Training [7/16] Loss: 0.00288 +Epoch [3138/4000] Training [8/16] Loss: 0.00473 +Epoch [3138/4000] Training [9/16] Loss: 0.00292 +Epoch [3138/4000] Training [10/16] Loss: 0.00232 +Epoch [3138/4000] Training [11/16] Loss: 0.00359 +Epoch [3138/4000] Training [12/16] Loss: 0.00385 +Epoch [3138/4000] Training [13/16] Loss: 0.00228 +Epoch [3138/4000] Training [14/16] Loss: 0.00277 +Epoch [3138/4000] Training [15/16] Loss: 0.00247 +Epoch [3138/4000] Training [16/16] Loss: 0.00338 +Epoch [3138/4000] Training metric {'Train/mean dice_metric': 0.9983072876930237, 'Train/mean miou_metric': 0.9963292479515076, 'Train/mean f1': 0.993189811706543, 'Train/mean precision': 0.9884425401687622, 'Train/mean recall': 0.9979829788208008, 'Train/mean hd95_metric': 0.720758318901062} +Epoch [3138/4000] Validation [1/4] Loss: 0.38027 focal_loss 0.31693 dice_loss 0.06333 +Epoch [3138/4000] Validation [2/4] Loss: 0.41738 focal_loss 0.30915 dice_loss 0.10823 +Epoch [3138/4000] Validation [3/4] Loss: 0.51880 focal_loss 0.42006 dice_loss 0.09874 +Epoch [3138/4000] Validation [4/4] Loss: 0.32033 focal_loss 0.22884 dice_loss 0.09149 +Epoch [3138/4000] Validation metric {'Val/mean dice_metric': 0.9743359684944153, 'Val/mean miou_metric': 0.9602438807487488, 'Val/mean f1': 0.9763072729110718, 'Val/mean precision': 0.9735373258590698, 'Val/mean recall': 0.9790931344032288, 'Val/mean hd95_metric': 4.911672592163086} +Cheakpoint... +Epoch [3138/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743359684944153, 'Val/mean miou_metric': 0.9602438807487488, 'Val/mean f1': 0.9763072729110718, 'Val/mean precision': 0.9735373258590698, 'Val/mean recall': 0.9790931344032288, 'Val/mean hd95_metric': 4.911672592163086} +Epoch [3139/4000] Training [1/16] Loss: 0.00362 +Epoch [3139/4000] Training [2/16] Loss: 0.00390 +Epoch [3139/4000] Training [3/16] Loss: 0.00313 +Epoch [3139/4000] Training [4/16] Loss: 0.00298 +Epoch [3139/4000] Training [5/16] Loss: 0.00255 +Epoch [3139/4000] Training [6/16] Loss: 0.00497 +Epoch [3139/4000] Training [7/16] Loss: 0.00323 +Epoch [3139/4000] Training [8/16] Loss: 0.00681 +Epoch [3139/4000] Training [9/16] Loss: 0.00286 +Epoch [3139/4000] Training [10/16] Loss: 0.00249 +Epoch [3139/4000] Training [11/16] Loss: 0.00223 +Epoch [3139/4000] Training [12/16] Loss: 0.00291 +Epoch [3139/4000] Training [13/16] Loss: 0.00341 +Epoch [3139/4000] Training [14/16] Loss: 0.00235 +Epoch [3139/4000] Training [15/16] Loss: 0.00180 +Epoch [3139/4000] Training [16/16] Loss: 0.00227 +Epoch [3139/4000] Training metric {'Train/mean dice_metric': 0.9983724355697632, 'Train/mean miou_metric': 0.9964742660522461, 'Train/mean f1': 0.9934427738189697, 'Train/mean precision': 0.9888735413551331, 'Train/mean recall': 0.9980545043945312, 'Train/mean hd95_metric': 0.7425523996353149} +Epoch [3139/4000] Validation [1/4] Loss: 0.38475 focal_loss 0.32117 dice_loss 0.06358 +Epoch [3139/4000] Validation [2/4] Loss: 0.96236 focal_loss 0.76661 dice_loss 0.19574 +Epoch [3139/4000] Validation [3/4] Loss: 0.49531 focal_loss 0.40095 dice_loss 0.09436 +Epoch [3139/4000] Validation [4/4] Loss: 0.37892 focal_loss 0.26678 dice_loss 0.11214 +Epoch [3139/4000] Validation metric {'Val/mean dice_metric': 0.9748796224594116, 'Val/mean miou_metric': 0.9603333473205566, 'Val/mean f1': 0.9758908748626709, 'Val/mean precision': 0.9737842679023743, 'Val/mean recall': 0.9780065417289734, 'Val/mean hd95_metric': 4.8315205574035645} +Cheakpoint... +Epoch [3139/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748796224594116, 'Val/mean miou_metric': 0.9603333473205566, 'Val/mean f1': 0.9758908748626709, 'Val/mean precision': 0.9737842679023743, 'Val/mean recall': 0.9780065417289734, 'Val/mean hd95_metric': 4.8315205574035645} +Epoch [3140/4000] Training [1/16] Loss: 0.00298 +Epoch [3140/4000] Training [2/16] Loss: 0.00304 +Epoch [3140/4000] Training [3/16] Loss: 0.00308 +Epoch [3140/4000] Training [4/16] Loss: 0.00316 +Epoch [3140/4000] Training [5/16] Loss: 0.00250 +Epoch [3140/4000] Training [6/16] Loss: 0.00223 +Epoch [3140/4000] Training [7/16] Loss: 0.00391 +Epoch [3140/4000] Training [8/16] Loss: 0.00171 +Epoch [3140/4000] Training [9/16] Loss: 0.00228 +Epoch [3140/4000] Training [10/16] Loss: 0.00250 +Epoch [3140/4000] Training [11/16] Loss: 0.00434 +Epoch [3140/4000] Training [12/16] Loss: 0.00235 +Epoch [3140/4000] Training [13/16] Loss: 0.00312 +Epoch [3140/4000] Training [14/16] Loss: 0.00329 +Epoch [3140/4000] Training [15/16] Loss: 0.00206 +Epoch [3140/4000] Training [16/16] Loss: 0.00212 +Epoch [3140/4000] Training metric {'Train/mean dice_metric': 0.9984267950057983, 'Train/mean miou_metric': 0.9965716600418091, 'Train/mean f1': 0.9934629797935486, 'Train/mean precision': 0.9888227581977844, 'Train/mean recall': 0.9981470108032227, 'Train/mean hd95_metric': 0.6940971612930298} +Epoch [3140/4000] Validation [1/4] Loss: 0.42288 focal_loss 0.35584 dice_loss 0.06704 +Epoch [3140/4000] Validation [2/4] Loss: 0.39138 focal_loss 0.28576 dice_loss 0.10561 +Epoch [3140/4000] Validation [3/4] Loss: 0.52815 focal_loss 0.43564 dice_loss 0.09252 +Epoch [3140/4000] Validation [4/4] Loss: 0.32750 focal_loss 0.23920 dice_loss 0.08830 +Epoch [3140/4000] Validation metric {'Val/mean dice_metric': 0.9729113578796387, 'Val/mean miou_metric': 0.9591680765151978, 'Val/mean f1': 0.9763498902320862, 'Val/mean precision': 0.9745398163795471, 'Val/mean recall': 0.9781665802001953, 'Val/mean hd95_metric': 4.969899654388428} +Cheakpoint... +Epoch [3140/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729113578796387, 'Val/mean miou_metric': 0.9591680765151978, 'Val/mean f1': 0.9763498902320862, 'Val/mean precision': 0.9745398163795471, 'Val/mean recall': 0.9781665802001953, 'Val/mean hd95_metric': 4.969899654388428} +Epoch [3141/4000] Training [1/16] Loss: 0.00307 +Epoch [3141/4000] Training [2/16] Loss: 0.00235 +Epoch [3141/4000] Training [3/16] Loss: 0.00348 +Epoch [3141/4000] Training [4/16] Loss: 0.00259 +Epoch [3141/4000] Training [5/16] Loss: 0.00232 +Epoch [3141/4000] Training [6/16] Loss: 0.00281 +Epoch [3141/4000] Training [7/16] Loss: 0.00215 +Epoch [3141/4000] Training [8/16] Loss: 0.00312 +Epoch [3141/4000] Training [9/16] Loss: 0.00354 +Epoch [3141/4000] Training [10/16] Loss: 0.00244 +Epoch [3141/4000] Training [11/16] Loss: 0.00251 +Epoch [3141/4000] Training [12/16] Loss: 0.00208 +Epoch [3141/4000] Training [13/16] Loss: 0.00271 +Epoch [3141/4000] Training [14/16] Loss: 0.00221 +Epoch [3141/4000] Training [15/16] Loss: 0.00374 +Epoch [3141/4000] Training [16/16] Loss: 0.00271 +Epoch [3141/4000] Training metric {'Train/mean dice_metric': 0.9984436631202698, 'Train/mean miou_metric': 0.9966193437576294, 'Train/mean f1': 0.9935740232467651, 'Train/mean precision': 0.9890713095664978, 'Train/mean recall': 0.9981178641319275, 'Train/mean hd95_metric': 0.6734651327133179} +Epoch [3141/4000] Validation [1/4] Loss: 0.38343 focal_loss 0.32127 dice_loss 0.06216 +Epoch [3141/4000] Validation [2/4] Loss: 0.39912 focal_loss 0.29181 dice_loss 0.10731 +Epoch [3141/4000] Validation [3/4] Loss: 0.50261 focal_loss 0.41092 dice_loss 0.09169 +Epoch [3141/4000] Validation [4/4] Loss: 0.29983 focal_loss 0.21742 dice_loss 0.08241 +Epoch [3141/4000] Validation metric {'Val/mean dice_metric': 0.9751035571098328, 'Val/mean miou_metric': 0.9610843658447266, 'Val/mean f1': 0.9766315221786499, 'Val/mean precision': 0.974542498588562, 'Val/mean recall': 0.9787296652793884, 'Val/mean hd95_metric': 4.6257829666137695} +Cheakpoint... +Epoch [3141/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751035571098328, 'Val/mean miou_metric': 0.9610843658447266, 'Val/mean f1': 0.9766315221786499, 'Val/mean precision': 0.974542498588562, 'Val/mean recall': 0.9787296652793884, 'Val/mean hd95_metric': 4.6257829666137695} +Epoch [3142/4000] Training [1/16] Loss: 0.00267 +Epoch [3142/4000] Training [2/16] Loss: 0.00293 +Epoch [3142/4000] Training [3/16] Loss: 0.00385 +Epoch [3142/4000] Training [4/16] Loss: 0.00251 +Epoch [3142/4000] Training [5/16] Loss: 0.00254 +Epoch [3142/4000] Training [6/16] Loss: 0.00404 +Epoch [3142/4000] Training [7/16] Loss: 0.00280 +Epoch [3142/4000] Training [8/16] Loss: 0.00380 +Epoch [3142/4000] Training [9/16] Loss: 0.00353 +Epoch [3142/4000] Training [10/16] Loss: 0.00279 +Epoch [3142/4000] Training [11/16] Loss: 0.00342 +Epoch [3142/4000] Training [12/16] Loss: 0.00278 +Epoch [3142/4000] Training [13/16] Loss: 0.00372 +Epoch [3142/4000] Training [14/16] Loss: 0.00306 +Epoch [3142/4000] Training [15/16] Loss: 0.00277 +Epoch [3142/4000] Training [16/16] Loss: 0.00347 +Epoch [3142/4000] Training metric {'Train/mean dice_metric': 0.9982128143310547, 'Train/mean miou_metric': 0.9961578249931335, 'Train/mean f1': 0.9932810664176941, 'Train/mean precision': 0.9887474775314331, 'Train/mean recall': 0.9978563785552979, 'Train/mean hd95_metric': 0.732254147529602} +Epoch [3142/4000] Validation [1/4] Loss: 0.41442 focal_loss 0.34850 dice_loss 0.06592 +Epoch [3142/4000] Validation [2/4] Loss: 0.85963 focal_loss 0.64792 dice_loss 0.21171 +Epoch [3142/4000] Validation [3/4] Loss: 0.53635 focal_loss 0.44104 dice_loss 0.09531 +Epoch [3142/4000] Validation [4/4] Loss: 0.36933 focal_loss 0.26747 dice_loss 0.10186 +Epoch [3142/4000] Validation metric {'Val/mean dice_metric': 0.9731059074401855, 'Val/mean miou_metric': 0.9585859179496765, 'Val/mean f1': 0.9753212332725525, 'Val/mean precision': 0.9720360636711121, 'Val/mean recall': 0.9786287546157837, 'Val/mean hd95_metric': 5.14042854309082} +Cheakpoint... +Epoch [3142/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731059074401855, 'Val/mean miou_metric': 0.9585859179496765, 'Val/mean f1': 0.9753212332725525, 'Val/mean precision': 0.9720360636711121, 'Val/mean recall': 0.9786287546157837, 'Val/mean hd95_metric': 5.14042854309082} +Epoch [3143/4000] Training [1/16] Loss: 0.00300 +Epoch [3143/4000] Training [2/16] Loss: 0.00368 +Epoch [3143/4000] Training [3/16] Loss: 0.00211 +Epoch [3143/4000] Training [4/16] Loss: 0.00271 +Epoch [3143/4000] Training [5/16] Loss: 0.00318 +Epoch [3143/4000] Training [6/16] Loss: 0.00206 +Epoch [3143/4000] Training [7/16] Loss: 0.00243 +Epoch [3143/4000] Training [8/16] Loss: 0.00264 +Epoch [3143/4000] Training [9/16] Loss: 0.00535 +Epoch [3143/4000] Training [10/16] Loss: 0.00306 +Epoch [3143/4000] Training [11/16] Loss: 0.00327 +Epoch [3143/4000] Training [12/16] Loss: 0.00276 +Epoch [3143/4000] Training [13/16] Loss: 0.00233 +Epoch [3143/4000] Training [14/16] Loss: 0.00394 +Epoch [3143/4000] Training [15/16] Loss: 0.00491 +Epoch [3143/4000] Training [16/16] Loss: 0.00295 +Epoch [3143/4000] Training metric {'Train/mean dice_metric': 0.9983839988708496, 'Train/mean miou_metric': 0.9965003728866577, 'Train/mean f1': 0.9935433268547058, 'Train/mean precision': 0.9890021085739136, 'Train/mean recall': 0.9981263875961304, 'Train/mean hd95_metric': 0.6823517680168152} +Epoch [3143/4000] Validation [1/4] Loss: 0.40704 focal_loss 0.34323 dice_loss 0.06382 +Epoch [3143/4000] Validation [2/4] Loss: 0.41577 focal_loss 0.30580 dice_loss 0.10997 +Epoch [3143/4000] Validation [3/4] Loss: 0.59875 focal_loss 0.49375 dice_loss 0.10500 +Epoch [3143/4000] Validation [4/4] Loss: 0.53879 focal_loss 0.40946 dice_loss 0.12933 +Epoch [3143/4000] Validation metric {'Val/mean dice_metric': 0.9740947484970093, 'Val/mean miou_metric': 0.959733784198761, 'Val/mean f1': 0.9761667847633362, 'Val/mean precision': 0.9730310440063477, 'Val/mean recall': 0.9793227910995483, 'Val/mean hd95_metric': 4.738579750061035} +Cheakpoint... +Epoch [3143/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740947484970093, 'Val/mean miou_metric': 0.959733784198761, 'Val/mean f1': 0.9761667847633362, 'Val/mean precision': 0.9730310440063477, 'Val/mean recall': 0.9793227910995483, 'Val/mean hd95_metric': 4.738579750061035} +Epoch [3144/4000] Training [1/16] Loss: 0.00297 +Epoch [3144/4000] Training [2/16] Loss: 0.00341 +Epoch [3144/4000] Training [3/16] Loss: 0.00365 +Epoch [3144/4000] Training [4/16] Loss: 0.00305 +Epoch [3144/4000] Training [5/16] Loss: 0.00333 +Epoch [3144/4000] Training [6/16] Loss: 0.00451 +Epoch [3144/4000] Training [7/16] Loss: 0.00374 +Epoch [3144/4000] Training [8/16] Loss: 0.00213 +Epoch [3144/4000] Training [9/16] Loss: 0.00247 +Epoch [3144/4000] Training [10/16] Loss: 0.00246 +Epoch [3144/4000] Training [11/16] Loss: 0.00287 +Epoch [3144/4000] Training [12/16] Loss: 0.00226 +Epoch [3144/4000] Training [13/16] Loss: 0.00315 +Epoch [3144/4000] Training [14/16] Loss: 0.00327 +Epoch [3144/4000] Training [15/16] Loss: 0.00263 +Epoch [3144/4000] Training [16/16] Loss: 0.00393 +Epoch [3144/4000] Training metric {'Train/mean dice_metric': 0.998171329498291, 'Train/mean miou_metric': 0.996066689491272, 'Train/mean f1': 0.9932170510292053, 'Train/mean precision': 0.9886147975921631, 'Train/mean recall': 0.9978623390197754, 'Train/mean hd95_metric': 0.7140190601348877} +Epoch [3144/4000] Validation [1/4] Loss: 0.41359 focal_loss 0.34823 dice_loss 0.06535 +Epoch [3144/4000] Validation [2/4] Loss: 0.98203 focal_loss 0.73165 dice_loss 0.25038 +Epoch [3144/4000] Validation [3/4] Loss: 0.53745 focal_loss 0.44093 dice_loss 0.09652 +Epoch [3144/4000] Validation [4/4] Loss: 0.30902 focal_loss 0.22399 dice_loss 0.08503 +Epoch [3144/4000] Validation metric {'Val/mean dice_metric': 0.9733484387397766, 'Val/mean miou_metric': 0.9586722254753113, 'Val/mean f1': 0.9751527309417725, 'Val/mean precision': 0.9726666808128357, 'Val/mean recall': 0.9776514172554016, 'Val/mean hd95_metric': 5.079531669616699} +Cheakpoint... +Epoch [3144/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733484387397766, 'Val/mean miou_metric': 0.9586722254753113, 'Val/mean f1': 0.9751527309417725, 'Val/mean precision': 0.9726666808128357, 'Val/mean recall': 0.9776514172554016, 'Val/mean hd95_metric': 5.079531669616699} +Epoch [3145/4000] Training [1/16] Loss: 0.00227 +Epoch [3145/4000] Training [2/16] Loss: 0.00217 +Epoch [3145/4000] Training [3/16] Loss: 0.00212 +Epoch [3145/4000] Training [4/16] Loss: 0.00332 +Epoch [3145/4000] Training [5/16] Loss: 0.00260 +Epoch [3145/4000] Training [6/16] Loss: 0.00452 +Epoch [3145/4000] Training [7/16] Loss: 0.00261 +Epoch [3145/4000] Training [8/16] Loss: 0.00520 +Epoch [3145/4000] Training [9/16] Loss: 0.00401 +Epoch [3145/4000] Training [10/16] Loss: 0.00293 +Epoch [3145/4000] Training [11/16] Loss: 0.00381 +Epoch [3145/4000] Training [12/16] Loss: 0.00254 +Epoch [3145/4000] Training [13/16] Loss: 0.00305 +Epoch [3145/4000] Training [14/16] Loss: 0.00414 +Epoch [3145/4000] Training [15/16] Loss: 0.00419 +Epoch [3145/4000] Training [16/16] Loss: 0.00180 +Epoch [3145/4000] Training metric {'Train/mean dice_metric': 0.9982553720474243, 'Train/mean miou_metric': 0.9962631464004517, 'Train/mean f1': 0.9934064149856567, 'Train/mean precision': 0.9888126254081726, 'Train/mean recall': 0.9980430006980896, 'Train/mean hd95_metric': 0.711011528968811} +Epoch [3145/4000] Validation [1/4] Loss: 0.39632 focal_loss 0.33089 dice_loss 0.06543 +Epoch [3145/4000] Validation [2/4] Loss: 0.49720 focal_loss 0.35521 dice_loss 0.14199 +Epoch [3145/4000] Validation [3/4] Loss: 0.52292 focal_loss 0.42922 dice_loss 0.09370 +Epoch [3145/4000] Validation [4/4] Loss: 0.54822 focal_loss 0.41556 dice_loss 0.13267 +Epoch [3145/4000] Validation metric {'Val/mean dice_metric': 0.974918007850647, 'Val/mean miou_metric': 0.9598039388656616, 'Val/mean f1': 0.9756731390953064, 'Val/mean precision': 0.9730613231658936, 'Val/mean recall': 0.9782991409301758, 'Val/mean hd95_metric': 5.216543197631836} +Cheakpoint... +Epoch [3145/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974918007850647, 'Val/mean miou_metric': 0.9598039388656616, 'Val/mean f1': 0.9756731390953064, 'Val/mean precision': 0.9730613231658936, 'Val/mean recall': 0.9782991409301758, 'Val/mean hd95_metric': 5.216543197631836} +Epoch [3146/4000] Training [1/16] Loss: 0.00208 +Epoch [3146/4000] Training [2/16] Loss: 0.00431 +Epoch [3146/4000] Training [3/16] Loss: 0.00269 +Epoch [3146/4000] Training [4/16] Loss: 0.00262 +Epoch [3146/4000] Training [5/16] Loss: 0.00365 +Epoch [3146/4000] Training [6/16] Loss: 0.00359 +Epoch [3146/4000] Training [7/16] Loss: 0.00260 +Epoch [3146/4000] Training [8/16] Loss: 0.00373 +Epoch [3146/4000] Training [9/16] Loss: 0.00302 +Epoch [3146/4000] Training [10/16] Loss: 0.00316 +Epoch [3146/4000] Training [11/16] Loss: 0.00209 +Epoch [3146/4000] Training [12/16] Loss: 0.00356 +Epoch [3146/4000] Training [13/16] Loss: 0.00475 +Epoch [3146/4000] Training [14/16] Loss: 0.00260 +Epoch [3146/4000] Training [15/16] Loss: 0.00457 +Epoch [3146/4000] Training [16/16] Loss: 0.00240 +Epoch [3146/4000] Training metric {'Train/mean dice_metric': 0.9982314109802246, 'Train/mean miou_metric': 0.9961949586868286, 'Train/mean f1': 0.993340790271759, 'Train/mean precision': 0.9887236952781677, 'Train/mean recall': 0.998001217842102, 'Train/mean hd95_metric': 0.714676022529602} +Epoch [3146/4000] Validation [1/4] Loss: 0.39898 focal_loss 0.33461 dice_loss 0.06437 +Epoch [3146/4000] Validation [2/4] Loss: 1.04193 focal_loss 0.77617 dice_loss 0.26576 +Epoch [3146/4000] Validation [3/4] Loss: 0.52054 focal_loss 0.42844 dice_loss 0.09210 +Epoch [3146/4000] Validation [4/4] Loss: 0.45852 focal_loss 0.33820 dice_loss 0.12031 +Epoch [3146/4000] Validation metric {'Val/mean dice_metric': 0.971767246723175, 'Val/mean miou_metric': 0.9572447538375854, 'Val/mean f1': 0.9750919938087463, 'Val/mean precision': 0.9731698632240295, 'Val/mean recall': 0.9770217537879944, 'Val/mean hd95_metric': 5.0588555335998535} +Cheakpoint... +Epoch [3146/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971767246723175, 'Val/mean miou_metric': 0.9572447538375854, 'Val/mean f1': 0.9750919938087463, 'Val/mean precision': 0.9731698632240295, 'Val/mean recall': 0.9770217537879944, 'Val/mean hd95_metric': 5.0588555335998535} +Epoch [3147/4000] Training [1/16] Loss: 0.00341 +Epoch [3147/4000] Training [2/16] Loss: 0.00221 +Epoch [3147/4000] Training [3/16] Loss: 0.00360 +Epoch [3147/4000] Training [4/16] Loss: 0.00194 +Epoch [3147/4000] Training [5/16] Loss: 0.00249 +Epoch [3147/4000] Training [6/16] Loss: 0.00343 +Epoch [3147/4000] Training [7/16] Loss: 0.00440 +Epoch [3147/4000] Training [8/16] Loss: 0.00395 +Epoch [3147/4000] Training [9/16] Loss: 0.00220 +Epoch [3147/4000] Training [10/16] Loss: 0.00431 +Epoch [3147/4000] Training [11/16] Loss: 0.00386 +Epoch [3147/4000] Training [12/16] Loss: 0.00285 +Epoch [3147/4000] Training [13/16] Loss: 0.00317 +Epoch [3147/4000] Training [14/16] Loss: 0.00219 +Epoch [3147/4000] Training [15/16] Loss: 0.00239 +Epoch [3147/4000] Training [16/16] Loss: 0.00328 +Epoch [3147/4000] Training metric {'Train/mean dice_metric': 0.9983009696006775, 'Train/mean miou_metric': 0.9963258504867554, 'Train/mean f1': 0.9933620691299438, 'Train/mean precision': 0.9887214303016663, 'Train/mean recall': 0.9980465173721313, 'Train/mean hd95_metric': 0.7348908185958862} +Epoch [3147/4000] Validation [1/4] Loss: 0.38617 focal_loss 0.32078 dice_loss 0.06538 +Epoch [3147/4000] Validation [2/4] Loss: 0.44453 focal_loss 0.32828 dice_loss 0.11625 +Epoch [3147/4000] Validation [3/4] Loss: 0.27573 focal_loss 0.20572 dice_loss 0.07002 +Epoch [3147/4000] Validation [4/4] Loss: 0.30447 focal_loss 0.22189 dice_loss 0.08258 +Epoch [3147/4000] Validation metric {'Val/mean dice_metric': 0.9743965864181519, 'Val/mean miou_metric': 0.960285484790802, 'Val/mean f1': 0.9760568141937256, 'Val/mean precision': 0.9737097024917603, 'Val/mean recall': 0.9784153699874878, 'Val/mean hd95_metric': 5.315086364746094} +Cheakpoint... +Epoch [3147/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743965864181519, 'Val/mean miou_metric': 0.960285484790802, 'Val/mean f1': 0.9760568141937256, 'Val/mean precision': 0.9737097024917603, 'Val/mean recall': 0.9784153699874878, 'Val/mean hd95_metric': 5.315086364746094} +Epoch [3148/4000] Training [1/16] Loss: 0.00341 +Epoch [3148/4000] Training [2/16] Loss: 0.00354 +Epoch [3148/4000] Training [3/16] Loss: 0.00228 +Epoch [3148/4000] Training [4/16] Loss: 0.00365 +Epoch [3148/4000] Training [5/16] Loss: 0.00272 +Epoch [3148/4000] Training [6/16] Loss: 0.00277 +Epoch [3148/4000] Training [7/16] Loss: 0.00278 +Epoch [3148/4000] Training [8/16] Loss: 0.00284 +Epoch [3148/4000] Training [9/16] Loss: 0.00291 +Epoch [3148/4000] Training [10/16] Loss: 0.00220 +Epoch [3148/4000] Training [11/16] Loss: 0.00344 +Epoch [3148/4000] Training [12/16] Loss: 0.00204 +Epoch [3148/4000] Training [13/16] Loss: 0.00338 +Epoch [3148/4000] Training [14/16] Loss: 0.00310 +Epoch [3148/4000] Training [15/16] Loss: 0.00309 +Epoch [3148/4000] Training [16/16] Loss: 0.00255 +Epoch [3148/4000] Training metric {'Train/mean dice_metric': 0.998413622379303, 'Train/mean miou_metric': 0.9965254068374634, 'Train/mean f1': 0.9929952025413513, 'Train/mean precision': 0.9880710244178772, 'Train/mean recall': 0.9979687333106995, 'Train/mean hd95_metric': 0.71262526512146} +Epoch [3148/4000] Validation [1/4] Loss: 0.38348 focal_loss 0.31667 dice_loss 0.06681 +Epoch [3148/4000] Validation [2/4] Loss: 0.41337 focal_loss 0.30323 dice_loss 0.11014 +Epoch [3148/4000] Validation [3/4] Loss: 0.25228 focal_loss 0.19024 dice_loss 0.06204 +Epoch [3148/4000] Validation [4/4] Loss: 0.31261 focal_loss 0.22233 dice_loss 0.09028 +Epoch [3148/4000] Validation metric {'Val/mean dice_metric': 0.974570095539093, 'Val/mean miou_metric': 0.9605962634086609, 'Val/mean f1': 0.9760263562202454, 'Val/mean precision': 0.9738878011703491, 'Val/mean recall': 0.9781742095947266, 'Val/mean hd95_metric': 4.86517333984375} +Cheakpoint... +Epoch [3148/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974570095539093, 'Val/mean miou_metric': 0.9605962634086609, 'Val/mean f1': 0.9760263562202454, 'Val/mean precision': 0.9738878011703491, 'Val/mean recall': 0.9781742095947266, 'Val/mean hd95_metric': 4.86517333984375} +Epoch [3149/4000] Training [1/16] Loss: 0.00189 +Epoch [3149/4000] Training [2/16] Loss: 0.00225 +Epoch [3149/4000] Training [3/16] Loss: 0.00231 +Epoch [3149/4000] Training [4/16] Loss: 0.00269 +Epoch [3149/4000] Training [5/16] Loss: 0.00386 +Epoch [3149/4000] Training [6/16] Loss: 0.00186 +Epoch [3149/4000] Training [7/16] Loss: 0.00221 +Epoch [3149/4000] Training [8/16] Loss: 0.00236 +Epoch [3149/4000] Training [9/16] Loss: 0.00248 +Epoch [3149/4000] Training [10/16] Loss: 0.00402 +Epoch [3149/4000] Training [11/16] Loss: 0.00346 +Epoch [3149/4000] Training [12/16] Loss: 0.00247 +Epoch [3149/4000] Training [13/16] Loss: 0.00297 +Epoch [3149/4000] Training [14/16] Loss: 0.00299 +Epoch [3149/4000] Training [15/16] Loss: 0.00364 +Epoch [3149/4000] Training [16/16] Loss: 0.00311 +Epoch [3149/4000] Training metric {'Train/mean dice_metric': 0.9985101222991943, 'Train/mean miou_metric': 0.9967213273048401, 'Train/mean f1': 0.9932923913002014, 'Train/mean precision': 0.9884437322616577, 'Train/mean recall': 0.9981889128684998, 'Train/mean hd95_metric': 0.6701170802116394} +Epoch [3149/4000] Validation [1/4] Loss: 0.43251 focal_loss 0.36417 dice_loss 0.06834 +Epoch [3149/4000] Validation [2/4] Loss: 0.39918 focal_loss 0.29196 dice_loss 0.10721 +Epoch [3149/4000] Validation [3/4] Loss: 0.53072 focal_loss 0.43513 dice_loss 0.09560 +Epoch [3149/4000] Validation [4/4] Loss: 0.31532 focal_loss 0.20689 dice_loss 0.10843 +Epoch [3149/4000] Validation metric {'Val/mean dice_metric': 0.9758630990982056, 'Val/mean miou_metric': 0.9612828493118286, 'Val/mean f1': 0.9764220118522644, 'Val/mean precision': 0.9732112884521484, 'Val/mean recall': 0.9796541333198547, 'Val/mean hd95_metric': 4.619287490844727} +Cheakpoint... +Epoch [3149/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758630990982056, 'Val/mean miou_metric': 0.9612828493118286, 'Val/mean f1': 0.9764220118522644, 'Val/mean precision': 0.9732112884521484, 'Val/mean recall': 0.9796541333198547, 'Val/mean hd95_metric': 4.619287490844727} +Epoch [3150/4000] Training [1/16] Loss: 0.00305 +Epoch [3150/4000] Training [2/16] Loss: 0.00341 +Epoch [3150/4000] Training [3/16] Loss: 0.00273 +Epoch [3150/4000] Training [4/16] Loss: 0.00324 +Epoch [3150/4000] Training [5/16] Loss: 0.00250 +Epoch [3150/4000] Training [6/16] Loss: 0.00423 +Epoch [3150/4000] Training [7/16] Loss: 0.00338 +Epoch [3150/4000] Training [8/16] Loss: 0.00235 +Epoch [3150/4000] Training [9/16] Loss: 0.00290 +Epoch [3150/4000] Training [10/16] Loss: 0.00325 +Epoch [3150/4000] Training [11/16] Loss: 0.00249 +Epoch [3150/4000] Training [12/16] Loss: 0.00275 +Epoch [3150/4000] Training [13/16] Loss: 0.00237 +Epoch [3150/4000] Training [14/16] Loss: 0.00253 +Epoch [3150/4000] Training [15/16] Loss: 0.00263 +Epoch [3150/4000] Training [16/16] Loss: 0.00211 +Epoch [3150/4000] Training metric {'Train/mean dice_metric': 0.9984943270683289, 'Train/mean miou_metric': 0.9966998100280762, 'Train/mean f1': 0.9934527277946472, 'Train/mean precision': 0.9887694716453552, 'Train/mean recall': 0.9981805682182312, 'Train/mean hd95_metric': 0.6974687576293945} +Epoch [3150/4000] Validation [1/4] Loss: 0.41745 focal_loss 0.35140 dice_loss 0.06605 +Epoch [3150/4000] Validation [2/4] Loss: 0.84438 focal_loss 0.63475 dice_loss 0.20964 +Epoch [3150/4000] Validation [3/4] Loss: 0.52570 focal_loss 0.43091 dice_loss 0.09479 +Epoch [3150/4000] Validation [4/4] Loss: 0.30369 focal_loss 0.21609 dice_loss 0.08760 +Epoch [3150/4000] Validation metric {'Val/mean dice_metric': 0.9728090167045593, 'Val/mean miou_metric': 0.9585155248641968, 'Val/mean f1': 0.9754074811935425, 'Val/mean precision': 0.9730372428894043, 'Val/mean recall': 0.9777894616127014, 'Val/mean hd95_metric': 4.954162120819092} +Cheakpoint... +Epoch [3150/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728090167045593, 'Val/mean miou_metric': 0.9585155248641968, 'Val/mean f1': 0.9754074811935425, 'Val/mean precision': 0.9730372428894043, 'Val/mean recall': 0.9777894616127014, 'Val/mean hd95_metric': 4.954162120819092} +Epoch [3151/4000] Training [1/16] Loss: 0.00276 +Epoch [3151/4000] Training [2/16] Loss: 0.00375 +Epoch [3151/4000] Training [3/16] Loss: 0.00560 +Epoch [3151/4000] Training [4/16] Loss: 0.00352 +Epoch [3151/4000] Training [5/16] Loss: 0.00477 +Epoch [3151/4000] Training [6/16] Loss: 0.00339 +Epoch [3151/4000] Training [7/16] Loss: 0.00313 +Epoch [3151/4000] Training [8/16] Loss: 0.00260 +Epoch [3151/4000] Training [9/16] Loss: 0.00199 +Epoch [3151/4000] Training [10/16] Loss: 0.00298 +Epoch [3151/4000] Training [11/16] Loss: 0.00477 +Epoch [3151/4000] Training [12/16] Loss: 0.00254 +Epoch [3151/4000] Training [13/16] Loss: 0.00303 +Epoch [3151/4000] Training [14/16] Loss: 0.00335 +Epoch [3151/4000] Training [15/16] Loss: 0.00284 +Epoch [3151/4000] Training [16/16] Loss: 0.00234 +Epoch [3151/4000] Training metric {'Train/mean dice_metric': 0.9979807138442993, 'Train/mean miou_metric': 0.995710015296936, 'Train/mean f1': 0.9930387735366821, 'Train/mean precision': 0.9883639812469482, 'Train/mean recall': 0.9977580308914185, 'Train/mean hd95_metric': 0.790754497051239} +Epoch [3151/4000] Validation [1/4] Loss: 0.38187 focal_loss 0.31723 dice_loss 0.06464 +Epoch [3151/4000] Validation [2/4] Loss: 0.43372 focal_loss 0.32046 dice_loss 0.11326 +Epoch [3151/4000] Validation [3/4] Loss: 0.54595 focal_loss 0.44648 dice_loss 0.09947 +Epoch [3151/4000] Validation [4/4] Loss: 0.26296 focal_loss 0.18294 dice_loss 0.08002 +Epoch [3151/4000] Validation metric {'Val/mean dice_metric': 0.9738844037055969, 'Val/mean miou_metric': 0.9594835042953491, 'Val/mean f1': 0.9762981534004211, 'Val/mean precision': 0.9738447666168213, 'Val/mean recall': 0.9787639379501343, 'Val/mean hd95_metric': 5.02987003326416} +Cheakpoint... +Epoch [3151/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738844037055969, 'Val/mean miou_metric': 0.9594835042953491, 'Val/mean f1': 0.9762981534004211, 'Val/mean precision': 0.9738447666168213, 'Val/mean recall': 0.9787639379501343, 'Val/mean hd95_metric': 5.02987003326416} +Epoch [3152/4000] Training [1/16] Loss: 0.00297 +Epoch [3152/4000] Training [2/16] Loss: 0.00232 +Epoch [3152/4000] Training [3/16] Loss: 0.00241 +Epoch [3152/4000] Training [4/16] Loss: 0.00349 +Epoch [3152/4000] Training [5/16] Loss: 0.00249 +Epoch [3152/4000] Training [6/16] Loss: 0.00246 +Epoch [3152/4000] Training [7/16] Loss: 0.00284 +Epoch [3152/4000] Training [8/16] Loss: 0.00278 +Epoch [3152/4000] Training [9/16] Loss: 0.00304 +Epoch [3152/4000] Training [10/16] Loss: 0.00321 +Epoch [3152/4000] Training [11/16] Loss: 0.00262 +Epoch [3152/4000] Training [12/16] Loss: 0.00818 +Epoch [3152/4000] Training [13/16] Loss: 0.00272 +Epoch [3152/4000] Training [14/16] Loss: 0.00233 +Epoch [3152/4000] Training [15/16] Loss: 0.00242 +Epoch [3152/4000] Training [16/16] Loss: 0.00251 +Epoch [3152/4000] Training metric {'Train/mean dice_metric': 0.9983867406845093, 'Train/mean miou_metric': 0.9964695572853088, 'Train/mean f1': 0.9928064346313477, 'Train/mean precision': 0.9877039790153503, 'Train/mean recall': 0.9979618787765503, 'Train/mean hd95_metric': 0.7236740589141846} +Epoch [3152/4000] Validation [1/4] Loss: 0.36917 focal_loss 0.30795 dice_loss 0.06123 +Epoch [3152/4000] Validation [2/4] Loss: 0.63541 focal_loss 0.47566 dice_loss 0.15975 +Epoch [3152/4000] Validation [3/4] Loss: 0.27936 focal_loss 0.21554 dice_loss 0.06382 +Epoch [3152/4000] Validation [4/4] Loss: 0.28857 focal_loss 0.20690 dice_loss 0.08167 +Epoch [3152/4000] Validation metric {'Val/mean dice_metric': 0.9732553362846375, 'Val/mean miou_metric': 0.9594491720199585, 'Val/mean f1': 0.9757238626480103, 'Val/mean precision': 0.9728641510009766, 'Val/mean recall': 0.9786005616188049, 'Val/mean hd95_metric': 5.148471355438232} +Cheakpoint... +Epoch [3152/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732553362846375, 'Val/mean miou_metric': 0.9594491720199585, 'Val/mean f1': 0.9757238626480103, 'Val/mean precision': 0.9728641510009766, 'Val/mean recall': 0.9786005616188049, 'Val/mean hd95_metric': 5.148471355438232} +Epoch [3153/4000] Training [1/16] Loss: 0.00327 +Epoch [3153/4000] Training [2/16] Loss: 0.00523 +Epoch [3153/4000] Training [3/16] Loss: 0.00184 +Epoch [3153/4000] Training [4/16] Loss: 0.00272 +Epoch [3153/4000] Training [5/16] Loss: 0.00372 +Epoch [3153/4000] Training [6/16] Loss: 0.00343 +Epoch [3153/4000] Training [7/16] Loss: 0.00505 +Epoch [3153/4000] Training [8/16] Loss: 0.00289 +Epoch [3153/4000] Training [9/16] Loss: 0.00200 +Epoch [3153/4000] Training [10/16] Loss: 0.00235 +Epoch [3153/4000] Training [11/16] Loss: 0.00366 +Epoch [3153/4000] Training [12/16] Loss: 0.00222 +Epoch [3153/4000] Training [13/16] Loss: 0.00260 +Epoch [3153/4000] Training [14/16] Loss: 0.00330 +Epoch [3153/4000] Training [15/16] Loss: 0.00209 +Epoch [3153/4000] Training [16/16] Loss: 0.00245 +Epoch [3153/4000] Training metric {'Train/mean dice_metric': 0.9983341693878174, 'Train/mean miou_metric': 0.9963980913162231, 'Train/mean f1': 0.9933931827545166, 'Train/mean precision': 0.9887939691543579, 'Train/mean recall': 0.9980354309082031, 'Train/mean hd95_metric': 0.6950470209121704} +Epoch [3153/4000] Validation [1/4] Loss: 0.37681 focal_loss 0.31173 dice_loss 0.06508 +Epoch [3153/4000] Validation [2/4] Loss: 0.86354 focal_loss 0.65385 dice_loss 0.20969 +Epoch [3153/4000] Validation [3/4] Loss: 0.51992 focal_loss 0.42322 dice_loss 0.09670 +Epoch [3153/4000] Validation [4/4] Loss: 0.30947 focal_loss 0.22518 dice_loss 0.08429 +Epoch [3153/4000] Validation metric {'Val/mean dice_metric': 0.9740961194038391, 'Val/mean miou_metric': 0.9601327776908875, 'Val/mean f1': 0.9762386083602905, 'Val/mean precision': 0.9733884334564209, 'Val/mean recall': 0.979105532169342, 'Val/mean hd95_metric': 5.215694904327393} +Cheakpoint... +Epoch [3153/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740961194038391, 'Val/mean miou_metric': 0.9601327776908875, 'Val/mean f1': 0.9762386083602905, 'Val/mean precision': 0.9733884334564209, 'Val/mean recall': 0.979105532169342, 'Val/mean hd95_metric': 5.215694904327393} +Epoch [3154/4000] Training [1/16] Loss: 0.00255 +Epoch [3154/4000] Training [2/16] Loss: 0.00176 +Epoch [3154/4000] Training [3/16] Loss: 0.00251 +Epoch [3154/4000] Training [4/16] Loss: 0.00305 +Epoch [3154/4000] Training [5/16] Loss: 0.00639 +Epoch [3154/4000] Training [6/16] Loss: 0.00186 +Epoch [3154/4000] Training [7/16] Loss: 0.00311 +Epoch [3154/4000] Training [8/16] Loss: 0.00590 +Epoch [3154/4000] Training [9/16] Loss: 0.00296 +Epoch [3154/4000] Training [10/16] Loss: 0.00215 +Epoch [3154/4000] Training [11/16] Loss: 0.00231 +Epoch [3154/4000] Training [12/16] Loss: 0.00228 +Epoch [3154/4000] Training [13/16] Loss: 0.00421 +Epoch [3154/4000] Training [14/16] Loss: 0.00265 +Epoch [3154/4000] Training [15/16] Loss: 0.00266 +Epoch [3154/4000] Training [16/16] Loss: 0.00217 +Epoch [3154/4000] Training metric {'Train/mean dice_metric': 0.9983357191085815, 'Train/mean miou_metric': 0.9964022636413574, 'Train/mean f1': 0.9933861494064331, 'Train/mean precision': 0.9887529611587524, 'Train/mean recall': 0.9980630278587341, 'Train/mean hd95_metric': 0.6752615571022034} +Epoch [3154/4000] Validation [1/4] Loss: 0.33257 focal_loss 0.27072 dice_loss 0.06185 +Epoch [3154/4000] Validation [2/4] Loss: 0.93664 focal_loss 0.73701 dice_loss 0.19963 +Epoch [3154/4000] Validation [3/4] Loss: 0.49092 focal_loss 0.40087 dice_loss 0.09005 +Epoch [3154/4000] Validation [4/4] Loss: 0.43471 focal_loss 0.32104 dice_loss 0.11367 +Epoch [3154/4000] Validation metric {'Val/mean dice_metric': 0.9718664288520813, 'Val/mean miou_metric': 0.9581655263900757, 'Val/mean f1': 0.9759422540664673, 'Val/mean precision': 0.9739603400230408, 'Val/mean recall': 0.9779322743415833, 'Val/mean hd95_metric': 4.79172945022583} +Cheakpoint... +Epoch [3154/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718664288520813, 'Val/mean miou_metric': 0.9581655263900757, 'Val/mean f1': 0.9759422540664673, 'Val/mean precision': 0.9739603400230408, 'Val/mean recall': 0.9779322743415833, 'Val/mean hd95_metric': 4.79172945022583} +Epoch [3155/4000] Training [1/16] Loss: 0.00395 +Epoch [3155/4000] Training [2/16] Loss: 0.00437 +Epoch [3155/4000] Training [3/16] Loss: 0.00447 +Epoch [3155/4000] Training [4/16] Loss: 0.00360 +Epoch [3155/4000] Training [5/16] Loss: 0.00305 +Epoch [3155/4000] Training [6/16] Loss: 0.00488 +Epoch [3155/4000] Training [7/16] Loss: 0.00297 +Epoch [3155/4000] Training [8/16] Loss: 0.00310 +Epoch [3155/4000] Training [9/16] Loss: 0.00278 +Epoch [3155/4000] Training [10/16] Loss: 0.00304 +Epoch [3155/4000] Training [11/16] Loss: 0.00251 +Epoch [3155/4000] Training [12/16] Loss: 0.00209 +Epoch [3155/4000] Training [13/16] Loss: 0.00383 +Epoch [3155/4000] Training [14/16] Loss: 0.00272 +Epoch [3155/4000] Training [15/16] Loss: 0.00415 +Epoch [3155/4000] Training [16/16] Loss: 0.00323 +Epoch [3155/4000] Training metric {'Train/mean dice_metric': 0.9983348846435547, 'Train/mean miou_metric': 0.9963414669036865, 'Train/mean f1': 0.9921559691429138, 'Train/mean precision': 0.9864599108695984, 'Train/mean recall': 0.9979183673858643, 'Train/mean hd95_metric': 0.6944612264633179} +Epoch [3155/4000] Validation [1/4] Loss: 0.36558 focal_loss 0.30456 dice_loss 0.06102 +Epoch [3155/4000] Validation [2/4] Loss: 0.93955 focal_loss 0.73740 dice_loss 0.20214 +Epoch [3155/4000] Validation [3/4] Loss: 0.52666 focal_loss 0.43267 dice_loss 0.09399 +Epoch [3155/4000] Validation [4/4] Loss: 0.31094 focal_loss 0.21856 dice_loss 0.09238 +Epoch [3155/4000] Validation metric {'Val/mean dice_metric': 0.9714509844779968, 'Val/mean miou_metric': 0.9579537510871887, 'Val/mean f1': 0.9747815728187561, 'Val/mean precision': 0.972438633441925, 'Val/mean recall': 0.9771358370780945, 'Val/mean hd95_metric': 5.044961452484131} +Cheakpoint... +Epoch [3155/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714509844779968, 'Val/mean miou_metric': 0.9579537510871887, 'Val/mean f1': 0.9747815728187561, 'Val/mean precision': 0.972438633441925, 'Val/mean recall': 0.9771358370780945, 'Val/mean hd95_metric': 5.044961452484131} +Epoch [3156/4000] Training [1/16] Loss: 0.00229 +Epoch [3156/4000] Training [2/16] Loss: 0.00241 +Epoch [3156/4000] Training [3/16] Loss: 0.00302 +Epoch [3156/4000] Training [4/16] Loss: 0.00312 +Epoch [3156/4000] Training [5/16] Loss: 0.00241 +Epoch [3156/4000] Training [6/16] Loss: 0.00408 +Epoch [3156/4000] Training [7/16] Loss: 0.00348 +Epoch [3156/4000] Training [8/16] Loss: 0.00278 +Epoch [3156/4000] Training [9/16] Loss: 0.00265 +Epoch [3156/4000] Training [10/16] Loss: 0.00288 +Epoch [3156/4000] Training [11/16] Loss: 0.00283 +Epoch [3156/4000] Training [12/16] Loss: 0.00253 +Epoch [3156/4000] Training [13/16] Loss: 0.00245 +Epoch [3156/4000] Training [14/16] Loss: 0.00381 +Epoch [3156/4000] Training [15/16] Loss: 0.00242 +Epoch [3156/4000] Training [16/16] Loss: 0.00325 +Epoch [3156/4000] Training metric {'Train/mean dice_metric': 0.9983862638473511, 'Train/mean miou_metric': 0.9964949488639832, 'Train/mean f1': 0.9934064745903015, 'Train/mean precision': 0.9887897968292236, 'Train/mean recall': 0.9980664849281311, 'Train/mean hd95_metric': 0.7143553495407104} +Epoch [3156/4000] Validation [1/4] Loss: 0.37621 focal_loss 0.31208 dice_loss 0.06413 +Epoch [3156/4000] Validation [2/4] Loss: 0.50793 focal_loss 0.35795 dice_loss 0.14998 +Epoch [3156/4000] Validation [3/4] Loss: 0.51346 focal_loss 0.42156 dice_loss 0.09190 +Epoch [3156/4000] Validation [4/4] Loss: 0.33362 focal_loss 0.24064 dice_loss 0.09298 +Epoch [3156/4000] Validation metric {'Val/mean dice_metric': 0.9737321734428406, 'Val/mean miou_metric': 0.9593799710273743, 'Val/mean f1': 0.9759474992752075, 'Val/mean precision': 0.9735628366470337, 'Val/mean recall': 0.9783439636230469, 'Val/mean hd95_metric': 4.784804821014404} +Cheakpoint... +Epoch [3156/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737321734428406, 'Val/mean miou_metric': 0.9593799710273743, 'Val/mean f1': 0.9759474992752075, 'Val/mean precision': 0.9735628366470337, 'Val/mean recall': 0.9783439636230469, 'Val/mean hd95_metric': 4.784804821014404} +Epoch [3157/4000] Training [1/16] Loss: 0.00333 +Epoch [3157/4000] Training [2/16] Loss: 0.00360 +Epoch [3157/4000] Training [3/16] Loss: 0.00253 +Epoch [3157/4000] Training [4/16] Loss: 0.00320 +Epoch [3157/4000] Training [5/16] Loss: 0.00272 +Epoch [3157/4000] Training [6/16] Loss: 0.00303 +Epoch [3157/4000] Training [7/16] Loss: 0.00362 +Epoch [3157/4000] Training [8/16] Loss: 0.00335 +Epoch [3157/4000] Training [9/16] Loss: 0.00294 +Epoch [3157/4000] Training [10/16] Loss: 0.00310 +Epoch [3157/4000] Training [11/16] Loss: 0.00198 +Epoch [3157/4000] Training [12/16] Loss: 0.00321 +Epoch [3157/4000] Training [13/16] Loss: 0.00319 +Epoch [3157/4000] Training [14/16] Loss: 0.00275 +Epoch [3157/4000] Training [15/16] Loss: 0.00225 +Epoch [3157/4000] Training [16/16] Loss: 0.00322 +Epoch [3157/4000] Training metric {'Train/mean dice_metric': 0.9982603192329407, 'Train/mean miou_metric': 0.9962321519851685, 'Train/mean f1': 0.9931142330169678, 'Train/mean precision': 0.9883391857147217, 'Train/mean recall': 0.9979355931282043, 'Train/mean hd95_metric': 0.7342073321342468} +Epoch [3157/4000] Validation [1/4] Loss: 0.37519 focal_loss 0.30736 dice_loss 0.06784 +Epoch [3157/4000] Validation [2/4] Loss: 0.38017 focal_loss 0.27780 dice_loss 0.10237 +Epoch [3157/4000] Validation [3/4] Loss: 0.53412 focal_loss 0.44100 dice_loss 0.09312 +Epoch [3157/4000] Validation [4/4] Loss: 0.30828 focal_loss 0.22100 dice_loss 0.08728 +Epoch [3157/4000] Validation metric {'Val/mean dice_metric': 0.9733829498291016, 'Val/mean miou_metric': 0.9590145349502563, 'Val/mean f1': 0.975560188293457, 'Val/mean precision': 0.9730432033538818, 'Val/mean recall': 0.9780903458595276, 'Val/mean hd95_metric': 5.065062522888184} +Cheakpoint... +Epoch [3157/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733829498291016, 'Val/mean miou_metric': 0.9590145349502563, 'Val/mean f1': 0.975560188293457, 'Val/mean precision': 0.9730432033538818, 'Val/mean recall': 0.9780903458595276, 'Val/mean hd95_metric': 5.065062522888184} +Epoch [3158/4000] Training [1/16] Loss: 0.00361 +Epoch [3158/4000] Training [2/16] Loss: 0.00215 +Epoch [3158/4000] Training [3/16] Loss: 0.00219 +Epoch [3158/4000] Training [4/16] Loss: 0.00297 +Epoch [3158/4000] Training [5/16] Loss: 0.00249 +Epoch [3158/4000] Training [6/16] Loss: 0.00199 +Epoch [3158/4000] Training [7/16] Loss: 0.00310 +Epoch [3158/4000] Training [8/16] Loss: 0.00276 +Epoch [3158/4000] Training [9/16] Loss: 0.00227 +Epoch [3158/4000] Training [10/16] Loss: 0.00255 +Epoch [3158/4000] Training [11/16] Loss: 0.00213 +Epoch [3158/4000] Training [12/16] Loss: 0.00332 +Epoch [3158/4000] Training [13/16] Loss: 0.00336 +Epoch [3158/4000] Training [14/16] Loss: 0.00222 +Epoch [3158/4000] Training [15/16] Loss: 0.00255 +Epoch [3158/4000] Training [16/16] Loss: 0.00237 +Epoch [3158/4000] Training metric {'Train/mean dice_metric': 0.9984923601150513, 'Train/mean miou_metric': 0.9966987371444702, 'Train/mean f1': 0.9935407042503357, 'Train/mean precision': 0.9889946579933167, 'Train/mean recall': 0.9981287717819214, 'Train/mean hd95_metric': 0.6851837038993835} +Epoch [3158/4000] Validation [1/4] Loss: 0.39932 focal_loss 0.33387 dice_loss 0.06545 +Epoch [3158/4000] Validation [2/4] Loss: 0.84986 focal_loss 0.64321 dice_loss 0.20665 +Epoch [3158/4000] Validation [3/4] Loss: 0.47968 focal_loss 0.38176 dice_loss 0.09792 +Epoch [3158/4000] Validation [4/4] Loss: 0.30653 focal_loss 0.22285 dice_loss 0.08368 +Epoch [3158/4000] Validation metric {'Val/mean dice_metric': 0.9729868769645691, 'Val/mean miou_metric': 0.9589826464653015, 'Val/mean f1': 0.9761186242103577, 'Val/mean precision': 0.9738485813140869, 'Val/mean recall': 0.9783992767333984, 'Val/mean hd95_metric': 4.712468147277832} +Cheakpoint... +Epoch [3158/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729868769645691, 'Val/mean miou_metric': 0.9589826464653015, 'Val/mean f1': 0.9761186242103577, 'Val/mean precision': 0.9738485813140869, 'Val/mean recall': 0.9783992767333984, 'Val/mean hd95_metric': 4.712468147277832} +Epoch [3159/4000] Training [1/16] Loss: 0.00408 +Epoch [3159/4000] Training [2/16] Loss: 0.00239 +Epoch [3159/4000] Training [3/16] Loss: 0.00238 +Epoch [3159/4000] Training [4/16] Loss: 0.00246 +Epoch [3159/4000] Training [5/16] Loss: 0.00352 +Epoch [3159/4000] Training [6/16] Loss: 0.00351 +Epoch [3159/4000] Training [7/16] Loss: 0.00261 +Epoch [3159/4000] Training [8/16] Loss: 0.00257 +Epoch [3159/4000] Training [9/16] Loss: 0.00336 +Epoch [3159/4000] Training [10/16] Loss: 0.00347 +Epoch [3159/4000] Training [11/16] Loss: 0.00403 +Epoch [3159/4000] Training [12/16] Loss: 0.00256 +Epoch [3159/4000] Training [13/16] Loss: 0.00297 +Epoch [3159/4000] Training [14/16] Loss: 0.00247 +Epoch [3159/4000] Training [15/16] Loss: 0.00274 +Epoch [3159/4000] Training [16/16] Loss: 0.00225 +Epoch [3159/4000] Training metric {'Train/mean dice_metric': 0.9983524084091187, 'Train/mean miou_metric': 0.996429443359375, 'Train/mean f1': 0.9934722781181335, 'Train/mean precision': 0.9888815879821777, 'Train/mean recall': 0.9981057047843933, 'Train/mean hd95_metric': 0.6870391964912415} +Epoch [3159/4000] Validation [1/4] Loss: 0.38275 focal_loss 0.31931 dice_loss 0.06344 +Epoch [3159/4000] Validation [2/4] Loss: 1.01570 focal_loss 0.75724 dice_loss 0.25847 +Epoch [3159/4000] Validation [3/4] Loss: 0.51995 focal_loss 0.42402 dice_loss 0.09593 +Epoch [3159/4000] Validation [4/4] Loss: 0.36134 focal_loss 0.25830 dice_loss 0.10304 +Epoch [3159/4000] Validation metric {'Val/mean dice_metric': 0.9727081060409546, 'Val/mean miou_metric': 0.9583190679550171, 'Val/mean f1': 0.9754676222801208, 'Val/mean precision': 0.9736112952232361, 'Val/mean recall': 0.9773312211036682, 'Val/mean hd95_metric': 4.942044734954834} +Cheakpoint... +Epoch [3159/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727081060409546, 'Val/mean miou_metric': 0.9583190679550171, 'Val/mean f1': 0.9754676222801208, 'Val/mean precision': 0.9736112952232361, 'Val/mean recall': 0.9773312211036682, 'Val/mean hd95_metric': 4.942044734954834} +Epoch [3160/4000] Training [1/16] Loss: 0.00306 +Epoch [3160/4000] Training [2/16] Loss: 0.00220 +Epoch [3160/4000] Training [3/16] Loss: 0.00246 +Epoch [3160/4000] Training [4/16] Loss: 0.00425 +Epoch [3160/4000] Training [5/16] Loss: 0.00246 +Epoch [3160/4000] Training [6/16] Loss: 0.00376 +Epoch [3160/4000] Training [7/16] Loss: 0.00266 +Epoch [3160/4000] Training [8/16] Loss: 0.00231 +Epoch [3160/4000] Training [9/16] Loss: 0.00414 +Epoch [3160/4000] Training [10/16] Loss: 0.00321 +Epoch [3160/4000] Training [11/16] Loss: 0.00373 +Epoch [3160/4000] Training [12/16] Loss: 0.00312 +Epoch [3160/4000] Training [13/16] Loss: 0.00319 +Epoch [3160/4000] Training [14/16] Loss: 0.00295 +Epoch [3160/4000] Training [15/16] Loss: 0.00193 +Epoch [3160/4000] Training [16/16] Loss: 0.00326 +Epoch [3160/4000] Training metric {'Train/mean dice_metric': 0.9984489679336548, 'Train/mean miou_metric': 0.9966017603874207, 'Train/mean f1': 0.9930298924446106, 'Train/mean precision': 0.9879941940307617, 'Train/mean recall': 0.9981173872947693, 'Train/mean hd95_metric': 0.6874299049377441} +Epoch [3160/4000] Validation [1/4] Loss: 0.40119 focal_loss 0.33646 dice_loss 0.06473 +Epoch [3160/4000] Validation [2/4] Loss: 0.78719 focal_loss 0.58688 dice_loss 0.20031 +Epoch [3160/4000] Validation [3/4] Loss: 0.51720 focal_loss 0.41826 dice_loss 0.09895 +Epoch [3160/4000] Validation [4/4] Loss: 0.32741 focal_loss 0.22294 dice_loss 0.10447 +Epoch [3160/4000] Validation metric {'Val/mean dice_metric': 0.9713245630264282, 'Val/mean miou_metric': 0.957327663898468, 'Val/mean f1': 0.9752398133277893, 'Val/mean precision': 0.972671389579773, 'Val/mean recall': 0.977821946144104, 'Val/mean hd95_metric': 5.464198112487793} +Cheakpoint... +Epoch [3160/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713245630264282, 'Val/mean miou_metric': 0.957327663898468, 'Val/mean f1': 0.9752398133277893, 'Val/mean precision': 0.972671389579773, 'Val/mean recall': 0.977821946144104, 'Val/mean hd95_metric': 5.464198112487793} +Epoch [3161/4000] Training [1/16] Loss: 0.00251 +Epoch [3161/4000] Training [2/16] Loss: 0.00248 +Epoch [3161/4000] Training [3/16] Loss: 0.00355 +Epoch [3161/4000] Training [4/16] Loss: 0.00406 +Epoch [3161/4000] Training [5/16] Loss: 0.00335 +Epoch [3161/4000] Training [6/16] Loss: 0.00279 +Epoch [3161/4000] Training [7/16] Loss: 0.00283 +Epoch [3161/4000] Training [8/16] Loss: 0.00284 +Epoch [3161/4000] Training [9/16] Loss: 0.00216 +Epoch [3161/4000] Training [10/16] Loss: 0.00337 +Epoch [3161/4000] Training [11/16] Loss: 0.00292 +Epoch [3161/4000] Training [12/16] Loss: 0.00299 +Epoch [3161/4000] Training [13/16] Loss: 0.00254 +Epoch [3161/4000] Training [14/16] Loss: 0.00171 +Epoch [3161/4000] Training [15/16] Loss: 0.00303 +Epoch [3161/4000] Training [16/16] Loss: 0.00353 +Epoch [3161/4000] Training metric {'Train/mean dice_metric': 0.9984707236289978, 'Train/mean miou_metric': 0.9966695308685303, 'Train/mean f1': 0.9934868812561035, 'Train/mean precision': 0.988921582698822, 'Train/mean recall': 0.9980946779251099, 'Train/mean hd95_metric': 0.6577701568603516} +Epoch [3161/4000] Validation [1/4] Loss: 0.37032 focal_loss 0.30498 dice_loss 0.06534 +Epoch [3161/4000] Validation [2/4] Loss: 0.39020 focal_loss 0.28554 dice_loss 0.10466 +Epoch [3161/4000] Validation [3/4] Loss: 0.48776 focal_loss 0.38995 dice_loss 0.09780 +Epoch [3161/4000] Validation [4/4] Loss: 0.31872 focal_loss 0.23279 dice_loss 0.08593 +Epoch [3161/4000] Validation metric {'Val/mean dice_metric': 0.9751617312431335, 'Val/mean miou_metric': 0.960868239402771, 'Val/mean f1': 0.976068913936615, 'Val/mean precision': 0.9732487201690674, 'Val/mean recall': 0.9789055585861206, 'Val/mean hd95_metric': 4.997652530670166} +Cheakpoint... +Epoch [3161/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751617312431335, 'Val/mean miou_metric': 0.960868239402771, 'Val/mean f1': 0.976068913936615, 'Val/mean precision': 0.9732487201690674, 'Val/mean recall': 0.9789055585861206, 'Val/mean hd95_metric': 4.997652530670166} +Epoch [3162/4000] Training [1/16] Loss: 0.00244 +Epoch [3162/4000] Training [2/16] Loss: 0.00273 +Epoch [3162/4000] Training [3/16] Loss: 0.00330 +Epoch [3162/4000] Training [4/16] Loss: 0.00379 +Epoch [3162/4000] Training [5/16] Loss: 0.00252 +Epoch [3162/4000] Training [6/16] Loss: 0.00314 +Epoch [3162/4000] Training [7/16] Loss: 0.00324 +Epoch [3162/4000] Training [8/16] Loss: 0.00223 +Epoch [3162/4000] Training [9/16] Loss: 0.00236 +Epoch [3162/4000] Training [10/16] Loss: 0.00220 +Epoch [3162/4000] Training [11/16] Loss: 0.00197 +Epoch [3162/4000] Training [12/16] Loss: 0.00273 +Epoch [3162/4000] Training [13/16] Loss: 0.00304 +Epoch [3162/4000] Training [14/16] Loss: 0.00313 +Epoch [3162/4000] Training [15/16] Loss: 0.00269 +Epoch [3162/4000] Training [16/16] Loss: 0.00267 +Epoch [3162/4000] Training metric {'Train/mean dice_metric': 0.9984588027000427, 'Train/mean miou_metric': 0.9966301918029785, 'Train/mean f1': 0.9934542775154114, 'Train/mean precision': 0.9888884425163269, 'Train/mean recall': 0.9980624914169312, 'Train/mean hd95_metric': 0.6929685473442078} +Epoch [3162/4000] Validation [1/4] Loss: 0.36827 focal_loss 0.30703 dice_loss 0.06123 +Epoch [3162/4000] Validation [2/4] Loss: 0.38078 focal_loss 0.27557 dice_loss 0.10521 +Epoch [3162/4000] Validation [3/4] Loss: 0.54445 focal_loss 0.44605 dice_loss 0.09840 +Epoch [3162/4000] Validation [4/4] Loss: 0.32058 focal_loss 0.21801 dice_loss 0.10257 +Epoch [3162/4000] Validation metric {'Val/mean dice_metric': 0.9738807678222656, 'Val/mean miou_metric': 0.959905743598938, 'Val/mean f1': 0.9761595726013184, 'Val/mean precision': 0.9732258319854736, 'Val/mean recall': 0.9791110754013062, 'Val/mean hd95_metric': 5.215035438537598} +Cheakpoint... +Epoch [3162/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738807678222656, 'Val/mean miou_metric': 0.959905743598938, 'Val/mean f1': 0.9761595726013184, 'Val/mean precision': 0.9732258319854736, 'Val/mean recall': 0.9791110754013062, 'Val/mean hd95_metric': 5.215035438537598} +Epoch [3163/4000] Training [1/16] Loss: 0.00438 +Epoch [3163/4000] Training [2/16] Loss: 0.00294 +Epoch [3163/4000] Training [3/16] Loss: 0.00254 +Epoch [3163/4000] Training [4/16] Loss: 0.00199 +Epoch [3163/4000] Training [5/16] Loss: 0.00291 +Epoch [3163/4000] Training [6/16] Loss: 0.00329 +Epoch [3163/4000] Training [7/16] Loss: 0.00219 +Epoch [3163/4000] Training [8/16] Loss: 0.00326 +Epoch [3163/4000] Training [9/16] Loss: 0.00302 +Epoch [3163/4000] Training [10/16] Loss: 0.00379 +Epoch [3163/4000] Training [11/16] Loss: 0.00329 +Epoch [3163/4000] Training [12/16] Loss: 0.00242 +Epoch [3163/4000] Training [13/16] Loss: 0.00285 +Epoch [3163/4000] Training [14/16] Loss: 0.00258 +Epoch [3163/4000] Training [15/16] Loss: 0.00406 +Epoch [3163/4000] Training [16/16] Loss: 0.00259 +Epoch [3163/4000] Training metric {'Train/mean dice_metric': 0.9982753992080688, 'Train/mean miou_metric': 0.996245801448822, 'Train/mean f1': 0.9925851225852966, 'Train/mean precision': 0.9872840642929077, 'Train/mean recall': 0.9979434609413147, 'Train/mean hd95_metric': 0.8111820220947266} +Epoch [3163/4000] Validation [1/4] Loss: 0.38688 focal_loss 0.31836 dice_loss 0.06852 +Epoch [3163/4000] Validation [2/4] Loss: 0.37220 focal_loss 0.27342 dice_loss 0.09878 +Epoch [3163/4000] Validation [3/4] Loss: 0.51704 focal_loss 0.42330 dice_loss 0.09374 +Epoch [3163/4000] Validation [4/4] Loss: 0.33068 focal_loss 0.24295 dice_loss 0.08773 +Epoch [3163/4000] Validation metric {'Val/mean dice_metric': 0.9745767712593079, 'Val/mean miou_metric': 0.9602203369140625, 'Val/mean f1': 0.9758026003837585, 'Val/mean precision': 0.9729353189468384, 'Val/mean recall': 0.9786868095397949, 'Val/mean hd95_metric': 4.858165740966797} +Cheakpoint... +Epoch [3163/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745767712593079, 'Val/mean miou_metric': 0.9602203369140625, 'Val/mean f1': 0.9758026003837585, 'Val/mean precision': 0.9729353189468384, 'Val/mean recall': 0.9786868095397949, 'Val/mean hd95_metric': 4.858165740966797} +Epoch [3164/4000] Training [1/16] Loss: 0.00278 +Epoch [3164/4000] Training [2/16] Loss: 0.00293 +Epoch [3164/4000] Training [3/16] Loss: 0.00177 +Epoch [3164/4000] Training [4/16] Loss: 0.00358 +Epoch [3164/4000] Training [5/16] Loss: 0.00339 +Epoch [3164/4000] Training [6/16] Loss: 0.00270 +Epoch [3164/4000] Training [7/16] Loss: 0.00390 +Epoch [3164/4000] Training [8/16] Loss: 0.00281 +Epoch [3164/4000] Training [9/16] Loss: 0.00283 +Epoch [3164/4000] Training [10/16] Loss: 0.00304 +Epoch [3164/4000] Training [11/16] Loss: 0.00238 +Epoch [3164/4000] Training [12/16] Loss: 0.00339 +Epoch [3164/4000] Training [13/16] Loss: 0.00356 +Epoch [3164/4000] Training [14/16] Loss: 0.00243 +Epoch [3164/4000] Training [15/16] Loss: 0.00294 +Epoch [3164/4000] Training [16/16] Loss: 0.00280 +Epoch [3164/4000] Training metric {'Train/mean dice_metric': 0.9983919858932495, 'Train/mean miou_metric': 0.9965157508850098, 'Train/mean f1': 0.993586003780365, 'Train/mean precision': 0.989112377166748, 'Train/mean recall': 0.9981002807617188, 'Train/mean hd95_metric': 0.7304922342300415} +Epoch [3164/4000] Validation [1/4] Loss: 0.36537 focal_loss 0.30511 dice_loss 0.06026 +Epoch [3164/4000] Validation [2/4] Loss: 0.61766 focal_loss 0.44883 dice_loss 0.16883 +Epoch [3164/4000] Validation [3/4] Loss: 0.50790 focal_loss 0.41915 dice_loss 0.08875 +Epoch [3164/4000] Validation [4/4] Loss: 0.29933 focal_loss 0.21466 dice_loss 0.08467 +Epoch [3164/4000] Validation metric {'Val/mean dice_metric': 0.9750901460647583, 'Val/mean miou_metric': 0.9610475301742554, 'Val/mean f1': 0.9764086008071899, 'Val/mean precision': 0.9739704132080078, 'Val/mean recall': 0.9788591861724854, 'Val/mean hd95_metric': 5.006058216094971} +Cheakpoint... +Epoch [3164/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750901460647583, 'Val/mean miou_metric': 0.9610475301742554, 'Val/mean f1': 0.9764086008071899, 'Val/mean precision': 0.9739704132080078, 'Val/mean recall': 0.9788591861724854, 'Val/mean hd95_metric': 5.006058216094971} +Epoch [3165/4000] Training [1/16] Loss: 0.00284 +Epoch [3165/4000] Training [2/16] Loss: 0.00169 +Epoch [3165/4000] Training [3/16] Loss: 0.00456 +Epoch [3165/4000] Training [4/16] Loss: 0.00412 +Epoch [3165/4000] Training [5/16] Loss: 0.00338 +Epoch [3165/4000] Training [6/16] Loss: 0.00301 +Epoch [3165/4000] Training [7/16] Loss: 0.00410 +Epoch [3165/4000] Training [8/16] Loss: 0.00407 +Epoch [3165/4000] Training [9/16] Loss: 0.00315 +Epoch [3165/4000] Training [10/16] Loss: 0.00318 +Epoch [3165/4000] Training [11/16] Loss: 0.00229 +Epoch [3165/4000] Training [12/16] Loss: 0.00200 +Epoch [3165/4000] Training [13/16] Loss: 0.00404 +Epoch [3165/4000] Training [14/16] Loss: 0.00303 +Epoch [3165/4000] Training [15/16] Loss: 0.00292 +Epoch [3165/4000] Training [16/16] Loss: 0.00199 +Epoch [3165/4000] Training metric {'Train/mean dice_metric': 0.998506486415863, 'Train/mean miou_metric': 0.9967180490493774, 'Train/mean f1': 0.9932129979133606, 'Train/mean precision': 0.9884276390075684, 'Train/mean recall': 0.9980448484420776, 'Train/mean hd95_metric': 0.6745392680168152} +Epoch [3165/4000] Validation [1/4] Loss: 0.43970 focal_loss 0.36909 dice_loss 0.07061 +Epoch [3165/4000] Validation [2/4] Loss: 0.74082 focal_loss 0.56546 dice_loss 0.17536 +Epoch [3165/4000] Validation [3/4] Loss: 0.54349 focal_loss 0.44926 dice_loss 0.09423 +Epoch [3165/4000] Validation [4/4] Loss: 0.42574 focal_loss 0.31918 dice_loss 0.10655 +Epoch [3165/4000] Validation metric {'Val/mean dice_metric': 0.9730264544487, 'Val/mean miou_metric': 0.9588336944580078, 'Val/mean f1': 0.9755514860153198, 'Val/mean precision': 0.9729570746421814, 'Val/mean recall': 0.9781597256660461, 'Val/mean hd95_metric': 4.979429244995117} +Cheakpoint... +Epoch [3165/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730264544487, 'Val/mean miou_metric': 0.9588336944580078, 'Val/mean f1': 0.9755514860153198, 'Val/mean precision': 0.9729570746421814, 'Val/mean recall': 0.9781597256660461, 'Val/mean hd95_metric': 4.979429244995117} +Epoch [3166/4000] Training [1/16] Loss: 0.00225 +Epoch [3166/4000] Training [2/16] Loss: 0.00284 +Epoch [3166/4000] Training [3/16] Loss: 0.00418 +Epoch [3166/4000] Training [4/16] Loss: 0.00286 +Epoch [3166/4000] Training [5/16] Loss: 0.00237 +Epoch [3166/4000] Training [6/16] Loss: 0.00271 +Epoch [3166/4000] Training [7/16] Loss: 0.00201 +Epoch [3166/4000] Training [8/16] Loss: 0.00296 +Epoch [3166/4000] Training [9/16] Loss: 0.00198 +Epoch [3166/4000] Training [10/16] Loss: 0.00315 +Epoch [3166/4000] Training [11/16] Loss: 0.00257 +Epoch [3166/4000] Training [12/16] Loss: 0.00346 +Epoch [3166/4000] Training [13/16] Loss: 0.00260 +Epoch [3166/4000] Training [14/16] Loss: 0.00328 +Epoch [3166/4000] Training [15/16] Loss: 0.00328 +Epoch [3166/4000] Training [16/16] Loss: 0.00292 +Epoch [3166/4000] Training metric {'Train/mean dice_metric': 0.9984116554260254, 'Train/mean miou_metric': 0.9965399503707886, 'Train/mean f1': 0.9934254884719849, 'Train/mean precision': 0.9887911081314087, 'Train/mean recall': 0.9981034398078918, 'Train/mean hd95_metric': 0.6795198917388916} +Epoch [3166/4000] Validation [1/4] Loss: 0.40512 focal_loss 0.34020 dice_loss 0.06492 +Epoch [3166/4000] Validation [2/4] Loss: 0.72387 focal_loss 0.53055 dice_loss 0.19333 +Epoch [3166/4000] Validation [3/4] Loss: 0.58245 focal_loss 0.48052 dice_loss 0.10193 +Epoch [3166/4000] Validation [4/4] Loss: 0.42464 focal_loss 0.31431 dice_loss 0.11033 +Epoch [3166/4000] Validation metric {'Val/mean dice_metric': 0.972878098487854, 'Val/mean miou_metric': 0.9582883715629578, 'Val/mean f1': 0.9747632145881653, 'Val/mean precision': 0.9718539118766785, 'Val/mean recall': 0.9776898622512817, 'Val/mean hd95_metric': 5.291825294494629} +Cheakpoint... +Epoch [3166/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972878098487854, 'Val/mean miou_metric': 0.9582883715629578, 'Val/mean f1': 0.9747632145881653, 'Val/mean precision': 0.9718539118766785, 'Val/mean recall': 0.9776898622512817, 'Val/mean hd95_metric': 5.291825294494629} +Epoch [3167/4000] Training [1/16] Loss: 0.00299 +Epoch [3167/4000] Training [2/16] Loss: 0.00280 +Epoch [3167/4000] Training [3/16] Loss: 0.00214 +Epoch [3167/4000] Training [4/16] Loss: 0.00289 +Epoch [3167/4000] Training [5/16] Loss: 0.00254 +Epoch [3167/4000] Training [6/16] Loss: 0.00286 +Epoch [3167/4000] Training [7/16] Loss: 0.00253 +Epoch [3167/4000] Training [8/16] Loss: 0.00386 +Epoch [3167/4000] Training [9/16] Loss: 0.00343 +Epoch [3167/4000] Training [10/16] Loss: 0.00293 +Epoch [3167/4000] Training [11/16] Loss: 0.00227 +Epoch [3167/4000] Training [12/16] Loss: 0.00230 +Epoch [3167/4000] Training [13/16] Loss: 0.00411 +Epoch [3167/4000] Training [14/16] Loss: 0.00336 +Epoch [3167/4000] Training [15/16] Loss: 0.00257 +Epoch [3167/4000] Training [16/16] Loss: 0.00193 +Epoch [3167/4000] Training metric {'Train/mean dice_metric': 0.998292088508606, 'Train/mean miou_metric': 0.9962916374206543, 'Train/mean f1': 0.9931746125221252, 'Train/mean precision': 0.9884582757949829, 'Train/mean recall': 0.9979361295700073, 'Train/mean hd95_metric': 0.7376026511192322} +Epoch [3167/4000] Validation [1/4] Loss: 0.34247 focal_loss 0.28236 dice_loss 0.06011 +Epoch [3167/4000] Validation [2/4] Loss: 1.11830 focal_loss 0.91812 dice_loss 0.20018 +Epoch [3167/4000] Validation [3/4] Loss: 0.55041 focal_loss 0.45319 dice_loss 0.09722 +Epoch [3167/4000] Validation [4/4] Loss: 0.26945 focal_loss 0.18340 dice_loss 0.08605 +Epoch [3167/4000] Validation metric {'Val/mean dice_metric': 0.9713048934936523, 'Val/mean miou_metric': 0.9578197598457336, 'Val/mean f1': 0.9756040573120117, 'Val/mean precision': 0.9724833369255066, 'Val/mean recall': 0.9787448644638062, 'Val/mean hd95_metric': 5.29052209854126} +Cheakpoint... +Epoch [3167/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713048934936523, 'Val/mean miou_metric': 0.9578197598457336, 'Val/mean f1': 0.9756040573120117, 'Val/mean precision': 0.9724833369255066, 'Val/mean recall': 0.9787448644638062, 'Val/mean hd95_metric': 5.29052209854126} +Epoch [3168/4000] Training [1/16] Loss: 0.00195 +Epoch [3168/4000] Training [2/16] Loss: 0.00344 +Epoch [3168/4000] Training [3/16] Loss: 0.00321 +Epoch [3168/4000] Training [4/16] Loss: 0.00214 +Epoch [3168/4000] Training [5/16] Loss: 0.00310 +Epoch [3168/4000] Training [6/16] Loss: 0.00390 +Epoch [3168/4000] Training [7/16] Loss: 0.00271 +Epoch [3168/4000] Training [8/16] Loss: 0.00260 +Epoch [3168/4000] Training [9/16] Loss: 0.00285 +Epoch [3168/4000] Training [10/16] Loss: 0.00322 +Epoch [3168/4000] Training [11/16] Loss: 0.00293 +Epoch [3168/4000] Training [12/16] Loss: 0.00293 +Epoch [3168/4000] Training [13/16] Loss: 0.00283 +Epoch [3168/4000] Training [14/16] Loss: 0.00204 +Epoch [3168/4000] Training [15/16] Loss: 0.00450 +Epoch [3168/4000] Training [16/16] Loss: 0.00236 +Epoch [3168/4000] Training metric {'Train/mean dice_metric': 0.9983628392219543, 'Train/mean miou_metric': 0.9964441657066345, 'Train/mean f1': 0.9932121634483337, 'Train/mean precision': 0.9884426593780518, 'Train/mean recall': 0.9980278015136719, 'Train/mean hd95_metric': 0.6991764307022095} +Epoch [3168/4000] Validation [1/4] Loss: 0.39740 focal_loss 0.33273 dice_loss 0.06467 +Epoch [3168/4000] Validation [2/4] Loss: 0.38274 focal_loss 0.27972 dice_loss 0.10303 +Epoch [3168/4000] Validation [3/4] Loss: 0.28117 focal_loss 0.21471 dice_loss 0.06645 +Epoch [3168/4000] Validation [4/4] Loss: 0.36694 focal_loss 0.26790 dice_loss 0.09904 +Epoch [3168/4000] Validation metric {'Val/mean dice_metric': 0.9752975702285767, 'Val/mean miou_metric': 0.961039662361145, 'Val/mean f1': 0.9765777587890625, 'Val/mean precision': 0.9735406637191772, 'Val/mean recall': 0.9796338081359863, 'Val/mean hd95_metric': 4.7583441734313965} +Cheakpoint... +Epoch [3168/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752975702285767, 'Val/mean miou_metric': 0.961039662361145, 'Val/mean f1': 0.9765777587890625, 'Val/mean precision': 0.9735406637191772, 'Val/mean recall': 0.9796338081359863, 'Val/mean hd95_metric': 4.7583441734313965} +Epoch [3169/4000] Training [1/16] Loss: 0.00206 +Epoch [3169/4000] Training [2/16] Loss: 0.00289 +Epoch [3169/4000] Training [3/16] Loss: 0.00389 +Epoch [3169/4000] Training [4/16] Loss: 0.00347 +Epoch [3169/4000] Training [5/16] Loss: 0.00304 +Epoch [3169/4000] Training [6/16] Loss: 0.00335 +Epoch [3169/4000] Training [7/16] Loss: 0.00235 +Epoch [3169/4000] Training [8/16] Loss: 0.00337 +Epoch [3169/4000] Training [9/16] Loss: 0.00241 +Epoch [3169/4000] Training [10/16] Loss: 0.00324 +Epoch [3169/4000] Training [11/16] Loss: 0.00246 +Epoch [3169/4000] Training [12/16] Loss: 0.00272 +Epoch [3169/4000] Training [13/16] Loss: 0.00253 +Epoch [3169/4000] Training [14/16] Loss: 0.00376 +Epoch [3169/4000] Training [15/16] Loss: 0.00316 +Epoch [3169/4000] Training [16/16] Loss: 0.00330 +Epoch [3169/4000] Training metric {'Train/mean dice_metric': 0.9982813596725464, 'Train/mean miou_metric': 0.9962950348854065, 'Train/mean f1': 0.9934054017066956, 'Train/mean precision': 0.98888099193573, 'Train/mean recall': 0.9979713559150696, 'Train/mean hd95_metric': 0.6973632574081421} +Epoch [3169/4000] Validation [1/4] Loss: 0.40303 focal_loss 0.33976 dice_loss 0.06327 +Epoch [3169/4000] Validation [2/4] Loss: 0.38568 focal_loss 0.28191 dice_loss 0.10377 +Epoch [3169/4000] Validation [3/4] Loss: 0.51772 focal_loss 0.42556 dice_loss 0.09216 +Epoch [3169/4000] Validation [4/4] Loss: 0.52952 focal_loss 0.39847 dice_loss 0.13105 +Epoch [3169/4000] Validation metric {'Val/mean dice_metric': 0.9729738235473633, 'Val/mean miou_metric': 0.9588095545768738, 'Val/mean f1': 0.9755071401596069, 'Val/mean precision': 0.9724069833755493, 'Val/mean recall': 0.9786271452903748, 'Val/mean hd95_metric': 5.5648980140686035} +Cheakpoint... +Epoch [3169/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729738235473633, 'Val/mean miou_metric': 0.9588095545768738, 'Val/mean f1': 0.9755071401596069, 'Val/mean precision': 0.9724069833755493, 'Val/mean recall': 0.9786271452903748, 'Val/mean hd95_metric': 5.5648980140686035} +Epoch [3170/4000] Training [1/16] Loss: 0.00244 +Epoch [3170/4000] Training [2/16] Loss: 0.00263 +Epoch [3170/4000] Training [3/16] Loss: 0.00247 +Epoch [3170/4000] Training [4/16] Loss: 0.00444 +Epoch [3170/4000] Training [5/16] Loss: 0.00261 +Epoch [3170/4000] Training [6/16] Loss: 0.00197 +Epoch [3170/4000] Training [7/16] Loss: 0.00322 +Epoch [3170/4000] Training [8/16] Loss: 0.00416 +Epoch [3170/4000] Training [9/16] Loss: 0.00240 +Epoch [3170/4000] Training [10/16] Loss: 0.00324 +Epoch [3170/4000] Training [11/16] Loss: 0.00328 +Epoch [3170/4000] Training [12/16] Loss: 0.00256 +Epoch [3170/4000] Training [13/16] Loss: 0.00352 +Epoch [3170/4000] Training [14/16] Loss: 0.00342 +Epoch [3170/4000] Training [15/16] Loss: 0.00254 +Epoch [3170/4000] Training [16/16] Loss: 0.00182 +Epoch [3170/4000] Training metric {'Train/mean dice_metric': 0.9984240531921387, 'Train/mean miou_metric': 0.996566653251648, 'Train/mean f1': 0.9932572841644287, 'Train/mean precision': 0.9884839653968811, 'Train/mean recall': 0.9980769157409668, 'Train/mean hd95_metric': 0.7102813720703125} +Epoch [3170/4000] Validation [1/4] Loss: 0.46413 focal_loss 0.39907 dice_loss 0.06506 +Epoch [3170/4000] Validation [2/4] Loss: 0.38174 focal_loss 0.27858 dice_loss 0.10316 +Epoch [3170/4000] Validation [3/4] Loss: 0.51137 focal_loss 0.42039 dice_loss 0.09098 +Epoch [3170/4000] Validation [4/4] Loss: 0.32678 focal_loss 0.23779 dice_loss 0.08900 +Epoch [3170/4000] Validation metric {'Val/mean dice_metric': 0.9737545251846313, 'Val/mean miou_metric': 0.9597163200378418, 'Val/mean f1': 0.975868284702301, 'Val/mean precision': 0.9734421372413635, 'Val/mean recall': 0.9783064723014832, 'Val/mean hd95_metric': 5.1114277839660645} +Cheakpoint... +Epoch [3170/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737545251846313, 'Val/mean miou_metric': 0.9597163200378418, 'Val/mean f1': 0.975868284702301, 'Val/mean precision': 0.9734421372413635, 'Val/mean recall': 0.9783064723014832, 'Val/mean hd95_metric': 5.1114277839660645} +Epoch [3171/4000] Training [1/16] Loss: 0.00212 +Epoch [3171/4000] Training [2/16] Loss: 0.00245 +Epoch [3171/4000] Training [3/16] Loss: 0.00268 +Epoch [3171/4000] Training [4/16] Loss: 0.00315 +Epoch [3171/4000] Training [5/16] Loss: 0.00231 +Epoch [3171/4000] Training [6/16] Loss: 0.00286 +Epoch [3171/4000] Training [7/16] Loss: 0.00203 +Epoch [3171/4000] Training [8/16] Loss: 0.00180 +Epoch [3171/4000] Training [9/16] Loss: 0.00221 +Epoch [3171/4000] Training [10/16] Loss: 0.00301 +Epoch [3171/4000] Training [11/16] Loss: 0.00304 +Epoch [3171/4000] Training [12/16] Loss: 0.00225 +Epoch [3171/4000] Training [13/16] Loss: 0.00255 +Epoch [3171/4000] Training [14/16] Loss: 0.00238 +Epoch [3171/4000] Training [15/16] Loss: 0.00356 +Epoch [3171/4000] Training [16/16] Loss: 0.00334 +Epoch [3171/4000] Training metric {'Train/mean dice_metric': 0.9985417723655701, 'Train/mean miou_metric': 0.9967939257621765, 'Train/mean f1': 0.9934080839157104, 'Train/mean precision': 0.9886788129806519, 'Train/mean recall': 0.9981828331947327, 'Train/mean hd95_metric': 0.6731719970703125} +Epoch [3171/4000] Validation [1/4] Loss: 0.41707 focal_loss 0.34887 dice_loss 0.06820 +Epoch [3171/4000] Validation [2/4] Loss: 0.97092 focal_loss 0.72910 dice_loss 0.24182 +Epoch [3171/4000] Validation [3/4] Loss: 0.53039 focal_loss 0.43181 dice_loss 0.09858 +Epoch [3171/4000] Validation [4/4] Loss: 0.47126 focal_loss 0.34561 dice_loss 0.12565 +Epoch [3171/4000] Validation metric {'Val/mean dice_metric': 0.9713481664657593, 'Val/mean miou_metric': 0.9572700262069702, 'Val/mean f1': 0.9749680757522583, 'Val/mean precision': 0.9723687171936035, 'Val/mean recall': 0.9775813221931458, 'Val/mean hd95_metric': 5.3290886878967285} +Cheakpoint... +Epoch [3171/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9713], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9713481664657593, 'Val/mean miou_metric': 0.9572700262069702, 'Val/mean f1': 0.9749680757522583, 'Val/mean precision': 0.9723687171936035, 'Val/mean recall': 0.9775813221931458, 'Val/mean hd95_metric': 5.3290886878967285} +Epoch [3172/4000] Training [1/16] Loss: 0.00205 +Epoch [3172/4000] Training [2/16] Loss: 0.00241 +Epoch [3172/4000] Training [3/16] Loss: 0.00241 +Epoch [3172/4000] Training [4/16] Loss: 0.00255 +Epoch [3172/4000] Training [5/16] Loss: 0.00492 +Epoch [3172/4000] Training [6/16] Loss: 0.00250 +Epoch [3172/4000] Training [7/16] Loss: 0.00300 +Epoch [3172/4000] Training [8/16] Loss: 0.00273 +Epoch [3172/4000] Training [9/16] Loss: 0.00319 +Epoch [3172/4000] Training [10/16] Loss: 0.00378 +Epoch [3172/4000] Training [11/16] Loss: 0.00266 +Epoch [3172/4000] Training [12/16] Loss: 0.00249 +Epoch [3172/4000] Training [13/16] Loss: 0.00316 +Epoch [3172/4000] Training [14/16] Loss: 0.00217 +Epoch [3172/4000] Training [15/16] Loss: 0.00254 +Epoch [3172/4000] Training [16/16] Loss: 0.00350 +Epoch [3172/4000] Training metric {'Train/mean dice_metric': 0.9985107779502869, 'Train/mean miou_metric': 0.9967526197433472, 'Train/mean f1': 0.9935845732688904, 'Train/mean precision': 0.9890977740287781, 'Train/mean recall': 0.9981122612953186, 'Train/mean hd95_metric': 0.686355710029602} +Epoch [3172/4000] Validation [1/4] Loss: 0.44109 focal_loss 0.37039 dice_loss 0.07070 +Epoch [3172/4000] Validation [2/4] Loss: 0.88875 focal_loss 0.69431 dice_loss 0.19444 +Epoch [3172/4000] Validation [3/4] Loss: 0.52253 focal_loss 0.43001 dice_loss 0.09253 +Epoch [3172/4000] Validation [4/4] Loss: 0.30471 focal_loss 0.21295 dice_loss 0.09176 +Epoch [3172/4000] Validation metric {'Val/mean dice_metric': 0.9727185964584351, 'Val/mean miou_metric': 0.9589439630508423, 'Val/mean f1': 0.9759834408760071, 'Val/mean precision': 0.9742481112480164, 'Val/mean recall': 0.9777249097824097, 'Val/mean hd95_metric': 4.910883903503418} +Cheakpoint... +Epoch [3172/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727185964584351, 'Val/mean miou_metric': 0.9589439630508423, 'Val/mean f1': 0.9759834408760071, 'Val/mean precision': 0.9742481112480164, 'Val/mean recall': 0.9777249097824097, 'Val/mean hd95_metric': 4.910883903503418} +Epoch [3173/4000] Training [1/16] Loss: 0.00361 +Epoch [3173/4000] Training [2/16] Loss: 0.00243 +Epoch [3173/4000] Training [3/16] Loss: 0.00246 +Epoch [3173/4000] Training [4/16] Loss: 0.00276 +Epoch [3173/4000] Training [5/16] Loss: 0.00284 +Epoch [3173/4000] Training [6/16] Loss: 0.00322 +Epoch [3173/4000] Training [7/16] Loss: 0.00266 +Epoch [3173/4000] Training [8/16] Loss: 0.00262 +Epoch [3173/4000] Training [9/16] Loss: 0.00258 +Epoch [3173/4000] Training [10/16] Loss: 0.00299 +Epoch [3173/4000] Training [11/16] Loss: 0.00312 +Epoch [3173/4000] Training [12/16] Loss: 0.00181 +Epoch [3173/4000] Training [13/16] Loss: 0.00339 +Epoch [3173/4000] Training [14/16] Loss: 0.00487 +Epoch [3173/4000] Training [15/16] Loss: 0.00498 +Epoch [3173/4000] Training [16/16] Loss: 0.00285 +Epoch [3173/4000] Training metric {'Train/mean dice_metric': 0.9983502626419067, 'Train/mean miou_metric': 0.9963771104812622, 'Train/mean f1': 0.9925016760826111, 'Train/mean precision': 0.9870546460151672, 'Train/mean recall': 0.9980090856552124, 'Train/mean hd95_metric': 0.6781803369522095} +Epoch [3173/4000] Validation [1/4] Loss: 0.35764 focal_loss 0.29555 dice_loss 0.06209 +Epoch [3173/4000] Validation [2/4] Loss: 0.36004 focal_loss 0.25823 dice_loss 0.10181 +Epoch [3173/4000] Validation [3/4] Loss: 0.28474 focal_loss 0.21463 dice_loss 0.07011 +Epoch [3173/4000] Validation [4/4] Loss: 0.35317 focal_loss 0.25116 dice_loss 0.10202 +Epoch [3173/4000] Validation metric {'Val/mean dice_metric': 0.9740921854972839, 'Val/mean miou_metric': 0.9600831270217896, 'Val/mean f1': 0.9760478138923645, 'Val/mean precision': 0.9733560085296631, 'Val/mean recall': 0.978754460811615, 'Val/mean hd95_metric': 4.7024827003479} +Cheakpoint... +Epoch [3173/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740921854972839, 'Val/mean miou_metric': 0.9600831270217896, 'Val/mean f1': 0.9760478138923645, 'Val/mean precision': 0.9733560085296631, 'Val/mean recall': 0.978754460811615, 'Val/mean hd95_metric': 4.7024827003479} +Epoch [3174/4000] Training [1/16] Loss: 0.00302 +Epoch [3174/4000] Training [2/16] Loss: 0.00243 +Epoch [3174/4000] Training [3/16] Loss: 0.00307 +Epoch [3174/4000] Training [4/16] Loss: 0.00288 +Epoch [3174/4000] Training [5/16] Loss: 0.00231 +Epoch [3174/4000] Training [6/16] Loss: 0.00323 +Epoch [3174/4000] Training [7/16] Loss: 0.00386 +Epoch [3174/4000] Training [8/16] Loss: 0.00227 +Epoch [3174/4000] Training [9/16] Loss: 0.00232 +Epoch [3174/4000] Training [10/16] Loss: 0.00366 +Epoch [3174/4000] Training [11/16] Loss: 0.00254 +Epoch [3174/4000] Training [12/16] Loss: 0.00217 +Epoch [3174/4000] Training [13/16] Loss: 0.00250 +Epoch [3174/4000] Training [14/16] Loss: 0.00247 +Epoch [3174/4000] Training [15/16] Loss: 0.00225 +Epoch [3174/4000] Training [16/16] Loss: 0.00416 +Epoch [3174/4000] Training metric {'Train/mean dice_metric': 0.9983408451080322, 'Train/mean miou_metric': 0.9963963031768799, 'Train/mean f1': 0.9932560920715332, 'Train/mean precision': 0.9885179400444031, 'Train/mean recall': 0.998039960861206, 'Train/mean hd95_metric': 0.7108952403068542} +Epoch [3174/4000] Validation [1/4] Loss: 0.38264 focal_loss 0.31912 dice_loss 0.06352 +Epoch [3174/4000] Validation [2/4] Loss: 0.89685 focal_loss 0.69953 dice_loss 0.19731 +Epoch [3174/4000] Validation [3/4] Loss: 0.49200 focal_loss 0.40546 dice_loss 0.08654 +Epoch [3174/4000] Validation [4/4] Loss: 0.32061 focal_loss 0.22048 dice_loss 0.10013 +Epoch [3174/4000] Validation metric {'Val/mean dice_metric': 0.9739199876785278, 'Val/mean miou_metric': 0.9602094888687134, 'Val/mean f1': 0.9765779376029968, 'Val/mean precision': 0.9738098382949829, 'Val/mean recall': 0.9793617129325867, 'Val/mean hd95_metric': 4.721964359283447} +Cheakpoint... +Epoch [3174/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739199876785278, 'Val/mean miou_metric': 0.9602094888687134, 'Val/mean f1': 0.9765779376029968, 'Val/mean precision': 0.9738098382949829, 'Val/mean recall': 0.9793617129325867, 'Val/mean hd95_metric': 4.721964359283447} +Epoch [3175/4000] Training [1/16] Loss: 0.00269 +Epoch [3175/4000] Training [2/16] Loss: 0.00319 +Epoch [3175/4000] Training [3/16] Loss: 0.00207 +Epoch [3175/4000] Training [4/16] Loss: 0.00318 +Epoch [3175/4000] Training [5/16] Loss: 0.00333 +Epoch [3175/4000] Training [6/16] Loss: 0.00320 +Epoch [3175/4000] Training [7/16] Loss: 0.00372 +Epoch [3175/4000] Training [8/16] Loss: 0.00377 +Epoch [3175/4000] Training [9/16] Loss: 0.00323 +Epoch [3175/4000] Training [10/16] Loss: 0.00329 +Epoch [3175/4000] Training [11/16] Loss: 0.00271 +Epoch [3175/4000] Training [12/16] Loss: 0.00201 +Epoch [3175/4000] Training [13/16] Loss: 0.00302 +Epoch [3175/4000] Training [14/16] Loss: 0.00309 +Epoch [3175/4000] Training [15/16] Loss: 0.00313 +Epoch [3175/4000] Training [16/16] Loss: 0.00306 +Epoch [3175/4000] Training metric {'Train/mean dice_metric': 0.9982479810714722, 'Train/mean miou_metric': 0.9962264895439148, 'Train/mean f1': 0.9933655261993408, 'Train/mean precision': 0.9888519048690796, 'Train/mean recall': 0.9979205131530762, 'Train/mean hd95_metric': 0.75950026512146} +Epoch [3175/4000] Validation [1/4] Loss: 0.42519 focal_loss 0.35893 dice_loss 0.06626 +Epoch [3175/4000] Validation [2/4] Loss: 0.44250 focal_loss 0.33018 dice_loss 0.11232 +Epoch [3175/4000] Validation [3/4] Loss: 0.53099 focal_loss 0.44005 dice_loss 0.09094 +Epoch [3175/4000] Validation [4/4] Loss: 0.33176 focal_loss 0.24019 dice_loss 0.09157 +Epoch [3175/4000] Validation metric {'Val/mean dice_metric': 0.9729175567626953, 'Val/mean miou_metric': 0.9586706161499023, 'Val/mean f1': 0.9762197136878967, 'Val/mean precision': 0.9745514392852783, 'Val/mean recall': 0.9778938293457031, 'Val/mean hd95_metric': 5.041658401489258} +Cheakpoint... +Epoch [3175/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729175567626953, 'Val/mean miou_metric': 0.9586706161499023, 'Val/mean f1': 0.9762197136878967, 'Val/mean precision': 0.9745514392852783, 'Val/mean recall': 0.9778938293457031, 'Val/mean hd95_metric': 5.041658401489258} +Epoch [3176/4000] Training [1/16] Loss: 0.00315 +Epoch [3176/4000] Training [2/16] Loss: 0.00283 +Epoch [3176/4000] Training [3/16] Loss: 0.00273 +Epoch [3176/4000] Training [4/16] Loss: 0.00236 +Epoch [3176/4000] Training [5/16] Loss: 0.00236 +Epoch [3176/4000] Training [6/16] Loss: 0.00215 +Epoch [3176/4000] Training [7/16] Loss: 0.00256 +Epoch [3176/4000] Training [8/16] Loss: 0.00342 +Epoch [3176/4000] Training [9/16] Loss: 0.00255 +Epoch [3176/4000] Training [10/16] Loss: 0.00253 +Epoch [3176/4000] Training [11/16] Loss: 0.00255 +Epoch [3176/4000] Training [12/16] Loss: 0.00260 +Epoch [3176/4000] Training [13/16] Loss: 0.00309 +Epoch [3176/4000] Training [14/16] Loss: 0.00209 +Epoch [3176/4000] Training [15/16] Loss: 0.00445 +Epoch [3176/4000] Training [16/16] Loss: 0.00252 +Epoch [3176/4000] Training metric {'Train/mean dice_metric': 0.998462438583374, 'Train/mean miou_metric': 0.9966429471969604, 'Train/mean f1': 0.9934327602386475, 'Train/mean precision': 0.9887216091156006, 'Train/mean recall': 0.9981889724731445, 'Train/mean hd95_metric': 0.7024967074394226} +Epoch [3176/4000] Validation [1/4] Loss: 0.38566 focal_loss 0.32156 dice_loss 0.06410 +Epoch [3176/4000] Validation [2/4] Loss: 0.91361 focal_loss 0.71518 dice_loss 0.19844 +Epoch [3176/4000] Validation [3/4] Loss: 0.51966 focal_loss 0.42431 dice_loss 0.09535 +Epoch [3176/4000] Validation [4/4] Loss: 0.32129 focal_loss 0.22980 dice_loss 0.09149 +Epoch [3176/4000] Validation metric {'Val/mean dice_metric': 0.9724323153495789, 'Val/mean miou_metric': 0.9589545130729675, 'Val/mean f1': 0.9762465357780457, 'Val/mean precision': 0.9736553430557251, 'Val/mean recall': 0.9788516759872437, 'Val/mean hd95_metric': 5.170905113220215} +Cheakpoint... +Epoch [3176/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724323153495789, 'Val/mean miou_metric': 0.9589545130729675, 'Val/mean f1': 0.9762465357780457, 'Val/mean precision': 0.9736553430557251, 'Val/mean recall': 0.9788516759872437, 'Val/mean hd95_metric': 5.170905113220215} +Epoch [3177/4000] Training [1/16] Loss: 0.00470 +Epoch [3177/4000] Training [2/16] Loss: 0.00221 +Epoch [3177/4000] Training [3/16] Loss: 0.00300 +Epoch [3177/4000] Training [4/16] Loss: 0.00233 +Epoch [3177/4000] Training [5/16] Loss: 0.00248 +Epoch [3177/4000] Training [6/16] Loss: 0.00246 +Epoch [3177/4000] Training [7/16] Loss: 0.00301 +Epoch [3177/4000] Training [8/16] Loss: 0.00302 +Epoch [3177/4000] Training [9/16] Loss: 0.00390 +Epoch [3177/4000] Training [10/16] Loss: 0.00361 +Epoch [3177/4000] Training [11/16] Loss: 0.00332 +Epoch [3177/4000] Training [12/16] Loss: 0.00299 +Epoch [3177/4000] Training [13/16] Loss: 0.00344 +Epoch [3177/4000] Training [14/16] Loss: 0.00254 +Epoch [3177/4000] Training [15/16] Loss: 0.00368 +Epoch [3177/4000] Training [16/16] Loss: 0.00232 +Epoch [3177/4000] Training metric {'Train/mean dice_metric': 0.9983450770378113, 'Train/mean miou_metric': 0.996414303779602, 'Train/mean f1': 0.9933706521987915, 'Train/mean precision': 0.9888058304786682, 'Train/mean recall': 0.9979778528213501, 'Train/mean hd95_metric': 0.7595476508140564} +Epoch [3177/4000] Validation [1/4] Loss: 0.41227 focal_loss 0.34696 dice_loss 0.06531 +Epoch [3177/4000] Validation [2/4] Loss: 0.36386 focal_loss 0.26324 dice_loss 0.10062 +Epoch [3177/4000] Validation [3/4] Loss: 0.27309 focal_loss 0.21026 dice_loss 0.06283 +Epoch [3177/4000] Validation [4/4] Loss: 0.42873 focal_loss 0.31733 dice_loss 0.11140 +Epoch [3177/4000] Validation metric {'Val/mean dice_metric': 0.9750076532363892, 'Val/mean miou_metric': 0.9611247777938843, 'Val/mean f1': 0.9768120050430298, 'Val/mean precision': 0.9733049273490906, 'Val/mean recall': 0.9803444743156433, 'Val/mean hd95_metric': 4.8555827140808105} +Cheakpoint... +Epoch [3177/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750076532363892, 'Val/mean miou_metric': 0.9611247777938843, 'Val/mean f1': 0.9768120050430298, 'Val/mean precision': 0.9733049273490906, 'Val/mean recall': 0.9803444743156433, 'Val/mean hd95_metric': 4.8555827140808105} +Epoch [3178/4000] Training [1/16] Loss: 0.00241 +Epoch [3178/4000] Training [2/16] Loss: 0.00258 +Epoch [3178/4000] Training [3/16] Loss: 0.00246 +Epoch [3178/4000] Training [4/16] Loss: 0.00404 +Epoch [3178/4000] Training [5/16] Loss: 0.00438 +Epoch [3178/4000] Training [6/16] Loss: 0.00263 +Epoch [3178/4000] Training [7/16] Loss: 0.00366 +Epoch [3178/4000] Training [8/16] Loss: 0.00287 +Epoch [3178/4000] Training [9/16] Loss: 0.00277 +Epoch [3178/4000] Training [10/16] Loss: 0.00253 +Epoch [3178/4000] Training [11/16] Loss: 0.00311 +Epoch [3178/4000] Training [12/16] Loss: 0.00237 +Epoch [3178/4000] Training [13/16] Loss: 0.00384 +Epoch [3178/4000] Training [14/16] Loss: 0.00399 +Epoch [3178/4000] Training [15/16] Loss: 0.00258 +Epoch [3178/4000] Training [16/16] Loss: 0.00192 +Epoch [3178/4000] Training metric {'Train/mean dice_metric': 0.9983046054840088, 'Train/mean miou_metric': 0.9963334202766418, 'Train/mean f1': 0.9932739734649658, 'Train/mean precision': 0.9885658025741577, 'Train/mean recall': 0.9980272054672241, 'Train/mean hd95_metric': 0.7160431146621704} +Epoch [3178/4000] Validation [1/4] Loss: 0.42180 focal_loss 0.35681 dice_loss 0.06499 +Epoch [3178/4000] Validation [2/4] Loss: 1.27784 focal_loss 0.99914 dice_loss 0.27870 +Epoch [3178/4000] Validation [3/4] Loss: 0.27704 focal_loss 0.20985 dice_loss 0.06720 +Epoch [3178/4000] Validation [4/4] Loss: 0.31886 focal_loss 0.22746 dice_loss 0.09141 +Epoch [3178/4000] Validation metric {'Val/mean dice_metric': 0.9720802307128906, 'Val/mean miou_metric': 0.9584068059921265, 'Val/mean f1': 0.9758557677268982, 'Val/mean precision': 0.9736877679824829, 'Val/mean recall': 0.9780333638191223, 'Val/mean hd95_metric': 4.955043792724609} +Cheakpoint... +Epoch [3178/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720802307128906, 'Val/mean miou_metric': 0.9584068059921265, 'Val/mean f1': 0.9758557677268982, 'Val/mean precision': 0.9736877679824829, 'Val/mean recall': 0.9780333638191223, 'Val/mean hd95_metric': 4.955043792724609} +Epoch [3179/4000] Training [1/16] Loss: 0.00221 +Epoch [3179/4000] Training [2/16] Loss: 0.00217 +Epoch [3179/4000] Training [3/16] Loss: 0.00306 +Epoch [3179/4000] Training [4/16] Loss: 0.00272 +Epoch [3179/4000] Training [5/16] Loss: 0.00375 +Epoch [3179/4000] Training [6/16] Loss: 0.00316 +Epoch [3179/4000] Training [7/16] Loss: 0.00294 +Epoch [3179/4000] Training [8/16] Loss: 0.00243 +Epoch [3179/4000] Training [9/16] Loss: 0.00283 +Epoch [3179/4000] Training [10/16] Loss: 0.00191 +Epoch [3179/4000] Training [11/16] Loss: 0.00331 +Epoch [3179/4000] Training [12/16] Loss: 0.00361 +Epoch [3179/4000] Training [13/16] Loss: 0.00448 +Epoch [3179/4000] Training [14/16] Loss: 0.00314 +Epoch [3179/4000] Training [15/16] Loss: 0.00276 +Epoch [3179/4000] Training [16/16] Loss: 0.00231 +Epoch [3179/4000] Training metric {'Train/mean dice_metric': 0.9983636140823364, 'Train/mean miou_metric': 0.9964568614959717, 'Train/mean f1': 0.9935358166694641, 'Train/mean precision': 0.9890708923339844, 'Train/mean recall': 0.9980412721633911, 'Train/mean hd95_metric': 0.7025666236877441} +Epoch [3179/4000] Validation [1/4] Loss: 0.41808 focal_loss 0.35216 dice_loss 0.06592 +Epoch [3179/4000] Validation [2/4] Loss: 0.41005 focal_loss 0.30308 dice_loss 0.10697 +Epoch [3179/4000] Validation [3/4] Loss: 0.57083 focal_loss 0.47122 dice_loss 0.09961 +Epoch [3179/4000] Validation [4/4] Loss: 0.43848 focal_loss 0.32564 dice_loss 0.11284 +Epoch [3179/4000] Validation metric {'Val/mean dice_metric': 0.9732414484024048, 'Val/mean miou_metric': 0.9585987329483032, 'Val/mean f1': 0.9757843613624573, 'Val/mean precision': 0.973257839679718, 'Val/mean recall': 0.9783240556716919, 'Val/mean hd95_metric': 5.1670823097229} +Cheakpoint... +Epoch [3179/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732414484024048, 'Val/mean miou_metric': 0.9585987329483032, 'Val/mean f1': 0.9757843613624573, 'Val/mean precision': 0.973257839679718, 'Val/mean recall': 0.9783240556716919, 'Val/mean hd95_metric': 5.1670823097229} +Epoch [3180/4000] Training [1/16] Loss: 0.00200 +Epoch [3180/4000] Training [2/16] Loss: 0.00403 +Epoch [3180/4000] Training [3/16] Loss: 0.00245 +Epoch [3180/4000] Training [4/16] Loss: 0.00221 +Epoch [3180/4000] Training [5/16] Loss: 0.00198 +Epoch [3180/4000] Training [6/16] Loss: 0.00360 +Epoch [3180/4000] Training [7/16] Loss: 0.00345 +Epoch [3180/4000] Training [8/16] Loss: 0.00317 +Epoch [3180/4000] Training [9/16] Loss: 0.00302 +Epoch [3180/4000] Training [10/16] Loss: 0.00249 +Epoch [3180/4000] Training [11/16] Loss: 0.00198 +Epoch [3180/4000] Training [12/16] Loss: 0.00323 +Epoch [3180/4000] Training [13/16] Loss: 0.00317 +Epoch [3180/4000] Training [14/16] Loss: 0.00269 +Epoch [3180/4000] Training [15/16] Loss: 0.00401 +Epoch [3180/4000] Training [16/16] Loss: 0.00369 +Epoch [3180/4000] Training metric {'Train/mean dice_metric': 0.9983516931533813, 'Train/mean miou_metric': 0.9964356422424316, 'Train/mean f1': 0.9934994578361511, 'Train/mean precision': 0.9889200925827026, 'Train/mean recall': 0.998121440410614, 'Train/mean hd95_metric': 0.7211213707923889} +Epoch [3180/4000] Validation [1/4] Loss: 0.37756 focal_loss 0.31437 dice_loss 0.06319 +Epoch [3180/4000] Validation [2/4] Loss: 1.16078 focal_loss 0.96598 dice_loss 0.19480 +Epoch [3180/4000] Validation [3/4] Loss: 0.50639 focal_loss 0.41697 dice_loss 0.08941 +Epoch [3180/4000] Validation [4/4] Loss: 0.45311 focal_loss 0.34964 dice_loss 0.10347 +Epoch [3180/4000] Validation metric {'Val/mean dice_metric': 0.9739570617675781, 'Val/mean miou_metric': 0.9599097967147827, 'Val/mean f1': 0.9762911200523376, 'Val/mean precision': 0.9742990136146545, 'Val/mean recall': 0.9782912731170654, 'Val/mean hd95_metric': 4.693340301513672} +Cheakpoint... +Epoch [3180/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739570617675781, 'Val/mean miou_metric': 0.9599097967147827, 'Val/mean f1': 0.9762911200523376, 'Val/mean precision': 0.9742990136146545, 'Val/mean recall': 0.9782912731170654, 'Val/mean hd95_metric': 4.693340301513672} +Epoch [3181/4000] Training [1/16] Loss: 0.00270 +Epoch [3181/4000] Training [2/16] Loss: 0.00173 +Epoch [3181/4000] Training [3/16] Loss: 0.00228 +Epoch [3181/4000] Training [4/16] Loss: 0.00304 +Epoch [3181/4000] Training [5/16] Loss: 0.00406 +Epoch [3181/4000] Training [6/16] Loss: 0.00349 +Epoch [3181/4000] Training [7/16] Loss: 0.00328 +Epoch [3181/4000] Training [8/16] Loss: 0.00297 +Epoch [3181/4000] Training [9/16] Loss: 0.00323 +Epoch [3181/4000] Training [10/16] Loss: 0.00423 +Epoch [3181/4000] Training [11/16] Loss: 0.00295 +Epoch [3181/4000] Training [12/16] Loss: 0.00232 +Epoch [3181/4000] Training [13/16] Loss: 0.00221 +Epoch [3181/4000] Training [14/16] Loss: 0.00341 +Epoch [3181/4000] Training [15/16] Loss: 0.00237 +Epoch [3181/4000] Training [16/16] Loss: 0.00246 +Epoch [3181/4000] Training metric {'Train/mean dice_metric': 0.9983364939689636, 'Train/mean miou_metric': 0.9963890314102173, 'Train/mean f1': 0.9933023452758789, 'Train/mean precision': 0.9886647462844849, 'Train/mean recall': 0.9979836344718933, 'Train/mean hd95_metric': 0.6954378485679626} +Epoch [3181/4000] Validation [1/4] Loss: 0.39141 focal_loss 0.32627 dice_loss 0.06514 +Epoch [3181/4000] Validation [2/4] Loss: 0.60434 focal_loss 0.44077 dice_loss 0.16357 +Epoch [3181/4000] Validation [3/4] Loss: 0.55564 focal_loss 0.45625 dice_loss 0.09939 +Epoch [3181/4000] Validation [4/4] Loss: 0.41509 focal_loss 0.31173 dice_loss 0.10336 +Epoch [3181/4000] Validation metric {'Val/mean dice_metric': 0.9730374217033386, 'Val/mean miou_metric': 0.9588285684585571, 'Val/mean f1': 0.9755761027336121, 'Val/mean precision': 0.9735751152038574, 'Val/mean recall': 0.9775853753089905, 'Val/mean hd95_metric': 4.938620090484619} +Cheakpoint... +Epoch [3181/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730374217033386, 'Val/mean miou_metric': 0.9588285684585571, 'Val/mean f1': 0.9755761027336121, 'Val/mean precision': 0.9735751152038574, 'Val/mean recall': 0.9775853753089905, 'Val/mean hd95_metric': 4.938620090484619} +Epoch [3182/4000] Training [1/16] Loss: 0.00449 +Epoch [3182/4000] Training [2/16] Loss: 0.00189 +Epoch [3182/4000] Training [3/16] Loss: 0.00267 +Epoch [3182/4000] Training [4/16] Loss: 0.00272 +Epoch [3182/4000] Training [5/16] Loss: 0.00365 +Epoch [3182/4000] Training [6/16] Loss: 0.00236 +Epoch [3182/4000] Training [7/16] Loss: 0.00282 +Epoch [3182/4000] Training [8/16] Loss: 0.00228 +Epoch [3182/4000] Training [9/16] Loss: 0.00231 +Epoch [3182/4000] Training [10/16] Loss: 0.00268 +Epoch [3182/4000] Training [11/16] Loss: 0.00393 +Epoch [3182/4000] Training [12/16] Loss: 0.00354 +Epoch [3182/4000] Training [13/16] Loss: 0.00290 +Epoch [3182/4000] Training [14/16] Loss: 0.00218 +Epoch [3182/4000] Training [15/16] Loss: 0.00186 +Epoch [3182/4000] Training [16/16] Loss: 0.00310 +Epoch [3182/4000] Training metric {'Train/mean dice_metric': 0.9983669519424438, 'Train/mean miou_metric': 0.9964450597763062, 'Train/mean f1': 0.9932664632797241, 'Train/mean precision': 0.9885203242301941, 'Train/mean recall': 0.9980583786964417, 'Train/mean hd95_metric': 0.7022734880447388} +Epoch [3182/4000] Validation [1/4] Loss: 0.39888 focal_loss 0.33148 dice_loss 0.06740 +Epoch [3182/4000] Validation [2/4] Loss: 0.39539 focal_loss 0.29153 dice_loss 0.10386 +Epoch [3182/4000] Validation [3/4] Loss: 0.52411 focal_loss 0.43424 dice_loss 0.08987 +Epoch [3182/4000] Validation [4/4] Loss: 0.34624 focal_loss 0.25610 dice_loss 0.09014 +Epoch [3182/4000] Validation metric {'Val/mean dice_metric': 0.9736772775650024, 'Val/mean miou_metric': 0.9594582319259644, 'Val/mean f1': 0.9760388731956482, 'Val/mean precision': 0.973362386226654, 'Val/mean recall': 0.9787302017211914, 'Val/mean hd95_metric': 5.40593957901001} +Cheakpoint... +Epoch [3182/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736772775650024, 'Val/mean miou_metric': 0.9594582319259644, 'Val/mean f1': 0.9760388731956482, 'Val/mean precision': 0.973362386226654, 'Val/mean recall': 0.9787302017211914, 'Val/mean hd95_metric': 5.40593957901001} +Epoch [3183/4000] Training [1/16] Loss: 0.00430 +Epoch [3183/4000] Training [2/16] Loss: 0.00361 +Epoch [3183/4000] Training [3/16] Loss: 0.00287 +Epoch [3183/4000] Training [4/16] Loss: 0.00304 +Epoch [3183/4000] Training [5/16] Loss: 0.00274 +Epoch [3183/4000] Training [6/16] Loss: 0.00229 +Epoch [3183/4000] Training [7/16] Loss: 0.00234 +Epoch [3183/4000] Training [8/16] Loss: 0.00285 +Epoch [3183/4000] Training [9/16] Loss: 0.00216 +Epoch [3183/4000] Training [10/16] Loss: 0.00298 +Epoch [3183/4000] Training [11/16] Loss: 0.00252 +Epoch [3183/4000] Training [12/16] Loss: 0.00336 +Epoch [3183/4000] Training [13/16] Loss: 0.00374 +Epoch [3183/4000] Training [14/16] Loss: 0.00273 +Epoch [3183/4000] Training [15/16] Loss: 0.00297 +Epoch [3183/4000] Training [16/16] Loss: 0.00230 +Epoch [3183/4000] Training metric {'Train/mean dice_metric': 0.9983918070793152, 'Train/mean miou_metric': 0.9964966773986816, 'Train/mean f1': 0.9932553172111511, 'Train/mean precision': 0.9884517788887024, 'Train/mean recall': 0.9981058239936829, 'Train/mean hd95_metric': 0.68869948387146} +Epoch [3183/4000] Validation [1/4] Loss: 0.37542 focal_loss 0.31178 dice_loss 0.06364 +Epoch [3183/4000] Validation [2/4] Loss: 0.41873 focal_loss 0.31033 dice_loss 0.10840 +Epoch [3183/4000] Validation [3/4] Loss: 0.51986 focal_loss 0.42788 dice_loss 0.09198 +Epoch [3183/4000] Validation [4/4] Loss: 0.35223 focal_loss 0.26170 dice_loss 0.09053 +Epoch [3183/4000] Validation metric {'Val/mean dice_metric': 0.97259920835495, 'Val/mean miou_metric': 0.959026038646698, 'Val/mean f1': 0.9758378863334656, 'Val/mean precision': 0.9742143154144287, 'Val/mean recall': 0.9774667620658875, 'Val/mean hd95_metric': 4.991657257080078} +Cheakpoint... +Epoch [3183/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97259920835495, 'Val/mean miou_metric': 0.959026038646698, 'Val/mean f1': 0.9758378863334656, 'Val/mean precision': 0.9742143154144287, 'Val/mean recall': 0.9774667620658875, 'Val/mean hd95_metric': 4.991657257080078} +Epoch [3184/4000] Training [1/16] Loss: 0.00197 +Epoch [3184/4000] Training [2/16] Loss: 0.00259 +Epoch [3184/4000] Training [3/16] Loss: 0.00333 +Epoch [3184/4000] Training [4/16] Loss: 0.00271 +Epoch [3184/4000] Training [5/16] Loss: 0.00319 +Epoch [3184/4000] Training [6/16] Loss: 0.00310 +Epoch [3184/4000] Training [7/16] Loss: 0.00314 +Epoch [3184/4000] Training [8/16] Loss: 0.00256 +Epoch [3184/4000] Training [9/16] Loss: 0.00418 +Epoch [3184/4000] Training [10/16] Loss: 0.00286 +Epoch [3184/4000] Training [11/16] Loss: 0.00288 +Epoch [3184/4000] Training [12/16] Loss: 0.00275 +Epoch [3184/4000] Training [13/16] Loss: 0.00368 +Epoch [3184/4000] Training [14/16] Loss: 0.00202 +Epoch [3184/4000] Training [15/16] Loss: 0.00251 +Epoch [3184/4000] Training [16/16] Loss: 0.00317 +Epoch [3184/4000] Training metric {'Train/mean dice_metric': 0.9984081387519836, 'Train/mean miou_metric': 0.9965450763702393, 'Train/mean f1': 0.9935730695724487, 'Train/mean precision': 0.9890632033348083, 'Train/mean recall': 0.9981241822242737, 'Train/mean hd95_metric': 0.741043210029602} +Epoch [3184/4000] Validation [1/4] Loss: 0.35050 focal_loss 0.28908 dice_loss 0.06142 +Epoch [3184/4000] Validation [2/4] Loss: 0.39632 focal_loss 0.28932 dice_loss 0.10700 +Epoch [3184/4000] Validation [3/4] Loss: 0.25846 focal_loss 0.19561 dice_loss 0.06285 +Epoch [3184/4000] Validation [4/4] Loss: 0.42891 focal_loss 0.32064 dice_loss 0.10828 +Epoch [3184/4000] Validation metric {'Val/mean dice_metric': 0.9751958847045898, 'Val/mean miou_metric': 0.9608637094497681, 'Val/mean f1': 0.9769536852836609, 'Val/mean precision': 0.9743970036506653, 'Val/mean recall': 0.9795238375663757, 'Val/mean hd95_metric': 4.7326765060424805} +Cheakpoint... +Epoch [3184/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751958847045898, 'Val/mean miou_metric': 0.9608637094497681, 'Val/mean f1': 0.9769536852836609, 'Val/mean precision': 0.9743970036506653, 'Val/mean recall': 0.9795238375663757, 'Val/mean hd95_metric': 4.7326765060424805} +Epoch [3185/4000] Training [1/16] Loss: 0.00183 +Epoch [3185/4000] Training [2/16] Loss: 0.00255 +Epoch [3185/4000] Training [3/16] Loss: 0.00352 +Epoch [3185/4000] Training [4/16] Loss: 0.00245 +Epoch [3185/4000] Training [5/16] Loss: 0.00301 +Epoch [3185/4000] Training [6/16] Loss: 0.00273 +Epoch [3185/4000] Training [7/16] Loss: 0.00240 +Epoch [3185/4000] Training [8/16] Loss: 0.00368 +Epoch [3185/4000] Training [9/16] Loss: 0.00392 +Epoch [3185/4000] Training [10/16] Loss: 0.00295 +Epoch [3185/4000] Training [11/16] Loss: 0.00266 +Epoch [3185/4000] Training [12/16] Loss: 0.00257 +Epoch [3185/4000] Training [13/16] Loss: 0.00325 +Epoch [3185/4000] Training [14/16] Loss: 0.00293 +Epoch [3185/4000] Training [15/16] Loss: 0.00232 +Epoch [3185/4000] Training [16/16] Loss: 0.00333 +Epoch [3185/4000] Training metric {'Train/mean dice_metric': 0.9984704852104187, 'Train/mean miou_metric': 0.9966623783111572, 'Train/mean f1': 0.993491530418396, 'Train/mean precision': 0.9889524579048157, 'Train/mean recall': 0.9980725049972534, 'Train/mean hd95_metric': 0.6653874516487122} +Epoch [3185/4000] Validation [1/4] Loss: 0.38223 focal_loss 0.31892 dice_loss 0.06331 +Epoch [3185/4000] Validation [2/4] Loss: 0.38302 focal_loss 0.28207 dice_loss 0.10095 +Epoch [3185/4000] Validation [3/4] Loss: 0.51245 focal_loss 0.42324 dice_loss 0.08921 +Epoch [3185/4000] Validation [4/4] Loss: 0.45563 focal_loss 0.34595 dice_loss 0.10968 +Epoch [3185/4000] Validation metric {'Val/mean dice_metric': 0.9743812680244446, 'Val/mean miou_metric': 0.9601435661315918, 'Val/mean f1': 0.9763675332069397, 'Val/mean precision': 0.9737688302993774, 'Val/mean recall': 0.9789801239967346, 'Val/mean hd95_metric': 4.836118698120117} +Cheakpoint... +Epoch [3185/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743812680244446, 'Val/mean miou_metric': 0.9601435661315918, 'Val/mean f1': 0.9763675332069397, 'Val/mean precision': 0.9737688302993774, 'Val/mean recall': 0.9789801239967346, 'Val/mean hd95_metric': 4.836118698120117} +Epoch [3186/4000] Training [1/16] Loss: 0.00265 +Epoch [3186/4000] Training [2/16] Loss: 0.00335 +Epoch [3186/4000] Training [3/16] Loss: 0.00341 +Epoch [3186/4000] Training [4/16] Loss: 0.00231 +Epoch [3186/4000] Training [5/16] Loss: 0.00207 +Epoch [3186/4000] Training [6/16] Loss: 0.00275 +Epoch [3186/4000] Training [7/16] Loss: 0.00219 +Epoch [3186/4000] Training [8/16] Loss: 0.00232 +Epoch [3186/4000] Training [9/16] Loss: 0.00318 +Epoch [3186/4000] Training [10/16] Loss: 0.00242 +Epoch [3186/4000] Training [11/16] Loss: 0.00275 +Epoch [3186/4000] Training [12/16] Loss: 0.00267 +Epoch [3186/4000] Training [13/16] Loss: 0.00230 +Epoch [3186/4000] Training [14/16] Loss: 0.00414 +Epoch [3186/4000] Training [15/16] Loss: 0.00251 +Epoch [3186/4000] Training [16/16] Loss: 0.00350 +Epoch [3186/4000] Training metric {'Train/mean dice_metric': 0.9984726905822754, 'Train/mean miou_metric': 0.996676504611969, 'Train/mean f1': 0.9935500621795654, 'Train/mean precision': 0.9889715909957886, 'Train/mean recall': 0.9981711506843567, 'Train/mean hd95_metric': 0.70139479637146} +Epoch [3186/4000] Validation [1/4] Loss: 0.39097 focal_loss 0.32643 dice_loss 0.06455 +Epoch [3186/4000] Validation [2/4] Loss: 0.40994 focal_loss 0.30413 dice_loss 0.10581 +Epoch [3186/4000] Validation [3/4] Loss: 0.52040 focal_loss 0.42352 dice_loss 0.09687 +Epoch [3186/4000] Validation [4/4] Loss: 0.31438 focal_loss 0.23156 dice_loss 0.08282 +Epoch [3186/4000] Validation metric {'Val/mean dice_metric': 0.9754416346549988, 'Val/mean miou_metric': 0.9610761404037476, 'Val/mean f1': 0.9762871861457825, 'Val/mean precision': 0.9739398956298828, 'Val/mean recall': 0.9786458015441895, 'Val/mean hd95_metric': 4.599584579467773} +Cheakpoint... +Epoch [3186/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754416346549988, 'Val/mean miou_metric': 0.9610761404037476, 'Val/mean f1': 0.9762871861457825, 'Val/mean precision': 0.9739398956298828, 'Val/mean recall': 0.9786458015441895, 'Val/mean hd95_metric': 4.599584579467773} +Epoch [3187/4000] Training [1/16] Loss: 0.00182 +Epoch [3187/4000] Training [2/16] Loss: 0.00183 +Epoch [3187/4000] Training [3/16] Loss: 0.00246 +Epoch [3187/4000] Training [4/16] Loss: 0.00196 +Epoch [3187/4000] Training [5/16] Loss: 0.00387 +Epoch [3187/4000] Training [6/16] Loss: 0.00293 +Epoch [3187/4000] Training [7/16] Loss: 0.00244 +Epoch [3187/4000] Training [8/16] Loss: 0.00170 +Epoch [3187/4000] Training [9/16] Loss: 0.00504 +Epoch [3187/4000] Training [10/16] Loss: 0.00413 +Epoch [3187/4000] Training [11/16] Loss: 0.00332 +Epoch [3187/4000] Training [12/16] Loss: 0.00280 +Epoch [3187/4000] Training [13/16] Loss: 0.00360 +Epoch [3187/4000] Training [14/16] Loss: 0.00387 +Epoch [3187/4000] Training [15/16] Loss: 0.00264 +Epoch [3187/4000] Training [16/16] Loss: 0.00273 +Epoch [3187/4000] Training metric {'Train/mean dice_metric': 0.998366117477417, 'Train/mean miou_metric': 0.9964619874954224, 'Train/mean f1': 0.9934973120689392, 'Train/mean precision': 0.9889469146728516, 'Train/mean recall': 0.9980898499488831, 'Train/mean hd95_metric': 0.6996369361877441} +Epoch [3187/4000] Validation [1/4] Loss: 0.35966 focal_loss 0.29732 dice_loss 0.06233 +Epoch [3187/4000] Validation [2/4] Loss: 0.97835 focal_loss 0.78539 dice_loss 0.19296 +Epoch [3187/4000] Validation [3/4] Loss: 0.49532 focal_loss 0.40657 dice_loss 0.08875 +Epoch [3187/4000] Validation [4/4] Loss: 0.42501 focal_loss 0.31254 dice_loss 0.11247 +Epoch [3187/4000] Validation metric {'Val/mean dice_metric': 0.9719417691230774, 'Val/mean miou_metric': 0.9583330154418945, 'Val/mean f1': 0.9757362008094788, 'Val/mean precision': 0.9742782711982727, 'Val/mean recall': 0.9771984815597534, 'Val/mean hd95_metric': 5.134235858917236} +Cheakpoint... +Epoch [3187/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719417691230774, 'Val/mean miou_metric': 0.9583330154418945, 'Val/mean f1': 0.9757362008094788, 'Val/mean precision': 0.9742782711982727, 'Val/mean recall': 0.9771984815597534, 'Val/mean hd95_metric': 5.134235858917236} +Epoch [3188/4000] Training [1/16] Loss: 0.00340 +Epoch [3188/4000] Training [2/16] Loss: 0.00241 +Epoch [3188/4000] Training [3/16] Loss: 0.00217 +Epoch [3188/4000] Training [4/16] Loss: 0.00302 +Epoch [3188/4000] Training [5/16] Loss: 0.00223 +Epoch [3188/4000] Training [6/16] Loss: 0.00372 +Epoch [3188/4000] Training [7/16] Loss: 0.00406 +Epoch [3188/4000] Training [8/16] Loss: 0.00306 +Epoch [3188/4000] Training [9/16] Loss: 0.00256 +Epoch [3188/4000] Training [10/16] Loss: 0.00427 +Epoch [3188/4000] Training [11/16] Loss: 0.00266 +Epoch [3188/4000] Training [12/16] Loss: 0.00283 +Epoch [3188/4000] Training [13/16] Loss: 0.00255 +Epoch [3188/4000] Training [14/16] Loss: 0.00346 +Epoch [3188/4000] Training [15/16] Loss: 0.00356 +Epoch [3188/4000] Training [16/16] Loss: 0.00218 +Epoch [3188/4000] Training metric {'Train/mean dice_metric': 0.9983558654785156, 'Train/mean miou_metric': 0.9964284300804138, 'Train/mean f1': 0.9933339953422546, 'Train/mean precision': 0.9886850714683533, 'Train/mean recall': 0.9980269074440002, 'Train/mean hd95_metric': 0.7201448678970337} +Epoch [3188/4000] Validation [1/4] Loss: 0.41493 focal_loss 0.35157 dice_loss 0.06336 +Epoch [3188/4000] Validation [2/4] Loss: 0.75126 focal_loss 0.56909 dice_loss 0.18218 +Epoch [3188/4000] Validation [3/4] Loss: 0.28101 focal_loss 0.21394 dice_loss 0.06707 +Epoch [3188/4000] Validation [4/4] Loss: 0.36777 focal_loss 0.26344 dice_loss 0.10434 +Epoch [3188/4000] Validation metric {'Val/mean dice_metric': 0.9725068211555481, 'Val/mean miou_metric': 0.9590696096420288, 'Val/mean f1': 0.9759040474891663, 'Val/mean precision': 0.9747058749198914, 'Val/mean recall': 0.9771051406860352, 'Val/mean hd95_metric': 5.314507961273193} +Cheakpoint... +Epoch [3188/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725068211555481, 'Val/mean miou_metric': 0.9590696096420288, 'Val/mean f1': 0.9759040474891663, 'Val/mean precision': 0.9747058749198914, 'Val/mean recall': 0.9771051406860352, 'Val/mean hd95_metric': 5.314507961273193} +Epoch [3189/4000] Training [1/16] Loss: 0.00428 +Epoch [3189/4000] Training [2/16] Loss: 0.00237 +Epoch [3189/4000] Training [3/16] Loss: 0.00293 +Epoch [3189/4000] Training [4/16] Loss: 0.00248 +Epoch [3189/4000] Training [5/16] Loss: 0.00360 +Epoch [3189/4000] Training [6/16] Loss: 0.00262 +Epoch [3189/4000] Training [7/16] Loss: 0.00276 +Epoch [3189/4000] Training [8/16] Loss: 0.00233 +Epoch [3189/4000] Training [9/16] Loss: 0.00363 +Epoch [3189/4000] Training [10/16] Loss: 0.00246 +Epoch [3189/4000] Training [11/16] Loss: 0.00267 +Epoch [3189/4000] Training [12/16] Loss: 0.00272 +Epoch [3189/4000] Training [13/16] Loss: 0.00401 +Epoch [3189/4000] Training [14/16] Loss: 0.00330 +Epoch [3189/4000] Training [15/16] Loss: 0.00241 +Epoch [3189/4000] Training [16/16] Loss: 0.00195 +Epoch [3189/4000] Training metric {'Train/mean dice_metric': 0.9983224868774414, 'Train/mean miou_metric': 0.9963764548301697, 'Train/mean f1': 0.9934868216514587, 'Train/mean precision': 0.9889464974403381, 'Train/mean recall': 0.9980689883232117, 'Train/mean hd95_metric': 0.7042267322540283} +Epoch [3189/4000] Validation [1/4] Loss: 0.35681 focal_loss 0.29538 dice_loss 0.06143 +Epoch [3189/4000] Validation [2/4] Loss: 0.84908 focal_loss 0.64793 dice_loss 0.20116 +Epoch [3189/4000] Validation [3/4] Loss: 0.51629 focal_loss 0.42413 dice_loss 0.09217 +Epoch [3189/4000] Validation [4/4] Loss: 0.24463 focal_loss 0.16706 dice_loss 0.07756 +Epoch [3189/4000] Validation metric {'Val/mean dice_metric': 0.9732421040534973, 'Val/mean miou_metric': 0.9590282440185547, 'Val/mean f1': 0.9758227467536926, 'Val/mean precision': 0.9739443063735962, 'Val/mean recall': 0.9777085185050964, 'Val/mean hd95_metric': 4.833431243896484} +Cheakpoint... +Epoch [3189/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732421040534973, 'Val/mean miou_metric': 0.9590282440185547, 'Val/mean f1': 0.9758227467536926, 'Val/mean precision': 0.9739443063735962, 'Val/mean recall': 0.9777085185050964, 'Val/mean hd95_metric': 4.833431243896484} +Epoch [3190/4000] Training [1/16] Loss: 0.00420 +Epoch [3190/4000] Training [2/16] Loss: 0.00204 +Epoch [3190/4000] Training [3/16] Loss: 0.00215 +Epoch [3190/4000] Training [4/16] Loss: 0.00239 +Epoch [3190/4000] Training [5/16] Loss: 0.00232 +Epoch [3190/4000] Training [6/16] Loss: 0.00256 +Epoch [3190/4000] Training [7/16] Loss: 0.00237 +Epoch [3190/4000] Training [8/16] Loss: 0.00336 +Epoch [3190/4000] Training [9/16] Loss: 0.00387 +Epoch [3190/4000] Training [10/16] Loss: 0.00270 +Epoch [3190/4000] Training [11/16] Loss: 0.00302 +Epoch [3190/4000] Training [12/16] Loss: 0.00235 +Epoch [3190/4000] Training [13/16] Loss: 0.00328 +Epoch [3190/4000] Training [14/16] Loss: 0.00225 +Epoch [3190/4000] Training [15/16] Loss: 0.00331 +Epoch [3190/4000] Training [16/16] Loss: 0.00240 +Epoch [3190/4000] Training metric {'Train/mean dice_metric': 0.9984256625175476, 'Train/mean miou_metric': 0.9965748190879822, 'Train/mean f1': 0.993466854095459, 'Train/mean precision': 0.9888785481452942, 'Train/mean recall': 0.9980979561805725, 'Train/mean hd95_metric': 0.6729767322540283} +Epoch [3190/4000] Validation [1/4] Loss: 0.37783 focal_loss 0.31546 dice_loss 0.06237 +Epoch [3190/4000] Validation [2/4] Loss: 0.66167 focal_loss 0.49212 dice_loss 0.16955 +Epoch [3190/4000] Validation [3/4] Loss: 0.51993 focal_loss 0.42791 dice_loss 0.09203 +Epoch [3190/4000] Validation [4/4] Loss: 0.33053 focal_loss 0.23420 dice_loss 0.09634 +Epoch [3190/4000] Validation metric {'Val/mean dice_metric': 0.9759731292724609, 'Val/mean miou_metric': 0.9614076614379883, 'Val/mean f1': 0.9764721393585205, 'Val/mean precision': 0.9738661050796509, 'Val/mean recall': 0.9790921807289124, 'Val/mean hd95_metric': 4.877659797668457} +Cheakpoint... +Epoch [3190/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759731292724609, 'Val/mean miou_metric': 0.9614076614379883, 'Val/mean f1': 0.9764721393585205, 'Val/mean precision': 0.9738661050796509, 'Val/mean recall': 0.9790921807289124, 'Val/mean hd95_metric': 4.877659797668457} +Epoch [3191/4000] Training [1/16] Loss: 0.00234 +Epoch [3191/4000] Training [2/16] Loss: 0.00290 +Epoch [3191/4000] Training [3/16] Loss: 0.00224 +Epoch [3191/4000] Training [4/16] Loss: 0.00260 +Epoch [3191/4000] Training [5/16] Loss: 0.00229 +Epoch [3191/4000] Training [6/16] Loss: 0.00306 +Epoch [3191/4000] Training [7/16] Loss: 0.00273 +Epoch [3191/4000] Training [8/16] Loss: 0.00444 +Epoch [3191/4000] Training [9/16] Loss: 0.00223 +Epoch [3191/4000] Training [10/16] Loss: 0.00426 +Epoch [3191/4000] Training [11/16] Loss: 0.00310 +Epoch [3191/4000] Training [12/16] Loss: 0.00269 +Epoch [3191/4000] Training [13/16] Loss: 0.00225 +Epoch [3191/4000] Training [14/16] Loss: 0.00274 +Epoch [3191/4000] Training [15/16] Loss: 0.00249 +Epoch [3191/4000] Training [16/16] Loss: 0.00381 +Epoch [3191/4000] Training metric {'Train/mean dice_metric': 0.9984017014503479, 'Train/mean miou_metric': 0.9965347051620483, 'Train/mean f1': 0.9935600161552429, 'Train/mean precision': 0.9890214204788208, 'Train/mean recall': 0.9981404542922974, 'Train/mean hd95_metric': 0.7085236310958862} +Epoch [3191/4000] Validation [1/4] Loss: 0.37044 focal_loss 0.30928 dice_loss 0.06116 +Epoch [3191/4000] Validation [2/4] Loss: 0.41835 focal_loss 0.31516 dice_loss 0.10319 +Epoch [3191/4000] Validation [3/4] Loss: 0.52375 focal_loss 0.43094 dice_loss 0.09281 +Epoch [3191/4000] Validation [4/4] Loss: 0.31868 focal_loss 0.22166 dice_loss 0.09702 +Epoch [3191/4000] Validation metric {'Val/mean dice_metric': 0.9735338091850281, 'Val/mean miou_metric': 0.9595796465873718, 'Val/mean f1': 0.9761191010475159, 'Val/mean precision': 0.9735089540481567, 'Val/mean recall': 0.978743314743042, 'Val/mean hd95_metric': 5.294730186462402} +Cheakpoint... +Epoch [3191/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735338091850281, 'Val/mean miou_metric': 0.9595796465873718, 'Val/mean f1': 0.9761191010475159, 'Val/mean precision': 0.9735089540481567, 'Val/mean recall': 0.978743314743042, 'Val/mean hd95_metric': 5.294730186462402} +Epoch [3192/4000] Training [1/16] Loss: 0.00260 +Epoch [3192/4000] Training [2/16] Loss: 0.00289 +Epoch [3192/4000] Training [3/16] Loss: 0.00330 +Epoch [3192/4000] Training [4/16] Loss: 0.00228 +Epoch [3192/4000] Training [5/16] Loss: 0.00358 +Epoch [3192/4000] Training [6/16] Loss: 0.00185 +Epoch [3192/4000] Training [7/16] Loss: 0.00283 +Epoch [3192/4000] Training [8/16] Loss: 0.00557 +Epoch [3192/4000] Training [9/16] Loss: 0.00296 +Epoch [3192/4000] Training [10/16] Loss: 0.00274 +Epoch [3192/4000] Training [11/16] Loss: 0.00285 +Epoch [3192/4000] Training [12/16] Loss: 0.00478 +Epoch [3192/4000] Training [13/16] Loss: 0.00297 +Epoch [3192/4000] Training [14/16] Loss: 0.00358 +Epoch [3192/4000] Training [15/16] Loss: 0.00279 +Epoch [3192/4000] Training [16/16] Loss: 0.00234 +Epoch [3192/4000] Training metric {'Train/mean dice_metric': 0.9984338283538818, 'Train/mean miou_metric': 0.9966004490852356, 'Train/mean f1': 0.9935881495475769, 'Train/mean precision': 0.989055335521698, 'Train/mean recall': 0.9981626868247986, 'Train/mean hd95_metric': 0.6982697248458862} +Epoch [3192/4000] Validation [1/4] Loss: 0.35931 focal_loss 0.29683 dice_loss 0.06249 +Epoch [3192/4000] Validation [2/4] Loss: 1.25931 focal_loss 1.06284 dice_loss 0.19647 +Epoch [3192/4000] Validation [3/4] Loss: 0.52482 focal_loss 0.42975 dice_loss 0.09508 +Epoch [3192/4000] Validation [4/4] Loss: 0.39744 focal_loss 0.29358 dice_loss 0.10386 +Epoch [3192/4000] Validation metric {'Val/mean dice_metric': 0.9728643298149109, 'Val/mean miou_metric': 0.9587686657905579, 'Val/mean f1': 0.9755566120147705, 'Val/mean precision': 0.9738062620162964, 'Val/mean recall': 0.977313220500946, 'Val/mean hd95_metric': 5.04742956161499} +Cheakpoint... +Epoch [3192/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728643298149109, 'Val/mean miou_metric': 0.9587686657905579, 'Val/mean f1': 0.9755566120147705, 'Val/mean precision': 0.9738062620162964, 'Val/mean recall': 0.977313220500946, 'Val/mean hd95_metric': 5.04742956161499} +Epoch [3193/4000] Training [1/16] Loss: 0.00406 +Epoch [3193/4000] Training [2/16] Loss: 0.00296 +Epoch [3193/4000] Training [3/16] Loss: 0.00255 +Epoch [3193/4000] Training [4/16] Loss: 0.00246 +Epoch [3193/4000] Training [5/16] Loss: 0.00312 +Epoch [3193/4000] Training [6/16] Loss: 0.00322 +Epoch [3193/4000] Training [7/16] Loss: 0.00334 +Epoch [3193/4000] Training [8/16] Loss: 0.00327 +Epoch [3193/4000] Training [9/16] Loss: 0.00279 +Epoch [3193/4000] Training [10/16] Loss: 0.00440 +Epoch [3193/4000] Training [11/16] Loss: 0.00211 +Epoch [3193/4000] Training [12/16] Loss: 0.00191 +Epoch [3193/4000] Training [13/16] Loss: 0.00322 +Epoch [3193/4000] Training [14/16] Loss: 0.00329 +Epoch [3193/4000] Training [15/16] Loss: 0.00288 +Epoch [3193/4000] Training [16/16] Loss: 0.00227 +Epoch [3193/4000] Training metric {'Train/mean dice_metric': 0.9984666109085083, 'Train/mean miou_metric': 0.9966520071029663, 'Train/mean f1': 0.9933080077171326, 'Train/mean precision': 0.9885966181755066, 'Train/mean recall': 0.9980644583702087, 'Train/mean hd95_metric': 0.6721256971359253} +Epoch [3193/4000] Validation [1/4] Loss: 0.36880 focal_loss 0.30680 dice_loss 0.06200 +Epoch [3193/4000] Validation [2/4] Loss: 0.94656 focal_loss 0.75552 dice_loss 0.19104 +Epoch [3193/4000] Validation [3/4] Loss: 0.48161 focal_loss 0.38894 dice_loss 0.09266 +Epoch [3193/4000] Validation [4/4] Loss: 0.32141 focal_loss 0.22053 dice_loss 0.10087 +Epoch [3193/4000] Validation metric {'Val/mean dice_metric': 0.9728007316589355, 'Val/mean miou_metric': 0.9596244692802429, 'Val/mean f1': 0.976327121257782, 'Val/mean precision': 0.9737519025802612, 'Val/mean recall': 0.9789159297943115, 'Val/mean hd95_metric': 4.870317459106445} +Cheakpoint... +Epoch [3193/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728007316589355, 'Val/mean miou_metric': 0.9596244692802429, 'Val/mean f1': 0.976327121257782, 'Val/mean precision': 0.9737519025802612, 'Val/mean recall': 0.9789159297943115, 'Val/mean hd95_metric': 4.870317459106445} +Epoch [3194/4000] Training [1/16] Loss: 0.00219 +Epoch [3194/4000] Training [2/16] Loss: 0.00307 +Epoch [3194/4000] Training [3/16] Loss: 0.00233 +Epoch [3194/4000] Training [4/16] Loss: 0.00299 +Epoch [3194/4000] Training [5/16] Loss: 0.00235 +Epoch [3194/4000] Training [6/16] Loss: 0.00301 +Epoch [3194/4000] Training [7/16] Loss: 0.00297 +Epoch [3194/4000] Training [8/16] Loss: 0.00292 +Epoch [3194/4000] Training [9/16] Loss: 0.00229 +Epoch [3194/4000] Training [10/16] Loss: 0.00281 +Epoch [3194/4000] Training [11/16] Loss: 0.00241 +Epoch [3194/4000] Training [12/16] Loss: 0.00342 +Epoch [3194/4000] Training [13/16] Loss: 0.00242 +Epoch [3194/4000] Training [14/16] Loss: 0.00275 +Epoch [3194/4000] Training [15/16] Loss: 0.00303 +Epoch [3194/4000] Training [16/16] Loss: 0.00271 +Epoch [3194/4000] Training metric {'Train/mean dice_metric': 0.9984571933746338, 'Train/mean miou_metric': 0.9966386556625366, 'Train/mean f1': 0.9934471249580383, 'Train/mean precision': 0.9888414144515991, 'Train/mean recall': 0.9980959892272949, 'Train/mean hd95_metric': 0.7063750624656677} +Epoch [3194/4000] Validation [1/4] Loss: 0.37523 focal_loss 0.31284 dice_loss 0.06239 +Epoch [3194/4000] Validation [2/4] Loss: 1.18921 focal_loss 0.99565 dice_loss 0.19357 +Epoch [3194/4000] Validation [3/4] Loss: 0.51708 focal_loss 0.42125 dice_loss 0.09583 +Epoch [3194/4000] Validation [4/4] Loss: 0.44736 focal_loss 0.33730 dice_loss 0.11006 +Epoch [3194/4000] Validation metric {'Val/mean dice_metric': 0.9725513458251953, 'Val/mean miou_metric': 0.9585859179496765, 'Val/mean f1': 0.9757073521614075, 'Val/mean precision': 0.9734798073768616, 'Val/mean recall': 0.9779450297355652, 'Val/mean hd95_metric': 5.216984272003174} +Cheakpoint... +Epoch [3194/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725513458251953, 'Val/mean miou_metric': 0.9585859179496765, 'Val/mean f1': 0.9757073521614075, 'Val/mean precision': 0.9734798073768616, 'Val/mean recall': 0.9779450297355652, 'Val/mean hd95_metric': 5.216984272003174} +Epoch [3195/4000] Training [1/16] Loss: 0.00300 +Epoch [3195/4000] Training [2/16] Loss: 0.00176 +Epoch [3195/4000] Training [3/16] Loss: 0.00252 +Epoch [3195/4000] Training [4/16] Loss: 0.00299 +Epoch [3195/4000] Training [5/16] Loss: 0.00236 +Epoch [3195/4000] Training [6/16] Loss: 0.00364 +Epoch [3195/4000] Training [7/16] Loss: 0.00305 +Epoch [3195/4000] Training [8/16] Loss: 0.00435 +Epoch [3195/4000] Training [9/16] Loss: 0.00341 +Epoch [3195/4000] Training [10/16] Loss: 0.00378 +Epoch [3195/4000] Training [11/16] Loss: 0.00337 +Epoch [3195/4000] Training [12/16] Loss: 0.00271 +Epoch [3195/4000] Training [13/16] Loss: 0.00292 +Epoch [3195/4000] Training [14/16] Loss: 0.00521 +Epoch [3195/4000] Training [15/16] Loss: 0.00235 +Epoch [3195/4000] Training [16/16] Loss: 0.00286 +Epoch [3195/4000] Training metric {'Train/mean dice_metric': 0.998346745967865, 'Train/mean miou_metric': 0.99639892578125, 'Train/mean f1': 0.9929277896881104, 'Train/mean precision': 0.9879063963890076, 'Train/mean recall': 0.9980005025863647, 'Train/mean hd95_metric': 0.7046029567718506} +Epoch [3195/4000] Validation [1/4] Loss: 0.45909 focal_loss 0.39025 dice_loss 0.06883 +Epoch [3195/4000] Validation [2/4] Loss: 0.42112 focal_loss 0.31538 dice_loss 0.10574 +Epoch [3195/4000] Validation [3/4] Loss: 0.55374 focal_loss 0.45342 dice_loss 0.10032 +Epoch [3195/4000] Validation [4/4] Loss: 0.48488 focal_loss 0.36361 dice_loss 0.12127 +Epoch [3195/4000] Validation metric {'Val/mean dice_metric': 0.9742463231086731, 'Val/mean miou_metric': 0.9595353007316589, 'Val/mean f1': 0.9757570624351501, 'Val/mean precision': 0.9730666279792786, 'Val/mean recall': 0.9784625172615051, 'Val/mean hd95_metric': 5.272948265075684} +Cheakpoint... +Epoch [3195/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742463231086731, 'Val/mean miou_metric': 0.9595353007316589, 'Val/mean f1': 0.9757570624351501, 'Val/mean precision': 0.9730666279792786, 'Val/mean recall': 0.9784625172615051, 'Val/mean hd95_metric': 5.272948265075684} +Epoch [3196/4000] Training [1/16] Loss: 0.00239 +Epoch [3196/4000] Training [2/16] Loss: 0.00242 +Epoch [3196/4000] Training [3/16] Loss: 0.00257 +Epoch [3196/4000] Training [4/16] Loss: 0.00300 +Epoch [3196/4000] Training [5/16] Loss: 0.00461 +Epoch [3196/4000] Training [6/16] Loss: 0.00389 +Epoch [3196/4000] Training [7/16] Loss: 0.00287 +Epoch [3196/4000] Training [8/16] Loss: 0.00262 +Epoch [3196/4000] Training [9/16] Loss: 0.00339 +Epoch [3196/4000] Training [10/16] Loss: 0.00279 +Epoch [3196/4000] Training [11/16] Loss: 0.00281 +Epoch [3196/4000] Training [12/16] Loss: 0.00345 +Epoch [3196/4000] Training [13/16] Loss: 0.00497 +Epoch [3196/4000] Training [14/16] Loss: 0.00292 +Epoch [3196/4000] Training [15/16] Loss: 0.00284 +Epoch [3196/4000] Training [16/16] Loss: 0.00295 +Epoch [3196/4000] Training metric {'Train/mean dice_metric': 0.9983630776405334, 'Train/mean miou_metric': 0.996440052986145, 'Train/mean f1': 0.993301510810852, 'Train/mean precision': 0.9885567426681519, 'Train/mean recall': 0.9980921745300293, 'Train/mean hd95_metric': 0.7007389068603516} +Epoch [3196/4000] Validation [1/4] Loss: 0.41133 focal_loss 0.34635 dice_loss 0.06497 +Epoch [3196/4000] Validation [2/4] Loss: 0.56201 focal_loss 0.40747 dice_loss 0.15454 +Epoch [3196/4000] Validation [3/4] Loss: 0.49503 focal_loss 0.40675 dice_loss 0.08828 +Epoch [3196/4000] Validation [4/4] Loss: 0.30874 focal_loss 0.22693 dice_loss 0.08181 +Epoch [3196/4000] Validation metric {'Val/mean dice_metric': 0.9719077944755554, 'Val/mean miou_metric': 0.9581013917922974, 'Val/mean f1': 0.9759078025817871, 'Val/mean precision': 0.9736029505729675, 'Val/mean recall': 0.9782236218452454, 'Val/mean hd95_metric': 4.981126308441162} +Cheakpoint... +Epoch [3196/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719077944755554, 'Val/mean miou_metric': 0.9581013917922974, 'Val/mean f1': 0.9759078025817871, 'Val/mean precision': 0.9736029505729675, 'Val/mean recall': 0.9782236218452454, 'Val/mean hd95_metric': 4.981126308441162} +Epoch [3197/4000] Training [1/16] Loss: 0.00222 +Epoch [3197/4000] Training [2/16] Loss: 0.00354 +Epoch [3197/4000] Training [3/16] Loss: 0.00226 +Epoch [3197/4000] Training [4/16] Loss: 0.00370 +Epoch [3197/4000] Training [5/16] Loss: 0.00270 +Epoch [3197/4000] Training [6/16] Loss: 0.00242 +Epoch [3197/4000] Training [7/16] Loss: 0.00308 +Epoch [3197/4000] Training [8/16] Loss: 0.00361 +Epoch [3197/4000] Training [9/16] Loss: 0.00305 +Epoch [3197/4000] Training [10/16] Loss: 0.00400 +Epoch [3197/4000] Training [11/16] Loss: 0.00415 +Epoch [3197/4000] Training [12/16] Loss: 0.00210 +Epoch [3197/4000] Training [13/16] Loss: 0.00298 +Epoch [3197/4000] Training [14/16] Loss: 0.00200 +Epoch [3197/4000] Training [15/16] Loss: 0.00381 +Epoch [3197/4000] Training [16/16] Loss: 0.00302 +Epoch [3197/4000] Training metric {'Train/mean dice_metric': 0.9983195066452026, 'Train/mean miou_metric': 0.9963696002960205, 'Train/mean f1': 0.9934436678886414, 'Train/mean precision': 0.9889123439788818, 'Train/mean recall': 0.9980167150497437, 'Train/mean hd95_metric': 0.6925356984138489} +Epoch [3197/4000] Validation [1/4] Loss: 0.35962 focal_loss 0.29746 dice_loss 0.06216 +Epoch [3197/4000] Validation [2/4] Loss: 0.72446 focal_loss 0.54295 dice_loss 0.18151 +Epoch [3197/4000] Validation [3/4] Loss: 0.47820 focal_loss 0.37819 dice_loss 0.10001 +Epoch [3197/4000] Validation [4/4] Loss: 0.40433 focal_loss 0.29681 dice_loss 0.10752 +Epoch [3197/4000] Validation metric {'Val/mean dice_metric': 0.9727321863174438, 'Val/mean miou_metric': 0.9586103558540344, 'Val/mean f1': 0.9758493900299072, 'Val/mean precision': 0.972429633140564, 'Val/mean recall': 0.9792933464050293, 'Val/mean hd95_metric': 5.612239360809326} +Cheakpoint... +Epoch [3197/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727321863174438, 'Val/mean miou_metric': 0.9586103558540344, 'Val/mean f1': 0.9758493900299072, 'Val/mean precision': 0.972429633140564, 'Val/mean recall': 0.9792933464050293, 'Val/mean hd95_metric': 5.612239360809326} +Epoch [3198/4000] Training [1/16] Loss: 0.00356 +Epoch [3198/4000] Training [2/16] Loss: 0.00222 +Epoch [3198/4000] Training [3/16] Loss: 0.00326 +Epoch [3198/4000] Training [4/16] Loss: 0.00311 +Epoch [3198/4000] Training [5/16] Loss: 0.00276 +Epoch [3198/4000] Training [6/16] Loss: 0.00267 +Epoch [3198/4000] Training [7/16] Loss: 0.00251 +Epoch [3198/4000] Training [8/16] Loss: 0.00364 +Epoch [3198/4000] Training [9/16] Loss: 0.00163 +Epoch [3198/4000] Training [10/16] Loss: 0.00243 +Epoch [3198/4000] Training [11/16] Loss: 0.00243 +Epoch [3198/4000] Training [12/16] Loss: 0.00316 +Epoch [3198/4000] Training [13/16] Loss: 0.00321 +Epoch [3198/4000] Training [14/16] Loss: 0.00257 +Epoch [3198/4000] Training [15/16] Loss: 0.00304 +Epoch [3198/4000] Training [16/16] Loss: 0.00267 +Epoch [3198/4000] Training metric {'Train/mean dice_metric': 0.9984054565429688, 'Train/mean miou_metric': 0.9964876174926758, 'Train/mean f1': 0.9924999475479126, 'Train/mean precision': 0.9870466589927673, 'Train/mean recall': 0.9980137944221497, 'Train/mean hd95_metric': 0.6930240392684937} +Epoch [3198/4000] Validation [1/4] Loss: 0.33944 focal_loss 0.27861 dice_loss 0.06083 +Epoch [3198/4000] Validation [2/4] Loss: 0.41406 focal_loss 0.30831 dice_loss 0.10575 +Epoch [3198/4000] Validation [3/4] Loss: 0.50748 focal_loss 0.41328 dice_loss 0.09420 +Epoch [3198/4000] Validation [4/4] Loss: 0.36763 focal_loss 0.26533 dice_loss 0.10229 +Epoch [3198/4000] Validation metric {'Val/mean dice_metric': 0.9738429188728333, 'Val/mean miou_metric': 0.9595564603805542, 'Val/mean f1': 0.9754433631896973, 'Val/mean precision': 0.9726698994636536, 'Val/mean recall': 0.9782326817512512, 'Val/mean hd95_metric': 5.021913051605225} +Cheakpoint... +Epoch [3198/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738429188728333, 'Val/mean miou_metric': 0.9595564603805542, 'Val/mean f1': 0.9754433631896973, 'Val/mean precision': 0.9726698994636536, 'Val/mean recall': 0.9782326817512512, 'Val/mean hd95_metric': 5.021913051605225} +Epoch [3199/4000] Training [1/16] Loss: 0.00397 +Epoch [3199/4000] Training [2/16] Loss: 0.00241 +Epoch [3199/4000] Training [3/16] Loss: 0.00303 +Epoch [3199/4000] Training [4/16] Loss: 0.00340 +Epoch [3199/4000] Training [5/16] Loss: 0.00279 +Epoch [3199/4000] Training [6/16] Loss: 0.00192 +Epoch [3199/4000] Training [7/16] Loss: 0.00332 +Epoch [3199/4000] Training [8/16] Loss: 0.00333 +Epoch [3199/4000] Training [9/16] Loss: 0.00181 +Epoch [3199/4000] Training [10/16] Loss: 0.00399 +Epoch [3199/4000] Training [11/16] Loss: 0.00521 +Epoch [3199/4000] Training [12/16] Loss: 0.00344 +Epoch [3199/4000] Training [13/16] Loss: 0.00262 +Epoch [3199/4000] Training [14/16] Loss: 0.00288 +Epoch [3199/4000] Training [15/16] Loss: 0.00356 +Epoch [3199/4000] Training [16/16] Loss: 0.00253 +Epoch [3199/4000] Training metric {'Train/mean dice_metric': 0.9982963800430298, 'Train/mean miou_metric': 0.9963266849517822, 'Train/mean f1': 0.9934445023536682, 'Train/mean precision': 0.9888919591903687, 'Train/mean recall': 0.998039186000824, 'Train/mean hd95_metric': 0.7089420557022095} +Epoch [3199/4000] Validation [1/4] Loss: 0.37210 focal_loss 0.31110 dice_loss 0.06101 +Epoch [3199/4000] Validation [2/4] Loss: 1.17781 focal_loss 0.89514 dice_loss 0.28267 +Epoch [3199/4000] Validation [3/4] Loss: 0.52403 focal_loss 0.43083 dice_loss 0.09319 +Epoch [3199/4000] Validation [4/4] Loss: 0.30051 focal_loss 0.21627 dice_loss 0.08424 +Epoch [3199/4000] Validation metric {'Val/mean dice_metric': 0.9707781076431274, 'Val/mean miou_metric': 0.9568135142326355, 'Val/mean f1': 0.9752992987632751, 'Val/mean precision': 0.9743728041648865, 'Val/mean recall': 0.9762274026870728, 'Val/mean hd95_metric': 5.084150791168213} +Cheakpoint... +Epoch [3199/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9708], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707781076431274, 'Val/mean miou_metric': 0.9568135142326355, 'Val/mean f1': 0.9752992987632751, 'Val/mean precision': 0.9743728041648865, 'Val/mean recall': 0.9762274026870728, 'Val/mean hd95_metric': 5.084150791168213} +Epoch [3200/4000] Training [1/16] Loss: 0.00273 +Epoch [3200/4000] Training [2/16] Loss: 0.00285 +Epoch [3200/4000] Training [3/16] Loss: 0.00247 +Epoch [3200/4000] Training [4/16] Loss: 0.00341 +Epoch [3200/4000] Training [5/16] Loss: 0.00216 +Epoch [3200/4000] Training [6/16] Loss: 0.00416 +Epoch [3200/4000] Training [7/16] Loss: 0.00379 +Epoch [3200/4000] Training [8/16] Loss: 0.00346 +Epoch [3200/4000] Training [9/16] Loss: 0.00283 +Epoch [3200/4000] Training [10/16] Loss: 0.00376 +Epoch [3200/4000] Training [11/16] Loss: 0.00304 +Epoch [3200/4000] Training [12/16] Loss: 0.00289 +Epoch [3200/4000] Training [13/16] Loss: 0.00269 +Epoch [3200/4000] Training [14/16] Loss: 0.00312 +Epoch [3200/4000] Training [15/16] Loss: 0.00243 +Epoch [3200/4000] Training [16/16] Loss: 0.00214 +Epoch [3200/4000] Training metric {'Train/mean dice_metric': 0.9984387159347534, 'Train/mean miou_metric': 0.9965996742248535, 'Train/mean f1': 0.9933452606201172, 'Train/mean precision': 0.9886613488197327, 'Train/mean recall': 0.9980737566947937, 'Train/mean hd95_metric': 0.6801757216453552} +Epoch [3200/4000] Validation [1/4] Loss: 0.36079 focal_loss 0.29880 dice_loss 0.06199 +Epoch [3200/4000] Validation [2/4] Loss: 0.72616 focal_loss 0.54423 dice_loss 0.18193 +Epoch [3200/4000] Validation [3/4] Loss: 0.53661 focal_loss 0.44389 dice_loss 0.09271 +Epoch [3200/4000] Validation [4/4] Loss: 0.46072 focal_loss 0.35054 dice_loss 0.11019 +Epoch [3200/4000] Validation metric {'Val/mean dice_metric': 0.9729377627372742, 'Val/mean miou_metric': 0.9589088559150696, 'Val/mean f1': 0.9758738279342651, 'Val/mean precision': 0.9739648699760437, 'Val/mean recall': 0.977790355682373, 'Val/mean hd95_metric': 5.130587100982666} +Cheakpoint... +Epoch [3200/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729377627372742, 'Val/mean miou_metric': 0.9589088559150696, 'Val/mean f1': 0.9758738279342651, 'Val/mean precision': 0.9739648699760437, 'Val/mean recall': 0.977790355682373, 'Val/mean hd95_metric': 5.130587100982666} +Epoch [3201/4000] Training [1/16] Loss: 0.00456 +Epoch [3201/4000] Training [2/16] Loss: 0.00238 +Epoch [3201/4000] Training [3/16] Loss: 0.00427 +Epoch [3201/4000] Training [4/16] Loss: 0.00479 +Epoch [3201/4000] Training [5/16] Loss: 0.00292 +Epoch [3201/4000] Training [6/16] Loss: 0.00290 +Epoch [3201/4000] Training [7/16] Loss: 0.00205 +Epoch [3201/4000] Training [8/16] Loss: 0.00425 +Epoch [3201/4000] Training [9/16] Loss: 0.00266 +Epoch [3201/4000] Training [10/16] Loss: 0.00282 +Epoch [3201/4000] Training [11/16] Loss: 0.00278 +Epoch [3201/4000] Training [12/16] Loss: 0.00212 +Epoch [3201/4000] Training [13/16] Loss: 0.00263 +Epoch [3201/4000] Training [14/16] Loss: 0.00272 +Epoch [3201/4000] Training [15/16] Loss: 0.00271 +Epoch [3201/4000] Training [16/16] Loss: 0.00259 +Epoch [3201/4000] Training metric {'Train/mean dice_metric': 0.9984965920448303, 'Train/mean miou_metric': 0.996672511100769, 'Train/mean f1': 0.9926022291183472, 'Train/mean precision': 0.9871712327003479, 'Train/mean recall': 0.99809330701828, 'Train/mean hd95_metric': 0.68284010887146} +Epoch [3201/4000] Validation [1/4] Loss: 0.37325 focal_loss 0.31131 dice_loss 0.06193 +Epoch [3201/4000] Validation [2/4] Loss: 0.63288 focal_loss 0.46925 dice_loss 0.16362 +Epoch [3201/4000] Validation [3/4] Loss: 0.51150 focal_loss 0.42181 dice_loss 0.08969 +Epoch [3201/4000] Validation [4/4] Loss: 0.41783 focal_loss 0.31240 dice_loss 0.10543 +Epoch [3201/4000] Validation metric {'Val/mean dice_metric': 0.972852885723114, 'Val/mean miou_metric': 0.9585394859313965, 'Val/mean f1': 0.9747689366340637, 'Val/mean precision': 0.971835196018219, 'Val/mean recall': 0.9777204990386963, 'Val/mean hd95_metric': 5.224905490875244} +Cheakpoint... +Epoch [3201/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972852885723114, 'Val/mean miou_metric': 0.9585394859313965, 'Val/mean f1': 0.9747689366340637, 'Val/mean precision': 0.971835196018219, 'Val/mean recall': 0.9777204990386963, 'Val/mean hd95_metric': 5.224905490875244} +Epoch [3202/4000] Training [1/16] Loss: 0.00350 +Epoch [3202/4000] Training [2/16] Loss: 0.00275 +Epoch [3202/4000] Training [3/16] Loss: 0.00315 +Epoch [3202/4000] Training [4/16] Loss: 0.00218 +Epoch [3202/4000] Training [5/16] Loss: 0.00277 +Epoch [3202/4000] Training [6/16] Loss: 0.00226 +Epoch [3202/4000] Training [7/16] Loss: 0.00230 +Epoch [3202/4000] Training [8/16] Loss: 0.00310 +Epoch [3202/4000] Training [9/16] Loss: 0.00186 +Epoch [3202/4000] Training [10/16] Loss: 0.00292 +Epoch [3202/4000] Training [11/16] Loss: 0.00282 +Epoch [3202/4000] Training [12/16] Loss: 0.00241 +Epoch [3202/4000] Training [13/16] Loss: 0.00208 +Epoch [3202/4000] Training [14/16] Loss: 0.00360 +Epoch [3202/4000] Training [15/16] Loss: 0.00353 +Epoch [3202/4000] Training [16/16] Loss: 0.00228 +Epoch [3202/4000] Training metric {'Train/mean dice_metric': 0.9985392093658447, 'Train/mean miou_metric': 0.9967533349990845, 'Train/mean f1': 0.9926479458808899, 'Train/mean precision': 0.9872342944145203, 'Train/mean recall': 0.9981213212013245, 'Train/mean hd95_metric': 0.6521760821342468} +Epoch [3202/4000] Validation [1/4] Loss: 0.41311 focal_loss 0.34960 dice_loss 0.06351 +Epoch [3202/4000] Validation [2/4] Loss: 0.43718 focal_loss 0.32733 dice_loss 0.10985 +Epoch [3202/4000] Validation [3/4] Loss: 0.47368 focal_loss 0.38752 dice_loss 0.08616 +Epoch [3202/4000] Validation [4/4] Loss: 0.50839 focal_loss 0.37815 dice_loss 0.13024 +Epoch [3202/4000] Validation metric {'Val/mean dice_metric': 0.9727716445922852, 'Val/mean miou_metric': 0.9588378667831421, 'Val/mean f1': 0.9752426743507385, 'Val/mean precision': 0.9732384085655212, 'Val/mean recall': 0.9772553443908691, 'Val/mean hd95_metric': 5.042690753936768} +Cheakpoint... +Epoch [3202/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727716445922852, 'Val/mean miou_metric': 0.9588378667831421, 'Val/mean f1': 0.9752426743507385, 'Val/mean precision': 0.9732384085655212, 'Val/mean recall': 0.9772553443908691, 'Val/mean hd95_metric': 5.042690753936768} +Epoch [3203/4000] Training [1/16] Loss: 0.00290 +Epoch [3203/4000] Training [2/16] Loss: 0.00348 +Epoch [3203/4000] Training [3/16] Loss: 0.00326 +Epoch [3203/4000] Training [4/16] Loss: 0.00275 +Epoch [3203/4000] Training [5/16] Loss: 0.00251 +Epoch [3203/4000] Training [6/16] Loss: 0.00613 +Epoch [3203/4000] Training [7/16] Loss: 0.00311 +Epoch [3203/4000] Training [8/16] Loss: 0.00355 +Epoch [3203/4000] Training [9/16] Loss: 0.00308 +Epoch [3203/4000] Training [10/16] Loss: 0.00279 +Epoch [3203/4000] Training [11/16] Loss: 0.00244 +Epoch [3203/4000] Training [12/16] Loss: 0.00313 +Epoch [3203/4000] Training [13/16] Loss: 0.00279 +Epoch [3203/4000] Training [14/16] Loss: 0.00271 +Epoch [3203/4000] Training [15/16] Loss: 0.00231 +Epoch [3203/4000] Training [16/16] Loss: 0.00330 +Epoch [3203/4000] Training metric {'Train/mean dice_metric': 0.9983195066452026, 'Train/mean miou_metric': 0.9963710904121399, 'Train/mean f1': 0.993471622467041, 'Train/mean precision': 0.9889208078384399, 'Train/mean recall': 0.9980644583702087, 'Train/mean hd95_metric': 0.6963444352149963} +Epoch [3203/4000] Validation [1/4] Loss: 0.37767 focal_loss 0.31571 dice_loss 0.06196 +Epoch [3203/4000] Validation [2/4] Loss: 0.75752 focal_loss 0.57200 dice_loss 0.18552 +Epoch [3203/4000] Validation [3/4] Loss: 0.55460 focal_loss 0.45294 dice_loss 0.10166 +Epoch [3203/4000] Validation [4/4] Loss: 0.43975 focal_loss 0.33567 dice_loss 0.10408 +Epoch [3203/4000] Validation metric {'Val/mean dice_metric': 0.9730289578437805, 'Val/mean miou_metric': 0.9589760899543762, 'Val/mean f1': 0.976224422454834, 'Val/mean precision': 0.9734489321708679, 'Val/mean recall': 0.9790157675743103, 'Val/mean hd95_metric': 5.174247741699219} +Cheakpoint... +Epoch [3203/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730289578437805, 'Val/mean miou_metric': 0.9589760899543762, 'Val/mean f1': 0.976224422454834, 'Val/mean precision': 0.9734489321708679, 'Val/mean recall': 0.9790157675743103, 'Val/mean hd95_metric': 5.174247741699219} +Epoch [3204/4000] Training [1/16] Loss: 0.00221 +Epoch [3204/4000] Training [2/16] Loss: 0.00266 +Epoch [3204/4000] Training [3/16] Loss: 0.00211 +Epoch [3204/4000] Training [4/16] Loss: 0.00338 +Epoch [3204/4000] Training [5/16] Loss: 0.00230 +Epoch [3204/4000] Training [6/16] Loss: 0.00268 +Epoch [3204/4000] Training [7/16] Loss: 0.00273 +Epoch [3204/4000] Training [8/16] Loss: 0.00255 +Epoch [3204/4000] Training [9/16] Loss: 0.00333 +Epoch [3204/4000] Training [10/16] Loss: 0.00323 +Epoch [3204/4000] Training [11/16] Loss: 0.00263 +Epoch [3204/4000] Training [12/16] Loss: 0.00338 +Epoch [3204/4000] Training [13/16] Loss: 0.00296 +Epoch [3204/4000] Training [14/16] Loss: 0.00373 +Epoch [3204/4000] Training [15/16] Loss: 0.00173 +Epoch [3204/4000] Training [16/16] Loss: 0.00288 +Epoch [3204/4000] Training metric {'Train/mean dice_metric': 0.9984387159347534, 'Train/mean miou_metric': 0.9966076612472534, 'Train/mean f1': 0.9936212301254272, 'Train/mean precision': 0.9891614317893982, 'Train/mean recall': 0.998121440410614, 'Train/mean hd95_metric': 0.6647735834121704} +Epoch [3204/4000] Validation [1/4] Loss: 0.38973 focal_loss 0.32603 dice_loss 0.06370 +Epoch [3204/4000] Validation [2/4] Loss: 0.42278 focal_loss 0.31656 dice_loss 0.10622 +Epoch [3204/4000] Validation [3/4] Loss: 0.50138 focal_loss 0.41441 dice_loss 0.08697 +Epoch [3204/4000] Validation [4/4] Loss: 0.29880 focal_loss 0.21786 dice_loss 0.08094 +Epoch [3204/4000] Validation metric {'Val/mean dice_metric': 0.9756518602371216, 'Val/mean miou_metric': 0.9616470336914062, 'Val/mean f1': 0.9769213199615479, 'Val/mean precision': 0.9746454358100891, 'Val/mean recall': 0.9792078733444214, 'Val/mean hd95_metric': 5.043567180633545} +Cheakpoint... +Epoch [3204/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756518602371216, 'Val/mean miou_metric': 0.9616470336914062, 'Val/mean f1': 0.9769213199615479, 'Val/mean precision': 0.9746454358100891, 'Val/mean recall': 0.9792078733444214, 'Val/mean hd95_metric': 5.043567180633545} +Epoch [3205/4000] Training [1/16] Loss: 0.00296 +Epoch [3205/4000] Training [2/16] Loss: 0.00292 +Epoch [3205/4000] Training [3/16] Loss: 0.00259 +Epoch [3205/4000] Training [4/16] Loss: 0.00212 +Epoch [3205/4000] Training [5/16] Loss: 0.00277 +Epoch [3205/4000] Training [6/16] Loss: 0.00256 +Epoch [3205/4000] Training [7/16] Loss: 0.00261 +Epoch [3205/4000] Training [8/16] Loss: 0.00383 +Epoch [3205/4000] Training [9/16] Loss: 0.00212 +Epoch [3205/4000] Training [10/16] Loss: 0.00222 +Epoch [3205/4000] Training [11/16] Loss: 0.00285 +Epoch [3205/4000] Training [12/16] Loss: 0.00244 +Epoch [3205/4000] Training [13/16] Loss: 0.00230 +Epoch [3205/4000] Training [14/16] Loss: 0.00394 +Epoch [3205/4000] Training [15/16] Loss: 0.00264 +Epoch [3205/4000] Training [16/16] Loss: 0.00262 +Epoch [3205/4000] Training metric {'Train/mean dice_metric': 0.9985957741737366, 'Train/mean miou_metric': 0.9968929290771484, 'Train/mean f1': 0.99331134557724, 'Train/mean precision': 0.9884280562400818, 'Train/mean recall': 0.9982431530952454, 'Train/mean hd95_metric': 0.6466094851493835} +Epoch [3205/4000] Validation [1/4] Loss: 0.38618 focal_loss 0.32320 dice_loss 0.06298 +Epoch [3205/4000] Validation [2/4] Loss: 0.88965 focal_loss 0.67789 dice_loss 0.21176 +Epoch [3205/4000] Validation [3/4] Loss: 0.27671 focal_loss 0.21159 dice_loss 0.06512 +Epoch [3205/4000] Validation [4/4] Loss: 0.29984 focal_loss 0.21779 dice_loss 0.08205 +Epoch [3205/4000] Validation metric {'Val/mean dice_metric': 0.9725750088691711, 'Val/mean miou_metric': 0.9589254260063171, 'Val/mean f1': 0.9761197566986084, 'Val/mean precision': 0.9738982319831848, 'Val/mean recall': 0.978351354598999, 'Val/mean hd95_metric': 5.08720588684082} +Cheakpoint... +Epoch [3205/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725750088691711, 'Val/mean miou_metric': 0.9589254260063171, 'Val/mean f1': 0.9761197566986084, 'Val/mean precision': 0.9738982319831848, 'Val/mean recall': 0.978351354598999, 'Val/mean hd95_metric': 5.08720588684082} +Epoch [3206/4000] Training [1/16] Loss: 0.00215 +Epoch [3206/4000] Training [2/16] Loss: 0.00259 +Epoch [3206/4000] Training [3/16] Loss: 0.00185 +Epoch [3206/4000] Training [4/16] Loss: 0.00207 +Epoch [3206/4000] Training [5/16] Loss: 0.00227 +Epoch [3206/4000] Training [6/16] Loss: 0.00198 +Epoch [3206/4000] Training [7/16] Loss: 0.00221 +Epoch [3206/4000] Training [8/16] Loss: 0.00204 +Epoch [3206/4000] Training [9/16] Loss: 0.00311 +Epoch [3206/4000] Training [10/16] Loss: 0.00286 +Epoch [3206/4000] Training [11/16] Loss: 0.00294 +Epoch [3206/4000] Training [12/16] Loss: 0.00289 +Epoch [3206/4000] Training [13/16] Loss: 0.00270 +Epoch [3206/4000] Training [14/16] Loss: 0.00338 +Epoch [3206/4000] Training [15/16] Loss: 0.00284 +Epoch [3206/4000] Training [16/16] Loss: 0.00330 +Epoch [3206/4000] Training metric {'Train/mean dice_metric': 0.9985976219177246, 'Train/mean miou_metric': 0.9968782663345337, 'Train/mean f1': 0.9927181005477905, 'Train/mean precision': 0.9872919321060181, 'Train/mean recall': 0.9982041716575623, 'Train/mean hd95_metric': 0.6355745196342468} +Epoch [3206/4000] Validation [1/4] Loss: 0.35164 focal_loss 0.29097 dice_loss 0.06067 +Epoch [3206/4000] Validation [2/4] Loss: 0.62256 focal_loss 0.45988 dice_loss 0.16268 +Epoch [3206/4000] Validation [3/4] Loss: 0.57307 focal_loss 0.47667 dice_loss 0.09640 +Epoch [3206/4000] Validation [4/4] Loss: 0.30631 focal_loss 0.22628 dice_loss 0.08003 +Epoch [3206/4000] Validation metric {'Val/mean dice_metric': 0.9742101430892944, 'Val/mean miou_metric': 0.9603912234306335, 'Val/mean f1': 0.9757212996482849, 'Val/mean precision': 0.9721086621284485, 'Val/mean recall': 0.9793610572814941, 'Val/mean hd95_metric': 5.148550033569336} +Cheakpoint... +Epoch [3206/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742101430892944, 'Val/mean miou_metric': 0.9603912234306335, 'Val/mean f1': 0.9757212996482849, 'Val/mean precision': 0.9721086621284485, 'Val/mean recall': 0.9793610572814941, 'Val/mean hd95_metric': 5.148550033569336} +Epoch [3207/4000] Training [1/16] Loss: 0.00233 +Epoch [3207/4000] Training [2/16] Loss: 0.00317 +Epoch [3207/4000] Training [3/16] Loss: 0.00308 +Epoch [3207/4000] Training [4/16] Loss: 0.00272 +Epoch [3207/4000] Training [5/16] Loss: 0.00325 +Epoch [3207/4000] Training [6/16] Loss: 0.00512 +Epoch [3207/4000] Training [7/16] Loss: 0.00203 +Epoch [3207/4000] Training [8/16] Loss: 0.00306 +Epoch [3207/4000] Training [9/16] Loss: 0.00204 +Epoch [3207/4000] Training [10/16] Loss: 0.00217 +Epoch [3207/4000] Training [11/16] Loss: 0.00189 +Epoch [3207/4000] Training [12/16] Loss: 0.00314 +Epoch [3207/4000] Training [13/16] Loss: 0.00305 +Epoch [3207/4000] Training [14/16] Loss: 0.00253 +Epoch [3207/4000] Training [15/16] Loss: 0.00201 +Epoch [3207/4000] Training [16/16] Loss: 0.00276 +Epoch [3207/4000] Training metric {'Train/mean dice_metric': 0.9985237121582031, 'Train/mean miou_metric': 0.996776819229126, 'Train/mean f1': 0.9935814142227173, 'Train/mean precision': 0.9890317916870117, 'Train/mean recall': 0.9981729984283447, 'Train/mean hd95_metric': 0.6721329689025879} +Epoch [3207/4000] Validation [1/4] Loss: 0.32629 focal_loss 0.26967 dice_loss 0.05663 +Epoch [3207/4000] Validation [2/4] Loss: 0.66580 focal_loss 0.50226 dice_loss 0.16355 +Epoch [3207/4000] Validation [3/4] Loss: 0.50667 focal_loss 0.41494 dice_loss 0.09173 +Epoch [3207/4000] Validation [4/4] Loss: 0.30063 focal_loss 0.21924 dice_loss 0.08140 +Epoch [3207/4000] Validation metric {'Val/mean dice_metric': 0.9752705693244934, 'Val/mean miou_metric': 0.9611892700195312, 'Val/mean f1': 0.9765160083770752, 'Val/mean precision': 0.9740322232246399, 'Val/mean recall': 0.9790124297142029, 'Val/mean hd95_metric': 4.649184226989746} +Cheakpoint... +Epoch [3207/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752705693244934, 'Val/mean miou_metric': 0.9611892700195312, 'Val/mean f1': 0.9765160083770752, 'Val/mean precision': 0.9740322232246399, 'Val/mean recall': 0.9790124297142029, 'Val/mean hd95_metric': 4.649184226989746} +Epoch [3208/4000] Training [1/16] Loss: 0.00188 +Epoch [3208/4000] Training [2/16] Loss: 0.00217 +Epoch [3208/4000] Training [3/16] Loss: 0.00228 +Epoch [3208/4000] Training [4/16] Loss: 0.00338 +Epoch [3208/4000] Training [5/16] Loss: 0.00310 +Epoch [3208/4000] Training [6/16] Loss: 0.00380 +Epoch [3208/4000] Training [7/16] Loss: 0.00439 +Epoch [3208/4000] Training [8/16] Loss: 0.00301 +Epoch [3208/4000] Training [9/16] Loss: 0.00197 +Epoch [3208/4000] Training [10/16] Loss: 0.00278 +Epoch [3208/4000] Training [11/16] Loss: 0.00310 +Epoch [3208/4000] Training [12/16] Loss: 0.00236 +Epoch [3208/4000] Training [13/16] Loss: 0.00233 +Epoch [3208/4000] Training [14/16] Loss: 0.00258 +Epoch [3208/4000] Training [15/16] Loss: 0.00274 +Epoch [3208/4000] Training [16/16] Loss: 0.00188 +Epoch [3208/4000] Training metric {'Train/mean dice_metric': 0.9984849691390991, 'Train/mean miou_metric': 0.996698260307312, 'Train/mean f1': 0.9935818314552307, 'Train/mean precision': 0.989059329032898, 'Train/mean recall': 0.9981459379196167, 'Train/mean hd95_metric': 0.6851139068603516} +Epoch [3208/4000] Validation [1/4] Loss: 0.37455 focal_loss 0.31158 dice_loss 0.06297 +Epoch [3208/4000] Validation [2/4] Loss: 0.46121 focal_loss 0.34613 dice_loss 0.11508 +Epoch [3208/4000] Validation [3/4] Loss: 0.50011 focal_loss 0.41016 dice_loss 0.08995 +Epoch [3208/4000] Validation [4/4] Loss: 0.29960 focal_loss 0.21252 dice_loss 0.08708 +Epoch [3208/4000] Validation metric {'Val/mean dice_metric': 0.9741819500923157, 'Val/mean miou_metric': 0.9601582288742065, 'Val/mean f1': 0.9761008024215698, 'Val/mean precision': 0.9731100797653198, 'Val/mean recall': 0.9791100025177002, 'Val/mean hd95_metric': 5.302393436431885} +Cheakpoint... +Epoch [3208/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741819500923157, 'Val/mean miou_metric': 0.9601582288742065, 'Val/mean f1': 0.9761008024215698, 'Val/mean precision': 0.9731100797653198, 'Val/mean recall': 0.9791100025177002, 'Val/mean hd95_metric': 5.302393436431885} +Epoch [3209/4000] Training [1/16] Loss: 0.00297 +Epoch [3209/4000] Training [2/16] Loss: 0.00295 +Epoch [3209/4000] Training [3/16] Loss: 0.00292 +Epoch [3209/4000] Training [4/16] Loss: 0.00288 +Epoch [3209/4000] Training [5/16] Loss: 0.00204 +Epoch [3209/4000] Training [6/16] Loss: 0.00250 +Epoch [3209/4000] Training [7/16] Loss: 0.00214 +Epoch [3209/4000] Training [8/16] Loss: 0.00210 +Epoch [3209/4000] Training [9/16] Loss: 0.00404 +Epoch [3209/4000] Training [10/16] Loss: 0.00370 +Epoch [3209/4000] Training [11/16] Loss: 0.00280 +Epoch [3209/4000] Training [12/16] Loss: 0.00276 +Epoch [3209/4000] Training [13/16] Loss: 0.00437 +Epoch [3209/4000] Training [14/16] Loss: 0.00328 +Epoch [3209/4000] Training [15/16] Loss: 0.00309 +Epoch [3209/4000] Training [16/16] Loss: 0.00210 +Epoch [3209/4000] Training metric {'Train/mean dice_metric': 0.9983479380607605, 'Train/mean miou_metric': 0.9964312314987183, 'Train/mean f1': 0.9934744834899902, 'Train/mean precision': 0.9889190793037415, 'Train/mean recall': 0.9980720281600952, 'Train/mean hd95_metric': 0.6752507090568542} +Epoch [3209/4000] Validation [1/4] Loss: 0.37394 focal_loss 0.31261 dice_loss 0.06133 +Epoch [3209/4000] Validation [2/4] Loss: 0.44756 focal_loss 0.33297 dice_loss 0.11460 +Epoch [3209/4000] Validation [3/4] Loss: 0.51847 focal_loss 0.42230 dice_loss 0.09616 +Epoch [3209/4000] Validation [4/4] Loss: 0.30305 focal_loss 0.22099 dice_loss 0.08205 +Epoch [3209/4000] Validation metric {'Val/mean dice_metric': 0.9731103777885437, 'Val/mean miou_metric': 0.9590326547622681, 'Val/mean f1': 0.9756402969360352, 'Val/mean precision': 0.9721011519432068, 'Val/mean recall': 0.9792052507400513, 'Val/mean hd95_metric': 5.430826187133789} +Cheakpoint... +Epoch [3209/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731103777885437, 'Val/mean miou_metric': 0.9590326547622681, 'Val/mean f1': 0.9756402969360352, 'Val/mean precision': 0.9721011519432068, 'Val/mean recall': 0.9792052507400513, 'Val/mean hd95_metric': 5.430826187133789} +Epoch [3210/4000] Training [1/16] Loss: 0.00313 +Epoch [3210/4000] Training [2/16] Loss: 0.00401 +Epoch [3210/4000] Training [3/16] Loss: 0.00238 +Epoch [3210/4000] Training [4/16] Loss: 0.00215 +Epoch [3210/4000] Training [5/16] Loss: 0.00271 +Epoch [3210/4000] Training [6/16] Loss: 0.00293 +Epoch [3210/4000] Training [7/16] Loss: 0.00323 +Epoch [3210/4000] Training [8/16] Loss: 0.00439 +Epoch [3210/4000] Training [9/16] Loss: 0.00298 +Epoch [3210/4000] Training [10/16] Loss: 0.00287 +Epoch [3210/4000] Training [11/16] Loss: 0.00261 +Epoch [3210/4000] Training [12/16] Loss: 0.00274 +Epoch [3210/4000] Training [13/16] Loss: 0.00245 +Epoch [3210/4000] Training [14/16] Loss: 0.00196 +Epoch [3210/4000] Training [15/16] Loss: 0.00282 +Epoch [3210/4000] Training [16/16] Loss: 0.00293 +Epoch [3210/4000] Training metric {'Train/mean dice_metric': 0.998457670211792, 'Train/mean miou_metric': 0.9966180324554443, 'Train/mean f1': 0.9933397173881531, 'Train/mean precision': 0.9885690808296204, 'Train/mean recall': 0.9981566071510315, 'Train/mean hd95_metric': 0.6964142322540283} +Epoch [3210/4000] Validation [1/4] Loss: 0.39923 focal_loss 0.33621 dice_loss 0.06302 +Epoch [3210/4000] Validation [2/4] Loss: 0.47177 focal_loss 0.35484 dice_loss 0.11693 +Epoch [3210/4000] Validation [3/4] Loss: 0.53977 focal_loss 0.44066 dice_loss 0.09911 +Epoch [3210/4000] Validation [4/4] Loss: 0.57796 focal_loss 0.44655 dice_loss 0.13140 +Epoch [3210/4000] Validation metric {'Val/mean dice_metric': 0.972922146320343, 'Val/mean miou_metric': 0.9587138295173645, 'Val/mean f1': 0.9761077165603638, 'Val/mean precision': 0.9738257527351379, 'Val/mean recall': 0.978400468826294, 'Val/mean hd95_metric': 5.058842182159424} +Cheakpoint... +Epoch [3210/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972922146320343, 'Val/mean miou_metric': 0.9587138295173645, 'Val/mean f1': 0.9761077165603638, 'Val/mean precision': 0.9738257527351379, 'Val/mean recall': 0.978400468826294, 'Val/mean hd95_metric': 5.058842182159424} +Epoch [3211/4000] Training [1/16] Loss: 0.00250 +Epoch [3211/4000] Training [2/16] Loss: 0.00287 +Epoch [3211/4000] Training [3/16] Loss: 0.00290 +Epoch [3211/4000] Training [4/16] Loss: 0.00308 +Epoch [3211/4000] Training [5/16] Loss: 0.00211 +Epoch [3211/4000] Training [6/16] Loss: 0.00205 +Epoch [3211/4000] Training [7/16] Loss: 0.00288 +Epoch [3211/4000] Training [8/16] Loss: 0.00229 +Epoch [3211/4000] Training [9/16] Loss: 0.00269 +Epoch [3211/4000] Training [10/16] Loss: 0.00299 +Epoch [3211/4000] Training [11/16] Loss: 0.00389 +Epoch [3211/4000] Training [12/16] Loss: 0.00232 +Epoch [3211/4000] Training [13/16] Loss: 0.00271 +Epoch [3211/4000] Training [14/16] Loss: 0.00314 +Epoch [3211/4000] Training [15/16] Loss: 0.00281 +Epoch [3211/4000] Training [16/16] Loss: 0.00339 +Epoch [3211/4000] Training metric {'Train/mean dice_metric': 0.9985089302062988, 'Train/mean miou_metric': 0.9967471361160278, 'Train/mean f1': 0.9936918020248413, 'Train/mean precision': 0.9892356991767883, 'Train/mean recall': 0.9981881976127625, 'Train/mean hd95_metric': 0.6747345924377441} +Epoch [3211/4000] Validation [1/4] Loss: 0.37911 focal_loss 0.31607 dice_loss 0.06303 +Epoch [3211/4000] Validation [2/4] Loss: 0.46107 focal_loss 0.34613 dice_loss 0.11495 +Epoch [3211/4000] Validation [3/4] Loss: 0.53436 focal_loss 0.43882 dice_loss 0.09554 +Epoch [3211/4000] Validation [4/4] Loss: 0.30328 focal_loss 0.22216 dice_loss 0.08112 +Epoch [3211/4000] Validation metric {'Val/mean dice_metric': 0.9740898013114929, 'Val/mean miou_metric': 0.9601999521255493, 'Val/mean f1': 0.9766590595245361, 'Val/mean precision': 0.9744676947593689, 'Val/mean recall': 0.9788603186607361, 'Val/mean hd95_metric': 4.8716607093811035} +Cheakpoint... +Epoch [3211/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740898013114929, 'Val/mean miou_metric': 0.9601999521255493, 'Val/mean f1': 0.9766590595245361, 'Val/mean precision': 0.9744676947593689, 'Val/mean recall': 0.9788603186607361, 'Val/mean hd95_metric': 4.8716607093811035} +Epoch [3212/4000] Training [1/16] Loss: 0.00323 +Epoch [3212/4000] Training [2/16] Loss: 0.00350 +Epoch [3212/4000] Training [3/16] Loss: 0.00286 +Epoch [3212/4000] Training [4/16] Loss: 0.00273 +Epoch [3212/4000] Training [5/16] Loss: 0.00325 +Epoch [3212/4000] Training [6/16] Loss: 0.00310 +Epoch [3212/4000] Training [7/16] Loss: 0.00298 +Epoch [3212/4000] Training [8/16] Loss: 0.00267 +Epoch [3212/4000] Training [9/16] Loss: 0.00347 +Epoch [3212/4000] Training [10/16] Loss: 0.00218 +Epoch [3212/4000] Training [11/16] Loss: 0.00275 +Epoch [3212/4000] Training [12/16] Loss: 0.00372 +Epoch [3212/4000] Training [13/16] Loss: 0.00198 +Epoch [3212/4000] Training [14/16] Loss: 0.00280 +Epoch [3212/4000] Training [15/16] Loss: 0.00549 +Epoch [3212/4000] Training [16/16] Loss: 0.00295 +Epoch [3212/4000] Training metric {'Train/mean dice_metric': 0.9983783960342407, 'Train/mean miou_metric': 0.9964739084243774, 'Train/mean f1': 0.9935015439987183, 'Train/mean precision': 0.9889742136001587, 'Train/mean recall': 0.9980705976486206, 'Train/mean hd95_metric': 0.6813052892684937} +Epoch [3212/4000] Validation [1/4] Loss: 0.34725 focal_loss 0.28546 dice_loss 0.06179 +Epoch [3212/4000] Validation [2/4] Loss: 0.43401 focal_loss 0.32327 dice_loss 0.11073 +Epoch [3212/4000] Validation [3/4] Loss: 0.51954 focal_loss 0.42969 dice_loss 0.08985 +Epoch [3212/4000] Validation [4/4] Loss: 0.35290 focal_loss 0.25273 dice_loss 0.10016 +Epoch [3212/4000] Validation metric {'Val/mean dice_metric': 0.9743850827217102, 'Val/mean miou_metric': 0.960641086101532, 'Val/mean f1': 0.9769238233566284, 'Val/mean precision': 0.9746101498603821, 'Val/mean recall': 0.9792486429214478, 'Val/mean hd95_metric': 4.807924747467041} +Cheakpoint... +Epoch [3212/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743850827217102, 'Val/mean miou_metric': 0.960641086101532, 'Val/mean f1': 0.9769238233566284, 'Val/mean precision': 0.9746101498603821, 'Val/mean recall': 0.9792486429214478, 'Val/mean hd95_metric': 4.807924747467041} +Epoch [3213/4000] Training [1/16] Loss: 0.00295 +Epoch [3213/4000] Training [2/16] Loss: 0.00401 +Epoch [3213/4000] Training [3/16] Loss: 0.00304 +Epoch [3213/4000] Training [4/16] Loss: 0.00264 +Epoch [3213/4000] Training [5/16] Loss: 0.00305 +Epoch [3213/4000] Training [6/16] Loss: 0.00238 +Epoch [3213/4000] Training [7/16] Loss: 0.00270 +Epoch [3213/4000] Training [8/16] Loss: 0.00259 +Epoch [3213/4000] Training [9/16] Loss: 0.00250 +Epoch [3213/4000] Training [10/16] Loss: 0.00395 +Epoch [3213/4000] Training [11/16] Loss: 0.00321 +Epoch [3213/4000] Training [12/16] Loss: 0.00331 +Epoch [3213/4000] Training [13/16] Loss: 0.00346 +Epoch [3213/4000] Training [14/16] Loss: 0.00239 +Epoch [3213/4000] Training [15/16] Loss: 0.00273 +Epoch [3213/4000] Training [16/16] Loss: 0.00361 +Epoch [3213/4000] Training metric {'Train/mean dice_metric': 0.9983371496200562, 'Train/mean miou_metric': 0.9964063167572021, 'Train/mean f1': 0.9935267567634583, 'Train/mean precision': 0.9890351891517639, 'Train/mean recall': 0.9980595111846924, 'Train/mean hd95_metric': 0.7318514585494995} +Epoch [3213/4000] Validation [1/4] Loss: 0.38695 focal_loss 0.32326 dice_loss 0.06369 +Epoch [3213/4000] Validation [2/4] Loss: 0.40292 focal_loss 0.29985 dice_loss 0.10307 +Epoch [3213/4000] Validation [3/4] Loss: 0.50554 focal_loss 0.41812 dice_loss 0.08742 +Epoch [3213/4000] Validation [4/4] Loss: 0.43039 focal_loss 0.32147 dice_loss 0.10891 +Epoch [3213/4000] Validation metric {'Val/mean dice_metric': 0.9725357890129089, 'Val/mean miou_metric': 0.958270251750946, 'Val/mean f1': 0.9759942293167114, 'Val/mean precision': 0.9734464883804321, 'Val/mean recall': 0.9785553812980652, 'Val/mean hd95_metric': 5.170862197875977} +Cheakpoint... +Epoch [3213/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725357890129089, 'Val/mean miou_metric': 0.958270251750946, 'Val/mean f1': 0.9759942293167114, 'Val/mean precision': 0.9734464883804321, 'Val/mean recall': 0.9785553812980652, 'Val/mean hd95_metric': 5.170862197875977} +Epoch [3214/4000] Training [1/16] Loss: 0.00274 +Epoch [3214/4000] Training [2/16] Loss: 0.00279 +Epoch [3214/4000] Training [3/16] Loss: 0.00350 +Epoch [3214/4000] Training [4/16] Loss: 0.00265 +Epoch [3214/4000] Training [5/16] Loss: 0.00384 +Epoch [3214/4000] Training [6/16] Loss: 0.00234 +Epoch [3214/4000] Training [7/16] Loss: 0.00266 +Epoch [3214/4000] Training [8/16] Loss: 0.00366 +Epoch [3214/4000] Training [9/16] Loss: 0.00320 +Epoch [3214/4000] Training [10/16] Loss: 0.00268 +Epoch [3214/4000] Training [11/16] Loss: 0.00361 +Epoch [3214/4000] Training [12/16] Loss: 0.00432 +Epoch [3214/4000] Training [13/16] Loss: 0.00229 +Epoch [3214/4000] Training [14/16] Loss: 0.00351 +Epoch [3214/4000] Training [15/16] Loss: 0.00327 +Epoch [3214/4000] Training [16/16] Loss: 0.00452 +Epoch [3214/4000] Training metric {'Train/mean dice_metric': 0.9983800053596497, 'Train/mean miou_metric': 0.9964765310287476, 'Train/mean f1': 0.9933750629425049, 'Train/mean precision': 0.988761305809021, 'Train/mean recall': 0.9980320930480957, 'Train/mean hd95_metric': 0.7111603021621704} +Epoch [3214/4000] Validation [1/4] Loss: 0.37552 focal_loss 0.31290 dice_loss 0.06262 +Epoch [3214/4000] Validation [2/4] Loss: 1.13128 focal_loss 0.86276 dice_loss 0.26852 +Epoch [3214/4000] Validation [3/4] Loss: 0.57615 focal_loss 0.47271 dice_loss 0.10344 +Epoch [3214/4000] Validation [4/4] Loss: 0.41700 focal_loss 0.31242 dice_loss 0.10458 +Epoch [3214/4000] Validation metric {'Val/mean dice_metric': 0.9728593826293945, 'Val/mean miou_metric': 0.9586901664733887, 'Val/mean f1': 0.9751260280609131, 'Val/mean precision': 0.9731320738792419, 'Val/mean recall': 0.9771283268928528, 'Val/mean hd95_metric': 5.619937896728516} +Cheakpoint... +Epoch [3214/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728593826293945, 'Val/mean miou_metric': 0.9586901664733887, 'Val/mean f1': 0.9751260280609131, 'Val/mean precision': 0.9731320738792419, 'Val/mean recall': 0.9771283268928528, 'Val/mean hd95_metric': 5.619937896728516} +Epoch [3215/4000] Training [1/16] Loss: 0.00399 +Epoch [3215/4000] Training [2/16] Loss: 0.00309 +Epoch [3215/4000] Training [3/16] Loss: 0.00258 +Epoch [3215/4000] Training [4/16] Loss: 0.00241 +Epoch [3215/4000] Training [5/16] Loss: 0.00180 +Epoch [3215/4000] Training [6/16] Loss: 0.00292 +Epoch [3215/4000] Training [7/16] Loss: 0.00223 +Epoch [3215/4000] Training [8/16] Loss: 0.00192 +Epoch [3215/4000] Training [9/16] Loss: 0.00347 +Epoch [3215/4000] Training [10/16] Loss: 0.00314 +Epoch [3215/4000] Training [11/16] Loss: 0.00428 +Epoch [3215/4000] Training [12/16] Loss: 0.00305 +Epoch [3215/4000] Training [13/16] Loss: 0.00378 +Epoch [3215/4000] Training [14/16] Loss: 0.00244 +Epoch [3215/4000] Training [15/16] Loss: 0.00292 +Epoch [3215/4000] Training [16/16] Loss: 0.00311 +Epoch [3215/4000] Training metric {'Train/mean dice_metric': 0.9984030723571777, 'Train/mean miou_metric': 0.9965388774871826, 'Train/mean f1': 0.9934955835342407, 'Train/mean precision': 0.988979160785675, 'Train/mean recall': 0.9980533719062805, 'Train/mean hd95_metric': 0.6517854928970337} +Epoch [3215/4000] Validation [1/4] Loss: 0.41791 focal_loss 0.35288 dice_loss 0.06503 +Epoch [3215/4000] Validation [2/4] Loss: 0.96717 focal_loss 0.77571 dice_loss 0.19146 +Epoch [3215/4000] Validation [3/4] Loss: 0.26124 focal_loss 0.19900 dice_loss 0.06224 +Epoch [3215/4000] Validation [4/4] Loss: 0.30749 focal_loss 0.22783 dice_loss 0.07966 +Epoch [3215/4000] Validation metric {'Val/mean dice_metric': 0.9751737713813782, 'Val/mean miou_metric': 0.961380124092102, 'Val/mean f1': 0.9761218428611755, 'Val/mean precision': 0.9731500744819641, 'Val/mean recall': 0.9791118502616882, 'Val/mean hd95_metric': 4.75960111618042} +Cheakpoint... +Epoch [3215/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751737713813782, 'Val/mean miou_metric': 0.961380124092102, 'Val/mean f1': 0.9761218428611755, 'Val/mean precision': 0.9731500744819641, 'Val/mean recall': 0.9791118502616882, 'Val/mean hd95_metric': 4.75960111618042} +Epoch [3216/4000] Training [1/16] Loss: 0.00177 +Epoch [3216/4000] Training [2/16] Loss: 0.00268 +Epoch [3216/4000] Training [3/16] Loss: 0.00221 +Epoch [3216/4000] Training [4/16] Loss: 0.00299 +Epoch [3216/4000] Training [5/16] Loss: 0.00460 +Epoch [3216/4000] Training [6/16] Loss: 0.00273 +Epoch [3216/4000] Training [7/16] Loss: 0.00252 +Epoch [3216/4000] Training [8/16] Loss: 0.00274 +Epoch [3216/4000] Training [9/16] Loss: 0.00266 +Epoch [3216/4000] Training [10/16] Loss: 0.00216 +Epoch [3216/4000] Training [11/16] Loss: 0.00272 +Epoch [3216/4000] Training [12/16] Loss: 0.00249 +Epoch [3216/4000] Training [13/16] Loss: 0.00526 +Epoch [3216/4000] Training [14/16] Loss: 0.00298 +Epoch [3216/4000] Training [15/16] Loss: 0.00313 +Epoch [3216/4000] Training [16/16] Loss: 0.00255 +Epoch [3216/4000] Training metric {'Train/mean dice_metric': 0.998462438583374, 'Train/mean miou_metric': 0.9966522455215454, 'Train/mean f1': 0.9936215281486511, 'Train/mean precision': 0.9891090989112854, 'Train/mean recall': 0.998175323009491, 'Train/mean hd95_metric': 0.676227331161499} +Epoch [3216/4000] Validation [1/4] Loss: 0.35965 focal_loss 0.29543 dice_loss 0.06422 +Epoch [3216/4000] Validation [2/4] Loss: 0.54555 focal_loss 0.39192 dice_loss 0.15363 +Epoch [3216/4000] Validation [3/4] Loss: 0.51696 focal_loss 0.42259 dice_loss 0.09438 +Epoch [3216/4000] Validation [4/4] Loss: 0.29290 focal_loss 0.21238 dice_loss 0.08052 +Epoch [3216/4000] Validation metric {'Val/mean dice_metric': 0.9725135564804077, 'Val/mean miou_metric': 0.9588258862495422, 'Val/mean f1': 0.9766204953193665, 'Val/mean precision': 0.9741314649581909, 'Val/mean recall': 0.9791223406791687, 'Val/mean hd95_metric': 4.934764385223389} +Cheakpoint... +Epoch [3216/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725135564804077, 'Val/mean miou_metric': 0.9588258862495422, 'Val/mean f1': 0.9766204953193665, 'Val/mean precision': 0.9741314649581909, 'Val/mean recall': 0.9791223406791687, 'Val/mean hd95_metric': 4.934764385223389} +Epoch [3217/4000] Training [1/16] Loss: 0.00383 +Epoch [3217/4000] Training [2/16] Loss: 0.00248 +Epoch [3217/4000] Training [3/16] Loss: 0.00389 +Epoch [3217/4000] Training [4/16] Loss: 0.00434 +Epoch [3217/4000] Training [5/16] Loss: 0.00296 +Epoch [3217/4000] Training [6/16] Loss: 0.00218 +Epoch [3217/4000] Training [7/16] Loss: 0.00406 +Epoch [3217/4000] Training [8/16] Loss: 0.00278 +Epoch [3217/4000] Training [9/16] Loss: 0.00237 +Epoch [3217/4000] Training [10/16] Loss: 0.00266 +Epoch [3217/4000] Training [11/16] Loss: 0.00216 +Epoch [3217/4000] Training [12/16] Loss: 0.00288 +Epoch [3217/4000] Training [13/16] Loss: 0.00295 +Epoch [3217/4000] Training [14/16] Loss: 0.00362 +Epoch [3217/4000] Training [15/16] Loss: 0.00359 +Epoch [3217/4000] Training [16/16] Loss: 0.00231 +Epoch [3217/4000] Training metric {'Train/mean dice_metric': 0.9983500838279724, 'Train/mean miou_metric': 0.9963790774345398, 'Train/mean f1': 0.9926132559776306, 'Train/mean precision': 0.9873327016830444, 'Train/mean recall': 0.997950553894043, 'Train/mean hd95_metric': 0.7156381607055664} +Epoch [3217/4000] Validation [1/4] Loss: 0.39082 focal_loss 0.32711 dice_loss 0.06372 +Epoch [3217/4000] Validation [2/4] Loss: 0.42761 focal_loss 0.31634 dice_loss 0.11128 +Epoch [3217/4000] Validation [3/4] Loss: 0.53943 focal_loss 0.44351 dice_loss 0.09592 +Epoch [3217/4000] Validation [4/4] Loss: 0.28902 focal_loss 0.20949 dice_loss 0.07953 +Epoch [3217/4000] Validation metric {'Val/mean dice_metric': 0.9763323068618774, 'Val/mean miou_metric': 0.9619844555854797, 'Val/mean f1': 0.9761307835578918, 'Val/mean precision': 0.9725599884986877, 'Val/mean recall': 0.9797279834747314, 'Val/mean hd95_metric': 4.819424152374268} +Cheakpoint... +Epoch [3217/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9763], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9763323068618774, 'Val/mean miou_metric': 0.9619844555854797, 'Val/mean f1': 0.9761307835578918, 'Val/mean precision': 0.9725599884986877, 'Val/mean recall': 0.9797279834747314, 'Val/mean hd95_metric': 4.819424152374268} +Epoch [3218/4000] Training [1/16] Loss: 0.00247 +Epoch [3218/4000] Training [2/16] Loss: 0.00270 +Epoch [3218/4000] Training [3/16] Loss: 0.00365 +Epoch [3218/4000] Training [4/16] Loss: 0.00470 +Epoch [3218/4000] Training [5/16] Loss: 0.00294 +Epoch [3218/4000] Training [6/16] Loss: 0.00195 +Epoch [3218/4000] Training [7/16] Loss: 0.00239 +Epoch [3218/4000] Training [8/16] Loss: 0.00236 +Epoch [3218/4000] Training [9/16] Loss: 0.00237 +Epoch [3218/4000] Training [10/16] Loss: 0.00214 +Epoch [3218/4000] Training [11/16] Loss: 0.00229 +Epoch [3218/4000] Training [12/16] Loss: 0.00381 +Epoch [3218/4000] Training [13/16] Loss: 0.00232 +Epoch [3218/4000] Training [14/16] Loss: 0.00384 +Epoch [3218/4000] Training [15/16] Loss: 0.00241 +Epoch [3218/4000] Training [16/16] Loss: 0.00429 +Epoch [3218/4000] Training metric {'Train/mean dice_metric': 0.9984009861946106, 'Train/mean miou_metric': 0.996532678604126, 'Train/mean f1': 0.9935113787651062, 'Train/mean precision': 0.9889400601387024, 'Train/mean recall': 0.9981251955032349, 'Train/mean hd95_metric': 0.7011295557022095} +Epoch [3218/4000] Validation [1/4] Loss: 0.36186 focal_loss 0.29729 dice_loss 0.06457 +Epoch [3218/4000] Validation [2/4] Loss: 1.16493 focal_loss 0.89177 dice_loss 0.27317 +Epoch [3218/4000] Validation [3/4] Loss: 0.51760 focal_loss 0.42777 dice_loss 0.08984 +Epoch [3218/4000] Validation [4/4] Loss: 0.31795 focal_loss 0.22643 dice_loss 0.09152 +Epoch [3218/4000] Validation metric {'Val/mean dice_metric': 0.9730542898178101, 'Val/mean miou_metric': 0.9588748216629028, 'Val/mean f1': 0.9753366112709045, 'Val/mean precision': 0.973402738571167, 'Val/mean recall': 0.9772781133651733, 'Val/mean hd95_metric': 5.111898899078369} +Cheakpoint... +Epoch [3218/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730542898178101, 'Val/mean miou_metric': 0.9588748216629028, 'Val/mean f1': 0.9753366112709045, 'Val/mean precision': 0.973402738571167, 'Val/mean recall': 0.9772781133651733, 'Val/mean hd95_metric': 5.111898899078369} +Epoch [3219/4000] Training [1/16] Loss: 0.00290 +Epoch [3219/4000] Training [2/16] Loss: 0.00303 +Epoch [3219/4000] Training [3/16] Loss: 0.00240 +Epoch [3219/4000] Training [4/16] Loss: 0.00393 +Epoch [3219/4000] Training [5/16] Loss: 0.00231 +Epoch [3219/4000] Training [6/16] Loss: 0.00250 +Epoch [3219/4000] Training [7/16] Loss: 0.00258 +Epoch [3219/4000] Training [8/16] Loss: 0.00427 +Epoch [3219/4000] Training [9/16] Loss: 0.00237 +Epoch [3219/4000] Training [10/16] Loss: 0.00200 +Epoch [3219/4000] Training [11/16] Loss: 0.00226 +Epoch [3219/4000] Training [12/16] Loss: 0.00155 +Epoch [3219/4000] Training [13/16] Loss: 0.00378 +Epoch [3219/4000] Training [14/16] Loss: 0.00223 +Epoch [3219/4000] Training [15/16] Loss: 0.00245 +Epoch [3219/4000] Training [16/16] Loss: 0.00399 +Epoch [3219/4000] Training metric {'Train/mean dice_metric': 0.9984997510910034, 'Train/mean miou_metric': 0.9967140555381775, 'Train/mean f1': 0.9934021234512329, 'Train/mean precision': 0.9886792898178101, 'Train/mean recall': 0.9981702566146851, 'Train/mean hd95_metric': 0.6541430354118347} +Epoch [3219/4000] Validation [1/4] Loss: 0.47808 focal_loss 0.40515 dice_loss 0.07293 +Epoch [3219/4000] Validation [2/4] Loss: 0.44456 focal_loss 0.32982 dice_loss 0.11474 +Epoch [3219/4000] Validation [3/4] Loss: 0.52816 focal_loss 0.43473 dice_loss 0.09344 +Epoch [3219/4000] Validation [4/4] Loss: 0.31253 focal_loss 0.22824 dice_loss 0.08429 +Epoch [3219/4000] Validation metric {'Val/mean dice_metric': 0.973258376121521, 'Val/mean miou_metric': 0.9592005610466003, 'Val/mean f1': 0.9763790965080261, 'Val/mean precision': 0.9743664860725403, 'Val/mean recall': 0.9784001708030701, 'Val/mean hd95_metric': 4.941141605377197} +Cheakpoint... +Epoch [3219/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973258376121521, 'Val/mean miou_metric': 0.9592005610466003, 'Val/mean f1': 0.9763790965080261, 'Val/mean precision': 0.9743664860725403, 'Val/mean recall': 0.9784001708030701, 'Val/mean hd95_metric': 4.941141605377197} +Epoch [3220/4000] Training [1/16] Loss: 0.00288 +Epoch [3220/4000] Training [2/16] Loss: 0.00297 +Epoch [3220/4000] Training [3/16] Loss: 0.00312 +Epoch [3220/4000] Training [4/16] Loss: 0.00229 +Epoch [3220/4000] Training [5/16] Loss: 0.00414 +Epoch [3220/4000] Training [6/16] Loss: 0.00405 +Epoch [3220/4000] Training [7/16] Loss: 0.00310 +Epoch [3220/4000] Training [8/16] Loss: 0.00256 +Epoch [3220/4000] Training [9/16] Loss: 0.00416 +Epoch [3220/4000] Training [10/16] Loss: 0.00323 +Epoch [3220/4000] Training [11/16] Loss: 0.00300 +Epoch [3220/4000] Training [12/16] Loss: 0.00271 +Epoch [3220/4000] Training [13/16] Loss: 0.00289 +Epoch [3220/4000] Training [14/16] Loss: 0.00365 +Epoch [3220/4000] Training [15/16] Loss: 0.00294 +Epoch [3220/4000] Training [16/16] Loss: 0.00222 +Epoch [3220/4000] Training metric {'Train/mean dice_metric': 0.998274564743042, 'Train/mean miou_metric': 0.9962499737739563, 'Train/mean f1': 0.9928660988807678, 'Train/mean precision': 0.987798810005188, 'Train/mean recall': 0.9979856610298157, 'Train/mean hd95_metric': 0.6882961392402649} +Epoch [3220/4000] Validation [1/4] Loss: 0.41739 focal_loss 0.35102 dice_loss 0.06637 +Epoch [3220/4000] Validation [2/4] Loss: 0.72010 focal_loss 0.53616 dice_loss 0.18394 +Epoch [3220/4000] Validation [3/4] Loss: 0.57368 focal_loss 0.47175 dice_loss 0.10193 +Epoch [3220/4000] Validation [4/4] Loss: 0.27791 focal_loss 0.20027 dice_loss 0.07764 +Epoch [3220/4000] Validation metric {'Val/mean dice_metric': 0.9727977514266968, 'Val/mean miou_metric': 0.9587713479995728, 'Val/mean f1': 0.9754588603973389, 'Val/mean precision': 0.9732475280761719, 'Val/mean recall': 0.9776801466941833, 'Val/mean hd95_metric': 4.726109981536865} +Cheakpoint... +Epoch [3220/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727977514266968, 'Val/mean miou_metric': 0.9587713479995728, 'Val/mean f1': 0.9754588603973389, 'Val/mean precision': 0.9732475280761719, 'Val/mean recall': 0.9776801466941833, 'Val/mean hd95_metric': 4.726109981536865} +Epoch [3221/4000] Training [1/16] Loss: 0.00357 +Epoch [3221/4000] Training [2/16] Loss: 0.00240 +Epoch [3221/4000] Training [3/16] Loss: 0.00298 +Epoch [3221/4000] Training [4/16] Loss: 0.00236 +Epoch [3221/4000] Training [5/16] Loss: 0.00921 +Epoch [3221/4000] Training [6/16] Loss: 0.00234 +Epoch [3221/4000] Training [7/16] Loss: 0.00303 +Epoch [3221/4000] Training [8/16] Loss: 0.00246 +Epoch [3221/4000] Training [9/16] Loss: 0.00220 +Epoch [3221/4000] Training [10/16] Loss: 0.00270 +Epoch [3221/4000] Training [11/16] Loss: 0.00366 +Epoch [3221/4000] Training [12/16] Loss: 0.00347 +Epoch [3221/4000] Training [13/16] Loss: 0.00231 +Epoch [3221/4000] Training [14/16] Loss: 0.00279 +Epoch [3221/4000] Training [15/16] Loss: 0.00218 +Epoch [3221/4000] Training [16/16] Loss: 0.00255 +Epoch [3221/4000] Training metric {'Train/mean dice_metric': 0.9983869791030884, 'Train/mean miou_metric': 0.9965062141418457, 'Train/mean f1': 0.9934349656105042, 'Train/mean precision': 0.9888932704925537, 'Train/mean recall': 0.9980185627937317, 'Train/mean hd95_metric': 0.7014574408531189} +Epoch [3221/4000] Validation [1/4] Loss: 0.43999 focal_loss 0.37131 dice_loss 0.06868 +Epoch [3221/4000] Validation [2/4] Loss: 0.45872 focal_loss 0.34557 dice_loss 0.11316 +Epoch [3221/4000] Validation [3/4] Loss: 0.51756 focal_loss 0.42432 dice_loss 0.09324 +Epoch [3221/4000] Validation [4/4] Loss: 0.32673 focal_loss 0.24576 dice_loss 0.08097 +Epoch [3221/4000] Validation metric {'Val/mean dice_metric': 0.9727474451065063, 'Val/mean miou_metric': 0.9584527015686035, 'Val/mean f1': 0.9756729006767273, 'Val/mean precision': 0.9738187193870544, 'Val/mean recall': 0.9775342345237732, 'Val/mean hd95_metric': 5.300922870635986} +Cheakpoint... +Epoch [3221/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727474451065063, 'Val/mean miou_metric': 0.9584527015686035, 'Val/mean f1': 0.9756729006767273, 'Val/mean precision': 0.9738187193870544, 'Val/mean recall': 0.9775342345237732, 'Val/mean hd95_metric': 5.300922870635986} +Epoch [3222/4000] Training [1/16] Loss: 0.00198 +Epoch [3222/4000] Training [2/16] Loss: 0.00271 +Epoch [3222/4000] Training [3/16] Loss: 0.00325 +Epoch [3222/4000] Training [4/16] Loss: 0.00280 +Epoch [3222/4000] Training [5/16] Loss: 0.00335 +Epoch [3222/4000] Training [6/16] Loss: 0.00347 +Epoch [3222/4000] Training [7/16] Loss: 0.00244 +Epoch [3222/4000] Training [8/16] Loss: 0.00198 +Epoch [3222/4000] Training [9/16] Loss: 0.00230 +Epoch [3222/4000] Training [10/16] Loss: 0.00239 +Epoch [3222/4000] Training [11/16] Loss: 0.00294 +Epoch [3222/4000] Training [12/16] Loss: 0.00236 +Epoch [3222/4000] Training [13/16] Loss: 0.00260 +Epoch [3222/4000] Training [14/16] Loss: 0.00246 +Epoch [3222/4000] Training [15/16] Loss: 0.00368 +Epoch [3222/4000] Training [16/16] Loss: 0.00293 +Epoch [3222/4000] Training metric {'Train/mean dice_metric': 0.9984914064407349, 'Train/mean miou_metric': 0.9967116117477417, 'Train/mean f1': 0.9935855865478516, 'Train/mean precision': 0.9890264272689819, 'Train/mean recall': 0.9981869459152222, 'Train/mean hd95_metric': 0.6959537863731384} +Epoch [3222/4000] Validation [1/4] Loss: 0.42384 focal_loss 0.35885 dice_loss 0.06499 +Epoch [3222/4000] Validation [2/4] Loss: 1.02199 focal_loss 0.80424 dice_loss 0.21775 +Epoch [3222/4000] Validation [3/4] Loss: 0.48677 focal_loss 0.39684 dice_loss 0.08993 +Epoch [3222/4000] Validation [4/4] Loss: 0.45637 focal_loss 0.35428 dice_loss 0.10209 +Epoch [3222/4000] Validation metric {'Val/mean dice_metric': 0.9725127220153809, 'Val/mean miou_metric': 0.958380401134491, 'Val/mean f1': 0.9759079217910767, 'Val/mean precision': 0.9741455912590027, 'Val/mean recall': 0.9776767492294312, 'Val/mean hd95_metric': 4.918700218200684} +Cheakpoint... +Epoch [3222/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725127220153809, 'Val/mean miou_metric': 0.958380401134491, 'Val/mean f1': 0.9759079217910767, 'Val/mean precision': 0.9741455912590027, 'Val/mean recall': 0.9776767492294312, 'Val/mean hd95_metric': 4.918700218200684} +Epoch [3223/4000] Training [1/16] Loss: 0.00285 +Epoch [3223/4000] Training [2/16] Loss: 0.00246 +Epoch [3223/4000] Training [3/16] Loss: 0.00294 +Epoch [3223/4000] Training [4/16] Loss: 0.00238 +Epoch [3223/4000] Training [5/16] Loss: 0.00239 +Epoch [3223/4000] Training [6/16] Loss: 0.00309 +Epoch [3223/4000] Training [7/16] Loss: 0.00243 +Epoch [3223/4000] Training [8/16] Loss: 0.00278 +Epoch [3223/4000] Training [9/16] Loss: 0.00342 +Epoch [3223/4000] Training [10/16] Loss: 0.00230 +Epoch [3223/4000] Training [11/16] Loss: 0.00178 +Epoch [3223/4000] Training [12/16] Loss: 0.00288 +Epoch [3223/4000] Training [13/16] Loss: 0.00209 +Epoch [3223/4000] Training [14/16] Loss: 0.00281 +Epoch [3223/4000] Training [15/16] Loss: 0.00184 +Epoch [3223/4000] Training [16/16] Loss: 0.00313 +Epoch [3223/4000] Training metric {'Train/mean dice_metric': 0.9985169768333435, 'Train/mean miou_metric': 0.9967209100723267, 'Train/mean f1': 0.9926955699920654, 'Train/mean precision': 0.9873530864715576, 'Train/mean recall': 0.998096227645874, 'Train/mean hd95_metric': 0.705112874507904} +Epoch [3223/4000] Validation [1/4] Loss: 0.37109 focal_loss 0.30952 dice_loss 0.06156 +Epoch [3223/4000] Validation [2/4] Loss: 0.68702 focal_loss 0.51033 dice_loss 0.17669 +Epoch [3223/4000] Validation [3/4] Loss: 0.53447 focal_loss 0.44132 dice_loss 0.09315 +Epoch [3223/4000] Validation [4/4] Loss: 0.38361 focal_loss 0.27524 dice_loss 0.10837 +Epoch [3223/4000] Validation metric {'Val/mean dice_metric': 0.9716461300849915, 'Val/mean miou_metric': 0.9578708410263062, 'Val/mean f1': 0.9751640558242798, 'Val/mean precision': 0.9727439880371094, 'Val/mean recall': 0.9775961637496948, 'Val/mean hd95_metric': 5.487685203552246} +Cheakpoint... +Epoch [3223/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716461300849915, 'Val/mean miou_metric': 0.9578708410263062, 'Val/mean f1': 0.9751640558242798, 'Val/mean precision': 0.9727439880371094, 'Val/mean recall': 0.9775961637496948, 'Val/mean hd95_metric': 5.487685203552246} +Epoch [3224/4000] Training [1/16] Loss: 0.00254 +Epoch [3224/4000] Training [2/16] Loss: 0.00238 +Epoch [3224/4000] Training [3/16] Loss: 0.00281 +Epoch [3224/4000] Training [4/16] Loss: 0.00402 +Epoch [3224/4000] Training [5/16] Loss: 0.00253 +Epoch [3224/4000] Training [6/16] Loss: 0.00200 +Epoch [3224/4000] Training [7/16] Loss: 0.00189 +Epoch [3224/4000] Training [8/16] Loss: 0.00181 +Epoch [3224/4000] Training [9/16] Loss: 0.00268 +Epoch [3224/4000] Training [10/16] Loss: 0.00342 +Epoch [3224/4000] Training [11/16] Loss: 0.00229 +Epoch [3224/4000] Training [12/16] Loss: 0.00216 +Epoch [3224/4000] Training [13/16] Loss: 0.00250 +Epoch [3224/4000] Training [14/16] Loss: 0.00311 +Epoch [3224/4000] Training [15/16] Loss: 0.00247 +Epoch [3224/4000] Training [16/16] Loss: 0.00268 +Epoch [3224/4000] Training metric {'Train/mean dice_metric': 0.9986729025840759, 'Train/mean miou_metric': 0.997075080871582, 'Train/mean f1': 0.9937248826026917, 'Train/mean precision': 0.9892093539237976, 'Train/mean recall': 0.9982818961143494, 'Train/mean hd95_metric': 0.6156526803970337} +Epoch [3224/4000] Validation [1/4] Loss: 0.38617 focal_loss 0.32221 dice_loss 0.06396 +Epoch [3224/4000] Validation [2/4] Loss: 1.44045 focal_loss 1.14216 dice_loss 0.29829 +Epoch [3224/4000] Validation [3/4] Loss: 0.52139 focal_loss 0.43041 dice_loss 0.09097 +Epoch [3224/4000] Validation [4/4] Loss: 0.32761 focal_loss 0.22122 dice_loss 0.10638 +Epoch [3224/4000] Validation metric {'Val/mean dice_metric': 0.9730682373046875, 'Val/mean miou_metric': 0.959263801574707, 'Val/mean f1': 0.9757004976272583, 'Val/mean precision': 0.9737679362297058, 'Val/mean recall': 0.9776409864425659, 'Val/mean hd95_metric': 4.994902610778809} +Cheakpoint... +Epoch [3224/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730682373046875, 'Val/mean miou_metric': 0.959263801574707, 'Val/mean f1': 0.9757004976272583, 'Val/mean precision': 0.9737679362297058, 'Val/mean recall': 0.9776409864425659, 'Val/mean hd95_metric': 4.994902610778809} +Epoch [3225/4000] Training [1/16] Loss: 0.00248 +Epoch [3225/4000] Training [2/16] Loss: 0.00180 +Epoch [3225/4000] Training [3/16] Loss: 0.00257 +Epoch [3225/4000] Training [4/16] Loss: 0.00315 +Epoch [3225/4000] Training [5/16] Loss: 0.00279 +Epoch [3225/4000] Training [6/16] Loss: 0.00278 +Epoch [3225/4000] Training [7/16] Loss: 0.00215 +Epoch [3225/4000] Training [8/16] Loss: 0.00261 +Epoch [3225/4000] Training [9/16] Loss: 0.00274 +Epoch [3225/4000] Training [10/16] Loss: 0.00291 +Epoch [3225/4000] Training [11/16] Loss: 0.00217 +Epoch [3225/4000] Training [12/16] Loss: 0.00223 +Epoch [3225/4000] Training [13/16] Loss: 0.00340 +Epoch [3225/4000] Training [14/16] Loss: 0.00436 +Epoch [3225/4000] Training [15/16] Loss: 0.00255 +Epoch [3225/4000] Training [16/16] Loss: 0.00257 +Epoch [3225/4000] Training metric {'Train/mean dice_metric': 0.9984082579612732, 'Train/mean miou_metric': 0.9965236186981201, 'Train/mean f1': 0.9933786988258362, 'Train/mean precision': 0.9886780977249146, 'Train/mean recall': 0.9981242418289185, 'Train/mean hd95_metric': 0.6726837754249573} +Epoch [3225/4000] Validation [1/4] Loss: 0.37684 focal_loss 0.31204 dice_loss 0.06480 +Epoch [3225/4000] Validation [2/4] Loss: 0.95981 focal_loss 0.75975 dice_loss 0.20006 +Epoch [3225/4000] Validation [3/4] Loss: 0.53432 focal_loss 0.43674 dice_loss 0.09758 +Epoch [3225/4000] Validation [4/4] Loss: 0.30890 focal_loss 0.22788 dice_loss 0.08102 +Epoch [3225/4000] Validation metric {'Val/mean dice_metric': 0.9720994830131531, 'Val/mean miou_metric': 0.9581331014633179, 'Val/mean f1': 0.9759522676467896, 'Val/mean precision': 0.9743742346763611, 'Val/mean recall': 0.9775354862213135, 'Val/mean hd95_metric': 5.2875590324401855} +Cheakpoint... +Epoch [3225/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720994830131531, 'Val/mean miou_metric': 0.9581331014633179, 'Val/mean f1': 0.9759522676467896, 'Val/mean precision': 0.9743742346763611, 'Val/mean recall': 0.9775354862213135, 'Val/mean hd95_metric': 5.2875590324401855} +Epoch [3226/4000] Training [1/16] Loss: 0.00348 +Epoch [3226/4000] Training [2/16] Loss: 0.00175 +Epoch [3226/4000] Training [3/16] Loss: 0.00263 +Epoch [3226/4000] Training [4/16] Loss: 0.00244 +Epoch [3226/4000] Training [5/16] Loss: 0.00266 +Epoch [3226/4000] Training [6/16] Loss: 0.00435 +Epoch [3226/4000] Training [7/16] Loss: 0.00324 +Epoch [3226/4000] Training [8/16] Loss: 0.00312 +Epoch [3226/4000] Training [9/16] Loss: 0.00301 +Epoch [3226/4000] Training [10/16] Loss: 0.00281 +Epoch [3226/4000] Training [11/16] Loss: 0.00252 +Epoch [3226/4000] Training [12/16] Loss: 0.00172 +Epoch [3226/4000] Training [13/16] Loss: 0.00297 +Epoch [3226/4000] Training [14/16] Loss: 0.00262 +Epoch [3226/4000] Training [15/16] Loss: 0.00222 +Epoch [3226/4000] Training [16/16] Loss: 0.00248 +Epoch [3226/4000] Training metric {'Train/mean dice_metric': 0.9985584020614624, 'Train/mean miou_metric': 0.9968377351760864, 'Train/mean f1': 0.9934779405593872, 'Train/mean precision': 0.9887365698814392, 'Train/mean recall': 0.9982650279998779, 'Train/mean hd95_metric': 0.6245394349098206} +Epoch [3226/4000] Validation [1/4] Loss: 0.41452 focal_loss 0.34762 dice_loss 0.06689 +Epoch [3226/4000] Validation [2/4] Loss: 0.97306 focal_loss 0.75742 dice_loss 0.21564 +Epoch [3226/4000] Validation [3/4] Loss: 0.51095 focal_loss 0.42204 dice_loss 0.08891 +Epoch [3226/4000] Validation [4/4] Loss: 0.42410 focal_loss 0.31866 dice_loss 0.10544 +Epoch [3226/4000] Validation metric {'Val/mean dice_metric': 0.9726316332817078, 'Val/mean miou_metric': 0.9584769010543823, 'Val/mean f1': 0.9755291938781738, 'Val/mean precision': 0.9735320806503296, 'Val/mean recall': 0.9775345921516418, 'Val/mean hd95_metric': 4.995145320892334} +Cheakpoint... +Epoch [3226/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726316332817078, 'Val/mean miou_metric': 0.9584769010543823, 'Val/mean f1': 0.9755291938781738, 'Val/mean precision': 0.9735320806503296, 'Val/mean recall': 0.9775345921516418, 'Val/mean hd95_metric': 4.995145320892334} +Epoch [3227/4000] Training [1/16] Loss: 0.00275 +Epoch [3227/4000] Training [2/16] Loss: 0.00314 +Epoch [3227/4000] Training [3/16] Loss: 0.00192 +Epoch [3227/4000] Training [4/16] Loss: 0.00314 +Epoch [3227/4000] Training [5/16] Loss: 0.00210 +Epoch [3227/4000] Training [6/16] Loss: 0.00267 +Epoch [3227/4000] Training [7/16] Loss: 0.00340 +Epoch [3227/4000] Training [8/16] Loss: 0.00362 +Epoch [3227/4000] Training [9/16] Loss: 0.00358 +Epoch [3227/4000] Training [10/16] Loss: 0.00264 +Epoch [3227/4000] Training [11/16] Loss: 0.00336 +Epoch [3227/4000] Training [12/16] Loss: 0.00284 +Epoch [3227/4000] Training [13/16] Loss: 0.00391 +Epoch [3227/4000] Training [14/16] Loss: 0.00227 +Epoch [3227/4000] Training [15/16] Loss: 0.00497 +Epoch [3227/4000] Training [16/16] Loss: 0.00263 +Epoch [3227/4000] Training metric {'Train/mean dice_metric': 0.998235821723938, 'Train/mean miou_metric': 0.9962082505226135, 'Train/mean f1': 0.993292510509491, 'Train/mean precision': 0.9887442588806152, 'Train/mean recall': 0.9978827238082886, 'Train/mean hd95_metric': 0.6598449349403381} +Epoch [3227/4000] Validation [1/4] Loss: 0.51659 focal_loss 0.43017 dice_loss 0.08642 +Epoch [3227/4000] Validation [2/4] Loss: 0.40343 focal_loss 0.30262 dice_loss 0.10081 +Epoch [3227/4000] Validation [3/4] Loss: 0.54819 focal_loss 0.44900 dice_loss 0.09918 +Epoch [3227/4000] Validation [4/4] Loss: 0.31614 focal_loss 0.22794 dice_loss 0.08819 +Epoch [3227/4000] Validation metric {'Val/mean dice_metric': 0.9739953279495239, 'Val/mean miou_metric': 0.9594591856002808, 'Val/mean f1': 0.9756535887718201, 'Val/mean precision': 0.9734718799591064, 'Val/mean recall': 0.9778451323509216, 'Val/mean hd95_metric': 4.879767894744873} +Cheakpoint... +Epoch [3227/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739953279495239, 'Val/mean miou_metric': 0.9594591856002808, 'Val/mean f1': 0.9756535887718201, 'Val/mean precision': 0.9734718799591064, 'Val/mean recall': 0.9778451323509216, 'Val/mean hd95_metric': 4.879767894744873} +Epoch [3228/4000] Training [1/16] Loss: 0.00259 +Epoch [3228/4000] Training [2/16] Loss: 0.00320 +Epoch [3228/4000] Training [3/16] Loss: 0.00255 +Epoch [3228/4000] Training [4/16] Loss: 0.00228 +Epoch [3228/4000] Training [5/16] Loss: 0.00316 +Epoch [3228/4000] Training [6/16] Loss: 0.00226 +Epoch [3228/4000] Training [7/16] Loss: 0.00356 +Epoch [3228/4000] Training [8/16] Loss: 0.00232 +Epoch [3228/4000] Training [9/16] Loss: 0.00349 +Epoch [3228/4000] Training [10/16] Loss: 0.00237 +Epoch [3228/4000] Training [11/16] Loss: 0.00284 +Epoch [3228/4000] Training [12/16] Loss: 0.00170 +Epoch [3228/4000] Training [13/16] Loss: 0.00194 +Epoch [3228/4000] Training [14/16] Loss: 0.00226 +Epoch [3228/4000] Training [15/16] Loss: 0.00392 +Epoch [3228/4000] Training [16/16] Loss: 0.00297 +Epoch [3228/4000] Training metric {'Train/mean dice_metric': 0.9984829425811768, 'Train/mean miou_metric': 0.9966935515403748, 'Train/mean f1': 0.9935925006866455, 'Train/mean precision': 0.989070475101471, 'Train/mean recall': 0.9981561303138733, 'Train/mean hd95_metric': 0.6772736310958862} +Epoch [3228/4000] Validation [1/4] Loss: 0.39428 focal_loss 0.33042 dice_loss 0.06386 +Epoch [3228/4000] Validation [2/4] Loss: 0.39698 focal_loss 0.29705 dice_loss 0.09993 +Epoch [3228/4000] Validation [3/4] Loss: 0.47909 focal_loss 0.39297 dice_loss 0.08612 +Epoch [3228/4000] Validation [4/4] Loss: 0.31810 focal_loss 0.23310 dice_loss 0.08500 +Epoch [3228/4000] Validation metric {'Val/mean dice_metric': 0.9749763607978821, 'Val/mean miou_metric': 0.9608726501464844, 'Val/mean f1': 0.9767266511917114, 'Val/mean precision': 0.9740922451019287, 'Val/mean recall': 0.9793753623962402, 'Val/mean hd95_metric': 4.806763648986816} +Cheakpoint... +Epoch [3228/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749763607978821, 'Val/mean miou_metric': 0.9608726501464844, 'Val/mean f1': 0.9767266511917114, 'Val/mean precision': 0.9740922451019287, 'Val/mean recall': 0.9793753623962402, 'Val/mean hd95_metric': 4.806763648986816} +Epoch [3229/4000] Training [1/16] Loss: 0.00328 +Epoch [3229/4000] Training [2/16] Loss: 0.00199 +Epoch [3229/4000] Training [3/16] Loss: 0.00424 +Epoch [3229/4000] Training [4/16] Loss: 0.00348 +Epoch [3229/4000] Training [5/16] Loss: 0.00386 +Epoch [3229/4000] Training [6/16] Loss: 0.00285 +Epoch [3229/4000] Training [7/16] Loss: 0.00291 +Epoch [3229/4000] Training [8/16] Loss: 0.00294 +Epoch [3229/4000] Training [9/16] Loss: 0.00296 +Epoch [3229/4000] Training [10/16] Loss: 0.00204 +Epoch [3229/4000] Training [11/16] Loss: 0.00249 +Epoch [3229/4000] Training [12/16] Loss: 0.00217 +Epoch [3229/4000] Training [13/16] Loss: 0.00309 +Epoch [3229/4000] Training [14/16] Loss: 0.00194 +Epoch [3229/4000] Training [15/16] Loss: 0.00227 +Epoch [3229/4000] Training [16/16] Loss: 0.00210 +Epoch [3229/4000] Training metric {'Train/mean dice_metric': 0.9984359741210938, 'Train/mean miou_metric': 0.9966039061546326, 'Train/mean f1': 0.9935177564620972, 'Train/mean precision': 0.989027738571167, 'Train/mean recall': 0.9980486631393433, 'Train/mean hd95_metric': 0.7110456228256226} +Epoch [3229/4000] Validation [1/4] Loss: 0.42999 focal_loss 0.36465 dice_loss 0.06534 +Epoch [3229/4000] Validation [2/4] Loss: 0.50508 focal_loss 0.36395 dice_loss 0.14113 +Epoch [3229/4000] Validation [3/4] Loss: 0.47205 focal_loss 0.38230 dice_loss 0.08976 +Epoch [3229/4000] Validation [4/4] Loss: 0.30462 focal_loss 0.22416 dice_loss 0.08046 +Epoch [3229/4000] Validation metric {'Val/mean dice_metric': 0.9753358960151672, 'Val/mean miou_metric': 0.9610870480537415, 'Val/mean f1': 0.976439356803894, 'Val/mean precision': 0.973686695098877, 'Val/mean recall': 0.9792075753211975, 'Val/mean hd95_metric': 4.775771617889404} +Cheakpoint... +Epoch [3229/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753358960151672, 'Val/mean miou_metric': 0.9610870480537415, 'Val/mean f1': 0.976439356803894, 'Val/mean precision': 0.973686695098877, 'Val/mean recall': 0.9792075753211975, 'Val/mean hd95_metric': 4.775771617889404} +Epoch [3230/4000] Training [1/16] Loss: 0.00270 +Epoch [3230/4000] Training [2/16] Loss: 0.00293 +Epoch [3230/4000] Training [3/16] Loss: 0.00236 +Epoch [3230/4000] Training [4/16] Loss: 0.00236 +Epoch [3230/4000] Training [5/16] Loss: 0.00248 +Epoch [3230/4000] Training [6/16] Loss: 0.00363 +Epoch [3230/4000] Training [7/16] Loss: 0.00206 +Epoch [3230/4000] Training [8/16] Loss: 0.00331 +Epoch [3230/4000] Training [9/16] Loss: 0.00298 +Epoch [3230/4000] Training [10/16] Loss: 0.00223 +Epoch [3230/4000] Training [11/16] Loss: 0.00341 +Epoch [3230/4000] Training [12/16] Loss: 0.00198 +Epoch [3230/4000] Training [13/16] Loss: 0.00272 +Epoch [3230/4000] Training [14/16] Loss: 0.00270 +Epoch [3230/4000] Training [15/16] Loss: 0.00418 +Epoch [3230/4000] Training [16/16] Loss: 0.00263 +Epoch [3230/4000] Training metric {'Train/mean dice_metric': 0.9984569549560547, 'Train/mean miou_metric': 0.9966319799423218, 'Train/mean f1': 0.9934677481651306, 'Train/mean precision': 0.988802433013916, 'Train/mean recall': 0.9981774091720581, 'Train/mean hd95_metric': 0.6786409616470337} +Epoch [3230/4000] Validation [1/4] Loss: 0.38225 focal_loss 0.31911 dice_loss 0.06313 +Epoch [3230/4000] Validation [2/4] Loss: 0.39916 focal_loss 0.29493 dice_loss 0.10423 +Epoch [3230/4000] Validation [3/4] Loss: 0.24595 focal_loss 0.18666 dice_loss 0.05930 +Epoch [3230/4000] Validation [4/4] Loss: 0.37806 focal_loss 0.26692 dice_loss 0.11114 +Epoch [3230/4000] Validation metric {'Val/mean dice_metric': 0.9747081995010376, 'Val/mean miou_metric': 0.9608137011528015, 'Val/mean f1': 0.9766767024993896, 'Val/mean precision': 0.9740909337997437, 'Val/mean recall': 0.979276180267334, 'Val/mean hd95_metric': 4.647769927978516} +Cheakpoint... +Epoch [3230/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747081995010376, 'Val/mean miou_metric': 0.9608137011528015, 'Val/mean f1': 0.9766767024993896, 'Val/mean precision': 0.9740909337997437, 'Val/mean recall': 0.979276180267334, 'Val/mean hd95_metric': 4.647769927978516} +Epoch [3231/4000] Training [1/16] Loss: 0.00314 +Epoch [3231/4000] Training [2/16] Loss: 0.00228 +Epoch [3231/4000] Training [3/16] Loss: 0.00373 +Epoch [3231/4000] Training [4/16] Loss: 0.00188 +Epoch [3231/4000] Training [5/16] Loss: 0.00191 +Epoch [3231/4000] Training [6/16] Loss: 0.00235 +Epoch [3231/4000] Training [7/16] Loss: 0.00304 +Epoch [3231/4000] Training [8/16] Loss: 0.00228 +Epoch [3231/4000] Training [9/16] Loss: 0.00224 +Epoch [3231/4000] Training [10/16] Loss: 0.00277 +Epoch [3231/4000] Training [11/16] Loss: 0.00182 +Epoch [3231/4000] Training [12/16] Loss: 0.00244 +Epoch [3231/4000] Training [13/16] Loss: 0.00225 +Epoch [3231/4000] Training [14/16] Loss: 0.00401 +Epoch [3231/4000] Training [15/16] Loss: 0.00314 +Epoch [3231/4000] Training [16/16] Loss: 0.00408 +Epoch [3231/4000] Training metric {'Train/mean dice_metric': 0.9986468553543091, 'Train/mean miou_metric': 0.9970090985298157, 'Train/mean f1': 0.9936307668685913, 'Train/mean precision': 0.988982081413269, 'Train/mean recall': 0.9983233213424683, 'Train/mean hd95_metric': 0.6378905773162842} +Epoch [3231/4000] Validation [1/4] Loss: 0.38089 focal_loss 0.31891 dice_loss 0.06198 +Epoch [3231/4000] Validation [2/4] Loss: 0.83621 focal_loss 0.64575 dice_loss 0.19046 +Epoch [3231/4000] Validation [3/4] Loss: 0.51085 focal_loss 0.41883 dice_loss 0.09202 +Epoch [3231/4000] Validation [4/4] Loss: 0.32101 focal_loss 0.22389 dice_loss 0.09711 +Epoch [3231/4000] Validation metric {'Val/mean dice_metric': 0.973265528678894, 'Val/mean miou_metric': 0.9596415758132935, 'Val/mean f1': 0.9762218594551086, 'Val/mean precision': 0.9741158485412598, 'Val/mean recall': 0.9783370494842529, 'Val/mean hd95_metric': 5.004763126373291} +Cheakpoint... +Epoch [3231/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973265528678894, 'Val/mean miou_metric': 0.9596415758132935, 'Val/mean f1': 0.9762218594551086, 'Val/mean precision': 0.9741158485412598, 'Val/mean recall': 0.9783370494842529, 'Val/mean hd95_metric': 5.004763126373291} +Epoch [3232/4000] Training [1/16] Loss: 0.00538 +Epoch [3232/4000] Training [2/16] Loss: 0.00198 +Epoch [3232/4000] Training [3/16] Loss: 0.00251 +Epoch [3232/4000] Training [4/16] Loss: 0.00290 +Epoch [3232/4000] Training [5/16] Loss: 0.00300 +Epoch [3232/4000] Training [6/16] Loss: 0.00295 +Epoch [3232/4000] Training [7/16] Loss: 0.00348 +Epoch [3232/4000] Training [8/16] Loss: 0.00290 +Epoch [3232/4000] Training [9/16] Loss: 0.00343 +Epoch [3232/4000] Training [10/16] Loss: 0.00296 +Epoch [3232/4000] Training [11/16] Loss: 0.00273 +Epoch [3232/4000] Training [12/16] Loss: 0.00221 +Epoch [3232/4000] Training [13/16] Loss: 0.00214 +Epoch [3232/4000] Training [14/16] Loss: 0.00205 +Epoch [3232/4000] Training [15/16] Loss: 0.00209 +Epoch [3232/4000] Training [16/16] Loss: 0.00310 +Epoch [3232/4000] Training metric {'Train/mean dice_metric': 0.9984387159347534, 'Train/mean miou_metric': 0.9965784549713135, 'Train/mean f1': 0.9928441047668457, 'Train/mean precision': 0.9877051115036011, 'Train/mean recall': 0.9980368614196777, 'Train/mean hd95_metric': 0.6860867142677307} +Epoch [3232/4000] Validation [1/4] Loss: 0.46566 focal_loss 0.39970 dice_loss 0.06595 +Epoch [3232/4000] Validation [2/4] Loss: 0.38113 focal_loss 0.27934 dice_loss 0.10180 +Epoch [3232/4000] Validation [3/4] Loss: 0.56778 focal_loss 0.46507 dice_loss 0.10271 +Epoch [3232/4000] Validation [4/4] Loss: 0.31180 focal_loss 0.22854 dice_loss 0.08326 +Epoch [3232/4000] Validation metric {'Val/mean dice_metric': 0.9729652404785156, 'Val/mean miou_metric': 0.9590386152267456, 'Val/mean f1': 0.9753603935241699, 'Val/mean precision': 0.9716169238090515, 'Val/mean recall': 0.979132890701294, 'Val/mean hd95_metric': 5.8546624183654785} +Cheakpoint... +Epoch [3232/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729652404785156, 'Val/mean miou_metric': 0.9590386152267456, 'Val/mean f1': 0.9753603935241699, 'Val/mean precision': 0.9716169238090515, 'Val/mean recall': 0.979132890701294, 'Val/mean hd95_metric': 5.8546624183654785} +Epoch [3233/4000] Training [1/16] Loss: 0.00288 +Epoch [3233/4000] Training [2/16] Loss: 0.00298 +Epoch [3233/4000] Training [3/16] Loss: 0.00252 +Epoch [3233/4000] Training [4/16] Loss: 0.00329 +Epoch [3233/4000] Training [5/16] Loss: 0.00300 +Epoch [3233/4000] Training [6/16] Loss: 0.00252 +Epoch [3233/4000] Training [7/16] Loss: 0.00304 +Epoch [3233/4000] Training [8/16] Loss: 0.00382 +Epoch [3233/4000] Training [9/16] Loss: 0.00275 +Epoch [3233/4000] Training [10/16] Loss: 0.00294 +Epoch [3233/4000] Training [11/16] Loss: 0.00315 +Epoch [3233/4000] Training [12/16] Loss: 0.00374 +Epoch [3233/4000] Training [13/16] Loss: 0.00263 +Epoch [3233/4000] Training [14/16] Loss: 0.00376 +Epoch [3233/4000] Training [15/16] Loss: 0.00416 +Epoch [3233/4000] Training [16/16] Loss: 0.00181 +Epoch [3233/4000] Training metric {'Train/mean dice_metric': 0.9982285499572754, 'Train/mean miou_metric': 0.9961904883384705, 'Train/mean f1': 0.9933962821960449, 'Train/mean precision': 0.9888246059417725, 'Train/mean recall': 0.9980103969573975, 'Train/mean hd95_metric': 0.7231369614601135} +Epoch [3233/4000] Validation [1/4] Loss: 0.38258 focal_loss 0.31813 dice_loss 0.06445 +Epoch [3233/4000] Validation [2/4] Loss: 0.76596 focal_loss 0.56088 dice_loss 0.20508 +Epoch [3233/4000] Validation [3/4] Loss: 0.49937 focal_loss 0.40755 dice_loss 0.09183 +Epoch [3233/4000] Validation [4/4] Loss: 0.36470 focal_loss 0.25927 dice_loss 0.10543 +Epoch [3233/4000] Validation metric {'Val/mean dice_metric': 0.9722013473510742, 'Val/mean miou_metric': 0.9574422836303711, 'Val/mean f1': 0.9754233360290527, 'Val/mean precision': 0.9734681844711304, 'Val/mean recall': 0.9773863554000854, 'Val/mean hd95_metric': 4.970349311828613} +Cheakpoint... +Epoch [3233/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722013473510742, 'Val/mean miou_metric': 0.9574422836303711, 'Val/mean f1': 0.9754233360290527, 'Val/mean precision': 0.9734681844711304, 'Val/mean recall': 0.9773863554000854, 'Val/mean hd95_metric': 4.970349311828613} +Epoch [3234/4000] Training [1/16] Loss: 0.00217 +Epoch [3234/4000] Training [2/16] Loss: 0.00196 +Epoch [3234/4000] Training [3/16] Loss: 0.00257 +Epoch [3234/4000] Training [4/16] Loss: 0.00210 +Epoch [3234/4000] Training [5/16] Loss: 0.00508 +Epoch [3234/4000] Training [6/16] Loss: 0.00228 +Epoch [3234/4000] Training [7/16] Loss: 0.00238 +Epoch [3234/4000] Training [8/16] Loss: 0.00148 +Epoch [3234/4000] Training [9/16] Loss: 0.00314 +Epoch [3234/4000] Training [10/16] Loss: 0.00284 +Epoch [3234/4000] Training [11/16] Loss: 0.00217 +Epoch [3234/4000] Training [12/16] Loss: 0.00290 +Epoch [3234/4000] Training [13/16] Loss: 0.00423 +Epoch [3234/4000] Training [14/16] Loss: 0.00292 +Epoch [3234/4000] Training [15/16] Loss: 0.00214 +Epoch [3234/4000] Training [16/16] Loss: 0.00299 +Epoch [3234/4000] Training metric {'Train/mean dice_metric': 0.9984680414199829, 'Train/mean miou_metric': 0.9966641664505005, 'Train/mean f1': 0.9935779571533203, 'Train/mean precision': 0.989088237285614, 'Train/mean recall': 0.9981086254119873, 'Train/mean hd95_metric': 0.6685823202133179} +Epoch [3234/4000] Validation [1/4] Loss: 0.38904 focal_loss 0.32666 dice_loss 0.06238 +Epoch [3234/4000] Validation [2/4] Loss: 0.87451 focal_loss 0.66822 dice_loss 0.20629 +Epoch [3234/4000] Validation [3/4] Loss: 0.47805 focal_loss 0.38379 dice_loss 0.09427 +Epoch [3234/4000] Validation [4/4] Loss: 0.48927 focal_loss 0.36848 dice_loss 0.12079 +Epoch [3234/4000] Validation metric {'Val/mean dice_metric': 0.973078727722168, 'Val/mean miou_metric': 0.9588869214057922, 'Val/mean f1': 0.9756782054901123, 'Val/mean precision': 0.9723906517028809, 'Val/mean recall': 0.9789880514144897, 'Val/mean hd95_metric': 4.9179463386535645} +Cheakpoint... +Epoch [3234/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973078727722168, 'Val/mean miou_metric': 0.9588869214057922, 'Val/mean f1': 0.9756782054901123, 'Val/mean precision': 0.9723906517028809, 'Val/mean recall': 0.9789880514144897, 'Val/mean hd95_metric': 4.9179463386535645} +Epoch [3235/4000] Training [1/16] Loss: 0.00278 +Epoch [3235/4000] Training [2/16] Loss: 0.00372 +Epoch [3235/4000] Training [3/16] Loss: 0.00260 +Epoch [3235/4000] Training [4/16] Loss: 0.00351 +Epoch [3235/4000] Training [5/16] Loss: 0.00293 +Epoch [3235/4000] Training [6/16] Loss: 0.00208 +Epoch [3235/4000] Training [7/16] Loss: 0.00220 +Epoch [3235/4000] Training [8/16] Loss: 0.00260 +Epoch [3235/4000] Training [9/16] Loss: 0.00261 +Epoch [3235/4000] Training [10/16] Loss: 0.00295 +Epoch [3235/4000] Training [11/16] Loss: 0.00300 +Epoch [3235/4000] Training [12/16] Loss: 0.00249 +Epoch [3235/4000] Training [13/16] Loss: 0.00257 +Epoch [3235/4000] Training [14/16] Loss: 0.00471 +Epoch [3235/4000] Training [15/16] Loss: 0.00189 +Epoch [3235/4000] Training [16/16] Loss: 0.00327 +Epoch [3235/4000] Training metric {'Train/mean dice_metric': 0.998618483543396, 'Train/mean miou_metric': 0.9969624280929565, 'Train/mean f1': 0.993614673614502, 'Train/mean precision': 0.9890288710594177, 'Train/mean recall': 0.9982432126998901, 'Train/mean hd95_metric': 0.6422150731086731} +Epoch [3235/4000] Validation [1/4] Loss: 0.39049 focal_loss 0.32706 dice_loss 0.06342 +Epoch [3235/4000] Validation [2/4] Loss: 0.51421 focal_loss 0.37617 dice_loss 0.13804 +Epoch [3235/4000] Validation [3/4] Loss: 0.56220 focal_loss 0.46114 dice_loss 0.10107 +Epoch [3235/4000] Validation [4/4] Loss: 0.40697 focal_loss 0.29770 dice_loss 0.10928 +Epoch [3235/4000] Validation metric {'Val/mean dice_metric': 0.9747880101203918, 'Val/mean miou_metric': 0.9602975845336914, 'Val/mean f1': 0.9760800004005432, 'Val/mean precision': 0.9733384847640991, 'Val/mean recall': 0.9788370132446289, 'Val/mean hd95_metric': 4.9498291015625} +Cheakpoint... +Epoch [3235/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747880101203918, 'Val/mean miou_metric': 0.9602975845336914, 'Val/mean f1': 0.9760800004005432, 'Val/mean precision': 0.9733384847640991, 'Val/mean recall': 0.9788370132446289, 'Val/mean hd95_metric': 4.9498291015625} +Epoch [3236/4000] Training [1/16] Loss: 0.00284 +Epoch [3236/4000] Training [2/16] Loss: 0.00362 +Epoch [3236/4000] Training [3/16] Loss: 0.00290 +Epoch [3236/4000] Training [4/16] Loss: 0.00329 +Epoch [3236/4000] Training [5/16] Loss: 0.00232 +Epoch [3236/4000] Training [6/16] Loss: 0.00327 +Epoch [3236/4000] Training [7/16] Loss: 0.00343 +Epoch [3236/4000] Training [8/16] Loss: 0.00316 +Epoch [3236/4000] Training [9/16] Loss: 0.00250 +Epoch [3236/4000] Training [10/16] Loss: 0.00318 +Epoch [3236/4000] Training [11/16] Loss: 0.00281 +Epoch [3236/4000] Training [12/16] Loss: 0.00239 +Epoch [3236/4000] Training [13/16] Loss: 0.00621 +Epoch [3236/4000] Training [14/16] Loss: 0.00251 +Epoch [3236/4000] Training [15/16] Loss: 0.00221 +Epoch [3236/4000] Training [16/16] Loss: 0.00302 +Epoch [3236/4000] Training metric {'Train/mean dice_metric': 0.9983326196670532, 'Train/mean miou_metric': 0.9963639974594116, 'Train/mean f1': 0.9927725195884705, 'Train/mean precision': 0.9875998497009277, 'Train/mean recall': 0.9979997277259827, 'Train/mean hd95_metric': 0.6898292303085327} +Epoch [3236/4000] Validation [1/4] Loss: 0.41232 focal_loss 0.34821 dice_loss 0.06411 +Epoch [3236/4000] Validation [2/4] Loss: 0.47168 focal_loss 0.35567 dice_loss 0.11601 +Epoch [3236/4000] Validation [3/4] Loss: 0.49390 focal_loss 0.40537 dice_loss 0.08853 +Epoch [3236/4000] Validation [4/4] Loss: 0.39534 focal_loss 0.29191 dice_loss 0.10343 +Epoch [3236/4000] Validation metric {'Val/mean dice_metric': 0.9741153717041016, 'Val/mean miou_metric': 0.9596952199935913, 'Val/mean f1': 0.975788950920105, 'Val/mean precision': 0.972829282283783, 'Val/mean recall': 0.978766679763794, 'Val/mean hd95_metric': 4.9058661460876465} +Cheakpoint... +Epoch [3236/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741153717041016, 'Val/mean miou_metric': 0.9596952199935913, 'Val/mean f1': 0.975788950920105, 'Val/mean precision': 0.972829282283783, 'Val/mean recall': 0.978766679763794, 'Val/mean hd95_metric': 4.9058661460876465} +Epoch [3237/4000] Training [1/16] Loss: 0.00361 +Epoch [3237/4000] Training [2/16] Loss: 0.00203 +Epoch [3237/4000] Training [3/16] Loss: 0.00334 +Epoch [3237/4000] Training [4/16] Loss: 0.00317 +Epoch [3237/4000] Training [5/16] Loss: 0.00246 +Epoch [3237/4000] Training [6/16] Loss: 0.00254 +Epoch [3237/4000] Training [7/16] Loss: 0.00309 +Epoch [3237/4000] Training [8/16] Loss: 0.00305 +Epoch [3237/4000] Training [9/16] Loss: 0.00408 +Epoch [3237/4000] Training [10/16] Loss: 0.00370 +Epoch [3237/4000] Training [11/16] Loss: 0.00307 +Epoch [3237/4000] Training [12/16] Loss: 0.00244 +Epoch [3237/4000] Training [13/16] Loss: 0.00406 +Epoch [3237/4000] Training [14/16] Loss: 0.00339 +Epoch [3237/4000] Training [15/16] Loss: 0.00197 +Epoch [3237/4000] Training [16/16] Loss: 0.00285 +Epoch [3237/4000] Training metric {'Train/mean dice_metric': 0.998375654220581, 'Train/mean miou_metric': 0.9964755773544312, 'Train/mean f1': 0.9933454394340515, 'Train/mean precision': 0.9887445569038391, 'Train/mean recall': 0.997989296913147, 'Train/mean hd95_metric': 0.6955353617668152} +Epoch [3237/4000] Validation [1/4] Loss: 0.42394 focal_loss 0.35967 dice_loss 0.06427 +Epoch [3237/4000] Validation [2/4] Loss: 0.43725 focal_loss 0.32847 dice_loss 0.10878 +Epoch [3237/4000] Validation [3/4] Loss: 0.50552 focal_loss 0.41060 dice_loss 0.09491 +Epoch [3237/4000] Validation [4/4] Loss: 0.44073 focal_loss 0.33014 dice_loss 0.11059 +Epoch [3237/4000] Validation metric {'Val/mean dice_metric': 0.9755657911300659, 'Val/mean miou_metric': 0.9608978033065796, 'Val/mean f1': 0.9760250449180603, 'Val/mean precision': 0.972754955291748, 'Val/mean recall': 0.9793172478675842, 'Val/mean hd95_metric': 5.146773338317871} +Cheakpoint... +Epoch [3237/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755657911300659, 'Val/mean miou_metric': 0.9608978033065796, 'Val/mean f1': 0.9760250449180603, 'Val/mean precision': 0.972754955291748, 'Val/mean recall': 0.9793172478675842, 'Val/mean hd95_metric': 5.146773338317871} +Epoch [3238/4000] Training [1/16] Loss: 0.00234 +Epoch [3238/4000] Training [2/16] Loss: 0.00347 +Epoch [3238/4000] Training [3/16] Loss: 0.00263 +Epoch [3238/4000] Training [4/16] Loss: 0.00419 +Epoch [3238/4000] Training [5/16] Loss: 0.00262 +Epoch [3238/4000] Training [6/16] Loss: 0.00272 +Epoch [3238/4000] Training [7/16] Loss: 0.00350 +Epoch [3238/4000] Training [8/16] Loss: 0.00312 +Epoch [3238/4000] Training [9/16] Loss: 0.00261 +Epoch [3238/4000] Training [10/16] Loss: 0.00213 +Epoch [3238/4000] Training [11/16] Loss: 0.00355 +Epoch [3238/4000] Training [12/16] Loss: 0.00347 +Epoch [3238/4000] Training [13/16] Loss: 0.00473 +Epoch [3238/4000] Training [14/16] Loss: 0.00372 +Epoch [3238/4000] Training [15/16] Loss: 0.00275 +Epoch [3238/4000] Training [16/16] Loss: 0.00231 +Epoch [3238/4000] Training metric {'Train/mean dice_metric': 0.9983190298080444, 'Train/mean miou_metric': 0.9963693618774414, 'Train/mean f1': 0.9934428930282593, 'Train/mean precision': 0.9889346361160278, 'Train/mean recall': 0.9979923963546753, 'Train/mean hd95_metric': 0.6992462873458862} +Epoch [3238/4000] Validation [1/4] Loss: 0.37381 focal_loss 0.31140 dice_loss 0.06241 +Epoch [3238/4000] Validation [2/4] Loss: 0.87183 focal_loss 0.66429 dice_loss 0.20754 +Epoch [3238/4000] Validation [3/4] Loss: 0.53345 focal_loss 0.44001 dice_loss 0.09344 +Epoch [3238/4000] Validation [4/4] Loss: 0.37329 focal_loss 0.27243 dice_loss 0.10086 +Epoch [3238/4000] Validation metric {'Val/mean dice_metric': 0.972176194190979, 'Val/mean miou_metric': 0.9577732086181641, 'Val/mean f1': 0.9753125309944153, 'Val/mean precision': 0.9726320505142212, 'Val/mean recall': 0.9780080318450928, 'Val/mean hd95_metric': 5.102464199066162} +Cheakpoint... +Epoch [3238/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972176194190979, 'Val/mean miou_metric': 0.9577732086181641, 'Val/mean f1': 0.9753125309944153, 'Val/mean precision': 0.9726320505142212, 'Val/mean recall': 0.9780080318450928, 'Val/mean hd95_metric': 5.102464199066162} +Epoch [3239/4000] Training [1/16] Loss: 0.00319 +Epoch [3239/4000] Training [2/16] Loss: 0.00186 +Epoch [3239/4000] Training [3/16] Loss: 0.00236 +Epoch [3239/4000] Training [4/16] Loss: 0.00305 +Epoch [3239/4000] Training [5/16] Loss: 0.00365 +Epoch [3239/4000] Training [6/16] Loss: 0.00204 +Epoch [3239/4000] Training [7/16] Loss: 0.00341 +Epoch [3239/4000] Training [8/16] Loss: 0.00332 +Epoch [3239/4000] Training [9/16] Loss: 0.00204 +Epoch [3239/4000] Training [10/16] Loss: 0.00245 +Epoch [3239/4000] Training [11/16] Loss: 0.00268 +Epoch [3239/4000] Training [12/16] Loss: 0.00231 +Epoch [3239/4000] Training [13/16] Loss: 0.00356 +Epoch [3239/4000] Training [14/16] Loss: 0.00278 +Epoch [3239/4000] Training [15/16] Loss: 0.00235 +Epoch [3239/4000] Training [16/16] Loss: 0.00316 +Epoch [3239/4000] Training metric {'Train/mean dice_metric': 0.9984828233718872, 'Train/mean miou_metric': 0.9966963529586792, 'Train/mean f1': 0.9935914874076843, 'Train/mean precision': 0.9890537261962891, 'Train/mean recall': 0.998171329498291, 'Train/mean hd95_metric': 0.6664772033691406} +Epoch [3239/4000] Validation [1/4] Loss: 0.34446 focal_loss 0.28474 dice_loss 0.05972 +Epoch [3239/4000] Validation [2/4] Loss: 0.43512 focal_loss 0.32521 dice_loss 0.10991 +Epoch [3239/4000] Validation [3/4] Loss: 0.25041 focal_loss 0.18897 dice_loss 0.06143 +Epoch [3239/4000] Validation [4/4] Loss: 0.30550 focal_loss 0.22154 dice_loss 0.08396 +Epoch [3239/4000] Validation metric {'Val/mean dice_metric': 0.9749774932861328, 'Val/mean miou_metric': 0.9609438180923462, 'Val/mean f1': 0.9763821959495544, 'Val/mean precision': 0.9738938808441162, 'Val/mean recall': 0.9788832664489746, 'Val/mean hd95_metric': 4.978981971740723} +Cheakpoint... +Epoch [3239/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749774932861328, 'Val/mean miou_metric': 0.9609438180923462, 'Val/mean f1': 0.9763821959495544, 'Val/mean precision': 0.9738938808441162, 'Val/mean recall': 0.9788832664489746, 'Val/mean hd95_metric': 4.978981971740723} +Epoch [3240/4000] Training [1/16] Loss: 0.00264 +Epoch [3240/4000] Training [2/16] Loss: 0.00240 +Epoch [3240/4000] Training [3/16] Loss: 0.00193 +Epoch [3240/4000] Training [4/16] Loss: 0.00243 +Epoch [3240/4000] Training [5/16] Loss: 0.00259 +Epoch [3240/4000] Training [6/16] Loss: 0.00281 +Epoch [3240/4000] Training [7/16] Loss: 0.00252 +Epoch [3240/4000] Training [8/16] Loss: 0.00239 +Epoch [3240/4000] Training [9/16] Loss: 0.00293 +Epoch [3240/4000] Training [10/16] Loss: 0.00234 +Epoch [3240/4000] Training [11/16] Loss: 0.00272 +Epoch [3240/4000] Training [12/16] Loss: 0.00234 +Epoch [3240/4000] Training [13/16] Loss: 0.00324 +Epoch [3240/4000] Training [14/16] Loss: 0.00285 +Epoch [3240/4000] Training [15/16] Loss: 0.00312 +Epoch [3240/4000] Training [16/16] Loss: 0.00283 +Epoch [3240/4000] Training metric {'Train/mean dice_metric': 0.9985182285308838, 'Train/mean miou_metric': 0.9967670440673828, 'Train/mean f1': 0.9937307834625244, 'Train/mean precision': 0.989209771156311, 'Train/mean recall': 0.9982933402061462, 'Train/mean hd95_metric': 0.6572402715682983} +Epoch [3240/4000] Validation [1/4] Loss: 0.41023 focal_loss 0.34640 dice_loss 0.06383 +Epoch [3240/4000] Validation [2/4] Loss: 1.31928 focal_loss 1.02461 dice_loss 0.29468 +Epoch [3240/4000] Validation [3/4] Loss: 0.50501 focal_loss 0.41010 dice_loss 0.09491 +Epoch [3240/4000] Validation [4/4] Loss: 0.48869 focal_loss 0.36367 dice_loss 0.12502 +Epoch [3240/4000] Validation metric {'Val/mean dice_metric': 0.9711118936538696, 'Val/mean miou_metric': 0.9573914408683777, 'Val/mean f1': 0.9757970571517944, 'Val/mean precision': 0.9737379550933838, 'Val/mean recall': 0.9778649210929871, 'Val/mean hd95_metric': 5.010904312133789} +Cheakpoint... +Epoch [3240/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9711], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9711118936538696, 'Val/mean miou_metric': 0.9573914408683777, 'Val/mean f1': 0.9757970571517944, 'Val/mean precision': 0.9737379550933838, 'Val/mean recall': 0.9778649210929871, 'Val/mean hd95_metric': 5.010904312133789} +Epoch [3241/4000] Training [1/16] Loss: 0.00198 +Epoch [3241/4000] Training [2/16] Loss: 0.00278 +Epoch [3241/4000] Training [3/16] Loss: 0.00407 +Epoch [3241/4000] Training [4/16] Loss: 0.00266 +Epoch [3241/4000] Training [5/16] Loss: 0.00262 +Epoch [3241/4000] Training [6/16] Loss: 0.00307 +Epoch [3241/4000] Training [7/16] Loss: 0.00262 +Epoch [3241/4000] Training [8/16] Loss: 0.00246 +Epoch [3241/4000] Training [9/16] Loss: 0.00271 +Epoch [3241/4000] Training [10/16] Loss: 0.00194 +Epoch [3241/4000] Training [11/16] Loss: 0.00395 +Epoch [3241/4000] Training [12/16] Loss: 0.00306 +Epoch [3241/4000] Training [13/16] Loss: 0.00249 +Epoch [3241/4000] Training [14/16] Loss: 0.00346 +Epoch [3241/4000] Training [15/16] Loss: 0.00242 +Epoch [3241/4000] Training [16/16] Loss: 0.00253 +Epoch [3241/4000] Training metric {'Train/mean dice_metric': 0.9985339641571045, 'Train/mean miou_metric': 0.996796727180481, 'Train/mean f1': 0.9937137365341187, 'Train/mean precision': 0.9892572164535522, 'Train/mean recall': 0.9982106685638428, 'Train/mean hd95_metric': 0.6720001697540283} +Epoch [3241/4000] Validation [1/4] Loss: 0.45112 focal_loss 0.38452 dice_loss 0.06660 +Epoch [3241/4000] Validation [2/4] Loss: 0.88212 focal_loss 0.68636 dice_loss 0.19576 +Epoch [3241/4000] Validation [3/4] Loss: 0.28330 focal_loss 0.21372 dice_loss 0.06958 +Epoch [3241/4000] Validation [4/4] Loss: 0.30281 focal_loss 0.21755 dice_loss 0.08526 +Epoch [3241/4000] Validation metric {'Val/mean dice_metric': 0.9737833142280579, 'Val/mean miou_metric': 0.9603608846664429, 'Val/mean f1': 0.9765289425849915, 'Val/mean precision': 0.9750040173530579, 'Val/mean recall': 0.9780586957931519, 'Val/mean hd95_metric': 5.023414611816406} +Cheakpoint... +Epoch [3241/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737833142280579, 'Val/mean miou_metric': 0.9603608846664429, 'Val/mean f1': 0.9765289425849915, 'Val/mean precision': 0.9750040173530579, 'Val/mean recall': 0.9780586957931519, 'Val/mean hd95_metric': 5.023414611816406} +Epoch [3242/4000] Training [1/16] Loss: 0.00281 +Epoch [3242/4000] Training [2/16] Loss: 0.00266 +Epoch [3242/4000] Training [3/16] Loss: 0.00251 +Epoch [3242/4000] Training [4/16] Loss: 0.00213 +Epoch [3242/4000] Training [5/16] Loss: 0.00247 +Epoch [3242/4000] Training [6/16] Loss: 0.00357 +Epoch [3242/4000] Training [7/16] Loss: 0.00228 +Epoch [3242/4000] Training [8/16] Loss: 0.00256 +Epoch [3242/4000] Training [9/16] Loss: 0.00311 +Epoch [3242/4000] Training [10/16] Loss: 0.00210 +Epoch [3242/4000] Training [11/16] Loss: 0.00235 +Epoch [3242/4000] Training [12/16] Loss: 0.00372 +Epoch [3242/4000] Training [13/16] Loss: 0.00254 +Epoch [3242/4000] Training [14/16] Loss: 0.00276 +Epoch [3242/4000] Training [15/16] Loss: 0.00326 +Epoch [3242/4000] Training [16/16] Loss: 0.00260 +Epoch [3242/4000] Training metric {'Train/mean dice_metric': 0.9984604120254517, 'Train/mean miou_metric': 0.9966430068016052, 'Train/mean f1': 0.9934742450714111, 'Train/mean precision': 0.9888449311256409, 'Train/mean recall': 0.9981470704078674, 'Train/mean hd95_metric': 0.6638248562812805} +Epoch [3242/4000] Validation [1/4] Loss: 0.40382 focal_loss 0.34082 dice_loss 0.06300 +Epoch [3242/4000] Validation [2/4] Loss: 0.93187 focal_loss 0.71921 dice_loss 0.21266 +Epoch [3242/4000] Validation [3/4] Loss: 0.53617 focal_loss 0.43584 dice_loss 0.10033 +Epoch [3242/4000] Validation [4/4] Loss: 0.43747 focal_loss 0.32593 dice_loss 0.11154 +Epoch [3242/4000] Validation metric {'Val/mean dice_metric': 0.9716987609863281, 'Val/mean miou_metric': 0.9573101997375488, 'Val/mean f1': 0.9753963351249695, 'Val/mean precision': 0.9735320806503296, 'Val/mean recall': 0.9772676825523376, 'Val/mean hd95_metric': 5.605865001678467} +Cheakpoint... +Epoch [3242/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716987609863281, 'Val/mean miou_metric': 0.9573101997375488, 'Val/mean f1': 0.9753963351249695, 'Val/mean precision': 0.9735320806503296, 'Val/mean recall': 0.9772676825523376, 'Val/mean hd95_metric': 5.605865001678467} +Epoch [3243/4000] Training [1/16] Loss: 0.00195 +Epoch [3243/4000] Training [2/16] Loss: 0.00324 +Epoch [3243/4000] Training [3/16] Loss: 0.00311 +Epoch [3243/4000] Training [4/16] Loss: 0.00318 +Epoch [3243/4000] Training [5/16] Loss: 0.00222 +Epoch [3243/4000] Training [6/16] Loss: 0.00388 +Epoch [3243/4000] Training [7/16] Loss: 0.00278 +Epoch [3243/4000] Training [8/16] Loss: 0.00226 +Epoch [3243/4000] Training [9/16] Loss: 0.00319 +Epoch [3243/4000] Training [10/16] Loss: 0.00219 +Epoch [3243/4000] Training [11/16] Loss: 0.00282 +Epoch [3243/4000] Training [12/16] Loss: 0.00312 +Epoch [3243/4000] Training [13/16] Loss: 0.00523 +Epoch [3243/4000] Training [14/16] Loss: 0.00321 +Epoch [3243/4000] Training [15/16] Loss: 0.00260 +Epoch [3243/4000] Training [16/16] Loss: 0.00230 +Epoch [3243/4000] Training metric {'Train/mean dice_metric': 0.9983971118927002, 'Train/mean miou_metric': 0.9965140223503113, 'Train/mean f1': 0.993435800075531, 'Train/mean precision': 0.9888849854469299, 'Train/mean recall': 0.9980287551879883, 'Train/mean hd95_metric': 0.6630159020423889} +Epoch [3243/4000] Validation [1/4] Loss: 0.45932 focal_loss 0.38217 dice_loss 0.07714 +Epoch [3243/4000] Validation [2/4] Loss: 0.39794 focal_loss 0.29480 dice_loss 0.10314 +Epoch [3243/4000] Validation [3/4] Loss: 0.48697 focal_loss 0.39746 dice_loss 0.08950 +Epoch [3243/4000] Validation [4/4] Loss: 0.46317 focal_loss 0.35581 dice_loss 0.10736 +Epoch [3243/4000] Validation metric {'Val/mean dice_metric': 0.9726840257644653, 'Val/mean miou_metric': 0.9588214755058289, 'Val/mean f1': 0.9763705134391785, 'Val/mean precision': 0.9747757911682129, 'Val/mean recall': 0.9779704213142395, 'Val/mean hd95_metric': 4.849286079406738} +Cheakpoint... +Epoch [3243/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726840257644653, 'Val/mean miou_metric': 0.9588214755058289, 'Val/mean f1': 0.9763705134391785, 'Val/mean precision': 0.9747757911682129, 'Val/mean recall': 0.9779704213142395, 'Val/mean hd95_metric': 4.849286079406738} +Epoch [3244/4000] Training [1/16] Loss: 0.00236 +Epoch [3244/4000] Training [2/16] Loss: 0.00261 +Epoch [3244/4000] Training [3/16] Loss: 0.00287 +Epoch [3244/4000] Training [4/16] Loss: 0.00322 +Epoch [3244/4000] Training [5/16] Loss: 0.00286 +Epoch [3244/4000] Training [6/16] Loss: 0.00251 +Epoch [3244/4000] Training [7/16] Loss: 0.00278 +Epoch [3244/4000] Training [8/16] Loss: 0.00404 +Epoch [3244/4000] Training [9/16] Loss: 0.00215 +Epoch [3244/4000] Training [10/16] Loss: 0.00267 +Epoch [3244/4000] Training [11/16] Loss: 0.00488 +Epoch [3244/4000] Training [12/16] Loss: 0.00363 +Epoch [3244/4000] Training [13/16] Loss: 0.00169 +Epoch [3244/4000] Training [14/16] Loss: 0.00293 +Epoch [3244/4000] Training [15/16] Loss: 0.00285 +Epoch [3244/4000] Training [16/16] Loss: 0.00357 +Epoch [3244/4000] Training metric {'Train/mean dice_metric': 0.9984456300735474, 'Train/mean miou_metric': 0.9966217279434204, 'Train/mean f1': 0.9935873746871948, 'Train/mean precision': 0.9890813827514648, 'Train/mean recall': 0.9981346130371094, 'Train/mean hd95_metric': 0.7074493169784546} +Epoch [3244/4000] Validation [1/4] Loss: 0.39644 focal_loss 0.33478 dice_loss 0.06166 +Epoch [3244/4000] Validation [2/4] Loss: 0.41222 focal_loss 0.30695 dice_loss 0.10528 +Epoch [3244/4000] Validation [3/4] Loss: 0.59703 focal_loss 0.48825 dice_loss 0.10877 +Epoch [3244/4000] Validation [4/4] Loss: 0.33481 focal_loss 0.24954 dice_loss 0.08527 +Epoch [3244/4000] Validation metric {'Val/mean dice_metric': 0.9739890098571777, 'Val/mean miou_metric': 0.9600345492362976, 'Val/mean f1': 0.9760362505912781, 'Val/mean precision': 0.9730337262153625, 'Val/mean recall': 0.9790573120117188, 'Val/mean hd95_metric': 5.489489555358887} +Cheakpoint... +Epoch [3244/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739890098571777, 'Val/mean miou_metric': 0.9600345492362976, 'Val/mean f1': 0.9760362505912781, 'Val/mean precision': 0.9730337262153625, 'Val/mean recall': 0.9790573120117188, 'Val/mean hd95_metric': 5.489489555358887} +Epoch [3245/4000] Training [1/16] Loss: 0.00242 +Epoch [3245/4000] Training [2/16] Loss: 0.00268 +Epoch [3245/4000] Training [3/16] Loss: 0.00342 +Epoch [3245/4000] Training [4/16] Loss: 0.00410 +Epoch [3245/4000] Training [5/16] Loss: 0.00277 +Epoch [3245/4000] Training [6/16] Loss: 0.00198 +Epoch [3245/4000] Training [7/16] Loss: 0.00424 +Epoch [3245/4000] Training [8/16] Loss: 0.00253 +Epoch [3245/4000] Training [9/16] Loss: 0.00296 +Epoch [3245/4000] Training [10/16] Loss: 0.00198 +Epoch [3245/4000] Training [11/16] Loss: 0.00280 +Epoch [3245/4000] Training [12/16] Loss: 0.00348 +Epoch [3245/4000] Training [13/16] Loss: 0.00313 +Epoch [3245/4000] Training [14/16] Loss: 0.00252 +Epoch [3245/4000] Training [15/16] Loss: 0.00266 +Epoch [3245/4000] Training [16/16] Loss: 0.00213 +Epoch [3245/4000] Training metric {'Train/mean dice_metric': 0.9984667301177979, 'Train/mean miou_metric': 0.9966549873352051, 'Train/mean f1': 0.9934969544410706, 'Train/mean precision': 0.988899290561676, 'Train/mean recall': 0.9981375932693481, 'Train/mean hd95_metric': 0.6699969172477722} +Epoch [3245/4000] Validation [1/4] Loss: 0.40877 focal_loss 0.34542 dice_loss 0.06335 +Epoch [3245/4000] Validation [2/4] Loss: 0.84669 focal_loss 0.64244 dice_loss 0.20425 +Epoch [3245/4000] Validation [3/4] Loss: 0.30815 focal_loss 0.23389 dice_loss 0.07426 +Epoch [3245/4000] Validation [4/4] Loss: 0.29973 focal_loss 0.21712 dice_loss 0.08261 +Epoch [3245/4000] Validation metric {'Val/mean dice_metric': 0.9727897644042969, 'Val/mean miou_metric': 0.9587559700012207, 'Val/mean f1': 0.9757099151611328, 'Val/mean precision': 0.9729344248771667, 'Val/mean recall': 0.9785013198852539, 'Val/mean hd95_metric': 5.62376070022583} +Cheakpoint... +Epoch [3245/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727897644042969, 'Val/mean miou_metric': 0.9587559700012207, 'Val/mean f1': 0.9757099151611328, 'Val/mean precision': 0.9729344248771667, 'Val/mean recall': 0.9785013198852539, 'Val/mean hd95_metric': 5.62376070022583} +Epoch [3246/4000] Training [1/16] Loss: 0.00201 +Epoch [3246/4000] Training [2/16] Loss: 0.00255 +Epoch [3246/4000] Training [3/16] Loss: 0.00191 +Epoch [3246/4000] Training [4/16] Loss: 0.00274 +Epoch [3246/4000] Training [5/16] Loss: 0.00243 +Epoch [3246/4000] Training [6/16] Loss: 0.00244 +Epoch [3246/4000] Training [7/16] Loss: 0.00230 +Epoch [3246/4000] Training [8/16] Loss: 0.00200 +Epoch [3246/4000] Training [9/16] Loss: 0.00231 +Epoch [3246/4000] Training [10/16] Loss: 0.00231 +Epoch [3246/4000] Training [11/16] Loss: 0.00178 +Epoch [3246/4000] Training [12/16] Loss: 0.00356 +Epoch [3246/4000] Training [13/16] Loss: 0.00251 +Epoch [3246/4000] Training [14/16] Loss: 0.00264 +Epoch [3246/4000] Training [15/16] Loss: 0.00395 +Epoch [3246/4000] Training [16/16] Loss: 0.00312 +Epoch [3246/4000] Training metric {'Train/mean dice_metric': 0.9986006021499634, 'Train/mean miou_metric': 0.9969020485877991, 'Train/mean f1': 0.9933207035064697, 'Train/mean precision': 0.9884613156318665, 'Train/mean recall': 0.998228132724762, 'Train/mean hd95_metric': 0.640945553779602} +Epoch [3246/4000] Validation [1/4] Loss: 0.36148 focal_loss 0.29884 dice_loss 0.06264 +Epoch [3246/4000] Validation [2/4] Loss: 0.52390 focal_loss 0.38073 dice_loss 0.14317 +Epoch [3246/4000] Validation [3/4] Loss: 0.52028 focal_loss 0.42484 dice_loss 0.09544 +Epoch [3246/4000] Validation [4/4] Loss: 0.35648 focal_loss 0.25801 dice_loss 0.09846 +Epoch [3246/4000] Validation metric {'Val/mean dice_metric': 0.9735884666442871, 'Val/mean miou_metric': 0.9592499732971191, 'Val/mean f1': 0.9760478138923645, 'Val/mean precision': 0.9739702343940735, 'Val/mean recall': 0.9781343340873718, 'Val/mean hd95_metric': 4.876614570617676} +Cheakpoint... +Epoch [3246/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735884666442871, 'Val/mean miou_metric': 0.9592499732971191, 'Val/mean f1': 0.9760478138923645, 'Val/mean precision': 0.9739702343940735, 'Val/mean recall': 0.9781343340873718, 'Val/mean hd95_metric': 4.876614570617676} +Epoch [3247/4000] Training [1/16] Loss: 0.00335 +Epoch [3247/4000] Training [2/16] Loss: 0.00197 +Epoch [3247/4000] Training [3/16] Loss: 0.00208 +Epoch [3247/4000] Training [4/16] Loss: 0.00241 +Epoch [3247/4000] Training [5/16] Loss: 0.00269 +Epoch [3247/4000] Training [6/16] Loss: 0.00316 +Epoch [3247/4000] Training [7/16] Loss: 0.00264 +Epoch [3247/4000] Training [8/16] Loss: 0.00347 +Epoch [3247/4000] Training [9/16] Loss: 0.00228 +Epoch [3247/4000] Training [10/16] Loss: 0.00281 +Epoch [3247/4000] Training [11/16] Loss: 0.00249 +Epoch [3247/4000] Training [12/16] Loss: 0.00196 +Epoch [3247/4000] Training [13/16] Loss: 0.00332 +Epoch [3247/4000] Training [14/16] Loss: 0.00282 +Epoch [3247/4000] Training [15/16] Loss: 0.00216 +Epoch [3247/4000] Training [16/16] Loss: 0.00233 +Epoch [3247/4000] Training metric {'Train/mean dice_metric': 0.9985299706459045, 'Train/mean miou_metric': 0.9967721104621887, 'Train/mean f1': 0.9933744072914124, 'Train/mean precision': 0.9885934591293335, 'Train/mean recall': 0.998201847076416, 'Train/mean hd95_metric': 0.6747347116470337} +Epoch [3247/4000] Validation [1/4] Loss: 0.36437 focal_loss 0.30307 dice_loss 0.06130 +Epoch [3247/4000] Validation [2/4] Loss: 0.42861 focal_loss 0.32171 dice_loss 0.10690 +Epoch [3247/4000] Validation [3/4] Loss: 0.49131 focal_loss 0.40043 dice_loss 0.09088 +Epoch [3247/4000] Validation [4/4] Loss: 0.44270 focal_loss 0.33451 dice_loss 0.10819 +Epoch [3247/4000] Validation metric {'Val/mean dice_metric': 0.9739179611206055, 'Val/mean miou_metric': 0.9596349596977234, 'Val/mean f1': 0.9761971831321716, 'Val/mean precision': 0.9730960130691528, 'Val/mean recall': 0.9793182611465454, 'Val/mean hd95_metric': 5.0777692794799805} +Cheakpoint... +Epoch [3247/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739179611206055, 'Val/mean miou_metric': 0.9596349596977234, 'Val/mean f1': 0.9761971831321716, 'Val/mean precision': 0.9730960130691528, 'Val/mean recall': 0.9793182611465454, 'Val/mean hd95_metric': 5.0777692794799805} +Epoch [3248/4000] Training [1/16] Loss: 0.00267 +Epoch [3248/4000] Training [2/16] Loss: 0.00269 +Epoch [3248/4000] Training [3/16] Loss: 0.00272 +Epoch [3248/4000] Training [4/16] Loss: 0.00384 +Epoch [3248/4000] Training [5/16] Loss: 0.00297 +Epoch [3248/4000] Training [6/16] Loss: 0.00365 +Epoch [3248/4000] Training [7/16] Loss: 0.00298 +Epoch [3248/4000] Training [8/16] Loss: 0.00298 +Epoch [3248/4000] Training [9/16] Loss: 0.00268 +Epoch [3248/4000] Training [10/16] Loss: 0.00417 +Epoch [3248/4000] Training [11/16] Loss: 0.00344 +Epoch [3248/4000] Training [12/16] Loss: 0.00274 +Epoch [3248/4000] Training [13/16] Loss: 0.00288 +Epoch [3248/4000] Training [14/16] Loss: 0.00198 +Epoch [3248/4000] Training [15/16] Loss: 0.00185 +Epoch [3248/4000] Training [16/16] Loss: 0.00229 +Epoch [3248/4000] Training metric {'Train/mean dice_metric': 0.9984778165817261, 'Train/mean miou_metric': 0.9966773986816406, 'Train/mean f1': 0.9934366345405579, 'Train/mean precision': 0.988802433013916, 'Train/mean recall': 0.9981144070625305, 'Train/mean hd95_metric': 0.6481721997261047} +Epoch [3248/4000] Validation [1/4] Loss: 0.39594 focal_loss 0.33167 dice_loss 0.06427 +Epoch [3248/4000] Validation [2/4] Loss: 0.40714 focal_loss 0.30245 dice_loss 0.10469 +Epoch [3248/4000] Validation [3/4] Loss: 0.54677 focal_loss 0.44878 dice_loss 0.09800 +Epoch [3248/4000] Validation [4/4] Loss: 0.31307 focal_loss 0.23200 dice_loss 0.08107 +Epoch [3248/4000] Validation metric {'Val/mean dice_metric': 0.974452793598175, 'Val/mean miou_metric': 0.9601764678955078, 'Val/mean f1': 0.9760202169418335, 'Val/mean precision': 0.9728399515151978, 'Val/mean recall': 0.9792213439941406, 'Val/mean hd95_metric': 4.894034385681152} +Cheakpoint... +Epoch [3248/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974452793598175, 'Val/mean miou_metric': 0.9601764678955078, 'Val/mean f1': 0.9760202169418335, 'Val/mean precision': 0.9728399515151978, 'Val/mean recall': 0.9792213439941406, 'Val/mean hd95_metric': 4.894034385681152} +Epoch [3249/4000] Training [1/16] Loss: 0.00271 +Epoch [3249/4000] Training [2/16] Loss: 0.00256 +Epoch [3249/4000] Training [3/16] Loss: 0.00187 +Epoch [3249/4000] Training [4/16] Loss: 0.00269 +Epoch [3249/4000] Training [5/16] Loss: 0.00303 +Epoch [3249/4000] Training [6/16] Loss: 0.00252 +Epoch [3249/4000] Training [7/16] Loss: 0.00263 +Epoch [3249/4000] Training [8/16] Loss: 0.00268 +Epoch [3249/4000] Training [9/16] Loss: 0.00193 +Epoch [3249/4000] Training [10/16] Loss: 0.00248 +Epoch [3249/4000] Training [11/16] Loss: 0.00287 +Epoch [3249/4000] Training [12/16] Loss: 0.00286 +Epoch [3249/4000] Training [13/16] Loss: 0.00259 +Epoch [3249/4000] Training [14/16] Loss: 0.00308 +Epoch [3249/4000] Training [15/16] Loss: 0.00228 +Epoch [3249/4000] Training [16/16] Loss: 0.00245 +Epoch [3249/4000] Training metric {'Train/mean dice_metric': 0.9986366629600525, 'Train/mean miou_metric': 0.9969989061355591, 'Train/mean f1': 0.9936115741729736, 'Train/mean precision': 0.9890565872192383, 'Train/mean recall': 0.9982087016105652, 'Train/mean hd95_metric': 0.6340396404266357} +Epoch [3249/4000] Validation [1/4] Loss: 0.38956 focal_loss 0.32508 dice_loss 0.06449 +Epoch [3249/4000] Validation [2/4] Loss: 0.58452 focal_loss 0.43146 dice_loss 0.15307 +Epoch [3249/4000] Validation [3/4] Loss: 0.52209 focal_loss 0.41921 dice_loss 0.10287 +Epoch [3249/4000] Validation [4/4] Loss: 0.28036 focal_loss 0.19942 dice_loss 0.08094 +Epoch [3249/4000] Validation metric {'Val/mean dice_metric': 0.9737324714660645, 'Val/mean miou_metric': 0.9593780636787415, 'Val/mean f1': 0.9760224223136902, 'Val/mean precision': 0.9728633165359497, 'Val/mean recall': 0.9792020320892334, 'Val/mean hd95_metric': 5.034725189208984} +Cheakpoint... +Epoch [3249/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737324714660645, 'Val/mean miou_metric': 0.9593780636787415, 'Val/mean f1': 0.9760224223136902, 'Val/mean precision': 0.9728633165359497, 'Val/mean recall': 0.9792020320892334, 'Val/mean hd95_metric': 5.034725189208984} +Epoch [3250/4000] Training [1/16] Loss: 0.00268 +Epoch [3250/4000] Training [2/16] Loss: 0.00239 +Epoch [3250/4000] Training [3/16] Loss: 0.00253 +Epoch [3250/4000] Training [4/16] Loss: 0.00343 +Epoch [3250/4000] Training [5/16] Loss: 0.00185 +Epoch [3250/4000] Training [6/16] Loss: 0.00356 +Epoch [3250/4000] Training [7/16] Loss: 0.00189 +Epoch [3250/4000] Training [8/16] Loss: 0.00242 +Epoch [3250/4000] Training [9/16] Loss: 0.00268 +Epoch [3250/4000] Training [10/16] Loss: 0.00321 +Epoch [3250/4000] Training [11/16] Loss: 0.00296 +Epoch [3250/4000] Training [12/16] Loss: 0.00200 +Epoch [3250/4000] Training [13/16] Loss: 0.00188 +Epoch [3250/4000] Training [14/16] Loss: 0.00312 +Epoch [3250/4000] Training [15/16] Loss: 0.00207 +Epoch [3250/4000] Training [16/16] Loss: 0.00238 +Epoch [3250/4000] Training metric {'Train/mean dice_metric': 0.998558521270752, 'Train/mean miou_metric': 0.996809720993042, 'Train/mean f1': 0.9927784204483032, 'Train/mean precision': 0.9874612092971802, 'Train/mean recall': 0.9981532096862793, 'Train/mean hd95_metric': 0.6572540998458862} +Epoch [3250/4000] Validation [1/4] Loss: 0.41059 focal_loss 0.34725 dice_loss 0.06335 +Epoch [3250/4000] Validation [2/4] Loss: 0.58032 focal_loss 0.42857 dice_loss 0.15175 +Epoch [3250/4000] Validation [3/4] Loss: 0.48516 focal_loss 0.38860 dice_loss 0.09656 +Epoch [3250/4000] Validation [4/4] Loss: 0.36153 focal_loss 0.25900 dice_loss 0.10254 +Epoch [3250/4000] Validation metric {'Val/mean dice_metric': 0.9742168188095093, 'Val/mean miou_metric': 0.960041880607605, 'Val/mean f1': 0.9753313660621643, 'Val/mean precision': 0.9706199169158936, 'Val/mean recall': 0.9800887107849121, 'Val/mean hd95_metric': 5.53269100189209} +Cheakpoint... +Epoch [3250/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742168188095093, 'Val/mean miou_metric': 0.960041880607605, 'Val/mean f1': 0.9753313660621643, 'Val/mean precision': 0.9706199169158936, 'Val/mean recall': 0.9800887107849121, 'Val/mean hd95_metric': 5.53269100189209} +Epoch [3251/4000] Training [1/16] Loss: 0.00292 +Epoch [3251/4000] Training [2/16] Loss: 0.00328 +Epoch [3251/4000] Training [3/16] Loss: 0.00219 +Epoch [3251/4000] Training [4/16] Loss: 0.00232 +Epoch [3251/4000] Training [5/16] Loss: 0.00210 +Epoch [3251/4000] Training [6/16] Loss: 0.00221 +Epoch [3251/4000] Training [7/16] Loss: 0.00272 +Epoch [3251/4000] Training [8/16] Loss: 0.00254 +Epoch [3251/4000] Training [9/16] Loss: 0.00265 +Epoch [3251/4000] Training [10/16] Loss: 0.00455 +Epoch [3251/4000] Training [11/16] Loss: 0.00283 +Epoch [3251/4000] Training [12/16] Loss: 0.00263 +Epoch [3251/4000] Training [13/16] Loss: 0.00267 +Epoch [3251/4000] Training [14/16] Loss: 0.00243 +Epoch [3251/4000] Training [15/16] Loss: 0.00355 +Epoch [3251/4000] Training [16/16] Loss: 0.00175 +Epoch [3251/4000] Training metric {'Train/mean dice_metric': 0.9986073970794678, 'Train/mean miou_metric': 0.9969334006309509, 'Train/mean f1': 0.9935218095779419, 'Train/mean precision': 0.9888570308685303, 'Train/mean recall': 0.9982308149337769, 'Train/mean hd95_metric': 0.6636993885040283} +Epoch [3251/4000] Validation [1/4] Loss: 0.40535 focal_loss 0.33692 dice_loss 0.06843 +Epoch [3251/4000] Validation [2/4] Loss: 0.42632 focal_loss 0.31581 dice_loss 0.11050 +Epoch [3251/4000] Validation [3/4] Loss: 0.53974 focal_loss 0.44429 dice_loss 0.09545 +Epoch [3251/4000] Validation [4/4] Loss: 0.31562 focal_loss 0.23151 dice_loss 0.08411 +Epoch [3251/4000] Validation metric {'Val/mean dice_metric': 0.9749221801757812, 'Val/mean miou_metric': 0.9609384536743164, 'Val/mean f1': 0.9765283465385437, 'Val/mean precision': 0.9728400111198425, 'Val/mean recall': 0.9802446961402893, 'Val/mean hd95_metric': 4.893942832946777} +Cheakpoint... +Epoch [3251/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749221801757812, 'Val/mean miou_metric': 0.9609384536743164, 'Val/mean f1': 0.9765283465385437, 'Val/mean precision': 0.9728400111198425, 'Val/mean recall': 0.9802446961402893, 'Val/mean hd95_metric': 4.893942832946777} +Epoch [3252/4000] Training [1/16] Loss: 0.00223 +Epoch [3252/4000] Training [2/16] Loss: 0.00479 +Epoch [3252/4000] Training [3/16] Loss: 0.00442 +Epoch [3252/4000] Training [4/16] Loss: 0.00201 +Epoch [3252/4000] Training [5/16] Loss: 0.00241 +Epoch [3252/4000] Training [6/16] Loss: 0.00270 +Epoch [3252/4000] Training [7/16] Loss: 0.00375 +Epoch [3252/4000] Training [8/16] Loss: 0.00278 +Epoch [3252/4000] Training [9/16] Loss: 0.00228 +Epoch [3252/4000] Training [10/16] Loss: 0.00209 +Epoch [3252/4000] Training [11/16] Loss: 0.00429 +Epoch [3252/4000] Training [12/16] Loss: 0.00353 +Epoch [3252/4000] Training [13/16] Loss: 0.00313 +Epoch [3252/4000] Training [14/16] Loss: 0.00317 +Epoch [3252/4000] Training [15/16] Loss: 0.00257 +Epoch [3252/4000] Training [16/16] Loss: 0.00204 +Epoch [3252/4000] Training metric {'Train/mean dice_metric': 0.9984807968139648, 'Train/mean miou_metric': 0.9966869354248047, 'Train/mean f1': 0.9934508800506592, 'Train/mean precision': 0.9888376593589783, 'Train/mean recall': 0.998107373714447, 'Train/mean hd95_metric': 0.6409178972244263} +Epoch [3252/4000] Validation [1/4] Loss: 0.37238 focal_loss 0.31019 dice_loss 0.06219 +Epoch [3252/4000] Validation [2/4] Loss: 0.42198 focal_loss 0.31653 dice_loss 0.10544 +Epoch [3252/4000] Validation [3/4] Loss: 0.52002 focal_loss 0.42817 dice_loss 0.09185 +Epoch [3252/4000] Validation [4/4] Loss: 0.35630 focal_loss 0.25105 dice_loss 0.10525 +Epoch [3252/4000] Validation metric {'Val/mean dice_metric': 0.9730388522148132, 'Val/mean miou_metric': 0.9589282870292664, 'Val/mean f1': 0.9757476449012756, 'Val/mean precision': 0.9738927483558655, 'Val/mean recall': 0.9776095747947693, 'Val/mean hd95_metric': 5.299559116363525} +Cheakpoint... +Epoch [3252/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730388522148132, 'Val/mean miou_metric': 0.9589282870292664, 'Val/mean f1': 0.9757476449012756, 'Val/mean precision': 0.9738927483558655, 'Val/mean recall': 0.9776095747947693, 'Val/mean hd95_metric': 5.299559116363525} +Epoch [3253/4000] Training [1/16] Loss: 0.00202 +Epoch [3253/4000] Training [2/16] Loss: 0.00255 +Epoch [3253/4000] Training [3/16] Loss: 0.00231 +Epoch [3253/4000] Training [4/16] Loss: 0.00363 +Epoch [3253/4000] Training [5/16] Loss: 0.00195 +Epoch [3253/4000] Training [6/16] Loss: 0.00244 +Epoch [3253/4000] Training [7/16] Loss: 0.00275 +Epoch [3253/4000] Training [8/16] Loss: 0.00205 +Epoch [3253/4000] Training [9/16] Loss: 0.00256 +Epoch [3253/4000] Training [10/16] Loss: 0.00217 +Epoch [3253/4000] Training [11/16] Loss: 0.00265 +Epoch [3253/4000] Training [12/16] Loss: 0.00279 +Epoch [3253/4000] Training [13/16] Loss: 0.00331 +Epoch [3253/4000] Training [14/16] Loss: 0.00321 +Epoch [3253/4000] Training [15/16] Loss: 0.00292 +Epoch [3253/4000] Training [16/16] Loss: 0.00216 +Epoch [3253/4000] Training metric {'Train/mean dice_metric': 0.998650312423706, 'Train/mean miou_metric': 0.9970267415046692, 'Train/mean f1': 0.9937440156936646, 'Train/mean precision': 0.9892749190330505, 'Train/mean recall': 0.9982536435127258, 'Train/mean hd95_metric': 0.5938751697540283} +Epoch [3253/4000] Validation [1/4] Loss: 0.36001 focal_loss 0.29928 dice_loss 0.06073 +Epoch [3253/4000] Validation [2/4] Loss: 0.43215 focal_loss 0.32212 dice_loss 0.11002 +Epoch [3253/4000] Validation [3/4] Loss: 0.50153 focal_loss 0.40823 dice_loss 0.09331 +Epoch [3253/4000] Validation [4/4] Loss: 0.32909 focal_loss 0.23462 dice_loss 0.09446 +Epoch [3253/4000] Validation metric {'Val/mean dice_metric': 0.9737693667411804, 'Val/mean miou_metric': 0.9594094157218933, 'Val/mean f1': 0.9760287404060364, 'Val/mean precision': 0.9732916951179504, 'Val/mean recall': 0.9787813425064087, 'Val/mean hd95_metric': 5.160143852233887} +Cheakpoint... +Epoch [3253/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737693667411804, 'Val/mean miou_metric': 0.9594094157218933, 'Val/mean f1': 0.9760287404060364, 'Val/mean precision': 0.9732916951179504, 'Val/mean recall': 0.9787813425064087, 'Val/mean hd95_metric': 5.160143852233887} +Epoch [3254/4000] Training [1/16] Loss: 0.00243 +Epoch [3254/4000] Training [2/16] Loss: 0.00352 +Epoch [3254/4000] Training [3/16] Loss: 0.00332 +Epoch [3254/4000] Training [4/16] Loss: 0.00262 +Epoch [3254/4000] Training [5/16] Loss: 0.00370 +Epoch [3254/4000] Training [6/16] Loss: 0.00313 +Epoch [3254/4000] Training [7/16] Loss: 0.00269 +Epoch [3254/4000] Training [8/16] Loss: 0.00326 +Epoch [3254/4000] Training [9/16] Loss: 0.00227 +Epoch [3254/4000] Training [10/16] Loss: 0.00208 +Epoch [3254/4000] Training [11/16] Loss: 0.00295 +Epoch [3254/4000] Training [12/16] Loss: 0.00228 +Epoch [3254/4000] Training [13/16] Loss: 0.00231 +Epoch [3254/4000] Training [14/16] Loss: 0.00286 +Epoch [3254/4000] Training [15/16] Loss: 0.00269 +Epoch [3254/4000] Training [16/16] Loss: 0.00207 +Epoch [3254/4000] Training metric {'Train/mean dice_metric': 0.9985767006874084, 'Train/mean miou_metric': 0.9968833327293396, 'Train/mean f1': 0.9935705661773682, 'Train/mean precision': 0.9890156984329224, 'Train/mean recall': 0.9981674551963806, 'Train/mean hd95_metric': 0.6239255666732788} +Epoch [3254/4000] Validation [1/4] Loss: 0.36573 focal_loss 0.30268 dice_loss 0.06305 +Epoch [3254/4000] Validation [2/4] Loss: 0.43725 focal_loss 0.32712 dice_loss 0.11013 +Epoch [3254/4000] Validation [3/4] Loss: 0.55671 focal_loss 0.46049 dice_loss 0.09622 +Epoch [3254/4000] Validation [4/4] Loss: 0.26041 focal_loss 0.18201 dice_loss 0.07841 +Epoch [3254/4000] Validation metric {'Val/mean dice_metric': 0.9735248684883118, 'Val/mean miou_metric': 0.9599006772041321, 'Val/mean f1': 0.9759279489517212, 'Val/mean precision': 0.9735989570617676, 'Val/mean recall': 0.9782680869102478, 'Val/mean hd95_metric': 5.18685245513916} +Cheakpoint... +Epoch [3254/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735248684883118, 'Val/mean miou_metric': 0.9599006772041321, 'Val/mean f1': 0.9759279489517212, 'Val/mean precision': 0.9735989570617676, 'Val/mean recall': 0.9782680869102478, 'Val/mean hd95_metric': 5.18685245513916} +Epoch [3255/4000] Training [1/16] Loss: 0.00278 +Epoch [3255/4000] Training [2/16] Loss: 0.00208 +Epoch [3255/4000] Training [3/16] Loss: 0.00424 +Epoch [3255/4000] Training [4/16] Loss: 0.00234 +Epoch [3255/4000] Training [5/16] Loss: 0.00295 +Epoch [3255/4000] Training [6/16] Loss: 0.00227 +Epoch [3255/4000] Training [7/16] Loss: 0.00240 +Epoch [3255/4000] Training [8/16] Loss: 0.00291 +Epoch [3255/4000] Training [9/16] Loss: 0.00274 +Epoch [3255/4000] Training [10/16] Loss: 0.00210 +Epoch [3255/4000] Training [11/16] Loss: 0.00279 +Epoch [3255/4000] Training [12/16] Loss: 0.00283 +Epoch [3255/4000] Training [13/16] Loss: 0.00264 +Epoch [3255/4000] Training [14/16] Loss: 0.00268 +Epoch [3255/4000] Training [15/16] Loss: 0.00290 +Epoch [3255/4000] Training [16/16] Loss: 0.00216 +Epoch [3255/4000] Training metric {'Train/mean dice_metric': 0.9986633658409119, 'Train/mean miou_metric': 0.9970413446426392, 'Train/mean f1': 0.9936456084251404, 'Train/mean precision': 0.9890207052230835, 'Train/mean recall': 0.9983139634132385, 'Train/mean hd95_metric': 0.626004159450531} +Epoch [3255/4000] Validation [1/4] Loss: 0.36497 focal_loss 0.30081 dice_loss 0.06416 +Epoch [3255/4000] Validation [2/4] Loss: 0.43956 focal_loss 0.33071 dice_loss 0.10885 +Epoch [3255/4000] Validation [3/4] Loss: 0.50419 focal_loss 0.41260 dice_loss 0.09160 +Epoch [3255/4000] Validation [4/4] Loss: 0.33178 focal_loss 0.24322 dice_loss 0.08856 +Epoch [3255/4000] Validation metric {'Val/mean dice_metric': 0.9755287170410156, 'Val/mean miou_metric': 0.9608936309814453, 'Val/mean f1': 0.9760326743125916, 'Val/mean precision': 0.9728441834449768, 'Val/mean recall': 0.9792423248291016, 'Val/mean hd95_metric': 5.067909240722656} +Cheakpoint... +Epoch [3255/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755287170410156, 'Val/mean miou_metric': 0.9608936309814453, 'Val/mean f1': 0.9760326743125916, 'Val/mean precision': 0.9728441834449768, 'Val/mean recall': 0.9792423248291016, 'Val/mean hd95_metric': 5.067909240722656} +Epoch [3256/4000] Training [1/16] Loss: 0.00375 +Epoch [3256/4000] Training [2/16] Loss: 0.00272 +Epoch [3256/4000] Training [3/16] Loss: 0.00434 +Epoch [3256/4000] Training [4/16] Loss: 0.00221 +Epoch [3256/4000] Training [5/16] Loss: 0.00226 +Epoch [3256/4000] Training [6/16] Loss: 0.00207 +Epoch [3256/4000] Training [7/16] Loss: 0.00257 +Epoch [3256/4000] Training [8/16] Loss: 0.00342 +Epoch [3256/4000] Training [9/16] Loss: 0.00296 +Epoch [3256/4000] Training [10/16] Loss: 0.00353 +Epoch [3256/4000] Training [11/16] Loss: 0.00262 +Epoch [3256/4000] Training [12/16] Loss: 0.00246 +Epoch [3256/4000] Training [13/16] Loss: 0.00219 +Epoch [3256/4000] Training [14/16] Loss: 0.00234 +Epoch [3256/4000] Training [15/16] Loss: 0.00281 +Epoch [3256/4000] Training [16/16] Loss: 0.00228 +Epoch [3256/4000] Training metric {'Train/mean dice_metric': 0.9985642433166504, 'Train/mean miou_metric': 0.996855616569519, 'Train/mean f1': 0.9935824275016785, 'Train/mean precision': 0.9890033602714539, 'Train/mean recall': 0.9982041120529175, 'Train/mean hd95_metric': 0.6308169960975647} +Epoch [3256/4000] Validation [1/4] Loss: 0.40178 focal_loss 0.33839 dice_loss 0.06339 +Epoch [3256/4000] Validation [2/4] Loss: 0.58292 focal_loss 0.43137 dice_loss 0.15155 +Epoch [3256/4000] Validation [3/4] Loss: 0.49404 focal_loss 0.40523 dice_loss 0.08881 +Epoch [3256/4000] Validation [4/4] Loss: 0.27867 focal_loss 0.19208 dice_loss 0.08659 +Epoch [3256/4000] Validation metric {'Val/mean dice_metric': 0.9739869236946106, 'Val/mean miou_metric': 0.9598299264907837, 'Val/mean f1': 0.9759189486503601, 'Val/mean precision': 0.97362220287323, 'Val/mean recall': 0.9782266020774841, 'Val/mean hd95_metric': 5.0362162590026855} +Cheakpoint... +Epoch [3256/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739869236946106, 'Val/mean miou_metric': 0.9598299264907837, 'Val/mean f1': 0.9759189486503601, 'Val/mean precision': 0.97362220287323, 'Val/mean recall': 0.9782266020774841, 'Val/mean hd95_metric': 5.0362162590026855} +Epoch [3257/4000] Training [1/16] Loss: 0.00389 +Epoch [3257/4000] Training [2/16] Loss: 0.00207 +Epoch [3257/4000] Training [3/16] Loss: 0.00286 +Epoch [3257/4000] Training [4/16] Loss: 0.00221 +Epoch [3257/4000] Training [5/16] Loss: 0.00315 +Epoch [3257/4000] Training [6/16] Loss: 0.00218 +Epoch [3257/4000] Training [7/16] Loss: 0.00392 +Epoch [3257/4000] Training [8/16] Loss: 0.00257 +Epoch [3257/4000] Training [9/16] Loss: 0.00288 +Epoch [3257/4000] Training [10/16] Loss: 0.00349 +Epoch [3257/4000] Training [11/16] Loss: 0.00388 +Epoch [3257/4000] Training [12/16] Loss: 0.00201 +Epoch [3257/4000] Training [13/16] Loss: 0.00295 +Epoch [3257/4000] Training [14/16] Loss: 0.00530 +Epoch [3257/4000] Training [15/16] Loss: 0.00263 +Epoch [3257/4000] Training [16/16] Loss: 0.00271 +Epoch [3257/4000] Training metric {'Train/mean dice_metric': 0.9982576966285706, 'Train/mean miou_metric': 0.9962466955184937, 'Train/mean f1': 0.9934068918228149, 'Train/mean precision': 0.9887662529945374, 'Train/mean recall': 0.9980912804603577, 'Train/mean hd95_metric': 0.7303218841552734} +Epoch [3257/4000] Validation [1/4] Loss: 0.41254 focal_loss 0.34898 dice_loss 0.06356 +Epoch [3257/4000] Validation [2/4] Loss: 0.98423 focal_loss 0.79551 dice_loss 0.18872 +Epoch [3257/4000] Validation [3/4] Loss: 0.46960 focal_loss 0.37274 dice_loss 0.09687 +Epoch [3257/4000] Validation [4/4] Loss: 0.32679 focal_loss 0.23949 dice_loss 0.08730 +Epoch [3257/4000] Validation metric {'Val/mean dice_metric': 0.9728344082832336, 'Val/mean miou_metric': 0.9593719244003296, 'Val/mean f1': 0.9760139584541321, 'Val/mean precision': 0.9740126729011536, 'Val/mean recall': 0.9780234694480896, 'Val/mean hd95_metric': 4.893415927886963} +Cheakpoint... +Epoch [3257/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728344082832336, 'Val/mean miou_metric': 0.9593719244003296, 'Val/mean f1': 0.9760139584541321, 'Val/mean precision': 0.9740126729011536, 'Val/mean recall': 0.9780234694480896, 'Val/mean hd95_metric': 4.893415927886963} +Epoch [3258/4000] Training [1/16] Loss: 0.00287 +Epoch [3258/4000] Training [2/16] Loss: 0.00232 +Epoch [3258/4000] Training [3/16] Loss: 0.00387 +Epoch [3258/4000] Training [4/16] Loss: 0.00386 +Epoch [3258/4000] Training [5/16] Loss: 0.00363 +Epoch [3258/4000] Training [6/16] Loss: 0.00298 +Epoch [3258/4000] Training [7/16] Loss: 0.00215 +Epoch [3258/4000] Training [8/16] Loss: 0.00284 +Epoch [3258/4000] Training [9/16] Loss: 0.00349 +Epoch [3258/4000] Training [10/16] Loss: 0.00235 +Epoch [3258/4000] Training [11/16] Loss: 0.00220 +Epoch [3258/4000] Training [12/16] Loss: 0.00209 +Epoch [3258/4000] Training [13/16] Loss: 0.00476 +Epoch [3258/4000] Training [14/16] Loss: 0.00300 +Epoch [3258/4000] Training [15/16] Loss: 0.00209 +Epoch [3258/4000] Training [16/16] Loss: 0.00309 +Epoch [3258/4000] Training metric {'Train/mean dice_metric': 0.998358964920044, 'Train/mean miou_metric': 0.9964509010314941, 'Train/mean f1': 0.9934420585632324, 'Train/mean precision': 0.9889305233955383, 'Train/mean recall': 0.9979948401451111, 'Train/mean hd95_metric': 0.6720001697540283} +Epoch [3258/4000] Validation [1/4] Loss: 0.45818 focal_loss 0.38839 dice_loss 0.06979 +Epoch [3258/4000] Validation [2/4] Loss: 0.44504 focal_loss 0.33629 dice_loss 0.10875 +Epoch [3258/4000] Validation [3/4] Loss: 0.49625 focal_loss 0.40727 dice_loss 0.08898 +Epoch [3258/4000] Validation [4/4] Loss: 0.26752 focal_loss 0.18516 dice_loss 0.08236 +Epoch [3258/4000] Validation metric {'Val/mean dice_metric': 0.9737812876701355, 'Val/mean miou_metric': 0.9595664739608765, 'Val/mean f1': 0.9759336113929749, 'Val/mean precision': 0.974149763584137, 'Val/mean recall': 0.9777238965034485, 'Val/mean hd95_metric': 4.961310386657715} +Cheakpoint... +Epoch [3258/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737812876701355, 'Val/mean miou_metric': 0.9595664739608765, 'Val/mean f1': 0.9759336113929749, 'Val/mean precision': 0.974149763584137, 'Val/mean recall': 0.9777238965034485, 'Val/mean hd95_metric': 4.961310386657715} +Epoch [3259/4000] Training [1/16] Loss: 0.00171 +Epoch [3259/4000] Training [2/16] Loss: 0.00276 +Epoch [3259/4000] Training [3/16] Loss: 0.00324 +Epoch [3259/4000] Training [4/16] Loss: 0.00183 +Epoch [3259/4000] Training [5/16] Loss: 0.00364 +Epoch [3259/4000] Training [6/16] Loss: 0.00277 +Epoch [3259/4000] Training [7/16] Loss: 0.00217 +Epoch [3259/4000] Training [8/16] Loss: 0.00262 +Epoch [3259/4000] Training [9/16] Loss: 0.00251 +Epoch [3259/4000] Training [10/16] Loss: 0.00250 +Epoch [3259/4000] Training [11/16] Loss: 0.00234 +Epoch [3259/4000] Training [12/16] Loss: 0.00390 +Epoch [3259/4000] Training [13/16] Loss: 0.00313 +Epoch [3259/4000] Training [14/16] Loss: 0.00483 +Epoch [3259/4000] Training [15/16] Loss: 0.00272 +Epoch [3259/4000] Training [16/16] Loss: 0.00183 +Epoch [3259/4000] Training metric {'Train/mean dice_metric': 0.9983950257301331, 'Train/mean miou_metric': 0.9965006709098816, 'Train/mean f1': 0.9933173060417175, 'Train/mean precision': 0.9886833429336548, 'Train/mean recall': 0.9979948997497559, 'Train/mean hd95_metric': 0.7056916952133179} +Epoch [3259/4000] Validation [1/4] Loss: 0.41012 focal_loss 0.34453 dice_loss 0.06559 +Epoch [3259/4000] Validation [2/4] Loss: 0.47276 focal_loss 0.35912 dice_loss 0.11365 +Epoch [3259/4000] Validation [3/4] Loss: 0.26105 focal_loss 0.19945 dice_loss 0.06161 +Epoch [3259/4000] Validation [4/4] Loss: 0.41168 focal_loss 0.30397 dice_loss 0.10771 +Epoch [3259/4000] Validation metric {'Val/mean dice_metric': 0.9738248586654663, 'Val/mean miou_metric': 0.9597074389457703, 'Val/mean f1': 0.9765167236328125, 'Val/mean precision': 0.9743937849998474, 'Val/mean recall': 0.9786489009857178, 'Val/mean hd95_metric': 5.035806179046631} +Cheakpoint... +Epoch [3259/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738248586654663, 'Val/mean miou_metric': 0.9597074389457703, 'Val/mean f1': 0.9765167236328125, 'Val/mean precision': 0.9743937849998474, 'Val/mean recall': 0.9786489009857178, 'Val/mean hd95_metric': 5.035806179046631} +Epoch [3260/4000] Training [1/16] Loss: 0.00233 +Epoch [3260/4000] Training [2/16] Loss: 0.00364 +Epoch [3260/4000] Training [3/16] Loss: 0.00307 +Epoch [3260/4000] Training [4/16] Loss: 0.00281 +Epoch [3260/4000] Training [5/16] Loss: 0.00197 +Epoch [3260/4000] Training [6/16] Loss: 0.00241 +Epoch [3260/4000] Training [7/16] Loss: 0.00288 +Epoch [3260/4000] Training [8/16] Loss: 0.00218 +Epoch [3260/4000] Training [9/16] Loss: 0.00324 +Epoch [3260/4000] Training [10/16] Loss: 0.00202 +Epoch [3260/4000] Training [11/16] Loss: 0.00349 +Epoch [3260/4000] Training [12/16] Loss: 0.00338 +Epoch [3260/4000] Training [13/16] Loss: 0.00304 +Epoch [3260/4000] Training [14/16] Loss: 0.00419 +Epoch [3260/4000] Training [15/16] Loss: 0.00256 +Epoch [3260/4000] Training [16/16] Loss: 0.00242 +Epoch [3260/4000] Training metric {'Train/mean dice_metric': 0.9985546469688416, 'Train/mean miou_metric': 0.9968377351760864, 'Train/mean f1': 0.9935894012451172, 'Train/mean precision': 0.989014744758606, 'Train/mean recall': 0.9982064962387085, 'Train/mean hd95_metric': 0.6209259629249573} +Epoch [3260/4000] Validation [1/4] Loss: 0.43955 focal_loss 0.37512 dice_loss 0.06443 +Epoch [3260/4000] Validation [2/4] Loss: 0.44823 focal_loss 0.33909 dice_loss 0.10914 +Epoch [3260/4000] Validation [3/4] Loss: 0.25963 focal_loss 0.20315 dice_loss 0.05648 +Epoch [3260/4000] Validation [4/4] Loss: 0.46033 focal_loss 0.34253 dice_loss 0.11780 +Epoch [3260/4000] Validation metric {'Val/mean dice_metric': 0.9740349054336548, 'Val/mean miou_metric': 0.9604671597480774, 'Val/mean f1': 0.9768424034118652, 'Val/mean precision': 0.9746068120002747, 'Val/mean recall': 0.9790882468223572, 'Val/mean hd95_metric': 5.013571739196777} +Cheakpoint... +Epoch [3260/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740349054336548, 'Val/mean miou_metric': 0.9604671597480774, 'Val/mean f1': 0.9768424034118652, 'Val/mean precision': 0.9746068120002747, 'Val/mean recall': 0.9790882468223572, 'Val/mean hd95_metric': 5.013571739196777} +Epoch [3261/4000] Training [1/16] Loss: 0.00541 +Epoch [3261/4000] Training [2/16] Loss: 0.00231 +Epoch [3261/4000] Training [3/16] Loss: 0.00237 +Epoch [3261/4000] Training [4/16] Loss: 0.00208 +Epoch [3261/4000] Training [5/16] Loss: 0.00165 +Epoch [3261/4000] Training [6/16] Loss: 0.00310 +Epoch [3261/4000] Training [7/16] Loss: 0.00292 +Epoch [3261/4000] Training [8/16] Loss: 0.00354 +Epoch [3261/4000] Training [9/16] Loss: 0.00349 +Epoch [3261/4000] Training [10/16] Loss: 0.00260 +Epoch [3261/4000] Training [11/16] Loss: 0.00341 +Epoch [3261/4000] Training [12/16] Loss: 0.00333 +Epoch [3261/4000] Training [13/16] Loss: 0.00218 +Epoch [3261/4000] Training [14/16] Loss: 0.00327 +Epoch [3261/4000] Training [15/16] Loss: 0.00302 +Epoch [3261/4000] Training [16/16] Loss: 0.00295 +Epoch [3261/4000] Training metric {'Train/mean dice_metric': 0.9983826875686646, 'Train/mean miou_metric': 0.9964649677276611, 'Train/mean f1': 0.992798924446106, 'Train/mean precision': 0.9875897169113159, 'Train/mean recall': 0.9980634450912476, 'Train/mean hd95_metric': 0.683426022529602} +Epoch [3261/4000] Validation [1/4] Loss: 0.34728 focal_loss 0.28721 dice_loss 0.06007 +Epoch [3261/4000] Validation [2/4] Loss: 0.42078 focal_loss 0.31412 dice_loss 0.10666 +Epoch [3261/4000] Validation [3/4] Loss: 0.51922 focal_loss 0.42894 dice_loss 0.09028 +Epoch [3261/4000] Validation [4/4] Loss: 0.31437 focal_loss 0.22855 dice_loss 0.08581 +Epoch [3261/4000] Validation metric {'Val/mean dice_metric': 0.9741566777229309, 'Val/mean miou_metric': 0.9600342512130737, 'Val/mean f1': 0.9757146239280701, 'Val/mean precision': 0.971019983291626, 'Val/mean recall': 0.9804549813270569, 'Val/mean hd95_metric': 5.089569568634033} +Cheakpoint... +Epoch [3261/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741566777229309, 'Val/mean miou_metric': 0.9600342512130737, 'Val/mean f1': 0.9757146239280701, 'Val/mean precision': 0.971019983291626, 'Val/mean recall': 0.9804549813270569, 'Val/mean hd95_metric': 5.089569568634033} +Epoch [3262/4000] Training [1/16] Loss: 0.00270 +Epoch [3262/4000] Training [2/16] Loss: 0.00315 +Epoch [3262/4000] Training [3/16] Loss: 0.00231 +Epoch [3262/4000] Training [4/16] Loss: 0.00233 +Epoch [3262/4000] Training [5/16] Loss: 0.00597 +Epoch [3262/4000] Training [6/16] Loss: 0.00211 +Epoch [3262/4000] Training [7/16] Loss: 0.00254 +Epoch [3262/4000] Training [8/16] Loss: 0.00436 +Epoch [3262/4000] Training [9/16] Loss: 0.00241 +Epoch [3262/4000] Training [10/16] Loss: 0.00288 +Epoch [3262/4000] Training [11/16] Loss: 0.00245 +Epoch [3262/4000] Training [12/16] Loss: 0.00273 +Epoch [3262/4000] Training [13/16] Loss: 0.00417 +Epoch [3262/4000] Training [14/16] Loss: 0.00307 +Epoch [3262/4000] Training [15/16] Loss: 0.00316 +Epoch [3262/4000] Training [16/16] Loss: 0.00263 +Epoch [3262/4000] Training metric {'Train/mean dice_metric': 0.9983214139938354, 'Train/mean miou_metric': 0.9963735342025757, 'Train/mean f1': 0.9933557510375977, 'Train/mean precision': 0.9886897802352905, 'Train/mean recall': 0.9980659484863281, 'Train/mean hd95_metric': 0.7011262774467468} +Epoch [3262/4000] Validation [1/4] Loss: 0.38778 focal_loss 0.32687 dice_loss 0.06091 +Epoch [3262/4000] Validation [2/4] Loss: 0.45170 focal_loss 0.34104 dice_loss 0.11065 +Epoch [3262/4000] Validation [3/4] Loss: 0.49687 focal_loss 0.40855 dice_loss 0.08832 +Epoch [3262/4000] Validation [4/4] Loss: 0.38854 focal_loss 0.27577 dice_loss 0.11276 +Epoch [3262/4000] Validation metric {'Val/mean dice_metric': 0.9744472503662109, 'Val/mean miou_metric': 0.960056483745575, 'Val/mean f1': 0.9766273498535156, 'Val/mean precision': 0.973326563835144, 'Val/mean recall': 0.979950487613678, 'Val/mean hd95_metric': 5.004544734954834} +Cheakpoint... +Epoch [3262/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744472503662109, 'Val/mean miou_metric': 0.960056483745575, 'Val/mean f1': 0.9766273498535156, 'Val/mean precision': 0.973326563835144, 'Val/mean recall': 0.979950487613678, 'Val/mean hd95_metric': 5.004544734954834} +Epoch [3263/4000] Training [1/16] Loss: 0.00344 +Epoch [3263/4000] Training [2/16] Loss: 0.00272 +Epoch [3263/4000] Training [3/16] Loss: 0.00280 +Epoch [3263/4000] Training [4/16] Loss: 0.00263 +Epoch [3263/4000] Training [5/16] Loss: 0.00263 +Epoch [3263/4000] Training [6/16] Loss: 0.00321 +Epoch [3263/4000] Training [7/16] Loss: 0.00303 +Epoch [3263/4000] Training [8/16] Loss: 0.00252 +Epoch [3263/4000] Training [9/16] Loss: 0.00373 +Epoch [3263/4000] Training [10/16] Loss: 0.00171 +Epoch [3263/4000] Training [11/16] Loss: 0.00258 +Epoch [3263/4000] Training [12/16] Loss: 0.00384 +Epoch [3263/4000] Training [13/16] Loss: 0.00276 +Epoch [3263/4000] Training [14/16] Loss: 0.00281 +Epoch [3263/4000] Training [15/16] Loss: 0.00238 +Epoch [3263/4000] Training [16/16] Loss: 0.00328 +Epoch [3263/4000] Training metric {'Train/mean dice_metric': 0.9984115362167358, 'Train/mean miou_metric': 0.9965366125106812, 'Train/mean f1': 0.9931867122650146, 'Train/mean precision': 0.9883688688278198, 'Train/mean recall': 0.9980517625808716, 'Train/mean hd95_metric': 0.6952424645423889} +Epoch [3263/4000] Validation [1/4] Loss: 0.35680 focal_loss 0.29763 dice_loss 0.05918 +Epoch [3263/4000] Validation [2/4] Loss: 0.47196 focal_loss 0.33446 dice_loss 0.13750 +Epoch [3263/4000] Validation [3/4] Loss: 0.51605 focal_loss 0.42635 dice_loss 0.08970 +Epoch [3263/4000] Validation [4/4] Loss: 0.45936 focal_loss 0.34902 dice_loss 0.11033 +Epoch [3263/4000] Validation metric {'Val/mean dice_metric': 0.9744560122489929, 'Val/mean miou_metric': 0.9601494669914246, 'Val/mean f1': 0.9761684536933899, 'Val/mean precision': 0.9731281995773315, 'Val/mean recall': 0.9792276620864868, 'Val/mean hd95_metric': 4.89116096496582} +Cheakpoint... +Epoch [3263/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744560122489929, 'Val/mean miou_metric': 0.9601494669914246, 'Val/mean f1': 0.9761684536933899, 'Val/mean precision': 0.9731281995773315, 'Val/mean recall': 0.9792276620864868, 'Val/mean hd95_metric': 4.89116096496582} +Epoch [3264/4000] Training [1/16] Loss: 0.00357 +Epoch [3264/4000] Training [2/16] Loss: 0.00218 +Epoch [3264/4000] Training [3/16] Loss: 0.00210 +Epoch [3264/4000] Training [4/16] Loss: 0.00391 +Epoch [3264/4000] Training [5/16] Loss: 0.00202 +Epoch [3264/4000] Training [6/16] Loss: 0.00272 +Epoch [3264/4000] Training [7/16] Loss: 0.00190 +Epoch [3264/4000] Training [8/16] Loss: 0.00190 +Epoch [3264/4000] Training [9/16] Loss: 0.00421 +Epoch [3264/4000] Training [10/16] Loss: 0.00350 +Epoch [3264/4000] Training [11/16] Loss: 0.00283 +Epoch [3264/4000] Training [12/16] Loss: 0.00224 +Epoch [3264/4000] Training [13/16] Loss: 0.00402 +Epoch [3264/4000] Training [14/16] Loss: 0.00210 +Epoch [3264/4000] Training [15/16] Loss: 0.00180 +Epoch [3264/4000] Training [16/16] Loss: 0.00277 +Epoch [3264/4000] Training metric {'Train/mean dice_metric': 0.9986177682876587, 'Train/mean miou_metric': 0.9969305992126465, 'Train/mean f1': 0.9931808710098267, 'Train/mean precision': 0.9881901741027832, 'Train/mean recall': 0.9982221722602844, 'Train/mean hd95_metric': 0.6451448798179626} +Epoch [3264/4000] Validation [1/4] Loss: 0.34335 focal_loss 0.28367 dice_loss 0.05968 +Epoch [3264/4000] Validation [2/4] Loss: 0.89886 focal_loss 0.68875 dice_loss 0.21011 +Epoch [3264/4000] Validation [3/4] Loss: 0.52300 focal_loss 0.42748 dice_loss 0.09553 +Epoch [3264/4000] Validation [4/4] Loss: 0.34289 focal_loss 0.24900 dice_loss 0.09389 +Epoch [3264/4000] Validation metric {'Val/mean dice_metric': 0.9728792905807495, 'Val/mean miou_metric': 0.9591701626777649, 'Val/mean f1': 0.9753607511520386, 'Val/mean precision': 0.971899688243866, 'Val/mean recall': 0.978846549987793, 'Val/mean hd95_metric': 5.258094787597656} +Cheakpoint... +Epoch [3264/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728792905807495, 'Val/mean miou_metric': 0.9591701626777649, 'Val/mean f1': 0.9753607511520386, 'Val/mean precision': 0.971899688243866, 'Val/mean recall': 0.978846549987793, 'Val/mean hd95_metric': 5.258094787597656} +Epoch [3265/4000] Training [1/16] Loss: 0.00308 +Epoch [3265/4000] Training [2/16] Loss: 0.00254 +Epoch [3265/4000] Training [3/16] Loss: 0.00226 +Epoch [3265/4000] Training [4/16] Loss: 0.00224 +Epoch [3265/4000] Training [5/16] Loss: 0.00389 +Epoch [3265/4000] Training [6/16] Loss: 0.00411 +Epoch [3265/4000] Training [7/16] Loss: 0.00325 +Epoch [3265/4000] Training [8/16] Loss: 0.00367 +Epoch [3265/4000] Training [9/16] Loss: 0.00279 +Epoch [3265/4000] Training [10/16] Loss: 0.00400 +Epoch [3265/4000] Training [11/16] Loss: 0.00315 +Epoch [3265/4000] Training [12/16] Loss: 0.00429 +Epoch [3265/4000] Training [13/16] Loss: 0.00232 +Epoch [3265/4000] Training [14/16] Loss: 0.00184 +Epoch [3265/4000] Training [15/16] Loss: 0.00291 +Epoch [3265/4000] Training [16/16] Loss: 0.00387 +Epoch [3265/4000] Training metric {'Train/mean dice_metric': 0.9983506202697754, 'Train/mean miou_metric': 0.9964318871498108, 'Train/mean f1': 0.9934350252151489, 'Train/mean precision': 0.9889203310012817, 'Train/mean recall': 0.997991144657135, 'Train/mean hd95_metric': 0.6586213111877441} +Epoch [3265/4000] Validation [1/4] Loss: 0.38225 focal_loss 0.32142 dice_loss 0.06083 +Epoch [3265/4000] Validation [2/4] Loss: 0.90796 focal_loss 0.69460 dice_loss 0.21336 +Epoch [3265/4000] Validation [3/4] Loss: 0.49376 focal_loss 0.40373 dice_loss 0.09003 +Epoch [3265/4000] Validation [4/4] Loss: 0.45925 focal_loss 0.34650 dice_loss 0.11275 +Epoch [3265/4000] Validation metric {'Val/mean dice_metric': 0.9722200632095337, 'Val/mean miou_metric': 0.9581001996994019, 'Val/mean f1': 0.9756516218185425, 'Val/mean precision': 0.9729670286178589, 'Val/mean recall': 0.9783510565757751, 'Val/mean hd95_metric': 5.236937999725342} +Cheakpoint... +Epoch [3265/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722200632095337, 'Val/mean miou_metric': 0.9581001996994019, 'Val/mean f1': 0.9756516218185425, 'Val/mean precision': 0.9729670286178589, 'Val/mean recall': 0.9783510565757751, 'Val/mean hd95_metric': 5.236937999725342} +Epoch [3266/4000] Training [1/16] Loss: 0.00235 +Epoch [3266/4000] Training [2/16] Loss: 0.00216 +Epoch [3266/4000] Training [3/16] Loss: 0.00283 +Epoch [3266/4000] Training [4/16] Loss: 0.00232 +Epoch [3266/4000] Training [5/16] Loss: 0.00271 +Epoch [3266/4000] Training [6/16] Loss: 0.00212 +Epoch [3266/4000] Training [7/16] Loss: 0.00388 +Epoch [3266/4000] Training [8/16] Loss: 0.00352 +Epoch [3266/4000] Training [9/16] Loss: 0.00318 +Epoch [3266/4000] Training [10/16] Loss: 0.00408 +Epoch [3266/4000] Training [11/16] Loss: 0.00252 +Epoch [3266/4000] Training [12/16] Loss: 0.00219 +Epoch [3266/4000] Training [13/16] Loss: 0.00431 +Epoch [3266/4000] Training [14/16] Loss: 0.00266 +Epoch [3266/4000] Training [15/16] Loss: 0.00254 +Epoch [3266/4000] Training [16/16] Loss: 0.00317 +Epoch [3266/4000] Training metric {'Train/mean dice_metric': 0.998367428779602, 'Train/mean miou_metric': 0.9964724779129028, 'Train/mean f1': 0.9935017824172974, 'Train/mean precision': 0.9889898896217346, 'Train/mean recall': 0.9980549812316895, 'Train/mean hd95_metric': 0.6564531326293945} +Epoch [3266/4000] Validation [1/4] Loss: 0.40445 focal_loss 0.33867 dice_loss 0.06578 +Epoch [3266/4000] Validation [2/4] Loss: 1.00937 focal_loss 0.81796 dice_loss 0.19141 +Epoch [3266/4000] Validation [3/4] Loss: 0.55909 focal_loss 0.46006 dice_loss 0.09903 +Epoch [3266/4000] Validation [4/4] Loss: 0.28425 focal_loss 0.19699 dice_loss 0.08725 +Epoch [3266/4000] Validation metric {'Val/mean dice_metric': 0.9736388325691223, 'Val/mean miou_metric': 0.9595013856887817, 'Val/mean f1': 0.9757537841796875, 'Val/mean precision': 0.9726417064666748, 'Val/mean recall': 0.9788857698440552, 'Val/mean hd95_metric': 4.9693922996521} +Cheakpoint... +Epoch [3266/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736388325691223, 'Val/mean miou_metric': 0.9595013856887817, 'Val/mean f1': 0.9757537841796875, 'Val/mean precision': 0.9726417064666748, 'Val/mean recall': 0.9788857698440552, 'Val/mean hd95_metric': 4.9693922996521} +Epoch [3267/4000] Training [1/16] Loss: 0.00293 +Epoch [3267/4000] Training [2/16] Loss: 0.00322 +Epoch [3267/4000] Training [3/16] Loss: 0.00245 +Epoch [3267/4000] Training [4/16] Loss: 0.00432 +Epoch [3267/4000] Training [5/16] Loss: 0.00337 +Epoch [3267/4000] Training [6/16] Loss: 0.00342 +Epoch [3267/4000] Training [7/16] Loss: 0.00235 +Epoch [3267/4000] Training [8/16] Loss: 0.00402 +Epoch [3267/4000] Training [9/16] Loss: 0.00197 +Epoch [3267/4000] Training [10/16] Loss: 0.00169 +Epoch [3267/4000] Training [11/16] Loss: 0.00368 +Epoch [3267/4000] Training [12/16] Loss: 0.00170 +Epoch [3267/4000] Training [13/16] Loss: 0.00315 +Epoch [3267/4000] Training [14/16] Loss: 0.00227 +Epoch [3267/4000] Training [15/16] Loss: 0.00314 +Epoch [3267/4000] Training [16/16] Loss: 0.00247 +Epoch [3267/4000] Training metric {'Train/mean dice_metric': 0.9984421730041504, 'Train/mean miou_metric': 0.9965908527374268, 'Train/mean f1': 0.9932778477668762, 'Train/mean precision': 0.9885839223861694, 'Train/mean recall': 0.9980165362358093, 'Train/mean hd95_metric': 0.6748734712600708} +Epoch [3267/4000] Validation [1/4] Loss: 0.38051 focal_loss 0.31042 dice_loss 0.07009 +Epoch [3267/4000] Validation [2/4] Loss: 0.47601 focal_loss 0.33764 dice_loss 0.13837 +Epoch [3267/4000] Validation [3/4] Loss: 0.53973 focal_loss 0.44058 dice_loss 0.09915 +Epoch [3267/4000] Validation [4/4] Loss: 0.33154 focal_loss 0.24172 dice_loss 0.08982 +Epoch [3267/4000] Validation metric {'Val/mean dice_metric': 0.9743765592575073, 'Val/mean miou_metric': 0.9600089192390442, 'Val/mean f1': 0.9761673212051392, 'Val/mean precision': 0.9729865193367004, 'Val/mean recall': 0.979369044303894, 'Val/mean hd95_metric': 5.0341057777404785} +Cheakpoint... +Epoch [3267/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743765592575073, 'Val/mean miou_metric': 0.9600089192390442, 'Val/mean f1': 0.9761673212051392, 'Val/mean precision': 0.9729865193367004, 'Val/mean recall': 0.979369044303894, 'Val/mean hd95_metric': 5.0341057777404785} +Epoch [3268/4000] Training [1/16] Loss: 0.00263 +Epoch [3268/4000] Training [2/16] Loss: 0.00320 +Epoch [3268/4000] Training [3/16] Loss: 0.00371 +Epoch [3268/4000] Training [4/16] Loss: 0.00197 +Epoch [3268/4000] Training [5/16] Loss: 0.00229 +Epoch [3268/4000] Training [6/16] Loss: 0.00199 +Epoch [3268/4000] Training [7/16] Loss: 0.00232 +Epoch [3268/4000] Training [8/16] Loss: 0.00280 +Epoch [3268/4000] Training [9/16] Loss: 0.00461 +Epoch [3268/4000] Training [10/16] Loss: 0.00210 +Epoch [3268/4000] Training [11/16] Loss: 0.00261 +Epoch [3268/4000] Training [12/16] Loss: 0.00200 +Epoch [3268/4000] Training [13/16] Loss: 0.00258 +Epoch [3268/4000] Training [14/16] Loss: 0.00217 +Epoch [3268/4000] Training [15/16] Loss: 0.00190 +Epoch [3268/4000] Training [16/16] Loss: 0.00260 +Epoch [3268/4000] Training metric {'Train/mean dice_metric': 0.9987139701843262, 'Train/mean miou_metric': 0.9971563816070557, 'Train/mean f1': 0.9937191605567932, 'Train/mean precision': 0.9891790151596069, 'Train/mean recall': 0.9983011484146118, 'Train/mean hd95_metric': 0.5781524777412415} +Epoch [3268/4000] Validation [1/4] Loss: 0.35543 focal_loss 0.29166 dice_loss 0.06377 +Epoch [3268/4000] Validation [2/4] Loss: 0.46162 focal_loss 0.34986 dice_loss 0.11176 +Epoch [3268/4000] Validation [3/4] Loss: 0.49298 focal_loss 0.40400 dice_loss 0.08898 +Epoch [3268/4000] Validation [4/4] Loss: 0.53755 focal_loss 0.41139 dice_loss 0.12617 +Epoch [3268/4000] Validation metric {'Val/mean dice_metric': 0.9758111834526062, 'Val/mean miou_metric': 0.961530327796936, 'Val/mean f1': 0.9765337705612183, 'Val/mean precision': 0.9743680953979492, 'Val/mean recall': 0.9787090420722961, 'Val/mean hd95_metric': 4.722109794616699} +Cheakpoint... +Epoch [3268/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758111834526062, 'Val/mean miou_metric': 0.961530327796936, 'Val/mean f1': 0.9765337705612183, 'Val/mean precision': 0.9743680953979492, 'Val/mean recall': 0.9787090420722961, 'Val/mean hd95_metric': 4.722109794616699} +Epoch [3269/4000] Training [1/16] Loss: 0.00293 +Epoch [3269/4000] Training [2/16] Loss: 0.00260 +Epoch [3269/4000] Training [3/16] Loss: 0.00213 +Epoch [3269/4000] Training [4/16] Loss: 0.00239 +Epoch [3269/4000] Training [5/16] Loss: 0.00310 +Epoch [3269/4000] Training [6/16] Loss: 0.00230 +Epoch [3269/4000] Training [7/16] Loss: 0.00218 +Epoch [3269/4000] Training [8/16] Loss: 0.00370 +Epoch [3269/4000] Training [9/16] Loss: 0.00434 +Epoch [3269/4000] Training [10/16] Loss: 0.00292 +Epoch [3269/4000] Training [11/16] Loss: 0.00249 +Epoch [3269/4000] Training [12/16] Loss: 0.00338 +Epoch [3269/4000] Training [13/16] Loss: 0.00242 +Epoch [3269/4000] Training [14/16] Loss: 0.00331 +Epoch [3269/4000] Training [15/16] Loss: 0.00196 +Epoch [3269/4000] Training [16/16] Loss: 0.00353 +Epoch [3269/4000] Training metric {'Train/mean dice_metric': 0.9983956217765808, 'Train/mean miou_metric': 0.9965194463729858, 'Train/mean f1': 0.9934854507446289, 'Train/mean precision': 0.9889135360717773, 'Train/mean recall': 0.9980998039245605, 'Train/mean hd95_metric': 0.6886018514633179} +Epoch [3269/4000] Validation [1/4] Loss: 0.38700 focal_loss 0.32233 dice_loss 0.06466 +Epoch [3269/4000] Validation [2/4] Loss: 0.66531 focal_loss 0.48377 dice_loss 0.18154 +Epoch [3269/4000] Validation [3/4] Loss: 0.56370 focal_loss 0.46841 dice_loss 0.09529 +Epoch [3269/4000] Validation [4/4] Loss: 0.25640 focal_loss 0.17272 dice_loss 0.08367 +Epoch [3269/4000] Validation metric {'Val/mean dice_metric': 0.9733020663261414, 'Val/mean miou_metric': 0.9587064981460571, 'Val/mean f1': 0.9756193161010742, 'Val/mean precision': 0.9725226759910583, 'Val/mean recall': 0.9787358641624451, 'Val/mean hd95_metric': 5.498324871063232} +Cheakpoint... +Epoch [3269/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733020663261414, 'Val/mean miou_metric': 0.9587064981460571, 'Val/mean f1': 0.9756193161010742, 'Val/mean precision': 0.9725226759910583, 'Val/mean recall': 0.9787358641624451, 'Val/mean hd95_metric': 5.498324871063232} +Epoch [3270/4000] Training [1/16] Loss: 0.00200 +Epoch [3270/4000] Training [2/16] Loss: 0.00311 +Epoch [3270/4000] Training [3/16] Loss: 0.00392 +Epoch [3270/4000] Training [4/16] Loss: 0.00363 +Epoch [3270/4000] Training [5/16] Loss: 0.00272 +Epoch [3270/4000] Training [6/16] Loss: 0.00301 +Epoch [3270/4000] Training [7/16] Loss: 0.00270 +Epoch [3270/4000] Training [8/16] Loss: 0.00251 +Epoch [3270/4000] Training [9/16] Loss: 0.00214 +Epoch [3270/4000] Training [10/16] Loss: 0.00215 +Epoch [3270/4000] Training [11/16] Loss: 0.00300 +Epoch [3270/4000] Training [12/16] Loss: 0.00259 +Epoch [3270/4000] Training [13/16] Loss: 0.00295 +Epoch [3270/4000] Training [14/16] Loss: 0.00308 +Epoch [3270/4000] Training [15/16] Loss: 0.00288 +Epoch [3270/4000] Training [16/16] Loss: 0.00373 +Epoch [3270/4000] Training metric {'Train/mean dice_metric': 0.9985621571540833, 'Train/mean miou_metric': 0.9968424439430237, 'Train/mean f1': 0.993513822555542, 'Train/mean precision': 0.9888181090354919, 'Train/mean recall': 0.9982542991638184, 'Train/mean hd95_metric': 0.6153596043586731} +Epoch [3270/4000] Validation [1/4] Loss: 0.35982 focal_loss 0.29830 dice_loss 0.06152 +Epoch [3270/4000] Validation [2/4] Loss: 0.44525 focal_loss 0.33293 dice_loss 0.11232 +Epoch [3270/4000] Validation [3/4] Loss: 0.45445 focal_loss 0.36010 dice_loss 0.09436 +Epoch [3270/4000] Validation [4/4] Loss: 0.33686 focal_loss 0.24553 dice_loss 0.09133 +Epoch [3270/4000] Validation metric {'Val/mean dice_metric': 0.9726701974868774, 'Val/mean miou_metric': 0.958743691444397, 'Val/mean f1': 0.976105809211731, 'Val/mean precision': 0.9744710922241211, 'Val/mean recall': 0.9777460098266602, 'Val/mean hd95_metric': 5.097310543060303} +Cheakpoint... +Epoch [3270/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726701974868774, 'Val/mean miou_metric': 0.958743691444397, 'Val/mean f1': 0.976105809211731, 'Val/mean precision': 0.9744710922241211, 'Val/mean recall': 0.9777460098266602, 'Val/mean hd95_metric': 5.097310543060303} +Epoch [3271/4000] Training [1/16] Loss: 0.00251 +Epoch [3271/4000] Training [2/16] Loss: 0.00316 +Epoch [3271/4000] Training [3/16] Loss: 0.00211 +Epoch [3271/4000] Training [4/16] Loss: 0.00276 +Epoch [3271/4000] Training [5/16] Loss: 0.00225 +Epoch [3271/4000] Training [6/16] Loss: 0.00251 +Epoch [3271/4000] Training [7/16] Loss: 0.00318 +Epoch [3271/4000] Training [8/16] Loss: 0.00337 +Epoch [3271/4000] Training [9/16] Loss: 0.00231 +Epoch [3271/4000] Training [10/16] Loss: 0.00360 +Epoch [3271/4000] Training [11/16] Loss: 0.00315 +Epoch [3271/4000] Training [12/16] Loss: 0.00282 +Epoch [3271/4000] Training [13/16] Loss: 0.00227 +Epoch [3271/4000] Training [14/16] Loss: 0.00224 +Epoch [3271/4000] Training [15/16] Loss: 0.00360 +Epoch [3271/4000] Training [16/16] Loss: 0.00249 +Epoch [3271/4000] Training metric {'Train/mean dice_metric': 0.9984718561172485, 'Train/mean miou_metric': 0.9966691732406616, 'Train/mean f1': 0.9933852553367615, 'Train/mean precision': 0.9887641072273254, 'Train/mean recall': 0.9980498552322388, 'Train/mean hd95_metric': 0.6197819709777832} +Epoch [3271/4000] Validation [1/4] Loss: 0.36012 focal_loss 0.29840 dice_loss 0.06172 +Epoch [3271/4000] Validation [2/4] Loss: 0.44651 focal_loss 0.33730 dice_loss 0.10922 +Epoch [3271/4000] Validation [3/4] Loss: 0.50559 focal_loss 0.41420 dice_loss 0.09139 +Epoch [3271/4000] Validation [4/4] Loss: 0.28217 focal_loss 0.19606 dice_loss 0.08611 +Epoch [3271/4000] Validation metric {'Val/mean dice_metric': 0.9751958847045898, 'Val/mean miou_metric': 0.9610100984573364, 'Val/mean f1': 0.9759966135025024, 'Val/mean precision': 0.9735844135284424, 'Val/mean recall': 0.9784209728240967, 'Val/mean hd95_metric': 5.142600059509277} +Cheakpoint... +Epoch [3271/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751958847045898, 'Val/mean miou_metric': 0.9610100984573364, 'Val/mean f1': 0.9759966135025024, 'Val/mean precision': 0.9735844135284424, 'Val/mean recall': 0.9784209728240967, 'Val/mean hd95_metric': 5.142600059509277} +Epoch [3272/4000] Training [1/16] Loss: 0.00524 +Epoch [3272/4000] Training [2/16] Loss: 0.00261 +Epoch [3272/4000] Training [3/16] Loss: 0.00232 +Epoch [3272/4000] Training [4/16] Loss: 0.00394 +Epoch [3272/4000] Training [5/16] Loss: 0.00286 +Epoch [3272/4000] Training [6/16] Loss: 0.00251 +Epoch [3272/4000] Training [7/16] Loss: 0.00309 +Epoch [3272/4000] Training [8/16] Loss: 0.00231 +Epoch [3272/4000] Training [9/16] Loss: 0.00348 +Epoch [3272/4000] Training [10/16] Loss: 0.00314 +Epoch [3272/4000] Training [11/16] Loss: 0.00236 +Epoch [3272/4000] Training [12/16] Loss: 0.00206 +Epoch [3272/4000] Training [13/16] Loss: 0.00213 +Epoch [3272/4000] Training [14/16] Loss: 0.00266 +Epoch [3272/4000] Training [15/16] Loss: 0.00266 +Epoch [3272/4000] Training [16/16] Loss: 0.00207 +Epoch [3272/4000] Training metric {'Train/mean dice_metric': 0.998481273651123, 'Train/mean miou_metric': 0.9966650009155273, 'Train/mean f1': 0.993025541305542, 'Train/mean precision': 0.9880554676055908, 'Train/mean recall': 0.9980458617210388, 'Train/mean hd95_metric': 0.6541569232940674} +Epoch [3272/4000] Validation [1/4] Loss: 0.40432 focal_loss 0.34243 dice_loss 0.06189 +Epoch [3272/4000] Validation [2/4] Loss: 1.16908 focal_loss 0.91532 dice_loss 0.25376 +Epoch [3272/4000] Validation [3/4] Loss: 0.55090 focal_loss 0.45357 dice_loss 0.09733 +Epoch [3272/4000] Validation [4/4] Loss: 0.36726 focal_loss 0.26650 dice_loss 0.10077 +Epoch [3272/4000] Validation metric {'Val/mean dice_metric': 0.974114716053009, 'Val/mean miou_metric': 0.9598973989486694, 'Val/mean f1': 0.9758267402648926, 'Val/mean precision': 0.972989022731781, 'Val/mean recall': 0.978681206703186, 'Val/mean hd95_metric': 4.7411580085754395} +Cheakpoint... +Epoch [3272/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974114716053009, 'Val/mean miou_metric': 0.9598973989486694, 'Val/mean f1': 0.9758267402648926, 'Val/mean precision': 0.972989022731781, 'Val/mean recall': 0.978681206703186, 'Val/mean hd95_metric': 4.7411580085754395} +Epoch [3273/4000] Training [1/16] Loss: 0.00188 +Epoch [3273/4000] Training [2/16] Loss: 0.00188 +Epoch [3273/4000] Training [3/16] Loss: 0.00243 +Epoch [3273/4000] Training [4/16] Loss: 0.00198 +Epoch [3273/4000] Training [5/16] Loss: 0.00339 +Epoch [3273/4000] Training [6/16] Loss: 0.00266 +Epoch [3273/4000] Training [7/16] Loss: 0.00323 +Epoch [3273/4000] Training [8/16] Loss: 0.00288 +Epoch [3273/4000] Training [9/16] Loss: 0.00259 +Epoch [3273/4000] Training [10/16] Loss: 0.00373 +Epoch [3273/4000] Training [11/16] Loss: 0.00331 +Epoch [3273/4000] Training [12/16] Loss: 0.00234 +Epoch [3273/4000] Training [13/16] Loss: 0.00147 +Epoch [3273/4000] Training [14/16] Loss: 0.00188 +Epoch [3273/4000] Training [15/16] Loss: 0.00188 +Epoch [3273/4000] Training [16/16] Loss: 0.00315 +Epoch [3273/4000] Training metric {'Train/mean dice_metric': 0.9986511468887329, 'Train/mean miou_metric': 0.9970248937606812, 'Train/mean f1': 0.9936506748199463, 'Train/mean precision': 0.9890921115875244, 'Train/mean recall': 0.9982514381408691, 'Train/mean hd95_metric': 0.6058592200279236} +Epoch [3273/4000] Validation [1/4] Loss: 0.36432 focal_loss 0.30186 dice_loss 0.06246 +Epoch [3273/4000] Validation [2/4] Loss: 0.43530 focal_loss 0.32675 dice_loss 0.10855 +Epoch [3273/4000] Validation [3/4] Loss: 0.51890 focal_loss 0.42472 dice_loss 0.09418 +Epoch [3273/4000] Validation [4/4] Loss: 0.31143 focal_loss 0.22364 dice_loss 0.08780 +Epoch [3273/4000] Validation metric {'Val/mean dice_metric': 0.9732147455215454, 'Val/mean miou_metric': 0.9596236944198608, 'Val/mean f1': 0.9759356379508972, 'Val/mean precision': 0.9735752940177917, 'Val/mean recall': 0.9783074855804443, 'Val/mean hd95_metric': 5.140506267547607} +Cheakpoint... +Epoch [3273/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732147455215454, 'Val/mean miou_metric': 0.9596236944198608, 'Val/mean f1': 0.9759356379508972, 'Val/mean precision': 0.9735752940177917, 'Val/mean recall': 0.9783074855804443, 'Val/mean hd95_metric': 5.140506267547607} +Epoch [3274/4000] Training [1/16] Loss: 0.00279 +Epoch [3274/4000] Training [2/16] Loss: 0.00260 +Epoch [3274/4000] Training [3/16] Loss: 0.00260 +Epoch [3274/4000] Training [4/16] Loss: 0.00208 +Epoch [3274/4000] Training [5/16] Loss: 0.00275 +Epoch [3274/4000] Training [6/16] Loss: 0.00976 +Epoch [3274/4000] Training [7/16] Loss: 0.00499 +Epoch [3274/4000] Training [8/16] Loss: 0.00216 +Epoch [3274/4000] Training [9/16] Loss: 0.00254 +Epoch [3274/4000] Training [10/16] Loss: 0.00195 +Epoch [3274/4000] Training [11/16] Loss: 0.00250 +Epoch [3274/4000] Training [12/16] Loss: 0.00202 +Epoch [3274/4000] Training [13/16] Loss: 0.00206 +Epoch [3274/4000] Training [14/16] Loss: 0.00280 +Epoch [3274/4000] Training [15/16] Loss: 0.00221 +Epoch [3274/4000] Training [16/16] Loss: 0.00274 +Epoch [3274/4000] Training metric {'Train/mean dice_metric': 0.9984939694404602, 'Train/mean miou_metric': 0.9967206716537476, 'Train/mean f1': 0.9935483336448669, 'Train/mean precision': 0.9889910221099854, 'Train/mean recall': 0.9981478452682495, 'Train/mean hd95_metric': 0.6090384125709534} +Epoch [3274/4000] Validation [1/4] Loss: 0.33313 focal_loss 0.27296 dice_loss 0.06018 +Epoch [3274/4000] Validation [2/4] Loss: 0.41978 focal_loss 0.31269 dice_loss 0.10709 +Epoch [3274/4000] Validation [3/4] Loss: 0.49744 focal_loss 0.40781 dice_loss 0.08963 +Epoch [3274/4000] Validation [4/4] Loss: 0.31184 focal_loss 0.22399 dice_loss 0.08785 +Epoch [3274/4000] Validation metric {'Val/mean dice_metric': 0.9741918444633484, 'Val/mean miou_metric': 0.9602136611938477, 'Val/mean f1': 0.9764040112495422, 'Val/mean precision': 0.9737719297409058, 'Val/mean recall': 0.9790503978729248, 'Val/mean hd95_metric': 4.716941833496094} +Cheakpoint... +Epoch [3274/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741918444633484, 'Val/mean miou_metric': 0.9602136611938477, 'Val/mean f1': 0.9764040112495422, 'Val/mean precision': 0.9737719297409058, 'Val/mean recall': 0.9790503978729248, 'Val/mean hd95_metric': 4.716941833496094} +Epoch [3275/4000] Training [1/16] Loss: 0.00293 +Epoch [3275/4000] Training [2/16] Loss: 0.00213 +Epoch [3275/4000] Training [3/16] Loss: 0.00206 +Epoch [3275/4000] Training [4/16] Loss: 0.00356 +Epoch [3275/4000] Training [5/16] Loss: 0.00307 +Epoch [3275/4000] Training [6/16] Loss: 0.00277 +Epoch [3275/4000] Training [7/16] Loss: 0.00298 +Epoch [3275/4000] Training [8/16] Loss: 0.00333 +Epoch [3275/4000] Training [9/16] Loss: 0.00227 +Epoch [3275/4000] Training [10/16] Loss: 0.00352 +Epoch [3275/4000] Training [11/16] Loss: 0.00361 +Epoch [3275/4000] Training [12/16] Loss: 0.00290 +Epoch [3275/4000] Training [13/16] Loss: 0.00583 +Epoch [3275/4000] Training [14/16] Loss: 0.00277 +Epoch [3275/4000] Training [15/16] Loss: 0.00223 +Epoch [3275/4000] Training [16/16] Loss: 0.00344 +Epoch [3275/4000] Training metric {'Train/mean dice_metric': 0.9984414577484131, 'Train/mean miou_metric': 0.9966161251068115, 'Train/mean f1': 0.9934298992156982, 'Train/mean precision': 0.9888966083526611, 'Train/mean recall': 0.9980047941207886, 'Train/mean hd95_metric': 0.6239398717880249} +Epoch [3275/4000] Validation [1/4] Loss: 0.39437 focal_loss 0.33112 dice_loss 0.06325 +Epoch [3275/4000] Validation [2/4] Loss: 0.42407 focal_loss 0.31373 dice_loss 0.11034 +Epoch [3275/4000] Validation [3/4] Loss: 0.52046 focal_loss 0.42954 dice_loss 0.09091 +Epoch [3275/4000] Validation [4/4] Loss: 0.30891 focal_loss 0.22592 dice_loss 0.08299 +Epoch [3275/4000] Validation metric {'Val/mean dice_metric': 0.9734663963317871, 'Val/mean miou_metric': 0.9594566226005554, 'Val/mean f1': 0.9759775996208191, 'Val/mean precision': 0.9739829897880554, 'Val/mean recall': 0.9779803156852722, 'Val/mean hd95_metric': 4.817146301269531} +Cheakpoint... +Epoch [3275/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734663963317871, 'Val/mean miou_metric': 0.9594566226005554, 'Val/mean f1': 0.9759775996208191, 'Val/mean precision': 0.9739829897880554, 'Val/mean recall': 0.9779803156852722, 'Val/mean hd95_metric': 4.817146301269531} +Epoch [3276/4000] Training [1/16] Loss: 0.00238 +Epoch [3276/4000] Training [2/16] Loss: 0.00304 +Epoch [3276/4000] Training [3/16] Loss: 0.00214 +Epoch [3276/4000] Training [4/16] Loss: 0.00356 +Epoch [3276/4000] Training [5/16] Loss: 0.00266 +Epoch [3276/4000] Training [6/16] Loss: 0.00316 +Epoch [3276/4000] Training [7/16] Loss: 0.00233 +Epoch [3276/4000] Training [8/16] Loss: 0.00268 +Epoch [3276/4000] Training [9/16] Loss: 0.00264 +Epoch [3276/4000] Training [10/16] Loss: 0.00354 +Epoch [3276/4000] Training [11/16] Loss: 0.00266 +Epoch [3276/4000] Training [12/16] Loss: 0.00249 +Epoch [3276/4000] Training [13/16] Loss: 0.00270 +Epoch [3276/4000] Training [14/16] Loss: 0.00273 +Epoch [3276/4000] Training [15/16] Loss: 0.00274 +Epoch [3276/4000] Training [16/16] Loss: 0.00225 +Epoch [3276/4000] Training metric {'Train/mean dice_metric': 0.9985971450805664, 'Train/mean miou_metric': 0.9969201683998108, 'Train/mean f1': 0.9936730265617371, 'Train/mean precision': 0.989155113697052, 'Train/mean recall': 0.998232364654541, 'Train/mean hd95_metric': 0.6427310705184937} +Epoch [3276/4000] Validation [1/4] Loss: 0.42286 focal_loss 0.35985 dice_loss 0.06301 +Epoch [3276/4000] Validation [2/4] Loss: 0.44524 focal_loss 0.33140 dice_loss 0.11383 +Epoch [3276/4000] Validation [3/4] Loss: 0.26068 focal_loss 0.19693 dice_loss 0.06375 +Epoch [3276/4000] Validation [4/4] Loss: 0.31539 focal_loss 0.23244 dice_loss 0.08295 +Epoch [3276/4000] Validation metric {'Val/mean dice_metric': 0.9744000434875488, 'Val/mean miou_metric': 0.9603859782218933, 'Val/mean f1': 0.9768714308738708, 'Val/mean precision': 0.9749454259872437, 'Val/mean recall': 0.9788050055503845, 'Val/mean hd95_metric': 4.946748733520508} +Cheakpoint... +Epoch [3276/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744000434875488, 'Val/mean miou_metric': 0.9603859782218933, 'Val/mean f1': 0.9768714308738708, 'Val/mean precision': 0.9749454259872437, 'Val/mean recall': 0.9788050055503845, 'Val/mean hd95_metric': 4.946748733520508} +Epoch [3277/4000] Training [1/16] Loss: 0.00161 +Epoch [3277/4000] Training [2/16] Loss: 0.00306 +Epoch [3277/4000] Training [3/16] Loss: 0.00283 +Epoch [3277/4000] Training [4/16] Loss: 0.00223 +Epoch [3277/4000] Training [5/16] Loss: 0.00350 +Epoch [3277/4000] Training [6/16] Loss: 0.00248 +Epoch [3277/4000] Training [7/16] Loss: 0.00326 +Epoch [3277/4000] Training [8/16] Loss: 0.00181 +Epoch [3277/4000] Training [9/16] Loss: 0.00503 +Epoch [3277/4000] Training [10/16] Loss: 0.00269 +Epoch [3277/4000] Training [11/16] Loss: 0.00205 +Epoch [3277/4000] Training [12/16] Loss: 0.00245 +Epoch [3277/4000] Training [13/16] Loss: 0.00293 +Epoch [3277/4000] Training [14/16] Loss: 0.00296 +Epoch [3277/4000] Training [15/16] Loss: 0.00283 +Epoch [3277/4000] Training [16/16] Loss: 0.00330 +Epoch [3277/4000] Training metric {'Train/mean dice_metric': 0.9986425042152405, 'Train/mean miou_metric': 0.9970124959945679, 'Train/mean f1': 0.9936379790306091, 'Train/mean precision': 0.9891073107719421, 'Train/mean recall': 0.9982103109359741, 'Train/mean hd95_metric': 0.6041291952133179} +Epoch [3277/4000] Validation [1/4] Loss: 0.39228 focal_loss 0.32936 dice_loss 0.06292 +Epoch [3277/4000] Validation [2/4] Loss: 0.42242 focal_loss 0.31573 dice_loss 0.10669 +Epoch [3277/4000] Validation [3/4] Loss: 0.52925 focal_loss 0.43392 dice_loss 0.09534 +Epoch [3277/4000] Validation [4/4] Loss: 0.25488 focal_loss 0.17483 dice_loss 0.08005 +Epoch [3277/4000] Validation metric {'Val/mean dice_metric': 0.9743199348449707, 'Val/mean miou_metric': 0.9606062769889832, 'Val/mean f1': 0.9764432907104492, 'Val/mean precision': 0.9740413427352905, 'Val/mean recall': 0.9788572192192078, 'Val/mean hd95_metric': 4.756413459777832} +Cheakpoint... +Epoch [3277/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743199348449707, 'Val/mean miou_metric': 0.9606062769889832, 'Val/mean f1': 0.9764432907104492, 'Val/mean precision': 0.9740413427352905, 'Val/mean recall': 0.9788572192192078, 'Val/mean hd95_metric': 4.756413459777832} +Epoch [3278/4000] Training [1/16] Loss: 0.00329 +Epoch [3278/4000] Training [2/16] Loss: 0.00293 +Epoch [3278/4000] Training [3/16] Loss: 0.00273 +Epoch [3278/4000] Training [4/16] Loss: 0.00221 +Epoch [3278/4000] Training [5/16] Loss: 0.00258 +Epoch [3278/4000] Training [6/16] Loss: 0.00390 +Epoch [3278/4000] Training [7/16] Loss: 0.00332 +Epoch [3278/4000] Training [8/16] Loss: 0.00258 +Epoch [3278/4000] Training [9/16] Loss: 0.00217 +Epoch [3278/4000] Training [10/16] Loss: 0.00227 +Epoch [3278/4000] Training [11/16] Loss: 0.00237 +Epoch [3278/4000] Training [12/16] Loss: 0.00285 +Epoch [3278/4000] Training [13/16] Loss: 0.00360 +Epoch [3278/4000] Training [14/16] Loss: 0.00317 +Epoch [3278/4000] Training [15/16] Loss: 0.00224 +Epoch [3278/4000] Training [16/16] Loss: 0.00277 +Epoch [3278/4000] Training metric {'Train/mean dice_metric': 0.998569130897522, 'Train/mean miou_metric': 0.9968636631965637, 'Train/mean f1': 0.9935665130615234, 'Train/mean precision': 0.9890702366828918, 'Train/mean recall': 0.9981038570404053, 'Train/mean hd95_metric': 0.6377228498458862} +Epoch [3278/4000] Validation [1/4] Loss: 0.38176 focal_loss 0.31897 dice_loss 0.06279 +Epoch [3278/4000] Validation [2/4] Loss: 0.46632 focal_loss 0.35325 dice_loss 0.11307 +Epoch [3278/4000] Validation [3/4] Loss: 0.50658 focal_loss 0.41297 dice_loss 0.09361 +Epoch [3278/4000] Validation [4/4] Loss: 0.31098 focal_loss 0.22691 dice_loss 0.08407 +Epoch [3278/4000] Validation metric {'Val/mean dice_metric': 0.9727510213851929, 'Val/mean miou_metric': 0.9585069417953491, 'Val/mean f1': 0.9758388996124268, 'Val/mean precision': 0.9735399484634399, 'Val/mean recall': 0.9781487584114075, 'Val/mean hd95_metric': 5.479976654052734} +Cheakpoint... +Epoch [3278/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727510213851929, 'Val/mean miou_metric': 0.9585069417953491, 'Val/mean f1': 0.9758388996124268, 'Val/mean precision': 0.9735399484634399, 'Val/mean recall': 0.9781487584114075, 'Val/mean hd95_metric': 5.479976654052734} +Epoch [3279/4000] Training [1/16] Loss: 0.00294 +Epoch [3279/4000] Training [2/16] Loss: 0.00281 +Epoch [3279/4000] Training [3/16] Loss: 0.00206 +Epoch [3279/4000] Training [4/16] Loss: 0.00260 +Epoch [3279/4000] Training [5/16] Loss: 0.00335 +Epoch [3279/4000] Training [6/16] Loss: 0.00203 +Epoch [3279/4000] Training [7/16] Loss: 0.00410 +Epoch [3279/4000] Training [8/16] Loss: 0.00399 +Epoch [3279/4000] Training [9/16] Loss: 0.00225 +Epoch [3279/4000] Training [10/16] Loss: 0.00176 +Epoch [3279/4000] Training [11/16] Loss: 0.00248 +Epoch [3279/4000] Training [12/16] Loss: 0.00247 +Epoch [3279/4000] Training [13/16] Loss: 0.00242 +Epoch [3279/4000] Training [14/16] Loss: 0.00283 +Epoch [3279/4000] Training [15/16] Loss: 0.00272 +Epoch [3279/4000] Training [16/16] Loss: 0.00332 +Epoch [3279/4000] Training metric {'Train/mean dice_metric': 0.9985048770904541, 'Train/mean miou_metric': 0.9967119097709656, 'Train/mean f1': 0.993319034576416, 'Train/mean precision': 0.9885256886482239, 'Train/mean recall': 0.9981590509414673, 'Train/mean hd95_metric': 0.6676056385040283} +Epoch [3279/4000] Validation [1/4] Loss: 0.40219 focal_loss 0.33625 dice_loss 0.06594 +Epoch [3279/4000] Validation [2/4] Loss: 0.51374 focal_loss 0.37100 dice_loss 0.14274 +Epoch [3279/4000] Validation [3/4] Loss: 0.51569 focal_loss 0.42279 dice_loss 0.09290 +Epoch [3279/4000] Validation [4/4] Loss: 0.31490 focal_loss 0.22741 dice_loss 0.08749 +Epoch [3279/4000] Validation metric {'Val/mean dice_metric': 0.9731680154800415, 'Val/mean miou_metric': 0.9588844180107117, 'Val/mean f1': 0.9754846096038818, 'Val/mean precision': 0.9732837677001953, 'Val/mean recall': 0.9776953458786011, 'Val/mean hd95_metric': 4.971818923950195} +Cheakpoint... +Epoch [3279/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731680154800415, 'Val/mean miou_metric': 0.9588844180107117, 'Val/mean f1': 0.9754846096038818, 'Val/mean precision': 0.9732837677001953, 'Val/mean recall': 0.9776953458786011, 'Val/mean hd95_metric': 4.971818923950195} +Epoch [3280/4000] Training [1/16] Loss: 0.00161 +Epoch [3280/4000] Training [2/16] Loss: 0.00222 +Epoch [3280/4000] Training [3/16] Loss: 0.00271 +Epoch [3280/4000] Training [4/16] Loss: 0.00297 +Epoch [3280/4000] Training [5/16] Loss: 0.00218 +Epoch [3280/4000] Training [6/16] Loss: 0.00338 +Epoch [3280/4000] Training [7/16] Loss: 0.00215 +Epoch [3280/4000] Training [8/16] Loss: 0.00186 +Epoch [3280/4000] Training [9/16] Loss: 0.00307 +Epoch [3280/4000] Training [10/16] Loss: 0.00214 +Epoch [3280/4000] Training [11/16] Loss: 0.00479 +Epoch [3280/4000] Training [12/16] Loss: 0.00264 +Epoch [3280/4000] Training [13/16] Loss: 0.00289 +Epoch [3280/4000] Training [14/16] Loss: 0.00241 +Epoch [3280/4000] Training [15/16] Loss: 0.00460 +Epoch [3280/4000] Training [16/16] Loss: 0.00292 +Epoch [3280/4000] Training metric {'Train/mean dice_metric': 0.9985833168029785, 'Train/mean miou_metric': 0.9968931674957275, 'Train/mean f1': 0.993644118309021, 'Train/mean precision': 0.9891361594200134, 'Train/mean recall': 0.9981933236122131, 'Train/mean hd95_metric': 0.609890878200531} +Epoch [3280/4000] Validation [1/4] Loss: 0.38072 focal_loss 0.31761 dice_loss 0.06311 +Epoch [3280/4000] Validation [2/4] Loss: 0.94638 focal_loss 0.75734 dice_loss 0.18904 +Epoch [3280/4000] Validation [3/4] Loss: 0.52957 focal_loss 0.43367 dice_loss 0.09590 +Epoch [3280/4000] Validation [4/4] Loss: 0.43478 focal_loss 0.31939 dice_loss 0.11538 +Epoch [3280/4000] Validation metric {'Val/mean dice_metric': 0.9727765321731567, 'Val/mean miou_metric': 0.9590984582901001, 'Val/mean f1': 0.9759158492088318, 'Val/mean precision': 0.973782479763031, 'Val/mean recall': 0.9780586361885071, 'Val/mean hd95_metric': 5.16032075881958} +Cheakpoint... +Epoch [3280/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727765321731567, 'Val/mean miou_metric': 0.9590984582901001, 'Val/mean f1': 0.9759158492088318, 'Val/mean precision': 0.973782479763031, 'Val/mean recall': 0.9780586361885071, 'Val/mean hd95_metric': 5.16032075881958} +Epoch [3281/4000] Training [1/16] Loss: 0.00317 +Epoch [3281/4000] Training [2/16] Loss: 0.00192 +Epoch [3281/4000] Training [3/16] Loss: 0.00255 +Epoch [3281/4000] Training [4/16] Loss: 0.00791 +Epoch [3281/4000] Training [5/16] Loss: 0.00225 +Epoch [3281/4000] Training [6/16] Loss: 0.00203 +Epoch [3281/4000] Training [7/16] Loss: 0.00288 +Epoch [3281/4000] Training [8/16] Loss: 0.00335 +Epoch [3281/4000] Training [9/16] Loss: 0.00233 +Epoch [3281/4000] Training [10/16] Loss: 0.00222 +Epoch [3281/4000] Training [11/16] Loss: 0.00293 +Epoch [3281/4000] Training [12/16] Loss: 0.00256 +Epoch [3281/4000] Training [13/16] Loss: 0.00312 +Epoch [3281/4000] Training [14/16] Loss: 0.00235 +Epoch [3281/4000] Training [15/16] Loss: 0.00168 +Epoch [3281/4000] Training [16/16] Loss: 0.00259 +Epoch [3281/4000] Training metric {'Train/mean dice_metric': 0.9985449314117432, 'Train/mean miou_metric': 0.9968129396438599, 'Train/mean f1': 0.9935368299484253, 'Train/mean precision': 0.9889155626296997, 'Train/mean recall': 0.9982014894485474, 'Train/mean hd95_metric': 0.6523714065551758} +Epoch [3281/4000] Validation [1/4] Loss: 0.40226 focal_loss 0.33996 dice_loss 0.06230 +Epoch [3281/4000] Validation [2/4] Loss: 0.39734 focal_loss 0.29553 dice_loss 0.10181 +Epoch [3281/4000] Validation [3/4] Loss: 0.51530 focal_loss 0.42567 dice_loss 0.08963 +Epoch [3281/4000] Validation [4/4] Loss: 0.27224 focal_loss 0.18237 dice_loss 0.08987 +Epoch [3281/4000] Validation metric {'Val/mean dice_metric': 0.9739183187484741, 'Val/mean miou_metric': 0.9600571393966675, 'Val/mean f1': 0.9764113426208496, 'Val/mean precision': 0.974251389503479, 'Val/mean recall': 0.9785809516906738, 'Val/mean hd95_metric': 4.759337902069092} +Cheakpoint... +Epoch [3281/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739183187484741, 'Val/mean miou_metric': 0.9600571393966675, 'Val/mean f1': 0.9764113426208496, 'Val/mean precision': 0.974251389503479, 'Val/mean recall': 0.9785809516906738, 'Val/mean hd95_metric': 4.759337902069092} +Epoch [3282/4000] Training [1/16] Loss: 0.00373 +Epoch [3282/4000] Training [2/16] Loss: 0.00338 +Epoch [3282/4000] Training [3/16] Loss: 0.00273 +Epoch [3282/4000] Training [4/16] Loss: 0.00314 +Epoch [3282/4000] Training [5/16] Loss: 0.00254 +Epoch [3282/4000] Training [6/16] Loss: 0.00236 +Epoch [3282/4000] Training [7/16] Loss: 0.00277 +Epoch [3282/4000] Training [8/16] Loss: 0.00310 +Epoch [3282/4000] Training [9/16] Loss: 0.00404 +Epoch [3282/4000] Training [10/16] Loss: 0.00230 +Epoch [3282/4000] Training [11/16] Loss: 0.00292 +Epoch [3282/4000] Training [12/16] Loss: 0.00369 +Epoch [3282/4000] Training [13/16] Loss: 0.00178 +Epoch [3282/4000] Training [14/16] Loss: 0.00248 +Epoch [3282/4000] Training [15/16] Loss: 0.00172 +Epoch [3282/4000] Training [16/16] Loss: 0.00241 +Epoch [3282/4000] Training metric {'Train/mean dice_metric': 0.9985507726669312, 'Train/mean miou_metric': 0.9968312978744507, 'Train/mean f1': 0.9936444163322449, 'Train/mean precision': 0.9891063570976257, 'Train/mean recall': 0.9982242584228516, 'Train/mean hd95_metric': 0.6307893395423889} +Epoch [3282/4000] Validation [1/4] Loss: 0.40454 focal_loss 0.34101 dice_loss 0.06353 +Epoch [3282/4000] Validation [2/4] Loss: 0.51487 focal_loss 0.37806 dice_loss 0.13681 +Epoch [3282/4000] Validation [3/4] Loss: 0.26451 focal_loss 0.19743 dice_loss 0.06708 +Epoch [3282/4000] Validation [4/4] Loss: 0.36482 focal_loss 0.25652 dice_loss 0.10830 +Epoch [3282/4000] Validation metric {'Val/mean dice_metric': 0.9758356213569641, 'Val/mean miou_metric': 0.9613332748413086, 'Val/mean f1': 0.9765804409980774, 'Val/mean precision': 0.973666250705719, 'Val/mean recall': 0.9795122146606445, 'Val/mean hd95_metric': 5.002470016479492} +Cheakpoint... +Epoch [3282/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758356213569641, 'Val/mean miou_metric': 0.9613332748413086, 'Val/mean f1': 0.9765804409980774, 'Val/mean precision': 0.973666250705719, 'Val/mean recall': 0.9795122146606445, 'Val/mean hd95_metric': 5.002470016479492} +Epoch [3283/4000] Training [1/16] Loss: 0.00231 +Epoch [3283/4000] Training [2/16] Loss: 0.00323 +Epoch [3283/4000] Training [3/16] Loss: 0.00317 +Epoch [3283/4000] Training [4/16] Loss: 0.00315 +Epoch [3283/4000] Training [5/16] Loss: 0.00268 +Epoch [3283/4000] Training [6/16] Loss: 0.00271 +Epoch [3283/4000] Training [7/16] Loss: 0.00252 +Epoch [3283/4000] Training [8/16] Loss: 0.00270 +Epoch [3283/4000] Training [9/16] Loss: 0.00324 +Epoch [3283/4000] Training [10/16] Loss: 0.00368 +Epoch [3283/4000] Training [11/16] Loss: 0.00286 +Epoch [3283/4000] Training [12/16] Loss: 0.00215 +Epoch [3283/4000] Training [13/16] Loss: 0.00297 +Epoch [3283/4000] Training [14/16] Loss: 0.00213 +Epoch [3283/4000] Training [15/16] Loss: 0.00245 +Epoch [3283/4000] Training [16/16] Loss: 0.00334 +Epoch [3283/4000] Training metric {'Train/mean dice_metric': 0.9985751509666443, 'Train/mean miou_metric': 0.9968655109405518, 'Train/mean f1': 0.9933620691299438, 'Train/mean precision': 0.9886427521705627, 'Train/mean recall': 0.9981266260147095, 'Train/mean hd95_metric': 0.6249997615814209} +Epoch [3283/4000] Validation [1/4] Loss: 0.35876 focal_loss 0.29916 dice_loss 0.05960 +Epoch [3283/4000] Validation [2/4] Loss: 1.18345 focal_loss 0.97408 dice_loss 0.20936 +Epoch [3283/4000] Validation [3/4] Loss: 0.55186 focal_loss 0.45297 dice_loss 0.09888 +Epoch [3283/4000] Validation [4/4] Loss: 0.46316 focal_loss 0.33173 dice_loss 0.13143 +Epoch [3283/4000] Validation metric {'Val/mean dice_metric': 0.9729684591293335, 'Val/mean miou_metric': 0.9588775634765625, 'Val/mean f1': 0.9758515954017639, 'Val/mean precision': 0.9731545448303223, 'Val/mean recall': 0.978563666343689, 'Val/mean hd95_metric': 4.568049430847168} +Cheakpoint... +Epoch [3283/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729684591293335, 'Val/mean miou_metric': 0.9588775634765625, 'Val/mean f1': 0.9758515954017639, 'Val/mean precision': 0.9731545448303223, 'Val/mean recall': 0.978563666343689, 'Val/mean hd95_metric': 4.568049430847168} +Epoch [3284/4000] Training [1/16] Loss: 0.00250 +Epoch [3284/4000] Training [2/16] Loss: 0.00259 +Epoch [3284/4000] Training [3/16] Loss: 0.00294 +Epoch [3284/4000] Training [4/16] Loss: 0.00223 +Epoch [3284/4000] Training [5/16] Loss: 0.00187 +Epoch [3284/4000] Training [6/16] Loss: 0.00352 +Epoch [3284/4000] Training [7/16] Loss: 0.00282 +Epoch [3284/4000] Training [8/16] Loss: 0.00246 +Epoch [3284/4000] Training [9/16] Loss: 0.00201 +Epoch [3284/4000] Training [10/16] Loss: 0.00246 +Epoch [3284/4000] Training [11/16] Loss: 0.00197 +Epoch [3284/4000] Training [12/16] Loss: 0.00212 +Epoch [3284/4000] Training [13/16] Loss: 0.00282 +Epoch [3284/4000] Training [14/16] Loss: 0.00319 +Epoch [3284/4000] Training [15/16] Loss: 0.00350 +Epoch [3284/4000] Training [16/16] Loss: 0.00343 +Epoch [3284/4000] Training metric {'Train/mean dice_metric': 0.9985212087631226, 'Train/mean miou_metric': 0.9967703819274902, 'Train/mean f1': 0.9935536980628967, 'Train/mean precision': 0.9890340566635132, 'Train/mean recall': 0.9981147646903992, 'Train/mean hd95_metric': 0.650711178779602} +Epoch [3284/4000] Validation [1/4] Loss: 0.36003 focal_loss 0.29860 dice_loss 0.06143 +Epoch [3284/4000] Validation [2/4] Loss: 1.30797 focal_loss 1.03035 dice_loss 0.27762 +Epoch [3284/4000] Validation [3/4] Loss: 0.31713 focal_loss 0.24303 dice_loss 0.07411 +Epoch [3284/4000] Validation [4/4] Loss: 0.32785 focal_loss 0.24076 dice_loss 0.08709 +Epoch [3284/4000] Validation metric {'Val/mean dice_metric': 0.973387598991394, 'Val/mean miou_metric': 0.9596306085586548, 'Val/mean f1': 0.9762367606163025, 'Val/mean precision': 0.9738660454750061, 'Val/mean recall': 0.9786190986633301, 'Val/mean hd95_metric': 4.983875751495361} +Cheakpoint... +Epoch [3284/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973387598991394, 'Val/mean miou_metric': 0.9596306085586548, 'Val/mean f1': 0.9762367606163025, 'Val/mean precision': 0.9738660454750061, 'Val/mean recall': 0.9786190986633301, 'Val/mean hd95_metric': 4.983875751495361} +Epoch [3285/4000] Training [1/16] Loss: 0.00275 +Epoch [3285/4000] Training [2/16] Loss: 0.00322 +Epoch [3285/4000] Training [3/16] Loss: 0.00275 +Epoch [3285/4000] Training [4/16] Loss: 0.00266 +Epoch [3285/4000] Training [5/16] Loss: 0.00230 +Epoch [3285/4000] Training [6/16] Loss: 0.00248 +Epoch [3285/4000] Training [7/16] Loss: 0.00314 +Epoch [3285/4000] Training [8/16] Loss: 0.00227 +Epoch [3285/4000] Training [9/16] Loss: 0.00294 +Epoch [3285/4000] Training [10/16] Loss: 0.00238 +Epoch [3285/4000] Training [11/16] Loss: 0.00226 +Epoch [3285/4000] Training [12/16] Loss: 0.00329 +Epoch [3285/4000] Training [13/16] Loss: 0.00201 +Epoch [3285/4000] Training [14/16] Loss: 0.00162 +Epoch [3285/4000] Training [15/16] Loss: 0.00274 +Epoch [3285/4000] Training [16/16] Loss: 0.00250 +Epoch [3285/4000] Training metric {'Train/mean dice_metric': 0.9985887408256531, 'Train/mean miou_metric': 0.9968830347061157, 'Train/mean f1': 0.9934072494506836, 'Train/mean precision': 0.9886391758918762, 'Train/mean recall': 0.9982215762138367, 'Train/mean hd95_metric': 0.6534454822540283} +Epoch [3285/4000] Validation [1/4] Loss: 0.46094 focal_loss 0.39041 dice_loss 0.07052 +Epoch [3285/4000] Validation [2/4] Loss: 0.41525 focal_loss 0.30932 dice_loss 0.10592 +Epoch [3285/4000] Validation [3/4] Loss: 0.25508 focal_loss 0.18933 dice_loss 0.06575 +Epoch [3285/4000] Validation [4/4] Loss: 0.30198 focal_loss 0.21267 dice_loss 0.08931 +Epoch [3285/4000] Validation metric {'Val/mean dice_metric': 0.9733875393867493, 'Val/mean miou_metric': 0.9590158462524414, 'Val/mean f1': 0.9757475852966309, 'Val/mean precision': 0.9733151793479919, 'Val/mean recall': 0.9781922698020935, 'Val/mean hd95_metric': 5.562332630157471} +Cheakpoint... +Epoch [3285/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733875393867493, 'Val/mean miou_metric': 0.9590158462524414, 'Val/mean f1': 0.9757475852966309, 'Val/mean precision': 0.9733151793479919, 'Val/mean recall': 0.9781922698020935, 'Val/mean hd95_metric': 5.562332630157471} +Epoch [3286/4000] Training [1/16] Loss: 0.00247 +Epoch [3286/4000] Training [2/16] Loss: 0.00341 +Epoch [3286/4000] Training [3/16] Loss: 0.00232 +Epoch [3286/4000] Training [4/16] Loss: 0.00329 +Epoch [3286/4000] Training [5/16] Loss: 0.00204 +Epoch [3286/4000] Training [6/16] Loss: 0.00259 +Epoch [3286/4000] Training [7/16] Loss: 0.00318 +Epoch [3286/4000] Training [8/16] Loss: 0.00234 +Epoch [3286/4000] Training [9/16] Loss: 0.00344 +Epoch [3286/4000] Training [10/16] Loss: 0.00278 +Epoch [3286/4000] Training [11/16] Loss: 0.00213 +Epoch [3286/4000] Training [12/16] Loss: 0.00294 +Epoch [3286/4000] Training [13/16] Loss: 0.00438 +Epoch [3286/4000] Training [14/16] Loss: 0.00265 +Epoch [3286/4000] Training [15/16] Loss: 0.00239 +Epoch [3286/4000] Training [16/16] Loss: 0.00335 +Epoch [3286/4000] Training metric {'Train/mean dice_metric': 0.9985717535018921, 'Train/mean miou_metric': 0.9968355298042297, 'Train/mean f1': 0.9928736686706543, 'Train/mean precision': 0.9876377582550049, 'Train/mean recall': 0.9981654286384583, 'Train/mean hd95_metric': 0.641922116279602} +Epoch [3286/4000] Validation [1/4] Loss: 0.34308 focal_loss 0.28524 dice_loss 0.05784 +Epoch [3286/4000] Validation [2/4] Loss: 0.42855 focal_loss 0.32030 dice_loss 0.10825 +Epoch [3286/4000] Validation [3/4] Loss: 0.26509 focal_loss 0.20239 dice_loss 0.06270 +Epoch [3286/4000] Validation [4/4] Loss: 0.42454 focal_loss 0.31797 dice_loss 0.10657 +Epoch [3286/4000] Validation metric {'Val/mean dice_metric': 0.9759495854377747, 'Val/mean miou_metric': 0.9618147015571594, 'Val/mean f1': 0.9760674238204956, 'Val/mean precision': 0.9726490378379822, 'Val/mean recall': 0.9795100092887878, 'Val/mean hd95_metric': 4.999035835266113} +Cheakpoint... +Epoch [3286/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759495854377747, 'Val/mean miou_metric': 0.9618147015571594, 'Val/mean f1': 0.9760674238204956, 'Val/mean precision': 0.9726490378379822, 'Val/mean recall': 0.9795100092887878, 'Val/mean hd95_metric': 4.999035835266113} +Epoch [3287/4000] Training [1/16] Loss: 0.00316 +Epoch [3287/4000] Training [2/16] Loss: 0.00274 +Epoch [3287/4000] Training [3/16] Loss: 0.00244 +Epoch [3287/4000] Training [4/16] Loss: 0.00248 +Epoch [3287/4000] Training [5/16] Loss: 0.00248 +Epoch [3287/4000] Training [6/16] Loss: 0.01019 +Epoch [3287/4000] Training [7/16] Loss: 0.00314 +Epoch [3287/4000] Training [8/16] Loss: 0.00212 +Epoch [3287/4000] Training [9/16] Loss: 0.00391 +Epoch [3287/4000] Training [10/16] Loss: 0.00266 +Epoch [3287/4000] Training [11/16] Loss: 0.00263 +Epoch [3287/4000] Training [12/16] Loss: 0.00336 +Epoch [3287/4000] Training [13/16] Loss: 0.00391 +Epoch [3287/4000] Training [14/16] Loss: 0.00217 +Epoch [3287/4000] Training [15/16] Loss: 0.00274 +Epoch [3287/4000] Training [16/16] Loss: 0.00280 +Epoch [3287/4000] Training metric {'Train/mean dice_metric': 0.9984872341156006, 'Train/mean miou_metric': 0.9966592788696289, 'Train/mean f1': 0.9926245212554932, 'Train/mean precision': 0.9872718453407288, 'Train/mean recall': 0.9980356097221375, 'Train/mean hd95_metric': 0.653989315032959} +Epoch [3287/4000] Validation [1/4] Loss: 0.33778 focal_loss 0.27785 dice_loss 0.05993 +Epoch [3287/4000] Validation [2/4] Loss: 0.62457 focal_loss 0.46049 dice_loss 0.16408 +Epoch [3287/4000] Validation [3/4] Loss: 0.32547 focal_loss 0.25474 dice_loss 0.07073 +Epoch [3287/4000] Validation [4/4] Loss: 0.31525 focal_loss 0.22622 dice_loss 0.08903 +Epoch [3287/4000] Validation metric {'Val/mean dice_metric': 0.9753831028938293, 'Val/mean miou_metric': 0.960918128490448, 'Val/mean f1': 0.9756464958190918, 'Val/mean precision': 0.9721367955207825, 'Val/mean recall': 0.9791815876960754, 'Val/mean hd95_metric': 5.2431206703186035} +Cheakpoint... +Epoch [3287/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753831028938293, 'Val/mean miou_metric': 0.960918128490448, 'Val/mean f1': 0.9756464958190918, 'Val/mean precision': 0.9721367955207825, 'Val/mean recall': 0.9791815876960754, 'Val/mean hd95_metric': 5.2431206703186035} +Epoch [3288/4000] Training [1/16] Loss: 0.00461 +Epoch [3288/4000] Training [2/16] Loss: 0.00222 +Epoch [3288/4000] Training [3/16] Loss: 0.00335 +Epoch [3288/4000] Training [4/16] Loss: 0.00367 +Epoch [3288/4000] Training [5/16] Loss: 0.00235 +Epoch [3288/4000] Training [6/16] Loss: 0.00305 +Epoch [3288/4000] Training [7/16] Loss: 0.00205 +Epoch [3288/4000] Training [8/16] Loss: 0.00258 +Epoch [3288/4000] Training [9/16] Loss: 0.00337 +Epoch [3288/4000] Training [10/16] Loss: 0.00192 +Epoch [3288/4000] Training [11/16] Loss: 0.00218 +Epoch [3288/4000] Training [12/16] Loss: 0.00278 +Epoch [3288/4000] Training [13/16] Loss: 0.00270 +Epoch [3288/4000] Training [14/16] Loss: 0.00340 +Epoch [3288/4000] Training [15/16] Loss: 0.00220 +Epoch [3288/4000] Training [16/16] Loss: 0.00180 +Epoch [3288/4000] Training metric {'Train/mean dice_metric': 0.9985073804855347, 'Train/mean miou_metric': 0.9967015981674194, 'Train/mean f1': 0.9927061796188354, 'Train/mean precision': 0.9873547554016113, 'Train/mean recall': 0.9981159567832947, 'Train/mean hd95_metric': 0.6521338820457458} +Epoch [3288/4000] Validation [1/4] Loss: 0.31204 focal_loss 0.25257 dice_loss 0.05947 +Epoch [3288/4000] Validation [2/4] Loss: 0.78274 focal_loss 0.59591 dice_loss 0.18683 +Epoch [3288/4000] Validation [3/4] Loss: 0.52307 focal_loss 0.43191 dice_loss 0.09115 +Epoch [3288/4000] Validation [4/4] Loss: 0.30434 focal_loss 0.21071 dice_loss 0.09363 +Epoch [3288/4000] Validation metric {'Val/mean dice_metric': 0.9726227521896362, 'Val/mean miou_metric': 0.95868980884552, 'Val/mean f1': 0.9752713441848755, 'Val/mean precision': 0.9716328978538513, 'Val/mean recall': 0.9789371490478516, 'Val/mean hd95_metric': 4.868971347808838} +Cheakpoint... +Epoch [3288/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726227521896362, 'Val/mean miou_metric': 0.95868980884552, 'Val/mean f1': 0.9752713441848755, 'Val/mean precision': 0.9716328978538513, 'Val/mean recall': 0.9789371490478516, 'Val/mean hd95_metric': 4.868971347808838} +Epoch [3289/4000] Training [1/16] Loss: 0.00200 +Epoch [3289/4000] Training [2/16] Loss: 0.00299 +Epoch [3289/4000] Training [3/16] Loss: 0.00341 +Epoch [3289/4000] Training [4/16] Loss: 0.00273 +Epoch [3289/4000] Training [5/16] Loss: 0.00386 +Epoch [3289/4000] Training [6/16] Loss: 0.00240 +Epoch [3289/4000] Training [7/16] Loss: 0.00255 +Epoch [3289/4000] Training [8/16] Loss: 0.00276 +Epoch [3289/4000] Training [9/16] Loss: 0.00219 +Epoch [3289/4000] Training [10/16] Loss: 0.00176 +Epoch [3289/4000] Training [11/16] Loss: 0.00265 +Epoch [3289/4000] Training [12/16] Loss: 0.00304 +Epoch [3289/4000] Training [13/16] Loss: 0.00178 +Epoch [3289/4000] Training [14/16] Loss: 0.00193 +Epoch [3289/4000] Training [15/16] Loss: 0.00207 +Epoch [3289/4000] Training [16/16] Loss: 0.00351 +Epoch [3289/4000] Training metric {'Train/mean dice_metric': 0.9986987113952637, 'Train/mean miou_metric': 0.9971247911453247, 'Train/mean f1': 0.9937576651573181, 'Train/mean precision': 0.9892145991325378, 'Train/mean recall': 0.9983425736427307, 'Train/mean hd95_metric': 0.6145083904266357} +Epoch [3289/4000] Validation [1/4] Loss: 0.48295 focal_loss 0.40982 dice_loss 0.07313 +Epoch [3289/4000] Validation [2/4] Loss: 0.41137 focal_loss 0.30908 dice_loss 0.10229 +Epoch [3289/4000] Validation [3/4] Loss: 0.51563 focal_loss 0.42615 dice_loss 0.08948 +Epoch [3289/4000] Validation [4/4] Loss: 0.33719 focal_loss 0.24090 dice_loss 0.09629 +Epoch [3289/4000] Validation metric {'Val/mean dice_metric': 0.975611686706543, 'Val/mean miou_metric': 0.9616788625717163, 'Val/mean f1': 0.9771301746368408, 'Val/mean precision': 0.9735393524169922, 'Val/mean recall': 0.980747640132904, 'Val/mean hd95_metric': 4.745694160461426} +Cheakpoint... +Epoch [3289/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975611686706543, 'Val/mean miou_metric': 0.9616788625717163, 'Val/mean f1': 0.9771301746368408, 'Val/mean precision': 0.9735393524169922, 'Val/mean recall': 0.980747640132904, 'Val/mean hd95_metric': 4.745694160461426} +Epoch [3290/4000] Training [1/16] Loss: 0.00201 +Epoch [3290/4000] Training [2/16] Loss: 0.00263 +Epoch [3290/4000] Training [3/16] Loss: 0.00221 +Epoch [3290/4000] Training [4/16] Loss: 0.00255 +Epoch [3290/4000] Training [5/16] Loss: 0.00360 +Epoch [3290/4000] Training [6/16] Loss: 0.00204 +Epoch [3290/4000] Training [7/16] Loss: 0.00334 +Epoch [3290/4000] Training [8/16] Loss: 0.00223 +Epoch [3290/4000] Training [9/16] Loss: 0.00294 +Epoch [3290/4000] Training [10/16] Loss: 0.00314 +Epoch [3290/4000] Training [11/16] Loss: 0.00310 +Epoch [3290/4000] Training [12/16] Loss: 0.00268 +Epoch [3290/4000] Training [13/16] Loss: 0.00278 +Epoch [3290/4000] Training [14/16] Loss: 0.00287 +Epoch [3290/4000] Training [15/16] Loss: 0.00265 +Epoch [3290/4000] Training [16/16] Loss: 0.00256 +Epoch [3290/4000] Training metric {'Train/mean dice_metric': 0.9985522627830505, 'Train/mean miou_metric': 0.9968322515487671, 'Train/mean f1': 0.9936743378639221, 'Train/mean precision': 0.9891520142555237, 'Train/mean recall': 0.998238205909729, 'Train/mean hd95_metric': 0.65256667137146} +Epoch [3290/4000] Validation [1/4] Loss: 0.37531 focal_loss 0.31442 dice_loss 0.06089 +Epoch [3290/4000] Validation [2/4] Loss: 0.38617 focal_loss 0.28358 dice_loss 0.10259 +Epoch [3290/4000] Validation [3/4] Loss: 0.53741 focal_loss 0.44379 dice_loss 0.09362 +Epoch [3290/4000] Validation [4/4] Loss: 0.29211 focal_loss 0.20161 dice_loss 0.09051 +Epoch [3290/4000] Validation metric {'Val/mean dice_metric': 0.9749605059623718, 'Val/mean miou_metric': 0.9610525965690613, 'Val/mean f1': 0.9764227867126465, 'Val/mean precision': 0.9722890257835388, 'Val/mean recall': 0.980591893196106, 'Val/mean hd95_metric': 5.19124174118042} +Cheakpoint... +Epoch [3290/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749605059623718, 'Val/mean miou_metric': 0.9610525965690613, 'Val/mean f1': 0.9764227867126465, 'Val/mean precision': 0.9722890257835388, 'Val/mean recall': 0.980591893196106, 'Val/mean hd95_metric': 5.19124174118042} +Epoch [3291/4000] Training [1/16] Loss: 0.00244 +Epoch [3291/4000] Training [2/16] Loss: 0.00250 +Epoch [3291/4000] Training [3/16] Loss: 0.00295 +Epoch [3291/4000] Training [4/16] Loss: 0.00237 +Epoch [3291/4000] Training [5/16] Loss: 0.00234 +Epoch [3291/4000] Training [6/16] Loss: 0.00260 +Epoch [3291/4000] Training [7/16] Loss: 0.00333 +Epoch [3291/4000] Training [8/16] Loss: 0.00428 +Epoch [3291/4000] Training [9/16] Loss: 0.00361 +Epoch [3291/4000] Training [10/16] Loss: 0.00254 +Epoch [3291/4000] Training [11/16] Loss: 0.00260 +Epoch [3291/4000] Training [12/16] Loss: 0.00201 +Epoch [3291/4000] Training [13/16] Loss: 0.00210 +Epoch [3291/4000] Training [14/16] Loss: 0.00355 +Epoch [3291/4000] Training [15/16] Loss: 0.00192 +Epoch [3291/4000] Training [16/16] Loss: 0.00277 +Epoch [3291/4000] Training metric {'Train/mean dice_metric': 0.998499870300293, 'Train/mean miou_metric': 0.9967284202575684, 'Train/mean f1': 0.9935545921325684, 'Train/mean precision': 0.9889944791793823, 'Train/mean recall': 0.9981569647789001, 'Train/mean hd95_metric': 0.6416289210319519} +Epoch [3291/4000] Validation [1/4] Loss: 0.37478 focal_loss 0.31509 dice_loss 0.05970 +Epoch [3291/4000] Validation [2/4] Loss: 0.77479 focal_loss 0.59158 dice_loss 0.18321 +Epoch [3291/4000] Validation [3/4] Loss: 0.25963 focal_loss 0.19684 dice_loss 0.06280 +Epoch [3291/4000] Validation [4/4] Loss: 0.35162 focal_loss 0.25335 dice_loss 0.09827 +Epoch [3291/4000] Validation metric {'Val/mean dice_metric': 0.9736654162406921, 'Val/mean miou_metric': 0.9598749279975891, 'Val/mean f1': 0.9760584235191345, 'Val/mean precision': 0.9736353158950806, 'Val/mean recall': 0.9784938097000122, 'Val/mean hd95_metric': 4.9145050048828125} +Cheakpoint... +Epoch [3291/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736654162406921, 'Val/mean miou_metric': 0.9598749279975891, 'Val/mean f1': 0.9760584235191345, 'Val/mean precision': 0.9736353158950806, 'Val/mean recall': 0.9784938097000122, 'Val/mean hd95_metric': 4.9145050048828125} +Epoch [3292/4000] Training [1/16] Loss: 0.00295 +Epoch [3292/4000] Training [2/16] Loss: 0.00300 +Epoch [3292/4000] Training [3/16] Loss: 0.00340 +Epoch [3292/4000] Training [4/16] Loss: 0.00259 +Epoch [3292/4000] Training [5/16] Loss: 0.00409 +Epoch [3292/4000] Training [6/16] Loss: 0.00232 +Epoch [3292/4000] Training [7/16] Loss: 0.00215 +Epoch [3292/4000] Training [8/16] Loss: 0.00408 +Epoch [3292/4000] Training [9/16] Loss: 0.00196 +Epoch [3292/4000] Training [10/16] Loss: 0.00243 +Epoch [3292/4000] Training [11/16] Loss: 0.00338 +Epoch [3292/4000] Training [12/16] Loss: 0.00379 +Epoch [3292/4000] Training [13/16] Loss: 0.00246 +Epoch [3292/4000] Training [14/16] Loss: 0.00379 +Epoch [3292/4000] Training [15/16] Loss: 0.00268 +Epoch [3292/4000] Training [16/16] Loss: 0.00181 +Epoch [3292/4000] Training metric {'Train/mean dice_metric': 0.9984751343727112, 'Train/mean miou_metric': 0.9966814517974854, 'Train/mean f1': 0.9935302734375, 'Train/mean precision': 0.988967776298523, 'Train/mean recall': 0.9981350302696228, 'Train/mean hd95_metric': 0.6469302177429199} +Epoch [3292/4000] Validation [1/4] Loss: 0.45527 focal_loss 0.39095 dice_loss 0.06432 +Epoch [3292/4000] Validation [2/4] Loss: 0.73288 focal_loss 0.56249 dice_loss 0.17039 +Epoch [3292/4000] Validation [3/4] Loss: 0.52938 focal_loss 0.43662 dice_loss 0.09276 +Epoch [3292/4000] Validation [4/4] Loss: 0.34801 focal_loss 0.25182 dice_loss 0.09619 +Epoch [3292/4000] Validation metric {'Val/mean dice_metric': 0.975528359413147, 'Val/mean miou_metric': 0.9613262414932251, 'Val/mean f1': 0.976346492767334, 'Val/mean precision': 0.9723739624023438, 'Val/mean recall': 0.9803515672683716, 'Val/mean hd95_metric': 4.675503253936768} +Cheakpoint... +Epoch [3292/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975528359413147, 'Val/mean miou_metric': 0.9613262414932251, 'Val/mean f1': 0.976346492767334, 'Val/mean precision': 0.9723739624023438, 'Val/mean recall': 0.9803515672683716, 'Val/mean hd95_metric': 4.675503253936768} +Epoch [3293/4000] Training [1/16] Loss: 0.00326 +Epoch [3293/4000] Training [2/16] Loss: 0.00200 +Epoch [3293/4000] Training [3/16] Loss: 0.00228 +Epoch [3293/4000] Training [4/16] Loss: 0.00326 +Epoch [3293/4000] Training [5/16] Loss: 0.00234 +Epoch [3293/4000] Training [6/16] Loss: 0.00323 +Epoch [3293/4000] Training [7/16] Loss: 0.00290 +Epoch [3293/4000] Training [8/16] Loss: 0.00190 +Epoch [3293/4000] Training [9/16] Loss: 0.00353 +Epoch [3293/4000] Training [10/16] Loss: 0.00301 +Epoch [3293/4000] Training [11/16] Loss: 0.00308 +Epoch [3293/4000] Training [12/16] Loss: 0.00377 +Epoch [3293/4000] Training [13/16] Loss: 0.00297 +Epoch [3293/4000] Training [14/16] Loss: 0.00257 +Epoch [3293/4000] Training [15/16] Loss: 0.00264 +Epoch [3293/4000] Training [16/16] Loss: 0.00208 +Epoch [3293/4000] Training metric {'Train/mean dice_metric': 0.9985511302947998, 'Train/mean miou_metric': 0.9968289136886597, 'Train/mean f1': 0.9936416149139404, 'Train/mean precision': 0.9891047477722168, 'Train/mean recall': 0.9982202649116516, 'Train/mean hd95_metric': 0.6553987264633179} +Epoch [3293/4000] Validation [1/4] Loss: 0.45419 focal_loss 0.39028 dice_loss 0.06391 +Epoch [3293/4000] Validation [2/4] Loss: 0.54089 focal_loss 0.39520 dice_loss 0.14569 +Epoch [3293/4000] Validation [3/4] Loss: 0.51811 focal_loss 0.42657 dice_loss 0.09153 +Epoch [3293/4000] Validation [4/4] Loss: 0.35990 focal_loss 0.26418 dice_loss 0.09573 +Epoch [3293/4000] Validation metric {'Val/mean dice_metric': 0.9755132794380188, 'Val/mean miou_metric': 0.9611756205558777, 'Val/mean f1': 0.976508617401123, 'Val/mean precision': 0.972685694694519, 'Val/mean recall': 0.9803617596626282, 'Val/mean hd95_metric': 5.037519931793213} +Cheakpoint... +Epoch [3293/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755132794380188, 'Val/mean miou_metric': 0.9611756205558777, 'Val/mean f1': 0.976508617401123, 'Val/mean precision': 0.972685694694519, 'Val/mean recall': 0.9803617596626282, 'Val/mean hd95_metric': 5.037519931793213} +Epoch [3294/4000] Training [1/16] Loss: 0.00235 +Epoch [3294/4000] Training [2/16] Loss: 0.00222 +Epoch [3294/4000] Training [3/16] Loss: 0.00341 +Epoch [3294/4000] Training [4/16] Loss: 0.00186 +Epoch [3294/4000] Training [5/16] Loss: 0.00412 +Epoch [3294/4000] Training [6/16] Loss: 0.00204 +Epoch [3294/4000] Training [7/16] Loss: 0.00200 +Epoch [3294/4000] Training [8/16] Loss: 0.00184 +Epoch [3294/4000] Training [9/16] Loss: 0.00341 +Epoch [3294/4000] Training [10/16] Loss: 0.00267 +Epoch [3294/4000] Training [11/16] Loss: 0.00299 +Epoch [3294/4000] Training [12/16] Loss: 0.00224 +Epoch [3294/4000] Training [13/16] Loss: 0.00263 +Epoch [3294/4000] Training [14/16] Loss: 0.00252 +Epoch [3294/4000] Training [15/16] Loss: 0.00207 +Epoch [3294/4000] Training [16/16] Loss: 0.00347 +Epoch [3294/4000] Training metric {'Train/mean dice_metric': 0.998626172542572, 'Train/mean miou_metric': 0.9969791173934937, 'Train/mean f1': 0.9937129616737366, 'Train/mean precision': 0.9891889095306396, 'Train/mean recall': 0.9982785582542419, 'Train/mean hd95_metric': 0.6073518991470337} +Epoch [3294/4000] Validation [1/4] Loss: 0.39461 focal_loss 0.33329 dice_loss 0.06132 +Epoch [3294/4000] Validation [2/4] Loss: 0.94081 focal_loss 0.71071 dice_loss 0.23011 +Epoch [3294/4000] Validation [3/4] Loss: 0.56619 focal_loss 0.47123 dice_loss 0.09496 +Epoch [3294/4000] Validation [4/4] Loss: 0.35161 focal_loss 0.24756 dice_loss 0.10406 +Epoch [3294/4000] Validation metric {'Val/mean dice_metric': 0.9725137948989868, 'Val/mean miou_metric': 0.9585415124893188, 'Val/mean f1': 0.9757248759269714, 'Val/mean precision': 0.9729605913162231, 'Val/mean recall': 0.9785048365592957, 'Val/mean hd95_metric': 5.32953405380249} +Cheakpoint... +Epoch [3294/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725137948989868, 'Val/mean miou_metric': 0.9585415124893188, 'Val/mean f1': 0.9757248759269714, 'Val/mean precision': 0.9729605913162231, 'Val/mean recall': 0.9785048365592957, 'Val/mean hd95_metric': 5.32953405380249} +Epoch [3295/4000] Training [1/16] Loss: 0.00249 +Epoch [3295/4000] Training [2/16] Loss: 0.00227 +Epoch [3295/4000] Training [3/16] Loss: 0.00186 +Epoch [3295/4000] Training [4/16] Loss: 0.00701 +Epoch [3295/4000] Training [5/16] Loss: 0.00239 +Epoch [3295/4000] Training [6/16] Loss: 0.00206 +Epoch [3295/4000] Training [7/16] Loss: 0.00178 +Epoch [3295/4000] Training [8/16] Loss: 0.00246 +Epoch [3295/4000] Training [9/16] Loss: 0.00580 +Epoch [3295/4000] Training [10/16] Loss: 0.00225 +Epoch [3295/4000] Training [11/16] Loss: 0.00246 +Epoch [3295/4000] Training [12/16] Loss: 0.00301 +Epoch [3295/4000] Training [13/16] Loss: 0.00321 +Epoch [3295/4000] Training [14/16] Loss: 0.00407 +Epoch [3295/4000] Training [15/16] Loss: 0.00257 +Epoch [3295/4000] Training [16/16] Loss: 0.00258 +Epoch [3295/4000] Training metric {'Train/mean dice_metric': 0.9983447790145874, 'Train/mean miou_metric': 0.9964262247085571, 'Train/mean f1': 0.9933817386627197, 'Train/mean precision': 0.9887186288833618, 'Train/mean recall': 0.9980890154838562, 'Train/mean hd95_metric': 0.807805597782135} +Epoch [3295/4000] Validation [1/4] Loss: 0.36986 focal_loss 0.31041 dice_loss 0.05945 +Epoch [3295/4000] Validation [2/4] Loss: 0.39607 focal_loss 0.29692 dice_loss 0.09915 +Epoch [3295/4000] Validation [3/4] Loss: 0.58801 focal_loss 0.48951 dice_loss 0.09849 +Epoch [3295/4000] Validation [4/4] Loss: 0.35599 focal_loss 0.25867 dice_loss 0.09733 +Epoch [3295/4000] Validation metric {'Val/mean dice_metric': 0.974780261516571, 'Val/mean miou_metric': 0.9606296420097351, 'Val/mean f1': 0.9761613011360168, 'Val/mean precision': 0.9726293683052063, 'Val/mean recall': 0.9797188639640808, 'Val/mean hd95_metric': 5.070006370544434} +Cheakpoint... +Epoch [3295/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974780261516571, 'Val/mean miou_metric': 0.9606296420097351, 'Val/mean f1': 0.9761613011360168, 'Val/mean precision': 0.9726293683052063, 'Val/mean recall': 0.9797188639640808, 'Val/mean hd95_metric': 5.070006370544434} +Epoch [3296/4000] Training [1/16] Loss: 0.00235 +Epoch [3296/4000] Training [2/16] Loss: 0.00232 +Epoch [3296/4000] Training [3/16] Loss: 0.00184 +Epoch [3296/4000] Training [4/16] Loss: 0.00182 +Epoch [3296/4000] Training [5/16] Loss: 0.00392 +Epoch [3296/4000] Training [6/16] Loss: 0.00230 +Epoch [3296/4000] Training [7/16] Loss: 0.00232 +Epoch [3296/4000] Training [8/16] Loss: 0.00307 +Epoch [3296/4000] Training [9/16] Loss: 0.00171 +Epoch [3296/4000] Training [10/16] Loss: 0.00404 +Epoch [3296/4000] Training [11/16] Loss: 0.00252 +Epoch [3296/4000] Training [12/16] Loss: 0.00347 +Epoch [3296/4000] Training [13/16] Loss: 0.00228 +Epoch [3296/4000] Training [14/16] Loss: 0.00242 +Epoch [3296/4000] Training [15/16] Loss: 0.00233 +Epoch [3296/4000] Training [16/16] Loss: 0.00230 +Epoch [3296/4000] Training metric {'Train/mean dice_metric': 0.9986193180084229, 'Train/mean miou_metric': 0.9969686269760132, 'Train/mean f1': 0.9937374591827393, 'Train/mean precision': 0.989256739616394, 'Train/mean recall': 0.9982589483261108, 'Train/mean hd95_metric': 0.5941959619522095} +Epoch [3296/4000] Validation [1/4] Loss: 0.41302 focal_loss 0.34954 dice_loss 0.06347 +Epoch [3296/4000] Validation [2/4] Loss: 0.40094 focal_loss 0.30000 dice_loss 0.10094 +Epoch [3296/4000] Validation [3/4] Loss: 0.51118 focal_loss 0.41885 dice_loss 0.09233 +Epoch [3296/4000] Validation [4/4] Loss: 0.28891 focal_loss 0.19641 dice_loss 0.09250 +Epoch [3296/4000] Validation metric {'Val/mean dice_metric': 0.9746235013008118, 'Val/mean miou_metric': 0.9601813554763794, 'Val/mean f1': 0.9764657020568848, 'Val/mean precision': 0.973638653755188, 'Val/mean recall': 0.9793091416358948, 'Val/mean hd95_metric': 5.079501152038574} +Cheakpoint... +Epoch [3296/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746235013008118, 'Val/mean miou_metric': 0.9601813554763794, 'Val/mean f1': 0.9764657020568848, 'Val/mean precision': 0.973638653755188, 'Val/mean recall': 0.9793091416358948, 'Val/mean hd95_metric': 5.079501152038574} +Epoch [3297/4000] Training [1/16] Loss: 0.00364 +Epoch [3297/4000] Training [2/16] Loss: 0.00280 +Epoch [3297/4000] Training [3/16] Loss: 0.00326 +Epoch [3297/4000] Training [4/16] Loss: 0.00249 +Epoch [3297/4000] Training [5/16] Loss: 0.00286 +Epoch [3297/4000] Training [6/16] Loss: 0.00228 +Epoch [3297/4000] Training [7/16] Loss: 0.00278 +Epoch [3297/4000] Training [8/16] Loss: 0.00228 +Epoch [3297/4000] Training [9/16] Loss: 0.00227 +Epoch [3297/4000] Training [10/16] Loss: 0.00201 +Epoch [3297/4000] Training [11/16] Loss: 0.00264 +Epoch [3297/4000] Training [12/16] Loss: 0.00173 +Epoch [3297/4000] Training [13/16] Loss: 0.00328 +Epoch [3297/4000] Training [14/16] Loss: 0.00214 +Epoch [3297/4000] Training [15/16] Loss: 0.00226 +Epoch [3297/4000] Training [16/16] Loss: 0.00336 +Epoch [3297/4000] Training metric {'Train/mean dice_metric': 0.9985636472702026, 'Train/mean miou_metric': 0.9968485832214355, 'Train/mean f1': 0.9935540556907654, 'Train/mean precision': 0.9889584183692932, 'Train/mean recall': 0.998192548751831, 'Train/mean hd95_metric': 0.6845002770423889} +Epoch [3297/4000] Validation [1/4] Loss: 0.34318 focal_loss 0.28433 dice_loss 0.05885 +Epoch [3297/4000] Validation [2/4] Loss: 0.41798 focal_loss 0.31466 dice_loss 0.10332 +Epoch [3297/4000] Validation [3/4] Loss: 0.51497 focal_loss 0.42314 dice_loss 0.09183 +Epoch [3297/4000] Validation [4/4] Loss: 0.33398 focal_loss 0.23602 dice_loss 0.09796 +Epoch [3297/4000] Validation metric {'Val/mean dice_metric': 0.9758386611938477, 'Val/mean miou_metric': 0.9619562029838562, 'Val/mean f1': 0.976730227470398, 'Val/mean precision': 0.9737178683280945, 'Val/mean recall': 0.9797613620758057, 'Val/mean hd95_metric': 4.994556427001953} +Cheakpoint... +Epoch [3297/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758386611938477, 'Val/mean miou_metric': 0.9619562029838562, 'Val/mean f1': 0.976730227470398, 'Val/mean precision': 0.9737178683280945, 'Val/mean recall': 0.9797613620758057, 'Val/mean hd95_metric': 4.994556427001953} +Epoch [3298/4000] Training [1/16] Loss: 0.00309 +Epoch [3298/4000] Training [2/16] Loss: 0.00232 +Epoch [3298/4000] Training [3/16] Loss: 0.00371 +Epoch [3298/4000] Training [4/16] Loss: 0.00268 +Epoch [3298/4000] Training [5/16] Loss: 0.00241 +Epoch [3298/4000] Training [6/16] Loss: 0.00318 +Epoch [3298/4000] Training [7/16] Loss: 0.00232 +Epoch [3298/4000] Training [8/16] Loss: 0.00278 +Epoch [3298/4000] Training [9/16] Loss: 0.00305 +Epoch [3298/4000] Training [10/16] Loss: 0.00187 +Epoch [3298/4000] Training [11/16] Loss: 0.00487 +Epoch [3298/4000] Training [12/16] Loss: 0.00286 +Epoch [3298/4000] Training [13/16] Loss: 0.00204 +Epoch [3298/4000] Training [14/16] Loss: 0.00330 +Epoch [3298/4000] Training [15/16] Loss: 0.00277 +Epoch [3298/4000] Training [16/16] Loss: 0.00325 +Epoch [3298/4000] Training metric {'Train/mean dice_metric': 0.9984058737754822, 'Train/mean miou_metric': 0.9965431094169617, 'Train/mean f1': 0.9934483170509338, 'Train/mean precision': 0.9889119863510132, 'Train/mean recall': 0.998026430606842, 'Train/mean hd95_metric': 0.6549382209777832} +Epoch [3298/4000] Validation [1/4] Loss: 0.38077 focal_loss 0.31760 dice_loss 0.06317 +Epoch [3298/4000] Validation [2/4] Loss: 0.54128 focal_loss 0.39649 dice_loss 0.14478 +Epoch [3298/4000] Validation [3/4] Loss: 0.55393 focal_loss 0.45535 dice_loss 0.09858 +Epoch [3298/4000] Validation [4/4] Loss: 0.55836 focal_loss 0.42251 dice_loss 0.13585 +Epoch [3298/4000] Validation metric {'Val/mean dice_metric': 0.9734989404678345, 'Val/mean miou_metric': 0.9588894844055176, 'Val/mean f1': 0.9751597046852112, 'Val/mean precision': 0.9718453288078308, 'Val/mean recall': 0.9784967303276062, 'Val/mean hd95_metric': 5.210778713226318} +Cheakpoint... +Epoch [3298/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734989404678345, 'Val/mean miou_metric': 0.9588894844055176, 'Val/mean f1': 0.9751597046852112, 'Val/mean precision': 0.9718453288078308, 'Val/mean recall': 0.9784967303276062, 'Val/mean hd95_metric': 5.210778713226318} +Epoch [3299/4000] Training [1/16] Loss: 0.00253 +Epoch [3299/4000] Training [2/16] Loss: 0.00222 +Epoch [3299/4000] Training [3/16] Loss: 0.00229 +Epoch [3299/4000] Training [4/16] Loss: 0.00343 +Epoch [3299/4000] Training [5/16] Loss: 0.00230 +Epoch [3299/4000] Training [6/16] Loss: 0.00281 +Epoch [3299/4000] Training [7/16] Loss: 0.00230 +Epoch [3299/4000] Training [8/16] Loss: 0.00363 +Epoch [3299/4000] Training [9/16] Loss: 0.00357 +Epoch [3299/4000] Training [10/16] Loss: 0.00179 +Epoch [3299/4000] Training [11/16] Loss: 0.00231 +Epoch [3299/4000] Training [12/16] Loss: 0.00259 +Epoch [3299/4000] Training [13/16] Loss: 0.00466 +Epoch [3299/4000] Training [14/16] Loss: 0.00201 +Epoch [3299/4000] Training [15/16] Loss: 0.00241 +Epoch [3299/4000] Training [16/16] Loss: 0.00212 +Epoch [3299/4000] Training metric {'Train/mean dice_metric': 0.9986119270324707, 'Train/mean miou_metric': 0.9969286322593689, 'Train/mean f1': 0.9934669733047485, 'Train/mean precision': 0.9887179136276245, 'Train/mean recall': 0.9982619285583496, 'Train/mean hd95_metric': 0.60422682762146} +Epoch [3299/4000] Validation [1/4] Loss: 0.35585 focal_loss 0.29387 dice_loss 0.06198 +Epoch [3299/4000] Validation [2/4] Loss: 0.88229 focal_loss 0.68707 dice_loss 0.19522 +Epoch [3299/4000] Validation [3/4] Loss: 0.57462 focal_loss 0.47945 dice_loss 0.09517 +Epoch [3299/4000] Validation [4/4] Loss: 0.45900 focal_loss 0.34320 dice_loss 0.11580 +Epoch [3299/4000] Validation metric {'Val/mean dice_metric': 0.9732044339179993, 'Val/mean miou_metric': 0.9591687917709351, 'Val/mean f1': 0.9757458567619324, 'Val/mean precision': 0.9730451703071594, 'Val/mean recall': 0.9784616231918335, 'Val/mean hd95_metric': 5.198578834533691} +Cheakpoint... +Epoch [3299/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732044339179993, 'Val/mean miou_metric': 0.9591687917709351, 'Val/mean f1': 0.9757458567619324, 'Val/mean precision': 0.9730451703071594, 'Val/mean recall': 0.9784616231918335, 'Val/mean hd95_metric': 5.198578834533691} +Epoch [3300/4000] Training [1/16] Loss: 0.00285 +Epoch [3300/4000] Training [2/16] Loss: 0.00310 +Epoch [3300/4000] Training [3/16] Loss: 0.00294 +Epoch [3300/4000] Training [4/16] Loss: 0.00186 +Epoch [3300/4000] Training [5/16] Loss: 0.00250 +Epoch [3300/4000] Training [6/16] Loss: 0.00236 +Epoch [3300/4000] Training [7/16] Loss: 0.00267 +Epoch [3300/4000] Training [8/16] Loss: 0.00422 +Epoch [3300/4000] Training [9/16] Loss: 0.00240 +Epoch [3300/4000] Training [10/16] Loss: 0.00222 +Epoch [3300/4000] Training [11/16] Loss: 0.00430 +Epoch [3300/4000] Training [12/16] Loss: 0.00333 +Epoch [3300/4000] Training [13/16] Loss: 0.00271 +Epoch [3300/4000] Training [14/16] Loss: 0.00323 +Epoch [3300/4000] Training [15/16] Loss: 0.00221 +Epoch [3300/4000] Training [16/16] Loss: 0.00233 +Epoch [3300/4000] Training metric {'Train/mean dice_metric': 0.9985437393188477, 'Train/mean miou_metric': 0.9968132376670837, 'Train/mean f1': 0.9935852289199829, 'Train/mean precision': 0.9890427589416504, 'Train/mean recall': 0.9981696605682373, 'Train/mean hd95_metric': 0.6631135940551758} +Epoch [3300/4000] Validation [1/4] Loss: 0.41970 focal_loss 0.35647 dice_loss 0.06323 +Epoch [3300/4000] Validation [2/4] Loss: 0.90803 focal_loss 0.71408 dice_loss 0.19396 +Epoch [3300/4000] Validation [3/4] Loss: 0.53706 focal_loss 0.44527 dice_loss 0.09179 +Epoch [3300/4000] Validation [4/4] Loss: 0.33245 focal_loss 0.24165 dice_loss 0.09080 +Epoch [3300/4000] Validation metric {'Val/mean dice_metric': 0.9725742340087891, 'Val/mean miou_metric': 0.9590315818786621, 'Val/mean f1': 0.975849449634552, 'Val/mean precision': 0.9729657173156738, 'Val/mean recall': 0.9787504076957703, 'Val/mean hd95_metric': 5.275803565979004} +Cheakpoint... +Epoch [3300/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725742340087891, 'Val/mean miou_metric': 0.9590315818786621, 'Val/mean f1': 0.975849449634552, 'Val/mean precision': 0.9729657173156738, 'Val/mean recall': 0.9787504076957703, 'Val/mean hd95_metric': 5.275803565979004} +Epoch [3301/4000] Training [1/16] Loss: 0.00221 +Epoch [3301/4000] Training [2/16] Loss: 0.00274 +Epoch [3301/4000] Training [3/16] Loss: 0.00278 +Epoch [3301/4000] Training [4/16] Loss: 0.00385 +Epoch [3301/4000] Training [5/16] Loss: 0.00330 +Epoch [3301/4000] Training [6/16] Loss: 0.00258 +Epoch [3301/4000] Training [7/16] Loss: 0.00226 +Epoch [3301/4000] Training [8/16] Loss: 0.00500 +Epoch [3301/4000] Training [9/16] Loss: 0.00247 +Epoch [3301/4000] Training [10/16] Loss: 0.00224 +Epoch [3301/4000] Training [11/16] Loss: 0.00252 +Epoch [3301/4000] Training [12/16] Loss: 0.00204 +Epoch [3301/4000] Training [13/16] Loss: 0.00174 +Epoch [3301/4000] Training [14/16] Loss: 0.00276 +Epoch [3301/4000] Training [15/16] Loss: 0.00325 +Epoch [3301/4000] Training [16/16] Loss: 0.00199 +Epoch [3301/4000] Training metric {'Train/mean dice_metric': 0.9986078143119812, 'Train/mean miou_metric': 0.9969342947006226, 'Train/mean f1': 0.9935135841369629, 'Train/mean precision': 0.9888764023780823, 'Train/mean recall': 0.9981945157051086, 'Train/mean hd95_metric': 0.5921354293823242} +Epoch [3301/4000] Validation [1/4] Loss: 0.44787 focal_loss 0.38481 dice_loss 0.06306 +Epoch [3301/4000] Validation [2/4] Loss: 1.36227 focal_loss 1.11100 dice_loss 0.25127 +Epoch [3301/4000] Validation [3/4] Loss: 0.54233 focal_loss 0.44557 dice_loss 0.09677 +Epoch [3301/4000] Validation [4/4] Loss: 0.34330 focal_loss 0.24088 dice_loss 0.10242 +Epoch [3301/4000] Validation metric {'Val/mean dice_metric': 0.973162829875946, 'Val/mean miou_metric': 0.9591692090034485, 'Val/mean f1': 0.9759128093719482, 'Val/mean precision': 0.9718738198280334, 'Val/mean recall': 0.9799854755401611, 'Val/mean hd95_metric': 5.23653507232666} +Cheakpoint... +Epoch [3301/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973162829875946, 'Val/mean miou_metric': 0.9591692090034485, 'Val/mean f1': 0.9759128093719482, 'Val/mean precision': 0.9718738198280334, 'Val/mean recall': 0.9799854755401611, 'Val/mean hd95_metric': 5.23653507232666} +Epoch [3302/4000] Training [1/16] Loss: 0.00208 +Epoch [3302/4000] Training [2/16] Loss: 0.00224 +Epoch [3302/4000] Training [3/16] Loss: 0.00225 +Epoch [3302/4000] Training [4/16] Loss: 0.00352 +Epoch [3302/4000] Training [5/16] Loss: 0.00418 +Epoch [3302/4000] Training [6/16] Loss: 0.00376 +Epoch [3302/4000] Training [7/16] Loss: 0.00263 +Epoch [3302/4000] Training [8/16] Loss: 0.00225 +Epoch [3302/4000] Training [9/16] Loss: 0.00369 +Epoch [3302/4000] Training [10/16] Loss: 0.00221 +Epoch [3302/4000] Training [11/16] Loss: 0.00247 +Epoch [3302/4000] Training [12/16] Loss: 0.00220 +Epoch [3302/4000] Training [13/16] Loss: 0.00266 +Epoch [3302/4000] Training [14/16] Loss: 0.00274 +Epoch [3302/4000] Training [15/16] Loss: 0.00353 +Epoch [3302/4000] Training [16/16] Loss: 0.00283 +Epoch [3302/4000] Training metric {'Train/mean dice_metric': 0.9984438419342041, 'Train/mean miou_metric': 0.9966186285018921, 'Train/mean f1': 0.9935622811317444, 'Train/mean precision': 0.9890769720077515, 'Train/mean recall': 0.9980884790420532, 'Train/mean hd95_metric': 0.6619694232940674} +Epoch [3302/4000] Validation [1/4] Loss: 0.35585 focal_loss 0.29419 dice_loss 0.06166 +Epoch [3302/4000] Validation [2/4] Loss: 0.52338 focal_loss 0.38504 dice_loss 0.13834 +Epoch [3302/4000] Validation [3/4] Loss: 0.52905 focal_loss 0.43889 dice_loss 0.09017 +Epoch [3302/4000] Validation [4/4] Loss: 0.43081 focal_loss 0.31690 dice_loss 0.11391 +Epoch [3302/4000] Validation metric {'Val/mean dice_metric': 0.9755646586418152, 'Val/mean miou_metric': 0.9610608816146851, 'Val/mean f1': 0.9764699935913086, 'Val/mean precision': 0.9734013676643372, 'Val/mean recall': 0.979557991027832, 'Val/mean hd95_metric': 4.901341915130615} +Cheakpoint... +Epoch [3302/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755646586418152, 'Val/mean miou_metric': 0.9610608816146851, 'Val/mean f1': 0.9764699935913086, 'Val/mean precision': 0.9734013676643372, 'Val/mean recall': 0.979557991027832, 'Val/mean hd95_metric': 4.901341915130615} +Epoch [3303/4000] Training [1/16] Loss: 0.00182 +Epoch [3303/4000] Training [2/16] Loss: 0.00214 +Epoch [3303/4000] Training [3/16] Loss: 0.00184 +Epoch [3303/4000] Training [4/16] Loss: 0.00278 +Epoch [3303/4000] Training [5/16] Loss: 0.00265 +Epoch [3303/4000] Training [6/16] Loss: 0.00229 +Epoch [3303/4000] Training [7/16] Loss: 0.00321 +Epoch [3303/4000] Training [8/16] Loss: 0.00258 +Epoch [3303/4000] Training [9/16] Loss: 0.00228 +Epoch [3303/4000] Training [10/16] Loss: 0.00228 +Epoch [3303/4000] Training [11/16] Loss: 0.00286 +Epoch [3303/4000] Training [12/16] Loss: 0.00229 +Epoch [3303/4000] Training [13/16] Loss: 0.00222 +Epoch [3303/4000] Training [14/16] Loss: 0.00398 +Epoch [3303/4000] Training [15/16] Loss: 0.00375 +Epoch [3303/4000] Training [16/16] Loss: 0.00240 +Epoch [3303/4000] Training metric {'Train/mean dice_metric': 0.9987112283706665, 'Train/mean miou_metric': 0.9971501231193542, 'Train/mean f1': 0.9937257170677185, 'Train/mean precision': 0.9891510009765625, 'Train/mean recall': 0.9983429312705994, 'Train/mean hd95_metric': 0.5687776803970337} +Epoch [3303/4000] Validation [1/4] Loss: 0.32470 focal_loss 0.26375 dice_loss 0.06096 +Epoch [3303/4000] Validation [2/4] Loss: 0.43293 focal_loss 0.32920 dice_loss 0.10373 +Epoch [3303/4000] Validation [3/4] Loss: 0.55831 focal_loss 0.46296 dice_loss 0.09535 +Epoch [3303/4000] Validation [4/4] Loss: 0.36941 focal_loss 0.27247 dice_loss 0.09693 +Epoch [3303/4000] Validation metric {'Val/mean dice_metric': 0.9747616052627563, 'Val/mean miou_metric': 0.9609342813491821, 'Val/mean f1': 0.9760338664054871, 'Val/mean precision': 0.9721944332122803, 'Val/mean recall': 0.9799038171768188, 'Val/mean hd95_metric': 5.184810161590576} +Cheakpoint... +Epoch [3303/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747616052627563, 'Val/mean miou_metric': 0.9609342813491821, 'Val/mean f1': 0.9760338664054871, 'Val/mean precision': 0.9721944332122803, 'Val/mean recall': 0.9799038171768188, 'Val/mean hd95_metric': 5.184810161590576} +Epoch [3304/4000] Training [1/16] Loss: 0.00294 +Epoch [3304/4000] Training [2/16] Loss: 0.00234 +Epoch [3304/4000] Training [3/16] Loss: 0.00322 +Epoch [3304/4000] Training [4/16] Loss: 0.00267 +Epoch [3304/4000] Training [5/16] Loss: 0.00357 +Epoch [3304/4000] Training [6/16] Loss: 0.00302 +Epoch [3304/4000] Training [7/16] Loss: 0.00246 +Epoch [3304/4000] Training [8/16] Loss: 0.00356 +Epoch [3304/4000] Training [9/16] Loss: 0.00298 +Epoch [3304/4000] Training [10/16] Loss: 0.00244 +Epoch [3304/4000] Training [11/16] Loss: 0.00332 +Epoch [3304/4000] Training [12/16] Loss: 0.00242 +Epoch [3304/4000] Training [13/16] Loss: 0.00389 +Epoch [3304/4000] Training [14/16] Loss: 0.00397 +Epoch [3304/4000] Training [15/16] Loss: 0.00429 +Epoch [3304/4000] Training [16/16] Loss: 0.00190 +Epoch [3304/4000] Training metric {'Train/mean dice_metric': 0.9984678030014038, 'Train/mean miou_metric': 0.9966641068458557, 'Train/mean f1': 0.9935563206672668, 'Train/mean precision': 0.9890137910842896, 'Train/mean recall': 0.9981407523155212, 'Train/mean hd95_metric': 0.6491763591766357} +Epoch [3304/4000] Validation [1/4] Loss: 0.36974 focal_loss 0.30829 dice_loss 0.06145 +Epoch [3304/4000] Validation [2/4] Loss: 0.43226 focal_loss 0.32924 dice_loss 0.10302 +Epoch [3304/4000] Validation [3/4] Loss: 0.51806 focal_loss 0.42883 dice_loss 0.08923 +Epoch [3304/4000] Validation [4/4] Loss: 0.34083 focal_loss 0.24921 dice_loss 0.09161 +Epoch [3304/4000] Validation metric {'Val/mean dice_metric': 0.9749770164489746, 'Val/mean miou_metric': 0.9608191251754761, 'Val/mean f1': 0.9765723943710327, 'Val/mean precision': 0.9740151166915894, 'Val/mean recall': 0.9791430830955505, 'Val/mean hd95_metric': 4.842519283294678} +Cheakpoint... +Epoch [3304/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749770164489746, 'Val/mean miou_metric': 0.9608191251754761, 'Val/mean f1': 0.9765723943710327, 'Val/mean precision': 0.9740151166915894, 'Val/mean recall': 0.9791430830955505, 'Val/mean hd95_metric': 4.842519283294678} +Epoch [3305/4000] Training [1/16] Loss: 0.00230 +Epoch [3305/4000] Training [2/16] Loss: 0.00309 +Epoch [3305/4000] Training [3/16] Loss: 0.00235 +Epoch [3305/4000] Training [4/16] Loss: 0.00311 +Epoch [3305/4000] Training [5/16] Loss: 0.00311 +Epoch [3305/4000] Training [6/16] Loss: 0.00242 +Epoch [3305/4000] Training [7/16] Loss: 0.00366 +Epoch [3305/4000] Training [8/16] Loss: 0.00424 +Epoch [3305/4000] Training [9/16] Loss: 0.00363 +Epoch [3305/4000] Training [10/16] Loss: 0.00214 +Epoch [3305/4000] Training [11/16] Loss: 0.00332 +Epoch [3305/4000] Training [12/16] Loss: 0.00381 +Epoch [3305/4000] Training [13/16] Loss: 0.00378 +Epoch [3305/4000] Training [14/16] Loss: 0.00381 +Epoch [3305/4000] Training [15/16] Loss: 0.00184 +Epoch [3305/4000] Training [16/16] Loss: 0.00405 +Epoch [3305/4000] Training metric {'Train/mean dice_metric': 0.998501718044281, 'Train/mean miou_metric': 0.996735692024231, 'Train/mean f1': 0.9936097860336304, 'Train/mean precision': 0.9890787601470947, 'Train/mean recall': 0.9981825351715088, 'Train/mean hd95_metric': 0.6225429773330688} +Epoch [3305/4000] Validation [1/4] Loss: 0.41046 focal_loss 0.34678 dice_loss 0.06368 +Epoch [3305/4000] Validation [2/4] Loss: 0.44192 focal_loss 0.33842 dice_loss 0.10350 +Epoch [3305/4000] Validation [3/4] Loss: 0.31545 focal_loss 0.24440 dice_loss 0.07106 +Epoch [3305/4000] Validation [4/4] Loss: 0.49519 focal_loss 0.36748 dice_loss 0.12771 +Epoch [3305/4000] Validation metric {'Val/mean dice_metric': 0.9746016263961792, 'Val/mean miou_metric': 0.960473895072937, 'Val/mean f1': 0.9765450954437256, 'Val/mean precision': 0.9745157361030579, 'Val/mean recall': 0.9785829186439514, 'Val/mean hd95_metric': 4.899564743041992} +Cheakpoint... +Epoch [3305/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746016263961792, 'Val/mean miou_metric': 0.960473895072937, 'Val/mean f1': 0.9765450954437256, 'Val/mean precision': 0.9745157361030579, 'Val/mean recall': 0.9785829186439514, 'Val/mean hd95_metric': 4.899564743041992} +Epoch [3306/4000] Training [1/16] Loss: 0.00215 +Epoch [3306/4000] Training [2/16] Loss: 0.00308 +Epoch [3306/4000] Training [3/16] Loss: 0.00183 +Epoch [3306/4000] Training [4/16] Loss: 0.00926 +Epoch [3306/4000] Training [5/16] Loss: 0.00260 +Epoch [3306/4000] Training [6/16] Loss: 0.00246 +Epoch [3306/4000] Training [7/16] Loss: 0.00235 +Epoch [3306/4000] Training [8/16] Loss: 0.00248 +Epoch [3306/4000] Training [9/16] Loss: 0.00218 +Epoch [3306/4000] Training [10/16] Loss: 0.00232 +Epoch [3306/4000] Training [11/16] Loss: 0.00537 +Epoch [3306/4000] Training [12/16] Loss: 0.00260 +Epoch [3306/4000] Training [13/16] Loss: 0.00310 +Epoch [3306/4000] Training [14/16] Loss: 0.00270 +Epoch [3306/4000] Training [15/16] Loss: 0.00241 +Epoch [3306/4000] Training [16/16] Loss: 0.00257 +Epoch [3306/4000] Training metric {'Train/mean dice_metric': 0.9984603524208069, 'Train/mean miou_metric': 0.9966564178466797, 'Train/mean f1': 0.9936544895172119, 'Train/mean precision': 0.98923259973526, 'Train/mean recall': 0.998116135597229, 'Train/mean hd95_metric': 0.6694890260696411} +Epoch [3306/4000] Validation [1/4] Loss: 0.39836 focal_loss 0.33419 dice_loss 0.06417 +Epoch [3306/4000] Validation [2/4] Loss: 0.83027 focal_loss 0.64851 dice_loss 0.18176 +Epoch [3306/4000] Validation [3/4] Loss: 0.25332 focal_loss 0.19213 dice_loss 0.06119 +Epoch [3306/4000] Validation [4/4] Loss: 0.43250 focal_loss 0.31774 dice_loss 0.11477 +Epoch [3306/4000] Validation metric {'Val/mean dice_metric': 0.9732343554496765, 'Val/mean miou_metric': 0.9588035345077515, 'Val/mean f1': 0.9762179851531982, 'Val/mean precision': 0.9729642271995544, 'Val/mean recall': 0.9794935584068298, 'Val/mean hd95_metric': 5.040574073791504} +Cheakpoint... +Epoch [3306/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732343554496765, 'Val/mean miou_metric': 0.9588035345077515, 'Val/mean f1': 0.9762179851531982, 'Val/mean precision': 0.9729642271995544, 'Val/mean recall': 0.9794935584068298, 'Val/mean hd95_metric': 5.040574073791504} +Epoch [3307/4000] Training [1/16] Loss: 0.00419 +Epoch [3307/4000] Training [2/16] Loss: 0.00284 +Epoch [3307/4000] Training [3/16] Loss: 0.00225 +Epoch [3307/4000] Training [4/16] Loss: 0.00265 +Epoch [3307/4000] Training [5/16] Loss: 0.00241 +Epoch [3307/4000] Training [6/16] Loss: 0.00248 +Epoch [3307/4000] Training [7/16] Loss: 0.00258 +Epoch [3307/4000] Training [8/16] Loss: 0.00308 +Epoch [3307/4000] Training [9/16] Loss: 0.00351 +Epoch [3307/4000] Training [10/16] Loss: 0.00212 +Epoch [3307/4000] Training [11/16] Loss: 0.00232 +Epoch [3307/4000] Training [12/16] Loss: 0.00321 +Epoch [3307/4000] Training [13/16] Loss: 0.00227 +Epoch [3307/4000] Training [14/16] Loss: 0.00351 +Epoch [3307/4000] Training [15/16] Loss: 0.00217 +Epoch [3307/4000] Training [16/16] Loss: 0.00285 +Epoch [3307/4000] Training metric {'Train/mean dice_metric': 0.9985611438751221, 'Train/mean miou_metric': 0.996811032295227, 'Train/mean f1': 0.9927677512168884, 'Train/mean precision': 0.9874842762947083, 'Train/mean recall': 0.9981080293655396, 'Train/mean hd95_metric': 0.636062741279602} +Epoch [3307/4000] Validation [1/4] Loss: 0.45634 focal_loss 0.38519 dice_loss 0.07116 +Epoch [3307/4000] Validation [2/4] Loss: 0.97158 focal_loss 0.74986 dice_loss 0.22172 +Epoch [3307/4000] Validation [3/4] Loss: 0.52368 focal_loss 0.43472 dice_loss 0.08895 +Epoch [3307/4000] Validation [4/4] Loss: 0.33755 focal_loss 0.22914 dice_loss 0.10840 +Epoch [3307/4000] Validation metric {'Val/mean dice_metric': 0.9729318618774414, 'Val/mean miou_metric': 0.9584291577339172, 'Val/mean f1': 0.9750978946685791, 'Val/mean precision': 0.9722591638565063, 'Val/mean recall': 0.9779531955718994, 'Val/mean hd95_metric': 5.0029401779174805} +Cheakpoint... +Epoch [3307/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729318618774414, 'Val/mean miou_metric': 0.9584291577339172, 'Val/mean f1': 0.9750978946685791, 'Val/mean precision': 0.9722591638565063, 'Val/mean recall': 0.9779531955718994, 'Val/mean hd95_metric': 5.0029401779174805} +Epoch [3308/4000] Training [1/16] Loss: 0.00204 +Epoch [3308/4000] Training [2/16] Loss: 0.00244 +Epoch [3308/4000] Training [3/16] Loss: 0.00259 +Epoch [3308/4000] Training [4/16] Loss: 0.00314 +Epoch [3308/4000] Training [5/16] Loss: 0.00369 +Epoch [3308/4000] Training [6/16] Loss: 0.00310 +Epoch [3308/4000] Training [7/16] Loss: 0.00179 +Epoch [3308/4000] Training [8/16] Loss: 0.00312 +Epoch [3308/4000] Training [9/16] Loss: 0.00256 +Epoch [3308/4000] Training [10/16] Loss: 0.00303 +Epoch [3308/4000] Training [11/16] Loss: 0.00209 +Epoch [3308/4000] Training [12/16] Loss: 0.00189 +Epoch [3308/4000] Training [13/16] Loss: 0.00722 +Epoch [3308/4000] Training [14/16] Loss: 0.00243 +Epoch [3308/4000] Training [15/16] Loss: 0.00146 +Epoch [3308/4000] Training [16/16] Loss: 0.00336 +Epoch [3308/4000] Training metric {'Train/mean dice_metric': 0.9986699819564819, 'Train/mean miou_metric': 0.9970656633377075, 'Train/mean f1': 0.993617594242096, 'Train/mean precision': 0.9890105724334717, 'Train/mean recall': 0.9982677698135376, 'Train/mean hd95_metric': 0.5691260099411011} +Epoch [3308/4000] Validation [1/4] Loss: 0.34721 focal_loss 0.28525 dice_loss 0.06196 +Epoch [3308/4000] Validation [2/4] Loss: 0.46858 focal_loss 0.35373 dice_loss 0.11485 +Epoch [3308/4000] Validation [3/4] Loss: 0.47463 focal_loss 0.37829 dice_loss 0.09634 +Epoch [3308/4000] Validation [4/4] Loss: 0.27169 focal_loss 0.18469 dice_loss 0.08700 +Epoch [3308/4000] Validation metric {'Val/mean dice_metric': 0.9757657051086426, 'Val/mean miou_metric': 0.9616317749023438, 'Val/mean f1': 0.9762698411941528, 'Val/mean precision': 0.9726906418800354, 'Val/mean recall': 0.9798754453659058, 'Val/mean hd95_metric': 4.841719627380371} +Cheakpoint... +Epoch [3308/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9757657051086426, 'Val/mean miou_metric': 0.9616317749023438, 'Val/mean f1': 0.9762698411941528, 'Val/mean precision': 0.9726906418800354, 'Val/mean recall': 0.9798754453659058, 'Val/mean hd95_metric': 4.841719627380371} +Epoch [3309/4000] Training [1/16] Loss: 0.00268 +Epoch [3309/4000] Training [2/16] Loss: 0.00211 +Epoch [3309/4000] Training [3/16] Loss: 0.00197 +Epoch [3309/4000] Training [4/16] Loss: 0.00228 +Epoch [3309/4000] Training [5/16] Loss: 0.00364 +Epoch [3309/4000] Training [6/16] Loss: 0.00304 +Epoch [3309/4000] Training [7/16] Loss: 0.00230 +Epoch [3309/4000] Training [8/16] Loss: 0.00291 +Epoch [3309/4000] Training [9/16] Loss: 0.00292 +Epoch [3309/4000] Training [10/16] Loss: 0.00210 +Epoch [3309/4000] Training [11/16] Loss: 0.00192 +Epoch [3309/4000] Training [12/16] Loss: 0.00428 +Epoch [3309/4000] Training [13/16] Loss: 0.00447 +Epoch [3309/4000] Training [14/16] Loss: 0.00197 +Epoch [3309/4000] Training [15/16] Loss: 0.00247 +Epoch [3309/4000] Training [16/16] Loss: 0.00358 +Epoch [3309/4000] Training metric {'Train/mean dice_metric': 0.9986663460731506, 'Train/mean miou_metric': 0.9970439672470093, 'Train/mean f1': 0.9936054944992065, 'Train/mean precision': 0.9889587163925171, 'Train/mean recall': 0.9982962012290955, 'Train/mean hd95_metric': 0.5824494361877441} +Epoch [3309/4000] Validation [1/4] Loss: 0.32557 focal_loss 0.26587 dice_loss 0.05970 +Epoch [3309/4000] Validation [2/4] Loss: 0.39449 focal_loss 0.29331 dice_loss 0.10118 +Epoch [3309/4000] Validation [3/4] Loss: 0.49381 focal_loss 0.40491 dice_loss 0.08891 +Epoch [3309/4000] Validation [4/4] Loss: 0.44119 focal_loss 0.32973 dice_loss 0.11146 +Epoch [3309/4000] Validation metric {'Val/mean dice_metric': 0.9752529263496399, 'Val/mean miou_metric': 0.9614102244377136, 'Val/mean f1': 0.977036714553833, 'Val/mean precision': 0.9742250442504883, 'Val/mean recall': 0.9798645377159119, 'Val/mean hd95_metric': 4.574669361114502} +Cheakpoint... +Epoch [3309/4000] best acc:tensor([0.9767], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752529263496399, 'Val/mean miou_metric': 0.9614102244377136, 'Val/mean f1': 0.977036714553833, 'Val/mean precision': 0.9742250442504883, 'Val/mean recall': 0.9798645377159119, 'Val/mean hd95_metric': 4.574669361114502} +Epoch [3310/4000] Training [1/16] Loss: 0.00253 +Epoch [3310/4000] Training [2/16] Loss: 0.00317 +Epoch [3310/4000] Training [3/16] Loss: 0.00283 +Epoch [3310/4000] Training [4/16] Loss: 0.00396 +Epoch [3310/4000] Training [5/16] Loss: 0.00248 +Epoch [3310/4000] Training [6/16] Loss: 0.00312 +Epoch [3310/4000] Training [7/16] Loss: 0.00282 +Epoch [3310/4000] Training [8/16] Loss: 0.00296 +Epoch [3310/4000] Training [9/16] Loss: 0.00265 +Epoch [3310/4000] Training [10/16] Loss: 0.00225 +Epoch [3310/4000] Training [11/16] Loss: 0.00255 +Epoch [3310/4000] Training [12/16] Loss: 0.00223 +Epoch [3310/4000] Training [13/16] Loss: 0.00219 +Epoch [3310/4000] Training [14/16] Loss: 0.00314 +Epoch [3310/4000] Training [15/16] Loss: 0.00191 +Epoch [3310/4000] Training [16/16] Loss: 0.00235 +Epoch [3310/4000] Training metric {'Train/mean dice_metric': 0.9985007047653198, 'Train/mean miou_metric': 0.9967319965362549, 'Train/mean f1': 0.9936851859092712, 'Train/mean precision': 0.9892280697822571, 'Train/mean recall': 0.9981826543807983, 'Train/mean hd95_metric': 0.6733673810958862} +Epoch [3310/4000] Validation [1/4] Loss: 0.38076 focal_loss 0.31862 dice_loss 0.06214 +Epoch [3310/4000] Validation [2/4] Loss: 0.44009 focal_loss 0.32797 dice_loss 0.11212 +Epoch [3310/4000] Validation [3/4] Loss: 0.53207 focal_loss 0.44066 dice_loss 0.09141 +Epoch [3310/4000] Validation [4/4] Loss: 0.33242 focal_loss 0.23874 dice_loss 0.09368 +Epoch [3310/4000] Validation metric {'Val/mean dice_metric': 0.9769495129585266, 'Val/mean miou_metric': 0.9624082446098328, 'Val/mean f1': 0.9768404960632324, 'Val/mean precision': 0.9728416204452515, 'Val/mean recall': 0.9808723330497742, 'Val/mean hd95_metric': 5.022289276123047} +Cheakpoint... +Epoch [3310/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9769], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9769495129585266, 'Val/mean miou_metric': 0.9624082446098328, 'Val/mean f1': 0.9768404960632324, 'Val/mean precision': 0.9728416204452515, 'Val/mean recall': 0.9808723330497742, 'Val/mean hd95_metric': 5.022289276123047} +Epoch [3311/4000] Training [1/16] Loss: 0.00256 +Epoch [3311/4000] Training [2/16] Loss: 0.00253 +Epoch [3311/4000] Training [3/16] Loss: 0.00240 +Epoch [3311/4000] Training [4/16] Loss: 0.00265 +Epoch [3311/4000] Training [5/16] Loss: 0.00331 +Epoch [3311/4000] Training [6/16] Loss: 0.00282 +Epoch [3311/4000] Training [7/16] Loss: 0.00223 +Epoch [3311/4000] Training [8/16] Loss: 0.00238 +Epoch [3311/4000] Training [9/16] Loss: 0.00291 +Epoch [3311/4000] Training [10/16] Loss: 0.00268 +Epoch [3311/4000] Training [11/16] Loss: 0.00208 +Epoch [3311/4000] Training [12/16] Loss: 0.00359 +Epoch [3311/4000] Training [13/16] Loss: 0.00482 +Epoch [3311/4000] Training [14/16] Loss: 0.00291 +Epoch [3311/4000] Training [15/16] Loss: 0.00344 +Epoch [3311/4000] Training [16/16] Loss: 0.00211 +Epoch [3311/4000] Training metric {'Train/mean dice_metric': 0.9984853267669678, 'Train/mean miou_metric': 0.9967015981674194, 'Train/mean f1': 0.993563711643219, 'Train/mean precision': 0.9890428781509399, 'Train/mean recall': 0.9981260299682617, 'Train/mean hd95_metric': 0.6478790640830994} +Epoch [3311/4000] Validation [1/4] Loss: 0.42963 focal_loss 0.36608 dice_loss 0.06355 +Epoch [3311/4000] Validation [2/4] Loss: 0.52942 focal_loss 0.38758 dice_loss 0.14184 +Epoch [3311/4000] Validation [3/4] Loss: 0.52156 focal_loss 0.43284 dice_loss 0.08872 +Epoch [3311/4000] Validation [4/4] Loss: 0.37804 focal_loss 0.27014 dice_loss 0.10790 +Epoch [3311/4000] Validation metric {'Val/mean dice_metric': 0.974541187286377, 'Val/mean miou_metric': 0.960364043712616, 'Val/mean f1': 0.9762916564941406, 'Val/mean precision': 0.9730938673019409, 'Val/mean recall': 0.9795103669166565, 'Val/mean hd95_metric': 5.031498908996582} +Cheakpoint... +Epoch [3311/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974541187286377, 'Val/mean miou_metric': 0.960364043712616, 'Val/mean f1': 0.9762916564941406, 'Val/mean precision': 0.9730938673019409, 'Val/mean recall': 0.9795103669166565, 'Val/mean hd95_metric': 5.031498908996582} +Epoch [3312/4000] Training [1/16] Loss: 0.00425 +Epoch [3312/4000] Training [2/16] Loss: 0.00383 +Epoch [3312/4000] Training [3/16] Loss: 0.00333 +Epoch [3312/4000] Training [4/16] Loss: 0.00368 +Epoch [3312/4000] Training [5/16] Loss: 0.00391 +Epoch [3312/4000] Training [6/16] Loss: 0.00251 +Epoch [3312/4000] Training [7/16] Loss: 0.00238 +Epoch [3312/4000] Training [8/16] Loss: 0.00280 +Epoch [3312/4000] Training [9/16] Loss: 0.00252 +Epoch [3312/4000] Training [10/16] Loss: 0.00310 +Epoch [3312/4000] Training [11/16] Loss: 0.00221 +Epoch [3312/4000] Training [12/16] Loss: 0.00184 +Epoch [3312/4000] Training [13/16] Loss: 0.00313 +Epoch [3312/4000] Training [14/16] Loss: 0.00544 +Epoch [3312/4000] Training [15/16] Loss: 0.00343 +Epoch [3312/4000] Training [16/16] Loss: 0.00283 +Epoch [3312/4000] Training metric {'Train/mean dice_metric': 0.9983381628990173, 'Train/mean miou_metric': 0.9963717460632324, 'Train/mean f1': 0.9926354885101318, 'Train/mean precision': 0.9873437285423279, 'Train/mean recall': 0.9979842305183411, 'Train/mean hd95_metric': 0.694168210029602} +Epoch [3312/4000] Validation [1/4] Loss: 0.48671 focal_loss 0.42092 dice_loss 0.06579 +Epoch [3312/4000] Validation [2/4] Loss: 0.42928 focal_loss 0.32203 dice_loss 0.10725 +Epoch [3312/4000] Validation [3/4] Loss: 0.53618 focal_loss 0.44069 dice_loss 0.09548 +Epoch [3312/4000] Validation [4/4] Loss: 0.34520 focal_loss 0.24692 dice_loss 0.09828 +Epoch [3312/4000] Validation metric {'Val/mean dice_metric': 0.9747130274772644, 'Val/mean miou_metric': 0.9603496789932251, 'Val/mean f1': 0.9757279753684998, 'Val/mean precision': 0.971502423286438, 'Val/mean recall': 0.9799904227256775, 'Val/mean hd95_metric': 4.996034622192383} +Cheakpoint... +Epoch [3312/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747130274772644, 'Val/mean miou_metric': 0.9603496789932251, 'Val/mean f1': 0.9757279753684998, 'Val/mean precision': 0.971502423286438, 'Val/mean recall': 0.9799904227256775, 'Val/mean hd95_metric': 4.996034622192383} +Epoch [3313/4000] Training [1/16] Loss: 0.00296 +Epoch [3313/4000] Training [2/16] Loss: 0.00220 +Epoch [3313/4000] Training [3/16] Loss: 0.00233 +Epoch [3313/4000] Training [4/16] Loss: 0.00319 +Epoch [3313/4000] Training [5/16] Loss: 0.00271 +Epoch [3313/4000] Training [6/16] Loss: 0.00241 +Epoch [3313/4000] Training [7/16] Loss: 0.00242 +Epoch [3313/4000] Training [8/16] Loss: 0.00401 +Epoch [3313/4000] Training [9/16] Loss: 0.00262 +Epoch [3313/4000] Training [10/16] Loss: 0.00243 +Epoch [3313/4000] Training [11/16] Loss: 0.00338 +Epoch [3313/4000] Training [12/16] Loss: 0.00323 +Epoch [3313/4000] Training [13/16] Loss: 0.00285 +Epoch [3313/4000] Training [14/16] Loss: 0.00221 +Epoch [3313/4000] Training [15/16] Loss: 0.00339 +Epoch [3313/4000] Training [16/16] Loss: 0.00293 +Epoch [3313/4000] Training metric {'Train/mean dice_metric': 0.9985021948814392, 'Train/mean miou_metric': 0.996731698513031, 'Train/mean f1': 0.9935182332992554, 'Train/mean precision': 0.9889744520187378, 'Train/mean recall': 0.9981039762496948, 'Train/mean hd95_metric': 0.6917742490768433} +Epoch [3313/4000] Validation [1/4] Loss: 0.37828 focal_loss 0.31763 dice_loss 0.06065 +Epoch [3313/4000] Validation [2/4] Loss: 0.39063 focal_loss 0.29003 dice_loss 0.10060 +Epoch [3313/4000] Validation [3/4] Loss: 0.54765 focal_loss 0.45186 dice_loss 0.09579 +Epoch [3313/4000] Validation [4/4] Loss: 0.42100 focal_loss 0.30240 dice_loss 0.11859 +Epoch [3313/4000] Validation metric {'Val/mean dice_metric': 0.9729186296463013, 'Val/mean miou_metric': 0.9590023756027222, 'Val/mean f1': 0.9757921695709229, 'Val/mean precision': 0.9727001786231995, 'Val/mean recall': 0.9789038300514221, 'Val/mean hd95_metric': 5.631976127624512} +Cheakpoint... +Epoch [3313/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729186296463013, 'Val/mean miou_metric': 0.9590023756027222, 'Val/mean f1': 0.9757921695709229, 'Val/mean precision': 0.9727001786231995, 'Val/mean recall': 0.9789038300514221, 'Val/mean hd95_metric': 5.631976127624512} +Epoch [3314/4000] Training [1/16] Loss: 0.00245 +Epoch [3314/4000] Training [2/16] Loss: 0.00246 +Epoch [3314/4000] Training [3/16] Loss: 0.00276 +Epoch [3314/4000] Training [4/16] Loss: 0.00233 +Epoch [3314/4000] Training [5/16] Loss: 0.00428 +Epoch [3314/4000] Training [6/16] Loss: 0.00294 +Epoch [3314/4000] Training [7/16] Loss: 0.00205 +Epoch [3314/4000] Training [8/16] Loss: 0.00315 +Epoch [3314/4000] Training [9/16] Loss: 0.00343 +Epoch [3314/4000] Training [10/16] Loss: 0.00209 +Epoch [3314/4000] Training [11/16] Loss: 0.00380 +Epoch [3314/4000] Training [12/16] Loss: 0.00228 +Epoch [3314/4000] Training [13/16] Loss: 0.00251 +Epoch [3314/4000] Training [14/16] Loss: 0.00250 +Epoch [3314/4000] Training [15/16] Loss: 0.00290 +Epoch [3314/4000] Training [16/16] Loss: 0.00364 +Epoch [3314/4000] Training metric {'Train/mean dice_metric': 0.9984538555145264, 'Train/mean miou_metric': 0.9966138601303101, 'Train/mean f1': 0.9932876229286194, 'Train/mean precision': 0.9885146617889404, 'Train/mean recall': 0.9981067776679993, 'Train/mean hd95_metric': 0.6470001935958862} +Epoch [3314/4000] Validation [1/4] Loss: 0.39797 focal_loss 0.33523 dice_loss 0.06274 +Epoch [3314/4000] Validation [2/4] Loss: 0.46380 focal_loss 0.35011 dice_loss 0.11368 +Epoch [3314/4000] Validation [3/4] Loss: 0.55259 focal_loss 0.45419 dice_loss 0.09840 +Epoch [3314/4000] Validation [4/4] Loss: 0.36805 focal_loss 0.26337 dice_loss 0.10467 +Epoch [3314/4000] Validation metric {'Val/mean dice_metric': 0.9733628034591675, 'Val/mean miou_metric': 0.959316074848175, 'Val/mean f1': 0.9759631752967834, 'Val/mean precision': 0.973240315914154, 'Val/mean recall': 0.9787011742591858, 'Val/mean hd95_metric': 5.175490856170654} +Cheakpoint... +Epoch [3314/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733628034591675, 'Val/mean miou_metric': 0.959316074848175, 'Val/mean f1': 0.9759631752967834, 'Val/mean precision': 0.973240315914154, 'Val/mean recall': 0.9787011742591858, 'Val/mean hd95_metric': 5.175490856170654} +Epoch [3315/4000] Training [1/16] Loss: 0.00203 +Epoch [3315/4000] Training [2/16] Loss: 0.00327 +Epoch [3315/4000] Training [3/16] Loss: 0.00213 +Epoch [3315/4000] Training [4/16] Loss: 0.00163 +Epoch [3315/4000] Training [5/16] Loss: 0.00210 +Epoch [3315/4000] Training [6/16] Loss: 0.00205 +Epoch [3315/4000] Training [7/16] Loss: 0.00324 +Epoch [3315/4000] Training [8/16] Loss: 0.00270 +Epoch [3315/4000] Training [9/16] Loss: 0.00370 +Epoch [3315/4000] Training [10/16] Loss: 0.00212 +Epoch [3315/4000] Training [11/16] Loss: 0.00220 +Epoch [3315/4000] Training [12/16] Loss: 0.00410 +Epoch [3315/4000] Training [13/16] Loss: 0.00287 +Epoch [3315/4000] Training [14/16] Loss: 0.00181 +Epoch [3315/4000] Training [15/16] Loss: 0.00305 +Epoch [3315/4000] Training [16/16] Loss: 0.00296 +Epoch [3315/4000] Training metric {'Train/mean dice_metric': 0.9985588788986206, 'Train/mean miou_metric': 0.9968469738960266, 'Train/mean f1': 0.9936922788619995, 'Train/mean precision': 0.9891329407691956, 'Train/mean recall': 0.9982938766479492, 'Train/mean hd95_metric': 0.6290320158004761} +Epoch [3315/4000] Validation [1/4] Loss: 0.37784 focal_loss 0.31792 dice_loss 0.05992 +Epoch [3315/4000] Validation [2/4] Loss: 0.55598 focal_loss 0.41171 dice_loss 0.14427 +Epoch [3315/4000] Validation [3/4] Loss: 0.56432 focal_loss 0.46770 dice_loss 0.09662 +Epoch [3315/4000] Validation [4/4] Loss: 0.34975 focal_loss 0.25539 dice_loss 0.09436 +Epoch [3315/4000] Validation metric {'Val/mean dice_metric': 0.9751434326171875, 'Val/mean miou_metric': 0.9607521891593933, 'Val/mean f1': 0.9760934710502625, 'Val/mean precision': 0.9730777144432068, 'Val/mean recall': 0.9791278839111328, 'Val/mean hd95_metric': 4.905275344848633} +Cheakpoint... +Epoch [3315/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751434326171875, 'Val/mean miou_metric': 0.9607521891593933, 'Val/mean f1': 0.9760934710502625, 'Val/mean precision': 0.9730777144432068, 'Val/mean recall': 0.9791278839111328, 'Val/mean hd95_metric': 4.905275344848633} +Epoch [3316/4000] Training [1/16] Loss: 0.00268 +Epoch [3316/4000] Training [2/16] Loss: 0.00232 +Epoch [3316/4000] Training [3/16] Loss: 0.00261 +Epoch [3316/4000] Training [4/16] Loss: 0.00174 +Epoch [3316/4000] Training [5/16] Loss: 0.00311 +Epoch [3316/4000] Training [6/16] Loss: 0.00226 +Epoch [3316/4000] Training [7/16] Loss: 0.00347 +Epoch [3316/4000] Training [8/16] Loss: 0.00252 +Epoch [3316/4000] Training [9/16] Loss: 0.00219 +Epoch [3316/4000] Training [10/16] Loss: 0.00225 +Epoch [3316/4000] Training [11/16] Loss: 0.00260 +Epoch [3316/4000] Training [12/16] Loss: 0.00233 +Epoch [3316/4000] Training [13/16] Loss: 0.00366 +Epoch [3316/4000] Training [14/16] Loss: 0.00290 +Epoch [3316/4000] Training [15/16] Loss: 0.00207 +Epoch [3316/4000] Training [16/16] Loss: 0.00323 +Epoch [3316/4000] Training metric {'Train/mean dice_metric': 0.9985617399215698, 'Train/mean miou_metric': 0.9968487024307251, 'Train/mean f1': 0.9936394095420837, 'Train/mean precision': 0.9891036152839661, 'Train/mean recall': 0.998216986656189, 'Train/mean hd95_metric': 0.6373323202133179} +Epoch [3316/4000] Validation [1/4] Loss: 0.39090 focal_loss 0.32493 dice_loss 0.06597 +Epoch [3316/4000] Validation [2/4] Loss: 0.81054 focal_loss 0.62731 dice_loss 0.18323 +Epoch [3316/4000] Validation [3/4] Loss: 0.29753 focal_loss 0.22899 dice_loss 0.06853 +Epoch [3316/4000] Validation [4/4] Loss: 0.31054 focal_loss 0.21267 dice_loss 0.09787 +Epoch [3316/4000] Validation metric {'Val/mean dice_metric': 0.9736602902412415, 'Val/mean miou_metric': 0.9595077633857727, 'Val/mean f1': 0.9762076139450073, 'Val/mean precision': 0.973224401473999, 'Val/mean recall': 0.979209303855896, 'Val/mean hd95_metric': 5.262806415557861} +Cheakpoint... +Epoch [3316/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736602902412415, 'Val/mean miou_metric': 0.9595077633857727, 'Val/mean f1': 0.9762076139450073, 'Val/mean precision': 0.973224401473999, 'Val/mean recall': 0.979209303855896, 'Val/mean hd95_metric': 5.262806415557861} +Epoch [3317/4000] Training [1/16] Loss: 0.00179 +Epoch [3317/4000] Training [2/16] Loss: 0.00374 +Epoch [3317/4000] Training [3/16] Loss: 0.00231 +Epoch [3317/4000] Training [4/16] Loss: 0.00207 +Epoch [3317/4000] Training [5/16] Loss: 0.00354 +Epoch [3317/4000] Training [6/16] Loss: 0.00272 +Epoch [3317/4000] Training [7/16] Loss: 0.00277 +Epoch [3317/4000] Training [8/16] Loss: 0.00232 +Epoch [3317/4000] Training [9/16] Loss: 0.00231 +Epoch [3317/4000] Training [10/16] Loss: 0.00265 +Epoch [3317/4000] Training [11/16] Loss: 0.00279 +Epoch [3317/4000] Training [12/16] Loss: 0.00367 +Epoch [3317/4000] Training [13/16] Loss: 0.00246 +Epoch [3317/4000] Training [14/16] Loss: 0.00379 +Epoch [3317/4000] Training [15/16] Loss: 0.00309 +Epoch [3317/4000] Training [16/16] Loss: 0.00245 +Epoch [3317/4000] Training metric {'Train/mean dice_metric': 0.998481810092926, 'Train/mean miou_metric': 0.9966915249824524, 'Train/mean f1': 0.9935644865036011, 'Train/mean precision': 0.9890539050102234, 'Train/mean recall': 0.9981163740158081, 'Train/mean hd95_metric': 0.6494695544242859} +Epoch [3317/4000] Validation [1/4] Loss: 0.43102 focal_loss 0.36793 dice_loss 0.06309 +Epoch [3317/4000] Validation [2/4] Loss: 0.54753 focal_loss 0.40715 dice_loss 0.14038 +Epoch [3317/4000] Validation [3/4] Loss: 0.51841 focal_loss 0.43151 dice_loss 0.08691 +Epoch [3317/4000] Validation [4/4] Loss: 0.48779 focal_loss 0.37292 dice_loss 0.11487 +Epoch [3317/4000] Validation metric {'Val/mean dice_metric': 0.9728719592094421, 'Val/mean miou_metric': 0.9589544534683228, 'Val/mean f1': 0.9761765599250793, 'Val/mean precision': 0.9734281897544861, 'Val/mean recall': 0.978940486907959, 'Val/mean hd95_metric': 5.093716144561768} +Cheakpoint... +Epoch [3317/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728719592094421, 'Val/mean miou_metric': 0.9589544534683228, 'Val/mean f1': 0.9761765599250793, 'Val/mean precision': 0.9734281897544861, 'Val/mean recall': 0.978940486907959, 'Val/mean hd95_metric': 5.093716144561768} +Epoch [3318/4000] Training [1/16] Loss: 0.00266 +Epoch [3318/4000] Training [2/16] Loss: 0.00323 +Epoch [3318/4000] Training [3/16] Loss: 0.00202 +Epoch [3318/4000] Training [4/16] Loss: 0.00251 +Epoch [3318/4000] Training [5/16] Loss: 0.00235 +Epoch [3318/4000] Training [6/16] Loss: 0.00249 +Epoch [3318/4000] Training [7/16] Loss: 0.00280 +Epoch [3318/4000] Training [8/16] Loss: 0.00289 +Epoch [3318/4000] Training [9/16] Loss: 0.00263 +Epoch [3318/4000] Training [10/16] Loss: 0.00351 +Epoch [3318/4000] Training [11/16] Loss: 0.00276 +Epoch [3318/4000] Training [12/16] Loss: 0.00299 +Epoch [3318/4000] Training [13/16] Loss: 0.00499 +Epoch [3318/4000] Training [14/16] Loss: 0.00257 +Epoch [3318/4000] Training [15/16] Loss: 0.00250 +Epoch [3318/4000] Training [16/16] Loss: 0.00230 +Epoch [3318/4000] Training metric {'Train/mean dice_metric': 0.9984635710716248, 'Train/mean miou_metric': 0.9966416358947754, 'Train/mean f1': 0.9935459494590759, 'Train/mean precision': 0.9889262318611145, 'Train/mean recall': 0.9982089996337891, 'Train/mean hd95_metric': 0.6638948321342468} +Epoch [3318/4000] Validation [1/4] Loss: 0.36699 focal_loss 0.30686 dice_loss 0.06013 +Epoch [3318/4000] Validation [2/4] Loss: 0.89929 focal_loss 0.70221 dice_loss 0.19707 +Epoch [3318/4000] Validation [3/4] Loss: 0.34409 focal_loss 0.27201 dice_loss 0.07208 +Epoch [3318/4000] Validation [4/4] Loss: 0.34885 focal_loss 0.24952 dice_loss 0.09934 +Epoch [3318/4000] Validation metric {'Val/mean dice_metric': 0.9752011299133301, 'Val/mean miou_metric': 0.9609216451644897, 'Val/mean f1': 0.9764887690544128, 'Val/mean precision': 0.9737622141838074, 'Val/mean recall': 0.9792307019233704, 'Val/mean hd95_metric': 5.023308753967285} +Cheakpoint... +Epoch [3318/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752011299133301, 'Val/mean miou_metric': 0.9609216451644897, 'Val/mean f1': 0.9764887690544128, 'Val/mean precision': 0.9737622141838074, 'Val/mean recall': 0.9792307019233704, 'Val/mean hd95_metric': 5.023308753967285} +Epoch [3319/4000] Training [1/16] Loss: 0.00281 +Epoch [3319/4000] Training [2/16] Loss: 0.00260 +Epoch [3319/4000] Training [3/16] Loss: 0.00305 +Epoch [3319/4000] Training [4/16] Loss: 0.00405 +Epoch [3319/4000] Training [5/16] Loss: 0.00223 +Epoch [3319/4000] Training [6/16] Loss: 0.00283 +Epoch [3319/4000] Training [7/16] Loss: 0.00278 +Epoch [3319/4000] Training [8/16] Loss: 0.00192 +Epoch [3319/4000] Training [9/16] Loss: 0.00172 +Epoch [3319/4000] Training [10/16] Loss: 0.00386 +Epoch [3319/4000] Training [11/16] Loss: 0.00313 +Epoch [3319/4000] Training [12/16] Loss: 0.00215 +Epoch [3319/4000] Training [13/16] Loss: 0.00247 +Epoch [3319/4000] Training [14/16] Loss: 0.00242 +Epoch [3319/4000] Training [15/16] Loss: 0.00275 +Epoch [3319/4000] Training [16/16] Loss: 0.00191 +Epoch [3319/4000] Training metric {'Train/mean dice_metric': 0.9986604452133179, 'Train/mean miou_metric': 0.9970217943191528, 'Train/mean f1': 0.9930089116096497, 'Train/mean precision': 0.9878562092781067, 'Train/mean recall': 0.9982156753540039, 'Train/mean hd95_metric': 0.6234650611877441} +Epoch [3319/4000] Validation [1/4] Loss: 0.43064 focal_loss 0.36530 dice_loss 0.06534 +Epoch [3319/4000] Validation [2/4] Loss: 0.44032 focal_loss 0.33114 dice_loss 0.10918 +Epoch [3319/4000] Validation [3/4] Loss: 0.50183 focal_loss 0.40506 dice_loss 0.09676 +Epoch [3319/4000] Validation [4/4] Loss: 0.30912 focal_loss 0.21031 dice_loss 0.09882 +Epoch [3319/4000] Validation metric {'Val/mean dice_metric': 0.9742492437362671, 'Val/mean miou_metric': 0.9605717658996582, 'Val/mean f1': 0.9760026335716248, 'Val/mean precision': 0.9725039601325989, 'Val/mean recall': 0.979526698589325, 'Val/mean hd95_metric': 5.059275150299072} +Cheakpoint... +Epoch [3319/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742492437362671, 'Val/mean miou_metric': 0.9605717658996582, 'Val/mean f1': 0.9760026335716248, 'Val/mean precision': 0.9725039601325989, 'Val/mean recall': 0.979526698589325, 'Val/mean hd95_metric': 5.059275150299072} +Epoch [3320/4000] Training [1/16] Loss: 0.00283 +Epoch [3320/4000] Training [2/16] Loss: 0.00261 +Epoch [3320/4000] Training [3/16] Loss: 0.00250 +Epoch [3320/4000] Training [4/16] Loss: 0.00378 +Epoch [3320/4000] Training [5/16] Loss: 0.00249 +Epoch [3320/4000] Training [6/16] Loss: 0.00218 +Epoch [3320/4000] Training [7/16] Loss: 0.00251 +Epoch [3320/4000] Training [8/16] Loss: 0.00370 +Epoch [3320/4000] Training [9/16] Loss: 0.00259 +Epoch [3320/4000] Training [10/16] Loss: 0.00281 +Epoch [3320/4000] Training [11/16] Loss: 0.00209 +Epoch [3320/4000] Training [12/16] Loss: 0.00309 +Epoch [3320/4000] Training [13/16] Loss: 0.00211 +Epoch [3320/4000] Training [14/16] Loss: 0.00264 +Epoch [3320/4000] Training [15/16] Loss: 0.00218 +Epoch [3320/4000] Training [16/16] Loss: 0.00299 +Epoch [3320/4000] Training metric {'Train/mean dice_metric': 0.9983853101730347, 'Train/mean miou_metric': 0.9964788556098938, 'Train/mean f1': 0.9931527376174927, 'Train/mean precision': 0.9883241057395935, 'Train/mean recall': 0.9980287551879883, 'Train/mean hd95_metric': 0.697097897529602} +Epoch [3320/4000] Validation [1/4] Loss: 0.41462 focal_loss 0.35062 dice_loss 0.06400 +Epoch [3320/4000] Validation [2/4] Loss: 0.43161 focal_loss 0.32409 dice_loss 0.10753 +Epoch [3320/4000] Validation [3/4] Loss: 0.53370 focal_loss 0.44239 dice_loss 0.09131 +Epoch [3320/4000] Validation [4/4] Loss: 0.34962 focal_loss 0.24955 dice_loss 0.10006 +Epoch [3320/4000] Validation metric {'Val/mean dice_metric': 0.9741228222846985, 'Val/mean miou_metric': 0.9600191116333008, 'Val/mean f1': 0.9760676026344299, 'Val/mean precision': 0.9727614521980286, 'Val/mean recall': 0.9793964624404907, 'Val/mean hd95_metric': 4.847349166870117} +Cheakpoint... +Epoch [3320/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741228222846985, 'Val/mean miou_metric': 0.9600191116333008, 'Val/mean f1': 0.9760676026344299, 'Val/mean precision': 0.9727614521980286, 'Val/mean recall': 0.9793964624404907, 'Val/mean hd95_metric': 4.847349166870117} +Epoch [3321/4000] Training [1/16] Loss: 0.00408 +Epoch [3321/4000] Training [2/16] Loss: 0.00212 +Epoch [3321/4000] Training [3/16] Loss: 0.00262 +Epoch [3321/4000] Training [4/16] Loss: 0.00315 +Epoch [3321/4000] Training [5/16] Loss: 0.00302 +Epoch [3321/4000] Training [6/16] Loss: 0.00279 +Epoch [3321/4000] Training [7/16] Loss: 0.00226 +Epoch [3321/4000] Training [8/16] Loss: 0.00277 +Epoch [3321/4000] Training [9/16] Loss: 0.00215 +Epoch [3321/4000] Training [10/16] Loss: 0.00265 +Epoch [3321/4000] Training [11/16] Loss: 0.00280 +Epoch [3321/4000] Training [12/16] Loss: 0.00191 +Epoch [3321/4000] Training [13/16] Loss: 0.00247 +Epoch [3321/4000] Training [14/16] Loss: 0.00279 +Epoch [3321/4000] Training [15/16] Loss: 0.00296 +Epoch [3321/4000] Training [16/16] Loss: 0.00250 +Epoch [3321/4000] Training metric {'Train/mean dice_metric': 0.9985339641571045, 'Train/mean miou_metric': 0.9967791438102722, 'Train/mean f1': 0.9935147762298584, 'Train/mean precision': 0.9889061450958252, 'Train/mean recall': 0.9981665015220642, 'Train/mean hd95_metric': 0.6292269229888916} +Epoch [3321/4000] Validation [1/4] Loss: 0.37753 focal_loss 0.31460 dice_loss 0.06293 +Epoch [3321/4000] Validation [2/4] Loss: 0.48681 focal_loss 0.37238 dice_loss 0.11442 +Epoch [3321/4000] Validation [3/4] Loss: 0.56140 focal_loss 0.45725 dice_loss 0.10415 +Epoch [3321/4000] Validation [4/4] Loss: 0.31393 focal_loss 0.22234 dice_loss 0.09159 +Epoch [3321/4000] Validation metric {'Val/mean dice_metric': 0.9746913909912109, 'Val/mean miou_metric': 0.9599853754043579, 'Val/mean f1': 0.9759958386421204, 'Val/mean precision': 0.9727266430854797, 'Val/mean recall': 0.9792870283126831, 'Val/mean hd95_metric': 4.929463863372803} +Cheakpoint... +Epoch [3321/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746913909912109, 'Val/mean miou_metric': 0.9599853754043579, 'Val/mean f1': 0.9759958386421204, 'Val/mean precision': 0.9727266430854797, 'Val/mean recall': 0.9792870283126831, 'Val/mean hd95_metric': 4.929463863372803} +Epoch [3322/4000] Training [1/16] Loss: 0.00244 +Epoch [3322/4000] Training [2/16] Loss: 0.00243 +Epoch [3322/4000] Training [3/16] Loss: 0.00227 +Epoch [3322/4000] Training [4/16] Loss: 0.00303 +Epoch [3322/4000] Training [5/16] Loss: 0.00341 +Epoch [3322/4000] Training [6/16] Loss: 0.00238 +Epoch [3322/4000] Training [7/16] Loss: 0.00286 +Epoch [3322/4000] Training [8/16] Loss: 0.00363 +Epoch [3322/4000] Training [9/16] Loss: 0.00235 +Epoch [3322/4000] Training [10/16] Loss: 0.00245 +Epoch [3322/4000] Training [11/16] Loss: 0.00330 +Epoch [3322/4000] Training [12/16] Loss: 0.00306 +Epoch [3322/4000] Training [13/16] Loss: 0.00240 +Epoch [3322/4000] Training [14/16] Loss: 0.00203 +Epoch [3322/4000] Training [15/16] Loss: 0.00223 +Epoch [3322/4000] Training [16/16] Loss: 0.00333 +Epoch [3322/4000] Training metric {'Train/mean dice_metric': 0.9987155199050903, 'Train/mean miou_metric': 0.9971563220024109, 'Train/mean f1': 0.9937442541122437, 'Train/mean precision': 0.9891941547393799, 'Train/mean recall': 0.9983363747596741, 'Train/mean hd95_metric': 0.5870671272277832} +Epoch [3322/4000] Validation [1/4] Loss: 0.35370 focal_loss 0.29205 dice_loss 0.06165 +Epoch [3322/4000] Validation [2/4] Loss: 0.53980 focal_loss 0.39923 dice_loss 0.14056 +Epoch [3322/4000] Validation [3/4] Loss: 0.53303 focal_loss 0.43762 dice_loss 0.09541 +Epoch [3322/4000] Validation [4/4] Loss: 0.33649 focal_loss 0.24497 dice_loss 0.09152 +Epoch [3322/4000] Validation metric {'Val/mean dice_metric': 0.9749155044555664, 'Val/mean miou_metric': 0.9609380960464478, 'Val/mean f1': 0.9766786694526672, 'Val/mean precision': 0.9743290543556213, 'Val/mean recall': 0.9790397882461548, 'Val/mean hd95_metric': 4.757244110107422} +Cheakpoint... +Epoch [3322/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749155044555664, 'Val/mean miou_metric': 0.9609380960464478, 'Val/mean f1': 0.9766786694526672, 'Val/mean precision': 0.9743290543556213, 'Val/mean recall': 0.9790397882461548, 'Val/mean hd95_metric': 4.757244110107422} +Epoch [3323/4000] Training [1/16] Loss: 0.00192 +Epoch [3323/4000] Training [2/16] Loss: 0.00218 +Epoch [3323/4000] Training [3/16] Loss: 0.00281 +Epoch [3323/4000] Training [4/16] Loss: 0.00354 +Epoch [3323/4000] Training [5/16] Loss: 0.00412 +Epoch [3323/4000] Training [6/16] Loss: 0.00299 +Epoch [3323/4000] Training [7/16] Loss: 0.00261 +Epoch [3323/4000] Training [8/16] Loss: 0.00176 +Epoch [3323/4000] Training [9/16] Loss: 0.00365 +Epoch [3323/4000] Training [10/16] Loss: 0.00217 +Epoch [3323/4000] Training [11/16] Loss: 0.00330 +Epoch [3323/4000] Training [12/16] Loss: 0.00273 +Epoch [3323/4000] Training [13/16] Loss: 0.00310 +Epoch [3323/4000] Training [14/16] Loss: 0.00228 +Epoch [3323/4000] Training [15/16] Loss: 0.00253 +Epoch [3323/4000] Training [16/16] Loss: 0.00225 +Epoch [3323/4000] Training metric {'Train/mean dice_metric': 0.9986149072647095, 'Train/mean miou_metric': 0.9969559907913208, 'Train/mean f1': 0.9936704635620117, 'Train/mean precision': 0.9890598654747009, 'Train/mean recall': 0.9983242154121399, 'Train/mean hd95_metric': 0.629910409450531} +Epoch [3323/4000] Validation [1/4] Loss: 0.37968 focal_loss 0.31894 dice_loss 0.06074 +Epoch [3323/4000] Validation [2/4] Loss: 0.45380 focal_loss 0.34387 dice_loss 0.10993 +Epoch [3323/4000] Validation [3/4] Loss: 0.55573 focal_loss 0.45056 dice_loss 0.10516 +Epoch [3323/4000] Validation [4/4] Loss: 0.34897 focal_loss 0.24989 dice_loss 0.09908 +Epoch [3323/4000] Validation metric {'Val/mean dice_metric': 0.9741967916488647, 'Val/mean miou_metric': 0.9596670269966125, 'Val/mean f1': 0.9761247038841248, 'Val/mean precision': 0.9731796979904175, 'Val/mean recall': 0.9790874123573303, 'Val/mean hd95_metric': 5.2079339027404785} +Cheakpoint... +Epoch [3323/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741967916488647, 'Val/mean miou_metric': 0.9596670269966125, 'Val/mean f1': 0.9761247038841248, 'Val/mean precision': 0.9731796979904175, 'Val/mean recall': 0.9790874123573303, 'Val/mean hd95_metric': 5.2079339027404785} +Epoch [3324/4000] Training [1/16] Loss: 0.00172 +Epoch [3324/4000] Training [2/16] Loss: 0.00265 +Epoch [3324/4000] Training [3/16] Loss: 0.00315 +Epoch [3324/4000] Training [4/16] Loss: 0.00240 +Epoch [3324/4000] Training [5/16] Loss: 0.00323 +Epoch [3324/4000] Training [6/16] Loss: 0.00196 +Epoch [3324/4000] Training [7/16] Loss: 0.00270 +Epoch [3324/4000] Training [8/16] Loss: 0.00275 +Epoch [3324/4000] Training [9/16] Loss: 0.00266 +Epoch [3324/4000] Training [10/16] Loss: 0.00273 +Epoch [3324/4000] Training [11/16] Loss: 0.00337 +Epoch [3324/4000] Training [12/16] Loss: 0.00297 +Epoch [3324/4000] Training [13/16] Loss: 0.00223 +Epoch [3324/4000] Training [14/16] Loss: 0.00273 +Epoch [3324/4000] Training [15/16] Loss: 0.00220 +Epoch [3324/4000] Training [16/16] Loss: 0.00997 +Epoch [3324/4000] Training metric {'Train/mean dice_metric': 0.9984175562858582, 'Train/mean miou_metric': 0.996574342250824, 'Train/mean f1': 0.9935609102249146, 'Train/mean precision': 0.9890126585960388, 'Train/mean recall': 0.9981511831283569, 'Train/mean hd95_metric': 0.6770346164703369} +Epoch [3324/4000] Validation [1/4] Loss: 0.39758 focal_loss 0.33336 dice_loss 0.06422 +Epoch [3324/4000] Validation [2/4] Loss: 1.05263 focal_loss 0.85657 dice_loss 0.19606 +Epoch [3324/4000] Validation [3/4] Loss: 0.52673 focal_loss 0.42936 dice_loss 0.09737 +Epoch [3324/4000] Validation [4/4] Loss: 0.46575 focal_loss 0.35112 dice_loss 0.11463 +Epoch [3324/4000] Validation metric {'Val/mean dice_metric': 0.9732488393783569, 'Val/mean miou_metric': 0.9591798782348633, 'Val/mean f1': 0.9760628938674927, 'Val/mean precision': 0.9730589985847473, 'Val/mean recall': 0.9790855646133423, 'Val/mean hd95_metric': 5.063758850097656} +Cheakpoint... +Epoch [3324/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732488393783569, 'Val/mean miou_metric': 0.9591798782348633, 'Val/mean f1': 0.9760628938674927, 'Val/mean precision': 0.9730589985847473, 'Val/mean recall': 0.9790855646133423, 'Val/mean hd95_metric': 5.063758850097656} +Epoch [3325/4000] Training [1/16] Loss: 0.00486 +Epoch [3325/4000] Training [2/16] Loss: 0.00526 +Epoch [3325/4000] Training [3/16] Loss: 0.00287 +Epoch [3325/4000] Training [4/16] Loss: 0.00257 +Epoch [3325/4000] Training [5/16] Loss: 0.00278 +Epoch [3325/4000] Training [6/16] Loss: 0.00276 +Epoch [3325/4000] Training [7/16] Loss: 0.00282 +Epoch [3325/4000] Training [8/16] Loss: 0.00341 +Epoch [3325/4000] Training [9/16] Loss: 0.00253 +Epoch [3325/4000] Training [10/16] Loss: 0.00176 +Epoch [3325/4000] Training [11/16] Loss: 0.00298 +Epoch [3325/4000] Training [12/16] Loss: 0.00239 +Epoch [3325/4000] Training [13/16] Loss: 0.00345 +Epoch [3325/4000] Training [14/16] Loss: 0.00305 +Epoch [3325/4000] Training [15/16] Loss: 0.00234 +Epoch [3325/4000] Training [16/16] Loss: 0.00246 +Epoch [3325/4000] Training metric {'Train/mean dice_metric': 0.9983748197555542, 'Train/mean miou_metric': 0.9964554905891418, 'Train/mean f1': 0.9927588105201721, 'Train/mean precision': 0.9875665307044983, 'Train/mean recall': 0.9980059266090393, 'Train/mean hd95_metric': 0.6276996731758118} +Epoch [3325/4000] Validation [1/4] Loss: 0.48433 focal_loss 0.41853 dice_loss 0.06580 +Epoch [3325/4000] Validation [2/4] Loss: 0.47121 focal_loss 0.35380 dice_loss 0.11741 +Epoch [3325/4000] Validation [3/4] Loss: 0.54766 focal_loss 0.45505 dice_loss 0.09261 +Epoch [3325/4000] Validation [4/4] Loss: 0.31137 focal_loss 0.21441 dice_loss 0.09696 +Epoch [3325/4000] Validation metric {'Val/mean dice_metric': 0.9762357473373413, 'Val/mean miou_metric': 0.9615136981010437, 'Val/mean f1': 0.9760099649429321, 'Val/mean precision': 0.9720070958137512, 'Val/mean recall': 0.9800459146499634, 'Val/mean hd95_metric': 4.674704551696777} +Cheakpoint... +Epoch [3325/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9762357473373413, 'Val/mean miou_metric': 0.9615136981010437, 'Val/mean f1': 0.9760099649429321, 'Val/mean precision': 0.9720070958137512, 'Val/mean recall': 0.9800459146499634, 'Val/mean hd95_metric': 4.674704551696777} +Epoch [3326/4000] Training [1/16] Loss: 0.00138 +Epoch [3326/4000] Training [2/16] Loss: 0.00285 +Epoch [3326/4000] Training [3/16] Loss: 0.00303 +Epoch [3326/4000] Training [4/16] Loss: 0.00265 +Epoch [3326/4000] Training [5/16] Loss: 0.00202 +Epoch [3326/4000] Training [6/16] Loss: 0.00277 +Epoch [3326/4000] Training [7/16] Loss: 0.00244 +Epoch [3326/4000] Training [8/16] Loss: 0.00330 +Epoch [3326/4000] Training [9/16] Loss: 0.00189 +Epoch [3326/4000] Training [10/16] Loss: 0.00251 +Epoch [3326/4000] Training [11/16] Loss: 0.00372 +Epoch [3326/4000] Training [12/16] Loss: 0.00189 +Epoch [3326/4000] Training [13/16] Loss: 0.00234 +Epoch [3326/4000] Training [14/16] Loss: 0.00192 +Epoch [3326/4000] Training [15/16] Loss: 0.00262 +Epoch [3326/4000] Training [16/16] Loss: 0.00387 +Epoch [3326/4000] Training metric {'Train/mean dice_metric': 0.9987005591392517, 'Train/mean miou_metric': 0.9971165657043457, 'Train/mean f1': 0.9934511184692383, 'Train/mean precision': 0.9887139201164246, 'Train/mean recall': 0.9982338547706604, 'Train/mean hd95_metric': 0.5763670206069946} +Epoch [3326/4000] Validation [1/4] Loss: 0.41221 focal_loss 0.34934 dice_loss 0.06288 +Epoch [3326/4000] Validation [2/4] Loss: 0.46708 focal_loss 0.35462 dice_loss 0.11246 +Epoch [3326/4000] Validation [3/4] Loss: 0.50637 focal_loss 0.40963 dice_loss 0.09675 +Epoch [3326/4000] Validation [4/4] Loss: 0.44122 focal_loss 0.32792 dice_loss 0.11331 +Epoch [3326/4000] Validation metric {'Val/mean dice_metric': 0.9764792323112488, 'Val/mean miou_metric': 0.9622205495834351, 'Val/mean f1': 0.9766614437103271, 'Val/mean precision': 0.9734442234039307, 'Val/mean recall': 0.9798998832702637, 'Val/mean hd95_metric': 4.622738361358643} +Cheakpoint... +Epoch [3326/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9765], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9764792323112488, 'Val/mean miou_metric': 0.9622205495834351, 'Val/mean f1': 0.9766614437103271, 'Val/mean precision': 0.9734442234039307, 'Val/mean recall': 0.9798998832702637, 'Val/mean hd95_metric': 4.622738361358643} +Epoch [3327/4000] Training [1/16] Loss: 0.00263 +Epoch [3327/4000] Training [2/16] Loss: 0.00218 +Epoch [3327/4000] Training [3/16] Loss: 0.00303 +Epoch [3327/4000] Training [4/16] Loss: 0.00231 +Epoch [3327/4000] Training [5/16] Loss: 0.00270 +Epoch [3327/4000] Training [6/16] Loss: 0.00461 +Epoch [3327/4000] Training [7/16] Loss: 0.00322 +Epoch [3327/4000] Training [8/16] Loss: 0.00298 +Epoch [3327/4000] Training [9/16] Loss: 0.00298 +Epoch [3327/4000] Training [10/16] Loss: 0.00258 +Epoch [3327/4000] Training [11/16] Loss: 0.00182 +Epoch [3327/4000] Training [12/16] Loss: 0.00286 +Epoch [3327/4000] Training [13/16] Loss: 0.00346 +Epoch [3327/4000] Training [14/16] Loss: 0.00272 +Epoch [3327/4000] Training [15/16] Loss: 0.00217 +Epoch [3327/4000] Training [16/16] Loss: 0.00240 +Epoch [3327/4000] Training metric {'Train/mean dice_metric': 0.9986287355422974, 'Train/mean miou_metric': 0.9969778656959534, 'Train/mean f1': 0.9935917258262634, 'Train/mean precision': 0.9890413880348206, 'Train/mean recall': 0.998184084892273, 'Train/mean hd95_metric': 0.6378207206726074} +Epoch [3327/4000] Validation [1/4] Loss: 0.40521 focal_loss 0.34269 dice_loss 0.06252 +Epoch [3327/4000] Validation [2/4] Loss: 0.53424 focal_loss 0.39824 dice_loss 0.13600 +Epoch [3327/4000] Validation [3/4] Loss: 0.54719 focal_loss 0.45048 dice_loss 0.09671 +Epoch [3327/4000] Validation [4/4] Loss: 0.39730 focal_loss 0.29366 dice_loss 0.10363 +Epoch [3327/4000] Validation metric {'Val/mean dice_metric': 0.9735398292541504, 'Val/mean miou_metric': 0.9594939351081848, 'Val/mean f1': 0.9761594533920288, 'Val/mean precision': 0.9731477499008179, 'Val/mean recall': 0.9791896939277649, 'Val/mean hd95_metric': 4.975041389465332} +Cheakpoint... +Epoch [3327/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735398292541504, 'Val/mean miou_metric': 0.9594939351081848, 'Val/mean f1': 0.9761594533920288, 'Val/mean precision': 0.9731477499008179, 'Val/mean recall': 0.9791896939277649, 'Val/mean hd95_metric': 4.975041389465332} +Epoch [3328/4000] Training [1/16] Loss: 0.00181 +Epoch [3328/4000] Training [2/16] Loss: 0.00213 +Epoch [3328/4000] Training [3/16] Loss: 0.00291 +Epoch [3328/4000] Training [4/16] Loss: 0.00355 +Epoch [3328/4000] Training [5/16] Loss: 0.00224 +Epoch [3328/4000] Training [6/16] Loss: 0.00248 +Epoch [3328/4000] Training [7/16] Loss: 0.00310 +Epoch [3328/4000] Training [8/16] Loss: 0.00211 +Epoch [3328/4000] Training [9/16] Loss: 0.00406 +Epoch [3328/4000] Training [10/16] Loss: 0.00215 +Epoch [3328/4000] Training [11/16] Loss: 0.00398 +Epoch [3328/4000] Training [12/16] Loss: 0.00272 +Epoch [3328/4000] Training [13/16] Loss: 0.00247 +Epoch [3328/4000] Training [14/16] Loss: 0.00272 +Epoch [3328/4000] Training [15/16] Loss: 0.00188 +Epoch [3328/4000] Training [16/16] Loss: 0.00296 +Epoch [3328/4000] Training metric {'Train/mean dice_metric': 0.9986450672149658, 'Train/mean miou_metric': 0.9970165491104126, 'Train/mean f1': 0.9936326742172241, 'Train/mean precision': 0.9890382289886475, 'Train/mean recall': 0.9982699155807495, 'Train/mean hd95_metric': 0.6216795444488525} +Epoch [3328/4000] Validation [1/4] Loss: 0.34921 focal_loss 0.28946 dice_loss 0.05975 +Epoch [3328/4000] Validation [2/4] Loss: 0.48598 focal_loss 0.37001 dice_loss 0.11597 +Epoch [3328/4000] Validation [3/4] Loss: 0.53486 focal_loss 0.44311 dice_loss 0.09174 +Epoch [3328/4000] Validation [4/4] Loss: 0.45321 focal_loss 0.33829 dice_loss 0.11493 +Epoch [3328/4000] Validation metric {'Val/mean dice_metric': 0.9744358062744141, 'Val/mean miou_metric': 0.9601923823356628, 'Val/mean f1': 0.9760268926620483, 'Val/mean precision': 0.9730585217475891, 'Val/mean recall': 0.9790134429931641, 'Val/mean hd95_metric': 4.8292555809021} +Cheakpoint... +Epoch [3328/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744358062744141, 'Val/mean miou_metric': 0.9601923823356628, 'Val/mean f1': 0.9760268926620483, 'Val/mean precision': 0.9730585217475891, 'Val/mean recall': 0.9790134429931641, 'Val/mean hd95_metric': 4.8292555809021} +Epoch [3329/4000] Training [1/16] Loss: 0.00289 +Epoch [3329/4000] Training [2/16] Loss: 0.00248 +Epoch [3329/4000] Training [3/16] Loss: 0.00293 +Epoch [3329/4000] Training [4/16] Loss: 0.00229 +Epoch [3329/4000] Training [5/16] Loss: 0.00265 +Epoch [3329/4000] Training [6/16] Loss: 0.00307 +Epoch [3329/4000] Training [7/16] Loss: 0.00268 +Epoch [3329/4000] Training [8/16] Loss: 0.00260 +Epoch [3329/4000] Training [9/16] Loss: 0.00226 +Epoch [3329/4000] Training [10/16] Loss: 0.00272 +Epoch [3329/4000] Training [11/16] Loss: 0.00239 +Epoch [3329/4000] Training [12/16] Loss: 0.00190 +Epoch [3329/4000] Training [13/16] Loss: 0.00233 +Epoch [3329/4000] Training [14/16] Loss: 0.00279 +Epoch [3329/4000] Training [15/16] Loss: 0.00236 +Epoch [3329/4000] Training [16/16] Loss: 0.00192 +Epoch [3329/4000] Training metric {'Train/mean dice_metric': 0.9986673593521118, 'Train/mean miou_metric': 0.9970444440841675, 'Train/mean f1': 0.993496835231781, 'Train/mean precision': 0.9888063073158264, 'Train/mean recall': 0.9982320666313171, 'Train/mean hd95_metric': 0.6290315389633179} +Epoch [3329/4000] Validation [1/4] Loss: 0.42902 focal_loss 0.36369 dice_loss 0.06533 +Epoch [3329/4000] Validation [2/4] Loss: 0.46973 focal_loss 0.35854 dice_loss 0.11118 +Epoch [3329/4000] Validation [3/4] Loss: 0.55154 focal_loss 0.45834 dice_loss 0.09320 +Epoch [3329/4000] Validation [4/4] Loss: 0.37869 focal_loss 0.27663 dice_loss 0.10207 +Epoch [3329/4000] Validation metric {'Val/mean dice_metric': 0.9748151898384094, 'Val/mean miou_metric': 0.9606515765190125, 'Val/mean f1': 0.9763842821121216, 'Val/mean precision': 0.972983181476593, 'Val/mean recall': 0.9798092842102051, 'Val/mean hd95_metric': 4.771422386169434} +Cheakpoint... +Epoch [3329/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748151898384094, 'Val/mean miou_metric': 0.9606515765190125, 'Val/mean f1': 0.9763842821121216, 'Val/mean precision': 0.972983181476593, 'Val/mean recall': 0.9798092842102051, 'Val/mean hd95_metric': 4.771422386169434} +Epoch [3330/4000] Training [1/16] Loss: 0.00212 +Epoch [3330/4000] Training [2/16] Loss: 0.00344 +Epoch [3330/4000] Training [3/16] Loss: 0.00239 +Epoch [3330/4000] Training [4/16] Loss: 0.00195 +Epoch [3330/4000] Training [5/16] Loss: 0.00289 +Epoch [3330/4000] Training [6/16] Loss: 0.00158 +Epoch [3330/4000] Training [7/16] Loss: 0.00336 +Epoch [3330/4000] Training [8/16] Loss: 0.00210 +Epoch [3330/4000] Training [9/16] Loss: 0.00234 +Epoch [3330/4000] Training [10/16] Loss: 0.00434 +Epoch [3330/4000] Training [11/16] Loss: 0.00272 +Epoch [3330/4000] Training [12/16] Loss: 0.00180 +Epoch [3330/4000] Training [13/16] Loss: 0.00356 +Epoch [3330/4000] Training [14/16] Loss: 0.00278 +Epoch [3330/4000] Training [15/16] Loss: 0.00219 +Epoch [3330/4000] Training [16/16] Loss: 0.00172 +Epoch [3330/4000] Training metric {'Train/mean dice_metric': 0.9987491369247437, 'Train/mean miou_metric': 0.9972234964370728, 'Train/mean f1': 0.9938051104545593, 'Train/mean precision': 0.9892293214797974, 'Train/mean recall': 0.9984233975410461, 'Train/mean hd95_metric': 0.5852814316749573} +Epoch [3330/4000] Validation [1/4] Loss: 0.47081 focal_loss 0.40552 dice_loss 0.06529 +Epoch [3330/4000] Validation [2/4] Loss: 0.50313 focal_loss 0.35773 dice_loss 0.14541 +Epoch [3330/4000] Validation [3/4] Loss: 0.55633 focal_loss 0.45993 dice_loss 0.09639 +Epoch [3330/4000] Validation [4/4] Loss: 0.52737 focal_loss 0.39857 dice_loss 0.12880 +Epoch [3330/4000] Validation metric {'Val/mean dice_metric': 0.9751073122024536, 'Val/mean miou_metric': 0.9604738354682922, 'Val/mean f1': 0.9760956764221191, 'Val/mean precision': 0.9722111225128174, 'Val/mean recall': 0.9800114035606384, 'Val/mean hd95_metric': 5.070716857910156} +Cheakpoint... +Epoch [3330/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751073122024536, 'Val/mean miou_metric': 0.9604738354682922, 'Val/mean f1': 0.9760956764221191, 'Val/mean precision': 0.9722111225128174, 'Val/mean recall': 0.9800114035606384, 'Val/mean hd95_metric': 5.070716857910156} +Epoch [3331/4000] Training [1/16] Loss: 0.00299 +Epoch [3331/4000] Training [2/16] Loss: 0.00287 +Epoch [3331/4000] Training [3/16] Loss: 0.00363 +Epoch [3331/4000] Training [4/16] Loss: 0.00286 +Epoch [3331/4000] Training [5/16] Loss: 0.00216 +Epoch [3331/4000] Training [6/16] Loss: 0.00275 +Epoch [3331/4000] Training [7/16] Loss: 0.00313 +Epoch [3331/4000] Training [8/16] Loss: 0.00355 +Epoch [3331/4000] Training [9/16] Loss: 0.00242 +Epoch [3331/4000] Training [10/16] Loss: 0.00363 +Epoch [3331/4000] Training [11/16] Loss: 0.00295 +Epoch [3331/4000] Training [12/16] Loss: 0.00335 +Epoch [3331/4000] Training [13/16] Loss: 0.00275 +Epoch [3331/4000] Training [14/16] Loss: 0.00326 +Epoch [3331/4000] Training [15/16] Loss: 0.00261 +Epoch [3331/4000] Training [16/16] Loss: 0.00222 +Epoch [3331/4000] Training metric {'Train/mean dice_metric': 0.9984769821166992, 'Train/mean miou_metric': 0.9966827034950256, 'Train/mean f1': 0.9936204552650452, 'Train/mean precision': 0.9890890121459961, 'Train/mean recall': 0.998193621635437, 'Train/mean hd95_metric': 0.6505159139633179} +Epoch [3331/4000] Validation [1/4] Loss: 0.45522 focal_loss 0.38923 dice_loss 0.06599 +Epoch [3331/4000] Validation [2/4] Loss: 0.83768 focal_loss 0.64913 dice_loss 0.18855 +Epoch [3331/4000] Validation [3/4] Loss: 0.29364 focal_loss 0.22686 dice_loss 0.06678 +Epoch [3331/4000] Validation [4/4] Loss: 0.37823 focal_loss 0.28113 dice_loss 0.09709 +Epoch [3331/4000] Validation metric {'Val/mean dice_metric': 0.9749916791915894, 'Val/mean miou_metric': 0.9608343839645386, 'Val/mean f1': 0.9766496419906616, 'Val/mean precision': 0.974108099937439, 'Val/mean recall': 0.9792045950889587, 'Val/mean hd95_metric': 4.747408390045166} +Cheakpoint... +Epoch [3331/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749916791915894, 'Val/mean miou_metric': 0.9608343839645386, 'Val/mean f1': 0.9766496419906616, 'Val/mean precision': 0.974108099937439, 'Val/mean recall': 0.9792045950889587, 'Val/mean hd95_metric': 4.747408390045166} +Epoch [3332/4000] Training [1/16] Loss: 0.00672 +Epoch [3332/4000] Training [2/16] Loss: 0.00326 +Epoch [3332/4000] Training [3/16] Loss: 0.00270 +Epoch [3332/4000] Training [4/16] Loss: 0.00206 +Epoch [3332/4000] Training [5/16] Loss: 0.00266 +Epoch [3332/4000] Training [6/16] Loss: 0.00237 +Epoch [3332/4000] Training [7/16] Loss: 0.00251 +Epoch [3332/4000] Training [8/16] Loss: 0.00244 +Epoch [3332/4000] Training [9/16] Loss: 0.00287 +Epoch [3332/4000] Training [10/16] Loss: 0.00192 +Epoch [3332/4000] Training [11/16] Loss: 0.00289 +Epoch [3332/4000] Training [12/16] Loss: 0.00228 +Epoch [3332/4000] Training [13/16] Loss: 0.00223 +Epoch [3332/4000] Training [14/16] Loss: 0.00216 +Epoch [3332/4000] Training [15/16] Loss: 0.00385 +Epoch [3332/4000] Training [16/16] Loss: 0.00218 +Epoch [3332/4000] Training metric {'Train/mean dice_metric': 0.9984980821609497, 'Train/mean miou_metric': 0.9966890215873718, 'Train/mean f1': 0.9927079677581787, 'Train/mean precision': 0.9874110221862793, 'Train/mean recall': 0.998062014579773, 'Train/mean hd95_metric': 1.0582383871078491} +Epoch [3332/4000] Validation [1/4] Loss: 0.39525 focal_loss 0.33086 dice_loss 0.06439 +Epoch [3332/4000] Validation [2/4] Loss: 1.16573 focal_loss 0.97424 dice_loss 0.19148 +Epoch [3332/4000] Validation [3/4] Loss: 0.25089 focal_loss 0.19451 dice_loss 0.05637 +Epoch [3332/4000] Validation [4/4] Loss: 0.42880 focal_loss 0.31981 dice_loss 0.10899 +Epoch [3332/4000] Validation metric {'Val/mean dice_metric': 0.972800612449646, 'Val/mean miou_metric': 0.9592509269714355, 'Val/mean f1': 0.9755011796951294, 'Val/mean precision': 0.9725742936134338, 'Val/mean recall': 0.9784459471702576, 'Val/mean hd95_metric': 5.270491600036621} +Cheakpoint... +Epoch [3332/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972800612449646, 'Val/mean miou_metric': 0.9592509269714355, 'Val/mean f1': 0.9755011796951294, 'Val/mean precision': 0.9725742936134338, 'Val/mean recall': 0.9784459471702576, 'Val/mean hd95_metric': 5.270491600036621} +Epoch [3333/4000] Training [1/16] Loss: 0.00232 +Epoch [3333/4000] Training [2/16] Loss: 0.00326 +Epoch [3333/4000] Training [3/16] Loss: 0.00330 +Epoch [3333/4000] Training [4/16] Loss: 0.00243 +Epoch [3333/4000] Training [5/16] Loss: 0.00270 +Epoch [3333/4000] Training [6/16] Loss: 0.00253 +Epoch [3333/4000] Training [7/16] Loss: 0.00169 +Epoch [3333/4000] Training [8/16] Loss: 0.00213 +Epoch [3333/4000] Training [9/16] Loss: 0.00242 +Epoch [3333/4000] Training [10/16] Loss: 0.00335 +Epoch [3333/4000] Training [11/16] Loss: 0.00409 +Epoch [3333/4000] Training [12/16] Loss: 0.00235 +Epoch [3333/4000] Training [13/16] Loss: 0.00233 +Epoch [3333/4000] Training [14/16] Loss: 0.00261 +Epoch [3333/4000] Training [15/16] Loss: 0.00189 +Epoch [3333/4000] Training [16/16] Loss: 0.00329 +Epoch [3333/4000] Training metric {'Train/mean dice_metric': 0.9985837936401367, 'Train/mean miou_metric': 0.9968792796134949, 'Train/mean f1': 0.9934894442558289, 'Train/mean precision': 0.9888051748275757, 'Train/mean recall': 0.9982184767723083, 'Train/mean hd95_metric': 0.6508088111877441} +Epoch [3333/4000] Validation [1/4] Loss: 0.37015 focal_loss 0.30649 dice_loss 0.06366 +Epoch [3333/4000] Validation [2/4] Loss: 0.94629 focal_loss 0.72911 dice_loss 0.21718 +Epoch [3333/4000] Validation [3/4] Loss: 0.51566 focal_loss 0.42780 dice_loss 0.08786 +Epoch [3333/4000] Validation [4/4] Loss: 0.33839 focal_loss 0.24465 dice_loss 0.09374 +Epoch [3333/4000] Validation metric {'Val/mean dice_metric': 0.9726421236991882, 'Val/mean miou_metric': 0.9590549468994141, 'Val/mean f1': 0.9757444858551025, 'Val/mean precision': 0.9734399914741516, 'Val/mean recall': 0.9780598282814026, 'Val/mean hd95_metric': 5.335685729980469} +Cheakpoint... +Epoch [3333/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726421236991882, 'Val/mean miou_metric': 0.9590549468994141, 'Val/mean f1': 0.9757444858551025, 'Val/mean precision': 0.9734399914741516, 'Val/mean recall': 0.9780598282814026, 'Val/mean hd95_metric': 5.335685729980469} +Epoch [3334/4000] Training [1/16] Loss: 0.00260 +Epoch [3334/4000] Training [2/16] Loss: 0.00241 +Epoch [3334/4000] Training [3/16] Loss: 0.00271 +Epoch [3334/4000] Training [4/16] Loss: 0.00320 +Epoch [3334/4000] Training [5/16] Loss: 0.00348 +Epoch [3334/4000] Training [6/16] Loss: 0.00305 +Epoch [3334/4000] Training [7/16] Loss: 0.00209 +Epoch [3334/4000] Training [8/16] Loss: 0.00294 +Epoch [3334/4000] Training [9/16] Loss: 0.00224 +Epoch [3334/4000] Training [10/16] Loss: 0.00278 +Epoch [3334/4000] Training [11/16] Loss: 0.00226 +Epoch [3334/4000] Training [12/16] Loss: 0.00277 +Epoch [3334/4000] Training [13/16] Loss: 0.00310 +Epoch [3334/4000] Training [14/16] Loss: 0.00513 +Epoch [3334/4000] Training [15/16] Loss: 0.00288 +Epoch [3334/4000] Training [16/16] Loss: 0.00218 +Epoch [3334/4000] Training metric {'Train/mean dice_metric': 0.9984129667282104, 'Train/mean miou_metric': 0.9965493083000183, 'Train/mean f1': 0.9933555126190186, 'Train/mean precision': 0.9887176156044006, 'Train/mean recall': 0.9980371594429016, 'Train/mean hd95_metric': 0.6805241107940674} +Epoch [3334/4000] Validation [1/4] Loss: 0.40668 focal_loss 0.34302 dice_loss 0.06365 +Epoch [3334/4000] Validation [2/4] Loss: 0.48257 focal_loss 0.36243 dice_loss 0.12015 +Epoch [3334/4000] Validation [3/4] Loss: 0.51472 focal_loss 0.42605 dice_loss 0.08868 +Epoch [3334/4000] Validation [4/4] Loss: 0.36974 focal_loss 0.27194 dice_loss 0.09779 +Epoch [3334/4000] Validation metric {'Val/mean dice_metric': 0.9716743230819702, 'Val/mean miou_metric': 0.9581245183944702, 'Val/mean f1': 0.9757342338562012, 'Val/mean precision': 0.9734553694725037, 'Val/mean recall': 0.9780238270759583, 'Val/mean hd95_metric': 5.242011070251465} +Cheakpoint... +Epoch [3334/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716743230819702, 'Val/mean miou_metric': 0.9581245183944702, 'Val/mean f1': 0.9757342338562012, 'Val/mean precision': 0.9734553694725037, 'Val/mean recall': 0.9780238270759583, 'Val/mean hd95_metric': 5.242011070251465} +Epoch [3335/4000] Training [1/16] Loss: 0.00234 +Epoch [3335/4000] Training [2/16] Loss: 0.00262 +Epoch [3335/4000] Training [3/16] Loss: 0.00230 +Epoch [3335/4000] Training [4/16] Loss: 0.00291 +Epoch [3335/4000] Training [5/16] Loss: 0.00334 +Epoch [3335/4000] Training [6/16] Loss: 0.00284 +Epoch [3335/4000] Training [7/16] Loss: 0.00203 +Epoch [3335/4000] Training [8/16] Loss: 0.00230 +Epoch [3335/4000] Training [9/16] Loss: 0.00336 +Epoch [3335/4000] Training [10/16] Loss: 0.00201 +Epoch [3335/4000] Training [11/16] Loss: 0.00290 +Epoch [3335/4000] Training [12/16] Loss: 0.00221 +Epoch [3335/4000] Training [13/16] Loss: 0.00175 +Epoch [3335/4000] Training [14/16] Loss: 0.00246 +Epoch [3335/4000] Training [15/16] Loss: 0.00205 +Epoch [3335/4000] Training [16/16] Loss: 0.00203 +Epoch [3335/4000] Training metric {'Train/mean dice_metric': 0.9987043738365173, 'Train/mean miou_metric': 0.9971314668655396, 'Train/mean f1': 0.9937669634819031, 'Train/mean precision': 0.9892531037330627, 'Train/mean recall': 0.9983221292495728, 'Train/mean hd95_metric': 0.5830075740814209} +Epoch [3335/4000] Validation [1/4] Loss: 0.44058 focal_loss 0.37380 dice_loss 0.06679 +Epoch [3335/4000] Validation [2/4] Loss: 0.54004 focal_loss 0.39681 dice_loss 0.14323 +Epoch [3335/4000] Validation [3/4] Loss: 0.27406 focal_loss 0.21344 dice_loss 0.06062 +Epoch [3335/4000] Validation [4/4] Loss: 0.39943 focal_loss 0.28605 dice_loss 0.11338 +Epoch [3335/4000] Validation metric {'Val/mean dice_metric': 0.9746061563491821, 'Val/mean miou_metric': 0.9604736566543579, 'Val/mean f1': 0.9768621325492859, 'Val/mean precision': 0.9744200706481934, 'Val/mean recall': 0.9793164730072021, 'Val/mean hd95_metric': 4.805368423461914} +Cheakpoint... +Epoch [3335/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746061563491821, 'Val/mean miou_metric': 0.9604736566543579, 'Val/mean f1': 0.9768621325492859, 'Val/mean precision': 0.9744200706481934, 'Val/mean recall': 0.9793164730072021, 'Val/mean hd95_metric': 4.805368423461914} +Epoch [3336/4000] Training [1/16] Loss: 0.00289 +Epoch [3336/4000] Training [2/16] Loss: 0.00211 +Epoch [3336/4000] Training [3/16] Loss: 0.00328 +Epoch [3336/4000] Training [4/16] Loss: 0.00250 +Epoch [3336/4000] Training [5/16] Loss: 0.00222 +Epoch [3336/4000] Training [6/16] Loss: 0.00259 +Epoch [3336/4000] Training [7/16] Loss: 0.00394 +Epoch [3336/4000] Training [8/16] Loss: 0.00338 +Epoch [3336/4000] Training [9/16] Loss: 0.00235 +Epoch [3336/4000] Training [10/16] Loss: 0.00210 +Epoch [3336/4000] Training [11/16] Loss: 0.00276 +Epoch [3336/4000] Training [12/16] Loss: 0.00265 +Epoch [3336/4000] Training [13/16] Loss: 0.00343 +Epoch [3336/4000] Training [14/16] Loss: 0.00209 +Epoch [3336/4000] Training [15/16] Loss: 0.00282 +Epoch [3336/4000] Training [16/16] Loss: 0.00270 +Epoch [3336/4000] Training metric {'Train/mean dice_metric': 0.9985410571098328, 'Train/mean miou_metric': 0.9968019127845764, 'Train/mean f1': 0.9933830499649048, 'Train/mean precision': 0.9886192679405212, 'Train/mean recall': 0.9981929063796997, 'Train/mean hd95_metric': 0.6658756732940674} +Epoch [3336/4000] Validation [1/4] Loss: 0.46220 focal_loss 0.39666 dice_loss 0.06554 +Epoch [3336/4000] Validation [2/4] Loss: 0.87473 focal_loss 0.65899 dice_loss 0.21574 +Epoch [3336/4000] Validation [3/4] Loss: 0.54343 focal_loss 0.44737 dice_loss 0.09606 +Epoch [3336/4000] Validation [4/4] Loss: 0.36824 focal_loss 0.26123 dice_loss 0.10701 +Epoch [3336/4000] Validation metric {'Val/mean dice_metric': 0.9722417593002319, 'Val/mean miou_metric': 0.9581823348999023, 'Val/mean f1': 0.9754101037979126, 'Val/mean precision': 0.9730929136276245, 'Val/mean recall': 0.9777384400367737, 'Val/mean hd95_metric': 4.971466064453125} +Cheakpoint... +Epoch [3336/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722417593002319, 'Val/mean miou_metric': 0.9581823348999023, 'Val/mean f1': 0.9754101037979126, 'Val/mean precision': 0.9730929136276245, 'Val/mean recall': 0.9777384400367737, 'Val/mean hd95_metric': 4.971466064453125} +Epoch [3337/4000] Training [1/16] Loss: 0.00160 +Epoch [3337/4000] Training [2/16] Loss: 0.00198 +Epoch [3337/4000] Training [3/16] Loss: 0.00171 +Epoch [3337/4000] Training [4/16] Loss: 0.00257 +Epoch [3337/4000] Training [5/16] Loss: 0.00265 +Epoch [3337/4000] Training [6/16] Loss: 0.00237 +Epoch [3337/4000] Training [7/16] Loss: 0.00294 +Epoch [3337/4000] Training [8/16] Loss: 0.00357 +Epoch [3337/4000] Training [9/16] Loss: 0.00247 +Epoch [3337/4000] Training [10/16] Loss: 0.00244 +Epoch [3337/4000] Training [11/16] Loss: 0.00222 +Epoch [3337/4000] Training [12/16] Loss: 0.00235 +Epoch [3337/4000] Training [13/16] Loss: 0.00266 +Epoch [3337/4000] Training [14/16] Loss: 0.00211 +Epoch [3337/4000] Training [15/16] Loss: 0.00343 +Epoch [3337/4000] Training [16/16] Loss: 0.00218 +Epoch [3337/4000] Training metric {'Train/mean dice_metric': 0.9986672401428223, 'Train/mean miou_metric': 0.9970641732215881, 'Train/mean f1': 0.9937902092933655, 'Train/mean precision': 0.9892840385437012, 'Train/mean recall': 0.9983376860618591, 'Train/mean hd95_metric': 0.5688750743865967} +Epoch [3337/4000] Validation [1/4] Loss: 0.46944 focal_loss 0.40151 dice_loss 0.06793 +Epoch [3337/4000] Validation [2/4] Loss: 0.43786 focal_loss 0.33171 dice_loss 0.10615 +Epoch [3337/4000] Validation [3/4] Loss: 0.54867 focal_loss 0.45389 dice_loss 0.09478 +Epoch [3337/4000] Validation [4/4] Loss: 0.43746 focal_loss 0.32884 dice_loss 0.10862 +Epoch [3337/4000] Validation metric {'Val/mean dice_metric': 0.9742904901504517, 'Val/mean miou_metric': 0.9601852297782898, 'Val/mean f1': 0.9766868352890015, 'Val/mean precision': 0.9747810363769531, 'Val/mean recall': 0.9785999655723572, 'Val/mean hd95_metric': 4.729063510894775} +Cheakpoint... +Epoch [3337/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742904901504517, 'Val/mean miou_metric': 0.9601852297782898, 'Val/mean f1': 0.9766868352890015, 'Val/mean precision': 0.9747810363769531, 'Val/mean recall': 0.9785999655723572, 'Val/mean hd95_metric': 4.729063510894775} +Epoch [3338/4000] Training [1/16] Loss: 0.00497 +Epoch [3338/4000] Training [2/16] Loss: 0.00256 +Epoch [3338/4000] Training [3/16] Loss: 0.00198 +Epoch [3338/4000] Training [4/16] Loss: 0.00260 +Epoch [3338/4000] Training [5/16] Loss: 0.00175 +Epoch [3338/4000] Training [6/16] Loss: 0.00287 +Epoch [3338/4000] Training [7/16] Loss: 0.00297 +Epoch [3338/4000] Training [8/16] Loss: 0.00341 +Epoch [3338/4000] Training [9/16] Loss: 0.00278 +Epoch [3338/4000] Training [10/16] Loss: 0.00272 +Epoch [3338/4000] Training [11/16] Loss: 0.00221 +Epoch [3338/4000] Training [12/16] Loss: 0.00235 +Epoch [3338/4000] Training [13/16] Loss: 0.00332 +Epoch [3338/4000] Training [14/16] Loss: 0.00226 +Epoch [3338/4000] Training [15/16] Loss: 0.00162 +Epoch [3338/4000] Training [16/16] Loss: 0.00235 +Epoch [3338/4000] Training metric {'Train/mean dice_metric': 0.9986159801483154, 'Train/mean miou_metric': 0.9969204664230347, 'Train/mean f1': 0.9930839538574219, 'Train/mean precision': 0.9880428910255432, 'Train/mean recall': 0.9981766939163208, 'Train/mean hd95_metric': 0.58127760887146} +Epoch [3338/4000] Validation [1/4] Loss: 0.38279 focal_loss 0.31794 dice_loss 0.06485 +Epoch [3338/4000] Validation [2/4] Loss: 0.94337 focal_loss 0.75064 dice_loss 0.19273 +Epoch [3338/4000] Validation [3/4] Loss: 0.52029 focal_loss 0.42551 dice_loss 0.09478 +Epoch [3338/4000] Validation [4/4] Loss: 0.28802 focal_loss 0.20073 dice_loss 0.08729 +Epoch [3338/4000] Validation metric {'Val/mean dice_metric': 0.974399745464325, 'Val/mean miou_metric': 0.960290789604187, 'Val/mean f1': 0.9760164618492126, 'Val/mean precision': 0.9737221598625183, 'Val/mean recall': 0.9783216714859009, 'Val/mean hd95_metric': 4.913778781890869} +Cheakpoint... +Epoch [3338/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974399745464325, 'Val/mean miou_metric': 0.960290789604187, 'Val/mean f1': 0.9760164618492126, 'Val/mean precision': 0.9737221598625183, 'Val/mean recall': 0.9783216714859009, 'Val/mean hd95_metric': 4.913778781890869} +Epoch [3339/4000] Training [1/16] Loss: 0.00256 +Epoch [3339/4000] Training [2/16] Loss: 0.00200 +Epoch [3339/4000] Training [3/16] Loss: 0.00217 +Epoch [3339/4000] Training [4/16] Loss: 0.00259 +Epoch [3339/4000] Training [5/16] Loss: 0.00378 +Epoch [3339/4000] Training [6/16] Loss: 0.00249 +Epoch [3339/4000] Training [7/16] Loss: 0.00427 +Epoch [3339/4000] Training [8/16] Loss: 0.00301 +Epoch [3339/4000] Training [9/16] Loss: 0.00334 +Epoch [3339/4000] Training [10/16] Loss: 0.00232 +Epoch [3339/4000] Training [11/16] Loss: 0.00188 +Epoch [3339/4000] Training [12/16] Loss: 0.00188 +Epoch [3339/4000] Training [13/16] Loss: 0.00202 +Epoch [3339/4000] Training [14/16] Loss: 0.00378 +Epoch [3339/4000] Training [15/16] Loss: 0.00220 +Epoch [3339/4000] Training [16/16] Loss: 0.00202 +Epoch [3339/4000] Training metric {'Train/mean dice_metric': 0.9986305236816406, 'Train/mean miou_metric': 0.996989369392395, 'Train/mean f1': 0.993677020072937, 'Train/mean precision': 0.9891161322593689, 'Train/mean recall': 0.9982801675796509, 'Train/mean hd95_metric': 0.6322680711746216} +Epoch [3339/4000] Validation [1/4] Loss: 0.41258 focal_loss 0.34738 dice_loss 0.06520 +Epoch [3339/4000] Validation [2/4] Loss: 0.57529 focal_loss 0.42766 dice_loss 0.14763 +Epoch [3339/4000] Validation [3/4] Loss: 0.55109 focal_loss 0.45510 dice_loss 0.09599 +Epoch [3339/4000] Validation [4/4] Loss: 0.33497 focal_loss 0.24484 dice_loss 0.09013 +Epoch [3339/4000] Validation metric {'Val/mean dice_metric': 0.9738283157348633, 'Val/mean miou_metric': 0.959424614906311, 'Val/mean f1': 0.975823700428009, 'Val/mean precision': 0.9733343124389648, 'Val/mean recall': 0.9783259034156799, 'Val/mean hd95_metric': 4.9730305671691895} +Cheakpoint... +Epoch [3339/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738283157348633, 'Val/mean miou_metric': 0.959424614906311, 'Val/mean f1': 0.975823700428009, 'Val/mean precision': 0.9733343124389648, 'Val/mean recall': 0.9783259034156799, 'Val/mean hd95_metric': 4.9730305671691895} +Epoch [3340/4000] Training [1/16] Loss: 0.00321 +Epoch [3340/4000] Training [2/16] Loss: 0.00270 +Epoch [3340/4000] Training [3/16] Loss: 0.00284 +Epoch [3340/4000] Training [4/16] Loss: 0.00339 +Epoch [3340/4000] Training [5/16] Loss: 0.00308 +Epoch [3340/4000] Training [6/16] Loss: 0.00264 +Epoch [3340/4000] Training [7/16] Loss: 0.00249 +Epoch [3340/4000] Training [8/16] Loss: 0.00317 +Epoch [3340/4000] Training [9/16] Loss: 0.00241 +Epoch [3340/4000] Training [10/16] Loss: 0.00291 +Epoch [3340/4000] Training [11/16] Loss: 0.00279 +Epoch [3340/4000] Training [12/16] Loss: 0.00225 +Epoch [3340/4000] Training [13/16] Loss: 0.00285 +Epoch [3340/4000] Training [14/16] Loss: 0.00275 +Epoch [3340/4000] Training [15/16] Loss: 0.00214 +Epoch [3340/4000] Training [16/16] Loss: 0.00281 +Epoch [3340/4000] Training metric {'Train/mean dice_metric': 0.9985027313232422, 'Train/mean miou_metric': 0.996735692024231, 'Train/mean f1': 0.9935781359672546, 'Train/mean precision': 0.9890884160995483, 'Train/mean recall': 0.9981088638305664, 'Train/mean hd95_metric': 0.6454378366470337} +Epoch [3340/4000] Validation [1/4] Loss: 0.36983 focal_loss 0.30916 dice_loss 0.06067 +Epoch [3340/4000] Validation [2/4] Loss: 0.44498 focal_loss 0.33808 dice_loss 0.10690 +Epoch [3340/4000] Validation [3/4] Loss: 0.51738 focal_loss 0.42295 dice_loss 0.09443 +Epoch [3340/4000] Validation [4/4] Loss: 0.60445 focal_loss 0.46853 dice_loss 0.13592 +Epoch [3340/4000] Validation metric {'Val/mean dice_metric': 0.9745914340019226, 'Val/mean miou_metric': 0.9604114294052124, 'Val/mean f1': 0.9766469597816467, 'Val/mean precision': 0.9743772745132446, 'Val/mean recall': 0.978927493095398, 'Val/mean hd95_metric': 4.920094013214111} +Cheakpoint... +Epoch [3340/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745914340019226, 'Val/mean miou_metric': 0.9604114294052124, 'Val/mean f1': 0.9766469597816467, 'Val/mean precision': 0.9743772745132446, 'Val/mean recall': 0.978927493095398, 'Val/mean hd95_metric': 4.920094013214111} +Epoch [3341/4000] Training [1/16] Loss: 0.00272 +Epoch [3341/4000] Training [2/16] Loss: 0.00255 +Epoch [3341/4000] Training [3/16] Loss: 0.00361 +Epoch [3341/4000] Training [4/16] Loss: 0.00209 +Epoch [3341/4000] Training [5/16] Loss: 0.00251 +Epoch [3341/4000] Training [6/16] Loss: 0.00244 +Epoch [3341/4000] Training [7/16] Loss: 0.00190 +Epoch [3341/4000] Training [8/16] Loss: 0.00494 +Epoch [3341/4000] Training [9/16] Loss: 0.00328 +Epoch [3341/4000] Training [10/16] Loss: 0.00222 +Epoch [3341/4000] Training [11/16] Loss: 0.00298 +Epoch [3341/4000] Training [12/16] Loss: 0.00379 +Epoch [3341/4000] Training [13/16] Loss: 0.00247 +Epoch [3341/4000] Training [14/16] Loss: 0.00280 +Epoch [3341/4000] Training [15/16] Loss: 0.00299 +Epoch [3341/4000] Training [16/16] Loss: 0.00363 +Epoch [3341/4000] Training metric {'Train/mean dice_metric': 0.9984828233718872, 'Train/mean miou_metric': 0.9966912269592285, 'Train/mean f1': 0.9935842156410217, 'Train/mean precision': 0.9890626668930054, 'Train/mean recall': 0.9981473088264465, 'Train/mean hd95_metric': 0.6494415998458862} +Epoch [3341/4000] Validation [1/4] Loss: 0.32688 focal_loss 0.26676 dice_loss 0.06012 +Epoch [3341/4000] Validation [2/4] Loss: 0.46053 focal_loss 0.35160 dice_loss 0.10892 +Epoch [3341/4000] Validation [3/4] Loss: 0.52286 focal_loss 0.43176 dice_loss 0.09109 +Epoch [3341/4000] Validation [4/4] Loss: 0.40950 focal_loss 0.29349 dice_loss 0.11600 +Epoch [3341/4000] Validation metric {'Val/mean dice_metric': 0.9746376872062683, 'Val/mean miou_metric': 0.9602395296096802, 'Val/mean f1': 0.9761089086532593, 'Val/mean precision': 0.9738656878471375, 'Val/mean recall': 0.9783623814582825, 'Val/mean hd95_metric': 4.742330551147461} +Cheakpoint... +Epoch [3341/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746376872062683, 'Val/mean miou_metric': 0.9602395296096802, 'Val/mean f1': 0.9761089086532593, 'Val/mean precision': 0.9738656878471375, 'Val/mean recall': 0.9783623814582825, 'Val/mean hd95_metric': 4.742330551147461} +Epoch [3342/4000] Training [1/16] Loss: 0.00263 +Epoch [3342/4000] Training [2/16] Loss: 0.00210 +Epoch [3342/4000] Training [3/16] Loss: 0.00319 +Epoch [3342/4000] Training [4/16] Loss: 0.00307 +Epoch [3342/4000] Training [5/16] Loss: 0.00371 +Epoch [3342/4000] Training [6/16] Loss: 0.00224 +Epoch [3342/4000] Training [7/16] Loss: 0.00254 +Epoch [3342/4000] Training [8/16] Loss: 0.00247 +Epoch [3342/4000] Training [9/16] Loss: 0.00302 +Epoch [3342/4000] Training [10/16] Loss: 0.00222 +Epoch [3342/4000] Training [11/16] Loss: 0.00413 +Epoch [3342/4000] Training [12/16] Loss: 0.00338 +Epoch [3342/4000] Training [13/16] Loss: 0.00206 +Epoch [3342/4000] Training [14/16] Loss: 0.00228 +Epoch [3342/4000] Training [15/16] Loss: 0.00310 +Epoch [3342/4000] Training [16/16] Loss: 0.00298 +Epoch [3342/4000] Training metric {'Train/mean dice_metric': 0.9985175132751465, 'Train/mean miou_metric': 0.9967649579048157, 'Train/mean f1': 0.993613064289093, 'Train/mean precision': 0.9890646934509277, 'Train/mean recall': 0.998203456401825, 'Train/mean hd95_metric': 0.6329261660575867} +Epoch [3342/4000] Validation [1/4] Loss: 0.43819 focal_loss 0.37469 dice_loss 0.06350 +Epoch [3342/4000] Validation [2/4] Loss: 0.46486 focal_loss 0.35492 dice_loss 0.10995 +Epoch [3342/4000] Validation [3/4] Loss: 0.56065 focal_loss 0.45966 dice_loss 0.10099 +Epoch [3342/4000] Validation [4/4] Loss: 0.34787 focal_loss 0.25009 dice_loss 0.09778 +Epoch [3342/4000] Validation metric {'Val/mean dice_metric': 0.9746792912483215, 'Val/mean miou_metric': 0.9602416753768921, 'Val/mean f1': 0.9764117002487183, 'Val/mean precision': 0.9741449952125549, 'Val/mean recall': 0.9786891341209412, 'Val/mean hd95_metric': 5.06585693359375} +Cheakpoint... +Epoch [3342/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746792912483215, 'Val/mean miou_metric': 0.9602416753768921, 'Val/mean f1': 0.9764117002487183, 'Val/mean precision': 0.9741449952125549, 'Val/mean recall': 0.9786891341209412, 'Val/mean hd95_metric': 5.06585693359375} +Epoch [3343/4000] Training [1/16] Loss: 0.00288 +Epoch [3343/4000] Training [2/16] Loss: 0.00259 +Epoch [3343/4000] Training [3/16] Loss: 0.00242 +Epoch [3343/4000] Training [4/16] Loss: 0.00174 +Epoch [3343/4000] Training [5/16] Loss: 0.00404 +Epoch [3343/4000] Training [6/16] Loss: 0.00205 +Epoch [3343/4000] Training [7/16] Loss: 0.00216 +Epoch [3343/4000] Training [8/16] Loss: 0.00333 +Epoch [3343/4000] Training [9/16] Loss: 0.00301 +Epoch [3343/4000] Training [10/16] Loss: 0.00311 +Epoch [3343/4000] Training [11/16] Loss: 0.00273 +Epoch [3343/4000] Training [12/16] Loss: 0.00265 +Epoch [3343/4000] Training [13/16] Loss: 0.00322 +Epoch [3343/4000] Training [14/16] Loss: 0.00252 +Epoch [3343/4000] Training [15/16] Loss: 0.00212 +Epoch [3343/4000] Training [16/16] Loss: 0.00243 +Epoch [3343/4000] Training metric {'Train/mean dice_metric': 0.9985131025314331, 'Train/mean miou_metric': 0.9967563152313232, 'Train/mean f1': 0.9936462044715881, 'Train/mean precision': 0.9891403913497925, 'Train/mean recall': 0.9981932640075684, 'Train/mean hd95_metric': 0.7756540775299072} +Epoch [3343/4000] Validation [1/4] Loss: 0.37862 focal_loss 0.31540 dice_loss 0.06322 +Epoch [3343/4000] Validation [2/4] Loss: 0.48785 focal_loss 0.37446 dice_loss 0.11339 +Epoch [3343/4000] Validation [3/4] Loss: 0.49580 focal_loss 0.40860 dice_loss 0.08720 +Epoch [3343/4000] Validation [4/4] Loss: 0.49371 focal_loss 0.37212 dice_loss 0.12159 +Epoch [3343/4000] Validation metric {'Val/mean dice_metric': 0.9730932116508484, 'Val/mean miou_metric': 0.95892733335495, 'Val/mean f1': 0.9761295914649963, 'Val/mean precision': 0.9750997424125671, 'Val/mean recall': 0.9771616458892822, 'Val/mean hd95_metric': 5.171658992767334} +Cheakpoint... +Epoch [3343/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730932116508484, 'Val/mean miou_metric': 0.95892733335495, 'Val/mean f1': 0.9761295914649963, 'Val/mean precision': 0.9750997424125671, 'Val/mean recall': 0.9771616458892822, 'Val/mean hd95_metric': 5.171658992767334} +Epoch [3344/4000] Training [1/16] Loss: 0.00316 +Epoch [3344/4000] Training [2/16] Loss: 0.00285 +Epoch [3344/4000] Training [3/16] Loss: 0.00237 +Epoch [3344/4000] Training [4/16] Loss: 0.00200 +Epoch [3344/4000] Training [5/16] Loss: 0.00288 +Epoch [3344/4000] Training [6/16] Loss: 0.00364 +Epoch [3344/4000] Training [7/16] Loss: 0.00276 +Epoch [3344/4000] Training [8/16] Loss: 0.00222 +Epoch [3344/4000] Training [9/16] Loss: 0.00281 +Epoch [3344/4000] Training [10/16] Loss: 0.00181 +Epoch [3344/4000] Training [11/16] Loss: 0.00161 +Epoch [3344/4000] Training [12/16] Loss: 0.00215 +Epoch [3344/4000] Training [13/16] Loss: 0.00272 +Epoch [3344/4000] Training [14/16] Loss: 0.00308 +Epoch [3344/4000] Training [15/16] Loss: 0.00281 +Epoch [3344/4000] Training [16/16] Loss: 0.00309 +Epoch [3344/4000] Training metric {'Train/mean dice_metric': 0.9986255168914795, 'Train/mean miou_metric': 0.9969534873962402, 'Train/mean f1': 0.9933680295944214, 'Train/mean precision': 0.9885477423667908, 'Train/mean recall': 0.9982355237007141, 'Train/mean hd95_metric': 0.5894807577133179} +Epoch [3344/4000] Validation [1/4] Loss: 0.38888 focal_loss 0.32602 dice_loss 0.06286 +Epoch [3344/4000] Validation [2/4] Loss: 0.49738 focal_loss 0.38176 dice_loss 0.11563 +Epoch [3344/4000] Validation [3/4] Loss: 0.29089 focal_loss 0.23077 dice_loss 0.06012 +Epoch [3344/4000] Validation [4/4] Loss: 0.35793 focal_loss 0.25693 dice_loss 0.10099 +Epoch [3344/4000] Validation metric {'Val/mean dice_metric': 0.9737415313720703, 'Val/mean miou_metric': 0.9598428606987, 'Val/mean f1': 0.9760066866874695, 'Val/mean precision': 0.9750638604164124, 'Val/mean recall': 0.9769513010978699, 'Val/mean hd95_metric': 4.762979984283447} +Cheakpoint... +Epoch [3344/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737415313720703, 'Val/mean miou_metric': 0.9598428606987, 'Val/mean f1': 0.9760066866874695, 'Val/mean precision': 0.9750638604164124, 'Val/mean recall': 0.9769513010978699, 'Val/mean hd95_metric': 4.762979984283447} +Epoch [3345/4000] Training [1/16] Loss: 0.00287 +Epoch [3345/4000] Training [2/16] Loss: 0.00234 +Epoch [3345/4000] Training [3/16] Loss: 0.00369 +Epoch [3345/4000] Training [4/16] Loss: 0.00413 +Epoch [3345/4000] Training [5/16] Loss: 0.00223 +Epoch [3345/4000] Training [6/16] Loss: 0.00223 +Epoch [3345/4000] Training [7/16] Loss: 0.00193 +Epoch [3345/4000] Training [8/16] Loss: 0.00237 +Epoch [3345/4000] Training [9/16] Loss: 0.00300 +Epoch [3345/4000] Training [10/16] Loss: 0.00276 +Epoch [3345/4000] Training [11/16] Loss: 0.00317 +Epoch [3345/4000] Training [12/16] Loss: 0.00236 +Epoch [3345/4000] Training [13/16] Loss: 0.00268 +Epoch [3345/4000] Training [14/16] Loss: 0.00270 +Epoch [3345/4000] Training [15/16] Loss: 0.00211 +Epoch [3345/4000] Training [16/16] Loss: 0.00295 +Epoch [3345/4000] Training metric {'Train/mean dice_metric': 0.9985288977622986, 'Train/mean miou_metric': 0.9967750906944275, 'Train/mean f1': 0.9936140179634094, 'Train/mean precision': 0.9890245199203491, 'Train/mean recall': 0.9982463121414185, 'Train/mean hd95_metric': 0.6066584587097168} +Epoch [3345/4000] Validation [1/4] Loss: 0.37821 focal_loss 0.31793 dice_loss 0.06029 +Epoch [3345/4000] Validation [2/4] Loss: 0.51018 focal_loss 0.39693 dice_loss 0.11325 +Epoch [3345/4000] Validation [3/4] Loss: 0.27687 focal_loss 0.21854 dice_loss 0.05833 +Epoch [3345/4000] Validation [4/4] Loss: 0.62439 focal_loss 0.49199 dice_loss 0.13240 +Epoch [3345/4000] Validation metric {'Val/mean dice_metric': 0.9736346006393433, 'Val/mean miou_metric': 0.9589725732803345, 'Val/mean f1': 0.975702166557312, 'Val/mean precision': 0.975441575050354, 'Val/mean recall': 0.9759629368782043, 'Val/mean hd95_metric': 5.00807523727417} +Cheakpoint... +Epoch [3345/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736346006393433, 'Val/mean miou_metric': 0.9589725732803345, 'Val/mean f1': 0.975702166557312, 'Val/mean precision': 0.975441575050354, 'Val/mean recall': 0.9759629368782043, 'Val/mean hd95_metric': 5.00807523727417} +Epoch [3346/4000] Training [1/16] Loss: 0.00268 +Epoch [3346/4000] Training [2/16] Loss: 0.00309 +Epoch [3346/4000] Training [3/16] Loss: 0.00246 +Epoch [3346/4000] Training [4/16] Loss: 0.00227 +Epoch [3346/4000] Training [5/16] Loss: 0.00408 +Epoch [3346/4000] Training [6/16] Loss: 0.00174 +Epoch [3346/4000] Training [7/16] Loss: 0.00353 +Epoch [3346/4000] Training [8/16] Loss: 0.00266 +Epoch [3346/4000] Training [9/16] Loss: 0.00290 +Epoch [3346/4000] Training [10/16] Loss: 0.00214 +Epoch [3346/4000] Training [11/16] Loss: 0.00209 +Epoch [3346/4000] Training [12/16] Loss: 0.00163 +Epoch [3346/4000] Training [13/16] Loss: 0.00271 +Epoch [3346/4000] Training [14/16] Loss: 0.00234 +Epoch [3346/4000] Training [15/16] Loss: 0.00249 +Epoch [3346/4000] Training [16/16] Loss: 0.00291 +Epoch [3346/4000] Training metric {'Train/mean dice_metric': 0.9984530210494995, 'Train/mean miou_metric': 0.9966354370117188, 'Train/mean f1': 0.9935620427131653, 'Train/mean precision': 0.9889814257621765, 'Train/mean recall': 0.9981853365898132, 'Train/mean hd95_metric': 0.624840497970581} +Epoch [3346/4000] Validation [1/4] Loss: 0.39382 focal_loss 0.32852 dice_loss 0.06529 +Epoch [3346/4000] Validation [2/4] Loss: 0.68008 focal_loss 0.50104 dice_loss 0.17904 +Epoch [3346/4000] Validation [3/4] Loss: 0.25515 focal_loss 0.19639 dice_loss 0.05875 +Epoch [3346/4000] Validation [4/4] Loss: 0.33693 focal_loss 0.24775 dice_loss 0.08918 +Epoch [3346/4000] Validation metric {'Val/mean dice_metric': 0.9722951054573059, 'Val/mean miou_metric': 0.9584997296333313, 'Val/mean f1': 0.9762482047080994, 'Val/mean precision': 0.9749286770820618, 'Val/mean recall': 0.9775713086128235, 'Val/mean hd95_metric': 5.064027786254883} +Cheakpoint... +Epoch [3346/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722951054573059, 'Val/mean miou_metric': 0.9584997296333313, 'Val/mean f1': 0.9762482047080994, 'Val/mean precision': 0.9749286770820618, 'Val/mean recall': 0.9775713086128235, 'Val/mean hd95_metric': 5.064027786254883} +Epoch [3347/4000] Training [1/16] Loss: 0.00268 +Epoch [3347/4000] Training [2/16] Loss: 0.00257 +Epoch [3347/4000] Training [3/16] Loss: 0.00242 +Epoch [3347/4000] Training [4/16] Loss: 0.00209 +Epoch [3347/4000] Training [5/16] Loss: 0.00203 +Epoch [3347/4000] Training [6/16] Loss: 0.00319 +Epoch [3347/4000] Training [7/16] Loss: 0.00260 +Epoch [3347/4000] Training [8/16] Loss: 0.00299 +Epoch [3347/4000] Training [9/16] Loss: 0.00221 +Epoch [3347/4000] Training [10/16] Loss: 0.00235 +Epoch [3347/4000] Training [11/16] Loss: 0.00250 +Epoch [3347/4000] Training [12/16] Loss: 0.00230 +Epoch [3347/4000] Training [13/16] Loss: 0.00312 +Epoch [3347/4000] Training [14/16] Loss: 0.00294 +Epoch [3347/4000] Training [15/16] Loss: 0.00233 +Epoch [3347/4000] Training [16/16] Loss: 0.00299 +Epoch [3347/4000] Training metric {'Train/mean dice_metric': 0.9985566139221191, 'Train/mean miou_metric': 0.9968436360359192, 'Train/mean f1': 0.9936656951904297, 'Train/mean precision': 0.9891654849052429, 'Train/mean recall': 0.9982070922851562, 'Train/mean hd95_metric': 0.6292545795440674} +Epoch [3347/4000] Validation [1/4] Loss: 0.38538 focal_loss 0.32209 dice_loss 0.06329 +Epoch [3347/4000] Validation [2/4] Loss: 1.01024 focal_loss 0.79966 dice_loss 0.21059 +Epoch [3347/4000] Validation [3/4] Loss: 0.52783 focal_loss 0.43653 dice_loss 0.09131 +Epoch [3347/4000] Validation [4/4] Loss: 0.32923 focal_loss 0.24396 dice_loss 0.08527 +Epoch [3347/4000] Validation metric {'Val/mean dice_metric': 0.9729348421096802, 'Val/mean miou_metric': 0.9591555595397949, 'Val/mean f1': 0.9761103987693787, 'Val/mean precision': 0.9745999574661255, 'Val/mean recall': 0.9776254892349243, 'Val/mean hd95_metric': 4.946681499481201} +Cheakpoint... +Epoch [3347/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729348421096802, 'Val/mean miou_metric': 0.9591555595397949, 'Val/mean f1': 0.9761103987693787, 'Val/mean precision': 0.9745999574661255, 'Val/mean recall': 0.9776254892349243, 'Val/mean hd95_metric': 4.946681499481201} +Epoch [3348/4000] Training [1/16] Loss: 0.00306 +Epoch [3348/4000] Training [2/16] Loss: 0.00186 +Epoch [3348/4000] Training [3/16] Loss: 0.00209 +Epoch [3348/4000] Training [4/16] Loss: 0.00326 +Epoch [3348/4000] Training [5/16] Loss: 0.00342 +Epoch [3348/4000] Training [6/16] Loss: 0.00274 +Epoch [3348/4000] Training [7/16] Loss: 0.00264 +Epoch [3348/4000] Training [8/16] Loss: 0.00398 +Epoch [3348/4000] Training [9/16] Loss: 0.00264 +Epoch [3348/4000] Training [10/16] Loss: 0.00361 +Epoch [3348/4000] Training [11/16] Loss: 0.00175 +Epoch [3348/4000] Training [12/16] Loss: 0.00251 +Epoch [3348/4000] Training [13/16] Loss: 0.00309 +Epoch [3348/4000] Training [14/16] Loss: 0.00235 +Epoch [3348/4000] Training [15/16] Loss: 0.00400 +Epoch [3348/4000] Training [16/16] Loss: 0.00207 +Epoch [3348/4000] Training metric {'Train/mean dice_metric': 0.9985053539276123, 'Train/mean miou_metric': 0.9967020750045776, 'Train/mean f1': 0.9928227066993713, 'Train/mean precision': 0.9876554012298584, 'Train/mean recall': 0.9980444312095642, 'Train/mean hd95_metric': 0.6039338707923889} +Epoch [3348/4000] Validation [1/4] Loss: 0.40853 focal_loss 0.34342 dice_loss 0.06511 +Epoch [3348/4000] Validation [2/4] Loss: 0.48045 focal_loss 0.36978 dice_loss 0.11067 +Epoch [3348/4000] Validation [3/4] Loss: 0.53159 focal_loss 0.43202 dice_loss 0.09956 +Epoch [3348/4000] Validation [4/4] Loss: 0.68948 focal_loss 0.54444 dice_loss 0.14504 +Epoch [3348/4000] Validation metric {'Val/mean dice_metric': 0.9739303588867188, 'Val/mean miou_metric': 0.9593408703804016, 'Val/mean f1': 0.9753643274307251, 'Val/mean precision': 0.9728390574455261, 'Val/mean recall': 0.9779026508331299, 'Val/mean hd95_metric': 4.80088996887207} +Cheakpoint... +Epoch [3348/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739303588867188, 'Val/mean miou_metric': 0.9593408703804016, 'Val/mean f1': 0.9753643274307251, 'Val/mean precision': 0.9728390574455261, 'Val/mean recall': 0.9779026508331299, 'Val/mean hd95_metric': 4.80088996887207} +Epoch [3349/4000] Training [1/16] Loss: 0.00284 +Epoch [3349/4000] Training [2/16] Loss: 0.00238 +Epoch [3349/4000] Training [3/16] Loss: 0.00350 +Epoch [3349/4000] Training [4/16] Loss: 0.00215 +Epoch [3349/4000] Training [5/16] Loss: 0.00276 +Epoch [3349/4000] Training [6/16] Loss: 0.00258 +Epoch [3349/4000] Training [7/16] Loss: 0.00219 +Epoch [3349/4000] Training [8/16] Loss: 0.00355 +Epoch [3349/4000] Training [9/16] Loss: 0.00273 +Epoch [3349/4000] Training [10/16] Loss: 0.00236 +Epoch [3349/4000] Training [11/16] Loss: 0.00229 +Epoch [3349/4000] Training [12/16] Loss: 0.00219 +Epoch [3349/4000] Training [13/16] Loss: 0.00220 +Epoch [3349/4000] Training [14/16] Loss: 0.00253 +Epoch [3349/4000] Training [15/16] Loss: 0.00170 +Epoch [3349/4000] Training [16/16] Loss: 0.00247 +Epoch [3349/4000] Training metric {'Train/mean dice_metric': 0.9986637830734253, 'Train/mean miou_metric': 0.9970182180404663, 'Train/mean f1': 0.9929022789001465, 'Train/mean precision': 0.987657904624939, 'Train/mean recall': 0.9982026219367981, 'Train/mean hd95_metric': 0.5928008556365967} +Epoch [3349/4000] Validation [1/4] Loss: 0.42090 focal_loss 0.35512 dice_loss 0.06577 +Epoch [3349/4000] Validation [2/4] Loss: 0.48806 focal_loss 0.37600 dice_loss 0.11206 +Epoch [3349/4000] Validation [3/4] Loss: 0.51499 focal_loss 0.42407 dice_loss 0.09092 +Epoch [3349/4000] Validation [4/4] Loss: 0.56344 focal_loss 0.43284 dice_loss 0.13060 +Epoch [3349/4000] Validation metric {'Val/mean dice_metric': 0.9762101173400879, 'Val/mean miou_metric': 0.961351215839386, 'Val/mean f1': 0.9756847023963928, 'Val/mean precision': 0.9737628698348999, 'Val/mean recall': 0.977614164352417, 'Val/mean hd95_metric': 4.677059173583984} +Cheakpoint... +Epoch [3349/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9762101173400879, 'Val/mean miou_metric': 0.961351215839386, 'Val/mean f1': 0.9756847023963928, 'Val/mean precision': 0.9737628698348999, 'Val/mean recall': 0.977614164352417, 'Val/mean hd95_metric': 4.677059173583984} +Epoch [3350/4000] Training [1/16] Loss: 0.00335 +Epoch [3350/4000] Training [2/16] Loss: 0.00292 +Epoch [3350/4000] Training [3/16] Loss: 0.00299 +Epoch [3350/4000] Training [4/16] Loss: 0.00289 +Epoch [3350/4000] Training [5/16] Loss: 0.00245 +Epoch [3350/4000] Training [6/16] Loss: 0.00212 +Epoch [3350/4000] Training [7/16] Loss: 0.00332 +Epoch [3350/4000] Training [8/16] Loss: 0.00242 +Epoch [3350/4000] Training [9/16] Loss: 0.00228 +Epoch [3350/4000] Training [10/16] Loss: 0.00315 +Epoch [3350/4000] Training [11/16] Loss: 0.00196 +Epoch [3350/4000] Training [12/16] Loss: 0.00277 +Epoch [3350/4000] Training [13/16] Loss: 0.00299 +Epoch [3350/4000] Training [14/16] Loss: 0.00363 +Epoch [3350/4000] Training [15/16] Loss: 0.00215 +Epoch [3350/4000] Training [16/16] Loss: 0.00232 +Epoch [3350/4000] Training metric {'Train/mean dice_metric': 0.9986296892166138, 'Train/mean miou_metric': 0.9969685673713684, 'Train/mean f1': 0.9934120178222656, 'Train/mean precision': 0.9886165857315063, 'Train/mean recall': 0.9982542395591736, 'Train/mean hd95_metric': 0.5889224410057068} +Epoch [3350/4000] Validation [1/4] Loss: 0.43181 focal_loss 0.36509 dice_loss 0.06672 +Epoch [3350/4000] Validation [2/4] Loss: 1.15629 focal_loss 0.89102 dice_loss 0.26528 +Epoch [3350/4000] Validation [3/4] Loss: 0.53565 focal_loss 0.44268 dice_loss 0.09297 +Epoch [3350/4000] Validation [4/4] Loss: 0.32828 focal_loss 0.23983 dice_loss 0.08845 +Epoch [3350/4000] Validation metric {'Val/mean dice_metric': 0.9727832674980164, 'Val/mean miou_metric': 0.9588168859481812, 'Val/mean f1': 0.9755715727806091, 'Val/mean precision': 0.9732878804206848, 'Val/mean recall': 0.9778658151626587, 'Val/mean hd95_metric': 4.922150611877441} +Cheakpoint... +Epoch [3350/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727832674980164, 'Val/mean miou_metric': 0.9588168859481812, 'Val/mean f1': 0.9755715727806091, 'Val/mean precision': 0.9732878804206848, 'Val/mean recall': 0.9778658151626587, 'Val/mean hd95_metric': 4.922150611877441} +Epoch [3351/4000] Training [1/16] Loss: 0.00217 +Epoch [3351/4000] Training [2/16] Loss: 0.00880 +Epoch [3351/4000] Training [3/16] Loss: 0.00249 +Epoch [3351/4000] Training [4/16] Loss: 0.00197 +Epoch [3351/4000] Training [5/16] Loss: 0.00337 +Epoch [3351/4000] Training [6/16] Loss: 0.00225 +Epoch [3351/4000] Training [7/16] Loss: 0.00151 +Epoch [3351/4000] Training [8/16] Loss: 0.00258 +Epoch [3351/4000] Training [9/16] Loss: 0.00235 +Epoch [3351/4000] Training [10/16] Loss: 0.00274 +Epoch [3351/4000] Training [11/16] Loss: 0.00281 +Epoch [3351/4000] Training [12/16] Loss: 0.00266 +Epoch [3351/4000] Training [13/16] Loss: 0.00291 +Epoch [3351/4000] Training [14/16] Loss: 0.00187 +Epoch [3351/4000] Training [15/16] Loss: 0.00227 +Epoch [3351/4000] Training [16/16] Loss: 0.00258 +Epoch [3351/4000] Training metric {'Train/mean dice_metric': 0.9985098242759705, 'Train/mean miou_metric': 0.9967318773269653, 'Train/mean f1': 0.9933455586433411, 'Train/mean precision': 0.9886290431022644, 'Train/mean recall': 0.9981072545051575, 'Train/mean hd95_metric': 0.6153779029846191} +Epoch [3351/4000] Validation [1/4] Loss: 0.40246 focal_loss 0.33930 dice_loss 0.06315 +Epoch [3351/4000] Validation [2/4] Loss: 0.48243 focal_loss 0.35157 dice_loss 0.13086 +Epoch [3351/4000] Validation [3/4] Loss: 0.55198 focal_loss 0.45438 dice_loss 0.09760 +Epoch [3351/4000] Validation [4/4] Loss: 0.30871 focal_loss 0.21316 dice_loss 0.09555 +Epoch [3351/4000] Validation metric {'Val/mean dice_metric': 0.9742556810379028, 'Val/mean miou_metric': 0.9599252939224243, 'Val/mean f1': 0.9763004779815674, 'Val/mean precision': 0.9731320738792419, 'Val/mean recall': 0.9794893264770508, 'Val/mean hd95_metric': 4.902461051940918} +Cheakpoint... +Epoch [3351/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742556810379028, 'Val/mean miou_metric': 0.9599252939224243, 'Val/mean f1': 0.9763004779815674, 'Val/mean precision': 0.9731320738792419, 'Val/mean recall': 0.9794893264770508, 'Val/mean hd95_metric': 4.902461051940918} +Epoch [3352/4000] Training [1/16] Loss: 0.00206 +Epoch [3352/4000] Training [2/16] Loss: 0.00210 +Epoch [3352/4000] Training [3/16] Loss: 0.00238 +Epoch [3352/4000] Training [4/16] Loss: 0.00215 +Epoch [3352/4000] Training [5/16] Loss: 0.00423 +Epoch [3352/4000] Training [6/16] Loss: 0.00261 +Epoch [3352/4000] Training [7/16] Loss: 0.00228 +Epoch [3352/4000] Training [8/16] Loss: 0.00282 +Epoch [3352/4000] Training [9/16] Loss: 0.00296 +Epoch [3352/4000] Training [10/16] Loss: 0.00266 +Epoch [3352/4000] Training [11/16] Loss: 0.00294 +Epoch [3352/4000] Training [12/16] Loss: 0.00305 +Epoch [3352/4000] Training [13/16] Loss: 0.00312 +Epoch [3352/4000] Training [14/16] Loss: 0.00226 +Epoch [3352/4000] Training [15/16] Loss: 0.00266 +Epoch [3352/4000] Training [16/16] Loss: 0.00298 +Epoch [3352/4000] Training metric {'Train/mean dice_metric': 0.9984787702560425, 'Train/mean miou_metric': 0.9966697096824646, 'Train/mean f1': 0.9933894872665405, 'Train/mean precision': 0.9886583089828491, 'Train/mean recall': 0.9981661438941956, 'Train/mean hd95_metric': 0.6243884563446045} +Epoch [3352/4000] Validation [1/4] Loss: 0.36602 focal_loss 0.30629 dice_loss 0.05972 +Epoch [3352/4000] Validation [2/4] Loss: 1.24007 focal_loss 1.02565 dice_loss 0.21442 +Epoch [3352/4000] Validation [3/4] Loss: 0.48739 focal_loss 0.38988 dice_loss 0.09751 +Epoch [3352/4000] Validation [4/4] Loss: 0.43222 focal_loss 0.32513 dice_loss 0.10709 +Epoch [3352/4000] Validation metric {'Val/mean dice_metric': 0.9741579294204712, 'Val/mean miou_metric': 0.9601650238037109, 'Val/mean f1': 0.976201593875885, 'Val/mean precision': 0.9726501107215881, 'Val/mean recall': 0.9797791242599487, 'Val/mean hd95_metric': 4.9290361404418945} +Cheakpoint... +Epoch [3352/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741579294204712, 'Val/mean miou_metric': 0.9601650238037109, 'Val/mean f1': 0.976201593875885, 'Val/mean precision': 0.9726501107215881, 'Val/mean recall': 0.9797791242599487, 'Val/mean hd95_metric': 4.9290361404418945} +Epoch [3353/4000] Training [1/16] Loss: 0.00213 +Epoch [3353/4000] Training [2/16] Loss: 0.00283 +Epoch [3353/4000] Training [3/16] Loss: 0.00226 +Epoch [3353/4000] Training [4/16] Loss: 0.00193 +Epoch [3353/4000] Training [5/16] Loss: 0.00207 +Epoch [3353/4000] Training [6/16] Loss: 0.00268 +Epoch [3353/4000] Training [7/16] Loss: 0.00247 +Epoch [3353/4000] Training [8/16] Loss: 0.00198 +Epoch [3353/4000] Training [9/16] Loss: 0.00195 +Epoch [3353/4000] Training [10/16] Loss: 0.00239 +Epoch [3353/4000] Training [11/16] Loss: 0.00280 +Epoch [3353/4000] Training [12/16] Loss: 0.00231 +Epoch [3353/4000] Training [13/16] Loss: 0.00250 +Epoch [3353/4000] Training [14/16] Loss: 0.00292 +Epoch [3353/4000] Training [15/16] Loss: 0.00280 +Epoch [3353/4000] Training [16/16] Loss: 0.00254 +Epoch [3353/4000] Training metric {'Train/mean dice_metric': 0.9987471103668213, 'Train/mean miou_metric': 0.9972002506256104, 'Train/mean f1': 0.9936355948448181, 'Train/mean precision': 0.9889919757843018, 'Train/mean recall': 0.9983229637145996, 'Train/mean hd95_metric': 0.5765900611877441} +Epoch [3353/4000] Validation [1/4] Loss: 0.38407 focal_loss 0.32164 dice_loss 0.06243 +Epoch [3353/4000] Validation [2/4] Loss: 0.42699 focal_loss 0.32130 dice_loss 0.10569 +Epoch [3353/4000] Validation [3/4] Loss: 0.56107 focal_loss 0.46536 dice_loss 0.09571 +Epoch [3353/4000] Validation [4/4] Loss: 0.39587 focal_loss 0.28333 dice_loss 0.11254 +Epoch [3353/4000] Validation metric {'Val/mean dice_metric': 0.9747330546379089, 'Val/mean miou_metric': 0.9606989026069641, 'Val/mean f1': 0.9763378500938416, 'Val/mean precision': 0.9729294776916504, 'Val/mean recall': 0.979770302772522, 'Val/mean hd95_metric': 4.813014984130859} +Cheakpoint... +Epoch [3353/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747330546379089, 'Val/mean miou_metric': 0.9606989026069641, 'Val/mean f1': 0.9763378500938416, 'Val/mean precision': 0.9729294776916504, 'Val/mean recall': 0.979770302772522, 'Val/mean hd95_metric': 4.813014984130859} +Epoch [3354/4000] Training [1/16] Loss: 0.00282 +Epoch [3354/4000] Training [2/16] Loss: 0.00215 +Epoch [3354/4000] Training [3/16] Loss: 0.00276 +Epoch [3354/4000] Training [4/16] Loss: 0.00231 +Epoch [3354/4000] Training [5/16] Loss: 0.00223 +Epoch [3354/4000] Training [6/16] Loss: 0.00260 +Epoch [3354/4000] Training [7/16] Loss: 0.00366 +Epoch [3354/4000] Training [8/16] Loss: 0.00324 +Epoch [3354/4000] Training [9/16] Loss: 0.00299 +Epoch [3354/4000] Training [10/16] Loss: 0.00276 +Epoch [3354/4000] Training [11/16] Loss: 0.00231 +Epoch [3354/4000] Training [12/16] Loss: 0.00266 +Epoch [3354/4000] Training [13/16] Loss: 0.00338 +Epoch [3354/4000] Training [14/16] Loss: 0.00177 +Epoch [3354/4000] Training [15/16] Loss: 0.00277 +Epoch [3354/4000] Training [16/16] Loss: 0.00261 +Epoch [3354/4000] Training metric {'Train/mean dice_metric': 0.9985625743865967, 'Train/mean miou_metric': 0.9968069791793823, 'Train/mean f1': 0.9925785660743713, 'Train/mean precision': 0.9871009588241577, 'Train/mean recall': 0.9981172680854797, 'Train/mean hd95_metric': 0.6067659258842468} +Epoch [3354/4000] Validation [1/4] Loss: 0.35933 focal_loss 0.29660 dice_loss 0.06274 +Epoch [3354/4000] Validation [2/4] Loss: 0.42090 focal_loss 0.31749 dice_loss 0.10341 +Epoch [3354/4000] Validation [3/4] Loss: 0.56100 focal_loss 0.46106 dice_loss 0.09994 +Epoch [3354/4000] Validation [4/4] Loss: 0.33261 focal_loss 0.22968 dice_loss 0.10293 +Epoch [3354/4000] Validation metric {'Val/mean dice_metric': 0.9738929867744446, 'Val/mean miou_metric': 0.9597393274307251, 'Val/mean f1': 0.975389838218689, 'Val/mean precision': 0.9719753265380859, 'Val/mean recall': 0.9788283705711365, 'Val/mean hd95_metric': 4.985832214355469} +Cheakpoint... +Epoch [3354/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738929867744446, 'Val/mean miou_metric': 0.9597393274307251, 'Val/mean f1': 0.975389838218689, 'Val/mean precision': 0.9719753265380859, 'Val/mean recall': 0.9788283705711365, 'Val/mean hd95_metric': 4.985832214355469} +Epoch [3355/4000] Training [1/16] Loss: 0.00327 +Epoch [3355/4000] Training [2/16] Loss: 0.00288 +Epoch [3355/4000] Training [3/16] Loss: 0.00220 +Epoch [3355/4000] Training [4/16] Loss: 0.00386 +Epoch [3355/4000] Training [5/16] Loss: 0.00267 +Epoch [3355/4000] Training [6/16] Loss: 0.00218 +Epoch [3355/4000] Training [7/16] Loss: 0.00304 +Epoch [3355/4000] Training [8/16] Loss: 0.00284 +Epoch [3355/4000] Training [9/16] Loss: 0.00238 +Epoch [3355/4000] Training [10/16] Loss: 0.00298 +Epoch [3355/4000] Training [11/16] Loss: 0.00312 +Epoch [3355/4000] Training [12/16] Loss: 0.00339 +Epoch [3355/4000] Training [13/16] Loss: 0.00190 +Epoch [3355/4000] Training [14/16] Loss: 0.00188 +Epoch [3355/4000] Training [15/16] Loss: 0.00205 +Epoch [3355/4000] Training [16/16] Loss: 0.00314 +Epoch [3355/4000] Training metric {'Train/mean dice_metric': 0.998611569404602, 'Train/mean miou_metric': 0.9969460964202881, 'Train/mean f1': 0.9935381412506104, 'Train/mean precision': 0.9889189600944519, 'Train/mean recall': 0.9982006549835205, 'Train/mean hd95_metric': 0.5999021530151367} +Epoch [3355/4000] Validation [1/4] Loss: 0.39266 focal_loss 0.32982 dice_loss 0.06284 +Epoch [3355/4000] Validation [2/4] Loss: 0.43272 focal_loss 0.32807 dice_loss 0.10465 +Epoch [3355/4000] Validation [3/4] Loss: 0.51787 focal_loss 0.42742 dice_loss 0.09045 +Epoch [3355/4000] Validation [4/4] Loss: 0.35585 focal_loss 0.26254 dice_loss 0.09332 +Epoch [3355/4000] Validation metric {'Val/mean dice_metric': 0.9748279452323914, 'Val/mean miou_metric': 0.9606813192367554, 'Val/mean f1': 0.9763235449790955, 'Val/mean precision': 0.9738660454750061, 'Val/mean recall': 0.9787936210632324, 'Val/mean hd95_metric': 4.73461389541626} +Cheakpoint... +Epoch [3355/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748279452323914, 'Val/mean miou_metric': 0.9606813192367554, 'Val/mean f1': 0.9763235449790955, 'Val/mean precision': 0.9738660454750061, 'Val/mean recall': 0.9787936210632324, 'Val/mean hd95_metric': 4.73461389541626} +Epoch [3356/4000] Training [1/16] Loss: 0.00223 +Epoch [3356/4000] Training [2/16] Loss: 0.00257 +Epoch [3356/4000] Training [3/16] Loss: 0.00244 +Epoch [3356/4000] Training [4/16] Loss: 0.00223 +Epoch [3356/4000] Training [5/16] Loss: 0.00201 +Epoch [3356/4000] Training [6/16] Loss: 0.00296 +Epoch [3356/4000] Training [7/16] Loss: 0.00220 +Epoch [3356/4000] Training [8/16] Loss: 0.00398 +Epoch [3356/4000] Training [9/16] Loss: 0.00249 +Epoch [3356/4000] Training [10/16] Loss: 0.00276 +Epoch [3356/4000] Training [11/16] Loss: 0.00213 +Epoch [3356/4000] Training [12/16] Loss: 0.00214 +Epoch [3356/4000] Training [13/16] Loss: 0.00224 +Epoch [3356/4000] Training [14/16] Loss: 0.00212 +Epoch [3356/4000] Training [15/16] Loss: 0.00264 +Epoch [3356/4000] Training [16/16] Loss: 0.00352 +Epoch [3356/4000] Training metric {'Train/mean dice_metric': 0.9986069202423096, 'Train/mean miou_metric': 0.996942400932312, 'Train/mean f1': 0.9936760067939758, 'Train/mean precision': 0.9891390800476074, 'Train/mean recall': 0.9982547760009766, 'Train/mean hd95_metric': 0.5784454941749573} +Epoch [3356/4000] Validation [1/4] Loss: 0.36762 focal_loss 0.30688 dice_loss 0.06074 +Epoch [3356/4000] Validation [2/4] Loss: 0.43130 focal_loss 0.32526 dice_loss 0.10604 +Epoch [3356/4000] Validation [3/4] Loss: 0.51292 focal_loss 0.42363 dice_loss 0.08929 +Epoch [3356/4000] Validation [4/4] Loss: 0.36756 focal_loss 0.26833 dice_loss 0.09923 +Epoch [3356/4000] Validation metric {'Val/mean dice_metric': 0.9748020172119141, 'Val/mean miou_metric': 0.9606486558914185, 'Val/mean f1': 0.976009726524353, 'Val/mean precision': 0.9724681973457336, 'Val/mean recall': 0.9795773029327393, 'Val/mean hd95_metric': 5.2599639892578125} +Cheakpoint... +Epoch [3356/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748020172119141, 'Val/mean miou_metric': 0.9606486558914185, 'Val/mean f1': 0.976009726524353, 'Val/mean precision': 0.9724681973457336, 'Val/mean recall': 0.9795773029327393, 'Val/mean hd95_metric': 5.2599639892578125} +Epoch [3357/4000] Training [1/16] Loss: 0.00250 +Epoch [3357/4000] Training [2/16] Loss: 0.00217 +Epoch [3357/4000] Training [3/16] Loss: 0.00349 +Epoch [3357/4000] Training [4/16] Loss: 0.00307 +Epoch [3357/4000] Training [5/16] Loss: 0.00361 +Epoch [3357/4000] Training [6/16] Loss: 0.00266 +Epoch [3357/4000] Training [7/16] Loss: 0.00342 +Epoch [3357/4000] Training [8/16] Loss: 0.00190 +Epoch [3357/4000] Training [9/16] Loss: 0.00171 +Epoch [3357/4000] Training [10/16] Loss: 0.00469 +Epoch [3357/4000] Training [11/16] Loss: 0.00222 +Epoch [3357/4000] Training [12/16] Loss: 0.00237 +Epoch [3357/4000] Training [13/16] Loss: 0.00303 +Epoch [3357/4000] Training [14/16] Loss: 0.00239 +Epoch [3357/4000] Training [15/16] Loss: 0.00333 +Epoch [3357/4000] Training [16/16] Loss: 0.00303 +Epoch [3357/4000] Training metric {'Train/mean dice_metric': 0.9984571933746338, 'Train/mean miou_metric': 0.9966437220573425, 'Train/mean f1': 0.9934923052787781, 'Train/mean precision': 0.9889225363731384, 'Train/mean recall': 0.9981045126914978, 'Train/mean hd95_metric': 0.6423683166503906} +Epoch [3357/4000] Validation [1/4] Loss: 0.36241 focal_loss 0.30055 dice_loss 0.06186 +Epoch [3357/4000] Validation [2/4] Loss: 0.44302 focal_loss 0.33417 dice_loss 0.10885 +Epoch [3357/4000] Validation [3/4] Loss: 0.51240 focal_loss 0.42084 dice_loss 0.09156 +Epoch [3357/4000] Validation [4/4] Loss: 0.33192 focal_loss 0.24260 dice_loss 0.08932 +Epoch [3357/4000] Validation metric {'Val/mean dice_metric': 0.9753043055534363, 'Val/mean miou_metric': 0.9607483148574829, 'Val/mean f1': 0.9762137532234192, 'Val/mean precision': 0.9733262658119202, 'Val/mean recall': 0.9791184067726135, 'Val/mean hd95_metric': 4.834566593170166} +Cheakpoint... +Epoch [3357/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753043055534363, 'Val/mean miou_metric': 0.9607483148574829, 'Val/mean f1': 0.9762137532234192, 'Val/mean precision': 0.9733262658119202, 'Val/mean recall': 0.9791184067726135, 'Val/mean hd95_metric': 4.834566593170166} +Epoch [3358/4000] Training [1/16] Loss: 0.00325 +Epoch [3358/4000] Training [2/16] Loss: 0.00238 +Epoch [3358/4000] Training [3/16] Loss: 0.00201 +Epoch [3358/4000] Training [4/16] Loss: 0.00342 +Epoch [3358/4000] Training [5/16] Loss: 0.00248 +Epoch [3358/4000] Training [6/16] Loss: 0.00302 +Epoch [3358/4000] Training [7/16] Loss: 0.00233 +Epoch [3358/4000] Training [8/16] Loss: 0.00267 +Epoch [3358/4000] Training [9/16] Loss: 0.00207 +Epoch [3358/4000] Training [10/16] Loss: 0.00273 +Epoch [3358/4000] Training [11/16] Loss: 0.00280 +Epoch [3358/4000] Training [12/16] Loss: 0.00208 +Epoch [3358/4000] Training [13/16] Loss: 0.00202 +Epoch [3358/4000] Training [14/16] Loss: 0.00361 +Epoch [3358/4000] Training [15/16] Loss: 0.00339 +Epoch [3358/4000] Training [16/16] Loss: 0.00239 +Epoch [3358/4000] Training metric {'Train/mean dice_metric': 0.9986472725868225, 'Train/mean miou_metric': 0.9969980716705322, 'Train/mean f1': 0.9934090971946716, 'Train/mean precision': 0.9885951280593872, 'Train/mean recall': 0.9982700943946838, 'Train/mean hd95_metric': 0.6043522357940674} +Epoch [3358/4000] Validation [1/4] Loss: 0.40294 focal_loss 0.33947 dice_loss 0.06347 +Epoch [3358/4000] Validation [2/4] Loss: 0.46923 focal_loss 0.33724 dice_loss 0.13199 +Epoch [3358/4000] Validation [3/4] Loss: 0.26682 focal_loss 0.20217 dice_loss 0.06465 +Epoch [3358/4000] Validation [4/4] Loss: 0.33660 focal_loss 0.22877 dice_loss 0.10783 +Epoch [3358/4000] Validation metric {'Val/mean dice_metric': 0.9734746813774109, 'Val/mean miou_metric': 0.9595977663993835, 'Val/mean f1': 0.975565493106842, 'Val/mean precision': 0.9726248383522034, 'Val/mean recall': 0.9785239696502686, 'Val/mean hd95_metric': 5.279764652252197} +Cheakpoint... +Epoch [3358/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734746813774109, 'Val/mean miou_metric': 0.9595977663993835, 'Val/mean f1': 0.975565493106842, 'Val/mean precision': 0.9726248383522034, 'Val/mean recall': 0.9785239696502686, 'Val/mean hd95_metric': 5.279764652252197} +Epoch [3359/4000] Training [1/16] Loss: 0.00345 +Epoch [3359/4000] Training [2/16] Loss: 0.00380 +Epoch [3359/4000] Training [3/16] Loss: 0.00260 +Epoch [3359/4000] Training [4/16] Loss: 0.00277 +Epoch [3359/4000] Training [5/16] Loss: 0.00238 +Epoch [3359/4000] Training [6/16] Loss: 0.00224 +Epoch [3359/4000] Training [7/16] Loss: 0.00354 +Epoch [3359/4000] Training [8/16] Loss: 0.00189 +Epoch [3359/4000] Training [9/16] Loss: 0.00299 +Epoch [3359/4000] Training [10/16] Loss: 0.00221 +Epoch [3359/4000] Training [11/16] Loss: 0.00249 +Epoch [3359/4000] Training [12/16] Loss: 0.00417 +Epoch [3359/4000] Training [13/16] Loss: 0.00238 +Epoch [3359/4000] Training [14/16] Loss: 0.00188 +Epoch [3359/4000] Training [15/16] Loss: 0.00342 +Epoch [3359/4000] Training [16/16] Loss: 0.00192 +Epoch [3359/4000] Training metric {'Train/mean dice_metric': 0.9986274838447571, 'Train/mean miou_metric': 0.996971845626831, 'Train/mean f1': 0.9936279058456421, 'Train/mean precision': 0.9890223145484924, 'Train/mean recall': 0.9982765913009644, 'Train/mean hd95_metric': 0.6200470924377441} +Epoch [3359/4000] Validation [1/4] Loss: 0.37013 focal_loss 0.30746 dice_loss 0.06267 +Epoch [3359/4000] Validation [2/4] Loss: 0.79976 focal_loss 0.61529 dice_loss 0.18447 +Epoch [3359/4000] Validation [3/4] Loss: 0.51896 focal_loss 0.42261 dice_loss 0.09635 +Epoch [3359/4000] Validation [4/4] Loss: 0.29279 focal_loss 0.20142 dice_loss 0.09137 +Epoch [3359/4000] Validation metric {'Val/mean dice_metric': 0.9738909006118774, 'Val/mean miou_metric': 0.960150420665741, 'Val/mean f1': 0.9763965010643005, 'Val/mean precision': 0.9739294648170471, 'Val/mean recall': 0.9788761138916016, 'Val/mean hd95_metric': 4.804998397827148} +Cheakpoint... +Epoch [3359/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738909006118774, 'Val/mean miou_metric': 0.960150420665741, 'Val/mean f1': 0.9763965010643005, 'Val/mean precision': 0.9739294648170471, 'Val/mean recall': 0.9788761138916016, 'Val/mean hd95_metric': 4.804998397827148} +Epoch [3360/4000] Training [1/16] Loss: 0.00342 +Epoch [3360/4000] Training [2/16] Loss: 0.00240 +Epoch [3360/4000] Training [3/16] Loss: 0.00327 +Epoch [3360/4000] Training [4/16] Loss: 0.00225 +Epoch [3360/4000] Training [5/16] Loss: 0.00278 +Epoch [3360/4000] Training [6/16] Loss: 0.00278 +Epoch [3360/4000] Training [7/16] Loss: 0.00247 +Epoch [3360/4000] Training [8/16] Loss: 0.00190 +Epoch [3360/4000] Training [9/16] Loss: 0.00294 +Epoch [3360/4000] Training [10/16] Loss: 0.00219 +Epoch [3360/4000] Training [11/16] Loss: 0.00240 +Epoch [3360/4000] Training [12/16] Loss: 0.00226 +Epoch [3360/4000] Training [13/16] Loss: 0.00291 +Epoch [3360/4000] Training [14/16] Loss: 0.00387 +Epoch [3360/4000] Training [15/16] Loss: 0.00221 +Epoch [3360/4000] Training [16/16] Loss: 0.00230 +Epoch [3360/4000] Training metric {'Train/mean dice_metric': 0.9986662864685059, 'Train/mean miou_metric': 0.9970256090164185, 'Train/mean f1': 0.9929701685905457, 'Train/mean precision': 0.987734854221344, 'Train/mean recall': 0.9982612133026123, 'Train/mean hd95_metric': 0.62717604637146} +Epoch [3360/4000] Validation [1/4] Loss: 0.45766 focal_loss 0.39153 dice_loss 0.06613 +Epoch [3360/4000] Validation [2/4] Loss: 0.42095 focal_loss 0.31617 dice_loss 0.10477 +Epoch [3360/4000] Validation [3/4] Loss: 0.52269 focal_loss 0.42559 dice_loss 0.09710 +Epoch [3360/4000] Validation [4/4] Loss: 0.27722 focal_loss 0.18667 dice_loss 0.09055 +Epoch [3360/4000] Validation metric {'Val/mean dice_metric': 0.975486159324646, 'Val/mean miou_metric': 0.9615284204483032, 'Val/mean f1': 0.9763596057891846, 'Val/mean precision': 0.9731115102767944, 'Val/mean recall': 0.979629397392273, 'Val/mean hd95_metric': 4.838985443115234} +Cheakpoint... +Epoch [3360/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975486159324646, 'Val/mean miou_metric': 0.9615284204483032, 'Val/mean f1': 0.9763596057891846, 'Val/mean precision': 0.9731115102767944, 'Val/mean recall': 0.979629397392273, 'Val/mean hd95_metric': 4.838985443115234} +Epoch [3361/4000] Training [1/16] Loss: 0.00198 +Epoch [3361/4000] Training [2/16] Loss: 0.00247 +Epoch [3361/4000] Training [3/16] Loss: 0.00213 +Epoch [3361/4000] Training [4/16] Loss: 0.00273 +Epoch [3361/4000] Training [5/16] Loss: 0.00171 +Epoch [3361/4000] Training [6/16] Loss: 0.00308 +Epoch [3361/4000] Training [7/16] Loss: 0.00257 +Epoch [3361/4000] Training [8/16] Loss: 0.00233 +Epoch [3361/4000] Training [9/16] Loss: 0.00334 +Epoch [3361/4000] Training [10/16] Loss: 0.00474 +Epoch [3361/4000] Training [11/16] Loss: 0.00248 +Epoch [3361/4000] Training [12/16] Loss: 0.00282 +Epoch [3361/4000] Training [13/16] Loss: 0.00248 +Epoch [3361/4000] Training [14/16] Loss: 0.00258 +Epoch [3361/4000] Training [15/16] Loss: 0.00239 +Epoch [3361/4000] Training [16/16] Loss: 0.00166 +Epoch [3361/4000] Training metric {'Train/mean dice_metric': 0.9986748099327087, 'Train/mean miou_metric': 0.9970492124557495, 'Train/mean f1': 0.9934194684028625, 'Train/mean precision': 0.988605260848999, 'Train/mean recall': 0.9982807636260986, 'Train/mean hd95_metric': 0.6033479571342468} +Epoch [3361/4000] Validation [1/4] Loss: 0.35394 focal_loss 0.29048 dice_loss 0.06346 +Epoch [3361/4000] Validation [2/4] Loss: 0.53305 focal_loss 0.37626 dice_loss 0.15680 +Epoch [3361/4000] Validation [3/4] Loss: 0.51745 focal_loss 0.42210 dice_loss 0.09536 +Epoch [3361/4000] Validation [4/4] Loss: 0.33054 focal_loss 0.23853 dice_loss 0.09201 +Epoch [3361/4000] Validation metric {'Val/mean dice_metric': 0.972734808921814, 'Val/mean miou_metric': 0.9585241079330444, 'Val/mean f1': 0.9761663675308228, 'Val/mean precision': 0.9737382531166077, 'Val/mean recall': 0.9786065220832825, 'Val/mean hd95_metric': 5.3873724937438965} +Cheakpoint... +Epoch [3361/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972734808921814, 'Val/mean miou_metric': 0.9585241079330444, 'Val/mean f1': 0.9761663675308228, 'Val/mean precision': 0.9737382531166077, 'Val/mean recall': 0.9786065220832825, 'Val/mean hd95_metric': 5.3873724937438965} +Epoch [3362/4000] Training [1/16] Loss: 0.00249 +Epoch [3362/4000] Training [2/16] Loss: 0.00323 +Epoch [3362/4000] Training [3/16] Loss: 0.00287 +Epoch [3362/4000] Training [4/16] Loss: 0.00370 +Epoch [3362/4000] Training [5/16] Loss: 0.00316 +Epoch [3362/4000] Training [6/16] Loss: 0.00295 +Epoch [3362/4000] Training [7/16] Loss: 0.00260 +Epoch [3362/4000] Training [8/16] Loss: 0.00316 +Epoch [3362/4000] Training [9/16] Loss: 0.00190 +Epoch [3362/4000] Training [10/16] Loss: 0.00187 +Epoch [3362/4000] Training [11/16] Loss: 0.00250 +Epoch [3362/4000] Training [12/16] Loss: 0.00325 +Epoch [3362/4000] Training [13/16] Loss: 0.00220 +Epoch [3362/4000] Training [14/16] Loss: 0.00197 +Epoch [3362/4000] Training [15/16] Loss: 0.00257 +Epoch [3362/4000] Training [16/16] Loss: 0.00252 +Epoch [3362/4000] Training metric {'Train/mean dice_metric': 0.9985854029655457, 'Train/mean miou_metric': 0.9968994855880737, 'Train/mean f1': 0.9936957359313965, 'Train/mean precision': 0.9892122149467468, 'Train/mean recall': 0.9982200860977173, 'Train/mean hd95_metric': 0.5806217193603516} +Epoch [3362/4000] Validation [1/4] Loss: 0.45234 focal_loss 0.38543 dice_loss 0.06690 +Epoch [3362/4000] Validation [2/4] Loss: 0.44167 focal_loss 0.33315 dice_loss 0.10852 +Epoch [3362/4000] Validation [3/4] Loss: 0.52474 focal_loss 0.43368 dice_loss 0.09106 +Epoch [3362/4000] Validation [4/4] Loss: 0.33542 focal_loss 0.23780 dice_loss 0.09762 +Epoch [3362/4000] Validation metric {'Val/mean dice_metric': 0.9737182855606079, 'Val/mean miou_metric': 0.9595638513565063, 'Val/mean f1': 0.9765779972076416, 'Val/mean precision': 0.9747115969657898, 'Val/mean recall': 0.9784514904022217, 'Val/mean hd95_metric': 5.026210308074951} +Cheakpoint... +Epoch [3362/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737182855606079, 'Val/mean miou_metric': 0.9595638513565063, 'Val/mean f1': 0.9765779972076416, 'Val/mean precision': 0.9747115969657898, 'Val/mean recall': 0.9784514904022217, 'Val/mean hd95_metric': 5.026210308074951} +Epoch [3363/4000] Training [1/16] Loss: 0.00200 +Epoch [3363/4000] Training [2/16] Loss: 0.00278 +Epoch [3363/4000] Training [3/16] Loss: 0.00213 +Epoch [3363/4000] Training [4/16] Loss: 0.00510 +Epoch [3363/4000] Training [5/16] Loss: 0.00248 +Epoch [3363/4000] Training [6/16] Loss: 0.00293 +Epoch [3363/4000] Training [7/16] Loss: 0.00398 +Epoch [3363/4000] Training [8/16] Loss: 0.00193 +Epoch [3363/4000] Training [9/16] Loss: 0.00210 +Epoch [3363/4000] Training [10/16] Loss: 0.00262 +Epoch [3363/4000] Training [11/16] Loss: 0.00232 +Epoch [3363/4000] Training [12/16] Loss: 0.00395 +Epoch [3363/4000] Training [13/16] Loss: 0.00225 +Epoch [3363/4000] Training [14/16] Loss: 0.00149 +Epoch [3363/4000] Training [15/16] Loss: 0.00386 +Epoch [3363/4000] Training [16/16] Loss: 0.00307 +Epoch [3363/4000] Training metric {'Train/mean dice_metric': 0.9985789656639099, 'Train/mean miou_metric': 0.9968262910842896, 'Train/mean f1': 0.9926135540008545, 'Train/mean precision': 0.9872181415557861, 'Train/mean recall': 0.9980682134628296, 'Train/mean hd95_metric': 0.606277585029602} +Epoch [3363/4000] Validation [1/4] Loss: 0.39477 focal_loss 0.33179 dice_loss 0.06299 +Epoch [3363/4000] Validation [2/4] Loss: 0.39758 focal_loss 0.29776 dice_loss 0.09982 +Epoch [3363/4000] Validation [3/4] Loss: 0.50774 focal_loss 0.41992 dice_loss 0.08782 +Epoch [3363/4000] Validation [4/4] Loss: 0.32783 focal_loss 0.23602 dice_loss 0.09180 +Epoch [3363/4000] Validation metric {'Val/mean dice_metric': 0.974242091178894, 'Val/mean miou_metric': 0.9604385495185852, 'Val/mean f1': 0.9760121703147888, 'Val/mean precision': 0.9722421765327454, 'Val/mean recall': 0.979811429977417, 'Val/mean hd95_metric': 4.960625171661377} +Cheakpoint... +Epoch [3363/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974242091178894, 'Val/mean miou_metric': 0.9604385495185852, 'Val/mean f1': 0.9760121703147888, 'Val/mean precision': 0.9722421765327454, 'Val/mean recall': 0.979811429977417, 'Val/mean hd95_metric': 4.960625171661377} +Epoch [3364/4000] Training [1/16] Loss: 0.00222 +Epoch [3364/4000] Training [2/16] Loss: 0.00352 +Epoch [3364/4000] Training [3/16] Loss: 0.00346 +Epoch [3364/4000] Training [4/16] Loss: 0.00194 +Epoch [3364/4000] Training [5/16] Loss: 0.00244 +Epoch [3364/4000] Training [6/16] Loss: 0.00192 +Epoch [3364/4000] Training [7/16] Loss: 0.00317 +Epoch [3364/4000] Training [8/16] Loss: 0.00360 +Epoch [3364/4000] Training [9/16] Loss: 0.00234 +Epoch [3364/4000] Training [10/16] Loss: 0.00275 +Epoch [3364/4000] Training [11/16] Loss: 0.00317 +Epoch [3364/4000] Training [12/16] Loss: 0.00268 +Epoch [3364/4000] Training [13/16] Loss: 0.00323 +Epoch [3364/4000] Training [14/16] Loss: 0.00188 +Epoch [3364/4000] Training [15/16] Loss: 0.00148 +Epoch [3364/4000] Training [16/16] Loss: 0.00323 +Epoch [3364/4000] Training metric {'Train/mean dice_metric': 0.9986826181411743, 'Train/mean miou_metric': 0.9970923662185669, 'Train/mean f1': 0.9936947822570801, 'Train/mean precision': 0.9891017079353333, 'Train/mean recall': 0.9983306527137756, 'Train/mean hd95_metric': 0.5815704464912415} +Epoch [3364/4000] Validation [1/4] Loss: 0.38218 focal_loss 0.31939 dice_loss 0.06279 +Epoch [3364/4000] Validation [2/4] Loss: 0.40509 focal_loss 0.30599 dice_loss 0.09910 +Epoch [3364/4000] Validation [3/4] Loss: 0.50628 focal_loss 0.41339 dice_loss 0.09290 +Epoch [3364/4000] Validation [4/4] Loss: 0.27638 focal_loss 0.18648 dice_loss 0.08990 +Epoch [3364/4000] Validation metric {'Val/mean dice_metric': 0.9745000600814819, 'Val/mean miou_metric': 0.9608526229858398, 'Val/mean f1': 0.9763908386230469, 'Val/mean precision': 0.973555862903595, 'Val/mean recall': 0.9792425036430359, 'Val/mean hd95_metric': 4.734906196594238} +Cheakpoint... +Epoch [3364/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745000600814819, 'Val/mean miou_metric': 0.9608526229858398, 'Val/mean f1': 0.9763908386230469, 'Val/mean precision': 0.973555862903595, 'Val/mean recall': 0.9792425036430359, 'Val/mean hd95_metric': 4.734906196594238} +Epoch [3365/4000] Training [1/16] Loss: 0.00259 +Epoch [3365/4000] Training [2/16] Loss: 0.00318 +Epoch [3365/4000] Training [3/16] Loss: 0.00257 +Epoch [3365/4000] Training [4/16] Loss: 0.00254 +Epoch [3365/4000] Training [5/16] Loss: 0.00317 +Epoch [3365/4000] Training [6/16] Loss: 0.00241 +Epoch [3365/4000] Training [7/16] Loss: 0.00357 +Epoch [3365/4000] Training [8/16] Loss: 0.00247 +Epoch [3365/4000] Training [9/16] Loss: 0.00159 +Epoch [3365/4000] Training [10/16] Loss: 0.00178 +Epoch [3365/4000] Training [11/16] Loss: 0.00410 +Epoch [3365/4000] Training [12/16] Loss: 0.00209 +Epoch [3365/4000] Training [13/16] Loss: 0.00301 +Epoch [3365/4000] Training [14/16] Loss: 0.00258 +Epoch [3365/4000] Training [15/16] Loss: 0.00312 +Epoch [3365/4000] Training [16/16] Loss: 0.00255 +Epoch [3365/4000] Training metric {'Train/mean dice_metric': 0.9986218214035034, 'Train/mean miou_metric': 0.9969639182090759, 'Train/mean f1': 0.9935667514801025, 'Train/mean precision': 0.9888995289802551, 'Train/mean recall': 0.9982782006263733, 'Train/mean hd95_metric': 0.6122345924377441} +Epoch [3365/4000] Validation [1/4] Loss: 0.42732 focal_loss 0.36280 dice_loss 0.06452 +Epoch [3365/4000] Validation [2/4] Loss: 0.45242 focal_loss 0.32599 dice_loss 0.12643 +Epoch [3365/4000] Validation [3/4] Loss: 0.52490 focal_loss 0.42824 dice_loss 0.09666 +Epoch [3365/4000] Validation [4/4] Loss: 0.46053 focal_loss 0.34893 dice_loss 0.11160 +Epoch [3365/4000] Validation metric {'Val/mean dice_metric': 0.9749821424484253, 'Val/mean miou_metric': 0.9605334997177124, 'Val/mean f1': 0.976030707359314, 'Val/mean precision': 0.9723215103149414, 'Val/mean recall': 0.9797682762145996, 'Val/mean hd95_metric': 4.985936164855957} +Cheakpoint... +Epoch [3365/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749821424484253, 'Val/mean miou_metric': 0.9605334997177124, 'Val/mean f1': 0.976030707359314, 'Val/mean precision': 0.9723215103149414, 'Val/mean recall': 0.9797682762145996, 'Val/mean hd95_metric': 4.985936164855957} +Epoch [3366/4000] Training [1/16] Loss: 0.00313 +Epoch [3366/4000] Training [2/16] Loss: 0.00242 +Epoch [3366/4000] Training [3/16] Loss: 0.00240 +Epoch [3366/4000] Training [4/16] Loss: 0.00190 +Epoch [3366/4000] Training [5/16] Loss: 0.00325 +Epoch [3366/4000] Training [6/16] Loss: 0.00208 +Epoch [3366/4000] Training [7/16] Loss: 0.00277 +Epoch [3366/4000] Training [8/16] Loss: 0.00361 +Epoch [3366/4000] Training [9/16] Loss: 0.00213 +Epoch [3366/4000] Training [10/16] Loss: 0.00213 +Epoch [3366/4000] Training [11/16] Loss: 0.00204 +Epoch [3366/4000] Training [12/16] Loss: 0.00291 +Epoch [3366/4000] Training [13/16] Loss: 0.00214 +Epoch [3366/4000] Training [14/16] Loss: 0.00268 +Epoch [3366/4000] Training [15/16] Loss: 0.00287 +Epoch [3366/4000] Training [16/16] Loss: 0.00226 +Epoch [3366/4000] Training metric {'Train/mean dice_metric': 0.9986943602561951, 'Train/mean miou_metric': 0.9970985054969788, 'Train/mean f1': 0.993483304977417, 'Train/mean precision': 0.9887548685073853, 'Train/mean recall': 0.9982571601867676, 'Train/mean hd95_metric': 0.58176589012146} +Epoch [3366/4000] Validation [1/4] Loss: 0.33217 focal_loss 0.27107 dice_loss 0.06111 +Epoch [3366/4000] Validation [2/4] Loss: 0.98352 focal_loss 0.72083 dice_loss 0.26269 +Epoch [3366/4000] Validation [3/4] Loss: 0.51500 focal_loss 0.42270 dice_loss 0.09231 +Epoch [3366/4000] Validation [4/4] Loss: 0.31551 focal_loss 0.22533 dice_loss 0.09018 +Epoch [3366/4000] Validation metric {'Val/mean dice_metric': 0.9724486470222473, 'Val/mean miou_metric': 0.9584709405899048, 'Val/mean f1': 0.9755889773368835, 'Val/mean precision': 0.9721558690071106, 'Val/mean recall': 0.9790462851524353, 'Val/mean hd95_metric': 5.220787525177002} +Cheakpoint... +Epoch [3366/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724486470222473, 'Val/mean miou_metric': 0.9584709405899048, 'Val/mean f1': 0.9755889773368835, 'Val/mean precision': 0.9721558690071106, 'Val/mean recall': 0.9790462851524353, 'Val/mean hd95_metric': 5.220787525177002} +Epoch [3367/4000] Training [1/16] Loss: 0.00228 +Epoch [3367/4000] Training [2/16] Loss: 0.00229 +Epoch [3367/4000] Training [3/16] Loss: 0.00379 +Epoch [3367/4000] Training [4/16] Loss: 0.00310 +Epoch [3367/4000] Training [5/16] Loss: 0.00225 +Epoch [3367/4000] Training [6/16] Loss: 0.00207 +Epoch [3367/4000] Training [7/16] Loss: 0.00283 +Epoch [3367/4000] Training [8/16] Loss: 0.00863 +Epoch [3367/4000] Training [9/16] Loss: 0.00204 +Epoch [3367/4000] Training [10/16] Loss: 0.00245 +Epoch [3367/4000] Training [11/16] Loss: 0.00276 +Epoch [3367/4000] Training [12/16] Loss: 0.00441 +Epoch [3367/4000] Training [13/16] Loss: 0.00308 +Epoch [3367/4000] Training [14/16] Loss: 0.00246 +Epoch [3367/4000] Training [15/16] Loss: 0.00229 +Epoch [3367/4000] Training [16/16] Loss: 0.00224 +Epoch [3367/4000] Training metric {'Train/mean dice_metric': 0.9984356164932251, 'Train/mean miou_metric': 0.9966115951538086, 'Train/mean f1': 0.9935444593429565, 'Train/mean precision': 0.9889289140701294, 'Train/mean recall': 0.9982032775878906, 'Train/mean hd95_metric': 0.6805031895637512} +Epoch [3367/4000] Validation [1/4] Loss: 0.35934 focal_loss 0.29899 dice_loss 0.06034 +Epoch [3367/4000] Validation [2/4] Loss: 0.45973 focal_loss 0.33370 dice_loss 0.12603 +Epoch [3367/4000] Validation [3/4] Loss: 0.49716 focal_loss 0.41107 dice_loss 0.08609 +Epoch [3367/4000] Validation [4/4] Loss: 0.29076 focal_loss 0.20155 dice_loss 0.08921 +Epoch [3367/4000] Validation metric {'Val/mean dice_metric': 0.9728587865829468, 'Val/mean miou_metric': 0.9591689109802246, 'Val/mean f1': 0.9762524962425232, 'Val/mean precision': 0.9735754132270813, 'Val/mean recall': 0.9789443612098694, 'Val/mean hd95_metric': 4.9822998046875} +Cheakpoint... +Epoch [3367/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728587865829468, 'Val/mean miou_metric': 0.9591689109802246, 'Val/mean f1': 0.9762524962425232, 'Val/mean precision': 0.9735754132270813, 'Val/mean recall': 0.9789443612098694, 'Val/mean hd95_metric': 4.9822998046875} +Epoch [3368/4000] Training [1/16] Loss: 0.00187 +Epoch [3368/4000] Training [2/16] Loss: 0.00219 +Epoch [3368/4000] Training [3/16] Loss: 0.00194 +Epoch [3368/4000] Training [4/16] Loss: 0.00265 +Epoch [3368/4000] Training [5/16] Loss: 0.00349 +Epoch [3368/4000] Training [6/16] Loss: 0.00268 +Epoch [3368/4000] Training [7/16] Loss: 0.00195 +Epoch [3368/4000] Training [8/16] Loss: 0.00245 +Epoch [3368/4000] Training [9/16] Loss: 0.00335 +Epoch [3368/4000] Training [10/16] Loss: 0.00292 +Epoch [3368/4000] Training [11/16] Loss: 0.00272 +Epoch [3368/4000] Training [12/16] Loss: 0.00333 +Epoch [3368/4000] Training [13/16] Loss: 0.00356 +Epoch [3368/4000] Training [14/16] Loss: 0.00162 +Epoch [3368/4000] Training [15/16] Loss: 0.00220 +Epoch [3368/4000] Training [16/16] Loss: 0.00253 +Epoch [3368/4000] Training metric {'Train/mean dice_metric': 0.9985871315002441, 'Train/mean miou_metric': 0.9968790411949158, 'Train/mean f1': 0.9930233955383301, 'Train/mean precision': 0.9879629015922546, 'Train/mean recall': 0.9981359243392944, 'Train/mean hd95_metric': 0.6073517799377441} +Epoch [3368/4000] Validation [1/4] Loss: 0.41690 focal_loss 0.35387 dice_loss 0.06303 +Epoch [3368/4000] Validation [2/4] Loss: 0.81856 focal_loss 0.62333 dice_loss 0.19523 +Epoch [3368/4000] Validation [3/4] Loss: 0.51619 focal_loss 0.41415 dice_loss 0.10204 +Epoch [3368/4000] Validation [4/4] Loss: 0.32731 focal_loss 0.23511 dice_loss 0.09220 +Epoch [3368/4000] Validation metric {'Val/mean dice_metric': 0.9736043810844421, 'Val/mean miou_metric': 0.9596064686775208, 'Val/mean f1': 0.9758743047714233, 'Val/mean precision': 0.9719807505607605, 'Val/mean recall': 0.9797991514205933, 'Val/mean hd95_metric': 4.999763488769531} +Cheakpoint... +Epoch [3368/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736043810844421, 'Val/mean miou_metric': 0.9596064686775208, 'Val/mean f1': 0.9758743047714233, 'Val/mean precision': 0.9719807505607605, 'Val/mean recall': 0.9797991514205933, 'Val/mean hd95_metric': 4.999763488769531} +Epoch [3369/4000] Training [1/16] Loss: 0.00225 +Epoch [3369/4000] Training [2/16] Loss: 0.00337 +Epoch [3369/4000] Training [3/16] Loss: 0.00458 +Epoch [3369/4000] Training [4/16] Loss: 0.00192 +Epoch [3369/4000] Training [5/16] Loss: 0.00213 +Epoch [3369/4000] Training [6/16] Loss: 0.00261 +Epoch [3369/4000] Training [7/16] Loss: 0.00207 +Epoch [3369/4000] Training [8/16] Loss: 0.00223 +Epoch [3369/4000] Training [9/16] Loss: 0.00242 +Epoch [3369/4000] Training [10/16] Loss: 0.00270 +Epoch [3369/4000] Training [11/16] Loss: 0.00257 +Epoch [3369/4000] Training [12/16] Loss: 0.00181 +Epoch [3369/4000] Training [13/16] Loss: 0.00280 +Epoch [3369/4000] Training [14/16] Loss: 0.00278 +Epoch [3369/4000] Training [15/16] Loss: 0.00197 +Epoch [3369/4000] Training [16/16] Loss: 0.00214 +Epoch [3369/4000] Training metric {'Train/mean dice_metric': 0.9987331628799438, 'Train/mean miou_metric': 0.9971920251846313, 'Train/mean f1': 0.9937632083892822, 'Train/mean precision': 0.9891942739486694, 'Train/mean recall': 0.9983745813369751, 'Train/mean hd95_metric': 0.5664615631103516} +Epoch [3369/4000] Validation [1/4] Loss: 0.38863 focal_loss 0.32264 dice_loss 0.06600 +Epoch [3369/4000] Validation [2/4] Loss: 0.82311 focal_loss 0.62188 dice_loss 0.20123 +Epoch [3369/4000] Validation [3/4] Loss: 0.27072 focal_loss 0.20917 dice_loss 0.06154 +Epoch [3369/4000] Validation [4/4] Loss: 0.31093 focal_loss 0.21518 dice_loss 0.09575 +Epoch [3369/4000] Validation metric {'Val/mean dice_metric': 0.9743537902832031, 'Val/mean miou_metric': 0.9602571725845337, 'Val/mean f1': 0.9767106771469116, 'Val/mean precision': 0.9747445583343506, 'Val/mean recall': 0.978684663772583, 'Val/mean hd95_metric': 4.442223072052002} +Cheakpoint... +Epoch [3369/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743537902832031, 'Val/mean miou_metric': 0.9602571725845337, 'Val/mean f1': 0.9767106771469116, 'Val/mean precision': 0.9747445583343506, 'Val/mean recall': 0.978684663772583, 'Val/mean hd95_metric': 4.442223072052002} +Epoch [3370/4000] Training [1/16] Loss: 0.00320 +Epoch [3370/4000] Training [2/16] Loss: 0.00195 +Epoch [3370/4000] Training [3/16] Loss: 0.00349 +Epoch [3370/4000] Training [4/16] Loss: 0.00200 +Epoch [3370/4000] Training [5/16] Loss: 0.00269 +Epoch [3370/4000] Training [6/16] Loss: 0.00199 +Epoch [3370/4000] Training [7/16] Loss: 0.00261 +Epoch [3370/4000] Training [8/16] Loss: 0.00416 +Epoch [3370/4000] Training [9/16] Loss: 0.00242 +Epoch [3370/4000] Training [10/16] Loss: 0.00231 +Epoch [3370/4000] Training [11/16] Loss: 0.00234 +Epoch [3370/4000] Training [12/16] Loss: 0.00256 +Epoch [3370/4000] Training [13/16] Loss: 0.00388 +Epoch [3370/4000] Training [14/16] Loss: 0.00291 +Epoch [3370/4000] Training [15/16] Loss: 0.00296 +Epoch [3370/4000] Training [16/16] Loss: 0.00195 +Epoch [3370/4000] Training metric {'Train/mean dice_metric': 0.998553991317749, 'Train/mean miou_metric': 0.9968225955963135, 'Train/mean f1': 0.9935176968574524, 'Train/mean precision': 0.9889110326766968, 'Train/mean recall': 0.9981675148010254, 'Train/mean hd95_metric': 0.6195588111877441} +Epoch [3370/4000] Validation [1/4] Loss: 0.42456 focal_loss 0.35914 dice_loss 0.06542 +Epoch [3370/4000] Validation [2/4] Loss: 1.18236 focal_loss 0.99268 dice_loss 0.18967 +Epoch [3370/4000] Validation [3/4] Loss: 0.52050 focal_loss 0.42922 dice_loss 0.09128 +Epoch [3370/4000] Validation [4/4] Loss: 0.37183 focal_loss 0.25895 dice_loss 0.11288 +Epoch [3370/4000] Validation metric {'Val/mean dice_metric': 0.9712203741073608, 'Val/mean miou_metric': 0.957746148109436, 'Val/mean f1': 0.9755496978759766, 'Val/mean precision': 0.9732233285903931, 'Val/mean recall': 0.9778872728347778, 'Val/mean hd95_metric': 5.121084690093994} +Cheakpoint... +Epoch [3370/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9712], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9712203741073608, 'Val/mean miou_metric': 0.957746148109436, 'Val/mean f1': 0.9755496978759766, 'Val/mean precision': 0.9732233285903931, 'Val/mean recall': 0.9778872728347778, 'Val/mean hd95_metric': 5.121084690093994} +Epoch [3371/4000] Training [1/16] Loss: 0.00389 +Epoch [3371/4000] Training [2/16] Loss: 0.00212 +Epoch [3371/4000] Training [3/16] Loss: 0.00308 +Epoch [3371/4000] Training [4/16] Loss: 0.00232 +Epoch [3371/4000] Training [5/16] Loss: 0.00320 +Epoch [3371/4000] Training [6/16] Loss: 0.00217 +Epoch [3371/4000] Training [7/16] Loss: 0.00302 +Epoch [3371/4000] Training [8/16] Loss: 0.00268 +Epoch [3371/4000] Training [9/16] Loss: 0.00276 +Epoch [3371/4000] Training [10/16] Loss: 0.00216 +Epoch [3371/4000] Training [11/16] Loss: 0.00214 +Epoch [3371/4000] Training [12/16] Loss: 0.00271 +Epoch [3371/4000] Training [13/16] Loss: 0.00233 +Epoch [3371/4000] Training [14/16] Loss: 0.00285 +Epoch [3371/4000] Training [15/16] Loss: 0.00280 +Epoch [3371/4000] Training [16/16] Loss: 0.00258 +Epoch [3371/4000] Training metric {'Train/mean dice_metric': 0.998553991317749, 'Train/mean miou_metric': 0.9968017339706421, 'Train/mean f1': 0.992807149887085, 'Train/mean precision': 0.9875460863113403, 'Train/mean recall': 0.9981245398521423, 'Train/mean hd95_metric': 0.6367464065551758} +Epoch [3371/4000] Validation [1/4] Loss: 0.41088 focal_loss 0.34212 dice_loss 0.06876 +Epoch [3371/4000] Validation [2/4] Loss: 0.39678 focal_loss 0.29885 dice_loss 0.09792 +Epoch [3371/4000] Validation [3/4] Loss: 0.50782 focal_loss 0.41178 dice_loss 0.09604 +Epoch [3371/4000] Validation [4/4] Loss: 0.27131 focal_loss 0.18192 dice_loss 0.08939 +Epoch [3371/4000] Validation metric {'Val/mean dice_metric': 0.9747918844223022, 'Val/mean miou_metric': 0.9601133465766907, 'Val/mean f1': 0.9756106734275818, 'Val/mean precision': 0.9726751446723938, 'Val/mean recall': 0.9785641431808472, 'Val/mean hd95_metric': 4.8097004890441895} +Cheakpoint... +Epoch [3371/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747918844223022, 'Val/mean miou_metric': 0.9601133465766907, 'Val/mean f1': 0.9756106734275818, 'Val/mean precision': 0.9726751446723938, 'Val/mean recall': 0.9785641431808472, 'Val/mean hd95_metric': 4.8097004890441895} +Epoch [3372/4000] Training [1/16] Loss: 0.00217 +Epoch [3372/4000] Training [2/16] Loss: 0.00217 +Epoch [3372/4000] Training [3/16] Loss: 0.00210 +Epoch [3372/4000] Training [4/16] Loss: 0.00255 +Epoch [3372/4000] Training [5/16] Loss: 0.00234 +Epoch [3372/4000] Training [6/16] Loss: 0.00282 +Epoch [3372/4000] Training [7/16] Loss: 0.00343 +Epoch [3372/4000] Training [8/16] Loss: 0.00419 +Epoch [3372/4000] Training [9/16] Loss: 0.00223 +Epoch [3372/4000] Training [10/16] Loss: 0.00221 +Epoch [3372/4000] Training [11/16] Loss: 0.00215 +Epoch [3372/4000] Training [12/16] Loss: 0.00282 +Epoch [3372/4000] Training [13/16] Loss: 0.00328 +Epoch [3372/4000] Training [14/16] Loss: 0.00321 +Epoch [3372/4000] Training [15/16] Loss: 0.00267 +Epoch [3372/4000] Training [16/16] Loss: 0.00334 +Epoch [3372/4000] Training metric {'Train/mean dice_metric': 0.9986996650695801, 'Train/mean miou_metric': 0.9971277117729187, 'Train/mean f1': 0.9937462210655212, 'Train/mean precision': 0.989236056804657, 'Train/mean recall': 0.9982976913452148, 'Train/mean hd95_metric': 0.557770311832428} +Epoch [3372/4000] Validation [1/4] Loss: 0.39720 focal_loss 0.33452 dice_loss 0.06268 +Epoch [3372/4000] Validation [2/4] Loss: 0.82381 focal_loss 0.62725 dice_loss 0.19656 +Epoch [3372/4000] Validation [3/4] Loss: 0.56138 focal_loss 0.46605 dice_loss 0.09533 +Epoch [3372/4000] Validation [4/4] Loss: 0.45543 focal_loss 0.34796 dice_loss 0.10747 +Epoch [3372/4000] Validation metric {'Val/mean dice_metric': 0.9722200632095337, 'Val/mean miou_metric': 0.958284854888916, 'Val/mean f1': 0.9756549000740051, 'Val/mean precision': 0.9736860990524292, 'Val/mean recall': 0.9776316285133362, 'Val/mean hd95_metric': 5.322341442108154} +Cheakpoint... +Epoch [3372/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722200632095337, 'Val/mean miou_metric': 0.958284854888916, 'Val/mean f1': 0.9756549000740051, 'Val/mean precision': 0.9736860990524292, 'Val/mean recall': 0.9776316285133362, 'Val/mean hd95_metric': 5.322341442108154} +Epoch [3373/4000] Training [1/16] Loss: 0.00291 +Epoch [3373/4000] Training [2/16] Loss: 0.00299 +Epoch [3373/4000] Training [3/16] Loss: 0.00174 +Epoch [3373/4000] Training [4/16] Loss: 0.00263 +Epoch [3373/4000] Training [5/16] Loss: 0.00222 +Epoch [3373/4000] Training [6/16] Loss: 0.00318 +Epoch [3373/4000] Training [7/16] Loss: 0.00200 +Epoch [3373/4000] Training [8/16] Loss: 0.00221 +Epoch [3373/4000] Training [9/16] Loss: 0.00326 +Epoch [3373/4000] Training [10/16] Loss: 0.00306 +Epoch [3373/4000] Training [11/16] Loss: 0.00330 +Epoch [3373/4000] Training [12/16] Loss: 0.00234 +Epoch [3373/4000] Training [13/16] Loss: 0.00298 +Epoch [3373/4000] Training [14/16] Loss: 0.00291 +Epoch [3373/4000] Training [15/16] Loss: 0.00208 +Epoch [3373/4000] Training [16/16] Loss: 0.00191 +Epoch [3373/4000] Training metric {'Train/mean dice_metric': 0.9985994100570679, 'Train/mean miou_metric': 0.9969158172607422, 'Train/mean f1': 0.993584156036377, 'Train/mean precision': 0.9889795184135437, 'Train/mean recall': 0.9982320070266724, 'Train/mean hd95_metric': 0.60862135887146} +Epoch [3373/4000] Validation [1/4] Loss: 0.41229 focal_loss 0.34464 dice_loss 0.06765 +Epoch [3373/4000] Validation [2/4] Loss: 0.83193 focal_loss 0.63298 dice_loss 0.19894 +Epoch [3373/4000] Validation [3/4] Loss: 0.54217 focal_loss 0.43992 dice_loss 0.10225 +Epoch [3373/4000] Validation [4/4] Loss: 0.26285 focal_loss 0.17760 dice_loss 0.08525 +Epoch [3373/4000] Validation metric {'Val/mean dice_metric': 0.9747387170791626, 'Val/mean miou_metric': 0.960241436958313, 'Val/mean f1': 0.9756953716278076, 'Val/mean precision': 0.9724692106246948, 'Val/mean recall': 0.9789429306983948, 'Val/mean hd95_metric': 5.474027633666992} +Cheakpoint... +Epoch [3373/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747387170791626, 'Val/mean miou_metric': 0.960241436958313, 'Val/mean f1': 0.9756953716278076, 'Val/mean precision': 0.9724692106246948, 'Val/mean recall': 0.9789429306983948, 'Val/mean hd95_metric': 5.474027633666992} +Epoch [3374/4000] Training [1/16] Loss: 0.00257 +Epoch [3374/4000] Training [2/16] Loss: 0.00236 +Epoch [3374/4000] Training [3/16] Loss: 0.00259 +Epoch [3374/4000] Training [4/16] Loss: 0.00249 +Epoch [3374/4000] Training [5/16] Loss: 0.00229 +Epoch [3374/4000] Training [6/16] Loss: 0.00414 +Epoch [3374/4000] Training [7/16] Loss: 0.00242 +Epoch [3374/4000] Training [8/16] Loss: 0.00311 +Epoch [3374/4000] Training [9/16] Loss: 0.00300 +Epoch [3374/4000] Training [10/16] Loss: 0.00333 +Epoch [3374/4000] Training [11/16] Loss: 0.00257 +Epoch [3374/4000] Training [12/16] Loss: 0.00216 +Epoch [3374/4000] Training [13/16] Loss: 0.00177 +Epoch [3374/4000] Training [14/16] Loss: 0.00181 +Epoch [3374/4000] Training [15/16] Loss: 0.00408 +Epoch [3374/4000] Training [16/16] Loss: 0.00388 +Epoch [3374/4000] Training metric {'Train/mean dice_metric': 0.9984343647956848, 'Train/mean miou_metric': 0.9965635538101196, 'Train/mean f1': 0.992772102355957, 'Train/mean precision': 0.9875084757804871, 'Train/mean recall': 0.9980921745300293, 'Train/mean hd95_metric': 0.5900944471359253} +Epoch [3374/4000] Validation [1/4] Loss: 0.36986 focal_loss 0.30867 dice_loss 0.06119 +Epoch [3374/4000] Validation [2/4] Loss: 0.42671 focal_loss 0.32456 dice_loss 0.10216 +Epoch [3374/4000] Validation [3/4] Loss: 0.27690 focal_loss 0.21157 dice_loss 0.06533 +Epoch [3374/4000] Validation [4/4] Loss: 0.36556 focal_loss 0.27066 dice_loss 0.09490 +Epoch [3374/4000] Validation metric {'Val/mean dice_metric': 0.975538432598114, 'Val/mean miou_metric': 0.961521327495575, 'Val/mean f1': 0.9764237403869629, 'Val/mean precision': 0.9731459617614746, 'Val/mean recall': 0.9797236919403076, 'Val/mean hd95_metric': 4.677260398864746} +Cheakpoint... +Epoch [3374/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975538432598114, 'Val/mean miou_metric': 0.961521327495575, 'Val/mean f1': 0.9764237403869629, 'Val/mean precision': 0.9731459617614746, 'Val/mean recall': 0.9797236919403076, 'Val/mean hd95_metric': 4.677260398864746} +Epoch [3375/4000] Training [1/16] Loss: 0.00260 +Epoch [3375/4000] Training [2/16] Loss: 0.00340 +Epoch [3375/4000] Training [3/16] Loss: 0.00234 +Epoch [3375/4000] Training [4/16] Loss: 0.00398 +Epoch [3375/4000] Training [5/16] Loss: 0.00232 +Epoch [3375/4000] Training [6/16] Loss: 0.00244 +Epoch [3375/4000] Training [7/16] Loss: 0.00222 +Epoch [3375/4000] Training [8/16] Loss: 0.00264 +Epoch [3375/4000] Training [9/16] Loss: 0.00315 +Epoch [3375/4000] Training [10/16] Loss: 0.00263 +Epoch [3375/4000] Training [11/16] Loss: 0.00286 +Epoch [3375/4000] Training [12/16] Loss: 0.00410 +Epoch [3375/4000] Training [13/16] Loss: 0.00196 +Epoch [3375/4000] Training [14/16] Loss: 0.00234 +Epoch [3375/4000] Training [15/16] Loss: 0.00231 +Epoch [3375/4000] Training [16/16] Loss: 0.00218 +Epoch [3375/4000] Training metric {'Train/mean dice_metric': 0.998615026473999, 'Train/mean miou_metric': 0.9969518780708313, 'Train/mean f1': 0.9935814738273621, 'Train/mean precision': 0.9889345765113831, 'Train/mean recall': 0.9982722401618958, 'Train/mean hd95_metric': 0.6098908185958862} +Epoch [3375/4000] Validation [1/4] Loss: 0.37019 focal_loss 0.31005 dice_loss 0.06015 +Epoch [3375/4000] Validation [2/4] Loss: 0.77877 focal_loss 0.56816 dice_loss 0.21061 +Epoch [3375/4000] Validation [3/4] Loss: 0.54106 focal_loss 0.44715 dice_loss 0.09391 +Epoch [3375/4000] Validation [4/4] Loss: 0.39217 focal_loss 0.28332 dice_loss 0.10885 +Epoch [3375/4000] Validation metric {'Val/mean dice_metric': 0.9732418060302734, 'Val/mean miou_metric': 0.9589874148368835, 'Val/mean f1': 0.9759951233863831, 'Val/mean precision': 0.9737387895584106, 'Val/mean recall': 0.9782620072364807, 'Val/mean hd95_metric': 4.954909324645996} +Cheakpoint... +Epoch [3375/4000] best acc:tensor([0.9769], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732418060302734, 'Val/mean miou_metric': 0.9589874148368835, 'Val/mean f1': 0.9759951233863831, 'Val/mean precision': 0.9737387895584106, 'Val/mean recall': 0.9782620072364807, 'Val/mean hd95_metric': 4.954909324645996} +Epoch [3376/4000] Training [1/16] Loss: 0.00305 +Epoch [3376/4000] Training [2/16] Loss: 0.00217 +Epoch [3376/4000] Training [3/16] Loss: 0.00238 +Epoch [3376/4000] Training [4/16] Loss: 0.00212 +Epoch [3376/4000] Training [5/16] Loss: 0.00303 +Epoch [3376/4000] Training [6/16] Loss: 0.00304 +Epoch [3376/4000] Training [7/16] Loss: 0.00240 +Epoch [3376/4000] Training [8/16] Loss: 0.00245 +Epoch [3376/4000] Training [9/16] Loss: 0.00218 +Epoch [3376/4000] Training [10/16] Loss: 0.00211 +Epoch [3376/4000] Training [11/16] Loss: 0.00346 +Epoch [3376/4000] Training [12/16] Loss: 0.00271 +Epoch [3376/4000] Training [13/16] Loss: 0.00291 +Epoch [3376/4000] Training [14/16] Loss: 0.00227 +Epoch [3376/4000] Training [15/16] Loss: 0.00183 +Epoch [3376/4000] Training [16/16] Loss: 0.00209 +Epoch [3376/4000] Training metric {'Train/mean dice_metric': 0.998737096786499, 'Train/mean miou_metric': 0.9971737861633301, 'Train/mean f1': 0.9933876991271973, 'Train/mean precision': 0.9885025024414062, 'Train/mean recall': 0.9983213543891907, 'Train/mean hd95_metric': 0.5954378247261047} +Epoch [3376/4000] Validation [1/4] Loss: 0.39135 focal_loss 0.32910 dice_loss 0.06225 +Epoch [3376/4000] Validation [2/4] Loss: 0.43632 focal_loss 0.33143 dice_loss 0.10489 +Epoch [3376/4000] Validation [3/4] Loss: 0.27287 focal_loss 0.21163 dice_loss 0.06123 +Epoch [3376/4000] Validation [4/4] Loss: 0.34036 focal_loss 0.24662 dice_loss 0.09375 +Epoch [3376/4000] Validation metric {'Val/mean dice_metric': 0.9776544570922852, 'Val/mean miou_metric': 0.9635767936706543, 'Val/mean f1': 0.977523922920227, 'Val/mean precision': 0.9747691750526428, 'Val/mean recall': 0.9802942872047424, 'Val/mean hd95_metric': 4.495543003082275} +Cheakpoint... +Epoch [3376/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9777], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9776544570922852, 'Val/mean miou_metric': 0.9635767936706543, 'Val/mean f1': 0.977523922920227, 'Val/mean precision': 0.9747691750526428, 'Val/mean recall': 0.9802942872047424, 'Val/mean hd95_metric': 4.495543003082275} +Epoch [3377/4000] Training [1/16] Loss: 0.00276 +Epoch [3377/4000] Training [2/16] Loss: 0.00308 +Epoch [3377/4000] Training [3/16] Loss: 0.00191 +Epoch [3377/4000] Training [4/16] Loss: 0.00225 +Epoch [3377/4000] Training [5/16] Loss: 0.00283 +Epoch [3377/4000] Training [6/16] Loss: 0.00168 +Epoch [3377/4000] Training [7/16] Loss: 0.00251 +Epoch [3377/4000] Training [8/16] Loss: 0.00254 +Epoch [3377/4000] Training [9/16] Loss: 0.00432 +Epoch [3377/4000] Training [10/16] Loss: 0.00258 +Epoch [3377/4000] Training [11/16] Loss: 0.00387 +Epoch [3377/4000] Training [12/16] Loss: 0.00318 +Epoch [3377/4000] Training [13/16] Loss: 0.00273 +Epoch [3377/4000] Training [14/16] Loss: 0.00270 +Epoch [3377/4000] Training [15/16] Loss: 0.00197 +Epoch [3377/4000] Training [16/16] Loss: 0.00248 +Epoch [3377/4000] Training metric {'Train/mean dice_metric': 0.9986065626144409, 'Train/mean miou_metric': 0.9969247579574585, 'Train/mean f1': 0.9932982921600342, 'Train/mean precision': 0.9884312152862549, 'Train/mean recall': 0.998213529586792, 'Train/mean hd95_metric': 0.5890900492668152} +Epoch [3377/4000] Validation [1/4] Loss: 0.42632 focal_loss 0.35834 dice_loss 0.06799 +Epoch [3377/4000] Validation [2/4] Loss: 0.53834 focal_loss 0.39441 dice_loss 0.14392 +Epoch [3377/4000] Validation [3/4] Loss: 0.23867 focal_loss 0.18452 dice_loss 0.05415 +Epoch [3377/4000] Validation [4/4] Loss: 0.37612 focal_loss 0.26251 dice_loss 0.11360 +Epoch [3377/4000] Validation metric {'Val/mean dice_metric': 0.9745023846626282, 'Val/mean miou_metric': 0.9598883390426636, 'Val/mean f1': 0.9759407043457031, 'Val/mean precision': 0.9737920165061951, 'Val/mean recall': 0.9780990481376648, 'Val/mean hd95_metric': 4.821557521820068} +Cheakpoint... +Epoch [3377/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745023846626282, 'Val/mean miou_metric': 0.9598883390426636, 'Val/mean f1': 0.9759407043457031, 'Val/mean precision': 0.9737920165061951, 'Val/mean recall': 0.9780990481376648, 'Val/mean hd95_metric': 4.821557521820068} +Epoch [3378/4000] Training [1/16] Loss: 0.00269 +Epoch [3378/4000] Training [2/16] Loss: 0.00284 +Epoch [3378/4000] Training [3/16] Loss: 0.00269 +Epoch [3378/4000] Training [4/16] Loss: 0.00312 +Epoch [3378/4000] Training [5/16] Loss: 0.00307 +Epoch [3378/4000] Training [6/16] Loss: 0.00304 +Epoch [3378/4000] Training [7/16] Loss: 0.00261 +Epoch [3378/4000] Training [8/16] Loss: 0.00234 +Epoch [3378/4000] Training [9/16] Loss: 0.00235 +Epoch [3378/4000] Training [10/16] Loss: 0.00302 +Epoch [3378/4000] Training [11/16] Loss: 0.00361 +Epoch [3378/4000] Training [12/16] Loss: 0.00280 +Epoch [3378/4000] Training [13/16] Loss: 0.00237 +Epoch [3378/4000] Training [14/16] Loss: 0.00241 +Epoch [3378/4000] Training [15/16] Loss: 0.00238 +Epoch [3378/4000] Training [16/16] Loss: 0.00255 +Epoch [3378/4000] Training metric {'Train/mean dice_metric': 0.9987189769744873, 'Train/mean miou_metric': 0.9971546530723572, 'Train/mean f1': 0.9936826825141907, 'Train/mean precision': 0.989107608795166, 'Train/mean recall': 0.9983002543449402, 'Train/mean hd95_metric': 0.5715396404266357} +Epoch [3378/4000] Validation [1/4] Loss: 0.37030 focal_loss 0.30761 dice_loss 0.06269 +Epoch [3378/4000] Validation [2/4] Loss: 0.41604 focal_loss 0.31361 dice_loss 0.10243 +Epoch [3378/4000] Validation [3/4] Loss: 0.52654 focal_loss 0.42923 dice_loss 0.09731 +Epoch [3378/4000] Validation [4/4] Loss: 0.33526 focal_loss 0.23881 dice_loss 0.09646 +Epoch [3378/4000] Validation metric {'Val/mean dice_metric': 0.9744783639907837, 'Val/mean miou_metric': 0.9605863690376282, 'Val/mean f1': 0.9766131043434143, 'Val/mean precision': 0.9740124344825745, 'Val/mean recall': 0.9792276620864868, 'Val/mean hd95_metric': 4.901737213134766} +Cheakpoint... +Epoch [3378/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744783639907837, 'Val/mean miou_metric': 0.9605863690376282, 'Val/mean f1': 0.9766131043434143, 'Val/mean precision': 0.9740124344825745, 'Val/mean recall': 0.9792276620864868, 'Val/mean hd95_metric': 4.901737213134766} +Epoch [3379/4000] Training [1/16] Loss: 0.00214 +Epoch [3379/4000] Training [2/16] Loss: 0.00176 +Epoch [3379/4000] Training [3/16] Loss: 0.00276 +Epoch [3379/4000] Training [4/16] Loss: 0.00249 +Epoch [3379/4000] Training [5/16] Loss: 0.00311 +Epoch [3379/4000] Training [6/16] Loss: 0.00262 +Epoch [3379/4000] Training [7/16] Loss: 0.00170 +Epoch [3379/4000] Training [8/16] Loss: 0.00204 +Epoch [3379/4000] Training [9/16] Loss: 0.00293 +Epoch [3379/4000] Training [10/16] Loss: 0.00264 +Epoch [3379/4000] Training [11/16] Loss: 0.00244 +Epoch [3379/4000] Training [12/16] Loss: 0.00281 +Epoch [3379/4000] Training [13/16] Loss: 0.00250 +Epoch [3379/4000] Training [14/16] Loss: 0.00258 +Epoch [3379/4000] Training [15/16] Loss: 0.00183 +Epoch [3379/4000] Training [16/16] Loss: 0.00278 +Epoch [3379/4000] Training metric {'Train/mean dice_metric': 0.998683750629425, 'Train/mean miou_metric': 0.9970955848693848, 'Train/mean f1': 0.9937368035316467, 'Train/mean precision': 0.9892101287841797, 'Train/mean recall': 0.9983050227165222, 'Train/mean hd95_metric': 0.5775666236877441} +Epoch [3379/4000] Validation [1/4] Loss: 0.48329 focal_loss 0.39948 dice_loss 0.08381 +Epoch [3379/4000] Validation [2/4] Loss: 0.76726 focal_loss 0.55338 dice_loss 0.21388 +Epoch [3379/4000] Validation [3/4] Loss: 0.51229 focal_loss 0.41848 dice_loss 0.09381 +Epoch [3379/4000] Validation [4/4] Loss: 0.37100 focal_loss 0.27197 dice_loss 0.09903 +Epoch [3379/4000] Validation metric {'Val/mean dice_metric': 0.9723352193832397, 'Val/mean miou_metric': 0.9584638476371765, 'Val/mean f1': 0.9760769605636597, 'Val/mean precision': 0.9739291071891785, 'Val/mean recall': 0.9782344102859497, 'Val/mean hd95_metric': 4.998517990112305} +Cheakpoint... +Epoch [3379/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723352193832397, 'Val/mean miou_metric': 0.9584638476371765, 'Val/mean f1': 0.9760769605636597, 'Val/mean precision': 0.9739291071891785, 'Val/mean recall': 0.9782344102859497, 'Val/mean hd95_metric': 4.998517990112305} +Epoch [3380/4000] Training [1/16] Loss: 0.00260 +Epoch [3380/4000] Training [2/16] Loss: 0.00357 +Epoch [3380/4000] Training [3/16] Loss: 0.00317 +Epoch [3380/4000] Training [4/16] Loss: 0.00337 +Epoch [3380/4000] Training [5/16] Loss: 0.00403 +Epoch [3380/4000] Training [6/16] Loss: 0.00198 +Epoch [3380/4000] Training [7/16] Loss: 0.00343 +Epoch [3380/4000] Training [8/16] Loss: 0.00143 +Epoch [3380/4000] Training [9/16] Loss: 0.00244 +Epoch [3380/4000] Training [10/16] Loss: 0.00233 +Epoch [3380/4000] Training [11/16] Loss: 0.00315 +Epoch [3380/4000] Training [12/16] Loss: 0.00238 +Epoch [3380/4000] Training [13/16] Loss: 0.00228 +Epoch [3380/4000] Training [14/16] Loss: 0.00173 +Epoch [3380/4000] Training [15/16] Loss: 0.00203 +Epoch [3380/4000] Training [16/16] Loss: 0.00253 +Epoch [3380/4000] Training metric {'Train/mean dice_metric': 0.9987055659294128, 'Train/mean miou_metric': 0.9971369504928589, 'Train/mean f1': 0.9938076734542847, 'Train/mean precision': 0.9893550276756287, 'Train/mean recall': 0.9983005523681641, 'Train/mean hd95_metric': 0.5894806385040283} +Epoch [3380/4000] Validation [1/4] Loss: 0.38810 focal_loss 0.32761 dice_loss 0.06049 +Epoch [3380/4000] Validation [2/4] Loss: 0.77308 focal_loss 0.60168 dice_loss 0.17139 +Epoch [3380/4000] Validation [3/4] Loss: 0.54425 focal_loss 0.44682 dice_loss 0.09743 +Epoch [3380/4000] Validation [4/4] Loss: 0.36155 focal_loss 0.25697 dice_loss 0.10458 +Epoch [3380/4000] Validation metric {'Val/mean dice_metric': 0.9743790626525879, 'Val/mean miou_metric': 0.9606110453605652, 'Val/mean f1': 0.9771566987037659, 'Val/mean precision': 0.9745583534240723, 'Val/mean recall': 0.9797688722610474, 'Val/mean hd95_metric': 4.71928596496582} +Cheakpoint... +Epoch [3380/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743790626525879, 'Val/mean miou_metric': 0.9606110453605652, 'Val/mean f1': 0.9771566987037659, 'Val/mean precision': 0.9745583534240723, 'Val/mean recall': 0.9797688722610474, 'Val/mean hd95_metric': 4.71928596496582} +Epoch [3381/4000] Training [1/16] Loss: 0.00268 +Epoch [3381/4000] Training [2/16] Loss: 0.00232 +Epoch [3381/4000] Training [3/16] Loss: 0.00221 +Epoch [3381/4000] Training [4/16] Loss: 0.00423 +Epoch [3381/4000] Training [5/16] Loss: 0.00311 +Epoch [3381/4000] Training [6/16] Loss: 0.00186 +Epoch [3381/4000] Training [7/16] Loss: 0.00258 +Epoch [3381/4000] Training [8/16] Loss: 0.00256 +Epoch [3381/4000] Training [9/16] Loss: 0.00159 +Epoch [3381/4000] Training [10/16] Loss: 0.00214 +Epoch [3381/4000] Training [11/16] Loss: 0.00271 +Epoch [3381/4000] Training [12/16] Loss: 0.00272 +Epoch [3381/4000] Training [13/16] Loss: 0.00283 +Epoch [3381/4000] Training [14/16] Loss: 0.00376 +Epoch [3381/4000] Training [15/16] Loss: 0.00274 +Epoch [3381/4000] Training [16/16] Loss: 0.00240 +Epoch [3381/4000] Training metric {'Train/mean dice_metric': 0.9984832406044006, 'Train/mean miou_metric': 0.9966994524002075, 'Train/mean f1': 0.9936181902885437, 'Train/mean precision': 0.9890892505645752, 'Train/mean recall': 0.998188853263855, 'Train/mean hd95_metric': 0.6096389889717102} +Epoch [3381/4000] Validation [1/4] Loss: 0.39316 focal_loss 0.32991 dice_loss 0.06325 +Epoch [3381/4000] Validation [2/4] Loss: 1.22526 focal_loss 1.03209 dice_loss 0.19317 +Epoch [3381/4000] Validation [3/4] Loss: 0.50644 focal_loss 0.41578 dice_loss 0.09066 +Epoch [3381/4000] Validation [4/4] Loss: 0.35522 focal_loss 0.26183 dice_loss 0.09339 +Epoch [3381/4000] Validation metric {'Val/mean dice_metric': 0.9732295870780945, 'Val/mean miou_metric': 0.9592240452766418, 'Val/mean f1': 0.9759787321090698, 'Val/mean precision': 0.9732915759086609, 'Val/mean recall': 0.9786806106567383, 'Val/mean hd95_metric': 4.977866172790527} +Cheakpoint... +Epoch [3381/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732295870780945, 'Val/mean miou_metric': 0.9592240452766418, 'Val/mean f1': 0.9759787321090698, 'Val/mean precision': 0.9732915759086609, 'Val/mean recall': 0.9786806106567383, 'Val/mean hd95_metric': 4.977866172790527} +Epoch [3382/4000] Training [1/16] Loss: 0.00235 +Epoch [3382/4000] Training [2/16] Loss: 0.00169 +Epoch [3382/4000] Training [3/16] Loss: 0.00205 +Epoch [3382/4000] Training [4/16] Loss: 0.00339 +Epoch [3382/4000] Training [5/16] Loss: 0.00224 +Epoch [3382/4000] Training [6/16] Loss: 0.00198 +Epoch [3382/4000] Training [7/16] Loss: 0.00247 +Epoch [3382/4000] Training [8/16] Loss: 0.00290 +Epoch [3382/4000] Training [9/16] Loss: 0.00262 +Epoch [3382/4000] Training [10/16] Loss: 0.00227 +Epoch [3382/4000] Training [11/16] Loss: 0.00143 +Epoch [3382/4000] Training [12/16] Loss: 0.00357 +Epoch [3382/4000] Training [13/16] Loss: 0.00220 +Epoch [3382/4000] Training [14/16] Loss: 0.00229 +Epoch [3382/4000] Training [15/16] Loss: 0.00270 +Epoch [3382/4000] Training [16/16] Loss: 0.00350 +Epoch [3382/4000] Training metric {'Train/mean dice_metric': 0.9986860752105713, 'Train/mean miou_metric': 0.9970738887786865, 'Train/mean f1': 0.9932040572166443, 'Train/mean precision': 0.9882016181945801, 'Train/mean recall': 0.9982574582099915, 'Train/mean hd95_metric': 0.569293737411499} +Epoch [3382/4000] Validation [1/4] Loss: 0.48037 focal_loss 0.40784 dice_loss 0.07253 +Epoch [3382/4000] Validation [2/4] Loss: 0.88271 focal_loss 0.67579 dice_loss 0.20693 +Epoch [3382/4000] Validation [3/4] Loss: 0.50372 focal_loss 0.40229 dice_loss 0.10143 +Epoch [3382/4000] Validation [4/4] Loss: 0.25872 focal_loss 0.17181 dice_loss 0.08691 +Epoch [3382/4000] Validation metric {'Val/mean dice_metric': 0.9742984771728516, 'Val/mean miou_metric': 0.9596490859985352, 'Val/mean f1': 0.9757084250450134, 'Val/mean precision': 0.9725756645202637, 'Val/mean recall': 0.9788612127304077, 'Val/mean hd95_metric': 5.075839519500732} +Cheakpoint... +Epoch [3382/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742984771728516, 'Val/mean miou_metric': 0.9596490859985352, 'Val/mean f1': 0.9757084250450134, 'Val/mean precision': 0.9725756645202637, 'Val/mean recall': 0.9788612127304077, 'Val/mean hd95_metric': 5.075839519500732} +Epoch [3383/4000] Training [1/16] Loss: 0.00300 +Epoch [3383/4000] Training [2/16] Loss: 0.00185 +Epoch [3383/4000] Training [3/16] Loss: 0.00335 +Epoch [3383/4000] Training [4/16] Loss: 0.00225 +Epoch [3383/4000] Training [5/16] Loss: 0.00411 +Epoch [3383/4000] Training [6/16] Loss: 0.00312 +Epoch [3383/4000] Training [7/16] Loss: 0.00323 +Epoch [3383/4000] Training [8/16] Loss: 0.00297 +Epoch [3383/4000] Training [9/16] Loss: 0.00296 +Epoch [3383/4000] Training [10/16] Loss: 0.00280 +Epoch [3383/4000] Training [11/16] Loss: 0.00220 +Epoch [3383/4000] Training [12/16] Loss: 0.00274 +Epoch [3383/4000] Training [13/16] Loss: 0.00330 +Epoch [3383/4000] Training [14/16] Loss: 0.00465 +Epoch [3383/4000] Training [15/16] Loss: 0.00288 +Epoch [3383/4000] Training [16/16] Loss: 0.00172 +Epoch [3383/4000] Training metric {'Train/mean dice_metric': 0.9984651803970337, 'Train/mean miou_metric': 0.9966490268707275, 'Train/mean f1': 0.9933451414108276, 'Train/mean precision': 0.9886035323143005, 'Train/mean recall': 0.9981324076652527, 'Train/mean hd95_metric': 0.6603289246559143} +Epoch [3383/4000] Validation [1/4] Loss: 0.36691 focal_loss 0.30604 dice_loss 0.06087 +Epoch [3383/4000] Validation [2/4] Loss: 0.45471 focal_loss 0.33716 dice_loss 0.11755 +Epoch [3383/4000] Validation [3/4] Loss: 0.27169 focal_loss 0.21290 dice_loss 0.05879 +Epoch [3383/4000] Validation [4/4] Loss: 0.31133 focal_loss 0.22267 dice_loss 0.08866 +Epoch [3383/4000] Validation metric {'Val/mean dice_metric': 0.9744666814804077, 'Val/mean miou_metric': 0.9607423543930054, 'Val/mean f1': 0.9765926599502563, 'Val/mean precision': 0.9736571907997131, 'Val/mean recall': 0.9795458316802979, 'Val/mean hd95_metric': 4.903437614440918} +Cheakpoint... +Epoch [3383/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744666814804077, 'Val/mean miou_metric': 0.9607423543930054, 'Val/mean f1': 0.9765926599502563, 'Val/mean precision': 0.9736571907997131, 'Val/mean recall': 0.9795458316802979, 'Val/mean hd95_metric': 4.903437614440918} +Epoch [3384/4000] Training [1/16] Loss: 0.00259 +Epoch [3384/4000] Training [2/16] Loss: 0.00542 +Epoch [3384/4000] Training [3/16] Loss: 0.00237 +Epoch [3384/4000] Training [4/16] Loss: 0.00264 +Epoch [3384/4000] Training [5/16] Loss: 0.00240 +Epoch [3384/4000] Training [6/16] Loss: 0.00255 +Epoch [3384/4000] Training [7/16] Loss: 0.00225 +Epoch [3384/4000] Training [8/16] Loss: 0.00249 +Epoch [3384/4000] Training [9/16] Loss: 0.00193 +Epoch [3384/4000] Training [10/16] Loss: 0.00217 +Epoch [3384/4000] Training [11/16] Loss: 0.00278 +Epoch [3384/4000] Training [12/16] Loss: 0.00341 +Epoch [3384/4000] Training [13/16] Loss: 0.00510 +Epoch [3384/4000] Training [14/16] Loss: 0.00197 +Epoch [3384/4000] Training [15/16] Loss: 0.00163 +Epoch [3384/4000] Training [16/16] Loss: 0.00382 +Epoch [3384/4000] Training metric {'Train/mean dice_metric': 0.9984942078590393, 'Train/mean miou_metric': 0.9967104196548462, 'Train/mean f1': 0.9935919642448425, 'Train/mean precision': 0.9889761209487915, 'Train/mean recall': 0.9982511401176453, 'Train/mean hd95_metric': 0.6437075138092041} +Epoch [3384/4000] Validation [1/4] Loss: 0.39977 focal_loss 0.33572 dice_loss 0.06405 +Epoch [3384/4000] Validation [2/4] Loss: 1.21879 focal_loss 0.92125 dice_loss 0.29754 +Epoch [3384/4000] Validation [3/4] Loss: 0.50061 focal_loss 0.40832 dice_loss 0.09229 +Epoch [3384/4000] Validation [4/4] Loss: 0.33036 focal_loss 0.23273 dice_loss 0.09763 +Epoch [3384/4000] Validation metric {'Val/mean dice_metric': 0.9737130999565125, 'Val/mean miou_metric': 0.9594934582710266, 'Val/mean f1': 0.9756714105606079, 'Val/mean precision': 0.9737325310707092, 'Val/mean recall': 0.9776179790496826, 'Val/mean hd95_metric': 5.258016109466553} +Cheakpoint... +Epoch [3384/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737130999565125, 'Val/mean miou_metric': 0.9594934582710266, 'Val/mean f1': 0.9756714105606079, 'Val/mean precision': 0.9737325310707092, 'Val/mean recall': 0.9776179790496826, 'Val/mean hd95_metric': 5.258016109466553} +Epoch [3385/4000] Training [1/16] Loss: 0.00194 +Epoch [3385/4000] Training [2/16] Loss: 0.00384 +Epoch [3385/4000] Training [3/16] Loss: 0.00331 +Epoch [3385/4000] Training [4/16] Loss: 0.00233 +Epoch [3385/4000] Training [5/16] Loss: 0.00290 +Epoch [3385/4000] Training [6/16] Loss: 0.00240 +Epoch [3385/4000] Training [7/16] Loss: 0.00255 +Epoch [3385/4000] Training [8/16] Loss: 0.00322 +Epoch [3385/4000] Training [9/16] Loss: 0.00240 +Epoch [3385/4000] Training [10/16] Loss: 0.00308 +Epoch [3385/4000] Training [11/16] Loss: 0.00205 +Epoch [3385/4000] Training [12/16] Loss: 0.00189 +Epoch [3385/4000] Training [13/16] Loss: 0.00265 +Epoch [3385/4000] Training [14/16] Loss: 0.00213 +Epoch [3385/4000] Training [15/16] Loss: 0.00250 +Epoch [3385/4000] Training [16/16] Loss: 0.00262 +Epoch [3385/4000] Training metric {'Train/mean dice_metric': 0.9984753131866455, 'Train/mean miou_metric': 0.9967064261436462, 'Train/mean f1': 0.9935981631278992, 'Train/mean precision': 0.9890838861465454, 'Train/mean recall': 0.9981538653373718, 'Train/mean hd95_metric': 0.6298495531082153} +Epoch [3385/4000] Validation [1/4] Loss: 0.36781 focal_loss 0.30562 dice_loss 0.06220 +Epoch [3385/4000] Validation [2/4] Loss: 1.24888 focal_loss 1.06303 dice_loss 0.18585 +Epoch [3385/4000] Validation [3/4] Loss: 0.25561 focal_loss 0.19704 dice_loss 0.05857 +Epoch [3385/4000] Validation [4/4] Loss: 0.50295 focal_loss 0.37655 dice_loss 0.12640 +Epoch [3385/4000] Validation metric {'Val/mean dice_metric': 0.9737655520439148, 'Val/mean miou_metric': 0.9597911834716797, 'Val/mean f1': 0.9762869477272034, 'Val/mean precision': 0.9746956825256348, 'Val/mean recall': 0.9778832793235779, 'Val/mean hd95_metric': 4.498518943786621} +Cheakpoint... +Epoch [3385/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737655520439148, 'Val/mean miou_metric': 0.9597911834716797, 'Val/mean f1': 0.9762869477272034, 'Val/mean precision': 0.9746956825256348, 'Val/mean recall': 0.9778832793235779, 'Val/mean hd95_metric': 4.498518943786621} +Epoch [3386/4000] Training [1/16] Loss: 0.00236 +Epoch [3386/4000] Training [2/16] Loss: 0.00228 +Epoch [3386/4000] Training [3/16] Loss: 0.00333 +Epoch [3386/4000] Training [4/16] Loss: 0.00276 +Epoch [3386/4000] Training [5/16] Loss: 0.00251 +Epoch [3386/4000] Training [6/16] Loss: 0.00273 +Epoch [3386/4000] Training [7/16] Loss: 0.00233 +Epoch [3386/4000] Training [8/16] Loss: 0.00185 +Epoch [3386/4000] Training [9/16] Loss: 0.00307 +Epoch [3386/4000] Training [10/16] Loss: 0.00206 +Epoch [3386/4000] Training [11/16] Loss: 0.00347 +Epoch [3386/4000] Training [12/16] Loss: 0.00290 +Epoch [3386/4000] Training [13/16] Loss: 0.00209 +Epoch [3386/4000] Training [14/16] Loss: 0.00271 +Epoch [3386/4000] Training [15/16] Loss: 0.00204 +Epoch [3386/4000] Training [16/16] Loss: 0.00314 +Epoch [3386/4000] Training metric {'Train/mean dice_metric': 0.9986238479614258, 'Train/mean miou_metric': 0.9969780445098877, 'Train/mean f1': 0.9937385320663452, 'Train/mean precision': 0.9892337322235107, 'Train/mean recall': 0.9982846975326538, 'Train/mean hd95_metric': 0.5730745196342468} +Epoch [3386/4000] Validation [1/4] Loss: 0.40505 focal_loss 0.33879 dice_loss 0.06627 +Epoch [3386/4000] Validation [2/4] Loss: 0.46671 focal_loss 0.35944 dice_loss 0.10727 +Epoch [3386/4000] Validation [3/4] Loss: 0.50639 focal_loss 0.41544 dice_loss 0.09095 +Epoch [3386/4000] Validation [4/4] Loss: 0.24049 focal_loss 0.16128 dice_loss 0.07921 +Epoch [3386/4000] Validation metric {'Val/mean dice_metric': 0.975112795829773, 'Val/mean miou_metric': 0.9613621830940247, 'Val/mean f1': 0.9765918254852295, 'Val/mean precision': 0.9745436310768127, 'Val/mean recall': 0.9786486029624939, 'Val/mean hd95_metric': 4.837951183319092} +Cheakpoint... +Epoch [3386/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975112795829773, 'Val/mean miou_metric': 0.9613621830940247, 'Val/mean f1': 0.9765918254852295, 'Val/mean precision': 0.9745436310768127, 'Val/mean recall': 0.9786486029624939, 'Val/mean hd95_metric': 4.837951183319092} +Epoch [3387/4000] Training [1/16] Loss: 0.00306 +Epoch [3387/4000] Training [2/16] Loss: 0.00229 +Epoch [3387/4000] Training [3/16] Loss: 0.00411 +Epoch [3387/4000] Training [4/16] Loss: 0.00248 +Epoch [3387/4000] Training [5/16] Loss: 0.00188 +Epoch [3387/4000] Training [6/16] Loss: 0.00254 +Epoch [3387/4000] Training [7/16] Loss: 0.00255 +Epoch [3387/4000] Training [8/16] Loss: 0.00272 +Epoch [3387/4000] Training [9/16] Loss: 0.00207 +Epoch [3387/4000] Training [10/16] Loss: 0.00189 +Epoch [3387/4000] Training [11/16] Loss: 0.00216 +Epoch [3387/4000] Training [12/16] Loss: 0.00377 +Epoch [3387/4000] Training [13/16] Loss: 0.00314 +Epoch [3387/4000] Training [14/16] Loss: 0.00369 +Epoch [3387/4000] Training [15/16] Loss: 0.00250 +Epoch [3387/4000] Training [16/16] Loss: 0.00402 +Epoch [3387/4000] Training metric {'Train/mean dice_metric': 0.9985530376434326, 'Train/mean miou_metric': 0.9968281388282776, 'Train/mean f1': 0.9935354590415955, 'Train/mean precision': 0.9889188408851624, 'Train/mean recall': 0.9981954097747803, 'Train/mean hd95_metric': 0.6370393633842468} +Epoch [3387/4000] Validation [1/4] Loss: 0.40758 focal_loss 0.34323 dice_loss 0.06434 +Epoch [3387/4000] Validation [2/4] Loss: 1.06662 focal_loss 0.81147 dice_loss 0.25515 +Epoch [3387/4000] Validation [3/4] Loss: 0.48104 focal_loss 0.38505 dice_loss 0.09599 +Epoch [3387/4000] Validation [4/4] Loss: 0.45234 focal_loss 0.34239 dice_loss 0.10995 +Epoch [3387/4000] Validation metric {'Val/mean dice_metric': 0.9719894528388977, 'Val/mean miou_metric': 0.9582465887069702, 'Val/mean f1': 0.9758085608482361, 'Val/mean precision': 0.9745360612869263, 'Val/mean recall': 0.977084219455719, 'Val/mean hd95_metric': 5.153954029083252} +Cheakpoint... +Epoch [3387/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719894528388977, 'Val/mean miou_metric': 0.9582465887069702, 'Val/mean f1': 0.9758085608482361, 'Val/mean precision': 0.9745360612869263, 'Val/mean recall': 0.977084219455719, 'Val/mean hd95_metric': 5.153954029083252} +Epoch [3388/4000] Training [1/16] Loss: 0.00208 +Epoch [3388/4000] Training [2/16] Loss: 0.00328 +Epoch [3388/4000] Training [3/16] Loss: 0.00204 +Epoch [3388/4000] Training [4/16] Loss: 0.00229 +Epoch [3388/4000] Training [5/16] Loss: 0.00229 +Epoch [3388/4000] Training [6/16] Loss: 0.00187 +Epoch [3388/4000] Training [7/16] Loss: 0.00295 +Epoch [3388/4000] Training [8/16] Loss: 0.00250 +Epoch [3388/4000] Training [9/16] Loss: 0.00233 +Epoch [3388/4000] Training [10/16] Loss: 0.00172 +Epoch [3388/4000] Training [11/16] Loss: 0.00280 +Epoch [3388/4000] Training [12/16] Loss: 0.00447 +Epoch [3388/4000] Training [13/16] Loss: 0.00254 +Epoch [3388/4000] Training [14/16] Loss: 0.00276 +Epoch [3388/4000] Training [15/16] Loss: 0.00229 +Epoch [3388/4000] Training [16/16] Loss: 0.00202 +Epoch [3388/4000] Training metric {'Train/mean dice_metric': 0.9987410306930542, 'Train/mean miou_metric': 0.9972013235092163, 'Train/mean f1': 0.9937605261802673, 'Train/mean precision': 0.9892057180404663, 'Train/mean recall': 0.9983574151992798, 'Train/mean hd95_metric': 0.58371901512146} +Epoch [3388/4000] Validation [1/4] Loss: 0.36607 focal_loss 0.30326 dice_loss 0.06281 +Epoch [3388/4000] Validation [2/4] Loss: 1.40411 focal_loss 1.10962 dice_loss 0.29450 +Epoch [3388/4000] Validation [3/4] Loss: 0.51836 focal_loss 0.42367 dice_loss 0.09469 +Epoch [3388/4000] Validation [4/4] Loss: 0.48178 focal_loss 0.36722 dice_loss 0.11456 +Epoch [3388/4000] Validation metric {'Val/mean dice_metric': 0.9717389941215515, 'Val/mean miou_metric': 0.9580413699150085, 'Val/mean f1': 0.9758313298225403, 'Val/mean precision': 0.9742870926856995, 'Val/mean recall': 0.9773805141448975, 'Val/mean hd95_metric': 5.25940465927124} +Cheakpoint... +Epoch [3388/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717389941215515, 'Val/mean miou_metric': 0.9580413699150085, 'Val/mean f1': 0.9758313298225403, 'Val/mean precision': 0.9742870926856995, 'Val/mean recall': 0.9773805141448975, 'Val/mean hd95_metric': 5.25940465927124} +Epoch [3389/4000] Training [1/16] Loss: 0.00300 +Epoch [3389/4000] Training [2/16] Loss: 0.00214 +Epoch [3389/4000] Training [3/16] Loss: 0.00253 +Epoch [3389/4000] Training [4/16] Loss: 0.00279 +Epoch [3389/4000] Training [5/16] Loss: 0.00178 +Epoch [3389/4000] Training [6/16] Loss: 0.00342 +Epoch [3389/4000] Training [7/16] Loss: 0.00367 +Epoch [3389/4000] Training [8/16] Loss: 0.00303 +Epoch [3389/4000] Training [9/16] Loss: 0.00240 +Epoch [3389/4000] Training [10/16] Loss: 0.00227 +Epoch [3389/4000] Training [11/16] Loss: 0.00283 +Epoch [3389/4000] Training [12/16] Loss: 0.00238 +Epoch [3389/4000] Training [13/16] Loss: 0.00300 +Epoch [3389/4000] Training [14/16] Loss: 0.00213 +Epoch [3389/4000] Training [15/16] Loss: 0.00283 +Epoch [3389/4000] Training [16/16] Loss: 0.00230 +Epoch [3389/4000] Training metric {'Train/mean dice_metric': 0.9985126256942749, 'Train/mean miou_metric': 0.9967560768127441, 'Train/mean f1': 0.9935964941978455, 'Train/mean precision': 0.98904949426651, 'Train/mean recall': 0.9981855154037476, 'Train/mean hd95_metric': 0.6260446310043335} +Epoch [3389/4000] Validation [1/4] Loss: 0.52861 focal_loss 0.43899 dice_loss 0.08962 +Epoch [3389/4000] Validation [2/4] Loss: 0.63649 focal_loss 0.47895 dice_loss 0.15754 +Epoch [3389/4000] Validation [3/4] Loss: 0.51363 focal_loss 0.41647 dice_loss 0.09715 +Epoch [3389/4000] Validation [4/4] Loss: 0.35916 focal_loss 0.25547 dice_loss 0.10369 +Epoch [3389/4000] Validation metric {'Val/mean dice_metric': 0.9733012318611145, 'Val/mean miou_metric': 0.9588810205459595, 'Val/mean f1': 0.9754498600959778, 'Val/mean precision': 0.9745727777481079, 'Val/mean recall': 0.9763284921646118, 'Val/mean hd95_metric': 4.88340950012207} +Cheakpoint... +Epoch [3389/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733012318611145, 'Val/mean miou_metric': 0.9588810205459595, 'Val/mean f1': 0.9754498600959778, 'Val/mean precision': 0.9745727777481079, 'Val/mean recall': 0.9763284921646118, 'Val/mean hd95_metric': 4.88340950012207} +Epoch [3390/4000] Training [1/16] Loss: 0.00246 +Epoch [3390/4000] Training [2/16] Loss: 0.00187 +Epoch [3390/4000] Training [3/16] Loss: 0.00281 +Epoch [3390/4000] Training [4/16] Loss: 0.00358 +Epoch [3390/4000] Training [5/16] Loss: 0.00271 +Epoch [3390/4000] Training [6/16] Loss: 0.00221 +Epoch [3390/4000] Training [7/16] Loss: 0.00283 +Epoch [3390/4000] Training [8/16] Loss: 0.00369 +Epoch [3390/4000] Training [9/16] Loss: 0.00230 +Epoch [3390/4000] Training [10/16] Loss: 0.00182 +Epoch [3390/4000] Training [11/16] Loss: 0.00328 +Epoch [3390/4000] Training [12/16] Loss: 0.00301 +Epoch [3390/4000] Training [13/16] Loss: 0.00195 +Epoch [3390/4000] Training [14/16] Loss: 0.00184 +Epoch [3390/4000] Training [15/16] Loss: 0.00244 +Epoch [3390/4000] Training [16/16] Loss: 0.00250 +Epoch [3390/4000] Training metric {'Train/mean dice_metric': 0.9986931085586548, 'Train/mean miou_metric': 0.9970872402191162, 'Train/mean f1': 0.9930469989776611, 'Train/mean precision': 0.9878961443901062, 'Train/mean recall': 0.9982517957687378, 'Train/mean hd95_metric': 0.5834258794784546} +Epoch [3390/4000] Validation [1/4] Loss: 0.44324 focal_loss 0.37321 dice_loss 0.07003 +Epoch [3390/4000] Validation [2/4] Loss: 0.45936 focal_loss 0.35183 dice_loss 0.10752 +Epoch [3390/4000] Validation [3/4] Loss: 0.52499 focal_loss 0.43282 dice_loss 0.09217 +Epoch [3390/4000] Validation [4/4] Loss: 0.32765 focal_loss 0.24071 dice_loss 0.08695 +Epoch [3390/4000] Validation metric {'Val/mean dice_metric': 0.9750386476516724, 'Val/mean miou_metric': 0.9604578018188477, 'Val/mean f1': 0.9759196639060974, 'Val/mean precision': 0.9736401438713074, 'Val/mean recall': 0.9782098531723022, 'Val/mean hd95_metric': 4.722403526306152} +Cheakpoint... +Epoch [3390/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750386476516724, 'Val/mean miou_metric': 0.9604578018188477, 'Val/mean f1': 0.9759196639060974, 'Val/mean precision': 0.9736401438713074, 'Val/mean recall': 0.9782098531723022, 'Val/mean hd95_metric': 4.722403526306152} +Epoch [3391/4000] Training [1/16] Loss: 0.00347 +Epoch [3391/4000] Training [2/16] Loss: 0.00289 +Epoch [3391/4000] Training [3/16] Loss: 0.00238 +Epoch [3391/4000] Training [4/16] Loss: 0.00242 +Epoch [3391/4000] Training [5/16] Loss: 0.00343 +Epoch [3391/4000] Training [6/16] Loss: 0.00245 +Epoch [3391/4000] Training [7/16] Loss: 0.00302 +Epoch [3391/4000] Training [8/16] Loss: 0.00420 +Epoch [3391/4000] Training [9/16] Loss: 0.00238 +Epoch [3391/4000] Training [10/16] Loss: 0.00250 +Epoch [3391/4000] Training [11/16] Loss: 0.00306 +Epoch [3391/4000] Training [12/16] Loss: 0.00266 +Epoch [3391/4000] Training [13/16] Loss: 0.00277 +Epoch [3391/4000] Training [14/16] Loss: 0.00315 +Epoch [3391/4000] Training [15/16] Loss: 0.00293 +Epoch [3391/4000] Training [16/16] Loss: 0.00292 +Epoch [3391/4000] Training metric {'Train/mean dice_metric': 0.9984970092773438, 'Train/mean miou_metric': 0.996718168258667, 'Train/mean f1': 0.9935653805732727, 'Train/mean precision': 0.9889471530914307, 'Train/mean recall': 0.9982270002365112, 'Train/mean hd95_metric': 0.6386017203330994} +Epoch [3391/4000] Validation [1/4] Loss: 0.38895 focal_loss 0.32648 dice_loss 0.06247 +Epoch [3391/4000] Validation [2/4] Loss: 0.48004 focal_loss 0.36829 dice_loss 0.11175 +Epoch [3391/4000] Validation [3/4] Loss: 0.25638 focal_loss 0.19816 dice_loss 0.05822 +Epoch [3391/4000] Validation [4/4] Loss: 0.49395 focal_loss 0.37887 dice_loss 0.11508 +Epoch [3391/4000] Validation metric {'Val/mean dice_metric': 0.974960207939148, 'Val/mean miou_metric': 0.9609375, 'Val/mean f1': 0.9765133857727051, 'Val/mean precision': 0.9741281867027283, 'Val/mean recall': 0.9789103269577026, 'Val/mean hd95_metric': 5.153777122497559} +Cheakpoint... +Epoch [3391/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974960207939148, 'Val/mean miou_metric': 0.9609375, 'Val/mean f1': 0.9765133857727051, 'Val/mean precision': 0.9741281867027283, 'Val/mean recall': 0.9789103269577026, 'Val/mean hd95_metric': 5.153777122497559} +Epoch [3392/4000] Training [1/16] Loss: 0.00443 +Epoch [3392/4000] Training [2/16] Loss: 0.00215 +Epoch [3392/4000] Training [3/16] Loss: 0.00340 +Epoch [3392/4000] Training [4/16] Loss: 0.00239 +Epoch [3392/4000] Training [5/16] Loss: 0.00314 +Epoch [3392/4000] Training [6/16] Loss: 0.00245 +Epoch [3392/4000] Training [7/16] Loss: 0.00190 +Epoch [3392/4000] Training [8/16] Loss: 0.00259 +Epoch [3392/4000] Training [9/16] Loss: 0.00237 +Epoch [3392/4000] Training [10/16] Loss: 0.00239 +Epoch [3392/4000] Training [11/16] Loss: 0.00206 +Epoch [3392/4000] Training [12/16] Loss: 0.00271 +Epoch [3392/4000] Training [13/16] Loss: 0.00227 +Epoch [3392/4000] Training [14/16] Loss: 0.00207 +Epoch [3392/4000] Training [15/16] Loss: 0.00227 +Epoch [3392/4000] Training [16/16] Loss: 0.00276 +Epoch [3392/4000] Training metric {'Train/mean dice_metric': 0.9986640810966492, 'Train/mean miou_metric': 0.9970405697822571, 'Train/mean f1': 0.9935021996498108, 'Train/mean precision': 0.9887914657592773, 'Train/mean recall': 0.9982580542564392, 'Train/mean hd95_metric': 0.6031526327133179} +Epoch [3392/4000] Validation [1/4] Loss: 0.39560 focal_loss 0.33169 dice_loss 0.06391 +Epoch [3392/4000] Validation [2/4] Loss: 0.65651 focal_loss 0.49448 dice_loss 0.16203 +Epoch [3392/4000] Validation [3/4] Loss: 0.50825 focal_loss 0.41685 dice_loss 0.09140 +Epoch [3392/4000] Validation [4/4] Loss: 0.46009 focal_loss 0.35059 dice_loss 0.10950 +Epoch [3392/4000] Validation metric {'Val/mean dice_metric': 0.9741414189338684, 'Val/mean miou_metric': 0.9596654772758484, 'Val/mean f1': 0.9760851263999939, 'Val/mean precision': 0.974530041217804, 'Val/mean recall': 0.977645218372345, 'Val/mean hd95_metric': 4.680424690246582} +Cheakpoint... +Epoch [3392/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741414189338684, 'Val/mean miou_metric': 0.9596654772758484, 'Val/mean f1': 0.9760851263999939, 'Val/mean precision': 0.974530041217804, 'Val/mean recall': 0.977645218372345, 'Val/mean hd95_metric': 4.680424690246582} +Epoch [3393/4000] Training [1/16] Loss: 0.00217 +Epoch [3393/4000] Training [2/16] Loss: 0.00185 +Epoch [3393/4000] Training [3/16] Loss: 0.00214 +Epoch [3393/4000] Training [4/16] Loss: 0.00251 +Epoch [3393/4000] Training [5/16] Loss: 0.00250 +Epoch [3393/4000] Training [6/16] Loss: 0.00241 +Epoch [3393/4000] Training [7/16] Loss: 0.00182 +Epoch [3393/4000] Training [8/16] Loss: 0.00226 +Epoch [3393/4000] Training [9/16] Loss: 0.00202 +Epoch [3393/4000] Training [10/16] Loss: 0.00336 +Epoch [3393/4000] Training [11/16] Loss: 0.00182 +Epoch [3393/4000] Training [12/16] Loss: 0.00210 +Epoch [3393/4000] Training [13/16] Loss: 0.00291 +Epoch [3393/4000] Training [14/16] Loss: 0.00349 +Epoch [3393/4000] Training [15/16] Loss: 0.00251 +Epoch [3393/4000] Training [16/16] Loss: 0.00225 +Epoch [3393/4000] Training metric {'Train/mean dice_metric': 0.9987612962722778, 'Train/mean miou_metric': 0.9972251057624817, 'Train/mean f1': 0.9934636950492859, 'Train/mean precision': 0.9886085391044617, 'Train/mean recall': 0.9983668327331543, 'Train/mean hd95_metric': 0.5684568881988525} +Epoch [3393/4000] Validation [1/4] Loss: 0.37362 focal_loss 0.30934 dice_loss 0.06428 +Epoch [3393/4000] Validation [2/4] Loss: 0.52074 focal_loss 0.38788 dice_loss 0.13287 +Epoch [3393/4000] Validation [3/4] Loss: 0.52904 focal_loss 0.43252 dice_loss 0.09653 +Epoch [3393/4000] Validation [4/4] Loss: 0.35178 focal_loss 0.25962 dice_loss 0.09216 +Epoch [3393/4000] Validation metric {'Val/mean dice_metric': 0.9733524322509766, 'Val/mean miou_metric': 0.9594228863716125, 'Val/mean f1': 0.975810170173645, 'Val/mean precision': 0.9731717109680176, 'Val/mean recall': 0.9784631729125977, 'Val/mean hd95_metric': 5.516315937042236} +Cheakpoint... +Epoch [3393/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733524322509766, 'Val/mean miou_metric': 0.9594228863716125, 'Val/mean f1': 0.975810170173645, 'Val/mean precision': 0.9731717109680176, 'Val/mean recall': 0.9784631729125977, 'Val/mean hd95_metric': 5.516315937042236} +Epoch [3394/4000] Training [1/16] Loss: 0.00314 +Epoch [3394/4000] Training [2/16] Loss: 0.00250 +Epoch [3394/4000] Training [3/16] Loss: 0.00244 +Epoch [3394/4000] Training [4/16] Loss: 0.00255 +Epoch [3394/4000] Training [5/16] Loss: 0.00222 +Epoch [3394/4000] Training [6/16] Loss: 0.00172 +Epoch [3394/4000] Training [7/16] Loss: 0.00171 +Epoch [3394/4000] Training [8/16] Loss: 0.00384 +Epoch [3394/4000] Training [9/16] Loss: 0.00250 +Epoch [3394/4000] Training [10/16] Loss: 0.00443 +Epoch [3394/4000] Training [11/16] Loss: 0.00239 +Epoch [3394/4000] Training [12/16] Loss: 0.00379 +Epoch [3394/4000] Training [13/16] Loss: 0.00183 +Epoch [3394/4000] Training [14/16] Loss: 0.00252 +Epoch [3394/4000] Training [15/16] Loss: 0.00189 +Epoch [3394/4000] Training [16/16] Loss: 0.00284 +Epoch [3394/4000] Training metric {'Train/mean dice_metric': 0.9985830783843994, 'Train/mean miou_metric': 0.9968588352203369, 'Train/mean f1': 0.9927789568901062, 'Train/mean precision': 0.9875323176383972, 'Train/mean recall': 0.998081624507904, 'Train/mean hd95_metric': 0.6314918994903564} +Epoch [3394/4000] Validation [1/4] Loss: 0.37167 focal_loss 0.30986 dice_loss 0.06181 +Epoch [3394/4000] Validation [2/4] Loss: 0.58598 focal_loss 0.43868 dice_loss 0.14729 +Epoch [3394/4000] Validation [3/4] Loss: 0.50059 focal_loss 0.40883 dice_loss 0.09175 +Epoch [3394/4000] Validation [4/4] Loss: 0.38301 focal_loss 0.27483 dice_loss 0.10818 +Epoch [3394/4000] Validation metric {'Val/mean dice_metric': 0.9737085103988647, 'Val/mean miou_metric': 0.9595836400985718, 'Val/mean f1': 0.9756436347961426, 'Val/mean precision': 0.9729438424110413, 'Val/mean recall': 0.9783584475517273, 'Val/mean hd95_metric': 4.818737983703613} +Cheakpoint... +Epoch [3394/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737085103988647, 'Val/mean miou_metric': 0.9595836400985718, 'Val/mean f1': 0.9756436347961426, 'Val/mean precision': 0.9729438424110413, 'Val/mean recall': 0.9783584475517273, 'Val/mean hd95_metric': 4.818737983703613} +Epoch [3395/4000] Training [1/16] Loss: 0.00212 +Epoch [3395/4000] Training [2/16] Loss: 0.00175 +Epoch [3395/4000] Training [3/16] Loss: 0.00260 +Epoch [3395/4000] Training [4/16] Loss: 0.00272 +Epoch [3395/4000] Training [5/16] Loss: 0.00304 +Epoch [3395/4000] Training [6/16] Loss: 0.00234 +Epoch [3395/4000] Training [7/16] Loss: 0.00265 +Epoch [3395/4000] Training [8/16] Loss: 0.00255 +Epoch [3395/4000] Training [9/16] Loss: 0.00324 +Epoch [3395/4000] Training [10/16] Loss: 0.00258 +Epoch [3395/4000] Training [11/16] Loss: 0.00335 +Epoch [3395/4000] Training [12/16] Loss: 0.00389 +Epoch [3395/4000] Training [13/16] Loss: 0.00298 +Epoch [3395/4000] Training [14/16] Loss: 0.00385 +Epoch [3395/4000] Training [15/16] Loss: 0.00235 +Epoch [3395/4000] Training [16/16] Loss: 0.00257 +Epoch [3395/4000] Training metric {'Train/mean dice_metric': 0.9985746741294861, 'Train/mean miou_metric': 0.9968633055686951, 'Train/mean f1': 0.9935008883476257, 'Train/mean precision': 0.9887547492980957, 'Train/mean recall': 0.9982928037643433, 'Train/mean hd95_metric': 0.6122347116470337} +Epoch [3395/4000] Validation [1/4] Loss: 0.40930 focal_loss 0.34466 dice_loss 0.06464 +Epoch [3395/4000] Validation [2/4] Loss: 0.51402 focal_loss 0.37894 dice_loss 0.13508 +Epoch [3395/4000] Validation [3/4] Loss: 0.23457 focal_loss 0.18197 dice_loss 0.05259 +Epoch [3395/4000] Validation [4/4] Loss: 0.30850 focal_loss 0.21011 dice_loss 0.09840 +Epoch [3395/4000] Validation metric {'Val/mean dice_metric': 0.9745855331420898, 'Val/mean miou_metric': 0.9605148434638977, 'Val/mean f1': 0.9765926003456116, 'Val/mean precision': 0.9743070602416992, 'Val/mean recall': 0.9788888692855835, 'Val/mean hd95_metric': 4.600202560424805} +Cheakpoint... +Epoch [3395/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745855331420898, 'Val/mean miou_metric': 0.9605148434638977, 'Val/mean f1': 0.9765926003456116, 'Val/mean precision': 0.9743070602416992, 'Val/mean recall': 0.9788888692855835, 'Val/mean hd95_metric': 4.600202560424805} +Epoch [3396/4000] Training [1/16] Loss: 0.00219 +Epoch [3396/4000] Training [2/16] Loss: 0.00299 +Epoch [3396/4000] Training [3/16] Loss: 0.00207 +Epoch [3396/4000] Training [4/16] Loss: 0.00301 +Epoch [3396/4000] Training [5/16] Loss: 0.00198 +Epoch [3396/4000] Training [6/16] Loss: 0.00250 +Epoch [3396/4000] Training [7/16] Loss: 0.00291 +Epoch [3396/4000] Training [8/16] Loss: 0.00321 +Epoch [3396/4000] Training [9/16] Loss: 0.00176 +Epoch [3396/4000] Training [10/16] Loss: 0.00274 +Epoch [3396/4000] Training [11/16] Loss: 0.00213 +Epoch [3396/4000] Training [12/16] Loss: 0.00261 +Epoch [3396/4000] Training [13/16] Loss: 0.00265 +Epoch [3396/4000] Training [14/16] Loss: 0.00363 +Epoch [3396/4000] Training [15/16] Loss: 0.00242 +Epoch [3396/4000] Training [16/16] Loss: 0.00295 +Epoch [3396/4000] Training metric {'Train/mean dice_metric': 0.9985619783401489, 'Train/mean miou_metric': 0.9968029856681824, 'Train/mean f1': 0.9924109578132629, 'Train/mean precision': 0.9868285059928894, 'Train/mean recall': 0.998056948184967, 'Train/mean hd95_metric': 0.6099885702133179} +Epoch [3396/4000] Validation [1/4] Loss: 0.39263 focal_loss 0.33247 dice_loss 0.06016 +Epoch [3396/4000] Validation [2/4] Loss: 1.26368 focal_loss 1.07616 dice_loss 0.18752 +Epoch [3396/4000] Validation [3/4] Loss: 0.50631 focal_loss 0.41544 dice_loss 0.09087 +Epoch [3396/4000] Validation [4/4] Loss: 0.36805 focal_loss 0.26356 dice_loss 0.10449 +Epoch [3396/4000] Validation metric {'Val/mean dice_metric': 0.9738748669624329, 'Val/mean miou_metric': 0.9599498510360718, 'Val/mean f1': 0.9752238988876343, 'Val/mean precision': 0.9716033339500427, 'Val/mean recall': 0.9788714647293091, 'Val/mean hd95_metric': 4.677505016326904} +Cheakpoint... +Epoch [3396/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738748669624329, 'Val/mean miou_metric': 0.9599498510360718, 'Val/mean f1': 0.9752238988876343, 'Val/mean precision': 0.9716033339500427, 'Val/mean recall': 0.9788714647293091, 'Val/mean hd95_metric': 4.677505016326904} +Epoch [3397/4000] Training [1/16] Loss: 0.00221 +Epoch [3397/4000] Training [2/16] Loss: 0.00238 +Epoch [3397/4000] Training [3/16] Loss: 0.00492 +Epoch [3397/4000] Training [4/16] Loss: 0.00344 +Epoch [3397/4000] Training [5/16] Loss: 0.00262 +Epoch [3397/4000] Training [6/16] Loss: 0.00189 +Epoch [3397/4000] Training [7/16] Loss: 0.00225 +Epoch [3397/4000] Training [8/16] Loss: 0.00262 +Epoch [3397/4000] Training [9/16] Loss: 0.00309 +Epoch [3397/4000] Training [10/16] Loss: 0.00287 +Epoch [3397/4000] Training [11/16] Loss: 0.00175 +Epoch [3397/4000] Training [12/16] Loss: 0.00357 +Epoch [3397/4000] Training [13/16] Loss: 0.00285 +Epoch [3397/4000] Training [14/16] Loss: 0.00239 +Epoch [3397/4000] Training [15/16] Loss: 0.00170 +Epoch [3397/4000] Training [16/16] Loss: 0.00210 +Epoch [3397/4000] Training metric {'Train/mean dice_metric': 0.9986394047737122, 'Train/mean miou_metric': 0.9970033168792725, 'Train/mean f1': 0.9936270713806152, 'Train/mean precision': 0.989020824432373, 'Train/mean recall': 0.9982763528823853, 'Train/mean hd95_metric': 0.5756634473800659} +Epoch [3397/4000] Validation [1/4] Loss: 0.41554 focal_loss 0.35078 dice_loss 0.06477 +Epoch [3397/4000] Validation [2/4] Loss: 0.46090 focal_loss 0.34989 dice_loss 0.11101 +Epoch [3397/4000] Validation [3/4] Loss: 0.49909 focal_loss 0.40879 dice_loss 0.09031 +Epoch [3397/4000] Validation [4/4] Loss: 0.46216 focal_loss 0.34346 dice_loss 0.11870 +Epoch [3397/4000] Validation metric {'Val/mean dice_metric': 0.9744308590888977, 'Val/mean miou_metric': 0.9602778553962708, 'Val/mean f1': 0.9764062762260437, 'Val/mean precision': 0.9739506840705872, 'Val/mean recall': 0.9788742661476135, 'Val/mean hd95_metric': 4.683525562286377} +Cheakpoint... +Epoch [3397/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744308590888977, 'Val/mean miou_metric': 0.9602778553962708, 'Val/mean f1': 0.9764062762260437, 'Val/mean precision': 0.9739506840705872, 'Val/mean recall': 0.9788742661476135, 'Val/mean hd95_metric': 4.683525562286377} +Epoch [3398/4000] Training [1/16] Loss: 0.00347 +Epoch [3398/4000] Training [2/16] Loss: 0.00270 +Epoch [3398/4000] Training [3/16] Loss: 0.00321 +Epoch [3398/4000] Training [4/16] Loss: 0.00332 +Epoch [3398/4000] Training [5/16] Loss: 0.00319 +Epoch [3398/4000] Training [6/16] Loss: 0.00377 +Epoch [3398/4000] Training [7/16] Loss: 0.00430 +Epoch [3398/4000] Training [8/16] Loss: 0.00314 +Epoch [3398/4000] Training [9/16] Loss: 0.00197 +Epoch [3398/4000] Training [10/16] Loss: 0.00194 +Epoch [3398/4000] Training [11/16] Loss: 0.00406 +Epoch [3398/4000] Training [12/16] Loss: 0.00204 +Epoch [3398/4000] Training [13/16] Loss: 0.00277 +Epoch [3398/4000] Training [14/16] Loss: 0.00208 +Epoch [3398/4000] Training [15/16] Loss: 0.00162 +Epoch [3398/4000] Training [16/16] Loss: 0.00302 +Epoch [3398/4000] Training metric {'Train/mean dice_metric': 0.9984610676765442, 'Train/mean miou_metric': 0.9966459274291992, 'Train/mean f1': 0.9933120608329773, 'Train/mean precision': 0.9886198043823242, 'Train/mean recall': 0.9980491399765015, 'Train/mean hd95_metric': 0.6049382090568542} +Epoch [3398/4000] Validation [1/4] Loss: 0.46219 focal_loss 0.39632 dice_loss 0.06587 +Epoch [3398/4000] Validation [2/4] Loss: 0.92527 focal_loss 0.73838 dice_loss 0.18689 +Epoch [3398/4000] Validation [3/4] Loss: 0.51710 focal_loss 0.41803 dice_loss 0.09907 +Epoch [3398/4000] Validation [4/4] Loss: 0.33497 focal_loss 0.23984 dice_loss 0.09513 +Epoch [3398/4000] Validation metric {'Val/mean dice_metric': 0.9752932786941528, 'Val/mean miou_metric': 0.9613796472549438, 'Val/mean f1': 0.9760839343070984, 'Val/mean precision': 0.9729713797569275, 'Val/mean recall': 0.9792165160179138, 'Val/mean hd95_metric': 5.023881435394287} +Cheakpoint... +Epoch [3398/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752932786941528, 'Val/mean miou_metric': 0.9613796472549438, 'Val/mean f1': 0.9760839343070984, 'Val/mean precision': 0.9729713797569275, 'Val/mean recall': 0.9792165160179138, 'Val/mean hd95_metric': 5.023881435394287} +Epoch [3399/4000] Training [1/16] Loss: 0.00207 +Epoch [3399/4000] Training [2/16] Loss: 0.00334 +Epoch [3399/4000] Training [3/16] Loss: 0.00217 +Epoch [3399/4000] Training [4/16] Loss: 0.00217 +Epoch [3399/4000] Training [5/16] Loss: 0.00418 +Epoch [3399/4000] Training [6/16] Loss: 0.00441 +Epoch [3399/4000] Training [7/16] Loss: 0.00224 +Epoch [3399/4000] Training [8/16] Loss: 0.00192 +Epoch [3399/4000] Training [9/16] Loss: 0.00185 +Epoch [3399/4000] Training [10/16] Loss: 0.00306 +Epoch [3399/4000] Training [11/16] Loss: 0.00430 +Epoch [3399/4000] Training [12/16] Loss: 0.00242 +Epoch [3399/4000] Training [13/16] Loss: 0.00287 +Epoch [3399/4000] Training [14/16] Loss: 0.00215 +Epoch [3399/4000] Training [15/16] Loss: 0.00233 +Epoch [3399/4000] Training [16/16] Loss: 0.00243 +Epoch [3399/4000] Training metric {'Train/mean dice_metric': 0.9986393451690674, 'Train/mean miou_metric': 0.9969813227653503, 'Train/mean f1': 0.9933375716209412, 'Train/mean precision': 0.9885125160217285, 'Train/mean recall': 0.9982099533081055, 'Train/mean hd95_metric': 0.5924104452133179} +Epoch [3399/4000] Validation [1/4] Loss: 0.41417 focal_loss 0.34939 dice_loss 0.06478 +Epoch [3399/4000] Validation [2/4] Loss: 0.95335 focal_loss 0.73566 dice_loss 0.21769 +Epoch [3399/4000] Validation [3/4] Loss: 0.51750 focal_loss 0.42017 dice_loss 0.09733 +Epoch [3399/4000] Validation [4/4] Loss: 0.45579 focal_loss 0.34702 dice_loss 0.10877 +Epoch [3399/4000] Validation metric {'Val/mean dice_metric': 0.9739009737968445, 'Val/mean miou_metric': 0.9597029685974121, 'Val/mean f1': 0.9759719371795654, 'Val/mean precision': 0.9735419154167175, 'Val/mean recall': 0.9784140586853027, 'Val/mean hd95_metric': 4.8591628074646} +Cheakpoint... +Epoch [3399/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739009737968445, 'Val/mean miou_metric': 0.9597029685974121, 'Val/mean f1': 0.9759719371795654, 'Val/mean precision': 0.9735419154167175, 'Val/mean recall': 0.9784140586853027, 'Val/mean hd95_metric': 4.8591628074646} +Epoch [3400/4000] Training [1/16] Loss: 0.00225 +Epoch [3400/4000] Training [2/16] Loss: 0.00205 +Epoch [3400/4000] Training [3/16] Loss: 0.00256 +Epoch [3400/4000] Training [4/16] Loss: 0.00179 +Epoch [3400/4000] Training [5/16] Loss: 0.00334 +Epoch [3400/4000] Training [6/16] Loss: 0.00296 +Epoch [3400/4000] Training [7/16] Loss: 0.00244 +Epoch [3400/4000] Training [8/16] Loss: 0.00277 +Epoch [3400/4000] Training [9/16] Loss: 0.00294 +Epoch [3400/4000] Training [10/16] Loss: 0.00209 +Epoch [3400/4000] Training [11/16] Loss: 0.00291 +Epoch [3400/4000] Training [12/16] Loss: 0.00384 +Epoch [3400/4000] Training [13/16] Loss: 0.00387 +Epoch [3400/4000] Training [14/16] Loss: 0.00298 +Epoch [3400/4000] Training [15/16] Loss: 0.00251 +Epoch [3400/4000] Training [16/16] Loss: 0.00354 +Epoch [3400/4000] Training metric {'Train/mean dice_metric': 0.9985764026641846, 'Train/mean miou_metric': 0.9968804121017456, 'Train/mean f1': 0.9936727285385132, 'Train/mean precision': 0.9891107082366943, 'Train/mean recall': 0.9982770085334778, 'Train/mean hd95_metric': 0.6324082612991333} +Epoch [3400/4000] Validation [1/4] Loss: 0.40834 focal_loss 0.34274 dice_loss 0.06559 +Epoch [3400/4000] Validation [2/4] Loss: 0.54655 focal_loss 0.40540 dice_loss 0.14116 +Epoch [3400/4000] Validation [3/4] Loss: 0.56325 focal_loss 0.46541 dice_loss 0.09785 +Epoch [3400/4000] Validation [4/4] Loss: 0.34369 focal_loss 0.24856 dice_loss 0.09513 +Epoch [3400/4000] Validation metric {'Val/mean dice_metric': 0.9739894866943359, 'Val/mean miou_metric': 0.9596532583236694, 'Val/mean f1': 0.9763786196708679, 'Val/mean precision': 0.9740636944770813, 'Val/mean recall': 0.9787046313285828, 'Val/mean hd95_metric': 5.1357316970825195} +Cheakpoint... +Epoch [3400/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739894866943359, 'Val/mean miou_metric': 0.9596532583236694, 'Val/mean f1': 0.9763786196708679, 'Val/mean precision': 0.9740636944770813, 'Val/mean recall': 0.9787046313285828, 'Val/mean hd95_metric': 5.1357316970825195} +Epoch [3401/4000] Training [1/16] Loss: 0.00240 +Epoch [3401/4000] Training [2/16] Loss: 0.00337 +Epoch [3401/4000] Training [3/16] Loss: 0.00305 +Epoch [3401/4000] Training [4/16] Loss: 0.00176 +Epoch [3401/4000] Training [5/16] Loss: 0.00317 +Epoch [3401/4000] Training [6/16] Loss: 0.00391 +Epoch [3401/4000] Training [7/16] Loss: 0.00269 +Epoch [3401/4000] Training [8/16] Loss: 0.00245 +Epoch [3401/4000] Training [9/16] Loss: 0.00309 +Epoch [3401/4000] Training [10/16] Loss: 0.00314 +Epoch [3401/4000] Training [11/16] Loss: 0.00244 +Epoch [3401/4000] Training [12/16] Loss: 0.00235 +Epoch [3401/4000] Training [13/16] Loss: 0.00267 +Epoch [3401/4000] Training [14/16] Loss: 0.00253 +Epoch [3401/4000] Training [15/16] Loss: 0.00233 +Epoch [3401/4000] Training [16/16] Loss: 0.00329 +Epoch [3401/4000] Training metric {'Train/mean dice_metric': 0.9986070394515991, 'Train/mean miou_metric': 0.9969431757926941, 'Train/mean f1': 0.9937244653701782, 'Train/mean precision': 0.9892400503158569, 'Train/mean recall': 0.9982497096061707, 'Train/mean hd95_metric': 0.6050080060958862} +Epoch [3401/4000] Validation [1/4] Loss: 0.46630 focal_loss 0.38809 dice_loss 0.07821 +Epoch [3401/4000] Validation [2/4] Loss: 0.41921 focal_loss 0.31892 dice_loss 0.10029 +Epoch [3401/4000] Validation [3/4] Loss: 0.53872 focal_loss 0.44350 dice_loss 0.09522 +Epoch [3401/4000] Validation [4/4] Loss: 0.37703 focal_loss 0.27387 dice_loss 0.10316 +Epoch [3401/4000] Validation metric {'Val/mean dice_metric': 0.9747985601425171, 'Val/mean miou_metric': 0.9605767130851746, 'Val/mean f1': 0.9765138626098633, 'Val/mean precision': 0.9737687110900879, 'Val/mean recall': 0.9792745113372803, 'Val/mean hd95_metric': 4.835666656494141} +Cheakpoint... +Epoch [3401/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747985601425171, 'Val/mean miou_metric': 0.9605767130851746, 'Val/mean f1': 0.9765138626098633, 'Val/mean precision': 0.9737687110900879, 'Val/mean recall': 0.9792745113372803, 'Val/mean hd95_metric': 4.835666656494141} +Epoch [3402/4000] Training [1/16] Loss: 0.00237 +Epoch [3402/4000] Training [2/16] Loss: 0.00299 +Epoch [3402/4000] Training [3/16] Loss: 0.00202 +Epoch [3402/4000] Training [4/16] Loss: 0.00266 +Epoch [3402/4000] Training [5/16] Loss: 0.00181 +Epoch [3402/4000] Training [6/16] Loss: 0.00261 +Epoch [3402/4000] Training [7/16] Loss: 0.00184 +Epoch [3402/4000] Training [8/16] Loss: 0.00286 +Epoch [3402/4000] Training [9/16] Loss: 0.00218 +Epoch [3402/4000] Training [10/16] Loss: 0.00188 +Epoch [3402/4000] Training [11/16] Loss: 0.00239 +Epoch [3402/4000] Training [12/16] Loss: 0.00242 +Epoch [3402/4000] Training [13/16] Loss: 0.00220 +Epoch [3402/4000] Training [14/16] Loss: 0.00187 +Epoch [3402/4000] Training [15/16] Loss: 0.00290 +Epoch [3402/4000] Training [16/16] Loss: 0.00210 +Epoch [3402/4000] Training metric {'Train/mean dice_metric': 0.9987611770629883, 'Train/mean miou_metric': 0.9972509145736694, 'Train/mean f1': 0.9938066005706787, 'Train/mean precision': 0.9892634153366089, 'Train/mean recall': 0.9983916878700256, 'Train/mean hd95_metric': 0.5760040283203125} +Epoch [3402/4000] Validation [1/4] Loss: 0.46929 focal_loss 0.39071 dice_loss 0.07859 +Epoch [3402/4000] Validation [2/4] Loss: 0.46352 focal_loss 0.33712 dice_loss 0.12640 +Epoch [3402/4000] Validation [3/4] Loss: 0.52378 focal_loss 0.42750 dice_loss 0.09628 +Epoch [3402/4000] Validation [4/4] Loss: 0.44333 focal_loss 0.33432 dice_loss 0.10901 +Epoch [3402/4000] Validation metric {'Val/mean dice_metric': 0.9742236137390137, 'Val/mean miou_metric': 0.9600276947021484, 'Val/mean f1': 0.9763508439064026, 'Val/mean precision': 0.9743626117706299, 'Val/mean recall': 0.9783473610877991, 'Val/mean hd95_metric': 4.811925411224365} +Cheakpoint... +Epoch [3402/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742236137390137, 'Val/mean miou_metric': 0.9600276947021484, 'Val/mean f1': 0.9763508439064026, 'Val/mean precision': 0.9743626117706299, 'Val/mean recall': 0.9783473610877991, 'Val/mean hd95_metric': 4.811925411224365} +Epoch [3403/4000] Training [1/16] Loss: 0.00200 +Epoch [3403/4000] Training [2/16] Loss: 0.00256 +Epoch [3403/4000] Training [3/16] Loss: 0.00343 +Epoch [3403/4000] Training [4/16] Loss: 0.00223 +Epoch [3403/4000] Training [5/16] Loss: 0.00270 +Epoch [3403/4000] Training [6/16] Loss: 0.00172 +Epoch [3403/4000] Training [7/16] Loss: 0.00188 +Epoch [3403/4000] Training [8/16] Loss: 0.00251 +Epoch [3403/4000] Training [9/16] Loss: 0.00160 +Epoch [3403/4000] Training [10/16] Loss: 0.00297 +Epoch [3403/4000] Training [11/16] Loss: 0.00233 +Epoch [3403/4000] Training [12/16] Loss: 0.00176 +Epoch [3403/4000] Training [13/16] Loss: 0.00309 +Epoch [3403/4000] Training [14/16] Loss: 0.00308 +Epoch [3403/4000] Training [15/16] Loss: 0.00382 +Epoch [3403/4000] Training [16/16] Loss: 0.00203 +Epoch [3403/4000] Training metric {'Train/mean dice_metric': 0.9987495541572571, 'Train/mean miou_metric': 0.9971901774406433, 'Train/mean f1': 0.9930317401885986, 'Train/mean precision': 0.9878111481666565, 'Train/mean recall': 0.9983077645301819, 'Train/mean hd95_metric': 0.5572540760040283} +Epoch [3403/4000] Validation [1/4] Loss: 0.35868 focal_loss 0.29696 dice_loss 0.06172 +Epoch [3403/4000] Validation [2/4] Loss: 0.50953 focal_loss 0.37250 dice_loss 0.13703 +Epoch [3403/4000] Validation [3/4] Loss: 0.52845 focal_loss 0.43477 dice_loss 0.09368 +Epoch [3403/4000] Validation [4/4] Loss: 0.29124 focal_loss 0.19960 dice_loss 0.09164 +Epoch [3403/4000] Validation metric {'Val/mean dice_metric': 0.9742988348007202, 'Val/mean miou_metric': 0.960374653339386, 'Val/mean f1': 0.9759365916252136, 'Val/mean precision': 0.9727813005447388, 'Val/mean recall': 0.979112446308136, 'Val/mean hd95_metric': 4.79655647277832} +Cheakpoint... +Epoch [3403/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742988348007202, 'Val/mean miou_metric': 0.960374653339386, 'Val/mean f1': 0.9759365916252136, 'Val/mean precision': 0.9727813005447388, 'Val/mean recall': 0.979112446308136, 'Val/mean hd95_metric': 4.79655647277832} +Epoch [3404/4000] Training [1/16] Loss: 0.00287 +Epoch [3404/4000] Training [2/16] Loss: 0.00381 +Epoch [3404/4000] Training [3/16] Loss: 0.00238 +Epoch [3404/4000] Training [4/16] Loss: 0.00252 +Epoch [3404/4000] Training [5/16] Loss: 0.00235 +Epoch [3404/4000] Training [6/16] Loss: 0.00341 +Epoch [3404/4000] Training [7/16] Loss: 0.00365 +Epoch [3404/4000] Training [8/16] Loss: 0.00300 +Epoch [3404/4000] Training [9/16] Loss: 0.00252 +Epoch [3404/4000] Training [10/16] Loss: 0.00235 +Epoch [3404/4000] Training [11/16] Loss: 0.00181 +Epoch [3404/4000] Training [12/16] Loss: 0.00283 +Epoch [3404/4000] Training [13/16] Loss: 0.00163 +Epoch [3404/4000] Training [14/16] Loss: 0.00230 +Epoch [3404/4000] Training [15/16] Loss: 0.00310 +Epoch [3404/4000] Training [16/16] Loss: 0.00221 +Epoch [3404/4000] Training metric {'Train/mean dice_metric': 0.998720645904541, 'Train/mean miou_metric': 0.9971431493759155, 'Train/mean f1': 0.9934579133987427, 'Train/mean precision': 0.9886611104011536, 'Train/mean recall': 0.9983014464378357, 'Train/mean hd95_metric': 0.5482696294784546} +Epoch [3404/4000] Validation [1/4] Loss: 0.38396 focal_loss 0.31871 dice_loss 0.06526 +Epoch [3404/4000] Validation [2/4] Loss: 0.47087 focal_loss 0.35808 dice_loss 0.11278 +Epoch [3404/4000] Validation [3/4] Loss: 0.53125 focal_loss 0.43748 dice_loss 0.09377 +Epoch [3404/4000] Validation [4/4] Loss: 0.32897 focal_loss 0.23390 dice_loss 0.09507 +Epoch [3404/4000] Validation metric {'Val/mean dice_metric': 0.9732615351676941, 'Val/mean miou_metric': 0.9592269062995911, 'Val/mean f1': 0.9761934876441956, 'Val/mean precision': 0.9746791124343872, 'Val/mean recall': 0.9777125120162964, 'Val/mean hd95_metric': 4.758819580078125} +Cheakpoint... +Epoch [3404/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732615351676941, 'Val/mean miou_metric': 0.9592269062995911, 'Val/mean f1': 0.9761934876441956, 'Val/mean precision': 0.9746791124343872, 'Val/mean recall': 0.9777125120162964, 'Val/mean hd95_metric': 4.758819580078125} +Epoch [3405/4000] Training [1/16] Loss: 0.00208 +Epoch [3405/4000] Training [2/16] Loss: 0.00257 +Epoch [3405/4000] Training [3/16] Loss: 0.00254 +Epoch [3405/4000] Training [4/16] Loss: 0.00220 +Epoch [3405/4000] Training [5/16] Loss: 0.00264 +Epoch [3405/4000] Training [6/16] Loss: 0.00255 +Epoch [3405/4000] Training [7/16] Loss: 0.00224 +Epoch [3405/4000] Training [8/16] Loss: 0.00251 +Epoch [3405/4000] Training [9/16] Loss: 0.00223 +Epoch [3405/4000] Training [10/16] Loss: 0.00254 +Epoch [3405/4000] Training [11/16] Loss: 0.00358 +Epoch [3405/4000] Training [12/16] Loss: 0.00276 +Epoch [3405/4000] Training [13/16] Loss: 0.00176 +Epoch [3405/4000] Training [14/16] Loss: 0.00316 +Epoch [3405/4000] Training [15/16] Loss: 0.00258 +Epoch [3405/4000] Training [16/16] Loss: 0.00206 +Epoch [3405/4000] Training metric {'Train/mean dice_metric': 0.9986749887466431, 'Train/mean miou_metric': 0.9970755577087402, 'Train/mean f1': 0.9936622977256775, 'Train/mean precision': 0.9890900254249573, 'Train/mean recall': 0.9982770085334778, 'Train/mean hd95_metric': 0.5876530408859253} +Epoch [3405/4000] Validation [1/4] Loss: 0.41893 focal_loss 0.35184 dice_loss 0.06709 +Epoch [3405/4000] Validation [2/4] Loss: 0.95599 focal_loss 0.74060 dice_loss 0.21538 +Epoch [3405/4000] Validation [3/4] Loss: 0.51696 focal_loss 0.42079 dice_loss 0.09617 +Epoch [3405/4000] Validation [4/4] Loss: 0.48046 focal_loss 0.36690 dice_loss 0.11356 +Epoch [3405/4000] Validation metric {'Val/mean dice_metric': 0.9735456705093384, 'Val/mean miou_metric': 0.9592620730400085, 'Val/mean f1': 0.9762548208236694, 'Val/mean precision': 0.9740618467330933, 'Val/mean recall': 0.9784575700759888, 'Val/mean hd95_metric': 4.781914234161377} +Cheakpoint... +Epoch [3405/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735456705093384, 'Val/mean miou_metric': 0.9592620730400085, 'Val/mean f1': 0.9762548208236694, 'Val/mean precision': 0.9740618467330933, 'Val/mean recall': 0.9784575700759888, 'Val/mean hd95_metric': 4.781914234161377} +Epoch [3406/4000] Training [1/16] Loss: 0.00253 +Epoch [3406/4000] Training [2/16] Loss: 0.00319 +Epoch [3406/4000] Training [3/16] Loss: 0.00204 +Epoch [3406/4000] Training [4/16] Loss: 0.00275 +Epoch [3406/4000] Training [5/16] Loss: 0.00341 +Epoch [3406/4000] Training [6/16] Loss: 0.00223 +Epoch [3406/4000] Training [7/16] Loss: 0.00199 +Epoch [3406/4000] Training [8/16] Loss: 0.00236 +Epoch [3406/4000] Training [9/16] Loss: 0.00221 +Epoch [3406/4000] Training [10/16] Loss: 0.00729 +Epoch [3406/4000] Training [11/16] Loss: 0.00223 +Epoch [3406/4000] Training [12/16] Loss: 0.00314 +Epoch [3406/4000] Training [13/16] Loss: 0.00199 +Epoch [3406/4000] Training [14/16] Loss: 0.00319 +Epoch [3406/4000] Training [15/16] Loss: 0.00187 +Epoch [3406/4000] Training [16/16] Loss: 0.00500 +Epoch [3406/4000] Training metric {'Train/mean dice_metric': 0.998528242111206, 'Train/mean miou_metric': 0.9967566132545471, 'Train/mean f1': 0.9928786158561707, 'Train/mean precision': 0.987736165523529, 'Train/mean recall': 0.9980748891830444, 'Train/mean hd95_metric': 0.5684191584587097} +Epoch [3406/4000] Validation [1/4] Loss: 0.37779 focal_loss 0.31221 dice_loss 0.06557 +Epoch [3406/4000] Validation [2/4] Loss: 0.43317 focal_loss 0.32975 dice_loss 0.10342 +Epoch [3406/4000] Validation [3/4] Loss: 0.53839 focal_loss 0.44396 dice_loss 0.09443 +Epoch [3406/4000] Validation [4/4] Loss: 0.34807 focal_loss 0.25198 dice_loss 0.09609 +Epoch [3406/4000] Validation metric {'Val/mean dice_metric': 0.9749321937561035, 'Val/mean miou_metric': 0.9602935910224915, 'Val/mean f1': 0.9759348630905151, 'Val/mean precision': 0.9729609489440918, 'Val/mean recall': 0.9789268970489502, 'Val/mean hd95_metric': 4.679287433624268} +Cheakpoint... +Epoch [3406/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749321937561035, 'Val/mean miou_metric': 0.9602935910224915, 'Val/mean f1': 0.9759348630905151, 'Val/mean precision': 0.9729609489440918, 'Val/mean recall': 0.9789268970489502, 'Val/mean hd95_metric': 4.679287433624268} +Epoch [3407/4000] Training [1/16] Loss: 0.01878 +Epoch [3407/4000] Training [2/16] Loss: 0.00205 +Epoch [3407/4000] Training [3/16] Loss: 0.00201 +Epoch [3407/4000] Training [4/16] Loss: 0.00260 +Epoch [3407/4000] Training [5/16] Loss: 0.00263 +Epoch [3407/4000] Training [6/16] Loss: 0.00223 +Epoch [3407/4000] Training [7/16] Loss: 0.00270 +Epoch [3407/4000] Training [8/16] Loss: 0.00246 +Epoch [3407/4000] Training [9/16] Loss: 0.00233 +Epoch [3407/4000] Training [10/16] Loss: 0.00282 +Epoch [3407/4000] Training [11/16] Loss: 0.00285 +Epoch [3407/4000] Training [12/16] Loss: 0.00195 +Epoch [3407/4000] Training [13/16] Loss: 0.00265 +Epoch [3407/4000] Training [14/16] Loss: 0.00282 +Epoch [3407/4000] Training [15/16] Loss: 0.00186 +Epoch [3407/4000] Training [16/16] Loss: 0.00182 +Epoch [3407/4000] Training metric {'Train/mean dice_metric': 0.9984625577926636, 'Train/mean miou_metric': 0.9966322779655457, 'Train/mean f1': 0.9927271008491516, 'Train/mean precision': 0.987453818321228, 'Train/mean recall': 0.998056948184967, 'Train/mean hd95_metric': 0.72184818983078} +Epoch [3407/4000] Validation [1/4] Loss: 0.40419 focal_loss 0.34022 dice_loss 0.06397 +Epoch [3407/4000] Validation [2/4] Loss: 0.54552 focal_loss 0.40653 dice_loss 0.13899 +Epoch [3407/4000] Validation [3/4] Loss: 0.25544 focal_loss 0.19862 dice_loss 0.05682 +Epoch [3407/4000] Validation [4/4] Loss: 0.33734 focal_loss 0.24238 dice_loss 0.09495 +Epoch [3407/4000] Validation metric {'Val/mean dice_metric': 0.9753171801567078, 'Val/mean miou_metric': 0.9613054990768433, 'Val/mean f1': 0.9759557247161865, 'Val/mean precision': 0.9721245169639587, 'Val/mean recall': 0.9798171520233154, 'Val/mean hd95_metric': 5.131606578826904} +Cheakpoint... +Epoch [3407/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753171801567078, 'Val/mean miou_metric': 0.9613054990768433, 'Val/mean f1': 0.9759557247161865, 'Val/mean precision': 0.9721245169639587, 'Val/mean recall': 0.9798171520233154, 'Val/mean hd95_metric': 5.131606578826904} +Epoch [3408/4000] Training [1/16] Loss: 0.00202 +Epoch [3408/4000] Training [2/16] Loss: 0.00317 +Epoch [3408/4000] Training [3/16] Loss: 0.00324 +Epoch [3408/4000] Training [4/16] Loss: 0.00295 +Epoch [3408/4000] Training [5/16] Loss: 0.00236 +Epoch [3408/4000] Training [6/16] Loss: 0.00265 +Epoch [3408/4000] Training [7/16] Loss: 0.00206 +Epoch [3408/4000] Training [8/16] Loss: 0.00248 +Epoch [3408/4000] Training [9/16] Loss: 0.00354 +Epoch [3408/4000] Training [10/16] Loss: 0.00377 +Epoch [3408/4000] Training [11/16] Loss: 0.00290 +Epoch [3408/4000] Training [12/16] Loss: 0.00219 +Epoch [3408/4000] Training [13/16] Loss: 0.00245 +Epoch [3408/4000] Training [14/16] Loss: 0.00385 +Epoch [3408/4000] Training [15/16] Loss: 0.00240 +Epoch [3408/4000] Training [16/16] Loss: 0.00277 +Epoch [3408/4000] Training metric {'Train/mean dice_metric': 0.9986225366592407, 'Train/mean miou_metric': 0.9969499111175537, 'Train/mean f1': 0.9930641651153564, 'Train/mean precision': 0.9879300594329834, 'Train/mean recall': 0.9982519149780273, 'Train/mean hd95_metric': 0.6137970685958862} +Epoch [3408/4000] Validation [1/4] Loss: 0.39784 focal_loss 0.33254 dice_loss 0.06530 +Epoch [3408/4000] Validation [2/4] Loss: 0.43870 focal_loss 0.33359 dice_loss 0.10511 +Epoch [3408/4000] Validation [3/4] Loss: 0.55191 focal_loss 0.45542 dice_loss 0.09649 +Epoch [3408/4000] Validation [4/4] Loss: 0.44667 focal_loss 0.33417 dice_loss 0.11250 +Epoch [3408/4000] Validation metric {'Val/mean dice_metric': 0.9733177423477173, 'Val/mean miou_metric': 0.959139347076416, 'Val/mean f1': 0.975812554359436, 'Val/mean precision': 0.9736093282699585, 'Val/mean recall': 0.9780259728431702, 'Val/mean hd95_metric': 4.799942970275879} +Cheakpoint... +Epoch [3408/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733177423477173, 'Val/mean miou_metric': 0.959139347076416, 'Val/mean f1': 0.975812554359436, 'Val/mean precision': 0.9736093282699585, 'Val/mean recall': 0.9780259728431702, 'Val/mean hd95_metric': 4.799942970275879} +Epoch [3409/4000] Training [1/16] Loss: 0.00181 +Epoch [3409/4000] Training [2/16] Loss: 0.00203 +Epoch [3409/4000] Training [3/16] Loss: 0.00221 +Epoch [3409/4000] Training [4/16] Loss: 0.00220 +Epoch [3409/4000] Training [5/16] Loss: 0.00291 +Epoch [3409/4000] Training [6/16] Loss: 0.00298 +Epoch [3409/4000] Training [7/16] Loss: 0.00247 +Epoch [3409/4000] Training [8/16] Loss: 0.00242 +Epoch [3409/4000] Training [9/16] Loss: 0.00235 +Epoch [3409/4000] Training [10/16] Loss: 0.00267 +Epoch [3409/4000] Training [11/16] Loss: 0.00162 +Epoch [3409/4000] Training [12/16] Loss: 0.00594 +Epoch [3409/4000] Training [13/16] Loss: 0.00190 +Epoch [3409/4000] Training [14/16] Loss: 0.00194 +Epoch [3409/4000] Training [15/16] Loss: 0.00266 +Epoch [3409/4000] Training [16/16] Loss: 0.00175 +Epoch [3409/4000] Training metric {'Train/mean dice_metric': 0.9986187815666199, 'Train/mean miou_metric': 0.9969689846038818, 'Train/mean f1': 0.9937391877174377, 'Train/mean precision': 0.9892023205757141, 'Train/mean recall': 0.9983178973197937, 'Train/mean hd95_metric': 0.5731261968612671} +Epoch [3409/4000] Validation [1/4] Loss: 0.37609 focal_loss 0.31449 dice_loss 0.06160 +Epoch [3409/4000] Validation [2/4] Loss: 0.43040 focal_loss 0.32710 dice_loss 0.10330 +Epoch [3409/4000] Validation [3/4] Loss: 0.53438 focal_loss 0.43696 dice_loss 0.09742 +Epoch [3409/4000] Validation [4/4] Loss: 0.33258 focal_loss 0.23873 dice_loss 0.09385 +Epoch [3409/4000] Validation metric {'Val/mean dice_metric': 0.9745985865592957, 'Val/mean miou_metric': 0.960544764995575, 'Val/mean f1': 0.9765635132789612, 'Val/mean precision': 0.9739204049110413, 'Val/mean recall': 0.9792208671569824, 'Val/mean hd95_metric': 4.992669105529785} +Cheakpoint... +Epoch [3409/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745985865592957, 'Val/mean miou_metric': 0.960544764995575, 'Val/mean f1': 0.9765635132789612, 'Val/mean precision': 0.9739204049110413, 'Val/mean recall': 0.9792208671569824, 'Val/mean hd95_metric': 4.992669105529785} +Epoch [3410/4000] Training [1/16] Loss: 0.00206 +Epoch [3410/4000] Training [2/16] Loss: 0.00318 +Epoch [3410/4000] Training [3/16] Loss: 0.00215 +Epoch [3410/4000] Training [4/16] Loss: 0.00272 +Epoch [3410/4000] Training [5/16] Loss: 0.00211 +Epoch [3410/4000] Training [6/16] Loss: 0.00286 +Epoch [3410/4000] Training [7/16] Loss: 0.00248 +Epoch [3410/4000] Training [8/16] Loss: 0.00252 +Epoch [3410/4000] Training [9/16] Loss: 0.00197 +Epoch [3410/4000] Training [10/16] Loss: 0.00407 +Epoch [3410/4000] Training [11/16] Loss: 0.00209 +Epoch [3410/4000] Training [12/16] Loss: 0.00288 +Epoch [3410/4000] Training [13/16] Loss: 0.00336 +Epoch [3410/4000] Training [14/16] Loss: 0.00258 +Epoch [3410/4000] Training [15/16] Loss: 0.00223 +Epoch [3410/4000] Training [16/16] Loss: 0.00282 +Epoch [3410/4000] Training metric {'Train/mean dice_metric': 0.9987140893936157, 'Train/mean miou_metric': 0.9971545934677124, 'Train/mean f1': 0.9937459826469421, 'Train/mean precision': 0.9891910552978516, 'Train/mean recall': 0.9983429908752441, 'Train/mean hd95_metric': 0.5721954107284546} +Epoch [3410/4000] Validation [1/4] Loss: 0.46816 focal_loss 0.39964 dice_loss 0.06852 +Epoch [3410/4000] Validation [2/4] Loss: 0.65488 focal_loss 0.48997 dice_loss 0.16491 +Epoch [3410/4000] Validation [3/4] Loss: 0.52753 focal_loss 0.43317 dice_loss 0.09436 +Epoch [3410/4000] Validation [4/4] Loss: 0.44599 focal_loss 0.33856 dice_loss 0.10743 +Epoch [3410/4000] Validation metric {'Val/mean dice_metric': 0.9719641804695129, 'Val/mean miou_metric': 0.9582024812698364, 'Val/mean f1': 0.9758102893829346, 'Val/mean precision': 0.9743085503578186, 'Val/mean recall': 0.977316677570343, 'Val/mean hd95_metric': 5.0449910163879395} +Cheakpoint... +Epoch [3410/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719641804695129, 'Val/mean miou_metric': 0.9582024812698364, 'Val/mean f1': 0.9758102893829346, 'Val/mean precision': 0.9743085503578186, 'Val/mean recall': 0.977316677570343, 'Val/mean hd95_metric': 5.0449910163879395} +Epoch [3411/4000] Training [1/16] Loss: 0.00253 +Epoch [3411/4000] Training [2/16] Loss: 0.00254 +Epoch [3411/4000] Training [3/16] Loss: 0.00277 +Epoch [3411/4000] Training [4/16] Loss: 0.00496 +Epoch [3411/4000] Training [5/16] Loss: 0.00473 +Epoch [3411/4000] Training [6/16] Loss: 0.00188 +Epoch [3411/4000] Training [7/16] Loss: 0.00240 +Epoch [3411/4000] Training [8/16] Loss: 0.00306 +Epoch [3411/4000] Training [9/16] Loss: 0.00214 +Epoch [3411/4000] Training [10/16] Loss: 0.00288 +Epoch [3411/4000] Training [11/16] Loss: 0.00334 +Epoch [3411/4000] Training [12/16] Loss: 0.00252 +Epoch [3411/4000] Training [13/16] Loss: 0.00225 +Epoch [3411/4000] Training [14/16] Loss: 0.00239 +Epoch [3411/4000] Training [15/16] Loss: 0.00276 +Epoch [3411/4000] Training [16/16] Loss: 0.00186 +Epoch [3411/4000] Training metric {'Train/mean dice_metric': 0.9984387159347534, 'Train/mean miou_metric': 0.9966092705726624, 'Train/mean f1': 0.9935333132743835, 'Train/mean precision': 0.9889899492263794, 'Train/mean recall': 0.9981186389923096, 'Train/mean hd95_metric': 0.8369826078414917} +Epoch [3411/4000] Validation [1/4] Loss: 0.41630 focal_loss 0.35061 dice_loss 0.06569 +Epoch [3411/4000] Validation [2/4] Loss: 0.46824 focal_loss 0.35913 dice_loss 0.10911 +Epoch [3411/4000] Validation [3/4] Loss: 0.53744 focal_loss 0.44234 dice_loss 0.09510 +Epoch [3411/4000] Validation [4/4] Loss: 0.31964 focal_loss 0.22906 dice_loss 0.09058 +Epoch [3411/4000] Validation metric {'Val/mean dice_metric': 0.9739891886711121, 'Val/mean miou_metric': 0.9596848487854004, 'Val/mean f1': 0.9758002758026123, 'Val/mean precision': 0.9735587239265442, 'Val/mean recall': 0.9780521988868713, 'Val/mean hd95_metric': 5.2799506187438965} +Cheakpoint... +Epoch [3411/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739891886711121, 'Val/mean miou_metric': 0.9596848487854004, 'Val/mean f1': 0.9758002758026123, 'Val/mean precision': 0.9735587239265442, 'Val/mean recall': 0.9780521988868713, 'Val/mean hd95_metric': 5.2799506187438965} +Epoch [3412/4000] Training [1/16] Loss: 0.00421 +Epoch [3412/4000] Training [2/16] Loss: 0.00219 +Epoch [3412/4000] Training [3/16] Loss: 0.00327 +Epoch [3412/4000] Training [4/16] Loss: 0.00185 +Epoch [3412/4000] Training [5/16] Loss: 0.00310 +Epoch [3412/4000] Training [6/16] Loss: 0.00188 +Epoch [3412/4000] Training [7/16] Loss: 0.00192 +Epoch [3412/4000] Training [8/16] Loss: 0.00358 +Epoch [3412/4000] Training [9/16] Loss: 0.00350 +Epoch [3412/4000] Training [10/16] Loss: 0.00239 +Epoch [3412/4000] Training [11/16] Loss: 0.00417 +Epoch [3412/4000] Training [12/16] Loss: 0.00233 +Epoch [3412/4000] Training [13/16] Loss: 0.00367 +Epoch [3412/4000] Training [14/16] Loss: 0.00259 +Epoch [3412/4000] Training [15/16] Loss: 0.00214 +Epoch [3412/4000] Training [16/16] Loss: 0.00168 +Epoch [3412/4000] Training metric {'Train/mean dice_metric': 0.9985069036483765, 'Train/mean miou_metric': 0.9967094659805298, 'Train/mean f1': 0.9932209849357605, 'Train/mean precision': 0.9883551597595215, 'Train/mean recall': 0.998134970664978, 'Train/mean hd95_metric': 0.6104068160057068} +Epoch [3412/4000] Validation [1/4] Loss: 0.43954 focal_loss 0.37141 dice_loss 0.06812 +Epoch [3412/4000] Validation [2/4] Loss: 1.50354 focal_loss 1.20335 dice_loss 0.30019 +Epoch [3412/4000] Validation [3/4] Loss: 0.52384 focal_loss 0.43286 dice_loss 0.09098 +Epoch [3412/4000] Validation [4/4] Loss: 0.41358 focal_loss 0.30930 dice_loss 0.10428 +Epoch [3412/4000] Validation metric {'Val/mean dice_metric': 0.9715476036071777, 'Val/mean miou_metric': 0.957629382610321, 'Val/mean f1': 0.975579023361206, 'Val/mean precision': 0.9736589193344116, 'Val/mean recall': 0.9775068759918213, 'Val/mean hd95_metric': 5.118810176849365} +Cheakpoint... +Epoch [3412/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715476036071777, 'Val/mean miou_metric': 0.957629382610321, 'Val/mean f1': 0.975579023361206, 'Val/mean precision': 0.9736589193344116, 'Val/mean recall': 0.9775068759918213, 'Val/mean hd95_metric': 5.118810176849365} +Epoch [3413/4000] Training [1/16] Loss: 0.00235 +Epoch [3413/4000] Training [2/16] Loss: 0.00315 +Epoch [3413/4000] Training [3/16] Loss: 0.00260 +Epoch [3413/4000] Training [4/16] Loss: 0.00237 +Epoch [3413/4000] Training [5/16] Loss: 0.00327 +Epoch [3413/4000] Training [6/16] Loss: 0.00203 +Epoch [3413/4000] Training [7/16] Loss: 0.00241 +Epoch [3413/4000] Training [8/16] Loss: 0.00193 +Epoch [3413/4000] Training [9/16] Loss: 0.00190 +Epoch [3413/4000] Training [10/16] Loss: 0.00306 +Epoch [3413/4000] Training [11/16] Loss: 0.00277 +Epoch [3413/4000] Training [12/16] Loss: 0.00250 +Epoch [3413/4000] Training [13/16] Loss: 0.00250 +Epoch [3413/4000] Training [14/16] Loss: 0.00248 +Epoch [3413/4000] Training [15/16] Loss: 0.00276 +Epoch [3413/4000] Training [16/16] Loss: 0.00280 +Epoch [3413/4000] Training metric {'Train/mean dice_metric': 0.9986495971679688, 'Train/mean miou_metric': 0.9970252513885498, 'Train/mean f1': 0.9936901926994324, 'Train/mean precision': 0.989135205745697, 'Train/mean recall': 0.9982873201370239, 'Train/mean hd95_metric': 0.5967072248458862} +Epoch [3413/4000] Validation [1/4] Loss: 0.41840 focal_loss 0.35355 dice_loss 0.06485 +Epoch [3413/4000] Validation [2/4] Loss: 0.82018 focal_loss 0.60304 dice_loss 0.21715 +Epoch [3413/4000] Validation [3/4] Loss: 0.53036 focal_loss 0.43436 dice_loss 0.09601 +Epoch [3413/4000] Validation [4/4] Loss: 0.32304 focal_loss 0.22418 dice_loss 0.09886 +Epoch [3413/4000] Validation metric {'Val/mean dice_metric': 0.9727157354354858, 'Val/mean miou_metric': 0.9587196111679077, 'Val/mean f1': 0.9764158725738525, 'Val/mean precision': 0.9741805195808411, 'Val/mean recall': 0.9786615967750549, 'Val/mean hd95_metric': 5.1788434982299805} +Cheakpoint... +Epoch [3413/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727157354354858, 'Val/mean miou_metric': 0.9587196111679077, 'Val/mean f1': 0.9764158725738525, 'Val/mean precision': 0.9741805195808411, 'Val/mean recall': 0.9786615967750549, 'Val/mean hd95_metric': 5.1788434982299805} +Epoch [3414/4000] Training [1/16] Loss: 0.00328 +Epoch [3414/4000] Training [2/16] Loss: 0.00225 +Epoch [3414/4000] Training [3/16] Loss: 0.00206 +Epoch [3414/4000] Training [4/16] Loss: 0.00234 +Epoch [3414/4000] Training [5/16] Loss: 0.00293 +Epoch [3414/4000] Training [6/16] Loss: 0.00258 +Epoch [3414/4000] Training [7/16] Loss: 0.00340 +Epoch [3414/4000] Training [8/16] Loss: 0.00278 +Epoch [3414/4000] Training [9/16] Loss: 0.00177 +Epoch [3414/4000] Training [10/16] Loss: 0.00212 +Epoch [3414/4000] Training [11/16] Loss: 0.00230 +Epoch [3414/4000] Training [12/16] Loss: 0.00248 +Epoch [3414/4000] Training [13/16] Loss: 0.00480 +Epoch [3414/4000] Training [14/16] Loss: 0.00251 +Epoch [3414/4000] Training [15/16] Loss: 0.00173 +Epoch [3414/4000] Training [16/16] Loss: 0.00272 +Epoch [3414/4000] Training metric {'Train/mean dice_metric': 0.9987753629684448, 'Train/mean miou_metric': 0.9972420930862427, 'Train/mean f1': 0.9929488301277161, 'Train/mean precision': 0.9877201318740845, 'Train/mean recall': 0.9982331395149231, 'Train/mean hd95_metric': 0.534695565700531} +Epoch [3414/4000] Validation [1/4] Loss: 0.39962 focal_loss 0.33638 dice_loss 0.06324 +Epoch [3414/4000] Validation [2/4] Loss: 0.94260 focal_loss 0.75516 dice_loss 0.18744 +Epoch [3414/4000] Validation [3/4] Loss: 0.52131 focal_loss 0.42871 dice_loss 0.09260 +Epoch [3414/4000] Validation [4/4] Loss: 0.37515 focal_loss 0.27374 dice_loss 0.10141 +Epoch [3414/4000] Validation metric {'Val/mean dice_metric': 0.9738143682479858, 'Val/mean miou_metric': 0.9602529406547546, 'Val/mean f1': 0.975492000579834, 'Val/mean precision': 0.9720417261123657, 'Val/mean recall': 0.978967010974884, 'Val/mean hd95_metric': 5.136096000671387} +Cheakpoint... +Epoch [3414/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738143682479858, 'Val/mean miou_metric': 0.9602529406547546, 'Val/mean f1': 0.975492000579834, 'Val/mean precision': 0.9720417261123657, 'Val/mean recall': 0.978967010974884, 'Val/mean hd95_metric': 5.136096000671387} +Epoch [3415/4000] Training [1/16] Loss: 0.00376 +Epoch [3415/4000] Training [2/16] Loss: 0.00239 +Epoch [3415/4000] Training [3/16] Loss: 0.00341 +Epoch [3415/4000] Training [4/16] Loss: 0.00283 +Epoch [3415/4000] Training [5/16] Loss: 0.00272 +Epoch [3415/4000] Training [6/16] Loss: 0.00253 +Epoch [3415/4000] Training [7/16] Loss: 0.00316 +Epoch [3415/4000] Training [8/16] Loss: 0.00282 +Epoch [3415/4000] Training [9/16] Loss: 0.00264 +Epoch [3415/4000] Training [10/16] Loss: 0.00204 +Epoch [3415/4000] Training [11/16] Loss: 0.00431 +Epoch [3415/4000] Training [12/16] Loss: 0.00259 +Epoch [3415/4000] Training [13/16] Loss: 0.00369 +Epoch [3415/4000] Training [14/16] Loss: 0.00178 +Epoch [3415/4000] Training [15/16] Loss: 0.00176 +Epoch [3415/4000] Training [16/16] Loss: 0.00265 +Epoch [3415/4000] Training metric {'Train/mean dice_metric': 0.9985904693603516, 'Train/mean miou_metric': 0.9968929290771484, 'Train/mean f1': 0.9934901595115662, 'Train/mean precision': 0.988771915435791, 'Train/mean recall': 0.9982536435127258, 'Train/mean hd95_metric': 0.57248854637146} +Epoch [3415/4000] Validation [1/4] Loss: 0.44649 focal_loss 0.37523 dice_loss 0.07126 +Epoch [3415/4000] Validation [2/4] Loss: 0.58107 focal_loss 0.43512 dice_loss 0.14595 +Epoch [3415/4000] Validation [3/4] Loss: 0.52815 focal_loss 0.43515 dice_loss 0.09301 +Epoch [3415/4000] Validation [4/4] Loss: 0.32971 focal_loss 0.22847 dice_loss 0.10124 +Epoch [3415/4000] Validation metric {'Val/mean dice_metric': 0.9728513956069946, 'Val/mean miou_metric': 0.9583970308303833, 'Val/mean f1': 0.9756061434745789, 'Val/mean precision': 0.9739656448364258, 'Val/mean recall': 0.9772521257400513, 'Val/mean hd95_metric': 4.973631858825684} +Cheakpoint... +Epoch [3415/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728513956069946, 'Val/mean miou_metric': 0.9583970308303833, 'Val/mean f1': 0.9756061434745789, 'Val/mean precision': 0.9739656448364258, 'Val/mean recall': 0.9772521257400513, 'Val/mean hd95_metric': 4.973631858825684} +Epoch [3416/4000] Training [1/16] Loss: 0.00184 +Epoch [3416/4000] Training [2/16] Loss: 0.00208 +Epoch [3416/4000] Training [3/16] Loss: 0.00238 +Epoch [3416/4000] Training [4/16] Loss: 0.00281 +Epoch [3416/4000] Training [5/16] Loss: 0.00230 +Epoch [3416/4000] Training [6/16] Loss: 0.00384 +Epoch [3416/4000] Training [7/16] Loss: 0.00261 +Epoch [3416/4000] Training [8/16] Loss: 0.00260 +Epoch [3416/4000] Training [9/16] Loss: 0.00185 +Epoch [3416/4000] Training [10/16] Loss: 0.00188 +Epoch [3416/4000] Training [11/16] Loss: 0.00208 +Epoch [3416/4000] Training [12/16] Loss: 0.00400 +Epoch [3416/4000] Training [13/16] Loss: 0.00409 +Epoch [3416/4000] Training [14/16] Loss: 0.00235 +Epoch [3416/4000] Training [15/16] Loss: 0.00238 +Epoch [3416/4000] Training [16/16] Loss: 0.00206 +Epoch [3416/4000] Training metric {'Train/mean dice_metric': 0.9986920356750488, 'Train/mean miou_metric': 0.9970942139625549, 'Train/mean f1': 0.9934474229812622, 'Train/mean precision': 0.9886549711227417, 'Train/mean recall': 0.9982865452766418, 'Train/mean hd95_metric': 0.5760082006454468} +Epoch [3416/4000] Validation [1/4] Loss: 0.40664 focal_loss 0.34186 dice_loss 0.06478 +Epoch [3416/4000] Validation [2/4] Loss: 0.46360 focal_loss 0.35505 dice_loss 0.10855 +Epoch [3416/4000] Validation [3/4] Loss: 0.53077 focal_loss 0.43177 dice_loss 0.09900 +Epoch [3416/4000] Validation [4/4] Loss: 0.45836 focal_loss 0.32779 dice_loss 0.13056 +Epoch [3416/4000] Validation metric {'Val/mean dice_metric': 0.9723300933837891, 'Val/mean miou_metric': 0.9582878947257996, 'Val/mean f1': 0.97551029920578, 'Val/mean precision': 0.9739516377449036, 'Val/mean recall': 0.9770740270614624, 'Val/mean hd95_metric': 4.988287448883057} +Cheakpoint... +Epoch [3416/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723300933837891, 'Val/mean miou_metric': 0.9582878947257996, 'Val/mean f1': 0.97551029920578, 'Val/mean precision': 0.9739516377449036, 'Val/mean recall': 0.9770740270614624, 'Val/mean hd95_metric': 4.988287448883057} +Epoch [3417/4000] Training [1/16] Loss: 0.00293 +Epoch [3417/4000] Training [2/16] Loss: 0.00268 +Epoch [3417/4000] Training [3/16] Loss: 0.00267 +Epoch [3417/4000] Training [4/16] Loss: 0.00201 +Epoch [3417/4000] Training [5/16] Loss: 0.00221 +Epoch [3417/4000] Training [6/16] Loss: 0.00302 +Epoch [3417/4000] Training [7/16] Loss: 0.00207 +Epoch [3417/4000] Training [8/16] Loss: 0.00292 +Epoch [3417/4000] Training [9/16] Loss: 0.00193 +Epoch [3417/4000] Training [10/16] Loss: 0.00308 +Epoch [3417/4000] Training [11/16] Loss: 0.00262 +Epoch [3417/4000] Training [12/16] Loss: 0.00177 +Epoch [3417/4000] Training [13/16] Loss: 0.00288 +Epoch [3417/4000] Training [14/16] Loss: 0.00233 +Epoch [3417/4000] Training [15/16] Loss: 0.00239 +Epoch [3417/4000] Training [16/16] Loss: 0.00176 +Epoch [3417/4000] Training metric {'Train/mean dice_metric': 0.9986850023269653, 'Train/mean miou_metric': 0.9970860481262207, 'Train/mean f1': 0.9934661388397217, 'Train/mean precision': 0.9887339472770691, 'Train/mean recall': 0.9982439875602722, 'Train/mean hd95_metric': 0.5875276327133179} +Epoch [3417/4000] Validation [1/4] Loss: 0.35008 focal_loss 0.28808 dice_loss 0.06200 +Epoch [3417/4000] Validation [2/4] Loss: 0.95191 focal_loss 0.76338 dice_loss 0.18854 +Epoch [3417/4000] Validation [3/4] Loss: 0.54120 focal_loss 0.44737 dice_loss 0.09382 +Epoch [3417/4000] Validation [4/4] Loss: 0.45247 focal_loss 0.34345 dice_loss 0.10902 +Epoch [3417/4000] Validation metric {'Val/mean dice_metric': 0.9731920957565308, 'Val/mean miou_metric': 0.9595237970352173, 'Val/mean f1': 0.9753203392028809, 'Val/mean precision': 0.972067654132843, 'Val/mean recall': 0.978594958782196, 'Val/mean hd95_metric': 5.383284568786621} +Cheakpoint... +Epoch [3417/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731920957565308, 'Val/mean miou_metric': 0.9595237970352173, 'Val/mean f1': 0.9753203392028809, 'Val/mean precision': 0.972067654132843, 'Val/mean recall': 0.978594958782196, 'Val/mean hd95_metric': 5.383284568786621} +Epoch [3418/4000] Training [1/16] Loss: 0.00182 +Epoch [3418/4000] Training [2/16] Loss: 0.00262 +Epoch [3418/4000] Training [3/16] Loss: 0.00176 +Epoch [3418/4000] Training [4/16] Loss: 0.00461 +Epoch [3418/4000] Training [5/16] Loss: 0.00310 +Epoch [3418/4000] Training [6/16] Loss: 0.00293 +Epoch [3418/4000] Training [7/16] Loss: 0.00167 +Epoch [3418/4000] Training [8/16] Loss: 0.00199 +Epoch [3418/4000] Training [9/16] Loss: 0.00324 +Epoch [3418/4000] Training [10/16] Loss: 0.00232 +Epoch [3418/4000] Training [11/16] Loss: 0.00189 +Epoch [3418/4000] Training [12/16] Loss: 0.00243 +Epoch [3418/4000] Training [13/16] Loss: 0.00200 +Epoch [3418/4000] Training [14/16] Loss: 0.00211 +Epoch [3418/4000] Training [15/16] Loss: 0.00233 +Epoch [3418/4000] Training [16/16] Loss: 0.00276 +Epoch [3418/4000] Training metric {'Train/mean dice_metric': 0.998691201210022, 'Train/mean miou_metric': 0.9971109628677368, 'Train/mean f1': 0.9937822222709656, 'Train/mean precision': 0.9892516732215881, 'Train/mean recall': 0.9983544945716858, 'Train/mean hd95_metric': 0.5732696056365967} +Epoch [3418/4000] Validation [1/4] Loss: 0.44860 focal_loss 0.38148 dice_loss 0.06712 +Epoch [3418/4000] Validation [2/4] Loss: 0.45627 focal_loss 0.34856 dice_loss 0.10772 +Epoch [3418/4000] Validation [3/4] Loss: 0.49100 focal_loss 0.39945 dice_loss 0.09155 +Epoch [3418/4000] Validation [4/4] Loss: 0.32501 focal_loss 0.24017 dice_loss 0.08484 +Epoch [3418/4000] Validation metric {'Val/mean dice_metric': 0.9743987917900085, 'Val/mean miou_metric': 0.9605938196182251, 'Val/mean f1': 0.9760251641273499, 'Val/mean precision': 0.9734657406806946, 'Val/mean recall': 0.9785980582237244, 'Val/mean hd95_metric': 5.021690845489502} +Cheakpoint... +Epoch [3418/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743987917900085, 'Val/mean miou_metric': 0.9605938196182251, 'Val/mean f1': 0.9760251641273499, 'Val/mean precision': 0.9734657406806946, 'Val/mean recall': 0.9785980582237244, 'Val/mean hd95_metric': 5.021690845489502} +Epoch [3419/4000] Training [1/16] Loss: 0.00173 +Epoch [3419/4000] Training [2/16] Loss: 0.00279 +Epoch [3419/4000] Training [3/16] Loss: 0.00266 +Epoch [3419/4000] Training [4/16] Loss: 0.00305 +Epoch [3419/4000] Training [5/16] Loss: 0.00308 +Epoch [3419/4000] Training [6/16] Loss: 0.00311 +Epoch [3419/4000] Training [7/16] Loss: 0.00205 +Epoch [3419/4000] Training [8/16] Loss: 0.00242 +Epoch [3419/4000] Training [9/16] Loss: 0.00267 +Epoch [3419/4000] Training [10/16] Loss: 0.00277 +Epoch [3419/4000] Training [11/16] Loss: 0.00211 +Epoch [3419/4000] Training [12/16] Loss: 0.00482 +Epoch [3419/4000] Training [13/16] Loss: 0.00222 +Epoch [3419/4000] Training [14/16] Loss: 0.00239 +Epoch [3419/4000] Training [15/16] Loss: 0.00244 +Epoch [3419/4000] Training [16/16] Loss: 0.00220 +Epoch [3419/4000] Training metric {'Train/mean dice_metric': 0.9985828399658203, 'Train/mean miou_metric': 0.9968947172164917, 'Train/mean f1': 0.9937558770179749, 'Train/mean precision': 0.9892834424972534, 'Train/mean recall': 0.9982689619064331, 'Train/mean hd95_metric': 0.6118718385696411} +Epoch [3419/4000] Validation [1/4] Loss: 0.40701 focal_loss 0.34193 dice_loss 0.06508 +Epoch [3419/4000] Validation [2/4] Loss: 0.47287 focal_loss 0.36208 dice_loss 0.11078 +Epoch [3419/4000] Validation [3/4] Loss: 0.51364 focal_loss 0.42176 dice_loss 0.09188 +Epoch [3419/4000] Validation [4/4] Loss: 0.32013 focal_loss 0.23308 dice_loss 0.08705 +Epoch [3419/4000] Validation metric {'Val/mean dice_metric': 0.9735868573188782, 'Val/mean miou_metric': 0.9594618678092957, 'Val/mean f1': 0.9763398170471191, 'Val/mean precision': 0.974958598613739, 'Val/mean recall': 0.9777252078056335, 'Val/mean hd95_metric': 4.7832932472229} +Cheakpoint... +Epoch [3419/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735868573188782, 'Val/mean miou_metric': 0.9594618678092957, 'Val/mean f1': 0.9763398170471191, 'Val/mean precision': 0.974958598613739, 'Val/mean recall': 0.9777252078056335, 'Val/mean hd95_metric': 4.7832932472229} +Epoch [3420/4000] Training [1/16] Loss: 0.00235 +Epoch [3420/4000] Training [2/16] Loss: 0.00235 +Epoch [3420/4000] Training [3/16] Loss: 0.00212 +Epoch [3420/4000] Training [4/16] Loss: 0.00275 +Epoch [3420/4000] Training [5/16] Loss: 0.00274 +Epoch [3420/4000] Training [6/16] Loss: 0.00268 +Epoch [3420/4000] Training [7/16] Loss: 0.00221 +Epoch [3420/4000] Training [8/16] Loss: 0.00216 +Epoch [3420/4000] Training [9/16] Loss: 0.00206 +Epoch [3420/4000] Training [10/16] Loss: 0.00396 +Epoch [3420/4000] Training [11/16] Loss: 0.00226 +Epoch [3420/4000] Training [12/16] Loss: 0.00284 +Epoch [3420/4000] Training [13/16] Loss: 0.00189 +Epoch [3420/4000] Training [14/16] Loss: 0.00324 +Epoch [3420/4000] Training [15/16] Loss: 0.00205 +Epoch [3420/4000] Training [16/16] Loss: 0.00308 +Epoch [3420/4000] Training metric {'Train/mean dice_metric': 0.9985969066619873, 'Train/mean miou_metric': 0.9969056844711304, 'Train/mean f1': 0.9934279322624207, 'Train/mean precision': 0.9886477589607239, 'Train/mean recall': 0.9982545375823975, 'Train/mean hd95_metric': 0.5611181855201721} +Epoch [3420/4000] Validation [1/4] Loss: 0.42135 focal_loss 0.35452 dice_loss 0.06683 +Epoch [3420/4000] Validation [2/4] Loss: 0.94258 focal_loss 0.72385 dice_loss 0.21873 +Epoch [3420/4000] Validation [3/4] Loss: 0.51691 focal_loss 0.42490 dice_loss 0.09200 +Epoch [3420/4000] Validation [4/4] Loss: 0.45139 focal_loss 0.34286 dice_loss 0.10854 +Epoch [3420/4000] Validation metric {'Val/mean dice_metric': 0.9731730222702026, 'Val/mean miou_metric': 0.9588766098022461, 'Val/mean f1': 0.9757024645805359, 'Val/mean precision': 0.9731897711753845, 'Val/mean recall': 0.9782282114028931, 'Val/mean hd95_metric': 4.758077621459961} +Cheakpoint... +Epoch [3420/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731730222702026, 'Val/mean miou_metric': 0.9588766098022461, 'Val/mean f1': 0.9757024645805359, 'Val/mean precision': 0.9731897711753845, 'Val/mean recall': 0.9782282114028931, 'Val/mean hd95_metric': 4.758077621459961} +Epoch [3421/4000] Training [1/16] Loss: 0.00392 +Epoch [3421/4000] Training [2/16] Loss: 0.00305 +Epoch [3421/4000] Training [3/16] Loss: 0.00361 +Epoch [3421/4000] Training [4/16] Loss: 0.00212 +Epoch [3421/4000] Training [5/16] Loss: 0.00345 +Epoch [3421/4000] Training [6/16] Loss: 0.00245 +Epoch [3421/4000] Training [7/16] Loss: 0.00226 +Epoch [3421/4000] Training [8/16] Loss: 0.00256 +Epoch [3421/4000] Training [9/16] Loss: 0.00194 +Epoch [3421/4000] Training [10/16] Loss: 0.00261 +Epoch [3421/4000] Training [11/16] Loss: 0.00198 +Epoch [3421/4000] Training [12/16] Loss: 0.00354 +Epoch [3421/4000] Training [13/16] Loss: 0.00211 +Epoch [3421/4000] Training [14/16] Loss: 0.00191 +Epoch [3421/4000] Training [15/16] Loss: 0.00148 +Epoch [3421/4000] Training [16/16] Loss: 0.00217 +Epoch [3421/4000] Training metric {'Train/mean dice_metric': 0.9986298680305481, 'Train/mean miou_metric': 0.9969761371612549, 'Train/mean f1': 0.9934176802635193, 'Train/mean precision': 0.9886250495910645, 'Train/mean recall': 0.9982569217681885, 'Train/mean hd95_metric': 0.5725163221359253} +Epoch [3421/4000] Validation [1/4] Loss: 0.41920 focal_loss 0.34513 dice_loss 0.07407 +Epoch [3421/4000] Validation [2/4] Loss: 1.11174 focal_loss 0.84309 dice_loss 0.26865 +Epoch [3421/4000] Validation [3/4] Loss: 0.26917 focal_loss 0.21052 dice_loss 0.05865 +Epoch [3421/4000] Validation [4/4] Loss: 0.43715 focal_loss 0.32947 dice_loss 0.10767 +Epoch [3421/4000] Validation metric {'Val/mean dice_metric': 0.9721082448959351, 'Val/mean miou_metric': 0.9580278396606445, 'Val/mean f1': 0.9749414324760437, 'Val/mean precision': 0.9729626178741455, 'Val/mean recall': 0.9769282341003418, 'Val/mean hd95_metric': 5.03865909576416} +Cheakpoint... +Epoch [3421/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721082448959351, 'Val/mean miou_metric': 0.9580278396606445, 'Val/mean f1': 0.9749414324760437, 'Val/mean precision': 0.9729626178741455, 'Val/mean recall': 0.9769282341003418, 'Val/mean hd95_metric': 5.03865909576416} +Epoch [3422/4000] Training [1/16] Loss: 0.00194 +Epoch [3422/4000] Training [2/16] Loss: 0.00289 +Epoch [3422/4000] Training [3/16] Loss: 0.00406 +Epoch [3422/4000] Training [4/16] Loss: 0.00247 +Epoch [3422/4000] Training [5/16] Loss: 0.00295 +Epoch [3422/4000] Training [6/16] Loss: 0.00273 +Epoch [3422/4000] Training [7/16] Loss: 0.00344 +Epoch [3422/4000] Training [8/16] Loss: 0.00168 +Epoch [3422/4000] Training [9/16] Loss: 0.00388 +Epoch [3422/4000] Training [10/16] Loss: 0.00159 +Epoch [3422/4000] Training [11/16] Loss: 0.00200 +Epoch [3422/4000] Training [12/16] Loss: 0.00321 +Epoch [3422/4000] Training [13/16] Loss: 0.00307 +Epoch [3422/4000] Training [14/16] Loss: 0.00249 +Epoch [3422/4000] Training [15/16] Loss: 0.00216 +Epoch [3422/4000] Training [16/16] Loss: 0.00238 +Epoch [3422/4000] Training metric {'Train/mean dice_metric': 0.9985744953155518, 'Train/mean miou_metric': 0.9968599081039429, 'Train/mean f1': 0.993533194065094, 'Train/mean precision': 0.9888579249382019, 'Train/mean recall': 0.9982528686523438, 'Train/mean hd95_metric': 0.5751250982284546} +Epoch [3422/4000] Validation [1/4] Loss: 0.39467 focal_loss 0.33040 dice_loss 0.06427 +Epoch [3422/4000] Validation [2/4] Loss: 0.51454 focal_loss 0.37707 dice_loss 0.13747 +Epoch [3422/4000] Validation [3/4] Loss: 0.51920 focal_loss 0.42819 dice_loss 0.09101 +Epoch [3422/4000] Validation [4/4] Loss: 0.33369 focal_loss 0.24277 dice_loss 0.09092 +Epoch [3422/4000] Validation metric {'Val/mean dice_metric': 0.9743853807449341, 'Val/mean miou_metric': 0.9601952433586121, 'Val/mean f1': 0.9763672351837158, 'Val/mean precision': 0.9735414981842041, 'Val/mean recall': 0.9792094826698303, 'Val/mean hd95_metric': 4.85493278503418} +Cheakpoint... +Epoch [3422/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743853807449341, 'Val/mean miou_metric': 0.9601952433586121, 'Val/mean f1': 0.9763672351837158, 'Val/mean precision': 0.9735414981842041, 'Val/mean recall': 0.9792094826698303, 'Val/mean hd95_metric': 4.85493278503418} +Epoch [3423/4000] Training [1/16] Loss: 0.00234 +Epoch [3423/4000] Training [2/16] Loss: 0.00231 +Epoch [3423/4000] Training [3/16] Loss: 0.00237 +Epoch [3423/4000] Training [4/16] Loss: 0.00250 +Epoch [3423/4000] Training [5/16] Loss: 0.00237 +Epoch [3423/4000] Training [6/16] Loss: 0.00236 +Epoch [3423/4000] Training [7/16] Loss: 0.00189 +Epoch [3423/4000] Training [8/16] Loss: 0.00210 +Epoch [3423/4000] Training [9/16] Loss: 0.00312 +Epoch [3423/4000] Training [10/16] Loss: 0.00228 +Epoch [3423/4000] Training [11/16] Loss: 0.00327 +Epoch [3423/4000] Training [12/16] Loss: 0.00276 +Epoch [3423/4000] Training [13/16] Loss: 0.00202 +Epoch [3423/4000] Training [14/16] Loss: 0.00270 +Epoch [3423/4000] Training [15/16] Loss: 0.00173 +Epoch [3423/4000] Training [16/16] Loss: 0.00195 +Epoch [3423/4000] Training metric {'Train/mean dice_metric': 0.9987697601318359, 'Train/mean miou_metric': 0.9972599148750305, 'Train/mean f1': 0.9937233924865723, 'Train/mean precision': 0.9891724586486816, 'Train/mean recall': 0.9983163475990295, 'Train/mean hd95_metric': 0.57444167137146} +Epoch [3423/4000] Validation [1/4] Loss: 0.35097 focal_loss 0.29113 dice_loss 0.05984 +Epoch [3423/4000] Validation [2/4] Loss: 0.83529 focal_loss 0.61774 dice_loss 0.21755 +Epoch [3423/4000] Validation [3/4] Loss: 0.26704 focal_loss 0.20918 dice_loss 0.05786 +Epoch [3423/4000] Validation [4/4] Loss: 0.44617 focal_loss 0.33752 dice_loss 0.10864 +Epoch [3423/4000] Validation metric {'Val/mean dice_metric': 0.9728254079818726, 'Val/mean miou_metric': 0.9590082168579102, 'Val/mean f1': 0.9756028652191162, 'Val/mean precision': 0.9738844037055969, 'Val/mean recall': 0.9773274660110474, 'Val/mean hd95_metric': 4.909671783447266} +Cheakpoint... +Epoch [3423/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728254079818726, 'Val/mean miou_metric': 0.9590082168579102, 'Val/mean f1': 0.9756028652191162, 'Val/mean precision': 0.9738844037055969, 'Val/mean recall': 0.9773274660110474, 'Val/mean hd95_metric': 4.909671783447266} +Epoch [3424/4000] Training [1/16] Loss: 0.00329 +Epoch [3424/4000] Training [2/16] Loss: 0.00261 +Epoch [3424/4000] Training [3/16] Loss: 0.00176 +Epoch [3424/4000] Training [4/16] Loss: 0.00298 +Epoch [3424/4000] Training [5/16] Loss: 0.00205 +Epoch [3424/4000] Training [6/16] Loss: 0.00236 +Epoch [3424/4000] Training [7/16] Loss: 0.00231 +Epoch [3424/4000] Training [8/16] Loss: 0.00215 +Epoch [3424/4000] Training [9/16] Loss: 0.00368 +Epoch [3424/4000] Training [10/16] Loss: 0.00218 +Epoch [3424/4000] Training [11/16] Loss: 0.00185 +Epoch [3424/4000] Training [12/16] Loss: 0.00202 +Epoch [3424/4000] Training [13/16] Loss: 0.00319 +Epoch [3424/4000] Training [14/16] Loss: 0.00344 +Epoch [3424/4000] Training [15/16] Loss: 0.00385 +Epoch [3424/4000] Training [16/16] Loss: 0.00251 +Epoch [3424/4000] Training metric {'Train/mean dice_metric': 0.9985873699188232, 'Train/mean miou_metric': 0.9968699216842651, 'Train/mean f1': 0.992936909198761, 'Train/mean precision': 0.9877229332923889, 'Train/mean recall': 0.9982062578201294, 'Train/mean hd95_metric': 0.6221954822540283} +Epoch [3424/4000] Validation [1/4] Loss: 0.41741 focal_loss 0.34973 dice_loss 0.06768 +Epoch [3424/4000] Validation [2/4] Loss: 0.45280 focal_loss 0.34515 dice_loss 0.10765 +Epoch [3424/4000] Validation [3/4] Loss: 0.50867 focal_loss 0.41464 dice_loss 0.09403 +Epoch [3424/4000] Validation [4/4] Loss: 0.31853 focal_loss 0.21869 dice_loss 0.09984 +Epoch [3424/4000] Validation metric {'Val/mean dice_metric': 0.973889172077179, 'Val/mean miou_metric': 0.9596713781356812, 'Val/mean f1': 0.9758026003837585, 'Val/mean precision': 0.9732937216758728, 'Val/mean recall': 0.9783244729042053, 'Val/mean hd95_metric': 4.702015399932861} +Cheakpoint... +Epoch [3424/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973889172077179, 'Val/mean miou_metric': 0.9596713781356812, 'Val/mean f1': 0.9758026003837585, 'Val/mean precision': 0.9732937216758728, 'Val/mean recall': 0.9783244729042053, 'Val/mean hd95_metric': 4.702015399932861} +Epoch [3425/4000] Training [1/16] Loss: 0.00220 +Epoch [3425/4000] Training [2/16] Loss: 0.00217 +Epoch [3425/4000] Training [3/16] Loss: 0.00288 +Epoch [3425/4000] Training [4/16] Loss: 0.00326 +Epoch [3425/4000] Training [5/16] Loss: 0.00206 +Epoch [3425/4000] Training [6/16] Loss: 0.00252 +Epoch [3425/4000] Training [7/16] Loss: 0.00270 +Epoch [3425/4000] Training [8/16] Loss: 0.00588 +Epoch [3425/4000] Training [9/16] Loss: 0.00255 +Epoch [3425/4000] Training [10/16] Loss: 0.00218 +Epoch [3425/4000] Training [11/16] Loss: 0.00381 +Epoch [3425/4000] Training [12/16] Loss: 0.00214 +Epoch [3425/4000] Training [13/16] Loss: 0.00289 +Epoch [3425/4000] Training [14/16] Loss: 0.00273 +Epoch [3425/4000] Training [15/16] Loss: 0.00188 +Epoch [3425/4000] Training [16/16] Loss: 0.00282 +Epoch [3425/4000] Training metric {'Train/mean dice_metric': 0.9985330104827881, 'Train/mean miou_metric': 0.9967943429946899, 'Train/mean f1': 0.993548572063446, 'Train/mean precision': 0.9889248609542847, 'Train/mean recall': 0.9982158541679382, 'Train/mean hd95_metric': 0.6303287744522095} +Epoch [3425/4000] Validation [1/4] Loss: 0.41510 focal_loss 0.34953 dice_loss 0.06558 +Epoch [3425/4000] Validation [2/4] Loss: 0.98011 focal_loss 0.79179 dice_loss 0.18832 +Epoch [3425/4000] Validation [3/4] Loss: 0.51210 focal_loss 0.41561 dice_loss 0.09649 +Epoch [3425/4000] Validation [4/4] Loss: 0.34134 focal_loss 0.24936 dice_loss 0.09198 +Epoch [3425/4000] Validation metric {'Val/mean dice_metric': 0.9728556871414185, 'Val/mean miou_metric': 0.9591204524040222, 'Val/mean f1': 0.9758028388023376, 'Val/mean precision': 0.9737726449966431, 'Val/mean recall': 0.9778414964675903, 'Val/mean hd95_metric': 4.926682949066162} +Cheakpoint... +Epoch [3425/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728556871414185, 'Val/mean miou_metric': 0.9591204524040222, 'Val/mean f1': 0.9758028388023376, 'Val/mean precision': 0.9737726449966431, 'Val/mean recall': 0.9778414964675903, 'Val/mean hd95_metric': 4.926682949066162} +Epoch [3426/4000] Training [1/16] Loss: 0.00555 +Epoch [3426/4000] Training [2/16] Loss: 0.00156 +Epoch [3426/4000] Training [3/16] Loss: 0.00416 +Epoch [3426/4000] Training [4/16] Loss: 0.00234 +Epoch [3426/4000] Training [5/16] Loss: 0.00287 +Epoch [3426/4000] Training [6/16] Loss: 0.00326 +Epoch [3426/4000] Training [7/16] Loss: 0.00357 +Epoch [3426/4000] Training [8/16] Loss: 0.00373 +Epoch [3426/4000] Training [9/16] Loss: 0.00229 +Epoch [3426/4000] Training [10/16] Loss: 0.00243 +Epoch [3426/4000] Training [11/16] Loss: 0.00244 +Epoch [3426/4000] Training [12/16] Loss: 0.00343 +Epoch [3426/4000] Training [13/16] Loss: 0.00265 +Epoch [3426/4000] Training [14/16] Loss: 0.00278 +Epoch [3426/4000] Training [15/16] Loss: 0.00184 +Epoch [3426/4000] Training [16/16] Loss: 0.00278 +Epoch [3426/4000] Training metric {'Train/mean dice_metric': 0.9983289241790771, 'Train/mean miou_metric': 0.9963617920875549, 'Train/mean f1': 0.9930670261383057, 'Train/mean precision': 0.988201379776001, 'Train/mean recall': 0.9979807734489441, 'Train/mean hd95_metric': 0.6592350602149963} +Epoch [3426/4000] Validation [1/4] Loss: 0.42218 focal_loss 0.35453 dice_loss 0.06765 +Epoch [3426/4000] Validation [2/4] Loss: 0.68468 focal_loss 0.50233 dice_loss 0.18234 +Epoch [3426/4000] Validation [3/4] Loss: 0.53787 focal_loss 0.44477 dice_loss 0.09311 +Epoch [3426/4000] Validation [4/4] Loss: 0.57652 focal_loss 0.44163 dice_loss 0.13489 +Epoch [3426/4000] Validation metric {'Val/mean dice_metric': 0.9716558456420898, 'Val/mean miou_metric': 0.9572193026542664, 'Val/mean f1': 0.9747354388237, 'Val/mean precision': 0.9725964665412903, 'Val/mean recall': 0.9768838882446289, 'Val/mean hd95_metric': 5.703479766845703} +Cheakpoint... +Epoch [3426/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716558456420898, 'Val/mean miou_metric': 0.9572193026542664, 'Val/mean f1': 0.9747354388237, 'Val/mean precision': 0.9725964665412903, 'Val/mean recall': 0.9768838882446289, 'Val/mean hd95_metric': 5.703479766845703} +Epoch [3427/4000] Training [1/16] Loss: 0.00161 +Epoch [3427/4000] Training [2/16] Loss: 0.00338 +Epoch [3427/4000] Training [3/16] Loss: 0.00173 +Epoch [3427/4000] Training [4/16] Loss: 0.00316 +Epoch [3427/4000] Training [5/16] Loss: 0.00207 +Epoch [3427/4000] Training [6/16] Loss: 0.00197 +Epoch [3427/4000] Training [7/16] Loss: 0.00193 +Epoch [3427/4000] Training [8/16] Loss: 0.00377 +Epoch [3427/4000] Training [9/16] Loss: 0.00261 +Epoch [3427/4000] Training [10/16] Loss: 0.00257 +Epoch [3427/4000] Training [11/16] Loss: 0.00252 +Epoch [3427/4000] Training [12/16] Loss: 0.00199 +Epoch [3427/4000] Training [13/16] Loss: 0.00244 +Epoch [3427/4000] Training [14/16] Loss: 0.00302 +Epoch [3427/4000] Training [15/16] Loss: 0.00213 +Epoch [3427/4000] Training [16/16] Loss: 0.00162 +Epoch [3427/4000] Training metric {'Train/mean dice_metric': 0.9988352656364441, 'Train/mean miou_metric': 0.9973925948143005, 'Train/mean f1': 0.9938587546348572, 'Train/mean precision': 0.9892844557762146, 'Train/mean recall': 0.9984754920005798, 'Train/mean hd95_metric': 0.5335514545440674} +Epoch [3427/4000] Validation [1/4] Loss: 0.42935 focal_loss 0.36352 dice_loss 0.06583 +Epoch [3427/4000] Validation [2/4] Loss: 0.49344 focal_loss 0.37582 dice_loss 0.11762 +Epoch [3427/4000] Validation [3/4] Loss: 0.25453 focal_loss 0.19597 dice_loss 0.05856 +Epoch [3427/4000] Validation [4/4] Loss: 0.39424 focal_loss 0.29016 dice_loss 0.10408 +Epoch [3427/4000] Validation metric {'Val/mean dice_metric': 0.9751482009887695, 'Val/mean miou_metric': 0.9611064791679382, 'Val/mean f1': 0.9770867228507996, 'Val/mean precision': 0.9753700494766235, 'Val/mean recall': 0.9788095355033875, 'Val/mean hd95_metric': 4.451064109802246} +Cheakpoint... +Epoch [3427/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751482009887695, 'Val/mean miou_metric': 0.9611064791679382, 'Val/mean f1': 0.9770867228507996, 'Val/mean precision': 0.9753700494766235, 'Val/mean recall': 0.9788095355033875, 'Val/mean hd95_metric': 4.451064109802246} +Epoch [3428/4000] Training [1/16] Loss: 0.00223 +Epoch [3428/4000] Training [2/16] Loss: 0.00231 +Epoch [3428/4000] Training [3/16] Loss: 0.00237 +Epoch [3428/4000] Training [4/16] Loss: 0.00202 +Epoch [3428/4000] Training [5/16] Loss: 0.00258 +Epoch [3428/4000] Training [6/16] Loss: 0.00234 +Epoch [3428/4000] Training [7/16] Loss: 0.00262 +Epoch [3428/4000] Training [8/16] Loss: 0.00188 +Epoch [3428/4000] Training [9/16] Loss: 0.00252 +Epoch [3428/4000] Training [10/16] Loss: 0.00307 +Epoch [3428/4000] Training [11/16] Loss: 0.00332 +Epoch [3428/4000] Training [12/16] Loss: 0.00269 +Epoch [3428/4000] Training [13/16] Loss: 0.00269 +Epoch [3428/4000] Training [14/16] Loss: 0.00215 +Epoch [3428/4000] Training [15/16] Loss: 0.00248 +Epoch [3428/4000] Training [16/16] Loss: 0.00230 +Epoch [3428/4000] Training metric {'Train/mean dice_metric': 0.9987483024597168, 'Train/mean miou_metric': 0.9972227811813354, 'Train/mean f1': 0.9939115047454834, 'Train/mean precision': 0.9894660115242004, 'Train/mean recall': 0.998397171497345, 'Train/mean hd95_metric': 0.5880157947540283} +Epoch [3428/4000] Validation [1/4] Loss: 0.42134 focal_loss 0.35530 dice_loss 0.06604 +Epoch [3428/4000] Validation [2/4] Loss: 1.02730 focal_loss 0.81198 dice_loss 0.21532 +Epoch [3428/4000] Validation [3/4] Loss: 0.55994 focal_loss 0.46448 dice_loss 0.09546 +Epoch [3428/4000] Validation [4/4] Loss: 0.32698 focal_loss 0.23616 dice_loss 0.09082 +Epoch [3428/4000] Validation metric {'Val/mean dice_metric': 0.9731978178024292, 'Val/mean miou_metric': 0.9593992233276367, 'Val/mean f1': 0.9763917922973633, 'Val/mean precision': 0.9739706516265869, 'Val/mean recall': 0.9788249731063843, 'Val/mean hd95_metric': 5.165093421936035} +Cheakpoint... +Epoch [3428/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731978178024292, 'Val/mean miou_metric': 0.9593992233276367, 'Val/mean f1': 0.9763917922973633, 'Val/mean precision': 0.9739706516265869, 'Val/mean recall': 0.9788249731063843, 'Val/mean hd95_metric': 5.165093421936035} +Epoch [3429/4000] Training [1/16] Loss: 0.00204 +Epoch [3429/4000] Training [2/16] Loss: 0.00225 +Epoch [3429/4000] Training [3/16] Loss: 0.00245 +Epoch [3429/4000] Training [4/16] Loss: 0.00209 +Epoch [3429/4000] Training [5/16] Loss: 0.00208 +Epoch [3429/4000] Training [6/16] Loss: 0.00233 +Epoch [3429/4000] Training [7/16] Loss: 0.00275 +Epoch [3429/4000] Training [8/16] Loss: 0.00296 +Epoch [3429/4000] Training [9/16] Loss: 0.00231 +Epoch [3429/4000] Training [10/16] Loss: 0.00231 +Epoch [3429/4000] Training [11/16] Loss: 0.00329 +Epoch [3429/4000] Training [12/16] Loss: 0.00364 +Epoch [3429/4000] Training [13/16] Loss: 0.00272 +Epoch [3429/4000] Training [14/16] Loss: 0.00233 +Epoch [3429/4000] Training [15/16] Loss: 0.00273 +Epoch [3429/4000] Training [16/16] Loss: 0.00454 +Epoch [3429/4000] Training metric {'Train/mean dice_metric': 0.9986361265182495, 'Train/mean miou_metric': 0.9969997406005859, 'Train/mean f1': 0.9936210513114929, 'Train/mean precision': 0.9890596866607666, 'Train/mean recall': 0.9982247352600098, 'Train/mean hd95_metric': 0.5807194709777832} +Epoch [3429/4000] Validation [1/4] Loss: 0.39537 focal_loss 0.33436 dice_loss 0.06101 +Epoch [3429/4000] Validation [2/4] Loss: 1.02627 focal_loss 0.77826 dice_loss 0.24801 +Epoch [3429/4000] Validation [3/4] Loss: 0.28837 focal_loss 0.22857 dice_loss 0.05980 +Epoch [3429/4000] Validation [4/4] Loss: 0.41641 focal_loss 0.30303 dice_loss 0.11338 +Epoch [3429/4000] Validation metric {'Val/mean dice_metric': 0.9730648994445801, 'Val/mean miou_metric': 0.9591778516769409, 'Val/mean f1': 0.975947916507721, 'Val/mean precision': 0.9738929271697998, 'Val/mean recall': 0.9780116081237793, 'Val/mean hd95_metric': 5.1002421379089355} +Cheakpoint... +Epoch [3429/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730648994445801, 'Val/mean miou_metric': 0.9591778516769409, 'Val/mean f1': 0.975947916507721, 'Val/mean precision': 0.9738929271697998, 'Val/mean recall': 0.9780116081237793, 'Val/mean hd95_metric': 5.1002421379089355} +Epoch [3430/4000] Training [1/16] Loss: 0.00204 +Epoch [3430/4000] Training [2/16] Loss: 0.00180 +Epoch [3430/4000] Training [3/16] Loss: 0.00240 +Epoch [3430/4000] Training [4/16] Loss: 0.00358 +Epoch [3430/4000] Training [5/16] Loss: 0.00245 +Epoch [3430/4000] Training [6/16] Loss: 0.00314 +Epoch [3430/4000] Training [7/16] Loss: 0.00266 +Epoch [3430/4000] Training [8/16] Loss: 0.00220 +Epoch [3430/4000] Training [9/16] Loss: 0.00243 +Epoch [3430/4000] Training [10/16] Loss: 0.00337 +Epoch [3430/4000] Training [11/16] Loss: 0.00198 +Epoch [3430/4000] Training [12/16] Loss: 0.00194 +Epoch [3430/4000] Training [13/16] Loss: 0.00257 +Epoch [3430/4000] Training [14/16] Loss: 0.00288 +Epoch [3430/4000] Training [15/16] Loss: 0.00213 +Epoch [3430/4000] Training [16/16] Loss: 0.00314 +Epoch [3430/4000] Training metric {'Train/mean dice_metric': 0.9987074136734009, 'Train/mean miou_metric': 0.9971362352371216, 'Train/mean f1': 0.9935969710350037, 'Train/mean precision': 0.9889195561408997, 'Train/mean recall': 0.9983187913894653, 'Train/mean hd95_metric': 0.5826447010040283} +Epoch [3430/4000] Validation [1/4] Loss: 0.49149 focal_loss 0.42267 dice_loss 0.06881 +Epoch [3430/4000] Validation [2/4] Loss: 0.47651 focal_loss 0.36709 dice_loss 0.10942 +Epoch [3430/4000] Validation [3/4] Loss: 0.27221 focal_loss 0.21344 dice_loss 0.05878 +Epoch [3430/4000] Validation [4/4] Loss: 0.31501 focal_loss 0.22703 dice_loss 0.08798 +Epoch [3430/4000] Validation metric {'Val/mean dice_metric': 0.975417971611023, 'Val/mean miou_metric': 0.9611692428588867, 'Val/mean f1': 0.9763655662536621, 'Val/mean precision': 0.9745013117790222, 'Val/mean recall': 0.9782371520996094, 'Val/mean hd95_metric': 4.6380228996276855} +Cheakpoint... +Epoch [3430/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975417971611023, 'Val/mean miou_metric': 0.9611692428588867, 'Val/mean f1': 0.9763655662536621, 'Val/mean precision': 0.9745013117790222, 'Val/mean recall': 0.9782371520996094, 'Val/mean hd95_metric': 4.6380228996276855} +Epoch [3431/4000] Training [1/16] Loss: 0.00347 +Epoch [3431/4000] Training [2/16] Loss: 0.00280 +Epoch [3431/4000] Training [3/16] Loss: 0.00223 +Epoch [3431/4000] Training [4/16] Loss: 0.00194 +Epoch [3431/4000] Training [5/16] Loss: 0.00243 +Epoch [3431/4000] Training [6/16] Loss: 0.00221 +Epoch [3431/4000] Training [7/16] Loss: 0.00257 +Epoch [3431/4000] Training [8/16] Loss: 0.00313 +Epoch [3431/4000] Training [9/16] Loss: 0.00230 +Epoch [3431/4000] Training [10/16] Loss: 0.00354 +Epoch [3431/4000] Training [11/16] Loss: 0.00214 +Epoch [3431/4000] Training [12/16] Loss: 0.00226 +Epoch [3431/4000] Training [13/16] Loss: 0.00282 +Epoch [3431/4000] Training [14/16] Loss: 0.00229 +Epoch [3431/4000] Training [15/16] Loss: 0.00291 +Epoch [3431/4000] Training [16/16] Loss: 0.00247 +Epoch [3431/4000] Training metric {'Train/mean dice_metric': 0.9987093210220337, 'Train/mean miou_metric': 0.9971384406089783, 'Train/mean f1': 0.9937866926193237, 'Train/mean precision': 0.9892680644989014, 'Train/mean recall': 0.9983468055725098, 'Train/mean hd95_metric': 0.5648990869522095} +Epoch [3431/4000] Validation [1/4] Loss: 0.48183 focal_loss 0.41403 dice_loss 0.06780 +Epoch [3431/4000] Validation [2/4] Loss: 0.60918 focal_loss 0.45223 dice_loss 0.15695 +Epoch [3431/4000] Validation [3/4] Loss: 0.53696 focal_loss 0.44111 dice_loss 0.09585 +Epoch [3431/4000] Validation [4/4] Loss: 0.35664 focal_loss 0.26890 dice_loss 0.08774 +Epoch [3431/4000] Validation metric {'Val/mean dice_metric': 0.9740099906921387, 'Val/mean miou_metric': 0.9599997401237488, 'Val/mean f1': 0.9764647483825684, 'Val/mean precision': 0.9749143123626709, 'Val/mean recall': 0.978020191192627, 'Val/mean hd95_metric': 4.92738151550293} +Cheakpoint... +Epoch [3431/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740099906921387, 'Val/mean miou_metric': 0.9599997401237488, 'Val/mean f1': 0.9764647483825684, 'Val/mean precision': 0.9749143123626709, 'Val/mean recall': 0.978020191192627, 'Val/mean hd95_metric': 4.92738151550293} +Epoch [3432/4000] Training [1/16] Loss: 0.00293 +Epoch [3432/4000] Training [2/16] Loss: 0.00195 +Epoch [3432/4000] Training [3/16] Loss: 0.00219 +Epoch [3432/4000] Training [4/16] Loss: 0.00244 +Epoch [3432/4000] Training [5/16] Loss: 0.00291 +Epoch [3432/4000] Training [6/16] Loss: 0.00238 +Epoch [3432/4000] Training [7/16] Loss: 0.00244 +Epoch [3432/4000] Training [8/16] Loss: 0.00234 +Epoch [3432/4000] Training [9/16] Loss: 0.00254 +Epoch [3432/4000] Training [10/16] Loss: 0.00255 +Epoch [3432/4000] Training [11/16] Loss: 0.00231 +Epoch [3432/4000] Training [12/16] Loss: 0.00219 +Epoch [3432/4000] Training [13/16] Loss: 0.00223 +Epoch [3432/4000] Training [14/16] Loss: 0.00235 +Epoch [3432/4000] Training [15/16] Loss: 0.00162 +Epoch [3432/4000] Training [16/16] Loss: 0.00384 +Epoch [3432/4000] Training metric {'Train/mean dice_metric': 0.998771607875824, 'Train/mean miou_metric': 0.9972481727600098, 'Train/mean f1': 0.9931508302688599, 'Train/mean precision': 0.9880412220954895, 'Train/mean recall': 0.9983135461807251, 'Train/mean hd95_metric': 0.5345810651779175} +Epoch [3432/4000] Validation [1/4] Loss: 0.46471 focal_loss 0.39909 dice_loss 0.06562 +Epoch [3432/4000] Validation [2/4] Loss: 0.98359 focal_loss 0.79399 dice_loss 0.18960 +Epoch [3432/4000] Validation [3/4] Loss: 0.52776 focal_loss 0.43500 dice_loss 0.09276 +Epoch [3432/4000] Validation [4/4] Loss: 0.37388 focal_loss 0.26854 dice_loss 0.10534 +Epoch [3432/4000] Validation metric {'Val/mean dice_metric': 0.971904456615448, 'Val/mean miou_metric': 0.9584565162658691, 'Val/mean f1': 0.9748377799987793, 'Val/mean precision': 0.9732666015625, 'Val/mean recall': 0.9764139652252197, 'Val/mean hd95_metric': 5.162063121795654} +Cheakpoint... +Epoch [3432/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971904456615448, 'Val/mean miou_metric': 0.9584565162658691, 'Val/mean f1': 0.9748377799987793, 'Val/mean precision': 0.9732666015625, 'Val/mean recall': 0.9764139652252197, 'Val/mean hd95_metric': 5.162063121795654} +Epoch [3433/4000] Training [1/16] Loss: 0.00232 +Epoch [3433/4000] Training [2/16] Loss: 0.00233 +Epoch [3433/4000] Training [3/16] Loss: 0.00270 +Epoch [3433/4000] Training [4/16] Loss: 0.00187 +Epoch [3433/4000] Training [5/16] Loss: 0.00213 +Epoch [3433/4000] Training [6/16] Loss: 0.00277 +Epoch [3433/4000] Training [7/16] Loss: 0.00607 +Epoch [3433/4000] Training [8/16] Loss: 0.00138 +Epoch [3433/4000] Training [9/16] Loss: 0.00233 +Epoch [3433/4000] Training [10/16] Loss: 0.00236 +Epoch [3433/4000] Training [11/16] Loss: 0.00283 +Epoch [3433/4000] Training [12/16] Loss: 0.00348 +Epoch [3433/4000] Training [13/16] Loss: 0.00245 +Epoch [3433/4000] Training [14/16] Loss: 0.00358 +Epoch [3433/4000] Training [15/16] Loss: 0.00332 +Epoch [3433/4000] Training [16/16] Loss: 0.00244 +Epoch [3433/4000] Training metric {'Train/mean dice_metric': 0.9986156821250916, 'Train/mean miou_metric': 0.9969612956047058, 'Train/mean f1': 0.993672251701355, 'Train/mean precision': 0.9891368746757507, 'Train/mean recall': 0.9982494115829468, 'Train/mean hd95_metric': 0.5815703868865967} +Epoch [3433/4000] Validation [1/4] Loss: 0.39840 focal_loss 0.33108 dice_loss 0.06733 +Epoch [3433/4000] Validation [2/4] Loss: 0.77433 focal_loss 0.56899 dice_loss 0.20534 +Epoch [3433/4000] Validation [3/4] Loss: 0.59156 focal_loss 0.48995 dice_loss 0.10161 +Epoch [3433/4000] Validation [4/4] Loss: 0.33505 focal_loss 0.24998 dice_loss 0.08506 +Epoch [3433/4000] Validation metric {'Val/mean dice_metric': 0.9721490740776062, 'Val/mean miou_metric': 0.9577468633651733, 'Val/mean f1': 0.9749861359596252, 'Val/mean precision': 0.9731576442718506, 'Val/mean recall': 0.9768213629722595, 'Val/mean hd95_metric': 5.414398670196533} +Cheakpoint... +Epoch [3433/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721490740776062, 'Val/mean miou_metric': 0.9577468633651733, 'Val/mean f1': 0.9749861359596252, 'Val/mean precision': 0.9731576442718506, 'Val/mean recall': 0.9768213629722595, 'Val/mean hd95_metric': 5.414398670196533} +Epoch [3434/4000] Training [1/16] Loss: 0.00207 +Epoch [3434/4000] Training [2/16] Loss: 0.00264 +Epoch [3434/4000] Training [3/16] Loss: 0.00267 +Epoch [3434/4000] Training [4/16] Loss: 0.00296 +Epoch [3434/4000] Training [5/16] Loss: 0.00348 +Epoch [3434/4000] Training [6/16] Loss: 0.00321 +Epoch [3434/4000] Training [7/16] Loss: 0.00194 +Epoch [3434/4000] Training [8/16] Loss: 0.00288 +Epoch [3434/4000] Training [9/16] Loss: 0.00183 +Epoch [3434/4000] Training [10/16] Loss: 0.00230 +Epoch [3434/4000] Training [11/16] Loss: 0.00249 +Epoch [3434/4000] Training [12/16] Loss: 0.00316 +Epoch [3434/4000] Training [13/16] Loss: 0.00197 +Epoch [3434/4000] Training [14/16] Loss: 0.00479 +Epoch [3434/4000] Training [15/16] Loss: 0.00198 +Epoch [3434/4000] Training [16/16] Loss: 0.00246 +Epoch [3434/4000] Training metric {'Train/mean dice_metric': 0.9985673427581787, 'Train/mean miou_metric': 0.9968584775924683, 'Train/mean f1': 0.9935843348503113, 'Train/mean precision': 0.9890140891075134, 'Train/mean recall': 0.9981970191001892, 'Train/mean hd95_metric': 0.5861603021621704} +Epoch [3434/4000] Validation [1/4] Loss: 0.45558 focal_loss 0.38423 dice_loss 0.07135 +Epoch [3434/4000] Validation [2/4] Loss: 1.18275 focal_loss 0.90185 dice_loss 0.28090 +Epoch [3434/4000] Validation [3/4] Loss: 0.24064 focal_loss 0.18608 dice_loss 0.05455 +Epoch [3434/4000] Validation [4/4] Loss: 0.34044 focal_loss 0.25388 dice_loss 0.08656 +Epoch [3434/4000] Validation metric {'Val/mean dice_metric': 0.9709394574165344, 'Val/mean miou_metric': 0.9571743011474609, 'Val/mean f1': 0.9751636385917664, 'Val/mean precision': 0.974170982837677, 'Val/mean recall': 0.9761583805084229, 'Val/mean hd95_metric': 5.047943592071533} +Cheakpoint... +Epoch [3434/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9709394574165344, 'Val/mean miou_metric': 0.9571743011474609, 'Val/mean f1': 0.9751636385917664, 'Val/mean precision': 0.974170982837677, 'Val/mean recall': 0.9761583805084229, 'Val/mean hd95_metric': 5.047943592071533} +Epoch [3435/4000] Training [1/16] Loss: 0.00235 +Epoch [3435/4000] Training [2/16] Loss: 0.00224 +Epoch [3435/4000] Training [3/16] Loss: 0.00187 +Epoch [3435/4000] Training [4/16] Loss: 0.00272 +Epoch [3435/4000] Training [5/16] Loss: 0.00280 +Epoch [3435/4000] Training [6/16] Loss: 0.00210 +Epoch [3435/4000] Training [7/16] Loss: 0.00209 +Epoch [3435/4000] Training [8/16] Loss: 0.00316 +Epoch [3435/4000] Training [9/16] Loss: 0.00197 +Epoch [3435/4000] Training [10/16] Loss: 0.00175 +Epoch [3435/4000] Training [11/16] Loss: 0.00225 +Epoch [3435/4000] Training [12/16] Loss: 0.00276 +Epoch [3435/4000] Training [13/16] Loss: 0.00423 +Epoch [3435/4000] Training [14/16] Loss: 0.00225 +Epoch [3435/4000] Training [15/16] Loss: 0.00216 +Epoch [3435/4000] Training [16/16] Loss: 0.00196 +Epoch [3435/4000] Training metric {'Train/mean dice_metric': 0.9986742734909058, 'Train/mean miou_metric': 0.9970636367797852, 'Train/mean f1': 0.993687093257904, 'Train/mean precision': 0.9891438484191895, 'Train/mean recall': 0.9982722401618958, 'Train/mean hd95_metric': 0.6085780262947083} +Epoch [3435/4000] Validation [1/4] Loss: 0.41802 focal_loss 0.35219 dice_loss 0.06583 +Epoch [3435/4000] Validation [2/4] Loss: 1.37705 focal_loss 1.09447 dice_loss 0.28259 +Epoch [3435/4000] Validation [3/4] Loss: 0.51269 focal_loss 0.41310 dice_loss 0.09959 +Epoch [3435/4000] Validation [4/4] Loss: 0.31968 focal_loss 0.22318 dice_loss 0.09651 +Epoch [3435/4000] Validation metric {'Val/mean dice_metric': 0.9708549380302429, 'Val/mean miou_metric': 0.9576873779296875, 'Val/mean f1': 0.9755412936210632, 'Val/mean precision': 0.9737909436225891, 'Val/mean recall': 0.9772979021072388, 'Val/mean hd95_metric': 5.497707843780518} +Cheakpoint... +Epoch [3435/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9709], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9708549380302429, 'Val/mean miou_metric': 0.9576873779296875, 'Val/mean f1': 0.9755412936210632, 'Val/mean precision': 0.9737909436225891, 'Val/mean recall': 0.9772979021072388, 'Val/mean hd95_metric': 5.497707843780518} +Epoch [3436/4000] Training [1/16] Loss: 0.00267 +Epoch [3436/4000] Training [2/16] Loss: 0.00264 +Epoch [3436/4000] Training [3/16] Loss: 0.00269 +Epoch [3436/4000] Training [4/16] Loss: 0.00222 +Epoch [3436/4000] Training [5/16] Loss: 0.00248 +Epoch [3436/4000] Training [6/16] Loss: 0.00244 +Epoch [3436/4000] Training [7/16] Loss: 0.00411 +Epoch [3436/4000] Training [8/16] Loss: 0.00310 +Epoch [3436/4000] Training [9/16] Loss: 0.00187 +Epoch [3436/4000] Training [10/16] Loss: 0.00361 +Epoch [3436/4000] Training [11/16] Loss: 0.00192 +Epoch [3436/4000] Training [12/16] Loss: 0.00236 +Epoch [3436/4000] Training [13/16] Loss: 0.00211 +Epoch [3436/4000] Training [14/16] Loss: 0.00174 +Epoch [3436/4000] Training [15/16] Loss: 0.00361 +Epoch [3436/4000] Training [16/16] Loss: 0.00278 +Epoch [3436/4000] Training metric {'Train/mean dice_metric': 0.9986035823822021, 'Train/mean miou_metric': 0.9969221353530884, 'Train/mean f1': 0.9935894012451172, 'Train/mean precision': 0.9890264272689819, 'Train/mean recall': 0.9981946349143982, 'Train/mean hd95_metric': 0.6056631803512573} +Epoch [3436/4000] Validation [1/4] Loss: 0.40032 focal_loss 0.33455 dice_loss 0.06577 +Epoch [3436/4000] Validation [2/4] Loss: 0.46682 focal_loss 0.35856 dice_loss 0.10826 +Epoch [3436/4000] Validation [3/4] Loss: 0.51747 focal_loss 0.42367 dice_loss 0.09380 +Epoch [3436/4000] Validation [4/4] Loss: 0.30496 focal_loss 0.21485 dice_loss 0.09012 +Epoch [3436/4000] Validation metric {'Val/mean dice_metric': 0.9735475778579712, 'Val/mean miou_metric': 0.9594029188156128, 'Val/mean f1': 0.976372480392456, 'Val/mean precision': 0.9738425016403198, 'Val/mean recall': 0.9789156913757324, 'Val/mean hd95_metric': 4.879327297210693} +Cheakpoint... +Epoch [3436/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735475778579712, 'Val/mean miou_metric': 0.9594029188156128, 'Val/mean f1': 0.976372480392456, 'Val/mean precision': 0.9738425016403198, 'Val/mean recall': 0.9789156913757324, 'Val/mean hd95_metric': 4.879327297210693} +Epoch [3437/4000] Training [1/16] Loss: 0.00382 +Epoch [3437/4000] Training [2/16] Loss: 0.00249 +Epoch [3437/4000] Training [3/16] Loss: 0.00279 +Epoch [3437/4000] Training [4/16] Loss: 0.00212 +Epoch [3437/4000] Training [5/16] Loss: 0.00327 +Epoch [3437/4000] Training [6/16] Loss: 0.00289 +Epoch [3437/4000] Training [7/16] Loss: 0.00238 +Epoch [3437/4000] Training [8/16] Loss: 0.00319 +Epoch [3437/4000] Training [9/16] Loss: 0.00194 +Epoch [3437/4000] Training [10/16] Loss: 0.00295 +Epoch [3437/4000] Training [11/16] Loss: 0.00609 +Epoch [3437/4000] Training [12/16] Loss: 0.00297 +Epoch [3437/4000] Training [13/16] Loss: 0.00312 +Epoch [3437/4000] Training [14/16] Loss: 0.00262 +Epoch [3437/4000] Training [15/16] Loss: 0.00242 +Epoch [3437/4000] Training [16/16] Loss: 0.00373 +Epoch [3437/4000] Training metric {'Train/mean dice_metric': 0.9984530210494995, 'Train/mean miou_metric': 0.9965804815292358, 'Train/mean f1': 0.9922307729721069, 'Train/mean precision': 0.9864765405654907, 'Train/mean recall': 0.9980525374412537, 'Train/mean hd95_metric': 0.6671479940414429} +Epoch [3437/4000] Validation [1/4] Loss: 0.42671 focal_loss 0.35979 dice_loss 0.06692 +Epoch [3437/4000] Validation [2/4] Loss: 0.85732 focal_loss 0.66107 dice_loss 0.19625 +Epoch [3437/4000] Validation [3/4] Loss: 0.53928 focal_loss 0.43963 dice_loss 0.09965 +Epoch [3437/4000] Validation [4/4] Loss: 0.31148 focal_loss 0.21722 dice_loss 0.09426 +Epoch [3437/4000] Validation metric {'Val/mean dice_metric': 0.9727684855461121, 'Val/mean miou_metric': 0.9583379626274109, 'Val/mean f1': 0.9743143320083618, 'Val/mean precision': 0.9706273078918457, 'Val/mean recall': 0.9780295491218567, 'Val/mean hd95_metric': 5.326808929443359} +Cheakpoint... +Epoch [3437/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727684855461121, 'Val/mean miou_metric': 0.9583379626274109, 'Val/mean f1': 0.9743143320083618, 'Val/mean precision': 0.9706273078918457, 'Val/mean recall': 0.9780295491218567, 'Val/mean hd95_metric': 5.326808929443359} +Epoch [3438/4000] Training [1/16] Loss: 0.00351 +Epoch [3438/4000] Training [2/16] Loss: 0.00307 +Epoch [3438/4000] Training [3/16] Loss: 0.00325 +Epoch [3438/4000] Training [4/16] Loss: 0.00266 +Epoch [3438/4000] Training [5/16] Loss: 0.00368 +Epoch [3438/4000] Training [6/16] Loss: 0.00323 +Epoch [3438/4000] Training [7/16] Loss: 0.00316 +Epoch [3438/4000] Training [8/16] Loss: 0.00234 +Epoch [3438/4000] Training [9/16] Loss: 0.00212 +Epoch [3438/4000] Training [10/16] Loss: 0.00304 +Epoch [3438/4000] Training [11/16] Loss: 0.00199 +Epoch [3438/4000] Training [12/16] Loss: 0.00202 +Epoch [3438/4000] Training [13/16] Loss: 0.00303 +Epoch [3438/4000] Training [14/16] Loss: 0.00307 +Epoch [3438/4000] Training [15/16] Loss: 0.00250 +Epoch [3438/4000] Training [16/16] Loss: 0.00245 +Epoch [3438/4000] Training metric {'Train/mean dice_metric': 0.9985685348510742, 'Train/mean miou_metric': 0.99686598777771, 'Train/mean f1': 0.9936793446540833, 'Train/mean precision': 0.9891632795333862, 'Train/mean recall': 0.9982368350028992, 'Train/mean hd95_metric': 0.6523711681365967} +Epoch [3438/4000] Validation [1/4] Loss: 0.39144 focal_loss 0.33181 dice_loss 0.05963 +Epoch [3438/4000] Validation [2/4] Loss: 0.67824 focal_loss 0.50545 dice_loss 0.17279 +Epoch [3438/4000] Validation [3/4] Loss: 0.53673 focal_loss 0.44412 dice_loss 0.09261 +Epoch [3438/4000] Validation [4/4] Loss: 0.36040 focal_loss 0.27265 dice_loss 0.08775 +Epoch [3438/4000] Validation metric {'Val/mean dice_metric': 0.974625289440155, 'Val/mean miou_metric': 0.9603235125541687, 'Val/mean f1': 0.9761115312576294, 'Val/mean precision': 0.9746623635292053, 'Val/mean recall': 0.9775651693344116, 'Val/mean hd95_metric': 4.931743621826172} +Cheakpoint... +Epoch [3438/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974625289440155, 'Val/mean miou_metric': 0.9603235125541687, 'Val/mean f1': 0.9761115312576294, 'Val/mean precision': 0.9746623635292053, 'Val/mean recall': 0.9775651693344116, 'Val/mean hd95_metric': 4.931743621826172} +Epoch [3439/4000] Training [1/16] Loss: 0.00182 +Epoch [3439/4000] Training [2/16] Loss: 0.00202 +Epoch [3439/4000] Training [3/16] Loss: 0.00258 +Epoch [3439/4000] Training [4/16] Loss: 0.00286 +Epoch [3439/4000] Training [5/16] Loss: 0.00177 +Epoch [3439/4000] Training [6/16] Loss: 0.00303 +Epoch [3439/4000] Training [7/16] Loss: 0.00190 +Epoch [3439/4000] Training [8/16] Loss: 0.00271 +Epoch [3439/4000] Training [9/16] Loss: 0.00327 +Epoch [3439/4000] Training [10/16] Loss: 0.00273 +Epoch [3439/4000] Training [11/16] Loss: 0.00422 +Epoch [3439/4000] Training [12/16] Loss: 0.00337 +Epoch [3439/4000] Training [13/16] Loss: 0.00424 +Epoch [3439/4000] Training [14/16] Loss: 0.00259 +Epoch [3439/4000] Training [15/16] Loss: 0.00318 +Epoch [3439/4000] Training [16/16] Loss: 0.00267 +Epoch [3439/4000] Training metric {'Train/mean dice_metric': 0.9985132813453674, 'Train/mean miou_metric': 0.9967389106750488, 'Train/mean f1': 0.9934893846511841, 'Train/mean precision': 0.9888829588890076, 'Train/mean recall': 0.998138964176178, 'Train/mean hd95_metric': 0.5794077515602112} +Epoch [3439/4000] Validation [1/4] Loss: 0.36590 focal_loss 0.30338 dice_loss 0.06252 +Epoch [3439/4000] Validation [2/4] Loss: 0.52388 focal_loss 0.39206 dice_loss 0.13182 +Epoch [3439/4000] Validation [3/4] Loss: 0.51546 focal_loss 0.42447 dice_loss 0.09099 +Epoch [3439/4000] Validation [4/4] Loss: 0.42202 focal_loss 0.31467 dice_loss 0.10736 +Epoch [3439/4000] Validation metric {'Val/mean dice_metric': 0.9741570353507996, 'Val/mean miou_metric': 0.9597295522689819, 'Val/mean f1': 0.9762957096099854, 'Val/mean precision': 0.974399745464325, 'Val/mean recall': 0.9781990647315979, 'Val/mean hd95_metric': 4.79089879989624} +Cheakpoint... +Epoch [3439/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741570353507996, 'Val/mean miou_metric': 0.9597295522689819, 'Val/mean f1': 0.9762957096099854, 'Val/mean precision': 0.974399745464325, 'Val/mean recall': 0.9781990647315979, 'Val/mean hd95_metric': 4.79089879989624} +Epoch [3440/4000] Training [1/16] Loss: 0.00365 +Epoch [3440/4000] Training [2/16] Loss: 0.00214 +Epoch [3440/4000] Training [3/16] Loss: 0.00324 +Epoch [3440/4000] Training [4/16] Loss: 0.00211 +Epoch [3440/4000] Training [5/16] Loss: 0.00193 +Epoch [3440/4000] Training [6/16] Loss: 0.00217 +Epoch [3440/4000] Training [7/16] Loss: 0.00315 +Epoch [3440/4000] Training [8/16] Loss: 0.00250 +Epoch [3440/4000] Training [9/16] Loss: 0.00236 +Epoch [3440/4000] Training [10/16] Loss: 0.00309 +Epoch [3440/4000] Training [11/16] Loss: 0.00221 +Epoch [3440/4000] Training [12/16] Loss: 0.00215 +Epoch [3440/4000] Training [13/16] Loss: 0.00185 +Epoch [3440/4000] Training [14/16] Loss: 0.00195 +Epoch [3440/4000] Training [15/16] Loss: 0.00259 +Epoch [3440/4000] Training [16/16] Loss: 0.00205 +Epoch [3440/4000] Training metric {'Train/mean dice_metric': 0.9986938834190369, 'Train/mean miou_metric': 0.997113049030304, 'Train/mean f1': 0.993682861328125, 'Train/mean precision': 0.9890782833099365, 'Train/mean recall': 0.9983305335044861, 'Train/mean hd95_metric': 0.575711190700531} +Epoch [3440/4000] Validation [1/4] Loss: 0.38424 focal_loss 0.32102 dice_loss 0.06322 +Epoch [3440/4000] Validation [2/4] Loss: 0.71381 focal_loss 0.52181 dice_loss 0.19200 +Epoch [3440/4000] Validation [3/4] Loss: 0.50988 focal_loss 0.41271 dice_loss 0.09716 +Epoch [3440/4000] Validation [4/4] Loss: 0.32781 focal_loss 0.23844 dice_loss 0.08937 +Epoch [3440/4000] Validation metric {'Val/mean dice_metric': 0.9732059240341187, 'Val/mean miou_metric': 0.9590317010879517, 'Val/mean f1': 0.9758597612380981, 'Val/mean precision': 0.9741717576980591, 'Val/mean recall': 0.9775536060333252, 'Val/mean hd95_metric': 4.780804634094238} +Cheakpoint... +Epoch [3440/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732059240341187, 'Val/mean miou_metric': 0.9590317010879517, 'Val/mean f1': 0.9758597612380981, 'Val/mean precision': 0.9741717576980591, 'Val/mean recall': 0.9775536060333252, 'Val/mean hd95_metric': 4.780804634094238} +Epoch [3441/4000] Training [1/16] Loss: 0.00215 +Epoch [3441/4000] Training [2/16] Loss: 0.00230 +Epoch [3441/4000] Training [3/16] Loss: 0.00228 +Epoch [3441/4000] Training [4/16] Loss: 0.00273 +Epoch [3441/4000] Training [5/16] Loss: 0.00177 +Epoch [3441/4000] Training [6/16] Loss: 0.00331 +Epoch [3441/4000] Training [7/16] Loss: 0.00228 +Epoch [3441/4000] Training [8/16] Loss: 0.00323 +Epoch [3441/4000] Training [9/16] Loss: 0.00284 +Epoch [3441/4000] Training [10/16] Loss: 0.00205 +Epoch [3441/4000] Training [11/16] Loss: 0.00445 +Epoch [3441/4000] Training [12/16] Loss: 0.00220 +Epoch [3441/4000] Training [13/16] Loss: 0.00185 +Epoch [3441/4000] Training [14/16] Loss: 0.00342 +Epoch [3441/4000] Training [15/16] Loss: 0.00337 +Epoch [3441/4000] Training [16/16] Loss: 0.00455 +Epoch [3441/4000] Training metric {'Train/mean dice_metric': 0.9985101819038391, 'Train/mean miou_metric': 0.99675452709198, 'Train/mean f1': 0.9935487508773804, 'Train/mean precision': 0.9891255497932434, 'Train/mean recall': 0.9980116486549377, 'Train/mean hd95_metric': 0.5985685586929321} +Epoch [3441/4000] Validation [1/4] Loss: 0.42224 focal_loss 0.35687 dice_loss 0.06537 +Epoch [3441/4000] Validation [2/4] Loss: 0.48185 focal_loss 0.37197 dice_loss 0.10989 +Epoch [3441/4000] Validation [3/4] Loss: 0.55740 focal_loss 0.46269 dice_loss 0.09472 +Epoch [3441/4000] Validation [4/4] Loss: 0.44711 focal_loss 0.33983 dice_loss 0.10728 +Epoch [3441/4000] Validation metric {'Val/mean dice_metric': 0.9743345379829407, 'Val/mean miou_metric': 0.9599746465682983, 'Val/mean f1': 0.9763182997703552, 'Val/mean precision': 0.9749060869216919, 'Val/mean recall': 0.9777346253395081, 'Val/mean hd95_metric': 4.905359745025635} +Cheakpoint... +Epoch [3441/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743345379829407, 'Val/mean miou_metric': 0.9599746465682983, 'Val/mean f1': 0.9763182997703552, 'Val/mean precision': 0.9749060869216919, 'Val/mean recall': 0.9777346253395081, 'Val/mean hd95_metric': 4.905359745025635} +Epoch [3442/4000] Training [1/16] Loss: 0.00172 +Epoch [3442/4000] Training [2/16] Loss: 0.00236 +Epoch [3442/4000] Training [3/16] Loss: 0.00233 +Epoch [3442/4000] Training [4/16] Loss: 0.00301 +Epoch [3442/4000] Training [5/16] Loss: 0.00234 +Epoch [3442/4000] Training [6/16] Loss: 0.00271 +Epoch [3442/4000] Training [7/16] Loss: 0.00345 +Epoch [3442/4000] Training [8/16] Loss: 0.00231 +Epoch [3442/4000] Training [9/16] Loss: 0.00329 +Epoch [3442/4000] Training [10/16] Loss: 0.00243 +Epoch [3442/4000] Training [11/16] Loss: 0.00232 +Epoch [3442/4000] Training [12/16] Loss: 0.00217 +Epoch [3442/4000] Training [13/16] Loss: 0.00188 +Epoch [3442/4000] Training [14/16] Loss: 0.00239 +Epoch [3442/4000] Training [15/16] Loss: 0.00345 +Epoch [3442/4000] Training [16/16] Loss: 0.00262 +Epoch [3442/4000] Training metric {'Train/mean dice_metric': 0.9987120628356934, 'Train/mean miou_metric': 0.997143030166626, 'Train/mean f1': 0.9935895800590515, 'Train/mean precision': 0.9888988733291626, 'Train/mean recall': 0.998324990272522, 'Train/mean hd95_metric': 0.5682892799377441} +Epoch [3442/4000] Validation [1/4] Loss: 0.32086 focal_loss 0.26280 dice_loss 0.05806 +Epoch [3442/4000] Validation [2/4] Loss: 0.72146 focal_loss 0.54181 dice_loss 0.17965 +Epoch [3442/4000] Validation [3/4] Loss: 0.56990 focal_loss 0.47176 dice_loss 0.09814 +Epoch [3442/4000] Validation [4/4] Loss: 0.32168 focal_loss 0.23746 dice_loss 0.08422 +Epoch [3442/4000] Validation metric {'Val/mean dice_metric': 0.97265625, 'Val/mean miou_metric': 0.9587876200675964, 'Val/mean f1': 0.9754081964492798, 'Val/mean precision': 0.9732207655906677, 'Val/mean recall': 0.9776053428649902, 'Val/mean hd95_metric': 5.346076011657715} +Cheakpoint... +Epoch [3442/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97265625, 'Val/mean miou_metric': 0.9587876200675964, 'Val/mean f1': 0.9754081964492798, 'Val/mean precision': 0.9732207655906677, 'Val/mean recall': 0.9776053428649902, 'Val/mean hd95_metric': 5.346076011657715} +Epoch [3443/4000] Training [1/16] Loss: 0.00230 +Epoch [3443/4000] Training [2/16] Loss: 0.00212 +Epoch [3443/4000] Training [3/16] Loss: 0.00450 +Epoch [3443/4000] Training [4/16] Loss: 0.00387 +Epoch [3443/4000] Training [5/16] Loss: 0.00377 +Epoch [3443/4000] Training [6/16] Loss: 0.00218 +Epoch [3443/4000] Training [7/16] Loss: 0.00294 +Epoch [3443/4000] Training [8/16] Loss: 0.00418 +Epoch [3443/4000] Training [9/16] Loss: 0.00224 +Epoch [3443/4000] Training [10/16] Loss: 0.00256 +Epoch [3443/4000] Training [11/16] Loss: 0.00238 +Epoch [3443/4000] Training [12/16] Loss: 0.00188 +Epoch [3443/4000] Training [13/16] Loss: 0.00428 +Epoch [3443/4000] Training [14/16] Loss: 0.00455 +Epoch [3443/4000] Training [15/16] Loss: 0.00346 +Epoch [3443/4000] Training [16/16] Loss: 0.00326 +Epoch [3443/4000] Training metric {'Train/mean dice_metric': 0.9985133409500122, 'Train/mean miou_metric': 0.9967514276504517, 'Train/mean f1': 0.9935466647148132, 'Train/mean precision': 0.9889724254608154, 'Train/mean recall': 0.9981633424758911, 'Train/mean hd95_metric': 0.5675380229949951} +Epoch [3443/4000] Validation [1/4] Loss: 0.40156 focal_loss 0.33793 dice_loss 0.06364 +Epoch [3443/4000] Validation [2/4] Loss: 0.46770 focal_loss 0.35864 dice_loss 0.10906 +Epoch [3443/4000] Validation [3/4] Loss: 0.51488 focal_loss 0.41682 dice_loss 0.09806 +Epoch [3443/4000] Validation [4/4] Loss: 0.36283 focal_loss 0.26039 dice_loss 0.10244 +Epoch [3443/4000] Validation metric {'Val/mean dice_metric': 0.9740279912948608, 'Val/mean miou_metric': 0.9595918655395508, 'Val/mean f1': 0.9757038354873657, 'Val/mean precision': 0.9733121991157532, 'Val/mean recall': 0.978107213973999, 'Val/mean hd95_metric': 5.230257987976074} +Cheakpoint... +Epoch [3443/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740279912948608, 'Val/mean miou_metric': 0.9595918655395508, 'Val/mean f1': 0.9757038354873657, 'Val/mean precision': 0.9733121991157532, 'Val/mean recall': 0.978107213973999, 'Val/mean hd95_metric': 5.230257987976074} +Epoch [3444/4000] Training [1/16] Loss: 0.00250 +Epoch [3444/4000] Training [2/16] Loss: 0.00272 +Epoch [3444/4000] Training [3/16] Loss: 0.00277 +Epoch [3444/4000] Training [4/16] Loss: 0.00186 +Epoch [3444/4000] Training [5/16] Loss: 0.00204 +Epoch [3444/4000] Training [6/16] Loss: 0.00281 +Epoch [3444/4000] Training [7/16] Loss: 0.00497 +Epoch [3444/4000] Training [8/16] Loss: 0.00235 +Epoch [3444/4000] Training [9/16] Loss: 0.00221 +Epoch [3444/4000] Training [10/16] Loss: 0.00208 +Epoch [3444/4000] Training [11/16] Loss: 0.00257 +Epoch [3444/4000] Training [12/16] Loss: 0.00252 +Epoch [3444/4000] Training [13/16] Loss: 0.00293 +Epoch [3444/4000] Training [14/16] Loss: 0.00193 +Epoch [3444/4000] Training [15/16] Loss: 0.00241 +Epoch [3444/4000] Training [16/16] Loss: 0.00233 +Epoch [3444/4000] Training metric {'Train/mean dice_metric': 0.9986478686332703, 'Train/mean miou_metric': 0.997017502784729, 'Train/mean f1': 0.9935688376426697, 'Train/mean precision': 0.9888896942138672, 'Train/mean recall': 0.9982924461364746, 'Train/mean hd95_metric': 0.5783057808876038} +Epoch [3444/4000] Validation [1/4] Loss: 0.38659 focal_loss 0.32712 dice_loss 0.05947 +Epoch [3444/4000] Validation [2/4] Loss: 0.94802 focal_loss 0.68843 dice_loss 0.25959 +Epoch [3444/4000] Validation [3/4] Loss: 0.50026 focal_loss 0.41473 dice_loss 0.08553 +Epoch [3444/4000] Validation [4/4] Loss: 0.32988 focal_loss 0.24623 dice_loss 0.08365 +Epoch [3444/4000] Validation metric {'Val/mean dice_metric': 0.9732002019882202, 'Val/mean miou_metric': 0.959101676940918, 'Val/mean f1': 0.9759491086006165, 'Val/mean precision': 0.9738031029701233, 'Val/mean recall': 0.9781045317649841, 'Val/mean hd95_metric': 4.919779300689697} +Cheakpoint... +Epoch [3444/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732002019882202, 'Val/mean miou_metric': 0.959101676940918, 'Val/mean f1': 0.9759491086006165, 'Val/mean precision': 0.9738031029701233, 'Val/mean recall': 0.9781045317649841, 'Val/mean hd95_metric': 4.919779300689697} +Epoch [3445/4000] Training [1/16] Loss: 0.00251 +Epoch [3445/4000] Training [2/16] Loss: 0.00237 +Epoch [3445/4000] Training [3/16] Loss: 0.00269 +Epoch [3445/4000] Training [4/16] Loss: 0.00149 +Epoch [3445/4000] Training [5/16] Loss: 0.00234 +Epoch [3445/4000] Training [6/16] Loss: 0.00307 +Epoch [3445/4000] Training [7/16] Loss: 0.00251 +Epoch [3445/4000] Training [8/16] Loss: 0.00366 +Epoch [3445/4000] Training [9/16] Loss: 0.00185 +Epoch [3445/4000] Training [10/16] Loss: 0.00259 +Epoch [3445/4000] Training [11/16] Loss: 0.00259 +Epoch [3445/4000] Training [12/16] Loss: 0.00245 +Epoch [3445/4000] Training [13/16] Loss: 0.00308 +Epoch [3445/4000] Training [14/16] Loss: 0.00282 +Epoch [3445/4000] Training [15/16] Loss: 0.00221 +Epoch [3445/4000] Training [16/16] Loss: 0.00174 +Epoch [3445/4000] Training metric {'Train/mean dice_metric': 0.9986515641212463, 'Train/mean miou_metric': 0.9970175623893738, 'Train/mean f1': 0.9934597015380859, 'Train/mean precision': 0.9886625409126282, 'Train/mean recall': 0.9983036518096924, 'Train/mean hd95_metric': 0.5778873562812805} +Epoch [3445/4000] Validation [1/4] Loss: 0.36617 focal_loss 0.30441 dice_loss 0.06176 +Epoch [3445/4000] Validation [2/4] Loss: 0.83081 focal_loss 0.61504 dice_loss 0.21577 +Epoch [3445/4000] Validation [3/4] Loss: 0.23783 focal_loss 0.18484 dice_loss 0.05299 +Epoch [3445/4000] Validation [4/4] Loss: 0.34088 focal_loss 0.25326 dice_loss 0.08762 +Epoch [3445/4000] Validation metric {'Val/mean dice_metric': 0.9740459322929382, 'Val/mean miou_metric': 0.9603821039199829, 'Val/mean f1': 0.9764798879623413, 'Val/mean precision': 0.9742034077644348, 'Val/mean recall': 0.9787670969963074, 'Val/mean hd95_metric': 4.755315780639648} +Cheakpoint... +Epoch [3445/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740459322929382, 'Val/mean miou_metric': 0.9603821039199829, 'Val/mean f1': 0.9764798879623413, 'Val/mean precision': 0.9742034077644348, 'Val/mean recall': 0.9787670969963074, 'Val/mean hd95_metric': 4.755315780639648} +Epoch [3446/4000] Training [1/16] Loss: 0.00187 +Epoch [3446/4000] Training [2/16] Loss: 0.00359 +Epoch [3446/4000] Training [3/16] Loss: 0.00408 +Epoch [3446/4000] Training [4/16] Loss: 0.00194 +Epoch [3446/4000] Training [5/16] Loss: 0.00216 +Epoch [3446/4000] Training [6/16] Loss: 0.00262 +Epoch [3446/4000] Training [7/16] Loss: 0.00275 +Epoch [3446/4000] Training [8/16] Loss: 0.00342 +Epoch [3446/4000] Training [9/16] Loss: 0.00233 +Epoch [3446/4000] Training [10/16] Loss: 0.00123 +Epoch [3446/4000] Training [11/16] Loss: 0.00403 +Epoch [3446/4000] Training [12/16] Loss: 0.00237 +Epoch [3446/4000] Training [13/16] Loss: 0.00306 +Epoch [3446/4000] Training [14/16] Loss: 0.00188 +Epoch [3446/4000] Training [15/16] Loss: 0.00210 +Epoch [3446/4000] Training [16/16] Loss: 0.00220 +Epoch [3446/4000] Training metric {'Train/mean dice_metric': 0.9987524151802063, 'Train/mean miou_metric': 0.9972295761108398, 'Train/mean f1': 0.9937376976013184, 'Train/mean precision': 0.989177405834198, 'Train/mean recall': 0.9983401894569397, 'Train/mean hd95_metric': 0.5423126220703125} +Epoch [3446/4000] Validation [1/4] Loss: 0.37026 focal_loss 0.30961 dice_loss 0.06065 +Epoch [3446/4000] Validation [2/4] Loss: 0.48861 focal_loss 0.37573 dice_loss 0.11288 +Epoch [3446/4000] Validation [3/4] Loss: 0.55843 focal_loss 0.45833 dice_loss 0.10011 +Epoch [3446/4000] Validation [4/4] Loss: 0.39616 focal_loss 0.28444 dice_loss 0.11171 +Epoch [3446/4000] Validation metric {'Val/mean dice_metric': 0.9744012951850891, 'Val/mean miou_metric': 0.9598175287246704, 'Val/mean f1': 0.9761499166488647, 'Val/mean precision': 0.9745351672172546, 'Val/mean recall': 0.977770209312439, 'Val/mean hd95_metric': 4.8025007247924805} +Cheakpoint... +Epoch [3446/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744012951850891, 'Val/mean miou_metric': 0.9598175287246704, 'Val/mean f1': 0.9761499166488647, 'Val/mean precision': 0.9745351672172546, 'Val/mean recall': 0.977770209312439, 'Val/mean hd95_metric': 4.8025007247924805} +Epoch [3447/4000] Training [1/16] Loss: 0.00181 +Epoch [3447/4000] Training [2/16] Loss: 0.00350 +Epoch [3447/4000] Training [3/16] Loss: 0.00315 +Epoch [3447/4000] Training [4/16] Loss: 0.00199 +Epoch [3447/4000] Training [5/16] Loss: 0.00204 +Epoch [3447/4000] Training [6/16] Loss: 0.00209 +Epoch [3447/4000] Training [7/16] Loss: 0.00224 +Epoch [3447/4000] Training [8/16] Loss: 0.00241 +Epoch [3447/4000] Training [9/16] Loss: 0.00431 +Epoch [3447/4000] Training [10/16] Loss: 0.00321 +Epoch [3447/4000] Training [11/16] Loss: 0.00264 +Epoch [3447/4000] Training [12/16] Loss: 0.00278 +Epoch [3447/4000] Training [13/16] Loss: 0.00208 +Epoch [3447/4000] Training [14/16] Loss: 0.00238 +Epoch [3447/4000] Training [15/16] Loss: 0.00294 +Epoch [3447/4000] Training [16/16] Loss: 0.00253 +Epoch [3447/4000] Training metric {'Train/mean dice_metric': 0.998664379119873, 'Train/mean miou_metric': 0.9970543384552002, 'Train/mean f1': 0.9936478137969971, 'Train/mean precision': 0.9890654683113098, 'Train/mean recall': 0.9982728362083435, 'Train/mean hd95_metric': 0.5905827283859253} +Epoch [3447/4000] Validation [1/4] Loss: 0.38120 focal_loss 0.31683 dice_loss 0.06437 +Epoch [3447/4000] Validation [2/4] Loss: 0.93130 focal_loss 0.70322 dice_loss 0.22808 +Epoch [3447/4000] Validation [3/4] Loss: 0.53256 focal_loss 0.43585 dice_loss 0.09671 +Epoch [3447/4000] Validation [4/4] Loss: 0.31498 focal_loss 0.22310 dice_loss 0.09189 +Epoch [3447/4000] Validation metric {'Val/mean dice_metric': 0.9719942808151245, 'Val/mean miou_metric': 0.9577583074569702, 'Val/mean f1': 0.975274384021759, 'Val/mean precision': 0.973519504070282, 'Val/mean recall': 0.977035641670227, 'Val/mean hd95_metric': 5.361588954925537} +Cheakpoint... +Epoch [3447/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719942808151245, 'Val/mean miou_metric': 0.9577583074569702, 'Val/mean f1': 0.975274384021759, 'Val/mean precision': 0.973519504070282, 'Val/mean recall': 0.977035641670227, 'Val/mean hd95_metric': 5.361588954925537} +Epoch [3448/4000] Training [1/16] Loss: 0.00239 +Epoch [3448/4000] Training [2/16] Loss: 0.00185 +Epoch [3448/4000] Training [3/16] Loss: 0.00267 +Epoch [3448/4000] Training [4/16] Loss: 0.00177 +Epoch [3448/4000] Training [5/16] Loss: 0.00324 +Epoch [3448/4000] Training [6/16] Loss: 0.00252 +Epoch [3448/4000] Training [7/16] Loss: 0.00336 +Epoch [3448/4000] Training [8/16] Loss: 0.00204 +Epoch [3448/4000] Training [9/16] Loss: 0.00182 +Epoch [3448/4000] Training [10/16] Loss: 0.00386 +Epoch [3448/4000] Training [11/16] Loss: 0.00265 +Epoch [3448/4000] Training [12/16] Loss: 0.00209 +Epoch [3448/4000] Training [13/16] Loss: 0.00269 +Epoch [3448/4000] Training [14/16] Loss: 0.00309 +Epoch [3448/4000] Training [15/16] Loss: 0.00261 +Epoch [3448/4000] Training [16/16] Loss: 0.00165 +Epoch [3448/4000] Training metric {'Train/mean dice_metric': 0.9986885190010071, 'Train/mean miou_metric': 0.9971041679382324, 'Train/mean f1': 0.9937729835510254, 'Train/mean precision': 0.989288330078125, 'Train/mean recall': 0.9982984662055969, 'Train/mean hd95_metric': 0.5453401803970337} +Epoch [3448/4000] Validation [1/4] Loss: 0.33271 focal_loss 0.27312 dice_loss 0.05959 +Epoch [3448/4000] Validation [2/4] Loss: 0.84578 focal_loss 0.65177 dice_loss 0.19402 +Epoch [3448/4000] Validation [3/4] Loss: 0.52259 focal_loss 0.43111 dice_loss 0.09148 +Epoch [3448/4000] Validation [4/4] Loss: 0.31089 focal_loss 0.22705 dice_loss 0.08385 +Epoch [3448/4000] Validation metric {'Val/mean dice_metric': 0.9750036001205444, 'Val/mean miou_metric': 0.9607208371162415, 'Val/mean f1': 0.9764401316642761, 'Val/mean precision': 0.9740101099014282, 'Val/mean recall': 0.978882372379303, 'Val/mean hd95_metric': 4.854396343231201} +Cheakpoint... +Epoch [3448/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750036001205444, 'Val/mean miou_metric': 0.9607208371162415, 'Val/mean f1': 0.9764401316642761, 'Val/mean precision': 0.9740101099014282, 'Val/mean recall': 0.978882372379303, 'Val/mean hd95_metric': 4.854396343231201} +Epoch [3449/4000] Training [1/16] Loss: 0.00232 +Epoch [3449/4000] Training [2/16] Loss: 0.00256 +Epoch [3449/4000] Training [3/16] Loss: 0.00256 +Epoch [3449/4000] Training [4/16] Loss: 0.00247 +Epoch [3449/4000] Training [5/16] Loss: 0.00600 +Epoch [3449/4000] Training [6/16] Loss: 0.00205 +Epoch [3449/4000] Training [7/16] Loss: 0.00255 +Epoch [3449/4000] Training [8/16] Loss: 0.00308 +Epoch [3449/4000] Training [9/16] Loss: 0.00242 +Epoch [3449/4000] Training [10/16] Loss: 0.00215 +Epoch [3449/4000] Training [11/16] Loss: 0.00328 +Epoch [3449/4000] Training [12/16] Loss: 0.00239 +Epoch [3449/4000] Training [13/16] Loss: 0.00195 +Epoch [3449/4000] Training [14/16] Loss: 0.00261 +Epoch [3449/4000] Training [15/16] Loss: 0.00283 +Epoch [3449/4000] Training [16/16] Loss: 0.00193 +Epoch [3449/4000] Training metric {'Train/mean dice_metric': 0.9986174702644348, 'Train/mean miou_metric': 0.9969654083251953, 'Train/mean f1': 0.9936997890472412, 'Train/mean precision': 0.9891301393508911, 'Train/mean recall': 0.9983118176460266, 'Train/mean hd95_metric': 0.5902198553085327} +Epoch [3449/4000] Validation [1/4] Loss: 0.47585 focal_loss 0.40680 dice_loss 0.06905 +Epoch [3449/4000] Validation [2/4] Loss: 0.47279 focal_loss 0.36292 dice_loss 0.10987 +Epoch [3449/4000] Validation [3/4] Loss: 0.25504 focal_loss 0.19959 dice_loss 0.05545 +Epoch [3449/4000] Validation [4/4] Loss: 0.26453 focal_loss 0.18350 dice_loss 0.08102 +Epoch [3449/4000] Validation metric {'Val/mean dice_metric': 0.974144458770752, 'Val/mean miou_metric': 0.9605371356010437, 'Val/mean f1': 0.9766815900802612, 'Val/mean precision': 0.9745616912841797, 'Val/mean recall': 0.9788108468055725, 'Val/mean hd95_metric': 4.810513019561768} +Cheakpoint... +Epoch [3449/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974144458770752, 'Val/mean miou_metric': 0.9605371356010437, 'Val/mean f1': 0.9766815900802612, 'Val/mean precision': 0.9745616912841797, 'Val/mean recall': 0.9788108468055725, 'Val/mean hd95_metric': 4.810513019561768} +Epoch [3450/4000] Training [1/16] Loss: 0.00187 +Epoch [3450/4000] Training [2/16] Loss: 0.00212 +Epoch [3450/4000] Training [3/16] Loss: 0.00223 +Epoch [3450/4000] Training [4/16] Loss: 0.00280 +Epoch [3450/4000] Training [5/16] Loss: 0.00241 +Epoch [3450/4000] Training [6/16] Loss: 0.00194 +Epoch [3450/4000] Training [7/16] Loss: 0.00232 +Epoch [3450/4000] Training [8/16] Loss: 0.00306 +Epoch [3450/4000] Training [9/16] Loss: 0.00318 +Epoch [3450/4000] Training [10/16] Loss: 0.00259 +Epoch [3450/4000] Training [11/16] Loss: 0.00218 +Epoch [3450/4000] Training [12/16] Loss: 0.00262 +Epoch [3450/4000] Training [13/16] Loss: 0.00176 +Epoch [3450/4000] Training [14/16] Loss: 0.00211 +Epoch [3450/4000] Training [15/16] Loss: 0.00263 +Epoch [3450/4000] Training [16/16] Loss: 0.00239 +Epoch [3450/4000] Training metric {'Train/mean dice_metric': 0.9987344741821289, 'Train/mean miou_metric': 0.9971473217010498, 'Train/mean f1': 0.992854118347168, 'Train/mean precision': 0.9875414967536926, 'Train/mean recall': 0.998224139213562, 'Train/mean hd95_metric': 0.5693634748458862} +Epoch [3450/4000] Validation [1/4] Loss: 0.36479 focal_loss 0.30255 dice_loss 0.06224 +Epoch [3450/4000] Validation [2/4] Loss: 0.46247 focal_loss 0.35419 dice_loss 0.10828 +Epoch [3450/4000] Validation [3/4] Loss: 0.54002 focal_loss 0.44345 dice_loss 0.09657 +Epoch [3450/4000] Validation [4/4] Loss: 0.46709 focal_loss 0.35932 dice_loss 0.10778 +Epoch [3450/4000] Validation metric {'Val/mean dice_metric': 0.9742733240127563, 'Val/mean miou_metric': 0.9598277807235718, 'Val/mean f1': 0.9755012392997742, 'Val/mean precision': 0.9721894264221191, 'Val/mean recall': 0.9788357019424438, 'Val/mean hd95_metric': 5.347579479217529} +Cheakpoint... +Epoch [3450/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742733240127563, 'Val/mean miou_metric': 0.9598277807235718, 'Val/mean f1': 0.9755012392997742, 'Val/mean precision': 0.9721894264221191, 'Val/mean recall': 0.9788357019424438, 'Val/mean hd95_metric': 5.347579479217529} +Epoch [3451/4000] Training [1/16] Loss: 0.00239 +Epoch [3451/4000] Training [2/16] Loss: 0.00268 +Epoch [3451/4000] Training [3/16] Loss: 0.00348 +Epoch [3451/4000] Training [4/16] Loss: 0.00279 +Epoch [3451/4000] Training [5/16] Loss: 0.00177 +Epoch [3451/4000] Training [6/16] Loss: 0.00239 +Epoch [3451/4000] Training [7/16] Loss: 0.00283 +Epoch [3451/4000] Training [8/16] Loss: 0.00266 +Epoch [3451/4000] Training [9/16] Loss: 0.00312 +Epoch [3451/4000] Training [10/16] Loss: 0.00231 +Epoch [3451/4000] Training [11/16] Loss: 0.00301 +Epoch [3451/4000] Training [12/16] Loss: 0.00195 +Epoch [3451/4000] Training [13/16] Loss: 0.00241 +Epoch [3451/4000] Training [14/16] Loss: 0.00258 +Epoch [3451/4000] Training [15/16] Loss: 0.00243 +Epoch [3451/4000] Training [16/16] Loss: 0.00208 +Epoch [3451/4000] Training metric {'Train/mean dice_metric': 0.9987589716911316, 'Train/mean miou_metric': 0.9972373247146606, 'Train/mean f1': 0.9936906099319458, 'Train/mean precision': 0.9890571236610413, 'Train/mean recall': 0.9983676671981812, 'Train/mean hd95_metric': 0.5702701807022095} +Epoch [3451/4000] Validation [1/4] Loss: 0.42585 focal_loss 0.36060 dice_loss 0.06525 +Epoch [3451/4000] Validation [2/4] Loss: 0.91727 focal_loss 0.72821 dice_loss 0.18906 +Epoch [3451/4000] Validation [3/4] Loss: 0.51128 focal_loss 0.42097 dice_loss 0.09031 +Epoch [3451/4000] Validation [4/4] Loss: 0.38893 focal_loss 0.28452 dice_loss 0.10441 +Epoch [3451/4000] Validation metric {'Val/mean dice_metric': 0.9729593992233276, 'Val/mean miou_metric': 0.9590753316879272, 'Val/mean f1': 0.9762075543403625, 'Val/mean precision': 0.9745627045631409, 'Val/mean recall': 0.9778577089309692, 'Val/mean hd95_metric': 5.078964710235596} +Cheakpoint... +Epoch [3451/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729593992233276, 'Val/mean miou_metric': 0.9590753316879272, 'Val/mean f1': 0.9762075543403625, 'Val/mean precision': 0.9745627045631409, 'Val/mean recall': 0.9778577089309692, 'Val/mean hd95_metric': 5.078964710235596} +Epoch [3452/4000] Training [1/16] Loss: 0.00206 +Epoch [3452/4000] Training [2/16] Loss: 0.00280 +Epoch [3452/4000] Training [3/16] Loss: 0.00177 +Epoch [3452/4000] Training [4/16] Loss: 0.00221 +Epoch [3452/4000] Training [5/16] Loss: 0.00212 +Epoch [3452/4000] Training [6/16] Loss: 0.00361 +Epoch [3452/4000] Training [7/16] Loss: 0.00179 +Epoch [3452/4000] Training [8/16] Loss: 0.00204 +Epoch [3452/4000] Training [9/16] Loss: 0.00204 +Epoch [3452/4000] Training [10/16] Loss: 0.00268 +Epoch [3452/4000] Training [11/16] Loss: 0.00196 +Epoch [3452/4000] Training [12/16] Loss: 0.00321 +Epoch [3452/4000] Training [13/16] Loss: 0.00191 +Epoch [3452/4000] Training [14/16] Loss: 0.00217 +Epoch [3452/4000] Training [15/16] Loss: 0.00228 +Epoch [3452/4000] Training [16/16] Loss: 0.00274 +Epoch [3452/4000] Training metric {'Train/mean dice_metric': 0.9987812042236328, 'Train/mean miou_metric': 0.9972785711288452, 'Train/mean f1': 0.9937683343887329, 'Train/mean precision': 0.989208996295929, 'Train/mean recall': 0.9983699321746826, 'Train/mean hd95_metric': 0.5557615756988525} +Epoch [3452/4000] Validation [1/4] Loss: 0.43851 focal_loss 0.37130 dice_loss 0.06721 +Epoch [3452/4000] Validation [2/4] Loss: 0.49703 focal_loss 0.38222 dice_loss 0.11481 +Epoch [3452/4000] Validation [3/4] Loss: 0.52490 focal_loss 0.42908 dice_loss 0.09582 +Epoch [3452/4000] Validation [4/4] Loss: 0.37643 focal_loss 0.27348 dice_loss 0.10295 +Epoch [3452/4000] Validation metric {'Val/mean dice_metric': 0.973980724811554, 'Val/mean miou_metric': 0.9598417282104492, 'Val/mean f1': 0.9765341877937317, 'Val/mean precision': 0.9739327430725098, 'Val/mean recall': 0.9791496396064758, 'Val/mean hd95_metric': 5.126059055328369} +Cheakpoint... +Epoch [3452/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973980724811554, 'Val/mean miou_metric': 0.9598417282104492, 'Val/mean f1': 0.9765341877937317, 'Val/mean precision': 0.9739327430725098, 'Val/mean recall': 0.9791496396064758, 'Val/mean hd95_metric': 5.126059055328369} +Epoch [3453/4000] Training [1/16] Loss: 0.00176 +Epoch [3453/4000] Training [2/16] Loss: 0.00345 +Epoch [3453/4000] Training [3/16] Loss: 0.00191 +Epoch [3453/4000] Training [4/16] Loss: 0.00228 +Epoch [3453/4000] Training [5/16] Loss: 0.00169 +Epoch [3453/4000] Training [6/16] Loss: 0.00315 +Epoch [3453/4000] Training [7/16] Loss: 0.00198 +Epoch [3453/4000] Training [8/16] Loss: 0.00203 +Epoch [3453/4000] Training [9/16] Loss: 0.00315 +Epoch [3453/4000] Training [10/16] Loss: 0.00284 +Epoch [3453/4000] Training [11/16] Loss: 0.00417 +Epoch [3453/4000] Training [12/16] Loss: 0.00242 +Epoch [3453/4000] Training [13/16] Loss: 0.00445 +Epoch [3453/4000] Training [14/16] Loss: 0.00271 +Epoch [3453/4000] Training [15/16] Loss: 0.00225 +Epoch [3453/4000] Training [16/16] Loss: 0.00312 +Epoch [3453/4000] Training metric {'Train/mean dice_metric': 0.9985344409942627, 'Train/mean miou_metric': 0.9967921376228333, 'Train/mean f1': 0.993506133556366, 'Train/mean precision': 0.988874077796936, 'Train/mean recall': 0.9981818199157715, 'Train/mean hd95_metric': 0.603318452835083} +Epoch [3453/4000] Validation [1/4] Loss: 0.36608 focal_loss 0.30363 dice_loss 0.06245 +Epoch [3453/4000] Validation [2/4] Loss: 0.49283 focal_loss 0.37815 dice_loss 0.11468 +Epoch [3453/4000] Validation [3/4] Loss: 0.54716 focal_loss 0.45056 dice_loss 0.09660 +Epoch [3453/4000] Validation [4/4] Loss: 0.29799 focal_loss 0.21399 dice_loss 0.08399 +Epoch [3453/4000] Validation metric {'Val/mean dice_metric': 0.9750527143478394, 'Val/mean miou_metric': 0.9608078002929688, 'Val/mean f1': 0.9765879511833191, 'Val/mean precision': 0.9743977189064026, 'Val/mean recall': 0.9787878394126892, 'Val/mean hd95_metric': 4.802916526794434} +Cheakpoint... +Epoch [3453/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750527143478394, 'Val/mean miou_metric': 0.9608078002929688, 'Val/mean f1': 0.9765879511833191, 'Val/mean precision': 0.9743977189064026, 'Val/mean recall': 0.9787878394126892, 'Val/mean hd95_metric': 4.802916526794434} +Epoch [3454/4000] Training [1/16] Loss: 0.00257 +Epoch [3454/4000] Training [2/16] Loss: 0.00215 +Epoch [3454/4000] Training [3/16] Loss: 0.00277 +Epoch [3454/4000] Training [4/16] Loss: 0.00334 +Epoch [3454/4000] Training [5/16] Loss: 0.00230 +Epoch [3454/4000] Training [6/16] Loss: 0.00216 +Epoch [3454/4000] Training [7/16] Loss: 0.00227 +Epoch [3454/4000] Training [8/16] Loss: 0.00337 +Epoch [3454/4000] Training [9/16] Loss: 0.00253 +Epoch [3454/4000] Training [10/16] Loss: 0.00261 +Epoch [3454/4000] Training [11/16] Loss: 0.00203 +Epoch [3454/4000] Training [12/16] Loss: 0.00213 +Epoch [3454/4000] Training [13/16] Loss: 0.00175 +Epoch [3454/4000] Training [14/16] Loss: 0.00168 +Epoch [3454/4000] Training [15/16] Loss: 0.00216 +Epoch [3454/4000] Training [16/16] Loss: 0.00251 +Epoch [3454/4000] Training metric {'Train/mean dice_metric': 0.9987572431564331, 'Train/mean miou_metric': 0.9972161054611206, 'Train/mean f1': 0.9931766390800476, 'Train/mean precision': 0.9880677461624146, 'Train/mean recall': 0.9983385801315308, 'Train/mean hd95_metric': 0.5364257097244263} +Epoch [3454/4000] Validation [1/4] Loss: 0.44042 focal_loss 0.37187 dice_loss 0.06855 +Epoch [3454/4000] Validation [2/4] Loss: 0.48682 focal_loss 0.37588 dice_loss 0.11094 +Epoch [3454/4000] Validation [3/4] Loss: 0.52300 focal_loss 0.42424 dice_loss 0.09876 +Epoch [3454/4000] Validation [4/4] Loss: 0.44172 focal_loss 0.33136 dice_loss 0.11036 +Epoch [3454/4000] Validation metric {'Val/mean dice_metric': 0.9736869931221008, 'Val/mean miou_metric': 0.9590662717819214, 'Val/mean f1': 0.9754807949066162, 'Val/mean precision': 0.9735444188117981, 'Val/mean recall': 0.9774248600006104, 'Val/mean hd95_metric': 5.0218424797058105} +Cheakpoint... +Epoch [3454/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736869931221008, 'Val/mean miou_metric': 0.9590662717819214, 'Val/mean f1': 0.9754807949066162, 'Val/mean precision': 0.9735444188117981, 'Val/mean recall': 0.9774248600006104, 'Val/mean hd95_metric': 5.0218424797058105} +Epoch [3455/4000] Training [1/16] Loss: 0.00326 +Epoch [3455/4000] Training [2/16] Loss: 0.00243 +Epoch [3455/4000] Training [3/16] Loss: 0.00200 +Epoch [3455/4000] Training [4/16] Loss: 0.00252 +Epoch [3455/4000] Training [5/16] Loss: 0.00195 +Epoch [3455/4000] Training [6/16] Loss: 0.00242 +Epoch [3455/4000] Training [7/16] Loss: 0.00347 +Epoch [3455/4000] Training [8/16] Loss: 0.00245 +Epoch [3455/4000] Training [9/16] Loss: 0.00293 +Epoch [3455/4000] Training [10/16] Loss: 0.00212 +Epoch [3455/4000] Training [11/16] Loss: 0.00249 +Epoch [3455/4000] Training [12/16] Loss: 0.00307 +Epoch [3455/4000] Training [13/16] Loss: 0.00268 +Epoch [3455/4000] Training [14/16] Loss: 0.00244 +Epoch [3455/4000] Training [15/16] Loss: 0.00371 +Epoch [3455/4000] Training [16/16] Loss: 0.00247 +Epoch [3455/4000] Training metric {'Train/mean dice_metric': 0.9986211061477661, 'Train/mean miou_metric': 0.9969579577445984, 'Train/mean f1': 0.9937799572944641, 'Train/mean precision': 0.9892957806587219, 'Train/mean recall': 0.9983049035072327, 'Train/mean hd95_metric': 0.587287425994873} +Epoch [3455/4000] Validation [1/4] Loss: 0.43727 focal_loss 0.37237 dice_loss 0.06490 +Epoch [3455/4000] Validation [2/4] Loss: 0.75953 focal_loss 0.54133 dice_loss 0.21820 +Epoch [3455/4000] Validation [3/4] Loss: 0.51517 focal_loss 0.42343 dice_loss 0.09174 +Epoch [3455/4000] Validation [4/4] Loss: 0.34241 focal_loss 0.25269 dice_loss 0.08972 +Epoch [3455/4000] Validation metric {'Val/mean dice_metric': 0.9721193313598633, 'Val/mean miou_metric': 0.958126425743103, 'Val/mean f1': 0.9764165878295898, 'Val/mean precision': 0.9743098616600037, 'Val/mean recall': 0.9785324335098267, 'Val/mean hd95_metric': 5.365663528442383} +Cheakpoint... +Epoch [3455/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721193313598633, 'Val/mean miou_metric': 0.958126425743103, 'Val/mean f1': 0.9764165878295898, 'Val/mean precision': 0.9743098616600037, 'Val/mean recall': 0.9785324335098267, 'Val/mean hd95_metric': 5.365663528442383} +Epoch [3456/4000] Training [1/16] Loss: 0.00189 +Epoch [3456/4000] Training [2/16] Loss: 0.00200 +Epoch [3456/4000] Training [3/16] Loss: 0.00212 +Epoch [3456/4000] Training [4/16] Loss: 0.00383 +Epoch [3456/4000] Training [5/16] Loss: 0.00339 +Epoch [3456/4000] Training [6/16] Loss: 0.00177 +Epoch [3456/4000] Training [7/16] Loss: 0.00256 +Epoch [3456/4000] Training [8/16] Loss: 0.00289 +Epoch [3456/4000] Training [9/16] Loss: 0.00225 +Epoch [3456/4000] Training [10/16] Loss: 0.00194 +Epoch [3456/4000] Training [11/16] Loss: 0.00222 +Epoch [3456/4000] Training [12/16] Loss: 0.00227 +Epoch [3456/4000] Training [13/16] Loss: 0.00251 +Epoch [3456/4000] Training [14/16] Loss: 0.00356 +Epoch [3456/4000] Training [15/16] Loss: 0.00304 +Epoch [3456/4000] Training [16/16] Loss: 0.00239 +Epoch [3456/4000] Training metric {'Train/mean dice_metric': 0.9986752271652222, 'Train/mean miou_metric': 0.9970777034759521, 'Train/mean f1': 0.9937042593955994, 'Train/mean precision': 0.9891462922096252, 'Train/mean recall': 0.9983044266700745, 'Train/mean hd95_metric': 0.5745670795440674} +Epoch [3456/4000] Validation [1/4] Loss: 0.39738 focal_loss 0.33315 dice_loss 0.06423 +Epoch [3456/4000] Validation [2/4] Loss: 0.92070 focal_loss 0.73217 dice_loss 0.18853 +Epoch [3456/4000] Validation [3/4] Loss: 0.27500 focal_loss 0.21192 dice_loss 0.06308 +Epoch [3456/4000] Validation [4/4] Loss: 0.32885 focal_loss 0.23718 dice_loss 0.09167 +Epoch [3456/4000] Validation metric {'Val/mean dice_metric': 0.9726483225822449, 'Val/mean miou_metric': 0.9590028524398804, 'Val/mean f1': 0.9762766361236572, 'Val/mean precision': 0.9752153158187866, 'Val/mean recall': 0.9773402810096741, 'Val/mean hd95_metric': 5.411053657531738} +Cheakpoint... +Epoch [3456/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726483225822449, 'Val/mean miou_metric': 0.9590028524398804, 'Val/mean f1': 0.9762766361236572, 'Val/mean precision': 0.9752153158187866, 'Val/mean recall': 0.9773402810096741, 'Val/mean hd95_metric': 5.411053657531738} +Epoch [3457/4000] Training [1/16] Loss: 0.00215 +Epoch [3457/4000] Training [2/16] Loss: 0.00270 +Epoch [3457/4000] Training [3/16] Loss: 0.00205 +Epoch [3457/4000] Training [4/16] Loss: 0.00272 +Epoch [3457/4000] Training [5/16] Loss: 0.00446 +Epoch [3457/4000] Training [6/16] Loss: 0.00277 +Epoch [3457/4000] Training [7/16] Loss: 0.00336 +Epoch [3457/4000] Training [8/16] Loss: 0.00262 +Epoch [3457/4000] Training [9/16] Loss: 0.00232 +Epoch [3457/4000] Training [10/16] Loss: 0.00360 +Epoch [3457/4000] Training [11/16] Loss: 0.00167 +Epoch [3457/4000] Training [12/16] Loss: 0.00336 +Epoch [3457/4000] Training [13/16] Loss: 0.00190 +Epoch [3457/4000] Training [14/16] Loss: 0.00283 +Epoch [3457/4000] Training [15/16] Loss: 0.00161 +Epoch [3457/4000] Training [16/16] Loss: 0.00250 +Epoch [3457/4000] Training metric {'Train/mean dice_metric': 0.9986064434051514, 'Train/mean miou_metric': 0.9969427585601807, 'Train/mean f1': 0.9937270879745483, 'Train/mean precision': 0.9892111420631409, 'Train/mean recall': 0.9982844591140747, 'Train/mean hd95_metric': 0.5824495553970337} +Epoch [3457/4000] Validation [1/4] Loss: 0.41874 focal_loss 0.35471 dice_loss 0.06404 +Epoch [3457/4000] Validation [2/4] Loss: 1.23576 focal_loss 1.02303 dice_loss 0.21273 +Epoch [3457/4000] Validation [3/4] Loss: 0.55953 focal_loss 0.46412 dice_loss 0.09541 +Epoch [3457/4000] Validation [4/4] Loss: 0.57078 focal_loss 0.44444 dice_loss 0.12634 +Epoch [3457/4000] Validation metric {'Val/mean dice_metric': 0.9723914861679077, 'Val/mean miou_metric': 0.9584637880325317, 'Val/mean f1': 0.9753546118736267, 'Val/mean precision': 0.9731341600418091, 'Val/mean recall': 0.9775852560997009, 'Val/mean hd95_metric': 5.228790760040283} +Cheakpoint... +Epoch [3457/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723914861679077, 'Val/mean miou_metric': 0.9584637880325317, 'Val/mean f1': 0.9753546118736267, 'Val/mean precision': 0.9731341600418091, 'Val/mean recall': 0.9775852560997009, 'Val/mean hd95_metric': 5.228790760040283} +Epoch [3458/4000] Training [1/16] Loss: 0.00353 +Epoch [3458/4000] Training [2/16] Loss: 0.00244 +Epoch [3458/4000] Training [3/16] Loss: 0.00156 +Epoch [3458/4000] Training [4/16] Loss: 0.00313 +Epoch [3458/4000] Training [5/16] Loss: 0.00200 +Epoch [3458/4000] Training [6/16] Loss: 0.00182 +Epoch [3458/4000] Training [7/16] Loss: 0.00250 +Epoch [3458/4000] Training [8/16] Loss: 0.00191 +Epoch [3458/4000] Training [9/16] Loss: 0.00215 +Epoch [3458/4000] Training [10/16] Loss: 0.00231 +Epoch [3458/4000] Training [11/16] Loss: 0.00264 +Epoch [3458/4000] Training [12/16] Loss: 0.00229 +Epoch [3458/4000] Training [13/16] Loss: 0.00366 +Epoch [3458/4000] Training [14/16] Loss: 0.00255 +Epoch [3458/4000] Training [15/16] Loss: 0.00423 +Epoch [3458/4000] Training [16/16] Loss: 0.00294 +Epoch [3458/4000] Training metric {'Train/mean dice_metric': 0.998590886592865, 'Train/mean miou_metric': 0.9968892335891724, 'Train/mean f1': 0.9935675859451294, 'Train/mean precision': 0.9888789653778076, 'Train/mean recall': 0.9983008503913879, 'Train/mean hd95_metric': 0.5611603260040283} +Epoch [3458/4000] Validation [1/4] Loss: 0.45484 focal_loss 0.38515 dice_loss 0.06969 +Epoch [3458/4000] Validation [2/4] Loss: 0.48719 focal_loss 0.37599 dice_loss 0.11119 +Epoch [3458/4000] Validation [3/4] Loss: 0.29600 focal_loss 0.23449 dice_loss 0.06151 +Epoch [3458/4000] Validation [4/4] Loss: 0.33294 focal_loss 0.23921 dice_loss 0.09373 +Epoch [3458/4000] Validation metric {'Val/mean dice_metric': 0.9745265245437622, 'Val/mean miou_metric': 0.9597593545913696, 'Val/mean f1': 0.9762486219406128, 'Val/mean precision': 0.9749047160148621, 'Val/mean recall': 0.9775964021682739, 'Val/mean hd95_metric': 4.9736809730529785} +Cheakpoint... +Epoch [3458/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745265245437622, 'Val/mean miou_metric': 0.9597593545913696, 'Val/mean f1': 0.9762486219406128, 'Val/mean precision': 0.9749047160148621, 'Val/mean recall': 0.9775964021682739, 'Val/mean hd95_metric': 4.9736809730529785} +Epoch [3459/4000] Training [1/16] Loss: 0.00311 +Epoch [3459/4000] Training [2/16] Loss: 0.00448 +Epoch [3459/4000] Training [3/16] Loss: 0.00208 +Epoch [3459/4000] Training [4/16] Loss: 0.00215 +Epoch [3459/4000] Training [5/16] Loss: 0.00272 +Epoch [3459/4000] Training [6/16] Loss: 0.00299 +Epoch [3459/4000] Training [7/16] Loss: 0.00260 +Epoch [3459/4000] Training [8/16] Loss: 0.00196 +Epoch [3459/4000] Training [9/16] Loss: 0.00241 +Epoch [3459/4000] Training [10/16] Loss: 0.00294 +Epoch [3459/4000] Training [11/16] Loss: 0.00245 +Epoch [3459/4000] Training [12/16] Loss: 0.00298 +Epoch [3459/4000] Training [13/16] Loss: 0.00218 +Epoch [3459/4000] Training [14/16] Loss: 0.00333 +Epoch [3459/4000] Training [15/16] Loss: 0.00207 +Epoch [3459/4000] Training [16/16] Loss: 0.00212 +Epoch [3459/4000] Training metric {'Train/mean dice_metric': 0.9987156987190247, 'Train/mean miou_metric': 0.9971560835838318, 'Train/mean f1': 0.9937599301338196, 'Train/mean precision': 0.9892224669456482, 'Train/mean recall': 0.9983392357826233, 'Train/mean hd95_metric': 0.5798826813697815} +Epoch [3459/4000] Validation [1/4] Loss: 0.38697 focal_loss 0.32277 dice_loss 0.06420 +Epoch [3459/4000] Validation [2/4] Loss: 1.24560 focal_loss 0.94856 dice_loss 0.29704 +Epoch [3459/4000] Validation [3/4] Loss: 0.53475 focal_loss 0.43763 dice_loss 0.09712 +Epoch [3459/4000] Validation [4/4] Loss: 0.45196 focal_loss 0.34412 dice_loss 0.10784 +Epoch [3459/4000] Validation metric {'Val/mean dice_metric': 0.9720595479011536, 'Val/mean miou_metric': 0.9582059979438782, 'Val/mean f1': 0.9758477807044983, 'Val/mean precision': 0.9744060039520264, 'Val/mean recall': 0.977293848991394, 'Val/mean hd95_metric': 4.937980651855469} +Cheakpoint... +Epoch [3459/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9720595479011536, 'Val/mean miou_metric': 0.9582059979438782, 'Val/mean f1': 0.9758477807044983, 'Val/mean precision': 0.9744060039520264, 'Val/mean recall': 0.977293848991394, 'Val/mean hd95_metric': 4.937980651855469} +Epoch [3460/4000] Training [1/16] Loss: 0.00312 +Epoch [3460/4000] Training [2/16] Loss: 0.00216 +Epoch [3460/4000] Training [3/16] Loss: 0.00200 +Epoch [3460/4000] Training [4/16] Loss: 0.00168 +Epoch [3460/4000] Training [5/16] Loss: 0.00178 +Epoch [3460/4000] Training [6/16] Loss: 0.00220 +Epoch [3460/4000] Training [7/16] Loss: 0.00268 +Epoch [3460/4000] Training [8/16] Loss: 0.00209 +Epoch [3460/4000] Training [9/16] Loss: 0.00217 +Epoch [3460/4000] Training [10/16] Loss: 0.00202 +Epoch [3460/4000] Training [11/16] Loss: 0.00199 +Epoch [3460/4000] Training [12/16] Loss: 0.00289 +Epoch [3460/4000] Training [13/16] Loss: 0.00137 +Epoch [3460/4000] Training [14/16] Loss: 0.00304 +Epoch [3460/4000] Training [15/16] Loss: 0.00175 +Epoch [3460/4000] Training [16/16] Loss: 0.00198 +Epoch [3460/4000] Training metric {'Train/mean dice_metric': 0.9988154768943787, 'Train/mean miou_metric': 0.9973390102386475, 'Train/mean f1': 0.99363774061203, 'Train/mean precision': 0.9889556765556335, 'Train/mean recall': 0.998364269733429, 'Train/mean hd95_metric': 0.513992428779602} +Epoch [3460/4000] Validation [1/4] Loss: 0.39774 focal_loss 0.33341 dice_loss 0.06433 +Epoch [3460/4000] Validation [2/4] Loss: 0.47994 focal_loss 0.36827 dice_loss 0.11168 +Epoch [3460/4000] Validation [3/4] Loss: 0.57277 focal_loss 0.47244 dice_loss 0.10033 +Epoch [3460/4000] Validation [4/4] Loss: 0.34428 focal_loss 0.25745 dice_loss 0.08683 +Epoch [3460/4000] Validation metric {'Val/mean dice_metric': 0.9746626019477844, 'Val/mean miou_metric': 0.9605482220649719, 'Val/mean f1': 0.9761756658554077, 'Val/mean precision': 0.973800539970398, 'Val/mean recall': 0.9785624146461487, 'Val/mean hd95_metric': 5.057796478271484} +Cheakpoint... +Epoch [3460/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746626019477844, 'Val/mean miou_metric': 0.9605482220649719, 'Val/mean f1': 0.9761756658554077, 'Val/mean precision': 0.973800539970398, 'Val/mean recall': 0.9785624146461487, 'Val/mean hd95_metric': 5.057796478271484} +Epoch [3461/4000] Training [1/16] Loss: 0.00270 +Epoch [3461/4000] Training [2/16] Loss: 0.00189 +Epoch [3461/4000] Training [3/16] Loss: 0.00312 +Epoch [3461/4000] Training [4/16] Loss: 0.00218 +Epoch [3461/4000] Training [5/16] Loss: 0.00261 +Epoch [3461/4000] Training [6/16] Loss: 0.00305 +Epoch [3461/4000] Training [7/16] Loss: 0.00235 +Epoch [3461/4000] Training [8/16] Loss: 0.00167 +Epoch [3461/4000] Training [9/16] Loss: 0.00258 +Epoch [3461/4000] Training [10/16] Loss: 0.00266 +Epoch [3461/4000] Training [11/16] Loss: 0.00411 +Epoch [3461/4000] Training [12/16] Loss: 0.00233 +Epoch [3461/4000] Training [13/16] Loss: 0.00249 +Epoch [3461/4000] Training [14/16] Loss: 0.00272 +Epoch [3461/4000] Training [15/16] Loss: 0.00195 +Epoch [3461/4000] Training [16/16] Loss: 0.00338 +Epoch [3461/4000] Training metric {'Train/mean dice_metric': 0.9986065626144409, 'Train/mean miou_metric': 0.9969428777694702, 'Train/mean f1': 0.9937251806259155, 'Train/mean precision': 0.9891683459281921, 'Train/mean recall': 0.9983242154121399, 'Train/mean hd95_metric': 0.5357697606086731} +Epoch [3461/4000] Validation [1/4] Loss: 0.35466 focal_loss 0.29712 dice_loss 0.05754 +Epoch [3461/4000] Validation [2/4] Loss: 0.93813 focal_loss 0.74664 dice_loss 0.19149 +Epoch [3461/4000] Validation [3/4] Loss: 0.52246 focal_loss 0.42836 dice_loss 0.09410 +Epoch [3461/4000] Validation [4/4] Loss: 0.37894 focal_loss 0.27449 dice_loss 0.10445 +Epoch [3461/4000] Validation metric {'Val/mean dice_metric': 0.9726694226264954, 'Val/mean miou_metric': 0.9589968919754028, 'Val/mean f1': 0.9759859442710876, 'Val/mean precision': 0.9734355211257935, 'Val/mean recall': 0.9785497784614563, 'Val/mean hd95_metric': 5.64323616027832} +Cheakpoint... +Epoch [3461/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726694226264954, 'Val/mean miou_metric': 0.9589968919754028, 'Val/mean f1': 0.9759859442710876, 'Val/mean precision': 0.9734355211257935, 'Val/mean recall': 0.9785497784614563, 'Val/mean hd95_metric': 5.64323616027832} +Epoch [3462/4000] Training [1/16] Loss: 0.00219 +Epoch [3462/4000] Training [2/16] Loss: 0.00320 +Epoch [3462/4000] Training [3/16] Loss: 0.00270 +Epoch [3462/4000] Training [4/16] Loss: 0.00288 +Epoch [3462/4000] Training [5/16] Loss: 0.00216 +Epoch [3462/4000] Training [6/16] Loss: 0.00366 +Epoch [3462/4000] Training [7/16] Loss: 0.00243 +Epoch [3462/4000] Training [8/16] Loss: 0.00253 +Epoch [3462/4000] Training [9/16] Loss: 0.00465 +Epoch [3462/4000] Training [10/16] Loss: 0.00296 +Epoch [3462/4000] Training [11/16] Loss: 0.00267 +Epoch [3462/4000] Training [12/16] Loss: 0.00276 +Epoch [3462/4000] Training [13/16] Loss: 0.00168 +Epoch [3462/4000] Training [14/16] Loss: 0.00347 +Epoch [3462/4000] Training [15/16] Loss: 0.00270 +Epoch [3462/4000] Training [16/16] Loss: 0.00260 +Epoch [3462/4000] Training metric {'Train/mean dice_metric': 0.9985777139663696, 'Train/mean miou_metric': 0.9968714714050293, 'Train/mean f1': 0.9935799241065979, 'Train/mean precision': 0.9889806509017944, 'Train/mean recall': 0.9982221722602844, 'Train/mean hd95_metric': 0.5799380540847778} +Epoch [3462/4000] Validation [1/4] Loss: 0.40054 focal_loss 0.33765 dice_loss 0.06289 +Epoch [3462/4000] Validation [2/4] Loss: 0.44880 focal_loss 0.33983 dice_loss 0.10896 +Epoch [3462/4000] Validation [3/4] Loss: 0.54441 focal_loss 0.44923 dice_loss 0.09518 +Epoch [3462/4000] Validation [4/4] Loss: 0.35693 focal_loss 0.26741 dice_loss 0.08952 +Epoch [3462/4000] Validation metric {'Val/mean dice_metric': 0.9746427536010742, 'Val/mean miou_metric': 0.9605663418769836, 'Val/mean f1': 0.9766901731491089, 'Val/mean precision': 0.9746288061141968, 'Val/mean recall': 0.9787601828575134, 'Val/mean hd95_metric': 4.722554683685303} +Cheakpoint... +Epoch [3462/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746427536010742, 'Val/mean miou_metric': 0.9605663418769836, 'Val/mean f1': 0.9766901731491089, 'Val/mean precision': 0.9746288061141968, 'Val/mean recall': 0.9787601828575134, 'Val/mean hd95_metric': 4.722554683685303} +Epoch [3463/4000] Training [1/16] Loss: 0.00208 +Epoch [3463/4000] Training [2/16] Loss: 0.00180 +Epoch [3463/4000] Training [3/16] Loss: 0.00349 +Epoch [3463/4000] Training [4/16] Loss: 0.00246 +Epoch [3463/4000] Training [5/16] Loss: 0.00232 +Epoch [3463/4000] Training [6/16] Loss: 0.00159 +Epoch [3463/4000] Training [7/16] Loss: 0.00194 +Epoch [3463/4000] Training [8/16] Loss: 0.00289 +Epoch [3463/4000] Training [9/16] Loss: 0.00198 +Epoch [3463/4000] Training [10/16] Loss: 0.00231 +Epoch [3463/4000] Training [11/16] Loss: 0.00196 +Epoch [3463/4000] Training [12/16] Loss: 0.00182 +Epoch [3463/4000] Training [13/16] Loss: 0.00304 +Epoch [3463/4000] Training [14/16] Loss: 0.00267 +Epoch [3463/4000] Training [15/16] Loss: 0.00292 +Epoch [3463/4000] Training [16/16] Loss: 0.00188 +Epoch [3463/4000] Training metric {'Train/mean dice_metric': 0.9987382888793945, 'Train/mean miou_metric': 0.9971925020217896, 'Train/mean f1': 0.993514358997345, 'Train/mean precision': 0.988775908946991, 'Train/mean recall': 0.9982984662055969, 'Train/mean hd95_metric': 0.54612135887146} +Epoch [3463/4000] Validation [1/4] Loss: 0.35474 focal_loss 0.29327 dice_loss 0.06147 +Epoch [3463/4000] Validation [2/4] Loss: 0.47086 focal_loss 0.36014 dice_loss 0.11072 +Epoch [3463/4000] Validation [3/4] Loss: 0.31096 focal_loss 0.24751 dice_loss 0.06345 +Epoch [3463/4000] Validation [4/4] Loss: 0.38935 focal_loss 0.28994 dice_loss 0.09941 +Epoch [3463/4000] Validation metric {'Val/mean dice_metric': 0.9749886393547058, 'Val/mean miou_metric': 0.960757851600647, 'Val/mean f1': 0.9760777950286865, 'Val/mean precision': 0.9740753769874573, 'Val/mean recall': 0.9780886173248291, 'Val/mean hd95_metric': 5.107352256774902} +Cheakpoint... +Epoch [3463/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749886393547058, 'Val/mean miou_metric': 0.960757851600647, 'Val/mean f1': 0.9760777950286865, 'Val/mean precision': 0.9740753769874573, 'Val/mean recall': 0.9780886173248291, 'Val/mean hd95_metric': 5.107352256774902} +Epoch [3464/4000] Training [1/16] Loss: 0.00220 +Epoch [3464/4000] Training [2/16] Loss: 0.00287 +Epoch [3464/4000] Training [3/16] Loss: 0.00141 +Epoch [3464/4000] Training [4/16] Loss: 0.00232 +Epoch [3464/4000] Training [5/16] Loss: 0.00230 +Epoch [3464/4000] Training [6/16] Loss: 0.00318 +Epoch [3464/4000] Training [7/16] Loss: 0.00255 +Epoch [3464/4000] Training [8/16] Loss: 0.00337 +Epoch [3464/4000] Training [9/16] Loss: 0.00189 +Epoch [3464/4000] Training [10/16] Loss: 0.00244 +Epoch [3464/4000] Training [11/16] Loss: 0.00222 +Epoch [3464/4000] Training [12/16] Loss: 0.00269 +Epoch [3464/4000] Training [13/16] Loss: 0.00428 +Epoch [3464/4000] Training [14/16] Loss: 0.00282 +Epoch [3464/4000] Training [15/16] Loss: 0.00229 +Epoch [3464/4000] Training [16/16] Loss: 0.00238 +Epoch [3464/4000] Training metric {'Train/mean dice_metric': 0.9987401962280273, 'Train/mean miou_metric': 0.9972096681594849, 'Train/mean f1': 0.9938575029373169, 'Train/mean precision': 0.9893730878829956, 'Train/mean recall': 0.9983828067779541, 'Train/mean hd95_metric': 0.5524269342422485} +Epoch [3464/4000] Validation [1/4] Loss: 0.37202 focal_loss 0.30959 dice_loss 0.06243 +Epoch [3464/4000] Validation [2/4] Loss: 0.47935 focal_loss 0.36859 dice_loss 0.11076 +Epoch [3464/4000] Validation [3/4] Loss: 0.53203 focal_loss 0.43201 dice_loss 0.10002 +Epoch [3464/4000] Validation [4/4] Loss: 0.35312 focal_loss 0.26415 dice_loss 0.08897 +Epoch [3464/4000] Validation metric {'Val/mean dice_metric': 0.9746028780937195, 'Val/mean miou_metric': 0.960620105266571, 'Val/mean f1': 0.9765810370445251, 'Val/mean precision': 0.9745499491691589, 'Val/mean recall': 0.9786205291748047, 'Val/mean hd95_metric': 4.63603401184082} +Cheakpoint... +Epoch [3464/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746028780937195, 'Val/mean miou_metric': 0.960620105266571, 'Val/mean f1': 0.9765810370445251, 'Val/mean precision': 0.9745499491691589, 'Val/mean recall': 0.9786205291748047, 'Val/mean hd95_metric': 4.63603401184082} +Epoch [3465/4000] Training [1/16] Loss: 0.00204 +Epoch [3465/4000] Training [2/16] Loss: 0.00212 +Epoch [3465/4000] Training [3/16] Loss: 0.00299 +Epoch [3465/4000] Training [4/16] Loss: 0.00265 +Epoch [3465/4000] Training [5/16] Loss: 0.00249 +Epoch [3465/4000] Training [6/16] Loss: 0.00222 +Epoch [3465/4000] Training [7/16] Loss: 0.00298 +Epoch [3465/4000] Training [8/16] Loss: 0.00359 +Epoch [3465/4000] Training [9/16] Loss: 0.00206 +Epoch [3465/4000] Training [10/16] Loss: 0.00220 +Epoch [3465/4000] Training [11/16] Loss: 0.00499 +Epoch [3465/4000] Training [12/16] Loss: 0.00194 +Epoch [3465/4000] Training [13/16] Loss: 0.00182 +Epoch [3465/4000] Training [14/16] Loss: 0.00215 +Epoch [3465/4000] Training [15/16] Loss: 0.00288 +Epoch [3465/4000] Training [16/16] Loss: 0.00192 +Epoch [3465/4000] Training metric {'Train/mean dice_metric': 0.9986186623573303, 'Train/mean miou_metric': 0.9969666004180908, 'Train/mean f1': 0.9937413334846497, 'Train/mean precision': 0.9892764091491699, 'Train/mean recall': 0.9982467293739319, 'Train/mean hd95_metric': 0.5796030163764954} +Epoch [3465/4000] Validation [1/4] Loss: 0.40929 focal_loss 0.34660 dice_loss 0.06269 +Epoch [3465/4000] Validation [2/4] Loss: 0.51078 focal_loss 0.38547 dice_loss 0.12530 +Epoch [3465/4000] Validation [3/4] Loss: 0.52366 focal_loss 0.43145 dice_loss 0.09220 +Epoch [3465/4000] Validation [4/4] Loss: 0.57910 focal_loss 0.44920 dice_loss 0.12991 +Epoch [3465/4000] Validation metric {'Val/mean dice_metric': 0.9738553166389465, 'Val/mean miou_metric': 0.9595716595649719, 'Val/mean f1': 0.9767473936080933, 'Val/mean precision': 0.9748533964157104, 'Val/mean recall': 0.9786487817764282, 'Val/mean hd95_metric': 4.760087013244629} +Cheakpoint... +Epoch [3465/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738553166389465, 'Val/mean miou_metric': 0.9595716595649719, 'Val/mean f1': 0.9767473936080933, 'Val/mean precision': 0.9748533964157104, 'Val/mean recall': 0.9786487817764282, 'Val/mean hd95_metric': 4.760087013244629} +Epoch [3466/4000] Training [1/16] Loss: 0.00242 +Epoch [3466/4000] Training [2/16] Loss: 0.00328 +Epoch [3466/4000] Training [3/16] Loss: 0.00287 +Epoch [3466/4000] Training [4/16] Loss: 0.00214 +Epoch [3466/4000] Training [5/16] Loss: 0.00246 +Epoch [3466/4000] Training [6/16] Loss: 0.00317 +Epoch [3466/4000] Training [7/16] Loss: 0.00191 +Epoch [3466/4000] Training [8/16] Loss: 0.00270 +Epoch [3466/4000] Training [9/16] Loss: 0.00202 +Epoch [3466/4000] Training [10/16] Loss: 0.00229 +Epoch [3466/4000] Training [11/16] Loss: 0.00340 +Epoch [3466/4000] Training [12/16] Loss: 0.00273 +Epoch [3466/4000] Training [13/16] Loss: 0.00257 +Epoch [3466/4000] Training [14/16] Loss: 0.00180 +Epoch [3466/4000] Training [15/16] Loss: 0.00312 +Epoch [3466/4000] Training [16/16] Loss: 0.00248 +Epoch [3466/4000] Training metric {'Train/mean dice_metric': 0.9984999895095825, 'Train/mean miou_metric': 0.9967314600944519, 'Train/mean f1': 0.9936437010765076, 'Train/mean precision': 0.9891601204872131, 'Train/mean recall': 0.9981680512428284, 'Train/mean hd95_metric': 0.6794498562812805} +Epoch [3466/4000] Validation [1/4] Loss: 0.49180 focal_loss 0.42478 dice_loss 0.06702 +Epoch [3466/4000] Validation [2/4] Loss: 0.72715 focal_loss 0.54603 dice_loss 0.18112 +Epoch [3466/4000] Validation [3/4] Loss: 0.52209 focal_loss 0.42125 dice_loss 0.10083 +Epoch [3466/4000] Validation [4/4] Loss: 0.37516 focal_loss 0.27139 dice_loss 0.10377 +Epoch [3466/4000] Validation metric {'Val/mean dice_metric': 0.973289966583252, 'Val/mean miou_metric': 0.9590320587158203, 'Val/mean f1': 0.976050615310669, 'Val/mean precision': 0.9737614393234253, 'Val/mean recall': 0.9783504605293274, 'Val/mean hd95_metric': 5.155555248260498} +Cheakpoint... +Epoch [3466/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973289966583252, 'Val/mean miou_metric': 0.9590320587158203, 'Val/mean f1': 0.976050615310669, 'Val/mean precision': 0.9737614393234253, 'Val/mean recall': 0.9783504605293274, 'Val/mean hd95_metric': 5.155555248260498} +Epoch [3467/4000] Training [1/16] Loss: 0.00209 +Epoch [3467/4000] Training [2/16] Loss: 0.00332 +Epoch [3467/4000] Training [3/16] Loss: 0.00199 +Epoch [3467/4000] Training [4/16] Loss: 0.00222 +Epoch [3467/4000] Training [5/16] Loss: 0.00177 +Epoch [3467/4000] Training [6/16] Loss: 0.00258 +Epoch [3467/4000] Training [7/16] Loss: 0.00213 +Epoch [3467/4000] Training [8/16] Loss: 0.00292 +Epoch [3467/4000] Training [9/16] Loss: 0.00183 +Epoch [3467/4000] Training [10/16] Loss: 0.00182 +Epoch [3467/4000] Training [11/16] Loss: 0.00251 +Epoch [3467/4000] Training [12/16] Loss: 0.00188 +Epoch [3467/4000] Training [13/16] Loss: 0.00231 +Epoch [3467/4000] Training [14/16] Loss: 0.00333 +Epoch [3467/4000] Training [15/16] Loss: 0.00253 +Epoch [3467/4000] Training [16/16] Loss: 0.00232 +Epoch [3467/4000] Training metric {'Train/mean dice_metric': 0.9987977743148804, 'Train/mean miou_metric': 0.9973227977752686, 'Train/mean f1': 0.993865966796875, 'Train/mean precision': 0.9893438816070557, 'Train/mean recall': 0.9984295964241028, 'Train/mean hd95_metric': 0.5121369957923889} +Epoch [3467/4000] Validation [1/4] Loss: 0.44579 focal_loss 0.37996 dice_loss 0.06583 +Epoch [3467/4000] Validation [2/4] Loss: 1.09453 focal_loss 0.82555 dice_loss 0.26898 +Epoch [3467/4000] Validation [3/4] Loss: 0.30970 focal_loss 0.24430 dice_loss 0.06541 +Epoch [3467/4000] Validation [4/4] Loss: 0.39264 focal_loss 0.28973 dice_loss 0.10291 +Epoch [3467/4000] Validation metric {'Val/mean dice_metric': 0.9724345207214355, 'Val/mean miou_metric': 0.9583156704902649, 'Val/mean f1': 0.9753954410552979, 'Val/mean precision': 0.974298894405365, 'Val/mean recall': 0.9764943718910217, 'Val/mean hd95_metric': 5.185554504394531} +Cheakpoint... +Epoch [3467/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724345207214355, 'Val/mean miou_metric': 0.9583156704902649, 'Val/mean f1': 0.9753954410552979, 'Val/mean precision': 0.974298894405365, 'Val/mean recall': 0.9764943718910217, 'Val/mean hd95_metric': 5.185554504394531} +Epoch [3468/4000] Training [1/16] Loss: 0.00201 +Epoch [3468/4000] Training [2/16] Loss: 0.00288 +Epoch [3468/4000] Training [3/16] Loss: 0.00210 +Epoch [3468/4000] Training [4/16] Loss: 0.00222 +Epoch [3468/4000] Training [5/16] Loss: 0.00214 +Epoch [3468/4000] Training [6/16] Loss: 0.00210 +Epoch [3468/4000] Training [7/16] Loss: 0.00355 +Epoch [3468/4000] Training [8/16] Loss: 0.00246 +Epoch [3468/4000] Training [9/16] Loss: 0.00301 +Epoch [3468/4000] Training [10/16] Loss: 0.00244 +Epoch [3468/4000] Training [11/16] Loss: 0.00405 +Epoch [3468/4000] Training [12/16] Loss: 0.00236 +Epoch [3468/4000] Training [13/16] Loss: 0.01161 +Epoch [3468/4000] Training [14/16] Loss: 0.00219 +Epoch [3468/4000] Training [15/16] Loss: 0.00218 +Epoch [3468/4000] Training [16/16] Loss: 0.00253 +Epoch [3468/4000] Training metric {'Train/mean dice_metric': 0.9985671043395996, 'Train/mean miou_metric': 0.9968636631965637, 'Train/mean f1': 0.9935885667800903, 'Train/mean precision': 0.9889605641365051, 'Train/mean recall': 0.9982601404190063, 'Train/mean hd95_metric': 0.6281406879425049} +Epoch [3468/4000] Validation [1/4] Loss: 0.41422 focal_loss 0.34599 dice_loss 0.06823 +Epoch [3468/4000] Validation [2/4] Loss: 0.51683 focal_loss 0.39210 dice_loss 0.12473 +Epoch [3468/4000] Validation [3/4] Loss: 0.52253 focal_loss 0.43476 dice_loss 0.08777 +Epoch [3468/4000] Validation [4/4] Loss: 0.35585 focal_loss 0.25921 dice_loss 0.09664 +Epoch [3468/4000] Validation metric {'Val/mean dice_metric': 0.9736846685409546, 'Val/mean miou_metric': 0.9596042633056641, 'Val/mean f1': 0.9758914113044739, 'Val/mean precision': 0.9739245176315308, 'Val/mean recall': 0.9778663516044617, 'Val/mean hd95_metric': 4.9684367179870605} +Cheakpoint... +Epoch [3468/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736846685409546, 'Val/mean miou_metric': 0.9596042633056641, 'Val/mean f1': 0.9758914113044739, 'Val/mean precision': 0.9739245176315308, 'Val/mean recall': 0.9778663516044617, 'Val/mean hd95_metric': 4.9684367179870605} +Epoch [3469/4000] Training [1/16] Loss: 0.00237 +Epoch [3469/4000] Training [2/16] Loss: 0.00226 +Epoch [3469/4000] Training [3/16] Loss: 0.00280 +Epoch [3469/4000] Training [4/16] Loss: 0.00278 +Epoch [3469/4000] Training [5/16] Loss: 0.00210 +Epoch [3469/4000] Training [6/16] Loss: 0.00278 +Epoch [3469/4000] Training [7/16] Loss: 0.00252 +Epoch [3469/4000] Training [8/16] Loss: 0.00275 +Epoch [3469/4000] Training [9/16] Loss: 0.00251 +Epoch [3469/4000] Training [10/16] Loss: 0.00152 +Epoch [3469/4000] Training [11/16] Loss: 0.00386 +Epoch [3469/4000] Training [12/16] Loss: 0.00173 +Epoch [3469/4000] Training [13/16] Loss: 0.00204 +Epoch [3469/4000] Training [14/16] Loss: 0.00299 +Epoch [3469/4000] Training [15/16] Loss: 0.00323 +Epoch [3469/4000] Training [16/16] Loss: 0.00283 +Epoch [3469/4000] Training metric {'Train/mean dice_metric': 0.9986947774887085, 'Train/mean miou_metric': 0.9971176385879517, 'Train/mean f1': 0.9937707781791687, 'Train/mean precision': 0.9893004298210144, 'Train/mean recall': 0.998281717300415, 'Train/mean hd95_metric': 0.5845267176628113} +Epoch [3469/4000] Validation [1/4] Loss: 0.43062 focal_loss 0.36433 dice_loss 0.06628 +Epoch [3469/4000] Validation [2/4] Loss: 0.48117 focal_loss 0.37012 dice_loss 0.11106 +Epoch [3469/4000] Validation [3/4] Loss: 0.55337 focal_loss 0.45838 dice_loss 0.09498 +Epoch [3469/4000] Validation [4/4] Loss: 0.34611 focal_loss 0.25883 dice_loss 0.08728 +Epoch [3469/4000] Validation metric {'Val/mean dice_metric': 0.9736995697021484, 'Val/mean miou_metric': 0.9595537185668945, 'Val/mean f1': 0.9760549068450928, 'Val/mean precision': 0.9745652675628662, 'Val/mean recall': 0.9775490164756775, 'Val/mean hd95_metric': 5.324244499206543} +Cheakpoint... +Epoch [3469/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736995697021484, 'Val/mean miou_metric': 0.9595537185668945, 'Val/mean f1': 0.9760549068450928, 'Val/mean precision': 0.9745652675628662, 'Val/mean recall': 0.9775490164756775, 'Val/mean hd95_metric': 5.324244499206543} +Epoch [3470/4000] Training [1/16] Loss: 0.00240 +Epoch [3470/4000] Training [2/16] Loss: 0.00294 +Epoch [3470/4000] Training [3/16] Loss: 0.00333 +Epoch [3470/4000] Training [4/16] Loss: 0.00199 +Epoch [3470/4000] Training [5/16] Loss: 0.00229 +Epoch [3470/4000] Training [6/16] Loss: 0.00295 +Epoch [3470/4000] Training [7/16] Loss: 0.00307 +Epoch [3470/4000] Training [8/16] Loss: 0.00184 +Epoch [3470/4000] Training [9/16] Loss: 0.00202 +Epoch [3470/4000] Training [10/16] Loss: 0.00214 +Epoch [3470/4000] Training [11/16] Loss: 0.00284 +Epoch [3470/4000] Training [12/16] Loss: 0.00260 +Epoch [3470/4000] Training [13/16] Loss: 0.00322 +Epoch [3470/4000] Training [14/16] Loss: 0.00181 +Epoch [3470/4000] Training [15/16] Loss: 0.00222 +Epoch [3470/4000] Training [16/16] Loss: 0.00364 +Epoch [3470/4000] Training metric {'Train/mean dice_metric': 0.998798668384552, 'Train/mean miou_metric': 0.9973257780075073, 'Train/mean f1': 0.9938169121742249, 'Train/mean precision': 0.9892681241035461, 'Train/mean recall': 0.998407781124115, 'Train/mean hd95_metric': 0.5507111549377441} +Epoch [3470/4000] Validation [1/4] Loss: 0.40997 focal_loss 0.34596 dice_loss 0.06401 +Epoch [3470/4000] Validation [2/4] Loss: 0.46778 focal_loss 0.35989 dice_loss 0.10789 +Epoch [3470/4000] Validation [3/4] Loss: 0.52224 focal_loss 0.43190 dice_loss 0.09035 +Epoch [3470/4000] Validation [4/4] Loss: 0.47367 focal_loss 0.36648 dice_loss 0.10719 +Epoch [3470/4000] Validation metric {'Val/mean dice_metric': 0.975113034248352, 'Val/mean miou_metric': 0.9611574411392212, 'Val/mean f1': 0.9766691327095032, 'Val/mean precision': 0.9745004773139954, 'Val/mean recall': 0.9788475036621094, 'Val/mean hd95_metric': 4.6718621253967285} +Cheakpoint... +Epoch [3470/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975113034248352, 'Val/mean miou_metric': 0.9611574411392212, 'Val/mean f1': 0.9766691327095032, 'Val/mean precision': 0.9745004773139954, 'Val/mean recall': 0.9788475036621094, 'Val/mean hd95_metric': 4.6718621253967285} +Epoch [3471/4000] Training [1/16] Loss: 0.00300 +Epoch [3471/4000] Training [2/16] Loss: 0.00312 +Epoch [3471/4000] Training [3/16] Loss: 0.00265 +Epoch [3471/4000] Training [4/16] Loss: 0.00229 +Epoch [3471/4000] Training [5/16] Loss: 0.00204 +Epoch [3471/4000] Training [6/16] Loss: 0.00237 +Epoch [3471/4000] Training [7/16] Loss: 0.00373 +Epoch [3471/4000] Training [8/16] Loss: 0.00198 +Epoch [3471/4000] Training [9/16] Loss: 0.00240 +Epoch [3471/4000] Training [10/16] Loss: 0.00214 +Epoch [3471/4000] Training [11/16] Loss: 0.00220 +Epoch [3471/4000] Training [12/16] Loss: 0.00244 +Epoch [3471/4000] Training [13/16] Loss: 0.00252 +Epoch [3471/4000] Training [14/16] Loss: 0.00231 +Epoch [3471/4000] Training [15/16] Loss: 0.00213 +Epoch [3471/4000] Training [16/16] Loss: 0.00197 +Epoch [3471/4000] Training metric {'Train/mean dice_metric': 0.9987511038780212, 'Train/mean miou_metric': 0.9972265958786011, 'Train/mean f1': 0.9937947392463684, 'Train/mean precision': 0.989264726638794, 'Train/mean recall': 0.9983664155006409, 'Train/mean hd95_metric': 0.586453378200531} +Epoch [3471/4000] Validation [1/4] Loss: 0.35478 focal_loss 0.29351 dice_loss 0.06127 +Epoch [3471/4000] Validation [2/4] Loss: 0.46849 focal_loss 0.35652 dice_loss 0.11197 +Epoch [3471/4000] Validation [3/4] Loss: 0.55906 focal_loss 0.46527 dice_loss 0.09379 +Epoch [3471/4000] Validation [4/4] Loss: 0.33444 focal_loss 0.24334 dice_loss 0.09111 +Epoch [3471/4000] Validation metric {'Val/mean dice_metric': 0.9743545651435852, 'Val/mean miou_metric': 0.9601051211357117, 'Val/mean f1': 0.9761282801628113, 'Val/mean precision': 0.9739786982536316, 'Val/mean recall': 0.9782872796058655, 'Val/mean hd95_metric': 5.159219264984131} +Cheakpoint... +Epoch [3471/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743545651435852, 'Val/mean miou_metric': 0.9601051211357117, 'Val/mean f1': 0.9761282801628113, 'Val/mean precision': 0.9739786982536316, 'Val/mean recall': 0.9782872796058655, 'Val/mean hd95_metric': 5.159219264984131} +Epoch [3472/4000] Training [1/16] Loss: 0.00210 +Epoch [3472/4000] Training [2/16] Loss: 0.00362 +Epoch [3472/4000] Training [3/16] Loss: 0.00321 +Epoch [3472/4000] Training [4/16] Loss: 0.00300 +Epoch [3472/4000] Training [5/16] Loss: 0.00225 +Epoch [3472/4000] Training [6/16] Loss: 0.00263 +Epoch [3472/4000] Training [7/16] Loss: 0.00293 +Epoch [3472/4000] Training [8/16] Loss: 0.00212 +Epoch [3472/4000] Training [9/16] Loss: 0.00199 +Epoch [3472/4000] Training [10/16] Loss: 0.00215 +Epoch [3472/4000] Training [11/16] Loss: 0.00305 +Epoch [3472/4000] Training [12/16] Loss: 0.00290 +Epoch [3472/4000] Training [13/16] Loss: 0.00212 +Epoch [3472/4000] Training [14/16] Loss: 0.00280 +Epoch [3472/4000] Training [15/16] Loss: 0.00350 +Epoch [3472/4000] Training [16/16] Loss: 0.00237 +Epoch [3472/4000] Training metric {'Train/mean dice_metric': 0.9987070560455322, 'Train/mean miou_metric': 0.9971222877502441, 'Train/mean f1': 0.9933164119720459, 'Train/mean precision': 0.9884122014045715, 'Train/mean recall': 0.9982696175575256, 'Train/mean hd95_metric': 0.562332272529602} +Epoch [3472/4000] Validation [1/4] Loss: 0.38025 focal_loss 0.31675 dice_loss 0.06350 +Epoch [3472/4000] Validation [2/4] Loss: 0.92554 focal_loss 0.73907 dice_loss 0.18648 +Epoch [3472/4000] Validation [3/4] Loss: 0.56596 focal_loss 0.46661 dice_loss 0.09935 +Epoch [3472/4000] Validation [4/4] Loss: 0.46498 focal_loss 0.35955 dice_loss 0.10543 +Epoch [3472/4000] Validation metric {'Val/mean dice_metric': 0.9731005430221558, 'Val/mean miou_metric': 0.9595815539360046, 'Val/mean f1': 0.9757830500602722, 'Val/mean precision': 0.9738367795944214, 'Val/mean recall': 0.9777370691299438, 'Val/mean hd95_metric': 5.506214141845703} +Cheakpoint... +Epoch [3472/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731005430221558, 'Val/mean miou_metric': 0.9595815539360046, 'Val/mean f1': 0.9757830500602722, 'Val/mean precision': 0.9738367795944214, 'Val/mean recall': 0.9777370691299438, 'Val/mean hd95_metric': 5.506214141845703} +Epoch [3473/4000] Training [1/16] Loss: 0.00198 +Epoch [3473/4000] Training [2/16] Loss: 0.00186 +Epoch [3473/4000] Training [3/16] Loss: 0.00187 +Epoch [3473/4000] Training [4/16] Loss: 0.00208 +Epoch [3473/4000] Training [5/16] Loss: 0.00197 +Epoch [3473/4000] Training [6/16] Loss: 0.00314 +Epoch [3473/4000] Training [7/16] Loss: 0.00186 +Epoch [3473/4000] Training [8/16] Loss: 0.00216 +Epoch [3473/4000] Training [9/16] Loss: 0.00212 +Epoch [3473/4000] Training [10/16] Loss: 0.00258 +Epoch [3473/4000] Training [11/16] Loss: 0.00286 +Epoch [3473/4000] Training [12/16] Loss: 0.00399 +Epoch [3473/4000] Training [13/16] Loss: 0.00255 +Epoch [3473/4000] Training [14/16] Loss: 0.00306 +Epoch [3473/4000] Training [15/16] Loss: 0.00283 +Epoch [3473/4000] Training [16/16] Loss: 0.00265 +Epoch [3473/4000] Training metric {'Train/mean dice_metric': 0.9986952543258667, 'Train/mean miou_metric': 0.9971158504486084, 'Train/mean f1': 0.9936601519584656, 'Train/mean precision': 0.9890660047531128, 'Train/mean recall': 0.9982972145080566, 'Train/mean hd95_metric': 0.5612858533859253} +Epoch [3473/4000] Validation [1/4] Loss: 0.53394 focal_loss 0.45603 dice_loss 0.07791 +Epoch [3473/4000] Validation [2/4] Loss: 0.72376 focal_loss 0.52707 dice_loss 0.19670 +Epoch [3473/4000] Validation [3/4] Loss: 0.57565 focal_loss 0.47529 dice_loss 0.10036 +Epoch [3473/4000] Validation [4/4] Loss: 0.35051 focal_loss 0.25179 dice_loss 0.09872 +Epoch [3473/4000] Validation metric {'Val/mean dice_metric': 0.972987174987793, 'Val/mean miou_metric': 0.958550751209259, 'Val/mean f1': 0.9753010272979736, 'Val/mean precision': 0.9729021191596985, 'Val/mean recall': 0.9777119159698486, 'Val/mean hd95_metric': 5.506798267364502} +Cheakpoint... +Epoch [3473/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972987174987793, 'Val/mean miou_metric': 0.958550751209259, 'Val/mean f1': 0.9753010272979736, 'Val/mean precision': 0.9729021191596985, 'Val/mean recall': 0.9777119159698486, 'Val/mean hd95_metric': 5.506798267364502} +Epoch [3474/4000] Training [1/16] Loss: 0.00205 +Epoch [3474/4000] Training [2/16] Loss: 0.00208 +Epoch [3474/4000] Training [3/16] Loss: 0.00244 +Epoch [3474/4000] Training [4/16] Loss: 0.00383 +Epoch [3474/4000] Training [5/16] Loss: 0.00254 +Epoch [3474/4000] Training [6/16] Loss: 0.00269 +Epoch [3474/4000] Training [7/16] Loss: 0.00253 +Epoch [3474/4000] Training [8/16] Loss: 0.00214 +Epoch [3474/4000] Training [9/16] Loss: 0.00231 +Epoch [3474/4000] Training [10/16] Loss: 0.00278 +Epoch [3474/4000] Training [11/16] Loss: 0.00227 +Epoch [3474/4000] Training [12/16] Loss: 0.00251 +Epoch [3474/4000] Training [13/16] Loss: 0.00221 +Epoch [3474/4000] Training [14/16] Loss: 0.00360 +Epoch [3474/4000] Training [15/16] Loss: 0.00146 +Epoch [3474/4000] Training [16/16] Loss: 0.00275 +Epoch [3474/4000] Training metric {'Train/mean dice_metric': 0.9988170266151428, 'Train/mean miou_metric': 0.9973576664924622, 'Train/mean f1': 0.9938481450080872, 'Train/mean precision': 0.9893066883087158, 'Train/mean recall': 0.9984314441680908, 'Train/mean hd95_metric': 0.5536684989929199} +Epoch [3474/4000] Validation [1/4] Loss: 0.43845 focal_loss 0.37283 dice_loss 0.06562 +Epoch [3474/4000] Validation [2/4] Loss: 0.48294 focal_loss 0.37108 dice_loss 0.11187 +Epoch [3474/4000] Validation [3/4] Loss: 0.54787 focal_loss 0.44651 dice_loss 0.10135 +Epoch [3474/4000] Validation [4/4] Loss: 0.34830 focal_loss 0.26167 dice_loss 0.08664 +Epoch [3474/4000] Validation metric {'Val/mean dice_metric': 0.9747209548950195, 'Val/mean miou_metric': 0.9605810046195984, 'Val/mean f1': 0.976426362991333, 'Val/mean precision': 0.9737306237220764, 'Val/mean recall': 0.9791370630264282, 'Val/mean hd95_metric': 5.062039852142334} +Cheakpoint... +Epoch [3474/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747209548950195, 'Val/mean miou_metric': 0.9605810046195984, 'Val/mean f1': 0.976426362991333, 'Val/mean precision': 0.9737306237220764, 'Val/mean recall': 0.9791370630264282, 'Val/mean hd95_metric': 5.062039852142334} +Epoch [3475/4000] Training [1/16] Loss: 0.00168 +Epoch [3475/4000] Training [2/16] Loss: 0.00330 +Epoch [3475/4000] Training [3/16] Loss: 0.00221 +Epoch [3475/4000] Training [4/16] Loss: 0.00302 +Epoch [3475/4000] Training [5/16] Loss: 0.00258 +Epoch [3475/4000] Training [6/16] Loss: 0.00236 +Epoch [3475/4000] Training [7/16] Loss: 0.00286 +Epoch [3475/4000] Training [8/16] Loss: 0.00262 +Epoch [3475/4000] Training [9/16] Loss: 0.00262 +Epoch [3475/4000] Training [10/16] Loss: 0.00300 +Epoch [3475/4000] Training [11/16] Loss: 0.00269 +Epoch [3475/4000] Training [12/16] Loss: 0.00255 +Epoch [3475/4000] Training [13/16] Loss: 0.00220 +Epoch [3475/4000] Training [14/16] Loss: 0.00193 +Epoch [3475/4000] Training [15/16] Loss: 0.00235 +Epoch [3475/4000] Training [16/16] Loss: 0.00219 +Epoch [3475/4000] Training metric {'Train/mean dice_metric': 0.9987609386444092, 'Train/mean miou_metric': 0.9972463250160217, 'Train/mean f1': 0.9937907457351685, 'Train/mean precision': 0.9892522096633911, 'Train/mean recall': 0.9983711242675781, 'Train/mean hd95_metric': 0.5832306146621704} +Epoch [3475/4000] Validation [1/4] Loss: 0.45206 focal_loss 0.38562 dice_loss 0.06644 +Epoch [3475/4000] Validation [2/4] Loss: 0.47995 focal_loss 0.36986 dice_loss 0.11010 +Epoch [3475/4000] Validation [3/4] Loss: 0.55212 focal_loss 0.45936 dice_loss 0.09276 +Epoch [3475/4000] Validation [4/4] Loss: 0.34880 focal_loss 0.25208 dice_loss 0.09672 +Epoch [3475/4000] Validation metric {'Val/mean dice_metric': 0.9750261306762695, 'Val/mean miou_metric': 0.9609792828559875, 'Val/mean f1': 0.976712703704834, 'Val/mean precision': 0.9740678668022156, 'Val/mean recall': 0.9793720841407776, 'Val/mean hd95_metric': 4.958922386169434} +Cheakpoint... +Epoch [3475/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750261306762695, 'Val/mean miou_metric': 0.9609792828559875, 'Val/mean f1': 0.976712703704834, 'Val/mean precision': 0.9740678668022156, 'Val/mean recall': 0.9793720841407776, 'Val/mean hd95_metric': 4.958922386169434} +Epoch [3476/4000] Training [1/16] Loss: 0.00180 +Epoch [3476/4000] Training [2/16] Loss: 0.00203 +Epoch [3476/4000] Training [3/16] Loss: 0.00368 +Epoch [3476/4000] Training [4/16] Loss: 0.00237 +Epoch [3476/4000] Training [5/16] Loss: 0.00378 +Epoch [3476/4000] Training [6/16] Loss: 0.00245 +Epoch [3476/4000] Training [7/16] Loss: 0.00248 +Epoch [3476/4000] Training [8/16] Loss: 0.00299 +Epoch [3476/4000] Training [9/16] Loss: 0.00261 +Epoch [3476/4000] Training [10/16] Loss: 0.00262 +Epoch [3476/4000] Training [11/16] Loss: 0.00342 +Epoch [3476/4000] Training [12/16] Loss: 0.00249 +Epoch [3476/4000] Training [13/16] Loss: 0.00246 +Epoch [3476/4000] Training [14/16] Loss: 0.00420 +Epoch [3476/4000] Training [15/16] Loss: 0.00153 +Epoch [3476/4000] Training [16/16] Loss: 0.00194 +Epoch [3476/4000] Training metric {'Train/mean dice_metric': 0.9985582828521729, 'Train/mean miou_metric': 0.996839165687561, 'Train/mean f1': 0.9935634136199951, 'Train/mean precision': 0.9889331459999084, 'Train/mean recall': 0.9982372522354126, 'Train/mean hd95_metric': 0.610016405582428} +Epoch [3476/4000] Validation [1/4] Loss: 0.40750 focal_loss 0.34587 dice_loss 0.06162 +Epoch [3476/4000] Validation [2/4] Loss: 0.46696 focal_loss 0.36019 dice_loss 0.10677 +Epoch [3476/4000] Validation [3/4] Loss: 0.54122 focal_loss 0.44520 dice_loss 0.09603 +Epoch [3476/4000] Validation [4/4] Loss: 0.33295 focal_loss 0.24753 dice_loss 0.08541 +Epoch [3476/4000] Validation metric {'Val/mean dice_metric': 0.9766381978988647, 'Val/mean miou_metric': 0.962211012840271, 'Val/mean f1': 0.9769375920295715, 'Val/mean precision': 0.9742109775543213, 'Val/mean recall': 0.9796794056892395, 'Val/mean hd95_metric': 4.737523078918457} +Cheakpoint... +Epoch [3476/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9766], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9766381978988647, 'Val/mean miou_metric': 0.962211012840271, 'Val/mean f1': 0.9769375920295715, 'Val/mean precision': 0.9742109775543213, 'Val/mean recall': 0.9796794056892395, 'Val/mean hd95_metric': 4.737523078918457} +Epoch [3477/4000] Training [1/16] Loss: 0.00328 +Epoch [3477/4000] Training [2/16] Loss: 0.00262 +Epoch [3477/4000] Training [3/16] Loss: 0.00227 +Epoch [3477/4000] Training [4/16] Loss: 0.00263 +Epoch [3477/4000] Training [5/16] Loss: 0.00166 +Epoch [3477/4000] Training [6/16] Loss: 0.00291 +Epoch [3477/4000] Training [7/16] Loss: 0.00299 +Epoch [3477/4000] Training [8/16] Loss: 0.00368 +Epoch [3477/4000] Training [9/16] Loss: 0.00337 +Epoch [3477/4000] Training [10/16] Loss: 0.00234 +Epoch [3477/4000] Training [11/16] Loss: 0.00180 +Epoch [3477/4000] Training [12/16] Loss: 0.00204 +Epoch [3477/4000] Training [13/16] Loss: 0.00340 +Epoch [3477/4000] Training [14/16] Loss: 0.00204 +Epoch [3477/4000] Training [15/16] Loss: 0.00177 +Epoch [3477/4000] Training [16/16] Loss: 0.00356 +Epoch [3477/4000] Training metric {'Train/mean dice_metric': 0.9985466599464417, 'Train/mean miou_metric': 0.9968059659004211, 'Train/mean f1': 0.9934141635894775, 'Train/mean precision': 0.9886894822120667, 'Train/mean recall': 0.9981842637062073, 'Train/mean hd95_metric': 0.5872889757156372} +Epoch [3477/4000] Validation [1/4] Loss: 0.44946 focal_loss 0.38706 dice_loss 0.06239 +Epoch [3477/4000] Validation [2/4] Loss: 0.49998 focal_loss 0.38852 dice_loss 0.11146 +Epoch [3477/4000] Validation [3/4] Loss: 0.27044 focal_loss 0.20937 dice_loss 0.06107 +Epoch [3477/4000] Validation [4/4] Loss: 0.28199 focal_loss 0.19918 dice_loss 0.08281 +Epoch [3477/4000] Validation metric {'Val/mean dice_metric': 0.9747272729873657, 'Val/mean miou_metric': 0.9608997106552124, 'Val/mean f1': 0.9763165712356567, 'Val/mean precision': 0.9740757942199707, 'Val/mean recall': 0.9785676002502441, 'Val/mean hd95_metric': 4.911064147949219} +Cheakpoint... +Epoch [3477/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747272729873657, 'Val/mean miou_metric': 0.9608997106552124, 'Val/mean f1': 0.9763165712356567, 'Val/mean precision': 0.9740757942199707, 'Val/mean recall': 0.9785676002502441, 'Val/mean hd95_metric': 4.911064147949219} +Epoch [3478/4000] Training [1/16] Loss: 0.00246 +Epoch [3478/4000] Training [2/16] Loss: 0.00212 +Epoch [3478/4000] Training [3/16] Loss: 0.00273 +Epoch [3478/4000] Training [4/16] Loss: 0.00273 +Epoch [3478/4000] Training [5/16] Loss: 0.00275 +Epoch [3478/4000] Training [6/16] Loss: 0.00228 +Epoch [3478/4000] Training [7/16] Loss: 0.00193 +Epoch [3478/4000] Training [8/16] Loss: 0.00239 +Epoch [3478/4000] Training [9/16] Loss: 0.00200 +Epoch [3478/4000] Training [10/16] Loss: 0.00236 +Epoch [3478/4000] Training [11/16] Loss: 0.00559 +Epoch [3478/4000] Training [12/16] Loss: 0.00410 +Epoch [3478/4000] Training [13/16] Loss: 0.00280 +Epoch [3478/4000] Training [14/16] Loss: 0.00200 +Epoch [3478/4000] Training [15/16] Loss: 0.00228 +Epoch [3478/4000] Training [16/16] Loss: 0.00356 +Epoch [3478/4000] Training metric {'Train/mean dice_metric': 0.9987303018569946, 'Train/mean miou_metric': 0.9971858263015747, 'Train/mean f1': 0.9937336444854736, 'Train/mean precision': 0.9891804456710815, 'Train/mean recall': 0.9983289837837219, 'Train/mean hd95_metric': 0.5337189435958862} +Epoch [3478/4000] Validation [1/4] Loss: 0.43829 focal_loss 0.37357 dice_loss 0.06472 +Epoch [3478/4000] Validation [2/4] Loss: 0.48518 focal_loss 0.37545 dice_loss 0.10973 +Epoch [3478/4000] Validation [3/4] Loss: 0.26685 focal_loss 0.20552 dice_loss 0.06133 +Epoch [3478/4000] Validation [4/4] Loss: 0.58682 focal_loss 0.45525 dice_loss 0.13157 +Epoch [3478/4000] Validation metric {'Val/mean dice_metric': 0.9749437570571899, 'Val/mean miou_metric': 0.9607380032539368, 'Val/mean f1': 0.9763796329498291, 'Val/mean precision': 0.9742560386657715, 'Val/mean recall': 0.9785124063491821, 'Val/mean hd95_metric': 5.050019264221191} +Cheakpoint... +Epoch [3478/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749437570571899, 'Val/mean miou_metric': 0.9607380032539368, 'Val/mean f1': 0.9763796329498291, 'Val/mean precision': 0.9742560386657715, 'Val/mean recall': 0.9785124063491821, 'Val/mean hd95_metric': 5.050019264221191} +Epoch [3479/4000] Training [1/16] Loss: 0.00240 +Epoch [3479/4000] Training [2/16] Loss: 0.00339 +Epoch [3479/4000] Training [3/16] Loss: 0.00269 +Epoch [3479/4000] Training [4/16] Loss: 0.00302 +Epoch [3479/4000] Training [5/16] Loss: 0.00181 +Epoch [3479/4000] Training [6/16] Loss: 0.00243 +Epoch [3479/4000] Training [7/16] Loss: 0.00298 +Epoch [3479/4000] Training [8/16] Loss: 0.00319 +Epoch [3479/4000] Training [9/16] Loss: 0.00327 +Epoch [3479/4000] Training [10/16] Loss: 0.00277 +Epoch [3479/4000] Training [11/16] Loss: 0.00286 +Epoch [3479/4000] Training [12/16] Loss: 0.00287 +Epoch [3479/4000] Training [13/16] Loss: 0.00220 +Epoch [3479/4000] Training [14/16] Loss: 0.00298 +Epoch [3479/4000] Training [15/16] Loss: 0.00229 +Epoch [3479/4000] Training [16/16] Loss: 0.00251 +Epoch [3479/4000] Training metric {'Train/mean dice_metric': 0.9986547827720642, 'Train/mean miou_metric': 0.9970362186431885, 'Train/mean f1': 0.9937126040458679, 'Train/mean precision': 0.9891783595085144, 'Train/mean recall': 0.9982885718345642, 'Train/mean hd95_metric': 0.5904572010040283} +Epoch [3479/4000] Validation [1/4] Loss: 0.41031 focal_loss 0.34536 dice_loss 0.06495 +Epoch [3479/4000] Validation [2/4] Loss: 0.58379 focal_loss 0.43880 dice_loss 0.14499 +Epoch [3479/4000] Validation [3/4] Loss: 0.56406 focal_loss 0.46765 dice_loss 0.09641 +Epoch [3479/4000] Validation [4/4] Loss: 0.36113 focal_loss 0.27190 dice_loss 0.08924 +Epoch [3479/4000] Validation metric {'Val/mean dice_metric': 0.9735828638076782, 'Val/mean miou_metric': 0.9590116739273071, 'Val/mean f1': 0.9760574102401733, 'Val/mean precision': 0.9741779565811157, 'Val/mean recall': 0.9779441952705383, 'Val/mean hd95_metric': 5.0711798667907715} +Cheakpoint... +Epoch [3479/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735828638076782, 'Val/mean miou_metric': 0.9590116739273071, 'Val/mean f1': 0.9760574102401733, 'Val/mean precision': 0.9741779565811157, 'Val/mean recall': 0.9779441952705383, 'Val/mean hd95_metric': 5.0711798667907715} +Epoch [3480/4000] Training [1/16] Loss: 0.00236 +Epoch [3480/4000] Training [2/16] Loss: 0.00188 +Epoch [3480/4000] Training [3/16] Loss: 0.00336 +Epoch [3480/4000] Training [4/16] Loss: 0.00244 +Epoch [3480/4000] Training [5/16] Loss: 0.00208 +Epoch [3480/4000] Training [6/16] Loss: 0.00197 +Epoch [3480/4000] Training [7/16] Loss: 0.00424 +Epoch [3480/4000] Training [8/16] Loss: 0.00246 +Epoch [3480/4000] Training [9/16] Loss: 0.00391 +Epoch [3480/4000] Training [10/16] Loss: 0.00296 +Epoch [3480/4000] Training [11/16] Loss: 0.00197 +Epoch [3480/4000] Training [12/16] Loss: 0.00282 +Epoch [3480/4000] Training [13/16] Loss: 0.00201 +Epoch [3480/4000] Training [14/16] Loss: 0.00293 +Epoch [3480/4000] Training [15/16] Loss: 0.00298 +Epoch [3480/4000] Training [16/16] Loss: 0.00202 +Epoch [3480/4000] Training metric {'Train/mean dice_metric': 0.998645544052124, 'Train/mean miou_metric': 0.9970148801803589, 'Train/mean f1': 0.9936206340789795, 'Train/mean precision': 0.9890198111534119, 'Train/mean recall': 0.9982644319534302, 'Train/mean hd95_metric': 0.5746369361877441} +Epoch [3480/4000] Validation [1/4] Loss: 0.39039 focal_loss 0.32601 dice_loss 0.06437 +Epoch [3480/4000] Validation [2/4] Loss: 0.58211 focal_loss 0.43958 dice_loss 0.14253 +Epoch [3480/4000] Validation [3/4] Loss: 0.56097 focal_loss 0.46535 dice_loss 0.09562 +Epoch [3480/4000] Validation [4/4] Loss: 0.35837 focal_loss 0.26667 dice_loss 0.09170 +Epoch [3480/4000] Validation metric {'Val/mean dice_metric': 0.9733618497848511, 'Val/mean miou_metric': 0.9590590596199036, 'Val/mean f1': 0.9754257798194885, 'Val/mean precision': 0.9727284908294678, 'Val/mean recall': 0.9781380295753479, 'Val/mean hd95_metric': 5.4238176345825195} +Cheakpoint... +Epoch [3480/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733618497848511, 'Val/mean miou_metric': 0.9590590596199036, 'Val/mean f1': 0.9754257798194885, 'Val/mean precision': 0.9727284908294678, 'Val/mean recall': 0.9781380295753479, 'Val/mean hd95_metric': 5.4238176345825195} +Epoch [3481/4000] Training [1/16] Loss: 0.00312 +Epoch [3481/4000] Training [2/16] Loss: 0.00287 +Epoch [3481/4000] Training [3/16] Loss: 0.00247 +Epoch [3481/4000] Training [4/16] Loss: 0.00379 +Epoch [3481/4000] Training [5/16] Loss: 0.00232 +Epoch [3481/4000] Training [6/16] Loss: 0.00228 +Epoch [3481/4000] Training [7/16] Loss: 0.00260 +Epoch [3481/4000] Training [8/16] Loss: 0.00312 +Epoch [3481/4000] Training [9/16] Loss: 0.00241 +Epoch [3481/4000] Training [10/16] Loss: 0.00229 +Epoch [3481/4000] Training [11/16] Loss: 0.00224 +Epoch [3481/4000] Training [12/16] Loss: 0.00328 +Epoch [3481/4000] Training [13/16] Loss: 0.00350 +Epoch [3481/4000] Training [14/16] Loss: 0.00168 +Epoch [3481/4000] Training [15/16] Loss: 0.00391 +Epoch [3481/4000] Training [16/16] Loss: 0.00253 +Epoch [3481/4000] Training metric {'Train/mean dice_metric': 0.9986081719398499, 'Train/mean miou_metric': 0.9969298839569092, 'Train/mean f1': 0.993523359298706, 'Train/mean precision': 0.9888580441474915, 'Train/mean recall': 0.998232901096344, 'Train/mean hd95_metric': 0.6354334950447083} +Epoch [3481/4000] Validation [1/4] Loss: 0.41440 focal_loss 0.34971 dice_loss 0.06469 +Epoch [3481/4000] Validation [2/4] Loss: 0.48664 focal_loss 0.37587 dice_loss 0.11077 +Epoch [3481/4000] Validation [3/4] Loss: 0.50823 focal_loss 0.42030 dice_loss 0.08793 +Epoch [3481/4000] Validation [4/4] Loss: 0.37517 focal_loss 0.27585 dice_loss 0.09932 +Epoch [3481/4000] Validation metric {'Val/mean dice_metric': 0.9737011194229126, 'Val/mean miou_metric': 0.9599262475967407, 'Val/mean f1': 0.9764155745506287, 'Val/mean precision': 0.9741964936256409, 'Val/mean recall': 0.9786447286605835, 'Val/mean hd95_metric': 4.596765518188477} +Cheakpoint... +Epoch [3481/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737011194229126, 'Val/mean miou_metric': 0.9599262475967407, 'Val/mean f1': 0.9764155745506287, 'Val/mean precision': 0.9741964936256409, 'Val/mean recall': 0.9786447286605835, 'Val/mean hd95_metric': 4.596765518188477} +Epoch [3482/4000] Training [1/16] Loss: 0.00201 +Epoch [3482/4000] Training [2/16] Loss: 0.00199 +Epoch [3482/4000] Training [3/16] Loss: 0.00246 +Epoch [3482/4000] Training [4/16] Loss: 0.00194 +Epoch [3482/4000] Training [5/16] Loss: 0.00256 +Epoch [3482/4000] Training [6/16] Loss: 0.00230 +Epoch [3482/4000] Training [7/16] Loss: 0.00278 +Epoch [3482/4000] Training [8/16] Loss: 0.00194 +Epoch [3482/4000] Training [9/16] Loss: 0.00203 +Epoch [3482/4000] Training [10/16] Loss: 0.00401 +Epoch [3482/4000] Training [11/16] Loss: 0.00203 +Epoch [3482/4000] Training [12/16] Loss: 0.00254 +Epoch [3482/4000] Training [13/16] Loss: 0.00230 +Epoch [3482/4000] Training [14/16] Loss: 0.00354 +Epoch [3482/4000] Training [15/16] Loss: 0.00167 +Epoch [3482/4000] Training [16/16] Loss: 0.00291 +Epoch [3482/4000] Training metric {'Train/mean dice_metric': 0.9987231492996216, 'Train/mean miou_metric': 0.9971637725830078, 'Train/mean f1': 0.9936746954917908, 'Train/mean precision': 0.9890034794807434, 'Train/mean recall': 0.998390257358551, 'Train/mean hd95_metric': 0.5526366233825684} +Epoch [3482/4000] Validation [1/4] Loss: 0.46665 focal_loss 0.39994 dice_loss 0.06671 +Epoch [3482/4000] Validation [2/4] Loss: 1.02595 focal_loss 0.80421 dice_loss 0.22174 +Epoch [3482/4000] Validation [3/4] Loss: 0.54659 focal_loss 0.44778 dice_loss 0.09880 +Epoch [3482/4000] Validation [4/4] Loss: 0.36282 focal_loss 0.26435 dice_loss 0.09847 +Epoch [3482/4000] Validation metric {'Val/mean dice_metric': 0.9726762771606445, 'Val/mean miou_metric': 0.9588934183120728, 'Val/mean f1': 0.9759874939918518, 'Val/mean precision': 0.9738986492156982, 'Val/mean recall': 0.9780853390693665, 'Val/mean hd95_metric': 5.119571208953857} +Cheakpoint... +Epoch [3482/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726762771606445, 'Val/mean miou_metric': 0.9588934183120728, 'Val/mean f1': 0.9759874939918518, 'Val/mean precision': 0.9738986492156982, 'Val/mean recall': 0.9780853390693665, 'Val/mean hd95_metric': 5.119571208953857} +Epoch [3483/4000] Training [1/16] Loss: 0.00409 +Epoch [3483/4000] Training [2/16] Loss: 0.00318 +Epoch [3483/4000] Training [3/16] Loss: 0.00330 +Epoch [3483/4000] Training [4/16] Loss: 0.00259 +Epoch [3483/4000] Training [5/16] Loss: 0.00192 +Epoch [3483/4000] Training [6/16] Loss: 0.00317 +Epoch [3483/4000] Training [7/16] Loss: 0.00281 +Epoch [3483/4000] Training [8/16] Loss: 0.00302 +Epoch [3483/4000] Training [9/16] Loss: 0.00299 +Epoch [3483/4000] Training [10/16] Loss: 0.00280 +Epoch [3483/4000] Training [11/16] Loss: 0.00193 +Epoch [3483/4000] Training [12/16] Loss: 0.00310 +Epoch [3483/4000] Training [13/16] Loss: 0.00139 +Epoch [3483/4000] Training [14/16] Loss: 0.00149 +Epoch [3483/4000] Training [15/16] Loss: 0.00204 +Epoch [3483/4000] Training [16/16] Loss: 0.00248 +Epoch [3483/4000] Training metric {'Train/mean dice_metric': 0.9986132383346558, 'Train/mean miou_metric': 0.996929407119751, 'Train/mean f1': 0.993129312992096, 'Train/mean precision': 0.9881216883659363, 'Train/mean recall': 0.9981878995895386, 'Train/mean hd95_metric': 0.6000003218650818} +Epoch [3483/4000] Validation [1/4] Loss: 0.41397 focal_loss 0.34896 dice_loss 0.06501 +Epoch [3483/4000] Validation [2/4] Loss: 0.56897 focal_loss 0.42566 dice_loss 0.14331 +Epoch [3483/4000] Validation [3/4] Loss: 0.28729 focal_loss 0.22554 dice_loss 0.06175 +Epoch [3483/4000] Validation [4/4] Loss: 0.35122 focal_loss 0.25993 dice_loss 0.09129 +Epoch [3483/4000] Validation metric {'Val/mean dice_metric': 0.9745985269546509, 'Val/mean miou_metric': 0.9602238535881042, 'Val/mean f1': 0.9760368466377258, 'Val/mean precision': 0.9732689261436462, 'Val/mean recall': 0.9788205027580261, 'Val/mean hd95_metric': 4.8120903968811035} +Cheakpoint... +Epoch [3483/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745985269546509, 'Val/mean miou_metric': 0.9602238535881042, 'Val/mean f1': 0.9760368466377258, 'Val/mean precision': 0.9732689261436462, 'Val/mean recall': 0.9788205027580261, 'Val/mean hd95_metric': 4.8120903968811035} +Epoch [3484/4000] Training [1/16] Loss: 0.00151 +Epoch [3484/4000] Training [2/16] Loss: 0.00358 +Epoch [3484/4000] Training [3/16] Loss: 0.00200 +Epoch [3484/4000] Training [4/16] Loss: 0.00263 +Epoch [3484/4000] Training [5/16] Loss: 0.00240 +Epoch [3484/4000] Training [6/16] Loss: 0.00182 +Epoch [3484/4000] Training [7/16] Loss: 0.00206 +Epoch [3484/4000] Training [8/16] Loss: 0.00209 +Epoch [3484/4000] Training [9/16] Loss: 0.00203 +Epoch [3484/4000] Training [10/16] Loss: 0.00201 +Epoch [3484/4000] Training [11/16] Loss: 0.00235 +Epoch [3484/4000] Training [12/16] Loss: 0.00200 +Epoch [3484/4000] Training [13/16] Loss: 0.00223 +Epoch [3484/4000] Training [14/16] Loss: 0.00404 +Epoch [3484/4000] Training [15/16] Loss: 0.00195 +Epoch [3484/4000] Training [16/16] Loss: 0.00225 +Epoch [3484/4000] Training metric {'Train/mean dice_metric': 0.9987573623657227, 'Train/mean miou_metric': 0.9972367286682129, 'Train/mean f1': 0.9937325716018677, 'Train/mean precision': 0.9891058206558228, 'Train/mean recall': 0.9984028339385986, 'Train/mean hd95_metric': 0.5475150942802429} +Epoch [3484/4000] Validation [1/4] Loss: 0.42074 focal_loss 0.35576 dice_loss 0.06498 +Epoch [3484/4000] Validation [2/4] Loss: 0.45858 focal_loss 0.35063 dice_loss 0.10795 +Epoch [3484/4000] Validation [3/4] Loss: 0.54409 focal_loss 0.44677 dice_loss 0.09732 +Epoch [3484/4000] Validation [4/4] Loss: 0.33790 focal_loss 0.24581 dice_loss 0.09210 +Epoch [3484/4000] Validation metric {'Val/mean dice_metric': 0.9744003415107727, 'Val/mean miou_metric': 0.9602044820785522, 'Val/mean f1': 0.9762415289878845, 'Val/mean precision': 0.9739723205566406, 'Val/mean recall': 0.9785211682319641, 'Val/mean hd95_metric': 4.640127658843994} +Cheakpoint... +Epoch [3484/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744003415107727, 'Val/mean miou_metric': 0.9602044820785522, 'Val/mean f1': 0.9762415289878845, 'Val/mean precision': 0.9739723205566406, 'Val/mean recall': 0.9785211682319641, 'Val/mean hd95_metric': 4.640127658843994} +Epoch [3485/4000] Training [1/16] Loss: 0.00183 +Epoch [3485/4000] Training [2/16] Loss: 0.00229 +Epoch [3485/4000] Training [3/16] Loss: 0.00338 +Epoch [3485/4000] Training [4/16] Loss: 0.00334 +Epoch [3485/4000] Training [5/16] Loss: 0.00295 +Epoch [3485/4000] Training [6/16] Loss: 0.00299 +Epoch [3485/4000] Training [7/16] Loss: 0.00208 +Epoch [3485/4000] Training [8/16] Loss: 0.00318 +Epoch [3485/4000] Training [9/16] Loss: 0.00262 +Epoch [3485/4000] Training [10/16] Loss: 0.00332 +Epoch [3485/4000] Training [11/16] Loss: 0.00360 +Epoch [3485/4000] Training [12/16] Loss: 0.00375 +Epoch [3485/4000] Training [13/16] Loss: 0.00226 +Epoch [3485/4000] Training [14/16] Loss: 0.00273 +Epoch [3485/4000] Training [15/16] Loss: 0.00277 +Epoch [3485/4000] Training [16/16] Loss: 0.00288 +Epoch [3485/4000] Training metric {'Train/mean dice_metric': 0.9985500574111938, 'Train/mean miou_metric': 0.9968295097351074, 'Train/mean f1': 0.9936589598655701, 'Train/mean precision': 0.9891347289085388, 'Train/mean recall': 0.9982247948646545, 'Train/mean hd95_metric': 0.5875276327133179} +Epoch [3485/4000] Validation [1/4] Loss: 0.36374 focal_loss 0.30095 dice_loss 0.06279 +Epoch [3485/4000] Validation [2/4] Loss: 0.89954 focal_loss 0.71540 dice_loss 0.18415 +Epoch [3485/4000] Validation [3/4] Loss: 0.53435 focal_loss 0.43947 dice_loss 0.09488 +Epoch [3485/4000] Validation [4/4] Loss: 0.47904 focal_loss 0.36596 dice_loss 0.11307 +Epoch [3485/4000] Validation metric {'Val/mean dice_metric': 0.9735738635063171, 'Val/mean miou_metric': 0.9595170021057129, 'Val/mean f1': 0.9764323830604553, 'Val/mean precision': 0.9743181467056274, 'Val/mean recall': 0.9785558581352234, 'Val/mean hd95_metric': 4.8655171394348145} +Cheakpoint... +Epoch [3485/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735738635063171, 'Val/mean miou_metric': 0.9595170021057129, 'Val/mean f1': 0.9764323830604553, 'Val/mean precision': 0.9743181467056274, 'Val/mean recall': 0.9785558581352234, 'Val/mean hd95_metric': 4.8655171394348145} +Epoch [3486/4000] Training [1/16] Loss: 0.00256 +Epoch [3486/4000] Training [2/16] Loss: 0.00252 +Epoch [3486/4000] Training [3/16] Loss: 0.00159 +Epoch [3486/4000] Training [4/16] Loss: 0.00223 +Epoch [3486/4000] Training [5/16] Loss: 0.00280 +Epoch [3486/4000] Training [6/16] Loss: 0.00214 +Epoch [3486/4000] Training [7/16] Loss: 0.00357 +Epoch [3486/4000] Training [8/16] Loss: 0.00226 +Epoch [3486/4000] Training [9/16] Loss: 0.00336 +Epoch [3486/4000] Training [10/16] Loss: 0.00196 +Epoch [3486/4000] Training [11/16] Loss: 0.00202 +Epoch [3486/4000] Training [12/16] Loss: 0.00243 +Epoch [3486/4000] Training [13/16] Loss: 0.00331 +Epoch [3486/4000] Training [14/16] Loss: 0.00170 +Epoch [3486/4000] Training [15/16] Loss: 0.00245 +Epoch [3486/4000] Training [16/16] Loss: 0.00167 +Epoch [3486/4000] Training metric {'Train/mean dice_metric': 0.9987596869468689, 'Train/mean miou_metric': 0.9972370862960815, 'Train/mean f1': 0.9937987327575684, 'Train/mean precision': 0.9892570376396179, 'Train/mean recall': 0.9983822703361511, 'Train/mean hd95_metric': 0.5791014432907104} +Epoch [3486/4000] Validation [1/4] Loss: 0.45329 focal_loss 0.38335 dice_loss 0.06993 +Epoch [3486/4000] Validation [2/4] Loss: 0.63222 focal_loss 0.45514 dice_loss 0.17708 +Epoch [3486/4000] Validation [3/4] Loss: 0.53791 focal_loss 0.44568 dice_loss 0.09224 +Epoch [3486/4000] Validation [4/4] Loss: 0.32286 focal_loss 0.23024 dice_loss 0.09262 +Epoch [3486/4000] Validation metric {'Val/mean dice_metric': 0.9730326533317566, 'Val/mean miou_metric': 0.9590522646903992, 'Val/mean f1': 0.9758725166320801, 'Val/mean precision': 0.9739804863929749, 'Val/mean recall': 0.9777719378471375, 'Val/mean hd95_metric': 5.086312294006348} +Cheakpoint... +Epoch [3486/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730326533317566, 'Val/mean miou_metric': 0.9590522646903992, 'Val/mean f1': 0.9758725166320801, 'Val/mean precision': 0.9739804863929749, 'Val/mean recall': 0.9777719378471375, 'Val/mean hd95_metric': 5.086312294006348} +Epoch [3487/4000] Training [1/16] Loss: 0.00272 +Epoch [3487/4000] Training [2/16] Loss: 0.00225 +Epoch [3487/4000] Training [3/16] Loss: 0.00215 +Epoch [3487/4000] Training [4/16] Loss: 0.00301 +Epoch [3487/4000] Training [5/16] Loss: 0.00210 +Epoch [3487/4000] Training [6/16] Loss: 0.00207 +Epoch [3487/4000] Training [7/16] Loss: 0.00245 +Epoch [3487/4000] Training [8/16] Loss: 0.00214 +Epoch [3487/4000] Training [9/16] Loss: 0.00286 +Epoch [3487/4000] Training [10/16] Loss: 0.00236 +Epoch [3487/4000] Training [11/16] Loss: 0.00263 +Epoch [3487/4000] Training [12/16] Loss: 0.00443 +Epoch [3487/4000] Training [13/16] Loss: 0.00225 +Epoch [3487/4000] Training [14/16] Loss: 0.00305 +Epoch [3487/4000] Training [15/16] Loss: 0.00211 +Epoch [3487/4000] Training [16/16] Loss: 0.00286 +Epoch [3487/4000] Training metric {'Train/mean dice_metric': 0.9988269805908203, 'Train/mean miou_metric': 0.9973787665367126, 'Train/mean f1': 0.9938583970069885, 'Train/mean precision': 0.9893452525138855, 'Train/mean recall': 0.9984129071235657, 'Train/mean hd95_metric': 0.514968991279602} +Epoch [3487/4000] Validation [1/4] Loss: 0.47722 focal_loss 0.41067 dice_loss 0.06655 +Epoch [3487/4000] Validation [2/4] Loss: 0.45016 focal_loss 0.34238 dice_loss 0.10777 +Epoch [3487/4000] Validation [3/4] Loss: 0.28553 focal_loss 0.22126 dice_loss 0.06428 +Epoch [3487/4000] Validation [4/4] Loss: 0.36892 focal_loss 0.27018 dice_loss 0.09874 +Epoch [3487/4000] Validation metric {'Val/mean dice_metric': 0.9738999605178833, 'Val/mean miou_metric': 0.9600874781608582, 'Val/mean f1': 0.9766882061958313, 'Val/mean precision': 0.9748712778091431, 'Val/mean recall': 0.9785118699073792, 'Val/mean hd95_metric': 4.752089023590088} +Cheakpoint... +Epoch [3487/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738999605178833, 'Val/mean miou_metric': 0.9600874781608582, 'Val/mean f1': 0.9766882061958313, 'Val/mean precision': 0.9748712778091431, 'Val/mean recall': 0.9785118699073792, 'Val/mean hd95_metric': 4.752089023590088} +Epoch [3488/4000] Training [1/16] Loss: 0.00204 +Epoch [3488/4000] Training [2/16] Loss: 0.00276 +Epoch [3488/4000] Training [3/16] Loss: 0.00238 +Epoch [3488/4000] Training [4/16] Loss: 0.00307 +Epoch [3488/4000] Training [5/16] Loss: 0.00291 +Epoch [3488/4000] Training [6/16] Loss: 0.00292 +Epoch [3488/4000] Training [7/16] Loss: 0.00202 +Epoch [3488/4000] Training [8/16] Loss: 0.00159 +Epoch [3488/4000] Training [9/16] Loss: 0.00305 +Epoch [3488/4000] Training [10/16] Loss: 0.00351 +Epoch [3488/4000] Training [11/16] Loss: 0.00298 +Epoch [3488/4000] Training [12/16] Loss: 0.00325 +Epoch [3488/4000] Training [13/16] Loss: 0.00319 +Epoch [3488/4000] Training [14/16] Loss: 0.00153 +Epoch [3488/4000] Training [15/16] Loss: 0.00308 +Epoch [3488/4000] Training [16/16] Loss: 0.00233 +Epoch [3488/4000] Training metric {'Train/mean dice_metric': 0.9986448287963867, 'Train/mean miou_metric': 0.9970147609710693, 'Train/mean f1': 0.9937428832054138, 'Train/mean precision': 0.9891967177391052, 'Train/mean recall': 0.9983310103416443, 'Train/mean hd95_metric': 0.5521061420440674} +Epoch [3488/4000] Validation [1/4] Loss: 0.39234 focal_loss 0.33024 dice_loss 0.06210 +Epoch [3488/4000] Validation [2/4] Loss: 0.91361 focal_loss 0.72742 dice_loss 0.18619 +Epoch [3488/4000] Validation [3/4] Loss: 0.52312 focal_loss 0.43260 dice_loss 0.09052 +Epoch [3488/4000] Validation [4/4] Loss: 0.44473 focal_loss 0.33811 dice_loss 0.10662 +Epoch [3488/4000] Validation metric {'Val/mean dice_metric': 0.9741670489311218, 'Val/mean miou_metric': 0.9605107307434082, 'Val/mean f1': 0.9764854311943054, 'Val/mean precision': 0.9739919304847717, 'Val/mean recall': 0.9789918661117554, 'Val/mean hd95_metric': 4.931513786315918} +Cheakpoint... +Epoch [3488/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741670489311218, 'Val/mean miou_metric': 0.9605107307434082, 'Val/mean f1': 0.9764854311943054, 'Val/mean precision': 0.9739919304847717, 'Val/mean recall': 0.9789918661117554, 'Val/mean hd95_metric': 4.931513786315918} +Epoch [3489/4000] Training [1/16] Loss: 0.00195 +Epoch [3489/4000] Training [2/16] Loss: 0.00432 +Epoch [3489/4000] Training [3/16] Loss: 0.00245 +Epoch [3489/4000] Training [4/16] Loss: 0.00205 +Epoch [3489/4000] Training [5/16] Loss: 0.00244 +Epoch [3489/4000] Training [6/16] Loss: 0.00239 +Epoch [3489/4000] Training [7/16] Loss: 0.00288 +Epoch [3489/4000] Training [8/16] Loss: 0.00195 +Epoch [3489/4000] Training [9/16] Loss: 0.00151 +Epoch [3489/4000] Training [10/16] Loss: 0.00278 +Epoch [3489/4000] Training [11/16] Loss: 0.00163 +Epoch [3489/4000] Training [12/16] Loss: 0.00252 +Epoch [3489/4000] Training [13/16] Loss: 0.00281 +Epoch [3489/4000] Training [14/16] Loss: 0.00249 +Epoch [3489/4000] Training [15/16] Loss: 0.00527 +Epoch [3489/4000] Training [16/16] Loss: 0.00383 +Epoch [3489/4000] Training metric {'Train/mean dice_metric': 0.9985285997390747, 'Train/mean miou_metric': 0.9967657327651978, 'Train/mean f1': 0.9933759570121765, 'Train/mean precision': 0.988738477230072, 'Train/mean recall': 0.9980571866035461, 'Train/mean hd95_metric': 0.6126185059547424} +Epoch [3489/4000] Validation [1/4] Loss: 0.44907 focal_loss 0.37858 dice_loss 0.07049 +Epoch [3489/4000] Validation [2/4] Loss: 0.90143 focal_loss 0.71574 dice_loss 0.18569 +Epoch [3489/4000] Validation [3/4] Loss: 0.28500 focal_loss 0.22396 dice_loss 0.06104 +Epoch [3489/4000] Validation [4/4] Loss: 0.36163 focal_loss 0.26329 dice_loss 0.09834 +Epoch [3489/4000] Validation metric {'Val/mean dice_metric': 0.9754130244255066, 'Val/mean miou_metric': 0.9613919258117676, 'Val/mean f1': 0.9765443801879883, 'Val/mean precision': 0.9739471077919006, 'Val/mean recall': 0.9791554808616638, 'Val/mean hd95_metric': 4.817380428314209} +Cheakpoint... +Epoch [3489/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754130244255066, 'Val/mean miou_metric': 0.9613919258117676, 'Val/mean f1': 0.9765443801879883, 'Val/mean precision': 0.9739471077919006, 'Val/mean recall': 0.9791554808616638, 'Val/mean hd95_metric': 4.817380428314209} +Epoch [3490/4000] Training [1/16] Loss: 0.00248 +Epoch [3490/4000] Training [2/16] Loss: 0.00325 +Epoch [3490/4000] Training [3/16] Loss: 0.00264 +Epoch [3490/4000] Training [4/16] Loss: 0.00333 +Epoch [3490/4000] Training [5/16] Loss: 0.00233 +Epoch [3490/4000] Training [6/16] Loss: 0.00193 +Epoch [3490/4000] Training [7/16] Loss: 0.00209 +Epoch [3490/4000] Training [8/16] Loss: 0.00207 +Epoch [3490/4000] Training [9/16] Loss: 0.00317 +Epoch [3490/4000] Training [10/16] Loss: 0.00298 +Epoch [3490/4000] Training [11/16] Loss: 0.00496 +Epoch [3490/4000] Training [12/16] Loss: 0.00287 +Epoch [3490/4000] Training [13/16] Loss: 0.00190 +Epoch [3490/4000] Training [14/16] Loss: 0.00258 +Epoch [3490/4000] Training [15/16] Loss: 0.00191 +Epoch [3490/4000] Training [16/16] Loss: 0.00397 +Epoch [3490/4000] Training metric {'Train/mean dice_metric': 0.99860680103302, 'Train/mean miou_metric': 0.9969260692596436, 'Train/mean f1': 0.9935521483421326, 'Train/mean precision': 0.9888558983802795, 'Train/mean recall': 0.9982932806015015, 'Train/mean hd95_metric': 0.5605745315551758} +Epoch [3490/4000] Validation [1/4] Loss: 0.36423 focal_loss 0.30352 dice_loss 0.06071 +Epoch [3490/4000] Validation [2/4] Loss: 0.55493 focal_loss 0.41112 dice_loss 0.14381 +Epoch [3490/4000] Validation [3/4] Loss: 0.51472 focal_loss 0.42043 dice_loss 0.09429 +Epoch [3490/4000] Validation [4/4] Loss: 0.38842 focal_loss 0.28826 dice_loss 0.10016 +Epoch [3490/4000] Validation metric {'Val/mean dice_metric': 0.9731742739677429, 'Val/mean miou_metric': 0.9593167304992676, 'Val/mean f1': 0.9758069515228271, 'Val/mean precision': 0.9723913073539734, 'Val/mean recall': 0.9792467951774597, 'Val/mean hd95_metric': 5.1751885414123535} +Cheakpoint... +Epoch [3490/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731742739677429, 'Val/mean miou_metric': 0.9593167304992676, 'Val/mean f1': 0.9758069515228271, 'Val/mean precision': 0.9723913073539734, 'Val/mean recall': 0.9792467951774597, 'Val/mean hd95_metric': 5.1751885414123535} +Epoch [3491/4000] Training [1/16] Loss: 0.00184 +Epoch [3491/4000] Training [2/16] Loss: 0.00267 +Epoch [3491/4000] Training [3/16] Loss: 0.00276 +Epoch [3491/4000] Training [4/16] Loss: 0.00279 +Epoch [3491/4000] Training [5/16] Loss: 0.00143 +Epoch [3491/4000] Training [6/16] Loss: 0.00160 +Epoch [3491/4000] Training [7/16] Loss: 0.00453 +Epoch [3491/4000] Training [8/16] Loss: 0.00242 +Epoch [3491/4000] Training [9/16] Loss: 0.00214 +Epoch [3491/4000] Training [10/16] Loss: 0.00207 +Epoch [3491/4000] Training [11/16] Loss: 0.00290 +Epoch [3491/4000] Training [12/16] Loss: 0.00344 +Epoch [3491/4000] Training [13/16] Loss: 0.00248 +Epoch [3491/4000] Training [14/16] Loss: 0.00189 +Epoch [3491/4000] Training [15/16] Loss: 0.00425 +Epoch [3491/4000] Training [16/16] Loss: 0.00202 +Epoch [3491/4000] Training metric {'Train/mean dice_metric': 0.9987185001373291, 'Train/mean miou_metric': 0.9971666932106018, 'Train/mean f1': 0.9938557147979736, 'Train/mean precision': 0.9893521070480347, 'Train/mean recall': 0.9984004497528076, 'Train/mean hd95_metric': 0.5706331133842468} +Epoch [3491/4000] Validation [1/4] Loss: 0.40366 focal_loss 0.33922 dice_loss 0.06444 +Epoch [3491/4000] Validation [2/4] Loss: 0.46848 focal_loss 0.35995 dice_loss 0.10853 +Epoch [3491/4000] Validation [3/4] Loss: 0.55487 focal_loss 0.45373 dice_loss 0.10115 +Epoch [3491/4000] Validation [4/4] Loss: 0.33210 focal_loss 0.24911 dice_loss 0.08299 +Epoch [3491/4000] Validation metric {'Val/mean dice_metric': 0.9750860929489136, 'Val/mean miou_metric': 0.9611045122146606, 'Val/mean f1': 0.9769999384880066, 'Val/mean precision': 0.9746626019477844, 'Val/mean recall': 0.9793486595153809, 'Val/mean hd95_metric': 4.590775012969971} +Cheakpoint... +Epoch [3491/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750860929489136, 'Val/mean miou_metric': 0.9611045122146606, 'Val/mean f1': 0.9769999384880066, 'Val/mean precision': 0.9746626019477844, 'Val/mean recall': 0.9793486595153809, 'Val/mean hd95_metric': 4.590775012969971} +Epoch [3492/4000] Training [1/16] Loss: 0.00328 +Epoch [3492/4000] Training [2/16] Loss: 0.00152 +Epoch [3492/4000] Training [3/16] Loss: 0.00369 +Epoch [3492/4000] Training [4/16] Loss: 0.00279 +Epoch [3492/4000] Training [5/16] Loss: 0.00250 +Epoch [3492/4000] Training [6/16] Loss: 0.00246 +Epoch [3492/4000] Training [7/16] Loss: 0.00277 +Epoch [3492/4000] Training [8/16] Loss: 0.00157 +Epoch [3492/4000] Training [9/16] Loss: 0.00218 +Epoch [3492/4000] Training [10/16] Loss: 0.00218 +Epoch [3492/4000] Training [11/16] Loss: 0.00195 +Epoch [3492/4000] Training [12/16] Loss: 0.00213 +Epoch [3492/4000] Training [13/16] Loss: 0.00272 +Epoch [3492/4000] Training [14/16] Loss: 0.00256 +Epoch [3492/4000] Training [15/16] Loss: 0.00218 +Epoch [3492/4000] Training [16/16] Loss: 0.00349 +Epoch [3492/4000] Training metric {'Train/mean dice_metric': 0.9987767338752747, 'Train/mean miou_metric': 0.9972788095474243, 'Train/mean f1': 0.9937852025032043, 'Train/mean precision': 0.9892547130584717, 'Train/mean recall': 0.998357355594635, 'Train/mean hd95_metric': 0.5394808053970337} +Epoch [3492/4000] Validation [1/4] Loss: 0.40052 focal_loss 0.33713 dice_loss 0.06338 +Epoch [3492/4000] Validation [2/4] Loss: 0.94717 focal_loss 0.75817 dice_loss 0.18900 +Epoch [3492/4000] Validation [3/4] Loss: 0.51396 focal_loss 0.42385 dice_loss 0.09011 +Epoch [3492/4000] Validation [4/4] Loss: 0.43716 focal_loss 0.33251 dice_loss 0.10464 +Epoch [3492/4000] Validation metric {'Val/mean dice_metric': 0.9740291833877563, 'Val/mean miou_metric': 0.9601766467094421, 'Val/mean f1': 0.9764442443847656, 'Val/mean precision': 0.9738309383392334, 'Val/mean recall': 0.9790716767311096, 'Val/mean hd95_metric': 4.837488651275635} +Cheakpoint... +Epoch [3492/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740291833877563, 'Val/mean miou_metric': 0.9601766467094421, 'Val/mean f1': 0.9764442443847656, 'Val/mean precision': 0.9738309383392334, 'Val/mean recall': 0.9790716767311096, 'Val/mean hd95_metric': 4.837488651275635} +Epoch [3493/4000] Training [1/16] Loss: 0.00253 +Epoch [3493/4000] Training [2/16] Loss: 0.00228 +Epoch [3493/4000] Training [3/16] Loss: 0.00506 +Epoch [3493/4000] Training [4/16] Loss: 0.00294 +Epoch [3493/4000] Training [5/16] Loss: 0.00359 +Epoch [3493/4000] Training [6/16] Loss: 0.00177 +Epoch [3493/4000] Training [7/16] Loss: 0.00255 +Epoch [3493/4000] Training [8/16] Loss: 0.00234 +Epoch [3493/4000] Training [9/16] Loss: 0.00297 +Epoch [3493/4000] Training [10/16] Loss: 0.00226 +Epoch [3493/4000] Training [11/16] Loss: 0.00260 +Epoch [3493/4000] Training [12/16] Loss: 0.00310 +Epoch [3493/4000] Training [13/16] Loss: 0.00202 +Epoch [3493/4000] Training [14/16] Loss: 0.00218 +Epoch [3493/4000] Training [15/16] Loss: 0.00322 +Epoch [3493/4000] Training [16/16] Loss: 0.00257 +Epoch [3493/4000] Training metric {'Train/mean dice_metric': 0.9986835718154907, 'Train/mean miou_metric': 0.9970771074295044, 'Train/mean f1': 0.993333637714386, 'Train/mean precision': 0.9884477853775024, 'Train/mean recall': 0.9982680082321167, 'Train/mean hd95_metric': 0.5669220685958862} +Epoch [3493/4000] Validation [1/4] Loss: 0.39455 focal_loss 0.33392 dice_loss 0.06064 +Epoch [3493/4000] Validation [2/4] Loss: 0.46527 focal_loss 0.35776 dice_loss 0.10751 +Epoch [3493/4000] Validation [3/4] Loss: 0.48676 focal_loss 0.39148 dice_loss 0.09528 +Epoch [3493/4000] Validation [4/4] Loss: 0.39381 focal_loss 0.28674 dice_loss 0.10707 +Epoch [3493/4000] Validation metric {'Val/mean dice_metric': 0.9746477007865906, 'Val/mean miou_metric': 0.9604970812797546, 'Val/mean f1': 0.976110577583313, 'Val/mean precision': 0.9732397198677063, 'Val/mean recall': 0.9789984822273254, 'Val/mean hd95_metric': 4.83986759185791} +Cheakpoint... +Epoch [3493/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746477007865906, 'Val/mean miou_metric': 0.9604970812797546, 'Val/mean f1': 0.976110577583313, 'Val/mean precision': 0.9732397198677063, 'Val/mean recall': 0.9789984822273254, 'Val/mean hd95_metric': 4.83986759185791} +Epoch [3494/4000] Training [1/16] Loss: 0.00262 +Epoch [3494/4000] Training [2/16] Loss: 0.00346 +Epoch [3494/4000] Training [3/16] Loss: 0.00223 +Epoch [3494/4000] Training [4/16] Loss: 0.00215 +Epoch [3494/4000] Training [5/16] Loss: 0.00341 +Epoch [3494/4000] Training [6/16] Loss: 0.00246 +Epoch [3494/4000] Training [7/16] Loss: 0.00226 +Epoch [3494/4000] Training [8/16] Loss: 0.00261 +Epoch [3494/4000] Training [9/16] Loss: 0.00337 +Epoch [3494/4000] Training [10/16] Loss: 0.00329 +Epoch [3494/4000] Training [11/16] Loss: 0.00233 +Epoch [3494/4000] Training [12/16] Loss: 0.00234 +Epoch [3494/4000] Training [13/16] Loss: 0.00187 +Epoch [3494/4000] Training [14/16] Loss: 0.00547 +Epoch [3494/4000] Training [15/16] Loss: 0.00201 +Epoch [3494/4000] Training [16/16] Loss: 0.00218 +Epoch [3494/4000] Training metric {'Train/mean dice_metric': 0.9985843896865845, 'Train/mean miou_metric': 0.9968910217285156, 'Train/mean f1': 0.9935294389724731, 'Train/mean precision': 0.9888882637023926, 'Train/mean recall': 0.9982143044471741, 'Train/mean hd95_metric': 0.5626808404922485} +Epoch [3494/4000] Validation [1/4] Loss: 0.41165 focal_loss 0.34809 dice_loss 0.06357 +Epoch [3494/4000] Validation [2/4] Loss: 0.95230 focal_loss 0.73685 dice_loss 0.21545 +Epoch [3494/4000] Validation [3/4] Loss: 0.28979 focal_loss 0.22739 dice_loss 0.06240 +Epoch [3494/4000] Validation [4/4] Loss: 0.34733 focal_loss 0.26083 dice_loss 0.08650 +Epoch [3494/4000] Validation metric {'Val/mean dice_metric': 0.9754515886306763, 'Val/mean miou_metric': 0.961452841758728, 'Val/mean f1': 0.9763930439949036, 'Val/mean precision': 0.9741184711456299, 'Val/mean recall': 0.978678286075592, 'Val/mean hd95_metric': 4.78005838394165} +Cheakpoint... +Epoch [3494/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754515886306763, 'Val/mean miou_metric': 0.961452841758728, 'Val/mean f1': 0.9763930439949036, 'Val/mean precision': 0.9741184711456299, 'Val/mean recall': 0.978678286075592, 'Val/mean hd95_metric': 4.78005838394165} +Epoch [3495/4000] Training [1/16] Loss: 0.00339 +Epoch [3495/4000] Training [2/16] Loss: 0.00301 +Epoch [3495/4000] Training [3/16] Loss: 0.00197 +Epoch [3495/4000] Training [4/16] Loss: 0.00246 +Epoch [3495/4000] Training [5/16] Loss: 0.00218 +Epoch [3495/4000] Training [6/16] Loss: 0.00250 +Epoch [3495/4000] Training [7/16] Loss: 0.00269 +Epoch [3495/4000] Training [8/16] Loss: 0.00320 +Epoch [3495/4000] Training [9/16] Loss: 0.00180 +Epoch [3495/4000] Training [10/16] Loss: 0.00178 +Epoch [3495/4000] Training [11/16] Loss: 0.00380 +Epoch [3495/4000] Training [12/16] Loss: 0.00198 +Epoch [3495/4000] Training [13/16] Loss: 0.00250 +Epoch [3495/4000] Training [14/16] Loss: 0.00219 +Epoch [3495/4000] Training [15/16] Loss: 0.00266 +Epoch [3495/4000] Training [16/16] Loss: 0.00279 +Epoch [3495/4000] Training metric {'Train/mean dice_metric': 0.9987430572509766, 'Train/mean miou_metric': 0.997197687625885, 'Train/mean f1': 0.9936150908470154, 'Train/mean precision': 0.9889565110206604, 'Train/mean recall': 0.9983177185058594, 'Train/mean hd95_metric': 0.5572541952133179} +Epoch [3495/4000] Validation [1/4] Loss: 0.41744 focal_loss 0.35313 dice_loss 0.06431 +Epoch [3495/4000] Validation [2/4] Loss: 0.47229 focal_loss 0.36212 dice_loss 0.11017 +Epoch [3495/4000] Validation [3/4] Loss: 0.55433 focal_loss 0.45974 dice_loss 0.09459 +Epoch [3495/4000] Validation [4/4] Loss: 0.35193 focal_loss 0.26539 dice_loss 0.08654 +Epoch [3495/4000] Validation metric {'Val/mean dice_metric': 0.9756963849067688, 'Val/mean miou_metric': 0.9616451263427734, 'Val/mean f1': 0.9767058491706848, 'Val/mean precision': 0.9737962484359741, 'Val/mean recall': 0.9796328544616699, 'Val/mean hd95_metric': 4.562711238861084} +Cheakpoint... +Epoch [3495/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756963849067688, 'Val/mean miou_metric': 0.9616451263427734, 'Val/mean f1': 0.9767058491706848, 'Val/mean precision': 0.9737962484359741, 'Val/mean recall': 0.9796328544616699, 'Val/mean hd95_metric': 4.562711238861084} +Epoch [3496/4000] Training [1/16] Loss: 0.00284 +Epoch [3496/4000] Training [2/16] Loss: 0.00356 +Epoch [3496/4000] Training [3/16] Loss: 0.00212 +Epoch [3496/4000] Training [4/16] Loss: 0.00254 +Epoch [3496/4000] Training [5/16] Loss: 0.00215 +Epoch [3496/4000] Training [6/16] Loss: 0.00265 +Epoch [3496/4000] Training [7/16] Loss: 0.00316 +Epoch [3496/4000] Training [8/16] Loss: 0.00221 +Epoch [3496/4000] Training [9/16] Loss: 0.00342 +Epoch [3496/4000] Training [10/16] Loss: 0.00295 +Epoch [3496/4000] Training [11/16] Loss: 0.00261 +Epoch [3496/4000] Training [12/16] Loss: 0.00269 +Epoch [3496/4000] Training [13/16] Loss: 0.00230 +Epoch [3496/4000] Training [14/16] Loss: 0.00177 +Epoch [3496/4000] Training [15/16] Loss: 0.00211 +Epoch [3496/4000] Training [16/16] Loss: 0.00280 +Epoch [3496/4000] Training metric {'Train/mean dice_metric': 0.9987508058547974, 'Train/mean miou_metric': 0.9972082376480103, 'Train/mean f1': 0.9935608506202698, 'Train/mean precision': 0.9888138771057129, 'Train/mean recall': 0.9983536005020142, 'Train/mean hd95_metric': 0.5572807192802429} +Epoch [3496/4000] Validation [1/4] Loss: 0.46975 focal_loss 0.40110 dice_loss 0.06865 +Epoch [3496/4000] Validation [2/4] Loss: 1.23390 focal_loss 1.01434 dice_loss 0.21956 +Epoch [3496/4000] Validation [3/4] Loss: 0.55325 focal_loss 0.45232 dice_loss 0.10093 +Epoch [3496/4000] Validation [4/4] Loss: 0.26572 focal_loss 0.18798 dice_loss 0.07774 +Epoch [3496/4000] Validation metric {'Val/mean dice_metric': 0.9751065969467163, 'Val/mean miou_metric': 0.9611126184463501, 'Val/mean f1': 0.9762619137763977, 'Val/mean precision': 0.9730631709098816, 'Val/mean recall': 0.9794818162918091, 'Val/mean hd95_metric': 4.831447124481201} +Cheakpoint... +Epoch [3496/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751065969467163, 'Val/mean miou_metric': 0.9611126184463501, 'Val/mean f1': 0.9762619137763977, 'Val/mean precision': 0.9730631709098816, 'Val/mean recall': 0.9794818162918091, 'Val/mean hd95_metric': 4.831447124481201} +Epoch [3497/4000] Training [1/16] Loss: 0.00329 +Epoch [3497/4000] Training [2/16] Loss: 0.00244 +Epoch [3497/4000] Training [3/16] Loss: 0.00312 +Epoch [3497/4000] Training [4/16] Loss: 0.00437 +Epoch [3497/4000] Training [5/16] Loss: 0.00268 +Epoch [3497/4000] Training [6/16] Loss: 0.00275 +Epoch [3497/4000] Training [7/16] Loss: 0.00289 +Epoch [3497/4000] Training [8/16] Loss: 0.00237 +Epoch [3497/4000] Training [9/16] Loss: 0.00209 +Epoch [3497/4000] Training [10/16] Loss: 0.00239 +Epoch [3497/4000] Training [11/16] Loss: 0.00417 +Epoch [3497/4000] Training [12/16] Loss: 0.00218 +Epoch [3497/4000] Training [13/16] Loss: 0.00195 +Epoch [3497/4000] Training [14/16] Loss: 0.00220 +Epoch [3497/4000] Training [15/16] Loss: 0.00236 +Epoch [3497/4000] Training [16/16] Loss: 0.00207 +Epoch [3497/4000] Training metric {'Train/mean dice_metric': 0.9986739754676819, 'Train/mean miou_metric': 0.9970472455024719, 'Train/mean f1': 0.9930711388587952, 'Train/mean precision': 0.9880499839782715, 'Train/mean recall': 0.9981436133384705, 'Train/mean hd95_metric': 0.6066681146621704} +Epoch [3497/4000] Validation [1/4] Loss: 0.36348 focal_loss 0.30327 dice_loss 0.06021 +Epoch [3497/4000] Validation [2/4] Loss: 0.49661 focal_loss 0.38508 dice_loss 0.11153 +Epoch [3497/4000] Validation [3/4] Loss: 0.53830 focal_loss 0.43957 dice_loss 0.09873 +Epoch [3497/4000] Validation [4/4] Loss: 0.37475 focal_loss 0.27659 dice_loss 0.09816 +Epoch [3497/4000] Validation metric {'Val/mean dice_metric': 0.9746034741401672, 'Val/mean miou_metric': 0.9604838490486145, 'Val/mean f1': 0.9759050011634827, 'Val/mean precision': 0.9735921025276184, 'Val/mean recall': 0.9782288670539856, 'Val/mean hd95_metric': 4.7041802406311035} +Cheakpoint... +Epoch [3497/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746034741401672, 'Val/mean miou_metric': 0.9604838490486145, 'Val/mean f1': 0.9759050011634827, 'Val/mean precision': 0.9735921025276184, 'Val/mean recall': 0.9782288670539856, 'Val/mean hd95_metric': 4.7041802406311035} +Epoch [3498/4000] Training [1/16] Loss: 0.00162 +Epoch [3498/4000] Training [2/16] Loss: 0.00399 +Epoch [3498/4000] Training [3/16] Loss: 0.00188 +Epoch [3498/4000] Training [4/16] Loss: 0.00328 +Epoch [3498/4000] Training [5/16] Loss: 0.00266 +Epoch [3498/4000] Training [6/16] Loss: 0.00231 +Epoch [3498/4000] Training [7/16] Loss: 0.00412 +Epoch [3498/4000] Training [8/16] Loss: 0.00197 +Epoch [3498/4000] Training [9/16] Loss: 0.00195 +Epoch [3498/4000] Training [10/16] Loss: 0.00273 +Epoch [3498/4000] Training [11/16] Loss: 0.00320 +Epoch [3498/4000] Training [12/16] Loss: 0.00232 +Epoch [3498/4000] Training [13/16] Loss: 0.00217 +Epoch [3498/4000] Training [14/16] Loss: 0.00290 +Epoch [3498/4000] Training [15/16] Loss: 0.00285 +Epoch [3498/4000] Training [16/16] Loss: 0.00220 +Epoch [3498/4000] Training metric {'Train/mean dice_metric': 0.9987298250198364, 'Train/mean miou_metric': 0.997187614440918, 'Train/mean f1': 0.9938161969184875, 'Train/mean precision': 0.9892457723617554, 'Train/mean recall': 0.9984290599822998, 'Train/mean hd95_metric': 0.5629181265830994} +Epoch [3498/4000] Validation [1/4] Loss: 0.46806 focal_loss 0.40142 dice_loss 0.06664 +Epoch [3498/4000] Validation [2/4] Loss: 0.48888 focal_loss 0.37663 dice_loss 0.11225 +Epoch [3498/4000] Validation [3/4] Loss: 0.52031 focal_loss 0.43084 dice_loss 0.08948 +Epoch [3498/4000] Validation [4/4] Loss: 0.35113 focal_loss 0.26169 dice_loss 0.08944 +Epoch [3498/4000] Validation metric {'Val/mean dice_metric': 0.9738231897354126, 'Val/mean miou_metric': 0.9598600268363953, 'Val/mean f1': 0.9765113592147827, 'Val/mean precision': 0.9748544096946716, 'Val/mean recall': 0.9781739115715027, 'Val/mean hd95_metric': 4.711690902709961} +Cheakpoint... +Epoch [3498/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738231897354126, 'Val/mean miou_metric': 0.9598600268363953, 'Val/mean f1': 0.9765113592147827, 'Val/mean precision': 0.9748544096946716, 'Val/mean recall': 0.9781739115715027, 'Val/mean hd95_metric': 4.711690902709961} +Epoch [3499/4000] Training [1/16] Loss: 0.00360 +Epoch [3499/4000] Training [2/16] Loss: 0.00301 +Epoch [3499/4000] Training [3/16] Loss: 0.00235 +Epoch [3499/4000] Training [4/16] Loss: 0.02169 +Epoch [3499/4000] Training [5/16] Loss: 0.00282 +Epoch [3499/4000] Training [6/16] Loss: 0.00245 +Epoch [3499/4000] Training [7/16] Loss: 0.00248 +Epoch [3499/4000] Training [8/16] Loss: 0.00184 +Epoch [3499/4000] Training [9/16] Loss: 0.00210 +Epoch [3499/4000] Training [10/16] Loss: 0.00172 +Epoch [3499/4000] Training [11/16] Loss: 0.00250 +Epoch [3499/4000] Training [12/16] Loss: 0.00301 +Epoch [3499/4000] Training [13/16] Loss: 0.00214 +Epoch [3499/4000] Training [14/16] Loss: 0.00305 +Epoch [3499/4000] Training [15/16] Loss: 0.00195 +Epoch [3499/4000] Training [16/16] Loss: 0.00222 +Epoch [3499/4000] Training metric {'Train/mean dice_metric': 0.9986026883125305, 'Train/mean miou_metric': 0.9969121813774109, 'Train/mean f1': 0.9932969212532043, 'Train/mean precision': 0.9885737895965576, 'Train/mean recall': 0.9980654716491699, 'Train/mean hd95_metric': 0.6580590009689331} +Epoch [3499/4000] Validation [1/4] Loss: 0.40006 focal_loss 0.33712 dice_loss 0.06295 +Epoch [3499/4000] Validation [2/4] Loss: 0.44323 focal_loss 0.33562 dice_loss 0.10761 +Epoch [3499/4000] Validation [3/4] Loss: 0.54870 focal_loss 0.45627 dice_loss 0.09243 +Epoch [3499/4000] Validation [4/4] Loss: 0.35651 focal_loss 0.24754 dice_loss 0.10897 +Epoch [3499/4000] Validation metric {'Val/mean dice_metric': 0.9719951748847961, 'Val/mean miou_metric': 0.958160400390625, 'Val/mean f1': 0.9752727746963501, 'Val/mean precision': 0.9717273116111755, 'Val/mean recall': 0.9788441061973572, 'Val/mean hd95_metric': 5.57351541519165} +Cheakpoint... +Epoch [3499/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9719951748847961, 'Val/mean miou_metric': 0.958160400390625, 'Val/mean f1': 0.9752727746963501, 'Val/mean precision': 0.9717273116111755, 'Val/mean recall': 0.9788441061973572, 'Val/mean hd95_metric': 5.57351541519165} +Epoch [3500/4000] Training [1/16] Loss: 0.00272 +Epoch [3500/4000] Training [2/16] Loss: 0.00192 +Epoch [3500/4000] Training [3/16] Loss: 0.00279 +Epoch [3500/4000] Training [4/16] Loss: 0.00275 +Epoch [3500/4000] Training [5/16] Loss: 0.00306 +Epoch [3500/4000] Training [6/16] Loss: 0.00258 +Epoch [3500/4000] Training [7/16] Loss: 0.00273 +Epoch [3500/4000] Training [8/16] Loss: 0.00298 +Epoch [3500/4000] Training [9/16] Loss: 0.00311 +Epoch [3500/4000] Training [10/16] Loss: 0.00246 +Epoch [3500/4000] Training [11/16] Loss: 0.00257 +Epoch [3500/4000] Training [12/16] Loss: 0.00220 +Epoch [3500/4000] Training [13/16] Loss: 0.00188 +Epoch [3500/4000] Training [14/16] Loss: 0.00234 +Epoch [3500/4000] Training [15/16] Loss: 0.00232 +Epoch [3500/4000] Training [16/16] Loss: 0.00219 +Epoch [3500/4000] Training metric {'Train/mean dice_metric': 0.9986898899078369, 'Train/mean miou_metric': 0.9971044063568115, 'Train/mean f1': 0.993742048740387, 'Train/mean precision': 0.9891651272773743, 'Train/mean recall': 0.9983615279197693, 'Train/mean hd95_metric': 0.5612580180168152} +Epoch [3500/4000] Validation [1/4] Loss: 0.43996 focal_loss 0.36995 dice_loss 0.07001 +Epoch [3500/4000] Validation [2/4] Loss: 0.44026 focal_loss 0.32160 dice_loss 0.11865 +Epoch [3500/4000] Validation [3/4] Loss: 0.53582 focal_loss 0.44183 dice_loss 0.09399 +Epoch [3500/4000] Validation [4/4] Loss: 0.36706 focal_loss 0.27299 dice_loss 0.09407 +Epoch [3500/4000] Validation metric {'Val/mean dice_metric': 0.9756919741630554, 'Val/mean miou_metric': 0.9611396789550781, 'Val/mean f1': 0.9763087630271912, 'Val/mean precision': 0.9737256169319153, 'Val/mean recall': 0.9789056181907654, 'Val/mean hd95_metric': 4.803656578063965} +Cheakpoint... +Epoch [3500/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756919741630554, 'Val/mean miou_metric': 0.9611396789550781, 'Val/mean f1': 0.9763087630271912, 'Val/mean precision': 0.9737256169319153, 'Val/mean recall': 0.9789056181907654, 'Val/mean hd95_metric': 4.803656578063965} +Epoch [3501/4000] Training [1/16] Loss: 0.00276 +Epoch [3501/4000] Training [2/16] Loss: 0.00201 +Epoch [3501/4000] Training [3/16] Loss: 0.00315 +Epoch [3501/4000] Training [4/16] Loss: 0.00301 +Epoch [3501/4000] Training [5/16] Loss: 0.00221 +Epoch [3501/4000] Training [6/16] Loss: 0.00275 +Epoch [3501/4000] Training [7/16] Loss: 0.00236 +Epoch [3501/4000] Training [8/16] Loss: 0.00178 +Epoch [3501/4000] Training [9/16] Loss: 0.00208 +Epoch [3501/4000] Training [10/16] Loss: 0.00182 +Epoch [3501/4000] Training [11/16] Loss: 0.00193 +Epoch [3501/4000] Training [12/16] Loss: 0.00290 +Epoch [3501/4000] Training [13/16] Loss: 0.00369 +Epoch [3501/4000] Training [14/16] Loss: 0.00229 +Epoch [3501/4000] Training [15/16] Loss: 0.00295 +Epoch [3501/4000] Training [16/16] Loss: 0.00214 +Epoch [3501/4000] Training metric {'Train/mean dice_metric': 0.9987320899963379, 'Train/mean miou_metric': 0.9971497654914856, 'Train/mean f1': 0.9927518367767334, 'Train/mean precision': 0.9873424172401428, 'Train/mean recall': 0.9982208609580994, 'Train/mean hd95_metric': 0.5874576568603516} +Epoch [3501/4000] Validation [1/4] Loss: 0.41292 focal_loss 0.34920 dice_loss 0.06372 +Epoch [3501/4000] Validation [2/4] Loss: 0.46865 focal_loss 0.34182 dice_loss 0.12683 +Epoch [3501/4000] Validation [3/4] Loss: 0.55196 focal_loss 0.45507 dice_loss 0.09689 +Epoch [3501/4000] Validation [4/4] Loss: 0.42254 focal_loss 0.30825 dice_loss 0.11429 +Epoch [3501/4000] Validation metric {'Val/mean dice_metric': 0.973659336566925, 'Val/mean miou_metric': 0.9592515230178833, 'Val/mean f1': 0.975253701210022, 'Val/mean precision': 0.9707776308059692, 'Val/mean recall': 0.9797712564468384, 'Val/mean hd95_metric': 5.349968910217285} +Cheakpoint... +Epoch [3501/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973659336566925, 'Val/mean miou_metric': 0.9592515230178833, 'Val/mean f1': 0.975253701210022, 'Val/mean precision': 0.9707776308059692, 'Val/mean recall': 0.9797712564468384, 'Val/mean hd95_metric': 5.349968910217285} +Epoch [3502/4000] Training [1/16] Loss: 0.00176 +Epoch [3502/4000] Training [2/16] Loss: 0.00358 +Epoch [3502/4000] Training [3/16] Loss: 0.00172 +Epoch [3502/4000] Training [4/16] Loss: 0.00308 +Epoch [3502/4000] Training [5/16] Loss: 0.00263 +Epoch [3502/4000] Training [6/16] Loss: 0.00194 +Epoch [3502/4000] Training [7/16] Loss: 0.00200 +Epoch [3502/4000] Training [8/16] Loss: 0.00228 +Epoch [3502/4000] Training [9/16] Loss: 0.00238 +Epoch [3502/4000] Training [10/16] Loss: 0.00442 +Epoch [3502/4000] Training [11/16] Loss: 0.00238 +Epoch [3502/4000] Training [12/16] Loss: 0.00171 +Epoch [3502/4000] Training [13/16] Loss: 0.00372 +Epoch [3502/4000] Training [14/16] Loss: 0.00351 +Epoch [3502/4000] Training [15/16] Loss: 0.00367 +Epoch [3502/4000] Training [16/16] Loss: 0.00198 +Epoch [3502/4000] Training metric {'Train/mean dice_metric': 0.998685359954834, 'Train/mean miou_metric': 0.9970970153808594, 'Train/mean f1': 0.9937703013420105, 'Train/mean precision': 0.9892753958702087, 'Train/mean recall': 0.9983062744140625, 'Train/mean hd95_metric': 0.5991065502166748} +Epoch [3502/4000] Validation [1/4] Loss: 0.34414 focal_loss 0.28465 dice_loss 0.05949 +Epoch [3502/4000] Validation [2/4] Loss: 0.47950 focal_loss 0.36127 dice_loss 0.11823 +Epoch [3502/4000] Validation [3/4] Loss: 0.27661 focal_loss 0.21710 dice_loss 0.05951 +Epoch [3502/4000] Validation [4/4] Loss: 0.28564 focal_loss 0.19531 dice_loss 0.09032 +Epoch [3502/4000] Validation metric {'Val/mean dice_metric': 0.9744554758071899, 'Val/mean miou_metric': 0.9607429504394531, 'Val/mean f1': 0.9763848185539246, 'Val/mean precision': 0.973947286605835, 'Val/mean recall': 0.9788345098495483, 'Val/mean hd95_metric': 5.178016185760498} +Cheakpoint... +Epoch [3502/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744554758071899, 'Val/mean miou_metric': 0.9607429504394531, 'Val/mean f1': 0.9763848185539246, 'Val/mean precision': 0.973947286605835, 'Val/mean recall': 0.9788345098495483, 'Val/mean hd95_metric': 5.178016185760498} +Epoch [3503/4000] Training [1/16] Loss: 0.00213 +Epoch [3503/4000] Training [2/16] Loss: 0.00229 +Epoch [3503/4000] Training [3/16] Loss: 0.00232 +Epoch [3503/4000] Training [4/16] Loss: 0.00289 +Epoch [3503/4000] Training [5/16] Loss: 0.00299 +Epoch [3503/4000] Training [6/16] Loss: 0.00291 +Epoch [3503/4000] Training [7/16] Loss: 0.00255 +Epoch [3503/4000] Training [8/16] Loss: 0.00240 +Epoch [3503/4000] Training [9/16] Loss: 0.00261 +Epoch [3503/4000] Training [10/16] Loss: 0.00246 +Epoch [3503/4000] Training [11/16] Loss: 0.00272 +Epoch [3503/4000] Training [12/16] Loss: 0.00174 +Epoch [3503/4000] Training [13/16] Loss: 0.00239 +Epoch [3503/4000] Training [14/16] Loss: 0.00232 +Epoch [3503/4000] Training [15/16] Loss: 0.00211 +Epoch [3503/4000] Training [16/16] Loss: 0.00208 +Epoch [3503/4000] Training metric {'Train/mean dice_metric': 0.9987027645111084, 'Train/mean miou_metric': 0.9971243739128113, 'Train/mean f1': 0.993740975856781, 'Train/mean precision': 0.9892459511756897, 'Train/mean recall': 0.9982770085334778, 'Train/mean hd95_metric': 0.6005159020423889} +Epoch [3503/4000] Validation [1/4] Loss: 0.35216 focal_loss 0.28962 dice_loss 0.06254 +Epoch [3503/4000] Validation [2/4] Loss: 0.93561 focal_loss 0.74182 dice_loss 0.19379 +Epoch [3503/4000] Validation [3/4] Loss: 0.52500 focal_loss 0.43330 dice_loss 0.09170 +Epoch [3503/4000] Validation [4/4] Loss: 0.31557 focal_loss 0.22570 dice_loss 0.08987 +Epoch [3503/4000] Validation metric {'Val/mean dice_metric': 0.9743524789810181, 'Val/mean miou_metric': 0.9606921076774597, 'Val/mean f1': 0.9766910076141357, 'Val/mean precision': 0.9738220572471619, 'Val/mean recall': 0.9795770049095154, 'Val/mean hd95_metric': 4.768553733825684} +Cheakpoint... +Epoch [3503/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743524789810181, 'Val/mean miou_metric': 0.9606921076774597, 'Val/mean f1': 0.9766910076141357, 'Val/mean precision': 0.9738220572471619, 'Val/mean recall': 0.9795770049095154, 'Val/mean hd95_metric': 4.768553733825684} +Epoch [3504/4000] Training [1/16] Loss: 0.00284 +Epoch [3504/4000] Training [2/16] Loss: 0.00169 +Epoch [3504/4000] Training [3/16] Loss: 0.00361 +Epoch [3504/4000] Training [4/16] Loss: 0.00222 +Epoch [3504/4000] Training [5/16] Loss: 0.00271 +Epoch [3504/4000] Training [6/16] Loss: 0.00218 +Epoch [3504/4000] Training [7/16] Loss: 0.00280 +Epoch [3504/4000] Training [8/16] Loss: 0.00194 +Epoch [3504/4000] Training [9/16] Loss: 0.00290 +Epoch [3504/4000] Training [10/16] Loss: 0.00171 +Epoch [3504/4000] Training [11/16] Loss: 0.00321 +Epoch [3504/4000] Training [12/16] Loss: 0.00313 +Epoch [3504/4000] Training [13/16] Loss: 0.00178 +Epoch [3504/4000] Training [14/16] Loss: 0.00166 +Epoch [3504/4000] Training [15/16] Loss: 0.00211 +Epoch [3504/4000] Training [16/16] Loss: 0.00344 +Epoch [3504/4000] Training metric {'Train/mean dice_metric': 0.9988356232643127, 'Train/mean miou_metric': 0.9973939657211304, 'Train/mean f1': 0.9938387274742126, 'Train/mean precision': 0.989277184009552, 'Train/mean recall': 0.9984424710273743, 'Train/mean hd95_metric': 0.5457306504249573} +Epoch [3504/4000] Validation [1/4] Loss: 0.41312 focal_loss 0.34851 dice_loss 0.06461 +Epoch [3504/4000] Validation [2/4] Loss: 0.43525 focal_loss 0.33042 dice_loss 0.10483 +Epoch [3504/4000] Validation [3/4] Loss: 0.52900 focal_loss 0.43333 dice_loss 0.09568 +Epoch [3504/4000] Validation [4/4] Loss: 0.27462 focal_loss 0.19250 dice_loss 0.08212 +Epoch [3504/4000] Validation metric {'Val/mean dice_metric': 0.9738601446151733, 'Val/mean miou_metric': 0.9605636596679688, 'Val/mean f1': 0.9765568375587463, 'Val/mean precision': 0.974229633808136, 'Val/mean recall': 0.9788953065872192, 'Val/mean hd95_metric': 4.53486442565918} +Cheakpoint... +Epoch [3504/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738601446151733, 'Val/mean miou_metric': 0.9605636596679688, 'Val/mean f1': 0.9765568375587463, 'Val/mean precision': 0.974229633808136, 'Val/mean recall': 0.9788953065872192, 'Val/mean hd95_metric': 4.53486442565918} +Epoch [3505/4000] Training [1/16] Loss: 0.00339 +Epoch [3505/4000] Training [2/16] Loss: 0.00198 +Epoch [3505/4000] Training [3/16] Loss: 0.00266 +Epoch [3505/4000] Training [4/16] Loss: 0.00256 +Epoch [3505/4000] Training [5/16] Loss: 0.00416 +Epoch [3505/4000] Training [6/16] Loss: 0.00257 +Epoch [3505/4000] Training [7/16] Loss: 0.00370 +Epoch [3505/4000] Training [8/16] Loss: 0.00155 +Epoch [3505/4000] Training [9/16] Loss: 0.00236 +Epoch [3505/4000] Training [10/16] Loss: 0.00236 +Epoch [3505/4000] Training [11/16] Loss: 0.00403 +Epoch [3505/4000] Training [12/16] Loss: 0.00256 +Epoch [3505/4000] Training [13/16] Loss: 0.00313 +Epoch [3505/4000] Training [14/16] Loss: 0.00310 +Epoch [3505/4000] Training [15/16] Loss: 0.00240 +Epoch [3505/4000] Training [16/16] Loss: 0.00310 +Epoch [3505/4000] Training metric {'Train/mean dice_metric': 0.9984160661697388, 'Train/mean miou_metric': 0.9965367317199707, 'Train/mean f1': 0.9931520223617554, 'Train/mean precision': 0.988301157951355, 'Train/mean recall': 0.9980508089065552, 'Train/mean hd95_metric': 0.6177309155464172} +Epoch [3505/4000] Validation [1/4] Loss: 0.39609 focal_loss 0.33485 dice_loss 0.06123 +Epoch [3505/4000] Validation [2/4] Loss: 0.90695 focal_loss 0.71965 dice_loss 0.18731 +Epoch [3505/4000] Validation [3/4] Loss: 0.26989 focal_loss 0.21121 dice_loss 0.05868 +Epoch [3505/4000] Validation [4/4] Loss: 0.33331 focal_loss 0.24185 dice_loss 0.09145 +Epoch [3505/4000] Validation metric {'Val/mean dice_metric': 0.9744279980659485, 'Val/mean miou_metric': 0.9605998992919922, 'Val/mean f1': 0.9763742685317993, 'Val/mean precision': 0.973539412021637, 'Val/mean recall': 0.9792255759239197, 'Val/mean hd95_metric': 4.84425687789917} +Cheakpoint... +Epoch [3505/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744279980659485, 'Val/mean miou_metric': 0.9605998992919922, 'Val/mean f1': 0.9763742685317993, 'Val/mean precision': 0.973539412021637, 'Val/mean recall': 0.9792255759239197, 'Val/mean hd95_metric': 4.84425687789917} +Epoch [3506/4000] Training [1/16] Loss: 0.00274 +Epoch [3506/4000] Training [2/16] Loss: 0.00258 +Epoch [3506/4000] Training [3/16] Loss: 0.00260 +Epoch [3506/4000] Training [4/16] Loss: 0.00206 +Epoch [3506/4000] Training [5/16] Loss: 0.00335 +Epoch [3506/4000] Training [6/16] Loss: 0.00227 +Epoch [3506/4000] Training [7/16] Loss: 0.00287 +Epoch [3506/4000] Training [8/16] Loss: 0.00328 +Epoch [3506/4000] Training [9/16] Loss: 0.00250 +Epoch [3506/4000] Training [10/16] Loss: 0.00260 +Epoch [3506/4000] Training [11/16] Loss: 0.00261 +Epoch [3506/4000] Training [12/16] Loss: 0.00269 +Epoch [3506/4000] Training [13/16] Loss: 0.00244 +Epoch [3506/4000] Training [14/16] Loss: 0.00217 +Epoch [3506/4000] Training [15/16] Loss: 0.00289 +Epoch [3506/4000] Training [16/16] Loss: 0.00263 +Epoch [3506/4000] Training metric {'Train/mean dice_metric': 0.9986790418624878, 'Train/mean miou_metric': 0.997049868106842, 'Train/mean f1': 0.9928885698318481, 'Train/mean precision': 0.9875643849372864, 'Train/mean recall': 0.9982705116271973, 'Train/mean hd95_metric': 0.5509065389633179} +Epoch [3506/4000] Validation [1/4] Loss: 0.41768 focal_loss 0.35626 dice_loss 0.06142 +Epoch [3506/4000] Validation [2/4] Loss: 0.46921 focal_loss 0.35859 dice_loss 0.11062 +Epoch [3506/4000] Validation [3/4] Loss: 0.26785 focal_loss 0.20481 dice_loss 0.06304 +Epoch [3506/4000] Validation [4/4] Loss: 0.34649 focal_loss 0.25811 dice_loss 0.08838 +Epoch [3506/4000] Validation metric {'Val/mean dice_metric': 0.9742667078971863, 'Val/mean miou_metric': 0.9604641199111938, 'Val/mean f1': 0.9760476350784302, 'Val/mean precision': 0.9730886220932007, 'Val/mean recall': 0.9790246486663818, 'Val/mean hd95_metric': 4.8320231437683105} +Cheakpoint... +Epoch [3506/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742667078971863, 'Val/mean miou_metric': 0.9604641199111938, 'Val/mean f1': 0.9760476350784302, 'Val/mean precision': 0.9730886220932007, 'Val/mean recall': 0.9790246486663818, 'Val/mean hd95_metric': 4.8320231437683105} +Epoch [3507/4000] Training [1/16] Loss: 0.00270 +Epoch [3507/4000] Training [2/16] Loss: 0.00263 +Epoch [3507/4000] Training [3/16] Loss: 0.00225 +Epoch [3507/4000] Training [4/16] Loss: 0.00288 +Epoch [3507/4000] Training [5/16] Loss: 0.00230 +Epoch [3507/4000] Training [6/16] Loss: 0.00216 +Epoch [3507/4000] Training [7/16] Loss: 0.00202 +Epoch [3507/4000] Training [8/16] Loss: 0.00255 +Epoch [3507/4000] Training [9/16] Loss: 0.00346 +Epoch [3507/4000] Training [10/16] Loss: 0.00180 +Epoch [3507/4000] Training [11/16] Loss: 0.00249 +Epoch [3507/4000] Training [12/16] Loss: 0.00196 +Epoch [3507/4000] Training [13/16] Loss: 0.00246 +Epoch [3507/4000] Training [14/16] Loss: 0.00341 +Epoch [3507/4000] Training [15/16] Loss: 0.00190 +Epoch [3507/4000] Training [16/16] Loss: 0.00317 +Epoch [3507/4000] Training metric {'Train/mean dice_metric': 0.9987400770187378, 'Train/mean miou_metric': 0.9971852898597717, 'Train/mean f1': 0.9936146140098572, 'Train/mean precision': 0.9889807105064392, 'Train/mean recall': 0.9982922077178955, 'Train/mean hd95_metric': 0.5489533543586731} +Epoch [3507/4000] Validation [1/4] Loss: 0.37445 focal_loss 0.31351 dice_loss 0.06094 +Epoch [3507/4000] Validation [2/4] Loss: 0.71632 focal_loss 0.50561 dice_loss 0.21071 +Epoch [3507/4000] Validation [3/4] Loss: 0.26002 focal_loss 0.20142 dice_loss 0.05860 +Epoch [3507/4000] Validation [4/4] Loss: 0.34351 focal_loss 0.25601 dice_loss 0.08750 +Epoch [3507/4000] Validation metric {'Val/mean dice_metric': 0.9735618829727173, 'Val/mean miou_metric': 0.9597846865653992, 'Val/mean f1': 0.9755256772041321, 'Val/mean precision': 0.9715346693992615, 'Val/mean recall': 0.9795495867729187, 'Val/mean hd95_metric': 5.345065116882324} +Cheakpoint... +Epoch [3507/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735618829727173, 'Val/mean miou_metric': 0.9597846865653992, 'Val/mean f1': 0.9755256772041321, 'Val/mean precision': 0.9715346693992615, 'Val/mean recall': 0.9795495867729187, 'Val/mean hd95_metric': 5.345065116882324} +Epoch [3508/4000] Training [1/16] Loss: 0.00195 +Epoch [3508/4000] Training [2/16] Loss: 0.00194 +Epoch [3508/4000] Training [3/16] Loss: 0.00229 +Epoch [3508/4000] Training [4/16] Loss: 0.00190 +Epoch [3508/4000] Training [5/16] Loss: 0.00256 +Epoch [3508/4000] Training [6/16] Loss: 0.00233 +Epoch [3508/4000] Training [7/16] Loss: 0.00210 +Epoch [3508/4000] Training [8/16] Loss: 0.00227 +Epoch [3508/4000] Training [9/16] Loss: 0.00234 +Epoch [3508/4000] Training [10/16] Loss: 0.00211 +Epoch [3508/4000] Training [11/16] Loss: 0.00326 +Epoch [3508/4000] Training [12/16] Loss: 0.00415 +Epoch [3508/4000] Training [13/16] Loss: 0.00376 +Epoch [3508/4000] Training [14/16] Loss: 0.00222 +Epoch [3508/4000] Training [15/16] Loss: 0.00251 +Epoch [3508/4000] Training [16/16] Loss: 0.00230 +Epoch [3508/4000] Training metric {'Train/mean dice_metric': 0.9986575841903687, 'Train/mean miou_metric': 0.9970446228981018, 'Train/mean f1': 0.9936906695365906, 'Train/mean precision': 0.9891200661659241, 'Train/mean recall': 0.9983037114143372, 'Train/mean hd95_metric': 0.600418210029602} +Epoch [3508/4000] Validation [1/4] Loss: 0.37891 focal_loss 0.31682 dice_loss 0.06209 +Epoch [3508/4000] Validation [2/4] Loss: 0.46163 focal_loss 0.35466 dice_loss 0.10697 +Epoch [3508/4000] Validation [3/4] Loss: 0.52328 focal_loss 0.43244 dice_loss 0.09084 +Epoch [3508/4000] Validation [4/4] Loss: 0.35833 focal_loss 0.27012 dice_loss 0.08820 +Epoch [3508/4000] Validation metric {'Val/mean dice_metric': 0.9750917553901672, 'Val/mean miou_metric': 0.9611635208129883, 'Val/mean f1': 0.9765629768371582, 'Val/mean precision': 0.974023699760437, 'Val/mean recall': 0.9791155457496643, 'Val/mean hd95_metric': 4.633462905883789} +Cheakpoint... +Epoch [3508/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750917553901672, 'Val/mean miou_metric': 0.9611635208129883, 'Val/mean f1': 0.9765629768371582, 'Val/mean precision': 0.974023699760437, 'Val/mean recall': 0.9791155457496643, 'Val/mean hd95_metric': 4.633462905883789} +Epoch [3509/4000] Training [1/16] Loss: 0.00163 +Epoch [3509/4000] Training [2/16] Loss: 0.00252 +Epoch [3509/4000] Training [3/16] Loss: 0.00333 +Epoch [3509/4000] Training [4/16] Loss: 0.00212 +Epoch [3509/4000] Training [5/16] Loss: 0.00326 +Epoch [3509/4000] Training [6/16] Loss: 0.00267 +Epoch [3509/4000] Training [7/16] Loss: 0.00354 +Epoch [3509/4000] Training [8/16] Loss: 0.00228 +Epoch [3509/4000] Training [9/16] Loss: 0.00207 +Epoch [3509/4000] Training [10/16] Loss: 0.00272 +Epoch [3509/4000] Training [11/16] Loss: 0.00404 +Epoch [3509/4000] Training [12/16] Loss: 0.00227 +Epoch [3509/4000] Training [13/16] Loss: 0.00204 +Epoch [3509/4000] Training [14/16] Loss: 0.00237 +Epoch [3509/4000] Training [15/16] Loss: 0.00322 +Epoch [3509/4000] Training [16/16] Loss: 0.00231 +Epoch [3509/4000] Training metric {'Train/mean dice_metric': 0.9980251789093018, 'Train/mean miou_metric': 0.9960318803787231, 'Train/mean f1': 0.9933654069900513, 'Train/mean precision': 0.9885939359664917, 'Train/mean recall': 0.9981832504272461, 'Train/mean hd95_metric': 0.7704641819000244} +Epoch [3509/4000] Validation [1/4] Loss: 0.47971 focal_loss 0.41304 dice_loss 0.06667 +Epoch [3509/4000] Validation [2/4] Loss: 0.49208 focal_loss 0.38025 dice_loss 0.11183 +Epoch [3509/4000] Validation [3/4] Loss: 0.28014 focal_loss 0.21762 dice_loss 0.06251 +Epoch [3509/4000] Validation [4/4] Loss: 0.31268 focal_loss 0.21839 dice_loss 0.09429 +Epoch [3509/4000] Validation metric {'Val/mean dice_metric': 0.9746105074882507, 'Val/mean miou_metric': 0.9602359533309937, 'Val/mean f1': 0.9764919281005859, 'Val/mean precision': 0.9745208024978638, 'Val/mean recall': 0.9784711599349976, 'Val/mean hd95_metric': 4.743104457855225} +Cheakpoint... +Epoch [3509/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746105074882507, 'Val/mean miou_metric': 0.9602359533309937, 'Val/mean f1': 0.9764919281005859, 'Val/mean precision': 0.9745208024978638, 'Val/mean recall': 0.9784711599349976, 'Val/mean hd95_metric': 4.743104457855225} +Epoch [3510/4000] Training [1/16] Loss: 0.00304 +Epoch [3510/4000] Training [2/16] Loss: 0.00415 +Epoch [3510/4000] Training [3/16] Loss: 0.00230 +Epoch [3510/4000] Training [4/16] Loss: 0.00282 +Epoch [3510/4000] Training [5/16] Loss: 0.00291 +Epoch [3510/4000] Training [6/16] Loss: 0.00249 +Epoch [3510/4000] Training [7/16] Loss: 0.00337 +Epoch [3510/4000] Training [8/16] Loss: 0.00235 +Epoch [3510/4000] Training [9/16] Loss: 0.00242 +Epoch [3510/4000] Training [10/16] Loss: 0.00429 +Epoch [3510/4000] Training [11/16] Loss: 0.00226 +Epoch [3510/4000] Training [12/16] Loss: 0.00247 +Epoch [3510/4000] Training [13/16] Loss: 0.00179 +Epoch [3510/4000] Training [14/16] Loss: 0.00233 +Epoch [3510/4000] Training [15/16] Loss: 0.00265 +Epoch [3510/4000] Training [16/16] Loss: 0.00208 +Epoch [3510/4000] Training metric {'Train/mean dice_metric': 0.9985520839691162, 'Train/mean miou_metric': 0.9968212842941284, 'Train/mean f1': 0.9933705925941467, 'Train/mean precision': 0.9886537790298462, 'Train/mean recall': 0.998132586479187, 'Train/mean hd95_metric': 0.610379159450531} +Epoch [3510/4000] Validation [1/4] Loss: 0.44033 focal_loss 0.37401 dice_loss 0.06632 +Epoch [3510/4000] Validation [2/4] Loss: 0.96041 focal_loss 0.77611 dice_loss 0.18431 +Epoch [3510/4000] Validation [3/4] Loss: 0.51610 focal_loss 0.42526 dice_loss 0.09084 +Epoch [3510/4000] Validation [4/4] Loss: 0.49112 focal_loss 0.36923 dice_loss 0.12189 +Epoch [3510/4000] Validation metric {'Val/mean dice_metric': 0.9730607867240906, 'Val/mean miou_metric': 0.9590304493904114, 'Val/mean f1': 0.9755088686943054, 'Val/mean precision': 0.9745155572891235, 'Val/mean recall': 0.9765041470527649, 'Val/mean hd95_metric': 4.704799175262451} +Cheakpoint... +Epoch [3510/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730607867240906, 'Val/mean miou_metric': 0.9590304493904114, 'Val/mean f1': 0.9755088686943054, 'Val/mean precision': 0.9745155572891235, 'Val/mean recall': 0.9765041470527649, 'Val/mean hd95_metric': 4.704799175262451} +Epoch [3511/4000] Training [1/16] Loss: 0.00170 +Epoch [3511/4000] Training [2/16] Loss: 0.00207 +Epoch [3511/4000] Training [3/16] Loss: 0.00220 +Epoch [3511/4000] Training [4/16] Loss: 0.00244 +Epoch [3511/4000] Training [5/16] Loss: 0.00253 +Epoch [3511/4000] Training [6/16] Loss: 0.00231 +Epoch [3511/4000] Training [7/16] Loss: 0.00221 +Epoch [3511/4000] Training [8/16] Loss: 0.00339 +Epoch [3511/4000] Training [9/16] Loss: 0.00231 +Epoch [3511/4000] Training [10/16] Loss: 0.00280 +Epoch [3511/4000] Training [11/16] Loss: 0.00274 +Epoch [3511/4000] Training [12/16] Loss: 0.00282 +Epoch [3511/4000] Training [13/16] Loss: 0.00143 +Epoch [3511/4000] Training [14/16] Loss: 0.00246 +Epoch [3511/4000] Training [15/16] Loss: 0.00173 +Epoch [3511/4000] Training [16/16] Loss: 0.00150 +Epoch [3511/4000] Training metric {'Train/mean dice_metric': 0.9988452196121216, 'Train/mean miou_metric': 0.997417688369751, 'Train/mean f1': 0.9938840270042419, 'Train/mean precision': 0.9893905520439148, 'Train/mean recall': 0.9984185099601746, 'Train/mean hd95_metric': 0.4999576807022095} +Epoch [3511/4000] Validation [1/4] Loss: 0.42279 focal_loss 0.35792 dice_loss 0.06487 +Epoch [3511/4000] Validation [2/4] Loss: 0.56245 focal_loss 0.41818 dice_loss 0.14427 +Epoch [3511/4000] Validation [3/4] Loss: 0.50848 focal_loss 0.41871 dice_loss 0.08977 +Epoch [3511/4000] Validation [4/4] Loss: 0.37477 focal_loss 0.26945 dice_loss 0.10532 +Epoch [3511/4000] Validation metric {'Val/mean dice_metric': 0.9731743931770325, 'Val/mean miou_metric': 0.959311306476593, 'Val/mean f1': 0.9758287668228149, 'Val/mean precision': 0.9745386242866516, 'Val/mean recall': 0.9771223664283752, 'Val/mean hd95_metric': 4.87724494934082} +Cheakpoint... +Epoch [3511/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731743931770325, 'Val/mean miou_metric': 0.959311306476593, 'Val/mean f1': 0.9758287668228149, 'Val/mean precision': 0.9745386242866516, 'Val/mean recall': 0.9771223664283752, 'Val/mean hd95_metric': 4.87724494934082} +Epoch [3512/4000] Training [1/16] Loss: 0.00252 +Epoch [3512/4000] Training [2/16] Loss: 0.00280 +Epoch [3512/4000] Training [3/16] Loss: 0.00199 +Epoch [3512/4000] Training [4/16] Loss: 0.00343 +Epoch [3512/4000] Training [5/16] Loss: 0.00315 +Epoch [3512/4000] Training [6/16] Loss: 0.00223 +Epoch [3512/4000] Training [7/16] Loss: 0.00329 +Epoch [3512/4000] Training [8/16] Loss: 0.00236 +Epoch [3512/4000] Training [9/16] Loss: 0.00295 +Epoch [3512/4000] Training [10/16] Loss: 0.00303 +Epoch [3512/4000] Training [11/16] Loss: 0.00212 +Epoch [3512/4000] Training [12/16] Loss: 0.00418 +Epoch [3512/4000] Training [13/16] Loss: 0.00239 +Epoch [3512/4000] Training [14/16] Loss: 0.00297 +Epoch [3512/4000] Training [15/16] Loss: 0.00329 +Epoch [3512/4000] Training [16/16] Loss: 0.00282 +Epoch [3512/4000] Training metric {'Train/mean dice_metric': 0.9985833168029785, 'Train/mean miou_metric': 0.9968713521957397, 'Train/mean f1': 0.9934099912643433, 'Train/mean precision': 0.9886853694915771, 'Train/mean recall': 0.9981799721717834, 'Train/mean hd95_metric': 0.5551058053970337} +Epoch [3512/4000] Validation [1/4] Loss: 0.34587 focal_loss 0.28900 dice_loss 0.05687 +Epoch [3512/4000] Validation [2/4] Loss: 1.04786 focal_loss 0.79893 dice_loss 0.24893 +Epoch [3512/4000] Validation [3/4] Loss: 0.53441 focal_loss 0.44203 dice_loss 0.09238 +Epoch [3512/4000] Validation [4/4] Loss: 0.51367 focal_loss 0.39736 dice_loss 0.11631 +Epoch [3512/4000] Validation metric {'Val/mean dice_metric': 0.9721430540084839, 'Val/mean miou_metric': 0.9578143358230591, 'Val/mean f1': 0.9751647710800171, 'Val/mean precision': 0.9729759693145752, 'Val/mean recall': 0.9773633480072021, 'Val/mean hd95_metric': 5.475275993347168} +Cheakpoint... +Epoch [3512/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9721], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721430540084839, 'Val/mean miou_metric': 0.9578143358230591, 'Val/mean f1': 0.9751647710800171, 'Val/mean precision': 0.9729759693145752, 'Val/mean recall': 0.9773633480072021, 'Val/mean hd95_metric': 5.475275993347168} +Epoch [3513/4000] Training [1/16] Loss: 0.00450 +Epoch [3513/4000] Training [2/16] Loss: 0.00372 +Epoch [3513/4000] Training [3/16] Loss: 0.00365 +Epoch [3513/4000] Training [4/16] Loss: 0.00250 +Epoch [3513/4000] Training [5/16] Loss: 0.00327 +Epoch [3513/4000] Training [6/16] Loss: 0.00284 +Epoch [3513/4000] Training [7/16] Loss: 0.00336 +Epoch [3513/4000] Training [8/16] Loss: 0.00287 +Epoch [3513/4000] Training [9/16] Loss: 0.00277 +Epoch [3513/4000] Training [10/16] Loss: 0.00248 +Epoch [3513/4000] Training [11/16] Loss: 0.00338 +Epoch [3513/4000] Training [12/16] Loss: 0.00202 +Epoch [3513/4000] Training [13/16] Loss: 0.00284 +Epoch [3513/4000] Training [14/16] Loss: 0.00380 +Epoch [3513/4000] Training [15/16] Loss: 0.00224 +Epoch [3513/4000] Training [16/16] Loss: 0.00384 +Epoch [3513/4000] Training metric {'Train/mean dice_metric': 0.9984382390975952, 'Train/mean miou_metric': 0.9966015815734863, 'Train/mean f1': 0.9934742450714111, 'Train/mean precision': 0.9889160990715027, 'Train/mean recall': 0.9980745911598206, 'Train/mean hd95_metric': 0.5854768753051758} +Epoch [3513/4000] Validation [1/4] Loss: 0.40903 focal_loss 0.34675 dice_loss 0.06228 +Epoch [3513/4000] Validation [2/4] Loss: 0.56469 focal_loss 0.40563 dice_loss 0.15906 +Epoch [3513/4000] Validation [3/4] Loss: 0.53965 focal_loss 0.44758 dice_loss 0.09208 +Epoch [3513/4000] Validation [4/4] Loss: 0.39433 focal_loss 0.28369 dice_loss 0.11064 +Epoch [3513/4000] Validation metric {'Val/mean dice_metric': 0.973465085029602, 'Val/mean miou_metric': 0.9587356448173523, 'Val/mean f1': 0.9755868315696716, 'Val/mean precision': 0.9727985262870789, 'Val/mean recall': 0.9783909916877747, 'Val/mean hd95_metric': 5.150259017944336} +Cheakpoint... +Epoch [3513/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973465085029602, 'Val/mean miou_metric': 0.9587356448173523, 'Val/mean f1': 0.9755868315696716, 'Val/mean precision': 0.9727985262870789, 'Val/mean recall': 0.9783909916877747, 'Val/mean hd95_metric': 5.150259017944336} +Epoch [3514/4000] Training [1/16] Loss: 0.00349 +Epoch [3514/4000] Training [2/16] Loss: 0.00221 +Epoch [3514/4000] Training [3/16] Loss: 0.00235 +Epoch [3514/4000] Training [4/16] Loss: 0.00225 +Epoch [3514/4000] Training [5/16] Loss: 0.00204 +Epoch [3514/4000] Training [6/16] Loss: 0.00210 +Epoch [3514/4000] Training [7/16] Loss: 0.00265 +Epoch [3514/4000] Training [8/16] Loss: 0.00198 +Epoch [3514/4000] Training [9/16] Loss: 0.00255 +Epoch [3514/4000] Training [10/16] Loss: 0.00333 +Epoch [3514/4000] Training [11/16] Loss: 0.00323 +Epoch [3514/4000] Training [12/16] Loss: 0.00345 +Epoch [3514/4000] Training [13/16] Loss: 0.00210 +Epoch [3514/4000] Training [14/16] Loss: 0.00271 +Epoch [3514/4000] Training [15/16] Loss: 0.00448 +Epoch [3514/4000] Training [16/16] Loss: 0.00203 +Epoch [3514/4000] Training metric {'Train/mean dice_metric': 0.9986797571182251, 'Train/mean miou_metric': 0.9970823526382446, 'Train/mean f1': 0.9937488436698914, 'Train/mean precision': 0.9892275333404541, 'Train/mean recall': 0.9983116388320923, 'Train/mean hd95_metric': 0.5489112734794617} +Epoch [3514/4000] Validation [1/4] Loss: 0.36522 focal_loss 0.30089 dice_loss 0.06433 +Epoch [3514/4000] Validation [2/4] Loss: 1.44753 focal_loss 1.15073 dice_loss 0.29680 +Epoch [3514/4000] Validation [3/4] Loss: 0.50803 focal_loss 0.42005 dice_loss 0.08798 +Epoch [3514/4000] Validation [4/4] Loss: 0.33783 focal_loss 0.24931 dice_loss 0.08851 +Epoch [3514/4000] Validation metric {'Val/mean dice_metric': 0.9727908968925476, 'Val/mean miou_metric': 0.9592221975326538, 'Val/mean f1': 0.9755775332450867, 'Val/mean precision': 0.9735012650489807, 'Val/mean recall': 0.9776626229286194, 'Val/mean hd95_metric': 5.216122150421143} +Cheakpoint... +Epoch [3514/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727908968925476, 'Val/mean miou_metric': 0.9592221975326538, 'Val/mean f1': 0.9755775332450867, 'Val/mean precision': 0.9735012650489807, 'Val/mean recall': 0.9776626229286194, 'Val/mean hd95_metric': 5.216122150421143} +Epoch [3515/4000] Training [1/16] Loss: 0.00228 +Epoch [3515/4000] Training [2/16] Loss: 0.00249 +Epoch [3515/4000] Training [3/16] Loss: 0.00266 +Epoch [3515/4000] Training [4/16] Loss: 0.00393 +Epoch [3515/4000] Training [5/16] Loss: 0.00199 +Epoch [3515/4000] Training [6/16] Loss: 0.00176 +Epoch [3515/4000] Training [7/16] Loss: 0.00353 +Epoch [3515/4000] Training [8/16] Loss: 0.00241 +Epoch [3515/4000] Training [9/16] Loss: 0.00332 +Epoch [3515/4000] Training [10/16] Loss: 0.00217 +Epoch [3515/4000] Training [11/16] Loss: 0.00200 +Epoch [3515/4000] Training [12/16] Loss: 0.00190 +Epoch [3515/4000] Training [13/16] Loss: 0.00279 +Epoch [3515/4000] Training [14/16] Loss: 0.00269 +Epoch [3515/4000] Training [15/16] Loss: 0.00251 +Epoch [3515/4000] Training [16/16] Loss: 0.00227 +Epoch [3515/4000] Training metric {'Train/mean dice_metric': 0.9987142086029053, 'Train/mean miou_metric': 0.9971539974212646, 'Train/mean f1': 0.9937518835067749, 'Train/mean precision': 0.9891851544380188, 'Train/mean recall': 0.9983608722686768, 'Train/mean hd95_metric': 0.6004458665847778} +Epoch [3515/4000] Validation [1/4] Loss: 0.45838 focal_loss 0.39441 dice_loss 0.06397 +Epoch [3515/4000] Validation [2/4] Loss: 1.45246 focal_loss 1.15644 dice_loss 0.29602 +Epoch [3515/4000] Validation [3/4] Loss: 0.51443 focal_loss 0.42382 dice_loss 0.09061 +Epoch [3515/4000] Validation [4/4] Loss: 0.35947 focal_loss 0.25593 dice_loss 0.10353 +Epoch [3515/4000] Validation metric {'Val/mean dice_metric': 0.9717861413955688, 'Val/mean miou_metric': 0.9581149816513062, 'Val/mean f1': 0.9754926562309265, 'Val/mean precision': 0.973421573638916, 'Val/mean recall': 0.977572500705719, 'Val/mean hd95_metric': 5.32526969909668} +Cheakpoint... +Epoch [3515/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9717861413955688, 'Val/mean miou_metric': 0.9581149816513062, 'Val/mean f1': 0.9754926562309265, 'Val/mean precision': 0.973421573638916, 'Val/mean recall': 0.977572500705719, 'Val/mean hd95_metric': 5.32526969909668} +Epoch [3516/4000] Training [1/16] Loss: 0.00206 +Epoch [3516/4000] Training [2/16] Loss: 0.00367 +Epoch [3516/4000] Training [3/16] Loss: 0.00275 +Epoch [3516/4000] Training [4/16] Loss: 0.00287 +Epoch [3516/4000] Training [5/16] Loss: 0.00289 +Epoch [3516/4000] Training [6/16] Loss: 0.00371 +Epoch [3516/4000] Training [7/16] Loss: 0.00188 +Epoch [3516/4000] Training [8/16] Loss: 0.00248 +Epoch [3516/4000] Training [9/16] Loss: 0.00155 +Epoch [3516/4000] Training [10/16] Loss: 0.00198 +Epoch [3516/4000] Training [11/16] Loss: 0.00229 +Epoch [3516/4000] Training [12/16] Loss: 0.00178 +Epoch [3516/4000] Training [13/16] Loss: 0.00224 +Epoch [3516/4000] Training [14/16] Loss: 0.00257 +Epoch [3516/4000] Training [15/16] Loss: 0.00286 +Epoch [3516/4000] Training [16/16] Loss: 0.00249 +Epoch [3516/4000] Training metric {'Train/mean dice_metric': 0.9987094402313232, 'Train/mean miou_metric': 0.9971480965614319, 'Train/mean f1': 0.9937342405319214, 'Train/mean precision': 0.9891943335533142, 'Train/mean recall': 0.9983159899711609, 'Train/mean hd95_metric': 0.5798404216766357} +Epoch [3516/4000] Validation [1/4] Loss: 0.43399 focal_loss 0.36867 dice_loss 0.06532 +Epoch [3516/4000] Validation [2/4] Loss: 0.51167 focal_loss 0.39809 dice_loss 0.11358 +Epoch [3516/4000] Validation [3/4] Loss: 0.54800 focal_loss 0.44640 dice_loss 0.10159 +Epoch [3516/4000] Validation [4/4] Loss: 0.47574 focal_loss 0.36496 dice_loss 0.11078 +Epoch [3516/4000] Validation metric {'Val/mean dice_metric': 0.9746597409248352, 'Val/mean miou_metric': 0.9600964784622192, 'Val/mean f1': 0.9760650992393494, 'Val/mean precision': 0.9744361639022827, 'Val/mean recall': 0.9776995182037354, 'Val/mean hd95_metric': 4.698143482208252} +Cheakpoint... +Epoch [3516/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746597409248352, 'Val/mean miou_metric': 0.9600964784622192, 'Val/mean f1': 0.9760650992393494, 'Val/mean precision': 0.9744361639022827, 'Val/mean recall': 0.9776995182037354, 'Val/mean hd95_metric': 4.698143482208252} +Epoch [3517/4000] Training [1/16] Loss: 0.00250 +Epoch [3517/4000] Training [2/16] Loss: 0.00238 +Epoch [3517/4000] Training [3/16] Loss: 0.00233 +Epoch [3517/4000] Training [4/16] Loss: 0.00394 +Epoch [3517/4000] Training [5/16] Loss: 0.00228 +Epoch [3517/4000] Training [6/16] Loss: 0.00186 +Epoch [3517/4000] Training [7/16] Loss: 0.00243 +Epoch [3517/4000] Training [8/16] Loss: 0.00175 +Epoch [3517/4000] Training [9/16] Loss: 0.00210 +Epoch [3517/4000] Training [10/16] Loss: 0.00338 +Epoch [3517/4000] Training [11/16] Loss: 0.00192 +Epoch [3517/4000] Training [12/16] Loss: 0.00242 +Epoch [3517/4000] Training [13/16] Loss: 0.00201 +Epoch [3517/4000] Training [14/16] Loss: 0.00190 +Epoch [3517/4000] Training [15/16] Loss: 0.00302 +Epoch [3517/4000] Training [16/16] Loss: 0.00217 +Epoch [3517/4000] Training metric {'Train/mean dice_metric': 0.9988215565681458, 'Train/mean miou_metric': 0.9973524808883667, 'Train/mean f1': 0.9935426115989685, 'Train/mean precision': 0.9888065457344055, 'Train/mean recall': 0.9983243346214294, 'Train/mean hd95_metric': 0.5292545557022095} +Epoch [3517/4000] Validation [1/4] Loss: 0.41796 focal_loss 0.34581 dice_loss 0.07215 +Epoch [3517/4000] Validation [2/4] Loss: 0.52600 focal_loss 0.39287 dice_loss 0.13314 +Epoch [3517/4000] Validation [3/4] Loss: 0.53933 focal_loss 0.44589 dice_loss 0.09343 +Epoch [3517/4000] Validation [4/4] Loss: 0.35577 focal_loss 0.26679 dice_loss 0.08899 +Epoch [3517/4000] Validation metric {'Val/mean dice_metric': 0.9743146896362305, 'Val/mean miou_metric': 0.9601227641105652, 'Val/mean f1': 0.9759933948516846, 'Val/mean precision': 0.9735331535339355, 'Val/mean recall': 0.9784660935401917, 'Val/mean hd95_metric': 4.8743438720703125} +Cheakpoint... +Epoch [3517/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743146896362305, 'Val/mean miou_metric': 0.9601227641105652, 'Val/mean f1': 0.9759933948516846, 'Val/mean precision': 0.9735331535339355, 'Val/mean recall': 0.9784660935401917, 'Val/mean hd95_metric': 4.8743438720703125} +Epoch [3518/4000] Training [1/16] Loss: 0.00260 +Epoch [3518/4000] Training [2/16] Loss: 0.00280 +Epoch [3518/4000] Training [3/16] Loss: 0.00222 +Epoch [3518/4000] Training [4/16] Loss: 0.03061 +Epoch [3518/4000] Training [5/16] Loss: 0.00449 +Epoch [3518/4000] Training [6/16] Loss: 0.00192 +Epoch [3518/4000] Training [7/16] Loss: 0.00219 +Epoch [3518/4000] Training [8/16] Loss: 0.00408 +Epoch [3518/4000] Training [9/16] Loss: 0.00373 +Epoch [3518/4000] Training [10/16] Loss: 0.00388 +Epoch [3518/4000] Training [11/16] Loss: 0.00168 +Epoch [3518/4000] Training [12/16] Loss: 0.00215 +Epoch [3518/4000] Training [13/16] Loss: 0.00308 +Epoch [3518/4000] Training [14/16] Loss: 0.00218 +Epoch [3518/4000] Training [15/16] Loss: 0.00167 +Epoch [3518/4000] Training [16/16] Loss: 0.00207 +Epoch [3518/4000] Training metric {'Train/mean dice_metric': 0.9983843564987183, 'Train/mean miou_metric': 0.9965673685073853, 'Train/mean f1': 0.9937505125999451, 'Train/mean precision': 0.989109456539154, 'Train/mean recall': 0.9984353184700012, 'Train/mean hd95_metric': 0.570268988609314} +Epoch [3518/4000] Validation [1/4] Loss: 0.48876 focal_loss 0.42022 dice_loss 0.06854 +Epoch [3518/4000] Validation [2/4] Loss: 0.48066 focal_loss 0.36996 dice_loss 0.11070 +Epoch [3518/4000] Validation [3/4] Loss: 0.53306 focal_loss 0.44382 dice_loss 0.08924 +Epoch [3518/4000] Validation [4/4] Loss: 0.44724 focal_loss 0.34276 dice_loss 0.10448 +Epoch [3518/4000] Validation metric {'Val/mean dice_metric': 0.972973644733429, 'Val/mean miou_metric': 0.9587668180465698, 'Val/mean f1': 0.9761016368865967, 'Val/mean precision': 0.9748048782348633, 'Val/mean recall': 0.9774019122123718, 'Val/mean hd95_metric': 5.227614402770996} +Cheakpoint... +Epoch [3518/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972973644733429, 'Val/mean miou_metric': 0.9587668180465698, 'Val/mean f1': 0.9761016368865967, 'Val/mean precision': 0.9748048782348633, 'Val/mean recall': 0.9774019122123718, 'Val/mean hd95_metric': 5.227614402770996} +Epoch [3519/4000] Training [1/16] Loss: 0.00179 +Epoch [3519/4000] Training [2/16] Loss: 0.00232 +Epoch [3519/4000] Training [3/16] Loss: 0.00277 +Epoch [3519/4000] Training [4/16] Loss: 0.00200 +Epoch [3519/4000] Training [5/16] Loss: 0.00213 +Epoch [3519/4000] Training [6/16] Loss: 0.00338 +Epoch [3519/4000] Training [7/16] Loss: 0.00159 +Epoch [3519/4000] Training [8/16] Loss: 0.00197 +Epoch [3519/4000] Training [9/16] Loss: 0.00225 +Epoch [3519/4000] Training [10/16] Loss: 0.00218 +Epoch [3519/4000] Training [11/16] Loss: 0.00220 +Epoch [3519/4000] Training [12/16] Loss: 0.00203 +Epoch [3519/4000] Training [13/16] Loss: 0.00227 +Epoch [3519/4000] Training [14/16] Loss: 0.00561 +Epoch [3519/4000] Training [15/16] Loss: 0.00429 +Epoch [3519/4000] Training [16/16] Loss: 0.00226 +Epoch [3519/4000] Training metric {'Train/mean dice_metric': 0.9987021684646606, 'Train/mean miou_metric': 0.9971014261245728, 'Train/mean f1': 0.9929820895195007, 'Train/mean precision': 0.9878316521644592, 'Train/mean recall': 0.9981865286827087, 'Train/mean hd95_metric': 0.5479624271392822} +Epoch [3519/4000] Validation [1/4] Loss: 0.40904 focal_loss 0.34292 dice_loss 0.06612 +Epoch [3519/4000] Validation [2/4] Loss: 0.49423 focal_loss 0.38097 dice_loss 0.11326 +Epoch [3519/4000] Validation [3/4] Loss: 0.52408 focal_loss 0.43659 dice_loss 0.08748 +Epoch [3519/4000] Validation [4/4] Loss: 0.39415 focal_loss 0.29333 dice_loss 0.10082 +Epoch [3519/4000] Validation metric {'Val/mean dice_metric': 0.9745495915412903, 'Val/mean miou_metric': 0.9602544903755188, 'Val/mean f1': 0.9758937358856201, 'Val/mean precision': 0.9736202955245972, 'Val/mean recall': 0.9781778454780579, 'Val/mean hd95_metric': 4.587954998016357} +Cheakpoint... +Epoch [3519/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745495915412903, 'Val/mean miou_metric': 0.9602544903755188, 'Val/mean f1': 0.9758937358856201, 'Val/mean precision': 0.9736202955245972, 'Val/mean recall': 0.9781778454780579, 'Val/mean hd95_metric': 4.587954998016357} +Epoch [3520/4000] Training [1/16] Loss: 0.00180 +Epoch [3520/4000] Training [2/16] Loss: 0.00348 +Epoch [3520/4000] Training [3/16] Loss: 0.00377 +Epoch [3520/4000] Training [4/16] Loss: 0.00278 +Epoch [3520/4000] Training [5/16] Loss: 0.00260 +Epoch [3520/4000] Training [6/16] Loss: 0.00233 +Epoch [3520/4000] Training [7/16] Loss: 0.00202 +Epoch [3520/4000] Training [8/16] Loss: 0.00292 +Epoch [3520/4000] Training [9/16] Loss: 0.00237 +Epoch [3520/4000] Training [10/16] Loss: 0.00296 +Epoch [3520/4000] Training [11/16] Loss: 0.00211 +Epoch [3520/4000] Training [12/16] Loss: 0.00198 +Epoch [3520/4000] Training [13/16] Loss: 0.00226 +Epoch [3520/4000] Training [14/16] Loss: 0.00376 +Epoch [3520/4000] Training [15/16] Loss: 0.00218 +Epoch [3520/4000] Training [16/16] Loss: 0.00306 +Epoch [3520/4000] Training metric {'Train/mean dice_metric': 0.9986208081245422, 'Train/mean miou_metric': 0.9969684481620789, 'Train/mean f1': 0.9936084151268005, 'Train/mean precision': 0.9890202283859253, 'Train/mean recall': 0.9982394576072693, 'Train/mean hd95_metric': 0.6021061539649963} +Epoch [3520/4000] Validation [1/4] Loss: 0.39761 focal_loss 0.33152 dice_loss 0.06608 +Epoch [3520/4000] Validation [2/4] Loss: 0.51301 focal_loss 0.38376 dice_loss 0.12926 +Epoch [3520/4000] Validation [3/4] Loss: 0.51776 focal_loss 0.42161 dice_loss 0.09615 +Epoch [3520/4000] Validation [4/4] Loss: 0.35112 focal_loss 0.26287 dice_loss 0.08825 +Epoch [3520/4000] Validation metric {'Val/mean dice_metric': 0.9743515849113464, 'Val/mean miou_metric': 0.9600240588188171, 'Val/mean f1': 0.9761314988136292, 'Val/mean precision': 0.9733425378799438, 'Val/mean recall': 0.978936493396759, 'Val/mean hd95_metric': 5.057585716247559} +Cheakpoint... +Epoch [3520/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743515849113464, 'Val/mean miou_metric': 0.9600240588188171, 'Val/mean f1': 0.9761314988136292, 'Val/mean precision': 0.9733425378799438, 'Val/mean recall': 0.978936493396759, 'Val/mean hd95_metric': 5.057585716247559} +Epoch [3521/4000] Training [1/16] Loss: 0.00235 +Epoch [3521/4000] Training [2/16] Loss: 0.00363 +Epoch [3521/4000] Training [3/16] Loss: 0.00392 +Epoch [3521/4000] Training [4/16] Loss: 0.00169 +Epoch [3521/4000] Training [5/16] Loss: 0.00439 +Epoch [3521/4000] Training [6/16] Loss: 0.00185 +Epoch [3521/4000] Training [7/16] Loss: 0.00239 +Epoch [3521/4000] Training [8/16] Loss: 0.00239 +Epoch [3521/4000] Training [9/16] Loss: 0.00304 +Epoch [3521/4000] Training [10/16] Loss: 0.00259 +Epoch [3521/4000] Training [11/16] Loss: 0.00217 +Epoch [3521/4000] Training [12/16] Loss: 0.00246 +Epoch [3521/4000] Training [13/16] Loss: 0.00363 +Epoch [3521/4000] Training [14/16] Loss: 0.00194 +Epoch [3521/4000] Training [15/16] Loss: 0.00258 +Epoch [3521/4000] Training [16/16] Loss: 0.00278 +Epoch [3521/4000] Training metric {'Train/mean dice_metric': 0.998615562915802, 'Train/mean miou_metric': 0.9969558715820312, 'Train/mean f1': 0.9936107397079468, 'Train/mean precision': 0.9890329241752625, 'Train/mean recall': 0.9982311129570007, 'Train/mean hd95_metric': 0.5620865821838379} +Epoch [3521/4000] Validation [1/4] Loss: 0.36930 focal_loss 0.30932 dice_loss 0.05998 +Epoch [3521/4000] Validation [2/4] Loss: 0.49018 focal_loss 0.37919 dice_loss 0.11100 +Epoch [3521/4000] Validation [3/4] Loss: 0.53773 focal_loss 0.44475 dice_loss 0.09298 +Epoch [3521/4000] Validation [4/4] Loss: 0.30349 focal_loss 0.21446 dice_loss 0.08904 +Epoch [3521/4000] Validation metric {'Val/mean dice_metric': 0.9730035662651062, 'Val/mean miou_metric': 0.9591418504714966, 'Val/mean f1': 0.9758912920951843, 'Val/mean precision': 0.9745990037918091, 'Val/mean recall': 0.977186918258667, 'Val/mean hd95_metric': 4.978296279907227} +Cheakpoint... +Epoch [3521/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730035662651062, 'Val/mean miou_metric': 0.9591418504714966, 'Val/mean f1': 0.9758912920951843, 'Val/mean precision': 0.9745990037918091, 'Val/mean recall': 0.977186918258667, 'Val/mean hd95_metric': 4.978296279907227} +Epoch [3522/4000] Training [1/16] Loss: 0.00244 +Epoch [3522/4000] Training [2/16] Loss: 0.01236 +Epoch [3522/4000] Training [3/16] Loss: 0.00184 +Epoch [3522/4000] Training [4/16] Loss: 0.00172 +Epoch [3522/4000] Training [5/16] Loss: 0.00286 +Epoch [3522/4000] Training [6/16] Loss: 0.00191 +Epoch [3522/4000] Training [7/16] Loss: 0.00305 +Epoch [3522/4000] Training [8/16] Loss: 0.00168 +Epoch [3522/4000] Training [9/16] Loss: 0.00188 +Epoch [3522/4000] Training [10/16] Loss: 0.00241 +Epoch [3522/4000] Training [11/16] Loss: 0.00339 +Epoch [3522/4000] Training [12/16] Loss: 0.00349 +Epoch [3522/4000] Training [13/16] Loss: 0.00167 +Epoch [3522/4000] Training [14/16] Loss: 0.00244 +Epoch [3522/4000] Training [15/16] Loss: 0.35360 +Epoch [3522/4000] Training [16/16] Loss: 0.00316 +Epoch [3522/4000] Training metric {'Train/mean dice_metric': 0.9967955350875854, 'Train/mean miou_metric': 0.994612991809845, 'Train/mean f1': 0.9927103519439697, 'Train/mean precision': 0.9883634448051453, 'Train/mean recall': 0.9970956444740295, 'Train/mean hd95_metric': 0.8158739805221558} +Epoch [3522/4000] Validation [1/4] Loss: 0.35125 focal_loss 0.29370 dice_loss 0.05756 +Epoch [3522/4000] Validation [2/4] Loss: 1.53675 focal_loss 1.23843 dice_loss 0.29832 +Epoch [3522/4000] Validation [3/4] Loss: 0.57797 focal_loss 0.46986 dice_loss 0.10810 +Epoch [3522/4000] Validation [4/4] Loss: 0.39397 focal_loss 0.28640 dice_loss 0.10757 +Epoch [3522/4000] Validation metric {'Val/mean dice_metric': 0.970071017742157, 'Val/mean miou_metric': 0.955575168132782, 'Val/mean f1': 0.9739835858345032, 'Val/mean precision': 0.9724041223526001, 'Val/mean recall': 0.9755681753158569, 'Val/mean hd95_metric': 5.686227798461914} +Cheakpoint... +Epoch [3522/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9701], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.970071017742157, 'Val/mean miou_metric': 0.955575168132782, 'Val/mean f1': 0.9739835858345032, 'Val/mean precision': 0.9724041223526001, 'Val/mean recall': 0.9755681753158569, 'Val/mean hd95_metric': 5.686227798461914} +Epoch [3523/4000] Training [1/16] Loss: 0.00195 +Epoch [3523/4000] Training [2/16] Loss: 0.00306 +Epoch [3523/4000] Training [3/16] Loss: 0.00346 +Epoch [3523/4000] Training [4/16] Loss: 0.00220 +Epoch [3523/4000] Training [5/16] Loss: 0.00222 +Epoch [3523/4000] Training [6/16] Loss: 0.00261 +Epoch [3523/4000] Training [7/16] Loss: 0.00232 +Epoch [3523/4000] Training [8/16] Loss: 0.00387 +Epoch [3523/4000] Training [9/16] Loss: 0.00276 +Epoch [3523/4000] Training [10/16] Loss: 0.00222 +Epoch [3523/4000] Training [11/16] Loss: 0.00324 +Epoch [3523/4000] Training [12/16] Loss: 0.00247 +Epoch [3523/4000] Training [13/16] Loss: 0.00212 +Epoch [3523/4000] Training [14/16] Loss: 0.00217 +Epoch [3523/4000] Training [15/16] Loss: 0.00163 +Epoch [3523/4000] Training [16/16] Loss: 0.00183 +Epoch [3523/4000] Training metric {'Train/mean dice_metric': 0.998792827129364, 'Train/mean miou_metric': 0.9972872734069824, 'Train/mean f1': 0.9931021928787231, 'Train/mean precision': 0.987919270992279, 'Train/mean recall': 0.9983397722244263, 'Train/mean hd95_metric': 0.5177731513977051} +Epoch [3523/4000] Validation [1/4] Loss: 0.38767 focal_loss 0.32481 dice_loss 0.06286 +Epoch [3523/4000] Validation [2/4] Loss: 0.50272 focal_loss 0.38284 dice_loss 0.11987 +Epoch [3523/4000] Validation [3/4] Loss: 0.52637 focal_loss 0.43508 dice_loss 0.09130 +Epoch [3523/4000] Validation [4/4] Loss: 0.32487 focal_loss 0.22997 dice_loss 0.09490 +Epoch [3523/4000] Validation metric {'Val/mean dice_metric': 0.9735719561576843, 'Val/mean miou_metric': 0.9596394300460815, 'Val/mean f1': 0.9757127165794373, 'Val/mean precision': 0.9734384417533875, 'Val/mean recall': 0.9779976010322571, 'Val/mean hd95_metric': 4.699784278869629} +Cheakpoint... +Epoch [3523/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735719561576843, 'Val/mean miou_metric': 0.9596394300460815, 'Val/mean f1': 0.9757127165794373, 'Val/mean precision': 0.9734384417533875, 'Val/mean recall': 0.9779976010322571, 'Val/mean hd95_metric': 4.699784278869629} +Epoch [3524/4000] Training [1/16] Loss: 0.00260 +Epoch [3524/4000] Training [2/16] Loss: 0.00328 +Epoch [3524/4000] Training [3/16] Loss: 0.00504 +Epoch [3524/4000] Training [4/16] Loss: 0.00348 +Epoch [3524/4000] Training [5/16] Loss: 0.00341 +Epoch [3524/4000] Training [6/16] Loss: 0.00268 +Epoch [3524/4000] Training [7/16] Loss: 0.00210 +Epoch [3524/4000] Training [8/16] Loss: 0.00203 +Epoch [3524/4000] Training [9/16] Loss: 0.00310 +Epoch [3524/4000] Training [10/16] Loss: 0.00294 +Epoch [3524/4000] Training [11/16] Loss: 0.00281 +Epoch [3524/4000] Training [12/16] Loss: 0.00207 +Epoch [3524/4000] Training [13/16] Loss: 0.00277 +Epoch [3524/4000] Training [14/16] Loss: 0.00193 +Epoch [3524/4000] Training [15/16] Loss: 0.00171 +Epoch [3524/4000] Training [16/16] Loss: 0.00179 +Epoch [3524/4000] Training metric {'Train/mean dice_metric': 0.9986127614974976, 'Train/mean miou_metric': 0.9969378113746643, 'Train/mean f1': 0.9936035871505737, 'Train/mean precision': 0.9889033436775208, 'Train/mean recall': 0.9983487725257874, 'Train/mean hd95_metric': 0.5779573321342468} +Epoch [3524/4000] Validation [1/4] Loss: 0.40246 focal_loss 0.33723 dice_loss 0.06523 +Epoch [3524/4000] Validation [2/4] Loss: 0.47654 focal_loss 0.36469 dice_loss 0.11185 +Epoch [3524/4000] Validation [3/4] Loss: 0.28686 focal_loss 0.22587 dice_loss 0.06098 +Epoch [3524/4000] Validation [4/4] Loss: 0.38667 focal_loss 0.28405 dice_loss 0.10262 +Epoch [3524/4000] Validation metric {'Val/mean dice_metric': 0.9736379384994507, 'Val/mean miou_metric': 0.9595664143562317, 'Val/mean f1': 0.9758114218711853, 'Val/mean precision': 0.9745142459869385, 'Val/mean recall': 0.9771122336387634, 'Val/mean hd95_metric': 4.830770492553711} +Cheakpoint... +Epoch [3524/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736379384994507, 'Val/mean miou_metric': 0.9595664143562317, 'Val/mean f1': 0.9758114218711853, 'Val/mean precision': 0.9745142459869385, 'Val/mean recall': 0.9771122336387634, 'Val/mean hd95_metric': 4.830770492553711} +Epoch [3525/4000] Training [1/16] Loss: 0.00209 +Epoch [3525/4000] Training [2/16] Loss: 0.00264 +Epoch [3525/4000] Training [3/16] Loss: 0.00288 +Epoch [3525/4000] Training [4/16] Loss: 0.00285 +Epoch [3525/4000] Training [5/16] Loss: 0.00285 +Epoch [3525/4000] Training [6/16] Loss: 0.00225 +Epoch [3525/4000] Training [7/16] Loss: 0.00157 +Epoch [3525/4000] Training [8/16] Loss: 0.00334 +Epoch [3525/4000] Training [9/16] Loss: 0.00281 +Epoch [3525/4000] Training [10/16] Loss: 0.00311 +Epoch [3525/4000] Training [11/16] Loss: 0.00277 +Epoch [3525/4000] Training [12/16] Loss: 0.00191 +Epoch [3525/4000] Training [13/16] Loss: 0.00241 +Epoch [3525/4000] Training [14/16] Loss: 0.00185 +Epoch [3525/4000] Training [15/16] Loss: 0.00365 +Epoch [3525/4000] Training [16/16] Loss: 0.00200 +Epoch [3525/4000] Training metric {'Train/mean dice_metric': 0.998808741569519, 'Train/mean miou_metric': 0.9973416328430176, 'Train/mean f1': 0.9937627911567688, 'Train/mean precision': 0.9891661405563354, 'Train/mean recall': 0.9984022974967957, 'Train/mean hd95_metric': 0.5228791236877441} +Epoch [3525/4000] Validation [1/4] Loss: 0.43262 focal_loss 0.36754 dice_loss 0.06508 +Epoch [3525/4000] Validation [2/4] Loss: 0.50381 focal_loss 0.36492 dice_loss 0.13889 +Epoch [3525/4000] Validation [3/4] Loss: 0.52398 focal_loss 0.42909 dice_loss 0.09489 +Epoch [3525/4000] Validation [4/4] Loss: 0.36861 focal_loss 0.27426 dice_loss 0.09435 +Epoch [3525/4000] Validation metric {'Val/mean dice_metric': 0.9749504327774048, 'Val/mean miou_metric': 0.9603994488716125, 'Val/mean f1': 0.9760618209838867, 'Val/mean precision': 0.9738591909408569, 'Val/mean recall': 0.978274405002594, 'Val/mean hd95_metric': 4.864073276519775} +Cheakpoint... +Epoch [3525/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749504327774048, 'Val/mean miou_metric': 0.9603994488716125, 'Val/mean f1': 0.9760618209838867, 'Val/mean precision': 0.9738591909408569, 'Val/mean recall': 0.978274405002594, 'Val/mean hd95_metric': 4.864073276519775} +Epoch [3526/4000] Training [1/16] Loss: 0.00261 +Epoch [3526/4000] Training [2/16] Loss: 0.00227 +Epoch [3526/4000] Training [3/16] Loss: 0.00299 +Epoch [3526/4000] Training [4/16] Loss: 0.00260 +Epoch [3526/4000] Training [5/16] Loss: 0.00309 +Epoch [3526/4000] Training [6/16] Loss: 0.00200 +Epoch [3526/4000] Training [7/16] Loss: 0.00254 +Epoch [3526/4000] Training [8/16] Loss: 0.00277 +Epoch [3526/4000] Training [9/16] Loss: 0.00227 +Epoch [3526/4000] Training [10/16] Loss: 0.00177 +Epoch [3526/4000] Training [11/16] Loss: 0.00237 +Epoch [3526/4000] Training [12/16] Loss: 0.00255 +Epoch [3526/4000] Training [13/16] Loss: 0.00236 +Epoch [3526/4000] Training [14/16] Loss: 0.00236 +Epoch [3526/4000] Training [15/16] Loss: 0.00194 +Epoch [3526/4000] Training [16/16] Loss: 0.00272 +Epoch [3526/4000] Training metric {'Train/mean dice_metric': 0.9987311363220215, 'Train/mean miou_metric': 0.9971796274185181, 'Train/mean f1': 0.9936964511871338, 'Train/mean precision': 0.9890812039375305, 'Train/mean recall': 0.9983550310134888, 'Train/mean hd95_metric': 0.5756135582923889} +Epoch [3526/4000] Validation [1/4] Loss: 0.40755 focal_loss 0.34091 dice_loss 0.06664 +Epoch [3526/4000] Validation [2/4] Loss: 0.48969 focal_loss 0.37228 dice_loss 0.11741 +Epoch [3526/4000] Validation [3/4] Loss: 0.31442 focal_loss 0.24759 dice_loss 0.06683 +Epoch [3526/4000] Validation [4/4] Loss: 0.32486 focal_loss 0.23870 dice_loss 0.08617 +Epoch [3526/4000] Validation metric {'Val/mean dice_metric': 0.9731338620185852, 'Val/mean miou_metric': 0.9594398736953735, 'Val/mean f1': 0.9760478138923645, 'Val/mean precision': 0.9750677347183228, 'Val/mean recall': 0.9770298600196838, 'Val/mean hd95_metric': 4.937185764312744} +Cheakpoint... +Epoch [3526/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731338620185852, 'Val/mean miou_metric': 0.9594398736953735, 'Val/mean f1': 0.9760478138923645, 'Val/mean precision': 0.9750677347183228, 'Val/mean recall': 0.9770298600196838, 'Val/mean hd95_metric': 4.937185764312744} +Epoch [3527/4000] Training [1/16] Loss: 0.00319 +Epoch [3527/4000] Training [2/16] Loss: 0.00286 +Epoch [3527/4000] Training [3/16] Loss: 0.00191 +Epoch [3527/4000] Training [4/16] Loss: 0.00260 +Epoch [3527/4000] Training [5/16] Loss: 0.00223 +Epoch [3527/4000] Training [6/16] Loss: 0.00337 +Epoch [3527/4000] Training [7/16] Loss: 0.00207 +Epoch [3527/4000] Training [8/16] Loss: 0.00228 +Epoch [3527/4000] Training [9/16] Loss: 0.00377 +Epoch [3527/4000] Training [10/16] Loss: 0.00231 +Epoch [3527/4000] Training [11/16] Loss: 0.00244 +Epoch [3527/4000] Training [12/16] Loss: 0.00143 +Epoch [3527/4000] Training [13/16] Loss: 0.00295 +Epoch [3527/4000] Training [14/16] Loss: 0.00231 +Epoch [3527/4000] Training [15/16] Loss: 0.00176 +Epoch [3527/4000] Training [16/16] Loss: 0.00165 +Epoch [3527/4000] Training metric {'Train/mean dice_metric': 0.9987914562225342, 'Train/mean miou_metric': 0.997291088104248, 'Train/mean f1': 0.9935581088066101, 'Train/mean precision': 0.9888226985931396, 'Train/mean recall': 0.9983391165733337, 'Train/mean hd95_metric': 0.5275665521621704} +Epoch [3527/4000] Validation [1/4] Loss: 0.45703 focal_loss 0.39101 dice_loss 0.06602 +Epoch [3527/4000] Validation [2/4] Loss: 0.89199 focal_loss 0.66683 dice_loss 0.22515 +Epoch [3527/4000] Validation [3/4] Loss: 0.53286 focal_loss 0.44014 dice_loss 0.09271 +Epoch [3527/4000] Validation [4/4] Loss: 0.35121 focal_loss 0.26137 dice_loss 0.08983 +Epoch [3527/4000] Validation metric {'Val/mean dice_metric': 0.9729406237602234, 'Val/mean miou_metric': 0.9587125778198242, 'Val/mean f1': 0.97535240650177, 'Val/mean precision': 0.9737641215324402, 'Val/mean recall': 0.976945698261261, 'Val/mean hd95_metric': 5.1015448570251465} +Cheakpoint... +Epoch [3527/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729406237602234, 'Val/mean miou_metric': 0.9587125778198242, 'Val/mean f1': 0.97535240650177, 'Val/mean precision': 0.9737641215324402, 'Val/mean recall': 0.976945698261261, 'Val/mean hd95_metric': 5.1015448570251465} +Epoch [3528/4000] Training [1/16] Loss: 0.00295 +Epoch [3528/4000] Training [2/16] Loss: 0.00256 +Epoch [3528/4000] Training [3/16] Loss: 0.00199 +Epoch [3528/4000] Training [4/16] Loss: 0.00268 +Epoch [3528/4000] Training [5/16] Loss: 0.00291 +Epoch [3528/4000] Training [6/16] Loss: 0.00170 +Epoch [3528/4000] Training [7/16] Loss: 0.00175 +Epoch [3528/4000] Training [8/16] Loss: 0.00203 +Epoch [3528/4000] Training [9/16] Loss: 0.00174 +Epoch [3528/4000] Training [10/16] Loss: 0.00324 +Epoch [3528/4000] Training [11/16] Loss: 0.00283 +Epoch [3528/4000] Training [12/16] Loss: 0.00420 +Epoch [3528/4000] Training [13/16] Loss: 0.00226 +Epoch [3528/4000] Training [14/16] Loss: 0.00285 +Epoch [3528/4000] Training [15/16] Loss: 0.00199 +Epoch [3528/4000] Training [16/16] Loss: 0.00298 +Epoch [3528/4000] Training metric {'Train/mean dice_metric': 0.9986165761947632, 'Train/mean miou_metric': 0.9969490766525269, 'Train/mean f1': 0.993575394153595, 'Train/mean precision': 0.9889506697654724, 'Train/mean recall': 0.998243510723114, 'Train/mean hd95_metric': 0.6929301023483276} +Epoch [3528/4000] Validation [1/4] Loss: 0.42664 focal_loss 0.36278 dice_loss 0.06387 +Epoch [3528/4000] Validation [2/4] Loss: 0.45072 focal_loss 0.34184 dice_loss 0.10888 +Epoch [3528/4000] Validation [3/4] Loss: 0.53670 focal_loss 0.43729 dice_loss 0.09941 +Epoch [3528/4000] Validation [4/4] Loss: 0.37282 focal_loss 0.26833 dice_loss 0.10449 +Epoch [3528/4000] Validation metric {'Val/mean dice_metric': 0.9744879603385925, 'Val/mean miou_metric': 0.9601324200630188, 'Val/mean f1': 0.9763262271881104, 'Val/mean precision': 0.9735189080238342, 'Val/mean recall': 0.9791496992111206, 'Val/mean hd95_metric': 4.9548563957214355} +Cheakpoint... +Epoch [3528/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744879603385925, 'Val/mean miou_metric': 0.9601324200630188, 'Val/mean f1': 0.9763262271881104, 'Val/mean precision': 0.9735189080238342, 'Val/mean recall': 0.9791496992111206, 'Val/mean hd95_metric': 4.9548563957214355} +Epoch [3529/4000] Training [1/16] Loss: 0.00228 +Epoch [3529/4000] Training [2/16] Loss: 0.00205 +Epoch [3529/4000] Training [3/16] Loss: 0.00161 +Epoch [3529/4000] Training [4/16] Loss: 0.00300 +Epoch [3529/4000] Training [5/16] Loss: 0.00336 +Epoch [3529/4000] Training [6/16] Loss: 0.00323 +Epoch [3529/4000] Training [7/16] Loss: 0.00348 +Epoch [3529/4000] Training [8/16] Loss: 0.00303 +Epoch [3529/4000] Training [9/16] Loss: 0.00220 +Epoch [3529/4000] Training [10/16] Loss: 0.00240 +Epoch [3529/4000] Training [11/16] Loss: 0.00210 +Epoch [3529/4000] Training [12/16] Loss: 0.00225 +Epoch [3529/4000] Training [13/16] Loss: 0.00202 +Epoch [3529/4000] Training [14/16] Loss: 0.00163 +Epoch [3529/4000] Training [15/16] Loss: 0.00245 +Epoch [3529/4000] Training [16/16] Loss: 0.00323 +Epoch [3529/4000] Training metric {'Train/mean dice_metric': 0.998727023601532, 'Train/mean miou_metric': 0.9971340894699097, 'Train/mean f1': 0.9926639795303345, 'Train/mean precision': 0.9871255159378052, 'Train/mean recall': 0.9982649087905884, 'Train/mean hd95_metric': 0.5436100959777832} +Epoch [3529/4000] Validation [1/4] Loss: 0.37490 focal_loss 0.31132 dice_loss 0.06358 +Epoch [3529/4000] Validation [2/4] Loss: 0.46821 focal_loss 0.35939 dice_loss 0.10882 +Epoch [3529/4000] Validation [3/4] Loss: 0.28923 focal_loss 0.22315 dice_loss 0.06608 +Epoch [3529/4000] Validation [4/4] Loss: 0.36843 focal_loss 0.26629 dice_loss 0.10214 +Epoch [3529/4000] Validation metric {'Val/mean dice_metric': 0.9742749333381653, 'Val/mean miou_metric': 0.9598388671875, 'Val/mean f1': 0.9754112362861633, 'Val/mean precision': 0.9729514122009277, 'Val/mean recall': 0.9778834581375122, 'Val/mean hd95_metric': 5.033051013946533} +Cheakpoint... +Epoch [3529/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742749333381653, 'Val/mean miou_metric': 0.9598388671875, 'Val/mean f1': 0.9754112362861633, 'Val/mean precision': 0.9729514122009277, 'Val/mean recall': 0.9778834581375122, 'Val/mean hd95_metric': 5.033051013946533} +Epoch [3530/4000] Training [1/16] Loss: 0.00192 +Epoch [3530/4000] Training [2/16] Loss: 0.00196 +Epoch [3530/4000] Training [3/16] Loss: 0.00259 +Epoch [3530/4000] Training [4/16] Loss: 0.00289 +Epoch [3530/4000] Training [5/16] Loss: 0.00223 +Epoch [3530/4000] Training [6/16] Loss: 0.00270 +Epoch [3530/4000] Training [7/16] Loss: 0.00196 +Epoch [3530/4000] Training [8/16] Loss: 0.00262 +Epoch [3530/4000] Training [9/16] Loss: 0.00294 +Epoch [3530/4000] Training [10/16] Loss: 0.00205 +Epoch [3530/4000] Training [11/16] Loss: 0.00197 +Epoch [3530/4000] Training [12/16] Loss: 0.00190 +Epoch [3530/4000] Training [13/16] Loss: 0.00336 +Epoch [3530/4000] Training [14/16] Loss: 0.00242 +Epoch [3530/4000] Training [15/16] Loss: 0.00242 +Epoch [3530/4000] Training [16/16] Loss: 0.00234 +Epoch [3530/4000] Training metric {'Train/mean dice_metric': 0.9986642599105835, 'Train/mean miou_metric': 0.9970550537109375, 'Train/mean f1': 0.993692934513092, 'Train/mean precision': 0.9891790151596069, 'Train/mean recall': 0.998248279094696, 'Train/mean hd95_metric': 0.5579376816749573} +Epoch [3530/4000] Validation [1/4] Loss: 0.46131 focal_loss 0.39192 dice_loss 0.06940 +Epoch [3530/4000] Validation [2/4] Loss: 0.46889 focal_loss 0.35827 dice_loss 0.11062 +Epoch [3530/4000] Validation [3/4] Loss: 0.58298 focal_loss 0.47413 dice_loss 0.10885 +Epoch [3530/4000] Validation [4/4] Loss: 0.53349 focal_loss 0.40910 dice_loss 0.12439 +Epoch [3530/4000] Validation metric {'Val/mean dice_metric': 0.9739665985107422, 'Val/mean miou_metric': 0.9592363238334656, 'Val/mean f1': 0.9758545756340027, 'Val/mean precision': 0.9739710688591003, 'Val/mean recall': 0.9777454137802124, 'Val/mean hd95_metric': 5.38466215133667} +Cheakpoint... +Epoch [3530/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739665985107422, 'Val/mean miou_metric': 0.9592363238334656, 'Val/mean f1': 0.9758545756340027, 'Val/mean precision': 0.9739710688591003, 'Val/mean recall': 0.9777454137802124, 'Val/mean hd95_metric': 5.38466215133667} +Epoch [3531/4000] Training [1/16] Loss: 0.00194 +Epoch [3531/4000] Training [2/16] Loss: 0.00217 +Epoch [3531/4000] Training [3/16] Loss: 0.00268 +Epoch [3531/4000] Training [4/16] Loss: 0.00261 +Epoch [3531/4000] Training [5/16] Loss: 0.00132 +Epoch [3531/4000] Training [6/16] Loss: 0.00320 +Epoch [3531/4000] Training [7/16] Loss: 0.00268 +Epoch [3531/4000] Training [8/16] Loss: 0.00266 +Epoch [3531/4000] Training [9/16] Loss: 0.00207 +Epoch [3531/4000] Training [10/16] Loss: 0.00217 +Epoch [3531/4000] Training [11/16] Loss: 0.00281 +Epoch [3531/4000] Training [12/16] Loss: 0.00288 +Epoch [3531/4000] Training [13/16] Loss: 0.00337 +Epoch [3531/4000] Training [14/16] Loss: 0.00189 +Epoch [3531/4000] Training [15/16] Loss: 0.00273 +Epoch [3531/4000] Training [16/16] Loss: 0.00315 +Epoch [3531/4000] Training metric {'Train/mean dice_metric': 0.998810887336731, 'Train/mean miou_metric': 0.9973440170288086, 'Train/mean f1': 0.9937077760696411, 'Train/mean precision': 0.9890642762184143, 'Train/mean recall': 0.9983952045440674, 'Train/mean hd95_metric': 0.5382111668586731} +Epoch [3531/4000] Validation [1/4] Loss: 0.44444 focal_loss 0.36716 dice_loss 0.07729 +Epoch [3531/4000] Validation [2/4] Loss: 0.95078 focal_loss 0.76237 dice_loss 0.18841 +Epoch [3531/4000] Validation [3/4] Loss: 0.51253 focal_loss 0.41249 dice_loss 0.10003 +Epoch [3531/4000] Validation [4/4] Loss: 0.35996 focal_loss 0.27192 dice_loss 0.08804 +Epoch [3531/4000] Validation metric {'Val/mean dice_metric': 0.9724943041801453, 'Val/mean miou_metric': 0.9582618474960327, 'Val/mean f1': 0.9753004908561707, 'Val/mean precision': 0.9741325974464417, 'Val/mean recall': 0.9764711856842041, 'Val/mean hd95_metric': 5.393500328063965} +Cheakpoint... +Epoch [3531/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724943041801453, 'Val/mean miou_metric': 0.9582618474960327, 'Val/mean f1': 0.9753004908561707, 'Val/mean precision': 0.9741325974464417, 'Val/mean recall': 0.9764711856842041, 'Val/mean hd95_metric': 5.393500328063965} +Epoch [3532/4000] Training [1/16] Loss: 0.00247 +Epoch [3532/4000] Training [2/16] Loss: 0.00178 +Epoch [3532/4000] Training [3/16] Loss: 0.00365 +Epoch [3532/4000] Training [4/16] Loss: 0.00250 +Epoch [3532/4000] Training [5/16] Loss: 0.00230 +Epoch [3532/4000] Training [6/16] Loss: 0.00176 +Epoch [3532/4000] Training [7/16] Loss: 0.00324 +Epoch [3532/4000] Training [8/16] Loss: 0.00191 +Epoch [3532/4000] Training [9/16] Loss: 0.00310 +Epoch [3532/4000] Training [10/16] Loss: 0.00302 +Epoch [3532/4000] Training [11/16] Loss: 0.00242 +Epoch [3532/4000] Training [12/16] Loss: 0.00227 +Epoch [3532/4000] Training [13/16] Loss: 0.00217 +Epoch [3532/4000] Training [14/16] Loss: 0.00198 +Epoch [3532/4000] Training [15/16] Loss: 0.00288 +Epoch [3532/4000] Training [16/16] Loss: 0.00317 +Epoch [3532/4000] Training metric {'Train/mean dice_metric': 0.9988056421279907, 'Train/mean miou_metric': 0.9973188638687134, 'Train/mean f1': 0.9936579465866089, 'Train/mean precision': 0.9890065789222717, 'Train/mean recall': 0.9983532428741455, 'Train/mean hd95_metric': 0.5172429084777832} +Epoch [3532/4000] Validation [1/4] Loss: 0.39510 focal_loss 0.33025 dice_loss 0.06485 +Epoch [3532/4000] Validation [2/4] Loss: 1.12056 focal_loss 0.92889 dice_loss 0.19168 +Epoch [3532/4000] Validation [3/4] Loss: 0.55138 focal_loss 0.45839 dice_loss 0.09299 +Epoch [3532/4000] Validation [4/4] Loss: 0.31840 focal_loss 0.21980 dice_loss 0.09860 +Epoch [3532/4000] Validation metric {'Val/mean dice_metric': 0.9729976654052734, 'Val/mean miou_metric': 0.9595041275024414, 'Val/mean f1': 0.9760121703147888, 'Val/mean precision': 0.9741935729980469, 'Val/mean recall': 0.9778376221656799, 'Val/mean hd95_metric': 4.579129219055176} +Cheakpoint... +Epoch [3532/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729976654052734, 'Val/mean miou_metric': 0.9595041275024414, 'Val/mean f1': 0.9760121703147888, 'Val/mean precision': 0.9741935729980469, 'Val/mean recall': 0.9778376221656799, 'Val/mean hd95_metric': 4.579129219055176} +Epoch [3533/4000] Training [1/16] Loss: 0.00444 +Epoch [3533/4000] Training [2/16] Loss: 0.00244 +Epoch [3533/4000] Training [3/16] Loss: 0.00246 +Epoch [3533/4000] Training [4/16] Loss: 0.00177 +Epoch [3533/4000] Training [5/16] Loss: 0.00149 +Epoch [3533/4000] Training [6/16] Loss: 0.00313 +Epoch [3533/4000] Training [7/16] Loss: 0.00237 +Epoch [3533/4000] Training [8/16] Loss: 0.00299 +Epoch [3533/4000] Training [9/16] Loss: 0.00191 +Epoch [3533/4000] Training [10/16] Loss: 0.00366 +Epoch [3533/4000] Training [11/16] Loss: 0.00431 +Epoch [3533/4000] Training [12/16] Loss: 0.00154 +Epoch [3533/4000] Training [13/16] Loss: 0.00276 +Epoch [3533/4000] Training [14/16] Loss: 0.00480 +Epoch [3533/4000] Training [15/16] Loss: 0.00237 +Epoch [3533/4000] Training [16/16] Loss: 0.00191 +Epoch [3533/4000] Training metric {'Train/mean dice_metric': 0.9984169602394104, 'Train/mean miou_metric': 0.996585488319397, 'Train/mean f1': 0.993546187877655, 'Train/mean precision': 0.9889007210731506, 'Train/mean recall': 0.9982355237007141, 'Train/mean hd95_metric': 0.6423704028129578} +Epoch [3533/4000] Validation [1/4] Loss: 0.48233 focal_loss 0.41418 dice_loss 0.06815 +Epoch [3533/4000] Validation [2/4] Loss: 0.46800 focal_loss 0.35878 dice_loss 0.10922 +Epoch [3533/4000] Validation [3/4] Loss: 0.52121 focal_loss 0.42802 dice_loss 0.09319 +Epoch [3533/4000] Validation [4/4] Loss: 0.45794 focal_loss 0.33825 dice_loss 0.11969 +Epoch [3533/4000] Validation metric {'Val/mean dice_metric': 0.9753257632255554, 'Val/mean miou_metric': 0.9604774713516235, 'Val/mean f1': 0.9759780168533325, 'Val/mean precision': 0.9739781618118286, 'Val/mean recall': 0.9779861569404602, 'Val/mean hd95_metric': 4.877011299133301} +Cheakpoint... +Epoch [3533/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753257632255554, 'Val/mean miou_metric': 0.9604774713516235, 'Val/mean f1': 0.9759780168533325, 'Val/mean precision': 0.9739781618118286, 'Val/mean recall': 0.9779861569404602, 'Val/mean hd95_metric': 4.877011299133301} +Epoch [3534/4000] Training [1/16] Loss: 0.00338 +Epoch [3534/4000] Training [2/16] Loss: 0.00279 +Epoch [3534/4000] Training [3/16] Loss: 0.00293 +Epoch [3534/4000] Training [4/16] Loss: 0.00274 +Epoch [3534/4000] Training [5/16] Loss: 0.00203 +Epoch [3534/4000] Training [6/16] Loss: 0.00277 +Epoch [3534/4000] Training [7/16] Loss: 0.00181 +Epoch [3534/4000] Training [8/16] Loss: 0.00358 +Epoch [3534/4000] Training [9/16] Loss: 0.00347 +Epoch [3534/4000] Training [10/16] Loss: 0.00285 +Epoch [3534/4000] Training [11/16] Loss: 0.00215 +Epoch [3534/4000] Training [12/16] Loss: 0.00346 +Epoch [3534/4000] Training [13/16] Loss: 0.00232 +Epoch [3534/4000] Training [14/16] Loss: 0.00210 +Epoch [3534/4000] Training [15/16] Loss: 0.00292 +Epoch [3534/4000] Training [16/16] Loss: 0.00226 +Epoch [3534/4000] Training metric {'Train/mean dice_metric': 0.998572587966919, 'Train/mean miou_metric': 0.9968506097793579, 'Train/mean f1': 0.9933335781097412, 'Train/mean precision': 0.9885535836219788, 'Train/mean recall': 0.9981600046157837, 'Train/mean hd95_metric': 0.6254690885543823} +Epoch [3534/4000] Validation [1/4] Loss: 0.35765 focal_loss 0.29830 dice_loss 0.05934 +Epoch [3534/4000] Validation [2/4] Loss: 1.10796 focal_loss 0.92266 dice_loss 0.18530 +Epoch [3534/4000] Validation [3/4] Loss: 0.56505 focal_loss 0.46821 dice_loss 0.09684 +Epoch [3534/4000] Validation [4/4] Loss: 0.43062 focal_loss 0.31857 dice_loss 0.11205 +Epoch [3534/4000] Validation metric {'Val/mean dice_metric': 0.9734930992126465, 'Val/mean miou_metric': 0.9594507217407227, 'Val/mean f1': 0.976004421710968, 'Val/mean precision': 0.9739318490028381, 'Val/mean recall': 0.9780858159065247, 'Val/mean hd95_metric': 4.968429088592529} +Cheakpoint... +Epoch [3534/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734930992126465, 'Val/mean miou_metric': 0.9594507217407227, 'Val/mean f1': 0.976004421710968, 'Val/mean precision': 0.9739318490028381, 'Val/mean recall': 0.9780858159065247, 'Val/mean hd95_metric': 4.968429088592529} +Epoch [3535/4000] Training [1/16] Loss: 0.00405 +Epoch [3535/4000] Training [2/16] Loss: 0.00174 +Epoch [3535/4000] Training [3/16] Loss: 0.00270 +Epoch [3535/4000] Training [4/16] Loss: 0.00223 +Epoch [3535/4000] Training [5/16] Loss: 0.00212 +Epoch [3535/4000] Training [6/16] Loss: 0.00173 +Epoch [3535/4000] Training [7/16] Loss: 0.00175 +Epoch [3535/4000] Training [8/16] Loss: 0.00270 +Epoch [3535/4000] Training [9/16] Loss: 0.00256 +Epoch [3535/4000] Training [10/16] Loss: 0.00212 +Epoch [3535/4000] Training [11/16] Loss: 0.00266 +Epoch [3535/4000] Training [12/16] Loss: 0.00211 +Epoch [3535/4000] Training [13/16] Loss: 0.00240 +Epoch [3535/4000] Training [14/16] Loss: 0.00199 +Epoch [3535/4000] Training [15/16] Loss: 0.00266 +Epoch [3535/4000] Training [16/16] Loss: 0.00282 +Epoch [3535/4000] Training metric {'Train/mean dice_metric': 0.9988312721252441, 'Train/mean miou_metric': 0.9973406791687012, 'Train/mean f1': 0.9928975105285645, 'Train/mean precision': 0.9874980449676514, 'Train/mean recall': 0.9983563423156738, 'Train/mean hd95_metric': 0.5152619481086731} +Epoch [3535/4000] Validation [1/4] Loss: 0.42883 focal_loss 0.36568 dice_loss 0.06315 +Epoch [3535/4000] Validation [2/4] Loss: 0.48389 focal_loss 0.37171 dice_loss 0.11218 +Epoch [3535/4000] Validation [3/4] Loss: 0.27992 focal_loss 0.21801 dice_loss 0.06190 +Epoch [3535/4000] Validation [4/4] Loss: 0.47243 focal_loss 0.36048 dice_loss 0.11195 +Epoch [3535/4000] Validation metric {'Val/mean dice_metric': 0.9750972986221313, 'Val/mean miou_metric': 0.9611610174179077, 'Val/mean f1': 0.9762297868728638, 'Val/mean precision': 0.9734721779823303, 'Val/mean recall': 0.9790030121803284, 'Val/mean hd95_metric': 4.634100437164307} +Cheakpoint... +Epoch [3535/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750972986221313, 'Val/mean miou_metric': 0.9611610174179077, 'Val/mean f1': 0.9762297868728638, 'Val/mean precision': 0.9734721779823303, 'Val/mean recall': 0.9790030121803284, 'Val/mean hd95_metric': 4.634100437164307} +Epoch [3536/4000] Training [1/16] Loss: 0.00205 +Epoch [3536/4000] Training [2/16] Loss: 0.00294 +Epoch [3536/4000] Training [3/16] Loss: 0.00302 +Epoch [3536/4000] Training [4/16] Loss: 0.00313 +Epoch [3536/4000] Training [5/16] Loss: 0.00153 +Epoch [3536/4000] Training [6/16] Loss: 0.00181 +Epoch [3536/4000] Training [7/16] Loss: 0.00204 +Epoch [3536/4000] Training [8/16] Loss: 0.00225 +Epoch [3536/4000] Training [9/16] Loss: 0.00217 +Epoch [3536/4000] Training [10/16] Loss: 0.00146 +Epoch [3536/4000] Training [11/16] Loss: 0.00190 +Epoch [3536/4000] Training [12/16] Loss: 0.00268 +Epoch [3536/4000] Training [13/16] Loss: 0.00389 +Epoch [3536/4000] Training [14/16] Loss: 0.00259 +Epoch [3536/4000] Training [15/16] Loss: 0.00247 +Epoch [3536/4000] Training [16/16] Loss: 0.00319 +Epoch [3536/4000] Training metric {'Train/mean dice_metric': 0.9988071918487549, 'Train/mean miou_metric': 0.9973416924476624, 'Train/mean f1': 0.9938647747039795, 'Train/mean precision': 0.9893543124198914, 'Train/mean recall': 0.998416543006897, 'Train/mean hd95_metric': 0.5079811215400696} +Epoch [3536/4000] Validation [1/4] Loss: 0.48146 focal_loss 0.41393 dice_loss 0.06752 +Epoch [3536/4000] Validation [2/4] Loss: 1.41856 focal_loss 1.13803 dice_loss 0.28053 +Epoch [3536/4000] Validation [3/4] Loss: 0.53408 focal_loss 0.43995 dice_loss 0.09413 +Epoch [3536/4000] Validation [4/4] Loss: 0.45463 focal_loss 0.34813 dice_loss 0.10650 +Epoch [3536/4000] Validation metric {'Val/mean dice_metric': 0.9707227945327759, 'Val/mean miou_metric': 0.9574060440063477, 'Val/mean f1': 0.9753457903862, 'Val/mean precision': 0.9747049808502197, 'Val/mean recall': 0.9759874939918518, 'Val/mean hd95_metric': 4.897182464599609} +Cheakpoint... +Epoch [3536/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9707], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9707227945327759, 'Val/mean miou_metric': 0.9574060440063477, 'Val/mean f1': 0.9753457903862, 'Val/mean precision': 0.9747049808502197, 'Val/mean recall': 0.9759874939918518, 'Val/mean hd95_metric': 4.897182464599609} +Epoch [3537/4000] Training [1/16] Loss: 0.00262 +Epoch [3537/4000] Training [2/16] Loss: 0.00350 +Epoch [3537/4000] Training [3/16] Loss: 0.00187 +Epoch [3537/4000] Training [4/16] Loss: 0.00275 +Epoch [3537/4000] Training [5/16] Loss: 0.00191 +Epoch [3537/4000] Training [6/16] Loss: 0.00389 +Epoch [3537/4000] Training [7/16] Loss: 0.00232 +Epoch [3537/4000] Training [8/16] Loss: 0.00288 +Epoch [3537/4000] Training [9/16] Loss: 0.00173 +Epoch [3537/4000] Training [10/16] Loss: 0.00251 +Epoch [3537/4000] Training [11/16] Loss: 0.00162 +Epoch [3537/4000] Training [12/16] Loss: 0.00209 +Epoch [3537/4000] Training [13/16] Loss: 0.00224 +Epoch [3537/4000] Training [14/16] Loss: 0.00283 +Epoch [3537/4000] Training [15/16] Loss: 0.00234 +Epoch [3537/4000] Training [16/16] Loss: 0.00201 +Epoch [3537/4000] Training metric {'Train/mean dice_metric': 0.9987766742706299, 'Train/mean miou_metric': 0.9972686767578125, 'Train/mean f1': 0.9936805367469788, 'Train/mean precision': 0.9890598654747009, 'Train/mean recall': 0.9983446002006531, 'Train/mean hd95_metric': 0.5612158179283142} +Epoch [3537/4000] Validation [1/4] Loss: 0.39884 focal_loss 0.33624 dice_loss 0.06260 +Epoch [3537/4000] Validation [2/4] Loss: 0.48943 focal_loss 0.37859 dice_loss 0.11084 +Epoch [3537/4000] Validation [3/4] Loss: 0.52461 focal_loss 0.43390 dice_loss 0.09071 +Epoch [3537/4000] Validation [4/4] Loss: 0.37286 focal_loss 0.28228 dice_loss 0.09058 +Epoch [3537/4000] Validation metric {'Val/mean dice_metric': 0.9745804667472839, 'Val/mean miou_metric': 0.9605180621147156, 'Val/mean f1': 0.9763404130935669, 'Val/mean precision': 0.9746178984642029, 'Val/mean recall': 0.978069007396698, 'Val/mean hd95_metric': 4.835129261016846} +Cheakpoint... +Epoch [3537/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745804667472839, 'Val/mean miou_metric': 0.9605180621147156, 'Val/mean f1': 0.9763404130935669, 'Val/mean precision': 0.9746178984642029, 'Val/mean recall': 0.978069007396698, 'Val/mean hd95_metric': 4.835129261016846} +Epoch [3538/4000] Training [1/16] Loss: 0.00242 +Epoch [3538/4000] Training [2/16] Loss: 0.00168 +Epoch [3538/4000] Training [3/16] Loss: 0.00155 +Epoch [3538/4000] Training [4/16] Loss: 0.00213 +Epoch [3538/4000] Training [5/16] Loss: 0.00232 +Epoch [3538/4000] Training [6/16] Loss: 0.00249 +Epoch [3538/4000] Training [7/16] Loss: 0.00163 +Epoch [3538/4000] Training [8/16] Loss: 0.00275 +Epoch [3538/4000] Training [9/16] Loss: 0.00195 +Epoch [3538/4000] Training [10/16] Loss: 0.00307 +Epoch [3538/4000] Training [11/16] Loss: 0.00236 +Epoch [3538/4000] Training [12/16] Loss: 0.00230 +Epoch [3538/4000] Training [13/16] Loss: 0.00178 +Epoch [3538/4000] Training [14/16] Loss: 0.00286 +Epoch [3538/4000] Training [15/16] Loss: 0.00324 +Epoch [3538/4000] Training [16/16] Loss: 0.00347 +Epoch [3538/4000] Training metric {'Train/mean dice_metric': 0.9987751245498657, 'Train/mean miou_metric': 0.9972512722015381, 'Train/mean f1': 0.9934707283973694, 'Train/mean precision': 0.9886348843574524, 'Train/mean recall': 0.9983540773391724, 'Train/mean hd95_metric': 0.5459260940551758} +Epoch [3538/4000] Validation [1/4] Loss: 0.40658 focal_loss 0.34315 dice_loss 0.06343 +Epoch [3538/4000] Validation [2/4] Loss: 0.52614 focal_loss 0.40014 dice_loss 0.12600 +Epoch [3538/4000] Validation [3/4] Loss: 0.56194 focal_loss 0.46142 dice_loss 0.10051 +Epoch [3538/4000] Validation [4/4] Loss: 0.39571 focal_loss 0.29228 dice_loss 0.10343 +Epoch [3538/4000] Validation metric {'Val/mean dice_metric': 0.9746655225753784, 'Val/mean miou_metric': 0.9603112936019897, 'Val/mean f1': 0.9756764769554138, 'Val/mean precision': 0.9746368527412415, 'Val/mean recall': 0.9767183065414429, 'Val/mean hd95_metric': 5.206738471984863} +Cheakpoint... +Epoch [3538/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746655225753784, 'Val/mean miou_metric': 0.9603112936019897, 'Val/mean f1': 0.9756764769554138, 'Val/mean precision': 0.9746368527412415, 'Val/mean recall': 0.9767183065414429, 'Val/mean hd95_metric': 5.206738471984863} +Epoch [3539/4000] Training [1/16] Loss: 0.00258 +Epoch [3539/4000] Training [2/16] Loss: 0.00285 +Epoch [3539/4000] Training [3/16] Loss: 0.00269 +Epoch [3539/4000] Training [4/16] Loss: 0.00236 +Epoch [3539/4000] Training [5/16] Loss: 0.00219 +Epoch [3539/4000] Training [6/16] Loss: 0.00179 +Epoch [3539/4000] Training [7/16] Loss: 0.00216 +Epoch [3539/4000] Training [8/16] Loss: 0.00206 +Epoch [3539/4000] Training [9/16] Loss: 0.00303 +Epoch [3539/4000] Training [10/16] Loss: 0.00203 +Epoch [3539/4000] Training [11/16] Loss: 0.00332 +Epoch [3539/4000] Training [12/16] Loss: 0.00134 +Epoch [3539/4000] Training [13/16] Loss: 0.00184 +Epoch [3539/4000] Training [14/16] Loss: 0.00234 +Epoch [3539/4000] Training [15/16] Loss: 0.00381 +Epoch [3539/4000] Training [16/16] Loss: 0.00249 +Epoch [3539/4000] Training metric {'Train/mean dice_metric': 0.998870849609375, 'Train/mean miou_metric': 0.9974405765533447, 'Train/mean f1': 0.99351966381073, 'Train/mean precision': 0.9886948466300964, 'Train/mean recall': 0.99839186668396, 'Train/mean hd95_metric': 0.5386993288993835} +Epoch [3539/4000] Validation [1/4] Loss: 0.48975 focal_loss 0.42072 dice_loss 0.06903 +Epoch [3539/4000] Validation [2/4] Loss: 1.44018 focal_loss 1.15300 dice_loss 0.28717 +Epoch [3539/4000] Validation [3/4] Loss: 0.54087 focal_loss 0.43905 dice_loss 0.10182 +Epoch [3539/4000] Validation [4/4] Loss: 0.40757 focal_loss 0.30152 dice_loss 0.10605 +Epoch [3539/4000] Validation metric {'Val/mean dice_metric': 0.9733611941337585, 'Val/mean miou_metric': 0.9592701196670532, 'Val/mean f1': 0.97493577003479, 'Val/mean precision': 0.9730755686759949, 'Val/mean recall': 0.9768030643463135, 'Val/mean hd95_metric': 5.238519191741943} +Cheakpoint... +Epoch [3539/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733611941337585, 'Val/mean miou_metric': 0.9592701196670532, 'Val/mean f1': 0.97493577003479, 'Val/mean precision': 0.9730755686759949, 'Val/mean recall': 0.9768030643463135, 'Val/mean hd95_metric': 5.238519191741943} +Epoch [3540/4000] Training [1/16] Loss: 0.00182 +Epoch [3540/4000] Training [2/16] Loss: 0.00365 +Epoch [3540/4000] Training [3/16] Loss: 0.00208 +Epoch [3540/4000] Training [4/16] Loss: 0.00243 +Epoch [3540/4000] Training [5/16] Loss: 0.00190 +Epoch [3540/4000] Training [6/16] Loss: 0.00147 +Epoch [3540/4000] Training [7/16] Loss: 0.00185 +Epoch [3540/4000] Training [8/16] Loss: 0.00223 +Epoch [3540/4000] Training [9/16] Loss: 0.00341 +Epoch [3540/4000] Training [10/16] Loss: 0.00229 +Epoch [3540/4000] Training [11/16] Loss: 0.00196 +Epoch [3540/4000] Training [12/16] Loss: 0.00361 +Epoch [3540/4000] Training [13/16] Loss: 0.00254 +Epoch [3540/4000] Training [14/16] Loss: 0.00337 +Epoch [3540/4000] Training [15/16] Loss: 0.00238 +Epoch [3540/4000] Training [16/16] Loss: 0.00172 +Epoch [3540/4000] Training metric {'Train/mean dice_metric': 0.9988850355148315, 'Train/mean miou_metric': 0.997495174407959, 'Train/mean f1': 0.9939741492271423, 'Train/mean precision': 0.9894892573356628, 'Train/mean recall': 0.998499870300293, 'Train/mean hd95_metric': 0.5345001220703125} +Epoch [3540/4000] Validation [1/4] Loss: 0.38297 focal_loss 0.31848 dice_loss 0.06449 +Epoch [3540/4000] Validation [2/4] Loss: 0.51536 focal_loss 0.39941 dice_loss 0.11595 +Epoch [3540/4000] Validation [3/4] Loss: 0.29782 focal_loss 0.23130 dice_loss 0.06653 +Epoch [3540/4000] Validation [4/4] Loss: 0.54483 focal_loss 0.41520 dice_loss 0.12963 +Epoch [3540/4000] Validation metric {'Val/mean dice_metric': 0.9735977053642273, 'Val/mean miou_metric': 0.9596329927444458, 'Val/mean f1': 0.9763281941413879, 'Val/mean precision': 0.9756498336791992, 'Val/mean recall': 0.9770074486732483, 'Val/mean hd95_metric': 5.136112689971924} +Cheakpoint... +Epoch [3540/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735977053642273, 'Val/mean miou_metric': 0.9596329927444458, 'Val/mean f1': 0.9763281941413879, 'Val/mean precision': 0.9756498336791992, 'Val/mean recall': 0.9770074486732483, 'Val/mean hd95_metric': 5.136112689971924} +Epoch [3541/4000] Training [1/16] Loss: 0.00273 +Epoch [3541/4000] Training [2/16] Loss: 0.00234 +Epoch [3541/4000] Training [3/16] Loss: 0.00283 +Epoch [3541/4000] Training [4/16] Loss: 0.00172 +Epoch [3541/4000] Training [5/16] Loss: 0.01604 +Epoch [3541/4000] Training [6/16] Loss: 0.01336 +Epoch [3541/4000] Training [7/16] Loss: 0.00236 +Epoch [3541/4000] Training [8/16] Loss: 0.00301 +Epoch [3541/4000] Training [9/16] Loss: 0.00264 +Epoch [3541/4000] Training [10/16] Loss: 0.00268 +Epoch [3541/4000] Training [11/16] Loss: 0.00264 +Epoch [3541/4000] Training [12/16] Loss: 0.00254 +Epoch [3541/4000] Training [13/16] Loss: 0.00295 +Epoch [3541/4000] Training [14/16] Loss: 0.00463 +Epoch [3541/4000] Training [15/16] Loss: 0.00272 +Epoch [3541/4000] Training [16/16] Loss: 0.00245 +Epoch [3541/4000] Training metric {'Train/mean dice_metric': 0.9979881644248962, 'Train/mean miou_metric': 0.9958831071853638, 'Train/mean f1': 0.9934918880462646, 'Train/mean precision': 0.9890585541725159, 'Train/mean recall': 0.9979650974273682, 'Train/mean hd95_metric': 0.6893104314804077} +Epoch [3541/4000] Validation [1/4] Loss: 0.40225 focal_loss 0.34002 dice_loss 0.06223 +Epoch [3541/4000] Validation [2/4] Loss: 0.95129 focal_loss 0.75960 dice_loss 0.19168 +Epoch [3541/4000] Validation [3/4] Loss: 0.53953 focal_loss 0.44454 dice_loss 0.09499 +Epoch [3541/4000] Validation [4/4] Loss: 0.39860 focal_loss 0.28311 dice_loss 0.11549 +Epoch [3541/4000] Validation metric {'Val/mean dice_metric': 0.9731589555740356, 'Val/mean miou_metric': 0.9585273861885071, 'Val/mean f1': 0.9756012558937073, 'Val/mean precision': 0.9731672406196594, 'Val/mean recall': 0.9780474901199341, 'Val/mean hd95_metric': 5.1468353271484375} +Cheakpoint... +Epoch [3541/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731589555740356, 'Val/mean miou_metric': 0.9585273861885071, 'Val/mean f1': 0.9756012558937073, 'Val/mean precision': 0.9731672406196594, 'Val/mean recall': 0.9780474901199341, 'Val/mean hd95_metric': 5.1468353271484375} +Epoch [3542/4000] Training [1/16] Loss: 0.00156 +Epoch [3542/4000] Training [2/16] Loss: 0.00248 +Epoch [3542/4000] Training [3/16] Loss: 0.00253 +Epoch [3542/4000] Training [4/16] Loss: 0.00239 +Epoch [3542/4000] Training [5/16] Loss: 0.00188 +Epoch [3542/4000] Training [6/16] Loss: 0.00224 +Epoch [3542/4000] Training [7/16] Loss: 0.00233 +Epoch [3542/4000] Training [8/16] Loss: 0.00195 +Epoch [3542/4000] Training [9/16] Loss: 0.00241 +Epoch [3542/4000] Training [10/16] Loss: 0.00155 +Epoch [3542/4000] Training [11/16] Loss: 0.00326 +Epoch [3542/4000] Training [12/16] Loss: 0.00259 +Epoch [3542/4000] Training [13/16] Loss: 0.00261 +Epoch [3542/4000] Training [14/16] Loss: 0.00315 +Epoch [3542/4000] Training [15/16] Loss: 0.00306 +Epoch [3542/4000] Training [16/16] Loss: 0.00291 +Epoch [3542/4000] Training metric {'Train/mean dice_metric': 0.9988269209861755, 'Train/mean miou_metric': 0.9973791241645813, 'Train/mean f1': 0.9938187599182129, 'Train/mean precision': 0.9892199039459229, 'Train/mean recall': 0.998460590839386, 'Train/mean hd95_metric': 0.5210317373275757} +Epoch [3542/4000] Validation [1/4] Loss: 0.39876 focal_loss 0.33501 dice_loss 0.06375 +Epoch [3542/4000] Validation [2/4] Loss: 0.47267 focal_loss 0.36036 dice_loss 0.11230 +Epoch [3542/4000] Validation [3/4] Loss: 0.53769 focal_loss 0.44553 dice_loss 0.09216 +Epoch [3542/4000] Validation [4/4] Loss: 0.34756 focal_loss 0.25890 dice_loss 0.08866 +Epoch [3542/4000] Validation metric {'Val/mean dice_metric': 0.9738636016845703, 'Val/mean miou_metric': 0.9600820541381836, 'Val/mean f1': 0.9763056039810181, 'Val/mean precision': 0.9741789698600769, 'Val/mean recall': 0.9784416556358337, 'Val/mean hd95_metric': 5.021085739135742} +Cheakpoint... +Epoch [3542/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738636016845703, 'Val/mean miou_metric': 0.9600820541381836, 'Val/mean f1': 0.9763056039810181, 'Val/mean precision': 0.9741789698600769, 'Val/mean recall': 0.9784416556358337, 'Val/mean hd95_metric': 5.021085739135742} +Epoch [3543/4000] Training [1/16] Loss: 0.00262 +Epoch [3543/4000] Training [2/16] Loss: 0.00289 +Epoch [3543/4000] Training [3/16] Loss: 0.00254 +Epoch [3543/4000] Training [4/16] Loss: 0.00255 +Epoch [3543/4000] Training [5/16] Loss: 0.00273 +Epoch [3543/4000] Training [6/16] Loss: 0.00222 +Epoch [3543/4000] Training [7/16] Loss: 0.00108 +Epoch [3543/4000] Training [8/16] Loss: 0.00226 +Epoch [3543/4000] Training [9/16] Loss: 0.00219 +Epoch [3543/4000] Training [10/16] Loss: 0.00288 +Epoch [3543/4000] Training [11/16] Loss: 0.00155 +Epoch [3543/4000] Training [12/16] Loss: 0.00296 +Epoch [3543/4000] Training [13/16] Loss: 0.00235 +Epoch [3543/4000] Training [14/16] Loss: 0.00444 +Epoch [3543/4000] Training [15/16] Loss: 0.00246 +Epoch [3543/4000] Training [16/16] Loss: 0.00289 +Epoch [3543/4000] Training metric {'Train/mean dice_metric': 0.9986878633499146, 'Train/mean miou_metric': 0.9970885515213013, 'Train/mean f1': 0.9936056137084961, 'Train/mean precision': 0.9889435172080994, 'Train/mean recall': 0.9983118176460266, 'Train/mean hd95_metric': 0.596511960029602} +Epoch [3543/4000] Validation [1/4] Loss: 0.43069 focal_loss 0.36429 dice_loss 0.06640 +Epoch [3543/4000] Validation [2/4] Loss: 1.00755 focal_loss 0.76250 dice_loss 0.24505 +Epoch [3543/4000] Validation [3/4] Loss: 0.53028 focal_loss 0.43951 dice_loss 0.09077 +Epoch [3543/4000] Validation [4/4] Loss: 0.36719 focal_loss 0.26895 dice_loss 0.09824 +Epoch [3543/4000] Validation metric {'Val/mean dice_metric': 0.9715613126754761, 'Val/mean miou_metric': 0.957714855670929, 'Val/mean f1': 0.9755728840827942, 'Val/mean precision': 0.9741511344909668, 'Val/mean recall': 0.9769988059997559, 'Val/mean hd95_metric': 5.056063652038574} +Cheakpoint... +Epoch [3543/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715613126754761, 'Val/mean miou_metric': 0.957714855670929, 'Val/mean f1': 0.9755728840827942, 'Val/mean precision': 0.9741511344909668, 'Val/mean recall': 0.9769988059997559, 'Val/mean hd95_metric': 5.056063652038574} +Epoch [3544/4000] Training [1/16] Loss: 0.00295 +Epoch [3544/4000] Training [2/16] Loss: 0.00165 +Epoch [3544/4000] Training [3/16] Loss: 0.00310 +Epoch [3544/4000] Training [4/16] Loss: 0.00192 +Epoch [3544/4000] Training [5/16] Loss: 0.00238 +Epoch [3544/4000] Training [6/16] Loss: 0.00325 +Epoch [3544/4000] Training [7/16] Loss: 0.00181 +Epoch [3544/4000] Training [8/16] Loss: 0.00283 +Epoch [3544/4000] Training [9/16] Loss: 0.00211 +Epoch [3544/4000] Training [10/16] Loss: 0.00317 +Epoch [3544/4000] Training [11/16] Loss: 0.00294 +Epoch [3544/4000] Training [12/16] Loss: 0.00295 +Epoch [3544/4000] Training [13/16] Loss: 0.00327 +Epoch [3544/4000] Training [14/16] Loss: 0.00281 +Epoch [3544/4000] Training [15/16] Loss: 0.00231 +Epoch [3544/4000] Training [16/16] Loss: 0.00268 +Epoch [3544/4000] Training metric {'Train/mean dice_metric': 0.998754620552063, 'Train/mean miou_metric': 0.9972167611122131, 'Train/mean f1': 0.9934704899787903, 'Train/mean precision': 0.988679051399231, 'Train/mean recall': 0.9983086585998535, 'Train/mean hd95_metric': 0.5598909258842468} +Epoch [3544/4000] Validation [1/4] Loss: 0.46754 focal_loss 0.39806 dice_loss 0.06948 +Epoch [3544/4000] Validation [2/4] Loss: 0.53644 focal_loss 0.39968 dice_loss 0.13676 +Epoch [3544/4000] Validation [3/4] Loss: 0.26188 focal_loss 0.20158 dice_loss 0.06030 +Epoch [3544/4000] Validation [4/4] Loss: 0.42992 focal_loss 0.32376 dice_loss 0.10616 +Epoch [3544/4000] Validation metric {'Val/mean dice_metric': 0.9748770594596863, 'Val/mean miou_metric': 0.9607938528060913, 'Val/mean f1': 0.976520299911499, 'Val/mean precision': 0.9742054343223572, 'Val/mean recall': 0.9788461923599243, 'Val/mean hd95_metric': 4.680422306060791} +Cheakpoint... +Epoch [3544/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748770594596863, 'Val/mean miou_metric': 0.9607938528060913, 'Val/mean f1': 0.976520299911499, 'Val/mean precision': 0.9742054343223572, 'Val/mean recall': 0.9788461923599243, 'Val/mean hd95_metric': 4.680422306060791} +Epoch [3545/4000] Training [1/16] Loss: 0.00166 +Epoch [3545/4000] Training [2/16] Loss: 0.00179 +Epoch [3545/4000] Training [3/16] Loss: 0.00408 +Epoch [3545/4000] Training [4/16] Loss: 0.00275 +Epoch [3545/4000] Training [5/16] Loss: 0.00213 +Epoch [3545/4000] Training [6/16] Loss: 0.00250 +Epoch [3545/4000] Training [7/16] Loss: 0.00154 +Epoch [3545/4000] Training [8/16] Loss: 0.00221 +Epoch [3545/4000] Training [9/16] Loss: 0.00204 +Epoch [3545/4000] Training [10/16] Loss: 0.00283 +Epoch [3545/4000] Training [11/16] Loss: 0.00330 +Epoch [3545/4000] Training [12/16] Loss: 0.00292 +Epoch [3545/4000] Training [13/16] Loss: 0.00376 +Epoch [3545/4000] Training [14/16] Loss: 0.00239 +Epoch [3545/4000] Training [15/16] Loss: 0.00177 +Epoch [3545/4000] Training [16/16] Loss: 0.00332 +Epoch [3545/4000] Training metric {'Train/mean dice_metric': 0.9987356662750244, 'Train/mean miou_metric': 0.997189998626709, 'Train/mean f1': 0.9935978651046753, 'Train/mean precision': 0.9889083504676819, 'Train/mean recall': 0.9983320236206055, 'Train/mean hd95_metric': 0.5561800003051758} +Epoch [3545/4000] Validation [1/4] Loss: 0.47690 focal_loss 0.41093 dice_loss 0.06597 +Epoch [3545/4000] Validation [2/4] Loss: 0.47570 focal_loss 0.36579 dice_loss 0.10991 +Epoch [3545/4000] Validation [3/4] Loss: 0.52415 focal_loss 0.42874 dice_loss 0.09540 +Epoch [3545/4000] Validation [4/4] Loss: 0.34211 focal_loss 0.24404 dice_loss 0.09807 +Epoch [3545/4000] Validation metric {'Val/mean dice_metric': 0.9747077822685242, 'Val/mean miou_metric': 0.9604923129081726, 'Val/mean f1': 0.9761731028556824, 'Val/mean precision': 0.9741542339324951, 'Val/mean recall': 0.9782002568244934, 'Val/mean hd95_metric': 4.518341064453125} +Cheakpoint... +Epoch [3545/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747077822685242, 'Val/mean miou_metric': 0.9604923129081726, 'Val/mean f1': 0.9761731028556824, 'Val/mean precision': 0.9741542339324951, 'Val/mean recall': 0.9782002568244934, 'Val/mean hd95_metric': 4.518341064453125} +Epoch [3546/4000] Training [1/16] Loss: 0.00161 +Epoch [3546/4000] Training [2/16] Loss: 0.00210 +Epoch [3546/4000] Training [3/16] Loss: 0.00248 +Epoch [3546/4000] Training [4/16] Loss: 0.00191 +Epoch [3546/4000] Training [5/16] Loss: 0.00329 +Epoch [3546/4000] Training [6/16] Loss: 0.00229 +Epoch [3546/4000] Training [7/16] Loss: 0.00385 +Epoch [3546/4000] Training [8/16] Loss: 0.00186 +Epoch [3546/4000] Training [9/16] Loss: 0.00203 +Epoch [3546/4000] Training [10/16] Loss: 0.00234 +Epoch [3546/4000] Training [11/16] Loss: 0.00172 +Epoch [3546/4000] Training [12/16] Loss: 0.00234 +Epoch [3546/4000] Training [13/16] Loss: 0.00430 +Epoch [3546/4000] Training [14/16] Loss: 0.00226 +Epoch [3546/4000] Training [15/16] Loss: 0.00221 +Epoch [3546/4000] Training [16/16] Loss: 0.00213 +Epoch [3546/4000] Training metric {'Train/mean dice_metric': 0.9988393783569336, 'Train/mean miou_metric': 0.9974029660224915, 'Train/mean f1': 0.9937717914581299, 'Train/mean precision': 0.9892706274986267, 'Train/mean recall': 0.9983140230178833, 'Train/mean hd95_metric': 0.526591420173645} +Epoch [3546/4000] Validation [1/4] Loss: 0.41655 focal_loss 0.35415 dice_loss 0.06241 +Epoch [3546/4000] Validation [2/4] Loss: 0.48191 focal_loss 0.36974 dice_loss 0.11216 +Epoch [3546/4000] Validation [3/4] Loss: 0.53273 focal_loss 0.43492 dice_loss 0.09781 +Epoch [3546/4000] Validation [4/4] Loss: 0.40257 focal_loss 0.28809 dice_loss 0.11447 +Epoch [3546/4000] Validation metric {'Val/mean dice_metric': 0.9728409647941589, 'Val/mean miou_metric': 0.9588408470153809, 'Val/mean f1': 0.9760152697563171, 'Val/mean precision': 0.9747282862663269, 'Val/mean recall': 0.9773057103157043, 'Val/mean hd95_metric': 4.641418933868408} +Cheakpoint... +Epoch [3546/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728409647941589, 'Val/mean miou_metric': 0.9588408470153809, 'Val/mean f1': 0.9760152697563171, 'Val/mean precision': 0.9747282862663269, 'Val/mean recall': 0.9773057103157043, 'Val/mean hd95_metric': 4.641418933868408} +Epoch [3547/4000] Training [1/16] Loss: 0.00247 +Epoch [3547/4000] Training [2/16] Loss: 0.00321 +Epoch [3547/4000] Training [3/16] Loss: 0.00198 +Epoch [3547/4000] Training [4/16] Loss: 0.00142 +Epoch [3547/4000] Training [5/16] Loss: 0.00211 +Epoch [3547/4000] Training [6/16] Loss: 0.00343 +Epoch [3547/4000] Training [7/16] Loss: 0.00176 +Epoch [3547/4000] Training [8/16] Loss: 0.00187 +Epoch [3547/4000] Training [9/16] Loss: 0.00185 +Epoch [3547/4000] Training [10/16] Loss: 0.00387 +Epoch [3547/4000] Training [11/16] Loss: 0.00283 +Epoch [3547/4000] Training [12/16] Loss: 0.00256 +Epoch [3547/4000] Training [13/16] Loss: 0.00343 +Epoch [3547/4000] Training [14/16] Loss: 0.00233 +Epoch [3547/4000] Training [15/16] Loss: 0.00213 +Epoch [3547/4000] Training [16/16] Loss: 0.00325 +Epoch [3547/4000] Training metric {'Train/mean dice_metric': 0.9987055063247681, 'Train/mean miou_metric': 0.9971350431442261, 'Train/mean f1': 0.9937034249305725, 'Train/mean precision': 0.9891446232795715, 'Train/mean recall': 0.9983044266700745, 'Train/mean hd95_metric': 0.57492995262146} +Epoch [3547/4000] Validation [1/4] Loss: 0.41598 focal_loss 0.35195 dice_loss 0.06403 +Epoch [3547/4000] Validation [2/4] Loss: 0.47389 focal_loss 0.36146 dice_loss 0.11243 +Epoch [3547/4000] Validation [3/4] Loss: 0.57009 focal_loss 0.47069 dice_loss 0.09941 +Epoch [3547/4000] Validation [4/4] Loss: 0.48658 focal_loss 0.37710 dice_loss 0.10948 +Epoch [3547/4000] Validation metric {'Val/mean dice_metric': 0.9756511449813843, 'Val/mean miou_metric': 0.9612848162651062, 'Val/mean f1': 0.9761131405830383, 'Val/mean precision': 0.9736902117729187, 'Val/mean recall': 0.9785481691360474, 'Val/mean hd95_metric': 5.335727691650391} +Cheakpoint... +Epoch [3547/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756511449813843, 'Val/mean miou_metric': 0.9612848162651062, 'Val/mean f1': 0.9761131405830383, 'Val/mean precision': 0.9736902117729187, 'Val/mean recall': 0.9785481691360474, 'Val/mean hd95_metric': 5.335727691650391} +Epoch [3548/4000] Training [1/16] Loss: 0.00226 +Epoch [3548/4000] Training [2/16] Loss: 0.00212 +Epoch [3548/4000] Training [3/16] Loss: 0.00156 +Epoch [3548/4000] Training [4/16] Loss: 0.00184 +Epoch [3548/4000] Training [5/16] Loss: 0.00207 +Epoch [3548/4000] Training [6/16] Loss: 0.00227 +Epoch [3548/4000] Training [7/16] Loss: 0.00271 +Epoch [3548/4000] Training [8/16] Loss: 0.00176 +Epoch [3548/4000] Training [9/16] Loss: 0.00210 +Epoch [3548/4000] Training [10/16] Loss: 0.00357 +Epoch [3548/4000] Training [11/16] Loss: 0.00316 +Epoch [3548/4000] Training [12/16] Loss: 0.00248 +Epoch [3548/4000] Training [13/16] Loss: 0.00267 +Epoch [3548/4000] Training [14/16] Loss: 0.00261 +Epoch [3548/4000] Training [15/16] Loss: 0.00224 +Epoch [3548/4000] Training [16/16] Loss: 0.00280 +Epoch [3548/4000] Training metric {'Train/mean dice_metric': 0.998723030090332, 'Train/mean miou_metric': 0.997135579586029, 'Train/mean f1': 0.9928229451179504, 'Train/mean precision': 0.9874402284622192, 'Train/mean recall': 0.9982647895812988, 'Train/mean hd95_metric': 0.5630437135696411} +Epoch [3548/4000] Validation [1/4] Loss: 0.43917 focal_loss 0.37479 dice_loss 0.06438 +Epoch [3548/4000] Validation [2/4] Loss: 0.50179 focal_loss 0.38505 dice_loss 0.11674 +Epoch [3548/4000] Validation [3/4] Loss: 0.49290 focal_loss 0.40081 dice_loss 0.09209 +Epoch [3548/4000] Validation [4/4] Loss: 0.29657 focal_loss 0.21184 dice_loss 0.08472 +Epoch [3548/4000] Validation metric {'Val/mean dice_metric': 0.9730390310287476, 'Val/mean miou_metric': 0.959150493144989, 'Val/mean f1': 0.9748165607452393, 'Val/mean precision': 0.9716785550117493, 'Val/mean recall': 0.9779748916625977, 'Val/mean hd95_metric': 5.238340854644775} +Cheakpoint... +Epoch [3548/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730390310287476, 'Val/mean miou_metric': 0.959150493144989, 'Val/mean f1': 0.9748165607452393, 'Val/mean precision': 0.9716785550117493, 'Val/mean recall': 0.9779748916625977, 'Val/mean hd95_metric': 5.238340854644775} +Epoch [3549/4000] Training [1/16] Loss: 0.00175 +Epoch [3549/4000] Training [2/16] Loss: 0.00234 +Epoch [3549/4000] Training [3/16] Loss: 0.00204 +Epoch [3549/4000] Training [4/16] Loss: 0.00305 +Epoch [3549/4000] Training [5/16] Loss: 0.00180 +Epoch [3549/4000] Training [6/16] Loss: 0.00427 +Epoch [3549/4000] Training [7/16] Loss: 0.00248 +Epoch [3549/4000] Training [8/16] Loss: 0.00197 +Epoch [3549/4000] Training [9/16] Loss: 0.00166 +Epoch [3549/4000] Training [10/16] Loss: 0.00223 +Epoch [3549/4000] Training [11/16] Loss: 0.00316 +Epoch [3549/4000] Training [12/16] Loss: 0.00330 +Epoch [3549/4000] Training [13/16] Loss: 0.00192 +Epoch [3549/4000] Training [14/16] Loss: 0.00251 +Epoch [3549/4000] Training [15/16] Loss: 0.00238 +Epoch [3549/4000] Training [16/16] Loss: 0.00200 +Epoch [3549/4000] Training metric {'Train/mean dice_metric': 0.9988341331481934, 'Train/mean miou_metric': 0.9973936080932617, 'Train/mean f1': 0.9938304424285889, 'Train/mean precision': 0.9893151521682739, 'Train/mean recall': 0.9983871579170227, 'Train/mean hd95_metric': 0.5260739326477051} +Epoch [3549/4000] Validation [1/4] Loss: 0.44844 focal_loss 0.38016 dice_loss 0.06828 +Epoch [3549/4000] Validation [2/4] Loss: 0.98803 focal_loss 0.79999 dice_loss 0.18805 +Epoch [3549/4000] Validation [3/4] Loss: 0.56155 focal_loss 0.46185 dice_loss 0.09970 +Epoch [3549/4000] Validation [4/4] Loss: 0.32658 focal_loss 0.24423 dice_loss 0.08235 +Epoch [3549/4000] Validation metric {'Val/mean dice_metric': 0.9740233421325684, 'Val/mean miou_metric': 0.9604299664497375, 'Val/mean f1': 0.9758087992668152, 'Val/mean precision': 0.9750328660011292, 'Val/mean recall': 0.9765860438346863, 'Val/mean hd95_metric': 4.833930492401123} +Cheakpoint... +Epoch [3549/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740233421325684, 'Val/mean miou_metric': 0.9604299664497375, 'Val/mean f1': 0.9758087992668152, 'Val/mean precision': 0.9750328660011292, 'Val/mean recall': 0.9765860438346863, 'Val/mean hd95_metric': 4.833930492401123} +Epoch [3550/4000] Training [1/16] Loss: 0.00400 +Epoch [3550/4000] Training [2/16] Loss: 0.00251 +Epoch [3550/4000] Training [3/16] Loss: 0.00204 +Epoch [3550/4000] Training [4/16] Loss: 0.00365 +Epoch [3550/4000] Training [5/16] Loss: 0.00271 +Epoch [3550/4000] Training [6/16] Loss: 0.00154 +Epoch [3550/4000] Training [7/16] Loss: 0.00227 +Epoch [3550/4000] Training [8/16] Loss: 0.00302 +Epoch [3550/4000] Training [9/16] Loss: 0.00229 +Epoch [3550/4000] Training [10/16] Loss: 0.00232 +Epoch [3550/4000] Training [11/16] Loss: 0.00305 +Epoch [3550/4000] Training [12/16] Loss: 0.00300 +Epoch [3550/4000] Training [13/16] Loss: 0.00206 +Epoch [3550/4000] Training [14/16] Loss: 0.00157 +Epoch [3550/4000] Training [15/16] Loss: 0.00209 +Epoch [3550/4000] Training [16/16] Loss: 0.00166 +Epoch [3550/4000] Training metric {'Train/mean dice_metric': 0.9987753629684448, 'Train/mean miou_metric': 0.9972773194313049, 'Train/mean f1': 0.9938508868217468, 'Train/mean precision': 0.9893712401390076, 'Train/mean recall': 0.9983713626861572, 'Train/mean hd95_metric': 0.5503482222557068} +Epoch [3550/4000] Validation [1/4] Loss: 0.42115 focal_loss 0.35730 dice_loss 0.06385 +Epoch [3550/4000] Validation [2/4] Loss: 1.00301 focal_loss 0.81308 dice_loss 0.18994 +Epoch [3550/4000] Validation [3/4] Loss: 0.49475 focal_loss 0.40685 dice_loss 0.08790 +Epoch [3550/4000] Validation [4/4] Loss: 0.51448 focal_loss 0.39163 dice_loss 0.12284 +Epoch [3550/4000] Validation metric {'Val/mean dice_metric': 0.9739745259284973, 'Val/mean miou_metric': 0.9607282876968384, 'Val/mean f1': 0.976547360420227, 'Val/mean precision': 0.9752183556556702, 'Val/mean recall': 0.9778800010681152, 'Val/mean hd95_metric': 4.6266913414001465} +Cheakpoint... +Epoch [3550/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739745259284973, 'Val/mean miou_metric': 0.9607282876968384, 'Val/mean f1': 0.976547360420227, 'Val/mean precision': 0.9752183556556702, 'Val/mean recall': 0.9778800010681152, 'Val/mean hd95_metric': 4.6266913414001465} +Epoch [3551/4000] Training [1/16] Loss: 0.00166 +Epoch [3551/4000] Training [2/16] Loss: 0.00350 +Epoch [3551/4000] Training [3/16] Loss: 0.00181 +Epoch [3551/4000] Training [4/16] Loss: 0.00286 +Epoch [3551/4000] Training [5/16] Loss: 0.00206 +Epoch [3551/4000] Training [6/16] Loss: 0.00234 +Epoch [3551/4000] Training [7/16] Loss: 0.00184 +Epoch [3551/4000] Training [8/16] Loss: 0.00323 +Epoch [3551/4000] Training [9/16] Loss: 0.00270 +Epoch [3551/4000] Training [10/16] Loss: 0.00302 +Epoch [3551/4000] Training [11/16] Loss: 0.00241 +Epoch [3551/4000] Training [12/16] Loss: 0.00522 +Epoch [3551/4000] Training [13/16] Loss: 0.00215 +Epoch [3551/4000] Training [14/16] Loss: 0.00281 +Epoch [3551/4000] Training [15/16] Loss: 0.00269 +Epoch [3551/4000] Training [16/16] Loss: 0.00278 +Epoch [3551/4000] Training metric {'Train/mean dice_metric': 0.9985820651054382, 'Train/mean miou_metric': 0.9968975186347961, 'Train/mean f1': 0.9936191439628601, 'Train/mean precision': 0.9891073107719421, 'Train/mean recall': 0.9981723427772522, 'Train/mean hd95_metric': 0.606602668762207} +Epoch [3551/4000] Validation [1/4] Loss: 0.34025 focal_loss 0.28021 dice_loss 0.06004 +Epoch [3551/4000] Validation [2/4] Loss: 0.55800 focal_loss 0.40952 dice_loss 0.14847 +Epoch [3551/4000] Validation [3/4] Loss: 0.56219 focal_loss 0.46739 dice_loss 0.09480 +Epoch [3551/4000] Validation [4/4] Loss: 0.29665 focal_loss 0.21135 dice_loss 0.08530 +Epoch [3551/4000] Validation metric {'Val/mean dice_metric': 0.9739344716072083, 'Val/mean miou_metric': 0.9602825045585632, 'Val/mean f1': 0.9762901663780212, 'Val/mean precision': 0.9747224450111389, 'Val/mean recall': 0.9778628945350647, 'Val/mean hd95_metric': 5.030959606170654} +Cheakpoint... +Epoch [3551/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739344716072083, 'Val/mean miou_metric': 0.9602825045585632, 'Val/mean f1': 0.9762901663780212, 'Val/mean precision': 0.9747224450111389, 'Val/mean recall': 0.9778628945350647, 'Val/mean hd95_metric': 5.030959606170654} +Epoch [3552/4000] Training [1/16] Loss: 0.00274 +Epoch [3552/4000] Training [2/16] Loss: 0.00354 +Epoch [3552/4000] Training [3/16] Loss: 0.00272 +Epoch [3552/4000] Training [4/16] Loss: 0.00178 +Epoch [3552/4000] Training [5/16] Loss: 0.00368 +Epoch [3552/4000] Training [6/16] Loss: 0.00261 +Epoch [3552/4000] Training [7/16] Loss: 0.00211 +Epoch [3552/4000] Training [8/16] Loss: 0.00229 +Epoch [3552/4000] Training [9/16] Loss: 0.00250 +Epoch [3552/4000] Training [10/16] Loss: 0.00251 +Epoch [3552/4000] Training [11/16] Loss: 0.00273 +Epoch [3552/4000] Training [12/16] Loss: 0.00182 +Epoch [3552/4000] Training [13/16] Loss: 0.00311 +Epoch [3552/4000] Training [14/16] Loss: 0.00306 +Epoch [3552/4000] Training [15/16] Loss: 0.00243 +Epoch [3552/4000] Training [16/16] Loss: 0.00226 +Epoch [3552/4000] Training metric {'Train/mean dice_metric': 0.9986746311187744, 'Train/mean miou_metric': 0.9970731735229492, 'Train/mean f1': 0.9937166571617126, 'Train/mean precision': 0.9891710877418518, 'Train/mean recall': 0.9983041286468506, 'Train/mean hd95_metric': 0.5740232467651367} +Epoch [3552/4000] Validation [1/4] Loss: 0.41377 focal_loss 0.34763 dice_loss 0.06614 +Epoch [3552/4000] Validation [2/4] Loss: 1.00403 focal_loss 0.81504 dice_loss 0.18900 +Epoch [3552/4000] Validation [3/4] Loss: 0.25769 focal_loss 0.19918 dice_loss 0.05852 +Epoch [3552/4000] Validation [4/4] Loss: 0.34326 focal_loss 0.25964 dice_loss 0.08362 +Epoch [3552/4000] Validation metric {'Val/mean dice_metric': 0.9749919176101685, 'Val/mean miou_metric': 0.9611334800720215, 'Val/mean f1': 0.9762720465660095, 'Val/mean precision': 0.9739618301391602, 'Val/mean recall': 0.9785932898521423, 'Val/mean hd95_metric': 4.771121978759766} +Cheakpoint... +Epoch [3552/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749919176101685, 'Val/mean miou_metric': 0.9611334800720215, 'Val/mean f1': 0.9762720465660095, 'Val/mean precision': 0.9739618301391602, 'Val/mean recall': 0.9785932898521423, 'Val/mean hd95_metric': 4.771121978759766} +Epoch [3553/4000] Training [1/16] Loss: 0.00235 +Epoch [3553/4000] Training [2/16] Loss: 0.00267 +Epoch [3553/4000] Training [3/16] Loss: 0.00214 +Epoch [3553/4000] Training [4/16] Loss: 0.00218 +Epoch [3553/4000] Training [5/16] Loss: 0.00234 +Epoch [3553/4000] Training [6/16] Loss: 0.00215 +Epoch [3553/4000] Training [7/16] Loss: 0.00193 +Epoch [3553/4000] Training [8/16] Loss: 0.00266 +Epoch [3553/4000] Training [9/16] Loss: 0.00222 +Epoch [3553/4000] Training [10/16] Loss: 0.00342 +Epoch [3553/4000] Training [11/16] Loss: 0.00220 +Epoch [3553/4000] Training [12/16] Loss: 0.00267 +Epoch [3553/4000] Training [13/16] Loss: 0.00144 +Epoch [3553/4000] Training [14/16] Loss: 0.00181 +Epoch [3553/4000] Training [15/16] Loss: 0.00167 +Epoch [3553/4000] Training [16/16] Loss: 0.00257 +Epoch [3553/4000] Training metric {'Train/mean dice_metric': 0.9988373517990112, 'Train/mean miou_metric': 0.9974017143249512, 'Train/mean f1': 0.993877112865448, 'Train/mean precision': 0.9893497824668884, 'Train/mean recall': 0.9984460473060608, 'Train/mean hd95_metric': 0.5165314674377441} +Epoch [3553/4000] Validation [1/4] Loss: 0.45568 focal_loss 0.38211 dice_loss 0.07357 +Epoch [3553/4000] Validation [2/4] Loss: 0.49270 focal_loss 0.38094 dice_loss 0.11176 +Epoch [3553/4000] Validation [3/4] Loss: 0.51237 focal_loss 0.42267 dice_loss 0.08970 +Epoch [3553/4000] Validation [4/4] Loss: 0.37272 focal_loss 0.28447 dice_loss 0.08825 +Epoch [3553/4000] Validation metric {'Val/mean dice_metric': 0.9738385081291199, 'Val/mean miou_metric': 0.9594970941543579, 'Val/mean f1': 0.9759881496429443, 'Val/mean precision': 0.9750464558601379, 'Val/mean recall': 0.9769316911697388, 'Val/mean hd95_metric': 4.804483890533447} +Cheakpoint... +Epoch [3553/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738385081291199, 'Val/mean miou_metric': 0.9594970941543579, 'Val/mean f1': 0.9759881496429443, 'Val/mean precision': 0.9750464558601379, 'Val/mean recall': 0.9769316911697388, 'Val/mean hd95_metric': 4.804483890533447} +Epoch [3554/4000] Training [1/16] Loss: 0.00179 +Epoch [3554/4000] Training [2/16] Loss: 0.00252 +Epoch [3554/4000] Training [3/16] Loss: 0.00254 +Epoch [3554/4000] Training [4/16] Loss: 0.00227 +Epoch [3554/4000] Training [5/16] Loss: 0.00253 +Epoch [3554/4000] Training [6/16] Loss: 0.00275 +Epoch [3554/4000] Training [7/16] Loss: 0.00376 +Epoch [3554/4000] Training [8/16] Loss: 0.00280 +Epoch [3554/4000] Training [9/16] Loss: 0.00226 +Epoch [3554/4000] Training [10/16] Loss: 0.00224 +Epoch [3554/4000] Training [11/16] Loss: 0.00300 +Epoch [3554/4000] Training [12/16] Loss: 0.00134 +Epoch [3554/4000] Training [13/16] Loss: 0.00282 +Epoch [3554/4000] Training [14/16] Loss: 0.00224 +Epoch [3554/4000] Training [15/16] Loss: 0.00186 +Epoch [3554/4000] Training [16/16] Loss: 0.00321 +Epoch [3554/4000] Training metric {'Train/mean dice_metric': 0.9987115263938904, 'Train/mean miou_metric': 0.9971460700035095, 'Train/mean f1': 0.9937717318534851, 'Train/mean precision': 0.9893031120300293, 'Train/mean recall': 0.9982810020446777, 'Train/mean hd95_metric': 0.5877116322517395} +Epoch [3554/4000] Validation [1/4] Loss: 0.38652 focal_loss 0.32457 dice_loss 0.06195 +Epoch [3554/4000] Validation [2/4] Loss: 0.99555 focal_loss 0.80713 dice_loss 0.18842 +Epoch [3554/4000] Validation [3/4] Loss: 0.29629 focal_loss 0.23090 dice_loss 0.06539 +Epoch [3554/4000] Validation [4/4] Loss: 0.38195 focal_loss 0.27994 dice_loss 0.10201 +Epoch [3554/4000] Validation metric {'Val/mean dice_metric': 0.9751280546188354, 'Val/mean miou_metric': 0.9612868428230286, 'Val/mean f1': 0.9768111705780029, 'Val/mean precision': 0.9748483300209045, 'Val/mean recall': 0.9787819385528564, 'Val/mean hd95_metric': 5.101159572601318} +Cheakpoint... +Epoch [3554/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751280546188354, 'Val/mean miou_metric': 0.9612868428230286, 'Val/mean f1': 0.9768111705780029, 'Val/mean precision': 0.9748483300209045, 'Val/mean recall': 0.9787819385528564, 'Val/mean hd95_metric': 5.101159572601318} +Epoch [3555/4000] Training [1/16] Loss: 0.00238 +Epoch [3555/4000] Training [2/16] Loss: 0.00169 +Epoch [3555/4000] Training [3/16] Loss: 0.00346 +Epoch [3555/4000] Training [4/16] Loss: 0.00200 +Epoch [3555/4000] Training [5/16] Loss: 0.00241 +Epoch [3555/4000] Training [6/16] Loss: 0.00204 +Epoch [3555/4000] Training [7/16] Loss: 0.00294 +Epoch [3555/4000] Training [8/16] Loss: 0.00156 +Epoch [3555/4000] Training [9/16] Loss: 0.00311 +Epoch [3555/4000] Training [10/16] Loss: 0.00204 +Epoch [3555/4000] Training [11/16] Loss: 0.00217 +Epoch [3555/4000] Training [12/16] Loss: 0.00314 +Epoch [3555/4000] Training [13/16] Loss: 0.00239 +Epoch [3555/4000] Training [14/16] Loss: 0.00178 +Epoch [3555/4000] Training [15/16] Loss: 0.00134 +Epoch [3555/4000] Training [16/16] Loss: 0.00310 +Epoch [3555/4000] Training metric {'Train/mean dice_metric': 0.9987668991088867, 'Train/mean miou_metric': 0.9972386360168457, 'Train/mean f1': 0.993436872959137, 'Train/mean precision': 0.9885900616645813, 'Train/mean recall': 0.9983314871788025, 'Train/mean hd95_metric': 0.5468050241470337} +Epoch [3555/4000] Validation [1/4] Loss: 0.45260 focal_loss 0.38355 dice_loss 0.06905 +Epoch [3555/4000] Validation [2/4] Loss: 0.53191 focal_loss 0.40459 dice_loss 0.12732 +Epoch [3555/4000] Validation [3/4] Loss: 0.49436 focal_loss 0.40173 dice_loss 0.09263 +Epoch [3555/4000] Validation [4/4] Loss: 0.33236 focal_loss 0.23448 dice_loss 0.09788 +Epoch [3555/4000] Validation metric {'Val/mean dice_metric': 0.9739211797714233, 'Val/mean miou_metric': 0.9595040082931519, 'Val/mean f1': 0.9756656885147095, 'Val/mean precision': 0.9736323952674866, 'Val/mean recall': 0.9777075052261353, 'Val/mean hd95_metric': 4.801363468170166} +Cheakpoint... +Epoch [3555/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739211797714233, 'Val/mean miou_metric': 0.9595040082931519, 'Val/mean f1': 0.9756656885147095, 'Val/mean precision': 0.9736323952674866, 'Val/mean recall': 0.9777075052261353, 'Val/mean hd95_metric': 4.801363468170166} +Epoch [3556/4000] Training [1/16] Loss: 0.00178 +Epoch [3556/4000] Training [2/16] Loss: 0.00230 +Epoch [3556/4000] Training [3/16] Loss: 0.00208 +Epoch [3556/4000] Training [4/16] Loss: 0.00266 +Epoch [3556/4000] Training [5/16] Loss: 0.00229 +Epoch [3556/4000] Training [6/16] Loss: 0.00153 +Epoch [3556/4000] Training [7/16] Loss: 0.00263 +Epoch [3556/4000] Training [8/16] Loss: 0.00325 +Epoch [3556/4000] Training [9/16] Loss: 0.00146 +Epoch [3556/4000] Training [10/16] Loss: 0.00182 +Epoch [3556/4000] Training [11/16] Loss: 0.00210 +Epoch [3556/4000] Training [12/16] Loss: 0.00304 +Epoch [3556/4000] Training [13/16] Loss: 0.00265 +Epoch [3556/4000] Training [14/16] Loss: 0.00289 +Epoch [3556/4000] Training [15/16] Loss: 0.00316 +Epoch [3556/4000] Training [16/16] Loss: 0.00243 +Epoch [3556/4000] Training metric {'Train/mean dice_metric': 0.9987971782684326, 'Train/mean miou_metric': 0.9973214864730835, 'Train/mean f1': 0.9938599467277527, 'Train/mean precision': 0.9893561601638794, 'Train/mean recall': 0.9984049201011658, 'Train/mean hd95_metric': 0.5253205895423889} +Epoch [3556/4000] Validation [1/4] Loss: 0.38730 focal_loss 0.32560 dice_loss 0.06170 +Epoch [3556/4000] Validation [2/4] Loss: 0.50104 focal_loss 0.38688 dice_loss 0.11416 +Epoch [3556/4000] Validation [3/4] Loss: 0.51089 focal_loss 0.42034 dice_loss 0.09055 +Epoch [3556/4000] Validation [4/4] Loss: 0.46187 focal_loss 0.34951 dice_loss 0.11236 +Epoch [3556/4000] Validation metric {'Val/mean dice_metric': 0.9747670888900757, 'Val/mean miou_metric': 0.9606994390487671, 'Val/mean f1': 0.9760755896568298, 'Val/mean precision': 0.9748596549034119, 'Val/mean recall': 0.9772945642471313, 'Val/mean hd95_metric': 4.881680965423584} +Cheakpoint... +Epoch [3556/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747670888900757, 'Val/mean miou_metric': 0.9606994390487671, 'Val/mean f1': 0.9760755896568298, 'Val/mean precision': 0.9748596549034119, 'Val/mean recall': 0.9772945642471313, 'Val/mean hd95_metric': 4.881680965423584} +Epoch [3557/4000] Training [1/16] Loss: 0.00263 +Epoch [3557/4000] Training [2/16] Loss: 0.00244 +Epoch [3557/4000] Training [3/16] Loss: 0.00327 +Epoch [3557/4000] Training [4/16] Loss: 0.00260 +Epoch [3557/4000] Training [5/16] Loss: 0.00278 +Epoch [3557/4000] Training [6/16] Loss: 0.00179 +Epoch [3557/4000] Training [7/16] Loss: 0.00262 +Epoch [3557/4000] Training [8/16] Loss: 0.00236 +Epoch [3557/4000] Training [9/16] Loss: 0.00264 +Epoch [3557/4000] Training [10/16] Loss: 0.00278 +Epoch [3557/4000] Training [11/16] Loss: 0.00274 +Epoch [3557/4000] Training [12/16] Loss: 0.00298 +Epoch [3557/4000] Training [13/16] Loss: 0.00303 +Epoch [3557/4000] Training [14/16] Loss: 0.00436 +Epoch [3557/4000] Training [15/16] Loss: 0.00264 +Epoch [3557/4000] Training [16/16] Loss: 0.00255 +Epoch [3557/4000] Training metric {'Train/mean dice_metric': 0.9985626935958862, 'Train/mean miou_metric': 0.9968308806419373, 'Train/mean f1': 0.9933674931526184, 'Train/mean precision': 0.9885913133621216, 'Train/mean recall': 0.9981899857521057, 'Train/mean hd95_metric': 0.6143829226493835} +Epoch [3557/4000] Validation [1/4] Loss: 0.50713 focal_loss 0.43637 dice_loss 0.07076 +Epoch [3557/4000] Validation [2/4] Loss: 0.50176 focal_loss 0.37937 dice_loss 0.12240 +Epoch [3557/4000] Validation [3/4] Loss: 0.50435 focal_loss 0.41726 dice_loss 0.08709 +Epoch [3557/4000] Validation [4/4] Loss: 0.40598 focal_loss 0.30253 dice_loss 0.10344 +Epoch [3557/4000] Validation metric {'Val/mean dice_metric': 0.9747620820999146, 'Val/mean miou_metric': 0.9606194496154785, 'Val/mean f1': 0.9763717651367188, 'Val/mean precision': 0.9738807082176208, 'Val/mean recall': 0.9788755774497986, 'Val/mean hd95_metric': 4.682888031005859} +Cheakpoint... +Epoch [3557/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747620820999146, 'Val/mean miou_metric': 0.9606194496154785, 'Val/mean f1': 0.9763717651367188, 'Val/mean precision': 0.9738807082176208, 'Val/mean recall': 0.9788755774497986, 'Val/mean hd95_metric': 4.682888031005859} +Epoch [3558/4000] Training [1/16] Loss: 0.00190 +Epoch [3558/4000] Training [2/16] Loss: 0.00235 +Epoch [3558/4000] Training [3/16] Loss: 0.00177 +Epoch [3558/4000] Training [4/16] Loss: 0.00319 +Epoch [3558/4000] Training [5/16] Loss: 0.00199 +Epoch [3558/4000] Training [6/16] Loss: 0.00191 +Epoch [3558/4000] Training [7/16] Loss: 0.00480 +Epoch [3558/4000] Training [8/16] Loss: 0.00413 +Epoch [3558/4000] Training [9/16] Loss: 0.00169 +Epoch [3558/4000] Training [10/16] Loss: 0.00182 +Epoch [3558/4000] Training [11/16] Loss: 0.00178 +Epoch [3558/4000] Training [12/16] Loss: 0.00625 +Epoch [3558/4000] Training [13/16] Loss: 0.00219 +Epoch [3558/4000] Training [14/16] Loss: 0.00198 +Epoch [3558/4000] Training [15/16] Loss: 0.00232 +Epoch [3558/4000] Training [16/16] Loss: 0.00206 +Epoch [3558/4000] Training metric {'Train/mean dice_metric': 0.9988260269165039, 'Train/mean miou_metric': 0.9973782300949097, 'Train/mean f1': 0.9938653111457825, 'Train/mean precision': 0.989372968673706, 'Train/mean recall': 0.9983986020088196, 'Train/mean hd95_metric': 0.5168946981430054} +Epoch [3558/4000] Validation [1/4] Loss: 0.46566 focal_loss 0.39860 dice_loss 0.06707 +Epoch [3558/4000] Validation [2/4] Loss: 0.64716 focal_loss 0.48655 dice_loss 0.16060 +Epoch [3558/4000] Validation [3/4] Loss: 0.49705 focal_loss 0.40337 dice_loss 0.09367 +Epoch [3558/4000] Validation [4/4] Loss: 0.36199 focal_loss 0.27345 dice_loss 0.08854 +Epoch [3558/4000] Validation metric {'Val/mean dice_metric': 0.9727153778076172, 'Val/mean miou_metric': 0.9591854214668274, 'Val/mean f1': 0.9762395024299622, 'Val/mean precision': 0.9751773476600647, 'Val/mean recall': 0.9773039817810059, 'Val/mean hd95_metric': 4.838115215301514} +Cheakpoint... +Epoch [3558/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727153778076172, 'Val/mean miou_metric': 0.9591854214668274, 'Val/mean f1': 0.9762395024299622, 'Val/mean precision': 0.9751773476600647, 'Val/mean recall': 0.9773039817810059, 'Val/mean hd95_metric': 4.838115215301514} +Epoch [3559/4000] Training [1/16] Loss: 0.00280 +Epoch [3559/4000] Training [2/16] Loss: 0.00257 +Epoch [3559/4000] Training [3/16] Loss: 0.00267 +Epoch [3559/4000] Training [4/16] Loss: 0.00241 +Epoch [3559/4000] Training [5/16] Loss: 0.00258 +Epoch [3559/4000] Training [6/16] Loss: 0.00261 +Epoch [3559/4000] Training [7/16] Loss: 0.00225 +Epoch [3559/4000] Training [8/16] Loss: 0.00149 +Epoch [3559/4000] Training [9/16] Loss: 0.00337 +Epoch [3559/4000] Training [10/16] Loss: 0.00174 +Epoch [3559/4000] Training [11/16] Loss: 0.00169 +Epoch [3559/4000] Training [12/16] Loss: 0.00368 +Epoch [3559/4000] Training [13/16] Loss: 0.00244 +Epoch [3559/4000] Training [14/16] Loss: 0.00263 +Epoch [3559/4000] Training [15/16] Loss: 0.00174 +Epoch [3559/4000] Training [16/16] Loss: 0.00259 +Epoch [3559/4000] Training metric {'Train/mean dice_metric': 0.9988059997558594, 'Train/mean miou_metric': 0.9973108768463135, 'Train/mean f1': 0.9936642050743103, 'Train/mean precision': 0.9889597296714783, 'Train/mean recall': 0.9984137415885925, 'Train/mean hd95_metric': 0.5430941581726074} +Epoch [3559/4000] Validation [1/4] Loss: 0.41250 focal_loss 0.35067 dice_loss 0.06183 +Epoch [3559/4000] Validation [2/4] Loss: 0.53347 focal_loss 0.40564 dice_loss 0.12783 +Epoch [3559/4000] Validation [3/4] Loss: 0.53317 focal_loss 0.44170 dice_loss 0.09146 +Epoch [3559/4000] Validation [4/4] Loss: 0.51408 focal_loss 0.38490 dice_loss 0.12918 +Epoch [3559/4000] Validation metric {'Val/mean dice_metric': 0.9738634824752808, 'Val/mean miou_metric': 0.9594326019287109, 'Val/mean f1': 0.9758769273757935, 'Val/mean precision': 0.974341094493866, 'Val/mean recall': 0.9774176478385925, 'Val/mean hd95_metric': 4.882418155670166} +Cheakpoint... +Epoch [3559/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738634824752808, 'Val/mean miou_metric': 0.9594326019287109, 'Val/mean f1': 0.9758769273757935, 'Val/mean precision': 0.974341094493866, 'Val/mean recall': 0.9774176478385925, 'Val/mean hd95_metric': 4.882418155670166} +Epoch [3560/4000] Training [1/16] Loss: 0.00224 +Epoch [3560/4000] Training [2/16] Loss: 0.00275 +Epoch [3560/4000] Training [3/16] Loss: 0.00196 +Epoch [3560/4000] Training [4/16] Loss: 0.00165 +Epoch [3560/4000] Training [5/16] Loss: 0.00321 +Epoch [3560/4000] Training [6/16] Loss: 0.00212 +Epoch [3560/4000] Training [7/16] Loss: 0.00239 +Epoch [3560/4000] Training [8/16] Loss: 0.00176 +Epoch [3560/4000] Training [9/16] Loss: 0.00585 +Epoch [3560/4000] Training [10/16] Loss: 0.00182 +Epoch [3560/4000] Training [11/16] Loss: 0.00187 +Epoch [3560/4000] Training [12/16] Loss: 0.00379 +Epoch [3560/4000] Training [13/16] Loss: 0.00251 +Epoch [3560/4000] Training [14/16] Loss: 0.00270 +Epoch [3560/4000] Training [15/16] Loss: 0.00238 +Epoch [3560/4000] Training [16/16] Loss: 0.00310 +Epoch [3560/4000] Training metric {'Train/mean dice_metric': 0.9986360669136047, 'Train/mean miou_metric': 0.9970014095306396, 'Train/mean f1': 0.9936959147453308, 'Train/mean precision': 0.9891576170921326, 'Train/mean recall': 0.9982759952545166, 'Train/mean hd95_metric': 0.5385705232620239} +Epoch [3560/4000] Validation [1/4] Loss: 0.38064 focal_loss 0.31738 dice_loss 0.06326 +Epoch [3560/4000] Validation [2/4] Loss: 0.49123 focal_loss 0.37979 dice_loss 0.11143 +Epoch [3560/4000] Validation [3/4] Loss: 0.54983 focal_loss 0.45706 dice_loss 0.09277 +Epoch [3560/4000] Validation [4/4] Loss: 0.44024 focal_loss 0.32080 dice_loss 0.11943 +Epoch [3560/4000] Validation metric {'Val/mean dice_metric': 0.973849892616272, 'Val/mean miou_metric': 0.9593936800956726, 'Val/mean f1': 0.9760727286338806, 'Val/mean precision': 0.9743706583976746, 'Val/mean recall': 0.9777807593345642, 'Val/mean hd95_metric': 4.666357517242432} +Cheakpoint... +Epoch [3560/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973849892616272, 'Val/mean miou_metric': 0.9593936800956726, 'Val/mean f1': 0.9760727286338806, 'Val/mean precision': 0.9743706583976746, 'Val/mean recall': 0.9777807593345642, 'Val/mean hd95_metric': 4.666357517242432} +Epoch [3561/4000] Training [1/16] Loss: 0.00428 +Epoch [3561/4000] Training [2/16] Loss: 0.00281 +Epoch [3561/4000] Training [3/16] Loss: 0.00105 +Epoch [3561/4000] Training [4/16] Loss: 0.00154 +Epoch [3561/4000] Training [5/16] Loss: 0.00251 +Epoch [3561/4000] Training [6/16] Loss: 0.00395 +Epoch [3561/4000] Training [7/16] Loss: 0.00216 +Epoch [3561/4000] Training [8/16] Loss: 0.00218 +Epoch [3561/4000] Training [9/16] Loss: 0.00222 +Epoch [3561/4000] Training [10/16] Loss: 0.00180 +Epoch [3561/4000] Training [11/16] Loss: 0.00252 +Epoch [3561/4000] Training [12/16] Loss: 0.00401 +Epoch [3561/4000] Training [13/16] Loss: 0.00208 +Epoch [3561/4000] Training [14/16] Loss: 0.00264 +Epoch [3561/4000] Training [15/16] Loss: 0.00252 +Epoch [3561/4000] Training [16/16] Loss: 0.00182 +Epoch [3561/4000] Training metric {'Train/mean dice_metric': 0.9988356828689575, 'Train/mean miou_metric': 0.997357964515686, 'Train/mean f1': 0.9929288625717163, 'Train/mean precision': 0.9875879883766174, 'Train/mean recall': 0.9983278512954712, 'Train/mean hd95_metric': 0.5082582831382751} +Epoch [3561/4000] Validation [1/4] Loss: 0.44376 focal_loss 0.38050 dice_loss 0.06326 +Epoch [3561/4000] Validation [2/4] Loss: 0.50567 focal_loss 0.38895 dice_loss 0.11672 +Epoch [3561/4000] Validation [3/4] Loss: 0.52998 focal_loss 0.43940 dice_loss 0.09058 +Epoch [3561/4000] Validation [4/4] Loss: 0.36794 focal_loss 0.26790 dice_loss 0.10005 +Epoch [3561/4000] Validation metric {'Val/mean dice_metric': 0.9729049801826477, 'Val/mean miou_metric': 0.9591168165206909, 'Val/mean f1': 0.9749732613563538, 'Val/mean precision': 0.9734110236167908, 'Val/mean recall': 0.9765406847000122, 'Val/mean hd95_metric': 4.640106678009033} +Cheakpoint... +Epoch [3561/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729049801826477, 'Val/mean miou_metric': 0.9591168165206909, 'Val/mean f1': 0.9749732613563538, 'Val/mean precision': 0.9734110236167908, 'Val/mean recall': 0.9765406847000122, 'Val/mean hd95_metric': 4.640106678009033} +Epoch [3562/4000] Training [1/16] Loss: 0.00277 +Epoch [3562/4000] Training [2/16] Loss: 0.00257 +Epoch [3562/4000] Training [3/16] Loss: 0.00279 +Epoch [3562/4000] Training [4/16] Loss: 0.00172 +Epoch [3562/4000] Training [5/16] Loss: 0.00185 +Epoch [3562/4000] Training [6/16] Loss: 0.00315 +Epoch [3562/4000] Training [7/16] Loss: 0.00487 +Epoch [3562/4000] Training [8/16] Loss: 0.00213 +Epoch [3562/4000] Training [9/16] Loss: 0.00297 +Epoch [3562/4000] Training [10/16] Loss: 0.00220 +Epoch [3562/4000] Training [11/16] Loss: 0.00180 +Epoch [3562/4000] Training [12/16] Loss: 0.00234 +Epoch [3562/4000] Training [13/16] Loss: 0.00292 +Epoch [3562/4000] Training [14/16] Loss: 0.00270 +Epoch [3562/4000] Training [15/16] Loss: 0.00233 +Epoch [3562/4000] Training [16/16] Loss: 0.00334 +Epoch [3562/4000] Training metric {'Train/mean dice_metric': 0.9987930059432983, 'Train/mean miou_metric': 0.9973047971725464, 'Train/mean f1': 0.9936705231666565, 'Train/mean precision': 0.9890079498291016, 'Train/mean recall': 0.9983772039413452, 'Train/mean hd95_metric': 0.5379734635353088} +Epoch [3562/4000] Validation [1/4] Loss: 0.41660 focal_loss 0.34807 dice_loss 0.06853 +Epoch [3562/4000] Validation [2/4] Loss: 0.57386 focal_loss 0.42353 dice_loss 0.15033 +Epoch [3562/4000] Validation [3/4] Loss: 0.52146 focal_loss 0.43004 dice_loss 0.09142 +Epoch [3562/4000] Validation [4/4] Loss: 0.36049 focal_loss 0.27204 dice_loss 0.08845 +Epoch [3562/4000] Validation metric {'Val/mean dice_metric': 0.9736306071281433, 'Val/mean miou_metric': 0.9595564603805542, 'Val/mean f1': 0.9757037162780762, 'Val/mean precision': 0.973667562007904, 'Val/mean recall': 0.977748453617096, 'Val/mean hd95_metric': 4.8107781410217285} +Cheakpoint... +Epoch [3562/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736306071281433, 'Val/mean miou_metric': 0.9595564603805542, 'Val/mean f1': 0.9757037162780762, 'Val/mean precision': 0.973667562007904, 'Val/mean recall': 0.977748453617096, 'Val/mean hd95_metric': 4.8107781410217285} +Epoch [3563/4000] Training [1/16] Loss: 0.00210 +Epoch [3563/4000] Training [2/16] Loss: 0.00230 +Epoch [3563/4000] Training [3/16] Loss: 0.00270 +Epoch [3563/4000] Training [4/16] Loss: 0.00251 +Epoch [3563/4000] Training [5/16] Loss: 0.00242 +Epoch [3563/4000] Training [6/16] Loss: 0.00184 +Epoch [3563/4000] Training [7/16] Loss: 0.00234 +Epoch [3563/4000] Training [8/16] Loss: 0.00251 +Epoch [3563/4000] Training [9/16] Loss: 0.00272 +Epoch [3563/4000] Training [10/16] Loss: 0.00176 +Epoch [3563/4000] Training [11/16] Loss: 0.00211 +Epoch [3563/4000] Training [12/16] Loss: 0.00235 +Epoch [3563/4000] Training [13/16] Loss: 0.00226 +Epoch [3563/4000] Training [14/16] Loss: 0.00255 +Epoch [3563/4000] Training [15/16] Loss: 0.00183 +Epoch [3563/4000] Training [16/16] Loss: 0.00218 +Epoch [3563/4000] Training metric {'Train/mean dice_metric': 0.9988405704498291, 'Train/mean miou_metric': 0.9974061250686646, 'Train/mean f1': 0.993871808052063, 'Train/mean precision': 0.9893479943275452, 'Train/mean recall': 0.9984371662139893, 'Train/mean hd95_metric': 0.5269805788993835} +Epoch [3563/4000] Validation [1/4] Loss: 0.41221 focal_loss 0.34828 dice_loss 0.06393 +Epoch [3563/4000] Validation [2/4] Loss: 0.49141 focal_loss 0.37913 dice_loss 0.11228 +Epoch [3563/4000] Validation [3/4] Loss: 0.53807 focal_loss 0.43798 dice_loss 0.10009 +Epoch [3563/4000] Validation [4/4] Loss: 0.29420 focal_loss 0.20578 dice_loss 0.08842 +Epoch [3563/4000] Validation metric {'Val/mean dice_metric': 0.9741939306259155, 'Val/mean miou_metric': 0.9600549936294556, 'Val/mean f1': 0.9760702252388, 'Val/mean precision': 0.9744667410850525, 'Val/mean recall': 0.9776789546012878, 'Val/mean hd95_metric': 5.162191390991211} +Cheakpoint... +Epoch [3563/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741939306259155, 'Val/mean miou_metric': 0.9600549936294556, 'Val/mean f1': 0.9760702252388, 'Val/mean precision': 0.9744667410850525, 'Val/mean recall': 0.9776789546012878, 'Val/mean hd95_metric': 5.162191390991211} +Epoch [3564/4000] Training [1/16] Loss: 0.00310 +Epoch [3564/4000] Training [2/16] Loss: 0.00277 +Epoch [3564/4000] Training [3/16] Loss: 0.00244 +Epoch [3564/4000] Training [4/16] Loss: 0.00445 +Epoch [3564/4000] Training [5/16] Loss: 0.00237 +Epoch [3564/4000] Training [6/16] Loss: 0.00251 +Epoch [3564/4000] Training [7/16] Loss: 0.00266 +Epoch [3564/4000] Training [8/16] Loss: 0.00240 +Epoch [3564/4000] Training [9/16] Loss: 0.00308 +Epoch [3564/4000] Training [10/16] Loss: 0.00254 +Epoch [3564/4000] Training [11/16] Loss: 0.00261 +Epoch [3564/4000] Training [12/16] Loss: 0.00168 +Epoch [3564/4000] Training [13/16] Loss: 0.00199 +Epoch [3564/4000] Training [14/16] Loss: 0.00287 +Epoch [3564/4000] Training [15/16] Loss: 0.00236 +Epoch [3564/4000] Training [16/16] Loss: 0.00149 +Epoch [3564/4000] Training metric {'Train/mean dice_metric': 0.9987553358078003, 'Train/mean miou_metric': 0.9972031116485596, 'Train/mean f1': 0.9929405450820923, 'Train/mean precision': 0.9876577258110046, 'Train/mean recall': 0.9982801675796509, 'Train/mean hd95_metric': 0.5658479928970337} +Epoch [3564/4000] Validation [1/4] Loss: 0.41839 focal_loss 0.35463 dice_loss 0.06376 +Epoch [3564/4000] Validation [2/4] Loss: 0.53104 focal_loss 0.40270 dice_loss 0.12834 +Epoch [3564/4000] Validation [3/4] Loss: 0.51272 focal_loss 0.41617 dice_loss 0.09654 +Epoch [3564/4000] Validation [4/4] Loss: 0.39902 focal_loss 0.30299 dice_loss 0.09604 +Epoch [3564/4000] Validation metric {'Val/mean dice_metric': 0.9745863080024719, 'Val/mean miou_metric': 0.9604377746582031, 'Val/mean f1': 0.9757869839668274, 'Val/mean precision': 0.9730191230773926, 'Val/mean recall': 0.9785706400871277, 'Val/mean hd95_metric': 4.761634349822998} +Cheakpoint... +Epoch [3564/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745863080024719, 'Val/mean miou_metric': 0.9604377746582031, 'Val/mean f1': 0.9757869839668274, 'Val/mean precision': 0.9730191230773926, 'Val/mean recall': 0.9785706400871277, 'Val/mean hd95_metric': 4.761634349822998} +Epoch [3565/4000] Training [1/16] Loss: 0.00250 +Epoch [3565/4000] Training [2/16] Loss: 0.00232 +Epoch [3565/4000] Training [3/16] Loss: 0.00174 +Epoch [3565/4000] Training [4/16] Loss: 0.00281 +Epoch [3565/4000] Training [5/16] Loss: 0.00285 +Epoch [3565/4000] Training [6/16] Loss: 0.00285 +Epoch [3565/4000] Training [7/16] Loss: 0.00202 +Epoch [3565/4000] Training [8/16] Loss: 0.00219 +Epoch [3565/4000] Training [9/16] Loss: 0.00148 +Epoch [3565/4000] Training [10/16] Loss: 0.00237 +Epoch [3565/4000] Training [11/16] Loss: 0.00222 +Epoch [3565/4000] Training [12/16] Loss: 0.00171 +Epoch [3565/4000] Training [13/16] Loss: 0.00211 +Epoch [3565/4000] Training [14/16] Loss: 0.00347 +Epoch [3565/4000] Training [15/16] Loss: 0.00255 +Epoch [3565/4000] Training [16/16] Loss: 0.00253 +Epoch [3565/4000] Training metric {'Train/mean dice_metric': 0.9988081455230713, 'Train/mean miou_metric': 0.9973391890525818, 'Train/mean f1': 0.9938319325447083, 'Train/mean precision': 0.989314079284668, 'Train/mean recall': 0.9983912110328674, 'Train/mean hd95_metric': 0.5432892441749573} +Epoch [3565/4000] Validation [1/4] Loss: 0.42562 focal_loss 0.36233 dice_loss 0.06328 +Epoch [3565/4000] Validation [2/4] Loss: 0.48581 focal_loss 0.37620 dice_loss 0.10961 +Epoch [3565/4000] Validation [3/4] Loss: 0.53699 focal_loss 0.43849 dice_loss 0.09850 +Epoch [3565/4000] Validation [4/4] Loss: 0.35071 focal_loss 0.25331 dice_loss 0.09740 +Epoch [3565/4000] Validation metric {'Val/mean dice_metric': 0.9741253852844238, 'Val/mean miou_metric': 0.9598215818405151, 'Val/mean f1': 0.9763367176055908, 'Val/mean precision': 0.97462397813797, 'Val/mean recall': 0.9780555963516235, 'Val/mean hd95_metric': 4.841825485229492} +Cheakpoint... +Epoch [3565/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741253852844238, 'Val/mean miou_metric': 0.9598215818405151, 'Val/mean f1': 0.9763367176055908, 'Val/mean precision': 0.97462397813797, 'Val/mean recall': 0.9780555963516235, 'Val/mean hd95_metric': 4.841825485229492} +Epoch [3566/4000] Training [1/16] Loss: 0.00842 +Epoch [3566/4000] Training [2/16] Loss: 0.01340 +Epoch [3566/4000] Training [3/16] Loss: 0.00323 +Epoch [3566/4000] Training [4/16] Loss: 0.00185 +Epoch [3566/4000] Training [5/16] Loss: 0.00204 +Epoch [3566/4000] Training [6/16] Loss: 0.00297 +Epoch [3566/4000] Training [7/16] Loss: 0.00408 +Epoch [3566/4000] Training [8/16] Loss: 0.00219 +Epoch [3566/4000] Training [9/16] Loss: 0.00354 +Epoch [3566/4000] Training [10/16] Loss: 0.00247 +Epoch [3566/4000] Training [11/16] Loss: 0.00217 +Epoch [3566/4000] Training [12/16] Loss: 0.00303 +Epoch [3566/4000] Training [13/16] Loss: 0.00269 +Epoch [3566/4000] Training [14/16] Loss: 0.00759 +Epoch [3566/4000] Training [15/16] Loss: 0.00187 +Epoch [3566/4000] Training [16/16] Loss: 0.00206 +Epoch [3566/4000] Training metric {'Train/mean dice_metric': 0.9981772303581238, 'Train/mean miou_metric': 0.9961157441139221, 'Train/mean f1': 0.9933030605316162, 'Train/mean precision': 0.9887242317199707, 'Train/mean recall': 0.9979245066642761, 'Train/mean hd95_metric': 0.818519115447998} +Epoch [3566/4000] Validation [1/4] Loss: 0.39087 focal_loss 0.32953 dice_loss 0.06135 +Epoch [3566/4000] Validation [2/4] Loss: 0.49923 focal_loss 0.38774 dice_loss 0.11149 +Epoch [3566/4000] Validation [3/4] Loss: 0.55287 focal_loss 0.45900 dice_loss 0.09387 +Epoch [3566/4000] Validation [4/4] Loss: 0.32241 focal_loss 0.22965 dice_loss 0.09276 +Epoch [3566/4000] Validation metric {'Val/mean dice_metric': 0.974315345287323, 'Val/mean miou_metric': 0.9597470164299011, 'Val/mean f1': 0.9760220050811768, 'Val/mean precision': 0.9737104177474976, 'Val/mean recall': 0.9783446788787842, 'Val/mean hd95_metric': 4.906412601470947} +Cheakpoint... +Epoch [3566/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974315345287323, 'Val/mean miou_metric': 0.9597470164299011, 'Val/mean f1': 0.9760220050811768, 'Val/mean precision': 0.9737104177474976, 'Val/mean recall': 0.9783446788787842, 'Val/mean hd95_metric': 4.906412601470947} +Epoch [3567/4000] Training [1/16] Loss: 0.00332 +Epoch [3567/4000] Training [2/16] Loss: 0.00249 +Epoch [3567/4000] Training [3/16] Loss: 0.00258 +Epoch [3567/4000] Training [4/16] Loss: 0.00232 +Epoch [3567/4000] Training [5/16] Loss: 0.00200 +Epoch [3567/4000] Training [6/16] Loss: 0.00240 +Epoch [3567/4000] Training [7/16] Loss: 0.00225 +Epoch [3567/4000] Training [8/16] Loss: 0.00215 +Epoch [3567/4000] Training [9/16] Loss: 0.00167 +Epoch [3567/4000] Training [10/16] Loss: 0.00198 +Epoch [3567/4000] Training [11/16] Loss: 0.00182 +Epoch [3567/4000] Training [12/16] Loss: 0.00378 +Epoch [3567/4000] Training [13/16] Loss: 0.00192 +Epoch [3567/4000] Training [14/16] Loss: 0.00312 +Epoch [3567/4000] Training [15/16] Loss: 0.00234 +Epoch [3567/4000] Training [16/16] Loss: 0.00235 +Epoch [3567/4000] Training metric {'Train/mean dice_metric': 0.9987939596176147, 'Train/mean miou_metric': 0.9972716569900513, 'Train/mean f1': 0.992746114730835, 'Train/mean precision': 0.987258791923523, 'Train/mean recall': 0.9982948303222656, 'Train/mean hd95_metric': 0.5352814793586731} +Epoch [3567/4000] Validation [1/4] Loss: 0.37791 focal_loss 0.31830 dice_loss 0.05961 +Epoch [3567/4000] Validation [2/4] Loss: 0.46170 focal_loss 0.35246 dice_loss 0.10924 +Epoch [3567/4000] Validation [3/4] Loss: 0.59497 focal_loss 0.48656 dice_loss 0.10841 +Epoch [3567/4000] Validation [4/4] Loss: 0.39891 focal_loss 0.29473 dice_loss 0.10418 +Epoch [3567/4000] Validation metric {'Val/mean dice_metric': 0.9741001129150391, 'Val/mean miou_metric': 0.9603370428085327, 'Val/mean f1': 0.9758391380310059, 'Val/mean precision': 0.9727402329444885, 'Val/mean recall': 0.9789580702781677, 'Val/mean hd95_metric': 5.400486946105957} +Cheakpoint... +Epoch [3567/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741001129150391, 'Val/mean miou_metric': 0.9603370428085327, 'Val/mean f1': 0.9758391380310059, 'Val/mean precision': 0.9727402329444885, 'Val/mean recall': 0.9789580702781677, 'Val/mean hd95_metric': 5.400486946105957} +Epoch [3568/4000] Training [1/16] Loss: 0.00325 +Epoch [3568/4000] Training [2/16] Loss: 0.00170 +Epoch [3568/4000] Training [3/16] Loss: 0.00208 +Epoch [3568/4000] Training [4/16] Loss: 0.00260 +Epoch [3568/4000] Training [5/16] Loss: 0.00247 +Epoch [3568/4000] Training [6/16] Loss: 0.00388 +Epoch [3568/4000] Training [7/16] Loss: 0.00236 +Epoch [3568/4000] Training [8/16] Loss: 0.00200 +Epoch [3568/4000] Training [9/16] Loss: 0.00198 +Epoch [3568/4000] Training [10/16] Loss: 0.00217 +Epoch [3568/4000] Training [11/16] Loss: 0.00482 +Epoch [3568/4000] Training [12/16] Loss: 0.00285 +Epoch [3568/4000] Training [13/16] Loss: 0.00454 +Epoch [3568/4000] Training [14/16] Loss: 0.00278 +Epoch [3568/4000] Training [15/16] Loss: 0.00285 +Epoch [3568/4000] Training [16/16] Loss: 0.00252 +Epoch [3568/4000] Training metric {'Train/mean dice_metric': 0.9985980987548828, 'Train/mean miou_metric': 0.9969056844711304, 'Train/mean f1': 0.9934673309326172, 'Train/mean precision': 0.9887664318084717, 'Train/mean recall': 0.9982130527496338, 'Train/mean hd95_metric': 0.6018829345703125} +Epoch [3568/4000] Validation [1/4] Loss: 0.43899 focal_loss 0.37588 dice_loss 0.06311 +Epoch [3568/4000] Validation [2/4] Loss: 0.53635 focal_loss 0.40196 dice_loss 0.13439 +Epoch [3568/4000] Validation [3/4] Loss: 0.55723 focal_loss 0.46251 dice_loss 0.09472 +Epoch [3568/4000] Validation [4/4] Loss: 0.28964 focal_loss 0.20446 dice_loss 0.08517 +Epoch [3568/4000] Validation metric {'Val/mean dice_metric': 0.9745451211929321, 'Val/mean miou_metric': 0.9602495431900024, 'Val/mean f1': 0.9761291146278381, 'Val/mean precision': 0.9728512763977051, 'Val/mean recall': 0.9794291853904724, 'Val/mean hd95_metric': 5.297575950622559} +Cheakpoint... +Epoch [3568/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745451211929321, 'Val/mean miou_metric': 0.9602495431900024, 'Val/mean f1': 0.9761291146278381, 'Val/mean precision': 0.9728512763977051, 'Val/mean recall': 0.9794291853904724, 'Val/mean hd95_metric': 5.297575950622559} +Epoch [3569/4000] Training [1/16] Loss: 0.00362 +Epoch [3569/4000] Training [2/16] Loss: 0.00199 +Epoch [3569/4000] Training [3/16] Loss: 0.00202 +Epoch [3569/4000] Training [4/16] Loss: 0.00227 +Epoch [3569/4000] Training [5/16] Loss: 0.00297 +Epoch [3569/4000] Training [6/16] Loss: 0.00148 +Epoch [3569/4000] Training [7/16] Loss: 0.00155 +Epoch [3569/4000] Training [8/16] Loss: 0.00266 +Epoch [3569/4000] Training [9/16] Loss: 0.00189 +Epoch [3569/4000] Training [10/16] Loss: 0.00281 +Epoch [3569/4000] Training [11/16] Loss: 0.00193 +Epoch [3569/4000] Training [12/16] Loss: 0.00315 +Epoch [3569/4000] Training [13/16] Loss: 0.00380 +Epoch [3569/4000] Training [14/16] Loss: 0.00239 +Epoch [3569/4000] Training [15/16] Loss: 0.00233 +Epoch [3569/4000] Training [16/16] Loss: 0.00202 +Epoch [3569/4000] Training metric {'Train/mean dice_metric': 0.9988319277763367, 'Train/mean miou_metric': 0.9973622560501099, 'Train/mean f1': 0.9932752847671509, 'Train/mean precision': 0.9882420301437378, 'Train/mean recall': 0.9983600974082947, 'Train/mean hd95_metric': 0.5204376578330994} +Epoch [3569/4000] Validation [1/4] Loss: 0.39615 focal_loss 0.33573 dice_loss 0.06042 +Epoch [3569/4000] Validation [2/4] Loss: 0.47682 focal_loss 0.36912 dice_loss 0.10769 +Epoch [3569/4000] Validation [3/4] Loss: 0.53140 focal_loss 0.43576 dice_loss 0.09564 +Epoch [3569/4000] Validation [4/4] Loss: 0.47644 focal_loss 0.36423 dice_loss 0.11221 +Epoch [3569/4000] Validation metric {'Val/mean dice_metric': 0.9748943448066711, 'Val/mean miou_metric': 0.9604728817939758, 'Val/mean f1': 0.9757382869720459, 'Val/mean precision': 0.9730962514877319, 'Val/mean recall': 0.9783946871757507, 'Val/mean hd95_metric': 5.003562927246094} +Cheakpoint... +Epoch [3569/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748943448066711, 'Val/mean miou_metric': 0.9604728817939758, 'Val/mean f1': 0.9757382869720459, 'Val/mean precision': 0.9730962514877319, 'Val/mean recall': 0.9783946871757507, 'Val/mean hd95_metric': 5.003562927246094} +Epoch [3570/4000] Training [1/16] Loss: 0.00206 +Epoch [3570/4000] Training [2/16] Loss: 0.00237 +Epoch [3570/4000] Training [3/16] Loss: 0.00269 +Epoch [3570/4000] Training [4/16] Loss: 0.00250 +Epoch [3570/4000] Training [5/16] Loss: 0.00214 +Epoch [3570/4000] Training [6/16] Loss: 0.00186 +Epoch [3570/4000] Training [7/16] Loss: 0.00162 +Epoch [3570/4000] Training [8/16] Loss: 0.00198 +Epoch [3570/4000] Training [9/16] Loss: 0.00240 +Epoch [3570/4000] Training [10/16] Loss: 0.00213 +Epoch [3570/4000] Training [11/16] Loss: 0.00214 +Epoch [3570/4000] Training [12/16] Loss: 0.00367 +Epoch [3570/4000] Training [13/16] Loss: 0.00308 +Epoch [3570/4000] Training [14/16] Loss: 0.00211 +Epoch [3570/4000] Training [15/16] Loss: 0.00267 +Epoch [3570/4000] Training [16/16] Loss: 0.00261 +Epoch [3570/4000] Training metric {'Train/mean dice_metric': 0.9987969398498535, 'Train/mean miou_metric': 0.997316837310791, 'Train/mean f1': 0.9938033819198608, 'Train/mean precision': 0.989274799823761, 'Train/mean recall': 0.9983736276626587, 'Train/mean hd95_metric': 0.5387970209121704} +Epoch [3570/4000] Validation [1/4] Loss: 0.40083 focal_loss 0.33513 dice_loss 0.06570 +Epoch [3570/4000] Validation [2/4] Loss: 0.97647 focal_loss 0.78902 dice_loss 0.18745 +Epoch [3570/4000] Validation [3/4] Loss: 0.54471 focal_loss 0.45192 dice_loss 0.09279 +Epoch [3570/4000] Validation [4/4] Loss: 0.42758 focal_loss 0.31938 dice_loss 0.10820 +Epoch [3570/4000] Validation metric {'Val/mean dice_metric': 0.9715805053710938, 'Val/mean miou_metric': 0.9586594700813293, 'Val/mean f1': 0.9761236906051636, 'Val/mean precision': 0.9747439026832581, 'Val/mean recall': 0.9775075316429138, 'Val/mean hd95_metric': 4.811704635620117} +Cheakpoint... +Epoch [3570/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9715805053710938, 'Val/mean miou_metric': 0.9586594700813293, 'Val/mean f1': 0.9761236906051636, 'Val/mean precision': 0.9747439026832581, 'Val/mean recall': 0.9775075316429138, 'Val/mean hd95_metric': 4.811704635620117} +Epoch [3571/4000] Training [1/16] Loss: 0.00314 +Epoch [3571/4000] Training [2/16] Loss: 0.00156 +Epoch [3571/4000] Training [3/16] Loss: 0.00207 +Epoch [3571/4000] Training [4/16] Loss: 0.00171 +Epoch [3571/4000] Training [5/16] Loss: 0.00270 +Epoch [3571/4000] Training [6/16] Loss: 0.00190 +Epoch [3571/4000] Training [7/16] Loss: 0.00199 +Epoch [3571/4000] Training [8/16] Loss: 0.00220 +Epoch [3571/4000] Training [9/16] Loss: 0.00266 +Epoch [3571/4000] Training [10/16] Loss: 0.00332 +Epoch [3571/4000] Training [11/16] Loss: 0.00328 +Epoch [3571/4000] Training [12/16] Loss: 0.00314 +Epoch [3571/4000] Training [13/16] Loss: 0.00280 +Epoch [3571/4000] Training [14/16] Loss: 0.00206 +Epoch [3571/4000] Training [15/16] Loss: 0.00193 +Epoch [3571/4000] Training [16/16] Loss: 0.00270 +Epoch [3571/4000] Training metric {'Train/mean dice_metric': 0.9987528324127197, 'Train/mean miou_metric': 0.997233510017395, 'Train/mean f1': 0.993774950504303, 'Train/mean precision': 0.9892440438270569, 'Train/mean recall': 0.9983475804328918, 'Train/mean hd95_metric': 0.5096254348754883} +Epoch [3571/4000] Validation [1/4] Loss: 0.40843 focal_loss 0.34134 dice_loss 0.06709 +Epoch [3571/4000] Validation [2/4] Loss: 0.52670 focal_loss 0.38362 dice_loss 0.14308 +Epoch [3571/4000] Validation [3/4] Loss: 0.55722 focal_loss 0.46290 dice_loss 0.09432 +Epoch [3571/4000] Validation [4/4] Loss: 0.45533 focal_loss 0.34846 dice_loss 0.10687 +Epoch [3571/4000] Validation metric {'Val/mean dice_metric': 0.9739503860473633, 'Val/mean miou_metric': 0.9597072601318359, 'Val/mean f1': 0.9761291146278381, 'Val/mean precision': 0.974515974521637, 'Val/mean recall': 0.9777477383613586, 'Val/mean hd95_metric': 4.725253582000732} +Cheakpoint... +Epoch [3571/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739503860473633, 'Val/mean miou_metric': 0.9597072601318359, 'Val/mean f1': 0.9761291146278381, 'Val/mean precision': 0.974515974521637, 'Val/mean recall': 0.9777477383613586, 'Val/mean hd95_metric': 4.725253582000732} +Epoch [3572/4000] Training [1/16] Loss: 0.00285 +Epoch [3572/4000] Training [2/16] Loss: 0.00285 +Epoch [3572/4000] Training [3/16] Loss: 0.00293 +Epoch [3572/4000] Training [4/16] Loss: 0.00335 +Epoch [3572/4000] Training [5/16] Loss: 0.00285 +Epoch [3572/4000] Training [6/16] Loss: 0.00228 +Epoch [3572/4000] Training [7/16] Loss: 0.00168 +Epoch [3572/4000] Training [8/16] Loss: 0.00210 +Epoch [3572/4000] Training [9/16] Loss: 0.00354 +Epoch [3572/4000] Training [10/16] Loss: 0.00219 +Epoch [3572/4000] Training [11/16] Loss: 0.00180 +Epoch [3572/4000] Training [12/16] Loss: 0.00218 +Epoch [3572/4000] Training [13/16] Loss: 0.00245 +Epoch [3572/4000] Training [14/16] Loss: 0.00293 +Epoch [3572/4000] Training [15/16] Loss: 0.00228 +Epoch [3572/4000] Training [16/16] Loss: 0.00247 +Epoch [3572/4000] Training metric {'Train/mean dice_metric': 0.9987317323684692, 'Train/mean miou_metric': 0.9971857070922852, 'Train/mean f1': 0.9937953352928162, 'Train/mean precision': 0.9893423318862915, 'Train/mean recall': 0.9982885718345642, 'Train/mean hd95_metric': 0.5473909378051758} +Epoch [3572/4000] Validation [1/4] Loss: 0.38606 focal_loss 0.32204 dice_loss 0.06401 +Epoch [3572/4000] Validation [2/4] Loss: 0.49458 focal_loss 0.37962 dice_loss 0.11496 +Epoch [3572/4000] Validation [3/4] Loss: 0.54806 focal_loss 0.44991 dice_loss 0.09816 +Epoch [3572/4000] Validation [4/4] Loss: 0.44904 focal_loss 0.33574 dice_loss 0.11330 +Epoch [3572/4000] Validation metric {'Val/mean dice_metric': 0.9738539457321167, 'Val/mean miou_metric': 0.959643542766571, 'Val/mean f1': 0.9764770269393921, 'Val/mean precision': 0.9749460220336914, 'Val/mean recall': 0.9780128598213196, 'Val/mean hd95_metric': 4.618810653686523} +Cheakpoint... +Epoch [3572/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738539457321167, 'Val/mean miou_metric': 0.959643542766571, 'Val/mean f1': 0.9764770269393921, 'Val/mean precision': 0.9749460220336914, 'Val/mean recall': 0.9780128598213196, 'Val/mean hd95_metric': 4.618810653686523} +Epoch [3573/4000] Training [1/16] Loss: 0.00378 +Epoch [3573/4000] Training [2/16] Loss: 0.00248 +Epoch [3573/4000] Training [3/16] Loss: 0.00216 +Epoch [3573/4000] Training [4/16] Loss: 0.00301 +Epoch [3573/4000] Training [5/16] Loss: 0.00241 +Epoch [3573/4000] Training [6/16] Loss: 0.00224 +Epoch [3573/4000] Training [7/16] Loss: 0.00208 +Epoch [3573/4000] Training [8/16] Loss: 0.00230 +Epoch [3573/4000] Training [9/16] Loss: 0.00225 +Epoch [3573/4000] Training [10/16] Loss: 0.00246 +Epoch [3573/4000] Training [11/16] Loss: 0.00239 +Epoch [3573/4000] Training [12/16] Loss: 0.00363 +Epoch [3573/4000] Training [13/16] Loss: 0.00394 +Epoch [3573/4000] Training [14/16] Loss: 0.00212 +Epoch [3573/4000] Training [15/16] Loss: 0.00375 +Epoch [3573/4000] Training [16/16] Loss: 0.00216 +Epoch [3573/4000] Training metric {'Train/mean dice_metric': 0.9987794160842896, 'Train/mean miou_metric': 0.9972829818725586, 'Train/mean f1': 0.9937809705734253, 'Train/mean precision': 0.9891965985298157, 'Train/mean recall': 0.9984080195426941, 'Train/mean hd95_metric': 0.5553985238075256} +Epoch [3573/4000] Validation [1/4] Loss: 0.38297 focal_loss 0.32129 dice_loss 0.06168 +Epoch [3573/4000] Validation [2/4] Loss: 0.53946 focal_loss 0.40686 dice_loss 0.13260 +Epoch [3573/4000] Validation [3/4] Loss: 0.52974 focal_loss 0.42942 dice_loss 0.10032 +Epoch [3573/4000] Validation [4/4] Loss: 0.39297 focal_loss 0.28539 dice_loss 0.10758 +Epoch [3573/4000] Validation metric {'Val/mean dice_metric': 0.9743059277534485, 'Val/mean miou_metric': 0.9601184725761414, 'Val/mean f1': 0.9763194918632507, 'Val/mean precision': 0.9735278487205505, 'Val/mean recall': 0.9791271090507507, 'Val/mean hd95_metric': 4.963414192199707} +Cheakpoint... +Epoch [3573/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743059277534485, 'Val/mean miou_metric': 0.9601184725761414, 'Val/mean f1': 0.9763194918632507, 'Val/mean precision': 0.9735278487205505, 'Val/mean recall': 0.9791271090507507, 'Val/mean hd95_metric': 4.963414192199707} +Epoch [3574/4000] Training [1/16] Loss: 0.00218 +Epoch [3574/4000] Training [2/16] Loss: 0.00205 +Epoch [3574/4000] Training [3/16] Loss: 0.00191 +Epoch [3574/4000] Training [4/16] Loss: 0.00304 +Epoch [3574/4000] Training [5/16] Loss: 0.00397 +Epoch [3574/4000] Training [6/16] Loss: 0.00321 +Epoch [3574/4000] Training [7/16] Loss: 0.00265 +Epoch [3574/4000] Training [8/16] Loss: 0.00268 +Epoch [3574/4000] Training [9/16] Loss: 0.00223 +Epoch [3574/4000] Training [10/16] Loss: 0.00178 +Epoch [3574/4000] Training [11/16] Loss: 0.00240 +Epoch [3574/4000] Training [12/16] Loss: 0.00258 +Epoch [3574/4000] Training [13/16] Loss: 0.00283 +Epoch [3574/4000] Training [14/16] Loss: 0.00282 +Epoch [3574/4000] Training [15/16] Loss: 0.00192 +Epoch [3574/4000] Training [16/16] Loss: 0.00361 +Epoch [3574/4000] Training metric {'Train/mean dice_metric': 0.9986288547515869, 'Train/mean miou_metric': 0.9969581365585327, 'Train/mean f1': 0.9930433034896851, 'Train/mean precision': 0.9879136085510254, 'Train/mean recall': 0.998226523399353, 'Train/mean hd95_metric': 0.557305634021759} +Epoch [3574/4000] Validation [1/4] Loss: 0.42815 focal_loss 0.36398 dice_loss 0.06416 +Epoch [3574/4000] Validation [2/4] Loss: 0.98031 focal_loss 0.77078 dice_loss 0.20953 +Epoch [3574/4000] Validation [3/4] Loss: 0.55243 focal_loss 0.45837 dice_loss 0.09406 +Epoch [3574/4000] Validation [4/4] Loss: 0.29635 focal_loss 0.21040 dice_loss 0.08595 +Epoch [3574/4000] Validation metric {'Val/mean dice_metric': 0.9738792181015015, 'Val/mean miou_metric': 0.9600608944892883, 'Val/mean f1': 0.9759554266929626, 'Val/mean precision': 0.9724334478378296, 'Val/mean recall': 0.9795029759407043, 'Val/mean hd95_metric': 4.892890930175781} +Cheakpoint... +Epoch [3574/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738792181015015, 'Val/mean miou_metric': 0.9600608944892883, 'Val/mean f1': 0.9759554266929626, 'Val/mean precision': 0.9724334478378296, 'Val/mean recall': 0.9795029759407043, 'Val/mean hd95_metric': 4.892890930175781} +Epoch [3575/4000] Training [1/16] Loss: 0.00229 +Epoch [3575/4000] Training [2/16] Loss: 0.00352 +Epoch [3575/4000] Training [3/16] Loss: 0.00195 +Epoch [3575/4000] Training [4/16] Loss: 0.00268 +Epoch [3575/4000] Training [5/16] Loss: 0.00186 +Epoch [3575/4000] Training [6/16] Loss: 0.00288 +Epoch [3575/4000] Training [7/16] Loss: 0.00288 +Epoch [3575/4000] Training [8/16] Loss: 0.00249 +Epoch [3575/4000] Training [9/16] Loss: 0.00218 +Epoch [3575/4000] Training [10/16] Loss: 0.00325 +Epoch [3575/4000] Training [11/16] Loss: 0.00255 +Epoch [3575/4000] Training [12/16] Loss: 0.00245 +Epoch [3575/4000] Training [13/16] Loss: 0.00421 +Epoch [3575/4000] Training [14/16] Loss: 0.00403 +Epoch [3575/4000] Training [15/16] Loss: 0.00324 +Epoch [3575/4000] Training [16/16] Loss: 0.00268 +Epoch [3575/4000] Training metric {'Train/mean dice_metric': 0.9985430836677551, 'Train/mean miou_metric': 0.9968169927597046, 'Train/mean f1': 0.9936923980712891, 'Train/mean precision': 0.989175021648407, 'Train/mean recall': 0.99825119972229, 'Train/mean hd95_metric': 0.6217350959777832} +Epoch [3575/4000] Validation [1/4] Loss: 0.44353 focal_loss 0.37970 dice_loss 0.06384 +Epoch [3575/4000] Validation [2/4] Loss: 0.87103 focal_loss 0.68086 dice_loss 0.19017 +Epoch [3575/4000] Validation [3/4] Loss: 0.53508 focal_loss 0.43934 dice_loss 0.09574 +Epoch [3575/4000] Validation [4/4] Loss: 0.36064 focal_loss 0.27158 dice_loss 0.08906 +Epoch [3575/4000] Validation metric {'Val/mean dice_metric': 0.973965048789978, 'Val/mean miou_metric': 0.9597774744033813, 'Val/mean f1': 0.9761365652084351, 'Val/mean precision': 0.9735523462295532, 'Val/mean recall': 0.9787344932556152, 'Val/mean hd95_metric': 4.7943806648254395} +Cheakpoint... +Epoch [3575/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973965048789978, 'Val/mean miou_metric': 0.9597774744033813, 'Val/mean f1': 0.9761365652084351, 'Val/mean precision': 0.9735523462295532, 'Val/mean recall': 0.9787344932556152, 'Val/mean hd95_metric': 4.7943806648254395} +Epoch [3576/4000] Training [1/16] Loss: 0.00220 +Epoch [3576/4000] Training [2/16] Loss: 0.00285 +Epoch [3576/4000] Training [3/16] Loss: 0.00263 +Epoch [3576/4000] Training [4/16] Loss: 0.00324 +Epoch [3576/4000] Training [5/16] Loss: 0.00263 +Epoch [3576/4000] Training [6/16] Loss: 0.00239 +Epoch [3576/4000] Training [7/16] Loss: 0.00204 +Epoch [3576/4000] Training [8/16] Loss: 0.00216 +Epoch [3576/4000] Training [9/16] Loss: 0.00199 +Epoch [3576/4000] Training [10/16] Loss: 0.00226 +Epoch [3576/4000] Training [11/16] Loss: 0.00195 +Epoch [3576/4000] Training [12/16] Loss: 0.00260 +Epoch [3576/4000] Training [13/16] Loss: 0.00211 +Epoch [3576/4000] Training [14/16] Loss: 0.00214 +Epoch [3576/4000] Training [15/16] Loss: 0.00266 +Epoch [3576/4000] Training [16/16] Loss: 0.00295 +Epoch [3576/4000] Training metric {'Train/mean dice_metric': 0.9988831281661987, 'Train/mean miou_metric': 0.9974715113639832, 'Train/mean f1': 0.9936208128929138, 'Train/mean precision': 0.9888449907302856, 'Train/mean recall': 0.9984429478645325, 'Train/mean hd95_metric': 0.511258065700531} +Epoch [3576/4000] Validation [1/4] Loss: 0.41872 focal_loss 0.35479 dice_loss 0.06393 +Epoch [3576/4000] Validation [2/4] Loss: 1.02056 focal_loss 0.83064 dice_loss 0.18992 +Epoch [3576/4000] Validation [3/4] Loss: 0.49587 focal_loss 0.39966 dice_loss 0.09622 +Epoch [3576/4000] Validation [4/4] Loss: 0.38701 focal_loss 0.27706 dice_loss 0.10995 +Epoch [3576/4000] Validation metric {'Val/mean dice_metric': 0.9753149151802063, 'Val/mean miou_metric': 0.9613379240036011, 'Val/mean f1': 0.9764835834503174, 'Val/mean precision': 0.9744380712509155, 'Val/mean recall': 0.9785375595092773, 'Val/mean hd95_metric': 4.769147872924805} +Cheakpoint... +Epoch [3576/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753149151802063, 'Val/mean miou_metric': 0.9613379240036011, 'Val/mean f1': 0.9764835834503174, 'Val/mean precision': 0.9744380712509155, 'Val/mean recall': 0.9785375595092773, 'Val/mean hd95_metric': 4.769147872924805} +Epoch [3577/4000] Training [1/16] Loss: 0.00327 +Epoch [3577/4000] Training [2/16] Loss: 0.00223 +Epoch [3577/4000] Training [3/16] Loss: 0.00274 +Epoch [3577/4000] Training [4/16] Loss: 0.00276 +Epoch [3577/4000] Training [5/16] Loss: 0.00291 +Epoch [3577/4000] Training [6/16] Loss: 0.00195 +Epoch [3577/4000] Training [7/16] Loss: 0.00303 +Epoch [3577/4000] Training [8/16] Loss: 0.00173 +Epoch [3577/4000] Training [9/16] Loss: 0.00346 +Epoch [3577/4000] Training [10/16] Loss: 0.00375 +Epoch [3577/4000] Training [11/16] Loss: 0.00169 +Epoch [3577/4000] Training [12/16] Loss: 0.00378 +Epoch [3577/4000] Training [13/16] Loss: 0.00317 +Epoch [3577/4000] Training [14/16] Loss: 0.00183 +Epoch [3577/4000] Training [15/16] Loss: 0.00177 +Epoch [3577/4000] Training [16/16] Loss: 0.00258 +Epoch [3577/4000] Training metric {'Train/mean dice_metric': 0.9986719489097595, 'Train/mean miou_metric': 0.9970301389694214, 'Train/mean f1': 0.9927961230278015, 'Train/mean precision': 0.9874289631843567, 'Train/mean recall': 0.9982219338417053, 'Train/mean hd95_metric': 0.5484650135040283} +Epoch [3577/4000] Validation [1/4] Loss: 0.38614 focal_loss 0.32507 dice_loss 0.06106 +Epoch [3577/4000] Validation [2/4] Loss: 0.51696 focal_loss 0.39389 dice_loss 0.12307 +Epoch [3577/4000] Validation [3/4] Loss: 0.25731 focal_loss 0.19935 dice_loss 0.05796 +Epoch [3577/4000] Validation [4/4] Loss: 0.35908 focal_loss 0.27029 dice_loss 0.08879 +Epoch [3577/4000] Validation metric {'Val/mean dice_metric': 0.9752548336982727, 'Val/mean miou_metric': 0.9611566662788391, 'Val/mean f1': 0.9760690331459045, 'Val/mean precision': 0.9732354283332825, 'Val/mean recall': 0.9789190888404846, 'Val/mean hd95_metric': 4.786983966827393} +Cheakpoint... +Epoch [3577/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752548336982727, 'Val/mean miou_metric': 0.9611566662788391, 'Val/mean f1': 0.9760690331459045, 'Val/mean precision': 0.9732354283332825, 'Val/mean recall': 0.9789190888404846, 'Val/mean hd95_metric': 4.786983966827393} +Epoch [3578/4000] Training [1/16] Loss: 0.00272 +Epoch [3578/4000] Training [2/16] Loss: 0.00243 +Epoch [3578/4000] Training [3/16] Loss: 0.00227 +Epoch [3578/4000] Training [4/16] Loss: 0.00167 +Epoch [3578/4000] Training [5/16] Loss: 0.00432 +Epoch [3578/4000] Training [6/16] Loss: 0.00246 +Epoch [3578/4000] Training [7/16] Loss: 0.00312 +Epoch [3578/4000] Training [8/16] Loss: 0.00277 +Epoch [3578/4000] Training [9/16] Loss: 0.00200 +Epoch [3578/4000] Training [10/16] Loss: 0.00275 +Epoch [3578/4000] Training [11/16] Loss: 0.00314 +Epoch [3578/4000] Training [12/16] Loss: 0.00318 +Epoch [3578/4000] Training [13/16] Loss: 0.00194 +Epoch [3578/4000] Training [14/16] Loss: 0.00211 +Epoch [3578/4000] Training [15/16] Loss: 0.00229 +Epoch [3578/4000] Training [16/16] Loss: 0.00347 +Epoch [3578/4000] Training metric {'Train/mean dice_metric': 0.9987132549285889, 'Train/mean miou_metric': 0.9971340894699097, 'Train/mean f1': 0.9934810996055603, 'Train/mean precision': 0.9887089133262634, 'Train/mean recall': 0.9982995986938477, 'Train/mean hd95_metric': 0.5382111668586731} +Epoch [3578/4000] Validation [1/4] Loss: 0.42434 focal_loss 0.36063 dice_loss 0.06371 +Epoch [3578/4000] Validation [2/4] Loss: 1.40480 focal_loss 1.13004 dice_loss 0.27476 +Epoch [3578/4000] Validation [3/4] Loss: 0.54673 focal_loss 0.45413 dice_loss 0.09260 +Epoch [3578/4000] Validation [4/4] Loss: 0.33993 focal_loss 0.25389 dice_loss 0.08604 +Epoch [3578/4000] Validation metric {'Val/mean dice_metric': 0.971626877784729, 'Val/mean miou_metric': 0.9582284688949585, 'Val/mean f1': 0.9758870005607605, 'Val/mean precision': 0.9738337397575378, 'Val/mean recall': 0.9779488444328308, 'Val/mean hd95_metric': 4.99806547164917} +Cheakpoint... +Epoch [3578/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.971626877784729, 'Val/mean miou_metric': 0.9582284688949585, 'Val/mean f1': 0.9758870005607605, 'Val/mean precision': 0.9738337397575378, 'Val/mean recall': 0.9779488444328308, 'Val/mean hd95_metric': 4.99806547164917} +Epoch [3579/4000] Training [1/16] Loss: 0.00218 +Epoch [3579/4000] Training [2/16] Loss: 0.00225 +Epoch [3579/4000] Training [3/16] Loss: 0.00417 +Epoch [3579/4000] Training [4/16] Loss: 0.00228 +Epoch [3579/4000] Training [5/16] Loss: 0.00284 +Epoch [3579/4000] Training [6/16] Loss: 0.00288 +Epoch [3579/4000] Training [7/16] Loss: 0.00187 +Epoch [3579/4000] Training [8/16] Loss: 0.00267 +Epoch [3579/4000] Training [9/16] Loss: 0.00181 +Epoch [3579/4000] Training [10/16] Loss: 0.00332 +Epoch [3579/4000] Training [11/16] Loss: 0.00373 +Epoch [3579/4000] Training [12/16] Loss: 0.00254 +Epoch [3579/4000] Training [13/16] Loss: 0.00269 +Epoch [3579/4000] Training [14/16] Loss: 0.00227 +Epoch [3579/4000] Training [15/16] Loss: 0.00361 +Epoch [3579/4000] Training [16/16] Loss: 0.00204 +Epoch [3579/4000] Training metric {'Train/mean dice_metric': 0.9985611438751221, 'Train/mean miou_metric': 0.9968414306640625, 'Train/mean f1': 0.9936073422431946, 'Train/mean precision': 0.9890589714050293, 'Train/mean recall': 0.9981976747512817, 'Train/mean hd95_metric': 0.5805941224098206} +Epoch [3579/4000] Validation [1/4] Loss: 0.40046 focal_loss 0.33660 dice_loss 0.06386 +Epoch [3579/4000] Validation [2/4] Loss: 0.52335 focal_loss 0.38453 dice_loss 0.13881 +Epoch [3579/4000] Validation [3/4] Loss: 0.52370 focal_loss 0.43052 dice_loss 0.09317 +Epoch [3579/4000] Validation [4/4] Loss: 0.43833 focal_loss 0.33445 dice_loss 0.10388 +Epoch [3579/4000] Validation metric {'Val/mean dice_metric': 0.9757137298583984, 'Val/mean miou_metric': 0.9609495401382446, 'Val/mean f1': 0.9762849807739258, 'Val/mean precision': 0.9743240475654602, 'Val/mean recall': 0.9782539010047913, 'Val/mean hd95_metric': 4.7144036293029785} +Cheakpoint... +Epoch [3579/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9757137298583984, 'Val/mean miou_metric': 0.9609495401382446, 'Val/mean f1': 0.9762849807739258, 'Val/mean precision': 0.9743240475654602, 'Val/mean recall': 0.9782539010047913, 'Val/mean hd95_metric': 4.7144036293029785} +Epoch [3580/4000] Training [1/16] Loss: 0.00229 +Epoch [3580/4000] Training [2/16] Loss: 0.00340 +Epoch [3580/4000] Training [3/16] Loss: 0.00346 +Epoch [3580/4000] Training [4/16] Loss: 0.00182 +Epoch [3580/4000] Training [5/16] Loss: 0.00196 +Epoch [3580/4000] Training [6/16] Loss: 0.00213 +Epoch [3580/4000] Training [7/16] Loss: 0.00230 +Epoch [3580/4000] Training [8/16] Loss: 0.00233 +Epoch [3580/4000] Training [9/16] Loss: 0.00246 +Epoch [3580/4000] Training [10/16] Loss: 0.00273 +Epoch [3580/4000] Training [11/16] Loss: 0.00182 +Epoch [3580/4000] Training [12/16] Loss: 0.00512 +Epoch [3580/4000] Training [13/16] Loss: 0.00200 +Epoch [3580/4000] Training [14/16] Loss: 0.00190 +Epoch [3580/4000] Training [15/16] Loss: 0.00264 +Epoch [3580/4000] Training [16/16] Loss: 0.00223 +Epoch [3580/4000] Training metric {'Train/mean dice_metric': 0.99867844581604, 'Train/mean miou_metric': 0.9970837831497192, 'Train/mean f1': 0.9938182830810547, 'Train/mean precision': 0.9893046021461487, 'Train/mean recall': 0.99837327003479, 'Train/mean hd95_metric': 0.5679962635040283} +Epoch [3580/4000] Validation [1/4] Loss: 0.39182 focal_loss 0.32824 dice_loss 0.06358 +Epoch [3580/4000] Validation [2/4] Loss: 0.48013 focal_loss 0.36940 dice_loss 0.11073 +Epoch [3580/4000] Validation [3/4] Loss: 0.52816 focal_loss 0.43389 dice_loss 0.09427 +Epoch [3580/4000] Validation [4/4] Loss: 0.45750 focal_loss 0.33887 dice_loss 0.11864 +Epoch [3580/4000] Validation metric {'Val/mean dice_metric': 0.9736520648002625, 'Val/mean miou_metric': 0.9593303799629211, 'Val/mean f1': 0.9759605526924133, 'Val/mean precision': 0.9730905294418335, 'Val/mean recall': 0.9788476824760437, 'Val/mean hd95_metric': 4.94578742980957} +Cheakpoint... +Epoch [3580/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736520648002625, 'Val/mean miou_metric': 0.9593303799629211, 'Val/mean f1': 0.9759605526924133, 'Val/mean precision': 0.9730905294418335, 'Val/mean recall': 0.9788476824760437, 'Val/mean hd95_metric': 4.94578742980957} +Epoch [3581/4000] Training [1/16] Loss: 0.00192 +Epoch [3581/4000] Training [2/16] Loss: 0.00311 +Epoch [3581/4000] Training [3/16] Loss: 0.00127 +Epoch [3581/4000] Training [4/16] Loss: 0.00383 +Epoch [3581/4000] Training [5/16] Loss: 0.00326 +Epoch [3581/4000] Training [6/16] Loss: 0.00155 +Epoch [3581/4000] Training [7/16] Loss: 0.00338 +Epoch [3581/4000] Training [8/16] Loss: 0.00178 +Epoch [3581/4000] Training [9/16] Loss: 0.00321 +Epoch [3581/4000] Training [10/16] Loss: 0.00215 +Epoch [3581/4000] Training [11/16] Loss: 0.00247 +Epoch [3581/4000] Training [12/16] Loss: 0.00224 +Epoch [3581/4000] Training [13/16] Loss: 0.00193 +Epoch [3581/4000] Training [14/16] Loss: 0.00287 +Epoch [3581/4000] Training [15/16] Loss: 0.00243 +Epoch [3581/4000] Training [16/16] Loss: 0.00287 +Epoch [3581/4000] Training metric {'Train/mean dice_metric': 0.998708188533783, 'Train/mean miou_metric': 0.9971433281898499, 'Train/mean f1': 0.9937107563018799, 'Train/mean precision': 0.9891418218612671, 'Train/mean recall': 0.998322069644928, 'Train/mean hd95_metric': 0.528611421585083} +Epoch [3581/4000] Validation [1/4] Loss: 0.41412 focal_loss 0.34885 dice_loss 0.06527 +Epoch [3581/4000] Validation [2/4] Loss: 0.49159 focal_loss 0.38027 dice_loss 0.11131 +Epoch [3581/4000] Validation [3/4] Loss: 0.54023 focal_loss 0.44387 dice_loss 0.09636 +Epoch [3581/4000] Validation [4/4] Loss: 0.40504 focal_loss 0.29733 dice_loss 0.10771 +Epoch [3581/4000] Validation metric {'Val/mean dice_metric': 0.972519040107727, 'Val/mean miou_metric': 0.9587548971176147, 'Val/mean f1': 0.9759080410003662, 'Val/mean precision': 0.974053144454956, 'Val/mean recall': 0.9777700304985046, 'Val/mean hd95_metric': 5.233911037445068} +Cheakpoint... +Epoch [3581/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972519040107727, 'Val/mean miou_metric': 0.9587548971176147, 'Val/mean f1': 0.9759080410003662, 'Val/mean precision': 0.974053144454956, 'Val/mean recall': 0.9777700304985046, 'Val/mean hd95_metric': 5.233911037445068} +Epoch [3582/4000] Training [1/16] Loss: 0.00288 +Epoch [3582/4000] Training [2/16] Loss: 0.00247 +Epoch [3582/4000] Training [3/16] Loss: 0.00343 +Epoch [3582/4000] Training [4/16] Loss: 0.00211 +Epoch [3582/4000] Training [5/16] Loss: 0.00259 +Epoch [3582/4000] Training [6/16] Loss: 0.00174 +Epoch [3582/4000] Training [7/16] Loss: 0.00263 +Epoch [3582/4000] Training [8/16] Loss: 0.00308 +Epoch [3582/4000] Training [9/16] Loss: 0.00321 +Epoch [3582/4000] Training [10/16] Loss: 0.00231 +Epoch [3582/4000] Training [11/16] Loss: 0.00214 +Epoch [3582/4000] Training [12/16] Loss: 0.00256 +Epoch [3582/4000] Training [13/16] Loss: 0.00165 +Epoch [3582/4000] Training [14/16] Loss: 0.00208 +Epoch [3582/4000] Training [15/16] Loss: 0.00263 +Epoch [3582/4000] Training [16/16] Loss: 0.00265 +Epoch [3582/4000] Training metric {'Train/mean dice_metric': 0.9987432956695557, 'Train/mean miou_metric': 0.9971802234649658, 'Train/mean f1': 0.9930059313774109, 'Train/mean precision': 0.987832248210907, 'Train/mean recall': 0.9982340931892395, 'Train/mean hd95_metric': 0.5636017322540283} +Epoch [3582/4000] Validation [1/4] Loss: 0.45998 focal_loss 0.38088 dice_loss 0.07910 +Epoch [3582/4000] Validation [2/4] Loss: 1.03026 focal_loss 0.78053 dice_loss 0.24973 +Epoch [3582/4000] Validation [3/4] Loss: 0.26347 focal_loss 0.20461 dice_loss 0.05886 +Epoch [3582/4000] Validation [4/4] Loss: 0.30839 focal_loss 0.22263 dice_loss 0.08576 +Epoch [3582/4000] Validation metric {'Val/mean dice_metric': 0.9730762243270874, 'Val/mean miou_metric': 0.9590328335762024, 'Val/mean f1': 0.9754753708839417, 'Val/mean precision': 0.9735615253448486, 'Val/mean recall': 0.9773966670036316, 'Val/mean hd95_metric': 4.958868026733398} +Cheakpoint... +Epoch [3582/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730762243270874, 'Val/mean miou_metric': 0.9590328335762024, 'Val/mean f1': 0.9754753708839417, 'Val/mean precision': 0.9735615253448486, 'Val/mean recall': 0.9773966670036316, 'Val/mean hd95_metric': 4.958868026733398} +Epoch [3583/4000] Training [1/16] Loss: 0.00181 +Epoch [3583/4000] Training [2/16] Loss: 0.00415 +Epoch [3583/4000] Training [3/16] Loss: 0.00229 +Epoch [3583/4000] Training [4/16] Loss: 0.00259 +Epoch [3583/4000] Training [5/16] Loss: 0.00284 +Epoch [3583/4000] Training [6/16] Loss: 0.00316 +Epoch [3583/4000] Training [7/16] Loss: 0.00216 +Epoch [3583/4000] Training [8/16] Loss: 0.00247 +Epoch [3583/4000] Training [9/16] Loss: 0.00247 +Epoch [3583/4000] Training [10/16] Loss: 0.00246 +Epoch [3583/4000] Training [11/16] Loss: 0.00246 +Epoch [3583/4000] Training [12/16] Loss: 0.00346 +Epoch [3583/4000] Training [13/16] Loss: 0.00234 +Epoch [3583/4000] Training [14/16] Loss: 0.00304 +Epoch [3583/4000] Training [15/16] Loss: 0.00209 +Epoch [3583/4000] Training [16/16] Loss: 0.00291 +Epoch [3583/4000] Training metric {'Train/mean dice_metric': 0.9985449910163879, 'Train/mean miou_metric': 0.9968030452728271, 'Train/mean f1': 0.9934033155441284, 'Train/mean precision': 0.9886230230331421, 'Train/mean recall': 0.9982300400733948, 'Train/mean hd95_metric': 0.607602596282959} +Epoch [3583/4000] Validation [1/4] Loss: 0.46995 focal_loss 0.40442 dice_loss 0.06553 +Epoch [3583/4000] Validation [2/4] Loss: 0.85612 focal_loss 0.63536 dice_loss 0.22075 +Epoch [3583/4000] Validation [3/4] Loss: 0.29996 focal_loss 0.23707 dice_loss 0.06289 +Epoch [3583/4000] Validation [4/4] Loss: 0.25697 focal_loss 0.17804 dice_loss 0.07893 +Epoch [3583/4000] Validation metric {'Val/mean dice_metric': 0.9751375317573547, 'Val/mean miou_metric': 0.9610527157783508, 'Val/mean f1': 0.9763503670692444, 'Val/mean precision': 0.9741255640983582, 'Val/mean recall': 0.9785853028297424, 'Val/mean hd95_metric': 5.080740451812744} +Cheakpoint... +Epoch [3583/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751375317573547, 'Val/mean miou_metric': 0.9610527157783508, 'Val/mean f1': 0.9763503670692444, 'Val/mean precision': 0.9741255640983582, 'Val/mean recall': 0.9785853028297424, 'Val/mean hd95_metric': 5.080740451812744} +Epoch [3584/4000] Training [1/16] Loss: 0.00362 +Epoch [3584/4000] Training [2/16] Loss: 0.00272 +Epoch [3584/4000] Training [3/16] Loss: 0.00211 +Epoch [3584/4000] Training [4/16] Loss: 0.00177 +Epoch [3584/4000] Training [5/16] Loss: 0.00195 +Epoch [3584/4000] Training [6/16] Loss: 0.00279 +Epoch [3584/4000] Training [7/16] Loss: 0.00224 +Epoch [3584/4000] Training [8/16] Loss: 0.00195 +Epoch [3584/4000] Training [9/16] Loss: 0.00222 +Epoch [3584/4000] Training [10/16] Loss: 0.00154 +Epoch [3584/4000] Training [11/16] Loss: 0.00284 +Epoch [3584/4000] Training [12/16] Loss: 0.00212 +Epoch [3584/4000] Training [13/16] Loss: 0.00270 +Epoch [3584/4000] Training [14/16] Loss: 0.00297 +Epoch [3584/4000] Training [15/16] Loss: 0.00297 +Epoch [3584/4000] Training [16/16] Loss: 0.00269 +Epoch [3584/4000] Training metric {'Train/mean dice_metric': 0.9987934827804565, 'Train/mean miou_metric': 0.9972779750823975, 'Train/mean f1': 0.9933763742446899, 'Train/mean precision': 0.988458514213562, 'Train/mean recall': 0.9983434677124023, 'Train/mean hd95_metric': 0.5450472831726074} +Epoch [3584/4000] Validation [1/4] Loss: 0.47053 focal_loss 0.40410 dice_loss 0.06644 +Epoch [3584/4000] Validation [2/4] Loss: 0.96168 focal_loss 0.77502 dice_loss 0.18665 +Epoch [3584/4000] Validation [3/4] Loss: 0.55575 focal_loss 0.46037 dice_loss 0.09538 +Epoch [3584/4000] Validation [4/4] Loss: 0.38962 focal_loss 0.28304 dice_loss 0.10659 +Epoch [3584/4000] Validation metric {'Val/mean dice_metric': 0.9743902087211609, 'Val/mean miou_metric': 0.9606983065605164, 'Val/mean f1': 0.9758244156837463, 'Val/mean precision': 0.9723405241966248, 'Val/mean recall': 0.9793334007263184, 'Val/mean hd95_metric': 5.073086738586426} +Cheakpoint... +Epoch [3584/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743902087211609, 'Val/mean miou_metric': 0.9606983065605164, 'Val/mean f1': 0.9758244156837463, 'Val/mean precision': 0.9723405241966248, 'Val/mean recall': 0.9793334007263184, 'Val/mean hd95_metric': 5.073086738586426} +Epoch [3585/4000] Training [1/16] Loss: 0.00164 +Epoch [3585/4000] Training [2/16] Loss: 0.00254 +Epoch [3585/4000] Training [3/16] Loss: 0.00231 +Epoch [3585/4000] Training [4/16] Loss: 0.00292 +Epoch [3585/4000] Training [5/16] Loss: 0.00300 +Epoch [3585/4000] Training [6/16] Loss: 0.00247 +Epoch [3585/4000] Training [7/16] Loss: 0.00302 +Epoch [3585/4000] Training [8/16] Loss: 0.00168 +Epoch [3585/4000] Training [9/16] Loss: 0.00247 +Epoch [3585/4000] Training [10/16] Loss: 0.00262 +Epoch [3585/4000] Training [11/16] Loss: 0.00212 +Epoch [3585/4000] Training [12/16] Loss: 0.00339 +Epoch [3585/4000] Training [13/16] Loss: 0.00216 +Epoch [3585/4000] Training [14/16] Loss: 0.00250 +Epoch [3585/4000] Training [15/16] Loss: 0.00243 +Epoch [3585/4000] Training [16/16] Loss: 0.00356 +Epoch [3585/4000] Training metric {'Train/mean dice_metric': 0.998809278011322, 'Train/mean miou_metric': 0.9973459243774414, 'Train/mean f1': 0.9938508868217468, 'Train/mean precision': 0.9893249273300171, 'Train/mean recall': 0.9984184503555298, 'Train/mean hd95_metric': 0.5222933292388916} +Epoch [3585/4000] Validation [1/4] Loss: 0.39298 focal_loss 0.33122 dice_loss 0.06177 +Epoch [3585/4000] Validation [2/4] Loss: 1.08976 focal_loss 0.90230 dice_loss 0.18746 +Epoch [3585/4000] Validation [3/4] Loss: 0.55688 focal_loss 0.46586 dice_loss 0.09102 +Epoch [3585/4000] Validation [4/4] Loss: 0.40411 focal_loss 0.29398 dice_loss 0.11013 +Epoch [3585/4000] Validation metric {'Val/mean dice_metric': 0.9755241274833679, 'Val/mean miou_metric': 0.9611396789550781, 'Val/mean f1': 0.9763497710227966, 'Val/mean precision': 0.9741923213005066, 'Val/mean recall': 0.9785168170928955, 'Val/mean hd95_metric': 4.579373359680176} +Cheakpoint... +Epoch [3585/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755241274833679, 'Val/mean miou_metric': 0.9611396789550781, 'Val/mean f1': 0.9763497710227966, 'Val/mean precision': 0.9741923213005066, 'Val/mean recall': 0.9785168170928955, 'Val/mean hd95_metric': 4.579373359680176} +Epoch [3586/4000] Training [1/16] Loss: 0.00282 +Epoch [3586/4000] Training [2/16] Loss: 0.00296 +Epoch [3586/4000] Training [3/16] Loss: 0.00232 +Epoch [3586/4000] Training [4/16] Loss: 0.00256 +Epoch [3586/4000] Training [5/16] Loss: 0.00229 +Epoch [3586/4000] Training [6/16] Loss: 0.00243 +Epoch [3586/4000] Training [7/16] Loss: 0.00336 +Epoch [3586/4000] Training [8/16] Loss: 0.00201 +Epoch [3586/4000] Training [9/16] Loss: 0.00300 +Epoch [3586/4000] Training [10/16] Loss: 0.00217 +Epoch [3586/4000] Training [11/16] Loss: 0.00232 +Epoch [3586/4000] Training [12/16] Loss: 0.00199 +Epoch [3586/4000] Training [13/16] Loss: 0.00226 +Epoch [3586/4000] Training [14/16] Loss: 0.00337 +Epoch [3586/4000] Training [15/16] Loss: 0.00237 +Epoch [3586/4000] Training [16/16] Loss: 0.00213 +Epoch [3586/4000] Training metric {'Train/mean dice_metric': 0.9988095760345459, 'Train/mean miou_metric': 0.9973381161689758, 'Train/mean f1': 0.9937905073165894, 'Train/mean precision': 0.9891988039016724, 'Train/mean recall': 0.9984250068664551, 'Train/mean hd95_metric': 0.5406802892684937} +Epoch [3586/4000] Validation [1/4] Loss: 0.38369 focal_loss 0.32043 dice_loss 0.06326 +Epoch [3586/4000] Validation [2/4] Loss: 1.13337 focal_loss 0.92738 dice_loss 0.20599 +Epoch [3586/4000] Validation [3/4] Loss: 0.55915 focal_loss 0.46548 dice_loss 0.09366 +Epoch [3586/4000] Validation [4/4] Loss: 0.35025 focal_loss 0.26219 dice_loss 0.08806 +Epoch [3586/4000] Validation metric {'Val/mean dice_metric': 0.976199746131897, 'Val/mean miou_metric': 0.9622315168380737, 'Val/mean f1': 0.9769095182418823, 'Val/mean precision': 0.9742939472198486, 'Val/mean recall': 0.9795392751693726, 'Val/mean hd95_metric': 4.5959906578063965} +Cheakpoint... +Epoch [3586/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.976199746131897, 'Val/mean miou_metric': 0.9622315168380737, 'Val/mean f1': 0.9769095182418823, 'Val/mean precision': 0.9742939472198486, 'Val/mean recall': 0.9795392751693726, 'Val/mean hd95_metric': 4.5959906578063965} +Epoch [3587/4000] Training [1/16] Loss: 0.00354 +Epoch [3587/4000] Training [2/16] Loss: 0.00211 +Epoch [3587/4000] Training [3/16] Loss: 0.00244 +Epoch [3587/4000] Training [4/16] Loss: 0.00229 +Epoch [3587/4000] Training [5/16] Loss: 0.00303 +Epoch [3587/4000] Training [6/16] Loss: 0.00191 +Epoch [3587/4000] Training [7/16] Loss: 0.00660 +Epoch [3587/4000] Training [8/16] Loss: 0.00322 +Epoch [3587/4000] Training [9/16] Loss: 0.00178 +Epoch [3587/4000] Training [10/16] Loss: 0.00170 +Epoch [3587/4000] Training [11/16] Loss: 0.00203 +Epoch [3587/4000] Training [12/16] Loss: 0.00275 +Epoch [3587/4000] Training [13/16] Loss: 0.00190 +Epoch [3587/4000] Training [14/16] Loss: 0.00359 +Epoch [3587/4000] Training [15/16] Loss: 0.00260 +Epoch [3587/4000] Training [16/16] Loss: 0.00493 +Epoch [3587/4000] Training metric {'Train/mean dice_metric': 0.9984645843505859, 'Train/mean miou_metric': 0.9966261386871338, 'Train/mean f1': 0.9929956793785095, 'Train/mean precision': 0.9879187345504761, 'Train/mean recall': 0.9981251358985901, 'Train/mean hd95_metric': 0.6326287984848022} +Epoch [3587/4000] Validation [1/4] Loss: 0.34561 focal_loss 0.28727 dice_loss 0.05834 +Epoch [3587/4000] Validation [2/4] Loss: 0.52932 focal_loss 0.40060 dice_loss 0.12872 +Epoch [3587/4000] Validation [3/4] Loss: 0.30051 focal_loss 0.23955 dice_loss 0.06096 +Epoch [3587/4000] Validation [4/4] Loss: 0.35048 focal_loss 0.26416 dice_loss 0.08632 +Epoch [3587/4000] Validation metric {'Val/mean dice_metric': 0.9749821424484253, 'Val/mean miou_metric': 0.9607526659965515, 'Val/mean f1': 0.9759833812713623, 'Val/mean precision': 0.9730739593505859, 'Val/mean recall': 0.9789102673530579, 'Val/mean hd95_metric': 5.172548770904541} +Cheakpoint... +Epoch [3587/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749821424484253, 'Val/mean miou_metric': 0.9607526659965515, 'Val/mean f1': 0.9759833812713623, 'Val/mean precision': 0.9730739593505859, 'Val/mean recall': 0.9789102673530579, 'Val/mean hd95_metric': 5.172548770904541} +Epoch [3588/4000] Training [1/16] Loss: 0.00207 +Epoch [3588/4000] Training [2/16] Loss: 0.00304 +Epoch [3588/4000] Training [3/16] Loss: 0.00180 +Epoch [3588/4000] Training [4/16] Loss: 0.00208 +Epoch [3588/4000] Training [5/16] Loss: 0.00350 +Epoch [3588/4000] Training [6/16] Loss: 0.00232 +Epoch [3588/4000] Training [7/16] Loss: 0.00238 +Epoch [3588/4000] Training [8/16] Loss: 0.00235 +Epoch [3588/4000] Training [9/16] Loss: 0.00201 +Epoch [3588/4000] Training [10/16] Loss: 0.00186 +Epoch [3588/4000] Training [11/16] Loss: 0.00177 +Epoch [3588/4000] Training [12/16] Loss: 0.00261 +Epoch [3588/4000] Training [13/16] Loss: 0.00170 +Epoch [3588/4000] Training [14/16] Loss: 0.00355 +Epoch [3588/4000] Training [15/16] Loss: 0.00332 +Epoch [3588/4000] Training [16/16] Loss: 0.00296 +Epoch [3588/4000] Training metric {'Train/mean dice_metric': 0.9987720847129822, 'Train/mean miou_metric': 0.9972675442695618, 'Train/mean f1': 0.9937949180603027, 'Train/mean precision': 0.9892199635505676, 'Train/mean recall': 0.9984124302864075, 'Train/mean hd95_metric': 0.5256413221359253} +Epoch [3588/4000] Validation [1/4] Loss: 0.42121 focal_loss 0.35853 dice_loss 0.06268 +Epoch [3588/4000] Validation [2/4] Loss: 0.51129 focal_loss 0.39795 dice_loss 0.11334 +Epoch [3588/4000] Validation [3/4] Loss: 0.53973 focal_loss 0.44704 dice_loss 0.09270 +Epoch [3588/4000] Validation [4/4] Loss: 0.44662 focal_loss 0.33514 dice_loss 0.11148 +Epoch [3588/4000] Validation metric {'Val/mean dice_metric': 0.975320041179657, 'Val/mean miou_metric': 0.9614105224609375, 'Val/mean f1': 0.9764827489852905, 'Val/mean precision': 0.9746212959289551, 'Val/mean recall': 0.9783515334129333, 'Val/mean hd95_metric': 4.599909782409668} +Cheakpoint... +Epoch [3588/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975320041179657, 'Val/mean miou_metric': 0.9614105224609375, 'Val/mean f1': 0.9764827489852905, 'Val/mean precision': 0.9746212959289551, 'Val/mean recall': 0.9783515334129333, 'Val/mean hd95_metric': 4.599909782409668} +Epoch [3589/4000] Training [1/16] Loss: 0.00166 +Epoch [3589/4000] Training [2/16] Loss: 0.00236 +Epoch [3589/4000] Training [3/16] Loss: 0.00221 +Epoch [3589/4000] Training [4/16] Loss: 0.00215 +Epoch [3589/4000] Training [5/16] Loss: 0.00266 +Epoch [3589/4000] Training [6/16] Loss: 0.00358 +Epoch [3589/4000] Training [7/16] Loss: 0.00167 +Epoch [3589/4000] Training [8/16] Loss: 0.00193 +Epoch [3589/4000] Training [9/16] Loss: 0.00322 +Epoch [3589/4000] Training [10/16] Loss: 0.00367 +Epoch [3589/4000] Training [11/16] Loss: 0.00207 +Epoch [3589/4000] Training [12/16] Loss: 0.00284 +Epoch [3589/4000] Training [13/16] Loss: 0.00188 +Epoch [3589/4000] Training [14/16] Loss: 0.00261 +Epoch [3589/4000] Training [15/16] Loss: 0.00157 +Epoch [3589/4000] Training [16/16] Loss: 0.00232 +Epoch [3589/4000] Training metric {'Train/mean dice_metric': 0.9987854957580566, 'Train/mean miou_metric': 0.9972731471061707, 'Train/mean f1': 0.9930678606033325, 'Train/mean precision': 0.9879385828971863, 'Train/mean recall': 0.9982506632804871, 'Train/mean hd95_metric': 0.6068713068962097} +Epoch [3589/4000] Validation [1/4] Loss: 0.38536 focal_loss 0.32490 dice_loss 0.06046 +Epoch [3589/4000] Validation [2/4] Loss: 0.96947 focal_loss 0.78053 dice_loss 0.18895 +Epoch [3589/4000] Validation [3/4] Loss: 0.52780 focal_loss 0.43764 dice_loss 0.09015 +Epoch [3589/4000] Validation [4/4] Loss: 0.33961 focal_loss 0.24846 dice_loss 0.09115 +Epoch [3589/4000] Validation metric {'Val/mean dice_metric': 0.9759937524795532, 'Val/mean miou_metric': 0.9623416066169739, 'Val/mean f1': 0.9762645959854126, 'Val/mean precision': 0.9733362197875977, 'Val/mean recall': 0.9792105555534363, 'Val/mean hd95_metric': 4.840355396270752} +Cheakpoint... +Epoch [3589/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759937524795532, 'Val/mean miou_metric': 0.9623416066169739, 'Val/mean f1': 0.9762645959854126, 'Val/mean precision': 0.9733362197875977, 'Val/mean recall': 0.9792105555534363, 'Val/mean hd95_metric': 4.840355396270752} +Epoch [3590/4000] Training [1/16] Loss: 0.00270 +Epoch [3590/4000] Training [2/16] Loss: 0.00221 +Epoch [3590/4000] Training [3/16] Loss: 0.00182 +Epoch [3590/4000] Training [4/16] Loss: 0.00217 +Epoch [3590/4000] Training [5/16] Loss: 0.00317 +Epoch [3590/4000] Training [6/16] Loss: 0.00221 +Epoch [3590/4000] Training [7/16] Loss: 0.00192 +Epoch [3590/4000] Training [8/16] Loss: 0.00273 +Epoch [3590/4000] Training [9/16] Loss: 0.00343 +Epoch [3590/4000] Training [10/16] Loss: 0.00288 +Epoch [3590/4000] Training [11/16] Loss: 0.00174 +Epoch [3590/4000] Training [12/16] Loss: 0.00238 +Epoch [3590/4000] Training [13/16] Loss: 0.00230 +Epoch [3590/4000] Training [14/16] Loss: 0.00248 +Epoch [3590/4000] Training [15/16] Loss: 0.00227 +Epoch [3590/4000] Training [16/16] Loss: 0.00220 +Epoch [3590/4000] Training metric {'Train/mean dice_metric': 0.9987818598747253, 'Train/mean miou_metric': 0.9972774982452393, 'Train/mean f1': 0.9936909675598145, 'Train/mean precision': 0.9890516996383667, 'Train/mean recall': 0.9983739256858826, 'Train/mean hd95_metric': 0.5116289854049683} +Epoch [3590/4000] Validation [1/4] Loss: 0.43965 focal_loss 0.37084 dice_loss 0.06881 +Epoch [3590/4000] Validation [2/4] Loss: 0.49958 focal_loss 0.38400 dice_loss 0.11558 +Epoch [3590/4000] Validation [3/4] Loss: 0.32237 focal_loss 0.25125 dice_loss 0.07113 +Epoch [3590/4000] Validation [4/4] Loss: 0.50540 focal_loss 0.38952 dice_loss 0.11588 +Epoch [3590/4000] Validation metric {'Val/mean dice_metric': 0.975375771522522, 'Val/mean miou_metric': 0.9609362483024597, 'Val/mean f1': 0.9758349061012268, 'Val/mean precision': 0.9731469750404358, 'Val/mean recall': 0.9785375595092773, 'Val/mean hd95_metric': 5.630535125732422} +Cheakpoint... +Epoch [3590/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975375771522522, 'Val/mean miou_metric': 0.9609362483024597, 'Val/mean f1': 0.9758349061012268, 'Val/mean precision': 0.9731469750404358, 'Val/mean recall': 0.9785375595092773, 'Val/mean hd95_metric': 5.630535125732422} +Epoch [3591/4000] Training [1/16] Loss: 0.00162 +Epoch [3591/4000] Training [2/16] Loss: 0.00247 +Epoch [3591/4000] Training [3/16] Loss: 0.00215 +Epoch [3591/4000] Training [4/16] Loss: 0.00171 +Epoch [3591/4000] Training [5/16] Loss: 0.00178 +Epoch [3591/4000] Training [6/16] Loss: 0.00214 +Epoch [3591/4000] Training [7/16] Loss: 0.00199 +Epoch [3591/4000] Training [8/16] Loss: 0.00362 +Epoch [3591/4000] Training [9/16] Loss: 0.00167 +Epoch [3591/4000] Training [10/16] Loss: 0.00350 +Epoch [3591/4000] Training [11/16] Loss: 0.00261 +Epoch [3591/4000] Training [12/16] Loss: 0.00237 +Epoch [3591/4000] Training [13/16] Loss: 0.00375 +Epoch [3591/4000] Training [14/16] Loss: 0.00159 +Epoch [3591/4000] Training [15/16] Loss: 0.00280 +Epoch [3591/4000] Training [16/16] Loss: 0.00237 +Epoch [3591/4000] Training metric {'Train/mean dice_metric': 0.9988178610801697, 'Train/mean miou_metric': 0.9973633289337158, 'Train/mean f1': 0.9938420653343201, 'Train/mean precision': 0.9893448352813721, 'Train/mean recall': 0.9983803629875183, 'Train/mean hd95_metric': 0.5333884954452515} +Epoch [3591/4000] Validation [1/4] Loss: 0.39908 focal_loss 0.33484 dice_loss 0.06423 +Epoch [3591/4000] Validation [2/4] Loss: 0.50890 focal_loss 0.39472 dice_loss 0.11418 +Epoch [3591/4000] Validation [3/4] Loss: 0.57143 focal_loss 0.47602 dice_loss 0.09541 +Epoch [3591/4000] Validation [4/4] Loss: 0.49263 focal_loss 0.37833 dice_loss 0.11431 +Epoch [3591/4000] Validation metric {'Val/mean dice_metric': 0.9727533459663391, 'Val/mean miou_metric': 0.9587756991386414, 'Val/mean f1': 0.9759268164634705, 'Val/mean precision': 0.9741678833961487, 'Val/mean recall': 0.9776923060417175, 'Val/mean hd95_metric': 5.009203910827637} +Cheakpoint... +Epoch [3591/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727533459663391, 'Val/mean miou_metric': 0.9587756991386414, 'Val/mean f1': 0.9759268164634705, 'Val/mean precision': 0.9741678833961487, 'Val/mean recall': 0.9776923060417175, 'Val/mean hd95_metric': 5.009203910827637} +Epoch [3592/4000] Training [1/16] Loss: 0.00399 +Epoch [3592/4000] Training [2/16] Loss: 0.00217 +Epoch [3592/4000] Training [3/16] Loss: 0.00239 +Epoch [3592/4000] Training [4/16] Loss: 0.00275 +Epoch [3592/4000] Training [5/16] Loss: 0.00317 +Epoch [3592/4000] Training [6/16] Loss: 0.00254 +Epoch [3592/4000] Training [7/16] Loss: 0.00213 +Epoch [3592/4000] Training [8/16] Loss: 0.00166 +Epoch [3592/4000] Training [9/16] Loss: 0.00294 +Epoch [3592/4000] Training [10/16] Loss: 0.00153 +Epoch [3592/4000] Training [11/16] Loss: 0.00294 +Epoch [3592/4000] Training [12/16] Loss: 0.00307 +Epoch [3592/4000] Training [13/16] Loss: 0.00226 +Epoch [3592/4000] Training [14/16] Loss: 0.00243 +Epoch [3592/4000] Training [15/16] Loss: 0.00205 +Epoch [3592/4000] Training [16/16] Loss: 0.00262 +Epoch [3592/4000] Training metric {'Train/mean dice_metric': 0.9986985921859741, 'Train/mean miou_metric': 0.997055172920227, 'Train/mean f1': 0.9924810528755188, 'Train/mean precision': 0.9868664741516113, 'Train/mean recall': 0.9981598854064941, 'Train/mean hd95_metric': 0.5765900611877441} +Epoch [3592/4000] Validation [1/4] Loss: 0.34813 focal_loss 0.28756 dice_loss 0.06057 +Epoch [3592/4000] Validation [2/4] Loss: 1.04025 focal_loss 0.84377 dice_loss 0.19649 +Epoch [3592/4000] Validation [3/4] Loss: 0.54745 focal_loss 0.45200 dice_loss 0.09545 +Epoch [3592/4000] Validation [4/4] Loss: 0.33844 focal_loss 0.25499 dice_loss 0.08345 +Epoch [3592/4000] Validation metric {'Val/mean dice_metric': 0.9742418527603149, 'Val/mean miou_metric': 0.9599323272705078, 'Val/mean f1': 0.9755339026451111, 'Val/mean precision': 0.9722625017166138, 'Val/mean recall': 0.9788273572921753, 'Val/mean hd95_metric': 5.504408836364746} +Cheakpoint... +Epoch [3592/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742418527603149, 'Val/mean miou_metric': 0.9599323272705078, 'Val/mean f1': 0.9755339026451111, 'Val/mean precision': 0.9722625017166138, 'Val/mean recall': 0.9788273572921753, 'Val/mean hd95_metric': 5.504408836364746} +Epoch [3593/4000] Training [1/16] Loss: 0.00230 +Epoch [3593/4000] Training [2/16] Loss: 0.00265 +Epoch [3593/4000] Training [3/16] Loss: 0.00256 +Epoch [3593/4000] Training [4/16] Loss: 0.00285 +Epoch [3593/4000] Training [5/16] Loss: 0.00276 +Epoch [3593/4000] Training [6/16] Loss: 0.00193 +Epoch [3593/4000] Training [7/16] Loss: 0.00151 +Epoch [3593/4000] Training [8/16] Loss: 0.00168 +Epoch [3593/4000] Training [9/16] Loss: 0.00206 +Epoch [3593/4000] Training [10/16] Loss: 0.00322 +Epoch [3593/4000] Training [11/16] Loss: 0.00177 +Epoch [3593/4000] Training [12/16] Loss: 0.00211 +Epoch [3593/4000] Training [13/16] Loss: 0.00213 +Epoch [3593/4000] Training [14/16] Loss: 0.00300 +Epoch [3593/4000] Training [15/16] Loss: 0.00196 +Epoch [3593/4000] Training [16/16] Loss: 0.00212 +Epoch [3593/4000] Training metric {'Train/mean dice_metric': 0.9988237619400024, 'Train/mean miou_metric': 0.9973769783973694, 'Train/mean f1': 0.9937942028045654, 'Train/mean precision': 0.9892000555992126, 'Train/mean recall': 0.9984312057495117, 'Train/mean hd95_metric': 0.5301600098609924} +Epoch [3593/4000] Validation [1/4] Loss: 0.40634 focal_loss 0.34283 dice_loss 0.06351 +Epoch [3593/4000] Validation [2/4] Loss: 0.65910 focal_loss 0.48613 dice_loss 0.17298 +Epoch [3593/4000] Validation [3/4] Loss: 0.54392 focal_loss 0.45255 dice_loss 0.09137 +Epoch [3593/4000] Validation [4/4] Loss: 0.28993 focal_loss 0.20783 dice_loss 0.08210 +Epoch [3593/4000] Validation metric {'Val/mean dice_metric': 0.9735881686210632, 'Val/mean miou_metric': 0.959675669670105, 'Val/mean f1': 0.9756609797477722, 'Val/mean precision': 0.9736812114715576, 'Val/mean recall': 0.9776488542556763, 'Val/mean hd95_metric': 4.880943775177002} +Cheakpoint... +Epoch [3593/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735881686210632, 'Val/mean miou_metric': 0.959675669670105, 'Val/mean f1': 0.9756609797477722, 'Val/mean precision': 0.9736812114715576, 'Val/mean recall': 0.9776488542556763, 'Val/mean hd95_metric': 4.880943775177002} +Epoch [3594/4000] Training [1/16] Loss: 0.00191 +Epoch [3594/4000] Training [2/16] Loss: 0.00354 +Epoch [3594/4000] Training [3/16] Loss: 0.00231 +Epoch [3594/4000] Training [4/16] Loss: 0.00205 +Epoch [3594/4000] Training [5/16] Loss: 0.00262 +Epoch [3594/4000] Training [6/16] Loss: 0.00174 +Epoch [3594/4000] Training [7/16] Loss: 0.00211 +Epoch [3594/4000] Training [8/16] Loss: 0.00230 +Epoch [3594/4000] Training [9/16] Loss: 0.00147 +Epoch [3594/4000] Training [10/16] Loss: 0.00208 +Epoch [3594/4000] Training [11/16] Loss: 0.00155 +Epoch [3594/4000] Training [12/16] Loss: 0.00215 +Epoch [3594/4000] Training [13/16] Loss: 0.00153 +Epoch [3594/4000] Training [14/16] Loss: 0.00167 +Epoch [3594/4000] Training [15/16] Loss: 0.00399 +Epoch [3594/4000] Training [16/16] Loss: 0.00125 +Epoch [3594/4000] Training metric {'Train/mean dice_metric': 0.9988889098167419, 'Train/mean miou_metric': 0.9974979758262634, 'Train/mean f1': 0.9938273429870605, 'Train/mean precision': 0.9892577528953552, 'Train/mean recall': 0.9984393119812012, 'Train/mean hd95_metric': 0.48423492908477783} +Epoch [3594/4000] Validation [1/4] Loss: 0.41694 focal_loss 0.35430 dice_loss 0.06264 +Epoch [3594/4000] Validation [2/4] Loss: 1.02681 focal_loss 0.77936 dice_loss 0.24745 +Epoch [3594/4000] Validation [3/4] Loss: 0.52536 focal_loss 0.43468 dice_loss 0.09068 +Epoch [3594/4000] Validation [4/4] Loss: 0.33680 focal_loss 0.25213 dice_loss 0.08467 +Epoch [3594/4000] Validation metric {'Val/mean dice_metric': 0.9721515774726868, 'Val/mean miou_metric': 0.9587723016738892, 'Val/mean f1': 0.9761191606521606, 'Val/mean precision': 0.9742312431335449, 'Val/mean recall': 0.9780144691467285, 'Val/mean hd95_metric': 4.994194507598877} +Cheakpoint... +Epoch [3594/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721515774726868, 'Val/mean miou_metric': 0.9587723016738892, 'Val/mean f1': 0.9761191606521606, 'Val/mean precision': 0.9742312431335449, 'Val/mean recall': 0.9780144691467285, 'Val/mean hd95_metric': 4.994194507598877} +Epoch [3595/4000] Training [1/16] Loss: 0.00279 +Epoch [3595/4000] Training [2/16] Loss: 0.00270 +Epoch [3595/4000] Training [3/16] Loss: 0.00287 +Epoch [3595/4000] Training [4/16] Loss: 0.00194 +Epoch [3595/4000] Training [5/16] Loss: 0.00328 +Epoch [3595/4000] Training [6/16] Loss: 0.00185 +Epoch [3595/4000] Training [7/16] Loss: 0.00278 +Epoch [3595/4000] Training [8/16] Loss: 0.00262 +Epoch [3595/4000] Training [9/16] Loss: 0.00217 +Epoch [3595/4000] Training [10/16] Loss: 0.00267 +Epoch [3595/4000] Training [11/16] Loss: 0.00153 +Epoch [3595/4000] Training [12/16] Loss: 0.00183 +Epoch [3595/4000] Training [13/16] Loss: 0.00264 +Epoch [3595/4000] Training [14/16] Loss: 0.00277 +Epoch [3595/4000] Training [15/16] Loss: 0.00177 +Epoch [3595/4000] Training [16/16] Loss: 0.00226 +Epoch [3595/4000] Training metric {'Train/mean dice_metric': 0.9987232089042664, 'Train/mean miou_metric': 0.9971603155136108, 'Train/mean f1': 0.9935937523841858, 'Train/mean precision': 0.9888783693313599, 'Train/mean recall': 0.9983543157577515, 'Train/mean hd95_metric': 0.548172116279602} +Epoch [3595/4000] Validation [1/4] Loss: 0.40863 focal_loss 0.34009 dice_loss 0.06854 +Epoch [3595/4000] Validation [2/4] Loss: 1.14565 focal_loss 0.94235 dice_loss 0.20330 +Epoch [3595/4000] Validation [3/4] Loss: 0.53578 focal_loss 0.44069 dice_loss 0.09510 +Epoch [3595/4000] Validation [4/4] Loss: 0.37891 focal_loss 0.26969 dice_loss 0.10922 +Epoch [3595/4000] Validation metric {'Val/mean dice_metric': 0.9731172323226929, 'Val/mean miou_metric': 0.9588598012924194, 'Val/mean f1': 0.975485622882843, 'Val/mean precision': 0.9729620814323425, 'Val/mean recall': 0.9780222773551941, 'Val/mean hd95_metric': 5.231719970703125} +Cheakpoint... +Epoch [3595/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731172323226929, 'Val/mean miou_metric': 0.9588598012924194, 'Val/mean f1': 0.975485622882843, 'Val/mean precision': 0.9729620814323425, 'Val/mean recall': 0.9780222773551941, 'Val/mean hd95_metric': 5.231719970703125} +Epoch [3596/4000] Training [1/16] Loss: 0.00172 +Epoch [3596/4000] Training [2/16] Loss: 0.00263 +Epoch [3596/4000] Training [3/16] Loss: 0.00252 +Epoch [3596/4000] Training [4/16] Loss: 0.00313 +Epoch [3596/4000] Training [5/16] Loss: 0.00272 +Epoch [3596/4000] Training [6/16] Loss: 0.00191 +Epoch [3596/4000] Training [7/16] Loss: 0.00211 +Epoch [3596/4000] Training [8/16] Loss: 0.00254 +Epoch [3596/4000] Training [9/16] Loss: 0.00380 +Epoch [3596/4000] Training [10/16] Loss: 0.00349 +Epoch [3596/4000] Training [11/16] Loss: 0.00206 +Epoch [3596/4000] Training [12/16] Loss: 0.00193 +Epoch [3596/4000] Training [13/16] Loss: 0.00171 +Epoch [3596/4000] Training [14/16] Loss: 0.00184 +Epoch [3596/4000] Training [15/16] Loss: 0.00383 +Epoch [3596/4000] Training [16/16] Loss: 0.00242 +Epoch [3596/4000] Training metric {'Train/mean dice_metric': 0.9988030195236206, 'Train/mean miou_metric': 0.9973297715187073, 'Train/mean f1': 0.9937548637390137, 'Train/mean precision': 0.9891741871833801, 'Train/mean recall': 0.9983782172203064, 'Train/mean hd95_metric': 0.5514726638793945} +Epoch [3596/4000] Validation [1/4] Loss: 0.37400 focal_loss 0.31290 dice_loss 0.06110 +Epoch [3596/4000] Validation [2/4] Loss: 0.54805 focal_loss 0.41858 dice_loss 0.12947 +Epoch [3596/4000] Validation [3/4] Loss: 0.54309 focal_loss 0.45033 dice_loss 0.09275 +Epoch [3596/4000] Validation [4/4] Loss: 0.46686 focal_loss 0.35583 dice_loss 0.11104 +Epoch [3596/4000] Validation metric {'Val/mean dice_metric': 0.9740127325057983, 'Val/mean miou_metric': 0.9598096609115601, 'Val/mean f1': 0.9761179685592651, 'Val/mean precision': 0.973518967628479, 'Val/mean recall': 0.9787306785583496, 'Val/mean hd95_metric': 5.037023067474365} +Cheakpoint... +Epoch [3596/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740127325057983, 'Val/mean miou_metric': 0.9598096609115601, 'Val/mean f1': 0.9761179685592651, 'Val/mean precision': 0.973518967628479, 'Val/mean recall': 0.9787306785583496, 'Val/mean hd95_metric': 5.037023067474365} +Epoch [3597/4000] Training [1/16] Loss: 0.00271 +Epoch [3597/4000] Training [2/16] Loss: 0.00157 +Epoch [3597/4000] Training [3/16] Loss: 0.00303 +Epoch [3597/4000] Training [4/16] Loss: 0.00310 +Epoch [3597/4000] Training [5/16] Loss: 0.00225 +Epoch [3597/4000] Training [6/16] Loss: 0.00335 +Epoch [3597/4000] Training [7/16] Loss: 0.00207 +Epoch [3597/4000] Training [8/16] Loss: 0.00192 +Epoch [3597/4000] Training [9/16] Loss: 0.00181 +Epoch [3597/4000] Training [10/16] Loss: 0.00255 +Epoch [3597/4000] Training [11/16] Loss: 0.00182 +Epoch [3597/4000] Training [12/16] Loss: 0.00179 +Epoch [3597/4000] Training [13/16] Loss: 0.00244 +Epoch [3597/4000] Training [14/16] Loss: 0.00239 +Epoch [3597/4000] Training [15/16] Loss: 0.00246 +Epoch [3597/4000] Training [16/16] Loss: 0.00291 +Epoch [3597/4000] Training metric {'Train/mean dice_metric': 0.9987810850143433, 'Train/mean miou_metric': 0.9972765445709229, 'Train/mean f1': 0.9937146902084351, 'Train/mean precision': 0.9891157746315002, 'Train/mean recall': 0.9983565807342529, 'Train/mean hd95_metric': 0.5483675003051758} +Epoch [3597/4000] Validation [1/4] Loss: 0.41293 focal_loss 0.34752 dice_loss 0.06541 +Epoch [3597/4000] Validation [2/4] Loss: 0.51393 focal_loss 0.40219 dice_loss 0.11174 +Epoch [3597/4000] Validation [3/4] Loss: 0.52455 focal_loss 0.43323 dice_loss 0.09132 +Epoch [3597/4000] Validation [4/4] Loss: 0.34185 focal_loss 0.25208 dice_loss 0.08978 +Epoch [3597/4000] Validation metric {'Val/mean dice_metric': 0.9761110544204712, 'Val/mean miou_metric': 0.9619113802909851, 'Val/mean f1': 0.9763336777687073, 'Val/mean precision': 0.9739925265312195, 'Val/mean recall': 0.9786860942840576, 'Val/mean hd95_metric': 4.689044952392578} +Cheakpoint... +Epoch [3597/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9761], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9761110544204712, 'Val/mean miou_metric': 0.9619113802909851, 'Val/mean f1': 0.9763336777687073, 'Val/mean precision': 0.9739925265312195, 'Val/mean recall': 0.9786860942840576, 'Val/mean hd95_metric': 4.689044952392578} +Epoch [3598/4000] Training [1/16] Loss: 0.00288 +Epoch [3598/4000] Training [2/16] Loss: 0.00397 +Epoch [3598/4000] Training [3/16] Loss: 0.00289 +Epoch [3598/4000] Training [4/16] Loss: 0.00166 +Epoch [3598/4000] Training [5/16] Loss: 0.00295 +Epoch [3598/4000] Training [6/16] Loss: 0.00232 +Epoch [3598/4000] Training [7/16] Loss: 0.00188 +Epoch [3598/4000] Training [8/16] Loss: 0.00285 +Epoch [3598/4000] Training [9/16] Loss: 0.00266 +Epoch [3598/4000] Training [10/16] Loss: 0.00186 +Epoch [3598/4000] Training [11/16] Loss: 0.00208 +Epoch [3598/4000] Training [12/16] Loss: 0.00196 +Epoch [3598/4000] Training [13/16] Loss: 0.00274 +Epoch [3598/4000] Training [14/16] Loss: 0.00172 +Epoch [3598/4000] Training [15/16] Loss: 0.00361 +Epoch [3598/4000] Training [16/16] Loss: 0.00193 +Epoch [3598/4000] Training metric {'Train/mean dice_metric': 0.9987037181854248, 'Train/mean miou_metric': 0.9971022605895996, 'Train/mean f1': 0.9930904507637024, 'Train/mean precision': 0.9879316091537476, 'Train/mean recall': 0.9983034729957581, 'Train/mean hd95_metric': 0.5536432266235352} +Epoch [3598/4000] Validation [1/4] Loss: 0.34441 focal_loss 0.28546 dice_loss 0.05895 +Epoch [3598/4000] Validation [2/4] Loss: 1.08667 focal_loss 0.90210 dice_loss 0.18457 +Epoch [3598/4000] Validation [3/4] Loss: 0.53934 focal_loss 0.44296 dice_loss 0.09638 +Epoch [3598/4000] Validation [4/4] Loss: 0.36538 focal_loss 0.26390 dice_loss 0.10148 +Epoch [3598/4000] Validation metric {'Val/mean dice_metric': 0.9739993810653687, 'Val/mean miou_metric': 0.9602231979370117, 'Val/mean f1': 0.9755178093910217, 'Val/mean precision': 0.9729419350624084, 'Val/mean recall': 0.9781075119972229, 'Val/mean hd95_metric': 4.998733997344971} +Cheakpoint... +Epoch [3598/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739993810653687, 'Val/mean miou_metric': 0.9602231979370117, 'Val/mean f1': 0.9755178093910217, 'Val/mean precision': 0.9729419350624084, 'Val/mean recall': 0.9781075119972229, 'Val/mean hd95_metric': 4.998733997344971} +Epoch [3599/4000] Training [1/16] Loss: 0.00165 +Epoch [3599/4000] Training [2/16] Loss: 0.00259 +Epoch [3599/4000] Training [3/16] Loss: 0.00219 +Epoch [3599/4000] Training [4/16] Loss: 0.00227 +Epoch [3599/4000] Training [5/16] Loss: 0.00423 +Epoch [3599/4000] Training [6/16] Loss: 0.00220 +Epoch [3599/4000] Training [7/16] Loss: 0.00169 +Epoch [3599/4000] Training [8/16] Loss: 0.00261 +Epoch [3599/4000] Training [9/16] Loss: 0.00213 +Epoch [3599/4000] Training [10/16] Loss: 0.00340 +Epoch [3599/4000] Training [11/16] Loss: 0.00241 +Epoch [3599/4000] Training [12/16] Loss: 0.00262 +Epoch [3599/4000] Training [13/16] Loss: 0.00350 +Epoch [3599/4000] Training [14/16] Loss: 0.00193 +Epoch [3599/4000] Training [15/16] Loss: 0.00158 +Epoch [3599/4000] Training [16/16] Loss: 0.00201 +Epoch [3599/4000] Training metric {'Train/mean dice_metric': 0.9986765384674072, 'Train/mean miou_metric': 0.997070848941803, 'Train/mean f1': 0.9935084581375122, 'Train/mean precision': 0.9888074398040771, 'Train/mean recall': 0.9982543587684631, 'Train/mean hd95_metric': 0.583258330821991} +Epoch [3599/4000] Validation [1/4] Loss: 0.38551 focal_loss 0.32280 dice_loss 0.06271 +Epoch [3599/4000] Validation [2/4] Loss: 0.90293 focal_loss 0.70436 dice_loss 0.19857 +Epoch [3599/4000] Validation [3/4] Loss: 0.55823 focal_loss 0.46502 dice_loss 0.09321 +Epoch [3599/4000] Validation [4/4] Loss: 0.36064 focal_loss 0.27089 dice_loss 0.08975 +Epoch [3599/4000] Validation metric {'Val/mean dice_metric': 0.9739478826522827, 'Val/mean miou_metric': 0.9600000381469727, 'Val/mean f1': 0.9761545062065125, 'Val/mean precision': 0.9733853936195374, 'Val/mean recall': 0.9789392948150635, 'Val/mean hd95_metric': 4.883787631988525} +Cheakpoint... +Epoch [3599/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739478826522827, 'Val/mean miou_metric': 0.9600000381469727, 'Val/mean f1': 0.9761545062065125, 'Val/mean precision': 0.9733853936195374, 'Val/mean recall': 0.9789392948150635, 'Val/mean hd95_metric': 4.883787631988525} +Epoch [3600/4000] Training [1/16] Loss: 0.00256 +Epoch [3600/4000] Training [2/16] Loss: 0.00172 +Epoch [3600/4000] Training [3/16] Loss: 0.00201 +Epoch [3600/4000] Training [4/16] Loss: 0.00334 +Epoch [3600/4000] Training [5/16] Loss: 0.00364 +Epoch [3600/4000] Training [6/16] Loss: 0.00254 +Epoch [3600/4000] Training [7/16] Loss: 0.00225 +Epoch [3600/4000] Training [8/16] Loss: 0.00223 +Epoch [3600/4000] Training [9/16] Loss: 0.00200 +Epoch [3600/4000] Training [10/16] Loss: 0.00230 +Epoch [3600/4000] Training [11/16] Loss: 0.00202 +Epoch [3600/4000] Training [12/16] Loss: 0.00253 +Epoch [3600/4000] Training [13/16] Loss: 0.00351 +Epoch [3600/4000] Training [14/16] Loss: 0.00229 +Epoch [3600/4000] Training [15/16] Loss: 0.00274 +Epoch [3600/4000] Training [16/16] Loss: 0.00216 +Epoch [3600/4000] Training metric {'Train/mean dice_metric': 0.9987806081771851, 'Train/mean miou_metric': 0.997264564037323, 'Train/mean f1': 0.9935759902000427, 'Train/mean precision': 0.9888288974761963, 'Train/mean recall': 0.9983689188957214, 'Train/mean hd95_metric': 0.514676034450531} +Epoch [3600/4000] Validation [1/4] Loss: 0.40475 focal_loss 0.34045 dice_loss 0.06430 +Epoch [3600/4000] Validation [2/4] Loss: 0.92000 focal_loss 0.72092 dice_loss 0.19907 +Epoch [3600/4000] Validation [3/4] Loss: 0.54577 focal_loss 0.45469 dice_loss 0.09108 +Epoch [3600/4000] Validation [4/4] Loss: 0.35036 focal_loss 0.26308 dice_loss 0.08728 +Epoch [3600/4000] Validation metric {'Val/mean dice_metric': 0.9725629091262817, 'Val/mean miou_metric': 0.9587095379829407, 'Val/mean f1': 0.9757001996040344, 'Val/mean precision': 0.9735884070396423, 'Val/mean recall': 0.977821409702301, 'Val/mean hd95_metric': 4.895668983459473} +Cheakpoint... +Epoch [3600/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725629091262817, 'Val/mean miou_metric': 0.9587095379829407, 'Val/mean f1': 0.9757001996040344, 'Val/mean precision': 0.9735884070396423, 'Val/mean recall': 0.977821409702301, 'Val/mean hd95_metric': 4.895668983459473} +Epoch [3601/4000] Training [1/16] Loss: 0.00269 +Epoch [3601/4000] Training [2/16] Loss: 0.00225 +Epoch [3601/4000] Training [3/16] Loss: 0.00216 +Epoch [3601/4000] Training [4/16] Loss: 0.00230 +Epoch [3601/4000] Training [5/16] Loss: 0.00280 +Epoch [3601/4000] Training [6/16] Loss: 0.00195 +Epoch [3601/4000] Training [7/16] Loss: 0.00252 +Epoch [3601/4000] Training [8/16] Loss: 0.00147 +Epoch [3601/4000] Training [9/16] Loss: 0.00302 +Epoch [3601/4000] Training [10/16] Loss: 0.00295 +Epoch [3601/4000] Training [11/16] Loss: 0.00225 +Epoch [3601/4000] Training [12/16] Loss: 0.00184 +Epoch [3601/4000] Training [13/16] Loss: 0.00230 +Epoch [3601/4000] Training [14/16] Loss: 0.00229 +Epoch [3601/4000] Training [15/16] Loss: 0.00259 +Epoch [3601/4000] Training [16/16] Loss: 0.00246 +Epoch [3601/4000] Training metric {'Train/mean dice_metric': 0.9987773299217224, 'Train/mean miou_metric': 0.9972808361053467, 'Train/mean f1': 0.9937179088592529, 'Train/mean precision': 0.9891332983970642, 'Train/mean recall': 0.9983452558517456, 'Train/mean hd95_metric': 0.5165365934371948} +Epoch [3601/4000] Validation [1/4] Loss: 0.46664 focal_loss 0.40169 dice_loss 0.06496 +Epoch [3601/4000] Validation [2/4] Loss: 0.49912 focal_loss 0.38753 dice_loss 0.11159 +Epoch [3601/4000] Validation [3/4] Loss: 0.52474 focal_loss 0.42838 dice_loss 0.09636 +Epoch [3601/4000] Validation [4/4] Loss: 0.35115 focal_loss 0.25746 dice_loss 0.09368 +Epoch [3601/4000] Validation metric {'Val/mean dice_metric': 0.9742395281791687, 'Val/mean miou_metric': 0.960295557975769, 'Val/mean f1': 0.9760528206825256, 'Val/mean precision': 0.974128246307373, 'Val/mean recall': 0.9779850244522095, 'Val/mean hd95_metric': 4.55379581451416} +Cheakpoint... +Epoch [3601/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742395281791687, 'Val/mean miou_metric': 0.960295557975769, 'Val/mean f1': 0.9760528206825256, 'Val/mean precision': 0.974128246307373, 'Val/mean recall': 0.9779850244522095, 'Val/mean hd95_metric': 4.55379581451416} +Epoch [3602/4000] Training [1/16] Loss: 0.00177 +Epoch [3602/4000] Training [2/16] Loss: 0.00277 +Epoch [3602/4000] Training [3/16] Loss: 0.00344 +Epoch [3602/4000] Training [4/16] Loss: 0.00342 +Epoch [3602/4000] Training [5/16] Loss: 0.00232 +Epoch [3602/4000] Training [6/16] Loss: 0.00391 +Epoch [3602/4000] Training [7/16] Loss: 0.00291 +Epoch [3602/4000] Training [8/16] Loss: 0.00149 +Epoch [3602/4000] Training [9/16] Loss: 0.00278 +Epoch [3602/4000] Training [10/16] Loss: 0.00292 +Epoch [3602/4000] Training [11/16] Loss: 0.00183 +Epoch [3602/4000] Training [12/16] Loss: 0.00263 +Epoch [3602/4000] Training [13/16] Loss: 0.00256 +Epoch [3602/4000] Training [14/16] Loss: 0.00227 +Epoch [3602/4000] Training [15/16] Loss: 0.00183 +Epoch [3602/4000] Training [16/16] Loss: 0.00176 +Epoch [3602/4000] Training metric {'Train/mean dice_metric': 0.9986806511878967, 'Train/mean miou_metric': 0.9970903992652893, 'Train/mean f1': 0.9937389492988586, 'Train/mean precision': 0.9892573356628418, 'Train/mean recall': 0.9982614517211914, 'Train/mean hd95_metric': 0.5442657470703125} +Epoch [3602/4000] Validation [1/4] Loss: 0.42418 focal_loss 0.36085 dice_loss 0.06333 +Epoch [3602/4000] Validation [2/4] Loss: 0.52876 focal_loss 0.41551 dice_loss 0.11325 +Epoch [3602/4000] Validation [3/4] Loss: 0.52405 focal_loss 0.43473 dice_loss 0.08932 +Epoch [3602/4000] Validation [4/4] Loss: 0.52120 focal_loss 0.39605 dice_loss 0.12515 +Epoch [3602/4000] Validation metric {'Val/mean dice_metric': 0.9753677248954773, 'Val/mean miou_metric': 0.9610974192619324, 'Val/mean f1': 0.9763904809951782, 'Val/mean precision': 0.9736602902412415, 'Val/mean recall': 0.9791359305381775, 'Val/mean hd95_metric': 4.899892330169678} +Cheakpoint... +Epoch [3602/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753677248954773, 'Val/mean miou_metric': 0.9610974192619324, 'Val/mean f1': 0.9763904809951782, 'Val/mean precision': 0.9736602902412415, 'Val/mean recall': 0.9791359305381775, 'Val/mean hd95_metric': 4.899892330169678} +Epoch [3603/4000] Training [1/16] Loss: 0.00225 +Epoch [3603/4000] Training [2/16] Loss: 0.00324 +Epoch [3603/4000] Training [3/16] Loss: 0.00310 +Epoch [3603/4000] Training [4/16] Loss: 0.00174 +Epoch [3603/4000] Training [5/16] Loss: 0.00171 +Epoch [3603/4000] Training [6/16] Loss: 0.00209 +Epoch [3603/4000] Training [7/16] Loss: 0.00244 +Epoch [3603/4000] Training [8/16] Loss: 0.00286 +Epoch [3603/4000] Training [9/16] Loss: 0.00223 +Epoch [3603/4000] Training [10/16] Loss: 0.00215 +Epoch [3603/4000] Training [11/16] Loss: 0.00363 +Epoch [3603/4000] Training [12/16] Loss: 0.00230 +Epoch [3603/4000] Training [13/16] Loss: 0.00248 +Epoch [3603/4000] Training [14/16] Loss: 0.00238 +Epoch [3603/4000] Training [15/16] Loss: 0.00227 +Epoch [3603/4000] Training [16/16] Loss: 0.00206 +Epoch [3603/4000] Training metric {'Train/mean dice_metric': 0.998766303062439, 'Train/mean miou_metric': 0.997256875038147, 'Train/mean f1': 0.9937737584114075, 'Train/mean precision': 0.9892228841781616, 'Train/mean recall': 0.9983667135238647, 'Train/mean hd95_metric': 0.5371091365814209} +Epoch [3603/4000] Validation [1/4] Loss: 0.41218 focal_loss 0.34837 dice_loss 0.06381 +Epoch [3603/4000] Validation [2/4] Loss: 0.91957 focal_loss 0.71658 dice_loss 0.20299 +Epoch [3603/4000] Validation [3/4] Loss: 0.50507 focal_loss 0.41855 dice_loss 0.08652 +Epoch [3603/4000] Validation [4/4] Loss: 0.46188 focal_loss 0.35155 dice_loss 0.11033 +Epoch [3603/4000] Validation metric {'Val/mean dice_metric': 0.9730775952339172, 'Val/mean miou_metric': 0.9590042233467102, 'Val/mean f1': 0.9756887555122375, 'Val/mean precision': 0.9727596640586853, 'Val/mean recall': 0.9786353707313538, 'Val/mean hd95_metric': 4.933901309967041} +Cheakpoint... +Epoch [3603/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730775952339172, 'Val/mean miou_metric': 0.9590042233467102, 'Val/mean f1': 0.9756887555122375, 'Val/mean precision': 0.9727596640586853, 'Val/mean recall': 0.9786353707313538, 'Val/mean hd95_metric': 4.933901309967041} +Epoch [3604/4000] Training [1/16] Loss: 0.00242 +Epoch [3604/4000] Training [2/16] Loss: 0.00183 +Epoch [3604/4000] Training [3/16] Loss: 0.00206 +Epoch [3604/4000] Training [4/16] Loss: 0.00240 +Epoch [3604/4000] Training [5/16] Loss: 0.00277 +Epoch [3604/4000] Training [6/16] Loss: 0.00204 +Epoch [3604/4000] Training [7/16] Loss: 0.00240 +Epoch [3604/4000] Training [8/16] Loss: 0.00214 +Epoch [3604/4000] Training [9/16] Loss: 0.00257 +Epoch [3604/4000] Training [10/16] Loss: 0.00157 +Epoch [3604/4000] Training [11/16] Loss: 0.00320 +Epoch [3604/4000] Training [12/16] Loss: 0.00216 +Epoch [3604/4000] Training [13/16] Loss: 0.00216 +Epoch [3604/4000] Training [14/16] Loss: 0.00280 +Epoch [3604/4000] Training [15/16] Loss: 0.00285 +Epoch [3604/4000] Training [16/16] Loss: 0.00200 +Epoch [3604/4000] Training metric {'Train/mean dice_metric': 0.9988227486610413, 'Train/mean miou_metric': 0.9973551034927368, 'Train/mean f1': 0.9936104416847229, 'Train/mean precision': 0.9889360070228577, 'Train/mean recall': 0.998329222202301, 'Train/mean hd95_metric': 0.538601815700531} +Epoch [3604/4000] Validation [1/4] Loss: 0.39943 focal_loss 0.33623 dice_loss 0.06320 +Epoch [3604/4000] Validation [2/4] Loss: 0.57009 focal_loss 0.43185 dice_loss 0.13824 +Epoch [3604/4000] Validation [3/4] Loss: 0.56190 focal_loss 0.45894 dice_loss 0.10296 +Epoch [3604/4000] Validation [4/4] Loss: 0.33486 focal_loss 0.24254 dice_loss 0.09232 +Epoch [3604/4000] Validation metric {'Val/mean dice_metric': 0.9733924865722656, 'Val/mean miou_metric': 0.9587913751602173, 'Val/mean f1': 0.9758509993553162, 'Val/mean precision': 0.9727127552032471, 'Val/mean recall': 0.9790095686912537, 'Val/mean hd95_metric': 5.4455647468566895} +Cheakpoint... +Epoch [3604/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733924865722656, 'Val/mean miou_metric': 0.9587913751602173, 'Val/mean f1': 0.9758509993553162, 'Val/mean precision': 0.9727127552032471, 'Val/mean recall': 0.9790095686912537, 'Val/mean hd95_metric': 5.4455647468566895} +Epoch [3605/4000] Training [1/16] Loss: 0.00179 +Epoch [3605/4000] Training [2/16] Loss: 0.00268 +Epoch [3605/4000] Training [3/16] Loss: 0.00269 +Epoch [3605/4000] Training [4/16] Loss: 0.00224 +Epoch [3605/4000] Training [5/16] Loss: 0.00177 +Epoch [3605/4000] Training [6/16] Loss: 0.00316 +Epoch [3605/4000] Training [7/16] Loss: 0.00428 +Epoch [3605/4000] Training [8/16] Loss: 0.00184 +Epoch [3605/4000] Training [9/16] Loss: 0.00387 +Epoch [3605/4000] Training [10/16] Loss: 0.00235 +Epoch [3605/4000] Training [11/16] Loss: 0.00236 +Epoch [3605/4000] Training [12/16] Loss: 0.00192 +Epoch [3605/4000] Training [13/16] Loss: 0.00301 +Epoch [3605/4000] Training [14/16] Loss: 0.00359 +Epoch [3605/4000] Training [15/16] Loss: 0.00282 +Epoch [3605/4000] Training [16/16] Loss: 0.00153 +Epoch [3605/4000] Training metric {'Train/mean dice_metric': 0.9986833333969116, 'Train/mean miou_metric': 0.997096061706543, 'Train/mean f1': 0.993773341178894, 'Train/mean precision': 0.9892690777778625, 'Train/mean recall': 0.9983187913894653, 'Train/mean hd95_metric': 0.5246841907501221} +Epoch [3605/4000] Validation [1/4] Loss: 0.40081 focal_loss 0.33330 dice_loss 0.06750 +Epoch [3605/4000] Validation [2/4] Loss: 0.49467 focal_loss 0.38672 dice_loss 0.10795 +Epoch [3605/4000] Validation [3/4] Loss: 0.53416 focal_loss 0.43848 dice_loss 0.09568 +Epoch [3605/4000] Validation [4/4] Loss: 0.36963 focal_loss 0.27534 dice_loss 0.09429 +Epoch [3605/4000] Validation metric {'Val/mean dice_metric': 0.9744208455085754, 'Val/mean miou_metric': 0.9600793123245239, 'Val/mean f1': 0.9765646457672119, 'Val/mean precision': 0.9740322828292847, 'Val/mean recall': 0.9791101813316345, 'Val/mean hd95_metric': 4.858600616455078} +Cheakpoint... +Epoch [3605/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744208455085754, 'Val/mean miou_metric': 0.9600793123245239, 'Val/mean f1': 0.9765646457672119, 'Val/mean precision': 0.9740322828292847, 'Val/mean recall': 0.9791101813316345, 'Val/mean hd95_metric': 4.858600616455078} +Epoch [3606/4000] Training [1/16] Loss: 0.00220 +Epoch [3606/4000] Training [2/16] Loss: 0.00240 +Epoch [3606/4000] Training [3/16] Loss: 0.00348 +Epoch [3606/4000] Training [4/16] Loss: 0.00319 +Epoch [3606/4000] Training [5/16] Loss: 0.00237 +Epoch [3606/4000] Training [6/16] Loss: 0.00200 +Epoch [3606/4000] Training [7/16] Loss: 0.00321 +Epoch [3606/4000] Training [8/16] Loss: 0.00235 +Epoch [3606/4000] Training [9/16] Loss: 0.00263 +Epoch [3606/4000] Training [10/16] Loss: 0.00226 +Epoch [3606/4000] Training [11/16] Loss: 0.00350 +Epoch [3606/4000] Training [12/16] Loss: 0.00226 +Epoch [3606/4000] Training [13/16] Loss: 0.00168 +Epoch [3606/4000] Training [14/16] Loss: 0.00277 +Epoch [3606/4000] Training [15/16] Loss: 0.00205 +Epoch [3606/4000] Training [16/16] Loss: 0.00261 +Epoch [3606/4000] Training metric {'Train/mean dice_metric': 0.9987425804138184, 'Train/mean miou_metric': 0.9971942901611328, 'Train/mean f1': 0.9934173226356506, 'Train/mean precision': 0.9885954260826111, 'Train/mean recall': 0.9982865452766418, 'Train/mean hd95_metric': 0.5522737503051758} +Epoch [3606/4000] Validation [1/4] Loss: 0.39185 focal_loss 0.32784 dice_loss 0.06401 +Epoch [3606/4000] Validation [2/4] Loss: 0.92653 focal_loss 0.72695 dice_loss 0.19958 +Epoch [3606/4000] Validation [3/4] Loss: 0.51422 focal_loss 0.41379 dice_loss 0.10043 +Epoch [3606/4000] Validation [4/4] Loss: 0.35535 focal_loss 0.26009 dice_loss 0.09525 +Epoch [3606/4000] Validation metric {'Val/mean dice_metric': 0.9734792709350586, 'Val/mean miou_metric': 0.9589623212814331, 'Val/mean f1': 0.9753062725067139, 'Val/mean precision': 0.9731709957122803, 'Val/mean recall': 0.9774509072303772, 'Val/mean hd95_metric': 5.3153252601623535} +Cheakpoint... +Epoch [3606/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734792709350586, 'Val/mean miou_metric': 0.9589623212814331, 'Val/mean f1': 0.9753062725067139, 'Val/mean precision': 0.9731709957122803, 'Val/mean recall': 0.9774509072303772, 'Val/mean hd95_metric': 5.3153252601623535} +Epoch [3607/4000] Training [1/16] Loss: 0.00297 +Epoch [3607/4000] Training [2/16] Loss: 0.00405 +Epoch [3607/4000] Training [3/16] Loss: 0.00258 +Epoch [3607/4000] Training [4/16] Loss: 0.00355 +Epoch [3607/4000] Training [5/16] Loss: 0.00221 +Epoch [3607/4000] Training [6/16] Loss: 0.00216 +Epoch [3607/4000] Training [7/16] Loss: 0.00275 +Epoch [3607/4000] Training [8/16] Loss: 0.00263 +Epoch [3607/4000] Training [9/16] Loss: 0.00186 +Epoch [3607/4000] Training [10/16] Loss: 0.00213 +Epoch [3607/4000] Training [11/16] Loss: 0.00243 +Epoch [3607/4000] Training [12/16] Loss: 0.00212 +Epoch [3607/4000] Training [13/16] Loss: 0.00289 +Epoch [3607/4000] Training [14/16] Loss: 0.00205 +Epoch [3607/4000] Training [15/16] Loss: 0.00248 +Epoch [3607/4000] Training [16/16] Loss: 0.00226 +Epoch [3607/4000] Training metric {'Train/mean dice_metric': 0.9987511038780212, 'Train/mean miou_metric': 0.997212290763855, 'Train/mean f1': 0.9936437010765076, 'Train/mean precision': 0.9889956712722778, 'Train/mean recall': 0.998335599899292, 'Train/mean hd95_metric': 0.5697540044784546} +Epoch [3607/4000] Validation [1/4] Loss: 0.41430 focal_loss 0.35348 dice_loss 0.06082 +Epoch [3607/4000] Validation [2/4] Loss: 0.90658 focal_loss 0.71303 dice_loss 0.19355 +Epoch [3607/4000] Validation [3/4] Loss: 0.53938 focal_loss 0.44776 dice_loss 0.09162 +Epoch [3607/4000] Validation [4/4] Loss: 0.35826 focal_loss 0.25743 dice_loss 0.10083 +Epoch [3607/4000] Validation metric {'Val/mean dice_metric': 0.972989559173584, 'Val/mean miou_metric': 0.9589309692382812, 'Val/mean f1': 0.9762852191925049, 'Val/mean precision': 0.974346935749054, 'Val/mean recall': 0.9782313108444214, 'Val/mean hd95_metric': 4.741342067718506} +Cheakpoint... +Epoch [3607/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972989559173584, 'Val/mean miou_metric': 0.9589309692382812, 'Val/mean f1': 0.9762852191925049, 'Val/mean precision': 0.974346935749054, 'Val/mean recall': 0.9782313108444214, 'Val/mean hd95_metric': 4.741342067718506} +Epoch [3608/4000] Training [1/16] Loss: 0.01360 +Epoch [3608/4000] Training [2/16] Loss: 0.00364 +Epoch [3608/4000] Training [3/16] Loss: 0.00309 +Epoch [3608/4000] Training [4/16] Loss: 0.00241 +Epoch [3608/4000] Training [5/16] Loss: 0.00228 +Epoch [3608/4000] Training [6/16] Loss: 0.00214 +Epoch [3608/4000] Training [7/16] Loss: 0.00298 +Epoch [3608/4000] Training [8/16] Loss: 0.00251 +Epoch [3608/4000] Training [9/16] Loss: 0.00234 +Epoch [3608/4000] Training [10/16] Loss: 0.00269 +Epoch [3608/4000] Training [11/16] Loss: 0.00224 +Epoch [3608/4000] Training [12/16] Loss: 0.00210 +Epoch [3608/4000] Training [13/16] Loss: 0.00217 +Epoch [3608/4000] Training [14/16] Loss: 0.00185 +Epoch [3608/4000] Training [15/16] Loss: 0.00275 +Epoch [3608/4000] Training [16/16] Loss: 0.00244 +Epoch [3608/4000] Training metric {'Train/mean dice_metric': 0.9986052513122559, 'Train/mean miou_metric': 0.9969440698623657, 'Train/mean f1': 0.9937421083450317, 'Train/mean precision': 0.989278256893158, 'Train/mean recall': 0.9982463717460632, 'Train/mean hd95_metric': 0.5675681233406067} +Epoch [3608/4000] Validation [1/4] Loss: 0.42010 focal_loss 0.35772 dice_loss 0.06238 +Epoch [3608/4000] Validation [2/4] Loss: 1.33671 focal_loss 1.07260 dice_loss 0.26410 +Epoch [3608/4000] Validation [3/4] Loss: 0.51046 focal_loss 0.42224 dice_loss 0.08822 +Epoch [3608/4000] Validation [4/4] Loss: 0.36517 focal_loss 0.27326 dice_loss 0.09192 +Epoch [3608/4000] Validation metric {'Val/mean dice_metric': 0.9728990793228149, 'Val/mean miou_metric': 0.9593685269355774, 'Val/mean f1': 0.9762941598892212, 'Val/mean precision': 0.9739962220191956, 'Val/mean recall': 0.978602945804596, 'Val/mean hd95_metric': 5.150403022766113} +Cheakpoint... +Epoch [3608/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728990793228149, 'Val/mean miou_metric': 0.9593685269355774, 'Val/mean f1': 0.9762941598892212, 'Val/mean precision': 0.9739962220191956, 'Val/mean recall': 0.978602945804596, 'Val/mean hd95_metric': 5.150403022766113} +Epoch [3609/4000] Training [1/16] Loss: 0.00196 +Epoch [3609/4000] Training [2/16] Loss: 0.00175 +Epoch [3609/4000] Training [3/16] Loss: 0.00184 +Epoch [3609/4000] Training [4/16] Loss: 0.00223 +Epoch [3609/4000] Training [5/16] Loss: 0.00319 +Epoch [3609/4000] Training [6/16] Loss: 0.00234 +Epoch [3609/4000] Training [7/16] Loss: 0.00273 +Epoch [3609/4000] Training [8/16] Loss: 0.00318 +Epoch [3609/4000] Training [9/16] Loss: 0.00190 +Epoch [3609/4000] Training [10/16] Loss: 0.00163 +Epoch [3609/4000] Training [11/16] Loss: 0.00333 +Epoch [3609/4000] Training [12/16] Loss: 0.00184 +Epoch [3609/4000] Training [13/16] Loss: 0.00253 +Epoch [3609/4000] Training [14/16] Loss: 0.00217 +Epoch [3609/4000] Training [15/16] Loss: 0.00190 +Epoch [3609/4000] Training [16/16] Loss: 0.00254 +Epoch [3609/4000] Training metric {'Train/mean dice_metric': 0.9988552927970886, 'Train/mean miou_metric': 0.9974274635314941, 'Train/mean f1': 0.9936887621879578, 'Train/mean precision': 0.9889630675315857, 'Train/mean recall': 0.9984599947929382, 'Train/mean hd95_metric': 0.4948517084121704} +Epoch [3609/4000] Validation [1/4] Loss: 0.40360 focal_loss 0.34279 dice_loss 0.06081 +Epoch [3609/4000] Validation [2/4] Loss: 0.52597 focal_loss 0.41005 dice_loss 0.11591 +Epoch [3609/4000] Validation [3/4] Loss: 0.56597 focal_loss 0.46139 dice_loss 0.10458 +Epoch [3609/4000] Validation [4/4] Loss: 0.34702 focal_loss 0.25605 dice_loss 0.09097 +Epoch [3609/4000] Validation metric {'Val/mean dice_metric': 0.9745451211929321, 'Val/mean miou_metric': 0.9609115719795227, 'Val/mean f1': 0.976292073726654, 'Val/mean precision': 0.9737630486488342, 'Val/mean recall': 0.9788342714309692, 'Val/mean hd95_metric': 4.6757121086120605} +Cheakpoint... +Epoch [3609/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745451211929321, 'Val/mean miou_metric': 0.9609115719795227, 'Val/mean f1': 0.976292073726654, 'Val/mean precision': 0.9737630486488342, 'Val/mean recall': 0.9788342714309692, 'Val/mean hd95_metric': 4.6757121086120605} +Epoch [3610/4000] Training [1/16] Loss: 0.00195 +Epoch [3610/4000] Training [2/16] Loss: 0.00336 +Epoch [3610/4000] Training [3/16] Loss: 0.00298 +Epoch [3610/4000] Training [4/16] Loss: 0.00313 +Epoch [3610/4000] Training [5/16] Loss: 0.00222 +Epoch [3610/4000] Training [6/16] Loss: 0.00300 +Epoch [3610/4000] Training [7/16] Loss: 0.00244 +Epoch [3610/4000] Training [8/16] Loss: 0.00285 +Epoch [3610/4000] Training [9/16] Loss: 0.00211 +Epoch [3610/4000] Training [10/16] Loss: 0.00226 +Epoch [3610/4000] Training [11/16] Loss: 0.00229 +Epoch [3610/4000] Training [12/16] Loss: 0.00495 +Epoch [3610/4000] Training [13/16] Loss: 0.00211 +Epoch [3610/4000] Training [14/16] Loss: 0.00250 +Epoch [3610/4000] Training [15/16] Loss: 0.00489 +Epoch [3610/4000] Training [16/16] Loss: 0.00227 +Epoch [3610/4000] Training metric {'Train/mean dice_metric': 0.9984824657440186, 'Train/mean miou_metric': 0.9966928362846375, 'Train/mean f1': 0.9935026168823242, 'Train/mean precision': 0.9888806939125061, 'Train/mean recall': 0.9981679916381836, 'Train/mean hd95_metric': 0.6014223694801331} +Epoch [3610/4000] Validation [1/4] Loss: 0.40426 focal_loss 0.34113 dice_loss 0.06313 +Epoch [3610/4000] Validation [2/4] Loss: 0.51177 focal_loss 0.39943 dice_loss 0.11234 +Epoch [3610/4000] Validation [3/4] Loss: 0.54620 focal_loss 0.44472 dice_loss 0.10148 +Epoch [3610/4000] Validation [4/4] Loss: 0.35275 focal_loss 0.26226 dice_loss 0.09049 +Epoch [3610/4000] Validation metric {'Val/mean dice_metric': 0.9764245748519897, 'Val/mean miou_metric': 0.9621604681015015, 'Val/mean f1': 0.9766942262649536, 'Val/mean precision': 0.9738941192626953, 'Val/mean recall': 0.9795104265213013, 'Val/mean hd95_metric': 4.5731682777404785} +Cheakpoint... +Epoch [3610/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9764], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9764245748519897, 'Val/mean miou_metric': 0.9621604681015015, 'Val/mean f1': 0.9766942262649536, 'Val/mean precision': 0.9738941192626953, 'Val/mean recall': 0.9795104265213013, 'Val/mean hd95_metric': 4.5731682777404785} +Epoch [3611/4000] Training [1/16] Loss: 0.00303 +Epoch [3611/4000] Training [2/16] Loss: 0.00311 +Epoch [3611/4000] Training [3/16] Loss: 0.00220 +Epoch [3611/4000] Training [4/16] Loss: 0.00212 +Epoch [3611/4000] Training [5/16] Loss: 0.00242 +Epoch [3611/4000] Training [6/16] Loss: 0.00273 +Epoch [3611/4000] Training [7/16] Loss: 0.00199 +Epoch [3611/4000] Training [8/16] Loss: 0.00196 +Epoch [3611/4000] Training [9/16] Loss: 0.00214 +Epoch [3611/4000] Training [10/16] Loss: 0.00155 +Epoch [3611/4000] Training [11/16] Loss: 0.00220 +Epoch [3611/4000] Training [12/16] Loss: 0.00218 +Epoch [3611/4000] Training [13/16] Loss: 0.00189 +Epoch [3611/4000] Training [14/16] Loss: 0.00234 +Epoch [3611/4000] Training [15/16] Loss: 0.00188 +Epoch [3611/4000] Training [16/16] Loss: 0.00221 +Epoch [3611/4000] Training metric {'Train/mean dice_metric': 0.9989114999771118, 'Train/mean miou_metric': 0.9975247383117676, 'Train/mean f1': 0.9932152032852173, 'Train/mean precision': 0.9880629777908325, 'Train/mean recall': 0.9984214305877686, 'Train/mean hd95_metric': 0.49963682889938354} +Epoch [3611/4000] Validation [1/4] Loss: 0.43286 focal_loss 0.35946 dice_loss 0.07340 +Epoch [3611/4000] Validation [2/4] Loss: 0.51142 focal_loss 0.39495 dice_loss 0.11647 +Epoch [3611/4000] Validation [3/4] Loss: 0.52761 focal_loss 0.43870 dice_loss 0.08891 +Epoch [3611/4000] Validation [4/4] Loss: 0.43182 focal_loss 0.32542 dice_loss 0.10640 +Epoch [3611/4000] Validation metric {'Val/mean dice_metric': 0.975997269153595, 'Val/mean miou_metric': 0.9619010090827942, 'Val/mean f1': 0.9761265516281128, 'Val/mean precision': 0.9737744331359863, 'Val/mean recall': 0.9784901142120361, 'Val/mean hd95_metric': 4.6336774826049805} +Cheakpoint... +Epoch [3611/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975997269153595, 'Val/mean miou_metric': 0.9619010090827942, 'Val/mean f1': 0.9761265516281128, 'Val/mean precision': 0.9737744331359863, 'Val/mean recall': 0.9784901142120361, 'Val/mean hd95_metric': 4.6336774826049805} +Epoch [3612/4000] Training [1/16] Loss: 0.00267 +Epoch [3612/4000] Training [2/16] Loss: 0.00262 +Epoch [3612/4000] Training [3/16] Loss: 0.00254 +Epoch [3612/4000] Training [4/16] Loss: 0.00242 +Epoch [3612/4000] Training [5/16] Loss: 0.00171 +Epoch [3612/4000] Training [6/16] Loss: 0.00199 +Epoch [3612/4000] Training [7/16] Loss: 0.00239 +Epoch [3612/4000] Training [8/16] Loss: 0.00214 +Epoch [3612/4000] Training [9/16] Loss: 0.00216 +Epoch [3612/4000] Training [10/16] Loss: 0.00278 +Epoch [3612/4000] Training [11/16] Loss: 0.00306 +Epoch [3612/4000] Training [12/16] Loss: 0.00240 +Epoch [3612/4000] Training [13/16] Loss: 0.00214 +Epoch [3612/4000] Training [14/16] Loss: 0.00145 +Epoch [3612/4000] Training [15/16] Loss: 0.00351 +Epoch [3612/4000] Training [16/16] Loss: 0.00267 +Epoch [3612/4000] Training metric {'Train/mean dice_metric': 0.9988230466842651, 'Train/mean miou_metric': 0.9973690509796143, 'Train/mean f1': 0.9938000440597534, 'Train/mean precision': 0.989234209060669, 'Train/mean recall': 0.9984081387519836, 'Train/mean hd95_metric': 0.5150667428970337} +Epoch [3612/4000] Validation [1/4] Loss: 0.39237 focal_loss 0.33094 dice_loss 0.06143 +Epoch [3612/4000] Validation [2/4] Loss: 0.50956 focal_loss 0.39742 dice_loss 0.11215 +Epoch [3612/4000] Validation [3/4] Loss: 0.55778 focal_loss 0.46428 dice_loss 0.09349 +Epoch [3612/4000] Validation [4/4] Loss: 0.61066 focal_loss 0.47620 dice_loss 0.13446 +Epoch [3612/4000] Validation metric {'Val/mean dice_metric': 0.9747813940048218, 'Val/mean miou_metric': 0.9606924057006836, 'Val/mean f1': 0.9767447710037231, 'Val/mean precision': 0.9744189381599426, 'Val/mean recall': 0.979081928730011, 'Val/mean hd95_metric': 4.723670959472656} +Cheakpoint... +Epoch [3612/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747813940048218, 'Val/mean miou_metric': 0.9606924057006836, 'Val/mean f1': 0.9767447710037231, 'Val/mean precision': 0.9744189381599426, 'Val/mean recall': 0.979081928730011, 'Val/mean hd95_metric': 4.723670959472656} +Epoch [3613/4000] Training [1/16] Loss: 0.00356 +Epoch [3613/4000] Training [2/16] Loss: 0.00232 +Epoch [3613/4000] Training [3/16] Loss: 0.00180 +Epoch [3613/4000] Training [4/16] Loss: 0.00230 +Epoch [3613/4000] Training [5/16] Loss: 0.00264 +Epoch [3613/4000] Training [6/16] Loss: 0.00175 +Epoch [3613/4000] Training [7/16] Loss: 0.00238 +Epoch [3613/4000] Training [8/16] Loss: 0.00271 +Epoch [3613/4000] Training [9/16] Loss: 0.00181 +Epoch [3613/4000] Training [10/16] Loss: 0.00361 +Epoch [3613/4000] Training [11/16] Loss: 0.00214 +Epoch [3613/4000] Training [12/16] Loss: 0.00163 +Epoch [3613/4000] Training [13/16] Loss: 0.00309 +Epoch [3613/4000] Training [14/16] Loss: 0.00317 +Epoch [3613/4000] Training [15/16] Loss: 0.00320 +Epoch [3613/4000] Training [16/16] Loss: 0.00273 +Epoch [3613/4000] Training metric {'Train/mean dice_metric': 0.9987725615501404, 'Train/mean miou_metric': 0.9972735643386841, 'Train/mean f1': 0.9937806129455566, 'Train/mean precision': 0.9892942309379578, 'Train/mean recall': 0.9983078241348267, 'Train/mean hd95_metric': 0.5200470685958862} +Epoch [3613/4000] Validation [1/4] Loss: 0.41217 focal_loss 0.34796 dice_loss 0.06421 +Epoch [3613/4000] Validation [2/4] Loss: 0.61199 focal_loss 0.45124 dice_loss 0.16076 +Epoch [3613/4000] Validation [3/4] Loss: 0.56292 focal_loss 0.46520 dice_loss 0.09772 +Epoch [3613/4000] Validation [4/4] Loss: 0.38024 focal_loss 0.28561 dice_loss 0.09463 +Epoch [3613/4000] Validation metric {'Val/mean dice_metric': 0.9740214347839355, 'Val/mean miou_metric': 0.9598062634468079, 'Val/mean f1': 0.9760255813598633, 'Val/mean precision': 0.973827064037323, 'Val/mean recall': 0.978234052658081, 'Val/mean hd95_metric': 5.214412689208984} +Cheakpoint... +Epoch [3613/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740214347839355, 'Val/mean miou_metric': 0.9598062634468079, 'Val/mean f1': 0.9760255813598633, 'Val/mean precision': 0.973827064037323, 'Val/mean recall': 0.978234052658081, 'Val/mean hd95_metric': 5.214412689208984} +Epoch [3614/4000] Training [1/16] Loss: 0.00263 +Epoch [3614/4000] Training [2/16] Loss: 0.00432 +Epoch [3614/4000] Training [3/16] Loss: 0.00190 +Epoch [3614/4000] Training [4/16] Loss: 0.00159 +Epoch [3614/4000] Training [5/16] Loss: 0.00261 +Epoch [3614/4000] Training [6/16] Loss: 0.00221 +Epoch [3614/4000] Training [7/16] Loss: 0.00346 +Epoch [3614/4000] Training [8/16] Loss: 0.00191 +Epoch [3614/4000] Training [9/16] Loss: 0.00312 +Epoch [3614/4000] Training [10/16] Loss: 0.00204 +Epoch [3614/4000] Training [11/16] Loss: 0.00260 +Epoch [3614/4000] Training [12/16] Loss: 0.00310 +Epoch [3614/4000] Training [13/16] Loss: 0.00297 +Epoch [3614/4000] Training [14/16] Loss: 0.00256 +Epoch [3614/4000] Training [15/16] Loss: 0.00293 +Epoch [3614/4000] Training [16/16] Loss: 0.00160 +Epoch [3614/4000] Training metric {'Train/mean dice_metric': 0.9987093210220337, 'Train/mean miou_metric': 0.9971193075180054, 'Train/mean f1': 0.9930036067962646, 'Train/mean precision': 0.9877811074256897, 'Train/mean recall': 0.9982816576957703, 'Train/mean hd95_metric': 0.5401642918586731} +Epoch [3614/4000] Validation [1/4] Loss: 0.42473 focal_loss 0.35899 dice_loss 0.06574 +Epoch [3614/4000] Validation [2/4] Loss: 0.49738 focal_loss 0.38600 dice_loss 0.11139 +Epoch [3614/4000] Validation [3/4] Loss: 0.29091 focal_loss 0.22490 dice_loss 0.06601 +Epoch [3614/4000] Validation [4/4] Loss: 0.46834 focal_loss 0.35572 dice_loss 0.11262 +Epoch [3614/4000] Validation metric {'Val/mean dice_metric': 0.9757927656173706, 'Val/mean miou_metric': 0.9614807367324829, 'Val/mean f1': 0.9757566452026367, 'Val/mean precision': 0.9727268218994141, 'Val/mean recall': 0.978805422782898, 'Val/mean hd95_metric': 4.707005023956299} +Cheakpoint... +Epoch [3614/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9757927656173706, 'Val/mean miou_metric': 0.9614807367324829, 'Val/mean f1': 0.9757566452026367, 'Val/mean precision': 0.9727268218994141, 'Val/mean recall': 0.978805422782898, 'Val/mean hd95_metric': 4.707005023956299} +Epoch [3615/4000] Training [1/16] Loss: 0.00145 +Epoch [3615/4000] Training [2/16] Loss: 0.00229 +Epoch [3615/4000] Training [3/16] Loss: 0.00238 +Epoch [3615/4000] Training [4/16] Loss: 0.00212 +Epoch [3615/4000] Training [5/16] Loss: 0.00170 +Epoch [3615/4000] Training [6/16] Loss: 0.00233 +Epoch [3615/4000] Training [7/16] Loss: 0.00194 +Epoch [3615/4000] Training [8/16] Loss: 0.00287 +Epoch [3615/4000] Training [9/16] Loss: 0.00252 +Epoch [3615/4000] Training [10/16] Loss: 0.00214 +Epoch [3615/4000] Training [11/16] Loss: 0.00263 +Epoch [3615/4000] Training [12/16] Loss: 0.00246 +Epoch [3615/4000] Training [13/16] Loss: 0.00282 +Epoch [3615/4000] Training [14/16] Loss: 0.00204 +Epoch [3615/4000] Training [15/16] Loss: 0.00180 +Epoch [3615/4000] Training [16/16] Loss: 0.00263 +Epoch [3615/4000] Training metric {'Train/mean dice_metric': 0.9988530874252319, 'Train/mean miou_metric': 0.9974193572998047, 'Train/mean f1': 0.9937295913696289, 'Train/mean precision': 0.9890657067298889, 'Train/mean recall': 0.9984375834465027, 'Train/mean hd95_metric': 0.5169498920440674} +Epoch [3615/4000] Validation [1/4] Loss: 0.45696 focal_loss 0.39052 dice_loss 0.06643 +Epoch [3615/4000] Validation [2/4] Loss: 0.93660 focal_loss 0.74936 dice_loss 0.18723 +Epoch [3615/4000] Validation [3/4] Loss: 0.58003 focal_loss 0.48557 dice_loss 0.09446 +Epoch [3615/4000] Validation [4/4] Loss: 0.47530 focal_loss 0.36042 dice_loss 0.11488 +Epoch [3615/4000] Validation metric {'Val/mean dice_metric': 0.9741848111152649, 'Val/mean miou_metric': 0.959980309009552, 'Val/mean f1': 0.9764513969421387, 'Val/mean precision': 0.9744952917098999, 'Val/mean recall': 0.978415310382843, 'Val/mean hd95_metric': 4.842169761657715} +Cheakpoint... +Epoch [3615/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741848111152649, 'Val/mean miou_metric': 0.959980309009552, 'Val/mean f1': 0.9764513969421387, 'Val/mean precision': 0.9744952917098999, 'Val/mean recall': 0.978415310382843, 'Val/mean hd95_metric': 4.842169761657715} +Epoch [3616/4000] Training [1/16] Loss: 0.00437 +Epoch [3616/4000] Training [2/16] Loss: 0.00199 +Epoch [3616/4000] Training [3/16] Loss: 0.00303 +Epoch [3616/4000] Training [4/16] Loss: 0.00205 +Epoch [3616/4000] Training [5/16] Loss: 0.00179 +Epoch [3616/4000] Training [6/16] Loss: 0.00202 +Epoch [3616/4000] Training [7/16] Loss: 0.00326 +Epoch [3616/4000] Training [8/16] Loss: 0.00309 +Epoch [3616/4000] Training [9/16] Loss: 0.00294 +Epoch [3616/4000] Training [10/16] Loss: 0.00344 +Epoch [3616/4000] Training [11/16] Loss: 0.00304 +Epoch [3616/4000] Training [12/16] Loss: 0.00320 +Epoch [3616/4000] Training [13/16] Loss: 0.00212 +Epoch [3616/4000] Training [14/16] Loss: 0.00244 +Epoch [3616/4000] Training [15/16] Loss: 0.00230 +Epoch [3616/4000] Training [16/16] Loss: 0.00273 +Epoch [3616/4000] Training metric {'Train/mean dice_metric': 0.9986705780029297, 'Train/mean miou_metric': 0.9970459938049316, 'Train/mean f1': 0.9934433698654175, 'Train/mean precision': 0.9886382818222046, 'Train/mean recall': 0.9982953667640686, 'Train/mean hd95_metric': 0.5663361549377441} +Epoch [3616/4000] Validation [1/4] Loss: 0.38345 focal_loss 0.32143 dice_loss 0.06202 +Epoch [3616/4000] Validation [2/4] Loss: 0.53877 focal_loss 0.41259 dice_loss 0.12618 +Epoch [3616/4000] Validation [3/4] Loss: 0.27243 focal_loss 0.20722 dice_loss 0.06521 +Epoch [3616/4000] Validation [4/4] Loss: 0.35979 focal_loss 0.27245 dice_loss 0.08733 +Epoch [3616/4000] Validation metric {'Val/mean dice_metric': 0.9747976064682007, 'Val/mean miou_metric': 0.9606605768203735, 'Val/mean f1': 0.9763262271881104, 'Val/mean precision': 0.973887026309967, 'Val/mean recall': 0.9787776470184326, 'Val/mean hd95_metric': 4.904594421386719} +Cheakpoint... +Epoch [3616/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747976064682007, 'Val/mean miou_metric': 0.9606605768203735, 'Val/mean f1': 0.9763262271881104, 'Val/mean precision': 0.973887026309967, 'Val/mean recall': 0.9787776470184326, 'Val/mean hd95_metric': 4.904594421386719} +Epoch [3617/4000] Training [1/16] Loss: 0.00247 +Epoch [3617/4000] Training [2/16] Loss: 0.00292 +Epoch [3617/4000] Training [3/16] Loss: 0.00185 +Epoch [3617/4000] Training [4/16] Loss: 0.00326 +Epoch [3617/4000] Training [5/16] Loss: 0.00203 +Epoch [3617/4000] Training [6/16] Loss: 0.00251 +Epoch [3617/4000] Training [7/16] Loss: 0.00207 +Epoch [3617/4000] Training [8/16] Loss: 0.00167 +Epoch [3617/4000] Training [9/16] Loss: 0.00372 +Epoch [3617/4000] Training [10/16] Loss: 0.00163 +Epoch [3617/4000] Training [11/16] Loss: 0.00258 +Epoch [3617/4000] Training [12/16] Loss: 0.00187 +Epoch [3617/4000] Training [13/16] Loss: 0.00302 +Epoch [3617/4000] Training [14/16] Loss: 0.00159 +Epoch [3617/4000] Training [15/16] Loss: 0.00191 +Epoch [3617/4000] Training [16/16] Loss: 0.00211 +Epoch [3617/4000] Training metric {'Train/mean dice_metric': 0.998816728591919, 'Train/mean miou_metric': 0.9973519444465637, 'Train/mean f1': 0.9937182664871216, 'Train/mean precision': 0.9890742897987366, 'Train/mean recall': 0.9984061121940613, 'Train/mean hd95_metric': 0.5236603617668152} +Epoch [3617/4000] Validation [1/4] Loss: 0.42724 focal_loss 0.36175 dice_loss 0.06548 +Epoch [3617/4000] Validation [2/4] Loss: 0.66682 focal_loss 0.49857 dice_loss 0.16825 +Epoch [3617/4000] Validation [3/4] Loss: 0.51265 focal_loss 0.41694 dice_loss 0.09570 +Epoch [3617/4000] Validation [4/4] Loss: 0.34548 focal_loss 0.25921 dice_loss 0.08628 +Epoch [3617/4000] Validation metric {'Val/mean dice_metric': 0.9752081036567688, 'Val/mean miou_metric': 0.9609893560409546, 'Val/mean f1': 0.9761013984680176, 'Val/mean precision': 0.9739125370979309, 'Val/mean recall': 0.978300154209137, 'Val/mean hd95_metric': 5.0992560386657715} +Cheakpoint... +Epoch [3617/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752081036567688, 'Val/mean miou_metric': 0.9609893560409546, 'Val/mean f1': 0.9761013984680176, 'Val/mean precision': 0.9739125370979309, 'Val/mean recall': 0.978300154209137, 'Val/mean hd95_metric': 5.0992560386657715} +Epoch [3618/4000] Training [1/16] Loss: 0.00264 +Epoch [3618/4000] Training [2/16] Loss: 0.00222 +Epoch [3618/4000] Training [3/16] Loss: 0.00240 +Epoch [3618/4000] Training [4/16] Loss: 0.00229 +Epoch [3618/4000] Training [5/16] Loss: 0.00439 +Epoch [3618/4000] Training [6/16] Loss: 0.00225 +Epoch [3618/4000] Training [7/16] Loss: 0.00330 +Epoch [3618/4000] Training [8/16] Loss: 0.00326 +Epoch [3618/4000] Training [9/16] Loss: 0.00183 +Epoch [3618/4000] Training [10/16] Loss: 0.00227 +Epoch [3618/4000] Training [11/16] Loss: 0.00328 +Epoch [3618/4000] Training [12/16] Loss: 0.00237 +Epoch [3618/4000] Training [13/16] Loss: 0.00222 +Epoch [3618/4000] Training [14/16] Loss: 0.00236 +Epoch [3618/4000] Training [15/16] Loss: 0.00272 +Epoch [3618/4000] Training [16/16] Loss: 0.00234 +Epoch [3618/4000] Training metric {'Train/mean dice_metric': 0.9986778497695923, 'Train/mean miou_metric': 0.9970748424530029, 'Train/mean f1': 0.9936123490333557, 'Train/mean precision': 0.988997757434845, 'Train/mean recall': 0.9982702136039734, 'Train/mean hd95_metric': 0.582840085029602} +Epoch [3618/4000] Validation [1/4] Loss: 0.34300 focal_loss 0.28722 dice_loss 0.05578 +Epoch [3618/4000] Validation [2/4] Loss: 0.49416 focal_loss 0.38256 dice_loss 0.11160 +Epoch [3618/4000] Validation [3/4] Loss: 0.52809 focal_loss 0.43658 dice_loss 0.09151 +Epoch [3618/4000] Validation [4/4] Loss: 0.36490 focal_loss 0.27435 dice_loss 0.09055 +Epoch [3618/4000] Validation metric {'Val/mean dice_metric': 0.9749091863632202, 'Val/mean miou_metric': 0.961115837097168, 'Val/mean f1': 0.9769806265830994, 'Val/mean precision': 0.9743937849998474, 'Val/mean recall': 0.9795812368392944, 'Val/mean hd95_metric': 4.670963287353516} +Cheakpoint... +Epoch [3618/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749091863632202, 'Val/mean miou_metric': 0.961115837097168, 'Val/mean f1': 0.9769806265830994, 'Val/mean precision': 0.9743937849998474, 'Val/mean recall': 0.9795812368392944, 'Val/mean hd95_metric': 4.670963287353516} +Epoch [3619/4000] Training [1/16] Loss: 0.00318 +Epoch [3619/4000] Training [2/16] Loss: 0.00205 +Epoch [3619/4000] Training [3/16] Loss: 0.00178 +Epoch [3619/4000] Training [4/16] Loss: 0.00281 +Epoch [3619/4000] Training [5/16] Loss: 0.00219 +Epoch [3619/4000] Training [6/16] Loss: 0.00406 +Epoch [3619/4000] Training [7/16] Loss: 0.00241 +Epoch [3619/4000] Training [8/16] Loss: 0.00212 +Epoch [3619/4000] Training [9/16] Loss: 0.00244 +Epoch [3619/4000] Training [10/16] Loss: 0.00198 +Epoch [3619/4000] Training [11/16] Loss: 0.00212 +Epoch [3619/4000] Training [12/16] Loss: 0.00193 +Epoch [3619/4000] Training [13/16] Loss: 0.00192 +Epoch [3619/4000] Training [14/16] Loss: 0.00205 +Epoch [3619/4000] Training [15/16] Loss: 0.00319 +Epoch [3619/4000] Training [16/16] Loss: 0.00198 +Epoch [3619/4000] Training metric {'Train/mean dice_metric': 0.9987406730651855, 'Train/mean miou_metric': 0.9972070455551147, 'Train/mean f1': 0.9938466548919678, 'Train/mean precision': 0.9894202947616577, 'Train/mean recall': 0.9983127117156982, 'Train/mean hd95_metric': 0.5572540760040283} +Epoch [3619/4000] Validation [1/4] Loss: 0.35812 focal_loss 0.29395 dice_loss 0.06417 +Epoch [3619/4000] Validation [2/4] Loss: 0.91182 focal_loss 0.71043 dice_loss 0.20139 +Epoch [3619/4000] Validation [3/4] Loss: 0.58917 focal_loss 0.48757 dice_loss 0.10160 +Epoch [3619/4000] Validation [4/4] Loss: 0.34740 focal_loss 0.25794 dice_loss 0.08946 +Epoch [3619/4000] Validation metric {'Val/mean dice_metric': 0.9743382334709167, 'Val/mean miou_metric': 0.9598022699356079, 'Val/mean f1': 0.9760034680366516, 'Val/mean precision': 0.9741863012313843, 'Val/mean recall': 0.9778273701667786, 'Val/mean hd95_metric': 5.178894519805908} +Cheakpoint... +Epoch [3619/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743382334709167, 'Val/mean miou_metric': 0.9598022699356079, 'Val/mean f1': 0.9760034680366516, 'Val/mean precision': 0.9741863012313843, 'Val/mean recall': 0.9778273701667786, 'Val/mean hd95_metric': 5.178894519805908} +Epoch [3620/4000] Training [1/16] Loss: 0.00263 +Epoch [3620/4000] Training [2/16] Loss: 0.00285 +Epoch [3620/4000] Training [3/16] Loss: 0.00238 +Epoch [3620/4000] Training [4/16] Loss: 0.00323 +Epoch [3620/4000] Training [5/16] Loss: 0.00250 +Epoch [3620/4000] Training [6/16] Loss: 0.00218 +Epoch [3620/4000] Training [7/16] Loss: 0.00174 +Epoch [3620/4000] Training [8/16] Loss: 0.00289 +Epoch [3620/4000] Training [9/16] Loss: 0.00189 +Epoch [3620/4000] Training [10/16] Loss: 0.00227 +Epoch [3620/4000] Training [11/16] Loss: 0.00284 +Epoch [3620/4000] Training [12/16] Loss: 0.00237 +Epoch [3620/4000] Training [13/16] Loss: 0.00370 +Epoch [3620/4000] Training [14/16] Loss: 0.00244 +Epoch [3620/4000] Training [15/16] Loss: 0.00289 +Epoch [3620/4000] Training [16/16] Loss: 0.00177 +Epoch [3620/4000] Training metric {'Train/mean dice_metric': 0.998784065246582, 'Train/mean miou_metric': 0.9972696900367737, 'Train/mean f1': 0.9936651587486267, 'Train/mean precision': 0.9890382289886475, 'Train/mean recall': 0.998335599899292, 'Train/mean hd95_metric': 0.55588698387146} +Epoch [3620/4000] Validation [1/4] Loss: 0.52011 focal_loss 0.43896 dice_loss 0.08116 +Epoch [3620/4000] Validation [2/4] Loss: 0.50066 focal_loss 0.38863 dice_loss 0.11202 +Epoch [3620/4000] Validation [3/4] Loss: 0.25335 focal_loss 0.19515 dice_loss 0.05821 +Epoch [3620/4000] Validation [4/4] Loss: 0.34686 focal_loss 0.25664 dice_loss 0.09022 +Epoch [3620/4000] Validation metric {'Val/mean dice_metric': 0.974105179309845, 'Val/mean miou_metric': 0.9602678418159485, 'Val/mean f1': 0.976324737071991, 'Val/mean precision': 0.9747025966644287, 'Val/mean recall': 0.9779521822929382, 'Val/mean hd95_metric': 5.004895210266113} +Cheakpoint... +Epoch [3620/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974105179309845, 'Val/mean miou_metric': 0.9602678418159485, 'Val/mean f1': 0.976324737071991, 'Val/mean precision': 0.9747025966644287, 'Val/mean recall': 0.9779521822929382, 'Val/mean hd95_metric': 5.004895210266113} +Epoch [3621/4000] Training [1/16] Loss: 0.00202 +Epoch [3621/4000] Training [2/16] Loss: 0.00217 +Epoch [3621/4000] Training [3/16] Loss: 0.00219 +Epoch [3621/4000] Training [4/16] Loss: 0.00347 +Epoch [3621/4000] Training [5/16] Loss: 0.00153 +Epoch [3621/4000] Training [6/16] Loss: 0.00230 +Epoch [3621/4000] Training [7/16] Loss: 0.00331 +Epoch [3621/4000] Training [8/16] Loss: 0.00288 +Epoch [3621/4000] Training [9/16] Loss: 0.00777 +Epoch [3621/4000] Training [10/16] Loss: 0.00190 +Epoch [3621/4000] Training [11/16] Loss: 0.00193 +Epoch [3621/4000] Training [12/16] Loss: 0.00191 +Epoch [3621/4000] Training [13/16] Loss: 0.00194 +Epoch [3621/4000] Training [14/16] Loss: 0.00141 +Epoch [3621/4000] Training [15/16] Loss: 0.00334 +Epoch [3621/4000] Training [16/16] Loss: 0.00194 +Epoch [3621/4000] Training metric {'Train/mean dice_metric': 0.9986712336540222, 'Train/mean miou_metric': 0.997072696685791, 'Train/mean f1': 0.9938080906867981, 'Train/mean precision': 0.9892801642417908, 'Train/mean recall': 0.9983776807785034, 'Train/mean hd95_metric': 0.5598207712173462} +Epoch [3621/4000] Validation [1/4] Loss: 0.43189 focal_loss 0.36549 dice_loss 0.06640 +Epoch [3621/4000] Validation [2/4] Loss: 0.87285 focal_loss 0.68417 dice_loss 0.18869 +Epoch [3621/4000] Validation [3/4] Loss: 0.58821 focal_loss 0.48712 dice_loss 0.10109 +Epoch [3621/4000] Validation [4/4] Loss: 0.31399 focal_loss 0.21641 dice_loss 0.09757 +Epoch [3621/4000] Validation metric {'Val/mean dice_metric': 0.9730303883552551, 'Val/mean miou_metric': 0.9586421251296997, 'Val/mean f1': 0.9762402176856995, 'Val/mean precision': 0.9736648797988892, 'Val/mean recall': 0.9788291454315186, 'Val/mean hd95_metric': 5.2857441902160645} +Cheakpoint... +Epoch [3621/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730303883552551, 'Val/mean miou_metric': 0.9586421251296997, 'Val/mean f1': 0.9762402176856995, 'Val/mean precision': 0.9736648797988892, 'Val/mean recall': 0.9788291454315186, 'Val/mean hd95_metric': 5.2857441902160645} +Epoch [3622/4000] Training [1/16] Loss: 0.00270 +Epoch [3622/4000] Training [2/16] Loss: 0.00177 +Epoch [3622/4000] Training [3/16] Loss: 0.00236 +Epoch [3622/4000] Training [4/16] Loss: 0.00212 +Epoch [3622/4000] Training [5/16] Loss: 0.00217 +Epoch [3622/4000] Training [6/16] Loss: 0.00230 +Epoch [3622/4000] Training [7/16] Loss: 0.00254 +Epoch [3622/4000] Training [8/16] Loss: 0.00256 +Epoch [3622/4000] Training [9/16] Loss: 0.00277 +Epoch [3622/4000] Training [10/16] Loss: 0.00224 +Epoch [3622/4000] Training [11/16] Loss: 0.00259 +Epoch [3622/4000] Training [12/16] Loss: 0.00237 +Epoch [3622/4000] Training [13/16] Loss: 0.00233 +Epoch [3622/4000] Training [14/16] Loss: 0.00219 +Epoch [3622/4000] Training [15/16] Loss: 0.00286 +Epoch [3622/4000] Training [16/16] Loss: 0.00189 +Epoch [3622/4000] Training metric {'Train/mean dice_metric': 0.9987185597419739, 'Train/mean miou_metric': 0.9971334934234619, 'Train/mean f1': 0.9928863644599915, 'Train/mean precision': 0.9876182079315186, 'Train/mean recall': 0.9982110261917114, 'Train/mean hd95_metric': 0.5954655408859253} +Epoch [3622/4000] Validation [1/4] Loss: 0.44432 focal_loss 0.37677 dice_loss 0.06755 +Epoch [3622/4000] Validation [2/4] Loss: 0.61097 focal_loss 0.45372 dice_loss 0.15725 +Epoch [3622/4000] Validation [3/4] Loss: 0.57505 focal_loss 0.47541 dice_loss 0.09964 +Epoch [3622/4000] Validation [4/4] Loss: 0.49725 focal_loss 0.38664 dice_loss 0.11061 +Epoch [3622/4000] Validation metric {'Val/mean dice_metric': 0.9726126790046692, 'Val/mean miou_metric': 0.9587234258651733, 'Val/mean f1': 0.9751599431037903, 'Val/mean precision': 0.9730632901191711, 'Val/mean recall': 0.9772657155990601, 'Val/mean hd95_metric': 4.769524574279785} +Cheakpoint... +Epoch [3622/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726126790046692, 'Val/mean miou_metric': 0.9587234258651733, 'Val/mean f1': 0.9751599431037903, 'Val/mean precision': 0.9730632901191711, 'Val/mean recall': 0.9772657155990601, 'Val/mean hd95_metric': 4.769524574279785} +Epoch [3623/4000] Training [1/16] Loss: 0.00182 +Epoch [3623/4000] Training [2/16] Loss: 0.00218 +Epoch [3623/4000] Training [3/16] Loss: 0.00257 +Epoch [3623/4000] Training [4/16] Loss: 0.00208 +Epoch [3623/4000] Training [5/16] Loss: 0.00263 +Epoch [3623/4000] Training [6/16] Loss: 0.00214 +Epoch [3623/4000] Training [7/16] Loss: 0.00264 +Epoch [3623/4000] Training [8/16] Loss: 0.00364 +Epoch [3623/4000] Training [9/16] Loss: 0.00196 +Epoch [3623/4000] Training [10/16] Loss: 0.00248 +Epoch [3623/4000] Training [11/16] Loss: 0.00192 +Epoch [3623/4000] Training [12/16] Loss: 0.00278 +Epoch [3623/4000] Training [13/16] Loss: 0.00253 +Epoch [3623/4000] Training [14/16] Loss: 0.00219 +Epoch [3623/4000] Training [15/16] Loss: 0.00201 +Epoch [3623/4000] Training [16/16] Loss: 0.00300 +Epoch [3623/4000] Training metric {'Train/mean dice_metric': 0.998738169670105, 'Train/mean miou_metric': 0.9971595406532288, 'Train/mean f1': 0.9929015040397644, 'Train/mean precision': 0.987514078617096, 'Train/mean recall': 0.99834805727005, 'Train/mean hd95_metric': 0.5587188005447388} +Epoch [3623/4000] Validation [1/4] Loss: 0.42314 focal_loss 0.35406 dice_loss 0.06909 +Epoch [3623/4000] Validation [2/4] Loss: 0.93592 focal_loss 0.73276 dice_loss 0.20316 +Epoch [3623/4000] Validation [3/4] Loss: 0.51307 focal_loss 0.42604 dice_loss 0.08703 +Epoch [3623/4000] Validation [4/4] Loss: 0.34886 focal_loss 0.26387 dice_loss 0.08499 +Epoch [3623/4000] Validation metric {'Val/mean dice_metric': 0.9729501008987427, 'Val/mean miou_metric': 0.9590005874633789, 'Val/mean f1': 0.9751965403556824, 'Val/mean precision': 0.9728894233703613, 'Val/mean recall': 0.9775146245956421, 'Val/mean hd95_metric': 4.804001808166504} +Cheakpoint... +Epoch [3623/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729501008987427, 'Val/mean miou_metric': 0.9590005874633789, 'Val/mean f1': 0.9751965403556824, 'Val/mean precision': 0.9728894233703613, 'Val/mean recall': 0.9775146245956421, 'Val/mean hd95_metric': 4.804001808166504} +Epoch [3624/4000] Training [1/16] Loss: 0.00200 +Epoch [3624/4000] Training [2/16] Loss: 0.00324 +Epoch [3624/4000] Training [3/16] Loss: 0.00428 +Epoch [3624/4000] Training [4/16] Loss: 0.00285 +Epoch [3624/4000] Training [5/16] Loss: 0.00315 +Epoch [3624/4000] Training [6/16] Loss: 0.00207 +Epoch [3624/4000] Training [7/16] Loss: 0.00210 +Epoch [3624/4000] Training [8/16] Loss: 0.00204 +Epoch [3624/4000] Training [9/16] Loss: 0.00278 +Epoch [3624/4000] Training [10/16] Loss: 0.00297 +Epoch [3624/4000] Training [11/16] Loss: 0.00198 +Epoch [3624/4000] Training [12/16] Loss: 0.00332 +Epoch [3624/4000] Training [13/16] Loss: 0.00217 +Epoch [3624/4000] Training [14/16] Loss: 0.00191 +Epoch [3624/4000] Training [15/16] Loss: 0.00263 +Epoch [3624/4000] Training [16/16] Loss: 0.00234 +Epoch [3624/4000] Training metric {'Train/mean dice_metric': 0.9986855387687683, 'Train/mean miou_metric': 0.99709552526474, 'Train/mean f1': 0.993641197681427, 'Train/mean precision': 0.9890492558479309, 'Train/mean recall': 0.9982759952545166, 'Train/mean hd95_metric': 0.5679264068603516} +Epoch [3624/4000] Validation [1/4] Loss: 0.39059 focal_loss 0.33157 dice_loss 0.05902 +Epoch [3624/4000] Validation [2/4] Loss: 0.49308 focal_loss 0.38138 dice_loss 0.11171 +Epoch [3624/4000] Validation [3/4] Loss: 0.53899 focal_loss 0.44927 dice_loss 0.08972 +Epoch [3624/4000] Validation [4/4] Loss: 0.34576 focal_loss 0.25716 dice_loss 0.08860 +Epoch [3624/4000] Validation metric {'Val/mean dice_metric': 0.9758782386779785, 'Val/mean miou_metric': 0.9619144201278687, 'Val/mean f1': 0.9762993454933167, 'Val/mean precision': 0.97382652759552, 'Val/mean recall': 0.9787849187850952, 'Val/mean hd95_metric': 4.729538917541504} +Cheakpoint... +Epoch [3624/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758782386779785, 'Val/mean miou_metric': 0.9619144201278687, 'Val/mean f1': 0.9762993454933167, 'Val/mean precision': 0.97382652759552, 'Val/mean recall': 0.9787849187850952, 'Val/mean hd95_metric': 4.729538917541504} +Epoch [3625/4000] Training [1/16] Loss: 0.00200 +Epoch [3625/4000] Training [2/16] Loss: 0.00209 +Epoch [3625/4000] Training [3/16] Loss: 0.00235 +Epoch [3625/4000] Training [4/16] Loss: 0.00239 +Epoch [3625/4000] Training [5/16] Loss: 0.00257 +Epoch [3625/4000] Training [6/16] Loss: 0.00156 +Epoch [3625/4000] Training [7/16] Loss: 0.00351 +Epoch [3625/4000] Training [8/16] Loss: 0.00421 +Epoch [3625/4000] Training [9/16] Loss: 0.00221 +Epoch [3625/4000] Training [10/16] Loss: 0.00186 +Epoch [3625/4000] Training [11/16] Loss: 0.00271 +Epoch [3625/4000] Training [12/16] Loss: 0.00162 +Epoch [3625/4000] Training [13/16] Loss: 0.00266 +Epoch [3625/4000] Training [14/16] Loss: 0.00285 +Epoch [3625/4000] Training [15/16] Loss: 0.00205 +Epoch [3625/4000] Training [16/16] Loss: 0.00210 +Epoch [3625/4000] Training metric {'Train/mean dice_metric': 0.9986906051635742, 'Train/mean miou_metric': 0.997107982635498, 'Train/mean f1': 0.9936989545822144, 'Train/mean precision': 0.989136815071106, 'Train/mean recall': 0.9983032941818237, 'Train/mean hd95_metric': 0.5429964065551758} +Epoch [3625/4000] Validation [1/4] Loss: 0.45530 focal_loss 0.39037 dice_loss 0.06492 +Epoch [3625/4000] Validation [2/4] Loss: 0.49932 focal_loss 0.38721 dice_loss 0.11212 +Epoch [3625/4000] Validation [3/4] Loss: 0.54633 focal_loss 0.45429 dice_loss 0.09204 +Epoch [3625/4000] Validation [4/4] Loss: 0.38326 focal_loss 0.29003 dice_loss 0.09323 +Epoch [3625/4000] Validation metric {'Val/mean dice_metric': 0.9744186401367188, 'Val/mean miou_metric': 0.9603427052497864, 'Val/mean f1': 0.9758326411247253, 'Val/mean precision': 0.9726752638816833, 'Val/mean recall': 0.9790105819702148, 'Val/mean hd95_metric': 5.14851713180542} +Cheakpoint... +Epoch [3625/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744186401367188, 'Val/mean miou_metric': 0.9603427052497864, 'Val/mean f1': 0.9758326411247253, 'Val/mean precision': 0.9726752638816833, 'Val/mean recall': 0.9790105819702148, 'Val/mean hd95_metric': 5.14851713180542} +Epoch [3626/4000] Training [1/16] Loss: 0.00257 +Epoch [3626/4000] Training [2/16] Loss: 0.00226 +Epoch [3626/4000] Training [3/16] Loss: 0.00277 +Epoch [3626/4000] Training [4/16] Loss: 0.00280 +Epoch [3626/4000] Training [5/16] Loss: 0.00181 +Epoch [3626/4000] Training [6/16] Loss: 0.00185 +Epoch [3626/4000] Training [7/16] Loss: 0.00219 +Epoch [3626/4000] Training [8/16] Loss: 0.00273 +Epoch [3626/4000] Training [9/16] Loss: 0.00390 +Epoch [3626/4000] Training [10/16] Loss: 0.00283 +Epoch [3626/4000] Training [11/16] Loss: 0.00329 +Epoch [3626/4000] Training [12/16] Loss: 0.00270 +Epoch [3626/4000] Training [13/16] Loss: 0.00219 +Epoch [3626/4000] Training [14/16] Loss: 0.00149 +Epoch [3626/4000] Training [15/16] Loss: 0.00391 +Epoch [3626/4000] Training [16/16] Loss: 0.00247 +Epoch [3626/4000] Training metric {'Train/mean dice_metric': 0.9986410140991211, 'Train/mean miou_metric': 0.9970108866691589, 'Train/mean f1': 0.9937995076179504, 'Train/mean precision': 0.9893732070922852, 'Train/mean recall': 0.9982655048370361, 'Train/mean hd95_metric': 0.571609616279602} +Epoch [3626/4000] Validation [1/4] Loss: 0.47644 focal_loss 0.41168 dice_loss 0.06476 +Epoch [3626/4000] Validation [2/4] Loss: 0.50645 focal_loss 0.39271 dice_loss 0.11374 +Epoch [3626/4000] Validation [3/4] Loss: 0.54598 focal_loss 0.44603 dice_loss 0.09995 +Epoch [3626/4000] Validation [4/4] Loss: 0.46182 focal_loss 0.35005 dice_loss 0.11177 +Epoch [3626/4000] Validation metric {'Val/mean dice_metric': 0.9742788076400757, 'Val/mean miou_metric': 0.9600902795791626, 'Val/mean f1': 0.9765776991844177, 'Val/mean precision': 0.9739952087402344, 'Val/mean recall': 0.9791739583015442, 'Val/mean hd95_metric': 4.816930294036865} +Cheakpoint... +Epoch [3626/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742788076400757, 'Val/mean miou_metric': 0.9600902795791626, 'Val/mean f1': 0.9765776991844177, 'Val/mean precision': 0.9739952087402344, 'Val/mean recall': 0.9791739583015442, 'Val/mean hd95_metric': 4.816930294036865} +Epoch [3627/4000] Training [1/16] Loss: 0.00177 +Epoch [3627/4000] Training [2/16] Loss: 0.00208 +Epoch [3627/4000] Training [3/16] Loss: 0.00176 +Epoch [3627/4000] Training [4/16] Loss: 0.00372 +Epoch [3627/4000] Training [5/16] Loss: 0.00323 +Epoch [3627/4000] Training [6/16] Loss: 0.00297 +Epoch [3627/4000] Training [7/16] Loss: 0.00162 +Epoch [3627/4000] Training [8/16] Loss: 0.00197 +Epoch [3627/4000] Training [9/16] Loss: 0.00234 +Epoch [3627/4000] Training [10/16] Loss: 0.00292 +Epoch [3627/4000] Training [11/16] Loss: 0.00206 +Epoch [3627/4000] Training [12/16] Loss: 0.00223 +Epoch [3627/4000] Training [13/16] Loss: 0.00379 +Epoch [3627/4000] Training [14/16] Loss: 0.00354 +Epoch [3627/4000] Training [15/16] Loss: 0.00205 +Epoch [3627/4000] Training [16/16] Loss: 0.00287 +Epoch [3627/4000] Training metric {'Train/mean dice_metric': 0.9986287355422974, 'Train/mean miou_metric': 0.9969787001609802, 'Train/mean f1': 0.9934849143028259, 'Train/mean precision': 0.9887884259223938, 'Train/mean recall': 0.9982262849807739, 'Train/mean hd95_metric': 0.5345003008842468} +Epoch [3627/4000] Validation [1/4] Loss: 0.44744 focal_loss 0.38414 dice_loss 0.06330 +Epoch [3627/4000] Validation [2/4] Loss: 1.44657 focal_loss 1.18375 dice_loss 0.26282 +Epoch [3627/4000] Validation [3/4] Loss: 0.54079 focal_loss 0.45104 dice_loss 0.08975 +Epoch [3627/4000] Validation [4/4] Loss: 0.39658 focal_loss 0.28565 dice_loss 0.11094 +Epoch [3627/4000] Validation metric {'Val/mean dice_metric': 0.9729785919189453, 'Val/mean miou_metric': 0.9591962695121765, 'Val/mean f1': 0.9756013751029968, 'Val/mean precision': 0.9724144339561462, 'Val/mean recall': 0.978809118270874, 'Val/mean hd95_metric': 4.673829078674316} +Cheakpoint... +Epoch [3627/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729785919189453, 'Val/mean miou_metric': 0.9591962695121765, 'Val/mean f1': 0.9756013751029968, 'Val/mean precision': 0.9724144339561462, 'Val/mean recall': 0.978809118270874, 'Val/mean hd95_metric': 4.673829078674316} +Epoch [3628/4000] Training [1/16] Loss: 0.00298 +Epoch [3628/4000] Training [2/16] Loss: 0.00302 +Epoch [3628/4000] Training [3/16] Loss: 0.00236 +Epoch [3628/4000] Training [4/16] Loss: 0.00180 +Epoch [3628/4000] Training [5/16] Loss: 0.00249 +Epoch [3628/4000] Training [6/16] Loss: 0.00279 +Epoch [3628/4000] Training [7/16] Loss: 0.00259 +Epoch [3628/4000] Training [8/16] Loss: 0.00263 +Epoch [3628/4000] Training [9/16] Loss: 0.00252 +Epoch [3628/4000] Training [10/16] Loss: 0.00191 +Epoch [3628/4000] Training [11/16] Loss: 0.00185 +Epoch [3628/4000] Training [12/16] Loss: 0.00228 +Epoch [3628/4000] Training [13/16] Loss: 0.00236 +Epoch [3628/4000] Training [14/16] Loss: 0.00228 +Epoch [3628/4000] Training [15/16] Loss: 0.00272 +Epoch [3628/4000] Training [16/16] Loss: 0.00170 +Epoch [3628/4000] Training metric {'Train/mean dice_metric': 0.9987356662750244, 'Train/mean miou_metric': 0.9971987009048462, 'Train/mean f1': 0.993765115737915, 'Train/mean precision': 0.9892672300338745, 'Train/mean recall': 0.9983041286468506, 'Train/mean hd95_metric': 0.5422150492668152} +Epoch [3628/4000] Validation [1/4] Loss: 0.39713 focal_loss 0.33266 dice_loss 0.06446 +Epoch [3628/4000] Validation [2/4] Loss: 0.51107 focal_loss 0.39854 dice_loss 0.11253 +Epoch [3628/4000] Validation [3/4] Loss: 0.28469 focal_loss 0.21907 dice_loss 0.06562 +Epoch [3628/4000] Validation [4/4] Loss: 0.53832 focal_loss 0.41383 dice_loss 0.12449 +Epoch [3628/4000] Validation metric {'Val/mean dice_metric': 0.9742286801338196, 'Val/mean miou_metric': 0.9602825045585632, 'Val/mean f1': 0.9762519598007202, 'Val/mean precision': 0.9745465517044067, 'Val/mean recall': 0.9779632687568665, 'Val/mean hd95_metric': 4.954337120056152} +Cheakpoint... +Epoch [3628/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742286801338196, 'Val/mean miou_metric': 0.9602825045585632, 'Val/mean f1': 0.9762519598007202, 'Val/mean precision': 0.9745465517044067, 'Val/mean recall': 0.9779632687568665, 'Val/mean hd95_metric': 4.954337120056152} +Epoch [3629/4000] Training [1/16] Loss: 0.00217 +Epoch [3629/4000] Training [2/16] Loss: 0.00176 +Epoch [3629/4000] Training [3/16] Loss: 0.00281 +Epoch [3629/4000] Training [4/16] Loss: 0.00192 +Epoch [3629/4000] Training [5/16] Loss: 0.00330 +Epoch [3629/4000] Training [6/16] Loss: 0.00205 +Epoch [3629/4000] Training [7/16] Loss: 0.00210 +Epoch [3629/4000] Training [8/16] Loss: 0.00355 +Epoch [3629/4000] Training [9/16] Loss: 0.00196 +Epoch [3629/4000] Training [10/16] Loss: 0.00194 +Epoch [3629/4000] Training [11/16] Loss: 0.00200 +Epoch [3629/4000] Training [12/16] Loss: 0.00270 +Epoch [3629/4000] Training [13/16] Loss: 0.00331 +Epoch [3629/4000] Training [14/16] Loss: 0.00213 +Epoch [3629/4000] Training [15/16] Loss: 0.00269 +Epoch [3629/4000] Training [16/16] Loss: 0.00228 +Epoch [3629/4000] Training metric {'Train/mean dice_metric': 0.9987053871154785, 'Train/mean miou_metric': 0.9971392154693604, 'Train/mean f1': 0.9937318563461304, 'Train/mean precision': 0.9891870617866516, 'Train/mean recall': 0.9983185529708862, 'Train/mean hd95_metric': 0.5782293081283569} +Epoch [3629/4000] Validation [1/4] Loss: 0.44946 focal_loss 0.38054 dice_loss 0.06893 +Epoch [3629/4000] Validation [2/4] Loss: 0.50660 focal_loss 0.39408 dice_loss 0.11253 +Epoch [3629/4000] Validation [3/4] Loss: 0.54493 focal_loss 0.44685 dice_loss 0.09808 +Epoch [3629/4000] Validation [4/4] Loss: 0.31573 focal_loss 0.22366 dice_loss 0.09206 +Epoch [3629/4000] Validation metric {'Val/mean dice_metric': 0.9740113019943237, 'Val/mean miou_metric': 0.9597154855728149, 'Val/mean f1': 0.9759032726287842, 'Val/mean precision': 0.9730302095413208, 'Val/mean recall': 0.9787933230400085, 'Val/mean hd95_metric': 5.143097877502441} +Cheakpoint... +Epoch [3629/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740113019943237, 'Val/mean miou_metric': 0.9597154855728149, 'Val/mean f1': 0.9759032726287842, 'Val/mean precision': 0.9730302095413208, 'Val/mean recall': 0.9787933230400085, 'Val/mean hd95_metric': 5.143097877502441} +Epoch [3630/4000] Training [1/16] Loss: 0.00244 +Epoch [3630/4000] Training [2/16] Loss: 0.00196 +Epoch [3630/4000] Training [3/16] Loss: 0.00253 +Epoch [3630/4000] Training [4/16] Loss: 0.00230 +Epoch [3630/4000] Training [5/16] Loss: 0.00309 +Epoch [3630/4000] Training [6/16] Loss: 0.00169 +Epoch [3630/4000] Training [7/16] Loss: 0.00200 +Epoch [3630/4000] Training [8/16] Loss: 0.00197 +Epoch [3630/4000] Training [9/16] Loss: 0.00234 +Epoch [3630/4000] Training [10/16] Loss: 0.00346 +Epoch [3630/4000] Training [11/16] Loss: 0.00198 +Epoch [3630/4000] Training [12/16] Loss: 0.00205 +Epoch [3630/4000] Training [13/16] Loss: 0.00180 +Epoch [3630/4000] Training [14/16] Loss: 0.00331 +Epoch [3630/4000] Training [15/16] Loss: 0.00187 +Epoch [3630/4000] Training [16/16] Loss: 0.00316 +Epoch [3630/4000] Training metric {'Train/mean dice_metric': 0.9988934993743896, 'Train/mean miou_metric': 0.9974762201309204, 'Train/mean f1': 0.9930543899536133, 'Train/mean precision': 0.9877508282661438, 'Train/mean recall': 0.9984151721000671, 'Train/mean hd95_metric': 0.5121369361877441} +Epoch [3630/4000] Validation [1/4] Loss: 0.47437 focal_loss 0.40903 dice_loss 0.06534 +Epoch [3630/4000] Validation [2/4] Loss: 1.35678 focal_loss 1.08121 dice_loss 0.27557 +Epoch [3630/4000] Validation [3/4] Loss: 0.53705 focal_loss 0.44126 dice_loss 0.09580 +Epoch [3630/4000] Validation [4/4] Loss: 0.36601 focal_loss 0.27649 dice_loss 0.08952 +Epoch [3630/4000] Validation metric {'Val/mean dice_metric': 0.9728472828865051, 'Val/mean miou_metric': 0.9590082168579102, 'Val/mean f1': 0.9749414920806885, 'Val/mean precision': 0.9721822142601013, 'Val/mean recall': 0.9777165651321411, 'Val/mean hd95_metric': 5.524401664733887} +Cheakpoint... +Epoch [3630/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728472828865051, 'Val/mean miou_metric': 0.9590082168579102, 'Val/mean f1': 0.9749414920806885, 'Val/mean precision': 0.9721822142601013, 'Val/mean recall': 0.9777165651321411, 'Val/mean hd95_metric': 5.524401664733887} +Epoch [3631/4000] Training [1/16] Loss: 0.00334 +Epoch [3631/4000] Training [2/16] Loss: 0.00229 +Epoch [3631/4000] Training [3/16] Loss: 0.00197 +Epoch [3631/4000] Training [4/16] Loss: 0.00288 +Epoch [3631/4000] Training [5/16] Loss: 0.00301 +Epoch [3631/4000] Training [6/16] Loss: 0.00220 +Epoch [3631/4000] Training [7/16] Loss: 0.00245 +Epoch [3631/4000] Training [8/16] Loss: 0.00254 +Epoch [3631/4000] Training [9/16] Loss: 0.00202 +Epoch [3631/4000] Training [10/16] Loss: 0.00200 +Epoch [3631/4000] Training [11/16] Loss: 0.00248 +Epoch [3631/4000] Training [12/16] Loss: 0.00310 +Epoch [3631/4000] Training [13/16] Loss: 0.00166 +Epoch [3631/4000] Training [14/16] Loss: 0.00218 +Epoch [3631/4000] Training [15/16] Loss: 0.00227 +Epoch [3631/4000] Training [16/16] Loss: 0.00362 +Epoch [3631/4000] Training metric {'Train/mean dice_metric': 0.9987173676490784, 'Train/mean miou_metric': 0.9971451163291931, 'Train/mean f1': 0.9934177994728088, 'Train/mean precision': 0.9886397123336792, 'Train/mean recall': 0.9982423186302185, 'Train/mean hd95_metric': 0.5443687438964844} +Epoch [3631/4000] Validation [1/4] Loss: 0.41116 focal_loss 0.34540 dice_loss 0.06576 +Epoch [3631/4000] Validation [2/4] Loss: 0.50942 focal_loss 0.39738 dice_loss 0.11204 +Epoch [3631/4000] Validation [3/4] Loss: 0.52543 focal_loss 0.43470 dice_loss 0.09073 +Epoch [3631/4000] Validation [4/4] Loss: 0.37513 focal_loss 0.28681 dice_loss 0.08832 +Epoch [3631/4000] Validation metric {'Val/mean dice_metric': 0.9756107330322266, 'Val/mean miou_metric': 0.9614532589912415, 'Val/mean f1': 0.9760433435440063, 'Val/mean precision': 0.9729968309402466, 'Val/mean recall': 0.979108989238739, 'Val/mean hd95_metric': 4.823370456695557} +Cheakpoint... +Epoch [3631/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756107330322266, 'Val/mean miou_metric': 0.9614532589912415, 'Val/mean f1': 0.9760433435440063, 'Val/mean precision': 0.9729968309402466, 'Val/mean recall': 0.979108989238739, 'Val/mean hd95_metric': 4.823370456695557} +Epoch [3632/4000] Training [1/16] Loss: 0.00262 +Epoch [3632/4000] Training [2/16] Loss: 0.00257 +Epoch [3632/4000] Training [3/16] Loss: 0.00155 +Epoch [3632/4000] Training [4/16] Loss: 0.00202 +Epoch [3632/4000] Training [5/16] Loss: 0.00263 +Epoch [3632/4000] Training [6/16] Loss: 0.00284 +Epoch [3632/4000] Training [7/16] Loss: 0.00202 +Epoch [3632/4000] Training [8/16] Loss: 0.00218 +Epoch [3632/4000] Training [9/16] Loss: 0.00164 +Epoch [3632/4000] Training [10/16] Loss: 0.00220 +Epoch [3632/4000] Training [11/16] Loss: 0.00197 +Epoch [3632/4000] Training [12/16] Loss: 0.00258 +Epoch [3632/4000] Training [13/16] Loss: 0.00221 +Epoch [3632/4000] Training [14/16] Loss: 0.00310 +Epoch [3632/4000] Training [15/16] Loss: 0.00181 +Epoch [3632/4000] Training [16/16] Loss: 0.00279 +Epoch [3632/4000] Training metric {'Train/mean dice_metric': 0.9987965822219849, 'Train/mean miou_metric': 0.9973105788230896, 'Train/mean f1': 0.9936303496360779, 'Train/mean precision': 0.9889888763427734, 'Train/mean recall': 0.9983156323432922, 'Train/mean hd95_metric': 0.51145339012146} +Epoch [3632/4000] Validation [1/4] Loss: 0.47601 focal_loss 0.41075 dice_loss 0.06525 +Epoch [3632/4000] Validation [2/4] Loss: 0.91468 focal_loss 0.71266 dice_loss 0.20202 +Epoch [3632/4000] Validation [3/4] Loss: 0.61001 focal_loss 0.50682 dice_loss 0.10319 +Epoch [3632/4000] Validation [4/4] Loss: 0.38438 focal_loss 0.28513 dice_loss 0.09925 +Epoch [3632/4000] Validation metric {'Val/mean dice_metric': 0.9728244543075562, 'Val/mean miou_metric': 0.9588924646377563, 'Val/mean f1': 0.9755240082740784, 'Val/mean precision': 0.973373532295227, 'Val/mean recall': 0.9776840806007385, 'Val/mean hd95_metric': 5.588433742523193} +Cheakpoint... +Epoch [3632/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728244543075562, 'Val/mean miou_metric': 0.9588924646377563, 'Val/mean f1': 0.9755240082740784, 'Val/mean precision': 0.973373532295227, 'Val/mean recall': 0.9776840806007385, 'Val/mean hd95_metric': 5.588433742523193} +Epoch [3633/4000] Training [1/16] Loss: 0.00203 +Epoch [3633/4000] Training [2/16] Loss: 0.00327 +Epoch [3633/4000] Training [3/16] Loss: 0.00175 +Epoch [3633/4000] Training [4/16] Loss: 0.00324 +Epoch [3633/4000] Training [5/16] Loss: 0.00243 +Epoch [3633/4000] Training [6/16] Loss: 0.00232 +Epoch [3633/4000] Training [7/16] Loss: 0.00122 +Epoch [3633/4000] Training [8/16] Loss: 0.00330 +Epoch [3633/4000] Training [9/16] Loss: 0.00246 +Epoch [3633/4000] Training [10/16] Loss: 0.00254 +Epoch [3633/4000] Training [11/16] Loss: 0.00256 +Epoch [3633/4000] Training [12/16] Loss: 0.00259 +Epoch [3633/4000] Training [13/16] Loss: 0.00210 +Epoch [3633/4000] Training [14/16] Loss: 0.00201 +Epoch [3633/4000] Training [15/16] Loss: 0.00230 +Epoch [3633/4000] Training [16/16] Loss: 0.00237 +Epoch [3633/4000] Training metric {'Train/mean dice_metric': 0.9988377094268799, 'Train/mean miou_metric': 0.9973990321159363, 'Train/mean f1': 0.9938321709632874, 'Train/mean precision': 0.9892922043800354, 'Train/mean recall': 0.9984140396118164, 'Train/mean hd95_metric': 0.5155549049377441} +Epoch [3633/4000] Validation [1/4] Loss: 0.39410 focal_loss 0.33242 dice_loss 0.06168 +Epoch [3633/4000] Validation [2/4] Loss: 0.90126 focal_loss 0.69992 dice_loss 0.20134 +Epoch [3633/4000] Validation [3/4] Loss: 0.54733 focal_loss 0.45241 dice_loss 0.09493 +Epoch [3633/4000] Validation [4/4] Loss: 0.40228 focal_loss 0.29554 dice_loss 0.10674 +Epoch [3633/4000] Validation metric {'Val/mean dice_metric': 0.9734256863594055, 'Val/mean miou_metric': 0.9592643976211548, 'Val/mean f1': 0.9760667681694031, 'Val/mean precision': 0.9742688536643982, 'Val/mean recall': 0.9778714179992676, 'Val/mean hd95_metric': 4.8397603034973145} +Cheakpoint... +Epoch [3633/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734256863594055, 'Val/mean miou_metric': 0.9592643976211548, 'Val/mean f1': 0.9760667681694031, 'Val/mean precision': 0.9742688536643982, 'Val/mean recall': 0.9778714179992676, 'Val/mean hd95_metric': 4.8397603034973145} +Epoch [3634/4000] Training [1/16] Loss: 0.00260 +Epoch [3634/4000] Training [2/16] Loss: 0.00246 +Epoch [3634/4000] Training [3/16] Loss: 0.00201 +Epoch [3634/4000] Training [4/16] Loss: 0.00187 +Epoch [3634/4000] Training [5/16] Loss: 0.00279 +Epoch [3634/4000] Training [6/16] Loss: 0.00352 +Epoch [3634/4000] Training [7/16] Loss: 0.00220 +Epoch [3634/4000] Training [8/16] Loss: 0.00222 +Epoch [3634/4000] Training [9/16] Loss: 0.00219 +Epoch [3634/4000] Training [10/16] Loss: 0.00234 +Epoch [3634/4000] Training [11/16] Loss: 0.00262 +Epoch [3634/4000] Training [12/16] Loss: 0.00185 +Epoch [3634/4000] Training [13/16] Loss: 0.00247 +Epoch [3634/4000] Training [14/16] Loss: 0.00309 +Epoch [3634/4000] Training [15/16] Loss: 0.00278 +Epoch [3634/4000] Training [16/16] Loss: 0.00169 +Epoch [3634/4000] Training metric {'Train/mean dice_metric': 0.998869001865387, 'Train/mean miou_metric': 0.9974621534347534, 'Train/mean f1': 0.9938248991966248, 'Train/mean precision': 0.9892024993896484, 'Train/mean recall': 0.9984906315803528, 'Train/mean hd95_metric': 0.539871335029602} +Epoch [3634/4000] Validation [1/4] Loss: 0.39215 focal_loss 0.32866 dice_loss 0.06349 +Epoch [3634/4000] Validation [2/4] Loss: 0.90046 focal_loss 0.70092 dice_loss 0.19954 +Epoch [3634/4000] Validation [3/4] Loss: 0.52629 focal_loss 0.43595 dice_loss 0.09034 +Epoch [3634/4000] Validation [4/4] Loss: 0.36062 focal_loss 0.27093 dice_loss 0.08969 +Epoch [3634/4000] Validation metric {'Val/mean dice_metric': 0.973993182182312, 'Val/mean miou_metric': 0.9600736498832703, 'Val/mean f1': 0.9761953353881836, 'Val/mean precision': 0.9737331867218018, 'Val/mean recall': 0.978670060634613, 'Val/mean hd95_metric': 4.701883792877197} +Cheakpoint... +Epoch [3634/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973993182182312, 'Val/mean miou_metric': 0.9600736498832703, 'Val/mean f1': 0.9761953353881836, 'Val/mean precision': 0.9737331867218018, 'Val/mean recall': 0.978670060634613, 'Val/mean hd95_metric': 4.701883792877197} +Epoch [3635/4000] Training [1/16] Loss: 0.00221 +Epoch [3635/4000] Training [2/16] Loss: 0.00317 +Epoch [3635/4000] Training [3/16] Loss: 0.00213 +Epoch [3635/4000] Training [4/16] Loss: 0.00202 +Epoch [3635/4000] Training [5/16] Loss: 0.00276 +Epoch [3635/4000] Training [6/16] Loss: 0.00265 +Epoch [3635/4000] Training [7/16] Loss: 0.00238 +Epoch [3635/4000] Training [8/16] Loss: 0.00198 +Epoch [3635/4000] Training [9/16] Loss: 0.00212 +Epoch [3635/4000] Training [10/16] Loss: 0.00266 +Epoch [3635/4000] Training [11/16] Loss: 0.00251 +Epoch [3635/4000] Training [12/16] Loss: 0.00332 +Epoch [3635/4000] Training [13/16] Loss: 0.00349 +Epoch [3635/4000] Training [14/16] Loss: 0.00217 +Epoch [3635/4000] Training [15/16] Loss: 0.00242 +Epoch [3635/4000] Training [16/16] Loss: 0.00195 +Epoch [3635/4000] Training metric {'Train/mean dice_metric': 0.9987717270851135, 'Train/mean miou_metric': 0.9972690939903259, 'Train/mean f1': 0.9938536882400513, 'Train/mean precision': 0.9893661141395569, 'Train/mean recall': 0.9983820915222168, 'Train/mean hd95_metric': 0.5118439793586731} +Epoch [3635/4000] Validation [1/4] Loss: 0.40518 focal_loss 0.34250 dice_loss 0.06268 +Epoch [3635/4000] Validation [2/4] Loss: 0.47105 focal_loss 0.36295 dice_loss 0.10809 +Epoch [3635/4000] Validation [3/4] Loss: 0.56303 focal_loss 0.45684 dice_loss 0.10619 +Epoch [3635/4000] Validation [4/4] Loss: 0.34731 focal_loss 0.25253 dice_loss 0.09477 +Epoch [3635/4000] Validation metric {'Val/mean dice_metric': 0.9737638235092163, 'Val/mean miou_metric': 0.9597271680831909, 'Val/mean f1': 0.9762370586395264, 'Val/mean precision': 0.9738681316375732, 'Val/mean recall': 0.9786175489425659, 'Val/mean hd95_metric': 5.1073527336120605} +Cheakpoint... +Epoch [3635/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737638235092163, 'Val/mean miou_metric': 0.9597271680831909, 'Val/mean f1': 0.9762370586395264, 'Val/mean precision': 0.9738681316375732, 'Val/mean recall': 0.9786175489425659, 'Val/mean hd95_metric': 5.1073527336120605} +Epoch [3636/4000] Training [1/16] Loss: 0.00247 +Epoch [3636/4000] Training [2/16] Loss: 0.00276 +Epoch [3636/4000] Training [3/16] Loss: 0.00231 +Epoch [3636/4000] Training [4/16] Loss: 0.00286 +Epoch [3636/4000] Training [5/16] Loss: 0.00326 +Epoch [3636/4000] Training [6/16] Loss: 0.00333 +Epoch [3636/4000] Training [7/16] Loss: 0.00194 +Epoch [3636/4000] Training [8/16] Loss: 0.00168 +Epoch [3636/4000] Training [9/16] Loss: 0.00254 +Epoch [3636/4000] Training [10/16] Loss: 0.00281 +Epoch [3636/4000] Training [11/16] Loss: 0.00241 +Epoch [3636/4000] Training [12/16] Loss: 0.00286 +Epoch [3636/4000] Training [13/16] Loss: 0.00194 +Epoch [3636/4000] Training [14/16] Loss: 0.00316 +Epoch [3636/4000] Training [15/16] Loss: 0.00264 +Epoch [3636/4000] Training [16/16] Loss: 0.00202 +Epoch [3636/4000] Training metric {'Train/mean dice_metric': 0.9987108707427979, 'Train/mean miou_metric': 0.9971458315849304, 'Train/mean f1': 0.9936717748641968, 'Train/mean precision': 0.9890902042388916, 'Train/mean recall': 0.9982959032058716, 'Train/mean hd95_metric': 0.5539339184761047} +Epoch [3636/4000] Validation [1/4] Loss: 0.41612 focal_loss 0.35192 dice_loss 0.06419 +Epoch [3636/4000] Validation [2/4] Loss: 0.91499 focal_loss 0.71254 dice_loss 0.20246 +Epoch [3636/4000] Validation [3/4] Loss: 0.53054 focal_loss 0.43400 dice_loss 0.09653 +Epoch [3636/4000] Validation [4/4] Loss: 0.34775 focal_loss 0.25170 dice_loss 0.09605 +Epoch [3636/4000] Validation metric {'Val/mean dice_metric': 0.9730866551399231, 'Val/mean miou_metric': 0.9586883783340454, 'Val/mean f1': 0.9754804372787476, 'Val/mean precision': 0.9734777212142944, 'Val/mean recall': 0.9774913787841797, 'Val/mean hd95_metric': 5.409449577331543} +Cheakpoint... +Epoch [3636/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730866551399231, 'Val/mean miou_metric': 0.9586883783340454, 'Val/mean f1': 0.9754804372787476, 'Val/mean precision': 0.9734777212142944, 'Val/mean recall': 0.9774913787841797, 'Val/mean hd95_metric': 5.409449577331543} +Epoch [3637/4000] Training [1/16] Loss: 0.00293 +Epoch [3637/4000] Training [2/16] Loss: 0.00284 +Epoch [3637/4000] Training [3/16] Loss: 0.00131 +Epoch [3637/4000] Training [4/16] Loss: 0.00221 +Epoch [3637/4000] Training [5/16] Loss: 0.00293 +Epoch [3637/4000] Training [6/16] Loss: 0.00248 +Epoch [3637/4000] Training [7/16] Loss: 0.00212 +Epoch [3637/4000] Training [8/16] Loss: 0.00250 +Epoch [3637/4000] Training [9/16] Loss: 0.00235 +Epoch [3637/4000] Training [10/16] Loss: 0.00263 +Epoch [3637/4000] Training [11/16] Loss: 0.00181 +Epoch [3637/4000] Training [12/16] Loss: 0.00309 +Epoch [3637/4000] Training [13/16] Loss: 0.00219 +Epoch [3637/4000] Training [14/16] Loss: 0.00340 +Epoch [3637/4000] Training [15/16] Loss: 0.00285 +Epoch [3637/4000] Training [16/16] Loss: 0.00373 +Epoch [3637/4000] Training metric {'Train/mean dice_metric': 0.9986592531204224, 'Train/mean miou_metric': 0.9970413446426392, 'Train/mean f1': 0.9936307072639465, 'Train/mean precision': 0.9890176057815552, 'Train/mean recall': 0.9982869625091553, 'Train/mean hd95_metric': 0.5593048930168152} +Epoch [3637/4000] Validation [1/4] Loss: 0.39312 focal_loss 0.33303 dice_loss 0.06009 +Epoch [3637/4000] Validation [2/4] Loss: 0.92232 focal_loss 0.66946 dice_loss 0.25286 +Epoch [3637/4000] Validation [3/4] Loss: 0.52263 focal_loss 0.42690 dice_loss 0.09572 +Epoch [3637/4000] Validation [4/4] Loss: 0.32501 focal_loss 0.22858 dice_loss 0.09643 +Epoch [3637/4000] Validation metric {'Val/mean dice_metric': 0.9736055135726929, 'Val/mean miou_metric': 0.9589446187019348, 'Val/mean f1': 0.9761459827423096, 'Val/mean precision': 0.9743120670318604, 'Val/mean recall': 0.9779868125915527, 'Val/mean hd95_metric': 5.200028896331787} +Cheakpoint... +Epoch [3637/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736055135726929, 'Val/mean miou_metric': 0.9589446187019348, 'Val/mean f1': 0.9761459827423096, 'Val/mean precision': 0.9743120670318604, 'Val/mean recall': 0.9779868125915527, 'Val/mean hd95_metric': 5.200028896331787} +Epoch [3638/4000] Training [1/16] Loss: 0.00325 +Epoch [3638/4000] Training [2/16] Loss: 0.00265 +Epoch [3638/4000] Training [3/16] Loss: 0.00287 +Epoch [3638/4000] Training [4/16] Loss: 0.00197 +Epoch [3638/4000] Training [5/16] Loss: 0.00305 +Epoch [3638/4000] Training [6/16] Loss: 0.00172 +Epoch [3638/4000] Training [7/16] Loss: 0.00224 +Epoch [3638/4000] Training [8/16] Loss: 0.00373 +Epoch [3638/4000] Training [9/16] Loss: 0.00202 +Epoch [3638/4000] Training [10/16] Loss: 0.00268 +Epoch [3638/4000] Training [11/16] Loss: 0.00174 +Epoch [3638/4000] Training [12/16] Loss: 0.00356 +Epoch [3638/4000] Training [13/16] Loss: 0.00178 +Epoch [3638/4000] Training [14/16] Loss: 0.00202 +Epoch [3638/4000] Training [15/16] Loss: 0.00240 +Epoch [3638/4000] Training [16/16] Loss: 0.00229 +Epoch [3638/4000] Training metric {'Train/mean dice_metric': 0.9987307786941528, 'Train/mean miou_metric': 0.9971795082092285, 'Train/mean f1': 0.9936503767967224, 'Train/mean precision': 0.9890270829200745, 'Train/mean recall': 0.9983170628547668, 'Train/mean hd95_metric': 0.5507111549377441} +Epoch [3638/4000] Validation [1/4] Loss: 0.38395 focal_loss 0.32226 dice_loss 0.06170 +Epoch [3638/4000] Validation [2/4] Loss: 0.50407 focal_loss 0.39100 dice_loss 0.11307 +Epoch [3638/4000] Validation [3/4] Loss: 0.54414 focal_loss 0.44993 dice_loss 0.09421 +Epoch [3638/4000] Validation [4/4] Loss: 0.45262 focal_loss 0.34315 dice_loss 0.10947 +Epoch [3638/4000] Validation metric {'Val/mean dice_metric': 0.9739394187927246, 'Val/mean miou_metric': 0.9601842761039734, 'Val/mean f1': 0.9765372276306152, 'Val/mean precision': 0.9744387269020081, 'Val/mean recall': 0.9786447882652283, 'Val/mean hd95_metric': 4.510683059692383} +Cheakpoint... +Epoch [3638/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739394187927246, 'Val/mean miou_metric': 0.9601842761039734, 'Val/mean f1': 0.9765372276306152, 'Val/mean precision': 0.9744387269020081, 'Val/mean recall': 0.9786447882652283, 'Val/mean hd95_metric': 4.510683059692383} +Epoch [3639/4000] Training [1/16] Loss: 0.00323 +Epoch [3639/4000] Training [2/16] Loss: 0.00257 +Epoch [3639/4000] Training [3/16] Loss: 0.00275 +Epoch [3639/4000] Training [4/16] Loss: 0.00159 +Epoch [3639/4000] Training [5/16] Loss: 0.00213 +Epoch [3639/4000] Training [6/16] Loss: 0.00276 +Epoch [3639/4000] Training [7/16] Loss: 0.00249 +Epoch [3639/4000] Training [8/16] Loss: 0.00172 +Epoch [3639/4000] Training [9/16] Loss: 0.00181 +Epoch [3639/4000] Training [10/16] Loss: 0.00194 +Epoch [3639/4000] Training [11/16] Loss: 0.00157 +Epoch [3639/4000] Training [12/16] Loss: 0.00238 +Epoch [3639/4000] Training [13/16] Loss: 0.00235 +Epoch [3639/4000] Training [14/16] Loss: 0.00242 +Epoch [3639/4000] Training [15/16] Loss: 0.00160 +Epoch [3639/4000] Training [16/16] Loss: 0.00291 +Epoch [3639/4000] Training metric {'Train/mean dice_metric': 0.9988351464271545, 'Train/mean miou_metric': 0.9973684549331665, 'Train/mean f1': 0.9934924244880676, 'Train/mean precision': 0.9886473417282104, 'Train/mean recall': 0.9983853101730347, 'Train/mean hd95_metric': 0.4954376816749573} +Epoch [3639/4000] Validation [1/4] Loss: 0.39194 focal_loss 0.32791 dice_loss 0.06403 +Epoch [3639/4000] Validation [2/4] Loss: 1.09617 focal_loss 0.90313 dice_loss 0.19303 +Epoch [3639/4000] Validation [3/4] Loss: 0.54269 focal_loss 0.45014 dice_loss 0.09255 +Epoch [3639/4000] Validation [4/4] Loss: 0.35060 focal_loss 0.26554 dice_loss 0.08506 +Epoch [3639/4000] Validation metric {'Val/mean dice_metric': 0.9735032916069031, 'Val/mean miou_metric': 0.9601949453353882, 'Val/mean f1': 0.9758199453353882, 'Val/mean precision': 0.9733614325523376, 'Val/mean recall': 0.9782910346984863, 'Val/mean hd95_metric': 4.595704078674316} +Cheakpoint... +Epoch [3639/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735032916069031, 'Val/mean miou_metric': 0.9601949453353882, 'Val/mean f1': 0.9758199453353882, 'Val/mean precision': 0.9733614325523376, 'Val/mean recall': 0.9782910346984863, 'Val/mean hd95_metric': 4.595704078674316} +Epoch [3640/4000] Training [1/16] Loss: 0.00338 +Epoch [3640/4000] Training [2/16] Loss: 0.00310 +Epoch [3640/4000] Training [3/16] Loss: 0.00199 +Epoch [3640/4000] Training [4/16] Loss: 0.00249 +Epoch [3640/4000] Training [5/16] Loss: 0.00220 +Epoch [3640/4000] Training [6/16] Loss: 0.00358 +Epoch [3640/4000] Training [7/16] Loss: 0.00195 +Epoch [3640/4000] Training [8/16] Loss: 0.00208 +Epoch [3640/4000] Training [9/16] Loss: 0.00200 +Epoch [3640/4000] Training [10/16] Loss: 0.00161 +Epoch [3640/4000] Training [11/16] Loss: 0.00271 +Epoch [3640/4000] Training [12/16] Loss: 0.00269 +Epoch [3640/4000] Training [13/16] Loss: 0.00219 +Epoch [3640/4000] Training [14/16] Loss: 0.00190 +Epoch [3640/4000] Training [15/16] Loss: 0.00171 +Epoch [3640/4000] Training [16/16] Loss: 0.00304 +Epoch [3640/4000] Training metric {'Train/mean dice_metric': 0.998689591884613, 'Train/mean miou_metric': 0.9970883727073669, 'Train/mean f1': 0.9934538006782532, 'Train/mean precision': 0.9886528849601746, 'Train/mean recall': 0.9983015060424805, 'Train/mean hd95_metric': 0.5722233057022095} +Epoch [3640/4000] Validation [1/4] Loss: 0.42123 focal_loss 0.35122 dice_loss 0.07002 +Epoch [3640/4000] Validation [2/4] Loss: 0.60437 focal_loss 0.44974 dice_loss 0.15463 +Epoch [3640/4000] Validation [3/4] Loss: 0.53049 focal_loss 0.43908 dice_loss 0.09141 +Epoch [3640/4000] Validation [4/4] Loss: 0.34636 focal_loss 0.26032 dice_loss 0.08604 +Epoch [3640/4000] Validation metric {'Val/mean dice_metric': 0.9752996563911438, 'Val/mean miou_metric': 0.9609467387199402, 'Val/mean f1': 0.9759830236434937, 'Val/mean precision': 0.9741364121437073, 'Val/mean recall': 0.9778366088867188, 'Val/mean hd95_metric': 4.5862884521484375} +Cheakpoint... +Epoch [3640/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752996563911438, 'Val/mean miou_metric': 0.9609467387199402, 'Val/mean f1': 0.9759830236434937, 'Val/mean precision': 0.9741364121437073, 'Val/mean recall': 0.9778366088867188, 'Val/mean hd95_metric': 4.5862884521484375} +Epoch [3641/4000] Training [1/16] Loss: 0.00298 +Epoch [3641/4000] Training [2/16] Loss: 0.00316 +Epoch [3641/4000] Training [3/16] Loss: 0.00230 +Epoch [3641/4000] Training [4/16] Loss: 0.00193 +Epoch [3641/4000] Training [5/16] Loss: 0.00288 +Epoch [3641/4000] Training [6/16] Loss: 0.00227 +Epoch [3641/4000] Training [7/16] Loss: 0.00246 +Epoch [3641/4000] Training [8/16] Loss: 0.00277 +Epoch [3641/4000] Training [9/16] Loss: 0.00237 +Epoch [3641/4000] Training [10/16] Loss: 0.00155 +Epoch [3641/4000] Training [11/16] Loss: 0.00258 +Epoch [3641/4000] Training [12/16] Loss: 0.00280 +Epoch [3641/4000] Training [13/16] Loss: 0.00182 +Epoch [3641/4000] Training [14/16] Loss: 0.00606 +Epoch [3641/4000] Training [15/16] Loss: 0.00230 +Epoch [3641/4000] Training [16/16] Loss: 0.00266 +Epoch [3641/4000] Training metric {'Train/mean dice_metric': 0.9986156225204468, 'Train/mean miou_metric': 0.9969469308853149, 'Train/mean f1': 0.993355393409729, 'Train/mean precision': 0.9885419607162476, 'Train/mean recall': 0.998215913772583, 'Train/mean hd95_metric': 0.5887960195541382} +Epoch [3641/4000] Validation [1/4] Loss: 0.41638 focal_loss 0.35072 dice_loss 0.06566 +Epoch [3641/4000] Validation [2/4] Loss: 0.49710 focal_loss 0.38367 dice_loss 0.11343 +Epoch [3641/4000] Validation [3/4] Loss: 0.58900 focal_loss 0.48820 dice_loss 0.10080 +Epoch [3641/4000] Validation [4/4] Loss: 0.49481 focal_loss 0.38549 dice_loss 0.10933 +Epoch [3641/4000] Validation metric {'Val/mean dice_metric': 0.974780261516571, 'Val/mean miou_metric': 0.9606633186340332, 'Val/mean f1': 0.976256787776947, 'Val/mean precision': 0.9737634658813477, 'Val/mean recall': 0.9787629246711731, 'Val/mean hd95_metric': 4.674927234649658} +Cheakpoint... +Epoch [3641/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974780261516571, 'Val/mean miou_metric': 0.9606633186340332, 'Val/mean f1': 0.976256787776947, 'Val/mean precision': 0.9737634658813477, 'Val/mean recall': 0.9787629246711731, 'Val/mean hd95_metric': 4.674927234649658} +Epoch [3642/4000] Training [1/16] Loss: 0.00219 +Epoch [3642/4000] Training [2/16] Loss: 0.00359 +Epoch [3642/4000] Training [3/16] Loss: 0.00460 +Epoch [3642/4000] Training [4/16] Loss: 0.00347 +Epoch [3642/4000] Training [5/16] Loss: 0.00345 +Epoch [3642/4000] Training [6/16] Loss: 0.00231 +Epoch [3642/4000] Training [7/16] Loss: 0.00309 +Epoch [3642/4000] Training [8/16] Loss: 0.00298 +Epoch [3642/4000] Training [9/16] Loss: 0.00177 +Epoch [3642/4000] Training [10/16] Loss: 0.00248 +Epoch [3642/4000] Training [11/16] Loss: 0.00207 +Epoch [3642/4000] Training [12/16] Loss: 0.00416 +Epoch [3642/4000] Training [13/16] Loss: 0.00181 +Epoch [3642/4000] Training [14/16] Loss: 0.00171 +Epoch [3642/4000] Training [15/16] Loss: 0.00302 +Epoch [3642/4000] Training [16/16] Loss: 0.00436 +Epoch [3642/4000] Training metric {'Train/mean dice_metric': 0.998626708984375, 'Train/mean miou_metric': 0.9969800710678101, 'Train/mean f1': 0.9936350584030151, 'Train/mean precision': 0.9891171455383301, 'Train/mean recall': 0.9981944561004639, 'Train/mean hd95_metric': 0.5480142831802368} +Epoch [3642/4000] Validation [1/4] Loss: 0.43152 focal_loss 0.36695 dice_loss 0.06457 +Epoch [3642/4000] Validation [2/4] Loss: 0.93770 focal_loss 0.75190 dice_loss 0.18580 +Epoch [3642/4000] Validation [3/4] Loss: 0.51977 focal_loss 0.42889 dice_loss 0.09089 +Epoch [3642/4000] Validation [4/4] Loss: 0.53361 focal_loss 0.40949 dice_loss 0.12412 +Epoch [3642/4000] Validation metric {'Val/mean dice_metric': 0.9731669425964355, 'Val/mean miou_metric': 0.9593355059623718, 'Val/mean f1': 0.9761041402816772, 'Val/mean precision': 0.9748304486274719, 'Val/mean recall': 0.97738116979599, 'Val/mean hd95_metric': 4.70460319519043} +Cheakpoint... +Epoch [3642/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731669425964355, 'Val/mean miou_metric': 0.9593355059623718, 'Val/mean f1': 0.9761041402816772, 'Val/mean precision': 0.9748304486274719, 'Val/mean recall': 0.97738116979599, 'Val/mean hd95_metric': 4.70460319519043} +Epoch [3643/4000] Training [1/16] Loss: 0.00395 +Epoch [3643/4000] Training [2/16] Loss: 0.00160 +Epoch [3643/4000] Training [3/16] Loss: 0.00279 +Epoch [3643/4000] Training [4/16] Loss: 0.00225 +Epoch [3643/4000] Training [5/16] Loss: 0.00290 +Epoch [3643/4000] Training [6/16] Loss: 0.00299 +Epoch [3643/4000] Training [7/16] Loss: 0.00317 +Epoch [3643/4000] Training [8/16] Loss: 0.00189 +Epoch [3643/4000] Training [9/16] Loss: 0.00170 +Epoch [3643/4000] Training [10/16] Loss: 0.00373 +Epoch [3643/4000] Training [11/16] Loss: 0.00352 +Epoch [3643/4000] Training [12/16] Loss: 0.00194 +Epoch [3643/4000] Training [13/16] Loss: 0.00193 +Epoch [3643/4000] Training [14/16] Loss: 0.00317 +Epoch [3643/4000] Training [15/16] Loss: 0.00282 +Epoch [3643/4000] Training [16/16] Loss: 0.00259 +Epoch [3643/4000] Training metric {'Train/mean dice_metric': 0.9985719919204712, 'Train/mean miou_metric': 0.9968706965446472, 'Train/mean f1': 0.9936212301254272, 'Train/mean precision': 0.9890525937080383, 'Train/mean recall': 0.9982322454452515, 'Train/mean hd95_metric': 0.5476417541503906} +Epoch [3643/4000] Validation [1/4] Loss: 0.39053 focal_loss 0.33033 dice_loss 0.06021 +Epoch [3643/4000] Validation [2/4] Loss: 0.60237 focal_loss 0.44465 dice_loss 0.15771 +Epoch [3643/4000] Validation [3/4] Loss: 0.28616 focal_loss 0.22378 dice_loss 0.06238 +Epoch [3643/4000] Validation [4/4] Loss: 0.34428 focal_loss 0.25053 dice_loss 0.09376 +Epoch [3643/4000] Validation metric {'Val/mean dice_metric': 0.9743000268936157, 'Val/mean miou_metric': 0.9602562785148621, 'Val/mean f1': 0.9764112234115601, 'Val/mean precision': 0.9745079874992371, 'Val/mean recall': 0.9783219695091248, 'Val/mean hd95_metric': 4.864107608795166} +Cheakpoint... +Epoch [3643/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743000268936157, 'Val/mean miou_metric': 0.9602562785148621, 'Val/mean f1': 0.9764112234115601, 'Val/mean precision': 0.9745079874992371, 'Val/mean recall': 0.9783219695091248, 'Val/mean hd95_metric': 4.864107608795166} +Epoch [3644/4000] Training [1/16] Loss: 0.00234 +Epoch [3644/4000] Training [2/16] Loss: 0.00206 +Epoch [3644/4000] Training [3/16] Loss: 0.00310 +Epoch [3644/4000] Training [4/16] Loss: 0.00232 +Epoch [3644/4000] Training [5/16] Loss: 0.00323 +Epoch [3644/4000] Training [6/16] Loss: 0.00196 +Epoch [3644/4000] Training [7/16] Loss: 0.00190 +Epoch [3644/4000] Training [8/16] Loss: 0.00279 +Epoch [3644/4000] Training [9/16] Loss: 0.00222 +Epoch [3644/4000] Training [10/16] Loss: 0.00158 +Epoch [3644/4000] Training [11/16] Loss: 0.00296 +Epoch [3644/4000] Training [12/16] Loss: 0.00336 +Epoch [3644/4000] Training [13/16] Loss: 0.00144 +Epoch [3644/4000] Training [14/16] Loss: 0.00219 +Epoch [3644/4000] Training [15/16] Loss: 0.00239 +Epoch [3644/4000] Training [16/16] Loss: 0.00242 +Epoch [3644/4000] Training metric {'Train/mean dice_metric': 0.9987310171127319, 'Train/mean miou_metric': 0.9971539974212646, 'Train/mean f1': 0.9931477904319763, 'Train/mean precision': 0.987999677658081, 'Train/mean recall': 0.9983499050140381, 'Train/mean hd95_metric': 0.5299103856086731} +Epoch [3644/4000] Validation [1/4] Loss: 0.36488 focal_loss 0.30530 dice_loss 0.05959 +Epoch [3644/4000] Validation [2/4] Loss: 0.58259 focal_loss 0.43566 dice_loss 0.14693 +Epoch [3644/4000] Validation [3/4] Loss: 0.54252 focal_loss 0.45062 dice_loss 0.09190 +Epoch [3644/4000] Validation [4/4] Loss: 0.29406 focal_loss 0.20470 dice_loss 0.08936 +Epoch [3644/4000] Validation metric {'Val/mean dice_metric': 0.9744588732719421, 'Val/mean miou_metric': 0.9604721069335938, 'Val/mean f1': 0.9760995507240295, 'Val/mean precision': 0.9728733897209167, 'Val/mean recall': 0.9793472290039062, 'Val/mean hd95_metric': 5.041258811950684} +Cheakpoint... +Epoch [3644/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744588732719421, 'Val/mean miou_metric': 0.9604721069335938, 'Val/mean f1': 0.9760995507240295, 'Val/mean precision': 0.9728733897209167, 'Val/mean recall': 0.9793472290039062, 'Val/mean hd95_metric': 5.041258811950684} +Epoch [3645/4000] Training [1/16] Loss: 0.00219 +Epoch [3645/4000] Training [2/16] Loss: 0.00344 +Epoch [3645/4000] Training [3/16] Loss: 0.00253 +Epoch [3645/4000] Training [4/16] Loss: 0.00219 +Epoch [3645/4000] Training [5/16] Loss: 0.00164 +Epoch [3645/4000] Training [6/16] Loss: 0.00325 +Epoch [3645/4000] Training [7/16] Loss: 0.00216 +Epoch [3645/4000] Training [8/16] Loss: 0.00246 +Epoch [3645/4000] Training [9/16] Loss: 0.00323 +Epoch [3645/4000] Training [10/16] Loss: 0.00181 +Epoch [3645/4000] Training [11/16] Loss: 0.00311 +Epoch [3645/4000] Training [12/16] Loss: 0.00280 +Epoch [3645/4000] Training [13/16] Loss: 0.00402 +Epoch [3645/4000] Training [14/16] Loss: 0.00183 +Epoch [3645/4000] Training [15/16] Loss: 0.00245 +Epoch [3645/4000] Training [16/16] Loss: 0.00237 +Epoch [3645/4000] Training metric {'Train/mean dice_metric': 0.9987125396728516, 'Train/mean miou_metric': 0.9971296787261963, 'Train/mean f1': 0.9933809638023376, 'Train/mean precision': 0.9884757995605469, 'Train/mean recall': 0.998335063457489, 'Train/mean hd95_metric': 0.5385318994522095} +Epoch [3645/4000] Validation [1/4] Loss: 0.47180 focal_loss 0.40714 dice_loss 0.06466 +Epoch [3645/4000] Validation [2/4] Loss: 0.49959 focal_loss 0.38795 dice_loss 0.11164 +Epoch [3645/4000] Validation [3/4] Loss: 0.54686 focal_loss 0.45550 dice_loss 0.09136 +Epoch [3645/4000] Validation [4/4] Loss: 0.34841 focal_loss 0.26117 dice_loss 0.08724 +Epoch [3645/4000] Validation metric {'Val/mean dice_metric': 0.9756442904472351, 'Val/mean miou_metric': 0.9616039395332336, 'Val/mean f1': 0.9759581089019775, 'Val/mean precision': 0.9736217856407166, 'Val/mean recall': 0.9783058762550354, 'Val/mean hd95_metric': 4.721320629119873} +Cheakpoint... +Epoch [3645/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756442904472351, 'Val/mean miou_metric': 0.9616039395332336, 'Val/mean f1': 0.9759581089019775, 'Val/mean precision': 0.9736217856407166, 'Val/mean recall': 0.9783058762550354, 'Val/mean hd95_metric': 4.721320629119873} +Epoch [3646/4000] Training [1/16] Loss: 0.00230 +Epoch [3646/4000] Training [2/16] Loss: 0.00181 +Epoch [3646/4000] Training [3/16] Loss: 0.00204 +Epoch [3646/4000] Training [4/16] Loss: 0.00284 +Epoch [3646/4000] Training [5/16] Loss: 0.00240 +Epoch [3646/4000] Training [6/16] Loss: 0.00341 +Epoch [3646/4000] Training [7/16] Loss: 0.00250 +Epoch [3646/4000] Training [8/16] Loss: 0.00244 +Epoch [3646/4000] Training [9/16] Loss: 0.00166 +Epoch [3646/4000] Training [10/16] Loss: 0.00243 +Epoch [3646/4000] Training [11/16] Loss: 0.00218 +Epoch [3646/4000] Training [12/16] Loss: 0.00274 +Epoch [3646/4000] Training [13/16] Loss: 0.00281 +Epoch [3646/4000] Training [14/16] Loss: 0.00249 +Epoch [3646/4000] Training [15/16] Loss: 0.00252 +Epoch [3646/4000] Training [16/16] Loss: 0.00219 +Epoch [3646/4000] Training metric {'Train/mean dice_metric': 0.9988477826118469, 'Train/mean miou_metric': 0.9974216818809509, 'Train/mean f1': 0.9938180446624756, 'Train/mean precision': 0.989291787147522, 'Train/mean recall': 0.9983858466148376, 'Train/mean hd95_metric': 0.51291823387146} +Epoch [3646/4000] Validation [1/4] Loss: 0.49346 focal_loss 0.42025 dice_loss 0.07321 +Epoch [3646/4000] Validation [2/4] Loss: 0.51244 focal_loss 0.40089 dice_loss 0.11154 +Epoch [3646/4000] Validation [3/4] Loss: 0.56667 focal_loss 0.47209 dice_loss 0.09458 +Epoch [3646/4000] Validation [4/4] Loss: 0.52461 focal_loss 0.39715 dice_loss 0.12747 +Epoch [3646/4000] Validation metric {'Val/mean dice_metric': 0.9728587865829468, 'Val/mean miou_metric': 0.9581268429756165, 'Val/mean f1': 0.975275993347168, 'Val/mean precision': 0.974673330783844, 'Val/mean recall': 0.9758793115615845, 'Val/mean hd95_metric': 5.05400276184082} +Cheakpoint... +Epoch [3646/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728587865829468, 'Val/mean miou_metric': 0.9581268429756165, 'Val/mean f1': 0.975275993347168, 'Val/mean precision': 0.974673330783844, 'Val/mean recall': 0.9758793115615845, 'Val/mean hd95_metric': 5.05400276184082} +Epoch [3647/4000] Training [1/16] Loss: 0.00223 +Epoch [3647/4000] Training [2/16] Loss: 0.00349 +Epoch [3647/4000] Training [3/16] Loss: 0.00185 +Epoch [3647/4000] Training [4/16] Loss: 0.00234 +Epoch [3647/4000] Training [5/16] Loss: 0.00222 +Epoch [3647/4000] Training [6/16] Loss: 0.00222 +Epoch [3647/4000] Training [7/16] Loss: 0.00234 +Epoch [3647/4000] Training [8/16] Loss: 0.00270 +Epoch [3647/4000] Training [9/16] Loss: 0.00287 +Epoch [3647/4000] Training [10/16] Loss: 0.00275 +Epoch [3647/4000] Training [11/16] Loss: 0.00212 +Epoch [3647/4000] Training [12/16] Loss: 0.00200 +Epoch [3647/4000] Training [13/16] Loss: 0.00220 +Epoch [3647/4000] Training [14/16] Loss: 0.00232 +Epoch [3647/4000] Training [15/16] Loss: 0.00203 +Epoch [3647/4000] Training [16/16] Loss: 0.00304 +Epoch [3647/4000] Training metric {'Train/mean dice_metric': 0.9987446069717407, 'Train/mean miou_metric': 0.9972001910209656, 'Train/mean f1': 0.9936595559120178, 'Train/mean precision': 0.9890403151512146, 'Train/mean recall': 0.998322069644928, 'Train/mean hd95_metric': 0.5441681146621704} +Epoch [3647/4000] Validation [1/4] Loss: 0.37754 focal_loss 0.31568 dice_loss 0.06186 +Epoch [3647/4000] Validation [2/4] Loss: 0.52040 focal_loss 0.40642 dice_loss 0.11398 +Epoch [3647/4000] Validation [3/4] Loss: 0.26922 focal_loss 0.20998 dice_loss 0.05924 +Epoch [3647/4000] Validation [4/4] Loss: 0.38955 focal_loss 0.28683 dice_loss 0.10272 +Epoch [3647/4000] Validation metric {'Val/mean dice_metric': 0.9731912612915039, 'Val/mean miou_metric': 0.9594632983207703, 'Val/mean f1': 0.9760454893112183, 'Val/mean precision': 0.975145161151886, 'Val/mean recall': 0.9769476056098938, 'Val/mean hd95_metric': 4.68639612197876} +Cheakpoint... +Epoch [3647/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731912612915039, 'Val/mean miou_metric': 0.9594632983207703, 'Val/mean f1': 0.9760454893112183, 'Val/mean precision': 0.975145161151886, 'Val/mean recall': 0.9769476056098938, 'Val/mean hd95_metric': 4.68639612197876} +Epoch [3648/4000] Training [1/16] Loss: 0.00230 +Epoch [3648/4000] Training [2/16] Loss: 0.00169 +Epoch [3648/4000] Training [3/16] Loss: 0.00223 +Epoch [3648/4000] Training [4/16] Loss: 0.00263 +Epoch [3648/4000] Training [5/16] Loss: 0.00187 +Epoch [3648/4000] Training [6/16] Loss: 0.00268 +Epoch [3648/4000] Training [7/16] Loss: 0.00226 +Epoch [3648/4000] Training [8/16] Loss: 0.00227 +Epoch [3648/4000] Training [9/16] Loss: 0.00265 +Epoch [3648/4000] Training [10/16] Loss: 0.00244 +Epoch [3648/4000] Training [11/16] Loss: 0.00205 +Epoch [3648/4000] Training [12/16] Loss: 0.00285 +Epoch [3648/4000] Training [13/16] Loss: 0.00190 +Epoch [3648/4000] Training [14/16] Loss: 0.00183 +Epoch [3648/4000] Training [15/16] Loss: 0.00264 +Epoch [3648/4000] Training [16/16] Loss: 0.00239 +Epoch [3648/4000] Training metric {'Train/mean dice_metric': 0.9988511800765991, 'Train/mean miou_metric': 0.9974271059036255, 'Train/mean f1': 0.9938949346542358, 'Train/mean precision': 0.989347517490387, 'Train/mean recall': 0.9984843730926514, 'Train/mean hd95_metric': 0.49273115396499634} +Epoch [3648/4000] Validation [1/4] Loss: 0.41511 focal_loss 0.35122 dice_loss 0.06389 +Epoch [3648/4000] Validation [2/4] Loss: 0.47823 focal_loss 0.36826 dice_loss 0.10996 +Epoch [3648/4000] Validation [3/4] Loss: 0.51937 focal_loss 0.42899 dice_loss 0.09038 +Epoch [3648/4000] Validation [4/4] Loss: 0.36473 focal_loss 0.26848 dice_loss 0.09625 +Epoch [3648/4000] Validation metric {'Val/mean dice_metric': 0.9751766920089722, 'Val/mean miou_metric': 0.9612639546394348, 'Val/mean f1': 0.9764158725738525, 'Val/mean precision': 0.9744369983673096, 'Val/mean recall': 0.9784030318260193, 'Val/mean hd95_metric': 4.735630989074707} +Cheakpoint... +Epoch [3648/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751766920089722, 'Val/mean miou_metric': 0.9612639546394348, 'Val/mean f1': 0.9764158725738525, 'Val/mean precision': 0.9744369983673096, 'Val/mean recall': 0.9784030318260193, 'Val/mean hd95_metric': 4.735630989074707} +Epoch [3649/4000] Training [1/16] Loss: 0.00411 +Epoch [3649/4000] Training [2/16] Loss: 0.00216 +Epoch [3649/4000] Training [3/16] Loss: 0.00330 +Epoch [3649/4000] Training [4/16] Loss: 0.00204 +Epoch [3649/4000] Training [5/16] Loss: 0.00211 +Epoch [3649/4000] Training [6/16] Loss: 0.00424 +Epoch [3649/4000] Training [7/16] Loss: 0.00258 +Epoch [3649/4000] Training [8/16] Loss: 0.00212 +Epoch [3649/4000] Training [9/16] Loss: 0.00281 +Epoch [3649/4000] Training [10/16] Loss: 0.00166 +Epoch [3649/4000] Training [11/16] Loss: 0.00286 +Epoch [3649/4000] Training [12/16] Loss: 0.00271 +Epoch [3649/4000] Training [13/16] Loss: 0.00138 +Epoch [3649/4000] Training [14/16] Loss: 0.00199 +Epoch [3649/4000] Training [15/16] Loss: 0.00279 +Epoch [3649/4000] Training [16/16] Loss: 0.00263 +Epoch [3649/4000] Training metric {'Train/mean dice_metric': 0.9986886978149414, 'Train/mean miou_metric': 0.997089147567749, 'Train/mean f1': 0.9933820962905884, 'Train/mean precision': 0.9885598421096802, 'Train/mean recall': 0.9982516765594482, 'Train/mean hd95_metric': 0.5347510576248169} +Epoch [3649/4000] Validation [1/4] Loss: 0.39572 focal_loss 0.32868 dice_loss 0.06704 +Epoch [3649/4000] Validation [2/4] Loss: 0.51791 focal_loss 0.40266 dice_loss 0.11525 +Epoch [3649/4000] Validation [3/4] Loss: 0.53839 focal_loss 0.44576 dice_loss 0.09263 +Epoch [3649/4000] Validation [4/4] Loss: 0.44589 focal_loss 0.32912 dice_loss 0.11677 +Epoch [3649/4000] Validation metric {'Val/mean dice_metric': 0.9730058908462524, 'Val/mean miou_metric': 0.9586116671562195, 'Val/mean f1': 0.9756568670272827, 'Val/mean precision': 0.973941445350647, 'Val/mean recall': 0.9773783683776855, 'Val/mean hd95_metric': 4.7259063720703125} +Cheakpoint... +Epoch [3649/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730058908462524, 'Val/mean miou_metric': 0.9586116671562195, 'Val/mean f1': 0.9756568670272827, 'Val/mean precision': 0.973941445350647, 'Val/mean recall': 0.9773783683776855, 'Val/mean hd95_metric': 4.7259063720703125} +Epoch [3650/4000] Training [1/16] Loss: 0.00206 +Epoch [3650/4000] Training [2/16] Loss: 0.00210 +Epoch [3650/4000] Training [3/16] Loss: 0.00206 +Epoch [3650/4000] Training [4/16] Loss: 0.00212 +Epoch [3650/4000] Training [5/16] Loss: 0.00355 +Epoch [3650/4000] Training [6/16] Loss: 0.00288 +Epoch [3650/4000] Training [7/16] Loss: 0.00201 +Epoch [3650/4000] Training [8/16] Loss: 0.00206 +Epoch [3650/4000] Training [9/16] Loss: 0.00205 +Epoch [3650/4000] Training [10/16] Loss: 0.00175 +Epoch [3650/4000] Training [11/16] Loss: 0.00153 +Epoch [3650/4000] Training [12/16] Loss: 0.00284 +Epoch [3650/4000] Training [13/16] Loss: 0.00343 +Epoch [3650/4000] Training [14/16] Loss: 0.00354 +Epoch [3650/4000] Training [15/16] Loss: 0.00180 +Epoch [3650/4000] Training [16/16] Loss: 0.00322 +Epoch [3650/4000] Training metric {'Train/mean dice_metric': 0.9987192749977112, 'Train/mean miou_metric': 0.9971600770950317, 'Train/mean f1': 0.9937493205070496, 'Train/mean precision': 0.9892241358757019, 'Train/mean recall': 0.9983161091804504, 'Train/mean hd95_metric': 0.5346959829330444} +Epoch [3650/4000] Validation [1/4] Loss: 0.43238 focal_loss 0.36696 dice_loss 0.06542 +Epoch [3650/4000] Validation [2/4] Loss: 0.96708 focal_loss 0.77660 dice_loss 0.19047 +Epoch [3650/4000] Validation [3/4] Loss: 0.26735 focal_loss 0.20352 dice_loss 0.06383 +Epoch [3650/4000] Validation [4/4] Loss: 0.32368 focal_loss 0.22517 dice_loss 0.09851 +Epoch [3650/4000] Validation metric {'Val/mean dice_metric': 0.9743579626083374, 'Val/mean miou_metric': 0.9606379270553589, 'Val/mean f1': 0.9769343137741089, 'Val/mean precision': 0.9748390316963196, 'Val/mean recall': 0.9790385365486145, 'Val/mean hd95_metric': 4.877857208251953} +Cheakpoint... +Epoch [3650/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743579626083374, 'Val/mean miou_metric': 0.9606379270553589, 'Val/mean f1': 0.9769343137741089, 'Val/mean precision': 0.9748390316963196, 'Val/mean recall': 0.9790385365486145, 'Val/mean hd95_metric': 4.877857208251953} +Epoch [3651/4000] Training [1/16] Loss: 0.00229 +Epoch [3651/4000] Training [2/16] Loss: 0.00259 +Epoch [3651/4000] Training [3/16] Loss: 0.00247 +Epoch [3651/4000] Training [4/16] Loss: 0.00219 +Epoch [3651/4000] Training [5/16] Loss: 0.00228 +Epoch [3651/4000] Training [6/16] Loss: 0.00220 +Epoch [3651/4000] Training [7/16] Loss: 0.00316 +Epoch [3651/4000] Training [8/16] Loss: 0.00280 +Epoch [3651/4000] Training [9/16] Loss: 0.00261 +Epoch [3651/4000] Training [10/16] Loss: 0.00254 +Epoch [3651/4000] Training [11/16] Loss: 0.00203 +Epoch [3651/4000] Training [12/16] Loss: 0.00237 +Epoch [3651/4000] Training [13/16] Loss: 0.00258 +Epoch [3651/4000] Training [14/16] Loss: 0.00278 +Epoch [3651/4000] Training [15/16] Loss: 0.00312 +Epoch [3651/4000] Training [16/16] Loss: 0.00318 +Epoch [3651/4000] Training metric {'Train/mean dice_metric': 0.9986740946769714, 'Train/mean miou_metric': 0.9970608353614807, 'Train/mean f1': 0.9934704899787903, 'Train/mean precision': 0.9887073040008545, 'Train/mean recall': 0.9982797503471375, 'Train/mean hd95_metric': 0.5661408305168152} +Epoch [3651/4000] Validation [1/4] Loss: 0.39619 focal_loss 0.33397 dice_loss 0.06222 +Epoch [3651/4000] Validation [2/4] Loss: 0.50968 focal_loss 0.39745 dice_loss 0.11223 +Epoch [3651/4000] Validation [3/4] Loss: 0.61382 focal_loss 0.51119 dice_loss 0.10263 +Epoch [3651/4000] Validation [4/4] Loss: 0.32848 focal_loss 0.22780 dice_loss 0.10068 +Epoch [3651/4000] Validation metric {'Val/mean dice_metric': 0.9756622314453125, 'Val/mean miou_metric': 0.9608612060546875, 'Val/mean f1': 0.9760615229606628, 'Val/mean precision': 0.9736860394477844, 'Val/mean recall': 0.9784485697746277, 'Val/mean hd95_metric': 5.055638313293457} +Cheakpoint... +Epoch [3651/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756622314453125, 'Val/mean miou_metric': 0.9608612060546875, 'Val/mean f1': 0.9760615229606628, 'Val/mean precision': 0.9736860394477844, 'Val/mean recall': 0.9784485697746277, 'Val/mean hd95_metric': 5.055638313293457} +Epoch [3652/4000] Training [1/16] Loss: 0.00210 +Epoch [3652/4000] Training [2/16] Loss: 0.00269 +Epoch [3652/4000] Training [3/16] Loss: 0.00275 +Epoch [3652/4000] Training [4/16] Loss: 0.00224 +Epoch [3652/4000] Training [5/16] Loss: 0.00210 +Epoch [3652/4000] Training [6/16] Loss: 0.00319 +Epoch [3652/4000] Training [7/16] Loss: 0.00343 +Epoch [3652/4000] Training [8/16] Loss: 0.00317 +Epoch [3652/4000] Training [9/16] Loss: 0.00148 +Epoch [3652/4000] Training [10/16] Loss: 0.00214 +Epoch [3652/4000] Training [11/16] Loss: 0.00281 +Epoch [3652/4000] Training [12/16] Loss: 0.00159 +Epoch [3652/4000] Training [13/16] Loss: 0.00193 +Epoch [3652/4000] Training [14/16] Loss: 0.00265 +Epoch [3652/4000] Training [15/16] Loss: 0.00352 +Epoch [3652/4000] Training [16/16] Loss: 0.00214 +Epoch [3652/4000] Training metric {'Train/mean dice_metric': 0.9987834692001343, 'Train/mean miou_metric': 0.997292160987854, 'Train/mean f1': 0.9937787055969238, 'Train/mean precision': 0.9892525672912598, 'Train/mean recall': 0.9983465075492859, 'Train/mean hd95_metric': 0.5532501935958862} +Epoch [3652/4000] Validation [1/4] Loss: 0.37448 focal_loss 0.31136 dice_loss 0.06312 +Epoch [3652/4000] Validation [2/4] Loss: 0.50001 focal_loss 0.38856 dice_loss 0.11145 +Epoch [3652/4000] Validation [3/4] Loss: 0.56958 focal_loss 0.47145 dice_loss 0.09813 +Epoch [3652/4000] Validation [4/4] Loss: 0.36564 focal_loss 0.27559 dice_loss 0.09004 +Epoch [3652/4000] Validation metric {'Val/mean dice_metric': 0.9748914837837219, 'Val/mean miou_metric': 0.9607158899307251, 'Val/mean f1': 0.976317286491394, 'Val/mean precision': 0.9741939902305603, 'Val/mean recall': 0.9784496426582336, 'Val/mean hd95_metric': 4.906802177429199} +Cheakpoint... +Epoch [3652/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748914837837219, 'Val/mean miou_metric': 0.9607158899307251, 'Val/mean f1': 0.976317286491394, 'Val/mean precision': 0.9741939902305603, 'Val/mean recall': 0.9784496426582336, 'Val/mean hd95_metric': 4.906802177429199} +Epoch [3653/4000] Training [1/16] Loss: 0.00278 +Epoch [3653/4000] Training [2/16] Loss: 0.00220 +Epoch [3653/4000] Training [3/16] Loss: 0.00298 +Epoch [3653/4000] Training [4/16] Loss: 0.00445 +Epoch [3653/4000] Training [5/16] Loss: 0.00222 +Epoch [3653/4000] Training [6/16] Loss: 0.00144 +Epoch [3653/4000] Training [7/16] Loss: 0.00226 +Epoch [3653/4000] Training [8/16] Loss: 0.00201 +Epoch [3653/4000] Training [9/16] Loss: 0.00193 +Epoch [3653/4000] Training [10/16] Loss: 0.00334 +Epoch [3653/4000] Training [11/16] Loss: 0.00349 +Epoch [3653/4000] Training [12/16] Loss: 0.00204 +Epoch [3653/4000] Training [13/16] Loss: 0.00149 +Epoch [3653/4000] Training [14/16] Loss: 0.00199 +Epoch [3653/4000] Training [15/16] Loss: 0.00242 +Epoch [3653/4000] Training [16/16] Loss: 0.00239 +Epoch [3653/4000] Training metric {'Train/mean dice_metric': 0.9987623691558838, 'Train/mean miou_metric': 0.997248649597168, 'Train/mean f1': 0.9938156604766846, 'Train/mean precision': 0.9892551302909851, 'Train/mean recall': 0.9984185099601746, 'Train/mean hd95_metric': 0.504226803779602} +Epoch [3653/4000] Validation [1/4] Loss: 0.38722 focal_loss 0.32469 dice_loss 0.06253 +Epoch [3653/4000] Validation [2/4] Loss: 0.97984 focal_loss 0.79030 dice_loss 0.18954 +Epoch [3653/4000] Validation [3/4] Loss: 0.54834 focal_loss 0.45533 dice_loss 0.09302 +Epoch [3653/4000] Validation [4/4] Loss: 0.52760 focal_loss 0.40951 dice_loss 0.11808 +Epoch [3653/4000] Validation metric {'Val/mean dice_metric': 0.9727531671524048, 'Val/mean miou_metric': 0.9590554237365723, 'Val/mean f1': 0.9760227799415588, 'Val/mean precision': 0.974382758140564, 'Val/mean recall': 0.9776684641838074, 'Val/mean hd95_metric': 4.676918983459473} +Cheakpoint... +Epoch [3653/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727531671524048, 'Val/mean miou_metric': 0.9590554237365723, 'Val/mean f1': 0.9760227799415588, 'Val/mean precision': 0.974382758140564, 'Val/mean recall': 0.9776684641838074, 'Val/mean hd95_metric': 4.676918983459473} +Epoch [3654/4000] Training [1/16] Loss: 0.00193 +Epoch [3654/4000] Training [2/16] Loss: 0.00198 +Epoch [3654/4000] Training [3/16] Loss: 0.00229 +Epoch [3654/4000] Training [4/16] Loss: 0.00227 +Epoch [3654/4000] Training [5/16] Loss: 0.00220 +Epoch [3654/4000] Training [6/16] Loss: 0.00252 +Epoch [3654/4000] Training [7/16] Loss: 0.00190 +Epoch [3654/4000] Training [8/16] Loss: 0.00225 +Epoch [3654/4000] Training [9/16] Loss: 0.00230 +Epoch [3654/4000] Training [10/16] Loss: 0.00251 +Epoch [3654/4000] Training [11/16] Loss: 0.00356 +Epoch [3654/4000] Training [12/16] Loss: 0.00273 +Epoch [3654/4000] Training [13/16] Loss: 0.00296 +Epoch [3654/4000] Training [14/16] Loss: 0.00219 +Epoch [3654/4000] Training [15/16] Loss: 0.00195 +Epoch [3654/4000] Training [16/16] Loss: 0.00207 +Epoch [3654/4000] Training metric {'Train/mean dice_metric': 0.9988346099853516, 'Train/mean miou_metric': 0.9973874688148499, 'Train/mean f1': 0.9937747120857239, 'Train/mean precision': 0.9891480803489685, 'Train/mean recall': 0.9984448552131653, 'Train/mean hd95_metric': 0.5100862383842468} +Epoch [3654/4000] Validation [1/4] Loss: 0.45933 focal_loss 0.39470 dice_loss 0.06463 +Epoch [3654/4000] Validation [2/4] Loss: 0.64273 focal_loss 0.47500 dice_loss 0.16772 +Epoch [3654/4000] Validation [3/4] Loss: 0.54012 focal_loss 0.44566 dice_loss 0.09446 +Epoch [3654/4000] Validation [4/4] Loss: 0.55086 focal_loss 0.42545 dice_loss 0.12540 +Epoch [3654/4000] Validation metric {'Val/mean dice_metric': 0.973501980304718, 'Val/mean miou_metric': 0.959050178527832, 'Val/mean f1': 0.9762774705886841, 'Val/mean precision': 0.9744419455528259, 'Val/mean recall': 0.9781199097633362, 'Val/mean hd95_metric': 5.314535617828369} +Cheakpoint... +Epoch [3654/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973501980304718, 'Val/mean miou_metric': 0.959050178527832, 'Val/mean f1': 0.9762774705886841, 'Val/mean precision': 0.9744419455528259, 'Val/mean recall': 0.9781199097633362, 'Val/mean hd95_metric': 5.314535617828369} +Epoch [3655/4000] Training [1/16] Loss: 0.00415 +Epoch [3655/4000] Training [2/16] Loss: 0.00190 +Epoch [3655/4000] Training [3/16] Loss: 0.00192 +Epoch [3655/4000] Training [4/16] Loss: 0.00358 +Epoch [3655/4000] Training [5/16] Loss: 0.00228 +Epoch [3655/4000] Training [6/16] Loss: 0.00195 +Epoch [3655/4000] Training [7/16] Loss: 0.00235 +Epoch [3655/4000] Training [8/16] Loss: 0.00272 +Epoch [3655/4000] Training [9/16] Loss: 0.00233 +Epoch [3655/4000] Training [10/16] Loss: 0.00285 +Epoch [3655/4000] Training [11/16] Loss: 0.00248 +Epoch [3655/4000] Training [12/16] Loss: 0.00167 +Epoch [3655/4000] Training [13/16] Loss: 0.00284 +Epoch [3655/4000] Training [14/16] Loss: 0.00257 +Epoch [3655/4000] Training [15/16] Loss: 0.00333 +Epoch [3655/4000] Training [16/16] Loss: 0.00321 +Epoch [3655/4000] Training metric {'Train/mean dice_metric': 0.9984922409057617, 'Train/mean miou_metric': 0.9967161417007446, 'Train/mean f1': 0.9935864210128784, 'Train/mean precision': 0.9890392422676086, 'Train/mean recall': 0.9981755614280701, 'Train/mean hd95_metric': 0.56955885887146} +Epoch [3655/4000] Validation [1/4] Loss: 0.46115 focal_loss 0.39551 dice_loss 0.06563 +Epoch [3655/4000] Validation [2/4] Loss: 0.61656 focal_loss 0.45972 dice_loss 0.15684 +Epoch [3655/4000] Validation [3/4] Loss: 0.54437 focal_loss 0.45053 dice_loss 0.09384 +Epoch [3655/4000] Validation [4/4] Loss: 0.35238 focal_loss 0.26797 dice_loss 0.08441 +Epoch [3655/4000] Validation metric {'Val/mean dice_metric': 0.9741972088813782, 'Val/mean miou_metric': 0.959769070148468, 'Val/mean f1': 0.9759315848350525, 'Val/mean precision': 0.9742628335952759, 'Val/mean recall': 0.9776060581207275, 'Val/mean hd95_metric': 4.792064189910889} +Cheakpoint... +Epoch [3655/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741972088813782, 'Val/mean miou_metric': 0.959769070148468, 'Val/mean f1': 0.9759315848350525, 'Val/mean precision': 0.9742628335952759, 'Val/mean recall': 0.9776060581207275, 'Val/mean hd95_metric': 4.792064189910889} +Epoch [3656/4000] Training [1/16] Loss: 0.00211 +Epoch [3656/4000] Training [2/16] Loss: 0.00214 +Epoch [3656/4000] Training [3/16] Loss: 0.00197 +Epoch [3656/4000] Training [4/16] Loss: 0.00184 +Epoch [3656/4000] Training [5/16] Loss: 0.00234 +Epoch [3656/4000] Training [6/16] Loss: 0.00249 +Epoch [3656/4000] Training [7/16] Loss: 0.00208 +Epoch [3656/4000] Training [8/16] Loss: 0.00185 +Epoch [3656/4000] Training [9/16] Loss: 0.00305 +Epoch [3656/4000] Training [10/16] Loss: 0.00238 +Epoch [3656/4000] Training [11/16] Loss: 0.00241 +Epoch [3656/4000] Training [12/16] Loss: 0.00143 +Epoch [3656/4000] Training [13/16] Loss: 0.00310 +Epoch [3656/4000] Training [14/16] Loss: 0.00212 +Epoch [3656/4000] Training [15/16] Loss: 0.00239 +Epoch [3656/4000] Training [16/16] Loss: 0.00259 +Epoch [3656/4000] Training metric {'Train/mean dice_metric': 0.998715877532959, 'Train/mean miou_metric': 0.9971485733985901, 'Train/mean f1': 0.9934857487678528, 'Train/mean precision': 0.9887295961380005, 'Train/mean recall': 0.9982877969741821, 'Train/mean hd95_metric': 0.5338166952133179} +Epoch [3656/4000] Validation [1/4] Loss: 0.40834 focal_loss 0.34348 dice_loss 0.06485 +Epoch [3656/4000] Validation [2/4] Loss: 0.48317 focal_loss 0.37388 dice_loss 0.10929 +Epoch [3656/4000] Validation [3/4] Loss: 0.54357 focal_loss 0.45027 dice_loss 0.09329 +Epoch [3656/4000] Validation [4/4] Loss: 0.46604 focal_loss 0.35356 dice_loss 0.11248 +Epoch [3656/4000] Validation metric {'Val/mean dice_metric': 0.9739536046981812, 'Val/mean miou_metric': 0.9599075317382812, 'Val/mean f1': 0.9759016633033752, 'Val/mean precision': 0.9740620255470276, 'Val/mean recall': 0.9777482748031616, 'Val/mean hd95_metric': 4.770076274871826} +Cheakpoint... +Epoch [3656/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739536046981812, 'Val/mean miou_metric': 0.9599075317382812, 'Val/mean f1': 0.9759016633033752, 'Val/mean precision': 0.9740620255470276, 'Val/mean recall': 0.9777482748031616, 'Val/mean hd95_metric': 4.770076274871826} +Epoch [3657/4000] Training [1/16] Loss: 0.00210 +Epoch [3657/4000] Training [2/16] Loss: 0.00295 +Epoch [3657/4000] Training [3/16] Loss: 0.00275 +Epoch [3657/4000] Training [4/16] Loss: 0.00367 +Epoch [3657/4000] Training [5/16] Loss: 0.00232 +Epoch [3657/4000] Training [6/16] Loss: 0.00253 +Epoch [3657/4000] Training [7/16] Loss: 0.00174 +Epoch [3657/4000] Training [8/16] Loss: 0.00357 +Epoch [3657/4000] Training [9/16] Loss: 0.00302 +Epoch [3657/4000] Training [10/16] Loss: 0.00263 +Epoch [3657/4000] Training [11/16] Loss: 0.00363 +Epoch [3657/4000] Training [12/16] Loss: 0.00401 +Epoch [3657/4000] Training [13/16] Loss: 0.00187 +Epoch [3657/4000] Training [14/16] Loss: 0.00194 +Epoch [3657/4000] Training [15/16] Loss: 0.00264 +Epoch [3657/4000] Training [16/16] Loss: 0.00274 +Epoch [3657/4000] Training metric {'Train/mean dice_metric': 0.9985557794570923, 'Train/mean miou_metric': 0.9968322515487671, 'Train/mean f1': 0.9934711456298828, 'Train/mean precision': 0.988807201385498, 'Train/mean recall': 0.9981793165206909, 'Train/mean hd95_metric': 0.5556217432022095} +Epoch [3657/4000] Validation [1/4] Loss: 0.39506 focal_loss 0.33197 dice_loss 0.06309 +Epoch [3657/4000] Validation [2/4] Loss: 0.51768 focal_loss 0.40503 dice_loss 0.11265 +Epoch [3657/4000] Validation [3/4] Loss: 0.53888 focal_loss 0.44199 dice_loss 0.09689 +Epoch [3657/4000] Validation [4/4] Loss: 0.48984 focal_loss 0.38352 dice_loss 0.10632 +Epoch [3657/4000] Validation metric {'Val/mean dice_metric': 0.9738319516181946, 'Val/mean miou_metric': 0.9597063064575195, 'Val/mean f1': 0.9761106371879578, 'Val/mean precision': 0.9743422865867615, 'Val/mean recall': 0.9778854846954346, 'Val/mean hd95_metric': 4.913687705993652} +Cheakpoint... +Epoch [3657/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738319516181946, 'Val/mean miou_metric': 0.9597063064575195, 'Val/mean f1': 0.9761106371879578, 'Val/mean precision': 0.9743422865867615, 'Val/mean recall': 0.9778854846954346, 'Val/mean hd95_metric': 4.913687705993652} +Epoch [3658/4000] Training [1/16] Loss: 0.00242 +Epoch [3658/4000] Training [2/16] Loss: 0.00272 +Epoch [3658/4000] Training [3/16] Loss: 0.00451 +Epoch [3658/4000] Training [4/16] Loss: 0.00201 +Epoch [3658/4000] Training [5/16] Loss: 0.00261 +Epoch [3658/4000] Training [6/16] Loss: 0.00272 +Epoch [3658/4000] Training [7/16] Loss: 0.00184 +Epoch [3658/4000] Training [8/16] Loss: 0.00370 +Epoch [3658/4000] Training [9/16] Loss: 0.00235 +Epoch [3658/4000] Training [10/16] Loss: 0.00176 +Epoch [3658/4000] Training [11/16] Loss: 0.00450 +Epoch [3658/4000] Training [12/16] Loss: 0.00186 +Epoch [3658/4000] Training [13/16] Loss: 0.00280 +Epoch [3658/4000] Training [14/16] Loss: 0.00176 +Epoch [3658/4000] Training [15/16] Loss: 0.00242 +Epoch [3658/4000] Training [16/16] Loss: 0.00257 +Epoch [3658/4000] Training metric {'Train/mean dice_metric': 0.998458743095398, 'Train/mean miou_metric': 0.9966561794281006, 'Train/mean f1': 0.9934451580047607, 'Train/mean precision': 0.9887160658836365, 'Train/mean recall': 0.9982197284698486, 'Train/mean hd95_metric': 0.6156716346740723} +Epoch [3658/4000] Validation [1/4] Loss: 0.40937 focal_loss 0.34566 dice_loss 0.06371 +Epoch [3658/4000] Validation [2/4] Loss: 0.52228 focal_loss 0.39600 dice_loss 0.12628 +Epoch [3658/4000] Validation [3/4] Loss: 0.49997 focal_loss 0.41242 dice_loss 0.08755 +Epoch [3658/4000] Validation [4/4] Loss: 0.36497 focal_loss 0.27603 dice_loss 0.08894 +Epoch [3658/4000] Validation metric {'Val/mean dice_metric': 0.9736868143081665, 'Val/mean miou_metric': 0.9596670269966125, 'Val/mean f1': 0.975788950920105, 'Val/mean precision': 0.9741916060447693, 'Val/mean recall': 0.9773916602134705, 'Val/mean hd95_metric': 4.913581371307373} +Cheakpoint... +Epoch [3658/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736868143081665, 'Val/mean miou_metric': 0.9596670269966125, 'Val/mean f1': 0.975788950920105, 'Val/mean precision': 0.9741916060447693, 'Val/mean recall': 0.9773916602134705, 'Val/mean hd95_metric': 4.913581371307373} +Epoch [3659/4000] Training [1/16] Loss: 0.00258 +Epoch [3659/4000] Training [2/16] Loss: 0.00234 +Epoch [3659/4000] Training [3/16] Loss: 0.00159 +Epoch [3659/4000] Training [4/16] Loss: 0.00297 +Epoch [3659/4000] Training [5/16] Loss: 0.00195 +Epoch [3659/4000] Training [6/16] Loss: 0.00261 +Epoch [3659/4000] Training [7/16] Loss: 0.00211 +Epoch [3659/4000] Training [8/16] Loss: 0.00190 +Epoch [3659/4000] Training [9/16] Loss: 0.00278 +Epoch [3659/4000] Training [10/16] Loss: 0.00278 +Epoch [3659/4000] Training [11/16] Loss: 0.00233 +Epoch [3659/4000] Training [12/16] Loss: 0.00244 +Epoch [3659/4000] Training [13/16] Loss: 0.00286 +Epoch [3659/4000] Training [14/16] Loss: 0.00203 +Epoch [3659/4000] Training [15/16] Loss: 0.00190 +Epoch [3659/4000] Training [16/16] Loss: 0.00295 +Epoch [3659/4000] Training metric {'Train/mean dice_metric': 0.9988002777099609, 'Train/mean miou_metric': 0.9973268508911133, 'Train/mean f1': 0.9938122630119324, 'Train/mean precision': 0.9892630577087402, 'Train/mean recall': 0.9984034895896912, 'Train/mean hd95_metric': 0.52854323387146} +Epoch [3659/4000] Validation [1/4] Loss: 0.42928 focal_loss 0.36508 dice_loss 0.06421 +Epoch [3659/4000] Validation [2/4] Loss: 1.02243 focal_loss 0.81995 dice_loss 0.20248 +Epoch [3659/4000] Validation [3/4] Loss: 0.26360 focal_loss 0.20387 dice_loss 0.05972 +Epoch [3659/4000] Validation [4/4] Loss: 0.40099 focal_loss 0.29307 dice_loss 0.10793 +Epoch [3659/4000] Validation metric {'Val/mean dice_metric': 0.9738473892211914, 'Val/mean miou_metric': 0.9599186182022095, 'Val/mean f1': 0.9763461947441101, 'Val/mean precision': 0.9747611880302429, 'Val/mean recall': 0.9779362678527832, 'Val/mean hd95_metric': 5.002874851226807} +Cheakpoint... +Epoch [3659/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738473892211914, 'Val/mean miou_metric': 0.9599186182022095, 'Val/mean f1': 0.9763461947441101, 'Val/mean precision': 0.9747611880302429, 'Val/mean recall': 0.9779362678527832, 'Val/mean hd95_metric': 5.002874851226807} +Epoch [3660/4000] Training [1/16] Loss: 0.00212 +Epoch [3660/4000] Training [2/16] Loss: 0.00169 +Epoch [3660/4000] Training [3/16] Loss: 0.00249 +Epoch [3660/4000] Training [4/16] Loss: 0.00179 +Epoch [3660/4000] Training [5/16] Loss: 0.00311 +Epoch [3660/4000] Training [6/16] Loss: 0.00152 +Epoch [3660/4000] Training [7/16] Loss: 0.00267 +Epoch [3660/4000] Training [8/16] Loss: 0.00479 +Epoch [3660/4000] Training [9/16] Loss: 0.00293 +Epoch [3660/4000] Training [10/16] Loss: 0.00319 +Epoch [3660/4000] Training [11/16] Loss: 0.00225 +Epoch [3660/4000] Training [12/16] Loss: 0.00336 +Epoch [3660/4000] Training [13/16] Loss: 0.00192 +Epoch [3660/4000] Training [14/16] Loss: 0.00324 +Epoch [3660/4000] Training [15/16] Loss: 0.00263 +Epoch [3660/4000] Training [16/16] Loss: 0.00292 +Epoch [3660/4000] Training metric {'Train/mean dice_metric': 0.9986467361450195, 'Train/mean miou_metric': 0.997023344039917, 'Train/mean f1': 0.9936894178390503, 'Train/mean precision': 0.9891592264175415, 'Train/mean recall': 0.9982612729072571, 'Train/mean hd95_metric': 0.5472064018249512} +Epoch [3660/4000] Validation [1/4] Loss: 0.45253 focal_loss 0.38710 dice_loss 0.06544 +Epoch [3660/4000] Validation [2/4] Loss: 0.98026 focal_loss 0.79192 dice_loss 0.18834 +Epoch [3660/4000] Validation [3/4] Loss: 0.56508 focal_loss 0.46966 dice_loss 0.09542 +Epoch [3660/4000] Validation [4/4] Loss: 0.28816 focal_loss 0.20272 dice_loss 0.08544 +Epoch [3660/4000] Validation metric {'Val/mean dice_metric': 0.9737232327461243, 'Val/mean miou_metric': 0.9599437713623047, 'Val/mean f1': 0.9761291742324829, 'Val/mean precision': 0.9736599922180176, 'Val/mean recall': 0.9786110520362854, 'Val/mean hd95_metric': 5.230585098266602} +Cheakpoint... +Epoch [3660/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737232327461243, 'Val/mean miou_metric': 0.9599437713623047, 'Val/mean f1': 0.9761291742324829, 'Val/mean precision': 0.9736599922180176, 'Val/mean recall': 0.9786110520362854, 'Val/mean hd95_metric': 5.230585098266602} +Epoch [3661/4000] Training [1/16] Loss: 0.00195 +Epoch [3661/4000] Training [2/16] Loss: 0.00232 +Epoch [3661/4000] Training [3/16] Loss: 0.00208 +Epoch [3661/4000] Training [4/16] Loss: 0.00229 +Epoch [3661/4000] Training [5/16] Loss: 0.00164 +Epoch [3661/4000] Training [6/16] Loss: 0.00195 +Epoch [3661/4000] Training [7/16] Loss: 0.00234 +Epoch [3661/4000] Training [8/16] Loss: 0.00270 +Epoch [3661/4000] Training [9/16] Loss: 0.00278 +Epoch [3661/4000] Training [10/16] Loss: 0.00189 +Epoch [3661/4000] Training [11/16] Loss: 0.00408 +Epoch [3661/4000] Training [12/16] Loss: 0.00259 +Epoch [3661/4000] Training [13/16] Loss: 0.00206 +Epoch [3661/4000] Training [14/16] Loss: 0.00266 +Epoch [3661/4000] Training [15/16] Loss: 0.00196 +Epoch [3661/4000] Training [16/16] Loss: 0.00222 +Epoch [3661/4000] Training metric {'Train/mean dice_metric': 0.998805046081543, 'Train/mean miou_metric': 0.997327983379364, 'Train/mean f1': 0.9936643242835999, 'Train/mean precision': 0.9890275001525879, 'Train/mean recall': 0.9983449578285217, 'Train/mean hd95_metric': 0.5219025015830994} +Epoch [3661/4000] Validation [1/4] Loss: 0.48686 focal_loss 0.41998 dice_loss 0.06688 +Epoch [3661/4000] Validation [2/4] Loss: 0.50938 focal_loss 0.39691 dice_loss 0.11247 +Epoch [3661/4000] Validation [3/4] Loss: 0.52029 focal_loss 0.43091 dice_loss 0.08938 +Epoch [3661/4000] Validation [4/4] Loss: 0.35381 focal_loss 0.26549 dice_loss 0.08832 +Epoch [3661/4000] Validation metric {'Val/mean dice_metric': 0.9753105044364929, 'Val/mean miou_metric': 0.9614232182502747, 'Val/mean f1': 0.976642906665802, 'Val/mean precision': 0.9742629528045654, 'Val/mean recall': 0.9790345430374146, 'Val/mean hd95_metric': 4.6670732498168945} +Cheakpoint... +Epoch [3661/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753105044364929, 'Val/mean miou_metric': 0.9614232182502747, 'Val/mean f1': 0.976642906665802, 'Val/mean precision': 0.9742629528045654, 'Val/mean recall': 0.9790345430374146, 'Val/mean hd95_metric': 4.6670732498168945} +Epoch [3662/4000] Training [1/16] Loss: 0.00248 +Epoch [3662/4000] Training [2/16] Loss: 0.00248 +Epoch [3662/4000] Training [3/16] Loss: 0.00197 +Epoch [3662/4000] Training [4/16] Loss: 0.00365 +Epoch [3662/4000] Training [5/16] Loss: 0.00318 +Epoch [3662/4000] Training [6/16] Loss: 0.00330 +Epoch [3662/4000] Training [7/16] Loss: 0.00259 +Epoch [3662/4000] Training [8/16] Loss: 0.00244 +Epoch [3662/4000] Training [9/16] Loss: 0.00208 +Epoch [3662/4000] Training [10/16] Loss: 0.00228 +Epoch [3662/4000] Training [11/16] Loss: 0.00252 +Epoch [3662/4000] Training [12/16] Loss: 0.00430 +Epoch [3662/4000] Training [13/16] Loss: 0.00271 +Epoch [3662/4000] Training [14/16] Loss: 0.00311 +Epoch [3662/4000] Training [15/16] Loss: 0.00292 +Epoch [3662/4000] Training [16/16] Loss: 0.00254 +Epoch [3662/4000] Training metric {'Train/mean dice_metric': 0.9985312819480896, 'Train/mean miou_metric': 0.9967606067657471, 'Train/mean f1': 0.9928154945373535, 'Train/mean precision': 0.9876075387001038, 'Train/mean recall': 0.9980785846710205, 'Train/mean hd95_metric': 0.5823374390602112} +Epoch [3662/4000] Validation [1/4] Loss: 0.36187 focal_loss 0.30002 dice_loss 0.06185 +Epoch [3662/4000] Validation [2/4] Loss: 0.95534 focal_loss 0.74387 dice_loss 0.21147 +Epoch [3662/4000] Validation [3/4] Loss: 0.53880 focal_loss 0.44458 dice_loss 0.09422 +Epoch [3662/4000] Validation [4/4] Loss: 0.35570 focal_loss 0.26429 dice_loss 0.09140 +Epoch [3662/4000] Validation metric {'Val/mean dice_metric': 0.9736087918281555, 'Val/mean miou_metric': 0.9592523574829102, 'Val/mean f1': 0.9753068089485168, 'Val/mean precision': 0.9726723432540894, 'Val/mean recall': 0.9779555797576904, 'Val/mean hd95_metric': 5.117001056671143} +Cheakpoint... +Epoch [3662/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736087918281555, 'Val/mean miou_metric': 0.9592523574829102, 'Val/mean f1': 0.9753068089485168, 'Val/mean precision': 0.9726723432540894, 'Val/mean recall': 0.9779555797576904, 'Val/mean hd95_metric': 5.117001056671143} +Epoch [3663/4000] Training [1/16] Loss: 0.00261 +Epoch [3663/4000] Training [2/16] Loss: 0.00185 +Epoch [3663/4000] Training [3/16] Loss: 0.00296 +Epoch [3663/4000] Training [4/16] Loss: 0.00156 +Epoch [3663/4000] Training [5/16] Loss: 0.00157 +Epoch [3663/4000] Training [6/16] Loss: 0.00313 +Epoch [3663/4000] Training [7/16] Loss: 0.00310 +Epoch [3663/4000] Training [8/16] Loss: 0.00192 +Epoch [3663/4000] Training [9/16] Loss: 0.00233 +Epoch [3663/4000] Training [10/16] Loss: 0.00187 +Epoch [3663/4000] Training [11/16] Loss: 0.00172 +Epoch [3663/4000] Training [12/16] Loss: 0.00210 +Epoch [3663/4000] Training [13/16] Loss: 0.00166 +Epoch [3663/4000] Training [14/16] Loss: 0.00377 +Epoch [3663/4000] Training [15/16] Loss: 0.00263 +Epoch [3663/4000] Training [16/16] Loss: 0.00186 +Epoch [3663/4000] Training metric {'Train/mean dice_metric': 0.9987934827804565, 'Train/mean miou_metric': 0.997314989566803, 'Train/mean f1': 0.9939051270484924, 'Train/mean precision': 0.9893829822540283, 'Train/mean recall': 0.9984687566757202, 'Train/mean hd95_metric': 0.5302034020423889} +Epoch [3663/4000] Validation [1/4] Loss: 0.39408 focal_loss 0.33239 dice_loss 0.06170 +Epoch [3663/4000] Validation [2/4] Loss: 0.53168 focal_loss 0.40485 dice_loss 0.12683 +Epoch [3663/4000] Validation [3/4] Loss: 0.26684 focal_loss 0.20803 dice_loss 0.05882 +Epoch [3663/4000] Validation [4/4] Loss: 0.32779 focal_loss 0.23680 dice_loss 0.09099 +Epoch [3663/4000] Validation metric {'Val/mean dice_metric': 0.9745771288871765, 'Val/mean miou_metric': 0.9608963131904602, 'Val/mean f1': 0.976847767829895, 'Val/mean precision': 0.9752364158630371, 'Val/mean recall': 0.9784645438194275, 'Val/mean hd95_metric': 4.900786399841309} +Cheakpoint... +Epoch [3663/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745771288871765, 'Val/mean miou_metric': 0.9608963131904602, 'Val/mean f1': 0.976847767829895, 'Val/mean precision': 0.9752364158630371, 'Val/mean recall': 0.9784645438194275, 'Val/mean hd95_metric': 4.900786399841309} +Epoch [3664/4000] Training [1/16] Loss: 0.00290 +Epoch [3664/4000] Training [2/16] Loss: 0.00196 +Epoch [3664/4000] Training [3/16] Loss: 0.00247 +Epoch [3664/4000] Training [4/16] Loss: 0.00317 +Epoch [3664/4000] Training [5/16] Loss: 0.00270 +Epoch [3664/4000] Training [6/16] Loss: 0.00192 +Epoch [3664/4000] Training [7/16] Loss: 0.00212 +Epoch [3664/4000] Training [8/16] Loss: 0.00278 +Epoch [3664/4000] Training [9/16] Loss: 0.00347 +Epoch [3664/4000] Training [10/16] Loss: 0.00302 +Epoch [3664/4000] Training [11/16] Loss: 0.00457 +Epoch [3664/4000] Training [12/16] Loss: 0.00291 +Epoch [3664/4000] Training [13/16] Loss: 0.00162 +Epoch [3664/4000] Training [14/16] Loss: 0.00278 +Epoch [3664/4000] Training [15/16] Loss: 0.00185 +Epoch [3664/4000] Training [16/16] Loss: 0.00184 +Epoch [3664/4000] Training metric {'Train/mean dice_metric': 0.9987045526504517, 'Train/mean miou_metric': 0.9971222281455994, 'Train/mean f1': 0.9936402440071106, 'Train/mean precision': 0.9890127778053284, 'Train/mean recall': 0.9983111619949341, 'Train/mean hd95_metric': 0.5433171391487122} +Epoch [3664/4000] Validation [1/4] Loss: 0.38682 focal_loss 0.32472 dice_loss 0.06210 +Epoch [3664/4000] Validation [2/4] Loss: 0.96289 focal_loss 0.74995 dice_loss 0.21294 +Epoch [3664/4000] Validation [3/4] Loss: 0.53354 focal_loss 0.44281 dice_loss 0.09073 +Epoch [3664/4000] Validation [4/4] Loss: 0.33049 focal_loss 0.24418 dice_loss 0.08630 +Epoch [3664/4000] Validation metric {'Val/mean dice_metric': 0.974089503288269, 'Val/mean miou_metric': 0.9602155685424805, 'Val/mean f1': 0.9760900139808655, 'Val/mean precision': 0.9738670587539673, 'Val/mean recall': 0.9783231616020203, 'Val/mean hd95_metric': 4.773723125457764} +Cheakpoint... +Epoch [3664/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974089503288269, 'Val/mean miou_metric': 0.9602155685424805, 'Val/mean f1': 0.9760900139808655, 'Val/mean precision': 0.9738670587539673, 'Val/mean recall': 0.9783231616020203, 'Val/mean hd95_metric': 4.773723125457764} +Epoch [3665/4000] Training [1/16] Loss: 0.00201 +Epoch [3665/4000] Training [2/16] Loss: 0.00254 +Epoch [3665/4000] Training [3/16] Loss: 0.00350 +Epoch [3665/4000] Training [4/16] Loss: 0.00207 +Epoch [3665/4000] Training [5/16] Loss: 0.00370 +Epoch [3665/4000] Training [6/16] Loss: 0.00183 +Epoch [3665/4000] Training [7/16] Loss: 0.00232 +Epoch [3665/4000] Training [8/16] Loss: 0.00187 +Epoch [3665/4000] Training [9/16] Loss: 0.00356 +Epoch [3665/4000] Training [10/16] Loss: 0.00198 +Epoch [3665/4000] Training [11/16] Loss: 0.00209 +Epoch [3665/4000] Training [12/16] Loss: 0.00391 +Epoch [3665/4000] Training [13/16] Loss: 0.00170 +Epoch [3665/4000] Training [14/16] Loss: 0.00242 +Epoch [3665/4000] Training [15/16] Loss: 0.00265 +Epoch [3665/4000] Training [16/16] Loss: 0.00418 +Epoch [3665/4000] Training metric {'Train/mean dice_metric': 0.9987361431121826, 'Train/mean miou_metric': 0.9971986413002014, 'Train/mean f1': 0.9936979413032532, 'Train/mean precision': 0.9891669750213623, 'Train/mean recall': 0.998270571231842, 'Train/mean hd95_metric': 0.5426335334777832} +Epoch [3665/4000] Validation [1/4] Loss: 0.45905 focal_loss 0.38273 dice_loss 0.07632 +Epoch [3665/4000] Validation [2/4] Loss: 0.47561 focal_loss 0.36494 dice_loss 0.11067 +Epoch [3665/4000] Validation [3/4] Loss: 0.57243 focal_loss 0.47740 dice_loss 0.09503 +Epoch [3665/4000] Validation [4/4] Loss: 0.31239 focal_loss 0.22556 dice_loss 0.08683 +Epoch [3665/4000] Validation metric {'Val/mean dice_metric': 0.9744974970817566, 'Val/mean miou_metric': 0.9603534936904907, 'Val/mean f1': 0.9760454297065735, 'Val/mean precision': 0.9731267690658569, 'Val/mean recall': 0.9789817929267883, 'Val/mean hd95_metric': 5.193137168884277} +Cheakpoint... +Epoch [3665/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744974970817566, 'Val/mean miou_metric': 0.9603534936904907, 'Val/mean f1': 0.9760454297065735, 'Val/mean precision': 0.9731267690658569, 'Val/mean recall': 0.9789817929267883, 'Val/mean hd95_metric': 5.193137168884277} +Epoch [3666/4000] Training [1/16] Loss: 0.00254 +Epoch [3666/4000] Training [2/16] Loss: 0.00279 +Epoch [3666/4000] Training [3/16] Loss: 0.00126 +Epoch [3666/4000] Training [4/16] Loss: 0.00224 +Epoch [3666/4000] Training [5/16] Loss: 0.00213 +Epoch [3666/4000] Training [6/16] Loss: 0.00375 +Epoch [3666/4000] Training [7/16] Loss: 0.00300 +Epoch [3666/4000] Training [8/16] Loss: 0.00185 +Epoch [3666/4000] Training [9/16] Loss: 0.00173 +Epoch [3666/4000] Training [10/16] Loss: 0.00474 +Epoch [3666/4000] Training [11/16] Loss: 0.00171 +Epoch [3666/4000] Training [12/16] Loss: 0.00202 +Epoch [3666/4000] Training [13/16] Loss: 0.00156 +Epoch [3666/4000] Training [14/16] Loss: 0.00208 +Epoch [3666/4000] Training [15/16] Loss: 0.00273 +Epoch [3666/4000] Training [16/16] Loss: 0.00240 +Epoch [3666/4000] Training metric {'Train/mean dice_metric': 0.9988275170326233, 'Train/mean miou_metric': 0.9973698854446411, 'Train/mean f1': 0.9936513304710388, 'Train/mean precision': 0.9889235496520996, 'Train/mean recall': 0.9984245896339417, 'Train/mean hd95_metric': 0.501980721950531} +Epoch [3666/4000] Validation [1/4] Loss: 0.34698 focal_loss 0.29012 dice_loss 0.05686 +Epoch [3666/4000] Validation [2/4] Loss: 1.02343 focal_loss 0.81355 dice_loss 0.20988 +Epoch [3666/4000] Validation [3/4] Loss: 0.53485 focal_loss 0.44596 dice_loss 0.08890 +Epoch [3666/4000] Validation [4/4] Loss: 0.43593 focal_loss 0.32414 dice_loss 0.11178 +Epoch [3666/4000] Validation metric {'Val/mean dice_metric': 0.9726667404174805, 'Val/mean miou_metric': 0.9589704275131226, 'Val/mean f1': 0.9758130311965942, 'Val/mean precision': 0.9734575748443604, 'Val/mean recall': 0.9781798720359802, 'Val/mean hd95_metric': 5.128820419311523} +Cheakpoint... +Epoch [3666/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726667404174805, 'Val/mean miou_metric': 0.9589704275131226, 'Val/mean f1': 0.9758130311965942, 'Val/mean precision': 0.9734575748443604, 'Val/mean recall': 0.9781798720359802, 'Val/mean hd95_metric': 5.128820419311523} +Epoch [3667/4000] Training [1/16] Loss: 0.00417 +Epoch [3667/4000] Training [2/16] Loss: 0.00162 +Epoch [3667/4000] Training [3/16] Loss: 0.00250 +Epoch [3667/4000] Training [4/16] Loss: 0.00229 +Epoch [3667/4000] Training [5/16] Loss: 0.00165 +Epoch [3667/4000] Training [6/16] Loss: 0.00211 +Epoch [3667/4000] Training [7/16] Loss: 0.00218 +Epoch [3667/4000] Training [8/16] Loss: 0.00223 +Epoch [3667/4000] Training [9/16] Loss: 0.00328 +Epoch [3667/4000] Training [10/16] Loss: 0.00183 +Epoch [3667/4000] Training [11/16] Loss: 0.00271 +Epoch [3667/4000] Training [12/16] Loss: 0.00215 +Epoch [3667/4000] Training [13/16] Loss: 0.00200 +Epoch [3667/4000] Training [14/16] Loss: 0.00223 +Epoch [3667/4000] Training [15/16] Loss: 0.00159 +Epoch [3667/4000] Training [16/16] Loss: 0.00283 +Epoch [3667/4000] Training metric {'Train/mean dice_metric': 0.9988850951194763, 'Train/mean miou_metric': 0.9974411129951477, 'Train/mean f1': 0.992717444896698, 'Train/mean precision': 0.9871428608894348, 'Train/mean recall': 0.9983553290367126, 'Train/mean hd95_metric': 0.5160012245178223} +Epoch [3667/4000] Validation [1/4] Loss: 0.39348 focal_loss 0.32853 dice_loss 0.06496 +Epoch [3667/4000] Validation [2/4] Loss: 0.97198 focal_loss 0.78438 dice_loss 0.18760 +Epoch [3667/4000] Validation [3/4] Loss: 0.55746 focal_loss 0.45885 dice_loss 0.09861 +Epoch [3667/4000] Validation [4/4] Loss: 0.37912 focal_loss 0.26849 dice_loss 0.11063 +Epoch [3667/4000] Validation metric {'Val/mean dice_metric': 0.973678469657898, 'Val/mean miou_metric': 0.9597071409225464, 'Val/mean f1': 0.9755104780197144, 'Val/mean precision': 0.972510039806366, 'Val/mean recall': 0.9785294532775879, 'Val/mean hd95_metric': 5.152710437774658} +Cheakpoint... +Epoch [3667/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973678469657898, 'Val/mean miou_metric': 0.9597071409225464, 'Val/mean f1': 0.9755104780197144, 'Val/mean precision': 0.972510039806366, 'Val/mean recall': 0.9785294532775879, 'Val/mean hd95_metric': 5.152710437774658} +Epoch [3668/4000] Training [1/16] Loss: 0.00279 +Epoch [3668/4000] Training [2/16] Loss: 0.00212 +Epoch [3668/4000] Training [3/16] Loss: 0.00158 +Epoch [3668/4000] Training [4/16] Loss: 0.00389 +Epoch [3668/4000] Training [5/16] Loss: 0.00183 +Epoch [3668/4000] Training [6/16] Loss: 0.00239 +Epoch [3668/4000] Training [7/16] Loss: 0.00267 +Epoch [3668/4000] Training [8/16] Loss: 0.00244 +Epoch [3668/4000] Training [9/16] Loss: 0.00314 +Epoch [3668/4000] Training [10/16] Loss: 0.00193 +Epoch [3668/4000] Training [11/16] Loss: 0.00281 +Epoch [3668/4000] Training [12/16] Loss: 0.00250 +Epoch [3668/4000] Training [13/16] Loss: 0.00224 +Epoch [3668/4000] Training [14/16] Loss: 0.00308 +Epoch [3668/4000] Training [15/16] Loss: 0.00266 +Epoch [3668/4000] Training [16/16] Loss: 0.00200 +Epoch [3668/4000] Training metric {'Train/mean dice_metric': 0.998764157295227, 'Train/mean miou_metric': 0.9972517490386963, 'Train/mean f1': 0.9937352538108826, 'Train/mean precision': 0.9891681671142578, 'Train/mean recall': 0.9983446598052979, 'Train/mean hd95_metric': 0.5638948082923889} +Epoch [3668/4000] Validation [1/4] Loss: 0.43992 focal_loss 0.37657 dice_loss 0.06335 +Epoch [3668/4000] Validation [2/4] Loss: 0.48013 focal_loss 0.37104 dice_loss 0.10909 +Epoch [3668/4000] Validation [3/4] Loss: 0.54547 focal_loss 0.45121 dice_loss 0.09426 +Epoch [3668/4000] Validation [4/4] Loss: 0.47981 focal_loss 0.37013 dice_loss 0.10968 +Epoch [3668/4000] Validation metric {'Val/mean dice_metric': 0.9750787615776062, 'Val/mean miou_metric': 0.9609947204589844, 'Val/mean f1': 0.9766290783882141, 'Val/mean precision': 0.974370539188385, 'Val/mean recall': 0.9788982272148132, 'Val/mean hd95_metric': 4.58454704284668} +Cheakpoint... +Epoch [3668/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750787615776062, 'Val/mean miou_metric': 0.9609947204589844, 'Val/mean f1': 0.9766290783882141, 'Val/mean precision': 0.974370539188385, 'Val/mean recall': 0.9788982272148132, 'Val/mean hd95_metric': 4.58454704284668} +Epoch [3669/4000] Training [1/16] Loss: 0.00331 +Epoch [3669/4000] Training [2/16] Loss: 0.00246 +Epoch [3669/4000] Training [3/16] Loss: 0.00225 +Epoch [3669/4000] Training [4/16] Loss: 0.00212 +Epoch [3669/4000] Training [5/16] Loss: 0.00187 +Epoch [3669/4000] Training [6/16] Loss: 0.00226 +Epoch [3669/4000] Training [7/16] Loss: 0.00206 +Epoch [3669/4000] Training [8/16] Loss: 0.00202 +Epoch [3669/4000] Training [9/16] Loss: 0.00354 +Epoch [3669/4000] Training [10/16] Loss: 0.00229 +Epoch [3669/4000] Training [11/16] Loss: 0.00260 +Epoch [3669/4000] Training [12/16] Loss: 0.00280 +Epoch [3669/4000] Training [13/16] Loss: 0.00185 +Epoch [3669/4000] Training [14/16] Loss: 0.00184 +Epoch [3669/4000] Training [15/16] Loss: 0.00271 +Epoch [3669/4000] Training [16/16] Loss: 0.00172 +Epoch [3669/4000] Training metric {'Train/mean dice_metric': 0.9988077282905579, 'Train/mean miou_metric': 0.9973124861717224, 'Train/mean f1': 0.9932754039764404, 'Train/mean precision': 0.9882479310035706, 'Train/mean recall': 0.9983542561531067, 'Train/mean hd95_metric': 0.5371370315551758} +Epoch [3669/4000] Validation [1/4] Loss: 0.42732 focal_loss 0.36374 dice_loss 0.06358 +Epoch [3669/4000] Validation [2/4] Loss: 0.95535 focal_loss 0.74242 dice_loss 0.21293 +Epoch [3669/4000] Validation [3/4] Loss: 0.29004 focal_loss 0.22588 dice_loss 0.06416 +Epoch [3669/4000] Validation [4/4] Loss: 0.43660 focal_loss 0.32944 dice_loss 0.10716 +Epoch [3669/4000] Validation metric {'Val/mean dice_metric': 0.9734493494033813, 'Val/mean miou_metric': 0.9595541954040527, 'Val/mean f1': 0.9760279059410095, 'Val/mean precision': 0.97370445728302, 'Val/mean recall': 0.9783624410629272, 'Val/mean hd95_metric': 5.138789653778076} +Cheakpoint... +Epoch [3669/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734493494033813, 'Val/mean miou_metric': 0.9595541954040527, 'Val/mean f1': 0.9760279059410095, 'Val/mean precision': 0.97370445728302, 'Val/mean recall': 0.9783624410629272, 'Val/mean hd95_metric': 5.138789653778076} +Epoch [3670/4000] Training [1/16] Loss: 0.00234 +Epoch [3670/4000] Training [2/16] Loss: 0.00268 +Epoch [3670/4000] Training [3/16] Loss: 0.00224 +Epoch [3670/4000] Training [4/16] Loss: 0.00298 +Epoch [3670/4000] Training [5/16] Loss: 0.00199 +Epoch [3670/4000] Training [6/16] Loss: 0.00259 +Epoch [3670/4000] Training [7/16] Loss: 0.00257 +Epoch [3670/4000] Training [8/16] Loss: 0.00320 +Epoch [3670/4000] Training [9/16] Loss: 0.00192 +Epoch [3670/4000] Training [10/16] Loss: 0.00183 +Epoch [3670/4000] Training [11/16] Loss: 0.00200 +Epoch [3670/4000] Training [12/16] Loss: 0.00239 +Epoch [3670/4000] Training [13/16] Loss: 0.00221 +Epoch [3670/4000] Training [14/16] Loss: 0.00362 +Epoch [3670/4000] Training [15/16] Loss: 0.00215 +Epoch [3670/4000] Training [16/16] Loss: 0.00208 +Epoch [3670/4000] Training metric {'Train/mean dice_metric': 0.9987620115280151, 'Train/mean miou_metric': 0.9972519874572754, 'Train/mean f1': 0.9938297271728516, 'Train/mean precision': 0.9893465638160706, 'Train/mean recall': 0.9983536601066589, 'Train/mean hd95_metric': 0.5366214513778687} +Epoch [3670/4000] Validation [1/4] Loss: 0.37829 focal_loss 0.31540 dice_loss 0.06289 +Epoch [3670/4000] Validation [2/4] Loss: 0.60227 focal_loss 0.43923 dice_loss 0.16304 +Epoch [3670/4000] Validation [3/4] Loss: 0.54337 focal_loss 0.44857 dice_loss 0.09480 +Epoch [3670/4000] Validation [4/4] Loss: 0.34794 focal_loss 0.25912 dice_loss 0.08882 +Epoch [3670/4000] Validation metric {'Val/mean dice_metric': 0.9745052456855774, 'Val/mean miou_metric': 0.9604485630989075, 'Val/mean f1': 0.9765699505805969, 'Val/mean precision': 0.9742340445518494, 'Val/mean recall': 0.9789170026779175, 'Val/mean hd95_metric': 4.745837211608887} +Cheakpoint... +Epoch [3670/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745052456855774, 'Val/mean miou_metric': 0.9604485630989075, 'Val/mean f1': 0.9765699505805969, 'Val/mean precision': 0.9742340445518494, 'Val/mean recall': 0.9789170026779175, 'Val/mean hd95_metric': 4.745837211608887} +Epoch [3671/4000] Training [1/16] Loss: 0.00165 +Epoch [3671/4000] Training [2/16] Loss: 0.00243 +Epoch [3671/4000] Training [3/16] Loss: 0.00220 +Epoch [3671/4000] Training [4/16] Loss: 0.00205 +Epoch [3671/4000] Training [5/16] Loss: 0.00332 +Epoch [3671/4000] Training [6/16] Loss: 0.00206 +Epoch [3671/4000] Training [7/16] Loss: 0.00255 +Epoch [3671/4000] Training [8/16] Loss: 0.00256 +Epoch [3671/4000] Training [9/16] Loss: 0.00373 +Epoch [3671/4000] Training [10/16] Loss: 0.00170 +Epoch [3671/4000] Training [11/16] Loss: 0.00256 +Epoch [3671/4000] Training [12/16] Loss: 0.00205 +Epoch [3671/4000] Training [13/16] Loss: 0.00298 +Epoch [3671/4000] Training [14/16] Loss: 0.00342 +Epoch [3671/4000] Training [15/16] Loss: 0.00219 +Epoch [3671/4000] Training [16/16] Loss: 0.00280 +Epoch [3671/4000] Training metric {'Train/mean dice_metric': 0.9987894296646118, 'Train/mean miou_metric': 0.9972970485687256, 'Train/mean f1': 0.9937009215354919, 'Train/mean precision': 0.9890508651733398, 'Train/mean recall': 0.9983949661254883, 'Train/mean hd95_metric': 0.5387469530105591} +Epoch [3671/4000] Validation [1/4] Loss: 0.46993 focal_loss 0.40710 dice_loss 0.06282 +Epoch [3671/4000] Validation [2/4] Loss: 0.50858 focal_loss 0.39335 dice_loss 0.11523 +Epoch [3671/4000] Validation [3/4] Loss: 0.54144 focal_loss 0.45079 dice_loss 0.09065 +Epoch [3671/4000] Validation [4/4] Loss: 0.31710 focal_loss 0.21983 dice_loss 0.09727 +Epoch [3671/4000] Validation metric {'Val/mean dice_metric': 0.9764137268066406, 'Val/mean miou_metric': 0.9622983932495117, 'Val/mean f1': 0.9768045544624329, 'Val/mean precision': 0.9739353060722351, 'Val/mean recall': 0.9796908497810364, 'Val/mean hd95_metric': 4.73822021484375} +Cheakpoint... +Epoch [3671/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9764], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9764137268066406, 'Val/mean miou_metric': 0.9622983932495117, 'Val/mean f1': 0.9768045544624329, 'Val/mean precision': 0.9739353060722351, 'Val/mean recall': 0.9796908497810364, 'Val/mean hd95_metric': 4.73822021484375} +Epoch [3672/4000] Training [1/16] Loss: 0.00221 +Epoch [3672/4000] Training [2/16] Loss: 0.00242 +Epoch [3672/4000] Training [3/16] Loss: 0.00281 +Epoch [3672/4000] Training [4/16] Loss: 0.00308 +Epoch [3672/4000] Training [5/16] Loss: 0.00326 +Epoch [3672/4000] Training [6/16] Loss: 0.00191 +Epoch [3672/4000] Training [7/16] Loss: 0.00262 +Epoch [3672/4000] Training [8/16] Loss: 0.00289 +Epoch [3672/4000] Training [9/16] Loss: 0.00230 +Epoch [3672/4000] Training [10/16] Loss: 0.00176 +Epoch [3672/4000] Training [11/16] Loss: 0.00178 +Epoch [3672/4000] Training [12/16] Loss: 0.00207 +Epoch [3672/4000] Training [13/16] Loss: 0.00197 +Epoch [3672/4000] Training [14/16] Loss: 0.00176 +Epoch [3672/4000] Training [15/16] Loss: 0.00322 +Epoch [3672/4000] Training [16/16] Loss: 0.00257 +Epoch [3672/4000] Training metric {'Train/mean dice_metric': 0.9988881349563599, 'Train/mean miou_metric': 0.9974900484085083, 'Train/mean f1': 0.993608295917511, 'Train/mean precision': 0.9888444542884827, 'Train/mean recall': 0.9984182715415955, 'Train/mean hd95_metric': 0.540847897529602} +Epoch [3672/4000] Validation [1/4] Loss: 0.40931 focal_loss 0.34666 dice_loss 0.06265 +Epoch [3672/4000] Validation [2/4] Loss: 0.92196 focal_loss 0.71916 dice_loss 0.20280 +Epoch [3672/4000] Validation [3/4] Loss: 0.52333 focal_loss 0.43260 dice_loss 0.09073 +Epoch [3672/4000] Validation [4/4] Loss: 0.44687 focal_loss 0.34131 dice_loss 0.10557 +Epoch [3672/4000] Validation metric {'Val/mean dice_metric': 0.9734021425247192, 'Val/mean miou_metric': 0.9598625302314758, 'Val/mean f1': 0.975770115852356, 'Val/mean precision': 0.9732712507247925, 'Val/mean recall': 0.9782819151878357, 'Val/mean hd95_metric': 5.182919979095459} +Cheakpoint... +Epoch [3672/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734021425247192, 'Val/mean miou_metric': 0.9598625302314758, 'Val/mean f1': 0.975770115852356, 'Val/mean precision': 0.9732712507247925, 'Val/mean recall': 0.9782819151878357, 'Val/mean hd95_metric': 5.182919979095459} +Epoch [3673/4000] Training [1/16] Loss: 0.00300 +Epoch [3673/4000] Training [2/16] Loss: 0.00156 +Epoch [3673/4000] Training [3/16] Loss: 0.00278 +Epoch [3673/4000] Training [4/16] Loss: 0.00217 +Epoch [3673/4000] Training [5/16] Loss: 0.00334 +Epoch [3673/4000] Training [6/16] Loss: 0.00237 +Epoch [3673/4000] Training [7/16] Loss: 0.00214 +Epoch [3673/4000] Training [8/16] Loss: 0.00255 +Epoch [3673/4000] Training [9/16] Loss: 0.00271 +Epoch [3673/4000] Training [10/16] Loss: 0.00345 +Epoch [3673/4000] Training [11/16] Loss: 0.00510 +Epoch [3673/4000] Training [12/16] Loss: 0.00237 +Epoch [3673/4000] Training [13/16] Loss: 0.00207 +Epoch [3673/4000] Training [14/16] Loss: 0.00227 +Epoch [3673/4000] Training [15/16] Loss: 0.00279 +Epoch [3673/4000] Training [16/16] Loss: 0.00276 +Epoch [3673/4000] Training metric {'Train/mean dice_metric': 0.9986944198608398, 'Train/mean miou_metric': 0.9970631003379822, 'Train/mean f1': 0.9925934672355652, 'Train/mean precision': 0.9870687127113342, 'Train/mean recall': 0.9981803894042969, 'Train/mean hd95_metric': 0.5380910634994507} +Epoch [3673/4000] Validation [1/4] Loss: 0.35561 focal_loss 0.29654 dice_loss 0.05907 +Epoch [3673/4000] Validation [2/4] Loss: 0.47896 focal_loss 0.36842 dice_loss 0.11054 +Epoch [3673/4000] Validation [3/4] Loss: 0.54736 focal_loss 0.45009 dice_loss 0.09727 +Epoch [3673/4000] Validation [4/4] Loss: 0.35590 focal_loss 0.27001 dice_loss 0.08589 +Epoch [3673/4000] Validation metric {'Val/mean dice_metric': 0.9748061895370483, 'Val/mean miou_metric': 0.960726261138916, 'Val/mean f1': 0.9757934808731079, 'Val/mean precision': 0.9726429581642151, 'Val/mean recall': 0.9789644479751587, 'Val/mean hd95_metric': 4.781993865966797} +Cheakpoint... +Epoch [3673/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748061895370483, 'Val/mean miou_metric': 0.960726261138916, 'Val/mean f1': 0.9757934808731079, 'Val/mean precision': 0.9726429581642151, 'Val/mean recall': 0.9789644479751587, 'Val/mean hd95_metric': 4.781993865966797} +Epoch [3674/4000] Training [1/16] Loss: 0.00280 +Epoch [3674/4000] Training [2/16] Loss: 0.00260 +Epoch [3674/4000] Training [3/16] Loss: 0.00194 +Epoch [3674/4000] Training [4/16] Loss: 0.00262 +Epoch [3674/4000] Training [5/16] Loss: 0.00256 +Epoch [3674/4000] Training [6/16] Loss: 0.00323 +Epoch [3674/4000] Training [7/16] Loss: 0.00216 +Epoch [3674/4000] Training [8/16] Loss: 0.00176 +Epoch [3674/4000] Training [9/16] Loss: 0.00184 +Epoch [3674/4000] Training [10/16] Loss: 0.00293 +Epoch [3674/4000] Training [11/16] Loss: 0.00274 +Epoch [3674/4000] Training [12/16] Loss: 0.00196 +Epoch [3674/4000] Training [13/16] Loss: 0.00177 +Epoch [3674/4000] Training [14/16] Loss: 0.00238 +Epoch [3674/4000] Training [15/16] Loss: 0.00298 +Epoch [3674/4000] Training [16/16] Loss: 0.00182 +Epoch [3674/4000] Training metric {'Train/mean dice_metric': 0.9989002346992493, 'Train/mean miou_metric': 0.9975153207778931, 'Train/mean f1': 0.9937775135040283, 'Train/mean precision': 0.9891321063041687, 'Train/mean recall': 0.9984667301177979, 'Train/mean hd95_metric': 0.5084527730941772} +Epoch [3674/4000] Validation [1/4] Loss: 0.44909 focal_loss 0.38181 dice_loss 0.06728 +Epoch [3674/4000] Validation [2/4] Loss: 0.58160 focal_loss 0.43183 dice_loss 0.14977 +Epoch [3674/4000] Validation [3/4] Loss: 0.28543 focal_loss 0.22203 dice_loss 0.06341 +Epoch [3674/4000] Validation [4/4] Loss: 0.39829 focal_loss 0.29465 dice_loss 0.10364 +Epoch [3674/4000] Validation metric {'Val/mean dice_metric': 0.9735029339790344, 'Val/mean miou_metric': 0.9597903490066528, 'Val/mean f1': 0.9760434031486511, 'Val/mean precision': 0.9747771620750427, 'Val/mean recall': 0.9773128628730774, 'Val/mean hd95_metric': 4.762503147125244} +Cheakpoint... +Epoch [3674/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735029339790344, 'Val/mean miou_metric': 0.9597903490066528, 'Val/mean f1': 0.9760434031486511, 'Val/mean precision': 0.9747771620750427, 'Val/mean recall': 0.9773128628730774, 'Val/mean hd95_metric': 4.762503147125244} +Epoch [3675/4000] Training [1/16] Loss: 0.00216 +Epoch [3675/4000] Training [2/16] Loss: 0.00218 +Epoch [3675/4000] Training [3/16] Loss: 0.00412 +Epoch [3675/4000] Training [4/16] Loss: 0.00366 +Epoch [3675/4000] Training [5/16] Loss: 0.00262 +Epoch [3675/4000] Training [6/16] Loss: 0.00335 +Epoch [3675/4000] Training [7/16] Loss: 0.00178 +Epoch [3675/4000] Training [8/16] Loss: 0.00248 +Epoch [3675/4000] Training [9/16] Loss: 0.00205 +Epoch [3675/4000] Training [10/16] Loss: 0.00372 +Epoch [3675/4000] Training [11/16] Loss: 0.00252 +Epoch [3675/4000] Training [12/16] Loss: 0.00371 +Epoch [3675/4000] Training [13/16] Loss: 0.00216 +Epoch [3675/4000] Training [14/16] Loss: 0.00262 +Epoch [3675/4000] Training [15/16] Loss: 0.00168 +Epoch [3675/4000] Training [16/16] Loss: 0.00163 +Epoch [3675/4000] Training metric {'Train/mean dice_metric': 0.998735785484314, 'Train/mean miou_metric': 0.9971503019332886, 'Train/mean f1': 0.9929377436637878, 'Train/mean precision': 0.9876600503921509, 'Train/mean recall': 0.9982721209526062, 'Train/mean hd95_metric': 0.6062637567520142} +Epoch [3675/4000] Validation [1/4] Loss: 0.39012 focal_loss 0.32728 dice_loss 0.06284 +Epoch [3675/4000] Validation [2/4] Loss: 0.64520 focal_loss 0.47716 dice_loss 0.16804 +Epoch [3675/4000] Validation [3/4] Loss: 0.56831 focal_loss 0.46992 dice_loss 0.09839 +Epoch [3675/4000] Validation [4/4] Loss: 0.29053 focal_loss 0.20789 dice_loss 0.08264 +Epoch [3675/4000] Validation metric {'Val/mean dice_metric': 0.9727495312690735, 'Val/mean miou_metric': 0.9589183926582336, 'Val/mean f1': 0.9755135774612427, 'Val/mean precision': 0.9732987284660339, 'Val/mean recall': 0.9777385592460632, 'Val/mean hd95_metric': 4.98827600479126} +Cheakpoint... +Epoch [3675/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727495312690735, 'Val/mean miou_metric': 0.9589183926582336, 'Val/mean f1': 0.9755135774612427, 'Val/mean precision': 0.9732987284660339, 'Val/mean recall': 0.9777385592460632, 'Val/mean hd95_metric': 4.98827600479126} +Epoch [3676/4000] Training [1/16] Loss: 0.00227 +Epoch [3676/4000] Training [2/16] Loss: 0.00194 +Epoch [3676/4000] Training [3/16] Loss: 0.00310 +Epoch [3676/4000] Training [4/16] Loss: 0.00220 +Epoch [3676/4000] Training [5/16] Loss: 0.00293 +Epoch [3676/4000] Training [6/16] Loss: 0.00187 +Epoch [3676/4000] Training [7/16] Loss: 0.00401 +Epoch [3676/4000] Training [8/16] Loss: 0.00307 +Epoch [3676/4000] Training [9/16] Loss: 0.00276 +Epoch [3676/4000] Training [10/16] Loss: 0.00271 +Epoch [3676/4000] Training [11/16] Loss: 0.00332 +Epoch [3676/4000] Training [12/16] Loss: 0.00186 +Epoch [3676/4000] Training [13/16] Loss: 0.00199 +Epoch [3676/4000] Training [14/16] Loss: 0.00178 +Epoch [3676/4000] Training [15/16] Loss: 0.00170 +Epoch [3676/4000] Training [16/16] Loss: 0.00245 +Epoch [3676/4000] Training metric {'Train/mean dice_metric': 0.9987295269966125, 'Train/mean miou_metric': 0.9971871376037598, 'Train/mean f1': 0.9937878251075745, 'Train/mean precision': 0.9892812371253967, 'Train/mean recall': 0.9983357191085815, 'Train/mean hd95_metric': 0.55784010887146} +Epoch [3676/4000] Validation [1/4] Loss: 0.40011 focal_loss 0.33390 dice_loss 0.06621 +Epoch [3676/4000] Validation [2/4] Loss: 0.53057 focal_loss 0.40773 dice_loss 0.12284 +Epoch [3676/4000] Validation [3/4] Loss: 0.55099 focal_loss 0.45835 dice_loss 0.09264 +Epoch [3676/4000] Validation [4/4] Loss: 0.32277 focal_loss 0.23579 dice_loss 0.08698 +Epoch [3676/4000] Validation metric {'Val/mean dice_metric': 0.9742586016654968, 'Val/mean miou_metric': 0.9598371386528015, 'Val/mean f1': 0.9761232137680054, 'Val/mean precision': 0.9737498760223389, 'Val/mean recall': 0.9785081744194031, 'Val/mean hd95_metric': 5.030516624450684} +Cheakpoint... +Epoch [3676/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742586016654968, 'Val/mean miou_metric': 0.9598371386528015, 'Val/mean f1': 0.9761232137680054, 'Val/mean precision': 0.9737498760223389, 'Val/mean recall': 0.9785081744194031, 'Val/mean hd95_metric': 5.030516624450684} +Epoch [3677/4000] Training [1/16] Loss: 0.00284 +Epoch [3677/4000] Training [2/16] Loss: 0.00258 +Epoch [3677/4000] Training [3/16] Loss: 0.00221 +Epoch [3677/4000] Training [4/16] Loss: 0.00253 +Epoch [3677/4000] Training [5/16] Loss: 0.00194 +Epoch [3677/4000] Training [6/16] Loss: 0.00179 +Epoch [3677/4000] Training [7/16] Loss: 0.00239 +Epoch [3677/4000] Training [8/16] Loss: 0.00263 +Epoch [3677/4000] Training [9/16] Loss: 0.00265 +Epoch [3677/4000] Training [10/16] Loss: 0.00201 +Epoch [3677/4000] Training [11/16] Loss: 0.00172 +Epoch [3677/4000] Training [12/16] Loss: 0.00330 +Epoch [3677/4000] Training [13/16] Loss: 0.00180 +Epoch [3677/4000] Training [14/16] Loss: 0.00369 +Epoch [3677/4000] Training [15/16] Loss: 0.00192 +Epoch [3677/4000] Training [16/16] Loss: 0.00225 +Epoch [3677/4000] Training metric {'Train/mean dice_metric': 0.9986934661865234, 'Train/mean miou_metric': 0.9971059560775757, 'Train/mean f1': 0.99365234375, 'Train/mean precision': 0.9890016317367554, 'Train/mean recall': 0.9983471035957336, 'Train/mean hd95_metric': 0.5601837635040283} +Epoch [3677/4000] Validation [1/4] Loss: 0.38164 focal_loss 0.31969 dice_loss 0.06195 +Epoch [3677/4000] Validation [2/4] Loss: 0.49697 focal_loss 0.38527 dice_loss 0.11170 +Epoch [3677/4000] Validation [3/4] Loss: 0.50009 focal_loss 0.40490 dice_loss 0.09519 +Epoch [3677/4000] Validation [4/4] Loss: 0.32163 focal_loss 0.22959 dice_loss 0.09204 +Epoch [3677/4000] Validation metric {'Val/mean dice_metric': 0.9761091470718384, 'Val/mean miou_metric': 0.9616845846176147, 'Val/mean f1': 0.976630687713623, 'Val/mean precision': 0.9741118550300598, 'Val/mean recall': 0.9791627526283264, 'Val/mean hd95_metric': 4.390841484069824} +Cheakpoint... +Epoch [3677/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9761], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9761091470718384, 'Val/mean miou_metric': 0.9616845846176147, 'Val/mean f1': 0.976630687713623, 'Val/mean precision': 0.9741118550300598, 'Val/mean recall': 0.9791627526283264, 'Val/mean hd95_metric': 4.390841484069824} +Epoch [3678/4000] Training [1/16] Loss: 0.00155 +Epoch [3678/4000] Training [2/16] Loss: 0.00203 +Epoch [3678/4000] Training [3/16] Loss: 0.00159 +Epoch [3678/4000] Training [4/16] Loss: 0.00198 +Epoch [3678/4000] Training [5/16] Loss: 0.00244 +Epoch [3678/4000] Training [6/16] Loss: 0.00287 +Epoch [3678/4000] Training [7/16] Loss: 0.00222 +Epoch [3678/4000] Training [8/16] Loss: 0.00237 +Epoch [3678/4000] Training [9/16] Loss: 0.00257 +Epoch [3678/4000] Training [10/16] Loss: 0.00260 +Epoch [3678/4000] Training [11/16] Loss: 0.00256 +Epoch [3678/4000] Training [12/16] Loss: 0.00292 +Epoch [3678/4000] Training [13/16] Loss: 0.00211 +Epoch [3678/4000] Training [14/16] Loss: 0.00265 +Epoch [3678/4000] Training [15/16] Loss: 0.00297 +Epoch [3678/4000] Training [16/16] Loss: 0.00156 +Epoch [3678/4000] Training metric {'Train/mean dice_metric': 0.9988747239112854, 'Train/mean miou_metric': 0.9974735379219055, 'Train/mean f1': 0.9938775300979614, 'Train/mean precision': 0.9893590211868286, 'Train/mean recall': 0.9984374642372131, 'Train/mean hd95_metric': 0.5428011417388916} +Epoch [3678/4000] Validation [1/4] Loss: 0.36586 focal_loss 0.30129 dice_loss 0.06457 +Epoch [3678/4000] Validation [2/4] Loss: 0.52543 focal_loss 0.40191 dice_loss 0.12352 +Epoch [3678/4000] Validation [3/4] Loss: 0.54302 focal_loss 0.45016 dice_loss 0.09286 +Epoch [3678/4000] Validation [4/4] Loss: 0.33571 focal_loss 0.24214 dice_loss 0.09357 +Epoch [3678/4000] Validation metric {'Val/mean dice_metric': 0.9748563766479492, 'Val/mean miou_metric': 0.9604284167289734, 'Val/mean f1': 0.9763946533203125, 'Val/mean precision': 0.9745453000068665, 'Val/mean recall': 0.9782509207725525, 'Val/mean hd95_metric': 4.859851837158203} +Cheakpoint... +Epoch [3678/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748563766479492, 'Val/mean miou_metric': 0.9604284167289734, 'Val/mean f1': 0.9763946533203125, 'Val/mean precision': 0.9745453000068665, 'Val/mean recall': 0.9782509207725525, 'Val/mean hd95_metric': 4.859851837158203} +Epoch [3679/4000] Training [1/16] Loss: 0.00232 +Epoch [3679/4000] Training [2/16] Loss: 0.00215 +Epoch [3679/4000] Training [3/16] Loss: 0.00183 +Epoch [3679/4000] Training [4/16] Loss: 0.00227 +Epoch [3679/4000] Training [5/16] Loss: 0.00216 +Epoch [3679/4000] Training [6/16] Loss: 0.00220 +Epoch [3679/4000] Training [7/16] Loss: 0.00350 +Epoch [3679/4000] Training [8/16] Loss: 0.00218 +Epoch [3679/4000] Training [9/16] Loss: 0.00219 +Epoch [3679/4000] Training [10/16] Loss: 0.00178 +Epoch [3679/4000] Training [11/16] Loss: 0.00217 +Epoch [3679/4000] Training [12/16] Loss: 0.00171 +Epoch [3679/4000] Training [13/16] Loss: 0.00245 +Epoch [3679/4000] Training [14/16] Loss: 0.00272 +Epoch [3679/4000] Training [15/16] Loss: 0.00340 +Epoch [3679/4000] Training [16/16] Loss: 0.00179 +Epoch [3679/4000] Training metric {'Train/mean dice_metric': 0.9988237619400024, 'Train/mean miou_metric': 0.9973748326301575, 'Train/mean f1': 0.9939378499984741, 'Train/mean precision': 0.9894902110099792, 'Train/mean recall': 0.9984256029129028, 'Train/mean hd95_metric': 0.5495392084121704} +Epoch [3679/4000] Validation [1/4] Loss: 0.41629 focal_loss 0.34936 dice_loss 0.06694 +Epoch [3679/4000] Validation [2/4] Loss: 0.47394 focal_loss 0.36590 dice_loss 0.10805 +Epoch [3679/4000] Validation [3/4] Loss: 0.59736 focal_loss 0.49771 dice_loss 0.09966 +Epoch [3679/4000] Validation [4/4] Loss: 0.34583 focal_loss 0.26237 dice_loss 0.08347 +Epoch [3679/4000] Validation metric {'Val/mean dice_metric': 0.9748954772949219, 'Val/mean miou_metric': 0.960817813873291, 'Val/mean f1': 0.9766899943351746, 'Val/mean precision': 0.9747906923294067, 'Val/mean recall': 0.9785967469215393, 'Val/mean hd95_metric': 4.809428691864014} +Cheakpoint... +Epoch [3679/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748954772949219, 'Val/mean miou_metric': 0.960817813873291, 'Val/mean f1': 0.9766899943351746, 'Val/mean precision': 0.9747906923294067, 'Val/mean recall': 0.9785967469215393, 'Val/mean hd95_metric': 4.809428691864014} +Epoch [3680/4000] Training [1/16] Loss: 0.00234 +Epoch [3680/4000] Training [2/16] Loss: 0.00149 +Epoch [3680/4000] Training [3/16] Loss: 0.00169 +Epoch [3680/4000] Training [4/16] Loss: 0.00183 +Epoch [3680/4000] Training [5/16] Loss: 0.00251 +Epoch [3680/4000] Training [6/16] Loss: 0.00279 +Epoch [3680/4000] Training [7/16] Loss: 0.00264 +Epoch [3680/4000] Training [8/16] Loss: 0.00221 +Epoch [3680/4000] Training [9/16] Loss: 0.00263 +Epoch [3680/4000] Training [10/16] Loss: 0.00269 +Epoch [3680/4000] Training [11/16] Loss: 0.00163 +Epoch [3680/4000] Training [12/16] Loss: 0.00338 +Epoch [3680/4000] Training [13/16] Loss: 0.00251 +Epoch [3680/4000] Training [14/16] Loss: 0.00265 +Epoch [3680/4000] Training [15/16] Loss: 0.00297 +Epoch [3680/4000] Training [16/16] Loss: 0.00194 +Epoch [3680/4000] Training metric {'Train/mean dice_metric': 0.9988601207733154, 'Train/mean miou_metric': 0.9974414110183716, 'Train/mean f1': 0.9937483072280884, 'Train/mean precision': 0.9891331791877747, 'Train/mean recall': 0.998406708240509, 'Train/mean hd95_metric': 0.504910409450531} +Epoch [3680/4000] Validation [1/4] Loss: 0.42116 focal_loss 0.35823 dice_loss 0.06293 +Epoch [3680/4000] Validation [2/4] Loss: 1.37042 focal_loss 1.09645 dice_loss 0.27397 +Epoch [3680/4000] Validation [3/4] Loss: 0.53517 focal_loss 0.44288 dice_loss 0.09229 +Epoch [3680/4000] Validation [4/4] Loss: 0.43828 focal_loss 0.32894 dice_loss 0.10935 +Epoch [3680/4000] Validation metric {'Val/mean dice_metric': 0.9746600985527039, 'Val/mean miou_metric': 0.9605600237846375, 'Val/mean f1': 0.9760295152664185, 'Val/mean precision': 0.973373532295227, 'Val/mean recall': 0.9787000417709351, 'Val/mean hd95_metric': 4.8558349609375} +Cheakpoint... +Epoch [3680/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746600985527039, 'Val/mean miou_metric': 0.9605600237846375, 'Val/mean f1': 0.9760295152664185, 'Val/mean precision': 0.973373532295227, 'Val/mean recall': 0.9787000417709351, 'Val/mean hd95_metric': 4.8558349609375} +Epoch [3681/4000] Training [1/16] Loss: 0.00390 +Epoch [3681/4000] Training [2/16] Loss: 0.00239 +Epoch [3681/4000] Training [3/16] Loss: 0.00256 +Epoch [3681/4000] Training [4/16] Loss: 0.00202 +Epoch [3681/4000] Training [5/16] Loss: 0.00260 +Epoch [3681/4000] Training [6/16] Loss: 0.00455 +Epoch [3681/4000] Training [7/16] Loss: 0.00331 +Epoch [3681/4000] Training [8/16] Loss: 0.00180 +Epoch [3681/4000] Training [9/16] Loss: 0.00228 +Epoch [3681/4000] Training [10/16] Loss: 0.00196 +Epoch [3681/4000] Training [11/16] Loss: 0.00257 +Epoch [3681/4000] Training [12/16] Loss: 0.00209 +Epoch [3681/4000] Training [13/16] Loss: 0.00376 +Epoch [3681/4000] Training [14/16] Loss: 0.00247 +Epoch [3681/4000] Training [15/16] Loss: 0.00201 +Epoch [3681/4000] Training [16/16] Loss: 0.00302 +Epoch [3681/4000] Training metric {'Train/mean dice_metric': 0.9986674785614014, 'Train/mean miou_metric': 0.9970377087593079, 'Train/mean f1': 0.9931231737136841, 'Train/mean precision': 0.9880392551422119, 'Train/mean recall': 0.9982596635818481, 'Train/mean hd95_metric': 0.562457799911499} +Epoch [3681/4000] Validation [1/4] Loss: 0.42305 focal_loss 0.35856 dice_loss 0.06449 +Epoch [3681/4000] Validation [2/4] Loss: 1.08957 focal_loss 0.90479 dice_loss 0.18478 +Epoch [3681/4000] Validation [3/4] Loss: 0.52601 focal_loss 0.43143 dice_loss 0.09458 +Epoch [3681/4000] Validation [4/4] Loss: 0.34038 focal_loss 0.25616 dice_loss 0.08423 +Epoch [3681/4000] Validation metric {'Val/mean dice_metric': 0.9751859903335571, 'Val/mean miou_metric': 0.9611791372299194, 'Val/mean f1': 0.9759445190429688, 'Val/mean precision': 0.9728586673736572, 'Val/mean recall': 0.9790498614311218, 'Val/mean hd95_metric': 4.686783313751221} +Cheakpoint... +Epoch [3681/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751859903335571, 'Val/mean miou_metric': 0.9611791372299194, 'Val/mean f1': 0.9759445190429688, 'Val/mean precision': 0.9728586673736572, 'Val/mean recall': 0.9790498614311218, 'Val/mean hd95_metric': 4.686783313751221} +Epoch [3682/4000] Training [1/16] Loss: 0.00183 +Epoch [3682/4000] Training [2/16] Loss: 0.00246 +Epoch [3682/4000] Training [3/16] Loss: 0.00192 +Epoch [3682/4000] Training [4/16] Loss: 0.00253 +Epoch [3682/4000] Training [5/16] Loss: 0.00352 +Epoch [3682/4000] Training [6/16] Loss: 0.00215 +Epoch [3682/4000] Training [7/16] Loss: 0.00276 +Epoch [3682/4000] Training [8/16] Loss: 0.00293 +Epoch [3682/4000] Training [9/16] Loss: 0.00221 +Epoch [3682/4000] Training [10/16] Loss: 0.00232 +Epoch [3682/4000] Training [11/16] Loss: 0.00295 +Epoch [3682/4000] Training [12/16] Loss: 0.00256 +Epoch [3682/4000] Training [13/16] Loss: 0.00227 +Epoch [3682/4000] Training [14/16] Loss: 0.00177 +Epoch [3682/4000] Training [15/16] Loss: 0.00189 +Epoch [3682/4000] Training [16/16] Loss: 0.00231 +Epoch [3682/4000] Training metric {'Train/mean dice_metric': 0.998786449432373, 'Train/mean miou_metric': 0.9972989559173584, 'Train/mean f1': 0.9938892722129822, 'Train/mean precision': 0.9894092679023743, 'Train/mean recall': 0.9984101057052612, 'Train/mean hd95_metric': 0.5113556981086731} +Epoch [3682/4000] Validation [1/4] Loss: 0.38742 focal_loss 0.32234 dice_loss 0.06508 +Epoch [3682/4000] Validation [2/4] Loss: 0.85075 focal_loss 0.63547 dice_loss 0.21528 +Epoch [3682/4000] Validation [3/4] Loss: 0.30303 focal_loss 0.23922 dice_loss 0.06381 +Epoch [3682/4000] Validation [4/4] Loss: 0.46807 focal_loss 0.36107 dice_loss 0.10700 +Epoch [3682/4000] Validation metric {'Val/mean dice_metric': 0.9738492965698242, 'Val/mean miou_metric': 0.9594941139221191, 'Val/mean f1': 0.9761587381362915, 'Val/mean precision': 0.9747948050498962, 'Val/mean recall': 0.9775265455245972, 'Val/mean hd95_metric': 5.1655449867248535} +Cheakpoint... +Epoch [3682/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738492965698242, 'Val/mean miou_metric': 0.9594941139221191, 'Val/mean f1': 0.9761587381362915, 'Val/mean precision': 0.9747948050498962, 'Val/mean recall': 0.9775265455245972, 'Val/mean hd95_metric': 5.1655449867248535} +Epoch [3683/4000] Training [1/16] Loss: 0.00319 +Epoch [3683/4000] Training [2/16] Loss: 0.00336 +Epoch [3683/4000] Training [3/16] Loss: 0.00151 +Epoch [3683/4000] Training [4/16] Loss: 0.00250 +Epoch [3683/4000] Training [5/16] Loss: 0.00216 +Epoch [3683/4000] Training [6/16] Loss: 0.00168 +Epoch [3683/4000] Training [7/16] Loss: 0.00359 +Epoch [3683/4000] Training [8/16] Loss: 0.00186 +Epoch [3683/4000] Training [9/16] Loss: 0.00204 +Epoch [3683/4000] Training [10/16] Loss: 0.00259 +Epoch [3683/4000] Training [11/16] Loss: 0.00269 +Epoch [3683/4000] Training [12/16] Loss: 0.00200 +Epoch [3683/4000] Training [13/16] Loss: 0.00212 +Epoch [3683/4000] Training [14/16] Loss: 0.00240 +Epoch [3683/4000] Training [15/16] Loss: 0.00256 +Epoch [3683/4000] Training [16/16] Loss: 0.00173 +Epoch [3683/4000] Training metric {'Train/mean dice_metric': 0.998802900314331, 'Train/mean miou_metric': 0.9973291754722595, 'Train/mean f1': 0.9938371181488037, 'Train/mean precision': 0.9893261790275574, 'Train/mean recall': 0.998389482498169, 'Train/mean hd95_metric': 0.5105743408203125} +Epoch [3683/4000] Validation [1/4] Loss: 0.40070 focal_loss 0.33558 dice_loss 0.06512 +Epoch [3683/4000] Validation [2/4] Loss: 0.63828 focal_loss 0.46791 dice_loss 0.17036 +Epoch [3683/4000] Validation [3/4] Loss: 0.52856 focal_loss 0.43463 dice_loss 0.09393 +Epoch [3683/4000] Validation [4/4] Loss: 0.36078 focal_loss 0.27290 dice_loss 0.08788 +Epoch [3683/4000] Validation metric {'Val/mean dice_metric': 0.973986804485321, 'Val/mean miou_metric': 0.9597373008728027, 'Val/mean f1': 0.9759216904640198, 'Val/mean precision': 0.9733321666717529, 'Val/mean recall': 0.9785250425338745, 'Val/mean hd95_metric': 5.2374420166015625} +Cheakpoint... +Epoch [3683/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973986804485321, 'Val/mean miou_metric': 0.9597373008728027, 'Val/mean f1': 0.9759216904640198, 'Val/mean precision': 0.9733321666717529, 'Val/mean recall': 0.9785250425338745, 'Val/mean hd95_metric': 5.2374420166015625} +Epoch [3684/4000] Training [1/16] Loss: 0.00202 +Epoch [3684/4000] Training [2/16] Loss: 0.00229 +Epoch [3684/4000] Training [3/16] Loss: 0.00178 +Epoch [3684/4000] Training [4/16] Loss: 0.00224 +Epoch [3684/4000] Training [5/16] Loss: 0.00301 +Epoch [3684/4000] Training [6/16] Loss: 0.00216 +Epoch [3684/4000] Training [7/16] Loss: 0.00330 +Epoch [3684/4000] Training [8/16] Loss: 0.00156 +Epoch [3684/4000] Training [9/16] Loss: 0.00279 +Epoch [3684/4000] Training [10/16] Loss: 0.00342 +Epoch [3684/4000] Training [11/16] Loss: 0.00281 +Epoch [3684/4000] Training [12/16] Loss: 0.00266 +Epoch [3684/4000] Training [13/16] Loss: 0.00252 +Epoch [3684/4000] Training [14/16] Loss: 0.00236 +Epoch [3684/4000] Training [15/16] Loss: 0.00308 +Epoch [3684/4000] Training [16/16] Loss: 0.00364 +Epoch [3684/4000] Training metric {'Train/mean dice_metric': 0.998714804649353, 'Train/mean miou_metric': 0.9971566200256348, 'Train/mean f1': 0.9937126040458679, 'Train/mean precision': 0.9891802668571472, 'Train/mean recall': 0.9982866048812866, 'Train/mean hd95_metric': 0.5967351198196411} +Epoch [3684/4000] Validation [1/4] Loss: 0.38511 focal_loss 0.32256 dice_loss 0.06254 +Epoch [3684/4000] Validation [2/4] Loss: 0.48543 focal_loss 0.37389 dice_loss 0.11154 +Epoch [3684/4000] Validation [3/4] Loss: 0.54964 focal_loss 0.45761 dice_loss 0.09203 +Epoch [3684/4000] Validation [4/4] Loss: 0.49856 focal_loss 0.38961 dice_loss 0.10895 +Epoch [3684/4000] Validation metric {'Val/mean dice_metric': 0.9746416211128235, 'Val/mean miou_metric': 0.9605774879455566, 'Val/mean f1': 0.9764039516448975, 'Val/mean precision': 0.9738593697547913, 'Val/mean recall': 0.9789618849754333, 'Val/mean hd95_metric': 4.777408599853516} +Cheakpoint... +Epoch [3684/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746416211128235, 'Val/mean miou_metric': 0.9605774879455566, 'Val/mean f1': 0.9764039516448975, 'Val/mean precision': 0.9738593697547913, 'Val/mean recall': 0.9789618849754333, 'Val/mean hd95_metric': 4.777408599853516} +Epoch [3685/4000] Training [1/16] Loss: 0.00216 +Epoch [3685/4000] Training [2/16] Loss: 0.00210 +Epoch [3685/4000] Training [3/16] Loss: 0.00175 +Epoch [3685/4000] Training [4/16] Loss: 0.00279 +Epoch [3685/4000] Training [5/16] Loss: 0.00255 +Epoch [3685/4000] Training [6/16] Loss: 0.00229 +Epoch [3685/4000] Training [7/16] Loss: 0.00240 +Epoch [3685/4000] Training [8/16] Loss: 0.00262 +Epoch [3685/4000] Training [9/16] Loss: 0.00371 +Epoch [3685/4000] Training [10/16] Loss: 0.00201 +Epoch [3685/4000] Training [11/16] Loss: 0.00324 +Epoch [3685/4000] Training [12/16] Loss: 0.00270 +Epoch [3685/4000] Training [13/16] Loss: 0.00238 +Epoch [3685/4000] Training [14/16] Loss: 0.00205 +Epoch [3685/4000] Training [15/16] Loss: 0.00244 +Epoch [3685/4000] Training [16/16] Loss: 0.00215 +Epoch [3685/4000] Training metric {'Train/mean dice_metric': 0.9988320469856262, 'Train/mean miou_metric': 0.99737149477005, 'Train/mean f1': 0.9936627745628357, 'Train/mean precision': 0.9890291094779968, 'Train/mean recall': 0.9983400106430054, 'Train/mean hd95_metric': 0.5076448917388916} +Epoch [3685/4000] Validation [1/4] Loss: 0.44979 focal_loss 0.38088 dice_loss 0.06891 +Epoch [3685/4000] Validation [2/4] Loss: 1.11649 focal_loss 0.92661 dice_loss 0.18989 +Epoch [3685/4000] Validation [3/4] Loss: 0.57848 focal_loss 0.48292 dice_loss 0.09556 +Epoch [3685/4000] Validation [4/4] Loss: 0.43891 focal_loss 0.32660 dice_loss 0.11231 +Epoch [3685/4000] Validation metric {'Val/mean dice_metric': 0.973440945148468, 'Val/mean miou_metric': 0.959499716758728, 'Val/mean f1': 0.9758298397064209, 'Val/mean precision': 0.9737359881401062, 'Val/mean recall': 0.9779326319694519, 'Val/mean hd95_metric': 4.777307033538818} +Cheakpoint... +Epoch [3685/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973440945148468, 'Val/mean miou_metric': 0.959499716758728, 'Val/mean f1': 0.9758298397064209, 'Val/mean precision': 0.9737359881401062, 'Val/mean recall': 0.9779326319694519, 'Val/mean hd95_metric': 4.777307033538818} +Epoch [3686/4000] Training [1/16] Loss: 0.00269 +Epoch [3686/4000] Training [2/16] Loss: 0.00210 +Epoch [3686/4000] Training [3/16] Loss: 0.00228 +Epoch [3686/4000] Training [4/16] Loss: 0.00262 +Epoch [3686/4000] Training [5/16] Loss: 0.00222 +Epoch [3686/4000] Training [6/16] Loss: 0.00259 +Epoch [3686/4000] Training [7/16] Loss: 0.00169 +Epoch [3686/4000] Training [8/16] Loss: 0.00216 +Epoch [3686/4000] Training [9/16] Loss: 0.00350 +Epoch [3686/4000] Training [10/16] Loss: 0.00176 +Epoch [3686/4000] Training [11/16] Loss: 0.00208 +Epoch [3686/4000] Training [12/16] Loss: 0.00262 +Epoch [3686/4000] Training [13/16] Loss: 0.00423 +Epoch [3686/4000] Training [14/16] Loss: 0.00214 +Epoch [3686/4000] Training [15/16] Loss: 0.00271 +Epoch [3686/4000] Training [16/16] Loss: 0.00249 +Epoch [3686/4000] Training metric {'Train/mean dice_metric': 0.9986904859542847, 'Train/mean miou_metric': 0.9970890283584595, 'Train/mean f1': 0.9933481812477112, 'Train/mean precision': 0.9885382652282715, 'Train/mean recall': 0.9982050657272339, 'Train/mean hd95_metric': 0.5567936897277832} +Epoch [3686/4000] Validation [1/4] Loss: 0.45264 focal_loss 0.38065 dice_loss 0.07199 +Epoch [3686/4000] Validation [2/4] Loss: 0.50975 focal_loss 0.39769 dice_loss 0.11206 +Epoch [3686/4000] Validation [3/4] Loss: 0.54516 focal_loss 0.44787 dice_loss 0.09729 +Epoch [3686/4000] Validation [4/4] Loss: 0.36674 focal_loss 0.27489 dice_loss 0.09185 +Epoch [3686/4000] Validation metric {'Val/mean dice_metric': 0.9748066067695618, 'Val/mean miou_metric': 0.9602681994438171, 'Val/mean f1': 0.9756560325622559, 'Val/mean precision': 0.97395259141922, 'Val/mean recall': 0.9773654937744141, 'Val/mean hd95_metric': 4.8453049659729} +Cheakpoint... +Epoch [3686/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748066067695618, 'Val/mean miou_metric': 0.9602681994438171, 'Val/mean f1': 0.9756560325622559, 'Val/mean precision': 0.97395259141922, 'Val/mean recall': 0.9773654937744141, 'Val/mean hd95_metric': 4.8453049659729} +Epoch [3687/4000] Training [1/16] Loss: 0.00193 +Epoch [3687/4000] Training [2/16] Loss: 0.00284 +Epoch [3687/4000] Training [3/16] Loss: 0.00147 +Epoch [3687/4000] Training [4/16] Loss: 0.00236 +Epoch [3687/4000] Training [5/16] Loss: 0.00242 +Epoch [3687/4000] Training [6/16] Loss: 0.00443 +Epoch [3687/4000] Training [7/16] Loss: 0.00212 +Epoch [3687/4000] Training [8/16] Loss: 0.00252 +Epoch [3687/4000] Training [9/16] Loss: 0.00199 +Epoch [3687/4000] Training [10/16] Loss: 0.00236 +Epoch [3687/4000] Training [11/16] Loss: 0.00262 +Epoch [3687/4000] Training [12/16] Loss: 0.00200 +Epoch [3687/4000] Training [13/16] Loss: 0.00268 +Epoch [3687/4000] Training [14/16] Loss: 0.00223 +Epoch [3687/4000] Training [15/16] Loss: 0.00183 +Epoch [3687/4000] Training [16/16] Loss: 0.00302 +Epoch [3687/4000] Training metric {'Train/mean dice_metric': 0.998695969581604, 'Train/mean miou_metric': 0.9971194267272949, 'Train/mean f1': 0.9937855005264282, 'Train/mean precision': 0.9892762899398804, 'Train/mean recall': 0.9983359575271606, 'Train/mean hd95_metric': 0.5797033309936523} +Epoch [3687/4000] Validation [1/4] Loss: 0.46922 focal_loss 0.40402 dice_loss 0.06520 +Epoch [3687/4000] Validation [2/4] Loss: 0.50037 focal_loss 0.38917 dice_loss 0.11120 +Epoch [3687/4000] Validation [3/4] Loss: 0.49510 focal_loss 0.39870 dice_loss 0.09640 +Epoch [3687/4000] Validation [4/4] Loss: 0.40877 focal_loss 0.30570 dice_loss 0.10307 +Epoch [3687/4000] Validation metric {'Val/mean dice_metric': 0.9748641848564148, 'Val/mean miou_metric': 0.9608286023139954, 'Val/mean f1': 0.9768037796020508, 'Val/mean precision': 0.9744130373001099, 'Val/mean recall': 0.9792063236236572, 'Val/mean hd95_metric': 4.724666118621826} +Cheakpoint... +Epoch [3687/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748641848564148, 'Val/mean miou_metric': 0.9608286023139954, 'Val/mean f1': 0.9768037796020508, 'Val/mean precision': 0.9744130373001099, 'Val/mean recall': 0.9792063236236572, 'Val/mean hd95_metric': 4.724666118621826} +Epoch [3688/4000] Training [1/16] Loss: 0.00212 +Epoch [3688/4000] Training [2/16] Loss: 0.00239 +Epoch [3688/4000] Training [3/16] Loss: 0.00259 +Epoch [3688/4000] Training [4/16] Loss: 0.00200 +Epoch [3688/4000] Training [5/16] Loss: 0.00419 +Epoch [3688/4000] Training [6/16] Loss: 0.00215 +Epoch [3688/4000] Training [7/16] Loss: 0.00168 +Epoch [3688/4000] Training [8/16] Loss: 0.00165 +Epoch [3688/4000] Training [9/16] Loss: 0.00419 +Epoch [3688/4000] Training [10/16] Loss: 0.00165 +Epoch [3688/4000] Training [11/16] Loss: 0.00188 +Epoch [3688/4000] Training [12/16] Loss: 0.00244 +Epoch [3688/4000] Training [13/16] Loss: 0.00232 +Epoch [3688/4000] Training [14/16] Loss: 0.00328 +Epoch [3688/4000] Training [15/16] Loss: 0.00287 +Epoch [3688/4000] Training [16/16] Loss: 0.00175 +Epoch [3688/4000] Training metric {'Train/mean dice_metric': 0.9988752603530884, 'Train/mean miou_metric': 0.9974751472473145, 'Train/mean f1': 0.9939018487930298, 'Train/mean precision': 0.9893849492073059, 'Train/mean recall': 0.9984601140022278, 'Train/mean hd95_metric': 0.5175080299377441} +Epoch [3688/4000] Validation [1/4] Loss: 0.44098 focal_loss 0.37608 dice_loss 0.06490 +Epoch [3688/4000] Validation [2/4] Loss: 0.58527 focal_loss 0.43378 dice_loss 0.15149 +Epoch [3688/4000] Validation [3/4] Loss: 0.54680 focal_loss 0.44328 dice_loss 0.10352 +Epoch [3688/4000] Validation [4/4] Loss: 0.38153 focal_loss 0.28927 dice_loss 0.09225 +Epoch [3688/4000] Validation metric {'Val/mean dice_metric': 0.9729700088500977, 'Val/mean miou_metric': 0.9590075612068176, 'Val/mean f1': 0.9759107828140259, 'Val/mean precision': 0.9736401438713074, 'Val/mean recall': 0.9781919717788696, 'Val/mean hd95_metric': 5.217654705047607} +Cheakpoint... +Epoch [3688/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729700088500977, 'Val/mean miou_metric': 0.9590075612068176, 'Val/mean f1': 0.9759107828140259, 'Val/mean precision': 0.9736401438713074, 'Val/mean recall': 0.9781919717788696, 'Val/mean hd95_metric': 5.217654705047607} +Epoch [3689/4000] Training [1/16] Loss: 0.00254 +Epoch [3689/4000] Training [2/16] Loss: 0.00302 +Epoch [3689/4000] Training [3/16] Loss: 0.00161 +Epoch [3689/4000] Training [4/16] Loss: 0.00312 +Epoch [3689/4000] Training [5/16] Loss: 0.00194 +Epoch [3689/4000] Training [6/16] Loss: 0.00298 +Epoch [3689/4000] Training [7/16] Loss: 0.00204 +Epoch [3689/4000] Training [8/16] Loss: 0.00197 +Epoch [3689/4000] Training [9/16] Loss: 0.00294 +Epoch [3689/4000] Training [10/16] Loss: 0.00236 +Epoch [3689/4000] Training [11/16] Loss: 0.00218 +Epoch [3689/4000] Training [12/16] Loss: 0.00266 +Epoch [3689/4000] Training [13/16] Loss: 0.00238 +Epoch [3689/4000] Training [14/16] Loss: 0.00225 +Epoch [3689/4000] Training [15/16] Loss: 0.00364 +Epoch [3689/4000] Training [16/16] Loss: 0.00128 +Epoch [3689/4000] Training metric {'Train/mean dice_metric': 0.9987558722496033, 'Train/mean miou_metric': 0.9972352981567383, 'Train/mean f1': 0.9938523173332214, 'Train/mean precision': 0.9893515706062317, 'Train/mean recall': 0.9983941912651062, 'Train/mean hd95_metric': 0.5318635106086731} +Epoch [3689/4000] Validation [1/4] Loss: 0.50546 focal_loss 0.42306 dice_loss 0.08240 +Epoch [3689/4000] Validation [2/4] Loss: 0.54178 focal_loss 0.41534 dice_loss 0.12644 +Epoch [3689/4000] Validation [3/4] Loss: 0.54092 focal_loss 0.44396 dice_loss 0.09696 +Epoch [3689/4000] Validation [4/4] Loss: 0.57761 focal_loss 0.44772 dice_loss 0.12989 +Epoch [3689/4000] Validation metric {'Val/mean dice_metric': 0.9740483164787292, 'Val/mean miou_metric': 0.9596111178398132, 'Val/mean f1': 0.9764343500137329, 'Val/mean precision': 0.9740990996360779, 'Val/mean recall': 0.9787808060646057, 'Val/mean hd95_metric': 4.837874412536621} +Cheakpoint... +Epoch [3689/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740483164787292, 'Val/mean miou_metric': 0.9596111178398132, 'Val/mean f1': 0.9764343500137329, 'Val/mean precision': 0.9740990996360779, 'Val/mean recall': 0.9787808060646057, 'Val/mean hd95_metric': 4.837874412536621} +Epoch [3690/4000] Training [1/16] Loss: 0.00201 +Epoch [3690/4000] Training [2/16] Loss: 0.00256 +Epoch [3690/4000] Training [3/16] Loss: 0.00244 +Epoch [3690/4000] Training [4/16] Loss: 0.00270 +Epoch [3690/4000] Training [5/16] Loss: 0.00321 +Epoch [3690/4000] Training [6/16] Loss: 0.00239 +Epoch [3690/4000] Training [7/16] Loss: 0.00209 +Epoch [3690/4000] Training [8/16] Loss: 0.00306 +Epoch [3690/4000] Training [9/16] Loss: 0.00275 +Epoch [3690/4000] Training [10/16] Loss: 0.00215 +Epoch [3690/4000] Training [11/16] Loss: 0.00390 +Epoch [3690/4000] Training [12/16] Loss: 0.00191 +Epoch [3690/4000] Training [13/16] Loss: 0.00243 +Epoch [3690/4000] Training [14/16] Loss: 0.00221 +Epoch [3690/4000] Training [15/16] Loss: 0.00267 +Epoch [3690/4000] Training [16/16] Loss: 0.00236 +Epoch [3690/4000] Training metric {'Train/mean dice_metric': 0.9988446235656738, 'Train/mean miou_metric': 0.997413694858551, 'Train/mean f1': 0.9938845038414001, 'Train/mean precision': 0.9893404841423035, 'Train/mean recall': 0.9984704256057739, 'Train/mean hd95_metric': 0.4867463707923889} +Epoch [3690/4000] Validation [1/4] Loss: 0.43363 focal_loss 0.37082 dice_loss 0.06281 +Epoch [3690/4000] Validation [2/4] Loss: 1.52604 focal_loss 1.24972 dice_loss 0.27632 +Epoch [3690/4000] Validation [3/4] Loss: 0.54593 focal_loss 0.44904 dice_loss 0.09689 +Epoch [3690/4000] Validation [4/4] Loss: 0.49229 focal_loss 0.38640 dice_loss 0.10589 +Epoch [3690/4000] Validation metric {'Val/mean dice_metric': 0.9732295870780945, 'Val/mean miou_metric': 0.959362804889679, 'Val/mean f1': 0.976182758808136, 'Val/mean precision': 0.9738367795944214, 'Val/mean recall': 0.9785400032997131, 'Val/mean hd95_metric': 4.764108180999756} +Cheakpoint... +Epoch [3690/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732295870780945, 'Val/mean miou_metric': 0.959362804889679, 'Val/mean f1': 0.976182758808136, 'Val/mean precision': 0.9738367795944214, 'Val/mean recall': 0.9785400032997131, 'Val/mean hd95_metric': 4.764108180999756} +Epoch [3691/4000] Training [1/16] Loss: 0.00246 +Epoch [3691/4000] Training [2/16] Loss: 0.00207 +Epoch [3691/4000] Training [3/16] Loss: 0.00223 +Epoch [3691/4000] Training [4/16] Loss: 0.00213 +Epoch [3691/4000] Training [5/16] Loss: 0.00273 +Epoch [3691/4000] Training [6/16] Loss: 0.00247 +Epoch [3691/4000] Training [7/16] Loss: 0.00217 +Epoch [3691/4000] Training [8/16] Loss: 0.00256 +Epoch [3691/4000] Training [9/16] Loss: 0.00176 +Epoch [3691/4000] Training [10/16] Loss: 0.00206 +Epoch [3691/4000] Training [11/16] Loss: 0.00342 +Epoch [3691/4000] Training [12/16] Loss: 0.00198 +Epoch [3691/4000] Training [13/16] Loss: 0.00304 +Epoch [3691/4000] Training [14/16] Loss: 0.00296 +Epoch [3691/4000] Training [15/16] Loss: 0.00247 +Epoch [3691/4000] Training [16/16] Loss: 0.00328 +Epoch [3691/4000] Training metric {'Train/mean dice_metric': 0.9987701773643494, 'Train/mean miou_metric': 0.9972537755966187, 'Train/mean f1': 0.9936489462852478, 'Train/mean precision': 0.9889938831329346, 'Train/mean recall': 0.9983481168746948, 'Train/mean hd95_metric': 0.555984616279602} +Epoch [3691/4000] Validation [1/4] Loss: 0.42862 focal_loss 0.36448 dice_loss 0.06414 +Epoch [3691/4000] Validation [2/4] Loss: 0.50929 focal_loss 0.39633 dice_loss 0.11296 +Epoch [3691/4000] Validation [3/4] Loss: 0.34486 focal_loss 0.27705 dice_loss 0.06781 +Epoch [3691/4000] Validation [4/4] Loss: 0.35508 focal_loss 0.26994 dice_loss 0.08514 +Epoch [3691/4000] Validation metric {'Val/mean dice_metric': 0.9737170934677124, 'Val/mean miou_metric': 0.9599965810775757, 'Val/mean f1': 0.9765844941139221, 'Val/mean precision': 0.9748892784118652, 'Val/mean recall': 0.9782856106758118, 'Val/mean hd95_metric': 4.933592319488525} +Cheakpoint... +Epoch [3691/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737170934677124, 'Val/mean miou_metric': 0.9599965810775757, 'Val/mean f1': 0.9765844941139221, 'Val/mean precision': 0.9748892784118652, 'Val/mean recall': 0.9782856106758118, 'Val/mean hd95_metric': 4.933592319488525} +Epoch [3692/4000] Training [1/16] Loss: 0.00218 +Epoch [3692/4000] Training [2/16] Loss: 0.00265 +Epoch [3692/4000] Training [3/16] Loss: 0.00194 +Epoch [3692/4000] Training [4/16] Loss: 0.00280 +Epoch [3692/4000] Training [5/16] Loss: 0.00382 +Epoch [3692/4000] Training [6/16] Loss: 0.00275 +Epoch [3692/4000] Training [7/16] Loss: 0.00208 +Epoch [3692/4000] Training [8/16] Loss: 0.00244 +Epoch [3692/4000] Training [9/16] Loss: 0.00232 +Epoch [3692/4000] Training [10/16] Loss: 0.00324 +Epoch [3692/4000] Training [11/16] Loss: 0.00206 +Epoch [3692/4000] Training [12/16] Loss: 0.00288 +Epoch [3692/4000] Training [13/16] Loss: 0.00225 +Epoch [3692/4000] Training [14/16] Loss: 0.00197 +Epoch [3692/4000] Training [15/16] Loss: 0.00184 +Epoch [3692/4000] Training [16/16] Loss: 0.00288 +Epoch [3692/4000] Training metric {'Train/mean dice_metric': 0.9988713264465332, 'Train/mean miou_metric': 0.9974635243415833, 'Train/mean f1': 0.9939136505126953, 'Train/mean precision': 0.9894033670425415, 'Train/mean recall': 0.9984651803970337, 'Train/mean hd95_metric': 0.5165312886238098} +Epoch [3692/4000] Validation [1/4] Loss: 0.35080 focal_loss 0.29196 dice_loss 0.05884 +Epoch [3692/4000] Validation [2/4] Loss: 0.87982 focal_loss 0.66008 dice_loss 0.21974 +Epoch [3692/4000] Validation [3/4] Loss: 0.52685 focal_loss 0.43597 dice_loss 0.09088 +Epoch [3692/4000] Validation [4/4] Loss: 0.57493 focal_loss 0.43510 dice_loss 0.13983 +Epoch [3692/4000] Validation metric {'Val/mean dice_metric': 0.9716607928276062, 'Val/mean miou_metric': 0.957730770111084, 'Val/mean f1': 0.9755597710609436, 'Val/mean precision': 0.9735979437828064, 'Val/mean recall': 0.9775293469429016, 'Val/mean hd95_metric': 5.086547374725342} +Cheakpoint... +Epoch [3692/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9717], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716607928276062, 'Val/mean miou_metric': 0.957730770111084, 'Val/mean f1': 0.9755597710609436, 'Val/mean precision': 0.9735979437828064, 'Val/mean recall': 0.9775293469429016, 'Val/mean hd95_metric': 5.086547374725342} +Epoch [3693/4000] Training [1/16] Loss: 0.00249 +Epoch [3693/4000] Training [2/16] Loss: 0.00317 +Epoch [3693/4000] Training [3/16] Loss: 0.00379 +Epoch [3693/4000] Training [4/16] Loss: 0.00196 +Epoch [3693/4000] Training [5/16] Loss: 0.00243 +Epoch [3693/4000] Training [6/16] Loss: 0.00217 +Epoch [3693/4000] Training [7/16] Loss: 0.00273 +Epoch [3693/4000] Training [8/16] Loss: 0.00208 +Epoch [3693/4000] Training [9/16] Loss: 0.00298 +Epoch [3693/4000] Training [10/16] Loss: 0.00180 +Epoch [3693/4000] Training [11/16] Loss: 0.00189 +Epoch [3693/4000] Training [12/16] Loss: 0.00209 +Epoch [3693/4000] Training [13/16] Loss: 0.00184 +Epoch [3693/4000] Training [14/16] Loss: 0.00248 +Epoch [3693/4000] Training [15/16] Loss: 0.00198 +Epoch [3693/4000] Training [16/16] Loss: 0.00377 +Epoch [3693/4000] Training metric {'Train/mean dice_metric': 0.9988011717796326, 'Train/mean miou_metric': 0.9973287582397461, 'Train/mean f1': 0.9937901496887207, 'Train/mean precision': 0.9892693161964417, 'Train/mean recall': 0.9983524084091187, 'Train/mean hd95_metric': 0.5142852067947388} +Epoch [3693/4000] Validation [1/4] Loss: 0.40097 focal_loss 0.33702 dice_loss 0.06395 +Epoch [3693/4000] Validation [2/4] Loss: 1.54075 focal_loss 1.26334 dice_loss 0.27741 +Epoch [3693/4000] Validation [3/4] Loss: 0.28793 focal_loss 0.22377 dice_loss 0.06416 +Epoch [3693/4000] Validation [4/4] Loss: 0.35617 focal_loss 0.27124 dice_loss 0.08492 +Epoch [3693/4000] Validation metric {'Val/mean dice_metric': 0.9740277528762817, 'Val/mean miou_metric': 0.9602857828140259, 'Val/mean f1': 0.9763261079788208, 'Val/mean precision': 0.9740391373634338, 'Val/mean recall': 0.9786238670349121, 'Val/mean hd95_metric': 4.636451244354248} +Cheakpoint... +Epoch [3693/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740277528762817, 'Val/mean miou_metric': 0.9602857828140259, 'Val/mean f1': 0.9763261079788208, 'Val/mean precision': 0.9740391373634338, 'Val/mean recall': 0.9786238670349121, 'Val/mean hd95_metric': 4.636451244354248} +Epoch [3694/4000] Training [1/16] Loss: 0.00285 +Epoch [3694/4000] Training [2/16] Loss: 0.00484 +Epoch [3694/4000] Training [3/16] Loss: 0.00185 +Epoch [3694/4000] Training [4/16] Loss: 0.00253 +Epoch [3694/4000] Training [5/16] Loss: 0.00185 +Epoch [3694/4000] Training [6/16] Loss: 0.00228 +Epoch [3694/4000] Training [7/16] Loss: 0.00337 +Epoch [3694/4000] Training [8/16] Loss: 0.00208 +Epoch [3694/4000] Training [9/16] Loss: 0.00181 +Epoch [3694/4000] Training [10/16] Loss: 0.00326 +Epoch [3694/4000] Training [11/16] Loss: 0.00307 +Epoch [3694/4000] Training [12/16] Loss: 0.00299 +Epoch [3694/4000] Training [13/16] Loss: 0.00206 +Epoch [3694/4000] Training [14/16] Loss: 0.00258 +Epoch [3694/4000] Training [15/16] Loss: 0.00241 +Epoch [3694/4000] Training [16/16] Loss: 0.00275 +Epoch [3694/4000] Training metric {'Train/mean dice_metric': 0.9988448619842529, 'Train/mean miou_metric': 0.997417151927948, 'Train/mean f1': 0.9938745498657227, 'Train/mean precision': 0.9893637299537659, 'Train/mean recall': 0.9984267354011536, 'Train/mean hd95_metric': 0.4886016845703125} +Epoch [3694/4000] Validation [1/4] Loss: 0.40998 focal_loss 0.34409 dice_loss 0.06589 +Epoch [3694/4000] Validation [2/4] Loss: 0.56764 focal_loss 0.43145 dice_loss 0.13619 +Epoch [3694/4000] Validation [3/4] Loss: 0.55912 focal_loss 0.46544 dice_loss 0.09367 +Epoch [3694/4000] Validation [4/4] Loss: 0.36110 focal_loss 0.27318 dice_loss 0.08792 +Epoch [3694/4000] Validation metric {'Val/mean dice_metric': 0.973962664604187, 'Val/mean miou_metric': 0.9596251249313354, 'Val/mean f1': 0.9761325716972351, 'Val/mean precision': 0.9735695719718933, 'Val/mean recall': 0.9787092208862305, 'Val/mean hd95_metric': 5.158430576324463} +Cheakpoint... +Epoch [3694/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973962664604187, 'Val/mean miou_metric': 0.9596251249313354, 'Val/mean f1': 0.9761325716972351, 'Val/mean precision': 0.9735695719718933, 'Val/mean recall': 0.9787092208862305, 'Val/mean hd95_metric': 5.158430576324463} +Epoch [3695/4000] Training [1/16] Loss: 0.00273 +Epoch [3695/4000] Training [2/16] Loss: 0.00385 +Epoch [3695/4000] Training [3/16] Loss: 0.00143 +Epoch [3695/4000] Training [4/16] Loss: 0.00216 +Epoch [3695/4000] Training [5/16] Loss: 0.00216 +Epoch [3695/4000] Training [6/16] Loss: 0.00279 +Epoch [3695/4000] Training [7/16] Loss: 0.00186 +Epoch [3695/4000] Training [8/16] Loss: 0.00345 +Epoch [3695/4000] Training [9/16] Loss: 0.00296 +Epoch [3695/4000] Training [10/16] Loss: 0.00264 +Epoch [3695/4000] Training [11/16] Loss: 0.00214 +Epoch [3695/4000] Training [12/16] Loss: 0.00244 +Epoch [3695/4000] Training [13/16] Loss: 0.00247 +Epoch [3695/4000] Training [14/16] Loss: 0.00314 +Epoch [3695/4000] Training [15/16] Loss: 0.00298 +Epoch [3695/4000] Training [16/16] Loss: 0.00257 +Epoch [3695/4000] Training metric {'Train/mean dice_metric': 0.9986992478370667, 'Train/mean miou_metric': 0.9971209764480591, 'Train/mean f1': 0.9936456084251404, 'Train/mean precision': 0.9890128374099731, 'Train/mean recall': 0.9983219504356384, 'Train/mean hd95_metric': 0.53684401512146} +Epoch [3695/4000] Validation [1/4] Loss: 0.38583 focal_loss 0.32391 dice_loss 0.06193 +Epoch [3695/4000] Validation [2/4] Loss: 0.49064 focal_loss 0.37906 dice_loss 0.11158 +Epoch [3695/4000] Validation [3/4] Loss: 0.59016 focal_loss 0.48708 dice_loss 0.10309 +Epoch [3695/4000] Validation [4/4] Loss: 0.29838 focal_loss 0.21289 dice_loss 0.08549 +Epoch [3695/4000] Validation metric {'Val/mean dice_metric': 0.9731770753860474, 'Val/mean miou_metric': 0.9597207903862, 'Val/mean f1': 0.9764871597290039, 'Val/mean precision': 0.9742028117179871, 'Val/mean recall': 0.9787823557853699, 'Val/mean hd95_metric': 5.027831077575684} +Cheakpoint... +Epoch [3695/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731770753860474, 'Val/mean miou_metric': 0.9597207903862, 'Val/mean f1': 0.9764871597290039, 'Val/mean precision': 0.9742028117179871, 'Val/mean recall': 0.9787823557853699, 'Val/mean hd95_metric': 5.027831077575684} +Epoch [3696/4000] Training [1/16] Loss: 0.00190 +Epoch [3696/4000] Training [2/16] Loss: 0.00217 +Epoch [3696/4000] Training [3/16] Loss: 0.00237 +Epoch [3696/4000] Training [4/16] Loss: 0.00227 +Epoch [3696/4000] Training [5/16] Loss: 0.00347 +Epoch [3696/4000] Training [6/16] Loss: 0.00145 +Epoch [3696/4000] Training [7/16] Loss: 0.00268 +Epoch [3696/4000] Training [8/16] Loss: 0.00213 +Epoch [3696/4000] Training [9/16] Loss: 0.00281 +Epoch [3696/4000] Training [10/16] Loss: 0.00179 +Epoch [3696/4000] Training [11/16] Loss: 0.00158 +Epoch [3696/4000] Training [12/16] Loss: 0.00307 +Epoch [3696/4000] Training [13/16] Loss: 0.00164 +Epoch [3696/4000] Training [14/16] Loss: 0.00235 +Epoch [3696/4000] Training [15/16] Loss: 0.00236 +Epoch [3696/4000] Training [16/16] Loss: 0.00239 +Epoch [3696/4000] Training metric {'Train/mean dice_metric': 0.9989255666732788, 'Train/mean miou_metric': 0.9975656270980835, 'Train/mean f1': 0.9938614368438721, 'Train/mean precision': 0.9892681837081909, 'Train/mean recall': 0.9984976053237915, 'Train/mean hd95_metric': 0.48088693618774414} +Epoch [3696/4000] Validation [1/4] Loss: 0.34292 focal_loss 0.28577 dice_loss 0.05715 +Epoch [3696/4000] Validation [2/4] Loss: 0.58022 focal_loss 0.43796 dice_loss 0.14225 +Epoch [3696/4000] Validation [3/4] Loss: 0.25754 focal_loss 0.19895 dice_loss 0.05859 +Epoch [3696/4000] Validation [4/4] Loss: 0.27764 focal_loss 0.19900 dice_loss 0.07865 +Epoch [3696/4000] Validation metric {'Val/mean dice_metric': 0.9755809903144836, 'Val/mean miou_metric': 0.9619795083999634, 'Val/mean f1': 0.9771010875701904, 'Val/mean precision': 0.9744480848312378, 'Val/mean recall': 0.9797686338424683, 'Val/mean hd95_metric': 4.765280246734619} +Cheakpoint... +Epoch [3696/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755809903144836, 'Val/mean miou_metric': 0.9619795083999634, 'Val/mean f1': 0.9771010875701904, 'Val/mean precision': 0.9744480848312378, 'Val/mean recall': 0.9797686338424683, 'Val/mean hd95_metric': 4.765280246734619} +Epoch [3697/4000] Training [1/16] Loss: 0.00251 +Epoch [3697/4000] Training [2/16] Loss: 0.00248 +Epoch [3697/4000] Training [3/16] Loss: 0.00180 +Epoch [3697/4000] Training [4/16] Loss: 0.00236 +Epoch [3697/4000] Training [5/16] Loss: 0.00203 +Epoch [3697/4000] Training [6/16] Loss: 0.00251 +Epoch [3697/4000] Training [7/16] Loss: 0.00187 +Epoch [3697/4000] Training [8/16] Loss: 0.00225 +Epoch [3697/4000] Training [9/16] Loss: 0.00314 +Epoch [3697/4000] Training [10/16] Loss: 0.00243 +Epoch [3697/4000] Training [11/16] Loss: 0.00309 +Epoch [3697/4000] Training [12/16] Loss: 0.00277 +Epoch [3697/4000] Training [13/16] Loss: 0.00256 +Epoch [3697/4000] Training [14/16] Loss: 0.00244 +Epoch [3697/4000] Training [15/16] Loss: 0.00206 +Epoch [3697/4000] Training [16/16] Loss: 0.00204 +Epoch [3697/4000] Training metric {'Train/mean dice_metric': 0.9987051486968994, 'Train/mean miou_metric': 0.997134804725647, 'Train/mean f1': 0.9937258958816528, 'Train/mean precision': 0.9891843795776367, 'Train/mean recall': 0.998309314250946, 'Train/mean hd95_metric': 0.557449460029602} +Epoch [3697/4000] Validation [1/4] Loss: 0.39108 focal_loss 0.32852 dice_loss 0.06256 +Epoch [3697/4000] Validation [2/4] Loss: 0.96159 focal_loss 0.77215 dice_loss 0.18944 +Epoch [3697/4000] Validation [3/4] Loss: 0.52679 focal_loss 0.43653 dice_loss 0.09026 +Epoch [3697/4000] Validation [4/4] Loss: 0.35556 focal_loss 0.26189 dice_loss 0.09367 +Epoch [3697/4000] Validation metric {'Val/mean dice_metric': 0.9740878939628601, 'Val/mean miou_metric': 0.9603161811828613, 'Val/mean f1': 0.9765411019325256, 'Val/mean precision': 0.9743255972862244, 'Val/mean recall': 0.9787667989730835, 'Val/mean hd95_metric': 4.818950176239014} +Cheakpoint... +Epoch [3697/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740878939628601, 'Val/mean miou_metric': 0.9603161811828613, 'Val/mean f1': 0.9765411019325256, 'Val/mean precision': 0.9743255972862244, 'Val/mean recall': 0.9787667989730835, 'Val/mean hd95_metric': 4.818950176239014} +Epoch [3698/4000] Training [1/16] Loss: 0.00367 +Epoch [3698/4000] Training [2/16] Loss: 0.00229 +Epoch [3698/4000] Training [3/16] Loss: 0.00161 +Epoch [3698/4000] Training [4/16] Loss: 0.00255 +Epoch [3698/4000] Training [5/16] Loss: 0.00249 +Epoch [3698/4000] Training [6/16] Loss: 0.00194 +Epoch [3698/4000] Training [7/16] Loss: 0.00223 +Epoch [3698/4000] Training [8/16] Loss: 0.00264 +Epoch [3698/4000] Training [9/16] Loss: 0.00269 +Epoch [3698/4000] Training [10/16] Loss: 0.00235 +Epoch [3698/4000] Training [11/16] Loss: 0.00255 +Epoch [3698/4000] Training [12/16] Loss: 0.00226 +Epoch [3698/4000] Training [13/16] Loss: 0.00162 +Epoch [3698/4000] Training [14/16] Loss: 0.00237 +Epoch [3698/4000] Training [15/16] Loss: 0.00207 +Epoch [3698/4000] Training [16/16] Loss: 0.00242 +Epoch [3698/4000] Training metric {'Train/mean dice_metric': 0.9987832307815552, 'Train/mean miou_metric': 0.9972912669181824, 'Train/mean f1': 0.993782103061676, 'Train/mean precision': 0.9892409443855286, 'Train/mean recall': 0.9983652234077454, 'Train/mean hd95_metric': 0.5646061897277832} +Epoch [3698/4000] Validation [1/4] Loss: 0.37726 focal_loss 0.31570 dice_loss 0.06156 +Epoch [3698/4000] Validation [2/4] Loss: 0.96315 focal_loss 0.77520 dice_loss 0.18795 +Epoch [3698/4000] Validation [3/4] Loss: 0.53375 focal_loss 0.43722 dice_loss 0.09654 +Epoch [3698/4000] Validation [4/4] Loss: 0.32935 focal_loss 0.23942 dice_loss 0.08993 +Epoch [3698/4000] Validation metric {'Val/mean dice_metric': 0.9733244776725769, 'Val/mean miou_metric': 0.9599385261535645, 'Val/mean f1': 0.9758298993110657, 'Val/mean precision': 0.9736934304237366, 'Val/mean recall': 0.9779757857322693, 'Val/mean hd95_metric': 5.223694801330566} +Cheakpoint... +Epoch [3698/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733244776725769, 'Val/mean miou_metric': 0.9599385261535645, 'Val/mean f1': 0.9758298993110657, 'Val/mean precision': 0.9736934304237366, 'Val/mean recall': 0.9779757857322693, 'Val/mean hd95_metric': 5.223694801330566} +Epoch [3699/4000] Training [1/16] Loss: 0.00276 +Epoch [3699/4000] Training [2/16] Loss: 0.00216 +Epoch [3699/4000] Training [3/16] Loss: 0.00203 +Epoch [3699/4000] Training [4/16] Loss: 0.00170 +Epoch [3699/4000] Training [5/16] Loss: 0.00338 +Epoch [3699/4000] Training [6/16] Loss: 0.00195 +Epoch [3699/4000] Training [7/16] Loss: 0.00160 +Epoch [3699/4000] Training [8/16] Loss: 0.00290 +Epoch [3699/4000] Training [9/16] Loss: 0.00183 +Epoch [3699/4000] Training [10/16] Loss: 0.00258 +Epoch [3699/4000] Training [11/16] Loss: 0.00246 +Epoch [3699/4000] Training [12/16] Loss: 0.00184 +Epoch [3699/4000] Training [13/16] Loss: 0.00196 +Epoch [3699/4000] Training [14/16] Loss: 0.00220 +Epoch [3699/4000] Training [15/16] Loss: 0.00201 +Epoch [3699/4000] Training [16/16] Loss: 0.00190 +Epoch [3699/4000] Training metric {'Train/mean dice_metric': 0.9989802241325378, 'Train/mean miou_metric': 0.997657835483551, 'Train/mean f1': 0.9933235049247742, 'Train/mean precision': 0.9882140159606934, 'Train/mean recall': 0.9984860420227051, 'Train/mean hd95_metric': 0.45774251222610474} +Epoch [3699/4000] Validation [1/4] Loss: 0.36094 focal_loss 0.30038 dice_loss 0.06056 +Epoch [3699/4000] Validation [2/4] Loss: 0.90853 focal_loss 0.70967 dice_loss 0.19886 +Epoch [3699/4000] Validation [3/4] Loss: 0.50487 focal_loss 0.41800 dice_loss 0.08687 +Epoch [3699/4000] Validation [4/4] Loss: 0.30414 focal_loss 0.21008 dice_loss 0.09406 +Epoch [3699/4000] Validation metric {'Val/mean dice_metric': 0.9728946685791016, 'Val/mean miou_metric': 0.9591922760009766, 'Val/mean f1': 0.9754551649093628, 'Val/mean precision': 0.9721386432647705, 'Val/mean recall': 0.9787943959236145, 'Val/mean hd95_metric': 5.022049427032471} +Cheakpoint... +Epoch [3699/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728946685791016, 'Val/mean miou_metric': 0.9591922760009766, 'Val/mean f1': 0.9754551649093628, 'Val/mean precision': 0.9721386432647705, 'Val/mean recall': 0.9787943959236145, 'Val/mean hd95_metric': 5.022049427032471} +Epoch [3700/4000] Training [1/16] Loss: 0.00462 +Epoch [3700/4000] Training [2/16] Loss: 0.00322 +Epoch [3700/4000] Training [3/16] Loss: 0.00145 +Epoch [3700/4000] Training [4/16] Loss: 0.00360 +Epoch [3700/4000] Training [5/16] Loss: 0.00247 +Epoch [3700/4000] Training [6/16] Loss: 0.00283 +Epoch [3700/4000] Training [7/16] Loss: 0.00166 +Epoch [3700/4000] Training [8/16] Loss: 0.00224 +Epoch [3700/4000] Training [9/16] Loss: 0.00200 +Epoch [3700/4000] Training [10/16] Loss: 0.00283 +Epoch [3700/4000] Training [11/16] Loss: 0.00224 +Epoch [3700/4000] Training [12/16] Loss: 0.00240 +Epoch [3700/4000] Training [13/16] Loss: 0.00224 +Epoch [3700/4000] Training [14/16] Loss: 0.00206 +Epoch [3700/4000] Training [15/16] Loss: 0.00293 +Epoch [3700/4000] Training [16/16] Loss: 0.00297 +Epoch [3700/4000] Training metric {'Train/mean dice_metric': 0.9987696409225464, 'Train/mean miou_metric': 0.9972383379936218, 'Train/mean f1': 0.9932490587234497, 'Train/mean precision': 0.9882322549819946, 'Train/mean recall': 0.9983170032501221, 'Train/mean hd95_metric': 0.5078402757644653} +Epoch [3700/4000] Validation [1/4] Loss: 0.40424 focal_loss 0.34340 dice_loss 0.06084 +Epoch [3700/4000] Validation [2/4] Loss: 0.84368 focal_loss 0.62912 dice_loss 0.21456 +Epoch [3700/4000] Validation [3/4] Loss: 0.54617 focal_loss 0.44884 dice_loss 0.09733 +Epoch [3700/4000] Validation [4/4] Loss: 0.34150 focal_loss 0.25845 dice_loss 0.08305 +Epoch [3700/4000] Validation metric {'Val/mean dice_metric': 0.9750511050224304, 'Val/mean miou_metric': 0.9609605669975281, 'Val/mean f1': 0.9758427739143372, 'Val/mean precision': 0.9724948406219482, 'Val/mean recall': 0.9792137145996094, 'Val/mean hd95_metric': 5.051703453063965} +Cheakpoint... +Epoch [3700/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750511050224304, 'Val/mean miou_metric': 0.9609605669975281, 'Val/mean f1': 0.9758427739143372, 'Val/mean precision': 0.9724948406219482, 'Val/mean recall': 0.9792137145996094, 'Val/mean hd95_metric': 5.051703453063965} +Epoch [3701/4000] Training [1/16] Loss: 0.00190 +Epoch [3701/4000] Training [2/16] Loss: 0.00184 +Epoch [3701/4000] Training [3/16] Loss: 0.00291 +Epoch [3701/4000] Training [4/16] Loss: 0.00250 +Epoch [3701/4000] Training [5/16] Loss: 0.00211 +Epoch [3701/4000] Training [6/16] Loss: 0.00185 +Epoch [3701/4000] Training [7/16] Loss: 0.00236 +Epoch [3701/4000] Training [8/16] Loss: 0.00261 +Epoch [3701/4000] Training [9/16] Loss: 0.00258 +Epoch [3701/4000] Training [10/16] Loss: 0.00182 +Epoch [3701/4000] Training [11/16] Loss: 0.00198 +Epoch [3701/4000] Training [12/16] Loss: 0.00270 +Epoch [3701/4000] Training [13/16] Loss: 0.00171 +Epoch [3701/4000] Training [14/16] Loss: 0.00231 +Epoch [3701/4000] Training [15/16] Loss: 0.00262 +Epoch [3701/4000] Training [16/16] Loss: 0.00209 +Epoch [3701/4000] Training metric {'Train/mean dice_metric': 0.9989334344863892, 'Train/mean miou_metric': 0.9975916147232056, 'Train/mean f1': 0.9939844608306885, 'Train/mean precision': 0.9894767999649048, 'Train/mean recall': 0.9985333681106567, 'Train/mean hd95_metric': 0.508258581161499} +Epoch [3701/4000] Validation [1/4] Loss: 0.44126 focal_loss 0.36308 dice_loss 0.07819 +Epoch [3701/4000] Validation [2/4] Loss: 0.49021 focal_loss 0.37958 dice_loss 0.11064 +Epoch [3701/4000] Validation [3/4] Loss: 0.52581 focal_loss 0.43583 dice_loss 0.08998 +Epoch [3701/4000] Validation [4/4] Loss: 0.33841 focal_loss 0.25325 dice_loss 0.08515 +Epoch [3701/4000] Validation metric {'Val/mean dice_metric': 0.9752708673477173, 'Val/mean miou_metric': 0.9614238739013672, 'Val/mean f1': 0.9769930243492126, 'Val/mean precision': 0.9747788906097412, 'Val/mean recall': 0.9792172908782959, 'Val/mean hd95_metric': 4.6907267570495605} +Cheakpoint... +Epoch [3701/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752708673477173, 'Val/mean miou_metric': 0.9614238739013672, 'Val/mean f1': 0.9769930243492126, 'Val/mean precision': 0.9747788906097412, 'Val/mean recall': 0.9792172908782959, 'Val/mean hd95_metric': 4.6907267570495605} +Epoch [3702/4000] Training [1/16] Loss: 0.00403 +Epoch [3702/4000] Training [2/16] Loss: 0.00280 +Epoch [3702/4000] Training [3/16] Loss: 0.00233 +Epoch [3702/4000] Training [4/16] Loss: 0.00258 +Epoch [3702/4000] Training [5/16] Loss: 0.00276 +Epoch [3702/4000] Training [6/16] Loss: 0.00189 +Epoch [3702/4000] Training [7/16] Loss: 0.00158 +Epoch [3702/4000] Training [8/16] Loss: 0.00206 +Epoch [3702/4000] Training [9/16] Loss: 0.00183 +Epoch [3702/4000] Training [10/16] Loss: 0.00301 +Epoch [3702/4000] Training [11/16] Loss: 0.00186 +Epoch [3702/4000] Training [12/16] Loss: 0.00237 +Epoch [3702/4000] Training [13/16] Loss: 0.00386 +Epoch [3702/4000] Training [14/16] Loss: 0.00213 +Epoch [3702/4000] Training [15/16] Loss: 0.00206 +Epoch [3702/4000] Training [16/16] Loss: 0.00231 +Epoch [3702/4000] Training metric {'Train/mean dice_metric': 0.9987257719039917, 'Train/mean miou_metric': 0.9971365928649902, 'Train/mean f1': 0.9928532838821411, 'Train/mean precision': 0.9874903559684753, 'Train/mean recall': 0.9982748627662659, 'Train/mean hd95_metric': 0.5213165879249573} +Epoch [3702/4000] Validation [1/4] Loss: 0.40834 focal_loss 0.34592 dice_loss 0.06242 +Epoch [3702/4000] Validation [2/4] Loss: 1.05061 focal_loss 0.80018 dice_loss 0.25043 +Epoch [3702/4000] Validation [3/4] Loss: 0.58218 focal_loss 0.48135 dice_loss 0.10084 +Epoch [3702/4000] Validation [4/4] Loss: 0.36187 focal_loss 0.27425 dice_loss 0.08762 +Epoch [3702/4000] Validation metric {'Val/mean dice_metric': 0.9718221426010132, 'Val/mean miou_metric': 0.9580059051513672, 'Val/mean f1': 0.9749674201011658, 'Val/mean precision': 0.9727650880813599, 'Val/mean recall': 0.9771797060966492, 'Val/mean hd95_metric': 5.131718635559082} +Cheakpoint... +Epoch [3702/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9718], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718221426010132, 'Val/mean miou_metric': 0.9580059051513672, 'Val/mean f1': 0.9749674201011658, 'Val/mean precision': 0.9727650880813599, 'Val/mean recall': 0.9771797060966492, 'Val/mean hd95_metric': 5.131718635559082} +Epoch [3703/4000] Training [1/16] Loss: 0.00227 +Epoch [3703/4000] Training [2/16] Loss: 0.00199 +Epoch [3703/4000] Training [3/16] Loss: 0.00225 +Epoch [3703/4000] Training [4/16] Loss: 0.00232 +Epoch [3703/4000] Training [5/16] Loss: 0.00260 +Epoch [3703/4000] Training [6/16] Loss: 0.00168 +Epoch [3703/4000] Training [7/16] Loss: 0.00165 +Epoch [3703/4000] Training [8/16] Loss: 0.00226 +Epoch [3703/4000] Training [9/16] Loss: 0.00213 +Epoch [3703/4000] Training [10/16] Loss: 0.00243 +Epoch [3703/4000] Training [11/16] Loss: 0.00217 +Epoch [3703/4000] Training [12/16] Loss: 0.00193 +Epoch [3703/4000] Training [13/16] Loss: 0.00240 +Epoch [3703/4000] Training [14/16] Loss: 0.00163 +Epoch [3703/4000] Training [15/16] Loss: 0.00223 +Epoch [3703/4000] Training [16/16] Loss: 0.00223 +Epoch [3703/4000] Training metric {'Train/mean dice_metric': 0.9988276958465576, 'Train/mean miou_metric': 0.9973832964897156, 'Train/mean f1': 0.9938567280769348, 'Train/mean precision': 0.9893265962600708, 'Train/mean recall': 0.9984285235404968, 'Train/mean hd95_metric': 0.5053026080131531} +Epoch [3703/4000] Validation [1/4] Loss: 0.35348 focal_loss 0.29234 dice_loss 0.06113 +Epoch [3703/4000] Validation [2/4] Loss: 0.58189 focal_loss 0.43167 dice_loss 0.15023 +Epoch [3703/4000] Validation [3/4] Loss: 0.28325 focal_loss 0.21863 dice_loss 0.06462 +Epoch [3703/4000] Validation [4/4] Loss: 0.28286 focal_loss 0.19919 dice_loss 0.08367 +Epoch [3703/4000] Validation metric {'Val/mean dice_metric': 0.9751647710800171, 'Val/mean miou_metric': 0.9614721536636353, 'Val/mean f1': 0.9768567085266113, 'Val/mean precision': 0.974810004234314, 'Val/mean recall': 0.9789118766784668, 'Val/mean hd95_metric': 4.683055877685547} +Cheakpoint... +Epoch [3703/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751647710800171, 'Val/mean miou_metric': 0.9614721536636353, 'Val/mean f1': 0.9768567085266113, 'Val/mean precision': 0.974810004234314, 'Val/mean recall': 0.9789118766784668, 'Val/mean hd95_metric': 4.683055877685547} +Epoch [3704/4000] Training [1/16] Loss: 0.00254 +Epoch [3704/4000] Training [2/16] Loss: 0.00205 +Epoch [3704/4000] Training [3/16] Loss: 0.00296 +Epoch [3704/4000] Training [4/16] Loss: 0.00221 +Epoch [3704/4000] Training [5/16] Loss: 0.00224 +Epoch [3704/4000] Training [6/16] Loss: 0.00299 +Epoch [3704/4000] Training [7/16] Loss: 0.00273 +Epoch [3704/4000] Training [8/16] Loss: 0.00209 +Epoch [3704/4000] Training [9/16] Loss: 0.00202 +Epoch [3704/4000] Training [10/16] Loss: 0.00231 +Epoch [3704/4000] Training [11/16] Loss: 0.00282 +Epoch [3704/4000] Training [12/16] Loss: 0.00327 +Epoch [3704/4000] Training [13/16] Loss: 0.00204 +Epoch [3704/4000] Training [14/16] Loss: 0.00313 +Epoch [3704/4000] Training [15/16] Loss: 0.00212 +Epoch [3704/4000] Training [16/16] Loss: 0.00249 +Epoch [3704/4000] Training metric {'Train/mean dice_metric': 0.9986997246742249, 'Train/mean miou_metric': 0.9971246123313904, 'Train/mean f1': 0.9937248229980469, 'Train/mean precision': 0.9891787767410278, 'Train/mean recall': 0.9983128309249878, 'Train/mean hd95_metric': 0.5687775015830994} +Epoch [3704/4000] Validation [1/4] Loss: 0.38421 focal_loss 0.32355 dice_loss 0.06066 +Epoch [3704/4000] Validation [2/4] Loss: 0.96273 focal_loss 0.70356 dice_loss 0.25917 +Epoch [3704/4000] Validation [3/4] Loss: 0.52503 focal_loss 0.43165 dice_loss 0.09339 +Epoch [3704/4000] Validation [4/4] Loss: 0.35136 focal_loss 0.26230 dice_loss 0.08906 +Epoch [3704/4000] Validation metric {'Val/mean dice_metric': 0.9729217290878296, 'Val/mean miou_metric': 0.9589914083480835, 'Val/mean f1': 0.975983738899231, 'Val/mean precision': 0.9738292694091797, 'Val/mean recall': 0.9781478643417358, 'Val/mean hd95_metric': 5.23026180267334} +Cheakpoint... +Epoch [3704/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729217290878296, 'Val/mean miou_metric': 0.9589914083480835, 'Val/mean f1': 0.975983738899231, 'Val/mean precision': 0.9738292694091797, 'Val/mean recall': 0.9781478643417358, 'Val/mean hd95_metric': 5.23026180267334} +Epoch [3705/4000] Training [1/16] Loss: 0.00191 +Epoch [3705/4000] Training [2/16] Loss: 0.00216 +Epoch [3705/4000] Training [3/16] Loss: 0.00265 +Epoch [3705/4000] Training [4/16] Loss: 0.00206 +Epoch [3705/4000] Training [5/16] Loss: 0.00221 +Epoch [3705/4000] Training [6/16] Loss: 0.00210 +Epoch [3705/4000] Training [7/16] Loss: 0.00187 +Epoch [3705/4000] Training [8/16] Loss: 0.00218 +Epoch [3705/4000] Training [9/16] Loss: 0.00288 +Epoch [3705/4000] Training [10/16] Loss: 0.00185 +Epoch [3705/4000] Training [11/16] Loss: 0.00214 +Epoch [3705/4000] Training [12/16] Loss: 0.00278 +Epoch [3705/4000] Training [13/16] Loss: 0.00294 +Epoch [3705/4000] Training [14/16] Loss: 0.00163 +Epoch [3705/4000] Training [15/16] Loss: 0.00169 +Epoch [3705/4000] Training [16/16] Loss: 0.00207 +Epoch [3705/4000] Training metric {'Train/mean dice_metric': 0.9989550709724426, 'Train/mean miou_metric': 0.9976261854171753, 'Train/mean f1': 0.9938900470733643, 'Train/mean precision': 0.989282488822937, 'Train/mean recall': 0.9985405802726746, 'Train/mean hd95_metric': 0.4729769825935364} +Epoch [3705/4000] Validation [1/4] Loss: 0.37463 focal_loss 0.31371 dice_loss 0.06092 +Epoch [3705/4000] Validation [2/4] Loss: 0.47101 focal_loss 0.36410 dice_loss 0.10691 +Epoch [3705/4000] Validation [3/4] Loss: 0.54274 focal_loss 0.45238 dice_loss 0.09036 +Epoch [3705/4000] Validation [4/4] Loss: 0.45300 focal_loss 0.33779 dice_loss 0.11521 +Epoch [3705/4000] Validation metric {'Val/mean dice_metric': 0.9748747944831848, 'Val/mean miou_metric': 0.9608017206192017, 'Val/mean f1': 0.9766110777854919, 'Val/mean precision': 0.9742250442504883, 'Val/mean recall': 0.9790089130401611, 'Val/mean hd95_metric': 4.880835056304932} +Cheakpoint... +Epoch [3705/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748747944831848, 'Val/mean miou_metric': 0.9608017206192017, 'Val/mean f1': 0.9766110777854919, 'Val/mean precision': 0.9742250442504883, 'Val/mean recall': 0.9790089130401611, 'Val/mean hd95_metric': 4.880835056304932} +Epoch [3706/4000] Training [1/16] Loss: 0.00225 +Epoch [3706/4000] Training [2/16] Loss: 0.00341 +Epoch [3706/4000] Training [3/16] Loss: 0.00170 +Epoch [3706/4000] Training [4/16] Loss: 0.00202 +Epoch [3706/4000] Training [5/16] Loss: 0.00266 +Epoch [3706/4000] Training [6/16] Loss: 0.00181 +Epoch [3706/4000] Training [7/16] Loss: 0.00199 +Epoch [3706/4000] Training [8/16] Loss: 0.00127 +Epoch [3706/4000] Training [9/16] Loss: 0.00209 +Epoch [3706/4000] Training [10/16] Loss: 0.00186 +Epoch [3706/4000] Training [11/16] Loss: 0.00238 +Epoch [3706/4000] Training [12/16] Loss: 0.00227 +Epoch [3706/4000] Training [13/16] Loss: 0.00242 +Epoch [3706/4000] Training [14/16] Loss: 0.00234 +Epoch [3706/4000] Training [15/16] Loss: 0.00328 +Epoch [3706/4000] Training [16/16] Loss: 0.00199 +Epoch [3706/4000] Training metric {'Train/mean dice_metric': 0.9989612102508545, 'Train/mean miou_metric': 0.9976462125778198, 'Train/mean f1': 0.9939706325531006, 'Train/mean precision': 0.989480197429657, 'Train/mean recall': 0.9985019564628601, 'Train/mean hd95_metric': 0.46838700771331787} +Epoch [3706/4000] Validation [1/4] Loss: 0.37747 focal_loss 0.31832 dice_loss 0.05915 +Epoch [3706/4000] Validation [2/4] Loss: 0.48578 focal_loss 0.37339 dice_loss 0.11239 +Epoch [3706/4000] Validation [3/4] Loss: 0.55203 focal_loss 0.45755 dice_loss 0.09448 +Epoch [3706/4000] Validation [4/4] Loss: 0.31638 focal_loss 0.22817 dice_loss 0.08821 +Epoch [3706/4000] Validation metric {'Val/mean dice_metric': 0.9723215103149414, 'Val/mean miou_metric': 0.9593207240104675, 'Val/mean f1': 0.9763109683990479, 'Val/mean precision': 0.9745498299598694, 'Val/mean recall': 0.9780783653259277, 'Val/mean hd95_metric': 5.331064701080322} +Cheakpoint... +Epoch [3706/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723215103149414, 'Val/mean miou_metric': 0.9593207240104675, 'Val/mean f1': 0.9763109683990479, 'Val/mean precision': 0.9745498299598694, 'Val/mean recall': 0.9780783653259277, 'Val/mean hd95_metric': 5.331064701080322} +Epoch [3707/4000] Training [1/16] Loss: 0.00209 +Epoch [3707/4000] Training [2/16] Loss: 0.00220 +Epoch [3707/4000] Training [3/16] Loss: 0.00203 +Epoch [3707/4000] Training [4/16] Loss: 0.00257 +Epoch [3707/4000] Training [5/16] Loss: 0.00179 +Epoch [3707/4000] Training [6/16] Loss: 0.00193 +Epoch [3707/4000] Training [7/16] Loss: 0.00281 +Epoch [3707/4000] Training [8/16] Loss: 0.00184 +Epoch [3707/4000] Training [9/16] Loss: 0.00214 +Epoch [3707/4000] Training [10/16] Loss: 0.00343 +Epoch [3707/4000] Training [11/16] Loss: 0.00208 +Epoch [3707/4000] Training [12/16] Loss: 0.00205 +Epoch [3707/4000] Training [13/16] Loss: 0.00257 +Epoch [3707/4000] Training [14/16] Loss: 0.00402 +Epoch [3707/4000] Training [15/16] Loss: 0.00172 +Epoch [3707/4000] Training [16/16] Loss: 0.00250 +Epoch [3707/4000] Training metric {'Train/mean dice_metric': 0.9988670349121094, 'Train/mean miou_metric': 0.997443437576294, 'Train/mean f1': 0.9936588406562805, 'Train/mean precision': 0.988936722278595, 'Train/mean recall': 0.9984262585639954, 'Train/mean hd95_metric': 0.5086212754249573} +Epoch [3707/4000] Validation [1/4] Loss: 0.39947 focal_loss 0.33878 dice_loss 0.06069 +Epoch [3707/4000] Validation [2/4] Loss: 0.87372 focal_loss 0.68303 dice_loss 0.19069 +Epoch [3707/4000] Validation [3/4] Loss: 0.56661 focal_loss 0.47503 dice_loss 0.09158 +Epoch [3707/4000] Validation [4/4] Loss: 0.39859 focal_loss 0.29531 dice_loss 0.10328 +Epoch [3707/4000] Validation metric {'Val/mean dice_metric': 0.973275363445282, 'Val/mean miou_metric': 0.9592908024787903, 'Val/mean f1': 0.9759358167648315, 'Val/mean precision': 0.9737868905067444, 'Val/mean recall': 0.9780945181846619, 'Val/mean hd95_metric': 5.268733978271484} +Cheakpoint... +Epoch [3707/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973275363445282, 'Val/mean miou_metric': 0.9592908024787903, 'Val/mean f1': 0.9759358167648315, 'Val/mean precision': 0.9737868905067444, 'Val/mean recall': 0.9780945181846619, 'Val/mean hd95_metric': 5.268733978271484} +Epoch [3708/4000] Training [1/16] Loss: 0.00289 +Epoch [3708/4000] Training [2/16] Loss: 0.00248 +Epoch [3708/4000] Training [3/16] Loss: 0.00268 +Epoch [3708/4000] Training [4/16] Loss: 0.00200 +Epoch [3708/4000] Training [5/16] Loss: 0.00253 +Epoch [3708/4000] Training [6/16] Loss: 0.00285 +Epoch [3708/4000] Training [7/16] Loss: 0.00181 +Epoch [3708/4000] Training [8/16] Loss: 0.00265 +Epoch [3708/4000] Training [9/16] Loss: 0.00286 +Epoch [3708/4000] Training [10/16] Loss: 0.00311 +Epoch [3708/4000] Training [11/16] Loss: 0.00196 +Epoch [3708/4000] Training [12/16] Loss: 0.00250 +Epoch [3708/4000] Training [13/16] Loss: 0.00194 +Epoch [3708/4000] Training [14/16] Loss: 0.00209 +Epoch [3708/4000] Training [15/16] Loss: 0.00185 +Epoch [3708/4000] Training [16/16] Loss: 0.00251 +Epoch [3708/4000] Training metric {'Train/mean dice_metric': 0.998798131942749, 'Train/mean miou_metric': 0.997316837310791, 'Train/mean f1': 0.9937925934791565, 'Train/mean precision': 0.9892351031303406, 'Train/mean recall': 0.9983922839164734, 'Train/mean hd95_metric': 0.5303789377212524} +Epoch [3708/4000] Validation [1/4] Loss: 0.48537 focal_loss 0.41899 dice_loss 0.06639 +Epoch [3708/4000] Validation [2/4] Loss: 0.48238 focal_loss 0.37285 dice_loss 0.10953 +Epoch [3708/4000] Validation [3/4] Loss: 0.52633 focal_loss 0.43582 dice_loss 0.09051 +Epoch [3708/4000] Validation [4/4] Loss: 0.29976 focal_loss 0.21441 dice_loss 0.08535 +Epoch [3708/4000] Validation metric {'Val/mean dice_metric': 0.9753106832504272, 'Val/mean miou_metric': 0.9614841341972351, 'Val/mean f1': 0.9767929315567017, 'Val/mean precision': 0.9739997982978821, 'Val/mean recall': 0.9796020984649658, 'Val/mean hd95_metric': 4.735487937927246} +Cheakpoint... +Epoch [3708/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753106832504272, 'Val/mean miou_metric': 0.9614841341972351, 'Val/mean f1': 0.9767929315567017, 'Val/mean precision': 0.9739997982978821, 'Val/mean recall': 0.9796020984649658, 'Val/mean hd95_metric': 4.735487937927246} +Epoch [3709/4000] Training [1/16] Loss: 0.00201 +Epoch [3709/4000] Training [2/16] Loss: 0.00252 +Epoch [3709/4000] Training [3/16] Loss: 0.00252 +Epoch [3709/4000] Training [4/16] Loss: 0.00255 +Epoch [3709/4000] Training [5/16] Loss: 0.00226 +Epoch [3709/4000] Training [6/16] Loss: 0.00307 +Epoch [3709/4000] Training [7/16] Loss: 0.00219 +Epoch [3709/4000] Training [8/16] Loss: 0.00195 +Epoch [3709/4000] Training [9/16] Loss: 0.00248 +Epoch [3709/4000] Training [10/16] Loss: 0.00278 +Epoch [3709/4000] Training [11/16] Loss: 0.00226 +Epoch [3709/4000] Training [12/16] Loss: 0.00168 +Epoch [3709/4000] Training [13/16] Loss: 0.00270 +Epoch [3709/4000] Training [14/16] Loss: 0.00229 +Epoch [3709/4000] Training [15/16] Loss: 0.00288 +Epoch [3709/4000] Training [16/16] Loss: 0.00322 +Epoch [3709/4000] Training metric {'Train/mean dice_metric': 0.9987761378288269, 'Train/mean miou_metric': 0.9972611665725708, 'Train/mean f1': 0.9934790134429932, 'Train/mean precision': 0.9886476397514343, 'Train/mean recall': 0.9983577728271484, 'Train/mean hd95_metric': 0.5380862355232239} +Epoch [3709/4000] Validation [1/4] Loss: 0.46765 focal_loss 0.40268 dice_loss 0.06497 +Epoch [3709/4000] Validation [2/4] Loss: 0.92973 focal_loss 0.74467 dice_loss 0.18506 +Epoch [3709/4000] Validation [3/4] Loss: 0.52275 focal_loss 0.43365 dice_loss 0.08911 +Epoch [3709/4000] Validation [4/4] Loss: 0.32163 focal_loss 0.23484 dice_loss 0.08679 +Epoch [3709/4000] Validation metric {'Val/mean dice_metric': 0.9716349840164185, 'Val/mean miou_metric': 0.9586718678474426, 'Val/mean f1': 0.9757792353630066, 'Val/mean precision': 0.9740190505981445, 'Val/mean recall': 0.9775457978248596, 'Val/mean hd95_metric': 4.998018741607666} +Cheakpoint... +Epoch [3709/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9716], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9716349840164185, 'Val/mean miou_metric': 0.9586718678474426, 'Val/mean f1': 0.9757792353630066, 'Val/mean precision': 0.9740190505981445, 'Val/mean recall': 0.9775457978248596, 'Val/mean hd95_metric': 4.998018741607666} +Epoch [3710/4000] Training [1/16] Loss: 0.00320 +Epoch [3710/4000] Training [2/16] Loss: 0.00297 +Epoch [3710/4000] Training [3/16] Loss: 0.00247 +Epoch [3710/4000] Training [4/16] Loss: 0.00260 +Epoch [3710/4000] Training [5/16] Loss: 0.00266 +Epoch [3710/4000] Training [6/16] Loss: 0.00153 +Epoch [3710/4000] Training [7/16] Loss: 0.00264 +Epoch [3710/4000] Training [8/16] Loss: 0.00205 +Epoch [3710/4000] Training [9/16] Loss: 0.00227 +Epoch [3710/4000] Training [10/16] Loss: 0.00238 +Epoch [3710/4000] Training [11/16] Loss: 0.00357 +Epoch [3710/4000] Training [12/16] Loss: 0.00296 +Epoch [3710/4000] Training [13/16] Loss: 0.00180 +Epoch [3710/4000] Training [14/16] Loss: 0.00323 +Epoch [3710/4000] Training [15/16] Loss: 0.00218 +Epoch [3710/4000] Training [16/16] Loss: 0.00194 +Epoch [3710/4000] Training metric {'Train/mean dice_metric': 0.9987057447433472, 'Train/mean miou_metric': 0.9971392154693604, 'Train/mean f1': 0.993831217288971, 'Train/mean precision': 0.989359974861145, 'Train/mean recall': 0.9983431100845337, 'Train/mean hd95_metric': 0.5448517799377441} +Epoch [3710/4000] Validation [1/4] Loss: 0.48836 focal_loss 0.42346 dice_loss 0.06490 +Epoch [3710/4000] Validation [2/4] Loss: 0.60246 focal_loss 0.44690 dice_loss 0.15556 +Epoch [3710/4000] Validation [3/4] Loss: 0.55345 focal_loss 0.45788 dice_loss 0.09557 +Epoch [3710/4000] Validation [4/4] Loss: 0.45726 focal_loss 0.34405 dice_loss 0.11321 +Epoch [3710/4000] Validation metric {'Val/mean dice_metric': 0.9741262197494507, 'Val/mean miou_metric': 0.9601278305053711, 'Val/mean f1': 0.976738452911377, 'Val/mean precision': 0.9744617938995361, 'Val/mean recall': 0.9790257215499878, 'Val/mean hd95_metric': 4.789425849914551} +Cheakpoint... +Epoch [3710/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741262197494507, 'Val/mean miou_metric': 0.9601278305053711, 'Val/mean f1': 0.976738452911377, 'Val/mean precision': 0.9744617938995361, 'Val/mean recall': 0.9790257215499878, 'Val/mean hd95_metric': 4.789425849914551} +Epoch [3711/4000] Training [1/16] Loss: 0.00197 +Epoch [3711/4000] Training [2/16] Loss: 0.00307 +Epoch [3711/4000] Training [3/16] Loss: 0.00185 +Epoch [3711/4000] Training [4/16] Loss: 0.00208 +Epoch [3711/4000] Training [5/16] Loss: 0.00242 +Epoch [3711/4000] Training [6/16] Loss: 0.00312 +Epoch [3711/4000] Training [7/16] Loss: 0.00305 +Epoch [3711/4000] Training [8/16] Loss: 0.00238 +Epoch [3711/4000] Training [9/16] Loss: 0.00206 +Epoch [3711/4000] Training [10/16] Loss: 0.00175 +Epoch [3711/4000] Training [11/16] Loss: 0.00299 +Epoch [3711/4000] Training [12/16] Loss: 0.00219 +Epoch [3711/4000] Training [13/16] Loss: 0.00277 +Epoch [3711/4000] Training [14/16] Loss: 0.00235 +Epoch [3711/4000] Training [15/16] Loss: 0.00271 +Epoch [3711/4000] Training [16/16] Loss: 0.00291 +Epoch [3711/4000] Training metric {'Train/mean dice_metric': 0.9988516569137573, 'Train/mean miou_metric': 0.9974274635314941, 'Train/mean f1': 0.9938247799873352, 'Train/mean precision': 0.9893104434013367, 'Train/mean recall': 0.9983805418014526, 'Train/mean hd95_metric': 0.5351839065551758} +Epoch [3711/4000] Validation [1/4] Loss: 0.36425 focal_loss 0.30481 dice_loss 0.05944 +Epoch [3711/4000] Validation [2/4] Loss: 0.49212 focal_loss 0.38102 dice_loss 0.11109 +Epoch [3711/4000] Validation [3/4] Loss: 0.54486 focal_loss 0.45103 dice_loss 0.09383 +Epoch [3711/4000] Validation [4/4] Loss: 0.37462 focal_loss 0.28201 dice_loss 0.09262 +Epoch [3711/4000] Validation metric {'Val/mean dice_metric': 0.9752119779586792, 'Val/mean miou_metric': 0.9613860845565796, 'Val/mean f1': 0.9765579104423523, 'Val/mean precision': 0.9741432666778564, 'Val/mean recall': 0.9789845943450928, 'Val/mean hd95_metric': 5.1493377685546875} +Cheakpoint... +Epoch [3711/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752119779586792, 'Val/mean miou_metric': 0.9613860845565796, 'Val/mean f1': 0.9765579104423523, 'Val/mean precision': 0.9741432666778564, 'Val/mean recall': 0.9789845943450928, 'Val/mean hd95_metric': 5.1493377685546875} +Epoch [3712/4000] Training [1/16] Loss: 0.00285 +Epoch [3712/4000] Training [2/16] Loss: 0.00186 +Epoch [3712/4000] Training [3/16] Loss: 0.00188 +Epoch [3712/4000] Training [4/16] Loss: 0.00195 +Epoch [3712/4000] Training [5/16] Loss: 0.00201 +Epoch [3712/4000] Training [6/16] Loss: 0.00338 +Epoch [3712/4000] Training [7/16] Loss: 0.00257 +Epoch [3712/4000] Training [8/16] Loss: 0.00157 +Epoch [3712/4000] Training [9/16] Loss: 0.00262 +Epoch [3712/4000] Training [10/16] Loss: 0.00377 +Epoch [3712/4000] Training [11/16] Loss: 0.00257 +Epoch [3712/4000] Training [12/16] Loss: 0.00212 +Epoch [3712/4000] Training [13/16] Loss: 0.00276 +Epoch [3712/4000] Training [14/16] Loss: 0.00269 +Epoch [3712/4000] Training [15/16] Loss: 0.00247 +Epoch [3712/4000] Training [16/16] Loss: 0.00205 +Epoch [3712/4000] Training metric {'Train/mean dice_metric': 0.9987706542015076, 'Train/mean miou_metric': 0.9972676038742065, 'Train/mean f1': 0.9938005208969116, 'Train/mean precision': 0.9892949461936951, 'Train/mean recall': 0.998347282409668, 'Train/mean hd95_metric': 0.52317214012146} +Epoch [3712/4000] Validation [1/4] Loss: 0.39482 focal_loss 0.32944 dice_loss 0.06537 +Epoch [3712/4000] Validation [2/4] Loss: 0.94757 focal_loss 0.73888 dice_loss 0.20869 +Epoch [3712/4000] Validation [3/4] Loss: 0.55215 focal_loss 0.45809 dice_loss 0.09405 +Epoch [3712/4000] Validation [4/4] Loss: 0.37766 focal_loss 0.28899 dice_loss 0.08867 +Epoch [3712/4000] Validation metric {'Val/mean dice_metric': 0.9730926752090454, 'Val/mean miou_metric': 0.9593165516853333, 'Val/mean f1': 0.9757760763168335, 'Val/mean precision': 0.9739538431167603, 'Val/mean recall': 0.9776052236557007, 'Val/mean hd95_metric': 4.874764442443848} +Cheakpoint... +Epoch [3712/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730926752090454, 'Val/mean miou_metric': 0.9593165516853333, 'Val/mean f1': 0.9757760763168335, 'Val/mean precision': 0.9739538431167603, 'Val/mean recall': 0.9776052236557007, 'Val/mean hd95_metric': 4.874764442443848} +Epoch [3713/4000] Training [1/16] Loss: 0.00320 +Epoch [3713/4000] Training [2/16] Loss: 0.00151 +Epoch [3713/4000] Training [3/16] Loss: 0.00276 +Epoch [3713/4000] Training [4/16] Loss: 0.00254 +Epoch [3713/4000] Training [5/16] Loss: 0.00287 +Epoch [3713/4000] Training [6/16] Loss: 0.00212 +Epoch [3713/4000] Training [7/16] Loss: 0.00274 +Epoch [3713/4000] Training [8/16] Loss: 0.00284 +Epoch [3713/4000] Training [9/16] Loss: 0.00364 +Epoch [3713/4000] Training [10/16] Loss: 0.00265 +Epoch [3713/4000] Training [11/16] Loss: 0.00158 +Epoch [3713/4000] Training [12/16] Loss: 0.00165 +Epoch [3713/4000] Training [13/16] Loss: 0.00224 +Epoch [3713/4000] Training [14/16] Loss: 0.00229 +Epoch [3713/4000] Training [15/16] Loss: 0.00232 +Epoch [3713/4000] Training [16/16] Loss: 0.00231 +Epoch [3713/4000] Training metric {'Train/mean dice_metric': 0.9988480806350708, 'Train/mean miou_metric': 0.9974208474159241, 'Train/mean f1': 0.993843138217926, 'Train/mean precision': 0.9893198609352112, 'Train/mean recall': 0.9984079599380493, 'Train/mean hd95_metric': 0.4867463707923889} +Epoch [3713/4000] Validation [1/4] Loss: 0.38621 focal_loss 0.32487 dice_loss 0.06134 +Epoch [3713/4000] Validation [2/4] Loss: 0.50764 focal_loss 0.39574 dice_loss 0.11190 +Epoch [3713/4000] Validation [3/4] Loss: 0.28924 focal_loss 0.22314 dice_loss 0.06610 +Epoch [3713/4000] Validation [4/4] Loss: 0.37827 focal_loss 0.28281 dice_loss 0.09546 +Epoch [3713/4000] Validation metric {'Val/mean dice_metric': 0.9755035638809204, 'Val/mean miou_metric': 0.9616777300834656, 'Val/mean f1': 0.9769247174263, 'Val/mean precision': 0.9749499559402466, 'Val/mean recall': 0.9789074063301086, 'Val/mean hd95_metric': 4.67515230178833} +Cheakpoint... +Epoch [3713/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755035638809204, 'Val/mean miou_metric': 0.9616777300834656, 'Val/mean f1': 0.9769247174263, 'Val/mean precision': 0.9749499559402466, 'Val/mean recall': 0.9789074063301086, 'Val/mean hd95_metric': 4.67515230178833} +Epoch [3714/4000] Training [1/16] Loss: 0.00190 +Epoch [3714/4000] Training [2/16] Loss: 0.00186 +Epoch [3714/4000] Training [3/16] Loss: 0.00310 +Epoch [3714/4000] Training [4/16] Loss: 0.00408 +Epoch [3714/4000] Training [5/16] Loss: 0.00256 +Epoch [3714/4000] Training [6/16] Loss: 0.00256 +Epoch [3714/4000] Training [7/16] Loss: 0.00183 +Epoch [3714/4000] Training [8/16] Loss: 0.00320 +Epoch [3714/4000] Training [9/16] Loss: 0.00233 +Epoch [3714/4000] Training [10/16] Loss: 0.00186 +Epoch [3714/4000] Training [11/16] Loss: 0.00171 +Epoch [3714/4000] Training [12/16] Loss: 0.00277 +Epoch [3714/4000] Training [13/16] Loss: 0.00205 +Epoch [3714/4000] Training [14/16] Loss: 0.00186 +Epoch [3714/4000] Training [15/16] Loss: 0.00409 +Epoch [3714/4000] Training [16/16] Loss: 0.00342 +Epoch [3714/4000] Training metric {'Train/mean dice_metric': 0.998807966709137, 'Train/mean miou_metric': 0.9973337650299072, 'Train/mean f1': 0.9936974048614502, 'Train/mean precision': 0.9890297651290894, 'Train/mean recall': 0.9984092712402344, 'Train/mean hd95_metric': 0.5225862264633179} +Epoch [3714/4000] Validation [1/4] Loss: 0.36745 focal_loss 0.30936 dice_loss 0.05809 +Epoch [3714/4000] Validation [2/4] Loss: 0.86669 focal_loss 0.64766 dice_loss 0.21903 +Epoch [3714/4000] Validation [3/4] Loss: 0.57263 focal_loss 0.47403 dice_loss 0.09860 +Epoch [3714/4000] Validation [4/4] Loss: 0.40152 focal_loss 0.29823 dice_loss 0.10329 +Epoch [3714/4000] Validation metric {'Val/mean dice_metric': 0.9733812212944031, 'Val/mean miou_metric': 0.9592880010604858, 'Val/mean f1': 0.9759137034416199, 'Val/mean precision': 0.9736354947090149, 'Val/mean recall': 0.9782026410102844, 'Val/mean hd95_metric': 5.1600236892700195} +Cheakpoint... +Epoch [3714/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733812212944031, 'Val/mean miou_metric': 0.9592880010604858, 'Val/mean f1': 0.9759137034416199, 'Val/mean precision': 0.9736354947090149, 'Val/mean recall': 0.9782026410102844, 'Val/mean hd95_metric': 5.1600236892700195} +Epoch [3715/4000] Training [1/16] Loss: 0.00258 +Epoch [3715/4000] Training [2/16] Loss: 0.00208 +Epoch [3715/4000] Training [3/16] Loss: 0.00317 +Epoch [3715/4000] Training [4/16] Loss: 0.00208 +Epoch [3715/4000] Training [5/16] Loss: 0.00360 +Epoch [3715/4000] Training [6/16] Loss: 0.00277 +Epoch [3715/4000] Training [7/16] Loss: 0.00196 +Epoch [3715/4000] Training [8/16] Loss: 0.00191 +Epoch [3715/4000] Training [9/16] Loss: 0.00296 +Epoch [3715/4000] Training [10/16] Loss: 0.00234 +Epoch [3715/4000] Training [11/16] Loss: 0.00410 +Epoch [3715/4000] Training [12/16] Loss: 0.00333 +Epoch [3715/4000] Training [13/16] Loss: 0.00288 +Epoch [3715/4000] Training [14/16] Loss: 0.00450 +Epoch [3715/4000] Training [15/16] Loss: 0.00392 +Epoch [3715/4000] Training [16/16] Loss: 0.00198 +Epoch [3715/4000] Training metric {'Train/mean dice_metric': 0.9985818862915039, 'Train/mean miou_metric': 0.9968883991241455, 'Train/mean f1': 0.993625819683075, 'Train/mean precision': 0.9890642166137695, 'Train/mean recall': 0.9982296824455261, 'Train/mean hd95_metric': 0.523269772529602} +Epoch [3715/4000] Validation [1/4] Loss: 0.37182 focal_loss 0.31244 dice_loss 0.05938 +Epoch [3715/4000] Validation [2/4] Loss: 0.47835 focal_loss 0.36937 dice_loss 0.10898 +Epoch [3715/4000] Validation [3/4] Loss: 0.55047 focal_loss 0.44943 dice_loss 0.10104 +Epoch [3715/4000] Validation [4/4] Loss: 0.38794 focal_loss 0.29878 dice_loss 0.08917 +Epoch [3715/4000] Validation metric {'Val/mean dice_metric': 0.9749311208724976, 'Val/mean miou_metric': 0.9603663682937622, 'Val/mean f1': 0.9759456515312195, 'Val/mean precision': 0.9727914929389954, 'Val/mean recall': 0.9791203141212463, 'Val/mean hd95_metric': 5.408294200897217} +Cheakpoint... +Epoch [3715/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749311208724976, 'Val/mean miou_metric': 0.9603663682937622, 'Val/mean f1': 0.9759456515312195, 'Val/mean precision': 0.9727914929389954, 'Val/mean recall': 0.9791203141212463, 'Val/mean hd95_metric': 5.408294200897217} +Epoch [3716/4000] Training [1/16] Loss: 0.00219 +Epoch [3716/4000] Training [2/16] Loss: 0.00269 +Epoch [3716/4000] Training [3/16] Loss: 0.00193 +Epoch [3716/4000] Training [4/16] Loss: 0.00228 +Epoch [3716/4000] Training [5/16] Loss: 0.00290 +Epoch [3716/4000] Training [6/16] Loss: 0.00202 +Epoch [3716/4000] Training [7/16] Loss: 0.00307 +Epoch [3716/4000] Training [8/16] Loss: 0.00198 +Epoch [3716/4000] Training [9/16] Loss: 0.00235 +Epoch [3716/4000] Training [10/16] Loss: 0.00258 +Epoch [3716/4000] Training [11/16] Loss: 0.00162 +Epoch [3716/4000] Training [12/16] Loss: 0.00362 +Epoch [3716/4000] Training [13/16] Loss: 0.00287 +Epoch [3716/4000] Training [14/16] Loss: 0.00278 +Epoch [3716/4000] Training [15/16] Loss: 0.00231 +Epoch [3716/4000] Training [16/16] Loss: 0.00242 +Epoch [3716/4000] Training metric {'Train/mean dice_metric': 0.9987860321998596, 'Train/mean miou_metric': 0.9972996115684509, 'Train/mean f1': 0.9937446117401123, 'Train/mean precision': 0.9891852736473083, 'Train/mean recall': 0.9983461499214172, 'Train/mean hd95_metric': 0.5236603021621704} +Epoch [3716/4000] Validation [1/4] Loss: 0.41928 focal_loss 0.35510 dice_loss 0.06418 +Epoch [3716/4000] Validation [2/4] Loss: 0.66677 focal_loss 0.49332 dice_loss 0.17346 +Epoch [3716/4000] Validation [3/4] Loss: 0.54991 focal_loss 0.45588 dice_loss 0.09404 +Epoch [3716/4000] Validation [4/4] Loss: 0.37513 focal_loss 0.28173 dice_loss 0.09340 +Epoch [3716/4000] Validation metric {'Val/mean dice_metric': 0.9750066995620728, 'Val/mean miou_metric': 0.9605430364608765, 'Val/mean f1': 0.9757307767868042, 'Val/mean precision': 0.9736739993095398, 'Val/mean recall': 0.977796196937561, 'Val/mean hd95_metric': 5.120530128479004} +Cheakpoint... +Epoch [3716/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750066995620728, 'Val/mean miou_metric': 0.9605430364608765, 'Val/mean f1': 0.9757307767868042, 'Val/mean precision': 0.9736739993095398, 'Val/mean recall': 0.977796196937561, 'Val/mean hd95_metric': 5.120530128479004} +Epoch [3717/4000] Training [1/16] Loss: 0.00287 +Epoch [3717/4000] Training [2/16] Loss: 0.00216 +Epoch [3717/4000] Training [3/16] Loss: 0.00240 +Epoch [3717/4000] Training [4/16] Loss: 0.00237 +Epoch [3717/4000] Training [5/16] Loss: 0.00173 +Epoch [3717/4000] Training [6/16] Loss: 0.00218 +Epoch [3717/4000] Training [7/16] Loss: 0.00230 +Epoch [3717/4000] Training [8/16] Loss: 0.00233 +Epoch [3717/4000] Training [9/16] Loss: 0.00481 +Epoch [3717/4000] Training [10/16] Loss: 0.00181 +Epoch [3717/4000] Training [11/16] Loss: 0.00244 +Epoch [3717/4000] Training [12/16] Loss: 0.00342 +Epoch [3717/4000] Training [13/16] Loss: 0.00214 +Epoch [3717/4000] Training [14/16] Loss: 0.00269 +Epoch [3717/4000] Training [15/16] Loss: 0.00264 +Epoch [3717/4000] Training [16/16] Loss: 0.00267 +Epoch [3717/4000] Training metric {'Train/mean dice_metric': 0.9987366795539856, 'Train/mean miou_metric': 0.9971897602081299, 'Train/mean f1': 0.9935903549194336, 'Train/mean precision': 0.9889445304870605, 'Train/mean recall': 0.9982799887657166, 'Train/mean hd95_metric': 0.5524689555168152} +Epoch [3717/4000] Validation [1/4] Loss: 0.40653 focal_loss 0.34486 dice_loss 0.06168 +Epoch [3717/4000] Validation [2/4] Loss: 0.96763 focal_loss 0.78053 dice_loss 0.18710 +Epoch [3717/4000] Validation [3/4] Loss: 0.53738 focal_loss 0.44198 dice_loss 0.09540 +Epoch [3717/4000] Validation [4/4] Loss: 0.35137 focal_loss 0.26063 dice_loss 0.09074 +Epoch [3717/4000] Validation metric {'Val/mean dice_metric': 0.974368691444397, 'Val/mean miou_metric': 0.9603394269943237, 'Val/mean f1': 0.9763200879096985, 'Val/mean precision': 0.9743073582649231, 'Val/mean recall': 0.9783412218093872, 'Val/mean hd95_metric': 4.729923248291016} +Cheakpoint... +Epoch [3717/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974368691444397, 'Val/mean miou_metric': 0.9603394269943237, 'Val/mean f1': 0.9763200879096985, 'Val/mean precision': 0.9743073582649231, 'Val/mean recall': 0.9783412218093872, 'Val/mean hd95_metric': 4.729923248291016} +Epoch [3718/4000] Training [1/16] Loss: 0.00165 +Epoch [3718/4000] Training [2/16] Loss: 0.00207 +Epoch [3718/4000] Training [3/16] Loss: 0.00249 +Epoch [3718/4000] Training [4/16] Loss: 0.00331 +Epoch [3718/4000] Training [5/16] Loss: 0.00186 +Epoch [3718/4000] Training [6/16] Loss: 0.00242 +Epoch [3718/4000] Training [7/16] Loss: 0.00240 +Epoch [3718/4000] Training [8/16] Loss: 0.00249 +Epoch [3718/4000] Training [9/16] Loss: 0.00190 +Epoch [3718/4000] Training [10/16] Loss: 0.00176 +Epoch [3718/4000] Training [11/16] Loss: 0.00254 +Epoch [3718/4000] Training [12/16] Loss: 0.00302 +Epoch [3718/4000] Training [13/16] Loss: 0.00194 +Epoch [3718/4000] Training [14/16] Loss: 0.00206 +Epoch [3718/4000] Training [15/16] Loss: 0.00197 +Epoch [3718/4000] Training [16/16] Loss: 0.00282 +Epoch [3718/4000] Training metric {'Train/mean dice_metric': 0.9988501071929932, 'Train/mean miou_metric': 0.9974241256713867, 'Train/mean f1': 0.9938809275627136, 'Train/mean precision': 0.9893643260002136, 'Train/mean recall': 0.9984390139579773, 'Train/mean hd95_metric': 0.5382111668586731} +Epoch [3718/4000] Validation [1/4] Loss: 0.44631 focal_loss 0.38021 dice_loss 0.06610 +Epoch [3718/4000] Validation [2/4] Loss: 1.42329 focal_loss 1.13505 dice_loss 0.28825 +Epoch [3718/4000] Validation [3/4] Loss: 0.26964 focal_loss 0.20751 dice_loss 0.06213 +Epoch [3718/4000] Validation [4/4] Loss: 0.34107 focal_loss 0.26028 dice_loss 0.08079 +Epoch [3718/4000] Validation metric {'Val/mean dice_metric': 0.9722196459770203, 'Val/mean miou_metric': 0.9587633013725281, 'Val/mean f1': 0.9757235646247864, 'Val/mean precision': 0.9744149446487427, 'Val/mean recall': 0.9770358204841614, 'Val/mean hd95_metric': 4.812473773956299} +Cheakpoint... +Epoch [3718/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722196459770203, 'Val/mean miou_metric': 0.9587633013725281, 'Val/mean f1': 0.9757235646247864, 'Val/mean precision': 0.9744149446487427, 'Val/mean recall': 0.9770358204841614, 'Val/mean hd95_metric': 4.812473773956299} +Epoch [3719/4000] Training [1/16] Loss: 0.00189 +Epoch [3719/4000] Training [2/16] Loss: 0.00257 +Epoch [3719/4000] Training [3/16] Loss: 0.00191 +Epoch [3719/4000] Training [4/16] Loss: 0.00317 +Epoch [3719/4000] Training [5/16] Loss: 0.00169 +Epoch [3719/4000] Training [6/16] Loss: 0.00156 +Epoch [3719/4000] Training [7/16] Loss: 0.00193 +Epoch [3719/4000] Training [8/16] Loss: 0.00308 +Epoch [3719/4000] Training [9/16] Loss: 0.00177 +Epoch [3719/4000] Training [10/16] Loss: 0.00228 +Epoch [3719/4000] Training [11/16] Loss: 0.00213 +Epoch [3719/4000] Training [12/16] Loss: 0.00310 +Epoch [3719/4000] Training [13/16] Loss: 0.00184 +Epoch [3719/4000] Training [14/16] Loss: 0.00387 +Epoch [3719/4000] Training [15/16] Loss: 0.00178 +Epoch [3719/4000] Training [16/16] Loss: 0.00239 +Epoch [3719/4000] Training metric {'Train/mean dice_metric': 0.9988627433776855, 'Train/mean miou_metric': 0.9974163770675659, 'Train/mean f1': 0.9931204915046692, 'Train/mean precision': 0.9879324436187744, 'Train/mean recall': 0.9983632564544678, 'Train/mean hd95_metric': 0.4866763949394226} +Epoch [3719/4000] Validation [1/4] Loss: 0.39392 focal_loss 0.33042 dice_loss 0.06351 +Epoch [3719/4000] Validation [2/4] Loss: 0.51741 focal_loss 0.40153 dice_loss 0.11588 +Epoch [3719/4000] Validation [3/4] Loss: 0.28932 focal_loss 0.22388 dice_loss 0.06545 +Epoch [3719/4000] Validation [4/4] Loss: 0.42473 focal_loss 0.31355 dice_loss 0.11118 +Epoch [3719/4000] Validation metric {'Val/mean dice_metric': 0.9749299883842468, 'Val/mean miou_metric': 0.9610263705253601, 'Val/mean f1': 0.9763351678848267, 'Val/mean precision': 0.97389155626297, 'Val/mean recall': 0.9787912964820862, 'Val/mean hd95_metric': 4.695748805999756} +Cheakpoint... +Epoch [3719/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749299883842468, 'Val/mean miou_metric': 0.9610263705253601, 'Val/mean f1': 0.9763351678848267, 'Val/mean precision': 0.97389155626297, 'Val/mean recall': 0.9787912964820862, 'Val/mean hd95_metric': 4.695748805999756} +Epoch [3720/4000] Training [1/16] Loss: 0.00169 +Epoch [3720/4000] Training [2/16] Loss: 0.00222 +Epoch [3720/4000] Training [3/16] Loss: 0.00249 +Epoch [3720/4000] Training [4/16] Loss: 0.00218 +Epoch [3720/4000] Training [5/16] Loss: 0.00259 +Epoch [3720/4000] Training [6/16] Loss: 0.00227 +Epoch [3720/4000] Training [7/16] Loss: 0.00191 +Epoch [3720/4000] Training [8/16] Loss: 0.00225 +Epoch [3720/4000] Training [9/16] Loss: 0.00280 +Epoch [3720/4000] Training [10/16] Loss: 0.00307 +Epoch [3720/4000] Training [11/16] Loss: 0.00171 +Epoch [3720/4000] Training [12/16] Loss: 0.00219 +Epoch [3720/4000] Training [13/16] Loss: 0.00209 +Epoch [3720/4000] Training [14/16] Loss: 0.00213 +Epoch [3720/4000] Training [15/16] Loss: 0.00387 +Epoch [3720/4000] Training [16/16] Loss: 0.00244 +Epoch [3720/4000] Training metric {'Train/mean dice_metric': 0.9987958073616028, 'Train/mean miou_metric': 0.9973185062408447, 'Train/mean f1': 0.9937708973884583, 'Train/mean precision': 0.9891987442970276, 'Train/mean recall': 0.998385488986969, 'Train/mean hd95_metric': 0.4828401505947113} +Epoch [3720/4000] Validation [1/4] Loss: 0.50333 focal_loss 0.42659 dice_loss 0.07674 +Epoch [3720/4000] Validation [2/4] Loss: 0.58725 focal_loss 0.43595 dice_loss 0.15131 +Epoch [3720/4000] Validation [3/4] Loss: 0.54046 focal_loss 0.44467 dice_loss 0.09579 +Epoch [3720/4000] Validation [4/4] Loss: 0.35631 focal_loss 0.26830 dice_loss 0.08801 +Epoch [3720/4000] Validation metric {'Val/mean dice_metric': 0.9733307957649231, 'Val/mean miou_metric': 0.9596338272094727, 'Val/mean f1': 0.9758465886116028, 'Val/mean precision': 0.9740186929702759, 'Val/mean recall': 0.9776813983917236, 'Val/mean hd95_metric': 4.766047954559326} +Cheakpoint... +Epoch [3720/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733307957649231, 'Val/mean miou_metric': 0.9596338272094727, 'Val/mean f1': 0.9758465886116028, 'Val/mean precision': 0.9740186929702759, 'Val/mean recall': 0.9776813983917236, 'Val/mean hd95_metric': 4.766047954559326} +Epoch [3721/4000] Training [1/16] Loss: 0.00310 +Epoch [3721/4000] Training [2/16] Loss: 0.00206 +Epoch [3721/4000] Training [3/16] Loss: 0.00214 +Epoch [3721/4000] Training [4/16] Loss: 0.00192 +Epoch [3721/4000] Training [5/16] Loss: 0.00179 +Epoch [3721/4000] Training [6/16] Loss: 0.00204 +Epoch [3721/4000] Training [7/16] Loss: 0.00232 +Epoch [3721/4000] Training [8/16] Loss: 0.00278 +Epoch [3721/4000] Training [9/16] Loss: 0.00269 +Epoch [3721/4000] Training [10/16] Loss: 0.00198 +Epoch [3721/4000] Training [11/16] Loss: 0.00226 +Epoch [3721/4000] Training [12/16] Loss: 0.00288 +Epoch [3721/4000] Training [13/16] Loss: 0.00226 +Epoch [3721/4000] Training [14/16] Loss: 0.00212 +Epoch [3721/4000] Training [15/16] Loss: 0.00254 +Epoch [3721/4000] Training [16/16] Loss: 0.00273 +Epoch [3721/4000] Training metric {'Train/mean dice_metric': 0.9989299178123474, 'Train/mean miou_metric': 0.9975776672363281, 'Train/mean f1': 0.9937858581542969, 'Train/mean precision': 0.9891438484191895, 'Train/mean recall': 0.9984716176986694, 'Train/mean hd95_metric': 0.49631667137145996} +Epoch [3721/4000] Validation [1/4] Loss: 0.46032 focal_loss 0.39691 dice_loss 0.06341 +Epoch [3721/4000] Validation [2/4] Loss: 1.31264 focal_loss 1.02349 dice_loss 0.28914 +Epoch [3721/4000] Validation [3/4] Loss: 0.28522 focal_loss 0.22051 dice_loss 0.06471 +Epoch [3721/4000] Validation [4/4] Loss: 0.46436 focal_loss 0.35383 dice_loss 0.11053 +Epoch [3721/4000] Validation metric {'Val/mean dice_metric': 0.9732826948165894, 'Val/mean miou_metric': 0.9598255157470703, 'Val/mean f1': 0.9762327075004578, 'Val/mean precision': 0.9739956855773926, 'Val/mean recall': 0.9784799814224243, 'Val/mean hd95_metric': 4.807789325714111} +Cheakpoint... +Epoch [3721/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732826948165894, 'Val/mean miou_metric': 0.9598255157470703, 'Val/mean f1': 0.9762327075004578, 'Val/mean precision': 0.9739956855773926, 'Val/mean recall': 0.9784799814224243, 'Val/mean hd95_metric': 4.807789325714111} +Epoch [3722/4000] Training [1/16] Loss: 0.00282 +Epoch [3722/4000] Training [2/16] Loss: 0.00340 +Epoch [3722/4000] Training [3/16] Loss: 0.00332 +Epoch [3722/4000] Training [4/16] Loss: 0.00231 +Epoch [3722/4000] Training [5/16] Loss: 0.00249 +Epoch [3722/4000] Training [6/16] Loss: 0.00376 +Epoch [3722/4000] Training [7/16] Loss: 0.00223 +Epoch [3722/4000] Training [8/16] Loss: 0.00207 +Epoch [3722/4000] Training [9/16] Loss: 0.00179 +Epoch [3722/4000] Training [10/16] Loss: 0.00255 +Epoch [3722/4000] Training [11/16] Loss: 0.00280 +Epoch [3722/4000] Training [12/16] Loss: 0.00294 +Epoch [3722/4000] Training [13/16] Loss: 0.00218 +Epoch [3722/4000] Training [14/16] Loss: 0.00202 +Epoch [3722/4000] Training [15/16] Loss: 0.00259 +Epoch [3722/4000] Training [16/16] Loss: 0.00222 +Epoch [3722/4000] Training metric {'Train/mean dice_metric': 0.9986059069633484, 'Train/mean miou_metric': 0.9969184398651123, 'Train/mean f1': 0.9933289885520935, 'Train/mean precision': 0.9884592890739441, 'Train/mean recall': 0.9982469081878662, 'Train/mean hd95_metric': 0.6842420101165771} +Epoch [3722/4000] Validation [1/4] Loss: 0.47431 focal_loss 0.40973 dice_loss 0.06458 +Epoch [3722/4000] Validation [2/4] Loss: 0.59860 focal_loss 0.44386 dice_loss 0.15474 +Epoch [3722/4000] Validation [3/4] Loss: 0.53459 focal_loss 0.44278 dice_loss 0.09181 +Epoch [3722/4000] Validation [4/4] Loss: 0.48664 focal_loss 0.37301 dice_loss 0.11363 +Epoch [3722/4000] Validation metric {'Val/mean dice_metric': 0.9735520482063293, 'Val/mean miou_metric': 0.9592477083206177, 'Val/mean f1': 0.9756292700767517, 'Val/mean precision': 0.9731010794639587, 'Val/mean recall': 0.97817063331604, 'Val/mean hd95_metric': 5.148342132568359} +Cheakpoint... +Epoch [3722/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735520482063293, 'Val/mean miou_metric': 0.9592477083206177, 'Val/mean f1': 0.9756292700767517, 'Val/mean precision': 0.9731010794639587, 'Val/mean recall': 0.97817063331604, 'Val/mean hd95_metric': 5.148342132568359} +Epoch [3723/4000] Training [1/16] Loss: 0.00250 +Epoch [3723/4000] Training [2/16] Loss: 0.00227 +Epoch [3723/4000] Training [3/16] Loss: 0.00231 +Epoch [3723/4000] Training [4/16] Loss: 0.00209 +Epoch [3723/4000] Training [5/16] Loss: 0.00276 +Epoch [3723/4000] Training [6/16] Loss: 0.00183 +Epoch [3723/4000] Training [7/16] Loss: 0.00198 +Epoch [3723/4000] Training [8/16] Loss: 0.00201 +Epoch [3723/4000] Training [9/16] Loss: 0.00150 +Epoch [3723/4000] Training [10/16] Loss: 0.00298 +Epoch [3723/4000] Training [11/16] Loss: 0.00181 +Epoch [3723/4000] Training [12/16] Loss: 0.00202 +Epoch [3723/4000] Training [13/16] Loss: 0.00152 +Epoch [3723/4000] Training [14/16] Loss: 0.00505 +Epoch [3723/4000] Training [15/16] Loss: 0.00253 +Epoch [3723/4000] Training [16/16] Loss: 0.00191 +Epoch [3723/4000] Training metric {'Train/mean dice_metric': 0.9988170862197876, 'Train/mean miou_metric': 0.997337818145752, 'Train/mean f1': 0.9935830235481262, 'Train/mean precision': 0.9888889789581299, 'Train/mean recall': 0.9983218312263489, 'Train/mean hd95_metric': 0.4984378218650818} +Epoch [3723/4000] Validation [1/4] Loss: 0.38888 focal_loss 0.32723 dice_loss 0.06165 +Epoch [3723/4000] Validation [2/4] Loss: 0.49013 focal_loss 0.37934 dice_loss 0.11079 +Epoch [3723/4000] Validation [3/4] Loss: 0.26596 focal_loss 0.20597 dice_loss 0.05999 +Epoch [3723/4000] Validation [4/4] Loss: 0.49853 focal_loss 0.37611 dice_loss 0.12242 +Epoch [3723/4000] Validation metric {'Val/mean dice_metric': 0.9765388369560242, 'Val/mean miou_metric': 0.9624532461166382, 'Val/mean f1': 0.9770523309707642, 'Val/mean precision': 0.9746610522270203, 'Val/mean recall': 0.9794555306434631, 'Val/mean hd95_metric': 4.660030364990234} +Cheakpoint... +Epoch [3723/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9765], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9765388369560242, 'Val/mean miou_metric': 0.9624532461166382, 'Val/mean f1': 0.9770523309707642, 'Val/mean precision': 0.9746610522270203, 'Val/mean recall': 0.9794555306434631, 'Val/mean hd95_metric': 4.660030364990234} +Epoch [3724/4000] Training [1/16] Loss: 0.00386 +Epoch [3724/4000] Training [2/16] Loss: 0.00466 +Epoch [3724/4000] Training [3/16] Loss: 0.00324 +Epoch [3724/4000] Training [4/16] Loss: 0.00195 +Epoch [3724/4000] Training [5/16] Loss: 0.00285 +Epoch [3724/4000] Training [6/16] Loss: 0.00175 +Epoch [3724/4000] Training [7/16] Loss: 0.00420 +Epoch [3724/4000] Training [8/16] Loss: 0.00266 +Epoch [3724/4000] Training [9/16] Loss: 0.00227 +Epoch [3724/4000] Training [10/16] Loss: 0.00270 +Epoch [3724/4000] Training [11/16] Loss: 0.00155 +Epoch [3724/4000] Training [12/16] Loss: 0.00288 +Epoch [3724/4000] Training [13/16] Loss: 0.00176 +Epoch [3724/4000] Training [14/16] Loss: 0.00395 +Epoch [3724/4000] Training [15/16] Loss: 0.00227 +Epoch [3724/4000] Training [16/16] Loss: 0.00268 +Epoch [3724/4000] Training metric {'Train/mean dice_metric': 0.9986305832862854, 'Train/mean miou_metric': 0.996954083442688, 'Train/mean f1': 0.9928833246231079, 'Train/mean precision': 0.9876720905303955, 'Train/mean recall': 0.9981498718261719, 'Train/mean hd95_metric': 0.5661407709121704} +Epoch [3724/4000] Validation [1/4] Loss: 0.38027 focal_loss 0.31687 dice_loss 0.06339 +Epoch [3724/4000] Validation [2/4] Loss: 1.42152 focal_loss 1.13788 dice_loss 0.28365 +Epoch [3724/4000] Validation [3/4] Loss: 0.27457 focal_loss 0.21258 dice_loss 0.06200 +Epoch [3724/4000] Validation [4/4] Loss: 0.52733 focal_loss 0.40681 dice_loss 0.12052 +Epoch [3724/4000] Validation metric {'Val/mean dice_metric': 0.9714605212211609, 'Val/mean miou_metric': 0.9579784274101257, 'Val/mean f1': 0.9748489260673523, 'Val/mean precision': 0.9726116061210632, 'Val/mean recall': 0.9770964980125427, 'Val/mean hd95_metric': 5.189177513122559} +Cheakpoint... +Epoch [3724/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9715], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9714605212211609, 'Val/mean miou_metric': 0.9579784274101257, 'Val/mean f1': 0.9748489260673523, 'Val/mean precision': 0.9726116061210632, 'Val/mean recall': 0.9770964980125427, 'Val/mean hd95_metric': 5.189177513122559} +Epoch [3725/4000] Training [1/16] Loss: 0.00232 +Epoch [3725/4000] Training [2/16] Loss: 0.00184 +Epoch [3725/4000] Training [3/16] Loss: 0.00303 +Epoch [3725/4000] Training [4/16] Loss: 0.00343 +Epoch [3725/4000] Training [5/16] Loss: 0.00239 +Epoch [3725/4000] Training [6/16] Loss: 0.00243 +Epoch [3725/4000] Training [7/16] Loss: 0.00143 +Epoch [3725/4000] Training [8/16] Loss: 0.00250 +Epoch [3725/4000] Training [9/16] Loss: 0.00254 +Epoch [3725/4000] Training [10/16] Loss: 0.00237 +Epoch [3725/4000] Training [11/16] Loss: 0.00275 +Epoch [3725/4000] Training [12/16] Loss: 0.00242 +Epoch [3725/4000] Training [13/16] Loss: 0.00229 +Epoch [3725/4000] Training [14/16] Loss: 0.00187 +Epoch [3725/4000] Training [15/16] Loss: 0.00251 +Epoch [3725/4000] Training [16/16] Loss: 0.00220 +Epoch [3725/4000] Training metric {'Train/mean dice_metric': 0.9988468885421753, 'Train/mean miou_metric': 0.9974197149276733, 'Train/mean f1': 0.9938903450965881, 'Train/mean precision': 0.9893838167190552, 'Train/mean recall': 0.9984381794929504, 'Train/mean hd95_metric': 0.5085234642028809} +Epoch [3725/4000] Validation [1/4] Loss: 0.46682 focal_loss 0.40172 dice_loss 0.06510 +Epoch [3725/4000] Validation [2/4] Loss: 0.96200 focal_loss 0.77745 dice_loss 0.18455 +Epoch [3725/4000] Validation [3/4] Loss: 0.52932 focal_loss 0.43369 dice_loss 0.09563 +Epoch [3725/4000] Validation [4/4] Loss: 0.47294 focal_loss 0.35185 dice_loss 0.12109 +Epoch [3725/4000] Validation metric {'Val/mean dice_metric': 0.9741302728652954, 'Val/mean miou_metric': 0.9604686498641968, 'Val/mean f1': 0.9765419363975525, 'Val/mean precision': 0.974288821220398, 'Val/mean recall': 0.978805422782898, 'Val/mean hd95_metric': 4.796876430511475} +Cheakpoint... +Epoch [3725/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741302728652954, 'Val/mean miou_metric': 0.9604686498641968, 'Val/mean f1': 0.9765419363975525, 'Val/mean precision': 0.974288821220398, 'Val/mean recall': 0.978805422782898, 'Val/mean hd95_metric': 4.796876430511475} +Epoch [3726/4000] Training [1/16] Loss: 0.00327 +Epoch [3726/4000] Training [2/16] Loss: 0.00392 +Epoch [3726/4000] Training [3/16] Loss: 0.00265 +Epoch [3726/4000] Training [4/16] Loss: 0.00363 +Epoch [3726/4000] Training [5/16] Loss: 0.00318 +Epoch [3726/4000] Training [6/16] Loss: 0.00314 +Epoch [3726/4000] Training [7/16] Loss: 0.00337 +Epoch [3726/4000] Training [8/16] Loss: 0.00265 +Epoch [3726/4000] Training [9/16] Loss: 0.00286 +Epoch [3726/4000] Training [10/16] Loss: 0.00227 +Epoch [3726/4000] Training [11/16] Loss: 0.00144 +Epoch [3726/4000] Training [12/16] Loss: 0.00205 +Epoch [3726/4000] Training [13/16] Loss: 0.00206 +Epoch [3726/4000] Training [14/16] Loss: 0.00210 +Epoch [3726/4000] Training [15/16] Loss: 0.00237 +Epoch [3726/4000] Training [16/16] Loss: 0.00222 +Epoch [3726/4000] Training metric {'Train/mean dice_metric': 0.9986521005630493, 'Train/mean miou_metric': 0.9970210790634155, 'Train/mean f1': 0.993441104888916, 'Train/mean precision': 0.9887126684188843, 'Train/mean recall': 0.9982149600982666, 'Train/mean hd95_metric': 0.5531526803970337} +Epoch [3726/4000] Validation [1/4] Loss: 0.35094 focal_loss 0.29218 dice_loss 0.05877 +Epoch [3726/4000] Validation [2/4] Loss: 1.55073 focal_loss 1.26826 dice_loss 0.28247 +Epoch [3726/4000] Validation [3/4] Loss: 0.54729 focal_loss 0.45492 dice_loss 0.09237 +Epoch [3726/4000] Validation [4/4] Loss: 0.47150 focal_loss 0.36689 dice_loss 0.10461 +Epoch [3726/4000] Validation metric {'Val/mean dice_metric': 0.9735159873962402, 'Val/mean miou_metric': 0.9594195485115051, 'Val/mean f1': 0.9758337736129761, 'Val/mean precision': 0.973509669303894, 'Val/mean recall': 0.9781689643859863, 'Val/mean hd95_metric': 4.781160354614258} +Cheakpoint... +Epoch [3726/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735159873962402, 'Val/mean miou_metric': 0.9594195485115051, 'Val/mean f1': 0.9758337736129761, 'Val/mean precision': 0.973509669303894, 'Val/mean recall': 0.9781689643859863, 'Val/mean hd95_metric': 4.781160354614258} +Epoch [3727/4000] Training [1/16] Loss: 0.00331 +Epoch [3727/4000] Training [2/16] Loss: 0.00188 +Epoch [3727/4000] Training [3/16] Loss: 0.00485 +Epoch [3727/4000] Training [4/16] Loss: 0.00186 +Epoch [3727/4000] Training [5/16] Loss: 0.00350 +Epoch [3727/4000] Training [6/16] Loss: 0.00196 +Epoch [3727/4000] Training [7/16] Loss: 0.00231 +Epoch [3727/4000] Training [8/16] Loss: 0.00351 +Epoch [3727/4000] Training [9/16] Loss: 0.00416 +Epoch [3727/4000] Training [10/16] Loss: 0.00201 +Epoch [3727/4000] Training [11/16] Loss: 0.00309 +Epoch [3727/4000] Training [12/16] Loss: 0.00312 +Epoch [3727/4000] Training [13/16] Loss: 0.00215 +Epoch [3727/4000] Training [14/16] Loss: 0.00128 +Epoch [3727/4000] Training [15/16] Loss: 0.00210 +Epoch [3727/4000] Training [16/16] Loss: 0.00215 +Epoch [3727/4000] Training metric {'Train/mean dice_metric': 0.9987667798995972, 'Train/mean miou_metric': 0.9972325563430786, 'Train/mean f1': 0.9932550191879272, 'Train/mean precision': 0.9882634878158569, 'Train/mean recall': 0.9982972741127014, 'Train/mean hd95_metric': 0.5361882448196411} +Epoch [3727/4000] Validation [1/4] Loss: 0.41907 focal_loss 0.35144 dice_loss 0.06763 +Epoch [3727/4000] Validation [2/4] Loss: 0.51855 focal_loss 0.40426 dice_loss 0.11429 +Epoch [3727/4000] Validation [3/4] Loss: 0.29072 focal_loss 0.22434 dice_loss 0.06638 +Epoch [3727/4000] Validation [4/4] Loss: 0.36388 focal_loss 0.27522 dice_loss 0.08867 +Epoch [3727/4000] Validation metric {'Val/mean dice_metric': 0.9748700261116028, 'Val/mean miou_metric': 0.9605873227119446, 'Val/mean f1': 0.976290225982666, 'Val/mean precision': 0.9740175604820251, 'Val/mean recall': 0.9785735011100769, 'Val/mean hd95_metric': 5.121090888977051} +Cheakpoint... +Epoch [3727/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748700261116028, 'Val/mean miou_metric': 0.9605873227119446, 'Val/mean f1': 0.976290225982666, 'Val/mean precision': 0.9740175604820251, 'Val/mean recall': 0.9785735011100769, 'Val/mean hd95_metric': 5.121090888977051} +Epoch [3728/4000] Training [1/16] Loss: 0.00211 +Epoch [3728/4000] Training [2/16] Loss: 0.00198 +Epoch [3728/4000] Training [3/16] Loss: 0.00323 +Epoch [3728/4000] Training [4/16] Loss: 0.00278 +Epoch [3728/4000] Training [5/16] Loss: 0.00332 +Epoch [3728/4000] Training [6/16] Loss: 0.00215 +Epoch [3728/4000] Training [7/16] Loss: 0.00254 +Epoch [3728/4000] Training [8/16] Loss: 0.00151 +Epoch [3728/4000] Training [9/16] Loss: 0.00177 +Epoch [3728/4000] Training [10/16] Loss: 0.00244 +Epoch [3728/4000] Training [11/16] Loss: 0.00210 +Epoch [3728/4000] Training [12/16] Loss: 0.00196 +Epoch [3728/4000] Training [13/16] Loss: 0.00490 +Epoch [3728/4000] Training [14/16] Loss: 0.00206 +Epoch [3728/4000] Training [15/16] Loss: 0.00224 +Epoch [3728/4000] Training [16/16] Loss: 0.00319 +Epoch [3728/4000] Training metric {'Train/mean dice_metric': 0.9988093376159668, 'Train/mean miou_metric': 0.9973419904708862, 'Train/mean f1': 0.9937582612037659, 'Train/mean precision': 0.9891045689582825, 'Train/mean recall': 0.9984560012817383, 'Train/mean hd95_metric': 0.49052712321281433} +Epoch [3728/4000] Validation [1/4] Loss: 0.50365 focal_loss 0.42053 dice_loss 0.08312 +Epoch [3728/4000] Validation [2/4] Loss: 0.51457 focal_loss 0.39936 dice_loss 0.11521 +Epoch [3728/4000] Validation [3/4] Loss: 0.27006 focal_loss 0.20842 dice_loss 0.06164 +Epoch [3728/4000] Validation [4/4] Loss: 0.29378 focal_loss 0.21205 dice_loss 0.08172 +Epoch [3728/4000] Validation metric {'Val/mean dice_metric': 0.9754959940910339, 'Val/mean miou_metric': 0.9612592458724976, 'Val/mean f1': 0.9767118692398071, 'Val/mean precision': 0.9750301837921143, 'Val/mean recall': 0.978399395942688, 'Val/mean hd95_metric': 4.602337837219238} +Cheakpoint... +Epoch [3728/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754959940910339, 'Val/mean miou_metric': 0.9612592458724976, 'Val/mean f1': 0.9767118692398071, 'Val/mean precision': 0.9750301837921143, 'Val/mean recall': 0.978399395942688, 'Val/mean hd95_metric': 4.602337837219238} +Epoch [3729/4000] Training [1/16] Loss: 0.00223 +Epoch [3729/4000] Training [2/16] Loss: 0.00182 +Epoch [3729/4000] Training [3/16] Loss: 0.00244 +Epoch [3729/4000] Training [4/16] Loss: 0.00243 +Epoch [3729/4000] Training [5/16] Loss: 0.00162 +Epoch [3729/4000] Training [6/16] Loss: 0.00155 +Epoch [3729/4000] Training [7/16] Loss: 0.00212 +Epoch [3729/4000] Training [8/16] Loss: 0.00155 +Epoch [3729/4000] Training [9/16] Loss: 0.00345 +Epoch [3729/4000] Training [10/16] Loss: 0.00241 +Epoch [3729/4000] Training [11/16] Loss: 0.00340 +Epoch [3729/4000] Training [12/16] Loss: 0.00257 +Epoch [3729/4000] Training [13/16] Loss: 0.00216 +Epoch [3729/4000] Training [14/16] Loss: 0.00384 +Epoch [3729/4000] Training [15/16] Loss: 0.00402 +Epoch [3729/4000] Training [16/16] Loss: 0.00249 +Epoch [3729/4000] Training metric {'Train/mean dice_metric': 0.9988021850585938, 'Train/mean miou_metric': 0.9973311424255371, 'Train/mean f1': 0.9937482476234436, 'Train/mean precision': 0.9891795516014099, 'Train/mean recall': 0.9983593821525574, 'Train/mean hd95_metric': 0.48723459243774414} +Epoch [3729/4000] Validation [1/4] Loss: 0.40234 focal_loss 0.33891 dice_loss 0.06343 +Epoch [3729/4000] Validation [2/4] Loss: 0.98029 focal_loss 0.71016 dice_loss 0.27013 +Epoch [3729/4000] Validation [3/4] Loss: 0.55001 focal_loss 0.45316 dice_loss 0.09685 +Epoch [3729/4000] Validation [4/4] Loss: 0.52450 focal_loss 0.40728 dice_loss 0.11722 +Epoch [3729/4000] Validation metric {'Val/mean dice_metric': 0.9721633791923523, 'Val/mean miou_metric': 0.9580084085464478, 'Val/mean f1': 0.9750954508781433, 'Val/mean precision': 0.9729449152946472, 'Val/mean recall': 0.9772557020187378, 'Val/mean hd95_metric': 5.078238487243652} +Cheakpoint... +Epoch [3729/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721633791923523, 'Val/mean miou_metric': 0.9580084085464478, 'Val/mean f1': 0.9750954508781433, 'Val/mean precision': 0.9729449152946472, 'Val/mean recall': 0.9772557020187378, 'Val/mean hd95_metric': 5.078238487243652} +Epoch [3730/4000] Training [1/16] Loss: 0.00208 +Epoch [3730/4000] Training [2/16] Loss: 0.00188 +Epoch [3730/4000] Training [3/16] Loss: 0.00225 +Epoch [3730/4000] Training [4/16] Loss: 0.00238 +Epoch [3730/4000] Training [5/16] Loss: 0.00308 +Epoch [3730/4000] Training [6/16] Loss: 0.00173 +Epoch [3730/4000] Training [7/16] Loss: 0.00305 +Epoch [3730/4000] Training [8/16] Loss: 0.00308 +Epoch [3730/4000] Training [9/16] Loss: 0.00201 +Epoch [3730/4000] Training [10/16] Loss: 0.00279 +Epoch [3730/4000] Training [11/16] Loss: 0.00256 +Epoch [3730/4000] Training [12/16] Loss: 0.00246 +Epoch [3730/4000] Training [13/16] Loss: 0.00282 +Epoch [3730/4000] Training [14/16] Loss: 0.00227 +Epoch [3730/4000] Training [15/16] Loss: 0.00315 +Epoch [3730/4000] Training [16/16] Loss: 0.00186 +Epoch [3730/4000] Training metric {'Train/mean dice_metric': 0.9987711906433105, 'Train/mean miou_metric': 0.9972624182701111, 'Train/mean f1': 0.9937668442726135, 'Train/mean precision': 0.9891971349716187, 'Train/mean recall': 0.9983789324760437, 'Train/mean hd95_metric': 0.523269772529602} +Epoch [3730/4000] Validation [1/4] Loss: 0.39592 focal_loss 0.33075 dice_loss 0.06516 +Epoch [3730/4000] Validation [2/4] Loss: 0.50328 focal_loss 0.39054 dice_loss 0.11274 +Epoch [3730/4000] Validation [3/4] Loss: 0.57461 focal_loss 0.47699 dice_loss 0.09762 +Epoch [3730/4000] Validation [4/4] Loss: 0.47997 focal_loss 0.35499 dice_loss 0.12498 +Epoch [3730/4000] Validation metric {'Val/mean dice_metric': 0.9740581512451172, 'Val/mean miou_metric': 0.9597637057304382, 'Val/mean f1': 0.976203441619873, 'Val/mean precision': 0.9737990498542786, 'Val/mean recall': 0.9786198139190674, 'Val/mean hd95_metric': 5.086511611938477} +Cheakpoint... +Epoch [3730/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740581512451172, 'Val/mean miou_metric': 0.9597637057304382, 'Val/mean f1': 0.976203441619873, 'Val/mean precision': 0.9737990498542786, 'Val/mean recall': 0.9786198139190674, 'Val/mean hd95_metric': 5.086511611938477} +Epoch [3731/4000] Training [1/16] Loss: 0.00421 +Epoch [3731/4000] Training [2/16] Loss: 0.00200 +Epoch [3731/4000] Training [3/16] Loss: 0.00236 +Epoch [3731/4000] Training [4/16] Loss: 0.00214 +Epoch [3731/4000] Training [5/16] Loss: 0.00146 +Epoch [3731/4000] Training [6/16] Loss: 0.00247 +Epoch [3731/4000] Training [7/16] Loss: 0.00155 +Epoch [3731/4000] Training [8/16] Loss: 0.00320 +Epoch [3731/4000] Training [9/16] Loss: 0.00456 +Epoch [3731/4000] Training [10/16] Loss: 0.00183 +Epoch [3731/4000] Training [11/16] Loss: 0.00308 +Epoch [3731/4000] Training [12/16] Loss: 0.00276 +Epoch [3731/4000] Training [13/16] Loss: 0.00374 +Epoch [3731/4000] Training [14/16] Loss: 0.00401 +Epoch [3731/4000] Training [15/16] Loss: 0.00120 +Epoch [3731/4000] Training [16/16] Loss: 0.00250 +Epoch [3731/4000] Training metric {'Train/mean dice_metric': 0.9986772537231445, 'Train/mean miou_metric': 0.9970700740814209, 'Train/mean f1': 0.9936699867248535, 'Train/mean precision': 0.9890698790550232, 'Train/mean recall': 0.9983131289482117, 'Train/mean hd95_metric': 0.5584259033203125} +Epoch [3731/4000] Validation [1/4] Loss: 0.47766 focal_loss 0.41011 dice_loss 0.06755 +Epoch [3731/4000] Validation [2/4] Loss: 0.92891 focal_loss 0.72432 dice_loss 0.20459 +Epoch [3731/4000] Validation [3/4] Loss: 0.50279 focal_loss 0.40717 dice_loss 0.09562 +Epoch [3731/4000] Validation [4/4] Loss: 0.47858 focal_loss 0.36746 dice_loss 0.11113 +Epoch [3731/4000] Validation metric {'Val/mean dice_metric': 0.9735130071640015, 'Val/mean miou_metric': 0.9591842889785767, 'Val/mean f1': 0.9758434891700745, 'Val/mean precision': 0.9736340641975403, 'Val/mean recall': 0.9780629873275757, 'Val/mean hd95_metric': 4.835906028747559} +Cheakpoint... +Epoch [3731/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735130071640015, 'Val/mean miou_metric': 0.9591842889785767, 'Val/mean f1': 0.9758434891700745, 'Val/mean precision': 0.9736340641975403, 'Val/mean recall': 0.9780629873275757, 'Val/mean hd95_metric': 4.835906028747559} +Epoch [3732/4000] Training [1/16] Loss: 0.00172 +Epoch [3732/4000] Training [2/16] Loss: 0.00208 +Epoch [3732/4000] Training [3/16] Loss: 0.00204 +Epoch [3732/4000] Training [4/16] Loss: 0.00158 +Epoch [3732/4000] Training [5/16] Loss: 0.00231 +Epoch [3732/4000] Training [6/16] Loss: 0.00342 +Epoch [3732/4000] Training [7/16] Loss: 0.00158 +Epoch [3732/4000] Training [8/16] Loss: 0.00200 +Epoch [3732/4000] Training [9/16] Loss: 0.00288 +Epoch [3732/4000] Training [10/16] Loss: 0.00189 +Epoch [3732/4000] Training [11/16] Loss: 0.00236 +Epoch [3732/4000] Training [12/16] Loss: 0.00315 +Epoch [3732/4000] Training [13/16] Loss: 0.00211 +Epoch [3732/4000] Training [14/16] Loss: 0.00224 +Epoch [3732/4000] Training [15/16] Loss: 0.00379 +Epoch [3732/4000] Training [16/16] Loss: 0.00214 +Epoch [3732/4000] Training metric {'Train/mean dice_metric': 0.9988114833831787, 'Train/mean miou_metric': 0.9973485469818115, 'Train/mean f1': 0.9937921762466431, 'Train/mean precision': 0.9892832636833191, 'Train/mean recall': 0.9983423948287964, 'Train/mean hd95_metric': 0.5165314674377441} +Epoch [3732/4000] Validation [1/4] Loss: 0.45893 focal_loss 0.39445 dice_loss 0.06448 +Epoch [3732/4000] Validation [2/4] Loss: 0.91047 focal_loss 0.71063 dice_loss 0.19984 +Epoch [3732/4000] Validation [3/4] Loss: 0.57774 focal_loss 0.48186 dice_loss 0.09588 +Epoch [3732/4000] Validation [4/4] Loss: 0.37601 focal_loss 0.28484 dice_loss 0.09117 +Epoch [3732/4000] Validation metric {'Val/mean dice_metric': 0.9736906290054321, 'Val/mean miou_metric': 0.959681510925293, 'Val/mean f1': 0.9761378169059753, 'Val/mean precision': 0.974061131477356, 'Val/mean recall': 0.9782233834266663, 'Val/mean hd95_metric': 4.933786392211914} +Cheakpoint... +Epoch [3732/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736906290054321, 'Val/mean miou_metric': 0.959681510925293, 'Val/mean f1': 0.9761378169059753, 'Val/mean precision': 0.974061131477356, 'Val/mean recall': 0.9782233834266663, 'Val/mean hd95_metric': 4.933786392211914} +Epoch [3733/4000] Training [1/16] Loss: 0.00208 +Epoch [3733/4000] Training [2/16] Loss: 0.00350 +Epoch [3733/4000] Training [3/16] Loss: 0.00168 +Epoch [3733/4000] Training [4/16] Loss: 0.00229 +Epoch [3733/4000] Training [5/16] Loss: 0.00244 +Epoch [3733/4000] Training [6/16] Loss: 0.00272 +Epoch [3733/4000] Training [7/16] Loss: 0.00209 +Epoch [3733/4000] Training [8/16] Loss: 0.00212 +Epoch [3733/4000] Training [9/16] Loss: 0.00298 +Epoch [3733/4000] Training [10/16] Loss: 0.00191 +Epoch [3733/4000] Training [11/16] Loss: 0.00197 +Epoch [3733/4000] Training [12/16] Loss: 0.00276 +Epoch [3733/4000] Training [13/16] Loss: 0.00263 +Epoch [3733/4000] Training [14/16] Loss: 0.00306 +Epoch [3733/4000] Training [15/16] Loss: 0.00174 +Epoch [3733/4000] Training [16/16] Loss: 0.00259 +Epoch [3733/4000] Training metric {'Train/mean dice_metric': 0.9987810254096985, 'Train/mean miou_metric': 0.997281551361084, 'Train/mean f1': 0.9936380982398987, 'Train/mean precision': 0.988961398601532, 'Train/mean recall': 0.9983593225479126, 'Train/mean hd95_metric': 0.521316647529602} +Epoch [3733/4000] Validation [1/4] Loss: 0.38380 focal_loss 0.32564 dice_loss 0.05816 +Epoch [3733/4000] Validation [2/4] Loss: 0.48840 focal_loss 0.37695 dice_loss 0.11145 +Epoch [3733/4000] Validation [3/4] Loss: 0.58066 focal_loss 0.48160 dice_loss 0.09906 +Epoch [3733/4000] Validation [4/4] Loss: 0.36659 focal_loss 0.27326 dice_loss 0.09333 +Epoch [3733/4000] Validation metric {'Val/mean dice_metric': 0.9748010635375977, 'Val/mean miou_metric': 0.9606701731681824, 'Val/mean f1': 0.9756432771682739, 'Val/mean precision': 0.9734394550323486, 'Val/mean recall': 0.9778571128845215, 'Val/mean hd95_metric': 5.27795934677124} +Cheakpoint... +Epoch [3733/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748010635375977, 'Val/mean miou_metric': 0.9606701731681824, 'Val/mean f1': 0.9756432771682739, 'Val/mean precision': 0.9734394550323486, 'Val/mean recall': 0.9778571128845215, 'Val/mean hd95_metric': 5.27795934677124} +Epoch [3734/4000] Training [1/16] Loss: 0.00251 +Epoch [3734/4000] Training [2/16] Loss: 0.00256 +Epoch [3734/4000] Training [3/16] Loss: 0.00185 +Epoch [3734/4000] Training [4/16] Loss: 0.00187 +Epoch [3734/4000] Training [5/16] Loss: 0.00333 +Epoch [3734/4000] Training [6/16] Loss: 0.00366 +Epoch [3734/4000] Training [7/16] Loss: 0.00229 +Epoch [3734/4000] Training [8/16] Loss: 0.00297 +Epoch [3734/4000] Training [9/16] Loss: 0.00274 +Epoch [3734/4000] Training [10/16] Loss: 0.00287 +Epoch [3734/4000] Training [11/16] Loss: 0.00225 +Epoch [3734/4000] Training [12/16] Loss: 0.00224 +Epoch [3734/4000] Training [13/16] Loss: 0.00255 +Epoch [3734/4000] Training [14/16] Loss: 0.00251 +Epoch [3734/4000] Training [15/16] Loss: 0.00244 +Epoch [3734/4000] Training [16/16] Loss: 0.00212 +Epoch [3734/4000] Training metric {'Train/mean dice_metric': 0.9985957145690918, 'Train/mean miou_metric': 0.9969217777252197, 'Train/mean f1': 0.993796706199646, 'Train/mean precision': 0.9893368482589722, 'Train/mean recall': 0.9982969164848328, 'Train/mean hd95_metric': 0.522976815700531} +Epoch [3734/4000] Validation [1/4] Loss: 0.39759 focal_loss 0.33475 dice_loss 0.06284 +Epoch [3734/4000] Validation [2/4] Loss: 0.49750 focal_loss 0.38618 dice_loss 0.11132 +Epoch [3734/4000] Validation [3/4] Loss: 0.53636 focal_loss 0.44455 dice_loss 0.09181 +Epoch [3734/4000] Validation [4/4] Loss: 0.36113 focal_loss 0.27387 dice_loss 0.08726 +Epoch [3734/4000] Validation metric {'Val/mean dice_metric': 0.9741207361221313, 'Val/mean miou_metric': 0.9598191976547241, 'Val/mean f1': 0.9764023423194885, 'Val/mean precision': 0.9739753007888794, 'Val/mean recall': 0.9788416028022766, 'Val/mean hd95_metric': 4.986434459686279} +Cheakpoint... +Epoch [3734/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741207361221313, 'Val/mean miou_metric': 0.9598191976547241, 'Val/mean f1': 0.9764023423194885, 'Val/mean precision': 0.9739753007888794, 'Val/mean recall': 0.9788416028022766, 'Val/mean hd95_metric': 4.986434459686279} +Epoch [3735/4000] Training [1/16] Loss: 0.00205 +Epoch [3735/4000] Training [2/16] Loss: 0.00251 +Epoch [3735/4000] Training [3/16] Loss: 0.00208 +Epoch [3735/4000] Training [4/16] Loss: 0.00229 +Epoch [3735/4000] Training [5/16] Loss: 0.00246 +Epoch [3735/4000] Training [6/16] Loss: 0.00219 +Epoch [3735/4000] Training [7/16] Loss: 0.00246 +Epoch [3735/4000] Training [8/16] Loss: 0.00244 +Epoch [3735/4000] Training [9/16] Loss: 0.00197 +Epoch [3735/4000] Training [10/16] Loss: 0.00230 +Epoch [3735/4000] Training [11/16] Loss: 0.00242 +Epoch [3735/4000] Training [12/16] Loss: 0.00288 +Epoch [3735/4000] Training [13/16] Loss: 0.00201 +Epoch [3735/4000] Training [14/16] Loss: 0.00357 +Epoch [3735/4000] Training [15/16] Loss: 0.00218 +Epoch [3735/4000] Training [16/16] Loss: 0.00217 +Epoch [3735/4000] Training metric {'Train/mean dice_metric': 0.9988380670547485, 'Train/mean miou_metric': 0.9974014163017273, 'Train/mean f1': 0.9937896132469177, 'Train/mean precision': 0.9892369508743286, 'Train/mean recall': 0.9983843564987183, 'Train/mean hd95_metric': 0.5344024896621704} +Epoch [3735/4000] Validation [1/4] Loss: 0.40820 focal_loss 0.34616 dice_loss 0.06203 +Epoch [3735/4000] Validation [2/4] Loss: 0.91638 focal_loss 0.71381 dice_loss 0.20258 +Epoch [3735/4000] Validation [3/4] Loss: 0.55721 focal_loss 0.46298 dice_loss 0.09423 +Epoch [3735/4000] Validation [4/4] Loss: 0.32174 focal_loss 0.23191 dice_loss 0.08983 +Epoch [3735/4000] Validation metric {'Val/mean dice_metric': 0.9736010432243347, 'Val/mean miou_metric': 0.9595824480056763, 'Val/mean f1': 0.9759320020675659, 'Val/mean precision': 0.9738532900810242, 'Val/mean recall': 0.9780195951461792, 'Val/mean hd95_metric': 4.958832740783691} +Cheakpoint... +Epoch [3735/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736010432243347, 'Val/mean miou_metric': 0.9595824480056763, 'Val/mean f1': 0.9759320020675659, 'Val/mean precision': 0.9738532900810242, 'Val/mean recall': 0.9780195951461792, 'Val/mean hd95_metric': 4.958832740783691} +Epoch [3736/4000] Training [1/16] Loss: 0.00285 +Epoch [3736/4000] Training [2/16] Loss: 0.00370 +Epoch [3736/4000] Training [3/16] Loss: 0.00253 +Epoch [3736/4000] Training [4/16] Loss: 0.00217 +Epoch [3736/4000] Training [5/16] Loss: 0.00186 +Epoch [3736/4000] Training [6/16] Loss: 0.00366 +Epoch [3736/4000] Training [7/16] Loss: 0.00227 +Epoch [3736/4000] Training [8/16] Loss: 0.00185 +Epoch [3736/4000] Training [9/16] Loss: 0.00338 +Epoch [3736/4000] Training [10/16] Loss: 0.00230 +Epoch [3736/4000] Training [11/16] Loss: 0.00163 +Epoch [3736/4000] Training [12/16] Loss: 0.00230 +Epoch [3736/4000] Training [13/16] Loss: 0.00250 +Epoch [3736/4000] Training [14/16] Loss: 0.00222 +Epoch [3736/4000] Training [15/16] Loss: 0.00203 +Epoch [3736/4000] Training [16/16] Loss: 0.00229 +Epoch [3736/4000] Training metric {'Train/mean dice_metric': 0.998846173286438, 'Train/mean miou_metric': 0.9974085688591003, 'Train/mean f1': 0.9937251806259155, 'Train/mean precision': 0.989072322845459, 'Train/mean recall': 0.9984220266342163, 'Train/mean hd95_metric': 0.5302730202674866} +Epoch [3736/4000] Validation [1/4] Loss: 0.47592 focal_loss 0.41108 dice_loss 0.06484 +Epoch [3736/4000] Validation [2/4] Loss: 0.94584 focal_loss 0.76112 dice_loss 0.18472 +Epoch [3736/4000] Validation [3/4] Loss: 0.56395 focal_loss 0.46606 dice_loss 0.09789 +Epoch [3736/4000] Validation [4/4] Loss: 0.47509 focal_loss 0.37145 dice_loss 0.10364 +Epoch [3736/4000] Validation metric {'Val/mean dice_metric': 0.9752966165542603, 'Val/mean miou_metric': 0.9613876342773438, 'Val/mean f1': 0.9762559533119202, 'Val/mean precision': 0.974023699760437, 'Val/mean recall': 0.9784984588623047, 'Val/mean hd95_metric': 4.885319709777832} +Cheakpoint... +Epoch [3736/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752966165542603, 'Val/mean miou_metric': 0.9613876342773438, 'Val/mean f1': 0.9762559533119202, 'Val/mean precision': 0.974023699760437, 'Val/mean recall': 0.9784984588623047, 'Val/mean hd95_metric': 4.885319709777832} +Epoch [3737/4000] Training [1/16] Loss: 0.00197 +Epoch [3737/4000] Training [2/16] Loss: 0.00260 +Epoch [3737/4000] Training [3/16] Loss: 0.00291 +Epoch [3737/4000] Training [4/16] Loss: 0.00297 +Epoch [3737/4000] Training [5/16] Loss: 0.00224 +Epoch [3737/4000] Training [6/16] Loss: 0.00222 +Epoch [3737/4000] Training [7/16] Loss: 0.00291 +Epoch [3737/4000] Training [8/16] Loss: 0.00258 +Epoch [3737/4000] Training [9/16] Loss: 0.00181 +Epoch [3737/4000] Training [10/16] Loss: 0.00198 +Epoch [3737/4000] Training [11/16] Loss: 0.00188 +Epoch [3737/4000] Training [12/16] Loss: 0.00228 +Epoch [3737/4000] Training [13/16] Loss: 0.00250 +Epoch [3737/4000] Training [14/16] Loss: 0.00261 +Epoch [3737/4000] Training [15/16] Loss: 0.00325 +Epoch [3737/4000] Training [16/16] Loss: 0.00262 +Epoch [3737/4000] Training metric {'Train/mean dice_metric': 0.9988694190979004, 'Train/mean miou_metric': 0.9974562525749207, 'Train/mean f1': 0.9937323331832886, 'Train/mean precision': 0.9890792369842529, 'Train/mean recall': 0.9984294176101685, 'Train/mean hd95_metric': 0.5320587158203125} +Epoch [3737/4000] Validation [1/4] Loss: 0.43757 focal_loss 0.37286 dice_loss 0.06471 +Epoch [3737/4000] Validation [2/4] Loss: 1.00068 focal_loss 0.72960 dice_loss 0.27108 +Epoch [3737/4000] Validation [3/4] Loss: 0.53465 focal_loss 0.44242 dice_loss 0.09223 +Epoch [3737/4000] Validation [4/4] Loss: 0.37461 focal_loss 0.28795 dice_loss 0.08666 +Epoch [3737/4000] Validation metric {'Val/mean dice_metric': 0.9738456606864929, 'Val/mean miou_metric': 0.9597323536872864, 'Val/mean f1': 0.9759030938148499, 'Val/mean precision': 0.9740003943443298, 'Val/mean recall': 0.977813184261322, 'Val/mean hd95_metric': 4.857682704925537} +Cheakpoint... +Epoch [3737/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738456606864929, 'Val/mean miou_metric': 0.9597323536872864, 'Val/mean f1': 0.9759030938148499, 'Val/mean precision': 0.9740003943443298, 'Val/mean recall': 0.977813184261322, 'Val/mean hd95_metric': 4.857682704925537} +Epoch [3738/4000] Training [1/16] Loss: 0.00251 +Epoch [3738/4000] Training [2/16] Loss: 0.00198 +Epoch [3738/4000] Training [3/16] Loss: 0.00254 +Epoch [3738/4000] Training [4/16] Loss: 0.00180 +Epoch [3738/4000] Training [5/16] Loss: 0.00285 +Epoch [3738/4000] Training [6/16] Loss: 0.00376 +Epoch [3738/4000] Training [7/16] Loss: 0.00173 +Epoch [3738/4000] Training [8/16] Loss: 0.00281 +Epoch [3738/4000] Training [9/16] Loss: 0.00237 +Epoch [3738/4000] Training [10/16] Loss: 0.00186 +Epoch [3738/4000] Training [11/16] Loss: 0.00167 +Epoch [3738/4000] Training [12/16] Loss: 0.00195 +Epoch [3738/4000] Training [13/16] Loss: 0.00136 +Epoch [3738/4000] Training [14/16] Loss: 0.00346 +Epoch [3738/4000] Training [15/16] Loss: 0.00262 +Epoch [3738/4000] Training [16/16] Loss: 0.00274 +Epoch [3738/4000] Training metric {'Train/mean dice_metric': 0.9988701343536377, 'Train/mean miou_metric': 0.9974679946899414, 'Train/mean f1': 0.9939754009246826, 'Train/mean precision': 0.9895045161247253, 'Train/mean recall': 0.9984870553016663, 'Train/mean hd95_metric': 0.5253204107284546} +Epoch [3738/4000] Validation [1/4] Loss: 0.38498 focal_loss 0.32337 dice_loss 0.06161 +Epoch [3738/4000] Validation [2/4] Loss: 0.84211 focal_loss 0.62332 dice_loss 0.21879 +Epoch [3738/4000] Validation [3/4] Loss: 0.29865 focal_loss 0.23417 dice_loss 0.06448 +Epoch [3738/4000] Validation [4/4] Loss: 0.35170 focal_loss 0.24006 dice_loss 0.11164 +Epoch [3738/4000] Validation metric {'Val/mean dice_metric': 0.97428959608078, 'Val/mean miou_metric': 0.9601030349731445, 'Val/mean f1': 0.9761791229248047, 'Val/mean precision': 0.9747829437255859, 'Val/mean recall': 0.9775792956352234, 'Val/mean hd95_metric': 4.9771270751953125} +Cheakpoint... +Epoch [3738/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97428959608078, 'Val/mean miou_metric': 0.9601030349731445, 'Val/mean f1': 0.9761791229248047, 'Val/mean precision': 0.9747829437255859, 'Val/mean recall': 0.9775792956352234, 'Val/mean hd95_metric': 4.9771270751953125} +Epoch [3739/4000] Training [1/16] Loss: 0.00202 +Epoch [3739/4000] Training [2/16] Loss: 0.00244 +Epoch [3739/4000] Training [3/16] Loss: 0.00357 +Epoch [3739/4000] Training [4/16] Loss: 0.00260 +Epoch [3739/4000] Training [5/16] Loss: 0.00365 +Epoch [3739/4000] Training [6/16] Loss: 0.00372 +Epoch [3739/4000] Training [7/16] Loss: 0.00172 +Epoch [3739/4000] Training [8/16] Loss: 0.00300 +Epoch [3739/4000] Training [9/16] Loss: 0.00193 +Epoch [3739/4000] Training [10/16] Loss: 0.00175 +Epoch [3739/4000] Training [11/16] Loss: 0.00292 +Epoch [3739/4000] Training [12/16] Loss: 0.00149 +Epoch [3739/4000] Training [13/16] Loss: 0.00374 +Epoch [3739/4000] Training [14/16] Loss: 0.00299 +Epoch [3739/4000] Training [15/16] Loss: 0.00184 +Epoch [3739/4000] Training [16/16] Loss: 0.00197 +Epoch [3739/4000] Training metric {'Train/mean dice_metric': 0.9986948370933533, 'Train/mean miou_metric': 0.9971193075180054, 'Train/mean f1': 0.993834376335144, 'Train/mean precision': 0.9893335700035095, 'Train/mean recall': 0.9983763098716736, 'Train/mean hd95_metric': 0.5465397834777832} +Epoch [3739/4000] Validation [1/4] Loss: 0.41978 focal_loss 0.35707 dice_loss 0.06270 +Epoch [3739/4000] Validation [2/4] Loss: 1.00566 focal_loss 0.81388 dice_loss 0.19178 +Epoch [3739/4000] Validation [3/4] Loss: 0.51166 focal_loss 0.42395 dice_loss 0.08770 +Epoch [3739/4000] Validation [4/4] Loss: 0.34206 focal_loss 0.25874 dice_loss 0.08332 +Epoch [3739/4000] Validation metric {'Val/mean dice_metric': 0.9756748080253601, 'Val/mean miou_metric': 0.9618250131607056, 'Val/mean f1': 0.9766818284988403, 'Val/mean precision': 0.9747116565704346, 'Val/mean recall': 0.9786599278450012, 'Val/mean hd95_metric': 4.611807823181152} +Cheakpoint... +Epoch [3739/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756748080253601, 'Val/mean miou_metric': 0.9618250131607056, 'Val/mean f1': 0.9766818284988403, 'Val/mean precision': 0.9747116565704346, 'Val/mean recall': 0.9786599278450012, 'Val/mean hd95_metric': 4.611807823181152} +Epoch [3740/4000] Training [1/16] Loss: 0.00328 +Epoch [3740/4000] Training [2/16] Loss: 0.00175 +Epoch [3740/4000] Training [3/16] Loss: 0.00207 +Epoch [3740/4000] Training [4/16] Loss: 0.00153 +Epoch [3740/4000] Training [5/16] Loss: 0.00251 +Epoch [3740/4000] Training [6/16] Loss: 0.00309 +Epoch [3740/4000] Training [7/16] Loss: 0.00204 +Epoch [3740/4000] Training [8/16] Loss: 0.00221 +Epoch [3740/4000] Training [9/16] Loss: 0.00142 +Epoch [3740/4000] Training [10/16] Loss: 0.00203 +Epoch [3740/4000] Training [11/16] Loss: 0.00404 +Epoch [3740/4000] Training [12/16] Loss: 0.00229 +Epoch [3740/4000] Training [13/16] Loss: 0.00161 +Epoch [3740/4000] Training [14/16] Loss: 0.00230 +Epoch [3740/4000] Training [15/16] Loss: 0.00250 +Epoch [3740/4000] Training [16/16] Loss: 0.00233 +Epoch [3740/4000] Training metric {'Train/mean dice_metric': 0.9988328218460083, 'Train/mean miou_metric': 0.997393012046814, 'Train/mean f1': 0.9939695000648499, 'Train/mean precision': 0.9894980192184448, 'Train/mean recall': 0.9984814524650574, 'Train/mean hd95_metric': 0.5083282589912415} +Epoch [3740/4000] Validation [1/4] Loss: 0.39570 focal_loss 0.33277 dice_loss 0.06293 +Epoch [3740/4000] Validation [2/4] Loss: 0.51747 focal_loss 0.40217 dice_loss 0.11531 +Epoch [3740/4000] Validation [3/4] Loss: 0.54896 focal_loss 0.45242 dice_loss 0.09654 +Epoch [3740/4000] Validation [4/4] Loss: 0.40680 focal_loss 0.30306 dice_loss 0.10374 +Epoch [3740/4000] Validation metric {'Val/mean dice_metric': 0.9737535715103149, 'Val/mean miou_metric': 0.959842324256897, 'Val/mean f1': 0.976081132888794, 'Val/mean precision': 0.9744730591773987, 'Val/mean recall': 0.9776945114135742, 'Val/mean hd95_metric': 5.110978126525879} +Cheakpoint... +Epoch [3740/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737535715103149, 'Val/mean miou_metric': 0.959842324256897, 'Val/mean f1': 0.976081132888794, 'Val/mean precision': 0.9744730591773987, 'Val/mean recall': 0.9776945114135742, 'Val/mean hd95_metric': 5.110978126525879} +Epoch [3741/4000] Training [1/16] Loss: 0.00194 +Epoch [3741/4000] Training [2/16] Loss: 0.00173 +Epoch [3741/4000] Training [3/16] Loss: 0.00287 +Epoch [3741/4000] Training [4/16] Loss: 0.00347 +Epoch [3741/4000] Training [5/16] Loss: 0.00181 +Epoch [3741/4000] Training [6/16] Loss: 0.00188 +Epoch [3741/4000] Training [7/16] Loss: 0.00180 +Epoch [3741/4000] Training [8/16] Loss: 0.00220 +Epoch [3741/4000] Training [9/16] Loss: 0.00245 +Epoch [3741/4000] Training [10/16] Loss: 0.00218 +Epoch [3741/4000] Training [11/16] Loss: 0.00186 +Epoch [3741/4000] Training [12/16] Loss: 0.00371 +Epoch [3741/4000] Training [13/16] Loss: 0.00225 +Epoch [3741/4000] Training [14/16] Loss: 0.00231 +Epoch [3741/4000] Training [15/16] Loss: 0.00336 +Epoch [3741/4000] Training [16/16] Loss: 0.00206 +Epoch [3741/4000] Training metric {'Train/mean dice_metric': 0.9988359212875366, 'Train/mean miou_metric': 0.9973896741867065, 'Train/mean f1': 0.9937382936477661, 'Train/mean precision': 0.9891396164894104, 'Train/mean recall': 0.9983799457550049, 'Train/mean hd95_metric': 0.5178009271621704} +Epoch [3741/4000] Validation [1/4] Loss: 0.40261 focal_loss 0.33819 dice_loss 0.06443 +Epoch [3741/4000] Validation [2/4] Loss: 0.48091 focal_loss 0.37120 dice_loss 0.10972 +Epoch [3741/4000] Validation [3/4] Loss: 0.56543 focal_loss 0.46401 dice_loss 0.10142 +Epoch [3741/4000] Validation [4/4] Loss: 0.35549 focal_loss 0.26866 dice_loss 0.08682 +Epoch [3741/4000] Validation metric {'Val/mean dice_metric': 0.974478542804718, 'Val/mean miou_metric': 0.9604400396347046, 'Val/mean f1': 0.9762758016586304, 'Val/mean precision': 0.9741596579551697, 'Val/mean recall': 0.9784013032913208, 'Val/mean hd95_metric': 5.395010471343994} +Cheakpoint... +Epoch [3741/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974478542804718, 'Val/mean miou_metric': 0.9604400396347046, 'Val/mean f1': 0.9762758016586304, 'Val/mean precision': 0.9741596579551697, 'Val/mean recall': 0.9784013032913208, 'Val/mean hd95_metric': 5.395010471343994} +Epoch [3742/4000] Training [1/16] Loss: 0.00341 +Epoch [3742/4000] Training [2/16] Loss: 0.00183 +Epoch [3742/4000] Training [3/16] Loss: 0.00220 +Epoch [3742/4000] Training [4/16] Loss: 0.00168 +Epoch [3742/4000] Training [5/16] Loss: 0.00254 +Epoch [3742/4000] Training [6/16] Loss: 0.00243 +Epoch [3742/4000] Training [7/16] Loss: 0.00208 +Epoch [3742/4000] Training [8/16] Loss: 0.00236 +Epoch [3742/4000] Training [9/16] Loss: 0.00307 +Epoch [3742/4000] Training [10/16] Loss: 0.00226 +Epoch [3742/4000] Training [11/16] Loss: 0.00249 +Epoch [3742/4000] Training [12/16] Loss: 0.00375 +Epoch [3742/4000] Training [13/16] Loss: 0.00282 +Epoch [3742/4000] Training [14/16] Loss: 0.00237 +Epoch [3742/4000] Training [15/16] Loss: 0.00326 +Epoch [3742/4000] Training [16/16] Loss: 0.00254 +Epoch [3742/4000] Training metric {'Train/mean dice_metric': 0.9987170696258545, 'Train/mean miou_metric': 0.9971532225608826, 'Train/mean f1': 0.9935908317565918, 'Train/mean precision': 0.9889078736305237, 'Train/mean recall': 0.9983184337615967, 'Train/mean hd95_metric': 0.5332445502281189} +Epoch [3742/4000] Validation [1/4] Loss: 0.38281 focal_loss 0.32191 dice_loss 0.06090 +Epoch [3742/4000] Validation [2/4] Loss: 0.50894 focal_loss 0.39604 dice_loss 0.11290 +Epoch [3742/4000] Validation [3/4] Loss: 0.30205 focal_loss 0.23886 dice_loss 0.06318 +Epoch [3742/4000] Validation [4/4] Loss: 0.43754 focal_loss 0.33131 dice_loss 0.10624 +Epoch [3742/4000] Validation metric {'Val/mean dice_metric': 0.9749809503555298, 'Val/mean miou_metric': 0.9609140157699585, 'Val/mean f1': 0.9763482809066772, 'Val/mean precision': 0.9737268090248108, 'Val/mean recall': 0.978983998298645, 'Val/mean hd95_metric': 5.093728065490723} +Cheakpoint... +Epoch [3742/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749809503555298, 'Val/mean miou_metric': 0.9609140157699585, 'Val/mean f1': 0.9763482809066772, 'Val/mean precision': 0.9737268090248108, 'Val/mean recall': 0.978983998298645, 'Val/mean hd95_metric': 5.093728065490723} +Epoch [3743/4000] Training [1/16] Loss: 0.00268 +Epoch [3743/4000] Training [2/16] Loss: 0.00235 +Epoch [3743/4000] Training [3/16] Loss: 0.00209 +Epoch [3743/4000] Training [4/16] Loss: 0.00283 +Epoch [3743/4000] Training [5/16] Loss: 0.00199 +Epoch [3743/4000] Training [6/16] Loss: 0.00173 +Epoch [3743/4000] Training [7/16] Loss: 0.00267 +Epoch [3743/4000] Training [8/16] Loss: 0.00223 +Epoch [3743/4000] Training [9/16] Loss: 0.00330 +Epoch [3743/4000] Training [10/16] Loss: 0.00315 +Epoch [3743/4000] Training [11/16] Loss: 0.00346 +Epoch [3743/4000] Training [12/16] Loss: 0.00193 +Epoch [3743/4000] Training [13/16] Loss: 0.00281 +Epoch [3743/4000] Training [14/16] Loss: 0.00264 +Epoch [3743/4000] Training [15/16] Loss: 0.00212 +Epoch [3743/4000] Training [16/16] Loss: 0.00218 +Epoch [3743/4000] Training metric {'Train/mean dice_metric': 0.9987192153930664, 'Train/mean miou_metric': 0.9971492290496826, 'Train/mean f1': 0.9934431314468384, 'Train/mean precision': 0.9887201189994812, 'Train/mean recall': 0.9982114434242249, 'Train/mean hd95_metric': 0.5258222222328186} +Epoch [3743/4000] Validation [1/4] Loss: 0.39106 focal_loss 0.32909 dice_loss 0.06197 +Epoch [3743/4000] Validation [2/4] Loss: 0.50103 focal_loss 0.38649 dice_loss 0.11454 +Epoch [3743/4000] Validation [3/4] Loss: 0.52657 focal_loss 0.43820 dice_loss 0.08837 +Epoch [3743/4000] Validation [4/4] Loss: 0.37140 focal_loss 0.28192 dice_loss 0.08948 +Epoch [3743/4000] Validation metric {'Val/mean dice_metric': 0.9751143455505371, 'Val/mean miou_metric': 0.960929274559021, 'Val/mean f1': 0.9763144850730896, 'Val/mean precision': 0.9741765260696411, 'Val/mean recall': 0.978461742401123, 'Val/mean hd95_metric': 4.7279157638549805} +Cheakpoint... +Epoch [3743/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751143455505371, 'Val/mean miou_metric': 0.960929274559021, 'Val/mean f1': 0.9763144850730896, 'Val/mean precision': 0.9741765260696411, 'Val/mean recall': 0.978461742401123, 'Val/mean hd95_metric': 4.7279157638549805} +Epoch [3744/4000] Training [1/16] Loss: 0.00328 +Epoch [3744/4000] Training [2/16] Loss: 0.00215 +Epoch [3744/4000] Training [3/16] Loss: 0.00177 +Epoch [3744/4000] Training [4/16] Loss: 0.00251 +Epoch [3744/4000] Training [5/16] Loss: 0.00240 +Epoch [3744/4000] Training [6/16] Loss: 0.00263 +Epoch [3744/4000] Training [7/16] Loss: 0.00261 +Epoch [3744/4000] Training [8/16] Loss: 0.00167 +Epoch [3744/4000] Training [9/16] Loss: 0.00188 +Epoch [3744/4000] Training [10/16] Loss: 0.00190 +Epoch [3744/4000] Training [11/16] Loss: 0.00256 +Epoch [3744/4000] Training [12/16] Loss: 0.00265 +Epoch [3744/4000] Training [13/16] Loss: 0.00314 +Epoch [3744/4000] Training [14/16] Loss: 0.00219 +Epoch [3744/4000] Training [15/16] Loss: 0.00216 +Epoch [3744/4000] Training [16/16] Loss: 0.00223 +Epoch [3744/4000] Training metric {'Train/mean dice_metric': 0.99878990650177, 'Train/mean miou_metric': 0.9972983002662659, 'Train/mean f1': 0.9936035871505737, 'Train/mean precision': 0.988892138004303, 'Train/mean recall': 0.9983600974082947, 'Train/mean hd95_metric': 0.5196565985679626} +Epoch [3744/4000] Validation [1/4] Loss: 0.43411 focal_loss 0.36079 dice_loss 0.07331 +Epoch [3744/4000] Validation [2/4] Loss: 0.46563 focal_loss 0.35460 dice_loss 0.11103 +Epoch [3744/4000] Validation [3/4] Loss: 0.29994 focal_loss 0.23370 dice_loss 0.06623 +Epoch [3744/4000] Validation [4/4] Loss: 0.31509 focal_loss 0.22338 dice_loss 0.09170 +Epoch [3744/4000] Validation metric {'Val/mean dice_metric': 0.9743286371231079, 'Val/mean miou_metric': 0.9606305956840515, 'Val/mean f1': 0.9764649868011475, 'Val/mean precision': 0.9739755392074585, 'Val/mean recall': 0.9789671897888184, 'Val/mean hd95_metric': 4.699490070343018} +Cheakpoint... +Epoch [3744/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743286371231079, 'Val/mean miou_metric': 0.9606305956840515, 'Val/mean f1': 0.9764649868011475, 'Val/mean precision': 0.9739755392074585, 'Val/mean recall': 0.9789671897888184, 'Val/mean hd95_metric': 4.699490070343018} +Epoch [3745/4000] Training [1/16] Loss: 0.00224 +Epoch [3745/4000] Training [2/16] Loss: 0.00191 +Epoch [3745/4000] Training [3/16] Loss: 0.00308 +Epoch [3745/4000] Training [4/16] Loss: 0.00158 +Epoch [3745/4000] Training [5/16] Loss: 0.00242 +Epoch [3745/4000] Training [6/16] Loss: 0.00216 +Epoch [3745/4000] Training [7/16] Loss: 0.00208 +Epoch [3745/4000] Training [8/16] Loss: 0.00148 +Epoch [3745/4000] Training [9/16] Loss: 0.00248 +Epoch [3745/4000] Training [10/16] Loss: 0.00220 +Epoch [3745/4000] Training [11/16] Loss: 0.00215 +Epoch [3745/4000] Training [12/16] Loss: 0.00218 +Epoch [3745/4000] Training [13/16] Loss: 0.00171 +Epoch [3745/4000] Training [14/16] Loss: 0.00255 +Epoch [3745/4000] Training [15/16] Loss: 0.00269 +Epoch [3745/4000] Training [16/16] Loss: 0.00242 +Epoch [3745/4000] Training metric {'Train/mean dice_metric': 0.9989131093025208, 'Train/mean miou_metric': 0.997546911239624, 'Train/mean f1': 0.9938341975212097, 'Train/mean precision': 0.9893007278442383, 'Train/mean recall': 0.9984093904495239, 'Train/mean hd95_metric': 0.49407055974006653} +Epoch [3745/4000] Validation [1/4] Loss: 0.44645 focal_loss 0.38172 dice_loss 0.06472 +Epoch [3745/4000] Validation [2/4] Loss: 0.48820 focal_loss 0.37466 dice_loss 0.11354 +Epoch [3745/4000] Validation [3/4] Loss: 0.55303 focal_loss 0.45908 dice_loss 0.09395 +Epoch [3745/4000] Validation [4/4] Loss: 0.45936 focal_loss 0.35031 dice_loss 0.10905 +Epoch [3745/4000] Validation metric {'Val/mean dice_metric': 0.9732730984687805, 'Val/mean miou_metric': 0.9595946073532104, 'Val/mean f1': 0.9761855006217957, 'Val/mean precision': 0.9744956493377686, 'Val/mean recall': 0.9778810739517212, 'Val/mean hd95_metric': 4.871493816375732} +Cheakpoint... +Epoch [3745/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732730984687805, 'Val/mean miou_metric': 0.9595946073532104, 'Val/mean f1': 0.9761855006217957, 'Val/mean precision': 0.9744956493377686, 'Val/mean recall': 0.9778810739517212, 'Val/mean hd95_metric': 4.871493816375732} +Epoch [3746/4000] Training [1/16] Loss: 0.00186 +Epoch [3746/4000] Training [2/16] Loss: 0.00219 +Epoch [3746/4000] Training [3/16] Loss: 0.00203 +Epoch [3746/4000] Training [4/16] Loss: 0.00291 +Epoch [3746/4000] Training [5/16] Loss: 0.00170 +Epoch [3746/4000] Training [6/16] Loss: 0.00310 +Epoch [3746/4000] Training [7/16] Loss: 0.00234 +Epoch [3746/4000] Training [8/16] Loss: 0.00322 +Epoch [3746/4000] Training [9/16] Loss: 0.00235 +Epoch [3746/4000] Training [10/16] Loss: 0.00190 +Epoch [3746/4000] Training [11/16] Loss: 0.00297 +Epoch [3746/4000] Training [12/16] Loss: 0.00316 +Epoch [3746/4000] Training [13/16] Loss: 0.00282 +Epoch [3746/4000] Training [14/16] Loss: 0.00386 +Epoch [3746/4000] Training [15/16] Loss: 0.00228 +Epoch [3746/4000] Training [16/16] Loss: 0.00257 +Epoch [3746/4000] Training metric {'Train/mean dice_metric': 0.9986977577209473, 'Train/mean miou_metric': 0.9971214532852173, 'Train/mean f1': 0.9936180710792542, 'Train/mean precision': 0.9890234470367432, 'Train/mean recall': 0.9982556104660034, 'Train/mean hd95_metric': 0.5636994242668152} +Epoch [3746/4000] Validation [1/4] Loss: 0.38681 focal_loss 0.32621 dice_loss 0.06060 +Epoch [3746/4000] Validation [2/4] Loss: 0.98666 focal_loss 0.79883 dice_loss 0.18783 +Epoch [3746/4000] Validation [3/4] Loss: 0.51566 focal_loss 0.42400 dice_loss 0.09166 +Epoch [3746/4000] Validation [4/4] Loss: 0.36284 focal_loss 0.27172 dice_loss 0.09112 +Epoch [3746/4000] Validation metric {'Val/mean dice_metric': 0.9746572375297546, 'Val/mean miou_metric': 0.9607704877853394, 'Val/mean f1': 0.9761447310447693, 'Val/mean precision': 0.9740909337997437, 'Val/mean recall': 0.9782070517539978, 'Val/mean hd95_metric': 4.902751922607422} +Cheakpoint... +Epoch [3746/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746572375297546, 'Val/mean miou_metric': 0.9607704877853394, 'Val/mean f1': 0.9761447310447693, 'Val/mean precision': 0.9740909337997437, 'Val/mean recall': 0.9782070517539978, 'Val/mean hd95_metric': 4.902751922607422} +Epoch [3747/4000] Training [1/16] Loss: 0.00284 +Epoch [3747/4000] Training [2/16] Loss: 0.00343 +Epoch [3747/4000] Training [3/16] Loss: 0.00255 +Epoch [3747/4000] Training [4/16] Loss: 0.00242 +Epoch [3747/4000] Training [5/16] Loss: 0.00171 +Epoch [3747/4000] Training [6/16] Loss: 0.00228 +Epoch [3747/4000] Training [7/16] Loss: 0.00169 +Epoch [3747/4000] Training [8/16] Loss: 0.00206 +Epoch [3747/4000] Training [9/16] Loss: 0.00219 +Epoch [3747/4000] Training [10/16] Loss: 0.00187 +Epoch [3747/4000] Training [11/16] Loss: 0.00271 +Epoch [3747/4000] Training [12/16] Loss: 0.00355 +Epoch [3747/4000] Training [13/16] Loss: 0.00266 +Epoch [3747/4000] Training [14/16] Loss: 0.00245 +Epoch [3747/4000] Training [15/16] Loss: 0.00244 +Epoch [3747/4000] Training [16/16] Loss: 0.00235 +Epoch [3747/4000] Training metric {'Train/mean dice_metric': 0.9987547397613525, 'Train/mean miou_metric': 0.9971785545349121, 'Train/mean f1': 0.9927175641059875, 'Train/mean precision': 0.9872272610664368, 'Train/mean recall': 0.9982692003250122, 'Train/mean hd95_metric': 0.5238279700279236} +Epoch [3747/4000] Validation [1/4] Loss: 0.38333 focal_loss 0.32224 dice_loss 0.06109 +Epoch [3747/4000] Validation [2/4] Loss: 1.00444 focal_loss 0.80144 dice_loss 0.20300 +Epoch [3747/4000] Validation [3/4] Loss: 0.56131 focal_loss 0.46730 dice_loss 0.09401 +Epoch [3747/4000] Validation [4/4] Loss: 0.36511 focal_loss 0.27627 dice_loss 0.08884 +Epoch [3747/4000] Validation metric {'Val/mean dice_metric': 0.9729892015457153, 'Val/mean miou_metric': 0.9595638513565063, 'Val/mean f1': 0.9747434854507446, 'Val/mean precision': 0.9710661172866821, 'Val/mean recall': 0.9784489274024963, 'Val/mean hd95_metric': 5.576991081237793} +Cheakpoint... +Epoch [3747/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9729892015457153, 'Val/mean miou_metric': 0.9595638513565063, 'Val/mean f1': 0.9747434854507446, 'Val/mean precision': 0.9710661172866821, 'Val/mean recall': 0.9784489274024963, 'Val/mean hd95_metric': 5.576991081237793} +Epoch [3748/4000] Training [1/16] Loss: 0.00129 +Epoch [3748/4000] Training [2/16] Loss: 0.00219 +Epoch [3748/4000] Training [3/16] Loss: 0.00265 +Epoch [3748/4000] Training [4/16] Loss: 0.00282 +Epoch [3748/4000] Training [5/16] Loss: 0.00242 +Epoch [3748/4000] Training [6/16] Loss: 0.00229 +Epoch [3748/4000] Training [7/16] Loss: 0.00291 +Epoch [3748/4000] Training [8/16] Loss: 0.00229 +Epoch [3748/4000] Training [9/16] Loss: 0.00252 +Epoch [3748/4000] Training [10/16] Loss: 0.00256 +Epoch [3748/4000] Training [11/16] Loss: 0.00171 +Epoch [3748/4000] Training [12/16] Loss: 0.00190 +Epoch [3748/4000] Training [13/16] Loss: 0.00139 +Epoch [3748/4000] Training [14/16] Loss: 0.00343 +Epoch [3748/4000] Training [15/16] Loss: 0.00158 +Epoch [3748/4000] Training [16/16] Loss: 0.00393 +Epoch [3748/4000] Training metric {'Train/mean dice_metric': 0.9988430142402649, 'Train/mean miou_metric': 0.9974004030227661, 'Train/mean f1': 0.993746817111969, 'Train/mean precision': 0.9891691207885742, 'Train/mean recall': 0.9983670711517334, 'Train/mean hd95_metric': 0.4969025254249573} +Epoch [3748/4000] Validation [1/4] Loss: 0.43697 focal_loss 0.37122 dice_loss 0.06576 +Epoch [3748/4000] Validation [2/4] Loss: 0.90017 focal_loss 0.70350 dice_loss 0.19667 +Epoch [3748/4000] Validation [3/4] Loss: 0.53459 focal_loss 0.44289 dice_loss 0.09170 +Epoch [3748/4000] Validation [4/4] Loss: 0.39743 focal_loss 0.29270 dice_loss 0.10472 +Epoch [3748/4000] Validation metric {'Val/mean dice_metric': 0.9739664793014526, 'Val/mean miou_metric': 0.959439754486084, 'Val/mean f1': 0.9760038256645203, 'Val/mean precision': 0.9738800525665283, 'Val/mean recall': 0.9781367778778076, 'Val/mean hd95_metric': 4.76698112487793} +Cheakpoint... +Epoch [3748/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739664793014526, 'Val/mean miou_metric': 0.959439754486084, 'Val/mean f1': 0.9760038256645203, 'Val/mean precision': 0.9738800525665283, 'Val/mean recall': 0.9781367778778076, 'Val/mean hd95_metric': 4.76698112487793} +Epoch [3749/4000] Training [1/16] Loss: 0.00230 +Epoch [3749/4000] Training [2/16] Loss: 0.00129 +Epoch [3749/4000] Training [3/16] Loss: 0.00266 +Epoch [3749/4000] Training [4/16] Loss: 0.00195 +Epoch [3749/4000] Training [5/16] Loss: 0.00282 +Epoch [3749/4000] Training [6/16] Loss: 0.00244 +Epoch [3749/4000] Training [7/16] Loss: 0.00241 +Epoch [3749/4000] Training [8/16] Loss: 0.00280 +Epoch [3749/4000] Training [9/16] Loss: 0.00205 +Epoch [3749/4000] Training [10/16] Loss: 0.00210 +Epoch [3749/4000] Training [11/16] Loss: 0.00253 +Epoch [3749/4000] Training [12/16] Loss: 0.00212 +Epoch [3749/4000] Training [13/16] Loss: 0.00200 +Epoch [3749/4000] Training [14/16] Loss: 0.00189 +Epoch [3749/4000] Training [15/16] Loss: 0.00360 +Epoch [3749/4000] Training [16/16] Loss: 0.00231 +Epoch [3749/4000] Training metric {'Train/mean dice_metric': 0.9989011883735657, 'Train/mean miou_metric': 0.9975279569625854, 'Train/mean f1': 0.9939277768135071, 'Train/mean precision': 0.9894034266471863, 'Train/mean recall': 0.9984936714172363, 'Train/mean hd95_metric': 0.4778596758842468} +Epoch [3749/4000] Validation [1/4] Loss: 0.41748 focal_loss 0.35489 dice_loss 0.06259 +Epoch [3749/4000] Validation [2/4] Loss: 0.62795 focal_loss 0.46763 dice_loss 0.16032 +Epoch [3749/4000] Validation [3/4] Loss: 0.56312 focal_loss 0.46265 dice_loss 0.10047 +Epoch [3749/4000] Validation [4/4] Loss: 0.39386 focal_loss 0.28958 dice_loss 0.10428 +Epoch [3749/4000] Validation metric {'Val/mean dice_metric': 0.9752237200737, 'Val/mean miou_metric': 0.9612275958061218, 'Val/mean f1': 0.97636878490448, 'Val/mean precision': 0.9738785028457642, 'Val/mean recall': 0.9788718223571777, 'Val/mean hd95_metric': 4.781573295593262} +Cheakpoint... +Epoch [3749/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752237200737, 'Val/mean miou_metric': 0.9612275958061218, 'Val/mean f1': 0.97636878490448, 'Val/mean precision': 0.9738785028457642, 'Val/mean recall': 0.9788718223571777, 'Val/mean hd95_metric': 4.781573295593262} +Epoch [3750/4000] Training [1/16] Loss: 0.00213 +Epoch [3750/4000] Training [2/16] Loss: 0.00375 +Epoch [3750/4000] Training [3/16] Loss: 0.00194 +Epoch [3750/4000] Training [4/16] Loss: 0.00203 +Epoch [3750/4000] Training [5/16] Loss: 0.00238 +Epoch [3750/4000] Training [6/16] Loss: 0.00253 +Epoch [3750/4000] Training [7/16] Loss: 0.00210 +Epoch [3750/4000] Training [8/16] Loss: 0.00216 +Epoch [3750/4000] Training [9/16] Loss: 0.00443 +Epoch [3750/4000] Training [10/16] Loss: 0.00164 +Epoch [3750/4000] Training [11/16] Loss: 0.00205 +Epoch [3750/4000] Training [12/16] Loss: 0.00183 +Epoch [3750/4000] Training [13/16] Loss: 0.00341 +Epoch [3750/4000] Training [14/16] Loss: 0.00227 +Epoch [3750/4000] Training [15/16] Loss: 0.00209 +Epoch [3750/4000] Training [16/16] Loss: 0.00296 +Epoch [3750/4000] Training metric {'Train/mean dice_metric': 0.9988372921943665, 'Train/mean miou_metric': 0.9973922967910767, 'Train/mean f1': 0.9936812520027161, 'Train/mean precision': 0.9889665246009827, 'Train/mean recall': 0.9984413385391235, 'Train/mean hd95_metric': 0.500320553779602} +Epoch [3750/4000] Validation [1/4] Loss: 0.38624 focal_loss 0.32503 dice_loss 0.06121 +Epoch [3750/4000] Validation [2/4] Loss: 1.39578 focal_loss 1.12073 dice_loss 0.27504 +Epoch [3750/4000] Validation [3/4] Loss: 0.58421 focal_loss 0.48663 dice_loss 0.09758 +Epoch [3750/4000] Validation [4/4] Loss: 0.42512 focal_loss 0.32127 dice_loss 0.10385 +Epoch [3750/4000] Validation metric {'Val/mean dice_metric': 0.9731176495552063, 'Val/mean miou_metric': 0.9594847559928894, 'Val/mean f1': 0.9756434559822083, 'Val/mean precision': 0.9735041856765747, 'Val/mean recall': 0.9777921438217163, 'Val/mean hd95_metric': 5.3584885597229} +Cheakpoint... +Epoch [3750/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731176495552063, 'Val/mean miou_metric': 0.9594847559928894, 'Val/mean f1': 0.9756434559822083, 'Val/mean precision': 0.9735041856765747, 'Val/mean recall': 0.9777921438217163, 'Val/mean hd95_metric': 5.3584885597229} +Epoch [3751/4000] Training [1/16] Loss: 0.00382 +Epoch [3751/4000] Training [2/16] Loss: 0.00267 +Epoch [3751/4000] Training [3/16] Loss: 0.00242 +Epoch [3751/4000] Training [4/16] Loss: 0.00245 +Epoch [3751/4000] Training [5/16] Loss: 0.00262 +Epoch [3751/4000] Training [6/16] Loss: 0.00255 +Epoch [3751/4000] Training [7/16] Loss: 0.00236 +Epoch [3751/4000] Training [8/16] Loss: 0.00216 +Epoch [3751/4000] Training [9/16] Loss: 0.00200 +Epoch [3751/4000] Training [10/16] Loss: 0.00225 +Epoch [3751/4000] Training [11/16] Loss: 0.00201 +Epoch [3751/4000] Training [12/16] Loss: 0.00217 +Epoch [3751/4000] Training [13/16] Loss: 0.00279 +Epoch [3751/4000] Training [14/16] Loss: 0.00181 +Epoch [3751/4000] Training [15/16] Loss: 0.00257 +Epoch [3751/4000] Training [16/16] Loss: 0.00253 +Epoch [3751/4000] Training metric {'Train/mean dice_metric': 0.9988479614257812, 'Train/mean miou_metric': 0.9973994493484497, 'Train/mean f1': 0.993459165096283, 'Train/mean precision': 0.9886163473129272, 'Train/mean recall': 0.998349666595459, 'Train/mean hd95_metric': 0.5527620315551758} +Epoch [3751/4000] Validation [1/4] Loss: 0.41865 focal_loss 0.35585 dice_loss 0.06281 +Epoch [3751/4000] Validation [2/4] Loss: 0.47289 focal_loss 0.36528 dice_loss 0.10761 +Epoch [3751/4000] Validation [3/4] Loss: 0.57427 focal_loss 0.47864 dice_loss 0.09563 +Epoch [3751/4000] Validation [4/4] Loss: 0.38885 focal_loss 0.29798 dice_loss 0.09087 +Epoch [3751/4000] Validation metric {'Val/mean dice_metric': 0.9749840497970581, 'Val/mean miou_metric': 0.9609886407852173, 'Val/mean f1': 0.9762966632843018, 'Val/mean precision': 0.9739124178886414, 'Val/mean recall': 0.9786925911903381, 'Val/mean hd95_metric': 5.035117149353027} +Cheakpoint... +Epoch [3751/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749840497970581, 'Val/mean miou_metric': 0.9609886407852173, 'Val/mean f1': 0.9762966632843018, 'Val/mean precision': 0.9739124178886414, 'Val/mean recall': 0.9786925911903381, 'Val/mean hd95_metric': 5.035117149353027} +Epoch [3752/4000] Training [1/16] Loss: 0.00271 +Epoch [3752/4000] Training [2/16] Loss: 0.00269 +Epoch [3752/4000] Training [3/16] Loss: 0.00208 +Epoch [3752/4000] Training [4/16] Loss: 0.00225 +Epoch [3752/4000] Training [5/16] Loss: 0.00324 +Epoch [3752/4000] Training [6/16] Loss: 0.00219 +Epoch [3752/4000] Training [7/16] Loss: 0.00270 +Epoch [3752/4000] Training [8/16] Loss: 0.00230 +Epoch [3752/4000] Training [9/16] Loss: 0.00191 +Epoch [3752/4000] Training [10/16] Loss: 0.00236 +Epoch [3752/4000] Training [11/16] Loss: 0.00219 +Epoch [3752/4000] Training [12/16] Loss: 0.00181 +Epoch [3752/4000] Training [13/16] Loss: 0.00283 +Epoch [3752/4000] Training [14/16] Loss: 0.00246 +Epoch [3752/4000] Training [15/16] Loss: 0.00190 +Epoch [3752/4000] Training [16/16] Loss: 0.01038 +Epoch [3752/4000] Training metric {'Train/mean dice_metric': 0.9986844062805176, 'Train/mean miou_metric': 0.9970970153808594, 'Train/mean f1': 0.9936299920082092, 'Train/mean precision': 0.9891793131828308, 'Train/mean recall': 0.998120903968811, 'Train/mean hd95_metric': 0.5620402097702026} +Epoch [3752/4000] Validation [1/4] Loss: 0.40302 focal_loss 0.33933 dice_loss 0.06369 +Epoch [3752/4000] Validation [2/4] Loss: 0.66148 focal_loss 0.49192 dice_loss 0.16956 +Epoch [3752/4000] Validation [3/4] Loss: 0.50123 focal_loss 0.41146 dice_loss 0.08977 +Epoch [3752/4000] Validation [4/4] Loss: 0.35196 focal_loss 0.24709 dice_loss 0.10487 +Epoch [3752/4000] Validation metric {'Val/mean dice_metric': 0.9726517796516418, 'Val/mean miou_metric': 0.9587377309799194, 'Val/mean f1': 0.9759690165519714, 'Val/mean precision': 0.9749503135681152, 'Val/mean recall': 0.9769899845123291, 'Val/mean hd95_metric': 4.907043933868408} +Cheakpoint... +Epoch [3752/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726517796516418, 'Val/mean miou_metric': 0.9587377309799194, 'Val/mean f1': 0.9759690165519714, 'Val/mean precision': 0.9749503135681152, 'Val/mean recall': 0.9769899845123291, 'Val/mean hd95_metric': 4.907043933868408} +Epoch [3753/4000] Training [1/16] Loss: 0.00264 +Epoch [3753/4000] Training [2/16] Loss: 0.00163 +Epoch [3753/4000] Training [3/16] Loss: 0.00215 +Epoch [3753/4000] Training [4/16] Loss: 0.00140 +Epoch [3753/4000] Training [5/16] Loss: 0.00311 +Epoch [3753/4000] Training [6/16] Loss: 0.00226 +Epoch [3753/4000] Training [7/16] Loss: 0.00337 +Epoch [3753/4000] Training [8/16] Loss: 0.00276 +Epoch [3753/4000] Training [9/16] Loss: 0.00153 +Epoch [3753/4000] Training [10/16] Loss: 0.00273 +Epoch [3753/4000] Training [11/16] Loss: 0.00348 +Epoch [3753/4000] Training [12/16] Loss: 0.00219 +Epoch [3753/4000] Training [13/16] Loss: 0.00228 +Epoch [3753/4000] Training [14/16] Loss: 0.00216 +Epoch [3753/4000] Training [15/16] Loss: 0.00316 +Epoch [3753/4000] Training [16/16] Loss: 0.00354 +Epoch [3753/4000] Training metric {'Train/mean dice_metric': 0.9987716674804688, 'Train/mean miou_metric': 0.9972546100616455, 'Train/mean f1': 0.9937154054641724, 'Train/mean precision': 0.9890295267105103, 'Train/mean recall': 0.9984458684921265, 'Train/mean hd95_metric': 0.4887971878051758} +Epoch [3753/4000] Validation [1/4] Loss: 0.41810 focal_loss 0.35373 dice_loss 0.06437 +Epoch [3753/4000] Validation [2/4] Loss: 0.48988 focal_loss 0.37752 dice_loss 0.11236 +Epoch [3753/4000] Validation [3/4] Loss: 0.55051 focal_loss 0.45281 dice_loss 0.09770 +Epoch [3753/4000] Validation [4/4] Loss: 0.36130 focal_loss 0.27319 dice_loss 0.08811 +Epoch [3753/4000] Validation metric {'Val/mean dice_metric': 0.9747929573059082, 'Val/mean miou_metric': 0.9606965780258179, 'Val/mean f1': 0.9764378666877747, 'Val/mean precision': 0.9741215109825134, 'Val/mean recall': 0.9787653684616089, 'Val/mean hd95_metric': 4.831560134887695} +Cheakpoint... +Epoch [3753/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747929573059082, 'Val/mean miou_metric': 0.9606965780258179, 'Val/mean f1': 0.9764378666877747, 'Val/mean precision': 0.9741215109825134, 'Val/mean recall': 0.9787653684616089, 'Val/mean hd95_metric': 4.831560134887695} +Epoch [3754/4000] Training [1/16] Loss: 0.00168 +Epoch [3754/4000] Training [2/16] Loss: 0.00301 +Epoch [3754/4000] Training [3/16] Loss: 0.00272 +Epoch [3754/4000] Training [4/16] Loss: 0.00222 +Epoch [3754/4000] Training [5/16] Loss: 0.00184 +Epoch [3754/4000] Training [6/16] Loss: 0.00228 +Epoch [3754/4000] Training [7/16] Loss: 0.00155 +Epoch [3754/4000] Training [8/16] Loss: 0.00254 +Epoch [3754/4000] Training [9/16] Loss: 0.00244 +Epoch [3754/4000] Training [10/16] Loss: 0.00265 +Epoch [3754/4000] Training [11/16] Loss: 0.00323 +Epoch [3754/4000] Training [12/16] Loss: 0.00170 +Epoch [3754/4000] Training [13/16] Loss: 0.00238 +Epoch [3754/4000] Training [14/16] Loss: 0.00315 +Epoch [3754/4000] Training [15/16] Loss: 0.00300 +Epoch [3754/4000] Training [16/16] Loss: 0.00191 +Epoch [3754/4000] Training metric {'Train/mean dice_metric': 0.9988664388656616, 'Train/mean miou_metric': 0.997458815574646, 'Train/mean f1': 0.9938979148864746, 'Train/mean precision': 0.9893884658813477, 'Train/mean recall': 0.9984486699104309, 'Train/mean hd95_metric': 0.49172672629356384} +Epoch [3754/4000] Validation [1/4] Loss: 0.41514 focal_loss 0.35258 dice_loss 0.06256 +Epoch [3754/4000] Validation [2/4] Loss: 0.49764 focal_loss 0.38591 dice_loss 0.11174 +Epoch [3754/4000] Validation [3/4] Loss: 0.57719 focal_loss 0.47289 dice_loss 0.10429 +Epoch [3754/4000] Validation [4/4] Loss: 0.33809 focal_loss 0.25249 dice_loss 0.08560 +Epoch [3754/4000] Validation metric {'Val/mean dice_metric': 0.9731358289718628, 'Val/mean miou_metric': 0.9593545198440552, 'Val/mean f1': 0.9761683940887451, 'Val/mean precision': 0.9739665985107422, 'Val/mean recall': 0.9783802032470703, 'Val/mean hd95_metric': 5.398803234100342} +Cheakpoint... +Epoch [3754/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731358289718628, 'Val/mean miou_metric': 0.9593545198440552, 'Val/mean f1': 0.9761683940887451, 'Val/mean precision': 0.9739665985107422, 'Val/mean recall': 0.9783802032470703, 'Val/mean hd95_metric': 5.398803234100342} +Epoch [3755/4000] Training [1/16] Loss: 0.00157 +Epoch [3755/4000] Training [2/16] Loss: 0.00223 +Epoch [3755/4000] Training [3/16] Loss: 0.00292 +Epoch [3755/4000] Training [4/16] Loss: 0.00334 +Epoch [3755/4000] Training [5/16] Loss: 0.00241 +Epoch [3755/4000] Training [6/16] Loss: 0.00368 +Epoch [3755/4000] Training [7/16] Loss: 0.00253 +Epoch [3755/4000] Training [8/16] Loss: 0.00262 +Epoch [3755/4000] Training [9/16] Loss: 0.00881 +Epoch [3755/4000] Training [10/16] Loss: 0.00216 +Epoch [3755/4000] Training [11/16] Loss: 0.00158 +Epoch [3755/4000] Training [12/16] Loss: 0.00205 +Epoch [3755/4000] Training [13/16] Loss: 0.00181 +Epoch [3755/4000] Training [14/16] Loss: 0.00235 +Epoch [3755/4000] Training [15/16] Loss: 0.00196 +Epoch [3755/4000] Training [16/16] Loss: 0.00188 +Epoch [3755/4000] Training metric {'Train/mean dice_metric': 0.9987863898277283, 'Train/mean miou_metric': 0.9972946047782898, 'Train/mean f1': 0.9937875866889954, 'Train/mean precision': 0.9892309308052063, 'Train/mean recall': 0.9983863830566406, 'Train/mean hd95_metric': 0.4995611906051636} +Epoch [3755/4000] Validation [1/4] Loss: 0.40080 focal_loss 0.33703 dice_loss 0.06377 +Epoch [3755/4000] Validation [2/4] Loss: 0.53670 focal_loss 0.40590 dice_loss 0.13081 +Epoch [3755/4000] Validation [3/4] Loss: 0.56781 focal_loss 0.46823 dice_loss 0.09958 +Epoch [3755/4000] Validation [4/4] Loss: 0.57945 focal_loss 0.45020 dice_loss 0.12925 +Epoch [3755/4000] Validation metric {'Val/mean dice_metric': 0.9743766784667969, 'Val/mean miou_metric': 0.9602231979370117, 'Val/mean f1': 0.9755387902259827, 'Val/mean precision': 0.9724097847938538, 'Val/mean recall': 0.9786880612373352, 'Val/mean hd95_metric': 5.457243919372559} +Cheakpoint... +Epoch [3755/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743766784667969, 'Val/mean miou_metric': 0.9602231979370117, 'Val/mean f1': 0.9755387902259827, 'Val/mean precision': 0.9724097847938538, 'Val/mean recall': 0.9786880612373352, 'Val/mean hd95_metric': 5.457243919372559} +Epoch [3756/4000] Training [1/16] Loss: 0.00265 +Epoch [3756/4000] Training [2/16] Loss: 0.00251 +Epoch [3756/4000] Training [3/16] Loss: 0.00311 +Epoch [3756/4000] Training [4/16] Loss: 0.00280 +Epoch [3756/4000] Training [5/16] Loss: 0.00363 +Epoch [3756/4000] Training [6/16] Loss: 0.00266 +Epoch [3756/4000] Training [7/16] Loss: 0.00166 +Epoch [3756/4000] Training [8/16] Loss: 0.00272 +Epoch [3756/4000] Training [9/16] Loss: 0.00260 +Epoch [3756/4000] Training [10/16] Loss: 0.00382 +Epoch [3756/4000] Training [11/16] Loss: 0.00212 +Epoch [3756/4000] Training [12/16] Loss: 0.00477 +Epoch [3756/4000] Training [13/16] Loss: 0.00175 +Epoch [3756/4000] Training [14/16] Loss: 0.00230 +Epoch [3756/4000] Training [15/16] Loss: 0.00325 +Epoch [3756/4000] Training [16/16] Loss: 0.00248 +Epoch [3756/4000] Training metric {'Train/mean dice_metric': 0.9985628128051758, 'Train/mean miou_metric': 0.9968277215957642, 'Train/mean f1': 0.9931166768074036, 'Train/mean precision': 0.9881003499031067, 'Train/mean recall': 0.9981842637062073, 'Train/mean hd95_metric': 0.6025667190551758} +Epoch [3756/4000] Validation [1/4] Loss: 0.41646 focal_loss 0.35408 dice_loss 0.06238 +Epoch [3756/4000] Validation [2/4] Loss: 0.89610 focal_loss 0.69607 dice_loss 0.20002 +Epoch [3756/4000] Validation [3/4] Loss: 0.50080 focal_loss 0.40587 dice_loss 0.09493 +Epoch [3756/4000] Validation [4/4] Loss: 0.35251 focal_loss 0.25882 dice_loss 0.09369 +Epoch [3756/4000] Validation metric {'Val/mean dice_metric': 0.9726072549819946, 'Val/mean miou_metric': 0.958636462688446, 'Val/mean f1': 0.9756595492362976, 'Val/mean precision': 0.9732531309127808, 'Val/mean recall': 0.9780780076980591, 'Val/mean hd95_metric': 4.778531551361084} +Cheakpoint... +Epoch [3756/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726072549819946, 'Val/mean miou_metric': 0.958636462688446, 'Val/mean f1': 0.9756595492362976, 'Val/mean precision': 0.9732531309127808, 'Val/mean recall': 0.9780780076980591, 'Val/mean hd95_metric': 4.778531551361084} +Epoch [3757/4000] Training [1/16] Loss: 0.00190 +Epoch [3757/4000] Training [2/16] Loss: 0.00290 +Epoch [3757/4000] Training [3/16] Loss: 0.00323 +Epoch [3757/4000] Training [4/16] Loss: 0.00253 +Epoch [3757/4000] Training [5/16] Loss: 0.00196 +Epoch [3757/4000] Training [6/16] Loss: 0.00193 +Epoch [3757/4000] Training [7/16] Loss: 0.00255 +Epoch [3757/4000] Training [8/16] Loss: 0.00160 +Epoch [3757/4000] Training [9/16] Loss: 0.00294 +Epoch [3757/4000] Training [10/16] Loss: 0.00215 +Epoch [3757/4000] Training [11/16] Loss: 0.00242 +Epoch [3757/4000] Training [12/16] Loss: 0.00272 +Epoch [3757/4000] Training [13/16] Loss: 0.00292 +Epoch [3757/4000] Training [14/16] Loss: 0.00163 +Epoch [3757/4000] Training [15/16] Loss: 0.00192 +Epoch [3757/4000] Training [16/16] Loss: 0.00392 +Epoch [3757/4000] Training metric {'Train/mean dice_metric': 0.9987472295761108, 'Train/mean miou_metric': 0.9972146153450012, 'Train/mean f1': 0.9935922622680664, 'Train/mean precision': 0.9889306426048279, 'Train/mean recall': 0.9982980489730835, 'Train/mean hd95_metric': 0.532547116279602} +Epoch [3757/4000] Validation [1/4] Loss: 0.39312 focal_loss 0.33134 dice_loss 0.06178 +Epoch [3757/4000] Validation [2/4] Loss: 0.52464 focal_loss 0.39343 dice_loss 0.13121 +Epoch [3757/4000] Validation [3/4] Loss: 0.55028 focal_loss 0.45129 dice_loss 0.09899 +Epoch [3757/4000] Validation [4/4] Loss: 0.43945 focal_loss 0.32837 dice_loss 0.11108 +Epoch [3757/4000] Validation metric {'Val/mean dice_metric': 0.973096489906311, 'Val/mean miou_metric': 0.959175705909729, 'Val/mean f1': 0.9760376811027527, 'Val/mean precision': 0.9740450382232666, 'Val/mean recall': 0.9780384302139282, 'Val/mean hd95_metric': 4.7937912940979} +Cheakpoint... +Epoch [3757/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973096489906311, 'Val/mean miou_metric': 0.959175705909729, 'Val/mean f1': 0.9760376811027527, 'Val/mean precision': 0.9740450382232666, 'Val/mean recall': 0.9780384302139282, 'Val/mean hd95_metric': 4.7937912940979} +Epoch [3758/4000] Training [1/16] Loss: 0.00248 +Epoch [3758/4000] Training [2/16] Loss: 0.00257 +Epoch [3758/4000] Training [3/16] Loss: 0.00308 +Epoch [3758/4000] Training [4/16] Loss: 0.00217 +Epoch [3758/4000] Training [5/16] Loss: 0.00167 +Epoch [3758/4000] Training [6/16] Loss: 0.00272 +Epoch [3758/4000] Training [7/16] Loss: 0.00505 +Epoch [3758/4000] Training [8/16] Loss: 0.00388 +Epoch [3758/4000] Training [9/16] Loss: 0.00161 +Epoch [3758/4000] Training [10/16] Loss: 0.00212 +Epoch [3758/4000] Training [11/16] Loss: 0.00205 +Epoch [3758/4000] Training [12/16] Loss: 0.00245 +Epoch [3758/4000] Training [13/16] Loss: 0.00162 +Epoch [3758/4000] Training [14/16] Loss: 0.00226 +Epoch [3758/4000] Training [15/16] Loss: 0.00179 +Epoch [3758/4000] Training [16/16] Loss: 0.00405 +Epoch [3758/4000] Training metric {'Train/mean dice_metric': 0.9987760186195374, 'Train/mean miou_metric': 0.9972727298736572, 'Train/mean f1': 0.9937363266944885, 'Train/mean precision': 0.989136815071106, 'Train/mean recall': 0.9983788728713989, 'Train/mean hd95_metric': 0.5100291967391968} +Epoch [3758/4000] Validation [1/4] Loss: 0.39481 focal_loss 0.33288 dice_loss 0.06193 +Epoch [3758/4000] Validation [2/4] Loss: 0.53144 focal_loss 0.40200 dice_loss 0.12944 +Epoch [3758/4000] Validation [3/4] Loss: 0.53318 focal_loss 0.43827 dice_loss 0.09490 +Epoch [3758/4000] Validation [4/4] Loss: 0.51811 focal_loss 0.40597 dice_loss 0.11214 +Epoch [3758/4000] Validation metric {'Val/mean dice_metric': 0.9733951687812805, 'Val/mean miou_metric': 0.9593344926834106, 'Val/mean f1': 0.9763537049293518, 'Val/mean precision': 0.9740655422210693, 'Val/mean recall': 0.9786525368690491, 'Val/mean hd95_metric': 4.879329204559326} +Cheakpoint... +Epoch [3758/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733951687812805, 'Val/mean miou_metric': 0.9593344926834106, 'Val/mean f1': 0.9763537049293518, 'Val/mean precision': 0.9740655422210693, 'Val/mean recall': 0.9786525368690491, 'Val/mean hd95_metric': 4.879329204559326} +Epoch [3759/4000] Training [1/16] Loss: 0.00225 +Epoch [3759/4000] Training [2/16] Loss: 0.00235 +Epoch [3759/4000] Training [3/16] Loss: 0.00216 +Epoch [3759/4000] Training [4/16] Loss: 0.00268 +Epoch [3759/4000] Training [5/16] Loss: 0.00274 +Epoch [3759/4000] Training [6/16] Loss: 0.00431 +Epoch [3759/4000] Training [7/16] Loss: 0.00348 +Epoch [3759/4000] Training [8/16] Loss: 0.00226 +Epoch [3759/4000] Training [9/16] Loss: 0.00270 +Epoch [3759/4000] Training [10/16] Loss: 0.00284 +Epoch [3759/4000] Training [11/16] Loss: 0.00203 +Epoch [3759/4000] Training [12/16] Loss: 0.00261 +Epoch [3759/4000] Training [13/16] Loss: 0.00215 +Epoch [3759/4000] Training [14/16] Loss: 0.00189 +Epoch [3759/4000] Training [15/16] Loss: 0.00198 +Epoch [3759/4000] Training [16/16] Loss: 0.00294 +Epoch [3759/4000] Training metric {'Train/mean dice_metric': 0.9987803101539612, 'Train/mean miou_metric': 0.9972845911979675, 'Train/mean f1': 0.9938206672668457, 'Train/mean precision': 0.9892861843109131, 'Train/mean recall': 0.9983969926834106, 'Train/mean hd95_metric': 0.55002760887146} +Epoch [3759/4000] Validation [1/4] Loss: 0.38045 focal_loss 0.31740 dice_loss 0.06305 +Epoch [3759/4000] Validation [2/4] Loss: 0.52802 focal_loss 0.39669 dice_loss 0.13133 +Epoch [3759/4000] Validation [3/4] Loss: 0.53704 focal_loss 0.43640 dice_loss 0.10064 +Epoch [3759/4000] Validation [4/4] Loss: 0.41519 focal_loss 0.30989 dice_loss 0.10530 +Epoch [3759/4000] Validation metric {'Val/mean dice_metric': 0.9746581315994263, 'Val/mean miou_metric': 0.9602481722831726, 'Val/mean f1': 0.9766169190406799, 'Val/mean precision': 0.973798930644989, 'Val/mean recall': 0.9794510006904602, 'Val/mean hd95_metric': 4.8853349685668945} +Cheakpoint... +Epoch [3759/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746581315994263, 'Val/mean miou_metric': 0.9602481722831726, 'Val/mean f1': 0.9766169190406799, 'Val/mean precision': 0.973798930644989, 'Val/mean recall': 0.9794510006904602, 'Val/mean hd95_metric': 4.8853349685668945} +Epoch [3760/4000] Training [1/16] Loss: 0.00256 +Epoch [3760/4000] Training [2/16] Loss: 0.00229 +Epoch [3760/4000] Training [3/16] Loss: 0.00248 +Epoch [3760/4000] Training [4/16] Loss: 0.00209 +Epoch [3760/4000] Training [5/16] Loss: 0.00141 +Epoch [3760/4000] Training [6/16] Loss: 0.00287 +Epoch [3760/4000] Training [7/16] Loss: 0.00257 +Epoch [3760/4000] Training [8/16] Loss: 0.00174 +Epoch [3760/4000] Training [9/16] Loss: 0.00263 +Epoch [3760/4000] Training [10/16] Loss: 0.00440 +Epoch [3760/4000] Training [11/16] Loss: 0.00224 +Epoch [3760/4000] Training [12/16] Loss: 0.00225 +Epoch [3760/4000] Training [13/16] Loss: 0.00216 +Epoch [3760/4000] Training [14/16] Loss: 0.00287 +Epoch [3760/4000] Training [15/16] Loss: 0.00320 +Epoch [3760/4000] Training [16/16] Loss: 0.00223 +Epoch [3760/4000] Training metric {'Train/mean dice_metric': 0.998751699924469, 'Train/mean miou_metric': 0.9972313642501831, 'Train/mean f1': 0.9938126802444458, 'Train/mean precision': 0.9893261194229126, 'Train/mean recall': 0.9983401298522949, 'Train/mean hd95_metric': 0.5478566884994507} +Epoch [3760/4000] Validation [1/4] Loss: 0.42521 focal_loss 0.36117 dice_loss 0.06405 +Epoch [3760/4000] Validation [2/4] Loss: 0.53198 focal_loss 0.40160 dice_loss 0.13039 +Epoch [3760/4000] Validation [3/4] Loss: 0.52596 focal_loss 0.43658 dice_loss 0.08938 +Epoch [3760/4000] Validation [4/4] Loss: 0.38475 focal_loss 0.28599 dice_loss 0.09876 +Epoch [3760/4000] Validation metric {'Val/mean dice_metric': 0.9762052297592163, 'Val/mean miou_metric': 0.9615906476974487, 'Val/mean f1': 0.9768097996711731, 'Val/mean precision': 0.9744544625282288, 'Val/mean recall': 0.9791765213012695, 'Val/mean hd95_metric': 4.633836269378662} +Cheakpoint... +Epoch [3760/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9762052297592163, 'Val/mean miou_metric': 0.9615906476974487, 'Val/mean f1': 0.9768097996711731, 'Val/mean precision': 0.9744544625282288, 'Val/mean recall': 0.9791765213012695, 'Val/mean hd95_metric': 4.633836269378662} +Epoch [3761/4000] Training [1/16] Loss: 0.00296 +Epoch [3761/4000] Training [2/16] Loss: 0.00171 +Epoch [3761/4000] Training [3/16] Loss: 0.00499 +Epoch [3761/4000] Training [4/16] Loss: 0.00265 +Epoch [3761/4000] Training [5/16] Loss: 0.00181 +Epoch [3761/4000] Training [6/16] Loss: 0.00217 +Epoch [3761/4000] Training [7/16] Loss: 0.00198 +Epoch [3761/4000] Training [8/16] Loss: 0.00227 +Epoch [3761/4000] Training [9/16] Loss: 0.00181 +Epoch [3761/4000] Training [10/16] Loss: 0.00326 +Epoch [3761/4000] Training [11/16] Loss: 0.00269 +Epoch [3761/4000] Training [12/16] Loss: 0.00180 +Epoch [3761/4000] Training [13/16] Loss: 0.00400 +Epoch [3761/4000] Training [14/16] Loss: 0.00195 +Epoch [3761/4000] Training [15/16] Loss: 0.00236 +Epoch [3761/4000] Training [16/16] Loss: 0.00244 +Epoch [3761/4000] Training metric {'Train/mean dice_metric': 0.9986884593963623, 'Train/mean miou_metric': 0.9970766305923462, 'Train/mean f1': 0.993196964263916, 'Train/mean precision': 0.988131046295166, 'Train/mean recall': 0.9983150362968445, 'Train/mean hd95_metric': 0.5479767918586731} +Epoch [3761/4000] Validation [1/4] Loss: 0.38554 focal_loss 0.32318 dice_loss 0.06236 +Epoch [3761/4000] Validation [2/4] Loss: 0.99996 focal_loss 0.80655 dice_loss 0.19340 +Epoch [3761/4000] Validation [3/4] Loss: 0.52479 focal_loss 0.43467 dice_loss 0.09012 +Epoch [3761/4000] Validation [4/4] Loss: 0.27494 focal_loss 0.19234 dice_loss 0.08259 +Epoch [3761/4000] Validation metric {'Val/mean dice_metric': 0.9732692837715149, 'Val/mean miou_metric': 0.9599161148071289, 'Val/mean f1': 0.9760267734527588, 'Val/mean precision': 0.9736273288726807, 'Val/mean recall': 0.9784379601478577, 'Val/mean hd95_metric': 4.853928089141846} +Cheakpoint... +Epoch [3761/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732692837715149, 'Val/mean miou_metric': 0.9599161148071289, 'Val/mean f1': 0.9760267734527588, 'Val/mean precision': 0.9736273288726807, 'Val/mean recall': 0.9784379601478577, 'Val/mean hd95_metric': 4.853928089141846} +Epoch [3762/4000] Training [1/16] Loss: 0.00206 +Epoch [3762/4000] Training [2/16] Loss: 0.00358 +Epoch [3762/4000] Training [3/16] Loss: 0.00247 +Epoch [3762/4000] Training [4/16] Loss: 0.00322 +Epoch [3762/4000] Training [5/16] Loss: 0.00210 +Epoch [3762/4000] Training [6/16] Loss: 0.00310 +Epoch [3762/4000] Training [7/16] Loss: 0.00340 +Epoch [3762/4000] Training [8/16] Loss: 0.00218 +Epoch [3762/4000] Training [9/16] Loss: 0.00208 +Epoch [3762/4000] Training [10/16] Loss: 0.00197 +Epoch [3762/4000] Training [11/16] Loss: 0.00247 +Epoch [3762/4000] Training [12/16] Loss: 0.00149 +Epoch [3762/4000] Training [13/16] Loss: 0.00245 +Epoch [3762/4000] Training [14/16] Loss: 0.00193 +Epoch [3762/4000] Training [15/16] Loss: 0.00390 +Epoch [3762/4000] Training [16/16] Loss: 0.00148 +Epoch [3762/4000] Training metric {'Train/mean dice_metric': 0.9986960887908936, 'Train/mean miou_metric': 0.9971212148666382, 'Train/mean f1': 0.9937716126441956, 'Train/mean precision': 0.9892386794090271, 'Train/mean recall': 0.998346209526062, 'Train/mean hd95_metric': 0.5337467789649963} +Epoch [3762/4000] Validation [1/4] Loss: 0.38038 focal_loss 0.31988 dice_loss 0.06050 +Epoch [3762/4000] Validation [2/4] Loss: 0.96579 focal_loss 0.77815 dice_loss 0.18764 +Epoch [3762/4000] Validation [3/4] Loss: 0.52207 focal_loss 0.43101 dice_loss 0.09106 +Epoch [3762/4000] Validation [4/4] Loss: 0.49587 focal_loss 0.38952 dice_loss 0.10636 +Epoch [3762/4000] Validation metric {'Val/mean dice_metric': 0.9745914340019226, 'Val/mean miou_metric': 0.9607337713241577, 'Val/mean f1': 0.9761934280395508, 'Val/mean precision': 0.9732682108879089, 'Val/mean recall': 0.9791365265846252, 'Val/mean hd95_metric': 5.091002941131592} +Cheakpoint... +Epoch [3762/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745914340019226, 'Val/mean miou_metric': 0.9607337713241577, 'Val/mean f1': 0.9761934280395508, 'Val/mean precision': 0.9732682108879089, 'Val/mean recall': 0.9791365265846252, 'Val/mean hd95_metric': 5.091002941131592} +Epoch [3763/4000] Training [1/16] Loss: 0.00247 +Epoch [3763/4000] Training [2/16] Loss: 0.00201 +Epoch [3763/4000] Training [3/16] Loss: 0.00197 +Epoch [3763/4000] Training [4/16] Loss: 0.00386 +Epoch [3763/4000] Training [5/16] Loss: 0.00335 +Epoch [3763/4000] Training [6/16] Loss: 0.00197 +Epoch [3763/4000] Training [7/16] Loss: 0.00199 +Epoch [3763/4000] Training [8/16] Loss: 0.00201 +Epoch [3763/4000] Training [9/16] Loss: 0.00296 +Epoch [3763/4000] Training [10/16] Loss: 0.00216 +Epoch [3763/4000] Training [11/16] Loss: 0.00267 +Epoch [3763/4000] Training [12/16] Loss: 0.00191 +Epoch [3763/4000] Training [13/16] Loss: 0.00172 +Epoch [3763/4000] Training [14/16] Loss: 0.00244 +Epoch [3763/4000] Training [15/16] Loss: 0.00274 +Epoch [3763/4000] Training [16/16] Loss: 0.00348 +Epoch [3763/4000] Training metric {'Train/mean dice_metric': 0.9988192319869995, 'Train/mean miou_metric': 0.9973543286323547, 'Train/mean f1': 0.9937891960144043, 'Train/mean precision': 0.9892083406448364, 'Train/mean recall': 0.9984127283096313, 'Train/mean hd95_metric': 0.4895784258842468} +Epoch [3763/4000] Validation [1/4] Loss: 0.35788 focal_loss 0.29933 dice_loss 0.05855 +Epoch [3763/4000] Validation [2/4] Loss: 0.51489 focal_loss 0.39810 dice_loss 0.11679 +Epoch [3763/4000] Validation [3/4] Loss: 0.52401 focal_loss 0.43376 dice_loss 0.09025 +Epoch [3763/4000] Validation [4/4] Loss: 0.34768 focal_loss 0.26141 dice_loss 0.08628 +Epoch [3763/4000] Validation metric {'Val/mean dice_metric': 0.9757240414619446, 'Val/mean miou_metric': 0.9619531631469727, 'Val/mean f1': 0.9764610528945923, 'Val/mean precision': 0.9742676019668579, 'Val/mean recall': 0.978664219379425, 'Val/mean hd95_metric': 4.711147308349609} +Cheakpoint... +Epoch [3763/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9757240414619446, 'Val/mean miou_metric': 0.9619531631469727, 'Val/mean f1': 0.9764610528945923, 'Val/mean precision': 0.9742676019668579, 'Val/mean recall': 0.978664219379425, 'Val/mean hd95_metric': 4.711147308349609} +Epoch [3764/4000] Training [1/16] Loss: 0.00179 +Epoch [3764/4000] Training [2/16] Loss: 0.00264 +Epoch [3764/4000] Training [3/16] Loss: 0.00197 +Epoch [3764/4000] Training [4/16] Loss: 0.00263 +Epoch [3764/4000] Training [5/16] Loss: 0.00195 +Epoch [3764/4000] Training [6/16] Loss: 0.00246 +Epoch [3764/4000] Training [7/16] Loss: 0.00359 +Epoch [3764/4000] Training [8/16] Loss: 0.00144 +Epoch [3764/4000] Training [9/16] Loss: 0.00198 +Epoch [3764/4000] Training [10/16] Loss: 0.00369 +Epoch [3764/4000] Training [11/16] Loss: 0.00146 +Epoch [3764/4000] Training [12/16] Loss: 0.00207 +Epoch [3764/4000] Training [13/16] Loss: 0.00214 +Epoch [3764/4000] Training [14/16] Loss: 0.00273 +Epoch [3764/4000] Training [15/16] Loss: 0.00247 +Epoch [3764/4000] Training [16/16] Loss: 0.00223 +Epoch [3764/4000] Training metric {'Train/mean dice_metric': 0.9988818168640137, 'Train/mean miou_metric': 0.9974880814552307, 'Train/mean f1': 0.9938982725143433, 'Train/mean precision': 0.9893638491630554, 'Train/mean recall': 0.9984744787216187, 'Train/mean hd95_metric': 0.48257482051849365} +Epoch [3764/4000] Validation [1/4] Loss: 0.37290 focal_loss 0.31271 dice_loss 0.06018 +Epoch [3764/4000] Validation [2/4] Loss: 0.47885 focal_loss 0.36928 dice_loss 0.10957 +Epoch [3764/4000] Validation [3/4] Loss: 0.56596 focal_loss 0.47115 dice_loss 0.09481 +Epoch [3764/4000] Validation [4/4] Loss: 0.32730 focal_loss 0.23102 dice_loss 0.09628 +Epoch [3764/4000] Validation metric {'Val/mean dice_metric': 0.9742071032524109, 'Val/mean miou_metric': 0.9604514837265015, 'Val/mean f1': 0.9766647219657898, 'Val/mean precision': 0.974452018737793, 'Val/mean recall': 0.9788874983787537, 'Val/mean hd95_metric': 4.943499565124512} +Cheakpoint... +Epoch [3764/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742071032524109, 'Val/mean miou_metric': 0.9604514837265015, 'Val/mean f1': 0.9766647219657898, 'Val/mean precision': 0.974452018737793, 'Val/mean recall': 0.9788874983787537, 'Val/mean hd95_metric': 4.943499565124512} +Epoch [3765/4000] Training [1/16] Loss: 0.00220 +Epoch [3765/4000] Training [2/16] Loss: 0.00338 +Epoch [3765/4000] Training [3/16] Loss: 0.00318 +Epoch [3765/4000] Training [4/16] Loss: 0.00227 +Epoch [3765/4000] Training [5/16] Loss: 0.00425 +Epoch [3765/4000] Training [6/16] Loss: 0.00141 +Epoch [3765/4000] Training [7/16] Loss: 0.00294 +Epoch [3765/4000] Training [8/16] Loss: 0.00328 +Epoch [3765/4000] Training [9/16] Loss: 0.00275 +Epoch [3765/4000] Training [10/16] Loss: 0.00293 +Epoch [3765/4000] Training [11/16] Loss: 0.00200 +Epoch [3765/4000] Training [12/16] Loss: 0.00328 +Epoch [3765/4000] Training [13/16] Loss: 0.00232 +Epoch [3765/4000] Training [14/16] Loss: 0.00188 +Epoch [3765/4000] Training [15/16] Loss: 0.00419 +Epoch [3765/4000] Training [16/16] Loss: 0.00305 +Epoch [3765/4000] Training metric {'Train/mean dice_metric': 0.9984028339385986, 'Train/mean miou_metric': 0.9965395927429199, 'Train/mean f1': 0.9935238361358643, 'Train/mean precision': 0.9889986515045166, 'Train/mean recall': 0.9980906844139099, 'Train/mean hd95_metric': 0.5647568106651306} +Epoch [3765/4000] Validation [1/4] Loss: 0.44374 focal_loss 0.38002 dice_loss 0.06372 +Epoch [3765/4000] Validation [2/4] Loss: 0.54753 focal_loss 0.40671 dice_loss 0.14083 +Epoch [3765/4000] Validation [3/4] Loss: 0.54434 focal_loss 0.45235 dice_loss 0.09199 +Epoch [3765/4000] Validation [4/4] Loss: 0.32581 focal_loss 0.23548 dice_loss 0.09033 +Epoch [3765/4000] Validation metric {'Val/mean dice_metric': 0.9731054306030273, 'Val/mean miou_metric': 0.9588292837142944, 'Val/mean f1': 0.9760423302650452, 'Val/mean precision': 0.9735336303710938, 'Val/mean recall': 0.9785640835762024, 'Val/mean hd95_metric': 4.944446086883545} +Cheakpoint... +Epoch [3765/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731054306030273, 'Val/mean miou_metric': 0.9588292837142944, 'Val/mean f1': 0.9760423302650452, 'Val/mean precision': 0.9735336303710938, 'Val/mean recall': 0.9785640835762024, 'Val/mean hd95_metric': 4.944446086883545} +Epoch [3766/4000] Training [1/16] Loss: 0.00249 +Epoch [3766/4000] Training [2/16] Loss: 0.00180 +Epoch [3766/4000] Training [3/16] Loss: 0.00314 +Epoch [3766/4000] Training [4/16] Loss: 0.00261 +Epoch [3766/4000] Training [5/16] Loss: 0.00288 +Epoch [3766/4000] Training [6/16] Loss: 0.00321 +Epoch [3766/4000] Training [7/16] Loss: 0.00274 +Epoch [3766/4000] Training [8/16] Loss: 0.00215 +Epoch [3766/4000] Training [9/16] Loss: 0.00217 +Epoch [3766/4000] Training [10/16] Loss: 0.00228 +Epoch [3766/4000] Training [11/16] Loss: 0.00221 +Epoch [3766/4000] Training [12/16] Loss: 0.00217 +Epoch [3766/4000] Training [13/16] Loss: 0.00336 +Epoch [3766/4000] Training [14/16] Loss: 0.00283 +Epoch [3766/4000] Training [15/16] Loss: 0.00233 +Epoch [3766/4000] Training [16/16] Loss: 0.00173 +Epoch [3766/4000] Training metric {'Train/mean dice_metric': 0.9987789392471313, 'Train/mean miou_metric': 0.997281551361084, 'Train/mean f1': 0.9937877655029297, 'Train/mean precision': 0.9891971349716187, 'Train/mean recall': 0.9984211921691895, 'Train/mean hd95_metric': 0.5090120434761047} +Epoch [3766/4000] Validation [1/4] Loss: 0.51483 focal_loss 0.44183 dice_loss 0.07299 +Epoch [3766/4000] Validation [2/4] Loss: 0.61446 focal_loss 0.45764 dice_loss 0.15682 +Epoch [3766/4000] Validation [3/4] Loss: 0.56374 focal_loss 0.46461 dice_loss 0.09913 +Epoch [3766/4000] Validation [4/4] Loss: 0.33024 focal_loss 0.24486 dice_loss 0.08537 +Epoch [3766/4000] Validation metric {'Val/mean dice_metric': 0.9751701354980469, 'Val/mean miou_metric': 0.9606853723526001, 'Val/mean f1': 0.9760362505912781, 'Val/mean precision': 0.9741402864456177, 'Val/mean recall': 0.9779394865036011, 'Val/mean hd95_metric': 5.126401424407959} +Cheakpoint... +Epoch [3766/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751701354980469, 'Val/mean miou_metric': 0.9606853723526001, 'Val/mean f1': 0.9760362505912781, 'Val/mean precision': 0.9741402864456177, 'Val/mean recall': 0.9779394865036011, 'Val/mean hd95_metric': 5.126401424407959} +Epoch [3767/4000] Training [1/16] Loss: 0.00370 +Epoch [3767/4000] Training [2/16] Loss: 0.00249 +Epoch [3767/4000] Training [3/16] Loss: 0.00195 +Epoch [3767/4000] Training [4/16] Loss: 0.00237 +Epoch [3767/4000] Training [5/16] Loss: 0.00197 +Epoch [3767/4000] Training [6/16] Loss: 0.00222 +Epoch [3767/4000] Training [7/16] Loss: 0.00195 +Epoch [3767/4000] Training [8/16] Loss: 0.00160 +Epoch [3767/4000] Training [9/16] Loss: 0.00293 +Epoch [3767/4000] Training [10/16] Loss: 0.00253 +Epoch [3767/4000] Training [11/16] Loss: 0.00246 +Epoch [3767/4000] Training [12/16] Loss: 0.00291 +Epoch [3767/4000] Training [13/16] Loss: 0.00267 +Epoch [3767/4000] Training [14/16] Loss: 0.00179 +Epoch [3767/4000] Training [15/16] Loss: 0.00170 +Epoch [3767/4000] Training [16/16] Loss: 0.00296 +Epoch [3767/4000] Training metric {'Train/mean dice_metric': 0.998862624168396, 'Train/mean miou_metric': 0.9974168539047241, 'Train/mean f1': 0.9929690361022949, 'Train/mean precision': 0.9876841902732849, 'Train/mean recall': 0.9983106851577759, 'Train/mean hd95_metric': 0.5071566104888916} +Epoch [3767/4000] Validation [1/4] Loss: 0.44146 focal_loss 0.36571 dice_loss 0.07575 +Epoch [3767/4000] Validation [2/4] Loss: 0.99278 focal_loss 0.75585 dice_loss 0.23693 +Epoch [3767/4000] Validation [3/4] Loss: 0.52614 focal_loss 0.43053 dice_loss 0.09561 +Epoch [3767/4000] Validation [4/4] Loss: 0.34735 focal_loss 0.25617 dice_loss 0.09119 +Epoch [3767/4000] Validation metric {'Val/mean dice_metric': 0.9723418951034546, 'Val/mean miou_metric': 0.9583187103271484, 'Val/mean f1': 0.9744815826416016, 'Val/mean precision': 0.9723845720291138, 'Val/mean recall': 0.9765876531600952, 'Val/mean hd95_metric': 5.292362213134766} +Cheakpoint... +Epoch [3767/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9723418951034546, 'Val/mean miou_metric': 0.9583187103271484, 'Val/mean f1': 0.9744815826416016, 'Val/mean precision': 0.9723845720291138, 'Val/mean recall': 0.9765876531600952, 'Val/mean hd95_metric': 5.292362213134766} +Epoch [3768/4000] Training [1/16] Loss: 0.00350 +Epoch [3768/4000] Training [2/16] Loss: 0.00192 +Epoch [3768/4000] Training [3/16] Loss: 0.00321 +Epoch [3768/4000] Training [4/16] Loss: 0.00254 +Epoch [3768/4000] Training [5/16] Loss: 0.00185 +Epoch [3768/4000] Training [6/16] Loss: 0.00196 +Epoch [3768/4000] Training [7/16] Loss: 0.00126 +Epoch [3768/4000] Training [8/16] Loss: 0.00281 +Epoch [3768/4000] Training [9/16] Loss: 0.00326 +Epoch [3768/4000] Training [10/16] Loss: 0.00225 +Epoch [3768/4000] Training [11/16] Loss: 0.00185 +Epoch [3768/4000] Training [12/16] Loss: 0.00154 +Epoch [3768/4000] Training [13/16] Loss: 0.00316 +Epoch [3768/4000] Training [14/16] Loss: 0.00388 +Epoch [3768/4000] Training [15/16] Loss: 0.00330 +Epoch [3768/4000] Training [16/16] Loss: 0.00284 +Epoch [3768/4000] Training metric {'Train/mean dice_metric': 0.998802900314331, 'Train/mean miou_metric': 0.9973326921463013, 'Train/mean f1': 0.9939088821411133, 'Train/mean precision': 0.9894489645957947, 'Train/mean recall': 0.9984092116355896, 'Train/mean hd95_metric': 0.4955354332923889} +Epoch [3768/4000] Validation [1/4] Loss: 0.42743 focal_loss 0.36544 dice_loss 0.06200 +Epoch [3768/4000] Validation [2/4] Loss: 0.90617 focal_loss 0.70649 dice_loss 0.19968 +Epoch [3768/4000] Validation [3/4] Loss: 0.57933 focal_loss 0.47760 dice_loss 0.10172 +Epoch [3768/4000] Validation [4/4] Loss: 0.33766 focal_loss 0.24654 dice_loss 0.09112 +Epoch [3768/4000] Validation metric {'Val/mean dice_metric': 0.9726113080978394, 'Val/mean miou_metric': 0.9587217569351196, 'Val/mean f1': 0.9759324193000793, 'Val/mean precision': 0.9741381406784058, 'Val/mean recall': 0.9777331948280334, 'Val/mean hd95_metric': 5.08447265625} +Cheakpoint... +Epoch [3768/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726113080978394, 'Val/mean miou_metric': 0.9587217569351196, 'Val/mean f1': 0.9759324193000793, 'Val/mean precision': 0.9741381406784058, 'Val/mean recall': 0.9777331948280334, 'Val/mean hd95_metric': 5.08447265625} +Epoch [3769/4000] Training [1/16] Loss: 0.00262 +Epoch [3769/4000] Training [2/16] Loss: 0.00210 +Epoch [3769/4000] Training [3/16] Loss: 0.00227 +Epoch [3769/4000] Training [4/16] Loss: 0.00254 +Epoch [3769/4000] Training [5/16] Loss: 0.00255 +Epoch [3769/4000] Training [6/16] Loss: 0.00151 +Epoch [3769/4000] Training [7/16] Loss: 0.00250 +Epoch [3769/4000] Training [8/16] Loss: 0.00204 +Epoch [3769/4000] Training [9/16] Loss: 0.00207 +Epoch [3769/4000] Training [10/16] Loss: 0.00330 +Epoch [3769/4000] Training [11/16] Loss: 0.00392 +Epoch [3769/4000] Training [12/16] Loss: 0.00183 +Epoch [3769/4000] Training [13/16] Loss: 0.00212 +Epoch [3769/4000] Training [14/16] Loss: 0.00234 +Epoch [3769/4000] Training [15/16] Loss: 0.00192 +Epoch [3769/4000] Training [16/16] Loss: 0.00172 +Epoch [3769/4000] Training metric {'Train/mean dice_metric': 0.9988569021224976, 'Train/mean miou_metric': 0.9974335432052612, 'Train/mean f1': 0.9937512874603271, 'Train/mean precision': 0.9891278147697449, 'Train/mean recall': 0.9984182119369507, 'Train/mean hd95_metric': 0.47749680280685425} +Epoch [3769/4000] Validation [1/4] Loss: 0.35707 focal_loss 0.29459 dice_loss 0.06248 +Epoch [3769/4000] Validation [2/4] Loss: 0.50434 focal_loss 0.37407 dice_loss 0.13026 +Epoch [3769/4000] Validation [3/4] Loss: 0.30940 focal_loss 0.23902 dice_loss 0.07038 +Epoch [3769/4000] Validation [4/4] Loss: 0.37461 focal_loss 0.28251 dice_loss 0.09210 +Epoch [3769/4000] Validation metric {'Val/mean dice_metric': 0.9755004048347473, 'Val/mean miou_metric': 0.9613872766494751, 'Val/mean f1': 0.9767591953277588, 'Val/mean precision': 0.9741843938827515, 'Val/mean recall': 0.9793477058410645, 'Val/mean hd95_metric': 4.522861957550049} +Cheakpoint... +Epoch [3769/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755004048347473, 'Val/mean miou_metric': 0.9613872766494751, 'Val/mean f1': 0.9767591953277588, 'Val/mean precision': 0.9741843938827515, 'Val/mean recall': 0.9793477058410645, 'Val/mean hd95_metric': 4.522861957550049} +Epoch [3770/4000] Training [1/16] Loss: 0.00214 +Epoch [3770/4000] Training [2/16] Loss: 0.00175 +Epoch [3770/4000] Training [3/16] Loss: 0.00332 +Epoch [3770/4000] Training [4/16] Loss: 0.00305 +Epoch [3770/4000] Training [5/16] Loss: 0.00281 +Epoch [3770/4000] Training [6/16] Loss: 0.00247 +Epoch [3770/4000] Training [7/16] Loss: 0.00135 +Epoch [3770/4000] Training [8/16] Loss: 0.00212 +Epoch [3770/4000] Training [9/16] Loss: 0.00160 +Epoch [3770/4000] Training [10/16] Loss: 0.00258 +Epoch [3770/4000] Training [11/16] Loss: 0.00375 +Epoch [3770/4000] Training [12/16] Loss: 0.00285 +Epoch [3770/4000] Training [13/16] Loss: 0.00243 +Epoch [3770/4000] Training [14/16] Loss: 0.00233 +Epoch [3770/4000] Training [15/16] Loss: 0.00274 +Epoch [3770/4000] Training [16/16] Loss: 0.00220 +Epoch [3770/4000] Training metric {'Train/mean dice_metric': 0.9987488389015198, 'Train/mean miou_metric': 0.9971973896026611, 'Train/mean f1': 0.9933496117591858, 'Train/mean precision': 0.9884704947471619, 'Train/mean recall': 0.9982771277427673, 'Train/mean hd95_metric': 0.5160403251647949} +Epoch [3770/4000] Validation [1/4] Loss: 0.42231 focal_loss 0.35697 dice_loss 0.06534 +Epoch [3770/4000] Validation [2/4] Loss: 0.88993 focal_loss 0.69106 dice_loss 0.19888 +Epoch [3770/4000] Validation [3/4] Loss: 0.56248 focal_loss 0.46681 dice_loss 0.09567 +Epoch [3770/4000] Validation [4/4] Loss: 0.49594 focal_loss 0.38168 dice_loss 0.11426 +Epoch [3770/4000] Validation metric {'Val/mean dice_metric': 0.9728485941886902, 'Val/mean miou_metric': 0.9586127400398254, 'Val/mean f1': 0.9755095839500427, 'Val/mean precision': 0.9722809791564941, 'Val/mean recall': 0.978759765625, 'Val/mean hd95_metric': 5.125734806060791} +Cheakpoint... +Epoch [3770/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728485941886902, 'Val/mean miou_metric': 0.9586127400398254, 'Val/mean f1': 0.9755095839500427, 'Val/mean precision': 0.9722809791564941, 'Val/mean recall': 0.978759765625, 'Val/mean hd95_metric': 5.125734806060791} +Epoch [3771/4000] Training [1/16] Loss: 0.00197 +Epoch [3771/4000] Training [2/16] Loss: 0.00290 +Epoch [3771/4000] Training [3/16] Loss: 0.00253 +Epoch [3771/4000] Training [4/16] Loss: 0.00259 +Epoch [3771/4000] Training [5/16] Loss: 0.00266 +Epoch [3771/4000] Training [6/16] Loss: 0.00206 +Epoch [3771/4000] Training [7/16] Loss: 0.00324 +Epoch [3771/4000] Training [8/16] Loss: 0.00200 +Epoch [3771/4000] Training [9/16] Loss: 0.00238 +Epoch [3771/4000] Training [10/16] Loss: 0.00238 +Epoch [3771/4000] Training [11/16] Loss: 0.00338 +Epoch [3771/4000] Training [12/16] Loss: 0.00233 +Epoch [3771/4000] Training [13/16] Loss: 0.00306 +Epoch [3771/4000] Training [14/16] Loss: 0.00331 +Epoch [3771/4000] Training [15/16] Loss: 0.00285 +Epoch [3771/4000] Training [16/16] Loss: 0.00139 +Epoch [3771/4000] Training metric {'Train/mean dice_metric': 0.9988148808479309, 'Train/mean miou_metric': 0.997325599193573, 'Train/mean f1': 0.9932558536529541, 'Train/mean precision': 0.9881832003593445, 'Train/mean recall': 0.9983808398246765, 'Train/mean hd95_metric': 0.5198990106582642} +Epoch [3771/4000] Validation [1/4] Loss: 0.36452 focal_loss 0.30264 dice_loss 0.06188 +Epoch [3771/4000] Validation [2/4] Loss: 0.51462 focal_loss 0.39148 dice_loss 0.12313 +Epoch [3771/4000] Validation [3/4] Loss: 0.56222 focal_loss 0.46853 dice_loss 0.09369 +Epoch [3771/4000] Validation [4/4] Loss: 0.44947 focal_loss 0.34115 dice_loss 0.10831 +Epoch [3771/4000] Validation metric {'Val/mean dice_metric': 0.9761185646057129, 'Val/mean miou_metric': 0.9618867635726929, 'Val/mean f1': 0.9762460589408875, 'Val/mean precision': 0.9736271500587463, 'Val/mean recall': 0.9788789749145508, 'Val/mean hd95_metric': 4.7764201164245605} +Cheakpoint... +Epoch [3771/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9761], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9761185646057129, 'Val/mean miou_metric': 0.9618867635726929, 'Val/mean f1': 0.9762460589408875, 'Val/mean precision': 0.9736271500587463, 'Val/mean recall': 0.9788789749145508, 'Val/mean hd95_metric': 4.7764201164245605} +Epoch [3772/4000] Training [1/16] Loss: 0.00351 +Epoch [3772/4000] Training [2/16] Loss: 0.00311 +Epoch [3772/4000] Training [3/16] Loss: 0.00293 +Epoch [3772/4000] Training [4/16] Loss: 0.00288 +Epoch [3772/4000] Training [5/16] Loss: 0.00241 +Epoch [3772/4000] Training [6/16] Loss: 0.00163 +Epoch [3772/4000] Training [7/16] Loss: 0.00194 +Epoch [3772/4000] Training [8/16] Loss: 0.00218 +Epoch [3772/4000] Training [9/16] Loss: 0.00250 +Epoch [3772/4000] Training [10/16] Loss: 0.00148 +Epoch [3772/4000] Training [11/16] Loss: 0.00247 +Epoch [3772/4000] Training [12/16] Loss: 0.00189 +Epoch [3772/4000] Training [13/16] Loss: 0.00253 +Epoch [3772/4000] Training [14/16] Loss: 0.00202 +Epoch [3772/4000] Training [15/16] Loss: 0.00250 +Epoch [3772/4000] Training [16/16] Loss: 0.00242 +Epoch [3772/4000] Training metric {'Train/mean dice_metric': 0.998820424079895, 'Train/mean miou_metric': 0.9973574280738831, 'Train/mean f1': 0.9937784671783447, 'Train/mean precision': 0.9892035126686096, 'Train/mean recall': 0.9983959197998047, 'Train/mean hd95_metric': 0.525222897529602} +Epoch [3772/4000] Validation [1/4] Loss: 0.50045 focal_loss 0.42550 dice_loss 0.07495 +Epoch [3772/4000] Validation [2/4] Loss: 0.90486 focal_loss 0.70261 dice_loss 0.20225 +Epoch [3772/4000] Validation [3/4] Loss: 0.54250 focal_loss 0.44789 dice_loss 0.09461 +Epoch [3772/4000] Validation [4/4] Loss: 0.39294 focal_loss 0.29874 dice_loss 0.09420 +Epoch [3772/4000] Validation metric {'Val/mean dice_metric': 0.9736213684082031, 'Val/mean miou_metric': 0.959358811378479, 'Val/mean f1': 0.9761874675750732, 'Val/mean precision': 0.9737942814826965, 'Val/mean recall': 0.9785925149917603, 'Val/mean hd95_metric': 5.136502742767334} +Cheakpoint... +Epoch [3772/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736213684082031, 'Val/mean miou_metric': 0.959358811378479, 'Val/mean f1': 0.9761874675750732, 'Val/mean precision': 0.9737942814826965, 'Val/mean recall': 0.9785925149917603, 'Val/mean hd95_metric': 5.136502742767334} +Epoch [3773/4000] Training [1/16] Loss: 0.00173 +Epoch [3773/4000] Training [2/16] Loss: 0.00215 +Epoch [3773/4000] Training [3/16] Loss: 0.00248 +Epoch [3773/4000] Training [4/16] Loss: 0.00203 +Epoch [3773/4000] Training [5/16] Loss: 0.00257 +Epoch [3773/4000] Training [6/16] Loss: 0.00212 +Epoch [3773/4000] Training [7/16] Loss: 0.00203 +Epoch [3773/4000] Training [8/16] Loss: 0.00282 +Epoch [3773/4000] Training [9/16] Loss: 0.00255 +Epoch [3773/4000] Training [10/16] Loss: 0.00231 +Epoch [3773/4000] Training [11/16] Loss: 0.00338 +Epoch [3773/4000] Training [12/16] Loss: 0.00193 +Epoch [3773/4000] Training [13/16] Loss: 0.00256 +Epoch [3773/4000] Training [14/16] Loss: 0.00296 +Epoch [3773/4000] Training [15/16] Loss: 0.00242 +Epoch [3773/4000] Training [16/16] Loss: 0.00185 +Epoch [3773/4000] Training metric {'Train/mean dice_metric': 0.9989140033721924, 'Train/mean miou_metric': 0.9975520968437195, 'Train/mean f1': 0.9939106106758118, 'Train/mean precision': 0.989404022693634, 'Train/mean recall': 0.9984585046768188, 'Train/mean hd95_metric': 0.4872346520423889} +Epoch [3773/4000] Validation [1/4] Loss: 0.36362 focal_loss 0.30145 dice_loss 0.06217 +Epoch [3773/4000] Validation [2/4] Loss: 0.60586 focal_loss 0.44891 dice_loss 0.15695 +Epoch [3773/4000] Validation [3/4] Loss: 0.55445 focal_loss 0.45793 dice_loss 0.09652 +Epoch [3773/4000] Validation [4/4] Loss: 0.42361 focal_loss 0.31951 dice_loss 0.10410 +Epoch [3773/4000] Validation metric {'Val/mean dice_metric': 0.9745195508003235, 'Val/mean miou_metric': 0.9602565765380859, 'Val/mean f1': 0.9763524532318115, 'Val/mean precision': 0.974785566329956, 'Val/mean recall': 0.9779243469238281, 'Val/mean hd95_metric': 4.538715839385986} +Cheakpoint... +Epoch [3773/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745195508003235, 'Val/mean miou_metric': 0.9602565765380859, 'Val/mean f1': 0.9763524532318115, 'Val/mean precision': 0.974785566329956, 'Val/mean recall': 0.9779243469238281, 'Val/mean hd95_metric': 4.538715839385986} +Epoch [3774/4000] Training [1/16] Loss: 0.00214 +Epoch [3774/4000] Training [2/16] Loss: 0.00194 +Epoch [3774/4000] Training [3/16] Loss: 0.00225 +Epoch [3774/4000] Training [4/16] Loss: 0.00275 +Epoch [3774/4000] Training [5/16] Loss: 0.00293 +Epoch [3774/4000] Training [6/16] Loss: 0.00201 +Epoch [3774/4000] Training [7/16] Loss: 0.00220 +Epoch [3774/4000] Training [8/16] Loss: 0.00193 +Epoch [3774/4000] Training [9/16] Loss: 0.00242 +Epoch [3774/4000] Training [10/16] Loss: 0.00337 +Epoch [3774/4000] Training [11/16] Loss: 0.00230 +Epoch [3774/4000] Training [12/16] Loss: 0.00205 +Epoch [3774/4000] Training [13/16] Loss: 0.00312 +Epoch [3774/4000] Training [14/16] Loss: 0.00341 +Epoch [3774/4000] Training [15/16] Loss: 0.00212 +Epoch [3774/4000] Training [16/16] Loss: 0.00261 +Epoch [3774/4000] Training metric {'Train/mean dice_metric': 0.998796820640564, 'Train/mean miou_metric': 0.9973018169403076, 'Train/mean f1': 0.9935111403465271, 'Train/mean precision': 0.988754153251648, 'Train/mean recall': 0.9983141422271729, 'Train/mean hd95_metric': 0.49973443150520325} +Epoch [3774/4000] Validation [1/4] Loss: 0.35041 focal_loss 0.29296 dice_loss 0.05746 +Epoch [3774/4000] Validation [2/4] Loss: 0.48734 focal_loss 0.37530 dice_loss 0.11205 +Epoch [3774/4000] Validation [3/4] Loss: 0.56526 focal_loss 0.46843 dice_loss 0.09682 +Epoch [3774/4000] Validation [4/4] Loss: 0.32295 focal_loss 0.23436 dice_loss 0.08859 +Epoch [3774/4000] Validation metric {'Val/mean dice_metric': 0.9747398495674133, 'Val/mean miou_metric': 0.9604779481887817, 'Val/mean f1': 0.9761250019073486, 'Val/mean precision': 0.9736236333847046, 'Val/mean recall': 0.9786391854286194, 'Val/mean hd95_metric': 5.501993656158447} +Cheakpoint... +Epoch [3774/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747398495674133, 'Val/mean miou_metric': 0.9604779481887817, 'Val/mean f1': 0.9761250019073486, 'Val/mean precision': 0.9736236333847046, 'Val/mean recall': 0.9786391854286194, 'Val/mean hd95_metric': 5.501993656158447} +Epoch [3775/4000] Training [1/16] Loss: 0.00321 +Epoch [3775/4000] Training [2/16] Loss: 0.00294 +Epoch [3775/4000] Training [3/16] Loss: 0.00190 +Epoch [3775/4000] Training [4/16] Loss: 0.00268 +Epoch [3775/4000] Training [5/16] Loss: 0.00146 +Epoch [3775/4000] Training [6/16] Loss: 0.00241 +Epoch [3775/4000] Training [7/16] Loss: 0.00257 +Epoch [3775/4000] Training [8/16] Loss: 0.00162 +Epoch [3775/4000] Training [9/16] Loss: 0.00215 +Epoch [3775/4000] Training [10/16] Loss: 0.00327 +Epoch [3775/4000] Training [11/16] Loss: 0.00204 +Epoch [3775/4000] Training [12/16] Loss: 0.00191 +Epoch [3775/4000] Training [13/16] Loss: 0.00217 +Epoch [3775/4000] Training [14/16] Loss: 0.00215 +Epoch [3775/4000] Training [15/16] Loss: 0.00201 +Epoch [3775/4000] Training [16/16] Loss: 0.00404 +Epoch [3775/4000] Training metric {'Train/mean dice_metric': 0.9987583160400391, 'Train/mean miou_metric': 0.9972440004348755, 'Train/mean f1': 0.9938514232635498, 'Train/mean precision': 0.9893930554389954, 'Train/mean recall': 0.9983501434326172, 'Train/mean hd95_metric': 0.5327897071838379} +Epoch [3775/4000] Validation [1/4] Loss: 0.39036 focal_loss 0.32797 dice_loss 0.06239 +Epoch [3775/4000] Validation [2/4] Loss: 0.59207 focal_loss 0.43894 dice_loss 0.15313 +Epoch [3775/4000] Validation [3/4] Loss: 0.54087 focal_loss 0.44855 dice_loss 0.09232 +Epoch [3775/4000] Validation [4/4] Loss: 0.33987 focal_loss 0.24601 dice_loss 0.09386 +Epoch [3775/4000] Validation metric {'Val/mean dice_metric': 0.973773181438446, 'Val/mean miou_metric': 0.9595462679862976, 'Val/mean f1': 0.975781261920929, 'Val/mean precision': 0.9734575152397156, 'Val/mean recall': 0.9781161546707153, 'Val/mean hd95_metric': 5.262871742248535} +Cheakpoint... +Epoch [3775/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973773181438446, 'Val/mean miou_metric': 0.9595462679862976, 'Val/mean f1': 0.975781261920929, 'Val/mean precision': 0.9734575152397156, 'Val/mean recall': 0.9781161546707153, 'Val/mean hd95_metric': 5.262871742248535} +Epoch [3776/4000] Training [1/16] Loss: 0.00158 +Epoch [3776/4000] Training [2/16] Loss: 0.00244 +Epoch [3776/4000] Training [3/16] Loss: 0.00265 +Epoch [3776/4000] Training [4/16] Loss: 0.00201 +Epoch [3776/4000] Training [5/16] Loss: 0.00274 +Epoch [3776/4000] Training [6/16] Loss: 0.00300 +Epoch [3776/4000] Training [7/16] Loss: 0.00202 +Epoch [3776/4000] Training [8/16] Loss: 0.00272 +Epoch [3776/4000] Training [9/16] Loss: 0.00151 +Epoch [3776/4000] Training [10/16] Loss: 0.00222 +Epoch [3776/4000] Training [11/16] Loss: 0.00222 +Epoch [3776/4000] Training [12/16] Loss: 0.00223 +Epoch [3776/4000] Training [13/16] Loss: 0.00190 +Epoch [3776/4000] Training [14/16] Loss: 0.00231 +Epoch [3776/4000] Training [15/16] Loss: 0.00281 +Epoch [3776/4000] Training [16/16] Loss: 0.00461 +Epoch [3776/4000] Training metric {'Train/mean dice_metric': 0.9987009763717651, 'Train/mean miou_metric': 0.9971081018447876, 'Train/mean f1': 0.9930871725082397, 'Train/mean precision': 0.9879904985427856, 'Train/mean recall': 0.9982366561889648, 'Train/mean hd95_metric': 0.5249853730201721} +Epoch [3776/4000] Validation [1/4] Loss: 0.45819 focal_loss 0.39282 dice_loss 0.06537 +Epoch [3776/4000] Validation [2/4] Loss: 0.47061 focal_loss 0.35954 dice_loss 0.11107 +Epoch [3776/4000] Validation [3/4] Loss: 0.30595 focal_loss 0.24151 dice_loss 0.06443 +Epoch [3776/4000] Validation [4/4] Loss: 0.34814 focal_loss 0.25941 dice_loss 0.08874 +Epoch [3776/4000] Validation metric {'Val/mean dice_metric': 0.9745486974716187, 'Val/mean miou_metric': 0.9608739614486694, 'Val/mean f1': 0.97620689868927, 'Val/mean precision': 0.9730733036994934, 'Val/mean recall': 0.9793607592582703, 'Val/mean hd95_metric': 5.009566783905029} +Cheakpoint... +Epoch [3776/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745486974716187, 'Val/mean miou_metric': 0.9608739614486694, 'Val/mean f1': 0.97620689868927, 'Val/mean precision': 0.9730733036994934, 'Val/mean recall': 0.9793607592582703, 'Val/mean hd95_metric': 5.009566783905029} +Epoch [3777/4000] Training [1/16] Loss: 0.00280 +Epoch [3777/4000] Training [2/16] Loss: 0.00305 +Epoch [3777/4000] Training [3/16] Loss: 0.00178 +Epoch [3777/4000] Training [4/16] Loss: 0.00249 +Epoch [3777/4000] Training [5/16] Loss: 0.00211 +Epoch [3777/4000] Training [6/16] Loss: 0.00318 +Epoch [3777/4000] Training [7/16] Loss: 0.00269 +Epoch [3777/4000] Training [8/16] Loss: 0.00233 +Epoch [3777/4000] Training [9/16] Loss: 0.00327 +Epoch [3777/4000] Training [10/16] Loss: 0.00197 +Epoch [3777/4000] Training [11/16] Loss: 0.00312 +Epoch [3777/4000] Training [12/16] Loss: 0.00155 +Epoch [3777/4000] Training [13/16] Loss: 0.00200 +Epoch [3777/4000] Training [14/16] Loss: 0.00211 +Epoch [3777/4000] Training [15/16] Loss: 0.00180 +Epoch [3777/4000] Training [16/16] Loss: 0.00218 +Epoch [3777/4000] Training metric {'Train/mean dice_metric': 0.9987732172012329, 'Train/mean miou_metric': 0.9972584843635559, 'Train/mean f1': 0.9936210513114929, 'Train/mean precision': 0.9889007210731506, 'Train/mean recall': 0.9983866810798645, 'Train/mean hd95_metric': 0.5127228498458862} +Epoch [3777/4000] Validation [1/4] Loss: 0.42775 focal_loss 0.36348 dice_loss 0.06427 +Epoch [3777/4000] Validation [2/4] Loss: 0.50307 focal_loss 0.37855 dice_loss 0.12452 +Epoch [3777/4000] Validation [3/4] Loss: 0.54301 focal_loss 0.44870 dice_loss 0.09430 +Epoch [3777/4000] Validation [4/4] Loss: 0.41952 focal_loss 0.31335 dice_loss 0.10616 +Epoch [3777/4000] Validation metric {'Val/mean dice_metric': 0.9728330373764038, 'Val/mean miou_metric': 0.958593487739563, 'Val/mean f1': 0.9753663539886475, 'Val/mean precision': 0.9723173379898071, 'Val/mean recall': 0.9784345626831055, 'Val/mean hd95_metric': 5.4044108390808105} +Cheakpoint... +Epoch [3777/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728330373764038, 'Val/mean miou_metric': 0.958593487739563, 'Val/mean f1': 0.9753663539886475, 'Val/mean precision': 0.9723173379898071, 'Val/mean recall': 0.9784345626831055, 'Val/mean hd95_metric': 5.4044108390808105} +Epoch [3778/4000] Training [1/16] Loss: 0.00240 +Epoch [3778/4000] Training [2/16] Loss: 0.00154 +Epoch [3778/4000] Training [3/16] Loss: 0.00285 +Epoch [3778/4000] Training [4/16] Loss: 0.00176 +Epoch [3778/4000] Training [5/16] Loss: 0.00228 +Epoch [3778/4000] Training [6/16] Loss: 0.00344 +Epoch [3778/4000] Training [7/16] Loss: 0.00342 +Epoch [3778/4000] Training [8/16] Loss: 0.00166 +Epoch [3778/4000] Training [9/16] Loss: 0.00305 +Epoch [3778/4000] Training [10/16] Loss: 0.00154 +Epoch [3778/4000] Training [11/16] Loss: 0.00205 +Epoch [3778/4000] Training [12/16] Loss: 0.00283 +Epoch [3778/4000] Training [13/16] Loss: 0.00186 +Epoch [3778/4000] Training [14/16] Loss: 0.00194 +Epoch [3778/4000] Training [15/16] Loss: 0.00230 +Epoch [3778/4000] Training [16/16] Loss: 0.00347 +Epoch [3778/4000] Training metric {'Train/mean dice_metric': 0.9988346099853516, 'Train/mean miou_metric': 0.9973672032356262, 'Train/mean f1': 0.9932056665420532, 'Train/mean precision': 0.988112211227417, 'Train/mean recall': 0.9983519315719604, 'Train/mean hd95_metric': 0.5128204226493835} +Epoch [3778/4000] Validation [1/4] Loss: 0.44382 focal_loss 0.37809 dice_loss 0.06574 +Epoch [3778/4000] Validation [2/4] Loss: 0.89032 focal_loss 0.69401 dice_loss 0.19631 +Epoch [3778/4000] Validation [3/4] Loss: 0.29438 focal_loss 0.22765 dice_loss 0.06674 +Epoch [3778/4000] Validation [4/4] Loss: 0.35043 focal_loss 0.24987 dice_loss 0.10056 +Epoch [3778/4000] Validation metric {'Val/mean dice_metric': 0.9743286967277527, 'Val/mean miou_metric': 0.9600847363471985, 'Val/mean f1': 0.9758522510528564, 'Val/mean precision': 0.9737014174461365, 'Val/mean recall': 0.9780126214027405, 'Val/mean hd95_metric': 5.1969475746154785} +Cheakpoint... +Epoch [3778/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743286967277527, 'Val/mean miou_metric': 0.9600847363471985, 'Val/mean f1': 0.9758522510528564, 'Val/mean precision': 0.9737014174461365, 'Val/mean recall': 0.9780126214027405, 'Val/mean hd95_metric': 5.1969475746154785} +Epoch [3779/4000] Training [1/16] Loss: 0.00205 +Epoch [3779/4000] Training [2/16] Loss: 0.00205 +Epoch [3779/4000] Training [3/16] Loss: 0.00229 +Epoch [3779/4000] Training [4/16] Loss: 0.00290 +Epoch [3779/4000] Training [5/16] Loss: 0.00153 +Epoch [3779/4000] Training [6/16] Loss: 0.00281 +Epoch [3779/4000] Training [7/16] Loss: 0.00234 +Epoch [3779/4000] Training [8/16] Loss: 0.00239 +Epoch [3779/4000] Training [9/16] Loss: 0.00344 +Epoch [3779/4000] Training [10/16] Loss: 0.00297 +Epoch [3779/4000] Training [11/16] Loss: 0.00334 +Epoch [3779/4000] Training [12/16] Loss: 0.00157 +Epoch [3779/4000] Training [13/16] Loss: 0.00254 +Epoch [3779/4000] Training [14/16] Loss: 0.00238 +Epoch [3779/4000] Training [15/16] Loss: 0.00290 +Epoch [3779/4000] Training [16/16] Loss: 0.00171 +Epoch [3779/4000] Training metric {'Train/mean dice_metric': 0.9986858367919922, 'Train/mean miou_metric': 0.9970719218254089, 'Train/mean f1': 0.9933672547340393, 'Train/mean precision': 0.9885348081588745, 'Train/mean recall': 0.9982470870018005, 'Train/mean hd95_metric': 0.5619970560073853} +Epoch [3779/4000] Validation [1/4] Loss: 0.43480 focal_loss 0.36885 dice_loss 0.06594 +Epoch [3779/4000] Validation [2/4] Loss: 0.58414 focal_loss 0.43337 dice_loss 0.15078 +Epoch [3779/4000] Validation [3/4] Loss: 0.56395 focal_loss 0.46931 dice_loss 0.09464 +Epoch [3779/4000] Validation [4/4] Loss: 0.38895 focal_loss 0.28987 dice_loss 0.09908 +Epoch [3779/4000] Validation metric {'Val/mean dice_metric': 0.974165141582489, 'Val/mean miou_metric': 0.9600837826728821, 'Val/mean f1': 0.9759079217910767, 'Val/mean precision': 0.9731672406196594, 'Val/mean recall': 0.978663980960846, 'Val/mean hd95_metric': 5.031843662261963} +Cheakpoint... +Epoch [3779/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974165141582489, 'Val/mean miou_metric': 0.9600837826728821, 'Val/mean f1': 0.9759079217910767, 'Val/mean precision': 0.9731672406196594, 'Val/mean recall': 0.978663980960846, 'Val/mean hd95_metric': 5.031843662261963} +Epoch [3780/4000] Training [1/16] Loss: 0.00167 +Epoch [3780/4000] Training [2/16] Loss: 0.00184 +Epoch [3780/4000] Training [3/16] Loss: 0.00242 +Epoch [3780/4000] Training [4/16] Loss: 0.00193 +Epoch [3780/4000] Training [5/16] Loss: 0.00177 +Epoch [3780/4000] Training [6/16] Loss: 0.00233 +Epoch [3780/4000] Training [7/16] Loss: 0.00225 +Epoch [3780/4000] Training [8/16] Loss: 0.00214 +Epoch [3780/4000] Training [9/16] Loss: 0.00245 +Epoch [3780/4000] Training [10/16] Loss: 0.00224 +Epoch [3780/4000] Training [11/16] Loss: 0.00198 +Epoch [3780/4000] Training [12/16] Loss: 0.00279 +Epoch [3780/4000] Training [13/16] Loss: 0.00228 +Epoch [3780/4000] Training [14/16] Loss: 0.00260 +Epoch [3780/4000] Training [15/16] Loss: 0.00231 +Epoch [3780/4000] Training [16/16] Loss: 0.00330 +Epoch [3780/4000] Training metric {'Train/mean dice_metric': 0.9988657236099243, 'Train/mean miou_metric': 0.9974503517150879, 'Train/mean f1': 0.9938482046127319, 'Train/mean precision': 0.9892948269844055, 'Train/mean recall': 0.9984437227249146, 'Train/mean hd95_metric': 0.5391177535057068} +Epoch [3780/4000] Validation [1/4] Loss: 0.37211 focal_loss 0.31212 dice_loss 0.05999 +Epoch [3780/4000] Validation [2/4] Loss: 1.04436 focal_loss 0.85706 dice_loss 0.18729 +Epoch [3780/4000] Validation [3/4] Loss: 0.53408 focal_loss 0.44276 dice_loss 0.09133 +Epoch [3780/4000] Validation [4/4] Loss: 0.39251 focal_loss 0.28193 dice_loss 0.11058 +Epoch [3780/4000] Validation metric {'Val/mean dice_metric': 0.9743003845214844, 'Val/mean miou_metric': 0.9602518081665039, 'Val/mean f1': 0.9763680100440979, 'Val/mean precision': 0.9742053151130676, 'Val/mean recall': 0.9785402417182922, 'Val/mean hd95_metric': 4.672336578369141} +Cheakpoint... +Epoch [3780/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743003845214844, 'Val/mean miou_metric': 0.9602518081665039, 'Val/mean f1': 0.9763680100440979, 'Val/mean precision': 0.9742053151130676, 'Val/mean recall': 0.9785402417182922, 'Val/mean hd95_metric': 4.672336578369141} +Epoch [3781/4000] Training [1/16] Loss: 0.00291 +Epoch [3781/4000] Training [2/16] Loss: 0.00234 +Epoch [3781/4000] Training [3/16] Loss: 0.00315 +Epoch [3781/4000] Training [4/16] Loss: 0.00336 +Epoch [3781/4000] Training [5/16] Loss: 0.00343 +Epoch [3781/4000] Training [6/16] Loss: 0.00325 +Epoch [3781/4000] Training [7/16] Loss: 0.00344 +Epoch [3781/4000] Training [8/16] Loss: 0.00246 +Epoch [3781/4000] Training [9/16] Loss: 0.00198 +Epoch [3781/4000] Training [10/16] Loss: 0.00315 +Epoch [3781/4000] Training [11/16] Loss: 0.00188 +Epoch [3781/4000] Training [12/16] Loss: 0.00312 +Epoch [3781/4000] Training [13/16] Loss: 0.00269 +Epoch [3781/4000] Training [14/16] Loss: 0.00170 +Epoch [3781/4000] Training [15/16] Loss: 0.00280 +Epoch [3781/4000] Training [16/16] Loss: 0.00204 +Epoch [3781/4000] Training metric {'Train/mean dice_metric': 0.9986250400543213, 'Train/mean miou_metric': 0.9969638586044312, 'Train/mean f1': 0.9934030771255493, 'Train/mean precision': 0.9886521100997925, 'Train/mean recall': 0.9982001185417175, 'Train/mean hd95_metric': 0.6039338707923889} +Epoch [3781/4000] Validation [1/4] Loss: 0.34909 focal_loss 0.29041 dice_loss 0.05868 +Epoch [3781/4000] Validation [2/4] Loss: 0.46288 focal_loss 0.35351 dice_loss 0.10937 +Epoch [3781/4000] Validation [3/4] Loss: 0.27838 focal_loss 0.21578 dice_loss 0.06260 +Epoch [3781/4000] Validation [4/4] Loss: 0.35286 focal_loss 0.24647 dice_loss 0.10639 +Epoch [3781/4000] Validation metric {'Val/mean dice_metric': 0.9753214120864868, 'Val/mean miou_metric': 0.961334228515625, 'Val/mean f1': 0.976475179195404, 'Val/mean precision': 0.973755955696106, 'Val/mean recall': 0.9792096614837646, 'Val/mean hd95_metric': 5.096806526184082} +Cheakpoint... +Epoch [3781/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753214120864868, 'Val/mean miou_metric': 0.961334228515625, 'Val/mean f1': 0.976475179195404, 'Val/mean precision': 0.973755955696106, 'Val/mean recall': 0.9792096614837646, 'Val/mean hd95_metric': 5.096806526184082} +Epoch [3782/4000] Training [1/16] Loss: 0.00222 +Epoch [3782/4000] Training [2/16] Loss: 0.00280 +Epoch [3782/4000] Training [3/16] Loss: 0.00230 +Epoch [3782/4000] Training [4/16] Loss: 0.00257 +Epoch [3782/4000] Training [5/16] Loss: 0.00277 +Epoch [3782/4000] Training [6/16] Loss: 0.00175 +Epoch [3782/4000] Training [7/16] Loss: 0.00244 +Epoch [3782/4000] Training [8/16] Loss: 0.00332 +Epoch [3782/4000] Training [9/16] Loss: 0.00210 +Epoch [3782/4000] Training [10/16] Loss: 0.00208 +Epoch [3782/4000] Training [11/16] Loss: 0.00163 +Epoch [3782/4000] Training [12/16] Loss: 0.00239 +Epoch [3782/4000] Training [13/16] Loss: 0.00205 +Epoch [3782/4000] Training [14/16] Loss: 0.00211 +Epoch [3782/4000] Training [15/16] Loss: 0.00236 +Epoch [3782/4000] Training [16/16] Loss: 0.00205 +Epoch [3782/4000] Training metric {'Train/mean dice_metric': 0.9988728761672974, 'Train/mean miou_metric': 0.9974719285964966, 'Train/mean f1': 0.9938845634460449, 'Train/mean precision': 0.9893894195556641, 'Train/mean recall': 0.998420774936676, 'Train/mean hd95_metric': 0.5111881494522095} +Epoch [3782/4000] Validation [1/4] Loss: 0.42334 focal_loss 0.35856 dice_loss 0.06478 +Epoch [3782/4000] Validation [2/4] Loss: 0.49174 focal_loss 0.37710 dice_loss 0.11464 +Epoch [3782/4000] Validation [3/4] Loss: 0.55210 focal_loss 0.45875 dice_loss 0.09334 +Epoch [3782/4000] Validation [4/4] Loss: 0.41002 focal_loss 0.30159 dice_loss 0.10843 +Epoch [3782/4000] Validation metric {'Val/mean dice_metric': 0.9740041494369507, 'Val/mean miou_metric': 0.960091769695282, 'Val/mean f1': 0.9761307239532471, 'Val/mean precision': 0.9742571115493774, 'Val/mean recall': 0.9780116081237793, 'Val/mean hd95_metric': 4.801729679107666} +Cheakpoint... +Epoch [3782/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740041494369507, 'Val/mean miou_metric': 0.960091769695282, 'Val/mean f1': 0.9761307239532471, 'Val/mean precision': 0.9742571115493774, 'Val/mean recall': 0.9780116081237793, 'Val/mean hd95_metric': 4.801729679107666} +Epoch [3783/4000] Training [1/16] Loss: 0.00187 +Epoch [3783/4000] Training [2/16] Loss: 0.00208 +Epoch [3783/4000] Training [3/16] Loss: 0.00264 +Epoch [3783/4000] Training [4/16] Loss: 0.00293 +Epoch [3783/4000] Training [5/16] Loss: 0.00293 +Epoch [3783/4000] Training [6/16] Loss: 0.00237 +Epoch [3783/4000] Training [7/16] Loss: 0.00211 +Epoch [3783/4000] Training [8/16] Loss: 0.00328 +Epoch [3783/4000] Training [9/16] Loss: 0.00171 +Epoch [3783/4000] Training [10/16] Loss: 0.00205 +Epoch [3783/4000] Training [11/16] Loss: 0.00241 +Epoch [3783/4000] Training [12/16] Loss: 0.00203 +Epoch [3783/4000] Training [13/16] Loss: 0.00262 +Epoch [3783/4000] Training [14/16] Loss: 0.00184 +Epoch [3783/4000] Training [15/16] Loss: 0.00125 +Epoch [3783/4000] Training [16/16] Loss: 0.00230 +Epoch [3783/4000] Training metric {'Train/mean dice_metric': 0.9988813996315002, 'Train/mean miou_metric': 0.9974535703659058, 'Train/mean f1': 0.9930632710456848, 'Train/mean precision': 0.9878292083740234, 'Train/mean recall': 0.998353123664856, 'Train/mean hd95_metric': 0.4984651207923889} +Epoch [3783/4000] Validation [1/4] Loss: 0.39249 focal_loss 0.33076 dice_loss 0.06172 +Epoch [3783/4000] Validation [2/4] Loss: 0.49113 focal_loss 0.37800 dice_loss 0.11314 +Epoch [3783/4000] Validation [3/4] Loss: 0.30627 focal_loss 0.23762 dice_loss 0.06864 +Epoch [3783/4000] Validation [4/4] Loss: 0.39240 focal_loss 0.29787 dice_loss 0.09453 +Epoch [3783/4000] Validation metric {'Val/mean dice_metric': 0.9742765426635742, 'Val/mean miou_metric': 0.9605363607406616, 'Val/mean f1': 0.9760645031929016, 'Val/mean precision': 0.9736925959587097, 'Val/mean recall': 0.9784478545188904, 'Val/mean hd95_metric': 4.759198188781738} +Cheakpoint... +Epoch [3783/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742765426635742, 'Val/mean miou_metric': 0.9605363607406616, 'Val/mean f1': 0.9760645031929016, 'Val/mean precision': 0.9736925959587097, 'Val/mean recall': 0.9784478545188904, 'Val/mean hd95_metric': 4.759198188781738} +Epoch [3784/4000] Training [1/16] Loss: 0.00206 +Epoch [3784/4000] Training [2/16] Loss: 0.00252 +Epoch [3784/4000] Training [3/16] Loss: 0.00198 +Epoch [3784/4000] Training [4/16] Loss: 0.00306 +Epoch [3784/4000] Training [5/16] Loss: 0.00218 +Epoch [3784/4000] Training [6/16] Loss: 0.00174 +Epoch [3784/4000] Training [7/16] Loss: 0.00375 +Epoch [3784/4000] Training [8/16] Loss: 0.00238 +Epoch [3784/4000] Training [9/16] Loss: 0.00286 +Epoch [3784/4000] Training [10/16] Loss: 0.00252 +Epoch [3784/4000] Training [11/16] Loss: 0.00351 +Epoch [3784/4000] Training [12/16] Loss: 0.00262 +Epoch [3784/4000] Training [13/16] Loss: 0.00223 +Epoch [3784/4000] Training [14/16] Loss: 0.00438 +Epoch [3784/4000] Training [15/16] Loss: 0.00183 +Epoch [3784/4000] Training [16/16] Loss: 0.00224 +Epoch [3784/4000] Training metric {'Train/mean dice_metric': 0.99872887134552, 'Train/mean miou_metric': 0.9971843957901001, 'Train/mean f1': 0.9936618208885193, 'Train/mean precision': 0.9891003966331482, 'Train/mean recall': 0.9982655644416809, 'Train/mean hd95_metric': 0.6475791335105896} +Epoch [3784/4000] Validation [1/4] Loss: 0.41159 focal_loss 0.35032 dice_loss 0.06128 +Epoch [3784/4000] Validation [2/4] Loss: 0.48547 focal_loss 0.37423 dice_loss 0.11124 +Epoch [3784/4000] Validation [3/4] Loss: 0.52387 focal_loss 0.42955 dice_loss 0.09432 +Epoch [3784/4000] Validation [4/4] Loss: 0.37284 focal_loss 0.27857 dice_loss 0.09427 +Epoch [3784/4000] Validation metric {'Val/mean dice_metric': 0.973946750164032, 'Val/mean miou_metric': 0.9600685238838196, 'Val/mean f1': 0.9760637283325195, 'Val/mean precision': 0.9737817049026489, 'Val/mean recall': 0.9783565998077393, 'Val/mean hd95_metric': 5.270079135894775} +Cheakpoint... +Epoch [3784/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973946750164032, 'Val/mean miou_metric': 0.9600685238838196, 'Val/mean f1': 0.9760637283325195, 'Val/mean precision': 0.9737817049026489, 'Val/mean recall': 0.9783565998077393, 'Val/mean hd95_metric': 5.270079135894775} +Epoch [3785/4000] Training [1/16] Loss: 0.00197 +Epoch [3785/4000] Training [2/16] Loss: 0.00242 +Epoch [3785/4000] Training [3/16] Loss: 0.00180 +Epoch [3785/4000] Training [4/16] Loss: 0.00205 +Epoch [3785/4000] Training [5/16] Loss: 0.00290 +Epoch [3785/4000] Training [6/16] Loss: 0.00359 +Epoch [3785/4000] Training [7/16] Loss: 0.00210 +Epoch [3785/4000] Training [8/16] Loss: 0.00238 +Epoch [3785/4000] Training [9/16] Loss: 0.00181 +Epoch [3785/4000] Training [10/16] Loss: 0.00149 +Epoch [3785/4000] Training [11/16] Loss: 0.00245 +Epoch [3785/4000] Training [12/16] Loss: 0.00216 +Epoch [3785/4000] Training [13/16] Loss: 0.00247 +Epoch [3785/4000] Training [14/16] Loss: 0.00219 +Epoch [3785/4000] Training [15/16] Loss: 0.00231 +Epoch [3785/4000] Training [16/16] Loss: 0.00225 +Epoch [3785/4000] Training metric {'Train/mean dice_metric': 0.9988425970077515, 'Train/mean miou_metric': 0.9974108338356018, 'Train/mean f1': 0.9938554763793945, 'Train/mean precision': 0.9893120527267456, 'Train/mean recall': 0.9984407424926758, 'Train/mean hd95_metric': 0.5061520338058472} +Epoch [3785/4000] Validation [1/4] Loss: 0.37389 focal_loss 0.31352 dice_loss 0.06037 +Epoch [3785/4000] Validation [2/4] Loss: 0.47920 focal_loss 0.36682 dice_loss 0.11238 +Epoch [3785/4000] Validation [3/4] Loss: 0.54851 focal_loss 0.45230 dice_loss 0.09621 +Epoch [3785/4000] Validation [4/4] Loss: 0.34807 focal_loss 0.26354 dice_loss 0.08453 +Epoch [3785/4000] Validation metric {'Val/mean dice_metric': 0.9747496843338013, 'Val/mean miou_metric': 0.9606670141220093, 'Val/mean f1': 0.9763750433921814, 'Val/mean precision': 0.9733022451400757, 'Val/mean recall': 0.9794673919677734, 'Val/mean hd95_metric': 5.492358684539795} +Cheakpoint... +Epoch [3785/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747496843338013, 'Val/mean miou_metric': 0.9606670141220093, 'Val/mean f1': 0.9763750433921814, 'Val/mean precision': 0.9733022451400757, 'Val/mean recall': 0.9794673919677734, 'Val/mean hd95_metric': 5.492358684539795} +Epoch [3786/4000] Training [1/16] Loss: 0.00221 +Epoch [3786/4000] Training [2/16] Loss: 0.00198 +Epoch [3786/4000] Training [3/16] Loss: 0.00216 +Epoch [3786/4000] Training [4/16] Loss: 0.00334 +Epoch [3786/4000] Training [5/16] Loss: 0.00221 +Epoch [3786/4000] Training [6/16] Loss: 0.00187 +Epoch [3786/4000] Training [7/16] Loss: 0.00308 +Epoch [3786/4000] Training [8/16] Loss: 0.00208 +Epoch [3786/4000] Training [9/16] Loss: 0.00208 +Epoch [3786/4000] Training [10/16] Loss: 0.00150 +Epoch [3786/4000] Training [11/16] Loss: 0.00191 +Epoch [3786/4000] Training [12/16] Loss: 0.00239 +Epoch [3786/4000] Training [13/16] Loss: 0.00305 +Epoch [3786/4000] Training [14/16] Loss: 0.00352 +Epoch [3786/4000] Training [15/16] Loss: 0.00195 +Epoch [3786/4000] Training [16/16] Loss: 0.00292 +Epoch [3786/4000] Training metric {'Train/mean dice_metric': 0.9987578392028809, 'Train/mean miou_metric': 0.9972314834594727, 'Train/mean f1': 0.9935523271560669, 'Train/mean precision': 0.9888730049133301, 'Train/mean recall': 0.9982761740684509, 'Train/mean hd95_metric': 0.5427034497261047} +Epoch [3786/4000] Validation [1/4] Loss: 0.42458 focal_loss 0.36086 dice_loss 0.06372 +Epoch [3786/4000] Validation [2/4] Loss: 0.50397 focal_loss 0.38416 dice_loss 0.11981 +Epoch [3786/4000] Validation [3/4] Loss: 0.51678 focal_loss 0.42674 dice_loss 0.09004 +Epoch [3786/4000] Validation [4/4] Loss: 0.37129 focal_loss 0.27855 dice_loss 0.09275 +Epoch [3786/4000] Validation metric {'Val/mean dice_metric': 0.9740297198295593, 'Val/mean miou_metric': 0.9602716565132141, 'Val/mean f1': 0.9764468669891357, 'Val/mean precision': 0.974040150642395, 'Val/mean recall': 0.9788655638694763, 'Val/mean hd95_metric': 4.67408561706543} +Cheakpoint... +Epoch [3786/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740297198295593, 'Val/mean miou_metric': 0.9602716565132141, 'Val/mean f1': 0.9764468669891357, 'Val/mean precision': 0.974040150642395, 'Val/mean recall': 0.9788655638694763, 'Val/mean hd95_metric': 4.67408561706543} +Epoch [3787/4000] Training [1/16] Loss: 0.00183 +Epoch [3787/4000] Training [2/16] Loss: 0.00189 +Epoch [3787/4000] Training [3/16] Loss: 0.00200 +Epoch [3787/4000] Training [4/16] Loss: 0.00237 +Epoch [3787/4000] Training [5/16] Loss: 0.00281 +Epoch [3787/4000] Training [6/16] Loss: 0.00193 +Epoch [3787/4000] Training [7/16] Loss: 0.00229 +Epoch [3787/4000] Training [8/16] Loss: 0.00303 +Epoch [3787/4000] Training [9/16] Loss: 0.00179 +Epoch [3787/4000] Training [10/16] Loss: 0.00207 +Epoch [3787/4000] Training [11/16] Loss: 0.00211 +Epoch [3787/4000] Training [12/16] Loss: 0.00279 +Epoch [3787/4000] Training [13/16] Loss: 0.00159 +Epoch [3787/4000] Training [14/16] Loss: 0.00399 +Epoch [3787/4000] Training [15/16] Loss: 0.00211 +Epoch [3787/4000] Training [16/16] Loss: 0.00282 +Epoch [3787/4000] Training metric {'Train/mean dice_metric': 0.998908519744873, 'Train/mean miou_metric': 0.997542142868042, 'Train/mean f1': 0.9939287900924683, 'Train/mean precision': 0.9894306063652039, 'Train/mean recall': 0.9984681010246277, 'Train/mean hd95_metric': 0.49585476517677307} +Epoch [3787/4000] Validation [1/4] Loss: 0.48910 focal_loss 0.41981 dice_loss 0.06929 +Epoch [3787/4000] Validation [2/4] Loss: 0.90050 focal_loss 0.64703 dice_loss 0.25347 +Epoch [3787/4000] Validation [3/4] Loss: 0.52663 focal_loss 0.43989 dice_loss 0.08674 +Epoch [3787/4000] Validation [4/4] Loss: 0.47570 focal_loss 0.36233 dice_loss 0.11337 +Epoch [3787/4000] Validation metric {'Val/mean dice_metric': 0.9726269841194153, 'Val/mean miou_metric': 0.9585052728652954, 'Val/mean f1': 0.9759594798088074, 'Val/mean precision': 0.9735940098762512, 'Val/mean recall': 0.9783366322517395, 'Val/mean hd95_metric': 4.924989700317383} +Cheakpoint... +Epoch [3787/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726269841194153, 'Val/mean miou_metric': 0.9585052728652954, 'Val/mean f1': 0.9759594798088074, 'Val/mean precision': 0.9735940098762512, 'Val/mean recall': 0.9783366322517395, 'Val/mean hd95_metric': 4.924989700317383} +Epoch [3788/4000] Training [1/16] Loss: 0.00364 +Epoch [3788/4000] Training [2/16] Loss: 0.00285 +Epoch [3788/4000] Training [3/16] Loss: 0.00272 +Epoch [3788/4000] Training [4/16] Loss: 0.00271 +Epoch [3788/4000] Training [5/16] Loss: 0.00280 +Epoch [3788/4000] Training [6/16] Loss: 0.00176 +Epoch [3788/4000] Training [7/16] Loss: 0.00211 +Epoch [3788/4000] Training [8/16] Loss: 0.00145 +Epoch [3788/4000] Training [9/16] Loss: 0.00252 +Epoch [3788/4000] Training [10/16] Loss: 0.00149 +Epoch [3788/4000] Training [11/16] Loss: 0.00246 +Epoch [3788/4000] Training [12/16] Loss: 0.00342 +Epoch [3788/4000] Training [13/16] Loss: 0.00208 +Epoch [3788/4000] Training [14/16] Loss: 0.00167 +Epoch [3788/4000] Training [15/16] Loss: 0.00251 +Epoch [3788/4000] Training [16/16] Loss: 0.00461 +Epoch [3788/4000] Training metric {'Train/mean dice_metric': 0.9987767934799194, 'Train/mean miou_metric': 0.9972447156906128, 'Train/mean f1': 0.9928850531578064, 'Train/mean precision': 0.9875602722167969, 'Train/mean recall': 0.9982675909996033, 'Train/mean hd95_metric': 0.48104023933410645} +Epoch [3788/4000] Validation [1/4] Loss: 0.39485 focal_loss 0.33074 dice_loss 0.06411 +Epoch [3788/4000] Validation [2/4] Loss: 0.62317 focal_loss 0.46329 dice_loss 0.15988 +Epoch [3788/4000] Validation [3/4] Loss: 0.52386 focal_loss 0.43044 dice_loss 0.09342 +Epoch [3788/4000] Validation [4/4] Loss: 0.33427 focal_loss 0.23810 dice_loss 0.09617 +Epoch [3788/4000] Validation metric {'Val/mean dice_metric': 0.9734489321708679, 'Val/mean miou_metric': 0.9593392610549927, 'Val/mean f1': 0.9754341244697571, 'Val/mean precision': 0.9728273153305054, 'Val/mean recall': 0.9780550003051758, 'Val/mean hd95_metric': 4.970217704772949} +Cheakpoint... +Epoch [3788/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734489321708679, 'Val/mean miou_metric': 0.9593392610549927, 'Val/mean f1': 0.9754341244697571, 'Val/mean precision': 0.9728273153305054, 'Val/mean recall': 0.9780550003051758, 'Val/mean hd95_metric': 4.970217704772949} +Epoch [3789/4000] Training [1/16] Loss: 0.00156 +Epoch [3789/4000] Training [2/16] Loss: 0.00225 +Epoch [3789/4000] Training [3/16] Loss: 0.00158 +Epoch [3789/4000] Training [4/16] Loss: 0.00184 +Epoch [3789/4000] Training [5/16] Loss: 0.00248 +Epoch [3789/4000] Training [6/16] Loss: 0.00240 +Epoch [3789/4000] Training [7/16] Loss: 0.00179 +Epoch [3789/4000] Training [8/16] Loss: 0.00204 +Epoch [3789/4000] Training [9/16] Loss: 0.00199 +Epoch [3789/4000] Training [10/16] Loss: 0.00227 +Epoch [3789/4000] Training [11/16] Loss: 0.00210 +Epoch [3789/4000] Training [12/16] Loss: 0.00234 +Epoch [3789/4000] Training [13/16] Loss: 0.00406 +Epoch [3789/4000] Training [14/16] Loss: 0.00198 +Epoch [3789/4000] Training [15/16] Loss: 0.00292 +Epoch [3789/4000] Training [16/16] Loss: 0.00228 +Epoch [3789/4000] Training metric {'Train/mean dice_metric': 0.998835027217865, 'Train/mean miou_metric': 0.9973477721214294, 'Train/mean f1': 0.9928364753723145, 'Train/mean precision': 0.9873778820037842, 'Train/mean recall': 0.9983556866645813, 'Train/mean hd95_metric': 0.4958283305168152} +Epoch [3789/4000] Validation [1/4] Loss: 0.41669 focal_loss 0.35396 dice_loss 0.06273 +Epoch [3789/4000] Validation [2/4] Loss: 0.47808 focal_loss 0.36923 dice_loss 0.10885 +Epoch [3789/4000] Validation [3/4] Loss: 0.51992 focal_loss 0.42988 dice_loss 0.09004 +Epoch [3789/4000] Validation [4/4] Loss: 0.37467 focal_loss 0.27120 dice_loss 0.10347 +Epoch [3789/4000] Validation metric {'Val/mean dice_metric': 0.9739105105400085, 'Val/mean miou_metric': 0.9596856832504272, 'Val/mean f1': 0.9756510257720947, 'Val/mean precision': 0.9730536341667175, 'Val/mean recall': 0.9782623052597046, 'Val/mean hd95_metric': 4.938722610473633} +Cheakpoint... +Epoch [3789/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739105105400085, 'Val/mean miou_metric': 0.9596856832504272, 'Val/mean f1': 0.9756510257720947, 'Val/mean precision': 0.9730536341667175, 'Val/mean recall': 0.9782623052597046, 'Val/mean hd95_metric': 4.938722610473633} +Epoch [3790/4000] Training [1/16] Loss: 0.00313 +Epoch [3790/4000] Training [2/16] Loss: 0.00407 +Epoch [3790/4000] Training [3/16] Loss: 0.00242 +Epoch [3790/4000] Training [4/16] Loss: 0.00289 +Epoch [3790/4000] Training [5/16] Loss: 0.00246 +Epoch [3790/4000] Training [6/16] Loss: 0.00213 +Epoch [3790/4000] Training [7/16] Loss: 0.00165 +Epoch [3790/4000] Training [8/16] Loss: 0.00214 +Epoch [3790/4000] Training [9/16] Loss: 0.00226 +Epoch [3790/4000] Training [10/16] Loss: 0.00244 +Epoch [3790/4000] Training [11/16] Loss: 0.00367 +Epoch [3790/4000] Training [12/16] Loss: 0.00239 +Epoch [3790/4000] Training [13/16] Loss: 0.00262 +Epoch [3790/4000] Training [14/16] Loss: 0.00285 +Epoch [3790/4000] Training [15/16] Loss: 0.00228 +Epoch [3790/4000] Training [16/16] Loss: 0.00264 +Epoch [3790/4000] Training metric {'Train/mean dice_metric': 0.9987210035324097, 'Train/mean miou_metric': 0.9971705079078674, 'Train/mean f1': 0.9937756061553955, 'Train/mean precision': 0.9892160296440125, 'Train/mean recall': 0.9983774423599243, 'Train/mean hd95_metric': 0.5000928640365601} +Epoch [3790/4000] Validation [1/4] Loss: 0.36953 focal_loss 0.30714 dice_loss 0.06239 +Epoch [3790/4000] Validation [2/4] Loss: 0.64320 focal_loss 0.47426 dice_loss 0.16894 +Epoch [3790/4000] Validation [3/4] Loss: 0.56389 focal_loss 0.46508 dice_loss 0.09881 +Epoch [3790/4000] Validation [4/4] Loss: 0.50945 focal_loss 0.38783 dice_loss 0.12162 +Epoch [3790/4000] Validation metric {'Val/mean dice_metric': 0.9738708734512329, 'Val/mean miou_metric': 0.9596638679504395, 'Val/mean f1': 0.9758577942848206, 'Val/mean precision': 0.9741264581680298, 'Val/mean recall': 0.9775952696800232, 'Val/mean hd95_metric': 4.727878093719482} +Cheakpoint... +Epoch [3790/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738708734512329, 'Val/mean miou_metric': 0.9596638679504395, 'Val/mean f1': 0.9758577942848206, 'Val/mean precision': 0.9741264581680298, 'Val/mean recall': 0.9775952696800232, 'Val/mean hd95_metric': 4.727878093719482} +Epoch [3791/4000] Training [1/16] Loss: 0.00276 +Epoch [3791/4000] Training [2/16] Loss: 0.00221 +Epoch [3791/4000] Training [3/16] Loss: 0.00296 +Epoch [3791/4000] Training [4/16] Loss: 0.00194 +Epoch [3791/4000] Training [5/16] Loss: 0.00351 +Epoch [3791/4000] Training [6/16] Loss: 0.00330 +Epoch [3791/4000] Training [7/16] Loss: 0.00225 +Epoch [3791/4000] Training [8/16] Loss: 0.00170 +Epoch [3791/4000] Training [9/16] Loss: 0.00226 +Epoch [3791/4000] Training [10/16] Loss: 0.00190 +Epoch [3791/4000] Training [11/16] Loss: 0.00221 +Epoch [3791/4000] Training [12/16] Loss: 0.00226 +Epoch [3791/4000] Training [13/16] Loss: 0.00191 +Epoch [3791/4000] Training [14/16] Loss: 0.00194 +Epoch [3791/4000] Training [15/16] Loss: 0.00226 +Epoch [3791/4000] Training [16/16] Loss: 0.00184 +Epoch [3791/4000] Training metric {'Train/mean dice_metric': 0.9988419413566589, 'Train/mean miou_metric': 0.9973974823951721, 'Train/mean f1': 0.9938138723373413, 'Train/mean precision': 0.9892168641090393, 'Train/mean recall': 0.9984538555145264, 'Train/mean hd95_metric': 0.500543475151062} +Epoch [3791/4000] Validation [1/4] Loss: 0.42360 focal_loss 0.35978 dice_loss 0.06382 +Epoch [3791/4000] Validation [2/4] Loss: 0.64901 focal_loss 0.48349 dice_loss 0.16553 +Epoch [3791/4000] Validation [3/4] Loss: 0.52134 focal_loss 0.43337 dice_loss 0.08798 +Epoch [3791/4000] Validation [4/4] Loss: 0.32606 focal_loss 0.23992 dice_loss 0.08614 +Epoch [3791/4000] Validation metric {'Val/mean dice_metric': 0.972673773765564, 'Val/mean miou_metric': 0.9589873552322388, 'Val/mean f1': 0.9760567545890808, 'Val/mean precision': 0.974088728427887, 'Val/mean recall': 0.9780328273773193, 'Val/mean hd95_metric': 5.159817218780518} +Cheakpoint... +Epoch [3791/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972673773765564, 'Val/mean miou_metric': 0.9589873552322388, 'Val/mean f1': 0.9760567545890808, 'Val/mean precision': 0.974088728427887, 'Val/mean recall': 0.9780328273773193, 'Val/mean hd95_metric': 5.159817218780518} +Epoch [3792/4000] Training [1/16] Loss: 0.00246 +Epoch [3792/4000] Training [2/16] Loss: 0.00214 +Epoch [3792/4000] Training [3/16] Loss: 0.00351 +Epoch [3792/4000] Training [4/16] Loss: 0.00258 +Epoch [3792/4000] Training [5/16] Loss: 0.00175 +Epoch [3792/4000] Training [6/16] Loss: 0.00263 +Epoch [3792/4000] Training [7/16] Loss: 0.00232 +Epoch [3792/4000] Training [8/16] Loss: 0.00202 +Epoch [3792/4000] Training [9/16] Loss: 0.00191 +Epoch [3792/4000] Training [10/16] Loss: 0.00210 +Epoch [3792/4000] Training [11/16] Loss: 0.00280 +Epoch [3792/4000] Training [12/16] Loss: 0.00170 +Epoch [3792/4000] Training [13/16] Loss: 0.00214 +Epoch [3792/4000] Training [14/16] Loss: 0.00130 +Epoch [3792/4000] Training [15/16] Loss: 0.00228 +Epoch [3792/4000] Training [16/16] Loss: 0.00379 +Epoch [3792/4000] Training metric {'Train/mean dice_metric': 0.9988325834274292, 'Train/mean miou_metric': 0.9973658323287964, 'Train/mean f1': 0.9934577941894531, 'Train/mean precision': 0.9886031746864319, 'Train/mean recall': 0.998360276222229, 'Train/mean hd95_metric': 0.5004458427429199} +Epoch [3792/4000] Validation [1/4] Loss: 0.41784 focal_loss 0.35361 dice_loss 0.06423 +Epoch [3792/4000] Validation [2/4] Loss: 0.48678 focal_loss 0.36816 dice_loss 0.11862 +Epoch [3792/4000] Validation [3/4] Loss: 0.55743 focal_loss 0.45677 dice_loss 0.10066 +Epoch [3792/4000] Validation [4/4] Loss: 0.36364 focal_loss 0.27662 dice_loss 0.08702 +Epoch [3792/4000] Validation metric {'Val/mean dice_metric': 0.974395751953125, 'Val/mean miou_metric': 0.9600669741630554, 'Val/mean f1': 0.9760338664054871, 'Val/mean precision': 0.9734832048416138, 'Val/mean recall': 0.9785981178283691, 'Val/mean hd95_metric': 5.094834804534912} +Cheakpoint... +Epoch [3792/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974395751953125, 'Val/mean miou_metric': 0.9600669741630554, 'Val/mean f1': 0.9760338664054871, 'Val/mean precision': 0.9734832048416138, 'Val/mean recall': 0.9785981178283691, 'Val/mean hd95_metric': 5.094834804534912} +Epoch [3793/4000] Training [1/16] Loss: 0.00334 +Epoch [3793/4000] Training [2/16] Loss: 0.00212 +Epoch [3793/4000] Training [3/16] Loss: 0.00212 +Epoch [3793/4000] Training [4/16] Loss: 0.00182 +Epoch [3793/4000] Training [5/16] Loss: 0.00180 +Epoch [3793/4000] Training [6/16] Loss: 0.00193 +Epoch [3793/4000] Training [7/16] Loss: 0.00251 +Epoch [3793/4000] Training [8/16] Loss: 0.00355 +Epoch [3793/4000] Training [9/16] Loss: 0.00388 +Epoch [3793/4000] Training [10/16] Loss: 0.00304 +Epoch [3793/4000] Training [11/16] Loss: 0.00195 +Epoch [3793/4000] Training [12/16] Loss: 0.00259 +Epoch [3793/4000] Training [13/16] Loss: 0.00247 +Epoch [3793/4000] Training [14/16] Loss: 0.00207 +Epoch [3793/4000] Training [15/16] Loss: 0.00221 +Epoch [3793/4000] Training [16/16] Loss: 0.00215 +Epoch [3793/4000] Training metric {'Train/mean dice_metric': 0.9988216161727905, 'Train/mean miou_metric': 0.9973485469818115, 'Train/mean f1': 0.9936681389808655, 'Train/mean precision': 0.9889938831329346, 'Train/mean recall': 0.998386800289154, 'Train/mean hd95_metric': 0.5302033424377441} +Epoch [3793/4000] Validation [1/4] Loss: 0.39436 focal_loss 0.33404 dice_loss 0.06032 +Epoch [3793/4000] Validation [2/4] Loss: 0.60586 focal_loss 0.44858 dice_loss 0.15728 +Epoch [3793/4000] Validation [3/4] Loss: 0.54512 focal_loss 0.45485 dice_loss 0.09027 +Epoch [3793/4000] Validation [4/4] Loss: 0.36086 focal_loss 0.27197 dice_loss 0.08889 +Epoch [3793/4000] Validation metric {'Val/mean dice_metric': 0.9743621945381165, 'Val/mean miou_metric': 0.9604597091674805, 'Val/mean f1': 0.976568341255188, 'Val/mean precision': 0.974061131477356, 'Val/mean recall': 0.9790883660316467, 'Val/mean hd95_metric': 5.015275955200195} +Cheakpoint... +Epoch [3793/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743621945381165, 'Val/mean miou_metric': 0.9604597091674805, 'Val/mean f1': 0.976568341255188, 'Val/mean precision': 0.974061131477356, 'Val/mean recall': 0.9790883660316467, 'Val/mean hd95_metric': 5.015275955200195} +Epoch [3794/4000] Training [1/16] Loss: 0.00197 +Epoch [3794/4000] Training [2/16] Loss: 0.00306 +Epoch [3794/4000] Training [3/16] Loss: 0.00227 +Epoch [3794/4000] Training [4/16] Loss: 0.00244 +Epoch [3794/4000] Training [5/16] Loss: 0.00268 +Epoch [3794/4000] Training [6/16] Loss: 0.00191 +Epoch [3794/4000] Training [7/16] Loss: 0.00239 +Epoch [3794/4000] Training [8/16] Loss: 0.00235 +Epoch [3794/4000] Training [9/16] Loss: 0.00309 +Epoch [3794/4000] Training [10/16] Loss: 0.00311 +Epoch [3794/4000] Training [11/16] Loss: 0.00230 +Epoch [3794/4000] Training [12/16] Loss: 0.00250 +Epoch [3794/4000] Training [13/16] Loss: 0.00369 +Epoch [3794/4000] Training [14/16] Loss: 0.00333 +Epoch [3794/4000] Training [15/16] Loss: 0.00297 +Epoch [3794/4000] Training [16/16] Loss: 0.00179 +Epoch [3794/4000] Training metric {'Train/mean dice_metric': 0.9986642599105835, 'Train/mean miou_metric': 0.9970470666885376, 'Train/mean f1': 0.9937005639076233, 'Train/mean precision': 0.9891355633735657, 'Train/mean recall': 0.9983079433441162, 'Train/mean hd95_metric': 0.5366556644439697} +Epoch [3794/4000] Validation [1/4] Loss: 0.39390 focal_loss 0.33133 dice_loss 0.06257 +Epoch [3794/4000] Validation [2/4] Loss: 0.49843 focal_loss 0.38517 dice_loss 0.11326 +Epoch [3794/4000] Validation [3/4] Loss: 0.27057 focal_loss 0.21058 dice_loss 0.05999 +Epoch [3794/4000] Validation [4/4] Loss: 0.46211 focal_loss 0.35211 dice_loss 0.11000 +Epoch [3794/4000] Validation metric {'Val/mean dice_metric': 0.9738094210624695, 'Val/mean miou_metric': 0.9600954055786133, 'Val/mean f1': 0.9768922328948975, 'Val/mean precision': 0.9753921627998352, 'Val/mean recall': 0.9783969521522522, 'Val/mean hd95_metric': 4.558837413787842} +Cheakpoint... +Epoch [3794/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738094210624695, 'Val/mean miou_metric': 0.9600954055786133, 'Val/mean f1': 0.9768922328948975, 'Val/mean precision': 0.9753921627998352, 'Val/mean recall': 0.9783969521522522, 'Val/mean hd95_metric': 4.558837413787842} +Epoch [3795/4000] Training [1/16] Loss: 0.00292 +Epoch [3795/4000] Training [2/16] Loss: 0.00224 +Epoch [3795/4000] Training [3/16] Loss: 0.00299 +Epoch [3795/4000] Training [4/16] Loss: 0.00250 +Epoch [3795/4000] Training [5/16] Loss: 0.00342 +Epoch [3795/4000] Training [6/16] Loss: 0.00244 +Epoch [3795/4000] Training [7/16] Loss: 0.00198 +Epoch [3795/4000] Training [8/16] Loss: 0.00291 +Epoch [3795/4000] Training [9/16] Loss: 0.00277 +Epoch [3795/4000] Training [10/16] Loss: 0.00256 +Epoch [3795/4000] Training [11/16] Loss: 0.00277 +Epoch [3795/4000] Training [12/16] Loss: 0.00239 +Epoch [3795/4000] Training [13/16] Loss: 0.00213 +Epoch [3795/4000] Training [14/16] Loss: 0.00261 +Epoch [3795/4000] Training [15/16] Loss: 0.00290 +Epoch [3795/4000] Training [16/16] Loss: 0.00254 +Epoch [3795/4000] Training metric {'Train/mean dice_metric': 0.9986625909805298, 'Train/mean miou_metric': 0.9970332384109497, 'Train/mean f1': 0.9933831691741943, 'Train/mean precision': 0.9886346459388733, 'Train/mean recall': 0.9981775879859924, 'Train/mean hd95_metric': 0.5380436182022095} +Epoch [3795/4000] Validation [1/4] Loss: 0.45832 focal_loss 0.38817 dice_loss 0.07016 +Epoch [3795/4000] Validation [2/4] Loss: 0.49460 focal_loss 0.38309 dice_loss 0.11150 +Epoch [3795/4000] Validation [3/4] Loss: 0.52289 focal_loss 0.43257 dice_loss 0.09032 +Epoch [3795/4000] Validation [4/4] Loss: 0.33605 focal_loss 0.25295 dice_loss 0.08310 +Epoch [3795/4000] Validation metric {'Val/mean dice_metric': 0.9750638008117676, 'Val/mean miou_metric': 0.9606019854545593, 'Val/mean f1': 0.9760533571243286, 'Val/mean precision': 0.9740738272666931, 'Val/mean recall': 0.978040874004364, 'Val/mean hd95_metric': 4.722205638885498} +Cheakpoint... +Epoch [3795/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750638008117676, 'Val/mean miou_metric': 0.9606019854545593, 'Val/mean f1': 0.9760533571243286, 'Val/mean precision': 0.9740738272666931, 'Val/mean recall': 0.978040874004364, 'Val/mean hd95_metric': 4.722205638885498} +Epoch [3796/4000] Training [1/16] Loss: 0.00386 +Epoch [3796/4000] Training [2/16] Loss: 0.00192 +Epoch [3796/4000] Training [3/16] Loss: 0.00293 +Epoch [3796/4000] Training [4/16] Loss: 0.00311 +Epoch [3796/4000] Training [5/16] Loss: 0.00195 +Epoch [3796/4000] Training [6/16] Loss: 0.00186 +Epoch [3796/4000] Training [7/16] Loss: 0.00274 +Epoch [3796/4000] Training [8/16] Loss: 0.00233 +Epoch [3796/4000] Training [9/16] Loss: 0.00314 +Epoch [3796/4000] Training [10/16] Loss: 0.00255 +Epoch [3796/4000] Training [11/16] Loss: 0.00206 +Epoch [3796/4000] Training [12/16] Loss: 0.00186 +Epoch [3796/4000] Training [13/16] Loss: 0.00256 +Epoch [3796/4000] Training [14/16] Loss: 0.00184 +Epoch [3796/4000] Training [15/16] Loss: 0.00274 +Epoch [3796/4000] Training [16/16] Loss: 0.00429 +Epoch [3796/4000] Training metric {'Train/mean dice_metric': 0.9987280368804932, 'Train/mean miou_metric': 0.9971411228179932, 'Train/mean f1': 0.99300217628479, 'Train/mean precision': 0.9877944588661194, 'Train/mean recall': 0.9982651472091675, 'Train/mean hd95_metric': 0.5136992931365967} +Epoch [3796/4000] Validation [1/4] Loss: 0.40203 focal_loss 0.33791 dice_loss 0.06412 +Epoch [3796/4000] Validation [2/4] Loss: 1.03749 focal_loss 0.78656 dice_loss 0.25093 +Epoch [3796/4000] Validation [3/4] Loss: 0.28866 focal_loss 0.22465 dice_loss 0.06402 +Epoch [3796/4000] Validation [4/4] Loss: 0.29777 focal_loss 0.20934 dice_loss 0.08842 +Epoch [3796/4000] Validation metric {'Val/mean dice_metric': 0.9748169183731079, 'Val/mean miou_metric': 0.9609201550483704, 'Val/mean f1': 0.9758898019790649, 'Val/mean precision': 0.972716212272644, 'Val/mean recall': 0.9790840148925781, 'Val/mean hd95_metric': 4.820969104766846} +Cheakpoint... +Epoch [3796/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748169183731079, 'Val/mean miou_metric': 0.9609201550483704, 'Val/mean f1': 0.9758898019790649, 'Val/mean precision': 0.972716212272644, 'Val/mean recall': 0.9790840148925781, 'Val/mean hd95_metric': 4.820969104766846} +Epoch [3797/4000] Training [1/16] Loss: 0.00228 +Epoch [3797/4000] Training [2/16] Loss: 0.00181 +Epoch [3797/4000] Training [3/16] Loss: 0.00235 +Epoch [3797/4000] Training [4/16] Loss: 0.00177 +Epoch [3797/4000] Training [5/16] Loss: 0.00218 +Epoch [3797/4000] Training [6/16] Loss: 0.00219 +Epoch [3797/4000] Training [7/16] Loss: 0.00166 +Epoch [3797/4000] Training [8/16] Loss: 0.00193 +Epoch [3797/4000] Training [9/16] Loss: 0.00234 +Epoch [3797/4000] Training [10/16] Loss: 0.00187 +Epoch [3797/4000] Training [11/16] Loss: 0.00203 +Epoch [3797/4000] Training [12/16] Loss: 0.00244 +Epoch [3797/4000] Training [13/16] Loss: 0.00340 +Epoch [3797/4000] Training [14/16] Loss: 0.00182 +Epoch [3797/4000] Training [15/16] Loss: 0.00182 +Epoch [3797/4000] Training [16/16] Loss: 0.00325 +Epoch [3797/4000] Training metric {'Train/mean dice_metric': 0.9988740682601929, 'Train/mean miou_metric': 0.9974750280380249, 'Train/mean f1': 0.9939168095588684, 'Train/mean precision': 0.989417552947998, 'Train/mean recall': 0.9984572529792786, 'Train/mean hd95_metric': 0.4891456663608551} +Epoch [3797/4000] Validation [1/4] Loss: 0.42839 focal_loss 0.36341 dice_loss 0.06498 +Epoch [3797/4000] Validation [2/4] Loss: 0.92496 focal_loss 0.71721 dice_loss 0.20774 +Epoch [3797/4000] Validation [3/4] Loss: 0.56444 focal_loss 0.46730 dice_loss 0.09714 +Epoch [3797/4000] Validation [4/4] Loss: 0.37026 focal_loss 0.27215 dice_loss 0.09812 +Epoch [3797/4000] Validation metric {'Val/mean dice_metric': 0.973800778388977, 'Val/mean miou_metric': 0.9597991704940796, 'Val/mean f1': 0.9758962392807007, 'Val/mean precision': 0.9740678668022156, 'Val/mean recall': 0.9777315855026245, 'Val/mean hd95_metric': 5.01678466796875} +Cheakpoint... +Epoch [3797/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973800778388977, 'Val/mean miou_metric': 0.9597991704940796, 'Val/mean f1': 0.9758962392807007, 'Val/mean precision': 0.9740678668022156, 'Val/mean recall': 0.9777315855026245, 'Val/mean hd95_metric': 5.01678466796875} +Epoch [3798/4000] Training [1/16] Loss: 0.00243 +Epoch [3798/4000] Training [2/16] Loss: 0.00162 +Epoch [3798/4000] Training [3/16] Loss: 0.00245 +Epoch [3798/4000] Training [4/16] Loss: 0.00187 +Epoch [3798/4000] Training [5/16] Loss: 0.00319 +Epoch [3798/4000] Training [6/16] Loss: 0.00313 +Epoch [3798/4000] Training [7/16] Loss: 0.00182 +Epoch [3798/4000] Training [8/16] Loss: 0.00244 +Epoch [3798/4000] Training [9/16] Loss: 0.00136 +Epoch [3798/4000] Training [10/16] Loss: 0.00344 +Epoch [3798/4000] Training [11/16] Loss: 0.00350 +Epoch [3798/4000] Training [12/16] Loss: 0.00276 +Epoch [3798/4000] Training [13/16] Loss: 0.00218 +Epoch [3798/4000] Training [14/16] Loss: 0.00234 +Epoch [3798/4000] Training [15/16] Loss: 0.00218 +Epoch [3798/4000] Training [16/16] Loss: 0.00221 +Epoch [3798/4000] Training metric {'Train/mean dice_metric': 0.9988644123077393, 'Train/mean miou_metric': 0.9974421262741089, 'Train/mean f1': 0.9937165975570679, 'Train/mean precision': 0.9890413880348206, 'Train/mean recall': 0.9984362125396729, 'Train/mean hd95_metric': 0.4989534914493561} +Epoch [3798/4000] Validation [1/4] Loss: 0.38904 focal_loss 0.32616 dice_loss 0.06288 +Epoch [3798/4000] Validation [2/4] Loss: 0.63682 focal_loss 0.47306 dice_loss 0.16376 +Epoch [3798/4000] Validation [3/4] Loss: 0.29504 focal_loss 0.23212 dice_loss 0.06292 +Epoch [3798/4000] Validation [4/4] Loss: 0.34179 focal_loss 0.25506 dice_loss 0.08673 +Epoch [3798/4000] Validation metric {'Val/mean dice_metric': 0.9753162264823914, 'Val/mean miou_metric': 0.9616045951843262, 'Val/mean f1': 0.9766507148742676, 'Val/mean precision': 0.9745919704437256, 'Val/mean recall': 0.978718101978302, 'Val/mean hd95_metric': 4.96969747543335} +Cheakpoint... +Epoch [3798/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753162264823914, 'Val/mean miou_metric': 0.9616045951843262, 'Val/mean f1': 0.9766507148742676, 'Val/mean precision': 0.9745919704437256, 'Val/mean recall': 0.978718101978302, 'Val/mean hd95_metric': 4.96969747543335} +Epoch [3799/4000] Training [1/16] Loss: 0.00208 +Epoch [3799/4000] Training [2/16] Loss: 0.00232 +Epoch [3799/4000] Training [3/16] Loss: 0.00191 +Epoch [3799/4000] Training [4/16] Loss: 0.00216 +Epoch [3799/4000] Training [5/16] Loss: 0.00345 +Epoch [3799/4000] Training [6/16] Loss: 0.00164 +Epoch [3799/4000] Training [7/16] Loss: 0.00191 +Epoch [3799/4000] Training [8/16] Loss: 0.00272 +Epoch [3799/4000] Training [9/16] Loss: 0.00206 +Epoch [3799/4000] Training [10/16] Loss: 0.00279 +Epoch [3799/4000] Training [11/16] Loss: 0.00216 +Epoch [3799/4000] Training [12/16] Loss: 0.00254 +Epoch [3799/4000] Training [13/16] Loss: 0.00187 +Epoch [3799/4000] Training [14/16] Loss: 0.00341 +Epoch [3799/4000] Training [15/16] Loss: 0.00220 +Epoch [3799/4000] Training [16/16] Loss: 0.00158 +Epoch [3799/4000] Training metric {'Train/mean dice_metric': 0.9988102316856384, 'Train/mean miou_metric': 0.9973469972610474, 'Train/mean f1': 0.9938802719116211, 'Train/mean precision': 0.9893540143966675, 'Train/mean recall': 0.9984481334686279, 'Train/mean hd95_metric': 0.5089143514633179} +Epoch [3799/4000] Validation [1/4] Loss: 0.42547 focal_loss 0.36113 dice_loss 0.06435 +Epoch [3799/4000] Validation [2/4] Loss: 0.93778 focal_loss 0.74915 dice_loss 0.18863 +Epoch [3799/4000] Validation [3/4] Loss: 0.57848 focal_loss 0.47946 dice_loss 0.09903 +Epoch [3799/4000] Validation [4/4] Loss: 0.29942 focal_loss 0.21262 dice_loss 0.08680 +Epoch [3799/4000] Validation metric {'Val/mean dice_metric': 0.9742456674575806, 'Val/mean miou_metric': 0.9607774615287781, 'Val/mean f1': 0.976849377155304, 'Val/mean precision': 0.9743476510047913, 'Val/mean recall': 0.9793638586997986, 'Val/mean hd95_metric': 4.852158546447754} +Cheakpoint... +Epoch [3799/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742456674575806, 'Val/mean miou_metric': 0.9607774615287781, 'Val/mean f1': 0.976849377155304, 'Val/mean precision': 0.9743476510047913, 'Val/mean recall': 0.9793638586997986, 'Val/mean hd95_metric': 4.852158546447754} +Epoch [3800/4000] Training [1/16] Loss: 0.00212 +Epoch [3800/4000] Training [2/16] Loss: 0.00187 +Epoch [3800/4000] Training [3/16] Loss: 0.00256 +Epoch [3800/4000] Training [4/16] Loss: 0.00230 +Epoch [3800/4000] Training [5/16] Loss: 0.00368 +Epoch [3800/4000] Training [6/16] Loss: 0.00186 +Epoch [3800/4000] Training [7/16] Loss: 0.00178 +Epoch [3800/4000] Training [8/16] Loss: 0.00200 +Epoch [3800/4000] Training [9/16] Loss: 0.00341 +Epoch [3800/4000] Training [10/16] Loss: 0.00293 +Epoch [3800/4000] Training [11/16] Loss: 0.00181 +Epoch [3800/4000] Training [12/16] Loss: 0.00148 +Epoch [3800/4000] Training [13/16] Loss: 0.00196 +Epoch [3800/4000] Training [14/16] Loss: 0.00249 +Epoch [3800/4000] Training [15/16] Loss: 0.00197 +Epoch [3800/4000] Training [16/16] Loss: 0.00300 +Epoch [3800/4000] Training metric {'Train/mean dice_metric': 0.9987953901290894, 'Train/mean miou_metric': 0.997320294380188, 'Train/mean f1': 0.9938439726829529, 'Train/mean precision': 0.9893130660057068, 'Train/mean recall': 0.9984166026115417, 'Train/mean hd95_metric': 0.485867440700531} +Epoch [3800/4000] Validation [1/4] Loss: 0.42826 focal_loss 0.36379 dice_loss 0.06447 +Epoch [3800/4000] Validation [2/4] Loss: 0.47564 focal_loss 0.36397 dice_loss 0.11167 +Epoch [3800/4000] Validation [3/4] Loss: 0.27376 focal_loss 0.21210 dice_loss 0.06166 +Epoch [3800/4000] Validation [4/4] Loss: 0.42203 focal_loss 0.32060 dice_loss 0.10143 +Epoch [3800/4000] Validation metric {'Val/mean dice_metric': 0.9752626419067383, 'Val/mean miou_metric': 0.9614704251289368, 'Val/mean f1': 0.976936399936676, 'Val/mean precision': 0.9746171236038208, 'Val/mean recall': 0.9792667031288147, 'Val/mean hd95_metric': 4.612786769866943} +Cheakpoint... +Epoch [3800/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752626419067383, 'Val/mean miou_metric': 0.9614704251289368, 'Val/mean f1': 0.976936399936676, 'Val/mean precision': 0.9746171236038208, 'Val/mean recall': 0.9792667031288147, 'Val/mean hd95_metric': 4.612786769866943} +Epoch [3801/4000] Training [1/16] Loss: 0.00263 +Epoch [3801/4000] Training [2/16] Loss: 0.00319 +Epoch [3801/4000] Training [3/16] Loss: 0.00202 +Epoch [3801/4000] Training [4/16] Loss: 0.00274 +Epoch [3801/4000] Training [5/16] Loss: 0.00277 +Epoch [3801/4000] Training [6/16] Loss: 0.00316 +Epoch [3801/4000] Training [7/16] Loss: 0.00202 +Epoch [3801/4000] Training [8/16] Loss: 0.00254 +Epoch [3801/4000] Training [9/16] Loss: 0.00226 +Epoch [3801/4000] Training [10/16] Loss: 0.00335 +Epoch [3801/4000] Training [11/16] Loss: 0.00266 +Epoch [3801/4000] Training [12/16] Loss: 0.00226 +Epoch [3801/4000] Training [13/16] Loss: 0.00181 +Epoch [3801/4000] Training [14/16] Loss: 0.00169 +Epoch [3801/4000] Training [15/16] Loss: 0.00274 +Epoch [3801/4000] Training [16/16] Loss: 0.00204 +Epoch [3801/4000] Training metric {'Train/mean dice_metric': 0.9987772703170776, 'Train/mean miou_metric': 0.9972834587097168, 'Train/mean f1': 0.9938164949417114, 'Train/mean precision': 0.9893183708190918, 'Train/mean recall': 0.9983557462692261, 'Train/mean hd95_metric': 0.5262970924377441} +Epoch [3801/4000] Validation [1/4] Loss: 0.37178 focal_loss 0.31105 dice_loss 0.06073 +Epoch [3801/4000] Validation [2/4] Loss: 0.49635 focal_loss 0.38433 dice_loss 0.11202 +Epoch [3801/4000] Validation [3/4] Loss: 0.31412 focal_loss 0.24596 dice_loss 0.06816 +Epoch [3801/4000] Validation [4/4] Loss: 0.35194 focal_loss 0.26508 dice_loss 0.08686 +Epoch [3801/4000] Validation metric {'Val/mean dice_metric': 0.9739635586738586, 'Val/mean miou_metric': 0.9603374600410461, 'Val/mean f1': 0.9761346578598022, 'Val/mean precision': 0.9744015336036682, 'Val/mean recall': 0.9778739809989929, 'Val/mean hd95_metric': 5.181576251983643} +Cheakpoint... +Epoch [3801/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739635586738586, 'Val/mean miou_metric': 0.9603374600410461, 'Val/mean f1': 0.9761346578598022, 'Val/mean precision': 0.9744015336036682, 'Val/mean recall': 0.9778739809989929, 'Val/mean hd95_metric': 5.181576251983643} +Epoch [3802/4000] Training [1/16] Loss: 0.00289 +Epoch [3802/4000] Training [2/16] Loss: 0.00243 +Epoch [3802/4000] Training [3/16] Loss: 0.00197 +Epoch [3802/4000] Training [4/16] Loss: 0.00231 +Epoch [3802/4000] Training [5/16] Loss: 0.00271 +Epoch [3802/4000] Training [6/16] Loss: 0.00202 +Epoch [3802/4000] Training [7/16] Loss: 0.00232 +Epoch [3802/4000] Training [8/16] Loss: 0.00143 +Epoch [3802/4000] Training [9/16] Loss: 0.00204 +Epoch [3802/4000] Training [10/16] Loss: 0.00218 +Epoch [3802/4000] Training [11/16] Loss: 0.00298 +Epoch [3802/4000] Training [12/16] Loss: 0.00190 +Epoch [3802/4000] Training [13/16] Loss: 0.00311 +Epoch [3802/4000] Training [14/16] Loss: 0.00183 +Epoch [3802/4000] Training [15/16] Loss: 0.00184 +Epoch [3802/4000] Training [16/16] Loss: 0.00257 +Epoch [3802/4000] Training metric {'Train/mean dice_metric': 0.9988716840744019, 'Train/mean miou_metric': 0.9974498748779297, 'Train/mean f1': 0.993638277053833, 'Train/mean precision': 0.9888760447502136, 'Train/mean recall': 0.9984465837478638, 'Train/mean hd95_metric': 0.506668210029602} +Epoch [3802/4000] Validation [1/4] Loss: 0.43022 focal_loss 0.36631 dice_loss 0.06391 +Epoch [3802/4000] Validation [2/4] Loss: 0.78772 focal_loss 0.58081 dice_loss 0.20691 +Epoch [3802/4000] Validation [3/4] Loss: 0.27270 focal_loss 0.21006 dice_loss 0.06264 +Epoch [3802/4000] Validation [4/4] Loss: 0.54486 focal_loss 0.41199 dice_loss 0.13287 +Epoch [3802/4000] Validation metric {'Val/mean dice_metric': 0.9732389450073242, 'Val/mean miou_metric': 0.9593818783760071, 'Val/mean f1': 0.9759225845336914, 'Val/mean precision': 0.9739823937416077, 'Val/mean recall': 0.977870523929596, 'Val/mean hd95_metric': 5.059831142425537} +Cheakpoint... +Epoch [3802/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732389450073242, 'Val/mean miou_metric': 0.9593818783760071, 'Val/mean f1': 0.9759225845336914, 'Val/mean precision': 0.9739823937416077, 'Val/mean recall': 0.977870523929596, 'Val/mean hd95_metric': 5.059831142425537} +Epoch [3803/4000] Training [1/16] Loss: 0.00273 +Epoch [3803/4000] Training [2/16] Loss: 0.00278 +Epoch [3803/4000] Training [3/16] Loss: 0.00266 +Epoch [3803/4000] Training [4/16] Loss: 0.00190 +Epoch [3803/4000] Training [5/16] Loss: 0.00257 +Epoch [3803/4000] Training [6/16] Loss: 0.00165 +Epoch [3803/4000] Training [7/16] Loss: 0.00227 +Epoch [3803/4000] Training [8/16] Loss: 0.00672 +Epoch [3803/4000] Training [9/16] Loss: 0.00315 +Epoch [3803/4000] Training [10/16] Loss: 0.00258 +Epoch [3803/4000] Training [11/16] Loss: 0.00304 +Epoch [3803/4000] Training [12/16] Loss: 0.00215 +Epoch [3803/4000] Training [13/16] Loss: 0.00325 +Epoch [3803/4000] Training [14/16] Loss: 0.00308 +Epoch [3803/4000] Training [15/16] Loss: 0.00222 +Epoch [3803/4000] Training [16/16] Loss: 0.00172 +Epoch [3803/4000] Training metric {'Train/mean dice_metric': 0.9986547231674194, 'Train/mean miou_metric': 0.9970351457595825, 'Train/mean f1': 0.9935054779052734, 'Train/mean precision': 0.9888678193092346, 'Train/mean recall': 0.9981868863105774, 'Train/mean hd95_metric': 0.5812252759933472} +Epoch [3803/4000] Validation [1/4] Loss: 0.42664 focal_loss 0.36237 dice_loss 0.06427 +Epoch [3803/4000] Validation [2/4] Loss: 0.88194 focal_loss 0.68216 dice_loss 0.19978 +Epoch [3803/4000] Validation [3/4] Loss: 0.53711 focal_loss 0.44596 dice_loss 0.09115 +Epoch [3803/4000] Validation [4/4] Loss: 0.41885 focal_loss 0.30854 dice_loss 0.11031 +Epoch [3803/4000] Validation metric {'Val/mean dice_metric': 0.9733415842056274, 'Val/mean miou_metric': 0.958991527557373, 'Val/mean f1': 0.9758519530296326, 'Val/mean precision': 0.9733119010925293, 'Val/mean recall': 0.978405237197876, 'Val/mean hd95_metric': 4.845996379852295} +Cheakpoint... +Epoch [3803/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733415842056274, 'Val/mean miou_metric': 0.958991527557373, 'Val/mean f1': 0.9758519530296326, 'Val/mean precision': 0.9733119010925293, 'Val/mean recall': 0.978405237197876, 'Val/mean hd95_metric': 4.845996379852295} +Epoch [3804/4000] Training [1/16] Loss: 0.00260 +Epoch [3804/4000] Training [2/16] Loss: 0.00302 +Epoch [3804/4000] Training [3/16] Loss: 0.00366 +Epoch [3804/4000] Training [4/16] Loss: 0.00243 +Epoch [3804/4000] Training [5/16] Loss: 0.00185 +Epoch [3804/4000] Training [6/16] Loss: 0.00184 +Epoch [3804/4000] Training [7/16] Loss: 0.00311 +Epoch [3804/4000] Training [8/16] Loss: 0.00205 +Epoch [3804/4000] Training [9/16] Loss: 0.00447 +Epoch [3804/4000] Training [10/16] Loss: 0.00192 +Epoch [3804/4000] Training [11/16] Loss: 0.00201 +Epoch [3804/4000] Training [12/16] Loss: 0.00161 +Epoch [3804/4000] Training [13/16] Loss: 0.00181 +Epoch [3804/4000] Training [14/16] Loss: 0.00180 +Epoch [3804/4000] Training [15/16] Loss: 0.00189 +Epoch [3804/4000] Training [16/16] Loss: 0.00218 +Epoch [3804/4000] Training metric {'Train/mean dice_metric': 0.9988304376602173, 'Train/mean miou_metric': 0.997370719909668, 'Train/mean f1': 0.9938005208969116, 'Train/mean precision': 0.9891926646232605, 'Train/mean recall': 0.9984515309333801, 'Train/mean hd95_metric': 0.49709776043891907} +Epoch [3804/4000] Validation [1/4] Loss: 0.43114 focal_loss 0.36638 dice_loss 0.06476 +Epoch [3804/4000] Validation [2/4] Loss: 0.43855 focal_loss 0.33122 dice_loss 0.10732 +Epoch [3804/4000] Validation [3/4] Loss: 0.59522 focal_loss 0.49850 dice_loss 0.09672 +Epoch [3804/4000] Validation [4/4] Loss: 0.40193 focal_loss 0.29748 dice_loss 0.10446 +Epoch [3804/4000] Validation metric {'Val/mean dice_metric': 0.9745508432388306, 'Val/mean miou_metric': 0.9600120782852173, 'Val/mean f1': 0.9764041900634766, 'Val/mean precision': 0.9739053845405579, 'Val/mean recall': 0.9789160490036011, 'Val/mean hd95_metric': 5.07785701751709} +Cheakpoint... +Epoch [3804/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745508432388306, 'Val/mean miou_metric': 0.9600120782852173, 'Val/mean f1': 0.9764041900634766, 'Val/mean precision': 0.9739053845405579, 'Val/mean recall': 0.9789160490036011, 'Val/mean hd95_metric': 5.07785701751709} +Epoch [3805/4000] Training [1/16] Loss: 0.00242 +Epoch [3805/4000] Training [2/16] Loss: 0.00272 +Epoch [3805/4000] Training [3/16] Loss: 0.00170 +Epoch [3805/4000] Training [4/16] Loss: 0.00190 +Epoch [3805/4000] Training [5/16] Loss: 0.00169 +Epoch [3805/4000] Training [6/16] Loss: 0.00312 +Epoch [3805/4000] Training [7/16] Loss: 0.00250 +Epoch [3805/4000] Training [8/16] Loss: 0.00244 +Epoch [3805/4000] Training [9/16] Loss: 0.00251 +Epoch [3805/4000] Training [10/16] Loss: 0.00459 +Epoch [3805/4000] Training [11/16] Loss: 0.00168 +Epoch [3805/4000] Training [12/16] Loss: 0.00201 +Epoch [3805/4000] Training [13/16] Loss: 0.00228 +Epoch [3805/4000] Training [14/16] Loss: 0.00356 +Epoch [3805/4000] Training [15/16] Loss: 0.00311 +Epoch [3805/4000] Training [16/16] Loss: 0.00216 +Epoch [3805/4000] Training metric {'Train/mean dice_metric': 0.9987009763717651, 'Train/mean miou_metric': 0.9971076250076294, 'Train/mean f1': 0.9931286573410034, 'Train/mean precision': 0.9879962205886841, 'Train/mean recall': 0.9983147382736206, 'Train/mean hd95_metric': 0.5321565270423889} +Epoch [3805/4000] Validation [1/4] Loss: 0.34475 focal_loss 0.28639 dice_loss 0.05836 +Epoch [3805/4000] Validation [2/4] Loss: 0.48715 focal_loss 0.37407 dice_loss 0.11308 +Epoch [3805/4000] Validation [3/4] Loss: 0.28414 focal_loss 0.22307 dice_loss 0.06107 +Epoch [3805/4000] Validation [4/4] Loss: 0.32161 focal_loss 0.23049 dice_loss 0.09111 +Epoch [3805/4000] Validation metric {'Val/mean dice_metric': 0.9762544631958008, 'Val/mean miou_metric': 0.9621379971504211, 'Val/mean f1': 0.9762710332870483, 'Val/mean precision': 0.9736711382865906, 'Val/mean recall': 0.9788849353790283, 'Val/mean hd95_metric': 4.801065444946289} +Cheakpoint... +Epoch [3805/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9763], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9762544631958008, 'Val/mean miou_metric': 0.9621379971504211, 'Val/mean f1': 0.9762710332870483, 'Val/mean precision': 0.9736711382865906, 'Val/mean recall': 0.9788849353790283, 'Val/mean hd95_metric': 4.801065444946289} +Epoch [3806/4000] Training [1/16] Loss: 0.00209 +Epoch [3806/4000] Training [2/16] Loss: 0.00252 +Epoch [3806/4000] Training [3/16] Loss: 0.00285 +Epoch [3806/4000] Training [4/16] Loss: 0.00230 +Epoch [3806/4000] Training [5/16] Loss: 0.00225 +Epoch [3806/4000] Training [6/16] Loss: 0.00226 +Epoch [3806/4000] Training [7/16] Loss: 0.00119 +Epoch [3806/4000] Training [8/16] Loss: 0.00377 +Epoch [3806/4000] Training [9/16] Loss: 0.00327 +Epoch [3806/4000] Training [10/16] Loss: 0.00281 +Epoch [3806/4000] Training [11/16] Loss: 0.00199 +Epoch [3806/4000] Training [12/16] Loss: 0.00235 +Epoch [3806/4000] Training [13/16] Loss: 0.00201 +Epoch [3806/4000] Training [14/16] Loss: 0.00258 +Epoch [3806/4000] Training [15/16] Loss: 0.00210 +Epoch [3806/4000] Training [16/16] Loss: 0.00206 +Epoch [3806/4000] Training metric {'Train/mean dice_metric': 0.998796820640564, 'Train/mean miou_metric': 0.9973189830780029, 'Train/mean f1': 0.9937978386878967, 'Train/mean precision': 0.9892987608909607, 'Train/mean recall': 0.998337984085083, 'Train/mean hd95_metric': 0.538406491279602} +Epoch [3806/4000] Validation [1/4] Loss: 0.38608 focal_loss 0.32513 dice_loss 0.06094 +Epoch [3806/4000] Validation [2/4] Loss: 0.90169 focal_loss 0.69935 dice_loss 0.20234 +Epoch [3806/4000] Validation [3/4] Loss: 0.58307 focal_loss 0.48300 dice_loss 0.10007 +Epoch [3806/4000] Validation [4/4] Loss: 0.59972 focal_loss 0.46746 dice_loss 0.13226 +Epoch [3806/4000] Validation metric {'Val/mean dice_metric': 0.9732492566108704, 'Val/mean miou_metric': 0.9590424299240112, 'Val/mean f1': 0.9761171340942383, 'Val/mean precision': 0.9741790294647217, 'Val/mean recall': 0.9780631065368652, 'Val/mean hd95_metric': 4.961945533752441} +Cheakpoint... +Epoch [3806/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732492566108704, 'Val/mean miou_metric': 0.9590424299240112, 'Val/mean f1': 0.9761171340942383, 'Val/mean precision': 0.9741790294647217, 'Val/mean recall': 0.9780631065368652, 'Val/mean hd95_metric': 4.961945533752441} +Epoch [3807/4000] Training [1/16] Loss: 0.00179 +Epoch [3807/4000] Training [2/16] Loss: 0.00196 +Epoch [3807/4000] Training [3/16] Loss: 0.00239 +Epoch [3807/4000] Training [4/16] Loss: 0.00223 +Epoch [3807/4000] Training [5/16] Loss: 0.00169 +Epoch [3807/4000] Training [6/16] Loss: 0.00311 +Epoch [3807/4000] Training [7/16] Loss: 0.00229 +Epoch [3807/4000] Training [8/16] Loss: 0.00221 +Epoch [3807/4000] Training [9/16] Loss: 0.00201 +Epoch [3807/4000] Training [10/16] Loss: 0.00219 +Epoch [3807/4000] Training [11/16] Loss: 0.00202 +Epoch [3807/4000] Training [12/16] Loss: 0.00308 +Epoch [3807/4000] Training [13/16] Loss: 0.00273 +Epoch [3807/4000] Training [14/16] Loss: 0.00227 +Epoch [3807/4000] Training [15/16] Loss: 0.00164 +Epoch [3807/4000] Training [16/16] Loss: 0.00256 +Epoch [3807/4000] Training metric {'Train/mean dice_metric': 0.9989109039306641, 'Train/mean miou_metric': 0.9975460767745972, 'Train/mean f1': 0.993840217590332, 'Train/mean precision': 0.9892478585243225, 'Train/mean recall': 0.9984753727912903, 'Train/mean hd95_metric': 0.4820864796638489} +Epoch [3807/4000] Validation [1/4] Loss: 0.39346 focal_loss 0.32838 dice_loss 0.06508 +Epoch [3807/4000] Validation [2/4] Loss: 1.00920 focal_loss 0.76342 dice_loss 0.24578 +Epoch [3807/4000] Validation [3/4] Loss: 0.54611 focal_loss 0.45639 dice_loss 0.08973 +Epoch [3807/4000] Validation [4/4] Loss: 0.32865 focal_loss 0.23006 dice_loss 0.09859 +Epoch [3807/4000] Validation metric {'Val/mean dice_metric': 0.973382830619812, 'Val/mean miou_metric': 0.9594675898551941, 'Val/mean f1': 0.9753296375274658, 'Val/mean precision': 0.9730886220932007, 'Val/mean recall': 0.9775809645652771, 'Val/mean hd95_metric': 5.3916449546813965} +Cheakpoint... +Epoch [3807/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973382830619812, 'Val/mean miou_metric': 0.9594675898551941, 'Val/mean f1': 0.9753296375274658, 'Val/mean precision': 0.9730886220932007, 'Val/mean recall': 0.9775809645652771, 'Val/mean hd95_metric': 5.3916449546813965} +Epoch [3808/4000] Training [1/16] Loss: 0.00231 +Epoch [3808/4000] Training [2/16] Loss: 0.00153 +Epoch [3808/4000] Training [3/16] Loss: 0.00309 +Epoch [3808/4000] Training [4/16] Loss: 0.00280 +Epoch [3808/4000] Training [5/16] Loss: 0.00260 +Epoch [3808/4000] Training [6/16] Loss: 0.00313 +Epoch [3808/4000] Training [7/16] Loss: 0.00294 +Epoch [3808/4000] Training [8/16] Loss: 0.00238 +Epoch [3808/4000] Training [9/16] Loss: 0.00213 +Epoch [3808/4000] Training [10/16] Loss: 0.00230 +Epoch [3808/4000] Training [11/16] Loss: 0.00186 +Epoch [3808/4000] Training [12/16] Loss: 0.00158 +Epoch [3808/4000] Training [13/16] Loss: 0.00265 +Epoch [3808/4000] Training [14/16] Loss: 0.00360 +Epoch [3808/4000] Training [15/16] Loss: 0.00188 +Epoch [3808/4000] Training [16/16] Loss: 0.00290 +Epoch [3808/4000] Training metric {'Train/mean dice_metric': 0.9987118244171143, 'Train/mean miou_metric': 0.9971516132354736, 'Train/mean f1': 0.9938932657241821, 'Train/mean precision': 0.9894498586654663, 'Train/mean recall': 0.998376727104187, 'Train/mean hd95_metric': 0.5085513591766357} +Epoch [3808/4000] Validation [1/4] Loss: 0.46679 focal_loss 0.40421 dice_loss 0.06258 +Epoch [3808/4000] Validation [2/4] Loss: 0.47834 focal_loss 0.36785 dice_loss 0.11048 +Epoch [3808/4000] Validation [3/4] Loss: 0.25393 focal_loss 0.19585 dice_loss 0.05808 +Epoch [3808/4000] Validation [4/4] Loss: 0.37123 focal_loss 0.26646 dice_loss 0.10477 +Epoch [3808/4000] Validation metric {'Val/mean dice_metric': 0.9753001928329468, 'Val/mean miou_metric': 0.9612953066825867, 'Val/mean f1': 0.977360725402832, 'Val/mean precision': 0.9751507639884949, 'Val/mean recall': 0.9795807600021362, 'Val/mean hd95_metric': 4.7494330406188965} +Cheakpoint... +Epoch [3808/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753001928329468, 'Val/mean miou_metric': 0.9612953066825867, 'Val/mean f1': 0.977360725402832, 'Val/mean precision': 0.9751507639884949, 'Val/mean recall': 0.9795807600021362, 'Val/mean hd95_metric': 4.7494330406188965} +Epoch [3809/4000] Training [1/16] Loss: 0.00187 +Epoch [3809/4000] Training [2/16] Loss: 0.00250 +Epoch [3809/4000] Training [3/16] Loss: 0.00228 +Epoch [3809/4000] Training [4/16] Loss: 0.00345 +Epoch [3809/4000] Training [5/16] Loss: 0.00193 +Epoch [3809/4000] Training [6/16] Loss: 0.00267 +Epoch [3809/4000] Training [7/16] Loss: 0.00167 +Epoch [3809/4000] Training [8/16] Loss: 0.00205 +Epoch [3809/4000] Training [9/16] Loss: 0.00199 +Epoch [3809/4000] Training [10/16] Loss: 0.00207 +Epoch [3809/4000] Training [11/16] Loss: 0.00333 +Epoch [3809/4000] Training [12/16] Loss: 0.00305 +Epoch [3809/4000] Training [13/16] Loss: 0.00247 +Epoch [3809/4000] Training [14/16] Loss: 0.00277 +Epoch [3809/4000] Training [15/16] Loss: 0.00167 +Epoch [3809/4000] Training [16/16] Loss: 0.00173 +Epoch [3809/4000] Training metric {'Train/mean dice_metric': 0.9989068508148193, 'Train/mean miou_metric': 0.9975398778915405, 'Train/mean f1': 0.9938664436340332, 'Train/mean precision': 0.9893155097961426, 'Train/mean recall': 0.9984594583511353, 'Train/mean hd95_metric': 0.5035432577133179} +Epoch [3809/4000] Validation [1/4] Loss: 0.41112 focal_loss 0.34633 dice_loss 0.06479 +Epoch [3809/4000] Validation [2/4] Loss: 0.88647 focal_loss 0.68771 dice_loss 0.19876 +Epoch [3809/4000] Validation [3/4] Loss: 0.54976 focal_loss 0.45502 dice_loss 0.09474 +Epoch [3809/4000] Validation [4/4] Loss: 0.44938 focal_loss 0.34006 dice_loss 0.10933 +Epoch [3809/4000] Validation metric {'Val/mean dice_metric': 0.9752310514450073, 'Val/mean miou_metric': 0.9611395597457886, 'Val/mean f1': 0.9763025641441345, 'Val/mean precision': 0.9735013246536255, 'Val/mean recall': 0.9791199564933777, 'Val/mean hd95_metric': 4.617178440093994} +Cheakpoint... +Epoch [3809/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9752310514450073, 'Val/mean miou_metric': 0.9611395597457886, 'Val/mean f1': 0.9763025641441345, 'Val/mean precision': 0.9735013246536255, 'Val/mean recall': 0.9791199564933777, 'Val/mean hd95_metric': 4.617178440093994} +Epoch [3810/4000] Training [1/16] Loss: 0.00185 +Epoch [3810/4000] Training [2/16] Loss: 0.00180 +Epoch [3810/4000] Training [3/16] Loss: 0.00127 +Epoch [3810/4000] Training [4/16] Loss: 0.00184 +Epoch [3810/4000] Training [5/16] Loss: 0.00313 +Epoch [3810/4000] Training [6/16] Loss: 0.00275 +Epoch [3810/4000] Training [7/16] Loss: 0.00248 +Epoch [3810/4000] Training [8/16] Loss: 0.00229 +Epoch [3810/4000] Training [9/16] Loss: 0.00400 +Epoch [3810/4000] Training [10/16] Loss: 0.00320 +Epoch [3810/4000] Training [11/16] Loss: 0.00213 +Epoch [3810/4000] Training [12/16] Loss: 0.00193 +Epoch [3810/4000] Training [13/16] Loss: 0.00335 +Epoch [3810/4000] Training [14/16] Loss: 0.00262 +Epoch [3810/4000] Training [15/16] Loss: 0.00164 +Epoch [3810/4000] Training [16/16] Loss: 0.00276 +Epoch [3810/4000] Training metric {'Train/mean dice_metric': 0.9988002777099609, 'Train/mean miou_metric': 0.9973269701004028, 'Train/mean f1': 0.9937606453895569, 'Train/mean precision': 0.9891848564147949, 'Train/mean recall': 0.9983789920806885, 'Train/mean hd95_metric': 0.5101138353347778} +Epoch [3810/4000] Validation [1/4] Loss: 0.43400 focal_loss 0.36886 dice_loss 0.06514 +Epoch [3810/4000] Validation [2/4] Loss: 0.49840 focal_loss 0.36908 dice_loss 0.12932 +Epoch [3810/4000] Validation [3/4] Loss: 0.55552 focal_loss 0.45778 dice_loss 0.09774 +Epoch [3810/4000] Validation [4/4] Loss: 0.32457 focal_loss 0.22884 dice_loss 0.09573 +Epoch [3810/4000] Validation metric {'Val/mean dice_metric': 0.9747153520584106, 'Val/mean miou_metric': 0.9607574343681335, 'Val/mean f1': 0.9762429594993591, 'Val/mean precision': 0.9732109904289246, 'Val/mean recall': 0.9792940020561218, 'Val/mean hd95_metric': 4.804223537445068} +Cheakpoint... +Epoch [3810/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747153520584106, 'Val/mean miou_metric': 0.9607574343681335, 'Val/mean f1': 0.9762429594993591, 'Val/mean precision': 0.9732109904289246, 'Val/mean recall': 0.9792940020561218, 'Val/mean hd95_metric': 4.804223537445068} +Epoch [3811/4000] Training [1/16] Loss: 0.00164 +Epoch [3811/4000] Training [2/16] Loss: 0.00144 +Epoch [3811/4000] Training [3/16] Loss: 0.00321 +Epoch [3811/4000] Training [4/16] Loss: 0.00287 +Epoch [3811/4000] Training [5/16] Loss: 0.00219 +Epoch [3811/4000] Training [6/16] Loss: 0.00227 +Epoch [3811/4000] Training [7/16] Loss: 0.00218 +Epoch [3811/4000] Training [8/16] Loss: 0.00190 +Epoch [3811/4000] Training [9/16] Loss: 0.00146 +Epoch [3811/4000] Training [10/16] Loss: 0.00194 +Epoch [3811/4000] Training [11/16] Loss: 0.00272 +Epoch [3811/4000] Training [12/16] Loss: 0.00195 +Epoch [3811/4000] Training [13/16] Loss: 0.00366 +Epoch [3811/4000] Training [14/16] Loss: 0.00334 +Epoch [3811/4000] Training [15/16] Loss: 0.00440 +Epoch [3811/4000] Training [16/16] Loss: 0.00272 +Epoch [3811/4000] Training metric {'Train/mean dice_metric': 0.9987750053405762, 'Train/mean miou_metric': 0.9972749352455139, 'Train/mean f1': 0.9937865138053894, 'Train/mean precision': 0.9892447590827942, 'Train/mean recall': 0.9983701109886169, 'Train/mean hd95_metric': 0.538851261138916} +Epoch [3811/4000] Validation [1/4] Loss: 0.39585 focal_loss 0.33426 dice_loss 0.06159 +Epoch [3811/4000] Validation [2/4] Loss: 0.48155 focal_loss 0.36964 dice_loss 0.11192 +Epoch [3811/4000] Validation [3/4] Loss: 0.58668 focal_loss 0.48817 dice_loss 0.09851 +Epoch [3811/4000] Validation [4/4] Loss: 0.32681 focal_loss 0.23075 dice_loss 0.09605 +Epoch [3811/4000] Validation metric {'Val/mean dice_metric': 0.9748314619064331, 'Val/mean miou_metric': 0.9605803489685059, 'Val/mean f1': 0.9764444231987, 'Val/mean precision': 0.9736494421958923, 'Val/mean recall': 0.9792553782463074, 'Val/mean hd95_metric': 5.465638637542725} +Cheakpoint... +Epoch [3811/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748314619064331, 'Val/mean miou_metric': 0.9605803489685059, 'Val/mean f1': 0.9764444231987, 'Val/mean precision': 0.9736494421958923, 'Val/mean recall': 0.9792553782463074, 'Val/mean hd95_metric': 5.465638637542725} +Epoch [3812/4000] Training [1/16] Loss: 0.00225 +Epoch [3812/4000] Training [2/16] Loss: 0.00263 +Epoch [3812/4000] Training [3/16] Loss: 0.00197 +Epoch [3812/4000] Training [4/16] Loss: 0.00197 +Epoch [3812/4000] Training [5/16] Loss: 0.00187 +Epoch [3812/4000] Training [6/16] Loss: 0.00285 +Epoch [3812/4000] Training [7/16] Loss: 0.00268 +Epoch [3812/4000] Training [8/16] Loss: 0.00155 +Epoch [3812/4000] Training [9/16] Loss: 0.00222 +Epoch [3812/4000] Training [10/16] Loss: 0.00278 +Epoch [3812/4000] Training [11/16] Loss: 0.00187 +Epoch [3812/4000] Training [12/16] Loss: 0.00295 +Epoch [3812/4000] Training [13/16] Loss: 0.00253 +Epoch [3812/4000] Training [14/16] Loss: 0.00189 +Epoch [3812/4000] Training [15/16] Loss: 0.00289 +Epoch [3812/4000] Training [16/16] Loss: 0.00429 +Epoch [3812/4000] Training metric {'Train/mean dice_metric': 0.9986653327941895, 'Train/mean miou_metric': 0.9970604777336121, 'Train/mean f1': 0.9937043786048889, 'Train/mean precision': 0.9892117977142334, 'Train/mean recall': 0.9982379674911499, 'Train/mean hd95_metric': 0.5529143214225769} +Epoch [3812/4000] Validation [1/4] Loss: 0.36180 focal_loss 0.29932 dice_loss 0.06248 +Epoch [3812/4000] Validation [2/4] Loss: 0.61628 focal_loss 0.45787 dice_loss 0.15841 +Epoch [3812/4000] Validation [3/4] Loss: 0.53491 focal_loss 0.43440 dice_loss 0.10051 +Epoch [3812/4000] Validation [4/4] Loss: 0.33831 focal_loss 0.25518 dice_loss 0.08313 +Epoch [3812/4000] Validation metric {'Val/mean dice_metric': 0.9755536913871765, 'Val/mean miou_metric': 0.9613246917724609, 'Val/mean f1': 0.9762676954269409, 'Val/mean precision': 0.9741385579109192, 'Val/mean recall': 0.9784061312675476, 'Val/mean hd95_metric': 4.799936294555664} +Cheakpoint... +Epoch [3812/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755536913871765, 'Val/mean miou_metric': 0.9613246917724609, 'Val/mean f1': 0.9762676954269409, 'Val/mean precision': 0.9741385579109192, 'Val/mean recall': 0.9784061312675476, 'Val/mean hd95_metric': 4.799936294555664} +Epoch [3813/4000] Training [1/16] Loss: 0.00229 +Epoch [3813/4000] Training [2/16] Loss: 0.00226 +Epoch [3813/4000] Training [3/16] Loss: 0.00244 +Epoch [3813/4000] Training [4/16] Loss: 0.00215 +Epoch [3813/4000] Training [5/16] Loss: 0.00184 +Epoch [3813/4000] Training [6/16] Loss: 0.00212 +Epoch [3813/4000] Training [7/16] Loss: 0.00175 +Epoch [3813/4000] Training [8/16] Loss: 0.00173 +Epoch [3813/4000] Training [9/16] Loss: 0.00346 +Epoch [3813/4000] Training [10/16] Loss: 0.00527 +Epoch [3813/4000] Training [11/16] Loss: 0.00205 +Epoch [3813/4000] Training [12/16] Loss: 0.00198 +Epoch [3813/4000] Training [13/16] Loss: 0.00152 +Epoch [3813/4000] Training [14/16] Loss: 0.00264 +Epoch [3813/4000] Training [15/16] Loss: 0.00208 +Epoch [3813/4000] Training [16/16] Loss: 0.00275 +Epoch [3813/4000] Training metric {'Train/mean dice_metric': 0.9987565279006958, 'Train/mean miou_metric': 0.9972149133682251, 'Train/mean f1': 0.9931222796440125, 'Train/mean precision': 0.9879851341247559, 'Train/mean recall': 0.9983131289482117, 'Train/mean hd95_metric': 0.505203366279602} +Epoch [3813/4000] Validation [1/4] Loss: 0.41737 focal_loss 0.35261 dice_loss 0.06477 +Epoch [3813/4000] Validation [2/4] Loss: 0.48567 focal_loss 0.37378 dice_loss 0.11188 +Epoch [3813/4000] Validation [3/4] Loss: 0.57364 focal_loss 0.47320 dice_loss 0.10043 +Epoch [3813/4000] Validation [4/4] Loss: 0.31748 focal_loss 0.22545 dice_loss 0.09203 +Epoch [3813/4000] Validation metric {'Val/mean dice_metric': 0.9739284515380859, 'Val/mean miou_metric': 0.9598894119262695, 'Val/mean f1': 0.9755985736846924, 'Val/mean precision': 0.9732313752174377, 'Val/mean recall': 0.9779772758483887, 'Val/mean hd95_metric': 4.821683406829834} +Cheakpoint... +Epoch [3813/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739284515380859, 'Val/mean miou_metric': 0.9598894119262695, 'Val/mean f1': 0.9755985736846924, 'Val/mean precision': 0.9732313752174377, 'Val/mean recall': 0.9779772758483887, 'Val/mean hd95_metric': 4.821683406829834} +Epoch [3814/4000] Training [1/16] Loss: 0.00306 +Epoch [3814/4000] Training [2/16] Loss: 0.00289 +Epoch [3814/4000] Training [3/16] Loss: 0.00644 +Epoch [3814/4000] Training [4/16] Loss: 0.00279 +Epoch [3814/4000] Training [5/16] Loss: 0.00182 +Epoch [3814/4000] Training [6/16] Loss: 0.00227 +Epoch [3814/4000] Training [7/16] Loss: 0.00270 +Epoch [3814/4000] Training [8/16] Loss: 0.00223 +Epoch [3814/4000] Training [9/16] Loss: 0.00191 +Epoch [3814/4000] Training [10/16] Loss: 0.00405 +Epoch [3814/4000] Training [11/16] Loss: 0.00196 +Epoch [3814/4000] Training [12/16] Loss: 0.00170 +Epoch [3814/4000] Training [13/16] Loss: 0.00146 +Epoch [3814/4000] Training [14/16] Loss: 0.00202 +Epoch [3814/4000] Training [15/16] Loss: 0.00227 +Epoch [3814/4000] Training [16/16] Loss: 0.00206 +Epoch [3814/4000] Training metric {'Train/mean dice_metric': 0.9986934661865234, 'Train/mean miou_metric': 0.9970940351486206, 'Train/mean f1': 0.9935659170150757, 'Train/mean precision': 0.9888533353805542, 'Train/mean recall': 0.9983235597610474, 'Train/mean hd95_metric': 0.8241646885871887} +Epoch [3814/4000] Validation [1/4] Loss: 0.41135 focal_loss 0.34653 dice_loss 0.06483 +Epoch [3814/4000] Validation [2/4] Loss: 0.46078 focal_loss 0.35480 dice_loss 0.10598 +Epoch [3814/4000] Validation [3/4] Loss: 0.25297 focal_loss 0.19468 dice_loss 0.05829 +Epoch [3814/4000] Validation [4/4] Loss: 0.35855 focal_loss 0.26795 dice_loss 0.09060 +Epoch [3814/4000] Validation metric {'Val/mean dice_metric': 0.9748546481132507, 'Val/mean miou_metric': 0.9608429074287415, 'Val/mean f1': 0.9764819145202637, 'Val/mean precision': 0.9745381474494934, 'Val/mean recall': 0.9784334897994995, 'Val/mean hd95_metric': 4.862630844116211} +Cheakpoint... +Epoch [3814/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748546481132507, 'Val/mean miou_metric': 0.9608429074287415, 'Val/mean f1': 0.9764819145202637, 'Val/mean precision': 0.9745381474494934, 'Val/mean recall': 0.9784334897994995, 'Val/mean hd95_metric': 4.862630844116211} +Epoch [3815/4000] Training [1/16] Loss: 0.00204 +Epoch [3815/4000] Training [2/16] Loss: 0.00189 +Epoch [3815/4000] Training [3/16] Loss: 0.00190 +Epoch [3815/4000] Training [4/16] Loss: 0.00389 +Epoch [3815/4000] Training [5/16] Loss: 0.00198 +Epoch [3815/4000] Training [6/16] Loss: 0.00189 +Epoch [3815/4000] Training [7/16] Loss: 0.00215 +Epoch [3815/4000] Training [8/16] Loss: 0.00227 +Epoch [3815/4000] Training [9/16] Loss: 0.00279 +Epoch [3815/4000] Training [10/16] Loss: 0.00216 +Epoch [3815/4000] Training [11/16] Loss: 0.00227 +Epoch [3815/4000] Training [12/16] Loss: 0.00201 +Epoch [3815/4000] Training [13/16] Loss: 0.00239 +Epoch [3815/4000] Training [14/16] Loss: 0.00393 +Epoch [3815/4000] Training [15/16] Loss: 0.00164 +Epoch [3815/4000] Training [16/16] Loss: 0.00348 +Epoch [3815/4000] Training metric {'Train/mean dice_metric': 0.9987503886222839, 'Train/mean miou_metric': 0.9972320199012756, 'Train/mean f1': 0.993907630443573, 'Train/mean precision': 0.9894635677337646, 'Train/mean recall': 0.9983918070793152, 'Train/mean hd95_metric': 0.514732301235199} +Epoch [3815/4000] Validation [1/4] Loss: 0.37173 focal_loss 0.30865 dice_loss 0.06309 +Epoch [3815/4000] Validation [2/4] Loss: 0.51556 focal_loss 0.39176 dice_loss 0.12380 +Epoch [3815/4000] Validation [3/4] Loss: 0.55889 focal_loss 0.45806 dice_loss 0.10083 +Epoch [3815/4000] Validation [4/4] Loss: 0.37314 focal_loss 0.28073 dice_loss 0.09241 +Epoch [3815/4000] Validation metric {'Val/mean dice_metric': 0.9747344851493835, 'Val/mean miou_metric': 0.9607735872268677, 'Val/mean f1': 0.976341187953949, 'Val/mean precision': 0.973330020904541, 'Val/mean recall': 0.9793709516525269, 'Val/mean hd95_metric': 5.1079230308532715} +Cheakpoint... +Epoch [3815/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747344851493835, 'Val/mean miou_metric': 0.9607735872268677, 'Val/mean f1': 0.976341187953949, 'Val/mean precision': 0.973330020904541, 'Val/mean recall': 0.9793709516525269, 'Val/mean hd95_metric': 5.1079230308532715} +Epoch [3816/4000] Training [1/16] Loss: 0.00181 +Epoch [3816/4000] Training [2/16] Loss: 0.00172 +Epoch [3816/4000] Training [3/16] Loss: 0.00189 +Epoch [3816/4000] Training [4/16] Loss: 0.00186 +Epoch [3816/4000] Training [5/16] Loss: 0.00204 +Epoch [3816/4000] Training [6/16] Loss: 0.00234 +Epoch [3816/4000] Training [7/16] Loss: 0.00282 +Epoch [3816/4000] Training [8/16] Loss: 0.00241 +Epoch [3816/4000] Training [9/16] Loss: 0.00208 +Epoch [3816/4000] Training [10/16] Loss: 0.00346 +Epoch [3816/4000] Training [11/16] Loss: 0.00231 +Epoch [3816/4000] Training [12/16] Loss: 0.00211 +Epoch [3816/4000] Training [13/16] Loss: 0.00300 +Epoch [3816/4000] Training [14/16] Loss: 0.00293 +Epoch [3816/4000] Training [15/16] Loss: 0.00295 +Epoch [3816/4000] Training [16/16] Loss: 0.00234 +Epoch [3816/4000] Training metric {'Train/mean dice_metric': 0.9988716840744019, 'Train/mean miou_metric': 0.997469961643219, 'Train/mean f1': 0.9939224720001221, 'Train/mean precision': 0.9894460439682007, 'Train/mean recall': 0.998439610004425, 'Train/mean hd95_metric': 0.526687741279602} +Epoch [3816/4000] Validation [1/4] Loss: 0.39666 focal_loss 0.33304 dice_loss 0.06362 +Epoch [3816/4000] Validation [2/4] Loss: 1.06854 focal_loss 0.81281 dice_loss 0.25572 +Epoch [3816/4000] Validation [3/4] Loss: 0.51392 focal_loss 0.42127 dice_loss 0.09265 +Epoch [3816/4000] Validation [4/4] Loss: 0.40589 focal_loss 0.30066 dice_loss 0.10523 +Epoch [3816/4000] Validation metric {'Val/mean dice_metric': 0.9721500277519226, 'Val/mean miou_metric': 0.9581279754638672, 'Val/mean f1': 0.9758104681968689, 'Val/mean precision': 0.9740484356880188, 'Val/mean recall': 0.97757887840271, 'Val/mean hd95_metric': 5.00203275680542} +Cheakpoint... +Epoch [3816/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9722], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9721500277519226, 'Val/mean miou_metric': 0.9581279754638672, 'Val/mean f1': 0.9758104681968689, 'Val/mean precision': 0.9740484356880188, 'Val/mean recall': 0.97757887840271, 'Val/mean hd95_metric': 5.00203275680542} +Epoch [3817/4000] Training [1/16] Loss: 0.00311 +Epoch [3817/4000] Training [2/16] Loss: 0.00227 +Epoch [3817/4000] Training [3/16] Loss: 0.00365 +Epoch [3817/4000] Training [4/16] Loss: 0.00344 +Epoch [3817/4000] Training [5/16] Loss: 0.00317 +Epoch [3817/4000] Training [6/16] Loss: 0.00302 +Epoch [3817/4000] Training [7/16] Loss: 0.00272 +Epoch [3817/4000] Training [8/16] Loss: 0.00190 +Epoch [3817/4000] Training [9/16] Loss: 0.00179 +Epoch [3817/4000] Training [10/16] Loss: 0.00245 +Epoch [3817/4000] Training [11/16] Loss: 0.00231 +Epoch [3817/4000] Training [12/16] Loss: 0.00178 +Epoch [3817/4000] Training [13/16] Loss: 0.00347 +Epoch [3817/4000] Training [14/16] Loss: 0.00236 +Epoch [3817/4000] Training [15/16] Loss: 0.00249 +Epoch [3817/4000] Training [16/16] Loss: 0.00170 +Epoch [3817/4000] Training metric {'Train/mean dice_metric': 0.9987061023712158, 'Train/mean miou_metric': 0.9971168041229248, 'Train/mean f1': 0.9933961629867554, 'Train/mean precision': 0.9885765910148621, 'Train/mean recall': 0.9982628226280212, 'Train/mean hd95_metric': 0.5267853140830994} +Epoch [3817/4000] Validation [1/4] Loss: 0.38629 focal_loss 0.32351 dice_loss 0.06279 +Epoch [3817/4000] Validation [2/4] Loss: 0.63270 focal_loss 0.47205 dice_loss 0.16065 +Epoch [3817/4000] Validation [3/4] Loss: 0.52450 focal_loss 0.43409 dice_loss 0.09040 +Epoch [3817/4000] Validation [4/4] Loss: 0.53644 focal_loss 0.41183 dice_loss 0.12462 +Epoch [3817/4000] Validation metric {'Val/mean dice_metric': 0.9734178781509399, 'Val/mean miou_metric': 0.9594526290893555, 'Val/mean f1': 0.9755082726478577, 'Val/mean precision': 0.9733861684799194, 'Val/mean recall': 0.9776396751403809, 'Val/mean hd95_metric': 5.161077976226807} +Cheakpoint... +Epoch [3817/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734178781509399, 'Val/mean miou_metric': 0.9594526290893555, 'Val/mean f1': 0.9755082726478577, 'Val/mean precision': 0.9733861684799194, 'Val/mean recall': 0.9776396751403809, 'Val/mean hd95_metric': 5.161077976226807} +Epoch [3818/4000] Training [1/16] Loss: 0.00197 +Epoch [3818/4000] Training [2/16] Loss: 0.00313 +Epoch [3818/4000] Training [3/16] Loss: 0.00215 +Epoch [3818/4000] Training [4/16] Loss: 0.00261 +Epoch [3818/4000] Training [5/16] Loss: 0.00219 +Epoch [3818/4000] Training [6/16] Loss: 0.00204 +Epoch [3818/4000] Training [7/16] Loss: 0.00200 +Epoch [3818/4000] Training [8/16] Loss: 0.00164 +Epoch [3818/4000] Training [9/16] Loss: 0.00219 +Epoch [3818/4000] Training [10/16] Loss: 0.00289 +Epoch [3818/4000] Training [11/16] Loss: 0.00428 +Epoch [3818/4000] Training [12/16] Loss: 0.00159 +Epoch [3818/4000] Training [13/16] Loss: 0.00188 +Epoch [3818/4000] Training [14/16] Loss: 0.00236 +Epoch [3818/4000] Training [15/16] Loss: 0.00252 +Epoch [3818/4000] Training [16/16] Loss: 0.00215 +Epoch [3818/4000] Training metric {'Train/mean dice_metric': 0.9987914562225342, 'Train/mean miou_metric': 0.9973107576370239, 'Train/mean f1': 0.9938839673995972, 'Train/mean precision': 0.9893825650215149, 'Train/mean recall': 0.9984265565872192, 'Train/mean hd95_metric': 0.5133088827133179} +Epoch [3818/4000] Validation [1/4] Loss: 0.40800 focal_loss 0.34675 dice_loss 0.06125 +Epoch [3818/4000] Validation [2/4] Loss: 0.48217 focal_loss 0.37265 dice_loss 0.10953 +Epoch [3818/4000] Validation [3/4] Loss: 0.53395 focal_loss 0.44311 dice_loss 0.09083 +Epoch [3818/4000] Validation [4/4] Loss: 0.41350 focal_loss 0.30626 dice_loss 0.10724 +Epoch [3818/4000] Validation metric {'Val/mean dice_metric': 0.9755048751831055, 'Val/mean miou_metric': 0.9613170623779297, 'Val/mean f1': 0.976807177066803, 'Val/mean precision': 0.9744935631752014, 'Val/mean recall': 0.9791317582130432, 'Val/mean hd95_metric': 4.688722133636475} +Cheakpoint... +Epoch [3818/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755048751831055, 'Val/mean miou_metric': 0.9613170623779297, 'Val/mean f1': 0.976807177066803, 'Val/mean precision': 0.9744935631752014, 'Val/mean recall': 0.9791317582130432, 'Val/mean hd95_metric': 4.688722133636475} +Epoch [3819/4000] Training [1/16] Loss: 0.00271 +Epoch [3819/4000] Training [2/16] Loss: 0.00236 +Epoch [3819/4000] Training [3/16] Loss: 0.00252 +Epoch [3819/4000] Training [4/16] Loss: 0.00147 +Epoch [3819/4000] Training [5/16] Loss: 0.00284 +Epoch [3819/4000] Training [6/16] Loss: 0.00200 +Epoch [3819/4000] Training [7/16] Loss: 0.00300 +Epoch [3819/4000] Training [8/16] Loss: 0.00196 +Epoch [3819/4000] Training [9/16] Loss: 0.00305 +Epoch [3819/4000] Training [10/16] Loss: 0.00210 +Epoch [3819/4000] Training [11/16] Loss: 0.00224 +Epoch [3819/4000] Training [12/16] Loss: 0.00215 +Epoch [3819/4000] Training [13/16] Loss: 0.00239 +Epoch [3819/4000] Training [14/16] Loss: 0.00234 +Epoch [3819/4000] Training [15/16] Loss: 0.00167 +Epoch [3819/4000] Training [16/16] Loss: 0.00347 +Epoch [3819/4000] Training metric {'Train/mean dice_metric': 0.9989105463027954, 'Train/mean miou_metric': 0.9975472688674927, 'Train/mean f1': 0.9938992261886597, 'Train/mean precision': 0.9893442988395691, 'Train/mean recall': 0.9984962940216064, 'Train/mean hd95_metric': 0.49846500158309937} +Epoch [3819/4000] Validation [1/4] Loss: 0.42316 focal_loss 0.35772 dice_loss 0.06544 +Epoch [3819/4000] Validation [2/4] Loss: 0.97561 focal_loss 0.78774 dice_loss 0.18788 +Epoch [3819/4000] Validation [3/4] Loss: 0.53875 focal_loss 0.44547 dice_loss 0.09329 +Epoch [3819/4000] Validation [4/4] Loss: 0.41941 focal_loss 0.30945 dice_loss 0.10996 +Epoch [3819/4000] Validation metric {'Val/mean dice_metric': 0.9735711812973022, 'Val/mean miou_metric': 0.9599533081054688, 'Val/mean f1': 0.9759402871131897, 'Val/mean precision': 0.9742164611816406, 'Val/mean recall': 0.9776702523231506, 'Val/mean hd95_metric': 4.914982318878174} +Cheakpoint... +Epoch [3819/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735711812973022, 'Val/mean miou_metric': 0.9599533081054688, 'Val/mean f1': 0.9759402871131897, 'Val/mean precision': 0.9742164611816406, 'Val/mean recall': 0.9776702523231506, 'Val/mean hd95_metric': 4.914982318878174} +Epoch [3820/4000] Training [1/16] Loss: 0.00282 +Epoch [3820/4000] Training [2/16] Loss: 0.00212 +Epoch [3820/4000] Training [3/16] Loss: 0.00196 +Epoch [3820/4000] Training [4/16] Loss: 0.00394 +Epoch [3820/4000] Training [5/16] Loss: 0.00197 +Epoch [3820/4000] Training [6/16] Loss: 0.00255 +Epoch [3820/4000] Training [7/16] Loss: 0.00197 +Epoch [3820/4000] Training [8/16] Loss: 0.00227 +Epoch [3820/4000] Training [9/16] Loss: 0.00406 +Epoch [3820/4000] Training [10/16] Loss: 0.00162 +Epoch [3820/4000] Training [11/16] Loss: 0.00244 +Epoch [3820/4000] Training [12/16] Loss: 0.00321 +Epoch [3820/4000] Training [13/16] Loss: 0.00201 +Epoch [3820/4000] Training [14/16] Loss: 0.00223 +Epoch [3820/4000] Training [15/16] Loss: 0.00230 +Epoch [3820/4000] Training [16/16] Loss: 0.00307 +Epoch [3820/4000] Training metric {'Train/mean dice_metric': 0.9987125992774963, 'Train/mean miou_metric': 0.9971418976783752, 'Train/mean f1': 0.9936226010322571, 'Train/mean precision': 0.9889827966690063, 'Train/mean recall': 0.998306155204773, 'Train/mean hd95_metric': 0.4994693696498871} +Epoch [3820/4000] Validation [1/4] Loss: 0.44963 focal_loss 0.38283 dice_loss 0.06680 +Epoch [3820/4000] Validation [2/4] Loss: 0.48087 focal_loss 0.37087 dice_loss 0.11001 +Epoch [3820/4000] Validation [3/4] Loss: 0.57468 focal_loss 0.48007 dice_loss 0.09461 +Epoch [3820/4000] Validation [4/4] Loss: 0.36535 focal_loss 0.27661 dice_loss 0.08875 +Epoch [3820/4000] Validation metric {'Val/mean dice_metric': 0.9748023152351379, 'Val/mean miou_metric': 0.9605388641357422, 'Val/mean f1': 0.9760861992835999, 'Val/mean precision': 0.9737549424171448, 'Val/mean recall': 0.9784284234046936, 'Val/mean hd95_metric': 5.167320728302002} +Cheakpoint... +Epoch [3820/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748023152351379, 'Val/mean miou_metric': 0.9605388641357422, 'Val/mean f1': 0.9760861992835999, 'Val/mean precision': 0.9737549424171448, 'Val/mean recall': 0.9784284234046936, 'Val/mean hd95_metric': 5.167320728302002} +Epoch [3821/4000] Training [1/16] Loss: 0.00195 +Epoch [3821/4000] Training [2/16] Loss: 0.00287 +Epoch [3821/4000] Training [3/16] Loss: 0.00241 +Epoch [3821/4000] Training [4/16] Loss: 0.00265 +Epoch [3821/4000] Training [5/16] Loss: 0.00271 +Epoch [3821/4000] Training [6/16] Loss: 0.00206 +Epoch [3821/4000] Training [7/16] Loss: 0.00195 +Epoch [3821/4000] Training [8/16] Loss: 0.00157 +Epoch [3821/4000] Training [9/16] Loss: 0.00450 +Epoch [3821/4000] Training [10/16] Loss: 0.00222 +Epoch [3821/4000] Training [11/16] Loss: 0.00229 +Epoch [3821/4000] Training [12/16] Loss: 0.00164 +Epoch [3821/4000] Training [13/16] Loss: 0.00237 +Epoch [3821/4000] Training [14/16] Loss: 0.00263 +Epoch [3821/4000] Training [15/16] Loss: 0.00242 +Epoch [3821/4000] Training [16/16] Loss: 0.00202 +Epoch [3821/4000] Training metric {'Train/mean dice_metric': 0.9988606572151184, 'Train/mean miou_metric': 0.9974436163902283, 'Train/mean f1': 0.9937752485275269, 'Train/mean precision': 0.9892320036888123, 'Train/mean recall': 0.9983603954315186, 'Train/mean hd95_metric': 0.5094729661941528} +Epoch [3821/4000] Validation [1/4] Loss: 0.41994 focal_loss 0.35447 dice_loss 0.06547 +Epoch [3821/4000] Validation [2/4] Loss: 0.51628 focal_loss 0.38672 dice_loss 0.12956 +Epoch [3821/4000] Validation [3/4] Loss: 0.53087 focal_loss 0.44292 dice_loss 0.08796 +Epoch [3821/4000] Validation [4/4] Loss: 0.42785 focal_loss 0.32073 dice_loss 0.10712 +Epoch [3821/4000] Validation metric {'Val/mean dice_metric': 0.97540682554245, 'Val/mean miou_metric': 0.9611765146255493, 'Val/mean f1': 0.976955235004425, 'Val/mean precision': 0.9740994572639465, 'Val/mean recall': 0.9798277020454407, 'Val/mean hd95_metric': 4.804290771484375} +Cheakpoint... +Epoch [3821/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97540682554245, 'Val/mean miou_metric': 0.9611765146255493, 'Val/mean f1': 0.976955235004425, 'Val/mean precision': 0.9740994572639465, 'Val/mean recall': 0.9798277020454407, 'Val/mean hd95_metric': 4.804290771484375} +Epoch [3822/4000] Training [1/16] Loss: 0.00338 +Epoch [3822/4000] Training [2/16] Loss: 0.00208 +Epoch [3822/4000] Training [3/16] Loss: 0.00180 +Epoch [3822/4000] Training [4/16] Loss: 0.00181 +Epoch [3822/4000] Training [5/16] Loss: 0.00262 +Epoch [3822/4000] Training [6/16] Loss: 0.00273 +Epoch [3822/4000] Training [7/16] Loss: 0.00360 +Epoch [3822/4000] Training [8/16] Loss: 0.00304 +Epoch [3822/4000] Training [9/16] Loss: 0.00191 +Epoch [3822/4000] Training [10/16] Loss: 0.00298 +Epoch [3822/4000] Training [11/16] Loss: 0.00388 +Epoch [3822/4000] Training [12/16] Loss: 0.00213 +Epoch [3822/4000] Training [13/16] Loss: 0.00396 +Epoch [3822/4000] Training [14/16] Loss: 0.00181 +Epoch [3822/4000] Training [15/16] Loss: 0.00385 +Epoch [3822/4000] Training [16/16] Loss: 0.00198 +Epoch [3822/4000] Training metric {'Train/mean dice_metric': 0.9987750053405762, 'Train/mean miou_metric': 0.9972468018531799, 'Train/mean f1': 0.9931743144989014, 'Train/mean precision': 0.9881721138954163, 'Train/mean recall': 0.9982273578643799, 'Train/mean hd95_metric': 0.5267322063446045} +Epoch [3822/4000] Validation [1/4] Loss: 0.45612 focal_loss 0.39228 dice_loss 0.06384 +Epoch [3822/4000] Validation [2/4] Loss: 0.45700 focal_loss 0.34960 dice_loss 0.10739 +Epoch [3822/4000] Validation [3/4] Loss: 0.54202 focal_loss 0.44629 dice_loss 0.09573 +Epoch [3822/4000] Validation [4/4] Loss: 0.40957 focal_loss 0.30074 dice_loss 0.10883 +Epoch [3822/4000] Validation metric {'Val/mean dice_metric': 0.9748153686523438, 'Val/mean miou_metric': 0.9606450200080872, 'Val/mean f1': 0.9757368564605713, 'Val/mean precision': 0.9725161790847778, 'Val/mean recall': 0.9789787530899048, 'Val/mean hd95_metric': 5.04783296585083} +Cheakpoint... +Epoch [3822/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748153686523438, 'Val/mean miou_metric': 0.9606450200080872, 'Val/mean f1': 0.9757368564605713, 'Val/mean precision': 0.9725161790847778, 'Val/mean recall': 0.9789787530899048, 'Val/mean hd95_metric': 5.04783296585083} +Epoch [3823/4000] Training [1/16] Loss: 0.00177 +Epoch [3823/4000] Training [2/16] Loss: 0.00221 +Epoch [3823/4000] Training [3/16] Loss: 0.00289 +Epoch [3823/4000] Training [4/16] Loss: 0.00256 +Epoch [3823/4000] Training [5/16] Loss: 0.00253 +Epoch [3823/4000] Training [6/16] Loss: 0.00166 +Epoch [3823/4000] Training [7/16] Loss: 0.00288 +Epoch [3823/4000] Training [8/16] Loss: 0.00266 +Epoch [3823/4000] Training [9/16] Loss: 0.00225 +Epoch [3823/4000] Training [10/16] Loss: 0.00249 +Epoch [3823/4000] Training [11/16] Loss: 0.00218 +Epoch [3823/4000] Training [12/16] Loss: 0.00215 +Epoch [3823/4000] Training [13/16] Loss: 0.00232 +Epoch [3823/4000] Training [14/16] Loss: 0.00238 +Epoch [3823/4000] Training [15/16] Loss: 0.00258 +Epoch [3823/4000] Training [16/16] Loss: 0.00343 +Epoch [3823/4000] Training metric {'Train/mean dice_metric': 0.9988085031509399, 'Train/mean miou_metric': 0.9973347783088684, 'Train/mean f1': 0.9937329888343811, 'Train/mean precision': 0.9890944957733154, 'Train/mean recall': 0.9984151124954224, 'Train/mean hd95_metric': 0.53830885887146} +Epoch [3823/4000] Validation [1/4] Loss: 0.40096 focal_loss 0.34062 dice_loss 0.06034 +Epoch [3823/4000] Validation [2/4] Loss: 0.48370 focal_loss 0.37226 dice_loss 0.11144 +Epoch [3823/4000] Validation [3/4] Loss: 0.51045 focal_loss 0.42298 dice_loss 0.08746 +Epoch [3823/4000] Validation [4/4] Loss: 0.31143 focal_loss 0.21864 dice_loss 0.09280 +Epoch [3823/4000] Validation metric {'Val/mean dice_metric': 0.9740579724311829, 'Val/mean miou_metric': 0.960513710975647, 'Val/mean f1': 0.9770328402519226, 'Val/mean precision': 0.9746407270431519, 'Val/mean recall': 0.9794368147850037, 'Val/mean hd95_metric': 4.649101734161377} +Cheakpoint... +Epoch [3823/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740579724311829, 'Val/mean miou_metric': 0.960513710975647, 'Val/mean f1': 0.9770328402519226, 'Val/mean precision': 0.9746407270431519, 'Val/mean recall': 0.9794368147850037, 'Val/mean hd95_metric': 4.649101734161377} +Epoch [3824/4000] Training [1/16] Loss: 0.00231 +Epoch [3824/4000] Training [2/16] Loss: 0.00167 +Epoch [3824/4000] Training [3/16] Loss: 0.00296 +Epoch [3824/4000] Training [4/16] Loss: 0.00189 +Epoch [3824/4000] Training [5/16] Loss: 0.00189 +Epoch [3824/4000] Training [6/16] Loss: 0.00189 +Epoch [3824/4000] Training [7/16] Loss: 0.00244 +Epoch [3824/4000] Training [8/16] Loss: 0.00261 +Epoch [3824/4000] Training [9/16] Loss: 0.00267 +Epoch [3824/4000] Training [10/16] Loss: 0.00357 +Epoch [3824/4000] Training [11/16] Loss: 0.00155 +Epoch [3824/4000] Training [12/16] Loss: 0.00206 +Epoch [3824/4000] Training [13/16] Loss: 0.00444 +Epoch [3824/4000] Training [14/16] Loss: 0.00189 +Epoch [3824/4000] Training [15/16] Loss: 0.00150 +Epoch [3824/4000] Training [16/16] Loss: 0.00187 +Epoch [3824/4000] Training metric {'Train/mean dice_metric': 0.9988434314727783, 'Train/mean miou_metric': 0.9973746538162231, 'Train/mean f1': 0.9930248856544495, 'Train/mean precision': 0.9877243638038635, 'Train/mean recall': 0.998382568359375, 'Train/mean hd95_metric': 0.4983178377151489} +Epoch [3824/4000] Validation [1/4] Loss: 0.42621 focal_loss 0.36254 dice_loss 0.06367 +Epoch [3824/4000] Validation [2/4] Loss: 0.47476 focal_loss 0.36637 dice_loss 0.10839 +Epoch [3824/4000] Validation [3/4] Loss: 0.55603 focal_loss 0.45233 dice_loss 0.10370 +Epoch [3824/4000] Validation [4/4] Loss: 0.46461 focal_loss 0.35427 dice_loss 0.11034 +Epoch [3824/4000] Validation metric {'Val/mean dice_metric': 0.9746279716491699, 'Val/mean miou_metric': 0.9604060053825378, 'Val/mean f1': 0.975652277469635, 'Val/mean precision': 0.9722164869308472, 'Val/mean recall': 0.9791125059127808, 'Val/mean hd95_metric': 5.355973720550537} +Cheakpoint... +Epoch [3824/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746279716491699, 'Val/mean miou_metric': 0.9604060053825378, 'Val/mean f1': 0.975652277469635, 'Val/mean precision': 0.9722164869308472, 'Val/mean recall': 0.9791125059127808, 'Val/mean hd95_metric': 5.355973720550537} +Epoch [3825/4000] Training [1/16] Loss: 0.00212 +Epoch [3825/4000] Training [2/16] Loss: 0.00204 +Epoch [3825/4000] Training [3/16] Loss: 0.00174 +Epoch [3825/4000] Training [4/16] Loss: 0.00231 +Epoch [3825/4000] Training [5/16] Loss: 0.00229 +Epoch [3825/4000] Training [6/16] Loss: 0.00242 +Epoch [3825/4000] Training [7/16] Loss: 0.00389 +Epoch [3825/4000] Training [8/16] Loss: 0.00341 +Epoch [3825/4000] Training [9/16] Loss: 0.00162 +Epoch [3825/4000] Training [10/16] Loss: 0.00225 +Epoch [3825/4000] Training [11/16] Loss: 0.00306 +Epoch [3825/4000] Training [12/16] Loss: 0.00191 +Epoch [3825/4000] Training [13/16] Loss: 0.00252 +Epoch [3825/4000] Training [14/16] Loss: 0.00231 +Epoch [3825/4000] Training [15/16] Loss: 0.00219 +Epoch [3825/4000] Training [16/16] Loss: 0.00238 +Epoch [3825/4000] Training metric {'Train/mean dice_metric': 0.9987075924873352, 'Train/mean miou_metric': 0.9971420168876648, 'Train/mean f1': 0.9938898086547852, 'Train/mean precision': 0.989437997341156, 'Train/mean recall': 0.9983818531036377, 'Train/mean hd95_metric': 0.5522736310958862} +Epoch [3825/4000] Validation [1/4] Loss: 0.40845 focal_loss 0.34376 dice_loss 0.06469 +Epoch [3825/4000] Validation [2/4] Loss: 0.48148 focal_loss 0.36978 dice_loss 0.11170 +Epoch [3825/4000] Validation [3/4] Loss: 0.54472 focal_loss 0.45299 dice_loss 0.09173 +Epoch [3825/4000] Validation [4/4] Loss: 0.51094 focal_loss 0.39785 dice_loss 0.11309 +Epoch [3825/4000] Validation metric {'Val/mean dice_metric': 0.9760887026786804, 'Val/mean miou_metric': 0.9613731503486633, 'Val/mean f1': 0.9766561985015869, 'Val/mean precision': 0.9742574095726013, 'Val/mean recall': 0.9790668487548828, 'Val/mean hd95_metric': 4.84207010269165} +Cheakpoint... +Epoch [3825/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9761], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9760887026786804, 'Val/mean miou_metric': 0.9613731503486633, 'Val/mean f1': 0.9766561985015869, 'Val/mean precision': 0.9742574095726013, 'Val/mean recall': 0.9790668487548828, 'Val/mean hd95_metric': 4.84207010269165} +Epoch [3826/4000] Training [1/16] Loss: 0.00182 +Epoch [3826/4000] Training [2/16] Loss: 0.00219 +Epoch [3826/4000] Training [3/16] Loss: 0.00408 +Epoch [3826/4000] Training [4/16] Loss: 0.00195 +Epoch [3826/4000] Training [5/16] Loss: 0.00190 +Epoch [3826/4000] Training [6/16] Loss: 0.00190 +Epoch [3826/4000] Training [7/16] Loss: 0.00157 +Epoch [3826/4000] Training [8/16] Loss: 0.00293 +Epoch [3826/4000] Training [9/16] Loss: 0.00208 +Epoch [3826/4000] Training [10/16] Loss: 0.00212 +Epoch [3826/4000] Training [11/16] Loss: 0.00235 +Epoch [3826/4000] Training [12/16] Loss: 0.00342 +Epoch [3826/4000] Training [13/16] Loss: 0.00276 +Epoch [3826/4000] Training [14/16] Loss: 0.00318 +Epoch [3826/4000] Training [15/16] Loss: 0.00181 +Epoch [3826/4000] Training [16/16] Loss: 0.00207 +Epoch [3826/4000] Training metric {'Train/mean dice_metric': 0.9987660050392151, 'Train/mean miou_metric': 0.9972567558288574, 'Train/mean f1': 0.9938251376152039, 'Train/mean precision': 0.9893580675125122, 'Train/mean recall': 0.998332679271698, 'Train/mean hd95_metric': 0.5338165163993835} +Epoch [3826/4000] Validation [1/4] Loss: 0.36627 focal_loss 0.30570 dice_loss 0.06057 +Epoch [3826/4000] Validation [2/4] Loss: 1.24212 focal_loss 0.96076 dice_loss 0.28136 +Epoch [3826/4000] Validation [3/4] Loss: 0.54041 focal_loss 0.44562 dice_loss 0.09479 +Epoch [3826/4000] Validation [4/4] Loss: 0.39662 focal_loss 0.28830 dice_loss 0.10831 +Epoch [3826/4000] Validation metric {'Val/mean dice_metric': 0.9728808403015137, 'Val/mean miou_metric': 0.9591679573059082, 'Val/mean f1': 0.975822925567627, 'Val/mean precision': 0.9730138182640076, 'Val/mean recall': 0.9786480665206909, 'Val/mean hd95_metric': 5.302567005157471} +Cheakpoint... +Epoch [3826/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728808403015137, 'Val/mean miou_metric': 0.9591679573059082, 'Val/mean f1': 0.975822925567627, 'Val/mean precision': 0.9730138182640076, 'Val/mean recall': 0.9786480665206909, 'Val/mean hd95_metric': 5.302567005157471} +Epoch [3827/4000] Training [1/16] Loss: 0.00170 +Epoch [3827/4000] Training [2/16] Loss: 0.00297 +Epoch [3827/4000] Training [3/16] Loss: 0.00247 +Epoch [3827/4000] Training [4/16] Loss: 0.00230 +Epoch [3827/4000] Training [5/16] Loss: 0.00188 +Epoch [3827/4000] Training [6/16] Loss: 0.00186 +Epoch [3827/4000] Training [7/16] Loss: 0.00192 +Epoch [3827/4000] Training [8/16] Loss: 0.00197 +Epoch [3827/4000] Training [9/16] Loss: 0.00317 +Epoch [3827/4000] Training [10/16] Loss: 0.00177 +Epoch [3827/4000] Training [11/16] Loss: 0.00227 +Epoch [3827/4000] Training [12/16] Loss: 0.00285 +Epoch [3827/4000] Training [13/16] Loss: 0.00198 +Epoch [3827/4000] Training [14/16] Loss: 0.00252 +Epoch [3827/4000] Training [15/16] Loss: 0.00242 +Epoch [3827/4000] Training [16/16] Loss: 0.00302 +Epoch [3827/4000] Training metric {'Train/mean dice_metric': 0.9987896680831909, 'Train/mean miou_metric': 0.9973040223121643, 'Train/mean f1': 0.9938582181930542, 'Train/mean precision': 0.9893161058425903, 'Train/mean recall': 0.9984422922134399, 'Train/mean hd95_metric': 0.5412663221359253} +Epoch [3827/4000] Validation [1/4] Loss: 0.48655 focal_loss 0.42022 dice_loss 0.06633 +Epoch [3827/4000] Validation [2/4] Loss: 0.65920 focal_loss 0.48501 dice_loss 0.17419 +Epoch [3827/4000] Validation [3/4] Loss: 0.54365 focal_loss 0.44800 dice_loss 0.09565 +Epoch [3827/4000] Validation [4/4] Loss: 0.36325 focal_loss 0.27426 dice_loss 0.08899 +Epoch [3827/4000] Validation metric {'Val/mean dice_metric': 0.9740702509880066, 'Val/mean miou_metric': 0.9599641561508179, 'Val/mean f1': 0.9762778878211975, 'Val/mean precision': 0.9739387035369873, 'Val/mean recall': 0.9786282777786255, 'Val/mean hd95_metric': 5.081568241119385} +Cheakpoint... +Epoch [3827/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740702509880066, 'Val/mean miou_metric': 0.9599641561508179, 'Val/mean f1': 0.9762778878211975, 'Val/mean precision': 0.9739387035369873, 'Val/mean recall': 0.9786282777786255, 'Val/mean hd95_metric': 5.081568241119385} +Epoch [3828/4000] Training [1/16] Loss: 0.00251 +Epoch [3828/4000] Training [2/16] Loss: 0.00279 +Epoch [3828/4000] Training [3/16] Loss: 0.00427 +Epoch [3828/4000] Training [4/16] Loss: 0.00155 +Epoch [3828/4000] Training [5/16] Loss: 0.00256 +Epoch [3828/4000] Training [6/16] Loss: 0.00244 +Epoch [3828/4000] Training [7/16] Loss: 0.00243 +Epoch [3828/4000] Training [8/16] Loss: 0.00323 +Epoch [3828/4000] Training [9/16] Loss: 0.00235 +Epoch [3828/4000] Training [10/16] Loss: 0.00280 +Epoch [3828/4000] Training [11/16] Loss: 0.00227 +Epoch [3828/4000] Training [12/16] Loss: 0.00189 +Epoch [3828/4000] Training [13/16] Loss: 0.00380 +Epoch [3828/4000] Training [14/16] Loss: 0.00199 +Epoch [3828/4000] Training [15/16] Loss: 0.00227 +Epoch [3828/4000] Training [16/16] Loss: 0.00270 +Epoch [3828/4000] Training metric {'Train/mean dice_metric': 0.9986906051635742, 'Train/mean miou_metric': 0.9970865249633789, 'Train/mean f1': 0.9933105111122131, 'Train/mean precision': 0.9884309768676758, 'Train/mean recall': 0.9982384443283081, 'Train/mean hd95_metric': 0.5450193881988525} +Epoch [3828/4000] Validation [1/4] Loss: 0.41444 focal_loss 0.34907 dice_loss 0.06537 +Epoch [3828/4000] Validation [2/4] Loss: 0.99801 focal_loss 0.79452 dice_loss 0.20349 +Epoch [3828/4000] Validation [3/4] Loss: 0.54935 focal_loss 0.45374 dice_loss 0.09561 +Epoch [3828/4000] Validation [4/4] Loss: 0.36481 focal_loss 0.27583 dice_loss 0.08898 +Epoch [3828/4000] Validation metric {'Val/mean dice_metric': 0.9740514755249023, 'Val/mean miou_metric': 0.9604093432426453, 'Val/mean f1': 0.9764167070388794, 'Val/mean precision': 0.9736636281013489, 'Val/mean recall': 0.9791853427886963, 'Val/mean hd95_metric': 4.777534008026123} +Cheakpoint... +Epoch [3828/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740514755249023, 'Val/mean miou_metric': 0.9604093432426453, 'Val/mean f1': 0.9764167070388794, 'Val/mean precision': 0.9736636281013489, 'Val/mean recall': 0.9791853427886963, 'Val/mean hd95_metric': 4.777534008026123} +Epoch [3829/4000] Training [1/16] Loss: 0.00333 +Epoch [3829/4000] Training [2/16] Loss: 0.00455 +Epoch [3829/4000] Training [3/16] Loss: 0.00172 +Epoch [3829/4000] Training [4/16] Loss: 0.00213 +Epoch [3829/4000] Training [5/16] Loss: 0.00173 +Epoch [3829/4000] Training [6/16] Loss: 0.00214 +Epoch [3829/4000] Training [7/16] Loss: 0.00251 +Epoch [3829/4000] Training [8/16] Loss: 0.00343 +Epoch [3829/4000] Training [9/16] Loss: 0.00229 +Epoch [3829/4000] Training [10/16] Loss: 0.00246 +Epoch [3829/4000] Training [11/16] Loss: 0.00286 +Epoch [3829/4000] Training [12/16] Loss: 0.00358 +Epoch [3829/4000] Training [13/16] Loss: 0.00203 +Epoch [3829/4000] Training [14/16] Loss: 0.00275 +Epoch [3829/4000] Training [15/16] Loss: 0.00206 +Epoch [3829/4000] Training [16/16] Loss: 0.00169 +Epoch [3829/4000] Training metric {'Train/mean dice_metric': 0.9988082051277161, 'Train/mean miou_metric': 0.9973087310791016, 'Train/mean f1': 0.9930182099342346, 'Train/mean precision': 0.987762451171875, 'Train/mean recall': 0.9983302354812622, 'Train/mean hd95_metric': 0.49489450454711914} +Epoch [3829/4000] Validation [1/4] Loss: 0.39568 focal_loss 0.33103 dice_loss 0.06465 +Epoch [3829/4000] Validation [2/4] Loss: 0.95755 focal_loss 0.76983 dice_loss 0.18772 +Epoch [3829/4000] Validation [3/4] Loss: 0.58003 focal_loss 0.47473 dice_loss 0.10531 +Epoch [3829/4000] Validation [4/4] Loss: 0.33050 focal_loss 0.24322 dice_loss 0.08728 +Epoch [3829/4000] Validation metric {'Val/mean dice_metric': 0.9731240272521973, 'Val/mean miou_metric': 0.9595798254013062, 'Val/mean f1': 0.9750810861587524, 'Val/mean precision': 0.9725163578987122, 'Val/mean recall': 0.9776593446731567, 'Val/mean hd95_metric': 5.076353073120117} +Cheakpoint... +Epoch [3829/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731240272521973, 'Val/mean miou_metric': 0.9595798254013062, 'Val/mean f1': 0.9750810861587524, 'Val/mean precision': 0.9725163578987122, 'Val/mean recall': 0.9776593446731567, 'Val/mean hd95_metric': 5.076353073120117} +Epoch [3830/4000] Training [1/16] Loss: 0.00261 +Epoch [3830/4000] Training [2/16] Loss: 0.00254 +Epoch [3830/4000] Training [3/16] Loss: 0.00312 +Epoch [3830/4000] Training [4/16] Loss: 0.00214 +Epoch [3830/4000] Training [5/16] Loss: 0.00305 +Epoch [3830/4000] Training [6/16] Loss: 0.00514 +Epoch [3830/4000] Training [7/16] Loss: 0.00297 +Epoch [3830/4000] Training [8/16] Loss: 0.00269 +Epoch [3830/4000] Training [9/16] Loss: 0.00260 +Epoch [3830/4000] Training [10/16] Loss: 0.00252 +Epoch [3830/4000] Training [11/16] Loss: 0.00185 +Epoch [3830/4000] Training [12/16] Loss: 0.00128 +Epoch [3830/4000] Training [13/16] Loss: 0.00263 +Epoch [3830/4000] Training [14/16] Loss: 0.00265 +Epoch [3830/4000] Training [15/16] Loss: 0.00322 +Epoch [3830/4000] Training [16/16] Loss: 0.00179 +Epoch [3830/4000] Training metric {'Train/mean dice_metric': 0.9987280368804932, 'Train/mean miou_metric': 0.9971845149993896, 'Train/mean f1': 0.9938294887542725, 'Train/mean precision': 0.9893712997436523, 'Train/mean recall': 0.9983280301094055, 'Train/mean hd95_metric': 0.5155549049377441} +Epoch [3830/4000] Validation [1/4] Loss: 0.41411 focal_loss 0.34933 dice_loss 0.06479 +Epoch [3830/4000] Validation [2/4] Loss: 0.48392 focal_loss 0.37247 dice_loss 0.11145 +Epoch [3830/4000] Validation [3/4] Loss: 0.30948 focal_loss 0.24377 dice_loss 0.06571 +Epoch [3830/4000] Validation [4/4] Loss: 0.34687 focal_loss 0.25776 dice_loss 0.08911 +Epoch [3830/4000] Validation metric {'Val/mean dice_metric': 0.9750667810440063, 'Val/mean miou_metric': 0.9611213803291321, 'Val/mean f1': 0.976844072341919, 'Val/mean precision': 0.9744948148727417, 'Val/mean recall': 0.9792046546936035, 'Val/mean hd95_metric': 4.758931636810303} +Cheakpoint... +Epoch [3830/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750667810440063, 'Val/mean miou_metric': 0.9611213803291321, 'Val/mean f1': 0.976844072341919, 'Val/mean precision': 0.9744948148727417, 'Val/mean recall': 0.9792046546936035, 'Val/mean hd95_metric': 4.758931636810303} +Epoch [3831/4000] Training [1/16] Loss: 0.00319 +Epoch [3831/4000] Training [2/16] Loss: 0.00281 +Epoch [3831/4000] Training [3/16] Loss: 0.00351 +Epoch [3831/4000] Training [4/16] Loss: 0.00209 +Epoch [3831/4000] Training [5/16] Loss: 0.00322 +Epoch [3831/4000] Training [6/16] Loss: 0.00172 +Epoch [3831/4000] Training [7/16] Loss: 0.00163 +Epoch [3831/4000] Training [8/16] Loss: 0.00214 +Epoch [3831/4000] Training [9/16] Loss: 0.00351 +Epoch [3831/4000] Training [10/16] Loss: 0.00324 +Epoch [3831/4000] Training [11/16] Loss: 0.00282 +Epoch [3831/4000] Training [12/16] Loss: 0.00150 +Epoch [3831/4000] Training [13/16] Loss: 0.00231 +Epoch [3831/4000] Training [14/16] Loss: 0.00166 +Epoch [3831/4000] Training [15/16] Loss: 0.00176 +Epoch [3831/4000] Training [16/16] Loss: 0.00232 +Epoch [3831/4000] Training metric {'Train/mean dice_metric': 0.9988293051719666, 'Train/mean miou_metric': 0.9973839521408081, 'Train/mean f1': 0.9938865303993225, 'Train/mean precision': 0.9893745183944702, 'Train/mean recall': 0.9984398484230042, 'Train/mean hd95_metric': 0.5126250982284546} +Epoch [3831/4000] Validation [1/4] Loss: 0.39980 focal_loss 0.33680 dice_loss 0.06300 +Epoch [3831/4000] Validation [2/4] Loss: 0.95842 focal_loss 0.76940 dice_loss 0.18902 +Epoch [3831/4000] Validation [3/4] Loss: 0.54393 focal_loss 0.45049 dice_loss 0.09344 +Epoch [3831/4000] Validation [4/4] Loss: 0.38077 focal_loss 0.27764 dice_loss 0.10313 +Epoch [3831/4000] Validation metric {'Val/mean dice_metric': 0.9728708267211914, 'Val/mean miou_metric': 0.9595023989677429, 'Val/mean f1': 0.97651606798172, 'Val/mean precision': 0.9746671915054321, 'Val/mean recall': 0.9783719778060913, 'Val/mean hd95_metric': 4.774734973907471} +Cheakpoint... +Epoch [3831/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9729], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9728708267211914, 'Val/mean miou_metric': 0.9595023989677429, 'Val/mean f1': 0.97651606798172, 'Val/mean precision': 0.9746671915054321, 'Val/mean recall': 0.9783719778060913, 'Val/mean hd95_metric': 4.774734973907471} +Epoch [3832/4000] Training [1/16] Loss: 0.00252 +Epoch [3832/4000] Training [2/16] Loss: 0.00208 +Epoch [3832/4000] Training [3/16] Loss: 0.00285 +Epoch [3832/4000] Training [4/16] Loss: 0.00175 +Epoch [3832/4000] Training [5/16] Loss: 0.00400 +Epoch [3832/4000] Training [6/16] Loss: 0.00278 +Epoch [3832/4000] Training [7/16] Loss: 0.00271 +Epoch [3832/4000] Training [8/16] Loss: 0.00384 +Epoch [3832/4000] Training [9/16] Loss: 0.00151 +Epoch [3832/4000] Training [10/16] Loss: 0.00181 +Epoch [3832/4000] Training [11/16] Loss: 0.00262 +Epoch [3832/4000] Training [12/16] Loss: 0.00172 +Epoch [3832/4000] Training [13/16] Loss: 0.00276 +Epoch [3832/4000] Training [14/16] Loss: 0.00259 +Epoch [3832/4000] Training [15/16] Loss: 0.00245 +Epoch [3832/4000] Training [16/16] Loss: 0.00171 +Epoch [3832/4000] Training metric {'Train/mean dice_metric': 0.9987608790397644, 'Train/mean miou_metric': 0.997226893901825, 'Train/mean f1': 0.9935431480407715, 'Train/mean precision': 0.9888684153556824, 'Train/mean recall': 0.998262345790863, 'Train/mean hd95_metric': 0.5604767799377441} +Epoch [3832/4000] Validation [1/4] Loss: 0.38328 focal_loss 0.32154 dice_loss 0.06174 +Epoch [3832/4000] Validation [2/4] Loss: 0.58075 focal_loss 0.43106 dice_loss 0.14968 +Epoch [3832/4000] Validation [3/4] Loss: 0.27198 focal_loss 0.20788 dice_loss 0.06409 +Epoch [3832/4000] Validation [4/4] Loss: 0.42399 focal_loss 0.30084 dice_loss 0.12314 +Epoch [3832/4000] Validation metric {'Val/mean dice_metric': 0.9743230938911438, 'Val/mean miou_metric': 0.9601840972900391, 'Val/mean f1': 0.9761016964912415, 'Val/mean precision': 0.9738032221794128, 'Val/mean recall': 0.9784110188484192, 'Val/mean hd95_metric': 4.6716108322143555} +Cheakpoint... +Epoch [3832/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743230938911438, 'Val/mean miou_metric': 0.9601840972900391, 'Val/mean f1': 0.9761016964912415, 'Val/mean precision': 0.9738032221794128, 'Val/mean recall': 0.9784110188484192, 'Val/mean hd95_metric': 4.6716108322143555} +Epoch [3833/4000] Training [1/16] Loss: 0.00278 +Epoch [3833/4000] Training [2/16] Loss: 0.00157 +Epoch [3833/4000] Training [3/16] Loss: 0.00234 +Epoch [3833/4000] Training [4/16] Loss: 0.00264 +Epoch [3833/4000] Training [5/16] Loss: 0.00327 +Epoch [3833/4000] Training [6/16] Loss: 0.00300 +Epoch [3833/4000] Training [7/16] Loss: 0.00266 +Epoch [3833/4000] Training [8/16] Loss: 0.00231 +Epoch [3833/4000] Training [9/16] Loss: 0.00207 +Epoch [3833/4000] Training [10/16] Loss: 0.00266 +Epoch [3833/4000] Training [11/16] Loss: 0.00324 +Epoch [3833/4000] Training [12/16] Loss: 0.00163 +Epoch [3833/4000] Training [13/16] Loss: 0.00208 +Epoch [3833/4000] Training [14/16] Loss: 0.00193 +Epoch [3833/4000] Training [15/16] Loss: 0.00190 +Epoch [3833/4000] Training [16/16] Loss: 0.00227 +Epoch [3833/4000] Training metric {'Train/mean dice_metric': 0.998719334602356, 'Train/mean miou_metric': 0.9971646070480347, 'Train/mean f1': 0.9937442541122437, 'Train/mean precision': 0.9892107844352722, 'Train/mean recall': 0.9983195066452026, 'Train/mean hd95_metric': 0.5486378073692322} +Epoch [3833/4000] Validation [1/4] Loss: 0.42639 focal_loss 0.36293 dice_loss 0.06346 +Epoch [3833/4000] Validation [2/4] Loss: 0.47931 focal_loss 0.36955 dice_loss 0.10976 +Epoch [3833/4000] Validation [3/4] Loss: 0.54302 focal_loss 0.44724 dice_loss 0.09578 +Epoch [3833/4000] Validation [4/4] Loss: 0.29953 focal_loss 0.21288 dice_loss 0.08665 +Epoch [3833/4000] Validation metric {'Val/mean dice_metric': 0.9758602976799011, 'Val/mean miou_metric': 0.9615545272827148, 'Val/mean f1': 0.9764305949211121, 'Val/mean precision': 0.9741488695144653, 'Val/mean recall': 0.9787230491638184, 'Val/mean hd95_metric': 4.797215461730957} +Cheakpoint... +Epoch [3833/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758602976799011, 'Val/mean miou_metric': 0.9615545272827148, 'Val/mean f1': 0.9764305949211121, 'Val/mean precision': 0.9741488695144653, 'Val/mean recall': 0.9787230491638184, 'Val/mean hd95_metric': 4.797215461730957} +Epoch [3834/4000] Training [1/16] Loss: 0.00261 +Epoch [3834/4000] Training [2/16] Loss: 0.00268 +Epoch [3834/4000] Training [3/16] Loss: 0.00182 +Epoch [3834/4000] Training [4/16] Loss: 0.00197 +Epoch [3834/4000] Training [5/16] Loss: 0.00256 +Epoch [3834/4000] Training [6/16] Loss: 0.00300 +Epoch [3834/4000] Training [7/16] Loss: 0.00204 +Epoch [3834/4000] Training [8/16] Loss: 0.00191 +Epoch [3834/4000] Training [9/16] Loss: 0.00202 +Epoch [3834/4000] Training [10/16] Loss: 0.00181 +Epoch [3834/4000] Training [11/16] Loss: 0.00258 +Epoch [3834/4000] Training [12/16] Loss: 0.00242 +Epoch [3834/4000] Training [13/16] Loss: 0.00201 +Epoch [3834/4000] Training [14/16] Loss: 0.00167 +Epoch [3834/4000] Training [15/16] Loss: 0.00206 +Epoch [3834/4000] Training [16/16] Loss: 0.00200 +Epoch [3834/4000] Training metric {'Train/mean dice_metric': 0.9989066123962402, 'Train/mean miou_metric': 0.99751877784729, 'Train/mean f1': 0.9936944842338562, 'Train/mean precision': 0.9889764189720154, 'Train/mean recall': 0.9984577894210815, 'Train/mean hd95_metric': 0.5024229288101196} +Epoch [3834/4000] Validation [1/4] Loss: 0.40642 focal_loss 0.33903 dice_loss 0.06738 +Epoch [3834/4000] Validation [2/4] Loss: 0.46044 focal_loss 0.35533 dice_loss 0.10511 +Epoch [3834/4000] Validation [3/4] Loss: 0.51511 focal_loss 0.41445 dice_loss 0.10066 +Epoch [3834/4000] Validation [4/4] Loss: 0.35379 focal_loss 0.26866 dice_loss 0.08513 +Epoch [3834/4000] Validation metric {'Val/mean dice_metric': 0.9744044542312622, 'Val/mean miou_metric': 0.9603347778320312, 'Val/mean f1': 0.9760429263114929, 'Val/mean precision': 0.9733445644378662, 'Val/mean recall': 0.978756308555603, 'Val/mean hd95_metric': 5.1475911140441895} +Cheakpoint... +Epoch [3834/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744044542312622, 'Val/mean miou_metric': 0.9603347778320312, 'Val/mean f1': 0.9760429263114929, 'Val/mean precision': 0.9733445644378662, 'Val/mean recall': 0.978756308555603, 'Val/mean hd95_metric': 5.1475911140441895} +Epoch [3835/4000] Training [1/16] Loss: 0.00275 +Epoch [3835/4000] Training [2/16] Loss: 0.00251 +Epoch [3835/4000] Training [3/16] Loss: 0.00234 +Epoch [3835/4000] Training [4/16] Loss: 0.00243 +Epoch [3835/4000] Training [5/16] Loss: 0.00227 +Epoch [3835/4000] Training [6/16] Loss: 0.00316 +Epoch [3835/4000] Training [7/16] Loss: 0.00194 +Epoch [3835/4000] Training [8/16] Loss: 0.00387 +Epoch [3835/4000] Training [9/16] Loss: 0.00188 +Epoch [3835/4000] Training [10/16] Loss: 0.00267 +Epoch [3835/4000] Training [11/16] Loss: 0.00219 +Epoch [3835/4000] Training [12/16] Loss: 0.00250 +Epoch [3835/4000] Training [13/16] Loss: 0.00424 +Epoch [3835/4000] Training [14/16] Loss: 0.00241 +Epoch [3835/4000] Training [15/16] Loss: 0.00196 +Epoch [3835/4000] Training [16/16] Loss: 0.00200 +Epoch [3835/4000] Training metric {'Train/mean dice_metric': 0.9988504648208618, 'Train/mean miou_metric': 0.9974098205566406, 'Train/mean f1': 0.9936561584472656, 'Train/mean precision': 0.9889507293701172, 'Train/mean recall': 0.9984065890312195, 'Train/mean hd95_metric': 0.5112859010696411} +Epoch [3835/4000] Validation [1/4] Loss: 0.49046 focal_loss 0.42470 dice_loss 0.06576 +Epoch [3835/4000] Validation [2/4] Loss: 0.94884 focal_loss 0.75906 dice_loss 0.18978 +Epoch [3835/4000] Validation [3/4] Loss: 0.53007 focal_loss 0.44250 dice_loss 0.08757 +Epoch [3835/4000] Validation [4/4] Loss: 0.39002 focal_loss 0.28947 dice_loss 0.10055 +Epoch [3835/4000] Validation metric {'Val/mean dice_metric': 0.9733957052230835, 'Val/mean miou_metric': 0.9600414037704468, 'Val/mean f1': 0.9762982726097107, 'Val/mean precision': 0.973812997341156, 'Val/mean recall': 0.9787962436676025, 'Val/mean hd95_metric': 4.772418022155762} +Cheakpoint... +Epoch [3835/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733957052230835, 'Val/mean miou_metric': 0.9600414037704468, 'Val/mean f1': 0.9762982726097107, 'Val/mean precision': 0.973812997341156, 'Val/mean recall': 0.9787962436676025, 'Val/mean hd95_metric': 4.772418022155762} +Epoch [3836/4000] Training [1/16] Loss: 0.00224 +Epoch [3836/4000] Training [2/16] Loss: 0.00202 +Epoch [3836/4000] Training [3/16] Loss: 0.00198 +Epoch [3836/4000] Training [4/16] Loss: 0.00317 +Epoch [3836/4000] Training [5/16] Loss: 0.00198 +Epoch [3836/4000] Training [6/16] Loss: 0.00232 +Epoch [3836/4000] Training [7/16] Loss: 0.00174 +Epoch [3836/4000] Training [8/16] Loss: 0.00228 +Epoch [3836/4000] Training [9/16] Loss: 0.00262 +Epoch [3836/4000] Training [10/16] Loss: 0.00180 +Epoch [3836/4000] Training [11/16] Loss: 0.00268 +Epoch [3836/4000] Training [12/16] Loss: 0.00307 +Epoch [3836/4000] Training [13/16] Loss: 0.00236 +Epoch [3836/4000] Training [14/16] Loss: 0.00295 +Epoch [3836/4000] Training [15/16] Loss: 0.00273 +Epoch [3836/4000] Training [16/16] Loss: 0.00296 +Epoch [3836/4000] Training metric {'Train/mean dice_metric': 0.9987776875495911, 'Train/mean miou_metric': 0.9972831606864929, 'Train/mean f1': 0.9938938021659851, 'Train/mean precision': 0.9894379377365112, 'Train/mean recall': 0.9983900189399719, 'Train/mean hd95_metric': 0.5498322248458862} +Epoch [3836/4000] Validation [1/4] Loss: 0.41951 focal_loss 0.34527 dice_loss 0.07424 +Epoch [3836/4000] Validation [2/4] Loss: 0.52888 focal_loss 0.40140 dice_loss 0.12748 +Epoch [3836/4000] Validation [3/4] Loss: 0.52337 focal_loss 0.42475 dice_loss 0.09861 +Epoch [3836/4000] Validation [4/4] Loss: 0.39324 focal_loss 0.29619 dice_loss 0.09705 +Epoch [3836/4000] Validation metric {'Val/mean dice_metric': 0.9739651679992676, 'Val/mean miou_metric': 0.9600340723991394, 'Val/mean f1': 0.9763281345367432, 'Val/mean precision': 0.9741226434707642, 'Val/mean recall': 0.9785435199737549, 'Val/mean hd95_metric': 4.756832122802734} +Cheakpoint... +Epoch [3836/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739651679992676, 'Val/mean miou_metric': 0.9600340723991394, 'Val/mean f1': 0.9763281345367432, 'Val/mean precision': 0.9741226434707642, 'Val/mean recall': 0.9785435199737549, 'Val/mean hd95_metric': 4.756832122802734} +Epoch [3837/4000] Training [1/16] Loss: 0.00192 +Epoch [3837/4000] Training [2/16] Loss: 0.00301 +Epoch [3837/4000] Training [3/16] Loss: 0.00222 +Epoch [3837/4000] Training [4/16] Loss: 0.00245 +Epoch [3837/4000] Training [5/16] Loss: 0.00244 +Epoch [3837/4000] Training [6/16] Loss: 0.00239 +Epoch [3837/4000] Training [7/16] Loss: 0.00286 +Epoch [3837/4000] Training [8/16] Loss: 0.00183 +Epoch [3837/4000] Training [9/16] Loss: 0.00174 +Epoch [3837/4000] Training [10/16] Loss: 0.00237 +Epoch [3837/4000] Training [11/16] Loss: 0.00279 +Epoch [3837/4000] Training [12/16] Loss: 0.00281 +Epoch [3837/4000] Training [13/16] Loss: 0.00318 +Epoch [3837/4000] Training [14/16] Loss: 0.00148 +Epoch [3837/4000] Training [15/16] Loss: 0.00158 +Epoch [3837/4000] Training [16/16] Loss: 0.00163 +Epoch [3837/4000] Training metric {'Train/mean dice_metric': 0.9988411068916321, 'Train/mean miou_metric': 0.9974104166030884, 'Train/mean f1': 0.9939004182815552, 'Train/mean precision': 0.9894042015075684, 'Train/mean recall': 0.9984376430511475, 'Train/mean hd95_metric': 0.5026642084121704} +Epoch [3837/4000] Validation [1/4] Loss: 0.38874 focal_loss 0.32518 dice_loss 0.06356 +Epoch [3837/4000] Validation [2/4] Loss: 1.05932 focal_loss 0.87375 dice_loss 0.18557 +Epoch [3837/4000] Validation [3/4] Loss: 0.52153 focal_loss 0.43142 dice_loss 0.09011 +Epoch [3837/4000] Validation [4/4] Loss: 0.38044 focal_loss 0.28477 dice_loss 0.09567 +Epoch [3837/4000] Validation metric {'Val/mean dice_metric': 0.9738951921463013, 'Val/mean miou_metric': 0.9602949023246765, 'Val/mean f1': 0.9762585759162903, 'Val/mean precision': 0.9734001755714417, 'Val/mean recall': 0.9791339039802551, 'Val/mean hd95_metric': 4.775047779083252} +Cheakpoint... +Epoch [3837/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738951921463013, 'Val/mean miou_metric': 0.9602949023246765, 'Val/mean f1': 0.9762585759162903, 'Val/mean precision': 0.9734001755714417, 'Val/mean recall': 0.9791339039802551, 'Val/mean hd95_metric': 4.775047779083252} +Epoch [3838/4000] Training [1/16] Loss: 0.00354 +Epoch [3838/4000] Training [2/16] Loss: 0.00235 +Epoch [3838/4000] Training [3/16] Loss: 0.00220 +Epoch [3838/4000] Training [4/16] Loss: 0.00196 +Epoch [3838/4000] Training [5/16] Loss: 0.00153 +Epoch [3838/4000] Training [6/16] Loss: 0.00286 +Epoch [3838/4000] Training [7/16] Loss: 0.00179 +Epoch [3838/4000] Training [8/16] Loss: 0.00207 +Epoch [3838/4000] Training [9/16] Loss: 0.00245 +Epoch [3838/4000] Training [10/16] Loss: 0.00406 +Epoch [3838/4000] Training [11/16] Loss: 0.00292 +Epoch [3838/4000] Training [12/16] Loss: 0.00260 +Epoch [3838/4000] Training [13/16] Loss: 0.00259 +Epoch [3838/4000] Training [14/16] Loss: 0.00197 +Epoch [3838/4000] Training [15/16] Loss: 0.00355 +Epoch [3838/4000] Training [16/16] Loss: 0.00235 +Epoch [3838/4000] Training metric {'Train/mean dice_metric': 0.9987602233886719, 'Train/mean miou_metric': 0.9972461462020874, 'Train/mean f1': 0.9938367009162903, 'Train/mean precision': 0.989319920539856, 'Train/mean recall': 0.9983949065208435, 'Train/mean hd95_metric': 0.5184915661811829} +Epoch [3838/4000] Validation [1/4] Loss: 0.42205 focal_loss 0.35784 dice_loss 0.06420 +Epoch [3838/4000] Validation [2/4] Loss: 0.45484 focal_loss 0.34821 dice_loss 0.10663 +Epoch [3838/4000] Validation [3/4] Loss: 0.27210 focal_loss 0.20566 dice_loss 0.06644 +Epoch [3838/4000] Validation [4/4] Loss: 0.34721 focal_loss 0.25824 dice_loss 0.08896 +Epoch [3838/4000] Validation metric {'Val/mean dice_metric': 0.9744985699653625, 'Val/mean miou_metric': 0.9606607556343079, 'Val/mean f1': 0.9766917824745178, 'Val/mean precision': 0.9744892120361328, 'Val/mean recall': 0.9789043664932251, 'Val/mean hd95_metric': 5.1338677406311035} +Cheakpoint... +Epoch [3838/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744985699653625, 'Val/mean miou_metric': 0.9606607556343079, 'Val/mean f1': 0.9766917824745178, 'Val/mean precision': 0.9744892120361328, 'Val/mean recall': 0.9789043664932251, 'Val/mean hd95_metric': 5.1338677406311035} +Epoch [3839/4000] Training [1/16] Loss: 0.00225 +Epoch [3839/4000] Training [2/16] Loss: 0.00241 +Epoch [3839/4000] Training [3/16] Loss: 0.00204 +Epoch [3839/4000] Training [4/16] Loss: 0.00249 +Epoch [3839/4000] Training [5/16] Loss: 0.00279 +Epoch [3839/4000] Training [6/16] Loss: 0.00346 +Epoch [3839/4000] Training [7/16] Loss: 0.00236 +Epoch [3839/4000] Training [8/16] Loss: 0.00185 +Epoch [3839/4000] Training [9/16] Loss: 0.00221 +Epoch [3839/4000] Training [10/16] Loss: 0.00233 +Epoch [3839/4000] Training [11/16] Loss: 0.00184 +Epoch [3839/4000] Training [12/16] Loss: 0.00191 +Epoch [3839/4000] Training [13/16] Loss: 0.00425 +Epoch [3839/4000] Training [14/16] Loss: 0.00206 +Epoch [3839/4000] Training [15/16] Loss: 0.00207 +Epoch [3839/4000] Training [16/16] Loss: 0.00352 +Epoch [3839/4000] Training metric {'Train/mean dice_metric': 0.9988083839416504, 'Train/mean miou_metric': 0.997338056564331, 'Train/mean f1': 0.9938032031059265, 'Train/mean precision': 0.9892207384109497, 'Train/mean recall': 0.9984282851219177, 'Train/mean hd95_metric': 0.5292267799377441} +Epoch [3839/4000] Validation [1/4] Loss: 0.52059 focal_loss 0.44069 dice_loss 0.07991 +Epoch [3839/4000] Validation [2/4] Loss: 0.47142 focal_loss 0.36132 dice_loss 0.11010 +Epoch [3839/4000] Validation [3/4] Loss: 0.54408 focal_loss 0.45213 dice_loss 0.09194 +Epoch [3839/4000] Validation [4/4] Loss: 0.58493 focal_loss 0.45806 dice_loss 0.12687 +Epoch [3839/4000] Validation metric {'Val/mean dice_metric': 0.9731351137161255, 'Val/mean miou_metric': 0.958926796913147, 'Val/mean f1': 0.9761227965354919, 'Val/mean precision': 0.9748257994651794, 'Val/mean recall': 0.9774231910705566, 'Val/mean hd95_metric': 4.645503044128418} +Cheakpoint... +Epoch [3839/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731351137161255, 'Val/mean miou_metric': 0.958926796913147, 'Val/mean f1': 0.9761227965354919, 'Val/mean precision': 0.9748257994651794, 'Val/mean recall': 0.9774231910705566, 'Val/mean hd95_metric': 4.645503044128418} +Epoch [3840/4000] Training [1/16] Loss: 0.00191 +Epoch [3840/4000] Training [2/16] Loss: 0.00289 +Epoch [3840/4000] Training [3/16] Loss: 0.00245 +Epoch [3840/4000] Training [4/16] Loss: 0.00217 +Epoch [3840/4000] Training [5/16] Loss: 0.00202 +Epoch [3840/4000] Training [6/16] Loss: 0.00290 +Epoch [3840/4000] Training [7/16] Loss: 0.00223 +Epoch [3840/4000] Training [8/16] Loss: 0.00188 +Epoch [3840/4000] Training [9/16] Loss: 0.00344 +Epoch [3840/4000] Training [10/16] Loss: 0.00377 +Epoch [3840/4000] Training [11/16] Loss: 0.00189 +Epoch [3840/4000] Training [12/16] Loss: 0.00244 +Epoch [3840/4000] Training [13/16] Loss: 0.00250 +Epoch [3840/4000] Training [14/16] Loss: 0.00256 +Epoch [3840/4000] Training [15/16] Loss: 0.00314 +Epoch [3840/4000] Training [16/16] Loss: 0.00368 +Epoch [3840/4000] Training metric {'Train/mean dice_metric': 0.9987491369247437, 'Train/mean miou_metric': 0.9972279071807861, 'Train/mean f1': 0.9937240481376648, 'Train/mean precision': 0.9891719818115234, 'Train/mean recall': 0.9983181953430176, 'Train/mean hd95_metric': 0.4973474442958832} +Epoch [3840/4000] Validation [1/4] Loss: 0.45302 focal_loss 0.38360 dice_loss 0.06942 +Epoch [3840/4000] Validation [2/4] Loss: 0.52268 focal_loss 0.39189 dice_loss 0.13079 +Epoch [3840/4000] Validation [3/4] Loss: 0.55395 focal_loss 0.45605 dice_loss 0.09790 +Epoch [3840/4000] Validation [4/4] Loss: 0.38322 focal_loss 0.28003 dice_loss 0.10319 +Epoch [3840/4000] Validation metric {'Val/mean dice_metric': 0.9731718301773071, 'Val/mean miou_metric': 0.9583554267883301, 'Val/mean f1': 0.975303053855896, 'Val/mean precision': 0.9729419350624084, 'Val/mean recall': 0.9776756167411804, 'Val/mean hd95_metric': 5.069316864013672} +Cheakpoint... +Epoch [3840/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731718301773071, 'Val/mean miou_metric': 0.9583554267883301, 'Val/mean f1': 0.975303053855896, 'Val/mean precision': 0.9729419350624084, 'Val/mean recall': 0.9776756167411804, 'Val/mean hd95_metric': 5.069316864013672} +Epoch [3841/4000] Training [1/16] Loss: 0.00268 +Epoch [3841/4000] Training [2/16] Loss: 0.00139 +Epoch [3841/4000] Training [3/16] Loss: 0.00183 +Epoch [3841/4000] Training [4/16] Loss: 0.00309 +Epoch [3841/4000] Training [5/16] Loss: 0.00149 +Epoch [3841/4000] Training [6/16] Loss: 0.00263 +Epoch [3841/4000] Training [7/16] Loss: 0.00203 +Epoch [3841/4000] Training [8/16] Loss: 0.00231 +Epoch [3841/4000] Training [9/16] Loss: 0.00257 +Epoch [3841/4000] Training [10/16] Loss: 0.00217 +Epoch [3841/4000] Training [11/16] Loss: 0.00207 +Epoch [3841/4000] Training [12/16] Loss: 0.00257 +Epoch [3841/4000] Training [13/16] Loss: 0.00208 +Epoch [3841/4000] Training [14/16] Loss: 0.00186 +Epoch [3841/4000] Training [15/16] Loss: 0.00188 +Epoch [3841/4000] Training [16/16] Loss: 0.00151 +Epoch [3841/4000] Training metric {'Train/mean dice_metric': 0.9989116191864014, 'Train/mean miou_metric': 0.9975306987762451, 'Train/mean f1': 0.9936819076538086, 'Train/mean precision': 0.9889847040176392, 'Train/mean recall': 0.9984239339828491, 'Train/mean hd95_metric': 0.47780925035476685} +Epoch [3841/4000] Validation [1/4] Loss: 0.42537 focal_loss 0.36217 dice_loss 0.06320 +Epoch [3841/4000] Validation [2/4] Loss: 0.47430 focal_loss 0.36429 dice_loss 0.11001 +Epoch [3841/4000] Validation [3/4] Loss: 0.54626 focal_loss 0.45182 dice_loss 0.09444 +Epoch [3841/4000] Validation [4/4] Loss: 0.47412 focal_loss 0.36176 dice_loss 0.11236 +Epoch [3841/4000] Validation metric {'Val/mean dice_metric': 0.9740597009658813, 'Val/mean miou_metric': 0.959823489189148, 'Val/mean f1': 0.9763213992118835, 'Val/mean precision': 0.9734920859336853, 'Val/mean recall': 0.9791671633720398, 'Val/mean hd95_metric': 5.064896106719971} +Cheakpoint... +Epoch [3841/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740597009658813, 'Val/mean miou_metric': 0.959823489189148, 'Val/mean f1': 0.9763213992118835, 'Val/mean precision': 0.9734920859336853, 'Val/mean recall': 0.9791671633720398, 'Val/mean hd95_metric': 5.064896106719971} +Epoch [3842/4000] Training [1/16] Loss: 0.00347 +Epoch [3842/4000] Training [2/16] Loss: 0.00296 +Epoch [3842/4000] Training [3/16] Loss: 0.00269 +Epoch [3842/4000] Training [4/16] Loss: 0.00194 +Epoch [3842/4000] Training [5/16] Loss: 0.00216 +Epoch [3842/4000] Training [6/16] Loss: 0.00158 +Epoch [3842/4000] Training [7/16] Loss: 0.00244 +Epoch [3842/4000] Training [8/16] Loss: 0.00173 +Epoch [3842/4000] Training [9/16] Loss: 0.00197 +Epoch [3842/4000] Training [10/16] Loss: 0.00255 +Epoch [3842/4000] Training [11/16] Loss: 0.00161 +Epoch [3842/4000] Training [12/16] Loss: 0.00238 +Epoch [3842/4000] Training [13/16] Loss: 0.00311 +Epoch [3842/4000] Training [14/16] Loss: 0.00280 +Epoch [3842/4000] Training [15/16] Loss: 0.00200 +Epoch [3842/4000] Training [16/16] Loss: 0.00164 +Epoch [3842/4000] Training metric {'Train/mean dice_metric': 0.9988223314285278, 'Train/mean miou_metric': 0.9973658323287964, 'Train/mean f1': 0.9937816858291626, 'Train/mean precision': 0.9892351627349854, 'Train/mean recall': 0.9983701109886169, 'Train/mean hd95_metric': 0.5021061897277832} +Epoch [3842/4000] Validation [1/4] Loss: 0.48089 focal_loss 0.40414 dice_loss 0.07675 +Epoch [3842/4000] Validation [2/4] Loss: 0.95242 focal_loss 0.76702 dice_loss 0.18540 +Epoch [3842/4000] Validation [3/4] Loss: 0.55619 focal_loss 0.46005 dice_loss 0.09614 +Epoch [3842/4000] Validation [4/4] Loss: 0.48698 focal_loss 0.37630 dice_loss 0.11068 +Epoch [3842/4000] Validation metric {'Val/mean dice_metric': 0.9748486280441284, 'Val/mean miou_metric': 0.9605954885482788, 'Val/mean f1': 0.9764241576194763, 'Val/mean precision': 0.9741458296775818, 'Val/mean recall': 0.9787130951881409, 'Val/mean hd95_metric': 5.09974479675293} +Cheakpoint... +Epoch [3842/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748486280441284, 'Val/mean miou_metric': 0.9605954885482788, 'Val/mean f1': 0.9764241576194763, 'Val/mean precision': 0.9741458296775818, 'Val/mean recall': 0.9787130951881409, 'Val/mean hd95_metric': 5.09974479675293} +Epoch [3843/4000] Training [1/16] Loss: 0.00270 +Epoch [3843/4000] Training [2/16] Loss: 0.00226 +Epoch [3843/4000] Training [3/16] Loss: 0.00335 +Epoch [3843/4000] Training [4/16] Loss: 0.00193 +Epoch [3843/4000] Training [5/16] Loss: 0.00215 +Epoch [3843/4000] Training [6/16] Loss: 0.00344 +Epoch [3843/4000] Training [7/16] Loss: 0.00301 +Epoch [3843/4000] Training [8/16] Loss: 0.00327 +Epoch [3843/4000] Training [9/16] Loss: 0.00171 +Epoch [3843/4000] Training [10/16] Loss: 0.00192 +Epoch [3843/4000] Training [11/16] Loss: 0.00323 +Epoch [3843/4000] Training [12/16] Loss: 0.00232 +Epoch [3843/4000] Training [13/16] Loss: 0.00205 +Epoch [3843/4000] Training [14/16] Loss: 0.00330 +Epoch [3843/4000] Training [15/16] Loss: 0.00142 +Epoch [3843/4000] Training [16/16] Loss: 0.00191 +Epoch [3843/4000] Training metric {'Train/mean dice_metric': 0.9988566637039185, 'Train/mean miou_metric': 0.9974379539489746, 'Train/mean f1': 0.9938300251960754, 'Train/mean precision': 0.9893096089363098, 'Train/mean recall': 0.9983919858932495, 'Train/mean hd95_metric': 0.5313751697540283} +Epoch [3843/4000] Validation [1/4] Loss: 0.35720 focal_loss 0.29870 dice_loss 0.05850 +Epoch [3843/4000] Validation [2/4] Loss: 1.10594 focal_loss 0.91618 dice_loss 0.18977 +Epoch [3843/4000] Validation [3/4] Loss: 0.52102 focal_loss 0.42878 dice_loss 0.09224 +Epoch [3843/4000] Validation [4/4] Loss: 0.49340 focal_loss 0.38451 dice_loss 0.10889 +Epoch [3843/4000] Validation metric {'Val/mean dice_metric': 0.9739671945571899, 'Val/mean miou_metric': 0.9605765342712402, 'Val/mean f1': 0.9761868715286255, 'Val/mean precision': 0.9737637042999268, 'Val/mean recall': 0.9786219596862793, 'Val/mean hd95_metric': 4.9330735206604} +Cheakpoint... +Epoch [3843/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739671945571899, 'Val/mean miou_metric': 0.9605765342712402, 'Val/mean f1': 0.9761868715286255, 'Val/mean precision': 0.9737637042999268, 'Val/mean recall': 0.9786219596862793, 'Val/mean hd95_metric': 4.9330735206604} +Epoch [3844/4000] Training [1/16] Loss: 0.00239 +Epoch [3844/4000] Training [2/16] Loss: 0.00187 +Epoch [3844/4000] Training [3/16] Loss: 0.00218 +Epoch [3844/4000] Training [4/16] Loss: 0.00217 +Epoch [3844/4000] Training [5/16] Loss: 0.00307 +Epoch [3844/4000] Training [6/16] Loss: 0.00246 +Epoch [3844/4000] Training [7/16] Loss: 0.00221 +Epoch [3844/4000] Training [8/16] Loss: 0.00233 +Epoch [3844/4000] Training [9/16] Loss: 0.00181 +Epoch [3844/4000] Training [10/16] Loss: 0.00186 +Epoch [3844/4000] Training [11/16] Loss: 0.00186 +Epoch [3844/4000] Training [12/16] Loss: 0.00348 +Epoch [3844/4000] Training [13/16] Loss: 0.00154 +Epoch [3844/4000] Training [14/16] Loss: 0.00160 +Epoch [3844/4000] Training [15/16] Loss: 0.00218 +Epoch [3844/4000] Training [16/16] Loss: 0.00217 +Epoch [3844/4000] Training metric {'Train/mean dice_metric': 0.9988640546798706, 'Train/mean miou_metric': 0.997446596622467, 'Train/mean f1': 0.9937307834625244, 'Train/mean precision': 0.9890916347503662, 'Train/mean recall': 0.9984136819839478, 'Train/mean hd95_metric': 0.4710237383842468} +Epoch [3844/4000] Validation [1/4] Loss: 0.43475 focal_loss 0.37083 dice_loss 0.06392 +Epoch [3844/4000] Validation [2/4] Loss: 1.04967 focal_loss 0.86337 dice_loss 0.18630 +Epoch [3844/4000] Validation [3/4] Loss: 0.51393 focal_loss 0.42642 dice_loss 0.08751 +Epoch [3844/4000] Validation [4/4] Loss: 0.35546 focal_loss 0.26777 dice_loss 0.08769 +Epoch [3844/4000] Validation metric {'Val/mean dice_metric': 0.9731143116950989, 'Val/mean miou_metric': 0.9600626826286316, 'Val/mean f1': 0.9759284257888794, 'Val/mean precision': 0.9737160801887512, 'Val/mean recall': 0.9781508445739746, 'Val/mean hd95_metric': 4.754673480987549} +Cheakpoint... +Epoch [3844/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731143116950989, 'Val/mean miou_metric': 0.9600626826286316, 'Val/mean f1': 0.9759284257888794, 'Val/mean precision': 0.9737160801887512, 'Val/mean recall': 0.9781508445739746, 'Val/mean hd95_metric': 4.754673480987549} +Epoch [3845/4000] Training [1/16] Loss: 0.00178 +Epoch [3845/4000] Training [2/16] Loss: 0.00211 +Epoch [3845/4000] Training [3/16] Loss: 0.00196 +Epoch [3845/4000] Training [4/16] Loss: 0.00251 +Epoch [3845/4000] Training [5/16] Loss: 0.00201 +Epoch [3845/4000] Training [6/16] Loss: 0.00697 +Epoch [3845/4000] Training [7/16] Loss: 0.00219 +Epoch [3845/4000] Training [8/16] Loss: 0.00277 +Epoch [3845/4000] Training [9/16] Loss: 0.00219 +Epoch [3845/4000] Training [10/16] Loss: 0.00362 +Epoch [3845/4000] Training [11/16] Loss: 0.00225 +Epoch [3845/4000] Training [12/16] Loss: 0.00201 +Epoch [3845/4000] Training [13/16] Loss: 0.00211 +Epoch [3845/4000] Training [14/16] Loss: 0.00233 +Epoch [3845/4000] Training [15/16] Loss: 0.00403 +Epoch [3845/4000] Training [16/16] Loss: 0.00274 +Epoch [3845/4000] Training metric {'Train/mean dice_metric': 0.9988519549369812, 'Train/mean miou_metric': 0.9974300861358643, 'Train/mean f1': 0.9938606023788452, 'Train/mean precision': 0.9892545938491821, 'Train/mean recall': 0.9985097050666809, 'Train/mean hd95_metric': 0.47065308690071106} +Epoch [3845/4000] Validation [1/4] Loss: 0.39130 focal_loss 0.32925 dice_loss 0.06205 +Epoch [3845/4000] Validation [2/4] Loss: 1.23803 focal_loss 0.95805 dice_loss 0.27997 +Epoch [3845/4000] Validation [3/4] Loss: 0.27782 focal_loss 0.21399 dice_loss 0.06383 +Epoch [3845/4000] Validation [4/4] Loss: 0.33737 focal_loss 0.23724 dice_loss 0.10012 +Epoch [3845/4000] Validation metric {'Val/mean dice_metric': 0.9734438061714172, 'Val/mean miou_metric': 0.9599847793579102, 'Val/mean f1': 0.9763919115066528, 'Val/mean precision': 0.9739696979522705, 'Val/mean recall': 0.9788262248039246, 'Val/mean hd95_metric': 4.834756374359131} +Cheakpoint... +Epoch [3845/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734438061714172, 'Val/mean miou_metric': 0.9599847793579102, 'Val/mean f1': 0.9763919115066528, 'Val/mean precision': 0.9739696979522705, 'Val/mean recall': 0.9788262248039246, 'Val/mean hd95_metric': 4.834756374359131} +Epoch [3846/4000] Training [1/16] Loss: 0.00189 +Epoch [3846/4000] Training [2/16] Loss: 0.00292 +Epoch [3846/4000] Training [3/16] Loss: 0.00303 +Epoch [3846/4000] Training [4/16] Loss: 0.00260 +Epoch [3846/4000] Training [5/16] Loss: 0.00198 +Epoch [3846/4000] Training [6/16] Loss: 0.00433 +Epoch [3846/4000] Training [7/16] Loss: 0.00672 +Epoch [3846/4000] Training [8/16] Loss: 0.00199 +Epoch [3846/4000] Training [9/16] Loss: 0.00177 +Epoch [3846/4000] Training [10/16] Loss: 0.00198 +Epoch [3846/4000] Training [11/16] Loss: 0.00185 +Epoch [3846/4000] Training [12/16] Loss: 0.00215 +Epoch [3846/4000] Training [13/16] Loss: 0.00281 +Epoch [3846/4000] Training [14/16] Loss: 0.00239 +Epoch [3846/4000] Training [15/16] Loss: 0.00225 +Epoch [3846/4000] Training [16/16] Loss: 0.00257 +Epoch [3846/4000] Training metric {'Train/mean dice_metric': 0.9987568855285645, 'Train/mean miou_metric': 0.9972364902496338, 'Train/mean f1': 0.9936098456382751, 'Train/mean precision': 0.9889497756958008, 'Train/mean recall': 0.9983139634132385, 'Train/mean hd95_metric': 0.5153313875198364} +Epoch [3846/4000] Validation [1/4] Loss: 0.38008 focal_loss 0.31974 dice_loss 0.06034 +Epoch [3846/4000] Validation [2/4] Loss: 1.00909 focal_loss 0.77153 dice_loss 0.23756 +Epoch [3846/4000] Validation [3/4] Loss: 0.52455 focal_loss 0.43424 dice_loss 0.09031 +Epoch [3846/4000] Validation [4/4] Loss: 0.36516 focal_loss 0.27628 dice_loss 0.08888 +Epoch [3846/4000] Validation metric {'Val/mean dice_metric': 0.9743889570236206, 'Val/mean miou_metric': 0.9601213335990906, 'Val/mean f1': 0.9755361676216125, 'Val/mean precision': 0.9730634093284607, 'Val/mean recall': 0.9780217409133911, 'Val/mean hd95_metric': 5.206894874572754} +Cheakpoint... +Epoch [3846/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743889570236206, 'Val/mean miou_metric': 0.9601213335990906, 'Val/mean f1': 0.9755361676216125, 'Val/mean precision': 0.9730634093284607, 'Val/mean recall': 0.9780217409133911, 'Val/mean hd95_metric': 5.206894874572754} +Epoch [3847/4000] Training [1/16] Loss: 0.00214 +Epoch [3847/4000] Training [2/16] Loss: 0.00252 +Epoch [3847/4000] Training [3/16] Loss: 0.00239 +Epoch [3847/4000] Training [4/16] Loss: 0.00281 +Epoch [3847/4000] Training [5/16] Loss: 0.00404 +Epoch [3847/4000] Training [6/16] Loss: 0.00219 +Epoch [3847/4000] Training [7/16] Loss: 0.00219 +Epoch [3847/4000] Training [8/16] Loss: 0.00225 +Epoch [3847/4000] Training [9/16] Loss: 0.00332 +Epoch [3847/4000] Training [10/16] Loss: 0.00263 +Epoch [3847/4000] Training [11/16] Loss: 0.00313 +Epoch [3847/4000] Training [12/16] Loss: 0.00193 +Epoch [3847/4000] Training [13/16] Loss: 0.00183 +Epoch [3847/4000] Training [14/16] Loss: 0.00156 +Epoch [3847/4000] Training [15/16] Loss: 0.00184 +Epoch [3847/4000] Training [16/16] Loss: 0.00459 +Epoch [3847/4000] Training metric {'Train/mean dice_metric': 0.9987480044364929, 'Train/mean miou_metric': 0.9972224235534668, 'Train/mean f1': 0.9937775135040283, 'Train/mean precision': 0.9892570972442627, 'Train/mean recall': 0.9983394742012024, 'Train/mean hd95_metric': 0.5632112622261047} +Epoch [3847/4000] Validation [1/4] Loss: 0.42658 focal_loss 0.36346 dice_loss 0.06311 +Epoch [3847/4000] Validation [2/4] Loss: 0.86935 focal_loss 0.67593 dice_loss 0.19342 +Epoch [3847/4000] Validation [3/4] Loss: 0.56476 focal_loss 0.47028 dice_loss 0.09448 +Epoch [3847/4000] Validation [4/4] Loss: 0.51581 focal_loss 0.40018 dice_loss 0.11563 +Epoch [3847/4000] Validation metric {'Val/mean dice_metric': 0.9732860326766968, 'Val/mean miou_metric': 0.9591529965400696, 'Val/mean f1': 0.9760125279426575, 'Val/mean precision': 0.9732846617698669, 'Val/mean recall': 0.9787556529045105, 'Val/mean hd95_metric': 5.076136112213135} +Cheakpoint... +Epoch [3847/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732860326766968, 'Val/mean miou_metric': 0.9591529965400696, 'Val/mean f1': 0.9760125279426575, 'Val/mean precision': 0.9732846617698669, 'Val/mean recall': 0.9787556529045105, 'Val/mean hd95_metric': 5.076136112213135} +Epoch [3848/4000] Training [1/16] Loss: 0.00231 +Epoch [3848/4000] Training [2/16] Loss: 0.00297 +Epoch [3848/4000] Training [3/16] Loss: 0.00278 +Epoch [3848/4000] Training [4/16] Loss: 0.00263 +Epoch [3848/4000] Training [5/16] Loss: 0.00234 +Epoch [3848/4000] Training [6/16] Loss: 0.00164 +Epoch [3848/4000] Training [7/16] Loss: 0.00166 +Epoch [3848/4000] Training [8/16] Loss: 0.00303 +Epoch [3848/4000] Training [9/16] Loss: 0.00180 +Epoch [3848/4000] Training [10/16] Loss: 0.00339 +Epoch [3848/4000] Training [11/16] Loss: 0.00159 +Epoch [3848/4000] Training [12/16] Loss: 0.00206 +Epoch [3848/4000] Training [13/16] Loss: 0.00168 +Epoch [3848/4000] Training [14/16] Loss: 0.00147 +Epoch [3848/4000] Training [15/16] Loss: 0.00217 +Epoch [3848/4000] Training [16/16] Loss: 0.00267 +Epoch [3848/4000] Training metric {'Train/mean dice_metric': 0.9989272356033325, 'Train/mean miou_metric': 0.9975809454917908, 'Train/mean f1': 0.9939438700675964, 'Train/mean precision': 0.9894852042198181, 'Train/mean recall': 0.9984428286552429, 'Train/mean hd95_metric': 0.4343603551387787} +Epoch [3848/4000] Validation [1/4] Loss: 0.41808 focal_loss 0.35453 dice_loss 0.06355 +Epoch [3848/4000] Validation [2/4] Loss: 0.47132 focal_loss 0.36194 dice_loss 0.10939 +Epoch [3848/4000] Validation [3/4] Loss: 0.25465 focal_loss 0.19626 dice_loss 0.05838 +Epoch [3848/4000] Validation [4/4] Loss: 0.40129 focal_loss 0.29792 dice_loss 0.10337 +Epoch [3848/4000] Validation metric {'Val/mean dice_metric': 0.9756636619567871, 'Val/mean miou_metric': 0.9620258212089539, 'Val/mean f1': 0.9771700501441956, 'Val/mean precision': 0.9751148223876953, 'Val/mean recall': 0.979233980178833, 'Val/mean hd95_metric': 4.477161884307861} +Cheakpoint... +Epoch [3848/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756636619567871, 'Val/mean miou_metric': 0.9620258212089539, 'Val/mean f1': 0.9771700501441956, 'Val/mean precision': 0.9751148223876953, 'Val/mean recall': 0.979233980178833, 'Val/mean hd95_metric': 4.477161884307861} +Epoch [3849/4000] Training [1/16] Loss: 0.00271 +Epoch [3849/4000] Training [2/16] Loss: 0.00235 +Epoch [3849/4000] Training [3/16] Loss: 0.00167 +Epoch [3849/4000] Training [4/16] Loss: 0.00293 +Epoch [3849/4000] Training [5/16] Loss: 0.00231 +Epoch [3849/4000] Training [6/16] Loss: 0.00220 +Epoch [3849/4000] Training [7/16] Loss: 0.00158 +Epoch [3849/4000] Training [8/16] Loss: 0.00301 +Epoch [3849/4000] Training [9/16] Loss: 0.00187 +Epoch [3849/4000] Training [10/16] Loss: 0.00226 +Epoch [3849/4000] Training [11/16] Loss: 0.00270 +Epoch [3849/4000] Training [12/16] Loss: 0.00216 +Epoch [3849/4000] Training [13/16] Loss: 0.00221 +Epoch [3849/4000] Training [14/16] Loss: 0.00286 +Epoch [3849/4000] Training [15/16] Loss: 0.00213 +Epoch [3849/4000] Training [16/16] Loss: 0.00241 +Epoch [3849/4000] Training metric {'Train/mean dice_metric': 0.9988781809806824, 'Train/mean miou_metric': 0.9974817633628845, 'Train/mean f1': 0.993863582611084, 'Train/mean precision': 0.989321768283844, 'Train/mean recall': 0.9984472990036011, 'Train/mean hd95_metric': 0.49485188722610474} +Epoch [3849/4000] Validation [1/4] Loss: 0.42087 focal_loss 0.35850 dice_loss 0.06237 +Epoch [3849/4000] Validation [2/4] Loss: 1.36997 focal_loss 1.09545 dice_loss 0.27452 +Epoch [3849/4000] Validation [3/4] Loss: 0.55153 focal_loss 0.45007 dice_loss 0.10146 +Epoch [3849/4000] Validation [4/4] Loss: 0.36797 focal_loss 0.28102 dice_loss 0.08695 +Epoch [3849/4000] Validation metric {'Val/mean dice_metric': 0.9724941253662109, 'Val/mean miou_metric': 0.9584447145462036, 'Val/mean f1': 0.9753976464271545, 'Val/mean precision': 0.9729921817779541, 'Val/mean recall': 0.9778149724006653, 'Val/mean hd95_metric': 5.304659366607666} +Cheakpoint... +Epoch [3849/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9724941253662109, 'Val/mean miou_metric': 0.9584447145462036, 'Val/mean f1': 0.9753976464271545, 'Val/mean precision': 0.9729921817779541, 'Val/mean recall': 0.9778149724006653, 'Val/mean hd95_metric': 5.304659366607666} +Epoch [3850/4000] Training [1/16] Loss: 0.00140 +Epoch [3850/4000] Training [2/16] Loss: 0.00208 +Epoch [3850/4000] Training [3/16] Loss: 0.00193 +Epoch [3850/4000] Training [4/16] Loss: 0.00286 +Epoch [3850/4000] Training [5/16] Loss: 0.00270 +Epoch [3850/4000] Training [6/16] Loss: 0.00273 +Epoch [3850/4000] Training [7/16] Loss: 0.00243 +Epoch [3850/4000] Training [8/16] Loss: 0.00298 +Epoch [3850/4000] Training [9/16] Loss: 0.00232 +Epoch [3850/4000] Training [10/16] Loss: 0.00245 +Epoch [3850/4000] Training [11/16] Loss: 0.00180 +Epoch [3850/4000] Training [12/16] Loss: 0.00274 +Epoch [3850/4000] Training [13/16] Loss: 0.00243 +Epoch [3850/4000] Training [14/16] Loss: 0.00225 +Epoch [3850/4000] Training [15/16] Loss: 0.00265 +Epoch [3850/4000] Training [16/16] Loss: 0.00275 +Epoch [3850/4000] Training metric {'Train/mean dice_metric': 0.998799204826355, 'Train/mean miou_metric': 0.9973227977752686, 'Train/mean f1': 0.9937846064567566, 'Train/mean precision': 0.9892399311065674, 'Train/mean recall': 0.9983712434768677, 'Train/mean hd95_metric': 0.49670732021331787} +Epoch [3850/4000] Validation [1/4] Loss: 0.43551 focal_loss 0.37342 dice_loss 0.06208 +Epoch [3850/4000] Validation [2/4] Loss: 1.10139 focal_loss 0.91202 dice_loss 0.18937 +Epoch [3850/4000] Validation [3/4] Loss: 0.50847 focal_loss 0.42250 dice_loss 0.08597 +Epoch [3850/4000] Validation [4/4] Loss: 0.37775 focal_loss 0.28446 dice_loss 0.09329 +Epoch [3850/4000] Validation metric {'Val/mean dice_metric': 0.9747703671455383, 'Val/mean miou_metric': 0.9609742164611816, 'Val/mean f1': 0.9766619205474854, 'Val/mean precision': 0.9739319086074829, 'Val/mean recall': 0.9794073700904846, 'Val/mean hd95_metric': 4.476895332336426} +Cheakpoint... +Epoch [3850/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747703671455383, 'Val/mean miou_metric': 0.9609742164611816, 'Val/mean f1': 0.9766619205474854, 'Val/mean precision': 0.9739319086074829, 'Val/mean recall': 0.9794073700904846, 'Val/mean hd95_metric': 4.476895332336426} +Epoch [3851/4000] Training [1/16] Loss: 0.00221 +Epoch [3851/4000] Training [2/16] Loss: 0.00217 +Epoch [3851/4000] Training [3/16] Loss: 0.00163 +Epoch [3851/4000] Training [4/16] Loss: 0.00233 +Epoch [3851/4000] Training [5/16] Loss: 0.00262 +Epoch [3851/4000] Training [6/16] Loss: 0.00221 +Epoch [3851/4000] Training [7/16] Loss: 0.00343 +Epoch [3851/4000] Training [8/16] Loss: 0.00346 +Epoch [3851/4000] Training [9/16] Loss: 0.00203 +Epoch [3851/4000] Training [10/16] Loss: 0.00257 +Epoch [3851/4000] Training [11/16] Loss: 0.00225 +Epoch [3851/4000] Training [12/16] Loss: 0.00182 +Epoch [3851/4000] Training [13/16] Loss: 0.00269 +Epoch [3851/4000] Training [14/16] Loss: 0.00202 +Epoch [3851/4000] Training [15/16] Loss: 0.00151 +Epoch [3851/4000] Training [16/16] Loss: 0.00176 +Epoch [3851/4000] Training metric {'Train/mean dice_metric': 0.9988987445831299, 'Train/mean miou_metric': 0.9975214004516602, 'Train/mean f1': 0.9939103126525879, 'Train/mean precision': 0.9893717765808105, 'Train/mean recall': 0.9984906911849976, 'Train/mean hd95_metric': 0.48401179909706116} +Epoch [3851/4000] Validation [1/4] Loss: 0.38334 focal_loss 0.32126 dice_loss 0.06209 +Epoch [3851/4000] Validation [2/4] Loss: 0.66646 focal_loss 0.48923 dice_loss 0.17723 +Epoch [3851/4000] Validation [3/4] Loss: 0.28479 focal_loss 0.22152 dice_loss 0.06327 +Epoch [3851/4000] Validation [4/4] Loss: 0.47665 focal_loss 0.37316 dice_loss 0.10349 +Epoch [3851/4000] Validation metric {'Val/mean dice_metric': 0.9744235277175903, 'Val/mean miou_metric': 0.9604776501655579, 'Val/mean f1': 0.9762485027313232, 'Val/mean precision': 0.9745506048202515, 'Val/mean recall': 0.9779523611068726, 'Val/mean hd95_metric': 5.182318210601807} +Cheakpoint... +Epoch [3851/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744235277175903, 'Val/mean miou_metric': 0.9604776501655579, 'Val/mean f1': 0.9762485027313232, 'Val/mean precision': 0.9745506048202515, 'Val/mean recall': 0.9779523611068726, 'Val/mean hd95_metric': 5.182318210601807} +Epoch [3852/4000] Training [1/16] Loss: 0.00186 +Epoch [3852/4000] Training [2/16] Loss: 0.00387 +Epoch [3852/4000] Training [3/16] Loss: 0.00175 +Epoch [3852/4000] Training [4/16] Loss: 0.00258 +Epoch [3852/4000] Training [5/16] Loss: 0.00415 +Epoch [3852/4000] Training [6/16] Loss: 0.00195 +Epoch [3852/4000] Training [7/16] Loss: 0.00210 +Epoch [3852/4000] Training [8/16] Loss: 0.00228 +Epoch [3852/4000] Training [9/16] Loss: 0.00200 +Epoch [3852/4000] Training [10/16] Loss: 0.00190 +Epoch [3852/4000] Training [11/16] Loss: 0.00202 +Epoch [3852/4000] Training [12/16] Loss: 0.00226 +Epoch [3852/4000] Training [13/16] Loss: 0.00174 +Epoch [3852/4000] Training [14/16] Loss: 0.00373 +Epoch [3852/4000] Training [15/16] Loss: 0.00253 +Epoch [3852/4000] Training [16/16] Loss: 0.00227 +Epoch [3852/4000] Training metric {'Train/mean dice_metric': 0.9988640546798706, 'Train/mean miou_metric': 0.9974499940872192, 'Train/mean f1': 0.9937506914138794, 'Train/mean precision': 0.9891445636749268, 'Train/mean recall': 0.9983997344970703, 'Train/mean hd95_metric': 0.5015202164649963} +Epoch [3852/4000] Validation [1/4] Loss: 0.39436 focal_loss 0.33184 dice_loss 0.06252 +Epoch [3852/4000] Validation [2/4] Loss: 0.54155 focal_loss 0.40761 dice_loss 0.13394 +Epoch [3852/4000] Validation [3/4] Loss: 0.52729 focal_loss 0.43752 dice_loss 0.08977 +Epoch [3852/4000] Validation [4/4] Loss: 0.37374 focal_loss 0.28236 dice_loss 0.09138 +Epoch [3852/4000] Validation metric {'Val/mean dice_metric': 0.974933922290802, 'Val/mean miou_metric': 0.9609335064888, 'Val/mean f1': 0.9765310287475586, 'Val/mean precision': 0.974051296710968, 'Val/mean recall': 0.9790234565734863, 'Val/mean hd95_metric': 4.686107635498047} +Cheakpoint... +Epoch [3852/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974933922290802, 'Val/mean miou_metric': 0.9609335064888, 'Val/mean f1': 0.9765310287475586, 'Val/mean precision': 0.974051296710968, 'Val/mean recall': 0.9790234565734863, 'Val/mean hd95_metric': 4.686107635498047} +Epoch [3853/4000] Training [1/16] Loss: 0.00188 +Epoch [3853/4000] Training [2/16] Loss: 0.00213 +Epoch [3853/4000] Training [3/16] Loss: 0.00195 +Epoch [3853/4000] Training [4/16] Loss: 0.00389 +Epoch [3853/4000] Training [5/16] Loss: 0.00180 +Epoch [3853/4000] Training [6/16] Loss: 0.00256 +Epoch [3853/4000] Training [7/16] Loss: 0.00201 +Epoch [3853/4000] Training [8/16] Loss: 0.00181 +Epoch [3853/4000] Training [9/16] Loss: 0.00281 +Epoch [3853/4000] Training [10/16] Loss: 0.00211 +Epoch [3853/4000] Training [11/16] Loss: 0.00221 +Epoch [3853/4000] Training [12/16] Loss: 0.00192 +Epoch [3853/4000] Training [13/16] Loss: 0.00168 +Epoch [3853/4000] Training [14/16] Loss: 0.00289 +Epoch [3853/4000] Training [15/16] Loss: 0.00217 +Epoch [3853/4000] Training [16/16] Loss: 0.00270 +Epoch [3853/4000] Training metric {'Train/mean dice_metric': 0.9987683296203613, 'Train/mean miou_metric': 0.9972611665725708, 'Train/mean f1': 0.9938229322433472, 'Train/mean precision': 0.9893214106559753, 'Train/mean recall': 0.998365581035614, 'Train/mean hd95_metric': 0.4967072606086731} +Epoch [3853/4000] Validation [1/4] Loss: 0.38379 focal_loss 0.32339 dice_loss 0.06039 +Epoch [3853/4000] Validation [2/4] Loss: 0.60236 focal_loss 0.44822 dice_loss 0.15415 +Epoch [3853/4000] Validation [3/4] Loss: 0.28825 focal_loss 0.22449 dice_loss 0.06376 +Epoch [3853/4000] Validation [4/4] Loss: 0.36403 focal_loss 0.27844 dice_loss 0.08559 +Epoch [3853/4000] Validation metric {'Val/mean dice_metric': 0.9751415252685547, 'Val/mean miou_metric': 0.961147665977478, 'Val/mean f1': 0.9765536785125732, 'Val/mean precision': 0.9742305278778076, 'Val/mean recall': 0.9788879752159119, 'Val/mean hd95_metric': 4.922210216522217} +Cheakpoint... +Epoch [3853/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751415252685547, 'Val/mean miou_metric': 0.961147665977478, 'Val/mean f1': 0.9765536785125732, 'Val/mean precision': 0.9742305278778076, 'Val/mean recall': 0.9788879752159119, 'Val/mean hd95_metric': 4.922210216522217} +Epoch [3854/4000] Training [1/16] Loss: 0.00201 +Epoch [3854/4000] Training [2/16] Loss: 0.00152 +Epoch [3854/4000] Training [3/16] Loss: 0.00250 +Epoch [3854/4000] Training [4/16] Loss: 0.00225 +Epoch [3854/4000] Training [5/16] Loss: 0.00282 +Epoch [3854/4000] Training [6/16] Loss: 0.00212 +Epoch [3854/4000] Training [7/16] Loss: 0.00212 +Epoch [3854/4000] Training [8/16] Loss: 0.00175 +Epoch [3854/4000] Training [9/16] Loss: 0.00209 +Epoch [3854/4000] Training [10/16] Loss: 0.00475 +Epoch [3854/4000] Training [11/16] Loss: 0.00316 +Epoch [3854/4000] Training [12/16] Loss: 0.00257 +Epoch [3854/4000] Training [13/16] Loss: 0.00176 +Epoch [3854/4000] Training [14/16] Loss: 0.00322 +Epoch [3854/4000] Training [15/16] Loss: 0.00237 +Epoch [3854/4000] Training [16/16] Loss: 0.00225 +Epoch [3854/4000] Training metric {'Train/mean dice_metric': 0.998857855796814, 'Train/mean miou_metric': 0.9974414110183716, 'Train/mean f1': 0.9939189553260803, 'Train/mean precision': 0.989374041557312, 'Train/mean recall': 0.9985057711601257, 'Train/mean hd95_metric': 0.4979431927204132} +Epoch [3854/4000] Validation [1/4] Loss: 0.38807 focal_loss 0.32358 dice_loss 0.06449 +Epoch [3854/4000] Validation [2/4] Loss: 0.46978 focal_loss 0.36151 dice_loss 0.10827 +Epoch [3854/4000] Validation [3/4] Loss: 0.54373 focal_loss 0.44535 dice_loss 0.09839 +Epoch [3854/4000] Validation [4/4] Loss: 0.35273 focal_loss 0.26819 dice_loss 0.08453 +Epoch [3854/4000] Validation metric {'Val/mean dice_metric': 0.9751905202865601, 'Val/mean miou_metric': 0.9613391160964966, 'Val/mean f1': 0.9768682718276978, 'Val/mean precision': 0.9739739894866943, 'Val/mean recall': 0.979779839515686, 'Val/mean hd95_metric': 4.8886871337890625} +Cheakpoint... +Epoch [3854/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751905202865601, 'Val/mean miou_metric': 0.9613391160964966, 'Val/mean f1': 0.9768682718276978, 'Val/mean precision': 0.9739739894866943, 'Val/mean recall': 0.979779839515686, 'Val/mean hd95_metric': 4.8886871337890625} +Epoch [3855/4000] Training [1/16] Loss: 0.00182 +Epoch [3855/4000] Training [2/16] Loss: 0.00442 +Epoch [3855/4000] Training [3/16] Loss: 0.00218 +Epoch [3855/4000] Training [4/16] Loss: 0.00313 +Epoch [3855/4000] Training [5/16] Loss: 0.00268 +Epoch [3855/4000] Training [6/16] Loss: 0.00343 +Epoch [3855/4000] Training [7/16] Loss: 0.00177 +Epoch [3855/4000] Training [8/16] Loss: 0.00329 +Epoch [3855/4000] Training [9/16] Loss: 0.00187 +Epoch [3855/4000] Training [10/16] Loss: 0.00201 +Epoch [3855/4000] Training [11/16] Loss: 0.00291 +Epoch [3855/4000] Training [12/16] Loss: 0.00214 +Epoch [3855/4000] Training [13/16] Loss: 0.00198 +Epoch [3855/4000] Training [14/16] Loss: 0.00232 +Epoch [3855/4000] Training [15/16] Loss: 0.00225 +Epoch [3855/4000] Training [16/16] Loss: 0.00232 +Epoch [3855/4000] Training metric {'Train/mean dice_metric': 0.9987959861755371, 'Train/mean miou_metric': 0.9973098635673523, 'Train/mean f1': 0.993739664554596, 'Train/mean precision': 0.9891323447227478, 'Train/mean recall': 0.9983901381492615, 'Train/mean hd95_metric': 0.5221955180168152} +Epoch [3855/4000] Validation [1/4] Loss: 0.42700 focal_loss 0.36371 dice_loss 0.06329 +Epoch [3855/4000] Validation [2/4] Loss: 0.49214 focal_loss 0.38069 dice_loss 0.11145 +Epoch [3855/4000] Validation [3/4] Loss: 0.55385 focal_loss 0.45490 dice_loss 0.09895 +Epoch [3855/4000] Validation [4/4] Loss: 0.34438 focal_loss 0.25703 dice_loss 0.08736 +Epoch [3855/4000] Validation metric {'Val/mean dice_metric': 0.9738033413887024, 'Val/mean miou_metric': 0.9600003957748413, 'Val/mean f1': 0.9763036966323853, 'Val/mean precision': 0.9744479060173035, 'Val/mean recall': 0.978166401386261, 'Val/mean hd95_metric': 4.803030967712402} +Cheakpoint... +Epoch [3855/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738033413887024, 'Val/mean miou_metric': 0.9600003957748413, 'Val/mean f1': 0.9763036966323853, 'Val/mean precision': 0.9744479060173035, 'Val/mean recall': 0.978166401386261, 'Val/mean hd95_metric': 4.803030967712402} +Epoch [3856/4000] Training [1/16] Loss: 0.00145 +Epoch [3856/4000] Training [2/16] Loss: 0.00221 +Epoch [3856/4000] Training [3/16] Loss: 0.00234 +Epoch [3856/4000] Training [4/16] Loss: 0.00262 +Epoch [3856/4000] Training [5/16] Loss: 0.00264 +Epoch [3856/4000] Training [6/16] Loss: 0.00216 +Epoch [3856/4000] Training [7/16] Loss: 0.00402 +Epoch [3856/4000] Training [8/16] Loss: 0.00205 +Epoch [3856/4000] Training [9/16] Loss: 0.00255 +Epoch [3856/4000] Training [10/16] Loss: 0.00203 +Epoch [3856/4000] Training [11/16] Loss: 0.00343 +Epoch [3856/4000] Training [12/16] Loss: 0.00185 +Epoch [3856/4000] Training [13/16] Loss: 0.00248 +Epoch [3856/4000] Training [14/16] Loss: 0.00288 +Epoch [3856/4000] Training [15/16] Loss: 0.00327 +Epoch [3856/4000] Training [16/16] Loss: 0.00186 +Epoch [3856/4000] Training metric {'Train/mean dice_metric': 0.9987972974777222, 'Train/mean miou_metric': 0.9973222017288208, 'Train/mean f1': 0.9938884377479553, 'Train/mean precision': 0.989418625831604, 'Train/mean recall': 0.9983987808227539, 'Train/mean hd95_metric': 0.5381134748458862} +Epoch [3856/4000] Validation [1/4] Loss: 0.38598 focal_loss 0.32189 dice_loss 0.06409 +Epoch [3856/4000] Validation [2/4] Loss: 0.48626 focal_loss 0.37558 dice_loss 0.11068 +Epoch [3856/4000] Validation [3/4] Loss: 0.53402 focal_loss 0.43656 dice_loss 0.09746 +Epoch [3856/4000] Validation [4/4] Loss: 0.49150 focal_loss 0.38436 dice_loss 0.10713 +Epoch [3856/4000] Validation metric {'Val/mean dice_metric': 0.9744459390640259, 'Val/mean miou_metric': 0.9602512121200562, 'Val/mean f1': 0.9763289093971252, 'Val/mean precision': 0.97450190782547, 'Val/mean recall': 0.9781628847122192, 'Val/mean hd95_metric': 4.833022594451904} +Cheakpoint... +Epoch [3856/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744459390640259, 'Val/mean miou_metric': 0.9602512121200562, 'Val/mean f1': 0.9763289093971252, 'Val/mean precision': 0.97450190782547, 'Val/mean recall': 0.9781628847122192, 'Val/mean hd95_metric': 4.833022594451904} +Epoch [3857/4000] Training [1/16] Loss: 0.00251 +Epoch [3857/4000] Training [2/16] Loss: 0.00303 +Epoch [3857/4000] Training [3/16] Loss: 0.00253 +Epoch [3857/4000] Training [4/16] Loss: 0.00179 +Epoch [3857/4000] Training [5/16] Loss: 0.00324 +Epoch [3857/4000] Training [6/16] Loss: 0.00217 +Epoch [3857/4000] Training [7/16] Loss: 0.00202 +Epoch [3857/4000] Training [8/16] Loss: 0.00292 +Epoch [3857/4000] Training [9/16] Loss: 0.00257 +Epoch [3857/4000] Training [10/16] Loss: 0.00284 +Epoch [3857/4000] Training [11/16] Loss: 0.00227 +Epoch [3857/4000] Training [12/16] Loss: 0.00238 +Epoch [3857/4000] Training [13/16] Loss: 0.00384 +Epoch [3857/4000] Training [14/16] Loss: 0.00239 +Epoch [3857/4000] Training [15/16] Loss: 0.00187 +Epoch [3857/4000] Training [16/16] Loss: 0.00231 +Epoch [3857/4000] Training metric {'Train/mean dice_metric': 0.9988601207733154, 'Train/mean miou_metric': 0.9974409937858582, 'Train/mean f1': 0.9938228130340576, 'Train/mean precision': 0.9892633557319641, 'Train/mean recall': 0.9984245300292969, 'Train/mean hd95_metric': 0.4728791117668152} +Epoch [3857/4000] Validation [1/4] Loss: 0.41847 focal_loss 0.35630 dice_loss 0.06218 +Epoch [3857/4000] Validation [2/4] Loss: 0.54079 focal_loss 0.40726 dice_loss 0.13354 +Epoch [3857/4000] Validation [3/4] Loss: 0.52704 focal_loss 0.43568 dice_loss 0.09136 +Epoch [3857/4000] Validation [4/4] Loss: 0.45860 focal_loss 0.35217 dice_loss 0.10643 +Epoch [3857/4000] Validation metric {'Val/mean dice_metric': 0.974450409412384, 'Val/mean miou_metric': 0.9603344798088074, 'Val/mean f1': 0.976441502571106, 'Val/mean precision': 0.9744839668273926, 'Val/mean recall': 0.9784069657325745, 'Val/mean hd95_metric': 4.656386852264404} +Cheakpoint... +Epoch [3857/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974450409412384, 'Val/mean miou_metric': 0.9603344798088074, 'Val/mean f1': 0.976441502571106, 'Val/mean precision': 0.9744839668273926, 'Val/mean recall': 0.9784069657325745, 'Val/mean hd95_metric': 4.656386852264404} +Epoch [3858/4000] Training [1/16] Loss: 0.00354 +Epoch [3858/4000] Training [2/16] Loss: 0.00174 +Epoch [3858/4000] Training [3/16] Loss: 0.00198 +Epoch [3858/4000] Training [4/16] Loss: 0.00376 +Epoch [3858/4000] Training [5/16] Loss: 0.00247 +Epoch [3858/4000] Training [6/16] Loss: 0.00210 +Epoch [3858/4000] Training [7/16] Loss: 0.00295 +Epoch [3858/4000] Training [8/16] Loss: 0.00195 +Epoch [3858/4000] Training [9/16] Loss: 0.00308 +Epoch [3858/4000] Training [10/16] Loss: 0.00278 +Epoch [3858/4000] Training [11/16] Loss: 0.00166 +Epoch [3858/4000] Training [12/16] Loss: 0.00174 +Epoch [3858/4000] Training [13/16] Loss: 0.00177 +Epoch [3858/4000] Training [14/16] Loss: 0.00208 +Epoch [3858/4000] Training [15/16] Loss: 0.00292 +Epoch [3858/4000] Training [16/16] Loss: 0.00240 +Epoch [3858/4000] Training metric {'Train/mean dice_metric': 0.9988148808479309, 'Train/mean miou_metric': 0.9973534345626831, 'Train/mean f1': 0.9938167333602905, 'Train/mean precision': 0.9893122315406799, 'Train/mean recall': 0.9983624815940857, 'Train/mean hd95_metric': 0.501980721950531} +Epoch [3858/4000] Validation [1/4] Loss: 0.39653 focal_loss 0.33234 dice_loss 0.06419 +Epoch [3858/4000] Validation [2/4] Loss: 0.94600 focal_loss 0.76044 dice_loss 0.18556 +Epoch [3858/4000] Validation [3/4] Loss: 0.52704 focal_loss 0.43345 dice_loss 0.09359 +Epoch [3858/4000] Validation [4/4] Loss: 0.33768 focal_loss 0.23149 dice_loss 0.10619 +Epoch [3858/4000] Validation metric {'Val/mean dice_metric': 0.9740772247314453, 'Val/mean miou_metric': 0.9603573083877563, 'Val/mean f1': 0.9763263463973999, 'Val/mean precision': 0.9729132652282715, 'Val/mean recall': 0.9797636866569519, 'Val/mean hd95_metric': 5.357568264007568} +Cheakpoint... +Epoch [3858/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740772247314453, 'Val/mean miou_metric': 0.9603573083877563, 'Val/mean f1': 0.9763263463973999, 'Val/mean precision': 0.9729132652282715, 'Val/mean recall': 0.9797636866569519, 'Val/mean hd95_metric': 5.357568264007568} +Epoch [3859/4000] Training [1/16] Loss: 0.00368 +Epoch [3859/4000] Training [2/16] Loss: 0.00244 +Epoch [3859/4000] Training [3/16] Loss: 0.00227 +Epoch [3859/4000] Training [4/16] Loss: 0.00207 +Epoch [3859/4000] Training [5/16] Loss: 0.00185 +Epoch [3859/4000] Training [6/16] Loss: 0.00130 +Epoch [3859/4000] Training [7/16] Loss: 0.00263 +Epoch [3859/4000] Training [8/16] Loss: 0.00309 +Epoch [3859/4000] Training [9/16] Loss: 0.00315 +Epoch [3859/4000] Training [10/16] Loss: 0.00318 +Epoch [3859/4000] Training [11/16] Loss: 0.00283 +Epoch [3859/4000] Training [12/16] Loss: 0.00170 +Epoch [3859/4000] Training [13/16] Loss: 0.00178 +Epoch [3859/4000] Training [14/16] Loss: 0.00193 +Epoch [3859/4000] Training [15/16] Loss: 0.00152 +Epoch [3859/4000] Training [16/16] Loss: 0.00163 +Epoch [3859/4000] Training metric {'Train/mean dice_metric': 0.9987621307373047, 'Train/mean miou_metric': 0.9972497820854187, 'Train/mean f1': 0.9938249588012695, 'Train/mean precision': 0.9893049597740173, 'Train/mean recall': 0.9983863830566406, 'Train/mean hd95_metric': 0.4915316104888916} +Epoch [3859/4000] Validation [1/4] Loss: 0.46713 focal_loss 0.40278 dice_loss 0.06435 +Epoch [3859/4000] Validation [2/4] Loss: 0.60530 focal_loss 0.45206 dice_loss 0.15324 +Epoch [3859/4000] Validation [3/4] Loss: 0.28351 focal_loss 0.21974 dice_loss 0.06377 +Epoch [3859/4000] Validation [4/4] Loss: 0.42449 focal_loss 0.32196 dice_loss 0.10253 +Epoch [3859/4000] Validation metric {'Val/mean dice_metric': 0.9760381579399109, 'Val/mean miou_metric': 0.9619145393371582, 'Val/mean f1': 0.9771187901496887, 'Val/mean precision': 0.9748868346214294, 'Val/mean recall': 0.9793609380722046, 'Val/mean hd95_metric': 4.594628810882568} +Cheakpoint... +Epoch [3859/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9760381579399109, 'Val/mean miou_metric': 0.9619145393371582, 'Val/mean f1': 0.9771187901496887, 'Val/mean precision': 0.9748868346214294, 'Val/mean recall': 0.9793609380722046, 'Val/mean hd95_metric': 4.594628810882568} +Epoch [3860/4000] Training [1/16] Loss: 0.00176 +Epoch [3860/4000] Training [2/16] Loss: 0.00300 +Epoch [3860/4000] Training [3/16] Loss: 0.00285 +Epoch [3860/4000] Training [4/16] Loss: 0.00218 +Epoch [3860/4000] Training [5/16] Loss: 0.00286 +Epoch [3860/4000] Training [6/16] Loss: 0.00280 +Epoch [3860/4000] Training [7/16] Loss: 0.00164 +Epoch [3860/4000] Training [8/16] Loss: 0.00180 +Epoch [3860/4000] Training [9/16] Loss: 0.00211 +Epoch [3860/4000] Training [10/16] Loss: 0.00232 +Epoch [3860/4000] Training [11/16] Loss: 0.00207 +Epoch [3860/4000] Training [12/16] Loss: 0.00208 +Epoch [3860/4000] Training [13/16] Loss: 0.00298 +Epoch [3860/4000] Training [14/16] Loss: 0.00257 +Epoch [3860/4000] Training [15/16] Loss: 0.00383 +Epoch [3860/4000] Training [16/16] Loss: 0.00240 +Epoch [3860/4000] Training metric {'Train/mean dice_metric': 0.9987174868583679, 'Train/mean miou_metric': 0.9971351623535156, 'Train/mean f1': 0.9932919144630432, 'Train/mean precision': 0.9883690476417542, 'Train/mean recall': 0.9982640743255615, 'Train/mean hd95_metric': 0.5459259748458862} +Epoch [3860/4000] Validation [1/4] Loss: 0.46521 focal_loss 0.39870 dice_loss 0.06652 +Epoch [3860/4000] Validation [2/4] Loss: 0.89443 focal_loss 0.69641 dice_loss 0.19802 +Epoch [3860/4000] Validation [3/4] Loss: 0.54738 focal_loss 0.45593 dice_loss 0.09145 +Epoch [3860/4000] Validation [4/4] Loss: 0.43486 focal_loss 0.33084 dice_loss 0.10402 +Epoch [3860/4000] Validation metric {'Val/mean dice_metric': 0.9734755754470825, 'Val/mean miou_metric': 0.9592851400375366, 'Val/mean f1': 0.975604236125946, 'Val/mean precision': 0.9730810523033142, 'Val/mean recall': 0.9781403541564941, 'Val/mean hd95_metric': 4.861084938049316} +Cheakpoint... +Epoch [3860/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734755754470825, 'Val/mean miou_metric': 0.9592851400375366, 'Val/mean f1': 0.975604236125946, 'Val/mean precision': 0.9730810523033142, 'Val/mean recall': 0.9781403541564941, 'Val/mean hd95_metric': 4.861084938049316} +Epoch [3861/4000] Training [1/16] Loss: 0.00290 +Epoch [3861/4000] Training [2/16] Loss: 0.00189 +Epoch [3861/4000] Training [3/16] Loss: 0.00273 +Epoch [3861/4000] Training [4/16] Loss: 0.00253 +Epoch [3861/4000] Training [5/16] Loss: 0.00244 +Epoch [3861/4000] Training [6/16] Loss: 0.00281 +Epoch [3861/4000] Training [7/16] Loss: 0.00189 +Epoch [3861/4000] Training [8/16] Loss: 0.00419 +Epoch [3861/4000] Training [9/16] Loss: 0.00182 +Epoch [3861/4000] Training [10/16] Loss: 0.00137 +Epoch [3861/4000] Training [11/16] Loss: 0.00146 +Epoch [3861/4000] Training [12/16] Loss: 0.00194 +Epoch [3861/4000] Training [13/16] Loss: 0.00232 +Epoch [3861/4000] Training [14/16] Loss: 0.00183 +Epoch [3861/4000] Training [15/16] Loss: 0.00273 +Epoch [3861/4000] Training [16/16] Loss: 0.00280 +Epoch [3861/4000] Training metric {'Train/mean dice_metric': 0.9987369775772095, 'Train/mean miou_metric': 0.9971977472305298, 'Train/mean f1': 0.9936754703521729, 'Train/mean precision': 0.989101231098175, 'Train/mean recall': 0.9982922077178955, 'Train/mean hd95_metric': 0.5413638353347778} +Epoch [3861/4000] Validation [1/4] Loss: 0.40348 focal_loss 0.34049 dice_loss 0.06299 +Epoch [3861/4000] Validation [2/4] Loss: 0.53449 focal_loss 0.40578 dice_loss 0.12871 +Epoch [3861/4000] Validation [3/4] Loss: 0.53214 focal_loss 0.44142 dice_loss 0.09073 +Epoch [3861/4000] Validation [4/4] Loss: 0.35392 focal_loss 0.25995 dice_loss 0.09397 +Epoch [3861/4000] Validation metric {'Val/mean dice_metric': 0.9739850163459778, 'Val/mean miou_metric': 0.9593557119369507, 'Val/mean f1': 0.9756230711936951, 'Val/mean precision': 0.9735465049743652, 'Val/mean recall': 0.9777085781097412, 'Val/mean hd95_metric': 5.338995456695557} +Cheakpoint... +Epoch [3861/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739850163459778, 'Val/mean miou_metric': 0.9593557119369507, 'Val/mean f1': 0.9756230711936951, 'Val/mean precision': 0.9735465049743652, 'Val/mean recall': 0.9777085781097412, 'Val/mean hd95_metric': 5.338995456695557} +Epoch [3862/4000] Training [1/16] Loss: 0.00180 +Epoch [3862/4000] Training [2/16] Loss: 0.00157 +Epoch [3862/4000] Training [3/16] Loss: 0.00232 +Epoch [3862/4000] Training [4/16] Loss: 0.00226 +Epoch [3862/4000] Training [5/16] Loss: 0.00191 +Epoch [3862/4000] Training [6/16] Loss: 0.00201 +Epoch [3862/4000] Training [7/16] Loss: 0.00232 +Epoch [3862/4000] Training [8/16] Loss: 0.00208 +Epoch [3862/4000] Training [9/16] Loss: 0.00216 +Epoch [3862/4000] Training [10/16] Loss: 0.00329 +Epoch [3862/4000] Training [11/16] Loss: 0.00353 +Epoch [3862/4000] Training [12/16] Loss: 0.00191 +Epoch [3862/4000] Training [13/16] Loss: 0.00222 +Epoch [3862/4000] Training [14/16] Loss: 0.00410 +Epoch [3862/4000] Training [15/16] Loss: 0.00277 +Epoch [3862/4000] Training [16/16] Loss: 0.00196 +Epoch [3862/4000] Training metric {'Train/mean dice_metric': 0.9987213611602783, 'Train/mean miou_metric': 0.9971723556518555, 'Train/mean f1': 0.9936874508857727, 'Train/mean precision': 0.9891481995582581, 'Train/mean recall': 0.9982686042785645, 'Train/mean hd95_metric': 0.5595278739929199} +Epoch [3862/4000] Validation [1/4] Loss: 0.48264 focal_loss 0.41618 dice_loss 0.06645 +Epoch [3862/4000] Validation [2/4] Loss: 0.91799 focal_loss 0.71601 dice_loss 0.20198 +Epoch [3862/4000] Validation [3/4] Loss: 0.53100 focal_loss 0.44139 dice_loss 0.08961 +Epoch [3862/4000] Validation [4/4] Loss: 0.52768 focal_loss 0.40502 dice_loss 0.12265 +Epoch [3862/4000] Validation metric {'Val/mean dice_metric': 0.9745997190475464, 'Val/mean miou_metric': 0.9601373672485352, 'Val/mean f1': 0.9759331345558167, 'Val/mean precision': 0.9741131067276001, 'Val/mean recall': 0.9777598977088928, 'Val/mean hd95_metric': 4.871548175811768} +Cheakpoint... +Epoch [3862/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745997190475464, 'Val/mean miou_metric': 0.9601373672485352, 'Val/mean f1': 0.9759331345558167, 'Val/mean precision': 0.9741131067276001, 'Val/mean recall': 0.9777598977088928, 'Val/mean hd95_metric': 4.871548175811768} +Epoch [3863/4000] Training [1/16] Loss: 0.00193 +Epoch [3863/4000] Training [2/16] Loss: 0.00214 +Epoch [3863/4000] Training [3/16] Loss: 0.00171 +Epoch [3863/4000] Training [4/16] Loss: 0.00368 +Epoch [3863/4000] Training [5/16] Loss: 0.00203 +Epoch [3863/4000] Training [6/16] Loss: 0.00238 +Epoch [3863/4000] Training [7/16] Loss: 0.00240 +Epoch [3863/4000] Training [8/16] Loss: 0.00214 +Epoch [3863/4000] Training [9/16] Loss: 0.00256 +Epoch [3863/4000] Training [10/16] Loss: 0.00268 +Epoch [3863/4000] Training [11/16] Loss: 0.00192 +Epoch [3863/4000] Training [12/16] Loss: 0.00205 +Epoch [3863/4000] Training [13/16] Loss: 0.00167 +Epoch [3863/4000] Training [14/16] Loss: 0.00248 +Epoch [3863/4000] Training [15/16] Loss: 0.00157 +Epoch [3863/4000] Training [16/16] Loss: 0.00450 +Epoch [3863/4000] Training metric {'Train/mean dice_metric': 0.9988383650779724, 'Train/mean miou_metric': 0.9974058270454407, 'Train/mean f1': 0.9939135313034058, 'Train/mean precision': 0.9893900156021118, 'Train/mean recall': 0.9984785318374634, 'Train/mean hd95_metric': 0.5103309154510498} +Epoch [3863/4000] Validation [1/4] Loss: 0.42707 focal_loss 0.35988 dice_loss 0.06719 +Epoch [3863/4000] Validation [2/4] Loss: 0.48817 focal_loss 0.37751 dice_loss 0.11067 +Epoch [3863/4000] Validation [3/4] Loss: 0.27125 focal_loss 0.20635 dice_loss 0.06489 +Epoch [3863/4000] Validation [4/4] Loss: 0.34800 focal_loss 0.26069 dice_loss 0.08731 +Epoch [3863/4000] Validation metric {'Val/mean dice_metric': 0.9759179949760437, 'Val/mean miou_metric': 0.961828351020813, 'Val/mean f1': 0.9765482544898987, 'Val/mean precision': 0.9745422005653381, 'Val/mean recall': 0.9785626530647278, 'Val/mean hd95_metric': 5.121705055236816} +Cheakpoint... +Epoch [3863/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759179949760437, 'Val/mean miou_metric': 0.961828351020813, 'Val/mean f1': 0.9765482544898987, 'Val/mean precision': 0.9745422005653381, 'Val/mean recall': 0.9785626530647278, 'Val/mean hd95_metric': 5.121705055236816} +Epoch [3864/4000] Training [1/16] Loss: 0.00230 +Epoch [3864/4000] Training [2/16] Loss: 0.00171 +Epoch [3864/4000] Training [3/16] Loss: 0.00197 +Epoch [3864/4000] Training [4/16] Loss: 0.00329 +Epoch [3864/4000] Training [5/16] Loss: 0.00202 +Epoch [3864/4000] Training [6/16] Loss: 0.00215 +Epoch [3864/4000] Training [7/16] Loss: 0.00274 +Epoch [3864/4000] Training [8/16] Loss: 0.00220 +Epoch [3864/4000] Training [9/16] Loss: 0.00193 +Epoch [3864/4000] Training [10/16] Loss: 0.00162 +Epoch [3864/4000] Training [11/16] Loss: 0.00235 +Epoch [3864/4000] Training [12/16] Loss: 0.00205 +Epoch [3864/4000] Training [13/16] Loss: 0.00299 +Epoch [3864/4000] Training [14/16] Loss: 0.00329 +Epoch [3864/4000] Training [15/16] Loss: 0.00209 +Epoch [3864/4000] Training [16/16] Loss: 0.00216 +Epoch [3864/4000] Training metric {'Train/mean dice_metric': 0.9988287687301636, 'Train/mean miou_metric': 0.9973838925361633, 'Train/mean f1': 0.9938505291938782, 'Train/mean precision': 0.9893524646759033, 'Train/mean recall': 0.998389720916748, 'Train/mean hd95_metric': 0.5029572248458862} +Epoch [3864/4000] Validation [1/4] Loss: 0.36603 focal_loss 0.30470 dice_loss 0.06133 +Epoch [3864/4000] Validation [2/4] Loss: 0.63014 focal_loss 0.47245 dice_loss 0.15769 +Epoch [3864/4000] Validation [3/4] Loss: 0.52607 focal_loss 0.43577 dice_loss 0.09030 +Epoch [3864/4000] Validation [4/4] Loss: 0.37158 focal_loss 0.27672 dice_loss 0.09486 +Epoch [3864/4000] Validation metric {'Val/mean dice_metric': 0.9756466746330261, 'Val/mean miou_metric': 0.961469829082489, 'Val/mean f1': 0.9764310717582703, 'Val/mean precision': 0.9744935631752014, 'Val/mean recall': 0.9783761501312256, 'Val/mean hd95_metric': 4.742024898529053} +Cheakpoint... +Epoch [3864/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756466746330261, 'Val/mean miou_metric': 0.961469829082489, 'Val/mean f1': 0.9764310717582703, 'Val/mean precision': 0.9744935631752014, 'Val/mean recall': 0.9783761501312256, 'Val/mean hd95_metric': 4.742024898529053} +Epoch [3865/4000] Training [1/16] Loss: 0.00240 +Epoch [3865/4000] Training [2/16] Loss: 0.00197 +Epoch [3865/4000] Training [3/16] Loss: 0.00195 +Epoch [3865/4000] Training [4/16] Loss: 0.00192 +Epoch [3865/4000] Training [5/16] Loss: 0.00209 +Epoch [3865/4000] Training [6/16] Loss: 0.00263 +Epoch [3865/4000] Training [7/16] Loss: 0.00198 +Epoch [3865/4000] Training [8/16] Loss: 0.00195 +Epoch [3865/4000] Training [9/16] Loss: 0.00278 +Epoch [3865/4000] Training [10/16] Loss: 0.00205 +Epoch [3865/4000] Training [11/16] Loss: 0.00228 +Epoch [3865/4000] Training [12/16] Loss: 0.00215 +Epoch [3865/4000] Training [13/16] Loss: 0.00201 +Epoch [3865/4000] Training [14/16] Loss: 0.00386 +Epoch [3865/4000] Training [15/16] Loss: 0.00323 +Epoch [3865/4000] Training [16/16] Loss: 0.00207 +Epoch [3865/4000] Training metric {'Train/mean dice_metric': 0.9988197088241577, 'Train/mean miou_metric': 0.997346043586731, 'Train/mean f1': 0.9934495687484741, 'Train/mean precision': 0.9886894822120667, 'Train/mean recall': 0.9982556700706482, 'Train/mean hd95_metric': 0.4965876340866089} +Epoch [3865/4000] Validation [1/4] Loss: 0.38755 focal_loss 0.32702 dice_loss 0.06053 +Epoch [3865/4000] Validation [2/4] Loss: 0.47646 focal_loss 0.36847 dice_loss 0.10800 +Epoch [3865/4000] Validation [3/4] Loss: 0.28233 focal_loss 0.21909 dice_loss 0.06323 +Epoch [3865/4000] Validation [4/4] Loss: 0.36470 focal_loss 0.27362 dice_loss 0.09109 +Epoch [3865/4000] Validation metric {'Val/mean dice_metric': 0.9756650924682617, 'Val/mean miou_metric': 0.9614086151123047, 'Val/mean f1': 0.9762963652610779, 'Val/mean precision': 0.9736562371253967, 'Val/mean recall': 0.9789507389068604, 'Val/mean hd95_metric': 4.961399078369141} +Cheakpoint... +Epoch [3865/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756650924682617, 'Val/mean miou_metric': 0.9614086151123047, 'Val/mean f1': 0.9762963652610779, 'Val/mean precision': 0.9736562371253967, 'Val/mean recall': 0.9789507389068604, 'Val/mean hd95_metric': 4.961399078369141} +Epoch [3866/4000] Training [1/16] Loss: 0.00231 +Epoch [3866/4000] Training [2/16] Loss: 0.00214 +Epoch [3866/4000] Training [3/16] Loss: 0.00185 +Epoch [3866/4000] Training [4/16] Loss: 0.00340 +Epoch [3866/4000] Training [5/16] Loss: 0.00205 +Epoch [3866/4000] Training [6/16] Loss: 0.00197 +Epoch [3866/4000] Training [7/16] Loss: 0.00262 +Epoch [3866/4000] Training [8/16] Loss: 0.00192 +Epoch [3866/4000] Training [9/16] Loss: 0.00293 +Epoch [3866/4000] Training [10/16] Loss: 0.00154 +Epoch [3866/4000] Training [11/16] Loss: 0.00280 +Epoch [3866/4000] Training [12/16] Loss: 0.00368 +Epoch [3866/4000] Training [13/16] Loss: 0.00240 +Epoch [3866/4000] Training [14/16] Loss: 0.00300 +Epoch [3866/4000] Training [15/16] Loss: 0.00182 +Epoch [3866/4000] Training [16/16] Loss: 0.00226 +Epoch [3866/4000] Training metric {'Train/mean dice_metric': 0.9988191723823547, 'Train/mean miou_metric': 0.9973644614219666, 'Train/mean f1': 0.9937403202056885, 'Train/mean precision': 0.9892525672912598, 'Train/mean recall': 0.9982689619064331, 'Train/mean hd95_metric': 0.497104674577713} +Epoch [3866/4000] Validation [1/4] Loss: 0.42054 focal_loss 0.35846 dice_loss 0.06207 +Epoch [3866/4000] Validation [2/4] Loss: 0.48581 focal_loss 0.37487 dice_loss 0.11094 +Epoch [3866/4000] Validation [3/4] Loss: 0.53923 focal_loss 0.44755 dice_loss 0.09168 +Epoch [3866/4000] Validation [4/4] Loss: 0.44172 focal_loss 0.33347 dice_loss 0.10825 +Epoch [3866/4000] Validation metric {'Val/mean dice_metric': 0.9749903678894043, 'Val/mean miou_metric': 0.9610821604728699, 'Val/mean f1': 0.9766346216201782, 'Val/mean precision': 0.9742985367774963, 'Val/mean recall': 0.9789817333221436, 'Val/mean hd95_metric': 4.585683345794678} +Cheakpoint... +Epoch [3866/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749903678894043, 'Val/mean miou_metric': 0.9610821604728699, 'Val/mean f1': 0.9766346216201782, 'Val/mean precision': 0.9742985367774963, 'Val/mean recall': 0.9789817333221436, 'Val/mean hd95_metric': 4.585683345794678} +Epoch [3867/4000] Training [1/16] Loss: 0.00252 +Epoch [3867/4000] Training [2/16] Loss: 0.00302 +Epoch [3867/4000] Training [3/16] Loss: 0.00199 +Epoch [3867/4000] Training [4/16] Loss: 0.00248 +Epoch [3867/4000] Training [5/16] Loss: 0.00184 +Epoch [3867/4000] Training [6/16] Loss: 0.00170 +Epoch [3867/4000] Training [7/16] Loss: 0.00244 +Epoch [3867/4000] Training [8/16] Loss: 0.00340 +Epoch [3867/4000] Training [9/16] Loss: 0.00173 +Epoch [3867/4000] Training [10/16] Loss: 0.00216 +Epoch [3867/4000] Training [11/16] Loss: 0.00225 +Epoch [3867/4000] Training [12/16] Loss: 0.00268 +Epoch [3867/4000] Training [13/16] Loss: 0.00236 +Epoch [3867/4000] Training [14/16] Loss: 0.00282 +Epoch [3867/4000] Training [15/16] Loss: 0.00187 +Epoch [3867/4000] Training [16/16] Loss: 0.00238 +Epoch [3867/4000] Training metric {'Train/mean dice_metric': 0.9987902641296387, 'Train/mean miou_metric': 0.9973072409629822, 'Train/mean f1': 0.9937624931335449, 'Train/mean precision': 0.9892156720161438, 'Train/mean recall': 0.9983513355255127, 'Train/mean hd95_metric': 0.5232976675033569} +Epoch [3867/4000] Validation [1/4] Loss: 0.43608 focal_loss 0.37130 dice_loss 0.06478 +Epoch [3867/4000] Validation [2/4] Loss: 0.49044 focal_loss 0.37971 dice_loss 0.11073 +Epoch [3867/4000] Validation [3/4] Loss: 0.55165 focal_loss 0.45920 dice_loss 0.09246 +Epoch [3867/4000] Validation [4/4] Loss: 0.28600 focal_loss 0.20222 dice_loss 0.08378 +Epoch [3867/4000] Validation metric {'Val/mean dice_metric': 0.973834216594696, 'Val/mean miou_metric': 0.9601069688796997, 'Val/mean f1': 0.976128339767456, 'Val/mean precision': 0.9736754894256592, 'Val/mean recall': 0.9785935282707214, 'Val/mean hd95_metric': 5.264883995056152} +Cheakpoint... +Epoch [3867/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973834216594696, 'Val/mean miou_metric': 0.9601069688796997, 'Val/mean f1': 0.976128339767456, 'Val/mean precision': 0.9736754894256592, 'Val/mean recall': 0.9785935282707214, 'Val/mean hd95_metric': 5.264883995056152} +Epoch [3868/4000] Training [1/16] Loss: 0.00241 +Epoch [3868/4000] Training [2/16] Loss: 0.00200 +Epoch [3868/4000] Training [3/16] Loss: 0.00183 +Epoch [3868/4000] Training [4/16] Loss: 0.00304 +Epoch [3868/4000] Training [5/16] Loss: 0.00286 +Epoch [3868/4000] Training [6/16] Loss: 0.00301 +Epoch [3868/4000] Training [7/16] Loss: 0.00194 +Epoch [3868/4000] Training [8/16] Loss: 0.00347 +Epoch [3868/4000] Training [9/16] Loss: 0.00241 +Epoch [3868/4000] Training [10/16] Loss: 0.00253 +Epoch [3868/4000] Training [11/16] Loss: 0.00316 +Epoch [3868/4000] Training [12/16] Loss: 0.00186 +Epoch [3868/4000] Training [13/16] Loss: 0.00263 +Epoch [3868/4000] Training [14/16] Loss: 0.00215 +Epoch [3868/4000] Training [15/16] Loss: 0.00142 +Epoch [3868/4000] Training [16/16] Loss: 0.00372 +Epoch [3868/4000] Training metric {'Train/mean dice_metric': 0.9987401366233826, 'Train/mean miou_metric': 0.9971994757652283, 'Train/mean f1': 0.9935286641120911, 'Train/mean precision': 0.988847017288208, 'Train/mean recall': 0.9982548356056213, 'Train/mean hd95_metric': 0.4782503843307495} +Epoch [3868/4000] Validation [1/4] Loss: 0.42434 focal_loss 0.35923 dice_loss 0.06511 +Epoch [3868/4000] Validation [2/4] Loss: 0.47154 focal_loss 0.36394 dice_loss 0.10761 +Epoch [3868/4000] Validation [3/4] Loss: 0.58464 focal_loss 0.48356 dice_loss 0.10108 +Epoch [3868/4000] Validation [4/4] Loss: 0.34046 focal_loss 0.24071 dice_loss 0.09975 +Epoch [3868/4000] Validation metric {'Val/mean dice_metric': 0.9744253158569336, 'Val/mean miou_metric': 0.9602099657058716, 'Val/mean f1': 0.9762158393859863, 'Val/mean precision': 0.9742389917373657, 'Val/mean recall': 0.9782008528709412, 'Val/mean hd95_metric': 5.0352559089660645} +Cheakpoint... +Epoch [3868/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744253158569336, 'Val/mean miou_metric': 0.9602099657058716, 'Val/mean f1': 0.9762158393859863, 'Val/mean precision': 0.9742389917373657, 'Val/mean recall': 0.9782008528709412, 'Val/mean hd95_metric': 5.0352559089660645} +Epoch [3869/4000] Training [1/16] Loss: 0.00205 +Epoch [3869/4000] Training [2/16] Loss: 0.00173 +Epoch [3869/4000] Training [3/16] Loss: 0.00233 +Epoch [3869/4000] Training [4/16] Loss: 0.00347 +Epoch [3869/4000] Training [5/16] Loss: 0.00189 +Epoch [3869/4000] Training [6/16] Loss: 0.00151 +Epoch [3869/4000] Training [7/16] Loss: 0.00170 +Epoch [3869/4000] Training [8/16] Loss: 0.00230 +Epoch [3869/4000] Training [9/16] Loss: 0.00187 +Epoch [3869/4000] Training [10/16] Loss: 0.00235 +Epoch [3869/4000] Training [11/16] Loss: 0.00168 +Epoch [3869/4000] Training [12/16] Loss: 0.00294 +Epoch [3869/4000] Training [13/16] Loss: 0.00232 +Epoch [3869/4000] Training [14/16] Loss: 0.00141 +Epoch [3869/4000] Training [15/16] Loss: 0.00227 +Epoch [3869/4000] Training [16/16] Loss: 0.00296 +Epoch [3869/4000] Training metric {'Train/mean dice_metric': 0.9989888668060303, 'Train/mean miou_metric': 0.9976953268051147, 'Train/mean f1': 0.993905782699585, 'Train/mean precision': 0.9893349409103394, 'Train/mean recall': 0.9985190629959106, 'Train/mean hd95_metric': 0.4367741048336029} +Epoch [3869/4000] Validation [1/4] Loss: 0.37146 focal_loss 0.31344 dice_loss 0.05803 +Epoch [3869/4000] Validation [2/4] Loss: 0.61950 focal_loss 0.46209 dice_loss 0.15741 +Epoch [3869/4000] Validation [3/4] Loss: 0.54600 focal_loss 0.45291 dice_loss 0.09308 +Epoch [3869/4000] Validation [4/4] Loss: 0.46636 focal_loss 0.35915 dice_loss 0.10721 +Epoch [3869/4000] Validation metric {'Val/mean dice_metric': 0.9726559519767761, 'Val/mean miou_metric': 0.9589077234268188, 'Val/mean f1': 0.9756496548652649, 'Val/mean precision': 0.9742756485939026, 'Val/mean recall': 0.9770275950431824, 'Val/mean hd95_metric': 5.1541218757629395} +Cheakpoint... +Epoch [3869/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9726559519767761, 'Val/mean miou_metric': 0.9589077234268188, 'Val/mean f1': 0.9756496548652649, 'Val/mean precision': 0.9742756485939026, 'Val/mean recall': 0.9770275950431824, 'Val/mean hd95_metric': 5.1541218757629395} +Epoch [3870/4000] Training [1/16] Loss: 0.00318 +Epoch [3870/4000] Training [2/16] Loss: 0.00386 +Epoch [3870/4000] Training [3/16] Loss: 0.00231 +Epoch [3870/4000] Training [4/16] Loss: 0.00242 +Epoch [3870/4000] Training [5/16] Loss: 0.00187 +Epoch [3870/4000] Training [6/16] Loss: 0.00189 +Epoch [3870/4000] Training [7/16] Loss: 0.00256 +Epoch [3870/4000] Training [8/16] Loss: 0.00246 +Epoch [3870/4000] Training [9/16] Loss: 0.00320 +Epoch [3870/4000] Training [10/16] Loss: 0.00393 +Epoch [3870/4000] Training [11/16] Loss: 0.00127 +Epoch [3870/4000] Training [12/16] Loss: 0.00248 +Epoch [3870/4000] Training [13/16] Loss: 0.00219 +Epoch [3870/4000] Training [14/16] Loss: 0.00261 +Epoch [3870/4000] Training [15/16] Loss: 0.00228 +Epoch [3870/4000] Training [16/16] Loss: 0.00213 +Epoch [3870/4000] Training metric {'Train/mean dice_metric': 0.9987278580665588, 'Train/mean miou_metric': 0.9971410632133484, 'Train/mean f1': 0.9928737878799438, 'Train/mean precision': 0.9875798225402832, 'Train/mean recall': 0.9982248544692993, 'Train/mean hd95_metric': 0.5075470209121704} +Epoch [3870/4000] Validation [1/4] Loss: 0.37146 focal_loss 0.31089 dice_loss 0.06057 +Epoch [3870/4000] Validation [2/4] Loss: 0.95132 focal_loss 0.76580 dice_loss 0.18552 +Epoch [3870/4000] Validation [3/4] Loss: 0.55476 focal_loss 0.46260 dice_loss 0.09216 +Epoch [3870/4000] Validation [4/4] Loss: 0.37289 focal_loss 0.28219 dice_loss 0.09070 +Epoch [3870/4000] Validation metric {'Val/mean dice_metric': 0.9740886688232422, 'Val/mean miou_metric': 0.9604606628417969, 'Val/mean f1': 0.9756088256835938, 'Val/mean precision': 0.9721252918243408, 'Val/mean recall': 0.9791173338890076, 'Val/mean hd95_metric': 5.23322057723999} +Cheakpoint... +Epoch [3870/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740886688232422, 'Val/mean miou_metric': 0.9604606628417969, 'Val/mean f1': 0.9756088256835938, 'Val/mean precision': 0.9721252918243408, 'Val/mean recall': 0.9791173338890076, 'Val/mean hd95_metric': 5.23322057723999} +Epoch [3871/4000] Training [1/16] Loss: 0.00321 +Epoch [3871/4000] Training [2/16] Loss: 0.00245 +Epoch [3871/4000] Training [3/16] Loss: 0.00174 +Epoch [3871/4000] Training [4/16] Loss: 0.00267 +Epoch [3871/4000] Training [5/16] Loss: 0.00243 +Epoch [3871/4000] Training [6/16] Loss: 0.00171 +Epoch [3871/4000] Training [7/16] Loss: 0.00189 +Epoch [3871/4000] Training [8/16] Loss: 0.00241 +Epoch [3871/4000] Training [9/16] Loss: 0.00298 +Epoch [3871/4000] Training [10/16] Loss: 0.00265 +Epoch [3871/4000] Training [11/16] Loss: 0.00248 +Epoch [3871/4000] Training [12/16] Loss: 0.00209 +Epoch [3871/4000] Training [13/16] Loss: 0.00221 +Epoch [3871/4000] Training [14/16] Loss: 0.00161 +Epoch [3871/4000] Training [15/16] Loss: 0.00170 +Epoch [3871/4000] Training [16/16] Loss: 0.00242 +Epoch [3871/4000] Training metric {'Train/mean dice_metric': 0.9988504648208618, 'Train/mean miou_metric': 0.9974260926246643, 'Train/mean f1': 0.9938908219337463, 'Train/mean precision': 0.9893304109573364, 'Train/mean recall': 0.9984933733940125, 'Train/mean hd95_metric': 0.4807892441749573} +Epoch [3871/4000] Validation [1/4] Loss: 0.41209 focal_loss 0.35093 dice_loss 0.06116 +Epoch [3871/4000] Validation [2/4] Loss: 0.47059 focal_loss 0.36270 dice_loss 0.10789 +Epoch [3871/4000] Validation [3/4] Loss: 0.58127 focal_loss 0.48489 dice_loss 0.09638 +Epoch [3871/4000] Validation [4/4] Loss: 0.35461 focal_loss 0.26994 dice_loss 0.08467 +Epoch [3871/4000] Validation metric {'Val/mean dice_metric': 0.9750779867172241, 'Val/mean miou_metric': 0.9611549377441406, 'Val/mean f1': 0.9767752289772034, 'Val/mean precision': 0.9745341539382935, 'Val/mean recall': 0.9790264964103699, 'Val/mean hd95_metric': 4.935883045196533} +Cheakpoint... +Epoch [3871/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750779867172241, 'Val/mean miou_metric': 0.9611549377441406, 'Val/mean f1': 0.9767752289772034, 'Val/mean precision': 0.9745341539382935, 'Val/mean recall': 0.9790264964103699, 'Val/mean hd95_metric': 4.935883045196533} +Epoch [3872/4000] Training [1/16] Loss: 0.00251 +Epoch [3872/4000] Training [2/16] Loss: 0.00301 +Epoch [3872/4000] Training [3/16] Loss: 0.00213 +Epoch [3872/4000] Training [4/16] Loss: 0.00218 +Epoch [3872/4000] Training [5/16] Loss: 0.00154 +Epoch [3872/4000] Training [6/16] Loss: 0.00265 +Epoch [3872/4000] Training [7/16] Loss: 0.00283 +Epoch [3872/4000] Training [8/16] Loss: 0.00205 +Epoch [3872/4000] Training [9/16] Loss: 0.00269 +Epoch [3872/4000] Training [10/16] Loss: 0.00217 +Epoch [3872/4000] Training [11/16] Loss: 0.00236 +Epoch [3872/4000] Training [12/16] Loss: 0.00212 +Epoch [3872/4000] Training [13/16] Loss: 0.00345 +Epoch [3872/4000] Training [14/16] Loss: 0.00260 +Epoch [3872/4000] Training [15/16] Loss: 0.00271 +Epoch [3872/4000] Training [16/16] Loss: 0.00340 +Epoch [3872/4000] Training metric {'Train/mean dice_metric': 0.9988468885421753, 'Train/mean miou_metric': 0.9974191188812256, 'Train/mean f1': 0.9938371777534485, 'Train/mean precision': 0.9892903566360474, 'Train/mean recall': 0.9984260201454163, 'Train/mean hd95_metric': 0.5133088827133179} +Epoch [3872/4000] Validation [1/4] Loss: 0.47418 focal_loss 0.40902 dice_loss 0.06517 +Epoch [3872/4000] Validation [2/4] Loss: 0.86215 focal_loss 0.67043 dice_loss 0.19172 +Epoch [3872/4000] Validation [3/4] Loss: 0.55666 focal_loss 0.45667 dice_loss 0.09999 +Epoch [3872/4000] Validation [4/4] Loss: 0.41251 focal_loss 0.30077 dice_loss 0.11174 +Epoch [3872/4000] Validation metric {'Val/mean dice_metric': 0.9733095169067383, 'Val/mean miou_metric': 0.9589744806289673, 'Val/mean f1': 0.9760229587554932, 'Val/mean precision': 0.9739378094673157, 'Val/mean recall': 0.9781171083450317, 'Val/mean hd95_metric': 5.254775047302246} +Cheakpoint... +Epoch [3872/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733095169067383, 'Val/mean miou_metric': 0.9589744806289673, 'Val/mean f1': 0.9760229587554932, 'Val/mean precision': 0.9739378094673157, 'Val/mean recall': 0.9781171083450317, 'Val/mean hd95_metric': 5.254775047302246} +Epoch [3873/4000] Training [1/16] Loss: 0.00203 +Epoch [3873/4000] Training [2/16] Loss: 0.00187 +Epoch [3873/4000] Training [3/16] Loss: 0.00352 +Epoch [3873/4000] Training [4/16] Loss: 0.00341 +Epoch [3873/4000] Training [5/16] Loss: 0.00230 +Epoch [3873/4000] Training [6/16] Loss: 0.00240 +Epoch [3873/4000] Training [7/16] Loss: 0.00232 +Epoch [3873/4000] Training [8/16] Loss: 0.00251 +Epoch [3873/4000] Training [9/16] Loss: 0.00142 +Epoch [3873/4000] Training [10/16] Loss: 0.00153 +Epoch [3873/4000] Training [11/16] Loss: 0.00222 +Epoch [3873/4000] Training [12/16] Loss: 0.00273 +Epoch [3873/4000] Training [13/16] Loss: 0.00137 +Epoch [3873/4000] Training [14/16] Loss: 0.00206 +Epoch [3873/4000] Training [15/16] Loss: 0.00255 +Epoch [3873/4000] Training [16/16] Loss: 0.00211 +Epoch [3873/4000] Training metric {'Train/mean dice_metric': 0.9988857507705688, 'Train/mean miou_metric': 0.9974950551986694, 'Train/mean f1': 0.9939380288124084, 'Train/mean precision': 0.9894047975540161, 'Train/mean recall': 0.9985129237174988, 'Train/mean hd95_metric': 0.4844304025173187} +Epoch [3873/4000] Validation [1/4] Loss: 0.38970 focal_loss 0.32642 dice_loss 0.06329 +Epoch [3873/4000] Validation [2/4] Loss: 0.48149 focal_loss 0.36970 dice_loss 0.11180 +Epoch [3873/4000] Validation [3/4] Loss: 0.29062 focal_loss 0.22414 dice_loss 0.06648 +Epoch [3873/4000] Validation [4/4] Loss: 0.30625 focal_loss 0.21940 dice_loss 0.08686 +Epoch [3873/4000] Validation metric {'Val/mean dice_metric': 0.9754670858383179, 'Val/mean miou_metric': 0.961591362953186, 'Val/mean f1': 0.9770968556404114, 'Val/mean precision': 0.975013256072998, 'Val/mean recall': 0.9791892170906067, 'Val/mean hd95_metric': 4.687247276306152} +Cheakpoint... +Epoch [3873/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754670858383179, 'Val/mean miou_metric': 0.961591362953186, 'Val/mean f1': 0.9770968556404114, 'Val/mean precision': 0.975013256072998, 'Val/mean recall': 0.9791892170906067, 'Val/mean hd95_metric': 4.687247276306152} +Epoch [3874/4000] Training [1/16] Loss: 0.00185 +Epoch [3874/4000] Training [2/16] Loss: 0.00969 +Epoch [3874/4000] Training [3/16] Loss: 0.00192 +Epoch [3874/4000] Training [4/16] Loss: 0.00254 +Epoch [3874/4000] Training [5/16] Loss: 0.00223 +Epoch [3874/4000] Training [6/16] Loss: 0.00195 +Epoch [3874/4000] Training [7/16] Loss: 0.00289 +Epoch [3874/4000] Training [8/16] Loss: 0.00303 +Epoch [3874/4000] Training [9/16] Loss: 0.00254 +Epoch [3874/4000] Training [10/16] Loss: 0.00344 +Epoch [3874/4000] Training [11/16] Loss: 0.00533 +Epoch [3874/4000] Training [12/16] Loss: 0.00220 +Epoch [3874/4000] Training [13/16] Loss: 0.00306 +Epoch [3874/4000] Training [14/16] Loss: 0.00222 +Epoch [3874/4000] Training [15/16] Loss: 0.00256 +Epoch [3874/4000] Training [16/16] Loss: 0.00259 +Epoch [3874/4000] Training metric {'Train/mean dice_metric': 0.998666524887085, 'Train/mean miou_metric': 0.9970651865005493, 'Train/mean f1': 0.9936396479606628, 'Train/mean precision': 0.9891951680183411, 'Train/mean recall': 0.9981241822242737, 'Train/mean hd95_metric': 0.5312771797180176} +Epoch [3874/4000] Validation [1/4] Loss: 0.43959 focal_loss 0.37480 dice_loss 0.06479 +Epoch [3874/4000] Validation [2/4] Loss: 0.47940 focal_loss 0.36930 dice_loss 0.11011 +Epoch [3874/4000] Validation [3/4] Loss: 0.56806 focal_loss 0.47331 dice_loss 0.09475 +Epoch [3874/4000] Validation [4/4] Loss: 0.39459 focal_loss 0.28435 dice_loss 0.11024 +Epoch [3874/4000] Validation metric {'Val/mean dice_metric': 0.9743491411209106, 'Val/mean miou_metric': 0.9600385427474976, 'Val/mean f1': 0.9761967062950134, 'Val/mean precision': 0.9743372201919556, 'Val/mean recall': 0.9780632853507996, 'Val/mean hd95_metric': 4.963919162750244} +Cheakpoint... +Epoch [3874/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743491411209106, 'Val/mean miou_metric': 0.9600385427474976, 'Val/mean f1': 0.9761967062950134, 'Val/mean precision': 0.9743372201919556, 'Val/mean recall': 0.9780632853507996, 'Val/mean hd95_metric': 4.963919162750244} +Epoch [3875/4000] Training [1/16] Loss: 0.00203 +Epoch [3875/4000] Training [2/16] Loss: 0.00226 +Epoch [3875/4000] Training [3/16] Loss: 0.00263 +Epoch [3875/4000] Training [4/16] Loss: 0.00318 +Epoch [3875/4000] Training [5/16] Loss: 0.00178 +Epoch [3875/4000] Training [6/16] Loss: 0.00332 +Epoch [3875/4000] Training [7/16] Loss: 0.00413 +Epoch [3875/4000] Training [8/16] Loss: 0.00185 +Epoch [3875/4000] Training [9/16] Loss: 0.00214 +Epoch [3875/4000] Training [10/16] Loss: 0.00255 +Epoch [3875/4000] Training [11/16] Loss: 0.00284 +Epoch [3875/4000] Training [12/16] Loss: 0.00252 +Epoch [3875/4000] Training [13/16] Loss: 0.00205 +Epoch [3875/4000] Training [14/16] Loss: 0.00225 +Epoch [3875/4000] Training [15/16] Loss: 0.00210 +Epoch [3875/4000] Training [16/16] Loss: 0.00273 +Epoch [3875/4000] Training metric {'Train/mean dice_metric': 0.9988427758216858, 'Train/mean miou_metric': 0.9974023699760437, 'Train/mean f1': 0.993666410446167, 'Train/mean precision': 0.9890143871307373, 'Train/mean recall': 0.9983623623847961, 'Train/mean hd95_metric': 0.5541188716888428} +Epoch [3875/4000] Validation [1/4] Loss: 0.39708 focal_loss 0.33361 dice_loss 0.06347 +Epoch [3875/4000] Validation [2/4] Loss: 0.51343 focal_loss 0.39311 dice_loss 0.12032 +Epoch [3875/4000] Validation [3/4] Loss: 0.58216 focal_loss 0.47780 dice_loss 0.10436 +Epoch [3875/4000] Validation [4/4] Loss: 0.33344 focal_loss 0.24291 dice_loss 0.09053 +Epoch [3875/4000] Validation metric {'Val/mean dice_metric': 0.9739154577255249, 'Val/mean miou_metric': 0.9596311450004578, 'Val/mean f1': 0.9763964414596558, 'Val/mean precision': 0.9743686318397522, 'Val/mean recall': 0.9784326553344727, 'Val/mean hd95_metric': 4.948447227478027} +Cheakpoint... +Epoch [3875/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739154577255249, 'Val/mean miou_metric': 0.9596311450004578, 'Val/mean f1': 0.9763964414596558, 'Val/mean precision': 0.9743686318397522, 'Val/mean recall': 0.9784326553344727, 'Val/mean hd95_metric': 4.948447227478027} +Epoch [3876/4000] Training [1/16] Loss: 0.00214 +Epoch [3876/4000] Training [2/16] Loss: 0.00176 +Epoch [3876/4000] Training [3/16] Loss: 0.00307 +Epoch [3876/4000] Training [4/16] Loss: 0.00163 +Epoch [3876/4000] Training [5/16] Loss: 0.00229 +Epoch [3876/4000] Training [6/16] Loss: 0.00253 +Epoch [3876/4000] Training [7/16] Loss: 0.00233 +Epoch [3876/4000] Training [8/16] Loss: 0.00166 +Epoch [3876/4000] Training [9/16] Loss: 0.00164 +Epoch [3876/4000] Training [10/16] Loss: 0.00318 +Epoch [3876/4000] Training [11/16] Loss: 0.00359 +Epoch [3876/4000] Training [12/16] Loss: 0.00268 +Epoch [3876/4000] Training [13/16] Loss: 0.00211 +Epoch [3876/4000] Training [14/16] Loss: 0.00225 +Epoch [3876/4000] Training [15/16] Loss: 0.00234 +Epoch [3876/4000] Training [16/16] Loss: 0.00365 +Epoch [3876/4000] Training metric {'Train/mean dice_metric': 0.9988227486610413, 'Train/mean miou_metric': 0.9973699450492859, 'Train/mean f1': 0.9938210248947144, 'Train/mean precision': 0.9892463088035583, 'Train/mean recall': 0.9984382390975952, 'Train/mean hd95_metric': 0.49280110001564026} +Epoch [3876/4000] Validation [1/4] Loss: 0.47181 focal_loss 0.40733 dice_loss 0.06448 +Epoch [3876/4000] Validation [2/4] Loss: 0.63870 focal_loss 0.46562 dice_loss 0.17307 +Epoch [3876/4000] Validation [3/4] Loss: 0.55184 focal_loss 0.45578 dice_loss 0.09606 +Epoch [3876/4000] Validation [4/4] Loss: 0.36511 focal_loss 0.27803 dice_loss 0.08708 +Epoch [3876/4000] Validation metric {'Val/mean dice_metric': 0.974463939666748, 'Val/mean miou_metric': 0.960211455821991, 'Val/mean f1': 0.9763096570968628, 'Val/mean precision': 0.9738191962242126, 'Val/mean recall': 0.9788128733634949, 'Val/mean hd95_metric': 4.805356979370117} +Cheakpoint... +Epoch [3876/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974463939666748, 'Val/mean miou_metric': 0.960211455821991, 'Val/mean f1': 0.9763096570968628, 'Val/mean precision': 0.9738191962242126, 'Val/mean recall': 0.9788128733634949, 'Val/mean hd95_metric': 4.805356979370117} +Epoch [3877/4000] Training [1/16] Loss: 0.00205 +Epoch [3877/4000] Training [2/16] Loss: 0.00228 +Epoch [3877/4000] Training [3/16] Loss: 0.00256 +Epoch [3877/4000] Training [4/16] Loss: 0.00315 +Epoch [3877/4000] Training [5/16] Loss: 0.00319 +Epoch [3877/4000] Training [6/16] Loss: 0.00236 +Epoch [3877/4000] Training [7/16] Loss: 0.00170 +Epoch [3877/4000] Training [8/16] Loss: 0.00215 +Epoch [3877/4000] Training [9/16] Loss: 0.00379 +Epoch [3877/4000] Training [10/16] Loss: 0.00173 +Epoch [3877/4000] Training [11/16] Loss: 0.00311 +Epoch [3877/4000] Training [12/16] Loss: 0.00189 +Epoch [3877/4000] Training [13/16] Loss: 0.00288 +Epoch [3877/4000] Training [14/16] Loss: 0.00119 +Epoch [3877/4000] Training [15/16] Loss: 0.00267 +Epoch [3877/4000] Training [16/16] Loss: 0.00257 +Epoch [3877/4000] Training metric {'Train/mean dice_metric': 0.9988551735877991, 'Train/mean miou_metric': 0.9974287748336792, 'Train/mean f1': 0.993812620639801, 'Train/mean precision': 0.9892493486404419, 'Train/mean recall': 0.9984180927276611, 'Train/mean hd95_metric': 0.48879706859588623} +Epoch [3877/4000] Validation [1/4] Loss: 0.38870 focal_loss 0.32542 dice_loss 0.06329 +Epoch [3877/4000] Validation [2/4] Loss: 0.47191 focal_loss 0.36287 dice_loss 0.10904 +Epoch [3877/4000] Validation [3/4] Loss: 0.30789 focal_loss 0.23950 dice_loss 0.06839 +Epoch [3877/4000] Validation [4/4] Loss: 0.36057 focal_loss 0.27048 dice_loss 0.09009 +Epoch [3877/4000] Validation metric {'Val/mean dice_metric': 0.9758184552192688, 'Val/mean miou_metric': 0.9615438580513, 'Val/mean f1': 0.9763776063919067, 'Val/mean precision': 0.973352313041687, 'Val/mean recall': 0.979421854019165, 'Val/mean hd95_metric': 5.070979118347168} +Cheakpoint... +Epoch [3877/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758184552192688, 'Val/mean miou_metric': 0.9615438580513, 'Val/mean f1': 0.9763776063919067, 'Val/mean precision': 0.973352313041687, 'Val/mean recall': 0.979421854019165, 'Val/mean hd95_metric': 5.070979118347168} +Epoch [3878/4000] Training [1/16] Loss: 0.00245 +Epoch [3878/4000] Training [2/16] Loss: 0.00231 +Epoch [3878/4000] Training [3/16] Loss: 0.00339 +Epoch [3878/4000] Training [4/16] Loss: 0.00186 +Epoch [3878/4000] Training [5/16] Loss: 0.00232 +Epoch [3878/4000] Training [6/16] Loss: 0.00264 +Epoch [3878/4000] Training [7/16] Loss: 0.00182 +Epoch [3878/4000] Training [8/16] Loss: 0.00231 +Epoch [3878/4000] Training [9/16] Loss: 0.00226 +Epoch [3878/4000] Training [10/16] Loss: 0.00375 +Epoch [3878/4000] Training [11/16] Loss: 0.00190 +Epoch [3878/4000] Training [12/16] Loss: 0.00211 +Epoch [3878/4000] Training [13/16] Loss: 0.00207 +Epoch [3878/4000] Training [14/16] Loss: 0.00205 +Epoch [3878/4000] Training [15/16] Loss: 0.00247 +Epoch [3878/4000] Training [16/16] Loss: 0.00350 +Epoch [3878/4000] Training metric {'Train/mean dice_metric': 0.9987736940383911, 'Train/mean miou_metric': 0.9972696900367737, 'Train/mean f1': 0.9937474131584167, 'Train/mean precision': 0.9892038702964783, 'Train/mean recall': 0.9983327984809875, 'Train/mean hd95_metric': 0.5238399505615234} +Epoch [3878/4000] Validation [1/4] Loss: 0.46322 focal_loss 0.39744 dice_loss 0.06578 +Epoch [3878/4000] Validation [2/4] Loss: 0.95818 focal_loss 0.76908 dice_loss 0.18909 +Epoch [3878/4000] Validation [3/4] Loss: 0.55321 focal_loss 0.45608 dice_loss 0.09714 +Epoch [3878/4000] Validation [4/4] Loss: 0.52296 focal_loss 0.39903 dice_loss 0.12394 +Epoch [3878/4000] Validation metric {'Val/mean dice_metric': 0.9735809564590454, 'Val/mean miou_metric': 0.9598276019096375, 'Val/mean f1': 0.9763567447662354, 'Val/mean precision': 0.9744691252708435, 'Val/mean recall': 0.9782516956329346, 'Val/mean hd95_metric': 4.831302642822266} +Cheakpoint... +Epoch [3878/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735809564590454, 'Val/mean miou_metric': 0.9598276019096375, 'Val/mean f1': 0.9763567447662354, 'Val/mean precision': 0.9744691252708435, 'Val/mean recall': 0.9782516956329346, 'Val/mean hd95_metric': 4.831302642822266} +Epoch [3879/4000] Training [1/16] Loss: 0.00305 +Epoch [3879/4000] Training [2/16] Loss: 0.00276 +Epoch [3879/4000] Training [3/16] Loss: 0.00347 +Epoch [3879/4000] Training [4/16] Loss: 0.00315 +Epoch [3879/4000] Training [5/16] Loss: 0.00256 +Epoch [3879/4000] Training [6/16] Loss: 0.00240 +Epoch [3879/4000] Training [7/16] Loss: 0.00156 +Epoch [3879/4000] Training [8/16] Loss: 0.00233 +Epoch [3879/4000] Training [9/16] Loss: 0.00316 +Epoch [3879/4000] Training [10/16] Loss: 0.00235 +Epoch [3879/4000] Training [11/16] Loss: 0.00193 +Epoch [3879/4000] Training [12/16] Loss: 0.00194 +Epoch [3879/4000] Training [13/16] Loss: 0.00171 +Epoch [3879/4000] Training [14/16] Loss: 0.00169 +Epoch [3879/4000] Training [15/16] Loss: 0.00160 +Epoch [3879/4000] Training [16/16] Loss: 0.00180 +Epoch [3879/4000] Training metric {'Train/mean dice_metric': 0.9987733364105225, 'Train/mean miou_metric': 0.9972637891769409, 'Train/mean f1': 0.9936092495918274, 'Train/mean precision': 0.9889479279518127, 'Train/mean recall': 0.9983147382736206, 'Train/mean hd95_metric': 0.5109649300575256} +Epoch [3879/4000] Validation [1/4] Loss: 0.44086 focal_loss 0.37602 dice_loss 0.06484 +Epoch [3879/4000] Validation [2/4] Loss: 0.59991 focal_loss 0.44756 dice_loss 0.15236 +Epoch [3879/4000] Validation [3/4] Loss: 0.55004 focal_loss 0.45685 dice_loss 0.09320 +Epoch [3879/4000] Validation [4/4] Loss: 0.46741 focal_loss 0.35699 dice_loss 0.11042 +Epoch [3879/4000] Validation metric {'Val/mean dice_metric': 0.9731451869010925, 'Val/mean miou_metric': 0.9594915509223938, 'Val/mean f1': 0.9762700200080872, 'Val/mean precision': 0.9746096730232239, 'Val/mean recall': 0.9779360890388489, 'Val/mean hd95_metric': 4.680188179016113} +Cheakpoint... +Epoch [3879/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731451869010925, 'Val/mean miou_metric': 0.9594915509223938, 'Val/mean f1': 0.9762700200080872, 'Val/mean precision': 0.9746096730232239, 'Val/mean recall': 0.9779360890388489, 'Val/mean hd95_metric': 4.680188179016113} +Epoch [3880/4000] Training [1/16] Loss: 0.00221 +Epoch [3880/4000] Training [2/16] Loss: 0.00171 +Epoch [3880/4000] Training [3/16] Loss: 0.00326 +Epoch [3880/4000] Training [4/16] Loss: 0.00197 +Epoch [3880/4000] Training [5/16] Loss: 0.00162 +Epoch [3880/4000] Training [6/16] Loss: 0.00251 +Epoch [3880/4000] Training [7/16] Loss: 0.00211 +Epoch [3880/4000] Training [8/16] Loss: 0.00160 +Epoch [3880/4000] Training [9/16] Loss: 0.00265 +Epoch [3880/4000] Training [10/16] Loss: 0.00270 +Epoch [3880/4000] Training [11/16] Loss: 0.00144 +Epoch [3880/4000] Training [12/16] Loss: 0.00179 +Epoch [3880/4000] Training [13/16] Loss: 0.00220 +Epoch [3880/4000] Training [14/16] Loss: 0.00309 +Epoch [3880/4000] Training [15/16] Loss: 0.00255 +Epoch [3880/4000] Training [16/16] Loss: 0.00233 +Epoch [3880/4000] Training metric {'Train/mean dice_metric': 0.9989049434661865, 'Train/mean miou_metric': 0.9975372552871704, 'Train/mean f1': 0.9938763380050659, 'Train/mean precision': 0.989343523979187, 'Train/mean recall': 0.9984508752822876, 'Train/mean hd95_metric': 0.49970683455467224} +Epoch [3880/4000] Validation [1/4] Loss: 0.46519 focal_loss 0.39485 dice_loss 0.07034 +Epoch [3880/4000] Validation [2/4] Loss: 0.95092 focal_loss 0.76258 dice_loss 0.18835 +Epoch [3880/4000] Validation [3/4] Loss: 0.53785 focal_loss 0.44564 dice_loss 0.09221 +Epoch [3880/4000] Validation [4/4] Loss: 0.36497 focal_loss 0.27631 dice_loss 0.08866 +Epoch [3880/4000] Validation metric {'Val/mean dice_metric': 0.973774790763855, 'Val/mean miou_metric': 0.9602916836738586, 'Val/mean f1': 0.9759212732315063, 'Val/mean precision': 0.973119854927063, 'Val/mean recall': 0.9787388443946838, 'Val/mean hd95_metric': 4.992393493652344} +Cheakpoint... +Epoch [3880/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973774790763855, 'Val/mean miou_metric': 0.9602916836738586, 'Val/mean f1': 0.9759212732315063, 'Val/mean precision': 0.973119854927063, 'Val/mean recall': 0.9787388443946838, 'Val/mean hd95_metric': 4.992393493652344} +Epoch [3881/4000] Training [1/16] Loss: 0.00180 +Epoch [3881/4000] Training [2/16] Loss: 0.00266 +Epoch [3881/4000] Training [3/16] Loss: 0.00334 +Epoch [3881/4000] Training [4/16] Loss: 0.00242 +Epoch [3881/4000] Training [5/16] Loss: 0.00264 +Epoch [3881/4000] Training [6/16] Loss: 0.00420 +Epoch [3881/4000] Training [7/16] Loss: 0.00185 +Epoch [3881/4000] Training [8/16] Loss: 0.00181 +Epoch [3881/4000] Training [9/16] Loss: 0.00312 +Epoch [3881/4000] Training [10/16] Loss: 0.00220 +Epoch [3881/4000] Training [11/16] Loss: 0.00170 +Epoch [3881/4000] Training [12/16] Loss: 0.00243 +Epoch [3881/4000] Training [13/16] Loss: 0.00220 +Epoch [3881/4000] Training [14/16] Loss: 0.00171 +Epoch [3881/4000] Training [15/16] Loss: 0.00258 +Epoch [3881/4000] Training [16/16] Loss: 0.00190 +Epoch [3881/4000] Training metric {'Train/mean dice_metric': 0.9988645315170288, 'Train/mean miou_metric': 0.9974489808082581, 'Train/mean f1': 0.9937891364097595, 'Train/mean precision': 0.9891666173934937, 'Train/mean recall': 0.9984551072120667, 'Train/mean hd95_metric': 0.4847428500652313} +Epoch [3881/4000] Validation [1/4] Loss: 0.36790 focal_loss 0.30611 dice_loss 0.06179 +Epoch [3881/4000] Validation [2/4] Loss: 0.47916 focal_loss 0.36842 dice_loss 0.11075 +Epoch [3881/4000] Validation [3/4] Loss: 0.53523 focal_loss 0.44403 dice_loss 0.09120 +Epoch [3881/4000] Validation [4/4] Loss: 0.37123 focal_loss 0.28029 dice_loss 0.09094 +Epoch [3881/4000] Validation metric {'Val/mean dice_metric': 0.9746378064155579, 'Val/mean miou_metric': 0.9606216549873352, 'Val/mean f1': 0.9763593077659607, 'Val/mean precision': 0.9740978479385376, 'Val/mean recall': 0.978631317615509, 'Val/mean hd95_metric': 4.756594657897949} +Cheakpoint... +Epoch [3881/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746378064155579, 'Val/mean miou_metric': 0.9606216549873352, 'Val/mean f1': 0.9763593077659607, 'Val/mean precision': 0.9740978479385376, 'Val/mean recall': 0.978631317615509, 'Val/mean hd95_metric': 4.756594657897949} +Epoch [3882/4000] Training [1/16] Loss: 0.00148 +Epoch [3882/4000] Training [2/16] Loss: 0.00175 +Epoch [3882/4000] Training [3/16] Loss: 0.00222 +Epoch [3882/4000] Training [4/16] Loss: 0.00237 +Epoch [3882/4000] Training [5/16] Loss: 0.00196 +Epoch [3882/4000] Training [6/16] Loss: 0.00287 +Epoch [3882/4000] Training [7/16] Loss: 0.00199 +Epoch [3882/4000] Training [8/16] Loss: 0.00246 +Epoch [3882/4000] Training [9/16] Loss: 0.00221 +Epoch [3882/4000] Training [10/16] Loss: 0.00171 +Epoch [3882/4000] Training [11/16] Loss: 0.00164 +Epoch [3882/4000] Training [12/16] Loss: 0.00293 +Epoch [3882/4000] Training [13/16] Loss: 0.00263 +Epoch [3882/4000] Training [14/16] Loss: 0.00303 +Epoch [3882/4000] Training [15/16] Loss: 0.00271 +Epoch [3882/4000] Training [16/16] Loss: 0.00253 +Epoch [3882/4000] Training metric {'Train/mean dice_metric': 0.9988459944725037, 'Train/mean miou_metric': 0.9974184036254883, 'Train/mean f1': 0.9938049912452698, 'Train/mean precision': 0.9892606735229492, 'Train/mean recall': 0.9983912706375122, 'Train/mean hd95_metric': 0.5414142608642578} +Epoch [3882/4000] Validation [1/4] Loss: 0.48061 focal_loss 0.41445 dice_loss 0.06616 +Epoch [3882/4000] Validation [2/4] Loss: 0.90978 focal_loss 0.70653 dice_loss 0.20325 +Epoch [3882/4000] Validation [3/4] Loss: 0.50924 focal_loss 0.41317 dice_loss 0.09607 +Epoch [3882/4000] Validation [4/4] Loss: 0.36546 focal_loss 0.27833 dice_loss 0.08713 +Epoch [3882/4000] Validation metric {'Val/mean dice_metric': 0.9733684659004211, 'Val/mean miou_metric': 0.9594029188156128, 'Val/mean f1': 0.9753976464271545, 'Val/mean precision': 0.9730414748191833, 'Val/mean recall': 0.9777653217315674, 'Val/mean hd95_metric': 5.258783340454102} +Cheakpoint... +Epoch [3882/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733684659004211, 'Val/mean miou_metric': 0.9594029188156128, 'Val/mean f1': 0.9753976464271545, 'Val/mean precision': 0.9730414748191833, 'Val/mean recall': 0.9777653217315674, 'Val/mean hd95_metric': 5.258783340454102} +Epoch [3883/4000] Training [1/16] Loss: 0.00294 +Epoch [3883/4000] Training [2/16] Loss: 0.00171 +Epoch [3883/4000] Training [3/16] Loss: 0.00258 +Epoch [3883/4000] Training [4/16] Loss: 0.00212 +Epoch [3883/4000] Training [5/16] Loss: 0.00199 +Epoch [3883/4000] Training [6/16] Loss: 0.00282 +Epoch [3883/4000] Training [7/16] Loss: 0.00232 +Epoch [3883/4000] Training [8/16] Loss: 0.00167 +Epoch [3883/4000] Training [9/16] Loss: 0.00366 +Epoch [3883/4000] Training [10/16] Loss: 0.00248 +Epoch [3883/4000] Training [11/16] Loss: 0.00216 +Epoch [3883/4000] Training [12/16] Loss: 0.00296 +Epoch [3883/4000] Training [13/16] Loss: 0.00377 +Epoch [3883/4000] Training [14/16] Loss: 0.00240 +Epoch [3883/4000] Training [15/16] Loss: 0.00296 +Epoch [3883/4000] Training [16/16] Loss: 0.00239 +Epoch [3883/4000] Training metric {'Train/mean dice_metric': 0.9987576603889465, 'Train/mean miou_metric': 0.9972391128540039, 'Train/mean f1': 0.9937126636505127, 'Train/mean precision': 0.9891072511672974, 'Train/mean recall': 0.9983611702919006, 'Train/mean hd95_metric': 0.5071842670440674} +Epoch [3883/4000] Validation [1/4] Loss: 0.44855 focal_loss 0.37881 dice_loss 0.06973 +Epoch [3883/4000] Validation [2/4] Loss: 0.91147 focal_loss 0.70972 dice_loss 0.20175 +Epoch [3883/4000] Validation [3/4] Loss: 0.56704 focal_loss 0.47089 dice_loss 0.09614 +Epoch [3883/4000] Validation [4/4] Loss: 0.47001 focal_loss 0.36007 dice_loss 0.10995 +Epoch [3883/4000] Validation metric {'Val/mean dice_metric': 0.9722896814346313, 'Val/mean miou_metric': 0.9577680826187134, 'Val/mean f1': 0.9752029180526733, 'Val/mean precision': 0.973430871963501, 'Val/mean recall': 0.9769814014434814, 'Val/mean hd95_metric': 5.2372870445251465} +Cheakpoint... +Epoch [3883/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722896814346313, 'Val/mean miou_metric': 0.9577680826187134, 'Val/mean f1': 0.9752029180526733, 'Val/mean precision': 0.973430871963501, 'Val/mean recall': 0.9769814014434814, 'Val/mean hd95_metric': 5.2372870445251465} +Epoch [3884/4000] Training [1/16] Loss: 0.00229 +Epoch [3884/4000] Training [2/16] Loss: 0.00182 +Epoch [3884/4000] Training [3/16] Loss: 0.00243 +Epoch [3884/4000] Training [4/16] Loss: 0.00394 +Epoch [3884/4000] Training [5/16] Loss: 0.00363 +Epoch [3884/4000] Training [6/16] Loss: 0.00288 +Epoch [3884/4000] Training [7/16] Loss: 0.00187 +Epoch [3884/4000] Training [8/16] Loss: 0.00353 +Epoch [3884/4000] Training [9/16] Loss: 0.00210 +Epoch [3884/4000] Training [10/16] Loss: 0.00211 +Epoch [3884/4000] Training [11/16] Loss: 0.00186 +Epoch [3884/4000] Training [12/16] Loss: 0.00293 +Epoch [3884/4000] Training [13/16] Loss: 0.00213 +Epoch [3884/4000] Training [14/16] Loss: 0.00183 +Epoch [3884/4000] Training [15/16] Loss: 0.00198 +Epoch [3884/4000] Training [16/16] Loss: 0.00282 +Epoch [3884/4000] Training metric {'Train/mean dice_metric': 0.9987919330596924, 'Train/mean miou_metric': 0.9973087310791016, 'Train/mean f1': 0.9938121438026428, 'Train/mean precision': 0.9892895221710205, 'Train/mean recall': 0.9983763098716736, 'Train/mean hd95_metric': 0.5212454199790955} +Epoch [3884/4000] Validation [1/4] Loss: 0.39999 focal_loss 0.33545 dice_loss 0.06454 +Epoch [3884/4000] Validation [2/4] Loss: 0.49921 focal_loss 0.38071 dice_loss 0.11850 +Epoch [3884/4000] Validation [3/4] Loss: 0.53339 focal_loss 0.44283 dice_loss 0.09056 +Epoch [3884/4000] Validation [4/4] Loss: 0.47829 focal_loss 0.36671 dice_loss 0.11158 +Epoch [3884/4000] Validation metric {'Val/mean dice_metric': 0.9731661081314087, 'Val/mean miou_metric': 0.9592045545578003, 'Val/mean f1': 0.9763808846473694, 'Val/mean precision': 0.9749118685722351, 'Val/mean recall': 0.9778541922569275, 'Val/mean hd95_metric': 4.694055557250977} +Cheakpoint... +Epoch [3884/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731661081314087, 'Val/mean miou_metric': 0.9592045545578003, 'Val/mean f1': 0.9763808846473694, 'Val/mean precision': 0.9749118685722351, 'Val/mean recall': 0.9778541922569275, 'Val/mean hd95_metric': 4.694055557250977} +Epoch [3885/4000] Training [1/16] Loss: 0.00216 +Epoch [3885/4000] Training [2/16] Loss: 0.00187 +Epoch [3885/4000] Training [3/16] Loss: 0.00194 +Epoch [3885/4000] Training [4/16] Loss: 0.00119 +Epoch [3885/4000] Training [5/16] Loss: 0.00308 +Epoch [3885/4000] Training [6/16] Loss: 0.00199 +Epoch [3885/4000] Training [7/16] Loss: 0.00285 +Epoch [3885/4000] Training [8/16] Loss: 0.00224 +Epoch [3885/4000] Training [9/16] Loss: 0.00227 +Epoch [3885/4000] Training [10/16] Loss: 0.00243 +Epoch [3885/4000] Training [11/16] Loss: 0.00508 +Epoch [3885/4000] Training [12/16] Loss: 0.00207 +Epoch [3885/4000] Training [13/16] Loss: 0.00347 +Epoch [3885/4000] Training [14/16] Loss: 0.00404 +Epoch [3885/4000] Training [15/16] Loss: 0.00241 +Epoch [3885/4000] Training [16/16] Loss: 0.00251 +Epoch [3885/4000] Training metric {'Train/mean dice_metric': 0.9987920522689819, 'Train/mean miou_metric': 0.9973129034042358, 'Train/mean f1': 0.9938097596168518, 'Train/mean precision': 0.9892783761024475, 'Train/mean recall': 0.9983828067779541, 'Train/mean hd95_metric': 0.5106721520423889} +Epoch [3885/4000] Validation [1/4] Loss: 0.36177 focal_loss 0.30225 dice_loss 0.05953 +Epoch [3885/4000] Validation [2/4] Loss: 0.97697 focal_loss 0.78941 dice_loss 0.18756 +Epoch [3885/4000] Validation [3/4] Loss: 0.53381 focal_loss 0.44285 dice_loss 0.09097 +Epoch [3885/4000] Validation [4/4] Loss: 0.35945 focal_loss 0.26905 dice_loss 0.09040 +Epoch [3885/4000] Validation metric {'Val/mean dice_metric': 0.9731780290603638, 'Val/mean miou_metric': 0.9596416354179382, 'Val/mean f1': 0.9759712815284729, 'Val/mean precision': 0.9748077392578125, 'Val/mean recall': 0.9771376252174377, 'Val/mean hd95_metric': 5.018551826477051} +Cheakpoint... +Epoch [3885/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731780290603638, 'Val/mean miou_metric': 0.9596416354179382, 'Val/mean f1': 0.9759712815284729, 'Val/mean precision': 0.9748077392578125, 'Val/mean recall': 0.9771376252174377, 'Val/mean hd95_metric': 5.018551826477051} +Epoch [3886/4000] Training [1/16] Loss: 0.00249 +Epoch [3886/4000] Training [2/16] Loss: 0.00229 +Epoch [3886/4000] Training [3/16] Loss: 0.00178 +Epoch [3886/4000] Training [4/16] Loss: 0.00275 +Epoch [3886/4000] Training [5/16] Loss: 0.00323 +Epoch [3886/4000] Training [6/16] Loss: 0.00234 +Epoch [3886/4000] Training [7/16] Loss: 0.00180 +Epoch [3886/4000] Training [8/16] Loss: 0.00318 +Epoch [3886/4000] Training [9/16] Loss: 0.00368 +Epoch [3886/4000] Training [10/16] Loss: 0.00301 +Epoch [3886/4000] Training [11/16] Loss: 0.00197 +Epoch [3886/4000] Training [12/16] Loss: 0.00177 +Epoch [3886/4000] Training [13/16] Loss: 0.00301 +Epoch [3886/4000] Training [14/16] Loss: 0.00173 +Epoch [3886/4000] Training [15/16] Loss: 0.00277 +Epoch [3886/4000] Training [16/16] Loss: 0.00240 +Epoch [3886/4000] Training metric {'Train/mean dice_metric': 0.998715877532959, 'Train/mean miou_metric': 0.997138261795044, 'Train/mean f1': 0.9934467673301697, 'Train/mean precision': 0.9887059330940247, 'Train/mean recall': 0.9982331991195679, 'Train/mean hd95_metric': 0.5384897589683533} +Epoch [3886/4000] Validation [1/4] Loss: 0.46514 focal_loss 0.38653 dice_loss 0.07861 +Epoch [3886/4000] Validation [2/4] Loss: 0.96796 focal_loss 0.77792 dice_loss 0.19003 +Epoch [3886/4000] Validation [3/4] Loss: 0.27677 focal_loss 0.21715 dice_loss 0.05962 +Epoch [3886/4000] Validation [4/4] Loss: 0.37042 focal_loss 0.26943 dice_loss 0.10099 +Epoch [3886/4000] Validation metric {'Val/mean dice_metric': 0.9743310213088989, 'Val/mean miou_metric': 0.9606624841690063, 'Val/mean f1': 0.9764121770858765, 'Val/mean precision': 0.9747864007949829, 'Val/mean recall': 0.9780434370040894, 'Val/mean hd95_metric': 4.7580976486206055} +Cheakpoint... +Epoch [3886/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743310213088989, 'Val/mean miou_metric': 0.9606624841690063, 'Val/mean f1': 0.9764121770858765, 'Val/mean precision': 0.9747864007949829, 'Val/mean recall': 0.9780434370040894, 'Val/mean hd95_metric': 4.7580976486206055} +Epoch [3887/4000] Training [1/16] Loss: 0.00224 +Epoch [3887/4000] Training [2/16] Loss: 0.00176 +Epoch [3887/4000] Training [3/16] Loss: 0.00254 +Epoch [3887/4000] Training [4/16] Loss: 0.00202 +Epoch [3887/4000] Training [5/16] Loss: 0.00194 +Epoch [3887/4000] Training [6/16] Loss: 0.00215 +Epoch [3887/4000] Training [7/16] Loss: 0.00301 +Epoch [3887/4000] Training [8/16] Loss: 0.00221 +Epoch [3887/4000] Training [9/16] Loss: 0.00244 +Epoch [3887/4000] Training [10/16] Loss: 0.00202 +Epoch [3887/4000] Training [11/16] Loss: 0.00201 +Epoch [3887/4000] Training [12/16] Loss: 0.00187 +Epoch [3887/4000] Training [13/16] Loss: 0.00273 +Epoch [3887/4000] Training [14/16] Loss: 0.00256 +Epoch [3887/4000] Training [15/16] Loss: 0.00275 +Epoch [3887/4000] Training [16/16] Loss: 0.00215 +Epoch [3887/4000] Training metric {'Train/mean dice_metric': 0.9987840056419373, 'Train/mean miou_metric': 0.9972900748252869, 'Train/mean f1': 0.9937748908996582, 'Train/mean precision': 0.9892072677612305, 'Train/mean recall': 0.9983848929405212, 'Train/mean hd95_metric': 0.510921835899353} +Epoch [3887/4000] Validation [1/4] Loss: 0.37328 focal_loss 0.30978 dice_loss 0.06349 +Epoch [3887/4000] Validation [2/4] Loss: 0.49849 focal_loss 0.38475 dice_loss 0.11374 +Epoch [3887/4000] Validation [3/4] Loss: 0.53371 focal_loss 0.44498 dice_loss 0.08873 +Epoch [3887/4000] Validation [4/4] Loss: 0.47399 focal_loss 0.36508 dice_loss 0.10891 +Epoch [3887/4000] Validation metric {'Val/mean dice_metric': 0.9741169810295105, 'Val/mean miou_metric': 0.9598779678344727, 'Val/mean f1': 0.975864052772522, 'Val/mean precision': 0.9742417931556702, 'Val/mean recall': 0.9774919152259827, 'Val/mean hd95_metric': 4.919242858886719} +Cheakpoint... +Epoch [3887/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9741], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741169810295105, 'Val/mean miou_metric': 0.9598779678344727, 'Val/mean f1': 0.975864052772522, 'Val/mean precision': 0.9742417931556702, 'Val/mean recall': 0.9774919152259827, 'Val/mean hd95_metric': 4.919242858886719} +Epoch [3888/4000] Training [1/16] Loss: 0.00184 +Epoch [3888/4000] Training [2/16] Loss: 0.00358 +Epoch [3888/4000] Training [3/16] Loss: 0.00277 +Epoch [3888/4000] Training [4/16] Loss: 0.00324 +Epoch [3888/4000] Training [5/16] Loss: 0.00368 +Epoch [3888/4000] Training [6/16] Loss: 0.00314 +Epoch [3888/4000] Training [7/16] Loss: 0.00157 +Epoch [3888/4000] Training [8/16] Loss: 0.00230 +Epoch [3888/4000] Training [9/16] Loss: 0.00236 +Epoch [3888/4000] Training [10/16] Loss: 0.00223 +Epoch [3888/4000] Training [11/16] Loss: 0.00220 +Epoch [3888/4000] Training [12/16] Loss: 0.00341 +Epoch [3888/4000] Training [13/16] Loss: 0.00163 +Epoch [3888/4000] Training [14/16] Loss: 0.00207 +Epoch [3888/4000] Training [15/16] Loss: 0.00209 +Epoch [3888/4000] Training [16/16] Loss: 0.00234 +Epoch [3888/4000] Training metric {'Train/mean dice_metric': 0.9986323714256287, 'Train/mean miou_metric': 0.9969826340675354, 'Train/mean f1': 0.9934191703796387, 'Train/mean precision': 0.9887039661407471, 'Train/mean recall': 0.99817955493927, 'Train/mean hd95_metric': 0.5662112236022949} +Epoch [3888/4000] Validation [1/4] Loss: 0.45646 focal_loss 0.39214 dice_loss 0.06432 +Epoch [3888/4000] Validation [2/4] Loss: 0.47191 focal_loss 0.36294 dice_loss 0.10897 +Epoch [3888/4000] Validation [3/4] Loss: 0.54280 focal_loss 0.44760 dice_loss 0.09521 +Epoch [3888/4000] Validation [4/4] Loss: 0.50183 focal_loss 0.39229 dice_loss 0.10954 +Epoch [3888/4000] Validation metric {'Val/mean dice_metric': 0.974338173866272, 'Val/mean miou_metric': 0.9601742029190063, 'Val/mean f1': 0.9761112332344055, 'Val/mean precision': 0.9732083678245544, 'Val/mean recall': 0.9790316224098206, 'Val/mean hd95_metric': 5.051825523376465} +Cheakpoint... +Epoch [3888/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974338173866272, 'Val/mean miou_metric': 0.9601742029190063, 'Val/mean f1': 0.9761112332344055, 'Val/mean precision': 0.9732083678245544, 'Val/mean recall': 0.9790316224098206, 'Val/mean hd95_metric': 5.051825523376465} +Epoch [3889/4000] Training [1/16] Loss: 0.00177 +Epoch [3889/4000] Training [2/16] Loss: 0.00173 +Epoch [3889/4000] Training [3/16] Loss: 0.00321 +Epoch [3889/4000] Training [4/16] Loss: 0.00242 +Epoch [3889/4000] Training [5/16] Loss: 0.00232 +Epoch [3889/4000] Training [6/16] Loss: 0.00232 +Epoch [3889/4000] Training [7/16] Loss: 0.00215 +Epoch [3889/4000] Training [8/16] Loss: 0.00253 +Epoch [3889/4000] Training [9/16] Loss: 0.00336 +Epoch [3889/4000] Training [10/16] Loss: 0.00214 +Epoch [3889/4000] Training [11/16] Loss: 0.00235 +Epoch [3889/4000] Training [12/16] Loss: 0.00189 +Epoch [3889/4000] Training [13/16] Loss: 0.00219 +Epoch [3889/4000] Training [14/16] Loss: 0.00242 +Epoch [3889/4000] Training [15/16] Loss: 0.00196 +Epoch [3889/4000] Training [16/16] Loss: 0.00249 +Epoch [3889/4000] Training metric {'Train/mean dice_metric': 0.9989010095596313, 'Train/mean miou_metric': 0.9975250959396362, 'Train/mean f1': 0.9939306974411011, 'Train/mean precision': 0.9894142746925354, 'Train/mean recall': 0.9984886050224304, 'Train/mean hd95_metric': 0.48645341396331787} +Epoch [3889/4000] Validation [1/4] Loss: 0.41502 focal_loss 0.35052 dice_loss 0.06450 +Epoch [3889/4000] Validation [2/4] Loss: 0.95570 focal_loss 0.76776 dice_loss 0.18794 +Epoch [3889/4000] Validation [3/4] Loss: 0.26893 focal_loss 0.20670 dice_loss 0.06223 +Epoch [3889/4000] Validation [4/4] Loss: 0.37758 focal_loss 0.28307 dice_loss 0.09451 +Epoch [3889/4000] Validation metric {'Val/mean dice_metric': 0.9738758206367493, 'Val/mean miou_metric': 0.9602193832397461, 'Val/mean f1': 0.9762229919433594, 'Val/mean precision': 0.9735905528068542, 'Val/mean recall': 0.9788696765899658, 'Val/mean hd95_metric': 5.401269912719727} +Cheakpoint... +Epoch [3889/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738758206367493, 'Val/mean miou_metric': 0.9602193832397461, 'Val/mean f1': 0.9762229919433594, 'Val/mean precision': 0.9735905528068542, 'Val/mean recall': 0.9788696765899658, 'Val/mean hd95_metric': 5.401269912719727} +Epoch [3890/4000] Training [1/16] Loss: 0.00302 +Epoch [3890/4000] Training [2/16] Loss: 0.00261 +Epoch [3890/4000] Training [3/16] Loss: 0.00309 +Epoch [3890/4000] Training [4/16] Loss: 0.00303 +Epoch [3890/4000] Training [5/16] Loss: 0.00196 +Epoch [3890/4000] Training [6/16] Loss: 0.00196 +Epoch [3890/4000] Training [7/16] Loss: 0.00327 +Epoch [3890/4000] Training [8/16] Loss: 0.00249 +Epoch [3890/4000] Training [9/16] Loss: 0.00287 +Epoch [3890/4000] Training [10/16] Loss: 0.00174 +Epoch [3890/4000] Training [11/16] Loss: 0.00277 +Epoch [3890/4000] Training [12/16] Loss: 0.00166 +Epoch [3890/4000] Training [13/16] Loss: 0.00276 +Epoch [3890/4000] Training [14/16] Loss: 0.00148 +Epoch [3890/4000] Training [15/16] Loss: 0.00222 +Epoch [3890/4000] Training [16/16] Loss: 0.00261 +Epoch [3890/4000] Training metric {'Train/mean dice_metric': 0.9987587928771973, 'Train/mean miou_metric': 0.9972025156021118, 'Train/mean f1': 0.9931880831718445, 'Train/mean precision': 0.9881026744842529, 'Train/mean recall': 0.9983260631561279, 'Train/mean hd95_metric': 0.48899245262145996} +Epoch [3890/4000] Validation [1/4] Loss: 0.39055 focal_loss 0.32746 dice_loss 0.06309 +Epoch [3890/4000] Validation [2/4] Loss: 0.49000 focal_loss 0.37682 dice_loss 0.11318 +Epoch [3890/4000] Validation [3/4] Loss: 0.56888 focal_loss 0.47396 dice_loss 0.09492 +Epoch [3890/4000] Validation [4/4] Loss: 0.34567 focal_loss 0.25239 dice_loss 0.09328 +Epoch [3890/4000] Validation metric {'Val/mean dice_metric': 0.9736879467964172, 'Val/mean miou_metric': 0.9596608281135559, 'Val/mean f1': 0.9760238528251648, 'Val/mean precision': 0.9734570384025574, 'Val/mean recall': 0.978604257106781, 'Val/mean hd95_metric': 4.812359809875488} +Cheakpoint... +Epoch [3890/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736879467964172, 'Val/mean miou_metric': 0.9596608281135559, 'Val/mean f1': 0.9760238528251648, 'Val/mean precision': 0.9734570384025574, 'Val/mean recall': 0.978604257106781, 'Val/mean hd95_metric': 4.812359809875488} +Epoch [3891/4000] Training [1/16] Loss: 0.00241 +Epoch [3891/4000] Training [2/16] Loss: 0.00235 +Epoch [3891/4000] Training [3/16] Loss: 0.00160 +Epoch [3891/4000] Training [4/16] Loss: 0.00227 +Epoch [3891/4000] Training [5/16] Loss: 0.00339 +Epoch [3891/4000] Training [6/16] Loss: 0.00359 +Epoch [3891/4000] Training [7/16] Loss: 0.00264 +Epoch [3891/4000] Training [8/16] Loss: 0.00210 +Epoch [3891/4000] Training [9/16] Loss: 0.00225 +Epoch [3891/4000] Training [10/16] Loss: 0.00247 +Epoch [3891/4000] Training [11/16] Loss: 0.00202 +Epoch [3891/4000] Training [12/16] Loss: 0.00221 +Epoch [3891/4000] Training [13/16] Loss: 0.00230 +Epoch [3891/4000] Training [14/16] Loss: 0.00299 +Epoch [3891/4000] Training [15/16] Loss: 0.00273 +Epoch [3891/4000] Training [16/16] Loss: 0.00258 +Epoch [3891/4000] Training metric {'Train/mean dice_metric': 0.998775064945221, 'Train/mean miou_metric': 0.9972788691520691, 'Train/mean f1': 0.9937839508056641, 'Train/mean precision': 0.9892338514328003, 'Train/mean recall': 0.9983760118484497, 'Train/mean hd95_metric': 0.5410431623458862} +Epoch [3891/4000] Validation [1/4] Loss: 0.40826 focal_loss 0.34315 dice_loss 0.06510 +Epoch [3891/4000] Validation [2/4] Loss: 0.88534 focal_loss 0.68815 dice_loss 0.19719 +Epoch [3891/4000] Validation [3/4] Loss: 0.57822 focal_loss 0.47796 dice_loss 0.10026 +Epoch [3891/4000] Validation [4/4] Loss: 0.50064 focal_loss 0.39025 dice_loss 0.11039 +Epoch [3891/4000] Validation metric {'Val/mean dice_metric': 0.972007155418396, 'Val/mean miou_metric': 0.9577571749687195, 'Val/mean f1': 0.9757060408592224, 'Val/mean precision': 0.9734764695167542, 'Val/mean recall': 0.9779458045959473, 'Val/mean hd95_metric': 5.4016804695129395} +Cheakpoint... +Epoch [3891/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9720], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972007155418396, 'Val/mean miou_metric': 0.9577571749687195, 'Val/mean f1': 0.9757060408592224, 'Val/mean precision': 0.9734764695167542, 'Val/mean recall': 0.9779458045959473, 'Val/mean hd95_metric': 5.4016804695129395} +Epoch [3892/4000] Training [1/16] Loss: 0.00234 +Epoch [3892/4000] Training [2/16] Loss: 0.00190 +Epoch [3892/4000] Training [3/16] Loss: 0.00287 +Epoch [3892/4000] Training [4/16] Loss: 0.00174 +Epoch [3892/4000] Training [5/16] Loss: 0.00195 +Epoch [3892/4000] Training [6/16] Loss: 0.00228 +Epoch [3892/4000] Training [7/16] Loss: 0.00256 +Epoch [3892/4000] Training [8/16] Loss: 0.00190 +Epoch [3892/4000] Training [9/16] Loss: 0.00208 +Epoch [3892/4000] Training [10/16] Loss: 0.00193 +Epoch [3892/4000] Training [11/16] Loss: 0.00182 +Epoch [3892/4000] Training [12/16] Loss: 0.00358 +Epoch [3892/4000] Training [13/16] Loss: 0.00255 +Epoch [3892/4000] Training [14/16] Loss: 0.00381 +Epoch [3892/4000] Training [15/16] Loss: 0.00300 +Epoch [3892/4000] Training [16/16] Loss: 0.00331 +Epoch [3892/4000] Training metric {'Train/mean dice_metric': 0.9988018274307251, 'Train/mean miou_metric': 0.9973280429840088, 'Train/mean f1': 0.9938277006149292, 'Train/mean precision': 0.9892853498458862, 'Train/mean recall': 0.998412013053894, 'Train/mean hd95_metric': 0.4988570809364319} +Epoch [3892/4000] Validation [1/4] Loss: 0.41552 focal_loss 0.35442 dice_loss 0.06110 +Epoch [3892/4000] Validation [2/4] Loss: 0.95136 focal_loss 0.76298 dice_loss 0.18837 +Epoch [3892/4000] Validation [3/4] Loss: 0.53519 focal_loss 0.44334 dice_loss 0.09185 +Epoch [3892/4000] Validation [4/4] Loss: 0.33525 focal_loss 0.24842 dice_loss 0.08683 +Epoch [3892/4000] Validation metric {'Val/mean dice_metric': 0.975658118724823, 'Val/mean miou_metric': 0.9621425867080688, 'Val/mean f1': 0.9769613742828369, 'Val/mean precision': 0.9741067886352539, 'Val/mean recall': 0.9798327684402466, 'Val/mean hd95_metric': 4.732493877410889} +Cheakpoint... +Epoch [3892/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975658118724823, 'Val/mean miou_metric': 0.9621425867080688, 'Val/mean f1': 0.9769613742828369, 'Val/mean precision': 0.9741067886352539, 'Val/mean recall': 0.9798327684402466, 'Val/mean hd95_metric': 4.732493877410889} +Epoch [3893/4000] Training [1/16] Loss: 0.00217 +Epoch [3893/4000] Training [2/16] Loss: 0.00275 +Epoch [3893/4000] Training [3/16] Loss: 0.00232 +Epoch [3893/4000] Training [4/16] Loss: 0.00457 +Epoch [3893/4000] Training [5/16] Loss: 0.00177 +Epoch [3893/4000] Training [6/16] Loss: 0.00215 +Epoch [3893/4000] Training [7/16] Loss: 0.00182 +Epoch [3893/4000] Training [8/16] Loss: 0.00262 +Epoch [3893/4000] Training [9/16] Loss: 0.00221 +Epoch [3893/4000] Training [10/16] Loss: 0.00221 +Epoch [3893/4000] Training [11/16] Loss: 0.00320 +Epoch [3893/4000] Training [12/16] Loss: 0.00259 +Epoch [3893/4000] Training [13/16] Loss: 0.00262 +Epoch [3893/4000] Training [14/16] Loss: 0.00195 +Epoch [3893/4000] Training [15/16] Loss: 0.00140 +Epoch [3893/4000] Training [16/16] Loss: 0.00240 +Epoch [3893/4000] Training metric {'Train/mean dice_metric': 0.9988328218460083, 'Train/mean miou_metric': 0.9973914623260498, 'Train/mean f1': 0.9938969016075134, 'Train/mean precision': 0.9893729090690613, 'Train/mean recall': 0.9984623789787292, 'Train/mean hd95_metric': 0.5186100602149963} +Epoch [3893/4000] Validation [1/4] Loss: 0.39473 focal_loss 0.33492 dice_loss 0.05981 +Epoch [3893/4000] Validation [2/4] Loss: 0.48242 focal_loss 0.37029 dice_loss 0.11213 +Epoch [3893/4000] Validation [3/4] Loss: 0.54395 focal_loss 0.45155 dice_loss 0.09241 +Epoch [3893/4000] Validation [4/4] Loss: 0.48834 focal_loss 0.37715 dice_loss 0.11119 +Epoch [3893/4000] Validation metric {'Val/mean dice_metric': 0.9747329950332642, 'Val/mean miou_metric': 0.9604440927505493, 'Val/mean f1': 0.9766196608543396, 'Val/mean precision': 0.9740108847618103, 'Val/mean recall': 0.9792423248291016, 'Val/mean hd95_metric': 4.906247615814209} +Cheakpoint... +Epoch [3893/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747329950332642, 'Val/mean miou_metric': 0.9604440927505493, 'Val/mean f1': 0.9766196608543396, 'Val/mean precision': 0.9740108847618103, 'Val/mean recall': 0.9792423248291016, 'Val/mean hd95_metric': 4.906247615814209} +Epoch [3894/4000] Training [1/16] Loss: 0.00377 +Epoch [3894/4000] Training [2/16] Loss: 0.00237 +Epoch [3894/4000] Training [3/16] Loss: 0.00205 +Epoch [3894/4000] Training [4/16] Loss: 0.00371 +Epoch [3894/4000] Training [5/16] Loss: 0.00241 +Epoch [3894/4000] Training [6/16] Loss: 0.00174 +Epoch [3894/4000] Training [7/16] Loss: 0.00278 +Epoch [3894/4000] Training [8/16] Loss: 0.00237 +Epoch [3894/4000] Training [9/16] Loss: 0.00206 +Epoch [3894/4000] Training [10/16] Loss: 0.00202 +Epoch [3894/4000] Training [11/16] Loss: 0.00243 +Epoch [3894/4000] Training [12/16] Loss: 0.00261 +Epoch [3894/4000] Training [13/16] Loss: 0.00298 +Epoch [3894/4000] Training [14/16] Loss: 0.00194 +Epoch [3894/4000] Training [15/16] Loss: 0.00216 +Epoch [3894/4000] Training [16/16] Loss: 0.00212 +Epoch [3894/4000] Training metric {'Train/mean dice_metric': 0.9987668991088867, 'Train/mean miou_metric': 0.9972245097160339, 'Train/mean f1': 0.992931067943573, 'Train/mean precision': 0.9876403212547302, 'Train/mean recall': 0.9982790350914001, 'Train/mean hd95_metric': 0.538894772529602} +Epoch [3894/4000] Validation [1/4] Loss: 0.38603 focal_loss 0.32456 dice_loss 0.06147 +Epoch [3894/4000] Validation [2/4] Loss: 0.60737 focal_loss 0.45205 dice_loss 0.15532 +Epoch [3894/4000] Validation [3/4] Loss: 0.30700 focal_loss 0.23705 dice_loss 0.06995 +Epoch [3894/4000] Validation [4/4] Loss: 0.47209 focal_loss 0.35161 dice_loss 0.12048 +Epoch [3894/4000] Validation metric {'Val/mean dice_metric': 0.9734653234481812, 'Val/mean miou_metric': 0.9597235918045044, 'Val/mean f1': 0.9751233458518982, 'Val/mean precision': 0.9720284342765808, 'Val/mean recall': 0.978238046169281, 'Val/mean hd95_metric': 5.627713203430176} +Cheakpoint... +Epoch [3894/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734653234481812, 'Val/mean miou_metric': 0.9597235918045044, 'Val/mean f1': 0.9751233458518982, 'Val/mean precision': 0.9720284342765808, 'Val/mean recall': 0.978238046169281, 'Val/mean hd95_metric': 5.627713203430176} +Epoch [3895/4000] Training [1/16] Loss: 0.00248 +Epoch [3895/4000] Training [2/16] Loss: 0.00228 +Epoch [3895/4000] Training [3/16] Loss: 0.00228 +Epoch [3895/4000] Training [4/16] Loss: 0.00268 +Epoch [3895/4000] Training [5/16] Loss: 0.00334 +Epoch [3895/4000] Training [6/16] Loss: 0.00310 +Epoch [3895/4000] Training [7/16] Loss: 0.00242 +Epoch [3895/4000] Training [8/16] Loss: 0.00287 +Epoch [3895/4000] Training [9/16] Loss: 0.00263 +Epoch [3895/4000] Training [10/16] Loss: 0.00188 +Epoch [3895/4000] Training [11/16] Loss: 0.00273 +Epoch [3895/4000] Training [12/16] Loss: 0.00277 +Epoch [3895/4000] Training [13/16] Loss: 0.00192 +Epoch [3895/4000] Training [14/16] Loss: 0.00252 +Epoch [3895/4000] Training [15/16] Loss: 0.00251 +Epoch [3895/4000] Training [16/16] Loss: 0.00358 +Epoch [3895/4000] Training metric {'Train/mean dice_metric': 0.9987409710884094, 'Train/mean miou_metric': 0.997205376625061, 'Train/mean f1': 0.9936985969543457, 'Train/mean precision': 0.9891111254692078, 'Train/mean recall': 0.9983288645744324, 'Train/mean hd95_metric': 0.5267853736877441} +Epoch [3895/4000] Validation [1/4] Loss: 0.46352 focal_loss 0.39753 dice_loss 0.06599 +Epoch [3895/4000] Validation [2/4] Loss: 0.47552 focal_loss 0.36493 dice_loss 0.11059 +Epoch [3895/4000] Validation [3/4] Loss: 0.54002 focal_loss 0.44655 dice_loss 0.09347 +Epoch [3895/4000] Validation [4/4] Loss: 0.41464 focal_loss 0.30538 dice_loss 0.10926 +Epoch [3895/4000] Validation metric {'Val/mean dice_metric': 0.9751423001289368, 'Val/mean miou_metric': 0.9606689214706421, 'Val/mean f1': 0.9765202403068542, 'Val/mean precision': 0.9740102291107178, 'Val/mean recall': 0.979043185710907, 'Val/mean hd95_metric': 4.738215923309326} +Cheakpoint... +Epoch [3895/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751423001289368, 'Val/mean miou_metric': 0.9606689214706421, 'Val/mean f1': 0.9765202403068542, 'Val/mean precision': 0.9740102291107178, 'Val/mean recall': 0.979043185710907, 'Val/mean hd95_metric': 4.738215923309326} +Epoch [3896/4000] Training [1/16] Loss: 0.00172 +Epoch [3896/4000] Training [2/16] Loss: 0.00166 +Epoch [3896/4000] Training [3/16] Loss: 0.00336 +Epoch [3896/4000] Training [4/16] Loss: 0.00166 +Epoch [3896/4000] Training [5/16] Loss: 0.00324 +Epoch [3896/4000] Training [6/16] Loss: 0.00201 +Epoch [3896/4000] Training [7/16] Loss: 0.00317 +Epoch [3896/4000] Training [8/16] Loss: 0.00201 +Epoch [3896/4000] Training [9/16] Loss: 0.00259 +Epoch [3896/4000] Training [10/16] Loss: 0.00222 +Epoch [3896/4000] Training [11/16] Loss: 0.00191 +Epoch [3896/4000] Training [12/16] Loss: 0.00240 +Epoch [3896/4000] Training [13/16] Loss: 0.00389 +Epoch [3896/4000] Training [14/16] Loss: 0.00255 +Epoch [3896/4000] Training [15/16] Loss: 0.00209 +Epoch [3896/4000] Training [16/16] Loss: 0.00242 +Epoch [3896/4000] Training metric {'Train/mean dice_metric': 0.9988892078399658, 'Train/mean miou_metric': 0.9975043535232544, 'Train/mean f1': 0.9939047694206238, 'Train/mean precision': 0.9893863797187805, 'Train/mean recall': 0.9984645843505859, 'Train/mean hd95_metric': 0.46623843908309937} +Epoch [3896/4000] Validation [1/4] Loss: 0.36584 focal_loss 0.30460 dice_loss 0.06124 +Epoch [3896/4000] Validation [2/4] Loss: 1.08344 focal_loss 0.89381 dice_loss 0.18963 +Epoch [3896/4000] Validation [3/4] Loss: 0.52150 focal_loss 0.42222 dice_loss 0.09928 +Epoch [3896/4000] Validation [4/4] Loss: 0.37806 focal_loss 0.28559 dice_loss 0.09247 +Epoch [3896/4000] Validation metric {'Val/mean dice_metric': 0.9747377634048462, 'Val/mean miou_metric': 0.9609441757202148, 'Val/mean f1': 0.9766137599945068, 'Val/mean precision': 0.9742540121078491, 'Val/mean recall': 0.9789849519729614, 'Val/mean hd95_metric': 4.430848598480225} +Cheakpoint... +Epoch [3896/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747377634048462, 'Val/mean miou_metric': 0.9609441757202148, 'Val/mean f1': 0.9766137599945068, 'Val/mean precision': 0.9742540121078491, 'Val/mean recall': 0.9789849519729614, 'Val/mean hd95_metric': 4.430848598480225} +Epoch [3897/4000] Training [1/16] Loss: 0.00289 +Epoch [3897/4000] Training [2/16] Loss: 0.00152 +Epoch [3897/4000] Training [3/16] Loss: 0.00307 +Epoch [3897/4000] Training [4/16] Loss: 0.00212 +Epoch [3897/4000] Training [5/16] Loss: 0.00193 +Epoch [3897/4000] Training [6/16] Loss: 0.00257 +Epoch [3897/4000] Training [7/16] Loss: 0.00275 +Epoch [3897/4000] Training [8/16] Loss: 0.00229 +Epoch [3897/4000] Training [9/16] Loss: 0.00124 +Epoch [3897/4000] Training [10/16] Loss: 0.00333 +Epoch [3897/4000] Training [11/16] Loss: 0.00250 +Epoch [3897/4000] Training [12/16] Loss: 0.00268 +Epoch [3897/4000] Training [13/16] Loss: 0.00153 +Epoch [3897/4000] Training [14/16] Loss: 0.00197 +Epoch [3897/4000] Training [15/16] Loss: 0.00216 +Epoch [3897/4000] Training [16/16] Loss: 0.00194 +Epoch [3897/4000] Training metric {'Train/mean dice_metric': 0.9989290833473206, 'Train/mean miou_metric': 0.9975730776786804, 'Train/mean f1': 0.9937356114387512, 'Train/mean precision': 0.9890149235725403, 'Train/mean recall': 0.9985015392303467, 'Train/mean hd95_metric': 0.46057432889938354} +Epoch [3897/4000] Validation [1/4] Loss: 0.42690 focal_loss 0.36337 dice_loss 0.06353 +Epoch [3897/4000] Validation [2/4] Loss: 1.09226 focal_loss 0.90424 dice_loss 0.18802 +Epoch [3897/4000] Validation [3/4] Loss: 0.51934 focal_loss 0.42943 dice_loss 0.08992 +Epoch [3897/4000] Validation [4/4] Loss: 0.38488 focal_loss 0.28247 dice_loss 0.10240 +Epoch [3897/4000] Validation metric {'Val/mean dice_metric': 0.974407970905304, 'Val/mean miou_metric': 0.9609310030937195, 'Val/mean f1': 0.9766180515289307, 'Val/mean precision': 0.9739639163017273, 'Val/mean recall': 0.9792866706848145, 'Val/mean hd95_metric': 4.493863105773926} +Cheakpoint... +Epoch [3897/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974407970905304, 'Val/mean miou_metric': 0.9609310030937195, 'Val/mean f1': 0.9766180515289307, 'Val/mean precision': 0.9739639163017273, 'Val/mean recall': 0.9792866706848145, 'Val/mean hd95_metric': 4.493863105773926} +Epoch [3898/4000] Training [1/16] Loss: 0.00298 +Epoch [3898/4000] Training [2/16] Loss: 0.00205 +Epoch [3898/4000] Training [3/16] Loss: 0.00225 +Epoch [3898/4000] Training [4/16] Loss: 0.00275 +Epoch [3898/4000] Training [5/16] Loss: 0.00240 +Epoch [3898/4000] Training [6/16] Loss: 0.00180 +Epoch [3898/4000] Training [7/16] Loss: 0.00381 +Epoch [3898/4000] Training [8/16] Loss: 0.00181 +Epoch [3898/4000] Training [9/16] Loss: 0.00365 +Epoch [3898/4000] Training [10/16] Loss: 0.00200 +Epoch [3898/4000] Training [11/16] Loss: 0.00235 +Epoch [3898/4000] Training [12/16] Loss: 0.00264 +Epoch [3898/4000] Training [13/16] Loss: 0.00207 +Epoch [3898/4000] Training [14/16] Loss: 0.00219 +Epoch [3898/4000] Training [15/16] Loss: 0.00185 +Epoch [3898/4000] Training [16/16] Loss: 0.00234 +Epoch [3898/4000] Training metric {'Train/mean dice_metric': 0.9987216591835022, 'Train/mean miou_metric': 0.997170627117157, 'Train/mean f1': 0.9937112331390381, 'Train/mean precision': 0.9891857504844666, 'Train/mean recall': 0.9982783198356628, 'Train/mean hd95_metric': 0.5384343266487122} +Epoch [3898/4000] Validation [1/4] Loss: 0.45298 focal_loss 0.38735 dice_loss 0.06563 +Epoch [3898/4000] Validation [2/4] Loss: 0.91250 focal_loss 0.71039 dice_loss 0.20211 +Epoch [3898/4000] Validation [3/4] Loss: 0.56983 focal_loss 0.47016 dice_loss 0.09967 +Epoch [3898/4000] Validation [4/4] Loss: 0.48512 focal_loss 0.38076 dice_loss 0.10436 +Epoch [3898/4000] Validation metric {'Val/mean dice_metric': 0.9733039140701294, 'Val/mean miou_metric': 0.958827018737793, 'Val/mean f1': 0.9756181836128235, 'Val/mean precision': 0.9739180207252502, 'Val/mean recall': 0.9773243069648743, 'Val/mean hd95_metric': 5.155696868896484} +Cheakpoint... +Epoch [3898/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733039140701294, 'Val/mean miou_metric': 0.958827018737793, 'Val/mean f1': 0.9756181836128235, 'Val/mean precision': 0.9739180207252502, 'Val/mean recall': 0.9773243069648743, 'Val/mean hd95_metric': 5.155696868896484} +Epoch [3899/4000] Training [1/16] Loss: 0.00333 +Epoch [3899/4000] Training [2/16] Loss: 0.00244 +Epoch [3899/4000] Training [3/16] Loss: 0.00323 +Epoch [3899/4000] Training [4/16] Loss: 0.00159 +Epoch [3899/4000] Training [5/16] Loss: 0.00226 +Epoch [3899/4000] Training [6/16] Loss: 0.00245 +Epoch [3899/4000] Training [7/16] Loss: 0.00181 +Epoch [3899/4000] Training [8/16] Loss: 0.00339 +Epoch [3899/4000] Training [9/16] Loss: 0.00167 +Epoch [3899/4000] Training [10/16] Loss: 0.00317 +Epoch [3899/4000] Training [11/16] Loss: 0.00219 +Epoch [3899/4000] Training [12/16] Loss: 0.00266 +Epoch [3899/4000] Training [13/16] Loss: 0.00257 +Epoch [3899/4000] Training [14/16] Loss: 0.00260 +Epoch [3899/4000] Training [15/16] Loss: 0.00250 +Epoch [3899/4000] Training [16/16] Loss: 0.00195 +Epoch [3899/4000] Training metric {'Train/mean dice_metric': 0.9979361891746521, 'Train/mean miou_metric': 0.9960851669311523, 'Train/mean f1': 0.9931729435920715, 'Train/mean precision': 0.9891786575317383, 'Train/mean recall': 0.9971998333930969, 'Train/mean hd95_metric': 0.6266450881958008} +Epoch [3899/4000] Validation [1/4] Loss: 0.38432 focal_loss 0.32195 dice_loss 0.06238 +Epoch [3899/4000] Validation [2/4] Loss: 0.47699 focal_loss 0.36735 dice_loss 0.10964 +Epoch [3899/4000] Validation [3/4] Loss: 0.32882 focal_loss 0.25735 dice_loss 0.07147 +Epoch [3899/4000] Validation [4/4] Loss: 0.33999 focal_loss 0.25126 dice_loss 0.08873 +Epoch [3899/4000] Validation metric {'Val/mean dice_metric': 0.9762312769889832, 'Val/mean miou_metric': 0.961929202079773, 'Val/mean f1': 0.9767181277275085, 'Val/mean precision': 0.9744725823402405, 'Val/mean recall': 0.9789740443229675, 'Val/mean hd95_metric': 5.0728631019592285} +Cheakpoint... +Epoch [3899/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9762], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9762312769889832, 'Val/mean miou_metric': 0.961929202079773, 'Val/mean f1': 0.9767181277275085, 'Val/mean precision': 0.9744725823402405, 'Val/mean recall': 0.9789740443229675, 'Val/mean hd95_metric': 5.0728631019592285} +Epoch [3900/4000] Training [1/16] Loss: 0.00322 +Epoch [3900/4000] Training [2/16] Loss: 0.00283 +Epoch [3900/4000] Training [3/16] Loss: 0.00295 +Epoch [3900/4000] Training [4/16] Loss: 0.00241 +Epoch [3900/4000] Training [5/16] Loss: 0.00196 +Epoch [3900/4000] Training [6/16] Loss: 0.00248 +Epoch [3900/4000] Training [7/16] Loss: 0.00188 +Epoch [3900/4000] Training [8/16] Loss: 0.00257 +Epoch [3900/4000] Training [9/16] Loss: 0.00250 +Epoch [3900/4000] Training [10/16] Loss: 0.00310 +Epoch [3900/4000] Training [11/16] Loss: 0.00201 +Epoch [3900/4000] Training [12/16] Loss: 0.00151 +Epoch [3900/4000] Training [13/16] Loss: 0.00223 +Epoch [3900/4000] Training [14/16] Loss: 0.00160 +Epoch [3900/4000] Training [15/16] Loss: 0.00221 +Epoch [3900/4000] Training [16/16] Loss: 0.00184 +Epoch [3900/4000] Training metric {'Train/mean dice_metric': 0.998850405216217, 'Train/mean miou_metric': 0.9973641633987427, 'Train/mean f1': 0.9925223588943481, 'Train/mean precision': 0.9867830872535706, 'Train/mean recall': 0.9983288049697876, 'Train/mean hd95_metric': 0.4933869540691376} +Epoch [3900/4000] Validation [1/4] Loss: 0.44800 focal_loss 0.38464 dice_loss 0.06337 +Epoch [3900/4000] Validation [2/4] Loss: 0.53785 focal_loss 0.40477 dice_loss 0.13308 +Epoch [3900/4000] Validation [3/4] Loss: 0.54799 focal_loss 0.45533 dice_loss 0.09266 +Epoch [3900/4000] Validation [4/4] Loss: 0.31978 focal_loss 0.23293 dice_loss 0.08685 +Epoch [3900/4000] Validation metric {'Val/mean dice_metric': 0.9748066067695618, 'Val/mean miou_metric': 0.9605442881584167, 'Val/mean f1': 0.9754301905632019, 'Val/mean precision': 0.9716732501983643, 'Val/mean recall': 0.9792163968086243, 'Val/mean hd95_metric': 5.117851734161377} +Cheakpoint... +Epoch [3900/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748066067695618, 'Val/mean miou_metric': 0.9605442881584167, 'Val/mean f1': 0.9754301905632019, 'Val/mean precision': 0.9716732501983643, 'Val/mean recall': 0.9792163968086243, 'Val/mean hd95_metric': 5.117851734161377} +Epoch [3901/4000] Training [1/16] Loss: 0.00234 +Epoch [3901/4000] Training [2/16] Loss: 0.00349 +Epoch [3901/4000] Training [3/16] Loss: 0.00274 +Epoch [3901/4000] Training [4/16] Loss: 0.00216 +Epoch [3901/4000] Training [5/16] Loss: 0.00202 +Epoch [3901/4000] Training [6/16] Loss: 0.00203 +Epoch [3901/4000] Training [7/16] Loss: 0.00321 +Epoch [3901/4000] Training [8/16] Loss: 0.00208 +Epoch [3901/4000] Training [9/16] Loss: 0.00106 +Epoch [3901/4000] Training [10/16] Loss: 0.00210 +Epoch [3901/4000] Training [11/16] Loss: 0.00132 +Epoch [3901/4000] Training [12/16] Loss: 0.00179 +Epoch [3901/4000] Training [13/16] Loss: 0.00279 +Epoch [3901/4000] Training [14/16] Loss: 0.00245 +Epoch [3901/4000] Training [15/16] Loss: 0.00190 +Epoch [3901/4000] Training [16/16] Loss: 0.00382 +Epoch [3901/4000] Training metric {'Train/mean dice_metric': 0.9987467527389526, 'Train/mean miou_metric': 0.9972091913223267, 'Train/mean f1': 0.9935705065727234, 'Train/mean precision': 0.9888849854469299, 'Train/mean recall': 0.9983006715774536, 'Train/mean hd95_metric': 0.5439306497573853} +Epoch [3901/4000] Validation [1/4] Loss: 0.47861 focal_loss 0.41311 dice_loss 0.06550 +Epoch [3901/4000] Validation [2/4] Loss: 0.93041 focal_loss 0.72601 dice_loss 0.20440 +Epoch [3901/4000] Validation [3/4] Loss: 0.55411 focal_loss 0.45767 dice_loss 0.09644 +Epoch [3901/4000] Validation [4/4] Loss: 0.38478 focal_loss 0.29213 dice_loss 0.09265 +Epoch [3901/4000] Validation metric {'Val/mean dice_metric': 0.9732626676559448, 'Val/mean miou_metric': 0.9590984582901001, 'Val/mean f1': 0.9758684039115906, 'Val/mean precision': 0.9736121296882629, 'Val/mean recall': 0.9781351685523987, 'Val/mean hd95_metric': 5.0445122718811035} +Cheakpoint... +Epoch [3901/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732626676559448, 'Val/mean miou_metric': 0.9590984582901001, 'Val/mean f1': 0.9758684039115906, 'Val/mean precision': 0.9736121296882629, 'Val/mean recall': 0.9781351685523987, 'Val/mean hd95_metric': 5.0445122718811035} +Epoch [3902/4000] Training [1/16] Loss: 0.00230 +Epoch [3902/4000] Training [2/16] Loss: 0.00264 +Epoch [3902/4000] Training [3/16] Loss: 0.00273 +Epoch [3902/4000] Training [4/16] Loss: 0.00312 +Epoch [3902/4000] Training [5/16] Loss: 0.00181 +Epoch [3902/4000] Training [6/16] Loss: 0.00274 +Epoch [3902/4000] Training [7/16] Loss: 0.00212 +Epoch [3902/4000] Training [8/16] Loss: 0.00311 +Epoch [3902/4000] Training [9/16] Loss: 0.00379 +Epoch [3902/4000] Training [10/16] Loss: 0.00231 +Epoch [3902/4000] Training [11/16] Loss: 0.00233 +Epoch [3902/4000] Training [12/16] Loss: 0.00217 +Epoch [3902/4000] Training [13/16] Loss: 0.00342 +Epoch [3902/4000] Training [14/16] Loss: 0.00190 +Epoch [3902/4000] Training [15/16] Loss: 0.00325 +Epoch [3902/4000] Training [16/16] Loss: 0.00182 +Epoch [3902/4000] Training metric {'Train/mean dice_metric': 0.9986590147018433, 'Train/mean miou_metric': 0.9970415830612183, 'Train/mean f1': 0.9936932921409607, 'Train/mean precision': 0.9891480803489685, 'Train/mean recall': 0.9982804656028748, 'Train/mean hd95_metric': 0.5546172857284546} +Epoch [3902/4000] Validation [1/4] Loss: 0.43654 focal_loss 0.37194 dice_loss 0.06460 +Epoch [3902/4000] Validation [2/4] Loss: 1.07712 focal_loss 0.88730 dice_loss 0.18982 +Epoch [3902/4000] Validation [3/4] Loss: 0.54332 focal_loss 0.45206 dice_loss 0.09125 +Epoch [3902/4000] Validation [4/4] Loss: 0.48526 focal_loss 0.37435 dice_loss 0.11091 +Epoch [3902/4000] Validation metric {'Val/mean dice_metric': 0.9738258123397827, 'Val/mean miou_metric': 0.959887683391571, 'Val/mean f1': 0.976489245891571, 'Val/mean precision': 0.9741563200950623, 'Val/mean recall': 0.9788333177566528, 'Val/mean hd95_metric': 4.6788330078125} +Cheakpoint... +Epoch [3902/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738258123397827, 'Val/mean miou_metric': 0.959887683391571, 'Val/mean f1': 0.976489245891571, 'Val/mean precision': 0.9741563200950623, 'Val/mean recall': 0.9788333177566528, 'Val/mean hd95_metric': 4.6788330078125} +Epoch [3903/4000] Training [1/16] Loss: 0.00387 +Epoch [3903/4000] Training [2/16] Loss: 0.00256 +Epoch [3903/4000] Training [3/16] Loss: 0.00247 +Epoch [3903/4000] Training [4/16] Loss: 0.00195 +Epoch [3903/4000] Training [5/16] Loss: 0.00274 +Epoch [3903/4000] Training [6/16] Loss: 0.00184 +Epoch [3903/4000] Training [7/16] Loss: 0.00287 +Epoch [3903/4000] Training [8/16] Loss: 0.00255 +Epoch [3903/4000] Training [9/16] Loss: 0.00146 +Epoch [3903/4000] Training [10/16] Loss: 0.00311 +Epoch [3903/4000] Training [11/16] Loss: 0.00187 +Epoch [3903/4000] Training [12/16] Loss: 0.00330 +Epoch [3903/4000] Training [13/16] Loss: 0.00265 +Epoch [3903/4000] Training [14/16] Loss: 0.00204 +Epoch [3903/4000] Training [15/16] Loss: 0.00179 +Epoch [3903/4000] Training [16/16] Loss: 0.00262 +Epoch [3903/4000] Training metric {'Train/mean dice_metric': 0.998772382736206, 'Train/mean miou_metric': 0.9972347021102905, 'Train/mean f1': 0.9929161071777344, 'Train/mean precision': 0.9876629114151001, 'Train/mean recall': 0.9982255101203918, 'Train/mean hd95_metric': 0.5375553369522095} +Epoch [3903/4000] Validation [1/4] Loss: 0.42480 focal_loss 0.36184 dice_loss 0.06296 +Epoch [3903/4000] Validation [2/4] Loss: 1.06747 focal_loss 0.87990 dice_loss 0.18757 +Epoch [3903/4000] Validation [3/4] Loss: 0.54467 focal_loss 0.45030 dice_loss 0.09437 +Epoch [3903/4000] Validation [4/4] Loss: 0.32637 focal_loss 0.23746 dice_loss 0.08890 +Epoch [3903/4000] Validation metric {'Val/mean dice_metric': 0.9745019674301147, 'Val/mean miou_metric': 0.9610183835029602, 'Val/mean f1': 0.9759650230407715, 'Val/mean precision': 0.9728267788887024, 'Val/mean recall': 0.9791234731674194, 'Val/mean hd95_metric': 4.5978827476501465} +Cheakpoint... +Epoch [3903/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745019674301147, 'Val/mean miou_metric': 0.9610183835029602, 'Val/mean f1': 0.9759650230407715, 'Val/mean precision': 0.9728267788887024, 'Val/mean recall': 0.9791234731674194, 'Val/mean hd95_metric': 4.5978827476501465} +Epoch [3904/4000] Training [1/16] Loss: 0.00292 +Epoch [3904/4000] Training [2/16] Loss: 0.00247 +Epoch [3904/4000] Training [3/16] Loss: 0.00186 +Epoch [3904/4000] Training [4/16] Loss: 0.00214 +Epoch [3904/4000] Training [5/16] Loss: 0.00255 +Epoch [3904/4000] Training [6/16] Loss: 0.00199 +Epoch [3904/4000] Training [7/16] Loss: 0.00273 +Epoch [3904/4000] Training [8/16] Loss: 0.00313 +Epoch [3904/4000] Training [9/16] Loss: 0.00131 +Epoch [3904/4000] Training [10/16] Loss: 0.00204 +Epoch [3904/4000] Training [11/16] Loss: 0.00145 +Epoch [3904/4000] Training [12/16] Loss: 0.00231 +Epoch [3904/4000] Training [13/16] Loss: 0.00260 +Epoch [3904/4000] Training [14/16] Loss: 0.00276 +Epoch [3904/4000] Training [15/16] Loss: 0.00208 +Epoch [3904/4000] Training [16/16] Loss: 0.00285 +Epoch [3904/4000] Training metric {'Train/mean dice_metric': 0.9988662004470825, 'Train/mean miou_metric': 0.9974328875541687, 'Train/mean f1': 0.9933145046234131, 'Train/mean precision': 0.9882597923278809, 'Train/mean recall': 0.9984212517738342, 'Train/mean hd95_metric': 0.4682193994522095} +Epoch [3904/4000] Validation [1/4] Loss: 0.37668 focal_loss 0.31582 dice_loss 0.06086 +Epoch [3904/4000] Validation [2/4] Loss: 0.98753 focal_loss 0.75240 dice_loss 0.23513 +Epoch [3904/4000] Validation [3/4] Loss: 0.53151 focal_loss 0.44078 dice_loss 0.09072 +Epoch [3904/4000] Validation [4/4] Loss: 0.35265 focal_loss 0.26296 dice_loss 0.08969 +Epoch [3904/4000] Validation metric {'Val/mean dice_metric': 0.972443699836731, 'Val/mean miou_metric': 0.9587764739990234, 'Val/mean f1': 0.9751609563827515, 'Val/mean precision': 0.9724525809288025, 'Val/mean recall': 0.9778843522071838, 'Val/mean hd95_metric': 5.140616416931152} +Cheakpoint... +Epoch [3904/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9724], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.972443699836731, 'Val/mean miou_metric': 0.9587764739990234, 'Val/mean f1': 0.9751609563827515, 'Val/mean precision': 0.9724525809288025, 'Val/mean recall': 0.9778843522071838, 'Val/mean hd95_metric': 5.140616416931152} +Epoch [3905/4000] Training [1/16] Loss: 0.00212 +Epoch [3905/4000] Training [2/16] Loss: 0.00368 +Epoch [3905/4000] Training [3/16] Loss: 0.00247 +Epoch [3905/4000] Training [4/16] Loss: 0.00242 +Epoch [3905/4000] Training [5/16] Loss: 0.00156 +Epoch [3905/4000] Training [6/16] Loss: 0.00231 +Epoch [3905/4000] Training [7/16] Loss: 0.00189 +Epoch [3905/4000] Training [8/16] Loss: 0.00228 +Epoch [3905/4000] Training [9/16] Loss: 0.00201 +Epoch [3905/4000] Training [10/16] Loss: 0.00215 +Epoch [3905/4000] Training [11/16] Loss: 0.00191 +Epoch [3905/4000] Training [12/16] Loss: 0.00408 +Epoch [3905/4000] Training [13/16] Loss: 0.00201 +Epoch [3905/4000] Training [14/16] Loss: 0.00407 +Epoch [3905/4000] Training [15/16] Loss: 0.00237 +Epoch [3905/4000] Training [16/16] Loss: 0.00495 +Epoch [3905/4000] Training metric {'Train/mean dice_metric': 0.9988088011741638, 'Train/mean miou_metric': 0.9973353147506714, 'Train/mean f1': 0.9936482906341553, 'Train/mean precision': 0.9889378547668457, 'Train/mean recall': 0.9984038472175598, 'Train/mean hd95_metric': 0.5183555483818054} +Epoch [3905/4000] Validation [1/4] Loss: 0.46732 focal_loss 0.40134 dice_loss 0.06598 +Epoch [3905/4000] Validation [2/4] Loss: 0.57693 focal_loss 0.42584 dice_loss 0.15110 +Epoch [3905/4000] Validation [3/4] Loss: 0.59401 focal_loss 0.49434 dice_loss 0.09966 +Epoch [3905/4000] Validation [4/4] Loss: 0.39895 focal_loss 0.29049 dice_loss 0.10846 +Epoch [3905/4000] Validation metric {'Val/mean dice_metric': 0.9740279912948608, 'Val/mean miou_metric': 0.9597376585006714, 'Val/mean f1': 0.9759737253189087, 'Val/mean precision': 0.974227249622345, 'Val/mean recall': 0.9777266383171082, 'Val/mean hd95_metric': 4.891314506530762} +Cheakpoint... +Epoch [3905/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740279912948608, 'Val/mean miou_metric': 0.9597376585006714, 'Val/mean f1': 0.9759737253189087, 'Val/mean precision': 0.974227249622345, 'Val/mean recall': 0.9777266383171082, 'Val/mean hd95_metric': 4.891314506530762} +Epoch [3906/4000] Training [1/16] Loss: 0.00239 +Epoch [3906/4000] Training [2/16] Loss: 0.00206 +Epoch [3906/4000] Training [3/16] Loss: 0.01603 +Epoch [3906/4000] Training [4/16] Loss: 0.00182 +Epoch [3906/4000] Training [5/16] Loss: 0.00333 +Epoch [3906/4000] Training [6/16] Loss: 0.00174 +Epoch [3906/4000] Training [7/16] Loss: 0.00193 +Epoch [3906/4000] Training [8/16] Loss: 0.00186 +Epoch [3906/4000] Training [9/16] Loss: 0.00153 +Epoch [3906/4000] Training [10/16] Loss: 0.00180 +Epoch [3906/4000] Training [11/16] Loss: 0.00176 +Epoch [3906/4000] Training [12/16] Loss: 0.00417 +Epoch [3906/4000] Training [13/16] Loss: 0.00223 +Epoch [3906/4000] Training [14/16] Loss: 0.00252 +Epoch [3906/4000] Training [15/16] Loss: 0.00307 +Epoch [3906/4000] Training [16/16] Loss: 0.00372 +Epoch [3906/4000] Training metric {'Train/mean dice_metric': 0.9985953569412231, 'Train/mean miou_metric': 0.9969203472137451, 'Train/mean f1': 0.9935434460639954, 'Train/mean precision': 0.9887511134147644, 'Train/mean recall': 0.9983825087547302, 'Train/mean hd95_metric': 0.5094470977783203} +Epoch [3906/4000] Validation [1/4] Loss: 0.38159 focal_loss 0.31819 dice_loss 0.06340 +Epoch [3906/4000] Validation [2/4] Loss: 0.61757 focal_loss 0.44903 dice_loss 0.16853 +Epoch [3906/4000] Validation [3/4] Loss: 0.54658 focal_loss 0.45491 dice_loss 0.09168 +Epoch [3906/4000] Validation [4/4] Loss: 0.33672 focal_loss 0.23466 dice_loss 0.10206 +Epoch [3906/4000] Validation metric {'Val/mean dice_metric': 0.9739959836006165, 'Val/mean miou_metric': 0.9597074389457703, 'Val/mean f1': 0.9761190414428711, 'Val/mean precision': 0.9733490943908691, 'Val/mean recall': 0.9789047241210938, 'Val/mean hd95_metric': 4.803253173828125} +Cheakpoint... +Epoch [3906/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739959836006165, 'Val/mean miou_metric': 0.9597074389457703, 'Val/mean f1': 0.9761190414428711, 'Val/mean precision': 0.9733490943908691, 'Val/mean recall': 0.9789047241210938, 'Val/mean hd95_metric': 4.803253173828125} +Epoch [3907/4000] Training [1/16] Loss: 0.00223 +Epoch [3907/4000] Training [2/16] Loss: 0.00258 +Epoch [3907/4000] Training [3/16] Loss: 0.00195 +Epoch [3907/4000] Training [4/16] Loss: 0.00227 +Epoch [3907/4000] Training [5/16] Loss: 0.00291 +Epoch [3907/4000] Training [6/16] Loss: 0.00234 +Epoch [3907/4000] Training [7/16] Loss: 0.00250 +Epoch [3907/4000] Training [8/16] Loss: 0.00239 +Epoch [3907/4000] Training [9/16] Loss: 0.00185 +Epoch [3907/4000] Training [10/16] Loss: 0.00205 +Epoch [3907/4000] Training [11/16] Loss: 0.00194 +Epoch [3907/4000] Training [12/16] Loss: 0.00270 +Epoch [3907/4000] Training [13/16] Loss: 0.00272 +Epoch [3907/4000] Training [14/16] Loss: 0.00331 +Epoch [3907/4000] Training [15/16] Loss: 0.00214 +Epoch [3907/4000] Training [16/16] Loss: 0.00259 +Epoch [3907/4000] Training metric {'Train/mean dice_metric': 0.998885989189148, 'Train/mean miou_metric': 0.9974800944328308, 'Train/mean f1': 0.9937301874160767, 'Train/mean precision': 0.9890905618667603, 'Train/mean recall': 0.9984135031700134, 'Train/mean hd95_metric': 0.5300079584121704} +Epoch [3907/4000] Validation [1/4] Loss: 0.43843 focal_loss 0.37607 dice_loss 0.06236 +Epoch [3907/4000] Validation [2/4] Loss: 0.49395 focal_loss 0.38142 dice_loss 0.11253 +Epoch [3907/4000] Validation [3/4] Loss: 0.56901 focal_loss 0.47165 dice_loss 0.09735 +Epoch [3907/4000] Validation [4/4] Loss: 0.27928 focal_loss 0.19744 dice_loss 0.08184 +Epoch [3907/4000] Validation metric {'Val/mean dice_metric': 0.9753336906433105, 'Val/mean miou_metric': 0.9613800048828125, 'Val/mean f1': 0.9765943884849548, 'Val/mean precision': 0.9739665389060974, 'Val/mean recall': 0.9792364239692688, 'Val/mean hd95_metric': 5.109055042266846} +Cheakpoint... +Epoch [3907/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753336906433105, 'Val/mean miou_metric': 0.9613800048828125, 'Val/mean f1': 0.9765943884849548, 'Val/mean precision': 0.9739665389060974, 'Val/mean recall': 0.9792364239692688, 'Val/mean hd95_metric': 5.109055042266846} +Epoch [3908/4000] Training [1/16] Loss: 0.00348 +Epoch [3908/4000] Training [2/16] Loss: 0.00213 +Epoch [3908/4000] Training [3/16] Loss: 0.00253 +Epoch [3908/4000] Training [4/16] Loss: 0.00288 +Epoch [3908/4000] Training [5/16] Loss: 0.00167 +Epoch [3908/4000] Training [6/16] Loss: 0.00324 +Epoch [3908/4000] Training [7/16] Loss: 0.00246 +Epoch [3908/4000] Training [8/16] Loss: 0.00261 +Epoch [3908/4000] Training [9/16] Loss: 0.00268 +Epoch [3908/4000] Training [10/16] Loss: 0.00273 +Epoch [3908/4000] Training [11/16] Loss: 0.00277 +Epoch [3908/4000] Training [12/16] Loss: 0.00223 +Epoch [3908/4000] Training [13/16] Loss: 0.00354 +Epoch [3908/4000] Training [14/16] Loss: 0.00206 +Epoch [3908/4000] Training [15/16] Loss: 0.00241 +Epoch [3908/4000] Training [16/16] Loss: 0.00171 +Epoch [3908/4000] Training metric {'Train/mean dice_metric': 0.9986730813980103, 'Train/mean miou_metric': 0.9970742464065552, 'Train/mean f1': 0.9937059283256531, 'Train/mean precision': 0.98916095495224, 'Train/mean recall': 0.9982929825782776, 'Train/mean hd95_metric': 0.5408755540847778} +Epoch [3908/4000] Validation [1/4] Loss: 0.37964 focal_loss 0.32173 dice_loss 0.05791 +Epoch [3908/4000] Validation [2/4] Loss: 0.59089 focal_loss 0.43923 dice_loss 0.15166 +Epoch [3908/4000] Validation [3/4] Loss: 0.57622 focal_loss 0.47526 dice_loss 0.10096 +Epoch [3908/4000] Validation [4/4] Loss: 0.37250 focal_loss 0.28127 dice_loss 0.09123 +Epoch [3908/4000] Validation metric {'Val/mean dice_metric': 0.9737518429756165, 'Val/mean miou_metric': 0.9597345590591431, 'Val/mean f1': 0.975831925868988, 'Val/mean precision': 0.9726582169532776, 'Val/mean recall': 0.9790264964103699, 'Val/mean hd95_metric': 5.84788703918457} +Cheakpoint... +Epoch [3908/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737518429756165, 'Val/mean miou_metric': 0.9597345590591431, 'Val/mean f1': 0.975831925868988, 'Val/mean precision': 0.9726582169532776, 'Val/mean recall': 0.9790264964103699, 'Val/mean hd95_metric': 5.84788703918457} +Epoch [3909/4000] Training [1/16] Loss: 0.00355 +Epoch [3909/4000] Training [2/16] Loss: 0.00246 +Epoch [3909/4000] Training [3/16] Loss: 0.00203 +Epoch [3909/4000] Training [4/16] Loss: 0.00189 +Epoch [3909/4000] Training [5/16] Loss: 0.00257 +Epoch [3909/4000] Training [6/16] Loss: 0.00329 +Epoch [3909/4000] Training [7/16] Loss: 0.00161 +Epoch [3909/4000] Training [8/16] Loss: 0.00210 +Epoch [3909/4000] Training [9/16] Loss: 0.00197 +Epoch [3909/4000] Training [10/16] Loss: 0.00165 +Epoch [3909/4000] Training [11/16] Loss: 0.00240 +Epoch [3909/4000] Training [12/16] Loss: 0.00202 +Epoch [3909/4000] Training [13/16] Loss: 0.00251 +Epoch [3909/4000] Training [14/16] Loss: 0.00383 +Epoch [3909/4000] Training [15/16] Loss: 0.00194 +Epoch [3909/4000] Training [16/16] Loss: 0.00220 +Epoch [3909/4000] Training metric {'Train/mean dice_metric': 0.9987854361534119, 'Train/mean miou_metric': 0.9972857236862183, 'Train/mean f1': 0.9937583804130554, 'Train/mean precision': 0.9891912341117859, 'Train/mean recall': 0.9983678460121155, 'Train/mean hd95_metric': 0.48821118474006653} +Epoch [3909/4000] Validation [1/4] Loss: 0.38017 focal_loss 0.31738 dice_loss 0.06279 +Epoch [3909/4000] Validation [2/4] Loss: 0.48803 focal_loss 0.37635 dice_loss 0.11169 +Epoch [3909/4000] Validation [3/4] Loss: 0.56063 focal_loss 0.46660 dice_loss 0.09404 +Epoch [3909/4000] Validation [4/4] Loss: 0.30240 focal_loss 0.21982 dice_loss 0.08257 +Epoch [3909/4000] Validation metric {'Val/mean dice_metric': 0.9754542112350464, 'Val/mean miou_metric': 0.9613044857978821, 'Val/mean f1': 0.9770947098731995, 'Val/mean precision': 0.974748969078064, 'Val/mean recall': 0.9794518947601318, 'Val/mean hd95_metric': 4.896349906921387} +Cheakpoint... +Epoch [3909/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9754542112350464, 'Val/mean miou_metric': 0.9613044857978821, 'Val/mean f1': 0.9770947098731995, 'Val/mean precision': 0.974748969078064, 'Val/mean recall': 0.9794518947601318, 'Val/mean hd95_metric': 4.896349906921387} +Epoch [3910/4000] Training [1/16] Loss: 0.00300 +Epoch [3910/4000] Training [2/16] Loss: 0.00256 +Epoch [3910/4000] Training [3/16] Loss: 0.00211 +Epoch [3910/4000] Training [4/16] Loss: 0.00202 +Epoch [3910/4000] Training [5/16] Loss: 0.00321 +Epoch [3910/4000] Training [6/16] Loss: 0.00149 +Epoch [3910/4000] Training [7/16] Loss: 0.00201 +Epoch [3910/4000] Training [8/16] Loss: 0.00149 +Epoch [3910/4000] Training [9/16] Loss: 0.00373 +Epoch [3910/4000] Training [10/16] Loss: 0.00190 +Epoch [3910/4000] Training [11/16] Loss: 0.00317 +Epoch [3910/4000] Training [12/16] Loss: 0.00258 +Epoch [3910/4000] Training [13/16] Loss: 0.00359 +Epoch [3910/4000] Training [14/16] Loss: 0.00204 +Epoch [3910/4000] Training [15/16] Loss: 0.00237 +Epoch [3910/4000] Training [16/16] Loss: 0.00150 +Epoch [3910/4000] Training metric {'Train/mean dice_metric': 0.9988105893135071, 'Train/mean miou_metric': 0.9973487854003906, 'Train/mean f1': 0.9938508868217468, 'Train/mean precision': 0.989303469657898, 'Train/mean recall': 0.9984403848648071, 'Train/mean hd95_metric': 0.544754147529602} +Epoch [3910/4000] Validation [1/4] Loss: 0.39211 focal_loss 0.32832 dice_loss 0.06379 +Epoch [3910/4000] Validation [2/4] Loss: 0.48009 focal_loss 0.37043 dice_loss 0.10966 +Epoch [3910/4000] Validation [3/4] Loss: 0.57758 focal_loss 0.48010 dice_loss 0.09748 +Epoch [3910/4000] Validation [4/4] Loss: 0.36462 focal_loss 0.27622 dice_loss 0.08840 +Epoch [3910/4000] Validation metric {'Val/mean dice_metric': 0.9750224947929382, 'Val/mean miou_metric': 0.9609891772270203, 'Val/mean f1': 0.9766177535057068, 'Val/mean precision': 0.9744080901145935, 'Val/mean recall': 0.9788374900817871, 'Val/mean hd95_metric': 4.9185404777526855} +Cheakpoint... +Epoch [3910/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750224947929382, 'Val/mean miou_metric': 0.9609891772270203, 'Val/mean f1': 0.9766177535057068, 'Val/mean precision': 0.9744080901145935, 'Val/mean recall': 0.9788374900817871, 'Val/mean hd95_metric': 4.9185404777526855} +Epoch [3911/4000] Training [1/16] Loss: 0.00199 +Epoch [3911/4000] Training [2/16] Loss: 0.00240 +Epoch [3911/4000] Training [3/16] Loss: 0.00191 +Epoch [3911/4000] Training [4/16] Loss: 0.00222 +Epoch [3911/4000] Training [5/16] Loss: 0.00173 +Epoch [3911/4000] Training [6/16] Loss: 0.00196 +Epoch [3911/4000] Training [7/16] Loss: 0.00211 +Epoch [3911/4000] Training [8/16] Loss: 0.00367 +Epoch [3911/4000] Training [9/16] Loss: 0.00218 +Epoch [3911/4000] Training [10/16] Loss: 0.00203 +Epoch [3911/4000] Training [11/16] Loss: 0.00203 +Epoch [3911/4000] Training [12/16] Loss: 0.00200 +Epoch [3911/4000] Training [13/16] Loss: 0.00169 +Epoch [3911/4000] Training [14/16] Loss: 0.00244 +Epoch [3911/4000] Training [15/16] Loss: 0.00309 +Epoch [3911/4000] Training [16/16] Loss: 0.00211 +Epoch [3911/4000] Training metric {'Train/mean dice_metric': 0.9988600015640259, 'Train/mean miou_metric': 0.9974445104598999, 'Train/mean f1': 0.9938756227493286, 'Train/mean precision': 0.9893429279327393, 'Train/mean recall': 0.998449981212616, 'Train/mean hd95_metric': 0.531570553779602} +Epoch [3911/4000] Validation [1/4] Loss: 0.40042 focal_loss 0.33849 dice_loss 0.06194 +Epoch [3911/4000] Validation [2/4] Loss: 0.96129 focal_loss 0.77339 dice_loss 0.18790 +Epoch [3911/4000] Validation [3/4] Loss: 0.54483 focal_loss 0.45183 dice_loss 0.09300 +Epoch [3911/4000] Validation [4/4] Loss: 0.47653 focal_loss 0.36374 dice_loss 0.11279 +Epoch [3911/4000] Validation metric {'Val/mean dice_metric': 0.9741584658622742, 'Val/mean miou_metric': 0.9607307314872742, 'Val/mean f1': 0.9767283201217651, 'Val/mean precision': 0.9745457172393799, 'Val/mean recall': 0.9789206981658936, 'Val/mean hd95_metric': 4.7326765060424805} +Cheakpoint... +Epoch [3911/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741584658622742, 'Val/mean miou_metric': 0.9607307314872742, 'Val/mean f1': 0.9767283201217651, 'Val/mean precision': 0.9745457172393799, 'Val/mean recall': 0.9789206981658936, 'Val/mean hd95_metric': 4.7326765060424805} +Epoch [3912/4000] Training [1/16] Loss: 0.00285 +Epoch [3912/4000] Training [2/16] Loss: 0.00344 +Epoch [3912/4000] Training [3/16] Loss: 0.00258 +Epoch [3912/4000] Training [4/16] Loss: 0.00217 +Epoch [3912/4000] Training [5/16] Loss: 0.00235 +Epoch [3912/4000] Training [6/16] Loss: 0.00173 +Epoch [3912/4000] Training [7/16] Loss: 0.00282 +Epoch [3912/4000] Training [8/16] Loss: 0.00211 +Epoch [3912/4000] Training [9/16] Loss: 0.00275 +Epoch [3912/4000] Training [10/16] Loss: 0.00432 +Epoch [3912/4000] Training [11/16] Loss: 0.00391 +Epoch [3912/4000] Training [12/16] Loss: 0.00233 +Epoch [3912/4000] Training [13/16] Loss: 0.00306 +Epoch [3912/4000] Training [14/16] Loss: 0.00334 +Epoch [3912/4000] Training [15/16] Loss: 0.00333 +Epoch [3912/4000] Training [16/16] Loss: 0.00338 +Epoch [3912/4000] Training metric {'Train/mean dice_metric': 0.9985179305076599, 'Train/mean miou_metric': 0.996756374835968, 'Train/mean f1': 0.9934622645378113, 'Train/mean precision': 0.9888769388198853, 'Train/mean recall': 0.9980903267860413, 'Train/mean hd95_metric': 0.5930097103118896} +Epoch [3912/4000] Validation [1/4] Loss: 0.38469 focal_loss 0.31967 dice_loss 0.06502 +Epoch [3912/4000] Validation [2/4] Loss: 0.46537 focal_loss 0.35713 dice_loss 0.10824 +Epoch [3912/4000] Validation [3/4] Loss: 0.27905 focal_loss 0.21263 dice_loss 0.06643 +Epoch [3912/4000] Validation [4/4] Loss: 0.44840 focal_loss 0.34108 dice_loss 0.10732 +Epoch [3912/4000] Validation metric {'Val/mean dice_metric': 0.9757705926895142, 'Val/mean miou_metric': 0.9612874984741211, 'Val/mean f1': 0.9763337969779968, 'Val/mean precision': 0.9740152359008789, 'Val/mean recall': 0.9786633849143982, 'Val/mean hd95_metric': 4.896543979644775} +Cheakpoint... +Epoch [3912/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9757705926895142, 'Val/mean miou_metric': 0.9612874984741211, 'Val/mean f1': 0.9763337969779968, 'Val/mean precision': 0.9740152359008789, 'Val/mean recall': 0.9786633849143982, 'Val/mean hd95_metric': 4.896543979644775} +Epoch [3913/4000] Training [1/16] Loss: 0.00198 +Epoch [3913/4000] Training [2/16] Loss: 0.00273 +Epoch [3913/4000] Training [3/16] Loss: 0.00221 +Epoch [3913/4000] Training [4/16] Loss: 0.00441 +Epoch [3913/4000] Training [5/16] Loss: 0.00174 +Epoch [3913/4000] Training [6/16] Loss: 0.00254 +Epoch [3913/4000] Training [7/16] Loss: 0.00356 +Epoch [3913/4000] Training [8/16] Loss: 0.00260 +Epoch [3913/4000] Training [9/16] Loss: 0.00289 +Epoch [3913/4000] Training [10/16] Loss: 0.00228 +Epoch [3913/4000] Training [11/16] Loss: 0.00271 +Epoch [3913/4000] Training [12/16] Loss: 0.00386 +Epoch [3913/4000] Training [13/16] Loss: 0.00168 +Epoch [3913/4000] Training [14/16] Loss: 0.00261 +Epoch [3913/4000] Training [15/16] Loss: 0.00192 +Epoch [3913/4000] Training [16/16] Loss: 0.00312 +Epoch [3913/4000] Training metric {'Train/mean dice_metric': 0.9987277388572693, 'Train/mean miou_metric': 0.9971643090248108, 'Train/mean f1': 0.9935547709465027, 'Train/mean precision': 0.9889018535614014, 'Train/mean recall': 0.9982516169548035, 'Train/mean hd95_metric': 0.537918210029602} +Epoch [3913/4000] Validation [1/4] Loss: 0.49095 focal_loss 0.42482 dice_loss 0.06613 +Epoch [3913/4000] Validation [2/4] Loss: 0.48600 focal_loss 0.37227 dice_loss 0.11374 +Epoch [3913/4000] Validation [3/4] Loss: 0.53943 focal_loss 0.44370 dice_loss 0.09573 +Epoch [3913/4000] Validation [4/4] Loss: 0.39088 focal_loss 0.29925 dice_loss 0.09163 +Epoch [3913/4000] Validation metric {'Val/mean dice_metric': 0.9739934206008911, 'Val/mean miou_metric': 0.9599636793136597, 'Val/mean f1': 0.9759970903396606, 'Val/mean precision': 0.9741394519805908, 'Val/mean recall': 0.9778618812561035, 'Val/mean hd95_metric': 4.898313522338867} +Cheakpoint... +Epoch [3913/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739934206008911, 'Val/mean miou_metric': 0.9599636793136597, 'Val/mean f1': 0.9759970903396606, 'Val/mean precision': 0.9741394519805908, 'Val/mean recall': 0.9778618812561035, 'Val/mean hd95_metric': 4.898313522338867} +Epoch [3914/4000] Training [1/16] Loss: 0.00241 +Epoch [3914/4000] Training [2/16] Loss: 0.00177 +Epoch [3914/4000] Training [3/16] Loss: 0.00336 +Epoch [3914/4000] Training [4/16] Loss: 0.00262 +Epoch [3914/4000] Training [5/16] Loss: 0.00209 +Epoch [3914/4000] Training [6/16] Loss: 0.00258 +Epoch [3914/4000] Training [7/16] Loss: 0.00380 +Epoch [3914/4000] Training [8/16] Loss: 0.00276 +Epoch [3914/4000] Training [9/16] Loss: 0.00250 +Epoch [3914/4000] Training [10/16] Loss: 0.00190 +Epoch [3914/4000] Training [11/16] Loss: 0.00352 +Epoch [3914/4000] Training [12/16] Loss: 0.00335 +Epoch [3914/4000] Training [13/16] Loss: 0.00228 +Epoch [3914/4000] Training [14/16] Loss: 0.00297 +Epoch [3914/4000] Training [15/16] Loss: 0.00217 +Epoch [3914/4000] Training [16/16] Loss: 0.00205 +Epoch [3914/4000] Training metric {'Train/mean dice_metric': 0.9988088607788086, 'Train/mean miou_metric': 0.997343897819519, 'Train/mean f1': 0.9938755631446838, 'Train/mean precision': 0.9893662929534912, 'Train/mean recall': 0.998426079750061, 'Train/mean hd95_metric': 0.5104768872261047} +Epoch [3914/4000] Validation [1/4] Loss: 0.42223 focal_loss 0.35845 dice_loss 0.06377 +Epoch [3914/4000] Validation [2/4] Loss: 1.07022 focal_loss 0.88184 dice_loss 0.18838 +Epoch [3914/4000] Validation [3/4] Loss: 0.57725 focal_loss 0.48029 dice_loss 0.09696 +Epoch [3914/4000] Validation [4/4] Loss: 0.45213 focal_loss 0.33823 dice_loss 0.11390 +Epoch [3914/4000] Validation metric {'Val/mean dice_metric': 0.9749658703804016, 'Val/mean miou_metric': 0.9608389139175415, 'Val/mean f1': 0.9764301776885986, 'Val/mean precision': 0.9737442135810852, 'Val/mean recall': 0.9791311025619507, 'Val/mean hd95_metric': 5.125539779663086} +Cheakpoint... +Epoch [3914/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749658703804016, 'Val/mean miou_metric': 0.9608389139175415, 'Val/mean f1': 0.9764301776885986, 'Val/mean precision': 0.9737442135810852, 'Val/mean recall': 0.9791311025619507, 'Val/mean hd95_metric': 5.125539779663086} +Epoch [3915/4000] Training [1/16] Loss: 0.00184 +Epoch [3915/4000] Training [2/16] Loss: 0.00231 +Epoch [3915/4000] Training [3/16] Loss: 0.00308 +Epoch [3915/4000] Training [4/16] Loss: 0.00281 +Epoch [3915/4000] Training [5/16] Loss: 0.00148 +Epoch [3915/4000] Training [6/16] Loss: 0.00296 +Epoch [3915/4000] Training [7/16] Loss: 0.00237 +Epoch [3915/4000] Training [8/16] Loss: 0.00238 +Epoch [3915/4000] Training [9/16] Loss: 0.00277 +Epoch [3915/4000] Training [10/16] Loss: 0.00170 +Epoch [3915/4000] Training [11/16] Loss: 0.00163 +Epoch [3915/4000] Training [12/16] Loss: 0.00234 +Epoch [3915/4000] Training [13/16] Loss: 0.00205 +Epoch [3915/4000] Training [14/16] Loss: 0.00230 +Epoch [3915/4000] Training [15/16] Loss: 0.00273 +Epoch [3915/4000] Training [16/16] Loss: 0.00312 +Epoch [3915/4000] Training metric {'Train/mean dice_metric': 0.9987386465072632, 'Train/mean miou_metric': 0.9972043037414551, 'Train/mean f1': 0.9938126802444458, 'Train/mean precision': 0.9892763495445251, 'Train/mean recall': 0.9983908534049988, 'Train/mean hd95_metric': 0.5145086050033569} +Epoch [3915/4000] Validation [1/4] Loss: 0.42060 focal_loss 0.35713 dice_loss 0.06346 +Epoch [3915/4000] Validation [2/4] Loss: 0.53117 focal_loss 0.39936 dice_loss 0.13181 +Epoch [3915/4000] Validation [3/4] Loss: 0.28414 focal_loss 0.22168 dice_loss 0.06246 +Epoch [3915/4000] Validation [4/4] Loss: 0.40314 focal_loss 0.29360 dice_loss 0.10953 +Epoch [3915/4000] Validation metric {'Val/mean dice_metric': 0.9748013615608215, 'Val/mean miou_metric': 0.9606016278266907, 'Val/mean f1': 0.9767161011695862, 'Val/mean precision': 0.974157452583313, 'Val/mean recall': 0.9792881011962891, 'Val/mean hd95_metric': 4.7761945724487305} +Cheakpoint... +Epoch [3915/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748013615608215, 'Val/mean miou_metric': 0.9606016278266907, 'Val/mean f1': 0.9767161011695862, 'Val/mean precision': 0.974157452583313, 'Val/mean recall': 0.9792881011962891, 'Val/mean hd95_metric': 4.7761945724487305} +Epoch [3916/4000] Training [1/16] Loss: 0.00243 +Epoch [3916/4000] Training [2/16] Loss: 0.00321 +Epoch [3916/4000] Training [3/16] Loss: 0.00290 +Epoch [3916/4000] Training [4/16] Loss: 0.00232 +Epoch [3916/4000] Training [5/16] Loss: 0.00290 +Epoch [3916/4000] Training [6/16] Loss: 0.00408 +Epoch [3916/4000] Training [7/16] Loss: 0.00162 +Epoch [3916/4000] Training [8/16] Loss: 0.00138 +Epoch [3916/4000] Training [9/16] Loss: 0.00270 +Epoch [3916/4000] Training [10/16] Loss: 0.00185 +Epoch [3916/4000] Training [11/16] Loss: 0.00432 +Epoch [3916/4000] Training [12/16] Loss: 0.00208 +Epoch [3916/4000] Training [13/16] Loss: 0.00200 +Epoch [3916/4000] Training [14/16] Loss: 0.00237 +Epoch [3916/4000] Training [15/16] Loss: 0.00146 +Epoch [3916/4000] Training [16/16] Loss: 0.00197 +Epoch [3916/4000] Training metric {'Train/mean dice_metric': 0.9987317323684692, 'Train/mean miou_metric': 0.9971637725830078, 'Train/mean f1': 0.9933415055274963, 'Train/mean precision': 0.9884424805641174, 'Train/mean recall': 0.9982894062995911, 'Train/mean hd95_metric': 0.46174636483192444} +Epoch [3916/4000] Validation [1/4] Loss: 0.41636 focal_loss 0.35236 dice_loss 0.06400 +Epoch [3916/4000] Validation [2/4] Loss: 0.49010 focal_loss 0.37873 dice_loss 0.11137 +Epoch [3916/4000] Validation [3/4] Loss: 0.52399 focal_loss 0.43041 dice_loss 0.09358 +Epoch [3916/4000] Validation [4/4] Loss: 0.34651 focal_loss 0.24123 dice_loss 0.10528 +Epoch [3916/4000] Validation metric {'Val/mean dice_metric': 0.9746583700180054, 'Val/mean miou_metric': 0.9603670239448547, 'Val/mean f1': 0.9761109948158264, 'Val/mean precision': 0.9731407761573792, 'Val/mean recall': 0.979099452495575, 'Val/mean hd95_metric': 5.2747883796691895} +Cheakpoint... +Epoch [3916/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746583700180054, 'Val/mean miou_metric': 0.9603670239448547, 'Val/mean f1': 0.9761109948158264, 'Val/mean precision': 0.9731407761573792, 'Val/mean recall': 0.979099452495575, 'Val/mean hd95_metric': 5.2747883796691895} +Epoch [3917/4000] Training [1/16] Loss: 0.00239 +Epoch [3917/4000] Training [2/16] Loss: 0.00182 +Epoch [3917/4000] Training [3/16] Loss: 0.00236 +Epoch [3917/4000] Training [4/16] Loss: 0.00208 +Epoch [3917/4000] Training [5/16] Loss: 0.00202 +Epoch [3917/4000] Training [6/16] Loss: 0.00161 +Epoch [3917/4000] Training [7/16] Loss: 0.00293 +Epoch [3917/4000] Training [8/16] Loss: 0.00233 +Epoch [3917/4000] Training [9/16] Loss: 0.00416 +Epoch [3917/4000] Training [10/16] Loss: 0.00223 +Epoch [3917/4000] Training [11/16] Loss: 0.00339 +Epoch [3917/4000] Training [12/16] Loss: 0.00444 +Epoch [3917/4000] Training [13/16] Loss: 0.00247 +Epoch [3917/4000] Training [14/16] Loss: 0.00256 +Epoch [3917/4000] Training [15/16] Loss: 0.00204 +Epoch [3917/4000] Training [16/16] Loss: 0.00183 +Epoch [3917/4000] Training metric {'Train/mean dice_metric': 0.998666524887085, 'Train/mean miou_metric': 0.9970519542694092, 'Train/mean f1': 0.9936303496360779, 'Train/mean precision': 0.9890099763870239, 'Train/mean recall': 0.9982940554618835, 'Train/mean hd95_metric': 0.5592350959777832} +Epoch [3917/4000] Validation [1/4] Loss: 0.49000 focal_loss 0.42257 dice_loss 0.06744 +Epoch [3917/4000] Validation [2/4] Loss: 0.47031 focal_loss 0.36068 dice_loss 0.10963 +Epoch [3917/4000] Validation [3/4] Loss: 0.53329 focal_loss 0.44261 dice_loss 0.09069 +Epoch [3917/4000] Validation [4/4] Loss: 0.60492 focal_loss 0.47376 dice_loss 0.13116 +Epoch [3917/4000] Validation metric {'Val/mean dice_metric': 0.9734899401664734, 'Val/mean miou_metric': 0.9594712257385254, 'Val/mean f1': 0.976261556148529, 'Val/mean precision': 0.9746453166007996, 'Val/mean recall': 0.9778831601142883, 'Val/mean hd95_metric': 4.66044807434082} +Cheakpoint... +Epoch [3917/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734899401664734, 'Val/mean miou_metric': 0.9594712257385254, 'Val/mean f1': 0.976261556148529, 'Val/mean precision': 0.9746453166007996, 'Val/mean recall': 0.9778831601142883, 'Val/mean hd95_metric': 4.66044807434082} +Epoch [3918/4000] Training [1/16] Loss: 0.00332 +Epoch [3918/4000] Training [2/16] Loss: 0.00236 +Epoch [3918/4000] Training [3/16] Loss: 0.00282 +Epoch [3918/4000] Training [4/16] Loss: 0.00150 +Epoch [3918/4000] Training [5/16] Loss: 0.00177 +Epoch [3918/4000] Training [6/16] Loss: 0.00229 +Epoch [3918/4000] Training [7/16] Loss: 0.00174 +Epoch [3918/4000] Training [8/16] Loss: 0.00217 +Epoch [3918/4000] Training [9/16] Loss: 0.00204 +Epoch [3918/4000] Training [10/16] Loss: 0.00276 +Epoch [3918/4000] Training [11/16] Loss: 0.00153 +Epoch [3918/4000] Training [12/16] Loss: 0.00290 +Epoch [3918/4000] Training [13/16] Loss: 0.00180 +Epoch [3918/4000] Training [14/16] Loss: 0.00355 +Epoch [3918/4000] Training [15/16] Loss: 0.00183 +Epoch [3918/4000] Training [16/16] Loss: 0.00382 +Epoch [3918/4000] Training metric {'Train/mean dice_metric': 0.9989259839057922, 'Train/mean miou_metric': 0.9975752830505371, 'Train/mean f1': 0.9939221739768982, 'Train/mean precision': 0.9893510341644287, 'Train/mean recall': 0.998535692691803, 'Train/mean hd95_metric': 0.49881839752197266} +Epoch [3918/4000] Validation [1/4] Loss: 0.47312 focal_loss 0.40767 dice_loss 0.06545 +Epoch [3918/4000] Validation [2/4] Loss: 1.06526 focal_loss 0.87740 dice_loss 0.18786 +Epoch [3918/4000] Validation [3/4] Loss: 0.52453 focal_loss 0.43421 dice_loss 0.09031 +Epoch [3918/4000] Validation [4/4] Loss: 0.30172 focal_loss 0.21655 dice_loss 0.08517 +Epoch [3918/4000] Validation metric {'Val/mean dice_metric': 0.9745817184448242, 'Val/mean miou_metric': 0.9611776471138, 'Val/mean f1': 0.9766331315040588, 'Val/mean precision': 0.973817765712738, 'Val/mean recall': 0.9794647097587585, 'Val/mean hd95_metric': 4.708536624908447} +Cheakpoint... +Epoch [3918/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745817184448242, 'Val/mean miou_metric': 0.9611776471138, 'Val/mean f1': 0.9766331315040588, 'Val/mean precision': 0.973817765712738, 'Val/mean recall': 0.9794647097587585, 'Val/mean hd95_metric': 4.708536624908447} +Epoch [3919/4000] Training [1/16] Loss: 0.00237 +Epoch [3919/4000] Training [2/16] Loss: 0.00206 +Epoch [3919/4000] Training [3/16] Loss: 0.00221 +Epoch [3919/4000] Training [4/16] Loss: 0.00235 +Epoch [3919/4000] Training [5/16] Loss: 0.00236 +Epoch [3919/4000] Training [6/16] Loss: 0.00258 +Epoch [3919/4000] Training [7/16] Loss: 0.00185 +Epoch [3919/4000] Training [8/16] Loss: 0.00201 +Epoch [3919/4000] Training [9/16] Loss: 0.00170 +Epoch [3919/4000] Training [10/16] Loss: 0.00193 +Epoch [3919/4000] Training [11/16] Loss: 0.00162 +Epoch [3919/4000] Training [12/16] Loss: 0.00251 +Epoch [3919/4000] Training [13/16] Loss: 0.00221 +Epoch [3919/4000] Training [14/16] Loss: 0.00217 +Epoch [3919/4000] Training [15/16] Loss: 0.00234 +Epoch [3919/4000] Training [16/16] Loss: 0.00188 +Epoch [3919/4000] Training metric {'Train/mean dice_metric': 0.9989811778068542, 'Train/mean miou_metric': 0.9976489543914795, 'Train/mean f1': 0.9931122064590454, 'Train/mean precision': 0.9878412485122681, 'Train/mean recall': 0.9984397888183594, 'Train/mean hd95_metric': 0.4606720507144928} +Epoch [3919/4000] Validation [1/4] Loss: 0.44598 focal_loss 0.37588 dice_loss 0.07010 +Epoch [3919/4000] Validation [2/4] Loss: 1.48983 focal_loss 1.21070 dice_loss 0.27912 +Epoch [3919/4000] Validation [3/4] Loss: 0.51695 focal_loss 0.42894 dice_loss 0.08801 +Epoch [3919/4000] Validation [4/4] Loss: 0.38397 focal_loss 0.29245 dice_loss 0.09152 +Epoch [3919/4000] Validation metric {'Val/mean dice_metric': 0.9731992483139038, 'Val/mean miou_metric': 0.9596681594848633, 'Val/mean f1': 0.9753366708755493, 'Val/mean precision': 0.972610592842102, 'Val/mean recall': 0.9780781269073486, 'Val/mean hd95_metric': 4.523563861846924} +Cheakpoint... +Epoch [3919/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731992483139038, 'Val/mean miou_metric': 0.9596681594848633, 'Val/mean f1': 0.9753366708755493, 'Val/mean precision': 0.972610592842102, 'Val/mean recall': 0.9780781269073486, 'Val/mean hd95_metric': 4.523563861846924} +Epoch [3920/4000] Training [1/16] Loss: 0.00225 +Epoch [3920/4000] Training [2/16] Loss: 0.00216 +Epoch [3920/4000] Training [3/16] Loss: 0.00212 +Epoch [3920/4000] Training [4/16] Loss: 0.00272 +Epoch [3920/4000] Training [5/16] Loss: 0.00200 +Epoch [3920/4000] Training [6/16] Loss: 0.00324 +Epoch [3920/4000] Training [7/16] Loss: 0.00222 +Epoch [3920/4000] Training [8/16] Loss: 0.00307 +Epoch [3920/4000] Training [9/16] Loss: 0.00303 +Epoch [3920/4000] Training [10/16] Loss: 0.00213 +Epoch [3920/4000] Training [11/16] Loss: 0.00137 +Epoch [3920/4000] Training [12/16] Loss: 0.00204 +Epoch [3920/4000] Training [13/16] Loss: 0.00213 +Epoch [3920/4000] Training [14/16] Loss: 0.00256 +Epoch [3920/4000] Training [15/16] Loss: 0.00180 +Epoch [3920/4000] Training [16/16] Loss: 0.00239 +Epoch [3920/4000] Training metric {'Train/mean dice_metric': 0.998833954334259, 'Train/mean miou_metric': 0.9973664283752441, 'Train/mean f1': 0.9933490753173828, 'Train/mean precision': 0.9883581399917603, 'Train/mean recall': 0.9983906149864197, 'Train/mean hd95_metric': 0.5171449184417725} +Epoch [3920/4000] Validation [1/4] Loss: 0.36364 focal_loss 0.30247 dice_loss 0.06117 +Epoch [3920/4000] Validation [2/4] Loss: 0.54436 focal_loss 0.40903 dice_loss 0.13533 +Epoch [3920/4000] Validation [3/4] Loss: 0.55938 focal_loss 0.46480 dice_loss 0.09459 +Epoch [3920/4000] Validation [4/4] Loss: 0.34487 focal_loss 0.26053 dice_loss 0.08434 +Epoch [3920/4000] Validation metric {'Val/mean dice_metric': 0.9758203625679016, 'Val/mean miou_metric': 0.9615631103515625, 'Val/mean f1': 0.9765572547912598, 'Val/mean precision': 0.9737465381622314, 'Val/mean recall': 0.9793843030929565, 'Val/mean hd95_metric': 4.721729755401611} +Cheakpoint... +Epoch [3920/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9758], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9758203625679016, 'Val/mean miou_metric': 0.9615631103515625, 'Val/mean f1': 0.9765572547912598, 'Val/mean precision': 0.9737465381622314, 'Val/mean recall': 0.9793843030929565, 'Val/mean hd95_metric': 4.721729755401611} +Epoch [3921/4000] Training [1/16] Loss: 0.00218 +Epoch [3921/4000] Training [2/16] Loss: 0.00330 +Epoch [3921/4000] Training [3/16] Loss: 0.00201 +Epoch [3921/4000] Training [4/16] Loss: 0.00204 +Epoch [3921/4000] Training [5/16] Loss: 0.00167 +Epoch [3921/4000] Training [6/16] Loss: 0.00257 +Epoch [3921/4000] Training [7/16] Loss: 0.00178 +Epoch [3921/4000] Training [8/16] Loss: 0.00301 +Epoch [3921/4000] Training [9/16] Loss: 0.00656 +Epoch [3921/4000] Training [10/16] Loss: 0.00178 +Epoch [3921/4000] Training [11/16] Loss: 0.00345 +Epoch [3921/4000] Training [12/16] Loss: 0.00254 +Epoch [3921/4000] Training [13/16] Loss: 0.00286 +Epoch [3921/4000] Training [14/16] Loss: 0.00233 +Epoch [3921/4000] Training [15/16] Loss: 0.00268 +Epoch [3921/4000] Training [16/16] Loss: 0.00348 +Epoch [3921/4000] Training metric {'Train/mean dice_metric': 0.9987626075744629, 'Train/mean miou_metric': 0.9972532987594604, 'Train/mean f1': 0.9937672019004822, 'Train/mean precision': 0.9892270565032959, 'Train/mean recall': 0.9983491897583008, 'Train/mean hd95_metric': 0.46883314847946167} +Epoch [3921/4000] Validation [1/4] Loss: 0.45356 focal_loss 0.38759 dice_loss 0.06597 +Epoch [3921/4000] Validation [2/4] Loss: 0.64398 focal_loss 0.47154 dice_loss 0.17244 +Epoch [3921/4000] Validation [3/4] Loss: 0.30649 focal_loss 0.23792 dice_loss 0.06857 +Epoch [3921/4000] Validation [4/4] Loss: 0.38767 focal_loss 0.27855 dice_loss 0.10912 +Epoch [3921/4000] Validation metric {'Val/mean dice_metric': 0.9735795855522156, 'Val/mean miou_metric': 0.9589662551879883, 'Val/mean f1': 0.9761906266212463, 'Val/mean precision': 0.9744266867637634, 'Val/mean recall': 0.977961003780365, 'Val/mean hd95_metric': 5.3126373291015625} +Cheakpoint... +Epoch [3921/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735795855522156, 'Val/mean miou_metric': 0.9589662551879883, 'Val/mean f1': 0.9761906266212463, 'Val/mean precision': 0.9744266867637634, 'Val/mean recall': 0.977961003780365, 'Val/mean hd95_metric': 5.3126373291015625} +Epoch [3922/4000] Training [1/16] Loss: 0.00206 +Epoch [3922/4000] Training [2/16] Loss: 0.00337 +Epoch [3922/4000] Training [3/16] Loss: 0.00221 +Epoch [3922/4000] Training [4/16] Loss: 0.00244 +Epoch [3922/4000] Training [5/16] Loss: 0.00423 +Epoch [3922/4000] Training [6/16] Loss: 0.00193 +Epoch [3922/4000] Training [7/16] Loss: 0.00183 +Epoch [3922/4000] Training [8/16] Loss: 0.00151 +Epoch [3922/4000] Training [9/16] Loss: 0.00289 +Epoch [3922/4000] Training [10/16] Loss: 0.00197 +Epoch [3922/4000] Training [11/16] Loss: 0.00241 +Epoch [3922/4000] Training [12/16] Loss: 0.00236 +Epoch [3922/4000] Training [13/16] Loss: 0.00219 +Epoch [3922/4000] Training [14/16] Loss: 0.00210 +Epoch [3922/4000] Training [15/16] Loss: 0.00285 +Epoch [3922/4000] Training [16/16] Loss: 0.00257 +Epoch [3922/4000] Training metric {'Train/mean dice_metric': 0.9989031553268433, 'Train/mean miou_metric': 0.9975137710571289, 'Train/mean f1': 0.9937507510185242, 'Train/mean precision': 0.989091694355011, 'Train/mean recall': 0.9984539747238159, 'Train/mean hd95_metric': 0.5095473527908325} +Epoch [3922/4000] Validation [1/4] Loss: 0.38854 focal_loss 0.32709 dice_loss 0.06145 +Epoch [3922/4000] Validation [2/4] Loss: 0.49579 focal_loss 0.38455 dice_loss 0.11124 +Epoch [3922/4000] Validation [3/4] Loss: 0.28329 focal_loss 0.21748 dice_loss 0.06581 +Epoch [3922/4000] Validation [4/4] Loss: 0.43107 focal_loss 0.32130 dice_loss 0.10977 +Epoch [3922/4000] Validation metric {'Val/mean dice_metric': 0.9741590619087219, 'Val/mean miou_metric': 0.9605177044868469, 'Val/mean f1': 0.9769507646560669, 'Val/mean precision': 0.9750732779502869, 'Val/mean recall': 0.9788353443145752, 'Val/mean hd95_metric': 4.6827569007873535} +Cheakpoint... +Epoch [3922/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9741590619087219, 'Val/mean miou_metric': 0.9605177044868469, 'Val/mean f1': 0.9769507646560669, 'Val/mean precision': 0.9750732779502869, 'Val/mean recall': 0.9788353443145752, 'Val/mean hd95_metric': 4.6827569007873535} +Epoch [3923/4000] Training [1/16] Loss: 0.00283 +Epoch [3923/4000] Training [2/16] Loss: 0.00251 +Epoch [3923/4000] Training [3/16] Loss: 0.00199 +Epoch [3923/4000] Training [4/16] Loss: 0.00167 +Epoch [3923/4000] Training [5/16] Loss: 0.00331 +Epoch [3923/4000] Training [6/16] Loss: 0.00314 +Epoch [3923/4000] Training [7/16] Loss: 0.00220 +Epoch [3923/4000] Training [8/16] Loss: 0.00224 +Epoch [3923/4000] Training [9/16] Loss: 0.00279 +Epoch [3923/4000] Training [10/16] Loss: 0.00331 +Epoch [3923/4000] Training [11/16] Loss: 0.00176 +Epoch [3923/4000] Training [12/16] Loss: 0.00204 +Epoch [3923/4000] Training [13/16] Loss: 0.00299 +Epoch [3923/4000] Training [14/16] Loss: 0.00354 +Epoch [3923/4000] Training [15/16] Loss: 0.00375 +Epoch [3923/4000] Training [16/16] Loss: 0.00223 +Epoch [3923/4000] Training metric {'Train/mean dice_metric': 0.9988007545471191, 'Train/mean miou_metric': 0.997328519821167, 'Train/mean f1': 0.993804931640625, 'Train/mean precision': 0.9892436265945435, 'Train/mean recall': 0.9984084963798523, 'Train/mean hd95_metric': 0.537429928779602} +Epoch [3923/4000] Validation [1/4] Loss: 0.41647 focal_loss 0.35513 dice_loss 0.06134 +Epoch [3923/4000] Validation [2/4] Loss: 0.94729 focal_loss 0.75954 dice_loss 0.18775 +Epoch [3923/4000] Validation [3/4] Loss: 0.57360 focal_loss 0.47366 dice_loss 0.09994 +Epoch [3923/4000] Validation [4/4] Loss: 0.32013 focal_loss 0.22990 dice_loss 0.09023 +Epoch [3923/4000] Validation metric {'Val/mean dice_metric': 0.9725933074951172, 'Val/mean miou_metric': 0.9591388702392578, 'Val/mean f1': 0.9759745001792908, 'Val/mean precision': 0.9743385314941406, 'Val/mean recall': 0.9776159524917603, 'Val/mean hd95_metric': 5.063614368438721} +Cheakpoint... +Epoch [3923/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725933074951172, 'Val/mean miou_metric': 0.9591388702392578, 'Val/mean f1': 0.9759745001792908, 'Val/mean precision': 0.9743385314941406, 'Val/mean recall': 0.9776159524917603, 'Val/mean hd95_metric': 5.063614368438721} +Epoch [3924/4000] Training [1/16] Loss: 0.00257 +Epoch [3924/4000] Training [2/16] Loss: 0.00219 +Epoch [3924/4000] Training [3/16] Loss: 0.00150 +Epoch [3924/4000] Training [4/16] Loss: 0.00219 +Epoch [3924/4000] Training [5/16] Loss: 0.00156 +Epoch [3924/4000] Training [6/16] Loss: 0.00186 +Epoch [3924/4000] Training [7/16] Loss: 0.00249 +Epoch [3924/4000] Training [8/16] Loss: 0.00299 +Epoch [3924/4000] Training [9/16] Loss: 0.00389 +Epoch [3924/4000] Training [10/16] Loss: 0.00317 +Epoch [3924/4000] Training [11/16] Loss: 0.00148 +Epoch [3924/4000] Training [12/16] Loss: 0.00141 +Epoch [3924/4000] Training [13/16] Loss: 0.00230 +Epoch [3924/4000] Training [14/16] Loss: 0.00350 +Epoch [3924/4000] Training [15/16] Loss: 0.00207 +Epoch [3924/4000] Training [16/16] Loss: 0.00236 +Epoch [3924/4000] Training metric {'Train/mean dice_metric': 0.998773992061615, 'Train/mean miou_metric': 0.997275710105896, 'Train/mean f1': 0.9937610626220703, 'Train/mean precision': 0.9892113208770752, 'Train/mean recall': 0.9983528852462769, 'Train/mean hd95_metric': 0.4761993885040283} +Epoch [3924/4000] Validation [1/4] Loss: 0.48856 focal_loss 0.42326 dice_loss 0.06530 +Epoch [3924/4000] Validation [2/4] Loss: 0.46478 focal_loss 0.35537 dice_loss 0.10941 +Epoch [3924/4000] Validation [3/4] Loss: 0.55604 focal_loss 0.45888 dice_loss 0.09716 +Epoch [3924/4000] Validation [4/4] Loss: 0.29223 focal_loss 0.21057 dice_loss 0.08166 +Epoch [3924/4000] Validation metric {'Val/mean dice_metric': 0.9763528108596802, 'Val/mean miou_metric': 0.9622905850410461, 'Val/mean f1': 0.9766117334365845, 'Val/mean precision': 0.9735690355300903, 'Val/mean recall': 0.9796737432479858, 'Val/mean hd95_metric': 4.643952369689941} +Cheakpoint... +Epoch [3924/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9764], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9763528108596802, 'Val/mean miou_metric': 0.9622905850410461, 'Val/mean f1': 0.9766117334365845, 'Val/mean precision': 0.9735690355300903, 'Val/mean recall': 0.9796737432479858, 'Val/mean hd95_metric': 4.643952369689941} +Epoch [3925/4000] Training [1/16] Loss: 0.00180 +Epoch [3925/4000] Training [2/16] Loss: 0.00201 +Epoch [3925/4000] Training [3/16] Loss: 0.00173 +Epoch [3925/4000] Training [4/16] Loss: 0.00260 +Epoch [3925/4000] Training [5/16] Loss: 0.00229 +Epoch [3925/4000] Training [6/16] Loss: 0.00167 +Epoch [3925/4000] Training [7/16] Loss: 0.00266 +Epoch [3925/4000] Training [8/16] Loss: 0.00316 +Epoch [3925/4000] Training [9/16] Loss: 0.00243 +Epoch [3925/4000] Training [10/16] Loss: 0.00268 +Epoch [3925/4000] Training [11/16] Loss: 0.00250 +Epoch [3925/4000] Training [12/16] Loss: 0.00251 +Epoch [3925/4000] Training [13/16] Loss: 0.00158 +Epoch [3925/4000] Training [14/16] Loss: 0.00237 +Epoch [3925/4000] Training [15/16] Loss: 0.00221 +Epoch [3925/4000] Training [16/16] Loss: 0.00222 +Epoch [3925/4000] Training metric {'Train/mean dice_metric': 0.9988384246826172, 'Train/mean miou_metric': 0.9973944425582886, 'Train/mean f1': 0.9937273859977722, 'Train/mean precision': 0.9890837073326111, 'Train/mean recall': 0.9984148144721985, 'Train/mean hd95_metric': 0.5025233030319214} +Epoch [3925/4000] Validation [1/4] Loss: 0.37142 focal_loss 0.31037 dice_loss 0.06105 +Epoch [3925/4000] Validation [2/4] Loss: 0.48336 focal_loss 0.37127 dice_loss 0.11209 +Epoch [3925/4000] Validation [3/4] Loss: 0.56247 focal_loss 0.46905 dice_loss 0.09342 +Epoch [3925/4000] Validation [4/4] Loss: 0.35592 focal_loss 0.26889 dice_loss 0.08702 +Epoch [3925/4000] Validation metric {'Val/mean dice_metric': 0.9751655459403992, 'Val/mean miou_metric': 0.9612704515457153, 'Val/mean f1': 0.9768049120903015, 'Val/mean precision': 0.9743157029151917, 'Val/mean recall': 0.979306697845459, 'Val/mean hd95_metric': 4.744986534118652} +Cheakpoint... +Epoch [3925/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9752], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751655459403992, 'Val/mean miou_metric': 0.9612704515457153, 'Val/mean f1': 0.9768049120903015, 'Val/mean precision': 0.9743157029151917, 'Val/mean recall': 0.979306697845459, 'Val/mean hd95_metric': 4.744986534118652} +Epoch [3926/4000] Training [1/16] Loss: 0.00321 +Epoch [3926/4000] Training [2/16] Loss: 0.00220 +Epoch [3926/4000] Training [3/16] Loss: 0.00430 +Epoch [3926/4000] Training [4/16] Loss: 0.00157 +Epoch [3926/4000] Training [5/16] Loss: 0.00228 +Epoch [3926/4000] Training [6/16] Loss: 0.00233 +Epoch [3926/4000] Training [7/16] Loss: 0.00210 +Epoch [3926/4000] Training [8/16] Loss: 0.00216 +Epoch [3926/4000] Training [9/16] Loss: 0.00323 +Epoch [3926/4000] Training [10/16] Loss: 0.00237 +Epoch [3926/4000] Training [11/16] Loss: 0.00426 +Epoch [3926/4000] Training [12/16] Loss: 0.00253 +Epoch [3926/4000] Training [13/16] Loss: 0.00243 +Epoch [3926/4000] Training [14/16] Loss: 0.00318 +Epoch [3926/4000] Training [15/16] Loss: 0.00238 +Epoch [3926/4000] Training [16/16] Loss: 0.00264 +Epoch [3926/4000] Training metric {'Train/mean dice_metric': 0.9986091256141663, 'Train/mean miou_metric': 0.9969485998153687, 'Train/mean f1': 0.9936806559562683, 'Train/mean precision': 0.989152729511261, 'Train/mean recall': 0.9982502460479736, 'Train/mean hd95_metric': 0.5352017879486084} +Epoch [3926/4000] Validation [1/4] Loss: 0.38908 focal_loss 0.32705 dice_loss 0.06203 +Epoch [3926/4000] Validation [2/4] Loss: 0.50398 focal_loss 0.38914 dice_loss 0.11485 +Epoch [3926/4000] Validation [3/4] Loss: 0.53005 focal_loss 0.43488 dice_loss 0.09517 +Epoch [3926/4000] Validation [4/4] Loss: 0.33380 focal_loss 0.23481 dice_loss 0.09898 +Epoch [3926/4000] Validation metric {'Val/mean dice_metric': 0.974260687828064, 'Val/mean miou_metric': 0.9599811434745789, 'Val/mean f1': 0.9765286445617676, 'Val/mean precision': 0.9743603467941284, 'Val/mean recall': 0.978706419467926, 'Val/mean hd95_metric': 4.983367919921875} +Cheakpoint... +Epoch [3926/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974260687828064, 'Val/mean miou_metric': 0.9599811434745789, 'Val/mean f1': 0.9765286445617676, 'Val/mean precision': 0.9743603467941284, 'Val/mean recall': 0.978706419467926, 'Val/mean hd95_metric': 4.983367919921875} +Epoch [3927/4000] Training [1/16] Loss: 0.00322 +Epoch [3927/4000] Training [2/16] Loss: 0.00247 +Epoch [3927/4000] Training [3/16] Loss: 0.00277 +Epoch [3927/4000] Training [4/16] Loss: 0.00193 +Epoch [3927/4000] Training [5/16] Loss: 0.00269 +Epoch [3927/4000] Training [6/16] Loss: 0.00183 +Epoch [3927/4000] Training [7/16] Loss: 0.00251 +Epoch [3927/4000] Training [8/16] Loss: 0.00165 +Epoch [3927/4000] Training [9/16] Loss: 0.00182 +Epoch [3927/4000] Training [10/16] Loss: 0.00211 +Epoch [3927/4000] Training [11/16] Loss: 0.00339 +Epoch [3927/4000] Training [12/16] Loss: 0.00176 +Epoch [3927/4000] Training [13/16] Loss: 0.00200 +Epoch [3927/4000] Training [14/16] Loss: 0.00245 +Epoch [3927/4000] Training [15/16] Loss: 0.00195 +Epoch [3927/4000] Training [16/16] Loss: 0.00204 +Epoch [3927/4000] Training metric {'Train/mean dice_metric': 0.9987794160842896, 'Train/mean miou_metric': 0.9972506761550903, 'Train/mean f1': 0.9931046366691589, 'Train/mean precision': 0.987891435623169, 'Train/mean recall': 0.9983731508255005, 'Train/mean hd95_metric': 0.507156491279602} +Epoch [3927/4000] Validation [1/4] Loss: 0.38009 focal_loss 0.31874 dice_loss 0.06134 +Epoch [3927/4000] Validation [2/4] Loss: 0.48104 focal_loss 0.37098 dice_loss 0.11006 +Epoch [3927/4000] Validation [3/4] Loss: 0.56451 focal_loss 0.46579 dice_loss 0.09872 +Epoch [3927/4000] Validation [4/4] Loss: 0.47947 focal_loss 0.36823 dice_loss 0.11124 +Epoch [3927/4000] Validation metric {'Val/mean dice_metric': 0.9735778570175171, 'Val/mean miou_metric': 0.95936119556427, 'Val/mean f1': 0.9753729104995728, 'Val/mean precision': 0.9726037979125977, 'Val/mean recall': 0.9781577587127686, 'Val/mean hd95_metric': 5.503543376922607} +Cheakpoint... +Epoch [3927/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735778570175171, 'Val/mean miou_metric': 0.95936119556427, 'Val/mean f1': 0.9753729104995728, 'Val/mean precision': 0.9726037979125977, 'Val/mean recall': 0.9781577587127686, 'Val/mean hd95_metric': 5.503543376922607} +Epoch [3928/4000] Training [1/16] Loss: 0.00189 +Epoch [3928/4000] Training [2/16] Loss: 0.00194 +Epoch [3928/4000] Training [3/16] Loss: 0.00200 +Epoch [3928/4000] Training [4/16] Loss: 0.00233 +Epoch [3928/4000] Training [5/16] Loss: 0.00301 +Epoch [3928/4000] Training [6/16] Loss: 0.00134 +Epoch [3928/4000] Training [7/16] Loss: 0.00180 +Epoch [3928/4000] Training [8/16] Loss: 0.00200 +Epoch [3928/4000] Training [9/16] Loss: 0.00267 +Epoch [3928/4000] Training [10/16] Loss: 0.00261 +Epoch [3928/4000] Training [11/16] Loss: 0.00266 +Epoch [3928/4000] Training [12/16] Loss: 0.00383 +Epoch [3928/4000] Training [13/16] Loss: 0.00172 +Epoch [3928/4000] Training [14/16] Loss: 0.00251 +Epoch [3928/4000] Training [15/16] Loss: 0.00238 +Epoch [3928/4000] Training [16/16] Loss: 0.00340 +Epoch [3928/4000] Training metric {'Train/mean dice_metric': 0.9988928437232971, 'Train/mean miou_metric': 0.9975063800811768, 'Train/mean f1': 0.9937626123428345, 'Train/mean precision': 0.9891728162765503, 'Train/mean recall': 0.9983952045440674, 'Train/mean hd95_metric': 0.46028152108192444} +Epoch [3928/4000] Validation [1/4] Loss: 0.41996 focal_loss 0.35446 dice_loss 0.06550 +Epoch [3928/4000] Validation [2/4] Loss: 0.47941 focal_loss 0.36995 dice_loss 0.10946 +Epoch [3928/4000] Validation [3/4] Loss: 0.56780 focal_loss 0.46976 dice_loss 0.09804 +Epoch [3928/4000] Validation [4/4] Loss: 0.53780 focal_loss 0.40593 dice_loss 0.13188 +Epoch [3928/4000] Validation metric {'Val/mean dice_metric': 0.975316047668457, 'Val/mean miou_metric': 0.9608222842216492, 'Val/mean f1': 0.9763607978820801, 'Val/mean precision': 0.9738974571228027, 'Val/mean recall': 0.9788367748260498, 'Val/mean hd95_metric': 4.936374664306641} +Cheakpoint... +Epoch [3928/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975316047668457, 'Val/mean miou_metric': 0.9608222842216492, 'Val/mean f1': 0.9763607978820801, 'Val/mean precision': 0.9738974571228027, 'Val/mean recall': 0.9788367748260498, 'Val/mean hd95_metric': 4.936374664306641} +Epoch [3929/4000] Training [1/16] Loss: 0.00241 +Epoch [3929/4000] Training [2/16] Loss: 0.00219 +Epoch [3929/4000] Training [3/16] Loss: 0.00259 +Epoch [3929/4000] Training [4/16] Loss: 0.00308 +Epoch [3929/4000] Training [5/16] Loss: 0.00309 +Epoch [3929/4000] Training [6/16] Loss: 0.00408 +Epoch [3929/4000] Training [7/16] Loss: 0.00261 +Epoch [3929/4000] Training [8/16] Loss: 0.00275 +Epoch [3929/4000] Training [9/16] Loss: 0.00296 +Epoch [3929/4000] Training [10/16] Loss: 0.00249 +Epoch [3929/4000] Training [11/16] Loss: 0.00164 +Epoch [3929/4000] Training [12/16] Loss: 0.00379 +Epoch [3929/4000] Training [13/16] Loss: 0.00226 +Epoch [3929/4000] Training [14/16] Loss: 0.00211 +Epoch [3929/4000] Training [15/16] Loss: 0.00235 +Epoch [3929/4000] Training [16/16] Loss: 0.00230 +Epoch [3929/4000] Training metric {'Train/mean dice_metric': 0.9987781047821045, 'Train/mean miou_metric': 0.9972857236862183, 'Train/mean f1': 0.9937639832496643, 'Train/mean precision': 0.9891975522041321, 'Train/mean recall': 0.9983727931976318, 'Train/mean hd95_metric': 0.519070565700531} +Epoch [3929/4000] Validation [1/4] Loss: 0.39545 focal_loss 0.33340 dice_loss 0.06205 +Epoch [3929/4000] Validation [2/4] Loss: 0.48801 focal_loss 0.37483 dice_loss 0.11318 +Epoch [3929/4000] Validation [3/4] Loss: 0.54457 focal_loss 0.44918 dice_loss 0.09540 +Epoch [3929/4000] Validation [4/4] Loss: 0.43290 focal_loss 0.32185 dice_loss 0.11105 +Epoch [3929/4000] Validation metric {'Val/mean dice_metric': 0.9747369885444641, 'Val/mean miou_metric': 0.9608815908432007, 'Val/mean f1': 0.9764460921287537, 'Val/mean precision': 0.9737738966941833, 'Val/mean recall': 0.979133129119873, 'Val/mean hd95_metric': 4.725948810577393} +Cheakpoint... +Epoch [3929/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747369885444641, 'Val/mean miou_metric': 0.9608815908432007, 'Val/mean f1': 0.9764460921287537, 'Val/mean precision': 0.9737738966941833, 'Val/mean recall': 0.979133129119873, 'Val/mean hd95_metric': 4.725948810577393} +Epoch [3930/4000] Training [1/16] Loss: 0.00288 +Epoch [3930/4000] Training [2/16] Loss: 0.00275 +Epoch [3930/4000] Training [3/16] Loss: 0.00192 +Epoch [3930/4000] Training [4/16] Loss: 0.00165 +Epoch [3930/4000] Training [5/16] Loss: 0.00201 +Epoch [3930/4000] Training [6/16] Loss: 0.00214 +Epoch [3930/4000] Training [7/16] Loss: 0.00199 +Epoch [3930/4000] Training [8/16] Loss: 0.00195 +Epoch [3930/4000] Training [9/16] Loss: 0.00170 +Epoch [3930/4000] Training [10/16] Loss: 0.00169 +Epoch [3930/4000] Training [11/16] Loss: 0.00175 +Epoch [3930/4000] Training [12/16] Loss: 0.00226 +Epoch [3930/4000] Training [13/16] Loss: 0.00198 +Epoch [3930/4000] Training [14/16] Loss: 0.00294 +Epoch [3930/4000] Training [15/16] Loss: 0.00201 +Epoch [3930/4000] Training [16/16] Loss: 0.00416 +Epoch [3930/4000] Training metric {'Train/mean dice_metric': 0.9988514184951782, 'Train/mean miou_metric': 0.9974192380905151, 'Train/mean f1': 0.9938112497329712, 'Train/mean precision': 0.9892234802246094, 'Train/mean recall': 0.9984418153762817, 'Train/mean hd95_metric': 0.5449771881103516} +Epoch [3930/4000] Validation [1/4] Loss: 0.47969 focal_loss 0.40285 dice_loss 0.07684 +Epoch [3930/4000] Validation [2/4] Loss: 0.49557 focal_loss 0.38197 dice_loss 0.11360 +Epoch [3930/4000] Validation [3/4] Loss: 0.54198 focal_loss 0.44515 dice_loss 0.09683 +Epoch [3930/4000] Validation [4/4] Loss: 0.34139 focal_loss 0.25067 dice_loss 0.09072 +Epoch [3930/4000] Validation metric {'Val/mean dice_metric': 0.9739547967910767, 'Val/mean miou_metric': 0.9601669311523438, 'Val/mean f1': 0.976090669631958, 'Val/mean precision': 0.9742341041564941, 'Val/mean recall': 0.9779543876647949, 'Val/mean hd95_metric': 4.826966762542725} +Cheakpoint... +Epoch [3930/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739547967910767, 'Val/mean miou_metric': 0.9601669311523438, 'Val/mean f1': 0.976090669631958, 'Val/mean precision': 0.9742341041564941, 'Val/mean recall': 0.9779543876647949, 'Val/mean hd95_metric': 4.826966762542725} +Epoch [3931/4000] Training [1/16] Loss: 0.00403 +Epoch [3931/4000] Training [2/16] Loss: 0.00242 +Epoch [3931/4000] Training [3/16] Loss: 0.00337 +Epoch [3931/4000] Training [4/16] Loss: 0.00156 +Epoch [3931/4000] Training [5/16] Loss: 0.00273 +Epoch [3931/4000] Training [6/16] Loss: 0.00209 +Epoch [3931/4000] Training [7/16] Loss: 0.00238 +Epoch [3931/4000] Training [8/16] Loss: 0.00354 +Epoch [3931/4000] Training [9/16] Loss: 0.00282 +Epoch [3931/4000] Training [10/16] Loss: 0.00167 +Epoch [3931/4000] Training [11/16] Loss: 0.00275 +Epoch [3931/4000] Training [12/16] Loss: 0.00274 +Epoch [3931/4000] Training [13/16] Loss: 0.00133 +Epoch [3931/4000] Training [14/16] Loss: 0.00206 +Epoch [3931/4000] Training [15/16] Loss: 0.00248 +Epoch [3931/4000] Training [16/16] Loss: 0.00194 +Epoch [3931/4000] Training metric {'Train/mean dice_metric': 0.9987914562225342, 'Train/mean miou_metric': 0.9972632527351379, 'Train/mean f1': 0.9927542209625244, 'Train/mean precision': 0.9872981905937195, 'Train/mean recall': 0.9982709288597107, 'Train/mean hd95_metric': 0.5284455418586731} +Epoch [3931/4000] Validation [1/4] Loss: 0.47592 focal_loss 0.41167 dice_loss 0.06426 +Epoch [3931/4000] Validation [2/4] Loss: 0.48647 focal_loss 0.37660 dice_loss 0.10987 +Epoch [3931/4000] Validation [3/4] Loss: 0.50344 focal_loss 0.41722 dice_loss 0.08622 +Epoch [3931/4000] Validation [4/4] Loss: 0.46716 focal_loss 0.35646 dice_loss 0.11069 +Epoch [3931/4000] Validation metric {'Val/mean dice_metric': 0.9745205640792847, 'Val/mean miou_metric': 0.9604703187942505, 'Val/mean f1': 0.9754014611244202, 'Val/mean precision': 0.971731424331665, 'Val/mean recall': 0.9790993928909302, 'Val/mean hd95_metric': 5.205205917358398} +Cheakpoint... +Epoch [3931/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745205640792847, 'Val/mean miou_metric': 0.9604703187942505, 'Val/mean f1': 0.9754014611244202, 'Val/mean precision': 0.971731424331665, 'Val/mean recall': 0.9790993928909302, 'Val/mean hd95_metric': 5.205205917358398} +Epoch [3932/4000] Training [1/16] Loss: 0.00289 +Epoch [3932/4000] Training [2/16] Loss: 0.00181 +Epoch [3932/4000] Training [3/16] Loss: 0.00297 +Epoch [3932/4000] Training [4/16] Loss: 0.00163 +Epoch [3932/4000] Training [5/16] Loss: 0.00209 +Epoch [3932/4000] Training [6/16] Loss: 0.00176 +Epoch [3932/4000] Training [7/16] Loss: 0.00276 +Epoch [3932/4000] Training [8/16] Loss: 0.00200 +Epoch [3932/4000] Training [9/16] Loss: 0.00272 +Epoch [3932/4000] Training [10/16] Loss: 0.00255 +Epoch [3932/4000] Training [11/16] Loss: 0.00186 +Epoch [3932/4000] Training [12/16] Loss: 0.00294 +Epoch [3932/4000] Training [13/16] Loss: 0.00316 +Epoch [3932/4000] Training [14/16] Loss: 0.00206 +Epoch [3932/4000] Training [15/16] Loss: 0.00283 +Epoch [3932/4000] Training [16/16] Loss: 0.00380 +Epoch [3932/4000] Training metric {'Train/mean dice_metric': 0.9987387657165527, 'Train/mean miou_metric': 0.9971781373023987, 'Train/mean f1': 0.9930383563041687, 'Train/mean precision': 0.9878991842269897, 'Train/mean recall': 0.9982312321662903, 'Train/mean hd95_metric': 0.5392853617668152} +Epoch [3932/4000] Validation [1/4] Loss: 0.46272 focal_loss 0.39794 dice_loss 0.06478 +Epoch [3932/4000] Validation [2/4] Loss: 0.48027 focal_loss 0.37031 dice_loss 0.10996 +Epoch [3932/4000] Validation [3/4] Loss: 0.55994 focal_loss 0.46592 dice_loss 0.09402 +Epoch [3932/4000] Validation [4/4] Loss: 0.31791 focal_loss 0.23375 dice_loss 0.08416 +Epoch [3932/4000] Validation metric {'Val/mean dice_metric': 0.9750803112983704, 'Val/mean miou_metric': 0.9610185623168945, 'Val/mean f1': 0.9757805466651917, 'Val/mean precision': 0.972734272480011, 'Val/mean recall': 0.9788459539413452, 'Val/mean hd95_metric': 5.2391133308410645} +Cheakpoint... +Epoch [3932/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750803112983704, 'Val/mean miou_metric': 0.9610185623168945, 'Val/mean f1': 0.9757805466651917, 'Val/mean precision': 0.972734272480011, 'Val/mean recall': 0.9788459539413452, 'Val/mean hd95_metric': 5.2391133308410645} +Epoch [3933/4000] Training [1/16] Loss: 0.00429 +Epoch [3933/4000] Training [2/16] Loss: 0.00279 +Epoch [3933/4000] Training [3/16] Loss: 0.00225 +Epoch [3933/4000] Training [4/16] Loss: 0.00208 +Epoch [3933/4000] Training [5/16] Loss: 0.00220 +Epoch [3933/4000] Training [6/16] Loss: 0.00303 +Epoch [3933/4000] Training [7/16] Loss: 0.00226 +Epoch [3933/4000] Training [8/16] Loss: 0.00240 +Epoch [3933/4000] Training [9/16] Loss: 0.00229 +Epoch [3933/4000] Training [10/16] Loss: 0.00222 +Epoch [3933/4000] Training [11/16] Loss: 0.00255 +Epoch [3933/4000] Training [12/16] Loss: 0.00264 +Epoch [3933/4000] Training [13/16] Loss: 0.00180 +Epoch [3933/4000] Training [14/16] Loss: 0.00255 +Epoch [3933/4000] Training [15/16] Loss: 0.00314 +Epoch [3933/4000] Training [16/16] Loss: 0.00277 +Epoch [3933/4000] Training metric {'Train/mean dice_metric': 0.9987378120422363, 'Train/mean miou_metric': 0.9972039461135864, 'Train/mean f1': 0.9937439560890198, 'Train/mean precision': 0.9892251491546631, 'Train/mean recall': 0.9983041882514954, 'Train/mean hd95_metric': 0.51340651512146} +Epoch [3933/4000] Validation [1/4] Loss: 0.39706 focal_loss 0.33671 dice_loss 0.06034 +Epoch [3933/4000] Validation [2/4] Loss: 0.54628 focal_loss 0.41369 dice_loss 0.13259 +Epoch [3933/4000] Validation [3/4] Loss: 0.54035 focal_loss 0.44428 dice_loss 0.09608 +Epoch [3933/4000] Validation [4/4] Loss: 0.40273 focal_loss 0.29622 dice_loss 0.10651 +Epoch [3933/4000] Validation metric {'Val/mean dice_metric': 0.9751442074775696, 'Val/mean miou_metric': 0.9608689546585083, 'Val/mean f1': 0.9764342904090881, 'Val/mean precision': 0.9741867780685425, 'Val/mean recall': 0.9786921739578247, 'Val/mean hd95_metric': 4.7693190574646} +Cheakpoint... +Epoch [3933/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9751442074775696, 'Val/mean miou_metric': 0.9608689546585083, 'Val/mean f1': 0.9764342904090881, 'Val/mean precision': 0.9741867780685425, 'Val/mean recall': 0.9786921739578247, 'Val/mean hd95_metric': 4.7693190574646} +Epoch [3934/4000] Training [1/16] Loss: 0.00325 +Epoch [3934/4000] Training [2/16] Loss: 0.00247 +Epoch [3934/4000] Training [3/16] Loss: 0.00284 +Epoch [3934/4000] Training [4/16] Loss: 0.00181 +Epoch [3934/4000] Training [5/16] Loss: 0.00276 +Epoch [3934/4000] Training [6/16] Loss: 0.00187 +Epoch [3934/4000] Training [7/16] Loss: 0.00245 +Epoch [3934/4000] Training [8/16] Loss: 0.00200 +Epoch [3934/4000] Training [9/16] Loss: 0.00210 +Epoch [3934/4000] Training [10/16] Loss: 0.00196 +Epoch [3934/4000] Training [11/16] Loss: 0.00211 +Epoch [3934/4000] Training [12/16] Loss: 0.00335 +Epoch [3934/4000] Training [13/16] Loss: 0.00213 +Epoch [3934/4000] Training [14/16] Loss: 0.00211 +Epoch [3934/4000] Training [15/16] Loss: 0.00304 +Epoch [3934/4000] Training [16/16] Loss: 0.00233 +Epoch [3934/4000] Training metric {'Train/mean dice_metric': 0.9987385869026184, 'Train/mean miou_metric': 0.997169554233551, 'Train/mean f1': 0.993377149105072, 'Train/mean precision': 0.988522469997406, 'Train/mean recall': 0.9982797503471375, 'Train/mean hd95_metric': 0.531998872756958} +Epoch [3934/4000] Validation [1/4] Loss: 0.36448 focal_loss 0.30615 dice_loss 0.05833 +Epoch [3934/4000] Validation [2/4] Loss: 0.47897 focal_loss 0.37055 dice_loss 0.10842 +Epoch [3934/4000] Validation [3/4] Loss: 0.52970 focal_loss 0.43566 dice_loss 0.09404 +Epoch [3934/4000] Validation [4/4] Loss: 0.32853 focal_loss 0.24065 dice_loss 0.08788 +Epoch [3934/4000] Validation metric {'Val/mean dice_metric': 0.9750407934188843, 'Val/mean miou_metric': 0.9609884023666382, 'Val/mean f1': 0.9764506220817566, 'Val/mean precision': 0.9737140536308289, 'Val/mean recall': 0.9792026877403259, 'Val/mean hd95_metric': 4.969216823577881} +Cheakpoint... +Epoch [3934/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750407934188843, 'Val/mean miou_metric': 0.9609884023666382, 'Val/mean f1': 0.9764506220817566, 'Val/mean precision': 0.9737140536308289, 'Val/mean recall': 0.9792026877403259, 'Val/mean hd95_metric': 4.969216823577881} +Epoch [3935/4000] Training [1/16] Loss: 0.00156 +Epoch [3935/4000] Training [2/16] Loss: 0.00268 +Epoch [3935/4000] Training [3/16] Loss: 0.00320 +Epoch [3935/4000] Training [4/16] Loss: 0.00204 +Epoch [3935/4000] Training [5/16] Loss: 0.00326 +Epoch [3935/4000] Training [6/16] Loss: 0.00296 +Epoch [3935/4000] Training [7/16] Loss: 0.00175 +Epoch [3935/4000] Training [8/16] Loss: 0.00244 +Epoch [3935/4000] Training [9/16] Loss: 0.00241 +Epoch [3935/4000] Training [10/16] Loss: 0.00234 +Epoch [3935/4000] Training [11/16] Loss: 0.00225 +Epoch [3935/4000] Training [12/16] Loss: 0.00237 +Epoch [3935/4000] Training [13/16] Loss: 0.00312 +Epoch [3935/4000] Training [14/16] Loss: 0.00349 +Epoch [3935/4000] Training [15/16] Loss: 0.00257 +Epoch [3935/4000] Training [16/16] Loss: 0.00211 +Epoch [3935/4000] Training metric {'Train/mean dice_metric': 0.9985578060150146, 'Train/mean miou_metric': 0.9968491196632385, 'Train/mean f1': 0.99369877576828, 'Train/mean precision': 0.9892128705978394, 'Train/mean recall': 0.9982255697250366, 'Train/mean hd95_metric': 0.5456608533859253} +Epoch [3935/4000] Validation [1/4] Loss: 0.43976 focal_loss 0.37737 dice_loss 0.06240 +Epoch [3935/4000] Validation [2/4] Loss: 0.49164 focal_loss 0.38053 dice_loss 0.11111 +Epoch [3935/4000] Validation [3/4] Loss: 0.56279 focal_loss 0.46925 dice_loss 0.09354 +Epoch [3935/4000] Validation [4/4] Loss: 0.38158 focal_loss 0.27844 dice_loss 0.10314 +Epoch [3935/4000] Validation metric {'Val/mean dice_metric': 0.9748967885971069, 'Val/mean miou_metric': 0.96075439453125, 'Val/mean f1': 0.9767849445343018, 'Val/mean precision': 0.9747415781021118, 'Val/mean recall': 0.9788369536399841, 'Val/mean hd95_metric': 4.825074195861816} +Cheakpoint... +Epoch [3935/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9749], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748967885971069, 'Val/mean miou_metric': 0.96075439453125, 'Val/mean f1': 0.9767849445343018, 'Val/mean precision': 0.9747415781021118, 'Val/mean recall': 0.9788369536399841, 'Val/mean hd95_metric': 4.825074195861816} +Epoch [3936/4000] Training [1/16] Loss: 0.00202 +Epoch [3936/4000] Training [2/16] Loss: 0.00198 +Epoch [3936/4000] Training [3/16] Loss: 0.00202 +Epoch [3936/4000] Training [4/16] Loss: 0.00218 +Epoch [3936/4000] Training [5/16] Loss: 0.00275 +Epoch [3936/4000] Training [6/16] Loss: 0.00211 +Epoch [3936/4000] Training [7/16] Loss: 0.00287 +Epoch [3936/4000] Training [8/16] Loss: 0.00152 +Epoch [3936/4000] Training [9/16] Loss: 0.00188 +Epoch [3936/4000] Training [10/16] Loss: 0.00258 +Epoch [3936/4000] Training [11/16] Loss: 0.00212 +Epoch [3936/4000] Training [12/16] Loss: 0.00254 +Epoch [3936/4000] Training [13/16] Loss: 0.00201 +Epoch [3936/4000] Training [14/16] Loss: 0.00177 +Epoch [3936/4000] Training [15/16] Loss: 0.00162 +Epoch [3936/4000] Training [16/16] Loss: 0.00237 +Epoch [3936/4000] Training metric {'Train/mean dice_metric': 0.9989733099937439, 'Train/mean miou_metric': 0.9976290464401245, 'Train/mean f1': 0.9930945634841919, 'Train/mean precision': 0.9878314137458801, 'Train/mean recall': 0.9984140396118164, 'Train/mean hd95_metric': 0.5025942325592041} +Epoch [3936/4000] Validation [1/4] Loss: 0.35420 focal_loss 0.29551 dice_loss 0.05869 +Epoch [3936/4000] Validation [2/4] Loss: 0.45677 focal_loss 0.34993 dice_loss 0.10685 +Epoch [3936/4000] Validation [3/4] Loss: 0.59747 focal_loss 0.49857 dice_loss 0.09890 +Epoch [3936/4000] Validation [4/4] Loss: 0.37728 focal_loss 0.26277 dice_loss 0.11451 +Epoch [3936/4000] Validation metric {'Val/mean dice_metric': 0.9748406410217285, 'Val/mean miou_metric': 0.9607908129692078, 'Val/mean f1': 0.9757012128829956, 'Val/mean precision': 0.9720802307128906, 'Val/mean recall': 0.9793491959571838, 'Val/mean hd95_metric': 5.302664279937744} +Cheakpoint... +Epoch [3936/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748406410217285, 'Val/mean miou_metric': 0.9607908129692078, 'Val/mean f1': 0.9757012128829956, 'Val/mean precision': 0.9720802307128906, 'Val/mean recall': 0.9793491959571838, 'Val/mean hd95_metric': 5.302664279937744} +Epoch [3937/4000] Training [1/16] Loss: 0.00264 +Epoch [3937/4000] Training [2/16] Loss: 0.00225 +Epoch [3937/4000] Training [3/16] Loss: 0.00281 +Epoch [3937/4000] Training [4/16] Loss: 0.00218 +Epoch [3937/4000] Training [5/16] Loss: 0.00191 +Epoch [3937/4000] Training [6/16] Loss: 0.00267 +Epoch [3937/4000] Training [7/16] Loss: 0.00272 +Epoch [3937/4000] Training [8/16] Loss: 0.00213 +Epoch [3937/4000] Training [9/16] Loss: 0.00185 +Epoch [3937/4000] Training [10/16] Loss: 0.00194 +Epoch [3937/4000] Training [11/16] Loss: 0.00305 +Epoch [3937/4000] Training [12/16] Loss: 0.00178 +Epoch [3937/4000] Training [13/16] Loss: 0.00320 +Epoch [3937/4000] Training [14/16] Loss: 0.00197 +Epoch [3937/4000] Training [15/16] Loss: 0.00244 +Epoch [3937/4000] Training [16/16] Loss: 0.00220 +Epoch [3937/4000] Training metric {'Train/mean dice_metric': 0.9987921714782715, 'Train/mean miou_metric': 0.9973050951957703, 'Train/mean f1': 0.9937006235122681, 'Train/mean precision': 0.9890991449356079, 'Train/mean recall': 0.9983450770378113, 'Train/mean hd95_metric': 0.5332305431365967} +Epoch [3937/4000] Validation [1/4] Loss: 0.39830 focal_loss 0.33677 dice_loss 0.06153 +Epoch [3937/4000] Validation [2/4] Loss: 0.54416 focal_loss 0.40895 dice_loss 0.13521 +Epoch [3937/4000] Validation [3/4] Loss: 0.53078 focal_loss 0.44122 dice_loss 0.08956 +Epoch [3937/4000] Validation [4/4] Loss: 0.35550 focal_loss 0.26924 dice_loss 0.08626 +Epoch [3937/4000] Validation metric {'Val/mean dice_metric': 0.9756087064743042, 'Val/mean miou_metric': 0.9616580009460449, 'Val/mean f1': 0.9764063358306885, 'Val/mean precision': 0.9735432267189026, 'Val/mean recall': 0.9792861342430115, 'Val/mean hd95_metric': 4.946992874145508} +Cheakpoint... +Epoch [3937/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756087064743042, 'Val/mean miou_metric': 0.9616580009460449, 'Val/mean f1': 0.9764063358306885, 'Val/mean precision': 0.9735432267189026, 'Val/mean recall': 0.9792861342430115, 'Val/mean hd95_metric': 4.946992874145508} +Epoch [3938/4000] Training [1/16] Loss: 0.00208 +Epoch [3938/4000] Training [2/16] Loss: 0.00198 +Epoch [3938/4000] Training [3/16] Loss: 0.00231 +Epoch [3938/4000] Training [4/16] Loss: 0.00314 +Epoch [3938/4000] Training [5/16] Loss: 0.00262 +Epoch [3938/4000] Training [6/16] Loss: 0.00194 +Epoch [3938/4000] Training [7/16] Loss: 0.00213 +Epoch [3938/4000] Training [8/16] Loss: 0.00244 +Epoch [3938/4000] Training [9/16] Loss: 0.00238 +Epoch [3938/4000] Training [10/16] Loss: 0.00196 +Epoch [3938/4000] Training [11/16] Loss: 0.00263 +Epoch [3938/4000] Training [12/16] Loss: 0.00362 +Epoch [3938/4000] Training [13/16] Loss: 0.00283 +Epoch [3938/4000] Training [14/16] Loss: 0.00218 +Epoch [3938/4000] Training [15/16] Loss: 0.00229 +Epoch [3938/4000] Training [16/16] Loss: 0.00196 +Epoch [3938/4000] Training metric {'Train/mean dice_metric': 0.998908519744873, 'Train/mean miou_metric': 0.9975413084030151, 'Train/mean f1': 0.9939149618148804, 'Train/mean precision': 0.9893527626991272, 'Train/mean recall': 0.9985193610191345, 'Train/mean hd95_metric': 0.4842071533203125} +Epoch [3938/4000] Validation [1/4] Loss: 0.40643 focal_loss 0.34281 dice_loss 0.06362 +Epoch [3938/4000] Validation [2/4] Loss: 0.48484 focal_loss 0.37323 dice_loss 0.11160 +Epoch [3938/4000] Validation [3/4] Loss: 0.54480 focal_loss 0.44753 dice_loss 0.09726 +Epoch [3938/4000] Validation [4/4] Loss: 0.39194 focal_loss 0.30111 dice_loss 0.09084 +Epoch [3938/4000] Validation metric {'Val/mean dice_metric': 0.9746366739273071, 'Val/mean miou_metric': 0.9606760144233704, 'Val/mean f1': 0.9762837290763855, 'Val/mean precision': 0.9747079014778137, 'Val/mean recall': 0.977864682674408, 'Val/mean hd95_metric': 4.595239162445068} +Cheakpoint... +Epoch [3938/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746366739273071, 'Val/mean miou_metric': 0.9606760144233704, 'Val/mean f1': 0.9762837290763855, 'Val/mean precision': 0.9747079014778137, 'Val/mean recall': 0.977864682674408, 'Val/mean hd95_metric': 4.595239162445068} +Epoch [3939/4000] Training [1/16] Loss: 0.00181 +Epoch [3939/4000] Training [2/16] Loss: 0.00213 +Epoch [3939/4000] Training [3/16] Loss: 0.00216 +Epoch [3939/4000] Training [4/16] Loss: 0.00252 +Epoch [3939/4000] Training [5/16] Loss: 0.00578 +Epoch [3939/4000] Training [6/16] Loss: 0.00213 +Epoch [3939/4000] Training [7/16] Loss: 0.00264 +Epoch [3939/4000] Training [8/16] Loss: 0.00213 +Epoch [3939/4000] Training [9/16] Loss: 0.00255 +Epoch [3939/4000] Training [10/16] Loss: 0.00281 +Epoch [3939/4000] Training [11/16] Loss: 0.00195 +Epoch [3939/4000] Training [12/16] Loss: 0.00213 +Epoch [3939/4000] Training [13/16] Loss: 0.00229 +Epoch [3939/4000] Training [14/16] Loss: 0.00292 +Epoch [3939/4000] Training [15/16] Loss: 0.00216 +Epoch [3939/4000] Training [16/16] Loss: 0.00369 +Epoch [3939/4000] Training metric {'Train/mean dice_metric': 0.9988279938697815, 'Train/mean miou_metric': 0.9973838329315186, 'Train/mean f1': 0.9938571453094482, 'Train/mean precision': 0.989306628704071, 'Train/mean recall': 0.9984497427940369, 'Train/mean hd95_metric': 0.5335513949394226} +Epoch [3939/4000] Validation [1/4] Loss: 0.38365 focal_loss 0.32248 dice_loss 0.06117 +Epoch [3939/4000] Validation [2/4] Loss: 0.97541 focal_loss 0.78571 dice_loss 0.18970 +Epoch [3939/4000] Validation [3/4] Loss: 0.59285 focal_loss 0.49230 dice_loss 0.10055 +Epoch [3939/4000] Validation [4/4] Loss: 0.43516 focal_loss 0.32062 dice_loss 0.11454 +Epoch [3939/4000] Validation metric {'Val/mean dice_metric': 0.9735792279243469, 'Val/mean miou_metric': 0.9596258401870728, 'Val/mean f1': 0.9760962724685669, 'Val/mean precision': 0.9740062355995178, 'Val/mean recall': 0.978195309638977, 'Val/mean hd95_metric': 5.356443405151367} +Cheakpoint... +Epoch [3939/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9736], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735792279243469, 'Val/mean miou_metric': 0.9596258401870728, 'Val/mean f1': 0.9760962724685669, 'Val/mean precision': 0.9740062355995178, 'Val/mean recall': 0.978195309638977, 'Val/mean hd95_metric': 5.356443405151367} +Epoch [3940/4000] Training [1/16] Loss: 0.00168 +Epoch [3940/4000] Training [2/16] Loss: 0.00259 +Epoch [3940/4000] Training [3/16] Loss: 0.00153 +Epoch [3940/4000] Training [4/16] Loss: 0.00242 +Epoch [3940/4000] Training [5/16] Loss: 0.00192 +Epoch [3940/4000] Training [6/16] Loss: 0.00256 +Epoch [3940/4000] Training [7/16] Loss: 0.00155 +Epoch [3940/4000] Training [8/16] Loss: 0.00326 +Epoch [3940/4000] Training [9/16] Loss: 0.00215 +Epoch [3940/4000] Training [10/16] Loss: 0.00150 +Epoch [3940/4000] Training [11/16] Loss: 0.00234 +Epoch [3940/4000] Training [12/16] Loss: 0.00347 +Epoch [3940/4000] Training [13/16] Loss: 0.01597 +Epoch [3940/4000] Training [14/16] Loss: 0.00207 +Epoch [3940/4000] Training [15/16] Loss: 0.00233 +Epoch [3940/4000] Training [16/16] Loss: 0.00204 +Epoch [3940/4000] Training metric {'Train/mean dice_metric': 0.9988092184066772, 'Train/mean miou_metric': 0.9973553419113159, 'Train/mean f1': 0.9938355684280396, 'Train/mean precision': 0.989344596862793, 'Train/mean recall': 0.9983674883842468, 'Train/mean hd95_metric': 0.48390790820121765} +Epoch [3940/4000] Validation [1/4] Loss: 0.42737 focal_loss 0.36420 dice_loss 0.06317 +Epoch [3940/4000] Validation [2/4] Loss: 0.45607 focal_loss 0.35034 dice_loss 0.10573 +Epoch [3940/4000] Validation [3/4] Loss: 0.52946 focal_loss 0.43930 dice_loss 0.09015 +Epoch [3940/4000] Validation [4/4] Loss: 0.33051 focal_loss 0.22727 dice_loss 0.10323 +Epoch [3940/4000] Validation metric {'Val/mean dice_metric': 0.975115954875946, 'Val/mean miou_metric': 0.9612016677856445, 'Val/mean f1': 0.9766960144042969, 'Val/mean precision': 0.9740175008773804, 'Val/mean recall': 0.9793893694877625, 'Val/mean hd95_metric': 4.648131847381592} +Cheakpoint... +Epoch [3940/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975115954875946, 'Val/mean miou_metric': 0.9612016677856445, 'Val/mean f1': 0.9766960144042969, 'Val/mean precision': 0.9740175008773804, 'Val/mean recall': 0.9793893694877625, 'Val/mean hd95_metric': 4.648131847381592} +Epoch [3941/4000] Training [1/16] Loss: 0.00214 +Epoch [3941/4000] Training [2/16] Loss: 0.00248 +Epoch [3941/4000] Training [3/16] Loss: 0.00177 +Epoch [3941/4000] Training [4/16] Loss: 0.00257 +Epoch [3941/4000] Training [5/16] Loss: 0.00294 +Epoch [3941/4000] Training [6/16] Loss: 0.00204 +Epoch [3941/4000] Training [7/16] Loss: 0.00385 +Epoch [3941/4000] Training [8/16] Loss: 0.00184 +Epoch [3941/4000] Training [9/16] Loss: 0.00238 +Epoch [3941/4000] Training [10/16] Loss: 0.00473 +Epoch [3941/4000] Training [11/16] Loss: 0.00199 +Epoch [3941/4000] Training [12/16] Loss: 0.00191 +Epoch [3941/4000] Training [13/16] Loss: 0.00214 +Epoch [3941/4000] Training [14/16] Loss: 0.00255 +Epoch [3941/4000] Training [15/16] Loss: 0.00253 +Epoch [3941/4000] Training [16/16] Loss: 0.00234 +Epoch [3941/4000] Training metric {'Train/mean dice_metric': 0.9987736344337463, 'Train/mean miou_metric': 0.9972753524780273, 'Train/mean f1': 0.9937485456466675, 'Train/mean precision': 0.9892001152038574, 'Train/mean recall': 0.9983389973640442, 'Train/mean hd95_metric': 0.5520901083946228} +Epoch [3941/4000] Validation [1/4] Loss: 0.42208 focal_loss 0.35911 dice_loss 0.06297 +Epoch [3941/4000] Validation [2/4] Loss: 0.79520 focal_loss 0.58647 dice_loss 0.20873 +Epoch [3941/4000] Validation [3/4] Loss: 0.57679 focal_loss 0.47654 dice_loss 0.10025 +Epoch [3941/4000] Validation [4/4] Loss: 0.34968 focal_loss 0.26172 dice_loss 0.08796 +Epoch [3941/4000] Validation metric {'Val/mean dice_metric': 0.9725703001022339, 'Val/mean miou_metric': 0.9588451385498047, 'Val/mean f1': 0.9754585027694702, 'Val/mean precision': 0.9731908440589905, 'Val/mean recall': 0.9777366518974304, 'Val/mean hd95_metric': 5.403246879577637} +Cheakpoint... +Epoch [3941/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9726], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725703001022339, 'Val/mean miou_metric': 0.9588451385498047, 'Val/mean f1': 0.9754585027694702, 'Val/mean precision': 0.9731908440589905, 'Val/mean recall': 0.9777366518974304, 'Val/mean hd95_metric': 5.403246879577637} +Epoch [3942/4000] Training [1/16] Loss: 0.00186 +Epoch [3942/4000] Training [2/16] Loss: 0.00216 +Epoch [3942/4000] Training [3/16] Loss: 0.00204 +Epoch [3942/4000] Training [4/16] Loss: 0.00191 +Epoch [3942/4000] Training [5/16] Loss: 0.00282 +Epoch [3942/4000] Training [6/16] Loss: 0.00183 +Epoch [3942/4000] Training [7/16] Loss: 0.00232 +Epoch [3942/4000] Training [8/16] Loss: 0.00220 +Epoch [3942/4000] Training [9/16] Loss: 0.00282 +Epoch [3942/4000] Training [10/16] Loss: 0.00213 +Epoch [3942/4000] Training [11/16] Loss: 0.00232 +Epoch [3942/4000] Training [12/16] Loss: 0.00348 +Epoch [3942/4000] Training [13/16] Loss: 0.00251 +Epoch [3942/4000] Training [14/16] Loss: 0.00355 +Epoch [3942/4000] Training [15/16] Loss: 0.00307 +Epoch [3942/4000] Training [16/16] Loss: 0.00180 +Epoch [3942/4000] Training metric {'Train/mean dice_metric': 0.9988518953323364, 'Train/mean miou_metric': 0.9974292516708374, 'Train/mean f1': 0.9939147233963013, 'Train/mean precision': 0.9894269108772278, 'Train/mean recall': 0.9984434843063354, 'Train/mean hd95_metric': 0.5090397596359253} +Epoch [3942/4000] Validation [1/4] Loss: 0.36764 focal_loss 0.30426 dice_loss 0.06339 +Epoch [3942/4000] Validation [2/4] Loss: 0.48657 focal_loss 0.37571 dice_loss 0.11086 +Epoch [3942/4000] Validation [3/4] Loss: 0.57115 focal_loss 0.47416 dice_loss 0.09699 +Epoch [3942/4000] Validation [4/4] Loss: 0.35461 focal_loss 0.26887 dice_loss 0.08575 +Epoch [3942/4000] Validation metric {'Val/mean dice_metric': 0.9746155738830566, 'Val/mean miou_metric': 0.9605865478515625, 'Val/mean f1': 0.9767003059387207, 'Val/mean precision': 0.9746196866035461, 'Val/mean recall': 0.9787898063659668, 'Val/mean hd95_metric': 4.864991188049316} +Cheakpoint... +Epoch [3942/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746155738830566, 'Val/mean miou_metric': 0.9605865478515625, 'Val/mean f1': 0.9767003059387207, 'Val/mean precision': 0.9746196866035461, 'Val/mean recall': 0.9787898063659668, 'Val/mean hd95_metric': 4.864991188049316} +Epoch [3943/4000] Training [1/16] Loss: 0.00311 +Epoch [3943/4000] Training [2/16] Loss: 0.00242 +Epoch [3943/4000] Training [3/16] Loss: 0.00319 +Epoch [3943/4000] Training [4/16] Loss: 0.00306 +Epoch [3943/4000] Training [5/16] Loss: 0.00185 +Epoch [3943/4000] Training [6/16] Loss: 0.00233 +Epoch [3943/4000] Training [7/16] Loss: 0.00312 +Epoch [3943/4000] Training [8/16] Loss: 0.00187 +Epoch [3943/4000] Training [9/16] Loss: 0.00182 +Epoch [3943/4000] Training [10/16] Loss: 0.00242 +Epoch [3943/4000] Training [11/16] Loss: 0.00187 +Epoch [3943/4000] Training [12/16] Loss: 0.00237 +Epoch [3943/4000] Training [13/16] Loss: 0.00204 +Epoch [3943/4000] Training [14/16] Loss: 0.00235 +Epoch [3943/4000] Training [15/16] Loss: 0.00328 +Epoch [3943/4000] Training [16/16] Loss: 0.00199 +Epoch [3943/4000] Training metric {'Train/mean dice_metric': 0.998963475227356, 'Train/mean miou_metric': 0.9976237416267395, 'Train/mean f1': 0.9934353828430176, 'Train/mean precision': 0.9884578585624695, 'Train/mean recall': 0.9984632730484009, 'Train/mean hd95_metric': 0.47551578283309937} +Epoch [3943/4000] Validation [1/4] Loss: 0.39760 focal_loss 0.33600 dice_loss 0.06160 +Epoch [3943/4000] Validation [2/4] Loss: 0.47662 focal_loss 0.36715 dice_loss 0.10948 +Epoch [3943/4000] Validation [3/4] Loss: 0.53045 focal_loss 0.44213 dice_loss 0.08832 +Epoch [3943/4000] Validation [4/4] Loss: 0.34359 focal_loss 0.25453 dice_loss 0.08906 +Epoch [3943/4000] Validation metric {'Val/mean dice_metric': 0.9753134846687317, 'Val/mean miou_metric': 0.9612358212471008, 'Val/mean f1': 0.9762434363365173, 'Val/mean precision': 0.9729439616203308, 'Val/mean recall': 0.9795652627944946, 'Val/mean hd95_metric': 5.0226969718933105} +Cheakpoint... +Epoch [3943/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753134846687317, 'Val/mean miou_metric': 0.9612358212471008, 'Val/mean f1': 0.9762434363365173, 'Val/mean precision': 0.9729439616203308, 'Val/mean recall': 0.9795652627944946, 'Val/mean hd95_metric': 5.0226969718933105} +Epoch [3944/4000] Training [1/16] Loss: 0.00195 +Epoch [3944/4000] Training [2/16] Loss: 0.00220 +Epoch [3944/4000] Training [3/16] Loss: 0.00209 +Epoch [3944/4000] Training [4/16] Loss: 0.00364 +Epoch [3944/4000] Training [5/16] Loss: 0.00202 +Epoch [3944/4000] Training [6/16] Loss: 0.00222 +Epoch [3944/4000] Training [7/16] Loss: 0.00324 +Epoch [3944/4000] Training [8/16] Loss: 0.00186 +Epoch [3944/4000] Training [9/16] Loss: 0.00230 +Epoch [3944/4000] Training [10/16] Loss: 0.00178 +Epoch [3944/4000] Training [11/16] Loss: 0.00220 +Epoch [3944/4000] Training [12/16] Loss: 0.00221 +Epoch [3944/4000] Training [13/16] Loss: 0.00281 +Epoch [3944/4000] Training [14/16] Loss: 0.00211 +Epoch [3944/4000] Training [15/16] Loss: 0.00334 +Epoch [3944/4000] Training [16/16] Loss: 0.00291 +Epoch [3944/4000] Training metric {'Train/mean dice_metric': 0.9987785220146179, 'Train/mean miou_metric': 0.9972834587097168, 'Train/mean f1': 0.9938384890556335, 'Train/mean precision': 0.9893620610237122, 'Train/mean recall': 0.9983556270599365, 'Train/mean hd95_metric': 0.5377228260040283} +Epoch [3944/4000] Validation [1/4] Loss: 0.40673 focal_loss 0.34529 dice_loss 0.06144 +Epoch [3944/4000] Validation [2/4] Loss: 0.59307 focal_loss 0.44123 dice_loss 0.15184 +Epoch [3944/4000] Validation [3/4] Loss: 0.57893 focal_loss 0.48032 dice_loss 0.09861 +Epoch [3944/4000] Validation [4/4] Loss: 0.32992 focal_loss 0.24351 dice_loss 0.08641 +Epoch [3944/4000] Validation metric {'Val/mean dice_metric': 0.9742342233657837, 'Val/mean miou_metric': 0.959935188293457, 'Val/mean f1': 0.9760210514068604, 'Val/mean precision': 0.9732904434204102, 'Val/mean recall': 0.9787670373916626, 'Val/mean hd95_metric': 5.670220851898193} +Cheakpoint... +Epoch [3944/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742342233657837, 'Val/mean miou_metric': 0.959935188293457, 'Val/mean f1': 0.9760210514068604, 'Val/mean precision': 0.9732904434204102, 'Val/mean recall': 0.9787670373916626, 'Val/mean hd95_metric': 5.670220851898193} +Epoch [3945/4000] Training [1/16] Loss: 0.00190 +Epoch [3945/4000] Training [2/16] Loss: 0.00295 +Epoch [3945/4000] Training [3/16] Loss: 0.00255 +Epoch [3945/4000] Training [4/16] Loss: 0.00212 +Epoch [3945/4000] Training [5/16] Loss: 0.00231 +Epoch [3945/4000] Training [6/16] Loss: 0.00223 +Epoch [3945/4000] Training [7/16] Loss: 0.00235 +Epoch [3945/4000] Training [8/16] Loss: 0.00244 +Epoch [3945/4000] Training [9/16] Loss: 0.00260 +Epoch [3945/4000] Training [10/16] Loss: 0.00183 +Epoch [3945/4000] Training [11/16] Loss: 0.00195 +Epoch [3945/4000] Training [12/16] Loss: 0.00361 +Epoch [3945/4000] Training [13/16] Loss: 0.00266 +Epoch [3945/4000] Training [14/16] Loss: 0.00201 +Epoch [3945/4000] Training [15/16] Loss: 0.00266 +Epoch [3945/4000] Training [16/16] Loss: 0.00224 +Epoch [3945/4000] Training metric {'Train/mean dice_metric': 0.9988899827003479, 'Train/mean miou_metric': 0.9974813461303711, 'Train/mean f1': 0.9935540556907654, 'Train/mean precision': 0.9887291193008423, 'Train/mean recall': 0.9984263181686401, 'Train/mean hd95_metric': 0.5151641368865967} +Epoch [3945/4000] Validation [1/4] Loss: 0.48129 focal_loss 0.41692 dice_loss 0.06438 +Epoch [3945/4000] Validation [2/4] Loss: 0.48389 focal_loss 0.37078 dice_loss 0.11310 +Epoch [3945/4000] Validation [3/4] Loss: 0.51222 focal_loss 0.41660 dice_loss 0.09563 +Epoch [3945/4000] Validation [4/4] Loss: 0.44631 focal_loss 0.34080 dice_loss 0.10550 +Epoch [3945/4000] Validation metric {'Val/mean dice_metric': 0.975555419921875, 'Val/mean miou_metric': 0.9615579843521118, 'Val/mean f1': 0.9760207533836365, 'Val/mean precision': 0.9736093878746033, 'Val/mean recall': 0.9784440398216248, 'Val/mean hd95_metric': 4.801754474639893} +Cheakpoint... +Epoch [3945/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9756], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975555419921875, 'Val/mean miou_metric': 0.9615579843521118, 'Val/mean f1': 0.9760207533836365, 'Val/mean precision': 0.9736093878746033, 'Val/mean recall': 0.9784440398216248, 'Val/mean hd95_metric': 4.801754474639893} +Epoch [3946/4000] Training [1/16] Loss: 0.00155 +Epoch [3946/4000] Training [2/16] Loss: 0.00241 +Epoch [3946/4000] Training [3/16] Loss: 0.00228 +Epoch [3946/4000] Training [4/16] Loss: 0.00225 +Epoch [3946/4000] Training [5/16] Loss: 0.00138 +Epoch [3946/4000] Training [6/16] Loss: 0.00216 +Epoch [3946/4000] Training [7/16] Loss: 0.00295 +Epoch [3946/4000] Training [8/16] Loss: 0.00277 +Epoch [3946/4000] Training [9/16] Loss: 0.00170 +Epoch [3946/4000] Training [10/16] Loss: 0.00171 +Epoch [3946/4000] Training [11/16] Loss: 0.00292 +Epoch [3946/4000] Training [12/16] Loss: 0.00241 +Epoch [3946/4000] Training [13/16] Loss: 0.00358 +Epoch [3946/4000] Training [14/16] Loss: 0.00246 +Epoch [3946/4000] Training [15/16] Loss: 0.00200 +Epoch [3946/4000] Training [16/16] Loss: 0.00177 +Epoch [3946/4000] Training metric {'Train/mean dice_metric': 0.9988794326782227, 'Train/mean miou_metric': 0.9974693059921265, 'Train/mean f1': 0.993573009967804, 'Train/mean precision': 0.9887905120849609, 'Train/mean recall': 0.9984019994735718, 'Train/mean hd95_metric': 0.47698086500167847} +Epoch [3946/4000] Validation [1/4] Loss: 0.39871 focal_loss 0.33377 dice_loss 0.06494 +Epoch [3946/4000] Validation [2/4] Loss: 1.37309 focal_loss 1.09436 dice_loss 0.27873 +Epoch [3946/4000] Validation [3/4] Loss: 0.54087 focal_loss 0.44864 dice_loss 0.09223 +Epoch [3946/4000] Validation [4/4] Loss: 0.38788 focal_loss 0.29627 dice_loss 0.09161 +Epoch [3946/4000] Validation metric {'Val/mean dice_metric': 0.9727880358695984, 'Val/mean miou_metric': 0.9591394662857056, 'Val/mean f1': 0.9755097031593323, 'Val/mean precision': 0.9731332659721375, 'Val/mean recall': 0.9778978824615479, 'Val/mean hd95_metric': 4.9731879234313965} +Cheakpoint... +Epoch [3946/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727880358695984, 'Val/mean miou_metric': 0.9591394662857056, 'Val/mean f1': 0.9755097031593323, 'Val/mean precision': 0.9731332659721375, 'Val/mean recall': 0.9778978824615479, 'Val/mean hd95_metric': 4.9731879234313965} +Epoch [3947/4000] Training [1/16] Loss: 0.00245 +Epoch [3947/4000] Training [2/16] Loss: 0.00213 +Epoch [3947/4000] Training [3/16] Loss: 0.00556 +Epoch [3947/4000] Training [4/16] Loss: 0.00255 +Epoch [3947/4000] Training [5/16] Loss: 0.00171 +Epoch [3947/4000] Training [6/16] Loss: 0.00231 +Epoch [3947/4000] Training [7/16] Loss: 0.00235 +Epoch [3947/4000] Training [8/16] Loss: 0.00270 +Epoch [3947/4000] Training [9/16] Loss: 0.00222 +Epoch [3947/4000] Training [10/16] Loss: 0.00291 +Epoch [3947/4000] Training [11/16] Loss: 0.00219 +Epoch [3947/4000] Training [12/16] Loss: 0.00375 +Epoch [3947/4000] Training [13/16] Loss: 0.00171 +Epoch [3947/4000] Training [14/16] Loss: 0.00190 +Epoch [3947/4000] Training [15/16] Loss: 0.00188 +Epoch [3947/4000] Training [16/16] Loss: 0.00240 +Epoch [3947/4000] Training metric {'Train/mean dice_metric': 0.9987204074859619, 'Train/mean miou_metric': 0.9971612095832825, 'Train/mean f1': 0.9936052560806274, 'Train/mean precision': 0.9889597296714783, 'Train/mean recall': 0.9982945919036865, 'Train/mean hd95_metric': 0.5145789980888367} +Epoch [3947/4000] Validation [1/4] Loss: 0.36916 focal_loss 0.30530 dice_loss 0.06386 +Epoch [3947/4000] Validation [2/4] Loss: 0.64048 focal_loss 0.46908 dice_loss 0.17140 +Epoch [3947/4000] Validation [3/4] Loss: 0.52678 focal_loss 0.43652 dice_loss 0.09026 +Epoch [3947/4000] Validation [4/4] Loss: 0.35368 focal_loss 0.24495 dice_loss 0.10873 +Epoch [3947/4000] Validation metric {'Val/mean dice_metric': 0.9733726382255554, 'Val/mean miou_metric': 0.9595229029655457, 'Val/mean f1': 0.9759275913238525, 'Val/mean precision': 0.973577618598938, 'Val/mean recall': 0.978289008140564, 'Val/mean hd95_metric': 4.79849910736084} +Cheakpoint... +Epoch [3947/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733726382255554, 'Val/mean miou_metric': 0.9595229029655457, 'Val/mean f1': 0.9759275913238525, 'Val/mean precision': 0.973577618598938, 'Val/mean recall': 0.978289008140564, 'Val/mean hd95_metric': 4.79849910736084} +Epoch [3948/4000] Training [1/16] Loss: 0.00193 +Epoch [3948/4000] Training [2/16] Loss: 0.00292 +Epoch [3948/4000] Training [3/16] Loss: 0.00224 +Epoch [3948/4000] Training [4/16] Loss: 0.00235 +Epoch [3948/4000] Training [5/16] Loss: 0.00153 +Epoch [3948/4000] Training [6/16] Loss: 0.00184 +Epoch [3948/4000] Training [7/16] Loss: 0.00156 +Epoch [3948/4000] Training [8/16] Loss: 0.00268 +Epoch [3948/4000] Training [9/16] Loss: 0.00277 +Epoch [3948/4000] Training [10/16] Loss: 0.00244 +Epoch [3948/4000] Training [11/16] Loss: 0.00224 +Epoch [3948/4000] Training [12/16] Loss: 0.00143 +Epoch [3948/4000] Training [13/16] Loss: 0.00128 +Epoch [3948/4000] Training [14/16] Loss: 0.00197 +Epoch [3948/4000] Training [15/16] Loss: 0.00176 +Epoch [3948/4000] Training [16/16] Loss: 0.00194 +Epoch [3948/4000] Training metric {'Train/mean dice_metric': 0.9989302158355713, 'Train/mean miou_metric': 0.9975862503051758, 'Train/mean f1': 0.9938912987709045, 'Train/mean precision': 0.9893286228179932, 'Train/mean recall': 0.9984962344169617, 'Train/mean hd95_metric': 0.4725862741470337} +Epoch [3948/4000] Validation [1/4] Loss: 0.42571 focal_loss 0.36253 dice_loss 0.06319 +Epoch [3948/4000] Validation [2/4] Loss: 0.45173 focal_loss 0.34292 dice_loss 0.10881 +Epoch [3948/4000] Validation [3/4] Loss: 0.52568 focal_loss 0.43855 dice_loss 0.08713 +Epoch [3948/4000] Validation [4/4] Loss: 0.29776 focal_loss 0.21577 dice_loss 0.08199 +Epoch [3948/4000] Validation metric {'Val/mean dice_metric': 0.9756965637207031, 'Val/mean miou_metric': 0.9616152048110962, 'Val/mean f1': 0.9768841862678528, 'Val/mean precision': 0.974104642868042, 'Val/mean recall': 0.9796795845031738, 'Val/mean hd95_metric': 4.6353325843811035} +Cheakpoint... +Epoch [3948/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9757], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9756965637207031, 'Val/mean miou_metric': 0.9616152048110962, 'Val/mean f1': 0.9768841862678528, 'Val/mean precision': 0.974104642868042, 'Val/mean recall': 0.9796795845031738, 'Val/mean hd95_metric': 4.6353325843811035} +Epoch [3949/4000] Training [1/16] Loss: 0.00175 +Epoch [3949/4000] Training [2/16] Loss: 0.00219 +Epoch [3949/4000] Training [3/16] Loss: 0.00266 +Epoch [3949/4000] Training [4/16] Loss: 0.00257 +Epoch [3949/4000] Training [5/16] Loss: 0.00345 +Epoch [3949/4000] Training [6/16] Loss: 0.00172 +Epoch [3949/4000] Training [7/16] Loss: 0.00256 +Epoch [3949/4000] Training [8/16] Loss: 0.00232 +Epoch [3949/4000] Training [9/16] Loss: 0.00320 +Epoch [3949/4000] Training [10/16] Loss: 0.00364 +Epoch [3949/4000] Training [11/16] Loss: 0.00208 +Epoch [3949/4000] Training [12/16] Loss: 0.00309 +Epoch [3949/4000] Training [13/16] Loss: 0.00356 +Epoch [3949/4000] Training [14/16] Loss: 0.00224 +Epoch [3949/4000] Training [15/16] Loss: 0.00208 +Epoch [3949/4000] Training [16/16] Loss: 0.00300 +Epoch [3949/4000] Training metric {'Train/mean dice_metric': 0.9987100958824158, 'Train/mean miou_metric': 0.9971471428871155, 'Train/mean f1': 0.9937891364097595, 'Train/mean precision': 0.9892975687980652, 'Train/mean recall': 0.9983215928077698, 'Train/mean hd95_metric': 0.5577423572540283} +Epoch [3949/4000] Validation [1/4] Loss: 0.34787 focal_loss 0.28914 dice_loss 0.05873 +Epoch [3949/4000] Validation [2/4] Loss: 0.61517 focal_loss 0.45944 dice_loss 0.15573 +Epoch [3949/4000] Validation [3/4] Loss: 0.53198 focal_loss 0.44173 dice_loss 0.09025 +Epoch [3949/4000] Validation [4/4] Loss: 0.30799 focal_loss 0.22194 dice_loss 0.08605 +Epoch [3949/4000] Validation metric {'Val/mean dice_metric': 0.9739105105400085, 'Val/mean miou_metric': 0.9603300094604492, 'Val/mean f1': 0.9763980507850647, 'Val/mean precision': 0.9747841358184814, 'Val/mean recall': 0.9780173301696777, 'Val/mean hd95_metric': 4.8080949783325195} +Cheakpoint... +Epoch [3949/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9739105105400085, 'Val/mean miou_metric': 0.9603300094604492, 'Val/mean f1': 0.9763980507850647, 'Val/mean precision': 0.9747841358184814, 'Val/mean recall': 0.9780173301696777, 'Val/mean hd95_metric': 4.8080949783325195} +Epoch [3950/4000] Training [1/16] Loss: 0.00196 +Epoch [3950/4000] Training [2/16] Loss: 0.00267 +Epoch [3950/4000] Training [3/16] Loss: 0.00218 +Epoch [3950/4000] Training [4/16] Loss: 0.00208 +Epoch [3950/4000] Training [5/16] Loss: 0.00268 +Epoch [3950/4000] Training [6/16] Loss: 0.00207 +Epoch [3950/4000] Training [7/16] Loss: 0.00172 +Epoch [3950/4000] Training [8/16] Loss: 0.00296 +Epoch [3950/4000] Training [9/16] Loss: 0.00212 +Epoch [3950/4000] Training [10/16] Loss: 0.00339 +Epoch [3950/4000] Training [11/16] Loss: 0.00259 +Epoch [3950/4000] Training [12/16] Loss: 0.00277 +Epoch [3950/4000] Training [13/16] Loss: 0.00215 +Epoch [3950/4000] Training [14/16] Loss: 0.00170 +Epoch [3950/4000] Training [15/16] Loss: 0.00226 +Epoch [3950/4000] Training [16/16] Loss: 0.00189 +Epoch [3950/4000] Training metric {'Train/mean dice_metric': 0.998839259147644, 'Train/mean miou_metric': 0.9974026679992676, 'Train/mean f1': 0.9937825798988342, 'Train/mean precision': 0.9892292022705078, 'Train/mean recall': 0.9983780384063721, 'Train/mean hd95_metric': 0.5313330888748169} +Epoch [3950/4000] Validation [1/4] Loss: 0.36810 focal_loss 0.30925 dice_loss 0.05885 +Epoch [3950/4000] Validation [2/4] Loss: 0.62305 focal_loss 0.45320 dice_loss 0.16985 +Epoch [3950/4000] Validation [3/4] Loss: 0.54624 focal_loss 0.45070 dice_loss 0.09554 +Epoch [3950/4000] Validation [4/4] Loss: 0.36303 focal_loss 0.26907 dice_loss 0.09396 +Epoch [3950/4000] Validation metric {'Val/mean dice_metric': 0.97393798828125, 'Val/mean miou_metric': 0.9597681760787964, 'Val/mean f1': 0.9763035178184509, 'Val/mean precision': 0.9731058478355408, 'Val/mean recall': 0.9795223474502563, 'Val/mean hd95_metric': 5.147668838500977} +Cheakpoint... +Epoch [3950/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9739], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97393798828125, 'Val/mean miou_metric': 0.9597681760787964, 'Val/mean f1': 0.9763035178184509, 'Val/mean precision': 0.9731058478355408, 'Val/mean recall': 0.9795223474502563, 'Val/mean hd95_metric': 5.147668838500977} +Epoch [3951/4000] Training [1/16] Loss: 0.00199 +Epoch [3951/4000] Training [2/16] Loss: 0.00184 +Epoch [3951/4000] Training [3/16] Loss: 0.00223 +Epoch [3951/4000] Training [4/16] Loss: 0.00127 +Epoch [3951/4000] Training [5/16] Loss: 0.00328 +Epoch [3951/4000] Training [6/16] Loss: 0.00253 +Epoch [3951/4000] Training [7/16] Loss: 0.00271 +Epoch [3951/4000] Training [8/16] Loss: 0.00228 +Epoch [3951/4000] Training [9/16] Loss: 0.00219 +Epoch [3951/4000] Training [10/16] Loss: 0.00307 +Epoch [3951/4000] Training [11/16] Loss: 0.00287 +Epoch [3951/4000] Training [12/16] Loss: 0.00229 +Epoch [3951/4000] Training [13/16] Loss: 0.00303 +Epoch [3951/4000] Training [14/16] Loss: 0.00370 +Epoch [3951/4000] Training [15/16] Loss: 0.00338 +Epoch [3951/4000] Training [16/16] Loss: 0.00198 +Epoch [3951/4000] Training metric {'Train/mean dice_metric': 0.998780369758606, 'Train/mean miou_metric': 0.9972842931747437, 'Train/mean f1': 0.9937642812728882, 'Train/mean precision': 0.9891679883003235, 'Train/mean recall': 0.9984034895896912, 'Train/mean hd95_metric': 0.5310823917388916} +Epoch [3951/4000] Validation [1/4] Loss: 0.39451 focal_loss 0.33374 dice_loss 0.06077 +Epoch [3951/4000] Validation [2/4] Loss: 0.44946 focal_loss 0.34493 dice_loss 0.10453 +Epoch [3951/4000] Validation [3/4] Loss: 0.55391 focal_loss 0.46203 dice_loss 0.09188 +Epoch [3951/4000] Validation [4/4] Loss: 0.30208 focal_loss 0.21900 dice_loss 0.08308 +Epoch [3951/4000] Validation metric {'Val/mean dice_metric': 0.9760241508483887, 'Val/mean miou_metric': 0.9619272947311401, 'Val/mean f1': 0.9768199920654297, 'Val/mean precision': 0.9739370942115784, 'Val/mean recall': 0.9797199368476868, 'Val/mean hd95_metric': 5.05514669418335} +Cheakpoint... +Epoch [3951/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9760241508483887, 'Val/mean miou_metric': 0.9619272947311401, 'Val/mean f1': 0.9768199920654297, 'Val/mean precision': 0.9739370942115784, 'Val/mean recall': 0.9797199368476868, 'Val/mean hd95_metric': 5.05514669418335} +Epoch [3952/4000] Training [1/16] Loss: 0.00182 +Epoch [3952/4000] Training [2/16] Loss: 0.00290 +Epoch [3952/4000] Training [3/16] Loss: 0.00180 +Epoch [3952/4000] Training [4/16] Loss: 0.00224 +Epoch [3952/4000] Training [5/16] Loss: 0.00213 +Epoch [3952/4000] Training [6/16] Loss: 0.00189 +Epoch [3952/4000] Training [7/16] Loss: 0.00294 +Epoch [3952/4000] Training [8/16] Loss: 0.00214 +Epoch [3952/4000] Training [9/16] Loss: 0.00184 +Epoch [3952/4000] Training [10/16] Loss: 0.00220 +Epoch [3952/4000] Training [11/16] Loss: 0.00282 +Epoch [3952/4000] Training [12/16] Loss: 0.00280 +Epoch [3952/4000] Training [13/16] Loss: 0.00185 +Epoch [3952/4000] Training [14/16] Loss: 0.00200 +Epoch [3952/4000] Training [15/16] Loss: 0.00341 +Epoch [3952/4000] Training [16/16] Loss: 0.00227 +Epoch [3952/4000] Training metric {'Train/mean dice_metric': 0.9989113807678223, 'Train/mean miou_metric': 0.9975504875183105, 'Train/mean f1': 0.9939573407173157, 'Train/mean precision': 0.9894857406616211, 'Train/mean recall': 0.9984694719314575, 'Train/mean hd95_metric': 0.4662385582923889} +Epoch [3952/4000] Validation [1/4] Loss: 0.44284 focal_loss 0.37881 dice_loss 0.06403 +Epoch [3952/4000] Validation [2/4] Loss: 1.33313 focal_loss 1.05889 dice_loss 0.27424 +Epoch [3952/4000] Validation [3/4] Loss: 0.52402 focal_loss 0.43421 dice_loss 0.08981 +Epoch [3952/4000] Validation [4/4] Loss: 0.40878 focal_loss 0.29795 dice_loss 0.11083 +Epoch [3952/4000] Validation metric {'Val/mean dice_metric': 0.9730208516120911, 'Val/mean miou_metric': 0.9594570398330688, 'Val/mean f1': 0.976231575012207, 'Val/mean precision': 0.9738244414329529, 'Val/mean recall': 0.9786505699157715, 'Val/mean hd95_metric': 4.682728290557861} +Cheakpoint... +Epoch [3952/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9730], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730208516120911, 'Val/mean miou_metric': 0.9594570398330688, 'Val/mean f1': 0.976231575012207, 'Val/mean precision': 0.9738244414329529, 'Val/mean recall': 0.9786505699157715, 'Val/mean hd95_metric': 4.682728290557861} +Epoch [3953/4000] Training [1/16] Loss: 0.00274 +Epoch [3953/4000] Training [2/16] Loss: 0.00324 +Epoch [3953/4000] Training [3/16] Loss: 0.00213 +Epoch [3953/4000] Training [4/16] Loss: 0.00205 +Epoch [3953/4000] Training [5/16] Loss: 0.00153 +Epoch [3953/4000] Training [6/16] Loss: 0.00217 +Epoch [3953/4000] Training [7/16] Loss: 0.00215 +Epoch [3953/4000] Training [8/16] Loss: 0.00193 +Epoch [3953/4000] Training [9/16] Loss: 0.00234 +Epoch [3953/4000] Training [10/16] Loss: 0.00243 +Epoch [3953/4000] Training [11/16] Loss: 0.00357 +Epoch [3953/4000] Training [12/16] Loss: 0.00255 +Epoch [3953/4000] Training [13/16] Loss: 0.00318 +Epoch [3953/4000] Training [14/16] Loss: 0.00381 +Epoch [3953/4000] Training [15/16] Loss: 0.00249 +Epoch [3953/4000] Training [16/16] Loss: 0.00290 +Epoch [3953/4000] Training metric {'Train/mean dice_metric': 0.9987576603889465, 'Train/mean miou_metric': 0.997226357460022, 'Train/mean f1': 0.9935144186019897, 'Train/mean precision': 0.9887548089027405, 'Train/mean recall': 0.9983201026916504, 'Train/mean hd95_metric': 0.49070683121681213} +Epoch [3953/4000] Validation [1/4] Loss: 0.40910 focal_loss 0.34463 dice_loss 0.06447 +Epoch [3953/4000] Validation [2/4] Loss: 0.46911 focal_loss 0.36017 dice_loss 0.10894 +Epoch [3953/4000] Validation [3/4] Loss: 0.27494 focal_loss 0.21492 dice_loss 0.06002 +Epoch [3953/4000] Validation [4/4] Loss: 0.31101 focal_loss 0.22117 dice_loss 0.08983 +Epoch [3953/4000] Validation metric {'Val/mean dice_metric': 0.9755327105522156, 'Val/mean miou_metric': 0.9617151021957397, 'Val/mean f1': 0.9768409729003906, 'Val/mean precision': 0.9740082621574402, 'Val/mean recall': 0.9796903133392334, 'Val/mean hd95_metric': 4.635943412780762} +Cheakpoint... +Epoch [3953/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755327105522156, 'Val/mean miou_metric': 0.9617151021957397, 'Val/mean f1': 0.9768409729003906, 'Val/mean precision': 0.9740082621574402, 'Val/mean recall': 0.9796903133392334, 'Val/mean hd95_metric': 4.635943412780762} +Epoch [3954/4000] Training [1/16] Loss: 0.00240 +Epoch [3954/4000] Training [2/16] Loss: 0.00272 +Epoch [3954/4000] Training [3/16] Loss: 0.00278 +Epoch [3954/4000] Training [4/16] Loss: 0.00214 +Epoch [3954/4000] Training [5/16] Loss: 0.00206 +Epoch [3954/4000] Training [6/16] Loss: 0.00166 +Epoch [3954/4000] Training [7/16] Loss: 0.00228 +Epoch [3954/4000] Training [8/16] Loss: 0.00217 +Epoch [3954/4000] Training [9/16] Loss: 0.00168 +Epoch [3954/4000] Training [10/16] Loss: 0.00174 +Epoch [3954/4000] Training [11/16] Loss: 0.00256 +Epoch [3954/4000] Training [12/16] Loss: 0.00281 +Epoch [3954/4000] Training [13/16] Loss: 0.00412 +Epoch [3954/4000] Training [14/16] Loss: 0.00211 +Epoch [3954/4000] Training [15/16] Loss: 0.00316 +Epoch [3954/4000] Training [16/16] Loss: 0.00211 +Epoch [3954/4000] Training metric {'Train/mean dice_metric': 0.9987666606903076, 'Train/mean miou_metric': 0.9972233772277832, 'Train/mean f1': 0.9929087162017822, 'Train/mean precision': 0.9876135587692261, 'Train/mean recall': 0.9982609152793884, 'Train/mean hd95_metric': 0.5471969246864319} +Epoch [3954/4000] Validation [1/4] Loss: 0.35684 focal_loss 0.29890 dice_loss 0.05794 +Epoch [3954/4000] Validation [2/4] Loss: 0.46918 focal_loss 0.36014 dice_loss 0.10904 +Epoch [3954/4000] Validation [3/4] Loss: 0.53346 focal_loss 0.44155 dice_loss 0.09192 +Epoch [3954/4000] Validation [4/4] Loss: 0.41931 focal_loss 0.30699 dice_loss 0.11232 +Epoch [3954/4000] Validation metric {'Val/mean dice_metric': 0.974460244178772, 'Val/mean miou_metric': 0.9603139162063599, 'Val/mean f1': 0.9758276343345642, 'Val/mean precision': 0.9728649854660034, 'Val/mean recall': 0.978808581829071, 'Val/mean hd95_metric': 4.837808609008789} +Cheakpoint... +Epoch [3954/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974460244178772, 'Val/mean miou_metric': 0.9603139162063599, 'Val/mean f1': 0.9758276343345642, 'Val/mean precision': 0.9728649854660034, 'Val/mean recall': 0.978808581829071, 'Val/mean hd95_metric': 4.837808609008789} +Epoch [3955/4000] Training [1/16] Loss: 0.00264 +Epoch [3955/4000] Training [2/16] Loss: 0.00274 +Epoch [3955/4000] Training [3/16] Loss: 0.00274 +Epoch [3955/4000] Training [4/16] Loss: 0.00170 +Epoch [3955/4000] Training [5/16] Loss: 0.00194 +Epoch [3955/4000] Training [6/16] Loss: 0.00227 +Epoch [3955/4000] Training [7/16] Loss: 0.00345 +Epoch [3955/4000] Training [8/16] Loss: 0.00240 +Epoch [3955/4000] Training [9/16] Loss: 0.00184 +Epoch [3955/4000] Training [10/16] Loss: 0.00217 +Epoch [3955/4000] Training [11/16] Loss: 0.00190 +Epoch [3955/4000] Training [12/16] Loss: 0.00304 +Epoch [3955/4000] Training [13/16] Loss: 0.00167 +Epoch [3955/4000] Training [14/16] Loss: 0.00290 +Epoch [3955/4000] Training [15/16] Loss: 0.00170 +Epoch [3955/4000] Training [16/16] Loss: 0.00168 +Epoch [3955/4000] Training metric {'Train/mean dice_metric': 0.998873770236969, 'Train/mean miou_metric': 0.9974446296691895, 'Train/mean f1': 0.9934337139129639, 'Train/mean precision': 0.9885686039924622, 'Train/mean recall': 0.9983470439910889, 'Train/mean hd95_metric': 0.4893409013748169} +Epoch [3955/4000] Validation [1/4] Loss: 0.42169 focal_loss 0.35767 dice_loss 0.06402 +Epoch [3955/4000] Validation [2/4] Loss: 0.87280 focal_loss 0.67438 dice_loss 0.19842 +Epoch [3955/4000] Validation [3/4] Loss: 0.29617 focal_loss 0.23018 dice_loss 0.06599 +Epoch [3955/4000] Validation [4/4] Loss: 0.46820 focal_loss 0.35746 dice_loss 0.11074 +Epoch [3955/4000] Validation metric {'Val/mean dice_metric': 0.9738292694091797, 'Val/mean miou_metric': 0.9600923657417297, 'Val/mean f1': 0.9762234091758728, 'Val/mean precision': 0.9735694527626038, 'Val/mean recall': 0.978891909122467, 'Val/mean hd95_metric': 4.869058132171631} +Cheakpoint... +Epoch [3955/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9738], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9738292694091797, 'Val/mean miou_metric': 0.9600923657417297, 'Val/mean f1': 0.9762234091758728, 'Val/mean precision': 0.9735694527626038, 'Val/mean recall': 0.978891909122467, 'Val/mean hd95_metric': 4.869058132171631} +Epoch [3956/4000] Training [1/16] Loss: 0.00190 +Epoch [3956/4000] Training [2/16] Loss: 0.00271 +Epoch [3956/4000] Training [3/16] Loss: 0.00364 +Epoch [3956/4000] Training [4/16] Loss: 0.00207 +Epoch [3956/4000] Training [5/16] Loss: 0.00370 +Epoch [3956/4000] Training [6/16] Loss: 0.00177 +Epoch [3956/4000] Training [7/16] Loss: 0.00328 +Epoch [3956/4000] Training [8/16] Loss: 0.00199 +Epoch [3956/4000] Training [9/16] Loss: 0.00251 +Epoch [3956/4000] Training [10/16] Loss: 0.00221 +Epoch [3956/4000] Training [11/16] Loss: 0.00191 +Epoch [3956/4000] Training [12/16] Loss: 0.00215 +Epoch [3956/4000] Training [13/16] Loss: 0.00246 +Epoch [3956/4000] Training [14/16] Loss: 0.00247 +Epoch [3956/4000] Training [15/16] Loss: 0.00251 +Epoch [3956/4000] Training [16/16] Loss: 0.00177 +Epoch [3956/4000] Training metric {'Train/mean dice_metric': 0.9988294839859009, 'Train/mean miou_metric': 0.997382640838623, 'Train/mean f1': 0.9938362240791321, 'Train/mean precision': 0.9893273115158081, 'Train/mean recall': 0.9983863830566406, 'Train/mean hd95_metric': 0.5000553131103516} +Epoch [3956/4000] Validation [1/4] Loss: 0.41521 focal_loss 0.35252 dice_loss 0.06269 +Epoch [3956/4000] Validation [2/4] Loss: 0.95181 focal_loss 0.76555 dice_loss 0.18626 +Epoch [3956/4000] Validation [3/4] Loss: 0.54354 focal_loss 0.44895 dice_loss 0.09459 +Epoch [3956/4000] Validation [4/4] Loss: 0.54787 focal_loss 0.41792 dice_loss 0.12995 +Epoch [3956/4000] Validation metric {'Val/mean dice_metric': 0.9735223054885864, 'Val/mean miou_metric': 0.9598264694213867, 'Val/mean f1': 0.9764251112937927, 'Val/mean precision': 0.9739195108413696, 'Val/mean recall': 0.9789437651634216, 'Val/mean hd95_metric': 5.053896903991699} +Cheakpoint... +Epoch [3956/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9735223054885864, 'Val/mean miou_metric': 0.9598264694213867, 'Val/mean f1': 0.9764251112937927, 'Val/mean precision': 0.9739195108413696, 'Val/mean recall': 0.9789437651634216, 'Val/mean hd95_metric': 5.053896903991699} +Epoch [3957/4000] Training [1/16] Loss: 0.00328 +Epoch [3957/4000] Training [2/16] Loss: 0.00285 +Epoch [3957/4000] Training [3/16] Loss: 0.00278 +Epoch [3957/4000] Training [4/16] Loss: 0.00268 +Epoch [3957/4000] Training [5/16] Loss: 0.00153 +Epoch [3957/4000] Training [6/16] Loss: 0.00285 +Epoch [3957/4000] Training [7/16] Loss: 0.00188 +Epoch [3957/4000] Training [8/16] Loss: 0.00285 +Epoch [3957/4000] Training [9/16] Loss: 0.00167 +Epoch [3957/4000] Training [10/16] Loss: 0.00250 +Epoch [3957/4000] Training [11/16] Loss: 0.00228 +Epoch [3957/4000] Training [12/16] Loss: 0.00157 +Epoch [3957/4000] Training [13/16] Loss: 0.00298 +Epoch [3957/4000] Training [14/16] Loss: 0.00164 +Epoch [3957/4000] Training [15/16] Loss: 0.00156 +Epoch [3957/4000] Training [16/16] Loss: 0.00246 +Epoch [3957/4000] Training metric {'Train/mean dice_metric': 0.9988282918930054, 'Train/mean miou_metric': 0.997372567653656, 'Train/mean f1': 0.9935867786407471, 'Train/mean precision': 0.9888455271720886, 'Train/mean recall': 0.9983737468719482, 'Train/mean hd95_metric': 0.5260041952133179} +Epoch [3957/4000] Validation [1/4] Loss: 0.41299 focal_loss 0.35010 dice_loss 0.06289 +Epoch [3957/4000] Validation [2/4] Loss: 0.52962 focal_loss 0.39771 dice_loss 0.13191 +Epoch [3957/4000] Validation [3/4] Loss: 0.55158 focal_loss 0.45754 dice_loss 0.09404 +Epoch [3957/4000] Validation [4/4] Loss: 0.38018 focal_loss 0.28438 dice_loss 0.09580 +Epoch [3957/4000] Validation metric {'Val/mean dice_metric': 0.9745414853096008, 'Val/mean miou_metric': 0.960247814655304, 'Val/mean f1': 0.9760888814926147, 'Val/mean precision': 0.9735991954803467, 'Val/mean recall': 0.97859126329422, 'Val/mean hd95_metric': 4.755982398986816} +Cheakpoint... +Epoch [3957/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745414853096008, 'Val/mean miou_metric': 0.960247814655304, 'Val/mean f1': 0.9760888814926147, 'Val/mean precision': 0.9735991954803467, 'Val/mean recall': 0.97859126329422, 'Val/mean hd95_metric': 4.755982398986816} +Epoch [3958/4000] Training [1/16] Loss: 0.00230 +Epoch [3958/4000] Training [2/16] Loss: 0.00255 +Epoch [3958/4000] Training [3/16] Loss: 0.00275 +Epoch [3958/4000] Training [4/16] Loss: 0.00216 +Epoch [3958/4000] Training [5/16] Loss: 0.00365 +Epoch [3958/4000] Training [6/16] Loss: 0.00308 +Epoch [3958/4000] Training [7/16] Loss: 0.00328 +Epoch [3958/4000] Training [8/16] Loss: 0.00215 +Epoch [3958/4000] Training [9/16] Loss: 0.00263 +Epoch [3958/4000] Training [10/16] Loss: 0.00185 +Epoch [3958/4000] Training [11/16] Loss: 0.00126 +Epoch [3958/4000] Training [12/16] Loss: 0.00363 +Epoch [3958/4000] Training [13/16] Loss: 0.00254 +Epoch [3958/4000] Training [14/16] Loss: 0.00216 +Epoch [3958/4000] Training [15/16] Loss: 0.00287 +Epoch [3958/4000] Training [16/16] Loss: 0.00231 +Epoch [3958/4000] Training metric {'Train/mean dice_metric': 0.9988034963607788, 'Train/mean miou_metric': 0.9973345994949341, 'Train/mean f1': 0.9937882423400879, 'Train/mean precision': 0.9892346858978271, 'Train/mean recall': 0.9983838796615601, 'Train/mean hd95_metric': 0.5009063482284546} +Epoch [3958/4000] Validation [1/4] Loss: 0.42085 focal_loss 0.35667 dice_loss 0.06418 +Epoch [3958/4000] Validation [2/4] Loss: 1.11801 focal_loss 0.90716 dice_loss 0.21085 +Epoch [3958/4000] Validation [3/4] Loss: 0.52649 focal_loss 0.43426 dice_loss 0.09223 +Epoch [3958/4000] Validation [4/4] Loss: 0.45957 focal_loss 0.35036 dice_loss 0.10921 +Epoch [3958/4000] Validation metric {'Val/mean dice_metric': 0.9733774065971375, 'Val/mean miou_metric': 0.9596823453903198, 'Val/mean f1': 0.9759512543678284, 'Val/mean precision': 0.9731190800666809, 'Val/mean recall': 0.9788000583648682, 'Val/mean hd95_metric': 4.6400861740112305} +Cheakpoint... +Epoch [3958/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733774065971375, 'Val/mean miou_metric': 0.9596823453903198, 'Val/mean f1': 0.9759512543678284, 'Val/mean precision': 0.9731190800666809, 'Val/mean recall': 0.9788000583648682, 'Val/mean hd95_metric': 4.6400861740112305} +Epoch [3959/4000] Training [1/16] Loss: 0.00173 +Epoch [3959/4000] Training [2/16] Loss: 0.00192 +Epoch [3959/4000] Training [3/16] Loss: 0.00238 +Epoch [3959/4000] Training [4/16] Loss: 0.00204 +Epoch [3959/4000] Training [5/16] Loss: 0.00217 +Epoch [3959/4000] Training [6/16] Loss: 0.00216 +Epoch [3959/4000] Training [7/16] Loss: 0.00363 +Epoch [3959/4000] Training [8/16] Loss: 0.00235 +Epoch [3959/4000] Training [9/16] Loss: 0.00193 +Epoch [3959/4000] Training [10/16] Loss: 0.00374 +Epoch [3959/4000] Training [11/16] Loss: 0.00255 +Epoch [3959/4000] Training [12/16] Loss: 0.00267 +Epoch [3959/4000] Training [13/16] Loss: 0.00277 +Epoch [3959/4000] Training [14/16] Loss: 0.00225 +Epoch [3959/4000] Training [15/16] Loss: 0.00187 +Epoch [3959/4000] Training [16/16] Loss: 0.00272 +Epoch [3959/4000] Training metric {'Train/mean dice_metric': 0.9987658262252808, 'Train/mean miou_metric': 0.9972585439682007, 'Train/mean f1': 0.9937945604324341, 'Train/mean precision': 0.9892370104789734, 'Train/mean recall': 0.998394250869751, 'Train/mean hd95_metric': 0.4895781874656677} +Epoch [3959/4000] Validation [1/4] Loss: 0.39165 focal_loss 0.32943 dice_loss 0.06222 +Epoch [3959/4000] Validation [2/4] Loss: 0.58345 focal_loss 0.43556 dice_loss 0.14790 +Epoch [3959/4000] Validation [3/4] Loss: 0.29386 focal_loss 0.22663 dice_loss 0.06724 +Epoch [3959/4000] Validation [4/4] Loss: 0.50098 focal_loss 0.39135 dice_loss 0.10963 +Epoch [3959/4000] Validation metric {'Val/mean dice_metric': 0.9747486114501953, 'Val/mean miou_metric': 0.9608345031738281, 'Val/mean f1': 0.976621687412262, 'Val/mean precision': 0.9744309186935425, 'Val/mean recall': 0.9788222908973694, 'Val/mean hd95_metric': 4.7078070640563965} +Cheakpoint... +Epoch [3959/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747486114501953, 'Val/mean miou_metric': 0.9608345031738281, 'Val/mean f1': 0.976621687412262, 'Val/mean precision': 0.9744309186935425, 'Val/mean recall': 0.9788222908973694, 'Val/mean hd95_metric': 4.7078070640563965} +Epoch [3960/4000] Training [1/16] Loss: 0.00213 +Epoch [3960/4000] Training [2/16] Loss: 0.00283 +Epoch [3960/4000] Training [3/16] Loss: 0.00218 +Epoch [3960/4000] Training [4/16] Loss: 0.00210 +Epoch [3960/4000] Training [5/16] Loss: 0.00251 +Epoch [3960/4000] Training [6/16] Loss: 0.00302 +Epoch [3960/4000] Training [7/16] Loss: 0.00310 +Epoch [3960/4000] Training [8/16] Loss: 0.02553 +Epoch [3960/4000] Training [9/16] Loss: 0.00194 +Epoch [3960/4000] Training [10/16] Loss: 0.00151 +Epoch [3960/4000] Training [11/16] Loss: 0.00245 +Epoch [3960/4000] Training [12/16] Loss: 0.00181 +Epoch [3960/4000] Training [13/16] Loss: 0.00302 +Epoch [3960/4000] Training [14/16] Loss: 0.00268 +Epoch [3960/4000] Training [15/16] Loss: 0.00351 +Epoch [3960/4000] Training [16/16] Loss: 0.00223 +Epoch [3960/4000] Training metric {'Train/mean dice_metric': 0.9983828067779541, 'Train/mean miou_metric': 0.9965187907218933, 'Train/mean f1': 0.9934180974960327, 'Train/mean precision': 0.9887129664421082, 'Train/mean recall': 0.9981682300567627, 'Train/mean hd95_metric': 0.7144159078598022} +Epoch [3960/4000] Validation [1/4] Loss: 0.41443 focal_loss 0.35323 dice_loss 0.06120 +Epoch [3960/4000] Validation [2/4] Loss: 0.49030 focal_loss 0.37591 dice_loss 0.11439 +Epoch [3960/4000] Validation [3/4] Loss: 0.55116 focal_loss 0.45933 dice_loss 0.09183 +Epoch [3960/4000] Validation [4/4] Loss: 0.34735 focal_loss 0.25120 dice_loss 0.09615 +Epoch [3960/4000] Validation metric {'Val/mean dice_metric': 0.9725131988525391, 'Val/mean miou_metric': 0.9580747485160828, 'Val/mean f1': 0.975790798664093, 'Val/mean precision': 0.973183810710907, 'Val/mean recall': 0.9784119129180908, 'Val/mean hd95_metric': 5.320434093475342} +Cheakpoint... +Epoch [3960/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9725], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9725131988525391, 'Val/mean miou_metric': 0.9580747485160828, 'Val/mean f1': 0.975790798664093, 'Val/mean precision': 0.973183810710907, 'Val/mean recall': 0.9784119129180908, 'Val/mean hd95_metric': 5.320434093475342} +Epoch [3961/4000] Training [1/16] Loss: 0.00228 +Epoch [3961/4000] Training [2/16] Loss: 0.00271 +Epoch [3961/4000] Training [3/16] Loss: 0.00178 +Epoch [3961/4000] Training [4/16] Loss: 0.00286 +Epoch [3961/4000] Training [5/16] Loss: 0.00163 +Epoch [3961/4000] Training [6/16] Loss: 0.00193 +Epoch [3961/4000] Training [7/16] Loss: 0.00198 +Epoch [3961/4000] Training [8/16] Loss: 0.00405 +Epoch [3961/4000] Training [9/16] Loss: 0.00231 +Epoch [3961/4000] Training [10/16] Loss: 0.00169 +Epoch [3961/4000] Training [11/16] Loss: 0.00258 +Epoch [3961/4000] Training [12/16] Loss: 0.00192 +Epoch [3961/4000] Training [13/16] Loss: 0.00268 +Epoch [3961/4000] Training [14/16] Loss: 0.00252 +Epoch [3961/4000] Training [15/16] Loss: 0.00259 +Epoch [3961/4000] Training [16/16] Loss: 0.00232 +Epoch [3961/4000] Training metric {'Train/mean dice_metric': 0.9987980127334595, 'Train/mean miou_metric': 0.997321605682373, 'Train/mean f1': 0.9938843250274658, 'Train/mean precision': 0.9893877506256104, 'Train/mean recall': 0.9984219670295715, 'Train/mean hd95_metric': 0.5341372489929199} +Epoch [3961/4000] Validation [1/4] Loss: 0.36750 focal_loss 0.30595 dice_loss 0.06154 +Epoch [3961/4000] Validation [2/4] Loss: 0.90485 focal_loss 0.70410 dice_loss 0.20075 +Epoch [3961/4000] Validation [3/4] Loss: 0.54851 focal_loss 0.45265 dice_loss 0.09586 +Epoch [3961/4000] Validation [4/4] Loss: 0.33127 focal_loss 0.24416 dice_loss 0.08711 +Epoch [3961/4000] Validation metric {'Val/mean dice_metric': 0.9727237820625305, 'Val/mean miou_metric': 0.958840012550354, 'Val/mean f1': 0.9759514927864075, 'Val/mean precision': 0.9743067622184753, 'Val/mean recall': 0.9776018261909485, 'Val/mean hd95_metric': 4.984984874725342} +Cheakpoint... +Epoch [3961/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727237820625305, 'Val/mean miou_metric': 0.958840012550354, 'Val/mean f1': 0.9759514927864075, 'Val/mean precision': 0.9743067622184753, 'Val/mean recall': 0.9776018261909485, 'Val/mean hd95_metric': 4.984984874725342} +Epoch [3962/4000] Training [1/16] Loss: 0.00239 +Epoch [3962/4000] Training [2/16] Loss: 0.00188 +Epoch [3962/4000] Training [3/16] Loss: 0.00184 +Epoch [3962/4000] Training [4/16] Loss: 0.00265 +Epoch [3962/4000] Training [5/16] Loss: 0.00198 +Epoch [3962/4000] Training [6/16] Loss: 0.00209 +Epoch [3962/4000] Training [7/16] Loss: 0.00239 +Epoch [3962/4000] Training [8/16] Loss: 0.00255 +Epoch [3962/4000] Training [9/16] Loss: 0.00253 +Epoch [3962/4000] Training [10/16] Loss: 0.00277 +Epoch [3962/4000] Training [11/16] Loss: 0.00207 +Epoch [3962/4000] Training [12/16] Loss: 0.00315 +Epoch [3962/4000] Training [13/16] Loss: 0.00211 +Epoch [3962/4000] Training [14/16] Loss: 0.00229 +Epoch [3962/4000] Training [15/16] Loss: 0.00279 +Epoch [3962/4000] Training [16/16] Loss: 0.00248 +Epoch [3962/4000] Training metric {'Train/mean dice_metric': 0.9988950490951538, 'Train/mean miou_metric': 0.9975156784057617, 'Train/mean f1': 0.9939063787460327, 'Train/mean precision': 0.9893820285797119, 'Train/mean recall': 0.998472273349762, 'Train/mean hd95_metric': 0.5102816224098206} +Epoch [3962/4000] Validation [1/4] Loss: 0.42346 focal_loss 0.35822 dice_loss 0.06524 +Epoch [3962/4000] Validation [2/4] Loss: 0.95590 focal_loss 0.76765 dice_loss 0.18826 +Epoch [3962/4000] Validation [3/4] Loss: 0.54500 focal_loss 0.44870 dice_loss 0.09630 +Epoch [3962/4000] Validation [4/4] Loss: 0.42818 focal_loss 0.32147 dice_loss 0.10671 +Epoch [3962/4000] Validation metric {'Val/mean dice_metric': 0.9755350351333618, 'Val/mean miou_metric': 0.9618663787841797, 'Val/mean f1': 0.9765785932540894, 'Val/mean precision': 0.973962664604187, 'Val/mean recall': 0.9792085289955139, 'Val/mean hd95_metric': 4.6604790687561035} +Cheakpoint... +Epoch [3962/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9755], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9755350351333618, 'Val/mean miou_metric': 0.9618663787841797, 'Val/mean f1': 0.9765785932540894, 'Val/mean precision': 0.973962664604187, 'Val/mean recall': 0.9792085289955139, 'Val/mean hd95_metric': 4.6604790687561035} +Epoch [3963/4000] Training [1/16] Loss: 0.00166 +Epoch [3963/4000] Training [2/16] Loss: 0.00309 +Epoch [3963/4000] Training [3/16] Loss: 0.00243 +Epoch [3963/4000] Training [4/16] Loss: 0.00412 +Epoch [3963/4000] Training [5/16] Loss: 0.00215 +Epoch [3963/4000] Training [6/16] Loss: 0.00185 +Epoch [3963/4000] Training [7/16] Loss: 0.00180 +Epoch [3963/4000] Training [8/16] Loss: 0.00135 +Epoch [3963/4000] Training [9/16] Loss: 0.00259 +Epoch [3963/4000] Training [10/16] Loss: 0.00151 +Epoch [3963/4000] Training [11/16] Loss: 0.00264 +Epoch [3963/4000] Training [12/16] Loss: 0.00223 +Epoch [3963/4000] Training [13/16] Loss: 0.00226 +Epoch [3963/4000] Training [14/16] Loss: 0.00350 +Epoch [3963/4000] Training [15/16] Loss: 0.00221 +Epoch [3963/4000] Training [16/16] Loss: 0.00175 +Epoch [3963/4000] Training metric {'Train/mean dice_metric': 0.998814582824707, 'Train/mean miou_metric': 0.9973559975624084, 'Train/mean f1': 0.9938735365867615, 'Train/mean precision': 0.9893987774848938, 'Train/mean recall': 0.998388946056366, 'Train/mean hd95_metric': 0.49338698387145996} +Epoch [3963/4000] Validation [1/4] Loss: 0.39042 focal_loss 0.32757 dice_loss 0.06285 +Epoch [3963/4000] Validation [2/4] Loss: 1.00293 focal_loss 0.76552 dice_loss 0.23741 +Epoch [3963/4000] Validation [3/4] Loss: 0.52733 focal_loss 0.43107 dice_loss 0.09627 +Epoch [3963/4000] Validation [4/4] Loss: 0.38238 focal_loss 0.28862 dice_loss 0.09377 +Epoch [3963/4000] Validation metric {'Val/mean dice_metric': 0.9731875658035278, 'Val/mean miou_metric': 0.9591673016548157, 'Val/mean f1': 0.9762506484985352, 'Val/mean precision': 0.9741209745407104, 'Val/mean recall': 0.9783898591995239, 'Val/mean hd95_metric': 4.805140495300293} +Cheakpoint... +Epoch [3963/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9732], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9731875658035278, 'Val/mean miou_metric': 0.9591673016548157, 'Val/mean f1': 0.9762506484985352, 'Val/mean precision': 0.9741209745407104, 'Val/mean recall': 0.9783898591995239, 'Val/mean hd95_metric': 4.805140495300293} +Epoch [3964/4000] Training [1/16] Loss: 0.00257 +Epoch [3964/4000] Training [2/16] Loss: 0.00229 +Epoch [3964/4000] Training [3/16] Loss: 0.00179 +Epoch [3964/4000] Training [4/16] Loss: 0.00270 +Epoch [3964/4000] Training [5/16] Loss: 0.00212 +Epoch [3964/4000] Training [6/16] Loss: 0.00295 +Epoch [3964/4000] Training [7/16] Loss: 0.00190 +Epoch [3964/4000] Training [8/16] Loss: 0.00235 +Epoch [3964/4000] Training [9/16] Loss: 0.00268 +Epoch [3964/4000] Training [10/16] Loss: 0.00270 +Epoch [3964/4000] Training [11/16] Loss: 0.00229 +Epoch [3964/4000] Training [12/16] Loss: 0.00237 +Epoch [3964/4000] Training [13/16] Loss: 0.00276 +Epoch [3964/4000] Training [14/16] Loss: 0.00208 +Epoch [3964/4000] Training [15/16] Loss: 0.00145 +Epoch [3964/4000] Training [16/16] Loss: 0.00270 +Epoch [3964/4000] Training metric {'Train/mean dice_metric': 0.9987893104553223, 'Train/mean miou_metric': 0.9973021745681763, 'Train/mean f1': 0.9937520027160645, 'Train/mean precision': 0.9891975522041321, 'Train/mean recall': 0.9983486533164978, 'Train/mean hd95_metric': 0.5218325853347778} +Epoch [3964/4000] Validation [1/4] Loss: 0.43657 focal_loss 0.37194 dice_loss 0.06463 +Epoch [3964/4000] Validation [2/4] Loss: 0.48535 focal_loss 0.37242 dice_loss 0.11292 +Epoch [3964/4000] Validation [3/4] Loss: 0.56941 focal_loss 0.47864 dice_loss 0.09077 +Epoch [3964/4000] Validation [4/4] Loss: 0.40888 focal_loss 0.30147 dice_loss 0.10741 +Epoch [3964/4000] Validation metric {'Val/mean dice_metric': 0.9746015667915344, 'Val/mean miou_metric': 0.9604889154434204, 'Val/mean f1': 0.9764654636383057, 'Val/mean precision': 0.9737261533737183, 'Val/mean recall': 0.9792203307151794, 'Val/mean hd95_metric': 5.064733028411865} +Cheakpoint... +Epoch [3964/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9746], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746015667915344, 'Val/mean miou_metric': 0.9604889154434204, 'Val/mean f1': 0.9764654636383057, 'Val/mean precision': 0.9737261533737183, 'Val/mean recall': 0.9792203307151794, 'Val/mean hd95_metric': 5.064733028411865} +Epoch [3965/4000] Training [1/16] Loss: 0.00298 +Epoch [3965/4000] Training [2/16] Loss: 0.00261 +Epoch [3965/4000] Training [3/16] Loss: 0.00175 +Epoch [3965/4000] Training [4/16] Loss: 0.00274 +Epoch [3965/4000] Training [5/16] Loss: 0.00195 +Epoch [3965/4000] Training [6/16] Loss: 0.00157 +Epoch [3965/4000] Training [7/16] Loss: 0.00157 +Epoch [3965/4000] Training [8/16] Loss: 0.00463 +Epoch [3965/4000] Training [9/16] Loss: 0.00211 +Epoch [3965/4000] Training [10/16] Loss: 0.00131 +Epoch [3965/4000] Training [11/16] Loss: 0.00300 +Epoch [3965/4000] Training [12/16] Loss: 0.00304 +Epoch [3965/4000] Training [13/16] Loss: 0.00290 +Epoch [3965/4000] Training [14/16] Loss: 0.00316 +Epoch [3965/4000] Training [15/16] Loss: 0.00200 +Epoch [3965/4000] Training [16/16] Loss: 0.00187 +Epoch [3965/4000] Training metric {'Train/mean dice_metric': 0.9987784624099731, 'Train/mean miou_metric': 0.9972782135009766, 'Train/mean f1': 0.9936658143997192, 'Train/mean precision': 0.9890403151512146, 'Train/mean recall': 0.9983347654342651, 'Train/mean hd95_metric': 0.5182569026947021} +Epoch [3965/4000] Validation [1/4] Loss: 0.41662 focal_loss 0.35352 dice_loss 0.06310 +Epoch [3965/4000] Validation [2/4] Loss: 0.46271 focal_loss 0.35371 dice_loss 0.10900 +Epoch [3965/4000] Validation [3/4] Loss: 0.48268 focal_loss 0.39198 dice_loss 0.09070 +Epoch [3965/4000] Validation [4/4] Loss: 0.38865 focal_loss 0.28806 dice_loss 0.10059 +Epoch [3965/4000] Validation metric {'Val/mean dice_metric': 0.9750804901123047, 'Val/mean miou_metric': 0.9612215161323547, 'Val/mean f1': 0.9765334129333496, 'Val/mean precision': 0.9735238552093506, 'Val/mean recall': 0.9795615077018738, 'Val/mean hd95_metric': 4.613585472106934} +Cheakpoint... +Epoch [3965/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750804901123047, 'Val/mean miou_metric': 0.9612215161323547, 'Val/mean f1': 0.9765334129333496, 'Val/mean precision': 0.9735238552093506, 'Val/mean recall': 0.9795615077018738, 'Val/mean hd95_metric': 4.613585472106934} +Epoch [3966/4000] Training [1/16] Loss: 0.00220 +Epoch [3966/4000] Training [2/16] Loss: 0.00489 +Epoch [3966/4000] Training [3/16] Loss: 0.00138 +Epoch [3966/4000] Training [4/16] Loss: 0.00342 +Epoch [3966/4000] Training [5/16] Loss: 0.00318 +Epoch [3966/4000] Training [6/16] Loss: 0.00263 +Epoch [3966/4000] Training [7/16] Loss: 0.00213 +Epoch [3966/4000] Training [8/16] Loss: 0.00166 +Epoch [3966/4000] Training [9/16] Loss: 0.00260 +Epoch [3966/4000] Training [10/16] Loss: 0.00203 +Epoch [3966/4000] Training [11/16] Loss: 0.00246 +Epoch [3966/4000] Training [12/16] Loss: 0.00261 +Epoch [3966/4000] Training [13/16] Loss: 0.00431 +Epoch [3966/4000] Training [14/16] Loss: 0.00282 +Epoch [3966/4000] Training [15/16] Loss: 0.00230 +Epoch [3966/4000] Training [16/16] Loss: 0.00202 +Epoch [3966/4000] Training metric {'Train/mean dice_metric': 0.9987574219703674, 'Train/mean miou_metric': 0.9972425699234009, 'Train/mean f1': 0.9938259720802307, 'Train/mean precision': 0.9893085956573486, 'Train/mean recall': 0.9983848333358765, 'Train/mean hd95_metric': 0.492828905582428} +Epoch [3966/4000] Validation [1/4] Loss: 0.37694 focal_loss 0.31740 dice_loss 0.05954 +Epoch [3966/4000] Validation [2/4] Loss: 0.95636 focal_loss 0.76681 dice_loss 0.18955 +Epoch [3966/4000] Validation [3/4] Loss: 0.53343 focal_loss 0.44284 dice_loss 0.09059 +Epoch [3966/4000] Validation [4/4] Loss: 0.38488 focal_loss 0.29573 dice_loss 0.08915 +Epoch [3966/4000] Validation metric {'Val/mean dice_metric': 0.9750128984451294, 'Val/mean miou_metric': 0.9612841606140137, 'Val/mean f1': 0.9770075082778931, 'Val/mean precision': 0.9745974540710449, 'Val/mean recall': 0.9794294834136963, 'Val/mean hd95_metric': 4.574310302734375} +Cheakpoint... +Epoch [3966/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9750128984451294, 'Val/mean miou_metric': 0.9612841606140137, 'Val/mean f1': 0.9770075082778931, 'Val/mean precision': 0.9745974540710449, 'Val/mean recall': 0.9794294834136963, 'Val/mean hd95_metric': 4.574310302734375} +Epoch [3967/4000] Training [1/16] Loss: 0.00358 +Epoch [3967/4000] Training [2/16] Loss: 0.00218 +Epoch [3967/4000] Training [3/16] Loss: 0.00202 +Epoch [3967/4000] Training [4/16] Loss: 0.00289 +Epoch [3967/4000] Training [5/16] Loss: 0.00205 +Epoch [3967/4000] Training [6/16] Loss: 0.00426 +Epoch [3967/4000] Training [7/16] Loss: 0.00200 +Epoch [3967/4000] Training [8/16] Loss: 0.00237 +Epoch [3967/4000] Training [9/16] Loss: 0.00208 +Epoch [3967/4000] Training [10/16] Loss: 0.00247 +Epoch [3967/4000] Training [11/16] Loss: 0.00322 +Epoch [3967/4000] Training [12/16] Loss: 0.00297 +Epoch [3967/4000] Training [13/16] Loss: 0.00178 +Epoch [3967/4000] Training [14/16] Loss: 0.00227 +Epoch [3967/4000] Training [15/16] Loss: 0.00171 +Epoch [3967/4000] Training [16/16] Loss: 0.00165 +Epoch [3967/4000] Training metric {'Train/mean dice_metric': 0.9988147020339966, 'Train/mean miou_metric': 0.9973284006118774, 'Train/mean f1': 0.9933435916900635, 'Train/mean precision': 0.9883332252502441, 'Train/mean recall': 0.9984049797058105, 'Train/mean hd95_metric': 0.4959259629249573} +Epoch [3967/4000] Validation [1/4] Loss: 0.44016 focal_loss 0.37717 dice_loss 0.06299 +Epoch [3967/4000] Validation [2/4] Loss: 0.88323 focal_loss 0.68569 dice_loss 0.19754 +Epoch [3967/4000] Validation [3/4] Loss: 0.53253 focal_loss 0.43728 dice_loss 0.09526 +Epoch [3967/4000] Validation [4/4] Loss: 0.36632 focal_loss 0.27740 dice_loss 0.08892 +Epoch [3967/4000] Validation metric {'Val/mean dice_metric': 0.9737359285354614, 'Val/mean miou_metric': 0.9596913456916809, 'Val/mean f1': 0.9760012030601501, 'Val/mean precision': 0.9731041193008423, 'Val/mean recall': 0.9789155125617981, 'Val/mean hd95_metric': 5.051198482513428} +Cheakpoint... +Epoch [3967/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9737359285354614, 'Val/mean miou_metric': 0.9596913456916809, 'Val/mean f1': 0.9760012030601501, 'Val/mean precision': 0.9731041193008423, 'Val/mean recall': 0.9789155125617981, 'Val/mean hd95_metric': 5.051198482513428} +Epoch [3968/4000] Training [1/16] Loss: 0.00187 +Epoch [3968/4000] Training [2/16] Loss: 0.00161 +Epoch [3968/4000] Training [3/16] Loss: 0.00261 +Epoch [3968/4000] Training [4/16] Loss: 0.00204 +Epoch [3968/4000] Training [5/16] Loss: 0.00279 +Epoch [3968/4000] Training [6/16] Loss: 0.00249 +Epoch [3968/4000] Training [7/16] Loss: 0.00276 +Epoch [3968/4000] Training [8/16] Loss: 0.00291 +Epoch [3968/4000] Training [9/16] Loss: 0.00242 +Epoch [3968/4000] Training [10/16] Loss: 0.00479 +Epoch [3968/4000] Training [11/16] Loss: 0.00171 +Epoch [3968/4000] Training [12/16] Loss: 0.00245 +Epoch [3968/4000] Training [13/16] Loss: 0.00278 +Epoch [3968/4000] Training [14/16] Loss: 0.00199 +Epoch [3968/4000] Training [15/16] Loss: 0.00229 +Epoch [3968/4000] Training [16/16] Loss: 0.00207 +Epoch [3968/4000] Training metric {'Train/mean dice_metric': 0.9987941980361938, 'Train/mean miou_metric': 0.9972931146621704, 'Train/mean f1': 0.9935068488121033, 'Train/mean precision': 0.9887391328811646, 'Train/mean recall': 0.9983207583427429, 'Train/mean hd95_metric': 0.5279293060302734} +Epoch [3968/4000] Validation [1/4] Loss: 0.41726 focal_loss 0.35294 dice_loss 0.06433 +Epoch [3968/4000] Validation [2/4] Loss: 0.94492 focal_loss 0.75821 dice_loss 0.18671 +Epoch [3968/4000] Validation [3/4] Loss: 0.53768 focal_loss 0.44556 dice_loss 0.09212 +Epoch [3968/4000] Validation [4/4] Loss: 0.45647 focal_loss 0.35023 dice_loss 0.10624 +Epoch [3968/4000] Validation metric {'Val/mean dice_metric': 0.9742685556411743, 'Val/mean miou_metric': 0.9604261517524719, 'Val/mean f1': 0.9759880900382996, 'Val/mean precision': 0.9733971953392029, 'Val/mean recall': 0.9785928130149841, 'Val/mean hd95_metric': 5.032262802124023} +Cheakpoint... +Epoch [3968/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742685556411743, 'Val/mean miou_metric': 0.9604261517524719, 'Val/mean f1': 0.9759880900382996, 'Val/mean precision': 0.9733971953392029, 'Val/mean recall': 0.9785928130149841, 'Val/mean hd95_metric': 5.032262802124023} +Epoch [3969/4000] Training [1/16] Loss: 0.00286 +Epoch [3969/4000] Training [2/16] Loss: 0.00370 +Epoch [3969/4000] Training [3/16] Loss: 0.00158 +Epoch [3969/4000] Training [4/16] Loss: 0.00285 +Epoch [3969/4000] Training [5/16] Loss: 0.00195 +Epoch [3969/4000] Training [6/16] Loss: 0.00211 +Epoch [3969/4000] Training [7/16] Loss: 0.00278 +Epoch [3969/4000] Training [8/16] Loss: 0.00312 +Epoch [3969/4000] Training [9/16] Loss: 0.00259 +Epoch [3969/4000] Training [10/16] Loss: 0.00339 +Epoch [3969/4000] Training [11/16] Loss: 0.00213 +Epoch [3969/4000] Training [12/16] Loss: 0.00243 +Epoch [3969/4000] Training [13/16] Loss: 0.00218 +Epoch [3969/4000] Training [14/16] Loss: 0.00208 +Epoch [3969/4000] Training [15/16] Loss: 0.00227 +Epoch [3969/4000] Training [16/16] Loss: 0.00212 +Epoch [3969/4000] Training metric {'Train/mean dice_metric': 0.9988198280334473, 'Train/mean miou_metric': 0.9973645210266113, 'Train/mean f1': 0.9938119053840637, 'Train/mean precision': 0.9892495274543762, 'Train/mean recall': 0.998416543006897, 'Train/mean hd95_metric': 0.5537385940551758} +Epoch [3969/4000] Validation [1/4] Loss: 0.42772 focal_loss 0.36368 dice_loss 0.06404 +Epoch [3969/4000] Validation [2/4] Loss: 0.48298 focal_loss 0.37140 dice_loss 0.11159 +Epoch [3969/4000] Validation [3/4] Loss: 0.54852 focal_loss 0.45749 dice_loss 0.09103 +Epoch [3969/4000] Validation [4/4] Loss: 0.36953 focal_loss 0.27061 dice_loss 0.09892 +Epoch [3969/4000] Validation metric {'Val/mean dice_metric': 0.9744993448257446, 'Val/mean miou_metric': 0.9602199792861938, 'Val/mean f1': 0.9761418700218201, 'Val/mean precision': 0.9740285277366638, 'Val/mean recall': 0.9782643914222717, 'Val/mean hd95_metric': 5.114460468292236} +Cheakpoint... +Epoch [3969/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9744993448257446, 'Val/mean miou_metric': 0.9602199792861938, 'Val/mean f1': 0.9761418700218201, 'Val/mean precision': 0.9740285277366638, 'Val/mean recall': 0.9782643914222717, 'Val/mean hd95_metric': 5.114460468292236} +Epoch [3970/4000] Training [1/16] Loss: 0.00279 +Epoch [3970/4000] Training [2/16] Loss: 0.00239 +Epoch [3970/4000] Training [3/16] Loss: 0.00176 +Epoch [3970/4000] Training [4/16] Loss: 0.00191 +Epoch [3970/4000] Training [5/16] Loss: 0.00298 +Epoch [3970/4000] Training [6/16] Loss: 0.00137 +Epoch [3970/4000] Training [7/16] Loss: 0.00233 +Epoch [3970/4000] Training [8/16] Loss: 0.00174 +Epoch [3970/4000] Training [9/16] Loss: 0.00237 +Epoch [3970/4000] Training [10/16] Loss: 0.00272 +Epoch [3970/4000] Training [11/16] Loss: 0.00178 +Epoch [3970/4000] Training [12/16] Loss: 0.00243 +Epoch [3970/4000] Training [13/16] Loss: 0.00159 +Epoch [3970/4000] Training [14/16] Loss: 0.00238 +Epoch [3970/4000] Training [15/16] Loss: 0.00181 +Epoch [3970/4000] Training [16/16] Loss: 0.00178 +Epoch [3970/4000] Training metric {'Train/mean dice_metric': 0.9989235401153564, 'Train/mean miou_metric': 0.9975709319114685, 'Train/mean f1': 0.9938990473747253, 'Train/mean precision': 0.9893787503242493, 'Train/mean recall': 0.9984608292579651, 'Train/mean hd95_metric': 0.44787919521331787} +Epoch [3970/4000] Validation [1/4] Loss: 0.45118 focal_loss 0.38580 dice_loss 0.06538 +Epoch [3970/4000] Validation [2/4] Loss: 0.48030 focal_loss 0.36962 dice_loss 0.11068 +Epoch [3970/4000] Validation [3/4] Loss: 0.26763 focal_loss 0.20301 dice_loss 0.06462 +Epoch [3970/4000] Validation [4/4] Loss: 0.34576 focal_loss 0.25893 dice_loss 0.08682 +Epoch [3970/4000] Validation metric {'Val/mean dice_metric': 0.9749577641487122, 'Val/mean miou_metric': 0.9614374041557312, 'Val/mean f1': 0.9768548607826233, 'Val/mean precision': 0.9750077724456787, 'Val/mean recall': 0.9787089228630066, 'Val/mean hd95_metric': 5.07330846786499} +Cheakpoint... +Epoch [3970/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9750], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9749577641487122, 'Val/mean miou_metric': 0.9614374041557312, 'Val/mean f1': 0.9768548607826233, 'Val/mean precision': 0.9750077724456787, 'Val/mean recall': 0.9787089228630066, 'Val/mean hd95_metric': 5.07330846786499} +Epoch [3971/4000] Training [1/16] Loss: 0.00249 +Epoch [3971/4000] Training [2/16] Loss: 0.00261 +Epoch [3971/4000] Training [3/16] Loss: 0.00210 +Epoch [3971/4000] Training [4/16] Loss: 0.00220 +Epoch [3971/4000] Training [5/16] Loss: 0.00242 +Epoch [3971/4000] Training [6/16] Loss: 0.00198 +Epoch [3971/4000] Training [7/16] Loss: 0.00254 +Epoch [3971/4000] Training [8/16] Loss: 0.00212 +Epoch [3971/4000] Training [9/16] Loss: 0.00129 +Epoch [3971/4000] Training [10/16] Loss: 0.00235 +Epoch [3971/4000] Training [11/16] Loss: 0.00231 +Epoch [3971/4000] Training [12/16] Loss: 0.00227 +Epoch [3971/4000] Training [13/16] Loss: 0.00370 +Epoch [3971/4000] Training [14/16] Loss: 0.00364 +Epoch [3971/4000] Training [15/16] Loss: 0.00285 +Epoch [3971/4000] Training [16/16] Loss: 0.00299 +Epoch [3971/4000] Training metric {'Train/mean dice_metric': 0.9988346099853516, 'Train/mean miou_metric': 0.99739670753479, 'Train/mean f1': 0.9938580989837646, 'Train/mean precision': 0.9893106818199158, 'Train/mean recall': 0.9984475374221802, 'Train/mean hd95_metric': 0.49992990493774414} +Epoch [3971/4000] Validation [1/4] Loss: 0.39557 focal_loss 0.33500 dice_loss 0.06057 +Epoch [3971/4000] Validation [2/4] Loss: 0.90017 focal_loss 0.69907 dice_loss 0.20110 +Epoch [3971/4000] Validation [3/4] Loss: 0.56156 focal_loss 0.46379 dice_loss 0.09776 +Epoch [3971/4000] Validation [4/4] Loss: 0.34958 focal_loss 0.26030 dice_loss 0.08928 +Epoch [3971/4000] Validation metric {'Val/mean dice_metric': 0.9734846949577332, 'Val/mean miou_metric': 0.9594631195068359, 'Val/mean f1': 0.9760496616363525, 'Val/mean precision': 0.9741137623786926, 'Val/mean recall': 0.977993369102478, 'Val/mean hd95_metric': 4.893173694610596} +Cheakpoint... +Epoch [3971/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734846949577332, 'Val/mean miou_metric': 0.9594631195068359, 'Val/mean f1': 0.9760496616363525, 'Val/mean precision': 0.9741137623786926, 'Val/mean recall': 0.977993369102478, 'Val/mean hd95_metric': 4.893173694610596} +Epoch [3972/4000] Training [1/16] Loss: 0.00223 +Epoch [3972/4000] Training [2/16] Loss: 0.00288 +Epoch [3972/4000] Training [3/16] Loss: 0.00207 +Epoch [3972/4000] Training [4/16] Loss: 0.00218 +Epoch [3972/4000] Training [5/16] Loss: 0.00214 +Epoch [3972/4000] Training [6/16] Loss: 0.00412 +Epoch [3972/4000] Training [7/16] Loss: 0.00265 +Epoch [3972/4000] Training [8/16] Loss: 0.00301 +Epoch [3972/4000] Training [9/16] Loss: 0.00247 +Epoch [3972/4000] Training [10/16] Loss: 0.00224 +Epoch [3972/4000] Training [11/16] Loss: 0.00157 +Epoch [3972/4000] Training [12/16] Loss: 0.00259 +Epoch [3972/4000] Training [13/16] Loss: 0.00236 +Epoch [3972/4000] Training [14/16] Loss: 0.00237 +Epoch [3972/4000] Training [15/16] Loss: 0.00222 +Epoch [3972/4000] Training [16/16] Loss: 0.00163 +Epoch [3972/4000] Training metric {'Train/mean dice_metric': 0.9986366033554077, 'Train/mean miou_metric': 0.9969945549964905, 'Train/mean f1': 0.9936450719833374, 'Train/mean precision': 0.9890565276145935, 'Train/mean recall': 0.9982763528823853, 'Train/mean hd95_metric': 0.571426510810852} +Epoch [3972/4000] Validation [1/4] Loss: 0.42339 focal_loss 0.35811 dice_loss 0.06528 +Epoch [3972/4000] Validation [2/4] Loss: 1.03680 focal_loss 0.79085 dice_loss 0.24595 +Epoch [3972/4000] Validation [3/4] Loss: 0.55058 focal_loss 0.45665 dice_loss 0.09393 +Epoch [3972/4000] Validation [4/4] Loss: 0.40299 focal_loss 0.30095 dice_loss 0.10205 +Epoch [3972/4000] Validation metric {'Val/mean dice_metric': 0.9727644920349121, 'Val/mean miou_metric': 0.9587462544441223, 'Val/mean f1': 0.9758205413818359, 'Val/mean precision': 0.9738619327545166, 'Val/mean recall': 0.9777868986129761, 'Val/mean hd95_metric': 4.958507537841797} +Cheakpoint... +Epoch [3972/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9728], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727644920349121, 'Val/mean miou_metric': 0.9587462544441223, 'Val/mean f1': 0.9758205413818359, 'Val/mean precision': 0.9738619327545166, 'Val/mean recall': 0.9777868986129761, 'Val/mean hd95_metric': 4.958507537841797} +Epoch [3973/4000] Training [1/16] Loss: 0.00317 +Epoch [3973/4000] Training [2/16] Loss: 0.00217 +Epoch [3973/4000] Training [3/16] Loss: 0.00256 +Epoch [3973/4000] Training [4/16] Loss: 0.00247 +Epoch [3973/4000] Training [5/16] Loss: 0.00220 +Epoch [3973/4000] Training [6/16] Loss: 0.00180 +Epoch [3973/4000] Training [7/16] Loss: 0.00376 +Epoch [3973/4000] Training [8/16] Loss: 0.00186 +Epoch [3973/4000] Training [9/16] Loss: 0.00311 +Epoch [3973/4000] Training [10/16] Loss: 0.00155 +Epoch [3973/4000] Training [11/16] Loss: 0.00235 +Epoch [3973/4000] Training [12/16] Loss: 0.00247 +Epoch [3973/4000] Training [13/16] Loss: 0.00261 +Epoch [3973/4000] Training [14/16] Loss: 0.00184 +Epoch [3973/4000] Training [15/16] Loss: 0.00276 +Epoch [3973/4000] Training [16/16] Loss: 0.00212 +Epoch [3973/4000] Training metric {'Train/mean dice_metric': 0.9986762404441833, 'Train/mean miou_metric': 0.9970648288726807, 'Train/mean f1': 0.9936421513557434, 'Train/mean precision': 0.9890042543411255, 'Train/mean recall': 0.9983237385749817, 'Train/mean hd95_metric': 0.5415171384811401} +Epoch [3973/4000] Validation [1/4] Loss: 0.37516 focal_loss 0.31342 dice_loss 0.06174 +Epoch [3973/4000] Validation [2/4] Loss: 1.05568 focal_loss 0.86781 dice_loss 0.18787 +Epoch [3973/4000] Validation [3/4] Loss: 0.55140 focal_loss 0.45999 dice_loss 0.09141 +Epoch [3973/4000] Validation [4/4] Loss: 0.30711 focal_loss 0.22028 dice_loss 0.08683 +Epoch [3973/4000] Validation metric {'Val/mean dice_metric': 0.9742532968521118, 'Val/mean miou_metric': 0.9605032801628113, 'Val/mean f1': 0.9758985042572021, 'Val/mean precision': 0.9725026488304138, 'Val/mean recall': 0.9793182015419006, 'Val/mean hd95_metric': 4.991663455963135} +Cheakpoint... +Epoch [3973/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9743], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742532968521118, 'Val/mean miou_metric': 0.9605032801628113, 'Val/mean f1': 0.9758985042572021, 'Val/mean precision': 0.9725026488304138, 'Val/mean recall': 0.9793182015419006, 'Val/mean hd95_metric': 4.991663455963135} +Epoch [3974/4000] Training [1/16] Loss: 0.00235 +Epoch [3974/4000] Training [2/16] Loss: 0.00255 +Epoch [3974/4000] Training [3/16] Loss: 0.00274 +Epoch [3974/4000] Training [4/16] Loss: 0.00224 +Epoch [3974/4000] Training [5/16] Loss: 0.00294 +Epoch [3974/4000] Training [6/16] Loss: 0.00450 +Epoch [3974/4000] Training [7/16] Loss: 0.00217 +Epoch [3974/4000] Training [8/16] Loss: 0.00227 +Epoch [3974/4000] Training [9/16] Loss: 0.00207 +Epoch [3974/4000] Training [10/16] Loss: 0.00309 +Epoch [3974/4000] Training [11/16] Loss: 0.00230 +Epoch [3974/4000] Training [12/16] Loss: 0.00314 +Epoch [3974/4000] Training [13/16] Loss: 0.00295 +Epoch [3974/4000] Training [14/16] Loss: 0.00308 +Epoch [3974/4000] Training [15/16] Loss: 0.00253 +Epoch [3974/4000] Training [16/16] Loss: 0.00192 +Epoch [3974/4000] Training metric {'Train/mean dice_metric': 0.9987214803695679, 'Train/mean miou_metric': 0.9971604347229004, 'Train/mean f1': 0.9937303066253662, 'Train/mean precision': 0.9892024993896484, 'Train/mean recall': 0.9982997179031372, 'Train/mean hd95_metric': 0.5401920080184937} +Epoch [3974/4000] Validation [1/4] Loss: 0.42618 focal_loss 0.36332 dice_loss 0.06286 +Epoch [3974/4000] Validation [2/4] Loss: 0.46659 focal_loss 0.35831 dice_loss 0.10827 +Epoch [3974/4000] Validation [3/4] Loss: 0.52787 focal_loss 0.43623 dice_loss 0.09165 +Epoch [3974/4000] Validation [4/4] Loss: 0.48797 focal_loss 0.37919 dice_loss 0.10878 +Epoch [3974/4000] Validation metric {'Val/mean dice_metric': 0.9722831845283508, 'Val/mean miou_metric': 0.9590066075325012, 'Val/mean f1': 0.9763873219490051, 'Val/mean precision': 0.9746684432029724, 'Val/mean recall': 0.9781121611595154, 'Val/mean hd95_metric': 4.925394058227539} +Cheakpoint... +Epoch [3974/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9723], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9722831845283508, 'Val/mean miou_metric': 0.9590066075325012, 'Val/mean f1': 0.9763873219490051, 'Val/mean precision': 0.9746684432029724, 'Val/mean recall': 0.9781121611595154, 'Val/mean hd95_metric': 4.925394058227539} +Epoch [3975/4000] Training [1/16] Loss: 0.00237 +Epoch [3975/4000] Training [2/16] Loss: 0.00252 +Epoch [3975/4000] Training [3/16] Loss: 0.00217 +Epoch [3975/4000] Training [4/16] Loss: 0.00258 +Epoch [3975/4000] Training [5/16] Loss: 0.00195 +Epoch [3975/4000] Training [6/16] Loss: 0.00280 +Epoch [3975/4000] Training [7/16] Loss: 0.00203 +Epoch [3975/4000] Training [8/16] Loss: 0.00433 +Epoch [3975/4000] Training [9/16] Loss: 0.00191 +Epoch [3975/4000] Training [10/16] Loss: 0.00205 +Epoch [3975/4000] Training [11/16] Loss: 0.00181 +Epoch [3975/4000] Training [12/16] Loss: 0.00233 +Epoch [3975/4000] Training [13/16] Loss: 0.00207 +Epoch [3975/4000] Training [14/16] Loss: 0.00287 +Epoch [3975/4000] Training [15/16] Loss: 0.00228 +Epoch [3975/4000] Training [16/16] Loss: 0.00144 +Epoch [3975/4000] Training metric {'Train/mean dice_metric': 0.9988293647766113, 'Train/mean miou_metric': 0.9973808526992798, 'Train/mean f1': 0.9937208294868469, 'Train/mean precision': 0.9890890717506409, 'Train/mean recall': 0.9983961582183838, 'Train/mean hd95_metric': 0.5198794603347778} +Epoch [3975/4000] Validation [1/4] Loss: 0.40383 focal_loss 0.34232 dice_loss 0.06151 +Epoch [3975/4000] Validation [2/4] Loss: 0.90525 focal_loss 0.70461 dice_loss 0.20064 +Epoch [3975/4000] Validation [3/4] Loss: 0.53730 focal_loss 0.44933 dice_loss 0.08797 +Epoch [3975/4000] Validation [4/4] Loss: 0.35016 focal_loss 0.26582 dice_loss 0.08434 +Epoch [3975/4000] Validation metric {'Val/mean dice_metric': 0.9753952026367188, 'Val/mean miou_metric': 0.9610193371772766, 'Val/mean f1': 0.976244330406189, 'Val/mean precision': 0.9736552834510803, 'Val/mean recall': 0.978847086429596, 'Val/mean hd95_metric': 4.90717077255249} +Cheakpoint... +Epoch [3975/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9754], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753952026367188, 'Val/mean miou_metric': 0.9610193371772766, 'Val/mean f1': 0.976244330406189, 'Val/mean precision': 0.9736552834510803, 'Val/mean recall': 0.978847086429596, 'Val/mean hd95_metric': 4.90717077255249} +Epoch [3976/4000] Training [1/16] Loss: 0.00210 +Epoch [3976/4000] Training [2/16] Loss: 0.00172 +Epoch [3976/4000] Training [3/16] Loss: 0.00239 +Epoch [3976/4000] Training [4/16] Loss: 0.00233 +Epoch [3976/4000] Training [5/16] Loss: 0.00270 +Epoch [3976/4000] Training [6/16] Loss: 0.00173 +Epoch [3976/4000] Training [7/16] Loss: 0.00220 +Epoch [3976/4000] Training [8/16] Loss: 0.00289 +Epoch [3976/4000] Training [9/16] Loss: 0.00169 +Epoch [3976/4000] Training [10/16] Loss: 0.00222 +Epoch [3976/4000] Training [11/16] Loss: 0.00312 +Epoch [3976/4000] Training [12/16] Loss: 0.00238 +Epoch [3976/4000] Training [13/16] Loss: 0.00174 +Epoch [3976/4000] Training [14/16] Loss: 0.00344 +Epoch [3976/4000] Training [15/16] Loss: 0.00344 +Epoch [3976/4000] Training [16/16] Loss: 0.00446 +Epoch [3976/4000] Training metric {'Train/mean dice_metric': 0.9988327026367188, 'Train/mean miou_metric': 0.9973739981651306, 'Train/mean f1': 0.9935985803604126, 'Train/mean precision': 0.9888050556182861, 'Train/mean recall': 0.9984387159347534, 'Train/mean hd95_metric': 0.4913361966609955} +Epoch [3976/4000] Validation [1/4] Loss: 0.41843 focal_loss 0.35721 dice_loss 0.06122 +Epoch [3976/4000] Validation [2/4] Loss: 0.47076 focal_loss 0.36280 dice_loss 0.10795 +Epoch [3976/4000] Validation [3/4] Loss: 0.53587 focal_loss 0.43613 dice_loss 0.09975 +Epoch [3976/4000] Validation [4/4] Loss: 0.34883 focal_loss 0.26604 dice_loss 0.08279 +Epoch [3976/4000] Validation metric {'Val/mean dice_metric': 0.974687933921814, 'Val/mean miou_metric': 0.9607175588607788, 'Val/mean f1': 0.9763122797012329, 'Val/mean precision': 0.9737905263900757, 'Val/mean recall': 0.978847086429596, 'Val/mean hd95_metric': 4.976922035217285} +Cheakpoint... +Epoch [3976/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974687933921814, 'Val/mean miou_metric': 0.9607175588607788, 'Val/mean f1': 0.9763122797012329, 'Val/mean precision': 0.9737905263900757, 'Val/mean recall': 0.978847086429596, 'Val/mean hd95_metric': 4.976922035217285} +Epoch [3977/4000] Training [1/16] Loss: 0.00277 +Epoch [3977/4000] Training [2/16] Loss: 0.00433 +Epoch [3977/4000] Training [3/16] Loss: 0.00209 +Epoch [3977/4000] Training [4/16] Loss: 0.00276 +Epoch [3977/4000] Training [5/16] Loss: 0.00251 +Epoch [3977/4000] Training [6/16] Loss: 0.00185 +Epoch [3977/4000] Training [7/16] Loss: 0.00194 +Epoch [3977/4000] Training [8/16] Loss: 0.00181 +Epoch [3977/4000] Training [9/16] Loss: 0.00325 +Epoch [3977/4000] Training [10/16] Loss: 0.00279 +Epoch [3977/4000] Training [11/16] Loss: 0.00202 +Epoch [3977/4000] Training [12/16] Loss: 0.00279 +Epoch [3977/4000] Training [13/16] Loss: 0.00228 +Epoch [3977/4000] Training [14/16] Loss: 0.00232 +Epoch [3977/4000] Training [15/16] Loss: 0.00211 +Epoch [3977/4000] Training [16/16] Loss: 0.00303 +Epoch [3977/4000] Training metric {'Train/mean dice_metric': 0.9987788200378418, 'Train/mean miou_metric': 0.9972606897354126, 'Train/mean f1': 0.9934362769126892, 'Train/mean precision': 0.9886243939399719, 'Train/mean recall': 0.998295247554779, 'Train/mean hd95_metric': 0.5187774896621704} +Epoch [3977/4000] Validation [1/4] Loss: 0.41731 focal_loss 0.35138 dice_loss 0.06593 +Epoch [3977/4000] Validation [2/4] Loss: 0.64421 focal_loss 0.47165 dice_loss 0.17257 +Epoch [3977/4000] Validation [3/4] Loss: 0.54939 focal_loss 0.45788 dice_loss 0.09151 +Epoch [3977/4000] Validation [4/4] Loss: 0.29429 focal_loss 0.21177 dice_loss 0.08252 +Epoch [3977/4000] Validation metric {'Val/mean dice_metric': 0.97596275806427, 'Val/mean miou_metric': 0.9615068435668945, 'Val/mean f1': 0.9762030839920044, 'Val/mean precision': 0.9735788702964783, 'Val/mean recall': 0.9788414835929871, 'Val/mean hd95_metric': 4.901552200317383} +Cheakpoint... +Epoch [3977/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.97596275806427, 'Val/mean miou_metric': 0.9615068435668945, 'Val/mean f1': 0.9762030839920044, 'Val/mean precision': 0.9735788702964783, 'Val/mean recall': 0.9788414835929871, 'Val/mean hd95_metric': 4.901552200317383} +Epoch [3978/4000] Training [1/16] Loss: 0.00283 +Epoch [3978/4000] Training [2/16] Loss: 0.00224 +Epoch [3978/4000] Training [3/16] Loss: 0.00258 +Epoch [3978/4000] Training [4/16] Loss: 0.00243 +Epoch [3978/4000] Training [5/16] Loss: 0.00308 +Epoch [3978/4000] Training [6/16] Loss: 0.00348 +Epoch [3978/4000] Training [7/16] Loss: 0.00280 +Epoch [3978/4000] Training [8/16] Loss: 0.00199 +Epoch [3978/4000] Training [9/16] Loss: 0.00293 +Epoch [3978/4000] Training [10/16] Loss: 0.00316 +Epoch [3978/4000] Training [11/16] Loss: 0.00234 +Epoch [3978/4000] Training [12/16] Loss: 0.00205 +Epoch [3978/4000] Training [13/16] Loss: 0.00228 +Epoch [3978/4000] Training [14/16] Loss: 0.00281 +Epoch [3978/4000] Training [15/16] Loss: 0.00347 +Epoch [3978/4000] Training [16/16] Loss: 0.00222 +Epoch [3978/4000] Training metric {'Train/mean dice_metric': 0.9986798167228699, 'Train/mean miou_metric': 0.9970879554748535, 'Train/mean f1': 0.9937227964401245, 'Train/mean precision': 0.9892039895057678, 'Train/mean recall': 0.9982830882072449, 'Train/mean hd95_metric': 0.5860627293586731} +Epoch [3978/4000] Validation [1/4] Loss: 0.41986 focal_loss 0.35655 dice_loss 0.06332 +Epoch [3978/4000] Validation [2/4] Loss: 0.46930 focal_loss 0.36034 dice_loss 0.10896 +Epoch [3978/4000] Validation [3/4] Loss: 0.53328 focal_loss 0.44371 dice_loss 0.08957 +Epoch [3978/4000] Validation [4/4] Loss: 0.31162 focal_loss 0.22335 dice_loss 0.08828 +Epoch [3978/4000] Validation metric {'Val/mean dice_metric': 0.9747117757797241, 'Val/mean miou_metric': 0.9609329104423523, 'Val/mean f1': 0.9766122102737427, 'Val/mean precision': 0.9744524955749512, 'Val/mean recall': 0.978781521320343, 'Val/mean hd95_metric': 4.9204301834106445} +Cheakpoint... +Epoch [3978/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747117757797241, 'Val/mean miou_metric': 0.9609329104423523, 'Val/mean f1': 0.9766122102737427, 'Val/mean precision': 0.9744524955749512, 'Val/mean recall': 0.978781521320343, 'Val/mean hd95_metric': 4.9204301834106445} +Epoch [3979/4000] Training [1/16] Loss: 0.00205 +Epoch [3979/4000] Training [2/16] Loss: 0.00295 +Epoch [3979/4000] Training [3/16] Loss: 0.00239 +Epoch [3979/4000] Training [4/16] Loss: 0.00121 +Epoch [3979/4000] Training [5/16] Loss: 0.00210 +Epoch [3979/4000] Training [6/16] Loss: 0.00173 +Epoch [3979/4000] Training [7/16] Loss: 0.00211 +Epoch [3979/4000] Training [8/16] Loss: 0.00192 +Epoch [3979/4000] Training [9/16] Loss: 0.00517 +Epoch [3979/4000] Training [10/16] Loss: 0.00136 +Epoch [3979/4000] Training [11/16] Loss: 0.00269 +Epoch [3979/4000] Training [12/16] Loss: 0.00215 +Epoch [3979/4000] Training [13/16] Loss: 0.00159 +Epoch [3979/4000] Training [14/16] Loss: 0.00178 +Epoch [3979/4000] Training [15/16] Loss: 0.00311 +Epoch [3979/4000] Training [16/16] Loss: 0.00150 +Epoch [3979/4000] Training metric {'Train/mean dice_metric': 0.9989415407180786, 'Train/mean miou_metric': 0.9976074695587158, 'Train/mean f1': 0.9939369559288025, 'Train/mean precision': 0.9894351959228516, 'Train/mean recall': 0.9984799027442932, 'Train/mean hd95_metric': 0.45581698417663574} +Epoch [3979/4000] Validation [1/4] Loss: 0.35310 focal_loss 0.29511 dice_loss 0.05800 +Epoch [3979/4000] Validation [2/4] Loss: 0.53001 focal_loss 0.39779 dice_loss 0.13221 +Epoch [3979/4000] Validation [3/4] Loss: 0.54981 focal_loss 0.45760 dice_loss 0.09221 +Epoch [3979/4000] Validation [4/4] Loss: 0.29136 focal_loss 0.21069 dice_loss 0.08067 +Epoch [3979/4000] Validation metric {'Val/mean dice_metric': 0.9753364324569702, 'Val/mean miou_metric': 0.9612236022949219, 'Val/mean f1': 0.9770911335945129, 'Val/mean precision': 0.9744163155555725, 'Val/mean recall': 0.9797806739807129, 'Val/mean hd95_metric': 4.755674839019775} +Cheakpoint... +Epoch [3979/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9753], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9753364324569702, 'Val/mean miou_metric': 0.9612236022949219, 'Val/mean f1': 0.9770911335945129, 'Val/mean precision': 0.9744163155555725, 'Val/mean recall': 0.9797806739807129, 'Val/mean hd95_metric': 4.755674839019775} +Epoch [3980/4000] Training [1/16] Loss: 0.00347 +Epoch [3980/4000] Training [2/16] Loss: 0.00376 +Epoch [3980/4000] Training [3/16] Loss: 0.00250 +Epoch [3980/4000] Training [4/16] Loss: 0.00382 +Epoch [3980/4000] Training [5/16] Loss: 0.00206 +Epoch [3980/4000] Training [6/16] Loss: 0.00205 +Epoch [3980/4000] Training [7/16] Loss: 0.00190 +Epoch [3980/4000] Training [8/16] Loss: 0.00186 +Epoch [3980/4000] Training [9/16] Loss: 0.00252 +Epoch [3980/4000] Training [10/16] Loss: 0.00194 +Epoch [3980/4000] Training [11/16] Loss: 0.00207 +Epoch [3980/4000] Training [12/16] Loss: 0.00186 +Epoch [3980/4000] Training [13/16] Loss: 0.00289 +Epoch [3980/4000] Training [14/16] Loss: 0.00143 +Epoch [3980/4000] Training [15/16] Loss: 0.00272 +Epoch [3980/4000] Training [16/16] Loss: 0.00234 +Epoch [3980/4000] Training metric {'Train/mean dice_metric': 0.9988234043121338, 'Train/mean miou_metric': 0.9973540306091309, 'Train/mean f1': 0.9935754537582397, 'Train/mean precision': 0.9887887239456177, 'Train/mean recall': 0.9984087347984314, 'Train/mean hd95_metric': 0.498562753200531} +Epoch [3980/4000] Validation [1/4] Loss: 0.41238 focal_loss 0.34931 dice_loss 0.06308 +Epoch [3980/4000] Validation [2/4] Loss: 0.88346 focal_loss 0.68735 dice_loss 0.19611 +Epoch [3980/4000] Validation [3/4] Loss: 0.56078 focal_loss 0.46408 dice_loss 0.09670 +Epoch [3980/4000] Validation [4/4] Loss: 0.39073 focal_loss 0.28882 dice_loss 0.10191 +Epoch [3980/4000] Validation metric {'Val/mean dice_metric': 0.9732887148857117, 'Val/mean miou_metric': 0.9590178728103638, 'Val/mean f1': 0.9758668541908264, 'Val/mean precision': 0.9734152555465698, 'Val/mean recall': 0.9783307313919067, 'Val/mean hd95_metric': 4.844011306762695} +Cheakpoint... +Epoch [3980/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9733], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9732887148857117, 'Val/mean miou_metric': 0.9590178728103638, 'Val/mean f1': 0.9758668541908264, 'Val/mean precision': 0.9734152555465698, 'Val/mean recall': 0.9783307313919067, 'Val/mean hd95_metric': 4.844011306762695} +Epoch [3981/4000] Training [1/16] Loss: 0.00432 +Epoch [3981/4000] Training [2/16] Loss: 0.00190 +Epoch [3981/4000] Training [3/16] Loss: 0.00177 +Epoch [3981/4000] Training [4/16] Loss: 0.00243 +Epoch [3981/4000] Training [5/16] Loss: 0.00182 +Epoch [3981/4000] Training [6/16] Loss: 0.00260 +Epoch [3981/4000] Training [7/16] Loss: 0.00253 +Epoch [3981/4000] Training [8/16] Loss: 0.00354 +Epoch [3981/4000] Training [9/16] Loss: 0.00173 +Epoch [3981/4000] Training [10/16] Loss: 0.00347 +Epoch [3981/4000] Training [11/16] Loss: 0.00294 +Epoch [3981/4000] Training [12/16] Loss: 0.00308 +Epoch [3981/4000] Training [13/16] Loss: 0.00198 +Epoch [3981/4000] Training [14/16] Loss: 0.00203 +Epoch [3981/4000] Training [15/16] Loss: 0.00287 +Epoch [3981/4000] Training [16/16] Loss: 0.00250 +Epoch [3981/4000] Training metric {'Train/mean dice_metric': 0.9987571835517883, 'Train/mean miou_metric': 0.9972344636917114, 'Train/mean f1': 0.9936351776123047, 'Train/mean precision': 0.9889834523200989, 'Train/mean recall': 0.99833083152771, 'Train/mean hd95_metric': 0.5108675956726074} +Epoch [3981/4000] Validation [1/4] Loss: 0.46401 focal_loss 0.39514 dice_loss 0.06887 +Epoch [3981/4000] Validation [2/4] Loss: 0.48247 focal_loss 0.37338 dice_loss 0.10909 +Epoch [3981/4000] Validation [3/4] Loss: 0.52952 focal_loss 0.43926 dice_loss 0.09026 +Epoch [3981/4000] Validation [4/4] Loss: 0.36609 focal_loss 0.27734 dice_loss 0.08875 +Epoch [3981/4000] Validation metric {'Val/mean dice_metric': 0.9748016595840454, 'Val/mean miou_metric': 0.9605633616447449, 'Val/mean f1': 0.9762079119682312, 'Val/mean precision': 0.9742651581764221, 'Val/mean recall': 0.9781584143638611, 'Val/mean hd95_metric': 4.693641662597656} +Cheakpoint... +Epoch [3981/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9748], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9748016595840454, 'Val/mean miou_metric': 0.9605633616447449, 'Val/mean f1': 0.9762079119682312, 'Val/mean precision': 0.9742651581764221, 'Val/mean recall': 0.9781584143638611, 'Val/mean hd95_metric': 4.693641662597656} +Epoch [3982/4000] Training [1/16] Loss: 0.00245 +Epoch [3982/4000] Training [2/16] Loss: 0.00264 +Epoch [3982/4000] Training [3/16] Loss: 0.00338 +Epoch [3982/4000] Training [4/16] Loss: 0.00253 +Epoch [3982/4000] Training [5/16] Loss: 0.00303 +Epoch [3982/4000] Training [6/16] Loss: 0.00175 +Epoch [3982/4000] Training [7/16] Loss: 0.00198 +Epoch [3982/4000] Training [8/16] Loss: 0.00270 +Epoch [3982/4000] Training [9/16] Loss: 0.00215 +Epoch [3982/4000] Training [10/16] Loss: 0.00198 +Epoch [3982/4000] Training [11/16] Loss: 0.00245 +Epoch [3982/4000] Training [12/16] Loss: 0.00184 +Epoch [3982/4000] Training [13/16] Loss: 0.00199 +Epoch [3982/4000] Training [14/16] Loss: 0.00307 +Epoch [3982/4000] Training [15/16] Loss: 0.00255 +Epoch [3982/4000] Training [16/16] Loss: 0.00223 +Epoch [3982/4000] Training metric {'Train/mean dice_metric': 0.998760461807251, 'Train/mean miou_metric': 0.9972363114356995, 'Train/mean f1': 0.9935306906700134, 'Train/mean precision': 0.9887925982475281, 'Train/mean recall': 0.998314380645752, 'Train/mean hd95_metric': 0.520047128200531} +Epoch [3982/4000] Validation [1/4] Loss: 0.39589 focal_loss 0.33315 dice_loss 0.06274 +Epoch [3982/4000] Validation [2/4] Loss: 1.51460 focal_loss 1.23325 dice_loss 0.28135 +Epoch [3982/4000] Validation [3/4] Loss: 0.55902 focal_loss 0.46318 dice_loss 0.09584 +Epoch [3982/4000] Validation [4/4] Loss: 0.34057 focal_loss 0.25554 dice_loss 0.08503 +Epoch [3982/4000] Validation metric {'Val/mean dice_metric': 0.9743648767471313, 'Val/mean miou_metric': 0.9605643153190613, 'Val/mean f1': 0.9756292700767517, 'Val/mean precision': 0.9730076789855957, 'Val/mean recall': 0.9782651662826538, 'Val/mean hd95_metric': 4.958003520965576} +Cheakpoint... +Epoch [3982/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9744], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9743648767471313, 'Val/mean miou_metric': 0.9605643153190613, 'Val/mean f1': 0.9756292700767517, 'Val/mean precision': 0.9730076789855957, 'Val/mean recall': 0.9782651662826538, 'Val/mean hd95_metric': 4.958003520965576} +Epoch [3983/4000] Training [1/16] Loss: 0.00219 +Epoch [3983/4000] Training [2/16] Loss: 0.00223 +Epoch [3983/4000] Training [3/16] Loss: 0.00141 +Epoch [3983/4000] Training [4/16] Loss: 0.00235 +Epoch [3983/4000] Training [5/16] Loss: 0.00190 +Epoch [3983/4000] Training [6/16] Loss: 0.00324 +Epoch [3983/4000] Training [7/16] Loss: 0.00154 +Epoch [3983/4000] Training [8/16] Loss: 0.00262 +Epoch [3983/4000] Training [9/16] Loss: 0.00271 +Epoch [3983/4000] Training [10/16] Loss: 0.00215 +Epoch [3983/4000] Training [11/16] Loss: 0.00204 +Epoch [3983/4000] Training [12/16] Loss: 0.00200 +Epoch [3983/4000] Training [13/16] Loss: 0.00212 +Epoch [3983/4000] Training [14/16] Loss: 0.00219 +Epoch [3983/4000] Training [15/16] Loss: 0.00229 +Epoch [3983/4000] Training [16/16] Loss: 0.00228 +Epoch [3983/4000] Training metric {'Train/mean dice_metric': 0.9989383816719055, 'Train/mean miou_metric': 0.9975811243057251, 'Train/mean f1': 0.9937805533409119, 'Train/mean precision': 0.9891108274459839, 'Train/mean recall': 0.9984947443008423, 'Train/mean hd95_metric': 0.4778595566749573} +Epoch [3983/4000] Validation [1/4] Loss: 0.48731 focal_loss 0.40860 dice_loss 0.07871 +Epoch [3983/4000] Validation [2/4] Loss: 0.54038 focal_loss 0.40933 dice_loss 0.13105 +Epoch [3983/4000] Validation [3/4] Loss: 0.52536 focal_loss 0.43497 dice_loss 0.09039 +Epoch [3983/4000] Validation [4/4] Loss: 0.36624 focal_loss 0.27106 dice_loss 0.09518 +Epoch [3983/4000] Validation metric {'Val/mean dice_metric': 0.9746584892272949, 'Val/mean miou_metric': 0.96044921875, 'Val/mean f1': 0.9762143492698669, 'Val/mean precision': 0.9743122458457947, 'Val/mean recall': 0.9781239628791809, 'Val/mean hd95_metric': 4.953300952911377} +Cheakpoint... +Epoch [3983/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9746584892272949, 'Val/mean miou_metric': 0.96044921875, 'Val/mean f1': 0.9762143492698669, 'Val/mean precision': 0.9743122458457947, 'Val/mean recall': 0.9781239628791809, 'Val/mean hd95_metric': 4.953300952911377} +Epoch [3984/4000] Training [1/16] Loss: 0.00318 +Epoch [3984/4000] Training [2/16] Loss: 0.00255 +Epoch [3984/4000] Training [3/16] Loss: 0.00165 +Epoch [3984/4000] Training [4/16] Loss: 0.00235 +Epoch [3984/4000] Training [5/16] Loss: 0.00230 +Epoch [3984/4000] Training [6/16] Loss: 0.00209 +Epoch [3984/4000] Training [7/16] Loss: 0.00367 +Epoch [3984/4000] Training [8/16] Loss: 0.00197 +Epoch [3984/4000] Training [9/16] Loss: 0.00170 +Epoch [3984/4000] Training [10/16] Loss: 0.00162 +Epoch [3984/4000] Training [11/16] Loss: 0.00188 +Epoch [3984/4000] Training [12/16] Loss: 0.00209 +Epoch [3984/4000] Training [13/16] Loss: 0.00291 +Epoch [3984/4000] Training [14/16] Loss: 0.00195 +Epoch [3984/4000] Training [15/16] Loss: 0.00220 +Epoch [3984/4000] Training [16/16] Loss: 0.00277 +Epoch [3984/4000] Training metric {'Train/mean dice_metric': 0.9988301992416382, 'Train/mean miou_metric': 0.997379720211029, 'Train/mean f1': 0.993820071220398, 'Train/mean precision': 0.9892342686653137, 'Train/mean recall': 0.9984485507011414, 'Train/mean hd95_metric': 0.5275943279266357} +Epoch [3984/4000] Validation [1/4] Loss: 0.41945 focal_loss 0.35541 dice_loss 0.06404 +Epoch [3984/4000] Validation [2/4] Loss: 0.48483 focal_loss 0.37634 dice_loss 0.10849 +Epoch [3984/4000] Validation [3/4] Loss: 0.56031 focal_loss 0.46360 dice_loss 0.09671 +Epoch [3984/4000] Validation [4/4] Loss: 0.50089 focal_loss 0.38647 dice_loss 0.11443 +Epoch [3984/4000] Validation metric {'Val/mean dice_metric': 0.9745494723320007, 'Val/mean miou_metric': 0.9602928161621094, 'Val/mean f1': 0.9763020873069763, 'Val/mean precision': 0.973809540271759, 'Val/mean recall': 0.9788073301315308, 'Val/mean hd95_metric': 5.538871765136719} +Cheakpoint... +Epoch [3984/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745494723320007, 'Val/mean miou_metric': 0.9602928161621094, 'Val/mean f1': 0.9763020873069763, 'Val/mean precision': 0.973809540271759, 'Val/mean recall': 0.9788073301315308, 'Val/mean hd95_metric': 5.538871765136719} +Epoch [3985/4000] Training [1/16] Loss: 0.00310 +Epoch [3985/4000] Training [2/16] Loss: 0.00261 +Epoch [3985/4000] Training [3/16] Loss: 0.00352 +Epoch [3985/4000] Training [4/16] Loss: 0.00227 +Epoch [3985/4000] Training [5/16] Loss: 0.00251 +Epoch [3985/4000] Training [6/16] Loss: 0.00292 +Epoch [3985/4000] Training [7/16] Loss: 0.00243 +Epoch [3985/4000] Training [8/16] Loss: 0.00170 +Epoch [3985/4000] Training [9/16] Loss: 0.00187 +Epoch [3985/4000] Training [10/16] Loss: 0.00248 +Epoch [3985/4000] Training [11/16] Loss: 0.00290 +Epoch [3985/4000] Training [12/16] Loss: 0.00147 +Epoch [3985/4000] Training [13/16] Loss: 0.00411 +Epoch [3985/4000] Training [14/16] Loss: 0.00183 +Epoch [3985/4000] Training [15/16] Loss: 0.00223 +Epoch [3985/4000] Training [16/16] Loss: 0.00225 +Epoch [3985/4000] Training metric {'Train/mean dice_metric': 0.9988451600074768, 'Train/mean miou_metric': 0.9974161386489868, 'Train/mean f1': 0.9939356446266174, 'Train/mean precision': 0.9894449710845947, 'Train/mean recall': 0.9984673261642456, 'Train/mean hd95_metric': 0.47903138399124146} +Epoch [3985/4000] Validation [1/4] Loss: 0.38537 focal_loss 0.32377 dice_loss 0.06161 +Epoch [3985/4000] Validation [2/4] Loss: 0.47633 focal_loss 0.36654 dice_loss 0.10979 +Epoch [3985/4000] Validation [3/4] Loss: 0.30461 focal_loss 0.23480 dice_loss 0.06981 +Epoch [3985/4000] Validation [4/4] Loss: 0.30207 focal_loss 0.21663 dice_loss 0.08545 +Epoch [3985/4000] Validation metric {'Val/mean dice_metric': 0.975119948387146, 'Val/mean miou_metric': 0.9611282348632812, 'Val/mean f1': 0.97708660364151, 'Val/mean precision': 0.9748232364654541, 'Val/mean recall': 0.9793604016304016, 'Val/mean hd95_metric': 5.045596122741699} +Cheakpoint... +Epoch [3985/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9751], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975119948387146, 'Val/mean miou_metric': 0.9611282348632812, 'Val/mean f1': 0.97708660364151, 'Val/mean precision': 0.9748232364654541, 'Val/mean recall': 0.9793604016304016, 'Val/mean hd95_metric': 5.045596122741699} +Epoch [3986/4000] Training [1/16] Loss: 0.00133 +Epoch [3986/4000] Training [2/16] Loss: 0.00227 +Epoch [3986/4000] Training [3/16] Loss: 0.00202 +Epoch [3986/4000] Training [4/16] Loss: 0.00195 +Epoch [3986/4000] Training [5/16] Loss: 0.00194 +Epoch [3986/4000] Training [6/16] Loss: 0.00401 +Epoch [3986/4000] Training [7/16] Loss: 0.00298 +Epoch [3986/4000] Training [8/16] Loss: 0.00184 +Epoch [3986/4000] Training [9/16] Loss: 0.00265 +Epoch [3986/4000] Training [10/16] Loss: 0.00243 +Epoch [3986/4000] Training [11/16] Loss: 0.00177 +Epoch [3986/4000] Training [12/16] Loss: 0.00295 +Epoch [3986/4000] Training [13/16] Loss: 0.00230 +Epoch [3986/4000] Training [14/16] Loss: 0.00247 +Epoch [3986/4000] Training [15/16] Loss: 0.00258 +Epoch [3986/4000] Training [16/16] Loss: 0.00164 +Epoch [3986/4000] Training metric {'Train/mean dice_metric': 0.9987852573394775, 'Train/mean miou_metric': 0.9972976446151733, 'Train/mean f1': 0.9938129782676697, 'Train/mean precision': 0.9892556667327881, 'Train/mean recall': 0.998412549495697, 'Train/mean hd95_metric': 0.5155550241470337} +Epoch [3986/4000] Validation [1/4] Loss: 0.42453 focal_loss 0.35938 dice_loss 0.06515 +Epoch [3986/4000] Validation [2/4] Loss: 0.90030 focal_loss 0.69933 dice_loss 0.20097 +Epoch [3986/4000] Validation [3/4] Loss: 0.50893 focal_loss 0.42306 dice_loss 0.08588 +Epoch [3986/4000] Validation [4/4] Loss: 0.41912 focal_loss 0.30608 dice_loss 0.11303 +Epoch [3986/4000] Validation metric {'Val/mean dice_metric': 0.9718559384346008, 'Val/mean miou_metric': 0.9581772685050964, 'Val/mean f1': 0.9755266308784485, 'Val/mean precision': 0.9733232259750366, 'Val/mean recall': 0.9777400493621826, 'Val/mean hd95_metric': 4.804888725280762} +Cheakpoint... +Epoch [3986/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9719], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9718559384346008, 'Val/mean miou_metric': 0.9581772685050964, 'Val/mean f1': 0.9755266308784485, 'Val/mean precision': 0.9733232259750366, 'Val/mean recall': 0.9777400493621826, 'Val/mean hd95_metric': 4.804888725280762} +Epoch [3987/4000] Training [1/16] Loss: 0.00366 +Epoch [3987/4000] Training [2/16] Loss: 0.00322 +Epoch [3987/4000] Training [3/16] Loss: 0.00277 +Epoch [3987/4000] Training [4/16] Loss: 0.00321 +Epoch [3987/4000] Training [5/16] Loss: 0.00274 +Epoch [3987/4000] Training [6/16] Loss: 0.00281 +Epoch [3987/4000] Training [7/16] Loss: 0.00208 +Epoch [3987/4000] Training [8/16] Loss: 0.00237 +Epoch [3987/4000] Training [9/16] Loss: 0.00294 +Epoch [3987/4000] Training [10/16] Loss: 0.00282 +Epoch [3987/4000] Training [11/16] Loss: 0.00194 +Epoch [3987/4000] Training [12/16] Loss: 0.00303 +Epoch [3987/4000] Training [13/16] Loss: 0.00316 +Epoch [3987/4000] Training [14/16] Loss: 0.00173 +Epoch [3987/4000] Training [15/16] Loss: 0.00184 +Epoch [3987/4000] Training [16/16] Loss: 0.00189 +Epoch [3987/4000] Training metric {'Train/mean dice_metric': 0.9987330436706543, 'Train/mean miou_metric': 0.9971785545349121, 'Train/mean f1': 0.9935213327407837, 'Train/mean precision': 0.9887788891792297, 'Train/mean recall': 0.9983095526695251, 'Train/mean hd95_metric': 0.5435122847557068} +Epoch [3987/4000] Validation [1/4] Loss: 0.46027 focal_loss 0.39580 dice_loss 0.06447 +Epoch [3987/4000] Validation [2/4] Loss: 0.53311 focal_loss 0.39812 dice_loss 0.13499 +Epoch [3987/4000] Validation [3/4] Loss: 0.54888 focal_loss 0.45274 dice_loss 0.09614 +Epoch [3987/4000] Validation [4/4] Loss: 0.41905 focal_loss 0.31134 dice_loss 0.10771 +Epoch [3987/4000] Validation metric {'Val/mean dice_metric': 0.974162220954895, 'Val/mean miou_metric': 0.9597957730293274, 'Val/mean f1': 0.9761490225791931, 'Val/mean precision': 0.9736487865447998, 'Val/mean recall': 0.9786621928215027, 'Val/mean hd95_metric': 4.829359531402588} +Cheakpoint... +Epoch [3987/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.974162220954895, 'Val/mean miou_metric': 0.9597957730293274, 'Val/mean f1': 0.9761490225791931, 'Val/mean precision': 0.9736487865447998, 'Val/mean recall': 0.9786621928215027, 'Val/mean hd95_metric': 4.829359531402588} +Epoch [3988/4000] Training [1/16] Loss: 0.00203 +Epoch [3988/4000] Training [2/16] Loss: 0.00186 +Epoch [3988/4000] Training [3/16] Loss: 0.00264 +Epoch [3988/4000] Training [4/16] Loss: 0.00332 +Epoch [3988/4000] Training [5/16] Loss: 0.00270 +Epoch [3988/4000] Training [6/16] Loss: 0.00318 +Epoch [3988/4000] Training [7/16] Loss: 0.00204 +Epoch [3988/4000] Training [8/16] Loss: 0.00303 +Epoch [3988/4000] Training [9/16] Loss: 0.00218 +Epoch [3988/4000] Training [10/16] Loss: 0.00344 +Epoch [3988/4000] Training [11/16] Loss: 0.00213 +Epoch [3988/4000] Training [12/16] Loss: 0.00174 +Epoch [3988/4000] Training [13/16] Loss: 0.00224 +Epoch [3988/4000] Training [14/16] Loss: 0.00193 +Epoch [3988/4000] Training [15/16] Loss: 0.00367 +Epoch [3988/4000] Training [16/16] Loss: 0.00226 +Epoch [3988/4000] Training metric {'Train/mean dice_metric': 0.9987402558326721, 'Train/mean miou_metric': 0.9972079992294312, 'Train/mean f1': 0.9937990307807922, 'Train/mean precision': 0.9893119931221008, 'Train/mean recall': 0.9983270168304443, 'Train/mean hd95_metric': 0.5041292309761047} +Epoch [3988/4000] Validation [1/4] Loss: 0.43879 focal_loss 0.37417 dice_loss 0.06461 +Epoch [3988/4000] Validation [2/4] Loss: 0.95569 focal_loss 0.76393 dice_loss 0.19177 +Epoch [3988/4000] Validation [3/4] Loss: 0.32019 focal_loss 0.25285 dice_loss 0.06733 +Epoch [3988/4000] Validation [4/4] Loss: 0.59195 focal_loss 0.46184 dice_loss 0.13011 +Epoch [3988/4000] Validation metric {'Val/mean dice_metric': 0.9730664491653442, 'Val/mean miou_metric': 0.9596287608146667, 'Val/mean f1': 0.976520836353302, 'Val/mean precision': 0.9747630953788757, 'Val/mean recall': 0.9782848954200745, 'Val/mean hd95_metric': 4.842789649963379} +Cheakpoint... +Epoch [3988/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730664491653442, 'Val/mean miou_metric': 0.9596287608146667, 'Val/mean f1': 0.976520836353302, 'Val/mean precision': 0.9747630953788757, 'Val/mean recall': 0.9782848954200745, 'Val/mean hd95_metric': 4.842789649963379} +Epoch [3989/4000] Training [1/16] Loss: 0.00295 +Epoch [3989/4000] Training [2/16] Loss: 0.00320 +Epoch [3989/4000] Training [3/16] Loss: 0.00237 +Epoch [3989/4000] Training [4/16] Loss: 0.00207 +Epoch [3989/4000] Training [5/16] Loss: 0.00306 +Epoch [3989/4000] Training [6/16] Loss: 0.00280 +Epoch [3989/4000] Training [7/16] Loss: 0.00186 +Epoch [3989/4000] Training [8/16] Loss: 0.00247 +Epoch [3989/4000] Training [9/16] Loss: 0.00195 +Epoch [3989/4000] Training [10/16] Loss: 0.00195 +Epoch [3989/4000] Training [11/16] Loss: 0.00229 +Epoch [3989/4000] Training [12/16] Loss: 0.00245 +Epoch [3989/4000] Training [13/16] Loss: 0.00248 +Epoch [3989/4000] Training [14/16] Loss: 0.00156 +Epoch [3989/4000] Training [15/16] Loss: 0.00174 +Epoch [3989/4000] Training [16/16] Loss: 0.00190 +Epoch [3989/4000] Training metric {'Train/mean dice_metric': 0.998856782913208, 'Train/mean miou_metric': 0.9974108338356018, 'Train/mean f1': 0.9933366775512695, 'Train/mean precision': 0.9883033633232117, 'Train/mean recall': 0.9984215497970581, 'Train/mean hd95_metric': 0.47776198387145996} +Epoch [3989/4000] Validation [1/4] Loss: 0.42472 focal_loss 0.36179 dice_loss 0.06293 +Epoch [3989/4000] Validation [2/4] Loss: 0.94612 focal_loss 0.75647 dice_loss 0.18965 +Epoch [3989/4000] Validation [3/4] Loss: 0.53014 focal_loss 0.43653 dice_loss 0.09360 +Epoch [3989/4000] Validation [4/4] Loss: 0.38069 focal_loss 0.28116 dice_loss 0.09953 +Epoch [3989/4000] Validation metric {'Val/mean dice_metric': 0.975987434387207, 'Val/mean miou_metric': 0.9619565010070801, 'Val/mean f1': 0.9764510989189148, 'Val/mean precision': 0.9733710289001465, 'Val/mean recall': 0.9795507788658142, 'Val/mean hd95_metric': 4.8227858543396} +Cheakpoint... +Epoch [3989/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9760], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.975987434387207, 'Val/mean miou_metric': 0.9619565010070801, 'Val/mean f1': 0.9764510989189148, 'Val/mean precision': 0.9733710289001465, 'Val/mean recall': 0.9795507788658142, 'Val/mean hd95_metric': 4.8227858543396} +Epoch [3990/4000] Training [1/16] Loss: 0.00261 +Epoch [3990/4000] Training [2/16] Loss: 0.00365 +Epoch [3990/4000] Training [3/16] Loss: 0.00296 +Epoch [3990/4000] Training [4/16] Loss: 0.00219 +Epoch [3990/4000] Training [5/16] Loss: 0.00206 +Epoch [3990/4000] Training [6/16] Loss: 0.00257 +Epoch [3990/4000] Training [7/16] Loss: 0.00311 +Epoch [3990/4000] Training [8/16] Loss: 0.00228 +Epoch [3990/4000] Training [9/16] Loss: 0.00171 +Epoch [3990/4000] Training [10/16] Loss: 0.00152 +Epoch [3990/4000] Training [11/16] Loss: 0.00279 +Epoch [3990/4000] Training [12/16] Loss: 0.00262 +Epoch [3990/4000] Training [13/16] Loss: 0.00237 +Epoch [3990/4000] Training [14/16] Loss: 0.00218 +Epoch [3990/4000] Training [15/16] Loss: 0.00254 +Epoch [3990/4000] Training [16/16] Loss: 0.00300 +Epoch [3990/4000] Training metric {'Train/mean dice_metric': 0.9986590147018433, 'Train/mean miou_metric': 0.9970402717590332, 'Train/mean f1': 0.9935304522514343, 'Train/mean precision': 0.988852322101593, 'Train/mean recall': 0.9982531070709229, 'Train/mean hd95_metric': 0.5588679909706116} +Epoch [3990/4000] Validation [1/4] Loss: 0.39536 focal_loss 0.33203 dice_loss 0.06333 +Epoch [3990/4000] Validation [2/4] Loss: 0.61529 focal_loss 0.45823 dice_loss 0.15706 +Epoch [3990/4000] Validation [3/4] Loss: 0.56581 focal_loss 0.45871 dice_loss 0.10710 +Epoch [3990/4000] Validation [4/4] Loss: 0.46632 focal_loss 0.35148 dice_loss 0.11484 +Epoch [3990/4000] Validation metric {'Val/mean dice_metric': 0.9727377891540527, 'Val/mean miou_metric': 0.9582993388175964, 'Val/mean f1': 0.9752727746963501, 'Val/mean precision': 0.9736835360527039, 'Val/mean recall': 0.9768674373626709, 'Val/mean hd95_metric': 5.453029155731201} +Cheakpoint... +Epoch [3990/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9727], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9727377891540527, 'Val/mean miou_metric': 0.9582993388175964, 'Val/mean f1': 0.9752727746963501, 'Val/mean precision': 0.9736835360527039, 'Val/mean recall': 0.9768674373626709, 'Val/mean hd95_metric': 5.453029155731201} +Epoch [3991/4000] Training [1/16] Loss: 0.00261 +Epoch [3991/4000] Training [2/16] Loss: 0.00149 +Epoch [3991/4000] Training [3/16] Loss: 0.00599 +Epoch [3991/4000] Training [4/16] Loss: 0.00176 +Epoch [3991/4000] Training [5/16] Loss: 0.00212 +Epoch [3991/4000] Training [6/16] Loss: 0.00173 +Epoch [3991/4000] Training [7/16] Loss: 0.00339 +Epoch [3991/4000] Training [8/16] Loss: 0.00247 +Epoch [3991/4000] Training [9/16] Loss: 0.00208 +Epoch [3991/4000] Training [10/16] Loss: 0.00210 +Epoch [3991/4000] Training [11/16] Loss: 0.00243 +Epoch [3991/4000] Training [12/16] Loss: 0.00294 +Epoch [3991/4000] Training [13/16] Loss: 0.00240 +Epoch [3991/4000] Training [14/16] Loss: 0.00200 +Epoch [3991/4000] Training [15/16] Loss: 0.00348 +Epoch [3991/4000] Training [16/16] Loss: 0.00161 +Epoch [3991/4000] Training metric {'Train/mean dice_metric': 0.9988012909889221, 'Train/mean miou_metric': 0.997301459312439, 'Train/mean f1': 0.9934342503547668, 'Train/mean precision': 0.9885447025299072, 'Train/mean recall': 0.9983723759651184, 'Train/mean hd95_metric': 0.642411470413208} +Epoch [3991/4000] Validation [1/4] Loss: 0.41687 focal_loss 0.35206 dice_loss 0.06480 +Epoch [3991/4000] Validation [2/4] Loss: 0.47760 focal_loss 0.36789 dice_loss 0.10971 +Epoch [3991/4000] Validation [3/4] Loss: 0.53455 focal_loss 0.44369 dice_loss 0.09086 +Epoch [3991/4000] Validation [4/4] Loss: 0.43860 focal_loss 0.33275 dice_loss 0.10585 +Epoch [3991/4000] Validation metric {'Val/mean dice_metric': 0.9742027521133423, 'Val/mean miou_metric': 0.9603632688522339, 'Val/mean f1': 0.9757546186447144, 'Val/mean precision': 0.9730526804924011, 'Val/mean recall': 0.978471577167511, 'Val/mean hd95_metric': 5.265133857727051} +Cheakpoint... +Epoch [3991/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9742], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9742027521133423, 'Val/mean miou_metric': 0.9603632688522339, 'Val/mean f1': 0.9757546186447144, 'Val/mean precision': 0.9730526804924011, 'Val/mean recall': 0.978471577167511, 'Val/mean hd95_metric': 5.265133857727051} +Epoch [3992/4000] Training [1/16] Loss: 0.00193 +Epoch [3992/4000] Training [2/16] Loss: 0.00179 +Epoch [3992/4000] Training [3/16] Loss: 0.00198 +Epoch [3992/4000] Training [4/16] Loss: 0.00199 +Epoch [3992/4000] Training [5/16] Loss: 0.00282 +Epoch [3992/4000] Training [6/16] Loss: 0.00245 +Epoch [3992/4000] Training [7/16] Loss: 0.00185 +Epoch [3992/4000] Training [8/16] Loss: 0.00171 +Epoch [3992/4000] Training [9/16] Loss: 0.00243 +Epoch [3992/4000] Training [10/16] Loss: 0.00283 +Epoch [3992/4000] Training [11/16] Loss: 0.00282 +Epoch [3992/4000] Training [12/16] Loss: 0.00191 +Epoch [3992/4000] Training [13/16] Loss: 0.00235 +Epoch [3992/4000] Training [14/16] Loss: 0.00255 +Epoch [3992/4000] Training [15/16] Loss: 0.00242 +Epoch [3992/4000] Training [16/16] Loss: 0.00264 +Epoch [3992/4000] Training metric {'Train/mean dice_metric': 0.9988411664962769, 'Train/mean miou_metric': 0.9973962903022766, 'Train/mean f1': 0.9936169385910034, 'Train/mean precision': 0.9888814687728882, 'Train/mean recall': 0.998397946357727, 'Train/mean hd95_metric': 0.50461745262146} +Epoch [3992/4000] Validation [1/4] Loss: 0.44257 focal_loss 0.37442 dice_loss 0.06816 +Epoch [3992/4000] Validation [2/4] Loss: 0.49024 focal_loss 0.37848 dice_loss 0.11176 +Epoch [3992/4000] Validation [3/4] Loss: 0.56015 focal_loss 0.46926 dice_loss 0.09089 +Epoch [3992/4000] Validation [4/4] Loss: 0.34042 focal_loss 0.24966 dice_loss 0.09076 +Epoch [3992/4000] Validation metric {'Val/mean dice_metric': 0.9736530184745789, 'Val/mean miou_metric': 0.9594805836677551, 'Val/mean f1': 0.9753485321998596, 'Val/mean precision': 0.9732537269592285, 'Val/mean recall': 0.9774523377418518, 'Val/mean hd95_metric': 5.484692573547363} +Cheakpoint... +Epoch [3992/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9737], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9736530184745789, 'Val/mean miou_metric': 0.9594805836677551, 'Val/mean f1': 0.9753485321998596, 'Val/mean precision': 0.9732537269592285, 'Val/mean recall': 0.9774523377418518, 'Val/mean hd95_metric': 5.484692573547363} +Epoch [3993/4000] Training [1/16] Loss: 0.00239 +Epoch [3993/4000] Training [2/16] Loss: 0.00246 +Epoch [3993/4000] Training [3/16] Loss: 0.00205 +Epoch [3993/4000] Training [4/16] Loss: 0.00252 +Epoch [3993/4000] Training [5/16] Loss: 0.00192 +Epoch [3993/4000] Training [6/16] Loss: 0.00305 +Epoch [3993/4000] Training [7/16] Loss: 0.00236 +Epoch [3993/4000] Training [8/16] Loss: 0.00199 +Epoch [3993/4000] Training [9/16] Loss: 0.00246 +Epoch [3993/4000] Training [10/16] Loss: 0.00248 +Epoch [3993/4000] Training [11/16] Loss: 0.00176 +Epoch [3993/4000] Training [12/16] Loss: 0.00238 +Epoch [3993/4000] Training [13/16] Loss: 0.00370 +Epoch [3993/4000] Training [14/16] Loss: 0.00271 +Epoch [3993/4000] Training [15/16] Loss: 0.00272 +Epoch [3993/4000] Training [16/16] Loss: 0.00161 +Epoch [3993/4000] Training metric {'Train/mean dice_metric': 0.9989097118377686, 'Train/mean miou_metric': 0.9975454807281494, 'Train/mean f1': 0.9938703179359436, 'Train/mean precision': 0.9893590211868286, 'Train/mean recall': 0.9984228610992432, 'Train/mean hd95_metric': 0.4867936372756958} +Epoch [3993/4000] Validation [1/4] Loss: 0.39946 focal_loss 0.33757 dice_loss 0.06189 +Epoch [3993/4000] Validation [2/4] Loss: 0.51187 focal_loss 0.38381 dice_loss 0.12806 +Epoch [3993/4000] Validation [3/4] Loss: 0.51895 focal_loss 0.42557 dice_loss 0.09338 +Epoch [3993/4000] Validation [4/4] Loss: 0.36221 focal_loss 0.27521 dice_loss 0.08700 +Epoch [3993/4000] Validation metric {'Val/mean dice_metric': 0.9759458303451538, 'Val/mean miou_metric': 0.9618595242500305, 'Val/mean f1': 0.9766867160797119, 'Val/mean precision': 0.9744987487792969, 'Val/mean recall': 0.9788846969604492, 'Val/mean hd95_metric': 4.559756278991699} +Cheakpoint... +Epoch [3993/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9759], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9759458303451538, 'Val/mean miou_metric': 0.9618595242500305, 'Val/mean f1': 0.9766867160797119, 'Val/mean precision': 0.9744987487792969, 'Val/mean recall': 0.9788846969604492, 'Val/mean hd95_metric': 4.559756278991699} +Epoch [3994/4000] Training [1/16] Loss: 0.00219 +Epoch [3994/4000] Training [2/16] Loss: 0.00136 +Epoch [3994/4000] Training [3/16] Loss: 0.00186 +Epoch [3994/4000] Training [4/16] Loss: 0.00143 +Epoch [3994/4000] Training [5/16] Loss: 0.00192 +Epoch [3994/4000] Training [6/16] Loss: 0.00229 +Epoch [3994/4000] Training [7/16] Loss: 0.00168 +Epoch [3994/4000] Training [8/16] Loss: 0.00414 +Epoch [3994/4000] Training [9/16] Loss: 0.00222 +Epoch [3994/4000] Training [10/16] Loss: 0.00218 +Epoch [3994/4000] Training [11/16] Loss: 0.00202 +Epoch [3994/4000] Training [12/16] Loss: 0.00378 +Epoch [3994/4000] Training [13/16] Loss: 0.00258 +Epoch [3994/4000] Training [14/16] Loss: 0.00192 +Epoch [3994/4000] Training [15/16] Loss: 0.00242 +Epoch [3994/4000] Training [16/16] Loss: 0.00369 +Epoch [3994/4000] Training metric {'Train/mean dice_metric': 0.9988694190979004, 'Train/mean miou_metric': 0.997462809085846, 'Train/mean f1': 0.9938358664512634, 'Train/mean precision': 0.9892550706863403, 'Train/mean recall': 0.9984593987464905, 'Train/mean hd95_metric': 0.48911789059638977} +Epoch [3994/4000] Validation [1/4] Loss: 0.42913 focal_loss 0.36584 dice_loss 0.06330 +Epoch [3994/4000] Validation [2/4] Loss: 0.47186 focal_loss 0.36119 dice_loss 0.11067 +Epoch [3994/4000] Validation [3/4] Loss: 0.56780 focal_loss 0.47285 dice_loss 0.09495 +Epoch [3994/4000] Validation [4/4] Loss: 0.33537 focal_loss 0.25260 dice_loss 0.08277 +Epoch [3994/4000] Validation metric {'Val/mean dice_metric': 0.9734939336776733, 'Val/mean miou_metric': 0.9596925973892212, 'Val/mean f1': 0.9760270118713379, 'Val/mean precision': 0.9746692180633545, 'Val/mean recall': 0.9773886203765869, 'Val/mean hd95_metric': 4.93385648727417} +Cheakpoint... +Epoch [3994/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9735], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9734939336776733, 'Val/mean miou_metric': 0.9596925973892212, 'Val/mean f1': 0.9760270118713379, 'Val/mean precision': 0.9746692180633545, 'Val/mean recall': 0.9773886203765869, 'Val/mean hd95_metric': 4.93385648727417} +Epoch [3995/4000] Training [1/16] Loss: 0.00251 +Epoch [3995/4000] Training [2/16] Loss: 0.00320 +Epoch [3995/4000] Training [3/16] Loss: 0.00246 +Epoch [3995/4000] Training [4/16] Loss: 0.00434 +Epoch [3995/4000] Training [5/16] Loss: 0.00319 +Epoch [3995/4000] Training [6/16] Loss: 0.00173 +Epoch [3995/4000] Training [7/16] Loss: 0.00265 +Epoch [3995/4000] Training [8/16] Loss: 0.00251 +Epoch [3995/4000] Training [9/16] Loss: 0.00245 +Epoch [3995/4000] Training [10/16] Loss: 0.00166 +Epoch [3995/4000] Training [11/16] Loss: 0.00265 +Epoch [3995/4000] Training [12/16] Loss: 0.00187 +Epoch [3995/4000] Training [13/16] Loss: 0.00200 +Epoch [3995/4000] Training [14/16] Loss: 0.00189 +Epoch [3995/4000] Training [15/16] Loss: 0.00156 +Epoch [3995/4000] Training [16/16] Loss: 0.00283 +Epoch [3995/4000] Training metric {'Train/mean dice_metric': 0.9988076686859131, 'Train/mean miou_metric': 0.9973411560058594, 'Train/mean f1': 0.9938391447067261, 'Train/mean precision': 0.9893142580986023, 'Train/mean recall': 0.9984056353569031, 'Train/mean hd95_metric': 0.48013341426849365} +Epoch [3995/4000] Validation [1/4] Loss: 0.38349 focal_loss 0.32316 dice_loss 0.06033 +Epoch [3995/4000] Validation [2/4] Loss: 0.46321 focal_loss 0.35505 dice_loss 0.10816 +Epoch [3995/4000] Validation [3/4] Loss: 0.57161 focal_loss 0.47707 dice_loss 0.09454 +Epoch [3995/4000] Validation [4/4] Loss: 0.47486 focal_loss 0.36098 dice_loss 0.11388 +Epoch [3995/4000] Validation metric {'Val/mean dice_metric': 0.973397433757782, 'Val/mean miou_metric': 0.9592896699905396, 'Val/mean f1': 0.9754558205604553, 'Val/mean precision': 0.9725479483604431, 'Val/mean recall': 0.9783811569213867, 'Val/mean hd95_metric': 5.736413478851318} +Cheakpoint... +Epoch [3995/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.973397433757782, 'Val/mean miou_metric': 0.9592896699905396, 'Val/mean f1': 0.9754558205604553, 'Val/mean precision': 0.9725479483604431, 'Val/mean recall': 0.9783811569213867, 'Val/mean hd95_metric': 5.736413478851318} +Epoch [3996/4000] Training [1/16] Loss: 0.00202 +Epoch [3996/4000] Training [2/16] Loss: 0.00320 +Epoch [3996/4000] Training [3/16] Loss: 0.00338 +Epoch [3996/4000] Training [4/16] Loss: 0.00359 +Epoch [3996/4000] Training [5/16] Loss: 0.00162 +Epoch [3996/4000] Training [6/16] Loss: 0.00225 +Epoch [3996/4000] Training [7/16] Loss: 0.00218 +Epoch [3996/4000] Training [8/16] Loss: 0.00166 +Epoch [3996/4000] Training [9/16] Loss: 0.00231 +Epoch [3996/4000] Training [10/16] Loss: 0.00344 +Epoch [3996/4000] Training [11/16] Loss: 0.00196 +Epoch [3996/4000] Training [12/16] Loss: 0.00223 +Epoch [3996/4000] Training [13/16] Loss: 0.00169 +Epoch [3996/4000] Training [14/16] Loss: 0.00250 +Epoch [3996/4000] Training [15/16] Loss: 0.00152 +Epoch [3996/4000] Training [16/16] Loss: 0.00210 +Epoch [3996/4000] Training metric {'Train/mean dice_metric': 0.9988751411437988, 'Train/mean miou_metric': 0.99747633934021, 'Train/mean f1': 0.9938725233078003, 'Train/mean precision': 0.9893494844436646, 'Train/mean recall': 0.9984371662139893, 'Train/mean hd95_metric': 0.470242440700531} +Epoch [3996/4000] Validation [1/4] Loss: 0.35432 focal_loss 0.29482 dice_loss 0.05951 +Epoch [3996/4000] Validation [2/4] Loss: 0.46685 focal_loss 0.35903 dice_loss 0.10782 +Epoch [3996/4000] Validation [3/4] Loss: 0.56096 focal_loss 0.46741 dice_loss 0.09355 +Epoch [3996/4000] Validation [4/4] Loss: 0.29367 focal_loss 0.21251 dice_loss 0.08116 +Epoch [3996/4000] Validation metric {'Val/mean dice_metric': 0.9745379686355591, 'Val/mean miou_metric': 0.960898220539093, 'Val/mean f1': 0.9765030145645142, 'Val/mean precision': 0.9745680093765259, 'Val/mean recall': 0.9784456491470337, 'Val/mean hd95_metric': 5.003001689910889} +Cheakpoint... +Epoch [3996/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9745], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9745379686355591, 'Val/mean miou_metric': 0.960898220539093, 'Val/mean f1': 0.9765030145645142, 'Val/mean precision': 0.9745680093765259, 'Val/mean recall': 0.9784456491470337, 'Val/mean hd95_metric': 5.003001689910889} +Epoch [3997/4000] Training [1/16] Loss: 0.00188 +Epoch [3997/4000] Training [2/16] Loss: 0.00177 +Epoch [3997/4000] Training [3/16] Loss: 0.00190 +Epoch [3997/4000] Training [4/16] Loss: 0.00188 +Epoch [3997/4000] Training [5/16] Loss: 0.00387 +Epoch [3997/4000] Training [6/16] Loss: 0.00212 +Epoch [3997/4000] Training [7/16] Loss: 0.00195 +Epoch [3997/4000] Training [8/16] Loss: 0.00220 +Epoch [3997/4000] Training [9/16] Loss: 0.00194 +Epoch [3997/4000] Training [10/16] Loss: 0.00269 +Epoch [3997/4000] Training [11/16] Loss: 0.00223 +Epoch [3997/4000] Training [12/16] Loss: 0.00186 +Epoch [3997/4000] Training [13/16] Loss: 0.00235 +Epoch [3997/4000] Training [14/16] Loss: 0.00262 +Epoch [3997/4000] Training [15/16] Loss: 0.00311 +Epoch [3997/4000] Training [16/16] Loss: 0.00181 +Epoch [3997/4000] Training metric {'Train/mean dice_metric': 0.9989105463027954, 'Train/mean miou_metric': 0.997546374797821, 'Train/mean f1': 0.9939801096916199, 'Train/mean precision': 0.9894982576370239, 'Train/mean recall': 0.9985026717185974, 'Train/mean hd95_metric': 0.5158952474594116} +Epoch [3997/4000] Validation [1/4] Loss: 0.44912 focal_loss 0.38467 dice_loss 0.06445 +Epoch [3997/4000] Validation [2/4] Loss: 0.49200 focal_loss 0.37770 dice_loss 0.11430 +Epoch [3997/4000] Validation [3/4] Loss: 0.30178 focal_loss 0.23796 dice_loss 0.06382 +Epoch [3997/4000] Validation [4/4] Loss: 0.29448 focal_loss 0.21098 dice_loss 0.08349 +Epoch [3997/4000] Validation metric {'Val/mean dice_metric': 0.9733675718307495, 'Val/mean miou_metric': 0.9599893689155579, 'Val/mean f1': 0.9767401814460754, 'Val/mean precision': 0.97478187084198, 'Val/mean recall': 0.9787063002586365, 'Val/mean hd95_metric': 5.057031154632568} +Cheakpoint... +Epoch [3997/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9734], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9733675718307495, 'Val/mean miou_metric': 0.9599893689155579, 'Val/mean f1': 0.9767401814460754, 'Val/mean precision': 0.97478187084198, 'Val/mean recall': 0.9787063002586365, 'Val/mean hd95_metric': 5.057031154632568} +Epoch [3998/4000] Training [1/16] Loss: 0.00254 +Epoch [3998/4000] Training [2/16] Loss: 0.00187 +Epoch [3998/4000] Training [3/16] Loss: 0.00228 +Epoch [3998/4000] Training [4/16] Loss: 0.00187 +Epoch [3998/4000] Training [5/16] Loss: 0.00215 +Epoch [3998/4000] Training [6/16] Loss: 0.00365 +Epoch [3998/4000] Training [7/16] Loss: 0.00212 +Epoch [3998/4000] Training [8/16] Loss: 0.00174 +Epoch [3998/4000] Training [9/16] Loss: 0.00199 +Epoch [3998/4000] Training [10/16] Loss: 0.00181 +Epoch [3998/4000] Training [11/16] Loss: 0.00166 +Epoch [3998/4000] Training [12/16] Loss: 0.00176 +Epoch [3998/4000] Training [13/16] Loss: 0.00282 +Epoch [3998/4000] Training [14/16] Loss: 0.00137 +Epoch [3998/4000] Training [15/16] Loss: 0.00216 +Epoch [3998/4000] Training [16/16] Loss: 0.00227 +Epoch [3998/4000] Training metric {'Train/mean dice_metric': 0.9989946484565735, 'Train/mean miou_metric': 0.9977127909660339, 'Train/mean f1': 0.9940029978752136, 'Train/mean precision': 0.9895326495170593, 'Train/mean recall': 0.99851393699646, 'Train/mean hd95_metric': 0.462429940700531} +Epoch [3998/4000] Validation [1/4] Loss: 0.47430 focal_loss 0.41024 dice_loss 0.06406 +Epoch [3998/4000] Validation [2/4] Loss: 0.99357 focal_loss 0.78064 dice_loss 0.21293 +Epoch [3998/4000] Validation [3/4] Loss: 0.29361 focal_loss 0.22657 dice_loss 0.06703 +Epoch [3998/4000] Validation [4/4] Loss: 0.38696 focal_loss 0.29433 dice_loss 0.09264 +Epoch [3998/4000] Validation metric {'Val/mean dice_metric': 0.9730767011642456, 'Val/mean miou_metric': 0.959880530834198, 'Val/mean f1': 0.9766265153884888, 'Val/mean precision': 0.9739738702774048, 'Val/mean recall': 0.9792937636375427, 'Val/mean hd95_metric': 4.952328681945801} +Cheakpoint... +Epoch [3998/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9731], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9730767011642456, 'Val/mean miou_metric': 0.959880530834198, 'Val/mean f1': 0.9766265153884888, 'Val/mean precision': 0.9739738702774048, 'Val/mean recall': 0.9792937636375427, 'Val/mean hd95_metric': 4.952328681945801} +Epoch [3999/4000] Training [1/16] Loss: 0.00212 +Epoch [3999/4000] Training [2/16] Loss: 0.00341 +Epoch [3999/4000] Training [3/16] Loss: 0.00252 +Epoch [3999/4000] Training [4/16] Loss: 0.00232 +Epoch [3999/4000] Training [5/16] Loss: 0.00231 +Epoch [3999/4000] Training [6/16] Loss: 0.00294 +Epoch [3999/4000] Training [7/16] Loss: 0.00243 +Epoch [3999/4000] Training [8/16] Loss: 0.00188 +Epoch [3999/4000] Training [9/16] Loss: 0.00162 +Epoch [3999/4000] Training [10/16] Loss: 0.00258 +Epoch [3999/4000] Training [11/16] Loss: 0.00259 +Epoch [3999/4000] Training [12/16] Loss: 0.00227 +Epoch [3999/4000] Training [13/16] Loss: 0.00260 +Epoch [3999/4000] Training [14/16] Loss: 0.00205 +Epoch [3999/4000] Training [15/16] Loss: 0.00386 +Epoch [3999/4000] Training [16/16] Loss: 0.00322 +Epoch [3999/4000] Training metric {'Train/mean dice_metric': 0.9987731575965881, 'Train/mean miou_metric': 0.9972385168075562, 'Train/mean f1': 0.9929482340812683, 'Train/mean precision': 0.9876734614372253, 'Train/mean recall': 0.9982796311378479, 'Train/mean hd95_metric': 0.5540311336517334} +Epoch [3999/4000] Validation [1/4] Loss: 0.42806 focal_loss 0.36511 dice_loss 0.06295 +Epoch [3999/4000] Validation [2/4] Loss: 0.48888 focal_loss 0.37542 dice_loss 0.11345 +Epoch [3999/4000] Validation [3/4] Loss: 0.55334 focal_loss 0.46099 dice_loss 0.09235 +Epoch [3999/4000] Validation [4/4] Loss: 0.51858 focal_loss 0.40755 dice_loss 0.11103 +Epoch [3999/4000] Validation metric {'Val/mean dice_metric': 0.9747454524040222, 'Val/mean miou_metric': 0.9606026411056519, 'Val/mean f1': 0.9758115410804749, 'Val/mean precision': 0.9729365110397339, 'Val/mean recall': 0.9787034392356873, 'Val/mean hd95_metric': 4.768134593963623} +Cheakpoint... +Epoch [3999/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9747], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9747454524040222, 'Val/mean miou_metric': 0.9606026411056519, 'Val/mean f1': 0.9758115410804749, 'Val/mean precision': 0.9729365110397339, 'Val/mean recall': 0.9787034392356873, 'Val/mean hd95_metric': 4.768134593963623} +Epoch [4000/4000] Training [1/16] Loss: 0.00229 +Epoch [4000/4000] Training [2/16] Loss: 0.00408 +Epoch [4000/4000] Training [3/16] Loss: 0.00227 +Epoch [4000/4000] Training [4/16] Loss: 0.00285 +Epoch [4000/4000] Training [5/16] Loss: 0.00332 +Epoch [4000/4000] Training [6/16] Loss: 0.00207 +Epoch [4000/4000] Training [7/16] Loss: 0.00148 +Epoch [4000/4000] Training [8/16] Loss: 0.00204 +Epoch [4000/4000] Training [9/16] Loss: 0.00230 +Epoch [4000/4000] Training [10/16] Loss: 0.00278 +Epoch [4000/4000] Training [11/16] Loss: 0.00376 +Epoch [4000/4000] Training [12/16] Loss: 0.00211 +Epoch [4000/4000] Training [13/16] Loss: 0.00301 +Epoch [4000/4000] Training [14/16] Loss: 0.00261 +Epoch [4000/4000] Training [15/16] Loss: 0.00234 +Epoch [4000/4000] Training [16/16] Loss: 0.00276 +Epoch [4000/4000] Training metric {'Train/mean dice_metric': 0.9987167119979858, 'Train/mean miou_metric': 0.9971345663070679, 'Train/mean f1': 0.9934052228927612, 'Train/mean precision': 0.988559365272522, 'Train/mean recall': 0.9982988238334656, 'Train/mean hd95_metric': 0.5517854690551758} +Epoch [4000/4000] Validation [1/4] Loss: 0.50433 focal_loss 0.42719 dice_loss 0.07714 +Epoch [4000/4000] Validation [2/4] Loss: 0.63195 focal_loss 0.46118 dice_loss 0.17077 +Epoch [4000/4000] Validation [3/4] Loss: 0.61258 focal_loss 0.51053 dice_loss 0.10206 +Epoch [4000/4000] Validation [4/4] Loss: 0.38931 focal_loss 0.29395 dice_loss 0.09536 +Epoch [4000/4000] Validation metric {'Val/mean dice_metric': 0.9740150570869446, 'Val/mean miou_metric': 0.9590480923652649, 'Val/mean f1': 0.9754215478897095, 'Val/mean precision': 0.9727479815483093, 'Val/mean recall': 0.9781098961830139, 'Val/mean hd95_metric': 5.328530788421631} +Cheakpoint... +Epoch [4000/4000] best acc:tensor([0.9777], device='cuda:0'), Now : mean acc: tensor([0.9740], device='cuda:0'), mean class: {'Val/mean dice_metric': 0.9740150570869446, 'Val/mean miou_metric': 0.9590480923652649, 'Val/mean f1': 0.9754215478897095, 'Val/mean precision': 0.9727479815483093, 'Val/mean recall': 0.9781098961830139, 'Val/mean hd95_metric': 5.328530788421631} +best acc: tensor([0.9777], device='cuda:0') +best class : {'Val/mean dice_metric': 0.9776544570922852, 'Val/mean miou_metric': 0.9635767936706543, 'Val/mean f1': 0.977523922920227, 'Val/mean precision': 0.9747691750526428, 'Val/mean recall': 0.9802942872047424, 'Val/mean hd95_metric': 4.495543003082275} +best epochs: 3375